diff --git a/.gitattributes b/.gitattributes index 0776429ba75525c3acab27edd2c2a63f8bcdc494..4a9e052dec3f6cf4bf547aafe35fc8a03b2dc4a1 100644 --- a/.gitattributes +++ b/.gitattributes @@ -34,3 +34,15 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text *.zst filter=lfs diff=lfs merge=lfs -text *tfevents* filter=lfs diff=lfs merge=lfs -text RIS-DMMI/refer/evaluation/tokenizer/stanford-corenlp-3.4.1.jar filter=lfs diff=lfs merge=lfs -text +LAVT-RIS/logs/old/gref_m10_mg12_tmp007_2gpu_bs16_ang.log filter=lfs diff=lfs merge=lfs -text +LAVT-RIS/refer/data/ref-zom/instances.json filter=lfs diff=lfs merge=lfs -text +LAVT-RIS/refer/data/ref-zom/refs(final).p filter=lfs diff=lfs merge=lfs -text +LAVT-RIS/refer/data/refcoco/instances.json filter=lfs diff=lfs merge=lfs -text +LAVT-RIS/refer/data/refcoco/refs(google).p filter=lfs diff=lfs merge=lfs -text +LAVT-RIS/refer/data/refcoco/refs(unc).p filter=lfs diff=lfs merge=lfs -text +LAVT-RIS/refer/data/refcoco+/instances.json filter=lfs diff=lfs merge=lfs -text +LAVT-RIS/refer/data/refcoco+/refs(unc).p filter=lfs diff=lfs merge=lfs -text +LAVT-RIS/refer/data/refcocog/instances.json filter=lfs diff=lfs merge=lfs -text +LAVT-RIS/refer/data/refcocog/refs(google).p filter=lfs diff=lfs merge=lfs -text +LAVT-RIS/refer/data/refcocog/refs(umd).p filter=lfs diff=lfs merge=lfs -text +LAVT-RIS/refer/evaluation/tokenizer/stanford-corenlp-3.4.1.jar filter=lfs diff=lfs merge=lfs -text diff --git a/LAVT-RIS/__pycache__/args.cpython-39.pyc b/LAVT-RIS/__pycache__/args.cpython-39.pyc new file mode 100644 index 0000000000000000000000000000000000000000..14354338b136a1d97455c0177ff0892cca349f02 Binary files /dev/null and b/LAVT-RIS/__pycache__/args.cpython-39.pyc differ diff --git a/LAVT-RIS/__pycache__/train_refzom.cpython-39.pyc b/LAVT-RIS/__pycache__/train_refzom.cpython-39.pyc new file mode 100644 index 0000000000000000000000000000000000000000..aca42a577b59c62d4351bcfce6dbbc94e6397688 Binary files /dev/null and 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"stdout", + "output_type": "stream", + "text": [ + "Collecting easydict\n", + " Downloading easydict-1.13-py3-none-any.whl.metadata (4.2 kB)\n", + "Downloading easydict-1.13-py3-none-any.whl (6.8 kB)\n", + "Installing collected packages: easydict\n", + "Successfully installed easydict-1.13\n" + ] + } + ], + "source": [ + "!pip install easydict" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": {}, + "outputs": [ + { + "ename": "ModuleNotFoundError", + "evalue": "No module named 'utils.dataset'; 'utils' is not a package", + "output_type": "error", + "traceback": [ + "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", + "\u001b[0;31mModuleNotFoundError\u001b[0m Traceback (most recent call last)", + "Cell \u001b[0;32mIn[3], line 23\u001b[0m\n\u001b[1;32m 20\u001b[0m \u001b[39mfrom\u001b[39;00m \u001b[39measydict\u001b[39;00m \u001b[39mimport\u001b[39;00m EasyDict\n\u001b[1;32m 21\u001b[0m \u001b[39mfrom\u001b[39;00m \u001b[39mfunctools\u001b[39;00m \u001b[39mimport\u001b[39;00m partial\n\u001b[0;32m---> 23\u001b[0m \u001b[39mfrom\u001b[39;00m \u001b[39mengine\u001b[39;00m\u001b[39m.\u001b[39;00m\u001b[39mengine\u001b[39;00m \u001b[39mimport\u001b[39;00m train, validate \n\u001b[1;32m 24\u001b[0m \u001b[39mfrom\u001b[39;00m \u001b[39mutils\u001b[39;00m\u001b[39m.\u001b[39;00m\u001b[39mdataset\u001b[39;00m \u001b[39mimport\u001b[39;00m RefDataset \u001b[39mas\u001b[39;00m origDataset\n\u001b[1;32m 25\u001b[0m \u001b[39mfrom\u001b[39;00m \u001b[39mutils\u001b[39;00m\u001b[39m.\u001b[39;00m\u001b[39msimple_tokenizer\u001b[39;00m \u001b[39mimport\u001b[39;00m SimpleTokenizer \u001b[39mas\u001b[39;00m _Tokenizer\n", + "File \u001b[0;32m/data2/projects/chaeyun/VerbCentric_RIS/engine/engine.py:14\u001b[0m\n\u001b[1;32m 12\u001b[0m \u001b[39mimport\u001b[39;00m \u001b[39mwandb\u001b[39;00m\n\u001b[1;32m 13\u001b[0m \u001b[39mfrom\u001b[39;00m \u001b[39mloguru\u001b[39;00m \u001b[39mimport\u001b[39;00m logger\n\u001b[0;32m---> 14\u001b[0m \u001b[39mfrom\u001b[39;00m \u001b[39mutils\u001b[39;00m\u001b[39m.\u001b[39;00m\u001b[39mdataset\u001b[39;00m \u001b[39mimport\u001b[39;00m tokenize\n\u001b[1;32m 15\u001b[0m \u001b[39mfrom\u001b[39;00m \u001b[39mutils\u001b[39;00m\u001b[39m.\u001b[39;00m\u001b[39mmisc\u001b[39;00m \u001b[39mimport\u001b[39;00m (AverageMeter, ProgressMeter, concat_all_gather,\n\u001b[1;32m 16\u001b[0m trainMetricGPU)\n\u001b[1;32m 19\u001b[0m \u001b[39mdef\u001b[39;00m \u001b[39mreturn_mask\u001b[39m(emb_distance):\n", + "\u001b[0;31mModuleNotFoundError\u001b[0m: No module named 'utils.dataset'; 'utils' is not a package" + ] + } + ], + "source": [ + "\n", + "import os\n", + "import sys\n", + "import cv2\n", + "import json\n", + "import time\n", + "import math\n", + "from tqdm import tqdm\n", + "\n", + "import torch\n", + "import torch.utils.data as data\n", + "import torch.nn.functional as F\n", + "import matplotlib.pyplot as plt\n", + "import numpy as np\n", + "import argparse\n", + "\n", + "HOME_ = '/data2/projects/chaeyun/VerbCentric_RIS'\n", + "sys.path.append(HOME_)\n", + "\n", + "\n", + "from easydict import EasyDict\n", + "from functools import partial\n", + "\n", + "from engine.engine import train, validate \n", + "from utils.dataset import RefDataset as origDataset\n", + "from utils.simple_tokenizer import SimpleTokenizer as _Tokenizer\n", + "\n", + "train_set_pth = '/data2/projects/chaeyun/VerbCentric_RIS/datasets/anns/refcocog_u/train.json'\n", + "val_set_pth = '/data2/projects/chaeyun/VerbCentric_RIS/datasets/anns/refcocog_u/val.json'\n", + "test_set_pth = '/data2/projects/chaeyun/VerbCentric_RIS/datasets/anns/refcocog_u/test.json'\n", + "mask_root = '/data2/projects/chaeyun/VerbCentric_RIS/datasets/masks/refcocog_u'\n", + "\n", + "# ORIGINAL MODEL CONFIG AND WEIGHTS\n", + "orig_config_path = '/data2/projects/chaeyun/VerbCentric_RIS/config/cris_r50.yaml'\n", + "orig_model_path = '/data2/projects/chaeyun/VerbCentric_RIS/exp/CRIS_R50/best_model_miou.pth'\n", + "\n", + "# NEW MODEL CONFIG AND WEIGHTS\n", + "new_config_path = '/data2/projects/chaeyun/VerbCentric_RIS/config/cris_verbonly_b64_nopos.yaml'\n", + "exo_name = 'ACE_hp10_m08_tmp005_b64_v1'\n", + "exo_name2 = 'ACE_hp10_m10_tmp005_b64_v1'\n", + "exo_name3 = 'ACE_hp10_m15_tmp005_b64_v1'\n", + "\n", + "# /data2/projects/chaeyun/VerbCentric_RIS/exp/ACE_hp10_m08_tmp005_b64_v1/\n", + "new_model_path = f'/data2/projects/chaeyun/VerbCentric_RIS/exp/{exo_name}/best_model_miou.pth'\n", + "new_model_path2=f'/data2/projects/chaeyun/VerbCentric_RIS/exp/{exo_name2}/best_model_miou.pth'\n", + "new_model_path3=f'/data2/projects/chaeyun/VerbCentric_RIS/exp/{exo_name3}/best_model_miou.pth'\n", + "\n", + "# IMAGE MIN AND STD \n", + "img_mean = np.array([0.48145466, 0.4578275,0.40821073]).reshape(1, 1, 3)\n", + "img_std = np.array([0.26862954, 0.26130258,0.27577711]).reshape(1, 1, 3)\n", + "\n", + "\n", + "os.environ['CUDA_VISIBLE_DEVICES'] = '3'" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "'/data2/projects/chaeyun/LAVT-RIS'" + ] + }, + "execution_count": 4, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "pwd" + ] + }, + { + "cell_type": "code", + "execution_count": 128, + "metadata": {}, + "outputs": [], + "source": [ + "import utils.config as config\n", + "from utils.dataset_verbonly import RefDataset\n", + "from utils.misc import (init_random_seed, set_random_seed, setup_logger,\n", + " worker_init_fn)\n", + "\n", + "from model_ import build_segmenter_original, build_segmenter_pos_rev2\n", + "from model_.clip import build_model\n", + "\n", + "from .segmenter import CRIS\n", + "from .segmenter_verbonly import CRIS_PosOnly\n", + "from .segmenter_verbonly_fin import CRIS_PosOnly_rev\n", + "from .segmenter_verbonly_ver3 import CRIS_PosOnly_ver3\n" + ] + }, + { + "cell_type": "code", + "execution_count": 129, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "{'dataset': 'refcocog_u', 'train_lmdb': '/home/seunghoon/research/VerbCentric_RIS/datasets/lmdb/refcocog_u/train.lmdb', 'train_split': 'train', 'val_lmdb': '/home/seunghoon/research/VerbCentric_RIS/datasets/lmdb/refcocog_u/val.lmdb', 'val_split': 'val', 'mask_root': '/home/seunghoon/research/VerbCentric_RIS/datasets/masks/refcocog_u', 'clip_pretrain': '/home/seunghoon/research/VerbCentric_RIS/pretrain/RN50.pt', 'input_size': 416, 'word_len': 22, 'word_dim': 1024, 'vis_dim': 512, 'fpn_in': [512, 1024, 1024], 'fpn_out': [256, 512, 1024], 'sync_bn': True, 'freeze': True, 'train_text_encoder': False, 'train_visual_encoder': False, 'num_layers': 3, 'num_head': 8, 'dim_ffn': 2048, 'dropout': 0.1, 'intermediate': False, 'workers': 4, 'workers_val': 4, 'epochs': 50, 'milestones': [35], 'start_epoch': 0, 'batch_size': 64, 'batch_size_val': 64, 'base_lr': 0.0001, 'lr_decay': 0.1, 'lr_multi': 0.1, 'weight_decay': 0.0, 'max_norm': 0.0, 'manual_seed': 0, 'print_freq': 100, 'metric_learning': True, 'metric_mode': 'original', 'exclude_multiobj': True, 'exclude_pos': True, 'loss_option': 'ACL_verbonly', 'metric_loss_weight': 0.1, 'hn_prob': 0.0, 'hn_celoss': True, 'margin_value': 20, 'temperature': 0.05, 'exp_name': 'CRIS_AML_verbonly_pos25_b32', 'output_folder': 'exp/refcocog_u/exclude_multiobj', 'save_freq': 1, 'weight': None, 'resume': 'latest', 'evaluate': True, 'dist_url': 'tcp://localhost:7024', 'dist_backend': 'nccl', 'multiprocessing_distributed': True, 'world_size': 1, 'rank': 0, 'test_split': 'val-test', 'test_lmdb': '/data2/projects/seunghoon/VerbRIS/VerbCentric_CY/datasets/lmdb/refcocog_u/val.lmdb', 'visualize': False}\n", + "CLIP FROZEN !!\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "\u001b[32m2024-12-10 01:09:00.796\u001b[0m | \u001b[1mINFO \u001b[0m | \u001b[36mmodel_\u001b[0m:\u001b[36mbuild_segmenter_pos_rev2\u001b[0m:\u001b[36m19\u001b[0m - \u001b[1mBackbone with decay=325, Head=124\u001b[0m\n" + ] + } + ], + "source": [ + "parser = argparse.ArgumentParser(\n", + " description='Pytorch Referring Expression Segmentation')\n", + "parser.add_argument('--config',\n", + " default=orig_config_path,\n", + " type=str,\n", + " help='config file')\n", + "parser.add_argument('--opts',\n", + " default=None,\n", + " nargs=argparse.REMAINDER,\n", + " help='override some settings in the config.')\n", + "\n", + "args = parser.parse_args([])\n", + "\n", + "cfg = config.load_cfg_from_cfg_file(orig_config_path)\n", + "cfg.metric_learning = True\n", + "args = EasyDict(cfg)\n", + "print(args)\n", + "original_model, original_param_list = build_segmenter_pos_rev2(args)\n", + "\n" + ] + }, + { + "cell_type": "code", + "execution_count": 130, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "{'dataset': 'refcocog_u', 'train_lmdb': '/home/seunghoon/research/VerbCentric_RIS/datasets/lmdb/refcocog_u/train.lmdb', 'train_split': 'train', 'val_lmdb': '/home/seunghoon/research/VerbCentric_RIS/datasets/lmdb/refcocog_u/val.lmdb', 'val_split': 'val', 'mask_root': '/home/seunghoon/research/VerbCentric_RIS/datasets/masks/refcocog_u', 'clip_pretrain': '/home/seunghoon/research/VerbCentric_RIS/pretrain/RN50.pt', 'input_size': 416, 'word_len': 22, 'word_dim': 1024, 'vis_dim': 512, 'fpn_in': [512, 1024, 1024], 'fpn_out': [256, 512, 1024], 'sync_bn': True, 'freeze': True, 'train_text_encoder': False, 'train_visual_encoder': False, 'num_layers': 3, 'num_head': 8, 'dim_ffn': 2048, 'dropout': 0.1, 'intermediate': False, 'workers': 0, 'workers_val': 0, 'epochs': 50, 'milestones': [35], 'start_epoch': 0, 'batch_size': 64, 'batch_size_val': 64, 'base_lr': 0.0001, 'textft_lr': 1e-05, 'visft_lr': 0.0, 'lr_decay': 0.1, 'lr_multi': 0.1, 'weight_decay': 0.0, 'max_norm': 0.0, 'manual_seed': 0, 'print_freq': 100, 'metric_learning': True, 'metric_mode': 'hardpos_only_ver3', 'exclude_multiobj': True, 'exclude_pos': True, 'loss_option': 'ranking_embed', 'metric_loss_weight': 0.1, 'hn_prob': 0.0, 'hn_celoss': False, 'margin_value': 10, 'temperature': 0.05, 'exp_name': 'CRIS_AML_verbonly_pos25_b32', 'output_folder': 'exp/refcocog_u/exclude_multiobj', 'save_freq': 1, 'weight': None, 'resume': 'latest', 'evaluate': True, 'dist_url': 'tcp://localhost:7024', 'dist_backend': 'nccl', 'multiprocessing_distributed': True, 'world_size': 1, 'rank': 0, 'test_split': 'val-test', 'test_lmdb': '/home/seunghoon/research/VerbCentric_RIS/datasets/lmdb/refcocog_u/val.lmdb', 'visualize': False}\n", + "CLIP FROZEN !!\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "\u001b[32m2024-12-10 01:09:02.415\u001b[0m | \u001b[1mINFO \u001b[0m | \u001b[36mmodel_\u001b[0m:\u001b[36mbuild_segmenter_pos_rev2\u001b[0m:\u001b[36m19\u001b[0m - \u001b[1mBackbone with decay=325, Head=124\u001b[0m\n" + ] + } + ], + "source": [ + "parser = argparse.ArgumentParser(\n", + " description='Pytorch Referring Expression Segmentation')\n", + "parser.add_argument('--config',\n", + " default=new_config_path,\n", + " type=str,\n", + " help='config file')\n", + "parser.add_argument('--opts',\n", + " default=None,\n", + " nargs=argparse.REMAINDER,\n", + " help='override some settings in the config.')\n", + "\n", + "args = parser.parse_args([])\n", + "\n", + "cfg = config.load_cfg_from_cfg_file(new_config_path)\n", + "cfg.metric_learning = True\n", + "args = EasyDict(cfg)\n", + "print(args)\n", + "new_model, new_param_list = build_segmenter_pos_rev2(args)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Define dataloader and util functions" + ] + }, + { + "cell_type": "code", + "execution_count": 131, + "metadata": {}, + "outputs": [], + "source": [ + "init_fn = partial(worker_init_fn,\n", + " num_workers=args.workers,\n", + " rank=args.rank,\n", + " seed=args.manual_seed)\n", + "val_data = origDataset(lmdb_dir=args.val_lmdb,\n", + " mask_dir=args.mask_root,\n", + " dataset=args.dataset,\n", + " split=args.val_split,\n", + " mode='val',\n", + " input_size=args.input_size,\n", + " word_length=args.word_len,\n", + " args=args)\n", + "val_loader = data.DataLoader(val_data,\n", + " batch_size=32,\n", + " shuffle=False,\n", + " num_workers=args.workers_val,\n", + " pin_memory=True,\n", + " drop_last=True)\n", + "\n", + "train_data = RefDataset(lmdb_dir=args.train_lmdb,\n", + " mask_dir=args.mask_root,\n", + " dataset=args.dataset,\n", + " split=args.train_split,\n", + " mode='train',\n", + " input_size=args.input_size,\n", + " word_length=args.word_len,\n", + " args=args)\n", + "train_loader = data.DataLoader(train_data,\n", + " batch_size=32,\n", + " shuffle=False,\n", + " num_workers=args.workers,\n", + " pin_memory=True,\n", + " worker_init_fn=init_fn,\n", + " drop_last=True)\n", + "# detokenizer\n", + "tokenizer = _Tokenizer()\n" + ] + }, + { + "cell_type": "code", + "execution_count": 132, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "torch.Size([32, 3, 416, 416]) torch.Size([32, 22]) torch.Size([32, 416, 416]) torch.Size([32, 22])\n", + "tensor([[ 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,\n", + " 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,\n", + " 0, 0],\n", + " [49406, 1265, 11688, 49407, 0, 0, 0, 0, 0, 0,\n", + " 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,\n", + " 0, 0],\n", + " [49406, 1960, 320, 31777, 8172, 49407, 0, 0, 0, 0,\n", + " 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,\n", + " 0, 0],\n", + " [49406, 1312, 536, 49407, 0, 0, 0, 0, 0, 0,\n", + " 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,\n", + " 0, 0],\n", + " [49406, 7435, 320, 3101, 2972, 49407, 0, 0, 0, 0,\n", + " 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,\n", + " 0, 0],\n", + " [49406, 2862, 530, 2184, 49407, 0, 0, 0, 0, 0,\n", + " 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,\n", + " 0, 0],\n", + " [49406, 2862, 525, 49407, 0, 0, 0, 0, 0, 0,\n", + " 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,\n", + " 0, 0],\n", + " [49406, 1265, 9729, 1952, 49407, 0, 0, 0, 0, 0,\n", + " 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,\n", + " 0, 0],\n", + " [ 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,\n", + " 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,\n", + " 0, 0],\n", + " [49406, 4919, 525, 49407, 0, 0, 0, 0, 0, 0,\n", + " 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,\n", + " 0, 0],\n", + " [ 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,\n", + " 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,\n", + " 0, 0],\n", + " [ 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,\n", + " 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,\n", + " 0, 0],\n", + " [49406, 1171, 874, 49407, 0, 0, 0, 0, 0, 0,\n", + " 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,\n", + " 0, 0],\n", + " [ 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,\n", + " 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,\n", + " 0, 0],\n", + " [49406, 2862, 7619, 531, 518, 1823, 49407, 0, 0, 0,\n", + " 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,\n", + " 0, 0],\n", + " [49406, 2862, 1131, 531, 49407, 0, 0, 0, 0, 0,\n", + " 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,\n", + " 0, 0],\n", + " [ 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,\n", + " 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,\n", + " 0, 0],\n", + " [49406, 1265, 530, 518, 1112, 4657, 49407, 0, 0, 0,\n", + " 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,\n", + " 0, 0],\n", + " [49406, 1401, 1074, 320, 3470, 1063, 49407, 0, 0, 0,\n", + " 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,\n", + " 0, 0],\n", + " [ 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,\n", + " 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,\n", + " 0, 0],\n", + " [ 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,\n", + " 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,\n", + " 0, 0],\n", + " [ 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,\n", + " 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,\n", + " 0, 0],\n", + " [ 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,\n", + " 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,\n", + " 0, 0],\n", + " [ 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,\n", + " 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,\n", + " 0, 0],\n", + " [ 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,\n", + " 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,\n", + " 0, 0],\n", + " [ 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,\n", + " 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,\n", + " 0, 0],\n", + " [49406, 1629, 5084, 49407, 0, 0, 0, 0, 0, 0,\n", + " 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,\n", + " 0, 0],\n", + " [49406, 1265, 32025, 49407, 0, 0, 0, 0, 0, 0,\n", + " 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,\n", + " 0, 0],\n", + " [49406, 530, 7860, 49407, 0, 0, 0, 0, 0, 0,\n", + " 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,\n", + " 0, 0],\n", + " [ 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,\n", + " 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,\n", + " 0, 0],\n", + " [ 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,\n", + " 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,\n", + " 0, 0],\n", + " [ 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,\n", + " 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,\n", + " 0, 0]])\n" + ] + } + ], + "source": [ + "for data in train_loader:\n", + " img, word_vec, mask, hardpos = data\n", + " print(img.shape, word_vec.shape, mask.shape, hardpos.shape)\n", + " print(hardpos)\n", + " break" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Load pretrained models" + ] + }, + { + "cell_type": "code", + "execution_count": 133, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "device: cuda\n" + ] + } + ], + "source": [ + "# get current device\n", + "device = torch.device('cuda' if torch.cuda.is_available() else 'cpu')\n", + "print('device:', device)" + ] + }, + { + "cell_type": "code", + "execution_count": 134, + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/tmp/ipykernel_1173351/383024302.py:1: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.\n", + " original_checkpoint = torch.load(orig_model_path, map_location='cuda')\n", + "/tmp/ipykernel_1173351/383024302.py:11: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.\n", + " new_checkpoint = torch.load(new_model_path, map_location='cuda')\n" + ] + } + ], + "source": [ + "original_checkpoint = torch.load(orig_model_path, map_location='cuda')\n", + "args.start_epoch = original_checkpoint['epoch']\n", + "best_IoU = original_checkpoint[\"best_iou\"]\n", + "best_oIoU = original_checkpoint[\"best_oiou\"]\n", + "original_model = torch.nn.DataParallel(original_model)\n", + "original_model.load_state_dict(original_checkpoint['state_dict'])\n", + "original_model = original_model.to(device)\n", + "#original_model.eval()\n", + "\n", + "\n", + "new_checkpoint = torch.load(new_model_path, map_location='cuda')\n", + "args.start_epoch = new_checkpoint['epoch']\n", + "best_IoU = new_checkpoint[\"best_iou\"]\n", + "best_oIoU = new_checkpoint[\"best_oiou\"]\n", + "new_model = torch.nn.DataParallel(new_model)\n", + "new_model.load_state_dict(new_checkpoint['state_dict'])\n", + "new_model = new_model.to(device)\n", + "#new_model.eval()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": 135, + "metadata": {}, + "outputs": [], + "source": [ + "# similarity matrix calc\n", + "def calc_sim(embeddings):\n", + " # embeddings : (b, c, h, w)\n", + " print(\"embedding shape: \", embeddings.size())\n", + " if len(embeddings.size()) == 3:\n", + " b, c, hw = embeddings.size()\n", + " embeddings = embeddings.view(b, c, -1).mean(dim=2)\n", + " \n", + " # cosine similarity\n", + " sim = F.cosine_similarity(embeddings.unsqueeze(1), embeddings.unsqueeze(0), dim=2)\n", + " return sim\n", + "\n", + "def draw_result(imgs, preds, masks, texts):\n", + " for img, pred, mask, orig_text in zip(imgs, preds, masks, texts):\n", + " # drop zeros of text\n", + " orig_text = orig_text[orig_text != 0]\n", + " orig_text = orig_text[1:-1]\n", + " orig_text = tokenizer.decode(orig_text)\n", + " img = img.permute(1, 2, 0).cpu().numpy()\n", + " # unscale using image_mean and image_std\n", + " img = img * img_std + img_mean\n", + " # and clamp to [0, 1]\n", + " img = np.clip(img, 0, 1)\n", + "\n", + " pred = pred.cpu().numpy()\n", + " mask = mask.cpu().numpy()\n", + " plt.title(f\"text: {orig_text}\")\n", + " plt.imshow(img)\n", + " plt.imshow(pred, alpha=0.5)\n", + " #plt.imshow(mask, alpha=0.5)\n", + " plt.show()\n", + "\n", + "\n", + "def return_mask(emb_distance, positive_verbs, negative_verbs, posneg_verbs=None, verb_mask=None):\n", + "\n", + " assert torch.sum(verb_mask) == torch.sum(positive_verbs + negative_verbs), \"Verb mask does not match the sum of positive and negative verbs.\"\n", + " assert len(positive_verbs) == len(negative_verbs), \"Positive and negative verbs do not have the same length.\"\n", + "\n", + " B_, B_ = emb_distance.shape\n", + " positive_mask = torch.zeros_like(emb_distance)\n", + " negative_mask = torch.ones_like(emb_distance)\n", + " hard_negative_mask = torch.zeros_like(emb_distance)\n", + " positive_mask.fill_diagonal_(1)\n", + "\n", + " # print(\"positive verbs: \", positive_verbs)\n", + " # print(\"negative verbs: \", negative_verbs)\n", + " # print(\"emb shape: \", emb_distance.shape)\n", + "\n", + " if B_ < len(verb_mask):\n", + " # Considering only verbs that pass the verb_mask filter\n", + " positive_verbs = torch.tensor(positive_verbs)[verb_mask]\n", + " negative_verbs = torch.tensor(negative_verbs)[verb_mask]\n", + "\n", + " # Exclude hard negatives from both masks (diagonal)\n", + " for i in range(B_):\n", + " if negative_verbs[i] == 1:\n", + " positive_mask[i, i] = 0\n", + " negative_mask[i, i] = 0\n", + " # Set the entire row and column for the hard negative, except the diagonal\n", + " hard_negative_mask[i, :] = 1 # Mark the i-th row\n", + " hard_negative_mask[:, i] = 1 # Mark the i-th column\n", + " hard_negative_mask[i, i] = 0 # Ensure diagonal element (i, i) is 0\n", + "\n", + " i = 0\n", + " while i < B_:\n", + " if positive_verbs[i] == 1: \n", + " if i + 1 < B_ and positive_verbs[i + 1] == 1:\n", + " positive_mask[i, i + 1] = 1\n", + " positive_mask[i + 1, i] = 1\n", + " i += 2 \n", + " else:\n", + " i += 1\n", + " else:\n", + " # Exclude hard negatives from both masks (diagonal)\n", + " for i in range(B_):\n", + " if negative_verbs[i] == 1:\n", + " positive_mask[i, i] = 0\n", + " negative_mask[i, i] = 0\n", + " # Set the entire row and column for the hard negative, except the diagonal\n", + " hard_negative_mask[i, :] = 1 # Mark the i-th row\n", + " hard_negative_mask[:, i] = 1 # Mark the i-th column\n", + " hard_negative_mask[i, i] = 0 # Ensure diagonal element (i, i) is 0\n", + "\n", + " # Apply the positive pairs logic similarly as above\n", + " i = 0\n", + " while i < B_:\n", + " if positive_verbs[i] == 1 and i + 1 < B_ and positive_verbs[i + 1] == 1:\n", + " positive_mask[i, i + 1] = 1\n", + " positive_mask[i + 1, i] = 1\n", + " i += 2\n", + " else:\n", + " i += 1\n", + "\n", + " negative_mask = negative_mask - positive_mask\n", + " negative_mask[hard_negative_mask.bool()] = 0 # Set hard negative indices to 0 in negative_mask\n", + " # print(\"positive mask: \", positive_mask)\n", + " # print(\"negative mask: \", negative_mask)\n", + " return positive_mask, negative_mask, hard_negative_mask\n", + "\n", + "\n", + "def infer_result(model_in_use, data_loader, vis = False, trial = 25):\n", + " with torch.no_grad(): \n", + " sims = []\n", + " pos_masks = []\n", + " neg_masks = []\n", + " iter = 0\n", + " for i, (imgs, texts, target, hardpos) in enumerate(train_loader):\n", + " # data\n", + " imgs = imgs.cuda(non_blocking=True)\n", + " texts = texts.cuda(non_blocking=True)\n", + " target = target.cuda(non_blocking=True).unsqueeze(1)\n", + " hardpos = hardpos.cuda(non_blocking=True)\n", + " #print(hardpos)\n", + " #print(\"shapes: \", imgs.shape, texts.shape, target.shape, hardpos.shape)\n", + "\n", + " # inference\n", + " # preds, tgts, loss, embeddings = model_in_use(image, text, target, hardpos)\n", + " preds, tgts, loss, sim_matrix, posverb_mask, negverb_mask = model_in_use(imgs, texts, target, hardpos)\n", + " verb_mask = posverb_mask + negverb_mask \n", + " positive_mask, negative_mask, hard_negative_mask = return_mask(sim_matrix, posverb_mask, negverb_mask, verb_mask=verb_mask)\n", + " # print(\"mask shapes: \", positive_mask.shape, negative_mask.shape)\n", + " # print(\"pos mask: \", positive_mask)\n", + " # print(\"neg mask: \", negative_mask)\n", + " # print(\"similarity matrix: \", sim_matrix)\n", + "\n", + " # calc similarity matrix\n", + " #sim = calc_sim(embeddings)\n", + " #print(sim_matrix.size())\n", + " #print(posverb_mask)\n", + " sims.append(sim_matrix.detach().cpu().numpy())\n", + " pos_masks.append(positive_mask.detach().cpu().numpy())\n", + " neg_masks.append(negative_mask.detach().cpu().numpy())\n", + " preds = torch.sigmoid(preds)\n", + " if preds.shape[-2:] != imgs.shape[-2:]:\n", + " preds = F.interpolate(preds,\n", + " size=imgs.shape[-2:],\n", + " mode='bicubic',\n", + " align_corners=True).squeeze(1)\n", + " # overlay image and preds mask\n", + " imgs = imgs.detach().cpu()\n", + " texts = texts.detach().cpu()\n", + " preds = preds.detach().cpu()\n", + " \n", + " #masks = masks.detach().cpu()\n", + " # texts to numpy\n", + " texts = texts.numpy()\n", + " \n", + " if vis:\n", + " draw_result(imgs, preds, tgts, texts)\n", + " # draw_result(imgs, preds, masks, texts)\n", + " iter+=1\n", + " if iter > trial:\n", + " break\n", + " return sims, pos_masks, neg_masks " + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "sims_orig, positive_mask_orig, negative_mask_orig = infer_result(original_model, train_loader, vis=False, trial=100)\n", + "sims_new, positive_mask_new, negative_mask_new = infer_result(new_model, train_loader, vis=False, trial=100)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/tmp/ipykernel_1173351/1865868274.py:13: RuntimeWarning: invalid value encountered in arccos\n", + " sim = np.arccos(sim)\n" + ] + }, + { + "data": { + "image/png": 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", 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "angle_vals = []\n", + "\n", + "def get_posneg_sim(sims, poses, negs, combined=False):\n", + " rad_ = 180 / math.pi\n", + " pos_vals = []\n", + " neg_vals = []\n", + " combined_vals = []\n", + " for sim, pos_, neg_ in zip(sims, poses, negs):\n", + " #print(sim.shape, pos_.shape, neg_.shape)\n", + " # make diagonals to 0\n", + " pos_ = pos_ - np.eye(pos_.shape[0])\n", + " neg_ = neg_ - np.eye(neg_.shape[0])\n", + " sim = np.arccos(sim)\n", + " # append, except for values with <0.05 \n", + " pos_vals.extend(sim[pos_ == 1].flatten())\n", + " neg_vals.extend(sim[neg_ == 1].flatten())\n", + " if combined :\n", + " combined_vals.extend(sim[pos_ == 1].flatten())\n", + " combined_vals.extend(sim[neg_ == 1].flatten())\n", + " \n", + " if combined : \n", + " return np.array(pos_vals) * rad_, np.array(neg_vals) * rad_, np.array(combined_vals) * rad_\n", + " else : \n", + " return np.array(pos_vals) * rad_, np.array(neg_vals) * rad_\n", + "\n", + "# pos_vals_orig, neg_vals_orig = get_posneg_sim(sims_orig, positive_mask_orig, negative_mask_orig)\n", + "# pos_vals_new, neg_vals_new = get_posneg_sim(sims_new, positive_mask_new, negative_mask_new)\n", + "\n", + "pos_vals_orig, neg_vals_orig, combined_vals_orig = get_posneg_sim(sims_orig, positive_mask_orig, negative_mask_orig, combined=True)\n", + "pos_vals_new, neg_vals_new, combined_vals_new = get_posneg_sim(sims_new, positive_mask_new, negative_mask_new, combined=True)\n", + "\n", + "\n", + "\n", + "\n", + "plt.hist(pos_vals_orig.repeat(10), bins=100, label=f'pos_orig, $\\mu$ = {np.mean(pos_vals_orig):.2f}', alpha=0.5)\n", + "plt.hist(neg_vals_orig, bins=100, label=f'neg_orig, $\\mu$ = {np.mean(neg_vals_orig):.2f}', alpha=0.5)\n", + "plt.xlabel('Angle (degree)', fontsize=12)\n", + "plt.ylabel('# Samples', fontsize=12)\n", + "plt.title('Pairwise Angular Distribution of Samples, CRIS')\n", + "plt.grid()\n", + "plt.legend()\n", + "plt.show()\n", + "\n", + "plt.hist(90 - pos_vals_new.repeat(10), bins=100, label=f'pos_ACE, $\\mu$ = {90 - np.mean(pos_vals_new):.2f}', alpha=0.5)\n", + "plt.hist(90 - neg_vals_new, bins=100, label=f'neg_ACE, $\\mu$ = {90 - np.mean(neg_vals_new):.2f}', alpha=0.5)\n", + "plt.xlabel('Angle (degree)', fontsize=12)\n", + "plt.ylabel('# Samples', fontsize=12)\n", + "plt.title('Pairwise Angular Distribution of Samples, CRIS+ACE')\n", + "plt.grid()\n", + "plt.legend()\n", + "plt.show()\n", + "\n", + "# for sim in sims:\n", + "# # get off-diagonal elements\n", + "# sim = sim\n", + "# # arccos\n", + "# sim = np.arccos(sim)\n", + "# # append, except for values with <0.05 \n", + "# sim = sim[sim > 0.05]\n", + "# angle_vals.extend(sim.flatten())\n", + "\n", + "# angle_vals_new = []\n", + "# for sim in sims_new:\n", + "# # get off-diagonal elements\n", + "# sim = sim\n", + "# # arccos\n", + "# sim = np.arccos(sim)\n", + "# # append, except for values with <0.05 \n", + "# sim = sim[sim > 0.05]\n", + "# angle_vals_new.extend(sim.flatten())\n", + "\n", + "# plt.hist(angle_vals, bins=100, label='original', alpha=0.5)\n", + "# plt.hist(angle_vals_new, bins=100, label='new', alpha=0.5)\n", + "# plt.legend()\n", + "# plt.show()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + } + ], + "metadata": { + "kernelspec": { + "display_name": "cris_new", + "language": "python", + "name": "cris_new" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.9.20" + } + }, + "nbformat": 4, + "nbformat_minor": 2 +} diff --git a/LAVT-RIS/args.py b/LAVT-RIS/args.py new file mode 100644 index 0000000000000000000000000000000000000000..d8fa9c7b433f15665bdd1c999480faea086ecd95 --- /dev/null +++ b/LAVT-RIS/args.py @@ -0,0 +1,62 @@ +import argparse + + +def get_parser(): + parser = argparse.ArgumentParser(description='LAVT training and testing') + parser.add_argument('--amsgrad', action='store_true', + help='if true, set amsgrad to True in an Adam or AdamW optimizer.') + parser.add_argument('-b', '--batch-size', default=8, type=int) + parser.add_argument('--bert_tokenizer', default='bert-base-uncased', help='BERT tokenizer') + parser.add_argument('--ck_bert', default='bert-base-uncased', help='pre-trained BERT weights') + parser.add_argument('--dataset', default='refcoco', help='refcoco, refcoco+, or refcocog') + parser.add_argument('--ddp_trained_weights', action='store_true', + help='Only needs specified when testing,' + 'whether the weights to be loaded are from a DDP-trained model') + parser.add_argument('--device', default='cuda:0', help='device') # only used when testing on a single machine + parser.add_argument('--epochs', default=40, type=int, metavar='N', help='number of total epochs to run') + parser.add_argument('--fusion_drop', default=0.0, type=float, help='dropout rate for PWAMs') + parser.add_argument('--img_size', default=480, type=int, help='input image size') + # parser.add_argument("--local_rank", type=int, help='local rank for DistributedDataParallel') + parser.add_argument('--lr', default=0.00005, type=float, help='the initial learning rate') + parser.add_argument('--mha', default='', help='If specified, should be in the format of a-b-c-d, e.g., 4-4-4-4,' + 'where a, b, c, and d refer to the numbers of heads in stage-1,' + 'stage-2, stage-3, and stage-4 PWAMs') + parser.add_argument('--model', default='lavt', help='model: lavt, lavt_one') + parser.add_argument('--model_id', default='lavt', help='name to identify the model') + parser.add_argument('--output-dir', default='./checkpoints/', help='path where to save checkpoint weights') + parser.add_argument('--pin_mem', action='store_true', + help='If true, pin memory when using the data loader.') + parser.add_argument('--pretrained_swin_weights', default='', + help='path to pre-trained Swin backbone weights') + parser.add_argument('--print-freq', default=10, type=int, help='print frequency') + parser.add_argument('--refer_data_root', default='./refer/data/', help='REFER dataset root directory') + parser.add_argument('--resume', default='', help='resume from checkpoint') + parser.add_argument('--split', default='test', help='only used when testing') + parser.add_argument('--splitBy', default='unc', help='change to umd or google when the dataset is G-Ref (RefCOCOg)') + parser.add_argument('--swin_type', default='base', + help='tiny, small, base, or large variants of the Swin Transformer') + parser.add_argument('--wd', '--weight-decay', default=1e-2, type=float, metavar='W', help='weight decay', + dest='weight_decay') + parser.add_argument('--window12', action='store_true', + help='only needs specified when testing,' + 'when training, window size is inferred from pre-trained weights file name' + '(containing \'window12\'). Initialize Swin with window size 12 instead of the default 7.') + parser.add_argument('-j', '--workers', default=8, type=int, metavar='N', help='number of data loading workers') + + # metric loss related ones + parser.add_argument('--metric_learning', action='store_true',help='whether to use metric learning') + parser.add_argument('--metric_loss_weight', default=0.1, type=float, help='weight for metric loss') + parser.add_argument('--metric_mode', default='hardpos_rev3', help='test options..') + parser.add_argument('--exclude_multiobj', action='store_true', help='exclude multi-object images') + parser.add_argument('--hn_prob', default=0.0, type=float, help='hard negative probability') + parser.add_argument('--hp_selection', default='naive', help='test options..') + parser.add_argument('--margin_value', default=10, type=float, help='weight for metric loss') + parser.add_argument('--temperature', default=0.05, type=float, help='test options..') + parser.add_argument('--addzero', action='store_true', help='test options..') + + return parser + + +if __name__ == "__main__": + parser = get_parser() + args_dict = parser.parse_args() diff --git a/LAVT-RIS/bert/__pycache__/activations.cpython-37.pyc b/LAVT-RIS/bert/__pycache__/activations.cpython-37.pyc new file mode 100644 index 0000000000000000000000000000000000000000..3893e9a663bce4d59782e1a6bfa69d34f24e1807 Binary files /dev/null and b/LAVT-RIS/bert/__pycache__/activations.cpython-37.pyc differ diff --git a/LAVT-RIS/bert/__pycache__/activations.cpython-39.pyc b/LAVT-RIS/bert/__pycache__/activations.cpython-39.pyc new file mode 100644 index 0000000000000000000000000000000000000000..a568e9fd4e18920fa6b823a32b9dfa55cf2cfd96 Binary files /dev/null and b/LAVT-RIS/bert/__pycache__/activations.cpython-39.pyc differ diff --git a/LAVT-RIS/bert/__pycache__/configuration_bert.cpython-37.pyc b/LAVT-RIS/bert/__pycache__/configuration_bert.cpython-37.pyc new file mode 100644 index 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0000000000000000000000000000000000000000..8a1206ee285ce3f0484d129711a2d684700a20a1 --- /dev/null +++ b/LAVT-RIS/bert/activations.py @@ -0,0 +1,56 @@ +import logging +import math + +import torch +import torch.nn.functional as F + + +logger = logging.getLogger(__name__) + + +def swish(x): + return x * torch.sigmoid(x) + + +def _gelu_python(x): + """ Original Implementation of the gelu activation function in Google Bert repo when initially created. + For information: OpenAI GPT's gelu is slightly different (and gives slightly different results): + 0.5 * x * (1 + torch.tanh(math.sqrt(2 / math.pi) * (x + 0.044715 * torch.pow(x, 3)))) + This is now written in C in torch.nn.functional + Also see https://arxiv.org/abs/1606.08415 + """ + return x * 0.5 * (1.0 + torch.erf(x / math.sqrt(2.0))) + + +def gelu_new(x): + """ Implementation of the gelu activation function currently in Google Bert repo (identical to OpenAI GPT). + Also see https://arxiv.org/abs/1606.08415 + """ + return 0.5 * x * (1.0 + torch.tanh(math.sqrt(2.0 / math.pi) * (x + 0.044715 * torch.pow(x, 3.0)))) + + +if torch.__version__ < "1.4.0": + gelu = _gelu_python +else: + gelu = F.gelu + + +def gelu_fast(x): + return 0.5 * x * (1.0 + torch.tanh(x * 0.7978845608 * (1.0 + 0.044715 * x * x))) + + +ACT2FN = { + "relu": F.relu, + "swish": swish, + "gelu": gelu, + "tanh": torch.tanh, + "gelu_new": gelu_new, + "gelu_fast": gelu_fast, +} + + +def get_activation(activation_string): + if activation_string in ACT2FN: + return ACT2FN[activation_string] + else: + raise KeyError("function {} not found in ACT2FN mapping {}".format(activation_string, list(ACT2FN.keys()))) diff --git a/LAVT-RIS/bert/configuration_bert.py b/LAVT-RIS/bert/configuration_bert.py new file mode 100644 index 0000000000000000000000000000000000000000..8e815837bc4dbc5fc8eec7ee37547b5d41519af5 --- /dev/null +++ b/LAVT-RIS/bert/configuration_bert.py @@ -0,0 +1,143 @@ +# coding=utf-8 +# Copyright 2018 The Google AI Language Team Authors and The HuggingFace Inc. team. +# Copyright (c) 2018, NVIDIA CORPORATION. All rights reserved. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +""" BERT model configuration """ + + +import logging + +from .configuration_utils import PretrainedConfig + + +logger = logging.getLogger(__name__) + +BERT_PRETRAINED_CONFIG_ARCHIVE_MAP = { + "bert-base-uncased": "https://s3.amazonaws.com/models.huggingface.co/bert/bert-base-uncased-config.json", + "bert-large-uncased": "https://s3.amazonaws.com/models.huggingface.co/bert/bert-large-uncased-config.json", + "bert-base-cased": "https://s3.amazonaws.com/models.huggingface.co/bert/bert-base-cased-config.json", + "bert-large-cased": "https://s3.amazonaws.com/models.huggingface.co/bert/bert-large-cased-config.json", + "bert-base-multilingual-uncased": "https://s3.amazonaws.com/models.huggingface.co/bert/bert-base-multilingual-uncased-config.json", + "bert-base-multilingual-cased": "https://s3.amazonaws.com/models.huggingface.co/bert/bert-base-multilingual-cased-config.json", + "bert-base-chinese": "https://s3.amazonaws.com/models.huggingface.co/bert/bert-base-chinese-config.json", + "bert-base-german-cased": "https://s3.amazonaws.com/models.huggingface.co/bert/bert-base-german-cased-config.json", + "bert-large-uncased-whole-word-masking": "https://s3.amazonaws.com/models.huggingface.co/bert/bert-large-uncased-whole-word-masking-config.json", + "bert-large-cased-whole-word-masking": "https://s3.amazonaws.com/models.huggingface.co/bert/bert-large-cased-whole-word-masking-config.json", + "bert-large-uncased-whole-word-masking-finetuned-squad": "https://s3.amazonaws.com/models.huggingface.co/bert/bert-large-uncased-whole-word-masking-finetuned-squad-config.json", + "bert-large-cased-whole-word-masking-finetuned-squad": "https://s3.amazonaws.com/models.huggingface.co/bert/bert-large-cased-whole-word-masking-finetuned-squad-config.json", + "bert-base-cased-finetuned-mrpc": "https://s3.amazonaws.com/models.huggingface.co/bert/bert-base-cased-finetuned-mrpc-config.json", + "bert-base-german-dbmdz-cased": "https://s3.amazonaws.com/models.huggingface.co/bert/bert-base-german-dbmdz-cased-config.json", + "bert-base-german-dbmdz-uncased": "https://s3.amazonaws.com/models.huggingface.co/bert/bert-base-german-dbmdz-uncased-config.json", + "cl-tohoku/bert-base-japanese": "https://s3.amazonaws.com/models.huggingface.co/bert/cl-tohoku/bert-base-japanese/config.json", + "cl-tohoku/bert-base-japanese-whole-word-masking": "https://s3.amazonaws.com/models.huggingface.co/bert/cl-tohoku/bert-base-japanese-whole-word-masking/config.json", + "cl-tohoku/bert-base-japanese-char": "https://s3.amazonaws.com/models.huggingface.co/bert/cl-tohoku/bert-base-japanese-char/config.json", + "cl-tohoku/bert-base-japanese-char-whole-word-masking": "https://s3.amazonaws.com/models.huggingface.co/bert/cl-tohoku/bert-base-japanese-char-whole-word-masking/config.json", + "TurkuNLP/bert-base-finnish-cased-v1": "https://s3.amazonaws.com/models.huggingface.co/bert/TurkuNLP/bert-base-finnish-cased-v1/config.json", + "TurkuNLP/bert-base-finnish-uncased-v1": "https://s3.amazonaws.com/models.huggingface.co/bert/TurkuNLP/bert-base-finnish-uncased-v1/config.json", + "wietsedv/bert-base-dutch-cased": "https://s3.amazonaws.com/models.huggingface.co/bert/wietsedv/bert-base-dutch-cased/config.json", + # See all BERT models at https://huggingface.co/models?filter=bert +} + + +class BertConfig(PretrainedConfig): + r""" + This is the configuration class to store the configuration of a :class:`~transformers.BertModel`. + It is used to instantiate an BERT model according to the specified arguments, defining the model + architecture. Instantiating a configuration with the defaults will yield a similar configuration to that of + the BERT `bert-base-uncased `__ architecture. + + Configuration objects inherit from :class:`~transformers.PretrainedConfig` and can be used + to control the model outputs. Read the documentation from :class:`~transformers.PretrainedConfig` + for more information. + + + Args: + vocab_size (:obj:`int`, optional, defaults to 30522): + Vocabulary size of the BERT model. Defines the different tokens that + can be represented by the `inputs_ids` passed to the forward method of :class:`~transformers.BertModel`. + hidden_size (:obj:`int`, optional, defaults to 768): + Dimensionality of the encoder layers and the pooler layer. + num_hidden_layers (:obj:`int`, optional, defaults to 12): + Number of hidden layers in the Transformer encoder. + num_attention_heads (:obj:`int`, optional, defaults to 12): + Number of attention heads for each attention layer in the Transformer encoder. + intermediate_size (:obj:`int`, optional, defaults to 3072): + Dimensionality of the "intermediate" (i.e., feed-forward) layer in the Transformer encoder. + hidden_act (:obj:`str` or :obj:`function`, optional, defaults to "gelu"): + The non-linear activation function (function or string) in the encoder and pooler. + If string, "gelu", "relu", "swish" and "gelu_new" are supported. + hidden_dropout_prob (:obj:`float`, optional, defaults to 0.1): + The dropout probabilitiy for all fully connected layers in the embeddings, encoder, and pooler. + attention_probs_dropout_prob (:obj:`float`, optional, defaults to 0.1): + The dropout ratio for the attention probabilities. + max_position_embeddings (:obj:`int`, optional, defaults to 512): + The maximum sequence length that this model might ever be used with. + Typically set this to something large just in case (e.g., 512 or 1024 or 2048). + type_vocab_size (:obj:`int`, optional, defaults to 2): + The vocabulary size of the `token_type_ids` passed into :class:`~transformers.BertModel`. + initializer_range (:obj:`float`, optional, defaults to 0.02): + The standard deviation of the truncated_normal_initializer for initializing all weight matrices. + layer_norm_eps (:obj:`float`, optional, defaults to 1e-12): + The epsilon used by the layer normalization layers. + gradient_checkpointing (:obj:`bool`, optional, defaults to False): + If True, use gradient checkpointing to save memory at the expense of slower backward pass. + + Example:: + + >>> from transformers import BertModel, BertConfig + + >>> # Initializing a BERT bert-base-uncased style configuration + >>> configuration = BertConfig() + + >>> # Initializing a model from the bert-base-uncased style configuration + >>> model = BertModel(configuration) + + >>> # Accessing the model configuration + >>> configuration = model.config + """ + model_type = "bert" + + def __init__( + self, + vocab_size=30522, + hidden_size=768, + num_hidden_layers=12, + num_attention_heads=12, + intermediate_size=3072, + hidden_act="gelu", + hidden_dropout_prob=0.1, + attention_probs_dropout_prob=0.1, + max_position_embeddings=512, + type_vocab_size=2, + initializer_range=0.02, + layer_norm_eps=1e-12, + pad_token_id=0, + gradient_checkpointing=False, + **kwargs + ): + super().__init__(pad_token_id=pad_token_id, **kwargs) + + self.vocab_size = vocab_size + self.hidden_size = hidden_size + self.num_hidden_layers = num_hidden_layers + self.num_attention_heads = num_attention_heads + self.hidden_act = hidden_act + self.intermediate_size = intermediate_size + self.hidden_dropout_prob = hidden_dropout_prob + self.attention_probs_dropout_prob = attention_probs_dropout_prob + self.max_position_embeddings = max_position_embeddings + self.type_vocab_size = type_vocab_size + self.initializer_range = initializer_range + self.layer_norm_eps = layer_norm_eps + self.gradient_checkpointing = gradient_checkpointing diff --git a/LAVT-RIS/bert/configuration_utils.py b/LAVT-RIS/bert/configuration_utils.py new file mode 100644 index 0000000000000000000000000000000000000000..9929ee4c19dab9a88bb51e0281d220a8456c2fce --- /dev/null +++ b/LAVT-RIS/bert/configuration_utils.py @@ -0,0 +1,408 @@ +# coding=utf-8 +# Copyright 2018 The Google AI Language Team Authors and The HuggingFace Inc. team. +# Copyright (c) 2018, NVIDIA CORPORATION. All rights reserved. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +""" Configuration base class and utilities.""" + + +import copy +import json +import logging +import os +from typing import Dict, Tuple + +from .file_utils import CONFIG_NAME, cached_path, hf_bucket_url, is_remote_url + + +logger = logging.getLogger(__name__) + + +class PretrainedConfig(object): + r""" Base class for all configuration classes. + Handles a few parameters common to all models' configurations as well as methods for loading/downloading/saving configurations. + + Note: + A configuration file can be loaded and saved to disk. Loading the configuration file and using this file to initialize a model does **not** load the model weights. + It only affects the model's configuration. + + Class attributes (overridden by derived classes): + - ``model_type``: a string that identifies the model type, that we serialize into the JSON file, and that we use to recreate the correct object in :class:`~transformers.AutoConfig`. + + Args: + finetuning_task (:obj:`string` or :obj:`None`, `optional`, defaults to :obj:`None`): + Name of the task used to fine-tune the model. This can be used when converting from an original (TensorFlow or PyTorch) checkpoint. + num_labels (:obj:`int`, `optional`, defaults to `2`): + Number of classes to use when the model is a classification model (sequences/tokens) + output_hidden_states (:obj:`bool`, `optional`, defaults to :obj:`False`): + Should the model returns all hidden-states. + output_attentions (:obj:`bool`, `optional`, defaults to :obj:`False`): + Should the model returns all attentions. + torchscript (:obj:`bool`, `optional`, defaults to :obj:`False`): + Is the model used with Torchscript (for PyTorch models). + """ + model_type: str = "" + + def __init__(self, **kwargs): + # Attributes with defaults + self.output_hidden_states = kwargs.pop("output_hidden_states", False) + self.output_attentions = kwargs.pop("output_attentions", False) + self.use_cache = kwargs.pop("use_cache", True) # Not used by all models + self.torchscript = kwargs.pop("torchscript", False) # Only used by PyTorch models + self.use_bfloat16 = kwargs.pop("use_bfloat16", False) + self.pruned_heads = kwargs.pop("pruned_heads", {}) + + # Is decoder is used in encoder-decoder models to differentiate encoder from decoder + self.is_encoder_decoder = kwargs.pop("is_encoder_decoder", False) + self.is_decoder = kwargs.pop("is_decoder", False) + + # Parameters for sequence generation + self.max_length = kwargs.pop("max_length", 20) + self.min_length = kwargs.pop("min_length", 0) + self.do_sample = kwargs.pop("do_sample", False) + self.early_stopping = kwargs.pop("early_stopping", False) + self.num_beams = kwargs.pop("num_beams", 1) + self.temperature = kwargs.pop("temperature", 1.0) + self.top_k = kwargs.pop("top_k", 50) + self.top_p = kwargs.pop("top_p", 1.0) + self.repetition_penalty = kwargs.pop("repetition_penalty", 1.0) + self.length_penalty = kwargs.pop("length_penalty", 1.0) + self.no_repeat_ngram_size = kwargs.pop("no_repeat_ngram_size", 0) + self.bad_words_ids = kwargs.pop("bad_words_ids", None) + self.num_return_sequences = kwargs.pop("num_return_sequences", 1) + + # Fine-tuning task arguments + self.architectures = kwargs.pop("architectures", None) + self.finetuning_task = kwargs.pop("finetuning_task", None) + self.id2label = kwargs.pop("id2label", None) + self.label2id = kwargs.pop("label2id", None) + if self.id2label is not None: + kwargs.pop("num_labels", None) + self.id2label = dict((int(key), value) for key, value in self.id2label.items()) + # Keys are always strings in JSON so convert ids to int here. + else: + self.num_labels = kwargs.pop("num_labels", 2) + + # Tokenizer arguments TODO: eventually tokenizer and models should share the same config + self.prefix = kwargs.pop("prefix", None) + self.bos_token_id = kwargs.pop("bos_token_id", None) + self.pad_token_id = kwargs.pop("pad_token_id", None) + self.eos_token_id = kwargs.pop("eos_token_id", None) + self.decoder_start_token_id = kwargs.pop("decoder_start_token_id", None) + + # task specific arguments + self.task_specific_params = kwargs.pop("task_specific_params", None) + + # TPU arguments + self.xla_device = kwargs.pop("xla_device", None) + + # Additional attributes without default values + for key, value in kwargs.items(): + try: + setattr(self, key, value) + except AttributeError as err: + logger.error("Can't set {} with value {} for {}".format(key, value, self)) + raise err + + @property + def num_labels(self): + return len(self.id2label) + + @num_labels.setter + def num_labels(self, num_labels): + self.id2label = {i: "LABEL_{}".format(i) for i in range(num_labels)} + self.label2id = dict(zip(self.id2label.values(), self.id2label.keys())) + + def save_pretrained(self, save_directory): + """ + Save a configuration object to the directory `save_directory`, so that it + can be re-loaded using the :func:`~transformers.PretrainedConfig.from_pretrained` class method. + + Args: + save_directory (:obj:`string`): + Directory where the configuration JSON file will be saved. + """ + if os.path.isfile(save_directory): + raise AssertionError("Provided path ({}) should be a directory, not a file".format(save_directory)) + os.makedirs(save_directory, exist_ok=True) + # If we save using the predefined names, we can load using `from_pretrained` + output_config_file = os.path.join(save_directory, CONFIG_NAME) + + self.to_json_file(output_config_file, use_diff=True) + logger.info("Configuration saved in {}".format(output_config_file)) + + @classmethod + def from_pretrained(cls, pretrained_model_name_or_path, **kwargs) -> "PretrainedConfig": + r""" + + Instantiate a :class:`~transformers.PretrainedConfig` (or a derived class) from a pre-trained model configuration. + + Args: + pretrained_model_name_or_path (:obj:`string`): + either: + - a string with the `shortcut name` of a pre-trained model configuration to load from cache or + download, e.g.: ``bert-base-uncased``. + - a string with the `identifier name` of a pre-trained model configuration that was user-uploaded to + our S3, e.g.: ``dbmdz/bert-base-german-cased``. + - a path to a `directory` containing a configuration file saved using the + :func:`~transformers.PretrainedConfig.save_pretrained` method, e.g.: ``./my_model_directory/``. + - a path or url to a saved configuration JSON `file`, e.g.: + ``./my_model_directory/configuration.json``. + cache_dir (:obj:`string`, `optional`): + Path to a directory in which a downloaded pre-trained model + configuration should be cached if the standard cache should not be used. + kwargs (:obj:`Dict[str, any]`, `optional`): + The values in kwargs of any keys which are configuration attributes will be used to override the loaded + values. Behavior concerning key/value pairs whose keys are *not* configuration attributes is + controlled by the `return_unused_kwargs` keyword parameter. + force_download (:obj:`bool`, `optional`, defaults to :obj:`False`): + Force to (re-)download the model weights and configuration files and override the cached versions if they exist. + resume_download (:obj:`bool`, `optional`, defaults to :obj:`False`): + Do not delete incompletely recieved file. Attempt to resume the download if such a file exists. + proxies (:obj:`Dict`, `optional`): + A dictionary of proxy servers to use by protocol or endpoint, e.g.: + :obj:`{'http': 'foo.bar:3128', 'http://hostname': 'foo.bar:4012'}.` + The proxies are used on each request. + return_unused_kwargs: (`optional`) bool: + If False, then this function returns just the final configuration object. + If True, then this functions returns a :obj:`Tuple(config, unused_kwargs)` where `unused_kwargs` is a + dictionary consisting of the key/value pairs whose keys are not configuration attributes: ie the part + of kwargs which has not been used to update `config` and is otherwise ignored. + + Returns: + :class:`PretrainedConfig`: An instance of a configuration object + + Examples:: + + # We can't instantiate directly the base class `PretrainedConfig` so let's show the examples on a + # derived class: BertConfig + config = BertConfig.from_pretrained('bert-base-uncased') # Download configuration from S3 and cache. + config = BertConfig.from_pretrained('./test/saved_model/') # E.g. config (or model) was saved using `save_pretrained('./test/saved_model/')` + config = BertConfig.from_pretrained('./test/saved_model/my_configuration.json') + config = BertConfig.from_pretrained('bert-base-uncased', output_attention=True, foo=False) + assert config.output_attention == True + config, unused_kwargs = BertConfig.from_pretrained('bert-base-uncased', output_attention=True, + foo=False, return_unused_kwargs=True) + assert config.output_attention == True + assert unused_kwargs == {'foo': False} + + """ + config_dict, kwargs = cls.get_config_dict(pretrained_model_name_or_path, **kwargs) + return cls.from_dict(config_dict, **kwargs) + + @classmethod + def get_config_dict(cls, pretrained_model_name_or_path: str, **kwargs) -> Tuple[Dict, Dict]: + """ + From a `pretrained_model_name_or_path`, resolve to a dictionary of parameters, to be used + for instantiating a Config using `from_dict`. + + Parameters: + pretrained_model_name_or_path (:obj:`string`): + The identifier of the pre-trained checkpoint from which we want the dictionary of parameters. + + Returns: + :obj:`Tuple[Dict, Dict]`: The dictionary that will be used to instantiate the configuration object. + + """ + cache_dir = kwargs.pop("cache_dir", None) + force_download = kwargs.pop("force_download", False) + resume_download = kwargs.pop("resume_download", False) + proxies = kwargs.pop("proxies", None) + local_files_only = kwargs.pop("local_files_only", False) + + if os.path.isdir(pretrained_model_name_or_path): + config_file = os.path.join(pretrained_model_name_or_path, CONFIG_NAME) + elif os.path.isfile(pretrained_model_name_or_path) or is_remote_url(pretrained_model_name_or_path): + config_file = pretrained_model_name_or_path + else: + config_file = hf_bucket_url(pretrained_model_name_or_path, filename=CONFIG_NAME, use_cdn=False) + + try: + # Load from URL or cache if already cached + resolved_config_file = cached_path( + config_file, + cache_dir=cache_dir, + force_download=force_download, + proxies=proxies, + resume_download=resume_download, + local_files_only=local_files_only, + ) + # Load config dict + if resolved_config_file is None: + raise EnvironmentError + config_dict = cls._dict_from_json_file(resolved_config_file) + + except EnvironmentError: + msg = ( + f"Can't load config for '{pretrained_model_name_or_path}'. Make sure that:\n\n" + f"- '{pretrained_model_name_or_path}' is a correct model identifier listed on 'https://huggingface.co/models'\n\n" + f"- or '{pretrained_model_name_or_path}' is the correct path to a directory containing a {CONFIG_NAME} file\n\n" + ) + raise EnvironmentError(msg) + + except json.JSONDecodeError: + msg = ( + "Couldn't reach server at '{}' to download configuration file or " + "configuration file is not a valid JSON file. " + "Please check network or file content here: {}.".format(config_file, resolved_config_file) + ) + raise EnvironmentError(msg) + + if resolved_config_file == config_file: + logger.info("loading configuration file {}".format(config_file)) + else: + logger.info("loading configuration file {} from cache at {}".format(config_file, resolved_config_file)) + + return config_dict, kwargs + + @classmethod + def from_dict(cls, config_dict: Dict, **kwargs) -> "PretrainedConfig": + """ + Constructs a `Config` from a Python dictionary of parameters. + + Args: + config_dict (:obj:`Dict[str, any]`): + Dictionary that will be used to instantiate the configuration object. Such a dictionary can be retrieved + from a pre-trained checkpoint by leveraging the :func:`~transformers.PretrainedConfig.get_config_dict` + method. + kwargs (:obj:`Dict[str, any]`): + Additional parameters from which to initialize the configuration object. + + Returns: + :class:`PretrainedConfig`: An instance of a configuration object + """ + return_unused_kwargs = kwargs.pop("return_unused_kwargs", False) + + config = cls(**config_dict) + + if hasattr(config, "pruned_heads"): + config.pruned_heads = dict((int(key), value) for key, value in config.pruned_heads.items()) + + # Update config with kwargs if needed + to_remove = [] + for key, value in kwargs.items(): + if hasattr(config, key): + setattr(config, key, value) + to_remove.append(key) + for key in to_remove: + kwargs.pop(key, None) + + logger.info("Model config %s", str(config)) + if return_unused_kwargs: + return config, kwargs + else: + return config + + @classmethod + def from_json_file(cls, json_file: str) -> "PretrainedConfig": + """ + Constructs a `Config` from the path to a json file of parameters. + + Args: + json_file (:obj:`string`): + Path to the JSON file containing the parameters. + + Returns: + :class:`PretrainedConfig`: An instance of a configuration object + + """ + config_dict = cls._dict_from_json_file(json_file) + return cls(**config_dict) + + @classmethod + def _dict_from_json_file(cls, json_file: str): + with open(json_file, "r", encoding="utf-8") as reader: + text = reader.read() + return json.loads(text) + + def __eq__(self, other): + return self.__dict__ == other.__dict__ + + def __repr__(self): + return "{} {}".format(self.__class__.__name__, self.to_json_string()) + + def to_diff_dict(self): + """ + Removes all attributes from config which correspond to the default + config attributes for better readability and serializes to a Python + dictionary. + + Returns: + :obj:`Dict[str, any]`: Dictionary of all the attributes that make up this configuration instance, + """ + config_dict = self.to_dict() + + # get the default config dict + default_config_dict = PretrainedConfig().to_dict() + + serializable_config_dict = {} + + # only serialize values that differ from the default config + for key, value in config_dict.items(): + if key not in default_config_dict or value != default_config_dict[key]: + serializable_config_dict[key] = value + + return serializable_config_dict + + def to_dict(self): + """ + Serializes this instance to a Python dictionary. + + Returns: + :obj:`Dict[str, any]`: Dictionary of all the attributes that make up this configuration instance, + """ + output = copy.deepcopy(self.__dict__) + if hasattr(self.__class__, "model_type"): + output["model_type"] = self.__class__.model_type + return output + + def to_json_string(self, use_diff=True): + """ + Serializes this instance to a JSON string. + + Args: + use_diff (:obj:`bool`): + If set to True, only the difference between the config instance and the default PretrainedConfig() is serialized to JSON string. + + Returns: + :obj:`string`: String containing all the attributes that make up this configuration instance in JSON format. + """ + if use_diff is True: + config_dict = self.to_diff_dict() + else: + config_dict = self.to_dict() + return json.dumps(config_dict, indent=2, sort_keys=True) + "\n" + + def to_json_file(self, json_file_path, use_diff=True): + """ + Save this instance to a json file. + + Args: + json_file_path (:obj:`string`): + Path to the JSON file in which this configuration instance's parameters will be saved. + use_diff (:obj:`bool`): + If set to True, only the difference between the config instance and the default PretrainedConfig() is serialized to JSON file. + """ + with open(json_file_path, "w", encoding="utf-8") as writer: + writer.write(self.to_json_string(use_diff=use_diff)) + + def update(self, config_dict: Dict): + """ + Updates attributes of this class + with attributes from `config_dict`. + + Args: + :obj:`Dict[str, any]`: Dictionary of attributes that shall be updated for this class. + """ + for key, value in config_dict.items(): + setattr(self, key, value) diff --git a/LAVT-RIS/bert/file_utils.py b/LAVT-RIS/bert/file_utils.py new file mode 100644 index 0000000000000000000000000000000000000000..81b76b7fefd186d540fda1014dd69724049a4483 --- /dev/null +++ b/LAVT-RIS/bert/file_utils.py @@ -0,0 +1,808 @@ +""" +Utilities for working with the local dataset cache. +This file is adapted from the AllenNLP library at https://github.com/allenai/allennlp +Copyright by the AllenNLP authors. +""" + +import fnmatch +import json +import logging +import os +import shutil +import sys +import tarfile +import tempfile +from contextlib import contextmanager +from functools import partial, wraps +from hashlib import sha256 +from pathlib import Path +from typing import Dict, Optional, Union +from urllib.parse import urlparse +from zipfile import ZipFile, is_zipfile + +import requests +from filelock import FileLock +from tqdm.auto import tqdm + +#from . import __version__ +__version__ = "3.0.2" + +logger = logging.getLogger(__name__) # pylint: disable=invalid-name + +try: + USE_TF = os.environ.get("USE_TF", "AUTO").upper() + USE_TORCH = os.environ.get("USE_TORCH", "AUTO").upper() + if USE_TORCH in ("1", "ON", "YES", "AUTO") and USE_TF not in ("1", "ON", "YES"): + import torch + + _torch_available = True # pylint: disable=invalid-name + logger.info("PyTorch version {} available.".format(torch.__version__)) + else: + logger.info("Disabling PyTorch because USE_TF is set") + _torch_available = False +except ImportError: + _torch_available = False # pylint: disable=invalid-name + +try: + USE_TF = os.environ.get("USE_TF", "AUTO").upper() + USE_TORCH = os.environ.get("USE_TORCH", "AUTO").upper() + + if USE_TF in ("1", "ON", "YES", "AUTO") and USE_TORCH not in ("1", "ON", "YES"): + import tensorflow as tf + + assert hasattr(tf, "__version__") and int(tf.__version__[0]) >= 2 + _tf_available = True # pylint: disable=invalid-name + logger.info("TensorFlow version {} available.".format(tf.__version__)) + else: + logger.info("Disabling Tensorflow because USE_TORCH is set") + _tf_available = False +except (ImportError, AssertionError): + _tf_available = False # pylint: disable=invalid-name + + +try: + from torch.hub import _get_torch_home + + torch_cache_home = _get_torch_home() +except ImportError: + torch_cache_home = os.path.expanduser( + os.getenv("TORCH_HOME", os.path.join(os.getenv("XDG_CACHE_HOME", "~/.cache"), "torch")) + ) + + +try: + import torch_xla.core.xla_model as xm # noqa: F401 + + if _torch_available: + _torch_tpu_available = True # pylint: disable= + else: + _torch_tpu_available = False +except ImportError: + _torch_tpu_available = False + + +try: + import psutil # noqa: F401 + + _psutil_available = True + +except ImportError: + _psutil_available = False + + +try: + import py3nvml # noqa: F401 + + _py3nvml_available = True + +except ImportError: + _py3nvml_available = False + + +try: + from apex import amp # noqa: F401 + + _has_apex = True +except ImportError: + _has_apex = False + +default_cache_path = os.path.join(torch_cache_home, "transformers") + + +PYTORCH_PRETRAINED_BERT_CACHE = os.getenv("PYTORCH_PRETRAINED_BERT_CACHE", default_cache_path) +PYTORCH_TRANSFORMERS_CACHE = os.getenv("PYTORCH_TRANSFORMERS_CACHE", PYTORCH_PRETRAINED_BERT_CACHE) +TRANSFORMERS_CACHE = os.getenv("TRANSFORMERS_CACHE", PYTORCH_TRANSFORMERS_CACHE) + +WEIGHTS_NAME = "pytorch_model.bin" +TF2_WEIGHTS_NAME = "tf_model.h5" +TF_WEIGHTS_NAME = "model.ckpt" +CONFIG_NAME = "config.json" +MODEL_CARD_NAME = "modelcard.json" + + +MULTIPLE_CHOICE_DUMMY_INPUTS = [[[0], [1]], [[0], [1]]] +DUMMY_INPUTS = [[7, 6, 0, 0, 1], [1, 2, 3, 0, 0], [0, 0, 0, 4, 5]] +DUMMY_MASK = [[1, 1, 1, 1, 1], [1, 1, 1, 0, 0], [0, 0, 0, 1, 1]] + +S3_BUCKET_PREFIX = "https://s3.amazonaws.com/models.huggingface.co/bert" +CLOUDFRONT_DISTRIB_PREFIX = "https://cdn.huggingface.co" + + +def is_torch_available(): + return _torch_available + + +def is_tf_available(): + return _tf_available + + +def is_torch_tpu_available(): + return _torch_tpu_available + + +def is_psutil_available(): + return _psutil_available + + +def is_py3nvml_available(): + return _py3nvml_available + + +def is_apex_available(): + return _has_apex + + +def add_start_docstrings(*docstr): + def docstring_decorator(fn): + fn.__doc__ = "".join(docstr) + (fn.__doc__ if fn.__doc__ is not None else "") + return fn + + return docstring_decorator + + +def add_start_docstrings_to_callable(*docstr): + def docstring_decorator(fn): + class_name = ":class:`~transformers.{}`".format(fn.__qualname__.split(".")[0]) + intro = " The {} forward method, overrides the :func:`__call__` special method.".format(class_name) + note = r""" + + .. note:: + Although the recipe for forward pass needs to be defined within + this function, one should call the :class:`Module` instance afterwards + instead of this since the former takes care of running the + pre and post processing steps while the latter silently ignores them. + """ + fn.__doc__ = intro + note + "".join(docstr) + (fn.__doc__ if fn.__doc__ is not None else "") + return fn + + return docstring_decorator + + +def add_end_docstrings(*docstr): + def docstring_decorator(fn): + fn.__doc__ = fn.__doc__ + "".join(docstr) + return fn + + return docstring_decorator + + +PT_TOKEN_CLASSIFICATION_SAMPLE = r""" + Example:: + + >>> from transformers import {tokenizer_class}, {model_class} + >>> import torch + + >>> tokenizer = {tokenizer_class}.from_pretrained('{checkpoint}') + >>> model = {model_class}.from_pretrained('{checkpoint}') + + >>> inputs = tokenizer("Hello, my dog is cute", return_tensors="pt") + >>> labels = torch.tensor([1] * inputs["input_ids"].size(1)).unsqueeze(0) # Batch size 1 + + >>> outputs = model(**inputs, labels=labels) + >>> loss, scores = outputs[:2] +""" + +PT_QUESTION_ANSWERING_SAMPLE = r""" + Example:: + + >>> from transformers import {tokenizer_class}, {model_class} + >>> import torch + + >>> tokenizer = {tokenizer_class}.from_pretrained('{checkpoint}') + >>> model = {model_class}.from_pretrained('{checkpoint}') + + >>> inputs = tokenizer("Hello, my dog is cute", return_tensors="pt") + >>> start_positions = torch.tensor([1]) + >>> end_positions = torch.tensor([3]) + + >>> outputs = model(**inputs, start_positions=start_positions, end_positions=end_positions) + >>> loss, start_scores, end_scores = outputs[:3] +""" + +PT_SEQUENCE_CLASSIFICATION_SAMPLE = r""" + Example:: + + >>> from transformers import {tokenizer_class}, {model_class} + >>> import torch + + >>> tokenizer = {tokenizer_class}.from_pretrained('{checkpoint}') + >>> model = {model_class}.from_pretrained('{checkpoint}') + + >>> inputs = tokenizer("Hello, my dog is cute", return_tensors="pt") + >>> labels = torch.tensor([1]).unsqueeze(0) # Batch size 1 + >>> outputs = model(**inputs, labels=labels) + >>> loss, logits = outputs[:2] +""" + +PT_MASKED_LM_SAMPLE = r""" + Example:: + + >>> from transformers import {tokenizer_class}, {model_class} + >>> import torch + + >>> tokenizer = {tokenizer_class}.from_pretrained('{checkpoint}') + >>> model = {model_class}.from_pretrained('{checkpoint}') + + >>> input_ids = tokenizer("Hello, my dog is cute", return_tensors="pt")["input_ids"] + + >>> outputs = model(input_ids, labels=input_ids) + >>> loss, prediction_scores = outputs[:2] +""" + +PT_BASE_MODEL_SAMPLE = r""" + Example:: + + >>> from transformers import {tokenizer_class}, {model_class} + >>> import torch + + >>> tokenizer = {tokenizer_class}.from_pretrained('{checkpoint}') + >>> model = {model_class}.from_pretrained('{checkpoint}') + + >>> inputs = tokenizer("Hello, my dog is cute", return_tensors="pt") + >>> outputs = model(**inputs) + + >>> last_hidden_states = outputs[0] # The last hidden-state is the first element of the output tuple +""" + +PT_MULTIPLE_CHOICE_SAMPLE = r""" + Example:: + + >>> from transformers import {tokenizer_class}, {model_class} + >>> import torch + + >>> tokenizer = {tokenizer_class}.from_pretrained('{checkpoint}') + >>> model = {model_class}.from_pretrained('{checkpoint}') + + >>> prompt = "In Italy, pizza served in formal settings, such as at a restaurant, is presented unsliced." + >>> choice0 = "It is eaten with a fork and a knife." + >>> choice1 = "It is eaten while held in the hand." + >>> labels = torch.tensor(0).unsqueeze(0) # choice0 is correct (according to Wikipedia ;)), batch size 1 + + >>> encoding = tokenizer([[prompt, prompt], [choice0, choice1]], return_tensors='pt', padding=True) + >>> outputs = model(**{{k: v.unsqueeze(0) for k,v in encoding.items()}}, labels=labels) # batch size is 1 + + >>> # the linear classifier still needs to be trained + >>> loss, logits = outputs[:2] +""" + +PT_CAUSAL_LM_SAMPLE = r""" + Example:: + + >>> import torch + >>> from transformers import {tokenizer_class}, {model_class} + + >>> tokenizer = {tokenizer_class}.from_pretrained('{checkpoint}') + >>> model = {model_class}.from_pretrained('{checkpoint}') + + >>> inputs = tokenizer("Hello, my dog is cute", return_tensors="pt") + >>> outputs = model(**inputs, labels=inputs["input_ids"]) + >>> loss, logits = outputs[:2] +""" + +TF_TOKEN_CLASSIFICATION_SAMPLE = r""" + Example:: + + >>> from transformers import {tokenizer_class}, {model_class} + >>> import tensorflow as tf + + >>> tokenizer = {tokenizer_class}.from_pretrained('{checkpoint}') + >>> model = {model_class}.from_pretrained('{checkpoint}') + + >>> inputs = tokenizer("Hello, my dog is cute", return_tensors="tf") + >>> input_ids = inputs["input_ids"] + >>> inputs["labels"] = tf.reshape(tf.constant([1] * tf.size(input_ids).numpy()), (-1, tf.size(input_ids))) # Batch size 1 + + >>> outputs = model(inputs) + >>> loss, scores = outputs[:2] +""" + +TF_QUESTION_ANSWERING_SAMPLE = r""" + Example:: + + >>> from transformers import {tokenizer_class}, {model_class} + >>> import tensorflow as tf + + >>> tokenizer = {tokenizer_class}.from_pretrained('{checkpoint}') + >>> model = {model_class}.from_pretrained('{checkpoint}') + + >>> question, text = "Who was Jim Henson?", "Jim Henson was a nice puppet" + >>> input_dict = tokenizer(question, text, return_tensors='tf') + >>> start_scores, end_scores = model(input_dict) + + >>> all_tokens = tokenizer.convert_ids_to_tokens(input_dict["input_ids"].numpy()[0]) + >>> answer = ' '.join(all_tokens[tf.math.argmax(start_scores, 1)[0] : tf.math.argmax(end_scores, 1)[0]+1]) +""" + +TF_SEQUENCE_CLASSIFICATION_SAMPLE = r""" + Example:: + + >>> from transformers import {tokenizer_class}, {model_class} + >>> import tensorflow as tf + + >>> tokenizer = {tokenizer_class}.from_pretrained('{checkpoint}') + >>> model = {model_class}.from_pretrained('{checkpoint}') + + >>> inputs = tokenizer("Hello, my dog is cute", return_tensors="tf") + >>> inputs["labels"] = tf.reshape(tf.constant(1), (-1, 1)) # Batch size 1 + + >>> outputs = model(inputs) + >>> loss, logits = outputs[:2] +""" + +TF_MASKED_LM_SAMPLE = r""" + Example:: + >>> from transformers import {tokenizer_class}, {model_class} + >>> import tensorflow as tf + + >>> tokenizer = {tokenizer_class}.from_pretrained('{checkpoint}') + >>> model = {model_class}.from_pretrained('{checkpoint}') + + >>> input_ids = tf.constant(tokenizer.encode("Hello, my dog is cute", add_special_tokens=True))[None, :] # Batch size 1 + + >>> outputs = model(input_ids) + >>> prediction_scores = outputs[0] +""" + +TF_BASE_MODEL_SAMPLE = r""" + Example:: + + >>> from transformers import {tokenizer_class}, {model_class} + >>> import tensorflow as tf + + >>> tokenizer = {tokenizer_class}.from_pretrained('{checkpoint}') + >>> model = {model_class}.from_pretrained('{checkpoint}') + + >>> inputs = tokenizer("Hello, my dog is cute", return_tensors="tf") + >>> outputs = model(inputs) + + >>> last_hidden_states = outputs[0] # The last hidden-state is the first element of the output tuple +""" + +TF_MULTIPLE_CHOICE_SAMPLE = r""" + Example:: + + >>> from transformers import {tokenizer_class}, {model_class} + >>> import tensorflow as tf + + >>> tokenizer = {tokenizer_class}.from_pretrained('{checkpoint}') + >>> model = {model_class}.from_pretrained('{checkpoint}') + + >>> prompt = "In Italy, pizza served in formal settings, such as at a restaurant, is presented unsliced." + >>> choice0 = "It is eaten with a fork and a knife." + >>> choice1 = "It is eaten while held in the hand." + + >>> encoding = tokenizer([[prompt, prompt], [choice0, choice1]], return_tensors='tf', padding=True) + >>> inputs = {{k: tf.expand_dims(v, 0) for k, v in encoding.items()}} + >>> outputs = model(inputs) # batch size is 1 + + >>> # the linear classifier still needs to be trained + >>> logits = outputs[0] +""" + +TF_CAUSAL_LM_SAMPLE = r""" + Example:: + + >>> from transformers import {tokenizer_class}, {model_class} + >>> import tensorflow as tf + + >>> tokenizer = {tokenizer_class}.from_pretrained('{checkpoint}') + >>> model = {model_class}.from_pretrained('{checkpoint}') + + >>> inputs = tokenizer("Hello, my dog is cute", return_tensors="tf") + >>> outputs = model(inputs) + >>> logits = outputs[0] +""" + + +def add_code_sample_docstrings(*docstr, tokenizer_class=None, checkpoint=None): + def docstring_decorator(fn): + model_class = fn.__qualname__.split(".")[0] + is_tf_class = model_class[:2] == "TF" + + if "SequenceClassification" in model_class: + code_sample = TF_SEQUENCE_CLASSIFICATION_SAMPLE if is_tf_class else PT_SEQUENCE_CLASSIFICATION_SAMPLE + elif "QuestionAnswering" in model_class: + code_sample = TF_QUESTION_ANSWERING_SAMPLE if is_tf_class else PT_QUESTION_ANSWERING_SAMPLE + elif "TokenClassification" in model_class: + code_sample = TF_TOKEN_CLASSIFICATION_SAMPLE if is_tf_class else PT_TOKEN_CLASSIFICATION_SAMPLE + elif "MultipleChoice" in model_class: + code_sample = TF_MULTIPLE_CHOICE_SAMPLE if is_tf_class else PT_MULTIPLE_CHOICE_SAMPLE + elif "MaskedLM" in model_class: + code_sample = TF_MASKED_LM_SAMPLE if is_tf_class else PT_MASKED_LM_SAMPLE + elif "LMHead" in model_class: + code_sample = TF_CAUSAL_LM_SAMPLE if is_tf_class else PT_CAUSAL_LM_SAMPLE + elif "Model" in model_class: + code_sample = TF_BASE_MODEL_SAMPLE if is_tf_class else PT_BASE_MODEL_SAMPLE + else: + raise ValueError(f"Docstring can't be built for model {model_class}") + + built_doc = code_sample.format(model_class=model_class, tokenizer_class=tokenizer_class, checkpoint=checkpoint) + fn.__doc__ = (fn.__doc__ or "") + "".join(docstr) + built_doc + return fn + + return docstring_decorator + + +def is_remote_url(url_or_filename): + parsed = urlparse(url_or_filename) + return parsed.scheme in ("http", "https") + + +def hf_bucket_url(model_id: str, filename: str, use_cdn=True) -> str: + """ + Resolve a model identifier, and a file name, to a HF-hosted url + on either S3 or Cloudfront (a Content Delivery Network, or CDN). + + Cloudfront is replicated over the globe so downloads are way faster + for the end user (and it also lowers our bandwidth costs). However, it + is more aggressively cached by default, so may not always reflect the + latest changes to the underlying file (default TTL is 24 hours). + + In terms of client-side caching from this library, even though + Cloudfront relays the ETags from S3, using one or the other + (or switching from one to the other) will affect caching: cached files + are not shared between the two because the cached file's name contains + a hash of the url. + """ + endpoint = CLOUDFRONT_DISTRIB_PREFIX if use_cdn else S3_BUCKET_PREFIX + legacy_format = "/" not in model_id + if legacy_format: + return f"{endpoint}/{model_id}-{filename}" + else: + return f"{endpoint}/{model_id}/{filename}" + + +def url_to_filename(url, etag=None): + """ + Convert `url` into a hashed filename in a repeatable way. + If `etag` is specified, append its hash to the url's, delimited + by a period. + If the url ends with .h5 (Keras HDF5 weights) adds '.h5' to the name + so that TF 2.0 can identify it as a HDF5 file + (see https://github.com/tensorflow/tensorflow/blob/00fad90125b18b80fe054de1055770cfb8fe4ba3/tensorflow/python/keras/engine/network.py#L1380) + """ + url_bytes = url.encode("utf-8") + url_hash = sha256(url_bytes) + filename = url_hash.hexdigest() + + if etag: + etag_bytes = etag.encode("utf-8") + etag_hash = sha256(etag_bytes) + filename += "." + etag_hash.hexdigest() + + if url.endswith(".h5"): + filename += ".h5" + + return filename + + +def filename_to_url(filename, cache_dir=None): + """ + Return the url and etag (which may be ``None``) stored for `filename`. + Raise ``EnvironmentError`` if `filename` or its stored metadata do not exist. + """ + if cache_dir is None: + cache_dir = TRANSFORMERS_CACHE + if isinstance(cache_dir, Path): + cache_dir = str(cache_dir) + + cache_path = os.path.join(cache_dir, filename) + if not os.path.exists(cache_path): + raise EnvironmentError("file {} not found".format(cache_path)) + + meta_path = cache_path + ".json" + if not os.path.exists(meta_path): + raise EnvironmentError("file {} not found".format(meta_path)) + + with open(meta_path, encoding="utf-8") as meta_file: + metadata = json.load(meta_file) + url = metadata["url"] + etag = metadata["etag"] + + return url, etag + + +def cached_path( + url_or_filename, + cache_dir=None, + force_download=False, + proxies=None, + resume_download=False, + user_agent: Union[Dict, str, None] = None, + extract_compressed_file=False, + force_extract=False, + local_files_only=False, +) -> Optional[str]: + """ + Given something that might be a URL (or might be a local path), + determine which. If it's a URL, download the file and cache it, and + return the path to the cached file. If it's already a local path, + make sure the file exists and then return the path. + Args: + cache_dir: specify a cache directory to save the file to (overwrite the default cache dir). + force_download: if True, re-dowload the file even if it's already cached in the cache dir. + resume_download: if True, resume the download if incompletly recieved file is found. + user_agent: Optional string or dict that will be appended to the user-agent on remote requests. + extract_compressed_file: if True and the path point to a zip or tar file, extract the compressed + file in a folder along the archive. + force_extract: if True when extract_compressed_file is True and the archive was already extracted, + re-extract the archive and overide the folder where it was extracted. + + Return: + None in case of non-recoverable file (non-existent or inaccessible url + no cache on disk). + Local path (string) otherwise + """ + if cache_dir is None: + cache_dir = TRANSFORMERS_CACHE + if isinstance(url_or_filename, Path): + url_or_filename = str(url_or_filename) + if isinstance(cache_dir, Path): + cache_dir = str(cache_dir) + + if is_remote_url(url_or_filename): + # URL, so get it from the cache (downloading if necessary) + output_path = get_from_cache( + url_or_filename, + cache_dir=cache_dir, + force_download=force_download, + proxies=proxies, + resume_download=resume_download, + user_agent=user_agent, + local_files_only=local_files_only, + ) + elif os.path.exists(url_or_filename): + # File, and it exists. + output_path = url_or_filename + elif urlparse(url_or_filename).scheme == "": + # File, but it doesn't exist. + raise EnvironmentError("file {} not found".format(url_or_filename)) + else: + # Something unknown + raise ValueError("unable to parse {} as a URL or as a local path".format(url_or_filename)) + + if extract_compressed_file: + if not is_zipfile(output_path) and not tarfile.is_tarfile(output_path): + return output_path + + # Path where we extract compressed archives + # We avoid '.' in dir name and add "-extracted" at the end: "./model.zip" => "./model-zip-extracted/" + output_dir, output_file = os.path.split(output_path) + output_extract_dir_name = output_file.replace(".", "-") + "-extracted" + output_path_extracted = os.path.join(output_dir, output_extract_dir_name) + + if os.path.isdir(output_path_extracted) and os.listdir(output_path_extracted) and not force_extract: + return output_path_extracted + + # Prevent parallel extractions + lock_path = output_path + ".lock" + with FileLock(lock_path): + shutil.rmtree(output_path_extracted, ignore_errors=True) + os.makedirs(output_path_extracted) + if is_zipfile(output_path): + with ZipFile(output_path, "r") as zip_file: + zip_file.extractall(output_path_extracted) + zip_file.close() + elif tarfile.is_tarfile(output_path): + tar_file = tarfile.open(output_path) + tar_file.extractall(output_path_extracted) + tar_file.close() + else: + raise EnvironmentError("Archive format of {} could not be identified".format(output_path)) + + return output_path_extracted + + return output_path + + +def http_get(url, temp_file, proxies=None, resume_size=0, user_agent: Union[Dict, str, None] = None): + ua = "transformers/{}; python/{}".format(__version__, sys.version.split()[0]) + if is_torch_available(): + ua += "; torch/{}".format(torch.__version__) + if is_tf_available(): + ua += "; tensorflow/{}".format(tf.__version__) + if isinstance(user_agent, dict): + ua += "; " + "; ".join("{}/{}".format(k, v) for k, v in user_agent.items()) + elif isinstance(user_agent, str): + ua += "; " + user_agent + headers = {"user-agent": ua} + if resume_size > 0: + headers["Range"] = "bytes=%d-" % (resume_size,) + response = requests.get(url, stream=True, proxies=proxies, headers=headers) + if response.status_code == 416: # Range not satisfiable + return + content_length = response.headers.get("Content-Length") + total = resume_size + int(content_length) if content_length is not None else None + progress = tqdm( + unit="B", + unit_scale=True, + total=total, + initial=resume_size, + desc="Downloading", + disable=bool(logger.getEffectiveLevel() == logging.NOTSET), + ) + for chunk in response.iter_content(chunk_size=1024): + if chunk: # filter out keep-alive new chunks + progress.update(len(chunk)) + temp_file.write(chunk) + progress.close() + + +def get_from_cache( + url, + cache_dir=None, + force_download=False, + proxies=None, + etag_timeout=10, + resume_download=False, + user_agent: Union[Dict, str, None] = None, + local_files_only=False, +) -> Optional[str]: + """ + Given a URL, look for the corresponding file in the local cache. + If it's not there, download it. Then return the path to the cached file. + + Return: + None in case of non-recoverable file (non-existent or inaccessible url + no cache on disk). + Local path (string) otherwise + """ + if cache_dir is None: + cache_dir = TRANSFORMERS_CACHE + if isinstance(cache_dir, Path): + cache_dir = str(cache_dir) + + os.makedirs(cache_dir, exist_ok=True) + + etag = None + if not local_files_only: + try: + response = requests.head(url, allow_redirects=True, proxies=proxies, timeout=etag_timeout) + if response.status_code == 200: + etag = response.headers.get("ETag") + except (EnvironmentError, requests.exceptions.Timeout): + # etag is already None + pass + + filename = url_to_filename(url, etag) + + # get cache path to put the file + cache_path = os.path.join(cache_dir, filename) + + # etag is None = we don't have a connection, or url doesn't exist, or is otherwise inaccessible. + # try to get the last downloaded one + if etag is None: + if os.path.exists(cache_path): + return cache_path + else: + matching_files = [ + file + for file in fnmatch.filter(os.listdir(cache_dir), filename + ".*") + if not file.endswith(".json") and not file.endswith(".lock") + ] + if len(matching_files) > 0: + return os.path.join(cache_dir, matching_files[-1]) + else: + # If files cannot be found and local_files_only=True, + # the models might've been found if local_files_only=False + # Notify the user about that + if local_files_only: + raise ValueError( + "Cannot find the requested files in the cached path and outgoing traffic has been" + " disabled. To enable model look-ups and downloads online, set 'local_files_only'" + " to False." + ) + return None + + # From now on, etag is not None. + if os.path.exists(cache_path) and not force_download: + return cache_path + + # Prevent parallel downloads of the same file with a lock. + lock_path = cache_path + ".lock" + with FileLock(lock_path): + + # If the download just completed while the lock was activated. + if os.path.exists(cache_path) and not force_download: + # Even if returning early like here, the lock will be released. + return cache_path + + if resume_download: + incomplete_path = cache_path + ".incomplete" + + @contextmanager + def _resumable_file_manager(): + with open(incomplete_path, "a+b") as f: + yield f + + temp_file_manager = _resumable_file_manager + if os.path.exists(incomplete_path): + resume_size = os.stat(incomplete_path).st_size + else: + resume_size = 0 + else: + temp_file_manager = partial(tempfile.NamedTemporaryFile, dir=cache_dir, delete=False) + resume_size = 0 + + # Download to temporary file, then copy to cache dir once finished. + # Otherwise you get corrupt cache entries if the download gets interrupted. + with temp_file_manager() as temp_file: + logger.info("%s not found in cache or force_download set to True, downloading to %s", url, temp_file.name) + + http_get(url, temp_file, proxies=proxies, resume_size=resume_size, user_agent=user_agent) + + logger.info("storing %s in cache at %s", url, cache_path) + os.replace(temp_file.name, cache_path) + + logger.info("creating metadata file for %s", cache_path) + meta = {"url": url, "etag": etag} + meta_path = cache_path + ".json" + with open(meta_path, "w") as meta_file: + json.dump(meta, meta_file) + + return cache_path + + +class cached_property(property): + """ + Descriptor that mimics @property but caches output in member variable. + + From tensorflow_datasets + + Built-in in functools from Python 3.8. + """ + + def __get__(self, obj, objtype=None): + # See docs.python.org/3/howto/descriptor.html#properties + if obj is None: + return self + if self.fget is None: + raise AttributeError("unreadable attribute") + attr = "__cached_" + self.fget.__name__ + cached = getattr(obj, attr, None) + if cached is None: + cached = self.fget(obj) + setattr(obj, attr, cached) + return cached + + +def torch_required(func): + # Chose a different decorator name than in tests so it's clear they are not the same. + @wraps(func) + def wrapper(*args, **kwargs): + if is_torch_available(): + return func(*args, **kwargs) + else: + raise ImportError(f"Method `{func.__name__}` requires PyTorch.") + + return wrapper + + +def tf_required(func): + # Chose a different decorator name than in tests so it's clear they are not the same. + @wraps(func) + def wrapper(*args, **kwargs): + if is_tf_available(): + return func(*args, **kwargs) + else: + raise ImportError(f"Method `{func.__name__}` requires TF.") + + return wrapper diff --git a/LAVT-RIS/bert/generation_utils.py b/LAVT-RIS/bert/generation_utils.py new file mode 100644 index 0000000000000000000000000000000000000000..3c49e15abf7bc822940112207f10e18e2e0230cc --- /dev/null +++ b/LAVT-RIS/bert/generation_utils.py @@ -0,0 +1,993 @@ +# coding=utf-8 +# Copyright 2018 The Google AI Language Team Authors, Facebook AI Research authors and The HuggingFace Inc. team. +# Copyright (c) 2018, NVIDIA CORPORATION. All rights reserved. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +import logging +from typing import Iterable, Optional, Tuple + +import torch +from torch import Tensor +from torch.nn import functional as F + + +logger = logging.getLogger(__name__) + + +class GenerationMixin: + """ + A class contraining all of the functions supporting generation, to be used as a mixin in PreTrainedModel. + """ + + def prepare_inputs_for_generation(self, input_ids, **kwargs): + return {"input_ids": input_ids} + + def adjust_logits_during_generation(self, logits, **kwargs): + return logits + + def _use_cache(self, outputs, use_cache): + """During generation, decide whether to pass the `past` variable to the next forward pass.""" + if len(outputs) <= 1 or use_cache is False: + return False + if hasattr(self.config, "mem_len") and self.config.mem_len == 0: + return False + return True + + def enforce_repetition_penalty_(self, lprobs, batch_size, num_beams, prev_output_tokens, repetition_penalty): + """repetition penalty (from CTRL paper https://arxiv.org/abs/1909.05858). """ + for i in range(batch_size * num_beams): + for previous_token in set(prev_output_tokens[i].tolist()): + # if score < 0 then repetition penalty has to multiplied to reduce the previous token probability + if lprobs[i, previous_token] < 0: + lprobs[i, previous_token] *= repetition_penalty + else: + lprobs[i, previous_token] /= repetition_penalty + + def postprocess_next_token_scores( + self, + scores, + input_ids, + no_repeat_ngram_size, + bad_words_ids, + cur_len, + min_length, + max_length, + eos_token_id, + repetition_penalty, + batch_size, + num_beams, + ): + # repetition penalty (from CTRL paper https://arxiv.org/abs/1909.05858) + if repetition_penalty != 1.0: + self.enforce_repetition_penalty_( + scores, batch_size, num_beams, input_ids, repetition_penalty, + ) + + # set eos token prob to zero if min_length is not reached + if eos_token_id is not None and cur_len < min_length: + scores[:, eos_token_id] = -float("inf") + + if no_repeat_ngram_size > 0: + # calculate a list of banned tokens to prevent repetitively generating the same ngrams + num_batch_hypotheses = batch_size * num_beams + # from fairseq: https://github.com/pytorch/fairseq/blob/a07cb6f40480928c9e0548b737aadd36ee66ac76/fairseq/sequence_generator.py#L345 + banned_batch_tokens = calc_banned_ngram_tokens( + input_ids, num_batch_hypotheses, no_repeat_ngram_size, cur_len + ) + for i, banned_tokens in enumerate(banned_batch_tokens): + scores[i, banned_tokens] = -float("inf") + + if bad_words_ids is not None: + # calculate a list of banned tokens according to bad words + banned_tokens = calc_banned_bad_words_ids(input_ids, bad_words_ids) + + for i, banned_tokens in enumerate(banned_tokens): + scores[i, banned_tokens] = -float("inf") + + return scores + + @torch.no_grad() + def generate( + self, + input_ids: Optional[torch.LongTensor] = None, + max_length: Optional[int] = None, + min_length: Optional[int] = None, + do_sample: Optional[bool] = None, + early_stopping: Optional[bool] = None, + num_beams: Optional[int] = None, + temperature: Optional[float] = None, + top_k: Optional[int] = None, + top_p: Optional[float] = None, + repetition_penalty: Optional[float] = None, + bad_words_ids: Optional[Iterable[int]] = None, + bos_token_id: Optional[int] = None, + pad_token_id: Optional[int] = None, + eos_token_id: Optional[int] = None, + length_penalty: Optional[float] = None, + no_repeat_ngram_size: Optional[int] = None, + num_return_sequences: Optional[int] = None, + attention_mask: Optional[torch.LongTensor] = None, + decoder_start_token_id: Optional[int] = None, + use_cache: Optional[bool] = None, + **model_specific_kwargs + ) -> torch.LongTensor: + r""" Generates sequences for models with a LM head. The method currently supports greedy decoding, beam-search decoding, sampling with temperature, sampling with top-k or nucleus sampling. + + Adapted in part from `Facebook's XLM beam search code`_. + + .. _`Facebook's XLM beam search code`: + https://github.com/facebookresearch/XLM/blob/9e6f6814d17be4fe5b15f2e6c43eb2b2d76daeb4/src/model/transformer.py#L529 + + + Parameters: + + input_ids: (`optional`) `torch.LongTensor` of shape `(batch_size, sequence_length)` + The sequence used as a prompt for the generation. If `None` the method initializes + it as an empty `torch.LongTensor` of shape `(1,)`. + + max_length: (`optional`) int + The max length of the sequence to be generated. Between `min_length` and infinity. Default to 20. + + min_length: (`optional`) int + The min length of the sequence to be generated. Between 0 and infinity. Default to 0. + + do_sample: (`optional`) bool + If set to `False` greedy decoding is used. Otherwise sampling is used. Defaults to `False` as defined in `configuration_utils.PretrainedConfig`. + + early_stopping: (`optional`) bool + if set to `True` beam search is stopped when at least `num_beams` sentences finished per batch. Defaults to `False` as defined in `configuration_utils.PretrainedConfig`. + + num_beams: (`optional`) int + Number of beams for beam search. Must be between 1 and infinity. 1 means no beam search. Default to 1. + + temperature: (`optional`) float + The value used to module the next token probabilities. Must be strictly positive. Default to 1.0. + + top_k: (`optional`) int + The number of highest probability vocabulary tokens to keep for top-k-filtering. Between 1 and infinity. Default to 50. + + top_p: (`optional`) float + The cumulative probability of parameter highest probability vocabulary tokens to keep for nucleus sampling. Must be between 0 and 1. Default to 1. + + repetition_penalty: (`optional`) float + The parameter for repetition penalty. Between 1.0 and infinity. 1.0 means no penalty. Default to 1.0. + + pad_token_id: (`optional`) int + Padding token. Default to specicic model pad_token_id or None if it does not exist. + + bos_token_id: (`optional`) int + BOS token. Defaults to `bos_token_id` as defined in the models config. + + eos_token_id: (`optional`) int + EOS token. Defaults to `eos_token_id` as defined in the models config. + + length_penalty: (`optional`) float + Exponential penalty to the length. Default to 1. + + no_repeat_ngram_size: (`optional`) int + If set to int > 0, all ngrams of size `no_repeat_ngram_size` can only occur once. + bad_words_ids: (`optional`) list of lists of int + `bad_words_ids` contains tokens that are not allowed to be generated. In order to get the tokens of the words that should not appear in the generated text, use `tokenizer.encode(bad_word, add_prefix_space=True)`. + + num_return_sequences: (`optional`) int + The number of independently computed returned sequences for each element in the batch. Default to 1. + + attention_mask (`optional`) obj: `torch.LongTensor` of same shape as `input_ids` + Mask to avoid performing attention on padding token indices. + Mask values selected in ``[0, 1]``: + ``1`` for tokens that are NOT MASKED, ``0`` for MASKED tokens. + Defaults to `None`. + + `What are attention masks? <../glossary.html#attention-mask>`__ + + decoder_start_token_id=None: (`optional`) int + If an encoder-decoder model starts decoding with a different token than BOS. + Defaults to `None` and is changed to `BOS` later. + + use_cache: (`optional`) bool + If `use_cache` is True, past key values are used to speed up decoding if applicable to model. Defaults to `True`. + + model_specific_kwargs: (`optional`) dict + Additional model specific kwargs will be forwarded to the `forward` function of the model. + + Return: + + output: `torch.LongTensor` of shape `(batch_size * num_return_sequences, sequence_length)` + sequence_length is either equal to max_length or shorter if all batches finished early due to the `eos_token_id` + + Examples:: + + tokenizer = AutoTokenizer.from_pretrained('distilgpt2') # Initialize tokenizer + model = AutoModelWithLMHead.from_pretrained('distilgpt2') # Download model and configuration from S3 and cache. + outputs = model.generate(max_length=40) # do greedy decoding + print('Generated: {}'.format(tokenizer.decode(outputs[0], skip_special_tokens=True))) + + tokenizer = AutoTokenizer.from_pretrained('openai-gpt') # Initialize tokenizer + model = AutoModelWithLMHead.from_pretrained('openai-gpt') # Download model and configuration from S3 and cache. + input_context = 'The dog' + input_ids = tokenizer.encode(input_context, return_tensors='pt') # encode input context + outputs = model.generate(input_ids=input_ids, num_beams=5, num_return_sequences=3, temperature=1.5) # generate 3 independent sequences using beam search decoding (5 beams) with sampling from initial context 'The dog' + for i in range(3): # 3 output sequences were generated + print('Generated {}: {}'.format(i, tokenizer.decode(outputs[i], skip_special_tokens=True))) + + tokenizer = AutoTokenizer.from_pretrained('distilgpt2') # Initialize tokenizer + model = AutoModelWithLMHead.from_pretrained('distilgpt2') # Download model and configuration from S3 and cache. + input_context = 'The dog' + input_ids = tokenizer.encode(input_context, return_tensors='pt') # encode input context + outputs = model.generate(input_ids=input_ids, max_length=40, temperature=0.7, num_return_sequences=3) # 3 generate sequences using by sampling + for i in range(3): # 3 output sequences were generated + print('Generated {}: {}'.format(i, tokenizer.decode(outputs[i], skip_special_tokens=True))) + + tokenizer = AutoTokenizer.from_pretrained('ctrl') # Initialize tokenizer + model = AutoModelWithLMHead.from_pretrained('ctrl') # Download model and configuration from S3 and cache. + input_context = 'Legal My neighbor is' # "Legal" is one of the control codes for ctrl + input_ids = tokenizer.encode(input_context, return_tensors='pt') # encode input context + outputs = model.generate(input_ids=input_ids, max_length=50, temperature=0.7, repetition_penalty=1.2) # generate sequences + print('Generated: {}'.format(tokenizer.decode(outputs[0], skip_special_tokens=True))) + + tokenizer = AutoTokenizer.from_pretrained('gpt2') # Initialize tokenizer + model = AutoModelWithLMHead.from_pretrained('gpt2') # Download model and configuration from S3 and cache. + input_context = 'My cute dog' # "Legal" is one of the control codes for ctrl + bad_words_ids = [tokenizer.encode(bad_word, add_prefix_space=True) for bad_word in ['idiot', 'stupid', 'shut up']] + input_ids = tokenizer.encode(input_context, return_tensors='pt') # encode input context + outputs = model.generate(input_ids=input_ids, max_length=100, do_sample=True, bad_words_ids=bad_words_ids) # generate sequences without allowing bad_words to be generated + """ + + # We cannot generate if the model does not have a LM head + if self.get_output_embeddings() is None: + raise AttributeError( + "You tried to generate sequences with a model that does not have a LM Head." + "Please use another model class (e.g. `OpenAIGPTLMHeadModel`, `XLNetLMHeadModel`, `GPT2LMHeadModel`, `CTRLLMHeadModel`, `T5WithLMHeadModel`, `TransfoXLLMHeadModel`, `XLMWithLMHeadModel`, `BartForConditionalGeneration` )" + ) + + max_length = max_length if max_length is not None else self.config.max_length + min_length = min_length if min_length is not None else self.config.min_length + do_sample = do_sample if do_sample is not None else self.config.do_sample + early_stopping = early_stopping if early_stopping is not None else self.config.early_stopping + use_cache = use_cache if use_cache is not None else self.config.use_cache + num_beams = num_beams if num_beams is not None else self.config.num_beams + temperature = temperature if temperature is not None else self.config.temperature + top_k = top_k if top_k is not None else self.config.top_k + top_p = top_p if top_p is not None else self.config.top_p + repetition_penalty = repetition_penalty if repetition_penalty is not None else self.config.repetition_penalty + bos_token_id = bos_token_id if bos_token_id is not None else self.config.bos_token_id + pad_token_id = pad_token_id if pad_token_id is not None else self.config.pad_token_id + eos_token_id = eos_token_id if eos_token_id is not None else self.config.eos_token_id + length_penalty = length_penalty if length_penalty is not None else self.config.length_penalty + no_repeat_ngram_size = ( + no_repeat_ngram_size if no_repeat_ngram_size is not None else self.config.no_repeat_ngram_size + ) + bad_words_ids = bad_words_ids if bad_words_ids is not None else self.config.bad_words_ids + num_return_sequences = ( + num_return_sequences if num_return_sequences is not None else self.config.num_return_sequences + ) + decoder_start_token_id = ( + decoder_start_token_id if decoder_start_token_id is not None else self.config.decoder_start_token_id + ) + + if input_ids is not None: + batch_size = input_ids.shape[0] # overriden by the input batch_size + else: + batch_size = 1 + + assert isinstance(max_length, int) and max_length > 0, "`max_length` should be a strictly positive integer." + assert isinstance(min_length, int) and min_length >= 0, "`min_length` should be a positive integer." + assert isinstance(do_sample, bool), "`do_sample` should be a boolean." + assert isinstance(early_stopping, bool), "`early_stopping` should be a boolean." + assert isinstance(use_cache, bool), "`use_cache` should be a boolean." + assert isinstance(num_beams, int) and num_beams > 0, "`num_beams` should be a strictly positive integer." + assert temperature > 0, "`temperature` should be strictly positive." + assert isinstance(top_k, int) and top_k >= 0, "`top_k` should be a positive integer." + assert 0 <= top_p <= 1, "`top_p` should be between 0 and 1." + assert repetition_penalty >= 1.0, "`repetition_penalty` should be >= 1." + assert input_ids is not None or ( + isinstance(bos_token_id, int) and bos_token_id >= 0 + ), "If input_ids is not defined, `bos_token_id` should be a positive integer." + assert pad_token_id is None or ( + isinstance(pad_token_id, int) and (pad_token_id >= 0) + ), "`pad_token_id` should be a positive integer." + assert (eos_token_id is None) or ( + isinstance(eos_token_id, int) and (eos_token_id >= 0) + ), "`eos_token_id` should be a positive integer." + assert length_penalty > 0, "`length_penalty` should be strictly positive." + assert ( + isinstance(no_repeat_ngram_size, int) and no_repeat_ngram_size >= 0 + ), "`no_repeat_ngram_size` should be a positive integer." + assert ( + isinstance(num_return_sequences, int) and num_return_sequences > 0 + ), "`num_return_sequences` should be a strictly positive integer." + assert ( + bad_words_ids is None or isinstance(bad_words_ids, list) and isinstance(bad_words_ids[0], list) + ), "`bad_words_ids` is either `None` or a list of lists of tokens that should not be generated" + + if input_ids is None: + assert isinstance(bos_token_id, int) and bos_token_id >= 0, ( + "you should either supply a context to complete as `input_ids` input " + "or a `bos_token_id` (integer >= 0) as a first token to start the generation." + ) + input_ids = torch.full( + (batch_size, 1), bos_token_id, dtype=torch.long, device=next(self.parameters()).device, + ) + else: + assert input_ids.dim() == 2, "Input prompt should be of shape (batch_size, sequence length)." + + # not allow to duplicate outputs when greedy decoding + if do_sample is False: + if num_beams == 1: + # no_beam_search greedy generation conditions + assert ( + num_return_sequences == 1 + ), "Greedy decoding will always produce the same output for num_beams == 1 and num_return_sequences > 1. Please set num_return_sequences = 1" + + else: + # beam_search greedy generation conditions + assert ( + num_beams >= num_return_sequences + ), "Greedy beam search decoding cannot return more sequences than it has beams. Please set num_beams >= num_return_sequences" + + # create attention mask if necessary + # TODO (PVP): this should later be handled by the forward fn() in each model in the future see PR 3140 + if (attention_mask is None) and (pad_token_id is not None) and (pad_token_id in input_ids): + attention_mask = input_ids.ne(pad_token_id).long() + elif attention_mask is None: + attention_mask = input_ids.new_ones(input_ids.shape) + + # set pad_token_id to eos_token_id if not set. Important that this is done after + # attention_mask is created + if pad_token_id is None and eos_token_id is not None: + logger.warning( + "Setting `pad_token_id` to {} (first `eos_token_id`) to generate sequence".format(eos_token_id) + ) + pad_token_id = eos_token_id + + # current position and vocab size + if hasattr(self.config, "vocab_size"): + vocab_size = self.config.vocab_size + elif ( + self.config.is_encoder_decoder + and hasattr(self.config, "decoder") + and hasattr(self.config.decoder, "vocab_size") + ): + vocab_size = self.config.decoder.vocab_size + + # set effective batch size and effective batch multiplier according to do_sample + if do_sample: + effective_batch_size = batch_size * num_return_sequences + effective_batch_mult = num_return_sequences + else: + effective_batch_size = batch_size + effective_batch_mult = 1 + + if self.config.is_encoder_decoder: + if decoder_start_token_id is None: + decoder_start_token_id = bos_token_id + + assert ( + decoder_start_token_id is not None + ), "decoder_start_token_id or bos_token_id has to be defined for encoder-decoder generation" + assert hasattr(self, "get_encoder"), "{} should have a 'get_encoder' function defined".format(self) + assert callable(self.get_encoder), "{} should be a method".format(self.get_encoder) + + # get encoder and store encoder outputs + encoder = self.get_encoder() + + encoder_outputs: tuple = encoder(input_ids, attention_mask=attention_mask) + + # Expand input ids if num_beams > 1 or num_return_sequences > 1 + if num_return_sequences > 1 or num_beams > 1: + input_ids_len = input_ids.shape[-1] + input_ids = input_ids.unsqueeze(1).expand(batch_size, effective_batch_mult * num_beams, input_ids_len) + attention_mask = attention_mask.unsqueeze(1).expand( + batch_size, effective_batch_mult * num_beams, input_ids_len + ) + + input_ids = input_ids.contiguous().view( + effective_batch_size * num_beams, input_ids_len + ) # shape: (batch_size * num_return_sequences * num_beams, cur_len) + attention_mask = attention_mask.contiguous().view( + effective_batch_size * num_beams, input_ids_len + ) # shape: (batch_size * num_return_sequences * num_beams, cur_len) + + if self.config.is_encoder_decoder: + # create empty decoder_input_ids + input_ids = torch.full( + (effective_batch_size * num_beams, 1), + decoder_start_token_id, + dtype=torch.long, + device=next(self.parameters()).device, + ) + cur_len = 1 + + assert ( + batch_size == encoder_outputs[0].shape[0] + ), f"expected encoder_outputs[0] to have 1st dimension bs={batch_size}, got {encoder_outputs[0].shape[0]} " + + # expand batch_idx to assign correct encoder output for expanded input_ids (due to num_beams > 1 and num_return_sequences > 1) + expanded_batch_idxs = ( + torch.arange(batch_size) + .view(-1, 1) + .repeat(1, num_beams * effective_batch_mult) + .view(-1) + .to(input_ids.device) + ) + # expand encoder_outputs + encoder_outputs = (encoder_outputs[0].index_select(0, expanded_batch_idxs), *encoder_outputs[1:]) + + else: + encoder_outputs = None + cur_len = input_ids.shape[-1] + + assert ( + cur_len < max_length + ), f"The context has {cur_len} number of tokens, but `max_length` is only {max_length}. Please make sure that `max_length` is bigger than the number of tokens, by setting either `generate(max_length=...,...)` or `config.max_length = ...`" + + if num_beams > 1: + output = self._generate_beam_search( + input_ids, + cur_len=cur_len, + max_length=max_length, + min_length=min_length, + do_sample=do_sample, + early_stopping=early_stopping, + temperature=temperature, + top_k=top_k, + top_p=top_p, + repetition_penalty=repetition_penalty, + no_repeat_ngram_size=no_repeat_ngram_size, + bad_words_ids=bad_words_ids, + pad_token_id=pad_token_id, + eos_token_id=eos_token_id, + batch_size=effective_batch_size, + num_return_sequences=num_return_sequences, + length_penalty=length_penalty, + num_beams=num_beams, + vocab_size=vocab_size, + encoder_outputs=encoder_outputs, + attention_mask=attention_mask, + use_cache=use_cache, + model_specific_kwargs=model_specific_kwargs, + ) + else: + output = self._generate_no_beam_search( + input_ids, + cur_len=cur_len, + max_length=max_length, + min_length=min_length, + do_sample=do_sample, + temperature=temperature, + top_k=top_k, + top_p=top_p, + repetition_penalty=repetition_penalty, + no_repeat_ngram_size=no_repeat_ngram_size, + bad_words_ids=bad_words_ids, + pad_token_id=pad_token_id, + eos_token_id=eos_token_id, + batch_size=effective_batch_size, + encoder_outputs=encoder_outputs, + attention_mask=attention_mask, + use_cache=use_cache, + model_specific_kwargs=model_specific_kwargs, + ) + + return output + + def _generate_no_beam_search( + self, + input_ids, + cur_len, + max_length, + min_length, + do_sample, + temperature, + top_k, + top_p, + repetition_penalty, + no_repeat_ngram_size, + bad_words_ids, + pad_token_id, + eos_token_id, + batch_size, + encoder_outputs, + attention_mask, + use_cache, + model_specific_kwargs, + ): + """ Generate sequences for each example without beam search (num_beams == 1). + All returned sequence are generated independantly. + """ + # length of generated sentences / unfinished sentences + unfinished_sents = input_ids.new(batch_size).fill_(1) + sent_lengths = input_ids.new(batch_size).fill_(max_length) + + past = (encoder_outputs, None) if encoder_outputs is not None else None + + while cur_len < max_length: + model_inputs = self.prepare_inputs_for_generation( + input_ids, past=past, attention_mask=attention_mask, use_cache=use_cache, **model_specific_kwargs + ) + + outputs = self(**model_inputs) + next_token_logits = outputs[0][:, -1, :] + + scores = self.postprocess_next_token_scores( + scores=next_token_logits, + input_ids=input_ids, + no_repeat_ngram_size=no_repeat_ngram_size, + bad_words_ids=bad_words_ids, + cur_len=cur_len, + min_length=min_length, + max_length=max_length, + eos_token_id=eos_token_id, + repetition_penalty=repetition_penalty, + batch_size=batch_size, + num_beams=1, + ) + + # if model has past, then set the past variable to speed up decoding + if self._use_cache(outputs, use_cache): + past = outputs[1] + + if do_sample: + # Temperature (higher temperature => more likely to sample low probability tokens) + if temperature != 1.0: + scores = scores / temperature + # Top-p/top-k filtering + next_token_logscores = top_k_top_p_filtering(scores, top_k=top_k, top_p=top_p) + # Sample + probs = F.softmax(next_token_logscores, dim=-1) + next_token = torch.multinomial(probs, num_samples=1).squeeze(1) + else: + # Greedy decoding + next_token = torch.argmax(next_token_logits, dim=-1) + + # update generations and finished sentences + if eos_token_id is not None: + # pad finished sentences if eos_token_id exist + tokens_to_add = next_token * unfinished_sents + (pad_token_id) * (1 - unfinished_sents) + else: + tokens_to_add = next_token + + # add token and increase length by one + input_ids = torch.cat([input_ids, tokens_to_add.unsqueeze(-1)], dim=-1) + cur_len = cur_len + 1 + + if eos_token_id is not None: + eos_in_sents = tokens_to_add == eos_token_id + # if sentence is unfinished and the token to add is eos, sent_lengths is filled with current length + is_sents_unfinished_and_token_to_add_is_eos = unfinished_sents.mul(eos_in_sents.long()).bool() + sent_lengths.masked_fill_(is_sents_unfinished_and_token_to_add_is_eos, cur_len) + # unfinished_sents is set to zero if eos in sentence + unfinished_sents.mul_((~eos_in_sents).long()) + + # stop when there is a in each sentence, or if we exceed the maximul length + if unfinished_sents.max() == 0: + break + + # extend attention_mask for new generated input if only decoder + if self.config.is_encoder_decoder is False: + attention_mask = torch.cat( + [attention_mask, attention_mask.new_ones((attention_mask.shape[0], 1))], dim=-1 + ) + + return input_ids + + def _generate_beam_search( + self, + input_ids, + cur_len, + max_length, + min_length, + do_sample, + early_stopping, + temperature, + top_k, + top_p, + repetition_penalty, + no_repeat_ngram_size, + bad_words_ids, + pad_token_id, + eos_token_id, + batch_size, + num_return_sequences, + length_penalty, + num_beams, + vocab_size, + encoder_outputs, + attention_mask, + use_cache, + model_specific_kwargs, + ): + """ Generate sequences for each example with beam search. + """ + + # generated hypotheses + generated_hyps = [ + BeamHypotheses(num_beams, max_length, length_penalty, early_stopping=early_stopping) + for _ in range(batch_size) + ] + + # scores for each sentence in the beam + beam_scores = torch.zeros((batch_size, num_beams), dtype=torch.float, device=input_ids.device) + + # for greedy decoding it is made sure that only tokens of the first beam are considered to avoid sampling the exact same tokens three times + if do_sample is False: + beam_scores[:, 1:] = -1e9 + beam_scores = beam_scores.view(-1) # shape (batch_size * num_beams,) + + # cache compute states + past = (encoder_outputs, None) if encoder_outputs is not None else None + + # done sentences + done = [False for _ in range(batch_size)] + + while cur_len < max_length: + model_inputs = self.prepare_inputs_for_generation( + input_ids, past=past, attention_mask=attention_mask, use_cache=use_cache, **model_specific_kwargs + ) + outputs = self(**model_inputs) # (batch_size * num_beams, cur_len, vocab_size) + next_token_logits = outputs[0][:, -1, :] # (batch_size * num_beams, vocab_size) + + # if model has past, then set the past variable to speed up decoding + if self._use_cache(outputs, use_cache): + past = outputs[1] + if self.config.is_encoder_decoder and do_sample is False: + # TODO (PVP) still a bit hacky here - there might be a better solution + next_token_logits = self.adjust_logits_during_generation( + next_token_logits, cur_len=cur_len, max_length=max_length + ) + + scores = F.log_softmax(next_token_logits, dim=-1) # (batch_size * num_beams, vocab_size) + + scores = self.postprocess_next_token_scores( + scores=scores, + input_ids=input_ids, + no_repeat_ngram_size=no_repeat_ngram_size, + bad_words_ids=bad_words_ids, + cur_len=cur_len, + min_length=min_length, + max_length=max_length, + eos_token_id=eos_token_id, + repetition_penalty=repetition_penalty, + batch_size=batch_size, + num_beams=num_beams, + ) + + assert scores.shape == (batch_size * num_beams, vocab_size), "Shapes of scores: {} != {}".format( + scores.shape, (batch_size * num_beams, vocab_size) + ) + + if do_sample: + _scores = scores + beam_scores[:, None].expand_as(scores) # (batch_size * num_beams, vocab_size) + # Temperature + if temperature != 1.0: + _scores = _scores / temperature + # Top-p/top-k filtering + _scores = top_k_top_p_filtering( + _scores, top_k=top_k, top_p=top_p, min_tokens_to_keep=2 + ) # (batch_size * num_beams, vocab_size) + # re-organize to group the beam together to sample from all beam_idxs + _scores = _scores.contiguous().view( + batch_size, num_beams * vocab_size + ) # (batch_size, num_beams * vocab_size) + + # Sample 2 next tokens for each beam (so we have some spare tokens and match output of greedy beam search) + probs = F.softmax(_scores, dim=-1) + next_tokens = torch.multinomial(probs, num_samples=2 * num_beams) # (batch_size, num_beams * 2) + # Compute next scores + next_scores = torch.gather(_scores, -1, next_tokens) # (batch_size, num_beams * 2) + # sort the sampled vector to make sure that the first num_beams samples are the best + next_scores, next_scores_indices = torch.sort(next_scores, descending=True, dim=1) + next_tokens = torch.gather(next_tokens, -1, next_scores_indices) # (batch_size, num_beams * 2) + + else: + next_scores = scores + beam_scores[:, None].expand_as(scores) # (batch_size * num_beams, vocab_size) + + # re-organize to group the beam together (we are keeping top hypothesis accross beams) + next_scores = next_scores.view( + batch_size, num_beams * vocab_size + ) # (batch_size, num_beams * vocab_size) + + next_scores, next_tokens = torch.topk(next_scores, 2 * num_beams, dim=1, largest=True, sorted=True) + + assert next_scores.size() == next_tokens.size() == (batch_size, 2 * num_beams) + + # next batch beam content + next_batch_beam = [] + + # for each sentence + for batch_idx in range(batch_size): + + # if we are done with this sentence, add a pad token + if done[batch_idx]: + assert ( + len(generated_hyps[batch_idx]) >= num_beams + ), "Batch can only be done if at least {} beams have been generated".format(num_beams) + assert ( + eos_token_id is not None and pad_token_id is not None + ), "generated beams >= num_beams -> eos_token_id and pad_token have to be defined" + next_batch_beam.extend([(0, pad_token_id, 0)] * num_beams) # pad the batch + continue + + # next sentence beam content, this will get added to next_batch_beam + next_sent_beam = [] + + # next tokens for this sentence + for beam_token_rank, (beam_token_id, beam_token_score) in enumerate( + zip(next_tokens[batch_idx], next_scores[batch_idx]) + ): + # get beam and token IDs + beam_id = beam_token_id // vocab_size + token_id = beam_token_id % vocab_size + + effective_beam_id = batch_idx * num_beams + beam_id + # add to generated hypotheses if end of sentence + if (eos_token_id is not None) and (token_id.item() == eos_token_id): + # if beam_token does not belong to top num_beams tokens, it should not be added + is_beam_token_worse_than_top_num_beams = beam_token_rank >= num_beams + if is_beam_token_worse_than_top_num_beams: + continue + generated_hyps[batch_idx].add( + input_ids[effective_beam_id].clone(), beam_token_score.item(), + ) + else: + # add next predicted token since it is not eos_token + next_sent_beam.append((beam_token_score, token_id, effective_beam_id)) + + # once the beam for next step is full, don't add more tokens to it. + if len(next_sent_beam) == num_beams: + break + + # Check if we are done so that we can save a pad step if all(done) + done[batch_idx] = done[batch_idx] or generated_hyps[batch_idx].is_done( + next_scores[batch_idx].max().item(), cur_len + ) + + # update next beam content + assert len(next_sent_beam) == num_beams, "Beam should always be full" + next_batch_beam.extend(next_sent_beam) + assert len(next_batch_beam) == num_beams * (batch_idx + 1), "We should have added num_beams each step" + + # stop when we are done with each sentence + if all(done): + break + + # sanity check / prepare next batch + assert len(next_batch_beam) == batch_size * num_beams + beam_scores = beam_scores.new([x[0] for x in next_batch_beam]) + beam_tokens = input_ids.new([x[1] for x in next_batch_beam]) + beam_idx = input_ids.new([x[2] for x in next_batch_beam]) + + # re-order batch and update current length + input_ids = input_ids[beam_idx, :] + input_ids = torch.cat([input_ids, beam_tokens.unsqueeze(1)], dim=-1) + cur_len = cur_len + 1 + + # re-order internal states + if past is not None: + past = self._reorder_cache(past, beam_idx) + + # extend attention_mask for new generated input if only decoder + if self.config.is_encoder_decoder is False: + attention_mask = torch.cat( + [attention_mask, attention_mask.new_ones((attention_mask.shape[0], 1))], dim=-1 + ) + + # finalize all open beam hypotheses and add to generated hypotheses + for batch_idx in range(batch_size): + if done[batch_idx]: + continue + + # test that beam scores match previously calculated scores if not eos and batch_idx not done + if eos_token_id is not None and all( + (token_id % vocab_size).item() != eos_token_id for token_id in next_tokens[batch_idx] + ): + assert torch.all( + next_scores[batch_idx, :num_beams] == beam_scores.view(batch_size, num_beams)[batch_idx] + ), "If batch_idx is not done, final next scores: {} have to equal to accumulated beam_scores: {}".format( + next_scores[:, :num_beams][batch_idx], beam_scores.view(batch_size, num_beams)[batch_idx], + ) + + # need to add best num_beams hypotheses to generated hyps + for beam_id in range(num_beams): + effective_beam_id = batch_idx * num_beams + beam_id + final_score = beam_scores[effective_beam_id].item() + final_tokens = input_ids[effective_beam_id] + generated_hyps[batch_idx].add(final_tokens, final_score) + + # depending on whether greedy generation is wanted or not define different output_batch_size and output_num_return_sequences_per_batch + output_batch_size = batch_size if do_sample else batch_size * num_return_sequences + output_num_return_sequences_per_batch = 1 if do_sample else num_return_sequences + + # select the best hypotheses + sent_lengths = input_ids.new(output_batch_size) + best = [] + + # retrieve best hypotheses + for i, hypotheses in enumerate(generated_hyps): + sorted_hyps = sorted(hypotheses.beams, key=lambda x: x[0]) + for j in range(output_num_return_sequences_per_batch): + effective_batch_idx = output_num_return_sequences_per_batch * i + j + best_hyp = sorted_hyps.pop()[1] + sent_lengths[effective_batch_idx] = len(best_hyp) + best.append(best_hyp) + + # shorter batches are padded + if sent_lengths.min().item() != sent_lengths.max().item(): + assert pad_token_id is not None, "`Pad_token_id` has to be defined" + sent_max_len = min(sent_lengths.max().item() + 1, max_length) + decoded = input_ids.new(output_batch_size, sent_max_len).fill_(pad_token_id) + + # fill with hypothesis and eos_token_id if necessary + for i, hypo in enumerate(best): + decoded[i, : sent_lengths[i]] = hypo + if sent_lengths[i] < max_length: + decoded[i, sent_lengths[i]] = eos_token_id + else: + # none of the hypotheses have an eos_token + assert (len(hypo) == max_length for hypo in best) + decoded = torch.stack(best).type(torch.long).to(next(self.parameters()).device) + + return decoded + + @staticmethod + def _reorder_cache(past: Tuple, beam_idx: Tensor) -> Tuple[Tensor]: + return tuple(layer_past.index_select(1, beam_idx) for layer_past in past) + + +def calc_banned_ngram_tokens(prev_input_ids: Tensor, num_hypos: int, no_repeat_ngram_size: int, cur_len: int) -> None: + """Copied from fairseq for no_repeat_ngram in beam_search""" + if cur_len + 1 < no_repeat_ngram_size: + # return no banned tokens if we haven't generated no_repeat_ngram_size tokens yet + return [[] for _ in range(num_hypos)] + generated_ngrams = [{} for _ in range(num_hypos)] + for idx in range(num_hypos): + gen_tokens = prev_input_ids[idx].tolist() + generated_ngram = generated_ngrams[idx] + for ngram in zip(*[gen_tokens[i:] for i in range(no_repeat_ngram_size)]): + prev_ngram_tuple = tuple(ngram[:-1]) + generated_ngram[prev_ngram_tuple] = generated_ngram.get(prev_ngram_tuple, []) + [ngram[-1]] + + def _get_generated_ngrams(hypo_idx): + # Before decoding the next token, prevent decoding of ngrams that have already appeared + start_idx = cur_len + 1 - no_repeat_ngram_size + ngram_idx = tuple(prev_input_ids[hypo_idx, start_idx:cur_len].tolist()) + return generated_ngrams[hypo_idx].get(ngram_idx, []) + + banned_tokens = [_get_generated_ngrams(hypo_idx) for hypo_idx in range(num_hypos)] + return banned_tokens + + +def calc_banned_bad_words_ids(prev_input_ids: Iterable[int], bad_words_ids: Iterable[int]) -> Iterable[int]: + banned_tokens = [] + + def _tokens_match(prev_tokens, tokens): + if len(tokens) == 0: + # if bad word tokens is just one token always ban it + return True + if len(tokens) > len(prev_input_ids): + # if bad word tokens are longer then prev input_ids they can't be equal + return False + + if prev_tokens[-len(tokens) :] == tokens: + # if tokens match + return True + else: + return False + + for prev_input_ids_slice in prev_input_ids: + banned_tokens_slice = [] + + for banned_token_seq in bad_words_ids: + assert len(banned_token_seq) > 0, "Banned words token sequences {} cannot have an empty list".format( + bad_words_ids + ) + + if _tokens_match(prev_input_ids_slice.tolist(), banned_token_seq[:-1]) is False: + # if tokens do not match continue + continue + + banned_tokens_slice.append(banned_token_seq[-1]) + + banned_tokens.append(banned_tokens_slice) + + return banned_tokens + + +def top_k_top_p_filtering( + logits: Tensor, + top_k: int = 0, + top_p: float = 1.0, + filter_value: float = -float("Inf"), + min_tokens_to_keep: int = 1, +) -> Tensor: + """ Filter a distribution of logits using top-k and/or nucleus (top-p) filtering + Args: + logits: logits distribution shape (batch size, vocabulary size) + if top_k > 0: keep only top k tokens with highest probability (top-k filtering). + if top_p < 1.0: keep the top tokens with cumulative probability >= top_p (nucleus filtering). + Nucleus filtering is described in Holtzman et al. (http://arxiv.org/abs/1904.09751) + Make sure we keep at least min_tokens_to_keep per batch example in the output + From: https://gist.github.com/thomwolf/1a5a29f6962089e871b94cbd09daf317 + """ + if top_k > 0: + top_k = min(max(top_k, min_tokens_to_keep), logits.size(-1)) # Safety check + # Remove all tokens with a probability less than the last token of the top-k + indices_to_remove = logits < torch.topk(logits, top_k)[0][..., -1, None] + logits[indices_to_remove] = filter_value + + if top_p < 1.0: + sorted_logits, sorted_indices = torch.sort(logits, descending=True) + cumulative_probs = torch.cumsum(F.softmax(sorted_logits, dim=-1), dim=-1) + + # Remove tokens with cumulative probability above the threshold (token with 0 are kept) + sorted_indices_to_remove = cumulative_probs > top_p + if min_tokens_to_keep > 1: + # Keep at least min_tokens_to_keep (set to min_tokens_to_keep-1 because we add the first one below) + sorted_indices_to_remove[..., :min_tokens_to_keep] = 0 + # Shift the indices to the right to keep also the first token above the threshold + sorted_indices_to_remove[..., 1:] = sorted_indices_to_remove[..., :-1].clone() + sorted_indices_to_remove[..., 0] = 0 + + # scatter sorted tensors to original indexing + indices_to_remove = sorted_indices_to_remove.scatter(1, sorted_indices, sorted_indices_to_remove) + logits[indices_to_remove] = filter_value + return logits + + +class BeamHypotheses(object): + def __init__(self, num_beams, max_length, length_penalty, early_stopping): + """ + Initialize n-best list of hypotheses. + """ + self.max_length = max_length - 1 # ignoring bos_token + self.length_penalty = length_penalty + self.early_stopping = early_stopping + self.num_beams = num_beams + self.beams = [] + self.worst_score = 1e9 + + def __len__(self): + """ + Number of hypotheses in the list. + """ + return len(self.beams) + + def add(self, hyp, sum_logprobs): + """ + Add a new hypothesis to the list. + """ + score = sum_logprobs / len(hyp) ** self.length_penalty + if len(self) < self.num_beams or score > self.worst_score: + self.beams.append((score, hyp)) + if len(self) > self.num_beams: + sorted_scores = sorted([(s, idx) for idx, (s, _) in enumerate(self.beams)]) + del self.beams[sorted_scores[0][1]] + self.worst_score = sorted_scores[1][0] + else: + self.worst_score = min(score, self.worst_score) + + def is_done(self, best_sum_logprobs, cur_len): + """ + If there are enough hypotheses and that none of the hypotheses being generated + can become better than the worst one in the heap, then we are done with this sentence. + """ + + if len(self) < self.num_beams: + return False + elif self.early_stopping: + return True + else: + cur_score = best_sum_logprobs / cur_len ** self.length_penalty + ret = self.worst_score >= cur_score + return ret diff --git a/LAVT-RIS/bert/modeling_bert.py b/LAVT-RIS/bert/modeling_bert.py new file mode 100644 index 0000000000000000000000000000000000000000..e796878aa2e6e39d6e65b0941396bcedca396a46 --- /dev/null +++ b/LAVT-RIS/bert/modeling_bert.py @@ -0,0 +1,1569 @@ +# coding=utf-8 +# Copyright 2018 The Google AI Language Team Authors and The HuggingFace Inc. team. +# Copyright (c) 2018, NVIDIA CORPORATION. All rights reserved. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +"""PyTorch BERT model. """ + + +import logging +import math +import os +import warnings + +import torch +import torch.utils.checkpoint +from torch import nn +from torch.nn import CrossEntropyLoss, MSELoss + +from .activations import gelu, gelu_new, swish +from .configuration_bert import BertConfig +from .file_utils import add_code_sample_docstrings, add_start_docstrings, add_start_docstrings_to_callable +from .modeling_utils import PreTrainedModel, find_pruneable_heads_and_indices, prune_linear_layer + + +logger = logging.getLogger(__name__) + +_TOKENIZER_FOR_DOC = "BertTokenizer" + +BERT_PRETRAINED_MODEL_ARCHIVE_LIST = [ + "bert-base-uncased", + "bert-large-uncased", + "bert-base-cased", + "bert-large-cased", + "bert-base-multilingual-uncased", + "bert-base-multilingual-cased", + "bert-base-chinese", + "bert-base-german-cased", + "bert-large-uncased-whole-word-masking", + "bert-large-cased-whole-word-masking", + "bert-large-uncased-whole-word-masking-finetuned-squad", + "bert-large-cased-whole-word-masking-finetuned-squad", + "bert-base-cased-finetuned-mrpc", + "bert-base-german-dbmdz-cased", + "bert-base-german-dbmdz-uncased", + "cl-tohoku/bert-base-japanese", + "cl-tohoku/bert-base-japanese-whole-word-masking", + "cl-tohoku/bert-base-japanese-char", + "cl-tohoku/bert-base-japanese-char-whole-word-masking", + "TurkuNLP/bert-base-finnish-cased-v1", + "TurkuNLP/bert-base-finnish-uncased-v1", + "wietsedv/bert-base-dutch-cased", + # See all BERT models at https://huggingface.co/models?filter=bert +] + + +def load_tf_weights_in_bert(model, config, tf_checkpoint_path): + """ Load tf checkpoints in a pytorch model. + """ + try: + import re + import numpy as np + import tensorflow as tf + except ImportError: + logger.error( + "Loading a TensorFlow model in PyTorch, requires TensorFlow to be installed. Please see " + "https://www.tensorflow.org/install/ for installation instructions." + ) + raise + tf_path = os.path.abspath(tf_checkpoint_path) + logger.info("Converting TensorFlow checkpoint from {}".format(tf_path)) + # Load weights from TF model + init_vars = tf.train.list_variables(tf_path) + names = [] + arrays = [] + for name, shape in init_vars: + logger.info("Loading TF weight {} with shape {}".format(name, shape)) + array = tf.train.load_variable(tf_path, name) + names.append(name) + arrays.append(array) + + for name, array in zip(names, arrays): + name = name.split("/") + # adam_v and adam_m are variables used in AdamWeightDecayOptimizer to calculated m and v + # which are not required for using pretrained model + if any( + n in ["adam_v", "adam_m", "AdamWeightDecayOptimizer", "AdamWeightDecayOptimizer_1", "global_step"] + for n in name + ): + logger.info("Skipping {}".format("/".join(name))) + continue + pointer = model + for m_name in name: + if re.fullmatch(r"[A-Za-z]+_\d+", m_name): + scope_names = re.split(r"_(\d+)", m_name) + else: + scope_names = [m_name] + if scope_names[0] == "kernel" or scope_names[0] == "gamma": + pointer = getattr(pointer, "weight") + elif scope_names[0] == "output_bias" or scope_names[0] == "beta": + pointer = getattr(pointer, "bias") + elif scope_names[0] == "output_weights": + pointer = getattr(pointer, "weight") + elif scope_names[0] == "squad": + pointer = getattr(pointer, "classifier") + else: + try: + pointer = getattr(pointer, scope_names[0]) + except AttributeError: + logger.info("Skipping {}".format("/".join(name))) + continue + if len(scope_names) >= 2: + num = int(scope_names[1]) + pointer = pointer[num] + if m_name[-11:] == "_embeddings": + pointer = getattr(pointer, "weight") + elif m_name == "kernel": + array = np.transpose(array) + try: + assert pointer.shape == array.shape + except AssertionError as e: + e.args += (pointer.shape, array.shape) + raise + logger.info("Initialize PyTorch weight {}".format(name)) + pointer.data = torch.from_numpy(array) + return model + + +def mish(x): + return x * torch.tanh(nn.functional.softplus(x)) + + +ACT2FN = {"gelu": gelu, "relu": torch.nn.functional.relu, "swish": swish, "gelu_new": gelu_new, "mish": mish} + + +BertLayerNorm = torch.nn.LayerNorm + + +class BertEmbeddings(nn.Module): + """Construct the embeddings from word, position and token_type embeddings. + """ + + def __init__(self, config): + super().__init__() + self.word_embeddings = nn.Embedding(config.vocab_size, config.hidden_size, padding_idx=config.pad_token_id) + self.position_embeddings = nn.Embedding(config.max_position_embeddings, config.hidden_size) + self.token_type_embeddings = nn.Embedding(config.type_vocab_size, config.hidden_size) + + # self.LayerNorm is not snake-cased to stick with TensorFlow model variable name and be able to load + # any TensorFlow checkpoint file + self.LayerNorm = BertLayerNorm(config.hidden_size, eps=config.layer_norm_eps) + self.dropout = nn.Dropout(config.hidden_dropout_prob) + + def forward(self, input_ids=None, token_type_ids=None, position_ids=None, inputs_embeds=None): + if input_ids is not None: + input_shape = input_ids.size() + else: + input_shape = inputs_embeds.size()[:-1] + + seq_length = input_shape[1] + device = input_ids.device if input_ids is not None else inputs_embeds.device + if position_ids is None: + position_ids = torch.arange(seq_length, dtype=torch.long, device=device) + position_ids = position_ids.unsqueeze(0).expand(input_shape) + if token_type_ids is None: + token_type_ids = torch.zeros(input_shape, dtype=torch.long, device=device) + + if inputs_embeds is None: + inputs_embeds = self.word_embeddings(input_ids) + position_embeddings = self.position_embeddings(position_ids) + token_type_embeddings = self.token_type_embeddings(token_type_ids) + + embeddings = inputs_embeds + position_embeddings + token_type_embeddings + embeddings = self.LayerNorm(embeddings) + embeddings = self.dropout(embeddings) + return embeddings + + +class BertSelfAttention(nn.Module): + def __init__(self, config): + super().__init__() + if config.hidden_size % config.num_attention_heads != 0 and not hasattr(config, "embedding_size"): + raise ValueError( + "The hidden size (%d) is not a multiple of the number of attention " + "heads (%d)" % (config.hidden_size, config.num_attention_heads) + ) + + self.num_attention_heads = config.num_attention_heads + self.attention_head_size = int(config.hidden_size / config.num_attention_heads) + self.all_head_size = self.num_attention_heads * self.attention_head_size + + self.query = nn.Linear(config.hidden_size, self.all_head_size) + self.key = nn.Linear(config.hidden_size, self.all_head_size) + self.value = nn.Linear(config.hidden_size, self.all_head_size) + + self.dropout = nn.Dropout(config.attention_probs_dropout_prob) + + def transpose_for_scores(self, x): + new_x_shape = x.size()[:-1] + (self.num_attention_heads, self.attention_head_size) + x = x.view(*new_x_shape) + return x.permute(0, 2, 1, 3) + + def forward( + self, + hidden_states, + attention_mask=None, + head_mask=None, + encoder_hidden_states=None, + encoder_attention_mask=None, + output_attentions=False, + ): + mixed_query_layer = self.query(hidden_states) + + # If this is instantiated as a cross-attention module, the keys + # and values come from an encoder; the attention mask needs to be + # such that the encoder's padding tokens are not attended to. + if encoder_hidden_states is not None: + mixed_key_layer = self.key(encoder_hidden_states) + mixed_value_layer = self.value(encoder_hidden_states) + attention_mask = encoder_attention_mask + else: + mixed_key_layer = self.key(hidden_states) + mixed_value_layer = self.value(hidden_states) + + query_layer = self.transpose_for_scores(mixed_query_layer) + key_layer = self.transpose_for_scores(mixed_key_layer) + value_layer = self.transpose_for_scores(mixed_value_layer) + + # Take the dot product between "query" and "key" to get the raw attention scores. + attention_scores = torch.matmul(query_layer, key_layer.transpose(-1, -2)) + attention_scores = attention_scores / math.sqrt(self.attention_head_size) + if attention_mask is not None: + # Apply the attention mask is (precomputed for all layers in BertModel forward() function) + attention_scores = attention_scores + attention_mask + + # Normalize the attention scores to probabilities. + attention_probs = nn.Softmax(dim=-1)(attention_scores) + + # This is actually dropping out entire tokens to attend to, which might + # seem a bit unusual, but is taken from the original Transformer paper. + attention_probs = self.dropout(attention_probs) + + # Mask heads if we want to + if head_mask is not None: + attention_probs = attention_probs * head_mask + + context_layer = torch.matmul(attention_probs, value_layer) + + context_layer = context_layer.permute(0, 2, 1, 3).contiguous() + new_context_layer_shape = context_layer.size()[:-2] + (self.all_head_size,) + context_layer = context_layer.view(*new_context_layer_shape) + + outputs = (context_layer, attention_probs) if output_attentions else (context_layer,) + return outputs + + +class BertSelfOutput(nn.Module): + def __init__(self, config): + super().__init__() + self.dense = nn.Linear(config.hidden_size, config.hidden_size) + self.LayerNorm = BertLayerNorm(config.hidden_size, eps=config.layer_norm_eps) + self.dropout = nn.Dropout(config.hidden_dropout_prob) + + def forward(self, hidden_states, input_tensor): + hidden_states = self.dense(hidden_states) + hidden_states = self.dropout(hidden_states) + hidden_states = self.LayerNorm(hidden_states + input_tensor) + return hidden_states + + +class BertAttention(nn.Module): + def __init__(self, config): + super().__init__() + self.self = BertSelfAttention(config) + self.output = BertSelfOutput(config) + self.pruned_heads = set() + + def prune_heads(self, heads): + if len(heads) == 0: + return + heads, index = find_pruneable_heads_and_indices( + heads, self.self.num_attention_heads, self.self.attention_head_size, self.pruned_heads + ) + + # Prune linear layers + self.self.query = prune_linear_layer(self.self.query, index) + self.self.key = prune_linear_layer(self.self.key, index) + self.self.value = prune_linear_layer(self.self.value, index) + self.output.dense = prune_linear_layer(self.output.dense, index, dim=1) + + # Update hyper params and store pruned heads + self.self.num_attention_heads = self.self.num_attention_heads - len(heads) + self.self.all_head_size = self.self.attention_head_size * self.self.num_attention_heads + self.pruned_heads = self.pruned_heads.union(heads) + + def forward( + self, + hidden_states, + attention_mask=None, + head_mask=None, + encoder_hidden_states=None, + encoder_attention_mask=None, + output_attentions=False, + ): + self_outputs = self.self( + hidden_states, attention_mask, head_mask, encoder_hidden_states, encoder_attention_mask, output_attentions, + ) + attention_output = self.output(self_outputs[0], hidden_states) + outputs = (attention_output,) + self_outputs[1:] # add attentions if we output them + return outputs + + +class BertIntermediate(nn.Module): + def __init__(self, config): + super().__init__() + self.dense = nn.Linear(config.hidden_size, config.intermediate_size) + if isinstance(config.hidden_act, str): + self.intermediate_act_fn = ACT2FN[config.hidden_act] + else: + self.intermediate_act_fn = config.hidden_act + + def forward(self, hidden_states): + hidden_states = self.dense(hidden_states) + hidden_states = self.intermediate_act_fn(hidden_states) + return hidden_states + + +class BertOutput(nn.Module): + def __init__(self, config): + super().__init__() + self.dense = nn.Linear(config.intermediate_size, config.hidden_size) + self.LayerNorm = BertLayerNorm(config.hidden_size, eps=config.layer_norm_eps) + self.dropout = nn.Dropout(config.hidden_dropout_prob) + + def forward(self, hidden_states, input_tensor): + hidden_states = self.dense(hidden_states) + hidden_states = self.dropout(hidden_states) + hidden_states = self.LayerNorm(hidden_states + input_tensor) + return hidden_states + + +class BertLayer(nn.Module): + def __init__(self, config): + super().__init__() + self.attention = BertAttention(config) + self.is_decoder = config.is_decoder + if self.is_decoder: + self.crossattention = BertAttention(config) + self.intermediate = BertIntermediate(config) + self.output = BertOutput(config) + + def forward( + self, + hidden_states, + attention_mask=None, + head_mask=None, + encoder_hidden_states=None, + encoder_attention_mask=None, + output_attentions=False, + ): + self_attention_outputs = self.attention( + hidden_states, attention_mask, head_mask, output_attentions=output_attentions, + ) + attention_output = self_attention_outputs[0] + outputs = self_attention_outputs[1:] # add self attentions if we output attention weights + + if self.is_decoder and encoder_hidden_states is not None: + cross_attention_outputs = self.crossattention( + attention_output, + attention_mask, + head_mask, + encoder_hidden_states, + encoder_attention_mask, + output_attentions, + ) + attention_output = cross_attention_outputs[0] + outputs = outputs + cross_attention_outputs[1:] # add cross attentions if we output attention weights + + intermediate_output = self.intermediate(attention_output) + layer_output = self.output(intermediate_output, attention_output) + outputs = (layer_output,) + outputs + return outputs + + +class BertEncoder(nn.Module): + def __init__(self, config): + super().__init__() + self.config = config + self.layer = nn.ModuleList([BertLayer(config) for _ in range(config.num_hidden_layers)]) + + def forward( + self, + hidden_states, + attention_mask=None, + head_mask=None, + encoder_hidden_states=None, + encoder_attention_mask=None, + output_attentions=False, + output_hidden_states=False, + ): + all_hidden_states = () + all_attentions = () + for i, layer_module in enumerate(self.layer): + if output_hidden_states: + all_hidden_states = all_hidden_states + (hidden_states,) + + if getattr(self.config, "gradient_checkpointing", False): + + def create_custom_forward(module): + def custom_forward(*inputs): + return module(*inputs, output_attentions) + + return custom_forward + + layer_outputs = torch.utils.checkpoint.checkpoint( + create_custom_forward(layer_module), + hidden_states, + attention_mask, + head_mask[i], + encoder_hidden_states, + encoder_attention_mask, + ) + else: + layer_outputs = layer_module( + hidden_states, + attention_mask, + head_mask[i], + encoder_hidden_states, + encoder_attention_mask, + output_attentions, + ) + hidden_states = layer_outputs[0] + + if output_attentions: + all_attentions = all_attentions + (layer_outputs[1],) + + # Add last layer + if output_hidden_states: + all_hidden_states = all_hidden_states + (hidden_states,) + + outputs = (hidden_states,) + if output_hidden_states: + outputs = outputs + (all_hidden_states,) + if output_attentions: + outputs = outputs + (all_attentions,) + return outputs # last-layer hidden state, (all hidden states), (all attentions) + + +class BertPooler(nn.Module): + def __init__(self, config): + super().__init__() + self.dense = nn.Linear(config.hidden_size, config.hidden_size) + self.activation = nn.Tanh() + + def forward(self, hidden_states): + # We "pool" the model by simply taking the hidden state corresponding + # to the first token. + first_token_tensor = hidden_states[:, 0] + pooled_output = self.dense(first_token_tensor) + pooled_output = self.activation(pooled_output) + return pooled_output + + +class BertPredictionHeadTransform(nn.Module): + def __init__(self, config): + super().__init__() + self.dense = nn.Linear(config.hidden_size, config.hidden_size) + if isinstance(config.hidden_act, str): + self.transform_act_fn = ACT2FN[config.hidden_act] + else: + self.transform_act_fn = config.hidden_act + self.LayerNorm = BertLayerNorm(config.hidden_size, eps=config.layer_norm_eps) + + def forward(self, hidden_states): + hidden_states = self.dense(hidden_states) + hidden_states = self.transform_act_fn(hidden_states) + hidden_states = self.LayerNorm(hidden_states) + return hidden_states + + +class BertLMPredictionHead(nn.Module): + def __init__(self, config): + super().__init__() + self.transform = BertPredictionHeadTransform(config) + + # The output weights are the same as the input embeddings, but there is + # an output-only bias for each token. + self.decoder = nn.Linear(config.hidden_size, config.vocab_size, bias=False) + + self.bias = nn.Parameter(torch.zeros(config.vocab_size)) + + # Need a link between the two variables so that the bias is correctly resized with `resize_token_embeddings` + self.decoder.bias = self.bias + + def forward(self, hidden_states): + hidden_states = self.transform(hidden_states) + hidden_states = self.decoder(hidden_states) + return hidden_states + + +class BertOnlyMLMHead(nn.Module): + def __init__(self, config): + super().__init__() + self.predictions = BertLMPredictionHead(config) + + def forward(self, sequence_output): + prediction_scores = self.predictions(sequence_output) + return prediction_scores + + +class BertOnlyNSPHead(nn.Module): + def __init__(self, config): + super().__init__() + self.seq_relationship = nn.Linear(config.hidden_size, 2) + + def forward(self, pooled_output): + seq_relationship_score = self.seq_relationship(pooled_output) + return seq_relationship_score + + +class BertPreTrainingHeads(nn.Module): + def __init__(self, config): + super().__init__() + self.predictions = BertLMPredictionHead(config) + self.seq_relationship = nn.Linear(config.hidden_size, 2) + + def forward(self, sequence_output, pooled_output): + prediction_scores = self.predictions(sequence_output) + seq_relationship_score = self.seq_relationship(pooled_output) + return prediction_scores, seq_relationship_score + + +class BertPreTrainedModel(PreTrainedModel): + """ An abstract class to handle weights initialization and + a simple interface for downloading and loading pretrained models. + """ + + config_class = BertConfig + load_tf_weights = load_tf_weights_in_bert + base_model_prefix = "bert" + + def _init_weights(self, module): + """ Initialize the weights """ + if isinstance(module, (nn.Linear, nn.Embedding)): + # Slightly different from the TF version which uses truncated_normal for initialization + # cf https://github.com/pytorch/pytorch/pull/5617 + module.weight.data.normal_(mean=0.0, std=self.config.initializer_range) + elif isinstance(module, BertLayerNorm): + module.bias.data.zero_() + module.weight.data.fill_(1.0) + if isinstance(module, nn.Linear) and module.bias is not None: + module.bias.data.zero_() + + +BERT_START_DOCSTRING = r""" + This model is a PyTorch `torch.nn.Module `_ sub-class. + Use it as a regular PyTorch Module and refer to the PyTorch documentation for all matter related to general + usage and behavior. + + Parameters: + config (:class:`~transformers.BertConfig`): Model configuration class with all the parameters of the model. + Initializing with a config file does not load the weights associated with the model, only the configuration. + Check out the :meth:`~transformers.PreTrainedModel.from_pretrained` method to load the model weights. +""" + +BERT_INPUTS_DOCSTRING = r""" + Args: + input_ids (:obj:`torch.LongTensor` of shape :obj:`{0}`): + Indices of input sequence tokens in the vocabulary. + + Indices can be obtained using :class:`transformers.BertTokenizer`. + See :func:`transformers.PreTrainedTokenizer.encode` and + :func:`transformers.PreTrainedTokenizer.__call__` for details. + + `What are input IDs? <../glossary.html#input-ids>`__ + attention_mask (:obj:`torch.FloatTensor` of shape :obj:`{0}`, `optional`, defaults to :obj:`None`): + Mask to avoid performing attention on padding token indices. + Mask values selected in ``[0, 1]``: + ``1`` for tokens that are NOT MASKED, ``0`` for MASKED tokens. + + `What are attention masks? <../glossary.html#attention-mask>`__ + token_type_ids (:obj:`torch.LongTensor` of shape :obj:`{0}`, `optional`, defaults to :obj:`None`): + Segment token indices to indicate first and second portions of the inputs. + Indices are selected in ``[0, 1]``: ``0`` corresponds to a `sentence A` token, ``1`` + corresponds to a `sentence B` token + + `What are token type IDs? <../glossary.html#token-type-ids>`_ + position_ids (:obj:`torch.LongTensor` of shape :obj:`{0}`, `optional`, defaults to :obj:`None`): + Indices of positions of each input sequence tokens in the position embeddings. + Selected in the range ``[0, config.max_position_embeddings - 1]``. + + `What are position IDs? <../glossary.html#position-ids>`_ + head_mask (:obj:`torch.FloatTensor` of shape :obj:`(num_heads,)` or :obj:`(num_layers, num_heads)`, `optional`, defaults to :obj:`None`): + Mask to nullify selected heads of the self-attention modules. + Mask values selected in ``[0, 1]``: + :obj:`1` indicates the head is **not masked**, :obj:`0` indicates the head is **masked**. + inputs_embeds (:obj:`torch.FloatTensor` of shape :obj:`(batch_size, sequence_length, hidden_size)`, `optional`, defaults to :obj:`None`): + Optionally, instead of passing :obj:`input_ids` you can choose to directly pass an embedded representation. + This is useful if you want more control over how to convert `input_ids` indices into associated vectors + than the model's internal embedding lookup matrix. + encoder_hidden_states (:obj:`torch.FloatTensor` of shape :obj:`(batch_size, sequence_length, hidden_size)`, `optional`, defaults to :obj:`None`): + Sequence of hidden-states at the output of the last layer of the encoder. Used in the cross-attention + if the model is configured as a decoder. + encoder_attention_mask (:obj:`torch.FloatTensor` of shape :obj:`(batch_size, sequence_length)`, `optional`, defaults to :obj:`None`): + Mask to avoid performing attention on the padding token indices of the encoder input. This mask + is used in the cross-attention if the model is configured as a decoder. + Mask values selected in ``[0, 1]``: + ``1`` for tokens that are NOT MASKED, ``0`` for MASKED tokens. + output_attentions (:obj:`bool`, `optional`, defaults to :obj:`None`): + If set to ``True``, the attentions tensors of all attention layers are returned. See ``attentions`` under returned tensors for more detail. +""" + + +@add_start_docstrings( + "The bare Bert Model transformer outputting raw hidden-states without any specific head on top.", + BERT_START_DOCSTRING, +) +class BertModel(BertPreTrainedModel): + """ + + The model can behave as an encoder (with only self-attention) as well + as a decoder, in which case a layer of cross-attention is added between + the self-attention layers, following the architecture described in `Attention is all you need`_ by Ashish Vaswani, + Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N. Gomez, Lukasz Kaiser and Illia Polosukhin. + + To behave as an decoder the model needs to be initialized with the + :obj:`is_decoder` argument of the configuration set to :obj:`True`; an + :obj:`encoder_hidden_states` is expected as an input to the forward pass. + + .. _`Attention is all you need`: + https://arxiv.org/abs/1706.03762 + + """ + + def __init__(self, config): + super().__init__(config) + self.config = config + + self.embeddings = BertEmbeddings(config) + self.encoder = BertEncoder(config) + self.pooler = BertPooler(config) + + self.init_weights() + + def get_input_embeddings(self): + return self.embeddings.word_embeddings + + def set_input_embeddings(self, value): + self.embeddings.word_embeddings = value + + def _prune_heads(self, heads_to_prune): + """ Prunes heads of the model. + heads_to_prune: dict of {layer_num: list of heads to prune in this layer} + See base class PreTrainedModel + """ + for layer, heads in heads_to_prune.items(): + self.encoder.layer[layer].attention.prune_heads(heads) + + @add_start_docstrings_to_callable(BERT_INPUTS_DOCSTRING.format("(batch_size, sequence_length)")) + @add_code_sample_docstrings(tokenizer_class=_TOKENIZER_FOR_DOC, checkpoint="bert-base-uncased") + def forward( + self, + input_ids=None, + attention_mask=None, + token_type_ids=None, + position_ids=None, + head_mask=None, + inputs_embeds=None, + encoder_hidden_states=None, + encoder_attention_mask=None, + output_attentions=None, + output_hidden_states=None, + ): + r""" + Return: + :obj:`tuple(torch.FloatTensor)` comprising various elements depending on the configuration (:class:`~transformers.BertConfig`) and inputs: + last_hidden_state (:obj:`torch.FloatTensor` of shape :obj:`(batch_size, sequence_length, hidden_size)`): + Sequence of hidden-states at the output of the last layer of the model. + pooler_output (:obj:`torch.FloatTensor`: of shape :obj:`(batch_size, hidden_size)`): + Last layer hidden-state of the first token of the sequence (classification token) + further processed by a Linear layer and a Tanh activation function. The Linear + layer weights are trained from the next sentence prediction (classification) + objective during pre-training. + + This output is usually *not* a good summary + of the semantic content of the input, you're often better with averaging or pooling + the sequence of hidden-states for the whole input sequence. + hidden_states (:obj:`tuple(torch.FloatTensor)`, `optional`, returned when ``output_hidden_states=True`` is passed or when ``config.output_hidden_states=True``): + Tuple of :obj:`torch.FloatTensor` (one for the output of the embeddings + one for the output of each layer) + of shape :obj:`(batch_size, sequence_length, hidden_size)`. + + Hidden-states of the model at the output of each layer plus the initial embedding outputs. + attentions (:obj:`tuple(torch.FloatTensor)`, `optional`, returned when ``output_attentions=True`` is passed or when ``config.output_attentions=True``): + Tuple of :obj:`torch.FloatTensor` (one for each layer) of shape + :obj:`(batch_size, num_heads, sequence_length, sequence_length)`. + + Attentions weights after the attention softmax, used to compute the weighted average in the self-attention + heads. + """ + output_attentions = output_attentions if output_attentions is not None else self.config.output_attentions + output_hidden_states = ( + output_hidden_states if output_hidden_states is not None else self.config.output_hidden_states + ) + + if input_ids is not None and inputs_embeds is not None: + raise ValueError("You cannot specify both input_ids and inputs_embeds at the same time") + elif input_ids is not None: + input_shape = input_ids.size() + elif inputs_embeds is not None: + input_shape = inputs_embeds.size()[:-1] + else: + raise ValueError("You have to specify either input_ids or inputs_embeds") + + device = input_ids.device if input_ids is not None else inputs_embeds.device + + if attention_mask is None: + attention_mask = torch.ones(input_shape, device=device) + if token_type_ids is None: + token_type_ids = torch.zeros(input_shape, dtype=torch.long, device=device) + + # We can provide a self-attention mask of dimensions [batch_size, from_seq_length, to_seq_length] + # ourselves in which case we just need to make it broadcastable to all heads. + extended_attention_mask: torch.Tensor = self.get_extended_attention_mask(attention_mask, input_shape, device) + + # If a 2D ou 3D attention mask is provided for the cross-attention + # we need to make broadcastabe to [batch_size, num_heads, seq_length, seq_length] + if self.config.is_decoder and encoder_hidden_states is not None: + encoder_batch_size, encoder_sequence_length, _ = encoder_hidden_states.size() + encoder_hidden_shape = (encoder_batch_size, encoder_sequence_length) + if encoder_attention_mask is None: + encoder_attention_mask = torch.ones(encoder_hidden_shape, device=device) + encoder_extended_attention_mask = self.invert_attention_mask(encoder_attention_mask) + else: + encoder_extended_attention_mask = None + + # Prepare head mask if needed + # 1.0 in head_mask indicate we keep the head + # attention_probs has shape bsz x n_heads x N x N + # input head_mask has shape [num_heads] or [num_hidden_layers x num_heads] + # and head_mask is converted to shape [num_hidden_layers x batch x num_heads x seq_length x seq_length] + head_mask = self.get_head_mask(head_mask, self.config.num_hidden_layers) + + embedding_output = self.embeddings( + input_ids=input_ids, position_ids=position_ids, token_type_ids=token_type_ids, inputs_embeds=inputs_embeds + ) + encoder_outputs = self.encoder( + embedding_output, + attention_mask=extended_attention_mask, + head_mask=head_mask, + encoder_hidden_states=encoder_hidden_states, + encoder_attention_mask=encoder_extended_attention_mask, + output_attentions=output_attentions, + output_hidden_states=output_hidden_states, + ) + sequence_output = encoder_outputs[0] + pooled_output = self.pooler(sequence_output) if self.pooler is not None else None + + outputs = (sequence_output, pooled_output,) + encoder_outputs[ + 1: + ] # add hidden_states and attentions if they are here + return outputs # sequence_output, pooled_output, (hidden_states), (attentions) + + +@add_start_docstrings( + """Bert Model with two heads on top as done during the pre-training: a `masked language modeling` head and + a `next sentence prediction (classification)` head. """, + BERT_START_DOCSTRING, +) +class BertForPreTraining(BertPreTrainedModel): + def __init__(self, config): + super().__init__(config) + + self.bert = BertModel(config) + self.cls = BertPreTrainingHeads(config) + + self.init_weights() + + def get_output_embeddings(self): + return self.cls.predictions.decoder + + @add_start_docstrings_to_callable(BERT_INPUTS_DOCSTRING.format("(batch_size, sequence_length)")) + def forward( + self, + input_ids=None, + attention_mask=None, + token_type_ids=None, + position_ids=None, + head_mask=None, + inputs_embeds=None, + labels=None, + next_sentence_label=None, + output_attentions=None, + output_hidden_states=None, + **kwargs + ): + r""" + labels (``torch.LongTensor`` of shape ``(batch_size, sequence_length)``, `optional`, defaults to :obj:`None`): + Labels for computing the masked language modeling loss. + Indices should be in ``[-100, 0, ..., config.vocab_size]`` (see ``input_ids`` docstring) + Tokens with indices set to ``-100`` are ignored (masked), the loss is only computed for the tokens with labels + in ``[0, ..., config.vocab_size]`` + next_sentence_label (``torch.LongTensor`` of shape ``(batch_size,)``, `optional`, defaults to :obj:`None`): + Labels for computing the next sequence prediction (classification) loss. Input should be a sequence pair (see :obj:`input_ids` docstring) + Indices should be in ``[0, 1]``. + ``0`` indicates sequence B is a continuation of sequence A, + ``1`` indicates sequence B is a random sequence. + kwargs (:obj:`Dict[str, any]`, optional, defaults to `{}`): + Used to hide legacy arguments that have been deprecated. + + Returns: + :obj:`tuple(torch.FloatTensor)` comprising various elements depending on the configuration (:class:`~transformers.BertConfig`) and inputs: + loss (`optional`, returned when ``labels`` is provided) ``torch.FloatTensor`` of shape ``(1,)``: + Total loss as the sum of the masked language modeling loss and the next sequence prediction (classification) loss. + prediction_scores (:obj:`torch.FloatTensor` of shape :obj:`(batch_size, sequence_length, config.vocab_size)`) + Prediction scores of the language modeling head (scores for each vocabulary token before SoftMax). + seq_relationship_scores (:obj:`torch.FloatTensor` of shape :obj:`(batch_size, 2)`): + Prediction scores of the next sequence prediction (classification) head (scores of True/False + continuation before SoftMax). + hidden_states (:obj:`tuple(torch.FloatTensor)`, `optional`, returned when ``output_hidden_states=True`` is passed or when ``config.output_hidden_states=True``): + Tuple of :obj:`torch.FloatTensor` (one for the output of the embeddings + one for the output of each layer) + of shape :obj:`(batch_size, sequence_length, hidden_size)`. + + Hidden-states of the model at the output of each layer plus the initial embedding outputs. + attentions (:obj:`tuple(torch.FloatTensor)`, `optional`, returned when ``output_attentions=True`` is passed or when ``config.output_attentions=True``): + Tuple of :obj:`torch.FloatTensor` (one for each layer) of shape + :obj:`(batch_size, num_heads, sequence_length, sequence_length)`. + + Attentions weights after the attention softmax, used to compute the weighted average in the self-attention + heads. + + + Examples:: + + >>> from transformers import BertTokenizer, BertForPreTraining + >>> import torch + + >>> tokenizer = BertTokenizer.from_pretrained('bert-base-uncased') + >>> model = BertForPreTraining.from_pretrained('bert-base-uncased') + + >>> inputs = tokenizer("Hello, my dog is cute", return_tensors="pt") + >>> outputs = model(**inputs) + + >>> prediction_scores, seq_relationship_scores = outputs[:2] + + """ + if "masked_lm_labels" in kwargs: + warnings.warn( + "The `masked_lm_labels` argument is deprecated and will be removed in a future version, use `labels` instead.", + DeprecationWarning, + ) + labels = kwargs.pop("masked_lm_labels") + assert kwargs == {}, f"Unexpected keyword arguments: {list(kwargs.keys())}." + + outputs = self.bert( + input_ids, + attention_mask=attention_mask, + token_type_ids=token_type_ids, + position_ids=position_ids, + head_mask=head_mask, + inputs_embeds=inputs_embeds, + output_attentions=output_attentions, + output_hidden_states=output_hidden_states, + ) + + sequence_output, pooled_output = outputs[:2] + prediction_scores, seq_relationship_score = self.cls(sequence_output, pooled_output) + + outputs = (prediction_scores, seq_relationship_score,) + outputs[ + 2: + ] # add hidden states and attention if they are here + + if labels is not None and next_sentence_label is not None: + loss_fct = CrossEntropyLoss() + masked_lm_loss = loss_fct(prediction_scores.view(-1, self.config.vocab_size), labels.view(-1)) + next_sentence_loss = loss_fct(seq_relationship_score.view(-1, 2), next_sentence_label.view(-1)) + total_loss = masked_lm_loss + next_sentence_loss + outputs = (total_loss,) + outputs + + return outputs # (loss), prediction_scores, seq_relationship_score, (hidden_states), (attentions) + + +@add_start_docstrings( + """Bert Model with a `language modeling` head on top for CLM fine-tuning. """, BERT_START_DOCSTRING +) +class BertLMHeadModel(BertPreTrainedModel): + def __init__(self, config): + super().__init__(config) + assert config.is_decoder, "If you want to use `BertLMHeadModel` as a standalone, add `is_decoder=True`." + + self.bert = BertModel(config) + self.cls = BertOnlyMLMHead(config) + + self.init_weights() + + def get_output_embeddings(self): + return self.cls.predictions.decoder + + @add_start_docstrings_to_callable(BERT_INPUTS_DOCSTRING.format("(batch_size, sequence_length)")) + def forward( + self, + input_ids=None, + attention_mask=None, + token_type_ids=None, + position_ids=None, + head_mask=None, + inputs_embeds=None, + labels=None, + encoder_hidden_states=None, + encoder_attention_mask=None, + output_attentions=None, + output_hidden_states=None, + **kwargs + ): + r""" + labels (:obj:`torch.LongTensor` of shape :obj:`(batch_size, sequence_length)`, `optional`, defaults to :obj:`None`): + Labels for computing the left-to-right language modeling loss (next word prediction). + Indices should be in ``[-100, 0, ..., config.vocab_size]`` (see ``input_ids`` docstring) + Tokens with indices set to ``-100`` are ignored (masked), the loss is only computed for the tokens with labels + in ``[0, ..., config.vocab_size]`` + kwargs (:obj:`Dict[str, any]`, optional, defaults to `{}`): + Used to hide legacy arguments that have been deprecated. + + Returns: + :obj:`tuple(torch.FloatTensor)` comprising various elements depending on the configuration (:class:`~transformers.BertConfig`) and inputs: + ltr_lm_loss (:obj:`torch.FloatTensor` of shape :obj:`(1,)`, `optional`, returned when :obj:`labels` is provided): + Next token prediction loss. + prediction_scores (:obj:`torch.FloatTensor` of shape :obj:`(batch_size, sequence_length, config.vocab_size)`) + Prediction scores of the language modeling head (scores for each vocabulary token before SoftMax). + hidden_states (:obj:`tuple(torch.FloatTensor)`, `optional`, returned when ``output_hidden_states=True`` is passed or when ``config.output_hidden_states=True``): + Tuple of :obj:`torch.FloatTensor` (one for the output of the embeddings + one for the output of each layer) + of shape :obj:`(batch_size, sequence_length, hidden_size)`. + + Hidden-states of the model at the output of each layer plus the initial embedding outputs. + attentions (:obj:`tuple(torch.FloatTensor)`, `optional`, returned when ``output_attentions=True`` is passed or when ``config.output_attentions=True``): + Tuple of :obj:`torch.FloatTensor` (one for each layer) of shape + :obj:`(batch_size, num_heads, sequence_length, sequence_length)`. + + Attentions weights after the attention softmax, used to compute the weighted average in the self-attention + heads. + + Example:: + + >>> from transformers import BertTokenizer, BertLMHeadModel, BertConfig + >>> import torch + + >>> tokenizer = BertTokenizer.from_pretrained('bert-base-cased') + >>> config = BertConfig.from_pretrained("bert-base-cased") + >>> config.is_decoder = True + >>> model = BertLMHeadModel.from_pretrained('bert-base-cased', config=config) + + >>> inputs = tokenizer("Hello, my dog is cute", return_tensors="pt") + >>> outputs = model(**inputs) + + >>> last_hidden_states = outputs[0] # The last hidden-state is the first element of the output tuple + """ + + outputs = self.bert( + input_ids, + attention_mask=attention_mask, + token_type_ids=token_type_ids, + position_ids=position_ids, + head_mask=head_mask, + inputs_embeds=inputs_embeds, + encoder_hidden_states=encoder_hidden_states, + encoder_attention_mask=encoder_attention_mask, + output_attentions=output_attentions, + output_hidden_states=output_hidden_states, + ) + + sequence_output = outputs[0] + prediction_scores = self.cls(sequence_output) + + outputs = (prediction_scores,) + outputs[2:] # Add hidden states and attention if they are here + + if labels is not None: + # we are doing next-token prediction; shift prediction scores and input ids by one + prediction_scores = prediction_scores[:, :-1, :].contiguous() + labels = labels[:, 1:].contiguous() + loss_fct = CrossEntropyLoss() + ltr_lm_loss = loss_fct(prediction_scores.view(-1, self.config.vocab_size), labels.view(-1)) + outputs = (ltr_lm_loss,) + outputs + + return outputs # (ltr_lm_loss), prediction_scores, (hidden_states), (attentions) + + def prepare_inputs_for_generation(self, input_ids, attention_mask=None, **model_kwargs): + input_shape = input_ids.shape + + # if model is used as a decoder in encoder-decoder model, the decoder attention mask is created on the fly + if attention_mask is None: + attention_mask = input_ids.new_ones(input_shape) + + return {"input_ids": input_ids, "attention_mask": attention_mask} + + +@add_start_docstrings("""Bert Model with a `language modeling` head on top. """, BERT_START_DOCSTRING) +class BertForMaskedLM(BertPreTrainedModel): + def __init__(self, config): + super().__init__(config) + assert ( + not config.is_decoder + ), "If you want to use `BertForMaskedLM` make sure `config.is_decoder=False` for bi-directional self-attention." + + self.bert = BertModel(config) + self.cls = BertOnlyMLMHead(config) + + self.init_weights() + + def get_output_embeddings(self): + return self.cls.predictions.decoder + + @add_start_docstrings_to_callable(BERT_INPUTS_DOCSTRING.format("(batch_size, sequence_length)")) + @add_code_sample_docstrings(tokenizer_class=_TOKENIZER_FOR_DOC, checkpoint="bert-base-uncased") + def forward( + self, + input_ids=None, + attention_mask=None, + token_type_ids=None, + position_ids=None, + head_mask=None, + inputs_embeds=None, + labels=None, + encoder_hidden_states=None, + encoder_attention_mask=None, + output_attentions=None, + output_hidden_states=None, + **kwargs + ): + r""" + labels (:obj:`torch.LongTensor` of shape :obj:`(batch_size, sequence_length)`, `optional`, defaults to :obj:`None`): + Labels for computing the masked language modeling loss. + Indices should be in ``[-100, 0, ..., config.vocab_size]`` (see ``input_ids`` docstring) + Tokens with indices set to ``-100`` are ignored (masked), the loss is only computed for the tokens with labels + in ``[0, ..., config.vocab_size]`` + kwargs (:obj:`Dict[str, any]`, optional, defaults to `{}`): + Used to hide legacy arguments that have been deprecated. + + Returns: + :obj:`tuple(torch.FloatTensor)` comprising various elements depending on the configuration (:class:`~transformers.BertConfig`) and inputs: + masked_lm_loss (`optional`, returned when ``labels`` is provided) ``torch.FloatTensor`` of shape ``(1,)``: + Masked language modeling loss. + prediction_scores (:obj:`torch.FloatTensor` of shape :obj:`(batch_size, sequence_length, config.vocab_size)`) + Prediction scores of the language modeling head (scores for each vocabulary token before SoftMax). + hidden_states (:obj:`tuple(torch.FloatTensor)`, `optional`, returned when ``output_hidden_states=True`` is passed or when ``config.output_hidden_states=True``): + Tuple of :obj:`torch.FloatTensor` (one for the output of the embeddings + one for the output of each layer) + of shape :obj:`(batch_size, sequence_length, hidden_size)`. + + Hidden-states of the model at the output of each layer plus the initial embedding outputs. + attentions (:obj:`tuple(torch.FloatTensor)`, `optional`, returned when ``output_attentions=True`` is passed or when ``config.output_attentions=True``): + Tuple of :obj:`torch.FloatTensor` (one for each layer) of shape + :obj:`(batch_size, num_heads, sequence_length, sequence_length)`. + + Attentions weights after the attention softmax, used to compute the weighted average in the self-attention + heads. + """ + if "masked_lm_labels" in kwargs: + warnings.warn( + "The `masked_lm_labels` argument is deprecated and will be removed in a future version, use `labels` instead.", + DeprecationWarning, + ) + labels = kwargs.pop("masked_lm_labels") + assert "lm_labels" not in kwargs, "Use `BertWithLMHead` for autoregressive language modeling task." + assert kwargs == {}, f"Unexpected keyword arguments: {list(kwargs.keys())}." + + outputs = self.bert( + input_ids, + attention_mask=attention_mask, + token_type_ids=token_type_ids, + position_ids=position_ids, + head_mask=head_mask, + inputs_embeds=inputs_embeds, + encoder_hidden_states=encoder_hidden_states, + encoder_attention_mask=encoder_attention_mask, + output_attentions=output_attentions, + output_hidden_states=output_hidden_states, + ) + + sequence_output = outputs[0] + prediction_scores = self.cls(sequence_output) + + outputs = (prediction_scores,) + outputs[2:] # Add hidden states and attention if they are here + + if labels is not None: + loss_fct = CrossEntropyLoss() # -100 index = padding token + masked_lm_loss = loss_fct(prediction_scores.view(-1, self.config.vocab_size), labels.view(-1)) + outputs = (masked_lm_loss,) + outputs + + return outputs # (masked_lm_loss), prediction_scores, (hidden_states), (attentions) + + def prepare_inputs_for_generation(self, input_ids, attention_mask=None, **model_kwargs): + input_shape = input_ids.shape + effective_batch_size = input_shape[0] + + # add a dummy token + assert self.config.pad_token_id is not None, "The PAD token should be defined for generation" + attention_mask = torch.cat([attention_mask, attention_mask.new_zeros((attention_mask.shape[0], 1))], dim=-1) + dummy_token = torch.full( + (effective_batch_size, 1), self.config.pad_token_id, dtype=torch.long, device=input_ids.device + ) + input_ids = torch.cat([input_ids, dummy_token], dim=1) + + return {"input_ids": input_ids, "attention_mask": attention_mask} + + +@add_start_docstrings( + """Bert Model with a `next sentence prediction (classification)` head on top. """, BERT_START_DOCSTRING, +) +class BertForNextSentencePrediction(BertPreTrainedModel): + def __init__(self, config): + super().__init__(config) + + self.bert = BertModel(config) + self.cls = BertOnlyNSPHead(config) + + self.init_weights() + + @add_start_docstrings_to_callable(BERT_INPUTS_DOCSTRING.format("(batch_size, sequence_length)")) + def forward( + self, + input_ids=None, + attention_mask=None, + token_type_ids=None, + position_ids=None, + head_mask=None, + inputs_embeds=None, + next_sentence_label=None, + output_attentions=None, + output_hidden_states=None, + ): + r""" + next_sentence_label (:obj:`torch.LongTensor` of shape :obj:`(batch_size,)`, `optional`, defaults to :obj:`None`): + Labels for computing the next sequence prediction (classification) loss. Input should be a sequence pair (see ``input_ids`` docstring) + Indices should be in ``[0, 1]``. + ``0`` indicates sequence B is a continuation of sequence A, + ``1`` indicates sequence B is a random sequence. + + Returns: + :obj:`tuple(torch.FloatTensor)` comprising various elements depending on the configuration (:class:`~transformers.BertConfig`) and inputs: + loss (:obj:`torch.FloatTensor` of shape :obj:`(1,)`, `optional`, returned when :obj:`next_sentence_label` is provided): + Next sequence prediction (classification) loss. + seq_relationship_scores (:obj:`torch.FloatTensor` of shape :obj:`(batch_size, 2)`): + Prediction scores of the next sequence prediction (classification) head (scores of True/False continuation before SoftMax). + hidden_states (:obj:`tuple(torch.FloatTensor)`, `optional`, returned when ``output_hidden_states=True`` is passed or when ``config.output_hidden_states=True``): + Tuple of :obj:`torch.FloatTensor` (one for the output of the embeddings + one for the output of each layer) + of shape :obj:`(batch_size, sequence_length, hidden_size)`. + + Hidden-states of the model at the output of each layer plus the initial embedding outputs. + attentions (:obj:`tuple(torch.FloatTensor)`, `optional`, returned when ``output_attentions=True`` is passed or when ``config.output_attentions=True``): + Tuple of :obj:`torch.FloatTensor` (one for each layer) of shape + :obj:`(batch_size, num_heads, sequence_length, sequence_length)`. + + Attentions weights after the attention softmax, used to compute the weighted average in the self-attention + heads. + + Examples:: + + >>> from transformers import BertTokenizer, BertForNextSentencePrediction + >>> import torch + + >>> tokenizer = BertTokenizer.from_pretrained('bert-base-uncased') + >>> model = BertForNextSentencePrediction.from_pretrained('bert-base-uncased') + + >>> prompt = "In Italy, pizza served in formal settings, such as at a restaurant, is presented unsliced." + >>> next_sentence = "The sky is blue due to the shorter wavelength of blue light." + >>> encoding = tokenizer(prompt, next_sentence, return_tensors='pt') + + >>> loss, logits = model(**encoding, next_sentence_label=torch.LongTensor([1])) + >>> assert logits[0, 0] < logits[0, 1] # next sentence was random + """ + + outputs = self.bert( + input_ids, + attention_mask=attention_mask, + token_type_ids=token_type_ids, + position_ids=position_ids, + head_mask=head_mask, + inputs_embeds=inputs_embeds, + output_attentions=output_attentions, + output_hidden_states=output_hidden_states, + ) + + pooled_output = outputs[1] + + seq_relationship_score = self.cls(pooled_output) + + outputs = (seq_relationship_score,) + outputs[2:] # add hidden states and attention if they are here + if next_sentence_label is not None: + loss_fct = CrossEntropyLoss() + next_sentence_loss = loss_fct(seq_relationship_score.view(-1, 2), next_sentence_label.view(-1)) + outputs = (next_sentence_loss,) + outputs + + return outputs # (next_sentence_loss), seq_relationship_score, (hidden_states), (attentions) + + +@add_start_docstrings( + """Bert Model transformer with a sequence classification/regression head on top (a linear layer on top of + the pooled output) e.g. for GLUE tasks. """, + BERT_START_DOCSTRING, +) +class BertForSequenceClassification(BertPreTrainedModel): + def __init__(self, config): + super().__init__(config) + self.num_labels = config.num_labels + + self.bert = BertModel(config) + self.dropout = nn.Dropout(config.hidden_dropout_prob) + self.classifier = nn.Linear(config.hidden_size, config.num_labels) + + self.init_weights() + + @add_start_docstrings_to_callable(BERT_INPUTS_DOCSTRING.format("(batch_size, sequence_length)")) + @add_code_sample_docstrings(tokenizer_class=_TOKENIZER_FOR_DOC, checkpoint="bert-base-uncased") + def forward( + self, + input_ids=None, + attention_mask=None, + token_type_ids=None, + position_ids=None, + head_mask=None, + inputs_embeds=None, + labels=None, + output_attentions=None, + output_hidden_states=None, + ): + r""" + labels (:obj:`torch.LongTensor` of shape :obj:`(batch_size,)`, `optional`, defaults to :obj:`None`): + Labels for computing the sequence classification/regression loss. + Indices should be in :obj:`[0, ..., config.num_labels - 1]`. + If :obj:`config.num_labels == 1` a regression loss is computed (Mean-Square loss), + If :obj:`config.num_labels > 1` a classification loss is computed (Cross-Entropy). + + Returns: + :obj:`tuple(torch.FloatTensor)` comprising various elements depending on the configuration (:class:`~transformers.BertConfig`) and inputs: + loss (:obj:`torch.FloatTensor` of shape :obj:`(1,)`, `optional`, returned when :obj:`label` is provided): + Classification (or regression if config.num_labels==1) loss. + logits (:obj:`torch.FloatTensor` of shape :obj:`(batch_size, config.num_labels)`): + Classification (or regression if config.num_labels==1) scores (before SoftMax). + hidden_states (:obj:`tuple(torch.FloatTensor)`, `optional`, returned when ``output_hidden_states=True`` is passed or when ``config.output_hidden_states=True``): + Tuple of :obj:`torch.FloatTensor` (one for the output of the embeddings + one for the output of each layer) + of shape :obj:`(batch_size, sequence_length, hidden_size)`. + + Hidden-states of the model at the output of each layer plus the initial embedding outputs. + attentions (:obj:`tuple(torch.FloatTensor)`, `optional`, returned when ``output_attentions=True`` is passed or when ``config.output_attentions=True``): + Tuple of :obj:`torch.FloatTensor` (one for each layer) of shape + :obj:`(batch_size, num_heads, sequence_length, sequence_length)`. + + Attentions weights after the attention softmax, used to compute the weighted average in the self-attention + heads. + """ + + outputs = self.bert( + input_ids, + attention_mask=attention_mask, + token_type_ids=token_type_ids, + position_ids=position_ids, + head_mask=head_mask, + inputs_embeds=inputs_embeds, + output_attentions=output_attentions, + output_hidden_states=output_hidden_states, + ) + + pooled_output = outputs[1] + + pooled_output = self.dropout(pooled_output) + logits = self.classifier(pooled_output) + + outputs = (logits,) + outputs[2:] # add hidden states and attention if they are here + + if labels is not None: + if self.num_labels == 1: + # We are doing regression + loss_fct = MSELoss() + loss = loss_fct(logits.view(-1), labels.view(-1)) + else: + loss_fct = CrossEntropyLoss() + loss = loss_fct(logits.view(-1, self.num_labels), labels.view(-1)) + outputs = (loss,) + outputs + + return outputs # (loss), logits, (hidden_states), (attentions) + + +@add_start_docstrings( + """Bert Model with a multiple choice classification head on top (a linear layer on top of + the pooled output and a softmax) e.g. for RocStories/SWAG tasks. """, + BERT_START_DOCSTRING, +) +class BertForMultipleChoice(BertPreTrainedModel): + def __init__(self, config): + super().__init__(config) + + self.bert = BertModel(config) + self.dropout = nn.Dropout(config.hidden_dropout_prob) + self.classifier = nn.Linear(config.hidden_size, 1) + + self.init_weights() + + @add_start_docstrings_to_callable(BERT_INPUTS_DOCSTRING.format("(batch_size, num_choices, sequence_length)")) + @add_code_sample_docstrings(tokenizer_class=_TOKENIZER_FOR_DOC, checkpoint="bert-base-uncased") + def forward( + self, + input_ids=None, + attention_mask=None, + token_type_ids=None, + position_ids=None, + head_mask=None, + inputs_embeds=None, + labels=None, + output_attentions=None, + output_hidden_states=None, + ): + r""" + labels (:obj:`torch.LongTensor` of shape :obj:`(batch_size,)`, `optional`, defaults to :obj:`None`): + Labels for computing the multiple choice classification loss. + Indices should be in ``[0, ..., num_choices-1]`` where `num_choices` is the size of the second dimension + of the input tensors. (see `input_ids` above) + + Returns: + :obj:`tuple(torch.FloatTensor)` comprising various elements depending on the configuration (:class:`~transformers.BertConfig`) and inputs: + loss (:obj:`torch.FloatTensor` of shape `(1,)`, `optional`, returned when :obj:`labels` is provided): + Classification loss. + classification_scores (:obj:`torch.FloatTensor` of shape :obj:`(batch_size, num_choices)`): + `num_choices` is the second dimension of the input tensors. (see `input_ids` above). + + Classification scores (before SoftMax). + hidden_states (:obj:`tuple(torch.FloatTensor)`, `optional`, returned when ``output_hidden_states=True`` is passed or when ``config.output_hidden_states=True``): + Tuple of :obj:`torch.FloatTensor` (one for the output of the embeddings + one for the output of each layer) + of shape :obj:`(batch_size, sequence_length, hidden_size)`. + + Hidden-states of the model at the output of each layer plus the initial embedding outputs. + attentions (:obj:`tuple(torch.FloatTensor)`, `optional`, returned when ``output_attentions=True`` is passed or when ``config.output_attentions=True``): + Tuple of :obj:`torch.FloatTensor` (one for each layer) of shape + :obj:`(batch_size, num_heads, sequence_length, sequence_length)`. + + Attentions weights after the attention softmax, used to compute the weighted average in the self-attention + heads. + """ + num_choices = input_ids.shape[1] if input_ids is not None else inputs_embeds.shape[1] + + input_ids = input_ids.view(-1, input_ids.size(-1)) if input_ids is not None else None + attention_mask = attention_mask.view(-1, attention_mask.size(-1)) if attention_mask is not None else None + token_type_ids = token_type_ids.view(-1, token_type_ids.size(-1)) if token_type_ids is not None else None + position_ids = position_ids.view(-1, position_ids.size(-1)) if position_ids is not None else None + inputs_embeds = ( + inputs_embeds.view(-1, inputs_embeds.size(-2), inputs_embeds.size(-1)) + if inputs_embeds is not None + else None + ) + + outputs = self.bert( + input_ids, + attention_mask=attention_mask, + token_type_ids=token_type_ids, + position_ids=position_ids, + head_mask=head_mask, + inputs_embeds=inputs_embeds, + output_attentions=output_attentions, + output_hidden_states=output_hidden_states, + ) + + pooled_output = outputs[1] + + pooled_output = self.dropout(pooled_output) + logits = self.classifier(pooled_output) + reshaped_logits = logits.view(-1, num_choices) + + outputs = (reshaped_logits,) + outputs[2:] # add hidden states and attention if they are here + + if labels is not None: + loss_fct = CrossEntropyLoss() + loss = loss_fct(reshaped_logits, labels) + outputs = (loss,) + outputs + + return outputs # (loss), reshaped_logits, (hidden_states), (attentions) + + +@add_start_docstrings( + """Bert Model with a token classification head on top (a linear layer on top of + the hidden-states output) e.g. for Named-Entity-Recognition (NER) tasks. """, + BERT_START_DOCSTRING, +) +class BertForTokenClassification(BertPreTrainedModel): + def __init__(self, config): + super().__init__(config) + self.num_labels = config.num_labels + + self.bert = BertModel(config) + self.dropout = nn.Dropout(config.hidden_dropout_prob) + self.classifier = nn.Linear(config.hidden_size, config.num_labels) + + self.init_weights() + + @add_start_docstrings_to_callable(BERT_INPUTS_DOCSTRING.format("(batch_size, sequence_length)")) + @add_code_sample_docstrings(tokenizer_class=_TOKENIZER_FOR_DOC, checkpoint="bert-base-uncased") + def forward( + self, + input_ids=None, + attention_mask=None, + token_type_ids=None, + position_ids=None, + head_mask=None, + inputs_embeds=None, + labels=None, + output_attentions=None, + output_hidden_states=None, + ): + r""" + labels (:obj:`torch.LongTensor` of shape :obj:`(batch_size, sequence_length)`, `optional`, defaults to :obj:`None`): + Labels for computing the token classification loss. + Indices should be in ``[0, ..., config.num_labels - 1]``. + + Returns: + :obj:`tuple(torch.FloatTensor)` comprising various elements depending on the configuration (:class:`~transformers.BertConfig`) and inputs: + loss (:obj:`torch.FloatTensor` of shape :obj:`(1,)`, `optional`, returned when ``labels`` is provided) : + Classification loss. + scores (:obj:`torch.FloatTensor` of shape :obj:`(batch_size, sequence_length, config.num_labels)`) + Classification scores (before SoftMax). + hidden_states (:obj:`tuple(torch.FloatTensor)`, `optional`, returned when ``output_hidden_states=True`` is passed or when ``config.output_hidden_states=True``): + Tuple of :obj:`torch.FloatTensor` (one for the output of the embeddings + one for the output of each layer) + of shape :obj:`(batch_size, sequence_length, hidden_size)`. + + Hidden-states of the model at the output of each layer plus the initial embedding outputs. + attentions (:obj:`tuple(torch.FloatTensor)`, `optional`, returned when ``output_attentions=True`` is passed or when ``config.output_attentions=True``): + Tuple of :obj:`torch.FloatTensor` (one for each layer) of shape + :obj:`(batch_size, num_heads, sequence_length, sequence_length)`. + + Attentions weights after the attention softmax, used to compute the weighted average in the self-attention + heads. + """ + + outputs = self.bert( + input_ids, + attention_mask=attention_mask, + token_type_ids=token_type_ids, + position_ids=position_ids, + head_mask=head_mask, + inputs_embeds=inputs_embeds, + output_attentions=output_attentions, + output_hidden_states=output_hidden_states, + ) + + sequence_output = outputs[0] + + sequence_output = self.dropout(sequence_output) + logits = self.classifier(sequence_output) + + outputs = (logits,) + outputs[2:] # add hidden states and attention if they are here + if labels is not None: + loss_fct = CrossEntropyLoss() + # Only keep active parts of the loss + if attention_mask is not None: + active_loss = attention_mask.view(-1) == 1 + active_logits = logits.view(-1, self.num_labels) + active_labels = torch.where( + active_loss, labels.view(-1), torch.tensor(loss_fct.ignore_index).type_as(labels) + ) + loss = loss_fct(active_logits, active_labels) + else: + loss = loss_fct(logits.view(-1, self.num_labels), labels.view(-1)) + outputs = (loss,) + outputs + + return outputs # (loss), scores, (hidden_states), (attentions) + + +@add_start_docstrings( + """Bert Model with a span classification head on top for extractive question-answering tasks like SQuAD (a linear + layers on top of the hidden-states output to compute `span start logits` and `span end logits`). """, + BERT_START_DOCSTRING, +) +class BertForQuestionAnswering(BertPreTrainedModel): + def __init__(self, config): + super().__init__(config) + self.num_labels = config.num_labels + + self.bert = BertModel(config) + self.qa_outputs = nn.Linear(config.hidden_size, config.num_labels) + + self.init_weights() + + @add_start_docstrings_to_callable(BERT_INPUTS_DOCSTRING.format("(batch_size, sequence_length)")) + @add_code_sample_docstrings(tokenizer_class=_TOKENIZER_FOR_DOC, checkpoint="bert-base-uncased") + def forward( + self, + input_ids=None, + attention_mask=None, + token_type_ids=None, + position_ids=None, + head_mask=None, + inputs_embeds=None, + start_positions=None, + end_positions=None, + output_attentions=None, + output_hidden_states=None, + ): + r""" + start_positions (:obj:`torch.LongTensor` of shape :obj:`(batch_size,)`, `optional`, defaults to :obj:`None`): + Labels for position (index) of the start of the labelled span for computing the token classification loss. + Positions are clamped to the length of the sequence (`sequence_length`). + Position outside of the sequence are not taken into account for computing the loss. + end_positions (:obj:`torch.LongTensor` of shape :obj:`(batch_size,)`, `optional`, defaults to :obj:`None`): + Labels for position (index) of the end of the labelled span for computing the token classification loss. + Positions are clamped to the length of the sequence (`sequence_length`). + Position outside of the sequence are not taken into account for computing the loss. + + Returns: + :obj:`tuple(torch.FloatTensor)` comprising various elements depending on the configuration (:class:`~transformers.BertConfig`) and inputs: + loss (:obj:`torch.FloatTensor` of shape :obj:`(1,)`, `optional`, returned when :obj:`labels` is provided): + Total span extraction loss is the sum of a Cross-Entropy for the start and end positions. + start_scores (:obj:`torch.FloatTensor` of shape :obj:`(batch_size, sequence_length,)`): + Span-start scores (before SoftMax). + end_scores (:obj:`torch.FloatTensor` of shape :obj:`(batch_size, sequence_length,)`): + Span-end scores (before SoftMax). + hidden_states (:obj:`tuple(torch.FloatTensor)`, `optional`, returned when ``output_hidden_states=True`` is passed or when ``config.output_hidden_states=True``): + Tuple of :obj:`torch.FloatTensor` (one for the output of the embeddings + one for the output of each layer) + of shape :obj:`(batch_size, sequence_length, hidden_size)`. + + Hidden-states of the model at the output of each layer plus the initial embedding outputs. + attentions (:obj:`tuple(torch.FloatTensor)`, `optional`, returned when ``output_attentions=True`` is passed or when ``config.output_attentions=True``): + Tuple of :obj:`torch.FloatTensor` (one for each layer) of shape + :obj:`(batch_size, num_heads, sequence_length, sequence_length)`. + + Attentions weights after the attention softmax, used to compute the weighted average in the self-attention + heads. + """ + + outputs = self.bert( + input_ids, + attention_mask=attention_mask, + token_type_ids=token_type_ids, + position_ids=position_ids, + head_mask=head_mask, + inputs_embeds=inputs_embeds, + output_attentions=output_attentions, + output_hidden_states=output_hidden_states, + ) + + sequence_output = outputs[0] + + logits = self.qa_outputs(sequence_output) + start_logits, end_logits = logits.split(1, dim=-1) + start_logits = start_logits.squeeze(-1) + end_logits = end_logits.squeeze(-1) + + outputs = (start_logits, end_logits,) + outputs[2:] + if start_positions is not None and end_positions is not None: + # If we are on multi-GPU, split add a dimension + if len(start_positions.size()) > 1: + start_positions = start_positions.squeeze(-1) + if len(end_positions.size()) > 1: + end_positions = end_positions.squeeze(-1) + # sometimes the start/end positions are outside our model inputs, we ignore these terms + ignored_index = start_logits.size(1) + start_positions.clamp_(0, ignored_index) + end_positions.clamp_(0, ignored_index) + + loss_fct = CrossEntropyLoss(ignore_index=ignored_index) + start_loss = loss_fct(start_logits, start_positions) + end_loss = loss_fct(end_logits, end_positions) + total_loss = (start_loss + end_loss) / 2 + outputs = (total_loss,) + outputs + + return outputs # (loss), start_logits, end_logits, (hidden_states), (attentions) diff --git a/LAVT-RIS/bert/modeling_utils.py b/LAVT-RIS/bert/modeling_utils.py new file mode 100644 index 0000000000000000000000000000000000000000..c5855e204247404cbfa6fed64fc930ca61d13780 --- /dev/null +++ b/LAVT-RIS/bert/modeling_utils.py @@ -0,0 +1,1268 @@ +# coding=utf-8 +# Copyright 2018 The Google AI Language Team Authors, Facebook AI Research authors and The HuggingFace Inc. team. +# Copyright (c) 2018, NVIDIA CORPORATION. All rights reserved. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +import inspect +import logging +import os +from typing import Callable, Dict, List, Optional, Tuple + +import torch +from torch import Tensor, device, dtype, nn +from torch.nn import CrossEntropyLoss +from torch.nn import functional as F + +from .activations import get_activation +from .configuration_utils import PretrainedConfig +from .file_utils import ( + DUMMY_INPUTS, + TF2_WEIGHTS_NAME, + TF_WEIGHTS_NAME, + WEIGHTS_NAME, + cached_path, + hf_bucket_url, + is_remote_url, +) +from .generation_utils import GenerationMixin + + +logger = logging.getLogger(__name__) + + +try: + from torch.nn import Identity +except ImportError: + # Older PyTorch compatibility + class Identity(nn.Module): + r"""A placeholder identity operator that is argument-insensitive. + """ + + def __init__(self, *args, **kwargs): + super().__init__() + + def forward(self, input): + return input + + +def find_pruneable_heads_and_indices( + heads: List, n_heads: int, head_size: int, already_pruned_heads: set +) -> Tuple[set, "torch.LongTensor"]: + mask = torch.ones(n_heads, head_size) + heads = set(heads) - already_pruned_heads # Convert to set and remove already pruned heads + for head in heads: + # Compute how many pruned heads are before the head and move the index accordingly + head = head - sum(1 if h < head else 0 for h in already_pruned_heads) + mask[head] = 0 + mask = mask.view(-1).contiguous().eq(1) + index: torch.LongTensor = torch.arange(len(mask))[mask].long() + return heads, index + + +class ModuleUtilsMixin: + """ + A few utilities for torch.nn.Modules, to be used as a mixin. + """ + + def num_parameters(self, only_trainable: bool = False) -> int: + """ + Get number of (optionally, trainable) parameters in the module. + """ + params = filter(lambda x: x.requires_grad, self.parameters()) if only_trainable else self.parameters() + return sum(p.numel() for p in params) + + @staticmethod + def _hook_rss_memory_pre_forward(module, *args, **kwargs): + try: + import psutil + except (ImportError): + raise ImportError("You need to install psutil (pip install psutil) to use memory tracing.") + + process = psutil.Process(os.getpid()) + mem = process.memory_info() + module.mem_rss_pre_forward = mem.rss + return None + + @staticmethod + def _hook_rss_memory_post_forward(module, *args, **kwargs): + try: + import psutil + except (ImportError): + raise ImportError("You need to install psutil (pip install psutil) to use memory tracing.") + + process = psutil.Process(os.getpid()) + mem = process.memory_info() + module.mem_rss_post_forward = mem.rss + mem_rss_diff = module.mem_rss_post_forward - module.mem_rss_pre_forward + module.mem_rss_diff = mem_rss_diff + (module.mem_rss_diff if hasattr(module, "mem_rss_diff") else 0) + return None + + def add_memory_hooks(self): + """ Add a memory hook before and after each sub-module forward pass to record increase in memory consumption. + Increase in memory consumption is stored in a `mem_rss_diff` attribute for each module and can be reset to zero with `model.reset_memory_hooks_state()` + """ + for module in self.modules(): + module.register_forward_pre_hook(self._hook_rss_memory_pre_forward) + module.register_forward_hook(self._hook_rss_memory_post_forward) + self.reset_memory_hooks_state() + + def reset_memory_hooks_state(self): + for module in self.modules(): + module.mem_rss_diff = 0 + module.mem_rss_post_forward = 0 + module.mem_rss_pre_forward = 0 + + @property + def device(self) -> device: + """ + Get torch.device from module, assuming that the whole module has one device. + """ + try: + return next(self.parameters()).device + except StopIteration: + # For nn.DataParallel compatibility in PyTorch 1.5 + + def find_tensor_attributes(module: nn.Module) -> List[Tuple[str, Tensor]]: + tuples = [(k, v) for k, v in module.__dict__.items() if torch.is_tensor(v)] + return tuples + + gen = self._named_members(get_members_fn=find_tensor_attributes) + first_tuple = next(gen) + return first_tuple[1].device + + @property + def dtype(self) -> dtype: + """ + Get torch.dtype from module, assuming that the whole module has one dtype. + """ + try: + return next(self.parameters()).dtype + except StopIteration: + # For nn.DataParallel compatibility in PyTorch 1.5 + + def find_tensor_attributes(module: nn.Module) -> List[Tuple[str, Tensor]]: + tuples = [(k, v) for k, v in module.__dict__.items() if torch.is_tensor(v)] + return tuples + + gen = self._named_members(get_members_fn=find_tensor_attributes) + first_tuple = next(gen) + return first_tuple[1].dtype + + def invert_attention_mask(self, encoder_attention_mask: Tensor) -> Tensor: + """type: torch.Tensor -> torch.Tensor""" + if encoder_attention_mask.dim() == 3: + encoder_extended_attention_mask = encoder_attention_mask[:, None, :, :] + if encoder_attention_mask.dim() == 2: + encoder_extended_attention_mask = encoder_attention_mask[:, None, None, :] + # T5 has a mask that can compare sequence ids, we can simulate this here with this transposition + # Cf. https://github.com/tensorflow/mesh/blob/8d2465e9bc93129b913b5ccc6a59aa97abd96ec6/mesh_tensorflow + # /transformer/transformer_layers.py#L270 + # encoder_extended_attention_mask = (encoder_extended_attention_mask == + # encoder_extended_attention_mask.transpose(-1, -2)) + encoder_extended_attention_mask = encoder_extended_attention_mask.to(dtype=self.dtype) # fp16 compatibility + + if self.dtype == torch.float16: + encoder_extended_attention_mask = (1.0 - encoder_extended_attention_mask) * -1e4 + elif self.dtype == torch.float32: + encoder_extended_attention_mask = (1.0 - encoder_extended_attention_mask) * -1e9 + else: + raise ValueError( + "{} not recognized. `dtype` should be set to either `torch.float32` or `torch.float16`".format( + self.dtype + ) + ) + + return encoder_extended_attention_mask + + def get_extended_attention_mask(self, attention_mask: Tensor, input_shape: Tuple, device: device) -> Tensor: + """Makes broadcastable attention mask and causal mask so that future and maked tokens are ignored. + + Arguments: + attention_mask: torch.Tensor with 1 indicating tokens to ATTEND to + input_shape: tuple, shape of input_ids + device: torch.Device, usually self.device + + Returns: + torch.Tensor with dtype of attention_mask.dtype + """ + # We can provide a self-attention mask of dimensions [batch_size, from_seq_length, to_seq_length] + # ourselves in which case we just need to make it broadcastable to all heads. + if attention_mask.dim() == 3: + extended_attention_mask = attention_mask[:, None, :, :] + elif attention_mask.dim() == 2: + # Provided a padding mask of dimensions [batch_size, seq_length] + # - if the model is a decoder, apply a causal mask in addition to the padding mask + # - if the model is an encoder, make the mask broadcastable to [batch_size, num_heads, seq_length, seq_length] + if self.config.is_decoder: + batch_size, seq_length = input_shape + seq_ids = torch.arange(seq_length, device=device) + causal_mask = seq_ids[None, None, :].repeat(batch_size, seq_length, 1) <= seq_ids[None, :, None] + # causal and attention masks must have same type with pytorch version < 1.3 + causal_mask = causal_mask.to(attention_mask.dtype) + extended_attention_mask = causal_mask[:, None, :, :] * attention_mask[:, None, None, :] + else: + extended_attention_mask = attention_mask[:, None, None, :] + else: + raise ValueError( + "Wrong shape for input_ids (shape {}) or attention_mask (shape {})".format( + input_shape, attention_mask.shape + ) + ) + + # Since attention_mask is 1.0 for positions we want to attend and 0.0 for + # masked positions, this operation will create a tensor which is 0.0 for + # positions we want to attend and -10000.0 for masked positions. + # Since we are adding it to the raw scores before the softmax, this is + # effectively the same as removing these entirely. + extended_attention_mask = extended_attention_mask.to(dtype=self.dtype) # fp16 compatibility + extended_attention_mask = (1.0 - extended_attention_mask) * -10000.0 + return extended_attention_mask + + def get_head_mask(self, head_mask: Tensor, num_hidden_layers: int, is_attention_chunked: bool = False) -> Tensor: + """ + # Prepare head mask if needed + # 1.0 in head_mask indicate we keep the head + attention_probs has shape bsz x n_heads x N x N + Arguments: + head_mask: torch.Tensor or None: has shape [num_heads] or [num_hidden_layers x num_heads] + num_hidden_layers: int + Returns: + Tensor of shape shape [num_hidden_layers x batch x num_heads x seq_length x seq_length] + or list with [None] for each layer + """ + if head_mask is not None: + head_mask = self._convert_head_mask_to_5d(head_mask, num_hidden_layers) + if is_attention_chunked is True: + head_mask = head_mask.unsqueeze(-1) + else: + head_mask = [None] * num_hidden_layers + + return head_mask + + def _convert_head_mask_to_5d(self, head_mask, num_hidden_layers): + """-> [num_hidden_layers x batch x num_heads x seq_length x seq_length]""" + if head_mask.dim() == 1: + head_mask = head_mask.unsqueeze(0).unsqueeze(0).unsqueeze(-1).unsqueeze(-1) + head_mask = head_mask.expand(num_hidden_layers, -1, -1, -1, -1) + elif head_mask.dim() == 2: + head_mask = head_mask.unsqueeze(1).unsqueeze(-1).unsqueeze(-1) # We can specify head_mask for each layer + assert head_mask.dim() == 5, f"head_mask.dim != 5, instead {head_mask.dim()}" + head_mask = head_mask.to(dtype=self.dtype) # switch to fload if need + fp16 compatibility + return head_mask + + +class PreTrainedModel(nn.Module, ModuleUtilsMixin, GenerationMixin): + r""" Base class for all models. + + :class:`~transformers.PreTrainedModel` takes care of storing the configuration of the models and handles methods for loading/downloading/saving models + as well as a few methods common to all models to (i) resize the input embeddings and (ii) prune heads in the self-attention heads. + + Class attributes (overridden by derived classes): + - ``config_class``: a class derived from :class:`~transformers.PretrainedConfig` to use as configuration class for this model architecture. + - ``load_tf_weights``: a python ``method`` for loading a TensorFlow checkpoint in a PyTorch model, taking as arguments: + + - ``model``: an instance of the relevant subclass of :class:`~transformers.PreTrainedModel`, + - ``config``: an instance of the relevant subclass of :class:`~transformers.PretrainedConfig`, + - ``path``: a path (string) to the TensorFlow checkpoint. + + - ``base_model_prefix``: a string indicating the attribute associated to the base model in derived classes of the same architecture adding modules on top of the base model. + """ + config_class = None + base_model_prefix = "" + + @property + def dummy_inputs(self): + """ Dummy inputs to do a forward pass in the network. + + Returns: + torch.Tensor with dummy inputs + """ + return {"input_ids": torch.tensor(DUMMY_INPUTS)} + + def __init__(self, config, *inputs, **kwargs): + super().__init__() + if not isinstance(config, PretrainedConfig): + raise ValueError( + "Parameter config in `{}(config)` should be an instance of class `PretrainedConfig`. " + "To create a model from a pretrained model use " + "`model = {}.from_pretrained(PRETRAINED_MODEL_NAME)`".format( + self.__class__.__name__, self.__class__.__name__ + ) + ) + # Save config in model + self.config = config + + @property + def base_model(self): + return getattr(self, self.base_model_prefix, self) + + def get_input_embeddings(self): + """ + Returns the model's input embeddings. + + Returns: + :obj:`nn.Module`: + A torch module mapping vocabulary to hidden states. + """ + base_model = getattr(self, self.base_model_prefix, self) + if base_model is not self: + return base_model.get_input_embeddings() + else: + raise NotImplementedError + + def set_input_embeddings(self, value: nn.Module): + """ + Set model's input embeddings + + Args: + value (:obj:`nn.Module`): + A module mapping vocabulary to hidden states. + """ + base_model = getattr(self, self.base_model_prefix, self) + if base_model is not self: + base_model.set_input_embeddings(value) + else: + raise NotImplementedError + + def get_output_embeddings(self): + """ + Returns the model's output embeddings. + + Returns: + :obj:`nn.Module`: + A torch module mapping hidden states to vocabulary. + """ + return None # Overwrite for models with output embeddings + + def tie_weights(self): + """ + Tie the weights between the input embeddings and the output embeddings. + If the `torchscript` flag is set in the configuration, can't handle parameter sharing so we are cloning + the weights instead. + """ + output_embeddings = self.get_output_embeddings() + if output_embeddings is not None: + self._tie_or_clone_weights(output_embeddings, self.get_input_embeddings()) + + def _tie_or_clone_weights(self, output_embeddings, input_embeddings): + """ Tie or clone module weights depending of whether we are using TorchScript or not + """ + if self.config.torchscript: + output_embeddings.weight = nn.Parameter(input_embeddings.weight.clone()) + else: + output_embeddings.weight = input_embeddings.weight + + if getattr(output_embeddings, "bias", None) is not None: + output_embeddings.bias.data = torch.nn.functional.pad( + output_embeddings.bias.data, + (0, output_embeddings.weight.shape[0] - output_embeddings.bias.shape[0],), + "constant", + 0, + ) + if hasattr(output_embeddings, "out_features") and hasattr(input_embeddings, "num_embeddings"): + output_embeddings.out_features = input_embeddings.num_embeddings + + def resize_token_embeddings(self, new_num_tokens: Optional[int] = None): + """ Resize input token embeddings matrix of the model if new_num_tokens != config.vocab_size. + Take care of tying weights embeddings afterwards if the model class has a `tie_weights()` method. + + Arguments: + + new_num_tokens: (`optional`) int: + New number of tokens in the embedding matrix. Increasing the size will add newly initialized vectors at the end. Reducing the size will remove vectors from the end. + If not provided or None: does nothing and just returns a pointer to the input tokens ``torch.nn.Embeddings`` Module of the model. + + Return: ``torch.nn.Embeddings`` + Pointer to the input tokens Embeddings Module of the model + """ + base_model = getattr(self, self.base_model_prefix, self) # get the base model if needed + model_embeds = base_model._resize_token_embeddings(new_num_tokens) + if new_num_tokens is None: + return model_embeds + + # Update base model and current model config + self.config.vocab_size = new_num_tokens + base_model.vocab_size = new_num_tokens + + # Tie weights again if needed + self.tie_weights() + + return model_embeds + + def _resize_token_embeddings(self, new_num_tokens): + old_embeddings = self.get_input_embeddings() + new_embeddings = self._get_resized_embeddings(old_embeddings, new_num_tokens) + self.set_input_embeddings(new_embeddings) + return self.get_input_embeddings() + + def _get_resized_embeddings( + self, old_embeddings: torch.nn.Embedding, new_num_tokens: Optional[int] = None + ) -> torch.nn.Embedding: + """ Build a resized Embedding Module from a provided token Embedding Module. + Increasing the size will add newly initialized vectors at the end + Reducing the size will remove vectors from the end + + Args: + old_embeddings: ``torch.nn.Embedding`` + Old embeddings to be resized. + new_num_tokens: (`optional`) int + New number of tokens in the embedding matrix. + Increasing the size will add newly initialized vectors at the end + Reducing the size will remove vectors from the end + If not provided or None: return the provided token Embedding Module. + Return: ``torch.nn.Embedding`` + Pointer to the resized Embedding Module or the old Embedding Module if new_num_tokens is None + """ + if new_num_tokens is None: + return old_embeddings + + old_num_tokens, old_embedding_dim = old_embeddings.weight.size() + if old_num_tokens == new_num_tokens: + return old_embeddings + + # Build new embeddings + new_embeddings = nn.Embedding(new_num_tokens, old_embedding_dim) + new_embeddings.to(old_embeddings.weight.device) + + # initialize all new embeddings (in particular added tokens) + self._init_weights(new_embeddings) + + # Copy token embeddings from the previous weights + num_tokens_to_copy = min(old_num_tokens, new_num_tokens) + new_embeddings.weight.data[:num_tokens_to_copy, :] = old_embeddings.weight.data[:num_tokens_to_copy, :] + + return new_embeddings + + def init_weights(self): + """ Initialize and prunes weights if needed. """ + # Initialize weights + self.apply(self._init_weights) + + # Prune heads if needed + if self.config.pruned_heads: + self.prune_heads(self.config.pruned_heads) + + # Tie weights if needed + self.tie_weights() + + def prune_heads(self, heads_to_prune: Dict): + """ Prunes heads of the base model. + + Arguments: + + heads_to_prune: dict with keys being selected layer indices (`int`) and associated values being the list of heads to prune in said layer (list of `int`). + E.g. {1: [0, 2], 2: [2, 3]} will prune heads 0 and 2 on layer 1 and heads 2 and 3 on layer 2. + """ + # save new sets of pruned heads as union of previously stored pruned heads and newly pruned heads + for layer, heads in heads_to_prune.items(): + union_heads = set(self.config.pruned_heads.get(layer, [])) | set(heads) + self.config.pruned_heads[layer] = list(union_heads) # Unfortunately we have to store it as list for JSON + + self.base_model._prune_heads(heads_to_prune) + + def save_pretrained(self, save_directory): + """ Save a model and its configuration file to a directory, so that it + can be re-loaded using the `:func:`~transformers.PreTrainedModel.from_pretrained`` class method. + + Arguments: + save_directory: directory to which to save. + """ + if os.path.isfile(save_directory): + logger.error("Provided path ({}) should be a directory, not a file".format(save_directory)) + return + os.makedirs(save_directory, exist_ok=True) + + # Only save the model itself if we are using distributed training + model_to_save = self.module if hasattr(self, "module") else self + + # Attach architecture to the config + model_to_save.config.architectures = [model_to_save.__class__.__name__] + + # If we save using the predefined names, we can load using `from_pretrained` + output_model_file = os.path.join(save_directory, WEIGHTS_NAME) + + if getattr(self.config, "xla_device", False): + import torch_xla.core.xla_model as xm + + if xm.is_master_ordinal(): + # Save configuration file + model_to_save.config.save_pretrained(save_directory) + # xm.save takes care of saving only from master + xm.save(model_to_save.state_dict(), output_model_file) + else: + model_to_save.config.save_pretrained(save_directory) + torch.save(model_to_save.state_dict(), output_model_file) + + logger.info("Model weights saved in {}".format(output_model_file)) + + @classmethod + def from_pretrained(cls, pretrained_model_name_or_path, *model_args, **kwargs): + r"""Instantiate a pretrained pytorch model from a pre-trained model configuration. + + The model is set in evaluation mode by default using ``model.eval()`` (Dropout modules are deactivated) + To train the model, you should first set it back in training mode with ``model.train()`` + + The warning ``Weights from XXX not initialized from pretrained model`` means that the weights of XXX do not come pre-trained with the rest of the model. + It is up to you to train those weights with a downstream fine-tuning task. + + The warning ``Weights from XXX not used in YYY`` means that the layer XXX is not used by YYY, therefore those weights are discarded. + + Parameters: + pretrained_model_name_or_path: either: + - a string with the `shortcut name` of a pre-trained model to load from cache or download, e.g.: ``bert-base-uncased``. + - a string with the `identifier name` of a pre-trained model that was user-uploaded to our S3, e.g.: ``dbmdz/bert-base-german-cased``. + - a path to a `directory` containing model weights saved using :func:`~transformers.PreTrainedModel.save_pretrained`, e.g.: ``./my_model_directory/``. + - a path or url to a `tensorflow index checkpoint file` (e.g. `./tf_model/model.ckpt.index`). In this case, ``from_tf`` should be set to True and a configuration object should be provided as ``config`` argument. This loading path is slower than converting the TensorFlow checkpoint in a PyTorch model using the provided conversion scripts and loading the PyTorch model afterwards. + - None if you are both providing the configuration and state dictionary (resp. with keyword arguments ``config`` and ``state_dict``) + + model_args: (`optional`) Sequence of positional arguments: + All remaning positional arguments will be passed to the underlying model's ``__init__`` method + + config: (`optional`) one of: + - an instance of a class derived from :class:`~transformers.PretrainedConfig`, or + - a string valid as input to :func:`~transformers.PretrainedConfig.from_pretrained()` + + Configuration for the model to use instead of an automatically loaded configuation. Configuration can be automatically loaded when: + - the model is a model provided by the library (loaded with the ``shortcut-name`` string of a pretrained model), or + - the model was saved using :func:`~transformers.PreTrainedModel.save_pretrained` and is reloaded by suppling the save directory. + - the model is loaded by suppling a local directory as ``pretrained_model_name_or_path`` and a configuration JSON file named `config.json` is found in the directory. + + state_dict: (`optional`) dict: + an optional state dictionnary for the model to use instead of a state dictionary loaded from saved weights file. + This option can be used if you want to create a model from a pretrained configuration but load your own weights. + In this case though, you should check if using :func:`~transformers.PreTrainedModel.save_pretrained` and :func:`~transformers.PreTrainedModel.from_pretrained` is not a simpler option. + + cache_dir: (`optional`) string: + Path to a directory in which a downloaded pre-trained model + configuration should be cached if the standard cache should not be used. + + force_download: (`optional`) boolean, default False: + Force to (re-)download the model weights and configuration files and override the cached versions if they exists. + + resume_download: (`optional`) boolean, default False: + Do not delete incompletely recieved file. Attempt to resume the download if such a file exists. + + proxies: (`optional`) dict, default None: + A dictionary of proxy servers to use by protocol or endpoint, e.g.: {'http': 'foo.bar:3128', 'http://hostname': 'foo.bar:4012'}. + The proxies are used on each request. + + output_loading_info: (`optional`) boolean: + Set to ``True`` to also return a dictionnary containing missing keys, unexpected keys and error messages. + + kwargs: (`optional`) Remaining dictionary of keyword arguments: + Can be used to update the configuration object (after it being loaded) and initiate the model. (e.g. ``output_attention=True``). Behave differently depending on whether a `config` is provided or automatically loaded: + + - If a configuration is provided with ``config``, ``**kwargs`` will be directly passed to the underlying model's ``__init__`` method (we assume all relevant updates to the configuration have already been done) + - If a configuration is not provided, ``kwargs`` will be first passed to the configuration class initialization function (:func:`~transformers.PretrainedConfig.from_pretrained`). Each key of ``kwargs`` that corresponds to a configuration attribute will be used to override said attribute with the supplied ``kwargs`` value. Remaining keys that do not correspond to any configuration attribute will be passed to the underlying model's ``__init__`` function. + + Examples:: + + # For example purposes. Not runnable. + model = BertModel.from_pretrained('bert-base-uncased') # Download model and configuration from S3 and cache. + model = BertModel.from_pretrained('./test/saved_model/') # E.g. model was saved using `save_pretrained('./test/saved_model/')` + model = BertModel.from_pretrained('bert-base-uncased', output_attention=True) # Update configuration during loading + assert model.config.output_attention == True + # Loading from a TF checkpoint file instead of a PyTorch model (slower) + config = BertConfig.from_json_file('./tf_model/my_tf_model_config.json') + model = BertModel.from_pretrained('./tf_model/my_tf_checkpoint.ckpt.index', from_tf=True, config=config) + + """ + config = kwargs.pop("config", None) + state_dict = kwargs.pop("state_dict", None) + cache_dir = kwargs.pop("cache_dir", None) + from_tf = kwargs.pop("from_tf", False) + force_download = kwargs.pop("force_download", False) + resume_download = kwargs.pop("resume_download", False) + proxies = kwargs.pop("proxies", None) + output_loading_info = kwargs.pop("output_loading_info", False) + local_files_only = kwargs.pop("local_files_only", False) + use_cdn = kwargs.pop("use_cdn", True) + + # Load config if we don't provide a configuration + if not isinstance(config, PretrainedConfig): + config_path = config if config is not None else pretrained_model_name_or_path + config, model_kwargs = cls.config_class.from_pretrained( + config_path, + *model_args, + cache_dir=cache_dir, + return_unused_kwargs=True, + force_download=force_download, + resume_download=resume_download, + proxies=proxies, + local_files_only=local_files_only, + **kwargs, + ) + else: + model_kwargs = kwargs + + # Load model + if pretrained_model_name_or_path is not None: + if os.path.isdir(pretrained_model_name_or_path): + if from_tf and os.path.isfile(os.path.join(pretrained_model_name_or_path, TF_WEIGHTS_NAME + ".index")): + # Load from a TF 1.0 checkpoint + archive_file = os.path.join(pretrained_model_name_or_path, TF_WEIGHTS_NAME + ".index") + elif from_tf and os.path.isfile(os.path.join(pretrained_model_name_or_path, TF2_WEIGHTS_NAME)): + # Load from a TF 2.0 checkpoint + archive_file = os.path.join(pretrained_model_name_or_path, TF2_WEIGHTS_NAME) + elif os.path.isfile(os.path.join(pretrained_model_name_or_path, WEIGHTS_NAME)): + # Load from a PyTorch checkpoint + archive_file = os.path.join(pretrained_model_name_or_path, WEIGHTS_NAME) + else: + raise EnvironmentError( + "Error no file named {} found in directory {} or `from_tf` set to False".format( + [WEIGHTS_NAME, TF2_WEIGHTS_NAME, TF_WEIGHTS_NAME + ".index"], + pretrained_model_name_or_path, + ) + ) + elif os.path.isfile(pretrained_model_name_or_path) or is_remote_url(pretrained_model_name_or_path): + archive_file = pretrained_model_name_or_path + elif os.path.isfile(pretrained_model_name_or_path + ".index"): + assert ( + from_tf + ), "We found a TensorFlow checkpoint at {}, please set from_tf to True to load from this checkpoint".format( + pretrained_model_name_or_path + ".index" + ) + archive_file = pretrained_model_name_or_path + ".index" + else: + archive_file = hf_bucket_url( + pretrained_model_name_or_path, + filename=(TF2_WEIGHTS_NAME if from_tf else WEIGHTS_NAME), + use_cdn=use_cdn, + ) + + try: + # Load from URL or cache if already cached + resolved_archive_file = cached_path( + archive_file, + cache_dir=cache_dir, + force_download=force_download, + proxies=proxies, + resume_download=resume_download, + local_files_only=local_files_only, + ) + if resolved_archive_file is None: + raise EnvironmentError + except EnvironmentError: + msg = ( + f"Can't load weights for '{pretrained_model_name_or_path}'. Make sure that:\n\n" + f"- '{pretrained_model_name_or_path}' is a correct model identifier listed on 'https://huggingface.co/models'\n\n" + f"- or '{pretrained_model_name_or_path}' is the correct path to a directory containing a file named one of {WEIGHTS_NAME}, {TF2_WEIGHTS_NAME}, {TF_WEIGHTS_NAME}.\n\n" + ) + raise EnvironmentError(msg) + + if resolved_archive_file == archive_file: + logger.info("loading weights file {}".format(archive_file)) + else: + logger.info("loading weights file {} from cache at {}".format(archive_file, resolved_archive_file)) + else: + resolved_archive_file = None + + # Instantiate model. + model = cls(config, *model_args, **model_kwargs) + + if state_dict is None and not from_tf: + try: + state_dict = torch.load(resolved_archive_file, map_location="cpu") + except Exception: + raise OSError( + "Unable to load weights from pytorch checkpoint file. " + "If you tried to load a PyTorch model from a TF 2.0 checkpoint, please set from_tf=True. " + ) + + missing_keys = [] + unexpected_keys = [] + error_msgs = [] + + if from_tf: + if resolved_archive_file.endswith(".index"): + # Load from a TensorFlow 1.X checkpoint - provided by original authors + model = cls.load_tf_weights(model, config, resolved_archive_file[:-6]) # Remove the '.index' + else: + # Load from our TensorFlow 2.0 checkpoints + try: + from transformers import load_tf2_checkpoint_in_pytorch_model + + model = load_tf2_checkpoint_in_pytorch_model(model, resolved_archive_file, allow_missing_keys=True) + except ImportError: + logger.error( + "Loading a TensorFlow model in PyTorch, requires both PyTorch and TensorFlow to be installed. Please see " + "https://pytorch.org/ and https://www.tensorflow.org/install/ for installation instructions." + ) + raise + else: + # Convert old format to new format if needed from a PyTorch state_dict + old_keys = [] + new_keys = [] + for key in state_dict.keys(): + new_key = None + if "gamma" in key: + new_key = key.replace("gamma", "weight") + if "beta" in key: + new_key = key.replace("beta", "bias") + if new_key: + old_keys.append(key) + new_keys.append(new_key) + for old_key, new_key in zip(old_keys, new_keys): + state_dict[new_key] = state_dict.pop(old_key) + + # copy state_dict so _load_from_state_dict can modify it + metadata = getattr(state_dict, "_metadata", None) + state_dict = state_dict.copy() + if metadata is not None: + state_dict._metadata = metadata + + ############################################################################################## + # Print out state_dict's contents: keys + ''' + for key, _ in state_dict.items(): + print(key) + ''' + ############################################################################################## + + + # PyTorch's `_load_from_state_dict` does not copy parameters in a module's descendants + # so we need to apply the function recursively. + def load(module: nn.Module, prefix=""): + local_metadata = {} if metadata is None else metadata.get(prefix[:-1], {}) + module._load_from_state_dict( + state_dict, prefix, local_metadata, True, missing_keys, unexpected_keys, error_msgs, + ) + for name, child in module._modules.items(): + if child is not None: + load(child, prefix + name + ".") + + # Make sure we are able to load base models as well as derived models (with heads) + start_prefix = "" + model_to_load = model + has_prefix_module = any(s.startswith(cls.base_model_prefix) for s in state_dict.keys()) + if not hasattr(model, cls.base_model_prefix) and has_prefix_module: + start_prefix = cls.base_model_prefix + "." + if hasattr(model, cls.base_model_prefix) and not has_prefix_module: + model_to_load = getattr(model, cls.base_model_prefix) + + load(model_to_load, prefix=start_prefix) + + if model.__class__.__name__ != model_to_load.__class__.__name__: + base_model_state_dict = model_to_load.state_dict().keys() + head_model_state_dict_without_base_prefix = [ + key.split(cls.base_model_prefix + ".")[-1] for key in model.state_dict().keys() + ] + + missing_keys.extend(head_model_state_dict_without_base_prefix - base_model_state_dict) + + if len(unexpected_keys) > 0: + logger.warning( + f"Some weights of the model checkpoint at {pretrained_model_name_or_path} were not used when " + f"initializing {model.__class__.__name__}: {unexpected_keys}\n" + f"- This IS expected if you are initializing {model.__class__.__name__} from the checkpoint of a model trained on another task " + f"or with another architecture (e.g. initializing a BertForSequenceClassification model from a BertForPretraining model).\n" + f"- This IS NOT expected if you are initializing {model.__class__.__name__} from the checkpoint of a model that you expect " + f"to be exactly identical (initializing a BertForSequenceClassification model from a BertForSequenceClassification model)." + ) + else: + logger.info(f"All model checkpoint weights were used when initializing {model.__class__.__name__}.\n") + if len(missing_keys) > 0: + logger.warning( + f"Some weights of {model.__class__.__name__} were not initialized from the model checkpoint at {pretrained_model_name_or_path} " + f"and are newly initialized: {missing_keys}\n" + f"You should probably TRAIN this model on a down-stream task to be able to use it for predictions and inference." + ) + else: + logger.info( + f"All the weights of {model.__class__.__name__} were initialized from the model checkpoint at {pretrained_model_name_or_path}.\n" + f"If your task is similar to the task the model of the ckeckpoint was trained on, " + f"you can already use {model.__class__.__name__} for predictions without further training." + ) + if len(error_msgs) > 0: + raise RuntimeError( + "Error(s) in loading state_dict for {}:\n\t{}".format( + model.__class__.__name__, "\n\t".join(error_msgs) + ) + ) + model.tie_weights() # make sure token embedding weights are still tied if needed + + # Set model in evaluation mode to deactivate DropOut modules by default + model.eval() + + if output_loading_info: + loading_info = { + "missing_keys": missing_keys, + "unexpected_keys": unexpected_keys, + "error_msgs": error_msgs, + } + return model, loading_info + + if hasattr(config, "xla_device") and config.xla_device: + import torch_xla.core.xla_model as xm + + model = xm.send_cpu_data_to_device(model, xm.xla_device()) + model.to(xm.xla_device()) + + return model + + +class Conv1D(nn.Module): + def __init__(self, nf, nx): + """ Conv1D layer as defined by Radford et al. for OpenAI GPT (and also used in GPT-2) + Basically works like a Linear layer but the weights are transposed + """ + super().__init__() + self.nf = nf + w = torch.empty(nx, nf) + nn.init.normal_(w, std=0.02) + self.weight = nn.Parameter(w) + self.bias = nn.Parameter(torch.zeros(nf)) + + def forward(self, x): + size_out = x.size()[:-1] + (self.nf,) + x = torch.addmm(self.bias, x.view(-1, x.size(-1)), self.weight) + x = x.view(*size_out) + return x + + +class PoolerStartLogits(nn.Module): + """ Compute SQuAD start_logits from sequence hidden states. """ + + def __init__(self, config): + super().__init__() + self.dense = nn.Linear(config.hidden_size, 1) + + def forward(self, hidden_states, p_mask=None): + """ Args: + **p_mask**: (`optional`) ``torch.FloatTensor`` of shape `(batch_size, seq_len)` + invalid position mask such as query and special symbols (PAD, SEP, CLS) + 1.0 means token should be masked. + """ + x = self.dense(hidden_states).squeeze(-1) + + if p_mask is not None: + if next(self.parameters()).dtype == torch.float16: + x = x * (1 - p_mask) - 65500 * p_mask + else: + x = x * (1 - p_mask) - 1e30 * p_mask + + return x + + +class PoolerEndLogits(nn.Module): + """ Compute SQuAD end_logits from sequence hidden states and start token hidden state. + """ + + def __init__(self, config): + super().__init__() + self.dense_0 = nn.Linear(config.hidden_size * 2, config.hidden_size) + self.activation = nn.Tanh() + self.LayerNorm = nn.LayerNorm(config.hidden_size, eps=config.layer_norm_eps) + self.dense_1 = nn.Linear(config.hidden_size, 1) + + def forward(self, hidden_states, start_states=None, start_positions=None, p_mask=None): + """ Args: + One of ``start_states``, ``start_positions`` should be not None. + If both are set, ``start_positions`` overrides ``start_states``. + + **start_states**: ``torch.LongTensor`` of shape identical to hidden_states + hidden states of the first tokens for the labeled span. + **start_positions**: ``torch.LongTensor`` of shape ``(batch_size,)`` + position of the first token for the labeled span: + **p_mask**: (`optional`) ``torch.FloatTensor`` of shape ``(batch_size, seq_len)`` + Mask of invalid position such as query and special symbols (PAD, SEP, CLS) + 1.0 means token should be masked. + """ + assert ( + start_states is not None or start_positions is not None + ), "One of start_states, start_positions should be not None" + if start_positions is not None: + slen, hsz = hidden_states.shape[-2:] + start_positions = start_positions[:, None, None].expand(-1, -1, hsz) # shape (bsz, 1, hsz) + start_states = hidden_states.gather(-2, start_positions) # shape (bsz, 1, hsz) + start_states = start_states.expand(-1, slen, -1) # shape (bsz, slen, hsz) + + x = self.dense_0(torch.cat([hidden_states, start_states], dim=-1)) + x = self.activation(x) + x = self.LayerNorm(x) + x = self.dense_1(x).squeeze(-1) + + if p_mask is not None: + if next(self.parameters()).dtype == torch.float16: + x = x * (1 - p_mask) - 65500 * p_mask + else: + x = x * (1 - p_mask) - 1e30 * p_mask + + return x + + +class PoolerAnswerClass(nn.Module): + """ Compute SQuAD 2.0 answer class from classification and start tokens hidden states. """ + + def __init__(self, config): + super().__init__() + self.dense_0 = nn.Linear(config.hidden_size * 2, config.hidden_size) + self.activation = nn.Tanh() + self.dense_1 = nn.Linear(config.hidden_size, 1, bias=False) + + def forward(self, hidden_states, start_states=None, start_positions=None, cls_index=None): + """ + Args: + One of ``start_states``, ``start_positions`` should be not None. + If both are set, ``start_positions`` overrides ``start_states``. + + **start_states**: ``torch.LongTensor`` of shape identical to ``hidden_states``. + hidden states of the first tokens for the labeled span. + **start_positions**: ``torch.LongTensor`` of shape ``(batch_size,)`` + position of the first token for the labeled span. + **cls_index**: torch.LongTensor of shape ``(batch_size,)`` + position of the CLS token. If None, take the last token. + + note(Original repo): + no dependency on end_feature so that we can obtain one single `cls_logits` + for each sample + """ + hsz = hidden_states.shape[-1] + assert ( + start_states is not None or start_positions is not None + ), "One of start_states, start_positions should be not None" + if start_positions is not None: + start_positions = start_positions[:, None, None].expand(-1, -1, hsz) # shape (bsz, 1, hsz) + start_states = hidden_states.gather(-2, start_positions).squeeze(-2) # shape (bsz, hsz) + + if cls_index is not None: + cls_index = cls_index[:, None, None].expand(-1, -1, hsz) # shape (bsz, 1, hsz) + cls_token_state = hidden_states.gather(-2, cls_index).squeeze(-2) # shape (bsz, hsz) + else: + cls_token_state = hidden_states[:, -1, :] # shape (bsz, hsz) + + x = self.dense_0(torch.cat([start_states, cls_token_state], dim=-1)) + x = self.activation(x) + x = self.dense_1(x).squeeze(-1) + + return x + + +class SQuADHead(nn.Module): + r""" A SQuAD head inspired by XLNet. + + Parameters: + config (:class:`~transformers.XLNetConfig`): Model configuration class with all the parameters of the model. + + Inputs: + **hidden_states**: ``torch.FloatTensor`` of shape ``(batch_size, seq_len, hidden_size)`` + hidden states of sequence tokens + **start_positions**: ``torch.LongTensor`` of shape ``(batch_size,)`` + position of the first token for the labeled span. + **end_positions**: ``torch.LongTensor`` of shape ``(batch_size,)`` + position of the last token for the labeled span. + **cls_index**: torch.LongTensor of shape ``(batch_size,)`` + position of the CLS token. If None, take the last token. + **is_impossible**: ``torch.LongTensor`` of shape ``(batch_size,)`` + Whether the question has a possible answer in the paragraph or not. + **p_mask**: (`optional`) ``torch.FloatTensor`` of shape ``(batch_size, seq_len)`` + Mask of invalid position such as query and special symbols (PAD, SEP, CLS) + 1.0 means token should be masked. + + Outputs: `Tuple` comprising various elements depending on the configuration (config) and inputs: + **loss**: (`optional`, returned if both ``start_positions`` and ``end_positions`` are provided) ``torch.FloatTensor`` of shape ``(1,)``: + Classification loss as the sum of start token, end token (and is_impossible if provided) classification losses. + **start_top_log_probs**: (`optional`, returned if ``start_positions`` or ``end_positions`` is not provided) + ``torch.FloatTensor`` of shape ``(batch_size, config.start_n_top)`` + Log probabilities for the top config.start_n_top start token possibilities (beam-search). + **start_top_index**: (`optional`, returned if ``start_positions`` or ``end_positions`` is not provided) + ``torch.LongTensor`` of shape ``(batch_size, config.start_n_top)`` + Indices for the top config.start_n_top start token possibilities (beam-search). + **end_top_log_probs**: (`optional`, returned if ``start_positions`` or ``end_positions`` is not provided) + ``torch.FloatTensor`` of shape ``(batch_size, config.start_n_top * config.end_n_top)`` + Log probabilities for the top ``config.start_n_top * config.end_n_top`` end token possibilities (beam-search). + **end_top_index**: (`optional`, returned if ``start_positions`` or ``end_positions`` is not provided) + ``torch.LongTensor`` of shape ``(batch_size, config.start_n_top * config.end_n_top)`` + Indices for the top ``config.start_n_top * config.end_n_top`` end token possibilities (beam-search). + **cls_logits**: (`optional`, returned if ``start_positions`` or ``end_positions`` is not provided) + ``torch.FloatTensor`` of shape ``(batch_size,)`` + Log probabilities for the ``is_impossible`` label of the answers. + """ + + def __init__(self, config): + super().__init__() + self.start_n_top = config.start_n_top + self.end_n_top = config.end_n_top + + self.start_logits = PoolerStartLogits(config) + self.end_logits = PoolerEndLogits(config) + self.answer_class = PoolerAnswerClass(config) + + def forward( + self, hidden_states, start_positions=None, end_positions=None, cls_index=None, is_impossible=None, p_mask=None, + ): + outputs = () + + start_logits = self.start_logits(hidden_states, p_mask=p_mask) + + if start_positions is not None and end_positions is not None: + # If we are on multi-GPU, let's remove the dimension added by batch splitting + for x in (start_positions, end_positions, cls_index, is_impossible): + if x is not None and x.dim() > 1: + x.squeeze_(-1) + + # during training, compute the end logits based on the ground truth of the start position + end_logits = self.end_logits(hidden_states, start_positions=start_positions, p_mask=p_mask) + + loss_fct = CrossEntropyLoss() + start_loss = loss_fct(start_logits, start_positions) + end_loss = loss_fct(end_logits, end_positions) + total_loss = (start_loss + end_loss) / 2 + + if cls_index is not None and is_impossible is not None: + # Predict answerability from the representation of CLS and START + cls_logits = self.answer_class(hidden_states, start_positions=start_positions, cls_index=cls_index) + loss_fct_cls = nn.BCEWithLogitsLoss() + cls_loss = loss_fct_cls(cls_logits, is_impossible) + + # note(zhiliny): by default multiply the loss by 0.5 so that the scale is comparable to start_loss and end_loss + total_loss += cls_loss * 0.5 + + outputs = (total_loss,) + outputs + + else: + # during inference, compute the end logits based on beam search + bsz, slen, hsz = hidden_states.size() + start_log_probs = F.softmax(start_logits, dim=-1) # shape (bsz, slen) + + start_top_log_probs, start_top_index = torch.topk( + start_log_probs, self.start_n_top, dim=-1 + ) # shape (bsz, start_n_top) + start_top_index_exp = start_top_index.unsqueeze(-1).expand(-1, -1, hsz) # shape (bsz, start_n_top, hsz) + start_states = torch.gather(hidden_states, -2, start_top_index_exp) # shape (bsz, start_n_top, hsz) + start_states = start_states.unsqueeze(1).expand(-1, slen, -1, -1) # shape (bsz, slen, start_n_top, hsz) + + hidden_states_expanded = hidden_states.unsqueeze(2).expand_as( + start_states + ) # shape (bsz, slen, start_n_top, hsz) + p_mask = p_mask.unsqueeze(-1) if p_mask is not None else None + end_logits = self.end_logits(hidden_states_expanded, start_states=start_states, p_mask=p_mask) + end_log_probs = F.softmax(end_logits, dim=1) # shape (bsz, slen, start_n_top) + + end_top_log_probs, end_top_index = torch.topk( + end_log_probs, self.end_n_top, dim=1 + ) # shape (bsz, end_n_top, start_n_top) + end_top_log_probs = end_top_log_probs.view(-1, self.start_n_top * self.end_n_top) + end_top_index = end_top_index.view(-1, self.start_n_top * self.end_n_top) + + start_states = torch.einsum("blh,bl->bh", hidden_states, start_log_probs) + cls_logits = self.answer_class(hidden_states, start_states=start_states, cls_index=cls_index) + + outputs = (start_top_log_probs, start_top_index, end_top_log_probs, end_top_index, cls_logits,) + outputs + + # return start_top_log_probs, start_top_index, end_top_log_probs, end_top_index, cls_logits + # or (if labels are provided) (total_loss,) + return outputs + + +class SequenceSummary(nn.Module): + r""" Compute a single vector summary of a sequence hidden states according to various possibilities: + Args of the config class: + summary_type: + - 'last' => [default] take the last token hidden state (like XLNet) + - 'first' => take the first token hidden state (like Bert) + - 'mean' => take the mean of all tokens hidden states + - 'cls_index' => supply a Tensor of classification token position (GPT/GPT-2) + - 'attn' => Not implemented now, use multi-head attention + summary_use_proj: Add a projection after the vector extraction + summary_proj_to_labels: If True, the projection outputs to config.num_labels classes (otherwise to hidden_size). Default: False. + summary_activation: 'tanh' or another string => add an activation to the output, Other => no activation. Default + summary_first_dropout: Add a dropout before the projection and activation + summary_last_dropout: Add a dropout after the projection and activation + """ + + def __init__(self, config: PretrainedConfig): + super().__init__() + + self.summary_type = getattr(config, "summary_type", "last") + if self.summary_type == "attn": + # We should use a standard multi-head attention module with absolute positional embedding for that. + # Cf. https://github.com/zihangdai/xlnet/blob/master/modeling.py#L253-L276 + # We can probably just use the multi-head attention module of PyTorch >=1.1.0 + raise NotImplementedError + + self.summary = Identity() + if hasattr(config, "summary_use_proj") and config.summary_use_proj: + if hasattr(config, "summary_proj_to_labels") and config.summary_proj_to_labels and config.num_labels > 0: + num_classes = config.num_labels + else: + num_classes = config.hidden_size + self.summary = nn.Linear(config.hidden_size, num_classes) + + activation_string = getattr(config, "summary_activation", None) + self.activation: Callable = (get_activation(activation_string) if activation_string else Identity()) + + self.first_dropout = Identity() + if hasattr(config, "summary_first_dropout") and config.summary_first_dropout > 0: + self.first_dropout = nn.Dropout(config.summary_first_dropout) + + self.last_dropout = Identity() + if hasattr(config, "summary_last_dropout") and config.summary_last_dropout > 0: + self.last_dropout = nn.Dropout(config.summary_last_dropout) + + def forward(self, hidden_states, cls_index=None): + """ hidden_states: float Tensor in shape [bsz, ..., seq_len, hidden_size], the hidden-states of the last layer. + cls_index: [optional] position of the classification token if summary_type == 'cls_index', + shape (bsz,) or more generally (bsz, ...) where ... are optional leading dimensions of hidden_states. + if summary_type == 'cls_index' and cls_index is None: + we take the last token of the sequence as classification token + """ + if self.summary_type == "last": + output = hidden_states[:, -1] + elif self.summary_type == "first": + output = hidden_states[:, 0] + elif self.summary_type == "mean": + output = hidden_states.mean(dim=1) + elif self.summary_type == "cls_index": + if cls_index is None: + cls_index = torch.full_like(hidden_states[..., :1, :], hidden_states.shape[-2] - 1, dtype=torch.long,) + else: + cls_index = cls_index.unsqueeze(-1).unsqueeze(-1) + cls_index = cls_index.expand((-1,) * (cls_index.dim() - 1) + (hidden_states.size(-1),)) + # shape of cls_index: (bsz, XX, 1, hidden_size) where XX are optional leading dim of hidden_states + output = hidden_states.gather(-2, cls_index).squeeze(-2) # shape (bsz, XX, hidden_size) + elif self.summary_type == "attn": + raise NotImplementedError + + output = self.first_dropout(output) + output = self.summary(output) + output = self.activation(output) + output = self.last_dropout(output) + + return output + + +def prune_linear_layer(layer, index, dim=0): + """ Prune a linear layer (a model parameters) to keep only entries in index. + Return the pruned layer as a new layer with requires_grad=True. + Used to remove heads. + """ + index = index.to(layer.weight.device) + W = layer.weight.index_select(dim, index).clone().detach() + if layer.bias is not None: + if dim == 1: + b = layer.bias.clone().detach() + else: + b = layer.bias[index].clone().detach() + new_size = list(layer.weight.size()) + new_size[dim] = len(index) + new_layer = nn.Linear(new_size[1], new_size[0], bias=layer.bias is not None).to(layer.weight.device) + new_layer.weight.requires_grad = False + new_layer.weight.copy_(W.contiguous()) + new_layer.weight.requires_grad = True + if layer.bias is not None: + new_layer.bias.requires_grad = False + new_layer.bias.copy_(b.contiguous()) + new_layer.bias.requires_grad = True + return new_layer + + +def prune_conv1d_layer(layer, index, dim=1): + """ Prune a Conv1D layer (a model parameters) to keep only entries in index. + A Conv1D work as a Linear layer (see e.g. BERT) but the weights are transposed. + Return the pruned layer as a new layer with requires_grad=True. + Used to remove heads. + """ + index = index.to(layer.weight.device) + W = layer.weight.index_select(dim, index).clone().detach() + if dim == 0: + b = layer.bias.clone().detach() + else: + b = layer.bias[index].clone().detach() + new_size = list(layer.weight.size()) + new_size[dim] = len(index) + new_layer = Conv1D(new_size[1], new_size[0]).to(layer.weight.device) + new_layer.weight.requires_grad = False + new_layer.weight.copy_(W.contiguous()) + new_layer.weight.requires_grad = True + new_layer.bias.requires_grad = False + new_layer.bias.copy_(b.contiguous()) + new_layer.bias.requires_grad = True + return new_layer + + +def prune_layer(layer, index, dim=None): + """ Prune a Conv1D or nn.Linear layer (a model parameters) to keep only entries in index. + Return the pruned layer as a new layer with requires_grad=True. + Used to remove heads. + """ + if isinstance(layer, nn.Linear): + return prune_linear_layer(layer, index, dim=0 if dim is None else dim) + elif isinstance(layer, Conv1D): + return prune_conv1d_layer(layer, index, dim=1 if dim is None else dim) + else: + raise ValueError("Can't prune layer of class {}".format(layer.__class__)) + + +def apply_chunking_to_forward( + chunk_size: int, chunk_dim: int, forward_fn: Callable[..., torch.Tensor], *input_tensors +) -> torch.Tensor: + """ + This function chunks the `input_tensors` into smaller input tensor parts of size `chunk_size` over the dimension `chunk_dim`. + It then applies a layer `forward_fn` to each chunk independently to save memory. + If the `forward_fn` is independent across the `chunk_dim` this function will yield the + same result as not applying it. + + Args: + chunk_size: int - the chunk size of a chunked tensor. `num_chunks` = `len(input_tensors[0]) / chunk_size` + chunk_dim: int - the dimension over which the input_tensors should be chunked + forward_fn: fn - the forward fn of the model + input_tensors: tuple(torch.Tensor) - the input tensors of `forward_fn` which are chunked + Returns: + a Tensor with the same shape the foward_fn would have given if applied + + + Examples:: + + # rename the usual forward() fn to forward_chunk() + def forward_chunk(self, hidden_states): + hidden_states = self.decoder(hidden_states) + return hidden_states + + # implement a chunked forward function + def forward(self, hidden_states): + return apply_chunking_to_forward(self.chunk_size_lm_head, self.seq_len_dim, self.forward_chunk, hidden_states) + """ + + assert len(input_tensors) > 0, "{} has to be a tuple/list of tensors".format(input_tensors) + tensor_shape = input_tensors[0].shape + assert all( + input_tensor.shape == tensor_shape for input_tensor in input_tensors + ), "All input tenors have to be of the same shape" + + # inspect.signature exist since python 3.5 and is a python method -> no problem with backward compability + num_args_in_forward_chunk_fn = len(inspect.signature(forward_fn).parameters) + assert num_args_in_forward_chunk_fn == len( + input_tensors + ), "forward_chunk_fn expects {} arguments, but only {} input tensors are given".format( + num_args_in_forward_chunk_fn, len(input_tensors) + ) + + if chunk_size > 0: + assert ( + input_tensors[0].shape[chunk_dim] % chunk_size == 0 + ), "The dimension to be chunked {} has to be a multiple of the chunk size {}".format( + input_tensors[0].shape[chunk_dim], chunk_size + ) + + num_chunks = input_tensors[0].shape[chunk_dim] // chunk_size + + # chunk input tensor into tuples + input_tensors_chunks = tuple(input_tensor.chunk(num_chunks, dim=chunk_dim) for input_tensor in input_tensors) + # apply forward fn to every tuple + output_chunks = tuple(forward_fn(*input_tensors_chunk) for input_tensors_chunk in zip(*input_tensors_chunks)) + # concatenate output at same dimension + return torch.cat(output_chunks, dim=chunk_dim) + + return forward_fn(*input_tensors) diff --git a/LAVT-RIS/bert/tokenization_bert.py b/LAVT-RIS/bert/tokenization_bert.py new file mode 100644 index 0000000000000000000000000000000000000000..972e1733163522359750dddedf6dea885085b2ca --- /dev/null +++ b/LAVT-RIS/bert/tokenization_bert.py @@ -0,0 +1,545 @@ +# coding=utf-8 +# Copyright 2018 The Google AI Language Team Authors and The HuggingFace Inc. team. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +"""Tokenization classes.""" + + +import collections +import logging +import os +import unicodedata +from typing import List, Optional + +from .tokenization_utils import PreTrainedTokenizer, _is_control, _is_punctuation, _is_whitespace + + +logger = logging.getLogger(__name__) + +VOCAB_FILES_NAMES = {"vocab_file": "vocab.txt"} + +PRETRAINED_VOCAB_FILES_MAP = { + "vocab_file": { + "bert-base-uncased": "https://s3.amazonaws.com/models.huggingface.co/bert/bert-base-uncased-vocab.txt", + "bert-large-uncased": "https://s3.amazonaws.com/models.huggingface.co/bert/bert-large-uncased-vocab.txt", + "bert-base-cased": "https://s3.amazonaws.com/models.huggingface.co/bert/bert-base-cased-vocab.txt", + "bert-large-cased": "https://s3.amazonaws.com/models.huggingface.co/bert/bert-large-cased-vocab.txt", + "bert-base-multilingual-uncased": "https://s3.amazonaws.com/models.huggingface.co/bert/bert-base-multilingual-uncased-vocab.txt", + "bert-base-multilingual-cased": "https://s3.amazonaws.com/models.huggingface.co/bert/bert-base-multilingual-cased-vocab.txt", + "bert-base-chinese": "https://s3.amazonaws.com/models.huggingface.co/bert/bert-base-chinese-vocab.txt", + "bert-base-german-cased": "https://int-deepset-models-bert.s3.eu-central-1.amazonaws.com/pytorch/bert-base-german-cased-vocab.txt", + "bert-large-uncased-whole-word-masking": "https://s3.amazonaws.com/models.huggingface.co/bert/bert-large-uncased-whole-word-masking-vocab.txt", + "bert-large-cased-whole-word-masking": "https://s3.amazonaws.com/models.huggingface.co/bert/bert-large-cased-whole-word-masking-vocab.txt", + "bert-large-uncased-whole-word-masking-finetuned-squad": "https://s3.amazonaws.com/models.huggingface.co/bert/bert-large-uncased-whole-word-masking-finetuned-squad-vocab.txt", + "bert-large-cased-whole-word-masking-finetuned-squad": "https://s3.amazonaws.com/models.huggingface.co/bert/bert-large-cased-whole-word-masking-finetuned-squad-vocab.txt", + "bert-base-cased-finetuned-mrpc": "https://s3.amazonaws.com/models.huggingface.co/bert/bert-base-cased-finetuned-mrpc-vocab.txt", + "bert-base-german-dbmdz-cased": "https://s3.amazonaws.com/models.huggingface.co/bert/bert-base-german-dbmdz-cased-vocab.txt", + "bert-base-german-dbmdz-uncased": "https://s3.amazonaws.com/models.huggingface.co/bert/bert-base-german-dbmdz-uncased-vocab.txt", + "TurkuNLP/bert-base-finnish-cased-v1": "https://s3.amazonaws.com/models.huggingface.co/bert/TurkuNLP/bert-base-finnish-cased-v1/vocab.txt", + "TurkuNLP/bert-base-finnish-uncased-v1": "https://s3.amazonaws.com/models.huggingface.co/bert/TurkuNLP/bert-base-finnish-uncased-v1/vocab.txt", + "wietsedv/bert-base-dutch-cased": "https://s3.amazonaws.com/models.huggingface.co/bert/wietsedv/bert-base-dutch-cased/vocab.txt", + } +} + +PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES = { + "bert-base-uncased": 512, + "bert-large-uncased": 512, + "bert-base-cased": 512, + "bert-large-cased": 512, + "bert-base-multilingual-uncased": 512, + "bert-base-multilingual-cased": 512, + "bert-base-chinese": 512, + "bert-base-german-cased": 512, + "bert-large-uncased-whole-word-masking": 512, + "bert-large-cased-whole-word-masking": 512, + "bert-large-uncased-whole-word-masking-finetuned-squad": 512, + "bert-large-cased-whole-word-masking-finetuned-squad": 512, + "bert-base-cased-finetuned-mrpc": 512, + "bert-base-german-dbmdz-cased": 512, + "bert-base-german-dbmdz-uncased": 512, + "TurkuNLP/bert-base-finnish-cased-v1": 512, + "TurkuNLP/bert-base-finnish-uncased-v1": 512, + "wietsedv/bert-base-dutch-cased": 512, +} + +PRETRAINED_INIT_CONFIGURATION = { + "bert-base-uncased": {"do_lower_case": True}, + "bert-large-uncased": {"do_lower_case": True}, + "bert-base-cased": {"do_lower_case": False}, + "bert-large-cased": {"do_lower_case": False}, + "bert-base-multilingual-uncased": {"do_lower_case": True}, + "bert-base-multilingual-cased": {"do_lower_case": False}, + "bert-base-chinese": {"do_lower_case": False}, + "bert-base-german-cased": {"do_lower_case": False}, + "bert-large-uncased-whole-word-masking": {"do_lower_case": True}, + "bert-large-cased-whole-word-masking": {"do_lower_case": False}, + "bert-large-uncased-whole-word-masking-finetuned-squad": {"do_lower_case": True}, + "bert-large-cased-whole-word-masking-finetuned-squad": {"do_lower_case": False}, + "bert-base-cased-finetuned-mrpc": {"do_lower_case": False}, + "bert-base-german-dbmdz-cased": {"do_lower_case": False}, + "bert-base-german-dbmdz-uncased": {"do_lower_case": True}, + "TurkuNLP/bert-base-finnish-cased-v1": {"do_lower_case": False}, + "TurkuNLP/bert-base-finnish-uncased-v1": {"do_lower_case": True}, + "wietsedv/bert-base-dutch-cased": {"do_lower_case": False}, +} + + +def load_vocab(vocab_file): + """Loads a vocabulary file into a dictionary.""" + vocab = collections.OrderedDict() + with open(vocab_file, "r", encoding="utf-8") as reader: + tokens = reader.readlines() + for index, token in enumerate(tokens): + token = token.rstrip("\n") + vocab[token] = index + return vocab + + +def whitespace_tokenize(text): + """Runs basic whitespace cleaning and splitting on a piece of text.""" + text = text.strip() + if not text: + return [] + tokens = text.split() + return tokens + + +class BertTokenizer(PreTrainedTokenizer): + r""" + Constructs a BERT tokenizer. Based on WordPiece. + + This tokenizer inherits from :class:`~transformers.PreTrainedTokenizer` which contains most of the methods. Users + should refer to the superclass for more information regarding methods. + + Args: + vocab_file (:obj:`string`): + File containing the vocabulary. + do_lower_case (:obj:`bool`, `optional`, defaults to :obj:`True`): + Whether to lowercase the input when tokenizing. + do_basic_tokenize (:obj:`bool`, `optional`, defaults to :obj:`True`): + Whether to do basic tokenization before WordPiece. + never_split (:obj:`Iterable`, `optional`, defaults to :obj:`None`): + Collection of tokens which will never be split during tokenization. Only has an effect when + :obj:`do_basic_tokenize=True` + unk_token (:obj:`string`, `optional`, defaults to "[UNK]"): + The unknown token. A token that is not in the vocabulary cannot be converted to an ID and is set to be this + token instead. + sep_token (:obj:`string`, `optional`, defaults to "[SEP]"): + The separator token, which is used when building a sequence from multiple sequences, e.g. two sequences + for sequence classification or for a text and a question for question answering. + It is also used as the last token of a sequence built with special tokens. + pad_token (:obj:`string`, `optional`, defaults to "[PAD]"): + The token used for padding, for example when batching sequences of different lengths. + cls_token (:obj:`string`, `optional`, defaults to "[CLS]"): + The classifier token which is used when doing sequence classification (classification of the whole + sequence instead of per-token classification). It is the first token of the sequence when built with + special tokens. + mask_token (:obj:`string`, `optional`, defaults to "[MASK]"): + The token used for masking values. This is the token used when training this model with masked language + modeling. This is the token which the model will try to predict. + tokenize_chinese_chars (:obj:`bool`, `optional`, defaults to :obj:`True`): + Whether to tokenize Chinese characters. + This should likely be deactivated for Japanese: + see: https://github.com/huggingface/transformers/issues/328 + """ + + vocab_files_names = VOCAB_FILES_NAMES + pretrained_vocab_files_map = PRETRAINED_VOCAB_FILES_MAP + pretrained_init_configuration = PRETRAINED_INIT_CONFIGURATION + max_model_input_sizes = PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES + + def __init__( + self, + vocab_file, + do_lower_case=True, + do_basic_tokenize=True, + never_split=None, + unk_token="[UNK]", + sep_token="[SEP]", + pad_token="[PAD]", + cls_token="[CLS]", + mask_token="[MASK]", + tokenize_chinese_chars=True, + **kwargs + ): + super().__init__( + unk_token=unk_token, + sep_token=sep_token, + pad_token=pad_token, + cls_token=cls_token, + mask_token=mask_token, + **kwargs, + ) + + if not os.path.isfile(vocab_file): + raise ValueError( + "Can't find a vocabulary file at path '{}'. To load the vocabulary from a Google pretrained " + "model use `tokenizer = BertTokenizer.from_pretrained(PRETRAINED_MODEL_NAME)`".format(vocab_file) + ) + self.vocab = load_vocab(vocab_file) + self.ids_to_tokens = collections.OrderedDict([(ids, tok) for tok, ids in self.vocab.items()]) + self.do_basic_tokenize = do_basic_tokenize + if do_basic_tokenize: + self.basic_tokenizer = BasicTokenizer( + do_lower_case=do_lower_case, never_split=never_split, tokenize_chinese_chars=tokenize_chinese_chars + ) + self.wordpiece_tokenizer = WordpieceTokenizer(vocab=self.vocab, unk_token=self.unk_token) + + @property + def vocab_size(self): + return len(self.vocab) + + def get_vocab(self): + return dict(self.vocab, **self.added_tokens_encoder) + + def _tokenize(self, text): + split_tokens = [] + if self.do_basic_tokenize: + for token in self.basic_tokenizer.tokenize(text, never_split=self.all_special_tokens): + + # If the token is part of the never_split set + if token in self.basic_tokenizer.never_split: + split_tokens.append(token) + else: + split_tokens += self.wordpiece_tokenizer.tokenize(token) + else: + split_tokens = self.wordpiece_tokenizer.tokenize(text) + return split_tokens + + def _convert_token_to_id(self, token): + """ Converts a token (str) in an id using the vocab. """ + return self.vocab.get(token, self.vocab.get(self.unk_token)) + + def _convert_id_to_token(self, index): + """Converts an index (integer) in a token (str) using the vocab.""" + return self.ids_to_tokens.get(index, self.unk_token) + + def convert_tokens_to_string(self, tokens): + """ Converts a sequence of tokens (string) in a single string. """ + out_string = " ".join(tokens).replace(" ##", "").strip() + return out_string + + def build_inputs_with_special_tokens( + self, token_ids_0: List[int], token_ids_1: Optional[List[int]] = None + ) -> List[int]: + """ + Build model inputs from a sequence or a pair of sequence for sequence classification tasks + by concatenating and adding special tokens. + A BERT sequence has the following format: + + - single sequence: ``[CLS] X [SEP]`` + - pair of sequences: ``[CLS] A [SEP] B [SEP]`` + + Args: + token_ids_0 (:obj:`List[int]`): + List of IDs to which the special tokens will be added + token_ids_1 (:obj:`List[int]`, `optional`, defaults to :obj:`None`): + Optional second list of IDs for sequence pairs. + + Returns: + :obj:`List[int]`: list of `input IDs <../glossary.html#input-ids>`__ with the appropriate special tokens. + """ + if token_ids_1 is None: + return [self.cls_token_id] + token_ids_0 + [self.sep_token_id] + cls = [self.cls_token_id] + sep = [self.sep_token_id] + return cls + token_ids_0 + sep + token_ids_1 + sep + + def get_special_tokens_mask( + self, token_ids_0: List[int], token_ids_1: Optional[List[int]] = None, already_has_special_tokens: bool = False + ) -> List[int]: + """ + Retrieves sequence ids from a token list that has no special tokens added. This method is called when adding + special tokens using the tokenizer ``prepare_for_model`` method. + + Args: + token_ids_0 (:obj:`List[int]`): + List of ids. + token_ids_1 (:obj:`List[int]`, `optional`, defaults to :obj:`None`): + Optional second list of IDs for sequence pairs. + already_has_special_tokens (:obj:`bool`, `optional`, defaults to :obj:`False`): + Set to True if the token list is already formatted with special tokens for the model + + Returns: + :obj:`List[int]`: A list of integers in the range [0, 1]: 1 for a special token, 0 for a sequence token. + """ + + if already_has_special_tokens: + if token_ids_1 is not None: + raise ValueError( + "You should not supply a second sequence if the provided sequence of " + "ids is already formated with special tokens for the model." + ) + return list(map(lambda x: 1 if x in [self.sep_token_id, self.cls_token_id] else 0, token_ids_0)) + + if token_ids_1 is not None: + return [1] + ([0] * len(token_ids_0)) + [1] + ([0] * len(token_ids_1)) + [1] + return [1] + ([0] * len(token_ids_0)) + [1] + + def create_token_type_ids_from_sequences( + self, token_ids_0: List[int], token_ids_1: Optional[List[int]] = None + ) -> List[int]: + """ + Creates a mask from the two sequences passed to be used in a sequence-pair classification task. + A BERT sequence pair mask has the following format: + + :: + + 0 0 0 0 0 0 0 0 0 0 0 1 1 1 1 1 1 1 1 1 + | first sequence | second sequence | + + if token_ids_1 is None, only returns the first portion of the mask (0's). + + Args: + token_ids_0 (:obj:`List[int]`): + List of ids. + token_ids_1 (:obj:`List[int]`, `optional`, defaults to :obj:`None`): + Optional second list of IDs for sequence pairs. + + Returns: + :obj:`List[int]`: List of `token type IDs <../glossary.html#token-type-ids>`_ according to the given + sequence(s). + """ + sep = [self.sep_token_id] + cls = [self.cls_token_id] + if token_ids_1 is None: + return len(cls + token_ids_0 + sep) * [0] + return len(cls + token_ids_0 + sep) * [0] + len(token_ids_1 + sep) * [1] + + def save_vocabulary(self, vocab_path): + """ + Save the sentencepiece vocabulary (copy original file) and special tokens file to a directory. + + Args: + vocab_path (:obj:`str`): + The directory in which to save the vocabulary. + + Returns: + :obj:`Tuple(str)`: Paths to the files saved. + """ + index = 0 + if os.path.isdir(vocab_path): + vocab_file = os.path.join(vocab_path, VOCAB_FILES_NAMES["vocab_file"]) + else: + vocab_file = vocab_path + with open(vocab_file, "w", encoding="utf-8") as writer: + for token, token_index in sorted(self.vocab.items(), key=lambda kv: kv[1]): + if index != token_index: + logger.warning( + "Saving vocabulary to {}: vocabulary indices are not consecutive." + " Please check that the vocabulary is not corrupted!".format(vocab_file) + ) + index = token_index + writer.write(token + "\n") + index += 1 + return (vocab_file,) + + +class BasicTokenizer(object): + """Runs basic tokenization (punctuation splitting, lower casing, etc.).""" + + def __init__(self, do_lower_case=True, never_split=None, tokenize_chinese_chars=True): + """ Constructs a BasicTokenizer. + + Args: + **do_lower_case**: Whether to lower case the input. + **never_split**: (`optional`) list of str + Kept for backward compatibility purposes. + Now implemented directly at the base class level (see :func:`PreTrainedTokenizer.tokenize`) + List of token not to split. + **tokenize_chinese_chars**: (`optional`) boolean (default True) + Whether to tokenize Chinese characters. + This should likely be deactivated for Japanese: + see: https://github.com/huggingface/pytorch-pretrained-BERT/issues/328 + """ + if never_split is None: + never_split = [] + self.do_lower_case = do_lower_case + self.never_split = set(never_split) + self.tokenize_chinese_chars = tokenize_chinese_chars + + def tokenize(self, text, never_split=None): + """ Basic Tokenization of a piece of text. + Split on "white spaces" only, for sub-word tokenization, see WordPieceTokenizer. + + Args: + **never_split**: (`optional`) list of str + Kept for backward compatibility purposes. + Now implemented directly at the base class level (see :func:`PreTrainedTokenizer.tokenize`) + List of token not to split. + """ + # union() returns a new set by concatenating the two sets. + never_split = self.never_split.union(set(never_split)) if never_split else self.never_split + + # This was added on November 1st, 2018 for the multilingual and Chinese + # models. This is also applied to the English models now, but it doesn't + # matter since the English models were not trained on any Chinese data + # and generally don't have any Chinese data in them (there are Chinese + # characters in the vocabulary because Wikipedia does have some Chinese + # words in the English Wikipedia.). + if self.tokenize_chinese_chars: + text = self._tokenize_chinese_chars(text) + orig_tokens = whitespace_tokenize(text) + split_tokens = [] + for token in orig_tokens: + if self.do_lower_case and token not in never_split: + token = token.lower() + token = self._run_strip_accents(token) + split_tokens.extend(self._run_split_on_punc(token, never_split)) + + output_tokens = whitespace_tokenize(" ".join(split_tokens)) + return output_tokens + + def _run_strip_accents(self, text): + """Strips accents from a piece of text.""" + text = unicodedata.normalize("NFD", text) + output = [] + for char in text: + cat = unicodedata.category(char) + if cat == "Mn": + continue + output.append(char) + return "".join(output) + + def _run_split_on_punc(self, text, never_split=None): + """Splits punctuation on a piece of text.""" + if never_split is not None and text in never_split: + return [text] + chars = list(text) + i = 0 + start_new_word = True + output = [] + while i < len(chars): + char = chars[i] + if _is_punctuation(char): + output.append([char]) + start_new_word = True + else: + if start_new_word: + output.append([]) + start_new_word = False + output[-1].append(char) + i += 1 + + return ["".join(x) for x in output] + + def _tokenize_chinese_chars(self, text): + """Adds whitespace around any CJK character.""" + output = [] + for char in text: + cp = ord(char) + if self._is_chinese_char(cp): + output.append(" ") + output.append(char) + output.append(" ") + else: + output.append(char) + return "".join(output) + + def _is_chinese_char(self, cp): + """Checks whether CP is the codepoint of a CJK character.""" + # This defines a "chinese character" as anything in the CJK Unicode block: + # https://en.wikipedia.org/wiki/CJK_Unified_Ideographs_(Unicode_block) + # + # Note that the CJK Unicode block is NOT all Japanese and Korean characters, + # despite its name. The modern Korean Hangul alphabet is a different block, + # as is Japanese Hiragana and Katakana. Those alphabets are used to write + # space-separated words, so they are not treated specially and handled + # like the all of the other languages. + if ( + (cp >= 0x4E00 and cp <= 0x9FFF) + or (cp >= 0x3400 and cp <= 0x4DBF) # + or (cp >= 0x20000 and cp <= 0x2A6DF) # + or (cp >= 0x2A700 and cp <= 0x2B73F) # + or (cp >= 0x2B740 and cp <= 0x2B81F) # + or (cp >= 0x2B820 and cp <= 0x2CEAF) # + or (cp >= 0xF900 and cp <= 0xFAFF) + or (cp >= 0x2F800 and cp <= 0x2FA1F) # + ): # + return True + + return False + + def _clean_text(self, text): + """Performs invalid character removal and whitespace cleanup on text.""" + output = [] + for char in text: + cp = ord(char) + if cp == 0 or cp == 0xFFFD or _is_control(char): + continue + if _is_whitespace(char): + output.append(" ") + else: + output.append(char) + return "".join(output) + + +class WordpieceTokenizer(object): + """Runs WordPiece tokenization.""" + + def __init__(self, vocab, unk_token, max_input_chars_per_word=100): + self.vocab = vocab + self.unk_token = unk_token + self.max_input_chars_per_word = max_input_chars_per_word + + def tokenize(self, text): + """Tokenizes a piece of text into its word pieces. + + This uses a greedy longest-match-first algorithm to perform tokenization + using the given vocabulary. + + For example: + input = "unaffable" + output = ["un", "##aff", "##able"] + + Args: + text: A single token or whitespace separated tokens. This should have + already been passed through `BasicTokenizer`. + + Returns: + A list of wordpiece tokens. + """ + + output_tokens = [] + for token in whitespace_tokenize(text): + chars = list(token) + if len(chars) > self.max_input_chars_per_word: + output_tokens.append(self.unk_token) + continue + + is_bad = False + start = 0 + sub_tokens = [] + while start < len(chars): + end = len(chars) + cur_substr = None + while start < end: + substr = "".join(chars[start:end]) + if start > 0: + substr = "##" + substr + if substr in self.vocab: + cur_substr = substr + break + end -= 1 + if cur_substr is None: + is_bad = True + break + sub_tokens.append(cur_substr) + start = end + + if is_bad: + output_tokens.append(self.unk_token) + else: + output_tokens.extend(sub_tokens) + return output_tokens + diff --git a/LAVT-RIS/bert/tokenization_utils.py b/LAVT-RIS/bert/tokenization_utils.py new file mode 100644 index 0000000000000000000000000000000000000000..d878210f407d8fb10226d9e4435c761a1f7483fc --- /dev/null +++ b/LAVT-RIS/bert/tokenization_utils.py @@ -0,0 +1,723 @@ +# coding=utf-8 +# Copyright 2020 The HuggingFace Inc. team. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +""" Tokenization classes for python tokenizers. + For fast tokenizers (provided by HuggingFace's tokenizers library) see tokenization_utils_fast.py +""" + +import itertools +import logging +import re +import unicodedata +from typing import Dict, List, Optional, Tuple, Union + +from .file_utils import add_end_docstrings +from .tokenization_utils_base import ( + ENCODE_KWARGS_DOCSTRING, + ENCODE_PLUS_ADDITIONAL_KWARGS_DOCSTRING, + AddedToken, + BatchEncoding, + EncodedInput, + EncodedInputPair, + PaddingStrategy, + PreTokenizedInput, + PreTokenizedInputPair, + PreTrainedTokenizerBase, + TensorType, + TextInput, + TextInputPair, + TruncationStrategy, +) + + +logger = logging.getLogger(__name__) + + +def _is_whitespace(char): + """Checks whether `chars` is a whitespace character.""" + # \t, \n, and \r are technically contorl characters but we treat them + # as whitespace since they are generally considered as such. + if char == " " or char == "\t" or char == "\n" or char == "\r": + return True + cat = unicodedata.category(char) + if cat == "Zs": + return True + return False + + +def _is_control(char): + """Checks whether `chars` is a control character.""" + # These are technically control characters but we count them as whitespace + # characters. + if char == "\t" or char == "\n" or char == "\r": + return False + cat = unicodedata.category(char) + if cat.startswith("C"): + return True + return False + + +def _is_punctuation(char): + """Checks whether `chars` is a punctuation character.""" + cp = ord(char) + # We treat all non-letter/number ASCII as punctuation. + # Characters such as "^", "$", and "`" are not in the Unicode + # Punctuation class but we treat them as punctuation anyways, for + # consistency. + if (cp >= 33 and cp <= 47) or (cp >= 58 and cp <= 64) or (cp >= 91 and cp <= 96) or (cp >= 123 and cp <= 126): + return True + cat = unicodedata.category(char) + if cat.startswith("P"): + return True + return False + + +def _is_end_of_word(text): + """Checks whether the last character in text is one of a punctuation, control or whitespace character.""" + last_char = text[-1] + return bool(_is_control(last_char) | _is_punctuation(last_char) | _is_whitespace(last_char)) + + +def _is_start_of_word(text): + """Checks whether the first character in text is one of a punctuation, control or whitespace character.""" + first_char = text[0] + return bool(_is_control(first_char) | _is_punctuation(first_char) | _is_whitespace(first_char)) + + +class PreTrainedTokenizer(PreTrainedTokenizerBase): + """ Base class for all slow tokenizers. + + Handle all the shared methods for tokenization and special tokens as well as methods + downloading/caching/loading pretrained tokenizers as well as adding tokens to the vocabulary. + + This class also contain the added tokens in a unified way on top of all tokenizers so we don't + have to handle the specific vocabulary augmentation methods of the various underlying + dictionary structures (BPE, sentencepiece...). + + Class attributes (overridden by derived classes): + + - ``vocab_files_names``: a python ``dict`` with, as keys, the ``__init__`` keyword name of each vocabulary file + required by the model, and as associated values, the filename for saving the associated file (string). + - ``pretrained_vocab_files_map``: a python ``dict of dict`` the high-level keys + being the ``__init__`` keyword name of each vocabulary file required by the model, the low-level being the + `short-cut-names` (string) of the pretrained models with, as associated values, the `url` (string) to the + associated pretrained vocabulary file. + - ``max_model_input_sizes``: a python ``dict`` with, as keys, the `short-cut-names` (string) of the pretrained + models, and as associated values, the maximum length of the sequence inputs of this model, or None if the + model has no maximum input size. + - ``pretrained_init_configuration``: a python ``dict`` with, as keys, the `short-cut-names` (string) of the + pretrained models, and as associated values, a dictionnary of specific arguments to pass to the + ``__init__``method of the tokenizer class for this pretrained model when loading the tokenizer with the + ``from_pretrained()`` method. + + Args: + - ``model_max_length``: (`Optional`) int: the maximum length in number of tokens for the inputs to the transformer model. + When the tokenizer is loaded with `from_pretrained`, this will be set to the value stored for the associated + model in ``max_model_input_sizes`` (see above). If no value is provided, will default to VERY_LARGE_INTEGER (`int(1e30)`). + no associated max_length can be found in ``max_model_input_sizes``. + - ``padding_side``: (`Optional`) string: the side on which the model should have padding applied. + Should be selected between ['right', 'left'] + - ``model_input_names``: (`Optional`) List[string]: the list of the forward pass inputs accepted by the + model ("token_type_ids", "attention_mask"...). + - ``bos_token``: (`Optional`) string: a beginning of sentence token. + Will be associated to ``self.bos_token`` and ``self.bos_token_id`` + - ``eos_token``: (`Optional`) string: an end of sentence token. + Will be associated to ``self.eos_token`` and ``self.eos_token_id`` + - ``unk_token``: (`Optional`) string: an unknown token. + Will be associated to ``self.unk_token`` and ``self.unk_token_id`` + - ``sep_token``: (`Optional`) string: a separation token (e.g. to separate context and query in an input sequence). + Will be associated to ``self.sep_token`` and ``self.sep_token_id`` + - ``pad_token``: (`Optional`) string: a padding token. + Will be associated to ``self.pad_token`` and ``self.pad_token_id`` + - ``cls_token``: (`Optional`) string: a classification token (e.g. to extract a summary of an input sequence + leveraging self-attention along the full depth of the model). + Will be associated to ``self.cls_token`` and ``self.cls_token_id`` + - ``mask_token``: (`Optional`) string: a masking token (e.g. when training a model with masked-language + modeling). Will be associated to ``self.mask_token`` and ``self.mask_token_id`` + - ``additional_special_tokens``: (`Optional`) list: a list of additional special tokens. + Adding all special tokens here ensure they won't be split by the tokenization process. + Will be associated to ``self.additional_special_tokens`` and ``self.additional_special_tokens_ids`` + + + .. automethod:: __call__ + """ + + def __init__(self, **kwargs): + super().__init__(**kwargs) + + # Added tokens - We store this for both slow and fast tokenizers + # until the serialization of Fast tokenizers is updated + self.added_tokens_encoder: Dict[str, int] = {} + self.added_tokens_decoder: Dict[int, str] = {} + self.unique_no_split_tokens: List[str] = [] + + @property + def is_fast(self) -> bool: + return False + + @property + def vocab_size(self) -> int: + """ Size of the base vocabulary (without the added tokens) """ + raise NotImplementedError + + def get_vocab(self): + """ Returns the vocabulary as a dict of {token: index} pairs. `tokenizer.get_vocab()[token]` is equivalent to `tokenizer.convert_tokens_to_ids(token)` when `token` is in the vocab. """ + raise NotImplementedError() + + def get_added_vocab(self) -> Dict[str, int]: + return self.added_tokens_encoder + + def __len__(self): + """ Size of the full vocabulary with the added tokens """ + return self.vocab_size + len(self.added_tokens_encoder) + + def _add_tokens(self, new_tokens: Union[List[str], List[AddedToken]], special_tokens=False) -> int: + """ + Add a list of new tokens to the tokenizer class. If the new tokens are not in the + vocabulary, they are added to it with indices starting from length of the current vocabulary. + + Args: + new_tokens: string or list of string. Each string is a token to add. Tokens are only added if they are not + already in the vocabulary (tested by checking if the tokenizer assign the index of the ``unk_token`` to them). + + Returns: + Number of tokens added to the vocabulary. + + Examples:: + + # Let's see how to increase the vocabulary of Bert model and tokenizer + tokenizer = BertTokenizer.from_pretrained('bert-base-uncased') + model = BertModel.from_pretrained('bert-base-uncased') + + num_added_toks = tokenizer.add_tokens(['new_tok1', 'my_new-tok2']) + print('We have added', num_added_toks, 'tokens') + model.resize_token_embeddings(len(tokenizer)) # Notice: resize_token_embeddings expect to receive the full size of the new vocabulary, i.e. the length of the tokenizer. + """ + new_tokens = [str(tok) for tok in new_tokens] + + tokens_to_add = [] + for token in new_tokens: + assert isinstance(token, str) + if not special_tokens and self.init_kwargs.get("do_lower_case", False): + token = token.lower() + if ( + token != self.unk_token + and self.convert_tokens_to_ids(token) == self.convert_tokens_to_ids(self.unk_token) + and token not in tokens_to_add + ): + tokens_to_add.append(token) + if self.verbose: + logger.info("Adding %s to the vocabulary", token) + + added_tok_encoder = dict((tok, len(self) + i) for i, tok in enumerate(tokens_to_add)) + added_tok_decoder = {v: k for k, v in added_tok_encoder.items()} + self.added_tokens_encoder.update(added_tok_encoder) + self.added_tokens_decoder.update(added_tok_decoder) + + # Make sure we don't split on any special tokens (even they were already in the vocab before e.g. for Albert) + if special_tokens: + self.unique_no_split_tokens = list(set(self.unique_no_split_tokens).union(set(new_tokens))) + else: + # Or on the newly added tokens + self.unique_no_split_tokens = list(set(self.unique_no_split_tokens).union(set(tokens_to_add))) + + return len(tokens_to_add) + + def num_special_tokens_to_add(self, pair=False): + """ + Returns the number of added tokens when encoding a sequence with special tokens. + + Note: + This encodes inputs and checks the number of added tokens, and is therefore not efficient. Do not put this + inside your training loop. + + Args: + pair: Returns the number of added tokens in the case of a sequence pair if set to True, returns the + number of added tokens in the case of a single sequence if set to False. + + Returns: + Number of tokens added to sequences + """ + token_ids_0 = [] + token_ids_1 = [] + return len(self.build_inputs_with_special_tokens(token_ids_0, token_ids_1 if pair else None)) + + def tokenize(self, text: TextInput, **kwargs): + """ Converts a string in a sequence of tokens (string), using the tokenizer. + Split in words for word-based vocabulary or sub-words for sub-word-based + vocabularies (BPE/SentencePieces/WordPieces). + + Take care of added tokens. + + Args: + text (:obj:`string`): The sequence to be encoded. + **kwargs (:obj: `dict`): Arguments passed to the model-specific `prepare_for_tokenization` preprocessing method. + """ + # Simple mapping string => AddedToken for special tokens with specific tokenization behaviors + all_special_tokens_extended = dict( + (str(t), t) for t in self.all_special_tokens_extended if isinstance(t, AddedToken) + ) + + text, kwargs = self.prepare_for_tokenization(text, **kwargs) + + if kwargs: + logger.warning(f"Keyword arguments {kwargs} not recognized.") + + # TODO: should this be in the base class? + if self.init_kwargs.get("do_lower_case", False): + # convert non-special tokens to lowercase + escaped_special_toks = [re.escape(s_tok) for s_tok in self.all_special_tokens] + pattern = r"(" + r"|".join(escaped_special_toks) + r")|" + r"(.+?)" + text = re.sub(pattern, lambda m: m.groups()[0] or m.groups()[1].lower(), text) + + def split_on_token(tok, text): + result = [] + tok_extended = all_special_tokens_extended.get(tok, None) + split_text = text.split(tok) + full_word = "" + for i, sub_text in enumerate(split_text): + # AddedToken can control whitespace stripping around them. + # We use them for GPT2 and Roberta to have different behavior depending on the special token + # Cf. https://github.com/huggingface/transformers/pull/2778 + # and https://github.com/huggingface/transformers/issues/3788 + if isinstance(tok_extended, AddedToken): + if tok_extended.single_word: + # Try to avoid splitting on token + if ( + i < len(split_text) - 1 + and not _is_end_of_word(sub_text) + and not _is_start_of_word(split_text[i + 1]) + ): + # Don't extract the special token + full_word += sub_text + tok + elif full_word: + full_word += sub_text + result += [full_word] + full_word = "" + continue + # Strip white spaces on the right + if tok_extended.rstrip and i > 0: + # A bit counter-intuitive but we strip the left of the string + # since tok_extended.rstrip means the special token is eating all white spaces on its right + sub_text = sub_text.lstrip() + # Strip white spaces on the left + if tok_extended.lstrip and i < len(split_text) - 1: + sub_text = sub_text.rstrip() # Opposite here + else: + # We strip left and right by default + if i < len(split_text) - 1: + sub_text = sub_text.rstrip() + if i > 0: + sub_text = sub_text.lstrip() + + if i == 0 and not sub_text: + result += [tok] + elif i == len(split_text) - 1: + if sub_text: + result += [sub_text] + else: + pass + else: + if sub_text: + result += [sub_text] + result += [tok] + return result + + def split_on_tokens(tok_list, text): + if not text.strip(): + return [] + if not tok_list: + return self._tokenize(text) + + tokenized_text = [] + text_list = [text] + for tok in tok_list: + tokenized_text = [] + for sub_text in text_list: + if sub_text not in self.unique_no_split_tokens: + tokenized_text += split_on_token(tok, sub_text) + else: + tokenized_text += [sub_text] + text_list = tokenized_text + + return list( + itertools.chain.from_iterable( + ( + self._tokenize(token) if token not in self.unique_no_split_tokens else [token] + for token in tokenized_text + ) + ) + ) + + no_split_token = self.unique_no_split_tokens + tokenized_text = split_on_tokens(no_split_token, text) + return tokenized_text + + def _tokenize(self, text, **kwargs): + """ Converts a string in a sequence of tokens (string), using the tokenizer. + Split in words for word-based vocabulary or sub-words for sub-word-based + vocabularies (BPE/SentencePieces/WordPieces). + + Do NOT take care of added tokens. + """ + raise NotImplementedError + + def convert_tokens_to_ids(self, tokens): + """ Converts a token string (or a sequence of tokens) in a single integer id + (or a sequence of ids), using the vocabulary. + """ + if tokens is None: + return None + + if isinstance(tokens, str): + return self._convert_token_to_id_with_added_voc(tokens) + + ids = [] + for token in tokens: + ids.append(self._convert_token_to_id_with_added_voc(token)) + return ids + + def _convert_token_to_id_with_added_voc(self, token): + if token is None: + return None + + if token in self.added_tokens_encoder: + return self.added_tokens_encoder[token] + return self._convert_token_to_id(token) + + def _convert_token_to_id(self, token): + raise NotImplementedError + + def _encode_plus( + self, + text: Union[TextInput, PreTokenizedInput, EncodedInput], + text_pair: Optional[Union[TextInput, PreTokenizedInput, EncodedInput]] = None, + add_special_tokens: bool = True, + padding_strategy: PaddingStrategy = PaddingStrategy.DO_NOT_PAD, + truncation_strategy: TruncationStrategy = TruncationStrategy.DO_NOT_TRUNCATE, + max_length: Optional[int] = None, + stride: int = 0, + is_pretokenized: bool = False, + pad_to_multiple_of: Optional[int] = None, + return_tensors: Optional[Union[str, TensorType]] = None, + return_token_type_ids: Optional[bool] = None, + return_attention_mask: Optional[bool] = None, + return_overflowing_tokens: bool = False, + return_special_tokens_mask: bool = False, + return_offsets_mapping: bool = False, + return_length: bool = False, + verbose: bool = True, + **kwargs + ) -> BatchEncoding: + def get_input_ids(text): + if isinstance(text, str): + tokens = self.tokenize(text, **kwargs) + return self.convert_tokens_to_ids(tokens) + elif isinstance(text, (list, tuple)) and len(text) > 0 and isinstance(text[0], str): + if is_pretokenized: + tokens = list(itertools.chain(*(self.tokenize(t, is_pretokenized=True, **kwargs) for t in text))) + return self.convert_tokens_to_ids(tokens) + else: + return self.convert_tokens_to_ids(text) + elif isinstance(text, (list, tuple)) and len(text) > 0 and isinstance(text[0], int): + return text + else: + if is_pretokenized: + raise ValueError( + f"Input {text} is not valid. Should be a string or a list/tuple of strings when `is_pretokenized=True`." + ) + else: + raise ValueError( + f"Input {text} is not valid. Should be a string, a list/tuple of strings or a list/tuple of integers." + ) + + if return_offsets_mapping: + raise NotImplementedError( + "return_offset_mapping is not available when using Python tokenizers." + "To use this feature, change your tokenizer to one deriving from " + "transformers.PreTrainedTokenizerFast." + "More information on available tokenizers at " + "https://github.com/huggingface/transformers/pull/2674" + ) + + first_ids = get_input_ids(text) + second_ids = get_input_ids(text_pair) if text_pair is not None else None + + return self.prepare_for_model( + first_ids, + pair_ids=second_ids, + add_special_tokens=add_special_tokens, + padding=padding_strategy.value, + truncation=truncation_strategy.value, + max_length=max_length, + stride=stride, + pad_to_multiple_of=pad_to_multiple_of, + return_tensors=return_tensors, + prepend_batch_axis=True, + return_attention_mask=return_attention_mask, + return_token_type_ids=return_token_type_ids, + return_overflowing_tokens=return_overflowing_tokens, + return_special_tokens_mask=return_special_tokens_mask, + return_length=return_length, + verbose=verbose, + ) + + def _batch_encode_plus( + self, + batch_text_or_text_pairs: Union[ + List[TextInput], + List[TextInputPair], + List[PreTokenizedInput], + List[PreTokenizedInputPair], + List[EncodedInput], + List[EncodedInputPair], + ], + add_special_tokens: bool = True, + padding_strategy: PaddingStrategy = PaddingStrategy.DO_NOT_PAD, + truncation_strategy: TruncationStrategy = TruncationStrategy.DO_NOT_TRUNCATE, + max_length: Optional[int] = None, + stride: int = 0, + is_pretokenized: bool = False, + pad_to_multiple_of: Optional[int] = None, + return_tensors: Optional[Union[str, TensorType]] = None, + return_token_type_ids: Optional[bool] = None, + return_attention_mask: Optional[bool] = None, + return_overflowing_tokens: bool = False, + return_special_tokens_mask: bool = False, + return_offsets_mapping: bool = False, + return_length: bool = False, + verbose: bool = True, + **kwargs + ) -> BatchEncoding: + def get_input_ids(text): + if isinstance(text, str): + tokens = self.tokenize(text, **kwargs) + return self.convert_tokens_to_ids(tokens) + elif isinstance(text, (list, tuple)) and len(text) > 0 and isinstance(text[0], str): + if is_pretokenized: + tokens = list(itertools.chain(*(self.tokenize(t, is_pretokenized=True, **kwargs) for t in text))) + return self.convert_tokens_to_ids(tokens) + else: + return self.convert_tokens_to_ids(text) + elif isinstance(text, (list, tuple)) and len(text) > 0 and isinstance(text[0], int): + return text + else: + raise ValueError( + "Input is not valid. Should be a string, a list/tuple of strings or a list/tuple of integers." + ) + + if return_offsets_mapping: + raise NotImplementedError( + "return_offset_mapping is not available when using Python tokenizers." + "To use this feature, change your tokenizer to one deriving from " + "transformers.PreTrainedTokenizerFast." + ) + + input_ids = [] + for ids_or_pair_ids in batch_text_or_text_pairs: + if not isinstance(ids_or_pair_ids, (list, tuple)): + ids, pair_ids = ids_or_pair_ids, None + elif is_pretokenized and not isinstance(ids_or_pair_ids[0], (list, tuple)): + ids, pair_ids = ids_or_pair_ids, None + else: + ids, pair_ids = ids_or_pair_ids + + first_ids = get_input_ids(ids) + second_ids = get_input_ids(pair_ids) if pair_ids is not None else None + input_ids.append((first_ids, second_ids)) + + batch_outputs = self._batch_prepare_for_model( + input_ids, + add_special_tokens=add_special_tokens, + padding_strategy=padding_strategy, + truncation_strategy=truncation_strategy, + max_length=max_length, + stride=stride, + pad_to_multiple_of=pad_to_multiple_of, + return_attention_mask=return_attention_mask, + return_token_type_ids=return_token_type_ids, + return_overflowing_tokens=return_overflowing_tokens, + return_special_tokens_mask=return_special_tokens_mask, + return_length=return_length, + return_tensors=return_tensors, + verbose=verbose, + ) + + return BatchEncoding(batch_outputs) + + @add_end_docstrings(ENCODE_KWARGS_DOCSTRING, ENCODE_PLUS_ADDITIONAL_KWARGS_DOCSTRING) + def _batch_prepare_for_model( + self, + batch_ids_pairs: List[Union[PreTokenizedInputPair, Tuple[List[int], None]]], + add_special_tokens: bool = True, + padding_strategy: PaddingStrategy = PaddingStrategy.DO_NOT_PAD, + truncation_strategy: TruncationStrategy = TruncationStrategy.DO_NOT_TRUNCATE, + max_length: Optional[int] = None, + stride: int = 0, + pad_to_multiple_of: Optional[int] = None, + return_tensors: Optional[str] = None, + return_token_type_ids: Optional[bool] = None, + return_attention_mask: Optional[bool] = None, + return_overflowing_tokens: bool = False, + return_special_tokens_mask: bool = False, + return_length: bool = False, + verbose: bool = True, + ) -> BatchEncoding: + """ Prepares a sequence of input id, or a pair of sequences of inputs ids so that it can be used by the model. + It adds special tokens, truncates sequences if overflowing while taking into account the special tokens and + manages a moving window (with user defined stride) for overflowing tokens + + Args: + batch_ids_pairs: list of tokenized input ids or input ids pairs + """ + + batch_outputs = {} + for first_ids, second_ids in batch_ids_pairs: + outputs = self.prepare_for_model( + first_ids, + second_ids, + add_special_tokens=add_special_tokens, + padding=PaddingStrategy.DO_NOT_PAD.value, # we pad in batch afterward + truncation=truncation_strategy.value, + max_length=max_length, + stride=stride, + pad_to_multiple_of=None, # we pad in batch afterward + return_attention_mask=False, # we pad in batch afterward + return_token_type_ids=return_token_type_ids, + return_overflowing_tokens=return_overflowing_tokens, + return_special_tokens_mask=return_special_tokens_mask, + return_length=return_length, + return_tensors=None, # We convert the whole batch to tensors at the end + prepend_batch_axis=False, + verbose=verbose, + ) + + for key, value in outputs.items(): + if key not in batch_outputs: + batch_outputs[key] = [] + batch_outputs[key].append(value) + + batch_outputs = self.pad( + batch_outputs, + padding=padding_strategy.value, + max_length=max_length, + pad_to_multiple_of=pad_to_multiple_of, + return_attention_mask=return_attention_mask, + ) + + batch_outputs = BatchEncoding(batch_outputs, tensor_type=return_tensors) + + return batch_outputs + + def prepare_for_tokenization(self, text: str, is_pretokenized=False, **kwargs) -> (str, dict): + """ Performs any necessary transformations before tokenization. + + This method should pop the arguments from kwargs and return kwargs as well. + We test kwargs at the end of the encoding process to be sure all the arguments have been used. + """ + return (text, kwargs) + + def get_special_tokens_mask( + self, token_ids_0: List, token_ids_1: Optional[List] = None, already_has_special_tokens: bool = False + ) -> List[int]: + """ + Retrieves sequence ids from a token list that has no special tokens added. This method is called when adding + special tokens using the tokenizer ``prepare_for_model`` method. + + Args: + token_ids_0: list of ids (must not contain special tokens) + token_ids_1: Optional list of ids (must not contain special tokens), necessary when fetching sequence ids + for sequence pairs + already_has_special_tokens: (default False) Set to True if the token list is already formated with + special tokens for the model + + Returns: + A list of integers in the range [0, 1]: 1 for a special token, 0 for a sequence token. + """ + return [0] * ((len(token_ids_1) if token_ids_1 else 0) + len(token_ids_0)) + + def convert_ids_to_tokens( + self, ids: Union[int, List[int]], skip_special_tokens: bool = False + ) -> Union[str, List[str]]: + """ Converts a single index or a sequence of indices (integers) in a token " + (resp.) a sequence of tokens (str), using the vocabulary and added tokens. + + Args: + skip_special_tokens: Don't decode special tokens (self.all_special_tokens). Default: False + """ + if isinstance(ids, int): + if ids in self.added_tokens_decoder: + return self.added_tokens_decoder[ids] + else: + return self._convert_id_to_token(ids) + tokens = [] + for index in ids: + index = int(index) + if skip_special_tokens and index in self.all_special_ids: + continue + if index in self.added_tokens_decoder: + tokens.append(self.added_tokens_decoder[index]) + else: + tokens.append(self._convert_id_to_token(index)) + return tokens + + def _convert_id_to_token(self, index: int) -> str: + raise NotImplementedError + + def convert_tokens_to_string(self, tokens: List[str]) -> str: + """ Converts a sequence of tokens (string) in a single string. + The most simple way to do it is ' '.join(self.convert_ids_to_tokens(token_ids)) + but we often want to remove sub-word tokenization artifacts at the same time. + """ + return " ".join(self.convert_ids_to_tokens(tokens)) + + def decode( + self, token_ids: List[int], skip_special_tokens: bool = False, clean_up_tokenization_spaces: bool = True + ) -> str: + filtered_tokens = self.convert_ids_to_tokens(token_ids, skip_special_tokens=skip_special_tokens) + + # To avoid mixing byte-level and unicode for byte-level BPT + # we need to build string separatly for added tokens and byte-level tokens + # cf. https://github.com/huggingface/transformers/issues/1133 + sub_texts = [] + current_sub_text = [] + for token in filtered_tokens: + if skip_special_tokens and token in self.all_special_ids: + continue + if token in self.added_tokens_encoder: + if current_sub_text: + sub_texts.append(self.convert_tokens_to_string(current_sub_text)) + current_sub_text = [] + sub_texts.append(token) + else: + current_sub_text.append(token) + if current_sub_text: + sub_texts.append(self.convert_tokens_to_string(current_sub_text)) + text = " ".join(sub_texts) + + if clean_up_tokenization_spaces: + clean_text = self.clean_up_tokenization(text) + return clean_text + else: + return text + + def save_vocabulary(self, save_directory) -> Tuple[str]: + """ Save the tokenizer vocabulary to a directory. This method does *NOT* save added tokens + and special token mappings. + + Please use :func:`~transformers.PreTrainedTokenizer.save_pretrained` `()` to save the full + Tokenizer state if you want to reload it using the :func:`~transformers.PreTrainedTokenizer.from_pretrained` + class method. + """ + raise NotImplementedError diff --git a/LAVT-RIS/bert/tokenization_utils_base.py b/LAVT-RIS/bert/tokenization_utils_base.py new file mode 100644 index 0000000000000000000000000000000000000000..6a1219a4d3473ae510f0da905ea09a76019a7996 --- /dev/null +++ b/LAVT-RIS/bert/tokenization_utils_base.py @@ -0,0 +1,2317 @@ +# coding=utf-8 +# Copyright 2020 The HuggingFace Inc. team. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +""" Base classes common to both the slow and the fast tokenization classes: + PreTrainedTokenizerBase (host all the user fronting encoding methodes) + Special token mixing (host the special tokens logic) and + BatchEncoding (wrap the dictionnary of output with special method for the Fast tokenizers) +""" + +import copy +import json +import logging +import os +import warnings +from collections import UserDict +from enum import Enum +from typing import Any, Dict, List, NamedTuple, Optional, Sequence, Tuple, Union + +import numpy as np +from tokenizers import AddedToken +from tokenizers import Encoding as EncodingFast + +from .file_utils import ( + add_end_docstrings, + cached_path, + hf_bucket_url, + is_remote_url, + is_tf_available, + is_torch_available, + torch_required, +) + + +if is_tf_available(): + import tensorflow as tf +if is_torch_available(): + import torch + + +logger = logging.getLogger(__name__) + +VERY_LARGE_INTEGER = int(1e30) # This is used to set the max input length for a model with infinite size input +LARGE_INTEGER = int(1e20) # This is used when we need something big but slightly smaller than VERY_LARGE_INTEGER + +# Define type aliases and NamedTuples +TextInput = str +PreTokenizedInput = List[str] +EncodedInput = List[int] +TextInputPair = Tuple[str, str] +PreTokenizedInputPair = Tuple[List[str], List[str]] +EncodedInputPair = Tuple[List[int], List[int]] + + +# Slow tokenizers used to be saved in three separated files +SPECIAL_TOKENS_MAP_FILE = "special_tokens_map.json" +ADDED_TOKENS_FILE = "added_tokens.json" +TOKENIZER_CONFIG_FILE = "tokenizer_config.json" + +# Fast tokenizers (provided by HuggingFace tokenizer's library) can be saved in a single file +FULL_TOKENIZER_FILE = "tokenizer.json" + + +class ExplicitEnum(Enum): + """ Enum with more explicit error message for missing values. + """ + + @classmethod + def _missing_(cls, value): + raise ValueError( + "%r is not a valid %s, please select one of %s" + % (value, cls.__name__, str(list(cls._value2member_map_.keys()))) + ) + + +class TruncationStrategy(ExplicitEnum): + ONLY_FIRST = "only_first" + ONLY_SECOND = "only_second" + LONGEST_FIRST = "longest_first" + DO_NOT_TRUNCATE = "do_not_truncate" + + +class PaddingStrategy(ExplicitEnum): + LONGEST = "longest" + MAX_LENGTH = "max_length" + DO_NOT_PAD = "do_not_pad" + + +class TensorType(ExplicitEnum): + PYTORCH = "pt" + TENSORFLOW = "tf" + NUMPY = "np" + + +class CharSpan(NamedTuple): + """ Character span in the original string + + Args: + start: index of the first character in the original string + end: index of the character following the last character in the original string + """ + + start: int + end: int + + +class TokenSpan(NamedTuple): + """ Token span in an encoded string (list of tokens) + + Args: + start: index of the first token in the span + end: index of the token following the last token in the span + """ + + start: int + end: int + + +class BatchEncoding(UserDict): + """ BatchEncoding hold the output of the encode and batch_encode methods (tokens, attention_masks, etc). + This class is derived from a python Dictionary and can be used as a dictionnary. + In addition, this class expose utility methods to map from word/char space to token space. + + Args: + data (:obj:`dict`): Dictionary of lists/arrays returned by the encode/batch_encode methods ('input_ids', 'attention_mask'...) + encoding (:obj:`EncodingFast`, :obj:`list(EncodingFast)`, `optional`, defaults to :obj:`None`): + If the tokenizer is a fast tokenizer which outputs additional informations like mapping from word/char space to token space + the `EncodingFast` instance or list of instance (for batches) hold these informations. + tensor_type (:obj:`Union[None, str, TensorType]`, `optional`, defaults to :obj:`None`): + You can give a tensor_type here to convert the lists of integers in PyTorch/TF/Numpy Tensors at initialization + prepend_batch_axis (:obj:`bool`, `optional`, defaults to :obj:`False`): + Set to True to add a batch axis when converting in Tensors (see :obj:`tensor_type` above) + """ + + def __init__( + self, + data: Optional[Dict[str, Any]] = None, + encoding: Optional[Union[EncodingFast, Sequence[EncodingFast]]] = None, + tensor_type: Union[None, str, TensorType] = None, + prepend_batch_axis: bool = False, + ): + super().__init__(data) + + if isinstance(encoding, EncodingFast): + encoding = [encoding] + + self._encodings = encoding + + self.convert_to_tensors(tensor_type=tensor_type, prepend_batch_axis=prepend_batch_axis) + + @property + def is_fast(self): + """ + Indicate if this BatchEncoding was generated from the result of a PreTrainedTokenizerFast + Returns: True if generated from subclasses of PreTrainedTokenizerFast, else otherwise + """ + return self._encodings is not None + + def __getitem__(self, item: Union[int, str]) -> EncodingFast: + """ If the key is a string, get the value of the dict associated to `key` ('input_ids', 'attention_mask'...) + If the key is an integer, get the EncodingFast for batch item with index `key` + """ + if isinstance(item, str): + return self.data[item] + elif self._encodings is not None: + return self._encodings[item] + else: + raise KeyError( + "Indexing with integers (to access backend Encoding for a given batch index) " + "is not available when using Python based tokenizers" + ) + + def __getattr__(self, item: str): + try: + return self.data[item] + except KeyError: + raise AttributeError + + def __getstate__(self): + return {"data": self.data, "encodings": self._encodings} + + def __setstate__(self, state): + if "data" in state: + self.data = state["data"] + + if "encodings" in state: + self._encodings = state["encodings"] + + def keys(self): + return self.data.keys() + + def values(self): + return self.data.values() + + def items(self): + return self.data.items() + + # After this point: + # Extended properties and methods only available for fast (Rust-based) tokenizers + # provided by HuggingFace tokenizers library. + + @property + def encodings(self) -> Optional[List[EncodingFast]]: + """ + Return the list all encoding from the tokenization process + + Returns: List[EncodingFast] or None if input was tokenized through Python (i.e. not fast) tokenizer + """ + return self._encodings + + def tokens(self, batch_index: int = 0) -> List[str]: + if not self._encodings: + raise ValueError("tokens() is not available when using Python based tokenizers") + return self._encodings[batch_index].tokens + + def words(self, batch_index: int = 0) -> List[Optional[int]]: + if not self._encodings: + raise ValueError("words() is not available when using Python based tokenizers") + return self._encodings[batch_index].words + + def token_to_word(self, batch_or_token_index: int, token_index: Optional[int] = None) -> int: + """ + Get the index of the word corresponding (i.e. comprising) to an encoded token + in a sequence of the batch. + + Can be called as: + + - ``self.token_to_word(token_index)`` if batch size is 1 + - ``self.token_to_word(batch_index, token_index)`` if batch size is greater than 1 + + This method is particularly suited when the input sequences are provided as + pre-tokenized sequences (i.e. words are defined by the user). In this case it allows + to easily associate encoded tokens with provided tokenized words. + + Args: + batch_or_token_index (:obj:`int`): + Index of the sequence in the batch. If the batch only comprise one sequence, + this can be the index of the token in the sequence + token_index (:obj:`int`, `optional`): + If a batch index is provided in `batch_or_token_index`, this can be the index + of the token in the sequence. + + Returns: + :obj:`int`: + index of the word in the input sequence. + + """ + + if not self._encodings: + raise ValueError("token_to_word() is not available when using Python based tokenizers") + if token_index is not None: + batch_index = batch_or_token_index + else: + batch_index = 0 + token_index = batch_or_token_index + if batch_index < 0: + batch_index = self._batch_size + batch_index + if token_index < 0: + token_index = self._seq_len + token_index + return self._encodings[batch_index].token_to_word(token_index) + + def word_to_tokens(self, batch_or_word_index: int, word_index: Optional[int] = None) -> TokenSpan: + """ + Get the encoded token span corresponding to a word in the sequence of the batch. + + Token spans are returned as a TokenSpan NamedTuple with: + + - start: index of the first token + - end: index of the token following the last token + + Can be called as: + + - ``self.word_to_tokens(word_index)`` if batch size is 1 + - ``self.word_to_tokens(batch_index, word_index)`` if batch size is greater or equal to 1 + + This method is particularly suited when the input sequences are provided as + pre-tokenized sequences (i.e. words are defined by the user). In this case it allows + to easily associate encoded tokens with provided tokenized words. + + Args: + batch_or_word_index (:obj:`int`): + Index of the sequence in the batch. If the batch only comprises one sequence, + this can be the index of the word in the sequence + word_index (:obj:`int`, `optional`): + If a batch index is provided in `batch_or_token_index`, this can be the index + of the word in the sequence. + + Returns: + :obj:`TokenSpan`: + Span of tokens in the encoded sequence. + + :obj:`TokenSpan` are NamedTuple with: + + - start: index of the first token + - end: index of the token following the last token + """ + + if not self._encodings: + raise ValueError("word_to_tokens() is not available when using Python based tokenizers") + if word_index is not None: + batch_index = batch_or_word_index + else: + batch_index = 0 + word_index = batch_or_word_index + if batch_index < 0: + batch_index = self._batch_size + batch_index + if word_index < 0: + word_index = self._seq_len + word_index + return TokenSpan(*(self._encodings[batch_index].word_to_tokens(word_index))) + + def token_to_chars(self, batch_or_token_index: int, token_index: Optional[int] = None) -> CharSpan: + """ + Get the character span corresponding to an encoded token in a sequence of the batch. + + Character spans are returned as a CharSpan NamedTuple with: + + - start: index of the first character in the original string associated to the token + - end: index of the character following the last character in the original string associated to the token + + Can be called as: + + - ``self.token_to_chars(token_index)`` if batch size is 1 + - ``self.token_to_chars(batch_index, token_index)`` if batch size is greater or equal to 1 + + Args: + batch_or_token_index (:obj:`int`): + Index of the sequence in the batch. If the batch only comprise one sequence, + this can be the index of the token in the sequence + token_index (:obj:`int`, `optional`): + If a batch index is provided in `batch_or_token_index`, this can be the index + of the token or tokens in the sequence. + + Returns: + :obj:`CharSpan`: + Span of characters in the original string. + + :obj:`CharSpan` are NamedTuple with: + + - start: index of the first character in the original string + - end: index of the character following the last character in the original string + """ + + if not self._encodings: + raise ValueError("token_to_chars() is not available when using Python based tokenizers") + if token_index is not None: + batch_index = batch_or_token_index + else: + batch_index = 0 + token_index = batch_or_token_index + return CharSpan(*(self._encodings[batch_index].token_to_chars(token_index))) + + def char_to_token(self, batch_or_char_index: int, char_index: Optional[int] = None) -> int: + """ + Get the index of the token in the encoded output comprising a character + in the original string for a sequence of the batch. + + Can be called as: + + - ``self.char_to_token(char_index)`` if batch size is 1 + - ``self.char_to_token(batch_index, char_index)`` if batch size is greater or equal to 1 + + This method is particularly suited when the input sequences are provided as + pre-tokenized sequences (i.e. words are defined by the user). In this case it allows + to easily associate encoded tokens with provided tokenized words. + + Args: + batch_or_char_index (:obj:`int`): + Index of the sequence in the batch. If the batch only comprise one sequence, + this can be the index of the word in the sequence + char_index (:obj:`int`, `optional`): + If a batch index is provided in `batch_or_token_index`, this can be the index + of the word in the sequence. + + + Returns: + :obj:`int`: Index of the token. + """ + + if not self._encodings: + raise ValueError("char_to_token() is not available when using Python based tokenizers") + if char_index is not None: + batch_index = batch_or_char_index + else: + batch_index = 0 + char_index = batch_or_char_index + return self._encodings[batch_index].char_to_token(char_index) + + def word_to_chars(self, batch_or_word_index: int, word_index: Optional[int] = None) -> CharSpan: + """ + Get the character span in the original string corresponding to given word in a sequence + of the batch. + + Character spans are returned as a CharSpan NamedTuple with: + + - start: index of the first character in the original string + - end: index of the character following the last character in the original string + + Can be called as: + + - ``self.word_to_chars(word_index)`` if batch size is 1 + - ``self.word_to_chars(batch_index, word_index)`` if batch size is greater or equal to 1 + + Args: + batch_or_word_index (:obj:`int`): + Index of the sequence in the batch. If the batch only comprise one sequence, + this can be the index of the word in the sequence + word_index (:obj:`int`, `optional`): + If a batch index is provided in `batch_or_token_index`, this can be the index + of the word in the sequence. + + Returns: + :obj:`CharSpan` or :obj:`List[CharSpan]`: + Span(s) of the associated character or characters in the string. + CharSpan are NamedTuple with: + + - start: index of the first character associated to the token in the original string + - end: index of the character following the last character associated to the token in the original string + """ + + if not self._encodings: + raise ValueError("word_to_chars() is not available when using Python based tokenizers") + if word_index is not None: + batch_index = batch_or_word_index + else: + batch_index = 0 + word_index = batch_or_word_index + return CharSpan(*(self._encodings[batch_index].word_to_chars(word_index))) + + def char_to_word(self, batch_or_char_index: int, char_index: Optional[int] = None) -> int: + """ + Get the word in the original string corresponding to a character in the original string of + a sequence of the batch. + + Can be called as: + + - ``self.char_to_word(char_index)`` if batch size is 1 + - ``self.char_to_word(batch_index, char_index)`` if batch size is greater than 1 + + This method is particularly suited when the input sequences are provided as + pre-tokenized sequences (i.e. words are defined by the user). In this case it allows + to easily associate encoded tokens with provided tokenized words. + + Args: + batch_or_char_index (:obj:`int`): + Index of the sequence in the batch. If the batch only comprise one sequence, + this can be the index of the character in the orginal string. + char_index (:obj:`int`, `optional`): + If a batch index is provided in `batch_or_token_index`, this can be the index + of the character in the orginal string. + + + Returns: + :obj:`int` or :obj:`List[int]`: + Index or indices of the associated encoded token(s). + """ + + if not self._encodings: + raise ValueError("char_to_word() is not available when using Python based tokenizers") + if char_index is not None: + batch_index = batch_or_char_index + else: + batch_index = 0 + char_index = batch_or_char_index + return self._encodings[batch_index].char_to_word(char_index) + + def convert_to_tensors(self, tensor_type: Union[None, str, TensorType], prepend_batch_axis: bool = False): + if tensor_type is None: + return self + + # Convert to TensorType + if not isinstance(tensor_type, TensorType): + tensor_type = TensorType(tensor_type) + + # Get a function reference for the correct framework + if tensor_type == TensorType.TENSORFLOW and is_tf_available(): + as_tensor = tf.constant + elif tensor_type == TensorType.PYTORCH and is_torch_available(): + as_tensor = torch.tensor + elif tensor_type == TensorType.NUMPY: + as_tensor = np.asarray + else: + raise ImportError( + "Unable to convert output to tensors format {}, PyTorch or TensorFlow is not available.".format( + tensor_type + ) + ) + + # Do the tensor conversion in batch + for key, value in self.items(): + try: + if prepend_batch_axis: + value = [value] + + tensor = as_tensor(value) + + # at-least2d + if tensor.ndim > 2: + tensor = tensor.squeeze(0) + elif tensor.ndim < 2: + tensor = tensor[None, :] + + self[key] = tensor + except: # noqa E722 + raise ValueError( + "Unable to create tensor, you should probably activate truncation and/or padding " + "with 'padding=True' 'truncation=True' to have batched tensors with the same length." + ) + + return self + + @torch_required + def to(self, device: str): + """Send all values to device by calling v.to(device)""" + self.data = {k: v.to(device) for k, v in self.data.items()} + return self + + +# class AddedToken(UserString): +# """ AddedToken represents a token to be added to a Tokenizer + +# An AddedToken can have special options defining the way it should behave. + +# Args: +# content: str: +# The content of the token + +# single_word: bool +# Whether this token should only match against single word. If True, +# this token will never match inside of a word. + +# lstrip: bool +# Whether this token should strip all potential whitespaces on the left side. +# If True, this token will greedily match any whitespace on the left and then strip +# them out. + +# rstrip: bool +# Whether this token should strip all potential whitespaces on the right side. +# If True, this token will greedily match any whitespace on the right and then strip +# them out. +# """ + +# def __init__( +# self, data: str, single_word: bool = False, lstrip: bool = False, rstrip: bool = False, +# ): +# super().__init__(data) + +# self._single_word = single_word +# self._lstrip = lstrip +# self._rstrip = rstrip + +# def lower(self): +# return AddedToken(self.data.lower(), self._single_word, self._lstrip, self._rstrip) + + +class SpecialTokensMixin: + """ SpecialTokensMixin is derived by ``PreTrainedTokenizer`` and ``PreTrainedTokenizerFast`` and + handles specific behaviors related to special tokens. In particular, this class hold the + attributes which can be used to directly access to these special tokens in a + model-independant manner and allow to set and update the special tokens. + """ + + SPECIAL_TOKENS_ATTRIBUTES = [ + "bos_token", + "eos_token", + "unk_token", + "sep_token", + "pad_token", + "cls_token", + "mask_token", + "additional_special_tokens", + ] + + def __init__(self, verbose=True, **kwargs): + self._bos_token = None + self._eos_token = None + self._unk_token = None + self._sep_token = None + self._pad_token = None + self._cls_token = None + self._mask_token = None + self._pad_token_type_id = 0 + self._additional_special_tokens = [] + self.verbose = verbose + + # We directly set the hidden value to allow initialization with special tokens + # which are not yet in the vocabulary. Necesssary for serialization/de-serialization + # TODO clean this up at some point (probably by sitching to fast tokenizers) + for key, value in kwargs.items(): + if key in self.SPECIAL_TOKENS_ATTRIBUTES: + if key == "additional_special_tokens": + assert isinstance(value, (list, tuple)) and all(isinstance(t, str) for t in value) + setattr(self, key, value) + elif isinstance(value, (str, AddedToken)): + setattr(self, key, value) + else: + raise TypeError( + "special token {} has to be either str or AddedToken but got: {}".format(key, type(value)) + ) + + def sanitize_special_tokens(self) -> int: + """ Make sure that all the special tokens attributes of the tokenizer (tokenizer.mask_token, tokenizer.cls_token, ...) + are in the vocabulary. Add the missing ones to the vocabulary if needed. + + Return: + Number of tokens added in the vocaulary during the operation. + """ + return self.add_tokens(self.all_special_tokens_extended, special_tokens=True) + + def add_special_tokens(self, special_tokens_dict: Dict[str, Union[str, AddedToken]]) -> int: + """ + Add a dictionary of special tokens (eos, pad, cls...) to the encoder and link them + to class attributes. If special tokens are NOT in the vocabulary, they are added + to it (indexed starting from the last index of the current vocabulary). + + Using `add_special_tokens` will ensure your special tokens can be used in several ways: + + - special tokens are carefully handled by the tokenizer (they are never split) + - you can easily refer to special tokens using tokenizer class attributes like `tokenizer.cls_token`. This makes it easy to develop model-agnostic training and fine-tuning scripts. + + When possible, special tokens are already registered for provided pretrained models (ex: BertTokenizer cls_token is already registered to be '[CLS]' and XLM's one is also registered to be '') + + Args: + special_tokens_dict: dict of string. Keys should be in the list of predefined special attributes: + [``bos_token``, ``eos_token``, ``unk_token``, ``sep_token``, ``pad_token``, ``cls_token``, ``mask_token``, + ``additional_special_tokens``]. + + Tokens are only added if they are not already in the vocabulary (tested by checking if the tokenizer assign the index of the ``unk_token`` to them). + + Returns: + Number of tokens added to the vocabulary. + + Examples:: + + # Let's see how to add a new classification token to GPT-2 + tokenizer = GPT2Tokenizer.from_pretrained('gpt2') + model = GPT2Model.from_pretrained('gpt2') + + special_tokens_dict = {'cls_token': ''} + + num_added_toks = tokenizer.add_special_tokens(special_tokens_dict) + print('We have added', num_added_toks, 'tokens') + model.resize_token_embeddings(len(tokenizer)) # Notice: resize_token_embeddings expect to receive the full size of the new vocabulary, i.e. the length of the tokenizer. + + assert tokenizer.cls_token == '' + """ + if not special_tokens_dict: + return 0 + + added_tokens = 0 + for key, value in special_tokens_dict.items(): + assert key in self.SPECIAL_TOKENS_ATTRIBUTES + + if self.verbose: + logger.info("Assigning %s to the %s key of the tokenizer", value, key) + setattr(self, key, value) + + if key == "additional_special_tokens": + assert isinstance(value, (list, tuple)) and all( + isinstance(t, (str, AddedToken)) for t in value + ), f"Tokens {value} for key {key} should all be str or AddedToken instances" + added_tokens += self.add_tokens(value, special_tokens=True) + else: + assert isinstance( + value, (str, AddedToken) + ), f"Token {value} for key {key} should be a str or an AddedToken instance" + added_tokens += self.add_tokens([value], special_tokens=True) + + return added_tokens + + def add_tokens(self, new_tokens: Union[str, AddedToken, List[str], List[AddedToken]], special_tokens=False) -> int: + """ + Add a list of new tokens to the tokenizer class. If the new tokens are not in the + vocabulary, they are added to it with indices starting from length of the current vocabulary. + + Args: + new_tokens: string or list of string or :class:`~transformers.AddedToken`. Each string is a token to add. + Tokens are only added if they are not already in the vocabulary. AddedToken wrap a string token to + let you personnalize it's behavior (Whether this token should only match against single word, whether + this token should strip all potential whitespaces on the left side, Whether this token should strip + all potential whitespaces on the right side...). + special_token: can be used to specify if the token is a special token. This mostly change the normalization + behavior (special tokens like CLS or [MASK] are usually not lower-cased for instance) + + See details for :class:`~transformers.AddedToken` in HuggingFace tokenizers library. + + Returns: + Number of tokens added to the vocabulary. + + Examples:: + + # Let's see how to increase the vocabulary of Bert model and tokenizer + tokenizer = BertTokenizerFast.from_pretrained('bert-base-uncased') + model = BertModel.from_pretrained('bert-base-uncased') + + num_added_toks = tokenizer.add_tokens(['new_tok1', 'my_new-tok2']) + print('We have added', num_added_toks, 'tokens') + model.resize_token_embeddings(len(tokenizer)) # Notice: resize_token_embeddings expect to receive the full size of the new vocabulary, i.e. the length of the tokenizer. + """ + if not new_tokens: + return 0 + + if not isinstance(new_tokens, (list, tuple)): + new_tokens = [new_tokens] + + return self._add_tokens(new_tokens, special_tokens=special_tokens) + + @property + def bos_token(self): + """ Beginning of sentence token (string). Log an error if used while not having been set. """ + if self._bos_token is None and self.verbose: + logger.error("Using bos_token, but it is not set yet.") + return None + return str(self._bos_token) + + @property + def eos_token(self): + """ End of sentence token (string). Log an error if used while not having been set. """ + if self._eos_token is None and self.verbose: + logger.error("Using eos_token, but it is not set yet.") + return None + return str(self._eos_token) + + @property + def unk_token(self): + """ Unknown token (string). Log an error if used while not having been set. """ + if self._unk_token is None and self.verbose: + logger.error("Using unk_token, but it is not set yet.") + return None + return str(self._unk_token) + + @property + def sep_token(self): + """ Separation token (string). E.g. separate context and query in an input sequence. Log an error if used while not having been set. """ + if self._sep_token is None and self.verbose: + logger.error("Using sep_token, but it is not set yet.") + return None + return str(self._sep_token) + + @property + def pad_token(self): + """ Padding token (string). Log an error if used while not having been set. """ + if self._pad_token is None and self.verbose: + logger.error("Using pad_token, but it is not set yet.") + return None + return str(self._pad_token) + + @property + def cls_token(self): + """ Classification token (string). E.g. to extract a summary of an input sequence leveraging self-attention along the full depth of the model. Log an error if used while not having been set. """ + if self._cls_token is None and self.verbose: + logger.error("Using cls_token, but it is not set yet.") + return None + return str(self._cls_token) + + @property + def mask_token(self): + """ Mask token (string). E.g. when training a model with masked-language modeling. Log an error if used while not having been set. """ + if self._mask_token is None and self.verbose: + logger.error("Using mask_token, but it is not set yet.") + return None + return str(self._mask_token) + + @property + def additional_special_tokens(self): + """ All the additional special tokens you may want to use (list of strings). Log an error if used while not having been set. """ + if self._additional_special_tokens is None and self.verbose: + logger.error("Using additional_special_tokens, but it is not set yet.") + return None + return [str(tok) for tok in self._additional_special_tokens] + + @bos_token.setter + def bos_token(self, value): + self._bos_token = value + + @eos_token.setter + def eos_token(self, value): + self._eos_token = value + + @unk_token.setter + def unk_token(self, value): + self._unk_token = value + + @sep_token.setter + def sep_token(self, value): + self._sep_token = value + + @pad_token.setter + def pad_token(self, value): + self._pad_token = value + + @cls_token.setter + def cls_token(self, value): + self._cls_token = value + + @mask_token.setter + def mask_token(self, value): + self._mask_token = value + + @additional_special_tokens.setter + def additional_special_tokens(self, value): + self._additional_special_tokens = value + + @property + def bos_token_id(self): + """ Id of the beginning of sentence token in the vocabulary. Log an error if used while not having been set. """ + if self._bos_token is None: + return None + return self.convert_tokens_to_ids(self.bos_token) + + @property + def eos_token_id(self): + """ Id of the end of sentence token in the vocabulary. Log an error if used while not having been set. """ + if self._eos_token is None: + return None + return self.convert_tokens_to_ids(self.eos_token) + + @property + def unk_token_id(self): + """ Id of the unknown token in the vocabulary. Log an error if used while not having been set. """ + if self._unk_token is None: + return None + return self.convert_tokens_to_ids(self.unk_token) + + @property + def sep_token_id(self): + """ Id of the separation token in the vocabulary. E.g. separate context and query in an input sequence. Log an error if used while not having been set. """ + if self._sep_token is None: + return None + return self.convert_tokens_to_ids(self.sep_token) + + @property + def pad_token_id(self): + """ Id of the padding token in the vocabulary. Log an error if used while not having been set. """ + if self._pad_token is None: + return None + return self.convert_tokens_to_ids(self.pad_token) + + @property + def pad_token_type_id(self): + """ Id of the padding token type in the vocabulary.""" + return self._pad_token_type_id + + @property + def cls_token_id(self): + """ Id of the classification token in the vocabulary. E.g. to extract a summary of an input sequence leveraging self-attention along the full depth of the model. Log an error if used while not having been set. """ + if self._cls_token is None: + return None + return self.convert_tokens_to_ids(self.cls_token) + + @property + def mask_token_id(self): + """ Id of the mask token in the vocabulary. E.g. when training a model with masked-language modeling. Log an error if used while not having been set. """ + if self._mask_token is None: + return None + return self.convert_tokens_to_ids(self.mask_token) + + @property + def additional_special_tokens_ids(self): + """ Ids of all the additional special tokens in the vocabulary (list of integers). Log an error if used while not having been set. """ + return self.convert_tokens_to_ids(self.additional_special_tokens) + + @property + def special_tokens_map(self): + """ A dictionary mapping special token class attribute (cls_token, unk_token...) to their + values ('', ''...) + Convert tokens of AddedToken type in string. + All returned tokens are strings + """ + set_attr = {} + for attr in self.SPECIAL_TOKENS_ATTRIBUTES: + attr_value = getattr(self, "_" + attr) + if attr_value: + set_attr[attr] = str(attr_value) + return set_attr + + @property + def special_tokens_map_extended(self): + """ A dictionary mapping special token class attribute (cls_token, unk_token...) to their + values ('', ''...) + Keep the tokens as AddedToken if they are of this type. + + AddedToken can be used to control more finely how special tokens are tokenized. + """ + set_attr = {} + for attr in self.SPECIAL_TOKENS_ATTRIBUTES: + attr_value = getattr(self, "_" + attr) + if attr_value: + set_attr[attr] = attr_value + return set_attr + + @property + def all_special_tokens(self): + """ List all the special tokens ('', ''...) mapped to class attributes + Convert tokens of AddedToken type in string. + All returned tokens are strings + (cls_token, unk_token...). + """ + all_toks = [str(s) for s in self.all_special_tokens_extended] + return all_toks + + @property + def all_special_tokens_extended(self): + """ List all the special tokens ('', ''...) mapped to class attributes + Keep the tokens as AddedToken if they are of this type. + + AddedToken can be used to control more finely how special tokens are tokenized. + """ + all_toks = [] + set_attr = self.special_tokens_map_extended + for attr_value in set_attr.values(): + all_toks = all_toks + (list(attr_value) if isinstance(attr_value, (list, tuple)) else [attr_value]) + all_toks = list(set(all_toks)) + return all_toks + + @property + def all_special_ids(self): + """ List the vocabulary indices of the special tokens ('', ''...) mapped to + class attributes (cls_token, unk_token...). + """ + all_toks = self.all_special_tokens + all_ids = self.convert_tokens_to_ids(all_toks) + return all_ids + + +ENCODE_KWARGS_DOCSTRING = r""" + add_special_tokens (:obj:`bool`, `optional`, defaults to :obj:`True`): + If set to ``True``, the sequences will be encoded with the special tokens relative + to their model. + `padding` (:obj:`Union[bool, str]`, `optional`, defaults to :obj:`False`): + Activate and control padding. Accepts the following values: + + * `True` or `'longest'`: pad to the longest sequence in the batch (or no padding if only a single sequence if provided), + * `'max_length'`: pad to a max length specified in `max_length` or to the max acceptable input length for the model if no length is provided (`max_length=None`) + * `False` or `'do_not_pad'` (default): No padding (i.e. can output batch with sequences of uneven lengths) + `truncation` (:obj:`Union[bool, str]`, `optional`, defaults to :obj:`False`): + Activate and control truncation. Accepts the following values: + + * `True` or `'longest_first'`: truncate to a max length specified in `max_length` or to the max acceptable input length for the model if no length is provided (`max_length=None`). This will truncate token by token, removing a token from the longest sequence in the pair if a pair of sequences (or a batch of pairs) is provided, + * `'only_first'`: truncate to a max length specified in `max_length` or to the max acceptable input length for the model if no length is provided (`max_length=None`). This will only truncate the first sequence of a pair if a pair of sequences (or a batch of pairs) is provided, + * `'only_second'`: truncate to a max length specified in `max_length` or to the max acceptable input length for the model if no length is provided (`max_length=None`). This will only truncate the second sequence of a pair if a pair of sequences (or a batch of pairs) is provided, + * `False` or `'do_not_truncate'` (default): No truncation (i.e. can output batch with sequences length greater than the model max admissible input size) + `max_length` (:obj:`Union[int, None]`, `optional`, defaults to :obj:`None`): + Control the length for padding/truncation. Accepts the following values + + * `None` (default): This will use the predefined model max length if required by one of the truncation/padding parameters. If the model has no specific max input length (e.g. XLNet) truncation/padding to max length is deactivated. + * `any integer value` (e.g. `42`): Use this specific maximum length value if required by one of the truncation/padding parameters. + stride (:obj:`int`, `optional`, defaults to ``0``): + If set to a number along with max_length, the overflowing tokens returned when `return_overflowing_tokens=True` + will contain some tokens from the end of the truncated sequence returned to provide some overlap between truncated and overflow ing sequences. + The value of this argument defines the number of overlapping tokens. + is_pretokenized (:obj:`bool`, defaults to :obj:`False`): + Set to True to indicate the input is already tokenized + pad_to_multiple_of: (optional) Integer if set will pad the sequence to a multiple of the provided value. + This is especially useful to enable the use of Tensor Core on NVIDIA hardware with compute capability + >= 7.5 (Volta). + return_tensors (:obj:`str`, `optional`, defaults to :obj:`None`): + Can be set to 'tf', 'pt' or 'np' to return respectively TensorFlow :obj:`tf.constant`, + PyTorch :obj:`torch.Tensor` or Numpy :oj: `np.ndarray` instead of a list of python integers. +""" + +ENCODE_PLUS_ADDITIONAL_KWARGS_DOCSTRING = r""" + return_token_type_ids (:obj:`bool`, `optional`, defaults to :obj:`None`): + Whether to return token type IDs. If left to the default, will return the token type IDs according + to the specific tokenizer's default, defined by the :obj:`return_outputs` attribute. + + `What are token type IDs? <../glossary.html#token-type-ids>`_ + return_attention_mask (:obj:`bool`, `optional`, defaults to :obj:`none`): + Whether to return the attention mask. If left to the default, will return the attention mask according + to the specific tokenizer's default, defined by the :obj:`return_outputs` attribute. + + `What are attention masks? <../glossary.html#attention-mask>`__ + return_overflowing_tokens (:obj:`bool`, `optional`, defaults to :obj:`False`): + Set to True to return overflowing token sequences (default False). + return_special_tokens_mask (:obj:`bool`, `optional`, defaults to :obj:`False`): + Set to True to return special tokens mask information (default False). + return_offsets_mapping (:obj:`bool`, `optional`, defaults to :obj:`False`): + Set to True to return (char_start, char_end) for each token (default False). + If using Python's tokenizer, this method will raise NotImplementedError. + This one is only available on fast tokenizers inheriting from PreTrainedTokenizerFast. + **kwargs: passed to the `self.tokenize()` method + + Return: + A Dictionary of shape:: + + { + input_ids: list[int], + token_type_ids: list[int] if return_token_type_ids is True (default) + attention_mask: list[int] if return_attention_mask is True (default) + overflowing_tokens: list[int] if the tokenizer is a slow tokenize, else a List[List[int]] if a ``max_length`` is specified and ``return_overflowing_tokens=True`` + special_tokens_mask: list[int] if ``add_special_tokens`` if set to ``True`` + and return_special_tokens_mask is True + } + + With the fields: + + - ``input_ids``: list of token ids to be fed to a model + - ``token_type_ids``: list of token type ids to be fed to a model + - ``attention_mask``: list of indices specifying which tokens should be attended to by the model + - ``overflowing_tokens``: list of overflowing tokens sequences if a max length is specified and ``return_overflowing_tokens=True``. + - ``special_tokens_mask``: if adding special tokens, this is a list of [0, 1], with 0 specifying special added + tokens and 1 specifying sequence tokens. +""" + + +class PreTrainedTokenizerBase(SpecialTokensMixin): + """ Base class for slow and fast tokenizers. + + Handle shared (mostly boiler plate) methods for slow and fast tokenizers. + """ + + vocab_files_names: Dict[str, str] = {} + pretrained_vocab_files_map: Dict[str, Dict[str, str]] = {} + pretrained_init_configuration: Dict[str, Dict[str, Any]] = {} + max_model_input_sizes: Dict[str, int] = {} + model_input_names: List[str] = ["token_type_ids", "attention_mask"] + + padding_side: str = "right" + + def __init__(self, **kwargs): + # inputs and kwargs for saving and re-loading (see ``from_pretrained`` and ``save_pretrained``) + self.init_inputs = () + self.init_kwargs = kwargs + + # For backward compatibility we fallback to set model_max_length from max_len if provided + model_max_length = kwargs.pop("model_max_length", kwargs.pop("max_len", None)) + self.model_max_length = model_max_length if model_max_length is not None else VERY_LARGE_INTEGER + + # Padding side is right by default and overridden in subclasses. If specified in the kwargs, it is changed. + self.padding_side = kwargs.pop("padding_side", self.padding_side) + assert self.padding_side in [ + "right", + "left", + ], f"Padding side should be selected between 'right' and 'left', current value: {self.padding_side}" + self.model_input_names = kwargs.pop("model_input_names", self.model_input_names) + + super().__init__(**kwargs) + + @property + def max_len(self) -> int: + """ Kept here for backward compatibility. + Now renamed to `model_max_length` to avoid ambiguity. + """ + return self.model_max_length + + @property + def max_len_single_sentence(self) -> int: + return self.model_max_length - self.num_special_tokens_to_add(pair=False) + + @property + def max_len_sentences_pair(self) -> int: + return self.model_max_length - self.num_special_tokens_to_add(pair=True) + + @max_len_single_sentence.setter + def max_len_single_sentence(self, value) -> int: + """ For backward compatibility, allow to try to setup 'max_len_single_sentence' """ + if value == self.model_max_length - self.num_special_tokens_to_add(pair=False) and self.verbose: + logger.warning( + "Setting 'max_len_single_sentence' is now deprecated. " "This value is automatically set up." + ) + else: + raise ValueError( + "Setting 'max_len_single_sentence' is now deprecated. " "This value is automatically set up." + ) + + @max_len_sentences_pair.setter + def max_len_sentences_pair(self, value) -> int: + """ For backward compatibility, allow to try to setup 'max_len_sentences_pair' """ + if value == self.model_max_length - self.num_special_tokens_to_add(pair=True) and self.verbose: + logger.warning( + "Setting 'max_len_sentences_pair' is now deprecated. " "This value is automatically set up." + ) + else: + raise ValueError( + "Setting 'max_len_sentences_pair' is now deprecated. " "This value is automatically set up." + ) + + @classmethod + def from_pretrained(cls, *inputs, **kwargs): + r""" + Instantiate a :class:`~transformers.PreTrainedTokenizer` (or a derived class) from a predefined tokenizer. + + Args: + pretrained_model_name_or_path: either: + + - a string with the `shortcut name` of a predefined tokenizer to load from cache or download, e.g.: ``bert-base-uncased``. + - a string with the `identifier name` of a predefined tokenizer that was user-uploaded to our S3, e.g.: ``dbmdz/bert-base-german-cased``. + - a path to a `directory` containing vocabulary files required by the tokenizer, for instance saved using the :func:`~transformers.PreTrainedTokenizer.save_pretrained` method, e.g.: ``./my_model_directory/``. + - (not applicable to all derived classes, deprecated) a path or url to a single saved vocabulary file if and only if the tokenizer only requires a single vocabulary file (e.g. Bert, XLNet), e.g.: ``./my_model_directory/vocab.txt``. + + cache_dir: (`optional`) string: + Path to a directory in which a downloaded predefined tokenizer vocabulary files should be cached if the standard cache should not be used. + + force_download: (`optional`) boolean, default False: + Force to (re-)download the vocabulary files and override the cached versions if they exists. + + resume_download: (`optional`) boolean, default False: + Do not delete incompletely recieved file. Attempt to resume the download if such a file exists. + + proxies: (`optional`) dict, default None: + A dictionary of proxy servers to use by protocol or endpoint, e.g.: {'http': 'foo.bar:3128', 'http://hostname': 'foo.bar:4012'}. + The proxies are used on each request. + + inputs: (`optional`) positional arguments: will be passed to the Tokenizer ``__init__`` method. + + kwargs: (`optional`) keyword arguments: will be passed to the Tokenizer ``__init__`` method. Can be used to set special tokens like ``bos_token``, ``eos_token``, ``unk_token``, ``sep_token``, ``pad_token``, ``cls_token``, ``mask_token``, ``additional_special_tokens``. See parameters in the doc string of :class:`~transformers.PreTrainedTokenizer` for details. + + Examples:: + + # We can't instantiate directly the base class `PreTrainedTokenizer` so let's show our examples on a derived class: BertTokenizer + + # Download vocabulary from S3 and cache. + tokenizer = BertTokenizer.from_pretrained('bert-base-uncased') + + # Download vocabulary from S3 (user-uploaded) and cache. + tokenizer = BertTokenizer.from_pretrained('dbmdz/bert-base-german-cased') + + # If vocabulary files are in a directory (e.g. tokenizer was saved using `save_pretrained('./test/saved_model/')`) + tokenizer = BertTokenizer.from_pretrained('./test/saved_model/') + + # If the tokenizer uses a single vocabulary file, you can point directly to this file + tokenizer = BertTokenizer.from_pretrained('./test/saved_model/my_vocab.txt') + + # You can link tokens to special vocabulary when instantiating + tokenizer = BertTokenizer.from_pretrained('bert-base-uncased', unk_token='') + # You should be sure '' is in the vocabulary when doing that. + # Otherwise use tokenizer.add_special_tokens({'unk_token': ''}) instead) + assert tokenizer.unk_token == '' + + """ + return cls._from_pretrained(*inputs, **kwargs) + + @classmethod + def _from_pretrained(cls, pretrained_model_name_or_path, *init_inputs, **kwargs): + cache_dir = kwargs.pop("cache_dir", None) + force_download = kwargs.pop("force_download", False) + resume_download = kwargs.pop("resume_download", False) + proxies = kwargs.pop("proxies", None) + local_files_only = kwargs.pop("local_files_only", False) + + s3_models = list(cls.max_model_input_sizes.keys()) + vocab_files = {} + init_configuration = {} + if pretrained_model_name_or_path in s3_models: + # Get the vocabulary from AWS S3 bucket + for file_id, map_list in cls.pretrained_vocab_files_map.items(): + vocab_files[file_id] = map_list[pretrained_model_name_or_path] + if ( + cls.pretrained_init_configuration + and pretrained_model_name_or_path in cls.pretrained_init_configuration + ): + init_configuration = cls.pretrained_init_configuration[pretrained_model_name_or_path].copy() + else: + # Get the vocabulary from local files + logger.info( + "Model name '{}' not found in model shortcut name list ({}). " + "Assuming '{}' is a path, a model identifier, or url to a directory containing tokenizer files.".format( + pretrained_model_name_or_path, ", ".join(s3_models), pretrained_model_name_or_path + ) + ) + + if os.path.isfile(pretrained_model_name_or_path) or is_remote_url(pretrained_model_name_or_path): + if len(cls.vocab_files_names) > 1: + raise ValueError( + "Calling {}.from_pretrained() with the path to a single file or url is not supported." + "Use a model identifier or the path to a directory instead.".format(cls.__name__) + ) + logger.warning( + "Calling {}.from_pretrained() with the path to a single file or url is deprecated".format( + cls.__name__ + ) + ) + file_id = list(cls.vocab_files_names.keys())[0] + vocab_files[file_id] = pretrained_model_name_or_path + else: + # At this point pretrained_model_name_or_path is either a directory or a model identifier name + additional_files_names = { + "added_tokens_file": ADDED_TOKENS_FILE, + "special_tokens_map_file": SPECIAL_TOKENS_MAP_FILE, + "tokenizer_config_file": TOKENIZER_CONFIG_FILE, + "full_tokenizer_file": FULL_TOKENIZER_FILE, + } + # Look for the tokenizer files + for file_id, file_name in {**cls.vocab_files_names, **additional_files_names}.items(): + if os.path.isdir(pretrained_model_name_or_path): + full_file_name = os.path.join(pretrained_model_name_or_path, file_name) + if not os.path.exists(full_file_name): + logger.info("Didn't find file {}. We won't load it.".format(full_file_name)) + full_file_name = None + else: + full_file_name = hf_bucket_url( + pretrained_model_name_or_path, filename=file_name, use_cdn=False + ) + + vocab_files[file_id] = full_file_name + + # Get files from url, cache, or disk depending on the case + try: + resolved_vocab_files = {} + for file_id, file_path in vocab_files.items(): + if file_path is None: + resolved_vocab_files[file_id] = None + else: + resolved_vocab_files[file_id] = cached_path( + file_path, + cache_dir=cache_dir, + force_download=force_download, + proxies=proxies, + resume_download=resume_download, + local_files_only=local_files_only, + ) + except EnvironmentError: + if pretrained_model_name_or_path in s3_models: + msg = "Couldn't reach server at '{}' to download vocabulary files." + else: + msg = ( + "Model name '{}' was not found in tokenizers model name list ({}). " + "We assumed '{}' was a path or url to a directory containing vocabulary files " + "named {}, but couldn't find such vocabulary files at this path or url.".format( + pretrained_model_name_or_path, + ", ".join(s3_models), + pretrained_model_name_or_path, + list(cls.vocab_files_names.values()), + ) + ) + + raise EnvironmentError(msg) + + if all(full_file_name is None for full_file_name in resolved_vocab_files.values()): + raise EnvironmentError( + "Model name '{}' was not found in tokenizers model name list ({}). " + "We assumed '{}' was a path, a model identifier, or url to a directory containing vocabulary files " + "named {} but couldn't find such vocabulary files at this path or url.".format( + pretrained_model_name_or_path, + ", ".join(s3_models), + pretrained_model_name_or_path, + list(cls.vocab_files_names.values()), + ) + ) + + for file_id, file_path in vocab_files.items(): + if file_path == resolved_vocab_files[file_id]: + logger.info("loading file {}".format(file_path)) + else: + logger.info("loading file {} from cache at {}".format(file_path, resolved_vocab_files[file_id])) + + # Prepare tokenizer initialization kwargs + # Did we saved some inputs and kwargs to reload ? + tokenizer_config_file = resolved_vocab_files.pop("tokenizer_config_file", None) + if tokenizer_config_file is not None: + with open(tokenizer_config_file, encoding="utf-8") as tokenizer_config_handle: + init_kwargs = json.load(tokenizer_config_handle) + saved_init_inputs = init_kwargs.pop("init_inputs", ()) + if not init_inputs: + init_inputs = saved_init_inputs + else: + init_kwargs = init_configuration + + # Update with newly provided kwargs + init_kwargs.update(kwargs) + + # Set max length if needed + if pretrained_model_name_or_path in cls.max_model_input_sizes: + # if we're using a pretrained model, ensure the tokenizer + # wont index sequences longer than the number of positional embeddings + model_max_length = cls.max_model_input_sizes[pretrained_model_name_or_path] + if model_max_length is not None and isinstance(model_max_length, (int, float)): + init_kwargs["model_max_length"] = min(init_kwargs.get("model_max_length", int(1e30)), model_max_length) + + # Merge resolved_vocab_files arguments in init_kwargs. + added_tokens_file = resolved_vocab_files.pop("added_tokens_file", None) + for args_name, file_path in resolved_vocab_files.items(): + if args_name not in init_kwargs: + init_kwargs[args_name] = file_path + + # Instantiate tokenizer. + try: + tokenizer = cls(*init_inputs, **init_kwargs) + except OSError: + raise OSError( + "Unable to load vocabulary from file. " + "Please check that the provided vocabulary is accessible and not corrupted." + ) + + # Save inputs and kwargs for saving and re-loading with ``save_pretrained`` + tokenizer.init_inputs = init_inputs + tokenizer.init_kwargs = init_kwargs + + # If there is a complementary special token map, load it + special_tokens_map_file = resolved_vocab_files.pop("special_tokens_map_file", None) + if special_tokens_map_file is not None: + with open(special_tokens_map_file, encoding="utf-8") as special_tokens_map_handle: + special_tokens_map = json.load(special_tokens_map_handle) + + for key, value in special_tokens_map.items(): + if isinstance(value, dict): + value = AddedToken(**value) + setattr(tokenizer, key, value) + + # Add supplementary tokens. + special_tokens = tokenizer.all_special_tokens + if added_tokens_file is not None: + with open(added_tokens_file, encoding="utf-8") as added_tokens_handle: + added_tok_encoder = json.load(added_tokens_handle) + + # Sort added tokens by index + added_tok_encoder_sorted = list(sorted(added_tok_encoder.items(), key=lambda x: x[1])) + + for token, index in added_tok_encoder_sorted: + assert index == len(tokenizer), ( + f"Non-consecutive added token '{token}' found. " + f"Should have index {len(tokenizer)} but has index {index} in saved vocabulary." + ) + tokenizer.add_tokens(token, special_tokens=bool(token in special_tokens)) + + # Check all our special tokens are registrered as "no split" token (we don't cut them) and are in the vocab + added_tokens = tokenizer.sanitize_special_tokens() + if added_tokens: + logger.warning( + "Special tokens have been added in the vocabulary, make sure the associated word emebedding are fine-tuned or trained." + ) + + return tokenizer + + def save_pretrained(self, save_directory) -> Tuple[str]: + """ Save the tokenizer vocabulary files together with: + - added tokens, + - special-tokens-to-class-attributes-mapping, + - tokenizer instantiation positional and keywords inputs (e.g. do_lower_case for Bert). + + Warning: This won't save modifications you may have applied to the tokenizer after the instantiation + (e.g. modifying tokenizer.do_lower_case after creation). + + This method make sure the full tokenizer can then be re-loaded using the + :func:`~transformers.PreTrainedTokenizer.from_pretrained` class method. + """ + if os.path.isfile(save_directory): + logger.error("Provided path ({}) should be a directory, not a file".format(save_directory)) + return + os.makedirs(save_directory, exist_ok=True) + + special_tokens_map_file = os.path.join(save_directory, SPECIAL_TOKENS_MAP_FILE) + added_tokens_file = os.path.join(save_directory, ADDED_TOKENS_FILE) + tokenizer_config_file = os.path.join(save_directory, TOKENIZER_CONFIG_FILE) + + tokenizer_config = copy.deepcopy(self.init_kwargs) + if len(self.init_inputs) > 0: + tokenizer_config["init_inputs"] = copy.deepcopy(self.init_inputs) + for file_id in self.vocab_files_names.keys(): + tokenizer_config.pop(file_id, None) + + with open(tokenizer_config_file, "w", encoding="utf-8") as f: + f.write(json.dumps(tokenizer_config, ensure_ascii=False)) + + with open(special_tokens_map_file, "w", encoding="utf-8") as f: + write_dict = {} + for key, value in self.special_tokens_map_extended.items(): + if isinstance(value, AddedToken): + write_dict[key] = value.__getstate__() + else: + write_dict[key] = value + f.write(json.dumps(write_dict, ensure_ascii=False)) + + added_vocab = self.get_added_vocab() + if added_vocab: + with open(added_tokens_file, "w", encoding="utf-8") as f: + out_str = json.dumps(added_vocab, ensure_ascii=False) + f.write(out_str) + + vocab_files = self.save_vocabulary(save_directory) + + return vocab_files + (special_tokens_map_file, added_tokens_file) + + @add_end_docstrings( + ENCODE_KWARGS_DOCSTRING, + """ + **kwargs: passed to the `self.tokenize()` method. + """, + ) + def encode( + self, + text: Union[TextInput, PreTokenizedInput, EncodedInput], + text_pair: Optional[Union[TextInput, PreTokenizedInput, EncodedInput]] = None, + add_special_tokens: bool = True, + padding: Union[bool, str] = False, + truncation: Union[bool, str] = False, + max_length: Optional[int] = None, + stride: int = 0, + return_tensors: Optional[Union[str, TensorType]] = None, + **kwargs + ): + """ + Converts a string in a sequence of ids (integer), using the tokenizer and vocabulary. + + Same as doing ``self.convert_tokens_to_ids(self.tokenize(text))``. + + Args: + text (:obj:`str`, :obj:`List[str]` or :obj:`List[int]`): + The first sequence to be encoded. This can be a string, a list of strings (tokenized string using + the `tokenize` method) or a list of integers (tokenized string ids using the `convert_tokens_to_ids` + method) + text_pair (:obj:`str`, :obj:`List[str]` or :obj:`List[int]`, `optional`, defaults to :obj:`None`): + Optional second sequence to be encoded. This can be a string, a list of strings (tokenized + string using the `tokenize` method) or a list of integers (tokenized string ids using the + `convert_tokens_to_ids` method) + """ + encoded_inputs = self.encode_plus( + text, + text_pair=text_pair, + add_special_tokens=add_special_tokens, + padding=padding, + truncation=truncation, + max_length=max_length, + stride=stride, + return_tensors=return_tensors, + **kwargs, + ) + + return encoded_inputs["input_ids"] + + def num_special_tokens_to_add(self, pair: bool = False) -> int: + raise NotImplementedError + + def _get_padding_truncation_strategies( + self, padding=False, truncation=False, max_length=None, pad_to_multiple_of=None, verbose=True, **kwargs + ): + """ Find the correct padding/truncation strategy with backward compatibility + for old arguments (truncation_strategy and pad_to_max_length) and behaviors. + """ + old_truncation_strategy = kwargs.pop("truncation_strategy", "do_not_truncate") + old_pad_to_max_length = kwargs.pop("pad_to_max_length", False) + + # Backward compatibility for previous behavior, maybe we should deprecate it: + # If you only set max_length, it activates truncation for max_length + if max_length is not None and padding is False and truncation is False: + if verbose: + logger.warning( + "Truncation was not explicitely activated but `max_length` is provided a specific value, " + "please use `truncation=True` to explicitely truncate examples to max length. " + "Defaulting to 'longest_first' truncation strategy. " + "If you encode pairs of sequences (GLUE-style) with the tokenizer you can select this strategy " + "more precisely by providing a specific strategy to `truncation`." + ) + truncation = "longest_first" + + # Get padding strategy + if padding is False and old_pad_to_max_length: + if verbose: + warnings.warn( + "The `pad_to_max_length` argument is deprecated and will be removed in a future version, " + "use `padding=True` or `padding='longest'` to pad to the longest sequence in the batch, or " + "use `padding='max_length'` to pad to a max length. In this case, you can give a specific " + "length with `max_length` (e.g. `max_length=45`) or leave max_length to None to pad to the " + "maximal input size of the model (e.g. 512 for Bert).", + DeprecationWarning, + ) + if max_length is None: + padding_strategy = PaddingStrategy.LONGEST + else: + padding_strategy = PaddingStrategy.MAX_LENGTH + elif padding is not False: + if padding is True: + padding_strategy = PaddingStrategy.LONGEST # Default to pad to the longest sequence in the batch + elif not isinstance(padding, PaddingStrategy): + padding_strategy = PaddingStrategy(padding) + else: + padding_strategy = PaddingStrategy.DO_NOT_PAD + + # Get truncation strategy + if truncation is False and old_truncation_strategy != "do_not_truncate": + if verbose: + warnings.warn( + "The `truncation_strategy` argument is deprecated and will be removed in a future version, " + "use `truncation=True` to truncate examples to a max length. You can give a specific " + "length with `max_length` (e.g. `max_length=45`) or leave max_length to None to truncate to the " + "maximal input size of the model (e.g. 512 for Bert). " + " If you have pairs of inputs, you can give a specific truncation strategy selected among " + "`truncation='only_first'` (will only truncate the first sentence in the pairs) " + "`truncation='only_second'` (will only truncate the second sentence in the pairs) " + "or `truncation='longest_first'` (will iteratively remove tokens from the longest sentence in the pairs).", + DeprecationWarning, + ) + truncation_strategy = TruncationStrategy(old_truncation_strategy) + elif truncation is not False: + if truncation is True: + truncation_strategy = ( + TruncationStrategy.LONGEST_FIRST + ) # Default to truncate the longest sequences in pairs of inputs + elif not isinstance(truncation, TruncationStrategy): + truncation_strategy = TruncationStrategy(truncation) + else: + truncation_strategy = TruncationStrategy.DO_NOT_TRUNCATE + + # Set max length if needed + if max_length is None: + if padding_strategy == PaddingStrategy.MAX_LENGTH: + if self.model_max_length > LARGE_INTEGER: + if verbose: + logger.warning( + "Asking to pad to max_length but no maximum length is provided and the model has no predefined maximum length. " + "Default to no padding." + ) + padding_strategy = PaddingStrategy.DO_NOT_PAD + else: + max_length = self.model_max_length + + if truncation_strategy != TruncationStrategy.DO_NOT_TRUNCATE: + if self.model_max_length > LARGE_INTEGER: + if verbose: + logger.warning( + "Asking to truncate to max_length but no maximum length is provided and the model has no predefined maximum length. " + "Default to no truncation." + ) + truncation_strategy = TruncationStrategy.DO_NOT_TRUNCATE + else: + max_length = self.model_max_length + + # Test if we have a padding token + if padding_strategy != PaddingStrategy.DO_NOT_PAD and (not self.pad_token or self.pad_token_id < 0): + raise ValueError( + "Asking to pad but the tokenizer does not have a padding token. " + "Please select a token to use as `pad_token` `(tokenizer.pad_token = tokenizer.eos_token e.g.)` " + "or add a new pad token via `tokenizer.add_special_tokens({'pad_token': '[PAD]'})`." + ) + + # Check that we will truncate to a multiple of pad_to_multiple_of if both are provided + if ( + truncation_strategy != TruncationStrategy.DO_NOT_TRUNCATE + and padding_strategy != PaddingStrategy.DO_NOT_PAD + and pad_to_multiple_of is not None + and max_length is not None + and (max_length % pad_to_multiple_of != 0) + ): + raise ValueError( + f"Truncation and padding are both activated but " + f"truncation length ({max_length}) is not a multiple of pad_to_multiple_of ({pad_to_multiple_of})." + ) + + return padding_strategy, truncation_strategy, max_length, kwargs + + @add_end_docstrings(ENCODE_KWARGS_DOCSTRING, ENCODE_PLUS_ADDITIONAL_KWARGS_DOCSTRING) + def __call__( + self, + text: Union[TextInput, PreTokenizedInput, List[TextInput], List[PreTokenizedInput]], + text_pair: Optional[Union[TextInput, PreTokenizedInput, List[TextInput], List[PreTokenizedInput]]] = None, + add_special_tokens: bool = True, + padding: Union[bool, str] = False, + truncation: Union[bool, str] = False, + max_length: Optional[int] = None, + stride: int = 0, + is_pretokenized: bool = False, + pad_to_multiple_of: Optional[int] = None, + return_tensors: Optional[Union[str, TensorType]] = None, + return_token_type_ids: Optional[bool] = None, + return_attention_mask: Optional[bool] = None, + return_overflowing_tokens: bool = False, + return_special_tokens_mask: bool = False, + return_offsets_mapping: bool = False, + return_length: bool = False, + verbose: bool = True, + **kwargs + ) -> BatchEncoding: + """ + Returns a dictionary containing the encoded sequence or sequence pair and additional information: + the mask for sequence classification and the overflowing elements if a ``max_length`` is specified. + + Args: + text (:obj:`str`, :obj:`List[str]`, :obj:`List[List[str]]``): + The sequence or batch of sequences to be encoded. + Each sequence can be a string or a list of strings (pre-tokenized string). + If the sequences are provided as list of strings (pretokenized), you must set `is_pretokenized=True` + (to lift the ambiguity with a batch of sequences) + text_pair (:obj:`str`, :obj:`List[str]`, :obj:`List[List[str]]``): + The sequence or batch of sequences to be encoded. + Each sequence can be a string or a list of strings (pre-tokenized string). + If the sequences are provided as list of strings (pretokenized), you must set `is_pretokenized=True` + (to lift the ambiguity with a batch of sequences) + """ + # Input type checking for clearer error + assert isinstance(text, str) or ( + isinstance(text, (list, tuple)) + and ( + len(text) == 0 + or ( + isinstance(text[0], str) + or (isinstance(text[0], (list, tuple)) and (len(text[0]) == 0 or isinstance(text[0][0], str))) + ) + ) + ), ( + "text input must of type `str` (single example), `List[str]` (batch or single pretokenized example) " + "or `List[List[str]]` (batch of pretokenized examples)." + ) + + assert ( + text_pair is None + or isinstance(text_pair, str) + or ( + isinstance(text_pair, (list, tuple)) + and ( + len(text_pair) == 0 + or ( + isinstance(text_pair[0], str) + or ( + isinstance(text_pair[0], (list, tuple)) + and (len(text_pair[0]) == 0 or isinstance(text_pair[0][0], str)) + ) + ) + ) + ) + ), ( + "text_pair input must of type `str` (single example), `List[str]` (batch or single pretokenized example) " + "or `List[List[str]]` (batch of pretokenized examples)." + ) + + is_batched = bool( + (not is_pretokenized and isinstance(text, (list, tuple))) + or (is_pretokenized and isinstance(text, (list, tuple)) and text and isinstance(text[0], (list, tuple))) + ) + + if is_batched: + batch_text_or_text_pairs = list(zip(text, text_pair)) if text_pair is not None else text + return self.batch_encode_plus( + batch_text_or_text_pairs=batch_text_or_text_pairs, + add_special_tokens=add_special_tokens, + padding=padding, + truncation=truncation, + max_length=max_length, + stride=stride, + is_pretokenized=is_pretokenized, + pad_to_multiple_of=pad_to_multiple_of, + return_tensors=return_tensors, + return_token_type_ids=return_token_type_ids, + return_attention_mask=return_attention_mask, + return_overflowing_tokens=return_overflowing_tokens, + return_special_tokens_mask=return_special_tokens_mask, + return_offsets_mapping=return_offsets_mapping, + return_length=return_length, + verbose=verbose, + **kwargs, + ) + else: + return self.encode_plus( + text=text, + text_pair=text_pair, + add_special_tokens=add_special_tokens, + padding=padding, + truncation=truncation, + max_length=max_length, + stride=stride, + is_pretokenized=is_pretokenized, + pad_to_multiple_of=pad_to_multiple_of, + return_tensors=return_tensors, + return_token_type_ids=return_token_type_ids, + return_attention_mask=return_attention_mask, + return_overflowing_tokens=return_overflowing_tokens, + return_special_tokens_mask=return_special_tokens_mask, + return_offsets_mapping=return_offsets_mapping, + return_length=return_length, + verbose=verbose, + **kwargs, + ) + + @add_end_docstrings(ENCODE_KWARGS_DOCSTRING, ENCODE_PLUS_ADDITIONAL_KWARGS_DOCSTRING) + def encode_plus( + self, + text: Union[TextInput, PreTokenizedInput, EncodedInput], + text_pair: Optional[Union[TextInput, PreTokenizedInput, EncodedInput]] = None, + add_special_tokens: bool = True, + padding: Union[bool, str] = False, + truncation: Union[bool, str] = False, + max_length: Optional[int] = None, + stride: int = 0, + is_pretokenized: bool = False, + pad_to_multiple_of: Optional[int] = None, + return_tensors: Optional[Union[str, TensorType]] = None, + return_token_type_ids: Optional[bool] = None, + return_attention_mask: Optional[bool] = None, + return_overflowing_tokens: bool = False, + return_special_tokens_mask: bool = False, + return_offsets_mapping: bool = False, + return_length: bool = False, + verbose: bool = True, + **kwargs + ) -> BatchEncoding: + """ + Returns a dictionary containing the encoded sequence or sequence pair and additional information: + the mask for sequence classification and the overflowing elements if a ``max_length`` is specified. + + Args: + text (:obj:`str`, :obj:`List[str]` or :obj:`List[int]` (the later only for not-fast tokenizers)): + The first sequence to be encoded. This can be a string, a list of strings (tokenized string using + the `tokenize` method) or a list of integers (tokenized string ids using the `convert_tokens_to_ids` + method) + text_pair (:obj:`str`, :obj:`List[str]` or :obj:`List[int]`, `optional`, defaults to :obj:`None`): + Optional second sequence to be encoded. This can be a string, a list of strings (tokenized + string using the `tokenize` method) or a list of integers (tokenized string ids using the + `convert_tokens_to_ids` method) + """ + + # Backward compatibility for 'truncation_strategy', 'pad_to_max_length' + padding_strategy, truncation_strategy, max_length, kwargs = self._get_padding_truncation_strategies( + padding=padding, + truncation=truncation, + max_length=max_length, + pad_to_multiple_of=pad_to_multiple_of, + verbose=verbose, + **kwargs, + ) + + return self._encode_plus( + text=text, + text_pair=text_pair, + add_special_tokens=add_special_tokens, + padding_strategy=padding_strategy, + truncation_strategy=truncation_strategy, + max_length=max_length, + stride=stride, + is_pretokenized=is_pretokenized, + pad_to_multiple_of=pad_to_multiple_of, + return_tensors=return_tensors, + return_token_type_ids=return_token_type_ids, + return_attention_mask=return_attention_mask, + return_overflowing_tokens=return_overflowing_tokens, + return_special_tokens_mask=return_special_tokens_mask, + return_offsets_mapping=return_offsets_mapping, + return_length=return_length, + verbose=verbose, + **kwargs, + ) + + def _encode_plus( + self, + text: Union[TextInput, PreTokenizedInput, EncodedInput], + text_pair: Optional[Union[TextInput, PreTokenizedInput, EncodedInput]] = None, + add_special_tokens: bool = True, + padding_strategy: PaddingStrategy = PaddingStrategy.DO_NOT_PAD, + truncation_strategy: TruncationStrategy = TruncationStrategy.DO_NOT_TRUNCATE, + max_length: Optional[int] = None, + stride: int = 0, + is_pretokenized: bool = False, + pad_to_multiple_of: Optional[int] = None, + return_tensors: Optional[Union[str, TensorType]] = None, + return_token_type_ids: Optional[bool] = None, + return_attention_mask: Optional[bool] = None, + return_overflowing_tokens: bool = False, + return_special_tokens_mask: bool = False, + return_offsets_mapping: bool = False, + return_length: bool = False, + verbose: bool = True, + **kwargs + ) -> BatchEncoding: + raise NotImplementedError + + @add_end_docstrings(ENCODE_KWARGS_DOCSTRING, ENCODE_PLUS_ADDITIONAL_KWARGS_DOCSTRING) + def batch_encode_plus( + self, + batch_text_or_text_pairs: Union[ + List[TextInput], + List[TextInputPair], + List[PreTokenizedInput], + List[PreTokenizedInputPair], + List[EncodedInput], + List[EncodedInputPair], + ], + add_special_tokens: bool = True, + padding: Union[bool, str] = False, + truncation: Union[bool, str] = False, + max_length: Optional[int] = None, + stride: int = 0, + is_pretokenized: bool = False, + pad_to_multiple_of: Optional[int] = None, + return_tensors: Optional[Union[str, TensorType]] = None, + return_token_type_ids: Optional[bool] = None, + return_attention_mask: Optional[bool] = None, + return_overflowing_tokens: bool = False, + return_special_tokens_mask: bool = False, + return_offsets_mapping: bool = False, + return_length: bool = False, + verbose: bool = True, + **kwargs + ) -> BatchEncoding: + """ + Returns a dictionary containing the encoded sequence or sequence pair and additional information: + the mask for sequence classification and the overflowing elements if a ``max_length`` is specified. + + Args: + batch_text_or_text_pairs (:obj:`List[str]`, :obj:`List[Tuple[str, str]]`, + :obj:`List[List[str]]`, :obj:`List[Tuple[List[str], List[str]]]`, + and for not-fast tokenizers, also: + :obj:`List[List[int]]`, :obj:`List[Tuple[List[int], List[int]]]`): + Batch of sequences or pair of sequences to be encoded. + This can be a list of string/string-sequences/int-sequences or a list of pair of + string/string-sequences/int-sequence (see details in encode_plus) + """ + + # Backward compatibility for 'truncation_strategy', 'pad_to_max_length' + padding_strategy, truncation_strategy, max_length, kwargs = self._get_padding_truncation_strategies( + padding=padding, + truncation=truncation, + max_length=max_length, + pad_to_multiple_of=pad_to_multiple_of, + verbose=verbose, + **kwargs, + ) + + return self._batch_encode_plus( + batch_text_or_text_pairs=batch_text_or_text_pairs, + add_special_tokens=add_special_tokens, + padding_strategy=padding_strategy, + truncation_strategy=truncation_strategy, + max_length=max_length, + stride=stride, + is_pretokenized=is_pretokenized, + pad_to_multiple_of=pad_to_multiple_of, + return_tensors=return_tensors, + return_token_type_ids=return_token_type_ids, + return_attention_mask=return_attention_mask, + return_overflowing_tokens=return_overflowing_tokens, + return_special_tokens_mask=return_special_tokens_mask, + return_offsets_mapping=return_offsets_mapping, + return_length=return_length, + verbose=verbose, + **kwargs, + ) + + def _batch_encode_plus( + self, + batch_text_or_text_pairs: Union[ + List[TextInput], + List[TextInputPair], + List[PreTokenizedInput], + List[PreTokenizedInputPair], + List[EncodedInput], + List[EncodedInputPair], + ], + add_special_tokens: bool = True, + padding_strategy: PaddingStrategy = PaddingStrategy.DO_NOT_PAD, + truncation_strategy: TruncationStrategy = TruncationStrategy.DO_NOT_TRUNCATE, + max_length: Optional[int] = None, + stride: int = 0, + is_pretokenized: bool = False, + pad_to_multiple_of: Optional[int] = None, + return_tensors: Optional[Union[str, TensorType]] = None, + return_token_type_ids: Optional[bool] = None, + return_attention_mask: Optional[bool] = None, + return_overflowing_tokens: bool = False, + return_special_tokens_mask: bool = False, + return_offsets_mapping: bool = False, + return_length: bool = False, + verbose: bool = True, + **kwargs + ) -> BatchEncoding: + raise NotImplementedError + + def pad( + self, + encoded_inputs: Union[ + BatchEncoding, + List[BatchEncoding], + Dict[str, EncodedInput], + Dict[str, List[EncodedInput]], + List[Dict[str, EncodedInput]], + ], + padding: Union[bool, str] = True, + max_length: Optional[int] = None, + pad_to_multiple_of: Optional[int] = None, + return_attention_mask: Optional[bool] = None, + return_tensors: Optional[Union[str, TensorType]] = None, + verbose: bool = True, + ) -> BatchEncoding: + """ Pad a single encoded input or a batch of encoded inputs up to predefined length or to the max sequence length in the batch. + + Padding side (left/right) padding token ids are defined at the tokenizer level + (with ``self.padding_side``, ``self.pad_token_id`` and ``self.pad_token_type_id``) + + Args: + encoded_inputs: Dictionary of tokenized inputs (`Dict[str, List[int]]`) or batch of tokenized inputs. + Batch of tokenized inputs can be given as dicts of lists or lists of dicts, both work so you can + use ``tokenizer.pad()`` during pre-processing as well as in a PyTorch Dataloader collate function. + (`Dict[str, List[List[int]]]` or `List[Dict[str, List[int]]]`). + padding: Boolean or specific strategy to use for padding. + Select a strategy to pad the returned sequences (according to the model's padding side and padding index) among: + - 'longest' (or `True`) Pad to the longest sequence in the batch + - 'max_length': Pad to the max length (default) + - 'do_not_pad' (or `False`): Do not pad + max_length: maximum length of the returned list and optionally padding length (see below). + Will truncate by taking into account the special tokens. + pad_to_multiple_of: (optional) Integer if set will pad the sequence to a multiple of the provided value. + This is especially useful to enable the use of Tensor Core on NVIDIA hardware with compute capability + >= 7.5 (Volta). + return_attention_mask: (optional) Set to False to avoid returning attention mask (default: set to model specifics) + return_tensors (:obj:`str`, `optional`, defaults to :obj:`None`): + Can be set to 'tf', 'pt' or 'np' to return respectively TensorFlow :obj:`tf.constant`, + PyTorch :obj:`torch.Tensor` or Numpy :oj: `np.ndarray` instead of a list of python integers. + verbose (:obj:`bool`, `optional`, defaults to :obj:`True`): + Set to ``False`` to avoid printing infos and warnings. + """ + # If we have a list of dicts, let's convert it in a dict of lists + if isinstance(encoded_inputs, (list, tuple)) and isinstance(encoded_inputs[0], (dict, BatchEncoding)): + encoded_inputs = {key: [example[key] for example in encoded_inputs] for key in encoded_inputs[0].keys()} + + assert "input_ids" in encoded_inputs, ( + "You should supply an encoding or a list of encodings to this method. " + "An encoding is the output of one the encoding methods of the tokenizer, i.e. " + "__call__/encode_plus/batch_encode_plus. " + ) + + if not encoded_inputs["input_ids"]: + if return_attention_mask: + encoded_inputs["attention_mask"] = [] + return encoded_inputs + + # Convert padding_strategy in PaddingStrategy + padding_strategy, _, max_length, _ = self._get_padding_truncation_strategies( + padding=padding, max_length=max_length, verbose=verbose + ) + + if encoded_inputs["input_ids"] and not isinstance(encoded_inputs["input_ids"][0], (list, tuple)): + encoded_inputs = self._pad( + encoded_inputs, + max_length=max_length, + padding_strategy=padding_strategy, + pad_to_multiple_of=pad_to_multiple_of, + return_attention_mask=return_attention_mask, + ) + return BatchEncoding(encoded_inputs, tensor_type=return_tensors) + + batch_size = len(encoded_inputs["input_ids"]) + assert all( + len(v) == batch_size for v in encoded_inputs.values() + ), "Some items in the output dictionnary have a different batch size than others." + + if padding_strategy == PaddingStrategy.LONGEST: + max_length = max(len(inputs) for inputs in encoded_inputs["input_ids"]) + padding_strategy = PaddingStrategy.MAX_LENGTH + + batch_outputs = {} + for i in range(batch_size): + inputs = dict((k, v[i]) for k, v in encoded_inputs.items()) + outputs = self._pad( + inputs, + max_length=max_length, + padding_strategy=padding_strategy, + pad_to_multiple_of=pad_to_multiple_of, + return_attention_mask=return_attention_mask, + ) + + for key, value in outputs.items(): + if key not in batch_outputs: + batch_outputs[key] = [] + batch_outputs[key].append(value) + + return BatchEncoding(batch_outputs, tensor_type=return_tensors) + + def create_token_type_ids_from_sequences(self, token_ids_0: List, token_ids_1: Optional[List] = None) -> List[int]: + if token_ids_1 is None: + return len(token_ids_0) * [0] + return [0] * len(token_ids_0) + [1] * len(token_ids_1) + + def build_inputs_with_special_tokens(self, token_ids_0: List, token_ids_1: Optional[List] = None) -> List: + """ + Build model inputs from a sequence or a pair of sequence for sequence classification tasks + by concatenating and adding special tokens. This implementation does not add special tokens. + """ + if token_ids_1 is None: + return token_ids_0 + return token_ids_0 + token_ids_1 + + @add_end_docstrings(ENCODE_KWARGS_DOCSTRING, ENCODE_PLUS_ADDITIONAL_KWARGS_DOCSTRING) + def prepare_for_model( + self, + ids: List[int], + pair_ids: Optional[List[int]] = None, + add_special_tokens: bool = True, + padding: Union[bool, str] = False, + truncation: Union[bool, str] = False, + max_length: Optional[int] = None, + stride: int = 0, + pad_to_multiple_of: Optional[int] = None, + return_tensors: Optional[Union[str, TensorType]] = None, + return_token_type_ids: Optional[bool] = None, + return_attention_mask: Optional[bool] = None, + return_overflowing_tokens: bool = False, + return_special_tokens_mask: bool = False, + return_offsets_mapping: bool = False, + return_length: bool = False, + verbose: bool = True, + prepend_batch_axis: bool = False, + **kwargs + ) -> BatchEncoding: + """ Prepares a sequence of input id, or a pair of sequences of inputs ids so that it can be used by the model. + It adds special tokens, truncates sequences if overflowing while taking into account the special tokens and + manages a moving window (with user defined stride) for overflowing tokens + + Args: + ids: list of tokenized input ids. Can be obtained from a string by chaining the + `tokenize` and `convert_tokens_to_ids` methods. + pair_ids: Optional second list of input ids. Can be obtained from a string by chaining the + `tokenize` and `convert_tokens_to_ids` methods. + """ + + if "return_lengths" in kwargs: + if verbose: + warnings.warn( + "The PreTrainedTokenizerBase.prepare_for_model `return_lengths` parameter is deprecated. " + "Please use `return_length` instead.", + FutureWarning, + ) + return_length = kwargs["return_lengths"] + + # Backward compatibility for 'truncation_strategy', 'pad_to_max_length' + padding_strategy, truncation_strategy, max_length, kwargs = self._get_padding_truncation_strategies( + padding=padding, + truncation=truncation, + max_length=max_length, + pad_to_multiple_of=pad_to_multiple_of, + verbose=verbose, + **kwargs, + ) + + pair = bool(pair_ids is not None) + len_ids = len(ids) + len_pair_ids = len(pair_ids) if pair else 0 + + # Load from model defaults + if return_token_type_ids is None: + return_token_type_ids = "token_type_ids" in self.model_input_names + if return_attention_mask is None: + return_attention_mask = "attention_mask" in self.model_input_names + + encoded_inputs = {} + + # Compute the total size of the returned encodings + total_len = len_ids + len_pair_ids + (self.num_special_tokens_to_add(pair=pair) if add_special_tokens else 0) + + # Truncation: Handle max sequence length + if truncation_strategy != TruncationStrategy.DO_NOT_TRUNCATE and max_length and total_len > max_length: + ids, pair_ids, overflowing_tokens = self.truncate_sequences( + ids, + pair_ids=pair_ids, + num_tokens_to_remove=total_len - max_length, + truncation_strategy=truncation_strategy, + stride=stride, + ) + if return_overflowing_tokens: + encoded_inputs["overflowing_tokens"] = overflowing_tokens + encoded_inputs["num_truncated_tokens"] = total_len - max_length + + # Add special tokens + if add_special_tokens: + sequence = self.build_inputs_with_special_tokens(ids, pair_ids) + token_type_ids = self.create_token_type_ids_from_sequences(ids, pair_ids) + else: + sequence = ids + pair_ids if pair else ids + token_type_ids = [0] * len(ids) + ([1] * len(pair_ids) if pair else []) + + # Build output dictionnary + encoded_inputs["input_ids"] = sequence + if return_token_type_ids: + encoded_inputs["token_type_ids"] = token_type_ids + if return_special_tokens_mask: + if add_special_tokens: + encoded_inputs["special_tokens_mask"] = self.get_special_tokens_mask(ids, pair_ids) + else: + encoded_inputs["special_tokens_mask"] = [0] * len(sequence) + + # Check lengths + if max_length is None and len(encoded_inputs["input_ids"]) > self.model_max_length and verbose: + logger.warning( + "Token indices sequence length is longer than the specified maximum sequence length " + "for this model ({} > {}). Running this sequence through the model will result in " + "indexing errors".format(len(ids), self.model_max_length) + ) + + # Padding + if padding_strategy != PaddingStrategy.DO_NOT_PAD or return_attention_mask: + encoded_inputs = self.pad( + encoded_inputs, + max_length=max_length, + padding=padding_strategy.value, + pad_to_multiple_of=pad_to_multiple_of, + return_attention_mask=return_attention_mask, + ) + + if return_length: + encoded_inputs["length"] = len(encoded_inputs["input_ids"]) + + batch_outputs = BatchEncoding( + encoded_inputs, tensor_type=return_tensors, prepend_batch_axis=prepend_batch_axis + ) + + return batch_outputs + + def truncate_sequences( + self, + ids: List[int], + pair_ids: Optional[List[int]] = None, + num_tokens_to_remove: int = 0, + truncation_strategy: Union[str, TruncationStrategy] = "longest_first", + stride: int = 0, + ) -> Tuple[List[int], List[int], List[int]]: + """ Truncates a sequence pair in place to the maximum length. + + Args: + ids: list of tokenized input ids. Can be obtained from a string by chaining the + `tokenize` and `convert_tokens_to_ids` methods. + pair_ids: Optional second list of input ids. Can be obtained from a string by chaining the + `tokenize` and `convert_tokens_to_ids` methods. + num_tokens_to_remove (:obj:`int`, `optional`, defaults to ``0``): + number of tokens to remove using the truncation strategy + truncation_strategy (:obj:`string`, `optional`, defaults to "longest_first"): + String selected in the following options: + + - 'longest_first' (default): Iteratively reduce the inputs sequence until the input is under max_length + starting from the longest one at each token (when there is a pair of input sequences). + Overflowing tokens only contains overflow from the first sequence. + - 'only_first': Only truncate the first sequence. raise an error if the first sequence is shorter or equal to than num_tokens_to_remove. + - 'only_second': Only truncate the second sequence + - 'do_not_truncate' + stride (:obj:`int`, `optional`, defaults to ``0``): + If set to a number along with max_length, the overflowing tokens returned will contain some tokens + from the main sequence returned. The value of this argument defines the number of additional tokens. + """ + if num_tokens_to_remove <= 0: + return ids, pair_ids, [] + + if not isinstance(truncation_strategy, TruncationStrategy): + truncation_strategy = TruncationStrategy(truncation_strategy) + + overflowing_tokens = [] + if truncation_strategy == TruncationStrategy.LONGEST_FIRST: + for _ in range(num_tokens_to_remove): + if pair_ids is None or len(ids) > len(pair_ids): + if not overflowing_tokens: + window_len = min(len(ids), stride + 1) + else: + window_len = 1 + overflowing_tokens.extend(ids[-window_len:]) + ids = ids[:-1] + else: + if not overflowing_tokens: + window_len = min(len(pair_ids), stride + 1) + else: + window_len = 1 + overflowing_tokens.extend(pair_ids[-window_len:]) + pair_ids = pair_ids[:-1] + elif truncation_strategy == TruncationStrategy.ONLY_FIRST: + if len(ids) > num_tokens_to_remove: + window_len = min(len(ids), stride + num_tokens_to_remove) + overflowing_tokens = ids[-window_len:] + ids = ids[:-num_tokens_to_remove] + else: + logger.error( + f"We need to remove {num_tokens_to_remove} to truncate the input" + f"but the first sequence has a length {len(ids)}. " + f"Please select another truncation strategy than {truncation_strategy}, " + f"for instance 'longest_first' or 'only_second'." + ) + elif truncation_strategy == TruncationStrategy.ONLY_SECOND and pair_ids is not None: + if len(pair_ids) > num_tokens_to_remove: + window_len = min(len(pair_ids), stride + num_tokens_to_remove) + overflowing_tokens = pair_ids[-window_len:] + pair_ids = pair_ids[:-num_tokens_to_remove] + else: + logger.error( + f"We need to remove {num_tokens_to_remove} to truncate the input" + f"but the second sequence has a length {len(pair_ids)}. " + f"Please select another truncation strategy than {truncation_strategy}, " + f"for instance 'longest_first' or 'only_first'." + ) + + return (ids, pair_ids, overflowing_tokens) + + def _pad( + self, + encoded_inputs: Union[Dict[str, EncodedInput], BatchEncoding], + max_length: Optional[int] = None, + padding_strategy: PaddingStrategy = PaddingStrategy.DO_NOT_PAD, + pad_to_multiple_of: Optional[int] = None, + return_attention_mask: Optional[bool] = None, + ) -> dict: + """ Pad encoded inputs (on left/right and up to predefined legnth or max length in the batch) + + Args: + encoded_inputs: Dictionary of tokenized inputs (`List[int]`) or batch of tokenized inputs (`List[List[int]]`). + max_length: maximum length of the returned list and optionally padding length (see below). + Will truncate by taking into account the special tokens. + padding_strategy: PaddingStrategy to use for padding. + - PaddingStrategy.LONGEST Pad to the longest sequence in the batch + - PaddingStrategy.MAX_LENGTH: Pad to the max length (default) + - PaddingStrategy.DO_NOT_PAD: Do not pad + The tokenizer padding sides are defined in self.padding_side: + - 'left': pads on the left of the sequences + - 'right': pads on the right of the sequences + pad_to_multiple_of: (optional) Integer if set will pad the sequence to a multiple of the provided value. + This is especially useful to enable the use of Tensor Core on NVIDIA hardware with compute capability + >= 7.5 (Volta). + return_attention_mask: (optional) Set to False to avoid returning attention mask (default: set to model specifics) + """ + # Load from model defaults + if return_attention_mask is None: + return_attention_mask = "attention_mask" in self.model_input_names + + if padding_strategy == PaddingStrategy.LONGEST: + max_length = len(encoded_inputs["input_ids"]) + + if max_length is not None and pad_to_multiple_of is not None and (max_length % pad_to_multiple_of != 0): + max_length = ((max_length // pad_to_multiple_of) + 1) * pad_to_multiple_of + + needs_to_be_padded = ( + padding_strategy != PaddingStrategy.DO_NOT_PAD and len(encoded_inputs["input_ids"]) != max_length + ) + + if needs_to_be_padded: + difference = max_length - len(encoded_inputs["input_ids"]) + if self.padding_side == "right": + if return_attention_mask: + encoded_inputs["attention_mask"] = [1] * len(encoded_inputs["input_ids"]) + [0] * difference + if "token_type_ids" in encoded_inputs: + encoded_inputs["token_type_ids"] = ( + encoded_inputs["token_type_ids"] + [self.pad_token_type_id] * difference + ) + if "special_tokens_mask" in encoded_inputs: + encoded_inputs["special_tokens_mask"] = encoded_inputs["special_tokens_mask"] + [1] * difference + encoded_inputs["input_ids"] = encoded_inputs["input_ids"] + [self.pad_token_id] * difference + elif self.padding_side == "left": + if return_attention_mask: + encoded_inputs["attention_mask"] = [0] * difference + [1] * len(encoded_inputs["input_ids"]) + if "token_type_ids" in encoded_inputs: + encoded_inputs["token_type_ids"] = [self.pad_token_type_id] * difference + encoded_inputs[ + "token_type_ids" + ] + if "special_tokens_mask" in encoded_inputs: + encoded_inputs["special_tokens_mask"] = [1] * difference + encoded_inputs["special_tokens_mask"] + encoded_inputs["input_ids"] = [self.pad_token_id] * difference + encoded_inputs["input_ids"] + else: + raise ValueError("Invalid padding strategy:" + str(self.padding_side)) + else: + if return_attention_mask: + encoded_inputs["attention_mask"] = [1] * len(encoded_inputs["input_ids"]) + + return encoded_inputs + + def batch_decode(self, sequences: List[List[int]], **kwargs) -> List[str]: + return [self.decode(seq, **kwargs) for seq in sequences] + + def decode( + self, token_ids: List[int], skip_special_tokens: bool = False, clean_up_tokenization_spaces: bool = True + ) -> str: + """ + Converts a sequence of ids (integer) in a string, using the tokenizer and vocabulary + with options to remove special tokens and clean up tokenization spaces. + Similar to doing ``self.convert_tokens_to_string(self.convert_ids_to_tokens(token_ids))``. + + Args: + token_ids: list of tokenized input ids. Can be obtained using the `encode` or `encode_plus` methods. + skip_special_tokens: if set to True, will replace special tokens. + clean_up_tokenization_spaces: if set to True, will clean up the tokenization spaces. + """ + raise NotImplementedError + + def get_special_tokens_mask( + self, token_ids_0: List, token_ids_1: Optional[List] = None, already_has_special_tokens: bool = False + ) -> List[int]: + """ + Retrieves sequence ids from a token list that has no special tokens added. This method is called when adding + special tokens using the tokenizer ``prepare_for_model`` or ``encode_plus`` methods. + + Args: + token_ids_0: list of ids (must not contain special tokens) + token_ids_1: Optional list of ids (must not contain special tokens), necessary when fetching sequence ids + for sequence pairs + already_has_special_tokens: (default False) Set to True if the token list is already formated with + special tokens for the model + + Returns: + A list of integers in the range [0, 1]: 1 for a special token, 0 for a sequence token. + """ + assert already_has_special_tokens and token_ids_1 is None, ( + "You cannot use ``already_has_special_tokens=False`` with this tokenizer. " + "Please use a slow (full python) tokenizer to activate this argument." + "Or set `return_special_token_mask=True` when calling the encoding method " + "to get the special tokens mask in any tokenizer. " + ) + + all_special_ids = self.all_special_ids # cache the property + + special_tokens_mask = [1 if token in all_special_ids else 0 for token in token_ids_0] + + return special_tokens_mask + + @staticmethod + def clean_up_tokenization(out_string: str) -> str: + """ Clean up a list of simple English tokenization artifacts like spaces before punctuations and abreviated forms. + """ + out_string = ( + out_string.replace(" .", ".") + .replace(" ?", "?") + .replace(" !", "!") + .replace(" ,", ",") + .replace(" ' ", "'") + .replace(" n't", "n't") + .replace(" 'm", "'m") + .replace(" 's", "'s") + .replace(" 've", "'ve") + .replace(" 're", "'re") + ) + return out_string diff --git a/LAVT-RIS/data.ipynb b/LAVT-RIS/data.ipynb new file mode 100644 index 0000000000000000000000000000000000000000..e584e8dade17f237e636cbca4a4694d092fd935d --- /dev/null +++ b/LAVT-RIS/data.ipynb @@ -0,0 +1,1139 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": 1, + "metadata": {}, + "outputs": [], + "source": [ + "import json\n", + "import os\n", + "\n", + "hardpos_path = os.path.join('/data2/projects/VRIS/llama3', 'verb_ext_text_example_refzom.json')\n", + "with open(hardpos_path, 'r', encoding='utf-8') as f:\n", + " hardpos_json = json.load(f)\n" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "57624\n", + "loading dataset ref-zom into memory...\n", + "loading dataset split final\n", + "creating index...\n", + "index created.\n", + "DONE (t=11.10s)\n" + ] + } + ], + "source": [ + "print(len(hardpos_json.keys()))\n", + "\n", + "from refer.refer_zom import ZREFER\n", + "refer = ZREFER('/data2/dataset/COCO2014/', 'ref-zom', 'final')\n" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "2327 {'2327': []}\n", + "{'sent_ids': [2327], 'file_name': 'COCO_train2014_000000318556.jpg', 'ann_id': [], 'ref_id': 2327, 'image_id': 318556, 'split': 'train', 'source': 'zero', 'sentences': [{'tokens': ['Cooking', 'table', 'in', 'background'], 'raw': 'Cooking table in background', 'sent_id': 2327, 'sent': 'Cooking table in background'}]}\n", + "2328 {'2328': []}\n", + "{'sent_ids': [2328], 'file_name': 'COCO_train2014_000000116100.jpg', 'ann_id': [], 'ref_id': 2328, 'image_id': 116100, 'split': 'train', 'source': 'zero', 'sentences': [{'tokens': ['An', 'elephant', 'that', 'has', \"it's\", 'trunk', 'and', 'all', 'four', 'feet', 'in', 'the', 'water.'], 'raw': \"An elephant that has it's trunk and all four feet in the water.\", 'sent_id': 2328, 'sent': \"An elephant that has it's trunk and all four feet in the water.\"}]}\n", + "2329 {'2329': ['carrying plates of pizza']}\n", + "{'sent_ids': [2329], 'file_name': 'COCO_train2014_000000538480.jpg', 'ann_id': [], 'ref_id': 2329, 'image_id': 538480, 'split': 'train', 'source': 'zero', 'sentences': [{'tokens': ['Man', 'in', 'a', 'black', 'shirt', 'carrying', 'plates', 'of', 'pizza.'], 'raw': 'Man in a black shirt carrying plates of pizza.', 'sent_id': 2329, 'sent': 'Man in a black shirt carrying plates of pizza.'}]}\n", + "2330 {'2330': ['holding']}\n", + "{'sent_ids': [2330], 'file_name': 'COCO_train2014_000000476220.jpg', 'ann_id': [], 'ref_id': 2330, 'image_id': 476220, 'split': 'train', 'source': 'zero', 'sentences': [{'tokens': ['The', 'stuffed', 'pig', 'that', 'the', 'blond', 'boy', 'is', 'holding'], 'raw': 'The stuffed pig that the blond boy is holding', 'sent_id': 2330, 'sent': 'The stuffed pig that the blond boy is holding'}]}\n", + "2331 {'2331': []}\n", + "{'sent_ids': [2331], 'file_name': 'COCO_train2014_000000299675.jpg', 'ann_id': [], 'ref_id': 2331, 'image_id': 299675, 'split': 'train', 'source': 'zero', 'sentences': [{'tokens': ['The', 'MacBook', 'Pro', 'box.'], 'raw': 'The MacBook Pro box.', 'sent_id': 2331, 'sent': 'The MacBook Pro box.'}]}\n", + "2332 {'2332': []}\n", + "{'sent_ids': [2332], 'file_name': 'COCO_train2014_000000032275.jpg', 'ann_id': [], 'ref_id': 2332, 'image_id': 32275, 'split': 'train', 'source': 'zero', 'sentences': [{'tokens': ['A', 'purple', 'brick', 'building', 'with', 'a', 'black', 'and', 'blue', 'parking', 'meter.', ''], 'raw': 'A purple brick building with a black and blue parking meter. ', 'sent_id': 2332, 'sent': 'A purple brick building with a black and blue parking meter. '}]}\n", + "2333 {'2333': ['being wrapped around']}\n", + "{'sent_ids': [2333], 'file_name': 'COCO_train2014_000000025470.jpg', 'ann_id': [], 'ref_id': 2333, 'image_id': 25470, 'split': 'train', 'source': 'zero', 'sentences': [{'tokens': ['The', 'lighter', 'colored', 'giraffe', 'whose', 'neck', 'is', 'wrapped', 'around', 'the', 'other', 'giraffes'], 'raw': 'The lighter colored giraffe whose neck is wrapped around the other giraffes', 'sent_id': 2333, 'sent': 'The lighter colored giraffe whose neck is wrapped around the other giraffes'}]}\n", + "2334 {'2334': ['reaching for a frisbee']}\n", + "{'sent_ids': [2334], 'file_name': 'COCO_train2014_000000513461.jpg', 'ann_id': [], 'ref_id': 2334, 'image_id': 513461, 'split': 'train', 'source': 'zero', 'sentences': [{'tokens': ['A', 'man', 'wearing', 'white', 'and', 'blue', 'shorts,', 'reaching', 'for', 'a', 'frisbee.'], 'raw': 'A man wearing white and blue shorts, reaching for a frisbee.', 'sent_id': 2334, 'sent': 'A man wearing white and blue shorts, reaching for a frisbee.'}]}\n", + "2335 {'2335': []}\n", + "{'sent_ids': [2335], 'file_name': 'COCO_train2014_000000285579.jpg', 'ann_id': [], 'ref_id': 2335, 'image_id': 285579, 'split': 'train', 'source': 'zero', 'sentences': [{'tokens': ['A', 'motorbike', 'occupied', 'by', 'two', 'men', 'dressed', 'like', 'teddy', 'bear.'], 'raw': 'A motorbike occupied by two men dressed like teddy bear.', 'sent_id': 2335, 'sent': 'A motorbike occupied by two men dressed like teddy bear.'}]}\n", + "2336 {'2336': []}\n", + "{'sent_ids': [2336], 'file_name': 'COCO_train2014_000000266366.jpg', 'ann_id': [], 'ref_id': 2336, 'image_id': 266366, 'split': 'train', 'source': 'zero', 'sentences': [{'tokens': ['left', 'portion', 'of', 'sandwich', 'closest', 'to', 'pickle'], 'raw': 'left portion of sandwich closest to pickle', 'sent_id': 2336, 'sent': 'left portion of sandwich closest to pickle'}]}\n", + "2337 {'2337': ['leaning over']}\n", + "{'sent_ids': [2337], 'file_name': 'COCO_train2014_000000321194.jpg', 'ann_id': [], 'ref_id': 2337, 'image_id': 321194, 'split': 'train', 'source': 'zero', 'sentences': [{'tokens': ['A', 'man', 'in', 'white', 'leaning', 'over.'], 'raw': 'A man in white leaning over.', 'sent_id': 2337, 'sent': 'A man in white leaning over.'}]}\n" + ] + } + ], + "source": [ + "for idx, key in enumerate(hardpos_json) :\n", + " print(key, hardpos_json[key])\n", + " print(refer.Refs[int(key)])\n", + " \n", + " if idx == 10 :\n", + " break" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "57624\n" + ] + } + ], + "source": [ + "ref_ids = refer.getRefIds(split='train')\n", + "print(len(ref_ids))" + ] + }, + { + "cell_type": "code", + "execution_count": 18, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "dict_values([['standing next to', 'being held'], ['standing in front']])\n" + ] + } + ], + "source": [ + "pos_sents = hardpos_json['9914'].values()\n", + "print(pos_sents)\n" + ] + }, + { + "cell_type": "code", + "execution_count": 17, + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": 19, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "dict_values([['standing next to', 'being held'], ['standing in front']])\n", + "[['standing next to', 'being held'], ['standing in front']]\n", + "['standing next to', 'being held']\n", + "[101, 100, 100, 102]\n" + ] + } + ], + "source": [ + "from bert.tokenization_bert import BertTokenizer\n", + "import random\n", + "pos_sents = hardpos_json['9914'].values()\n", + "print(pos_sents)\n", + "pos_sents = [s for s in pos_sents if s is not None]\n", + "print(pos_sents)\n", + "pos_sent_picked = random.choice(list(pos_sents))\n", + "print(pos_sent_picked)\n", + "\n", + "\n", + "attention_mask = [0] * 20\n", + "padded_input_ids = [0] * 20\n", + "tokenizer = BertTokenizer.from_pretrained('bert-base-uncased')\n", + "\n", + "input_ids = tokenizer.encode(text=pos_sent_picked, add_special_tokens=True)\n", + "input_ids = input_ids[:20]\n", + "print(input_ids)\n" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/home/seunghoon/.conda/envs/lavt/lib/python3.9/site-packages/tqdm/auto.py:21: TqdmWarning: IProgress not found. Please update jupyter and ipywidgets. See https://ipywidgets.readthedocs.io/en/stable/user_install.html\n", + " from .autonotebook import tqdm as notebook_tqdm\n", + "/home/seunghoon/.conda/envs/lavt/lib/python3.9/site-packages/timm/models/layers/__init__.py:48: FutureWarning: Importing from timm.models.layers is deprecated, please import via timm.layers\n", + " warnings.warn(f\"Importing from {__name__} is deprecated, please import via timm.layers\", FutureWarning)\n" + ] + } + ], + "source": [ + "import datetime\n", + "import argparse\n", + "import os\n", + "import time\n", + "\n", + "import torch\n", + "import torch.utils.data\n", + "from torch import nn\n", + "\n", + "from functools import reduce\n", + "import operator\n", + "from bert.modeling_bert import BertModel\n", + "import torchvision\n", + "from lib import segmentation\n", + "\n", + "import transforms as T\n", + "import utils\n", + "import numpy as np\n", + "\n", + "import torch.nn.functional as F\n", + "\n", + "import gc\n", + "from collections import OrderedDict\n" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Image size: 480\n" + ] + } + ], + "source": [ + "# python -m torch.distributed.launch \\\n", + "# --nproc_per_node 4 \\\n", + "# --master_port ${LOCALHOST} \\\n", + "# train.py \\\n", + "# --model lavt_one \\\n", + "# --dataset refcocog \\\n", + "# --splitBy umd \\\n", + "# --model_id gref_umd \\\n", + "# --batch-size 8 \\\n", + "# --lr 0.00005 \\\n", + "# --wd 1e-2 \\\n", + "# --output-dir ./models/gref_umd/lavt_test_lr \\\n", + "# --swin_type base \\\n", + "# --pretrained_swin_weights ./pretrained_weights/swin_base_patch4_window12_384_22k.pth \\\n", + "# --epochs 40 \\\n", + "# --img_size 480 2>&1 | tee ./models/gref_umd/lavt_test_lr\n", + "import argparse\n", + "from utils import init_distributed_mode\n", + "\n", + "def get_parser():\n", + " parser = argparse.ArgumentParser(description=\"Model Training Configuration\")\n", + " parser.add_argument('--batch_size', default=8, type=int)\n", + " parser.add_argument('--output_dir', default='./models/gref_umd/lavt_test_dset', type=str)\n", + " parser.add_argument('--pretrained_swin_weights', default='./pretrained_weights/swin_base_patch4_window12_384_22k.pth', type=str)\n", + " parser.add_argument('--dataset', default='refcocog', type=str)\n", + " parser.add_argument('--splitBy', default='umd', type=str)\n", + " parser.add_argument('--model', default='lavt_one', type=str)\n", + "\n", + " parser.add_argument('--amsgrad', action='store_true',\n", + " help='if true, set amsgrad to True in an Adam or AdamW optimizer.')\n", + " parser.add_argument('-b', '--batch-size', default=8, type=int)\n", + " parser.add_argument('--bert_tokenizer', default='bert-base-uncased', help='BERT tokenizer')\n", + " parser.add_argument('--ck_bert', default='bert-base-uncased', help='pre-trained BERT weights')\n", + " #parser.add_argument('--dataset', default='refcoco', help='refcoco, refcoco+, or refcocog')\n", + " parser.add_argument('--ddp_trained_weights', action='store_true',\n", + " help='Only needs specified when testing,'\n", + " 'whether the weights to be loaded are from a DDP-trained model')\n", + " parser.add_argument('--device', default='cuda:0', help='device') # only used when testing on a single machine\n", + " parser.add_argument('--epochs', default=40, type=int, metavar='N', help='number of total epochs to run')\n", + " parser.add_argument('--fusion_drop', default=0.0, type=float, help='dropout rate for PWAMs')\n", + " parser.add_argument('--img_size', default=480, type=int, help='input image size')\n", + " parser.add_argument(\"--local_rank\", type=int, help='local rank for DistributedDataParallel')\n", + " parser.add_argument('--lr', default=0.00005, type=float, help='the initial learning rate')\n", + " parser.add_argument('--mha', default='', help='If specified, should be in the format of a-b-c-d, e.g., 4-4-4-4,'\n", + " 'where a, b, c, and d refer to the numbers of heads in stage-1,'\n", + " 'stage-2, stage-3, and stage-4 PWAMs')\n", + " #parser.add_argument('--model', default='lavt', help='model: lavt, lavt_one')\n", + " parser.add_argument('--model_id', default='lavt', help='name to identify the model')\n", + " parser.add_argument('--output-dir', default='./checkpoints/', help='path where to save checkpoint weights')\n", + " parser.add_argument('--pin_mem', action='store_true',\n", + " help='If true, pin memory when using the data loader.')\n", + " parser.add_argument('--print-freq', default=10, type=int, help='print frequency')\n", + " parser.add_argument('--refer_data_root', default='./refer/data/', help='REFER dataset root directory')\n", + " parser.add_argument('--resume', default='', help='resume from checkpoint')\n", + " parser.add_argument('--split', default='test', help='only used when testing')\n", + " #parser.add_argument('--splitBy', default='unc', help='change to umd or google when the dataset is G-Ref (RefCOCOg)')\n", + " parser.add_argument('--swin_type', default='base',\n", + " help='tiny, small, base, or large variants of the Swin Transformer')\n", + " parser.add_argument('--wd', '--weight-decay', default=1e-2, type=float, metavar='W', help='weight decay',\n", + " dest='weight_decay')\n", + " parser.add_argument('--window12', action='store_true',\n", + " help='only needs specified when testing,'\n", + " 'when training, window size is inferred from pre-trained weights file name'\n", + " '(containing \\'window12\\'). Initialize Swin with window size 12 instead of the default 7.')\n", + " parser.add_argument('-j', '--workers', default=8, type=int, metavar='N', help='number of data loading workers')\n", + "\n", + " parser.add_argument('--metric_learning', default=True, type=bool, help='whether to use metric learning')\n", + " parser.add_argument('--exclude_multiobj', default=True, type=bool, help='whether to exclude multi-object images')\n", + " parser.add_argument('--metric_mode', default='both', type=str, help='both : add hp and hn')\n", + " parser.add_argument('--hn_prob', default=0.5, type=float, help='negative sample prob')\n", + " \n", + " return parser\n", + "\n", + "parser = get_parser()\n", + "args = parser.parse_args([])\n", + "print('Image size: {}'.format(str(args.img_size)))" + ] + }, + { + "cell_type": "code", + "execution_count": 107, + "metadata": {}, + "outputs": [], + "source": [ + "import os\n", + "import sys\n", + "import json\n", + "import torch.utils.data as data\n", + "import torch\n", + "from torchvision import transforms\n", + "from torch.autograd import Variable\n", + "import numpy as np\n", + "from PIL import Image\n", + "import torchvision.transforms.functional as TF\n", + "import random\n", + "\n", + "from bert.tokenization_bert import BertTokenizer\n", + "\n", + "import h5py\n", + "from refer.refer import REFER\n", + "\n", + "from args import get_parser\n", + "\n", + "# Dataset configuration initialization\n", + "# parser = get_parser()\n", + "# args = parser.parse_args()\n", + "\n", + "\n", + "class ReferDataset(data.Dataset):\n", + "\n", + " def __init__(self,\n", + " args,\n", + " image_transforms=None,\n", + " target_transforms=None,\n", + " split='train',\n", + " eval_mode=False):\n", + "\n", + " self.classes = []\n", + " self.image_transforms = image_transforms\n", + " self.target_transform = target_transforms\n", + " self.split = split\n", + " self.refer = REFER(args.refer_data_root, args.dataset, args.splitBy)\n", + "\n", + " self.max_tokens = 20\n", + "\n", + " ref_ids = self.refer.getRefIds(split=self.split)\n", + " img_ids = self.refer.getImgIds(ref_ids)\n", + "\n", + " all_imgs = self.refer.Imgs\n", + " self.imgs = list(all_imgs[i] for i in img_ids)\n", + " self.ref_ids = ref_ids\n", + "\n", + " self.input_ids = []\n", + " self.attention_masks = []\n", + " self.tokenizer = BertTokenizer.from_pretrained(args.bert_tokenizer)\n", + "\n", + " # for metric learning\n", + " self.ROOT = '/data2/projects/seunghoon/VerbRIS/VerbCentric_CY/datasets/VRIS'\n", + " self.metric_learning = args.metric_learning\n", + " self.exclude_multiobj = args.exclude_multiobj\n", + " self.metric_mode = args.metric_mode\n", + " self.exclude_position = False\n", + "\n", + " if self.metric_learning:\n", + " self.hardneg_prob = args.hn_prob \n", + " self.multi_obj_ref_ids = self._load_multi_obj_ref_ids()\n", + " self.hardpos_meta, self.hardneg_meta = self._load_metadata()\n", + " else:\n", + " self.hardneg_prob = 0.0\n", + " self.multi_obj_ref_ids = None\n", + " self.hardpos_meta, self.hardneg_meta = None, None\n", + "\n", + "\n", + " self.eval_mode = eval_mode\n", + " # if we are testing on a dataset, test all sentences of an object;\n", + " # o/w, we are validating during training, randomly sample one sentence for efficiency\n", + " for r in ref_ids:\n", + " ref = self.refer.Refs[r]\n", + "\n", + " sentences_for_ref = []\n", + " attentions_for_ref = []\n", + "\n", + " for i, (el, sent_id) in enumerate(zip(ref['sentences'], ref['sent_ids'])):\n", + " sentence_raw = el['raw']\n", + " attention_mask = [0] * self.max_tokens\n", + " padded_input_ids = [0] * self.max_tokens\n", + "\n", + " input_ids = self.tokenizer.encode(text=sentence_raw, add_special_tokens=True)\n", + "\n", + " # truncation of tokens\n", + " input_ids = input_ids[:self.max_tokens]\n", + "\n", + " padded_input_ids[:len(input_ids)] = input_ids\n", + " attention_mask[:len(input_ids)] = [1]*len(input_ids)\n", + "\n", + " sentences_for_ref.append(torch.tensor(padded_input_ids).unsqueeze(0))\n", + " attentions_for_ref.append(torch.tensor(attention_mask).unsqueeze(0))\n", + "\n", + " self.input_ids.append(sentences_for_ref)\n", + " self.attention_masks.append(attentions_for_ref)\n", + "\n", + "\n", + " def _tokenize(self, sentence):\n", + " attention_mask = [0] * self.max_tokens\n", + " padded_input_ids = [0] * self.max_tokens\n", + "\n", + " input_ids = self.tokenizer.encode(text=sentence, add_special_tokens=True)\n", + " # truncation of tokens\n", + " input_ids = input_ids[:self.max_tokens]\n", + " padded_input_ids[:len(input_ids)] = input_ids\n", + " attention_mask[:len(input_ids)] = [1]*len(input_ids)\n", + "\n", + " return torch.tensor(padded_input_ids), torch.tensor(attention_mask)\n", + " \n", + " def _plot(self, img, target):\n", + " import matplotlib.pyplot as plt\n", + "\n", + " # If img is a PyTorch tensor, convert it to a NumPy array and adjust shape\n", + " if isinstance(img, torch.Tensor):\n", + " img = img.cpu().numpy()\n", + " if img.shape[0] == 3: # Shape is (channels, height, width)\n", + " img = img.transpose(1, 2, 0) # Now shape is (height, width, channels)\n", + "\n", + " # Ensure target is a NumPy array\n", + " if isinstance(target, torch.Tensor):\n", + " target = target.cpu().numpy()\n", + " if target.ndim == 3 and target.shape[0] == 1: # Shape is (1, height, width)\n", + " target = target.squeeze(0) # Now shape is (height, width)\n", + "\n", + " plt.imshow(img)\n", + " plt.imshow(target, alpha=0.5)\n", + " plt.show()\n", + "\n", + "\n", + " def _load_multi_obj_ref_ids(self):\n", + " # Load multi-object reference IDs based on configurations\n", + " if not self.exclude_multiobj and not self.exclude_position :\n", + " return None\n", + " elif self.exclude_position:\n", + " multiobj_path = os.path.join(self.ROOT, 'multiobj_ov2_nopos.txt')\n", + " elif self.exclude_multiobj :\n", + " multiobj_path = os.path.join(self.ROOT, 'multiobj_ov3.txt')\n", + " with open(multiobj_path, 'r') as f:\n", + " return [int(line.strip()) for line in f.readlines()]\n", + "\n", + " def _load_metadata(self):\n", + " # Load metadata for hard positive verb phrases, hard negative queries\n", + " if 'op2' in self.metric_mode :\n", + " hardpos_path = os.path.join(self.ROOT, 'hardpos_verbphrase_op2_1024upd.json') \n", + " else :\n", + " hardpos_path = os.path.join(self.ROOT, 'hardpos_verbphrase_0906upd.json')\n", + " # do not use hardneg_path\n", + " hardneg_path = os.path.join(self.ROOT, 'hardneg_verb.json')\n", + "\n", + " with open(hardpos_path, 'r', encoding='utf-8') as f:\n", + " hardpos_json = json.load(f)\n", + " if \"hardpos_only\" in self.metric_mode :\n", + " hardneg_json = None\n", + " else : \n", + " with open(hardneg_path, 'r', encoding='utf-8') as q:\n", + " hardneg_json = json.load(q)\n", + " return hardpos_json, hardneg_json\n", + "\n", + " def get_classes(self):\n", + " return self.classes\n", + "\n", + " def __len__(self):\n", + " return len(self.ref_ids)\n", + "\n", + " def __getitem__(self, index):\n", + " this_ref_id = self.ref_ids[index]\n", + " this_img_id = self.refer.getImgIds(this_ref_id)\n", + " this_img = self.refer.Imgs[this_img_id[0]]\n", + "\n", + " img = Image.open(os.path.join(self.refer.IMAGE_DIR, this_img['file_name'])).convert(\"RGB\")\n", + "\n", + " ref = self.refer.loadRefs(this_ref_id)\n", + " #print(ref)\n", + "\n", + " ref_mask = np.array(self.refer.getMask(ref[0])['mask'])\n", + " annot = np.zeros(ref_mask.shape)\n", + " annot[ref_mask == 1] = 1\n", + "\n", + " annot = Image.fromarray(annot.astype(np.uint8), mode=\"P\")\n", + "\n", + " if self.image_transforms is not None:\n", + " # resize, from PIL to tensor, and mean and std normalization\n", + " img, target = self.image_transforms(img, annot)\n", + "\n", + " pos_sent = None\n", + " neg_sent = None\n", + " pos_attn_mask = None\n", + " neg_attn_mask = None\n", + " choice_sent = None\n", + "\n", + " if self.eval_mode:\n", + " embedding = []\n", + " att = []\n", + " for s in range(len(self.input_ids[index])):\n", + " e = self.input_ids[index][s]\n", + " a = self.attention_masks[index][s]\n", + " embedding.append(e.unsqueeze(-1))\n", + " att.append(a.unsqueeze(-1))\n", + "\n", + " tensor_embeddings = torch.cat(embedding, dim=-1)\n", + " attention_mask = torch.cat(att, dim=-1)\n", + " else: # train phase\n", + " choice_sent = np.random.choice(len(self.input_ids[index]))\n", + " tensor_embeddings = self.input_ids[index][choice_sent]\n", + " attention_mask = self.attention_masks[index][choice_sent]\n", + "\n", + " # print(\"object id: \", this_ref_id)\n", + " # print(\"sentence ids: \", self.input_ids[index])\n", + " # for i in range(len(self.input_ids[index])):\n", + " # print(\"object sentences: \", self.tokenizer.decode(self.input_ids[index][i].squeeze(0).tolist()))\n", + " # # plot selected refid\n", + " # self._plot(img, target)\n", + "\n", + " pos_sent, neg_sent = None, None\n", + " pos_attn_mask, neg_attn_mask = None, None\n", + " pos_mask = [[1, ]] # (GT, pos) 초기화\n", + " neg_mask = [[0, ]] # (GT, neg) 초기화\n", + "\n", + " if self.metric_learning:\n", + " if self.metric_mode in ['hardpos_only', 'hardpos_only_rev'] or self.hardneg_prob == 0.0:\n", + " pos_sent_dict = self.hardpos_meta.get(str(this_ref_id), {})\n", + " pos_sents = []\n", + " for sent_list in pos_sent_dict.values():\n", + " pos_sents.extend(sent_list)\n", + " if pos_sents:\n", + " pos_sent = random.choice(pos_sents)\n", + " pos_sent, pos_attn_mask = self._tokenize(pos_sent)\n", + " else:\n", + " if random.random() < self.hardneg_prob:\n", + " neg_sent_dict = self.hardneg_meta.get(str(this_ref_id), {})\n", + " neg_sents = []\n", + " for sent_list in neg_sent_dict.values():\n", + " neg_sents.extend(sent_list)\n", + " if neg_sents:\n", + " neg_sent = random.choice(neg_sents)\n", + " neg_sent, neg_attn_mask = self._tokenize(neg_sent)\n", + " else:\n", + " pos_sent_dict = self.hardpos_meta.get(str(this_ref_id), {})\n", + " pos_sents = []\n", + " for sent_list in pos_sent_dict.values():\n", + " pos_sents.extend(sent_list)\n", + " if pos_sents:\n", + " pos_sent = random.choice(pos_sents)\n", + " #print(\"original pos sentence: \", pos_sent)\n", + " pos_sent, pos_attn_mask = self._tokenize(pos_sent)\n", + " if pos_sent is None and len(self.input_ids[index]) > 1:\n", + " to_select = list(range(len(self.input_ids[index])))\n", + " to_select.remove(choice_sent)\n", + " choice_sent = np.random.choice(to_select)\n", + " pos_sent = self.input_ids[index][choice_sent]\n", + " pos_attn_mask = self.attention_masks[index][choice_sent]\n", + " #print(\"pos sent does not exist, use other sentence : \", self.tokenizer.decode(pos_sent.squeeze(0).tolist()))\n", + "\n", + " # concat tensors\n", + " if img.dim() == 3:\n", + " img = img.unsqueeze(0) # [1, C, H, W]\n", + " if target.dim() == 2:\n", + " target = target.unsqueeze(0) # [1, H, W]\n", + " if tensor_embeddings.dim() == 1:\n", + " tensor_embeddings = tensor_embeddings.unsqueeze(0) # [1, max_tokens]\n", + " if attention_mask.dim() == 1:\n", + " attention_mask = attention_mask.unsqueeze(0) # [1, max_tokens]\n", + " if pos_sent is not None and pos_sent.dim() == 1:\n", + " pos_sent = pos_sent.unsqueeze(0)\n", + " if neg_sent is not None and neg_sent.dim() == 1:\n", + " neg_sent = neg_sent.unsqueeze(0)\n", + " if pos_attn_mask is not None and pos_attn_mask.dim() == 1:\n", + " pos_attn_mask = pos_attn_mask.unsqueeze(0)\n", + " if neg_attn_mask is not None and neg_attn_mask.dim() == 1:\n", + " neg_attn_mask = neg_attn_mask.unsqueeze(0)\n", + "\n", + "\n", + " # print(\"index: \", self.input_ids[index])\n", + " # print(\"choice_sent: \", choice_sent)\n", + " # print(\"tensor_embeddings: \", tensor_embeddings)\n", + " # print(\"original sentence: \", self.tokenizer.decode(tensor_embeddings.squeeze(0).tolist()))\n", + " # print(\"pos_sent: \", pos_sent)\n", + " # print(\"neg_sent: \", neg_sent)\n", + " # print(\"pos_attn_mask: \", pos_attn_mask)\n", + " # print(\"neg_attn_mask: \", neg_attn_mask)\n", + " # print(img.shape, target.shape, tensor_embeddings.shape, attention_mask.shape, pos_mask, neg_mask)\n", + "\n", + " if (pos_sent is not None) and (neg_sent is not None):\n", + " img = torch.stack([img, img, img], dim=0)\n", + " target = torch.stack([target, target, target], dim=0)\n", + " tensor_embeddings = torch.stack([tensor_embeddings, pos_sent, neg_sent], dim=0)\n", + " attention_mask = torch.stack([attention_mask, pos_attn_mask, neg_attn_mask], dim=0)\n", + " pos_mask = [[1, 1, 0]]\n", + " neg_mask = [[0, 0, 1]]\n", + " elif (pos_sent is not None and not neg_sent) or (neg_sent is not None and not pos_sent):\n", + " img = torch.stack([img, img], dim=0)\n", + " target = torch.stack([target, target], dim=0)\n", + " tensor_embeddings = torch.stack([tensor_embeddings, pos_sent], dim=0) if (pos_sent is not None) \\\n", + " else torch.stack([tensor_embeddings, neg_sent], dim=0)\n", + " attention_mask = torch.stack([attention_mask, pos_attn_mask], dim=0) if (pos_attn_mask is not None) \\\n", + " else torch.stack([attention_mask, neg_attn_mask], dim=0)\n", + " pos_mask = [[1, int(pos_sent is not None)]]\n", + " neg_mask = [[0, int(neg_sent is not None)]]\n", + " else:\n", + " pass\n", + " return img, target, tensor_embeddings, attention_mask, pos_mask, neg_mask\n" + ] + }, + { + "cell_type": "code", + "execution_count": 108, + "metadata": {}, + "outputs": [], + "source": [ + "def get_dataset(image_set, transform, args):\n", + " #from data.dataset_refer_bert import ReferDataset\n", + " ds = ReferDataset(args,\n", + " split=image_set,\n", + " image_transforms=transform,\n", + " target_transforms=None\n", + " )\n", + " num_classes = 2\n", + "\n", + " return ds, num_classes\n", + "\n", + "def get_transform(args):\n", + " transforms = [T.Resize(args.img_size, args.img_size),\n", + " T.ToTensor(),\n", + " T.Normalize(mean=[0.485, 0.456, 0.406], std=[0.229, 0.224, 0.225])\n", + " ]\n", + "\n", + " return T.Compose(transforms)\n", + "\n", + "\n", + "def criterion(input, target):\n", + " weight = torch.FloatTensor([0.9, 1.1]).cuda()\n", + " return nn.functional.cross_entropy(input, target, weight=weight)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "loading dataset refcocog into memory...\n", + "Split by umd!\n", + "creating index...\n", + "index created.\n", + "DONE (t=6.64s)\n" + ] + } + ], + "source": [ + "dataset, num_classes = get_dataset(\"train\",\n", + " get_transform(args=args),\n", + " args=args)\n", + "train_sampler = torch.utils.data.distributed.DistributedSampler(dataset, num_replicas=1, rank=0,\n", + " shuffle=True)\n" + ] + }, + { + "cell_type": "code", + "execution_count": 118, + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/home/seunghoon/.conda/envs/lavt/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum.\n", + " warnings.warn(\n", + "/home/seunghoon/.conda/envs/lavt/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum.\n", + " warnings.warn(\n", + "/home/seunghoon/.conda/envs/lavt/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum.\n", + " warnings.warn(\n", + "/home/seunghoon/.conda/envs/lavt/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum.\n", + " warnings.warn(\n", + "/home/seunghoon/.conda/envs/lavt/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum.\n", + " warnings.warn(\n", + "/home/seunghoon/.conda/envs/lavt/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum.\n", + " warnings.warn(\n", + "/home/seunghoon/.conda/envs/lavt/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum.\n", + " warnings.warn(\n", + "/home/seunghoon/.conda/envs/lavt/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum.\n", + " warnings.warn(\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "torch.Size([2, 1, 20])\n", + "torch.Size([2, 1, 20])\n", + "torch.Size([2, 1, 20])\n", + "torch.Size([2, 1, 20])torch.Size([2, 1, 20])torch.Size([2, 1, 20])torch.Size([3, 1, 20])\n", + "\n", + "\n", + "\n", + "torch.Size([2, 1, 20])torch.Size([2, 1, 20])torch.Size([2, 1, 20])torch.Size([3, 1, 20])torch.Size([2, 1, 20])\n", + "\n", + "\n", + "\n", + "\n", + "torch.Size([1, 20])torch.Size([3, 1, 20])torch.Size([2, 1, 20])torch.Size([2, 1, 20])torch.Size([2, 1, 20])\n", + "\n", + "\n", + "\n", + "torch.Size([3, 1, 20])\n", + "torch.Size([2, 1, 20])torch.Size([1, 20])torch.Size([2, 1, 20])torch.Size([1, 20])\n", + "torch.Size([2, 1, 20])\n", + "\n", + "\n", + "\n", + "torch.Size([2, 1, 20])torch.Size([2, 1, 20])\n", + "torch.Size([2, 1, 20])torch.Size([2, 1, 20])torch.Size([3, 1, 20])torch.Size([1, 20])\n", + "\n", + "torch.Size([3, 1, 20])\n", + "\n", + "\n", + "\n", + "torch.Size([2, 1, 20])\n", + "torch.Size([2, 1, 20])torch.Size([2, 1, 20])torch.Size([2, 1, 20])torch.Size([2, 1, 20])\n", + "torch.Size([2, 1, 20])\n", + "\n", + "\n", + "\n", + "torch.Size([2, 1, 20])torch.Size([3, 1, 20])\n", + "torch.Size([2, 1, 20])torch.Size([2, 1, 20])torch.Size([2, 1, 20])torch.Size([2, 1, 20])\n", + "\n", + "torch.Size([2, 1, 20])\n", + "\n", + "\n", + "torch.Size([2, 1, 20])\n", + "torch.Size([2, 1, 20])\n", + "torch.Size([2, 1, 20])torch.Size([2, 1, 20])\n", + "torch.Size([2, 1, 20])torch.Size([2, 1, 20])\n", + "torch.Size([2, 1, 20])\n", + "\n", + "torch.Size([2, 1, 20])\n", + "\n", + "torch.Size([2, 1, 20])\n", + "\n", + "torch.Size([3, 1, 20])\n", + "torch.Size([2, 1, 20])torch.Size([3, 1, 20])\n", + "torch.Size([3, 1, 20])\n", + "\n", + "torch.Size([3, 1, 20])\n", + "torch.Size([2, 1, 20])\n", + "torch.Size([2, 1, 20])\n", + "torch.Size([3, 1, 20])\n", + "\n", + "torch.Size([2, 1, 20])\n", + "torch.Size([2, 1, 20])torch.Size([2, 1, 20])\n", + "\n", + "torch.Size([2, 1, 20])\n" + ] + }, + { + "ename": "TypeError", + "evalue": "Caught TypeError in DataLoader worker process 0.\nOriginal Traceback (most recent call last):\n File \"/home/seunghoon/.conda/envs/lavt/lib/python3.9/site-packages/torch/utils/data/_utils/worker.py\", line 302, in _worker_loop\n data = fetcher.fetch(index)\n File \"/home/seunghoon/.conda/envs/lavt/lib/python3.9/site-packages/torch/utils/data/_utils/fetch.py\", line 52, in fetch\n return self.collate_fn(data)\n File \"/tmp/ipykernel_2235050/518736739.py\", line 10, in custom_collate\n tensor_embeddings = torch.cat(*tensor_embeddings, dim=0)\nTypeError: cat() received an invalid combination of arguments - got (Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, dim=int), but expected one of:\n * (tuple of Tensors tensors, int dim, *, Tensor out)\n * (tuple of Tensors tensors, name dim, *, Tensor out)\n\n", + "output_type": "error", + "traceback": [ + "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", + "\u001b[0;31mTypeError\u001b[0m Traceback (most recent call last)", + "Cell \u001b[0;32mIn[118], line 36\u001b[0m\n\u001b[1;32m 30\u001b[0m data_loader \u001b[38;5;241m=\u001b[39m torch\u001b[38;5;241m.\u001b[39mutils\u001b[38;5;241m.\u001b[39mdata\u001b[38;5;241m.\u001b[39mDataLoader(\n\u001b[1;32m 31\u001b[0m dataset, batch_size\u001b[38;5;241m=\u001b[39margs\u001b[38;5;241m.\u001b[39mbatch_size,\n\u001b[1;32m 32\u001b[0m sampler\u001b[38;5;241m=\u001b[39mtrain_sampler, num_workers\u001b[38;5;241m=\u001b[39margs\u001b[38;5;241m.\u001b[39mworkers, \n\u001b[1;32m 33\u001b[0m collate_fn\u001b[38;5;241m=\u001b[39mcustom_collate, pin_memory\u001b[38;5;241m=\u001b[39margs\u001b[38;5;241m.\u001b[39mpin_mem, drop_last\u001b[38;5;241m=\u001b[39m\u001b[38;5;28;01mTrue\u001b[39;00m)\n\u001b[1;32m 35\u001b[0m \u001b[38;5;66;03m# single sample from dataloader\u001b[39;00m\n\u001b[0;32m---> 36\u001b[0m img, target, tensor_embeddings, attention_mask, pos_mask, neg_mask \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;43mnext\u001b[39;49m\u001b[43m(\u001b[49m\u001b[38;5;28;43miter\u001b[39;49m\u001b[43m(\u001b[49m\u001b[43mdata_loader\u001b[49m\u001b[43m)\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 38\u001b[0m \u001b[38;5;28mprint\u001b[39m(img\u001b[38;5;241m.\u001b[39mshape, target\u001b[38;5;241m.\u001b[39mshape, tensor_embeddings\u001b[38;5;241m.\u001b[39mshape, attention_mask\u001b[38;5;241m.\u001b[39mshape, pos_mask, neg_mask)\n", + "File \u001b[0;32m~/.conda/envs/lavt/lib/python3.9/site-packages/torch/utils/data/dataloader.py:652\u001b[0m, in \u001b[0;36m_BaseDataLoaderIter.__next__\u001b[0;34m(self)\u001b[0m\n\u001b[1;32m 649\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_sampler_iter \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m:\n\u001b[1;32m 650\u001b[0m \u001b[38;5;66;03m# TODO(https://github.com/pytorch/pytorch/issues/76750)\u001b[39;00m\n\u001b[1;32m 651\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_reset() \u001b[38;5;66;03m# type: ignore[call-arg]\u001b[39;00m\n\u001b[0;32m--> 652\u001b[0m data \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_next_data\u001b[49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 653\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_num_yielded \u001b[38;5;241m+\u001b[39m\u001b[38;5;241m=\u001b[39m \u001b[38;5;241m1\u001b[39m\n\u001b[1;32m 654\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_dataset_kind \u001b[38;5;241m==\u001b[39m _DatasetKind\u001b[38;5;241m.\u001b[39mIterable \u001b[38;5;129;01mand\u001b[39;00m \\\n\u001b[1;32m 655\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_IterableDataset_len_called \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m \u001b[38;5;129;01mand\u001b[39;00m \\\n\u001b[1;32m 656\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_num_yielded \u001b[38;5;241m>\u001b[39m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_IterableDataset_len_called:\n", + "File \u001b[0;32m~/.conda/envs/lavt/lib/python3.9/site-packages/torch/utils/data/dataloader.py:1347\u001b[0m, in \u001b[0;36m_MultiProcessingDataLoaderIter._next_data\u001b[0;34m(self)\u001b[0m\n\u001b[1;32m 1345\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[1;32m 1346\u001b[0m \u001b[38;5;28;01mdel\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_task_info[idx]\n\u001b[0;32m-> 1347\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_process_data\u001b[49m\u001b[43m(\u001b[49m\u001b[43mdata\u001b[49m\u001b[43m)\u001b[49m\n", + "File \u001b[0;32m~/.conda/envs/lavt/lib/python3.9/site-packages/torch/utils/data/dataloader.py:1373\u001b[0m, in \u001b[0;36m_MultiProcessingDataLoaderIter._process_data\u001b[0;34m(self, data)\u001b[0m\n\u001b[1;32m 1371\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_try_put_index()\n\u001b[1;32m 1372\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28misinstance\u001b[39m(data, ExceptionWrapper):\n\u001b[0;32m-> 1373\u001b[0m \u001b[43mdata\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mreraise\u001b[49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 1374\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m data\n", + "File \u001b[0;32m~/.conda/envs/lavt/lib/python3.9/site-packages/torch/_utils.py:461\u001b[0m, in \u001b[0;36mExceptionWrapper.reraise\u001b[0;34m(self)\u001b[0m\n\u001b[1;32m 457\u001b[0m \u001b[38;5;28;01mexcept\u001b[39;00m \u001b[38;5;167;01mTypeError\u001b[39;00m:\n\u001b[1;32m 458\u001b[0m \u001b[38;5;66;03m# If the exception takes multiple arguments, don't try to\u001b[39;00m\n\u001b[1;32m 459\u001b[0m \u001b[38;5;66;03m# instantiate since we don't know how to\u001b[39;00m\n\u001b[1;32m 460\u001b[0m \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mRuntimeError\u001b[39;00m(msg) \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m\n\u001b[0;32m--> 461\u001b[0m \u001b[38;5;28;01mraise\u001b[39;00m exception\n", + "\u001b[0;31mTypeError\u001b[0m: Caught TypeError in DataLoader worker process 0.\nOriginal Traceback (most recent call last):\n File \"/home/seunghoon/.conda/envs/lavt/lib/python3.9/site-packages/torch/utils/data/_utils/worker.py\", line 302, in _worker_loop\n data = fetcher.fetch(index)\n File \"/home/seunghoon/.conda/envs/lavt/lib/python3.9/site-packages/torch/utils/data/_utils/fetch.py\", line 52, in fetch\n return self.collate_fn(data)\n File \"/tmp/ipykernel_2235050/518736739.py\", line 10, in custom_collate\n tensor_embeddings = torch.cat(*tensor_embeddings, dim=0)\nTypeError: cat() received an invalid combination of arguments - got (Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, dim=int), but expected one of:\n * (tuple of Tensors tensors, int dim, *, Tensor out)\n * (tuple of Tensors tensors, name dim, *, Tensor out)\n\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "torch.Size([2, 1, 20])\n", + "torch.Size([3, 1, 20])torch.Size([2, 1, 20])\n", + "torch.Size([2, 1, 20])\n", + "\n", + "torch.Size([2, 1, 20])torch.Size([3, 1, 20])\n", + "\n", + "torch.Size([2, 1, 20])torch.Size([3, 1, 20])\n", + "\n", + "torch.Size([3, 1, 20])torch.Size([3, 1, 20])\n", + "\n", + "torch.Size([2, 1, 20])torch.Size([2, 1, 20])\n", + "\n", + "torch.Size([2, 1, 20])torch.Size([2, 1, 20])\n", + "torch.Size([2, 1, 20])\n", + "torch.Size([3, 1, 20])\n", + "torch.Size([2, 1, 20])\n", + "torch.Size([2, 1, 20])\n", + "torch.Size([3, 1, 20])\n", + "\n", + "torch.Size([3, 1, 20])torch.Size([2, 1, 20])\n", + "\n", + "torch.Size([2, 1, 20])torch.Size([2, 1, 20])\n", + "\n", + "torch.Size([2, 1, 20])torch.Size([2, 1, 20])\n", + "\n", + "torch.Size([3, 1, 20])torch.Size([3, 1, 20])\n", + "\n", + "torch.Size([2, 1, 20])torch.Size([2, 1, 20])\n", + "\n", + "torch.Size([2, 1, 20])torch.Size([2, 1, 20])\n", + "\n", + "torch.Size([2, 1, 20])\n", + "torch.Size([2, 1, 20])\n", + "torch.Size([2, 1, 20])\n", + "torch.Size([2, 1, 20])\n", + "torch.Size([2, 1, 20])\n", + "torch.Size([2, 1, 20])\n", + "torch.Size([2, 1, 20])\n", + "torch.Size([3, 1, 20])\n", + "torch.Size([3, 1, 20])\n", + "torch.Size([3, 1, 20])\n", + "torch.Size([3, 1, 20])\n", + "torch.Size([1, 20])\n", + "torch.Size([3, 1, 20])\n", + "torch.Size([3, 1, 20])\n", + "torch.Size([2, 1, 20])torch.Size([2, 1, 20])\n", + "\n", + "torch.Size([2, 1, 20])torch.Size([2, 1, 20])\n", + "\n", + "torch.Size([2, 1, 20])torch.Size([2, 1, 20])\n", + "\n", + "torch.Size([2, 1, 20])\n", + "torch.Size([2, 1, 20])\n", + "torch.Size([3, 1, 20])\n", + "torch.Size([3, 1, 20])\n", + "torch.Size([2, 1, 20])\n", + "torch.Size([2, 1, 20])\n", + "torch.Size([3, 1, 20])\n", + "torch.Size([3, 1, 20])\n", + "torch.Size([2, 1, 20])\n", + "torch.Size([2, 1, 20])\n", + "torch.Size([3, 1, 20])\n", + "torch.Size([3, 1, 20])\n", + "torch.Size([3, 1, 20])\n", + "torch.Size([3, 1, 20])\n", + "torch.Size([2, 1, 20])\n", + "torch.Size([2, 1, 20])\n", + "torch.Size([2, 1, 20])\n", + "torch.Size([2, 1, 20])\n", + "torch.Size([1, 20])\n", + "torch.Size([2, 1, 20])\n", + "torch.Size([3, 1, 20])\n" + ] + } + ], + "source": [ + "from torch.nn.utils.rnn import pad_sequence\n", + "\n", + "def custom_collate(batch):\n", + " imgs, targets, tensor_embeddings, attention_masks, pos_masks, neg_masks = zip(*batch)\n", + " imgs = torch.cat([img for img in imgs], dim=0)\n", + " targets = torch.cat([tgt for tgt in targets], dim=0)\n", + " \n", + " tensor_embeddings = torch.cat([t_e for t_e in tensor_embeddings], dim=0)\n", + " attention_masks = torch.cat([a_m for a_m in attention_masks], dim=0)\n", + "\n", + " # Handle pos_masks\n", + " if any(pos_mask is not None for pos_mask in pos_masks):\n", + " pos_masks = [mask if mask is not None else torch.zeros_like(tensor_embeddings[0]) for mask in pos_masks]\n", + " pos_masks = pad_sequence(pos_masks, batch_first=True, padding_value=0)\n", + " else:\n", + " pos_masks = None\n", + "\n", + " # Handle neg_masks\n", + " if any(neg_mask is not None for neg_mask in neg_masks):\n", + " neg_masks = [mask if mask is not None else torch.zeros_like(tensor_embeddings[0]) for mask in neg_masks]\n", + " neg_masks = pad_sequence(neg_masks, batch_first=True, padding_value=0)\n", + " else:\n", + " neg_masks = None\n", + "\n", + " return imgs, targets, tensor_embeddings, attention_masks, pos_masks, neg_masks\n", + "\n", + "\n", + "data_loader = torch.utils.data.DataLoader(\n", + " dataset, batch_size=args.batch_size,\n", + " sampler=train_sampler, num_workers=args.workers, \n", + " collate_fn=custom_collate, pin_memory=args.pin_mem, drop_last=True)\n", + "\n", + "# single sample from dataloader\n", + "img, target, tensor_embeddings, attention_mask, pos_mask, neg_mask = next(iter(data_loader))\n", + "\n", + "print(img.shape, target.shape, tensor_embeddings.shape, attention_mask.shape, pos_mask, neg_mask)" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[{'image_id': 391435, 'split': 'train', 'sentences': [{'tokens': ['the', 'reflection', 'of', 'the', 'man', 'shaving'], 'raw': 'the reflection of the man shaving', 'sent_id': 13437, 'sent': 'the reflection of the man shaving'}, {'tokens': ['image', 'of', 'a', 'man', 'shaving', 'on', 'a', 'laptop', 'screen'], 'raw': 'image of a man shaving on a laptop screen', 'sent_id': 13438, 'sent': 'image of a man shaving on a laptop screen'}], 'file_name': 'COCO_train2014_000000391435_1709050.jpg', 'category_id': 1, 'ann_id': 1709050, 'sent_ids': [13437, 13438], 'ref_id': 45871}][{'image_id': 421848, 'split': 'train', 'sentences': [{'tokens': ['the', 'tallest', 'giraffe', 'among', 'the', 'two'], 'raw': 'The tallest giraffe among the two', 'sent_id': 82708, 'sent': 'the tallest giraffe among the two'}, {'tokens': ['the', 'tallest', 'of', 'two', 'giraffes'], 'raw': 'The tallest of two giraffes.', 'sent_id': 82709, 'sent': 'the tallest of two giraffes'}], 'file_name': 'COCO_train2014_000000421848_596471.jpg', 'category_id': 25, 'ann_id': 596471, 'sent_ids': [82708, 82709], 'ref_id': 36770}]\n", + "[{'image_id': 13468, 'split': 'train', 'sentences': [{'tokens': ['a', 'sandwich', 'right', 'of', 'another'], 'raw': 'A sandwich right of another.', 'sent_id': 5866, 'sent': 'a sandwich right of another'}, {'tokens': ['sandwich', 'half', 'furthest', 'to', 'right'], 'raw': 'sandwich half furthest to right', 'sent_id': 5867, 'sent': 'sandwich half furthest to right'}], 'file_name': 'COCO_train2014_000000013468_310040.jpg', 'category_id': 54, 'ann_id': 310040, 'sent_ids': [5866, 5867], 'ref_id': 7280}][{'image_id': 181054, 'split': 'train', 'sentences': [{'tokens': ['a', 'man', 'in', 'a', 'white', 'shirt', 'with', 'a', 'woman', 'buttoning', 'it', 'up'], 'raw': 'A man in a white shirt with a woman buttoning it up.', 'sent_id': 68075, 'sent': 'a man in a white shirt with a woman buttoning it up'}, {'tokens': ['a', 'man', 'in', 'a', 'white', 'shirt', 'looks', 'nervous', 'as', 'an', 'older', 'woman', 'buttons', 'him', 'up'], 'raw': 'A man in a white shirt looks nervous as an older woman buttons him up.', 'sent_id': 68076, 'sent': 'a man in a white shirt looks nervous as an older woman buttons him up'}], 'file_name': 'COCO_train2014_000000181054_484268.jpg', 'category_id': 1, 'ann_id': 484268, 'sent_ids': [68075, 68076], 'ref_id': 48236}]\n", + "\n", + "\n", + "[{'image_id': 569919, 'split': 'train', 'sentences': [{'tokens': ['the', 'spoon', 'next', 'to', 'the', 'pizza'], 'raw': 'The spoon next to the pizza.', 'sent_id': 97107, 'sent': 'the spoon next to the pizza'}, {'tokens': ['a', 'metal', 'spoon', 'on', 'a', 'plate', 'on', 'a', 'table'], 'raw': 'A metal spoon on a plate on a table.', 'sent_id': 97108, 'sent': 'a metal spoon on a plate on a table'}], 'file_name': 'COCO_train2014_000000569919_703521.jpg', 'category_id': 50, 'ann_id': 703521, 'sent_ids': [97107, 97108], 'ref_id': 42368}][{'image_id': 129359, 'split': 'train', 'sentences': [{'tokens': ['a', 'white', 'dish', 'with', 'some', 'kind', 'of', 'sauce', 'in', 'it', 'along', 'with', 'a', 'silver', 'spoon'], 'raw': 'A white dish with some kind of sauce in it along with a silver spoon', 'sent_id': 97230, 'sent': 'a white dish with some kind of sauce in it along with a silver spoon'}, {'tokens': ['a', 'cup', 'of', 'food', 'with', 'a', 'spoon'], 'raw': 'A cup of food with a spoon.', 'sent_id': 97231, 'sent': 'a cup of food with a spoon'}], 'file_name': 'COCO_train2014_000000129359_1039869.jpg', 'category_id': 51, 'ann_id': 1039869, 'sent_ids': [97230, 97231], 'ref_id': 42420}][{'image_id': 2964, 'split': 'train', 'sentences': [{'tokens': ['bottle', 'of', '14', 'hands', 'wine'], 'raw': 'bottle of 14 Hands wine', 'sent_id': 44379, 'sent': 'bottle of 14 hands wine'}, {'tokens': ['a', 'bottle', 'of', 'wine', 'that', 'says', '14', 'hands', 'and', 'has', 'a', 'purple', 'horse', 'on', 'it'], 'raw': 'A bottle of wine that says 14 hands and has a purple horse on it.', 'sent_id': 44380, 'sent': 'a bottle of wine that says 14 hands and has a purple horse on it'}], 'file_name': 'COCO_train2014_000000002964_91245.jpg', 'category_id': 44, 'ann_id': 91245, 'sent_ids': [44379, 44380], 'ref_id': 22056}]\n", + "\n", + "\n", + "[{'image_id': 330683, 'split': 'train', 'sentences': [{'tokens': ['a', 'black', 'cow', 'alongside', 'a', 'brown', 'cow'], 'raw': 'A black cow alongside a brown cow.', 'sent_id': 78006, 'sent': 'a black cow alongside a brown cow'}, {'tokens': ['a', 'black', 'cow', 'standing', 'between', 'another', 'black', 'cow', 'and', 'a', 'brown', 'cow'], 'raw': 'A black cow standing between another black cow and a brown cow', 'sent_id': 78007, 'sent': 'a black cow standing between another black cow and a brown cow'}], 'file_name': 'COCO_train2014_000000330683_76006.jpg', 'category_id': 21, 'ann_id': 76006, 'sent_ids': [78006, 78007], 'ref_id': 34980}]\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/home/seunghoon/.conda/envs/lavt/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum.\n", + " warnings.warn(\n", + "/home/seunghoon/.conda/envs/lavt/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum.\n", + " warnings.warn(\n", + "/home/seunghoon/.conda/envs/lavt/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum.\n", + " warnings.warn(\n", + "/home/seunghoon/.conda/envs/lavt/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum.\n", + " warnings.warn(\n", + "/home/seunghoon/.conda/envs/lavt/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum.\n", + " warnings.warn(\n", + "/home/seunghoon/.conda/envs/lavt/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum.\n", + " warnings.warn(\n", + "/home/seunghoon/.conda/envs/lavt/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum.\n", + " warnings.warn(\n", + "/home/seunghoon/.conda/envs/lavt/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum.\n", + " warnings.warn(\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[{'image_id': 263823, 'split': 'train', 'sentences': [{'tokens': ['the', 'umpire', 'behind', 'the', 'plate'], 'raw': 'the umpire behind the plate', 'sent_id': 9335, 'sent': 'the umpire behind the plate'}, {'tokens': ['umpire', 'wearing', 'blue'], 'raw': 'umpire wearing blue', 'sent_id': 9336, 'sent': 'umpire wearing blue'}], 'file_name': 'COCO_train2014_000000263823_2160611.jpg', 'category_id': 1, 'ann_id': 2160611, 'sent_ids': [9335, 9336], 'ref_id': 8614}]\n", + "[{'image_id': 170366, 'split': 'train', 'sentences': [{'tokens': ['the', 'boy', 'in', 'the', 'suit'], 'raw': 'The boy in the suit.', 'sent_id': 96474, 'sent': 'the boy in the suit'}, {'tokens': ['a', 'young', 'man', 'with', 'brown', 'hair', 'in', 'a', 'black', 'suit', ',', 'with', 'a', 'black', 'hat', 'with', 'sunglasses', 'resting', 'on', 'it'], 'raw': 'A young man with brown hair in a black suit, with a black hat with sunglasses resting on it', 'sent_id': 96475, 'sent': 'a young man with brown hair in a black suit , with a black hat with sunglasses resting on it'}], 'file_name': 'COCO_train2014_000000170366_484717.jpg', 'category_id': 1, 'ann_id': 484717, 'sent_ids': [96474, 96475], 'ref_id': 42104}][{'image_id': 181316, 'split': 'train', 'sentences': [{'tokens': ['the', 'racket', 'held', 'by', 'a', 'girl', 'wearing', 'dark', 'skirt'], 'raw': 'The racket held by a girl wearing dark skirt.', 'sent_id': 14001, 'sent': 'the racket held by a girl wearing dark skirt'}, {'tokens': ['a', 'racket', 'being', 'held', 'by', 'the', 'girl', 'in', 'the', 'black', 'skirt'], 'raw': 'A racket being held by the girl in the black skirt.', 'sent_id': 14002, 'sent': 'a racket being held by the girl in the black skirt'}], 'file_name': 'COCO_train2014_000000181316_655443.jpg', 'category_id': 43, 'ann_id': 655443, 'sent_ids': [14001, 14002], 'ref_id': 45890}]\n", + "\n", + "[{'image_id': 96723, 'split': 'train', 'sentences': [{'tokens': ['a', 'number', 'of', 'books', 'on', 'a', 'shelf'], 'raw': 'A number of books on a shelf.', 'sent_id': 35543, 'sent': 'a number of books on a shelf'}, {'tokens': ['a', 'bunch', 'of', 'books', 'on', 'a', 'shelf'], 'raw': 'A bunch of books on a shelf.', 'sent_id': 35544, 'sent': 'a bunch of books on a shelf'}], 'file_name': 'COCO_train2014_000000096723_1139765.jpg', 'category_id': 84, 'ann_id': 1139765, 'sent_ids': [35543, 35544], 'ref_id': 18668}]\n", + "[{'image_id': 273951, 'split': 'train', 'sentences': [{'tokens': ['a', 'white', 'woman', 'skier', 'with', 'a', 'colorful', 'hat', 'sitting', 'between', 'two', 'men', 'skiers'], 'raw': 'A white woman skier with a colorful hat sitting between two men skiers.', 'sent_id': 34676, 'sent': 'a white woman skier with a colorful hat sitting between two men skiers'}, {'tokens': ['a', 'blonde', 'woman', 'in', 'red'], 'raw': 'A blonde woman in red', 'sent_id': 34677, 'sent': 'a blonde woman in red'}], 'file_name': 'COCO_train2014_000000273951_509586.jpg', 'category_id': 1, 'ann_id': 509586, 'sent_ids': [34676, 34677], 'ref_id': 18328}][{'image_id': 387527, 'split': 'train', 'sentences': [{'tokens': ['a', 'banana', 'to', 'the', 'far', 'left', 'of', 'the', 'fruit', 'bowl'], 'raw': 'A banana to the far left of the fruit bowl.', 'sent_id': 65272, 'sent': 'a banana to the far left of the fruit bowl'}, {'tokens': ['the', 'farthest', 'banana', 'away', 'from', 'the', 'camera'], 'raw': 'The farthest banana away from the camera.', 'sent_id': 65273, 'sent': 'the farthest banana away from the camera'}], 'file_name': 'COCO_train2014_000000387527_1043422.jpg', 'category_id': 52, 'ann_id': 1043422, 'sent_ids': [65272, 65273], 'ref_id': 30094}][{'image_id': 103510, 'split': 'train', 'sentences': [{'tokens': ['the', 'carrots'], 'raw': 'the carrots', 'sent_id': 63484, 'sent': 'the carrots'}, {'tokens': ['a', 'group', 'of', 'fresh', 'baby', 'carrots'], 'raw': 'A group of fresh baby carrots.', 'sent_id': 63485, 'sent': 'a group of fresh baby carrots'}], 'file_name': 'COCO_train2014_000000103510_1063832.jpg', 'category_id': 57, 'ann_id': 1063832, 'sent_ids': [63484, 63485], 'ref_id': 29390}]\n", + "\n", + "\n", + "[{'image_id': 427633, 'split': 'train', 'sentences': [{'tokens': ['the', 'back', 'side', 'of', 'a', 'multi', 'light', 'traffic', 'light'], 'raw': 'The back side of a multi light traffic light.', 'sent_id': 52260, 'sent': 'the back side of a multi light traffic light'}, {'tokens': ['a', 'stoplight', 'faces', 'to', 'the', 'right'], 'raw': 'A stoplight faces to the right.', 'sent_id': 52261, 'sent': 'a stoplight faces to the right'}], 'file_name': 'COCO_train2014_000000427633_2172860.jpg', 'category_id': 10, 'ann_id': 2172860, 'sent_ids': [52260, 52261], 'ref_id': 25098}]\n", + "[{'image_id': 350083, 'split': 'train', 'sentences': [{'tokens': ['giraffe', 'to', 'left', 'of', 'other'], 'raw': 'giraffe to left of other', 'sent_id': 33055, 'sent': 'giraffe to left of other'}, {'tokens': ['the', 'slightly', 'shorter', 'giraffe'], 'raw': 'the slightly shorter giraffe', 'sent_id': 33056, 'sent': 'the slightly shorter giraffe'}], 'file_name': 'COCO_train2014_000000350083_599600.jpg', 'category_id': 25, 'ann_id': 599600, 'sent_ids': [33055, 33056], 'ref_id': 46695}]\n", + "[{'image_id': 287519, 'split': 'train', 'sentences': [{'tokens': ['a', 'man', 'with', 'cream', '&', 'black', 'colored', 'shirt', 'and', 'short', 'trousers', 'walking', 'behind', 'a', 'police', 'man'], 'raw': 'a man with cream & black colored shirt and short trousers walking behind a police man', 'sent_id': 99833, 'sent': 'a man with cream & black colored shirt and short trousers walking behind a police man'}, {'tokens': ['a', 'guy', 'wearing', 'a', 'short', 'sleeve', 'shirt', 'with', 'an', 'interesting', 'design'], 'raw': 'a guy wearing a short sleeve shirt with an interesting design', 'sent_id': 99834, 'sent': 'a guy wearing a short sleeve shirt with an interesting design'}], 'file_name': 'COCO_train2014_000000287519_2206490.jpg', 'category_id': 1, 'ann_id': 2206490, 'sent_ids': [99833, 99834], 'ref_id': 43469}]\n", + "[{'image_id': 54141, 'split': 'train', 'sentences': [{'tokens': ['a', 'speed', 'boat', 'on', 'a', 'lake'], 'raw': 'A speed boat on a lake.', 'sent_id': 67100, 'sent': 'a speed boat on a lake'}, {'tokens': ['a', 'speedboat', 'pulling', 'a', 'wake', 'boarder', 'behind', 'it'], 'raw': 'A speedboat pulling a wake boarder behind it', 'sent_id': 67101, 'sent': 'a speedboat pulling a wake boarder behind it'}], 'file_name': 'COCO_train2014_000000054141_180852.jpg', 'category_id': 9, 'ann_id': 180852, 'sent_ids': [67100, 67101], 'ref_id': 48196}]\n", + "[{'image_id': 156296, 'split': 'train', 'sentences': [{'tokens': ['a', 'woman', 'in', 'rain', 'boots', 'trying', 'to', 'fix', 'her', 'umbrella'], 'raw': 'A woman in rain boots trying to fix her umbrella.', 'sent_id': 9312, 'sent': 'a woman in rain boots trying to fix her umbrella'}, {'tokens': ['the', 'woman', 'with', 'the', 'black', 'umbrella'], 'raw': 'The woman with the black umbrella.', 'sent_id': 9313, 'sent': 'the woman with the black umbrella'}], 'file_name': 'COCO_train2014_000000156296_518143.jpg', 'category_id': 1, 'ann_id': 518143, 'sent_ids': [9312, 9313], 'ref_id': 8608}][{'image_id': 402212, 'split': 'train', 'sentences': [{'tokens': ['a', 'colorful', 'toy', 'van', 'in', 'the', 'street'], 'raw': 'a colorful toy van in the street', 'sent_id': 14596, 'sent': 'a colorful toy van in the street'}, {'tokens': ['colorful', 'truck'], 'raw': 'Colorful truck.', 'sent_id': 14597, 'sent': 'colorful truck'}], 'file_name': 'COCO_train2014_000000402212_396551.jpg', 'category_id': 8, 'ann_id': 396551, 'sent_ids': [14596, 14597], 'ref_id': 45911}]\n", + "[{'image_id': 521796, 'split': 'train', 'sentences': [{'tokens': ['shelf', 'in', 'camper'], 'raw': 'Shelf in camper.', 'sent_id': 70798, 'sent': 'shelf in camper'}], 'file_name': 'COCO_train2014_000000521796_1978969.jpg', 'category_id': 78, 'ann_id': 1978969, 'sent_ids': [70798], 'ref_id': 48359}]\n", + "[{'image_id': 136953, 'split': 'train', 'sentences': [{'tokens': ['a', 'man', 'wearing', 'a', 'striped', 'shirt', 'and', 'black', 'pants'], 'raw': 'A man wearing a striped shirt and black pants.', 'sent_id': 21168, 'sent': 'a man wearing a striped shirt and black pants'}, {'tokens': ['a', 'man', 'in', 'a', 'striped', 'shirt'], 'raw': 'A man in a striped shirt.', 'sent_id': 21169, 'sent': 'a man in a striped shirt'}], 'file_name': 'COCO_train2014_000000136953_530897.jpg', 'category_id': 1, 'ann_id': 530897, 'sent_ids': [21168, 21169], 'ref_id': 13173}]\n", + "[{'image_id': 179209, 'split': 'train', 'sentences': [{'tokens': ['the', 'large', 'truck', 'in', 'the', 'very', 'back'], 'raw': 'the large truck in the very back', 'sent_id': 45782, 'sent': 'the large truck in the very back'}, {'tokens': ['large', 'multiwheeled', 'truck', 'behind', 'a', 'truck', 'full', 'of', 'bananas'], 'raw': 'Large multiwheeled truck behind a truck full of bananas.', 'sent_id': 45783, 'sent': 'large multiwheeled truck behind a truck full of bananas'}], 'file_name': 'COCO_train2014_000000179209_2054261.jpg', 'category_id': 8, 'ann_id': 2054261, 'sent_ids': [45782, 45783], 'ref_id': 22607}]\n", + "\n", + "[{'image_id': 175565, 'split': 'train', 'sentences': [{'tokens': ['the', 'couch', ',', 'a', 'lady', 'sitted', 'on', 'it'], 'raw': 'the couch, a lady sitted on it.', 'sent_id': 1112, 'sent': 'the couch , a lady sitted on it'}], 'file_name': 'COCO_train2014_000000175565_99716.jpg', 'category_id': 63, 'ann_id': 99716, 'sent_ids': [1112], 'ref_id': 5449}]\n", + "[{'image_id': 168217, 'split': 'train', 'sentences': [{'tokens': ['brown', 'and', 'pink', 'teddy', 'bears'], 'raw': 'Brown and pink teddy bears.', 'sent_id': 4409, 'sent': 'brown and pink teddy bears'}, {'tokens': ['a', 'brown', 'teddy', 'bear', 'with', 'a', 'morose', 'expression', 'sits', 'in', 'front', 'of', 'a', 'pink', 'teddy', 'bear', 'with', 'an', 'identical', 'expression'], 'raw': 'A brown teddy bear with a morose expression sits in front of a pink teddy bear with an identical expression.', 'sent_id': 4410, 'sent': 'a brown teddy bear with a morose expression sits in front of a pink teddy bear with an identical expression'}], 'file_name': 'COCO_train2014_000000168217_1162820.jpg', 'category_id': 88, 'ann_id': 1162820, 'sent_ids': [4409, 4410], 'ref_id': 6702}]\n", + "[{'image_id': 413164, 'split': 'train', 'sentences': [{'tokens': ['a', 'table', 'with', 'a', 'white', 'tablecloth', 'on', 'it'], 'raw': 'A table with a white tablecloth on it', 'sent_id': 19497, 'sent': 'a table with a white tablecloth on it'}], 'file_name': 'COCO_train2014_000000413164_1092064.jpg', 'category_id': 67, 'ann_id': 1092064, 'sent_ids': [19497], 'ref_id': 12539}]\n", + "[{'image_id': 30387, 'split': 'train', 'sentences': [{'tokens': ['the', 'man', 'all', 'way', 'at', 'the', 'end', 'of', 'the', 'line', 'who', 'is', 'barely', 'visible'], 'raw': 'The man all way at the end of the line who is barely visible.', 'sent_id': 12240, 'sent': 'the man all way at the end of the line who is barely visible'}, {'tokens': ['a', 'man', 'who', 'is', 'mostly', 'covered', 'up', 'by', 'the', 'arms', 'of', 'another', 'man'], 'raw': 'A man who is mostly covered up by the arms of another man.', 'sent_id': 12241, 'sent': 'a man who is mostly covered up by the arms of another man'}], 'file_name': 'COCO_train2014_000000030387_1706152.jpg', 'category_id': 1, 'ann_id': 1706152, 'sent_ids': [12240, 12241], 'ref_id': 9755}]\n", + "[{'image_id': 347263, 'split': 'train', 'sentences': [{'tokens': ['woman', 'wearing', 'black', 'showing', 'someone', 'a', 'technique'], 'raw': 'Woman wearing black showing someone a technique', 'sent_id': 68299, 'sent': 'woman wearing black showing someone a technique'}, {'tokens': ['woman', 'with', 'sunglasses', 'on', 'her', 'head', 'is', 'cutting', 'a', 'roast', 'in', 'the', 'kitchen'], 'raw': 'woman with sunglasses on her head is cutting a roast in the kitchen', 'sent_id': 68300, 'sent': 'woman with sunglasses on her head is cutting a roast in the kitchen'}], 'file_name': 'COCO_train2014_000000347263_556785.jpg', 'category_id': 1, 'ann_id': 556785, 'sent_ids': [68299, 68300], 'ref_id': 31255}][{'image_id': 492325, 'split': 'train', 'sentences': [{'tokens': ['a', 'beer', 'which', 'is', 'standing'], 'raw': 'A beer which is standing', 'sent_id': 13351, 'sent': 'a beer which is standing'}, {'tokens': ['a', 'bear', 'that', 'is', 'sitting', 'up'], 'raw': 'A bear that is sitting up.', 'sent_id': 13352, 'sent': 'a bear that is sitting up'}], 'file_name': 'COCO_train2014_000000492325_588117.jpg', 'category_id': 23, 'ann_id': 588117, 'sent_ids': [13351, 13352], 'ref_id': 10175}]\n", + "\n", + "[{'image_id': 409706, 'split': 'train', 'sentences': [{'tokens': ['paper', 'being', 'drawn', 'on'], 'raw': 'paper being drawn on', 'sent_id': 84661, 'sent': 'paper being drawn on'}, {'tokens': ['drawing', 'book'], 'raw': 'drawing book', 'sent_id': 84662, 'sent': 'drawing book'}], 'file_name': 'COCO_train2014_000000409706_1140323.jpg', 'category_id': 84, 'ann_id': 1140323, 'sent_ids': [84661, 84662], 'ref_id': 37505}]\n", + "[{'image_id': 526922, 'split': 'train', 'sentences': [{'tokens': ['a', 'bus', 'that', 'says', 'sebastian', 'el', 'gde'], 'raw': 'A bus that says Sebastian El GDE.', 'sent_id': 77013, 'sent': 'a bus that says sebastian el gde'}, {'tokens': ['the', 'r1', 'bus'], 'raw': 'The R1 bus.', 'sent_id': 77014, 'sent': 'the r1 bus'}], 'file_name': 'COCO_train2014_000000526922_248285.jpg', 'category_id': 6, 'ann_id': 248285, 'sent_ids': [77013, 77014], 'ref_id': 34577}]\n", + "[{'image_id': 26274, 'split': 'train', 'sentences': [{'tokens': ['a', 'silver', 'van', 'with', 'people', 'facing', 'it'], 'raw': 'A silver van with people facing it.', 'sent_id': 61777, 'sent': 'a silver van with people facing it'}], 'file_name': 'COCO_train2014_000000026274_136004.jpg', 'category_id': 3, 'ann_id': 136004, 'sent_ids': [61777], 'ref_id': 28715}][{'image_id': 65842, 'split': 'train', 'sentences': [{'tokens': ['orange', 'sitting', 'in', 'boiling', 'wate', 'with', 'a', 'crack', 'on', 'the', 'side', 'and', 'a', 'white', 'spot', 'on', 'top'], 'raw': 'Orange sitting in boiling wate with a crack on the side and a white spot on top.', 'sent_id': 90770, 'sent': 'orange sitting in boiling wate with a crack on the side and a white spot on top'}, {'tokens': ['a', 'single', 'lemon', 'in', 'a', 'boiling', 'pot', 'with', 'five', 'lemons', 'surrounding'], 'raw': 'A single lemon in a boiling pot with five lemons surrounding.', 'sent_id': 90771, 'sent': 'a single lemon in a boiling pot with five lemons surrounding'}], 'file_name': 'COCO_train2014_000000065842_1050797.jpg', 'category_id': 55, 'ann_id': 1050797, 'sent_ids': [90770, 90771], 'ref_id': 49234}]\n", + "\n", + "[{'image_id': 315831, 'split': 'train', 'sentences': [{'tokens': ['donut', 'with', 'pink', 'frosting', 'and', 'sprinkles'], 'raw': 'Donut with pink frosting and sprinkles.', 'sent_id': 16573, 'sent': 'donut with pink frosting and sprinkles'}, {'tokens': ['a', 'purple', 'donut'], 'raw': 'A purple donut.', 'sent_id': 16574, 'sent': 'a purple donut'}], 'file_name': 'COCO_train2014_000000315831_1573196.jpg', 'category_id': 60, 'ann_id': 1573196, 'sent_ids': [16573, 16574], 'ref_id': 11418}]\n", + "[{'image_id': 34404, 'split': 'train', 'sentences': [{'tokens': ['person', 'on', 'left', 'cut', 'off'], 'raw': 'person on left cut off', 'sent_id': 29208, 'sent': 'person on left cut off'}, {'tokens': ['the', 'skiir', 'standing', 'up'], 'raw': 'the skiir standing up', 'sent_id': 29209, 'sent': 'the skiir standing up'}], 'file_name': 'COCO_train2014_000000034404_467515.jpg', 'category_id': 1, 'ann_id': 467515, 'sent_ids': [29208, 29209], 'ref_id': 16214}]\n", + "[{'image_id': 427523, 'split': 'train', 'sentences': [{'tokens': ['horse', 'on', 'the', 'left', 'in', 'the', 'right', 'hand', 'picture'], 'raw': 'horse on the left in the right hand picture', 'sent_id': 19348, 'sent': 'horse on the left in the right hand picture'}, {'tokens': ['horse', 'on', 'the', 'left'], 'raw': 'horse on the left', 'sent_id': 19349, 'sent': 'horse on the left'}], 'file_name': 'COCO_train2014_000000427523_54859.jpg', 'category_id': 19, 'ann_id': 54859, 'sent_ids': [19348, 19349], 'ref_id': 12482}]\n", + "[{'image_id': 231963, 'split': 'train', 'sentences': [{'tokens': ['a', 'black', ',', 'green', 'and', 'red', 'train', 'car', 'stopped', 'on', 'the', 'tracks', 'to', 'the', 'right', 'of', 'a', 'train', 'engine'], 'raw': 'A black, green and red train car stopped on the tracks to the right of a train engine.', 'sent_id': 91692, 'sent': 'a black , green and red train car stopped on the tracks to the right of a train engine'}, {'tokens': ['the', 'back', 'of', 'the', 'train', 'leaving'], 'raw': 'The back of the train leaving', 'sent_id': 91693, 'sent': 'the back of the train leaving'}], 'file_name': 'COCO_train2014_000000231963_169754.jpg', 'category_id': 7, 'ann_id': 169754, 'sent_ids': [91692, 91693], 'ref_id': 40250}][{'image_id': 399922, 'split': 'train', 'sentences': [{'tokens': ['purse', 'on', 'front', 'mans', 'back'], 'raw': 'purse on front mans back', 'sent_id': 96153, 'sent': 'purse on front mans back'}, {'tokens': ['a', 'beige', 'satchel'], 'raw': 'a beige satchel.', 'sent_id': 96154, 'sent': 'a beige satchel'}], 'file_name': 'COCO_train2014_000000399922_1176815.jpg', 'category_id': 31, 'ann_id': 1176815, 'sent_ids': [96153, 96154], 'ref_id': 41986}]\n", + "\n", + "[{'image_id': 269045, 'split': 'train', 'sentences': [{'tokens': ['a', 'see', 'through', 'table'], 'raw': 'a see through table', 'sent_id': 36678, 'sent': 'a see through table'}, {'tokens': ['a', 'grilled', 'table', 'near', 'the', 'person', 'with', 'a', 'laptop'], 'raw': 'A grilled table near the person with a laptop', 'sent_id': 36679, 'sent': 'a grilled table near the person with a laptop'}], 'file_name': 'COCO_train2014_000000269045_1612853.jpg', 'category_id': 67, 'ann_id': 1612853, 'sent_ids': [36678, 36679], 'ref_id': 19074}]\n", + "[{'image_id': 419297, 'split': 'train', 'sentences': [{'tokens': ['a', 'white', 'truck', 'filled', 'with', 'luggage'], 'raw': 'A white truck filled with luggage', 'sent_id': 50699, 'sent': 'a white truck filled with luggage'}, {'tokens': ['a', 'white', 'color', 'truck'], 'raw': 'A white color truck.', 'sent_id': 50700, 'sent': 'a white color truck'}], 'file_name': 'COCO_train2014_000000419297_1370937.jpg', 'category_id': 8, 'ann_id': 1370937, 'sent_ids': [50699, 50700], 'ref_id': 24467}]\n", + "[{'image_id': 153609, 'split': 'train', 'sentences': [{'tokens': ['a', 'gentleman', 'wearing', 'a', 'suit', ',', 'looking', 'down', ',', 'and', 'walking', 'with', 'his', 'hands', 'on', 'his', 'hips'], 'raw': 'A gentleman wearing a suit, looking down, and walking with his hands on his hips.', 'sent_id': 102251, 'sent': 'a gentleman wearing a suit , looking down , and walking with his hands on his hips'}, {'tokens': ['a', 'man', 'in', 'a', 'black', 'suit', 'walking'], 'raw': 'A man in a black suit walking.', 'sent_id': 102252, 'sent': 'a man in a black suit walking'}], 'file_name': 'COCO_train2014_000000153609_462146.jpg', 'category_id': 1, 'ann_id': 462146, 'sent_ids': [102251, 102252], 'ref_id': 44392}][{'image_id': 61498, 'split': 'train', 'sentences': [{'tokens': ['a', 'man', 'in', 'a', 'blue', 'shirt'], 'raw': 'A man in a blue shirt.', 'sent_id': 72219, 'sent': 'a man in a blue shirt'}, {'tokens': ['blue', 'shirt', 'boy'], 'raw': 'blue shirt boy', 'sent_id': 72220, 'sent': 'blue shirt boy'}], 'file_name': 'COCO_train2014_000000061498_500279.jpg', 'category_id': 1, 'ann_id': 500279, 'sent_ids': [72219, 72220], 'ref_id': 48407}]\n", + "\n", + "[{'image_id': 334714, 'split': 'train', 'sentences': [{'tokens': ['a', 'long', 'narrow', 'multi', '-', 'colored', 'kite', 'to', 'the', 'left', 'of', 'two', 'other', 'kites', 'of', 'the', 'same', 'colors'], 'raw': 'A long narrow multi-colored kite to the left of two other kites of the same colors.', 'sent_id': 29361, 'sent': 'a long narrow multi - colored kite to the left of two other kites of the same colors'}, {'tokens': ['a', 'side', 'of', 'the', 'kite', 'that', 'is', 'closest', 'to', 'the', 'man', 'in', 'black'], 'raw': 'A side of the kite that is closest to the man in black.', 'sent_id': 29362, 'sent': 'a side of the kite that is closest to the man in black'}], 'file_name': 'COCO_train2014_000000334714_623960.jpg', 'category_id': 38, 'ann_id': 623960, 'sent_ids': [29361, 29362], 'ref_id': 16269}]\n", + "[{'image_id': 233111, 'split': 'train', 'sentences': [{'tokens': ['a', 'tennis', 'player', 'with', 'his', 'right', 'foot', 'balanced', 'on', 'its', 'toes'], 'raw': 'A tennis player with his right foot balanced on its toes.', 'sent_id': 94813, 'sent': 'a tennis player with his right foot balanced on its toes'}, {'tokens': ['a', 'man', 'in', 'a', 'blue', 'shirt', 'holding', 'a', 'tennis', 'racket'], 'raw': 'A man in a 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'in', 'the', 'water', 'with', 'the', 'words', 'u', '.', 's', '.', 'coast', 'guard', 'on', 'the', 'side'], 'raw': 'a boat in the water with the words U.S. Coast Guard on the side', 'sent_id': 78927, 'sent': 'a boat in the water with the words u . s . coast guard on the side'}, {'tokens': ['a', 'red', 'and', 'white', 'us', 'coast', 'guard', 'ship'], 'raw': 'A red and white US Coast Guard Ship.', 'sent_id': 78928, 'sent': 'a red and white us coast guard ship'}], 'file_name': 'COCO_train2014_000000063217_179804.jpg', 'category_id': 9, 'ann_id': 179804, 'sent_ids': [78927, 78928], 'ref_id': 35324}]\n", + "\n", + "[{'image_id': 17520, 'split': 'train', 'sentences': [{'tokens': ['a', 'man', 'wearing', 'a', 'checkered', 'shirt', 'walking', 'and', 'talking', 'on', 'the', 'phone'], 'raw': 'A man wearing a checkered shirt walking and talking on the phone.', 'sent_id': 56923, 'sent': 'a man wearing a checkered shirt walking and talking on the phone'}, {'tokens': ['man', 'wearing', 'a', 'plaid', 'shirt'], 'raw': 'man wearing a plaid shirt.', 'sent_id': 56924, 'sent': 'man wearing a plaid shirt'}], 'file_name': 'COCO_train2014_000000017520_196780.jpg', 'category_id': 1, 'ann_id': 196780, 'sent_ids': [56923, 56924], 'ref_id': 26881}]\n", + "[{'image_id': 137203, 'split': 'train', 'sentences': [{'tokens': ['a', 'woman', 'in', 'red', 'is', 'trying', 'to', 'catch', 'a', 'pink', 'frisbee'], 'raw': 'A woman in red is trying to catch a pink frisbee', 'sent_id': 100490, 'sent': 'a woman in red is trying to catch a pink frisbee'}, {'tokens': ['a', 'woman', 'in', 'a', 'red', 'shirt', 'and', 'jean', 'shorts', 'about', 'to', 'catch', 'a', 'frisbee'], 'raw': 'A woman in a red shirt and jean shorts about to catch a Frisbee.', 'sent_id': 100491, 'sent': 'a woman in a red shirt and jean shorts about to catch a frisbee'}], 'file_name': 'COCO_train2014_000000137203_459492.jpg', 'category_id': 1, 'ann_id': 459492, 'sent_ids': [100490, 100491], 'ref_id': 49657}]\n", + "[{'image_id': 34674, 'split': 'train', 'sentences': [{'tokens': ['the', 'horse', 'of', 'the', 'man', 'without', 'a', 'hat'], 'raw': 'The horse of the man without a hat', 'sent_id': 47889, 'sent': 'the horse of the man without a hat'}, {'tokens': ['horse', 'being', 'ridden', 'by', 'the', 'man', 'without', 'a', 'hat'], 'raw': 'Horse being ridden by the man without a hat.', 'sent_id': 47890, 'sent': 'horse being ridden by the man without a hat'}], 'file_name': 'COCO_train2014_000000034674_56042.jpg', 'category_id': 19, 'ann_id': 56042, 'sent_ids': [47889, 47890], 'ref_id': 23399}]\n", + "[{'image_id': 293975, 'split': 'train', 'sentences': [{'tokens': ['a', 'white', 'laptop', 'comuter'], 'raw': 'A white laptop comuter.', 'sent_id': 48293, 'sent': 'a white laptop comuter'}, {'tokens': ['white', 'laptop'], 'raw': 'white laptop', 'sent_id': 48294, 'sent': 'white laptop'}], 'file_name': 'COCO_train2014_000000293975_1099887.jpg', 'category_id': 73, 'ann_id': 1099887, 'sent_ids': [48293, 48294], 'ref_id': 23543}]\n", + "[{'image_id': 323705, 'split': 'train', 'sentences': [{'tokens': ['a', 'clock', 'face', 'where', 'all', 'the', 'numbers', 'are', 'displayed'], 'raw': 'A clock face where all the numbers are displayed.', 'sent_id': 8682, 'sent': 'a clock face where all the numbers are displayed'}, {'tokens': ['clock', 'facing', 'the', 'front'], 'raw': 'clock facing the front.', 'sent_id': 8683, 'sent': 'clock facing the front'}], 'file_name': 'COCO_train2014_000000323705_335093.jpg', 'category_id': 85, 'ann_id': 335093, 'sent_ids': [8682, 8683], 'ref_id': 8358}]\n", + "[{'image_id': 416819, 'split': 'train', 'sentences': [{'tokens': ['a', 'zebra', 'with', 'his', 'back', 'to', 'the', 'camera'], 'raw': 'A zebra with his back to the camera', 'sent_id': 56637, 'sent': 'a zebra with his back to the camera'}, {'tokens': ['zebra', 'turn', 'the', 'head', 'left', 'hand', 'side'], 'raw': 'Zebra turn the head left hand side', 'sent_id': 56638, 'sent': 'zebra turn the head left hand side'}], 'file_name': 'COCO_train2014_000000416819_591965.jpg', 'category_id': 24, 'ann_id': 591965, 'sent_ids': [56637, 56638], 'ref_id': 26766}]\n", + "[{'image_id': 522298, 'split': 'train', 'sentences': [{'tokens': ['a', 'pink', 'umbrella'], 'raw': 'A pink umbrella.', 'sent_id': 54683, 'sent': 'a pink umbrella'}, {'tokens': ['the', 'red', 'umbrella'], 'raw': 'the red umbrella', 'sent_id': 54684, 'sent': 'the red umbrella'}], 'file_name': 'COCO_train2014_000000522298_283547.jpg', 'category_id': 28, 'ann_id': 283547, 'sent_ids': [54683, 54684], 'ref_id': 26042}]\n", + "[{'image_id': 427756, 'split': 'train', 'sentences': [{'tokens': ['a', 'man', 'standing', 'with', 'blue', 'striped', 'shirt'], 'raw': 'A man standing with blue striped shirt.', 'sent_id': 62696, 'sent': 'a man standing with blue striped shirt'}, {'tokens': ['a', 'man', 'in', 'black', 'jeans', 'and', 'blue', 'and', 'black', 'striped', 'shirt', 'holding', 'wii', 'in', 'hand', 'standing', 'in', 'front', 'of', 'tv'], 'raw': 'A man in black jeans and blue and black striped shirt holding wii in hand standing in front of TV.', 'sent_id': 62697, 'sent': 'a man in black jeans and blue and black striped shirt holding wii in hand standing in front of tv'}], 'file_name': 'COCO_train2014_000000427756_490450.jpg', 'category_id': 1, 'ann_id': 490450, 'sent_ids': [62696, 62697], 'ref_id': 29075}][{'image_id': 405136, 'split': 'train', 'sentences': [{'tokens': ['a', 'woman', 'in', 'a', 'sleeveless', 'shirt', 'is', 'sitting', 'in', 'the', 'passenger', 'seat', 'watching', 'a', 'horse'], 'raw': 'A woman in a sleeveless shirt is sitting in the passenger seat watching a horse', 'sent_id': 12514, 'sent': 'a woman in a sleeveless shirt is sitting in the passenger seat watching a horse'}, {'tokens': ['a', 'person', 'sitting', 'next', 'to', 'the', 'driver'], 'raw': 'A person sitting next to the driver', 'sent_id': 12515, 'sent': 'a person sitting next to the driver'}], 'file_name': 'COCO_train2014_000000405136_188388.jpg', 'category_id': 1, 'ann_id': 188388, 'sent_ids': [12514, 12515], 'ref_id': 9851}]\n", + "\n", + "[{'image_id': 16465, 'split': 'train', 'sentences': [{'tokens': ['a', 'man', 'in', 'a', 'white', 'soccer', 'uniform'], 'raw': 'A man in a white soccer uniform.', 'sent_id': 31029, 'sent': 'a man in a white soccer uniform'}, {'tokens': ['the', 'player', 'wearing', 'the', 'white', 'clothes'], 'raw': 'The player wearing the white clothes.', 'sent_id': 31030, 'sent': 'the player wearing the white clothes'}], 'file_name': 'COCO_train2014_000000016465_477891.jpg', 'category_id': 1, 'ann_id': 477891, 'sent_ids': [31029, 31030], 'ref_id': 16909}]\n", + "[{'image_id': 326685, 'split': 'train', 'sentences': [{'tokens': ['a', 'blurry', 'shot', 'of', 'people', 'riding', 'a', 'scooter', 'in', 'the', 'rain'], 'raw': 'a blurry shot of people riding a scooter in the rain', 'sent_id': 19396, 'sent': 'a blurry shot of people riding a scooter in the rain'}, {'tokens': ['top', 'right', 'blurry', 'motorcyclist', 'going', 'out', 'of', 'frame'], 'raw': 'top right blurry motorcyclist going out of frame.', 'sent_id': 19397, 'sent': 'top right blurry motorcyclist going out of frame'}], 'file_name': 'COCO_train2014_000000326685_1713145.jpg', 'category_id': 1, 'ann_id': 1713145, 'sent_ids': [19396, 19397], 'ref_id': 12499}]\n", + "[{'image_id': 326685, 'split': 'train', 'sentences': [{'tokens': ['green', '&', 'white', 'scooter', 'that', 'women', 'are', 'riding', 'in', 'rain'], 'raw': 'Green & white scooter that women are riding in rain', 'sent_id': 98188, 'sent': 'green & white scooter that women are riding in rain'}, {'tokens': ['white', 'color', 'motor', 'cycle'], 'raw': 'white color motor cycle', 'sent_id': 98189, 'sent': 'white color motor cycle'}], 'file_name': 'COCO_train2014_000000326685_147911.jpg', 'category_id': 4, 'ann_id': 147911, 'sent_ids': [98188, 98189], 'ref_id': 42804}][{'image_id': 316667, 'split': 'train', 'sentences': [{'tokens': ['a', 'bench', 'that', 'is', 'laying', 'on', 'the', 'ground'], 'raw': 'A bench that is laying on the ground', 'sent_id': 15264, 'sent': 'a bench that is laying on the ground'}, {'tokens': ['a', 'bench', 'on', 'which', 'the', 'guy', 'is', 'operating', 'the', 'skate', 'board'], 'raw': 'A bench on which the guy is operating the skate board', 'sent_id': 15265, 'sent': 'a bench on which the guy is operating the skate board'}], 'file_name': 'COCO_train2014_000000316667_1394952.jpg', 'category_id': 15, 'ann_id': 1394952, 'sent_ids': [15264, 15265], 'ref_id': 10907}]\n", + "\n", + "[{'image_id': 60170, 'split': 'train', 'sentences': [{'tokens': ['a', 'baby', 'elephant'], 'raw': 'A baby elephant', 'sent_id': 50475, 'sent': 'a baby elephant'}, {'tokens': ['an', 'elephant', 'that', 'is', 'relatively', 'small'], 'raw': 'An elephant that is relatively small.', 'sent_id': 50476, 'sent': 'an elephant that is relatively small'}], 'file_name': 'COCO_train2014_000000060170_582132.jpg', 'category_id': 22, 'ann_id': 582132, 'sent_ids': [50475, 50476], 'ref_id': 24381}]\n", + "[{'image_id': 546366, 'split': 'train', 'sentences': [{'tokens': ['tennis', 'player', 'holding', 'racquet'], 'raw': 'tennis player holding racquet', 'sent_id': 1541, 'sent': 'tennis player holding racquet'}, {'tokens': ['a', 'woman', 'wearing', 'white'], 'raw': 'a woman wearing white.', 'sent_id': 1542, 'sent': 'a woman wearing white'}], 'file_name': 'COCO_train2014_000000546366_2150776.jpg', 'category_id': 1, 'ann_id': 2150776, 'sent_ids': [1541, 1542], 'ref_id': 45385}][{'image_id': 191994, 'split': 'train', 'sentences': [{'tokens': ['pizza', 'in', 'a', 'tray', 'ready', 'to', 'eat'], 'raw': 'pizza in a tray ready to eat', 'sent_id': 67556, 'sent': 'pizza in a tray ready to eat'}, {'tokens': ['a', 'sandwich', 'with', 'vegetables', 'on', 'a', 'white', 'bread', 'in', 'a', 'carrier'], 'raw': 'A sandwich with vegetables on a white bread in a carrier.', 'sent_id': 67557, 'sent': 'a sandwich with vegetables on a white bread in a carrier'}], 'file_name': 'COCO_train2014_000000191994_1539809.jpg', 'category_id': 51, 'ann_id': 1539809, 'sent_ids': [67556, 67557], 'ref_id': 30964}]\n", + "\n", + "[{'image_id': 239803, 'split': 'train', 'sentences': [{'tokens': ['a', 'teen', 'in', 'a', 'black', 'coat', 'to', 'the', 'right', 'of', 'two', 'other', 'teens'], 'raw': 'A teen in a black coat to the right of two other teens.', 'sent_id': 64376, 'sent': 'a teen in a black coat to the right of two other teens'}, {'tokens': ['a', 'young', 'gentleman', 'wearing', 'a', 'black', 'leather', 'jacket'], 'raw': 'A young gentleman wearing a black leather jacket', 'sent_id': 64377, 'sent': 'a young gentleman wearing a black leather jacket'}], 'file_name': 'COCO_train2014_000000239803_2166462.jpg', 'category_id': 1, 'ann_id': 2166462, 'sent_ids': [64376, 64377], 'ref_id': 29734}]\n", + "[{'image_id': 235646, 'split': 'train', 'sentences': [{'tokens': ['the', 'giraffe', 'whose', 'head', 'is', 'not', 'visible'], 'raw': 'The giraffe whose head is not visible', 'sent_id': 50286, 'sent': 'the giraffe whose head is not visible'}, {'tokens': ['body', 'of', 'a', 'giraffe', 'stading', 'to', 'the', 'upper', 'right', 'of', 'the', 'group', 'against', 'the', 'fence'], 'raw': 'Body of a giraffe stading to the upper right of the group against the fence', 'sent_id': 50287, 'sent': 'body of a giraffe stading to the upper right of the group against the fence'}], 'file_name': 'COCO_train2014_000000235646_1414611.jpg', 'category_id': 25, 'ann_id': 1414611, 'sent_ids': [50286, 50287], 'ref_id': 24303}][{'image_id': 176385, 'split': 'train', 'sentences': [{'tokens': ['there', 'is', 'nobody', 'riding', 'this', 'skateboard'], 'raw': 'There is nobody riding this skateboard.', 'sent_id': 24280, 'sent': 'there is nobody riding this skateboard'}, {'tokens': ['a', 'skateboard', 'alone', 'on', 'the', 'ground'], 'raw': 'A skateboard alone on the ground.', 'sent_id': 24281, 'sent': 'a skateboard alone on the ground'}], 'file_name': 'COCO_train2014_000000176385_645613.jpg', 'category_id': 41, 'ann_id': 645613, 'sent_ids': [24280, 24281], 'ref_id': 14373}]\n", + "\n", + "[{'image_id': 131007, 'split': 'train', 'sentences': [{'tokens': ['black', 'chair', 'in', 'corner'], 'raw': 'black chair in corner', 'sent_id': 98162, 'sent': 'black chair in corner'}, {'tokens': ['a', 'black', 'recliner', 'chair'], 'raw': 'a black recliner chair', 'sent_id': 98163, 'sent': 'a black recliner chair'}], 'file_name': 'COCO_train2014_000000131007_115747.jpg', 'category_id': 63, 'ann_id': 115747, 'sent_ids': [98162, 98163], 'ref_id': 42794}]\n", + "[{'image_id': 155995, 'split': 'train', 'sentences': [{'tokens': ['a', 'child', 'baseball', 'player', 'throwing', 'a', 'pitch', 'to', 'a', 'batter'], 'raw': 'A child baseball player throwing a pitch to a batter.', 'sent_id': 15351, 'sent': 'a child baseball player throwing a pitch to a batter'}, {'tokens': ['the', 'pitcher'], 'raw': 'the pitcher', 'sent_id': 15352, 'sent': 'the pitcher'}], 'file_name': 'COCO_train2014_000000155995_525361.jpg', 'category_id': 1, 'ann_id': 525361, 'sent_ids': [15351, 15352], 'ref_id': 10939}][{'image_id': 514025, 'split': 'train', 'sentences': [{'tokens': ['a', 'large', 'blue', 'and', 'white', 'crane', 'standing', 'on', 'the', 'dock'], 'raw': 'a large blue and white crane standing on the dock', 'sent_id': 43870, 'sent': 'a large blue and white crane standing on the dock'}, {'tokens': ['a', 'bird', 'that', 'is', 'standing', 'on', 'the', 'dock', 'with', 'long', 'legs', 'and', 'a', 'scrunched', 'up', 'neck'], 'raw': 'A bird that is standing on the dock with long legs and a scrunched up neck.', 'sent_id': 43871, 'sent': 'a bird that is standing on the dock with long legs and a scrunched up neck'}], 'file_name': 'COCO_train2014_000000514025_36534.jpg', 'category_id': 16, 'ann_id': 36534, 'sent_ids': [43870, 43871], 'ref_id': 21856}]\n", + "[{'image_id': 485705, 'split': 'train', 'sentences': [{'tokens': ['middle', 'banana', 'in', 'the', 'bunch'], 'raw': 'middle banana in the bunch', 'sent_id': 30403, 'sent': 'middle banana in the bunch'}, {'tokens': ['the', 'bottom', 'banana', 'in', 'the', 'right', 'hand', 'picture'], 'raw': 'the bottom banana in the right hand picture', 'sent_id': 30404, 'sent': 'the bottom banana in the right hand picture'}], 'file_name': 'COCO_train2014_000000485705_1043190.jpg', 'category_id': 52, 'ann_id': 1043190, 'sent_ids': [30403, 30404], 'ref_id': 16660}]\n", + "\n", + "[{'image_id': 308758, 'split': 'train', 'sentences': [{'tokens': ['a', 'man', 'wearing', 'a', 'chef', 'jacket'], 'raw': 'a man wearing a chef jacket', 'sent_id': 30897, 'sent': 'a man wearing a chef jacket'}, {'tokens': ['man', 'preparing', 'a', 'dish'], 'raw': 'Man preparing a dish', 'sent_id': 30898, 'sent': 'man preparing a dish'}], 'file_name': 'COCO_train2014_000000308758_196341.jpg', 'category_id': 1, 'ann_id': 196341, 'sent_ids': [30897, 30898], 'ref_id': 16860}][{'image_id': 54194, 'split': 'train', 'sentences': [{'tokens': ['a', 'lady', 'with', 'black', 'long', 'hair', 'in', 'a', 'yellow', 'shirt', ',', 'putting', 'butter', 'on', 'a', 'bread'], 'raw': 'a lady with black long hair in a yellow shirt, putting butter on a bread', 'sent_id': 52248, 'sent': 'a lady with black long hair in a yellow shirt , putting butter on a bread'}, {'tokens': ['a', 'woman', 'in', 'yellow', 'with', 'a', 'knife', 'in', 'her', 'hand', 'buttering', 'her', 'sub', 'sandwich'], 'raw': 'A woman in yellow with a knife in her hand buttering her sub sandwich.', 'sent_id': 52249, 'sent': 'a woman in yellow with a knife in her hand buttering her sub sandwich'}], 'file_name': 'COCO_train2014_000000054194_233992.jpg', 'category_id': 1, 'ann_id': 233992, 'sent_ids': [52248, 52249], 'ref_id': 25093}]\n", + "\n", + "[{'image_id': 563447, 'split': 'train', 'sentences': [{'tokens': ['the', 'kid', 'wearing', 'glasses'], 'raw': 'the kid wearing glasses', 'sent_id': 46806, 'sent': 'the kid wearing glasses'}, {'tokens': ['a', 'short', 'girl', 'standing', 'next', 'to', 'a', 'short', 'horse', 'wearing', 'a', 'belt', 'buckle', 'and', 'glasses'], 'raw': 'A short girl standing next to a short horse wearing a belt buckle and glasses', 'sent_id': 46807, 'sent': 'a short girl standing next to a short horse wearing a belt buckle and glasses'}], 'file_name': 'COCO_train2014_000000563447_186920.jpg', 'category_id': 1, 'ann_id': 186920, 'sent_ids': [46806, 46807], 'ref_id': 22985}]\n", + "[{'image_id': 404592, 'split': 'train', 'sentences': [{'tokens': ['a', 'man', 'sitting', 'on', 'a', 'couch', 'between', 'two', 'other', 'people'], 'raw': 'A man sitting on a couch between two other people.', 'sent_id': 37227, 'sent': 'a man sitting on a couch between two other people'}, {'tokens': ['a', 'man', 'with', 'black', 'hair', 'wearing', 'a', 'black', 'shirt', 'and', 'holding', 'an', 'apple', 'laptop', 'between', 'a', 'man', 'and', 'a', 'woman'], 'raw': 'A man with black hair wearing a black shirt and holding an apple laptop between a man and a woman.', 'sent_id': 37228, 'sent': 'a man with black hair wearing a black shirt and holding an apple laptop between a man and a woman'}], 'file_name': 'COCO_train2014_000000404592_203428.jpg', 'category_id': 1, 'ann_id': 203428, 'sent_ids': [37227, 37228], 'ref_id': 19287}]\n", + "[{'image_id': 36041, 'split': 'train', 'sentences': [{'tokens': ['a', 'girl', 'uitting', 'the', 'bike', 'with', 'boy', 'friend'], 'raw': 'A GIRL UITTING THE BIKE WITH BOY FRIEND', 'sent_id': 75019, 'sent': 'a girl uitting the bike with boy friend'}, {'tokens': ['the', 'girl', 'on', 'the', 'red', 'scooter'], 'raw': 'The girl on the red scooter', 'sent_id': 75020, 'sent': 'the girl on the red scooter'}], 'file_name': 'COCO_train2014_000000036041_199362.jpg', 'category_id': 1, 'ann_id': 199362, 'sent_ids': [75019, 75020], 'ref_id': 33798}]\n", + "[{'image_id': 58105, 'split': 'train', 'sentences': [{'tokens': ['upside', 'down', 'chair'], 'raw': 'upside down chair', 'sent_id': 15047, 'sent': 'upside down chair'}, {'tokens': ['the', 'upside', 'down', 'chair'], 'raw': 'The upside down chair.', 'sent_id': 15048, 'sent': 'the upside down chair'}], 'file_name': 'COCO_train2014_000000058105_1587145.jpg', 'category_id': 62, 'ann_id': 1587145, 'sent_ids': [15047, 15048], 'ref_id': 10822}]\n", + "[{'image_id': 309386, 'split': 'train', 'sentences': [{'tokens': ['a', 'food', 'on', 'tabule'], 'raw': 'a food on tabule', 'sent_id': 62106, 'sent': 'a food on tabule'}, {'tokens': ['a', 'table', 'with', 'pizza', 'slices', 'and', 'beer', 'on', 'it'], 'raw': 'A table with pizza slices and beer on it.', 'sent_id': 62107, 'sent': 'a table with pizza slices and beer on it'}], 'file_name': 'COCO_train2014_000000309386_1091316.jpg', 'category_id': 67, 'ann_id': 1091316, 'sent_ids': [62106, 62107], 'ref_id': 28845}][{'image_id': 419062, 'split': 'train', 'sentences': [{'tokens': ['a', 'medium', 'elephant', 'on', 'the', 'left'], 'raw': 'a medium elephant on the left', 'sent_id': 73909, 'sent': 'a medium elephant on the left'}, {'tokens': ['elephant', 'on', 'shore'], 'raw': 'elephant on shore', 'sent_id': 73910, 'sent': 'elephant on shore'}], 'file_name': 'COCO_train2014_000000419062_580921.jpg', 'category_id': 22, 'ann_id': 580921, 'sent_ids': [73909, 73910], 'ref_id': 33380}]\n", + "\n", + "[{'image_id': 325837, 'split': 'train', 'sentences': [{'tokens': ['a', 'glass', 'window', 'pain', 'behind', 'a', 'man', \"'\", 's'], 'raw': \"a glass window pain behind a man's\", 'sent_id': 68994, 'sent': \"a glass window pain behind a man ' s\"}, {'tokens': ['a', 'window', 'right', 'behind', 'the', 'man', \"'\", 's', 'head'], 'raw': \"a window right behind the man's head\", 'sent_id': 68995, 'sent': \"a window right behind the man ' s head\"}], 'file_name': 'COCO_train2014_000000325837_1732077.jpg', 'category_id': 1, 'ann_id': 1732077, 'sent_ids': [68994, 68995], 'ref_id': 31514}]\n", + "[{'image_id': 258727, 'split': 'train', 'sentences': [{'tokens': ['a', 'sheep', 'eating', 'grass', 'facing', 'away', 'from', 'the', 'camera', 'and', 'closer', 'to', 'the', 'building'], 'raw': 'A sheep eating grass facing away from the camera and closer to the building.', 'sent_id': 95715, 'sent': 'a sheep eating grass facing away from the camera and closer to the building'}, {'tokens': ['there', 'is', 'one', 'sheep', 'is', 'eating', 'grass', 'infront', 'of', 'a', 'home'], 'raw': 'There is one sheep is eating grass infront of a home', 'sent_id': 95716, 'sent': 'there is one sheep is eating grass infront of a home'}], 'file_name': 'COCO_train2014_000000258727_62432.jpg', 'category_id': 20, 'ann_id': 62432, 'sent_ids': [95715, 95716], 'ref_id': 41806}]\n", + "[{'image_id': 15262, 'split': 'train', 'sentences': [{'tokens': ['a', 'fork', 'on', 'a', 'plate'], 'raw': 'A fork on a plate', 'sent_id': 21138, 'sent': 'a fork on a plate'}, {'tokens': ['a', 'silver', 'fork'], 'raw': 'a silver fork', 'sent_id': 21139, 'sent': 'a silver fork'}], 'file_name': 'COCO_train2014_000000015262_1889611.jpg', 'category_id': 48, 'ann_id': 1889611, 'sent_ids': [21138, 21139], 'ref_id': 13163}]\n", + "[{'image_id': 62336, 'split': 'train', 'sentences': [{'tokens': ['the', 'man', 'in', 'the', 'black', 'pullover', 'jacket', 'sitting', 'on', 'the', 'right'], 'raw': 'the man in the black pullover jacket sitting on the right', 'sent_id': 36534, 'sent': 'the man in the black pullover jacket sitting on the right'}, {'tokens': ['a', 'man', 'in', 'a', 'black', 'jacket', 'with', 'his', 'eyes', 'closed', ',', 'drinking', 'from', 'a', 'glass', 'of', 'wine'], 'raw': 'A man in a black jacket with his eyes closed, drinking from a glass of wine', 'sent_id': 36535, 'sent': 'a man in a black jacket with his eyes closed , drinking from a glass of wine'}], 'file_name': 'COCO_train2014_000000062336_1716597.jpg', 'category_id': 1, 'ann_id': 1716597, 'sent_ids': [36534, 36535], 'ref_id': 19021}]\n", + "torch.Size([8, 3, 480, 480])\n", + "torch.Size([8, 480, 480])\n", + "torch.Size([8, 1, 20])\n", + "torch.Size([8, 1, 20])\n", + "tensor([[1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]])\n" + ] + } + ], + "source": [ + "# sample datas\n", + "for i, (img, target, tensor_embeddings, attention_mask) in enumerate(data_loader):\n", + " print(img.shape)\n", + " print(target.shape)\n", + " print(tensor_embeddings.shape)\n", + " print(attention_mask.shape)\n", + " print(attention_mask[0])\n", + " break" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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", 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" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "import matplotlib.pyplot as plt\n", + "from matplotlib.ticker import MaxNLocator, FormatStrFormatter\n", + "\n", + "# Data from the table\n", + "models = ['eqV2-S', 'eqV2-M', 'eqV2-L'] \n", + "layers = [2, 4, 8, 3, 6, 12, 5, 10, 20]\n", + "original_layers = [8, 12, 20]\n", + "original_throughput = [9.4, 7.4, 4.9]\n", + "ours_throughput = [40.4, 28.7, 16.8, 31.6, 22.3, 13.9, 24.1, 15.8, 9.4]\n", + "\n", + "# Create the plot\n", + "fig, ax = plt.subplots(figsize=(8, 6))\n", + "ax.scatter(original_layers, original_throughput, label='Original')\n", + "ax.scatter(layers, ours_throughput, label='Ours')\n", + "ax.set_xscale('log', base=2)\n", + "ax.set_yscale('log',base=2)\n", + "ax.set_title('Throughput Comparison', fontsize=16)\n", + "ax.set_xlabel('Number of Layers', fontsize=13)\n", + "ax.set_ylabel('Throughput (samples/sec)', fontsize=13)\n", + "ax.legend(fontsize=12)\n", + "\n", + "# Set the tick locator and formatter to show integer values\n", + "ax.xaxis.set_major_locator(MaxNLocator(integer=True))\n", + "ax.xaxis.set_major_formatter(FormatStrFormatter('%.0f'))\n", + "ax.yaxis.set_major_locator(MaxNLocator(integer=True))\n", + "ax.yaxis.set_major_formatter(FormatStrFormatter('%.0f'))\n", + "ax.grid(True)\n", + "\n", + "plt.show()" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "lavt", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.9.21" + } + }, + "nbformat": 4, + "nbformat_minor": 2 +} diff --git a/LAVT-RIS/data/__pycache__/dataset_refer_bert.cpython-39.pyc b/LAVT-RIS/data/__pycache__/dataset_refer_bert.cpython-39.pyc new file mode 100644 index 0000000000000000000000000000000000000000..b26c94924653cbca7fa25ca15cf676925710229e Binary files /dev/null and b/LAVT-RIS/data/__pycache__/dataset_refer_bert.cpython-39.pyc differ diff --git a/LAVT-RIS/data/__pycache__/dataset_refer_bert_mostat.cpython-39.pyc b/LAVT-RIS/data/__pycache__/dataset_refer_bert_mostat.cpython-39.pyc new file mode 100644 index 0000000000000000000000000000000000000000..a133acfbb74e0020783b36d62792d546722d61b3 Binary files /dev/null and b/LAVT-RIS/data/__pycache__/dataset_refer_bert_mostat.cpython-39.pyc differ diff --git a/LAVT-RIS/data/__pycache__/dataset_refer_bert_rev.cpython-39.pyc b/LAVT-RIS/data/__pycache__/dataset_refer_bert_rev.cpython-39.pyc new file mode 100644 index 0000000000000000000000000000000000000000..7729006a2e500b6baa90760299c62e144b220214 Binary files /dev/null and b/LAVT-RIS/data/__pycache__/dataset_refer_bert_rev.cpython-39.pyc differ diff --git a/LAVT-RIS/data/__pycache__/dataset_refer_zom.cpython-39.pyc b/LAVT-RIS/data/__pycache__/dataset_refer_zom.cpython-39.pyc new file mode 100644 index 0000000000000000000000000000000000000000..759eee3c1c147d4431e788acf0de514fdbde22db Binary files /dev/null and b/LAVT-RIS/data/__pycache__/dataset_refer_zom.cpython-39.pyc differ diff --git a/LAVT-RIS/data/dataset_refer_bert.py b/LAVT-RIS/data/dataset_refer_bert.py new file mode 100644 index 0000000000000000000000000000000000000000..d39ca4c0d41eab0b02984f9eaa16907238c27dec --- /dev/null +++ b/LAVT-RIS/data/dataset_refer_bert.py @@ -0,0 +1,228 @@ +import os +import sys +import json +import torch.utils.data as data +import torch +from torchvision import transforms +import numpy as np +from PIL import Image +import torchvision.transforms.functional as TF +import random + +from bert.tokenization_bert import BertTokenizer +from refer.refer import REFER + +from args import get_parser + +# Dataset configuration initialization +# parser = get_parser() +# args = parser.parse_args() + + +class ReferDataset(data.Dataset): + + def __init__(self, + args, + image_transforms=None, + target_transforms=None, + split='train', + eval_mode=False): + + self.classes = [] + self.image_transforms = image_transforms + self.target_transform = target_transforms + self.split = split + self.refer = REFER(args.refer_data_root, args.dataset, args.splitBy) + + self.max_tokens = 20 + + ref_ids = self.refer.getRefIds(split=self.split) + img_ids = self.refer.getImgIds(ref_ids) + + all_imgs = self.refer.Imgs + self.imgs = list(all_imgs[i] for i in img_ids) + self.ref_ids = ref_ids + + self.input_ids = [] + self.attention_masks = [] + self.tokenizer = BertTokenizer.from_pretrained(args.bert_tokenizer) + + # for metric learning + self.ROOT = '/data2/dataset/RefCOCO/VRIS' + self.metric_learning = args.metric_learning + self.exclude_multiobj = args.exclude_multiobj + self.metric_mode = args.metric_mode + self.exclude_position = False + + if self.metric_learning and eval_mode == False: + self.hardneg_prob = args.hn_prob + self.multi_obj_ref_ids = self._load_multi_obj_ref_ids() + self.hardpos_meta, self.hardneg_meta = self._load_metadata() + else: + self.hardneg_prob = 0.0 + self.multi_obj_ref_ids = None + self.hardpos_meta, self.hardneg_meta = None, None + + + self.eval_mode = eval_mode + # if we are testing on a dataset, test all sentences of an object; + # o/w, we are validating during training, randomly sample one sentence for efficiency + for r in ref_ids: + ref = self.refer.Refs[r] + + sentences_for_ref = [] + attentions_for_ref = [] + + for i, (el, sent_id) in enumerate(zip(ref['sentences'], ref['sent_ids'])): + sentence_raw = el['raw'] + attention_mask = [0] * self.max_tokens + padded_input_ids = [0] * self.max_tokens + + input_ids = self.tokenizer.encode(text=sentence_raw, add_special_tokens=True) + + # truncation of tokens + input_ids = input_ids[:self.max_tokens] + + padded_input_ids[:len(input_ids)] = input_ids + attention_mask[:len(input_ids)] = [1]*len(input_ids) + + sentences_for_ref.append(torch.tensor(padded_input_ids).unsqueeze(0)) + attentions_for_ref.append(torch.tensor(attention_mask).unsqueeze(0)) + + self.input_ids.append(sentences_for_ref) + self.attention_masks.append(attentions_for_ref) + + + def _tokenize(self, sentence): + attention_mask = [0] * self.max_tokens + padded_input_ids = [0] * self.max_tokens + + input_ids = self.tokenizer.encode(text=sentence, add_special_tokens=True) + # truncation of tokens + input_ids = input_ids[:self.max_tokens] + padded_input_ids[:len(input_ids)] = input_ids + attention_mask[:len(input_ids)] = [1]*len(input_ids) + + # match shape as (1, max_tokens) + return torch.tensor(padded_input_ids).unsqueeze(0), torch.tensor(attention_mask).unsqueeze(0) + + + def _load_multi_obj_ref_ids(self): + # Load multi-object reference IDs based on configurations + if not self.exclude_multiobj and not self.exclude_position : + return None + elif self.exclude_position: + multiobj_path = os.path.join(self.ROOT, 'multiobj_ov2_nopos.txt') + elif self.exclude_multiobj : + multiobj_path = os.path.join(self.ROOT, 'multiobj_ov3.txt') + with open(multiobj_path, 'r') as f: + return [int(line.strip()) for line in f.readlines()] + + def _load_metadata(self): + # Load metadata for hard positive verb phrases, hard negative queries + if 'refined' in self.metric_mode or 'hardneg' in self.metric_mode : + hardpos_path = os.path.join(self.ROOT, 'hardpos_verdict_gref_v4.json') + else : + hardpos_path = os.path.join(self.ROOT, 'hardpos_verbphrase_0906upd.json') + # do not use hardneg_path + hardneg_path = os.path.join(self.ROOT, 'hardneg_verb.json') + + with open(hardpos_path, 'r', encoding='utf-8') as f: + hardpos_json = json.load(f) + if "hardpos_only" in self.metric_mode : + hardneg_json = None + else : + with open(hardneg_path, 'r', encoding='utf-8') as q: + hardneg_json = json.load(q) + return hardpos_json, hardneg_json + + + def get_classes(self): + return self.classes + + def __len__(self): + return len(self.ref_ids) + + def __getitem__(self, index): + this_ref_id = self.ref_ids[index] + this_img_id = self.refer.getImgIds(this_ref_id) + this_img = self.refer.Imgs[this_img_id[0]] + + IMAGE_DIR = '/data2/dataset/COCO2014/trainval2014/' + img = Image.open(os.path.join(IMAGE_DIR, this_img['file_name'])).convert("RGB") + + ref = self.refer.loadRefs(this_ref_id) + #print(ref) + + ref_mask = np.array(self.refer.getMask(ref[0])['mask']) + annot = np.zeros(ref_mask.shape) + annot[ref_mask == 1] = 1 + annot = Image.fromarray(annot.astype(np.uint8), mode="P") + + if self.image_transforms is not None: + # resize, from PIL to tensor, and mean and std normalization + img, target = self.image_transforms(img, annot) + + if self.eval_mode: + embedding = [] + att = [] + for s in range(len(self.input_ids[index])): + e = self.input_ids[index][s] + a = self.attention_masks[index][s] + embedding.append(e.unsqueeze(-1)) + att.append(a.unsqueeze(-1)) + + tensor_embeddings = torch.cat(embedding, dim=-1) + attention_mask = torch.cat(att, dim=-1) + + return img, target, tensor_embeddings, attention_mask + + else: # train phase + choice_sent = np.random.choice(len(self.input_ids[index])) + tensor_embeddings = self.input_ids[index][choice_sent] + attention_mask = self.attention_masks[index][choice_sent] + + pos_sent = torch.zeros_like(tensor_embeddings) + neg_sent = torch.zeros_like(tensor_embeddings) + pos_attn_mask = torch.zeros_like(attention_mask) + neg_attn_mask = torch.zeros_like(attention_mask) + + if self.metric_learning: + if 'hardpos_' in self.metric_mode or self.hardneg_prob == 0.0: + pos_sents = self.hardpos_meta[str(this_ref_id)].values() + # drop elements with none + pos_sents = [s for s in pos_sents if s is not None] + pos_sent_picked = random.choice(list(pos_sents)) + if pos_sent_picked: + pos_sent, pos_attn_mask = self._tokenize(pos_sent_picked) + else: + pos_sents = self.hardpos_meta[str(this_ref_id)].values() + # drop elements with none + pos_sents = [s for s in pos_sents if s is not None] + pos_sent_picked = random.choice(list(pos_sents)) + + if pos_sent_picked: + pos_sent, pos_attn_mask = self._tokenize(pos_sent_picked) + + if random.random() < self.hardneg_prob: + neg_sents = self.hardneg_meta[str(this_ref_id)].values() + neg_sents = [s for s in neg_sents if s is not None] + neg_sent_picked = random.choice(list(neg_sents)) + #print("neg_sent: ", neg_sent) + + if neg_sent_picked: + neg_sent, neg_attn_mask = self._tokenize(neg_sent_picked) + + # print("index: ", self.input_ids[index]) + # print("choice_sent: ", choice_sent) + # print("tensor_embeddings: ", tensor_embeddings) + # print("original sentence: ", self.tokenizer.decode(tensor_embeddings.squeeze(0).tolist())) + # print("pos_sent: ", pos_sent) + # print("neg_sent: ", neg_sent) + # print("pos_attn_mask: ", pos_attn_mask) + # print("neg_attn_mask: ", neg_attn_mask) + + #exit() + + + return img, target, tensor_embeddings, attention_mask, pos_sent, pos_attn_mask, neg_sent, neg_attn_mask diff --git a/LAVT-RIS/data/dataset_refer_bert_mostat.py b/LAVT-RIS/data/dataset_refer_bert_mostat.py new file mode 100644 index 0000000000000000000000000000000000000000..dc6b26da589ff8d012ee7391382f9fc329ecfdf2 --- /dev/null +++ b/LAVT-RIS/data/dataset_refer_bert_mostat.py @@ -0,0 +1,136 @@ +import os +import sys +import torch.utils.data as data +import torch +from torchvision import transforms +from torch.autograd import Variable +import numpy as np +from PIL import Image +import torchvision.transforms.functional as TF +import random + +from bert.tokenization_bert import BertTokenizer + +import h5py +from refer.refer import REFER + +from args import get_parser + +# Dataset configuration initialization +parser = get_parser() +args = parser.parse_args() + + +class ReferDataset(data.Dataset): + + def __init__(self, + args, + image_transforms=None, + target_transforms=None, + split='train', + eval_mode=False): + + self.classes = [] + self.image_transforms = image_transforms + self.target_transform = target_transforms + self.split = split + self.dataset = args.dataset + self.args = args + if args.dataset == 'refcocog' and args.split in ['motion', 'static']: + import json + print(f"Easy & Hard Example Experiments - dataset : {args.dataset}, split : {args.split}") + if args.split == 'motion' : + meta_fp = '/data2/projects/chaeyun/LAVT-RIS/test_ablation_motion.json' + else : + meta_fp = '/data2/projects/chaeyun/LAVT-RIS/test_ablation_static.json' + + with open(meta_fp, 'r') as f : + ref_metas = json.load(f) + + self.refer = REFER(args.refer_data_root, args.dataset, args.splitBy) + + self.max_tokens = 20 + + # motion, static split binning + self.input_ids = [] + self.attention_masks = [] + self.tokenizer = BertTokenizer.from_pretrained(args.bert_tokenizer) + self.ref_ids = [] + self.eval_mode = eval_mode + self.refer_ctmz = {} + + for ref in ref_metas : + sentences_for_ref = [] + attentions_for_ref = [] + sent_lens_for_ref = [] + + for i, sents in enumerate(ref['sentences']) : + sentence_raw = sents['sent'] + + attention_mask = [0] * self.max_tokens + padded_input_ids = [0] * self.max_tokens + input_ids = self.tokenizer.encode(text=sentence_raw, add_special_tokens=True) + input_ids = input_ids[:self.max_tokens] + + padded_input_ids[:len(input_ids)] = input_ids + attention_mask[:len(input_ids)] = [1]*len(input_ids) + + sentences_for_ref.append(torch.tensor(padded_input_ids).unsqueeze(0)) + attentions_for_ref.append(torch.tensor(attention_mask).unsqueeze(0)) + + self.input_ids.append(sentences_for_ref) + self.attention_masks.append(attentions_for_ref) + self.ref_ids.append(ref['segment_id']) + + if ref['segment_id'] not in self.refer_ctmz : + self.refer_ctmz[ref['segment_id']] = ref + + img_ids = self.refer.getImgIds(self.ref_ids) + all_imgs = self.refer.Imgs + self.imgs = list(all_imgs[i] for i in img_ids) + + def get_classes(self): + return self.classes + + def __len__(self): + return len(self.ref_ids) + + def __getitem__(self, index): + this_ref_id = self.ref_ids[index] + this_img_id = self.refer.getImgIds(this_ref_id) + this_img = self.refer.Imgs[this_img_id[0]] + + IMAGE_DIR = '/data2/dataset/COCO2014/train2014/' + img = Image.open(os.path.join(IMAGE_DIR, this_img['file_name'])).convert("RGB") + ref_orig = self.refer.loadRefs(this_ref_id) + ref = self.refer_ctmz[this_ref_id] + + ref_mask = np.array(self.refer.getMask(ref_orig[0])['mask']) + annot = np.zeros(ref_mask.shape) + + annot[ref_mask == 1] = 1 + annot = Image.fromarray(annot.astype(np.uint8), mode="P") + + if self.image_transforms is not None: + # resize, from PIL to tensor, and mean and std normalization + img, target = self.image_transforms(img, annot) + + if self.eval_mode: + embedding = [] + att = [] + for s in range(len(self.input_ids[index])): + e = self.input_ids[index][s] + a = self.attention_masks[index][s] + embedding.append(e.unsqueeze(-1)) + att.append(a.unsqueeze(-1)) + + tensor_embeddings = torch.cat(embedding, dim=-1) + attention_mask = torch.cat(att, dim=-1) + + return img, target, tensor_embeddings, attention_mask + else: + choice_sent = np.random.choice(len(self.input_ids[index])) + tensor_embeddings = self.input_ids[index][choice_sent] + attention_mask = self.attention_masks[index][choice_sent] + + return img, target, tensor_embeddings, attention_mask \ No newline at end of file diff --git a/LAVT-RIS/data/dataset_refer_bert_rev.py b/LAVT-RIS/data/dataset_refer_bert_rev.py new file mode 100644 index 0000000000000000000000000000000000000000..56aefd9f2cde06322fb7cdbddb056849abe1768c --- /dev/null +++ b/LAVT-RIS/data/dataset_refer_bert_rev.py @@ -0,0 +1,246 @@ +import os +import sys +import json +import torch.utils.data as data +import torch +import itertools +from torchvision import transforms +from torch.autograd import Variable +import numpy as np +from PIL import Image +import torchvision.transforms.functional as TF +import random + +from bert.tokenization_bert import BertTokenizer + +import h5py +from refer.refer import REFER + +from args import get_parser + +# Dataset configuration initialization +# parser = get_parser() +# args = parser.parse_args() + + +class ReferDataset(data.Dataset): + + def __init__(self, + args, + image_transforms=None, + target_transforms=None, + split='train', + eval_mode=False): + + self.classes = [] + self.image_transforms = image_transforms + self.target_transform = target_transforms + self.split = split + self.refer = REFER(args.refer_data_root, args.dataset, args.splitBy) + + self.max_tokens = 20 + + ref_ids = self.refer.getRefIds(split=self.split) + img_ids = self.refer.getImgIds(ref_ids) + + all_imgs = self.refer.Imgs + self.imgs = list(all_imgs[i] for i in img_ids) + self.ref_ids = ref_ids + + self.input_ids = [] + self.attention_masks = [] + self.tokenizer = BertTokenizer.from_pretrained(args.bert_tokenizer) + + # for metric learning + self.ROOT = '/data2/projects/seunghoon/VerbRIS/VerbCentric_CY/datasets/VRIS' + self.metric_learning = args.metric_learning + self.exclude_multiobj = args.exclude_multiobj + self.metric_mode = args.metric_mode + self.exclude_position = False + self.hp_selection = args.hp_selection + + if self.metric_learning and eval_mode == False: + self.hardneg_prob = args.hn_prob + self.multi_obj_ref_ids = self._load_multi_obj_ref_ids() + self.hardpos_meta, self.hardneg_meta = self._load_metadata() + else: + self.hardneg_prob = 0.0 + self.multi_obj_ref_ids = None + self.hardpos_meta, self.hardneg_meta = None, None + + + self.eval_mode = eval_mode + # if we are testing on a dataset, test all sentences of an object; + # o/w, we are validating during training, randomly sample one sentence for efficiency + for r in ref_ids: + ref = self.refer.Refs[r] + + sentences_for_ref = [] + attentions_for_ref = [] + + for i, (el, sent_id) in enumerate(zip(ref['sentences'], ref['sent_ids'])): + sentence_raw = el['raw'] + attention_mask = [0] * self.max_tokens + padded_input_ids = [0] * self.max_tokens + + input_ids = self.tokenizer.encode(text=sentence_raw, add_special_tokens=True) + + # truncation of tokens + input_ids = input_ids[:self.max_tokens] + + padded_input_ids[:len(input_ids)] = input_ids + attention_mask[:len(input_ids)] = [1]*len(input_ids) + + sentences_for_ref.append(torch.tensor(padded_input_ids).unsqueeze(0)) + attentions_for_ref.append(torch.tensor(attention_mask).unsqueeze(0)) + + self.input_ids.append(sentences_for_ref) + self.attention_masks.append(attentions_for_ref) + + + def _tokenize(self, sentence): + attention_mask = [0] * self.max_tokens + padded_input_ids = [0] * self.max_tokens + + input_ids = self.tokenizer.encode(text=sentence, add_special_tokens=True) + # truncation of tokens + input_ids = input_ids[:self.max_tokens] + padded_input_ids[:len(input_ids)] = input_ids + attention_mask[:len(input_ids)] = [1]*len(input_ids) + + # match shape as (1, max_tokens) + return torch.tensor(padded_input_ids).unsqueeze(0), torch.tensor(attention_mask).unsqueeze(0) + + + def _load_multi_obj_ref_ids(self): + # Load multi-object reference IDs based on configurations + if not self.exclude_multiobj and not self.exclude_position : + return None + elif self.exclude_position: + multiobj_path = os.path.join(self.ROOT, 'multiobj_ov2_nopos.txt') + elif self.exclude_multiobj : + multiobj_path = os.path.join(self.ROOT, 'multiobj_ov3.txt') + with open(multiobj_path, 'r') as f: + return [int(line.strip()) for line in f.readlines()] + + def _load_metadata(self): + # Load metadata for hard positive verb phrases, hard negative queries + if 'refined' in self.metric_mode or 'hardneg' in self.metric_mode : + hardpos_path = os.path.join(self.ROOT, 'hardpos_verdict_gref_v4.json') + else : + hardpos_path = os.path.join(self.ROOT, 'hardpos_verbphrase_0906upd.json') + # do not use hardneg_path + hardneg_path = os.path.join(self.ROOT, 'hardneg_verb.json') + + with open(hardpos_path, 'r', encoding='utf-8') as f: + hardpos_json = json.load(f) + if "hardpos_only" in self.metric_mode : + hardneg_json = None + else : + with open(hardneg_path, 'r', encoding='utf-8') as q: + hardneg_json = json.load(q) + return hardpos_json, hardneg_json + + + def _get_hardpos_verb(self, ref, seg_id, sent_idx) : + if seg_id in self.multi_obj_ref_ids: + return '' + + # Extract metadata for hard positives if present + hardpos_dict = self.hardpos_meta.get(str(seg_id), {}) + if self.hp_selection == 'strict' : + sent_id_list = list(hardpos_dict.keys()) + cur_hardpos = hardpos_dict.get(sent_id_list[sent_idx], {}).get('phrases', []) + else : + cur_hardpos = list(itertools.chain.from_iterable(hardpos_dict[sid]['phrases'] for sid in hardpos_dict)) + + if cur_hardpos: + # Assign a hard positive verb phrase if available + raw_verb = random.choice(cur_hardpos) + return raw_verb + + return '' + + + def get_classes(self): + return self.classes + + def __len__(self): + return len(self.ref_ids) + + def __getitem__(self, index): + this_ref_id = self.ref_ids[index] + this_img_id = self.refer.getImgIds(this_ref_id) + this_img = self.refer.Imgs[this_img_id[0]] + + IMAGE_DIR = '/data2/dataset/COCO2014/trainval2014/' + img = Image.open(os.path.join(IMAGE_DIR, this_img['file_name'])).convert("RGB") + ref = self.refer.loadRefs(this_ref_id) + + ref_mask = np.array(self.refer.getMask(ref[0])['mask']) + annot = np.zeros(ref_mask.shape) + annot[ref_mask == 1] = 1 + + annot = Image.fromarray(annot.astype(np.uint8), mode="P") + + if self.image_transforms is not None: + # resize, from PIL to tensor, and mean and std normalization + img, target = self.image_transforms(img, annot) + + if self.eval_mode: + embedding = [] + att = [] + for s in range(len(self.input_ids[index])): + e = self.input_ids[index][s] + a = self.attention_masks[index][s] + embedding.append(e.unsqueeze(-1)) + att.append(a.unsqueeze(-1)) + + tensor_embeddings = torch.cat(embedding, dim=-1) + attention_mask = torch.cat(att, dim=-1) + + return img, target, tensor_embeddings, attention_mask + + else: # train phase + choice_sent = np.random.choice(len(self.input_ids[index])) + tensor_embeddings = self.input_ids[index][choice_sent] + attention_mask = self.attention_masks[index][choice_sent] + + if self.metric_learning: + pos_sent = torch.zeros_like(tensor_embeddings) + pos_attn_mask = torch.zeros_like(attention_mask) + + if 'hardpos_' in self.metric_mode or self.hardneg_prob == 0.0: + if 'refined' in self.metric_mode : + pos_sent_picked = self._get_hardpos_verb(ref, this_ref_id, choice_sent) + else : + pos_sents = self.hardpos_meta[str(this_ref_id)].values() + # drop elements with none + pos_sents = [s for s in pos_sents if s is not None] + pos_sent_picked = random.choice(list(pos_sents)) + if pos_sent_picked: + pos_sent, pos_attn_mask = self._tokenize(pos_sent_picked) + + return img, target, tensor_embeddings, attention_mask, pos_sent, pos_attn_mask + else: + neg_sent = torch.zeros_like(tensor_embeddings) + neg_attn_mask = torch.zeros_like(attention_mask) + + pos_sents = self.hardpos_meta[str(this_ref_id)].values() + # drop elements with none + pos_sents = [s for s in pos_sents if s is not None] + pos_sent_picked = random.choice(list(pos_sents)) + + if pos_sent_picked: + pos_sent, pos_attn_mask = self._tokenize(pos_sent_picked) + + if random.random() < self.hardneg_prob: + neg_sents = self.hardneg_meta[str(this_ref_id)].values() + neg_sents = [s for s in neg_sents if s is not None] + neg_sent_picked = random.choice(list(neg_sents)) + #print("neg_sent: ", neg_sent) + + if neg_sent_picked: + neg_sent, neg_attn_mask = self._tokenize(neg_sent_picked) + + return img, target, tensor_embeddings, attention_mask, pos_sent, pos_attn_mask, neg_sent, neg_attn_mask diff --git a/LAVT-RIS/data/dataset_refer_zom.py b/LAVT-RIS/data/dataset_refer_zom.py new file mode 100644 index 0000000000000000000000000000000000000000..793278e8c3d35a22fff42c34af7d189819c51d6b --- /dev/null +++ b/LAVT-RIS/data/dataset_refer_zom.py @@ -0,0 +1,296 @@ +import os +import sys +import json +import torch.utils.data as data +import torch +import itertools +import numpy as np +from PIL import Image +import pdb +import copy +from random import choice +from bert.tokenization_bert import BertTokenizer + +from refer.refer_zom import ZREFER +import copy +import random +import torch +from collections import defaultdict + +import torch +import torch.distributed as dist +from torch.utils.data.distributed import DistributedSampler + +from args import get_parser +import random +# Dataset configuration initialization +parser = get_parser() +args = parser.parse_args() + + +class Referzom_Dataset(data.Dataset): + + def __init__(self, + args, + image_transforms=None, + target_transforms=None, + split='train', + eval_mode=False): + + self.classes = [] + self.image_transforms = image_transforms + self.target_transform = target_transforms + self.split = split + self.refer = ZREFER(args.refer_data_root, args.dataset, args.splitBy) + self.dataset_type = args.dataset + self.max_tokens = 20 + ref_ids = self.refer.getRefIds(split=self.split) + self.img_ids = self.refer.getImgIds(ref_ids) + + all_imgs = self.refer.Imgs + self.imgs = list(all_imgs[i] for i in self.img_ids) + self.ref_ids = ref_ids + + self.input_ids = [] + self.attention_masks = [] + self.tokenizer = BertTokenizer.from_pretrained(args.bert_tokenizer) + + self.ROOT = '/data2/dataset/RefCOCO/VRIS' + self.metric_learning = args.metric_learning + self.exclude_multiobj = args.exclude_multiobj + self.metric_mode = args.metric_mode + self.exclude_position = False + + if self.metric_learning and eval_mode == False: + self.hardneg_prob = args.hn_prob + self.multi_obj_ref_ids = self._load_multi_obj_ref_ids() + self.hardpos_meta, self.hardneg_meta = self._load_metadata() + else: + self.hardneg_prob = 0.0 + self.multi_obj_ref_ids = None + self.hardpos_meta, self.hardneg_meta = None, None + + self.eval_mode = eval_mode + + self.zero_sent_id_list = [] + self.one_sent_id_list = [] + self.all_sent_id_list = [] + self.sent_2_refid = {} + + + for r in ref_ids: + ref = self.refer.loadRefs(r) + source_type = ref[0]['source'] + + for sent_dict in ref[0]['sentences']: + sent_id = sent_dict['sent_id'] + + self.sent_2_refid[sent_id] = r + self.all_sent_id_list.append(sent_id) + if source_type=='zero': + self.zero_sent_id_list.append(sent_id) + else: + self.one_sent_id_list.append(sent_id) + + for r in ref_ids: + ref = self.refer.Refs[r] + + sentences_for_ref = [] + attentions_for_ref = [] + + for i, el in enumerate(ref['sentences']): + sentence_raw = el['raw'] + attention_mask = [0] * self.max_tokens + padded_input_ids = [0] * self.max_tokens + + input_ids = self.tokenizer.encode(text=sentence_raw, add_special_tokens=True) + + # truncation of tokens + input_ids = input_ids[:self.max_tokens] + + padded_input_ids[:len(input_ids)] = input_ids + attention_mask[:len(input_ids)] = [1]*len(input_ids) + + sentences_for_ref.append(torch.tensor(padded_input_ids).unsqueeze(0)) + attentions_for_ref.append(torch.tensor(attention_mask).unsqueeze(0)) + + self.input_ids.extend(sentences_for_ref) + self.attention_masks.extend(attentions_for_ref) + + + def get_classes(self): + return self.classes + + + def _tokenize(self, sentence): + attention_mask = [0] * self.max_tokens + padded_input_ids = [0] * self.max_tokens + + input_ids = self.tokenizer.encode(text=sentence, add_special_tokens=True) + # truncation of tokens + input_ids = input_ids[:self.max_tokens] + padded_input_ids[:len(input_ids)] = input_ids + attention_mask[:len(input_ids)] = [1]*len(input_ids) + + # match shape as (1, max_tokens) + return torch.tensor(padded_input_ids).unsqueeze(0), torch.tensor(attention_mask).unsqueeze(0) + + def _load_multi_obj_ref_ids(self): + # Load multi-object reference IDs based on configurations + if not self.exclude_multiobj and not self.exclude_position : + return None + elif self.exclude_position: + multiobj_path = os.path.join(self.ROOT, 'multiobj_ov2_nopos.txt') + elif self.exclude_multiobj : + multiobj_path = os.path.join(self.ROOT, 'multiobj_ov3.txt') + with open(multiobj_path, 'r') as f: + return [int(line.strip()) for line in f.readlines()] + + def _load_metadata(self): + hardpos_path = os.path.join(self.ROOT, 'verb_ext_text_example_refzom.json') + with open(hardpos_path, 'r', encoding='utf-8') as f: + hardpos_json = json.load(f) + if "hardpos_only" in self.metric_mode : + hardneg_json = None + # else : + # hardneg_path = os.path.join(self.ROOT, 'hardneg_verb.json') + # with open(hardneg_path, 'r', encoding='utf-8') as q: + # hardneg_json = json.load(q) + return hardpos_json, hardneg_json + + + def _get_hardpos_verb(self, ref, seg_id, sent_idx) : + if seg_id in self.multi_obj_ref_ids: + return '' + + # Extract metadata for hard positives if present + hardpos_dict = self.hardpos_meta.get(str(seg_id), {}) + if self.hp_selection == 'strict' : + sent_id_list = list(hardpos_dict.keys()) + cur_hardpos = hardpos_dict.get(sent_id_list[sent_idx], {}).get('phrases', []) + else : + cur_hardpos = list(itertools.chain.from_iterable(hardpos_dict[sid]['phrases'] for sid in hardpos_dict)) + + if cur_hardpos: + # Assign a hard positive verb phrase if available + raw_verb = random.choice(cur_hardpos) + return raw_verb + + return '' + + def __len__(self): + return len(self.all_sent_id_list) + + def __getitem__(self, index): + + sent_id = self.all_sent_id_list[index] + this_ref_id = self.sent_2_refid[sent_id] + + this_img_id = self.refer.getImgIds(this_ref_id) + this_img = self.refer.Imgs[this_img_id[0]] + + IMAGE_DIR = '/data2/dataset/COCO2014/trainval2014/' + img = Image.open(os.path.join(IMAGE_DIR, this_img['file_name'])).convert("RGB") + + ref = self.refer.loadRefs(this_ref_id) + if self.dataset_type == 'ref-zom': + source_type = ref[0]['source'] + else: + source_type = 'not_zero' + + ref_mask = np.array(self.refer.getMask(ref[0])['mask']) + annot = np.zeros(ref_mask.shape) + annot[ref_mask == 1] = 1 + annot = Image.fromarray(annot.astype(np.uint8), mode="P") + + + if self.image_transforms is not None: + img, target = self.image_transforms(img, annot) + + if self.eval_mode: + embedding = [] + att = [] + for s in range(len(self.input_ids[index])): + padded_input_ids = self.input_ids[index][s] + attention_mask = self.attention_masks[index][s] + + embedding.append(padded_input_ids.unsqueeze(-1)) + att.append(attention_mask.unsqueeze(-1)) + + tensor_embeddings = torch.cat(embedding, dim=-1) + attention_mask = torch.cat(att, dim=-1) + return img, target, source_type, tensor_embeddings, attention_mask + + else: + choice_sent = np.random.choice(len(self.input_ids[index])) + tensor_embeddings = self.input_ids[index][choice_sent] + attention_mask = self.attention_masks[index][choice_sent] + + if self.metric_learning : + pos_sent = torch.zeros_like(tensor_embeddings) + pos_attn_mask = torch.zeros_like(attention_mask) + + ## Only the case with hardpos_ in metric_mode + if 'hardpos_' in self.metric_mode or self.hardneg_prob == 0.0: + pos_type = 'zero' + if 'refined' in self.metric_mode : + pos_sent_picked = self._get_hardpos_verb(ref, this_ref_id, choice_sent) + else : + pos_sents = self.hardpos_meta[str(this_ref_id)].values() + # drop elements with none + pos_sents = [s for s in pos_sents if s is not None] + pos_sent_picked = random.choice(list(pos_sents)) + if pos_sent_picked : + pos_type = 'hardpos' + pos_sent, pos_attn_mask = self._tokenize(pos_sent_picked) + pos_sent = pos_sent.squeeze(0) if pos_sent.dim() == 2 and pos_sent.size(0) == 1 else pos_sent + pos_attn_mask = pos_attn_mask.squeeze(0) if pos_attn_mask.size(0) == 1 else pos_attn_mask + + return img, target, source_type, tensor_embeddings, attention_mask, pos_sent, pos_attn_mask, pos_type + + return img, target, source_type, tensor_embeddings, attention_mask + + + + +class Refzom_DistributedSampler(DistributedSampler): + def __init__(self, dataset, num_replicas=None, rank=None, shuffle=True): + super().__init__(dataset, num_replicas=num_replicas, rank=rank, shuffle=shuffle) + self.one_id_list = dataset.one_sent_id_list + + self.zero_id_list = dataset.zero_sent_id_list + self.sent_ids_list = dataset.all_sent_id_list + if self.shuffle==True: + random.shuffle(self.one_id_list) + random.shuffle(self.zero_id_list) + + self.sent_id = self.insert_evenly(self.zero_id_list,self.one_id_list) + self.indices = self.get_positions(self.sent_ids_list, self.sent_id) + + def get_positions(self, list_a, list_b): + position_dict = {value: index for index, value in enumerate(list_a)} + positions = [position_dict[item] for item in list_b] + + return positions + + def insert_evenly(self, list_a, list_b): + len_a = len(list_a) + len_b = len(list_b) + block_size = len_b // len_a + + result = [] + for i in range(len_a): + start = i * block_size + end = (i + 1) * block_size + result.extend(list_b[start:end]) + result.append(list_a[i]) + + remaining = list_b[(len_a * block_size):] + result.extend(remaining) + + return result + + def __iter__(self): + + indices_per_process = self.indices[self.rank::self.num_replicas] + return iter(indices_per_process) \ No newline at end of file diff --git a/LAVT-RIS/datagen.txt b/LAVT-RIS/datagen.txt new file mode 100644 index 0000000000000000000000000000000000000000..6ef7109935e30b04a9d1fa230b1d4a0aaeea17b1 --- /dev/null +++ b/LAVT-RIS/datagen.txt @@ -0,0 +1,49 @@ +[I 2024-12-15 13:30:17.641 ServerApp] jupyter_lsp | extension was successfully linked. +[I 2024-12-15 13:30:17.652 ServerApp] jupyter_server_terminals | extension was successfully linked. +[I 2024-12-15 13:30:17.663 ServerApp] jupyterlab | extension was successfully linked. +[W 2024-12-15 13:30:17.687 JupyterNotebookApp] 'password' has moved from NotebookApp to ServerApp. This config will be passed to ServerApp. Be sure to update your config before our next release. +[W 2024-12-15 13:30:17.690 ServerApp] ServerApp.password config is deprecated in 2.0. 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(orig_h, orig_w, 3); for visualization +original_w, original_h = img.size # PIL .size returns width first and height second + +image_transforms = T.Compose( + [ + T.Resize(480), + T.ToTensor(), + T.Normalize(mean=[0.485, 0.456, 0.406], std=[0.229, 0.224, 0.225]) + ] +) + +img = image_transforms(img).unsqueeze(0) # (1, 3, 480, 480) +img = img.to(device) # for inference (input) + +# pre-process the raw sentence +from bert.tokenization_bert import BertTokenizer +import torch +tokenizer = BertTokenizer.from_pretrained('bert-base-uncased') +sentence_tokenized = tokenizer.encode(text=sentence, add_special_tokens=True) +sentence_tokenized = sentence_tokenized[:20] # if the sentence is longer than 20, then this truncates it to 20 words +# pad the tokenized sentence +padded_sent_toks = [0] * 20 +padded_sent_toks[:len(sentence_tokenized)] = sentence_tokenized +# create a sentence token mask: 1 for real words; 0 for padded tokens +attention_mask = [0] * 20 +attention_mask[:len(sentence_tokenized)] = [1]*len(sentence_tokenized) +# convert lists to tensors +padded_sent_toks = torch.tensor(padded_sent_toks).unsqueeze(0) # (1, 20) +attention_mask = torch.tensor(attention_mask).unsqueeze(0) # (1, 20) +padded_sent_toks = padded_sent_toks.to(device) # for inference (input) +attention_mask = attention_mask.to(device) # for inference (input) + +# initialize model and load weights +from bert.modeling_bert import BertModel +from lib import segmentation + +# construct a mini args class; like from a config file + + +class args: + swin_type = 'base' + window12 = True + mha = '' + fusion_drop = 0.0 + + +single_model = segmentation.__dict__['lavt'](pretrained='', args=args) +single_model.to(device) +model_class = BertModel +single_bert_model = model_class.from_pretrained('bert-base-uncased') +single_bert_model.pooler = None + +checkpoint = torch.load(weights, map_location='cpu') +single_bert_model.load_state_dict(checkpoint['bert_model']) +single_model.load_state_dict(checkpoint['model']) +model = single_model.to(device) +bert_model = single_bert_model.to(device) + + +# inference +import torch.nn.functional as F +last_hidden_states = bert_model(padded_sent_toks, attention_mask=attention_mask)[0] +embedding = last_hidden_states.permute(0, 2, 1) +output = model(img, embedding, l_mask=attention_mask.unsqueeze(-1)) +output = output.argmax(1, keepdim=True) # (1, 1, 480, 480) +output = F.interpolate(output.float(), (original_h, original_w)) # 'nearest'; resize to the original image size +output = output.squeeze() # (orig_h, orig_w) +output = output.cpu().data.numpy() # (orig_h, orig_w) + + +# show/save results +def overlay_davis(image, mask, colors=[[0, 0, 0], [255, 0, 0]], cscale=1, alpha=0.4): + from scipy.ndimage.morphology import binary_dilation + + colors = np.reshape(colors, (-1, 3)) + colors = np.atleast_2d(colors) * cscale + + im_overlay = image.copy() + object_ids = np.unique(mask) + + for object_id in object_ids[1:]: + # Overlay color on binary mask + foreground = image*alpha + np.ones(image.shape)*(1-alpha) * np.array(colors[object_id]) + binary_mask = mask == object_id + + # Compose image + im_overlay[binary_mask] = foreground[binary_mask] + + # countours = skimage.morphology.binary.binary_dilation(binary_mask) - binary_mask + countours = binary_dilation(binary_mask) ^ binary_mask + # countours = cv2.dilate(binary_mask, cv2.getStructuringElement(cv2.MORPH_CROSS,(3,3))) - binary_mask + im_overlay[countours, :] = 0 + + return im_overlay.astype(image.dtype) + + +output = output.astype(np.uint8) # (orig_h, orig_w), np.uint8 +# Overlay the mask on the image +visualization = overlay_davis(img_ndarray, output) # red +visualization = Image.fromarray(visualization) +# show the visualization +#visualization.show() +# Save the visualization +visualization.save('./demo/demo_result.jpg') + + + + diff --git a/LAVT-RIS/donghwa/args.py b/LAVT-RIS/donghwa/args.py new file mode 100644 index 0000000000000000000000000000000000000000..fb0c6c477b160531189df7a1f1d62dc43485cbfa --- /dev/null +++ b/LAVT-RIS/donghwa/args.py @@ -0,0 +1,212 @@ +import argparse + + +def get_parser(): + parser = argparse.ArgumentParser(description='LAVT training and testing') + parser.add_argument('--amsgrad', action='store_true', + help='if true, set amsgrad to True in an Adam or AdamW optimizer.') + parser.add_argument('-b', '--batch-size', default=8, type=int) + parser.add_argument('--bert_tokenizer', default='bert-base-uncased', help='BERT tokenizer') + parser.add_argument('--ck_bert', default='bert-base-uncased', help='pre-trained BERT weights') + parser.add_argument('--dataset', default='refcoco', help='refcoco, refcoco+, or refcocog') + parser.add_argument('--ddp_trained_weights', action='store_true', + help='Only needs specified when testing,' + 'whether the weights to be loaded are from a DDP-trained model') + parser.add_argument('--device', default='cuda:0', help='device') # only used when testing on a single machine + parser.add_argument('--epochs', default=40, type=int, metavar='N', help='number of total epochs to run') + parser.add_argument('--fusion_drop', default=0.0, type=float, help='dropout rate for PWAMs') + parser.add_argument('--img_size', default=480, type=int, help='input image size') + parser.add_argument("--local_rank", type=int, help='local rank for DistributedDataParallel') + parser.add_argument('--lr', default=0.00005, type=float, help='the initial learning rate') + parser.add_argument('--mha', default='', help='If specified, should be in the format of a-b-c-d, e.g., 4-4-4-4,' + 'where a, b, c, and d refer to the numbers of heads in stage-1,' + 'stage-2, stage-3, and stage-4 PWAMs') + parser.add_argument('--model', default='lavt', help='model: lavt, lavt_one') + parser.add_argument('--model_id', default='lavt', help='name to identify the model') + parser.add_argument('--output-dir', default='./checkpoints/', help='path where to save checkpoint weights') + parser.add_argument('--pin_mem', action='store_true', + help='If true, pin memory when using the data loader.') + parser.add_argument('--pretrained_swin_weights', default='', + help='path to pre-trained Swin backbone weights') + parser.add_argument('--print-freq', default=10, type=int, help='print frequency') + parser.add_argument('--refer_data_root', default='./refer/data/', help='REFER dataset root directory') + parser.add_argument('--resume', default='', help='resume from checkpoint') + parser.add_argument('--split', default='test', help='only used when testing') + parser.add_argument('--splitBy', default='unc', help='change to umd or google when the dataset is G-Ref (RefCOCOg)') + parser.add_argument('--swin_type', default='base', + help='tiny, small, base, or large variants of the Swin Transformer') + parser.add_argument('--wd', '--weight-decay', default=1e-2, type=float, metavar='W', help='weight decay', + dest='weight_decay') + parser.add_argument('--window12', action='store_true', + help='only needs specified when testing,' + 'when training, window size is inferred from pre-trained weights file name' + '(containing \'window12\'). Initialize Swin with window size 12 instead of the default 7.') + parser.add_argument('-j', '--workers', default=8, type=int, metavar='N', help='number of data loading workers') + parser.add_argument('--config', + default='path to xxx.yaml', + type=str, + help='config file') + return parser + +# ----------------------------------------------------------------------------- +# Functions for parsing args +# ----------------------------------------------------------------------------- +import copy +import os +from ast import literal_eval + +import yaml + + +class CfgNode(dict): + """ + CfgNode represents an internal node in the configuration tree. It's a simple + dict-like container that allows for attribute-based access to keys. + """ + def __init__(self, init_dict=None, key_list=None, new_allowed=False): + # Recursively convert nested dictionaries in init_dict into CfgNodes + init_dict = {} if init_dict is None else init_dict + key_list = [] if key_list is None else key_list + for k, v in init_dict.items(): + if type(v) is dict: + # Convert dict to CfgNode + init_dict[k] = CfgNode(v, key_list=key_list + [k]) + super(CfgNode, self).__init__(init_dict) + + def __getattr__(self, name): + if name in self: + return self[name] + else: + raise AttributeError(name) + + def __setattr__(self, name, value): + self[name] = value + + def __str__(self): + def _indent(s_, num_spaces): + s = s_.split("\n") + if len(s) == 1: + return s_ + first = s.pop(0) + s = [(num_spaces * " ") + line for line in s] + s = "\n".join(s) + s = first + "\n" + s + return s + + r = "" + s = [] + for k, v in sorted(self.items()): + seperator = "\n" if isinstance(v, CfgNode) else " " + attr_str = "{}:{}{}".format(str(k), seperator, str(v)) + attr_str = _indent(attr_str, 2) + s.append(attr_str) + r += "\n".join(s) + return r + + def __repr__(self): + return "{}({})".format(self.__class__.__name__, + super(CfgNode, self).__repr__()) + + +def load_cfg_from_cfg_file(file): + cfg = {} + assert os.path.isfile(file) and file.endswith('.yaml'), \ + '{} is not a yaml file'.format(file) + + with open(file, 'r') as f: + cfg_from_file = yaml.safe_load(f) + + for key in cfg_from_file: + for k, v in cfg_from_file[key].items(): + cfg[k] = v + + cfg = CfgNode(cfg) + return cfg + + +def merge_cfg_from_list(cfg, cfg_list): + new_cfg = copy.deepcopy(cfg) + assert len(cfg_list) % 2 == 0 + for full_key, v in zip(cfg_list[0::2], cfg_list[1::2]): + subkey = full_key.split('.')[-1] + assert subkey in cfg, 'Non-existent key: {}'.format(full_key) + value = _decode_cfg_value(v) + value = _check_and_coerce_cfg_value_type(value, cfg[subkey], subkey, + full_key) + setattr(new_cfg, subkey, value) + + return new_cfg + + +def _decode_cfg_value(v): + """Decodes a raw config value (e.g., from a yaml config files or command + line argument) into a Python object. + """ + # All remaining processing is only applied to strings + if not isinstance(v, str): + return v + # Try to interpret `v` as a: + # string, number, tuple, list, dict, boolean, or None + try: + v = literal_eval(v) + # The following two excepts allow v to pass through when it represents a + # string. + # + # Longer explanation: + # The type of v is always a string (before calling literal_eval), but + # sometimes it *represents* a string and other times a data structure, like + # a list. In the case that v represents a string, what we got back from the + # yaml parser is 'foo' *without quotes* (so, not '"foo"'). literal_eval is + # ok with '"foo"', but will raise a ValueError if given 'foo'. In other + # cases, like paths (v = 'foo/bar' and not v = '"foo/bar"'), literal_eval + # will raise a SyntaxError. + except ValueError: + pass + except SyntaxError: + pass + return v + + +def _check_and_coerce_cfg_value_type(replacement, original, key, full_key): + """Checks that `replacement`, which is intended to replace `original` is of + the right type. The type is correct if it matches exactly or is one of a few + cases in which the type can be easily coerced. + """ + original_type = type(original) + replacement_type = type(replacement) + + # The types must match (with some exceptions) + if replacement_type == original_type: + return replacement + + # Cast replacement from from_type to to_type if the replacement and original + # types match from_type and to_type + def conditional_cast(from_type, to_type): + if replacement_type == from_type and original_type == to_type: + return True, to_type(replacement) + else: + return False, None + + # Conditionally casts + # list <-> tuple + casts = [(tuple, list), (list, tuple)] + # For py2: allow converting from str (bytes) to a unicode string + try: + casts.append((str, unicode)) # noqa: F821 + except Exception: + pass + + for (from_type, to_type) in casts: + converted, converted_value = conditional_cast(from_type, to_type) + if converted: + return converted_value + + raise ValueError( + "Type mismatch ({} vs. {}) with values ({} vs. {}) for config " + "key: {}".format(original_type, replacement_type, original, + replacement, full_key)) + + +if __name__ == "__main__": + parser = get_parser() + args_dict = parser.parse_args() diff --git a/LAVT-RIS/donghwa/config/__pycache__/utils.cpython-37.pyc b/LAVT-RIS/donghwa/config/__pycache__/utils.cpython-37.pyc new file mode 100644 index 0000000000000000000000000000000000000000..acbe42dde2e9527a0f752fbe0f4a064439fe320d Binary files /dev/null and b/LAVT-RIS/donghwa/config/__pycache__/utils.cpython-37.pyc differ diff --git a/LAVT-RIS/donghwa/config/n_obj/n_12.yaml b/LAVT-RIS/donghwa/config/n_obj/n_12.yaml new file mode 100644 index 0000000000000000000000000000000000000000..e4cec3fbdc0bd85a0a322f7ab48995d4410e6082 --- /dev/null +++ b/LAVT-RIS/donghwa/config/n_obj/n_12.yaml @@ -0,0 +1 @@ +n_obj_bin : n_12 \ No newline at end of file diff --git a/LAVT-RIS/donghwa/config/n_obj/n_34.yaml b/LAVT-RIS/donghwa/config/n_obj/n_34.yaml new file mode 100644 index 0000000000000000000000000000000000000000..d6300f9d989b2183f55b7b6f8d443ef5e4b05630 --- /dev/null +++ b/LAVT-RIS/donghwa/config/n_obj/n_34.yaml @@ -0,0 +1 @@ +n_obj_bin : n_34 \ No newline at end of file diff --git a/LAVT-RIS/donghwa/config/n_obj/n_56.yaml b/LAVT-RIS/donghwa/config/n_obj/n_56.yaml new file mode 100644 index 0000000000000000000000000000000000000000..6da47433f19c83762cad936434070f7598609531 --- /dev/null +++ b/LAVT-RIS/donghwa/config/n_obj/n_56.yaml @@ -0,0 +1 @@ +n_obj_bin : n_56 \ No newline at end of file diff --git a/LAVT-RIS/donghwa/config/n_obj/n_78.yaml b/LAVT-RIS/donghwa/config/n_obj/n_78.yaml new file mode 100644 index 0000000000000000000000000000000000000000..5aac0cf7c4c0bebaed4ab9c52024ce92614c18d1 --- /dev/null +++ b/LAVT-RIS/donghwa/config/n_obj/n_78.yaml @@ -0,0 +1 @@ +n_obj_bin : n_78 \ No newline at end of file diff --git a/LAVT-RIS/donghwa/config/random_460.yaml b/LAVT-RIS/donghwa/config/random_460.yaml new file mode 100644 index 0000000000000000000000000000000000000000..b6373f114ffaa5c27bf8fdaf56651e45b51331a0 --- /dev/null +++ b/LAVT-RIS/donghwa/config/random_460.yaml @@ -0,0 +1,11 @@ +aug: + num_bgs : 4 + aug_prob : 0.6 + num_anchors : 0 + random_target : False + blur : False + feature_path : None + lower : 0 + upper : 100 + move_crs_pnt : False + tgt_selection : 'fixed' \ No newline at end of file diff --git a/LAVT-RIS/donghwa/config/random_550.yaml b/LAVT-RIS/donghwa/config/random_550.yaml new file mode 100644 index 0000000000000000000000000000000000000000..025b39b5fef316284113eefe7ee5822ce1af1e76 --- /dev/null +++ b/LAVT-RIS/donghwa/config/random_550.yaml @@ -0,0 +1,11 @@ +aug: + num_bgs : 4 + aug_prob : 0.5 + num_anchors : 0 + random_target : False + blur : False + feature_path : None + lower : 0 + upper : 100 + move_crs_pnt : False + tgt_selection : 'fixed' \ No newline at end of file diff --git a/LAVT-RIS/donghwa/config/retrieval_424_10up.yaml b/LAVT-RIS/donghwa/config/retrieval_424_10up.yaml new file mode 100644 index 0000000000000000000000000000000000000000..d413de904f451d8022774dddad510916d8c734da --- /dev/null +++ b/LAVT-RIS/donghwa/config/retrieval_424_10up.yaml @@ -0,0 +1,12 @@ +aug : + num_bgs : 4 + aug_prob : 0.6 + retr_prob : 0.4 + rand_prob : 0.2 + blur : False + move_crs_pnt : False + tgt_selection : 'fixed' + retrieval_epoch : 10 + sim_thres : 0.76594 + top_k : 200 + \ No newline at end of file diff --git a/LAVT-RIS/donghwa/config/retrieval_433_0up.yaml b/LAVT-RIS/donghwa/config/retrieval_433_0up.yaml new file mode 100644 index 0000000000000000000000000000000000000000..fc38fad140db37d9f33a5645f69890d3bad66dcf --- /dev/null +++ b/LAVT-RIS/donghwa/config/retrieval_433_0up.yaml @@ -0,0 +1,12 @@ +aug : + num_bgs : 4 + aug_prob : 0.6 + retr_prob : 0.3 + rand_prob : 0.3 + blur : False + move_crs_pnt : False + tgt_selection : 'fixed' + retrieval_epoch : 0 + sim_thres : 0.76594 + top_k : 200 + \ No newline at end of file diff --git a/LAVT-RIS/donghwa/config/retrieval_433_10up.yaml b/LAVT-RIS/donghwa/config/retrieval_433_10up.yaml new file mode 100644 index 0000000000000000000000000000000000000000..668f7e192cfcd58b9e04af9343d1c01d1fcb1776 --- /dev/null +++ b/LAVT-RIS/donghwa/config/retrieval_433_10up.yaml @@ -0,0 +1,11 @@ +aug : + num_bgs : 4 + aug_prob : 0.6 + retr_prob : 0.3 + rand_prob : 0.3 + blur : False + move_crs_pnt : False + tgt_selection : 'fixed' + retrieval_epoch : 10 + sim_thres : 0.76594 + top_k : 200 \ No newline at end of file diff --git a/LAVT-RIS/donghwa/config/retrieval_433_10wm6to3.yaml b/LAVT-RIS/donghwa/config/retrieval_433_10wm6to3.yaml new file mode 100644 index 0000000000000000000000000000000000000000..d11ed13715d6696ed3edd7521f91b311b2da5502 --- /dev/null +++ b/LAVT-RIS/donghwa/config/retrieval_433_10wm6to3.yaml @@ -0,0 +1,11 @@ +aug : + num_bgs : 4 + aug_prob : 0.6 + retr_prob : 0.3 + blur : False + move_crs_pnt : False + tgt_selection : 'fixed' + warmup_epoch : 10 + sim_thres : 0.76594 + top_k : 200 + \ No newline at end of file diff --git a/LAVT-RIS/donghwa/config/retrieval_522_10up.yaml b/LAVT-RIS/donghwa/config/retrieval_522_10up.yaml new file mode 100644 index 0000000000000000000000000000000000000000..0126a205639da6178a973ddd6ff3e32258d2cbde --- /dev/null +++ b/LAVT-RIS/donghwa/config/retrieval_522_10up.yaml @@ -0,0 +1,12 @@ +aug : + num_bgs : 4 + aug_prob : 0.5 + retr_prob : 0.25 + rand_prob : 0.25 + blur : False + move_crs_pnt : False + tgt_selection : 'fixed' + retrieval_epoch : 10 + sim_thres : 0.76594 + top_k : 200 + \ No newline at end of file diff --git a/LAVT-RIS/donghwa/config/sent_len/sent_len_11_20.yaml b/LAVT-RIS/donghwa/config/sent_len/sent_len_11_20.yaml new file mode 100644 index 0000000000000000000000000000000000000000..06ec47b0a64f801bdaa2a79e615871bc8678e5a3 --- /dev/null +++ b/LAVT-RIS/donghwa/config/sent_len/sent_len_11_20.yaml @@ -0,0 +1,3 @@ +sent_len : + min : 11 + max : 100000 diff --git a/LAVT-RIS/donghwa/config/sent_len/sent_len_1_5.yaml b/LAVT-RIS/donghwa/config/sent_len/sent_len_1_5.yaml new file mode 100644 index 0000000000000000000000000000000000000000..5b6bf562de49ad761654cc2ccf30a7e822870847 --- /dev/null +++ b/LAVT-RIS/donghwa/config/sent_len/sent_len_1_5.yaml @@ -0,0 +1,3 @@ +sent_len : + min : 1 + max : 5 diff --git a/LAVT-RIS/donghwa/config/sent_len/sent_len_6_7.yaml b/LAVT-RIS/donghwa/config/sent_len/sent_len_6_7.yaml new file mode 100644 index 0000000000000000000000000000000000000000..314dcbe5bd3bd57968fef6bb271c44dc5e21c331 --- /dev/null +++ b/LAVT-RIS/donghwa/config/sent_len/sent_len_6_7.yaml @@ -0,0 +1,3 @@ +sent_len : + min : 6 + max : 7 diff --git a/LAVT-RIS/donghwa/config/sent_len/sent_len_8_10.yaml b/LAVT-RIS/donghwa/config/sent_len/sent_len_8_10.yaml new file mode 100644 index 0000000000000000000000000000000000000000..130540393e81f8187dd0ef62e4bb20153d260db2 --- /dev/null +++ b/LAVT-RIS/donghwa/config/sent_len/sent_len_8_10.yaml @@ -0,0 +1,3 @@ +sent_len : + min : 8 + max : 10 diff --git a/LAVT-RIS/donghwa/config/utils.py b/LAVT-RIS/donghwa/config/utils.py new file mode 100644 index 0000000000000000000000000000000000000000..e42704dcba2fb2f751fec413551a5069e63f25c9 --- /dev/null +++ b/LAVT-RIS/donghwa/config/utils.py @@ -0,0 +1,153 @@ +# Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved. +# Copy from fvcore + +import logging +import os +from typing import Any +import yaml +from yacs.config import CfgNode as _CfgNode + +import io as PathManager + +BASE_KEY = "_BASE_" + + +class CfgNode(_CfgNode): + """ + Our own extended version of :class:`yacs.config.CfgNode`. + It contains the following extra features: + + 1. The :meth:`merge_from_file` method supports the "_BASE_" key, + which allows the new CfgNode to inherit all the attributes from the + base configuration file. + 2. Keys that start with "COMPUTED_" are treated as insertion-only + "computed" attributes. They can be inserted regardless of whether + the CfgNode is frozen or not. + 3. With "allow_unsafe=True", it supports pyyaml tags that evaluate + expressions in config. See examples in + https://pyyaml.org/wiki/PyYAMLDocumentation#yaml-tags-and-python-types + Note that this may lead to arbitrary code execution: you must not + load a config file from untrusted sources before manually inspecting + the content of the file. + """ + + @staticmethod + def load_yaml_with_base(filename, allow_unsafe = False): + """ + Just like `yaml.load(open(filename))`, but inherit attributes from its + `_BASE_`. + + Args: + filename (str): the file name of the current config. Will be used to + find the base config file. + allow_unsafe (bool): whether to allow loading the config file with + `yaml.unsafe_load`. + + Returns: + (dict): the loaded yaml + """ + with PathManager.open(filename, "r") as f: + try: + cfg = yaml.safe_load(f) + except yaml.constructor.ConstructorError: + if not allow_unsafe: + raise + logger = logging.getLogger(__name__) + logger.warning( + "Loading config {} with yaml.unsafe_load. Your machine may " + "be at risk if the file contains malicious content.".format( + filename + ) + ) + f.close() + with open(filename, "r") as f: + cfg = yaml.unsafe_load(f) + + def merge_a_into_b(a, b): + # merge dict a into dict b. values in a will overwrite b. + for k, v in a.items(): + if isinstance(v, dict) and k in b: + assert isinstance( + b[k], dict + ), "Cannot inherit key '{}' from base!".format(k) + merge_a_into_b(v, b[k]) + else: + b[k] = v + + if BASE_KEY in cfg: + base_cfg_file = cfg[BASE_KEY] + if base_cfg_file.startswith("~"): + base_cfg_file = os.path.expanduser(base_cfg_file) + if not any( + map(base_cfg_file.startswith, ["/", "https://", "http://"]) + ): + # the path to base cfg is relative to the config file itself. + base_cfg_file = os.path.join( + os.path.dirname(filename), base_cfg_file + ) + base_cfg = CfgNode.load_yaml_with_base( + base_cfg_file, allow_unsafe=allow_unsafe + ) + del cfg[BASE_KEY] + + merge_a_into_b(cfg, base_cfg) + return base_cfg + return cfg + + def merge_from_file(self, cfg_filename, allow_unsafe = False): + """ + Merge configs from a given yaml file. + + Args: + cfg_filename: the file name of the yaml config. + allow_unsafe: whether to allow loading the config file with + `yaml.unsafe_load`. + """ + loaded_cfg = CfgNode.load_yaml_with_base( + cfg_filename, allow_unsafe=allow_unsafe + ) + loaded_cfg = type(self)(loaded_cfg) + self.merge_from_other_cfg(loaded_cfg) + + # Forward the following calls to base, but with a check on the BASE_KEY. + def merge_from_other_cfg(self, cfg_other): + """ + Args: + cfg_other (CfgNode): configs to merge from. + """ + assert ( + BASE_KEY not in cfg_other + ), "The reserved key '{}' can only be used in files!".format(BASE_KEY) + return super().merge_from_other_cfg(cfg_other) + + def merge_from_list(self, cfg_list): + """ + Args: + cfg_list (list): list of configs to merge from. + """ + keys = set(cfg_list[0::2]) + assert ( + BASE_KEY not in keys + ), "The reserved key '{}' can only be used in files!".format(BASE_KEY) + return super().merge_from_list(cfg_list) + + def __setattr__(self, name, val): + if name.startswith("COMPUTED_"): + if name in self: + old_val = self[name] + if old_val == val: + return + raise KeyError( + "Computed attributed '{}' already exists " + "with a different value! old={}, new={}.".format( + name, old_val, val + ) + ) + self[name] = val + else: + super().__setattr__(name, val) + + +if __name__ == '__main__': + cfg = CfgNode.load_yaml_with_base('configs/updown_long.yml') + print(cfg) \ No newline at end of file diff --git a/LAVT-RIS/donghwa/dataset_grefer.py b/LAVT-RIS/donghwa/dataset_grefer.py new file mode 100644 index 0000000000000000000000000000000000000000..b7ece14a6658e7a1fb6f1d3c9e9e13d80fc1b901 --- /dev/null +++ b/LAVT-RIS/donghwa/dataset_grefer.py @@ -0,0 +1,296 @@ +import contextlib +import io +import logging +import numpy as np +import os +import random +import copy +import pycocotools.mask as mask_util +from fvcore.common.timer import Timer +from PIL import Image +import torch.utils.data as data + +from detectron2.structures import Boxes, BoxMode, PolygonMasks, RotatedBoxes +from detectron2.utils.file_io import PathManager + +import time +import copy +import logging +import torch + +from detectron2.config import configurable +from detectron2.data import detection_utils as utils +from detectron2.data import transforms as T + +# from transformers import BertTokenizer +from bert.tokenization_bert import BertTokenizer +from pycocotools import mask as coco_mask +from data.utils import convert_coco_poly_to_mask, build_transform_train, build_transform_test +""" +This file contains functions to parse RefCOCO-format annotations into dicts in "Detectron2 format". +""" + + +logger = logging.getLogger(__name__) + +__all__ = ["load_refcoco_json"] + +class GReferDataset(data.Dataset): + def __init__(self, + args, refer_root, dataset_name, splitby, split, image_root, + img_format="RGB", merge=True, + extra_annotation_keys=None, extra_refer_keys=None): + + self.refer_root = refer_root + self.dataset_name = dataset_name + self.splitby = splitby + self.split = split + self.image_root = image_root + self.extra_annotation_keys = extra_annotation_keys + self.extra_refer_keys = extra_refer_keys + self.img_format = img_format + self.merge = merge + self.max_tokens = 20 + self.tokenizer = BertTokenizer.from_pretrained(args.bert_tokenizer) + + if split == "train": + self.tfm_gens = build_transform_train(args) + elif split in ["val", "test", "testA", "testB"]: + self.tfm_gens = build_transform_test(args) + + if self.dataset_name == 'refcocop': + self.dataset_name = 'refcoco+' + if self.dataset_name == 'refcoco' or self.dataset_name == 'refcoco+': + self.splitby == 'unc' + if self.dataset_name == 'refcocog': + assert self.splitby == 'umd' or self.splitby == 'google' + + dataset_id = '_'.join([self.dataset_name, self.splitby, self.split]) + + from refer.grefer import G_REFER + logger.info('Loading dataset {} ({}-{}) ...'.format(self.dataset_name, self.splitby, self.split)) + logger.info('Refcoco root: {}'.format(self.refer_root)) + timer = Timer() + self.refer_root = PathManager.get_local_path(self.refer_root) + with contextlib.redirect_stdout(io.StringIO()): + refer_api = G_REFER(data_root=self.refer_root, + dataset=self.dataset_name, + splitBy=self.splitby) + if timer.seconds() > 1: + logger.info("Loading {} takes {:.2f} seconds.".format(dataset_id, timer.seconds())) + + self.ref_ids = refer_api.getRefIds(split=self.split) + self.img_ids = refer_api.getImgIds(self.ref_ids) + self.refs = refer_api.loadRefs(self.ref_ids) + imgs = [refer_api.loadImgs(ref['image_id'])[0] for ref in self.refs] + anns = [refer_api.loadAnns(ref['ann_id']) for ref in self.refs] + self.imgs_refs_anns = list(zip(imgs, self.refs, anns)) + + logger.info("Loaded {} images, {} referring object sets in G_RefCOCO format from {}".format(len(self.img_ids), len(self.ref_ids), dataset_id)) + + + self.dataset_dicts = [] + + ann_keys = ["iscrowd", "bbox", "category_id"] + (self.extra_annotation_keys or []) + ref_keys = ["raw", "sent_id"] + (self.extra_refer_keys or []) + + ann_lib = {} + + NT_count = 0 + MT_count = 0 + + for idx, (img_dict, ref_dict, anno_dicts) in enumerate(self.imgs_refs_anns): + record = {} + record['id'] = idx + record["source"] = 'grefcoco' + record["file_name"] = os.path.join(self.image_root, img_dict["file_name"]) + record["height"] = img_dict["height"] + record["width"] = img_dict["width"] + image_id = record["image_id"] = img_dict["id"] + + # Check that information of image, ann and ref match each other + # This fails only when the data parsing logic or the annotation file is buggy. + assert ref_dict['image_id'] == image_id + assert ref_dict['split'] == self.split + if not isinstance(ref_dict['ann_id'], list): + ref_dict['ann_id'] = [ref_dict['ann_id']] + + # No target samples + if None in anno_dicts: + assert anno_dicts == [None] + assert ref_dict['ann_id'] == [-1] + record['empty'] = True + obj = {key: None for key in ann_keys if key in ann_keys} + obj["bbox_mode"] = BoxMode.XYWH_ABS + obj["empty"] = True + obj = [obj] + + # Multi target samples + else: + record['empty'] = False + obj = [] + for anno_dict in anno_dicts: + ann_id = anno_dict['id'] + if anno_dict['iscrowd']: + continue + assert anno_dict["image_id"] == image_id + assert ann_id in ref_dict['ann_id'] + + if ann_id in ann_lib: + ann = ann_lib[ann_id] + else: + ann = {key: anno_dict[key] for key in ann_keys if key in anno_dict} + ann["bbox_mode"] = BoxMode.XYWH_ABS + ann["empty"] = False + + segm = anno_dict.get("segmentation", None) + assert segm # either list[list[float]] or dict(RLE) + if isinstance(segm, dict): + if isinstance(segm["counts"], list): + # convert to compressed RLE + segm = mask_util.frPyObjects(segm, *segm["size"]) + else: + # filter out invalid polygons (< 3 points) + segm = [poly for poly in segm if len(poly) % 2 == 0 and len(poly) >= 6] + if len(segm) == 0: + num_instances_without_valid_segmentation += 1 + continue # ignore this instance + ann["segmentation"] = segm + ann_lib[ann_id] = ann + + obj.append(ann) + + record["annotations"] = obj + + # Process referring expressions + sents = ref_dict['sentences'] + for sent in sents: + ref_record = record.copy() + ref = {key: sent[key] for key in ref_keys if key in sent} + ref["ref_id"] = ref_dict["ref_id"] + ref_record["sentence"] = ref + self.dataset_dicts.append(ref_record) + # if ref_record['empty']: + # NT_count += 1 + # else: + # MT_count += 1 + + # logger.info("NT samples: %d, MT samples: %d", NT_count, MT_count) + + # Debug mode + # return self.dataset_dicts[:100] + + @staticmethod + def _merge_masks(x): + return x.sum(dim=0, keepdim=True).clamp(max=1) + + + def __getitem__(self, index): + + dataset_dict = copy.deepcopy(self.dataset_dicts[index]) + # dataset_dict = copy.deepcopy(dataset_dict) # it will be modified by code below + image = utils.read_image(dataset_dict["file_name"], format=self.img_format) + utils.check_image_size(dataset_dict, image) + + # TODO: get padding mask + # by feeding a "segmentation mask" to the same transforms + padding_mask = np.ones(image.shape[:2]) + image, transforms = T.apply_transform_gens(self.tfm_gens, image) + # the crop transformation has default padding value 0 for segmentation + padding_mask = transforms.apply_segmentation(padding_mask) + padding_mask = ~padding_mask.astype(bool) + + image_shape = image.shape[:2] # h, w + + # Pytorch's dataloader is efficient on torch.Tensor due to shared-memory, + # but not efficient on large generic data structures due to the use of pickle & mp.Queue. + # Therefore it's important to use torch.Tensor. + dataset_dict["image"] = torch.as_tensor(np.ascontiguousarray(image.transpose(2, 0, 1))) + dataset_dict["padding_mask"] = torch.as_tensor(np.ascontiguousarray(padding_mask)) + + # USER: Implement additional transformations if you have other types of data + annos = [ + utils.transform_instance_annotations(obj, transforms, image_shape) + for obj in dataset_dict.pop("annotations") + if (obj.get("iscrowd", 0) == 0) and (obj.get("empty", False) == False) + ] + instances = utils.annotations_to_instances(annos, image_shape) + + empty = dataset_dict.get("empty", False) + + if len(instances) > 0: + assert (not empty) + instances.gt_boxes = instances.gt_masks.get_bounding_boxes() + # Generate masks from polygon + h, w = instances.image_size + assert hasattr(instances, 'gt_masks') + gt_masks = instances.gt_masks + gt_masks = convert_coco_poly_to_mask(gt_masks.polygons, h, w) + instances.gt_masks = gt_masks + else: + assert empty + gt_masks = torch.zeros((0, image_shape[0], image_shape[1]), dtype=torch.uint8) + instances.gt_masks = gt_masks + + if self.split == "train" : + dataset_dict["instances"] = instances + else: + dataset_dict["gt_mask"] = gt_masks + + dataset_dict["empty"] = empty + dataset_dict["gt_mask_merged"] = self._merge_masks(gt_masks) if self.merge else None + # dataset_dict["gt_mask_merged"] = dataset_dict["gt_mask_merged"].float() + + # Language data + sentence_raw = dataset_dict['sentence']['raw'] + attention_mask = [0] * self.max_tokens + padded_input_ids = [0] * self.max_tokens + + input_ids = self.tokenizer.encode(text=sentence_raw, add_special_tokens=True) + + input_ids = input_ids[:self.max_tokens] + padded_input_ids[:len(input_ids)] = input_ids + + attention_mask[:len(input_ids)] = [1] * len(input_ids) + + dataset_dict['lang_tokens'] = torch.tensor(padded_input_ids).unsqueeze(0) + dataset_dict['lang_mask'] = torch.tensor(attention_mask).unsqueeze(0) + + return dataset_dict["image"].float(), dataset_dict["gt_mask_merged"].squeeze(0).long(), dataset_dict['lang_tokens'], dataset_dict['lang_mask'] + + + def __len__(self): + return len(self.dataset_dicts) + + + + + + + +if __name__ == "__main__": + """ + Test the COCO json dataset loader. + + Usage: + python -m detectron2.data.datasets.coco \ + path/to/json path/to/image_root dataset_name + + "dataset_name" can be "coco_2014_minival_100", or other + pre-registered ones + """ + from detectron2.utils.logger import setup_logger + from detectron2.utils.visualizer import Visualizer + import detectron2.data.datasets # noqa # add pre-defined metadata + import sys + + REFCOCO_PATH = '/data2/projects/donghwa/RIS/ReLA/datasets' + COCO_TRAIN_2014_IMAGE_ROOT = '/data2/projects/donghwa/RIS/ReLA/datasets/images' + REFCOCO_DATASET = 'grefcoco' + REFCOCO_SPLITBY = 'unc' + REFCOCO_SPLIT = 'train' + + logger = setup_logger(name=__name__) + dicts = load_grefcoco_json(REFCOCO_PATH, REFCOCO_DATASET, REFCOCO_SPLITBY, REFCOCO_SPLIT, COCO_TRAIN_2014_IMAGE_ROOT) + logger.info("Done loading {} samples.".format(len(dicts))) + \ No newline at end of file diff --git a/LAVT-RIS/donghwa/dataset_grefer_mosaic.py b/LAVT-RIS/donghwa/dataset_grefer_mosaic.py new file mode 100644 index 0000000000000000000000000000000000000000..c95dfd2d7b93ef96616d4c985660db760708601e --- /dev/null +++ b/LAVT-RIS/donghwa/dataset_grefer_mosaic.py @@ -0,0 +1,497 @@ +import contextlib +import io +import logging +import numpy as np +import os +import random +import copy +import pycocotools.mask as mask_util +from fvcore.common.timer import Timer +from PIL import Image +import torch.utils.data as data + +from detectron2.structures import Boxes, BoxMode, PolygonMasks, RotatedBoxes +from detectron2.utils.file_io import PathManager + +import time +import copy +import logging +import torch +import math + +from detectron2.config import configurable +from detectron2.data import detection_utils as utils +from detectron2.data import transforms as T + +# from transformers import BertTokenizer +from bert.tokenization_bert import BertTokenizer +from pycocotools import mask as coco_mask +from data.utils import convert_coco_poly_to_mask, build_transform_train, build_transform_test +""" +This file contains functions to parse RefCOCO-format annotations into dicts in "Detectron2 format". +""" + + +import albumentations as A +from albumentations.pytorch import ToTensorV2 +from PIL import Image, ImageDraw, ImageFilter + +# class aug: +# num_bgs = 4 +# aug_prob = 0.5 +# num_anchors = 0 +# random_target = False +# blur = False +# feature_path = None +# lower = 0 +# upper = 100 +# move_crs_pnt = False +# tgt_selection = 'fixed' + + +logger = logging.getLogger(__name__) + +__all__ = ["load_refcoco_json"] + +class GReferDataset(data.Dataset): + def __init__(self, + args, refer_root, dataset_name, splitby, split, image_root, + img_format="RGB", merge=True, + extra_annotation_keys=None, extra_refer_keys=None): + + self.refer_root = refer_root + self.dataset_name = dataset_name + self.splitby = splitby + self.split = split + self.image_root = image_root + self.extra_annotation_keys = extra_annotation_keys + self.extra_refer_keys = extra_refer_keys + self.img_format = img_format + self.merge = merge + self.max_tokens = 20 + self.tokenizer = BertTokenizer.from_pretrained(args.bert_tokenizer) + + if split == "train": + self.tfm_gens = build_transform_train(args) + elif split in ["val", "test", "testA", "testB"]: + self.tfm_gens = build_transform_test(args) + + if self.dataset_name == 'refcocop': + self.dataset_name = 'refcoco+' + if self.dataset_name == 'refcoco' or self.dataset_name == 'refcoco+': + self.splitby == 'unc' + if self.dataset_name == 'refcocog': + assert self.splitby == 'umd' or self.splitby == 'google' + + dataset_id = '_'.join([self.dataset_name, self.splitby, self.split]) + + from refer.grefer import G_REFER + logger.info('Loading dataset {} ({}-{}) ...'.format(self.dataset_name, self.splitby, self.split)) + logger.info('Refcoco root: {}'.format(self.refer_root)) + timer = Timer() + self.refer_root = PathManager.get_local_path(self.refer_root) + with contextlib.redirect_stdout(io.StringIO()): + self.refer = G_REFER(data_root=self.refer_root, + dataset=self.dataset_name, + splitBy=self.splitby) + if timer.seconds() > 1: + logger.info("Loading {} takes {:.2f} seconds.".format(dataset_id, timer.seconds())) + + self.ref_ids = self.refer.getRefIds(split=self.split) + self.img_ids = self.refer.getImgIds(self.ref_ids) + self.refs = self.refer.loadRefs(self.ref_ids) + imgs = [self.refer.loadImgs(ref['image_id'])[0] for ref in self.refs] + anns = [self.refer.loadAnns(ref['ann_id']) for ref in self.refs] + self.imgs_refs_anns = list(zip(imgs, self.refs, anns)) + + logger.info("Loaded {} images, {} referring object sets in G_RefCOCO format from {}".format(len(self.img_ids), len(self.ref_ids), dataset_id)) + + + self.dataset_dicts = [] + + ann_keys = ["iscrowd", "bbox", "category_id"] + (self.extra_annotation_keys or []) + ref_keys = ["raw", "sent_id"] + (self.extra_refer_keys or []) + + ann_lib = {} + + NT_count = 0 + MT_count = 0 + + for idx, (img_dict, ref_dict, anno_dicts) in enumerate(self.imgs_refs_anns): + record = {} + record['id'] = idx + record["source"] = 'grefcoco' + record["file_name"] = os.path.join(self.image_root, img_dict["file_name"]) + record["height"] = img_dict["height"] + record["width"] = img_dict["width"] + image_id = record["image_id"] = img_dict["id"] + + # Check that information of image, ann and ref match each other + # This fails only when the data parsing logic or the annotation file is buggy. + assert ref_dict['image_id'] == image_id + assert ref_dict['split'] == self.split + if not isinstance(ref_dict['ann_id'], list): + ref_dict['ann_id'] = [ref_dict['ann_id']] + + # No target samples + if None in anno_dicts: + assert anno_dicts == [None] + assert ref_dict['ann_id'] == [-1] + record['empty'] = True + obj = {key: None for key in ann_keys if key in ann_keys} + obj["bbox_mode"] = BoxMode.XYWH_ABS + obj["empty"] = True + obj = [obj] + + # Multi target samples + else: + record['empty'] = False + obj = [] + for anno_dict in anno_dicts: + ann_id = anno_dict['id'] + if anno_dict['iscrowd']: + continue + assert anno_dict["image_id"] == image_id + assert ann_id in ref_dict['ann_id'] + + if ann_id in ann_lib: + ann = ann_lib[ann_id] + else: + ann = {key: anno_dict[key] for key in ann_keys if key in anno_dict} + ann["bbox_mode"] = BoxMode.XYWH_ABS + ann["empty"] = False + + segm = anno_dict.get("segmentation", None) + assert segm # either list[list[float]] or dict(RLE) + if isinstance(segm, dict): + if isinstance(segm["counts"], list): + # convert to compressed RLE + segm = mask_util.frPyObjects(segm, *segm["size"]) + else: + # filter out invalid polygons (< 3 points) + segm = [poly for poly in segm if len(poly) % 2 == 0 and len(poly) >= 6] + if len(segm) == 0: + num_instances_without_valid_segmentation += 1 + continue # ignore this instance + ann["segmentation"] = segm + ann_lib[ann_id] = ann + + obj.append(ann) + + record["annotations"] = obj + + # Process referring expressions + sents = ref_dict['sentences'] + for sent in sents: + ref_record = record.copy() + ref = {key: sent[key] for key in ref_keys if key in sent} + ref["ref_id"] = ref_dict["ref_id"] + ref_record["sentence"] = ref + self.dataset_dicts.append(ref_record) + # if ref_record['empty']: + # NT_count += 1 + # else: + # MT_count += 1 + + # logger.info("NT samples: %d, MT samples: %d", NT_count, MT_count) + + # Debug mode + # return self.dataset_dicts[:100] + + # grefcoco + self.classes = [] + self.aug = args.aug + self.bert_type = args.bert_tokenizer + + self.img_sz = args.img_size + + each_img_sz = int(args.img_size/math.sqrt(self.aug.num_bgs)) + mean = (0.485, 0.456, 0.406) + std = (0.229, 0.224, 0.225) + + self.resize_bg1 = A.Compose([ + A.Resize(args.img_size, args.img_size, always_apply=True)]) + + self.resize_bg4 = A.Compose([ + A.Resize(each_img_sz, each_img_sz, always_apply=True)], + additional_targets={'image1': 'image', 'image2': 'image', 'image3': 'image', + 'mask1': 'mask', 'mask2': 'mask', 'mask3': 'mask',}) + + self.transforms = A.Compose([ + A.Normalize(mean=mean, std=std), + ToTensorV2 (), + ]) + + # ref_ids = self.refer.getRefIds(split=self.split) + # img_ids = self.refer.getImgIds(ref_ids) + all_imgs = self.refer.Imgs + self.imgs = list(all_imgs[i] for i in self.img_ids) + # self.ref_ids = ref_ids#[:500] + self.ref_id2idx = dict(zip(self.ref_ids, range(len(self.ref_ids)))) + self.ref_idx2id = dict(zip(range(len(self.ref_ids)), self.ref_ids)) + self.img2refs = self.refer.imgToRefs + + + # self.tokenizer.add_special_tokens({'additional_special_tokens': task_tokens}) + # self.tokenizer.add_tokens(position_tokens) + + # if we are testing on a dataset, test all sentences of an object; + # o/w, we are validating during training, randomly sample one sentence for efficiency + self.max_tokens = 20 + self.is_train = True if split == "train" else False + self.input_ids = [] + self.attention_masks = [] + for i, r in enumerate(self.ref_ids): + ref = self.refer.Refs[r] + + sentences_for_ref = [] + attentions_for_ref = [] + for j, (el, sent_id) in enumerate(zip(ref['sentences'], ref['sent_ids'])): + sentence_raw = el['raw'] + input_ids = self.tokenizer.encode(text=sentence_raw, add_special_tokens=True, max_length=self.max_tokens, truncation=True) + #input_ids = input_ids[:self.max_tokens] + padded_input_ids = [0] * self.max_tokens + padded_input_ids[:len(input_ids)] = input_ids + attention_mask = [0] * self.max_tokens + attention_mask[:len(input_ids)] = [1]*len(input_ids) + sentences_for_ref.append(padded_input_ids) + attentions_for_ref.append(attention_mask) + + self.input_ids.append(sentences_for_ref) + self.attention_masks.append(attentions_for_ref) + + if self.aug.blur: + self.blur = ImageFilter.GaussianBlur(100) + np.random.seed() + + + + @staticmethod + def _merge_masks(x): + return x.sum(dim=0, keepdim=True).clamp(max=1) + + def __len__(self): + return len(self.dataset_dicts) + + + def __getitem__(self, index): + + dataset_dict = copy.deepcopy(self.dataset_dicts[index]) + img_id = dataset_dict["image_id"] + index = dataset_dict["id"] + + # decide mosaic size + if self.split=='train': + if self.aug.num_bgs==4: + aug_prob = self.aug.aug_prob + num_bgs = np.random.choice([1, 4], p=[1-aug_prob, aug_prob]) + else: + num_bgs = 1 + else: + num_bgs = 1 + + + target_sent_idx = np.random.choice(len(self.input_ids[index])) + + if num_bgs==1: + ref_ids = [] + sent_idxs = [] + sents = np.array([], dtype='str') + + else: + ref_ids = list(np.random.choice(self.ref_ids, size=num_bgs-1, replace=False)) + sent_idxs = [np.random.choice(len(self.refer.Refs[r]['sentences'])) for r in ref_ids] + sents = np.array([self.refer.Refs[r]['sentences'][sent_idxs[i]]['raw'] for i, r in enumerate(ref_ids)], dtype='str') + + insert_idx = np.random.choice(range(num_bgs)) + ref_ids = np.insert(ref_ids, insert_idx, self.ref_idx2id[index]).astype(int) + sents = np.insert(sents, insert_idx, + self.refer.Refs[ref_ids[insert_idx]]['sentences'][target_sent_idx]['raw']) + sent_idxs = np.insert(sent_idxs, insert_idx, target_sent_idx).astype(int) + + # pick a target origin + if self.aug.tgt_selection == 'random': + target_idx = np.random.choice(range(num_bgs)) + target_ref_idx = self.ref_id2idx[ref_ids[target_idx]] + target_sent_idx = int(np.random.choice(len(self.input_ids[target_ref_idx]))) + elif self.aug.tgt_selection == 'longest': + target_idx = np.argmax(list(map(len, sents))) + target_sent_idx = sent_idxs[target_idx] + elif self.aug.tgt_selection == 'fixed': + target_idx = insert_idx + target_ref_id = ref_ids[target_idx] + + # load items + imgs, masks = [], [] + for ref_id in ref_ids: + img_id = self.refer.getImgIds([ref_id])[0] + img_info = self.refer.Imgs[img_id] + img_path = os.path.join(self.refer.IMAGE_DIR, img_info['file_name']) + img = Image.open(img_path).convert("RGB") + imgs.append(np.array(img)) + ref = self.refer.loadRefs(ref_ids=[ref_id]) + if self.dataset_name in ['refcoco', 'refcoco+', 'refcocog']: + mask = np.array(self.refer.getMask(ref[0])['mask']) + elif self.dataset_name in ['grefcoco'] : + mask = self.refer.getMaskByRef(ref[0], ref_id, self.merge)['mask'] + masks.append(mask) + + # image resize and apply 4in1 augmentation + if num_bgs==1: + resized = self.resize_bg1(image=imgs[0], mask=masks[0]) + imgs, masks = [resized['image']], [resized['mask']] + img = imgs[0] + else: + if self.aug.move_crs_pnt: + crs_y = np.random.randint(0, self.img_sz+1) + crs_x = np.random.randint(0, self.img_sz+1) + else: + crs_y = 480//2 # + crs_x = 480//2 # + + if crs_y==0 or crs_x==0: + img1 = np.zeros([0,crs_x,3]) if crs_y==0 else np.zeros([crs_y,0,3]) + mask1 = np.zeros([0,crs_x]) if crs_y==0 else np.zeros([crs_y,0]) + else: + resize_bg1 = A.Compose([A.Resize(crs_y, crs_x, always_apply=True)]) + temp = resize_bg1(image=imgs[0], mask=masks[0]) + img1 = temp['image'] + mask1 = temp['mask'] + + if crs_y==0 or crs_x==self.img_sz: + img2 = np.zeros([0,self.img_sz-crs_x,3]) if crs_y==0 \ + else np.zeros([crs_y,0,3]) + mask2 = np.zeros([0,self.img_sz-crs_x]) if crs_y==0 \ + else np.zeros([crs_y,0]) + else: + resize_bg2 = A.Compose([ + A.Resize(crs_y, self.img_sz-crs_x, always_apply=True)]) + temp = resize_bg2(image=imgs[1], mask=masks[1]) + img2 = temp['image'] + mask2 = temp['mask'] + + if crs_y==self.img_sz or crs_x==0: + img3 = np.zeros([0,crs_x,3]) if crs_y==self.img_sz \ + else np.zeros([self.img_sz-crs_y,0,3]) + mask3 = np.zeros([0,crs_x]) if crs_y==self.img_sz \ + else np.zeros([self.img_sz-crs_y,0]) + else: + resize_bg3 = A.Compose([ + A.Resize(self.img_sz-crs_y, crs_x, always_apply=True)]) + temp = resize_bg3(image=imgs[2], mask=masks[2]) + img3 = temp['image'] + mask3 = temp['mask'] + + if crs_y==self.img_sz or crs_x==self.img_sz: + img4 = np.zeros([0,self.img_sz-crs_x,3]) if crs_y==self.img_sz \ + else np.zeros([self.img_sz-crs_y,0,3]) + mask4 = np.zeros([0,self.img_sz-crs_x]) if crs_y==self.img_sz \ + else np.zeros([self.img_sz-crs_y,0]) + else: + resize_bg4 = A.Compose([ + A.Resize(self.img_sz-crs_y, + self.img_sz-crs_x, always_apply=True)]) + temp = resize_bg4(image=imgs[3], mask=masks[3]) + img4 = temp['image'] + mask4 = temp['mask'] + + imgs = [img1, img2, img3, img4] + masks = [mask1, mask2, mask3, mask4] + + # scale effect ablation + if self.aug.blur: + imgs = [np.asarray(Image.fromarray(x).filter(self.blur)) if i!=insert_idx else x for i, x in enumerate(imgs)] + + num_rows = num_cols = int(math.sqrt(num_bgs)) + idxs = [(i*num_cols,i*num_cols+num_cols) for i in range(num_rows)] + img = [np.concatenate(imgs[_from:_to], axis=1) for (_from, _to) in idxs] + img = np.concatenate(img, axis=0).astype(np.uint8) + + masks_arr = [] + for bg_idx in range(num_bgs): + mask = masks[bg_idx] + temp = [mask if idx==bg_idx else np.zeros_like(masks[idx]) for idx in range(num_bgs)] + mask = [np.concatenate(temp[_from:_to], axis=1) for (_from, _to) in idxs] + mask = np.concatenate(mask, axis=0).astype(np.int32) + masks_arr.append(mask) + masks = masks_arr + + mask = masks[target_idx] + mask = mask.astype(np.uint8) + mask[mask>0] = 1 + + item = self.transforms(image=img, mask=mask) + img_tensor = item['image'] + target = item['mask'].long() + + target_ref_idx = self.ref_id2idx[target_ref_id] + # if self.is_train: + # embedding = [] + # att = [] + # for s in range(len(self.input_ids[target_ref_idx])): + # padded_input_ids = self.input_ids[target_ref_idx][s] + # tensor_embeddings = torch.tensor(padded_input_ids).unsqueeze(0) + # attention_mask = self.attention_masks[target_ref_idx][s] + # attention_mask = torch.tensor(attention_mask).unsqueeze(0) + # embedding.append(tensor_embeddings.unsqueeze(-1)) + # att.append(attention_mask.unsqueeze(-1)) + # tensor_embeddings = torch.cat(embedding, dim=-1) + # attention_mask = torch.cat(att, dim=-1) + # else: + padded_input_ids = self.input_ids[target_ref_idx][target_sent_idx] + tensor_embeddings = torch.tensor(padded_input_ids).unsqueeze(0) + attention_mask = self.attention_masks[target_ref_idx][target_sent_idx] + attention_mask = torch.tensor(attention_mask).unsqueeze(0) + + empty = dataset_dict.get("empty", False) + dataset_dict["empty"] = empty + dataset_dict['image'] = img_tensor + dataset_dict['gt_masks'] = target.unsqueeze(0) + dataset_dict['lang_tokens'] = tensor_embeddings + dataset_dict['lang_mask'] = attention_mask + # dataset_dict["gt_mask_merged"] = self._merge_masks(target) if self.merge else None + dataset_dict["gt_mask_merged"] = target.unsqueeze(0) + + + item = { + 'image': img_tensor.float(), + 'seg_target': target.long(), + 'sentence': tensor_embeddings, + 'attn_mask': attention_mask, + } + return item + + + + + + + + + +if __name__ == "__main__": + """ + Test the COCO json dataset loader. + + Usage: + python -m detectron2.data.datasets.coco \ + path/to/json path/to/image_root dataset_name + + "dataset_name" can be "coco_2014_minival_100", or other + pre-registered ones + """ + from detectron2.utils.logger import setup_logger + from detectron2.utils.visualizer import Visualizer + import detectron2.data.datasets # noqa # add pre-defined metadata + import sys + + REFCOCO_PATH = '/data2/projects/donghwa/RIS/ReLA/datasets' + COCO_TRAIN_2014_IMAGE_ROOT = '/data2/projects/donghwa/RIS/ReLA/datasets/images' + REFCOCO_DATASET = 'grefcoco' + REFCOCO_SPLITBY = 'unc' + REFCOCO_SPLIT = 'train' + + logger = setup_logger(name=__name__) + dicts = load_grefcoco_json(REFCOCO_PATH, REFCOCO_DATASET, REFCOCO_SPLITBY, REFCOCO_SPLIT, COCO_TRAIN_2014_IMAGE_ROOT) + logger.info("Done loading {} samples.".format(len(dicts))) + \ No newline at end of file diff --git a/LAVT-RIS/donghwa/dataset_grefer_mosaic_retrieval.py b/LAVT-RIS/donghwa/dataset_grefer_mosaic_retrieval.py new file mode 100644 index 0000000000000000000000000000000000000000..aa295788b3fe167ee31e5c4c09eb48197d15c476 --- /dev/null +++ b/LAVT-RIS/donghwa/dataset_grefer_mosaic_retrieval.py @@ -0,0 +1,547 @@ +import contextlib +import io +import logging +import numpy as np +import os +import random +import copy +import pycocotools.mask as mask_util +from fvcore.common.timer import Timer +from PIL import Image +import torch.utils.data as data + +from detectron2.structures import Boxes, BoxMode, PolygonMasks, RotatedBoxes +from detectron2.utils.file_io import PathManager + +import time +import copy +import logging +import torch +import math + +from detectron2.config import configurable +from detectron2.data import detection_utils as utils +from detectron2.data import transforms as T + +# from transformers import BertTokenizer +from bert.tokenization_bert import BertTokenizer +from pycocotools import mask as coco_mask +from data.utils import convert_coco_poly_to_mask, build_transform_train, build_transform_test +from .utils import cosine_annealing +""" +This file contains functions to parse RefCOCO-format annotations into dicts in "Detectron2 format". +""" + + +import albumentations as A +from albumentations.pytorch import ToTensorV2 +from PIL import Image, ImageDraw, ImageFilter +import lmdb +import pyarrow as pa + + + +def loads_pyarrow(buf): + return pa.deserialize(buf) + + + +logger = logging.getLogger(__name__) + +__all__ = ["load_refcoco_json"] + +class GReferDataset(data.Dataset): + def __init__(self, + args, refer_root, dataset_name, splitby, split, image_root, + img_format="RGB", merge=True, + extra_annotation_keys=None, extra_refer_keys=None): + + self.refer_root = refer_root + self.dataset_name = dataset_name + self.splitby = splitby + self.split = split + self.image_root = image_root + self.extra_annotation_keys = extra_annotation_keys + self.extra_refer_keys = extra_refer_keys + self.img_format = img_format + self.merge = merge + self.max_tokens = 20 + self.tokenizer = BertTokenizer.from_pretrained(args.bert_tokenizer) + + if split == "train": + self.tfm_gens = build_transform_train(args) + elif split in ["val", "test", "testA", "testB"]: + self.tfm_gens = build_transform_test(args) + + if self.dataset_name == 'refcocop': + self.dataset_name = 'refcoco+' + if self.dataset_name == 'refcoco' or self.dataset_name == 'refcoco+': + self.splitby == 'unc' + if self.dataset_name == 'refcocog': + assert self.splitby == 'umd' or self.splitby == 'google' + + dataset_id = '_'.join([self.dataset_name, self.splitby, self.split]) + + from refer.grefer import G_REFER + logger.info('Loading dataset {} ({}-{}) ...'.format(self.dataset_name, self.splitby, self.split)) + logger.info('Refcoco root: {}'.format(self.refer_root)) + timer = Timer() + self.refer_root = PathManager.get_local_path(self.refer_root) + with contextlib.redirect_stdout(io.StringIO()): + self.refer = G_REFER(data_root=self.refer_root, + dataset=self.dataset_name, + splitBy=self.splitby) + if timer.seconds() > 1: + logger.info("Loading {} takes {:.2f} seconds.".format(dataset_id, timer.seconds())) + + self.ref_ids = self.refer.getRefIds(split=self.split) + self.img_ids = self.refer.getImgIds(self.ref_ids) + self.refs = self.refer.loadRefs(self.ref_ids) + imgs = [self.refer.loadImgs(ref['image_id'])[0] for ref in self.refs] + anns = [self.refer.loadAnns(ref['ann_id']) for ref in self.refs] + self.imgs_refs_anns = list(zip(imgs, self.refs, anns)) + + logger.info("Loaded {} images, {} referring object sets in G_RefCOCO format from {}".format(len(self.img_ids), len(self.ref_ids), dataset_id)) + + + self.dataset_dicts = [] + + ann_keys = ["iscrowd", "bbox", "category_id"] + (self.extra_annotation_keys or []) + ref_keys = ["raw", "sent_id"] + (self.extra_refer_keys or []) + + ann_lib = {} + + NT_count = 0 + MT_count = 0 + + for idx, (img_dict, ref_dict, anno_dicts) in enumerate(self.imgs_refs_anns): + record = {} + record['id'] = idx + record["source"] = 'grefcoco' + record["file_name"] = os.path.join(self.image_root, img_dict["file_name"]) + record["height"] = img_dict["height"] + record["width"] = img_dict["width"] + image_id = record["image_id"] = img_dict["id"] + + # Check that information of image, ann and ref match each other + # This fails only when the data parsing logic or the annotation file is buggy. + assert ref_dict['image_id'] == image_id + assert ref_dict['split'] == self.split + if not isinstance(ref_dict['ann_id'], list): + ref_dict['ann_id'] = [ref_dict['ann_id']] + + # No target samples + if None in anno_dicts: + assert anno_dicts == [None] + assert ref_dict['ann_id'] == [-1] + record['empty'] = True + obj = {key: None for key in ann_keys if key in ann_keys} + obj["bbox_mode"] = BoxMode.XYWH_ABS + obj["empty"] = True + obj = [obj] + + # Multi target samples + else: + record['empty'] = False + obj = [] + for anno_dict in anno_dicts: + ann_id = anno_dict['id'] + if anno_dict['iscrowd']: + continue + assert anno_dict["image_id"] == image_id + assert ann_id in ref_dict['ann_id'] + + if ann_id in ann_lib: + ann = ann_lib[ann_id] + else: + ann = {key: anno_dict[key] for key in ann_keys if key in anno_dict} + ann["bbox_mode"] = BoxMode.XYWH_ABS + ann["empty"] = False + + segm = anno_dict.get("segmentation", None) + assert segm # either list[list[float]] or dict(RLE) + if isinstance(segm, dict): + if isinstance(segm["counts"], list): + # convert to compressed RLE + segm = mask_util.frPyObjects(segm, *segm["size"]) + else: + # filter out invalid polygons (< 3 points) + segm = [poly for poly in segm if len(poly) % 2 == 0 and len(poly) >= 6] + if len(segm) == 0: + num_instances_without_valid_segmentation += 1 + continue # ignore this instance + ann["segmentation"] = segm + ann_lib[ann_id] = ann + + obj.append(ann) + + record["annotations"] = obj + + # Process referring expressions + sents = ref_dict['sentences'] + for sent in sents: + ref_record = record.copy() + ref = {key: sent[key] for key in ref_keys if key in sent} + ref["ref_id"] = ref_dict["ref_id"] + ref_record["sentence"] = ref + self.dataset_dicts.append(ref_record) + # if ref_record['empty']: + # NT_count += 1 + # else: + # MT_count += 1 + + # logger.info("NT samples: %d, MT samples: %d", NT_count, MT_count) + + # Debug mode + # return self.dataset_dicts[:100] + + # grefcoco + self.classes = [] + self.aug = args.aug + self.bert_type = args.bert_tokenizer + + self.img_sz = args.img_size + + each_img_sz = int(args.img_size/math.sqrt(self.aug.num_bgs)) + mean = (0.485, 0.456, 0.406) + std = (0.229, 0.224, 0.225) + + self.resize_bg1 = A.Compose([ + A.Resize(args.img_size, args.img_size, always_apply=True)]) + + self.resize_bg4 = A.Compose([ + A.Resize(each_img_sz, each_img_sz, always_apply=True)], + additional_targets={'image1': 'image', 'image2': 'image', 'image3': 'image', + 'mask1': 'mask', 'mask2': 'mask', 'mask3': 'mask',}) + + self.transforms = A.Compose([ + A.Normalize(mean=mean, std=std), + ToTensorV2 (), + ]) + + # ref_ids = self.refer.getRefIds(split=self.split) + # img_ids = self.refer.getImgIds(ref_ids) + all_imgs = self.refer.Imgs + self.imgs = list(all_imgs[i] for i in self.img_ids) + # self.ref_ids = ref_ids#[:500] + self.ref_id2idx = dict(zip(self.ref_ids, range(len(self.ref_ids)))) + self.ref_idx2id = dict(zip(range(len(self.ref_ids)), self.ref_ids)) + self.img2refs = self.refer.imgToRefs + + + # self.tokenizer.add_special_tokens({'additional_special_tokens': task_tokens}) + # self.tokenizer.add_tokens(position_tokens) + + # if we are testing on a dataset, test all sentences of an object; + # o/w, we are validating during training, randomly sample one sentence for efficiency + self.max_tokens = 20 + self.is_train = True if split == "train" else False + self.input_ids = [] + self.attention_masks = [] + for i, r in enumerate(self.ref_ids): + ref = self.refer.Refs[r] + + sentences_for_ref = [] + attentions_for_ref = [] + for j, (el, sent_id) in enumerate(zip(ref['sentences'], ref['sent_ids'])): + sentence_raw = el['raw'] + input_ids = self.tokenizer.encode(text=sentence_raw, add_special_tokens=True, max_length=self.max_tokens, truncation=True) + #input_ids = input_ids[:self.max_tokens] + padded_input_ids = [0] * self.max_tokens + padded_input_ids[:len(input_ids)] = input_ids + attention_mask = [0] * self.max_tokens + attention_mask[:len(input_ids)] = [1]*len(input_ids) + sentences_for_ref.append(padded_input_ids) + attentions_for_ref.append(attention_mask) + + self.input_ids.append(sentences_for_ref) + self.attention_masks.append(attentions_for_ref) + + if self.aug.blur: + self.blur = ImageFilter.GaussianBlur(100) + + # Load mldb data / temptative + lmdb_path = f'/data2/dataset/RefCOCO/logit_db/grefcoco/grefcoco.lmdb' + # self.lmdb_dict = read_from_lmdb(lmdb_dir) + self.lmdb_env = lmdb.open( + lmdb_path, subdir=False, max_readers=32, + readonly=True, lock=False, + readahead=False, meminit=False + ) + with self.lmdb_env.begin(write=False) as txn: + self.length = loads_pyarrow(txn.get(b'__len__')) + self.keys = loads_pyarrow(txn.get(b'__keys__')) + + self.epoch = 0 + np.random.seed() + + + + @staticmethod + def _merge_masks(x): + return x.sum(dim=0, keepdim=True).clamp(max=1) + + def __len__(self): + return len(self.dataset_dicts) + + + def __getitem__(self, index): + + refid = self.ref_idx2id[index] + with self.lmdb_env.begin(write=False) as txn: + byteflow = txn.get(self.keys[refid]) + lmdb_dict = loads_pyarrow(byteflow) + + + dataset_dict = copy.deepcopy(self.dataset_dicts[index]) + img_id = dataset_dict["image_id"] + index = dataset_dict["id"] + + # decide mosaic size + if self.split=='train': + if self.aug.num_bgs==4: + aug_prob = self.aug.aug_prob # 0.6 + if self.epoch < self.aug.retrieval_epoch : + num_bgs = np.random.choice([1, 4], p=[1-aug_prob, aug_prob]) + else : + rand_prob = cosine_annealing(epoch=self.epoch-self.aug.retrieval_epoch, \ + n_epochs=self.args.epochs-self.aug.retrieval_epoch, + n_cycles=1, lrate_max=aug_prob) + retr_prob = aug_prob-rand_prob + choice = np.random.choice(['one', 'random', 'retrieval'], p=[1-aug_prob, rand_prob, retr_prob]) + if choice == 'one': + num_bgs = 1 + else : + num_bgs = 4 + else: + num_bgs = 1 + else: + num_bgs = 1 + + + target_sent_idx = np.random.choice(len(self.input_ids[index])) + ref_id = self.ref_idx2id[index] + insert_idx = np.random.choice(range(num_bgs)) + + if num_bgs==1: + ref_ids = [] + sent_idxs = [] + sents = np.array([], dtype='str') + img_ids = [self.refer.Refs[ref_id]['image_id']] + + else: + if self.epoch >= self.aug.retrieval_epoch : + sent_id = list(lmdb_dict.keys())[target_sent_idx] + img_ids = list(np.random.choice(lmdb_dict[sent_id], size=num_bgs-1, replace=True)) + img_ids = np.insert(img_ids, insert_idx, self.refer.Refs[ref_id]['image_id']) + + ref_ids = list(np.random.choice(self.ref_ids, size=num_bgs-1, replace=False)) + sent_idxs = [np.random.choice(len(self.refer.Refs[r]['sentences'])) for r in ref_ids] + sents = np.array([self.refer.Refs[r]['sentences'][sent_idxs[i]]['raw'] for i, r in enumerate(ref_ids)], dtype='str') + + ref_ids = np.insert(ref_ids, insert_idx, self.ref_idx2id[index]).astype(int) + sents = np.insert(sents, insert_idx, + self.refer.Refs[ref_ids[insert_idx]]['sentences'][target_sent_idx]['raw']) + sent_idxs = np.insert(sent_idxs, insert_idx, target_sent_idx).astype(int) + + # pick a target origin + if self.aug.tgt_selection == 'random': + target_idx = np.random.choice(range(num_bgs)) + target_ref_idx = self.ref_id2idx[ref_ids[target_idx]] + target_sent_idx = int(np.random.choice(len(self.input_ids[target_ref_idx]))) + elif self.aug.tgt_selection == 'longest': + target_idx = np.argmax(list(map(len, sents))) + target_sent_idx = sent_idxs[target_idx] + elif self.aug.tgt_selection == 'fixed': + target_idx = insert_idx + # target_ref_id = ref_ids[target_idx] + target_ref_id = self.ref_idx2id[index] + + # load items + imgs, masks = [], [] + if self.epoch >= self.aug.retrieval_epoch : + for img_id in img_ids: + img_info = self.refer.Imgs[img_id] + img_path = os.path.join(self.refer.IMAGE_DIR, img_info['file_name']) + img = Image.open(img_path).convert("RGB") + imgs.append(np.array(img)) + ref = self.refer.imgToRefs[img_id][0] + # if self.dataset_name in ['refcoco', 'refcoco+', 'refcocog']: + # mask = np.array(self.refer.getMask(ref)['mask']) + # elif self.dataset_name in ['grefcoco'] : + mask = self.refer.getMaskByRef(ref, ref['ref_id'], self.merge)['mask'] + masks.append(mask) + + else : + for ref_id in ref_ids: + img_id = self.refer.getImgIds([ref_id])[0] + img_info = self.refer.Imgs[img_id] + img_path = os.path.join(self.refer.IMAGE_DIR, img_info['file_name']) + img = Image.open(img_path).convert("RGB") + imgs.append(np.array(img)) + ref = self.refer.loadRefs(ref_ids=[ref_id]) + # if self.dataset_name in ['refcoco', 'refcoco+', 'refcocog']: + # mask = np.array(self.refer.getMask(ref[0])['mask']) + # elif self.dataset_name in ['grefcoco'] : + mask = self.refer.getMaskByRef(ref[0], ref_id, self.merge)['mask'] + masks.append(mask) + + # image resize and apply 4in1 augmentation + if num_bgs==1: + resized = self.resize_bg1(image=imgs[0], mask=masks[0]) + imgs, masks = [resized['image']], [resized['mask']] + img = imgs[0] + else: + if self.aug.move_crs_pnt: + crs_y = np.random.randint(0, self.img_sz+1) + crs_x = np.random.randint(0, self.img_sz+1) + else: + crs_y = 480//2 # + crs_x = 480//2 # + + if crs_y==0 or crs_x==0: + img1 = np.zeros([0,crs_x,3]) if crs_y==0 else np.zeros([crs_y,0,3]) + mask1 = np.zeros([0,crs_x]) if crs_y==0 else np.zeros([crs_y,0]) + else: + resize_bg1 = A.Compose([A.Resize(crs_y, crs_x, always_apply=True)]) + temp = resize_bg1(image=imgs[0], mask=masks[0]) + img1 = temp['image'] + mask1 = temp['mask'] + + if crs_y==0 or crs_x==self.img_sz: + img2 = np.zeros([0,self.img_sz-crs_x,3]) if crs_y==0 \ + else np.zeros([crs_y,0,3]) + mask2 = np.zeros([0,self.img_sz-crs_x]) if crs_y==0 \ + else np.zeros([crs_y,0]) + else: + resize_bg2 = A.Compose([ + A.Resize(crs_y, self.img_sz-crs_x, always_apply=True)]) + temp = resize_bg2(image=imgs[1], mask=masks[1]) + img2 = temp['image'] + mask2 = temp['mask'] + + if crs_y==self.img_sz or crs_x==0: + img3 = np.zeros([0,crs_x,3]) if crs_y==self.img_sz \ + else np.zeros([self.img_sz-crs_y,0,3]) + mask3 = np.zeros([0,crs_x]) if crs_y==self.img_sz \ + else np.zeros([self.img_sz-crs_y,0]) + else: + resize_bg3 = A.Compose([ + A.Resize(self.img_sz-crs_y, crs_x, always_apply=True)]) + temp = resize_bg3(image=imgs[2], mask=masks[2]) + img3 = temp['image'] + mask3 = temp['mask'] + + if crs_y==self.img_sz or crs_x==self.img_sz: + img4 = np.zeros([0,self.img_sz-crs_x,3]) if crs_y==self.img_sz \ + else np.zeros([self.img_sz-crs_y,0,3]) + mask4 = np.zeros([0,self.img_sz-crs_x]) if crs_y==self.img_sz \ + else np.zeros([self.img_sz-crs_y,0]) + else: + resize_bg4 = A.Compose([ + A.Resize(self.img_sz-crs_y, + self.img_sz-crs_x, always_apply=True)]) + temp = resize_bg4(image=imgs[3], mask=masks[3]) + img4 = temp['image'] + mask4 = temp['mask'] + + imgs = [img1, img2, img3, img4] + masks = [mask1, mask2, mask3, mask4] + + # scale effect ablation + if self.aug.blur: + imgs = [np.asarray(Image.fromarray(x).filter(self.blur)) if i!=insert_idx else x for i, x in enumerate(imgs)] + + num_rows = num_cols = int(math.sqrt(num_bgs)) + idxs = [(i*num_cols,i*num_cols+num_cols) for i in range(num_rows)] + img = [np.concatenate(imgs[_from:_to], axis=1) for (_from, _to) in idxs] + img = np.concatenate(img, axis=0).astype(np.uint8) + + masks_arr = [] + for bg_idx in range(num_bgs): + mask = masks[bg_idx] + temp = [mask if idx==bg_idx else np.zeros_like(masks[idx]) for idx in range(num_bgs)] + mask = [np.concatenate(temp[_from:_to], axis=1) for (_from, _to) in idxs] + mask = np.concatenate(mask, axis=0).astype(np.int32) + masks_arr.append(mask) + masks = masks_arr + + mask = masks[target_idx] + mask = mask.astype(np.uint8) + mask[mask>0] = 1 + + item = self.transforms(image=img, mask=mask) + img_tensor = item['image'] + target = item['mask'].long() + + target_ref_idx = self.ref_id2idx[target_ref_id] + # if self.is_train: + # embedding = [] + # att = [] + # for s in range(len(self.input_ids[target_ref_idx])): + # padded_input_ids = self.input_ids[target_ref_idx][s] + # tensor_embeddings = torch.tensor(padded_input_ids).unsqueeze(0) + # attention_mask = self.attention_masks[target_ref_idx][s] + # attention_mask = torch.tensor(attention_mask).unsqueeze(0) + # embedding.append(tensor_embeddings.unsqueeze(-1)) + # att.append(attention_mask.unsqueeze(-1)) + # tensor_embeddings = torch.cat(embedding, dim=-1) + # attention_mask = torch.cat(att, dim=-1) + # else: + padded_input_ids = self.input_ids[target_ref_idx][target_sent_idx] + tensor_embeddings = torch.tensor(padded_input_ids).unsqueeze(0) + attention_mask = self.attention_masks[target_ref_idx][target_sent_idx] + attention_mask = torch.tensor(attention_mask).unsqueeze(0) + + empty = dataset_dict.get("empty", False) + dataset_dict["empty"] = empty + dataset_dict['image'] = img_tensor + dataset_dict['gt_masks'] = target.unsqueeze(0) + dataset_dict['lang_tokens'] = tensor_embeddings + dataset_dict['lang_mask'] = attention_mask + # dataset_dict["gt_mask_merged"] = self._merge_masks(target) if self.merge else None + dataset_dict["gt_mask_merged"] = target.unsqueeze(0) + + + item = { + 'image': img_tensor.float(), + 'seg_target': target.long(), + 'sentence': tensor_embeddings, + 'attn_mask': attention_mask, + } + return item + + + + + + + + + +if __name__ == "__main__": + """ + Test the COCO json dataset loader. + + Usage: + python -m detectron2.data.datasets.coco \ + path/to/json path/to/image_root dataset_name + + "dataset_name" can be "coco_2014_minival_100", or other + pre-registered ones + """ + from detectron2.utils.logger import setup_logger + from detectron2.utils.visualizer import Visualizer + import detectron2.data.datasets # noqa # add pre-defined metadata + import sys + + REFCOCO_PATH = '/data2/projects/donghwa/RIS/ReLA/datasets' + COCO_TRAIN_2014_IMAGE_ROOT = '/data2/projects/donghwa/RIS/ReLA/datasets/images' + REFCOCO_DATASET = 'grefcoco' + REFCOCO_SPLITBY = 'unc' + REFCOCO_SPLIT = 'train' + + logger = setup_logger(name=__name__) + dicts = load_grefcoco_json(REFCOCO_PATH, REFCOCO_DATASET, REFCOCO_SPLITBY, REFCOCO_SPLIT, COCO_TRAIN_2014_IMAGE_ROOT) + logger.info("Done loading {} samples.".format(len(dicts))) + \ No newline at end of file diff --git a/LAVT-RIS/donghwa/dataset_refer_bert.py b/LAVT-RIS/donghwa/dataset_refer_bert.py new file mode 100644 index 0000000000000000000000000000000000000000..298e61fda7377016f8c595ea216ec5645beb1526 --- /dev/null +++ b/LAVT-RIS/donghwa/dataset_refer_bert.py @@ -0,0 +1,128 @@ +import os +import sys +import torch.utils.data as data +import torch +from torchvision import transforms +from torch.autograd import Variable +import numpy as np +from PIL import Image +import torchvision.transforms.functional as TF +import random + +from bert.tokenization_bert import BertTokenizer + +import h5py +from refer.refer import REFER + +from args import get_parser + +# Dataset configuration initialization +# parser = get_parser() +# args = parser.parse_args() + + +class ReferDataset(data.Dataset): + + def __init__(self, + args, + image_transforms=None, + target_transforms=None, + split='train', + eval_mode=False): + + self.classes = [] + self.image_transforms = image_transforms + self.target_transform = target_transforms + self.split = split + self.dataset = args.dataset + if args.dataset == 'refcocog' and args.split in ['testA', 'testB']: + print(f"Easy & Hard Example Experiments - dataset : {args.dataset}, split : {args.split}") + from refer.refer_test import REFER + self.refer = REFER(args.refer_data_root, args.dataset, args.splitBy) + else : + from refer.refer import REFER + self.refer = REFER(args.refer_data_root, args.dataset, args.splitBy) + + self.max_tokens = 20 + + ref_ids = self.refer.getRefIds(split=self.split) + img_ids = self.refer.getImgIds(ref_ids) + + all_imgs = self.refer.Imgs + self.imgs = list(all_imgs[i] for i in img_ids) + self.ref_ids = ref_ids + + self.input_ids = [] + self.attention_masks = [] + self.tokenizer = BertTokenizer.from_pretrained(args.bert_tokenizer) + + self.eval_mode = eval_mode + # if we are testing on a dataset, test all sentences of an object; + # o/w, we are validating during training, randomly sample one sentence for efficiency + for r in ref_ids: + ref = self.refer.Refs[r] + + sentences_for_ref = [] + attentions_for_ref = [] + + for i, (el, sent_id) in enumerate(zip(ref['sentences'], ref['sent_ids'])): + sentence_raw = el['raw'] + attention_mask = [0] * self.max_tokens + padded_input_ids = [0] * self.max_tokens + + input_ids = self.tokenizer.encode(text=sentence_raw, add_special_tokens=True) + + # truncation of tokens + input_ids = input_ids[:self.max_tokens] + + padded_input_ids[:len(input_ids)] = input_ids + attention_mask[:len(input_ids)] = [1]*len(input_ids) + + sentences_for_ref.append(torch.tensor(padded_input_ids).unsqueeze(0)) + attentions_for_ref.append(torch.tensor(attention_mask).unsqueeze(0)) + + self.input_ids.append(sentences_for_ref) + self.attention_masks.append(attentions_for_ref) + + def get_classes(self): + return self.classes + + def __len__(self): + return len(self.ref_ids) + + def __getitem__(self, index): + this_ref_id = self.ref_ids[index] + this_img_id = self.refer.getImgIds(this_ref_id) + this_img = self.refer.Imgs[this_img_id[0]] + + img = Image.open(os.path.join(self.refer.IMAGE_DIR, this_img['file_name'])).convert("RGB") + + ref = self.refer.loadRefs(this_ref_id) + + ref_mask = np.array(self.refer.getMask(ref[0])['mask']) + annot = np.zeros(ref_mask.shape) + annot[ref_mask == 1] = 1 + + annot = Image.fromarray(annot.astype(np.uint8), mode="P") + + if self.image_transforms is not None: + # resize, from PIL to tensor, and mean and std normalization + img, target = self.image_transforms(img, annot) + + if self.eval_mode: + embedding = [] + att = [] + for s in range(len(self.input_ids[index])): + e = self.input_ids[index][s] + a = self.attention_masks[index][s] + embedding.append(e.unsqueeze(-1)) + att.append(a.unsqueeze(-1)) + + tensor_embeddings = torch.cat(embedding, dim=-1) + attention_mask = torch.cat(att, dim=-1) + else: + choice_sent = np.random.choice(len(self.input_ids[index])) + tensor_embeddings = self.input_ids[index][choice_sent] + attention_mask = self.attention_masks[index][choice_sent] + + return img, target, tensor_embeddings, attention_mask diff --git a/LAVT-RIS/donghwa/dataset_refer_bert_mosaic.py b/LAVT-RIS/donghwa/dataset_refer_bert_mosaic.py new file mode 100644 index 0000000000000000000000000000000000000000..3e6c0332c695afedfd19e473dfc4cc1fad96b53c --- /dev/null +++ b/LAVT-RIS/donghwa/dataset_refer_bert_mosaic.py @@ -0,0 +1,337 @@ +import os +import sys +import cv2 +import math +import glob +import json +import random +import pickle +import numpy as np +import pandas as pd + +from PIL import Image, ImageDraw, ImageFilter +from bert.tokenization_bert import BertTokenizer + +import albumentations as A +from albumentations.pytorch import ToTensorV2 + +import torch, gc +import torch.utils.data as data +gc.collect() +torch.cuda.empty_cache() + +# class aug: +# num_bgs = 4 +# aug_prob = 0.5 +# num_anchors = 0 +# random_target = False +# blur = False +# feature_path = None +# lower = 0 +# upper = 100 +# move_crs_pnt = False +# tgt_selection = 'fixed' + +class ReferDataset(data.Dataset): + + def __init__(self, + args, + split='train', + eval_mode=False): + + self.classes = [] + self.args = args + self.split = split + self.aug = args.aug + self.img_sz = args.img_size + + each_img_sz = int(args.img_size/math.sqrt(self.aug.num_bgs)) + mean = (0.485, 0.456, 0.406) + std = (0.229, 0.224, 0.225) + + self.resize_bg1 = A.Compose([ + A.Resize(args.img_size, args.img_size, always_apply=True)]) + + self.resize_bg4 = A.Compose([ + A.Resize(each_img_sz, each_img_sz, always_apply=True)], + additional_targets={'image1': 'image', 'image2': 'image', 'image3': 'image', + 'mask1': 'mask', 'mask2': 'mask', 'mask3': 'mask',}) + + self.transforms = A.Compose([ + A.Normalize(mean=mean, std=std), + ToTensorV2 (), + ]) + + # load annotations + if args.dataset == 'refcocog' and args.split in ['testA', 'testB']: + print(f"Easy & Hard Example Experiments - dataset : {args.dataset}, split : {args.split}") + from refer.refer_test import REFER + self.refer = REFER(args.refer_data_root, args.dataset, args.splitBy) + else : + from refer.refer import REFER + self.refer = REFER(args.refer_data_root, args.dataset, args.splitBy) + ref_ids = self.refer.getRefIds(split=self.split) + img_ids = self.refer.getImgIds(ref_ids) + all_imgs = self.refer.Imgs + self.imgs = list(all_imgs[i] for i in img_ids) + self.ref_ids = ref_ids #[:50] # for debug + self.ref_id2idx = dict(zip(ref_ids, range(len(ref_ids)))) + self.ref_idx2id = dict(zip(range(len(ref_ids)), ref_ids)) + + # tokenizer setting + # if args.text_encoder.model=='bert': + self.tokenizer = BertTokenizer.from_pretrained('bert-base-uncased') + # elif args.text_encoder.model=='roberta': + # self.tokenizer = RobertaTokenizerFast.from_pretrained(args.text_encoder.tokenizer) + # elif args.text_encoder.model=='clip': + # self.tokenizer = AutoTokenizer.from_pretrained(args.text_encoder.tokenizer) + # elif args.text_encoder.model=='llama': + # self.tokenizer = AutoTokenizer.from_pretrained(args.text_encoder.tokenizer) + + # self.tokenizer.add_special_tokens({'additional_special_tokens': task_tokens}) + # self.tokenizer.add_tokens(position_tokens) + + # if we are testing on a dataset, test all sentences of an object; + # o/w, we are validating during training, randomly sample one sentence for efficiency + self.max_tokens = 20 + self.eval_mode = False if split=='train' else True + self.input_ids = [] + self.attention_masks = [] + for i, r in enumerate(ref_ids): + ref = self.refer.Refs[r] + + sentences_for_ref = [] + attentions_for_ref = [] + for j, (el, sent_id) in enumerate(zip(ref['sentences'], ref['sent_ids'])): + sentence_raw = el['raw'] + input_ids = self.tokenizer.encode(text=sentence_raw, add_special_tokens=True, max_length=self.max_tokens, truncation=True) + #input_ids = input_ids[:self.max_tokens] + padded_input_ids = [0] * self.max_tokens + padded_input_ids[:len(input_ids)] = input_ids + attention_mask = [0] * self.max_tokens + attention_mask[:len(input_ids)] = [1]*len(input_ids) + sentences_for_ref.append(padded_input_ids) + attentions_for_ref.append(attention_mask) + + self.input_ids.append(sentences_for_ref) + self.attention_masks.append(attentions_for_ref) + + if self.aug.blur: + self.blur = ImageFilter.GaussianBlur(100) + + np.random.seed() + + def get_classes(self): + return self.classes + + def __len__(self): + return len(self.ref_ids) + + def __getitem__(self, index): + + # decide mosaic size + if self.split=='train': + if self.aug.num_bgs==4: + aug_prob = self.aug.aug_prob + num_bgs = np.random.choice([1, 4], p=[1-aug_prob, aug_prob]) + else: + num_bgs = 1 + else: + num_bgs = 1 + + target_sent_idx = np.random.choice(len(self.input_ids[index])) + + if num_bgs==1: + ref_ids = [] + sent_idxs = [] + sents = np.array([], dtype='str') + + else: + # if self.aug.feature_path: + # num_abgs = 3 #np.random.randint(low=0, high=num_bgs) + # item = self.h5.select('scores', where=f'ref_id=={self.ref_ids[index]} & sent_idx=={target_sent_idx}') + # score = np.asarray(json.loads(item['sim_scores'].values[0])) + # lower = self.aug.lower #np.percentile(score, self.aug.lower) + # upper = self.aug.upper #np.percentile(score, self.aug.upper) + # top_k_idxs = np.asarray(json.loads(item['top_k_idxs_corpus'].values[0])) + # cands = top_k_idxs[np.all([score=lower], axis=0)] + + # try: + # idx_list = list(np.random.choice(np.arange(len(cands)), + # size=num_abgs, replace=False)) + # cands_picked = [cands[x] for x in idx_list] + # #scores_picked = [score[score_mask][x] for x in idx_list] + # np.random.shuffle(cands_picked) + + # ref_ids = [x[0] for x in cands_picked] + # sent_idxs = [x[1] for x in cands_picked] + # sents = [self.refer.Refs[x[0]]['sentences'][x[1]]['raw'] for x in cands_picked] # 비슷한 문장들 가지고옴 + # except Exception as e: + # ref_ids = list(np.random.choice(self.ref_ids, size=num_bgs-1, replace=False)) + # sent_idxs = [np.random.choice(len(self.refer.Refs[r]['sentences'])) for r in ref_ids] + # sents = np.array([self.refer.Refs[r]['sentences'][sent_idxs[i]]['raw'] for i, r in enumerate(ref_ids)], dtype='str') + # else: + ref_ids = list(np.random.choice(self.ref_ids, size=num_bgs-1, replace=False)) + sent_idxs = [np.random.choice(len(self.refer.Refs[r]['sentences'])) for r in ref_ids] + sents = np.array([self.refer.Refs[r]['sentences'][sent_idxs[i]]['raw'] for i, r in enumerate(ref_ids)], dtype='str') + + insert_idx = np.random.choice(range(num_bgs)) + ref_ids = np.insert(ref_ids, insert_idx, self.ref_idx2id[index]).astype(int) + sents = np.insert(sents, insert_idx, + self.refer.Refs[ref_ids[insert_idx]]['sentences'][target_sent_idx]['raw']) + sent_idxs = np.insert(sent_idxs, insert_idx, target_sent_idx).astype(int) + + # pick a target origin + if self.aug.tgt_selection == 'random': + target_idx = np.random.choice(range(num_bgs)) + target_ref_idx = self.ref_id2idx[ref_ids[target_idx]] + target_sent_idx = int(np.random.choice(len(self.input_ids[target_ref_idx]))) + elif self.aug.tgt_selection == 'longest': + target_idx = np.argmax(list(map(len, sents))) + target_sent_idx = sent_idxs[target_idx] + elif self.aug.tgt_selection == 'fixed': + target_idx = insert_idx + target_ref_id = ref_ids[target_idx] + + # load items + imgs, masks = [], [] + for ref_id in ref_ids: + img_id = self.refer.getImgIds([ref_id])[0] + img_info = self.refer.Imgs[img_id] + img_path = os.path.join(self.refer.IMAGE_DIR, img_info['file_name']) + + img = Image.open(img_path).convert("RGB") + imgs.append(np.array(img)) + ref = self.refer.loadRefs(ref_ids=[ref_id]) + mask = np.array(self.refer.getMask(ref[0])['mask']) + masks.append(mask) + + # image resize and apply 4in1 augmentation + if num_bgs==1: + resized = self.resize_bg1(image=imgs[0], mask=masks[0]) + imgs, masks = [resized['image']], [resized['mask']] + img = imgs[0] + else: + + if self.aug.move_crs_pnt: + crs_y = np.random.randint(0, self.img_sz+1) + crs_x = np.random.randint(0, self.img_sz+1) + else: + crs_y = 480//2 # + crs_x = 480//2 # + + if crs_y==0 or crs_x==0: + img1 = np.zeros([0,crs_x,3]) if crs_y==0 else np.zeros([crs_y,0,3]) + mask1 = np.zeros([0,crs_x]) if crs_y==0 else np.zeros([crs_y,0]) + else: + resize_bg1 = A.Compose([A.Resize(crs_y, crs_x, always_apply=True)]) + temp = resize_bg1(image=imgs[0], mask=masks[0]) + img1 = temp['image'] + mask1 = temp['mask'] + + if crs_y==0 or crs_x==self.img_sz: + img2 = np.zeros([0,self.img_sz-crs_x,3]) if crs_y==0 \ + else np.zeros([crs_y,0,3]) + mask2 = np.zeros([0,self.img_sz-crs_x]) if crs_y==0 \ + else np.zeros([crs_y,0]) + else: + resize_bg2 = A.Compose([ + A.Resize(crs_y, self.img_sz-crs_x, always_apply=True)]) + temp = resize_bg2(image=imgs[1], mask=masks[1]) + img2 = temp['image'] + mask2 = temp['mask'] + + if crs_y==self.img_sz or crs_x==0: + img3 = np.zeros([0,crs_x,3]) if crs_y==self.img_sz \ + else np.zeros([self.img_sz-crs_y,0,3]) + mask3 = np.zeros([0,crs_x]) if crs_y==self.img_sz \ + else np.zeros([self.img_sz-crs_y,0]) + else: + resize_bg3 = A.Compose([ + A.Resize(self.img_sz-crs_y, crs_x, always_apply=True)]) + temp = resize_bg3(image=imgs[2], mask=masks[2]) + img3 = temp['image'] + mask3 = temp['mask'] + + if crs_y==self.img_sz or crs_x==self.img_sz: + img4 = np.zeros([0,self.img_sz-crs_x,3]) if crs_y==self.img_sz \ + else np.zeros([self.img_sz-crs_y,0,3]) + mask4 = np.zeros([0,self.img_sz-crs_x]) if crs_y==self.img_sz \ + else np.zeros([self.img_sz-crs_y,0]) + else: + resize_bg4 = A.Compose([ + A.Resize(self.img_sz-crs_y, + self.img_sz-crs_x, always_apply=True)]) + temp = resize_bg4(image=imgs[3], mask=masks[3]) + img4 = temp['image'] + mask4 = temp['mask'] + + imgs = [img1, img2, img3, img4] + masks = [mask1, mask2, mask3, mask4] + # imgs = [bg1['image'], bg2['image'], bg3['image'], bg4['image']] + # masks = [bg1['mask'], bg2['mask'], bg3['mask'], bg4['mask']] + + # resized = self.resize_bg4(image=imgs[0], mask=masks[0], + # image1=imgs[1], mask1=masks[1], + # image2=imgs[2], mask2=masks[2], + # image3=imgs[3], mask3=masks[3]) + # imgs = [resized['image'], resized['image1'], resized['image2'], resized['image3']] + # masks = [resized['mask'], resized['mask1'], resized['mask2'], resized['mask3']] + + # scale effect ablation + if self.aug.blur: + imgs = [np.asarray(Image.fromarray(x).filter(self.blur)) if i!=insert_idx else x for i, x in enumerate(imgs)] + + num_rows = num_cols = int(math.sqrt(num_bgs)) + idxs = [(i*num_cols,i*num_cols+num_cols) for i in range(num_rows)] + img = [np.concatenate(imgs[_from:_to], axis=1) for (_from, _to) in idxs] + img = np.concatenate(img, axis=0).astype(np.uint8) + + masks_arr = [] + for bg_idx in range(num_bgs): + mask = masks[bg_idx] + temp = [mask if idx==bg_idx else np.zeros_like(masks[idx]) for idx in range(num_bgs)] + mask = [np.concatenate(temp[_from:_to], axis=1) for (_from, _to) in idxs] + mask = np.concatenate(mask, axis=0).astype(np.int32) + masks_arr.append(mask) + masks = masks_arr + + mask = masks[target_idx] + mask = mask.astype(np.uint8) + mask[mask>0] = 1 + + item = self.transforms(image=img, mask=mask) + img_tensor = item['image'] + target = item['mask'].long() + + target_ref_idx = self.ref_id2idx[target_ref_id] + if self.eval_mode: + embedding = [] + att = [] + + for s in range(len(self.input_ids[target_ref_idx])): + padded_input_ids = self.input_ids[target_ref_idx][s] + #padded_input_ids = task_id + pos_id + padded_input_ids + tensor_embeddings = torch.tensor(padded_input_ids).unsqueeze(0) + + attention_mask = self.attention_masks[target_ref_idx][s] + attention_mask = torch.tensor(attention_mask).unsqueeze(0) + + embedding.append(tensor_embeddings.unsqueeze(-1)) + att.append(attention_mask.unsqueeze(-1)) + tensor_embeddings = torch.cat(embedding, dim=-1) + attention_mask = torch.cat(att, dim=-1) + else: + padded_input_ids = self.input_ids[target_ref_idx][target_sent_idx] + #padded_input_ids = task_id + pos_id + padded_input_ids + tensor_embeddings = torch.tensor(padded_input_ids).unsqueeze(0) + attention_mask = self.attention_masks[target_ref_idx][target_sent_idx] + attention_mask = torch.tensor(attention_mask).unsqueeze(0) + + item = { + 'image': img_tensor, + 'seg_target': target, + 'sentence': tensor_embeddings, + 'attn_mask': attention_mask + } + return item diff --git a/LAVT-RIS/donghwa/dataset_refer_bert_mosaic_retrieval.py b/LAVT-RIS/donghwa/dataset_refer_bert_mosaic_retrieval.py new file mode 100644 index 0000000000000000000000000000000000000000..9dd27bd39c352ad84a2575fb3eae9b17573f2030 --- /dev/null +++ b/LAVT-RIS/donghwa/dataset_refer_bert_mosaic_retrieval.py @@ -0,0 +1,378 @@ +import os +import sys +import cv2 +import math +import glob +import json +import random +import pickle +import numpy as np +import pandas as pd + +from PIL import Image, ImageDraw, ImageFilter +from bert.tokenization_bert import BertTokenizer + +import albumentations as A +from albumentations.pytorch import ToTensorV2 + +import torch, gc +import torch.utils.data as data + +import lmdb +import pyarrow as pa +import warnings +from .utils import get_warmup_value + +warnings.simplefilter(action='ignore', category=FutureWarning) +gc.collect() +torch.cuda.empty_cache() + + + +def loads_pyarrow(buf): + return pa.deserialize(buf) + + +class ReferDataset(data.Dataset): + + def __init__(self, + args, + split='train', + eval_mode=False): + + self.classes = [] + self.args = args + self.split = split + self.aug = args.aug + self.img_sz = args.img_size + + each_img_sz = int(args.img_size/math.sqrt(self.aug.num_bgs)) + mean = (0.485, 0.456, 0.406) + std = (0.229, 0.224, 0.225) + + self.resize_bg1 = A.Compose([ + A.Resize(args.img_size, args.img_size, always_apply=True)]) + + self.resize_bg4 = A.Compose([ + A.Resize(each_img_sz, each_img_sz, always_apply=True)], + additional_targets={'image1': 'image', 'image2': 'image', 'image3': 'image', + 'mask1': 'mask', 'mask2': 'mask', 'mask3': 'mask',}) + + self.transforms = A.Compose([ + A.Normalize(mean=mean, std=std), + ToTensorV2 (), + ]) + + # load annotations + if args.dataset == 'refcocog' and args.split in ['testA', 'testB']: + print(f"Easy & Hard Example Experiments - dataset : {args.dataset}, split : {args.split}") + from refer.refer_test import REFER + self.refer = REFER(args.refer_data_root, args.dataset, args.splitBy) + else : + from refer.refer import REFER + self.refer = REFER(args.refer_data_root, args.dataset, args.splitBy) + ref_ids = self.refer.getRefIds(split=self.split) + img_ids = self.refer.getImgIds(ref_ids) + all_imgs = self.refer.Imgs + self.imgs = list(all_imgs[i] for i in img_ids) + self.ref_ids = ref_ids#[:500] + self.ref_id2idx = dict(zip(ref_ids, range(len(ref_ids)))) + self.ref_idx2id = dict(zip(range(len(ref_ids)), ref_ids)) + + # tokenizer setting + # if args.text_encoder.model=='bert': + self.tokenizer = BertTokenizer.from_pretrained('bert-base-uncased') + # elif args.text_encoder.model=='roberta': + # self.tokenizer = RobertaTokenizerFast.from_pretrained(args.text_encoder.tokenizer) + # elif args.text_encoder.model=='clip': + # self.tokenizer = AutoTokenizer.from_pretrained(args.text_encoder.tokenizer) + # elif args.text_encoder.model=='llama': + # self.tokenizer = AutoTokenizer.from_pretrained(args.text_encoder.tokenizer) + + # self.tokenizer.add_special_tokens({'additional_special_tokens': task_tokens}) + # self.tokenizer.add_tokens(position_tokens) + + # if we are testing on a dataset, test all sentences of an object; + # o/w, we are validating during training, randomly sample one sentence for efficiency + self.max_tokens = 20 + self.eval_mode = eval_mode + self.input_ids = [] + self.attention_masks = [] + for i, r in enumerate(ref_ids): + ref = self.refer.Refs[r] + + sentences_for_ref = [] + attentions_for_ref = [] + for j, (el, sent_id) in enumerate(zip(ref['sentences'], ref['sent_ids'])): + sentence_raw = el['raw'] + input_ids = self.tokenizer.encode(text=sentence_raw, add_special_tokens=True, max_length=self.max_tokens, truncation=True) + #input_ids = input_ids[:self.max_tokens] + padded_input_ids = [0] * self.max_tokens + padded_input_ids[:len(input_ids)] = input_ids + attention_mask = [0] * self.max_tokens + attention_mask[:len(input_ids)] = [1]*len(input_ids) + sentences_for_ref.append(padded_input_ids) + attentions_for_ref.append(attention_mask) + + self.input_ids.append(sentences_for_ref) + self.attention_masks.append(attentions_for_ref) + + if self.aug.blur: + self.blur = ImageFilter.GaussianBlur(100) + + # Load mldb data + if args.dataset == 'refcoco': + lmdb_path = f'/data2/dataset/RefCOCO/logit_db/refcoco/refcoco_logit.lmdb' + elif args.dataset == 'refcoco+': + lmdb_path = f'/data2/dataset/RefCOCO/logit_db/refcoco+/refcocop_logit.lmdb' + elif args.dataset == 'refcocog' and args.splitBy == 'umd': + lmdb_path = f'/data2/dataset/RefCOCO/logit_db/refcocog_u/refcocog_u_logit.lmdb' + # elif args.datset == 'refcocog' and args.splitBy == 'google': + # lmdb_path = f'/data2/projects/donghwa/RIS/LAVT-RIS/data/logit_db/{args.dataset}/refcocog_g_logit.lmdb' + self.lmdb_env = lmdb.open( + lmdb_path, subdir=False, max_readers=32, + readonly=True, lock=False, + readahead=False, meminit=False) + with self.lmdb_env.begin(write=False) as txn: + self.length = loads_pyarrow(txn.get(b'__len__')) + self.keys = loads_pyarrow(txn.get(b'__keys__')) + + self.epoch = 0 + np.random.seed() + + def get_classes(self): + return self.classes + + def __len__(self): + return len(self.ref_ids) + + + def __getitem__(self, index): + + refid = self.ref_idx2id[index] + with self.lmdb_env.begin(write=False) as txn: + byteflow = txn.get(self.keys[refid]) + lmdb_dict = loads_pyarrow(byteflow) + + + # decide mosaic size + if self.split=='train': + if self.aug.num_bgs==4: + aug_prob = self.aug.aug_prob + # Before retrieval_iter: One Image or Random Mosaic + if self.epoch < self.aug.retrieval_epoch: + # num_bgs = np.random.choice([1, 4], p=[1-aug_prob, aug_prob]) + choice = np.random.choice(['one', 'random'], p=[1-aug_prob, aug_prob]) + else: + rand_prob = self.aug.rand_prob + retr_prob = self.aug.retr_prob + # After retrieval_iter: Decide between One Image, Random Mosaic, or Retrieval Based Mosaic + choice = np.random.choice(['one', 'random', 'retrieval'], p=[1-(rand_prob + retr_prob), rand_prob, retr_prob]) + + if choice == 'one': + num_bgs = 1 + else: + num_bgs = 4 + else: + num_bgs = 1 + choice = 'one' + else: # test, val + num_bgs = 1 + choice = 'one' + + target_sent_idx = np.random.choice(len(self.input_ids[index])) + ref_id = self.ref_idx2id[index] + insert_idx = np.random.choice(range(num_bgs)) + + if num_bgs==1: + ref_ids = [] + sent_idxs = [] + sents = np.array([], dtype='str') + img_ids = [self.refer.Refs[ref_id]['image_id']] + + else: + if choice == 'retrieval': + sent_id = list(lmdb_dict.keys())[target_sent_idx] + img_ids = list(np.random.choice(lmdb_dict[sent_id][:self.aug.top_k], size=num_bgs-1, replace=True)) + img_ids = np.insert(img_ids, insert_idx, self.refer.Refs[ref_id]['image_id']) + + ref_ids = list(np.random.choice(self.ref_ids, size=num_bgs-1, replace=False)) + sent_idxs = [np.random.choice(len(self.refer.Refs[r]['sentences'])) for r in ref_ids] + sents = np.array([self.refer.Refs[r]['sentences'][sent_idxs[i]]['raw'] for i, r in enumerate(ref_ids)], dtype='str') + + ref_ids = np.insert(ref_ids, insert_idx, self.ref_idx2id[index]).astype(int) + sents = np.insert(sents, insert_idx, + self.refer.Refs[ref_ids[insert_idx]]['sentences'][target_sent_idx]['raw']) + sent_idxs = np.insert(sent_idxs, insert_idx, target_sent_idx).astype(int) + + + # pick a target origin + if self.aug.tgt_selection == 'random': + target_idx = np.random.choice(range(num_bgs)) + target_ref_idx = self.ref_id2idx[ref_ids[target_idx]] + target_sent_idx = int(np.random.choice(len(self.input_ids[target_ref_idx]))) + elif self.aug.tgt_selection == 'longest': + target_idx = np.argmax(list(map(len, sents))) + target_sent_idx = sent_idxs[target_idx] + elif self.aug.tgt_selection == 'fixed': + target_idx = insert_idx + # target_ref_id = ref_ids[target_idx] + target_ref_id = self.ref_idx2id[index] + + + # load items + imgs, masks = [], [] + if choice == 'retrieval': + # for ref_id in ref_ids: + for img_id in img_ids: + # img_id = self.refer.getImgIds([ref_id])[0] + img_info = self.refer.Imgs[img_id] + img_path = os.path.join(self.refer.IMAGE_DIR, img_info['file_name']) + + img = Image.open(img_path).convert("RGB") + imgs.append(np.array(img)) + ref = self.refer.imgToRefs[img_id][0] + mask = np.array(self.refer.getMask(ref)['mask']) + masks.append(mask) + else : + for ref_id in ref_ids: + # for img_id in img_ids: + img_id = self.refer.getImgIds([ref_id])[0] + img_info = self.refer.Imgs[img_id] + img_path = os.path.join(self.refer.IMAGE_DIR, img_info['file_name']) + + img = Image.open(img_path).convert("RGB") + imgs.append(np.array(img)) + ref = self.refer.loadRefs(ref_ids=[ref_id]) + mask = np.array(self.refer.getMask(ref[0])['mask']) + masks.append(mask) + + # image resize and apply 4in1 augmentation + if num_bgs==1: + resized = self.resize_bg1(image=imgs[0], mask=masks[0]) + imgs, masks = [resized['image']], [resized['mask']] + img = imgs[0] + else: + + if self.aug.move_crs_pnt: + crs_y = np.random.randint(0, self.img_sz+1) + crs_x = np.random.randint(0, self.img_sz+1) + else: + crs_y = 480//2 # + crs_x = 480//2 # + + if crs_y==0 or crs_x==0: + img1 = np.zeros([0,crs_x,3]) if crs_y==0 else np.zeros([crs_y,0,3]) + mask1 = np.zeros([0,crs_x]) if crs_y==0 else np.zeros([crs_y,0]) + else: + resize_bg1 = A.Compose([A.Resize(crs_y, crs_x, always_apply=True)]) + temp = resize_bg1(image=imgs[0], mask=masks[0]) + img1 = temp['image'] + mask1 = temp['mask'] + + if crs_y==0 or crs_x==self.img_sz: + img2 = np.zeros([0,self.img_sz-crs_x,3]) if crs_y==0 \ + else np.zeros([crs_y,0,3]) + mask2 = np.zeros([0,self.img_sz-crs_x]) if crs_y==0 \ + else np.zeros([crs_y,0]) + else: + resize_bg2 = A.Compose([ + A.Resize(crs_y, self.img_sz-crs_x, always_apply=True)]) + temp = resize_bg2(image=imgs[1], mask=masks[1]) + img2 = temp['image'] + mask2 = temp['mask'] + + if crs_y==self.img_sz or crs_x==0: + img3 = np.zeros([0,crs_x,3]) if crs_y==self.img_sz \ + else np.zeros([self.img_sz-crs_y,0,3]) + mask3 = np.zeros([0,crs_x]) if crs_y==self.img_sz \ + else np.zeros([self.img_sz-crs_y,0]) + else: + resize_bg3 = A.Compose([ + A.Resize(self.img_sz-crs_y, crs_x, always_apply=True)]) + temp = resize_bg3(image=imgs[2], mask=masks[2]) + img3 = temp['image'] + mask3 = temp['mask'] + + if crs_y==self.img_sz or crs_x==self.img_sz: + img4 = np.zeros([0,self.img_sz-crs_x,3]) if crs_y==self.img_sz \ + else np.zeros([self.img_sz-crs_y,0,3]) + mask4 = np.zeros([0,self.img_sz-crs_x]) if crs_y==self.img_sz \ + else np.zeros([self.img_sz-crs_y,0]) + else: + resize_bg4 = A.Compose([ + A.Resize(self.img_sz-crs_y, + self.img_sz-crs_x, always_apply=True)]) + temp = resize_bg4(image=imgs[3], mask=masks[3]) + img4 = temp['image'] + mask4 = temp['mask'] + + imgs = [img1, img2, img3, img4] + masks = [mask1, mask2, mask3, mask4] + # imgs = [bg1['image'], bg2['image'], bg3['image'], bg4['image']] + # masks = [bg1['mask'], bg2['mask'], bg3['mask'], bg4['mask']] + + # resized = self.resize_bg4(image=imgs[0], mask=masks[0], + # image1=imgs[1], mask1=masks[1], + # image2=imgs[2], mask2=masks[2], + # image3=imgs[3], mask3=masks[3]) + # imgs = [resized['image'], resized['image1'], resized['image2'], resized['image3']] + # masks = [resized['mask'], resized['mask1'], resized['mask2'], resized['mask3']] + + # scale effect ablation + if self.aug.blur: + imgs = [np.asarray(Image.fromarray(x).filter(self.blur)) if i!=insert_idx else x for i, x in enumerate(imgs)] + + num_rows = num_cols = int(math.sqrt(num_bgs)) + idxs = [(i*num_cols,i*num_cols+num_cols) for i in range(num_rows)] + img = [np.concatenate(imgs[_from:_to], axis=1) for (_from, _to) in idxs] + img = np.concatenate(img, axis=0).astype(np.uint8) + + masks_arr = [] + for bg_idx in range(num_bgs): + mask = masks[bg_idx] + temp = [mask if idx==bg_idx else np.zeros_like(masks[idx]) for idx in range(num_bgs)] + mask = [np.concatenate(temp[_from:_to], axis=1) for (_from, _to) in idxs] + mask = np.concatenate(mask, axis=0).astype(np.int32) + masks_arr.append(mask) + masks = masks_arr + + mask = masks[target_idx] + mask = mask.astype(np.uint8) + mask[mask>0] = 1 + + item = self.transforms(image=img, mask=mask) + img_tensor = item['image'] + target = item['mask'].long() + + target_ref_idx = self.ref_id2idx[target_ref_id] + if self.eval_mode: + embedding = [] + att = [] + + for s in range(len(self.input_ids[target_ref_idx])): + padded_input_ids = self.input_ids[target_ref_idx][s] + #padded_input_ids = task_id + pos_id + padded_input_ids + tensor_embeddings = torch.tensor(padded_input_ids).unsqueeze(0) + + attention_mask = self.attention_masks[target_ref_idx][s] + attention_mask = torch.tensor(attention_mask).unsqueeze(0) + + embedding.append(tensor_embeddings.unsqueeze(-1)) + att.append(attention_mask.unsqueeze(-1)) + tensor_embeddings = torch.cat(embedding, dim=-1) + attention_mask = torch.cat(att, dim=-1) + else: + padded_input_ids = self.input_ids[target_ref_idx][target_sent_idx] + #padded_input_ids = task_id + pos_id + padded_input_ids + tensor_embeddings = torch.tensor(padded_input_ids).unsqueeze(0) + attention_mask = self.attention_masks[target_ref_idx][target_sent_idx] + attention_mask = torch.tensor(attention_mask).unsqueeze(0) + + item = { + 'image': img_tensor, + 'seg_target': target, + 'sentence': tensor_embeddings, + 'attn_mask': attention_mask + } + return item diff --git a/LAVT-RIS/donghwa/dataset_refer_bert_mosaic_retrieval_filter.py b/LAVT-RIS/donghwa/dataset_refer_bert_mosaic_retrieval_filter.py new file mode 100644 index 0000000000000000000000000000000000000000..092abf49d98a0597156ed81a9b841ddcc895a64c --- /dev/null +++ b/LAVT-RIS/donghwa/dataset_refer_bert_mosaic_retrieval_filter.py @@ -0,0 +1,418 @@ +import os +import sys +import cv2 +import math +import glob +import json +import random +import pickle +import numpy as np +import pandas as pd + +from PIL import Image, ImageDraw, ImageFilter +from bert.tokenization_bert import BertTokenizer + +import albumentations as A +from albumentations.pytorch import ToTensorV2 + +import torch, gc +import torch.utils.data as data + +import lmdb +import pyarrow as pa +import warnings +from .utils import get_warmup_value + +warnings.simplefilter(action='ignore', category=FutureWarning) +gc.collect() +torch.cuda.empty_cache() + + + +def loads_pyarrow(buf): + return pa.deserialize(buf) + + +class ReferDataset(data.Dataset): + + def __init__(self, + args, + split='train', + eval_mode=False): + + self.classes = [] + self.args = args + self.split = split + self.aug = args.aug + self.img_sz = args.img_size + + each_img_sz = int(args.img_size/math.sqrt(self.aug.num_bgs)) + mean = (0.485, 0.456, 0.406) + std = (0.229, 0.224, 0.225) + + self.resize_bg1 = A.Compose([ + A.Resize(args.img_size, args.img_size, always_apply=True)]) + + self.resize_bg4 = A.Compose([ + A.Resize(each_img_sz, each_img_sz, always_apply=True)], + additional_targets={'image1': 'image', 'image2': 'image', 'image3': 'image', + 'mask1': 'mask', 'mask2': 'mask', 'mask3': 'mask',}) + + self.transforms = A.Compose([ + A.Normalize(mean=mean, std=std), + ToTensorV2 (), + ]) + + # load annotations + if args.dataset == 'refcocog' and args.split in ['testA', 'testB']: + print(f"Easy & Hard Example Experiments - dataset : {args.dataset}, split : {args.split}") + from refer.refer_test import REFER + self.refer = REFER(args.refer_data_root, args.dataset, args.splitBy) + else : + from refer.refer import REFER + self.refer = REFER(args.refer_data_root, args.dataset, args.splitBy) + ref_ids = self.refer.getRefIds(split=self.split) + img_ids = self.refer.getImgIds(ref_ids) + img_ids.sort() + all_imgs = self.refer.Imgs + self.imgs = list(all_imgs[i] for i in img_ids) + self.ref_ids = ref_ids#[:500] + self.ref_id2idx = dict(zip(ref_ids, range(len(ref_ids)))) + self.ref_idx2id = dict(zip(range(len(ref_ids)), ref_ids)) + + # lmdb img2img + self.img_id2idx = dict(zip(img_ids, range(len(img_ids)))) # ref_id -> idx(key) + self.idx2img_id = dict(zip(range(len(img_ids)), img_ids)) # idx(key) -> ref_id + + # tokenizer setting + # if args.text_encoder.model=='bert': + self.tokenizer = BertTokenizer.from_pretrained('bert-base-uncased') + # elif args.text_encoder.model=='roberta': + # self.tokenizer = RobertaTokenizerFast.from_pretrained(args.text_encoder.tokenizer) + # elif args.text_encoder.model=='clip': + # self.tokenizer = AutoTokenizer.from_pretrained(args.text_encoder.tokenizer) + # elif args.text_encoder.model=='llama': + # self.tokenizer = AutoTokenizer.from_pretrained(args.text_encoder.tokenizer) + + # self.tokenizer.add_special_tokens({'additional_special_tokens': task_tokens}) + # self.tokenizer.add_tokens(position_tokens) + + # if we are testing on a dataset, test all sentences of an object; + # o/w, we are validating during training, randomly sample one sentence for efficiency + self.max_tokens = 20 + self.eval_mode = eval_mode + self.input_ids = [] + self.attention_masks = [] + for i, r in enumerate(ref_ids): + ref = self.refer.Refs[r] + + sentences_for_ref = [] + attentions_for_ref = [] + for j, (el, sent_id) in enumerate(zip(ref['sentences'], ref['sent_ids'])): + sentence_raw = el['raw'] + input_ids = self.tokenizer.encode(text=sentence_raw, add_special_tokens=True, max_length=self.max_tokens, truncation=True) + #input_ids = input_ids[:self.max_tokens] + padded_input_ids = [0] * self.max_tokens + padded_input_ids[:len(input_ids)] = input_ids + attention_mask = [0] * self.max_tokens + attention_mask[:len(input_ids)] = [1]*len(input_ids) + sentences_for_ref.append(padded_input_ids) + attentions_for_ref.append(attention_mask) + + self.input_ids.append(sentences_for_ref) + self.attention_masks.append(attentions_for_ref) + + if self.aug.blur: + self.blur = ImageFilter.GaussianBlur(100) + + # retrieval filtering + if args.dataset == 'refcocog' and args.splitBy == 'umd': + img2img_path = '/data2/projects/chaeyun/CRIS_R/logit_db/refcocog_u/refcocog_u_logit_i2i_score.lmdb' + text2img_path = '/data2/projects/chaeyun/CRIS_R/logit_db/refcocog_u/refcocog_u_logit_t2i_score.lmdb' + elif args.datset == 'refcocog' and args.splitBy == 'google': + img2img_path = '/data2/projects/chaeyun/CRIS_R/logit_db/refcocog_g/refcocog_g_logit_i2i_score_5k.lmdb' + text2img_path = '/data2/projects/chaeyun/CRIS_R/logit_db/refcocog_g/refcocog_g_logit_t2i_score.lmdb' + elif args.dataset == 'refcoco' : + img2img_path = '/data2/projects/chaeyun/CRIS_R/logit_db/refcoco/refcoco_logit_i2i_score_5k.lmdb' + text2img_path = '/data2/projects/chaeyun/CRIS_R/logit_db/refcoco/refcoco_logit_t2i_score.lmdb' + elif args.dataset == 'refcoco+' : + img2img_path = '/data2/projects/chaeyun/CRIS_R/logit_db/refcoco+/refcocop_logit_i2i_score_5k.lmdb' + text2img_path = '/data2/projects/chaeyun/CRIS_R/logit_db/refcoco+/refcocop_logit_t2i_score.lmdb' + else : + img2img_path = '' + text2img_path = '' + + self.i2i_env = lmdb.open( + img2img_path, subdir=False, max_readers=32, + readonly=True, lock=False, + readahead=False, meminit=False + ) + self.t2i_env = lmdb.open( + text2img_path, subdir=False, max_readers=32, + readonly=True, lock=False, + readahead=False, meminit=False + ) + + with self.i2i_env.begin(write=False) as txn: + logit_length_i = loads_pyarrow(txn.get(b'__len__')) + self.logit_keys_i = loads_pyarrow(txn.get(b'__keys__')) + + with self.t2i_env.begin(write=False) as txn: + logit_length = loads_pyarrow(txn.get(b'__len__')) + self.logit_keys = loads_pyarrow(txn.get(b'__keys__')) + + + self.epoch = 0 + np.random.seed() + + def get_classes(self): + return self.classes + + def __len__(self): + return len(self.ref_ids) + + + def __getitem__(self, index): + + + # retrieval filtering + ref_id = self.ref_idx2id[index] + ref_img_id = self.refer.Refs[ref_id]['image_id'] + i2i_index = self.img_id2idx[ref_img_id] + + with self.i2i_env.begin(write=False) as txn: + i2i_byteflow = txn.get(self.logit_keys_i[i2i_index]) + i2i_similarity = loads_pyarrow(i2i_byteflow) + invalid_choices = set([img_id for img_id, score in i2i_similarity if score > self.aug.sim_thres]) + + t2i_index = self.ref_id2idx[ref_id] + with self.t2i_env.begin(write=False) as txn: + t2i_byteflow = txn.get(self.logit_keys[t2i_index]) + t2i_similarity = loads_pyarrow(t2i_byteflow) + + + # decide mosaic size + if self.split=='train': + if self.aug.num_bgs==4: + aug_prob = self.aug.aug_prob + # Before retrieval_iter: One Image or Random Mosaic + if self.epoch < self.aug.retrieval_epoch: + # num_bgs = np.random.choice([1, 4], p=[1-aug_prob, aug_prob]) + choice = np.random.choice(['one', 'random'], p=[1-aug_prob, aug_prob]) + else: + rand_prob = self.aug.rand_prob + retr_prob = self.aug.retr_prob + # After retrieval_iter: Decide between One Image, Random Mosaic, or Retrieval Based Mosaic + choice = np.random.choice(['one', 'random', 'retrieval'], p=[1-(rand_prob + retr_prob), rand_prob, retr_prob]) + + if choice == 'one': + num_bgs = 1 + else: + num_bgs = 4 + else: + num_bgs = 1 + choice = 'one' + else: # test, val + num_bgs = 1 + choice = 'one' + + target_sent_idx = np.random.choice(len(self.input_ids[index])) + ref_id = self.ref_idx2id[index] + insert_idx = np.random.choice(range(num_bgs)) + + if num_bgs==1: + ref_ids = [] + sent_idxs = [] + sents = np.array([], dtype='str') + img_ids = [self.refer.Refs[ref_id]['image_id']] + + else: + if choice == 'retrieval': + # sent_id = list(lmdb_dict.keys())[target_sent_idx] + # img_ids = list(np.random.choice(lmdb_dict[sent_id], size=num_bgs-1, replace=True)) + # img_ids = np.insert(img_ids, insert_idx, self.refer.Refs[ref_id]['image_id']) + sent_id = list(t2i_similarity.keys())[target_sent_idx] + valid_img_score_list = [pair[0] for pair in t2i_similarity[sent_id] if pair[0] not in invalid_choices] + img_ids = list(np.random.choice(valid_img_score_list[:self.aug.top_k], size=num_bgs-1, replace=True)) + img_ids = np.insert(img_ids, insert_idx, self.refer.Refs[ref_id]['image_id']) + + ref_ids = list(np.random.choice(self.ref_ids, size=num_bgs-1, replace=False)) + sent_idxs = [np.random.choice(len(self.refer.Refs[r]['sentences'])) for r in ref_ids] + sents = np.array([self.refer.Refs[r]['sentences'][sent_idxs[i]]['raw'] for i, r in enumerate(ref_ids)], dtype='str') + + ref_ids = np.insert(ref_ids, insert_idx, self.ref_idx2id[index]).astype(int) + sents = np.insert(sents, insert_idx, + self.refer.Refs[ref_ids[insert_idx]]['sentences'][target_sent_idx]['raw']) + sent_idxs = np.insert(sent_idxs, insert_idx, target_sent_idx).astype(int) + + + # pick a target origin + if self.aug.tgt_selection == 'random': + target_idx = np.random.choice(range(num_bgs)) + target_ref_idx = self.ref_id2idx[ref_ids[target_idx]] + target_sent_idx = int(np.random.choice(len(self.input_ids[target_ref_idx]))) + elif self.aug.tgt_selection == 'longest': + target_idx = np.argmax(list(map(len, sents))) + target_sent_idx = sent_idxs[target_idx] + elif self.aug.tgt_selection == 'fixed': + target_idx = insert_idx + # target_ref_id = ref_ids[target_idx] + target_ref_id = self.ref_idx2id[index] + + + # load items + imgs, masks = [], [] + if choice == 'retrieval': + # for ref_id in ref_ids: + for img_id in img_ids: + # img_id = self.refer.getImgIds([ref_id])[0] + img_info = self.refer.Imgs[img_id] + img_path = os.path.join(self.refer.IMAGE_DIR, img_info['file_name']) + + img = Image.open(img_path).convert("RGB") + imgs.append(np.array(img)) + ref = self.refer.imgToRefs[img_id][0] + mask = np.array(self.refer.getMask(ref)['mask']) + masks.append(mask) + else : + for ref_id in ref_ids: + # for img_id in img_ids: + img_id = self.refer.getImgIds([ref_id])[0] + img_info = self.refer.Imgs[img_id] + img_path = os.path.join(self.refer.IMAGE_DIR, img_info['file_name']) + + img = Image.open(img_path).convert("RGB") + imgs.append(np.array(img)) + ref = self.refer.loadRefs(ref_ids=[ref_id]) + mask = np.array(self.refer.getMask(ref[0])['mask']) + masks.append(mask) + + # image resize and apply 4in1 augmentation + if num_bgs==1: + resized = self.resize_bg1(image=imgs[0], mask=masks[0]) + imgs, masks = [resized['image']], [resized['mask']] + img = imgs[0] + else: + + if self.aug.move_crs_pnt: + crs_y = np.random.randint(0, self.img_sz+1) + crs_x = np.random.randint(0, self.img_sz+1) + else: + crs_y = 480//2 # + crs_x = 480//2 # + + if crs_y==0 or crs_x==0: + img1 = np.zeros([0,crs_x,3]) if crs_y==0 else np.zeros([crs_y,0,3]) + mask1 = np.zeros([0,crs_x]) if crs_y==0 else np.zeros([crs_y,0]) + else: + resize_bg1 = A.Compose([A.Resize(crs_y, crs_x, always_apply=True)]) + temp = resize_bg1(image=imgs[0], mask=masks[0]) + img1 = temp['image'] + mask1 = temp['mask'] + + if crs_y==0 or crs_x==self.img_sz: + img2 = np.zeros([0,self.img_sz-crs_x,3]) if crs_y==0 \ + else np.zeros([crs_y,0,3]) + mask2 = np.zeros([0,self.img_sz-crs_x]) if crs_y==0 \ + else np.zeros([crs_y,0]) + else: + resize_bg2 = A.Compose([ + A.Resize(crs_y, self.img_sz-crs_x, always_apply=True)]) + temp = resize_bg2(image=imgs[1], mask=masks[1]) + img2 = temp['image'] + mask2 = temp['mask'] + + if crs_y==self.img_sz or crs_x==0: + img3 = np.zeros([0,crs_x,3]) if crs_y==self.img_sz \ + else np.zeros([self.img_sz-crs_y,0,3]) + mask3 = np.zeros([0,crs_x]) if crs_y==self.img_sz \ + else np.zeros([self.img_sz-crs_y,0]) + else: + resize_bg3 = A.Compose([ + A.Resize(self.img_sz-crs_y, crs_x, always_apply=True)]) + temp = resize_bg3(image=imgs[2], mask=masks[2]) + img3 = temp['image'] + mask3 = temp['mask'] + + if crs_y==self.img_sz or crs_x==self.img_sz: + img4 = np.zeros([0,self.img_sz-crs_x,3]) if crs_y==self.img_sz \ + else np.zeros([self.img_sz-crs_y,0,3]) + mask4 = np.zeros([0,self.img_sz-crs_x]) if crs_y==self.img_sz \ + else np.zeros([self.img_sz-crs_y,0]) + else: + resize_bg4 = A.Compose([ + A.Resize(self.img_sz-crs_y, + self.img_sz-crs_x, always_apply=True)]) + temp = resize_bg4(image=imgs[3], mask=masks[3]) + img4 = temp['image'] + mask4 = temp['mask'] + + imgs = [img1, img2, img3, img4] + masks = [mask1, mask2, mask3, mask4] + # imgs = [bg1['image'], bg2['image'], bg3['image'], bg4['image']] + # masks = [bg1['mask'], bg2['mask'], bg3['mask'], bg4['mask']] + + # resized = self.resize_bg4(image=imgs[0], mask=masks[0], + # image1=imgs[1], mask1=masks[1], + # image2=imgs[2], mask2=masks[2], + # image3=imgs[3], mask3=masks[3]) + # imgs = [resized['image'], resized['image1'], resized['image2'], resized['image3']] + # masks = [resized['mask'], resized['mask1'], resized['mask2'], resized['mask3']] + + # scale effect ablation + if self.aug.blur: + imgs = [np.asarray(Image.fromarray(x).filter(self.blur)) if i!=insert_idx else x for i, x in enumerate(imgs)] + + num_rows = num_cols = int(math.sqrt(num_bgs)) + idxs = [(i*num_cols,i*num_cols+num_cols) for i in range(num_rows)] + img = [np.concatenate(imgs[_from:_to], axis=1) for (_from, _to) in idxs] + img = np.concatenate(img, axis=0).astype(np.uint8) + + masks_arr = [] + for bg_idx in range(num_bgs): + mask = masks[bg_idx] + temp = [mask if idx==bg_idx else np.zeros_like(masks[idx]) for idx in range(num_bgs)] + mask = [np.concatenate(temp[_from:_to], axis=1) for (_from, _to) in idxs] + mask = np.concatenate(mask, axis=0).astype(np.int32) + masks_arr.append(mask) + masks = masks_arr + + mask = masks[target_idx] + mask = mask.astype(np.uint8) + mask[mask>0] = 1 + + item = self.transforms(image=img, mask=mask) + img_tensor = item['image'] + target = item['mask'].long() + + target_ref_idx = self.ref_id2idx[target_ref_id] + if self.eval_mode: + embedding = [] + att = [] + + for s in range(len(self.input_ids[target_ref_idx])): + padded_input_ids = self.input_ids[target_ref_idx][s] + #padded_input_ids = task_id + pos_id + padded_input_ids + tensor_embeddings = torch.tensor(padded_input_ids).unsqueeze(0) + + attention_mask = self.attention_masks[target_ref_idx][s] + attention_mask = torch.tensor(attention_mask).unsqueeze(0) + + embedding.append(tensor_embeddings.unsqueeze(-1)) + att.append(attention_mask.unsqueeze(-1)) + tensor_embeddings = torch.cat(embedding, dim=-1) + attention_mask = torch.cat(att, dim=-1) + else: + padded_input_ids = self.input_ids[target_ref_idx][target_sent_idx] + #padded_input_ids = task_id + pos_id + padded_input_ids + tensor_embeddings = torch.tensor(padded_input_ids).unsqueeze(0) + attention_mask = self.attention_masks[target_ref_idx][target_sent_idx] + attention_mask = torch.tensor(attention_mask).unsqueeze(0) + + item = { + 'image': img_tensor, + 'seg_target': target, + 'sentence': tensor_embeddings, + 'attn_mask': attention_mask + } + return item diff --git a/LAVT-RIS/donghwa/dataset_refer_bert_mosaic_retrieval_warmup.py b/LAVT-RIS/donghwa/dataset_refer_bert_mosaic_retrieval_warmup.py new file mode 100644 index 0000000000000000000000000000000000000000..a819ca3d4ad74e21164083a1ac7e8a84753be30f --- /dev/null +++ b/LAVT-RIS/donghwa/dataset_refer_bert_mosaic_retrieval_warmup.py @@ -0,0 +1,380 @@ +import os +import sys +import cv2 +import math +import glob +import json +import random +import pickle +import numpy as np +import pandas as pd + +from PIL import Image, ImageDraw, ImageFilter +from bert.tokenization_bert import BertTokenizer + +import albumentations as A +from albumentations.pytorch import ToTensorV2 + +import torch, gc +import torch.utils.data as data + +import lmdb +import pyarrow as pa +import warnings +from .utils import get_warmup_value + +warnings.simplefilter(action='ignore', category=FutureWarning) +gc.collect() +torch.cuda.empty_cache() + + + +def loads_pyarrow(buf): + return pa.deserialize(buf) + + +class ReferDataset(data.Dataset): + + def __init__(self, + args, + split='train', + eval_mode=False): + + self.classes = [] + self.args = args + self.split = split + self.aug = args.aug + self.img_sz = args.img_size + + each_img_sz = int(args.img_size/math.sqrt(self.aug.num_bgs)) + mean = (0.485, 0.456, 0.406) + std = (0.229, 0.224, 0.225) + + self.resize_bg1 = A.Compose([ + A.Resize(args.img_size, args.img_size, always_apply=True)]) + + self.resize_bg4 = A.Compose([ + A.Resize(each_img_sz, each_img_sz, always_apply=True)], + additional_targets={'image1': 'image', 'image2': 'image', 'image3': 'image', + 'mask1': 'mask', 'mask2': 'mask', 'mask3': 'mask',}) + + self.transforms = A.Compose([ + A.Normalize(mean=mean, std=std), + ToTensorV2 (), + ]) + + # load annotations + if args.dataset == 'refcocog' and args.split in ['testA', 'testB']: + print(f"Easy & Hard Example Experiments - dataset : {args.dataset}, split : {args.split}") + from refer.refer_test import REFER + self.refer = REFER(args.refer_data_root, args.dataset, args.splitBy) + else : + from refer.refer import REFER + self.refer = REFER(args.refer_data_root, args.dataset, args.splitBy) + ref_ids = self.refer.getRefIds(split=self.split) + img_ids = self.refer.getImgIds(ref_ids) + all_imgs = self.refer.Imgs + self.imgs = list(all_imgs[i] for i in img_ids) + self.ref_ids = ref_ids#[:500] + self.ref_id2idx = dict(zip(ref_ids, range(len(ref_ids)))) + self.ref_idx2id = dict(zip(range(len(ref_ids)), ref_ids)) + + # tokenizer setting + # if args.text_encoder.model=='bert': + self.tokenizer = BertTokenizer.from_pretrained('bert-base-uncased') + # elif args.text_encoder.model=='roberta': + # self.tokenizer = RobertaTokenizerFast.from_pretrained(args.text_encoder.tokenizer) + # elif args.text_encoder.model=='clip': + # self.tokenizer = AutoTokenizer.from_pretrained(args.text_encoder.tokenizer) + # elif args.text_encoder.model=='llama': + # self.tokenizer = AutoTokenizer.from_pretrained(args.text_encoder.tokenizer) + + # self.tokenizer.add_special_tokens({'additional_special_tokens': task_tokens}) + # self.tokenizer.add_tokens(position_tokens) + + # if we are testing on a dataset, test all sentences of an object; + # o/w, we are validating during training, randomly sample one sentence for efficiency + self.max_tokens = 20 + self.eval_mode = eval_mode + self.input_ids = [] + self.attention_masks = [] + for i, r in enumerate(ref_ids): + ref = self.refer.Refs[r] + + sentences_for_ref = [] + attentions_for_ref = [] + for j, (el, sent_id) in enumerate(zip(ref['sentences'], ref['sent_ids'])): + sentence_raw = el['raw'] + input_ids = self.tokenizer.encode(text=sentence_raw, add_special_tokens=True, max_length=self.max_tokens, truncation=True) + #input_ids = input_ids[:self.max_tokens] + padded_input_ids = [0] * self.max_tokens + padded_input_ids[:len(input_ids)] = input_ids + attention_mask = [0] * self.max_tokens + attention_mask[:len(input_ids)] = [1]*len(input_ids) + sentences_for_ref.append(padded_input_ids) + attentions_for_ref.append(attention_mask) + + self.input_ids.append(sentences_for_ref) + self.attention_masks.append(attentions_for_ref) + + if self.aug.blur: + self.blur = ImageFilter.GaussianBlur(100) + + # Load mldb data + if args.dataset == 'refcoco': + lmdb_path = f'/data2/dataset/RefCOCO/logit_db/refcoco/refcoco_logit.lmdb' + elif args.dataset == 'refcoco+': + lmdb_path = f'/data2/dataset/RefCOCO/logit_db/refcoco+/refcocop_logit.lmdb' + elif args.dataset == 'refcocog' and args.splitBy == 'umd': + lmdb_path = f'/data2/dataset/RefCOCO/logit_db/refcocog_u/refcocog_u_logit.lmdb' + # elif args.datset == 'refcocog' and args.splitBy == 'google': + # lmdb_path = f'/data2/projects/donghwa/RIS/LAVT-RIS/data/logit_db/{args.dataset}/refcocog_g_logit.lmdb' + self.lmdb_env = lmdb.open( + lmdb_path, subdir=False, max_readers=32, + readonly=True, lock=False, + readahead=False, meminit=False) + with self.lmdb_env.begin(write=False) as txn: + self.length = loads_pyarrow(txn.get(b'__len__')) + self.keys = loads_pyarrow(txn.get(b'__keys__')) + + self.epoch = 0 + np.random.seed() + + def get_classes(self): + return self.classes + + def __len__(self): + return len(self.ref_ids) + + + def __getitem__(self, index): + + refid = self.ref_idx2id[index] + with self.lmdb_env.begin(write=False) as txn: + byteflow = txn.get(self.keys[refid]) + lmdb_dict = loads_pyarrow(byteflow) + + + # decide mosaic size + if self.split=='train': + if self.aug.num_bgs==4: + aug_prob = self.aug.aug_prob # 0.6 + retr_prob = self.aug.retr_prob # 0.3 + rand_prob = aug_prob - retr_prob # 0.3 + + if self.epoch < self.aug.warmup_epoch : + prob_rand = get_warmup_value(aug_prob, rand_prob, self.epoch, self.aug.warmup_epoch) + prob_retr = get_warmup_value(0, retr_prob, self.epoch, self.aug.warmup_epoch) + # print(1-aug_prob, prob_rand, prob_retr) + choice = np.random.choice(['one', 'random', 'retrieval'], p=[1-aug_prob, prob_rand, prob_retr]) + else : + choice = np.random.choice(['one', 'random', 'retrieval'], p=[1-aug_prob, rand_prob, retr_prob]) + + if choice == 'one': + num_bgs = 1 + else : + num_bgs = 4 + else: + num_bgs = 1 + choice = 'one' + else: # test, val + num_bgs = 1 + choice = 'one' + + target_sent_idx = np.random.choice(len(self.input_ids[index])) + ref_id = self.ref_idx2id[index] + + insert_idx = np.random.choice(range(num_bgs)) + + if num_bgs==1: + ref_ids = [] + sent_idxs = [] + sents = np.array([], dtype='str') + img_ids = [self.refer.Refs[ref_id]['image_id']] + + else: + if choice == 'retrieval': + sent_id = list(lmdb_dict.keys())[target_sent_idx] + img_ids = list(np.random.choice(lmdb_dict[sent_id][:self.aug.top_k], size=num_bgs-1, replace=True)) + img_ids = np.insert(img_ids, insert_idx, self.refer.Refs[ref_id]['image_id']) + + ref_ids = list(np.random.choice(self.ref_ids, size=num_bgs-1, replace=False)) + sent_idxs = [np.random.choice(len(self.refer.Refs[r]['sentences'])) for r in ref_ids] + sents = np.array([self.refer.Refs[r]['sentences'][sent_idxs[i]]['raw'] for i, r in enumerate(ref_ids)], dtype='str') + + ref_ids = np.insert(ref_ids, insert_idx, self.ref_idx2id[index]).astype(int) + sents = np.insert(sents, insert_idx, + self.refer.Refs[ref_ids[insert_idx]]['sentences'][target_sent_idx]['raw']) + sent_idxs = np.insert(sent_idxs, insert_idx, target_sent_idx).astype(int) + + + # pick a target origin + if self.aug.tgt_selection == 'random': + target_idx = np.random.choice(range(num_bgs)) + target_ref_idx = self.ref_id2idx[ref_ids[target_idx]] + target_sent_idx = int(np.random.choice(len(self.input_ids[target_ref_idx]))) + elif self.aug.tgt_selection == 'longest': + target_idx = np.argmax(list(map(len, sents))) + target_sent_idx = sent_idxs[target_idx] + elif self.aug.tgt_selection == 'fixed': + target_idx = insert_idx + # target_ref_id = ref_ids[target_idx] + target_ref_id = self.ref_idx2id[index] + + + # load items + imgs, masks = [], [] + if choice == 'retrieval': + # for ref_id in ref_ids: + for img_id in img_ids: + # img_id = self.refer.getImgIds([ref_id])[0] + img_info = self.refer.Imgs[img_id] + img_path = os.path.join(self.refer.IMAGE_DIR, img_info['file_name']) + + img = Image.open(img_path).convert("RGB") + imgs.append(np.array(img)) + ref = self.refer.imgToRefs[img_id][0] + mask = np.array(self.refer.getMask(ref)['mask']) + masks.append(mask) + else : + for ref_id in ref_ids: + # for img_id in img_ids: + img_id = self.refer.getImgIds([ref_id])[0] + img_info = self.refer.Imgs[img_id] + img_path = os.path.join(self.refer.IMAGE_DIR, img_info['file_name']) + + img = Image.open(img_path).convert("RGB") + imgs.append(np.array(img)) + ref = self.refer.loadRefs(ref_ids=[ref_id]) + mask = np.array(self.refer.getMask(ref[0])['mask']) + masks.append(mask) + + # image resize and apply 4in1 augmentation + if num_bgs==1: + resized = self.resize_bg1(image=imgs[0], mask=masks[0]) + imgs, masks = [resized['image']], [resized['mask']] + img = imgs[0] + else: + + if self.aug.move_crs_pnt: + crs_y = np.random.randint(0, self.img_sz+1) + crs_x = np.random.randint(0, self.img_sz+1) + else: + crs_y = 480//2 # + crs_x = 480//2 # + + if crs_y==0 or crs_x==0: + img1 = np.zeros([0,crs_x,3]) if crs_y==0 else np.zeros([crs_y,0,3]) + mask1 = np.zeros([0,crs_x]) if crs_y==0 else np.zeros([crs_y,0]) + else: + resize_bg1 = A.Compose([A.Resize(crs_y, crs_x, always_apply=True)]) + temp = resize_bg1(image=imgs[0], mask=masks[0]) + img1 = temp['image'] + mask1 = temp['mask'] + + if crs_y==0 or crs_x==self.img_sz: + img2 = np.zeros([0,self.img_sz-crs_x,3]) if crs_y==0 \ + else np.zeros([crs_y,0,3]) + mask2 = np.zeros([0,self.img_sz-crs_x]) if crs_y==0 \ + else np.zeros([crs_y,0]) + else: + resize_bg2 = A.Compose([ + A.Resize(crs_y, self.img_sz-crs_x, always_apply=True)]) + temp = resize_bg2(image=imgs[1], mask=masks[1]) + img2 = temp['image'] + mask2 = temp['mask'] + + if crs_y==self.img_sz or crs_x==0: + img3 = np.zeros([0,crs_x,3]) if crs_y==self.img_sz \ + else np.zeros([self.img_sz-crs_y,0,3]) + mask3 = np.zeros([0,crs_x]) if crs_y==self.img_sz \ + else np.zeros([self.img_sz-crs_y,0]) + else: + resize_bg3 = A.Compose([ + A.Resize(self.img_sz-crs_y, crs_x, always_apply=True)]) + temp = resize_bg3(image=imgs[2], mask=masks[2]) + img3 = temp['image'] + mask3 = temp['mask'] + + if crs_y==self.img_sz or crs_x==self.img_sz: + img4 = np.zeros([0,self.img_sz-crs_x,3]) if crs_y==self.img_sz \ + else np.zeros([self.img_sz-crs_y,0,3]) + mask4 = np.zeros([0,self.img_sz-crs_x]) if crs_y==self.img_sz \ + else np.zeros([self.img_sz-crs_y,0]) + else: + resize_bg4 = A.Compose([ + A.Resize(self.img_sz-crs_y, + self.img_sz-crs_x, always_apply=True)]) + temp = resize_bg4(image=imgs[3], mask=masks[3]) + img4 = temp['image'] + mask4 = temp['mask'] + + imgs = [img1, img2, img3, img4] + masks = [mask1, mask2, mask3, mask4] + # imgs = [bg1['image'], bg2['image'], bg3['image'], bg4['image']] + # masks = [bg1['mask'], bg2['mask'], bg3['mask'], bg4['mask']] + + # resized = self.resize_bg4(image=imgs[0], mask=masks[0], + # image1=imgs[1], mask1=masks[1], + # image2=imgs[2], mask2=masks[2], + # image3=imgs[3], mask3=masks[3]) + # imgs = [resized['image'], resized['image1'], resized['image2'], resized['image3']] + # masks = [resized['mask'], resized['mask1'], resized['mask2'], resized['mask3']] + + # scale effect ablation + if self.aug.blur: + imgs = [np.asarray(Image.fromarray(x).filter(self.blur)) if i!=insert_idx else x for i, x in enumerate(imgs)] + + num_rows = num_cols = int(math.sqrt(num_bgs)) + idxs = [(i*num_cols,i*num_cols+num_cols) for i in range(num_rows)] + img = [np.concatenate(imgs[_from:_to], axis=1) for (_from, _to) in idxs] + img = np.concatenate(img, axis=0).astype(np.uint8) + + masks_arr = [] + for bg_idx in range(num_bgs): + mask = masks[bg_idx] + temp = [mask if idx==bg_idx else np.zeros_like(masks[idx]) for idx in range(num_bgs)] + mask = [np.concatenate(temp[_from:_to], axis=1) for (_from, _to) in idxs] + mask = np.concatenate(mask, axis=0).astype(np.int32) + masks_arr.append(mask) + masks = masks_arr + + mask = masks[target_idx] + mask = mask.astype(np.uint8) + mask[mask>0] = 1 + + item = self.transforms(image=img, mask=mask) + img_tensor = item['image'] + target = item['mask'].long() + + target_ref_idx = self.ref_id2idx[target_ref_id] + if self.eval_mode: + embedding = [] + att = [] + + for s in range(len(self.input_ids[target_ref_idx])): + padded_input_ids = self.input_ids[target_ref_idx][s] + #padded_input_ids = task_id + pos_id + padded_input_ids + tensor_embeddings = torch.tensor(padded_input_ids).unsqueeze(0) + + attention_mask = self.attention_masks[target_ref_idx][s] + attention_mask = torch.tensor(attention_mask).unsqueeze(0) + + embedding.append(tensor_embeddings.unsqueeze(-1)) + att.append(attention_mask.unsqueeze(-1)) + tensor_embeddings = torch.cat(embedding, dim=-1) + attention_mask = torch.cat(att, dim=-1) + else: + padded_input_ids = self.input_ids[target_ref_idx][target_sent_idx] + #padded_input_ids = task_id + pos_id + padded_input_ids + tensor_embeddings = torch.tensor(padded_input_ids).unsqueeze(0) + attention_mask = self.attention_masks[target_ref_idx][target_sent_idx] + attention_mask = torch.tensor(attention_mask).unsqueeze(0) + + item = { + 'image': img_tensor, + 'seg_target': target, + 'sentence': tensor_embeddings, + 'attn_mask': attention_mask + } + return item diff --git a/LAVT-RIS/donghwa/dataset_refer_bert_n_obj.py b/LAVT-RIS/donghwa/dataset_refer_bert_n_obj.py new file mode 100644 index 0000000000000000000000000000000000000000..dfcc516c9759abe645b33d9348d6482730330a96 --- /dev/null +++ b/LAVT-RIS/donghwa/dataset_refer_bert_n_obj.py @@ -0,0 +1,149 @@ +import os +import sys +import torch.utils.data as data +import torch +from torchvision import transforms +from torch.autograd import Variable +import numpy as np +from PIL import Image +import torchvision.transforms.functional as TF +import random + +from bert.tokenization_bert import BertTokenizer + +import h5py +from refer.refer import REFER + +from args import get_parser + +# Dataset configuration initialization +parser = get_parser() +args = parser.parse_args() + + +class ReferDataset(data.Dataset): + + def __init__(self, + args, + image_transforms=None, + target_transforms=None, + split='train', + eval_mode=False): + + self.classes = [] + self.image_transforms = image_transforms + self.target_transform = target_transforms + self.split = split + self.dataset = args.dataset + self.args = args + if args.dataset == 'refcocog' and args.split in ['testA', 'testB']: + print(f"Easy & Hard Example Experiments - dataset : {args.dataset}, split : {args.split}") + from refer.refer_test import REFER + self.refer = REFER(args.refer_data_root, args.dataset, args.splitBy) + else : + from refer.refer import REFER + self.refer = REFER(args.refer_data_root, args.dataset, args.splitBy) + + self.max_tokens = 20 + + ref_ids = self.refer.getRefIds(split=self.split) + img_ids = self.refer.getImgIds(ref_ids) + + # n_obj binning + import json + nobj_fpath = '/data/projects/chaeyun/Co-DETR/SotaFiltered_thres035_binned_nobj.json' + with open(nobj_fpath, 'r') as f: + nobj_dict = json.load(f) + ref_ids = nobj_dict[args.n_obj_bin] + # self.refer.Refs = {k : self.refer.Refs[k] for k in ref_ids} + + all_imgs = self.refer.Imgs + self.imgs = list(all_imgs[i] for i in img_ids) + self.ref_ids = ref_ids + + self.input_ids = [] + self.attention_masks = [] + self.sent_lens = [] + self.tokenizer = BertTokenizer.from_pretrained(args.bert_tokenizer) + + self.eval_mode = eval_mode + # if we are testing on a dataset, test all sentences of an object; + # o/w, we are validating during training, randomly sample one sentence for efficiency + for r in ref_ids: + ref = self.refer.Refs[r] + + sentences_for_ref = [] + attentions_for_ref = [] + sent_lens_for_ref = [] + + for i, (el, sent_id) in enumerate(zip(ref['sentences'], ref['sent_ids'])): + sentence_raw = el['raw'] + # sent_len = len(sentence_raw.split()) + # if sent_len <= self.args.seq_len.min or sent_len >= self.args.seq_len.max : + # continue + attention_mask = [0] * self.max_tokens + padded_input_ids = [0] * self.max_tokens + + input_ids = self.tokenizer.encode(text=sentence_raw, add_special_tokens=True) + + # truncation of tokens + input_ids = input_ids[:self.max_tokens] + + padded_input_ids[:len(input_ids)] = input_ids + attention_mask[:len(input_ids)] = [1]*len(input_ids) + + sentences_for_ref.append(torch.tensor(padded_input_ids).unsqueeze(0)) + attentions_for_ref.append(torch.tensor(attention_mask).unsqueeze(0)) + # sent_lens_for_ref.append(torch.tensor(sent_len)) + + self.input_ids.append(sentences_for_ref) + self.attention_masks.append(attentions_for_ref) + self.sent_lens.append(sent_lens_for_ref) + + def get_classes(self): + return self.classes + + def __len__(self): + return len(self.ref_ids) + + def __getitem__(self, index): + this_ref_id = self.ref_ids[index] + this_img_id = self.refer.getImgIds(this_ref_id) + this_img = self.refer.Imgs[this_img_id[0]] + + img = Image.open(os.path.join(self.refer.IMAGE_DIR, this_img['file_name'])).convert("RGB") + + ref = self.refer.loadRefs(this_ref_id) + + ref_mask = np.array(self.refer.getMask(ref[0])['mask']) + annot = np.zeros(ref_mask.shape) + annot[ref_mask == 1] = 1 + + annot = Image.fromarray(annot.astype(np.uint8), mode="P") + + if self.image_transforms is not None: + # resize, from PIL to tensor, and mean and std normalization + img, target = self.image_transforms(img, annot) + + if self.eval_mode: + embedding = [] + att = [] + # sent_lens = [] + for s in range(len(self.input_ids[index])): + e = self.input_ids[index][s] + a = self.attention_masks[index][s] + # ss = self.sent_lens[index][s] + embedding.append(e.unsqueeze(-1)) + att.append(a.unsqueeze(-1)) + # sent_lens.append(ss) + + tensor_embeddings = torch.cat(embedding, dim=-1) + attention_mask = torch.cat(att, dim=-1) + # sent_lens = torch.tensor(sent_lens) + else: + choice_sent = np.random.choice(len(self.input_ids[index])) + tensor_embeddings = self.input_ids[index][choice_sent] + attention_mask = self.attention_masks[index][choice_sent] + # sent_lens = self.sent_lens[index][choice_sent] + + return img, target, tensor_embeddings, attention_mask #, sent_lens diff --git a/LAVT-RIS/donghwa/dataset_refer_bert_sent_len.py b/LAVT-RIS/donghwa/dataset_refer_bert_sent_len.py new file mode 100644 index 0000000000000000000000000000000000000000..4ad566e248442e2cb03b4561024a34965493fd57 --- /dev/null +++ b/LAVT-RIS/donghwa/dataset_refer_bert_sent_len.py @@ -0,0 +1,161 @@ +import os +import sys +import torch.utils.data as data +import torch +from torchvision import transforms +from torch.autograd import Variable +import numpy as np +from PIL import Image +import torchvision.transforms.functional as TF +import random + +from bert.tokenization_bert import BertTokenizer + +import h5py +from refer.refer import REFER + +from args import get_parser + +# Dataset configuration initialization +parser = get_parser() +args = parser.parse_args() + + +class ReferDataset(data.Dataset): + + def __init__(self, + args, + image_transforms=None, + target_transforms=None, + split='train', + eval_mode=False): + + self.classes = [] + self.image_transforms = image_transforms + self.target_transform = target_transforms + self.split = split + self.dataset = args.dataset + self.args = args + if args.dataset == 'refcocog' and args.split in ['testA', 'testB']: + print(f"Easy & Hard Example Experiments - dataset : {args.dataset}, split : {args.split}") + from refer.refer_test import REFER + self.refer = REFER(args.refer_data_root, args.dataset, args.splitBy) + else : + from refer.refer import REFER + self.refer = REFER(args.refer_data_root, args.dataset, args.splitBy) + + self.max_tokens = 20 + + ref_ids = self.refer.getRefIds(split=self.split) + img_ids = self.refer.getImgIds(ref_ids) + + # sent_len experiments + import copy + new_ref_ids = [] + new_refs = {} + for ref_id in ref_ids: + ref = copy.deepcopy(self.refer.Refs[ref_id]) + new_sents = [] + for sent in ref['sentences']: + words = sent['raw'].split(' ') + if len(words)>= args.sent_len.min and len(words) <= args.sent_len.max: # 여기는 수정 + new_sents.append(sent) + + if len(new_sents)>0: + ref['sentences'] = new_sents + new_refs[ref_id] = ref + new_ref_ids.append(ref_id) + + ref_ids = new_ref_ids + self.refer.Refs = new_refs + + all_imgs = self.refer.Imgs + self.imgs = list(all_imgs[i] for i in img_ids) + self.ref_ids = ref_ids + + self.input_ids = [] + self.attention_masks = [] + self.sent_lens = [] + self.tokenizer = BertTokenizer.from_pretrained(args.bert_tokenizer) + + self.eval_mode = eval_mode + # if we are testing on a dataset, test all sentences of an object; + # o/w, we are validating during training, randomly sample one sentence for efficiency + for r in ref_ids: + ref = self.refer.Refs[r] + + sentences_for_ref = [] + attentions_for_ref = [] + sent_lens_for_ref = [] + + for i, (el, sent_id) in enumerate(zip(ref['sentences'], ref['sent_ids'])): + sentence_raw = el['raw'] + # sent_len = len(sentence_raw.split()) + # if sent_len <= self.args.seq_len.min or sent_len >= self.args.seq_len.max : + # continue + attention_mask = [0] * self.max_tokens + padded_input_ids = [0] * self.max_tokens + + input_ids = self.tokenizer.encode(text=sentence_raw, add_special_tokens=True) + + # truncation of tokens + input_ids = input_ids[:self.max_tokens] + + padded_input_ids[:len(input_ids)] = input_ids + attention_mask[:len(input_ids)] = [1]*len(input_ids) + + sentences_for_ref.append(torch.tensor(padded_input_ids).unsqueeze(0)) + attentions_for_ref.append(torch.tensor(attention_mask).unsqueeze(0)) + # sent_lens_for_ref.append(torch.tensor(sent_len)) + + self.input_ids.append(sentences_for_ref) + self.attention_masks.append(attentions_for_ref) + self.sent_lens.append(sent_lens_for_ref) + + def get_classes(self): + return self.classes + + def __len__(self): + return len(self.ref_ids) + + def __getitem__(self, index): + this_ref_id = self.ref_ids[index] + this_img_id = self.refer.getImgIds(this_ref_id) + this_img = self.refer.Imgs[this_img_id[0]] + + img = Image.open(os.path.join(self.refer.IMAGE_DIR, this_img['file_name'])).convert("RGB") + + ref = self.refer.loadRefs(this_ref_id) + + ref_mask = np.array(self.refer.getMask(ref[0])['mask']) + annot = np.zeros(ref_mask.shape) + annot[ref_mask == 1] = 1 + + annot = Image.fromarray(annot.astype(np.uint8), mode="P") + + if self.image_transforms is not None: + # resize, from PIL to tensor, and mean and std normalization + img, target = self.image_transforms(img, annot) + + if self.eval_mode: + embedding = [] + att = [] + # sent_lens = [] + for s in range(len(self.input_ids[index])): + e = self.input_ids[index][s] + a = self.attention_masks[index][s] + # ss = self.sent_lens[index][s] + embedding.append(e.unsqueeze(-1)) + att.append(a.unsqueeze(-1)) + # sent_lens.append(ss) + + tensor_embeddings = torch.cat(embedding, dim=-1) + attention_mask = torch.cat(att, dim=-1) + # sent_lens = torch.tensor(sent_lens) + else: + choice_sent = np.random.choice(len(self.input_ids[index])) + tensor_embeddings = self.input_ids[index][choice_sent] + attention_mask = self.attention_masks[index][choice_sent] + # sent_lens = self.sent_lens[index][choice_sent] + + return img, target, tensor_embeddings, attention_mask #, sent_lens diff --git a/LAVT-RIS/donghwa/demo_inference.py b/LAVT-RIS/donghwa/demo_inference.py new file mode 100644 index 0000000000000000000000000000000000000000..a56fd37329f1bb19e771d86bdb15753b811e2227 --- /dev/null +++ b/LAVT-RIS/donghwa/demo_inference.py @@ -0,0 +1,118 @@ +image_path = './demo/demo.jpg' +sentence = 'the most handsome guy' +weights = './checkpoints/refcoco.pth' +device = 'cuda:0' + +# pre-process the input image +from PIL import Image +import torchvision.transforms as T +import numpy as np +img = Image.open(image_path).convert("RGB") +img_ndarray = np.array(img) # (orig_h, orig_w, 3); for visualization +original_w, original_h = img.size # PIL .size returns width first and height second + +image_transforms = T.Compose( + [ + T.Resize(480), + T.ToTensor(), + T.Normalize(mean=[0.485, 0.456, 0.406], std=[0.229, 0.224, 0.225]) + ] +) + +img = image_transforms(img).unsqueeze(0) # (1, 3, 480, 480) +img = img.to(device) # for inference (input) + +# pre-process the raw sentence +from bert.tokenization_bert import BertTokenizer +import torch +tokenizer = BertTokenizer.from_pretrained('bert-base-uncased') +sentence_tokenized = tokenizer.encode(text=sentence, add_special_tokens=True) +sentence_tokenized = sentence_tokenized[:20] # if the sentence is longer than 20, then this truncates it to 20 words +# pad the tokenized sentence +padded_sent_toks = [0] * 20 +padded_sent_toks[:len(sentence_tokenized)] = sentence_tokenized +# create a sentence token mask: 1 for real words; 0 for padded tokens +attention_mask = [0] * 20 +attention_mask[:len(sentence_tokenized)] = [1]*len(sentence_tokenized) +# convert lists to tensors +padded_sent_toks = torch.tensor(padded_sent_toks).unsqueeze(0) # (1, 20) +attention_mask = torch.tensor(attention_mask).unsqueeze(0) # (1, 20) +padded_sent_toks = padded_sent_toks.to(device) # for inference (input) +attention_mask = attention_mask.to(device) # for inference (input) + +# initialize model and load weights +from bert.modeling_bert import BertModel +from lib import segmentation + +# construct a mini args class; like from a config file + + +class args: + swin_type = 'base' + window12 = True + mha = '' + fusion_drop = 0.0 + + +single_model = segmentation.__dict__['lavt'](pretrained='', args=args) +single_model.to(device) +model_class = BertModel +single_bert_model = model_class.from_pretrained('bert-base-uncased') +single_bert_model.pooler = None + +checkpoint = torch.load(weights, map_location='cpu') +single_bert_model.load_state_dict(checkpoint['bert_model']) +single_model.load_state_dict(checkpoint['model']) +model = single_model.to(device) +bert_model = single_bert_model.to(device) + + +# inference +import torch.nn.functional as F +last_hidden_states = bert_model(padded_sent_toks, attention_mask=attention_mask)[0] +embedding = last_hidden_states.permute(0, 2, 1) +output = model(img, embedding, l_mask=attention_mask.unsqueeze(-1)) +output = output.argmax(1, keepdim=True) # (1, 1, 480, 480) +output = F.interpolate(output.float(), (original_h, original_w)) # 'nearest'; resize to the original image size +output = output.squeeze() # (orig_h, orig_w) +output = output.cpu().data.numpy() # (orig_h, orig_w) + + +# show/save results +def overlay_davis(image, mask, colors=[[0, 0, 0], [255, 0, 0]], cscale=1, alpha=0.4): + from scipy.ndimage.morphology import binary_dilation + + colors = np.reshape(colors, (-1, 3)) + colors = np.atleast_2d(colors) * cscale + + im_overlay = image.copy() + object_ids = np.unique(mask) + + for object_id in object_ids[1:]: + # Overlay color on binary mask + foreground = image*alpha + np.ones(image.shape)*(1-alpha) * np.array(colors[object_id]) + binary_mask = mask == object_id + + # Compose image + im_overlay[binary_mask] = foreground[binary_mask] + + # countours = skimage.morphology.binary.binary_dilation(binary_mask) - binary_mask + countours = binary_dilation(binary_mask) ^ binary_mask + # countours = cv2.dilate(binary_mask, cv2.getStructuringElement(cv2.MORPH_CROSS,(3,3))) - binary_mask + im_overlay[countours, :] = 0 + + return im_overlay.astype(image.dtype) + + +output = output.astype(np.uint8) # (orig_h, orig_w), np.uint8 +# Overlay the mask on the image +visualization = overlay_davis(img_ndarray, output) # red +visualization = Image.fromarray(visualization) +# show the visualization +#visualization.show() +# Save the visualization +visualization.save('./demo/demo_result.jpg') + + + + diff --git a/LAVT-RIS/donghwa/scripts/submit_jupyter.sh b/LAVT-RIS/donghwa/scripts/submit_jupyter.sh new file mode 100644 index 0000000000000000000000000000000000000000..da7c677dab6e9cb999ae64abd2def856053e9466 --- /dev/null +++ b/LAVT-RIS/donghwa/scripts/submit_jupyter.sh @@ -0,0 +1,17 @@ +#!/bin/bash + +#SBATCH --job-name=jupyter # Submit a job named "example" +#SBATCH --mail-user=vip.maildummy@gmail.com +#SBATCH --mail-type=BEGIN,END,FAIL +#SBATCH --partition=a4000 # a6000 or a100 +#SBATCH --gres=gpu:1 +#SBATCH --time=7-00:00:00 # d-hh:mm:ss, max time limit +#SBATCH --mem=48000 # cpu memory size +#SBATCH --cpus-per-task=8 # cpu num +#SBATCH --output=log_jupyter.txt # std output filename + +ml cuda/11.0 # 필요한 쿠다 버전 로드 +eval "$(conda shell.bash hook)" # Initialize Conda Environment +conda activate lavt # Activate your conda environment + +jupyter notebook --no-browser --port=1234 \ No newline at end of file diff --git a/LAVT-RIS/donghwa/scripts/submit_pty.sh b/LAVT-RIS/donghwa/scripts/submit_pty.sh new file mode 100644 index 0000000000000000000000000000000000000000..623d5cb0a15823386be7a8998eace7b950a6ad5e --- /dev/null +++ b/LAVT-RIS/donghwa/scripts/submit_pty.sh @@ -0,0 +1,2 @@ +srun --job-name "rela_eval" --cpus-per-task 8 --mem 84000 --time 7-00:00:00 -p a3000 --gres gpu:4 --pty bash +srun --job-name "jupyter" --cpus-per-task 4 --mem 48000 --time 7-00:00:00 -p a4000 --gres gpu:1 --pty bash diff --git a/LAVT-RIS/donghwa/scripts/submit_test.sh b/LAVT-RIS/donghwa/scripts/submit_test.sh new file mode 100644 index 0000000000000000000000000000000000000000..b18e5c9aa55851f26faaeeb6aa5cca7ed29a524d --- /dev/null +++ b/LAVT-RIS/donghwa/scripts/submit_test.sh @@ -0,0 +1,55 @@ +#!/bin/bash + +#SBATCH --job-name=test # Submit a job named "example" +#SBATCH --mail-user=vip.maildummy@gmail.com +#SBATCH --mail-type=BEGIN,END,FAIL +#SBATCH --partition=a4000 # a6000 or a100 +#SBATCH --gres=gpu:1 +#SBATCH --time=7-00:00:00 # d-hh:mm:ss, max time limit +#SBATCH --mem=48000 # cpu memory size +#SBATCH --cpus-per-task=4 # cpu num +#SBATCH --output=log_refcoco_retrieval_433_10up_testAB.txt # std output filename + +ml cuda/11.0 # 필요한 쿠다 버전 로드 +eval "$(conda shell.bash hook)" # Initialize Conda Environment +conda activate lavt # Activate your conda environment + + +# test +# python test.py --model lavt_one --swin_type base --dataset refcoco --split testA --resume ./checkpoints/repro_lavt_one/model_best_refcoco_lavt_one.pth --workers 4 --ddp_trained_weights --window12 --img_size 480 +# python test.py --model lavt_one --swin_type base --dataset refcoco --split testB --resume ./checkpoints/repro_lavt_one/model_best_refcoco_lavt_one.pth --workers 4 --ddp_trained_weights --window12 --img_size 480 + +# python test.py --model lavt_one --swin_type base --dataset refcoco+ --split val --resume ./checkpoints/refcoco+.pth --workers 4 --ddp_trained_weights --window12 --img_size 480 +# python test.py --model lavt_one --swin_type base --dataset refcocog --splitBy umd --split test --resume ./checkpoints/gref_umd.pth --workers 4 --ddp_trained_weights --window12 --img_size 480 +# python test.py --model lavt_one --swin_type base --dataset refcocog --splitBy google --split val --resume ./checkpoints/gref_google.pth --workers 4 --ddp_trained_weights --window12 --img_size 480 +# python test.py --model lavt_one --swin_type base --dataset grefcoco --splitBy unc --split val --resume ./checkpoints/gref_umd.pth --workers 4 --ddp_trained_weights --window12 --img_size 480 + +# test lavt_one +# python test.py --model lavt_one --swin_type base --dataset refcocog --splitBy umd --split test --resume ./checkpoints/model_best_gref_umd_lavt_one.pth --workers 4 --ddp_trained_weights --window12 --img_size 480 +# python test.py --model lavt_one --swin_type base --dataset refcocog --splitBy google --split val --resume ./checkpoints/lavt_one/gref_google.pth --workers 4 --ddp_trained_weights --window12 --img_size 480 + +# python test.py --model lavt_one --swin_type base --dataset refcoco --split val --resume ./checkpoints/lavt_one/refcoco.pth --workers 4 --ddp_trained_weights --window12 --img_size 480 +# python test_mosaic.py --model lavt_one --swin_type base --dataset refcoco --split testA --resume ./checkpoints/mosaic_lavt_one/model_best_mosaic_refcoco_lavt_one.pth --workers 4 --ddp_trained_weights --window12 --img_size 480 +# python test_mosaic.py --model lavt_one --swin_type base --dataset refcoco --split testB --resume ./checkpoints/mosaic_lavt_one/model_best_mosaic_refcoco_lavt_one.pth --workers 4 --ddp_trained_weights --window12 --img_size 480 + +# srun python test.py --model lavt_one --swin_type base --dataset refcoco+ --split val --resume ./checkpoints/lavt_one/refcoco+.pth --workers 4 --ddp_trained_weights --window12 --img_size 480 +# srun python test.py --model lavt_one --swin_type base --dataset refcoco+ --split testA --resume ./checkpoints/retrieval_lavt_one/Retrieval_433_10wm6to3/model_best_retrieval_refcoco+_OneStage_433_10wm6to3.pth --workers 4 --ddp_trained_weights --window12 --img_size 480 +# srun python test.py --model lavt_one --swin_type base --dataset refcoco+ --split testB --resume ./checkpoints/retrieval_lavt_one/Retrieval_433_10wm6to3/model_best_retrieval_refcoco+_OneStage_433_10wm6to3.pth --workers 4 --ddp_trained_weights --window12 --img_size 480 + +# random +# srun python test_mosaic.py --model lavt_one --swin_type base --dataset refcoco --split testA --resume experiments/refcoco_unc/refcoco_random_460/model_best_refcoco_random_460.pth --workers 4 --ddp_trained_weights --window12 --img_size 480 --config config/random_460.yaml +# srun python test_mosaic.py --model lavt_one --swin_type base --dataset refcoco --split testB --resume experiments/refcoco_unc/refcoco_random_460/model_best_refcoco_random_460.pth --workers 4 --ddp_trained_weights --window12 --img_size 480 --config config/random_460.yaml + +# srun python test_mosaic.py --model lavt_one --swin_type base --dataset refcoco+ --split testA --resume experiments/refcoco+_unc/refcoco+_random_460/model_best_refcoco+_random_460.pth --workers 4 --ddp_trained_weights --window12 --img_size 480 --config config/random_460.yaml +# srun python test_mosaic.py --model lavt_one --swin_type base --dataset refcoco+ --split testB --resume experiments/refcoco+_unc/refcoco+_random_460/model_best_refcoco+_random_460.pth --workers 4 --ddp_trained_weights --window12 --img_size 480 --config config/random_460.yaml + +# srun python test_mosaic.py --model lavt_one --swin_type base --dataset refcocog --splitBy umd --split test --resume experiments/refcocog_umd/random_gref_umd_460_40epoch_2/model_best_random_gref_umd_460_40epoch_2.pth --workers 4 --ddp_trained_weights --window12 --img_size 480 --config config/random_460.yaml + +# retrieval +# srun python test_mosaic_retrieval.py --model lavt_one --swin_type base --dataset refcocog --splitBy umd --split test --resume experiments/refcocog_umd/retrieval_filter_gref_umd_433_10up_top200/model_best_retrieval_filter_gref_umd_433_10up_top200.pth --workers 4 --ddp_trained_weights --window12 --img_size 480 --config config/retrieval_433_10up.yaml + +# srun python test_mosaic_retrieval.py --model lavt_one --swin_type base --dataset refcoco+ --split testA --resume experiments/refcoco+_unc/refcoco+_retrieval_filter_433_10up/model_best_refcoco+_retrieval_filter_433_10up.pth --workers 4 --ddp_trained_weights --window12 --img_size 480 --config config/retrieval_433_10up.yaml +# srun python test_mosaic_retrieval.py --model lavt_one --swin_type base --dataset refcoco+ --split testB --resume experiments/refcoco+_unc/refcoco+_retrieval_filter_433_10up/model_best_refcoco+_retrieval_filter_433_10up.pth --workers 4 --ddp_trained_weights --window12 --img_size 480 --config config/retrieval_433_10up.yaml + +srun python test_mosaic_retrieval.py --model lavt_one --swin_type base --dataset refcoco --split testA --resume experiments/refcoco_unc/refcoco_retrieval_filter_433_10up/model_best_refcoco_retrieval_filter_433_10up.pth --workers 4 --ddp_trained_weights --window12 --img_size 480 --config config/retrieval_433_10up.yaml +srun python test_mosaic_retrieval.py --model lavt_one --swin_type base --dataset refcoco --split testB --resume experiments/refcoco_unc/refcoco_retrieval_filter_433_10up/model_best_refcoco_retrieval_filter_433_10up.pth --workers 4 --ddp_trained_weights --window12 --img_size 480 --config config/retrieval_433_10up.yaml \ No newline at end of file diff --git a/LAVT-RIS/donghwa/scripts/submit_test_easyhard.sh b/LAVT-RIS/donghwa/scripts/submit_test_easyhard.sh new file mode 100644 index 0000000000000000000000000000000000000000..b97eac8620ca619b9676e5b9c0f1a3dba71c88df --- /dev/null +++ b/LAVT-RIS/donghwa/scripts/submit_test_easyhard.sh @@ -0,0 +1,43 @@ +#!/bin/bash + +#SBATCH --job-name=lavt_easyhard # Submit a job named "example" +#SBATCH --mail-user=vip.maildummy@gmail.com +#SBATCH --mail-type=BEGIN,END,FAIL +#SBATCH --partition=a4000 # a6000 or a100 +#SBATCH --gres=gpu:1 +#SBATCH --time=7-00:00:00 # d-hh:mm:ss, max time limit +#SBATCH --mem=48000 # cpu memory size +#SBATCH --cpus-per-task=4 # cpu num +#SBATCH --output=log_refcocog_umd_ckpt_testAB.txt # std output filename + +ml cuda/11.0 # 필요한 쿠다 버전 로드 +eval "$(conda shell.bash hook)" # Initialize Conda Environment +conda activate lavt # Activate your conda environment + + + +# test lavt_one + + +srun python test.py --model lavt_one --swin_type base --dataset refcocog --splitBy umd --split testA --resume ./checkpoints/ckpt_lavt_one/gref_umd.pth --workers 4 --ddp_trained_weights --window12 --img_size 480 +srun python test.py --model lavt_one --swin_type base --dataset refcocog --splitBy umd --split testB --resume ./checkpoints/ckpt_lavt_one/gref_umd.pth --workers 4 --ddp_trained_weights --window12 --img_size 480 + +# srun python test.py --model lavt_one --swin_type base --dataset refcocog --splitBy umd --split testA --resume ./checkpoints/repro_lavt_one/model_best_gref_umd_lavt_one.pth --workers 4 --ddp_trained_weights --window12 --img_size 480 +# srun python test.py --model lavt_one --swin_type base --dataset refcocog --splitBy umd --split testB --resume ./checkpoints/repro_lavt_one/model_best_gref_umd_lavt_one.pth --workers 4 --ddp_trained_weights --window12 --img_size 480 + +# srun python test_mosaic.py --model lavt_one --swin_type base --dataset refcocog --splitBy umd --split testA --resume ./checkpoints/random_550_lavt_one/model_best_mosaic_gref_umd_lavt_one.pth --workers 4 --ddp_trained_weights --window12 --img_size 480 --config config/random_550.yaml +# srun python test_mosaic.py --model lavt_one --swin_type base --dataset refcocog --splitBy umd --split testB --resume ./checkpoints/random_550_lavt_one/model_best_mosaic_gref_umd_lavt_one.pth --workers 4 --ddp_trained_weights --window12 --img_size 480 --config config/random_550.yaml + +# srun python test_mosaic.py --model lavt_one --swin_type base --dataset refcocog --splitBy umd --split testA --resume experiments/refcocog_umd/random_gref_umd_460_40epoch_2/model_best_random_gref_umd_460_40epoch_2.pth --workers 4 --ddp_trained_weights --window12 --img_size 480 --config config/random_460.yaml +# srun python test_mosaic.py --model lavt_one --swin_type base --dataset refcocog --splitBy umd --split testB --resume experiments/refcocog_umd/random_gref_umd_460_40epoch_2/model_best_random_gref_umd_460_40epoch_2.pth --workers 4 --ddp_trained_weights --window12 --img_size 480 --config config/random_460.yaml + + +# retrieval +# srun python test_mosaic_retrieval.py --model lavt_one --swin_type base --dataset refcocog \ +# --splitBy umd --split testA --resume experiments/refcocog_umd/retrieval_filter_gref_umd_433_10up_top200/model_best_retrieval_filter_gref_umd_433_10up_top200.pth \ +# --workers 4 --ddp_trained_weights --window12 --img_size 480 --config config/retrieval_433_10up.yaml + +# srun python test_mosaic_retrieval.py --model lavt_one --swin_type base --dataset refcocog \ +# --splitBy umd --split testB --resume experiments/refcocog_umd/retrieval_filter_gref_umd_433_10up_top200/model_best_retrieval_filter_gref_umd_433_10up_top200.pth \ +# --workers 4 --ddp_trained_weights --window12 --img_size 480 --config config/retrieval_433_10up.yaml + diff --git a/LAVT-RIS/donghwa/scripts/submit_test_n_obj.sh b/LAVT-RIS/donghwa/scripts/submit_test_n_obj.sh new file mode 100644 index 0000000000000000000000000000000000000000..53a56650fbdf463df9868d852ed54747d820eca5 --- /dev/null +++ b/LAVT-RIS/donghwa/scripts/submit_test_n_obj.sh @@ -0,0 +1,101 @@ +#!/bin/bash + +#SBATCH --job-name=n_obj_ours # Submit a job named "example" +#SBATCH --mail-user=vip.maildummy@gmail.com +#SBATCH --mail-type=BEGIN,END,FAIL +#SBATCH --partition=a5000 # a6000 or a100 +#SBATCH --gres=gpu:1 +#SBATCH --time=7-00:00:00 # d-hh:mm:ss, max time limit +#SBATCH --mem=48000 # cpu memory size +#SBATCH --cpus-per-task=4 # cpu num +#SBATCH --output=log_refcocog_umd_repro_n_obj.txt # std output filename + +ml cuda/11.0 # 필요한 쿠다 버전 로드 +eval "$(conda shell.bash hook)" # Initialize Conda Environment +conda activate lavt # Activate your conda environment + + +# ckpt +# srun python test_n_obj.py --model lavt_one --swin_type base --dataset refcocog --splitBy umd --split test \ +# --resume checkpoints/ckpt_lavt_one/gref_umd.pth --workers 4 --ddp_trained_weights --window12 --img_size 480 \ +# --config config/n_obj/n_12.yaml + +# srun python test_n_obj.py --model lavt_one --swin_type base --dataset refcocog --splitBy umd --split test \ +# --resume checkpoints/ckpt_lavt_one/gref_umd.pth --workers 4 --ddp_trained_weights --window12 --img_size 480 \ +# --config config/n_obj/n_34.yaml + +# srun python test_n_obj.py --model lavt_one --swin_type base --dataset refcocog --splitBy umd --split test \ +# --resume checkpoints/ckpt_lavt_one/gref_umd.pth --workers 4 --ddp_trained_weights --window12 --img_size 480 \ +# --config config/n_obj/n_56.yaml + +# srun python test_n_obj.py --model lavt_one --swin_type base --dataset refcocog --splitBy umd --split test \ +# --resume checkpoints/ckpt_lavt_one/gref_umd.pth --workers 4 --ddp_trained_weights --window12 --img_size 480 \ +# --config config/n_obj/n_78.yaml + +# repro +srun python test_n_obj.py --model lavt_one --swin_type base --dataset refcocog --splitBy umd --split test \ + --resume checkpoints/repro_lavt_one/model_best_gref_umd_lavt_one.pth \ + --workers 4 --ddp_trained_weights --window12 --img_size 480 \ + --config config/n_obj/n_12.yaml + +srun python test_n_obj.py --model lavt_one --swin_type base --dataset refcocog --splitBy umd --split test \ + --resume checkpoints/repro_lavt_one/model_best_gref_umd_lavt_one.pth \ + --workers 4 --ddp_trained_weights --window12 --img_size 480 \ + --config config/n_obj/n_34.yaml + +srun python test_n_obj.py --model lavt_one --swin_type base --dataset refcocog --splitBy umd --split test \ + --resume checkpoints/repro_lavt_one/model_best_gref_umd_lavt_one.pth \ + --workers 4 --ddp_trained_weights --window12 --img_size 480 \ + --config config/n_obj/n_56.yaml + +srun python test_n_obj.py --model lavt_one --swin_type base --dataset refcocog --splitBy umd --split test \ + --resume checkpoints/repro_lavt_one/model_best_gref_umd_lavt_one.pth \ + --workers 4 --ddp_trained_weights --window12 --img_size 480 \ + --config config/n_obj/n_78.yaml + + +# our best_model (retrieval) + +# srun python test_n_obj.py --model lavt_one --swin_type base --dataset refcocog --splitBy umd --split test \ +# --resume experiments/refcocog_umd/retrieval_gref_umd_433_10up_40epoch/model_best_retrieval_gref_umd_433_10up_40epoch.pth \ +# --workers 4 --ddp_trained_weights --window12 --img_size 480 \ +# --config config/n_obj/n_12.yaml + +# srun python test_n_obj.py --model lavt_one --swin_type base --dataset refcocog --splitBy umd --split test \ +# --resume experiments/refcocog_umd/retrieval_gref_umd_433_10up_40epoch/model_best_retrieval_gref_umd_433_10up_40epoch.pth \ +# --workers 4 --ddp_trained_weights --window12 --img_size 480 \ +# --config config/n_obj/n_34.yaml + +# srun python test_n_obj.py --model lavt_one --swin_type base --dataset refcocog --splitBy umd --split test \ +# --resume experiments/refcocog_umd/retrieval_gref_umd_433_10up_40epoch/model_best_retrieval_gref_umd_433_10up_40epoch.pth \ +# --workers 4 --ddp_trained_weights --window12 --img_size 480 \ +# --config config/n_obj/n_56.yaml + +# srun python test_n_obj.py --model lavt_one --swin_type base --dataset refcocog --splitBy umd --split test \ +# --resume experiments/refcocog_umd/retrieval_gref_umd_433_10up_40epoch/model_best_retrieval_gref_umd_433_10up_40epoch.pth \ +# --workers 4 --ddp_trained_weights --window12 --img_size 480 \ +# --config config/n_obj/n_78.yaml + + + +# random + +# srun python test_n_obj.py --model lavt_one --swin_type base --dataset refcocog --splitBy umd --split test \ +# --resume checkpoints/random_550_lavt_one/model_best_mosaic_gref_umd_lavt_one.pth \ +# --workers 4 --ddp_trained_weights --window12 --img_size 480 \ +# --config config/n_obj/n_12.yaml + +# srun python test_n_obj.py --model lavt_one --swin_type base --dataset refcocog --splitBy umd --split test \ +# --resume checkpoints/random_550_lavt_one/model_best_mosaic_gref_umd_lavt_one.pth \ +# --workers 4 --ddp_trained_weights --window12 --img_size 480 \ +# --config config/n_obj/n_34.yaml + +# srun python test_n_obj.py --model lavt_one --swin_type base --dataset refcocog --splitBy umd --split test \ +# --resume checkpoints/random_550_lavt_one/model_best_mosaic_gref_umd_lavt_one.pth \ +# --workers 4 --ddp_trained_weights --window12 --img_size 480 \ +# --config config/n_obj/n_56.yaml + +# srun python test_n_obj.py --model lavt_one --swin_type base --dataset refcocog --splitBy umd --split test \ +# --resume checkpoints/random_550_lavt_one/model_best_mosaic_gref_umd_lavt_one.pth \ +# --workers 4 --ddp_trained_weights --window12 --img_size 480 \ +# --config config/n_obj/n_78.yaml \ No newline at end of file diff --git a/LAVT-RIS/donghwa/scripts/submit_test_seq_len.sh b/LAVT-RIS/donghwa/scripts/submit_test_seq_len.sh new file mode 100644 index 0000000000000000000000000000000000000000..3a8bd069597c13ebc10608410965a258a591221c --- /dev/null +++ b/LAVT-RIS/donghwa/scripts/submit_test_seq_len.sh @@ -0,0 +1,51 @@ +#!/bin/bash + +#SBATCH --job-name=sent_len # Submit a job named "example" +#SBATCH --mail-user=vip.maildummy@gmail.com +#SBATCH --mail-type=BEGIN,END,FAIL +#SBATCH --partition=a3000 # a6000 or a100 +#SBATCH --gres=gpu:1 +#SBATCH --time=7-00:00:00 # d-hh:mm:ss, max time limit +#SBATCH --mem=48000 # cpu memory size +#SBATCH --cpus-per-task=4 # cpu num +#SBATCH --output=log_refcocog_umd_repro_sent_len_2.txt # std output filename + +ml cuda/11.0 # 필요한 쿠다 버전 로드 +eval "$(conda shell.bash hook)" # Initialize Conda Environment +conda activate lavt # Activate your conda environment + + +# repro +# python test_sent_len.py --model lavt_one --swin_type base --dataset refcocog --splitBy umd --split test \ +# --resume checkpoints/repro_lavt_one/model_best_gref_umd_lavt_one.pth --workers 4 --ddp_trained_weights --window12 --img_size 480 \ +# --config config/sent_len_1_5.yaml + +python test_sent_len.py --model lavt_one --swin_type base --dataset refcocog --splitBy umd --split test \ + --resume checkpoints/repro_lavt_one/model_best_gref_umd_lavt_one.pth --workers 4 --ddp_trained_weights --window12 --img_size 480 \ + --config config/sent_len_6_7.yaml + +python test_sent_len.py --model lavt_one --swin_type base --dataset refcocog --splitBy umd --split test \ + --resume checkpoints/repro_lavt_one/model_best_gref_umd_lavt_one.pth --workers 4 --ddp_trained_weights --window12 --img_size 480 \ + --config config/sent_len_8_10.yaml + +python test_sent_len.py --model lavt_one --swin_type base --dataset refcocog --splitBy umd --split test \ + --resume checkpoints/repro_lavt_one/model_best_gref_umd_lavt_one.pth --workers 4 --ddp_trained_weights --window12 --img_size 480 \ + --config config/sent_len_11_20.yaml + +# best_model (Random_550_0up) + +# python test_sent_len.py --model lavt_one --swin_type base --dataset refcocog --splitBy umd --split test \ +# --resume checkpoints/random_550_lavt_one/model_best_mosaic_gref_umd_lavt_one.pth --workers 4 --ddp_trained_weights --window12 --img_size 480 \ +# --config config/sent_len_1_5.yaml + +# python test_sent_len.py --model lavt_one --swin_type base --dataset refcocog --splitBy umd --split test \ +# --resume checkpoints/random_550_lavt_one/model_best_mosaic_gref_umd_lavt_one.pth --workers 4 --ddp_trained_weights --window12 --img_size 480 \ +# --config config/sent_len_6_7.yaml + +# python test_sent_len.py --model lavt_one --swin_type base --dataset refcocog --splitBy umd --split test \ +# --resume checkpoints/random_550_lavt_one/model_best_mosaic_gref_umd_lavt_one.pth --workers 4 --ddp_trained_weights --window12 --img_size 480 \ +# --config config/sent_len_8_10.yaml + +# python test_sent_len.py --model lavt_one --swin_type base --dataset refcocog --splitBy umd --split test \ +# --resume checkpoints/random_550_lavt_one/model_best_mosaic_gref_umd_lavt_one.pth --workers 4 --ddp_trained_weights --window12 --img_size 480 \ +# --config config/sent_len_11_20.yaml \ No newline at end of file diff --git a/LAVT-RIS/donghwa/scripts/submit_train_grefcoco.sh b/LAVT-RIS/donghwa/scripts/submit_train_grefcoco.sh new file mode 100644 index 0000000000000000000000000000000000000000..94f2b7eba5813f3ca4e97d399fa23df6a6b869d2 --- /dev/null +++ b/LAVT-RIS/donghwa/scripts/submit_train_grefcoco.sh @@ -0,0 +1,26 @@ +#!/bin/bash + +#SBATCH --job-name=lavt_gcc # Submit a job named "example" +#SBATCH --mail-user=vip.maildummy@gmail.com +#SBATCH --mail-type=BEGIN,END,FAIL +#SBATCH --partition=a100 # a6000 or a100 +#SBATCH --gres=gpu:2 +#SBATCH --time=7-00:00:00 # d-hh:mm:ss, max time limit +#SBATCH --mem=84000 # cpu memory size +#SBATCH --cpus-per-task=8 # cpu num +#SBATCH --output=log_grefcoco_unc_lavt_one.txt # std output filename + +ml cuda/11.0 # 필요한 쿠다 버전 로드 +eval "$(conda shell.bash hook)" # Initialize Conda Environment +conda activate lavt # Activate your conda environment + + + +# train +# mkdir ./models + +# mkdir ./models/gref_unc +# CUDA_VISIBLE_DEVICES=0,1 python -m torch.distributed.launch --nproc_per_node 2 --master_port 12345 train.py --model lavt --dataset grefcoco --splitBy unc --model_id gref_unc --batch-size 14 --lr 0.00005 --wd 1e-2 --swin_type base --pretrained_swin_weights ./pretrained_weights/swin_base_patch4_window12_384_22k.pth --epochs 40 --img_size 480 2>&1 | tee ./models/gref_unc/output + +mkdir ./models/gref_unc_lavt_one +srun python -m torch.distributed.launch --nproc_per_node 2 --master_port 12226 train.py --model lavt_one --dataset grefcoco --splitBy unc --model_id gref_unc_lavt_one --batch-size 14 --lr 0.00005 --wd 1e-2 --swin_type base --pretrained_swin_weights ./pretrained_weights/swin_base_patch4_window12_384_22k.pth --epochs 50 --img_size 480 2>&1 | tee ./models/gref_unc_lavt_one/output \ No newline at end of file diff --git a/LAVT-RIS/donghwa/scripts/submit_train_grefcoco_mosaic.sh b/LAVT-RIS/donghwa/scripts/submit_train_grefcoco_mosaic.sh new file mode 100644 index 0000000000000000000000000000000000000000..384d2dcdfd958dacac5bef15689a3075ef8a495d --- /dev/null +++ b/LAVT-RIS/donghwa/scripts/submit_train_grefcoco_mosaic.sh @@ -0,0 +1,26 @@ +#!/bin/bash + +#SBATCH --job-name=lavt_gccm # Submit a job named "example" +#SBATCH --mail-user=vip.maildummy@gmail.com +#SBATCH --mail-type=BEGIN,END,FAIL +#SBATCH --partition=a100 # a6000 or a100 +#SBATCH --gres=gpu:2 +#SBATCH --time=7-00:00:00 # d-hh:mm:ss, max time limit +#SBATCH --mem=84000 # cpu memory size +#SBATCH --cpus-per-task=8 # cpu num +#SBATCH --output=log_mosaic_grefcoco_unc_lavt_one.txt # std output filename + +ml cuda/11.0 # 필요한 쿠다 버전 로드 +eval "$(conda shell.bash hook)" # Initialize Conda Environment +conda activate lavt # Activate your conda environment + + + +# train +# mkdir ./models + +# mkdir ./models/gref_unc +# CUDA_VISIBLE_DEVICES=0,1 python -m torch.distributed.launch --nproc_per_node 2 --master_port 12345 train_mosaic.py --model lavt --dataset grefcoco --splitBy unc --model_id gref_unc --batch-size 14 --lr 0.00005 --wd 1e-2 --swin_type base --pretrained_swin_weights ./pretrained_weights/swin_base_patch4_window12_384_22k.pth --epochs 40 --img_size 480 2>&1 | tee ./models/gref_unc/output + +mkdir ./models/mosaic_gref_unc_lavt_one +srun python -m torch.distributed.launch --nproc_per_node 2 --master_port 13336 train_mosaic.py --model lavt_one --dataset grefcoco --splitBy unc --model_id mosaic_gref_unc_lavt_one --batch-size 14 --lr 0.00005 --wd 1e-2 --swin_type base --pretrained_swin_weights ./pretrained_weights/swin_base_patch4_window12_384_22k.pth --epochs 50 --img_size 480 2>&1 | tee ./models/mosaic_gref_unc_lavt_one/output \ No newline at end of file diff --git a/LAVT-RIS/donghwa/scripts/submit_train_grefcoco_mosaic_retrieval.sh b/LAVT-RIS/donghwa/scripts/submit_train_grefcoco_mosaic_retrieval.sh new file mode 100644 index 0000000000000000000000000000000000000000..49b36d476abc3aacefe819d2007dd62c64aacf41 --- /dev/null +++ b/LAVT-RIS/donghwa/scripts/submit_train_grefcoco_mosaic_retrieval.sh @@ -0,0 +1,26 @@ +#!/bin/bash + +#SBATCH --job-name=lavt_gccr # Submit a job named "example" +#SBATCH --mail-user=vip.maildummy@gmail.com +#SBATCH --mail-type=BEGIN,END,FAIL +#SBATCH --partition=a100 # a6000 or a100 +#SBATCH --gres=gpu:2 +#SBATCH --time=7-00:00:00 # d-hh:mm:ss, max time limit +#SBATCH --mem=84000 # cpu memory size +#SBATCH --cpus-per-task=8 # cpu num +#SBATCH --output=log_retrieval_grefcoco_unc_lavt_one.txt # std output filename + +ml cuda/11.0 # 필요한 쿠다 버전 로드 +eval "$(conda shell.bash hook)" # Initialize Conda Environment +conda activate lavt # Activate your conda environment + + + +# train +# mkdir ./models + +# mkdir ./models/gref_unc +# CUDA_VISIBLE_DEVICES=0,1 python -m torch.distributed.launch --nproc_per_node 2 --master_port 12345 train_mosaic.py --model lavt --dataset grefcoco --splitBy unc --model_id gref_unc --batch-size 14 --lr 0.00005 --wd 1e-2 --swin_type base --pretrained_swin_weights ./pretrained_weights/swin_base_patch4_window12_384_22k.pth --epochs 40 --img_size 480 2>&1 | tee ./models/gref_unc/output + +mkdir ./models/retrieval_gref_unc_lavt_one +srun python -m torch.distributed.launch --nproc_per_node 1 --master_port 33336 train_mosaic_retrieval.py --model lavt_one --dataset grefcoco --splitBy unc --model_id retrieval_gref_unc_lavt_one --batch-size 2 --lr 0.00005 --wd 1e-2 --swin_type base --pretrained_swin_weights ./pretrained_weights/swin_base_patch4_window12_384_22k.pth --epochs 50 --img_size 480 --config config/train.yaml 2>&1 | tee ./models/retrieval_gref_unc_lavt_one/output \ No newline at end of file diff --git a/LAVT-RIS/donghwa/scripts/submit_train_refcoco+.sh b/LAVT-RIS/donghwa/scripts/submit_train_refcoco+.sh new file mode 100644 index 0000000000000000000000000000000000000000..645a14387cded29aaa711b79ad0e4b7f5c2159c8 --- /dev/null +++ b/LAVT-RIS/donghwa/scripts/submit_train_refcoco+.sh @@ -0,0 +1,26 @@ +#!/bin/bash + +#SBATCH --job-name=lavt_cc+ # Submit a job named "example" +#SBATCH --mail-user=vip.maildummy@gmail.com +#SBATCH --mail-type=BEGIN,END,FAIL +#SBATCH --partition=a100 # a6000 or a100 +#SBATCH --gres=gpu:2 +#SBATCH --time=7-00:00:00 # d-hh:mm:ss, max time limit +#SBATCH --mem=84000 # cpu memory size +#SBATCH --cpus-per-task=8 # cpu num +#SBATCH --output=log_refcoco+_lavt_one.txt # std output filename + +ml cuda/11.0 # 필요한 쿠다 버전 로드 +eval "$(conda shell.bash hook)" # Initialize Conda Environment +conda activate lavt # Activate your conda environment + + + +# train +# mkdir ./models + +# mkdir ./models/refcoco+ +# CUDA_VISIBLE_DEVICES=0,1,2,3 python -m torch.distributed.launch --nproc_per_node 4 --master_port 12345 train.py --model lavt --dataset refcoco+ --model_id refcoco+ --batch-size 8 --lr 0.00005 --wd 1e-2 --swin_type base --pretrained_swin_weights ./pretrained_weights/swin_base_patch4_window12_384_22k.pth --epochs 40 --img_size 480 2>&1 | tee ./models/refcoco+/output + +mkdir ./models/refcoco+_lavt_one +srun python -m torch.distributed.launch --nproc_per_node 2 --master_port 11115 train.py --model lavt_one --dataset refcoco+ --model_id refcoco+_lavt_one --batch-size 14 --lr 0.00005 --wd 1e-2 --swin_type base --pretrained_swin_weights ./pretrained_weights/swin_base_patch4_window12_384_22k.pth --epochs 50 --img_size 480 2>&1 | tee ./models/refcoco+_lavt_one/output diff --git a/LAVT-RIS/donghwa/scripts/submit_train_refcoco+_mosaic.sh b/LAVT-RIS/donghwa/scripts/submit_train_refcoco+_mosaic.sh new file mode 100644 index 0000000000000000000000000000000000000000..3cdf5e9c1c98a71984e77955889dc8c09ac51f5c --- /dev/null +++ b/LAVT-RIS/donghwa/scripts/submit_train_refcoco+_mosaic.sh @@ -0,0 +1,29 @@ +#!/bin/bash + +#SBATCH --job-name=lavt_cc+r # Submit a job named "example" +#SBATCH --mail-user=vip.maildummy@gmail.com +#SBATCH --mail-type=BEGIN,END,FAIL +#SBATCH --partition=a3000 # a6000 or a100 +#SBATCH --gres=gpu:2 +#SBATCH --time=7-00:00:00 # d-hh:mm:ss, max time limit +#SBATCH --mem=84000 # cpu memory size +#SBATCH --cpus-per-task=8 # cpu num +#SBATCH --output=log_refcoco+_random_460.txt # std output filename + +ml cuda/11.0 # 필요한 쿠다 버전 로드 +eval "$(conda shell.bash hook)" # Initialize Conda Environment +conda activate lavt # Activate your conda environment + + + +# train +# mkdir ./models + +# mkdir ./models/refcoco+ +# CUDA_VISIBLE_DEVICES=0,1,2,3 python -m torch.distributed.launch --nproc_per_node 4 --master_port 12345 train_mosaic.py --model lavt --dataset refcoco+ --model_id refcoco+ --batch-size 8 --lr 0.00005 --wd 1e-2 --swin_type base --pretrained_swin_weights ./pretrained_weights/swin_base_patch4_window12_384_22k.pth --epochs 40 --img_size 480 2>&1 | tee ./models/refcoco+/output + +# mkdir ./models/mosaic_refcoco+_lavt_one +# srun python -m torch.distributed.launch --nproc_per_node 2 --master_port 12348 train_mosaic.py --model lavt_one --dataset refcoco+ --model_id mosaic_refcoco+_lavt_one --batch-size 14 --lr 0.00005 --wd 1e-2 --swin_type base --pretrained_swin_weights ./pretrained_weights/swin_base_patch4_window12_384_22k.pth --epochs 50 --img_size 480 2>&1 | tee ./models/mosaic_refcoco+_lavt_one/output + +mkdir ./experiments/refcoco+_unc/refcoco+_random_460/ +srun python -m torch.distributed.launch --nproc_per_node 2 --master_port 92348 train_mosaic.py --model lavt_one --dataset refcoco+ --model_id refcoco+_random_460 --batch-size 16 --lr 0.00005 --wd 1e-2 --swin_type base --pretrained_swin_weights ./pretrained_weights/swin_base_patch4_window12_384_22k.pth --epochs 40 --img_size 480 --config config/random_460.yaml 2>&1 | tee ./experiments/refcoco+_unc/refcoco+_random_460/log.txt \ No newline at end of file diff --git a/LAVT-RIS/donghwa/scripts/submit_train_refcoco+_mosaic_retrieval.sh b/LAVT-RIS/donghwa/scripts/submit_train_refcoco+_mosaic_retrieval.sh new file mode 100644 index 0000000000000000000000000000000000000000..c38f1fa82e8a8728810dde503f3896330d0d66d8 --- /dev/null +++ b/LAVT-RIS/donghwa/scripts/submit_train_refcoco+_mosaic_retrieval.sh @@ -0,0 +1,26 @@ +#!/bin/bash + +#SBATCH --job-name=lavt_cc+r # Submit a job named "example" +#SBATCH --mail-user=vip.maildummy@gmail.com +#SBATCH --mail-type=BEGIN,END,FAIL +#SBATCH --partition=a100 # a6000 or a100 +#SBATCH --gres=gpu:2 +#SBATCH --time=7-00:00:00 # d-hh:mm:ss, max time limit +#SBATCH --mem=84000 # cpu memory size +#SBATCH --cpus-per-task=8 # cpu num +#SBATCH --output=log_retrieval_refcoco+_lavt_one.txt # std output filename + +ml cuda/11.0 # 필요한 쿠다 버전 로드 +eval "$(conda shell.bash hook)" # Initialize Conda Environment +conda activate lavt # Activate your conda environment + + + +# train +# mkdir ./models + +# mkdir ./models/refcoco+ +# CUDA_VISIBLE_DEVICES=0,1,2,3 python -m torch.distributed.launch --nproc_per_node 4 --master_port 12345 train_mosaic.py --model lavt --dataset refcoco+ --model_id refcoco+ --batch-size 8 --lr 0.00005 --wd 1e-2 --swin_type base --pretrained_swin_weights ./pretrained_weights/swin_base_patch4_window12_384_22k.pth --epochs 40 --img_size 480 2>&1 | tee ./models/refcoco+/output + +mkdir ./models/retrieval_refcoco+_OneStage_433_10wm6to3 +srun python -m torch.distributed.launch --nproc_per_node 2 --master_port 12348 train_mosaic_retrieval.py --model lavt_one --dataset refcoco+ --model_id retrieval_refcoco+_OneStage_433_10wm6to3 --batch-size 14 --lr 0.00005 --wd 1e-2 --swin_type base --pretrained_swin_weights ./pretrained_weights/swin_base_patch4_window12_384_22k.pth --epochs 50 --img_size 480 --config config/OneStage_433_10wm6to3.yaml 2>&1 | tee ./models/retrieval_refcoco+_OneStage_433_10wm6to3/output diff --git a/LAVT-RIS/donghwa/scripts/submit_train_refcoco+_mosaic_retrieval_filter.sh b/LAVT-RIS/donghwa/scripts/submit_train_refcoco+_mosaic_retrieval_filter.sh new file mode 100644 index 0000000000000000000000000000000000000000..94bd511351df20d0214100e047c28f46682aed89 --- /dev/null +++ b/LAVT-RIS/donghwa/scripts/submit_train_refcoco+_mosaic_retrieval_filter.sh @@ -0,0 +1,34 @@ +#!/bin/bash + +#SBATCH --job-name=lavt_cc+r # Submit a job named "example" +#SBATCH --mail-user=vip.maildummy@gmail.com +#SBATCH --mail-type=BEGIN,END,FAIL +#SBATCH --partition=a3000 # a6000 or a100 +#SBATCH --gres=gpu:2 +#SBATCH --time=7-00:00:00 # d-hh:mm:ss, max time limit +#SBATCH --mem=84000 # cpu memory size +#SBATCH --cpus-per-task=8 # cpu num +#SBATCH --output=log_refcoco+_retrieval_filter_433_10up.txt # std output filename + +ml cuda/11.0 # 필요한 쿠다 버전 로드 +eval "$(conda shell.bash hook)" # Initialize Conda Environment +conda activate lavt # Activate your conda environment + + +# train +# mkdir ./models + +# mkdir ./models/refcoco+ +# CUDA_VISIBLE_DEVICES=0,1,2,3 python -m torch.distributed.launch --nproc_per_node 4 --master_port 12345 train_mosaic.py --model lavt --dataset refcoco+ --model_id refcoco+ --batch-size 8 --lr 0.00005 --wd 1e-2 --swin_type base --pretrained_swin_weights ./pretrained_weights/swin_base_patch4_window12_384_22k.pth --epochs 40 --img_size 480 2>&1 | tee ./models/refcoco+/output + +# mkdir ./models/retrieval_refcoco+_OneStage_433_10wm6to3 +# srun python -m torch.distributed.launch --nproc_per_node 2 --master_port 12348 train_mosaic_retrieval.py --model lavt_one --dataset refcoco+ --model_id retrieval_refcoco+_OneStage_433_10wm6to3 --batch-size 14 --lr 0.00005 --wd 1e-2 --swin_type base --pretrained_swin_weights ./pretrained_weights/swin_base_patch4_window12_384_22k.pth --epochs 50 --img_size 480 --config config/OneStage_433_10wm6to3.yaml 2>&1 | tee ./models/retrieval_refcoco+_OneStage_433_10wm6to3/output + +mkdir ./experiments/refcoco+_unc/refcoco+_retrieval_filter_433_10up +srun python -m torch.distributed.launch --nproc_per_node 2 --master_port 72847 train_mosaic_retrieval_filter.py \ + --model lavt_one --dataset refcoco+ \ + --model_id refcoco+_retrieval_filter_433_10up --batch-size 16 --lr 0.00005 \ + --wd 1e-2 --swin_type base \ + --pretrained_swin_weights ./pretrained_weights/swin_base_patch4_window12_384_22k.pth \ + --epochs 40 --img_size 480 \ + --config config/retrieval_433_10up.yaml 2>&1 | tee ./experiments/refcoco+_unc/refcoco+_retrieval_filter_433_10up/log.txt diff --git a/LAVT-RIS/donghwa/scripts/submit_train_refcoco.sh b/LAVT-RIS/donghwa/scripts/submit_train_refcoco.sh new file mode 100644 index 0000000000000000000000000000000000000000..83a0793d3fdf1faa47d90a385bb65338d9a43251 --- /dev/null +++ b/LAVT-RIS/donghwa/scripts/submit_train_refcoco.sh @@ -0,0 +1,26 @@ +#!/bin/bash + +#SBATCH --job-name=lavt_cc # Submit a job named "example" +#SBATCH --mail-user=vip.maildummy@gmail.com +#SBATCH --mail-type=BEGIN,END,FAIL +#SBATCH --partition=a100 # a6000 or a100 +#SBATCH --gres=gpu:2 +#SBATCH --time=7-00:00:00 # d-hh:mm:ss, max time limit +#SBATCH --mem=84000 # cpu memory size +#SBATCH --cpus-per-task=8 # cpu num +#SBATCH --output=log_refcoco_lavt_one.txt # std output filename + +ml cuda/11.0 # 필요한 쿠다 버전 로드 +eval "$(conda shell.bash hook)" # Initialize Conda Environment +conda activate lavt # Activate your conda environment + + + +# train +# mkdir ./models + +# mkdir ./models/refcoco +# CUDA_VISIBLE_DEVICES=0,1,2,3 python -m torch.distributed.launch --nproc_per_node 4 --master_port 12345 train.py --model lavt --dataset refcoco --model_id refcoco --batch-size 8 --lr 0.00005 --wd 1e-2 --swin_type base --pretrained_swin_weights ./pretrained_weights/swin_base_patch4_window12_384_22k.pth --epochs 40 --img_size 480 2>&1 | tee ./models/refcoco/output + +mkdir ./models/refcoco_lavt_one +srun python -m torch.distributed.launch --nproc_per_node 2 --master_port 12349 train.py --model lavt_one --dataset refcoco --model_id refcoco_lavt_one --batch-size 14 --lr 0.00005 --wd 1e-2 --swin_type base --pretrained_swin_weights ./pretrained_weights/swin_base_patch4_window12_384_22k.pth --epochs 50 --img_size 480 2>&1 | tee ./models/refcoco_lavt_one/output diff --git a/LAVT-RIS/donghwa/scripts/submit_train_refcoco_mosaic.sh b/LAVT-RIS/donghwa/scripts/submit_train_refcoco_mosaic.sh new file mode 100644 index 0000000000000000000000000000000000000000..ac91006765ed734bbb5d6170ef21a3f726f052b7 --- /dev/null +++ b/LAVT-RIS/donghwa/scripts/submit_train_refcoco_mosaic.sh @@ -0,0 +1,26 @@ +#!/bin/bash + +#SBATCH --job-name=lavt_ccr # Submit a job named "example" +#SBATCH --mail-user=vip.maildummy@gmail.com +#SBATCH --mail-type=BEGIN,END,FAIL +#SBATCH --partition=a3000 # a6000 or a100 +#SBATCH --gres=gpu:2 +#SBATCH --time=7-00:00:00 # d-hh:mm:ss, max time limit +#SBATCH --mem=84000 # cpu memory size +#SBATCH --cpus-per-task=8 # cpu num +#SBATCH --output=log_refcoco_random_460.txt # std output filename + +ml cuda/11.0 # 필요한 쿠다 버전 로드 +eval "$(conda shell.bash hook)" # Initialize Conda Environment +conda activate lavt # Activate your conda environment + + + +# train +# mkdir ./models + +# mkdir ./models/refcoco +# CUDA_VISIBLE_DEVICES=0,1,2,3 python -m torch.distributed.launch --nproc_per_node 4 --master_port 12345 train_mosaic.py --model lavt --dataset refcoco --model_id refcoco --batch-size 8 --lr 0.00005 --wd 1e-2 --swin_type base --pretrained_swin_weights ./pretrained_weights/swin_base_patch4_window12_384_22k.pth --epochs 40 --img_size 480 2>&1 | tee ./models/refcoco/output + +mkdir ./experiments/refcoco_unc/refcoco_random_460/ +srun python -m torch.distributed.launch --nproc_per_node 2 --master_port 12347 train_mosaic.py --model lavt_one --dataset refcoco --model_id refcoco_random_460 --batch-size 16 --lr 0.00005 --wd 1e-2 --swin_type base --pretrained_swin_weights ./pretrained_weights/swin_base_patch4_window12_384_22k.pth --epochs 40 --img_size 480 --config config/random_460.yaml 2>&1 | tee ./experiments/refcoco_unc/refcoco_random_460/log.txt diff --git a/LAVT-RIS/donghwa/scripts/submit_train_refcoco_mosaic_retrieval.sh b/LAVT-RIS/donghwa/scripts/submit_train_refcoco_mosaic_retrieval.sh new file mode 100644 index 0000000000000000000000000000000000000000..39933044eb9c6faa10f7ead47127505803a3298b --- /dev/null +++ b/LAVT-RIS/donghwa/scripts/submit_train_refcoco_mosaic_retrieval.sh @@ -0,0 +1,27 @@ +#!/bin/bash + +#SBATCH --job-name=lavt_ccr # Submit a job named "example" +#SBATCH --mail-user=vip.maildummy@gmail.com +#SBATCH --mail-type=BEGIN,END,FAIL +#SBATCH --partition=a100 # a6000 or a100 +#SBATCH --gres=gpu:2 +#SBATCH --time=7-00:00:00 # d-hh:mm:ss, max time limit +#SBATCH --mem=84000 # cpu memory size +#SBATCH --cpus-per-task=8 # cpu num +#SBATCH --output=log_retrieval_refcoco_lavt_one.txt # std output filename + +ml cuda/11.0 # 필요한 쿠다 버전 로드 +eval "$(conda shell.bash hook)" # Initialize Conda Environment +conda activate lavt # Activate your conda environment + + + +# train +# mkdir ./models + +# mkdir ./models/refcoco +# CUDA_VISIBLE_DEVICES=0,1,2,3 python -m torch.distributed.launch --nproc_per_node 4 --master_port 12345 train_mosaic.py --model lavt --dataset refcoco --model_id refcoco --batch-size 8 --lr 0.00005 --wd 1e-2 --swin_type base --pretrained_swin_weights ./pretrained_weights/swin_base_patch4_window12_384_22k.pth --epochs 40 --img_size 480 2>&1 | tee ./models/refcoco/output + +# warmup +mkdir ./experiments/retrieval_refcoco_433_10wm6to3 +srun python -m torch.distributed.launch --nproc_per_node 2 --master_port 8247 train_mosaic_retrieval_warmup.py --model lavt_one --dataset refcoco --model_id retrieval_refcoco_433_10wm6to3 --resume ./checkpoints/model_best_retrieval_refcoco_433_10wm6to3.pth --batch-size 12 --lr 0.00005 --wd 1e-2 --swin_type base --pretrained_swin_weights ./pretrained_weights/swin_base_patch4_window12_384_22k.pth --epochs 50 --img_size 480 --config config/retrieval_433_10wm6to3.yaml 2>&1 | tee ./experiments/retrieval_refcoco_433_10wm6to3/log2.txt diff --git a/LAVT-RIS/donghwa/scripts/submit_train_refcoco_mosaic_retrieval_filter.sh b/LAVT-RIS/donghwa/scripts/submit_train_refcoco_mosaic_retrieval_filter.sh new file mode 100644 index 0000000000000000000000000000000000000000..2e064aa11ba803c965eb4ca1077db3dad96b7515 --- /dev/null +++ b/LAVT-RIS/donghwa/scripts/submit_train_refcoco_mosaic_retrieval_filter.sh @@ -0,0 +1,36 @@ +#!/bin/bash + +#SBATCH --job-name=lavt_ccr # Submit a job named "example" +#SBATCH --mail-user=vip.maildummy@gmail.com +#SBATCH --mail-type=BEGIN,END,FAIL +#SBATCH --partition=a3000 # a6000 or a100 +#SBATCH --gres=gpu:2 +#SBATCH --time=7-00:00:00 # d-hh:mm:ss, max time limit +#SBATCH --mem=84000 # cpu memory size +#SBATCH --cpus-per-task=8 # cpu num +#SBATCH --output=log_refcoco_retrieval_filter_433_10up.txt # std output filename + +ml cuda/11.0 # 필요한 쿠다 버전 로드 +eval "$(conda shell.bash hook)" # Initialize Conda Environment +conda activate lavt # Activate your conda environment + + + +# train +# mkdir ./models + +# mkdir ./models/refcoco +# CUDA_VISIBLE_DEVICES=0,1,2,3 python -m torch.distributed.launch --nproc_per_node 4 --master_port 12345 train_mosaic.py --model lavt --dataset refcoco --model_id refcoco --batch-size 8 --lr 0.00005 --wd 1e-2 --swin_type base --pretrained_swin_weights ./pretrained_weights/swin_base_patch4_window12_384_22k.pth --epochs 40 --img_size 480 2>&1 | tee ./models/refcoco/output + +# warmup +# mkdir ./experiments/retrieval_refcoco_433_10wm6to3 +# srun python -m torch.distributed.launch --nproc_per_node 2 --master_port 8247 train_mosaic_retrieval_warmup.py --model lavt_one --dataset refcoco --model_id retrieval_refcoco_433_10wm6to3 --resume ./checkpoints/model_best_retrieval_refcoco_433_10wm6to3.pth --batch-size 12 --lr 0.00005 --wd 1e-2 --swin_type base --pretrained_swin_weights ./pretrained_weights/swin_base_patch4_window12_384_22k.pth --epochs 50 --img_size 480 --config config/retrieval_433_10wm6to3.yaml 2>&1 | tee ./experiments/retrieval_refcoco_433_10wm6to3/log2.txt + +mkdir ./experiments/refcoco_unc/refcoco_retrieval_filter_433_10up +srun python -m torch.distributed.launch --nproc_per_node 2 --master_port 22947 train_mosaic_retrieval_filter.py \ + --model lavt_one --dataset refcoco \ + --model_id refcoco_retrieval_filter_433_10up --batch-size 16 --lr 0.00005 \ + --wd 1e-2 --swin_type base \ + --pretrained_swin_weights ./pretrained_weights/swin_base_patch4_window12_384_22k.pth \ + --epochs 40 --img_size 480 \ + --config config/retrieval_433_10up.yaml 2>&1 | tee ./experiments/refcoco_unc/refcoco_retrieval_filter_433_10up/log.txt diff --git a/LAVT-RIS/donghwa/scripts/submit_train_refcocog.sh b/LAVT-RIS/donghwa/scripts/submit_train_refcocog.sh new file mode 100644 index 0000000000000000000000000000000000000000..e1fd874022a33f10e8fee819fc74637368e8aa67 --- /dev/null +++ b/LAVT-RIS/donghwa/scripts/submit_train_refcocog.sh @@ -0,0 +1,31 @@ +#!/bin/bash + +#SBATCH --job-name=lavt_ccg # Submit a job named "example" +#SBATCH --mail-user=vip.maildummy@gmail.com +#SBATCH --mail-type=BEGIN,END,FAIL +#SBATCH --partition=a100 # a6000 or a100 +#SBATCH --gres=gpu:2 +#SBATCH --time=7-00:00:00 # d-hh:mm:ss, max time limit +#SBATCH --mem=84000 # cpu memory size +#SBATCH --cpus-per-task=8 # cpu num +#SBATCH --output=log_refcocog_google_lavt_one.txt # std output filename + +ml cuda/11.0 # 필요한 쿠다 버전 로드 +eval "$(conda shell.bash hook)" # Initialize Conda Environment +conda activate lavt # Activate your conda environment + + +# train +# mkdir ./models + +# mkdir ./models/gref_umd/ +# CUDA_VISIBLE_DEVICES=0,1 python -m torch.distributed.launch --nproc_per_node 2 --master_port 12345 train.py --model lavt --dataset refcocog --splitBy umd --model_id gref_umd --batch-size 14 --lr 0.00005 --wd 1e-2 --swin_type base --pretrained_swin_weights ./pretrained_weights/swin_base_patch4_window12_384_22k.pth --epochs 40 --img_size 480 2>&1 | tee ./models/gref_umd/output + +# mkdir ./models/gref_umd_lavt_one/ +# srun python -m torch.distributed.launch --nproc_per_node 2 --master_port 12345 train.py --model lavt_one --dataset refcocog --splitBy umd --model_id gref_umd_lavt_one --batch-size 14 --lr 0.00005 --wd 1e-2 --swin_type base --pretrained_swin_weights ./pretrained_weights/swin_base_patch4_window12_384_22k.pth --epochs 40 --img_size 480 2>&1 | tee ./models/gref_umd_lavt_one/output + +# mkdir ./models/gref_google +# CUDA_VISIBLE_DEVICES=0,1,2,3 python -m torch.distributed.launch --nproc_per_node 4 --master_port 12345 train.py --model lavt --dataset refcocog --splitBy google --model_id gref_google --batch-size 8 --lr 0.00005 --wd 1e-2 --swin_type base --pretrained_swin_weights ./pretrained_weights/swin_base_patch4_window12_384_22k.pth --epochs 40 --img_size 480 2>&1 | tee ./models/gref_google/output + +mkdir ./models/gref_google_lavt_one +srun python -m torch.distributed.launch --nproc_per_node 2 --master_port 12347 train.py --model lavt_one --dataset refcocog --splitBy google --model_id gref_google_lavt_one --batch-size 14 --lr 0.00005 --wd 1e-2 --swin_type base --pretrained_swin_weights ./pretrained_weights/swin_base_patch4_window12_384_22k.pth --epochs 50 --img_size 480 2>&1 | tee ./models/gref_google_lavt_one/output \ No newline at end of file diff --git a/LAVT-RIS/donghwa/scripts/submit_train_refcocog_mosaic.sh b/LAVT-RIS/donghwa/scripts/submit_train_refcocog_mosaic.sh new file mode 100644 index 0000000000000000000000000000000000000000..9f642e241b777700584588ffa09cd4f003b2f86f --- /dev/null +++ b/LAVT-RIS/donghwa/scripts/submit_train_refcocog_mosaic.sh @@ -0,0 +1,43 @@ +#!/bin/bash + +#SBATCH --job-name=lavt_ccggr # Submit a job named "example" +#SBATCH --mail-user=vip.maildummy@gmail.com +#SBATCH --mail-type=BEGIN,END,FAIL +#SBATCH --partition=a3000 # a6000 or a100 +#SBATCH --gres=gpu:2 +#SBATCH --time=7-00:00:00 # d-hh:mm:ss, max time limit +#SBATCH --mem=84000 # cpu memory size +#SBATCH --cpus-per-task=8 # cpu num +#SBATCH --output=log_refcocog_google_random_460_0up_resume.txt # std output filename + +ml cuda/11.0 # 필요한 쿠다 버전 로드 +eval "$(conda shell.bash hook)" # Initialize Conda Environment +conda activate lavt # Activate your conda environment + + + +# train +# mkdir ./models + +# mkdir ./models/gref_umd/ +# srun python -m torch.distributed.launch --nproc_per_node 2 --master_port 12345 train_mosaic.py --model lavt --dataset refcocog --splitBy umd --model_id gref_umd --batch-size 14 --lr 0.00005 --wd 1e-2 --swin_type base --pretrained_swin_weights ./pretrained_weights/swin_base_patch4_window12_384_22k.pth --epochs 40 --img_size 480 2>&1 | tee ./models/gref_umd/output + +# mkdir ./models/mosaic_gref_umd_lavt_one/ +# srun python -m torch.distributed.launch --nproc_per_node 2 --master_port 12345 train_mosaic.py --model lavt_one --dataset refcocog --splitBy umd --model_id mosaic_gref_umd_lavt_one --batch-size 14 --lr 0.00005 --wd 1e-2 --swin_type base --pretrained_swin_weights ./pretrained_weights/swin_base_patch4_window12_384_22k.pth --epochs 40 --img_size 480 2>&1 | tee ./models/mosaic_gref_umd_lavt_one/output + +# mkdir ./models/gref_google +# srun python -m torch.distributed.launch --nproc_per_node 2 --master_port 12345 train_mosaic.py --model lavt_one --dataset refcocog --splitBy google --model_id gref_google_lavt_one --batch-size 8 --lr 0.00005 --wd 1e-2 --swin_type base --pretrained_swin_weights ./pretrained_weights/swin_base_patch4_window12_384_22k.pth --epochs 40 --img_size 480 2>&1 | tee ./models/mosaic_gref_google_lavt_one/output + +# mkdir ./models/mosaic_gref_google_lavt_one +# srun python -m torch.distributed.launch --nproc_per_node 2 --master_port 13347 train_mosaic.py --model lavt_one --dataset refcocog --splitBy google --model_id mosaic_gref_google_lavt_one --batch-size 14 --lr 0.00005 --wd 1e-2 --swin_type base --pretrained_swin_weights ./pretrained_weights/swin_base_patch4_window12_384_22k.pth --epochs 50 --img_size 480 2>&1 | tee ./models/mosaic_gref_google_lavt_one/output + +# tensorboard X +# srun python -m torch.distributed.launch --nproc_per_node 1 --master_port 14567 train_mosaic.py --model lavt_one --dataset refcocog --splitBy umd --model_id lmdb_test --batch-size 5 --lr 0.00005 --wd 1e-2 --swin_type base --pretrained_swin_weights ./pretrained_weights/swin_base_patch4_window12_384_22k.pth --epochs 50 --img_size 480 2>&1 | tee ./models/lmdb_test/output + +# tensorboard O +# mkdir ./experiments/refcocog_google/gref_google_random_460_0up +srun python -m torch.distributed.launch --nproc_per_node 2 --master_port 35327 train_mosaic.py \ + --model lavt_one --dataset refcocog --splitBy google --model_id gref_google_random_460_0up \ + --batch-size 16 --lr 0.00005 --wd 1e-2 --swin_type base --pretrained_swin_weights ./pretrained_weights/swin_base_patch4_window12_384_22k.pth \ + --epochs 40 --img_size 480 --config config/random_460.yaml \ + --resume experiments/refcocog_google/gref_google_random_460_0up/model_best_gref_google_random_460_0up.pth 2>&1 | tee ./experiments/refcocog_google/gref_google_random_460_0up/log_resume.txt diff --git a/LAVT-RIS/donghwa/scripts/submit_train_refcocog_mosaic_retrieval.sh b/LAVT-RIS/donghwa/scripts/submit_train_refcocog_mosaic_retrieval.sh new file mode 100644 index 0000000000000000000000000000000000000000..a7477bb770c08a4f059256e3e2fbad989f0d4608 --- /dev/null +++ b/LAVT-RIS/donghwa/scripts/submit_train_refcocog_mosaic_retrieval.sh @@ -0,0 +1,40 @@ +#!/bin/bash + +#SBATCH --job-name=lavt_ccgur # Submit a job named "example" +#SBATCH --mail-user=vip.maildummy@gmail.com +#SBATCH --mail-type=BEGIN,END,FAIL +#SBATCH --partition=a3000 # a6000 or a100 +#SBATCH --gres=gpu:2 +#SBATCH --time=7-00:00:00 # d-hh:mm:ss, max time limit +#SBATCH --mem=84000 # cpu memory size +#SBATCH --cpus-per-task=8 # cpu num +#SBATCH --output=log_retrieval_refcocog_umd_lavt_one.txt # std output filename + +ml cuda/11.0 # 필요한 쿠다 버전 로드 +eval "$(conda shell.bash hook)" # Initialize Conda Environment +conda activate lavt # Activate your conda environment + + + +# train +# mkdir ./models + +# mkdir ./models/gref_umd/ +# srun python -m torch.distributed.launch --nproc_per_node 2 --master_port 12345 train_mosaic.py --model lavt --dataset refcocog --splitBy umd --model_id gref_umd --batch-size 14 --lr 0.00005 --wd 1e-2 --swin_type base --pretrained_swin_weights ./pretrained_weights/swin_base_patch4_window12_384_22k.pth --epochs 40 --img_size 480 2>&1 | tee ./models/gref_umd/output + +# mkdir ./models/mosaic_gref_umd_lavt_one/ +# srun python -m torch.distributed.launch --nproc_per_node 2 --master_port 12345 train_mosaic.py --model lavt_one --dataset refcocog --splitBy umd --model_id mosaic_gref_umd_lavt_one --batch-size 14 --lr 0.00005 --wd 1e-2 --swin_type base --pretrained_swin_weights ./pretrained_weights/swin_base_patch4_window12_384_22k.pth --epochs 40 --img_size 480 2>&1 | tee ./models/mosaic_gref_umd_lavt_one/output + +# mkdir ./models/gref_google +# srun python -m torch.distributed.launch --nproc_per_node 2 --master_port 12345 train_mosaic.py --model lavt_one --dataset refcocog --splitBy google --model_id gref_google_lavt_one --batch-size 8 --lr 0.00005 --wd 1e-2 --swin_type base --pretrained_swin_weights ./pretrained_weights/swin_base_patch4_window12_384_22k.pth --epochs 40 --img_size 480 2>&1 | tee ./models/mosaic_gref_google_lavt_one/output + +mkdir ./experiments/retrieval_gref_umd_433_0up +srun python -m torch.distributed.launch --nproc_per_node 2 --master_port 23147 +train_mosaic_retrieval.py --model lavt_one --dataset refcocog --splitBy umd +--model_id retrieval_gref_umd_433_0up --batch-size 16 --lr 0.00005 +--wd 1e-2 --swin_type base +--pretrained_swin_weights ./pretrained_weights/swin_base_patch4_window12_384_22k.pth +--epochs 40 --img_size 480 +--config config/retrieval_433_0up.yaml +--resume ./checkpoints/model_best_retrieval_gref_umd_433_0up.pth +2>&1 | tee ./experiments/retrieval_gref_umd_433_0up/log2.txt diff --git a/LAVT-RIS/donghwa/scripts/submit_train_refcocog_mosaic_retrieval_filter.sh b/LAVT-RIS/donghwa/scripts/submit_train_refcocog_mosaic_retrieval_filter.sh new file mode 100644 index 0000000000000000000000000000000000000000..c1c2fdce5d9fbf012e9303b4ab037027ec91fa2b --- /dev/null +++ b/LAVT-RIS/donghwa/scripts/submit_train_refcocog_mosaic_retrieval_filter.sh @@ -0,0 +1,38 @@ +#!/bin/bash + +#SBATCH --job-name=lavt_ccggr # Submit a job named "example" +#SBATCH --mail-user=vip.maildummy@gmail.com +#SBATCH --mail-type=BEGIN,END,FAIL +#SBATCH --partition=a3000 # a6000 or a100 +#SBATCH --gres=gpu:2 +#SBATCH --time=7-00:00:00 # d-hh:mm:ss, max time limit +#SBATCH --mem=84000 # cpu memory size +#SBATCH --cpus-per-task=8 # cpu num +#SBATCH --output=log_refcocog_google_retrieval_filter_433_10up.txt # std output filename + +ml cuda/11.0 # 필요한 쿠다 버전 로드 +eval "$(conda shell.bash hook)" # Initialize Conda Environment +conda activate lavt # Activate your conda environment + + + +# train +# mkdir ./models + +# mkdir ./models/gref_umd/ +# srun python -m torch.distributed.launch --nproc_per_node 2 --master_port 12345 train_mosaic.py --model lavt --dataset refcocog --splitBy umd --model_id gref_umd --batch-size 14 --lr 0.00005 --wd 1e-2 --swin_type base --pretrained_swin_weights ./pretrained_weights/swin_base_patch4_window12_384_22k.pth --epochs 40 --img_size 480 2>&1 | tee ./models/gref_umd/output + +# mkdir ./models/mosaic_gref_umd_lavt_one/ +# srun python -m torch.distributed.launch --nproc_per_node 2 --master_port 12345 train_mosaic.py --model lavt_one --dataset refcocog --splitBy umd --model_id mosaic_gref_umd_lavt_one --batch-size 14 --lr 0.00005 --wd 1e-2 --swin_type base --pretrained_swin_weights ./pretrained_weights/swin_base_patch4_window12_384_22k.pth --epochs 40 --img_size 480 2>&1 | tee ./models/mosaic_gref_umd_lavt_one/output + +# mkdir ./models/gref_google +# srun python -m torch.distributed.launch --nproc_per_node 2 --master_port 12345 train_mosaic.py --model lavt_one --dataset refcocog --splitBy google --model_id gref_google_lavt_one --batch-size 8 --lr 0.00005 --wd 1e-2 --swin_type base --pretrained_swin_weights ./pretrained_weights/swin_base_patch4_window12_384_22k.pth --epochs 40 --img_size 480 2>&1 | tee ./models/mosaic_gref_google_lavt_one/output + +mkdir ./experiments/refcocog_google/retrieval_filter_gref_google_433_10up +srun python -m torch.distributed.launch --nproc_per_node 2 --master_port 83847 train_mosaic_retrieval_filter.py \ + --model lavt_one --dataset refcocog --splitBy google \ + --model_id retrieval_filter_gref_google_433_10up --batch-size 16 --lr 0.00005 \ + --wd 1e-2 --swin_type base \ + --pretrained_swin_weights ./pretrained_weights/swin_base_patch4_window12_384_22k.pth \ + --epochs 40 --img_size 480 \ + --config config/retrieval_433_10up.yaml 2>&1 | tee ./experiments/refcocog_google/retrieval_filter_gref_google_433_10up/log.txt diff --git a/LAVT-RIS/donghwa/test.py b/LAVT-RIS/donghwa/test.py new file mode 100644 index 0000000000000000000000000000000000000000..71a66268b7b064eacb2a206a2179ff1a04918675 --- /dev/null +++ b/LAVT-RIS/donghwa/test.py @@ -0,0 +1,152 @@ +import datetime +import os +import time + +import torch +import torch.utils.data +from torch import nn + +from bert.modeling_bert import BertModel +import torchvision + +from lib import segmentation +import transforms as T +import utils + +import numpy as np +from PIL import Image +import torch.nn.functional as F + + +def get_dataset(image_set, transform, args): + if args.dataset == "grefcoco": + from data.dataset_grefer import GReferDataset + ds = GReferDataset(args=args, + refer_root=args.refer_data_root, + dataset_name=args.dataset, + splitby=args.splitBy, + split=image_set, + image_root=os.path.join(args.refer_data_root, 'images/train2014') + ) + from data.utils import MosaicVisualization + fpath = os.path.join('coco-data-vis', args.model_id, image_set) + MosaicVisualization(ds, fpath) + else : + from data.dataset_refer_bert import ReferDataset + ds = ReferDataset(args, + split=image_set, + image_transforms=transform, + target_transforms=None, + eval_mode=True + ) + num_classes = 2 + return ds, num_classes + + +def evaluate(model, data_loader, bert_model, device): + model.eval() + metric_logger = utils.MetricLogger(delimiter=" ") + + # evaluation variables + cum_I, cum_U = 0, 0 + eval_seg_iou_list = [.5, .6, .7, .8, .9] + seg_correct = np.zeros(len(eval_seg_iou_list), dtype=np.int32) + seg_total = 0 + mean_IoU = [] + header = 'Test:' + + with torch.no_grad(): + for data in metric_logger.log_every(data_loader, 100, header): + image, target, sentences, attentions = data + image, target, sentences, attentions = image.to(device), target.to(device), \ + sentences.to(device), attentions.to(device) + sentences = sentences.squeeze(1) + attentions = attentions.squeeze(1) + target = target.cpu().data.numpy() + for j in range(sentences.size(-1)): + if bert_model is not None: + last_hidden_states = bert_model(sentences[:, :, j], attention_mask=attentions[:, :, j])[0] + embedding = last_hidden_states.permute(0, 2, 1) + output = model(image, embedding, l_mask=attentions[:, :, j].unsqueeze(-1)) + else: + output = model(image, sentences[:, :, j], l_mask=attentions[:, :, j]) + + output = output.cpu() + output_mask = output.argmax(1).data.numpy() + I, U = computeIoU(output_mask, target) + if U == 0: + this_iou = 0.0 + else: + this_iou = I*1.0/U + mean_IoU.append(this_iou) + cum_I += I + cum_U += U + for n_eval_iou in range(len(eval_seg_iou_list)): + eval_seg_iou = eval_seg_iou_list[n_eval_iou] + seg_correct[n_eval_iou] += (this_iou >= eval_seg_iou) + seg_total += 1 + + del image, target, sentences, attentions, output, output_mask + if bert_model is not None: + del last_hidden_states, embedding + + mean_IoU = np.array(mean_IoU) + mIoU = np.mean(mean_IoU) + print('Final results:') + print('Mean IoU is %.2f\n' % (mIoU*100.)) + results_str = '' + for n_eval_iou in range(len(eval_seg_iou_list)): + results_str += ' precision@%s = %.2f\n' % \ + (str(eval_seg_iou_list[n_eval_iou]), seg_correct[n_eval_iou] * 100. / seg_total) + results_str += ' overall IoU = %.2f\n' % (cum_I * 100. / cum_U) + print(results_str) + + +def get_transform(args): + transforms = [T.Resize(args.img_size, args.img_size), + T.ToTensor(), + T.Normalize(mean=[0.485, 0.456, 0.406], std=[0.229, 0.224, 0.225]) + ] + + return T.Compose(transforms) + + +def computeIoU(pred_seg, gd_seg): + I = np.sum(np.logical_and(pred_seg, gd_seg)) + U = np.sum(np.logical_or(pred_seg, gd_seg)) + + return I, U + + +def main(args): + device = torch.device(args.device) + dataset_test, _ = get_dataset(args.split, get_transform(args=args), args) + test_sampler = torch.utils.data.SequentialSampler(dataset_test) + data_loader_test = torch.utils.data.DataLoader(dataset_test, batch_size=1, + sampler=test_sampler, num_workers=args.workers) + print(args.model) + single_model = segmentation.__dict__[args.model](pretrained='',args=args) + checkpoint = torch.load(args.resume, map_location='cpu') + single_model.load_state_dict(checkpoint['model']) + model = single_model.to(device) + + if args.model != 'lavt_one': + model_class = BertModel + single_bert_model = model_class.from_pretrained(args.ck_bert) + # work-around for a transformers bug; need to update to a newer version of transformers to remove these two lines + if args.ddp_trained_weights: + single_bert_model.pooler = None + single_bert_model.load_state_dict(checkpoint['bert_model']) + bert_model = single_bert_model.to(device) + else: + bert_model = None + + evaluate(model, data_loader_test, bert_model, device=device) + + +if __name__ == "__main__": + from args import get_parser + parser = get_parser() + args = parser.parse_args() + print('Image size: {}'.format(str(args.img_size))) + main(args) diff --git a/LAVT-RIS/donghwa/test_gres.py b/LAVT-RIS/donghwa/test_gres.py new file mode 100644 index 0000000000000000000000000000000000000000..bb2e0491a985e0d8d0964d7b8a7ac7e51073fca0 --- /dev/null +++ b/LAVT-RIS/donghwa/test_gres.py @@ -0,0 +1,155 @@ +import datetime +import os +import time + +import torch +import torch.utils.data +from torch import nn + +from bert.modeling_bert import BertModel +import torchvision + +from lib import segmentation +import transforms as T +import utils + +import numpy as np +from PIL import Image +import torch.nn.functional as F + + +def get_dataset(image_set, transform, args): + if args.dataset == "grefcoco": + from data.dataset_grefer import GReferDataset + ds = GReferDataset(args=args, + refer_root=args.refer_data_root, + dataset_name=args.dataset, + splitby=args.splitBy, + split=image_set, + image_root=os.path.join(args.refer_data_root, 'images/train2014') + ) + from data.utils import MosaicVisualization + fpath = os.path.join('coco-data-vis', "_".join([args.dataset, args.splitBy, image_set])) + MosaicVisualization(ds, fpath) + else : + from data.dataset_refer_bert import ReferDataset + ds = ReferDataset(args, + split=image_set, + image_transforms=transform, + target_transforms=None, + eval_mode=True + ) + num_classes = 2 + return ds, num_classes + + +def evaluate(model, data_loader, bert_model, device): + model.eval() + metric_logger = utils.MetricLogger(delimiter=" ") + + # evaluation variables + cum_I, cum_U = 0, 0 + eval_seg_iou_list = [.5, .6, .7, .8, .9] + seg_correct = np.zeros(len(eval_seg_iou_list), dtype=np.int32) + seg_total = 0 + mean_IoU = [] + header = 'Test:' + + with torch.no_grad(): + for data in metric_logger.log_every(data_loader, 100, header): + image, target, sentences, attentions = data + image, target, sentences, attentions = image.to(device), target.to(device), \ + sentences.to(device), attentions.to(device) + sentences = sentences.squeeze(1) + attentions = attentions.squeeze(1) + target = target.cpu().data.numpy() + for j in range(sentences.size(-1)): + if bert_model is not None: + last_hidden_states = bert_model(sentences[:, :, j], attention_mask=attentions[:, :, j])[0] + embedding = last_hidden_states.permute(0, 2, 1) + output = model(image, embedding, l_mask=attentions[:, :, j].unsqueeze(-1)) + else: + output = model(image, sentences[:, :, j], l_mask=attentions[:, :, j]) + + output = output.cpu() + output_mask = output.argmax(1).data.numpy() + I, U = computeIoU(output_mask, target) + if U == 0: + this_iou = 0.0 + else: + this_iou = I*1.0/U + mean_IoU.append(this_iou) + cum_I += I + cum_U += U + for n_eval_iou in range(len(eval_seg_iou_list)): + eval_seg_iou = eval_seg_iou_list[n_eval_iou] + seg_correct[n_eval_iou] += (this_iou >= eval_seg_iou) + seg_total += 1 + + # for GRES + import pudb; pudb.set_trace() + + del image, target, sentences, attentions, output, output_mask + if bert_model is not None: + del last_hidden_states, embedding + + mean_IoU = np.array(mean_IoU) + mIoU = np.mean(mean_IoU) + print('Final results:') + print('Mean IoU is %.2f\n' % (mIoU*100.)) + results_str = '' + for n_eval_iou in range(len(eval_seg_iou_list)): + results_str += ' precision@%s = %.2f\n' % \ + (str(eval_seg_iou_list[n_eval_iou]), seg_correct[n_eval_iou] * 100. / seg_total) + results_str += ' overall IoU = %.2f\n' % (cum_I * 100. / cum_U) + print(results_str) + + +def get_transform(args): + transforms = [T.Resize(args.img_size, args.img_size), + T.ToTensor(), + T.Normalize(mean=[0.485, 0.456, 0.406], std=[0.229, 0.224, 0.225]) + ] + + return T.Compose(transforms) + + +def computeIoU(pred_seg, gd_seg): + I = np.sum(np.logical_and(pred_seg, gd_seg)) + U = np.sum(np.logical_or(pred_seg, gd_seg)) + + return I, U + + +def main(args): + device = torch.device(args.device) + dataset_test, _ = get_dataset(args.split, get_transform(args=args), args) + test_sampler = torch.utils.data.SequentialSampler(dataset_test) + data_loader_test = torch.utils.data.DataLoader(dataset_test, batch_size=1, + sampler=test_sampler, num_workers=args.workers) + print(args.model) + single_model = segmentation.__dict__[args.model](pretrained='',args=args) + checkpoint = torch.load(args.resume, map_location='cpu') + single_model.load_state_dict(checkpoint['model']) + model = single_model.to(device) + + if args.model != 'lavt_one': + model_class = BertModel + single_bert_model = model_class.from_pretrained(args.ck_bert) + # work-around for a transformers bug; need to update to a newer version of transformers to remove these two lines + if args.ddp_trained_weights: + single_bert_model.pooler = None + single_bert_model.load_state_dict(checkpoint['bert_model']) + bert_model = single_bert_model.to(device) + else: + bert_model = None + + evaluate(model, data_loader_test, bert_model, device=device) + + +if __name__ == "__main__": + from args import get_parser + parser = get_parser() + args = parser.parse_args() + print('Image size: {}'.format(str(args.img_size))) + main(args) diff --git a/LAVT-RIS/donghwa/test_mosaic.py b/LAVT-RIS/donghwa/test_mosaic.py new file mode 100644 index 0000000000000000000000000000000000000000..6c20b4a8639367e0c00f9c3b03214e09ea948b4b --- /dev/null +++ b/LAVT-RIS/donghwa/test_mosaic.py @@ -0,0 +1,235 @@ +import datetime +import os +import time + +import torch +import torch.utils.data +from torch import nn + +from functools import reduce +import operator +from bert.modeling_bert import BertModel + +import torchvision +from lib import segmentation + +import transforms as T +import utils +import numpy as np + +import torch.nn.functional as F + +import gc +from collections import OrderedDict +from data.utils import MosaicVisualization, COCOVisualization + +import albumentations as A +from albumentations.pytorch import ToTensorV2 + +def get_dataset(image_set, transform, args): + if args.dataset == "grefcoco": + # from data.dataset_grefer import GReferDataset + from data.dataset_grefer_mosaic import GReferDataset + ds = GReferDataset(args=args, + refer_root=args.refer_data_root, + dataset_name=args.dataset, + splitby=args.splitBy, + split=image_set, + image_root=os.path.join(args.refer_data_root, 'images/train2014') + ) + fpath = os.path.join('coco-data-vis-mosaic', args.model_id, image_set) + MosaicVisualization(ds, fpath) + else : + # from data.dataset_refer_bert import ReferDataset + from data.dataset_refer_bert_mosaic import ReferDataset + ds = ReferDataset(args, + split=image_set + ) + fpath = os.path.join('coco-data-vis-mosaic', args.model_id, image_set) + MosaicVisualization(ds, fpath) + num_classes = 2 + + return ds, num_classes + + +# IoU calculation for validation +def IoU(pred, gt): + pred = pred.argmax(1) + + intersection = torch.sum(torch.mul(pred, gt)) + union = torch.sum(torch.add(pred, gt)) - intersection + + if intersection == 0 or union == 0: + iou = 0 + else: + iou = float(intersection) / float(union) + + return iou, intersection, union + + +def get_transform(args): + transforms = [T.Resize(args.img_size, args.img_size), + T.ToTensor(), + T.Normalize(mean=[0.485, 0.456, 0.406], std=[0.229, 0.224, 0.225]) + ] + + return T.Compose(transforms) + + +def criterion(input, target): + weight = torch.FloatTensor([0.9, 1.1]).cuda() + return nn.functional.cross_entropy(input, target, weight=weight) + + +def evaluate(model, data_loader, bert_model=None): + model.eval() + metric_logger = utils.MetricLogger(delimiter=" ") + header = 'Test:' + total_its = 0 + acc_ious = 0 + + # evaluation variables + cum_I, cum_U = 0, 0 + eval_seg_iou_list = [.5, .6, .7, .8, .9] + seg_correct = np.zeros(len(eval_seg_iou_list), dtype=np.int32) + seg_total = 0 + mean_IoU = [] + + with torch.no_grad(): + for data in metric_logger.log_every(data_loader, 100, header): + total_its += 1 + image, target, sentences, attentions = data['image'], data['seg_target'], data['sentence'], data['attn_mask'] + image, target, sentences, attentions = image.cuda(non_blocking=True),\ + target.cuda(non_blocking=True),\ + sentences.cuda(non_blocking=True),\ + attentions.cuda(non_blocking=True) + + sentences = sentences.squeeze(1) + attentions = attentions.squeeze(1) + for j in range(sentences.size(-1)): + + if bert_model is not None: + last_hidden_states = bert_model(sentences, attention_mask=attentions)[0] + embedding = last_hidden_states.permute(0, 2, 1) # (B, 768, N_l) to make Conv1d happy + attentions = attentions.unsqueeze(dim=-1) # (B, N_l, 1) + output = model(image, embedding, l_mask=attentions) + else: + output = model(image, sentences[:,:,j], l_mask=attentions[:,:,j]) + + iou, I, U = IoU(output, target) + acc_ious += iou + mean_IoU.append(iou) + cum_I += I + cum_U += U + for n_eval_iou in range(len(eval_seg_iou_list)): + eval_seg_iou = eval_seg_iou_list[n_eval_iou] + seg_correct[n_eval_iou] += (iou >= eval_seg_iou) + seg_total += 1 + + # for GRES + + + iou = acc_ious / total_its + + mean_IoU = np.array(mean_IoU) + mIoU = np.mean(mean_IoU) + print('Final results:') + print('Mean IoU is %.2f\n' % (mIoU * 100.)) + results_str = '' + for n_eval_iou in range(len(eval_seg_iou_list)): + results_str += ' precision@%s = %.2f\n' % \ + (str(eval_seg_iou_list[n_eval_iou]), seg_correct[n_eval_iou] * 100. / seg_total) + results_str += ' overall IoU = %.2f\n' % (cum_I * 100. / cum_U) + print(results_str) + + return 100 * iou, 100 * cum_I / cum_U + + + +# def get_transform(args): +# transforms = T.Compose([ +# T.Resize(args.img_size, args.img_size), +# T.ToTensor(), +# T.Normalize(mean=[0.485, 0.456, 0.406], std=[0.229, 0.224, 0.225])]) +# return transforms + +def get_transform(args): + mean = (0.485, 0.456, 0.406) + std = (0.229, 0.224, 0.225) + transforms = A.Compose([ + A.Resize(args.img_size, args.img_size, always_apply=True), + A.Normalize(mean=mean, std=std), + ToTensorV2 (), + ]) #, + return transforms + + +def computeIoU(pred_seg, gd_seg): + I = np.sum(np.logical_and(pred_seg, gd_seg)) + U = np.sum(np.logical_or(pred_seg, gd_seg)) + return I, U + + +def main(args): + device = 'cuda' + dataset_test,_ = get_dataset(args.split, get_transform(args=args), args=args) + test_sampler = torch.utils.data.SequentialSampler(dataset_test) + data_loader_test = torch.utils.data.DataLoader( + dataset_test, batch_size=1, sampler=test_sampler, num_workers=args.workers) + + # model initialization + print(args.model) + model = segmentation.__dict__[args.model](pretrained=args.pretrained_swin_weights, + args=args) + model = torch.nn.SyncBatchNorm.convert_sync_batchnorm(model) + # model.cuda() + # model = torch.nn.parallel.DistributedDataParallel(model, device_ids=[args.local_rank], find_unused_parameters=True) + # single_model = model.module + + # make sure embedding layer size matches + model.text_encoder.resize_token_embeddings(len(dataset_test.tokenizer)) + model.cuda() + checkpoint = torch.load(args.resume, map_location='cpu') + model.load_state_dict(checkpoint['model'], strict=True) + + # evaluate(model, data_loader_test, device=device) + iou, overallIoU = evaluate(model, data_loader_test) + + print('Average object IoU {}'.format(iou)) + print('Overall IoU {}'.format(overallIoU)) + +def parse_args(): + parser = argparse.ArgumentParser(description='RefCOCO Test') + # parser.add_argument("--local_rank", + # type=int, + # help='local rank for DistributedDataParallel') + # parser.add_argument('--config', + # default='path to xxx.yaml', + # type=str, + # help='config file') + # parser.add_argument('--opts', + # default=None, + # nargs=argparse.REMAINDER, + # help='override some settings in the config.') + args = parser.parse_args() + assert args.config is not None + cfg = OmegaConf.load(args.config) + cfg['local_rank'] = args.local_rank + return cfg + +if __name__ == "__main__": + from args import get_parser + parser = get_parser() + args = parser.parse_args() + if args.config is not None : + from config.utils import CfgNode + cn = CfgNode(CfgNode.load_yaml_with_base(args.config)) + for k,v in cn.items(): + if not hasattr(args, k): + print('Warning: key %s not in args' %k) + setattr(args, k, v) + args = parser.parse_args(namespace=args) + print(args) + + print(f'Image size: {args.img_size}') + main(args) diff --git a/LAVT-RIS/donghwa/test_mosaic_retrieval.py b/LAVT-RIS/donghwa/test_mosaic_retrieval.py new file mode 100644 index 0000000000000000000000000000000000000000..9b415bfcbf99030d11579d9bd599398ffebc2fd2 --- /dev/null +++ b/LAVT-RIS/donghwa/test_mosaic_retrieval.py @@ -0,0 +1,233 @@ +import datetime +import os +import time + +import torch +import torch.utils.data +from torch import nn + +from functools import reduce +import operator +from bert.modeling_bert import BertModel + +import torchvision +from lib import segmentation + +import transforms as T +import utils +import numpy as np + +import torch.nn.functional as F + +import gc +from collections import OrderedDict +from data.utils import MosaicVisualization, COCOVisualization + +import albumentations as A +from albumentations.pytorch import ToTensorV2 + +def get_dataset(image_set, transform, args): + if args.dataset == "grefcoco": + # from data.dataset_grefer import GReferDataset + from data.dataset_grefer_mosaic_retrieval import GReferDataset + ds = GReferDataset(args=args, + refer_root=args.refer_data_root, + dataset_name=args.dataset, + splitby=args.splitBy, + split=image_set, + image_root=os.path.join(args.refer_data_root, 'images/train2014') + ) + fpath = os.path.join('coco-data-vis-retrieval', args.model_id, image_set) + MosaicVisualization(ds, fpath) + else : + # from data.dataset_refer_bert import ReferDataset + from data.dataset_refer_bert_mosaic_retrieval import ReferDataset + ds = ReferDataset(args, + split=image_set + ) + fpath = os.path.join('coco-data-vis-retrieval', args.model_id, image_set) + MosaicVisualization(ds, fpath) + num_classes = 2 + + return ds, num_classes + + +# IoU calculation for validation +def IoU(pred, gt): + pred = pred.argmax(1) + + intersection = torch.sum(torch.mul(pred, gt)) + union = torch.sum(torch.add(pred, gt)) - intersection + + if intersection == 0 or union == 0: + iou = 0 + else: + iou = float(intersection) / float(union) + + return iou, intersection, union + + +def get_transform(args): + transforms = [T.Resize(args.img_size, args.img_size), + T.ToTensor(), + T.Normalize(mean=[0.485, 0.456, 0.406], std=[0.229, 0.224, 0.225]) + ] + + return T.Compose(transforms) + + +def criterion(input, target): + weight = torch.FloatTensor([0.9, 1.1]).cuda() + return nn.functional.cross_entropy(input, target, weight=weight) + + +def evaluate(model, data_loader, bert_model=None): + model.eval() + metric_logger = utils.MetricLogger(delimiter=" ") + header = 'Test:' + total_its = 0 + acc_ious = 0 + + # evaluation variables + cum_I, cum_U = 0, 0 + eval_seg_iou_list = [.5, .6, .7, .8, .9] + seg_correct = np.zeros(len(eval_seg_iou_list), dtype=np.int32) + seg_total = 0 + mean_IoU = [] + + with torch.no_grad(): + for data in metric_logger.log_every(data_loader, 100, header): + total_its += 1 + image, target, sentences, attentions = data['image'], data['seg_target'], data['sentence'], data['attn_mask'] + image, target, sentences, attentions = image.cuda(non_blocking=True),\ + target.cuda(non_blocking=True),\ + sentences.cuda(non_blocking=True),\ + attentions.cuda(non_blocking=True) + + sentences = sentences.squeeze(1) + attentions = attentions.squeeze(1) + + if bert_model is not None: + last_hidden_states = bert_model(sentences, attention_mask=attentions)[0] + embedding = last_hidden_states.permute(0, 2, 1) # (B, 768, N_l) to make Conv1d happy + attentions = attentions.unsqueeze(dim=-1) # (B, N_l, 1) + output = model(image, embedding, l_mask=attentions) + else: + output = model(image, sentences, l_mask=attentions) + + iou, I, U = IoU(output, target) + acc_ious += iou + mean_IoU.append(iou) + cum_I += I + cum_U += U + for n_eval_iou in range(len(eval_seg_iou_list)): + eval_seg_iou = eval_seg_iou_list[n_eval_iou] + seg_correct[n_eval_iou] += (iou >= eval_seg_iou) + seg_total += 1 + + # for GRES + + + iou = acc_ious / total_its + + mean_IoU = np.array(mean_IoU) + mIoU = np.mean(mean_IoU) + print('Final results:') + print('Mean IoU is %.2f\n' % (mIoU * 100.)) + results_str = '' + for n_eval_iou in range(len(eval_seg_iou_list)): + results_str += ' precision@%s = %.2f\n' % \ + (str(eval_seg_iou_list[n_eval_iou]), seg_correct[n_eval_iou] * 100. / seg_total) + results_str += ' overall IoU = %.2f\n' % (cum_I * 100. / cum_U) + print(results_str) + + return 100 * iou, 100 * cum_I / cum_U + + + +# def get_transform(args): +# transforms = T.Compose([ +# T.Resize(args.img_size, args.img_size), +# T.ToTensor(), +# T.Normalize(mean=[0.485, 0.456, 0.406], std=[0.229, 0.224, 0.225])]) +# return transforms + +def get_transform(args): + mean = (0.485, 0.456, 0.406) + std = (0.229, 0.224, 0.225) + transforms = A.Compose([ + A.Resize(args.img_size, args.img_size, always_apply=True), + A.Normalize(mean=mean, std=std), + ToTensorV2 (), + ]) #, + return transforms + + +def computeIoU(pred_seg, gd_seg): + I = np.sum(np.logical_and(pred_seg, gd_seg)) + U = np.sum(np.logical_or(pred_seg, gd_seg)) + return I, U + + +def main(args): + device = 'cuda' + dataset_test,_ = get_dataset(args.split, get_transform(args=args), args=args) + test_sampler = torch.utils.data.SequentialSampler(dataset_test) + data_loader_test = torch.utils.data.DataLoader( + dataset_test, batch_size=1, sampler=test_sampler, num_workers=args.workers) + + # model initialization + print(args.model) + model = segmentation.__dict__[args.model](pretrained=args.pretrained_swin_weights, + args=args) + model = torch.nn.SyncBatchNorm.convert_sync_batchnorm(model) + # model.cuda() + # model = torch.nn.parallel.DistributedDataParallel(model, device_ids=[args.local_rank], find_unused_parameters=True) + # single_model = model.module + + # make sure embedding layer size matches + model.text_encoder.resize_token_embeddings(len(dataset_test.tokenizer)) + model.cuda() + checkpoint = torch.load(args.resume, map_location='cpu') + model.load_state_dict(checkpoint['model'], strict=True) + + # evaluate(model, data_loader_test, device=device) + iou, overallIoU = evaluate(model, data_loader_test) + + print('Average object IoU {}'.format(iou)) + print('Overall IoU {}'.format(overallIoU)) + +def parse_args(): + parser = argparse.ArgumentParser(description='RefCOCO Test') + # parser.add_argument("--local_rank", + # type=int, + # help='local rank for DistributedDataParallel') + # parser.add_argument('--config', + # default='path to xxx.yaml', + # type=str, + # help='config file') + # parser.add_argument('--opts', + # default=None, + # nargs=argparse.REMAINDER, + # help='override some settings in the config.') + args = parser.parse_args() + assert args.config is not None + cfg = OmegaConf.load(args.config) + cfg['local_rank'] = args.local_rank + return cfg + +if __name__ == "__main__": + from args import get_parser + parser = get_parser() + args = parser.parse_args() + if args.config is not None : + from config.utils import CfgNode + cn = CfgNode(CfgNode.load_yaml_with_base(args.config)) + for k,v in cn.items(): + if not hasattr(args, k): + print('Warning: key %s not in args' %k) + setattr(args, k, v) + args = parser.parse_args(namespace=args) + print(args) + print(f'Image size: {args.img_size}') + main(args) diff --git a/LAVT-RIS/donghwa/test_n_obj.py b/LAVT-RIS/donghwa/test_n_obj.py new file mode 100644 index 0000000000000000000000000000000000000000..67bf7e36f461120e10069a0bc70204e283cfa568 --- /dev/null +++ b/LAVT-RIS/donghwa/test_n_obj.py @@ -0,0 +1,160 @@ +import datetime +import os +import time + +import torch +import torch.utils.data +from torch import nn + +from bert.modeling_bert import BertModel +import torchvision + +from lib import segmentation +import transforms as T +import utils + +import numpy as np +from PIL import Image +import torch.nn.functional as F + + +def get_dataset(image_set, transform, args): + if args.dataset == "grefcoco": + from data.dataset_grefer import GReferDataset + ds = GReferDataset(args=args, + refer_root=args.refer_data_root, + dataset_name=args.dataset, + splitby=args.splitBy, + split=image_set, + image_root=os.path.join(args.refer_data_root, 'images/train2014') + ) + from data.utils import MosaicVisualization + fpath = os.path.join('coco-data-vis', args.model_id, image_set) + MosaicVisualization(ds, fpath) + else : + from data.dataset_refer_bert_n_obj import ReferDataset + ds = ReferDataset(args, + split=image_set, + image_transforms=transform, + target_transforms=None, + eval_mode=True + ) + num_classes = 2 + return ds, num_classes + + +def evaluate(model, data_loader, bert_model, device): + model.eval() + metric_logger = utils.MetricLogger(delimiter=" ") + + # evaluation variables + cum_I, cum_U = 0, 0 + eval_seg_iou_list = [.5, .6, .7, .8, .9] + seg_correct = np.zeros(len(eval_seg_iou_list), dtype=np.int32) + seg_total = 0 + mean_IoU = [] + header = 'Test:' + + with torch.no_grad(): + for data in metric_logger.log_every(data_loader, 100, header): + image, target, sentences, attentions = data + image, target, sentences, attentions = image.to(device), target.to(device), \ + sentences.to(device), attentions.to(device) + sentences = sentences.squeeze(1) + attentions = attentions.squeeze(1) + target = target.cpu().data.numpy() + for j in range(sentences.size(-1)): + if bert_model is not None: + last_hidden_states = bert_model(sentences[:, :, j], attention_mask=attentions[:, :, j])[0] + embedding = last_hidden_states.permute(0, 2, 1) + output = model(image, embedding, l_mask=attentions[:, :, j].unsqueeze(-1)) + else: + output = model(image, sentences[:, :, j], l_mask=attentions[:, :, j]) + + output = output.cpu() + output_mask = output.argmax(1).data.numpy() + I, U = computeIoU(output_mask, target) + if U == 0: + this_iou = 0.0 + else: + this_iou = I*1.0/U + mean_IoU.append(this_iou) + cum_I += I + cum_U += U + for n_eval_iou in range(len(eval_seg_iou_list)): + eval_seg_iou = eval_seg_iou_list[n_eval_iou] + seg_correct[n_eval_iou] += (this_iou >= eval_seg_iou) + seg_total += 1 + + del image, target, sentences, attentions, output, output_mask + if bert_model is not None: + del last_hidden_states, embedding + + mean_IoU = np.array(mean_IoU) + mIoU = np.mean(mean_IoU) + print('Final results:') + print('Mean IoU is %.2f\n' % (mIoU*100.)) + results_str = '' + for n_eval_iou in range(len(eval_seg_iou_list)): + results_str += ' precision@%s = %.2f\n' % \ + (str(eval_seg_iou_list[n_eval_iou]), seg_correct[n_eval_iou] * 100. / seg_total) + results_str += ' overall IoU = %.2f\n' % (cum_I * 100. / cum_U) + print(results_str) + + +def get_transform(args): + transforms = [T.Resize(args.img_size, args.img_size), + T.ToTensor(), + T.Normalize(mean=[0.485, 0.456, 0.406], std=[0.229, 0.224, 0.225]) + ] + + return T.Compose(transforms) + + +def computeIoU(pred_seg, gd_seg): + I = np.sum(np.logical_and(pred_seg, gd_seg)) + U = np.sum(np.logical_or(pred_seg, gd_seg)) + + return I, U + + +def main(args): + device = torch.device(args.device) + dataset_test, _ = get_dataset(args.split, get_transform(args=args), args) + test_sampler = torch.utils.data.SequentialSampler(dataset_test) + data_loader_test = torch.utils.data.DataLoader(dataset_test, batch_size=1, + sampler=test_sampler, num_workers=args.workers) + print(args.model) + single_model = segmentation.__dict__[args.model](pretrained='',args=args) + checkpoint = torch.load(args.resume, map_location='cpu') + single_model.load_state_dict(checkpoint['model']) + model = single_model.to(device) + + if args.model != 'lavt_one': + model_class = BertModel + single_bert_model = model_class.from_pretrained(args.ck_bert) + # work-around for a transformers bug; need to update to a newer version of transformers to remove these two lines + if args.ddp_trained_weights: + single_bert_model.pooler = None + single_bert_model.load_state_dict(checkpoint['bert_model']) + bert_model = single_bert_model.to(device) + else: + bert_model = None + + evaluate(model, data_loader_test, bert_model, device=device) + + +if __name__ == "__main__": + from args import get_parser + parser = get_parser() + args = parser.parse_args() + if args.config is not None : + from config.utils import CfgNode + cn = CfgNode(CfgNode.load_yaml_with_base(args.config)) + for k,v in cn.items(): + if not hasattr(args, k): + print('Warning: key %s not in args' %k) + setattr(args, k, v) + args = parser.parse_args(namespace=args) + print('Image size: {}'.format(str(args.img_size))) + main(args) diff --git a/LAVT-RIS/donghwa/test_sent_len.py b/LAVT-RIS/donghwa/test_sent_len.py new file mode 100644 index 0000000000000000000000000000000000000000..cd3f622e5ee563650c04b3fc48f463d39384c737 --- /dev/null +++ b/LAVT-RIS/donghwa/test_sent_len.py @@ -0,0 +1,163 @@ +import datetime +import os +import time + +import torch +import torch.utils.data +from torch import nn + +from bert.modeling_bert import BertModel +import torchvision + +from lib import segmentation +import transforms as T +import utils + +import numpy as np +from PIL import Image +import torch.nn.functional as F + + +def get_dataset(image_set, transform, args): + if args.dataset == "grefcoco": + from data.dataset_grefer import GReferDataset + ds = GReferDataset(args=args, + refer_root=args.refer_data_root, + dataset_name=args.dataset, + splitby=args.splitBy, + split=image_set, + image_root=os.path.join(args.refer_data_root, 'images/train2014') + ) + from data.utils import MosaicVisualization + fpath = os.path.join('coco-data-vis', args.model_id, image_set) + MosaicVisualization(ds, fpath) + else : + from data.dataset_refer_bert_sent_len import ReferDataset + ds = ReferDataset(args, + split=image_set, + image_transforms=transform, + target_transforms=None, + eval_mode=True + ) + num_classes = 2 + return ds, num_classes + + +def evaluate(model, data_loader, bert_model, device, args): + model.eval() + metric_logger = utils.MetricLogger(delimiter=" ") + + # evaluation variables + cum_I, cum_U = 0, 0 + eval_seg_iou_list = [.5, .6, .7, .8, .9] + seg_correct = np.zeros(len(eval_seg_iou_list), dtype=np.int32) + seg_total = 0 + mean_IoU = [] + header = 'Test:' + + with torch.no_grad(): + for data in metric_logger.log_every(data_loader, 100, header): + image, target, sentences, attentions = data # + image, target, sentences, attentions = image.to(device), target.to(device), \ + sentences.to(device), attentions.to(device) + sentences = sentences.squeeze(1) + attentions = attentions.squeeze(1) + target = target.cpu().data.numpy() + for j in range(sentences.size(-1)): + # if sent_lens[:,0].item() < args.sent_len.min and sent_lens[:,0].item() > args.sent_len.max : + # break + if bert_model is not None: + last_hidden_states = bert_model(sentences[:, :, j], attention_mask=attentions[:, :, j])[0] + embedding = last_hidden_states.permute(0, 2, 1) + output = model(image, embedding, l_mask=attentions[:, :, j].unsqueeze(-1)) + else: + output = model(image, sentences[:, :, j], l_mask=attentions[:, :, j]) + + output = output.cpu() + output_mask = output.argmax(1).data.numpy() + I, U = computeIoU(output_mask, target) + if U == 0: + this_iou = 0.0 + else: + this_iou = I*1.0/U + mean_IoU.append(this_iou) + cum_I += I + cum_U += U + for n_eval_iou in range(len(eval_seg_iou_list)): + eval_seg_iou = eval_seg_iou_list[n_eval_iou] + seg_correct[n_eval_iou] += (this_iou >= eval_seg_iou) + seg_total += 1 + + del image, target, sentences, attentions, output, output_mask + if bert_model is not None: + del last_hidden_states, embedding + + mean_IoU = np.array(mean_IoU) + mIoU = np.mean(mean_IoU) + print('Final results:') + print('Mean IoU is %.2f\n' % (mIoU*100.)) + results_str = '' + for n_eval_iou in range(len(eval_seg_iou_list)): + results_str += ' precision@%s = %.2f\n' % \ + (str(eval_seg_iou_list[n_eval_iou]), seg_correct[n_eval_iou] * 100. / seg_total) + results_str += ' overall IoU = %.2f\n' % (cum_I * 100. / cum_U) + print(results_str) + + +def get_transform(args): + transforms = [T.Resize(args.img_size, args.img_size), + T.ToTensor(), + T.Normalize(mean=[0.485, 0.456, 0.406], std=[0.229, 0.224, 0.225]) + ] + + return T.Compose(transforms) + + +def computeIoU(pred_seg, gd_seg): + I = np.sum(np.logical_and(pred_seg, gd_seg)) + U = np.sum(np.logical_or(pred_seg, gd_seg)) + + return I, U + + +def main(args): + device = torch.device(args.device) + dataset_test, _ = get_dataset(args.split, get_transform(args=args), args) + test_sampler = torch.utils.data.SequentialSampler(dataset_test) + data_loader_test = torch.utils.data.DataLoader(dataset_test, batch_size=1, + sampler=test_sampler, num_workers=args.workers) + print(args.model) + single_model = segmentation.__dict__[args.model](pretrained='',args=args) + checkpoint = torch.load(args.resume, map_location='cpu') + single_model.load_state_dict(checkpoint['model']) + model = single_model.to(device) + + if args.model != 'lavt_one': + model_class = BertModel + single_bert_model = model_class.from_pretrained(args.ck_bert) + # work-around for a transformers bug; need to update to a newer version of transformers to remove these two lines + if args.ddp_trained_weights: + single_bert_model.pooler = None + single_bert_model.load_state_dict(checkpoint['bert_model']) + bert_model = single_bert_model.to(device) + else: + bert_model = None + + evaluate(model, data_loader_test, bert_model, device, args) + + +if __name__ == "__main__": + from args import get_parser + parser = get_parser() + args = parser.parse_args() + if args.config is not None : + from config.utils import CfgNode + cn = CfgNode(CfgNode.load_yaml_with_base(args.config)) + for k,v in cn.items(): + if not hasattr(args, k): + print('Warning: key %s not in args' %k) + setattr(args, k, v) + args = parser.parse_args(namespace=args) + print(args) + print('Image size: {}'.format(str(args.img_size))) + main(args) diff --git a/LAVT-RIS/donghwa/train.py b/LAVT-RIS/donghwa/train.py new file mode 100644 index 0000000000000000000000000000000000000000..aa95cbb543af1444a66645f1e1028d4dbb8b40b3 --- /dev/null +++ b/LAVT-RIS/donghwa/train.py @@ -0,0 +1,333 @@ +import datetime +import os +import time + +import torch +import torch.utils.data +from torch import nn + +from functools import reduce +import operator +from bert.modeling_bert import BertModel + +import torchvision +from lib import segmentation + +import transforms as T +import utils +import numpy as np + +import torch.nn.functional as F + +import gc +from collections import OrderedDict + +from data.utils import COCOVisualization +def get_dataset(image_set, transform, args): + if args.dataset == "grefcoco": + from data.dataset_grefer import GReferDataset + ds = GReferDataset(args=args, + refer_root=args.refer_data_root, + dataset_name=args.dataset, + splitby=args.splitBy, + split=image_set, + image_root=os.path.join(args.refer_data_root, 'images/train2014') + ) + + fpath = os.path.join('coco-data-vis', "_".join([args.dataset, args.splitBy, image_set])) + COCOVisualization(ds, fpath) + else : + from data.dataset_refer_bert import ReferDataset + ds = ReferDataset(args, + split=image_set, + image_transforms=transform, + target_transforms=None + ) + fpath = os.path.join('coco-data-vis', "_".join([args.dataset, args.splitBy, image_set])) + COCOVisualization(ds, fpath) + num_classes = 2 + + return ds, num_classes + + +# IoU calculation for validation +def IoU(pred, gt): + pred = pred.argmax(1) + + intersection = torch.sum(torch.mul(pred, gt)) + union = torch.sum(torch.add(pred, gt)) - intersection + + if intersection == 0 or union == 0: + iou = 0 + else: + iou = float(intersection) / float(union) + + return iou, intersection, union + + +def get_transform(args): + transforms = [T.Resize(args.img_size, args.img_size), + T.ToTensor(), + T.Normalize(mean=[0.485, 0.456, 0.406], std=[0.229, 0.224, 0.225]) + ] + + return T.Compose(transforms) + + +def criterion(input, target): + weight = torch.FloatTensor([0.9, 1.1]).cuda() + return nn.functional.cross_entropy(input, target, weight=weight) + + +def evaluate(model, data_loader, bert_model): + model.eval() + metric_logger = utils.MetricLogger(delimiter=" ") + header = 'Test:' + total_its = 0 + acc_ious = 0 + + # evaluation variables + cum_I, cum_U = 0, 0 + eval_seg_iou_list = [.5, .6, .7, .8, .9] + seg_correct = np.zeros(len(eval_seg_iou_list), dtype=np.int32) + seg_total = 0 + mean_IoU = [] + + with torch.no_grad(): + for data in metric_logger.log_every(data_loader, 100, header): + total_its += 1 + image, target, sentences, attentions = data + image, target, sentences, attentions = image.cuda(non_blocking=True),\ + target.cuda(non_blocking=True),\ + sentences.cuda(non_blocking=True),\ + attentions.cuda(non_blocking=True) + + sentences = sentences.squeeze(1) + attentions = attentions.squeeze(1) + + if bert_model is not None: + last_hidden_states = bert_model(sentences, attention_mask=attentions)[0] + embedding = last_hidden_states.permute(0, 2, 1) # (B, 768, N_l) to make Conv1d happy + attentions = attentions.unsqueeze(dim=-1) # (B, N_l, 1) + output = model(image, embedding, l_mask=attentions) + else: + output = model(image, sentences, l_mask=attentions) + + iou, I, U = IoU(output, target) + acc_ious += iou + mean_IoU.append(iou) + cum_I += I + cum_U += U + for n_eval_iou in range(len(eval_seg_iou_list)): + eval_seg_iou = eval_seg_iou_list[n_eval_iou] + seg_correct[n_eval_iou] += (iou >= eval_seg_iou) + seg_total += 1 + iou = acc_ious / total_its + + mean_IoU = np.array(mean_IoU) + mIoU = np.mean(mean_IoU) + print('Final results:') + print('Mean IoU is %.2f\n' % (mIoU * 100.)) + results_str = '' + for n_eval_iou in range(len(eval_seg_iou_list)): + results_str += ' precision@%s = %.2f\n' % \ + (str(eval_seg_iou_list[n_eval_iou]), seg_correct[n_eval_iou] * 100. / seg_total) + results_str += ' overall IoU = %.2f\n' % (cum_I * 100. / cum_U) + print(results_str) + + return 100 * iou, 100 * cum_I / cum_U + + +def train_one_epoch(model, criterion, optimizer, data_loader, lr_scheduler, epoch, print_freq, + iterations, bert_model): + model.train() + metric_logger = utils.MetricLogger(delimiter=" ") + metric_logger.add_meter('lr', utils.SmoothedValue(window_size=1, fmt='{value}')) + header = 'Epoch: [{}]'.format(epoch) + train_loss = 0 + total_its = 0 + + for data in metric_logger.log_every(data_loader, print_freq, header): + total_its += 1 + image, target, sentences, attentions = data + image, target, sentences, attentions = image.cuda(non_blocking=True),\ + target.cuda(non_blocking=True),\ + sentences.cuda(non_blocking=True),\ + attentions.cuda(non_blocking=True) + + sentences = sentences.squeeze(1) + attentions = attentions.squeeze(1) + + if bert_model is not None: + last_hidden_states = bert_model(sentences, attention_mask=attentions)[0] # (6, 10, 768) + embedding = last_hidden_states.permute(0, 2, 1) # (B, 768, N_l) to make Conv1d happy + attentions = attentions.unsqueeze(dim=-1) # (batch, N_l, 1) + output = model(image, embedding, l_mask=attentions) + else: + output = model(image, sentences, l_mask=attentions) + + loss = criterion(output, target) + optimizer.zero_grad() # set_to_none=True is only available in pytorch 1.6+ + loss.backward() + optimizer.step() + lr_scheduler.step() + + torch.cuda.synchronize() + train_loss += loss.item() + iterations += 1 + metric_logger.update(loss=loss.item(), lr=optimizer.param_groups[0]["lr"]) + + del image, target, sentences, attentions, loss, output, data + if bert_model is not None: + del last_hidden_states, embedding + + gc.collect() + torch.cuda.empty_cache() + torch.cuda.synchronize() + + +def main(args): + dataset, num_classes = get_dataset("train", + get_transform(args=args), + args=args) + dataset_test, _ = get_dataset("val", + get_transform(args=args), + args=args) + + # batch sampler + print(f"local rank {args.local_rank} / global rank {utils.get_rank()} successfully built train dataset.") + num_tasks = utils.get_world_size() + global_rank = utils.get_rank() + train_sampler = torch.utils.data.distributed.DistributedSampler(dataset, num_replicas=num_tasks, rank=global_rank, + shuffle=True) + test_sampler = torch.utils.data.SequentialSampler(dataset_test) + + # data loader + data_loader = torch.utils.data.DataLoader( + dataset, batch_size=args.batch_size, + sampler=train_sampler, num_workers=args.workers, pin_memory=args.pin_mem, drop_last=True) + + data_loader_test = torch.utils.data.DataLoader( + dataset_test, batch_size=1, sampler=test_sampler, num_workers=args.workers) + + # model initialization + print(args.model) + model = segmentation.__dict__[args.model](pretrained=args.pretrained_swin_weights, + args=args) + model = torch.nn.SyncBatchNorm.convert_sync_batchnorm(model) + model.cuda() + model = torch.nn.parallel.DistributedDataParallel(model, device_ids=[args.local_rank], find_unused_parameters=True) + single_model = model.module + + if args.model != 'lavt_one': + model_class = BertModel + bert_model = model_class.from_pretrained(args.ck_bert) + bert_model.pooler = None # a work-around for a bug in Transformers = 3.0.2 that appears for DistributedDataParallel + bert_model.cuda() + bert_model = torch.nn.SyncBatchNorm.convert_sync_batchnorm(bert_model) + bert_model = torch.nn.parallel.DistributedDataParallel(bert_model, device_ids=[args.local_rank]) + single_bert_model = bert_model.module + else: + bert_model = None + single_bert_model = None + + # resume training + if args.resume: + checkpoint = torch.load(args.resume, map_location='cpu') + single_model.load_state_dict(checkpoint['model']) + if args.model != 'lavt_one': + single_bert_model.load_state_dict(checkpoint['bert_model']) + + # parameters to optimize + backbone_no_decay = list() + backbone_decay = list() + for name, m in single_model.backbone.named_parameters(): + if 'norm' in name or 'absolute_pos_embed' in name or 'relative_position_bias_table' in name: + backbone_no_decay.append(m) + else: + backbone_decay.append(m) + + if args.model != 'lavt_one': + params_to_optimize = [ + {'params': backbone_no_decay, 'weight_decay': 0.0}, + {'params': backbone_decay}, + {"params": [p for p in single_model.classifier.parameters() if p.requires_grad]}, + # the following are the parameters of bert + {"params": reduce(operator.concat, + [[p for p in single_bert_model.encoder.layer[i].parameters() + if p.requires_grad] for i in range(10)])}, + ] + else: + params_to_optimize = [ + {'params': backbone_no_decay, 'weight_decay': 0.0}, + {'params': backbone_decay}, + {"params": [p for p in single_model.classifier.parameters() if p.requires_grad]}, + # the following are the parameters of bert + {"params": reduce(operator.concat, + [[p for p in single_model.text_encoder.encoder.layer[i].parameters() + if p.requires_grad] for i in range(10)])}, + ] + + # optimizer + optimizer = torch.optim.AdamW(params_to_optimize, + lr=args.lr, + weight_decay=args.weight_decay, + amsgrad=args.amsgrad + ) + + # learning rate scheduler + lr_scheduler = torch.optim.lr_scheduler.LambdaLR(optimizer, + lambda x: (1 - x / (len(data_loader) * args.epochs)) ** 0.9) + + # housekeeping + start_time = time.time() + iterations = 0 + best_oIoU = -0.1 + + # resume training (optimizer, lr scheduler, and the epoch) + if args.resume: + optimizer.load_state_dict(checkpoint['optimizer']) + lr_scheduler.load_state_dict(checkpoint['lr_scheduler']) + resume_epoch = checkpoint['epoch'] + else: + resume_epoch = -999 + + # training loops + for epoch in range(max(0, resume_epoch+1), args.epochs): + data_loader.sampler.set_epoch(epoch) + train_one_epoch(model, criterion, optimizer, data_loader, lr_scheduler, epoch, args.print_freq, + iterations, bert_model) + iou, overallIoU = evaluate(model, data_loader_test, bert_model) + + print('Average object IoU {}'.format(iou)) + print('Overall IoU {}'.format(overallIoU)) + save_checkpoint = (best_oIoU < overallIoU) + if save_checkpoint: + print('Better epoch: {}\n'.format(epoch)) + if single_bert_model is not None: + dict_to_save = {'model': single_model.state_dict(), 'bert_model': single_bert_model.state_dict(), + 'optimizer': optimizer.state_dict(), 'epoch': epoch, 'args': args, + 'lr_scheduler': lr_scheduler.state_dict()} + else: + dict_to_save = {'model': single_model.state_dict(), + 'optimizer': optimizer.state_dict(), 'epoch': epoch, 'args': args, + 'lr_scheduler': lr_scheduler.state_dict()} + + utils.save_on_master(dict_to_save, os.path.join(args.output_dir, + 'model_best_{}.pth'.format(args.model_id))) + best_oIoU = overallIoU + + # summarize + total_time = time.time() - start_time + total_time_str = str(datetime.timedelta(seconds=int(total_time))) + print('Training time {}'.format(total_time_str)) + + +if __name__ == "__main__": + from args import get_parser + parser = get_parser() + args = parser.parse_args() + # set up distributed learning + utils.init_distributed_mode(args) + print('Image size: {}'.format(str(args.img_size))) + main(args) diff --git a/LAVT-RIS/donghwa/train_mosaic.py b/LAVT-RIS/donghwa/train_mosaic.py new file mode 100644 index 0000000000000000000000000000000000000000..4ab079af713ece5aa5843ac3790037416a301116 --- /dev/null +++ b/LAVT-RIS/donghwa/train_mosaic.py @@ -0,0 +1,368 @@ +import datetime +import os +import time + +import torch +import torch.utils.data +from torch import nn + +from functools import reduce +import operator +from bert.modeling_bert import BertModel + +import torchvision +from lib import segmentation + +import transforms as T +import utils +import numpy as np + +import torch.nn.functional as F + +import gc +from collections import OrderedDict +from data.utils import MosaicVisualization, COCOVisualization +from torch.utils.tensorboard import SummaryWriter + +def get_dataset(image_set, transform, args): + if args.dataset == "grefcoco": + # from data.dataset_grefer import GReferDataset + from data.dataset_grefer_mosaic import GReferDataset + ds = GReferDataset(args=args, + refer_root=args.refer_data_root, + dataset_name=args.dataset, + splitby=args.splitBy, + split=image_set, + image_root=os.path.join(args.refer_data_root, 'images/train2014') + ) + fpath = os.path.join('coco-data-vis-mosaic', args.model_id, 'train') + MosaicVisualization(ds, fpath) + else : + from data.dataset_refer_bert_mosaic import ReferDataset + ds = ReferDataset(args, + split=image_set + ) + fpath = os.path.join('coco-data-vis-mosaic', args.model_id, image_set) + MosaicVisualization(ds, fpath) + num_classes = 2 + + return ds, num_classes + + +# IoU calculation for validation +def IoU(pred, gt): + pred = pred.argmax(1) + + intersection = torch.sum(torch.mul(pred, gt)) + union = torch.sum(torch.add(pred, gt)) - intersection + + if intersection == 0 or union == 0: + iou = 0 + else: + iou = float(intersection) / float(union) + + return iou, intersection, union + + +def get_transform(args): + transforms = [T.Resize(args.img_size, args.img_size), + T.ToTensor(), + T.Normalize(mean=[0.485, 0.456, 0.406], std=[0.229, 0.224, 0.225]) + ] + + return T.Compose(transforms) + + +def criterion(input, target): + weight = torch.FloatTensor([0.9, 1.1]).cuda() + return nn.functional.cross_entropy(input, target, weight=weight) + + +def evaluate(model, data_loader, bert_model): + model.eval() + metric_logger = utils.MetricLogger(delimiter=" ") + header = 'Test:' + total_its = 0 + acc_ious = 0 + + # evaluation variables + cum_I, cum_U = 0, 0 + eval_seg_iou_list = [.5, .6, .7, .8, .9] + seg_correct = np.zeros(len(eval_seg_iou_list), dtype=np.int32) + seg_total = 0 + mean_IoU = [] + + with torch.no_grad(): + for data in metric_logger.log_every(data_loader, 100, header): + total_its += 1 + image, target, sentences, attentions = data['image'], data['seg_target'], data['sentence'], data['attn_mask'] + image, target, sentences, attentions = image.cuda(non_blocking=True),\ + target.cuda(non_blocking=True),\ + sentences.cuda(non_blocking=True),\ + attentions.cuda(non_blocking=True) + + sentences = sentences.squeeze(1) + attentions = attentions.squeeze(1) + + if bert_model is not None: + last_hidden_states = bert_model(sentences, attention_mask=attentions)[0] + embedding = last_hidden_states.permute(0, 2, 1) # (B, 768, N_l) to make Conv1d happy + attentions = attentions.unsqueeze(dim=-1) # (B, N_l, 1) + output = model(image, embedding, l_mask=attentions) + else: + output = model(image, sentences, l_mask=attentions) + + iou, I, U = IoU(output, target) + acc_ious += iou + mean_IoU.append(iou) + cum_I += I + cum_U += U + for n_eval_iou in range(len(eval_seg_iou_list)): + eval_seg_iou = eval_seg_iou_list[n_eval_iou] + seg_correct[n_eval_iou] += (iou >= eval_seg_iou) + seg_total += 1 + + + iou = acc_ious / total_its + + mean_IoU = np.array(mean_IoU) + mIoU = np.mean(mean_IoU) + print('Final results:') + print('Mean IoU is %.2f\n' % (mIoU * 100.)) + results_str = '' + precs = [] + for n_eval_iou in range(len(eval_seg_iou_list)): + results_str += ' precision@%s = %.2f\n' % \ + (str(eval_seg_iou_list[n_eval_iou]), seg_correct[n_eval_iou] * 100. / seg_total) + precs.append(seg_correct[n_eval_iou] * 100. / seg_total) + results_str += ' overall IoU = %.2f\n' % (cum_I * 100. / cum_U) + print(results_str) + + return 100 * iou, 100 * cum_I / cum_U, precs + + +def train_one_epoch(model, criterion, optimizer, data_loader, lr_scheduler, epoch, print_freq, + iterations, bert_model): + model.train() + metric_logger = utils.MetricLogger(delimiter=" ") + metric_logger.add_meter('lr', utils.SmoothedValue(window_size=1, fmt='{value}')) + header = 'Epoch: [{}]'.format(epoch) + train_loss = 0 + total_its = 0 + + for data in metric_logger.log_every(data_loader, print_freq, header): + total_its += 1 + image, target, sentences, attentions = data['image'], data['seg_target'], data['sentence'], data['attn_mask'] + image, target, sentences, attentions = image.cuda(non_blocking=True),\ + target.cuda(non_blocking=True),\ + sentences.cuda(non_blocking=True),\ + attentions.cuda(non_blocking=True) + + sentences = sentences.squeeze(1) + attentions = attentions.squeeze(1) + + if bert_model is not None: + last_hidden_states = bert_model(sentences, attention_mask=attentions)[0] # (6, 10, 768) + embedding = last_hidden_states.permute(0, 2, 1) # (B, 768, N_l) to make Conv1d happy + attentions = attentions.unsqueeze(dim=-1) # (batch, N_l, 1) + output = model(image, embedding, l_mask=attentions) + else: + output = model(image, sentences, l_mask=attentions) + + loss = criterion(output, target) + optimizer.zero_grad() # set_to_none=True is only available in pytorch 1.6+ + loss.backward() + optimizer.step() + lr_scheduler.step() + + torch.cuda.synchronize() + train_loss += loss.item() + iterations += 1 + metric_logger.update(loss=loss.item(), lr=optimizer.param_groups[0]["lr"]) + + del image, target, sentences, attentions, loss, output, data + if bert_model is not None: + del last_hidden_states, embedding + + gc.collect() + torch.cuda.empty_cache() + torch.cuda.synchronize() + + loss_log = { + 'loss': metric_logger.meters['loss'].global_avg + } + return iterations, loss_log + + +def main(args): + writer = SummaryWriter('./experiments/{}/{}'.format("_".join([args.dataset, args.splitBy]), args.model_id)) + dataset, num_classes = get_dataset("train", + get_transform(args=args), + args=args) + dataset_test, _ = get_dataset("val", + get_transform(args=args), + args=args) + + # batch sampler + print(f"local rank {args.local_rank} / global rank {utils.get_rank()} successfully built train dataset.") + num_tasks = utils.get_world_size() + global_rank = utils.get_rank() + train_sampler = torch.utils.data.distributed.DistributedSampler(dataset, num_replicas=num_tasks, rank=global_rank, + shuffle=True) + test_sampler = torch.utils.data.SequentialSampler(dataset_test) + + # data loader + data_loader = torch.utils.data.DataLoader( + dataset, batch_size=args.batch_size, + sampler=train_sampler, num_workers=args.workers, pin_memory=args.pin_mem, drop_last=True) + + data_loader_test = torch.utils.data.DataLoader( + dataset_test, batch_size=1, sampler=test_sampler, num_workers=args.workers) + + # model initialization + print(args.model) + model = segmentation.__dict__[args.model](pretrained=args.pretrained_swin_weights, + args=args) + model = torch.nn.SyncBatchNorm.convert_sync_batchnorm(model) + model.cuda() + model = torch.nn.parallel.DistributedDataParallel(model, device_ids=[args.local_rank], find_unused_parameters=True) + single_model = model.module + + if args.model != 'lavt_one': + model_class = BertModel + bert_model = model_class.from_pretrained(args.ck_bert) + bert_model.pooler = None # a work-around for a bug in Transformers = 3.0.2 that appears for DistributedDataParallel + bert_model.cuda() + bert_model = torch.nn.SyncBatchNorm.convert_sync_batchnorm(bert_model) + bert_model = torch.nn.parallel.DistributedDataParallel(bert_model, device_ids=[args.local_rank]) + single_bert_model = bert_model.module + else: + bert_model = None + single_bert_model = None + + # resume training + if args.resume: + checkpoint = torch.load(args.resume, map_location='cpu') + single_model.load_state_dict(checkpoint['model']) + if args.model != 'lavt_one': + single_bert_model.load_state_dict(checkpoint['bert_model']) + + # parameters to optimize + backbone_no_decay = list() + backbone_decay = list() + for name, m in single_model.backbone.named_parameters(): + if 'norm' in name or 'absolute_pos_embed' in name or 'relative_position_bias_table' in name: + backbone_no_decay.append(m) + else: + backbone_decay.append(m) + + if args.model != 'lavt_one': + params_to_optimize = [ + {'params': backbone_no_decay, 'weight_decay': 0.0}, + {'params': backbone_decay}, + {"params": [p for p in single_model.classifier.parameters() if p.requires_grad]}, + # the following are the parameters of bert + {"params": reduce(operator.concat, + [[p for p in single_bert_model.encoder.layer[i].parameters() + if p.requires_grad] for i in range(10)])}, + ] + else: + params_to_optimize = [ + {'params': backbone_no_decay, 'weight_decay': 0.0}, + {'params': backbone_decay}, + {"params": [p for p in single_model.classifier.parameters() if p.requires_grad]}, + # the following are the parameters of bert + {"params": reduce(operator.concat, + [[p for p in single_model.text_encoder.encoder.layer[i].parameters() + if p.requires_grad] for i in range(10)])}, + ] + + # optimizer + optimizer = torch.optim.AdamW(params_to_optimize, + lr=args.lr, + weight_decay=args.weight_decay, + amsgrad=args.amsgrad + ) + + # learning rate scheduler + lr_scheduler = torch.optim.lr_scheduler.LambdaLR(optimizer, + lambda x: (1 - x / (len(data_loader) * args.epochs)) ** 0.9) + + # housekeeping + start_time = time.time() + iterations = 0 + best_oIoU = -0.1 + + # resume training (optimizer, lr scheduler, and the epoch) + if args.resume: + optimizer.load_state_dict(checkpoint['optimizer']) + lr_scheduler.load_state_dict(checkpoint['lr_scheduler']) + resume_epoch = checkpoint['epoch'] + else: + resume_epoch = -999 + + # training loops + for epoch in range(max(0, resume_epoch+1), args.epochs): + dataset.epoch = epoch + data_loader.sampler.set_epoch(epoch) + itrs_temp, loss_log = train_one_epoch(model, criterion, optimizer, data_loader, lr_scheduler, epoch, args.print_freq, + iterations, bert_model) + iterations += itrs_temp + iou, overallIoU, precs = evaluate(model, data_loader_test, bert_model) + + print('Average object IoU {}'.format(iou)) + print('Overall IoU {}'.format(overallIoU)) + save_checkpoint = (best_oIoU < overallIoU) + if save_checkpoint: + print('Better epoch: {}\n'.format(epoch)) + if single_bert_model is not None: + dict_to_save = {'model': single_model.state_dict(), 'bert_model': single_bert_model.state_dict(), + 'optimizer': optimizer.state_dict(), 'epoch': epoch, 'args': args, + 'lr_scheduler': lr_scheduler.state_dict()} + else: + dict_to_save = {'model': single_model.state_dict(), + 'optimizer': optimizer.state_dict(), 'epoch': epoch, 'args': args, + 'lr_scheduler': lr_scheduler.state_dict()} + + utils.save_on_master(dict_to_save, os.path.join(args.output_dir, + 'model_best_{}.pth'.format(args.model_id))) + best_oIoU = overallIoU + aug_prob = args.aug.aug_prob + if utils.is_main_process(): + writer.add_scalar('val/mIoU', iou, epoch) + writer.add_scalar('val/oIoU', overallIoU, epoch) + writer.add_scalar('val/Prec/50', precs[0], epoch) + writer.add_scalar('val/Prec/60', precs[1], epoch) + writer.add_scalar('val/Prec/70', precs[2], epoch) + writer.add_scalar('val/Prec/80', precs[3], epoch) + writer.add_scalar('val/Prec/90', precs[4], epoch) + writer.add_scalar('train/loss', loss_log['loss'], epoch) + writer.add_scalar('train/one_prob', 1-aug_prob, epoch) + # writer.add_scalar('train/retr_prob', retr_prob, epoch) + # writer.add_scalar('train/rand_prob', rand_prob, epoch) + + writer.flush() + # summarize + total_time = time.time() - start_time + total_time_str = str(datetime.timedelta(seconds=int(total_time))) + print('Training time {}'.format(total_time_str)) + + +if __name__ == "__main__": + from args import get_parser + parser = get_parser() + args = parser.parse_args() + if args.config is not None : + from config.utils import CfgNode + cn = CfgNode(CfgNode.load_yaml_with_base(args.config)) + for k,v in cn.items(): + if not hasattr(args, k): + print('Warning: key %s not in args' %k) + setattr(args, k, v) + args = parser.parse_args(namespace=args) + print(args) + args.output_dir = './experiments/{}/{}'.format("_".join([args.dataset, args.splitBy]), args.model_id) + # set up distributed learning + utils.init_distributed_mode(args) + print('Image size: {}'.format(str(args.img_size))) + main(args) diff --git a/LAVT-RIS/donghwa/train_mosaic_retrieval.py b/LAVT-RIS/donghwa/train_mosaic_retrieval.py new file mode 100644 index 0000000000000000000000000000000000000000..0141768f6928517010f90c4a6cdd315285ac961b --- /dev/null +++ b/LAVT-RIS/donghwa/train_mosaic_retrieval.py @@ -0,0 +1,391 @@ +import datetime +import os +import time + +import torch +import torch.utils.data +from torch import nn + +import yaml +from functools import reduce +import operator +from bert.modeling_bert import BertModel + +import torchvision +from lib import segmentation + +import transforms as T +import utils +import numpy as np + +import torch.nn.functional as F + +import gc +from collections import OrderedDict +from data.utils import MosaicVisualization, COCOVisualization +from torch.utils.tensorboard import SummaryWriter +from data.utils import get_warmup_value + +def get_dataset(image_set, transform, args): + + assert "retrieval" in args.model_id + if args.dataset == "grefcoco": + from data.dataset_grefer_mosaic_retrieval import GReferDataset + ds = GReferDataset(args=args, + refer_root=args.refer_data_root, + dataset_name=args.dataset, + splitby=args.splitBy, + split=image_set, + image_root=os.path.join(args.refer_data_root, 'images/train2014') + ) + + else : + from data.dataset_refer_bert_mosaic_retrieval import ReferDataset + ds = ReferDataset(args, + split=image_set + ) + + if image_set == "val" : + fpath = os.path.join('coco-data-vis-retrieval-filter', args.model_id, 'val') + MosaicVisualization(ds, fpath) + num_classes = 2 + + return ds, num_classes + + +# IoU calculation for validation +def IoU(pred, gt): + pred = pred.argmax(1) + + intersection = torch.sum(torch.mul(pred, gt)) + union = torch.sum(torch.add(pred, gt)) - intersection + + if intersection == 0 or union == 0: + iou = 0 + else: + iou = float(intersection) / float(union) + + return iou, intersection, union + + +def get_transform(args): + transforms = [T.Resize(args.img_size, args.img_size), + T.ToTensor(), + T.Normalize(mean=[0.485, 0.456, 0.406], std=[0.229, 0.224, 0.225]) + ] + + return T.Compose(transforms) + + +def criterion(input, target): + weight = torch.FloatTensor([0.9, 1.1]).cuda() + return nn.functional.cross_entropy(input, target, weight=weight) + + +def evaluate(model, data_loader, bert_model): + model.eval() + metric_logger = utils.MetricLogger(delimiter=" ") + header = 'Test:' + total_its = 0 + acc_ious = 0 + + # evaluation variables + cum_I, cum_U = 0, 0 + eval_seg_iou_list = [.5, .6, .7, .8, .9] + seg_correct = np.zeros(len(eval_seg_iou_list), dtype=np.int32) + seg_total = 0 + mean_IoU = [] + + with torch.no_grad(): + for data in metric_logger.log_every(data_loader, 100, header): + total_its += 1 + image, target, sentences, attentions = data['image'], data['seg_target'], data['sentence'], data['attn_mask'] + image, target, sentences, attentions = image.cuda(non_blocking=True),\ + target.cuda(non_blocking=True),\ + sentences.cuda(non_blocking=True),\ + attentions.cuda(non_blocking=True) + + sentences = sentences.squeeze(1) + attentions = attentions.squeeze(1) + + if bert_model is not None: + last_hidden_states = bert_model(sentences, attention_mask=attentions)[0] + embedding = last_hidden_states.permute(0, 2, 1) # (B, 768, N_l) to make Conv1d happy + attentions = attentions.unsqueeze(dim=-1) # (B, N_l, 1) + output = model(image, embedding, l_mask=attentions) + else: + output = model(image, sentences, l_mask=attentions) + + iou, I, U = IoU(output, target) + acc_ious += iou + mean_IoU.append(iou) + cum_I += I + cum_U += U + for n_eval_iou in range(len(eval_seg_iou_list)): + eval_seg_iou = eval_seg_iou_list[n_eval_iou] + seg_correct[n_eval_iou] += (iou >= eval_seg_iou) + seg_total += 1 + iou = acc_ious / total_its + + mean_IoU = np.array(mean_IoU) + mIoU = np.mean(mean_IoU) + print('Final results:') + print('Mean IoU is %.2f\n' % (mIoU * 100.)) + results_str = '' + precs = [] + for n_eval_iou in range(len(eval_seg_iou_list)): + results_str += ' precision@%s = %.2f\n' % \ + (str(eval_seg_iou_list[n_eval_iou]), seg_correct[n_eval_iou] * 100. / seg_total) + precs.append(seg_correct[n_eval_iou] * 100. / seg_total) + results_str += ' overall IoU = %.2f\n' % (cum_I * 100. / cum_U) + print(results_str) + + return 100 * iou, 100 * cum_I / cum_U, precs + + +def train_one_epoch(model, criterion, optimizer, data_loader, lr_scheduler, epoch, print_freq, + iterations, bert_model): + model.train() + metric_logger = utils.MetricLogger(delimiter=" ") + metric_logger.add_meter('lr', utils.SmoothedValue(window_size=1, fmt='{value}')) + header = 'Epoch: [{}]'.format(epoch) + train_loss = 0 + total_its = 0 + + for data in metric_logger.log_every(data_loader, print_freq, header): + total_its += 1 + image, target, sentences, attentions = data['image'], data['seg_target'], data['sentence'], data['attn_mask'] + image, target, sentences, attentions = image.cuda(non_blocking=True),\ + target.cuda(non_blocking=True),\ + sentences.cuda(non_blocking=True),\ + attentions.cuda(non_blocking=True) + + sentences = sentences.squeeze(1) + attentions = attentions.squeeze(1) + + if bert_model is not None: + last_hidden_states = bert_model(sentences, attention_mask=attentions)[0] # (6, 10, 768) + embedding = last_hidden_states.permute(0, 2, 1) # (B, 768, N_l) to make Conv1d happy + attentions = attentions.unsqueeze(dim=-1) # (batch, N_l, 1) + output = model(image, embedding, l_mask=attentions) + else: + output = model(image, sentences, l_mask=attentions) + + loss = criterion(output, target) + optimizer.zero_grad() # set_to_none=True is only available in pytorch 1.6+ + loss.backward() + optimizer.step() + lr_scheduler.step() + + torch.cuda.synchronize() + train_loss += loss.item() + iterations += 1 + metric_logger.update(loss=loss.item(), lr=optimizer.param_groups[0]["lr"]) + + del image, target, sentences, attentions, loss, output, data + if bert_model is not None: + del last_hidden_states, embedding + + gc.collect() + torch.cuda.empty_cache() + torch.cuda.synchronize() + + loss_log = { + 'loss': metric_logger.meters['loss'].global_avg + } + return iterations, loss_log + + +def main(args): + writer = SummaryWriter('./experiments/{}'.format(args.model_id)) + + dataset, num_classes = get_dataset("train", + get_transform(args=args), + args=args) + dataset_test, _ = get_dataset("val", + get_transform(args=args), + args=args) + + # batch sampler + print(f"local rank {args.local_rank} / global rank {utils.get_rank()} successfully built train dataset.") + num_tasks = utils.get_world_size() + global_rank = utils.get_rank() + train_sampler = torch.utils.data.distributed.DistributedSampler(dataset, num_replicas=num_tasks, rank=global_rank, + shuffle=True) + test_sampler = torch.utils.data.SequentialSampler(dataset_test) + + # data loader + data_loader = torch.utils.data.DataLoader( + dataset, batch_size=args.batch_size, + sampler=train_sampler, num_workers=args.workers, pin_memory=args.pin_mem, drop_last=True) + + data_loader_test = torch.utils.data.DataLoader( + dataset_test, batch_size=1, sampler=test_sampler, num_workers=args.workers) + + # model initialization + print(args.model) + model = segmentation.__dict__[args.model](pretrained=args.pretrained_swin_weights, + args=args) + model = torch.nn.SyncBatchNorm.convert_sync_batchnorm(model) + model.cuda() + model = torch.nn.parallel.DistributedDataParallel(model, device_ids=[args.local_rank], find_unused_parameters=True) + single_model = model.module + + if args.model != 'lavt_one': + model_class = BertModel + bert_model = model_class.from_pretrained(args.ck_bert) + bert_model.pooler = None # a work-around for a bug in Transformers = 3.0.2 that appears for DistributedDataParallel + bert_model.cuda() + bert_model = torch.nn.SyncBatchNorm.convert_sync_batchnorm(bert_model) + bert_model = torch.nn.parallel.DistributedDataParallel(bert_model, device_ids=[args.local_rank]) + single_bert_model = bert_model.module + else: + bert_model = None + single_bert_model = None + + # resume training + if args.resume: + checkpoint = torch.load(args.resume, map_location='cpu') + single_model.load_state_dict(checkpoint['model']) + if args.model != 'lavt_one': + single_bert_model.load_state_dict(checkpoint['bert_model']) + + # parameters to optimize + backbone_no_decay = list() + backbone_decay = list() + for name, m in single_model.backbone.named_parameters(): + if 'norm' in name or 'absolute_pos_embed' in name or 'relative_position_bias_table' in name: + backbone_no_decay.append(m) + else: + backbone_decay.append(m) + + if args.model != 'lavt_one': + params_to_optimize = [ + {'params': backbone_no_decay, 'weight_decay': 0.0}, + {'params': backbone_decay}, + {"params": [p for p in single_model.classifier.parameters() if p.requires_grad]}, + # the following are the parameters of bert + {"params": reduce(operator.concat, + [[p for p in single_bert_model.encoder.layer[i].parameters() + if p.requires_grad] for i in range(10)])}, + ] + else: + params_to_optimize = [ + {'params': backbone_no_decay, 'weight_decay': 0.0}, + {'params': backbone_decay}, + {"params": [p for p in single_model.classifier.parameters() if p.requires_grad]}, + # the following are the parameters of bert + {"params": reduce(operator.concat, + [[p for p in single_model.text_encoder.encoder.layer[i].parameters() + if p.requires_grad] for i in range(10)])}, + ] + + # optimizer + optimizer = torch.optim.AdamW(params_to_optimize, + lr=args.lr, + weight_decay=args.weight_decay, + amsgrad=args.amsgrad + ) + + # learning rate scheduler + lr_scheduler = torch.optim.lr_scheduler.LambdaLR(optimizer, + lambda x: (1 - x / (len(data_loader) * args.epochs)) ** 0.9) + + # housekeeping + start_time = time.time() + iterations = 0 + best_oIoU = -0.1 + + # resume training (optimizer, lr scheduler, and the epoch) + if args.resume: + optimizer.load_state_dict(checkpoint['optimizer']) + lr_scheduler.load_state_dict(checkpoint['lr_scheduler']) + resume_epoch = checkpoint['epoch'] + else: + resume_epoch = -999 + + # training loops + for epoch in range(max(0, resume_epoch+1), args.epochs): + dataset.epoch = epoch + data_loader.sampler.set_epoch(epoch) + if epoch%10 == 0: + fpath = os.path.join('coco-data-vis-retrieval', args.model_id, 'train', "epoch%02d"%epoch) + MosaicVisualization(dataset, fpath) + itrs_temp, loss_log = train_one_epoch(model, criterion, optimizer, data_loader, lr_scheduler, epoch, args.print_freq, + iterations, bert_model) + iterations += itrs_temp + iou, overallIoU, precs = evaluate(model, data_loader_test, bert_model) + + print('Average object IoU {}'.format(iou)) + print('Overall IoU {}'.format(overallIoU)) + save_checkpoint = (best_oIoU < overallIoU) + if save_checkpoint: + print('Better epoch: {}\n'.format(epoch)) + if single_bert_model is not None: + dict_to_save = {'model': single_model.state_dict(), 'bert_model': single_bert_model.state_dict(), + 'optimizer': optimizer.state_dict(), 'epoch': epoch, 'args': args, + 'lr_scheduler': lr_scheduler.state_dict()} + else: + dict_to_save = {'model': single_model.state_dict(), + 'optimizer': optimizer.state_dict(), 'epoch': epoch, 'args': args, + 'lr_scheduler': lr_scheduler.state_dict()} + + utils.save_on_master(dict_to_save, os.path.join(args.output_dir, + 'model_best_{}.pth'.format(args.model_id))) + best_oIoU = overallIoU + + # dataset_refer_bert_mosaic_retrieval_warmup.py + # aug_prob = args.aug.aug_prob # 0.6 + # retr_prob = args.aug.retr_prob # 0.3 + # rand_prob = aug_prob - retr_prob # 0.3 + + # if epoch < args.aug.warmup_epoch : + # retr_prob = get_warmup_value(0, retr_prob, epoch, args.aug.warmup_epoch) + # rand_prob = get_warmup_value(aug_prob, rand_prob, epoch, args.aug.warmup_epoch) + + aug_prob = args.aug.aug_prob + if epoch < args.aug.retrieval_epoch: + rand_prob = aug_prob + retr_prob = 0 + else : + rand_prob = args.aug.rand_prob + retr_prob = args.aug.retr_prob + + if utils.is_main_process(): + writer.add_scalar('val/mIoU', iou, epoch) + writer.add_scalar('val/oIoU', overallIoU, epoch) + writer.add_scalar('val/Prec/50', precs[0], epoch) + writer.add_scalar('val/Prec/60', precs[1], epoch) + writer.add_scalar('val/Prec/70', precs[2], epoch) + writer.add_scalar('val/Prec/80', precs[3], epoch) + writer.add_scalar('val/Prec/90', precs[4], epoch) + writer.add_scalar('train/loss', loss_log['loss'], epoch) + writer.add_scalar('train/one_prob', 1-aug_prob, epoch) + writer.add_scalar('train/retr_prob', retr_prob, epoch) + writer.add_scalar('train/rand_prob', rand_prob, epoch) + + writer.flush() + # summarize + total_time = time.time() - start_time + total_time_str = str(datetime.timedelta(seconds=int(total_time))) + print('Training time {}'.format(total_time_str)) + + +if __name__ == "__main__": + from args import get_parser + parser = get_parser() + args = parser.parse_args() + if args.config is not None : + from config.utils import CfgNode + cn = CfgNode(CfgNode.load_yaml_with_base(args.config)) + for k,v in cn.items(): + if not hasattr(args, k): + print('Warning: key %s not in args' %k) + setattr(args, k, v) + args = parser.parse_args(namespace=args) + print(args) + args.output_dir = './experiments/{}/{}'.format("_".join([args.dataset, args.splitBy]), args.model_id) + # set up distributed learning + utils.init_distributed_mode(args) + print('Image size: {}'.format(str(args.img_size))) + main(args) diff --git a/LAVT-RIS/donghwa/train_mosaic_retrieval_filter.py b/LAVT-RIS/donghwa/train_mosaic_retrieval_filter.py new file mode 100644 index 0000000000000000000000000000000000000000..790a9fec6fa5aadd83778032100938d35bcd235c --- /dev/null +++ b/LAVT-RIS/donghwa/train_mosaic_retrieval_filter.py @@ -0,0 +1,390 @@ +import datetime +import os +import time + +import torch +import torch.utils.data +from torch import nn + +import yaml +from functools import reduce +import operator +from bert.modeling_bert import BertModel + +import torchvision +from lib import segmentation + +import transforms as T +import utils +import numpy as np + +import torch.nn.functional as F + +import gc +from collections import OrderedDict +from data.utils import MosaicVisualization, COCOVisualization +from torch.utils.tensorboard import SummaryWriter + +def get_dataset(image_set, transform, args): + + assert "retrieval" in args.model_id + if args.dataset == "grefcoco": + from data.dataset_grefer_mosaic_retrieval import GReferDataset + ds = GReferDataset(args=args, + refer_root=args.refer_data_root, + dataset_name=args.dataset, + splitby=args.splitBy, + split=image_set, + image_root=os.path.join(args.refer_data_root, 'images/train2014') + ) + + else : + from data.dataset_refer_bert_mosaic_retrieval_filter import ReferDataset + ds = ReferDataset(args, + split=image_set + ) + + if image_set == "val" : + fpath = os.path.join('coco-data-vis-retrieval-filter', args.model_id, 'val') + MosaicVisualization(ds, fpath) + num_classes = 2 + + return ds, num_classes + + +# IoU calculation for validation +def IoU(pred, gt): + pred = pred.argmax(1) + + intersection = torch.sum(torch.mul(pred, gt)) + union = torch.sum(torch.add(pred, gt)) - intersection + + if intersection == 0 or union == 0: + iou = 0 + else: + iou = float(intersection) / float(union) + + return iou, intersection, union + + +def get_transform(args): + transforms = [T.Resize(args.img_size, args.img_size), + T.ToTensor(), + T.Normalize(mean=[0.485, 0.456, 0.406], std=[0.229, 0.224, 0.225]) + ] + + return T.Compose(transforms) + + +def criterion(input, target): + weight = torch.FloatTensor([0.9, 1.1]).cuda() + return nn.functional.cross_entropy(input, target, weight=weight) + + +def evaluate(model, data_loader, bert_model): + model.eval() + metric_logger = utils.MetricLogger(delimiter=" ") + header = 'Test:' + total_its = 0 + acc_ious = 0 + + # evaluation variables + cum_I, cum_U = 0, 0 + eval_seg_iou_list = [.5, .6, .7, .8, .9] + seg_correct = np.zeros(len(eval_seg_iou_list), dtype=np.int32) + seg_total = 0 + mean_IoU = [] + + with torch.no_grad(): + for data in metric_logger.log_every(data_loader, 100, header): + total_its += 1 + image, target, sentences, attentions = data['image'], data['seg_target'], data['sentence'], data['attn_mask'] + image, target, sentences, attentions = image.cuda(non_blocking=True),\ + target.cuda(non_blocking=True),\ + sentences.cuda(non_blocking=True),\ + attentions.cuda(non_blocking=True) + + sentences = sentences.squeeze(1) + attentions = attentions.squeeze(1) + + if bert_model is not None: + last_hidden_states = bert_model(sentences, attention_mask=attentions)[0] + embedding = last_hidden_states.permute(0, 2, 1) # (B, 768, N_l) to make Conv1d happy + attentions = attentions.unsqueeze(dim=-1) # (B, N_l, 1) + output = model(image, embedding, l_mask=attentions) + else: + output = model(image, sentences, l_mask=attentions) + + iou, I, U = IoU(output, target) + acc_ious += iou + mean_IoU.append(iou) + cum_I += I + cum_U += U + for n_eval_iou in range(len(eval_seg_iou_list)): + eval_seg_iou = eval_seg_iou_list[n_eval_iou] + seg_correct[n_eval_iou] += (iou >= eval_seg_iou) + seg_total += 1 + iou = acc_ious / total_its + + mean_IoU = np.array(mean_IoU) + mIoU = np.mean(mean_IoU) + print('Final results:') + print('Mean IoU is %.2f\n' % (mIoU * 100.)) + results_str = '' + precs = [] + for n_eval_iou in range(len(eval_seg_iou_list)): + results_str += ' precision@%s = %.2f\n' % \ + (str(eval_seg_iou_list[n_eval_iou]), seg_correct[n_eval_iou] * 100. / seg_total) + precs.append(seg_correct[n_eval_iou] * 100. / seg_total) + results_str += ' overall IoU = %.2f\n' % (cum_I * 100. / cum_U) + print(results_str) + + return 100 * iou, 100 * cum_I / cum_U, precs + + +def train_one_epoch(model, criterion, optimizer, data_loader, lr_scheduler, epoch, print_freq, + iterations, bert_model): + model.train() + metric_logger = utils.MetricLogger(delimiter=" ") + metric_logger.add_meter('lr', utils.SmoothedValue(window_size=1, fmt='{value}')) + header = 'Epoch: [{}]'.format(epoch) + train_loss = 0 + total_its = 0 + + for data in metric_logger.log_every(data_loader, print_freq, header): + total_its += 1 + image, target, sentences, attentions = data['image'], data['seg_target'], data['sentence'], data['attn_mask'] + image, target, sentences, attentions = image.cuda(non_blocking=True),\ + target.cuda(non_blocking=True),\ + sentences.cuda(non_blocking=True),\ + attentions.cuda(non_blocking=True) + + sentences = sentences.squeeze(1) + attentions = attentions.squeeze(1) + + if bert_model is not None: + last_hidden_states = bert_model(sentences, attention_mask=attentions)[0] # (6, 10, 768) + embedding = last_hidden_states.permute(0, 2, 1) # (B, 768, N_l) to make Conv1d happy + attentions = attentions.unsqueeze(dim=-1) # (batch, N_l, 1) + output = model(image, embedding, l_mask=attentions) + else: + output = model(image, sentences, l_mask=attentions) + + loss = criterion(output, target) + optimizer.zero_grad() # set_to_none=True is only available in pytorch 1.6+ + loss.backward() + optimizer.step() + lr_scheduler.step() + + torch.cuda.synchronize() + train_loss += loss.item() + iterations += 1 + metric_logger.update(loss=loss.item(), lr=optimizer.param_groups[0]["lr"]) + + del image, target, sentences, attentions, loss, output, data + if bert_model is not None: + del last_hidden_states, embedding + + gc.collect() + torch.cuda.empty_cache() + torch.cuda.synchronize() + + loss_log = { + 'loss': metric_logger.meters['loss'].global_avg + } + return iterations, loss_log + + +def main(args): + writer = SummaryWriter('./experiments/{}/{}'.format("_".join([args.dataset, args.splitBy]), args.model_id)) + + dataset, num_classes = get_dataset("train", + get_transform(args=args), + args=args) + dataset_test, _ = get_dataset("val", + get_transform(args=args), + args=args) + + # batch sampler + print(f"local rank {args.local_rank} / global rank {utils.get_rank()} successfully built train dataset.") + num_tasks = utils.get_world_size() + global_rank = utils.get_rank() + train_sampler = torch.utils.data.distributed.DistributedSampler(dataset, num_replicas=num_tasks, rank=global_rank, + shuffle=True) + test_sampler = torch.utils.data.SequentialSampler(dataset_test) + + # data loader + data_loader = torch.utils.data.DataLoader( + dataset, batch_size=args.batch_size, + sampler=train_sampler, num_workers=args.workers, pin_memory=args.pin_mem, drop_last=True) + + data_loader_test = torch.utils.data.DataLoader( + dataset_test, batch_size=1, sampler=test_sampler, num_workers=args.workers) + + # model initialization + print(args.model) + model = segmentation.__dict__[args.model](pretrained=args.pretrained_swin_weights, + args=args) + model = torch.nn.SyncBatchNorm.convert_sync_batchnorm(model) + model.cuda() + model = torch.nn.parallel.DistributedDataParallel(model, device_ids=[args.local_rank], find_unused_parameters=True) + single_model = model.module + + if args.model != 'lavt_one': + model_class = BertModel + bert_model = model_class.from_pretrained(args.ck_bert) + bert_model.pooler = None # a work-around for a bug in Transformers = 3.0.2 that appears for DistributedDataParallel + bert_model.cuda() + bert_model = torch.nn.SyncBatchNorm.convert_sync_batchnorm(bert_model) + bert_model = torch.nn.parallel.DistributedDataParallel(bert_model, device_ids=[args.local_rank]) + single_bert_model = bert_model.module + else: + bert_model = None + single_bert_model = None + + # resume training + if args.resume: + checkpoint = torch.load(args.resume, map_location='cpu') + single_model.load_state_dict(checkpoint['model']) + if args.model != 'lavt_one': + single_bert_model.load_state_dict(checkpoint['bert_model']) + + # parameters to optimize + backbone_no_decay = list() + backbone_decay = list() + for name, m in single_model.backbone.named_parameters(): + if 'norm' in name or 'absolute_pos_embed' in name or 'relative_position_bias_table' in name: + backbone_no_decay.append(m) + else: + backbone_decay.append(m) + + if args.model != 'lavt_one': + params_to_optimize = [ + {'params': backbone_no_decay, 'weight_decay': 0.0}, + {'params': backbone_decay}, + {"params": [p for p in single_model.classifier.parameters() if p.requires_grad]}, + # the following are the parameters of bert + {"params": reduce(operator.concat, + [[p for p in single_bert_model.encoder.layer[i].parameters() + if p.requires_grad] for i in range(10)])}, + ] + else: + params_to_optimize = [ + {'params': backbone_no_decay, 'weight_decay': 0.0}, + {'params': backbone_decay}, + {"params": [p for p in single_model.classifier.parameters() if p.requires_grad]}, + # the following are the parameters of bert + {"params": reduce(operator.concat, + [[p for p in single_model.text_encoder.encoder.layer[i].parameters() + if p.requires_grad] for i in range(10)])}, + ] + + # optimizer + optimizer = torch.optim.AdamW(params_to_optimize, + lr=args.lr, + weight_decay=args.weight_decay, + amsgrad=args.amsgrad + ) + + # learning rate scheduler + lr_scheduler = torch.optim.lr_scheduler.LambdaLR(optimizer, + lambda x: (1 - x / (len(data_loader) * args.epochs)) ** 0.9) + + # housekeeping + start_time = time.time() + iterations = 0 + best_oIoU = -0.1 + + # resume training (optimizer, lr scheduler, and the epoch) + if args.resume: + optimizer.load_state_dict(checkpoint['optimizer']) + lr_scheduler.load_state_dict(checkpoint['lr_scheduler']) + resume_epoch = checkpoint['epoch'] + else: + resume_epoch = -999 + + # training loops + for epoch in range(max(0, resume_epoch+1), args.epochs): + dataset.epoch = epoch + data_loader.sampler.set_epoch(epoch) + if epoch%10 == 0: + fpath = os.path.join('coco-data-vis-retrieval-filter', args.model_id, 'train', "epoch%02d"%epoch) + MosaicVisualization(dataset, fpath) + itrs_temp, loss_log = train_one_epoch(model, criterion, optimizer, data_loader, lr_scheduler, epoch, args.print_freq, + iterations, bert_model) + iterations += itrs_temp + iou, overallIoU, precs = evaluate(model, data_loader_test, bert_model) + + print('Average object IoU {}'.format(iou)) + print('Overall IoU {}'.format(overallIoU)) + save_checkpoint = (best_oIoU < overallIoU) + if save_checkpoint: + print('Better epoch: {}\n'.format(epoch)) + if single_bert_model is not None: + dict_to_save = {'model': single_model.state_dict(), 'bert_model': single_bert_model.state_dict(), + 'optimizer': optimizer.state_dict(), 'epoch': epoch, 'args': args, + 'lr_scheduler': lr_scheduler.state_dict()} + else: + dict_to_save = {'model': single_model.state_dict(), + 'optimizer': optimizer.state_dict(), 'epoch': epoch, 'args': args, + 'lr_scheduler': lr_scheduler.state_dict()} + + utils.save_on_master(dict_to_save, os.path.join(args.output_dir, + 'model_best_{}.pth'.format(args.model_id))) + best_oIoU = overallIoU + + # dataset_refer_bert_mosaic_retrieval_warmup.py + # aug_prob = args.aug.aug_prob # 0.6 + # retr_prob = args.aug.retr_prob # 0.3 + # rand_prob = aug_prob - retr_prob # 0.3 + + # if epoch < args.aug.warmup_epoch : + # retr_prob = get_warmup_value(0, retr_prob, epoch, args.aug.warmup_epoch) + # rand_prob = get_warmup_value(aug_prob, rand_prob, epoch, args.aug.warmup_epoch) + + aug_prob = args.aug.aug_prob + if epoch < args.aug.retrieval_epoch: + rand_prob = aug_prob + retr_prob = 0 + else : + rand_prob = args.aug.rand_prob + retr_prob = args.aug.retr_prob + + if utils.is_main_process(): + writer.add_scalar('val/mIoU', iou, epoch) + writer.add_scalar('val/oIoU', overallIoU, epoch) + writer.add_scalar('val/Prec/50', precs[0], epoch) + writer.add_scalar('val/Prec/60', precs[1], epoch) + writer.add_scalar('val/Prec/70', precs[2], epoch) + writer.add_scalar('val/Prec/80', precs[3], epoch) + writer.add_scalar('val/Prec/90', precs[4], epoch) + writer.add_scalar('train/loss', loss_log['loss'], epoch) + writer.add_scalar('train/one_prob', 1-aug_prob, epoch) + writer.add_scalar('train/retr_prob', retr_prob, epoch) + writer.add_scalar('train/rand_prob', rand_prob, epoch) + + writer.flush() + # summarize + total_time = time.time() - start_time + total_time_str = str(datetime.timedelta(seconds=int(total_time))) + print('Training time {}'.format(total_time_str)) + + +if __name__ == "__main__": + from args import get_parser + parser = get_parser() + args = parser.parse_args() + if args.config is not None : + from config.utils import CfgNode + cn = CfgNode(CfgNode.load_yaml_with_base(args.config)) + for k,v in cn.items(): + if not hasattr(args, k): + print('Warning: key %s not in args' %k) + setattr(args, k, v) + args = parser.parse_args(namespace=args) + print(args) + args.output_dir = './experiments/{}/{}'.format("_".join([args.dataset, args.splitBy]), args.model_id) + # set up distributed learning + utils.init_distributed_mode(args) + print('Image size: {}'.format(str(args.img_size))) + main(args) diff --git a/LAVT-RIS/donghwa/train_mosaic_retrieval_warmup.py b/LAVT-RIS/donghwa/train_mosaic_retrieval_warmup.py new file mode 100644 index 0000000000000000000000000000000000000000..e9a6dfa97e5bcc41e2358fdc643f3235fc27619f --- /dev/null +++ b/LAVT-RIS/donghwa/train_mosaic_retrieval_warmup.py @@ -0,0 +1,391 @@ +import datetime +import os +import time + +import torch +import torch.utils.data +from torch import nn + +import yaml +from functools import reduce +import operator +from bert.modeling_bert import BertModel + +import torchvision +from lib import segmentation + +import transforms as T +import utils +import numpy as np + +import torch.nn.functional as F + +import gc +from collections import OrderedDict +from data.utils import MosaicVisualization, COCOVisualization +from torch.utils.tensorboard import SummaryWriter +from data.utils import get_warmup_value + +def get_dataset(image_set, transform, args): + + assert "retrieval" in args.model_id + if args.dataset == "grefcoco": + from data.dataset_grefer_mosaic_retrieval import GReferDataset + ds = GReferDataset(args=args, + refer_root=args.refer_data_root, + dataset_name=args.dataset, + splitby=args.splitBy, + split=image_set, + image_root=os.path.join(args.refer_data_root, 'images/train2014') + ) + + else : + from data.dataset_refer_bert_mosaic_retrieval_warmup import ReferDataset + ds = ReferDataset(args, + split=image_set + ) + + if image_set == "val" : + fpath = os.path.join('coco-data-vis-retrieval-filter', args.model_id, 'val') + MosaicVisualization(ds, fpath) + num_classes = 2 + + return ds, num_classes + + +# IoU calculation for validation +def IoU(pred, gt): + pred = pred.argmax(1) + + intersection = torch.sum(torch.mul(pred, gt)) + union = torch.sum(torch.add(pred, gt)) - intersection + + if intersection == 0 or union == 0: + iou = 0 + else: + iou = float(intersection) / float(union) + + return iou, intersection, union + + +def get_transform(args): + transforms = [T.Resize(args.img_size, args.img_size), + T.ToTensor(), + T.Normalize(mean=[0.485, 0.456, 0.406], std=[0.229, 0.224, 0.225]) + ] + + return T.Compose(transforms) + + +def criterion(input, target): + weight = torch.FloatTensor([0.9, 1.1]).cuda() + return nn.functional.cross_entropy(input, target, weight=weight) + + +def evaluate(model, data_loader, bert_model): + model.eval() + metric_logger = utils.MetricLogger(delimiter=" ") + header = 'Test:' + total_its = 0 + acc_ious = 0 + + # evaluation variables + cum_I, cum_U = 0, 0 + eval_seg_iou_list = [.5, .6, .7, .8, .9] + seg_correct = np.zeros(len(eval_seg_iou_list), dtype=np.int32) + seg_total = 0 + mean_IoU = [] + + with torch.no_grad(): + for data in metric_logger.log_every(data_loader, 100, header): + total_its += 1 + image, target, sentences, attentions = data['image'], data['seg_target'], data['sentence'], data['attn_mask'] + image, target, sentences, attentions = image.cuda(non_blocking=True),\ + target.cuda(non_blocking=True),\ + sentences.cuda(non_blocking=True),\ + attentions.cuda(non_blocking=True) + + sentences = sentences.squeeze(1) + attentions = attentions.squeeze(1) + + if bert_model is not None: + last_hidden_states = bert_model(sentences, attention_mask=attentions)[0] + embedding = last_hidden_states.permute(0, 2, 1) # (B, 768, N_l) to make Conv1d happy + attentions = attentions.unsqueeze(dim=-1) # (B, N_l, 1) + output = model(image, embedding, l_mask=attentions) + else: + output = model(image, sentences, l_mask=attentions) + + iou, I, U = IoU(output, target) + acc_ious += iou + mean_IoU.append(iou) + cum_I += I + cum_U += U + for n_eval_iou in range(len(eval_seg_iou_list)): + eval_seg_iou = eval_seg_iou_list[n_eval_iou] + seg_correct[n_eval_iou] += (iou >= eval_seg_iou) + seg_total += 1 + iou = acc_ious / total_its + + mean_IoU = np.array(mean_IoU) + mIoU = np.mean(mean_IoU) + print('Final results:') + print('Mean IoU is %.2f\n' % (mIoU * 100.)) + results_str = '' + precs = [] + for n_eval_iou in range(len(eval_seg_iou_list)): + results_str += ' precision@%s = %.2f\n' % \ + (str(eval_seg_iou_list[n_eval_iou]), seg_correct[n_eval_iou] * 100. / seg_total) + precs.append(seg_correct[n_eval_iou] * 100. / seg_total) + results_str += ' overall IoU = %.2f\n' % (cum_I * 100. / cum_U) + print(results_str) + + return 100 * iou, 100 * cum_I / cum_U, precs + + +def train_one_epoch(model, criterion, optimizer, data_loader, lr_scheduler, epoch, print_freq, + iterations, bert_model): + model.train() + metric_logger = utils.MetricLogger(delimiter=" ") + metric_logger.add_meter('lr', utils.SmoothedValue(window_size=1, fmt='{value}')) + header = 'Epoch: [{}]'.format(epoch) + train_loss = 0 + total_its = 0 + + for data in metric_logger.log_every(data_loader, print_freq, header): + total_its += 1 + image, target, sentences, attentions = data['image'], data['seg_target'], data['sentence'], data['attn_mask'] + image, target, sentences, attentions = image.cuda(non_blocking=True),\ + target.cuda(non_blocking=True),\ + sentences.cuda(non_blocking=True),\ + attentions.cuda(non_blocking=True) + + sentences = sentences.squeeze(1) + attentions = attentions.squeeze(1) + + if bert_model is not None: + last_hidden_states = bert_model(sentences, attention_mask=attentions)[0] # (6, 10, 768) + embedding = last_hidden_states.permute(0, 2, 1) # (B, 768, N_l) to make Conv1d happy + attentions = attentions.unsqueeze(dim=-1) # (batch, N_l, 1) + output = model(image, embedding, l_mask=attentions) + else: + output = model(image, sentences, l_mask=attentions) + + loss = criterion(output, target) + optimizer.zero_grad() # set_to_none=True is only available in pytorch 1.6+ + loss.backward() + optimizer.step() + lr_scheduler.step() + + torch.cuda.synchronize() + train_loss += loss.item() + iterations += 1 + metric_logger.update(loss=loss.item(), lr=optimizer.param_groups[0]["lr"]) + + del image, target, sentences, attentions, loss, output, data + if bert_model is not None: + del last_hidden_states, embedding + + gc.collect() + torch.cuda.empty_cache() + torch.cuda.synchronize() + + loss_log = { + 'loss': metric_logger.meters['loss'].global_avg + } + return iterations, loss_log + + +def main(args): + writer = SummaryWriter('./experiments/{}'.format(args.model_id)) + + dataset, num_classes = get_dataset("train", + get_transform(args=args), + args=args) + dataset_test, _ = get_dataset("val", + get_transform(args=args), + args=args) + + # batch sampler + print(f"local rank {args.local_rank} / global rank {utils.get_rank()} successfully built train dataset.") + num_tasks = utils.get_world_size() + global_rank = utils.get_rank() + train_sampler = torch.utils.data.distributed.DistributedSampler(dataset, num_replicas=num_tasks, rank=global_rank, + shuffle=True) + test_sampler = torch.utils.data.SequentialSampler(dataset_test) + + # data loader + data_loader = torch.utils.data.DataLoader( + dataset, batch_size=args.batch_size, + sampler=train_sampler, num_workers=args.workers, pin_memory=args.pin_mem, drop_last=True) + + data_loader_test = torch.utils.data.DataLoader( + dataset_test, batch_size=1, sampler=test_sampler, num_workers=args.workers) + + # model initialization + print(args.model) + model = segmentation.__dict__[args.model](pretrained=args.pretrained_swin_weights, + args=args) + model = torch.nn.SyncBatchNorm.convert_sync_batchnorm(model) + model.cuda() + model = torch.nn.parallel.DistributedDataParallel(model, device_ids=[args.local_rank], find_unused_parameters=True) + single_model = model.module + + if args.model != 'lavt_one': + model_class = BertModel + bert_model = model_class.from_pretrained(args.ck_bert) + bert_model.pooler = None # a work-around for a bug in Transformers = 3.0.2 that appears for DistributedDataParallel + bert_model.cuda() + bert_model = torch.nn.SyncBatchNorm.convert_sync_batchnorm(bert_model) + bert_model = torch.nn.parallel.DistributedDataParallel(bert_model, device_ids=[args.local_rank]) + single_bert_model = bert_model.module + else: + bert_model = None + single_bert_model = None + + # resume training + if args.resume: + checkpoint = torch.load(args.resume, map_location='cpu') + single_model.load_state_dict(checkpoint['model']) + if args.model != 'lavt_one': + single_bert_model.load_state_dict(checkpoint['bert_model']) + + # parameters to optimize + backbone_no_decay = list() + backbone_decay = list() + for name, m in single_model.backbone.named_parameters(): + if 'norm' in name or 'absolute_pos_embed' in name or 'relative_position_bias_table' in name: + backbone_no_decay.append(m) + else: + backbone_decay.append(m) + + if args.model != 'lavt_one': + params_to_optimize = [ + {'params': backbone_no_decay, 'weight_decay': 0.0}, + {'params': backbone_decay}, + {"params": [p for p in single_model.classifier.parameters() if p.requires_grad]}, + # the following are the parameters of bert + {"params": reduce(operator.concat, + [[p for p in single_bert_model.encoder.layer[i].parameters() + if p.requires_grad] for i in range(10)])}, + ] + else: + params_to_optimize = [ + {'params': backbone_no_decay, 'weight_decay': 0.0}, + {'params': backbone_decay}, + {"params": [p for p in single_model.classifier.parameters() if p.requires_grad]}, + # the following are the parameters of bert + {"params": reduce(operator.concat, + [[p for p in single_model.text_encoder.encoder.layer[i].parameters() + if p.requires_grad] for i in range(10)])}, + ] + + # optimizer + optimizer = torch.optim.AdamW(params_to_optimize, + lr=args.lr, + weight_decay=args.weight_decay, + amsgrad=args.amsgrad + ) + + # learning rate scheduler + lr_scheduler = torch.optim.lr_scheduler.LambdaLR(optimizer, + lambda x: (1 - x / (len(data_loader) * args.epochs)) ** 0.9) + + # housekeeping + start_time = time.time() + iterations = 0 + best_oIoU = -0.1 + + # resume training (optimizer, lr scheduler, and the epoch) + if args.resume: + optimizer.load_state_dict(checkpoint['optimizer']) + lr_scheduler.load_state_dict(checkpoint['lr_scheduler']) + resume_epoch = checkpoint['epoch'] + else: + resume_epoch = -999 + + # training loops + for epoch in range(max(0, resume_epoch+1), args.epochs): + dataset.epoch = epoch + data_loader.sampler.set_epoch(epoch) + if epoch%10 == 0: + fpath = os.path.join('coco-data-vis-retrieval-filter', args.model_id, 'train', "epoch%02d"%epoch) + MosaicVisualization(dataset, fpath) + itrs_temp, loss_log = train_one_epoch(model, criterion, optimizer, data_loader, lr_scheduler, epoch, args.print_freq, + iterations, bert_model) + iterations += itrs_temp + iou, overallIoU, precs = evaluate(model, data_loader_test, bert_model) + + print('Average object IoU {}'.format(iou)) + print('Overall IoU {}'.format(overallIoU)) + save_checkpoint = (best_oIoU < overallIoU) + if save_checkpoint: + print('Better epoch: {}\n'.format(epoch)) + if single_bert_model is not None: + dict_to_save = {'model': single_model.state_dict(), 'bert_model': single_bert_model.state_dict(), + 'optimizer': optimizer.state_dict(), 'epoch': epoch, 'args': args, + 'lr_scheduler': lr_scheduler.state_dict()} + else: + dict_to_save = {'model': single_model.state_dict(), + 'optimizer': optimizer.state_dict(), 'epoch': epoch, 'args': args, + 'lr_scheduler': lr_scheduler.state_dict()} + + utils.save_on_master(dict_to_save, os.path.join(args.output_dir, + 'model_best_{}.pth'.format(args.model_id))) + best_oIoU = overallIoU + + # dataset_refer_bert_mosaic_retrieval_warmup.py + aug_prob = args.aug.aug_prob # 0.6 + retr_prob = args.aug.retr_prob # 0.3 + rand_prob = aug_prob - retr_prob # 0.3 + + if epoch < args.aug.warmup_epoch : + retr_prob = get_warmup_value(0, retr_prob, epoch, args.aug.warmup_epoch) + rand_prob = get_warmup_value(aug_prob, rand_prob, epoch, args.aug.warmup_epoch) + + # aug_prob = args.aug.aug_prob + # if epoch < args.aug.retrieval_epoch: + # rand_prob = aug_prob + # retr_prob = 0 + # else : + # rand_prob = args.aug.rand_prob + # retr_prob = args.aug.retr_prob + + if utils.is_main_process(): + writer.add_scalar('val/mIoU', iou, epoch) + writer.add_scalar('val/oIoU', overallIoU, epoch) + writer.add_scalar('val/Prec/50', precs[0], epoch) + writer.add_scalar('val/Prec/60', precs[1], epoch) + writer.add_scalar('val/Prec/70', precs[2], epoch) + writer.add_scalar('val/Prec/80', precs[3], epoch) + writer.add_scalar('val/Prec/90', precs[4], epoch) + writer.add_scalar('train/loss', loss_log['loss'], epoch) + writer.add_scalar('train/one_prob', 1-aug_prob, epoch) + writer.add_scalar('train/retr_prob', retr_prob, epoch) + writer.add_scalar('train/rand_prob', rand_prob, epoch) + + writer.flush() + # summarize + total_time = time.time() - start_time + total_time_str = str(datetime.timedelta(seconds=int(total_time))) + print('Training time {}'.format(total_time_str)) + + +if __name__ == "__main__": + from args import get_parser + parser = get_parser() + args = parser.parse_args() + if args.config is not None : + from config.utils import CfgNode + cn = CfgNode(CfgNode.load_yaml_with_base(args.config)) + for k,v in cn.items(): + if not hasattr(args, k): + print('Warning: key %s not in args' %k) + setattr(args, k, v) + args = parser.parse_args(namespace=args) + print(args) + args.output_dir = './experiments/{}/{}'.format("_".join([args.dataset, args.splitBy]), args.model_id) + # set up distributed learning + utils.init_distributed_mode(args) + print('Image size: {}'.format(str(args.img_size))) + main(args) diff --git a/LAVT-RIS/donghwa/transforms.py b/LAVT-RIS/donghwa/transforms.py new file mode 100644 index 0000000000000000000000000000000000000000..0d22889dbab930ebe2a41dd01b8067465343079f --- /dev/null +++ b/LAVT-RIS/donghwa/transforms.py @@ -0,0 +1,124 @@ +import numpy as np +from PIL import Image +import random + +import torch +from torchvision import transforms as T +from torchvision.transforms import functional as F + + +def pad_if_smaller(img, size, fill=0): + min_size = min(img.size) + if min_size < size: + ow, oh = img.size + padh = size - oh if oh < size else 0 + padw = size - ow if ow < size else 0 + img = F.pad(img, (0, 0, padw, padh), fill=fill) + return img + + +class Compose(object): + def __init__(self, transforms): + self.transforms = transforms + + def __call__(self, image, target): + for t in self.transforms: + image, target = t(image, target) + return image, target + + +class Resize(object): + def __init__(self, h, w): + self.h = h + self.w = w + + def __call__(self, image, target): + image = F.resize(image, (self.h, self.w)) + # If size is a sequence like (h, w), the output size will be matched to this. + # If size is an int, the smaller edge of the image will be matched to this number maintaining the aspect ratio + target = F.resize(target, (self.h, self.w), interpolation=Image.NEAREST) + return image, target + + +class RandomResize(object): + def __init__(self, min_size, max_size=None): + self.min_size = min_size + if max_size is None: + max_size = min_size + self.max_size = max_size + + def __call__(self, image, target): + size = random.randint(self.min_size, self.max_size) # Return a random integer N such that a <= N <= b. Alias for randrange(a, b+1) + image = F.resize(image, size) + # If size is a sequence like (h, w), the output size will be matched to this. + # If size is an int, the smaller edge of the image will be matched to this number maintaining the aspect ratio + target = F.resize(target, size, interpolation=Image.NEAREST) + return image, target + + +class RandomHorizontalFlip(object): + def __init__(self, flip_prob): + self.flip_prob = flip_prob + + def __call__(self, image, target): + if random.random() < self.flip_prob: + image = F.hflip(image) + target = F.hflip(target) + return image, target + + +class RandomCrop(object): + def __init__(self, size): + self.size = size + + def __call__(self, image, target): + image = pad_if_smaller(image, self.size) + target = pad_if_smaller(target, self.size, fill=255) + crop_params = T.RandomCrop.get_params(image, (self.size, self.size)) + image = F.crop(image, *crop_params) + target = F.crop(target, *crop_params) + return image, target + + +class CenterCrop(object): + def __init__(self, size): + self.size = size + + def __call__(self, image, target): + image = F.center_crop(image, self.size) + target = F.center_crop(target, self.size) + return image, target + + +class ToTensor(object): + def __call__(self, image, target): + image = F.to_tensor(image) + target = torch.as_tensor(np.asarray(target).copy(), dtype=torch.int64) + return image, target + + +class RandomAffine(object): + def __init__(self, angle, translate, scale, shear, resample=0, fillcolor=None): + self.angle = angle + self.translate = translate + self.scale = scale + self.shear = shear + self.resample = resample + self.fillcolor = fillcolor + + def __call__(self, image, target): + affine_params = T.RandomAffine.get_params(self.angle, self.translate, self.scale, self.shear, image.size) + image = F.affine(image, *affine_params) + target = F.affine(target, *affine_params) + return image, target + + +class Normalize(object): + def __init__(self, mean, std): + self.mean = mean + self.std = std + + def __call__(self, image, target): + image = F.normalize(image, mean=self.mean, std=self.std) + return image, target + diff --git a/LAVT-RIS/donghwa/utils.py b/LAVT-RIS/donghwa/utils.py new file mode 100644 index 0000000000000000000000000000000000000000..fd9a4debeab890df91aa2df54cae244b521814f4 --- /dev/null +++ b/LAVT-RIS/donghwa/utils.py @@ -0,0 +1,216 @@ +import os +import time +import copy +import logging +import math + +import numpy as np +import torch +import random +import matplotlib.pyplot as plt + +from detectron2.config import configurable +from detectron2.data import detection_utils as utils +from detectron2.data import transforms as T + +from transformers import BertTokenizer +from pycocotools import mask as coco_mask + +import albumentations as A +# from albumentations.pytorch import ToTensorV2 +from PIL import Image, ImageDraw, ImageFilter +from detectron2.utils.visualizer import Visualizer + + +def convert_coco_poly_to_mask(segmentations, height, width): + masks = [] + for polygons in segmentations: + rles = coco_mask.frPyObjects(polygons, height, width) + mask = coco_mask.decode(rles) + if len(mask.shape) < 3: + mask = mask[..., None] + mask = torch.as_tensor(mask, dtype=torch.uint8) + mask = mask.any(dim=2) + masks.append(mask) + if masks: + masks = torch.stack(masks, dim=0) + else: + masks = torch.zeros((0, height, width), dtype=torch.uint8) + return masks + + +def build_transform_train(cfg): + image_size = cfg.img_size + # min_scale = cfg.INPUT.MIN_SCALE + + augmentation = [] + + augmentation.extend([ + T.Resize((image_size, image_size)) + ]) + + return augmentation + + +def build_transform_test(cfg): + image_size = cfg.img_size + + augmentation = [] + + augmentation.extend([ + T.Resize((image_size, image_size)) + ]) + + return augmentation + + +def COCOVisualization(dataloader, dirname="coco-aug-data-vis"): + + mean = (0.485, 0.456, 0.406) + std = (0.229, 0.224, 0.225) + denorm = A.Normalize( + mean=[-m / s for m, s in zip(mean, std)], + std=[1.0 / s for s in std], + max_pixel_value=1.0 + ) + tokenizer = BertTokenizer.from_pretrained("bert-base-uncased") + + sent_idx = 0 + os.makedirs(dirname, exist_ok=True) + # dataloader = build_detection_train_loader(cfg, mapper=mapper) + it = iter(dataloader) + batch = next(it) + n_sample = random.randint(4, len(batch)) + + for i in range(n_sample): + batch = next(it) + img, gt_mask, lang_tokens, lang_mask = batch + img_np = np.transpose(img.cpu().numpy(), (1,2,0)) + # img_denorm = denorm(image=img_np)['image'] + # img_ndarray = (img_denorm*255).astype(np.uint8) + seg_target = gt_mask[:,:].cpu().numpy() + tokens = lang_tokens.reshape(-1).cpu().numpy() + sentences = tokenizer.decode(tokens, skip_special_tokens=True) + fpath = os.path.join(dirname, f'sample_{i+1}.jpg') + fig = plt.figure(figsize=(10,6)) + ax1 = fig.add_subplot(1,2,1) + ax1.imshow(img_np.astype('uint8')) + ax1.set_xlabel("Mosaic Image") + ax2 = fig.add_subplot(1,2,2) + ax2.imshow(seg_target) + ax2.set_xlabel("Segmentation Map") + plt.suptitle(sentences) + plt.tight_layout() + plt.savefig(fpath) + + # if 'gt_masks' in batch[0].keys(): + # for i in range(n_sample): + # data = batch[i] + # img = data['image'].unsqueeze(0) + # img_np = np.transpose(img[0].cpu().numpy(), (1,2,0)) + # img_denorm = denorm(image=img_np)['image'] + # img_ndarray = (img_denorm*255).astype(np.uint8) + # seg_target = data['gt_masks'].squeeze(0) + # tensor_embedding = data['lang_tokens'][:,:] + # sentences = tokenizer.decode(tensor_embedding[0], skip_special_tokens=True) + # # tokens = [ds.tokenizer.decode([w], skip_special_tokens=False) for w in tensor_embedding[0]] + # # tokens = [x for x in tokens if x!='[PAD]'] + + # fpath = os.path.join(dirname, os.path.basename(data["file_name"])) + # fig = plt.figure(figsize=(10,6)) + # ax1 = fig.add_subplot(1,2,1) + # ax1.imshow(img_ndarray) + # ax1.set_xlabel("Mosaic Image") + # ax2 = fig.add_subplot(1,2,2) + # ax2.imshow(seg_target) + # ax2.set_xlabel("Segmentation Map") + # plt.suptitle(sentences) + # plt.tight_layout() + # plt.savefig(fpath) + + # else : + + # for i in range(n_sample): + # d = batch[i] + # img = np.array(Image.open(d["file_name"])) + # visualizer = Visualizer(img, metadata={}) + # vis = visualizer.draw_dataset_dict(d) + # fpath = os.path.join(dirname, os.path.basename(d["file_name"])) + # vis.save(fpath) + +def MosaicVisualization(dataset, dirname="coco-aug-data-vis", n_sample=4): + + mean = (0.485, 0.456, 0.406) + std = (0.229, 0.224, 0.225) + denorm = A.Normalize( + mean=[-m / s for m, s in zip(mean, std)], + std=[1.0 / s for s in std], + max_pixel_value=1.0 + ) + tokenizer = BertTokenizer.from_pretrained("bert-base-uncased") + + os.makedirs(dirname, exist_ok=True) + # dataset = build_detection_train_loader(cfg, mapper=mapper) + it = iter(dataset) + while(n_sample): + try : + data = next(it) + # n_sample = random.randint(1, len(batch)) + # if 'seg_target' in batch[0].keys(): + # for i in range(n_sample): + # data = batch[i] + img = data['image'] + img_np = np.transpose(img.cpu().numpy(), (1,2,0)) + img_denorm = denorm(image=img_np)['image'] + img_ndarray = (img_denorm*255).astype(np.uint8) + seg_target = data['seg_target'] + tensor_embedding = data['sentence'].reshape(-1).cpu().numpy() + sentences = tokenizer.decode(tensor_embedding, skip_special_tokens=True) + # tokens = [ds.tokenizer.decode([w], skip_special_tokens=False) for w in tensor_embedding[0]] + # tokens = [x for x in tokens if x!='[PAD]'] + + fpath = os.path.join(dirname, f'sample_{n_sample}.jpg') + fig = plt.figure(figsize=(10,6)) + ax1 = fig.add_subplot(1,2,1) + ax1.imshow(img_ndarray) + ax1.set_xlabel("Mosaic Image") + ax2 = fig.add_subplot(1,2,2) + ax2.imshow(seg_target) + ax2.set_xlabel("Segmentation Map") + plt.suptitle(sentences) + plt.tight_layout() + plt.savefig(fpath) + n_sample -= 1 + except : + break + + # else : + + # for i in range(n_sample): + # d = batch[i] + # img = np.array(Image.open(d["file_name"])) + # visualizer = Visualizer(img, metadata={}) + # vis = visualizer.draw_dataset_dict(d) + # fpath = os.path.join(dirname, os.path.basename(d["file_name"])) + # vis.save(fpath) + + +def cosine_annealing(epoch, n_epochs, n_cycles, lrate_max=1): + """ + epoch : specific epoch you want to calcuate the probability + n_epochs : total number of epochs + n_cycles : number of cycle of cosine cf. 1 cycle = half of a period + lrate_max : maximum of probability + """ + epochs_per_cycle = math.floor(n_epochs/n_cycles) + cos_inner = (math.pi * (epoch % epochs_per_cycle)) / (epochs_per_cycle) + + return lrate_max/2 * (math.cos(cos_inner) + 1) + + +def get_warmup_value(start_value, end_value, step, total_steps): + if step >= total_steps: + return end_value + mul = np.cos((1 - (step / total_steps)) * math.pi / 2) # Adjust the cosine function for warmup + warmup_range = end_value - start_value + return warmup_range * mul + start_value diff --git 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0000000000000000000000000000000000000000..5911028e5857cdcdb4089b188f26dae983fc7230 Binary files /dev/null and b/LAVT-RIS/lib/__pycache__/segmentation.cpython-37.pyc differ diff --git a/LAVT-RIS/lib/__pycache__/segmentation.cpython-39.pyc b/LAVT-RIS/lib/__pycache__/segmentation.cpython-39.pyc new file mode 100644 index 0000000000000000000000000000000000000000..c307aa0c6682083bc6bb56deab506db893b4f860 Binary files /dev/null and b/LAVT-RIS/lib/__pycache__/segmentation.cpython-39.pyc differ diff --git a/LAVT-RIS/lib/_utils.py b/LAVT-RIS/lib/_utils.py new file mode 100644 index 0000000000000000000000000000000000000000..2993384f10ba862b7f8e08a24e674def023a6850 --- /dev/null +++ b/LAVT-RIS/lib/_utils.py @@ -0,0 +1,61 @@ +from collections import OrderedDict +import sys +import torch +from torch import nn +from torch.nn import functional as F +from bert.modeling_bert import BertModel + + +class _LAVTSimpleDecode(nn.Module): + def __init__(self, backbone, classifier): + super(_LAVTSimpleDecode, self).__init__() + self.backbone = backbone + self.classifier = classifier + + def forward(self, x, l_feats, l_mask): + input_shape = x.shape[-2:] + features = self.backbone(x, l_feats, l_mask) + x_c1, x_c2, x_c3, x_c4 = features + x = self.classifier(x_c4, x_c3, x_c2, x_c1) + x = F.interpolate(x, size=input_shape, mode='bilinear', align_corners=True) + + return x + + +class LAVT(_LAVTSimpleDecode): + pass + + +############################################### +# LAVT One: put BERT inside the overall model # +############################################### + + +class _LAVTOneSimpleDecode(nn.Module): + def __init__(self, backbone, classifier, args): + super(_LAVTOneSimpleDecode, self).__init__() + self.backbone = backbone + self.classifier = classifier + self.text_encoder = BertModel.from_pretrained(args.ck_bert) + self.text_encoder.pooler = None + + def forward(self, x, text, l_mask, is_train=True): + input_shape = x.shape[-2:] + ### language inference ### + l_feats = self.text_encoder(text, attention_mask=l_mask)[0] # (6, 10, 768) + l_feats = l_feats.permute(0, 2, 1) # (B, 768, N_l) to make Conv1d happy + l_mask = l_mask.unsqueeze(dim=-1) # (batch, N_l, 1) + ########################## + features = self.backbone(x, l_feats, l_mask) + x_c1, x_c2, x_c3, x_c4 = features + x = self.classifier(x_c4, x_c3, x_c2, x_c1) + x = F.interpolate(x, size=input_shape, mode='bilinear', align_corners=True) + + if is_train : + return x, x_c4 + else : + return x + + +class LAVTOne(_LAVTOneSimpleDecode): + pass diff --git a/LAVT-RIS/lib/backbone.py b/LAVT-RIS/lib/backbone.py new file mode 100644 index 0000000000000000000000000000000000000000..37b6c2287922cb0f6b840a720c98920fb6e12133 --- /dev/null +++ b/LAVT-RIS/lib/backbone.py @@ -0,0 +1,715 @@ +import torch +import torch.nn as nn +import torch.nn.functional as F +import torch.utils.checkpoint as checkpoint +import numpy as np +from timm.models.layers import DropPath, to_2tuple, trunc_normal_ +from .mmcv_custom import load_checkpoint +from mmseg.utils import get_root_logger + + +class Mlp(nn.Module): + """ Multilayer perceptron.""" + + def __init__(self, in_features, hidden_features=None, out_features=None, act_layer=nn.GELU, drop=0.): + super().__init__() + out_features = out_features or in_features + hidden_features = hidden_features or in_features + self.fc1 = nn.Linear(in_features, hidden_features) + self.act = act_layer() + self.fc2 = nn.Linear(hidden_features, out_features) + self.drop = nn.Dropout(drop) + + def forward(self, x): + x = self.fc1(x) + x = self.act(x) + x = self.drop(x) + x = self.fc2(x) + x = self.drop(x) + return x + + +def window_partition(x, window_size): + """ + Args: + x: (B, H, W, C) + window_size (int): window size + + Returns: + windows: (num_windows*B, window_size, window_size, C) + """ + B, H, W, C = x.shape + x = x.view(B, H // window_size, window_size, W // window_size, window_size, C) + windows = x.permute(0, 1, 3, 2, 4, 5).contiguous().view(-1, window_size, window_size, C) + return windows + + +def window_reverse(windows, window_size, H, W): + """ + Args: + windows: (num_windows*B, window_size, window_size, C) + window_size (int): Window size + H (int): Height of image + W (int): Width of image + + Returns: + x: (B, H, W, C) + """ + B = int(windows.shape[0] / (H * W / window_size / window_size)) + x = windows.view(B, H // window_size, W // window_size, window_size, window_size, -1) + x = x.permute(0, 1, 3, 2, 4, 5).contiguous().view(B, H, W, -1) + return x + + +class WindowAttention(nn.Module): + """ Window based multi-head self attention (W-MSA) module with relative position bias. + It supports both of shifted and non-shifted window. + + Args: + dim (int): Number of input channels. + window_size (tuple[int]): The height and width of the window. + num_heads (int): Number of attention heads. + qkv_bias (bool, optional): If True, add a learnable bias to query, key, value. Default: True + qk_scale (float | None, optional): Override default qk scale of head_dim ** -0.5 if set + attn_drop (float, optional): Dropout ratio of attention weight. Default: 0.0 + proj_drop (float, optional): Dropout ratio of output. Default: 0.0 + """ + + def __init__(self, dim, window_size, num_heads, qkv_bias=True, qk_scale=None, attn_drop=0., proj_drop=0.): + + super().__init__() + self.dim = dim + self.window_size = window_size # Wh, Ww + self.num_heads = num_heads + head_dim = dim // num_heads + self.scale = qk_scale or head_dim ** -0.5 + + # define a parameter table of relative position bias + self.relative_position_bias_table = nn.Parameter( + torch.zeros((2 * window_size[0] - 1) * (2 * window_size[1] - 1), num_heads)) # 2*Wh-1 * 2*Ww-1, nH + + # get pair-wise relative position index for each token inside the window + coords_h = torch.arange(self.window_size[0]) + coords_w = torch.arange(self.window_size[1]) + coords = torch.stack(torch.meshgrid([coords_h, coords_w])) # 2, Wh, Ww + coords_flatten = torch.flatten(coords, 1) # 2, Wh*Ww + relative_coords = coords_flatten[:, :, None] - coords_flatten[:, None, :] # 2, Wh*Ww, Wh*Ww + relative_coords = relative_coords.permute(1, 2, 0).contiguous() # Wh*Ww, Wh*Ww, 2 + relative_coords[:, :, 0] += self.window_size[0] - 1 # shift to start from 0 + relative_coords[:, :, 1] += self.window_size[1] - 1 + relative_coords[:, :, 0] *= 2 * self.window_size[1] - 1 + relative_position_index = relative_coords.sum(-1) # Wh*Ww, Wh*Ww + self.register_buffer("relative_position_index", relative_position_index) + + self.qkv = nn.Linear(dim, dim * 3, bias=qkv_bias) + self.attn_drop = nn.Dropout(attn_drop) + self.proj = nn.Linear(dim, dim) + self.proj_drop = nn.Dropout(proj_drop) + + trunc_normal_(self.relative_position_bias_table, std=.02) + self.softmax = nn.Softmax(dim=-1) + + def forward(self, x, mask=None): + """ Forward function. + + Args: + x: input features with shape of (num_windows*B, N, C) + mask: (0/-inf) mask with shape of (num_windows, Wh*Ww, Wh*Ww) or None + """ + B_, N, C = x.shape + qkv = self.qkv(x).reshape(B_, N, 3, self.num_heads, C // self.num_heads).permute(2, 0, 3, 1, 4) + q, k, v = qkv[0], qkv[1], qkv[2] # make torchscript happy (cannot use tensor as tuple) + q = q * self.scale + attn = (q @ k.transpose(-2, -1)) + relative_position_bias = self.relative_position_bias_table[self.relative_position_index.view(-1)].view( + self.window_size[0] * self.window_size[1], self.window_size[0] * self.window_size[1], -1) # Wh*Ww,Wh*Ww,nH + relative_position_bias = relative_position_bias.permute(2, 0, 1).contiguous() # nH, Wh*Ww, Wh*Ww + attn = attn + relative_position_bias.unsqueeze(0) + + if mask is not None: + nW = mask.shape[0] + attn = attn.view(B_ // nW, nW, self.num_heads, N, N) + mask.unsqueeze(1).unsqueeze(0) + attn = attn.view(-1, self.num_heads, N, N) + attn = self.softmax(attn) + else: + attn = self.softmax(attn) + + attn = self.attn_drop(attn) + + x = (attn @ v).transpose(1, 2).reshape(B_, N, C) # cat op + x = self.proj(x) + x = self.proj_drop(x) + return x + + +class SwinTransformerBlock(nn.Module): + """ Swin Transformer Block. + + Args: + dim (int): Number of input channels. + num_heads (int): Number of attention heads. + window_size (int): Window size. + shift_size (int): Shift size for SW-MSA. + mlp_ratio (float): Ratio of mlp hidden dim to embedding dim. + qkv_bias (bool, optional): If True, add a learnable bias to query, key, value. Default: True + qk_scale (float | None, optional): Override default qk scale of head_dim ** -0.5 if set. + drop (float, optional): Dropout rate. Default: 0.0 + attn_drop (float, optional): Attention dropout rate. Default: 0.0 + drop_path (float, optional): Stochastic depth rate. Default: 0.0 + act_layer (nn.Module, optional): Activation layer. Default: nn.GELU + norm_layer (nn.Module, optional): Normalization layer. Default: nn.LayerNorm + """ + + def __init__(self, dim, num_heads, window_size=7, shift_size=0, + mlp_ratio=4., qkv_bias=True, qk_scale=None, drop=0., attn_drop=0., drop_path=0., + act_layer=nn.GELU, norm_layer=nn.LayerNorm): + super().__init__() + self.dim = dim + self.num_heads = num_heads + self.window_size = window_size + self.shift_size = shift_size + self.mlp_ratio = mlp_ratio + assert 0 <= self.shift_size < self.window_size, "shift_size must in 0-window_size" + + self.norm1 = norm_layer(dim) + self.attn = WindowAttention( + dim, window_size=to_2tuple(self.window_size), num_heads=num_heads, + qkv_bias=qkv_bias, qk_scale=qk_scale, attn_drop=attn_drop, proj_drop=drop) + + self.drop_path = DropPath(drop_path) if drop_path > 0. else nn.Identity() + self.norm2 = norm_layer(dim) + mlp_hidden_dim = int(dim * mlp_ratio) + self.mlp = Mlp(in_features=dim, hidden_features=mlp_hidden_dim, act_layer=act_layer, drop=drop) + + self.H = None + self.W = None + + def forward(self, x, mask_matrix): + """ Forward function. + + Args: + x: Input feature, tensor size (B, H*W, C). + H, W: Spatial resolution of the input feature. + mask_matrix: Attention mask for cyclic shift. + """ + B, L, C = x.shape + H, W = self.H, self.W + assert L == H * W, "input feature has wrong size" + + shortcut = x + x = self.norm1(x) + x = x.view(B, H, W, C) + + # pad feature maps to multiples of window size + pad_l = pad_t = 0 + pad_r = (self.window_size - W % self.window_size) % self.window_size + pad_b = (self.window_size - H % self.window_size) % self.window_size + x = F.pad(x, (0, 0, pad_l, pad_r, pad_t, pad_b)) + _, Hp, Wp, _ = x.shape + + # cyclic shift + if self.shift_size > 0: + shifted_x = torch.roll(x, shifts=(-self.shift_size, -self.shift_size), dims=(1, 2)) + attn_mask = mask_matrix + else: + shifted_x = x + attn_mask = None + + # partition windows + x_windows = window_partition(shifted_x, self.window_size) # nW*B, window_size, window_size, C + x_windows = x_windows.view(-1, self.window_size * self.window_size, C) # nW*B, window_size*window_size, C + + # W-MSA/SW-MSA + attn_windows = self.attn(x_windows, mask=attn_mask) # nW*B, window_size*window_size, C + + # merge windows + attn_windows = attn_windows.view(-1, self.window_size, self.window_size, C) + shifted_x = window_reverse(attn_windows, self.window_size, Hp, Wp) # B H' W' C + + # reverse cyclic shift + if self.shift_size > 0: + x = torch.roll(shifted_x, shifts=(self.shift_size, self.shift_size), dims=(1, 2)) + else: + x = shifted_x + + if pad_r > 0 or pad_b > 0: + x = x[:, :H, :W, :].contiguous() + + x = x.view(B, H * W, C) + + # FFN feed-forward network + x = shortcut + self.drop_path(x) + x = x + self.drop_path(self.mlp(self.norm2(x))) + + return x + + +class PatchMerging(nn.Module): + """ Patch Merging Layer + + Args: + dim (int): Number of input channels. + norm_layer (nn.Module, optional): Normalization layer. Default: nn.LayerNorm + """ + def __init__(self, dim, norm_layer=nn.LayerNorm): + super().__init__() + self.dim = dim + self.reduction = nn.Linear(4 * dim, 2 * dim, bias=False) + self.norm = norm_layer(4 * dim) + + def forward(self, x, H, W): + """ Forward function. + + Args: + x: Input feature, tensor size (B, H*W, C). + H, W: Spatial resolution of the input feature. + """ + B, L, C = x.shape + assert L == H * W, "input feature has wrong size" + + x = x.view(B, H, W, C) + + # padding + pad_input = (H % 2 == 1) or (W % 2 == 1) + if pad_input: + x = F.pad(x, (0, 0, 0, W % 2, 0, H % 2)) + + x0 = x[:, 0::2, 0::2, :] # B H/2 W/2 C + x1 = x[:, 1::2, 0::2, :] # B H/2 W/2 C + x2 = x[:, 0::2, 1::2, :] # B H/2 W/2 C + x3 = x[:, 1::2, 1::2, :] # B H/2 W/2 C + x = torch.cat([x0, x1, x2, x3], -1) # B H/2 W/2 4*C + x = x.view(B, -1, 4 * C) # B H/2*W/2 4*C + + x = self.norm(x) + x = self.reduction(x) + + return x + + +class PatchEmbed(nn.Module): + """ Image to Patch Embedding + + Args: + patch_size (int): Patch token size. Default: 4. + in_chans (int): Number of input image channels. Default: 3. + embed_dim (int): Number of linear projection output channels. Default: 96. + norm_layer (nn.Module, optional): Normalization layer. Default: None + """ + + def __init__(self, patch_size=4, in_chans=3, embed_dim=96, norm_layer=None): + super().__init__() + patch_size = to_2tuple(patch_size) + self.patch_size = patch_size + + self.in_chans = in_chans + self.embed_dim = embed_dim + + self.proj = nn.Conv2d(in_chans, embed_dim, kernel_size=patch_size, stride=patch_size) + if norm_layer is not None: + self.norm = norm_layer(embed_dim) + else: + self.norm = None + + def forward(self, x): + """Forward function.""" + # padding + _, _, H, W = x.size() + if W % self.patch_size[1] != 0: + x = F.pad(x, (0, self.patch_size[1] - W % self.patch_size[1])) + if H % self.patch_size[0] != 0: + x = F.pad(x, (0, 0, 0, self.patch_size[0] - H % self.patch_size[0])) + + x = self.proj(x) # B C Wh Ww + if self.norm is not None: + Wh, Ww = x.size(2), x.size(3) + x = x.flatten(2).transpose(1, 2) + x = self.norm(x) + x = x.transpose(1, 2).view(-1, self.embed_dim, Wh, Ww) + + return x + + +class MultiModalSwinTransformer(nn.Module): + def __init__(self, + pretrain_img_size=224, + patch_size=4, + in_chans=3, + embed_dim=96, + depths=[2, 2, 6, 2], + num_heads=[3, 6, 12, 24], + window_size=7, + mlp_ratio=4., + qkv_bias=True, + qk_scale=None, + drop_rate=0., + attn_drop_rate=0., + drop_path_rate=0.2, + norm_layer=nn.LayerNorm, + ape=False, + patch_norm=True, + out_indices=(0, 1, 2, 3), + frozen_stages=-1, + use_checkpoint=False, + num_heads_fusion=[1, 1, 1, 1], + fusion_drop=0.0 + ): + super().__init__() + + self.pretrain_img_size = pretrain_img_size + self.num_layers = len(depths) + self.embed_dim = embed_dim + self.ape = ape + self.patch_norm = patch_norm + self.out_indices = out_indices + self.frozen_stages = frozen_stages + + # split image into non-overlapping patches + self.patch_embed = PatchEmbed( + patch_size=patch_size, in_chans=in_chans, embed_dim=embed_dim, + norm_layer=norm_layer if self.patch_norm else None) + + # absolute position embedding + if self.ape: + pretrain_img_size = to_2tuple(pretrain_img_size) + patch_size = to_2tuple(patch_size) + patches_resolution = [pretrain_img_size[0] // patch_size[0], pretrain_img_size[1] // patch_size[1]] + + self.absolute_pos_embed = nn.Parameter(torch.zeros(1, embed_dim, patches_resolution[0], patches_resolution[1])) + trunc_normal_(self.absolute_pos_embed, std=.02) + + self.pos_drop = nn.Dropout(p=drop_rate) + + # stochastic depth + dpr = [x.item() for x in torch.linspace(0, drop_path_rate, sum(depths))] # stochastic depth decay rule + + # build layers + self.layers = nn.ModuleList() + for i_layer in range(self.num_layers): + layer = MMBasicLayer( + dim=int(embed_dim * 2 ** i_layer), + depth=depths[i_layer], + num_heads=num_heads[i_layer], + window_size=window_size, + mlp_ratio=mlp_ratio, + qkv_bias=qkv_bias, + qk_scale=qk_scale, + drop=drop_rate, + attn_drop=attn_drop_rate, + drop_path=dpr[sum(depths[:i_layer]):sum(depths[:i_layer + 1])], + norm_layer=norm_layer, + downsample=PatchMerging if (i_layer < self.num_layers - 1) else None, + use_checkpoint=use_checkpoint, + num_heads_fusion=num_heads_fusion[i_layer], + fusion_drop=fusion_drop + ) + self.layers.append(layer) + + num_features = [int(embed_dim * 2 ** i) for i in range(self.num_layers)] + self.num_features = num_features + + # add a norm layer for each output + for i_layer in out_indices: + layer = norm_layer(num_features[i_layer]) + layer_name = f'norm{i_layer}' + self.add_module(layer_name, layer) + + self._freeze_stages() + + def _freeze_stages(self): + if self.frozen_stages >= 0: + self.patch_embed.eval() + for param in self.patch_embed.parameters(): + param.requires_grad = False + + if self.frozen_stages >= 1 and self.ape: + self.absolute_pos_embed.requires_grad = False + + if self.frozen_stages >= 2: + self.pos_drop.eval() + for i in range(0, self.frozen_stages - 1): + m = self.layers[i] + m.eval() + for param in m.parameters(): + param.requires_grad = False + + def init_weights(self, pretrained=None): + """Initialize the weights in backbone. + + Args: + pretrained (str, optional): Path to pre-trained weights. + Defaults to None. + """ + + def _init_weights(m): + if isinstance(m, nn.Linear): + trunc_normal_(m.weight, std=.02) + if isinstance(m, nn.Linear) and m.bias is not None: + nn.init.constant_(m.bias, 0) + elif isinstance(m, nn.LayerNorm): + nn.init.constant_(m.bias, 0) + nn.init.constant_(m.weight, 1.0) + + if isinstance(pretrained, str): + self.apply(_init_weights) + logger = get_root_logger() + load_checkpoint(self, pretrained, strict=('upernet' in pretrained), logger=logger) + elif pretrained is None: + self.apply(_init_weights) + else: + raise TypeError('pretrained must be a str or None') + + def forward(self, x, l, l_mask): + """Forward function.""" + x = self.patch_embed(x) + + Wh, Ww = x.size(2), x.size(3) + if self.ape: + # interpolate the position embedding to the corresponding size + absolute_pos_embed = F.interpolate(self.absolute_pos_embed, size=(Wh, Ww), mode='bicubic') + x = (x + absolute_pos_embed).flatten(2).transpose(1, 2) # B Wh*Ww C + else: + x = x.flatten(2).transpose(1, 2) + x = self.pos_drop(x) + + outs = [] + for i in range(self.num_layers): + layer = self.layers[i] + x_out, H, W, x, Wh, Ww = layer(x, Wh, Ww, l, l_mask) + + if i in self.out_indices: + norm_layer = getattr(self, f'norm{i}') + x_out = norm_layer(x_out) # output of a Block has shape (B, H*W, dim) + + out = x_out.view(-1, H, W, self.num_features[i]).permute(0, 3, 1, 2).contiguous() + outs.append(out) + + return tuple(outs) + + def train(self, mode=True): + """Convert the model into training mode while keep layers freezed.""" + super(MultiModalSwinTransformer, self).train(mode) + self._freeze_stages() + + +class MMBasicLayer(nn.Module): + def __init__(self, + dim, + depth, + num_heads, + window_size=7, + mlp_ratio=4., + qkv_bias=True, + qk_scale=None, + drop=0., + attn_drop=0., + drop_path=0., + norm_layer=nn.LayerNorm, + downsample=None, + use_checkpoint=False, + num_heads_fusion=1, + fusion_drop=0.0 + ): + super().__init__() + self.window_size = window_size + self.shift_size = window_size // 2 + self.depth = depth + self.use_checkpoint = use_checkpoint + self.dim = dim + + # build blocks + self.blocks = nn.ModuleList([ + SwinTransformerBlock( + dim=dim, + num_heads=num_heads, + window_size=window_size, + shift_size=0 if (i % 2 == 0) else window_size // 2, + mlp_ratio=mlp_ratio, + qkv_bias=qkv_bias, + qk_scale=qk_scale, + drop=drop, + attn_drop=attn_drop, + drop_path=drop_path[i] if isinstance(drop_path, list) else drop_path, + norm_layer=norm_layer) + for i in range(depth)]) + + # fuse before downsampling + self.fusion = PWAM(dim, # both the visual input and for combining, num of channels + dim, # v_in + 768, # l_in + dim, # key + dim, # value + num_heads=num_heads_fusion, + dropout=fusion_drop) + + self.res_gate = nn.Sequential( + nn.Linear(dim, dim, bias=False), + nn.ReLU(), + nn.Linear(dim, dim, bias=False), + nn.Tanh() + ) + # patch merging layer + if downsample is not None: + self.downsample = downsample(dim=dim, norm_layer=norm_layer) + else: + self.downsample = None + + def forward(self, x, H, W, l, l_mask): + """ Forward function. + + Args: + x: Input feature, tensor size (B, H*W, C). + H, W: Spatial resolution of the input feature. + """ + + # calculate attention mask for SW-MSA + Hp = int(np.ceil(H / self.window_size)) * self.window_size + Wp = int(np.ceil(W / self.window_size)) * self.window_size + img_mask = torch.zeros((1, Hp, Wp, 1), device=x.device) # 1 Hp Wp 1 + h_slices = (slice(0, -self.window_size), + slice(-self.window_size, -self.shift_size), + slice(-self.shift_size, None)) + w_slices = (slice(0, -self.window_size), + slice(-self.window_size, -self.shift_size), + slice(-self.shift_size, None)) + cnt = 0 + for h in h_slices: + for w in w_slices: + img_mask[:, h, w, :] = cnt + cnt += 1 + + mask_windows = window_partition(img_mask, self.window_size) # nW, window_size, window_size, 1 + mask_windows = mask_windows.view(-1, self.window_size * self.window_size) + attn_mask = mask_windows.unsqueeze(1) - mask_windows.unsqueeze(2) + attn_mask = attn_mask.masked_fill(attn_mask != 0, float(-100.0)).masked_fill(attn_mask == 0, float(0.0)) + + for blk in self.blocks: + blk.H, blk.W = H, W + if self.use_checkpoint: + x = checkpoint.checkpoint(blk, x, attn_mask) + else: + x = blk(x, attn_mask) # output of a Block has shape (B, H*W, dim) + + # PWAM fusion + x_residual = self.fusion(x, l, l_mask) + # apply a gate on the residual + x = x + (self.res_gate(x_residual) * x_residual) + + if self.downsample is not None: + x_down = self.downsample(x, H, W) + Wh, Ww = (H + 1) // 2, (W + 1) // 2 + return x_residual, H, W, x_down, Wh, Ww + else: + return x_residual, H, W, x, H, W + + +class PWAM(nn.Module): + def __init__(self, dim, v_in_channels, l_in_channels, key_channels, value_channels, num_heads=0, dropout=0.0): + super(PWAM, self).__init__() + # input x shape: (B, H*W, dim) + self.vis_project = nn.Sequential(nn.Conv1d(dim, dim, 1, 1), # the init function sets bias to 0 if bias is True + nn.GELU(), + nn.Dropout(dropout) + ) + + self.image_lang_att = SpatialImageLanguageAttention(v_in_channels, # v_in + l_in_channels, # l_in + key_channels, # key + value_channels, # value + out_channels=value_channels, # out + num_heads=num_heads) + + self.project_mm = nn.Sequential(nn.Conv1d(value_channels, value_channels, 1, 1), + nn.GELU(), + nn.Dropout(dropout) + ) + + def forward(self, x, l, l_mask): + # input x shape: (B, H*W, dim) + vis = self.vis_project(x.permute(0, 2, 1)) # (B, dim, H*W) + + lang = self.image_lang_att(x, l, l_mask) # (B, H*W, dim) + + lang = lang.permute(0, 2, 1) # (B, dim, H*W) + + mm = torch.mul(vis, lang) + mm = self.project_mm(mm) # (B, dim, H*W) + + mm = mm.permute(0, 2, 1) # (B, H*W, dim) + + return mm + + +class SpatialImageLanguageAttention(nn.Module): + def __init__(self, v_in_channels, l_in_channels, key_channels, value_channels, out_channels=None, num_heads=1): + super(SpatialImageLanguageAttention, self).__init__() + # x shape: (B, H*W, v_in_channels) + # l input shape: (B, l_in_channels, N_l) + # l_mask shape: (B, N_l, 1) + self.v_in_channels = v_in_channels + self.l_in_channels = l_in_channels + self.out_channels = out_channels + self.key_channels = key_channels + self.value_channels = value_channels + self.num_heads = num_heads + if out_channels is None: + self.out_channels = self.value_channels + + # Keys: language features: (B, l_in_channels, #words) + # avoid any form of spatial normalization because a sentence contains many padding 0s + self.f_key = nn.Sequential( + nn.Conv1d(self.l_in_channels, self.key_channels, kernel_size=1, stride=1), + ) + + # Queries: visual features: (B, H*W, v_in_channels) + self.f_query = nn.Sequential( + nn.Conv1d(self.v_in_channels, self.key_channels, kernel_size=1, stride=1), + nn.InstanceNorm1d(self.key_channels), + ) + + # Values: language features: (B, l_in_channels, #words) + self.f_value = nn.Sequential( + nn.Conv1d(self.l_in_channels, self.value_channels, kernel_size=1, stride=1), + ) + + # Out projection + self.W = nn.Sequential( + nn.Conv1d(self.value_channels, self.out_channels, kernel_size=1, stride=1), + nn.InstanceNorm1d(self.out_channels), + ) + + def forward(self, x, l, l_mask): + # x shape: (B, H*W, v_in_channels) + # l input shape: (B, l_in_channels, N_l) + # l_mask shape: (B, N_l, 1) + B, HW = x.size(0), x.size(1) + x = x.permute(0, 2, 1) # (B, key_channels, H*W) + l_mask = l_mask.permute(0, 2, 1) # (B, N_l, 1) -> (B, 1, N_l) + + query = self.f_query(x) # (B, key_channels, H*W) if Conv1D + query = query.permute(0, 2, 1) # (B, H*W, key_channels) + key = self.f_key(l) # (B, key_channels, N_l) + value = self.f_value(l) # (B, self.value_channels, N_l) + key = key * l_mask # (B, key_channels, N_l) + value = value * l_mask # (B, self.value_channels, N_l) + n_l = value.size(-1) + query = query.reshape(B, HW, self.num_heads, self.key_channels//self.num_heads).permute(0, 2, 1, 3) + # (b, num_heads, H*W, self.key_channels//self.num_heads) + key = key.reshape(B, self.num_heads, self.key_channels//self.num_heads, n_l) + # (b, num_heads, self.key_channels//self.num_heads, n_l) + value = value.reshape(B, self.num_heads, self.value_channels//self.num_heads, n_l) + # # (b, num_heads, self.value_channels//self.num_heads, n_l) + l_mask = l_mask.unsqueeze(1) # (b, 1, 1, n_l) + + sim_map = torch.matmul(query, key) # (B, self.num_heads, H*W, N_l) + sim_map = (self.key_channels ** -.5) * sim_map # scaled dot product + + sim_map = sim_map + (1e4*l_mask - 1e4) # assign a very small number to padding positions + sim_map = F.softmax(sim_map, dim=-1) # (B, num_heads, h*w, N_l) + out = torch.matmul(sim_map, value.permute(0, 1, 3, 2)) # (B, num_heads, H*W, self.value_channels//num_heads) + out = out.permute(0, 2, 1, 3).contiguous().reshape(B, HW, self.value_channels) # (B, H*W, value_channels) + out = out.permute(0, 2, 1) # (B, value_channels, HW) + out = self.W(out) # (B, value_channels, HW) + out = out.permute(0, 2, 1) # (B, HW, value_channels) + + return out diff --git a/LAVT-RIS/lib/mask_predictor.py b/LAVT-RIS/lib/mask_predictor.py new file mode 100644 index 0000000000000000000000000000000000000000..bea268a17d3a39c216a48496846327cfcbed425a --- /dev/null +++ b/LAVT-RIS/lib/mask_predictor.py @@ -0,0 +1,72 @@ +import torch +from torch import nn +from torch.nn import functional as F +from collections import OrderedDict + + +class SimpleDecoding(nn.Module): + def __init__(self, c4_dims, factor=2): + super(SimpleDecoding, self).__init__() + + hidden_size = c4_dims//factor + c4_size = c4_dims + c3_size = c4_dims//(factor**1) + c2_size = c4_dims//(factor**2) + c1_size = c4_dims//(factor**3) + + self.conv1_4 = nn.Conv2d(c4_size+c3_size, hidden_size, 3, padding=1, bias=False) + self.bn1_4 = nn.BatchNorm2d(hidden_size) + self.relu1_4 = nn.ReLU() + self.conv2_4 = nn.Conv2d(hidden_size, hidden_size, 3, padding=1, bias=False) + self.bn2_4 = nn.BatchNorm2d(hidden_size) + self.relu2_4 = nn.ReLU() + + self.conv1_3 = nn.Conv2d(hidden_size + c2_size, hidden_size, 3, padding=1, bias=False) + self.bn1_3 = nn.BatchNorm2d(hidden_size) + self.relu1_3 = nn.ReLU() + self.conv2_3 = nn.Conv2d(hidden_size, hidden_size, 3, padding=1, bias=False) + self.bn2_3 = nn.BatchNorm2d(hidden_size) + self.relu2_3 = nn.ReLU() + + self.conv1_2 = nn.Conv2d(hidden_size + c1_size, hidden_size, 3, padding=1, bias=False) + self.bn1_2 = nn.BatchNorm2d(hidden_size) + self.relu1_2 = nn.ReLU() + self.conv2_2 = nn.Conv2d(hidden_size, hidden_size, 3, padding=1, bias=False) + self.bn2_2 = nn.BatchNorm2d(hidden_size) + self.relu2_2 = nn.ReLU() + + self.conv1_1 = nn.Conv2d(hidden_size, 2, 1) + + def forward(self, x_c4, x_c3, x_c2, x_c1): + # fuse Y4 and Y3 + if x_c4.size(-2) < x_c3.size(-2) or x_c4.size(-1) < x_c3.size(-1): + x_c4 = F.interpolate(input=x_c4, size=(x_c3.size(-2), x_c3.size(-1)), mode='bilinear', align_corners=True) + x = torch.cat([x_c4, x_c3], dim=1) + x = self.conv1_4(x) + x = self.bn1_4(x) + x = self.relu1_4(x) + x = self.conv2_4(x) + x = self.bn2_4(x) + x = self.relu2_4(x) + # fuse top-down features and Y2 features + if x.size(-2) < x_c2.size(-2) or x.size(-1) < x_c2.size(-1): + x = F.interpolate(input=x, size=(x_c2.size(-2), x_c2.size(-1)), mode='bilinear', align_corners=True) + x = torch.cat([x, x_c2], dim=1) + x = self.conv1_3(x) + x = self.bn1_3(x) + x = self.relu1_3(x) + x = self.conv2_3(x) + x = self.bn2_3(x) + x = self.relu2_3(x) + # fuse top-down features and Y1 features + if x.size(-2) < x_c1.size(-2) or x.size(-1) < x_c1.size(-1): + x = F.interpolate(input=x, size=(x_c1.size(-2), x_c1.size(-1)), mode='bilinear', align_corners=True) + x = torch.cat([x, x_c1], dim=1) + x = self.conv1_2(x) + x = self.bn1_2(x) + x = self.relu1_2(x) + x = self.conv2_2(x) + x = self.bn2_2(x) + x = self.relu2_2(x) + + return self.conv1_1(x) diff --git a/LAVT-RIS/lib/mmcv_custom/__init__.py b/LAVT-RIS/lib/mmcv_custom/__init__.py new file mode 100644 index 0000000000000000000000000000000000000000..7e0e39b03e2a149c33c372472b2b814a872ec55c --- /dev/null +++ b/LAVT-RIS/lib/mmcv_custom/__init__.py @@ -0,0 +1,5 @@ +# -*- coding: utf-8 -*- + +from .checkpoint import load_checkpoint + +__all__ = ['load_checkpoint'] diff --git a/LAVT-RIS/lib/mmcv_custom/__pycache__/__init__.cpython-37.pyc b/LAVT-RIS/lib/mmcv_custom/__pycache__/__init__.cpython-37.pyc new file mode 100644 index 0000000000000000000000000000000000000000..26687f11226b8cc8c99882c4a629eb7a2c2288c4 Binary files /dev/null and b/LAVT-RIS/lib/mmcv_custom/__pycache__/__init__.cpython-37.pyc differ diff --git a/LAVT-RIS/lib/mmcv_custom/__pycache__/__init__.cpython-39.pyc b/LAVT-RIS/lib/mmcv_custom/__pycache__/__init__.cpython-39.pyc new file mode 100644 index 0000000000000000000000000000000000000000..252e567a52d6277dd6068767c638c48de0522480 Binary files /dev/null and b/LAVT-RIS/lib/mmcv_custom/__pycache__/__init__.cpython-39.pyc differ diff --git a/LAVT-RIS/lib/mmcv_custom/__pycache__/checkpoint.cpython-37.pyc b/LAVT-RIS/lib/mmcv_custom/__pycache__/checkpoint.cpython-37.pyc new file mode 100644 index 0000000000000000000000000000000000000000..3a2b9b7831bb39973b99bdf679d0cdf8ca2121ba Binary files /dev/null and b/LAVT-RIS/lib/mmcv_custom/__pycache__/checkpoint.cpython-37.pyc differ diff --git a/LAVT-RIS/lib/mmcv_custom/__pycache__/checkpoint.cpython-39.pyc b/LAVT-RIS/lib/mmcv_custom/__pycache__/checkpoint.cpython-39.pyc new file mode 100644 index 0000000000000000000000000000000000000000..ef6ef1742fab293719c09a65a50a8a59df590fbe Binary files /dev/null and b/LAVT-RIS/lib/mmcv_custom/__pycache__/checkpoint.cpython-39.pyc differ diff --git a/LAVT-RIS/lib/mmcv_custom/checkpoint.py b/LAVT-RIS/lib/mmcv_custom/checkpoint.py new file mode 100644 index 0000000000000000000000000000000000000000..9158fd60581ae96d2f13eed25e915f5e423585da --- /dev/null +++ b/LAVT-RIS/lib/mmcv_custom/checkpoint.py @@ -0,0 +1,508 @@ +# Copyright (c) Open-MMLab. All rights reserved. +import io +import os +import os.path as osp +import pkgutil +import time +import warnings +from collections import OrderedDict +from importlib import import_module +from tempfile import TemporaryDirectory + +import torch +import torchvision +from torch.optim import Optimizer +from torch.utils import model_zoo +from torch.nn import functional as F + +import mmcv +from mmengine.fileio import FileClient +# from mmcv.fileio import FileClient +# from mmcv.parallel import is_module_wrapper +from mmengine.fileio import load as load_file +from mmengine.model.wrappers.utils import is_model_wrapper +from mmengine.utils.path import mkdir_or_exist +# from mmcv.utils import mkdir_or_exist +from mmengine.dist.utils import get_dist_info +# from mmcv.runner import get_dist_info + +ENV_MMCV_HOME = 'MMCV_HOME' +ENV_XDG_CACHE_HOME = 'XDG_CACHE_HOME' +DEFAULT_CACHE_DIR = '~/.cache' + + +def _get_mmcv_home(): + mmcv_home = os.path.expanduser( + os.getenv( + ENV_MMCV_HOME, + os.path.join( + os.getenv(ENV_XDG_CACHE_HOME, DEFAULT_CACHE_DIR), 'mmcv'))) + + mkdir_or_exist(mmcv_home) + return mmcv_home + + +def load_state_dict(module, state_dict, strict=False, logger=None): + """Load state_dict to a module. + + This method is modified from :meth:`torch.nn.Module.load_state_dict`. + Default value for ``strict`` is set to ``False`` and the message for + param mismatch will NOT be shown if strict is False. + + Args: + module (Module): Module that receives the state_dict. + state_dict (OrderedDict): Weights. + strict (bool): whether to strictly enforce that the keys + in :attr:`state_dict` match the keys returned by this module's + :meth:`~torch.nn.Module.state_dict` function. Default: ``False``. + logger (:obj:`logging.Logger`, optional): Logger to log the error + message. If not specified, print function will be used. + """ + unexpected_keys = [] + all_missing_keys = [] + err_msg = [] + + metadata = getattr(state_dict, '_metadata', None) + state_dict = state_dict.copy() + if metadata is not None: + state_dict._metadata = metadata + + # use _load_from_state_dict to enable checkpoint version control + def load(module, prefix=''): + # recursively check parallel module in case that the model has a + # complicated structure, e.g., nn.Module(nn.Module(DDP)) + if is_model_wrapper(module): + module = module.module + local_metadata = {} if metadata is None else metadata.get( + prefix[:-1], {}) + module._load_from_state_dict(state_dict, prefix, local_metadata, True, + all_missing_keys, unexpected_keys, + err_msg) + for name, child in module._modules.items(): + if child is not None: + load(child, prefix + name + '.') + + load(module) + load = None # break load->load reference cycle + + # ignore "num_batches_tracked" of BN layers + missing_keys = [ + key for key in all_missing_keys if 'num_batches_tracked' not in key + ] + + if unexpected_keys: + err_msg.append('unexpected key in source ' + f'state_dict: {", ".join(unexpected_keys)}\n') + if missing_keys: + err_msg.append( + f'missing keys in source state_dict: {", ".join(missing_keys)}\n') + + if strict: + rank, _ = get_dist_info() + if len(err_msg) > 0 and rank == 0: + err_msg.insert( + 0, 'The model and loaded state dict do not match exactly\n') + err_msg = '\n'.join(err_msg) + if strict: + raise RuntimeError(err_msg) + elif logger is not None: + logger.warning(err_msg) + else: + print(err_msg) + + +def load_url_dist(url, model_dir=None): + """In distributed setting, this function only download checkpoint at local + rank 0.""" + rank, world_size = get_dist_info() + rank = int(os.environ.get('LOCAL_RANK', rank)) + if rank == 0: + checkpoint = model_zoo.load_url(url, model_dir=model_dir) + if world_size > 1: + torch.distributed.barrier() + if rank > 0: + checkpoint = model_zoo.load_url(url, model_dir=model_dir) + return checkpoint + + +def load_pavimodel_dist(model_path, map_location=None): + """In distributed setting, this function only download checkpoint at local + rank 0.""" + try: + from pavi import modelcloud + except ImportError: + raise ImportError( + 'Please install pavi to load checkpoint from modelcloud.') + rank, world_size = get_dist_info() + rank = int(os.environ.get('LOCAL_RANK', rank)) + if rank == 0: + model = modelcloud.get(model_path) + with TemporaryDirectory() as tmp_dir: + downloaded_file = osp.join(tmp_dir, model.name) + model.download(downloaded_file) + checkpoint = torch.load(downloaded_file, map_location=map_location) + if world_size > 1: + torch.distributed.barrier() + if rank > 0: + model = modelcloud.get(model_path) + with TemporaryDirectory() as tmp_dir: + downloaded_file = osp.join(tmp_dir, model.name) + model.download(downloaded_file) + checkpoint = torch.load( + downloaded_file, map_location=map_location) + return checkpoint + + +def load_fileclient_dist(filename, backend, map_location): + """In distributed setting, this function only download checkpoint at local + rank 0.""" + rank, world_size = get_dist_info() + rank = int(os.environ.get('LOCAL_RANK', rank)) + allowed_backends = ['ceph'] + if backend not in allowed_backends: + raise ValueError(f'Load from Backend {backend} is not supported.') + if rank == 0: + fileclient = FileClient(backend=backend) + buffer = io.BytesIO(fileclient.get(filename)) + checkpoint = torch.load(buffer, map_location=map_location) + if world_size > 1: + torch.distributed.barrier() + if rank > 0: + fileclient = FileClient(backend=backend) + buffer = io.BytesIO(fileclient.get(filename)) + checkpoint = torch.load(buffer, map_location=map_location) + return checkpoint + + +def get_torchvision_models(): + model_urls = dict() + for _, name, ispkg in pkgutil.walk_packages(torchvision.models.__path__): + if ispkg: + continue + _zoo = import_module(f'torchvision.models.{name}') + if hasattr(_zoo, 'model_urls'): + _urls = getattr(_zoo, 'model_urls') + model_urls.update(_urls) + return model_urls + + +def get_external_models(): + mmcv_home = _get_mmcv_home() + default_json_path = osp.join(mmcv.__path__[0], 'model_zoo/open_mmlab.json') + default_urls = load_file(default_json_path) + assert isinstance(default_urls, dict) + external_json_path = osp.join(mmcv_home, 'open_mmlab.json') + if osp.exists(external_json_path): + external_urls = load_file(external_json_path) + assert isinstance(external_urls, dict) + default_urls.update(external_urls) + + return default_urls + + +def get_mmcls_models(): + mmcls_json_path = osp.join(mmcv.__path__[0], 'model_zoo/mmcls.json') + mmcls_urls = load_file(mmcls_json_path) + + return mmcls_urls + + +def get_deprecated_model_names(): + deprecate_json_path = osp.join(mmcv.__path__[0], + 'model_zoo/deprecated.json') + deprecate_urls = load_file(deprecate_json_path) + assert isinstance(deprecate_urls, dict) + + return deprecate_urls + + +def _process_mmcls_checkpoint(checkpoint): + state_dict = checkpoint['state_dict'] + new_state_dict = OrderedDict() + for k, v in state_dict.items(): + if k.startswith('backbone.'): + new_state_dict[k[9:]] = v + new_checkpoint = dict(state_dict=new_state_dict) + + return new_checkpoint + + +def _load_checkpoint(filename, map_location=None): + """Load checkpoint from somewhere (modelzoo, file, url). + + Args: + filename (str): Accept local filepath, URL, ``torchvision://xxx``, + ``open-mmlab://xxx``. Please refer to ``docs/model_zoo.md`` for + details. + map_location (str | None): Same as :func:`torch.load`. Default: None. + + Returns: + dict | OrderedDict: The loaded checkpoint. It can be either an + OrderedDict storing model weights or a dict containing other + information, which depends on the checkpoint. + """ + if filename.startswith('modelzoo://'): + warnings.warn('The URL scheme of "modelzoo://" is deprecated, please ' + 'use "torchvision://" instead') + model_urls = get_torchvision_models() + model_name = filename[11:] + checkpoint = load_url_dist(model_urls[model_name]) + elif filename.startswith('torchvision://'): + model_urls = get_torchvision_models() + model_name = filename[14:] + checkpoint = load_url_dist(model_urls[model_name]) + elif filename.startswith('open-mmlab://'): + model_urls = get_external_models() + model_name = filename[13:] + deprecated_urls = get_deprecated_model_names() + if model_name in deprecated_urls: + warnings.warn(f'open-mmlab://{model_name} is deprecated in favor ' + f'of open-mmlab://{deprecated_urls[model_name]}') + model_name = deprecated_urls[model_name] + model_url = model_urls[model_name] + # check if is url + if model_url.startswith(('http://', 'https://')): + checkpoint = load_url_dist(model_url) + else: + filename = osp.join(_get_mmcv_home(), model_url) + if not osp.isfile(filename): + raise IOError(f'{filename} is not a checkpoint file') + checkpoint = torch.load(filename, map_location=map_location) + elif filename.startswith('mmcls://'): + model_urls = get_mmcls_models() + model_name = filename[8:] + checkpoint = load_url_dist(model_urls[model_name]) + checkpoint = _process_mmcls_checkpoint(checkpoint) + elif filename.startswith(('http://', 'https://')): + checkpoint = load_url_dist(filename) + elif filename.startswith('pavi://'): + model_path = filename[7:] + checkpoint = load_pavimodel_dist(model_path, map_location=map_location) + elif filename.startswith('s3://'): + checkpoint = load_fileclient_dist( + filename, backend='ceph', map_location=map_location) + else: + if not osp.isfile(filename): + raise IOError(f'{filename} is not a checkpoint file') + checkpoint = torch.load(filename, map_location=map_location) + return checkpoint + + +def load_checkpoint(model, + filename, + map_location='cpu', + strict=False, + logger=None): + """Load checkpoint from a file or URI. + + Args: + model (Module): Module to load checkpoint. + filename (str): Accept local filepath, URL, ``torchvision://xxx``, + ``open-mmlab://xxx``. Please refer to ``docs/model_zoo.md`` for + details. + map_location (str): Same as :func:`torch.load`. + strict (bool): Whether to allow different params for the model and + checkpoint. + logger (:mod:`logging.Logger` or None): The logger for error message. + + Returns: + dict or OrderedDict: The loaded checkpoint. + """ + checkpoint = _load_checkpoint(filename, map_location) + # OrderedDict is a subclass of dict + if not isinstance(checkpoint, dict): + raise RuntimeError( + f'No state_dict found in checkpoint file {filename}') + # get state_dict from checkpoint + if 'state_dict' in checkpoint: + state_dict = checkpoint['state_dict'] + elif 'model' in checkpoint: + state_dict = checkpoint['model'] + else: + state_dict = checkpoint + # strip prefix of state_dict + if list(state_dict.keys())[0].startswith('module.'): + state_dict = {k[7:]: v for k, v in state_dict.items()} + # for upper net weights only + if list(state_dict.keys())[0].startswith('backbone.'): + print('Start stripping upper net pre-fix and loading backbone weights to our swin encoder') + state_dict = {k.replace('backbone.', ''): v for k, v in state_dict.items() if k.startswith('backbone.')} + # for MoBY, load model of online branch + if sorted(list(state_dict.keys()))[0].startswith('encoder'): + state_dict = {k.replace('encoder.', ''): v for k, v in state_dict.items() if k.startswith('encoder.')} + + # reshape absolute position embedding + if state_dict.get('absolute_pos_embed') is not None: + absolute_pos_embed = state_dict['absolute_pos_embed'] + N1, L, C1 = absolute_pos_embed.size() + N2, C2, H, W = model.absolute_pos_embed.size() + if N1 != N2 or C1 != C2 or L != H*W: + logger.warning("Error in loading absolute_pos_embed, pass") + else: + state_dict['absolute_pos_embed'] = absolute_pos_embed.view(N2, H, W, C2).permute(0, 3, 1, 2) + + # interpolate position bias table if needed + relative_position_bias_table_keys = [k for k in state_dict.keys() if "relative_position_bias_table" in k] + for table_key in relative_position_bias_table_keys: + table_pretrained = state_dict[table_key] + table_current = model.state_dict()[table_key] + L1, nH1 = table_pretrained.size() + L2, nH2 = table_current.size() + if nH1 != nH2: + logger.warning(f"Error in loading {table_key}, pass") + else: + if L1 != L2: + S1 = int(L1 ** 0.5) + S2 = int(L2 ** 0.5) + table_pretrained_resized = F.interpolate( + table_pretrained.permute(1, 0).view(1, nH1, S1, S1), + size=(S2, S2), mode='bicubic') + state_dict[table_key] = table_pretrained_resized.view(nH2, L2).permute(1, 0) + + # load state_dict + load_state_dict(model, state_dict, strict, logger) + return checkpoint + + +def weights_to_cpu(state_dict): + """Copy a model state_dict to cpu. + + Args: + state_dict (OrderedDict): Model weights on GPU. + + Returns: + OrderedDict: Model weights on GPU. + """ + state_dict_cpu = OrderedDict() + for key, val in state_dict.items(): + state_dict_cpu[key] = val.cpu() + return state_dict_cpu + + +def _save_to_state_dict(module, destination, prefix, keep_vars): + """Saves module state to `destination` dictionary. + + This method is modified from :meth:`torch.nn.Module._save_to_state_dict`. + + Args: + module (nn.Module): The module to generate state_dict. + destination (dict): A dict where state will be stored. + prefix (str): The prefix for parameters and buffers used in this + module. + """ + for name, param in module._parameters.items(): + if param is not None: + destination[prefix + name] = param if keep_vars else param.detach() + for name, buf in module._buffers.items(): + # remove check of _non_persistent_buffers_set to allow nn.BatchNorm2d + if buf is not None: + destination[prefix + name] = buf if keep_vars else buf.detach() + + +def get_state_dict(module, destination=None, prefix='', keep_vars=False): + """Returns a dictionary containing a whole state of the module. + + Both parameters and persistent buffers (e.g. running averages) are + included. Keys are corresponding parameter and buffer names. + + This method is modified from :meth:`torch.nn.Module.state_dict` to + recursively check parallel module in case that the model has a complicated + structure, e.g., nn.Module(nn.Module(DDP)). + + Args: + module (nn.Module): The module to generate state_dict. + destination (OrderedDict): Returned dict for the state of the + module. + prefix (str): Prefix of the key. + keep_vars (bool): Whether to keep the variable property of the + parameters. Default: False. + + Returns: + dict: A dictionary containing a whole state of the module. + """ + # recursively check parallel module in case that the model has a + # complicated structure, e.g., nn.Module(nn.Module(DDP)) + if is_model_wrapper(module): + module = module.module + + # below is the same as torch.nn.Module.state_dict() + if destination is None: + destination = OrderedDict() + destination._metadata = OrderedDict() + destination._metadata[prefix[:-1]] = local_metadata = dict( + version=module._version) + _save_to_state_dict(module, destination, prefix, keep_vars) + for name, child in module._modules.items(): + if child is not None: + get_state_dict( + child, destination, prefix + name + '.', keep_vars=keep_vars) + for hook in module._state_dict_hooks.values(): + hook_result = hook(module, destination, prefix, local_metadata) + if hook_result is not None: + destination = hook_result + return destination + + +def save_checkpoint(model, filename, optimizer=None, meta=None): + """Save checkpoint to file. + + The checkpoint will have 3 fields: ``meta``, ``state_dict`` and + ``optimizer``. By default ``meta`` will contain version and time info. + + Args: + model (Module): Module whose params are to be saved. + filename (str): Checkpoint filename. + optimizer (:obj:`Optimizer`, optional): Optimizer to be saved. + meta (dict, optional): Metadata to be saved in checkpoint. + """ + if meta is None: + meta = {} + elif not isinstance(meta, dict): + raise TypeError(f'meta must be a dict or None, but got {type(meta)}') + meta.update(mmcv_version=mmcv.__version__, time=time.asctime()) + + if is_model_wrapper(model): + model = model.module + + if hasattr(model, 'CLASSES') and model.CLASSES is not None: + # save class name to the meta + meta.update(CLASSES=model.CLASSES) + + checkpoint = { + 'meta': meta, + 'state_dict': weights_to_cpu(get_state_dict(model)) + } + # save optimizer state dict in the checkpoint + if isinstance(optimizer, Optimizer): + checkpoint['optimizer'] = optimizer.state_dict() + elif isinstance(optimizer, dict): + checkpoint['optimizer'] = {} + for name, optim in optimizer.items(): + checkpoint['optimizer'][name] = optim.state_dict() + + if filename.startswith('pavi://'): + try: + from pavi import modelcloud + from pavi.exception import NodeNotFoundError + except ImportError: + raise ImportError( + 'Please install pavi to load checkpoint from modelcloud.') + model_path = filename[7:] + root = modelcloud.Folder() + model_dir, model_name = osp.split(model_path) + try: + model = modelcloud.get(model_dir) + except NodeNotFoundError: + model = root.create_training_model(model_dir) + with TemporaryDirectory() as tmp_dir: + checkpoint_file = osp.join(tmp_dir, model_name) + with open(checkpoint_file, 'wb') as f: + torch.save(checkpoint, f) + f.flush() + model.create_file(checkpoint_file, name=model_name) + else: + mmcv.mkdir_or_exist(osp.dirname(filename)) + # immediately flush buffer + with open(filename, 'wb') as f: + torch.save(checkpoint, f) + f.flush() diff --git a/LAVT-RIS/lib/segmentation.py b/LAVT-RIS/lib/segmentation.py new file mode 100644 index 0000000000000000000000000000000000000000..13a8da3080a9bec357d1d9343d16a933298b0c8d --- /dev/null +++ b/LAVT-RIS/lib/segmentation.py @@ -0,0 +1,143 @@ +import torch +import torch.nn as nn +from .mask_predictor import SimpleDecoding +from .backbone import MultiModalSwinTransformer +from ._utils import LAVT, LAVTOne + +__all__ = ['lavt', 'lavt_one'] + + +# LAVT +def _segm_lavt(pretrained, args): + # initialize the SwinTransformer backbone with the specified version + if args.swin_type == 'tiny': + embed_dim = 96 + depths = [2, 2, 6, 2] + num_heads = [3, 6, 12, 24] + elif args.swin_type == 'small': + embed_dim = 96 + depths = [2, 2, 18, 2] + num_heads = [3, 6, 12, 24] + elif args.swin_type == 'base': + embed_dim = 128 + depths = [2, 2, 18, 2] + num_heads = [4, 8, 16, 32] + elif args.swin_type == 'large': + embed_dim = 192 + depths = [2, 2, 18, 2] + num_heads = [6, 12, 24, 48] + else: + assert False + # args.window12 added for test.py because state_dict is loaded after model initialization + if 'window12' in pretrained or args.window12: + print('Window size 12!') + window_size = 12 + else: + window_size = 7 + + if args.mha: + mha = args.mha.split('-') # if non-empty, then ['a', 'b', 'c', 'd'] + mha = [int(a) for a in mha] + else: + mha = [1, 1, 1, 1] + + out_indices = (0, 1, 2, 3) + backbone = MultiModalSwinTransformer(embed_dim=embed_dim, depths=depths, num_heads=num_heads, + window_size=window_size, + ape=False, drop_path_rate=0.3, patch_norm=True, + out_indices=out_indices, + use_checkpoint=False, num_heads_fusion=mha, + fusion_drop=args.fusion_drop + ) + if pretrained: + print('Initializing Multi-modal Swin Transformer weights from ' + pretrained) + backbone.init_weights(pretrained=pretrained) + else: + print('Randomly initialize Multi-modal Swin Transformer weights.') + backbone.init_weights() + + model_map = [SimpleDecoding, LAVT] + + classifier = model_map[0](8*embed_dim) + base_model = model_map[1] + + model = base_model(backbone, classifier) + return model + + +def _load_model_lavt(pretrained, args): + model = _segm_lavt(pretrained, args) + return model + + +def lavt(pretrained='', args=None): + return _load_model_lavt(pretrained, args) + + +############################################### +# LAVT One: put BERT inside the overall model # +############################################### +def _segm_lavt_one(pretrained, args): + # initialize the SwinTransformer backbone with the specified version + if args.swin_type == 'tiny': + embed_dim = 96 + depths = [2, 2, 6, 2] + num_heads = [3, 6, 12, 24] + elif args.swin_type == 'small': + embed_dim = 96 + depths = [2, 2, 18, 2] + num_heads = [3, 6, 12, 24] + elif args.swin_type == 'base': + embed_dim = 128 + depths = [2, 2, 18, 2] + num_heads = [4, 8, 16, 32] + elif args.swin_type == 'large': + embed_dim = 192 + depths = [2, 2, 18, 2] + num_heads = [6, 12, 24, 48] + else: + assert False + # args.window12 added for test.py because state_dict is loaded after model initialization + if 'window12' in pretrained or args.window12: + print('Window size 12!') + window_size = 12 + else: + window_size = 7 + + if args.mha: + mha = args.mha.split('-') # if non-empty, then ['a', 'b', 'c', 'd'] + mha = [int(a) for a in mha] + else: + mha = [1, 1, 1, 1] + + out_indices = (0, 1, 2, 3) + backbone = MultiModalSwinTransformer(embed_dim=embed_dim, depths=depths, num_heads=num_heads, + window_size=window_size, + ape=False, drop_path_rate=0.3, patch_norm=True, + out_indices=out_indices, + use_checkpoint=False, num_heads_fusion=mha, + fusion_drop=args.fusion_drop + ) + if pretrained: + print('Initializing Multi-modal Swin Transformer weights from ' + pretrained) + backbone.init_weights(pretrained=pretrained) + else: + print('Randomly initialize Multi-modal Swin Transformer weights.') + backbone.init_weights() + + model_map = [SimpleDecoding, LAVTOne] + + classifier = model_map[0](8*embed_dim) + base_model = model_map[1] + + model = base_model(backbone, classifier, args) + return model + + +def _load_model_lavt_one(pretrained, args): + model = _segm_lavt_one(pretrained, args) + return model + + +def lavt_one(pretrained='', args=None): + return _load_model_lavt_one(pretrained, args) diff --git a/LAVT-RIS/logs/gref_m10_tmp005_4gpu_bs32.log b/LAVT-RIS/logs/gref_m10_tmp005_4gpu_bs32.log new file mode 100644 index 0000000000000000000000000000000000000000..0fefc6d8dc174ccff6af96abe9354e1f1b946248 --- /dev/null +++ b/LAVT-RIS/logs/gref_m10_tmp005_4gpu_bs32.log @@ -0,0 +1,12089 @@ +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torch/distributed/launch.py:178: FutureWarning: The module torch.distributed.launch is deprecated +and will be removed in future. Use torchrun. +Note that --use_env is set by default in torchrun. +If your script expects `--local_rank` argument to be set, please +change it to read from `os.environ['LOCAL_RANK']` instead. See +https://pytorch.org/docs/stable/distributed.html#launch-utility for +further instructions + + warnings.warn( +WARNING:torch.distributed.run: +***************************************** +Setting OMP_NUM_THREADS environment variable for each process to be 1 in default, to avoid your system being overloaded, please further tune the variable for optimal performance in your application as needed. +***************************************** +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/timm/models/layers/__init__.py:48: FutureWarning: Importing from timm.models.layers is deprecated, please import via timm.layers + warnings.warn(f"Importing from {__name__} is deprecated, please import via timm.layers", FutureWarning) +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/timm/models/layers/__init__.py:48: FutureWarning: Importing from timm.models.layers is deprecated, please import via timm.layers + warnings.warn(f"Importing from {__name__} is deprecated, please import via timm.layers", FutureWarning) +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/timm/models/layers/__init__.py:48: FutureWarning: Importing from timm.models.layers is deprecated, please import via timm.layers + warnings.warn(f"Importing from {__name__} is deprecated, please import via timm.layers", FutureWarning) +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/timm/models/layers/__init__.py:48: FutureWarning: Importing from timm.models.layers is deprecated, please import via timm.layers + warnings.warn(f"Importing from {__name__} is deprecated, please import via timm.layers", FutureWarning) +RANK and WORLD_SIZE in environment: 1/4 +RANK and WORLD_SIZE in environment: 2/4 +RANK and WORLD_SIZE in environment: 0/4 +RANK and WORLD_SIZE in environment: 3/4 +Image size: 480 +loading dataset refcocog into memory... +creating index... +index created. +DONE (t=8.18s) +loading dataset refcocog into memory... +creating index... +index created. +DONE (t=6.54s) +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torch/functional.py:478: UserWarning: torch.meshgrid: in an upcoming release, it will be required to pass the indexing argument. (Triggered internally at ../aten/src/ATen/native/TensorShape.cpp:2894.) + return _VF.meshgrid(tensors, **kwargs) # type: ignore[attr-defined] +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torch/functional.py:478: UserWarning: torch.meshgrid: in an upcoming release, it will be required to pass the indexing argument. (Triggered internally at ../aten/src/ATen/native/TensorShape.cpp:2894.) + return _VF.meshgrid(tensors, **kwargs) # type: ignore[attr-defined] +local rank 0 / global rank 0 successfully built train dataset. +lavt_one +Window size 12! +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torch/functional.py:478: UserWarning: torch.meshgrid: in an upcoming release, it will be required to pass the indexing argument. (Triggered internally at ../aten/src/ATen/native/TensorShape.cpp:2894.) + return _VF.meshgrid(tensors, **kwargs) # type: ignore[attr-defined] +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torch/functional.py:478: UserWarning: torch.meshgrid: in an upcoming release, it will be required to pass the indexing argument. (Triggered internally at ../aten/src/ATen/native/TensorShape.cpp:2894.) + return _VF.meshgrid(tensors, **kwargs) # type: ignore[attr-defined] +Initializing Multi-modal Swin Transformer weights from ./pretrained_weights/swin_base_patch4_window12_384_22k.pth +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [0] [ 0/1319] eta: 10:54:59 lr: 4.9999147080313756e-05 loss: 0.7529 (0.7529) time: 29.7952 data: 6.7522 max mem: 20156 +Epoch: [0] [ 10/1319] eta: 2:05:27 lr: 4.999061779453083e-05 loss: 0.5984 (0.6214) time: 5.7503 data: 0.6223 max mem: 28287 +Epoch: [0] [ 20/1319] eta: 1:39:38 lr: 4.9982088347050674e-05 loss: 0.4711 (0.5108) time: 3.3427 data: 0.0079 max mem: 28287 +Epoch: [0] [ 30/1319] eta: 1:30:24 lr: 4.9973558737839576e-05 loss: 0.3432 (0.4513) time: 3.3600 data: 0.0070 max mem: 28287 +Epoch: [0] [ 40/1319] eta: 1:25:24 lr: 4.9965028966863786e-05 loss: 0.2950 (0.4112) time: 3.3808 data: 0.0076 max mem: 29995 +Epoch: [0] [ 50/1319] eta: 1:22:11 lr: 4.995649903408956e-05 loss: 0.2810 (0.3949) time: 3.3865 data: 0.0075 max mem: 29995 +Epoch: [0] [ 60/1319] eta: 1:19:40 lr: 4.9947968939483133e-05 loss: 0.3270 (0.3890) time: 3.3687 data: 0.0076 max mem: 29995 +Epoch: [0] [ 70/1319] eta: 1:17:51 lr: 4.993943868301072e-05 loss: 0.3065 (0.3790) time: 3.3688 data: 0.0081 max mem: 31676 +Epoch: [0] [ 80/1319] eta: 1:16:20 lr: 4.993090826463852e-05 loss: 0.2842 (0.3647) time: 3.3909 data: 0.0080 max mem: 31676 +Epoch: [0] [ 90/1319] eta: 1:15:07 lr: 4.9922377684332736e-05 loss: 0.2471 (0.3542) time: 3.4093 data: 0.0078 max mem: 31676 +Epoch: [0] [ 100/1319] eta: 1:13:54 lr: 4.991384694205954e-05 loss: 0.2443 (0.3457) time: 3.3980 data: 0.0075 max mem: 31676 +Epoch: [0] [ 110/1319] eta: 1:12:53 lr: 4.990531603778512e-05 loss: 0.2748 (0.3432) time: 3.3874 data: 0.0074 max mem: 31676 +Epoch: [0] [ 120/1319] eta: 1:11:53 lr: 4.98967849714756e-05 loss: 0.2770 (0.3369) time: 3.3960 data: 0.0075 max mem: 31676 +Epoch: [0] [ 130/1319] eta: 1:10:57 lr: 4.988825374309713e-05 loss: 0.2614 (0.3331) time: 3.3791 data: 0.0073 max mem: 31676 +Epoch: [0] [ 140/1319] eta: 1:10:04 lr: 4.987972235261584e-05 loss: 0.2736 (0.3276) time: 3.3756 data: 0.0074 max mem: 31676 +Epoch: [0] [ 150/1319] eta: 1:09:12 lr: 4.987119079999784e-05 loss: 0.2451 (0.3248) time: 3.3660 data: 0.0076 max mem: 31676 +Epoch: [0] [ 160/1319] eta: 1:08:23 lr: 4.986265908520923e-05 loss: 0.2435 (0.3202) time: 3.3559 data: 0.0075 max mem: 31676 +Epoch: [0] [ 170/1319] eta: 1:07:35 lr: 4.985412720821609e-05 loss: 0.2435 (0.3177) time: 3.3595 data: 0.0073 max mem: 31676 +Epoch: [0] [ 180/1319] eta: 1:06:52 lr: 4.984559516898449e-05 loss: 0.2489 (0.3132) time: 3.3840 data: 0.0076 max mem: 31677 +Epoch: [0] [ 190/1319] eta: 1:06:06 lr: 4.98370629674805e-05 loss: 0.2489 (0.3104) time: 3.3736 data: 0.0079 max mem: 31677 +Epoch: [0] [ 200/1319] eta: 1:05:26 lr: 4.982853060367015e-05 loss: 0.2584 (0.3078) time: 3.3816 data: 0.0077 max mem: 31677 +Epoch: [0] [ 210/1319] eta: 1:04:45 lr: 4.9819998077519475e-05 loss: 0.2406 (0.3060) time: 3.4061 data: 0.0075 max mem: 31677 +Epoch: [0] [ 220/1319] eta: 1:04:04 lr: 4.98114653889945e-05 loss: 0.2233 (0.3025) time: 3.3864 data: 0.0075 max mem: 31677 +Epoch: [0] [ 230/1319] eta: 1:03:24 lr: 4.980293253806122e-05 loss: 0.2322 (0.3006) time: 3.3898 data: 0.0074 max mem: 31677 +Epoch: [0] [ 240/1319] eta: 1:02:42 lr: 4.9794399524685624e-05 loss: 0.2375 (0.2990) time: 3.3738 data: 0.0074 max mem: 31677 +Epoch: [0] [ 250/1319] eta: 1:02:05 lr: 4.97858663488337e-05 loss: 0.2377 (0.2966) time: 3.3886 data: 0.0075 max mem: 31677 +Epoch: [0] [ 260/1319] eta: 1:01:27 lr: 4.977733301047139e-05 loss: 0.2253 (0.2935) time: 3.4112 data: 0.0076 max mem: 31677 +Epoch: [0] [ 270/1319] eta: 1:00:49 lr: 4.9768799509564675e-05 loss: 0.2287 (0.2923) time: 3.4058 data: 0.0078 max mem: 31677 +Epoch: [0] [ 280/1319] eta: 1:00:11 lr: 4.976026584607946e-05 loss: 0.2287 (0.2901) time: 3.3974 data: 0.0078 max mem: 31677 +Epoch: [0] [ 290/1319] eta: 0:59:33 lr: 4.9751732019981684e-05 loss: 0.2436 (0.2898) time: 3.3872 data: 0.0075 max mem: 31677 +Epoch: [0] [ 300/1319] eta: 0:58:56 lr: 4.974319803123725e-05 loss: 0.2570 (0.2893) time: 3.3946 data: 0.0075 max mem: 31677 +Epoch: [0] [ 310/1319] eta: 0:58:18 lr: 4.973466387981205e-05 loss: 0.2736 (0.2892) time: 3.3930 data: 0.0075 max mem: 31677 +Epoch: [0] [ 320/1319] eta: 0:57:42 lr: 4.972612956567197e-05 loss: 0.2736 (0.2882) time: 3.3967 data: 0.0075 max mem: 31677 +Epoch: [0] [ 330/1319] eta: 0:57:04 lr: 4.971759508878288e-05 loss: 0.2364 (0.2869) time: 3.3773 data: 0.0076 max mem: 31677 +Epoch: [0] [ 340/1319] eta: 0:56:27 lr: 4.970906044911062e-05 loss: 0.2407 (0.2862) time: 3.3671 data: 0.0074 max mem: 31677 +Epoch: [0] [ 350/1319] eta: 0:55:51 lr: 4.970052564662105e-05 loss: 0.2388 (0.2848) time: 3.3967 data: 0.0076 max mem: 31677 +Epoch: [0] [ 360/1319] eta: 0:55:14 lr: 4.9691990681279974e-05 loss: 0.2185 (0.2833) time: 3.4007 data: 0.0078 max mem: 31677 +Epoch: [0] [ 370/1319] eta: 0:54:39 lr: 4.9683455553053225e-05 loss: 0.2323 (0.2822) time: 3.4044 data: 0.0077 max mem: 31677 +Epoch: [0] [ 380/1319] eta: 0:54:03 lr: 4.9674920261906595e-05 loss: 0.2137 (0.2804) time: 3.4059 data: 0.0077 max mem: 31677 +Epoch: [0] [ 390/1319] eta: 0:53:27 lr: 4.966638480780586e-05 loss: 0.1989 (0.2788) time: 3.3888 data: 0.0077 max mem: 31677 +Epoch: [0] [ 400/1319] eta: 0:52:51 lr: 4.9657849190716805e-05 loss: 0.2263 (0.2782) time: 3.3919 data: 0.0077 max mem: 31677 +Epoch: [0] [ 410/1319] eta: 0:52:15 lr: 4.964931341060517e-05 loss: 0.2263 (0.2771) time: 3.3952 data: 0.0076 max mem: 31677 +Epoch: [0] [ 420/1319] eta: 0:51:39 lr: 4.964077746743672e-05 loss: 0.2271 (0.2763) time: 3.3924 data: 0.0078 max mem: 31677 +Epoch: [0] [ 430/1319] eta: 0:51:04 lr: 4.963224136117718e-05 loss: 0.2352 (0.2754) time: 3.3984 data: 0.0077 max mem: 31677 +Epoch: [0] [ 440/1319] eta: 0:50:28 lr: 4.962370509179226e-05 loss: 0.2355 (0.2746) time: 3.3779 data: 0.0075 max mem: 31677 +Epoch: [0] [ 450/1319] eta: 0:49:52 lr: 4.9615168659247665e-05 loss: 0.2274 (0.2733) time: 3.3771 data: 0.0075 max mem: 31677 +Epoch: [0] [ 460/1319] eta: 0:49:16 lr: 4.960663206350908e-05 loss: 0.2095 (0.2721) time: 3.3709 data: 0.0077 max mem: 31677 +Epoch: [0] [ 470/1319] eta: 0:48:39 lr: 4.959809530454219e-05 loss: 0.2095 (0.2707) time: 3.3308 data: 0.0078 max mem: 31677 +Epoch: [0] [ 480/1319] eta: 0:48:04 lr: 4.958955838231264e-05 loss: 0.2132 (0.2697) time: 3.3518 data: 0.0080 max mem: 33368 +Epoch: [0] [ 490/1319] eta: 0:47:29 lr: 4.9581021296786104e-05 loss: 0.2132 (0.2686) time: 3.3994 data: 0.0079 max mem: 33368 +Epoch: [0] [ 500/1319] eta: 0:46:54 lr: 4.957248404792819e-05 loss: 0.2039 (0.2676) time: 3.3997 data: 0.0077 max mem: 33368 +Epoch: [0] [ 510/1319] eta: 0:46:18 lr: 4.956394663570453e-05 loss: 0.2062 (0.2668) time: 3.3709 data: 0.0077 max mem: 33368 +Epoch: [0] [ 520/1319] eta: 0:45:42 lr: 4.955540906008073e-05 loss: 0.2189 (0.2658) time: 3.3430 data: 0.0078 max mem: 33368 +Epoch: [0] [ 530/1319] eta: 0:45:07 lr: 4.954687132102238e-05 loss: 0.2013 (0.2647) time: 3.3575 data: 0.0078 max mem: 33368 +Epoch: [0] [ 540/1319] eta: 0:44:32 lr: 4.9538333418495056e-05 loss: 0.2013 (0.2638) time: 3.3873 data: 0.0077 max mem: 33368 +Epoch: [0] [ 550/1319] eta: 0:43:58 lr: 4.952979535246434e-05 loss: 0.2235 (0.2637) time: 3.3917 data: 0.0076 max mem: 33368 +Epoch: [0] [ 560/1319] eta: 0:43:22 lr: 4.952125712289576e-05 loss: 0.2256 (0.2632) time: 3.3837 data: 0.0075 max mem: 33368 +Epoch: [0] [ 570/1319] eta: 0:42:48 lr: 4.9512718729754866e-05 loss: 0.2307 (0.2629) time: 3.3824 data: 0.0076 max mem: 33368 +Epoch: [0] [ 580/1319] eta: 0:42:13 lr: 4.9504180173007175e-05 loss: 0.2307 (0.2624) time: 3.3920 data: 0.0077 max mem: 33368 +Epoch: [0] [ 590/1319] eta: 0:41:38 lr: 4.9495641452618194e-05 loss: 0.2146 (0.2619) time: 3.3811 data: 0.0077 max mem: 33368 +Epoch: [0] [ 600/1319] eta: 0:41:03 lr: 4.948710256855343e-05 loss: 0.2094 (0.2612) time: 3.3872 data: 0.0076 max mem: 33368 +Epoch: [0] [ 610/1319] eta: 0:40:29 lr: 4.9478563520778356e-05 loss: 0.2443 (0.2616) time: 3.3970 data: 0.0074 max mem: 33368 +Epoch: [0] [ 620/1319] eta: 0:39:54 lr: 4.947002430925844e-05 loss: 0.2578 (0.2614) time: 3.3838 data: 0.0077 max mem: 33368 +Epoch: [0] [ 630/1319] eta: 0:39:19 lr: 4.946148493395914e-05 loss: 0.2420 (0.2611) time: 3.3901 data: 0.0079 max mem: 33368 +Epoch: [0] [ 640/1319] eta: 0:38:45 lr: 4.945294539484589e-05 loss: 0.2272 (0.2605) time: 3.3882 data: 0.0076 max mem: 33368 +Epoch: [0] [ 650/1319] eta: 0:38:10 lr: 4.944440569188412e-05 loss: 0.2124 (0.2597) time: 3.3887 data: 0.0076 max mem: 33368 +Epoch: [0] [ 660/1319] eta: 0:37:36 lr: 4.943586582503924e-05 loss: 0.2298 (0.2597) time: 3.3958 data: 0.0076 max mem: 33368 +Epoch: [0] [ 670/1319] eta: 0:37:01 lr: 4.942732579427665e-05 loss: 0.2521 (0.2596) time: 3.3693 data: 0.0077 max mem: 33368 +Epoch: [0] [ 680/1319] eta: 0:36:26 lr: 4.941878559956172e-05 loss: 0.2294 (0.2589) time: 3.3645 data: 0.0075 max mem: 33368 +Epoch: [0] [ 690/1319] eta: 0:35:51 lr: 4.941024524085985e-05 loss: 0.2177 (0.2588) time: 3.3551 data: 0.0075 max mem: 33368 +Epoch: [0] [ 700/1319] eta: 0:35:16 lr: 4.940170471813637e-05 loss: 0.2177 (0.2585) time: 3.3596 data: 0.0076 max mem: 33368 +Epoch: [0] [ 710/1319] eta: 0:34:42 lr: 4.939316403135663e-05 loss: 0.2170 (0.2584) time: 3.3855 data: 0.0077 max mem: 33368 +Epoch: [0] [ 720/1319] eta: 0:34:08 lr: 4.938462318048596e-05 loss: 0.2200 (0.2579) time: 3.3894 data: 0.0077 max mem: 33368 +Epoch: [0] [ 730/1319] eta: 0:33:33 lr: 4.937608216548967e-05 loss: 0.2161 (0.2571) time: 3.3989 data: 0.0076 max mem: 33368 +Epoch: [0] [ 740/1319] eta: 0:32:59 lr: 4.936754098633307e-05 loss: 0.2015 (0.2568) time: 3.3862 data: 0.0077 max mem: 33368 +Epoch: [0] [ 750/1319] eta: 0:32:24 lr: 4.935899964298143e-05 loss: 0.2004 (0.2559) time: 3.3883 data: 0.0075 max mem: 33368 +Epoch: [0] [ 760/1319] eta: 0:31:50 lr: 4.9350458135400046e-05 loss: 0.1841 (0.2554) time: 3.4099 data: 0.0076 max mem: 33368 +Epoch: [0] [ 770/1319] eta: 0:31:15 lr: 4.934191646355415e-05 loss: 0.2032 (0.2550) time: 3.3789 data: 0.0078 max mem: 33368 +Epoch: [0] [ 780/1319] eta: 0:30:41 lr: 4.9333374627409e-05 loss: 0.2207 (0.2546) time: 3.3543 data: 0.0077 max mem: 33368 +Epoch: [0] [ 790/1319] eta: 0:30:06 lr: 4.932483262692982e-05 loss: 0.2207 (0.2541) time: 3.3557 data: 0.0077 max mem: 33368 +Epoch: [0] [ 800/1319] eta: 0:29:32 lr: 4.931629046208183e-05 loss: 0.2020 (0.2535) time: 3.3807 data: 0.0076 max mem: 33368 +Epoch: [0] [ 810/1319] eta: 0:28:58 lr: 4.9307748132830237e-05 loss: 0.2041 (0.2533) time: 3.4009 data: 0.0074 max mem: 33368 +Epoch: [0] [ 820/1319] eta: 0:28:24 lr: 4.929920563914022e-05 loss: 0.2260 (0.2531) time: 3.4185 data: 0.0078 max mem: 33368 +Epoch: [0] [ 830/1319] eta: 0:27:49 lr: 4.929066298097696e-05 loss: 0.2179 (0.2527) time: 3.3973 data: 0.0079 max mem: 33368 +Epoch: [0] [ 840/1319] eta: 0:27:15 lr: 4.928212015830561e-05 loss: 0.1984 (0.2520) time: 3.3787 data: 0.0080 max mem: 33368 +Epoch: [0] [ 850/1319] eta: 0:26:41 lr: 4.927357717109131e-05 loss: 0.1984 (0.2518) time: 3.4090 data: 0.0080 max mem: 33368 +Epoch: [0] [ 860/1319] eta: 0:26:07 lr: 4.926503401929921e-05 loss: 0.2183 (0.2514) time: 3.3909 data: 0.0081 max mem: 33368 +Epoch: [0] [ 870/1319] eta: 0:25:32 lr: 4.925649070289441e-05 loss: 0.2233 (0.2512) time: 3.3826 data: 0.0080 max mem: 33368 +Epoch: [0] [ 880/1319] eta: 0:24:58 lr: 4.9247947221842024e-05 loss: 0.2219 (0.2510) time: 3.3871 data: 0.0076 max mem: 33368 +Epoch: [0] [ 890/1319] eta: 0:24:24 lr: 4.923940357610714e-05 loss: 0.1977 (0.2504) time: 3.3762 data: 0.0076 max mem: 33368 +Epoch: [0] [ 900/1319] eta: 0:23:50 lr: 4.9230859765654824e-05 loss: 0.1914 (0.2500) time: 3.3974 data: 0.0078 max mem: 33368 +Epoch: [0] [ 910/1319] eta: 0:23:15 lr: 4.922231579045014e-05 loss: 0.1863 (0.2492) time: 3.4051 data: 0.0078 max mem: 33368 +Epoch: [0] [ 920/1319] eta: 0:22:41 lr: 4.921377165045815e-05 loss: 0.1883 (0.2490) time: 3.4081 data: 0.0078 max mem: 33368 +Epoch: [0] [ 930/1319] eta: 0:22:07 lr: 4.9205227345643864e-05 loss: 0.2210 (0.2487) time: 3.4069 data: 0.0079 max mem: 33368 +Epoch: [0] [ 940/1319] eta: 0:21:33 lr: 4.919668287597232e-05 loss: 0.2210 (0.2488) time: 3.4016 data: 0.0078 max mem: 33368 +Epoch: [0] [ 950/1319] eta: 0:20:58 lr: 4.918813824140851e-05 loss: 0.2105 (0.2484) time: 3.3718 data: 0.0078 max mem: 33368 +Epoch: [0] [ 960/1319] eta: 0:20:24 lr: 4.9179593441917424e-05 loss: 0.1989 (0.2479) time: 3.3641 data: 0.0079 max mem: 33368 +Epoch: [0] [ 970/1319] eta: 0:19:50 lr: 4.917104847746404e-05 loss: 0.1961 (0.2474) time: 3.3957 data: 0.0079 max mem: 33368 +Epoch: [0] [ 980/1319] eta: 0:19:16 lr: 4.916250334801333e-05 loss: 0.2092 (0.2471) time: 3.3838 data: 0.0082 max mem: 33368 +Epoch: [0] [ 990/1319] eta: 0:18:42 lr: 4.915395805353022e-05 loss: 0.2036 (0.2467) time: 3.3992 data: 0.0081 max mem: 33368 +Epoch: [0] [1000/1319] eta: 0:18:08 lr: 4.9145412593979664e-05 loss: 0.1921 (0.2463) time: 3.4055 data: 0.0075 max mem: 33368 +Epoch: [0] [1010/1319] eta: 0:17:33 lr: 4.913686696932656e-05 loss: 0.1924 (0.2458) time: 3.3874 data: 0.0075 max mem: 33368 +Epoch: [0] [1020/1319] eta: 0:16:59 lr: 4.9128321179535836e-05 loss: 0.1924 (0.2454) time: 3.3989 data: 0.0080 max mem: 33368 +Epoch: [0] [1030/1319] eta: 0:16:25 lr: 4.911977522457237e-05 loss: 0.2059 (0.2453) time: 3.4044 data: 0.0081 max mem: 33368 +Epoch: [0] [1040/1319] eta: 0:15:51 lr: 4.9111229104401044e-05 loss: 0.2158 (0.2451) time: 3.3823 data: 0.0078 max mem: 33368 +Epoch: [0] [1050/1319] eta: 0:15:17 lr: 4.910268281898671e-05 loss: 0.2158 (0.2450) time: 3.3889 data: 0.0083 max mem: 33368 +Epoch: [0] [1060/1319] eta: 0:14:43 lr: 4.9094136368294215e-05 loss: 0.2169 (0.2448) time: 3.3763 data: 0.0083 max mem: 33368 +Epoch: [0] [1070/1319] eta: 0:14:09 lr: 4.90855897522884e-05 loss: 0.2191 (0.2446) time: 3.3917 data: 0.0083 max mem: 33368 +Epoch: [0] [1080/1319] eta: 0:13:34 lr: 4.907704297093409e-05 loss: 0.1964 (0.2440) time: 3.4284 data: 0.0082 max mem: 33368 +Epoch: [0] [1090/1319] eta: 0:13:00 lr: 4.906849602419608e-05 loss: 0.1818 (0.2439) time: 3.3712 data: 0.0075 max mem: 33368 +Epoch: [0] [1100/1319] eta: 0:12:26 lr: 4.905994891203916e-05 loss: 0.2085 (0.2438) time: 3.3456 data: 0.0075 max mem: 33368 +Epoch: [0] [1110/1319] eta: 0:11:52 lr: 4.905140163442811e-05 loss: 0.2081 (0.2434) time: 3.3816 data: 0.0078 max mem: 33368 +Epoch: [0] [1120/1319] eta: 0:11:18 lr: 4.904285419132769e-05 loss: 0.1923 (0.2430) time: 3.3957 data: 0.0079 max mem: 33368 +Epoch: [0] [1130/1319] eta: 0:10:44 lr: 4.903430658270266e-05 loss: 0.2035 (0.2428) time: 3.3977 data: 0.0077 max mem: 33368 +Epoch: [0] [1140/1319] eta: 0:10:10 lr: 4.902575880851773e-05 loss: 0.2043 (0.2424) time: 3.3900 data: 0.0075 max mem: 33368 +Epoch: [0] [1150/1319] eta: 0:09:35 lr: 4.9017210868737634e-05 loss: 0.1887 (0.2420) time: 3.3771 data: 0.0074 max mem: 33368 +Epoch: [0] [1160/1319] eta: 0:09:01 lr: 4.900866276332707e-05 loss: 0.1827 (0.2415) time: 3.3870 data: 0.0077 max mem: 33368 +Epoch: [0] [1170/1319] eta: 0:08:27 lr: 4.9000114492250734e-05 loss: 0.1815 (0.2410) time: 3.4073 data: 0.0080 max mem: 33368 +Epoch: [0] [1180/1319] eta: 0:07:53 lr: 4.8991566055473306e-05 loss: 0.1815 (0.2405) time: 3.4259 data: 0.0077 max mem: 33368 +Epoch: [0] [1190/1319] eta: 0:07:19 lr: 4.8983017452959435e-05 loss: 0.1787 (0.2401) time: 3.4152 data: 0.0078 max mem: 33368 +Epoch: [0] [1200/1319] eta: 0:06:45 lr: 4.8974468684673776e-05 loss: 0.1907 (0.2401) time: 3.3919 data: 0.0075 max mem: 33368 +Epoch: [0] [1210/1319] eta: 0:06:11 lr: 4.896591975058095e-05 loss: 0.1981 (0.2396) time: 3.3924 data: 0.0076 max mem: 33368 +Epoch: [0] [1220/1319] eta: 0:05:37 lr: 4.89573706506456e-05 loss: 0.1801 (0.2393) time: 3.3888 data: 0.0079 max mem: 33368 +Epoch: [0] [1230/1319] eta: 0:05:03 lr: 4.89488213848323e-05 loss: 0.1995 (0.2391) time: 3.3821 data: 0.0076 max mem: 33368 +Epoch: [0] [1240/1319] eta: 0:04:29 lr: 4.894027195310566e-05 loss: 0.1915 (0.2387) time: 3.3858 data: 0.0077 max mem: 33368 +Epoch: [0] [1250/1319] eta: 0:03:55 lr: 4.893172235543025e-05 loss: 0.1896 (0.2385) time: 3.3740 data: 0.0077 max mem: 33368 +Epoch: [0] [1260/1319] eta: 0:03:20 lr: 4.892317259177062e-05 loss: 0.2077 (0.2384) time: 3.3735 data: 0.0075 max mem: 33368 +Epoch: [0] [1270/1319] eta: 0:02:46 lr: 4.8914622662091334e-05 loss: 0.2064 (0.2381) time: 3.3695 data: 0.0076 max mem: 33368 +Epoch: [0] [1280/1319] eta: 0:02:12 lr: 4.890607256635692e-05 loss: 0.1982 (0.2378) time: 3.3651 data: 0.0082 max mem: 33368 +Epoch: [0] [1290/1319] eta: 0:01:38 lr: 4.8897522304531876e-05 loss: 0.1879 (0.2375) time: 3.3712 data: 0.0083 max mem: 33368 +Epoch: [0] [1300/1319] eta: 0:01:04 lr: 4.888897187658072e-05 loss: 0.2001 (0.2372) time: 3.3710 data: 0.0078 max mem: 33368 +Epoch: [0] [1310/1319] eta: 0:00:30 lr: 4.888042128246795e-05 loss: 0.2022 (0.2371) time: 3.3874 data: 0.0075 max mem: 33368 +Epoch: [0] Total time: 1:14:52 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 2:34:35 time: 3.6048 data: 3.3044 max mem: 33368 +Test: [ 100/2573] eta: 0:04:40 time: 0.0784 data: 0.0016 max mem: 33368 +Test: [ 200/2573] eta: 0:03:50 time: 0.0789 data: 0.0014 max mem: 33368 +Test: [ 300/2573] eta: 0:03:26 time: 0.0812 data: 0.0014 max mem: 33368 +Test: [ 400/2573] eta: 0:03:10 time: 0.0814 data: 0.0014 max mem: 33368 +Test: [ 500/2573] eta: 0:02:58 time: 0.0799 data: 0.0014 max mem: 33368 +Test: [ 600/2573] eta: 0:02:48 time: 0.0807 data: 0.0015 max mem: 33368 +Test: [ 700/2573] eta: 0:02:39 time: 0.0824 data: 0.0014 max mem: 33368 +Test: [ 800/2573] eta: 0:02:29 time: 0.0829 data: 0.0013 max mem: 33368 +Test: [ 900/2573] eta: 0:02:20 time: 0.0816 data: 0.0014 max mem: 33368 +Test: [1000/2573] eta: 0:02:11 time: 0.0804 data: 0.0013 max mem: 33368 +Test: [1100/2573] eta: 0:02:03 time: 0.0808 data: 0.0014 max mem: 33368 +Test: [1200/2573] eta: 0:01:54 time: 0.0804 data: 0.0013 max mem: 33368 +Test: [1300/2573] eta: 0:01:46 time: 0.0802 data: 0.0014 max mem: 33368 +Test: [1400/2573] eta: 0:01:37 time: 0.0796 data: 0.0014 max mem: 33368 +Test: [1500/2573] eta: 0:01:29 time: 0.0820 data: 0.0014 max mem: 33368 +Test: [1600/2573] eta: 0:01:20 time: 0.0833 data: 0.0014 max mem: 33368 +Test: [1700/2573] eta: 0:01:12 time: 0.0802 data: 0.0014 max mem: 33368 +Test: [1800/2573] eta: 0:01:03 time: 0.0822 data: 0.0014 max mem: 33368 +Test: [1900/2573] eta: 0:00:55 time: 0.0794 data: 0.0013 max mem: 33368 +Test: [2000/2573] eta: 0:00:47 time: 0.0814 data: 0.0015 max mem: 33368 +Test: [2100/2573] eta: 0:00:38 time: 0.0821 data: 0.0014 max mem: 33368 +Test: [2200/2573] eta: 0:00:30 time: 0.0824 data: 0.0014 max mem: 33368 +Test: [2300/2573] eta: 0:00:22 time: 0.0820 data: 0.0014 max mem: 33368 +Test: [2400/2573] eta: 0:00:14 time: 0.0792 data: 0.0014 max mem: 33368 +Test: [2500/2573] eta: 0:00:05 time: 0.0804 data: 0.0013 max mem: 33368 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: Total time: 0:03:31 +Final results: +Mean IoU is 29.27 + + precision@0.5 = 26.76 + precision@0.6 = 19.75 + precision@0.7 = 12.75 + precision@0.8 = 6.90 + precision@0.9 = 1.49 + overall IoU = 35.82 + +Average object IoU 29.27170928147743 +Overall IoU 35.82221221923828 +Better epoch: 0 + +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [1] [ 0/1319] eta: 1:57:17 lr: 4.8872725605668895e-05 loss: 0.1816 (0.1816) time: 5.3355 data: 1.8084 max mem: 33368 +Epoch: [1] [ 10/1319] eta: 1:17:55 lr: 4.886417469575114e-05 loss: 0.1926 (0.1977) time: 3.5714 data: 0.1717 max mem: 33368 +Epoch: [1] [ 20/1319] eta: 1:15:36 lr: 4.88556236195687e-05 loss: 0.1926 (0.1883) time: 3.4000 data: 0.0078 max mem: 33368 +Epoch: [1] [ 30/1319] eta: 1:14:09 lr: 4.884707237708599e-05 loss: 0.1947 (0.1911) time: 3.3856 data: 0.0079 max mem: 33368 +Epoch: [1] [ 40/1319] eta: 1:13:03 lr: 4.883852096826744e-05 loss: 0.1962 (0.1975) time: 3.3589 data: 0.0083 max mem: 33368 +Epoch: [1] [ 50/1319] eta: 1:12:20 lr: 4.882996939307746e-05 loss: 0.2022 (0.1979) time: 3.3722 data: 0.0081 max mem: 33368 +Epoch: [1] [ 60/1319] eta: 1:11:34 lr: 4.882141765148041e-05 loss: 0.1818 (0.1973) time: 3.3776 data: 0.0078 max mem: 33368 +Epoch: [1] [ 70/1319] eta: 1:10:56 lr: 4.881286574344069e-05 loss: 0.1741 (0.1926) time: 3.3764 data: 0.0077 max mem: 33368 +Epoch: [1] [ 80/1319] eta: 1:10:15 lr: 4.8804313668922646e-05 loss: 0.1562 (0.1925) time: 3.3778 data: 0.0077 max mem: 33368 +Epoch: [1] [ 90/1319] eta: 1:09:36 lr: 4.879576142789063e-05 loss: 0.1762 (0.1921) time: 3.3634 data: 0.0078 max mem: 33368 +Epoch: [1] [ 100/1319] eta: 1:09:05 lr: 4.878720902030896e-05 loss: 0.1792 (0.1927) time: 3.3933 data: 0.0079 max mem: 33368 +Epoch: [1] [ 110/1319] eta: 1:08:30 lr: 4.877865644614197e-05 loss: 0.1813 (0.1919) time: 3.4079 data: 0.0079 max mem: 33368 +Epoch: [1] [ 120/1319] eta: 1:07:53 lr: 4.877010370535394e-05 loss: 0.1832 (0.1932) time: 3.3804 data: 0.0078 max mem: 33368 +Epoch: [1] [ 130/1319] eta: 1:07:17 lr: 4.8761550797909164e-05 loss: 0.1972 (0.1926) time: 3.3711 data: 0.0080 max mem: 33368 +Epoch: [1] [ 140/1319] eta: 1:06:40 lr: 4.875299772377192e-05 loss: 0.1935 (0.1937) time: 3.3649 data: 0.0080 max mem: 33368 +Epoch: [1] [ 150/1319] eta: 1:06:09 lr: 4.874444448290645e-05 loss: 0.1917 (0.1938) time: 3.3949 data: 0.0078 max mem: 33368 +Epoch: [1] [ 160/1319] eta: 1:05:34 lr: 4.873589107527701e-05 loss: 0.1808 (0.1927) time: 3.4078 data: 0.0077 max mem: 33368 +Epoch: [1] [ 170/1319] eta: 1:04:59 lr: 4.872733750084782e-05 loss: 0.1860 (0.1933) time: 3.3790 data: 0.0080 max mem: 33368 +Epoch: [1] [ 180/1319] eta: 1:04:25 lr: 4.871878375958309e-05 loss: 0.2015 (0.1939) time: 3.3901 data: 0.0082 max mem: 33368 +Epoch: [1] [ 190/1319] eta: 1:03:51 lr: 4.871022985144703e-05 loss: 0.1884 (0.1933) time: 3.3923 data: 0.0077 max mem: 33368 +Epoch: [1] [ 200/1319] eta: 1:03:18 lr: 4.870167577640381e-05 loss: 0.1948 (0.1951) time: 3.3956 data: 0.0076 max mem: 33368 +Epoch: [1] [ 210/1319] eta: 1:02:43 lr: 4.869312153441761e-05 loss: 0.2047 (0.1959) time: 3.3915 data: 0.0080 max mem: 33368 +Epoch: [1] [ 220/1319] eta: 1:02:08 lr: 4.868456712545258e-05 loss: 0.1791 (0.1967) time: 3.3764 data: 0.0081 max mem: 33368 +Epoch: [1] [ 230/1319] eta: 1:01:34 lr: 4.8676012549472854e-05 loss: 0.1774 (0.1959) time: 3.3807 data: 0.0080 max mem: 33368 +Epoch: [1] [ 240/1319] eta: 1:00:58 lr: 4.866745780644256e-05 loss: 0.1751 (0.1950) time: 3.3688 data: 0.0079 max mem: 33368 +Epoch: [1] [ 250/1319] eta: 1:00:23 lr: 4.865890289632581e-05 loss: 0.1858 (0.1954) time: 3.3606 data: 0.0080 max mem: 33368 +Epoch: [1] [ 260/1319] eta: 0:59:48 lr: 4.8650347819086694e-05 loss: 0.1906 (0.1946) time: 3.3621 data: 0.0080 max mem: 33368 +Epoch: [1] [ 270/1319] eta: 0:59:14 lr: 4.864179257468931e-05 loss: 0.1628 (0.1945) time: 3.3756 data: 0.0081 max mem: 33368 +Epoch: [1] [ 280/1319] eta: 0:58:41 lr: 4.8633237163097687e-05 loss: 0.1746 (0.1949) time: 3.3970 data: 0.0079 max mem: 33368 +Epoch: [1] [ 290/1319] eta: 0:58:06 lr: 4.862468158427592e-05 loss: 0.1902 (0.1951) time: 3.3809 data: 0.0077 max mem: 33368 +Epoch: [1] [ 300/1319] eta: 0:57:31 lr: 4.861612583818801e-05 loss: 0.1808 (0.1959) time: 3.3618 data: 0.0077 max mem: 33368 +Epoch: [1] [ 310/1319] eta: 0:56:55 lr: 4.860756992479799e-05 loss: 0.1868 (0.1965) time: 3.3449 data: 0.0078 max mem: 33368 +Epoch: [1] [ 320/1319] eta: 0:56:22 lr: 4.859901384406988e-05 loss: 0.1868 (0.1964) time: 3.3620 data: 0.0077 max mem: 33368 +Epoch: [1] [ 330/1319] eta: 0:55:47 lr: 4.8590457595967656e-05 loss: 0.1920 (0.1967) time: 3.3700 data: 0.0077 max mem: 33368 +Epoch: [1] [ 340/1319] eta: 0:55:13 lr: 4.85819011804553e-05 loss: 0.1677 (0.1957) time: 3.3573 data: 0.0083 max mem: 33368 +Epoch: [1] [ 350/1319] eta: 0:54:38 lr: 4.8573344597496775e-05 loss: 0.1677 (0.1958) time: 3.3741 data: 0.0082 max mem: 33368 +Epoch: [1] [ 360/1319] eta: 0:54:05 lr: 4.856478784705602e-05 loss: 0.1928 (0.1958) time: 3.3795 data: 0.0080 max mem: 33368 +Epoch: [1] [ 370/1319] eta: 0:53:31 lr: 4.8556230929096985e-05 loss: 0.1928 (0.1960) time: 3.3813 data: 0.0082 max mem: 33368 +Epoch: [1] [ 380/1319] eta: 0:52:56 lr: 4.854767384358357e-05 loss: 0.1737 (0.1955) time: 3.3682 data: 0.0081 max mem: 33368 +Epoch: [1] [ 390/1319] eta: 0:52:23 lr: 4.8539116590479686e-05 loss: 0.1737 (0.1963) time: 3.3914 data: 0.0081 max mem: 33368 +Epoch: [1] [ 400/1319] eta: 0:51:49 lr: 4.8530559169749225e-05 loss: 0.1785 (0.1957) time: 3.3933 data: 0.0081 max mem: 33368 +Epoch: [1] [ 410/1319] eta: 0:51:15 lr: 4.852200158135605e-05 loss: 0.1785 (0.1955) time: 3.3739 data: 0.0079 max mem: 33368 +Epoch: [1] [ 420/1319] eta: 0:50:41 lr: 4.851344382526403e-05 loss: 0.1787 (0.1952) time: 3.3817 data: 0.0081 max mem: 33368 +Epoch: [1] [ 430/1319] eta: 0:50:07 lr: 4.850488590143701e-05 loss: 0.1853 (0.1957) time: 3.3749 data: 0.0081 max mem: 33368 +Epoch: [1] [ 440/1319] eta: 0:49:34 lr: 4.84963278098388e-05 loss: 0.1853 (0.1955) time: 3.4064 data: 0.0084 max mem: 33368 +Epoch: [1] [ 450/1319] eta: 0:49:01 lr: 4.8487769550433236e-05 loss: 0.1558 (0.1951) time: 3.4359 data: 0.0083 max mem: 33368 +Epoch: [1] [ 460/1319] eta: 0:48:29 lr: 4.84792111231841e-05 loss: 0.1509 (0.1943) time: 3.4340 data: 0.0080 max mem: 33368 +Epoch: [1] [ 470/1319] eta: 0:47:54 lr: 4.847065252805519e-05 loss: 0.1639 (0.1943) time: 3.3973 data: 0.0083 max mem: 33368 +Epoch: [1] [ 480/1319] eta: 0:47:20 lr: 4.846209376501027e-05 loss: 0.1884 (0.1942) time: 3.3591 data: 0.0084 max mem: 33368 +Epoch: [1] [ 490/1319] eta: 0:46:46 lr: 4.8453534834013074e-05 loss: 0.1884 (0.1944) time: 3.3800 data: 0.0079 max mem: 33368 +Epoch: [1] [ 500/1319] eta: 0:46:12 lr: 4.844497573502737e-05 loss: 0.1847 (0.1944) time: 3.3769 data: 0.0081 max mem: 33368 +Epoch: [1] [ 510/1319] eta: 0:45:39 lr: 4.8436416468016874e-05 loss: 0.1803 (0.1946) time: 3.3909 data: 0.0082 max mem: 33368 +Epoch: [1] [ 520/1319] eta: 0:45:06 lr: 4.8427857032945285e-05 loss: 0.1803 (0.1944) time: 3.4291 data: 0.0082 max mem: 33368 +Epoch: [1] [ 530/1319] eta: 0:44:32 lr: 4.841929742977631e-05 loss: 0.1758 (0.1941) time: 3.4078 data: 0.0085 max mem: 33368 +Epoch: [1] [ 540/1319] eta: 0:43:58 lr: 4.841073765847362e-05 loss: 0.1918 (0.1945) time: 3.4046 data: 0.0084 max mem: 33368 +Epoch: [1] [ 550/1319] eta: 0:43:25 lr: 4.840217771900089e-05 loss: 0.1991 (0.1943) time: 3.4203 data: 0.0081 max mem: 33368 +Epoch: [1] [ 560/1319] eta: 0:42:51 lr: 4.8393617611321754e-05 loss: 0.1793 (0.1944) time: 3.4098 data: 0.0080 max mem: 33368 +Epoch: [1] [ 570/1319] eta: 0:42:17 lr: 4.838505733539985e-05 loss: 0.1811 (0.1946) time: 3.3981 data: 0.0080 max mem: 33368 +Epoch: [1] [ 580/1319] eta: 0:41:44 lr: 4.83764968911988e-05 loss: 0.1721 (0.1942) time: 3.4000 data: 0.0079 max mem: 33368 +Epoch: [1] [ 590/1319] eta: 0:41:10 lr: 4.836793627868222e-05 loss: 0.1707 (0.1942) time: 3.3967 data: 0.0080 max mem: 33368 +Epoch: [1] [ 600/1319] eta: 0:40:35 lr: 4.835937549781368e-05 loss: 0.1963 (0.1942) time: 3.3653 data: 0.0084 max mem: 33368 +Epoch: [1] [ 610/1319] eta: 0:40:01 lr: 4.835081454855677e-05 loss: 0.1754 (0.1938) time: 3.3377 data: 0.0089 max mem: 33368 +Epoch: [1] [ 620/1319] eta: 0:39:28 lr: 4.8342253430875026e-05 loss: 0.1652 (0.1936) time: 3.3884 data: 0.0092 max mem: 33368 +Epoch: [1] [ 630/1319] eta: 0:38:54 lr: 4.833369214473202e-05 loss: 0.1615 (0.1935) time: 3.4260 data: 0.0087 max mem: 33368 +Epoch: [1] [ 640/1319] eta: 0:38:20 lr: 4.832513069009127e-05 loss: 0.1567 (0.1930) time: 3.4057 data: 0.0084 max mem: 33368 +Epoch: [1] [ 650/1319] eta: 0:37:47 lr: 4.8316569066916287e-05 loss: 0.1671 (0.1934) time: 3.4056 data: 0.0086 max mem: 33368 +Epoch: [1] [ 660/1319] eta: 0:37:12 lr: 4.8308007275170564e-05 loss: 0.1781 (0.1932) time: 3.3818 data: 0.0085 max mem: 33368 +Epoch: [1] [ 670/1319] eta: 0:36:39 lr: 4.829944531481759e-05 loss: 0.1711 (0.1929) time: 3.3753 data: 0.0083 max mem: 33368 +Epoch: [1] [ 680/1319] eta: 0:36:04 lr: 4.8290883185820843e-05 loss: 0.1683 (0.1927) time: 3.3690 data: 0.0084 max mem: 33368 +Epoch: [1] [ 690/1319] eta: 0:35:30 lr: 4.828232088814377e-05 loss: 0.1735 (0.1928) time: 3.3649 data: 0.0081 max mem: 33368 +Epoch: [1] [ 700/1319] eta: 0:34:56 lr: 4.827375842174981e-05 loss: 0.1609 (0.1924) time: 3.3875 data: 0.0078 max mem: 33368 +Epoch: [1] [ 710/1319] eta: 0:34:23 lr: 4.826519578660238e-05 loss: 0.1702 (0.1924) time: 3.3974 data: 0.0081 max mem: 33368 +Epoch: [1] [ 720/1319] eta: 0:33:49 lr: 4.825663298266489e-05 loss: 0.1839 (0.1923) time: 3.3841 data: 0.0082 max mem: 33368 +Epoch: [1] [ 730/1319] eta: 0:33:15 lr: 4.824807000990074e-05 loss: 0.1665 (0.1921) time: 3.3896 data: 0.0079 max mem: 33368 +Epoch: [1] [ 740/1319] eta: 0:32:41 lr: 4.82395068682733e-05 loss: 0.1617 (0.1922) time: 3.3904 data: 0.0088 max mem: 33368 +Epoch: [1] [ 750/1319] eta: 0:32:07 lr: 4.823094355774595e-05 loss: 0.1871 (0.1923) time: 3.4036 data: 0.0088 max mem: 33368 +Epoch: [1] [ 760/1319] eta: 0:31:33 lr: 4.822238007828201e-05 loss: 0.1847 (0.1922) time: 3.4060 data: 0.0080 max mem: 33368 +Epoch: [1] [ 770/1319] eta: 0:30:59 lr: 4.8213816429844826e-05 loss: 0.1813 (0.1922) time: 3.3651 data: 0.0085 max mem: 33368 +Epoch: [1] [ 780/1319] eta: 0:30:26 lr: 4.8205252612397726e-05 loss: 0.1640 (0.1918) time: 3.3888 data: 0.0083 max mem: 33368 +Epoch: [1] [ 790/1319] eta: 0:29:52 lr: 4.8196688625903984e-05 loss: 0.1592 (0.1919) time: 3.3823 data: 0.0078 max mem: 33368 +Epoch: [1] [ 800/1319] eta: 0:29:18 lr: 4.8188124470326915e-05 loss: 0.1668 (0.1917) time: 3.3799 data: 0.0078 max mem: 33368 +Epoch: [1] [ 810/1319] eta: 0:28:44 lr: 4.8179560145629784e-05 loss: 0.1815 (0.1919) time: 3.3904 data: 0.0084 max mem: 33368 +Epoch: [1] [ 820/1319] eta: 0:28:10 lr: 4.817099565177583e-05 loss: 0.1862 (0.1920) time: 3.3717 data: 0.0089 max mem: 33368 +Epoch: [1] [ 830/1319] eta: 0:27:36 lr: 4.8162430988728305e-05 loss: 0.1802 (0.1920) time: 3.3720 data: 0.0085 max mem: 33368 +Epoch: [1] [ 840/1319] eta: 0:27:02 lr: 4.815386615645044e-05 loss: 0.1749 (0.1917) time: 3.3645 data: 0.0083 max mem: 33368 +Epoch: [1] [ 850/1319] eta: 0:26:28 lr: 4.814530115490545e-05 loss: 0.1749 (0.1917) time: 3.3639 data: 0.0082 max mem: 33368 +Epoch: [1] [ 860/1319] eta: 0:25:54 lr: 4.813673598405651e-05 loss: 0.1829 (0.1916) time: 3.3595 data: 0.0080 max mem: 33368 +Epoch: [1] [ 870/1319] eta: 0:25:20 lr: 4.812817064386682e-05 loss: 0.1748 (0.1916) time: 3.3792 data: 0.0082 max mem: 33368 +Epoch: [1] [ 880/1319] eta: 0:24:46 lr: 4.8119605134299526e-05 loss: 0.1749 (0.1915) time: 3.3972 data: 0.0080 max mem: 33368 +Epoch: [1] [ 890/1319] eta: 0:24:12 lr: 4.81110394553178e-05 loss: 0.1733 (0.1912) time: 3.3791 data: 0.0080 max mem: 33368 +Epoch: [1] [ 900/1319] eta: 0:23:38 lr: 4.810247360688475e-05 loss: 0.1665 (0.1910) time: 3.3752 data: 0.0078 max mem: 33368 +Epoch: [1] [ 910/1319] eta: 0:23:04 lr: 4.809390758896352e-05 loss: 0.1561 (0.1907) time: 3.3622 data: 0.0076 max mem: 33368 +Epoch: [1] [ 920/1319] eta: 0:22:30 lr: 4.808534140151719e-05 loss: 0.1701 (0.1909) time: 3.3454 data: 0.0077 max mem: 33368 +Epoch: [1] [ 930/1319] eta: 0:21:57 lr: 4.807677504450886e-05 loss: 0.1701 (0.1907) time: 3.3847 data: 0.0077 max mem: 33368 +Epoch: [1] [ 940/1319] eta: 0:21:23 lr: 4.806820851790161e-05 loss: 0.1603 (0.1907) time: 3.3973 data: 0.0081 max mem: 33368 +Epoch: [1] [ 950/1319] eta: 0:20:49 lr: 4.805964182165848e-05 loss: 0.1747 (0.1906) time: 3.3861 data: 0.0079 max mem: 33368 +Epoch: [1] [ 960/1319] eta: 0:20:15 lr: 4.8051074955742525e-05 loss: 0.1756 (0.1904) time: 3.3882 data: 0.0082 max mem: 33368 +Epoch: [1] [ 970/1319] eta: 0:19:41 lr: 4.804250792011677e-05 loss: 0.1869 (0.1905) time: 3.3858 data: 0.0086 max mem: 33368 +Epoch: [1] [ 980/1319] eta: 0:19:07 lr: 4.803394071474422e-05 loss: 0.1940 (0.1907) time: 3.3793 data: 0.0083 max mem: 33368 +Epoch: [1] [ 990/1319] eta: 0:18:33 lr: 4.802537333958788e-05 loss: 0.1919 (0.1906) time: 3.3783 data: 0.0081 max mem: 33368 +Epoch: [1] [1000/1319] eta: 0:18:00 lr: 4.801680579461071e-05 loss: 0.2046 (0.1908) time: 3.4031 data: 0.0079 max mem: 33368 +Epoch: [1] [1010/1319] eta: 0:17:26 lr: 4.80082380797757e-05 loss: 0.2046 (0.1909) time: 3.4206 data: 0.0078 max mem: 33368 +Epoch: [1] [1020/1319] eta: 0:16:52 lr: 4.79996701950458e-05 loss: 0.2183 (0.1913) time: 3.4250 data: 0.0078 max mem: 33368 +Epoch: [1] [1030/1319] eta: 0:16:18 lr: 4.799110214038392e-05 loss: 0.2183 (0.1913) time: 3.4197 data: 0.0078 max mem: 33368 +Epoch: [1] [1040/1319] eta: 0:15:45 lr: 4.7982533915752995e-05 loss: 0.2010 (0.1915) time: 3.4095 data: 0.0080 max mem: 33368 +Epoch: [1] [1050/1319] eta: 0:15:11 lr: 4.797396552111593e-05 loss: 0.1840 (0.1914) time: 3.4066 data: 0.0081 max mem: 33368 +Epoch: [1] [1060/1319] eta: 0:14:37 lr: 4.7965396956435596e-05 loss: 0.1614 (0.1912) time: 3.4017 data: 0.0080 max mem: 33368 +Epoch: [1] [1070/1319] eta: 0:14:03 lr: 4.795682822167489e-05 loss: 0.1890 (0.1913) time: 3.3976 data: 0.0081 max mem: 33368 +Epoch: [1] [1080/1319] eta: 0:13:29 lr: 4.794825931679665e-05 loss: 0.2029 (0.1915) time: 3.3724 data: 0.0081 max mem: 33368 +Epoch: [1] [1090/1319] eta: 0:12:55 lr: 4.7939690241763725e-05 loss: 0.1763 (0.1913) time: 3.3591 data: 0.0083 max mem: 33368 +Epoch: [1] [1100/1319] eta: 0:12:21 lr: 4.793112099653894e-05 loss: 0.1609 (0.1912) time: 3.3734 data: 0.0085 max mem: 33368 +Epoch: [1] [1110/1319] eta: 0:11:47 lr: 4.79225515810851e-05 loss: 0.1609 (0.1913) time: 3.3643 data: 0.0081 max mem: 33368 +Epoch: [1] [1120/1319] eta: 0:11:13 lr: 4.791398199536501e-05 loss: 0.1852 (0.1916) time: 3.3588 data: 0.0079 max mem: 33368 +Epoch: [1] [1130/1319] eta: 0:10:40 lr: 4.790541223934144e-05 loss: 0.1949 (0.1916) time: 3.3821 data: 0.0081 max mem: 33368 +Epoch: [1] [1140/1319] eta: 0:10:06 lr: 4.7896842312977156e-05 loss: 0.1987 (0.1918) time: 3.3922 data: 0.0082 max mem: 33368 +Epoch: [1] [1150/1319] eta: 0:09:32 lr: 4.788827221623491e-05 loss: 0.1881 (0.1916) time: 3.3843 data: 0.0078 max mem: 33368 +Epoch: [1] [1160/1319] eta: 0:08:58 lr: 4.787970194907743e-05 loss: 0.1785 (0.1916) time: 3.3784 data: 0.0078 max mem: 33368 +Epoch: [1] [1170/1319] eta: 0:08:24 lr: 4.787113151146744e-05 loss: 0.1785 (0.1914) time: 3.3635 data: 0.0083 max mem: 33368 +Epoch: [1] [1180/1319] eta: 0:07:50 lr: 4.786256090336764e-05 loss: 0.1844 (0.1915) time: 3.3897 data: 0.0083 max mem: 33368 +Epoch: [1] [1190/1319] eta: 0:07:16 lr: 4.7853990124740705e-05 loss: 0.1758 (0.1912) time: 3.4138 data: 0.0081 max mem: 33368 +Epoch: [1] [1200/1319] eta: 0:06:43 lr: 4.784541917554932e-05 loss: 0.1739 (0.1911) time: 3.3979 data: 0.0083 max mem: 33368 +Epoch: [1] [1210/1319] eta: 0:06:09 lr: 4.783684805575612e-05 loss: 0.1739 (0.1911) time: 3.3804 data: 0.0082 max mem: 33368 +Epoch: [1] [1220/1319] eta: 0:05:35 lr: 4.782827676532376e-05 loss: 0.1635 (0.1910) time: 3.3562 data: 0.0078 max mem: 33368 +Epoch: [1] [1230/1319] eta: 0:05:01 lr: 4.781970530421487e-05 loss: 0.1658 (0.1910) time: 3.3796 data: 0.0079 max mem: 33368 +Epoch: [1] [1240/1319] eta: 0:04:27 lr: 4.7811133672392044e-05 loss: 0.1631 (0.1907) time: 3.4135 data: 0.0086 max mem: 33368 +Epoch: [1] [1250/1319] eta: 0:03:53 lr: 4.780256186981787e-05 loss: 0.1546 (0.1905) time: 3.3897 data: 0.0082 max mem: 33368 +Epoch: [1] [1260/1319] eta: 0:03:19 lr: 4.779398989645494e-05 loss: 0.1823 (0.1905) time: 3.3556 data: 0.0077 max mem: 33368 +Epoch: [1] [1270/1319] eta: 0:02:45 lr: 4.778541775226581e-05 loss: 0.1751 (0.1905) time: 3.3576 data: 0.0083 max mem: 33368 +Epoch: [1] [1280/1319] eta: 0:02:12 lr: 4.777684543721302e-05 loss: 0.1745 (0.1903) time: 3.3883 data: 0.0082 max mem: 33368 +Epoch: [1] [1290/1319] eta: 0:01:38 lr: 4.776827295125911e-05 loss: 0.1745 (0.1902) time: 3.3862 data: 0.0082 max mem: 33368 +Epoch: [1] [1300/1319] eta: 0:01:04 lr: 4.775970029436657e-05 loss: 0.1451 (0.1900) time: 3.3652 data: 0.0079 max mem: 33368 +Epoch: [1] [1310/1319] eta: 0:00:30 lr: 4.7751127466497925e-05 loss: 0.1704 (0.1899) time: 3.3924 data: 0.0075 max mem: 33368 +Epoch: [1] Total time: 1:14:27 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 3:15:17 time: 4.5539 data: 4.4421 max mem: 33368 +Test: [ 100/2573] eta: 0:05:00 time: 0.0766 data: 0.0013 max mem: 33368 +Test: [ 200/2573] eta: 0:03:58 time: 0.0797 data: 0.0015 max mem: 33368 +Test: [ 300/2573] eta: 0:03:31 time: 0.0814 data: 0.0014 max mem: 33368 +Test: [ 400/2573] eta: 0:03:15 time: 0.0811 data: 0.0015 max mem: 33368 +Test: [ 500/2573] eta: 0:03:01 time: 0.0795 data: 0.0014 max mem: 33368 +Test: [ 600/2573] eta: 0:02:50 time: 0.0796 data: 0.0014 max mem: 33368 +Test: [ 700/2573] eta: 0:02:40 time: 0.0808 data: 0.0016 max mem: 33368 +Test: [ 800/2573] eta: 0:02:31 time: 0.0836 data: 0.0014 max mem: 33368 +Test: [ 900/2573] eta: 0:02:22 time: 0.0810 data: 0.0015 max mem: 33368 +Test: [1000/2573] eta: 0:02:12 time: 0.0800 data: 0.0014 max mem: 33368 +Test: [1100/2573] eta: 0:02:03 time: 0.0797 data: 0.0013 max mem: 33368 +Test: [1200/2573] eta: 0:01:55 time: 0.0800 data: 0.0013 max mem: 33368 +Test: [1300/2573] eta: 0:01:46 time: 0.0802 data: 0.0013 max mem: 33368 +Test: [1400/2573] eta: 0:01:37 time: 0.0790 data: 0.0013 max mem: 33368 +Test: [1500/2573] eta: 0:01:29 time: 0.0811 data: 0.0015 max mem: 33368 +Test: [1600/2573] eta: 0:01:20 time: 0.0838 data: 0.0014 max mem: 33368 +Test: [1700/2573] eta: 0:01:12 time: 0.0793 data: 0.0014 max mem: 33368 +Test: [1800/2573] eta: 0:01:03 time: 0.0821 data: 0.0015 max mem: 33368 +Test: [1900/2573] eta: 0:00:55 time: 0.0784 data: 0.0014 max mem: 33368 +Test: [2000/2573] eta: 0:00:47 time: 0.0794 data: 0.0014 max mem: 33368 +Test: [2100/2573] eta: 0:00:38 time: 0.0818 data: 0.0014 max mem: 33368 +Test: [2200/2573] eta: 0:00:30 time: 0.0818 data: 0.0014 max mem: 33368 +Test: [2300/2573] eta: 0:00:22 time: 0.0817 data: 0.0014 max mem: 33368 +Test: [2400/2573] eta: 0:00:14 time: 0.0776 data: 0.0015 max mem: 33368 +Test: [2500/2573] eta: 0:00:05 time: 0.0805 data: 0.0015 max mem: 33368 +Test: Total time: 0:03:31 +Final results: +Mean IoU is 39.89 + + precision@0.5 = 38.56 + precision@0.6 = 29.58 + precision@0.7 = 20.63 + precision@0.8 = 12.54 + precision@0.9 = 3.68 + overall IoU = 42.83 + +Average object IoU 39.890024274241775 +Overall IoU 42.83464050292969 +Better epoch: 1 + +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [2] [ 0/1319] eta: 2:01:10 lr: 4.774341177520056e-05 loss: 0.1084 (0.1084) time: 5.5123 data: 1.9080 max mem: 33368 +Epoch: [2] [ 10/1319] eta: 1:17:46 lr: 4.773483862237391e-05 loss: 0.1674 (0.1756) time: 3.5649 data: 0.1802 max mem: 33368 +Epoch: [2] [ 20/1319] eta: 1:15:13 lr: 4.772626529846231e-05 loss: 0.1677 (0.1742) time: 3.3730 data: 0.0076 max mem: 33368 +Epoch: [2] [ 30/1319] eta: 1:14:01 lr: 4.771769180342819e-05 loss: 0.1552 (0.1726) time: 3.3801 data: 0.0078 max mem: 33368 +Epoch: [2] [ 40/1319] eta: 1:12:59 lr: 4.7709118137233964e-05 loss: 0.1538 (0.1689) time: 3.3717 data: 0.0076 max mem: 33368 +Epoch: [2] [ 50/1319] eta: 1:12:16 lr: 4.770054429984204e-05 loss: 0.1538 (0.1677) time: 3.3724 data: 0.0080 max mem: 33368 +Epoch: [2] [ 60/1319] eta: 1:11:30 lr: 4.769197029121481e-05 loss: 0.1650 (0.1690) time: 3.3729 data: 0.0081 max mem: 33368 +Epoch: [2] [ 70/1319] eta: 1:10:51 lr: 4.7683396111314645e-05 loss: 0.1840 (0.1760) time: 3.3719 data: 0.0077 max mem: 33368 +Epoch: [2] [ 80/1319] eta: 1:10:13 lr: 4.7674821760103904e-05 loss: 0.1696 (0.1735) time: 3.3799 data: 0.0079 max mem: 33368 +Epoch: [2] [ 90/1319] eta: 1:09:36 lr: 4.766624723754494e-05 loss: 0.1460 (0.1710) time: 3.3783 data: 0.0082 max mem: 33368 +Epoch: [2] [ 100/1319] eta: 1:09:01 lr: 4.7657672543600056e-05 loss: 0.1776 (0.1718) time: 3.3839 data: 0.0083 max mem: 33368 +Epoch: [2] [ 110/1319] eta: 1:08:31 lr: 4.764909767823158e-05 loss: 0.1780 (0.1713) time: 3.4087 data: 0.0081 max mem: 33369 +Epoch: [2] [ 120/1319] eta: 1:07:57 lr: 4.76405226414018e-05 loss: 0.1622 (0.1710) time: 3.4165 data: 0.0079 max mem: 33369 +Epoch: [2] [ 130/1319] eta: 1:07:23 lr: 4.7631947433073e-05 loss: 0.1622 (0.1696) time: 3.4055 data: 0.0080 max mem: 33369 +Epoch: [2] [ 140/1319] eta: 1:06:50 lr: 4.762337205320744e-05 loss: 0.1613 (0.1688) time: 3.4091 data: 0.0081 max mem: 33369 +Epoch: [2] [ 150/1319] eta: 1:06:14 lr: 4.7614796501767376e-05 loss: 0.1692 (0.1687) time: 3.3901 data: 0.0081 max mem: 33369 +Epoch: [2] [ 160/1319] eta: 1:05:40 lr: 4.760622077871502e-05 loss: 0.1724 (0.1689) time: 3.3848 data: 0.0080 max mem: 33369 +Epoch: [2] [ 170/1319] eta: 1:05:04 lr: 4.75976448840126e-05 loss: 0.1570 (0.1683) time: 3.3902 data: 0.0080 max mem: 33369 +Epoch: [2] [ 180/1319] eta: 1:04:30 lr: 4.7589068817622304e-05 loss: 0.1542 (0.1672) time: 3.3844 data: 0.0078 max mem: 33369 +Epoch: [2] [ 190/1319] eta: 1:03:55 lr: 4.758049257950633e-05 loss: 0.1620 (0.1685) time: 3.3828 data: 0.0080 max mem: 33369 +Epoch: [2] [ 200/1319] eta: 1:03:18 lr: 4.757191616962685e-05 loss: 0.1662 (0.1688) time: 3.3593 data: 0.0081 max mem: 33369 +Epoch: [2] [ 210/1319] eta: 1:02:43 lr: 4.756333958794601e-05 loss: 0.1616 (0.1684) time: 3.3650 data: 0.0078 max mem: 33369 +Epoch: [2] [ 220/1319] eta: 1:02:08 lr: 4.7554762834425936e-05 loss: 0.1523 (0.1682) time: 3.3732 data: 0.0079 max mem: 33369 +Epoch: [2] [ 230/1319] eta: 1:01:34 lr: 4.7546185909028754e-05 loss: 0.1783 (0.1702) time: 3.3745 data: 0.0076 max mem: 33369 +Epoch: [2] [ 240/1319] eta: 1:01:01 lr: 4.753760881171657e-05 loss: 0.1722 (0.1698) time: 3.4068 data: 0.0075 max mem: 33369 +Epoch: [2] [ 250/1319] eta: 1:00:27 lr: 4.7529031542451477e-05 loss: 0.1667 (0.1710) time: 3.4086 data: 0.0077 max mem: 33369 +Epoch: [2] [ 260/1319] eta: 0:59:54 lr: 4.7520454101195535e-05 loss: 0.1653 (0.1714) time: 3.4062 data: 0.0076 max mem: 33369 +Epoch: [2] [ 270/1319] eta: 0:59:22 lr: 4.751187648791081e-05 loss: 0.1653 (0.1711) time: 3.4311 data: 0.0077 max mem: 33369 +Epoch: [2] [ 280/1319] eta: 0:58:47 lr: 4.7503298702559326e-05 loss: 0.1644 (0.1707) time: 3.4042 data: 0.0079 max mem: 33369 +Epoch: [2] [ 290/1319] eta: 0:58:12 lr: 4.7494720745103136e-05 loss: 0.1644 (0.1712) time: 3.3622 data: 0.0083 max mem: 33369 +Epoch: [2] [ 300/1319] eta: 0:57:38 lr: 4.748614261550422e-05 loss: 0.1523 (0.1706) time: 3.3820 data: 0.0082 max mem: 33369 +Epoch: [2] [ 310/1319] eta: 0:57:05 lr: 4.7477564313724594e-05 loss: 0.1523 (0.1704) time: 3.4020 data: 0.0078 max mem: 33369 +Epoch: [2] [ 320/1319] eta: 0:56:30 lr: 4.746898583972622e-05 loss: 0.1692 (0.1721) time: 3.3866 data: 0.0078 max mem: 33369 +Epoch: [2] [ 330/1319] eta: 0:55:56 lr: 4.746040719347105e-05 loss: 0.1711 (0.1719) time: 3.3886 data: 0.0079 max mem: 33369 +Epoch: [2] [ 340/1319] eta: 0:55:22 lr: 4.745182837492104e-05 loss: 0.1711 (0.1721) time: 3.3945 data: 0.0080 max mem: 33369 +Epoch: [2] [ 350/1319] eta: 0:54:48 lr: 4.744324938403812e-05 loss: 0.1741 (0.1723) time: 3.3942 data: 0.0079 max mem: 33369 +Epoch: [2] [ 360/1319] eta: 0:54:14 lr: 4.7434670220784206e-05 loss: 0.1680 (0.1718) time: 3.3931 data: 0.0076 max mem: 33369 +Epoch: [2] [ 370/1319] eta: 0:53:39 lr: 4.7426090885121175e-05 loss: 0.1535 (0.1714) time: 3.3708 data: 0.0076 max mem: 33369 +Epoch: [2] [ 380/1319] eta: 0:53:06 lr: 4.741751137701092e-05 loss: 0.1710 (0.1718) time: 3.3814 data: 0.0077 max mem: 33369 +Epoch: [2] [ 390/1319] eta: 0:52:31 lr: 4.74089316964153e-05 loss: 0.1948 (0.1728) time: 3.3909 data: 0.0079 max mem: 33369 +Epoch: [2] [ 400/1319] eta: 0:51:57 lr: 4.740035184329618e-05 loss: 0.1675 (0.1728) time: 3.3769 data: 0.0079 max mem: 33369 +Epoch: [2] [ 410/1319] eta: 0:51:22 lr: 4.739177181761536e-05 loss: 0.1666 (0.1725) time: 3.3678 data: 0.0079 max mem: 33369 +Epoch: [2] [ 420/1319] eta: 0:50:48 lr: 4.738319161933468e-05 loss: 0.1606 (0.1723) time: 3.3584 data: 0.0082 max mem: 33369 +Epoch: [2] [ 430/1319] eta: 0:50:14 lr: 4.737461124841593e-05 loss: 0.1499 (0.1719) time: 3.3820 data: 0.0080 max mem: 33369 +Epoch: [2] [ 440/1319] eta: 0:49:39 lr: 4.736603070482089e-05 loss: 0.1442 (0.1713) time: 3.3635 data: 0.0076 max mem: 33369 +Epoch: [2] [ 450/1319] eta: 0:49:04 lr: 4.735744998851133e-05 loss: 0.1413 (0.1707) time: 3.3194 data: 0.0075 max mem: 33369 +Epoch: [2] [ 460/1319] eta: 0:48:30 lr: 4.734886909944901e-05 loss: 0.1534 (0.1711) time: 3.3513 data: 0.0075 max mem: 33369 +Epoch: [2] [ 470/1319] eta: 0:47:56 lr: 4.734028803759565e-05 loss: 0.1842 (0.1708) time: 3.3811 data: 0.0079 max mem: 33369 +Epoch: [2] [ 480/1319] eta: 0:47:21 lr: 4.733170680291298e-05 loss: 0.1537 (0.1704) time: 3.3743 data: 0.0081 max mem: 33369 +Epoch: [2] [ 490/1319] eta: 0:46:47 lr: 4.7323125395362694e-05 loss: 0.1464 (0.1698) time: 3.3663 data: 0.0078 max mem: 33369 +Epoch: [2] [ 500/1319] eta: 0:46:13 lr: 4.731454381490648e-05 loss: 0.1551 (0.1702) time: 3.3607 data: 0.0079 max mem: 33369 +Epoch: [2] [ 510/1319] eta: 0:45:39 lr: 4.730596206150601e-05 loss: 0.1490 (0.1697) time: 3.3704 data: 0.0079 max mem: 33369 +Epoch: [2] [ 520/1319] eta: 0:45:05 lr: 4.729738013512294e-05 loss: 0.1310 (0.1694) time: 3.3785 data: 0.0076 max mem: 33369 +Epoch: [2] [ 530/1319] eta: 0:44:30 lr: 4.72887980357189e-05 loss: 0.1568 (0.1698) time: 3.3559 data: 0.0082 max mem: 33369 +Epoch: [2] [ 540/1319] eta: 0:43:56 lr: 4.7280215763255517e-05 loss: 0.1570 (0.1698) time: 3.3431 data: 0.0084 max mem: 33369 +Epoch: [2] [ 550/1319] eta: 0:43:22 lr: 4.7271633317694384e-05 loss: 0.1551 (0.1696) time: 3.3754 data: 0.0081 max mem: 33369 +Epoch: [2] [ 560/1319] eta: 0:42:48 lr: 4.726305069899711e-05 loss: 0.1723 (0.1701) time: 3.3808 data: 0.0082 max mem: 33369 +Epoch: [2] [ 570/1319] eta: 0:42:14 lr: 4.725446790712525e-05 loss: 0.1751 (0.1703) time: 3.3685 data: 0.0079 max mem: 33369 +Epoch: [2] [ 580/1319] eta: 0:41:40 lr: 4.7245884942040375e-05 loss: 0.1737 (0.1703) time: 3.3620 data: 0.0078 max mem: 33369 +Epoch: [2] [ 590/1319] eta: 0:41:05 lr: 4.7237301803704005e-05 loss: 0.1607 (0.1704) time: 3.3390 data: 0.0077 max mem: 33369 +Epoch: [2] [ 600/1319] eta: 0:40:31 lr: 4.722871849207768e-05 loss: 0.1591 (0.1701) time: 3.3434 data: 0.0081 max mem: 33369 +Epoch: [2] [ 610/1319] eta: 0:39:57 lr: 4.72201350071229e-05 loss: 0.1592 (0.1701) time: 3.3596 data: 0.0082 max mem: 33369 +Epoch: [2] [ 620/1319] eta: 0:39:24 lr: 4.7211551348801154e-05 loss: 0.1607 (0.1700) time: 3.3796 data: 0.0076 max mem: 33369 +Epoch: [2] [ 630/1319] eta: 0:38:49 lr: 4.7202967517073924e-05 loss: 0.1591 (0.1704) time: 3.3728 data: 0.0074 max mem: 33369 +Epoch: [2] [ 640/1319] eta: 0:38:16 lr: 4.719438351190267e-05 loss: 0.1503 (0.1703) time: 3.3780 data: 0.0074 max mem: 33369 +Epoch: [2] [ 650/1319] eta: 0:37:42 lr: 4.718579933324881e-05 loss: 0.1503 (0.1702) time: 3.3910 data: 0.0076 max mem: 33369 +Epoch: [2] [ 660/1319] eta: 0:37:08 lr: 4.71772149810738e-05 loss: 0.1571 (0.1702) time: 3.3716 data: 0.0080 max mem: 33369 +Epoch: [2] [ 670/1319] eta: 0:36:34 lr: 4.716863045533903e-05 loss: 0.1591 (0.1704) time: 3.3721 data: 0.0079 max mem: 33369 +Epoch: [2] [ 680/1319] eta: 0:36:01 lr: 4.71600457560059e-05 loss: 0.1672 (0.1703) time: 3.4036 data: 0.0075 max mem: 33369 +Epoch: [2] [ 690/1319] eta: 0:35:27 lr: 4.7151460883035786e-05 loss: 0.1727 (0.1709) time: 3.4135 data: 0.0078 max mem: 33369 +Epoch: [2] [ 700/1319] eta: 0:34:54 lr: 4.714287583639004e-05 loss: 0.1492 (0.1705) time: 3.4282 data: 0.0080 max mem: 33369 +Epoch: [2] [ 710/1319] eta: 0:34:20 lr: 4.713429061603002e-05 loss: 0.1492 (0.1706) time: 3.4354 data: 0.0078 max mem: 33369 +Epoch: [2] [ 720/1319] eta: 0:33:47 lr: 4.712570522191704e-05 loss: 0.1685 (0.1705) time: 3.4090 data: 0.0082 max mem: 33369 +Epoch: [2] [ 730/1319] eta: 0:33:13 lr: 4.7117119654012416e-05 loss: 0.1595 (0.1702) time: 3.3907 data: 0.0081 max mem: 33369 +Epoch: [2] [ 740/1319] eta: 0:32:39 lr: 4.7108533912277444e-05 loss: 0.1595 (0.1701) time: 3.3826 data: 0.0079 max mem: 33369 +Epoch: [2] [ 750/1319] eta: 0:32:05 lr: 4.709994799667339e-05 loss: 0.1733 (0.1705) time: 3.3943 data: 0.0082 max mem: 33369 +Epoch: [2] [ 760/1319] eta: 0:31:31 lr: 4.709136190716153e-05 loss: 0.1724 (0.1703) time: 3.3978 data: 0.0084 max mem: 33369 +Epoch: [2] [ 770/1319] eta: 0:30:58 lr: 4.708277564370309e-05 loss: 0.1542 (0.1702) time: 3.4044 data: 0.0085 max mem: 33369 +Epoch: [2] [ 780/1319] eta: 0:30:24 lr: 4.707418920625932e-05 loss: 0.1545 (0.1701) time: 3.4103 data: 0.0080 max mem: 33369 +Epoch: [2] [ 790/1319] eta: 0:29:50 lr: 4.706560259479142e-05 loss: 0.1623 (0.1701) time: 3.3927 data: 0.0076 max mem: 33369 +Epoch: [2] [ 800/1319] eta: 0:29:17 lr: 4.705701580926059e-05 loss: 0.1691 (0.1706) time: 3.4084 data: 0.0074 max mem: 33369 +Epoch: [2] [ 810/1319] eta: 0:28:43 lr: 4.7048428849628004e-05 loss: 0.1859 (0.1709) time: 3.4046 data: 0.0076 max mem: 33369 +Epoch: [2] [ 820/1319] eta: 0:28:09 lr: 4.703984171585482e-05 loss: 0.1698 (0.1707) time: 3.3831 data: 0.0078 max mem: 33369 +Epoch: [2] [ 830/1319] eta: 0:27:35 lr: 4.703125440790219e-05 loss: 0.1456 (0.1707) time: 3.3906 data: 0.0078 max mem: 33369 +Epoch: [2] [ 840/1319] eta: 0:27:02 lr: 4.702266692573125e-05 loss: 0.1622 (0.1705) time: 3.4112 data: 0.0082 max mem: 33369 +Epoch: [2] [ 850/1319] eta: 0:26:28 lr: 4.70140792693031e-05 loss: 0.1641 (0.1706) time: 3.4389 data: 0.0082 max mem: 33369 +Epoch: [2] [ 860/1319] eta: 0:25:54 lr: 4.700549143857884e-05 loss: 0.1752 (0.1708) time: 3.4152 data: 0.0079 max mem: 33369 +Epoch: [2] [ 870/1319] eta: 0:25:20 lr: 4.699690343351954e-05 loss: 0.1780 (0.1709) time: 3.4001 data: 0.0077 max mem: 33369 +Epoch: [2] [ 880/1319] eta: 0:24:46 lr: 4.698831525408628e-05 loss: 0.1645 (0.1712) time: 3.3956 data: 0.0074 max mem: 33369 +Epoch: [2] [ 890/1319] eta: 0:24:13 lr: 4.697972690024009e-05 loss: 0.1686 (0.1710) time: 3.3749 data: 0.0077 max mem: 33369 +Epoch: [2] [ 900/1319] eta: 0:23:39 lr: 4.6971138371942025e-05 loss: 0.1348 (0.1707) time: 3.3658 data: 0.0080 max mem: 33369 +Epoch: [2] [ 910/1319] eta: 0:23:04 lr: 4.696254966915307e-05 loss: 0.1376 (0.1706) time: 3.3477 data: 0.0074 max mem: 33369 +Epoch: [2] [ 920/1319] eta: 0:22:31 lr: 4.695396079183423e-05 loss: 0.1533 (0.1705) time: 3.3603 data: 0.0077 max mem: 33369 +Epoch: [2] [ 930/1319] eta: 0:21:57 lr: 4.694537173994649e-05 loss: 0.1669 (0.1708) time: 3.3695 data: 0.0081 max mem: 33369 +Epoch: [2] [ 940/1319] eta: 0:21:23 lr: 4.69367825134508e-05 loss: 0.1677 (0.1706) time: 3.3517 data: 0.0077 max mem: 33369 +Epoch: [2] [ 950/1319] eta: 0:20:49 lr: 4.692819311230812e-05 loss: 0.1577 (0.1708) time: 3.3569 data: 0.0078 max mem: 33369 +Epoch: [2] [ 960/1319] eta: 0:20:15 lr: 4.6919603536479375e-05 loss: 0.1887 (0.1710) time: 3.3669 data: 0.0077 max mem: 33369 +Epoch: [2] [ 970/1319] eta: 0:19:41 lr: 4.691101378592547e-05 loss: 0.1733 (0.1712) time: 3.3788 data: 0.0074 max mem: 33369 +Epoch: [2] [ 980/1319] eta: 0:19:07 lr: 4.690242386060732e-05 loss: 0.1595 (0.1710) time: 3.3879 data: 0.0076 max mem: 33369 +Epoch: [2] [ 990/1319] eta: 0:18:33 lr: 4.6893833760485775e-05 loss: 0.1595 (0.1708) time: 3.3783 data: 0.0077 max mem: 33369 +Epoch: [2] [1000/1319] eta: 0:17:59 lr: 4.688524348552173e-05 loss: 0.1560 (0.1708) time: 3.3809 data: 0.0075 max mem: 33369 +Epoch: [2] [1010/1319] eta: 0:17:26 lr: 4.6876653035676014e-05 loss: 0.1616 (0.1708) time: 3.4073 data: 0.0082 max mem: 33369 +Epoch: [2] [1020/1319] eta: 0:16:52 lr: 4.6868062410909454e-05 loss: 0.1693 (0.1708) time: 3.3859 data: 0.0085 max mem: 33369 +Epoch: [2] [1030/1319] eta: 0:16:18 lr: 4.685947161118287e-05 loss: 0.1617 (0.1707) time: 3.3667 data: 0.0077 max mem: 33369 +Epoch: [2] [1040/1319] eta: 0:15:44 lr: 4.685088063645705e-05 loss: 0.1476 (0.1706) time: 3.3697 data: 0.0079 max mem: 33369 +Epoch: [2] [1050/1319] eta: 0:15:10 lr: 4.684228948669277e-05 loss: 0.1511 (0.1704) time: 3.3595 data: 0.0081 max mem: 33369 +Epoch: [2] [1060/1319] eta: 0:14:36 lr: 4.683369816185082e-05 loss: 0.1315 (0.1700) time: 3.3612 data: 0.0077 max mem: 33369 +Epoch: [2] [1070/1319] eta: 0:14:02 lr: 4.682510666189191e-05 loss: 0.1337 (0.1699) time: 3.3627 data: 0.0075 max mem: 33369 +Epoch: [2] [1080/1319] eta: 0:13:28 lr: 4.681651498677679e-05 loss: 0.1553 (0.1700) time: 3.3713 data: 0.0077 max mem: 33369 +Epoch: [2] [1090/1319] eta: 0:12:54 lr: 4.680792313646616e-05 loss: 0.1624 (0.1701) time: 3.3625 data: 0.0078 max mem: 33369 +Epoch: [2] [1100/1319] eta: 0:12:20 lr: 4.679933111092072e-05 loss: 0.1595 (0.1699) time: 3.3420 data: 0.0077 max mem: 33369 +Epoch: [2] [1110/1319] eta: 0:11:47 lr: 4.6790738910101147e-05 loss: 0.1667 (0.1702) time: 3.3724 data: 0.0078 max mem: 33369 +Epoch: [2] [1120/1319] eta: 0:11:13 lr: 4.67821465339681e-05 loss: 0.1733 (0.1703) time: 3.4009 data: 0.0080 max mem: 33369 +Epoch: [2] [1130/1319] eta: 0:10:39 lr: 4.677355398248223e-05 loss: 0.1733 (0.1703) time: 3.3970 data: 0.0080 max mem: 33369 +Epoch: [2] [1140/1319] eta: 0:10:05 lr: 4.676496125560416e-05 loss: 0.1770 (0.1705) time: 3.3862 data: 0.0083 max mem: 33369 +Epoch: [2] [1150/1319] eta: 0:09:31 lr: 4.6756368353294506e-05 loss: 0.1407 (0.1702) time: 3.4027 data: 0.0081 max mem: 33369 +Epoch: [2] [1160/1319] eta: 0:08:58 lr: 4.6747775275513856e-05 loss: 0.1325 (0.1701) time: 3.3995 data: 0.0079 max mem: 33369 +Epoch: [2] [1170/1319] eta: 0:08:24 lr: 4.6739182022222775e-05 loss: 0.1549 (0.1700) time: 3.3789 data: 0.0080 max mem: 33369 +Epoch: [2] [1180/1319] eta: 0:07:50 lr: 4.6730588593381847e-05 loss: 0.1561 (0.1701) time: 3.3811 data: 0.0077 max mem: 33369 +Epoch: [2] [1190/1319] eta: 0:07:16 lr: 4.67219949889516e-05 loss: 0.1596 (0.1702) time: 3.3613 data: 0.0079 max mem: 33369 +Epoch: [2] [1200/1319] eta: 0:06:42 lr: 4.6713401208892564e-05 loss: 0.1621 (0.1703) time: 3.3849 data: 0.0083 max mem: 33369 +Epoch: [2] [1210/1319] eta: 0:06:08 lr: 4.6704807253165246e-05 loss: 0.1611 (0.1703) time: 3.3836 data: 0.0083 max mem: 33369 +Epoch: [2] [1220/1319] eta: 0:05:34 lr: 4.6696213121730145e-05 loss: 0.1614 (0.1705) time: 3.3521 data: 0.0081 max mem: 33369 +Epoch: [2] [1230/1319] eta: 0:05:01 lr: 4.668761881454772e-05 loss: 0.1678 (0.1705) time: 3.3704 data: 0.0076 max mem: 33369 +Epoch: [2] [1240/1319] eta: 0:04:27 lr: 4.6679024331578444e-05 loss: 0.1684 (0.1707) time: 3.3755 data: 0.0073 max mem: 33369 +Epoch: [2] [1250/1319] eta: 0:03:53 lr: 4.6670429672782765e-05 loss: 0.1482 (0.1706) time: 3.3709 data: 0.0080 max mem: 33369 +Epoch: [2] [1260/1319] eta: 0:03:19 lr: 4.6661834838121084e-05 loss: 0.1391 (0.1705) time: 3.3745 data: 0.0082 max mem: 33369 +Epoch: [2] [1270/1319] eta: 0:02:45 lr: 4.665323982755382e-05 loss: 0.1482 (0.1704) time: 3.3596 data: 0.0077 max mem: 33369 +Epoch: [2] [1280/1319] eta: 0:02:11 lr: 4.664464464104137e-05 loss: 0.1501 (0.1704) time: 3.3479 data: 0.0074 max mem: 33369 +Epoch: [2] [1290/1319] eta: 0:01:38 lr: 4.6636049278544094e-05 loss: 0.1501 (0.1703) time: 3.3752 data: 0.0076 max mem: 33369 +Epoch: [2] [1300/1319] eta: 0:01:04 lr: 4.662745374002236e-05 loss: 0.1710 (0.1703) time: 3.3758 data: 0.0080 max mem: 33369 +Epoch: [2] [1310/1319] eta: 0:00:30 lr: 4.6618858025436495e-05 loss: 0.1843 (0.1706) time: 3.3622 data: 0.0078 max mem: 33369 +Epoch: [2] Total time: 1:14:22 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 2:55:50 time: 4.1004 data: 4.0162 max mem: 33369 +Test: [ 100/2573] eta: 0:04:49 time: 0.0772 data: 0.0014 max mem: 33369 +Test: [ 200/2573] eta: 0:03:53 time: 0.0788 data: 0.0016 max mem: 33369 +Test: [ 300/2573] eta: 0:03:28 time: 0.0811 data: 0.0014 max mem: 33369 +Test: [ 400/2573] eta: 0:03:11 time: 0.0802 data: 0.0014 max mem: 33369 +Test: [ 500/2573] eta: 0:02:59 time: 0.0798 data: 0.0015 max mem: 33369 +Test: [ 600/2573] eta: 0:02:48 time: 0.0795 data: 0.0014 max mem: 33369 +Test: [ 700/2573] eta: 0:02:39 time: 0.0796 data: 0.0016 max mem: 33369 +Test: [ 800/2573] eta: 0:02:29 time: 0.0826 data: 0.0014 max mem: 33369 +Test: [ 900/2573] eta: 0:02:20 time: 0.0789 data: 0.0014 max mem: 33369 +Test: [1000/2573] eta: 0:02:11 time: 0.0793 data: 0.0014 max mem: 33369 +Test: [1100/2573] eta: 0:02:02 time: 0.0808 data: 0.0015 max mem: 33369 +Test: [1200/2573] eta: 0:01:54 time: 0.0808 data: 0.0014 max mem: 33369 +Test: [1300/2573] eta: 0:01:45 time: 0.0800 data: 0.0013 max mem: 33369 +Test: [1400/2573] eta: 0:01:36 time: 0.0783 data: 0.0014 max mem: 33369 +Test: [1500/2573] eta: 0:01:28 time: 0.0797 data: 0.0014 max mem: 33369 +Test: [1600/2573] eta: 0:01:20 time: 0.0833 data: 0.0014 max mem: 33369 +Test: [1700/2573] eta: 0:01:11 time: 0.0791 data: 0.0014 max mem: 33369 +Test: [1800/2573] eta: 0:01:03 time: 0.0820 data: 0.0015 max mem: 33369 +Test: [1900/2573] eta: 0:00:55 time: 0.0781 data: 0.0014 max mem: 33369 +Test: [2000/2573] eta: 0:00:46 time: 0.0809 data: 0.0014 max mem: 33369 +Test: [2100/2573] eta: 0:00:38 time: 0.0820 data: 0.0013 max mem: 33369 +Test: [2200/2573] eta: 0:00:30 time: 0.0828 data: 0.0015 max mem: 33369 +Test: [2300/2573] eta: 0:00:22 time: 0.0822 data: 0.0014 max mem: 33369 +Test: [2400/2573] eta: 0:00:14 time: 0.0774 data: 0.0014 max mem: 33369 +Test: [2500/2573] eta: 0:00:05 time: 0.0811 data: 0.0016 max mem: 33369 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: Total time: 0:03:30 +Final results: +Mean IoU is 40.12 + + precision@0.5 = 41.61 + precision@0.6 = 33.86 + precision@0.7 = 24.88 + precision@0.8 = 15.71 + precision@0.9 = 4.78 + overall IoU = 44.33 + +Average object IoU 40.122019322415134 +Overall IoU 44.33049774169922 +Better epoch: 2 + +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [3] [ 0/1319] eta: 1:57:32 lr: 4.661112173174161e-05 loss: 0.1104 (0.1104) time: 5.3467 data: 1.8063 max mem: 33369 +Epoch: [3] [ 10/1319] eta: 1:17:37 lr: 4.660252568252458e-05 loss: 0.1398 (0.1500) time: 3.5582 data: 0.1724 max mem: 33369 +Epoch: [3] [ 20/1319] eta: 1:15:54 lr: 4.6593929457128314e-05 loss: 0.1399 (0.1547) time: 3.4143 data: 0.0086 max mem: 33369 +Epoch: [3] [ 30/1319] eta: 1:14:24 lr: 4.6585333055513096e-05 loss: 0.1329 (0.1515) time: 3.4115 data: 0.0084 max mem: 33369 +Epoch: [3] [ 40/1319] eta: 1:13:31 lr: 4.657673647763916e-05 loss: 0.1546 (0.1619) time: 3.3886 data: 0.0084 max mem: 33369 +Epoch: [3] [ 50/1319] eta: 1:12:46 lr: 4.656813972346675e-05 loss: 0.1560 (0.1601) time: 3.4062 data: 0.0079 max mem: 33369 +Epoch: [3] [ 60/1319] eta: 1:12:01 lr: 4.655954279295608e-05 loss: 0.1377 (0.1560) time: 3.3989 data: 0.0076 max mem: 33369 +Epoch: [3] [ 70/1319] eta: 1:11:17 lr: 4.655094568606738e-05 loss: 0.1360 (0.1554) time: 3.3843 data: 0.0077 max mem: 33369 +Epoch: [3] [ 80/1319] eta: 1:10:37 lr: 4.6542348402760813e-05 loss: 0.1360 (0.1541) time: 3.3815 data: 0.0080 max mem: 33369 +Epoch: [3] [ 90/1319] eta: 1:09:56 lr: 4.653375094299656e-05 loss: 0.1420 (0.1571) time: 3.3777 data: 0.0080 max mem: 33369 +Epoch: [3] [ 100/1319] eta: 1:09:24 lr: 4.652515330673476e-05 loss: 0.1361 (0.1554) time: 3.4029 data: 0.0076 max mem: 33369 +Epoch: [3] [ 110/1319] eta: 1:08:51 lr: 4.651655549393556e-05 loss: 0.1179 (0.1545) time: 3.4281 data: 0.0075 max mem: 33369 +Epoch: [3] [ 120/1319] eta: 1:08:10 lr: 4.650795750455908e-05 loss: 0.1385 (0.1545) time: 3.3849 data: 0.0076 max mem: 33369 +Epoch: [3] [ 130/1319] eta: 1:07:33 lr: 4.649935933856541e-05 loss: 0.1426 (0.1538) time: 3.3671 data: 0.0078 max mem: 33369 +Epoch: [3] [ 140/1319] eta: 1:06:56 lr: 4.6490760995914644e-05 loss: 0.1265 (0.1519) time: 3.3788 data: 0.0079 max mem: 33369 +Epoch: [3] [ 150/1319] eta: 1:06:23 lr: 4.648216247656684e-05 loss: 0.1357 (0.1522) time: 3.3980 data: 0.0082 max mem: 33369 +Epoch: [3] [ 160/1319] eta: 1:05:49 lr: 4.647356378048206e-05 loss: 0.1357 (0.1511) time: 3.4128 data: 0.0082 max mem: 33369 +Epoch: [3] [ 170/1319] eta: 1:05:13 lr: 4.646496490762032e-05 loss: 0.1443 (0.1525) time: 3.3908 data: 0.0080 max mem: 33369 +Epoch: [3] [ 180/1319] eta: 1:04:36 lr: 4.645636585794164e-05 loss: 0.1659 (0.1523) time: 3.3743 data: 0.0083 max mem: 33369 +Epoch: [3] [ 190/1319] eta: 1:04:00 lr: 4.644776663140602e-05 loss: 0.1572 (0.1530) time: 3.3677 data: 0.0079 max mem: 33369 +Epoch: [3] [ 200/1319] eta: 1:03:26 lr: 4.6439167227973446e-05 loss: 0.1572 (0.1535) time: 3.3858 data: 0.0077 max mem: 33369 +Epoch: [3] [ 210/1319] eta: 1:02:52 lr: 4.643056764760387e-05 loss: 0.1450 (0.1542) time: 3.3976 data: 0.0077 max mem: 33369 +Epoch: [3] [ 220/1319] eta: 1:02:15 lr: 4.642196789025724e-05 loss: 0.1595 (0.1547) time: 3.3688 data: 0.0075 max mem: 33369 +Epoch: [3] [ 230/1319] eta: 1:01:40 lr: 4.641336795589349e-05 loss: 0.1585 (0.1544) time: 3.3607 data: 0.0077 max mem: 33369 +Epoch: [3] [ 240/1319] eta: 1:01:04 lr: 4.6404767844472526e-05 loss: 0.1474 (0.1544) time: 3.3658 data: 0.0077 max mem: 33369 +Epoch: [3] [ 250/1319] eta: 1:00:30 lr: 4.639616755595424e-05 loss: 0.1483 (0.1544) time: 3.3770 data: 0.0077 max mem: 33369 +Epoch: [3] [ 260/1319] eta: 0:59:54 lr: 4.638756709029851e-05 loss: 0.1462 (0.1544) time: 3.3754 data: 0.0080 max mem: 33369 +Epoch: [3] [ 270/1319] eta: 0:59:19 lr: 4.6378966447465196e-05 loss: 0.1462 (0.1551) time: 3.3596 data: 0.0078 max mem: 33369 +Epoch: [3] [ 280/1319] eta: 0:58:47 lr: 4.637036562741414e-05 loss: 0.1513 (0.1550) time: 3.3957 data: 0.0077 max mem: 33369 +Epoch: [3] [ 290/1319] eta: 0:58:12 lr: 4.636176463010516e-05 loss: 0.1300 (0.1558) time: 3.3951 data: 0.0079 max mem: 33369 +Epoch: [3] [ 300/1319] eta: 0:57:38 lr: 4.635316345549808e-05 loss: 0.1312 (0.1554) time: 3.3850 data: 0.0080 max mem: 33369 +Epoch: [3] [ 310/1319] eta: 0:57:04 lr: 4.634456210355267e-05 loss: 0.1454 (0.1554) time: 3.4015 data: 0.0079 max mem: 33369 +Epoch: [3] [ 320/1319] eta: 0:56:30 lr: 4.633596057422871e-05 loss: 0.1536 (0.1553) time: 3.3973 data: 0.0082 max mem: 33369 +Epoch: [3] [ 330/1319] eta: 0:55:56 lr: 4.632735886748595e-05 loss: 0.1517 (0.1553) time: 3.3827 data: 0.0082 max mem: 33369 +Epoch: [3] [ 340/1319] eta: 0:55:24 lr: 4.6318756983284134e-05 loss: 0.1517 (0.1555) time: 3.4130 data: 0.0079 max mem: 33369 +Epoch: [3] [ 350/1319] eta: 0:54:49 lr: 4.6310154921582983e-05 loss: 0.1584 (0.1554) time: 3.4231 data: 0.0077 max mem: 33369 +Epoch: [3] [ 360/1319] eta: 0:54:16 lr: 4.630155268234219e-05 loss: 0.1559 (0.1555) time: 3.4108 data: 0.0078 max mem: 33369 +Epoch: [3] [ 370/1319] eta: 0:53:41 lr: 4.629295026552143e-05 loss: 0.1516 (0.1553) time: 3.3903 data: 0.0082 max mem: 33369 +Epoch: [3] [ 380/1319] eta: 0:53:07 lr: 4.6284347671080394e-05 loss: 0.1369 (0.1552) time: 3.3655 data: 0.0080 max mem: 33369 +Epoch: [3] [ 390/1319] eta: 0:52:33 lr: 4.627574489897873e-05 loss: 0.1446 (0.1548) time: 3.3882 data: 0.0077 max mem: 33369 +Epoch: [3] [ 400/1319] eta: 0:52:00 lr: 4.626714194917605e-05 loss: 0.1431 (0.1543) time: 3.4170 data: 0.0076 max mem: 33369 +Epoch: [3] [ 410/1319] eta: 0:51:26 lr: 4.625853882163199e-05 loss: 0.1423 (0.1539) time: 3.4162 data: 0.0081 max mem: 33369 +Epoch: [3] [ 420/1319] eta: 0:50:53 lr: 4.624993551630613e-05 loss: 0.1447 (0.1538) time: 3.4017 data: 0.0089 max mem: 33369 +Epoch: [3] [ 430/1319] eta: 0:50:18 lr: 4.624133203315806e-05 loss: 0.1450 (0.1538) time: 3.3973 data: 0.0083 max mem: 33369 +Epoch: [3] [ 440/1319] eta: 0:49:44 lr: 4.6232728372147346e-05 loss: 0.1408 (0.1534) time: 3.3852 data: 0.0077 max mem: 33369 +Epoch: [3] [ 450/1319] eta: 0:49:09 lr: 4.6224124533233514e-05 loss: 0.1454 (0.1535) time: 3.3690 data: 0.0078 max mem: 33369 +Epoch: [3] [ 460/1319] eta: 0:48:37 lr: 4.621552051637611e-05 loss: 0.1627 (0.1539) time: 3.4091 data: 0.0077 max mem: 33369 +Epoch: [3] [ 470/1319] eta: 0:48:02 lr: 4.620691632153463e-05 loss: 0.1414 (0.1538) time: 3.4216 data: 0.0079 max mem: 33369 +Epoch: [3] [ 480/1319] eta: 0:47:29 lr: 4.619831194866858e-05 loss: 0.1395 (0.1538) time: 3.3941 data: 0.0079 max mem: 33369 +Epoch: [3] [ 490/1319] eta: 0:46:54 lr: 4.618970739773742e-05 loss: 0.1408 (0.1535) time: 3.3883 data: 0.0077 max mem: 33369 +Epoch: [3] [ 500/1319] eta: 0:46:20 lr: 4.618110266870061e-05 loss: 0.1502 (0.1541) time: 3.3582 data: 0.0081 max mem: 33369 +Epoch: [3] [ 510/1319] eta: 0:45:45 lr: 4.6172497761517596e-05 loss: 0.1547 (0.1540) time: 3.3637 data: 0.0081 max mem: 33369 +Epoch: [3] [ 520/1319] eta: 0:45:12 lr: 4.6163892676147796e-05 loss: 0.1516 (0.1542) time: 3.3991 data: 0.0076 max mem: 33369 +Epoch: [3] [ 530/1319] eta: 0:44:37 lr: 4.615528741255061e-05 loss: 0.1502 (0.1542) time: 3.3836 data: 0.0074 max mem: 33369 +Epoch: [3] [ 540/1319] eta: 0:44:03 lr: 4.6146681970685424e-05 loss: 0.1463 (0.1541) time: 3.3662 data: 0.0079 max mem: 33369 +Epoch: [3] [ 550/1319] eta: 0:43:28 lr: 4.613807635051161e-05 loss: 0.1384 (0.1542) time: 3.3604 data: 0.0080 max mem: 33369 +Epoch: [3] [ 560/1319] eta: 0:42:55 lr: 4.612947055198852e-05 loss: 0.1680 (0.1545) time: 3.3699 data: 0.0080 max mem: 33369 +Epoch: [3] [ 570/1319] eta: 0:42:21 lr: 4.612086457507548e-05 loss: 0.1680 (0.1551) time: 3.4006 data: 0.0082 max mem: 33369 +Epoch: [3] [ 580/1319] eta: 0:41:47 lr: 4.611225841973181e-05 loss: 0.1564 (0.1549) time: 3.3864 data: 0.0079 max mem: 33369 +Epoch: [3] [ 590/1319] eta: 0:41:13 lr: 4.610365208591681e-05 loss: 0.1214 (0.1546) time: 3.3855 data: 0.0077 max mem: 33369 +Epoch: [3] [ 600/1319] eta: 0:40:39 lr: 4.609504557358975e-05 loss: 0.1436 (0.1547) time: 3.3937 data: 0.0082 max mem: 33369 +Epoch: [3] [ 610/1319] eta: 0:40:05 lr: 4.60864388827099e-05 loss: 0.1516 (0.1548) time: 3.3857 data: 0.0083 max mem: 33369 +Epoch: [3] [ 620/1319] eta: 0:39:30 lr: 4.6077832013236505e-05 loss: 0.1687 (0.1548) time: 3.3528 data: 0.0081 max mem: 33369 +Epoch: [3] [ 630/1319] eta: 0:38:56 lr: 4.606922496512879e-05 loss: 0.1549 (0.1550) time: 3.3570 data: 0.0077 max mem: 33369 +Epoch: [3] [ 640/1319] eta: 0:38:22 lr: 4.606061773834596e-05 loss: 0.1432 (0.1550) time: 3.3669 data: 0.0076 max mem: 33369 +Epoch: [3] [ 650/1319] eta: 0:37:48 lr: 4.60520103328472e-05 loss: 0.1507 (0.1552) time: 3.3656 data: 0.0079 max mem: 33369 +Epoch: [3] [ 660/1319] eta: 0:37:13 lr: 4.60434027485917e-05 loss: 0.1545 (0.1552) time: 3.3633 data: 0.0081 max mem: 33369 +Epoch: [3] [ 670/1319] eta: 0:36:39 lr: 4.6034794985538615e-05 loss: 0.1545 (0.1552) time: 3.3236 data: 0.0080 max mem: 33369 +Epoch: [3] [ 680/1319] eta: 0:36:05 lr: 4.602618704364706e-05 loss: 0.1515 (0.1551) time: 3.3428 data: 0.0085 max mem: 33369 +Epoch: [3] [ 690/1319] eta: 0:35:31 lr: 4.601757892287618e-05 loss: 0.1482 (0.1553) time: 3.3870 data: 0.0086 max mem: 33369 +Epoch: [3] [ 700/1319] eta: 0:34:57 lr: 4.600897062318506e-05 loss: 0.1557 (0.1557) time: 3.4019 data: 0.0081 max mem: 33369 +Epoch: [3] [ 710/1319] eta: 0:34:23 lr: 4.600036214453279e-05 loss: 0.1484 (0.1557) time: 3.3924 data: 0.0081 max mem: 33369 +Epoch: [3] [ 720/1319] eta: 0:33:49 lr: 4.599175348687844e-05 loss: 0.1237 (0.1555) time: 3.3864 data: 0.0080 max mem: 33369 +Epoch: [3] [ 730/1319] eta: 0:33:16 lr: 4.598314465018106e-05 loss: 0.1216 (0.1555) time: 3.4002 data: 0.0080 max mem: 33369 +Epoch: [3] [ 740/1319] eta: 0:32:41 lr: 4.5974535634399665e-05 loss: 0.1406 (0.1554) time: 3.3798 data: 0.0086 max mem: 33369 +Epoch: [3] [ 750/1319] eta: 0:32:08 lr: 4.596592643949328e-05 loss: 0.1560 (0.1554) time: 3.3809 data: 0.0082 max mem: 33369 +Epoch: [3] [ 760/1319] eta: 0:31:33 lr: 4.595731706542089e-05 loss: 0.1566 (0.1556) time: 3.3777 data: 0.0081 max mem: 33369 +Epoch: [3] [ 770/1319] eta: 0:30:59 lr: 4.5948707512141485e-05 loss: 0.1678 (0.1557) time: 3.3579 data: 0.0082 max mem: 33369 +Epoch: [3] [ 780/1319] eta: 0:30:25 lr: 4.594009777961402e-05 loss: 0.1358 (0.1555) time: 3.3527 data: 0.0081 max mem: 33369 +Epoch: [3] [ 790/1319] eta: 0:29:51 lr: 4.593148786779743e-05 loss: 0.1358 (0.1557) time: 3.3308 data: 0.0084 max mem: 33369 +Epoch: [3] [ 800/1319] eta: 0:29:17 lr: 4.592287777665063e-05 loss: 0.1510 (0.1557) time: 3.3377 data: 0.0081 max mem: 33369 +Epoch: [3] [ 810/1319] eta: 0:28:43 lr: 4.5914267506132555e-05 loss: 0.1493 (0.1558) time: 3.3793 data: 0.0080 max mem: 33369 +Epoch: [3] [ 820/1319] eta: 0:28:09 lr: 4.590565705620206e-05 loss: 0.1577 (0.1557) time: 3.3837 data: 0.0080 max mem: 33369 +Epoch: [3] [ 830/1319] eta: 0:27:35 lr: 4.589704642681802e-05 loss: 0.1247 (0.1555) time: 3.3822 data: 0.0077 max mem: 33369 +Epoch: [3] [ 840/1319] eta: 0:27:01 lr: 4.58884356179393e-05 loss: 0.1440 (0.1559) time: 3.3875 data: 0.0075 max mem: 33369 +Epoch: [3] [ 850/1319] eta: 0:26:28 lr: 4.5879824629524725e-05 loss: 0.1440 (0.1556) time: 3.3901 data: 0.0077 max mem: 33369 +Epoch: [3] [ 860/1319] eta: 0:25:54 lr: 4.5871213461533106e-05 loss: 0.1350 (0.1558) time: 3.3863 data: 0.0080 max mem: 33369 +Epoch: [3] [ 870/1319] eta: 0:25:20 lr: 4.5862602113923244e-05 loss: 0.1485 (0.1558) time: 3.3604 data: 0.0081 max mem: 33369 +Epoch: [3] [ 880/1319] eta: 0:24:46 lr: 4.585399058665391e-05 loss: 0.1340 (0.1556) time: 3.3799 data: 0.0082 max mem: 33369 +Epoch: [3] [ 890/1319] eta: 0:24:12 lr: 4.5845378879683885e-05 loss: 0.1312 (0.1556) time: 3.3848 data: 0.0080 max mem: 33369 +Epoch: [3] [ 900/1319] eta: 0:23:38 lr: 4.583676699297189e-05 loss: 0.1557 (0.1556) time: 3.3573 data: 0.0076 max mem: 33369 +Epoch: [3] [ 910/1319] eta: 0:23:04 lr: 4.582815492647665e-05 loss: 0.1611 (0.1557) time: 3.3757 data: 0.0080 max mem: 33369 +Epoch: [3] [ 920/1319] eta: 0:22:30 lr: 4.5819542680156885e-05 loss: 0.1615 (0.1560) time: 3.4041 data: 0.0083 max mem: 33369 +Epoch: [3] [ 930/1319] eta: 0:21:56 lr: 4.5810930253971277e-05 loss: 0.1517 (0.1559) time: 3.3705 data: 0.0080 max mem: 33369 +Epoch: [3] [ 940/1319] eta: 0:21:23 lr: 4.580231764787849e-05 loss: 0.1583 (0.1562) time: 3.3871 data: 0.0077 max mem: 33369 +Epoch: [3] [ 950/1319] eta: 0:20:49 lr: 4.579370486183719e-05 loss: 0.1608 (0.1562) time: 3.4260 data: 0.0080 max mem: 33369 +Epoch: [3] [ 960/1319] eta: 0:20:15 lr: 4.5785091895806004e-05 loss: 0.1260 (0.1560) time: 3.3815 data: 0.0081 max mem: 33369 +Epoch: [3] [ 970/1319] eta: 0:19:41 lr: 4.577647874974354e-05 loss: 0.1273 (0.1560) time: 3.3564 data: 0.0080 max mem: 33369 +Epoch: [3] [ 980/1319] eta: 0:19:07 lr: 4.57678654236084e-05 loss: 0.1293 (0.1557) time: 3.3730 data: 0.0081 max mem: 33369 +Epoch: [3] [ 990/1319] eta: 0:18:33 lr: 4.575925191735917e-05 loss: 0.1321 (0.1557) time: 3.4084 data: 0.0079 max mem: 33369 +Epoch: [3] [1000/1319] eta: 0:17:59 lr: 4.57506382309544e-05 loss: 0.1348 (0.1558) time: 3.3923 data: 0.0079 max mem: 33369 +Epoch: [3] [1010/1319] eta: 0:17:26 lr: 4.574202436435264e-05 loss: 0.1522 (0.1558) time: 3.3632 data: 0.0074 max mem: 33369 +Epoch: [3] [1020/1319] eta: 0:16:52 lr: 4.573341031751242e-05 loss: 0.1459 (0.1557) time: 3.3959 data: 0.0074 max mem: 33369 +Epoch: [3] [1030/1319] eta: 0:16:18 lr: 4.5724796090392234e-05 loss: 0.1276 (0.1556) time: 3.4003 data: 0.0076 max mem: 33369 +Epoch: [3] [1040/1319] eta: 0:15:44 lr: 4.571618168295058e-05 loss: 0.1269 (0.1554) time: 3.3854 data: 0.0078 max mem: 33369 +Epoch: [3] [1050/1319] eta: 0:15:10 lr: 4.570756709514592e-05 loss: 0.1268 (0.1551) time: 3.3727 data: 0.0076 max mem: 33369 +Epoch: [3] [1060/1319] eta: 0:14:36 lr: 4.569895232693671e-05 loss: 0.1362 (0.1552) time: 3.3563 data: 0.0075 max mem: 33369 +Epoch: [3] [1070/1319] eta: 0:14:02 lr: 4.569033737828139e-05 loss: 0.1399 (0.1551) time: 3.3692 data: 0.0078 max mem: 33369 +Epoch: [3] [1080/1319] eta: 0:13:29 lr: 4.568172224913836e-05 loss: 0.1339 (0.1549) time: 3.3816 data: 0.0080 max mem: 33369 +Epoch: [3] [1090/1319] eta: 0:12:55 lr: 4.567310693946603e-05 loss: 0.1339 (0.1550) time: 3.3728 data: 0.0078 max mem: 33369 +Epoch: [3] [1100/1319] eta: 0:12:21 lr: 4.566449144922278e-05 loss: 0.1501 (0.1549) time: 3.3568 data: 0.0077 max mem: 33369 +Epoch: [3] [1110/1319] eta: 0:11:47 lr: 4.565587577836695e-05 loss: 0.1369 (0.1549) time: 3.3712 data: 0.0076 max mem: 33369 +Epoch: [3] [1120/1319] eta: 0:11:13 lr: 4.5647259926856906e-05 loss: 0.1536 (0.1550) time: 3.3834 data: 0.0074 max mem: 33369 +Epoch: [3] [1130/1319] eta: 0:10:39 lr: 4.563864389465096e-05 loss: 0.1341 (0.1549) time: 3.3762 data: 0.0074 max mem: 33369 +Epoch: [3] [1140/1319] eta: 0:10:05 lr: 4.563002768170741e-05 loss: 0.1452 (0.1550) time: 3.4072 data: 0.0078 max mem: 33369 +Epoch: [3] [1150/1319] eta: 0:09:32 lr: 4.562141128798457e-05 loss: 0.1467 (0.1551) time: 3.4084 data: 0.0082 max mem: 33369 +Epoch: [3] [1160/1319] eta: 0:08:58 lr: 4.561279471344068e-05 loss: 0.1667 (0.1554) time: 3.3918 data: 0.0081 max mem: 33369 +Epoch: [3] [1170/1319] eta: 0:08:24 lr: 4.5604177958034e-05 loss: 0.1739 (0.1555) time: 3.3987 data: 0.0078 max mem: 33369 +Epoch: [3] [1180/1319] eta: 0:07:50 lr: 4.559556102172276e-05 loss: 0.1545 (0.1555) time: 3.4136 data: 0.0075 max mem: 33369 +Epoch: [3] [1190/1319] eta: 0:07:16 lr: 4.5586943904465176e-05 loss: 0.1497 (0.1557) time: 3.4353 data: 0.0077 max mem: 33369 +Epoch: [3] [1200/1319] eta: 0:06:42 lr: 4.557832660621944e-05 loss: 0.1371 (0.1555) time: 3.4216 data: 0.0080 max mem: 33369 +Epoch: [3] [1210/1319] eta: 0:06:09 lr: 4.556970912694373e-05 loss: 0.1358 (0.1556) time: 3.4118 data: 0.0077 max mem: 33369 +Epoch: [3] [1220/1319] eta: 0:05:35 lr: 4.5561091466596205e-05 loss: 0.1685 (0.1557) time: 3.4212 data: 0.0073 max mem: 33369 +Epoch: [3] [1230/1319] eta: 0:05:01 lr: 4.555247362513501e-05 loss: 0.1450 (0.1556) time: 3.4030 data: 0.0071 max mem: 33369 +Epoch: [3] [1240/1319] eta: 0:04:27 lr: 4.5543855602518245e-05 loss: 0.1395 (0.1555) time: 3.3553 data: 0.0071 max mem: 33369 +Epoch: [3] [1250/1319] eta: 0:03:53 lr: 4.553523739870403e-05 loss: 0.1395 (0.1554) time: 3.3692 data: 0.0072 max mem: 33369 +Epoch: [3] [1260/1319] eta: 0:03:19 lr: 4.552661901365045e-05 loss: 0.1467 (0.1554) time: 3.4128 data: 0.0075 max mem: 33369 +Epoch: [3] [1270/1319] eta: 0:02:45 lr: 4.551800044731557e-05 loss: 0.1549 (0.1554) time: 3.4216 data: 0.0078 max mem: 33369 +Epoch: [3] [1280/1319] eta: 0:02:12 lr: 4.550938169965743e-05 loss: 0.1495 (0.1554) time: 3.3904 data: 0.0079 max mem: 33369 +Epoch: [3] [1290/1319] eta: 0:01:38 lr: 4.550076277063406e-05 loss: 0.1610 (0.1554) time: 3.3593 data: 0.0078 max mem: 33369 +Epoch: [3] [1300/1319] eta: 0:01:04 lr: 4.549214366020347e-05 loss: 0.1684 (0.1559) time: 3.3697 data: 0.0080 max mem: 33369 +Epoch: [3] [1310/1319] eta: 0:00:30 lr: 4.5483524368323656e-05 loss: 0.1505 (0.1560) time: 3.3916 data: 0.0081 max mem: 33369 +Epoch: [3] Total time: 1:14:27 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 2:28:58 time: 3.4738 data: 3.3440 max mem: 33369 +Test: [ 100/2573] eta: 0:04:34 time: 0.0780 data: 0.0015 max mem: 33369 +Test: [ 200/2573] eta: 0:03:47 time: 0.0793 data: 0.0014 max mem: 33369 +Test: [ 300/2573] eta: 0:03:24 time: 0.0822 data: 0.0016 max mem: 33369 +Test: [ 400/2573] eta: 0:03:09 time: 0.0807 data: 0.0014 max mem: 33369 +Test: [ 500/2573] eta: 0:02:57 time: 0.0799 data: 0.0015 max mem: 33369 +Test: [ 600/2573] eta: 0:02:47 time: 0.0803 data: 0.0015 max mem: 33369 +Test: [ 700/2573] eta: 0:02:38 time: 0.0801 data: 0.0014 max mem: 33369 +Test: [ 800/2573] eta: 0:02:29 time: 0.0834 data: 0.0013 max mem: 33369 +Test: [ 900/2573] eta: 0:02:20 time: 0.0806 data: 0.0014 max mem: 33369 +Test: [1000/2573] eta: 0:02:11 time: 0.0799 data: 0.0014 max mem: 33369 +Test: [1100/2573] eta: 0:02:02 time: 0.0801 data: 0.0014 max mem: 33369 +Test: [1200/2573] eta: 0:01:54 time: 0.0803 data: 0.0014 max mem: 33369 +Test: [1300/2573] eta: 0:01:45 time: 0.0797 data: 0.0013 max mem: 33369 +Test: [1400/2573] eta: 0:01:36 time: 0.0793 data: 0.0014 max mem: 33369 +Test: [1500/2573] eta: 0:01:28 time: 0.0811 data: 0.0015 max mem: 33369 +Test: [1600/2573] eta: 0:01:20 time: 0.0834 data: 0.0014 max mem: 33369 +Test: [1700/2573] eta: 0:01:11 time: 0.0788 data: 0.0014 max mem: 33369 +Test: [1800/2573] eta: 0:01:03 time: 0.0821 data: 0.0014 max mem: 33369 +Test: [1900/2573] eta: 0:00:55 time: 0.0787 data: 0.0013 max mem: 33369 +Test: [2000/2573] eta: 0:00:46 time: 0.0811 data: 0.0015 max mem: 33369 +Test: [2100/2573] eta: 0:00:38 time: 0.0815 data: 0.0014 max mem: 33369 +Test: [2200/2573] eta: 0:00:30 time: 0.0810 data: 0.0013 max mem: 33369 +Test: [2300/2573] eta: 0:00:22 time: 0.0819 data: 0.0014 max mem: 33369 +Test: [2400/2573] eta: 0:00:14 time: 0.0769 data: 0.0014 max mem: 33369 +Test: [2500/2573] eta: 0:00:05 time: 0.0792 data: 0.0014 max mem: 33369 +Test: Total time: 0:03:30 +Final results: +Mean IoU is 45.69 + + precision@0.5 = 49.02 + precision@0.6 = 40.67 + precision@0.7 = 32.13 + precision@0.8 = 21.49 + precision@0.9 = 7.68 + overall IoU = 48.62 + +Average object IoU 45.69385165692057 +Overall IoU 48.61656951904297 +Better epoch: 3 + +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [4] [ 0/1319] eta: 1:53:35 lr: 4.547576685045799e-05 loss: 0.1090 (0.1090) time: 5.1672 data: 1.8150 max mem: 33369 +Epoch: [4] [ 10/1319] eta: 1:17:14 lr: 4.546714721370884e-05 loss: 0.1172 (0.1324) time: 3.5404 data: 0.1722 max mem: 33369 +Epoch: [4] [ 20/1319] eta: 1:14:43 lr: 4.5458527395388535e-05 loss: 0.1263 (0.1312) time: 3.3657 data: 0.0077 max mem: 33369 +Epoch: [4] [ 30/1319] eta: 1:13:14 lr: 4.544990739545498e-05 loss: 0.1223 (0.1369) time: 3.3367 data: 0.0077 max mem: 33369 +Epoch: [4] [ 40/1319] eta: 1:12:33 lr: 4.544128721386609e-05 loss: 0.1173 (0.1383) time: 3.3535 data: 0.0079 max mem: 33369 +Epoch: [4] [ 50/1319] eta: 1:12:04 lr: 4.543266685057974e-05 loss: 0.1224 (0.1346) time: 3.4051 data: 0.0084 max mem: 33369 +Epoch: [4] [ 60/1319] eta: 1:11:32 lr: 4.54240463055538e-05 loss: 0.1224 (0.1351) time: 3.4204 data: 0.0088 max mem: 33369 +Epoch: [4] [ 70/1319] eta: 1:11:00 lr: 4.541542557874611e-05 loss: 0.1315 (0.1355) time: 3.4197 data: 0.0086 max mem: 33369 +Epoch: [4] [ 80/1319] eta: 1:10:19 lr: 4.540680467011449e-05 loss: 0.1339 (0.1356) time: 3.3955 data: 0.0082 max mem: 33369 +Epoch: [4] [ 90/1319] eta: 1:09:48 lr: 4.5398183579616753e-05 loss: 0.1389 (0.1363) time: 3.3978 data: 0.0078 max mem: 33369 +Epoch: [4] [ 100/1319] eta: 1:09:08 lr: 4.5389562307210684e-05 loss: 0.1411 (0.1367) time: 3.3923 data: 0.0078 max mem: 33369 +Epoch: [4] [ 110/1319] eta: 1:08:31 lr: 4.5380940852854056e-05 loss: 0.1397 (0.1370) time: 3.3692 data: 0.0081 max mem: 33369 +Epoch: [4] [ 120/1319] eta: 1:07:59 lr: 4.537231921650461e-05 loss: 0.1171 (0.1368) time: 3.3988 data: 0.0082 max mem: 33369 +Epoch: [4] [ 130/1319] eta: 1:07:23 lr: 4.53636973981201e-05 loss: 0.1283 (0.1370) time: 3.4009 data: 0.0081 max mem: 33369 +Epoch: [4] [ 140/1319] eta: 1:06:49 lr: 4.535507539765821e-05 loss: 0.1373 (0.1373) time: 3.3912 data: 0.0079 max mem: 33369 +Epoch: [4] [ 150/1319] eta: 1:06:14 lr: 4.534645321507665e-05 loss: 0.1366 (0.1383) time: 3.3949 data: 0.0084 max mem: 33369 +Epoch: [4] [ 160/1319] eta: 1:05:41 lr: 4.53378308503331e-05 loss: 0.1316 (0.1389) time: 3.4029 data: 0.0087 max mem: 33369 +Epoch: [4] [ 170/1319] eta: 1:05:05 lr: 4.532920830338521e-05 loss: 0.1328 (0.1391) time: 3.3927 data: 0.0084 max mem: 33369 +Epoch: [4] [ 180/1319] eta: 1:04:30 lr: 4.5320585574190625e-05 loss: 0.1276 (0.1393) time: 3.3730 data: 0.0081 max mem: 33369 +Epoch: [4] [ 190/1319] eta: 1:03:56 lr: 4.5311962662706955e-05 loss: 0.1268 (0.1397) time: 3.3845 data: 0.0080 max mem: 33369 +Epoch: [4] [ 200/1319] eta: 1:03:20 lr: 4.5303339568891794e-05 loss: 0.1248 (0.1385) time: 3.3837 data: 0.0081 max mem: 33369 +Epoch: [4] [ 210/1319] eta: 1:02:48 lr: 4.529471629270274e-05 loss: 0.1210 (0.1383) time: 3.4053 data: 0.0080 max mem: 33369 +Epoch: [4] [ 220/1319] eta: 1:02:14 lr: 4.5286092834097356e-05 loss: 0.1321 (0.1385) time: 3.4155 data: 0.0078 max mem: 33369 +Epoch: [4] [ 230/1319] eta: 1:01:40 lr: 4.527746919303318e-05 loss: 0.1341 (0.1388) time: 3.3899 data: 0.0083 max mem: 33369 +Epoch: [4] [ 240/1319] eta: 1:01:05 lr: 4.5268845369467734e-05 loss: 0.1260 (0.1383) time: 3.3870 data: 0.0083 max mem: 33369 +Epoch: [4] [ 250/1319] eta: 1:00:30 lr: 4.526022136335852e-05 loss: 0.1345 (0.1384) time: 3.3727 data: 0.0076 max mem: 33370 +Epoch: [4] [ 260/1319] eta: 0:59:54 lr: 4.525159717466304e-05 loss: 0.1436 (0.1390) time: 3.3536 data: 0.0077 max mem: 33370 +Epoch: [4] [ 270/1319] eta: 0:59:17 lr: 4.524297280333875e-05 loss: 0.1334 (0.1389) time: 3.3370 data: 0.0078 max mem: 33370 +Epoch: [4] [ 280/1319] eta: 0:58:42 lr: 4.5234348249343114e-05 loss: 0.1282 (0.1390) time: 3.3451 data: 0.0076 max mem: 33370 +Epoch: [4] [ 290/1319] eta: 0:58:08 lr: 4.522572351263354e-05 loss: 0.1282 (0.1396) time: 3.3729 data: 0.0076 max mem: 33370 +Epoch: [4] [ 300/1319] eta: 0:57:34 lr: 4.521709859316746e-05 loss: 0.1376 (0.1397) time: 3.3795 data: 0.0079 max mem: 33370 +Epoch: [4] [ 310/1319] eta: 0:57:00 lr: 4.520847349090225e-05 loss: 0.1294 (0.1392) time: 3.3894 data: 0.0080 max mem: 33370 +Epoch: [4] [ 320/1319] eta: 0:56:25 lr: 4.5199848205795306e-05 loss: 0.1293 (0.1392) time: 3.3820 data: 0.0079 max mem: 33370 +Epoch: [4] [ 330/1319] eta: 0:55:52 lr: 4.519122273780396e-05 loss: 0.1182 (0.1387) time: 3.3776 data: 0.0078 max mem: 33370 +Epoch: [4] [ 340/1319] eta: 0:55:17 lr: 4.518259708688556e-05 loss: 0.1322 (0.1386) time: 3.3777 data: 0.0081 max mem: 33370 +Epoch: [4] [ 350/1319] eta: 0:54:43 lr: 4.5173971252997424e-05 loss: 0.1342 (0.1385) time: 3.3740 data: 0.0083 max mem: 33370 +Epoch: [4] [ 360/1319] eta: 0:54:09 lr: 4.5165345236096837e-05 loss: 0.1342 (0.1390) time: 3.3797 data: 0.0080 max mem: 33370 +Epoch: [4] [ 370/1319] eta: 0:53:34 lr: 4.5156719036141086e-05 loss: 0.1590 (0.1393) time: 3.3660 data: 0.0080 max mem: 33370 +Epoch: [4] [ 380/1319] eta: 0:53:00 lr: 4.5148092653087434e-05 loss: 0.1590 (0.1396) time: 3.3656 data: 0.0078 max mem: 33370 +Epoch: [4] [ 390/1319] eta: 0:52:26 lr: 4.5139466086893116e-05 loss: 0.1262 (0.1394) time: 3.3718 data: 0.0079 max mem: 33370 +Epoch: [4] [ 400/1319] eta: 0:51:51 lr: 4.513083933751536e-05 loss: 0.1275 (0.1395) time: 3.3717 data: 0.0081 max mem: 33370 +Epoch: [4] [ 410/1319] eta: 0:51:18 lr: 4.512221240491136e-05 loss: 0.1217 (0.1392) time: 3.3866 data: 0.0078 max mem: 33370 +Epoch: [4] [ 420/1319] eta: 0:50:44 lr: 4.5113585289038304e-05 loss: 0.1222 (0.1394) time: 3.3844 data: 0.0078 max mem: 33370 +Epoch: [4] [ 430/1319] eta: 0:50:09 lr: 4.510495798985335e-05 loss: 0.1362 (0.1396) time: 3.3558 data: 0.0078 max mem: 33370 +Epoch: [4] [ 440/1319] eta: 0:49:35 lr: 4.509633050731365e-05 loss: 0.1473 (0.1400) time: 3.3555 data: 0.0080 max mem: 33370 +Epoch: [4] [ 450/1319] eta: 0:49:01 lr: 4.5087702841376343e-05 loss: 0.1268 (0.1400) time: 3.3771 data: 0.0086 max mem: 33370 +Epoch: [4] [ 460/1319] eta: 0:48:27 lr: 4.507907499199851e-05 loss: 0.1268 (0.1402) time: 3.3870 data: 0.0081 max mem: 33370 +Epoch: [4] [ 470/1319] eta: 0:47:52 lr: 4.507044695913725e-05 loss: 0.1470 (0.1402) time: 3.3508 data: 0.0081 max mem: 33370 +Epoch: [4] [ 480/1319] eta: 0:47:18 lr: 4.506181874274963e-05 loss: 0.1287 (0.1400) time: 3.3406 data: 0.0084 max mem: 33370 +Epoch: [4] [ 490/1319] eta: 0:46:45 lr: 4.5053190342792706e-05 loss: 0.1287 (0.1399) time: 3.4076 data: 0.0082 max mem: 33370 +Epoch: [4] [ 500/1319] eta: 0:46:11 lr: 4.50445617592235e-05 loss: 0.1356 (0.1400) time: 3.4165 data: 0.0080 max mem: 33370 +Epoch: [4] [ 510/1319] eta: 0:45:37 lr: 4.503593299199903e-05 loss: 0.1175 (0.1396) time: 3.3758 data: 0.0078 max mem: 33370 +Epoch: [4] [ 520/1319] eta: 0:45:04 lr: 4.502730404107628e-05 loss: 0.1158 (0.1394) time: 3.3929 data: 0.0079 max mem: 33370 +Epoch: [4] [ 530/1319] eta: 0:44:30 lr: 4.5018674906412226e-05 loss: 0.1340 (0.1396) time: 3.4007 data: 0.0084 max mem: 33370 +Epoch: [4] [ 540/1319] eta: 0:43:56 lr: 4.5010045587963815e-05 loss: 0.1575 (0.1400) time: 3.3810 data: 0.0086 max mem: 33370 +Epoch: [4] [ 550/1319] eta: 0:43:22 lr: 4.5001416085688e-05 loss: 0.1338 (0.1400) time: 3.3781 data: 0.0081 max mem: 33370 +Epoch: [4] [ 560/1319] eta: 0:42:48 lr: 4.4992786399541676e-05 loss: 0.1262 (0.1398) time: 3.3561 data: 0.0079 max mem: 33370 +Epoch: [4] [ 570/1319] eta: 0:42:14 lr: 4.498415652948174e-05 loss: 0.1260 (0.1401) time: 3.3771 data: 0.0080 max mem: 33370 +Epoch: [4] [ 580/1319] eta: 0:41:40 lr: 4.497552647546508e-05 loss: 0.1342 (0.1401) time: 3.3950 data: 0.0078 max mem: 33370 +Epoch: [4] [ 590/1319] eta: 0:41:06 lr: 4.496689623744855e-05 loss: 0.1340 (0.1398) time: 3.3721 data: 0.0078 max mem: 33370 +Epoch: [4] [ 600/1319] eta: 0:40:33 lr: 4.495826581538897e-05 loss: 0.1206 (0.1398) time: 3.3837 data: 0.0076 max mem: 33370 +Epoch: [4] [ 610/1319] eta: 0:39:59 lr: 4.494963520924318e-05 loss: 0.1206 (0.1397) time: 3.4149 data: 0.0076 max mem: 33370 +Epoch: [4] [ 620/1319] eta: 0:39:25 lr: 4.4941004418967974e-05 loss: 0.1093 (0.1397) time: 3.3995 data: 0.0079 max mem: 33370 +Epoch: [4] [ 630/1319] eta: 0:38:52 lr: 4.493237344452013e-05 loss: 0.1093 (0.1394) time: 3.3857 data: 0.0081 max mem: 33370 +Epoch: [4] [ 640/1319] eta: 0:38:18 lr: 4.4923742285856394e-05 loss: 0.1174 (0.1393) time: 3.3935 data: 0.0081 max mem: 33370 +Epoch: [4] [ 650/1319] eta: 0:37:44 lr: 4.491511094293352e-05 loss: 0.1348 (0.1397) time: 3.3920 data: 0.0082 max mem: 33370 +Epoch: [4] [ 660/1319] eta: 0:37:10 lr: 4.4906479415708236e-05 loss: 0.1343 (0.1395) time: 3.3998 data: 0.0084 max mem: 33370 +Epoch: [4] [ 670/1319] eta: 0:36:37 lr: 4.489784770413723e-05 loss: 0.1343 (0.1395) time: 3.4010 data: 0.0083 max mem: 33370 +Epoch: [4] [ 680/1319] eta: 0:36:03 lr: 4.48892158081772e-05 loss: 0.1384 (0.1396) time: 3.3963 data: 0.0081 max mem: 33370 +Epoch: [4] [ 690/1319] eta: 0:35:29 lr: 4.4880583727784795e-05 loss: 0.1389 (0.1399) time: 3.3922 data: 0.0078 max mem: 33370 +Epoch: [4] [ 700/1319] eta: 0:34:55 lr: 4.487195146291666e-05 loss: 0.1389 (0.1399) time: 3.4052 data: 0.0081 max mem: 33370 +Epoch: [4] [ 710/1319] eta: 0:34:22 lr: 4.486331901352942e-05 loss: 0.1262 (0.1398) time: 3.4178 data: 0.0084 max mem: 33370 +Epoch: [4] [ 720/1319] eta: 0:33:48 lr: 4.4854686379579686e-05 loss: 0.1262 (0.1398) time: 3.4104 data: 0.0082 max mem: 33370 +Epoch: [4] [ 730/1319] eta: 0:33:15 lr: 4.4846053561024035e-05 loss: 0.1186 (0.1394) time: 3.4131 data: 0.0081 max mem: 33370 +Epoch: [4] [ 740/1319] eta: 0:32:41 lr: 4.4837420557819036e-05 loss: 0.1197 (0.1394) time: 3.4092 data: 0.0081 max mem: 33370 +Epoch: [4] [ 750/1319] eta: 0:32:07 lr: 4.482878736992124e-05 loss: 0.1219 (0.1393) time: 3.4026 data: 0.0080 max mem: 33370 +Epoch: [4] [ 760/1319] eta: 0:31:33 lr: 4.4820153997287166e-05 loss: 0.1251 (0.1393) time: 3.4035 data: 0.0080 max mem: 33370 +Epoch: [4] [ 770/1319] eta: 0:30:59 lr: 4.481152043987333e-05 loss: 0.1335 (0.1394) time: 3.3843 data: 0.0080 max mem: 33370 +Epoch: [4] [ 780/1319] eta: 0:30:26 lr: 4.48028866976362e-05 loss: 0.1414 (0.1396) time: 3.3964 data: 0.0079 max mem: 33370 +Epoch: [4] [ 790/1319] eta: 0:29:52 lr: 4.4794252770532266e-05 loss: 0.1252 (0.1394) time: 3.3938 data: 0.0078 max mem: 33370 +Epoch: [4] [ 800/1319] eta: 0:29:18 lr: 4.4785618658517975e-05 loss: 0.1394 (0.1394) time: 3.3757 data: 0.0079 max mem: 33370 +Epoch: [4] [ 810/1319] eta: 0:28:44 lr: 4.477698436154974e-05 loss: 0.1339 (0.1392) time: 3.3791 data: 0.0082 max mem: 33370 +Epoch: [4] [ 820/1319] eta: 0:28:10 lr: 4.476834987958398e-05 loss: 0.1087 (0.1391) time: 3.3941 data: 0.0079 max mem: 33370 +Epoch: [4] [ 830/1319] eta: 0:27:36 lr: 4.4759715212577086e-05 loss: 0.1201 (0.1392) time: 3.4046 data: 0.0075 max mem: 33370 +Epoch: [4] [ 840/1319] eta: 0:27:02 lr: 4.475108036048542e-05 loss: 0.1398 (0.1393) time: 3.4022 data: 0.0075 max mem: 33370 +Epoch: [4] [ 850/1319] eta: 0:26:29 lr: 4.4742445323265344e-05 loss: 0.1398 (0.1394) time: 3.4029 data: 0.0078 max mem: 33370 +Epoch: [4] [ 860/1319] eta: 0:25:55 lr: 4.473381010087318e-05 loss: 0.1299 (0.1393) time: 3.3829 data: 0.0079 max mem: 33370 +Epoch: [4] [ 870/1319] eta: 0:25:21 lr: 4.4725174693265234e-05 loss: 0.1282 (0.1392) time: 3.3846 data: 0.0079 max mem: 33370 +Epoch: [4] [ 880/1319] eta: 0:24:47 lr: 4.471653910039782e-05 loss: 0.1394 (0.1394) time: 3.3918 data: 0.0082 max mem: 33370 +Epoch: [4] [ 890/1319] eta: 0:24:13 lr: 4.4707903322227184e-05 loss: 0.1373 (0.1394) time: 3.3819 data: 0.0081 max mem: 33370 +Epoch: [4] [ 900/1319] eta: 0:23:39 lr: 4.469926735870959e-05 loss: 0.1318 (0.1395) time: 3.3881 data: 0.0082 max mem: 33370 +Epoch: [4] [ 910/1319] eta: 0:23:05 lr: 4.4690631209801266e-05 loss: 0.1254 (0.1394) time: 3.3952 data: 0.0080 max mem: 33370 +Epoch: [4] [ 920/1319] eta: 0:22:31 lr: 4.4681994875458425e-05 loss: 0.1153 (0.1393) time: 3.3963 data: 0.0079 max mem: 33370 +Epoch: [4] [ 930/1319] eta: 0:21:58 lr: 4.467335835563727e-05 loss: 0.1188 (0.1390) time: 3.3942 data: 0.0081 max mem: 33370 +Epoch: [4] [ 940/1319] eta: 0:21:24 lr: 4.466472165029396e-05 loss: 0.1280 (0.1393) time: 3.3957 data: 0.0079 max mem: 33370 +Epoch: [4] [ 950/1319] eta: 0:20:50 lr: 4.4656084759384645e-05 loss: 0.1430 (0.1393) time: 3.4066 data: 0.0083 max mem: 33370 +Epoch: [4] [ 960/1319] eta: 0:20:16 lr: 4.464744768286547e-05 loss: 0.1414 (0.1393) time: 3.3986 data: 0.0084 max mem: 33370 +Epoch: [4] [ 970/1319] eta: 0:19:42 lr: 4.463881042069255e-05 loss: 0.1271 (0.1393) time: 3.3682 data: 0.0082 max mem: 33370 +Epoch: [4] [ 980/1319] eta: 0:19:08 lr: 4.463017297282197e-05 loss: 0.1214 (0.1391) time: 3.3718 data: 0.0078 max mem: 33370 +Epoch: [4] [ 990/1319] eta: 0:18:34 lr: 4.4621535339209816e-05 loss: 0.1312 (0.1391) time: 3.4074 data: 0.0078 max mem: 33370 +Epoch: [4] [1000/1319] eta: 0:18:01 lr: 4.461289751981212e-05 loss: 0.1366 (0.1390) time: 3.4113 data: 0.0082 max mem: 33370 +Epoch: [4] [1010/1319] eta: 0:17:27 lr: 4.460425951458493e-05 loss: 0.1441 (0.1391) time: 3.4020 data: 0.0079 max mem: 33370 +Epoch: [4] [1020/1319] eta: 0:16:53 lr: 4.459562132348427e-05 loss: 0.1540 (0.1392) time: 3.3852 data: 0.0079 max mem: 33370 +Epoch: [4] [1030/1319] eta: 0:16:19 lr: 4.458698294646612e-05 loss: 0.1248 (0.1390) time: 3.3858 data: 0.0082 max mem: 33370 +Epoch: [4] [1040/1319] eta: 0:15:45 lr: 4.457834438348646e-05 loss: 0.1167 (0.1388) time: 3.3654 data: 0.0084 max mem: 33370 +Epoch: [4] [1050/1319] eta: 0:15:11 lr: 4.456970563450125e-05 loss: 0.1239 (0.1388) time: 3.3580 data: 0.0082 max mem: 33370 +Epoch: [4] [1060/1319] eta: 0:14:37 lr: 4.456106669946641e-05 loss: 0.1219 (0.1387) time: 3.4152 data: 0.0081 max mem: 33370 +Epoch: [4] [1070/1319] eta: 0:14:03 lr: 4.4552427578337865e-05 loss: 0.1266 (0.1386) time: 3.4237 data: 0.0084 max mem: 33370 +Epoch: [4] [1080/1319] eta: 0:13:29 lr: 4.45437882710715e-05 loss: 0.1306 (0.1387) time: 3.3899 data: 0.0084 max mem: 33370 +Epoch: [4] [1090/1319] eta: 0:12:56 lr: 4.453514877762321e-05 loss: 0.1222 (0.1386) time: 3.3776 data: 0.0081 max mem: 33370 +Epoch: [4] [1100/1319] eta: 0:12:22 lr: 4.4526509097948836e-05 loss: 0.1204 (0.1385) time: 3.3950 data: 0.0081 max mem: 33370 +Epoch: [4] [1110/1319] eta: 0:11:48 lr: 4.451786923200421e-05 loss: 0.1240 (0.1386) time: 3.3994 data: 0.0084 max mem: 33370 +Epoch: [4] [1120/1319] eta: 0:11:14 lr: 4.450922917974515e-05 loss: 0.1326 (0.1387) time: 3.3793 data: 0.0087 max mem: 33370 +Epoch: [4] [1130/1319] eta: 0:10:40 lr: 4.4500588941127465e-05 loss: 0.1452 (0.1387) time: 3.4008 data: 0.0084 max mem: 33370 +Epoch: [4] [1140/1319] eta: 0:10:06 lr: 4.449194851610691e-05 loss: 0.1415 (0.1390) time: 3.4198 data: 0.0081 max mem: 33370 +Epoch: [4] [1150/1319] eta: 0:09:32 lr: 4.4483307904639245e-05 loss: 0.1339 (0.1390) time: 3.3884 data: 0.0084 max mem: 33370 +Epoch: [4] [1160/1319] eta: 0:08:58 lr: 4.447466710668021e-05 loss: 0.1214 (0.1391) time: 3.3851 data: 0.0081 max mem: 33370 +Epoch: [4] [1170/1319] eta: 0:08:25 lr: 4.4466026122185514e-05 loss: 0.1193 (0.1389) time: 3.4162 data: 0.0080 max mem: 33370 +Epoch: [4] [1180/1319] eta: 0:07:51 lr: 4.4457384951110855e-05 loss: 0.1223 (0.1390) time: 3.4194 data: 0.0082 max mem: 33370 +Epoch: [4] [1190/1319] eta: 0:07:17 lr: 4.44487435934119e-05 loss: 0.1312 (0.1389) time: 3.3815 data: 0.0079 max mem: 33370 +Epoch: [4] [1200/1319] eta: 0:06:43 lr: 4.4440102049044326e-05 loss: 0.1325 (0.1390) time: 3.3889 data: 0.0077 max mem: 33370 +Epoch: [4] [1210/1319] eta: 0:06:09 lr: 4.443146031796374e-05 loss: 0.1241 (0.1389) time: 3.3955 data: 0.0080 max mem: 33370 +Epoch: [4] [1220/1319] eta: 0:05:35 lr: 4.442281840012577e-05 loss: 0.1387 (0.1390) time: 3.3829 data: 0.0079 max mem: 33370 +Epoch: [4] [1230/1319] eta: 0:05:01 lr: 4.441417629548601e-05 loss: 0.1576 (0.1392) time: 3.3958 data: 0.0078 max mem: 33370 +Epoch: [4] [1240/1319] eta: 0:04:27 lr: 4.4405534004000035e-05 loss: 0.1520 (0.1393) time: 3.3965 data: 0.0080 max mem: 33370 +Epoch: [4] [1250/1319] eta: 0:03:53 lr: 4.439689152562339e-05 loss: 0.1517 (0.1394) time: 3.4001 data: 0.0079 max mem: 33370 +Epoch: [4] [1260/1319] eta: 0:03:19 lr: 4.438824886031161e-05 loss: 0.1453 (0.1395) time: 3.3920 data: 0.0078 max mem: 33370 +Epoch: [4] [1270/1319] eta: 0:02:46 lr: 4.437960600802022e-05 loss: 0.1366 (0.1394) time: 3.4077 data: 0.0077 max mem: 33370 +Epoch: [4] [1280/1319] eta: 0:02:12 lr: 4.4370962968704706e-05 loss: 0.1360 (0.1395) time: 3.4209 data: 0.0075 max mem: 33370 +Epoch: [4] [1290/1319] eta: 0:01:38 lr: 4.436231974232054e-05 loss: 0.1303 (0.1393) time: 3.3892 data: 0.0080 max mem: 33370 +Epoch: [4] [1300/1319] eta: 0:01:04 lr: 4.435367632882316e-05 loss: 0.1121 (0.1392) time: 3.3787 data: 0.0080 max mem: 33370 +Epoch: [4] [1310/1319] eta: 0:00:30 lr: 4.434503272816803e-05 loss: 0.1149 (0.1392) time: 3.3982 data: 0.0075 max mem: 33370 +Epoch: [4] Total time: 1:14:32 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 2:47:46 time: 3.9123 data: 3.8288 max mem: 33370 +Test: [ 100/2573] eta: 0:04:47 time: 0.0778 data: 0.0015 max mem: 33370 +Test: [ 200/2573] eta: 0:03:52 time: 0.0789 data: 0.0014 max mem: 33370 +Test: [ 300/2573] eta: 0:03:27 time: 0.0815 data: 0.0017 max mem: 33370 +Test: [ 400/2573] eta: 0:03:12 time: 0.0819 data: 0.0014 max mem: 33370 +Test: [ 500/2573] eta: 0:03:00 time: 0.0797 data: 0.0014 max mem: 33370 +Test: [ 600/2573] eta: 0:02:49 time: 0.0800 data: 0.0014 max mem: 33370 +Test: [ 700/2573] eta: 0:02:39 time: 0.0804 data: 0.0014 max mem: 33370 +Test: [ 800/2573] eta: 0:02:30 time: 0.0833 data: 0.0014 max mem: 33370 +Test: [ 900/2573] eta: 0:02:21 time: 0.0809 data: 0.0014 max mem: 33370 +Test: [1000/2573] eta: 0:02:12 time: 0.0806 data: 0.0015 max mem: 33370 +Test: [1100/2573] eta: 0:02:03 time: 0.0812 data: 0.0016 max mem: 33370 +Test: [1200/2573] eta: 0:01:54 time: 0.0801 data: 0.0013 max mem: 33370 +Test: [1300/2573] eta: 0:01:46 time: 0.0806 data: 0.0013 max mem: 33370 +Test: [1400/2573] eta: 0:01:37 time: 0.0784 data: 0.0015 max mem: 33370 +Test: [1500/2573] eta: 0:01:29 time: 0.0800 data: 0.0013 max mem: 33370 +Test: [1600/2573] eta: 0:01:20 time: 0.0851 data: 0.0016 max mem: 33370 +Test: [1700/2573] eta: 0:01:12 time: 0.0803 data: 0.0015 max mem: 33370 +Test: [1800/2573] eta: 0:01:03 time: 0.0819 data: 0.0014 max mem: 33370 +Test: [1900/2573] eta: 0:00:55 time: 0.0792 data: 0.0014 max mem: 33370 +Test: [2000/2573] eta: 0:00:47 time: 0.0804 data: 0.0015 max mem: 33370 +Test: [2100/2573] eta: 0:00:38 time: 0.0823 data: 0.0013 max mem: 33370 +Test: [2200/2573] eta: 0:00:30 time: 0.0825 data: 0.0015 max mem: 33370 +Test: [2300/2573] eta: 0:00:22 time: 0.0813 data: 0.0014 max mem: 33370 +Test: [2400/2573] eta: 0:00:14 time: 0.0784 data: 0.0015 max mem: 33370 +Test: [2500/2573] eta: 0:00:05 time: 0.0804 data: 0.0014 max mem: 33370 +Test: Total time: 0:03:31 +Final results: +Mean IoU is 48.79 + + precision@0.5 = 53.27 + precision@0.6 = 46.47 + precision@0.7 = 37.79 + precision@0.8 = 25.71 + precision@0.9 = 9.78 + overall IoU = 50.76 + +Average object IoU 48.78558121582876 +Overall IoU 50.76420211791992 +Better epoch: 4 + +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [5] [ 0/1319] eta: 1:55:31 lr: 4.433725332752167e-05 loss: 0.1609 (0.1609) time: 5.2555 data: 1.7794 max mem: 33370 +Epoch: [5] [ 10/1319] eta: 1:18:29 lr: 4.432860937114392e-05 loss: 0.0951 (0.1193) time: 3.5978 data: 0.1690 max mem: 33370 +Epoch: [5] [ 20/1319] eta: 1:15:41 lr: 4.4319965227479046e-05 loss: 0.1119 (0.1243) time: 3.4081 data: 0.0075 max mem: 33370 +Epoch: [5] [ 30/1319] eta: 1:14:25 lr: 4.43113208964824e-05 loss: 0.1119 (0.1232) time: 3.3904 data: 0.0079 max mem: 33370 +Epoch: [5] [ 40/1319] eta: 1:13:32 lr: 4.43026763781093e-05 loss: 0.1051 (0.1223) time: 3.4019 data: 0.0083 max mem: 33370 +Epoch: [5] [ 50/1319] eta: 1:12:45 lr: 4.429403167231508e-05 loss: 0.1297 (0.1268) time: 3.4025 data: 0.0077 max mem: 33370 +Epoch: [5] [ 60/1319] eta: 1:11:57 lr: 4.428538677905502e-05 loss: 0.1295 (0.1254) time: 3.3873 data: 0.0077 max mem: 33370 +Epoch: [5] [ 70/1319] eta: 1:11:18 lr: 4.4276741698284395e-05 loss: 0.1139 (0.1269) time: 3.3894 data: 0.0077 max mem: 33370 +Epoch: [5] [ 80/1319] eta: 1:10:44 lr: 4.4268096429958464e-05 loss: 0.1139 (0.1267) time: 3.4139 data: 0.0075 max mem: 33370 +Epoch: [5] [ 90/1319] eta: 1:10:07 lr: 4.425945097403244e-05 loss: 0.1130 (0.1276) time: 3.4149 data: 0.0079 max mem: 33370 +Epoch: [5] [ 100/1319] eta: 1:09:26 lr: 4.425080533046155e-05 loss: 0.1093 (0.1254) time: 3.3875 data: 0.0082 max mem: 33370 +Epoch: [5] [ 110/1319] eta: 1:08:48 lr: 4.424215949920098e-05 loss: 0.1093 (0.1262) time: 3.3752 data: 0.0081 max mem: 33370 +Epoch: [5] [ 120/1319] eta: 1:08:08 lr: 4.423351348020589e-05 loss: 0.1438 (0.1297) time: 3.3701 data: 0.0079 max mem: 33370 +Epoch: [5] [ 130/1319] eta: 1:07:30 lr: 4.4224867273431445e-05 loss: 0.1122 (0.1280) time: 3.3601 data: 0.0080 max mem: 33370 +Epoch: [5] [ 140/1319] eta: 1:06:51 lr: 4.421622087883277e-05 loss: 0.1095 (0.1286) time: 3.3535 data: 0.0084 max mem: 33370 +Epoch: [5] [ 150/1319] eta: 1:06:16 lr: 4.4207574296364965e-05 loss: 0.1095 (0.1270) time: 3.3698 data: 0.0083 max mem: 33370 +Epoch: [5] [ 160/1319] eta: 1:05:40 lr: 4.419892752598312e-05 loss: 0.0998 (0.1267) time: 3.3868 data: 0.0083 max mem: 33370 +Epoch: [5] [ 170/1319] eta: 1:05:07 lr: 4.419028056764231e-05 loss: 0.1237 (0.1271) time: 3.3947 data: 0.0088 max mem: 33370 +Epoch: [5] [ 180/1319] eta: 1:04:33 lr: 4.418163342129758e-05 loss: 0.1222 (0.1290) time: 3.4018 data: 0.0088 max mem: 33370 +Epoch: [5] [ 190/1319] eta: 1:03:56 lr: 4.417298608690395e-05 loss: 0.1161 (0.1287) time: 3.3796 data: 0.0084 max mem: 33370 +Epoch: [5] [ 200/1319] eta: 1:03:21 lr: 4.416433856441643e-05 loss: 0.1114 (0.1282) time: 3.3697 data: 0.0080 max mem: 33370 +Epoch: [5] [ 210/1319] eta: 1:02:44 lr: 4.415569085379001e-05 loss: 0.1114 (0.1280) time: 3.3604 data: 0.0081 max mem: 33370 +Epoch: [5] [ 220/1319] eta: 1:02:09 lr: 4.4147042954979643e-05 loss: 0.1147 (0.1281) time: 3.3595 data: 0.0088 max mem: 33370 +Epoch: [5] [ 230/1319] eta: 1:01:35 lr: 4.413839486794028e-05 loss: 0.1271 (0.1288) time: 3.3820 data: 0.0087 max mem: 33370 +Epoch: [5] [ 240/1319] eta: 1:01:01 lr: 4.412974659262685e-05 loss: 0.1271 (0.1287) time: 3.3914 data: 0.0080 max mem: 33370 +Epoch: [5] [ 250/1319] eta: 1:00:27 lr: 4.412109812899424e-05 loss: 0.1261 (0.1286) time: 3.3841 data: 0.0079 max mem: 33370 +Epoch: [5] [ 260/1319] eta: 0:59:52 lr: 4.411244947699735e-05 loss: 0.1280 (0.1287) time: 3.3800 data: 0.0080 max mem: 33370 +Epoch: [5] [ 270/1319] eta: 0:59:17 lr: 4.4103800636591036e-05 loss: 0.1213 (0.1284) time: 3.3708 data: 0.0079 max mem: 33370 +Epoch: [5] [ 280/1319] eta: 0:58:43 lr: 4.409515160773014e-05 loss: 0.1178 (0.1285) time: 3.3678 data: 0.0079 max mem: 33370 +Epoch: [5] [ 290/1319] eta: 0:58:07 lr: 4.408650239036947e-05 loss: 0.1197 (0.1289) time: 3.3666 data: 0.0084 max mem: 33370 +Epoch: [5] [ 300/1319] eta: 0:57:34 lr: 4.407785298446384e-05 loss: 0.1080 (0.1282) time: 3.3769 data: 0.0082 max mem: 33370 +Epoch: [5] [ 310/1319] eta: 0:57:01 lr: 4.406920338996803e-05 loss: 0.1023 (0.1279) time: 3.4072 data: 0.0079 max mem: 33370 +Epoch: [5] [ 320/1319] eta: 0:56:27 lr: 4.406055360683679e-05 loss: 0.1056 (0.1278) time: 3.4019 data: 0.0080 max mem: 33370 +Epoch: [5] [ 330/1319] eta: 0:55:53 lr: 4.4051903635024855e-05 loss: 0.1221 (0.1279) time: 3.3950 data: 0.0081 max mem: 33370 +Epoch: [5] [ 340/1319] eta: 0:55:19 lr: 4.404325347448695e-05 loss: 0.1230 (0.1278) time: 3.3963 data: 0.0079 max mem: 33370 +Epoch: [5] [ 350/1319] eta: 0:54:45 lr: 4.403460312517776e-05 loss: 0.1152 (0.1275) time: 3.3850 data: 0.0081 max mem: 33370 +Epoch: [5] [ 360/1319] eta: 0:54:12 lr: 4.402595258705198e-05 loss: 0.1268 (0.1278) time: 3.4013 data: 0.0082 max mem: 33370 +Epoch: [5] [ 370/1319] eta: 0:53:38 lr: 4.401730186006425e-05 loss: 0.1281 (0.1281) time: 3.4031 data: 0.0080 max mem: 33370 +Epoch: [5] [ 380/1319] eta: 0:53:04 lr: 4.40086509441692e-05 loss: 0.1267 (0.1283) time: 3.3925 data: 0.0079 max mem: 33370 +Epoch: [5] [ 390/1319] eta: 0:52:32 lr: 4.399999983932147e-05 loss: 0.1258 (0.1280) time: 3.4309 data: 0.0080 max mem: 33370 +Epoch: [5] [ 400/1319] eta: 0:52:00 lr: 4.399134854547561e-05 loss: 0.1213 (0.1278) time: 3.4609 data: 0.0077 max mem: 33370 +Epoch: [5] [ 410/1319] eta: 0:51:26 lr: 4.3982697062586214e-05 loss: 0.1072 (0.1279) time: 3.4264 data: 0.0077 max mem: 33370 +Epoch: [5] [ 420/1319] eta: 0:50:51 lr: 4.397404539060784e-05 loss: 0.1072 (0.1277) time: 3.3772 data: 0.0082 max mem: 33370 +Epoch: [5] [ 430/1319] eta: 0:50:18 lr: 4.3965393529495005e-05 loss: 0.1055 (0.1273) time: 3.3956 data: 0.0087 max mem: 33370 +Epoch: [5] [ 440/1319] eta: 0:49:44 lr: 4.3956741479202226e-05 loss: 0.1283 (0.1274) time: 3.4147 data: 0.0084 max mem: 33370 +Epoch: [5] [ 450/1319] eta: 0:49:10 lr: 4.3948089239683975e-05 loss: 0.1334 (0.1277) time: 3.3995 data: 0.0079 max mem: 33370 +Epoch: [5] [ 460/1319] eta: 0:48:36 lr: 4.3939436810894734e-05 loss: 0.1345 (0.1280) time: 3.3940 data: 0.0080 max mem: 33370 +Epoch: [5] [ 470/1319] eta: 0:48:02 lr: 4.393078419278895e-05 loss: 0.1298 (0.1277) time: 3.3960 data: 0.0080 max mem: 33370 +Epoch: [5] [ 480/1319] eta: 0:47:28 lr: 4.3922131385321036e-05 loss: 0.1162 (0.1275) time: 3.4088 data: 0.0080 max mem: 33370 +Epoch: [5] [ 490/1319] eta: 0:46:55 lr: 4.3913478388445405e-05 loss: 0.1195 (0.1277) time: 3.4108 data: 0.0079 max mem: 33370 +Epoch: [5] [ 500/1319] eta: 0:46:21 lr: 4.390482520211644e-05 loss: 0.1223 (0.1274) time: 3.3989 data: 0.0081 max mem: 33370 +Epoch: [5] [ 510/1319] eta: 0:45:46 lr: 4.389617182628851e-05 loss: 0.1264 (0.1275) time: 3.3859 data: 0.0082 max mem: 33370 +Epoch: [5] [ 520/1319] eta: 0:45:13 lr: 4.3887518260915935e-05 loss: 0.1264 (0.1277) time: 3.3970 data: 0.0080 max mem: 33370 +Epoch: [5] [ 530/1319] eta: 0:44:38 lr: 4.3878864505953046e-05 loss: 0.1059 (0.1272) time: 3.3920 data: 0.0083 max mem: 33370 +Epoch: [5] [ 540/1319] eta: 0:44:04 lr: 4.387021056135415e-05 loss: 0.1193 (0.1276) time: 3.3651 data: 0.0086 max mem: 33370 +Epoch: [5] [ 550/1319] eta: 0:43:30 lr: 4.386155642707351e-05 loss: 0.1245 (0.1277) time: 3.3767 data: 0.0082 max mem: 33370 +Epoch: [5] [ 560/1319] eta: 0:42:56 lr: 4.3852902103065404e-05 loss: 0.1042 (0.1274) time: 3.3956 data: 0.0077 max mem: 33370 +Epoch: [5] [ 570/1319] eta: 0:42:22 lr: 4.3844247589284045e-05 loss: 0.1073 (0.1272) time: 3.3795 data: 0.0075 max mem: 33370 +Epoch: [5] [ 580/1319] eta: 0:41:47 lr: 4.383559288568366e-05 loss: 0.1330 (0.1274) time: 3.3565 data: 0.0075 max mem: 33370 +Epoch: [5] [ 590/1319] eta: 0:41:13 lr: 4.382693799221843e-05 loss: 0.1331 (0.1275) time: 3.3717 data: 0.0079 max mem: 33370 +Epoch: [5] [ 600/1319] eta: 0:40:39 lr: 4.381828290884256e-05 loss: 0.1298 (0.1276) time: 3.3884 data: 0.0080 max mem: 33370 +Epoch: [5] [ 610/1319] eta: 0:40:05 lr: 4.380962763551017e-05 loss: 0.1133 (0.1274) time: 3.3829 data: 0.0078 max mem: 33370 +Epoch: [5] [ 620/1319] eta: 0:39:31 lr: 4.38009721721754e-05 loss: 0.1127 (0.1273) time: 3.3702 data: 0.0084 max mem: 33370 +Epoch: [5] [ 630/1319] eta: 0:38:57 lr: 4.3792316518792354e-05 loss: 0.1119 (0.1269) time: 3.3775 data: 0.0083 max mem: 33370 +Epoch: [5] [ 640/1319] eta: 0:38:23 lr: 4.378366067531513e-05 loss: 0.1150 (0.1269) time: 3.3988 data: 0.0076 max mem: 33370 +Epoch: [5] [ 650/1319] eta: 0:37:49 lr: 4.37750046416978e-05 loss: 0.1124 (0.1266) time: 3.3811 data: 0.0081 max mem: 33370 +Epoch: [5] [ 660/1319] eta: 0:37:15 lr: 4.376634841789439e-05 loss: 0.1133 (0.1268) time: 3.3711 data: 0.0083 max mem: 33370 +Epoch: [5] [ 670/1319] eta: 0:36:41 lr: 4.375769200385893e-05 loss: 0.1409 (0.1271) time: 3.4048 data: 0.0077 max mem: 33370 +Epoch: [5] [ 680/1319] eta: 0:36:07 lr: 4.3749035399545434e-05 loss: 0.1275 (0.1272) time: 3.3763 data: 0.0078 max mem: 33370 +Epoch: [5] [ 690/1319] eta: 0:35:33 lr: 4.374037860490788e-05 loss: 0.1284 (0.1272) time: 3.3698 data: 0.0081 max mem: 33370 +Epoch: [5] [ 700/1319] eta: 0:34:59 lr: 4.373172161990022e-05 loss: 0.1293 (0.1278) time: 3.4178 data: 0.0084 max mem: 33370 +Epoch: [5] [ 710/1319] eta: 0:34:25 lr: 4.372306444447641e-05 loss: 0.1350 (0.1279) time: 3.3933 data: 0.0085 max mem: 33370 +Epoch: [5] [ 720/1319] eta: 0:33:51 lr: 4.3714407078590355e-05 loss: 0.1310 (0.1279) time: 3.3694 data: 0.0080 max mem: 33370 +Epoch: [5] [ 730/1319] eta: 0:33:17 lr: 4.370574952219595e-05 loss: 0.1310 (0.1282) time: 3.3811 data: 0.0080 max mem: 33370 +Epoch: [5] [ 740/1319] eta: 0:32:43 lr: 4.369709177524708e-05 loss: 0.1265 (0.1283) time: 3.3737 data: 0.0083 max mem: 33370 +Epoch: [5] [ 750/1319] eta: 0:32:09 lr: 4.36884338376976e-05 loss: 0.1262 (0.1283) time: 3.3627 data: 0.0082 max mem: 33370 +Epoch: [5] [ 760/1319] eta: 0:31:35 lr: 4.3679775709501325e-05 loss: 0.1326 (0.1283) time: 3.3580 data: 0.0081 max mem: 33370 +Epoch: [5] [ 770/1319] eta: 0:31:01 lr: 4.3671117390612085e-05 loss: 0.1302 (0.1284) time: 3.3695 data: 0.0083 max mem: 33370 +Epoch: [5] [ 780/1319] eta: 0:30:27 lr: 4.366245888098367e-05 loss: 0.1095 (0.1286) time: 3.3930 data: 0.0086 max mem: 33370 +Epoch: [5] [ 790/1319] eta: 0:29:53 lr: 4.3653800180569845e-05 loss: 0.1194 (0.1287) time: 3.4015 data: 0.0086 max mem: 33370 +Epoch: [5] [ 800/1319] eta: 0:29:19 lr: 4.364514128932435e-05 loss: 0.1302 (0.1286) time: 3.3993 data: 0.0085 max mem: 33370 +Epoch: [5] [ 810/1319] eta: 0:28:45 lr: 4.363648220720092e-05 loss: 0.1183 (0.1283) time: 3.3848 data: 0.0081 max mem: 33370 +Epoch: [5] [ 820/1319] eta: 0:28:11 lr: 4.3627822934153263e-05 loss: 0.1072 (0.1283) time: 3.3657 data: 0.0083 max mem: 33370 +Epoch: [5] [ 830/1319] eta: 0:27:37 lr: 4.361916347013505e-05 loss: 0.1072 (0.1283) time: 3.3630 data: 0.0088 max mem: 33370 +Epoch: [5] [ 840/1319] eta: 0:27:03 lr: 4.361050381509995e-05 loss: 0.1051 (0.1282) time: 3.4000 data: 0.0083 max mem: 33370 +Epoch: [5] [ 850/1319] eta: 0:26:29 lr: 4.3601843969001596e-05 loss: 0.1146 (0.1282) time: 3.3799 data: 0.0080 max mem: 33370 +Epoch: [5] [ 860/1319] eta: 0:25:55 lr: 4.359318393179363e-05 loss: 0.1130 (0.1282) time: 3.3741 data: 0.0080 max mem: 33370 +Epoch: [5] [ 870/1319] eta: 0:25:21 lr: 4.3584523703429616e-05 loss: 0.1149 (0.1283) time: 3.3827 data: 0.0077 max mem: 33370 +Epoch: [5] [ 880/1319] eta: 0:24:47 lr: 4.357586328386315e-05 loss: 0.1185 (0.1283) time: 3.3503 data: 0.0084 max mem: 33370 +Epoch: [5] [ 890/1319] eta: 0:24:13 lr: 4.356720267304778e-05 loss: 0.1106 (0.1283) time: 3.3628 data: 0.0084 max mem: 33370 +Epoch: [5] [ 900/1319] eta: 0:23:39 lr: 4.3558541870937056e-05 loss: 0.1119 (0.1282) time: 3.3792 data: 0.0081 max mem: 33370 +Epoch: [5] [ 910/1319] eta: 0:23:06 lr: 4.354988087748445e-05 loss: 0.1036 (0.1278) time: 3.3878 data: 0.0084 max mem: 33370 +Epoch: [5] [ 920/1319] eta: 0:22:32 lr: 4.35412196926435e-05 loss: 0.1036 (0.1280) time: 3.3778 data: 0.0085 max mem: 33370 +Epoch: [5] [ 930/1319] eta: 0:21:58 lr: 4.353255831636764e-05 loss: 0.1261 (0.1281) time: 3.3624 data: 0.0081 max mem: 33370 +Epoch: [5] [ 940/1319] eta: 0:21:24 lr: 4.352389674861032e-05 loss: 0.1253 (0.1282) time: 3.3567 data: 0.0077 max mem: 33370 +Epoch: [5] [ 950/1319] eta: 0:20:50 lr: 4.3515234989324975e-05 loss: 0.1253 (0.1284) time: 3.3640 data: 0.0079 max mem: 33370 +Epoch: [5] [ 960/1319] eta: 0:20:16 lr: 4.350657303846501e-05 loss: 0.1254 (0.1284) time: 3.3605 data: 0.0080 max mem: 33370 +Epoch: [5] [ 970/1319] eta: 0:19:42 lr: 4.34979108959838e-05 loss: 0.1145 (0.1284) time: 3.3814 data: 0.0084 max mem: 33370 +Epoch: [5] [ 980/1319] eta: 0:19:08 lr: 4.348924856183469e-05 loss: 0.1245 (0.1287) time: 3.3932 data: 0.0085 max mem: 33370 +Epoch: [5] [ 990/1319] eta: 0:18:34 lr: 4.348058603597104e-05 loss: 0.1164 (0.1287) time: 3.4000 data: 0.0084 max mem: 33370 +Epoch: [5] [1000/1319] eta: 0:18:00 lr: 4.347192331834616e-05 loss: 0.1124 (0.1287) time: 3.4241 data: 0.0084 max mem: 33370 +Epoch: [5] [1010/1319] eta: 0:17:27 lr: 4.346326040891335e-05 loss: 0.1312 (0.1286) time: 3.4210 data: 0.0081 max mem: 33370 +Epoch: [5] [1020/1319] eta: 0:16:53 lr: 4.345459730762588e-05 loss: 0.1312 (0.1289) time: 3.3995 data: 0.0081 max mem: 33370 +Epoch: [5] [1030/1319] eta: 0:16:19 lr: 4.344593401443699e-05 loss: 0.1320 (0.1289) time: 3.3954 data: 0.0080 max mem: 33370 +Epoch: [5] [1040/1319] eta: 0:15:45 lr: 4.343727052929992e-05 loss: 0.1254 (0.1288) time: 3.3903 data: 0.0079 max mem: 33370 +Epoch: [5] [1050/1319] eta: 0:15:11 lr: 4.342860685216788e-05 loss: 0.1224 (0.1288) time: 3.3740 data: 0.0082 max mem: 33370 +Epoch: [5] [1060/1319] eta: 0:14:37 lr: 4.341994298299405e-05 loss: 0.1194 (0.1287) time: 3.3528 data: 0.0083 max mem: 33370 +Epoch: [5] [1070/1319] eta: 0:14:03 lr: 4.341127892173159e-05 loss: 0.1320 (0.1288) time: 3.3792 data: 0.0080 max mem: 33370 +Epoch: [5] [1080/1319] eta: 0:13:29 lr: 4.3402614668333656e-05 loss: 0.1299 (0.1287) time: 3.3995 data: 0.0081 max mem: 33370 +Epoch: [5] [1090/1319] eta: 0:12:55 lr: 4.339395022275336e-05 loss: 0.1148 (0.1287) time: 3.3623 data: 0.0079 max mem: 33370 +Epoch: [5] [1100/1319] eta: 0:12:21 lr: 4.33852855849438e-05 loss: 0.1013 (0.1285) time: 3.3727 data: 0.0078 max mem: 33370 +Epoch: [5] [1110/1319] eta: 0:11:48 lr: 4.337662075485806e-05 loss: 0.1013 (0.1283) time: 3.4128 data: 0.0081 max mem: 33370 +Epoch: [5] [1120/1319] eta: 0:11:14 lr: 4.3367955732449175e-05 loss: 0.1043 (0.1283) time: 3.4138 data: 0.0080 max mem: 33370 +Epoch: [5] [1130/1319] eta: 0:10:40 lr: 4.3359290517670206e-05 loss: 0.1230 (0.1282) time: 3.3902 data: 0.0080 max mem: 33370 +Epoch: [5] [1140/1319] eta: 0:10:06 lr: 4.335062511047415e-05 loss: 0.1230 (0.1283) time: 3.3837 data: 0.0084 max mem: 33370 +Epoch: [5] [1150/1319] eta: 0:09:32 lr: 4.3341959510813994e-05 loss: 0.1319 (0.1283) time: 3.3854 data: 0.0081 max mem: 33370 +Epoch: [5] [1160/1319] eta: 0:08:58 lr: 4.33332937186427e-05 loss: 0.1205 (0.1281) time: 3.3834 data: 0.0079 max mem: 33370 +Epoch: [5] [1170/1319] eta: 0:08:24 lr: 4.332462773391324e-05 loss: 0.1240 (0.1281) time: 3.3434 data: 0.0078 max mem: 33370 +Epoch: [5] [1180/1319] eta: 0:07:50 lr: 4.331596155657851e-05 loss: 0.1257 (0.1281) time: 3.3430 data: 0.0080 max mem: 33370 +Epoch: [5] [1190/1319] eta: 0:07:16 lr: 4.3307295186591415e-05 loss: 0.1238 (0.1283) time: 3.3859 data: 0.0081 max mem: 33370 +Epoch: [5] [1200/1319] eta: 0:06:43 lr: 4.329862862390485e-05 loss: 0.1405 (0.1285) time: 3.3789 data: 0.0078 max mem: 33370 +Epoch: [5] [1210/1319] eta: 0:06:09 lr: 4.328996186847165e-05 loss: 0.1365 (0.1285) time: 3.3553 data: 0.0079 max mem: 33370 +Epoch: [5] [1220/1319] eta: 0:05:35 lr: 4.328129492024467e-05 loss: 0.1213 (0.1285) time: 3.3764 data: 0.0082 max mem: 33370 +Epoch: [5] [1230/1319] eta: 0:05:01 lr: 4.3272627779176715e-05 loss: 0.1127 (0.1284) time: 3.4163 data: 0.0081 max mem: 33370 +Epoch: [5] [1240/1319] eta: 0:04:27 lr: 4.326396044522058e-05 loss: 0.1098 (0.1284) time: 3.3968 data: 0.0081 max mem: 33370 +Epoch: [5] [1250/1319] eta: 0:03:53 lr: 4.3255292918329036e-05 loss: 0.1209 (0.1284) time: 3.3544 data: 0.0085 max mem: 33370 +Epoch: [5] [1260/1319] eta: 0:03:19 lr: 4.324662519845482e-05 loss: 0.1307 (0.1285) time: 3.3553 data: 0.0087 max mem: 33370 +Epoch: [5] [1270/1319] eta: 0:02:45 lr: 4.323795728555066e-05 loss: 0.1309 (0.1285) time: 3.3909 data: 0.0086 max mem: 33370 +Epoch: [5] [1280/1319] eta: 0:02:12 lr: 4.322928917956926e-05 loss: 0.1196 (0.1285) time: 3.4086 data: 0.0082 max mem: 33370 +Epoch: [5] [1290/1319] eta: 0:01:38 lr: 4.322062088046332e-05 loss: 0.1202 (0.1285) time: 3.3884 data: 0.0079 max mem: 33370 +Epoch: [5] [1300/1319] eta: 0:01:04 lr: 4.321195238818547e-05 loss: 0.1202 (0.1286) time: 3.3689 data: 0.0079 max mem: 33370 +Epoch: [5] [1310/1319] eta: 0:00:30 lr: 4.3203283702688355e-05 loss: 0.1144 (0.1284) time: 3.3653 data: 0.0077 max mem: 33370 +Epoch: [5] Total time: 1:14:27 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 3:15:26 time: 4.5577 data: 4.3881 max mem: 33370 +Test: [ 100/2573] eta: 0:04:57 time: 0.0756 data: 0.0014 max mem: 33370 +Test: [ 200/2573] eta: 0:03:55 time: 0.0776 data: 0.0015 max mem: 33370 +Test: [ 300/2573] eta: 0:03:28 time: 0.0795 data: 0.0015 max mem: 33370 +Test: [ 400/2573] eta: 0:03:11 time: 0.0794 data: 0.0014 max mem: 33370 +Test: [ 500/2573] eta: 0:02:58 time: 0.0780 data: 0.0014 max mem: 33370 +Test: [ 600/2573] eta: 0:02:47 time: 0.0787 data: 0.0015 max mem: 33370 +Test: [ 700/2573] eta: 0:02:37 time: 0.0788 data: 0.0015 max mem: 33370 +Test: [ 800/2573] eta: 0:02:28 time: 0.0818 data: 0.0014 max mem: 33370 +Test: [ 900/2573] eta: 0:02:19 time: 0.0782 data: 0.0014 max mem: 33370 +Test: [1000/2573] eta: 0:02:10 time: 0.0796 data: 0.0016 max mem: 33370 +Test: [1100/2573] eta: 0:02:01 time: 0.0792 data: 0.0015 max mem: 33370 +Test: [1200/2573] eta: 0:01:52 time: 0.0791 data: 0.0015 max mem: 33370 +Test: [1300/2573] eta: 0:01:44 time: 0.0788 data: 0.0014 max mem: 33370 +Test: [1400/2573] eta: 0:01:35 time: 0.0778 data: 0.0015 max mem: 33370 +Test: [1500/2573] eta: 0:01:27 time: 0.0800 data: 0.0015 max mem: 33370 +Test: [1600/2573] eta: 0:01:19 time: 0.0826 data: 0.0014 max mem: 33370 +Test: [1700/2573] eta: 0:01:11 time: 0.0779 data: 0.0014 max mem: 33370 +Test: [1800/2573] eta: 0:01:02 time: 0.0809 data: 0.0014 max mem: 33370 +Test: [1900/2573] eta: 0:00:54 time: 0.0783 data: 0.0014 max mem: 33370 +Test: [2000/2573] eta: 0:00:46 time: 0.0799 data: 0.0014 max mem: 33370 +Test: [2100/2573] eta: 0:00:38 time: 0.0820 data: 0.0015 max mem: 33370 +Test: [2200/2573] eta: 0:00:30 time: 0.0814 data: 0.0014 max mem: 33370 +Test: [2300/2573] eta: 0:00:22 time: 0.0810 data: 0.0014 max mem: 33370 +Test: [2400/2573] eta: 0:00:13 time: 0.0773 data: 0.0014 max mem: 33370 +Test: [2500/2573] eta: 0:00:05 time: 0.0806 data: 0.0014 max mem: 33370 +Test: Total time: 0:03:28 +Final results: +Mean IoU is 54.52 + + precision@0.5 = 60.46 + precision@0.6 = 52.86 + precision@0.7 = 43.10 + precision@0.8 = 30.39 + precision@0.9 = 11.95 + overall IoU = 54.85 + +Average object IoU 54.51717272082166 +Overall IoU 54.84678268432617 +Better epoch: 5 + +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [6] [ 0/1319] eta: 1:58:52 lr: 4.319548172049932e-05 loss: 0.0693 (0.0693) time: 5.4074 data: 1.9390 max mem: 33370 +Epoch: [6] [ 10/1319] eta: 1:18:31 lr: 4.318681266775505e-05 loss: 0.1120 (0.1168) time: 3.5996 data: 0.1842 max mem: 33370 +Epoch: [6] [ 20/1319] eta: 1:15:41 lr: 4.317814342165404e-05 loss: 0.1046 (0.1131) time: 3.4007 data: 0.0079 max mem: 33370 +Epoch: [6] [ 30/1319] eta: 1:14:17 lr: 4.316947398214883e-05 loss: 0.1011 (0.1080) time: 3.3802 data: 0.0076 max mem: 33370 +Epoch: [6] [ 40/1319] eta: 1:13:23 lr: 4.316080434919196e-05 loss: 0.1056 (0.1111) time: 3.3872 data: 0.0084 max mem: 33370 +Epoch: [6] [ 50/1319] eta: 1:12:43 lr: 4.315213452273593e-05 loss: 0.0937 (0.1069) time: 3.4082 data: 0.0086 max mem: 33370 +Epoch: [6] [ 60/1319] eta: 1:11:51 lr: 4.314346450273323e-05 loss: 0.0940 (0.1099) time: 3.3870 data: 0.0084 max mem: 33370 +Epoch: [6] [ 70/1319] eta: 1:11:16 lr: 4.313479428913631e-05 loss: 0.1157 (0.1122) time: 3.3858 data: 0.0080 max mem: 33370 +Epoch: [6] [ 80/1319] eta: 1:10:36 lr: 4.312612388189762e-05 loss: 0.0949 (0.1093) time: 3.4043 data: 0.0079 max mem: 33370 +Epoch: [6] [ 90/1319] eta: 1:09:59 lr: 4.311745328096956e-05 loss: 0.0949 (0.1110) time: 3.3925 data: 0.0079 max mem: 33370 +Epoch: [6] [ 100/1319] eta: 1:09:25 lr: 4.3108782486304546e-05 loss: 0.0985 (0.1097) time: 3.4072 data: 0.0078 max mem: 33370 +Epoch: [6] [ 110/1319] eta: 1:08:43 lr: 4.310011149785494e-05 loss: 0.0985 (0.1097) time: 3.3828 data: 0.0080 max mem: 33370 +Epoch: [6] [ 120/1319] eta: 1:08:04 lr: 4.309144031557308e-05 loss: 0.1035 (0.1105) time: 3.3509 data: 0.0083 max mem: 33370 +Epoch: [6] [ 130/1319] eta: 1:07:22 lr: 4.308276893941131e-05 loss: 0.0996 (0.1102) time: 3.3385 data: 0.0082 max mem: 33370 +Epoch: [6] [ 140/1319] eta: 1:06:46 lr: 4.307409736932192e-05 loss: 0.0854 (0.1093) time: 3.3482 data: 0.0084 max mem: 33370 +Epoch: [6] [ 150/1319] eta: 1:06:16 lr: 4.306542560525721e-05 loss: 0.0905 (0.1098) time: 3.4133 data: 0.0083 max mem: 33370 +Epoch: [6] [ 160/1319] eta: 1:05:41 lr: 4.305675364716942e-05 loss: 0.1113 (0.1101) time: 3.4180 data: 0.0079 max mem: 33370 +Epoch: [6] [ 170/1319] eta: 1:05:04 lr: 4.3048081495010805e-05 loss: 0.1164 (0.1114) time: 3.3752 data: 0.0080 max mem: 33370 +Epoch: [6] [ 180/1319] eta: 1:04:27 lr: 4.303940914873357e-05 loss: 0.1209 (0.1116) time: 3.3564 data: 0.0085 max mem: 33370 +Epoch: [6] [ 190/1319] eta: 1:03:52 lr: 4.30307366082899e-05 loss: 0.1103 (0.1114) time: 3.3621 data: 0.0084 max mem: 33370 +Epoch: [6] [ 200/1319] eta: 1:03:17 lr: 4.302206387363197e-05 loss: 0.1039 (0.1118) time: 3.3774 data: 0.0081 max mem: 33370 +Epoch: [6] [ 210/1319] eta: 1:02:42 lr: 4.301339094471194e-05 loss: 0.1256 (0.1125) time: 3.3706 data: 0.0080 max mem: 33370 +Epoch: [6] [ 220/1319] eta: 1:02:07 lr: 4.300471782148193e-05 loss: 0.1204 (0.1137) time: 3.3755 data: 0.0079 max mem: 33370 +Epoch: [6] [ 230/1319] eta: 1:01:31 lr: 4.299604450389403e-05 loss: 0.1099 (0.1147) time: 3.3640 data: 0.0080 max mem: 33370 +Epoch: [6] [ 240/1319] eta: 1:00:57 lr: 4.298737099190034e-05 loss: 0.1119 (0.1154) time: 3.3626 data: 0.0079 max mem: 33370 +Epoch: [6] [ 250/1319] eta: 1:00:23 lr: 4.297869728545289e-05 loss: 0.1016 (0.1147) time: 3.3876 data: 0.0085 max mem: 33370 +Epoch: [6] [ 260/1319] eta: 0:59:49 lr: 4.2970023384503735e-05 loss: 0.1035 (0.1147) time: 3.3848 data: 0.0088 max mem: 33370 +Epoch: [6] [ 270/1319] eta: 0:59:14 lr: 4.296134928900489e-05 loss: 0.1115 (0.1155) time: 3.3770 data: 0.0088 max mem: 33370 +Epoch: [6] [ 280/1319] eta: 0:58:40 lr: 4.295267499890832e-05 loss: 0.1065 (0.1158) time: 3.3753 data: 0.0085 max mem: 33370 +Epoch: [6] [ 290/1319] eta: 0:58:06 lr: 4.2944000514166015e-05 loss: 0.1071 (0.1160) time: 3.3847 data: 0.0081 max mem: 33370 +Epoch: [6] [ 300/1319] eta: 0:57:32 lr: 4.293532583472992e-05 loss: 0.0980 (0.1154) time: 3.3846 data: 0.0079 max mem: 33370 +Epoch: [6] [ 310/1319] eta: 0:56:57 lr: 4.292665096055194e-05 loss: 0.0993 (0.1152) time: 3.3699 data: 0.0080 max mem: 33370 +Epoch: [6] [ 320/1319] eta: 0:56:22 lr: 4.2917975891583976e-05 loss: 0.1085 (0.1149) time: 3.3505 data: 0.0081 max mem: 33370 +Epoch: [6] [ 330/1319] eta: 0:55:48 lr: 4.2909300627777926e-05 loss: 0.1102 (0.1155) time: 3.3640 data: 0.0078 max mem: 33370 +Epoch: [6] [ 340/1319] eta: 0:55:15 lr: 4.290062516908562e-05 loss: 0.1229 (0.1158) time: 3.3928 data: 0.0077 max mem: 33370 +Epoch: [6] [ 350/1319] eta: 0:54:41 lr: 4.2891949515458894e-05 loss: 0.1224 (0.1158) time: 3.4050 data: 0.0084 max mem: 33370 +Epoch: [6] [ 360/1319] eta: 0:54:08 lr: 4.288327366684957e-05 loss: 0.1092 (0.1161) time: 3.4097 data: 0.0089 max mem: 33370 +Epoch: [6] [ 370/1319] eta: 0:53:34 lr: 4.287459762320942e-05 loss: 0.0927 (0.1153) time: 3.4005 data: 0.0080 max mem: 33370 +Epoch: [6] [ 380/1319] eta: 0:53:01 lr: 4.28659213844902e-05 loss: 0.0964 (0.1156) time: 3.3947 data: 0.0076 max mem: 33370 +Epoch: [6] [ 390/1319] eta: 0:52:26 lr: 4.285724495064366e-05 loss: 0.1146 (0.1161) time: 3.3729 data: 0.0081 max mem: 33370 +Epoch: [6] [ 400/1319] eta: 0:51:52 lr: 4.2848568321621514e-05 loss: 0.1132 (0.1162) time: 3.3674 data: 0.0084 max mem: 33370 +Epoch: [6] [ 410/1319] eta: 0:51:19 lr: 4.283989149737546e-05 loss: 0.1121 (0.1163) time: 3.3965 data: 0.0082 max mem: 33370 +Epoch: [6] [ 420/1319] eta: 0:50:44 lr: 4.283121447785717e-05 loss: 0.1253 (0.1167) time: 3.3801 data: 0.0082 max mem: 33370 +Epoch: [6] [ 430/1319] eta: 0:50:10 lr: 4.2822537263018285e-05 loss: 0.1146 (0.1168) time: 3.3754 data: 0.0082 max mem: 33370 +Epoch: [6] [ 440/1319] eta: 0:49:37 lr: 4.281385985281043e-05 loss: 0.1003 (0.1163) time: 3.3995 data: 0.0081 max mem: 33370 +Epoch: [6] [ 450/1319] eta: 0:49:04 lr: 4.280518224718522e-05 loss: 0.1059 (0.1163) time: 3.4184 data: 0.0084 max mem: 33370 +Epoch: [6] [ 460/1319] eta: 0:48:31 lr: 4.2796504446094225e-05 loss: 0.1106 (0.1162) time: 3.4335 data: 0.0085 max mem: 33370 +Epoch: [6] [ 470/1319] eta: 0:47:57 lr: 4.278782644948901e-05 loss: 0.1106 (0.1164) time: 3.4098 data: 0.0082 max mem: 33370 +Epoch: [6] [ 480/1319] eta: 0:47:23 lr: 4.27791482573211e-05 loss: 0.1110 (0.1163) time: 3.4014 data: 0.0080 max mem: 33370 +Epoch: [6] [ 490/1319] eta: 0:46:50 lr: 4.2770469869541996e-05 loss: 0.0953 (0.1157) time: 3.4159 data: 0.0081 max mem: 33370 +Epoch: [6] [ 500/1319] eta: 0:46:16 lr: 4.276179128610321e-05 loss: 0.0789 (0.1150) time: 3.4003 data: 0.0082 max mem: 33370 +Epoch: [6] [ 510/1319] eta: 0:45:42 lr: 4.2753112506956194e-05 loss: 0.0900 (0.1150) time: 3.3771 data: 0.0078 max mem: 33370 +Epoch: [6] [ 520/1319] eta: 0:45:07 lr: 4.274443353205239e-05 loss: 0.1198 (0.1149) time: 3.3669 data: 0.0076 max mem: 33370 +Epoch: [6] [ 530/1319] eta: 0:44:34 lr: 4.2735754361343224e-05 loss: 0.1119 (0.1149) time: 3.3735 data: 0.0077 max mem: 33370 +Epoch: [6] [ 540/1319] eta: 0:44:00 lr: 4.2727074994780086e-05 loss: 0.1137 (0.1153) time: 3.3893 data: 0.0080 max mem: 33370 +Epoch: [6] [ 550/1319] eta: 0:43:25 lr: 4.271839543231435e-05 loss: 0.1111 (0.1150) time: 3.3779 data: 0.0082 max mem: 33370 +Epoch: [6] [ 560/1319] eta: 0:42:51 lr: 4.270971567389736e-05 loss: 0.1089 (0.1149) time: 3.3742 data: 0.0079 max mem: 33370 +Epoch: [6] [ 570/1319] eta: 0:42:18 lr: 4.270103571948045e-05 loss: 0.1114 (0.1148) time: 3.4010 data: 0.0079 max mem: 33370 +Epoch: [6] [ 580/1319] eta: 0:41:44 lr: 4.2692355569014936e-05 loss: 0.1114 (0.1149) time: 3.3950 data: 0.0082 max mem: 33370 +Epoch: [6] [ 590/1319] eta: 0:41:10 lr: 4.268367522245208e-05 loss: 0.1186 (0.1149) time: 3.3774 data: 0.0081 max mem: 33370 +Epoch: [6] [ 600/1319] eta: 0:40:36 lr: 4.267499467974314e-05 loss: 0.1097 (0.1148) time: 3.3988 data: 0.0078 max mem: 33370 +Epoch: [6] [ 610/1319] eta: 0:40:02 lr: 4.2666313940839357e-05 loss: 0.1054 (0.1149) time: 3.3674 data: 0.0082 max mem: 33370 +Epoch: [6] [ 620/1319] eta: 0:39:28 lr: 4.2657633005691946e-05 loss: 0.1090 (0.1151) time: 3.3458 data: 0.0086 max mem: 33370 +Epoch: [6] [ 630/1319] eta: 0:38:53 lr: 4.264895187425208e-05 loss: 0.1252 (0.1152) time: 3.3683 data: 0.0089 max mem: 33370 +Epoch: [6] [ 640/1319] eta: 0:38:19 lr: 4.264027054647094e-05 loss: 0.1079 (0.1150) time: 3.3618 data: 0.0088 max mem: 33370 +Epoch: [6] [ 650/1319] eta: 0:37:45 lr: 4.263158902229967e-05 loss: 0.0978 (0.1147) time: 3.3662 data: 0.0092 max mem: 33370 +Epoch: [6] [ 660/1319] eta: 0:37:11 lr: 4.262290730168937e-05 loss: 0.1005 (0.1155) time: 3.3733 data: 0.0095 max mem: 33370 +Epoch: [6] [ 670/1319] eta: 0:36:37 lr: 4.261422538459115e-05 loss: 0.0932 (0.1152) time: 3.3832 data: 0.0087 max mem: 33370 +Epoch: [6] [ 680/1319] eta: 0:36:04 lr: 4.260554327095607e-05 loss: 0.0862 (0.1152) time: 3.3868 data: 0.0083 max mem: 33370 +Epoch: [6] [ 690/1319] eta: 0:35:29 lr: 4.2596860960735204e-05 loss: 0.1269 (0.1154) time: 3.3710 data: 0.0080 max mem: 33370 +Epoch: [6] [ 700/1319] eta: 0:34:55 lr: 4.258817845387955e-05 loss: 0.1269 (0.1154) time: 3.3620 data: 0.0080 max mem: 33370 +Epoch: [6] [ 710/1319] eta: 0:34:22 lr: 4.257949575034011e-05 loss: 0.1032 (0.1153) time: 3.3754 data: 0.0082 max mem: 33370 +Epoch: [6] [ 720/1319] eta: 0:33:47 lr: 4.257081285006789e-05 loss: 0.0914 (0.1152) time: 3.3680 data: 0.0081 max mem: 33370 +Epoch: [6] [ 730/1319] eta: 0:33:13 lr: 4.256212975301382e-05 loss: 0.1002 (0.1153) time: 3.3481 data: 0.0079 max mem: 33370 +Epoch: [6] [ 740/1319] eta: 0:32:39 lr: 4.255344645912884e-05 loss: 0.1204 (0.1157) time: 3.3642 data: 0.0080 max mem: 33370 +Epoch: [6] [ 750/1319] eta: 0:32:06 lr: 4.254476296836386e-05 loss: 0.0976 (0.1155) time: 3.3862 data: 0.0080 max mem: 33370 +Epoch: [6] [ 760/1319] eta: 0:31:31 lr: 4.253607928066978e-05 loss: 0.0972 (0.1159) time: 3.3602 data: 0.0083 max mem: 33370 +Epoch: [6] [ 770/1319] eta: 0:30:57 lr: 4.252739539599743e-05 loss: 0.1115 (0.1163) time: 3.3630 data: 0.0082 max mem: 33370 +Epoch: [6] [ 780/1319] eta: 0:30:24 lr: 4.2518711314297674e-05 loss: 0.1080 (0.1167) time: 3.3960 data: 0.0077 max mem: 33370 +Epoch: [6] [ 790/1319] eta: 0:29:50 lr: 4.2510027035521314e-05 loss: 0.1191 (0.1171) time: 3.3796 data: 0.0077 max mem: 33370 +Epoch: [6] [ 800/1319] eta: 0:29:16 lr: 4.250134255961916e-05 loss: 0.1193 (0.1172) time: 3.3950 data: 0.0080 max mem: 33370 +Epoch: [6] [ 810/1319] eta: 0:28:42 lr: 4.2492657886541955e-05 loss: 0.1193 (0.1173) time: 3.4034 data: 0.0085 max mem: 33370 +Epoch: [6] [ 820/1319] eta: 0:28:08 lr: 4.2483973016240455e-05 loss: 0.1186 (0.1174) time: 3.3858 data: 0.0086 max mem: 33370 +Epoch: [6] [ 830/1319] eta: 0:27:35 lr: 4.247528794866539e-05 loss: 0.1111 (0.1178) time: 3.3821 data: 0.0083 max mem: 33370 +Epoch: [6] [ 840/1319] eta: 0:27:01 lr: 4.2466602683767445e-05 loss: 0.1111 (0.1178) time: 3.3631 data: 0.0083 max mem: 33370 +Epoch: [6] [ 850/1319] eta: 0:26:27 lr: 4.24579172214973e-05 loss: 0.1274 (0.1179) time: 3.3557 data: 0.0082 max mem: 33370 +Epoch: [6] [ 860/1319] eta: 0:25:53 lr: 4.244923156180561e-05 loss: 0.1162 (0.1180) time: 3.3757 data: 0.0080 max mem: 33370 +Epoch: [6] [ 870/1319] eta: 0:25:19 lr: 4.2440545704643e-05 loss: 0.1073 (0.1178) time: 3.3689 data: 0.0078 max mem: 33370 +Epoch: [6] [ 880/1319] eta: 0:24:45 lr: 4.243185964996007e-05 loss: 0.1133 (0.1179) time: 3.3888 data: 0.0081 max mem: 33370 +Epoch: [6] [ 890/1319] eta: 0:24:11 lr: 4.24231733977074e-05 loss: 0.1133 (0.1179) time: 3.4068 data: 0.0085 max mem: 33370 +Epoch: [6] [ 900/1319] eta: 0:23:38 lr: 4.2414486947835554e-05 loss: 0.1061 (0.1179) time: 3.3931 data: 0.0083 max mem: 33370 +Epoch: [6] [ 910/1319] eta: 0:23:04 lr: 4.240580030029505e-05 loss: 0.0971 (0.1179) time: 3.3950 data: 0.0078 max mem: 33370 +Epoch: [6] [ 920/1319] eta: 0:22:30 lr: 4.239711345503641e-05 loss: 0.1060 (0.1179) time: 3.3701 data: 0.0083 max mem: 33370 +Epoch: [6] [ 930/1319] eta: 0:21:56 lr: 4.2388426412010114e-05 loss: 0.0970 (0.1179) time: 3.3582 data: 0.0085 max mem: 33370 +Epoch: [6] [ 940/1319] eta: 0:21:22 lr: 4.237973917116662e-05 loss: 0.0970 (0.1179) time: 3.3672 data: 0.0080 max mem: 33370 +Epoch: [6] [ 950/1319] eta: 0:20:48 lr: 4.237105173245638e-05 loss: 0.1042 (0.1179) time: 3.3546 data: 0.0082 max mem: 33370 +Epoch: [6] [ 960/1319] eta: 0:20:14 lr: 4.23623640958298e-05 loss: 0.1041 (0.1178) time: 3.3592 data: 0.0082 max mem: 33370 +Epoch: [6] [ 970/1319] eta: 0:19:40 lr: 4.235367626123727e-05 loss: 0.1041 (0.1180) time: 3.3600 data: 0.0082 max mem: 33370 +Epoch: [6] [ 980/1319] eta: 0:19:06 lr: 4.234498822862916e-05 loss: 0.0989 (0.1178) time: 3.3651 data: 0.0083 max mem: 33370 +Epoch: [6] [ 990/1319] eta: 0:18:32 lr: 4.23362999979558e-05 loss: 0.1105 (0.1178) time: 3.3957 data: 0.0084 max mem: 33370 +Epoch: [6] [1000/1319] eta: 0:17:59 lr: 4.2327611569167524e-05 loss: 0.1109 (0.1178) time: 3.3774 data: 0.0082 max mem: 33370 +Epoch: [6] [1010/1319] eta: 0:17:25 lr: 4.2318922942214635e-05 loss: 0.1071 (0.1177) time: 3.3885 data: 0.0084 max mem: 33370 +Epoch: [6] [1020/1319] eta: 0:16:51 lr: 4.231023411704738e-05 loss: 0.1108 (0.1178) time: 3.4020 data: 0.0083 max mem: 33370 +Epoch: [6] [1030/1319] eta: 0:16:17 lr: 4.230154509361603e-05 loss: 0.1208 (0.1179) time: 3.3578 data: 0.0078 max mem: 33370 +Epoch: [6] [1040/1319] eta: 0:15:43 lr: 4.229285587187079e-05 loss: 0.1086 (0.1178) time: 3.3828 data: 0.0078 max mem: 33370 +Epoch: [6] [1050/1319] eta: 0:15:10 lr: 4.2284166451761876e-05 loss: 0.1251 (0.1180) time: 3.4105 data: 0.0079 max mem: 33370 +Epoch: [6] [1060/1319] eta: 0:14:36 lr: 4.2275476833239456e-05 loss: 0.1183 (0.1181) time: 3.3845 data: 0.0079 max mem: 33370 +Epoch: [6] [1070/1319] eta: 0:14:02 lr: 4.2266787016253686e-05 loss: 0.0938 (0.1180) time: 3.3915 data: 0.0080 max mem: 33370 +Epoch: [6] [1080/1319] eta: 0:13:28 lr: 4.22580970007547e-05 loss: 0.0972 (0.1182) time: 3.3805 data: 0.0079 max mem: 33370 +Epoch: [6] [1090/1319] eta: 0:12:54 lr: 4.224940678669259e-05 loss: 0.1175 (0.1181) time: 3.3633 data: 0.0083 max mem: 33370 +Epoch: [6] [1100/1319] eta: 0:12:20 lr: 4.2240716374017434e-05 loss: 0.1187 (0.1185) time: 3.3534 data: 0.0081 max mem: 33370 +Epoch: [6] [1110/1319] eta: 0:11:46 lr: 4.2232025762679314e-05 loss: 0.1167 (0.1185) time: 3.3588 data: 0.0079 max mem: 33370 +Epoch: [6] [1120/1319] eta: 0:11:13 lr: 4.2223334952628234e-05 loss: 0.1021 (0.1183) time: 3.3934 data: 0.0083 max mem: 33370 +Epoch: [6] [1130/1319] eta: 0:10:39 lr: 4.221464394381422e-05 loss: 0.1046 (0.1182) time: 3.3992 data: 0.0082 max mem: 33370 +Epoch: [6] [1140/1319] eta: 0:10:05 lr: 4.220595273618725e-05 loss: 0.1046 (0.1181) time: 3.3938 data: 0.0086 max mem: 33370 +Epoch: [6] [1150/1319] eta: 0:09:31 lr: 4.2197261329697285e-05 loss: 0.0957 (0.1180) time: 3.3919 data: 0.0086 max mem: 33370 +Epoch: [6] [1160/1319] eta: 0:08:57 lr: 4.218856972429426e-05 loss: 0.1014 (0.1179) time: 3.3736 data: 0.0083 max mem: 33370 +Epoch: [6] [1170/1319] eta: 0:08:24 lr: 4.2179877919928104e-05 loss: 0.1058 (0.1180) time: 3.3619 data: 0.0086 max mem: 33370 +Epoch: [6] [1180/1319] eta: 0:07:50 lr: 4.217118591654868e-05 loss: 0.1074 (0.1180) time: 3.3506 data: 0.0082 max mem: 33370 +Epoch: [6] [1190/1319] eta: 0:07:16 lr: 4.2162493714105874e-05 loss: 0.1012 (0.1179) time: 3.3502 data: 0.0081 max mem: 33370 +Epoch: [6] [1200/1319] eta: 0:06:42 lr: 4.2153801312549505e-05 loss: 0.0992 (0.1177) time: 3.3647 data: 0.0081 max mem: 33370 +Epoch: [6] [1210/1319] eta: 0:06:08 lr: 4.2145108711829405e-05 loss: 0.0860 (0.1175) time: 3.3763 data: 0.0079 max mem: 33370 +Epoch: [6] [1220/1319] eta: 0:05:34 lr: 4.213641591189537e-05 loss: 0.0816 (0.1172) time: 3.3917 data: 0.0080 max mem: 33370 +Epoch: [6] [1230/1319] eta: 0:05:00 lr: 4.212772291269716e-05 loss: 0.1022 (0.1173) time: 3.3762 data: 0.0080 max mem: 33370 +Epoch: [6] [1240/1319] eta: 0:04:27 lr: 4.2119029714184504e-05 loss: 0.1224 (0.1175) time: 3.3544 data: 0.0078 max mem: 33370 +Epoch: [6] [1250/1319] eta: 0:03:53 lr: 4.211033631630714e-05 loss: 0.1346 (0.1176) time: 3.3631 data: 0.0079 max mem: 33370 +Epoch: [6] [1260/1319] eta: 0:03:19 lr: 4.2101642719014764e-05 loss: 0.1218 (0.1175) time: 3.3873 data: 0.0079 max mem: 33370 +Epoch: [6] [1270/1319] eta: 0:02:45 lr: 4.2092948922257045e-05 loss: 0.1263 (0.1178) time: 3.4114 data: 0.0077 max mem: 33370 +Epoch: [6] [1280/1319] eta: 0:02:11 lr: 4.208425492598362e-05 loss: 0.1361 (0.1179) time: 3.3872 data: 0.0078 max mem: 33370 +Epoch: [6] [1290/1319] eta: 0:01:38 lr: 4.207556073014412e-05 loss: 0.1317 (0.1181) time: 3.3695 data: 0.0079 max mem: 33370 +Epoch: [6] [1300/1319] eta: 0:01:04 lr: 4.2066866334688144e-05 loss: 0.1250 (0.1181) time: 3.3988 data: 0.0080 max mem: 33370 +Epoch: [6] [1310/1319] eta: 0:00:30 lr: 4.205817173956526e-05 loss: 0.1148 (0.1181) time: 3.3869 data: 0.0078 max mem: 33370 +Epoch: [6] Total time: 1:14:21 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 2:36:03 time: 3.6391 data: 3.5536 max mem: 33370 +Test: [ 100/2573] eta: 0:04:38 time: 0.0768 data: 0.0014 max mem: 33370 +Test: [ 200/2573] eta: 0:03:48 time: 0.0786 data: 0.0014 max mem: 33370 +Test: [ 300/2573] eta: 0:03:24 time: 0.0803 data: 0.0014 max mem: 33370 +Test: [ 400/2573] eta: 0:03:09 time: 0.0814 data: 0.0015 max mem: 33370 +Test: [ 500/2573] eta: 0:02:57 time: 0.0796 data: 0.0014 max mem: 33370 +Test: [ 600/2573] eta: 0:02:47 time: 0.0801 data: 0.0015 max mem: 33370 +Test: [ 700/2573] eta: 0:02:38 time: 0.0800 data: 0.0015 max mem: 33370 +Test: [ 800/2573] eta: 0:02:28 time: 0.0828 data: 0.0014 max mem: 33370 +Test: [ 900/2573] eta: 0:02:19 time: 0.0796 data: 0.0014 max mem: 33370 +Test: [1000/2573] eta: 0:02:10 time: 0.0790 data: 0.0014 max mem: 33370 +Test: [1100/2573] eta: 0:02:02 time: 0.0801 data: 0.0015 max mem: 33370 +Test: [1200/2573] eta: 0:01:53 time: 0.0798 data: 0.0014 max mem: 33370 +Test: [1300/2573] eta: 0:01:45 time: 0.0808 data: 0.0015 max mem: 33370 +Test: [1400/2573] eta: 0:01:36 time: 0.0777 data: 0.0014 max mem: 33370 +Test: [1500/2573] eta: 0:01:28 time: 0.0798 data: 0.0014 max mem: 33370 +Test: [1600/2573] eta: 0:01:19 time: 0.0831 data: 0.0014 max mem: 33370 +Test: [1700/2573] eta: 0:01:11 time: 0.0788 data: 0.0014 max mem: 33370 +Test: [1800/2573] eta: 0:01:03 time: 0.0813 data: 0.0014 max mem: 33370 +Test: [1900/2573] eta: 0:00:54 time: 0.0793 data: 0.0015 max mem: 33370 +Test: [2000/2573] eta: 0:00:46 time: 0.0812 data: 0.0016 max mem: 33370 +Test: [2100/2573] eta: 0:00:38 time: 0.0812 data: 0.0014 max mem: 33370 +Test: [2200/2573] eta: 0:00:30 time: 0.0810 data: 0.0014 max mem: 33370 +Test: [2300/2573] eta: 0:00:22 time: 0.0823 data: 0.0015 max mem: 33370 +Test: [2400/2573] eta: 0:00:14 time: 0.0777 data: 0.0015 max mem: 33370 +Test: [2500/2573] eta: 0:00:05 time: 0.0794 data: 0.0014 max mem: 33370 +Test: Total time: 0:03:29 +Final results: +Mean IoU is 57.03 + + precision@0.5 = 63.01 + precision@0.6 = 56.00 + precision@0.7 = 46.79 + precision@0.8 = 34.25 + precision@0.9 = 13.68 + overall IoU = 57.05 + +Average object IoU 57.025778214390165 +Overall IoU 57.054344177246094 +Better epoch: 6 + +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [7] [ 0/1319] eta: 2:00:17 lr: 4.205034643319776e-05 loss: 0.0790 (0.0790) time: 5.4717 data: 1.9067 max mem: 33370 +Epoch: [7] [ 10/1319] eta: 1:19:02 lr: 4.204165145856875e-05 loss: 0.0790 (0.0969) time: 3.6232 data: 0.1813 max mem: 33370 +Epoch: [7] [ 20/1319] eta: 1:16:04 lr: 4.203295628412646e-05 loss: 0.0869 (0.0938) time: 3.4160 data: 0.0076 max mem: 33370 +Epoch: [7] [ 30/1319] eta: 1:14:38 lr: 4.202426090982037e-05 loss: 0.0897 (0.0959) time: 3.3922 data: 0.0078 max mem: 33370 +Epoch: [7] [ 40/1319] eta: 1:13:24 lr: 4.201556533559993e-05 loss: 0.0897 (0.0967) time: 3.3696 data: 0.0087 max mem: 33370 +Epoch: [7] [ 50/1319] eta: 1:12:34 lr: 4.2006869561414584e-05 loss: 0.0901 (0.1011) time: 3.3652 data: 0.0082 max mem: 33370 +Epoch: [7] [ 60/1319] eta: 1:11:45 lr: 4.199817358721372e-05 loss: 0.1040 (0.1010) time: 3.3704 data: 0.0078 max mem: 33370 +Epoch: [7] [ 70/1319] eta: 1:11:12 lr: 4.1989477412946735e-05 loss: 0.1157 (0.1045) time: 3.3922 data: 0.0078 max mem: 33370 +Epoch: [7] [ 80/1319] eta: 1:10:33 lr: 4.1980781038562975e-05 loss: 0.1113 (0.1034) time: 3.4102 data: 0.0079 max mem: 33370 +Epoch: [7] [ 90/1319] eta: 1:09:57 lr: 4.1972084464011784e-05 loss: 0.1093 (0.1030) time: 3.3960 data: 0.0078 max mem: 33370 +Epoch: [7] [ 100/1319] eta: 1:09:21 lr: 4.1963387689242456e-05 loss: 0.0883 (0.1028) time: 3.3997 data: 0.0079 max mem: 33370 +Epoch: [7] [ 110/1319] eta: 1:08:51 lr: 4.1954690714204276e-05 loss: 0.0894 (0.1024) time: 3.4284 data: 0.0084 max mem: 33370 +Epoch: [7] [ 120/1319] eta: 1:08:16 lr: 4.194599353884651e-05 loss: 0.0975 (0.1043) time: 3.4300 data: 0.0084 max mem: 33370 +Epoch: [7] [ 130/1319] eta: 1:07:29 lr: 4.193729616311839e-05 loss: 0.0975 (0.1053) time: 3.3406 data: 0.0085 max mem: 33370 +Epoch: [7] [ 140/1319] eta: 1:06:50 lr: 4.1928598586969124e-05 loss: 0.1210 (0.1086) time: 3.3146 data: 0.0086 max mem: 33370 +Epoch: [7] [ 150/1319] eta: 1:06:16 lr: 4.1919900810347894e-05 loss: 0.1052 (0.1075) time: 3.3737 data: 0.0080 max mem: 33370 +Epoch: [7] [ 160/1319] eta: 1:05:44 lr: 4.191120283320388e-05 loss: 0.0962 (0.1080) time: 3.4117 data: 0.0078 max mem: 33370 +Epoch: [7] [ 170/1319] eta: 1:05:11 lr: 4.190250465548619e-05 loss: 0.0977 (0.1075) time: 3.4232 data: 0.0078 max mem: 33370 +Epoch: [7] [ 180/1319] eta: 1:04:39 lr: 4.189380627714394e-05 loss: 0.0977 (0.1078) time: 3.4314 data: 0.0080 max mem: 33370 +Epoch: [7] [ 190/1319] eta: 1:04:05 lr: 4.188510769812624e-05 loss: 0.0949 (0.1077) time: 3.4213 data: 0.0079 max mem: 33370 +Epoch: [7] [ 200/1319] eta: 1:03:31 lr: 4.1876408918382123e-05 loss: 0.1066 (0.1075) time: 3.4008 data: 0.0082 max mem: 33370 +Epoch: [7] [ 210/1319] eta: 1:02:53 lr: 4.1867709937860646e-05 loss: 0.1071 (0.1071) time: 3.3731 data: 0.0088 max mem: 33370 +Epoch: [7] [ 220/1319] eta: 1:02:17 lr: 4.185901075651081e-05 loss: 0.0914 (0.1071) time: 3.3500 data: 0.0087 max mem: 33370 +Epoch: [7] [ 230/1319] eta: 1:01:41 lr: 4.185031137428161e-05 loss: 0.0946 (0.1072) time: 3.3565 data: 0.0080 max mem: 33370 +Epoch: [7] [ 240/1319] eta: 1:01:05 lr: 4.1841611791121996e-05 loss: 0.0953 (0.1072) time: 3.3569 data: 0.0080 max mem: 33370 +Epoch: [7] [ 250/1319] eta: 1:00:29 lr: 4.183291200698093e-05 loss: 0.0835 (0.1067) time: 3.3598 data: 0.0083 max mem: 33370 +Epoch: [7] [ 260/1319] eta: 0:59:54 lr: 4.182421202180731e-05 loss: 0.0894 (0.1065) time: 3.3627 data: 0.0080 max mem: 33370 +Epoch: [7] [ 270/1319] eta: 0:59:19 lr: 4.181551183555002e-05 loss: 0.1059 (0.1070) time: 3.3577 data: 0.0083 max mem: 33370 +Epoch: [7] [ 280/1319] eta: 0:58:43 lr: 4.180681144815793e-05 loss: 0.1232 (0.1080) time: 3.3550 data: 0.0085 max mem: 33370 +Epoch: [7] [ 290/1319] eta: 0:58:10 lr: 4.179811085957988e-05 loss: 0.1030 (0.1077) time: 3.3795 data: 0.0081 max mem: 33370 +Epoch: [7] [ 300/1319] eta: 0:57:35 lr: 4.178941006976469e-05 loss: 0.0890 (0.1072) time: 3.3872 data: 0.0078 max mem: 33370 +Epoch: [7] [ 310/1319] eta: 0:57:01 lr: 4.1780709078661134e-05 loss: 0.1019 (0.1069) time: 3.3703 data: 0.0077 max mem: 33370 +Epoch: [7] [ 320/1319] eta: 0:56:27 lr: 4.177200788621799e-05 loss: 0.1053 (0.1070) time: 3.3865 data: 0.0078 max mem: 33370 +Epoch: [7] [ 330/1319] eta: 0:55:51 lr: 4.176330649238398e-05 loss: 0.0938 (0.1068) time: 3.3651 data: 0.0080 max mem: 33370 +Epoch: [7] [ 340/1319] eta: 0:55:17 lr: 4.175460489710785e-05 loss: 0.0984 (0.1082) time: 3.3435 data: 0.0081 max mem: 33370 +Epoch: [7] [ 350/1319] eta: 0:54:42 lr: 4.174590310033826e-05 loss: 0.1008 (0.1085) time: 3.3624 data: 0.0083 max mem: 33370 +Epoch: [7] [ 360/1319] eta: 0:54:09 lr: 4.173720110202388e-05 loss: 0.0915 (0.1081) time: 3.3855 data: 0.0087 max mem: 33370 +Epoch: [7] [ 370/1319] eta: 0:53:34 lr: 4.172849890211337e-05 loss: 0.0926 (0.1084) time: 3.3872 data: 0.0087 max mem: 33370 +Epoch: [7] [ 380/1319] eta: 0:52:59 lr: 4.171979650055532e-05 loss: 0.1077 (0.1087) time: 3.3583 data: 0.0083 max mem: 33370 +Epoch: [7] [ 390/1319] eta: 0:52:26 lr: 4.171109389729833e-05 loss: 0.1043 (0.1082) time: 3.3758 data: 0.0081 max mem: 33370 +Epoch: [7] [ 400/1319] eta: 0:51:51 lr: 4.1702391092290966e-05 loss: 0.0942 (0.1085) time: 3.3755 data: 0.0081 max mem: 33370 +Epoch: [7] [ 410/1319] eta: 0:51:17 lr: 4.169368808548177e-05 loss: 0.1097 (0.1087) time: 3.3508 data: 0.0080 max mem: 33370 +Epoch: [7] [ 420/1319] eta: 0:50:42 lr: 4.168498487681925e-05 loss: 0.1098 (0.1087) time: 3.3436 data: 0.0079 max mem: 33370 +Epoch: [7] [ 430/1319] eta: 0:50:08 lr: 4.1676281466251895e-05 loss: 0.0975 (0.1084) time: 3.3573 data: 0.0080 max mem: 33370 +Epoch: [7] [ 440/1319] eta: 0:49:34 lr: 4.166757785372817e-05 loss: 0.0973 (0.1082) time: 3.3837 data: 0.0081 max mem: 33370 +Epoch: [7] [ 450/1319] eta: 0:49:00 lr: 4.1658874039196515e-05 loss: 0.1048 (0.1084) time: 3.3807 data: 0.0082 max mem: 33370 +Epoch: [7] [ 460/1319] eta: 0:48:27 lr: 4.165017002260535e-05 loss: 0.0938 (0.1085) time: 3.3903 data: 0.0082 max mem: 33370 +Epoch: [7] [ 470/1319] eta: 0:47:52 lr: 4.164146580390306e-05 loss: 0.1024 (0.1087) time: 3.3862 data: 0.0085 max mem: 33370 +Epoch: [7] [ 480/1319] eta: 0:47:18 lr: 4.163276138303801e-05 loss: 0.1054 (0.1089) time: 3.3726 data: 0.0085 max mem: 33370 +Epoch: [7] [ 490/1319] eta: 0:46:45 lr: 4.1624056759958536e-05 loss: 0.0970 (0.1092) time: 3.4007 data: 0.0083 max mem: 33370 +Epoch: [7] [ 500/1319] eta: 0:46:12 lr: 4.161535193461295e-05 loss: 0.0902 (0.1092) time: 3.4226 data: 0.0082 max mem: 33370 +Epoch: [7] [ 510/1319] eta: 0:45:38 lr: 4.1606646906949546e-05 loss: 0.1103 (0.1093) time: 3.3903 data: 0.0080 max mem: 33370 +Epoch: [7] [ 520/1319] eta: 0:45:04 lr: 4.159794167691658e-05 loss: 0.1147 (0.1098) time: 3.3609 data: 0.0079 max mem: 33370 +Epoch: [7] [ 530/1319] eta: 0:44:29 lr: 4.158923624446229e-05 loss: 0.1235 (0.1098) time: 3.3560 data: 0.0081 max mem: 33370 +Epoch: [7] [ 540/1319] eta: 0:43:56 lr: 4.15805306095349e-05 loss: 0.1002 (0.1095) time: 3.3876 data: 0.0082 max mem: 33370 +Epoch: [7] [ 550/1319] eta: 0:43:22 lr: 4.1571824772082586e-05 loss: 0.0851 (0.1094) time: 3.4044 data: 0.0084 max mem: 33370 +Epoch: [7] [ 560/1319] eta: 0:42:48 lr: 4.156311873205351e-05 loss: 0.0793 (0.1090) time: 3.3702 data: 0.0083 max mem: 33370 +Epoch: [7] [ 570/1319] eta: 0:42:14 lr: 4.1554412489395805e-05 loss: 0.0854 (0.1087) time: 3.3557 data: 0.0077 max mem: 33370 +Epoch: [7] [ 580/1319] eta: 0:41:39 lr: 4.15457060440576e-05 loss: 0.0933 (0.1086) time: 3.3512 data: 0.0078 max mem: 33370 +Epoch: [7] [ 590/1319] eta: 0:41:06 lr: 4.1536999395986964e-05 loss: 0.1159 (0.1089) time: 3.3715 data: 0.0081 max mem: 33370 +Epoch: [7] [ 600/1319] eta: 0:40:31 lr: 4.152829254513196e-05 loss: 0.1136 (0.1089) time: 3.3369 data: 0.0081 max mem: 33370 +Epoch: [7] [ 610/1319] eta: 0:39:57 lr: 4.151958549144062e-05 loss: 0.1021 (0.1090) time: 3.3487 data: 0.0079 max mem: 33370 +Epoch: [7] [ 620/1319] eta: 0:39:24 lr: 4.151087823486097e-05 loss: 0.1038 (0.1090) time: 3.4035 data: 0.0082 max mem: 33370 +Epoch: [7] [ 630/1319] eta: 0:38:49 lr: 4.1502170775340975e-05 loss: 0.1038 (0.1091) time: 3.3569 data: 0.0083 max mem: 33370 +Epoch: [7] [ 640/1319] eta: 0:38:15 lr: 4.14934631128286e-05 loss: 0.1044 (0.1090) time: 3.3490 data: 0.0078 max mem: 33370 +Epoch: [7] [ 650/1319] eta: 0:37:41 lr: 4.148475524727178e-05 loss: 0.0994 (0.1091) time: 3.3732 data: 0.0079 max mem: 33370 +Epoch: [7] [ 660/1319] eta: 0:37:07 lr: 4.147604717861842e-05 loss: 0.0946 (0.1093) time: 3.3702 data: 0.0081 max mem: 33370 +Epoch: [7] [ 670/1319] eta: 0:36:34 lr: 4.14673389068164e-05 loss: 0.1074 (0.1093) time: 3.3806 data: 0.0080 max mem: 33370 +Epoch: [7] [ 680/1319] eta: 0:35:59 lr: 4.145863043181359e-05 loss: 0.1080 (0.1092) time: 3.3615 data: 0.0083 max mem: 33370 +Epoch: [7] [ 690/1319] eta: 0:35:26 lr: 4.144992175355781e-05 loss: 0.0968 (0.1091) time: 3.3572 data: 0.0083 max mem: 33370 +Epoch: [7] [ 700/1319] eta: 0:34:52 lr: 4.1441212871996857e-05 loss: 0.1039 (0.1091) time: 3.3777 data: 0.0082 max mem: 33370 +Epoch: [7] [ 710/1319] eta: 0:34:18 lr: 4.143250378707853e-05 loss: 0.1039 (0.1091) time: 3.3909 data: 0.0086 max mem: 33370 +Epoch: [7] [ 720/1319] eta: 0:33:44 lr: 4.142379449875057e-05 loss: 0.0973 (0.1090) time: 3.3826 data: 0.0083 max mem: 33370 +Epoch: [7] [ 730/1319] eta: 0:33:10 lr: 4.141508500696071e-05 loss: 0.0933 (0.1090) time: 3.3748 data: 0.0081 max mem: 33370 +Epoch: [7] [ 740/1319] eta: 0:32:37 lr: 4.140637531165665e-05 loss: 0.1074 (0.1090) time: 3.3907 data: 0.0086 max mem: 33370 +Epoch: [7] [ 750/1319] eta: 0:32:03 lr: 4.139766541278606e-05 loss: 0.1183 (0.1093) time: 3.3725 data: 0.0084 max mem: 33370 +Epoch: [7] [ 760/1319] eta: 0:31:29 lr: 4.138895531029661e-05 loss: 0.1101 (0.1092) time: 3.3529 data: 0.0081 max mem: 33370 +Epoch: [7] [ 770/1319] eta: 0:30:55 lr: 4.138024500413592e-05 loss: 0.0865 (0.1091) time: 3.3571 data: 0.0081 max mem: 33370 +Epoch: [7] [ 780/1319] eta: 0:30:21 lr: 4.137153449425158e-05 loss: 0.0983 (0.1092) time: 3.3562 data: 0.0079 max mem: 33370 +Epoch: [7] [ 790/1319] eta: 0:29:47 lr: 4.136282378059117e-05 loss: 0.0983 (0.1090) time: 3.3514 data: 0.0081 max mem: 33370 +Epoch: [7] [ 800/1319] eta: 0:29:13 lr: 4.1354112863102244e-05 loss: 0.0982 (0.1088) time: 3.3499 data: 0.0087 max mem: 33370 +Epoch: [7] [ 810/1319] eta: 0:28:39 lr: 4.134540174173232e-05 loss: 0.1079 (0.1089) time: 3.3620 data: 0.0084 max mem: 33370 +Epoch: [7] [ 820/1319] eta: 0:28:05 lr: 4.1336690416428894e-05 loss: 0.0998 (0.1087) time: 3.3885 data: 0.0078 max mem: 33370 +Epoch: [7] [ 830/1319] eta: 0:27:32 lr: 4.132797888713944e-05 loss: 0.0879 (0.1085) time: 3.3791 data: 0.0081 max mem: 33370 +Epoch: [7] [ 840/1319] eta: 0:26:58 lr: 4.13192671538114e-05 loss: 0.0977 (0.1088) time: 3.3686 data: 0.0083 max mem: 33370 +Epoch: [7] [ 850/1319] eta: 0:26:24 lr: 4.1310555216392185e-05 loss: 0.0995 (0.1087) time: 3.3822 data: 0.0082 max mem: 33370 +Epoch: [7] [ 860/1319] eta: 0:25:50 lr: 4.130184307482921e-05 loss: 0.0915 (0.1087) time: 3.3850 data: 0.0083 max mem: 33370 +Epoch: [7] [ 870/1319] eta: 0:25:17 lr: 4.1293130729069835e-05 loss: 0.0940 (0.1087) time: 3.3917 data: 0.0080 max mem: 33370 +Epoch: [7] [ 880/1319] eta: 0:24:43 lr: 4.128441817906139e-05 loss: 0.1016 (0.1087) time: 3.4111 data: 0.0079 max mem: 33370 +Epoch: [7] [ 890/1319] eta: 0:24:09 lr: 4.1275705424751206e-05 loss: 0.1016 (0.1087) time: 3.4172 data: 0.0079 max mem: 33370 +Epoch: [7] [ 900/1319] eta: 0:23:35 lr: 4.1266992466086555e-05 loss: 0.0897 (0.1086) time: 3.3813 data: 0.0078 max mem: 33370 +Epoch: [7] [ 910/1319] eta: 0:23:02 lr: 4.125827930301473e-05 loss: 0.0914 (0.1086) time: 3.3589 data: 0.0080 max mem: 33370 +Epoch: [7] [ 920/1319] eta: 0:22:28 lr: 4.124956593548294e-05 loss: 0.1093 (0.1087) time: 3.3810 data: 0.0080 max mem: 33370 +Epoch: [7] [ 930/1319] eta: 0:21:54 lr: 4.124085236343841e-05 loss: 0.1030 (0.1087) time: 3.4021 data: 0.0081 max mem: 33370 +Epoch: [7] [ 940/1319] eta: 0:21:20 lr: 4.123213858682832e-05 loss: 0.1136 (0.1088) time: 3.3903 data: 0.0080 max mem: 33370 +Epoch: [7] [ 950/1319] eta: 0:20:47 lr: 4.122342460559985e-05 loss: 0.1022 (0.1087) time: 3.3675 data: 0.0078 max mem: 33370 +Epoch: [7] [ 960/1319] eta: 0:20:13 lr: 4.12147104197001e-05 loss: 0.0926 (0.1087) time: 3.3716 data: 0.0079 max mem: 33370 +Epoch: [7] [ 970/1319] eta: 0:19:39 lr: 4.12059960290762e-05 loss: 0.0996 (0.1089) time: 3.3827 data: 0.0079 max mem: 33370 +Epoch: [7] [ 980/1319] eta: 0:19:05 lr: 4.119728143367523e-05 loss: 0.1103 (0.1093) time: 3.3805 data: 0.0076 max mem: 33370 +Epoch: [7] [ 990/1319] eta: 0:18:31 lr: 4.1188566633444246e-05 loss: 0.1085 (0.1093) time: 3.3531 data: 0.0078 max mem: 33370 +Epoch: [7] [1000/1319] eta: 0:17:57 lr: 4.1179851628330275e-05 loss: 0.0970 (0.1093) time: 3.3392 data: 0.0079 max mem: 33370 +Epoch: [7] [1010/1319] eta: 0:17:24 lr: 4.117113641828032e-05 loss: 0.0970 (0.1094) time: 3.3639 data: 0.0079 max mem: 33370 +Epoch: [7] [1020/1319] eta: 0:16:50 lr: 4.116242100324135e-05 loss: 0.1046 (0.1094) time: 3.3655 data: 0.0079 max mem: 33370 +Epoch: [7] [1030/1319] eta: 0:16:16 lr: 4.1153705383160326e-05 loss: 0.1031 (0.1096) time: 3.3738 data: 0.0076 max mem: 33370 +Epoch: [7] [1040/1319] eta: 0:15:42 lr: 4.114498955798418e-05 loss: 0.1032 (0.1097) time: 3.3529 data: 0.0078 max mem: 33370 +Epoch: [7] [1050/1319] eta: 0:15:08 lr: 4.113627352765979e-05 loss: 0.1032 (0.1096) time: 3.3181 data: 0.0080 max mem: 33370 +Epoch: [7] [1060/1319] eta: 0:14:34 lr: 4.1127557292134045e-05 loss: 0.0990 (0.1096) time: 3.3664 data: 0.0077 max mem: 33370 +Epoch: [7] [1070/1319] eta: 0:14:00 lr: 4.111884085135378e-05 loss: 0.1048 (0.1097) time: 3.3625 data: 0.0076 max mem: 33370 +Epoch: [7] [1080/1319] eta: 0:13:27 lr: 4.111012420526582e-05 loss: 0.1044 (0.1097) time: 3.3232 data: 0.0077 max mem: 33370 +Epoch: [7] [1090/1319] eta: 0:12:53 lr: 4.110140735381696e-05 loss: 0.0983 (0.1096) time: 3.3475 data: 0.0077 max mem: 33370 +Epoch: [7] [1100/1319] eta: 0:12:19 lr: 4.109269029695397e-05 loss: 0.0966 (0.1096) time: 3.3988 data: 0.0077 max mem: 33370 +Epoch: [7] [1110/1319] eta: 0:11:45 lr: 4.108397303462358e-05 loss: 0.1141 (0.1096) time: 3.3943 data: 0.0076 max mem: 33370 +Epoch: [7] [1120/1319] eta: 0:11:11 lr: 4.1075255566772506e-05 loss: 0.0906 (0.1096) time: 3.3593 data: 0.0077 max mem: 33370 +Epoch: [7] [1130/1319] eta: 0:10:38 lr: 4.106653789334745e-05 loss: 0.1139 (0.1097) time: 3.3668 data: 0.0076 max mem: 33370 +Epoch: [7] [1140/1319] eta: 0:10:04 lr: 4.105782001429505e-05 loss: 0.1181 (0.1101) time: 3.3630 data: 0.0076 max mem: 33370 +Epoch: [7] [1150/1319] eta: 0:09:30 lr: 4.104910192956196e-05 loss: 0.1178 (0.1103) time: 3.3480 data: 0.0078 max mem: 33370 +Epoch: [7] [1160/1319] eta: 0:08:56 lr: 4.104038363909479e-05 loss: 0.1108 (0.1101) time: 3.3578 data: 0.0084 max mem: 33370 +Epoch: [7] [1170/1319] eta: 0:08:23 lr: 4.1031665142840106e-05 loss: 0.0869 (0.1101) time: 3.3648 data: 0.0085 max mem: 33370 +Epoch: [7] [1180/1319] eta: 0:07:49 lr: 4.1022946440744476e-05 loss: 0.1167 (0.1107) time: 3.3975 data: 0.0080 max mem: 33370 +Epoch: [7] [1190/1319] eta: 0:07:15 lr: 4.1014227532754415e-05 loss: 0.1177 (0.1107) time: 3.3905 data: 0.0079 max mem: 33370 +Epoch: [7] [1200/1319] eta: 0:06:41 lr: 4.100550841881645e-05 loss: 0.1139 (0.1108) time: 3.3769 data: 0.0079 max mem: 33370 +Epoch: [7] [1210/1319] eta: 0:06:08 lr: 4.099678909887704e-05 loss: 0.1041 (0.1110) time: 3.3984 data: 0.0084 max mem: 33370 +Epoch: [7] [1220/1319] eta: 0:05:34 lr: 4.098806957288263e-05 loss: 0.1069 (0.1109) time: 3.3795 data: 0.0084 max mem: 33370 +Epoch: [7] [1230/1319] eta: 0:05:00 lr: 4.0979349840779665e-05 loss: 0.1057 (0.1109) time: 3.3934 data: 0.0084 max mem: 33370 +Epoch: [7] [1240/1319] eta: 0:04:26 lr: 4.0970629902514516e-05 loss: 0.0997 (0.1109) time: 3.4065 data: 0.0087 max mem: 33370 +Epoch: [7] [1250/1319] eta: 0:03:53 lr: 4.0961909758033565e-05 loss: 0.1002 (0.1109) time: 3.3933 data: 0.0086 max mem: 33370 +Epoch: [7] [1260/1319] eta: 0:03:19 lr: 4.095318940728316e-05 loss: 0.1002 (0.1109) time: 3.3971 data: 0.0084 max mem: 33370 +Epoch: [7] [1270/1319] eta: 0:02:45 lr: 4.0944468850209605e-05 loss: 0.0951 (0.1107) time: 3.3803 data: 0.0083 max mem: 33370 +Epoch: [7] [1280/1319] eta: 0:02:11 lr: 4.093574808675919e-05 loss: 0.0929 (0.1107) time: 3.3697 data: 0.0079 max mem: 33370 +Epoch: [7] [1290/1319] eta: 0:01:37 lr: 4.09270271168782e-05 loss: 0.0929 (0.1107) time: 3.3820 data: 0.0078 max mem: 33370 +Epoch: [7] [1300/1319] eta: 0:01:04 lr: 4.091830594051285e-05 loss: 0.1032 (0.1106) time: 3.3478 data: 0.0081 max mem: 33370 +Epoch: [7] [1310/1319] eta: 0:00:30 lr: 4.090958455760934e-05 loss: 0.0873 (0.1106) time: 3.3391 data: 0.0077 max mem: 33370 +Epoch: [7] Total time: 1:14:14 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 3:36:25 time: 5.0467 data: 4.9518 max mem: 33370 +Test: [ 100/2573] eta: 0:05:12 time: 0.0766 data: 0.0014 max mem: 33370 +Test: [ 200/2573] eta: 0:04:03 time: 0.0774 data: 0.0014 max mem: 33370 +Test: [ 300/2573] eta: 0:03:33 time: 0.0797 data: 0.0014 max mem: 33370 +Test: [ 400/2573] eta: 0:03:15 time: 0.0801 data: 0.0014 max mem: 33370 +Test: [ 500/2573] eta: 0:03:02 time: 0.0783 data: 0.0014 max mem: 33370 +Test: [ 600/2573] eta: 0:02:50 time: 0.0783 data: 0.0015 max mem: 33370 +Test: [ 700/2573] eta: 0:02:40 time: 0.0785 data: 0.0014 max mem: 33370 +Test: [ 800/2573] eta: 0:02:30 time: 0.0818 data: 0.0014 max mem: 33370 +Test: [ 900/2573] eta: 0:02:21 time: 0.0795 data: 0.0014 max mem: 33370 +Test: [1000/2573] eta: 0:02:11 time: 0.0796 data: 0.0014 max mem: 33370 +Test: [1100/2573] eta: 0:02:02 time: 0.0803 data: 0.0014 max mem: 33370 +Test: [1200/2573] eta: 0:01:54 time: 0.0800 data: 0.0014 max mem: 33370 +Test: [1300/2573] eta: 0:01:45 time: 0.0806 data: 0.0014 max mem: 33370 +Test: [1400/2573] eta: 0:01:37 time: 0.0788 data: 0.0015 max mem: 33370 +Test: [1500/2573] eta: 0:01:28 time: 0.0810 data: 0.0014 max mem: 33370 +Test: [1600/2573] eta: 0:01:20 time: 0.0835 data: 0.0015 max mem: 33370 +Test: [1700/2573] eta: 0:01:11 time: 0.0791 data: 0.0014 max mem: 33370 +Test: [1800/2573] eta: 0:01:03 time: 0.0811 data: 0.0014 max mem: 33370 +Test: [1900/2573] eta: 0:00:55 time: 0.0785 data: 0.0014 max mem: 33370 +Test: [2000/2573] eta: 0:00:46 time: 0.0811 data: 0.0015 max mem: 33370 +Test: [2100/2573] eta: 0:00:38 time: 0.0821 data: 0.0015 max mem: 33370 +Test: [2200/2573] eta: 0:00:30 time: 0.0809 data: 0.0014 max mem: 33370 +Test: [2300/2573] eta: 0:00:22 time: 0.0814 data: 0.0014 max mem: 33370 +Test: [2400/2573] eta: 0:00:14 time: 0.0781 data: 0.0015 max mem: 33370 +Test: [2500/2573] eta: 0:00:05 time: 0.0797 data: 0.0014 max mem: 33370 +Test: Total time: 0:03:30 +Final results: +Mean IoU is 58.06 + + precision@0.5 = 64.79 + precision@0.6 = 57.78 + precision@0.7 = 48.35 + precision@0.8 = 35.78 + precision@0.9 = 14.85 + overall IoU = 57.41 + +Average object IoU 58.064063941497025 +Overall IoU 57.40825653076172 +Better epoch: 7 + +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [8] [ 0/1319] eta: 1:52:29 lr: 4.09017351363616e-05 loss: 0.1210 (0.1210) time: 5.1175 data: 1.7904 max mem: 33370 +Epoch: [8] [ 10/1319] eta: 1:17:15 lr: 4.089301336088734e-05 loss: 0.0992 (0.0975) time: 3.5411 data: 0.1697 max mem: 33370 +Epoch: [8] [ 20/1319] eta: 1:15:29 lr: 4.088429137871879e-05 loss: 0.0970 (0.1066) time: 3.4053 data: 0.0078 max mem: 33370 +Epoch: [8] [ 30/1319] eta: 1:14:05 lr: 4.087556918980205e-05 loss: 0.0970 (0.1056) time: 3.3976 data: 0.0078 max mem: 33370 +Epoch: [8] [ 40/1319] eta: 1:13:05 lr: 4.0866846794083216e-05 loss: 0.0792 (0.0989) time: 3.3687 data: 0.0079 max mem: 33370 +Epoch: [8] [ 50/1319] eta: 1:12:14 lr: 4.0858124191508315e-05 loss: 0.0673 (0.0950) time: 3.3653 data: 0.0079 max mem: 33370 +Epoch: [8] [ 60/1319] eta: 1:11:33 lr: 4.08494013820234e-05 loss: 0.0819 (0.0948) time: 3.3709 data: 0.0077 max mem: 33370 +Epoch: [8] [ 70/1319] eta: 1:10:55 lr: 4.0840678365574436e-05 loss: 0.0985 (0.0958) time: 3.3837 data: 0.0080 max mem: 33370 +Epoch: [8] [ 80/1319] eta: 1:10:15 lr: 4.083195514210742e-05 loss: 0.0912 (0.0934) time: 3.3776 data: 0.0079 max mem: 33370 +Epoch: [8] [ 90/1319] eta: 1:09:39 lr: 4.0823231711568287e-05 loss: 0.0648 (0.0928) time: 3.3787 data: 0.0076 max mem: 33370 +Epoch: [8] [ 100/1319] eta: 1:09:02 lr: 4.081450807390295e-05 loss: 0.0733 (0.0923) time: 3.3835 data: 0.0077 max mem: 33370 +Epoch: [8] [ 110/1319] eta: 1:08:28 lr: 4.0805784229057304e-05 loss: 0.0750 (0.0917) time: 3.3867 data: 0.0082 max mem: 33370 +Epoch: [8] [ 120/1319] eta: 1:07:53 lr: 4.079706017697721e-05 loss: 0.0873 (0.0925) time: 3.3951 data: 0.0086 max mem: 33370 +Epoch: [8] [ 130/1319] eta: 1:07:18 lr: 4.0788335917608504e-05 loss: 0.0874 (0.0925) time: 3.3873 data: 0.0085 max mem: 33370 +Epoch: [8] [ 140/1319] eta: 1:06:42 lr: 4.077961145089699e-05 loss: 0.0972 (0.0938) time: 3.3794 data: 0.0081 max mem: 33370 +Epoch: [8] [ 150/1319] eta: 1:06:07 lr: 4.0770886776788466e-05 loss: 0.1029 (0.0959) time: 3.3755 data: 0.0077 max mem: 33370 +Epoch: [8] [ 160/1319] eta: 1:05:28 lr: 4.076216189522867e-05 loss: 0.1001 (0.0969) time: 3.3516 data: 0.0075 max mem: 33370 +Epoch: [8] [ 170/1319] eta: 1:04:55 lr: 4.075343680616333e-05 loss: 0.0873 (0.0957) time: 3.3640 data: 0.0076 max mem: 33370 +Epoch: [8] [ 180/1319] eta: 1:04:21 lr: 4.074471150953815e-05 loss: 0.0767 (0.0966) time: 3.3914 data: 0.0080 max mem: 33370 +Epoch: [8] [ 190/1319] eta: 1:03:45 lr: 4.0735986005298814e-05 loss: 0.0853 (0.0961) time: 3.3696 data: 0.0080 max mem: 33370 +Epoch: [8] [ 200/1319] eta: 1:03:12 lr: 4.072726029339096e-05 loss: 0.0869 (0.0964) time: 3.3825 data: 0.0078 max mem: 33370 +Epoch: [8] [ 210/1319] eta: 1:02:39 lr: 4.07185343737602e-05 loss: 0.0869 (0.0974) time: 3.4122 data: 0.0079 max mem: 33370 +Epoch: [8] [ 220/1319] eta: 1:02:06 lr: 4.070980824635213e-05 loss: 0.0794 (0.0972) time: 3.4061 data: 0.0079 max mem: 33370 +Epoch: [8] [ 230/1319] eta: 1:01:32 lr: 4.070108191111232e-05 loss: 0.0811 (0.0972) time: 3.3931 data: 0.0078 max mem: 33370 +Epoch: [8] [ 240/1319] eta: 1:00:56 lr: 4.069235536798631e-05 loss: 0.0864 (0.0969) time: 3.3669 data: 0.0083 max mem: 33370 +Epoch: [8] [ 250/1319] eta: 1:00:21 lr: 4.0683628616919596e-05 loss: 0.0856 (0.0962) time: 3.3603 data: 0.0083 max mem: 33370 +Epoch: [8] [ 260/1319] eta: 0:59:48 lr: 4.0674901657857675e-05 loss: 0.0856 (0.0975) time: 3.3849 data: 0.0079 max mem: 33370 +Epoch: [8] [ 270/1319] eta: 0:59:15 lr: 4.066617449074599e-05 loss: 0.0909 (0.0980) time: 3.4005 data: 0.0080 max mem: 33370 +Epoch: [8] [ 280/1319] eta: 0:58:40 lr: 4.065744711552997e-05 loss: 0.1005 (0.0988) time: 3.3843 data: 0.0080 max mem: 33370 +Epoch: [8] [ 290/1319] eta: 0:58:07 lr: 4.064871953215503e-05 loss: 0.1097 (0.0992) time: 3.3977 data: 0.0080 max mem: 33370 +Epoch: [8] [ 300/1319] eta: 0:57:34 lr: 4.063999174056654e-05 loss: 0.0925 (0.0988) time: 3.4161 data: 0.0077 max mem: 33370 +Epoch: [8] [ 310/1319] eta: 0:56:59 lr: 4.063126374070984e-05 loss: 0.0776 (0.0985) time: 3.3777 data: 0.0076 max mem: 33370 +Epoch: [8] [ 320/1319] eta: 0:56:25 lr: 4.0622535532530246e-05 loss: 0.0793 (0.0982) time: 3.3758 data: 0.0078 max mem: 33370 +Epoch: [8] [ 330/1319] eta: 0:55:50 lr: 4.0613807115973054e-05 loss: 0.0793 (0.0980) time: 3.3713 data: 0.0081 max mem: 33370 +Epoch: [8] [ 340/1319] eta: 0:55:17 lr: 4.060507849098353e-05 loss: 0.0824 (0.0984) time: 3.3849 data: 0.0081 max mem: 33370 +Epoch: [8] [ 350/1319] eta: 0:54:43 lr: 4.059634965750692e-05 loss: 0.0878 (0.0985) time: 3.3938 data: 0.0080 max mem: 33370 +Epoch: [8] [ 360/1319] eta: 0:54:09 lr: 4.0587620615488406e-05 loss: 0.0878 (0.0988) time: 3.3800 data: 0.0080 max mem: 33370 +Epoch: [8] [ 370/1319] eta: 0:53:35 lr: 4.0578891364873185e-05 loss: 0.0878 (0.0988) time: 3.3961 data: 0.0081 max mem: 33370 +Epoch: [8] [ 380/1319] eta: 0:53:00 lr: 4.0570161905606414e-05 loss: 0.0884 (0.0988) time: 3.3672 data: 0.0080 max mem: 33370 +Epoch: [8] [ 390/1319] eta: 0:52:27 lr: 4.056143223763321e-05 loss: 0.0811 (0.0984) time: 3.3709 data: 0.0080 max mem: 33370 +Epoch: [8] [ 400/1319] eta: 0:51:51 lr: 4.055270236089869e-05 loss: 0.0778 (0.0983) time: 3.3669 data: 0.0078 max mem: 33370 +Epoch: [8] [ 410/1319] eta: 0:51:17 lr: 4.054397227534791e-05 loss: 0.0888 (0.0984) time: 3.3346 data: 0.0078 max mem: 33370 +Epoch: [8] [ 420/1319] eta: 0:50:42 lr: 4.0535241980925915e-05 loss: 0.0907 (0.0983) time: 3.3523 data: 0.0081 max mem: 33370 +Epoch: [8] [ 430/1319] eta: 0:50:09 lr: 4.0526511477577724e-05 loss: 0.0911 (0.0983) time: 3.3787 data: 0.0080 max mem: 33370 +Epoch: [8] [ 440/1319] eta: 0:49:35 lr: 4.051778076524832e-05 loss: 0.0911 (0.0983) time: 3.3911 data: 0.0079 max mem: 33370 +Epoch: [8] [ 450/1319] eta: 0:49:01 lr: 4.050904984388268e-05 loss: 0.0844 (0.0981) time: 3.3924 data: 0.0085 max mem: 33370 +Epoch: [8] [ 460/1319] eta: 0:48:28 lr: 4.0500318713425716e-05 loss: 0.0797 (0.0980) time: 3.3940 data: 0.0084 max mem: 33370 +Epoch: [8] [ 470/1319] eta: 0:47:54 lr: 4.0491587373822346e-05 loss: 0.0909 (0.0981) time: 3.3863 data: 0.0078 max mem: 33370 +Epoch: [8] [ 480/1319] eta: 0:47:20 lr: 4.048285582501745e-05 loss: 0.0909 (0.0984) time: 3.3807 data: 0.0079 max mem: 33370 +Epoch: [8] [ 490/1319] eta: 0:46:46 lr: 4.047412406695587e-05 loss: 0.0957 (0.0987) time: 3.3984 data: 0.0077 max mem: 33370 +Epoch: [8] [ 500/1319] eta: 0:46:13 lr: 4.046539209958243e-05 loss: 0.0906 (0.0987) time: 3.4112 data: 0.0076 max mem: 33370 +Epoch: [8] [ 510/1319] eta: 0:45:39 lr: 4.0456659922841925e-05 loss: 0.0918 (0.0988) time: 3.4098 data: 0.0079 max mem: 33370 +Epoch: [8] [ 520/1319] eta: 0:45:06 lr: 4.044792753667913e-05 loss: 0.0918 (0.0987) time: 3.4028 data: 0.0077 max mem: 33370 +Epoch: [8] [ 530/1319] eta: 0:44:31 lr: 4.0439194941038765e-05 loss: 0.0888 (0.0986) time: 3.3745 data: 0.0082 max mem: 33370 +Epoch: [8] [ 540/1319] eta: 0:43:57 lr: 4.043046213586556e-05 loss: 0.0925 (0.0987) time: 3.3423 data: 0.0088 max mem: 33370 +Epoch: [8] [ 550/1319] eta: 0:43:23 lr: 4.042172912110419e-05 loss: 0.0851 (0.0984) time: 3.3708 data: 0.0085 max mem: 33370 +Epoch: [8] [ 560/1319] eta: 0:42:49 lr: 4.0412995896699314e-05 loss: 0.0810 (0.0984) time: 3.4066 data: 0.0087 max mem: 33370 +Epoch: [8] [ 570/1319] eta: 0:42:15 lr: 4.040426246259555e-05 loss: 0.1013 (0.0990) time: 3.3895 data: 0.0085 max mem: 33370 +Epoch: [8] [ 580/1319] eta: 0:41:41 lr: 4.03955288187375e-05 loss: 0.1054 (0.0989) time: 3.3730 data: 0.0080 max mem: 33370 +Epoch: [8] [ 590/1319] eta: 0:41:07 lr: 4.038679496506974e-05 loss: 0.0913 (0.0991) time: 3.3603 data: 0.0082 max mem: 33370 +Epoch: [8] [ 600/1319] eta: 0:40:33 lr: 4.0378060901536817e-05 loss: 0.0930 (0.0991) time: 3.3670 data: 0.0080 max mem: 33370 +Epoch: [8] [ 610/1319] eta: 0:39:59 lr: 4.0369326628083236e-05 loss: 0.0885 (0.0990) time: 3.3653 data: 0.0079 max mem: 33370 +Epoch: [8] [ 620/1319] eta: 0:39:25 lr: 4.0360592144653494e-05 loss: 0.0930 (0.0990) time: 3.3472 data: 0.0079 max mem: 33370 +Epoch: [8] [ 630/1319] eta: 0:38:50 lr: 4.0351857451192053e-05 loss: 0.0945 (0.0991) time: 3.3477 data: 0.0076 max mem: 33370 +Epoch: [8] [ 640/1319] eta: 0:38:17 lr: 4.034312254764333e-05 loss: 0.0945 (0.0991) time: 3.3612 data: 0.0077 max mem: 33370 +Epoch: [8] [ 650/1319] eta: 0:37:43 lr: 4.033438743395174e-05 loss: 0.0988 (0.0991) time: 3.3755 data: 0.0082 max mem: 33370 +Epoch: [8] [ 660/1319] eta: 0:37:09 lr: 4.032565211006165e-05 loss: 0.0977 (0.0996) time: 3.3724 data: 0.0085 max mem: 33370 +Epoch: [8] [ 670/1319] eta: 0:36:34 lr: 4.031691657591742e-05 loss: 0.1032 (0.0997) time: 3.3550 data: 0.0082 max mem: 33370 +Epoch: [8] [ 680/1319] eta: 0:36:00 lr: 4.030818083146336e-05 loss: 0.1107 (0.0999) time: 3.3453 data: 0.0078 max mem: 33370 +Epoch: [8] [ 690/1319] eta: 0:35:26 lr: 4.029944487664375e-05 loss: 0.1084 (0.1000) time: 3.3428 data: 0.0080 max mem: 33370 +Epoch: [8] [ 700/1319] eta: 0:34:52 lr: 4.0290708711402866e-05 loss: 0.1015 (0.1001) time: 3.3513 data: 0.0082 max mem: 33370 +Epoch: [8] [ 710/1319] eta: 0:34:18 lr: 4.028197233568494e-05 loss: 0.0966 (0.0999) time: 3.3642 data: 0.0081 max mem: 33370 +Epoch: [8] [ 720/1319] eta: 0:33:44 lr: 4.027323574943419e-05 loss: 0.0983 (0.1000) time: 3.3711 data: 0.0079 max mem: 33370 +Epoch: [8] [ 730/1319] eta: 0:33:10 lr: 4.0264498952594776e-05 loss: 0.0983 (0.1001) time: 3.3714 data: 0.0077 max mem: 33370 +Epoch: [8] [ 740/1319] eta: 0:32:37 lr: 4.0255761945110847e-05 loss: 0.0964 (0.1000) time: 3.3785 data: 0.0076 max mem: 33370 +Epoch: [8] [ 750/1319] eta: 0:32:03 lr: 4.0247024726926543e-05 loss: 0.0990 (0.1003) time: 3.3817 data: 0.0079 max mem: 33370 +Epoch: [8] [ 760/1319] eta: 0:31:29 lr: 4.0238287297985935e-05 loss: 0.1060 (0.1005) time: 3.3807 data: 0.0080 max mem: 33370 +Epoch: [8] [ 770/1319] eta: 0:30:56 lr: 4.022954965823311e-05 loss: 0.0903 (0.1004) time: 3.4005 data: 0.0077 max mem: 33370 +Epoch: [8] [ 780/1319] eta: 0:30:21 lr: 4.0220811807612084e-05 loss: 0.0958 (0.1004) time: 3.3780 data: 0.0080 max mem: 33370 +Epoch: [8] [ 790/1319] eta: 0:29:48 lr: 4.021207374606688e-05 loss: 0.0958 (0.1005) time: 3.3585 data: 0.0082 max mem: 33370 +Epoch: [8] [ 800/1319] eta: 0:29:14 lr: 4.0203335473541464e-05 loss: 0.1035 (0.1007) time: 3.3613 data: 0.0080 max mem: 33370 +Epoch: [8] [ 810/1319] eta: 0:28:40 lr: 4.01945969899798e-05 loss: 0.0877 (0.1005) time: 3.3662 data: 0.0080 max mem: 33370 +Epoch: [8] [ 820/1319] eta: 0:28:06 lr: 4.0185858295325805e-05 loss: 0.0731 (0.1003) time: 3.3695 data: 0.0077 max mem: 33370 +Epoch: [8] [ 830/1319] eta: 0:27:32 lr: 4.017711938952337e-05 loss: 0.0921 (0.1005) time: 3.3491 data: 0.0079 max mem: 33370 +Epoch: [8] [ 840/1319] eta: 0:26:58 lr: 4.0168380272516376e-05 loss: 0.1211 (0.1013) time: 3.3416 data: 0.0082 max mem: 33370 +Epoch: [8] [ 850/1319] eta: 0:26:24 lr: 4.0159640944248643e-05 loss: 0.1006 (0.1011) time: 3.3430 data: 0.0079 max mem: 33370 +Epoch: [8] [ 860/1319] eta: 0:25:50 lr: 4.0150901404663985e-05 loss: 0.0979 (0.1011) time: 3.3525 data: 0.0081 max mem: 33370 +Epoch: [8] [ 870/1319] eta: 0:25:16 lr: 4.0142161653706185e-05 loss: 0.1022 (0.1014) time: 3.3697 data: 0.0082 max mem: 33370 +Epoch: [8] [ 880/1319] eta: 0:24:43 lr: 4.013342169131899e-05 loss: 0.1021 (0.1014) time: 3.4045 data: 0.0081 max mem: 33370 +Epoch: [8] [ 890/1319] eta: 0:24:09 lr: 4.012468151744613e-05 loss: 0.0948 (0.1015) time: 3.4109 data: 0.0083 max mem: 33370 +Epoch: [8] [ 900/1319] eta: 0:23:35 lr: 4.01159411320313e-05 loss: 0.0926 (0.1014) time: 3.3767 data: 0.0084 max mem: 33370 +Epoch: [8] [ 910/1319] eta: 0:23:01 lr: 4.010720053501816e-05 loss: 0.0925 (0.1015) time: 3.3738 data: 0.0084 max mem: 33370 +Epoch: [8] [ 920/1319] eta: 0:22:28 lr: 4.009845972635034e-05 loss: 0.0778 (0.1014) time: 3.3970 data: 0.0080 max mem: 33370 +Epoch: [8] [ 930/1319] eta: 0:21:54 lr: 4.008971870597147e-05 loss: 0.0782 (0.1013) time: 3.4128 data: 0.0079 max mem: 33370 +Epoch: [8] [ 940/1319] eta: 0:21:20 lr: 4.008097747382511e-05 loss: 0.0945 (0.1014) time: 3.4078 data: 0.0079 max mem: 33370 +Epoch: [8] [ 950/1319] eta: 0:20:47 lr: 4.0072236029854826e-05 loss: 0.1102 (0.1015) time: 3.4021 data: 0.0081 max mem: 33370 +Epoch: [8] [ 960/1319] eta: 0:20:13 lr: 4.006349437400413e-05 loss: 0.1028 (0.1015) time: 3.3924 data: 0.0082 max mem: 33370 +Epoch: [8] [ 970/1319] eta: 0:19:39 lr: 4.005475250621652e-05 loss: 0.0906 (0.1013) time: 3.3709 data: 0.0080 max mem: 33370 +Epoch: [8] [ 980/1319] eta: 0:19:05 lr: 4.004601042643546e-05 loss: 0.0722 (0.1011) time: 3.3515 data: 0.0078 max mem: 33370 +Epoch: [8] [ 990/1319] eta: 0:18:31 lr: 4.003726813460439e-05 loss: 0.0896 (0.1013) time: 3.3687 data: 0.0079 max mem: 33370 +Epoch: [8] [1000/1319] eta: 0:17:58 lr: 4.0028525630666715e-05 loss: 0.0999 (0.1013) time: 3.3799 data: 0.0079 max mem: 33370 +Epoch: [8] [1010/1319] eta: 0:17:24 lr: 4.00197829145658e-05 loss: 0.0971 (0.1014) time: 3.3634 data: 0.0079 max mem: 33370 +Epoch: [8] [1020/1319] eta: 0:16:50 lr: 4.001103998624502e-05 loss: 0.0972 (0.1014) time: 3.3652 data: 0.0076 max mem: 33370 +Epoch: [8] [1030/1319] eta: 0:16:16 lr: 4.000229684564768e-05 loss: 0.0972 (0.1014) time: 3.3650 data: 0.0082 max mem: 33370 +Epoch: [8] [1040/1319] eta: 0:15:42 lr: 3.9993553492717074e-05 loss: 0.0981 (0.1014) time: 3.3714 data: 0.0088 max mem: 33370 +Epoch: [8] [1050/1319] eta: 0:15:08 lr: 3.998480992739647e-05 loss: 0.0939 (0.1015) time: 3.3560 data: 0.0083 max mem: 33370 +Epoch: [8] [1060/1319] eta: 0:14:34 lr: 3.9976066149629094e-05 loss: 0.0913 (0.1015) time: 3.3460 data: 0.0081 max mem: 33370 +Epoch: [8] [1070/1319] eta: 0:14:01 lr: 3.9967322159358156e-05 loss: 0.0925 (0.1015) time: 3.3659 data: 0.0079 max mem: 33370 +Epoch: [8] [1080/1319] eta: 0:13:27 lr: 3.995857795652683e-05 loss: 0.0956 (0.1016) time: 3.3642 data: 0.0078 max mem: 33370 +Epoch: [8] [1090/1319] eta: 0:12:53 lr: 3.994983354107826e-05 loss: 0.0963 (0.1016) time: 3.3483 data: 0.0084 max mem: 33370 +Epoch: [8] [1100/1319] eta: 0:12:19 lr: 3.994108891295557e-05 loss: 0.0838 (0.1015) time: 3.3606 data: 0.0087 max mem: 33370 +Epoch: [8] [1110/1319] eta: 0:11:45 lr: 3.9932344072101854e-05 loss: 0.0906 (0.1015) time: 3.3846 data: 0.0084 max mem: 33370 +Epoch: [8] [1120/1319] eta: 0:11:12 lr: 3.9923599018460164e-05 loss: 0.0924 (0.1016) time: 3.3822 data: 0.0085 max mem: 33370 +Epoch: [8] [1130/1319] eta: 0:10:38 lr: 3.991485375197353e-05 loss: 0.1010 (0.1016) time: 3.3771 data: 0.0083 max mem: 33370 +Epoch: [8] [1140/1319] eta: 0:10:04 lr: 3.990610827258495e-05 loss: 0.0941 (0.1016) time: 3.3860 data: 0.0079 max mem: 33370 +Epoch: [8] [1150/1319] eta: 0:09:30 lr: 3.9897362580237394e-05 loss: 0.0858 (0.1016) time: 3.3914 data: 0.0077 max mem: 33370 +Epoch: [8] [1160/1319] eta: 0:08:57 lr: 3.988861667487383e-05 loss: 0.0945 (0.1018) time: 3.3794 data: 0.0079 max mem: 33370 +Epoch: [8] [1170/1319] eta: 0:08:23 lr: 3.987987055643715e-05 loss: 0.1066 (0.1018) time: 3.3759 data: 0.0078 max mem: 33370 +Epoch: [8] [1180/1319] eta: 0:07:49 lr: 3.9871124224870237e-05 loss: 0.1066 (0.1018) time: 3.3753 data: 0.0081 max mem: 33370 +Epoch: [8] [1190/1319] eta: 0:07:15 lr: 3.986237768011596e-05 loss: 0.1013 (0.1019) time: 3.3707 data: 0.0086 max mem: 33370 +Epoch: [8] [1200/1319] eta: 0:06:41 lr: 3.985363092211714e-05 loss: 0.0949 (0.1018) time: 3.3697 data: 0.0084 max mem: 33370 +Epoch: [8] [1210/1319] eta: 0:06:08 lr: 3.984488395081657e-05 loss: 0.0897 (0.1018) time: 3.3560 data: 0.0079 max mem: 33370 +Epoch: [8] [1220/1319] eta: 0:05:34 lr: 3.9836136766157016e-05 loss: 0.0900 (0.1018) time: 3.3647 data: 0.0076 max mem: 33370 +Epoch: [8] [1230/1319] eta: 0:05:00 lr: 3.9827389368081224e-05 loss: 0.1005 (0.1018) time: 3.3744 data: 0.0079 max mem: 33370 +Epoch: [8] [1240/1319] eta: 0:04:26 lr: 3.9818641756531906e-05 loss: 0.0993 (0.1019) time: 3.3684 data: 0.0079 max mem: 33370 +Epoch: [8] [1250/1319] eta: 0:03:53 lr: 3.980989393145173e-05 loss: 0.0992 (0.1019) time: 3.3697 data: 0.0079 max mem: 33370 +Epoch: [8] [1260/1319] eta: 0:03:19 lr: 3.9801145892783356e-05 loss: 0.0952 (0.1020) time: 3.3732 data: 0.0078 max mem: 33370 +Epoch: [8] [1270/1319] eta: 0:02:45 lr: 3.97923976404694e-05 loss: 0.0932 (0.1020) time: 3.3694 data: 0.0075 max mem: 33370 +Epoch: [8] [1280/1319] eta: 0:02:11 lr: 3.978364917445246e-05 loss: 0.1024 (0.1021) time: 3.3737 data: 0.0078 max mem: 33370 +Epoch: [8] [1290/1319] eta: 0:01:37 lr: 3.9774900494675086e-05 loss: 0.1016 (0.1020) time: 3.3493 data: 0.0081 max mem: 33370 +Epoch: [8] [1300/1319] eta: 0:01:04 lr: 3.976615160107982e-05 loss: 0.0923 (0.1021) time: 3.3378 data: 0.0080 max mem: 33370 +Epoch: [8] [1310/1319] eta: 0:00:30 lr: 3.975740249360917e-05 loss: 0.0923 (0.1021) time: 3.3743 data: 0.0078 max mem: 33370 +Epoch: [8] Total time: 1:14:14 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 3:11:24 time: 4.4635 data: 4.3673 max mem: 33370 +Test: [ 100/2573] eta: 0:04:55 time: 0.0764 data: 0.0015 max mem: 33370 +Test: [ 200/2573] eta: 0:03:55 time: 0.0772 data: 0.0015 max mem: 33370 +Test: [ 300/2573] eta: 0:03:28 time: 0.0798 data: 0.0015 max mem: 33370 +Test: [ 400/2573] eta: 0:03:11 time: 0.0790 data: 0.0014 max mem: 33370 +Test: [ 500/2573] eta: 0:02:58 time: 0.0774 data: 0.0015 max mem: 33370 +Test: [ 600/2573] eta: 0:02:47 time: 0.0781 data: 0.0014 max mem: 33370 +Test: [ 700/2573] eta: 0:02:37 time: 0.0779 data: 0.0014 max mem: 33370 +Test: [ 800/2573] eta: 0:02:27 time: 0.0809 data: 0.0014 max mem: 33370 +Test: [ 900/2573] eta: 0:02:18 time: 0.0792 data: 0.0014 max mem: 33370 +Test: [1000/2573] eta: 0:02:10 time: 0.0794 data: 0.0014 max mem: 33370 +Test: [1100/2573] eta: 0:02:01 time: 0.0788 data: 0.0015 max mem: 33370 +Test: [1200/2573] eta: 0:01:53 time: 0.0786 data: 0.0013 max mem: 33370 +Test: [1300/2573] eta: 0:01:44 time: 0.0792 data: 0.0014 max mem: 33370 +Test: [1400/2573] eta: 0:01:36 time: 0.0775 data: 0.0014 max mem: 33370 +Test: [1500/2573] eta: 0:01:27 time: 0.0794 data: 0.0015 max mem: 33370 +Test: [1600/2573] eta: 0:01:19 time: 0.0827 data: 0.0015 max mem: 33370 +Test: [1700/2573] eta: 0:01:11 time: 0.0780 data: 0.0014 max mem: 33370 +Test: [1800/2573] eta: 0:01:03 time: 0.0820 data: 0.0015 max mem: 33370 +Test: [1900/2573] eta: 0:00:54 time: 0.0784 data: 0.0015 max mem: 33370 +Test: [2000/2573] eta: 0:00:46 time: 0.0807 data: 0.0015 max mem: 33370 +Test: [2100/2573] eta: 0:00:38 time: 0.0816 data: 0.0015 max mem: 33370 +Test: [2200/2573] eta: 0:00:30 time: 0.0824 data: 0.0015 max mem: 33370 +Test: [2300/2573] eta: 0:00:22 time: 0.0805 data: 0.0014 max mem: 33370 +Test: [2400/2573] eta: 0:00:14 time: 0.0767 data: 0.0013 max mem: 33370 +Test: [2500/2573] eta: 0:00:05 time: 0.0792 data: 0.0013 max mem: 33370 +Test: Total time: 0:03:28 +Final results: +Mean IoU is 58.57 + + precision@0.5 = 64.52 + precision@0.6 = 58.03 + precision@0.7 = 49.18 + precision@0.8 = 36.83 + precision@0.9 = 16.40 + overall IoU = 57.86 + +Average object IoU 58.57134323018299 +Overall IoU 57.86140441894531 +Better epoch: 8 + +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [9] [ 0/1319] eta: 2:01:59 lr: 3.974952811397457e-05 loss: 0.1719 (0.1719) time: 5.5492 data: 1.9193 max mem: 33370 +Epoch: [9] [ 10/1319] eta: 1:17:41 lr: 3.974077859998216e-05 loss: 0.0950 (0.0973) time: 3.5608 data: 0.1822 max mem: 33370 +Epoch: [9] [ 20/1319] eta: 1:15:09 lr: 3.9732028871947454e-05 loss: 0.0905 (0.0953) time: 3.3674 data: 0.0079 max mem: 33370 +Epoch: [9] [ 30/1319] eta: 1:13:58 lr: 3.972327892981283e-05 loss: 0.0727 (0.0955) time: 3.3784 data: 0.0076 max mem: 33370 +Epoch: [9] [ 40/1319] eta: 1:13:08 lr: 3.971452877352066e-05 loss: 0.0687 (0.0889) time: 3.3897 data: 0.0077 max mem: 33370 +Epoch: [9] [ 50/1319] eta: 1:12:20 lr: 3.9705778403013264e-05 loss: 0.0768 (0.0950) time: 3.3845 data: 0.0077 max mem: 33370 +Epoch: [9] [ 60/1319] eta: 1:11:40 lr: 3.969702781823294e-05 loss: 0.0888 (0.0959) time: 3.3828 data: 0.0081 max mem: 33370 +Epoch: [9] [ 70/1319] eta: 1:10:52 lr: 3.9688277019121967e-05 loss: 0.0875 (0.0957) time: 3.3664 data: 0.0082 max mem: 33370 +Epoch: [9] [ 80/1319] eta: 1:10:14 lr: 3.967952600562257e-05 loss: 0.0875 (0.0958) time: 3.3594 data: 0.0080 max mem: 33370 +Epoch: [9] [ 90/1319] eta: 1:09:36 lr: 3.967077477767697e-05 loss: 0.0858 (0.0964) time: 3.3745 data: 0.0080 max mem: 33370 +Epoch: [9] [ 100/1319] eta: 1:08:55 lr: 3.966202333522733e-05 loss: 0.0914 (0.0980) time: 3.3557 data: 0.0077 max mem: 33370 +Epoch: [9] [ 110/1319] eta: 1:08:21 lr: 3.965327167821583e-05 loss: 0.0839 (0.0969) time: 3.3654 data: 0.0076 max mem: 33370 +Epoch: [9] [ 120/1319] eta: 1:07:49 lr: 3.9644519806584564e-05 loss: 0.0739 (0.0956) time: 3.4005 data: 0.0080 max mem: 33370 +Epoch: [9] [ 130/1319] eta: 1:07:10 lr: 3.963576772027564e-05 loss: 0.0903 (0.0951) time: 3.3751 data: 0.0081 max mem: 33370 +Epoch: [9] [ 140/1319] eta: 1:06:38 lr: 3.96270154192311e-05 loss: 0.0881 (0.0947) time: 3.3775 data: 0.0083 max mem: 33370 +Epoch: [9] [ 150/1319] eta: 1:06:03 lr: 3.9618262903393e-05 loss: 0.0788 (0.0942) time: 3.3961 data: 0.0082 max mem: 33370 +Epoch: [9] [ 160/1319] eta: 1:05:28 lr: 3.960951017270332e-05 loss: 0.0751 (0.0937) time: 3.3722 data: 0.0077 max mem: 33370 +Epoch: [9] [ 170/1319] eta: 1:04:51 lr: 3.9600757227104046e-05 loss: 0.0925 (0.0942) time: 3.3555 data: 0.0076 max mem: 33370 +Epoch: [9] [ 180/1319] eta: 1:04:15 lr: 3.95920040665371e-05 loss: 0.0942 (0.0938) time: 3.3551 data: 0.0078 max mem: 33370 +Epoch: [9] [ 190/1319] eta: 1:03:39 lr: 3.958325069094442e-05 loss: 0.0898 (0.0944) time: 3.3533 data: 0.0079 max mem: 33370 +Epoch: [9] [ 200/1319] eta: 1:03:05 lr: 3.957449710026786e-05 loss: 0.0936 (0.0946) time: 3.3617 data: 0.0081 max mem: 33370 +Epoch: [9] [ 210/1319] eta: 1:02:30 lr: 3.9565743294449283e-05 loss: 0.0936 (0.0944) time: 3.3757 data: 0.0082 max mem: 33370 +Epoch: [9] [ 220/1319] eta: 1:01:54 lr: 3.955698927343052e-05 loss: 0.0879 (0.0942) time: 3.3507 data: 0.0081 max mem: 33370 +Epoch: [9] [ 230/1319] eta: 1:01:22 lr: 3.954823503715335e-05 loss: 0.0736 (0.0938) time: 3.3700 data: 0.0078 max mem: 33370 +Epoch: [9] [ 240/1319] eta: 1:00:47 lr: 3.953948058555954e-05 loss: 0.0736 (0.0937) time: 3.3808 data: 0.0077 max mem: 33370 +Epoch: [9] [ 250/1319] eta: 1:00:12 lr: 3.9530725918590825e-05 loss: 0.0884 (0.0934) time: 3.3603 data: 0.0078 max mem: 33370 +Epoch: [9] [ 260/1319] eta: 0:59:37 lr: 3.952197103618889e-05 loss: 0.0794 (0.0935) time: 3.3533 data: 0.0079 max mem: 33370 +Epoch: [9] [ 270/1319] eta: 0:59:02 lr: 3.951321593829542e-05 loss: 0.0912 (0.0936) time: 3.3398 data: 0.0079 max mem: 33370 +Epoch: [9] [ 280/1319] eta: 0:58:28 lr: 3.9504460624852056e-05 loss: 0.0908 (0.0935) time: 3.3535 data: 0.0081 max mem: 33370 +Epoch: [9] [ 290/1319] eta: 0:57:53 lr: 3.94957050958004e-05 loss: 0.0802 (0.0932) time: 3.3554 data: 0.0080 max mem: 33370 +Epoch: [9] [ 300/1319] eta: 0:57:19 lr: 3.9486949351082035e-05 loss: 0.0756 (0.0927) time: 3.3580 data: 0.0082 max mem: 33370 +Epoch: [9] [ 310/1319] eta: 0:56:44 lr: 3.9478193390638515e-05 loss: 0.0756 (0.0928) time: 3.3635 data: 0.0086 max mem: 33370 +Epoch: [9] [ 320/1319] eta: 0:56:11 lr: 3.946943721441136e-05 loss: 0.0939 (0.0929) time: 3.3698 data: 0.0086 max mem: 33370 +Epoch: [9] [ 330/1319] eta: 0:55:37 lr: 3.946068082234206e-05 loss: 0.0802 (0.0923) time: 3.3742 data: 0.0085 max mem: 33370 +Epoch: [9] [ 340/1319] eta: 0:55:04 lr: 3.945192421437206e-05 loss: 0.0865 (0.0927) time: 3.3809 data: 0.0083 max mem: 33370 +Epoch: [9] [ 350/1319] eta: 0:54:30 lr: 3.944316739044282e-05 loss: 0.0927 (0.0927) time: 3.3921 data: 0.0083 max mem: 33370 +Epoch: [9] [ 360/1319] eta: 0:53:56 lr: 3.94344103504957e-05 loss: 0.0920 (0.0927) time: 3.3642 data: 0.0086 max mem: 33370 +Epoch: [9] [ 370/1319] eta: 0:53:23 lr: 3.94256530944721e-05 loss: 0.0916 (0.0928) time: 3.3714 data: 0.0085 max mem: 33370 +Epoch: [9] [ 380/1319] eta: 0:52:48 lr: 3.9416895622313336e-05 loss: 0.0911 (0.0929) time: 3.3716 data: 0.0082 max mem: 33370 +Epoch: [9] [ 390/1319] eta: 0:52:14 lr: 3.9408137933960734e-05 loss: 0.0974 (0.0929) time: 3.3592 data: 0.0082 max mem: 33370 +Epoch: [9] [ 400/1319] eta: 0:51:40 lr: 3.939938002935556e-05 loss: 0.0853 (0.0927) time: 3.3721 data: 0.0081 max mem: 33370 +Epoch: [9] [ 410/1319] eta: 0:51:07 lr: 3.9390621908439054e-05 loss: 0.0815 (0.0923) time: 3.3757 data: 0.0082 max mem: 33370 +Epoch: [9] [ 420/1319] eta: 0:50:33 lr: 3.938186357115245e-05 loss: 0.0708 (0.0927) time: 3.3784 data: 0.0082 max mem: 33370 +Epoch: [9] [ 430/1319] eta: 0:49:59 lr: 3.937310501743692e-05 loss: 0.0951 (0.0928) time: 3.3768 data: 0.0080 max mem: 33370 +Epoch: [9] [ 440/1319] eta: 0:49:25 lr: 3.936434624723363e-05 loss: 0.0951 (0.0930) time: 3.3619 data: 0.0079 max mem: 33370 +Epoch: [9] [ 450/1319] eta: 0:48:51 lr: 3.9355587260483696e-05 loss: 0.0905 (0.0934) time: 3.3519 data: 0.0077 max mem: 33370 +Epoch: [9] [ 460/1319] eta: 0:48:17 lr: 3.9346828057128216e-05 loss: 0.0941 (0.0935) time: 3.3554 data: 0.0076 max mem: 33370 +Epoch: [9] [ 470/1319] eta: 0:47:43 lr: 3.9338068637108247e-05 loss: 0.0916 (0.0931) time: 3.3473 data: 0.0079 max mem: 33370 +Epoch: [9] [ 480/1319] eta: 0:47:09 lr: 3.932930900036482e-05 loss: 0.0652 (0.0929) time: 3.3641 data: 0.0083 max mem: 33370 +Epoch: [9] [ 490/1319] eta: 0:46:36 lr: 3.932054914683895e-05 loss: 0.0779 (0.0928) time: 3.3873 data: 0.0081 max mem: 33370 +Epoch: [9] [ 500/1319] eta: 0:46:01 lr: 3.9311789076471614e-05 loss: 0.0845 (0.0928) time: 3.3619 data: 0.0081 max mem: 33370 +Epoch: [9] [ 510/1319] eta: 0:45:27 lr: 3.930302878920372e-05 loss: 0.0797 (0.0927) time: 3.3442 data: 0.0084 max mem: 33370 +Epoch: [9] [ 520/1319] eta: 0:44:54 lr: 3.929426828497621e-05 loss: 0.0761 (0.0927) time: 3.3614 data: 0.0081 max mem: 33370 +Epoch: [9] [ 530/1319] eta: 0:44:20 lr: 3.9285507563729945e-05 loss: 0.0761 (0.0925) time: 3.3699 data: 0.0083 max mem: 33370 +Epoch: [9] [ 540/1319] eta: 0:43:47 lr: 3.927674662540578e-05 loss: 0.0821 (0.0924) time: 3.3968 data: 0.0082 max mem: 33370 +Epoch: [9] [ 550/1319] eta: 0:43:14 lr: 3.926798546994454e-05 loss: 0.0830 (0.0925) time: 3.4127 data: 0.0075 max mem: 33370 +Epoch: [9] [ 560/1319] eta: 0:42:40 lr: 3.9259224097287e-05 loss: 0.0929 (0.0926) time: 3.4114 data: 0.0077 max mem: 33370 +Epoch: [9] [ 570/1319] eta: 0:42:06 lr: 3.925046250737393e-05 loss: 0.0968 (0.0928) time: 3.3877 data: 0.0082 max mem: 33370 +Epoch: [9] [ 580/1319] eta: 0:41:33 lr: 3.924170070014604e-05 loss: 0.0964 (0.0928) time: 3.3798 data: 0.0081 max mem: 33370 +Epoch: [9] [ 590/1319] eta: 0:41:00 lr: 3.923293867554403e-05 loss: 0.0813 (0.0934) time: 3.3988 data: 0.0079 max mem: 33370 +Epoch: [9] [ 600/1319] eta: 0:40:26 lr: 3.9224176433508566e-05 loss: 0.0926 (0.0937) time: 3.3811 data: 0.0079 max mem: 33370 +Epoch: [9] [ 610/1319] eta: 0:39:52 lr: 3.9215413973980275e-05 loss: 0.0926 (0.0936) time: 3.3756 data: 0.0078 max mem: 33370 +Epoch: [9] [ 620/1319] eta: 0:39:19 lr: 3.920665129689976e-05 loss: 0.0776 (0.0934) time: 3.3849 data: 0.0080 max mem: 33370 +Epoch: [9] [ 630/1319] eta: 0:38:45 lr: 3.919788840220759e-05 loss: 0.0812 (0.0936) time: 3.3829 data: 0.0078 max mem: 33370 +Epoch: [9] [ 640/1319] eta: 0:38:11 lr: 3.918912528984432e-05 loss: 0.0938 (0.0935) time: 3.3537 data: 0.0076 max mem: 33370 +Epoch: [9] [ 650/1319] eta: 0:37:37 lr: 3.918036195975044e-05 loss: 0.0757 (0.0934) time: 3.3500 data: 0.0078 max mem: 33370 +Epoch: [9] [ 660/1319] eta: 0:37:03 lr: 3.9171598411866434e-05 loss: 0.0875 (0.0937) time: 3.3912 data: 0.0079 max mem: 33370 +Epoch: [9] [ 670/1319] eta: 0:36:30 lr: 3.9162834646132755e-05 loss: 0.1109 (0.0943) time: 3.3899 data: 0.0083 max mem: 33370 +Epoch: [9] [ 680/1319] eta: 0:35:56 lr: 3.915407066248981e-05 loss: 0.1032 (0.0944) time: 3.3739 data: 0.0082 max mem: 33370 +Epoch: [9] [ 690/1319] eta: 0:35:22 lr: 3.914530646087798e-05 loss: 0.0809 (0.0942) time: 3.3776 data: 0.0077 max mem: 33370 +Epoch: [9] [ 700/1319] eta: 0:34:48 lr: 3.9136542041237625e-05 loss: 0.0786 (0.0943) time: 3.3754 data: 0.0080 max mem: 33370 +Epoch: [9] [ 710/1319] eta: 0:34:15 lr: 3.9127777403509066e-05 loss: 0.0786 (0.0941) time: 3.3636 data: 0.0081 max mem: 33370 +Epoch: [9] [ 720/1319] eta: 0:33:40 lr: 3.9119012547632586e-05 loss: 0.0801 (0.0943) time: 3.3444 data: 0.0079 max mem: 33370 +Epoch: [9] [ 730/1319] eta: 0:33:07 lr: 3.911024747354846e-05 loss: 0.0889 (0.0942) time: 3.3582 data: 0.0080 max mem: 33370 +Epoch: [9] [ 740/1319] eta: 0:32:33 lr: 3.9101482181196904e-05 loss: 0.0741 (0.0940) time: 3.3766 data: 0.0079 max mem: 33370 +Epoch: [9] [ 750/1319] eta: 0:31:59 lr: 3.909271667051812e-05 loss: 0.0741 (0.0939) time: 3.3634 data: 0.0078 max mem: 33370 +Epoch: [9] [ 760/1319] eta: 0:31:25 lr: 3.908395094145227e-05 loss: 0.0914 (0.0940) time: 3.3568 data: 0.0079 max mem: 33370 +Epoch: [9] [ 770/1319] eta: 0:30:52 lr: 3.9075184993939487e-05 loss: 0.0895 (0.0941) time: 3.3793 data: 0.0082 max mem: 33370 +Epoch: [9] [ 780/1319] eta: 0:30:18 lr: 3.906641882791989e-05 loss: 0.1022 (0.0945) time: 3.3778 data: 0.0079 max mem: 33370 +Epoch: [9] [ 790/1319] eta: 0:29:44 lr: 3.9057652443333534e-05 loss: 0.0966 (0.0944) time: 3.3625 data: 0.0080 max mem: 33370 +Epoch: [9] [ 800/1319] eta: 0:29:10 lr: 3.904888584012046e-05 loss: 0.0819 (0.0943) time: 3.3675 data: 0.0081 max mem: 33370 +Epoch: [9] [ 810/1319] eta: 0:28:36 lr: 3.904011901822068e-05 loss: 0.0831 (0.0945) time: 3.3543 data: 0.0079 max mem: 33370 +Epoch: [9] [ 820/1319] eta: 0:28:03 lr: 3.9031351977574175e-05 loss: 0.0831 (0.0945) time: 3.3441 data: 0.0079 max mem: 33370 +Epoch: [9] [ 830/1319] eta: 0:27:29 lr: 3.9022584718120886e-05 loss: 0.0885 (0.0945) time: 3.3449 data: 0.0081 max mem: 33370 +Epoch: [9] [ 840/1319] eta: 0:26:55 lr: 3.901381723980073e-05 loss: 0.0811 (0.0944) time: 3.3450 data: 0.0085 max mem: 33370 +Epoch: [9] [ 850/1319] eta: 0:26:21 lr: 3.900504954255358e-05 loss: 0.0811 (0.0944) time: 3.3637 data: 0.0084 max mem: 33370 +Epoch: [9] [ 860/1319] eta: 0:25:47 lr: 3.899628162631931e-05 loss: 0.0864 (0.0945) time: 3.3796 data: 0.0081 max mem: 33370 +Epoch: [9] [ 870/1319] eta: 0:25:14 lr: 3.898751349103772e-05 loss: 0.0880 (0.0947) time: 3.3641 data: 0.0079 max mem: 33370 +Epoch: [9] [ 880/1319] eta: 0:24:40 lr: 3.8978745136648617e-05 loss: 0.0820 (0.0946) time: 3.3641 data: 0.0078 max mem: 33370 +Epoch: [9] [ 890/1319] eta: 0:24:06 lr: 3.896997656309173e-05 loss: 0.0816 (0.0948) time: 3.3779 data: 0.0083 max mem: 33370 +Epoch: [9] [ 900/1319] eta: 0:23:33 lr: 3.896120777030681e-05 loss: 0.0925 (0.0949) time: 3.3950 data: 0.0083 max mem: 33370 +Epoch: [9] [ 910/1319] eta: 0:22:59 lr: 3.895243875823353e-05 loss: 0.0860 (0.0948) time: 3.3898 data: 0.0079 max mem: 33370 +Epoch: [9] [ 920/1319] eta: 0:22:25 lr: 3.894366952681158e-05 loss: 0.0902 (0.0949) time: 3.3754 data: 0.0080 max mem: 33370 +Epoch: [9] [ 930/1319] eta: 0:21:52 lr: 3.8934900075980555e-05 loss: 0.0980 (0.0949) time: 3.3854 data: 0.0076 max mem: 33370 +Epoch: [9] [ 940/1319] eta: 0:21:18 lr: 3.8926130405680076e-05 loss: 0.0878 (0.0949) time: 3.3660 data: 0.0077 max mem: 33370 +Epoch: [9] [ 950/1319] eta: 0:20:44 lr: 3.8917360515849704e-05 loss: 0.0846 (0.0948) time: 3.3478 data: 0.0078 max mem: 33370 +Epoch: [9] [ 960/1319] eta: 0:20:10 lr: 3.8908590406428975e-05 loss: 0.0742 (0.0947) time: 3.3561 data: 0.0079 max mem: 33370 +Epoch: [9] [ 970/1319] eta: 0:19:36 lr: 3.889982007735738e-05 loss: 0.0768 (0.0946) time: 3.3650 data: 0.0082 max mem: 33370 +Epoch: [9] [ 980/1319] eta: 0:19:03 lr: 3.889104952857442e-05 loss: 0.0768 (0.0945) time: 3.3483 data: 0.0081 max mem: 33370 +Epoch: [9] [ 990/1319] eta: 0:18:29 lr: 3.888227876001951e-05 loss: 0.0840 (0.0947) time: 3.3470 data: 0.0077 max mem: 33370 +Epoch: [9] [1000/1319] eta: 0:17:55 lr: 3.887350777163206e-05 loss: 0.1034 (0.0948) time: 3.3782 data: 0.0080 max mem: 33370 +Epoch: [9] [1010/1319] eta: 0:17:21 lr: 3.886473656335145e-05 loss: 0.0834 (0.0947) time: 3.3910 data: 0.0082 max mem: 33370 +Epoch: [9] [1020/1319] eta: 0:16:48 lr: 3.8855965135117015e-05 loss: 0.0834 (0.0947) time: 3.3899 data: 0.0078 max mem: 33370 +Epoch: [9] [1030/1319] eta: 0:16:14 lr: 3.8847193486868084e-05 loss: 0.0802 (0.0946) time: 3.3845 data: 0.0077 max mem: 33370 +Epoch: [9] [1040/1319] eta: 0:15:40 lr: 3.883842161854392e-05 loss: 0.0763 (0.0945) time: 3.3937 data: 0.0078 max mem: 33370 +Epoch: [9] [1050/1319] eta: 0:15:07 lr: 3.8829649530083775e-05 loss: 0.0958 (0.0946) time: 3.3861 data: 0.0080 max mem: 33370 +Epoch: [9] [1060/1319] eta: 0:14:33 lr: 3.882087722142687e-05 loss: 0.0958 (0.0948) time: 3.3710 data: 0.0084 max mem: 33370 +Epoch: [9] [1070/1319] eta: 0:13:59 lr: 3.8812104692512384e-05 loss: 0.0888 (0.0947) time: 3.3748 data: 0.0085 max mem: 33370 +Epoch: [9] [1080/1319] eta: 0:13:26 lr: 3.880333194327947e-05 loss: 0.0867 (0.0947) time: 3.3754 data: 0.0081 max mem: 33370 +Epoch: [9] [1090/1319] eta: 0:12:52 lr: 3.879455897366725e-05 loss: 0.0825 (0.0946) time: 3.3988 data: 0.0082 max mem: 33370 +Epoch: [9] [1100/1319] eta: 0:12:18 lr: 3.878578578361481e-05 loss: 0.1010 (0.0947) time: 3.3918 data: 0.0080 max mem: 33370 +Epoch: [9] [1110/1319] eta: 0:11:45 lr: 3.87770123730612e-05 loss: 0.0885 (0.0946) time: 3.3851 data: 0.0080 max mem: 33370 +Epoch: [9] [1120/1319] eta: 0:11:11 lr: 3.876823874194545e-05 loss: 0.0815 (0.0946) time: 3.4060 data: 0.0078 max mem: 33370 +Epoch: [9] [1130/1319] eta: 0:10:37 lr: 3.8759464890206544e-05 loss: 0.0794 (0.0945) time: 3.4034 data: 0.0076 max mem: 33370 +Epoch: [9] [1140/1319] eta: 0:10:03 lr: 3.875069081778345e-05 loss: 0.0844 (0.0945) time: 3.4133 data: 0.0077 max mem: 33370 +Epoch: [9] [1150/1319] eta: 0:09:30 lr: 3.874191652461509e-05 loss: 0.0901 (0.0945) time: 3.4331 data: 0.0077 max mem: 33370 +Epoch: [9] [1160/1319] eta: 0:08:56 lr: 3.8733142010640345e-05 loss: 0.0844 (0.0944) time: 3.4228 data: 0.0080 max mem: 33370 +Epoch: [9] [1170/1319] eta: 0:08:22 lr: 3.872436727579809e-05 loss: 0.0855 (0.0944) time: 3.4162 data: 0.0080 max mem: 33370 +Epoch: [9] [1180/1319] eta: 0:07:49 lr: 3.871559232002716e-05 loss: 0.0846 (0.0944) time: 3.3949 data: 0.0081 max mem: 33370 +Epoch: [9] [1190/1319] eta: 0:07:15 lr: 3.870681714326634e-05 loss: 0.0992 (0.0944) time: 3.3433 data: 0.0082 max mem: 33370 +Epoch: [9] [1200/1319] eta: 0:06:41 lr: 3.86980417454544e-05 loss: 0.0992 (0.0944) time: 3.3445 data: 0.0080 max mem: 33370 +Epoch: [9] [1210/1319] eta: 0:06:07 lr: 3.8689266126530076e-05 loss: 0.0961 (0.0945) time: 3.3965 data: 0.0078 max mem: 33370 +Epoch: [9] [1220/1319] eta: 0:05:34 lr: 3.868049028643206e-05 loss: 0.0951 (0.0945) time: 3.3765 data: 0.0080 max mem: 33370 +Epoch: [9] [1230/1319] eta: 0:05:00 lr: 3.867171422509902e-05 loss: 0.0837 (0.0946) time: 3.3699 data: 0.0079 max mem: 33370 +Epoch: [9] [1240/1319] eta: 0:04:26 lr: 3.866293794246959e-05 loss: 0.0973 (0.0947) time: 3.4058 data: 0.0081 max mem: 33370 +Epoch: [9] [1250/1319] eta: 0:03:52 lr: 3.8654161438482394e-05 loss: 0.0877 (0.0947) time: 3.3998 data: 0.0082 max mem: 33370 +Epoch: [9] [1260/1319] eta: 0:03:19 lr: 3.864538471307598e-05 loss: 0.0785 (0.0945) time: 3.3752 data: 0.0078 max mem: 33370 +Epoch: [9] [1270/1319] eta: 0:02:45 lr: 3.863660776618888e-05 loss: 0.0810 (0.0945) time: 3.3566 data: 0.0078 max mem: 33370 +Epoch: [9] [1280/1319] eta: 0:02:11 lr: 3.8627830597759606e-05 loss: 0.0955 (0.0946) time: 3.3629 data: 0.0079 max mem: 33370 +Epoch: [9] [1290/1319] eta: 0:01:37 lr: 3.861905320772664e-05 loss: 0.0955 (0.0947) time: 3.3752 data: 0.0079 max mem: 33370 +Epoch: [9] [1300/1319] eta: 0:01:04 lr: 3.861027559602841e-05 loss: 0.0862 (0.0947) time: 3.3719 data: 0.0078 max mem: 33370 +Epoch: [9] [1310/1319] eta: 0:00:30 lr: 3.860149776260333e-05 loss: 0.0862 (0.0947) time: 3.3537 data: 0.0076 max mem: 33370 +Epoch: [9] Total time: 1:14:12 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 2:58:20 time: 4.1587 data: 4.0587 max mem: 33370 +Test: [ 100/2573] eta: 0:04:50 time: 0.0772 data: 0.0014 max mem: 33370 +Test: [ 200/2573] eta: 0:03:53 time: 0.0783 data: 0.0014 max mem: 33370 +Test: [ 300/2573] eta: 0:03:28 time: 0.0813 data: 0.0014 max mem: 33370 +Test: [ 400/2573] eta: 0:03:11 time: 0.0799 data: 0.0013 max mem: 33370 +Test: [ 500/2573] eta: 0:02:59 time: 0.0789 data: 0.0015 max mem: 33370 +Test: [ 600/2573] eta: 0:02:48 time: 0.0793 data: 0.0015 max mem: 33370 +Test: [ 700/2573] eta: 0:02:38 time: 0.0796 data: 0.0015 max mem: 33370 +Test: [ 800/2573] eta: 0:02:29 time: 0.0834 data: 0.0014 max mem: 33370 +Test: [ 900/2573] eta: 0:02:20 time: 0.0803 data: 0.0014 max mem: 33370 +Test: [1000/2573] eta: 0:02:11 time: 0.0800 data: 0.0015 max mem: 33370 +Test: [1100/2573] eta: 0:02:02 time: 0.0798 data: 0.0013 max mem: 33370 +Test: [1200/2573] eta: 0:01:54 time: 0.0804 data: 0.0014 max mem: 33370 +Test: [1300/2573] eta: 0:01:45 time: 0.0799 data: 0.0014 max mem: 33370 +Test: [1400/2573] eta: 0:01:37 time: 0.0787 data: 0.0015 max mem: 33370 +Test: [1500/2573] eta: 0:01:28 time: 0.0800 data: 0.0014 max mem: 33370 +Test: [1600/2573] eta: 0:01:20 time: 0.0842 data: 0.0015 max mem: 33370 +Test: [1700/2573] eta: 0:01:11 time: 0.0790 data: 0.0015 max mem: 33370 +Test: [1800/2573] eta: 0:01:03 time: 0.0813 data: 0.0015 max mem: 33370 +Test: [1900/2573] eta: 0:00:55 time: 0.0784 data: 0.0014 max mem: 33370 +Test: [2000/2573] eta: 0:00:46 time: 0.0794 data: 0.0014 max mem: 33370 +Test: [2100/2573] eta: 0:00:38 time: 0.0813 data: 0.0013 max mem: 33370 +Test: [2200/2573] eta: 0:00:30 time: 0.0810 data: 0.0013 max mem: 33370 +Test: [2300/2573] eta: 0:00:22 time: 0.0816 data: 0.0014 max mem: 33370 +Test: [2400/2573] eta: 0:00:14 time: 0.0766 data: 0.0013 max mem: 33370 +Test: [2500/2573] eta: 0:00:05 time: 0.0785 data: 0.0013 max mem: 33370 +Test: Total time: 0:03:30 +Final results: +Mean IoU is 59.41 + + precision@0.5 = 65.75 + precision@0.6 = 59.84 + precision@0.7 = 52.14 + precision@0.8 = 39.87 + precision@0.9 = 17.46 + overall IoU = 58.54 + +Average object IoU 59.41499817405332 +Overall IoU 58.536808013916016 +Better epoch: 9 + +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [10] [ 0/1319] eta: 1:57:27 lr: 3.859359752289337e-05 loss: 0.1234 (0.1234) time: 5.3429 data: 1.8227 max mem: 33370 +Epoch: [10] [ 10/1319] eta: 1:18:48 lr: 3.858481926801746e-05 loss: 0.0806 (0.0837) time: 3.6127 data: 0.1721 max mem: 33370 +Epoch: [10] [ 20/1319] eta: 1:15:42 lr: 3.857604079123589e-05 loss: 0.0782 (0.0812) time: 3.4047 data: 0.0077 max mem: 33370 +Epoch: [10] [ 30/1319] eta: 1:14:10 lr: 3.856726209248695e-05 loss: 0.0782 (0.0818) time: 3.3645 data: 0.0083 max mem: 33370 +Epoch: [10] [ 40/1319] eta: 1:13:19 lr: 3.855848317170887e-05 loss: 0.0822 (0.0886) time: 3.3796 data: 0.0080 max mem: 33370 +Epoch: [10] [ 50/1319] eta: 1:12:32 lr: 3.854970402883988e-05 loss: 0.0755 (0.0867) time: 3.3943 data: 0.0080 max mem: 33370 +Epoch: [10] [ 60/1319] eta: 1:11:55 lr: 3.854092466381814e-05 loss: 0.0753 (0.0869) time: 3.4028 data: 0.0081 max mem: 33370 +Epoch: [10] [ 70/1319] eta: 1:11:12 lr: 3.853214507658182e-05 loss: 0.0799 (0.0849) time: 3.3969 data: 0.0083 max mem: 33370 +Epoch: [10] [ 80/1319] eta: 1:10:28 lr: 3.852336526706903e-05 loss: 0.0777 (0.0862) time: 3.3682 data: 0.0082 max mem: 33370 +Epoch: [10] [ 90/1319] eta: 1:09:48 lr: 3.8514585235217835e-05 loss: 0.0805 (0.0862) time: 3.3633 data: 0.0080 max mem: 33370 +Epoch: [10] [ 100/1319] eta: 1:09:09 lr: 3.850580498096631e-05 loss: 0.0747 (0.0865) time: 3.3696 data: 0.0083 max mem: 33370 +Epoch: [10] [ 110/1319] eta: 1:08:31 lr: 3.849702450425245e-05 loss: 0.0741 (0.0855) time: 3.3669 data: 0.0081 max mem: 33370 +Epoch: [10] [ 120/1319] eta: 1:07:59 lr: 3.8488243805014244e-05 loss: 0.0750 (0.0842) time: 3.3905 data: 0.0078 max mem: 33370 +Epoch: [10] [ 130/1319] eta: 1:07:24 lr: 3.8479462883189646e-05 loss: 0.0750 (0.0843) time: 3.4068 data: 0.0079 max mem: 33370 +Epoch: [10] [ 140/1319] eta: 1:06:49 lr: 3.8470681738716575e-05 loss: 0.0848 (0.0840) time: 3.3901 data: 0.0079 max mem: 33370 +Epoch: [10] [ 150/1319] eta: 1:06:13 lr: 3.846190037153291e-05 loss: 0.0822 (0.0843) time: 3.3802 data: 0.0079 max mem: 33370 +Epoch: [10] [ 160/1319] eta: 1:05:39 lr: 3.84531187815765e-05 loss: 0.0822 (0.0844) time: 3.3910 data: 0.0082 max mem: 33370 +Epoch: [10] [ 170/1319] eta: 1:05:06 lr: 3.844433696878517e-05 loss: 0.0785 (0.0839) time: 3.4118 data: 0.0081 max mem: 33370 +Epoch: [10] [ 180/1319] eta: 1:04:33 lr: 3.843555493309671e-05 loss: 0.0725 (0.0839) time: 3.4096 data: 0.0078 max mem: 33370 +Epoch: [10] [ 190/1319] eta: 1:03:59 lr: 3.842677267444885e-05 loss: 0.0729 (0.0842) time: 3.4032 data: 0.0079 max mem: 33370 +Epoch: [10] [ 200/1319] eta: 1:03:20 lr: 3.8417990192779335e-05 loss: 0.0739 (0.0840) time: 3.3642 data: 0.0080 max mem: 33370 +Epoch: [10] [ 210/1319] eta: 1:02:45 lr: 3.8409207488025836e-05 loss: 0.0782 (0.0845) time: 3.3475 data: 0.0084 max mem: 33370 +Epoch: [10] [ 220/1319] eta: 1:02:12 lr: 3.8400424560126e-05 loss: 0.0782 (0.0842) time: 3.3946 data: 0.0081 max mem: 33370 +Epoch: [10] [ 230/1319] eta: 1:01:37 lr: 3.839164140901745e-05 loss: 0.0715 (0.0839) time: 3.3895 data: 0.0078 max mem: 33370 +Epoch: [10] [ 240/1319] eta: 1:01:02 lr: 3.838285803463778e-05 loss: 0.0636 (0.0841) time: 3.3663 data: 0.0080 max mem: 33370 +Epoch: [10] [ 250/1319] eta: 1:00:28 lr: 3.8374074436924536e-05 loss: 0.0822 (0.0846) time: 3.3909 data: 0.0081 max mem: 33370 +Epoch: [10] [ 260/1319] eta: 0:59:53 lr: 3.836529061581523e-05 loss: 0.0822 (0.0842) time: 3.3898 data: 0.0082 max mem: 33370 +Epoch: [10] [ 270/1319] eta: 0:59:21 lr: 3.8356506571247355e-05 loss: 0.0743 (0.0843) time: 3.3969 data: 0.0083 max mem: 33370 +Epoch: [10] [ 280/1319] eta: 0:58:47 lr: 3.834772230315837e-05 loss: 0.0821 (0.0844) time: 3.4137 data: 0.0085 max mem: 33370 +Epoch: [10] [ 290/1319] eta: 0:58:12 lr: 3.833893781148568e-05 loss: 0.0765 (0.0842) time: 3.3896 data: 0.0084 max mem: 33370 +Epoch: [10] [ 300/1319] eta: 0:57:39 lr: 3.833015309616668e-05 loss: 0.0707 (0.0839) time: 3.3906 data: 0.0084 max mem: 33370 +Epoch: [10] [ 310/1319] eta: 0:57:05 lr: 3.832136815713871e-05 loss: 0.0749 (0.0842) time: 3.4015 data: 0.0086 max mem: 33370 +Epoch: [10] [ 320/1319] eta: 0:56:31 lr: 3.83125829943391e-05 loss: 0.0844 (0.0842) time: 3.3982 data: 0.0084 max mem: 33370 +Epoch: [10] [ 330/1319] eta: 0:55:56 lr: 3.830379760770512e-05 loss: 0.0697 (0.0837) time: 3.3789 data: 0.0081 max mem: 33370 +Epoch: [10] [ 340/1319] eta: 0:55:22 lr: 3.829501199717404e-05 loss: 0.0639 (0.0838) time: 3.3758 data: 0.0080 max mem: 33370 +Epoch: [10] [ 350/1319] eta: 0:54:48 lr: 3.828622616268306e-05 loss: 0.0704 (0.0839) time: 3.3943 data: 0.0079 max mem: 33370 +Epoch: [10] [ 360/1319] eta: 0:54:14 lr: 3.8277440104169376e-05 loss: 0.0757 (0.0841) time: 3.3844 data: 0.0080 max mem: 33370 +Epoch: [10] [ 370/1319] eta: 0:53:39 lr: 3.826865382157014e-05 loss: 0.0812 (0.0841) time: 3.3621 data: 0.0082 max mem: 33370 +Epoch: [10] [ 380/1319] eta: 0:53:05 lr: 3.8259867314822454e-05 loss: 0.0812 (0.0840) time: 3.3818 data: 0.0080 max mem: 33370 +Epoch: [10] [ 390/1319] eta: 0:52:32 lr: 3.825108058386341e-05 loss: 0.0831 (0.0842) time: 3.4091 data: 0.0080 max mem: 33370 +Epoch: [10] [ 400/1319] eta: 0:51:57 lr: 3.824229362863006e-05 loss: 0.0747 (0.0840) time: 3.3755 data: 0.0080 max mem: 33370 +Epoch: [10] [ 410/1319] eta: 0:51:22 lr: 3.823350644905941e-05 loss: 0.0734 (0.0839) time: 3.3510 data: 0.0083 max mem: 33370 +Epoch: [10] [ 420/1319] eta: 0:50:48 lr: 3.822471904508845e-05 loss: 0.0700 (0.0838) time: 3.3774 data: 0.0088 max mem: 33370 +Epoch: [10] [ 430/1319] eta: 0:50:14 lr: 3.821593141665413e-05 loss: 0.0757 (0.0841) time: 3.3970 data: 0.0084 max mem: 33370 +Epoch: [10] [ 440/1319] eta: 0:49:40 lr: 3.8207143563693345e-05 loss: 0.0786 (0.0840) time: 3.3913 data: 0.0081 max mem: 33370 +Epoch: [10] [ 450/1319] eta: 0:49:06 lr: 3.819835548614299e-05 loss: 0.0840 (0.0844) time: 3.3884 data: 0.0081 max mem: 33370 +Epoch: [10] [ 460/1319] eta: 0:48:32 lr: 3.8189567183939914e-05 loss: 0.0818 (0.0842) time: 3.3713 data: 0.0080 max mem: 33370 +Epoch: [10] [ 470/1319] eta: 0:47:57 lr: 3.8180778657020925e-05 loss: 0.0614 (0.0838) time: 3.3487 data: 0.0081 max mem: 33370 +Epoch: [10] [ 480/1319] eta: 0:47:23 lr: 3.81719899053228e-05 loss: 0.0599 (0.0837) time: 3.3656 data: 0.0082 max mem: 33370 +Epoch: [10] [ 490/1319] eta: 0:46:49 lr: 3.8163200928782287e-05 loss: 0.0735 (0.0835) time: 3.3759 data: 0.0087 max mem: 33370 +Epoch: [10] [ 500/1319] eta: 0:46:14 lr: 3.8154411727336084e-05 loss: 0.0841 (0.0838) time: 3.3600 data: 0.0088 max mem: 33370 +Epoch: [10] [ 510/1319] eta: 0:45:40 lr: 3.814562230092089e-05 loss: 0.0935 (0.0840) time: 3.3551 data: 0.0083 max mem: 33370 +Epoch: [10] [ 520/1319] eta: 0:45:06 lr: 3.8136832649473325e-05 loss: 0.0739 (0.0838) time: 3.3745 data: 0.0084 max mem: 33370 +Epoch: [10] [ 530/1319] eta: 0:44:32 lr: 3.812804277293001e-05 loss: 0.0729 (0.0840) time: 3.3798 data: 0.0086 max mem: 33370 +Epoch: [10] [ 540/1319] eta: 0:43:58 lr: 3.811925267122751e-05 loss: 0.0789 (0.0841) time: 3.3626 data: 0.0083 max mem: 33370 +Epoch: [10] [ 550/1319] eta: 0:43:24 lr: 3.8110462344302376e-05 loss: 0.0789 (0.0841) time: 3.3913 data: 0.0079 max mem: 33370 +Epoch: [10] [ 560/1319] eta: 0:42:50 lr: 3.8101671792091106e-05 loss: 0.0815 (0.0844) time: 3.3802 data: 0.0082 max mem: 33370 +Epoch: [10] [ 570/1319] eta: 0:42:16 lr: 3.809288101453017e-05 loss: 0.0921 (0.0848) time: 3.3510 data: 0.0086 max mem: 33370 +Epoch: [10] [ 580/1319] eta: 0:41:42 lr: 3.808409001155601e-05 loss: 0.0892 (0.0849) time: 3.3783 data: 0.0082 max mem: 33370 +Epoch: [10] [ 590/1319] eta: 0:41:07 lr: 3.807529878310503e-05 loss: 0.0630 (0.0849) time: 3.3661 data: 0.0079 max mem: 33370 +Epoch: [10] [ 600/1319] eta: 0:40:34 lr: 3.806650732911359e-05 loss: 0.0661 (0.0848) time: 3.3822 data: 0.0080 max mem: 33370 +Epoch: [10] [ 610/1319] eta: 0:40:00 lr: 3.8057715649518045e-05 loss: 0.0661 (0.0846) time: 3.4162 data: 0.0087 max mem: 33370 +Epoch: [10] [ 620/1319] eta: 0:39:27 lr: 3.804892374425468e-05 loss: 0.0803 (0.0847) time: 3.3942 data: 0.0091 max mem: 33370 +Epoch: [10] [ 630/1319] eta: 0:38:53 lr: 3.804013161325975e-05 loss: 0.0849 (0.0846) time: 3.3951 data: 0.0084 max mem: 33370 +Epoch: [10] [ 640/1319] eta: 0:38:19 lr: 3.803133925646951e-05 loss: 0.0828 (0.0850) time: 3.3810 data: 0.0079 max mem: 33370 +Epoch: [10] [ 650/1319] eta: 0:37:45 lr: 3.802254667382014e-05 loss: 0.0828 (0.0852) time: 3.3783 data: 0.0080 max mem: 33370 +Epoch: [10] [ 660/1319] eta: 0:37:11 lr: 3.801375386524781e-05 loss: 0.0771 (0.0853) time: 3.3861 data: 0.0079 max mem: 33370 +Epoch: [10] [ 670/1319] eta: 0:36:37 lr: 3.800496083068865e-05 loss: 0.0767 (0.0851) time: 3.3680 data: 0.0078 max mem: 33370 +Epoch: [10] [ 680/1319] eta: 0:36:03 lr: 3.799616757007876e-05 loss: 0.0689 (0.0851) time: 3.3742 data: 0.0077 max mem: 33370 +Epoch: [10] [ 690/1319] eta: 0:35:29 lr: 3.798737408335417e-05 loss: 0.0783 (0.0851) time: 3.3674 data: 0.0075 max mem: 33370 +Epoch: [10] [ 700/1319] eta: 0:34:55 lr: 3.797858037045094e-05 loss: 0.0783 (0.0850) time: 3.3763 data: 0.0075 max mem: 33370 +Epoch: [10] [ 710/1319] eta: 0:34:21 lr: 3.796978643130504e-05 loss: 0.0662 (0.0848) time: 3.3907 data: 0.0078 max mem: 33370 +Epoch: [10] [ 720/1319] eta: 0:33:47 lr: 3.796099226585244e-05 loss: 0.0775 (0.0851) time: 3.3758 data: 0.0083 max mem: 33370 +Epoch: [10] [ 730/1319] eta: 0:33:14 lr: 3.795219787402904e-05 loss: 0.0946 (0.0852) time: 3.3822 data: 0.0080 max mem: 33370 +Epoch: [10] [ 740/1319] eta: 0:32:40 lr: 3.794340325577075e-05 loss: 0.0934 (0.0853) time: 3.3898 data: 0.0081 max mem: 33370 +Epoch: [10] [ 750/1319] eta: 0:32:05 lr: 3.79346084110134e-05 loss: 0.0891 (0.0856) time: 3.3579 data: 0.0083 max mem: 33370 +Epoch: [10] [ 760/1319] eta: 0:31:32 lr: 3.7925813339692824e-05 loss: 0.0812 (0.0856) time: 3.3590 data: 0.0081 max mem: 33370 +Epoch: [10] [ 770/1319] eta: 0:30:57 lr: 3.79170180417448e-05 loss: 0.0806 (0.0857) time: 3.3613 data: 0.0078 max mem: 33370 +Epoch: [10] [ 780/1319] eta: 0:30:23 lr: 3.790822251710506e-05 loss: 0.0923 (0.0860) time: 3.3439 data: 0.0076 max mem: 33370 +Epoch: [10] [ 790/1319] eta: 0:29:49 lr: 3.789942676570934e-05 loss: 0.0728 (0.0857) time: 3.3541 data: 0.0076 max mem: 33370 +Epoch: [10] [ 800/1319] eta: 0:29:16 lr: 3.7890630787493295e-05 loss: 0.0701 (0.0857) time: 3.3774 data: 0.0078 max mem: 33370 +Epoch: [10] [ 810/1319] eta: 0:28:41 lr: 3.788183458239259e-05 loss: 0.0760 (0.0859) time: 3.3734 data: 0.0085 max mem: 33370 +Epoch: [10] [ 820/1319] eta: 0:28:08 lr: 3.7873038150342824e-05 loss: 0.0750 (0.0857) time: 3.3729 data: 0.0085 max mem: 33370 +Epoch: [10] [ 830/1319] eta: 0:27:34 lr: 3.7864241491279565e-05 loss: 0.0733 (0.0858) time: 3.3686 data: 0.0081 max mem: 33370 +Epoch: [10] [ 840/1319] eta: 0:27:00 lr: 3.785544460513836e-05 loss: 0.0777 (0.0857) time: 3.3527 data: 0.0080 max mem: 33370 +Epoch: [10] [ 850/1319] eta: 0:26:26 lr: 3.784664749185471e-05 loss: 0.0765 (0.0858) time: 3.3761 data: 0.0077 max mem: 33370 +Epoch: [10] [ 860/1319] eta: 0:25:52 lr: 3.7837850151364085e-05 loss: 0.0765 (0.0856) time: 3.3827 data: 0.0077 max mem: 33370 +Epoch: [10] [ 870/1319] eta: 0:25:18 lr: 3.78290525836019e-05 loss: 0.0765 (0.0857) time: 3.3647 data: 0.0077 max mem: 33370 +Epoch: [10] [ 880/1319] eta: 0:24:44 lr: 3.782025478850358e-05 loss: 0.0711 (0.0856) time: 3.3649 data: 0.0075 max mem: 33370 +Epoch: [10] [ 890/1319] eta: 0:24:11 lr: 3.7811456766004476e-05 loss: 0.0669 (0.0856) time: 3.3928 data: 0.0077 max mem: 33370 +Epoch: [10] [ 900/1319] eta: 0:23:37 lr: 3.780265851603992e-05 loss: 0.0736 (0.0856) time: 3.3706 data: 0.0080 max mem: 33370 +Epoch: [10] [ 910/1319] eta: 0:23:03 lr: 3.779386003854519e-05 loss: 0.0831 (0.0860) time: 3.3447 data: 0.0079 max mem: 33370 +Epoch: [10] [ 920/1319] eta: 0:22:29 lr: 3.7785061333455565e-05 loss: 0.0790 (0.0859) time: 3.3725 data: 0.0076 max mem: 33370 +Epoch: [10] [ 930/1319] eta: 0:21:55 lr: 3.7776262400706265e-05 loss: 0.0783 (0.0862) time: 3.4136 data: 0.0075 max mem: 33370 +Epoch: [10] [ 940/1319] eta: 0:21:21 lr: 3.776746324023246e-05 loss: 0.0837 (0.0863) time: 3.4143 data: 0.0074 max mem: 33370 +Epoch: [10] [ 950/1319] eta: 0:20:48 lr: 3.775866385196932e-05 loss: 0.0837 (0.0864) time: 3.3974 data: 0.0079 max mem: 33370 +Epoch: [10] [ 960/1319] eta: 0:20:14 lr: 3.774986423585195e-05 loss: 0.0850 (0.0868) time: 3.4036 data: 0.0080 max mem: 33370 +Epoch: [10] [ 970/1319] eta: 0:19:40 lr: 3.7741064391815444e-05 loss: 0.0938 (0.0869) time: 3.3843 data: 0.0078 max mem: 33370 +Epoch: [10] [ 980/1319] eta: 0:19:06 lr: 3.7732264319794836e-05 loss: 0.0784 (0.0868) time: 3.3751 data: 0.0080 max mem: 33370 +Epoch: [10] [ 990/1319] eta: 0:18:32 lr: 3.772346401972514e-05 loss: 0.0665 (0.0868) time: 3.3596 data: 0.0081 max mem: 33370 +Epoch: [10] [1000/1319] eta: 0:17:58 lr: 3.771466349154134e-05 loss: 0.0770 (0.0868) time: 3.3387 data: 0.0084 max mem: 33370 +Epoch: [10] [1010/1319] eta: 0:17:24 lr: 3.7705862735178374e-05 loss: 0.0770 (0.0870) time: 3.3416 data: 0.0084 max mem: 33370 +Epoch: [10] [1020/1319] eta: 0:16:50 lr: 3.7697061750571136e-05 loss: 0.0724 (0.0870) time: 3.3435 data: 0.0081 max mem: 33370 +Epoch: [10] [1030/1319] eta: 0:16:17 lr: 3.768826053765451e-05 loss: 0.0885 (0.0872) time: 3.3553 data: 0.0081 max mem: 33370 +Epoch: [10] [1040/1319] eta: 0:15:43 lr: 3.767945909636332e-05 loss: 0.0885 (0.0872) time: 3.3442 data: 0.0079 max mem: 33370 +Epoch: [10] [1050/1319] eta: 0:15:09 lr: 3.767065742663237e-05 loss: 0.0726 (0.0870) time: 3.3512 data: 0.0078 max mem: 33370 +Epoch: [10] [1060/1319] eta: 0:14:35 lr: 3.7661855528396415e-05 loss: 0.0687 (0.0870) time: 3.3531 data: 0.0078 max mem: 33370 +Epoch: [10] [1070/1319] eta: 0:14:01 lr: 3.765305340159019e-05 loss: 0.0944 (0.0871) time: 3.3172 data: 0.0079 max mem: 33370 +Epoch: [10] [1080/1319] eta: 0:13:27 lr: 3.764425104614838e-05 loss: 0.0953 (0.0872) time: 3.3293 data: 0.0079 max mem: 33370 +Epoch: [10] [1090/1319] eta: 0:12:53 lr: 3.763544846200565e-05 loss: 0.0930 (0.0875) time: 3.3722 data: 0.0082 max mem: 33370 +Epoch: [10] [1100/1319] eta: 0:12:19 lr: 3.7626645649096614e-05 loss: 0.0772 (0.0874) time: 3.3684 data: 0.0084 max mem: 33370 +Epoch: [10] [1110/1319] eta: 0:11:46 lr: 3.761784260735586e-05 loss: 0.0758 (0.0873) time: 3.3605 data: 0.0082 max mem: 33370 +Epoch: [10] [1120/1319] eta: 0:11:12 lr: 3.760903933671793e-05 loss: 0.0762 (0.0872) time: 3.3510 data: 0.0079 max mem: 33370 +Epoch: [10] [1130/1319] eta: 0:10:38 lr: 3.760023583711735e-05 loss: 0.0801 (0.0875) time: 3.3494 data: 0.0082 max mem: 33370 +Epoch: [10] [1140/1319] eta: 0:10:04 lr: 3.7591432108488584e-05 loss: 0.0765 (0.0874) time: 3.3499 data: 0.0083 max mem: 33370 +Epoch: [10] [1150/1319] eta: 0:09:30 lr: 3.758262815076608e-05 loss: 0.0765 (0.0874) time: 3.3192 data: 0.0080 max mem: 33370 +Epoch: [10] [1160/1319] eta: 0:08:56 lr: 3.7573823963884245e-05 loss: 0.0886 (0.0874) time: 3.3210 data: 0.0078 max mem: 33370 +Epoch: [10] [1170/1319] eta: 0:08:23 lr: 3.756501954777745e-05 loss: 0.0859 (0.0875) time: 3.3423 data: 0.0075 max mem: 33370 +Epoch: [10] [1180/1319] eta: 0:07:49 lr: 3.755621490238003e-05 loss: 0.0859 (0.0874) time: 3.3422 data: 0.0076 max mem: 33370 +Epoch: [10] [1190/1319] eta: 0:07:15 lr: 3.754741002762627e-05 loss: 0.0848 (0.0875) time: 3.3480 data: 0.0079 max mem: 33370 +Epoch: [10] [1200/1319] eta: 0:06:41 lr: 3.753860492345044e-05 loss: 0.0862 (0.0876) time: 3.3854 data: 0.0078 max mem: 33370 +Epoch: [10] [1210/1319] eta: 0:06:07 lr: 3.7529799589786776e-05 loss: 0.0782 (0.0876) time: 3.3700 data: 0.0077 max mem: 33370 +Epoch: [10] [1220/1319] eta: 0:05:34 lr: 3.752099402656945e-05 loss: 0.0855 (0.0876) time: 3.3320 data: 0.0077 max mem: 33370 +Epoch: [10] [1230/1319] eta: 0:05:00 lr: 3.751218823373263e-05 loss: 0.0921 (0.0878) time: 3.3309 data: 0.0078 max mem: 33370 +Epoch: [10] [1240/1319] eta: 0:04:26 lr: 3.750338221121043e-05 loss: 0.0799 (0.0877) time: 3.3458 data: 0.0078 max mem: 33370 +Epoch: [10] [1250/1319] eta: 0:03:52 lr: 3.749457595893693e-05 loss: 0.0763 (0.0879) time: 3.3639 data: 0.0077 max mem: 33370 +Epoch: [10] [1260/1319] eta: 0:03:19 lr: 3.748576947684619e-05 loss: 0.0794 (0.0879) time: 3.3634 data: 0.0080 max mem: 33370 +Epoch: [10] [1270/1319] eta: 0:02:45 lr: 3.74769627648722e-05 loss: 0.0808 (0.0881) time: 3.3564 data: 0.0080 max mem: 33370 +Epoch: [10] [1280/1319] eta: 0:02:11 lr: 3.746815582294894e-05 loss: 0.0808 (0.0880) time: 3.3689 data: 0.0079 max mem: 33370 +Epoch: [10] [1290/1319] eta: 0:01:37 lr: 3.745934865101035e-05 loss: 0.0751 (0.0880) time: 3.3589 data: 0.0082 max mem: 33370 +Epoch: [10] [1300/1319] eta: 0:01:04 lr: 3.7450541248990324e-05 loss: 0.0765 (0.0880) time: 3.3560 data: 0.0081 max mem: 33370 +Epoch: [10] [1310/1319] eta: 0:00:30 lr: 3.7441733616822736e-05 loss: 0.0828 (0.0881) time: 3.3453 data: 0.0075 max mem: 33370 +Epoch: [10] Total time: 1:14:10 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 3:05:10 time: 4.3180 data: 4.2362 max mem: 33370 +Test: [ 100/2573] eta: 0:04:51 time: 0.0759 data: 0.0015 max mem: 33370 +Test: [ 200/2573] eta: 0:03:53 time: 0.0775 data: 0.0015 max mem: 33370 +Test: [ 300/2573] eta: 0:03:26 time: 0.0791 data: 0.0014 max mem: 33370 +Test: [ 400/2573] eta: 0:03:10 time: 0.0797 data: 0.0014 max mem: 33370 +Test: [ 500/2573] eta: 0:02:57 time: 0.0785 data: 0.0015 max mem: 33370 +Test: [ 600/2573] eta: 0:02:46 time: 0.0777 data: 0.0013 max mem: 33370 +Test: [ 700/2573] eta: 0:02:37 time: 0.0779 data: 0.0013 max mem: 33370 +Test: [ 800/2573] eta: 0:02:27 time: 0.0816 data: 0.0013 max mem: 33370 +Test: [ 900/2573] eta: 0:02:18 time: 0.0796 data: 0.0014 max mem: 33370 +Test: [1000/2573] eta: 0:02:10 time: 0.0793 data: 0.0015 max mem: 33370 +Test: [1100/2573] eta: 0:02:01 time: 0.0792 data: 0.0014 max mem: 33370 +Test: [1200/2573] eta: 0:01:52 time: 0.0800 data: 0.0014 max mem: 33370 +Test: [1300/2573] eta: 0:01:44 time: 0.0796 data: 0.0013 max mem: 33370 +Test: [1400/2573] eta: 0:01:35 time: 0.0769 data: 0.0014 max mem: 33370 +Test: [1500/2573] eta: 0:01:27 time: 0.0793 data: 0.0015 max mem: 33370 +Test: [1600/2573] eta: 0:01:19 time: 0.0837 data: 0.0016 max mem: 33370 +Test: [1700/2573] eta: 0:01:11 time: 0.0792 data: 0.0014 max mem: 33370 +Test: [1800/2573] eta: 0:01:02 time: 0.0812 data: 0.0014 max mem: 33370 +Test: [1900/2573] eta: 0:00:54 time: 0.0787 data: 0.0015 max mem: 33370 +Test: [2000/2573] eta: 0:00:46 time: 0.0795 data: 0.0014 max mem: 33370 +Test: [2100/2573] eta: 0:00:38 time: 0.0813 data: 0.0014 max mem: 33370 +Test: [2200/2573] eta: 0:00:30 time: 0.0813 data: 0.0013 max mem: 33370 +Test: [2300/2573] eta: 0:00:22 time: 0.0806 data: 0.0013 max mem: 33370 +Test: [2400/2573] eta: 0:00:13 time: 0.0758 data: 0.0013 max mem: 33370 +Test: [2500/2573] eta: 0:00:05 time: 0.0794 data: 0.0015 max mem: 33370 +Test: Total time: 0:03:28 +Final results: +Mean IoU is 60.11 + + precision@0.5 = 66.83 + precision@0.6 = 60.93 + precision@0.7 = 52.70 + precision@0.8 = 40.40 + precision@0.9 = 18.22 + overall IoU = 58.81 + +Average object IoU 60.11112736332799 +Overall IoU 58.80549240112305 +Better epoch: 10 + +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [11] [ 0/1319] eta: 2:00:11 lr: 3.743380655104104e-05 loss: 0.0576 (0.0576) time: 5.4677 data: 1.8784 max mem: 33370 +Epoch: [11] [ 10/1319] eta: 1:18:39 lr: 3.742499848141075e-05 loss: 0.0706 (0.0785) time: 3.6055 data: 0.1779 max mem: 33370 +Epoch: [11] [ 20/1319] eta: 1:15:57 lr: 3.741619018144089e-05 loss: 0.0607 (0.0790) time: 3.4103 data: 0.0078 max mem: 33370 +Epoch: [11] [ 30/1319] eta: 1:14:39 lr: 3.7407381651065185e-05 loss: 0.0574 (0.0819) time: 3.4038 data: 0.0079 max mem: 33370 +Epoch: [11] [ 40/1319] eta: 1:13:47 lr: 3.739857289021734e-05 loss: 0.0695 (0.0813) time: 3.4121 data: 0.0079 max mem: 33370 +Epoch: [11] [ 50/1319] eta: 1:12:59 lr: 3.738976389883098e-05 loss: 0.0767 (0.0822) time: 3.4142 data: 0.0076 max mem: 33370 +Epoch: [11] [ 60/1319] eta: 1:12:21 lr: 3.738095467683973e-05 loss: 0.0742 (0.0819) time: 3.4226 data: 0.0075 max mem: 33370 +Epoch: [11] [ 70/1319] eta: 1:11:31 lr: 3.737214522417717e-05 loss: 0.0735 (0.0808) time: 3.3956 data: 0.0078 max mem: 33370 +Epoch: [11] [ 80/1319] eta: 1:10:45 lr: 3.736333554077684e-05 loss: 0.0687 (0.0799) time: 3.3584 data: 0.0079 max mem: 33370 +Epoch: [11] [ 90/1319] eta: 1:10:06 lr: 3.735452562657224e-05 loss: 0.0737 (0.0819) time: 3.3764 data: 0.0079 max mem: 33370 +Epoch: [11] [ 100/1319] eta: 1:09:27 lr: 3.734571548149683e-05 loss: 0.0776 (0.0825) time: 3.3870 data: 0.0080 max mem: 33370 +Epoch: [11] [ 110/1319] eta: 1:08:48 lr: 3.733690510548406e-05 loss: 0.0741 (0.0818) time: 3.3813 data: 0.0079 max mem: 33370 +Epoch: [11] [ 120/1319] eta: 1:08:08 lr: 3.732809449846732e-05 loss: 0.0741 (0.0815) time: 3.3637 data: 0.0080 max mem: 33370 +Epoch: [11] [ 130/1319] eta: 1:07:28 lr: 3.7319283660379954e-05 loss: 0.0654 (0.0798) time: 3.3495 data: 0.0079 max mem: 33370 +Epoch: [11] [ 140/1319] eta: 1:06:50 lr: 3.7310472591155297e-05 loss: 0.0626 (0.0792) time: 3.3542 data: 0.0080 max mem: 33370 +Epoch: [11] [ 150/1319] eta: 1:06:13 lr: 3.7301661290726626e-05 loss: 0.0717 (0.0789) time: 3.3570 data: 0.0081 max mem: 33370 +Epoch: [11] [ 160/1319] eta: 1:05:35 lr: 3.729284975902719e-05 loss: 0.0771 (0.0792) time: 3.3518 data: 0.0081 max mem: 33370 +Epoch: [11] [ 170/1319] eta: 1:05:01 lr: 3.728403799599019e-05 loss: 0.0751 (0.0788) time: 3.3736 data: 0.0082 max mem: 33370 +Epoch: [11] [ 180/1319] eta: 1:04:27 lr: 3.727522600154881e-05 loss: 0.0753 (0.0798) time: 3.3930 data: 0.0080 max mem: 33370 +Epoch: [11] [ 190/1319] eta: 1:03:52 lr: 3.7266413775636196e-05 loss: 0.0852 (0.0804) time: 3.3832 data: 0.0078 max mem: 33370 +Epoch: [11] [ 200/1319] eta: 1:03:15 lr: 3.725760131818543e-05 loss: 0.0830 (0.0798) time: 3.3615 data: 0.0078 max mem: 33370 +Epoch: [11] [ 210/1319] eta: 1:02:38 lr: 3.724878862912958e-05 loss: 0.0621 (0.0796) time: 3.3369 data: 0.0081 max mem: 33370 +Epoch: [11] [ 220/1319] eta: 1:02:01 lr: 3.723997570840168e-05 loss: 0.0673 (0.0801) time: 3.3281 data: 0.0084 max mem: 33370 +Epoch: [11] [ 230/1319] eta: 1:01:26 lr: 3.723116255593471e-05 loss: 0.0704 (0.0800) time: 3.3396 data: 0.0082 max mem: 33370 +Epoch: [11] [ 240/1319] eta: 1:00:52 lr: 3.7222349171661633e-05 loss: 0.0788 (0.0805) time: 3.3722 data: 0.0078 max mem: 33370 +Epoch: [11] [ 250/1319] eta: 1:00:14 lr: 3.721353555551535e-05 loss: 0.0778 (0.0799) time: 3.3437 data: 0.0081 max mem: 33370 +Epoch: [11] [ 260/1319] eta: 0:59:39 lr: 3.720472170742875e-05 loss: 0.0722 (0.0802) time: 3.3212 data: 0.0081 max mem: 33370 +Epoch: [11] [ 270/1319] eta: 0:59:03 lr: 3.719590762733466e-05 loss: 0.0862 (0.0804) time: 3.3319 data: 0.0079 max mem: 33370 +Epoch: [11] [ 280/1319] eta: 0:58:28 lr: 3.718709331516589e-05 loss: 0.0820 (0.0803) time: 3.3377 data: 0.0079 max mem: 33370 +Epoch: [11] [ 290/1319] eta: 0:57:55 lr: 3.7178278770855225e-05 loss: 0.0783 (0.0800) time: 3.3763 data: 0.0081 max mem: 33370 +Epoch: [11] [ 300/1319] eta: 0:57:21 lr: 3.716946399433537e-05 loss: 0.0738 (0.0799) time: 3.3786 data: 0.0083 max mem: 33370 +Epoch: [11] [ 310/1319] eta: 0:56:46 lr: 3.716064898553902e-05 loss: 0.0738 (0.0801) time: 3.3596 data: 0.0080 max mem: 33370 +Epoch: [11] [ 320/1319] eta: 0:56:11 lr: 3.715183374439884e-05 loss: 0.0706 (0.0797) time: 3.3468 data: 0.0079 max mem: 33370 +Epoch: [11] [ 330/1319] eta: 0:55:37 lr: 3.7143018270847454e-05 loss: 0.0706 (0.0796) time: 3.3391 data: 0.0082 max mem: 33370 +Epoch: [11] [ 340/1319] eta: 0:55:03 lr: 3.713420256481742e-05 loss: 0.0676 (0.0795) time: 3.3541 data: 0.0080 max mem: 33370 +Epoch: [11] [ 350/1319] eta: 0:54:28 lr: 3.712538662624129e-05 loss: 0.0700 (0.0793) time: 3.3537 data: 0.0078 max mem: 33370 +Epoch: [11] [ 360/1319] eta: 0:53:54 lr: 3.7116570455051586e-05 loss: 0.0679 (0.0792) time: 3.3579 data: 0.0081 max mem: 33370 +Epoch: [11] [ 370/1319] eta: 0:53:19 lr: 3.710775405118075e-05 loss: 0.0814 (0.0795) time: 3.3455 data: 0.0079 max mem: 33370 +Epoch: [11] [ 380/1319] eta: 0:52:45 lr: 3.709893741456123e-05 loss: 0.0759 (0.0794) time: 3.3387 data: 0.0076 max mem: 33370 +Epoch: [11] [ 390/1319] eta: 0:52:11 lr: 3.709012054512541e-05 loss: 0.0721 (0.0797) time: 3.3524 data: 0.0075 max mem: 33370 +Epoch: [11] [ 400/1319] eta: 0:51:37 lr: 3.7081303442805645e-05 loss: 0.0730 (0.0799) time: 3.3483 data: 0.0078 max mem: 33370 +Epoch: [11] [ 410/1319] eta: 0:51:01 lr: 3.7072486107534264e-05 loss: 0.0801 (0.0801) time: 3.3231 data: 0.0080 max mem: 33370 +Epoch: [11] [ 420/1319] eta: 0:50:28 lr: 3.706366853924354e-05 loss: 0.0795 (0.0800) time: 3.3337 data: 0.0078 max mem: 33370 +Epoch: [11] [ 430/1319] eta: 0:49:54 lr: 3.705485073786572e-05 loss: 0.0766 (0.0798) time: 3.3594 data: 0.0077 max mem: 33370 +Epoch: [11] [ 440/1319] eta: 0:49:20 lr: 3.704603270333301e-05 loss: 0.0606 (0.0795) time: 3.3722 data: 0.0079 max mem: 33370 +Epoch: [11] [ 450/1319] eta: 0:48:46 lr: 3.703721443557757e-05 loss: 0.0679 (0.0799) time: 3.3626 data: 0.0079 max mem: 33370 +Epoch: [11] [ 460/1319] eta: 0:48:12 lr: 3.702839593453153e-05 loss: 0.0715 (0.0798) time: 3.3367 data: 0.0075 max mem: 33370 +Epoch: [11] [ 470/1319] eta: 0:47:38 lr: 3.7019577200126995e-05 loss: 0.0750 (0.0801) time: 3.3561 data: 0.0074 max mem: 33370 +Epoch: [11] [ 480/1319] eta: 0:47:04 lr: 3.701075823229601e-05 loss: 0.0715 (0.0801) time: 3.3514 data: 0.0076 max mem: 33370 +Epoch: [11] [ 490/1319] eta: 0:46:30 lr: 3.700193903097059e-05 loss: 0.0715 (0.0802) time: 3.3451 data: 0.0082 max mem: 33370 +Epoch: [11] [ 500/1319] eta: 0:45:57 lr: 3.6993119596082715e-05 loss: 0.0836 (0.0801) time: 3.3772 data: 0.0081 max mem: 33370 +Epoch: [11] [ 510/1319] eta: 0:45:23 lr: 3.698429992756433e-05 loss: 0.0758 (0.0801) time: 3.3776 data: 0.0077 max mem: 33370 +Epoch: [11] [ 520/1319] eta: 0:44:49 lr: 3.6975480025347336e-05 loss: 0.0801 (0.0801) time: 3.3575 data: 0.0079 max mem: 33370 +Epoch: [11] [ 530/1319] eta: 0:44:16 lr: 3.69666598893636e-05 loss: 0.0801 (0.0803) time: 3.3834 data: 0.0081 max mem: 33370 +Epoch: [11] [ 540/1319] eta: 0:43:42 lr: 3.695783951954495e-05 loss: 0.0876 (0.0805) time: 3.3789 data: 0.0081 max mem: 33370 +Epoch: [11] [ 550/1319] eta: 0:43:08 lr: 3.694901891582318e-05 loss: 0.0864 (0.0806) time: 3.3328 data: 0.0079 max mem: 33370 +Epoch: [11] [ 560/1319] eta: 0:42:34 lr: 3.694019807813003e-05 loss: 0.0818 (0.0806) time: 3.3425 data: 0.0076 max mem: 33370 +Epoch: [11] [ 570/1319] eta: 0:42:01 lr: 3.6931377006397214e-05 loss: 0.0735 (0.0807) time: 3.3728 data: 0.0076 max mem: 33370 +Epoch: [11] [ 580/1319] eta: 0:41:28 lr: 3.692255570055642e-05 loss: 0.0665 (0.0804) time: 3.3902 data: 0.0077 max mem: 33370 +Epoch: [11] [ 590/1319] eta: 0:40:54 lr: 3.691373416053928e-05 loss: 0.0678 (0.0804) time: 3.3859 data: 0.0076 max mem: 33370 +Epoch: [11] [ 600/1319] eta: 0:40:20 lr: 3.690491238627739e-05 loss: 0.0705 (0.0803) time: 3.3713 data: 0.0079 max mem: 33370 +Epoch: [11] [ 610/1319] eta: 0:39:47 lr: 3.6896090377702305e-05 loss: 0.0723 (0.0805) time: 3.3655 data: 0.0082 max mem: 33370 +Epoch: [11] [ 620/1319] eta: 0:39:12 lr: 3.688726813474555e-05 loss: 0.0723 (0.0805) time: 3.3365 data: 0.0083 max mem: 33370 +Epoch: [11] [ 630/1319] eta: 0:38:39 lr: 3.687844565733862e-05 loss: 0.0665 (0.0805) time: 3.3316 data: 0.0079 max mem: 33370 +Epoch: [11] [ 640/1319] eta: 0:38:05 lr: 3.686962294541296e-05 loss: 0.0645 (0.0802) time: 3.3428 data: 0.0075 max mem: 33370 +Epoch: [11] [ 650/1319] eta: 0:37:31 lr: 3.686079999889997e-05 loss: 0.0652 (0.0810) time: 3.3784 data: 0.0079 max mem: 33370 +Epoch: [11] [ 660/1319] eta: 0:36:58 lr: 3.6851976817731035e-05 loss: 0.0905 (0.0811) time: 3.3875 data: 0.0078 max mem: 33370 +Epoch: [11] [ 670/1319] eta: 0:36:24 lr: 3.684315340183746e-05 loss: 0.0870 (0.0812) time: 3.3592 data: 0.0076 max mem: 33370 +Epoch: [11] [ 680/1319] eta: 0:35:50 lr: 3.683432975115057e-05 loss: 0.0870 (0.0812) time: 3.3555 data: 0.0075 max mem: 33370 +Epoch: [11] [ 690/1319] eta: 0:35:17 lr: 3.682550586560159e-05 loss: 0.0823 (0.0814) time: 3.3723 data: 0.0074 max mem: 33370 +Epoch: [11] [ 700/1319] eta: 0:34:43 lr: 3.6816681745121755e-05 loss: 0.0823 (0.0815) time: 3.3844 data: 0.0077 max mem: 33370 +Epoch: [11] [ 710/1319] eta: 0:34:10 lr: 3.680785738964223e-05 loss: 0.0805 (0.0814) time: 3.4002 data: 0.0082 max mem: 33370 +Epoch: [11] [ 720/1319] eta: 0:33:36 lr: 3.679903279909417e-05 loss: 0.0692 (0.0814) time: 3.3843 data: 0.0080 max mem: 33370 +Epoch: [11] [ 730/1319] eta: 0:33:03 lr: 3.679020797340866e-05 loss: 0.0726 (0.0815) time: 3.3642 data: 0.0079 max mem: 33370 +Epoch: [11] [ 740/1319] eta: 0:32:29 lr: 3.678138291251678e-05 loss: 0.0802 (0.0816) time: 3.4018 data: 0.0080 max mem: 33370 +Epoch: [11] [ 750/1319] eta: 0:31:56 lr: 3.677255761634953e-05 loss: 0.0790 (0.0816) time: 3.4123 data: 0.0078 max mem: 33370 +Epoch: [11] [ 760/1319] eta: 0:31:23 lr: 3.6763732084837915e-05 loss: 0.0814 (0.0817) time: 3.3975 data: 0.0075 max mem: 33370 +Epoch: [11] [ 770/1319] eta: 0:30:49 lr: 3.675490631791288e-05 loss: 0.0849 (0.0822) time: 3.3822 data: 0.0077 max mem: 33370 +Epoch: [11] [ 780/1319] eta: 0:30:15 lr: 3.6746080315505315e-05 loss: 0.0791 (0.0821) time: 3.3707 data: 0.0077 max mem: 33370 +Epoch: [11] [ 790/1319] eta: 0:29:41 lr: 3.6737254077546116e-05 loss: 0.0806 (0.0825) time: 3.3660 data: 0.0074 max mem: 33370 +Epoch: [11] [ 800/1319] eta: 0:29:08 lr: 3.672842760396608e-05 loss: 0.0839 (0.0823) time: 3.3934 data: 0.0076 max mem: 33370 +Epoch: [11] [ 810/1319] eta: 0:28:34 lr: 3.6719600894696026e-05 loss: 0.0792 (0.0824) time: 3.3879 data: 0.0080 max mem: 33370 +Epoch: [11] [ 820/1319] eta: 0:28:01 lr: 3.6710773949666697e-05 loss: 0.0828 (0.0825) time: 3.3798 data: 0.0082 max mem: 33370 +Epoch: [11] [ 830/1319] eta: 0:27:27 lr: 3.6701946768808805e-05 loss: 0.0834 (0.0827) time: 3.3756 data: 0.0078 max mem: 33370 +Epoch: [11] [ 840/1319] eta: 0:26:53 lr: 3.6693119352053024e-05 loss: 0.0827 (0.0826) time: 3.3460 data: 0.0076 max mem: 33370 +Epoch: [11] [ 850/1319] eta: 0:26:20 lr: 3.668429169932999e-05 loss: 0.0833 (0.0828) time: 3.3604 data: 0.0080 max mem: 33370 +Epoch: [11] [ 860/1319] eta: 0:25:46 lr: 3.667546381057031e-05 loss: 0.0765 (0.0827) time: 3.3770 data: 0.0081 max mem: 33370 +Epoch: [11] [ 870/1319] eta: 0:25:12 lr: 3.666663568570454e-05 loss: 0.0691 (0.0826) time: 3.3526 data: 0.0077 max mem: 33370 +Epoch: [11] [ 880/1319] eta: 0:24:38 lr: 3.665780732466318e-05 loss: 0.0657 (0.0824) time: 3.3528 data: 0.0076 max mem: 33370 +Epoch: [11] [ 890/1319] eta: 0:24:05 lr: 3.6648978727376724e-05 loss: 0.0708 (0.0824) time: 3.3805 data: 0.0078 max mem: 33370 +Epoch: [11] [ 900/1319] eta: 0:23:31 lr: 3.664014989377562e-05 loss: 0.0708 (0.0823) time: 3.3784 data: 0.0078 max mem: 33370 +Epoch: [11] [ 910/1319] eta: 0:22:57 lr: 3.663132082379026e-05 loss: 0.0657 (0.0823) time: 3.3758 data: 0.0076 max mem: 33370 +Epoch: [11] [ 920/1319] eta: 0:22:24 lr: 3.6622491517351006e-05 loss: 0.0782 (0.0824) time: 3.3730 data: 0.0077 max mem: 33370 +Epoch: [11] [ 930/1319] eta: 0:21:50 lr: 3.661366197438818e-05 loss: 0.0819 (0.0824) time: 3.3831 data: 0.0080 max mem: 33370 +Epoch: [11] [ 940/1319] eta: 0:21:17 lr: 3.660483219483207e-05 loss: 0.0841 (0.0825) time: 3.3946 data: 0.0081 max mem: 33370 +Epoch: [11] [ 950/1319] eta: 0:20:43 lr: 3.659600217861292e-05 loss: 0.0794 (0.0825) time: 3.3980 data: 0.0077 max mem: 33370 +Epoch: [11] [ 960/1319] eta: 0:20:09 lr: 3.658717192566094e-05 loss: 0.0750 (0.0824) time: 3.3884 data: 0.0080 max mem: 33370 +Epoch: [11] [ 970/1319] eta: 0:19:36 lr: 3.6578341435906296e-05 loss: 0.0724 (0.0824) time: 3.3732 data: 0.0082 max mem: 33370 +Epoch: [11] [ 980/1319] eta: 0:19:02 lr: 3.656951070927911e-05 loss: 0.0684 (0.0823) time: 3.3849 data: 0.0074 max mem: 33370 +Epoch: [11] [ 990/1319] eta: 0:18:28 lr: 3.656067974570946e-05 loss: 0.0674 (0.0823) time: 3.3887 data: 0.0076 max mem: 33370 +Epoch: [11] [1000/1319] eta: 0:17:55 lr: 3.655184854512743e-05 loss: 0.0874 (0.0823) time: 3.3584 data: 0.0081 max mem: 33370 +Epoch: [11] [1010/1319] eta: 0:17:21 lr: 3.654301710746299e-05 loss: 0.0706 (0.0825) time: 3.3760 data: 0.0081 max mem: 33370 +Epoch: [11] [1020/1319] eta: 0:16:47 lr: 3.653418543264612e-05 loss: 0.0653 (0.0823) time: 3.3919 data: 0.0081 max mem: 33370 +Epoch: [11] [1030/1319] eta: 0:16:14 lr: 3.652535352060675e-05 loss: 0.0678 (0.0824) time: 3.3628 data: 0.0078 max mem: 33370 +Epoch: [11] [1040/1319] eta: 0:15:40 lr: 3.651652137127478e-05 loss: 0.0878 (0.0824) time: 3.3389 data: 0.0076 max mem: 33370 +Epoch: [11] [1050/1319] eta: 0:15:06 lr: 3.6507688984580056e-05 loss: 0.0798 (0.0824) time: 3.3367 data: 0.0077 max mem: 33370 +Epoch: [11] [1060/1319] eta: 0:14:32 lr: 3.649885636045239e-05 loss: 0.0741 (0.0822) time: 3.3671 data: 0.0078 max mem: 33370 +Epoch: [11] [1070/1319] eta: 0:13:59 lr: 3.6490023498821546e-05 loss: 0.0570 (0.0821) time: 3.3596 data: 0.0076 max mem: 33370 +Epoch: [11] [1080/1319] eta: 0:13:25 lr: 3.648119039961727e-05 loss: 0.0676 (0.0820) time: 3.3336 data: 0.0077 max mem: 33370 +Epoch: [11] [1090/1319] eta: 0:12:51 lr: 3.647235706276924e-05 loss: 0.0735 (0.0821) time: 3.3566 data: 0.0079 max mem: 33370 +Epoch: [11] [1100/1319] eta: 0:12:17 lr: 3.646352348820711e-05 loss: 0.0672 (0.0820) time: 3.3639 data: 0.0076 max mem: 33370 +Epoch: [11] [1110/1319] eta: 0:11:44 lr: 3.6454689675860496e-05 loss: 0.0697 (0.0819) time: 3.3488 data: 0.0073 max mem: 33370 +Epoch: [11] [1120/1319] eta: 0:11:10 lr: 3.6445855625658975e-05 loss: 0.0850 (0.0822) time: 3.3289 data: 0.0075 max mem: 33370 +Epoch: [11] [1130/1319] eta: 0:10:36 lr: 3.643702133753208e-05 loss: 0.0771 (0.0821) time: 3.3252 data: 0.0076 max mem: 33370 +Epoch: [11] [1140/1319] eta: 0:10:02 lr: 3.6428186811409296e-05 loss: 0.0761 (0.0822) time: 3.3579 data: 0.0078 max mem: 33370 +Epoch: [11] [1150/1319] eta: 0:09:29 lr: 3.641935204722008e-05 loss: 0.0844 (0.0822) time: 3.3949 data: 0.0078 max mem: 33370 +Epoch: [11] [1160/1319] eta: 0:08:55 lr: 3.6410517044893844e-05 loss: 0.0702 (0.0822) time: 3.4059 data: 0.0081 max mem: 33370 +Epoch: [11] [1170/1319] eta: 0:08:21 lr: 3.6401681804359965e-05 loss: 0.0702 (0.0822) time: 3.3694 data: 0.0081 max mem: 33370 +Epoch: [11] [1180/1319] eta: 0:07:48 lr: 3.6392846325547776e-05 loss: 0.0889 (0.0823) time: 3.3448 data: 0.0077 max mem: 33370 +Epoch: [11] [1190/1319] eta: 0:07:14 lr: 3.638401060838657e-05 loss: 0.0876 (0.0824) time: 3.3547 data: 0.0075 max mem: 33370 +Epoch: [11] [1200/1319] eta: 0:06:40 lr: 3.63751746528056e-05 loss: 0.0801 (0.0824) time: 3.3680 data: 0.0074 max mem: 33370 +Epoch: [11] [1210/1319] eta: 0:06:07 lr: 3.636633845873407e-05 loss: 0.0849 (0.0826) time: 3.3756 data: 0.0074 max mem: 33370 +Epoch: [11] [1220/1319] eta: 0:05:33 lr: 3.6357502026101176e-05 loss: 0.0973 (0.0827) time: 3.3644 data: 0.0071 max mem: 33370 +Epoch: [11] [1230/1319] eta: 0:04:59 lr: 3.6348665354836024e-05 loss: 0.0961 (0.0826) time: 3.3422 data: 0.0074 max mem: 33370 +Epoch: [11] [1240/1319] eta: 0:04:26 lr: 3.6339828444867725e-05 loss: 0.0756 (0.0826) time: 3.3637 data: 0.0076 max mem: 33370 +Epoch: [11] [1250/1319] eta: 0:03:52 lr: 3.6330991296125324e-05 loss: 0.0739 (0.0825) time: 3.3971 data: 0.0074 max mem: 33370 +Epoch: [11] [1260/1319] eta: 0:03:18 lr: 3.632215390853783e-05 loss: 0.0795 (0.0825) time: 3.4003 data: 0.0073 max mem: 33370 +Epoch: [11] [1270/1319] eta: 0:02:45 lr: 3.631331628203422e-05 loss: 0.0825 (0.0825) time: 3.3969 data: 0.0076 max mem: 33370 +Epoch: [11] [1280/1319] eta: 0:02:11 lr: 3.630447841654343e-05 loss: 0.0701 (0.0824) time: 3.3811 data: 0.0079 max mem: 33370 +Epoch: [11] [1290/1319] eta: 0:01:37 lr: 3.629564031199434e-05 loss: 0.0687 (0.0824) time: 3.3854 data: 0.0079 max mem: 33370 +Epoch: [11] [1300/1319] eta: 0:01:04 lr: 3.6286801968315816e-05 loss: 0.0799 (0.0824) time: 3.3934 data: 0.0079 max mem: 33370 +Epoch: [11] [1310/1319] eta: 0:00:30 lr: 3.627796338543665e-05 loss: 0.0784 (0.0824) time: 3.3878 data: 0.0074 max mem: 33370 +Epoch: [11] Total time: 1:14:05 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 2:56:12 time: 4.1090 data: 3.9945 max mem: 33370 +Test: [ 100/2573] eta: 0:04:47 time: 0.0766 data: 0.0014 max mem: 33370 +Test: [ 200/2573] eta: 0:03:51 time: 0.0776 data: 0.0014 max mem: 33370 +Test: [ 300/2573] eta: 0:03:26 time: 0.0802 data: 0.0013 max mem: 33370 +Test: [ 400/2573] eta: 0:03:10 time: 0.0800 data: 0.0014 max mem: 33370 +Test: [ 500/2573] eta: 0:02:58 time: 0.0789 data: 0.0014 max mem: 33370 +Test: [ 600/2573] eta: 0:02:47 time: 0.0793 data: 0.0014 max mem: 33370 +Test: [ 700/2573] eta: 0:02:38 time: 0.0790 data: 0.0014 max mem: 33370 +Test: [ 800/2573] eta: 0:02:28 time: 0.0836 data: 0.0015 max mem: 33370 +Test: [ 900/2573] eta: 0:02:19 time: 0.0788 data: 0.0014 max mem: 33370 +Test: [1000/2573] eta: 0:02:10 time: 0.0794 data: 0.0014 max mem: 33370 +Test: [1100/2573] eta: 0:02:02 time: 0.0801 data: 0.0014 max mem: 33370 +Test: [1200/2573] eta: 0:01:53 time: 0.0794 data: 0.0014 max mem: 33370 +Test: [1300/2573] eta: 0:01:44 time: 0.0802 data: 0.0014 max mem: 33370 +Test: [1400/2573] eta: 0:01:36 time: 0.0788 data: 0.0014 max mem: 33370 +Test: [1500/2573] eta: 0:01:28 time: 0.0794 data: 0.0014 max mem: 33370 +Test: [1600/2573] eta: 0:01:19 time: 0.0823 data: 0.0013 max mem: 33370 +Test: [1700/2573] eta: 0:01:11 time: 0.0783 data: 0.0013 max mem: 33370 +Test: [1800/2573] eta: 0:01:03 time: 0.0809 data: 0.0014 max mem: 33370 +Test: [1900/2573] eta: 0:00:54 time: 0.0787 data: 0.0014 max mem: 33370 +Test: [2000/2573] eta: 0:00:46 time: 0.0795 data: 0.0013 max mem: 33370 +Test: [2100/2573] eta: 0:00:38 time: 0.0813 data: 0.0014 max mem: 33370 +Test: [2200/2573] eta: 0:00:30 time: 0.0813 data: 0.0014 max mem: 33370 +Test: [2300/2573] eta: 0:00:22 time: 0.0806 data: 0.0013 max mem: 33370 +Test: [2400/2573] eta: 0:00:14 time: 0.0759 data: 0.0014 max mem: 33370 +Test: [2500/2573] eta: 0:00:05 time: 0.0793 data: 0.0014 max mem: 33370 +Test: Total time: 0:03:28 +Final results: +Mean IoU is 60.73 + + precision@0.5 = 67.99 + precision@0.6 = 61.66 + precision@0.7 = 53.55 + precision@0.8 = 41.81 + precision@0.9 = 19.22 + overall IoU = 59.73 + +Average object IoU 60.73024296414127 +Overall IoU 59.73251724243164 +Better epoch: 11 + +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [12] [ 0/1319] eta: 2:06:05 lr: 3.6270008456269996e-05 loss: 0.0617 (0.0617) time: 5.7357 data: 2.3607 max mem: 33370 +Epoch: [12] [ 10/1319] eta: 1:18:14 lr: 3.6261169418713356e-05 loss: 0.0703 (0.0734) time: 3.5865 data: 0.2211 max mem: 33370 +Epoch: [12] [ 20/1319] eta: 1:15:04 lr: 3.62523301417494e-05 loss: 0.0753 (0.0808) time: 3.3544 data: 0.0069 max mem: 33370 +Epoch: [12] [ 30/1319] eta: 1:13:53 lr: 3.624349062530679e-05 loss: 0.0751 (0.0774) time: 3.3584 data: 0.0071 max mem: 33370 +Epoch: [12] [ 40/1319] eta: 1:13:05 lr: 3.623465086931413e-05 loss: 0.0643 (0.0801) time: 3.3874 data: 0.0077 max mem: 33370 +Epoch: [12] [ 50/1319] eta: 1:12:15 lr: 3.62258108737e-05 loss: 0.0626 (0.0791) time: 3.3815 data: 0.0078 max mem: 33370 +Epoch: [12] [ 60/1319] eta: 1:11:30 lr: 3.621697063839292e-05 loss: 0.0740 (0.0804) time: 3.3663 data: 0.0081 max mem: 33370 +Epoch: [12] [ 70/1319] eta: 1:10:53 lr: 3.6208130163321375e-05 loss: 0.0696 (0.0794) time: 3.3769 data: 0.0081 max mem: 33370 +Epoch: [12] [ 80/1319] eta: 1:10:11 lr: 3.619928944841383e-05 loss: 0.0675 (0.0785) time: 3.3726 data: 0.0076 max mem: 33370 +Epoch: [12] [ 90/1319] eta: 1:09:32 lr: 3.6190448493598675e-05 loss: 0.0663 (0.0795) time: 3.3570 data: 0.0076 max mem: 33370 +Epoch: [12] [ 100/1319] eta: 1:08:59 lr: 3.61816072988043e-05 loss: 0.0663 (0.0803) time: 3.3810 data: 0.0076 max mem: 33370 +Epoch: [12] [ 110/1319] eta: 1:08:19 lr: 3.617276586395901e-05 loss: 0.0661 (0.0793) time: 3.3712 data: 0.0075 max mem: 33370 +Epoch: [12] [ 120/1319] eta: 1:07:41 lr: 3.61639241889911e-05 loss: 0.0638 (0.0775) time: 3.3452 data: 0.0077 max mem: 33370 +Epoch: [12] [ 130/1319] eta: 1:07:01 lr: 3.615508227382881e-05 loss: 0.0655 (0.0785) time: 3.3369 data: 0.0078 max mem: 33370 +Epoch: [12] [ 140/1319] eta: 1:06:27 lr: 3.614624011840035e-05 loss: 0.0840 (0.0788) time: 3.3509 data: 0.0079 max mem: 33370 +Epoch: [12] [ 150/1319] eta: 1:05:52 lr: 3.613739772263389e-05 loss: 0.0647 (0.0777) time: 3.3705 data: 0.0080 max mem: 33370 +Epoch: [12] [ 160/1319] eta: 1:05:16 lr: 3.6128555086457536e-05 loss: 0.0595 (0.0767) time: 3.3575 data: 0.0077 max mem: 33370 +Epoch: [12] [ 170/1319] eta: 1:04:41 lr: 3.6119712209799373e-05 loss: 0.0613 (0.0762) time: 3.3576 data: 0.0080 max mem: 33370 +Epoch: [12] [ 180/1319] eta: 1:04:08 lr: 3.6110869092587446e-05 loss: 0.0641 (0.0771) time: 3.3755 data: 0.0082 max mem: 33370 +Epoch: [12] [ 190/1319] eta: 1:03:35 lr: 3.610202573474975e-05 loss: 0.0663 (0.0765) time: 3.3935 data: 0.0077 max mem: 33370 +Epoch: [12] [ 200/1319] eta: 1:03:01 lr: 3.609318213621424e-05 loss: 0.0639 (0.0765) time: 3.3884 data: 0.0075 max mem: 33370 +Epoch: [12] [ 210/1319] eta: 1:02:26 lr: 3.608433829690883e-05 loss: 0.0771 (0.0768) time: 3.3617 data: 0.0075 max mem: 33370 +Epoch: [12] [ 220/1319] eta: 1:01:50 lr: 3.607549421676141e-05 loss: 0.0744 (0.0765) time: 3.3422 data: 0.0077 max mem: 33370 +Epoch: [12] [ 230/1319] eta: 1:01:16 lr: 3.6066649895699786e-05 loss: 0.0693 (0.0762) time: 3.3599 data: 0.0078 max mem: 33370 +Epoch: [12] [ 240/1319] eta: 1:00:43 lr: 3.6057805333651786e-05 loss: 0.0712 (0.0773) time: 3.3767 data: 0.0075 max mem: 33370 +Epoch: [12] [ 250/1319] eta: 1:00:08 lr: 3.604896053054513e-05 loss: 0.0888 (0.0779) time: 3.3653 data: 0.0074 max mem: 33370 +Epoch: [12] [ 260/1319] eta: 0:59:34 lr: 3.604011548630754e-05 loss: 0.0727 (0.0774) time: 3.3593 data: 0.0076 max mem: 33370 +Epoch: [12] [ 270/1319] eta: 0:59:00 lr: 3.6031270200866694e-05 loss: 0.0667 (0.0774) time: 3.3692 data: 0.0077 max mem: 33370 +Epoch: [12] [ 280/1319] eta: 0:58:26 lr: 3.6022424674150204e-05 loss: 0.0749 (0.0777) time: 3.3670 data: 0.0074 max mem: 33370 +Epoch: [12] [ 290/1319] eta: 0:57:51 lr: 3.601357890608566e-05 loss: 0.0748 (0.0776) time: 3.3516 data: 0.0079 max mem: 33370 +Epoch: [12] [ 300/1319] eta: 0:57:17 lr: 3.6004732896600616e-05 loss: 0.0626 (0.0774) time: 3.3621 data: 0.0083 max mem: 33370 +Epoch: [12] [ 310/1319] eta: 0:56:44 lr: 3.599588664562255e-05 loss: 0.0626 (0.0773) time: 3.3870 data: 0.0079 max mem: 33370 +Epoch: [12] [ 320/1319] eta: 0:56:10 lr: 3.598704015307894e-05 loss: 0.0678 (0.0771) time: 3.3768 data: 0.0078 max mem: 33370 +Epoch: [12] [ 330/1319] eta: 0:55:36 lr: 3.597819341889721e-05 loss: 0.0664 (0.0768) time: 3.3586 data: 0.0075 max mem: 33370 +Epoch: [12] [ 340/1319] eta: 0:55:04 lr: 3.5969346443004724e-05 loss: 0.0648 (0.0765) time: 3.3980 data: 0.0077 max mem: 33370 +Epoch: [12] [ 350/1319] eta: 0:54:31 lr: 3.596049922532882e-05 loss: 0.0612 (0.0765) time: 3.4261 data: 0.0080 max mem: 33370 +Epoch: [12] [ 360/1319] eta: 0:53:58 lr: 3.5951651765796805e-05 loss: 0.0650 (0.0763) time: 3.4136 data: 0.0080 max mem: 33370 +Epoch: [12] [ 370/1319] eta: 0:53:23 lr: 3.594280406433592e-05 loss: 0.0649 (0.0759) time: 3.3649 data: 0.0081 max mem: 33370 +Epoch: [12] [ 380/1319] eta: 0:52:48 lr: 3.593395612087339e-05 loss: 0.0702 (0.0766) time: 3.3229 data: 0.0081 max mem: 33370 +Epoch: [12] [ 390/1319] eta: 0:52:14 lr: 3.5925107935336354e-05 loss: 0.0711 (0.0766) time: 3.3431 data: 0.0080 max mem: 33370 +Epoch: [12] [ 400/1319] eta: 0:51:40 lr: 3.5916259507651966e-05 loss: 0.0682 (0.0767) time: 3.3612 data: 0.0076 max mem: 33370 +Epoch: [12] [ 410/1319] eta: 0:51:06 lr: 3.59074108377473e-05 loss: 0.0644 (0.0766) time: 3.3671 data: 0.0077 max mem: 33370 +Epoch: [12] [ 420/1319] eta: 0:50:33 lr: 3.58985619255494e-05 loss: 0.0580 (0.0765) time: 3.3910 data: 0.0078 max mem: 33370 +Epoch: [12] [ 430/1319] eta: 0:49:59 lr: 3.588971277098527e-05 loss: 0.0520 (0.0760) time: 3.3822 data: 0.0080 max mem: 33370 +Epoch: [12] [ 440/1319] eta: 0:49:26 lr: 3.588086337398186e-05 loss: 0.0590 (0.0761) time: 3.3807 data: 0.0077 max mem: 33370 +Epoch: [12] [ 450/1319] eta: 0:48:53 lr: 3.58720137344661e-05 loss: 0.0653 (0.0760) time: 3.4055 data: 0.0076 max mem: 33370 +Epoch: [12] [ 460/1319] eta: 0:48:19 lr: 3.5863163852364855e-05 loss: 0.0814 (0.0761) time: 3.3880 data: 0.0077 max mem: 33370 +Epoch: [12] [ 470/1319] eta: 0:47:46 lr: 3.585431372760496e-05 loss: 0.0686 (0.0763) time: 3.3827 data: 0.0075 max mem: 33370 +Epoch: [12] [ 480/1319] eta: 0:47:12 lr: 3.5845463360113225e-05 loss: 0.0602 (0.0762) time: 3.3910 data: 0.0078 max mem: 33370 +Epoch: [12] [ 490/1319] eta: 0:46:38 lr: 3.583661274981637e-05 loss: 0.0649 (0.0763) time: 3.3803 data: 0.0081 max mem: 33370 +Epoch: [12] [ 500/1319] eta: 0:46:04 lr: 3.582776189664111e-05 loss: 0.0658 (0.0762) time: 3.3692 data: 0.0077 max mem: 33370 +Epoch: [12] [ 510/1319] eta: 0:45:30 lr: 3.581891080051412e-05 loss: 0.0622 (0.0760) time: 3.3538 data: 0.0075 max mem: 33370 +Epoch: [12] [ 520/1319] eta: 0:44:56 lr: 3.5810059461362006e-05 loss: 0.0817 (0.0767) time: 3.3544 data: 0.0076 max mem: 33370 +Epoch: [12] [ 530/1319] eta: 0:44:22 lr: 3.580120787911136e-05 loss: 0.0817 (0.0768) time: 3.3753 data: 0.0077 max mem: 33370 +Epoch: [12] [ 540/1319] eta: 0:43:49 lr: 3.579235605368871e-05 loss: 0.0722 (0.0770) time: 3.3905 data: 0.0074 max mem: 33370 +Epoch: [12] [ 550/1319] eta: 0:43:15 lr: 3.578350398502055e-05 loss: 0.0881 (0.0771) time: 3.3685 data: 0.0074 max mem: 33370 +Epoch: [12] [ 560/1319] eta: 0:42:41 lr: 3.5774651673033346e-05 loss: 0.0658 (0.0770) time: 3.3418 data: 0.0078 max mem: 33370 +Epoch: [12] [ 570/1319] eta: 0:42:07 lr: 3.57657991176535e-05 loss: 0.0644 (0.0771) time: 3.3445 data: 0.0078 max mem: 33370 +Epoch: [12] [ 580/1319] eta: 0:41:33 lr: 3.5756946318807374e-05 loss: 0.0630 (0.0770) time: 3.3631 data: 0.0078 max mem: 33370 +Epoch: [12] [ 590/1319] eta: 0:40:59 lr: 3.5748093276421306e-05 loss: 0.0681 (0.0769) time: 3.3805 data: 0.0080 max mem: 33370 +Epoch: [12] [ 600/1319] eta: 0:40:25 lr: 3.573923999042157e-05 loss: 0.0653 (0.0772) time: 3.3549 data: 0.0083 max mem: 33370 +Epoch: [12] [ 610/1319] eta: 0:39:51 lr: 3.573038646073439e-05 loss: 0.0653 (0.0772) time: 3.3483 data: 0.0079 max mem: 33370 +Epoch: [12] [ 620/1319] eta: 0:39:17 lr: 3.5721532687286004e-05 loss: 0.0619 (0.0771) time: 3.3722 data: 0.0077 max mem: 33370 +Epoch: [12] [ 630/1319] eta: 0:38:44 lr: 3.571267867000252e-05 loss: 0.0608 (0.0770) time: 3.3846 data: 0.0077 max mem: 33370 +Epoch: [12] [ 640/1319] eta: 0:38:10 lr: 3.570382440881008e-05 loss: 0.0598 (0.0769) time: 3.3888 data: 0.0075 max mem: 33370 +Epoch: [12] [ 650/1319] eta: 0:37:37 lr: 3.5694969903634736e-05 loss: 0.0614 (0.0769) time: 3.3811 data: 0.0078 max mem: 33370 +Epoch: [12] [ 660/1319] eta: 0:37:03 lr: 3.568611515440253e-05 loss: 0.0614 (0.0768) time: 3.3758 data: 0.0079 max mem: 33370 +Epoch: [12] [ 670/1319] eta: 0:36:29 lr: 3.567726016103943e-05 loss: 0.0621 (0.0768) time: 3.3672 data: 0.0079 max mem: 33370 +Epoch: [12] [ 680/1319] eta: 0:35:55 lr: 3.5668404923471386e-05 loss: 0.0700 (0.0767) time: 3.3625 data: 0.0078 max mem: 33370 +Epoch: [12] [ 690/1319] eta: 0:35:22 lr: 3.565954944162429e-05 loss: 0.0730 (0.0769) time: 3.3774 data: 0.0076 max mem: 33370 +Epoch: [12] [ 700/1319] eta: 0:34:48 lr: 3.5650693715424005e-05 loss: 0.0724 (0.0771) time: 3.3692 data: 0.0078 max mem: 33370 +Epoch: [12] [ 710/1319] eta: 0:34:14 lr: 3.564183774479633e-05 loss: 0.0600 (0.0770) time: 3.3675 data: 0.0081 max mem: 33370 +Epoch: [12] [ 720/1319] eta: 0:33:40 lr: 3.563298152966704e-05 loss: 0.0503 (0.0766) time: 3.3771 data: 0.0082 max mem: 33370 +Epoch: [12] [ 730/1319] eta: 0:33:06 lr: 3.562412506996187e-05 loss: 0.0503 (0.0766) time: 3.3694 data: 0.0078 max mem: 33370 +Epoch: [12] [ 740/1319] eta: 0:32:33 lr: 3.561526836560649e-05 loss: 0.0685 (0.0767) time: 3.3734 data: 0.0078 max mem: 33370 +Epoch: [12] [ 750/1319] eta: 0:31:59 lr: 3.560641141652653e-05 loss: 0.0686 (0.0766) time: 3.3759 data: 0.0078 max mem: 33370 +Epoch: [12] [ 760/1319] eta: 0:31:25 lr: 3.5597554222647605e-05 loss: 0.0534 (0.0764) time: 3.3659 data: 0.0080 max mem: 33370 +Epoch: [12] [ 770/1319] eta: 0:30:51 lr: 3.558869678389526e-05 loss: 0.0712 (0.0765) time: 3.3637 data: 0.0078 max mem: 33370 +Epoch: [12] [ 780/1319] eta: 0:30:18 lr: 3.5579839100195013e-05 loss: 0.0798 (0.0766) time: 3.3623 data: 0.0078 max mem: 33370 +Epoch: [12] [ 790/1319] eta: 0:29:44 lr: 3.5570981171472317e-05 loss: 0.0798 (0.0768) time: 3.3581 data: 0.0079 max mem: 33370 +Epoch: [12] [ 800/1319] eta: 0:29:10 lr: 3.55621229976526e-05 loss: 0.0785 (0.0769) time: 3.3523 data: 0.0075 max mem: 33370 +Epoch: [12] [ 810/1319] eta: 0:28:36 lr: 3.555326457866125e-05 loss: 0.0715 (0.0767) time: 3.3317 data: 0.0075 max mem: 33370 +Epoch: [12] [ 820/1319] eta: 0:28:02 lr: 3.554440591442359e-05 loss: 0.0580 (0.0768) time: 3.3225 data: 0.0078 max mem: 33370 +Epoch: [12] [ 830/1319] eta: 0:27:28 lr: 3.5535547004864924e-05 loss: 0.0580 (0.0767) time: 3.3364 data: 0.0077 max mem: 33370 +Epoch: [12] [ 840/1319] eta: 0:26:54 lr: 3.552668784991049e-05 loss: 0.0557 (0.0766) time: 3.3572 data: 0.0075 max mem: 33370 +Epoch: [12] [ 850/1319] eta: 0:26:20 lr: 3.551782844948551e-05 loss: 0.0610 (0.0766) time: 3.3668 data: 0.0075 max mem: 33370 +Epoch: [12] [ 860/1319] eta: 0:25:46 lr: 3.550896880351513e-05 loss: 0.0635 (0.0765) time: 3.3441 data: 0.0077 max mem: 33370 +Epoch: [12] [ 870/1319] eta: 0:25:13 lr: 3.550010891192448e-05 loss: 0.0665 (0.0765) time: 3.3545 data: 0.0078 max mem: 33370 +Epoch: [12] [ 880/1319] eta: 0:24:39 lr: 3.549124877463863e-05 loss: 0.0674 (0.0764) time: 3.3754 data: 0.0078 max mem: 33370 +Epoch: [12] [ 890/1319] eta: 0:24:05 lr: 3.548238839158261e-05 loss: 0.0686 (0.0764) time: 3.3505 data: 0.0076 max mem: 33370 +Epoch: [12] [ 900/1319] eta: 0:23:31 lr: 3.5473527762681414e-05 loss: 0.0766 (0.0765) time: 3.3274 data: 0.0075 max mem: 33370 +Epoch: [12] [ 910/1319] eta: 0:22:58 lr: 3.546466688785999e-05 loss: 0.0775 (0.0765) time: 3.3373 data: 0.0076 max mem: 33370 +Epoch: [12] [ 920/1319] eta: 0:22:24 lr: 3.545580576704322e-05 loss: 0.0667 (0.0764) time: 3.3532 data: 0.0077 max mem: 33370 +Epoch: [12] [ 930/1319] eta: 0:21:50 lr: 3.544694440015598e-05 loss: 0.0688 (0.0766) time: 3.3633 data: 0.0077 max mem: 33370 +Epoch: [12] [ 940/1319] eta: 0:21:16 lr: 3.543808278712307e-05 loss: 0.0931 (0.0769) time: 3.3725 data: 0.0079 max mem: 33370 +Epoch: [12] [ 950/1319] eta: 0:20:43 lr: 3.542922092786927e-05 loss: 0.0723 (0.0770) time: 3.3548 data: 0.0085 max mem: 33370 +Epoch: [12] [ 960/1319] eta: 0:20:09 lr: 3.542035882231929e-05 loss: 0.0713 (0.0770) time: 3.3606 data: 0.0083 max mem: 33370 +Epoch: [12] [ 970/1319] eta: 0:19:35 lr: 3.541149647039783e-05 loss: 0.0764 (0.0771) time: 3.3749 data: 0.0076 max mem: 33370 +Epoch: [12] [ 980/1319] eta: 0:19:02 lr: 3.540263387202951e-05 loss: 0.0859 (0.0771) time: 3.3821 data: 0.0077 max mem: 33370 +Epoch: [12] [ 990/1319] eta: 0:18:28 lr: 3.5393771027138936e-05 loss: 0.0778 (0.0772) time: 3.3685 data: 0.0079 max mem: 33370 +Epoch: [12] [1000/1319] eta: 0:17:54 lr: 3.5384907935650645e-05 loss: 0.0744 (0.0771) time: 3.3505 data: 0.0078 max mem: 33370 +Epoch: [12] [1010/1319] eta: 0:17:20 lr: 3.5376044597489155e-05 loss: 0.0716 (0.0773) time: 3.3629 data: 0.0080 max mem: 33370 +Epoch: [12] [1020/1319] eta: 0:16:47 lr: 3.536718101257892e-05 loss: 0.0764 (0.0775) time: 3.3604 data: 0.0078 max mem: 33370 +Epoch: [12] [1030/1319] eta: 0:16:13 lr: 3.5358317180844356e-05 loss: 0.0764 (0.0777) time: 3.3671 data: 0.0079 max mem: 33370 +Epoch: [12] [1040/1319] eta: 0:15:39 lr: 3.5349453102209835e-05 loss: 0.0697 (0.0777) time: 3.3739 data: 0.0080 max mem: 33370 +Epoch: [12] [1050/1319] eta: 0:15:06 lr: 3.534058877659969e-05 loss: 0.0607 (0.0776) time: 3.3766 data: 0.0077 max mem: 33370 +Epoch: [12] [1060/1319] eta: 0:14:32 lr: 3.5331724203938196e-05 loss: 0.0648 (0.0775) time: 3.3581 data: 0.0083 max mem: 33370 +Epoch: [12] [1070/1319] eta: 0:13:58 lr: 3.53228593841496e-05 loss: 0.0704 (0.0776) time: 3.3615 data: 0.0083 max mem: 33370 +Epoch: [12] [1080/1319] eta: 0:13:25 lr: 3.53139943171581e-05 loss: 0.0802 (0.0777) time: 3.3688 data: 0.0079 max mem: 33370 +Epoch: [12] [1090/1319] eta: 0:12:51 lr: 3.5305129002887835e-05 loss: 0.0797 (0.0777) time: 3.3488 data: 0.0077 max mem: 33370 +Epoch: [12] [1100/1319] eta: 0:12:17 lr: 3.529626344126292e-05 loss: 0.0747 (0.0777) time: 3.3857 data: 0.0074 max mem: 33370 +Epoch: [12] [1110/1319] eta: 0:11:44 lr: 3.5287397632207417e-05 loss: 0.0747 (0.0777) time: 3.3863 data: 0.0078 max mem: 33370 +Epoch: [12] [1120/1319] eta: 0:11:10 lr: 3.527853157564535e-05 loss: 0.0679 (0.0777) time: 3.3627 data: 0.0079 max mem: 33370 +Epoch: [12] [1130/1319] eta: 0:10:36 lr: 3.526966527150067e-05 loss: 0.0730 (0.0778) time: 3.3802 data: 0.0078 max mem: 33370 +Epoch: [12] [1140/1319] eta: 0:10:03 lr: 3.5260798719697326e-05 loss: 0.0885 (0.0781) time: 3.3709 data: 0.0079 max mem: 33370 +Epoch: [12] [1150/1319] eta: 0:09:29 lr: 3.52519319201592e-05 loss: 0.0837 (0.0781) time: 3.3457 data: 0.0076 max mem: 33370 +Epoch: [12] [1160/1319] eta: 0:08:55 lr: 3.524306487281011e-05 loss: 0.0698 (0.0780) time: 3.3618 data: 0.0074 max mem: 33370 +Epoch: [12] [1170/1319] eta: 0:08:21 lr: 3.523419757757387e-05 loss: 0.0613 (0.0779) time: 3.3499 data: 0.0075 max mem: 33370 +Epoch: [12] [1180/1319] eta: 0:07:48 lr: 3.5225330034374235e-05 loss: 0.0669 (0.0778) time: 3.3441 data: 0.0076 max mem: 33370 +Epoch: [12] [1190/1319] eta: 0:07:14 lr: 3.5216462243134885e-05 loss: 0.0669 (0.0778) time: 3.3765 data: 0.0075 max mem: 33370 +Epoch: [12] [1200/1319] eta: 0:06:40 lr: 3.52075942037795e-05 loss: 0.0704 (0.0778) time: 3.3847 data: 0.0078 max mem: 33370 +Epoch: [12] [1210/1319] eta: 0:06:07 lr: 3.519872591623169e-05 loss: 0.0740 (0.0778) time: 3.3946 data: 0.0078 max mem: 33370 +Epoch: [12] [1220/1319] eta: 0:05:33 lr: 3.518985738041502e-05 loss: 0.0774 (0.0778) time: 3.3679 data: 0.0077 max mem: 33370 +Epoch: [12] [1230/1319] eta: 0:04:59 lr: 3.518098859625303e-05 loss: 0.0696 (0.0778) time: 3.3513 data: 0.0076 max mem: 33370 +Epoch: [12] [1240/1319] eta: 0:04:26 lr: 3.517211956366918e-05 loss: 0.0669 (0.0778) time: 3.3903 data: 0.0076 max mem: 33370 +Epoch: [12] [1250/1319] eta: 0:03:52 lr: 3.5163250282586914e-05 loss: 0.0773 (0.0779) time: 3.3853 data: 0.0074 max mem: 33370 +Epoch: [12] [1260/1319] eta: 0:03:18 lr: 3.515438075292963e-05 loss: 0.0777 (0.0779) time: 3.3684 data: 0.0075 max mem: 33370 +Epoch: [12] [1270/1319] eta: 0:02:45 lr: 3.514551097462066e-05 loss: 0.0777 (0.0781) time: 3.3728 data: 0.0082 max mem: 33370 +Epoch: [12] [1280/1319] eta: 0:02:11 lr: 3.513664094758331e-05 loss: 0.0817 (0.0781) time: 3.3880 data: 0.0079 max mem: 33370 +Epoch: [12] [1290/1319] eta: 0:01:37 lr: 3.512777067174083e-05 loss: 0.0799 (0.0781) time: 3.3832 data: 0.0073 max mem: 33370 +Epoch: [12] [1300/1319] eta: 0:01:04 lr: 3.511890014701643e-05 loss: 0.0677 (0.0780) time: 3.3745 data: 0.0077 max mem: 33370 +Epoch: [12] [1310/1319] eta: 0:00:30 lr: 3.511002937333328e-05 loss: 0.0701 (0.0781) time: 3.3939 data: 0.0076 max mem: 33370 +Epoch: [12] Total time: 1:14:05 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 2:53:56 time: 4.0560 data: 3.9369 max mem: 33370 +Test: [ 100/2573] eta: 0:04:50 time: 0.0769 data: 0.0014 max mem: 33370 +Test: [ 200/2573] eta: 0:03:55 time: 0.0801 data: 0.0015 max mem: 33370 +Test: [ 300/2573] eta: 0:03:29 time: 0.0813 data: 0.0014 max mem: 33370 +Test: [ 400/2573] eta: 0:03:13 time: 0.0817 data: 0.0014 max mem: 33370 +Test: [ 500/2573] eta: 0:03:00 time: 0.0795 data: 0.0013 max mem: 33370 +Test: [ 600/2573] eta: 0:02:49 time: 0.0808 data: 0.0015 max mem: 33370 +Test: [ 700/2573] eta: 0:02:40 time: 0.0803 data: 0.0014 max mem: 33370 +Test: [ 800/2573] eta: 0:02:30 time: 0.0833 data: 0.0014 max mem: 33370 +Test: [ 900/2573] eta: 0:02:21 time: 0.0803 data: 0.0014 max mem: 33370 +Test: [1000/2573] eta: 0:02:12 time: 0.0793 data: 0.0014 max mem: 33370 +Test: [1100/2573] eta: 0:02:03 time: 0.0794 data: 0.0013 max mem: 33370 +Test: [1200/2573] eta: 0:01:54 time: 0.0795 data: 0.0014 max mem: 33370 +Test: [1300/2573] eta: 0:01:45 time: 0.0797 data: 0.0013 max mem: 33370 +Test: [1400/2573] eta: 0:01:37 time: 0.0783 data: 0.0014 max mem: 33370 +Test: [1500/2573] eta: 0:01:28 time: 0.0799 data: 0.0014 max mem: 33370 +Test: [1600/2573] eta: 0:01:20 time: 0.0838 data: 0.0016 max mem: 33370 +Test: [1700/2573] eta: 0:01:11 time: 0.0773 data: 0.0013 max mem: 33370 +Test: [1800/2573] eta: 0:01:03 time: 0.0812 data: 0.0015 max mem: 33370 +Test: [1900/2573] eta: 0:00:55 time: 0.0778 data: 0.0014 max mem: 33370 +Test: [2000/2573] eta: 0:00:46 time: 0.0805 data: 0.0014 max mem: 33370 +Test: [2100/2573] eta: 0:00:38 time: 0.0814 data: 0.0014 max mem: 33370 +Test: [2200/2573] eta: 0:00:30 time: 0.0818 data: 0.0014 max mem: 33370 +Test: [2300/2573] eta: 0:00:22 time: 0.0810 data: 0.0015 max mem: 33370 +Test: [2400/2573] eta: 0:00:14 time: 0.0764 data: 0.0014 max mem: 33370 +Test: [2500/2573] eta: 0:00:05 time: 0.0798 data: 0.0014 max mem: 33370 +Test: Total time: 0:03:29 +Final results: +Mean IoU is 60.96 + + precision@0.5 = 67.77 + precision@0.6 = 62.17 + precision@0.7 = 54.47 + precision@0.8 = 42.75 + precision@0.9 = 19.91 + overall IoU = 58.81 + +Average object IoU 60.95501161796288 +Overall IoU 58.80502700805664 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [13] [ 0/1319] eta: 3:25:31 lr: 3.510204546409517e-05 loss: 0.0774 (0.0774) time: 9.3492 data: 2.4325 max mem: 33370 +Epoch: [13] [ 10/1319] eta: 1:25:44 lr: 3.509317421717855e-05 loss: 0.0675 (0.0675) time: 3.9304 data: 0.2282 max mem: 33370 +Epoch: [13] [ 20/1319] eta: 1:19:17 lr: 3.50843027210801e-05 loss: 0.0645 (0.0725) time: 3.3777 data: 0.0076 max mem: 33370 +Epoch: [13] [ 30/1319] eta: 1:16:32 lr: 3.5075430975722793e-05 loss: 0.0769 (0.0823) time: 3.3611 data: 0.0079 max mem: 33370 +Epoch: [13] [ 40/1319] eta: 1:15:07 lr: 3.506655898102959e-05 loss: 0.0769 (0.0825) time: 3.3801 data: 0.0081 max mem: 33370 +Epoch: [13] [ 50/1319] eta: 1:13:50 lr: 3.505768673692337e-05 loss: 0.0595 (0.0778) time: 3.3802 data: 0.0079 max mem: 33370 +Epoch: [13] [ 60/1319] eta: 1:13:00 lr: 3.5048814243327e-05 loss: 0.0631 (0.0792) time: 3.3857 data: 0.0081 max mem: 33370 +Epoch: [13] [ 70/1319] eta: 1:12:02 lr: 3.503994150016327e-05 loss: 0.0631 (0.0767) time: 3.3828 data: 0.0082 max mem: 33370 +Epoch: [13] [ 80/1319] eta: 1:11:12 lr: 3.503106850735495e-05 loss: 0.0545 (0.0737) time: 3.3564 data: 0.0082 max mem: 33370 +Epoch: [13] [ 90/1319] eta: 1:10:29 lr: 3.502219526482476e-05 loss: 0.0549 (0.0736) time: 3.3729 data: 0.0084 max mem: 33370 +Epoch: [13] [ 100/1319] eta: 1:09:45 lr: 3.501332177249536e-05 loss: 0.0565 (0.0724) time: 3.3703 data: 0.0081 max mem: 33370 +Epoch: [13] [ 110/1319] eta: 1:09:00 lr: 3.500444803028936e-05 loss: 0.0531 (0.0723) time: 3.3467 data: 0.0078 max mem: 33370 +Epoch: [13] [ 120/1319] eta: 1:08:25 lr: 3.499557403812936e-05 loss: 0.0518 (0.0721) time: 3.3765 data: 0.0081 max mem: 33370 +Epoch: [13] [ 130/1319] eta: 1:07:47 lr: 3.498669979593787e-05 loss: 0.0668 (0.0721) time: 3.4001 data: 0.0080 max mem: 33370 +Epoch: [13] [ 140/1319] eta: 1:07:08 lr: 3.497782530363739e-05 loss: 0.0670 (0.0719) time: 3.3760 data: 0.0077 max mem: 33370 +Epoch: [13] [ 150/1319] eta: 1:06:28 lr: 3.4968950561150356e-05 loss: 0.0585 (0.0719) time: 3.3528 data: 0.0075 max mem: 33370 +Epoch: [13] [ 160/1319] eta: 1:05:51 lr: 3.496007556839915e-05 loss: 0.0667 (0.0727) time: 3.3586 data: 0.0077 max mem: 33370 +Epoch: [13] [ 170/1319] eta: 1:05:13 lr: 3.495120032530614e-05 loss: 0.0681 (0.0728) time: 3.3626 data: 0.0078 max mem: 33370 +Epoch: [13] [ 180/1319] eta: 1:04:38 lr: 3.49423248317936e-05 loss: 0.0612 (0.0729) time: 3.3709 data: 0.0076 max mem: 33370 +Epoch: [13] [ 190/1319] eta: 1:03:59 lr: 3.493344908778381e-05 loss: 0.0700 (0.0733) time: 3.3534 data: 0.0077 max mem: 33370 +Epoch: [13] [ 200/1319] eta: 1:03:22 lr: 3.4924573093198975e-05 loss: 0.0730 (0.0734) time: 3.3292 data: 0.0080 max mem: 33370 +Epoch: [13] [ 210/1319] eta: 1:02:47 lr: 3.491569684796125e-05 loss: 0.0730 (0.0731) time: 3.3616 data: 0.0079 max mem: 33370 +Epoch: [13] [ 220/1319] eta: 1:02:11 lr: 3.490682035199276e-05 loss: 0.0615 (0.0728) time: 3.3733 data: 0.0076 max mem: 33370 +Epoch: [13] [ 230/1319] eta: 1:01:36 lr: 3.4897943605215565e-05 loss: 0.0621 (0.0729) time: 3.3711 data: 0.0075 max mem: 33370 +Epoch: [13] [ 240/1319] eta: 1:01:04 lr: 3.488906660755169e-05 loss: 0.0621 (0.0727) time: 3.3992 data: 0.0077 max mem: 33370 +Epoch: [13] [ 250/1319] eta: 1:00:29 lr: 3.4880189358923125e-05 loss: 0.0563 (0.0726) time: 3.4042 data: 0.0085 max mem: 33370 +Epoch: [13] [ 260/1319] eta: 0:59:54 lr: 3.487131185925179e-05 loss: 0.0617 (0.0721) time: 3.3691 data: 0.0081 max mem: 33370 +Epoch: [13] [ 270/1319] eta: 0:59:20 lr: 3.486243410845958e-05 loss: 0.0663 (0.0722) time: 3.3804 data: 0.0080 max mem: 33370 +Epoch: [13] [ 280/1319] eta: 0:58:45 lr: 3.485355610646832e-05 loss: 0.0663 (0.0724) time: 3.3867 data: 0.0087 max mem: 33370 +Epoch: [13] [ 290/1319] eta: 0:58:11 lr: 3.484467785319982e-05 loss: 0.0589 (0.0718) time: 3.3835 data: 0.0087 max mem: 33370 +Epoch: [13] [ 300/1319] eta: 0:57:38 lr: 3.483579934857581e-05 loss: 0.0589 (0.0722) time: 3.4074 data: 0.0081 max mem: 33370 +Epoch: [13] [ 310/1319] eta: 0:57:03 lr: 3.4826920592518003e-05 loss: 0.0691 (0.0722) time: 3.3830 data: 0.0077 max mem: 33370 +Epoch: [13] [ 320/1319] eta: 0:56:28 lr: 3.481804158494804e-05 loss: 0.0717 (0.0727) time: 3.3528 data: 0.0080 max mem: 33370 +Epoch: [13] [ 330/1319] eta: 0:55:53 lr: 3.4809162325787535e-05 loss: 0.0758 (0.0729) time: 3.3588 data: 0.0079 max mem: 33370 +Epoch: [13] [ 340/1319] eta: 0:55:18 lr: 3.480028281495805e-05 loss: 0.0674 (0.0729) time: 3.3544 data: 0.0076 max mem: 33370 +Epoch: [13] [ 350/1319] eta: 0:54:44 lr: 3.479140305238109e-05 loss: 0.0724 (0.0730) time: 3.3746 data: 0.0083 max mem: 33370 +Epoch: [13] [ 360/1319] eta: 0:54:09 lr: 3.478252303797812e-05 loss: 0.0675 (0.0729) time: 3.3665 data: 0.0089 max mem: 33370 +Epoch: [13] [ 370/1319] eta: 0:53:35 lr: 3.4773642771670566e-05 loss: 0.0560 (0.0726) time: 3.3525 data: 0.0082 max mem: 33370 +Epoch: [13] [ 380/1319] eta: 0:53:01 lr: 3.47647622533798e-05 loss: 0.0537 (0.0723) time: 3.3826 data: 0.0075 max mem: 33370 +Epoch: [13] [ 390/1319] eta: 0:52:27 lr: 3.475588148302715e-05 loss: 0.0645 (0.0721) time: 3.3908 data: 0.0074 max mem: 33370 +Epoch: [13] [ 400/1319] eta: 0:51:53 lr: 3.474700046053388e-05 loss: 0.0635 (0.0720) time: 3.3822 data: 0.0080 max mem: 33370 +Epoch: [13] [ 410/1319] eta: 0:51:18 lr: 3.473811918582123e-05 loss: 0.0682 (0.0722) time: 3.3709 data: 0.0081 max mem: 33370 +Epoch: [13] [ 420/1319] eta: 0:50:44 lr: 3.47292376588104e-05 loss: 0.0678 (0.0718) time: 3.3576 data: 0.0078 max mem: 33370 +Epoch: [13] [ 430/1319] eta: 0:50:09 lr: 3.472035587942251e-05 loss: 0.0655 (0.0718) time: 3.3538 data: 0.0079 max mem: 33370 +Epoch: [13] [ 440/1319] eta: 0:49:36 lr: 3.4711473847578654e-05 loss: 0.0722 (0.0722) time: 3.3762 data: 0.0080 max mem: 33370 +Epoch: [13] [ 450/1319] eta: 0:49:02 lr: 3.470259156319988e-05 loss: 0.0804 (0.0725) time: 3.3861 data: 0.0082 max mem: 33370 +Epoch: [13] [ 460/1319] eta: 0:48:27 lr: 3.469370902620718e-05 loss: 0.0732 (0.0728) time: 3.3680 data: 0.0077 max mem: 33370 +Epoch: [13] [ 470/1319] eta: 0:47:54 lr: 3.4684826236521504e-05 loss: 0.0647 (0.0726) time: 3.3793 data: 0.0078 max mem: 33370 +Epoch: [13] [ 480/1319] eta: 0:47:20 lr: 3.467594319406376e-05 loss: 0.0597 (0.0723) time: 3.3873 data: 0.0084 max mem: 33370 +Epoch: [13] [ 490/1319] eta: 0:46:45 lr: 3.466705989875479e-05 loss: 0.0609 (0.0728) time: 3.3507 data: 0.0081 max mem: 33370 +Epoch: [13] [ 500/1319] eta: 0:46:11 lr: 3.465817635051541e-05 loss: 0.0703 (0.0727) time: 3.3508 data: 0.0078 max mem: 33370 +Epoch: [13] [ 510/1319] eta: 0:45:37 lr: 3.4649292549266374e-05 loss: 0.0708 (0.0728) time: 3.3870 data: 0.0076 max mem: 33370 +Epoch: [13] [ 520/1319] eta: 0:45:03 lr: 3.464040849492841e-05 loss: 0.0671 (0.0726) time: 3.3764 data: 0.0077 max mem: 33370 +Epoch: [13] [ 530/1319] eta: 0:44:29 lr: 3.463152418742217e-05 loss: 0.0630 (0.0727) time: 3.3608 data: 0.0079 max mem: 33370 +Epoch: [13] [ 540/1319] eta: 0:43:55 lr: 3.4622639626668276e-05 loss: 0.0577 (0.0726) time: 3.3726 data: 0.0083 max mem: 33370 +Epoch: [13] [ 550/1319] eta: 0:43:21 lr: 3.461375481258729e-05 loss: 0.0584 (0.0728) time: 3.3766 data: 0.0086 max mem: 33370 +Epoch: [13] [ 560/1319] eta: 0:42:47 lr: 3.460486974509975e-05 loss: 0.0662 (0.0727) time: 3.3904 data: 0.0081 max mem: 33370 +Epoch: [13] [ 570/1319] eta: 0:42:14 lr: 3.4595984424126115e-05 loss: 0.0662 (0.0727) time: 3.3981 data: 0.0079 max mem: 33370 +Epoch: [13] [ 580/1319] eta: 0:41:40 lr: 3.458709884958682e-05 loss: 0.0696 (0.0726) time: 3.3909 data: 0.0079 max mem: 33370 +Epoch: [13] [ 590/1319] eta: 0:41:06 lr: 3.457821302140224e-05 loss: 0.0634 (0.0726) time: 3.3618 data: 0.0080 max mem: 33370 +Epoch: [13] [ 600/1319] eta: 0:40:32 lr: 3.456932693949272e-05 loss: 0.0611 (0.0726) time: 3.3590 data: 0.0083 max mem: 33370 +Epoch: [13] [ 610/1319] eta: 0:39:58 lr: 3.456044060377853e-05 loss: 0.0759 (0.0729) time: 3.3732 data: 0.0080 max mem: 33370 +Epoch: [13] [ 620/1319] eta: 0:39:24 lr: 3.455155401417991e-05 loss: 0.0774 (0.0730) time: 3.3779 data: 0.0078 max mem: 33370 +Epoch: [13] [ 630/1319] eta: 0:38:50 lr: 3.4542667170617054e-05 loss: 0.0611 (0.0728) time: 3.3800 data: 0.0079 max mem: 33370 +Epoch: [13] [ 640/1319] eta: 0:38:16 lr: 3.453378007301009e-05 loss: 0.0596 (0.0730) time: 3.3576 data: 0.0080 max mem: 33370 +Epoch: [13] [ 650/1319] eta: 0:37:42 lr: 3.4524892721279126e-05 loss: 0.0635 (0.0730) time: 3.3676 data: 0.0080 max mem: 33370 +Epoch: [13] [ 660/1319] eta: 0:37:08 lr: 3.4516005115344196e-05 loss: 0.0547 (0.0727) time: 3.3632 data: 0.0078 max mem: 33370 +Epoch: [13] [ 670/1319] eta: 0:36:34 lr: 3.45071172551253e-05 loss: 0.0567 (0.0727) time: 3.3673 data: 0.0078 max mem: 33370 +Epoch: [13] [ 680/1319] eta: 0:36:00 lr: 3.4498229140542384e-05 loss: 0.0594 (0.0728) time: 3.3971 data: 0.0078 max mem: 33370 +Epoch: [13] [ 690/1319] eta: 0:35:26 lr: 3.448934077151535e-05 loss: 0.0599 (0.0728) time: 3.3671 data: 0.0077 max mem: 33370 +Epoch: [13] [ 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0.0080 max mem: 33370 +Epoch: [13] [ 860/1319] eta: 0:25:50 lr: 3.433819949025503e-05 loss: 0.0624 (0.0734) time: 3.3801 data: 0.0076 max mem: 33370 +Epoch: [13] [ 870/1319] eta: 0:25:16 lr: 3.432930652748169e-05 loss: 0.0583 (0.0733) time: 3.3625 data: 0.0080 max mem: 33370 +Epoch: [13] [ 880/1319] eta: 0:24:42 lr: 3.432041330873315e-05 loss: 0.0560 (0.0733) time: 3.3501 data: 0.0083 max mem: 33370 +Epoch: [13] [ 890/1319] eta: 0:24:09 lr: 3.4311519833928315e-05 loss: 0.0566 (0.0733) time: 3.3784 data: 0.0079 max mem: 33370 +Epoch: [13] [ 900/1319] eta: 0:23:35 lr: 3.430262610298607e-05 loss: 0.0635 (0.0735) time: 3.3902 data: 0.0081 max mem: 33370 +Epoch: [13] [ 910/1319] eta: 0:23:01 lr: 3.429373211582526e-05 loss: 0.0575 (0.0734) time: 3.3724 data: 0.0080 max mem: 33370 +Epoch: [13] [ 920/1319] eta: 0:22:27 lr: 3.428483787236465e-05 loss: 0.0636 (0.0733) time: 3.3620 data: 0.0077 max mem: 33370 +Epoch: [13] [ 930/1319] eta: 0:21:53 lr: 3.4275943372522975e-05 loss: 0.0748 (0.0734) time: 3.3607 data: 0.0078 max mem: 33370 +Epoch: [13] [ 940/1319] eta: 0:21:19 lr: 3.426704861621893e-05 loss: 0.0560 (0.0734) time: 3.3594 data: 0.0080 max mem: 33370 +Epoch: [13] [ 950/1319] eta: 0:20:46 lr: 3.4258153603371135e-05 loss: 0.0560 (0.0736) time: 3.3630 data: 0.0076 max mem: 33370 +Epoch: [13] [ 960/1319] eta: 0:20:12 lr: 3.424925833389819e-05 loss: 0.0586 (0.0736) time: 3.3679 data: 0.0075 max mem: 33370 +Epoch: [13] [ 970/1319] eta: 0:19:38 lr: 3.424036280771861e-05 loss: 0.0593 (0.0737) time: 3.3513 data: 0.0081 max mem: 33370 +Epoch: [13] [ 980/1319] eta: 0:19:04 lr: 3.42314670247509e-05 loss: 0.0738 (0.0738) time: 3.3452 data: 0.0080 max mem: 33370 +Epoch: [13] [ 990/1319] eta: 0:18:30 lr: 3.422257098491348e-05 loss: 0.0763 (0.0738) time: 3.3613 data: 0.0078 max mem: 33370 +Epoch: [13] [1000/1319] eta: 0:17:56 lr: 3.4213674688124745e-05 loss: 0.0712 (0.0739) time: 3.3606 data: 0.0077 max mem: 33370 +Epoch: [13] [1010/1319] eta: 0:17:23 lr: 3.420477813430303e-05 loss: 0.0625 (0.0737) time: 3.3645 data: 0.0073 max mem: 33370 +Epoch: [13] [1020/1319] eta: 0:16:49 lr: 3.419588132336663e-05 loss: 0.0625 (0.0739) time: 3.3834 data: 0.0072 max mem: 33370 +Epoch: [13] [1030/1319] eta: 0:16:15 lr: 3.418698425523378e-05 loss: 0.0611 (0.0738) time: 3.3802 data: 0.0076 max mem: 33370 +Epoch: [13] [1040/1319] eta: 0:15:41 lr: 3.417808692982266e-05 loss: 0.0553 (0.0737) time: 3.3769 data: 0.0080 max mem: 33370 +Epoch: [13] [1050/1319] eta: 0:15:08 lr: 3.4169189347051416e-05 loss: 0.0555 (0.0738) time: 3.3928 data: 0.0079 max mem: 33370 +Epoch: [13] [1060/1319] eta: 0:14:34 lr: 3.416029150683815e-05 loss: 0.0706 (0.0738) time: 3.4118 data: 0.0079 max mem: 33370 +Epoch: [13] [1070/1319] eta: 0:14:00 lr: 3.4151393409100875e-05 loss: 0.0761 (0.0740) time: 3.3906 data: 0.0080 max mem: 33370 +Epoch: [13] [1080/1319] eta: 0:13:27 lr: 3.41424950537576e-05 loss: 0.0761 (0.0741) time: 3.3644 data: 0.0079 max mem: 33370 +Epoch: [13] [1090/1319] eta: 0:12:53 lr: 3.413359644072625e-05 loss: 0.0708 (0.0741) time: 3.3616 data: 0.0080 max mem: 33370 +Epoch: [13] [1100/1319] eta: 0:12:19 lr: 3.412469756992473e-05 loss: 0.0643 (0.0740) time: 3.3732 data: 0.0082 max mem: 33370 +Epoch: [13] [1110/1319] eta: 0:11:45 lr: 3.411579844127087e-05 loss: 0.0613 (0.0739) time: 3.4026 data: 0.0081 max mem: 33370 +Epoch: [13] [1120/1319] eta: 0:11:12 lr: 3.410689905468246e-05 loss: 0.0600 (0.0738) time: 3.3985 data: 0.0075 max mem: 33370 +Epoch: [13] [1130/1319] eta: 0:10:38 lr: 3.409799941007725e-05 loss: 0.0604 (0.0738) time: 3.3715 data: 0.0073 max mem: 33370 +Epoch: [13] [1140/1319] eta: 0:10:04 lr: 3.408909950737292e-05 loss: 0.0571 (0.0737) time: 3.3538 data: 0.0077 max mem: 33370 +Epoch: [13] [1150/1319] eta: 0:09:30 lr: 3.4080199346487104e-05 loss: 0.0552 (0.0737) time: 3.3433 data: 0.0078 max mem: 33370 +Epoch: [13] [1160/1319] eta: 0:08:56 lr: 3.4071298927337405e-05 loss: 0.0708 (0.0737) time: 3.3517 data: 0.0077 max mem: 33370 +Epoch: [13] [1170/1319] eta: 0:08:23 lr: 3.406239824984136e-05 loss: 0.0788 (0.0739) time: 3.3617 data: 0.0079 max mem: 33370 +Epoch: [13] [1180/1319] eta: 0:07:49 lr: 3.405349731391645e-05 loss: 0.0620 (0.0738) time: 3.3554 data: 0.0078 max mem: 33370 +Epoch: [13] [1190/1319] eta: 0:07:15 lr: 3.404459611948011e-05 loss: 0.0613 (0.0738) time: 3.3699 data: 0.0074 max mem: 33370 +Epoch: [13] [1200/1319] eta: 0:06:41 lr: 3.4035694666449745e-05 loss: 0.0646 (0.0737) time: 3.4003 data: 0.0074 max mem: 33370 +Epoch: [13] [1210/1319] eta: 0:06:07 lr: 3.402679295474268e-05 loss: 0.0563 (0.0737) time: 3.3832 data: 0.0076 max mem: 33370 +Epoch: [13] [1220/1319] eta: 0:05:34 lr: 3.401789098427621e-05 loss: 0.0685 (0.0738) time: 3.3551 data: 0.0078 max mem: 33370 +Epoch: [13] [1230/1319] eta: 0:05:00 lr: 3.400898875496756e-05 loss: 0.0644 (0.0737) time: 3.3416 data: 0.0079 max mem: 33370 +Epoch: [13] [1240/1319] eta: 0:04:26 lr: 3.400008626673392e-05 loss: 0.0594 (0.0736) time: 3.3431 data: 0.0077 max mem: 33370 +Epoch: [13] [1250/1319] eta: 0:03:52 lr: 3.399118351949243e-05 loss: 0.0613 (0.0736) time: 3.3446 data: 0.0079 max mem: 33370 +Epoch: [13] [1260/1319] eta: 0:03:19 lr: 3.398228051316017e-05 loss: 0.0650 (0.0736) time: 3.3399 data: 0.0079 max mem: 33370 +Epoch: [13] [1270/1319] eta: 0:02:45 lr: 3.397337724765419e-05 loss: 0.0732 (0.0737) time: 3.3490 data: 0.0076 max mem: 33370 +Epoch: [13] [1280/1319] eta: 0:02:11 lr: 3.396447372289146e-05 loss: 0.0749 (0.0737) time: 3.3685 data: 0.0077 max mem: 33370 +Epoch: [13] [1290/1319] eta: 0:01:37 lr: 3.395556993878891e-05 loss: 0.0705 (0.0739) time: 3.3723 data: 0.0080 max mem: 33370 +Epoch: [13] [1300/1319] eta: 0:01:04 lr: 3.394666589526343e-05 loss: 0.0614 (0.0739) time: 3.3621 data: 0.0078 max mem: 33370 +Epoch: [13] [1310/1319] eta: 0:00:30 lr: 3.393776159223184e-05 loss: 0.0576 (0.0737) time: 3.3531 data: 0.0075 max mem: 33370 +Epoch: [13] Total time: 1:14:11 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 3:04:08 time: 4.2940 data: 4.2118 max mem: 33370 +Test: [ 100/2573] eta: 0:04:50 time: 0.0753 data: 0.0015 max mem: 33370 +Test: [ 200/2573] eta: 0:03:52 time: 0.0776 data: 0.0014 max mem: 33370 +Test: [ 300/2573] eta: 0:03:25 time: 0.0788 data: 0.0013 max mem: 33370 +Test: [ 400/2573] eta: 0:03:09 time: 0.0791 data: 0.0015 max mem: 33370 +Test: [ 500/2573] eta: 0:02:56 time: 0.0772 data: 0.0014 max mem: 33370 +Test: [ 600/2573] eta: 0:02:45 time: 0.0774 data: 0.0014 max mem: 33370 +Test: [ 700/2573] eta: 0:02:36 time: 0.0775 data: 0.0014 max mem: 33370 +Test: [ 800/2573] eta: 0:02:26 time: 0.0813 data: 0.0015 max mem: 33370 +Test: [ 900/2573] eta: 0:02:17 time: 0.0779 data: 0.0014 max mem: 33370 +Test: [1000/2573] eta: 0:02:09 time: 0.0781 data: 0.0014 max mem: 33370 +Test: [1100/2573] eta: 0:02:00 time: 0.0781 data: 0.0014 max mem: 33370 +Test: [1200/2573] eta: 0:01:51 time: 0.0795 data: 0.0015 max mem: 33370 +Test: [1300/2573] eta: 0:01:43 time: 0.0794 data: 0.0013 max mem: 33370 +Test: [1400/2573] eta: 0:01:35 time: 0.0773 data: 0.0014 max mem: 33370 +Test: [1500/2573] eta: 0:01:26 time: 0.0791 data: 0.0014 max mem: 33370 +Test: [1600/2573] eta: 0:01:18 time: 0.0823 data: 0.0014 max mem: 33370 +Test: [1700/2573] eta: 0:01:10 time: 0.0777 data: 0.0014 max mem: 33370 +Test: [1800/2573] eta: 0:01:02 time: 0.0807 data: 0.0014 max mem: 33370 +Test: [1900/2573] eta: 0:00:54 time: 0.0786 data: 0.0014 max mem: 33370 +Test: [2000/2573] eta: 0:00:46 time: 0.0797 data: 0.0014 max mem: 33370 +Test: [2100/2573] eta: 0:00:38 time: 0.0817 data: 0.0014 max mem: 33370 +Test: [2200/2573] eta: 0:00:29 time: 0.0809 data: 0.0014 max mem: 33370 +Test: [2300/2573] eta: 0:00:21 time: 0.0805 data: 0.0014 max mem: 33370 +Test: [2400/2573] eta: 0:00:13 time: 0.0771 data: 0.0014 max mem: 33370 +Test: [2500/2573] eta: 0:00:05 time: 0.0803 data: 0.0015 max mem: 33370 +Test: Total time: 0:03:27 +Final results: +Mean IoU is 61.66 + + precision@0.5 = 68.73 + precision@0.6 = 63.17 + precision@0.7 = 55.33 + precision@0.8 = 44.22 + precision@0.9 = 20.98 + overall IoU = 59.77 + +Average object IoU 61.65872751975665 +Overall IoU 59.766357421875 +Better epoch: 13 + +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [14] [ 0/1319] eta: 1:59:51 lr: 3.392974749755691e-05 loss: 0.0427 (0.0427) time: 5.4520 data: 1.9240 max mem: 33370 +Epoch: [14] [ 10/1319] eta: 1:18:04 lr: 3.392084270123441e-05 loss: 0.0576 (0.0558) time: 3.5790 data: 0.1825 max mem: 33370 +Epoch: [14] [ 20/1319] eta: 1:15:15 lr: 3.391193764516433e-05 loss: 0.0669 (0.0695) time: 3.3772 data: 0.0074 max mem: 33370 +Epoch: [14] [ 30/1319] eta: 1:14:19 lr: 3.3903032329263314e-05 loss: 0.0719 (0.0702) time: 3.3940 data: 0.0075 max mem: 33370 +Epoch: [14] [ 40/1319] eta: 1:13:21 lr: 3.389412675344791e-05 loss: 0.0752 (0.0717) time: 3.4045 data: 0.0085 max mem: 33370 +Epoch: [14] [ 50/1319] eta: 1:12:21 lr: 3.388522091763468e-05 loss: 0.0746 (0.0700) time: 3.3624 data: 0.0084 max mem: 33370 +Epoch: [14] [ 60/1319] eta: 1:11:42 lr: 3.387631482174009e-05 loss: 0.0606 (0.0714) time: 3.3683 data: 0.0082 max mem: 33370 +Epoch: [14] [ 70/1319] eta: 1:11:00 lr: 3.386740846568057e-05 loss: 0.0570 (0.0686) time: 3.3850 data: 0.0083 max mem: 33370 +Epoch: [14] [ 80/1319] eta: 1:10:16 lr: 3.385850184937249e-05 loss: 0.0515 (0.0677) time: 3.3600 data: 0.0080 max mem: 33370 +Epoch: [14] [ 90/1319] eta: 1:09:45 lr: 3.3849594972732175e-05 loss: 0.0475 (0.0661) time: 3.3845 data: 0.0075 max mem: 33370 +Epoch: [14] [ 100/1319] eta: 1:09:12 lr: 3.38406878356759e-05 loss: 0.0524 (0.0656) time: 3.4199 data: 0.0074 max mem: 33370 +Epoch: [14] [ 110/1319] eta: 1:08:32 lr: 3.3831780438119907e-05 loss: 0.0615 (0.0662) time: 3.3835 data: 0.0076 max mem: 33370 +Epoch: [14] [ 120/1319] eta: 1:08:02 lr: 3.3822872779980336e-05 loss: 0.0674 (0.0674) time: 3.3989 data: 0.0079 max mem: 33370 +Epoch: [14] [ 130/1319] eta: 1:07:24 lr: 3.381396486117332e-05 loss: 0.0728 (0.0674) time: 3.4030 data: 0.0079 max mem: 33370 +Epoch: [14] [ 140/1319] eta: 1:06:49 lr: 3.380505668161494e-05 loss: 0.0667 (0.0680) time: 3.3721 data: 0.0078 max mem: 33370 +Epoch: [14] [ 150/1319] eta: 1:06:12 lr: 3.3796148241221185e-05 loss: 0.0649 (0.0675) time: 3.3777 data: 0.0078 max mem: 33370 +Epoch: [14] [ 160/1319] eta: 1:05:37 lr: 3.378723953990804e-05 loss: 0.0582 (0.0674) time: 3.3755 data: 0.0078 max mem: 33370 +Epoch: [14] [ 170/1319] eta: 1:05:01 lr: 3.3778330577591404e-05 loss: 0.0536 (0.0675) time: 3.3761 data: 0.0082 max mem: 33370 +Epoch: [14] [ 180/1319] eta: 1:04:28 lr: 3.3769421354187145e-05 loss: 0.0689 (0.0679) time: 3.3875 data: 0.0084 max mem: 33370 +Epoch: [14] [ 190/1319] eta: 1:03:52 lr: 3.376051186961107e-05 loss: 0.0773 (0.0700) time: 3.3867 data: 0.0080 max mem: 33370 +Epoch: [14] [ 200/1319] eta: 1:03:17 lr: 3.375160212377894e-05 loss: 0.0773 (0.0705) time: 3.3687 data: 0.0077 max mem: 33370 +Epoch: [14] [ 210/1319] eta: 1:02:41 lr: 3.374269211660646e-05 loss: 0.0629 (0.0699) time: 3.3583 data: 0.0079 max mem: 33370 +Epoch: [14] [ 220/1319] eta: 1:02:06 lr: 3.373378184800928e-05 loss: 0.0594 (0.0697) time: 3.3629 data: 0.0080 max mem: 33370 +Epoch: [14] [ 230/1319] eta: 1:01:30 lr: 3.372487131790299e-05 loss: 0.0594 (0.0698) time: 3.3666 data: 0.0078 max mem: 33370 +Epoch: [14] [ 240/1319] eta: 1:00:55 lr: 3.371596052620316e-05 loss: 0.0614 (0.0706) time: 3.3553 data: 0.0077 max mem: 33370 +Epoch: [14] [ 250/1319] eta: 1:00:22 lr: 3.370704947282529e-05 loss: 0.0645 (0.0705) time: 3.3858 data: 0.0079 max mem: 33370 +Epoch: [14] [ 260/1319] eta: 0:59:49 lr: 3.3698138157684804e-05 loss: 0.0644 (0.0699) time: 3.4046 data: 0.0078 max mem: 33370 +Epoch: [14] [ 270/1319] eta: 0:59:15 lr: 3.368922658069711e-05 loss: 0.0514 (0.0692) time: 3.3976 data: 0.0077 max mem: 33370 +Epoch: [14] [ 280/1319] eta: 0:58:41 lr: 3.368031474177754e-05 loss: 0.0517 (0.0694) time: 3.3881 data: 0.0083 max mem: 33370 +Epoch: [14] [ 290/1319] eta: 0:58:08 lr: 3.367140264084139e-05 loss: 0.0646 (0.0696) time: 3.4029 data: 0.0082 max mem: 33370 +Epoch: [14] [ 300/1319] eta: 0:57:33 lr: 3.366249027780389e-05 loss: 0.0661 (0.0699) time: 3.3913 data: 0.0077 max mem: 33370 +Epoch: [14] [ 310/1319] eta: 0:56:58 lr: 3.365357765258022e-05 loss: 0.0595 (0.0694) time: 3.3449 data: 0.0078 max mem: 33370 +Epoch: [14] [ 320/1319] eta: 0:56:26 lr: 3.364466476508552e-05 loss: 0.0595 (0.0694) time: 3.3980 data: 0.0076 max mem: 33370 +Epoch: [14] [ 330/1319] eta: 0:55:51 lr: 3.363575161523487e-05 loss: 0.0495 (0.0687) time: 3.4123 data: 0.0074 max mem: 33370 +Epoch: [14] [ 340/1319] eta: 0:55:15 lr: 3.362683820294329e-05 loss: 0.0606 (0.0691) time: 3.3405 data: 0.0080 max mem: 33370 +Epoch: [14] [ 350/1319] eta: 0:54:41 lr: 3.361792452812576e-05 loss: 0.0648 (0.0689) time: 3.3348 data: 0.0082 max mem: 33370 +Epoch: [14] [ 360/1319] eta: 0:54:06 lr: 3.36090105906972e-05 loss: 0.0603 (0.0692) time: 3.3628 data: 0.0081 max mem: 33370 +Epoch: [14] [ 370/1319] eta: 0:53:34 lr: 3.3600096390572475e-05 loss: 0.0669 (0.0693) time: 3.4075 data: 0.0079 max mem: 33370 +Epoch: [14] [ 380/1319] eta: 0:53:00 lr: 3.3591181927666404e-05 loss: 0.0575 (0.0690) time: 3.4148 data: 0.0076 max mem: 33370 +Epoch: [14] [ 390/1319] eta: 0:52:26 lr: 3.358226720189375e-05 loss: 0.0566 (0.0688) time: 3.3851 data: 0.0077 max mem: 33370 +Epoch: [14] [ 400/1319] eta: 0:51:52 lr: 3.357335221316921e-05 loss: 0.0543 (0.0686) time: 3.3915 data: 0.0079 max mem: 33370 +Epoch: [14] [ 410/1319] eta: 0:51:18 lr: 3.3564436961407466e-05 loss: 0.0571 (0.0687) time: 3.3698 data: 0.0081 max mem: 33370 +Epoch: [14] [ 420/1319] eta: 0:50:44 lr: 3.35555214465231e-05 loss: 0.0657 (0.0690) time: 3.3686 data: 0.0082 max mem: 33370 +Epoch: [14] [ 430/1319] eta: 0:50:10 lr: 3.354660566843068e-05 loss: 0.0702 (0.0691) time: 3.3840 data: 0.0078 max mem: 33370 +Epoch: [14] [ 440/1319] eta: 0:49:36 lr: 3.353768962704469e-05 loss: 0.0734 (0.0693) time: 3.3724 data: 0.0077 max mem: 33370 +Epoch: [14] [ 450/1319] eta: 0:49:01 lr: 3.352877332227959e-05 loss: 0.0570 (0.0690) time: 3.3568 data: 0.0081 max mem: 33370 +Epoch: [14] [ 460/1319] eta: 0:48:27 lr: 3.351985675404978e-05 loss: 0.0520 (0.0689) time: 3.3643 data: 0.0079 max mem: 33370 +Epoch: [14] [ 470/1319] eta: 0:47:54 lr: 3.3510939922269576e-05 loss: 0.0602 (0.0689) time: 3.4020 data: 0.0074 max mem: 33370 +Epoch: [14] [ 480/1319] eta: 0:47:20 lr: 3.350202282685327e-05 loss: 0.0754 (0.0695) time: 3.3899 data: 0.0076 max mem: 33370 +Epoch: [14] [ 490/1319] eta: 0:46:46 lr: 3.34931054677151e-05 loss: 0.0706 (0.0693) time: 3.3701 data: 0.0077 max mem: 33370 +Epoch: [14] [ 500/1319] eta: 0:46:11 lr: 3.3484187844769246e-05 loss: 0.0691 (0.0693) time: 3.3645 data: 0.0078 max mem: 33370 +Epoch: [14] [ 510/1319] eta: 0:45:37 lr: 3.347526995792984e-05 loss: 0.0632 (0.0692) time: 3.3616 data: 0.0080 max mem: 33370 +Epoch: [14] [ 520/1319] eta: 0:45:03 lr: 3.346635180711094e-05 loss: 0.0632 (0.0692) time: 3.3724 data: 0.0080 max mem: 33370 +Epoch: [14] [ 530/1319] eta: 0:44:29 lr: 3.3457433392226575e-05 loss: 0.0604 (0.0690) time: 3.3610 data: 0.0079 max mem: 33370 +Epoch: [14] [ 540/1319] eta: 0:43:55 lr: 3.344851471319071e-05 loss: 0.0600 (0.0691) time: 3.3583 data: 0.0078 max mem: 33370 +Epoch: [14] [ 550/1319] eta: 0:43:21 lr: 3.343959576991726e-05 loss: 0.0629 (0.0690) time: 3.3676 data: 0.0075 max mem: 33370 +Epoch: [14] [ 560/1319] eta: 0:42:47 lr: 3.343067656232008e-05 loss: 0.0598 (0.0688) time: 3.3716 data: 0.0074 max mem: 33370 +Epoch: [14] [ 570/1319] eta: 0:42:13 lr: 3.342175709031298e-05 loss: 0.0599 (0.0690) time: 3.3856 data: 0.0078 max mem: 33370 +Epoch: [14] [ 580/1319] eta: 0:41:39 lr: 3.341283735380971e-05 loss: 0.0668 (0.0690) time: 3.3949 data: 0.0077 max mem: 33370 +Epoch: [14] [ 590/1319] eta: 0:41:05 lr: 3.3403917352723954e-05 loss: 0.0624 (0.0688) time: 3.3778 data: 0.0076 max mem: 33370 +Epoch: [14] [ 600/1319] eta: 0:40:32 lr: 3.339499708696938e-05 loss: 0.0607 (0.0688) time: 3.3750 data: 0.0078 max mem: 33370 +Epoch: [14] [ 610/1319] eta: 0:39:57 lr: 3.3386076556459565e-05 loss: 0.0644 (0.0689) time: 3.3682 data: 0.0075 max mem: 33370 +Epoch: [14] [ 620/1319] eta: 0:39:24 lr: 3.337715576110804e-05 loss: 0.0624 (0.0687) time: 3.3633 data: 0.0076 max mem: 33370 +Epoch: [14] [ 630/1319] eta: 0:38:50 lr: 3.336823470082831e-05 loss: 0.0545 (0.0685) time: 3.3847 data: 0.0078 max mem: 33370 +Epoch: [14] [ 640/1319] eta: 0:38:16 lr: 3.335931337553377e-05 loss: 0.0593 (0.0690) time: 3.3954 data: 0.0075 max mem: 33370 +Epoch: [14] [ 650/1319] eta: 0:37:42 lr: 3.3350391785137824e-05 loss: 0.0677 (0.0695) time: 3.3955 data: 0.0075 max mem: 33370 +Epoch: [14] [ 660/1319] eta: 0:37:08 lr: 3.334146992955378e-05 loss: 0.0677 (0.0694) time: 3.3771 data: 0.0080 max mem: 33370 +Epoch: [14] [ 670/1319] eta: 0:36:35 lr: 3.33325478086949e-05 loss: 0.0621 (0.0695) time: 3.3775 data: 0.0079 max mem: 33370 +Epoch: [14] [ 680/1319] eta: 0:36:01 lr: 3.332362542247442e-05 loss: 0.0732 (0.0698) time: 3.3755 data: 0.0081 max mem: 33370 +Epoch: [14] [ 690/1319] eta: 0:35:27 lr: 3.3314702770805464e-05 loss: 0.0873 (0.0700) time: 3.3763 data: 0.0083 max mem: 33370 +Epoch: [14] [ 700/1319] eta: 0:34:53 lr: 3.330577985360116e-05 loss: 0.0622 (0.0698) time: 3.3901 data: 0.0082 max mem: 33370 +Epoch: [14] [ 710/1319] eta: 0:34:19 lr: 3.329685667077455e-05 loss: 0.0622 (0.0698) time: 3.3614 data: 0.0084 max mem: 33370 +Epoch: [14] [ 720/1319] eta: 0:33:45 lr: 3.3287933222238623e-05 loss: 0.0657 (0.0699) time: 3.3688 data: 0.0080 max mem: 33370 +Epoch: [14] [ 730/1319] eta: 0:33:11 lr: 3.327900950790632e-05 loss: 0.0680 (0.0699) time: 3.3701 data: 0.0080 max mem: 33370 +Epoch: [14] [ 740/1319] eta: 0:32:37 lr: 3.327008552769054e-05 loss: 0.0609 (0.0699) time: 3.3715 data: 0.0083 max mem: 33370 +Epoch: [14] [ 750/1319] eta: 0:32:04 lr: 3.32611612815041e-05 loss: 0.0687 (0.0700) time: 3.3863 data: 0.0078 max mem: 33370 +Epoch: [14] [ 760/1319] eta: 0:31:30 lr: 3.325223676925979e-05 loss: 0.0648 (0.0699) time: 3.3649 data: 0.0074 max mem: 33370 +Epoch: [14] [ 770/1319] eta: 0:30:55 lr: 3.324331199087032e-05 loss: 0.0613 (0.0699) time: 3.3469 data: 0.0075 max mem: 33370 +Epoch: [14] [ 780/1319] eta: 0:30:22 lr: 3.323438694624837e-05 loss: 0.0627 (0.0698) time: 3.3568 data: 0.0080 max mem: 33370 +Epoch: [14] [ 790/1319] eta: 0:29:48 lr: 3.322546163530654e-05 loss: 0.0592 (0.0697) time: 3.3622 data: 0.0079 max mem: 33370 +Epoch: [14] [ 800/1319] eta: 0:29:14 lr: 3.32165360579574e-05 loss: 0.0525 (0.0697) time: 3.3433 data: 0.0079 max mem: 33370 +Epoch: [14] [ 810/1319] eta: 0:28:39 lr: 3.320761021411345e-05 loss: 0.0670 (0.0697) time: 3.3346 data: 0.0081 max mem: 33370 +Epoch: [14] [ 820/1319] eta: 0:28:05 lr: 3.3198684103687127e-05 loss: 0.0583 (0.0696) time: 3.3374 data: 0.0079 max mem: 33370 +Epoch: [14] [ 830/1319] eta: 0:27:32 lr: 3.318975772659084e-05 loss: 0.0667 (0.0697) time: 3.3636 data: 0.0080 max mem: 33370 +Epoch: [14] [ 840/1319] eta: 0:26:58 lr: 3.3180831082736915e-05 loss: 0.0668 (0.0696) time: 3.3597 data: 0.0078 max mem: 33370 +Epoch: [14] [ 850/1319] eta: 0:26:24 lr: 3.3171904172037654e-05 loss: 0.0619 (0.0696) time: 3.3678 data: 0.0079 max mem: 33370 +Epoch: [14] [ 860/1319] eta: 0:25:50 lr: 3.3162976994405264e-05 loss: 0.0670 (0.0697) time: 3.3740 data: 0.0079 max mem: 33370 +Epoch: [14] [ 870/1319] eta: 0:25:16 lr: 3.315404954975194e-05 loss: 0.0603 (0.0696) time: 3.3603 data: 0.0080 max mem: 33370 +Epoch: [14] [ 880/1319] eta: 0:24:42 lr: 3.314512183798977e-05 loss: 0.0590 (0.0696) time: 3.3548 data: 0.0083 max mem: 33370 +Epoch: [14] [ 890/1319] eta: 0:24:08 lr: 3.3136193859030854e-05 loss: 0.0590 (0.0695) time: 3.3386 data: 0.0078 max mem: 33370 +Epoch: [14] [ 900/1319] eta: 0:23:34 lr: 3.312726561278717e-05 loss: 0.0648 (0.0696) time: 3.3545 data: 0.0075 max mem: 33370 +Epoch: [14] [ 910/1319] eta: 0:23:01 lr: 3.311833709917069e-05 loss: 0.0681 (0.0697) time: 3.3888 data: 0.0077 max mem: 33370 +Epoch: [14] [ 920/1319] eta: 0:22:27 lr: 3.3109408318093296e-05 loss: 0.0719 (0.0698) time: 3.4004 data: 0.0078 max mem: 33370 +Epoch: [14] [ 930/1319] eta: 0:21:53 lr: 3.310047926946684e-05 loss: 0.0660 (0.0696) time: 3.3740 data: 0.0078 max mem: 33370 +Epoch: [14] [ 940/1319] eta: 0:21:19 lr: 3.309154995320309e-05 loss: 0.0640 (0.0697) time: 3.3610 data: 0.0075 max mem: 33370 +Epoch: [14] [ 950/1319] eta: 0:20:46 lr: 3.308262036921381e-05 loss: 0.0735 (0.0698) time: 3.3651 data: 0.0076 max mem: 33370 +Epoch: [14] [ 960/1319] eta: 0:20:12 lr: 3.307369051741064e-05 loss: 0.0764 (0.0699) time: 3.3473 data: 0.0077 max mem: 33370 +Epoch: [14] [ 970/1319] eta: 0:19:38 lr: 3.306476039770522e-05 loss: 0.0649 (0.0698) time: 3.3730 data: 0.0075 max mem: 33370 +Epoch: [14] [ 980/1319] eta: 0:19:04 lr: 3.30558300100091e-05 loss: 0.0687 (0.0699) time: 3.3981 data: 0.0075 max mem: 33370 +Epoch: [14] [ 990/1319] eta: 0:18:30 lr: 3.30468993542338e-05 loss: 0.0694 (0.0700) time: 3.3549 data: 0.0075 max mem: 33370 +Epoch: [14] [1000/1319] eta: 0:17:57 lr: 3.3037968430290776e-05 loss: 0.0629 (0.0699) time: 3.3571 data: 0.0075 max mem: 33370 +Epoch: [14] [1010/1319] eta: 0:17:23 lr: 3.3029037238091407e-05 loss: 0.0629 (0.0700) time: 3.3861 data: 0.0074 max mem: 33370 +Epoch: [14] [1020/1319] eta: 0:16:49 lr: 3.3020105777547046e-05 loss: 0.0640 (0.0700) time: 3.3581 data: 0.0075 max mem: 33370 +Epoch: [14] [1030/1319] eta: 0:16:15 lr: 3.301117404856897e-05 loss: 0.0615 (0.0699) time: 3.3463 data: 0.0074 max mem: 33370 +Epoch: [14] [1040/1319] eta: 0:15:42 lr: 3.300224205106842e-05 loss: 0.0579 (0.0699) time: 3.3841 data: 0.0075 max mem: 33370 +Epoch: [14] [1050/1319] eta: 0:15:08 lr: 3.2993309784956545e-05 loss: 0.0675 (0.0701) time: 3.3938 data: 0.0077 max mem: 33370 +Epoch: [14] [1060/1319] eta: 0:14:34 lr: 3.298437725014447e-05 loss: 0.0664 (0.0701) time: 3.3677 data: 0.0082 max mem: 33370 +Epoch: [14] [1070/1319] eta: 0:14:00 lr: 3.297544444654327e-05 loss: 0.0535 (0.0700) time: 3.3662 data: 0.0084 max mem: 33370 +Epoch: [14] [1080/1319] eta: 0:13:26 lr: 3.296651137406393e-05 loss: 0.0587 (0.0701) time: 3.3666 data: 0.0081 max mem: 33370 +Epoch: [14] [1090/1319] eta: 0:12:53 lr: 3.2957578032617413e-05 loss: 0.0562 (0.0700) time: 3.3581 data: 0.0076 max mem: 33370 +Epoch: [14] [1100/1319] eta: 0:12:19 lr: 3.29486444221146e-05 loss: 0.0633 (0.0701) time: 3.3770 data: 0.0073 max mem: 33370 +Epoch: [14] [1110/1319] eta: 0:11:45 lr: 3.293971054246633e-05 loss: 0.0688 (0.0701) time: 3.3606 data: 0.0076 max mem: 33370 +Epoch: [14] [1120/1319] eta: 0:11:11 lr: 3.293077639358339e-05 loss: 0.0688 (0.0702) time: 3.3271 data: 0.0081 max mem: 33370 +Epoch: [14] [1130/1319] eta: 0:10:37 lr: 3.2921841975376476e-05 loss: 0.0658 (0.0701) time: 3.3455 data: 0.0082 max mem: 33370 +Epoch: [14] [1140/1319] eta: 0:10:04 lr: 3.291290728775627e-05 loss: 0.0601 (0.0701) time: 3.3604 data: 0.0081 max mem: 33370 +Epoch: [14] [1150/1319] eta: 0:09:30 lr: 3.290397233063338e-05 loss: 0.0572 (0.0700) time: 3.3749 data: 0.0079 max mem: 33370 +Epoch: [14] [1160/1319] eta: 0:08:56 lr: 3.2895037103918356e-05 loss: 0.0529 (0.0700) time: 3.3761 data: 0.0080 max mem: 33370 +Epoch: [14] [1170/1319] eta: 0:08:22 lr: 3.2886101607521696e-05 loss: 0.0633 (0.0702) time: 3.3740 data: 0.0083 max mem: 33370 +Epoch: [14] [1180/1319] eta: 0:07:49 lr: 3.287716584135384e-05 loss: 0.0655 (0.0702) time: 3.3749 data: 0.0082 max mem: 33370 +Epoch: [14] [1190/1319] eta: 0:07:15 lr: 3.286822980532516e-05 loss: 0.0613 (0.0704) time: 3.3505 data: 0.0079 max mem: 33370 +Epoch: [14] [1200/1319] eta: 0:06:41 lr: 3.285929349934599e-05 loss: 0.0613 (0.0704) time: 3.3476 data: 0.0077 max mem: 33370 +Epoch: [14] [1210/1319] eta: 0:06:07 lr: 3.28503569233266e-05 loss: 0.0556 (0.0703) time: 3.3727 data: 0.0077 max mem: 33370 +Epoch: [14] [1220/1319] eta: 0:05:34 lr: 3.284142007717719e-05 loss: 0.0721 (0.0704) time: 3.3585 data: 0.0081 max mem: 33370 +Epoch: [14] [1230/1319] eta: 0:05:00 lr: 3.283248296080793e-05 loss: 0.0713 (0.0704) time: 3.3625 data: 0.0080 max mem: 33370 +Epoch: [14] [1240/1319] eta: 0:04:26 lr: 3.2823545574128904e-05 loss: 0.0641 (0.0704) time: 3.4134 data: 0.0075 max mem: 33370 +Epoch: [14] [1250/1319] eta: 0:03:52 lr: 3.2814607917050156e-05 loss: 0.0582 (0.0704) time: 3.3986 data: 0.0080 max mem: 33370 +Epoch: [14] [1260/1319] eta: 0:03:19 lr: 3.280566998948166e-05 loss: 0.0557 (0.0703) time: 3.3960 data: 0.0083 max mem: 33370 +Epoch: [14] [1270/1319] eta: 0:02:45 lr: 3.2796731791333364e-05 loss: 0.0556 (0.0703) time: 3.4078 data: 0.0079 max mem: 33370 +Epoch: [14] [1280/1319] eta: 0:02:11 lr: 3.278779332251511e-05 loss: 0.0603 (0.0702) time: 3.3736 data: 0.0077 max mem: 33370 +Epoch: [14] [1290/1319] eta: 0:01:37 lr: 3.277885458293673e-05 loss: 0.0619 (0.0703) time: 3.3850 data: 0.0075 max mem: 33370 +Epoch: [14] [1300/1319] eta: 0:01:04 lr: 3.276991557250796e-05 loss: 0.0757 (0.0703) time: 3.3785 data: 0.0077 max mem: 33370 +Epoch: [14] [1310/1319] eta: 0:00:30 lr: 3.276097629113851e-05 loss: 0.0694 (0.0704) time: 3.3694 data: 0.0075 max mem: 33370 +Epoch: [14] Total time: 1:14:12 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 2:54:39 time: 4.0727 data: 3.9827 max mem: 33370 +Test: [ 100/2573] eta: 0:04:51 time: 0.0778 data: 0.0015 max mem: 33370 +Test: [ 200/2573] eta: 0:03:54 time: 0.0792 data: 0.0014 max mem: 33370 +Test: [ 300/2573] eta: 0:03:28 time: 0.0806 data: 0.0014 max mem: 33370 +Test: [ 400/2573] eta: 0:03:12 time: 0.0804 data: 0.0013 max mem: 33370 +Test: [ 500/2573] eta: 0:02:59 time: 0.0787 data: 0.0014 max mem: 33370 +Test: [ 600/2573] eta: 0:02:48 time: 0.0793 data: 0.0014 max mem: 33370 +Test: [ 700/2573] eta: 0:02:39 time: 0.0790 data: 0.0014 max mem: 33370 +Test: [ 800/2573] eta: 0:02:29 time: 0.0823 data: 0.0013 max mem: 33370 +Test: [ 900/2573] eta: 0:02:20 time: 0.0793 data: 0.0014 max mem: 33370 +Test: [1000/2573] eta: 0:02:11 time: 0.0793 data: 0.0013 max mem: 33370 +Test: [1100/2573] eta: 0:02:02 time: 0.0799 data: 0.0013 max mem: 33370 +Test: [1200/2573] eta: 0:01:53 time: 0.0791 data: 0.0013 max mem: 33370 +Test: [1300/2573] eta: 0:01:45 time: 0.0790 data: 0.0013 max mem: 33370 +Test: [1400/2573] eta: 0:01:36 time: 0.0776 data: 0.0014 max mem: 33370 +Test: [1500/2573] eta: 0:01:28 time: 0.0796 data: 0.0014 max mem: 33370 +Test: [1600/2573] eta: 0:01:19 time: 0.0831 data: 0.0015 max mem: 33370 +Test: [1700/2573] eta: 0:01:11 time: 0.0784 data: 0.0013 max mem: 33370 +Test: [1800/2573] eta: 0:01:03 time: 0.0815 data: 0.0014 max mem: 33370 +Test: [1900/2573] eta: 0:00:54 time: 0.0787 data: 0.0014 max mem: 33370 +Test: [2000/2573] eta: 0:00:46 time: 0.0798 data: 0.0015 max mem: 33370 +Test: [2100/2573] eta: 0:00:38 time: 0.0816 data: 0.0014 max mem: 33370 +Test: [2200/2573] eta: 0:00:30 time: 0.0816 data: 0.0013 max mem: 33370 +Test: [2300/2573] eta: 0:00:22 time: 0.0817 data: 0.0015 max mem: 33370 +Test: [2400/2573] eta: 0:00:14 time: 0.0760 data: 0.0014 max mem: 33370 +Test: [2500/2573] eta: 0:00:05 time: 0.0792 data: 0.0013 max mem: 33370 +Test: Total time: 0:03:28 +Final results: +Mean IoU is 61.55 + + precision@0.5 = 68.81 + precision@0.6 = 63.11 + precision@0.7 = 56.33 + precision@0.8 = 44.49 + precision@0.9 = 20.57 + overall IoU = 59.96 + +Average object IoU 61.54912000067756 +Overall IoU 59.95973587036133 +Better epoch: 14 + +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [15] [ 0/1319] eta: 1:54:10 lr: 3.275293070617704e-05 loss: 0.1009 (0.1009) time: 5.1940 data: 1.8152 max mem: 33370 +Epoch: [15] [ 10/1319] eta: 1:17:07 lr: 3.274399090977129e-05 loss: 0.0635 (0.0667) time: 3.5348 data: 0.1729 max mem: 33370 +Epoch: [15] [ 20/1319] eta: 1:14:36 lr: 3.2735050842162644e-05 loss: 0.0586 (0.0654) time: 3.3589 data: 0.0081 max mem: 33370 +Epoch: [15] [ 30/1319] eta: 1:13:26 lr: 3.2726110503260586e-05 loss: 0.0578 (0.0655) time: 3.3551 data: 0.0078 max mem: 33370 +Epoch: [15] [ 40/1319] eta: 1:12:32 lr: 3.271716989297451e-05 loss: 0.0560 (0.0644) time: 3.3572 data: 0.0078 max mem: 33370 +Epoch: [15] [ 50/1319] eta: 1:11:50 lr: 3.2708229011213794e-05 loss: 0.0639 (0.0659) time: 3.3627 data: 0.0078 max mem: 33370 +Epoch: [15] [ 60/1319] eta: 1:10:56 lr: 3.269928785788772e-05 loss: 0.0651 (0.0681) time: 3.3349 data: 0.0081 max mem: 33370 +Epoch: [15] [ 70/1319] eta: 1:10:17 lr: 3.2690346432905536e-05 loss: 0.0723 (0.0690) time: 3.3244 data: 0.0082 max mem: 33370 +Epoch: [15] [ 80/1319] eta: 1:09:39 lr: 3.268140473617642e-05 loss: 0.0562 (0.0679) time: 3.3509 data: 0.0079 max mem: 33370 +Epoch: [15] [ 90/1319] eta: 1:09:00 lr: 3.26724627676095e-05 loss: 0.0507 (0.0666) time: 3.3424 data: 0.0074 max mem: 33370 +Epoch: [15] [ 100/1319] eta: 1:08:27 lr: 3.266352052711384e-05 loss: 0.0573 (0.0664) time: 3.3545 data: 0.0077 max mem: 33370 +Epoch: [15] [ 110/1319] eta: 1:07:50 lr: 3.265457801459844e-05 loss: 0.0573 (0.0659) time: 3.3561 data: 0.0082 max mem: 33370 +Epoch: [15] [ 120/1319] eta: 1:07:17 lr: 3.2645635229972264e-05 loss: 0.0551 (0.0656) time: 3.3587 data: 0.0082 max mem: 33370 +Epoch: [15] [ 130/1319] eta: 1:06:43 lr: 3.2636692173144204e-05 loss: 0.0560 (0.0650) time: 3.3696 data: 0.0085 max mem: 33370 +Epoch: [15] [ 140/1319] eta: 1:06:09 lr: 3.2627748844023084e-05 loss: 0.0526 (0.0644) time: 3.3598 data: 0.0086 max mem: 33370 +Epoch: [15] [ 150/1319] eta: 1:05:36 lr: 3.261880524251768e-05 loss: 0.0555 (0.0644) time: 3.3663 data: 0.0081 max mem: 33370 +Epoch: [15] [ 160/1319] eta: 1:05:01 lr: 3.260986136853672e-05 loss: 0.0694 (0.0642) time: 3.3651 data: 0.0082 max mem: 33370 +Epoch: [15] [ 170/1319] eta: 1:04:28 lr: 3.2600917221988844e-05 loss: 0.0593 (0.0641) time: 3.3654 data: 0.0083 max mem: 33370 +Epoch: [15] [ 180/1319] eta: 1:03:54 lr: 3.259197280278268e-05 loss: 0.0593 (0.0645) time: 3.3659 data: 0.0079 max mem: 33370 +Epoch: [15] [ 190/1319] eta: 1:03:20 lr: 3.258302811082674e-05 loss: 0.0560 (0.0641) time: 3.3633 data: 0.0081 max mem: 33370 +Epoch: [15] [ 200/1319] eta: 1:02:44 lr: 3.257408314602953e-05 loss: 0.0520 (0.0639) time: 3.3435 data: 0.0082 max mem: 33370 +Epoch: [15] [ 210/1319] eta: 1:02:08 lr: 3.2565137908299456e-05 loss: 0.0642 (0.0646) time: 3.3172 data: 0.0077 max mem: 33370 +Epoch: [15] [ 220/1319] eta: 1:01:35 lr: 3.25561923975449e-05 loss: 0.0642 (0.0646) time: 3.3500 data: 0.0078 max mem: 33370 +Epoch: [15] [ 230/1319] eta: 1:01:04 lr: 3.2547246613674155e-05 loss: 0.0600 (0.0646) time: 3.3967 data: 0.0079 max mem: 33370 +Epoch: [15] [ 240/1319] eta: 1:00:31 lr: 3.253830055659547e-05 loss: 0.0575 (0.0642) time: 3.3909 data: 0.0079 max mem: 33370 +Epoch: [15] [ 250/1319] eta: 0:59:58 lr: 3.252935422621704e-05 loss: 0.0546 (0.0643) time: 3.3826 data: 0.0079 max mem: 33370 +Epoch: [15] [ 260/1319] eta: 0:59:26 lr: 3.252040762244701e-05 loss: 0.0564 (0.0641) time: 3.3962 data: 0.0079 max mem: 33370 +Epoch: [15] [ 270/1319] eta: 0:58:53 lr: 3.251146074519342e-05 loss: 0.0568 (0.0645) time: 3.4004 data: 0.0081 max mem: 33370 +Epoch: [15] [ 280/1319] eta: 0:58:19 lr: 3.2502513594364305e-05 loss: 0.0561 (0.0644) time: 3.3761 data: 0.0077 max mem: 33370 +Epoch: [15] [ 290/1319] eta: 0:57:47 lr: 3.2493566169867616e-05 loss: 0.0561 (0.0643) time: 3.3826 data: 0.0073 max mem: 33370 +Epoch: [15] [ 300/1319] eta: 0:57:14 lr: 3.248461847161124e-05 loss: 0.0538 (0.0640) time: 3.3965 data: 0.0076 max mem: 33370 +Epoch: [15] [ 310/1319] eta: 0:56:39 lr: 3.247567049950301e-05 loss: 0.0538 (0.0639) time: 3.3625 data: 0.0076 max mem: 33370 +Epoch: [15] [ 320/1319] eta: 0:56:05 lr: 3.246672225345071e-05 loss: 0.0614 (0.0638) time: 3.3499 data: 0.0077 max mem: 33370 +Epoch: [15] [ 330/1319] eta: 0:55:30 lr: 3.245777373336205e-05 loss: 0.0614 (0.0639) time: 3.3474 data: 0.0080 max mem: 33370 +Epoch: [15] [ 340/1319] eta: 0:54:57 lr: 3.244882493914469e-05 loss: 0.0568 (0.0635) time: 3.3512 data: 0.0077 max mem: 33370 +Epoch: [15] [ 350/1319] eta: 0:54:23 lr: 3.243987587070623e-05 loss: 0.0464 (0.0637) time: 3.3641 data: 0.0077 max mem: 33370 +Epoch: [15] [ 360/1319] eta: 0:53:49 lr: 3.24309265279542e-05 loss: 0.0604 (0.0640) time: 3.3653 data: 0.0078 max mem: 33370 +Epoch: [15] [ 370/1319] eta: 0:53:16 lr: 3.2421976910796087e-05 loss: 0.0668 (0.0638) time: 3.3755 data: 0.0078 max mem: 33370 +Epoch: [15] [ 380/1319] eta: 0:52:42 lr: 3.24130270191393e-05 loss: 0.0552 (0.0638) time: 3.3688 data: 0.0079 max mem: 33370 +Epoch: [15] [ 390/1319] eta: 0:52:09 lr: 3.2404076852891215e-05 loss: 0.0552 (0.0640) time: 3.3693 data: 0.0081 max mem: 33370 +Epoch: [15] [ 400/1319] eta: 0:51:36 lr: 3.239512641195912e-05 loss: 0.0687 (0.0642) time: 3.3962 data: 0.0079 max mem: 33370 +Epoch: [15] [ 410/1319] eta: 0:51:03 lr: 3.238617569625025e-05 loss: 0.0641 (0.0642) time: 3.4001 data: 0.0076 max mem: 33370 +Epoch: [15] [ 420/1319] eta: 0:50:29 lr: 3.23772247056718e-05 loss: 0.0566 (0.0640) time: 3.3847 data: 0.0084 max mem: 33370 +Epoch: [15] [ 430/1319] eta: 0:49:55 lr: 3.2368273440130875e-05 loss: 0.0585 (0.0643) time: 3.3585 data: 0.0085 max mem: 33370 +Epoch: [15] [ 440/1319] eta: 0:49:21 lr: 3.235932189953454e-05 loss: 0.0574 (0.0640) time: 3.3618 data: 0.0077 max mem: 33370 +Epoch: [15] [ 450/1319] eta: 0:48:48 lr: 3.23503700837898e-05 loss: 0.0577 (0.0640) time: 3.3800 data: 0.0076 max mem: 33370 +Epoch: [15] [ 460/1319] eta: 0:48:15 lr: 3.234141799280359e-05 loss: 0.0624 (0.0640) time: 3.3889 data: 0.0080 max mem: 33370 +Epoch: [15] [ 470/1319] eta: 0:47:41 lr: 3.2332465626482786e-05 loss: 0.0623 (0.0641) time: 3.3736 data: 0.0082 max mem: 33370 +Epoch: [15] [ 480/1319] eta: 0:47:07 lr: 3.232351298473422e-05 loss: 0.0610 (0.0641) time: 3.3666 data: 0.0080 max mem: 33370 +Epoch: [15] [ 490/1319] eta: 0:46:33 lr: 3.231456006746465e-05 loss: 0.0574 (0.0643) time: 3.3718 data: 0.0078 max mem: 33370 +Epoch: [15] [ 500/1319] eta: 0:46:00 lr: 3.2305606874580764e-05 loss: 0.0573 (0.0645) time: 3.3737 data: 0.0077 max mem: 33370 +Epoch: [15] [ 510/1319] eta: 0:45:27 lr: 3.229665340598921e-05 loss: 0.0516 (0.0646) time: 3.4035 data: 0.0081 max mem: 33370 +Epoch: [15] [ 520/1319] eta: 0:44:53 lr: 3.228769966159657e-05 loss: 0.0630 (0.0647) time: 3.3863 data: 0.0082 max mem: 33370 +Epoch: [15] [ 530/1319] eta: 0:44:19 lr: 3.227874564130935e-05 loss: 0.0595 (0.0648) time: 3.3489 data: 0.0077 max mem: 33370 +Epoch: [15] [ 540/1319] eta: 0:43:45 lr: 3.2269791345034015e-05 loss: 0.0558 (0.0650) time: 3.3615 data: 0.0078 max mem: 33370 +Epoch: [15] [ 550/1319] eta: 0:43:11 lr: 3.226083677267696e-05 loss: 0.0637 (0.0654) time: 3.3670 data: 0.0084 max mem: 33370 +Epoch: [15] [ 560/1319] eta: 0:42:37 lr: 3.225188192414452e-05 loss: 0.0634 (0.0653) time: 3.3413 data: 0.0084 max mem: 33370 +Epoch: [15] [ 570/1319] eta: 0:42:04 lr: 3.224292679934298e-05 loss: 0.0573 (0.0653) time: 3.3680 data: 0.0079 max mem: 33370 +Epoch: [15] [ 580/1319] eta: 0:41:30 lr: 3.2233971398178544e-05 loss: 0.0590 (0.0652) time: 3.3790 data: 0.0079 max mem: 33370 +Epoch: [15] [ 590/1319] eta: 0:40:57 lr: 3.2225015720557374e-05 loss: 0.0568 (0.0652) time: 3.3873 data: 0.0078 max mem: 33370 +Epoch: [15] [ 600/1319] eta: 0:40:23 lr: 3.221605976638556e-05 loss: 0.0619 (0.0652) time: 3.3907 data: 0.0076 max mem: 33370 +Epoch: [15] [ 610/1319] eta: 0:39:49 lr: 3.2207103535569134e-05 loss: 0.0641 (0.0653) time: 3.3731 data: 0.0077 max mem: 33370 +Epoch: [15] [ 620/1319] eta: 0:39:17 lr: 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eta: 0:34:47 lr: 3.212648499367893e-05 loss: 0.0497 (0.0654) time: 3.3538 data: 0.0076 max mem: 33370 +Epoch: [15] [ 710/1319] eta: 0:34:13 lr: 3.211752599123473e-05 loss: 0.0602 (0.0655) time: 3.3445 data: 0.0077 max mem: 33370 +Epoch: [15] [ 720/1319] eta: 0:33:39 lr: 3.210856671110825e-05 loss: 0.0602 (0.0656) time: 3.3551 data: 0.0077 max mem: 33370 +Epoch: [15] [ 730/1319] eta: 0:33:05 lr: 3.2099607153204766e-05 loss: 0.0568 (0.0656) time: 3.3305 data: 0.0079 max mem: 33370 +Epoch: [15] [ 740/1319] eta: 0:32:31 lr: 3.209064731742954e-05 loss: 0.0568 (0.0656) time: 3.3579 data: 0.0077 max mem: 33370 +Epoch: [15] [ 750/1319] eta: 0:31:57 lr: 3.208168720368771e-05 loss: 0.0625 (0.0658) time: 3.3663 data: 0.0075 max mem: 33370 +Epoch: [15] [ 760/1319] eta: 0:31:24 lr: 3.2072726811884414e-05 loss: 0.0647 (0.0658) time: 3.3684 data: 0.0073 max mem: 33370 +Epoch: [15] [ 770/1319] eta: 0:30:50 lr: 3.20637661419247e-05 loss: 0.0570 (0.0658) time: 3.3820 data: 0.0077 max mem: 33370 +Epoch: 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mem: 33370 +Epoch: [15] [ 860/1319] eta: 0:25:46 lr: 3.198310757955068e-05 loss: 0.0639 (0.0655) time: 3.3453 data: 0.0085 max mem: 33370 +Epoch: [15] [ 870/1319] eta: 0:25:13 lr: 3.197414412279081e-05 loss: 0.0563 (0.0656) time: 3.3773 data: 0.0084 max mem: 33370 +Epoch: [15] [ 880/1319] eta: 0:24:39 lr: 3.196518038682597e-05 loss: 0.0534 (0.0657) time: 3.4175 data: 0.0081 max mem: 33370 +Epoch: [15] [ 890/1319] eta: 0:24:06 lr: 3.1956216371560456e-05 loss: 0.0534 (0.0656) time: 3.4195 data: 0.0078 max mem: 33370 +Epoch: [15] [ 900/1319] eta: 0:23:32 lr: 3.194725207689851e-05 loss: 0.0550 (0.0657) time: 3.3819 data: 0.0076 max mem: 33370 +Epoch: [15] [ 910/1319] eta: 0:22:58 lr: 3.1938287502744314e-05 loss: 0.0626 (0.0657) time: 3.3731 data: 0.0078 max mem: 33370 +Epoch: [15] [ 920/1319] eta: 0:22:25 lr: 3.192932264900198e-05 loss: 0.0637 (0.0658) time: 3.3456 data: 0.0081 max mem: 33370 +Epoch: [15] [ 930/1319] eta: 0:21:51 lr: 3.192035751557555e-05 loss: 0.0549 (0.0656) time: 3.3319 data: 0.0077 max mem: 33370 +Epoch: [15] [ 940/1319] eta: 0:21:17 lr: 3.1911392102369026e-05 loss: 0.0566 (0.0656) time: 3.3602 data: 0.0078 max mem: 33370 +Epoch: [15] [ 950/1319] eta: 0:20:43 lr: 3.1902426409286326e-05 loss: 0.0601 (0.0656) time: 3.3710 data: 0.0081 max mem: 33370 +Epoch: [15] [ 960/1319] eta: 0:20:10 lr: 3.189346043623133e-05 loss: 0.0612 (0.0656) time: 3.3609 data: 0.0078 max mem: 33370 +Epoch: [15] [ 970/1319] eta: 0:19:36 lr: 3.1884494183107815e-05 loss: 0.0638 (0.0658) time: 3.3795 data: 0.0079 max mem: 33370 +Epoch: [15] [ 980/1319] eta: 0:19:02 lr: 3.187552764981953e-05 loss: 0.0575 (0.0657) time: 3.3919 data: 0.0080 max mem: 33370 +Epoch: [15] [ 990/1319] eta: 0:18:28 lr: 3.186656083627014e-05 loss: 0.0575 (0.0656) time: 3.3689 data: 0.0079 max mem: 33370 +Epoch: [15] [1000/1319] eta: 0:17:55 lr: 3.1857593742363276e-05 loss: 0.0612 (0.0657) time: 3.3537 data: 0.0077 max mem: 33370 +Epoch: [15] [1010/1319] eta: 0:17:21 lr: 3.184862636800246e-05 loss: 0.0516 (0.0656) time: 3.3480 data: 0.0073 max mem: 33370 +Epoch: [15] [1020/1319] eta: 0:16:47 lr: 3.183965871309119e-05 loss: 0.0527 (0.0656) time: 3.3504 data: 0.0074 max mem: 33370 +Epoch: [15] [1030/1319] eta: 0:16:13 lr: 3.1830690777532884e-05 loss: 0.0508 (0.0654) time: 3.3448 data: 0.0081 max mem: 33370 +Epoch: [15] [1040/1319] eta: 0:15:40 lr: 3.182172256123091e-05 loss: 0.0499 (0.0654) time: 3.3422 data: 0.0080 max mem: 33370 +Epoch: [15] [1050/1319] eta: 0:15:06 lr: 3.181275406408854e-05 loss: 0.0552 (0.0655) time: 3.3784 data: 0.0078 max mem: 33370 +Epoch: [15] [1060/1319] eta: 0:14:32 lr: 3.180378528600901e-05 loss: 0.0669 (0.0657) time: 3.3801 data: 0.0078 max mem: 33370 +Epoch: [15] [1070/1319] eta: 0:13:59 lr: 3.17948162268955e-05 loss: 0.0699 (0.0657) time: 3.3472 data: 0.0074 max mem: 33370 +Epoch: [15] [1080/1319] eta: 0:13:25 lr: 3.17858468866511e-05 loss: 0.0649 (0.0657) time: 3.3773 data: 0.0076 max mem: 33370 +Epoch: [15] [1090/1319] eta: 0:12:51 lr: 3.177687726517885e-05 loss: 0.0623 (0.0657) time: 3.3868 data: 0.0078 max mem: 33370 +Epoch: [15] [1100/1319] eta: 0:12:18 lr: 3.1767907362381725e-05 loss: 0.0573 (0.0657) time: 3.3715 data: 0.0080 max mem: 33370 +Epoch: [15] [1110/1319] eta: 0:11:44 lr: 3.175893717816263e-05 loss: 0.0541 (0.0656) time: 3.3740 data: 0.0080 max mem: 33370 +Epoch: [15] [1120/1319] eta: 0:11:10 lr: 3.174996671242443e-05 loss: 0.0568 (0.0656) time: 3.3930 data: 0.0078 max mem: 33370 +Epoch: [15] [1130/1319] eta: 0:10:37 lr: 3.1740995965069895e-05 loss: 0.0568 (0.0655) time: 3.4066 data: 0.0077 max mem: 33370 +Epoch: [15] [1140/1319] eta: 0:10:03 lr: 3.173202493600174e-05 loss: 0.0570 (0.0654) time: 3.3880 data: 0.0077 max mem: 33370 +Epoch: [15] [1150/1319] eta: 0:09:29 lr: 3.172305362512263e-05 loss: 0.0611 (0.0654) time: 3.3680 data: 0.0077 max mem: 33370 +Epoch: [15] [1160/1319] eta: 0:08:55 lr: 3.171408203233514e-05 loss: 0.0673 (0.0655) time: 3.3775 data: 0.0078 max mem: 33370 +Epoch: [15] [1170/1319] eta: 0:08:22 lr: 3.170511015754181e-05 loss: 0.0701 (0.0657) time: 3.4000 data: 0.0078 max mem: 33370 +Epoch: [15] [1180/1319] eta: 0:07:48 lr: 3.16961380006451e-05 loss: 0.0621 (0.0657) time: 3.3833 data: 0.0078 max mem: 33370 +Epoch: [15] [1190/1319] eta: 0:07:14 lr: 3.16871655615474e-05 loss: 0.0506 (0.0656) time: 3.3711 data: 0.0080 max mem: 33370 +Epoch: [15] [1200/1319] eta: 0:06:41 lr: 3.1678192840151044e-05 loss: 0.0521 (0.0656) time: 3.3830 data: 0.0081 max mem: 33370 +Epoch: [15] [1210/1319] eta: 0:06:07 lr: 3.16692198363583e-05 loss: 0.0541 (0.0656) time: 3.3894 data: 0.0077 max mem: 33370 +Epoch: [15] [1220/1319] eta: 0:05:33 lr: 3.1660246550071386e-05 loss: 0.0575 (0.0656) time: 3.3962 data: 0.0078 max mem: 33370 +Epoch: [15] [1230/1319] eta: 0:05:00 lr: 3.165127298119242e-05 loss: 0.0675 (0.0657) time: 3.3788 data: 0.0079 max mem: 33370 +Epoch: [15] [1240/1319] eta: 0:04:26 lr: 3.164229912962349e-05 loss: 0.0627 (0.0657) time: 3.3616 data: 0.0077 max mem: 33370 +Epoch: [15] [1250/1319] eta: 0:03:52 lr: 3.163332499526659e-05 loss: 0.0548 (0.0656) time: 3.3857 data: 0.0078 max mem: 33370 +Epoch: [15] [1260/1319] eta: 0:03:18 lr: 3.162435057802369e-05 loss: 0.0557 (0.0656) time: 3.3747 data: 0.0077 max mem: 33370 +Epoch: [15] [1270/1319] eta: 0:02:45 lr: 3.161537587779665e-05 loss: 0.0618 (0.0656) time: 3.3532 data: 0.0078 max mem: 33370 +Epoch: [15] [1280/1319] eta: 0:02:11 lr: 3.1606400894487287e-05 loss: 0.0694 (0.0658) time: 3.3619 data: 0.0078 max mem: 33370 +Epoch: [15] [1290/1319] eta: 0:01:37 lr: 3.159742562799735e-05 loss: 0.0700 (0.0658) time: 3.3686 data: 0.0083 max mem: 33370 +Epoch: [15] [1300/1319] eta: 0:01:04 lr: 3.158845007822852e-05 loss: 0.0636 (0.0659) time: 3.3506 data: 0.0083 max mem: 33370 +Epoch: [15] [1310/1319] eta: 0:00:30 lr: 3.1579474245082424e-05 loss: 0.0614 (0.0660) time: 3.3723 data: 0.0074 max mem: 33370 +Epoch: [15] Total time: 1:14:07 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 2:50:06 time: 3.9668 data: 3.8432 max mem: 33370 +Test: [ 100/2573] eta: 0:04:46 time: 0.0772 data: 0.0013 max mem: 33370 +Test: [ 200/2573] eta: 0:03:52 time: 0.0788 data: 0.0013 max mem: 33370 +Test: [ 300/2573] eta: 0:03:27 time: 0.0812 data: 0.0015 max mem: 33370 +Test: [ 400/2573] eta: 0:03:11 time: 0.0814 data: 0.0014 max mem: 33370 +Test: [ 500/2573] eta: 0:02:59 time: 0.0799 data: 0.0014 max mem: 33370 +Test: [ 600/2573] eta: 0:02:48 time: 0.0796 data: 0.0014 max mem: 33370 +Test: [ 700/2573] eta: 0:02:39 time: 0.0808 data: 0.0014 max mem: 33370 +Test: [ 800/2573] eta: 0:02:29 time: 0.0828 data: 0.0014 max mem: 33370 +Test: [ 900/2573] eta: 0:02:20 time: 0.0805 data: 0.0015 max mem: 33370 +Test: [1000/2573] eta: 0:02:11 time: 0.0792 data: 0.0013 max mem: 33370 +Test: [1100/2573] eta: 0:02:02 time: 0.0795 data: 0.0013 max mem: 33370 +Test: [1200/2573] eta: 0:01:54 time: 0.0795 data: 0.0014 max mem: 33370 +Test: [1300/2573] eta: 0:01:45 time: 0.0790 data: 0.0013 max mem: 33370 +Test: [1400/2573] eta: 0:01:36 time: 0.0779 data: 0.0014 max mem: 33370 +Test: [1500/2573] eta: 0:01:28 time: 0.0796 data: 0.0013 max mem: 33370 +Test: [1600/2573] eta: 0:01:19 time: 0.0825 data: 0.0013 max mem: 33370 +Test: [1700/2573] eta: 0:01:11 time: 0.0783 data: 0.0014 max mem: 33370 +Test: [1800/2573] eta: 0:01:03 time: 0.0806 data: 0.0014 max mem: 33370 +Test: [1900/2573] eta: 0:00:55 time: 0.0785 data: 0.0014 max mem: 33370 +Test: [2000/2573] eta: 0:00:46 time: 0.0787 data: 0.0013 max mem: 33370 +Test: [2100/2573] eta: 0:00:38 time: 0.0813 data: 0.0013 max mem: 33370 +Test: [2200/2573] eta: 0:00:30 time: 0.0810 data: 0.0014 max mem: 33370 +Test: [2300/2573] eta: 0:00:22 time: 0.0815 data: 0.0014 max mem: 33370 +Test: [2400/2573] eta: 0:00:14 time: 0.0774 data: 0.0015 max mem: 33370 +Test: [2500/2573] eta: 0:00:05 time: 0.0794 data: 0.0014 max mem: 33370 +Test: Total time: 0:03:29 +Final results: +Mean IoU is 62.65 + + precision@0.5 = 70.04 + precision@0.6 = 64.20 + precision@0.7 = 56.99 + precision@0.8 = 44.75 + precision@0.9 = 21.04 + overall IoU = 60.60 + +Average object IoU 62.65489930302562 +Overall IoU 60.59933090209961 +Better epoch: 15 + +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [16] [ 0/1319] eta: 2:09:26 lr: 3.157139575288201e-05 loss: 0.0529 (0.0529) time: 5.8878 data: 2.3611 max mem: 33370 +Epoch: [16] [ 10/1319] eta: 1:17:32 lr: 3.1562419381047834e-05 loss: 0.0478 (0.0526) time: 3.5544 data: 0.2221 max mem: 33370 +Epoch: [16] [ 20/1319] eta: 1:15:11 lr: 3.155344272555071e-05 loss: 0.0505 (0.0545) time: 3.3525 data: 0.0078 max mem: 33370 +Epoch: [16] [ 30/1319] eta: 1:13:50 lr: 3.154446578629201e-05 loss: 0.0510 (0.0566) time: 3.3731 data: 0.0078 max mem: 33370 +Epoch: [16] [ 40/1319] eta: 1:12:52 lr: 3.153548856317304e-05 loss: 0.0498 (0.0578) time: 3.3612 data: 0.0081 max mem: 33370 +Epoch: [16] [ 50/1319] eta: 1:12:09 lr: 3.152651105609501e-05 loss: 0.0459 (0.0549) time: 3.3724 data: 0.0079 max mem: 33370 +Epoch: [16] [ 60/1319] eta: 1:11:23 lr: 3.1517533264959104e-05 loss: 0.0444 (0.0553) time: 3.3699 data: 0.0077 max mem: 33370 +Epoch: [16] [ 70/1319] eta: 1:10:39 lr: 3.150855518966642e-05 loss: 0.0503 (0.0568) time: 3.3499 data: 0.0074 max mem: 33370 +Epoch: [16] [ 80/1319] eta: 1:09:58 lr: 3.1499576830118e-05 loss: 0.0572 (0.0571) time: 3.3445 data: 0.0079 max mem: 33370 +Epoch: [16] [ 90/1319] eta: 1:09:23 lr: 3.14905981862148e-05 loss: 0.0519 (0.0569) time: 3.3653 data: 0.0079 max mem: 33370 +Epoch: [16] [ 100/1319] eta: 1:08:46 lr: 3.1481619257857746e-05 loss: 0.0519 (0.0573) time: 3.3735 data: 0.0077 max mem: 33370 +Epoch: [16] [ 110/1319] eta: 1:08:10 lr: 3.147264004494766e-05 loss: 0.0611 (0.0581) time: 3.3608 data: 0.0081 max mem: 33370 +Epoch: [16] [ 120/1319] eta: 1:07:31 lr: 3.1463660547385324e-05 loss: 0.0661 (0.0590) time: 3.3484 data: 0.0078 max mem: 33370 +Epoch: [16] [ 130/1319] eta: 1:06:59 lr: 3.1454680765071425e-05 loss: 0.0661 (0.0594) time: 3.3654 data: 0.0078 max mem: 33370 +Epoch: [16] [ 140/1319] eta: 1:06:22 lr: 3.1445700697906627e-05 loss: 0.0562 (0.0592) time: 3.3720 data: 0.0084 max mem: 33370 +Epoch: [16] [ 150/1319] eta: 1:05:46 lr: 3.1436720345791495e-05 loss: 0.0605 (0.0593) time: 3.3500 data: 0.0081 max mem: 33370 +Epoch: [16] [ 160/1319] eta: 1:05:14 lr: 3.1427739708626534e-05 loss: 0.0498 (0.0585) time: 3.3743 data: 0.0078 max mem: 33370 +Epoch: [16] [ 170/1319] eta: 1:04:38 lr: 3.141875878631219e-05 loss: 0.0444 (0.0585) time: 3.3695 data: 0.0081 max mem: 33370 +Epoch: [16] [ 180/1319] eta: 1:04:03 lr: 3.140977757874883e-05 loss: 0.0577 (0.0593) time: 3.3480 data: 0.0079 max mem: 33370 +Epoch: [16] [ 190/1319] eta: 1:03:29 lr: 3.140079608583676e-05 loss: 0.0534 (0.0594) time: 3.3649 data: 0.0078 max mem: 33370 +Epoch: [16] [ 200/1319] eta: 1:02:56 lr: 3.1391814307476244e-05 loss: 0.0491 (0.0587) time: 3.3784 data: 0.0077 max mem: 33370 +Epoch: [16] [ 210/1319] eta: 1:02:24 lr: 3.138283224356744e-05 loss: 0.0455 (0.0588) time: 3.3968 data: 0.0077 max mem: 33370 +Epoch: [16] [ 220/1319] eta: 1:01:51 lr: 3.137384989401046e-05 loss: 0.0484 (0.0587) time: 3.3971 data: 0.0076 max mem: 33370 +Epoch: [16] [ 230/1319] eta: 1:01:16 lr: 3.136486725870535e-05 loss: 0.0484 (0.0592) time: 3.3753 data: 0.0077 max mem: 33370 +Epoch: [16] [ 240/1319] eta: 1:00:43 lr: 3.1355884337552074e-05 loss: 0.0504 (0.0591) time: 3.3793 data: 0.0080 max mem: 33370 +Epoch: [16] [ 250/1319] eta: 1:00:09 lr: 3.1346901130450554e-05 loss: 0.0548 (0.0595) time: 3.3828 data: 0.0077 max mem: 33370 +Epoch: [16] [ 260/1319] eta: 0:59:36 lr: 3.133791763730062e-05 loss: 0.0563 (0.0598) time: 3.3814 data: 0.0074 max mem: 33370 +Epoch: [16] [ 270/1319] eta: 0:59:01 lr: 3.132893385800206e-05 loss: 0.0564 (0.0601) time: 3.3634 data: 0.0075 max mem: 33370 +Epoch: [16] [ 280/1319] eta: 0:58:28 lr: 3.131994979245456e-05 loss: 0.0561 (0.0607) time: 3.3675 data: 0.0077 max mem: 33370 +Epoch: [16] [ 290/1319] eta: 0:57:54 lr: 3.131096544055778e-05 loss: 0.0569 (0.0607) time: 3.3869 data: 0.0075 max mem: 33370 +Epoch: [16] [ 300/1319] eta: 0:57:21 lr: 3.130198080221128e-05 loss: 0.0652 (0.0616) time: 3.3935 data: 0.0075 max mem: 33370 +Epoch: [16] [ 310/1319] eta: 0:56:49 lr: 3.129299587731458e-05 loss: 0.0548 (0.0614) time: 3.4116 data: 0.0074 max mem: 33370 +Epoch: [16] [ 320/1319] eta: 0:56:15 lr: 3.1284010665767105e-05 loss: 0.0547 (0.0621) time: 3.3927 data: 0.0075 max mem: 33370 +Epoch: [16] [ 330/1319] eta: 0:55:40 lr: 3.1275025167468235e-05 loss: 0.0616 (0.0630) time: 3.3574 data: 0.0077 max mem: 33370 +Epoch: [16] [ 340/1319] eta: 0:55:07 lr: 3.126603938231727e-05 loss: 0.0616 (0.0629) time: 3.3712 data: 0.0079 max mem: 33370 +Epoch: [16] [ 350/1319] eta: 0:54:32 lr: 3.1257053310213444e-05 loss: 0.0585 (0.0630) time: 3.3724 data: 0.0082 max mem: 33370 +Epoch: [16] [ 360/1319] eta: 0:53:57 lr: 3.124806695105593e-05 loss: 0.0650 (0.0630) time: 3.3351 data: 0.0079 max mem: 33370 +Epoch: [16] [ 370/1319] eta: 0:53:23 lr: 3.1239080304743815e-05 loss: 0.0667 (0.0634) time: 3.3401 data: 0.0078 max mem: 33370 +Epoch: [16] [ 380/1319] eta: 0:52:49 lr: 3.123009337117616e-05 loss: 0.0603 (0.0631) time: 3.3734 data: 0.0081 max mem: 33370 +Epoch: [16] [ 390/1319] eta: 0:52:16 lr: 3.12211061502519e-05 loss: 0.0527 (0.0630) time: 3.3935 data: 0.0081 max mem: 33370 +Epoch: [16] [ 400/1319] eta: 0:51:42 lr: 3.121211864186995e-05 loss: 0.0591 (0.0631) time: 3.3818 data: 0.0083 max mem: 33370 +Epoch: [16] [ 410/1319] eta: 0:51:08 lr: 3.120313084592913e-05 loss: 0.0619 (0.0632) time: 3.3687 data: 0.0082 max mem: 33370 +Epoch: [16] [ 420/1319] eta: 0:50:35 lr: 3.119414276232821e-05 loss: 0.0556 (0.0630) time: 3.3886 data: 0.0083 max mem: 33370 +Epoch: [16] [ 430/1319] eta: 0:50:02 lr: 3.118515439096588e-05 loss: 0.0556 (0.0629) time: 3.4031 data: 0.0083 max mem: 33370 +Epoch: [16] [ 440/1319] eta: 0:49:28 lr: 3.117616573174077e-05 loss: 0.0630 (0.0631) time: 3.3782 data: 0.0079 max mem: 33370 +Epoch: [16] [ 450/1319] eta: 0:48:54 lr: 3.116717678455143e-05 loss: 0.0627 (0.0631) time: 3.3676 data: 0.0078 max mem: 33370 +Epoch: [16] [ 460/1319] eta: 0:48:21 lr: 3.115818754929635e-05 loss: 0.0569 (0.0629) time: 3.3910 data: 0.0077 max mem: 33370 +Epoch: [16] [ 470/1319] eta: 0:47:46 lr: 3.1149198025873954e-05 loss: 0.0572 (0.0629) time: 3.3760 data: 0.0075 max mem: 33370 +Epoch: [16] [ 480/1319] eta: 0:47:13 lr: 3.1140208214182586e-05 loss: 0.0572 (0.0627) time: 3.3707 data: 0.0077 max mem: 33370 +Epoch: [16] [ 490/1319] eta: 0:46:40 lr: 3.113121811412054e-05 loss: 0.0484 (0.0626) time: 3.4004 data: 0.0080 max mem: 33370 +Epoch: [16] [ 500/1319] eta: 0:46:06 lr: 3.1122227725586026e-05 loss: 0.0549 (0.0627) time: 3.3900 data: 0.0078 max mem: 33370 +Epoch: [16] [ 510/1319] eta: 0:45:32 lr: 3.1113237048477186e-05 loss: 0.0546 (0.0627) time: 3.3753 data: 0.0074 max mem: 33370 +Epoch: [16] [ 520/1319] eta: 0:44:58 lr: 3.11042460826921e-05 loss: 0.0490 (0.0624) time: 3.3596 data: 0.0076 max mem: 33370 +Epoch: [16] [ 530/1319] eta: 0:44:23 lr: 3.1095254828128786e-05 loss: 0.0482 (0.0624) time: 3.3443 data: 0.0077 max mem: 33370 +Epoch: [16] [ 540/1319] eta: 0:43:49 lr: 3.108626328468517e-05 loss: 0.0544 (0.0622) time: 3.3419 data: 0.0076 max mem: 33370 +Epoch: [16] [ 550/1319] eta: 0:43:15 lr: 3.107727145225915e-05 loss: 0.0539 (0.0622) time: 3.3449 data: 0.0079 max mem: 33370 +Epoch: [16] [ 560/1319] eta: 0:42:40 lr: 3.106827933074849e-05 loss: 0.0573 (0.0623) time: 3.3347 data: 0.0080 max mem: 33370 +Epoch: [16] [ 570/1319] eta: 0:42:07 lr: 3.105928692005095e-05 loss: 0.0512 (0.0622) time: 3.3441 data: 0.0078 max mem: 33370 +Epoch: [16] [ 580/1319] eta: 0:41:33 lr: 3.105029422006419e-05 loss: 0.0502 (0.0623) time: 3.3615 data: 0.0078 max mem: 33370 +Epoch: [16] [ 590/1319] eta: 0:40:59 lr: 3.104130123068579e-05 loss: 0.0676 (0.0626) time: 3.3555 data: 0.0076 max mem: 33370 +Epoch: [16] [ 600/1319] eta: 0:40:25 lr: 3.10323079518133e-05 loss: 0.0676 (0.0624) time: 3.3774 data: 0.0076 max mem: 33370 +Epoch: [16] [ 610/1319] eta: 0:39:51 lr: 3.102331438334416e-05 loss: 0.0529 (0.0624) time: 3.3731 data: 0.0079 max mem: 33370 +Epoch: [16] [ 620/1319] eta: 0:39:18 lr: 3.1014320525175755e-05 loss: 0.0529 (0.0624) time: 3.3707 data: 0.0077 max mem: 33370 +Epoch: [16] [ 630/1319] eta: 0:38:44 lr: 3.100532637720542e-05 loss: 0.0553 (0.0628) time: 3.3785 data: 0.0076 max mem: 33370 +Epoch: [16] [ 640/1319] eta: 0:38:11 lr: 3.099633193933038e-05 loss: 0.0589 (0.0628) time: 3.3965 data: 0.0079 max mem: 33370 +Epoch: [16] [ 650/1319] eta: 0:37:37 lr: 3.098733721144784e-05 loss: 0.0538 (0.0627) time: 3.3956 data: 0.0081 max mem: 33370 +Epoch: [16] [ 660/1319] eta: 0:37:03 lr: 3.097834219345489e-05 loss: 0.0511 (0.0628) time: 3.3636 data: 0.0080 max mem: 33370 +Epoch: [16] [ 670/1319] eta: 0:36:30 lr: 3.0969346885248574e-05 loss: 0.0487 (0.0628) time: 3.3847 data: 0.0077 max mem: 33370 +Epoch: [16] [ 680/1319] eta: 0:35:56 lr: 3.0960351286725865e-05 loss: 0.0482 (0.0627) time: 3.3873 data: 0.0077 max mem: 33370 +Epoch: [16] [ 690/1319] eta: 0:35:22 lr: 3.0951355397783653e-05 loss: 0.0503 (0.0629) time: 3.3683 data: 0.0077 max mem: 33370 +Epoch: [16] [ 700/1319] eta: 0:34:48 lr: 3.0942359218318776e-05 loss: 0.0596 (0.0629) time: 3.3626 data: 0.0077 max mem: 33370 +Epoch: [16] [ 710/1319] eta: 0:34:14 lr: 3.0933362748228e-05 loss: 0.0596 (0.0630) time: 3.3700 data: 0.0078 max mem: 33370 +Epoch: [16] [ 720/1319] eta: 0:33:40 lr: 3.092436598740799e-05 loss: 0.0495 (0.0630) time: 3.3619 data: 0.0079 max mem: 33370 +Epoch: [16] [ 730/1319] eta: 0:33:06 lr: 3.09153689357554e-05 loss: 0.0497 (0.0630) time: 3.3436 data: 0.0079 max mem: 33370 +Epoch: [16] [ 740/1319] eta: 0:32:33 lr: 3.090637159316675e-05 loss: 0.0497 (0.0629) time: 3.3601 data: 0.0077 max mem: 33370 +Epoch: [16] [ 750/1319] eta: 0:31:59 lr: 3.089737395953854e-05 loss: 0.0504 (0.0628) time: 3.3639 data: 0.0079 max mem: 33370 +Epoch: [16] [ 760/1319] eta: 0:31:25 lr: 3.088837603476717e-05 loss: 0.0569 (0.0630) time: 3.3861 data: 0.0080 max mem: 33370 +Epoch: [16] [ 770/1319] eta: 0:30:52 lr: 3.087937781874897e-05 loss: 0.0526 (0.0630) time: 3.3826 data: 0.0078 max mem: 33370 +Epoch: [16] [ 780/1319] eta: 0:30:18 lr: 3.087037931138022e-05 loss: 0.0526 (0.0630) time: 3.3704 data: 0.0077 max mem: 33370 +Epoch: [16] [ 790/1319] eta: 0:29:44 lr: 3.086138051255712e-05 loss: 0.0547 (0.0629) time: 3.3884 data: 0.0076 max mem: 33370 +Epoch: [16] [ 800/1319] eta: 0:29:11 lr: 3.085238142217579e-05 loss: 0.0476 (0.0628) time: 3.3782 data: 0.0078 max mem: 33370 +Epoch: [16] [ 810/1319] eta: 0:28:37 lr: 3.084338204013227e-05 loss: 0.0581 (0.0630) time: 3.3568 data: 0.0076 max mem: 33370 +Epoch: [16] [ 820/1319] eta: 0:28:03 lr: 3.0834382366322574e-05 loss: 0.0620 (0.0630) time: 3.3615 data: 0.0073 max mem: 33370 +Epoch: [16] [ 830/1319] eta: 0:27:29 lr: 3.08253824006426e-05 loss: 0.0600 (0.0631) time: 3.3887 data: 0.0077 max mem: 33370 +Epoch: [16] [ 840/1319] eta: 0:26:56 lr: 3.08163821429882e-05 loss: 0.0584 (0.0631) time: 3.3941 data: 0.0077 max mem: 33370 +Epoch: [16] [ 850/1319] eta: 0:26:22 lr: 3.0807381593255134e-05 loss: 0.0544 (0.0631) time: 3.3739 data: 0.0077 max mem: 33370 +Epoch: [16] [ 860/1319] eta: 0:25:48 lr: 3.079838075133912e-05 loss: 0.0574 (0.0631) time: 3.3716 data: 0.0078 max mem: 33370 +Epoch: [16] [ 870/1319] eta: 0:25:15 lr: 3.0789379617135774e-05 loss: 0.0590 (0.0632) time: 3.3935 data: 0.0081 max mem: 33370 +Epoch: [16] [ 880/1319] eta: 0:24:41 lr: 3.078037819054066e-05 loss: 0.0590 (0.0631) time: 3.4076 data: 0.0084 max mem: 33370 +Epoch: [16] [ 890/1319] eta: 0:24:07 lr: 3.0771376471449264e-05 loss: 0.0580 (0.0632) time: 3.3827 data: 0.0083 max mem: 33370 +Epoch: [16] [ 900/1319] eta: 0:23:33 lr: 3.076237445975701e-05 loss: 0.0580 (0.0633) time: 3.3694 data: 0.0079 max mem: 33370 +Epoch: [16] [ 910/1319] eta: 0:23:00 lr: 3.075337215535924e-05 loss: 0.0588 (0.0634) time: 3.3824 data: 0.0074 max mem: 33370 +Epoch: [16] [ 920/1319] eta: 0:22:26 lr: 3.074436955815122e-05 loss: 0.0660 (0.0636) time: 3.3813 data: 0.0074 max mem: 33370 +Epoch: [16] [ 930/1319] eta: 0:21:52 lr: 3.073536666802816e-05 loss: 0.0576 (0.0635) time: 3.3757 data: 0.0079 max mem: 33370 +Epoch: [16] [ 940/1319] eta: 0:21:18 lr: 3.0726363484885186e-05 loss: 0.0557 (0.0635) time: 3.3682 data: 0.0079 max mem: 33370 +Epoch: [16] [ 950/1319] eta: 0:20:45 lr: 3.0717360008617356e-05 loss: 0.0516 (0.0634) time: 3.3752 data: 0.0076 max mem: 33370 +Epoch: [16] [ 960/1319] eta: 0:20:11 lr: 3.070835623911966e-05 loss: 0.0568 (0.0634) time: 3.3859 data: 0.0078 max mem: 33370 +Epoch: [16] [ 970/1319] eta: 0:19:37 lr: 3.069935217628702e-05 loss: 0.0568 (0.0633) time: 3.3690 data: 0.0079 max mem: 33370 +Epoch: [16] [ 980/1319] eta: 0:19:04 lr: 3.0690347820014265e-05 loss: 0.0522 (0.0632) time: 3.3696 data: 0.0076 max mem: 33370 +Epoch: [16] [ 990/1319] eta: 0:18:30 lr: 3.068134317019618e-05 loss: 0.0559 (0.0631) time: 3.3797 data: 0.0076 max mem: 33370 +Epoch: [16] [1000/1319] eta: 0:17:56 lr: 3.0672338226727455e-05 loss: 0.0564 (0.0631) time: 3.3680 data: 0.0076 max mem: 33370 +Epoch: [16] [1010/1319] eta: 0:17:22 lr: 3.066333298950271e-05 loss: 0.0590 (0.0631) time: 3.3562 data: 0.0077 max mem: 33370 +Epoch: [16] [1020/1319] eta: 0:16:48 lr: 3.065432745841652e-05 loss: 0.0590 (0.0631) time: 3.3385 data: 0.0078 max mem: 33370 +Epoch: [16] [1030/1319] eta: 0:16:15 lr: 3.064532163336335e-05 loss: 0.0641 (0.0635) time: 3.3647 data: 0.0078 max mem: 33370 +Epoch: [16] [1040/1319] eta: 0:15:41 lr: 3.063631551423762e-05 loss: 0.0647 (0.0634) time: 3.3944 data: 0.0076 max mem: 33370 +Epoch: [16] [1050/1319] eta: 0:15:07 lr: 3.062730910093366e-05 loss: 0.0434 (0.0633) time: 3.3869 data: 0.0075 max mem: 33370 +Epoch: [16] [1060/1319] eta: 0:14:34 lr: 3.061830239334574e-05 loss: 0.0432 (0.0633) time: 3.3943 data: 0.0076 max mem: 33370 +Epoch: [16] [1070/1319] eta: 0:14:00 lr: 3.0609295391368055e-05 loss: 0.0614 (0.0634) time: 3.3711 data: 0.0077 max mem: 33370 +Epoch: [16] [1080/1319] eta: 0:13:26 lr: 3.060028809489473e-05 loss: 0.0533 (0.0633) time: 3.3544 data: 0.0078 max mem: 33370 +Epoch: [16] [1090/1319] eta: 0:12:52 lr: 3.059128050381978e-05 loss: 0.0532 (0.0633) time: 3.3866 data: 0.0080 max mem: 33370 +Epoch: [16] [1100/1319] eta: 0:12:18 lr: 3.058227261803723e-05 loss: 0.0532 (0.0633) time: 3.3786 data: 0.0083 max mem: 33370 +Epoch: [16] [1110/1319] eta: 0:11:45 lr: 3.0573264437440946e-05 loss: 0.0649 (0.0633) time: 3.3521 data: 0.0083 max mem: 33370 +Epoch: [16] [1120/1319] eta: 0:11:11 lr: 3.056425596192476e-05 loss: 0.0619 (0.0632) time: 3.3642 data: 0.0079 max mem: 33370 +Epoch: [16] [1130/1319] eta: 0:10:37 lr: 3.0555247191382436e-05 loss: 0.0507 (0.0632) time: 3.3677 data: 0.0080 max mem: 33370 +Epoch: [16] [1140/1319] eta: 0:10:03 lr: 3.054623812570766e-05 loss: 0.0542 (0.0631) time: 3.3661 data: 0.0081 max mem: 33370 +Epoch: [16] [1150/1319] eta: 0:09:30 lr: 3.053722876479403e-05 loss: 0.0576 (0.0630) time: 3.3765 data: 0.0082 max mem: 33370 +Epoch: [16] [1160/1319] eta: 0:08:56 lr: 3.0528219108535084e-05 loss: 0.0576 (0.0630) time: 3.3926 data: 0.0084 max mem: 33370 +Epoch: [16] [1170/1319] eta: 0:08:22 lr: 3.0519209156824297e-05 loss: 0.0576 (0.0630) time: 3.3798 data: 0.0083 max mem: 33370 +Epoch: [16] [1180/1319] eta: 0:07:48 lr: 3.0510198909555044e-05 loss: 0.0592 (0.0631) time: 3.3581 data: 0.0081 max mem: 33370 +Epoch: [16] [1190/1319] eta: 0:07:15 lr: 3.0501188366620653e-05 loss: 0.0574 (0.0631) time: 3.3752 data: 0.0077 max mem: 33370 +Epoch: [16] [1200/1319] eta: 0:06:41 lr: 3.0492177527914355e-05 loss: 0.0556 (0.0631) time: 3.3762 data: 0.0076 max mem: 33370 +Epoch: [16] [1210/1319] eta: 0:06:07 lr: 3.0483166393329327e-05 loss: 0.0534 (0.0631) time: 3.3568 data: 0.0081 max mem: 33370 +Epoch: [16] [1220/1319] eta: 0:05:33 lr: 3.0474154962758662e-05 loss: 0.0530 (0.0631) time: 3.3480 data: 0.0080 max mem: 33370 +Epoch: [16] [1230/1319] eta: 0:05:00 lr: 3.0465143236095372e-05 loss: 0.0593 (0.0631) time: 3.3742 data: 0.0076 max mem: 33370 +Epoch: [16] [1240/1319] eta: 0:04:26 lr: 3.045613121323242e-05 loss: 0.0497 (0.0630) time: 3.3935 data: 0.0079 max mem: 33370 +Epoch: [16] [1250/1319] eta: 0:03:52 lr: 3.044711889406267e-05 loss: 0.0447 (0.0630) time: 3.3820 data: 0.0085 max mem: 33370 +Epoch: [16] [1260/1319] eta: 0:03:19 lr: 3.0438106278478923e-05 loss: 0.0550 (0.0630) time: 3.3538 data: 0.0083 max mem: 33370 +Epoch: [16] [1270/1319] eta: 0:02:45 lr: 3.0429093366373907e-05 loss: 0.0754 (0.0631) time: 3.3382 data: 0.0078 max mem: 33370 +Epoch: [16] [1280/1319] eta: 0:02:11 lr: 3.0420080157640274e-05 loss: 0.0643 (0.0631) time: 3.3555 data: 0.0078 max mem: 33370 +Epoch: [16] [1290/1319] eta: 0:01:37 lr: 3.0411066652170593e-05 loss: 0.0605 (0.0632) time: 3.3790 data: 0.0081 max mem: 33370 +Epoch: [16] [1300/1319] eta: 0:01:04 lr: 3.040205284985739e-05 loss: 0.0564 (0.0631) time: 3.3968 data: 0.0079 max mem: 33370 +Epoch: [16] [1310/1319] eta: 0:00:30 lr: 3.039303875059306e-05 loss: 0.0480 (0.0630) time: 3.3964 data: 0.0077 max mem: 33370 +Epoch: [16] Total time: 1:14:10 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 2:40:25 time: 3.7409 data: 3.6330 max mem: 33370 +Test: [ 100/2573] eta: 0:04:38 time: 0.0763 data: 0.0014 max mem: 33370 +Test: [ 200/2573] eta: 0:03:47 time: 0.0784 data: 0.0015 max mem: 33370 +Test: [ 300/2573] eta: 0:03:23 time: 0.0801 data: 0.0014 max mem: 33370 +Test: [ 400/2573] eta: 0:03:08 time: 0.0804 data: 0.0015 max mem: 33370 +Test: [ 500/2573] eta: 0:02:56 time: 0.0788 data: 0.0015 max mem: 33370 +Test: [ 600/2573] eta: 0:02:46 time: 0.0800 data: 0.0014 max mem: 33370 +Test: [ 700/2573] eta: 0:02:37 time: 0.0796 data: 0.0013 max mem: 33370 +Test: [ 800/2573] eta: 0:02:28 time: 0.0821 data: 0.0013 max mem: 33370 +Test: [ 900/2573] eta: 0:02:19 time: 0.0792 data: 0.0014 max mem: 33370 +Test: [1000/2573] eta: 0:02:10 time: 0.0799 data: 0.0014 max mem: 33370 +Test: [1100/2573] eta: 0:02:01 time: 0.0801 data: 0.0014 max mem: 33370 +Test: [1200/2573] eta: 0:01:53 time: 0.0805 data: 0.0015 max mem: 33370 +Test: [1300/2573] eta: 0:01:44 time: 0.0797 data: 0.0014 max mem: 33370 +Test: [1400/2573] eta: 0:01:36 time: 0.0788 data: 0.0015 max mem: 33370 +Test: [1500/2573] eta: 0:01:27 time: 0.0802 data: 0.0014 max mem: 33370 +Test: [1600/2573] eta: 0:01:19 time: 0.0833 data: 0.0015 max mem: 33370 +Test: [1700/2573] eta: 0:01:11 time: 0.0783 data: 0.0014 max mem: 33370 +Test: [1800/2573] eta: 0:01:03 time: 0.0816 data: 0.0014 max mem: 33370 +Test: [1900/2573] eta: 0:00:54 time: 0.0784 data: 0.0014 max mem: 33370 +Test: [2000/2573] eta: 0:00:46 time: 0.0790 data: 0.0015 max mem: 33370 +Test: [2100/2573] eta: 0:00:38 time: 0.0810 data: 0.0014 max mem: 33370 +Test: [2200/2573] eta: 0:00:30 time: 0.0812 data: 0.0013 max mem: 33370 +Test: [2300/2573] eta: 0:00:22 time: 0.0823 data: 0.0014 max mem: 33370 +Test: [2400/2573] eta: 0:00:14 time: 0.0771 data: 0.0014 max mem: 33370 +Test: [2500/2573] eta: 0:00:05 time: 0.0802 data: 0.0014 max mem: 33370 +Test: Total time: 0:03:28 +Final results: +Mean IoU is 62.31 + + precision@0.5 = 69.73 + precision@0.6 = 64.07 + precision@0.7 = 56.90 + precision@0.8 = 45.20 + precision@0.9 = 21.49 + overall IoU = 60.30 + +Average object IoU 62.31097473132278 +Overall IoU 60.30236053466797 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [17] [ 0/1319] eta: 3:16:43 lr: 3.0384925807273e-05 loss: 0.0495 (0.0495) time: 8.9489 data: 2.3822 max mem: 33370 +Epoch: [17] [ 10/1319] eta: 1:25:07 lr: 3.0375911143504937e-05 loss: 0.0506 (0.0539) time: 3.9015 data: 0.2236 max mem: 33370 +Epoch: [17] [ 20/1319] eta: 1:19:14 lr: 3.0366896182473385e-05 loss: 0.0533 (0.0575) time: 3.3954 data: 0.0077 max mem: 33370 +Epoch: [17] [ 30/1319] eta: 1:16:22 lr: 3.035788092407048e-05 loss: 0.0547 (0.0585) time: 3.3640 data: 0.0080 max mem: 33370 +Epoch: [17] [ 40/1319] eta: 1:14:48 lr: 3.034886536818829e-05 loss: 0.0487 (0.0599) time: 3.3520 data: 0.0079 max mem: 33370 +Epoch: [17] [ 50/1319] eta: 1:13:30 lr: 3.0339849514718806e-05 loss: 0.0453 (0.0578) time: 3.3525 data: 0.0079 max mem: 33370 +Epoch: [17] [ 60/1319] eta: 1:12:38 lr: 3.033083336355392e-05 loss: 0.0515 (0.0580) time: 3.3648 data: 0.0082 max mem: 33370 +Epoch: [17] [ 70/1319] eta: 1:11:50 lr: 3.03218169145855e-05 loss: 0.0515 (0.0570) time: 3.3878 data: 0.0077 max mem: 33370 +Epoch: [17] [ 80/1319] eta: 1:11:06 lr: 3.0312800167705292e-05 loss: 0.0618 (0.0590) time: 3.3876 data: 0.0077 max mem: 33370 +Epoch: [17] [ 90/1319] eta: 1:10:26 lr: 3.030378312280498e-05 loss: 0.0540 (0.0590) time: 3.3987 data: 0.0080 max mem: 33370 +Epoch: [17] [ 100/1319] eta: 1:09:48 lr: 3.0294765779776184e-05 loss: 0.0522 (0.0587) time: 3.4033 data: 0.0080 max mem: 33370 +Epoch: [17] [ 110/1319] eta: 1:09:02 lr: 3.0285748138510444e-05 loss: 0.0553 (0.0585) time: 3.3674 data: 0.0080 max mem: 33370 +Epoch: [17] [ 120/1319] eta: 1:08:20 lr: 3.0276730198899216e-05 loss: 0.0447 (0.0574) time: 3.3399 data: 0.0077 max mem: 33370 +Epoch: [17] [ 130/1319] eta: 1:07:39 lr: 3.0267711960833896e-05 loss: 0.0417 (0.0564) time: 3.3470 data: 0.0077 max mem: 33370 +Epoch: [17] [ 140/1319] eta: 1:07:01 lr: 3.0258693424205785e-05 loss: 0.0434 (0.0566) time: 3.3559 data: 0.0076 max mem: 33370 +Epoch: [17] [ 150/1319] eta: 1:06:24 lr: 3.024967458890613e-05 loss: 0.0482 (0.0568) time: 3.3715 data: 0.0074 max mem: 33370 +Epoch: [17] [ 160/1319] eta: 1:05:47 lr: 3.0240655454826085e-05 loss: 0.0497 (0.0575) time: 3.3711 data: 0.0079 max mem: 33370 +Epoch: [17] [ 170/1319] eta: 1:05:08 lr: 3.023163602185673e-05 loss: 0.0537 (0.0575) time: 3.3477 data: 0.0077 max mem: 33370 +Epoch: [17] [ 180/1319] eta: 1:04:29 lr: 3.022261628988908e-05 loss: 0.0553 (0.0579) time: 3.3255 data: 0.0076 max mem: 33370 +Epoch: [17] [ 190/1319] eta: 1:03:54 lr: 3.0213596258814065e-05 loss: 0.0563 (0.0594) time: 3.3541 data: 0.0077 max mem: 33370 +Epoch: [17] [ 200/1319] eta: 1:03:18 lr: 3.020457592852254e-05 loss: 0.0551 (0.0606) time: 3.3755 data: 0.0079 max mem: 33370 +Epoch: [17] [ 210/1319] eta: 1:02:43 lr: 3.0195555298905282e-05 loss: 0.0516 (0.0607) time: 3.3671 data: 0.0084 max mem: 33370 +Epoch: [17] [ 220/1319] eta: 1:02:06 lr: 3.0186534369853002e-05 loss: 0.0469 (0.0602) time: 3.3480 data: 0.0079 max mem: 33370 +Epoch: [17] [ 230/1319] eta: 1:01:31 lr: 3.0177513141256336e-05 loss: 0.0469 (0.0596) time: 3.3437 data: 0.0078 max mem: 33370 +Epoch: [17] [ 240/1319] eta: 1:00:57 lr: 3.0168491613005817e-05 loss: 0.0463 (0.0599) time: 3.3763 data: 0.0083 max mem: 33370 +Epoch: [17] [ 250/1319] eta: 1:00:22 lr: 3.0159469784991934e-05 loss: 0.0609 (0.0606) time: 3.3810 data: 0.0080 max mem: 33370 +Epoch: [17] [ 260/1319] eta: 0:59:49 lr: 3.0150447657105084e-05 loss: 0.0580 (0.0608) time: 3.3845 data: 0.0078 max mem: 33370 +Epoch: [17] [ 270/1319] eta: 0:59:14 lr: 3.0141425229235594e-05 loss: 0.0500 (0.0606) time: 3.3806 data: 0.0083 max mem: 33370 +Epoch: [17] [ 280/1319] eta: 0:58:38 lr: 3.01324025012737e-05 loss: 0.0476 (0.0601) time: 3.3510 data: 0.0083 max mem: 33370 +Epoch: [17] [ 290/1319] eta: 0:58:01 lr: 3.012337947310957e-05 loss: 0.0539 (0.0602) time: 3.3179 data: 0.0083 max mem: 33370 +Epoch: [17] [ 300/1319] eta: 0:57:25 lr: 3.0114356144633316e-05 loss: 0.0600 (0.0600) time: 3.3075 data: 0.0080 max mem: 33370 +Epoch: [17] [ 310/1319] eta: 0:56:50 lr: 3.010533251573493e-05 loss: 0.0546 (0.0598) time: 3.3323 data: 0.0078 max mem: 33370 +Epoch: [17] [ 320/1319] eta: 0:56:16 lr: 3.0096308586304355e-05 loss: 0.0501 (0.0596) time: 3.3631 data: 0.0080 max mem: 33370 +Epoch: [17] [ 330/1319] eta: 0:55:42 lr: 3.0087284356231465e-05 loss: 0.0508 (0.0594) time: 3.3670 data: 0.0078 max mem: 33370 +Epoch: [17] [ 340/1319] eta: 0:55:07 lr: 3.0078259825406035e-05 loss: 0.0585 (0.0595) time: 3.3602 data: 0.0078 max mem: 33370 +Epoch: [17] [ 350/1319] eta: 0:54:35 lr: 3.0069234993717783e-05 loss: 0.0504 (0.0592) time: 3.3887 data: 0.0076 max mem: 33370 +Epoch: [17] [ 360/1319] eta: 0:54:01 lr: 3.006020986105632e-05 loss: 0.0427 (0.0594) time: 3.4078 data: 0.0077 max mem: 33370 +Epoch: [17] [ 370/1319] eta: 0:53:28 lr: 3.005118442731122e-05 loss: 0.0582 (0.0595) time: 3.4017 data: 0.0078 max mem: 33370 +Epoch: [17] [ 380/1319] eta: 0:52:55 lr: 3.004215869237195e-05 loss: 0.0526 (0.0592) time: 3.4148 data: 0.0074 max mem: 33370 +Epoch: [17] [ 390/1319] eta: 0:52:22 lr: 3.0033132656127906e-05 loss: 0.0443 (0.0588) time: 3.4100 data: 0.0078 max mem: 33370 +Epoch: [17] [ 400/1319] eta: 0:51:47 lr: 3.002410631846841e-05 loss: 0.0453 (0.0589) time: 3.3633 data: 0.0079 max mem: 33370 +Epoch: [17] [ 410/1319] eta: 0:51:13 lr: 3.0015079679282703e-05 loss: 0.0568 (0.0591) time: 3.3501 data: 0.0074 max mem: 33370 +Epoch: [17] [ 420/1319] eta: 0:50:38 lr: 3.0006052738459948e-05 loss: 0.0562 (0.0589) time: 3.3570 data: 0.0074 max mem: 33370 +Epoch: [17] [ 430/1319] eta: 0:50:04 lr: 2.999702549588924e-05 loss: 0.0515 (0.0589) time: 3.3477 data: 0.0075 max mem: 33370 +Epoch: [17] [ 440/1319] eta: 0:49:30 lr: 2.998799795145959e-05 loss: 0.0503 (0.0589) time: 3.3734 data: 0.0077 max mem: 33370 +Epoch: [17] [ 450/1319] eta: 0:48:56 lr: 2.9978970105059916e-05 loss: 0.0450 (0.0586) time: 3.3735 data: 0.0079 max mem: 33370 +Epoch: [17] [ 460/1319] eta: 0:48:21 lr: 2.9969941956579083e-05 loss: 0.0450 (0.0584) time: 3.3338 data: 0.0079 max mem: 33370 +Epoch: [17] [ 470/1319] eta: 0:47:47 lr: 2.9960913505905863e-05 loss: 0.0580 (0.0586) time: 3.3484 data: 0.0077 max mem: 33370 +Epoch: [17] [ 480/1319] eta: 0:47:13 lr: 2.995188475292896e-05 loss: 0.0577 (0.0587) time: 3.3775 data: 0.0076 max mem: 33370 +Epoch: [17] [ 490/1319] eta: 0:46:40 lr: 2.9942855697536976e-05 loss: 0.0552 (0.0590) time: 3.3862 data: 0.0078 max mem: 33370 +Epoch: [17] [ 500/1319] eta: 0:46:06 lr: 2.9933826339618466e-05 loss: 0.0586 (0.0594) time: 3.3775 data: 0.0077 max mem: 33370 +Epoch: [17] [ 510/1319] eta: 0:45:32 lr: 2.992479667906189e-05 loss: 0.0583 (0.0593) time: 3.3547 data: 0.0079 max mem: 33370 +Epoch: [17] [ 520/1319] eta: 0:44:58 lr: 2.9915766715755623e-05 loss: 0.0543 (0.0595) time: 3.3594 data: 0.0081 max mem: 33370 +Epoch: [17] [ 530/1319] eta: 0:44:24 lr: 2.990673644958798e-05 loss: 0.0552 (0.0595) time: 3.3717 data: 0.0077 max mem: 33370 +Epoch: [17] [ 540/1319] eta: 0:43:50 lr: 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eta: 0:39:18 lr: 2.9825450406848343e-05 loss: 0.0627 (0.0602) time: 3.3642 data: 0.0076 max mem: 33370 +Epoch: [17] [ 630/1319] eta: 0:38:44 lr: 2.981641710590631e-05 loss: 0.0586 (0.0602) time: 3.3725 data: 0.0077 max mem: 33370 +Epoch: [17] [ 640/1319] eta: 0:38:10 lr: 2.9807383500869036e-05 loss: 0.0586 (0.0604) time: 3.3580 data: 0.0076 max mem: 33370 +Epoch: [17] [ 650/1319] eta: 0:37:36 lr: 2.9798349591623877e-05 loss: 0.0624 (0.0605) time: 3.3666 data: 0.0078 max mem: 33370 +Epoch: [17] [ 660/1319] eta: 0:37:03 lr: 2.9789315378058107e-05 loss: 0.0651 (0.0606) time: 3.3969 data: 0.0075 max mem: 33370 +Epoch: [17] [ 670/1319] eta: 0:36:29 lr: 2.978028086005893e-05 loss: 0.0563 (0.0606) time: 3.3833 data: 0.0074 max mem: 33370 +Epoch: [17] [ 680/1319] eta: 0:35:56 lr: 2.977124603751345e-05 loss: 0.0484 (0.0605) time: 3.3900 data: 0.0075 max mem: 33370 +Epoch: [17] [ 690/1319] eta: 0:35:22 lr: 2.9762210910308712e-05 loss: 0.0493 (0.0605) time: 3.4034 data: 0.0075 max mem: 33370 +Epoch: [17] [ 700/1319] eta: 0:34:48 lr: 2.9753175478331675e-05 loss: 0.0595 (0.0604) time: 3.3833 data: 0.0073 max mem: 33370 +Epoch: [17] [ 710/1319] eta: 0:34:14 lr: 2.97441397414692e-05 loss: 0.0546 (0.0603) time: 3.3633 data: 0.0075 max mem: 33370 +Epoch: [17] [ 720/1319] eta: 0:33:41 lr: 2.973510369960809e-05 loss: 0.0459 (0.0602) time: 3.3591 data: 0.0076 max mem: 33370 +Epoch: [17] [ 730/1319] eta: 0:33:07 lr: 2.9726067352635072e-05 loss: 0.0493 (0.0602) time: 3.3690 data: 0.0075 max mem: 33370 +Epoch: [17] [ 740/1319] eta: 0:32:33 lr: 2.971703070043676e-05 loss: 0.0565 (0.0602) time: 3.3692 data: 0.0078 max mem: 33370 +Epoch: [17] [ 750/1319] eta: 0:31:59 lr: 2.970799374289972e-05 loss: 0.0592 (0.0603) time: 3.3622 data: 0.0078 max mem: 33370 +Epoch: [17] [ 760/1319] eta: 0:31:26 lr: 2.9698956479910424e-05 loss: 0.0510 (0.0601) time: 3.3695 data: 0.0074 max mem: 33370 +Epoch: [17] [ 770/1319] eta: 0:30:52 lr: 2.9689918911355265e-05 loss: 0.0483 (0.0602) time: 3.3915 data: 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time: 3.4178 data: 0.0078 max mem: 33370 +Epoch: [17] [ 860/1319] eta: 0:25:50 lr: 2.96085670251099e-05 loss: 0.0547 (0.0600) time: 3.3750 data: 0.0082 max mem: 33370 +Epoch: [17] [ 870/1319] eta: 0:25:16 lr: 2.959952639462995e-05 loss: 0.0559 (0.0600) time: 3.4045 data: 0.0083 max mem: 33370 +Epoch: [17] [ 880/1319] eta: 0:24:42 lr: 2.9590485457329127e-05 loss: 0.0575 (0.0600) time: 3.4264 data: 0.0079 max mem: 33370 +Epoch: [17] [ 890/1319] eta: 0:24:09 lr: 2.9581444213092834e-05 loss: 0.0555 (0.0599) time: 3.4108 data: 0.0076 max mem: 33370 +Epoch: [17] [ 900/1319] eta: 0:23:35 lr: 2.957240266180642e-05 loss: 0.0522 (0.0600) time: 3.3908 data: 0.0078 max mem: 33370 +Epoch: [17] [ 910/1319] eta: 0:23:01 lr: 2.956336080335514e-05 loss: 0.0568 (0.0600) time: 3.3778 data: 0.0075 max mem: 33370 +Epoch: [17] [ 920/1319] eta: 0:22:27 lr: 2.955431863762416e-05 loss: 0.0568 (0.0600) time: 3.3832 data: 0.0078 max mem: 33370 +Epoch: [17] [ 930/1319] eta: 0:21:54 lr: 2.9545276164498587e-05 loss: 0.0549 (0.0600) time: 3.3887 data: 0.0083 max mem: 33370 +Epoch: [17] [ 940/1319] eta: 0:21:20 lr: 2.953623338386342e-05 loss: 0.0667 (0.0600) time: 3.3538 data: 0.0077 max mem: 33370 +Epoch: [17] [ 950/1319] eta: 0:20:46 lr: 2.9527190295603586e-05 loss: 0.0602 (0.0600) time: 3.3403 data: 0.0074 max mem: 33370 +Epoch: [17] [ 960/1319] eta: 0:20:12 lr: 2.9518146899603932e-05 loss: 0.0537 (0.0600) time: 3.3544 data: 0.0076 max mem: 33370 +Epoch: [17] [ 970/1319] eta: 0:19:38 lr: 2.9509103195749226e-05 loss: 0.0533 (0.0600) time: 3.3809 data: 0.0078 max mem: 33370 +Epoch: [17] [ 980/1319] eta: 0:19:05 lr: 2.9500059183924145e-05 loss: 0.0587 (0.0604) time: 3.3956 data: 0.0079 max mem: 33370 +Epoch: [17] [ 990/1319] eta: 0:18:31 lr: 2.9491014864013282e-05 loss: 0.0510 (0.0604) time: 3.3831 data: 0.0075 max mem: 33370 +Epoch: [17] [1000/1319] eta: 0:17:57 lr: 2.9481970235901164e-05 loss: 0.0501 (0.0604) time: 3.3765 data: 0.0073 max mem: 33370 +Epoch: [17] [1010/1319] eta: 0:17:23 lr: 2.9472925299472214e-05 loss: 0.0514 (0.0604) time: 3.3618 data: 0.0075 max mem: 33370 +Epoch: [17] [1020/1319] eta: 0:16:49 lr: 2.9463880054610792e-05 loss: 0.0507 (0.0604) time: 3.3769 data: 0.0081 max mem: 33370 +Epoch: [17] [1030/1319] eta: 0:16:16 lr: 2.9454834501201163e-05 loss: 0.0637 (0.0605) time: 3.3802 data: 0.0082 max mem: 33370 +Epoch: [17] [1040/1319] eta: 0:15:42 lr: 2.9445788639127496e-05 loss: 0.0561 (0.0604) time: 3.3816 data: 0.0079 max mem: 33370 +Epoch: [17] [1050/1319] eta: 0:15:08 lr: 2.943674246827392e-05 loss: 0.0512 (0.0604) time: 3.3916 data: 0.0079 max mem: 33370 +Epoch: [17] [1060/1319] eta: 0:14:34 lr: 2.9427695988524433e-05 loss: 0.0503 (0.0603) time: 3.3659 data: 0.0075 max mem: 33370 +Epoch: [17] [1070/1319] eta: 0:14:00 lr: 2.941864919976297e-05 loss: 0.0553 (0.0604) time: 3.3459 data: 0.0074 max mem: 33370 +Epoch: [17] [1080/1319] eta: 0:13:27 lr: 2.9409602101873397e-05 loss: 0.0553 (0.0604) time: 3.3594 data: 0.0082 max mem: 33370 +Epoch: [17] [1090/1319] eta: 0:12:53 lr: 2.9400554694739468e-05 loss: 0.0549 (0.0605) time: 3.3799 data: 0.0086 max mem: 33370 +Epoch: [17] [1100/1319] eta: 0:12:19 lr: 2.9391506978244877e-05 loss: 0.0494 (0.0604) time: 3.3765 data: 0.0082 max mem: 33370 +Epoch: [17] [1110/1319] eta: 0:11:45 lr: 2.9382458952273217e-05 loss: 0.0536 (0.0604) time: 3.3430 data: 0.0079 max mem: 33370 +Epoch: [17] [1120/1319] eta: 0:11:11 lr: 2.937341061670802e-05 loss: 0.0578 (0.0604) time: 3.3501 data: 0.0075 max mem: 33370 +Epoch: [17] [1130/1319] eta: 0:10:38 lr: 2.9364361971432715e-05 loss: 0.0602 (0.0604) time: 3.3969 data: 0.0075 max mem: 33370 +Epoch: [17] [1140/1319] eta: 0:10:04 lr: 2.9355313016330638e-05 loss: 0.0578 (0.0605) time: 3.3817 data: 0.0078 max mem: 33370 +Epoch: [17] [1150/1319] eta: 0:09:30 lr: 2.934626375128508e-05 loss: 0.0606 (0.0605) time: 3.3724 data: 0.0076 max mem: 33370 +Epoch: [17] [1160/1319] eta: 0:08:56 lr: 2.93372141761792e-05 loss: 0.0572 (0.0605) time: 3.3652 data: 0.0077 max mem: 33370 +Epoch: [17] [1170/1319] eta: 0:08:23 lr: 2.9328164290896108e-05 loss: 0.0532 (0.0605) time: 3.3445 data: 0.0082 max mem: 33370 +Epoch: [17] [1180/1319] eta: 0:07:49 lr: 2.9319114095318817e-05 loss: 0.0543 (0.0605) time: 3.3518 data: 0.0080 max mem: 33370 +Epoch: [17] [1190/1319] eta: 0:07:15 lr: 2.9310063589330256e-05 loss: 0.0506 (0.0605) time: 3.3794 data: 0.0076 max mem: 33370 +Epoch: [17] [1200/1319] eta: 0:06:41 lr: 2.9301012772813273e-05 loss: 0.0520 (0.0605) time: 3.3795 data: 0.0076 max mem: 33370 +Epoch: [17] [1210/1319] eta: 0:06:08 lr: 2.9291961645650624e-05 loss: 0.0584 (0.0605) time: 3.3758 data: 0.0081 max mem: 33370 +Epoch: [17] [1220/1319] eta: 0:05:34 lr: 2.9282910207724996e-05 loss: 0.0541 (0.0605) time: 3.3762 data: 0.0082 max mem: 33370 +Epoch: [17] [1230/1319] eta: 0:05:00 lr: 2.9273858458918974e-05 loss: 0.0511 (0.0605) time: 3.3528 data: 0.0081 max mem: 33370 +Epoch: [17] [1240/1319] eta: 0:04:26 lr: 2.9264806399115058e-05 loss: 0.0511 (0.0604) time: 3.3730 data: 0.0081 max mem: 33370 +Epoch: [17] [1250/1319] eta: 0:03:52 lr: 2.925575402819568e-05 loss: 0.0450 (0.0603) time: 3.3953 data: 0.0080 max mem: 33370 +Epoch: [17] [1260/1319] eta: 0:03:19 lr: 2.9246701346043183e-05 loss: 0.0471 (0.0603) time: 3.3702 data: 0.0080 max mem: 33370 +Epoch: [17] [1270/1319] eta: 0:02:45 lr: 2.9237648352539803e-05 loss: 0.0579 (0.0603) time: 3.3459 data: 0.0078 max mem: 33370 +Epoch: [17] [1280/1319] eta: 0:02:11 lr: 2.9228595047567713e-05 loss: 0.0621 (0.0603) time: 3.3745 data: 0.0076 max mem: 33370 +Epoch: [17] [1290/1319] eta: 0:01:37 lr: 2.9219541431009008e-05 loss: 0.0567 (0.0603) time: 3.3754 data: 0.0075 max mem: 33370 +Epoch: [17] [1300/1319] eta: 0:01:04 lr: 2.921048750274567e-05 loss: 0.0530 (0.0603) time: 3.3738 data: 0.0074 max mem: 33370 +Epoch: [17] [1310/1319] eta: 0:00:30 lr: 2.9201433262659623e-05 loss: 0.0497 (0.0603) time: 3.3569 data: 0.0072 max mem: 33370 +Epoch: [17] Total time: 1:14:12 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 2:52:30 time: 4.0229 data: 3.9321 max mem: 33370 +Test: [ 100/2573] eta: 0:04:46 time: 0.0766 data: 0.0015 max mem: 33370 +Test: [ 200/2573] eta: 0:03:50 time: 0.0780 data: 0.0014 max mem: 33370 +Test: [ 300/2573] eta: 0:03:25 time: 0.0800 data: 0.0014 max mem: 33370 +Test: [ 400/2573] eta: 0:03:09 time: 0.0797 data: 0.0013 max mem: 33370 +Test: [ 500/2573] eta: 0:02:57 time: 0.0788 data: 0.0014 max mem: 33370 +Test: [ 600/2573] eta: 0:02:46 time: 0.0782 data: 0.0013 max mem: 33370 +Test: [ 700/2573] eta: 0:02:37 time: 0.0788 data: 0.0013 max mem: 33370 +Test: [ 800/2573] eta: 0:02:28 time: 0.0820 data: 0.0013 max mem: 33370 +Test: [ 900/2573] eta: 0:02:19 time: 0.0799 data: 0.0013 max mem: 33370 +Test: [1000/2573] eta: 0:02:10 time: 0.0792 data: 0.0014 max mem: 33370 +Test: [1100/2573] eta: 0:02:01 time: 0.0800 data: 0.0015 max mem: 33370 +Test: [1200/2573] eta: 0:01:53 time: 0.0799 data: 0.0015 max mem: 33370 +Test: [1300/2573] eta: 0:01:44 time: 0.0792 data: 0.0014 max mem: 33370 +Test: [1400/2573] eta: 0:01:36 time: 0.0779 data: 0.0014 max mem: 33370 +Test: [1500/2573] eta: 0:01:27 time: 0.0795 data: 0.0013 max mem: 33370 +Test: [1600/2573] eta: 0:01:19 time: 0.0824 data: 0.0014 max mem: 33370 +Test: [1700/2573] eta: 0:01:11 time: 0.0794 data: 0.0013 max mem: 33370 +Test: [1800/2573] eta: 0:01:02 time: 0.0810 data: 0.0015 max mem: 33370 +Test: [1900/2573] eta: 0:00:54 time: 0.0777 data: 0.0014 max mem: 33370 +Test: [2000/2573] eta: 0:00:46 time: 0.0801 data: 0.0015 max mem: 33370 +Test: [2100/2573] eta: 0:00:38 time: 0.0805 data: 0.0014 max mem: 33370 +Test: [2200/2573] eta: 0:00:30 time: 0.0808 data: 0.0013 max mem: 33370 +Test: [2300/2573] eta: 0:00:22 time: 0.0828 data: 0.0015 max mem: 33370 +Test: [2400/2573] eta: 0:00:13 time: 0.0767 data: 0.0014 max mem: 33370 +Test: [2500/2573] eta: 0:00:05 time: 0.0798 data: 0.0014 max mem: 33370 +Test: Total time: 0:03:28 +Final results: +Mean IoU is 62.86 + + precision@0.5 = 70.42 + precision@0.6 = 64.75 + precision@0.7 = 57.37 + precision@0.8 = 45.67 + precision@0.9 = 22.10 + overall IoU = 60.17 + +Average object IoU 62.8627127785078 +Overall IoU 60.170894622802734 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [18] [ 0/1319] eta: 3:15:50 lr: 2.9193284179876086e-05 loss: 0.0367 (0.0367) time: 8.9089 data: 2.4271 max mem: 33370 +Epoch: [18] [ 10/1319] eta: 1:26:02 lr: 2.9184229347001237e-05 loss: 0.0484 (0.0490) time: 3.9435 data: 0.2280 max mem: 33370 +Epoch: [18] [ 20/1319] eta: 1:19:30 lr: 2.9175174201960736e-05 loss: 0.0513 (0.0612) time: 3.4107 data: 0.0078 max mem: 33370 +Epoch: [18] [ 30/1319] eta: 1:16:54 lr: 2.9166118744636155e-05 loss: 0.0555 (0.0625) time: 3.3796 data: 0.0078 max mem: 33370 +Epoch: [18] [ 40/1319] eta: 1:15:10 lr: 2.9157062974908988e-05 loss: 0.0516 (0.0618) time: 3.3733 data: 0.0080 max mem: 33370 +Epoch: [18] [ 50/1319] eta: 1:13:53 lr: 2.9148006892660646e-05 loss: 0.0451 (0.0601) time: 3.3609 data: 0.0080 max mem: 33370 +Epoch: [18] [ 60/1319] eta: 1:12:53 lr: 2.9138950497772444e-05 loss: 0.0439 (0.0602) time: 3.3654 data: 0.0080 max mem: 33370 +Epoch: [18] [ 70/1319] eta: 1:11:58 lr: 2.9129893790125616e-05 loss: 0.0405 (0.0583) time: 3.3650 data: 0.0081 max mem: 33370 +Epoch: [18] [ 80/1319] eta: 1:11:13 lr: 2.9120836769601318e-05 loss: 0.0495 (0.0582) time: 3.3737 data: 0.0082 max mem: 33370 +Epoch: [18] [ 90/1319] eta: 1:10:29 lr: 2.9111779436080605e-05 loss: 0.0495 (0.0583) time: 3.3854 data: 0.0080 max mem: 33370 +Epoch: [18] [ 100/1319] eta: 1:09:47 lr: 2.910272178944446e-05 loss: 0.0419 (0.0579) time: 3.3794 data: 0.0079 max mem: 33370 +Epoch: [18] [ 110/1319] eta: 1:09:07 lr: 2.9093663829573763e-05 loss: 0.0491 (0.0580) time: 3.3775 data: 0.0079 max mem: 33370 +Epoch: [18] [ 120/1319] eta: 1:08:30 lr: 2.9084605556349322e-05 loss: 0.0461 (0.0575) time: 3.3935 data: 0.0079 max mem: 33370 +Epoch: [18] [ 130/1319] eta: 1:07:52 lr: 2.9075546969651845e-05 loss: 0.0454 (0.0573) time: 3.3989 data: 0.0083 max mem: 33370 +Epoch: [18] [ 140/1319] eta: 1:07:16 lr: 2.906648806936197e-05 loss: 0.0620 (0.0577) time: 3.3934 data: 0.0086 max mem: 33370 +Epoch: [18] [ 150/1319] eta: 1:06:35 lr: 2.9057428855360237e-05 loss: 0.0521 (0.0573) time: 3.3705 data: 0.0081 max mem: 33370 +Epoch: [18] [ 160/1319] eta: 1:05:58 lr: 2.9048369327527098e-05 loss: 0.0521 (0.0571) time: 3.3572 data: 0.0077 max mem: 33370 +Epoch: [18] [ 170/1319] eta: 1:05:20 lr: 2.903930948574293e-05 loss: 0.0498 (0.0570) time: 3.3668 data: 0.0075 max mem: 33370 +Epoch: [18] [ 180/1319] eta: 1:04:44 lr: 2.9030249329888e-05 loss: 0.0489 (0.0567) time: 3.3698 data: 0.0077 max mem: 33370 +Epoch: [18] [ 190/1319] eta: 1:04:07 lr: 2.9021188859842518e-05 loss: 0.0460 (0.0561) time: 3.3700 data: 0.0083 max mem: 33370 +Epoch: [18] [ 200/1319] eta: 1:03:32 lr: 2.9012128075486583e-05 loss: 0.0450 (0.0568) time: 3.3758 data: 0.0083 max mem: 33370 +Epoch: [18] [ 210/1319] eta: 1:02:56 lr: 2.900306697670022e-05 loss: 0.0547 (0.0572) time: 3.3797 data: 0.0080 max mem: 33370 +Epoch: [18] [ 220/1319] eta: 1:02:19 lr: 2.8994005563363352e-05 loss: 0.0648 (0.0574) time: 3.3633 data: 0.0080 max mem: 33370 +Epoch: [18] [ 230/1319] eta: 1:01:44 lr: 2.8984943835355838e-05 loss: 0.0594 (0.0572) time: 3.3648 data: 0.0076 max mem: 33370 +Epoch: [18] [ 240/1319] eta: 1:01:06 lr: 2.8975881792557412e-05 loss: 0.0476 (0.0576) time: 3.3434 data: 0.0076 max mem: 33370 +Epoch: [18] [ 250/1319] eta: 1:00:30 lr: 2.8966819434847762e-05 loss: 0.0560 (0.0573) time: 3.3294 data: 0.0085 max mem: 33370 +Epoch: [18] [ 260/1319] eta: 0:59:55 lr: 2.8957756762106468e-05 loss: 0.0560 (0.0573) time: 3.3596 data: 0.0081 max mem: 33370 +Epoch: [18] [ 270/1319] eta: 0:59:19 lr: 2.8948693774213014e-05 loss: 0.0499 (0.0570) time: 3.3560 data: 0.0081 max mem: 33370 +Epoch: [18] [ 280/1319] eta: 0:58:44 lr: 2.8939630471046815e-05 loss: 0.0520 (0.0573) time: 3.3548 data: 0.0086 max mem: 33370 +Epoch: [18] [ 290/1319] eta: 0:58:08 lr: 2.893056685248718e-05 loss: 0.0614 (0.0576) time: 3.3523 data: 0.0081 max mem: 33370 +Epoch: [18] [ 300/1319] eta: 0:57:33 lr: 2.892150291841334e-05 loss: 0.0524 (0.0573) time: 3.3533 data: 0.0082 max mem: 33370 +Epoch: [18] [ 310/1319] eta: 0:56:58 lr: 2.891243866870445e-05 loss: 0.0467 (0.0571) time: 3.3584 data: 0.0084 max mem: 33370 +Epoch: [18] [ 320/1319] eta: 0:56:24 lr: 2.8903374103239537e-05 loss: 0.0479 (0.0572) time: 3.3679 data: 0.0081 max mem: 33370 +Epoch: [18] [ 330/1319] eta: 0:55:49 lr: 2.889430922189758e-05 loss: 0.0511 (0.0571) time: 3.3738 data: 0.0081 max mem: 33370 +Epoch: [18] [ 340/1319] eta: 0:55:15 lr: 2.8885244024557463e-05 loss: 0.0511 (0.0570) time: 3.3665 data: 0.0080 max mem: 33370 +Epoch: [18] [ 350/1319] eta: 0:54:41 lr: 2.8876178511097952e-05 loss: 0.0512 (0.0574) time: 3.3738 data: 0.0078 max mem: 33370 +Epoch: [18] [ 360/1319] eta: 0:54:07 lr: 2.886711268139775e-05 loss: 0.0494 (0.0570) time: 3.3737 data: 0.0081 max mem: 33370 +Epoch: [18] [ 370/1319] eta: 0:53:32 lr: 2.8858046535335475e-05 loss: 0.0492 (0.0570) time: 3.3689 data: 0.0080 max mem: 33370 +Epoch: [18] [ 380/1319] eta: 0:52:57 lr: 2.8848980072789644e-05 loss: 0.0504 (0.0570) time: 3.3517 data: 0.0079 max mem: 33370 +Epoch: [18] [ 390/1319] eta: 0:52:24 lr: 2.8839913293638683e-05 loss: 0.0526 (0.0569) time: 3.3644 data: 0.0078 max mem: 33370 +Epoch: [18] [ 400/1319] eta: 0:51:49 lr: 2.8830846197760937e-05 loss: 0.0584 (0.0571) time: 3.3766 data: 0.0079 max mem: 33370 +Epoch: [18] [ 410/1319] eta: 0:51:16 lr: 2.8821778785034654e-05 loss: 0.0651 (0.0573) time: 3.3826 data: 0.0083 max mem: 33370 +Epoch: [18] [ 420/1319] eta: 0:50:42 lr: 2.8812711055338004e-05 loss: 0.0513 (0.0571) time: 3.3928 data: 0.0082 max mem: 33370 +Epoch: [18] [ 430/1319] eta: 0:50:08 lr: 2.8803643008549054e-05 loss: 0.0513 (0.0570) time: 3.3721 data: 0.0080 max mem: 33370 +Epoch: [18] [ 440/1319] eta: 0:49:34 lr: 2.879457464454579e-05 loss: 0.0503 (0.0570) time: 3.3805 data: 0.0080 max mem: 33370 +Epoch: [18] [ 450/1319] eta: 0:49:00 lr: 2.8785505963206112e-05 loss: 0.0498 (0.0570) time: 3.3945 data: 0.0080 max mem: 33370 +Epoch: [18] [ 460/1319] eta: 0:48:25 lr: 2.877643696440781e-05 loss: 0.0498 (0.0570) time: 3.3552 data: 0.0080 max mem: 33370 +Epoch: [18] [ 470/1319] eta: 0:47:52 lr: 2.876736764802861e-05 loss: 0.0470 (0.0568) time: 3.3625 data: 0.0076 max mem: 33370 +Epoch: [18] [ 480/1319] eta: 0:47:17 lr: 2.8758298013946133e-05 loss: 0.0442 (0.0566) time: 3.3687 data: 0.0074 max mem: 33370 +Epoch: [18] [ 490/1319] eta: 0:46:42 lr: 2.8749228062037915e-05 loss: 0.0483 (0.0567) time: 3.3304 data: 0.0078 max mem: 33370 +Epoch: [18] [ 500/1319] eta: 0:46:08 lr: 2.87401577921814e-05 loss: 0.0600 (0.0568) time: 3.3407 data: 0.0077 max mem: 33370 +Epoch: [18] [ 510/1319] eta: 0:45:34 lr: 2.8731087204253943e-05 loss: 0.0542 (0.0566) time: 3.3593 data: 0.0077 max mem: 33370 +Epoch: [18] [ 520/1319] eta: 0:45:00 lr: 2.8722016298132803e-05 loss: 0.0513 (0.0566) time: 3.3545 data: 0.0079 max mem: 33370 +Epoch: [18] [ 530/1319] eta: 0:44:25 lr: 2.8712945073695164e-05 loss: 0.0608 (0.0568) time: 3.3386 data: 0.0078 max mem: 33370 +Epoch: [18] [ 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(0.0566) time: 3.3412 data: 0.0074 max mem: 33370 +Epoch: [18] [ 780/1319] eta: 0:30:19 lr: 2.8486060648757875e-05 loss: 0.0476 (0.0565) time: 3.3426 data: 0.0078 max mem: 33370 +Epoch: [18] [ 790/1319] eta: 0:29:46 lr: 2.8476981104680245e-05 loss: 0.0500 (0.0565) time: 3.3927 data: 0.0082 max mem: 33370 +Epoch: [18] [ 800/1319] eta: 0:29:12 lr: 2.846790123893523e-05 loss: 0.0524 (0.0565) time: 3.3869 data: 0.0078 max mem: 33370 +Epoch: [18] [ 810/1319] eta: 0:28:38 lr: 2.8458821051397444e-05 loss: 0.0628 (0.0567) time: 3.3499 data: 0.0076 max mem: 33370 +Epoch: [18] [ 820/1319] eta: 0:28:04 lr: 2.844974054194138e-05 loss: 0.0628 (0.0568) time: 3.3810 data: 0.0078 max mem: 33370 +Epoch: [18] [ 830/1319] eta: 0:27:30 lr: 2.844065971044146e-05 loss: 0.0495 (0.0568) time: 3.3731 data: 0.0080 max mem: 33370 +Epoch: [18] [ 840/1319] eta: 0:26:57 lr: 2.8431578556772e-05 loss: 0.0673 (0.0572) time: 3.3869 data: 0.0079 max mem: 33370 +Epoch: [18] [ 850/1319] eta: 0:26:23 lr: 2.8422497080807237e-05 loss: 0.0537 (0.0571) time: 3.3989 data: 0.0082 max mem: 33370 +Epoch: [18] [ 860/1319] eta: 0:25:49 lr: 2.8413415282421285e-05 loss: 0.0529 (0.0573) time: 3.3641 data: 0.0081 max mem: 33370 +Epoch: [18] [ 870/1319] eta: 0:25:16 lr: 2.840433316148819e-05 loss: 0.0529 (0.0572) time: 3.3735 data: 0.0074 max mem: 33370 +Epoch: [18] [ 880/1319] eta: 0:24:42 lr: 2.8395250717881906e-05 loss: 0.0499 (0.0572) time: 3.3889 data: 0.0080 max mem: 33370 +Epoch: [18] [ 890/1319] eta: 0:24:08 lr: 2.8386167951476273e-05 loss: 0.0572 (0.0573) time: 3.3677 data: 0.0082 max mem: 33370 +Epoch: [18] [ 900/1319] eta: 0:23:34 lr: 2.8377084862145048e-05 loss: 0.0531 (0.0573) time: 3.3485 data: 0.0079 max mem: 33370 +Epoch: [18] [ 910/1319] eta: 0:23:00 lr: 2.8368001449761894e-05 loss: 0.0487 (0.0573) time: 3.3608 data: 0.0082 max mem: 33370 +Epoch: [18] [ 920/1319] eta: 0:22:27 lr: 2.8358917714200377e-05 loss: 0.0477 (0.0572) time: 3.3690 data: 0.0079 max mem: 33370 +Epoch: [18] [ 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33370 +Epoch: [18] [1010/1319] eta: 0:17:22 lr: 2.8277149530212353e-05 loss: 0.0576 (0.0575) time: 3.3956 data: 0.0079 max mem: 33370 +Epoch: [18] [1020/1319] eta: 0:16:48 lr: 2.8268062555892616e-05 loss: 0.0541 (0.0575) time: 3.3981 data: 0.0077 max mem: 33370 +Epoch: [18] [1030/1319] eta: 0:16:15 lr: 2.82589752569975e-05 loss: 0.0490 (0.0574) time: 3.3532 data: 0.0079 max mem: 33370 +Epoch: [18] [1040/1319] eta: 0:15:41 lr: 2.8249887633399437e-05 loss: 0.0455 (0.0574) time: 3.3622 data: 0.0079 max mem: 33370 +Epoch: [18] [1050/1319] eta: 0:15:07 lr: 2.8240799684970753e-05 loss: 0.0454 (0.0573) time: 3.3705 data: 0.0082 max mem: 33370 +Epoch: [18] [1060/1319] eta: 0:14:33 lr: 2.8231711411583693e-05 loss: 0.0501 (0.0573) time: 3.3837 data: 0.0082 max mem: 33370 +Epoch: [18] [1070/1319] eta: 0:14:00 lr: 2.8222622813110382e-05 loss: 0.0501 (0.0572) time: 3.3821 data: 0.0079 max mem: 33370 +Epoch: [18] [1080/1319] eta: 0:13:26 lr: 2.821353388942287e-05 loss: 0.0471 (0.0572) time: 3.3831 data: 0.0079 max mem: 33370 +Epoch: [18] [1090/1319] eta: 0:12:52 lr: 2.820444464039311e-05 loss: 0.0469 (0.0571) time: 3.3726 data: 0.0080 max mem: 33370 +Epoch: [18] [1100/1319] eta: 0:12:18 lr: 2.819535506589294e-05 loss: 0.0510 (0.0572) time: 3.3401 data: 0.0076 max mem: 33370 +Epoch: [18] [1110/1319] eta: 0:11:45 lr: 2.8186265165794125e-05 loss: 0.0448 (0.0571) time: 3.3309 data: 0.0075 max mem: 33370 +Epoch: [18] [1120/1319] eta: 0:11:11 lr: 2.817717493996831e-05 loss: 0.0444 (0.0571) time: 3.3707 data: 0.0078 max mem: 33370 +Epoch: [18] [1130/1319] eta: 0:10:37 lr: 2.816808438828707e-05 loss: 0.0479 (0.0572) time: 3.3827 data: 0.0078 max mem: 33370 +Epoch: [18] [1140/1319] eta: 0:10:03 lr: 2.8158993510621856e-05 loss: 0.0444 (0.0571) time: 3.3583 data: 0.0076 max mem: 33370 +Epoch: [18] [1150/1319] eta: 0:09:30 lr: 2.814990230684405e-05 loss: 0.0460 (0.0571) time: 3.3722 data: 0.0075 max mem: 33370 +Epoch: [18] [1160/1319] eta: 0:08:56 lr: 2.814081077682491e-05 loss: 0.0513 (0.0571) time: 3.3771 data: 0.0073 max mem: 33370 +Epoch: [18] [1170/1319] eta: 0:08:22 lr: 2.8131718920435623e-05 loss: 0.0578 (0.0572) time: 3.3538 data: 0.0078 max mem: 33370 +Epoch: [18] [1180/1319] eta: 0:07:48 lr: 2.812262673754726e-05 loss: 0.0503 (0.0572) time: 3.3499 data: 0.0080 max mem: 33370 +Epoch: [18] [1190/1319] eta: 0:07:15 lr: 2.8113534228030784e-05 loss: 0.0486 (0.0571) time: 3.3346 data: 0.0078 max mem: 33370 +Epoch: [18] [1200/1319] eta: 0:06:41 lr: 2.8104441391757102e-05 loss: 0.0499 (0.0571) time: 3.3373 data: 0.0082 max mem: 33370 +Epoch: [18] [1210/1319] eta: 0:06:07 lr: 2.809534822859698e-05 loss: 0.0612 (0.0571) time: 3.3849 data: 0.0078 max mem: 33370 +Epoch: [18] [1220/1319] eta: 0:05:33 lr: 2.8086254738421114e-05 loss: 0.0557 (0.0571) time: 3.3904 data: 0.0077 max mem: 33370 +Epoch: [18] [1230/1319] eta: 0:05:00 lr: 2.8077160921100087e-05 loss: 0.0484 (0.0571) time: 3.3712 data: 0.0079 max mem: 33370 +Epoch: [18] [1240/1319] eta: 0:04:26 lr: 2.8068066776504393e-05 loss: 0.0493 (0.0570) time: 3.3566 data: 0.0077 max mem: 33370 +Epoch: [18] [1250/1319] eta: 0:03:52 lr: 2.8058972304504428e-05 loss: 0.0493 (0.0570) time: 3.3639 data: 0.0075 max mem: 33370 +Epoch: [18] [1260/1319] eta: 0:03:18 lr: 2.8049877504970483e-05 loss: 0.0539 (0.0572) time: 3.3666 data: 0.0073 max mem: 33370 +Epoch: [18] [1270/1319] eta: 0:02:45 lr: 2.8040782377772763e-05 loss: 0.0560 (0.0572) time: 3.3435 data: 0.0074 max mem: 33370 +Epoch: [18] [1280/1319] eta: 0:02:11 lr: 2.803168692278136e-05 loss: 0.0507 (0.0571) time: 3.3544 data: 0.0076 max mem: 33370 +Epoch: [18] [1290/1319] eta: 0:01:37 lr: 2.8022591139866265e-05 loss: 0.0507 (0.0572) time: 3.3823 data: 0.0078 max mem: 33370 +Epoch: [18] [1300/1319] eta: 0:01:04 lr: 2.80134950288974e-05 loss: 0.0470 (0.0571) time: 3.3838 data: 0.0078 max mem: 33370 +Epoch: [18] [1310/1319] eta: 0:00:30 lr: 2.800439858974456e-05 loss: 0.0579 (0.0572) time: 3.3449 data: 0.0076 max mem: 33370 +Epoch: [18] Total time: 1:14:08 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 2:49:43 time: 3.9580 data: 3.8697 max mem: 33370 +Test: [ 100/2573] eta: 0:04:44 time: 0.0763 data: 0.0014 max mem: 33370 +Test: [ 200/2573] eta: 0:03:49 time: 0.0780 data: 0.0013 max mem: 33370 +Test: [ 300/2573] eta: 0:03:24 time: 0.0795 data: 0.0013 max mem: 33370 +Test: [ 400/2573] eta: 0:03:08 time: 0.0791 data: 0.0013 max mem: 33370 +Test: [ 500/2573] eta: 0:02:56 time: 0.0784 data: 0.0014 max mem: 33370 +Test: [ 600/2573] eta: 0:02:45 time: 0.0780 data: 0.0014 max mem: 33370 +Test: [ 700/2573] eta: 0:02:36 time: 0.0783 data: 0.0013 max mem: 33370 +Test: [ 800/2573] eta: 0:02:27 time: 0.0820 data: 0.0013 max mem: 33370 +Test: [ 900/2573] eta: 0:02:18 time: 0.0793 data: 0.0014 max mem: 33370 +Test: [1000/2573] eta: 0:02:09 time: 0.0797 data: 0.0014 max mem: 33370 +Test: [1100/2573] eta: 0:02:01 time: 0.0797 data: 0.0014 max mem: 33370 +Test: [1200/2573] eta: 0:01:52 time: 0.0786 data: 0.0013 max mem: 33370 +Test: [1300/2573] eta: 0:01:44 time: 0.0793 data: 0.0013 max mem: 33370 +Test: [1400/2573] eta: 0:01:35 time: 0.0781 data: 0.0015 max mem: 33370 +Test: [1500/2573] eta: 0:01:27 time: 0.0796 data: 0.0015 max mem: 33370 +Test: [1600/2573] eta: 0:01:19 time: 0.0827 data: 0.0014 max mem: 33370 +Test: [1700/2573] eta: 0:01:10 time: 0.0791 data: 0.0014 max mem: 33370 +Test: [1800/2573] eta: 0:01:02 time: 0.0813 data: 0.0014 max mem: 33370 +Test: [1900/2573] eta: 0:00:54 time: 0.0781 data: 0.0014 max mem: 33370 +Test: [2000/2573] eta: 0:00:46 time: 0.0795 data: 0.0015 max mem: 33370 +Test: [2100/2573] eta: 0:00:38 time: 0.0807 data: 0.0014 max mem: 33370 +Test: [2200/2573] eta: 0:00:30 time: 0.0813 data: 0.0014 max mem: 33370 +Test: [2300/2573] eta: 0:00:22 time: 0.0811 data: 0.0013 max mem: 33370 +Test: [2400/2573] eta: 0:00:13 time: 0.0754 data: 0.0013 max mem: 33370 +Test: [2500/2573] eta: 0:00:05 time: 0.0790 data: 0.0014 max mem: 33370 +Test: Total time: 0:03:27 +Final results: +Mean IoU is 62.96 + + precision@0.5 = 70.49 + precision@0.6 = 64.34 + precision@0.7 = 57.23 + precision@0.8 = 45.83 + precision@0.9 = 22.39 + overall IoU = 60.68 + +Average object IoU 62.95508892633676 +Overall IoU 60.684532165527344 +Better epoch: 18 + +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [19] [ 0/1319] eta: 1:55:20 lr: 2.7996211513802005e-05 loss: 0.0458 (0.0458) time: 5.2469 data: 1.7288 max mem: 33370 +Epoch: [19] [ 10/1319] eta: 1:17:59 lr: 2.7987114450740563e-05 loss: 0.0488 (0.0587) time: 3.5752 data: 0.1644 max mem: 33370 +Epoch: [19] [ 20/1319] eta: 1:16:12 lr: 2.7978017059117013e-05 loss: 0.0471 (0.0539) time: 3.4340 data: 0.0084 max mem: 33370 +Epoch: [19] [ 30/1319] eta: 1:14:19 lr: 2.7968919338800786e-05 loss: 0.0408 (0.0663) time: 3.3966 data: 0.0087 max mem: 33370 +Epoch: [19] [ 40/1319] eta: 1:13:31 lr: 2.7959821289661182e-05 loss: 0.0456 (0.0635) time: 3.3742 data: 0.0081 max mem: 33370 +Epoch: [19] [ 50/1319] eta: 1:12:43 lr: 2.795072291156743e-05 loss: 0.0472 (0.0617) time: 3.4062 data: 0.0081 max mem: 33370 +Epoch: [19] [ 60/1319] eta: 1:11:51 lr: 2.7941624204388656e-05 loss: 0.0505 (0.0634) time: 3.3737 data: 0.0083 max mem: 33370 +Epoch: [19] [ 70/1319] eta: 1:11:07 lr: 2.7932525167993873e-05 loss: 0.0505 (0.0610) time: 3.3608 data: 0.0078 max mem: 33370 +Epoch: [19] [ 80/1319] eta: 1:10:28 lr: 2.7923425802252002e-05 loss: 0.0477 (0.0590) time: 3.3771 data: 0.0078 max mem: 33370 +Epoch: [19] [ 90/1319] eta: 1:09:43 lr: 2.791432610703186e-05 loss: 0.0459 (0.0578) time: 3.3576 data: 0.0078 max mem: 33370 +Epoch: [19] [ 100/1319] eta: 1:09:05 lr: 2.790522608220219e-05 loss: 0.0530 (0.0579) time: 3.3520 data: 0.0077 max mem: 33370 +Epoch: [19] [ 110/1319] eta: 1:08:29 lr: 2.789612572763159e-05 loss: 0.0519 (0.0574) time: 3.3788 data: 0.0077 max mem: 33370 +Epoch: [19] [ 120/1319] eta: 1:07:54 lr: 2.7887025043188598e-05 loss: 0.0412 (0.0567) time: 3.3838 data: 0.0077 max mem: 33370 +Epoch: [19] [ 130/1319] eta: 1:07:14 lr: 2.7877924028741625e-05 loss: 0.0473 (0.0564) time: 3.3606 data: 0.0078 max mem: 33370 +Epoch: [19] [ 140/1319] eta: 1:06:37 lr: 2.7868822684159008e-05 loss: 0.0473 (0.0562) time: 3.3495 data: 0.0079 max mem: 33370 +Epoch: [19] [ 150/1319] eta: 1:06:05 lr: 2.7859721009308947e-05 loss: 0.0425 (0.0554) time: 3.3865 data: 0.0081 max mem: 33370 +Epoch: [19] [ 160/1319] eta: 1:05:30 lr: 2.7850619004059574e-05 loss: 0.0425 (0.0562) time: 3.3900 data: 0.0083 max mem: 33370 +Epoch: [19] [ 170/1319] eta: 1:04:54 lr: 2.7841516668278917e-05 loss: 0.0447 (0.0556) time: 3.3641 data: 0.0082 max mem: 33370 +Epoch: [19] [ 180/1319] eta: 1:04:20 lr: 2.7832414001834883e-05 loss: 0.0419 (0.0552) time: 3.3788 data: 0.0082 max mem: 33370 +Epoch: [19] [ 190/1319] eta: 1:03:46 lr: 2.782331100459529e-05 loss: 0.0454 (0.0551) time: 3.3873 data: 0.0084 max mem: 33370 +Epoch: [19] [ 200/1319] eta: 1:03:11 lr: 2.781420767642787e-05 loss: 0.0427 (0.0546) time: 3.3778 data: 0.0081 max mem: 33370 +Epoch: [19] [ 210/1319] eta: 1:02:35 lr: 2.7805104017200224e-05 loss: 0.0446 (0.0546) time: 3.3611 data: 0.0078 max mem: 33370 +Epoch: [19] [ 220/1319] eta: 1:02:03 lr: 2.779600002677987e-05 loss: 0.0536 (0.0546) time: 3.3804 data: 0.0077 max mem: 33370 +Epoch: [19] [ 230/1319] eta: 1:01:28 lr: 2.778689570503424e-05 loss: 0.0501 (0.0544) time: 3.3950 data: 0.0079 max mem: 33370 +Epoch: [19] [ 240/1319] eta: 1:00:53 lr: 2.7777791051830626e-05 loss: 0.0513 (0.0545) time: 3.3695 data: 0.0078 max mem: 33370 +Epoch: [19] [ 250/1319] eta: 1:00:19 lr: 2.7768686067036253e-05 loss: 0.0554 (0.0546) time: 3.3760 data: 0.0079 max mem: 33370 +Epoch: [19] [ 260/1319] eta: 0:59:44 lr: 2.775958075051822e-05 loss: 0.0432 (0.0543) time: 3.3740 data: 0.0080 max mem: 33370 +Epoch: [19] [ 270/1319] eta: 0:59:11 lr: 2.7750475102143547e-05 loss: 0.0406 (0.0541) time: 3.3786 data: 0.0079 max mem: 33370 +Epoch: [19] [ 280/1319] eta: 0:58:36 lr: 2.7741369121779126e-05 loss: 0.0412 (0.0540) time: 3.3775 data: 0.0083 max mem: 33370 +Epoch: [19] [ 290/1319] eta: 0:58:01 lr: 2.7732262809291776e-05 loss: 0.0523 (0.0541) time: 3.3545 data: 0.0085 max mem: 33370 +Epoch: [19] [ 300/1319] eta: 0:57:27 lr: 2.7723156164548194e-05 loss: 0.0516 (0.0548) time: 3.3556 data: 0.0085 max mem: 33370 +Epoch: [19] [ 310/1319] eta: 0:56:51 lr: 2.771404918741497e-05 loss: 0.0510 (0.0550) time: 3.3479 data: 0.0082 max mem: 33370 +Epoch: [19] [ 320/1319] eta: 0:56:16 lr: 2.7704941877758615e-05 loss: 0.0538 (0.0549) time: 3.3423 data: 0.0079 max mem: 33370 +Epoch: [19] [ 330/1319] eta: 0:55:42 lr: 2.7695834235445526e-05 loss: 0.0490 (0.0548) time: 3.3500 data: 0.0079 max mem: 33370 +Epoch: [19] [ 340/1319] eta: 0:55:07 lr: 2.7686726260341988e-05 loss: 0.0420 (0.0544) time: 3.3557 data: 0.0078 max mem: 33370 +Epoch: [19] [ 350/1319] eta: 0:54:34 lr: 2.7677617952314193e-05 loss: 0.0475 (0.0545) time: 3.3724 data: 0.0077 max mem: 33370 +Epoch: [19] [ 360/1319] eta: 0:53:59 lr: 2.7668509311228242e-05 loss: 0.0505 (0.0545) time: 3.3623 data: 0.0076 max mem: 33370 +Epoch: [19] [ 370/1319] eta: 0:53:26 lr: 2.7659400336950098e-05 loss: 0.0510 (0.0544) time: 3.3728 data: 0.0081 max mem: 33370 +Epoch: [19] [ 380/1319] eta: 0:52:52 lr: 2.765029102934566e-05 loss: 0.0482 (0.0545) time: 3.3880 data: 0.0081 max mem: 33370 +Epoch: [19] [ 390/1319] eta: 0:52:19 lr: 2.764118138828069e-05 loss: 0.0495 (0.0547) time: 3.3873 data: 0.0078 max mem: 33370 +Epoch: [19] [ 400/1319] eta: 0:51:44 lr: 2.763207141362088e-05 loss: 0.0532 (0.0550) time: 3.3760 data: 0.0077 max mem: 33370 +Epoch: [19] [ 410/1319] eta: 0:51:11 lr: 2.7622961105231792e-05 loss: 0.0532 (0.0550) time: 3.3711 data: 0.0079 max mem: 33370 +Epoch: [19] [ 420/1319] eta: 0:50:37 lr: 2.7613850462978895e-05 loss: 0.0469 (0.0547) time: 3.3963 data: 0.0079 max mem: 33370 +Epoch: [19] [ 430/1319] eta: 0:50:03 lr: 2.7604739486727564e-05 loss: 0.0489 (0.0547) time: 3.3850 data: 0.0077 max mem: 33370 +Epoch: [19] [ 440/1319] eta: 0:49:30 lr: 2.759562817634305e-05 loss: 0.0543 (0.0549) time: 3.3790 data: 0.0079 max mem: 33370 +Epoch: [19] [ 450/1319] eta: 0:48:56 lr: 2.7586516531690514e-05 loss: 0.0504 (0.0549) time: 3.3826 data: 0.0083 max mem: 33370 +Epoch: [19] [ 460/1319] eta: 0:48:22 lr: 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data: 0.0075 max mem: 33370 +Epoch: [19] [1090/1319] eta: 0:12:52 lr: 2.700266974524126e-05 loss: 0.0550 (0.0570) time: 3.3922 data: 0.0077 max mem: 33370 +Epoch: [19] [1100/1319] eta: 0:12:18 lr: 2.699353607885957e-05 loss: 0.0531 (0.0570) time: 3.3998 data: 0.0079 max mem: 33370 +Epoch: [19] [1110/1319] eta: 0:11:44 lr: 2.6984402069074687e-05 loss: 0.0531 (0.0570) time: 3.4086 data: 0.0077 max mem: 33370 +Epoch: [19] [1120/1319] eta: 0:11:11 lr: 2.6975267715744523e-05 loss: 0.0544 (0.0569) time: 3.4200 data: 0.0074 max mem: 33370 +Epoch: [19] [1130/1319] eta: 0:10:37 lr: 2.6966133018726902e-05 loss: 0.0490 (0.0569) time: 3.3980 data: 0.0074 max mem: 33370 +Epoch: [19] [1140/1319] eta: 0:10:03 lr: 2.6956997977879505e-05 loss: 0.0490 (0.0569) time: 3.3696 data: 0.0080 max mem: 33370 +Epoch: [19] [1150/1319] eta: 0:09:29 lr: 2.6947862593059943e-05 loss: 0.0481 (0.0569) time: 3.3622 data: 0.0077 max mem: 33370 +Epoch: [19] [1160/1319] eta: 0:08:56 lr: 2.6938726864125667e-05 loss: 0.0474 (0.0569) time: 3.3613 data: 0.0073 max mem: 33370 +Epoch: [19] [1170/1319] eta: 0:08:22 lr: 2.6929590790934063e-05 loss: 0.0467 (0.0569) time: 3.3612 data: 0.0077 max mem: 33370 +Epoch: [19] [1180/1319] eta: 0:07:48 lr: 2.6920454373342357e-05 loss: 0.0532 (0.0569) time: 3.3462 data: 0.0084 max mem: 33370 +Epoch: [19] [1190/1319] eta: 0:07:15 lr: 2.6911317611207703e-05 loss: 0.0600 (0.0570) time: 3.3558 data: 0.0082 max mem: 33370 +Epoch: [19] [1200/1319] eta: 0:06:41 lr: 2.6902180504387114e-05 loss: 0.0605 (0.0570) time: 3.3547 data: 0.0077 max mem: 33370 +Epoch: [19] [1210/1319] eta: 0:06:07 lr: 2.689304305273751e-05 loss: 0.0608 (0.0571) time: 3.3350 data: 0.0077 max mem: 33370 +Epoch: [19] [1220/1319] eta: 0:05:33 lr: 2.6883905256115667e-05 loss: 0.0608 (0.0571) time: 3.3648 data: 0.0076 max mem: 33370 +Epoch: [19] [1230/1319] eta: 0:05:00 lr: 2.687476711437828e-05 loss: 0.0532 (0.0571) time: 3.3765 data: 0.0075 max mem: 33370 +Epoch: [19] [1240/1319] eta: 0:04:26 lr: 2.6865628627381928e-05 loss: 0.0532 (0.0571) time: 3.3672 data: 0.0075 max mem: 33370 +Epoch: [19] [1250/1319] eta: 0:03:52 lr: 2.6856489794983043e-05 loss: 0.0522 (0.0572) time: 3.3773 data: 0.0073 max mem: 33370 +Epoch: [19] [1260/1319] eta: 0:03:18 lr: 2.6847350617037976e-05 loss: 0.0516 (0.0572) time: 3.3744 data: 0.0075 max mem: 33370 +Epoch: [19] [1270/1319] eta: 0:02:45 lr: 2.683821109340296e-05 loss: 0.0496 (0.0572) time: 3.3573 data: 0.0078 max mem: 33370 +Epoch: [19] [1280/1319] eta: 0:02:11 lr: 2.68290712239341e-05 loss: 0.0474 (0.0572) time: 3.3588 data: 0.0079 max mem: 33370 +Epoch: [19] [1290/1319] eta: 0:01:37 lr: 2.681993100848739e-05 loss: 0.0495 (0.0573) time: 3.3775 data: 0.0078 max mem: 33370 +Epoch: [19] [1300/1319] eta: 0:01:04 lr: 2.6810790446918727e-05 loss: 0.0620 (0.0573) time: 3.3667 data: 0.0081 max mem: 33370 +Epoch: [19] [1310/1319] eta: 0:00:30 lr: 2.680164953908387e-05 loss: 0.0624 (0.0574) time: 3.3519 data: 0.0082 max mem: 33370 +Epoch: [19] Total time: 1:14:07 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 2:50:35 time: 3.9780 data: 3.8882 max mem: 33370 +Test: [ 100/2573] eta: 0:04:44 time: 0.0760 data: 0.0014 max mem: 33370 +Test: [ 200/2573] eta: 0:03:49 time: 0.0774 data: 0.0015 max mem: 33370 +Test: [ 300/2573] eta: 0:03:24 time: 0.0789 data: 0.0013 max mem: 33370 +Test: [ 400/2573] eta: 0:03:08 time: 0.0792 data: 0.0014 max mem: 33370 +Test: [ 500/2573] eta: 0:02:56 time: 0.0789 data: 0.0014 max mem: 33370 +Test: [ 600/2573] eta: 0:02:46 time: 0.0788 data: 0.0015 max mem: 33370 +Test: [ 700/2573] eta: 0:02:36 time: 0.0780 data: 0.0014 max mem: 33370 +Test: [ 800/2573] eta: 0:02:27 time: 0.0811 data: 0.0013 max mem: 33370 +Test: [ 900/2573] eta: 0:02:18 time: 0.0779 data: 0.0015 max mem: 33370 +Test: [1000/2573] eta: 0:02:09 time: 0.0785 data: 0.0015 max mem: 33370 +Test: [1100/2573] eta: 0:02:00 time: 0.0788 data: 0.0014 max mem: 33370 +Test: [1200/2573] eta: 0:01:52 time: 0.0781 data: 0.0014 max mem: 33370 +Test: [1300/2573] eta: 0:01:43 time: 0.0784 data: 0.0013 max mem: 33370 +Test: [1400/2573] eta: 0:01:35 time: 0.0768 data: 0.0014 max mem: 33370 +Test: [1500/2573] eta: 0:01:27 time: 0.0793 data: 0.0014 max mem: 33370 +Test: [1600/2573] eta: 0:01:18 time: 0.0821 data: 0.0014 max mem: 33370 +Test: [1700/2573] eta: 0:01:10 time: 0.0773 data: 0.0014 max mem: 33370 +Test: [1800/2573] eta: 0:01:02 time: 0.0816 data: 0.0014 max mem: 33370 +Test: [1900/2573] eta: 0:00:54 time: 0.0786 data: 0.0015 max mem: 33370 +Test: [2000/2573] eta: 0:00:46 time: 0.0786 data: 0.0014 max mem: 33370 +Test: [2100/2573] eta: 0:00:38 time: 0.0812 data: 0.0014 max mem: 33370 +Test: [2200/2573] eta: 0:00:29 time: 0.0809 data: 0.0014 max mem: 33370 +Test: [2300/2573] eta: 0:00:21 time: 0.0825 data: 0.0015 max mem: 33370 +Test: [2400/2573] eta: 0:00:13 time: 0.0750 data: 0.0014 max mem: 33370 +Test: [2500/2573] eta: 0:00:05 time: 0.0797 data: 0.0014 max mem: 33370 +Test: Total time: 0:03:27 +Final results: +Mean IoU is 62.44 + + precision@0.5 = 69.79 + precision@0.6 = 64.79 + precision@0.7 = 57.99 + precision@0.8 = 46.34 + precision@0.9 = 21.96 + overall IoU = 60.34 + +Average object IoU 62.43724562268626 +Overall IoU 60.33876037597656 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [20] [ 0/1319] eta: 3:12:40 lr: 2.6793422425855603e-05 loss: 0.0408 (0.0408) time: 8.7648 data: 2.8795 max mem: 33370 +Epoch: [20] [ 10/1319] eta: 1:24:02 lr: 2.678428085971722e-05 loss: 0.0478 (0.0483) time: 3.8519 data: 0.2691 max mem: 33370 +Epoch: [20] [ 20/1319] eta: 1:18:34 lr: 2.6775138946893718e-05 loss: 0.0478 (0.0493) time: 3.3724 data: 0.0081 max mem: 33370 +Epoch: [20] [ 30/1319] eta: 1:16:15 lr: 2.6765996687240426e-05 loss: 0.0498 (0.0503) time: 3.3836 data: 0.0082 max mem: 33370 +Epoch: [20] [ 40/1319] eta: 1:14:41 lr: 2.675685408061254e-05 loss: 0.0491 (0.0487) time: 3.3721 data: 0.0079 max mem: 33370 +Epoch: [20] [ 50/1319] eta: 1:13:44 lr: 2.6747711126865168e-05 loss: 0.0391 (0.0486) time: 3.3889 data: 0.0079 max mem: 33370 +Epoch: [20] [ 60/1319] eta: 1:12:50 lr: 2.6738567825853273e-05 loss: 0.0459 (0.0488) time: 3.4045 data: 0.0081 max mem: 33370 +Epoch: [20] [ 70/1319] eta: 1:11:52 lr: 2.6729424177431713e-05 loss: 0.0459 (0.0487) time: 3.3652 data: 0.0080 max mem: 33370 +Epoch: [20] [ 80/1319] eta: 1:10:57 lr: 2.6720280181455227e-05 loss: 0.0439 (0.0492) time: 3.3306 data: 0.0082 max mem: 33370 +Epoch: [20] [ 90/1319] eta: 1:10:12 lr: 2.671113583777845e-05 loss: 0.0410 (0.0488) time: 3.3389 data: 0.0085 max mem: 33370 +Epoch: [20] [ 100/1319] eta: 1:09:32 lr: 2.670199114625589e-05 loss: 0.0426 (0.0490) time: 3.3677 data: 0.0084 max mem: 33370 +Epoch: [20] [ 110/1319] eta: 1:08:50 lr: 2.6692846106741932e-05 loss: 0.0477 (0.0487) time: 3.3671 data: 0.0081 max mem: 33370 +Epoch: [20] [ 120/1319] eta: 1:08:08 lr: 2.668370071909087e-05 loss: 0.0403 (0.0488) time: 3.3434 data: 0.0079 max mem: 33370 +Epoch: [20] [ 130/1319] eta: 1:07:29 lr: 2.6674554983156852e-05 loss: 0.0437 (0.0489) time: 3.3470 data: 0.0083 max mem: 33370 +Epoch: [20] [ 140/1319] eta: 1:06:50 lr: 2.666540889879393e-05 loss: 0.0437 (0.0491) time: 3.3509 data: 0.0088 max mem: 33370 +Epoch: [20] [ 150/1319] eta: 1:06:09 lr: 2.6656262465856026e-05 loss: 0.0457 (0.0495) time: 3.3257 data: 0.0088 max mem: 33370 +Epoch: [20] [ 160/1319] eta: 1:05:31 lr: 2.6647115684196954e-05 loss: 0.0458 (0.0495) time: 3.3300 data: 0.0081 max mem: 33370 +Epoch: [20] [ 170/1319] eta: 1:04:54 lr: 2.663796855367041e-05 loss: 0.0409 (0.0491) time: 3.3418 data: 0.0075 max mem: 33370 +Epoch: [20] [ 180/1319] eta: 1:04:19 lr: 2.662882107412996e-05 loss: 0.0461 (0.0495) time: 3.3591 data: 0.0077 max mem: 33370 +Epoch: [20] [ 190/1319] eta: 1:03:43 lr: 2.661967324542908e-05 loss: 0.0461 (0.0493) time: 3.3672 data: 0.0076 max mem: 33370 +Epoch: [20] [ 200/1319] eta: 1:03:09 lr: 2.6610525067421092e-05 loss: 0.0447 (0.0492) time: 3.3638 data: 0.0076 max mem: 33370 +Epoch: [20] [ 210/1319] eta: 1:02:36 lr: 2.6601376539959238e-05 loss: 0.0506 (0.0498) time: 3.3934 data: 0.0075 max mem: 33370 +Epoch: [20] [ 220/1319] eta: 1:02:02 lr: 2.6592227662896617e-05 loss: 0.0556 (0.0505) time: 3.3973 data: 0.0079 max mem: 33370 +Epoch: [20] [ 230/1319] eta: 1:01:26 lr: 2.658307843608621e-05 loss: 0.0551 (0.0507) time: 3.3672 data: 0.0084 max mem: 33370 +Epoch: [20] [ 240/1319] eta: 1:00:53 lr: 2.65739288593809e-05 loss: 0.0543 (0.0515) time: 3.3668 data: 0.0080 max mem: 33370 +Epoch: [20] [ 250/1319] eta: 1:00:19 lr: 2.6564778932633426e-05 loss: 0.0541 (0.0514) time: 3.3843 data: 0.0077 max mem: 33370 +Epoch: [20] [ 260/1319] eta: 0:59:46 lr: 2.655562865569643e-05 loss: 0.0443 (0.0513) time: 3.3996 data: 0.0075 max mem: 33370 +Epoch: [20] [ 270/1319] eta: 0:59:10 lr: 2.654647802842242e-05 loss: 0.0439 (0.0512) time: 3.3790 data: 0.0076 max mem: 33370 +Epoch: [20] [ 280/1319] eta: 0:58:37 lr: 2.6537327050663813e-05 loss: 0.0486 (0.0513) time: 3.3668 data: 0.0076 max mem: 33370 +Epoch: [20] [ 290/1319] eta: 0:58:03 lr: 2.6528175722272857e-05 loss: 0.0464 (0.0512) time: 3.3854 data: 0.0074 max mem: 33370 +Epoch: [20] [ 300/1319] eta: 0:57:27 lr: 2.6519024043101733e-05 loss: 0.0543 (0.0520) time: 3.3581 data: 0.0079 max mem: 33370 +Epoch: [20] [ 310/1319] eta: 0:56:53 lr: 2.6509872013002462e-05 loss: 0.0599 (0.0523) time: 3.3523 data: 0.0085 max mem: 33370 +Epoch: [20] [ 320/1319] eta: 0:56:18 lr: 2.6500719631826982e-05 loss: 0.0388 (0.0519) time: 3.3653 data: 0.0081 max mem: 33370 +Epoch: [20] [ 330/1319] eta: 0:55:43 lr: 2.649156689942709e-05 loss: 0.0388 (0.0517) time: 3.3515 data: 0.0078 max mem: 33370 +Epoch: [20] [ 340/1319] eta: 0:55:10 lr: 2.648241381565446e-05 loss: 0.0404 (0.0514) time: 3.3630 data: 0.0081 max mem: 33370 +Epoch: [20] [ 350/1319] eta: 0:54:37 lr: 2.6473260380360663e-05 loss: 0.0510 (0.0519) time: 3.4013 data: 0.0083 max mem: 33370 +Epoch: [20] [ 360/1319] eta: 0:54:03 lr: 2.6464106593397137e-05 loss: 0.0510 (0.0520) time: 3.3959 data: 0.0084 max mem: 33370 +Epoch: [20] [ 370/1319] eta: 0:53:28 lr: 2.6454952454615202e-05 loss: 0.0529 (0.0523) time: 3.3657 data: 0.0082 max mem: 33370 +Epoch: [20] [ 380/1319] eta: 0:52:55 lr: 2.6445797963866064e-05 loss: 0.0428 (0.0520) time: 3.3755 data: 0.0078 max mem: 33370 +Epoch: [20] [ 390/1319] eta: 0:52:21 lr: 2.643664312100081e-05 loss: 0.0399 (0.0521) time: 3.3837 data: 0.0075 max mem: 33370 +Epoch: [20] [ 400/1319] eta: 0:51:48 lr: 2.6427487925870388e-05 loss: 0.0488 (0.0519) time: 3.4000 data: 0.0080 max mem: 33370 +Epoch: [20] [ 410/1319] eta: 0:51:15 lr: 2.641833237832565e-05 loss: 0.0449 (0.0520) time: 3.4115 data: 0.0079 max mem: 33370 +Epoch: [20] [ 420/1319] eta: 0:50:42 lr: 2.6409176478217318e-05 loss: 0.0443 (0.0525) time: 3.4218 data: 0.0074 max mem: 33370 +Epoch: [20] [ 430/1319] eta: 0:50:09 lr: 2.640002022539598e-05 loss: 0.0443 (0.0528) time: 3.4224 data: 0.0077 max mem: 33370 +Epoch: [20] [ 440/1319] eta: 0:49:35 lr: 2.6390863619712137e-05 loss: 0.0498 (0.0528) time: 3.3965 data: 0.0079 max mem: 33370 +Epoch: [20] [ 450/1319] eta: 0:49:01 lr: 2.6381706661016125e-05 loss: 0.0466 (0.0526) time: 3.3984 data: 0.0077 max mem: 33370 +Epoch: [20] [ 460/1319] eta: 0:48:28 lr: 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data: 0.0079 max mem: 33370 +Epoch: [20] [1090/1319] eta: 0:12:57 lr: 2.5794920097242954e-05 loss: 0.0519 (0.0523) time: 3.4473 data: 0.0078 max mem: 33370 +Epoch: [20] [1100/1319] eta: 0:12:23 lr: 2.5785739865855164e-05 loss: 0.0402 (0.0523) time: 3.4428 data: 0.0079 max mem: 33370 +Epoch: [20] [1110/1319] eta: 0:11:49 lr: 2.5776559271303753e-05 loss: 0.0431 (0.0523) time: 3.3939 data: 0.0079 max mem: 33370 +Epoch: [20] [1120/1319] eta: 0:11:15 lr: 2.5767378313430623e-05 loss: 0.0453 (0.0522) time: 3.3772 data: 0.0083 max mem: 33370 +Epoch: [20] [1130/1319] eta: 0:10:41 lr: 2.5758196992077554e-05 loss: 0.0474 (0.0524) time: 3.3836 data: 0.0083 max mem: 33370 +Epoch: [20] [1140/1319] eta: 0:10:07 lr: 2.574901530708619e-05 loss: 0.0548 (0.0523) time: 3.3871 data: 0.0080 max mem: 33370 +Epoch: [20] [1150/1319] eta: 0:09:33 lr: 2.573983325829803e-05 loss: 0.0475 (0.0524) time: 3.4050 data: 0.0079 max mem: 33370 +Epoch: [20] [1160/1319] eta: 0:08:59 lr: 2.573065084555446e-05 loss: 0.0499 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2.5657178422133044e-05 loss: 0.0464 (0.0528) time: 3.4219 data: 0.0084 max mem: 33370 +Epoch: [20] [1250/1319] eta: 0:03:54 lr: 2.564799272663101e-05 loss: 0.0527 (0.0529) time: 3.4428 data: 0.0083 max mem: 33370 +Epoch: [20] [1260/1319] eta: 0:03:20 lr: 2.5638806665580068e-05 loss: 0.0532 (0.0529) time: 3.4535 data: 0.0082 max mem: 33370 +Epoch: [20] [1270/1319] eta: 0:02:46 lr: 2.5629620238820134e-05 loss: 0.0520 (0.0530) time: 3.4615 data: 0.0085 max mem: 33370 +Epoch: [20] [1280/1319] eta: 0:02:12 lr: 2.562043344619099e-05 loss: 0.0510 (0.0530) time: 3.4624 data: 0.0087 max mem: 33370 +Epoch: [20] [1290/1319] eta: 0:01:38 lr: 2.5611246287532285e-05 loss: 0.0497 (0.0530) time: 3.4620 data: 0.0088 max mem: 33370 +Epoch: [20] [1300/1319] eta: 0:01:04 lr: 2.560205876268355e-05 loss: 0.0515 (0.0531) time: 3.4645 data: 0.0089 max mem: 33370 +Epoch: [20] [1310/1319] eta: 0:00:30 lr: 2.5592870871484144e-05 loss: 0.0468 (0.0531) time: 3.4461 data: 0.0086 max mem: 33370 +Epoch: [20] Total time: 1:14:45 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 2:52:04 time: 4.0125 data: 3.9162 max mem: 33370 +Test: [ 100/2573] eta: 0:04:52 time: 0.0787 data: 0.0016 max mem: 33370 +Test: [ 200/2573] eta: 0:03:56 time: 0.0807 data: 0.0016 max mem: 33370 +Test: [ 300/2573] eta: 0:03:30 time: 0.0809 data: 0.0016 max mem: 33370 +Test: [ 400/2573] eta: 0:03:14 time: 0.0818 data: 0.0015 max mem: 33370 +Test: [ 500/2573] eta: 0:03:01 time: 0.0800 data: 0.0015 max mem: 33370 +Test: [ 600/2573] eta: 0:02:50 time: 0.0802 data: 0.0016 max mem: 33370 +Test: [ 700/2573] eta: 0:02:40 time: 0.0801 data: 0.0015 max mem: 33370 +Test: [ 800/2573] eta: 0:02:31 time: 0.0829 data: 0.0015 max mem: 33370 +Test: [ 900/2573] eta: 0:02:21 time: 0.0798 data: 0.0014 max mem: 33370 +Test: [1000/2573] eta: 0:02:12 time: 0.0800 data: 0.0015 max mem: 33370 +Test: [1100/2573] eta: 0:02:03 time: 0.0805 data: 0.0015 max mem: 33370 +Test: [1200/2573] eta: 0:01:55 time: 0.0807 data: 0.0014 max mem: 33370 +Test: [1300/2573] eta: 0:01:46 time: 0.0802 data: 0.0014 max mem: 33370 +Test: [1400/2573] eta: 0:01:37 time: 0.0795 data: 0.0015 max mem: 33370 +Test: [1500/2573] eta: 0:01:29 time: 0.0815 data: 0.0016 max mem: 33370 +Test: [1600/2573] eta: 0:01:20 time: 0.0841 data: 0.0014 max mem: 33370 +Test: [1700/2573] eta: 0:01:12 time: 0.0784 data: 0.0014 max mem: 33370 +Test: [1800/2573] eta: 0:01:04 time: 0.0819 data: 0.0015 max mem: 33370 +Test: [1900/2573] eta: 0:00:55 time: 0.0789 data: 0.0014 max mem: 33370 +Test: [2000/2573] eta: 0:00:47 time: 0.0804 data: 0.0016 max mem: 33370 +Test: [2100/2573] eta: 0:00:38 time: 0.0825 data: 0.0015 max mem: 33370 +Test: [2200/2573] eta: 0:00:30 time: 0.0823 data: 0.0015 max mem: 33370 +Test: [2300/2573] eta: 0:00:22 time: 0.0821 data: 0.0015 max mem: 33370 +Test: [2400/2573] eta: 0:00:14 time: 0.0776 data: 0.0015 max mem: 33370 +Test: [2500/2573] eta: 0:00:05 time: 0.0803 data: 0.0015 max mem: 33370 +Test: Total time: 0:03:31 +Final results: +Mean IoU is 63.86 + + precision@0.5 = 71.85 + precision@0.6 = 66.20 + precision@0.7 = 59.58 + precision@0.8 = 47.98 + precision@0.9 = 23.06 + overall IoU = 61.63 + +Average object IoU 63.85792356287661 +Overall IoU 61.62606430053711 +Better epoch: 20 + +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [21] [ 0/1319] eta: 2:18:35 lr: 2.5584601456041995e-05 loss: 0.0506 (0.0506) time: 6.3041 data: 2.6974 max mem: 33370 +Epoch: [21] [ 10/1319] eta: 1:21:03 lr: 2.5575412868333344e-05 loss: 0.0489 (0.0515) time: 3.7153 data: 0.2522 max mem: 33370 +Epoch: [21] [ 20/1319] eta: 1:18:17 lr: 2.5566223913807464e-05 loss: 0.0472 (0.0485) time: 3.4819 data: 0.0079 max mem: 33370 +Epoch: [21] [ 30/1319] eta: 1:16:09 lr: 2.5557034592303224e-05 loss: 0.0447 (0.0490) time: 3.4512 data: 0.0085 max mem: 33370 +Epoch: [21] [ 40/1319] eta: 1:15:07 lr: 2.5547844903659336e-05 loss: 0.0453 (0.0493) time: 3.4270 data: 0.0087 max mem: 33370 +Epoch: [21] [ 50/1319] eta: 1:14:09 lr: 2.5538654847714393e-05 loss: 0.0479 (0.0494) time: 3.4473 data: 0.0085 max mem: 33370 +Epoch: [21] [ 60/1319] eta: 1:13:15 lr: 2.552946442430683e-05 loss: 0.0409 (0.0480) time: 3.4253 data: 0.0085 max mem: 33370 +Epoch: [21] [ 70/1319] eta: 1:12:27 lr: 2.552027363327497e-05 loss: 0.0437 (0.0482) time: 3.4159 data: 0.0085 max mem: 33370 +Epoch: [21] [ 80/1319] eta: 1:11:49 lr: 2.551108247445699e-05 loss: 0.0456 (0.0481) time: 3.4369 data: 0.0085 max mem: 33370 +Epoch: [21] [ 90/1319] eta: 1:11:05 lr: 2.5501890947690927e-05 loss: 0.0425 (0.0476) time: 3.4342 data: 0.0086 max mem: 33370 +Epoch: [21] [ 100/1319] eta: 1:10:27 lr: 2.5492699052814688e-05 loss: 0.0496 (0.0487) time: 3.4288 data: 0.0086 max mem: 33370 +Epoch: [21] [ 110/1319] eta: 1:09:49 lr: 2.548350678966605e-05 loss: 0.0438 (0.0479) time: 3.4404 data: 0.0086 max mem: 33370 +Epoch: [21] [ 120/1319] eta: 1:09:15 lr: 2.547431415808263e-05 loss: 0.0405 (0.0481) time: 3.4523 data: 0.0085 max mem: 33370 +Epoch: [21] [ 130/1319] eta: 1:08:42 lr: 2.5465121157901932e-05 loss: 0.0437 (0.0480) time: 3.4787 data: 0.0084 max mem: 33370 +Epoch: [21] [ 140/1319] eta: 1:08:05 lr: 2.5455927788961316e-05 loss: 0.0414 (0.0475) time: 3.4610 data: 0.0086 max mem: 33370 +Epoch: [21] [ 150/1319] eta: 1:07:31 lr: 2.5446734051098e-05 loss: 0.0414 (0.0472) time: 3.4559 data: 0.0083 max mem: 33370 +Epoch: [21] [ 160/1319] eta: 1:06:55 lr: 2.5437539944149068e-05 loss: 0.0468 (0.0475) time: 3.4634 data: 0.0080 max mem: 33370 +Epoch: [21] [ 170/1319] eta: 1:06:19 lr: 2.542834546795147e-05 loss: 0.0473 (0.0474) time: 3.4420 data: 0.0080 max mem: 33370 +Epoch: [21] [ 180/1319] eta: 1:05:38 lr: 2.5419150622342014e-05 loss: 0.0472 (0.0479) time: 3.4031 data: 0.0082 max mem: 33370 +Epoch: [21] [ 190/1319] eta: 1:05:03 lr: 2.5409955407157366e-05 loss: 0.0455 (0.0475) time: 3.4098 data: 0.0081 max mem: 33370 +Epoch: [21] [ 200/1319] eta: 1:04:24 lr: 2.5400759822234066e-05 loss: 0.0360 (0.0472) time: 3.4101 data: 0.0082 max mem: 33370 +Epoch: [21] [ 210/1319] eta: 1:03:47 lr: 2.539156386740852e-05 loss: 0.0364 (0.0472) time: 3.3951 data: 0.0085 max mem: 33370 +Epoch: [21] [ 220/1319] eta: 1:03:13 lr: 2.538236754251696e-05 loss: 0.0479 (0.0482) time: 3.4409 data: 0.0083 max mem: 33370 +Epoch: [21] [ 230/1319] eta: 1:02:38 lr: 2.5373170847395516e-05 loss: 0.0446 (0.0478) time: 3.4459 data: 0.0081 max mem: 33370 +Epoch: [21] [ 240/1319] eta: 1:02:02 lr: 2.536397378188018e-05 loss: 0.0430 (0.0483) time: 3.4262 data: 0.0087 max mem: 33370 +Epoch: [21] [ 250/1319] eta: 1:01:30 lr: 2.5354776345806775e-05 loss: 0.0456 (0.0484) time: 3.4681 data: 0.0087 max mem: 33370 +Epoch: [21] [ 260/1319] eta: 1:00:54 lr: 2.534557853901102e-05 loss: 0.0442 (0.0483) time: 3.4668 data: 0.0087 max mem: 33370 +Epoch: [21] [ 270/1319] eta: 1:00:19 lr: 2.5336380361328465e-05 loss: 0.0400 (0.0479) time: 3.4241 data: 0.0089 max mem: 33370 +Epoch: [21] [ 280/1319] eta: 0:59:42 lr: 2.532718181259454e-05 loss: 0.0361 (0.0478) time: 3.4032 data: 0.0084 max mem: 33370 +Epoch: [21] [ 290/1319] eta: 0:59:07 lr: 2.531798289264453e-05 loss: 0.0458 (0.0480) time: 3.4113 data: 0.0082 max mem: 33370 +Epoch: [21] [ 300/1319] eta: 0:58:34 lr: 2.5308783601313586e-05 loss: 0.0505 (0.0483) time: 3.4675 data: 0.0082 max mem: 33370 +Epoch: [21] [ 310/1319] eta: 0:58:00 lr: 2.52995839384367e-05 loss: 0.0447 (0.0482) time: 3.4749 data: 0.0085 max mem: 33370 +Epoch: [21] [ 320/1319] eta: 0:57:23 lr: 2.5290383903848747e-05 loss: 0.0439 (0.0484) time: 3.4140 data: 0.0086 max mem: 33370 +Epoch: [21] [ 330/1319] eta: 0:56:46 lr: 2.5281183497384443e-05 loss: 0.0454 (0.0488) time: 3.3590 data: 0.0085 max mem: 33370 +Epoch: [21] [ 340/1319] eta: 0:56:09 lr: 2.5271982718878386e-05 loss: 0.0522 (0.0492) time: 3.3611 data: 0.0083 max mem: 33370 +Epoch: [21] [ 350/1319] eta: 0:55:32 lr: 2.5262781568165e-05 loss: 0.0485 (0.0491) time: 3.3639 data: 0.0080 max mem: 33370 +Epoch: [21] [ 360/1319] eta: 0:54:56 lr: 2.5253580045078606e-05 loss: 0.0397 (0.0490) time: 3.3522 data: 0.0078 max mem: 33370 +Epoch: [21] [ 370/1319] eta: 0:54:22 lr: 2.5244378149453368e-05 loss: 0.0435 (0.0490) time: 3.4042 data: 0.0079 max mem: 33370 +Epoch: [21] [ 380/1319] eta: 0:53:46 lr: 2.5235175881123296e-05 loss: 0.0380 (0.0488) time: 3.4141 data: 0.0079 max mem: 33370 +Epoch: [21] [ 390/1319] eta: 0:53:11 lr: 2.5225973239922274e-05 loss: 0.0374 (0.0487) time: 3.3893 data: 0.0077 max mem: 33370 +Epoch: [21] [ 400/1319] eta: 0:52:35 lr: 2.5216770225684038e-05 loss: 0.0424 (0.0489) time: 3.3956 data: 0.0077 max mem: 33370 +Epoch: [21] [ 410/1319] eta: 0:52:01 lr: 2.520756683824219e-05 loss: 0.0424 (0.0489) time: 3.4034 data: 0.0080 max mem: 33370 +Epoch: [21] [ 420/1319] eta: 0:51:28 lr: 2.5198363077430187e-05 loss: 0.0407 (0.0491) time: 3.4607 data: 0.0082 max mem: 33370 +Epoch: [21] [ 430/1319] eta: 0:50:52 lr: 2.5189158943081348e-05 loss: 0.0428 (0.0489) time: 3.4476 data: 0.0078 max mem: 33370 +Epoch: [21] [ 440/1319] eta: 0:50:17 lr: 2.5179954435028824e-05 loss: 0.0445 (0.0489) time: 3.3991 data: 0.0077 max mem: 33370 +Epoch: [21] [ 450/1319] eta: 0:49:41 lr: 2.517074955310566e-05 loss: 0.0494 (0.0489) time: 3.3723 data: 0.0082 max mem: 33370 +Epoch: [21] [ 460/1319] eta: 0:49:06 lr: 2.5161544297144735e-05 loss: 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(0.0489) time: 3.3380 data: 0.0078 max mem: 33370 +Epoch: [21] [ 860/1319] eta: 0:26:02 lr: 2.4793025411504282e-05 loss: 0.0459 (0.0489) time: 3.3404 data: 0.0077 max mem: 33370 +Epoch: [21] [ 870/1319] eta: 0:25:27 lr: 2.4783804674327604e-05 loss: 0.0386 (0.0488) time: 3.3523 data: 0.0077 max mem: 33370 +Epoch: [21] [ 880/1319] eta: 0:24:53 lr: 2.4774583555963328e-05 loss: 0.0386 (0.0487) time: 3.3820 data: 0.0077 max mem: 33370 +Epoch: [21] [ 890/1319] eta: 0:24:19 lr: 2.4765362056238035e-05 loss: 0.0393 (0.0487) time: 3.4003 data: 0.0077 max mem: 33370 +Epoch: [21] [ 900/1319] eta: 0:23:45 lr: 2.4756140174978167e-05 loss: 0.0447 (0.0488) time: 3.3743 data: 0.0076 max mem: 33370 +Epoch: [21] [ 910/1319] eta: 0:23:11 lr: 2.4746917912010012e-05 loss: 0.0543 (0.0490) time: 3.3731 data: 0.0077 max mem: 33370 +Epoch: [21] [ 920/1319] eta: 0:22:37 lr: 2.4737695267159685e-05 loss: 0.0487 (0.0490) time: 3.3678 data: 0.0081 max mem: 33370 +Epoch: [21] [ 930/1319] eta: 0:22:03 lr: 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mem: 33370 +Epoch: [21] [1090/1319] eta: 0:12:57 lr: 2.4580851707520996e-05 loss: 0.0502 (0.0493) time: 3.3772 data: 0.0078 max mem: 33370 +Epoch: [21] [1100/1319] eta: 0:12:23 lr: 2.457162215888721e-05 loss: 0.0403 (0.0493) time: 3.3842 data: 0.0079 max mem: 33370 +Epoch: [21] [1110/1319] eta: 0:11:49 lr: 2.456239222503884e-05 loss: 0.0398 (0.0493) time: 3.3904 data: 0.0079 max mem: 33370 +Epoch: [21] [1120/1319] eta: 0:11:15 lr: 2.455316190579896e-05 loss: 0.0416 (0.0493) time: 3.4029 data: 0.0080 max mem: 33370 +Epoch: [21] [1130/1319] eta: 0:10:41 lr: 2.4543931200990468e-05 loss: 0.0416 (0.0492) time: 3.3757 data: 0.0081 max mem: 33370 +Epoch: [21] [1140/1319] eta: 0:10:07 lr: 2.4534700110436136e-05 loss: 0.0451 (0.0493) time: 3.3481 data: 0.0079 max mem: 33370 +Epoch: [21] [1150/1319] eta: 0:09:33 lr: 2.452546863395857e-05 loss: 0.0429 (0.0493) time: 3.3801 data: 0.0078 max mem: 33370 +Epoch: [21] [1160/1319] eta: 0:08:59 lr: 2.451623677138022e-05 loss: 0.0413 (0.0494) time: 3.4005 data: 0.0081 max mem: 33370 +Epoch: [21] [1170/1319] eta: 0:08:25 lr: 2.4507004522523372e-05 loss: 0.0443 (0.0495) time: 3.3933 data: 0.0083 max mem: 33370 +Epoch: [21] [1180/1319] eta: 0:07:51 lr: 2.4497771887210175e-05 loss: 0.0404 (0.0494) time: 3.3825 data: 0.0082 max mem: 33370 +Epoch: [21] [1190/1319] eta: 0:07:17 lr: 2.4488538865262596e-05 loss: 0.0410 (0.0494) time: 3.3887 data: 0.0083 max mem: 33370 +Epoch: [21] [1200/1319] eta: 0:06:43 lr: 2.4479305456502462e-05 loss: 0.0448 (0.0495) time: 3.3714 data: 0.0083 max mem: 33370 +Epoch: [21] [1210/1319] eta: 0:06:09 lr: 2.4470071660751444e-05 loss: 0.0477 (0.0494) time: 3.3343 data: 0.0077 max mem: 33370 +Epoch: [21] [1220/1319] eta: 0:05:35 lr: 2.446083747783105e-05 loss: 0.0486 (0.0496) time: 3.3426 data: 0.0076 max mem: 33370 +Epoch: [21] [1230/1319] eta: 0:05:01 lr: 2.4451602907562637e-05 loss: 0.0472 (0.0496) time: 3.3720 data: 0.0080 max mem: 33370 +Epoch: [21] [1240/1319] eta: 0:04:28 lr: 2.4442367949767393e-05 loss: 0.0447 (0.0496) time: 3.3845 data: 0.0082 max mem: 33370 +Epoch: [21] [1250/1319] eta: 0:03:54 lr: 2.4433132604266355e-05 loss: 0.0456 (0.0496) time: 3.3646 data: 0.0081 max mem: 33370 +Epoch: [21] [1260/1319] eta: 0:03:20 lr: 2.442389687088041e-05 loss: 0.0483 (0.0496) time: 3.3678 data: 0.0083 max mem: 33370 +Epoch: [21] [1270/1319] eta: 0:02:46 lr: 2.441466074943027e-05 loss: 0.0468 (0.0496) time: 3.3810 data: 0.0080 max mem: 33370 +Epoch: [21] [1280/1319] eta: 0:02:12 lr: 2.440542423973651e-05 loss: 0.0468 (0.0496) time: 3.3722 data: 0.0075 max mem: 33370 +Epoch: [21] [1290/1319] eta: 0:01:38 lr: 2.439618734161953e-05 loss: 0.0451 (0.0496) time: 3.3634 data: 0.0073 max mem: 33370 +Epoch: [21] [1300/1319] eta: 0:01:04 lr: 2.4386950054899575e-05 loss: 0.0467 (0.0496) time: 3.3794 data: 0.0075 max mem: 33370 +Epoch: [21] [1310/1319] eta: 0:00:30 lr: 2.4377712379396728e-05 loss: 0.0467 (0.0495) time: 3.3681 data: 0.0075 max mem: 33370 +Epoch: [21] Total time: 1:14:33 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 4:40:08 time: 6.5325 data: 6.4500 max mem: 33370 +Test: [ 100/2573] eta: 0:05:44 time: 0.0751 data: 0.0015 max mem: 33370 +Test: [ 200/2573] eta: 0:04:18 time: 0.0776 data: 0.0015 max mem: 33370 +Test: [ 300/2573] eta: 0:03:42 time: 0.0784 data: 0.0014 max mem: 33370 +Test: [ 400/2573] eta: 0:03:21 time: 0.0787 data: 0.0014 max mem: 33370 +Test: [ 500/2573] eta: 0:03:05 time: 0.0782 data: 0.0015 max mem: 33370 +Test: [ 600/2573] eta: 0:02:53 time: 0.0778 data: 0.0015 max mem: 33370 +Test: [ 700/2573] eta: 0:02:42 time: 0.0775 data: 0.0014 max mem: 33370 +Test: [ 800/2573] eta: 0:02:32 time: 0.0817 data: 0.0014 max mem: 33370 +Test: [ 900/2573] eta: 0:02:22 time: 0.0779 data: 0.0014 max mem: 33370 +Test: [1000/2573] eta: 0:02:12 time: 0.0785 data: 0.0014 max mem: 33370 +Test: [1100/2573] eta: 0:02:03 time: 0.0789 data: 0.0014 max mem: 33370 +Test: [1200/2573] eta: 0:01:54 time: 0.0791 data: 0.0013 max mem: 33370 +Test: [1300/2573] eta: 0:01:45 time: 0.0793 data: 0.0014 max mem: 33370 +Test: [1400/2573] eta: 0:01:37 time: 0.0773 data: 0.0014 max mem: 33370 +Test: [1500/2573] eta: 0:01:28 time: 0.0787 data: 0.0014 max mem: 33370 +Test: [1600/2573] eta: 0:01:20 time: 0.0826 data: 0.0014 max mem: 33370 +Test: [1700/2573] eta: 0:01:11 time: 0.0777 data: 0.0014 max mem: 33370 +Test: [1800/2573] eta: 0:01:03 time: 0.0806 data: 0.0014 max mem: 33370 +Test: [1900/2573] eta: 0:00:55 time: 0.0780 data: 0.0014 max mem: 33370 +Test: [2000/2573] eta: 0:00:46 time: 0.0789 data: 0.0014 max mem: 33370 +Test: [2100/2573] eta: 0:00:38 time: 0.0815 data: 0.0014 max mem: 33370 +Test: [2200/2573] eta: 0:00:30 time: 0.0806 data: 0.0014 max mem: 33370 +Test: [2300/2573] eta: 0:00:22 time: 0.0811 data: 0.0014 max mem: 33370 +Test: [2400/2573] eta: 0:00:14 time: 0.0761 data: 0.0014 max mem: 33370 +Test: [2500/2573] eta: 0:00:05 time: 0.0792 data: 0.0014 max mem: 33370 +Test: Total time: 0:03:29 +Final results: +Mean IoU is 63.18 + + precision@0.5 = 70.92 + precision@0.6 = 65.67 + precision@0.7 = 59.09 + precision@0.8 = 47.57 + precision@0.9 = 23.79 + overall IoU = 60.83 + +Average object IoU 63.17779816425833 +Overall IoU 60.82572937011719 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [22] [ 0/1319] eta: 3:40:20 lr: 2.4369398138885975e-05 loss: 0.0435 (0.0435) time: 10.0231 data: 3.5876 max mem: 33370 +Epoch: [22] [ 10/1319] eta: 1:27:43 lr: 2.436015972419942e-05 loss: 0.0435 (0.0430) time: 4.0206 data: 0.3320 max mem: 33370 +Epoch: [22] [ 20/1319] eta: 1:20:33 lr: 2.4350920920207323e-05 loss: 0.0466 (0.0554) time: 3.4061 data: 0.0067 max mem: 33370 +Epoch: [22] [ 30/1319] eta: 1:17:30 lr: 2.4341681726729162e-05 loss: 0.0487 (0.0518) time: 3.3810 data: 0.0072 max mem: 33370 +Epoch: [22] [ 40/1319] eta: 1:15:42 lr: 2.4332442143584247e-05 loss: 0.0487 (0.0528) time: 3.3733 data: 0.0076 max mem: 33370 +Epoch: [22] [ 50/1319] eta: 1:14:24 lr: 2.4323202170591704e-05 loss: 0.0528 (0.0528) time: 3.3779 data: 0.0078 max mem: 33370 +Epoch: [22] [ 60/1319] eta: 1:13:20 lr: 2.4313961807570534e-05 loss: 0.0495 (0.0533) time: 3.3806 data: 0.0079 max mem: 33370 +Epoch: [22] [ 70/1319] eta: 1:12:19 lr: 2.430472105433956e-05 loss: 0.0391 (0.0518) time: 3.3637 data: 0.0076 max mem: 33370 +Epoch: [22] [ 80/1319] eta: 1:11:33 lr: 2.4295479910717442e-05 loss: 0.0416 (0.0512) time: 3.3731 data: 0.0076 max mem: 33370 +Epoch: [22] [ 90/1319] eta: 1:10:44 lr: 2.4286238376522685e-05 loss: 0.0417 (0.0500) time: 3.3792 data: 0.0078 max mem: 33370 +Epoch: [22] [ 100/1319] eta: 1:09:59 lr: 2.4276996451573638e-05 loss: 0.0417 (0.0496) time: 3.3650 data: 0.0079 max mem: 33370 +Epoch: [22] [ 110/1319] eta: 1:09:17 lr: 2.426775413568847e-05 loss: 0.0417 (0.0495) time: 3.3706 data: 0.0083 max mem: 33370 +Epoch: [22] [ 120/1319] eta: 1:08:31 lr: 2.4258511428685206e-05 loss: 0.0417 (0.0495) time: 3.3474 data: 0.0079 max mem: 33370 +Epoch: [22] [ 130/1319] eta: 1:07:51 lr: 2.4249268330381702e-05 loss: 0.0405 (0.0489) time: 3.3473 data: 0.0075 max mem: 33370 +Epoch: [22] [ 140/1319] eta: 1:07:10 lr: 2.4240024840595657e-05 loss: 0.0412 (0.0488) time: 3.3533 data: 0.0078 max mem: 33370 +Epoch: [22] [ 150/1319] eta: 1:06:33 lr: 2.4230780959144606e-05 loss: 0.0426 (0.0489) time: 3.3598 data: 0.0083 max mem: 33370 +Epoch: [22] [ 160/1319] eta: 1:05:54 lr: 2.4221536685845908e-05 loss: 0.0454 (0.0491) time: 3.3691 data: 0.0083 max mem: 33370 +Epoch: [22] [ 170/1319] eta: 1:05:18 lr: 2.421229202051678e-05 loss: 0.0454 (0.0487) time: 3.3649 data: 0.0078 max mem: 33370 +Epoch: [22] [ 180/1319] eta: 1:04:43 lr: 2.420304696297427e-05 loss: 0.0448 (0.0486) time: 3.3853 data: 0.0078 max mem: 33370 +Epoch: [22] [ 190/1319] eta: 1:04:06 lr: 2.419380151303525e-05 loss: 0.0426 (0.0484) time: 3.3853 data: 0.0080 max mem: 33370 +Epoch: [22] [ 200/1319] eta: 1:03:32 lr: 2.418455567051645e-05 loss: 0.0462 (0.0486) time: 3.3872 data: 0.0081 max mem: 33370 +Epoch: [22] [ 210/1319] eta: 1:02:59 lr: 2.417530943523442e-05 loss: 0.0463 (0.0488) time: 3.4114 data: 0.0078 max mem: 33370 +Epoch: [22] [ 220/1319] eta: 1:02:22 lr: 2.416606280700555e-05 loss: 0.0371 (0.0482) time: 3.3840 data: 0.0073 max mem: 33370 +Epoch: [22] [ 230/1319] eta: 1:01:47 lr: 2.4156815785646067e-05 loss: 0.0374 (0.0488) time: 3.3650 data: 0.0074 max mem: 33370 +Epoch: [22] [ 240/1319] eta: 1:01:13 lr: 2.414756837097204e-05 loss: 0.0437 (0.0486) time: 3.3935 data: 0.0076 max mem: 33370 +Epoch: [22] [ 250/1319] eta: 1:00:39 lr: 2.4138320562799363e-05 loss: 0.0437 (0.0485) time: 3.4107 data: 0.0078 max mem: 33370 +Epoch: [22] [ 260/1319] eta: 1:00:06 lr: 2.412907236094378e-05 loss: 0.0476 (0.0488) time: 3.4234 data: 0.0078 max mem: 33370 +Epoch: [22] [ 270/1319] eta: 0:59:31 lr: 2.411982376522085e-05 loss: 0.0442 (0.0487) time: 3.4080 data: 0.0076 max mem: 33370 +Epoch: [22] [ 280/1319] eta: 0:58:57 lr: 2.411057477544598e-05 loss: 0.0396 (0.0487) time: 3.3911 data: 0.0078 max mem: 33370 +Epoch: [22] [ 290/1319] eta: 0:58:23 lr: 2.4101325391434414e-05 loss: 0.0422 (0.0487) time: 3.4049 data: 0.0079 max mem: 33370 +Epoch: [22] [ 300/1319] eta: 0:57:49 lr: 2.4092075613001218e-05 loss: 0.0422 (0.0486) time: 3.4125 data: 0.0079 max mem: 33370 +Epoch: [22] [ 310/1319] eta: 0:57:17 lr: 2.4082825439961318e-05 loss: 0.0395 (0.0486) time: 3.4315 data: 0.0079 max mem: 33370 +Epoch: [22] [ 320/1319] eta: 0:56:42 lr: 2.4073574872129434e-05 loss: 0.0441 (0.0486) time: 3.4144 data: 0.0080 max mem: 33370 +Epoch: [22] [ 330/1319] eta: 0:56:07 lr: 2.4064323909320154e-05 loss: 0.0481 (0.0485) time: 3.3768 data: 0.0081 max mem: 33370 +Epoch: [22] [ 340/1319] eta: 0:55:32 lr: 2.405507255134789e-05 loss: 0.0482 (0.0488) time: 3.3751 data: 0.0079 max mem: 33370 +Epoch: [22] [ 350/1319] eta: 0:54:57 lr: 2.404582079802688e-05 loss: 0.0428 (0.0486) time: 3.3790 data: 0.0077 max mem: 33370 +Epoch: [22] [ 360/1319] eta: 0:54:22 lr: 2.4036568649171213e-05 loss: 0.0431 (0.0489) time: 3.3715 data: 0.0077 max mem: 33370 +Epoch: [22] [ 370/1319] eta: 0:53:49 lr: 2.402731610459478e-05 loss: 0.0497 (0.0490) time: 3.3892 data: 0.0079 max mem: 33370 +Epoch: [22] [ 380/1319] eta: 0:53:14 lr: 2.401806316411133e-05 loss: 0.0421 (0.0488) time: 3.4048 data: 0.0081 max mem: 33370 +Epoch: [22] [ 390/1319] eta: 0:52:41 lr: 2.400880982753445e-05 loss: 0.0421 (0.0490) time: 3.4126 data: 0.0083 max mem: 33370 +Epoch: [22] [ 400/1319] eta: 0:52:07 lr: 2.399955609467753e-05 loss: 0.0517 (0.0498) time: 3.4220 data: 0.0085 max mem: 33370 +Epoch: [22] [ 410/1319] eta: 0:51:32 lr: 2.3990301965353823e-05 loss: 0.0513 (0.0498) time: 3.3931 data: 0.0083 max mem: 33370 +Epoch: [22] [ 420/1319] eta: 0:50:57 lr: 2.39810474393764e-05 loss: 0.0417 (0.0497) time: 3.3664 data: 0.0079 max mem: 33370 +Epoch: [22] [ 430/1319] eta: 0:50:23 lr: 2.3971792516558155e-05 loss: 0.0382 (0.0494) time: 3.3663 data: 0.0078 max mem: 33370 +Epoch: [22] [ 440/1319] eta: 0:49:48 lr: 2.3962537196711826e-05 loss: 0.0396 (0.0494) time: 3.3791 data: 0.0082 max mem: 33370 +Epoch: [22] [ 450/1319] eta: 0:49:14 lr: 2.3953281479649982e-05 loss: 0.0440 (0.0494) time: 3.3707 data: 0.0083 max mem: 33370 +Epoch: [22] [ 460/1319] eta: 0:48:40 lr: 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2.322080833697593e-05 loss: 0.0455 (0.0489) time: 3.4565 data: 0.0088 max mem: 33370 +Epoch: [22] [1250/1319] eta: 0:03:55 lr: 2.3211520220014678e-05 loss: 0.0470 (0.0489) time: 3.4436 data: 0.0090 max mem: 33370 +Epoch: [22] [1260/1319] eta: 0:03:21 lr: 2.320223169007385e-05 loss: 0.0382 (0.0488) time: 3.4331 data: 0.0093 max mem: 33370 +Epoch: [22] [1270/1319] eta: 0:02:47 lr: 2.319294274695137e-05 loss: 0.0382 (0.0488) time: 3.4591 data: 0.0096 max mem: 33370 +Epoch: [22] [1280/1319] eta: 0:02:13 lr: 2.318365339044496e-05 loss: 0.0432 (0.0488) time: 3.4637 data: 0.0099 max mem: 33370 +Epoch: [22] [1290/1319] eta: 0:01:38 lr: 2.3174363620352174e-05 loss: 0.0460 (0.0489) time: 3.4933 data: 0.0091 max mem: 33370 +Epoch: [22] [1300/1319] eta: 0:01:04 lr: 2.3165073436470368e-05 loss: 0.0515 (0.0489) time: 3.4923 data: 0.0081 max mem: 33370 +Epoch: [22] [1310/1319] eta: 0:00:30 lr: 2.3155782838596706e-05 loss: 0.0508 (0.0489) time: 3.4616 data: 0.0080 max mem: 33370 +Epoch: [22] Total time: 1:15:05 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 2:08:45 time: 3.0025 data: 2.8008 max mem: 33370 +Test: [ 100/2573] eta: 0:04:25 time: 0.0782 data: 0.0016 max mem: 33370 +Test: [ 200/2573] eta: 0:03:43 time: 0.0792 data: 0.0015 max mem: 33370 +Test: [ 300/2573] eta: 0:03:22 time: 0.0805 data: 0.0014 max mem: 33370 +Test: [ 400/2573] eta: 0:03:08 time: 0.0807 data: 0.0014 max mem: 33370 +Test: [ 500/2573] eta: 0:02:56 time: 0.0798 data: 0.0015 max mem: 33370 +Test: [ 600/2573] eta: 0:02:46 time: 0.0805 data: 0.0015 max mem: 33370 +Test: [ 700/2573] eta: 0:02:37 time: 0.0803 data: 0.0015 max mem: 33370 +Test: [ 800/2573] eta: 0:02:29 time: 0.0838 data: 0.0015 max mem: 33370 +Test: [ 900/2573] eta: 0:02:20 time: 0.0803 data: 0.0015 max mem: 33370 +Test: [1000/2573] eta: 0:02:11 time: 0.0807 data: 0.0015 max mem: 33370 +Test: [1100/2573] eta: 0:02:02 time: 0.0825 data: 0.0015 max mem: 33370 +Test: [1200/2573] eta: 0:01:54 time: 0.0809 data: 0.0014 max mem: 33370 +Test: [1300/2573] eta: 0:01:45 time: 0.0810 data: 0.0015 max mem: 33370 +Test: [1400/2573] eta: 0:01:37 time: 0.0786 data: 0.0015 max mem: 33370 +Test: [1500/2573] eta: 0:01:28 time: 0.0803 data: 0.0015 max mem: 33370 +Test: [1600/2573] eta: 0:01:20 time: 0.0835 data: 0.0015 max mem: 33370 +Test: [1700/2573] eta: 0:01:12 time: 0.0790 data: 0.0015 max mem: 33370 +Test: [1800/2573] eta: 0:01:03 time: 0.0824 data: 0.0015 max mem: 33370 +Test: [1900/2573] eta: 0:00:55 time: 0.0788 data: 0.0015 max mem: 33370 +Test: [2000/2573] eta: 0:00:47 time: 0.0806 data: 0.0016 max mem: 33370 +Test: [2100/2573] eta: 0:00:38 time: 0.0823 data: 0.0016 max mem: 33370 +Test: [2200/2573] eta: 0:00:30 time: 0.0824 data: 0.0015 max mem: 33370 +Test: [2300/2573] eta: 0:00:22 time: 0.0823 data: 0.0015 max mem: 33370 +Test: [2400/2573] eta: 0:00:14 time: 0.0777 data: 0.0016 max mem: 33370 +Test: [2500/2573] eta: 0:00:05 time: 0.0805 data: 0.0016 max mem: 33370 +Test: Total time: 0:03:31 +Final results: +Mean IoU is 63.59 + + precision@0.5 = 71.00 + precision@0.6 = 66.03 + precision@0.7 = 59.13 + precision@0.8 = 47.45 + precision@0.9 = 23.65 + overall IoU = 61.30 + +Average object IoU 63.58642892201212 +Overall IoU 61.29557418823242 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [23] [ 0/1319] eta: 3:33:21 lr: 2.3147420946379584e-05 loss: 0.0785 (0.0785) time: 9.7053 data: 2.5404 max mem: 33370 +Epoch: [23] [ 10/1319] eta: 1:27:38 lr: 2.313812956136191e-05 loss: 0.0420 (0.0466) time: 4.0170 data: 0.2397 max mem: 33370 +Epoch: [23] [ 20/1319] eta: 1:21:23 lr: 2.3128837761763095e-05 loss: 0.0456 (0.0484) time: 3.4619 data: 0.0090 max mem: 33370 +Epoch: [23] [ 30/1319] eta: 1:18:19 lr: 2.3119545547379566e-05 loss: 0.0456 (0.0472) time: 3.4419 data: 0.0089 max mem: 33370 +Epoch: [23] [ 40/1319] eta: 1:16:53 lr: 2.3110252918007542e-05 loss: 0.0394 (0.0465) time: 3.4481 data: 0.0094 max mem: 33370 +Epoch: [23] [ 50/1319] eta: 1:15:52 lr: 2.3100959873443074e-05 loss: 0.0390 (0.0459) time: 3.4969 data: 0.0090 max mem: 33370 +Epoch: [23] [ 60/1319] eta: 1:14:45 lr: 2.3091666413482015e-05 loss: 0.0390 (0.0466) time: 3.4720 data: 0.0090 max mem: 33370 +Epoch: [23] [ 70/1319] eta: 1:13:54 lr: 2.3082372537920018e-05 loss: 0.0359 (0.0466) time: 3.4568 data: 0.0090 max mem: 33370 +Epoch: [23] [ 80/1319] eta: 1:13:12 lr: 2.307307824655256e-05 loss: 0.0379 (0.0466) time: 3.4916 data: 0.0091 max mem: 33370 +Epoch: [23] [ 90/1319] eta: 1:12:18 lr: 2.3063783539174907e-05 loss: 0.0447 (0.0460) time: 3.4568 data: 0.0091 max mem: 33370 +Epoch: [23] [ 100/1319] eta: 1:11:29 lr: 2.3054488415582145e-05 loss: 0.0387 (0.0460) time: 3.4097 data: 0.0088 max mem: 33370 +Epoch: [23] [ 110/1319] eta: 1:10:52 lr: 2.3045192875569164e-05 loss: 0.0398 (0.0461) time: 3.4603 data: 0.0088 max mem: 33370 +Epoch: [23] [ 120/1319] eta: 1:10:09 lr: 2.3035896918930662e-05 loss: 0.0460 (0.0469) time: 3.4744 data: 0.0087 max mem: 33370 +Epoch: [23] [ 130/1319] eta: 1:09:31 lr: 2.3026600545461138e-05 loss: 0.0485 (0.0478) time: 3.4555 data: 0.0091 max mem: 33370 +Epoch: [23] [ 140/1319] eta: 1:08:55 lr: 2.3017303754954915e-05 loss: 0.0447 (0.0479) time: 3.4861 data: 0.0092 max mem: 33370 +Epoch: [23] [ 150/1319] eta: 1:08:17 lr: 2.300800654720609e-05 loss: 0.0424 (0.0473) time: 3.4868 data: 0.0092 max mem: 33370 +Epoch: [23] [ 160/1319] eta: 1:07:36 lr: 2.2998708922008593e-05 loss: 0.0424 (0.0474) time: 3.4477 data: 0.0098 max mem: 33370 +Epoch: [23] [ 170/1319] eta: 1:06:57 lr: 2.2989410879156158e-05 loss: 0.0485 (0.0475) time: 3.4271 data: 0.0100 max mem: 33370 +Epoch: [23] [ 180/1319] eta: 1:06:23 lr: 2.298011241844231e-05 loss: 0.0461 (0.0474) time: 3.4711 data: 0.0092 max mem: 33370 +Epoch: [23] [ 190/1319] eta: 1:05:43 lr: 2.2970813539660394e-05 loss: 0.0410 (0.0471) time: 3.4678 data: 0.0089 max mem: 33370 +Epoch: [23] [ 200/1319] eta: 1:05:07 lr: 2.296151424260354e-05 loss: 0.0416 (0.0471) time: 3.4471 data: 0.0090 max mem: 33370 +Epoch: [23] [ 210/1319] eta: 1:04:28 lr: 2.2952214527064705e-05 loss: 0.0420 (0.0470) time: 3.4387 data: 0.0088 max mem: 33370 +Epoch: [23] [ 220/1319] eta: 1:03:51 lr: 2.294291439283664e-05 loss: 0.0392 (0.0469) time: 3.4281 data: 0.0086 max mem: 33370 +Epoch: [23] [ 230/1319] eta: 1:03:13 lr: 2.2933613839711898e-05 loss: 0.0447 (0.0470) time: 3.4349 data: 0.0086 max mem: 33370 +Epoch: [23] [ 240/1319] eta: 1:02:34 lr: 2.292431286748284e-05 loss: 0.0461 (0.0468) time: 3.4055 data: 0.0087 max mem: 33370 +Epoch: [23] [ 250/1319] eta: 1:01:57 lr: 2.2915011475941626e-05 loss: 0.0403 (0.0464) time: 3.4136 data: 0.0087 max mem: 33370 +Epoch: [23] [ 260/1319] eta: 1:01:18 lr: 2.2905709664880228e-05 loss: 0.0403 (0.0468) time: 3.4052 data: 0.0084 max mem: 33370 +Epoch: [23] [ 270/1319] eta: 1:00:41 lr: 2.28964074340904e-05 loss: 0.0341 (0.0467) time: 3.3893 data: 0.0080 max mem: 33370 +Epoch: [23] [ 280/1319] eta: 1:00:02 lr: 2.2887104783363728e-05 loss: 0.0386 (0.0465) time: 3.3759 data: 0.0078 max mem: 33370 +Epoch: [23] [ 290/1319] eta: 0:59:24 lr: 2.2877801712491578e-05 loss: 0.0393 (0.0465) time: 3.3646 data: 0.0082 max mem: 33370 +Epoch: [23] [ 300/1319] eta: 0:58:48 lr: 2.2868498221265136e-05 loss: 0.0426 (0.0465) time: 3.3974 data: 0.0088 max mem: 33370 +Epoch: [23] [ 310/1319] eta: 0:58:12 lr: 2.2859194309475363e-05 loss: 0.0420 (0.0464) time: 3.4242 data: 0.0087 max mem: 33370 +Epoch: [23] [ 320/1319] eta: 0:57:36 lr: 2.2849889976913045e-05 loss: 0.0435 (0.0465) time: 3.4175 data: 0.0082 max mem: 33370 +Epoch: [23] [ 330/1319] eta: 0:57:00 lr: 2.2840585223368763e-05 loss: 0.0426 (0.0464) time: 3.4133 data: 0.0080 max mem: 33370 +Epoch: [23] [ 340/1319] eta: 0:56:25 lr: 2.2831280048632893e-05 loss: 0.0402 (0.0464) time: 3.4356 data: 0.0085 max mem: 33370 +Epoch: [23] [ 350/1319] eta: 0:55:48 lr: 2.282197445249563e-05 loss: 0.0408 (0.0462) time: 3.4140 data: 0.0085 max mem: 33370 +Epoch: [23] [ 360/1319] eta: 0:55:13 lr: 2.2812668434746943e-05 loss: 0.0408 (0.0461) time: 3.4077 data: 0.0087 max mem: 33370 +Epoch: [23] [ 370/1319] eta: 0:54:38 lr: 2.2803361995176614e-05 loss: 0.0453 (0.0463) time: 3.4371 data: 0.0089 max mem: 33370 +Epoch: [23] [ 380/1319] eta: 0:54:04 lr: 2.279405513357423e-05 loss: 0.0453 (0.0464) time: 3.4576 data: 0.0081 max mem: 33370 +Epoch: [23] [ 390/1319] eta: 0:53:28 lr: 2.278474784972917e-05 loss: 0.0449 (0.0465) time: 3.4347 data: 0.0079 max mem: 33370 +Epoch: [23] [ 400/1319] eta: 0:52:53 lr: 2.277544014343061e-05 loss: 0.0472 (0.0465) time: 3.4162 data: 0.0082 max mem: 33370 +Epoch: [23] [ 410/1319] eta: 0:52:18 lr: 2.2766132014467546e-05 loss: 0.0375 (0.0463) time: 3.4238 data: 0.0090 max mem: 33370 +Epoch: [23] [ 420/1319] eta: 0:51:42 lr: 2.2756823462628737e-05 loss: 0.0356 (0.0461) time: 3.3967 data: 0.0089 max mem: 33370 +Epoch: [23] [ 430/1319] eta: 0:51:06 lr: 2.2747514487702767e-05 loss: 0.0361 (0.0459) time: 3.3982 data: 0.0089 max mem: 33370 +Epoch: [23] [ 440/1319] eta: 0:50:30 lr: 2.2738205089478008e-05 loss: 0.0360 (0.0459) time: 3.3942 data: 0.0086 max mem: 33370 +Epoch: [23] [ 450/1319] eta: 0:49:55 lr: 2.272889526774264e-05 loss: 0.0418 (0.0459) time: 3.3965 data: 0.0083 max mem: 33370 +Epoch: [23] [ 460/1319] eta: 0:49:20 lr: 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mem: 33370 +Epoch: [23] [1010/1319] eta: 0:17:41 lr: 2.2206862697871013e-05 loss: 0.0456 (0.0462) time: 3.4473 data: 0.0082 max mem: 33370 +Epoch: [23] [1020/1319] eta: 0:17:06 lr: 2.2197528379165116e-05 loss: 0.0467 (0.0462) time: 3.4561 data: 0.0085 max mem: 33370 +Epoch: [23] [1030/1319] eta: 0:16:32 lr: 2.218819362430666e-05 loss: 0.0408 (0.0462) time: 3.4253 data: 0.0087 max mem: 33370 +Epoch: [23] [1040/1319] eta: 0:15:57 lr: 2.217885843307136e-05 loss: 0.0417 (0.0462) time: 3.4098 data: 0.0089 max mem: 33370 +Epoch: [23] [1050/1319] eta: 0:15:23 lr: 2.2169522805234726e-05 loss: 0.0495 (0.0463) time: 3.4028 data: 0.0090 max mem: 33370 +Epoch: [23] [1060/1319] eta: 0:14:49 lr: 2.2160186740572026e-05 loss: 0.0402 (0.0463) time: 3.3800 data: 0.0086 max mem: 33370 +Epoch: [23] [1070/1319] eta: 0:14:14 lr: 2.215085023885832e-05 loss: 0.0402 (0.0463) time: 3.4103 data: 0.0081 max mem: 33370 +Epoch: [23] [1080/1319] eta: 0:13:40 lr: 2.2141513299868444e-05 loss: 0.0520 (0.0463) time: 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2.199206262187655e-05 loss: 0.0454 (0.0462) time: 3.4117 data: 0.0087 max mem: 33370 +Epoch: [23] [1250/1319] eta: 0:03:56 lr: 2.1982718214526003e-05 loss: 0.0442 (0.0462) time: 3.4121 data: 0.0084 max mem: 33370 +Epoch: [23] [1260/1319] eta: 0:03:22 lr: 2.1973373365808168e-05 loss: 0.0401 (0.0462) time: 3.4169 data: 0.0084 max mem: 33370 +Epoch: [23] [1270/1319] eta: 0:02:48 lr: 2.1964028075493602e-05 loss: 0.0447 (0.0463) time: 3.4326 data: 0.0082 max mem: 33370 +Epoch: [23] [1280/1319] eta: 0:02:13 lr: 2.1954682343352655e-05 loss: 0.0456 (0.0463) time: 3.4209 data: 0.0084 max mem: 33370 +Epoch: [23] [1290/1319] eta: 0:01:39 lr: 2.1945336169155447e-05 loss: 0.0456 (0.0464) time: 3.4530 data: 0.0080 max mem: 33370 +Epoch: [23] [1300/1319] eta: 0:01:05 lr: 2.1935989552671862e-05 loss: 0.0465 (0.0465) time: 3.4380 data: 0.0077 max mem: 33370 +Epoch: [23] [1310/1319] eta: 0:00:30 lr: 2.192664249367156e-05 loss: 0.0476 (0.0464) time: 3.4188 data: 0.0077 max mem: 33370 +Epoch: [23] Total time: 1:15:28 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 2:38:40 time: 3.7001 data: 3.5891 max mem: 33370 +Test: [ 100/2573] eta: 0:04:42 time: 0.0784 data: 0.0014 max mem: 33370 +Test: [ 200/2573] eta: 0:03:51 time: 0.0801 data: 0.0016 max mem: 33370 +Test: [ 300/2573] eta: 0:03:27 time: 0.0815 data: 0.0015 max mem: 33370 +Test: [ 400/2573] eta: 0:03:12 time: 0.0809 data: 0.0014 max mem: 33370 +Test: [ 500/2573] eta: 0:03:00 time: 0.0819 data: 0.0016 max mem: 33370 +Test: [ 600/2573] eta: 0:02:49 time: 0.0807 data: 0.0016 max mem: 33370 +Test: [ 700/2573] eta: 0:02:40 time: 0.0806 data: 0.0015 max mem: 33370 +Test: [ 800/2573] eta: 0:02:31 time: 0.0835 data: 0.0015 max mem: 33370 +Test: [ 900/2573] eta: 0:02:21 time: 0.0807 data: 0.0015 max mem: 33370 +Test: [1000/2573] eta: 0:02:12 time: 0.0808 data: 0.0014 max mem: 33370 +Test: [1100/2573] eta: 0:02:03 time: 0.0813 data: 0.0015 max mem: 33370 +Test: [1200/2573] eta: 0:01:55 time: 0.0816 data: 0.0014 max mem: 33370 +Test: [1300/2573] eta: 0:01:46 time: 0.0812 data: 0.0014 max mem: 33370 +Test: [1400/2573] eta: 0:01:37 time: 0.0789 data: 0.0014 max mem: 33370 +Test: [1500/2573] eta: 0:01:29 time: 0.0801 data: 0.0014 max mem: 33370 +Test: [1600/2573] eta: 0:01:20 time: 0.0836 data: 0.0013 max mem: 33370 +Test: [1700/2573] eta: 0:01:12 time: 0.0789 data: 0.0014 max mem: 33370 +Test: [1800/2573] eta: 0:01:04 time: 0.0825 data: 0.0015 max mem: 33370 +Test: [1900/2573] eta: 0:00:55 time: 0.0799 data: 0.0014 max mem: 33370 +Test: [2000/2573] eta: 0:00:47 time: 0.0805 data: 0.0014 max mem: 33370 +Test: [2100/2573] eta: 0:00:39 time: 0.0831 data: 0.0016 max mem: 33370 +Test: [2200/2573] eta: 0:00:30 time: 0.0815 data: 0.0015 max mem: 33370 +Test: [2300/2573] eta: 0:00:22 time: 0.0821 data: 0.0015 max mem: 33370 +Test: [2400/2573] eta: 0:00:14 time: 0.0788 data: 0.0016 max mem: 33370 +Test: [2500/2573] eta: 0:00:06 time: 0.0811 data: 0.0015 max mem: 33370 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: Total time: 0:03:32 +Final results: +Mean IoU is 63.48 + + precision@0.5 = 71.16 + precision@0.6 = 65.46 + precision@0.7 = 59.27 + precision@0.8 = 48.08 + precision@0.9 = 23.84 + overall IoU = 60.65 + +Average object IoU 63.47989991993067 +Overall IoU 60.646324157714844 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [24] [ 0/1319] eta: 3:04:32 lr: 2.1918229762028934e-05 loss: 0.0631 (0.0631) time: 8.3943 data: 2.0503 max mem: 33370 +Epoch: [24] [ 10/1319] eta: 1:24:23 lr: 2.1908881861611456e-05 loss: 0.0432 (0.0434) time: 3.8685 data: 0.1937 max mem: 33370 +Epoch: [24] [ 20/1319] eta: 1:18:55 lr: 2.1899533518007982e-05 loss: 0.0413 (0.0451) time: 3.4077 data: 0.0080 max mem: 33370 +Epoch: [24] [ 30/1319] eta: 1:16:39 lr: 2.189018473098726e-05 loss: 0.0386 (0.0436) time: 3.4032 data: 0.0082 max mem: 33370 +Epoch: [24] [ 40/1319] eta: 1:15:10 lr: 2.188083550031783e-05 loss: 0.0339 (0.0419) time: 3.4027 data: 0.0086 max mem: 33370 +Epoch: [24] [ 50/1319] eta: 1:14:06 lr: 2.1871485825767997e-05 loss: 0.0384 (0.0436) time: 3.4036 data: 0.0083 max mem: 33370 +Epoch: [24] [ 60/1319] eta: 1:13:12 lr: 2.1862135707105826e-05 loss: 0.0384 (0.0444) time: 3.4106 data: 0.0085 max mem: 33370 +Epoch: [24] [ 70/1319] eta: 1:12:19 lr: 2.1852785144099174e-05 loss: 0.0382 (0.0441) time: 3.4009 data: 0.0085 max mem: 33370 +Epoch: [24] [ 80/1319] eta: 1:11:36 lr: 2.184343413651562e-05 loss: 0.0425 (0.0445) time: 3.4037 data: 0.0080 max mem: 33370 +Epoch: [24] [ 90/1319] eta: 1:10:56 lr: 2.1834082684122557e-05 loss: 0.0394 (0.0438) time: 3.4236 data: 0.0079 max mem: 33370 +Epoch: [24] [ 100/1319] eta: 1:10:16 lr: 2.1824730786687132e-05 loss: 0.0395 (0.0441) time: 3.4249 data: 0.0082 max mem: 33370 +Epoch: [24] [ 110/1319] eta: 1:09:38 lr: 2.181537844397624e-05 loss: 0.0441 (0.0439) time: 3.4237 data: 0.0084 max mem: 33370 +Epoch: [24] [ 120/1319] eta: 1:09:00 lr: 2.1806025655756576e-05 loss: 0.0399 (0.0438) time: 3.4243 data: 0.0085 max mem: 33370 +Epoch: [24] [ 130/1319] eta: 1:08:24 lr: 2.1796672421794575e-05 loss: 0.0399 (0.0437) time: 3.4291 data: 0.0091 max mem: 33370 +Epoch: [24] [ 140/1319] eta: 1:07:51 lr: 2.1787318741856443e-05 loss: 0.0364 (0.0438) time: 3.4515 data: 0.0087 max mem: 33370 +Epoch: [24] [ 150/1319] eta: 1:07:17 lr: 2.1777964615708157e-05 loss: 0.0343 (0.0433) time: 3.4624 data: 0.0081 max mem: 33370 +Epoch: [24] [ 160/1319] eta: 1:06:40 lr: 2.1768610043115462e-05 loss: 0.0415 (0.0439) time: 3.4416 data: 0.0080 max mem: 33370 +Epoch: [24] [ 170/1319] eta: 1:06:04 lr: 2.1759255023843863e-05 loss: 0.0451 (0.0440) time: 3.4291 data: 0.0079 max mem: 33370 +Epoch: [24] [ 180/1319] eta: 1:05:29 lr: 2.1749899557658636e-05 loss: 0.0439 (0.0443) time: 3.4382 data: 0.0081 max mem: 33370 +Epoch: [24] [ 190/1319] eta: 1:04:56 lr: 2.17405436443248e-05 loss: 0.0407 (0.0442) time: 3.4524 data: 0.0081 max mem: 33370 +Epoch: [24] [ 200/1319] eta: 1:04:22 lr: 2.1731187283607167e-05 loss: 0.0389 (0.0438) time: 3.4626 data: 0.0081 max mem: 33370 +Epoch: [24] [ 210/1319] eta: 1:03:47 lr: 2.17218304752703e-05 loss: 0.0405 (0.0444) time: 3.4536 data: 0.0084 max mem: 33370 +Epoch: [24] [ 220/1319] eta: 1:03:11 lr: 2.171247321907852e-05 loss: 0.0498 (0.0445) time: 3.4321 data: 0.0085 max mem: 33370 +Epoch: [24] [ 230/1319] eta: 1:02:36 lr: 2.1703115514795925e-05 loss: 0.0467 (0.0446) time: 3.4319 data: 0.0083 max mem: 33370 +Epoch: [24] [ 240/1319] eta: 1:02:01 lr: 2.1693757362186356e-05 loss: 0.0476 (0.0451) time: 3.4457 data: 0.0080 max mem: 33370 +Epoch: [24] [ 250/1319] eta: 1:01:24 lr: 2.1684398761013434e-05 loss: 0.0403 (0.0451) time: 3.4197 data: 0.0080 max mem: 33370 +Epoch: [24] [ 260/1319] eta: 1:00:48 lr: 2.1675039711040532e-05 loss: 0.0399 (0.0450) time: 3.3957 data: 0.0086 max mem: 33370 +Epoch: [24] [ 270/1319] eta: 1:00:13 lr: 2.166568021203079e-05 loss: 0.0385 (0.0448) time: 3.4147 data: 0.0087 max mem: 33370 +Epoch: [24] [ 280/1319] eta: 0:59:38 lr: 2.1656320263747106e-05 loss: 0.0388 (0.0445) time: 3.4298 data: 0.0083 max mem: 33370 +Epoch: [24] [ 290/1319] eta: 0:59:03 lr: 2.164695986595215e-05 loss: 0.0410 (0.0444) time: 3.4260 data: 0.0081 max mem: 33370 +Epoch: [24] [ 300/1319] eta: 0:58:27 lr: 2.163759901840832e-05 loss: 0.0396 (0.0442) time: 3.4177 data: 0.0083 max mem: 33370 +Epoch: [24] [ 310/1319] eta: 0:57:52 lr: 2.1628237720877814e-05 loss: 0.0396 (0.0444) time: 3.4196 data: 0.0084 max mem: 33370 +Epoch: [24] [ 320/1319] eta: 0:57:17 lr: 2.161887597312257e-05 loss: 0.0456 (0.0445) time: 3.4175 data: 0.0083 max mem: 33370 +Epoch: [24] [ 330/1319] eta: 0:56:41 lr: 2.160951377490428e-05 loss: 0.0425 (0.0446) time: 3.3979 data: 0.0083 max mem: 33370 +Epoch: [24] [ 340/1319] eta: 0:56:05 lr: 2.160015112598442e-05 loss: 0.0378 (0.0445) time: 3.3904 data: 0.0082 max mem: 33370 +Epoch: [24] [ 350/1319] eta: 0:55:30 lr: 2.1590788026124187e-05 loss: 0.0398 (0.0444) time: 3.4023 data: 0.0083 max mem: 33370 +Epoch: [24] [ 360/1319] eta: 0:54:54 lr: 2.158142447508457e-05 loss: 0.0411 (0.0447) time: 3.3929 data: 0.0088 max mem: 33370 +Epoch: [24] [ 370/1319] eta: 0:54:20 lr: 2.1572060472626296e-05 loss: 0.0421 (0.0446) time: 3.4111 data: 0.0086 max mem: 33370 +Epoch: [24] [ 380/1319] eta: 0:53:45 lr: 2.156269601850986e-05 loss: 0.0410 (0.0446) time: 3.4308 data: 0.0084 max mem: 33370 +Epoch: [24] [ 390/1319] eta: 0:53:11 lr: 2.1553331112495514e-05 loss: 0.0396 (0.0447) time: 3.4354 data: 0.0086 max mem: 33370 +Epoch: [24] [ 400/1319] eta: 0:52:36 lr: 2.1543965754343263e-05 loss: 0.0445 (0.0449) time: 3.4222 data: 0.0086 max mem: 33370 +Epoch: [24] [ 410/1319] eta: 0:52:02 lr: 2.1534599943812868e-05 loss: 0.0445 (0.0450) time: 3.4172 data: 0.0087 max mem: 33370 +Epoch: [24] [ 420/1319] eta: 0:51:28 lr: 2.1525233680663844e-05 loss: 0.0383 (0.0449) time: 3.4459 data: 0.0090 max mem: 33370 +Epoch: [24] [ 430/1319] eta: 0:50:53 lr: 2.151586696465547e-05 loss: 0.0378 (0.0451) time: 3.4251 data: 0.0087 max mem: 33370 +Epoch: [24] [ 440/1319] eta: 0:50:19 lr: 2.1506499795546773e-05 loss: 0.0394 (0.0451) time: 3.4256 data: 0.0087 max mem: 33370 +Epoch: [24] [ 450/1319] eta: 0:49:44 lr: 2.1497132173096545e-05 loss: 0.0362 (0.0449) time: 3.4461 data: 0.0092 max mem: 33370 +Epoch: [24] [ 460/1319] eta: 0:49:10 lr: 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eta: 0:22:18 lr: 2.104694837585335e-05 loss: 0.0378 (0.0446) time: 3.4494 data: 0.0089 max mem: 33370 +Epoch: [24] [ 940/1319] eta: 0:21:44 lr: 2.1037558238977907e-05 loss: 0.0311 (0.0445) time: 3.4681 data: 0.0091 max mem: 33370 +Epoch: [24] [ 950/1319] eta: 0:21:09 lr: 2.1028167636379597e-05 loss: 0.0423 (0.0446) time: 3.4626 data: 0.0093 max mem: 33370 +Epoch: [24] [ 960/1319] eta: 0:20:35 lr: 2.1018776567804213e-05 loss: 0.0499 (0.0446) time: 3.4517 data: 0.0090 max mem: 33370 +Epoch: [24] [ 970/1319] eta: 0:20:01 lr: 2.1009385032997278e-05 loss: 0.0393 (0.0445) time: 3.4585 data: 0.0090 max mem: 33370 +Epoch: [24] [ 980/1319] eta: 0:19:26 lr: 2.0999993031704057e-05 loss: 0.0373 (0.0445) time: 3.4529 data: 0.0092 max mem: 33370 +Epoch: [24] [ 990/1319] eta: 0:18:52 lr: 2.0990600563669546e-05 loss: 0.0373 (0.0445) time: 3.4479 data: 0.0091 max mem: 33370 +Epoch: [24] [1000/1319] eta: 0:18:17 lr: 2.0981207628638462e-05 loss: 0.0429 (0.0445) time: 3.4649 data: 0.0093 max mem: 33370 +Epoch: [24] [1010/1319] eta: 0:17:43 lr: 2.0971814226355274e-05 loss: 0.0415 (0.0445) time: 3.4536 data: 0.0089 max mem: 33370 +Epoch: [24] [1020/1319] eta: 0:17:09 lr: 2.0962420356564173e-05 loss: 0.0380 (0.0446) time: 3.4630 data: 0.0087 max mem: 33370 +Epoch: [24] [1030/1319] eta: 0:16:34 lr: 2.0953026019009095e-05 loss: 0.0432 (0.0447) time: 3.4867 data: 0.0094 max mem: 33370 +Epoch: [24] [1040/1319] eta: 0:16:00 lr: 2.0943631213433694e-05 loss: 0.0439 (0.0447) time: 3.4475 data: 0.0092 max mem: 33370 +Epoch: [24] [1050/1319] eta: 0:15:26 lr: 2.0934235939581352e-05 loss: 0.0408 (0.0448) time: 3.4366 data: 0.0089 max mem: 33370 +Epoch: [24] [1060/1319] eta: 0:14:51 lr: 2.0924840197195202e-05 loss: 0.0390 (0.0448) time: 3.4368 data: 0.0091 max mem: 33370 +Epoch: [24] [1070/1319] eta: 0:14:17 lr: 2.0915443986018095e-05 loss: 0.0363 (0.0449) time: 3.4292 data: 0.0089 max mem: 33370 +Epoch: [24] [1080/1319] eta: 0:13:42 lr: 2.0906047305792607e-05 loss: 0.0337 (0.0449) time: 3.4156 data: 0.0088 max mem: 33370 +Epoch: [24] [1090/1319] eta: 0:13:08 lr: 2.0896650156261064e-05 loss: 0.0477 (0.0451) time: 3.4192 data: 0.0086 max mem: 33370 +Epoch: [24] [1100/1319] eta: 0:12:33 lr: 2.0887252537165494e-05 loss: 0.0477 (0.0451) time: 3.4548 data: 0.0086 max mem: 33370 +Epoch: [24] [1110/1319] eta: 0:11:59 lr: 2.087785444824768e-05 loss: 0.0447 (0.0452) time: 3.4673 data: 0.0087 max mem: 33370 +Epoch: [24] [1120/1319] eta: 0:11:25 lr: 2.086845588924912e-05 loss: 0.0462 (0.0452) time: 3.4640 data: 0.0088 max mem: 33370 +Epoch: [24] [1130/1319] eta: 0:10:50 lr: 2.0859056859911038e-05 loss: 0.0493 (0.0453) time: 3.4549 data: 0.0087 max mem: 33370 +Epoch: [24] [1140/1319] eta: 0:10:16 lr: 2.0849657359974397e-05 loss: 0.0597 (0.0455) time: 3.4579 data: 0.0087 max mem: 33370 +Epoch: [24] [1150/1319] eta: 0:09:41 lr: 2.084025738917989e-05 loss: 0.0479 (0.0454) time: 3.4444 data: 0.0089 max mem: 33370 +Epoch: [24] [1160/1319] eta: 0:09:07 lr: 2.083085694726791e-05 loss: 0.0400 (0.0454) time: 3.4315 data: 0.0088 max mem: 33370 +Epoch: [24] [1170/1319] eta: 0:08:32 lr: 2.0821456033978605e-05 loss: 0.0375 (0.0453) time: 3.4342 data: 0.0087 max mem: 33370 +Epoch: [24] [1180/1319] eta: 0:07:58 lr: 2.0812054649051834e-05 loss: 0.0383 (0.0454) time: 3.4308 data: 0.0086 max mem: 33370 +Epoch: [24] [1190/1319] eta: 0:07:24 lr: 2.0802652792227197e-05 loss: 0.0405 (0.0454) time: 3.4484 data: 0.0081 max mem: 33370 +Epoch: [24] [1200/1319] eta: 0:06:49 lr: 2.0793250463244006e-05 loss: 0.0405 (0.0454) time: 3.4385 data: 0.0084 max mem: 33370 +Epoch: [24] [1210/1319] eta: 0:06:15 lr: 2.07838476618413e-05 loss: 0.0437 (0.0454) time: 3.4282 data: 0.0091 max mem: 33370 +Epoch: [24] [1220/1319] eta: 0:05:40 lr: 2.077444438775784e-05 loss: 0.0470 (0.0455) time: 3.4265 data: 0.0093 max mem: 33370 +Epoch: [24] [1230/1319] eta: 0:05:06 lr: 2.0765040640732118e-05 loss: 0.0417 (0.0455) time: 3.4189 data: 0.0093 max mem: 33370 +Epoch: [24] [1240/1319] eta: 0:04:31 lr: 2.0755636420502354e-05 loss: 0.0423 (0.0456) time: 3.4371 data: 0.0090 max mem: 33370 +Epoch: [24] [1250/1319] eta: 0:03:57 lr: 2.074623172680648e-05 loss: 0.0498 (0.0457) time: 3.4310 data: 0.0088 max mem: 33370 +Epoch: [24] [1260/1319] eta: 0:03:23 lr: 2.0736826559382146e-05 loss: 0.0473 (0.0457) time: 3.4172 data: 0.0087 max mem: 33370 +Epoch: [24] [1270/1319] eta: 0:02:48 lr: 2.072742091796674e-05 loss: 0.0458 (0.0457) time: 3.4495 data: 0.0084 max mem: 33370 +Epoch: [24] [1280/1319] eta: 0:02:14 lr: 2.071801480229737e-05 loss: 0.0444 (0.0457) time: 3.4584 data: 0.0089 max mem: 33370 +Epoch: [24] [1290/1319] eta: 0:01:39 lr: 2.0708608212110852e-05 loss: 0.0405 (0.0457) time: 3.4282 data: 0.0091 max mem: 33370 +Epoch: [24] [1300/1319] eta: 0:01:05 lr: 2.0699201147143737e-05 loss: 0.0410 (0.0457) time: 3.4374 data: 0.0087 max mem: 33370 +Epoch: [24] [1310/1319] eta: 0:00:30 lr: 2.0689793607132295e-05 loss: 0.0343 (0.0457) time: 3.4544 data: 0.0083 max mem: 33370 +Epoch: [24] Total time: 1:15:40 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 2:30:49 time: 3.5171 data: 3.3975 max mem: 33370 +Test: [ 100/2573] eta: 0:04:36 time: 0.0775 data: 0.0015 max mem: 33370 +Test: [ 200/2573] eta: 0:03:48 time: 0.0798 data: 0.0016 max mem: 33370 +Test: [ 300/2573] eta: 0:03:25 time: 0.0814 data: 0.0015 max mem: 33370 +Test: [ 400/2573] eta: 0:03:11 time: 0.0823 data: 0.0016 max mem: 33370 +Test: [ 500/2573] eta: 0:02:59 time: 0.0811 data: 0.0015 max mem: 33370 +Test: [ 600/2573] eta: 0:02:49 time: 0.0814 data: 0.0017 max mem: 33370 +Test: [ 700/2573] eta: 0:02:39 time: 0.0810 data: 0.0014 max mem: 33370 +Test: [ 800/2573] eta: 0:02:30 time: 0.0840 data: 0.0014 max mem: 33370 +Test: [ 900/2573] eta: 0:02:21 time: 0.0813 data: 0.0014 max mem: 33370 +Test: [1000/2573] eta: 0:02:12 time: 0.0818 data: 0.0016 max mem: 33370 +Test: [1100/2573] eta: 0:02:03 time: 0.0813 data: 0.0016 max mem: 33370 +Test: [1200/2573] eta: 0:01:55 time: 0.0805 data: 0.0014 max mem: 33370 +Test: [1300/2573] eta: 0:01:46 time: 0.0808 data: 0.0014 max mem: 33370 +Test: [1400/2573] eta: 0:01:37 time: 0.0801 data: 0.0014 max mem: 33370 +Test: [1500/2573] eta: 0:01:29 time: 0.0805 data: 0.0014 max mem: 33370 +Test: [1600/2573] eta: 0:01:20 time: 0.0833 data: 0.0014 max mem: 33370 +Test: [1700/2573] eta: 0:01:12 time: 0.0791 data: 0.0014 max mem: 33370 +Test: [1800/2573] eta: 0:01:04 time: 0.0827 data: 0.0016 max mem: 33370 +Test: [1900/2573] eta: 0:00:55 time: 0.0789 data: 0.0015 max mem: 33370 +Test: [2000/2573] eta: 0:00:47 time: 0.0804 data: 0.0014 max mem: 33370 +Test: [2100/2573] eta: 0:00:38 time: 0.0823 data: 0.0014 max mem: 33370 +Test: [2200/2573] eta: 0:00:30 time: 0.0818 data: 0.0014 max mem: 33370 +Test: [2300/2573] eta: 0:00:22 time: 0.0825 data: 0.0015 max mem: 33370 +Test: [2400/2573] eta: 0:00:14 time: 0.0776 data: 0.0014 max mem: 33370 +Test: [2500/2573] eta: 0:00:05 time: 0.0798 data: 0.0014 max mem: 33370 +Test: Total time: 0:03:31 +Final results: +Mean IoU is 63.58 + + precision@0.5 = 71.47 + precision@0.6 = 65.91 + precision@0.7 = 59.35 + precision@0.8 = 47.88 + precision@0.9 = 24.00 + overall IoU = 61.26 + +Average object IoU 63.57809162401311 +Overall IoU 61.25690841674805 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [25] [ 0/1319] eta: 3:11:09 lr: 2.0681326414740886e-05 loss: 0.0407 (0.0407) time: 8.6957 data: 1.9014 max mem: 33370 +Epoch: [25] [ 10/1319] eta: 1:24:56 lr: 2.0671917971417626e-05 loss: 0.0386 (0.0433) time: 3.8932 data: 0.1812 max mem: 33370 +Epoch: [25] [ 20/1319] eta: 1:19:41 lr: 2.0662509052283616e-05 loss: 0.0389 (0.0437) time: 3.4302 data: 0.0087 max mem: 33370 +Epoch: [25] [ 30/1319] eta: 1:17:38 lr: 2.0653099657074033e-05 loss: 0.0368 (0.0420) time: 3.4607 data: 0.0089 max mem: 33370 +Epoch: [25] [ 40/1319] eta: 1:15:46 lr: 2.064368978552377e-05 loss: 0.0331 (0.0450) time: 3.4217 data: 0.0087 max mem: 33370 +Epoch: [25] [ 50/1319] eta: 1:14:38 lr: 2.0634279437367437e-05 loss: 0.0373 (0.0436) time: 3.3964 data: 0.0081 max mem: 33370 +Epoch: [25] [ 60/1319] eta: 1:13:40 lr: 2.0624868612339364e-05 loss: 0.0371 (0.0427) time: 3.4217 data: 0.0084 max mem: 33370 +Epoch: [25] [ 70/1319] eta: 1:12:45 lr: 2.0615457310173584e-05 loss: 0.0381 (0.0423) time: 3.4102 data: 0.0082 max mem: 33370 +Epoch: [25] [ 80/1319] eta: 1:11:56 lr: 2.0606045530603866e-05 loss: 0.0381 (0.0426) time: 3.4010 data: 0.0081 max mem: 33370 +Epoch: [25] [ 90/1319] eta: 1:11:12 lr: 2.059663327336368e-05 loss: 0.0372 (0.0425) time: 3.4088 data: 0.0084 max mem: 33370 +Epoch: [25] [ 100/1319] eta: 1:10:30 lr: 2.058722053818622e-05 loss: 0.0331 (0.0418) time: 3.4149 data: 0.0086 max mem: 33370 +Epoch: [25] [ 110/1319] eta: 1:09:53 lr: 2.0577807324804403e-05 loss: 0.0363 (0.0428) time: 3.4324 data: 0.0084 max mem: 33370 +Epoch: [25] [ 120/1319] eta: 1:09:14 lr: 2.0568393632950847e-05 loss: 0.0462 (0.0431) time: 3.4391 data: 0.0082 max mem: 33370 +Epoch: [25] [ 130/1319] eta: 1:08:37 lr: 2.055897946235788e-05 loss: 0.0466 (0.0430) time: 3.4351 data: 0.0082 max mem: 33370 +Epoch: [25] [ 140/1319] eta: 1:08:01 lr: 2.054956481275756e-05 loss: 0.0413 (0.0431) time: 3.4411 data: 0.0087 max mem: 33370 +Epoch: [25] [ 150/1319] eta: 1:07:25 lr: 2.0540149683881653e-05 loss: 0.0370 (0.0433) time: 3.4436 data: 0.0088 max mem: 33370 +Epoch: [25] [ 160/1319] eta: 1:06:52 lr: 2.0530734075461633e-05 loss: 0.0366 (0.0429) time: 3.4673 data: 0.0084 max mem: 33370 +Epoch: [25] [ 170/1319] eta: 1:06:16 lr: 2.05213179872287e-05 loss: 0.0366 (0.0433) time: 3.4608 data: 0.0080 max mem: 33370 +Epoch: [25] [ 180/1319] eta: 1:05:43 lr: 2.051190141891374e-05 loss: 0.0442 (0.0433) time: 3.4653 data: 0.0080 max mem: 33370 +Epoch: [25] [ 190/1319] eta: 1:05:08 lr: 2.050248437024738e-05 loss: 0.0389 (0.0430) time: 3.4724 data: 0.0082 max mem: 33370 +Epoch: [25] [ 200/1319] eta: 1:04:32 lr: 2.049306684095994e-05 loss: 0.0360 (0.0427) time: 3.4422 data: 0.0084 max mem: 33370 +Epoch: [25] [ 210/1319] eta: 1:03:53 lr: 2.048364883078146e-05 loss: 0.0365 (0.0428) time: 3.4063 data: 0.0085 max mem: 33370 +Epoch: [25] [ 220/1319] eta: 1:03:18 lr: 2.0474230339441687e-05 loss: 0.0370 (0.0432) time: 3.4089 data: 0.0083 max mem: 33370 +Epoch: [25] [ 230/1319] eta: 1:02:42 lr: 2.0464811366670074e-05 loss: 0.0376 (0.0431) time: 3.4350 data: 0.0083 max mem: 33370 +Epoch: [25] [ 240/1319] eta: 1:02:05 lr: 2.0455391912195788e-05 loss: 0.0411 (0.0432) time: 3.4176 data: 0.0085 max mem: 33370 +Epoch: [25] [ 250/1319] eta: 1:01:30 lr: 2.0445971975747706e-05 loss: 0.0417 (0.0432) time: 3.4261 data: 0.0084 max mem: 33370 +Epoch: [25] [ 260/1319] eta: 1:00:54 lr: 2.0436551557054405e-05 loss: 0.0417 (0.0431) time: 3.4249 data: 0.0082 max mem: 33370 +Epoch: [25] [ 270/1319] eta: 1:00:19 lr: 2.0427130655844186e-05 loss: 0.0396 (0.0430) time: 3.4207 data: 0.0080 max mem: 33370 +Epoch: [25] [ 280/1319] eta: 0:59:43 lr: 2.041770927184505e-05 loss: 0.0377 (0.0432) time: 3.4257 data: 0.0080 max mem: 33370 +Epoch: [25] [ 290/1319] eta: 0:59:07 lr: 2.0408287404784693e-05 loss: 0.0377 (0.0430) time: 3.4095 data: 0.0083 max mem: 33370 +Epoch: [25] [ 300/1319] eta: 0:58:31 lr: 2.0398865054390533e-05 loss: 0.0367 (0.0430) time: 3.4003 data: 0.0083 max mem: 33370 +Epoch: [25] [ 310/1319] eta: 0:57:55 lr: 2.038944222038969e-05 loss: 0.0373 (0.0430) time: 3.3976 data: 0.0082 max mem: 33370 +Epoch: [25] [ 320/1319] eta: 0:57:19 lr: 2.0380018902508984e-05 loss: 0.0342 (0.0429) time: 3.4015 data: 0.0083 max mem: 33370 +Epoch: [25] [ 330/1319] eta: 0:56:43 lr: 2.0370595100474957e-05 loss: 0.0342 (0.0429) time: 3.4021 data: 0.0084 max mem: 33370 +Epoch: [25] [ 340/1319] eta: 0:56:08 lr: 2.036117081401383e-05 loss: 0.0401 (0.0428) time: 3.4008 data: 0.0086 max mem: 33370 +Epoch: [25] [ 350/1319] eta: 0:55:32 lr: 2.035174604285155e-05 loss: 0.0414 (0.0430) time: 3.4030 data: 0.0086 max mem: 33370 +Epoch: [25] [ 360/1319] eta: 0:54:59 lr: 2.0342320786713757e-05 loss: 0.0404 (0.0427) time: 3.4369 data: 0.0088 max mem: 33370 +Epoch: [25] [ 370/1319] eta: 0:54:24 lr: 2.03328950453258e-05 loss: 0.0329 (0.0427) time: 3.4496 data: 0.0091 max mem: 33370 +Epoch: [25] [ 380/1319] eta: 0:53:49 lr: 2.0323468818412736e-05 loss: 0.0377 (0.0426) time: 3.4131 data: 0.0090 max mem: 33370 +Epoch: [25] [ 390/1319] eta: 0:53:13 lr: 2.03140421056993e-05 loss: 0.0386 (0.0426) time: 3.3944 data: 0.0087 max mem: 33370 +Epoch: [25] [ 400/1319] eta: 0:52:39 lr: 2.0304614906909954e-05 loss: 0.0362 (0.0426) time: 3.4130 data: 0.0082 max mem: 33370 +Epoch: [25] [ 410/1319] eta: 0:52:04 lr: 2.0295187221768858e-05 loss: 0.0424 (0.0428) time: 3.4394 data: 0.0084 max mem: 33370 +Epoch: [25] [ 420/1319] eta: 0:51:30 lr: 2.028575904999986e-05 loss: 0.0464 (0.0429) time: 3.4505 data: 0.0087 max mem: 33370 +Epoch: [25] [ 430/1319] eta: 0:50:56 lr: 2.0276330391326524e-05 loss: 0.0420 (0.0429) time: 3.4458 data: 0.0084 max mem: 33370 +Epoch: [25] [ 440/1319] eta: 0:50:23 lr: 2.026690124547211e-05 loss: 0.0400 (0.0430) time: 3.4611 data: 0.0080 max mem: 33370 +Epoch: [25] [ 450/1319] eta: 0:49:47 lr: 2.025747161215956e-05 loss: 0.0388 (0.0429) time: 3.4321 data: 0.0081 max mem: 33370 +Epoch: [25] [ 460/1319] eta: 0:49:12 lr: 2.0248041491111535e-05 loss: 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(0.0431) time: 3.4509 data: 0.0089 max mem: 33370 +Epoch: [25] [ 860/1319] eta: 0:26:15 lr: 1.987043348451999e-05 loss: 0.0485 (0.0432) time: 3.4322 data: 0.0090 max mem: 33370 +Epoch: [25] [ 870/1319] eta: 0:25:41 lr: 1.9860983123743625e-05 loss: 0.0382 (0.0432) time: 3.4521 data: 0.0087 max mem: 33370 +Epoch: [25] [ 880/1319] eta: 0:25:07 lr: 1.9851532263305046e-05 loss: 0.0382 (0.0432) time: 3.4750 data: 0.0085 max mem: 33370 +Epoch: [25] [ 890/1319] eta: 0:24:32 lr: 1.98420809029135e-05 loss: 0.0443 (0.0433) time: 3.4620 data: 0.0083 max mem: 33370 +Epoch: [25] [ 900/1319] eta: 0:23:58 lr: 1.9832629042277908e-05 loss: 0.0416 (0.0432) time: 3.4722 data: 0.0081 max mem: 33370 +Epoch: [25] [ 910/1319] eta: 0:23:24 lr: 1.982317668110687e-05 loss: 0.0386 (0.0432) time: 3.4698 data: 0.0082 max mem: 33370 +Epoch: [25] [ 920/1319] eta: 0:22:50 lr: 1.981372381910867e-05 loss: 0.0409 (0.0432) time: 3.4659 data: 0.0086 max mem: 33370 +Epoch: [25] [ 930/1319] eta: 0:22:16 lr: 1.980427045599124e-05 loss: 0.0416 (0.0434) time: 3.4813 data: 0.0086 max mem: 33370 +Epoch: [25] [ 940/1319] eta: 0:21:42 lr: 1.9794816591462205e-05 loss: 0.0422 (0.0434) time: 3.4849 data: 0.0082 max mem: 33370 +Epoch: [25] [ 950/1319] eta: 0:21:07 lr: 1.9785362225228878e-05 loss: 0.0422 (0.0434) time: 3.4744 data: 0.0082 max mem: 33370 +Epoch: [25] [ 960/1319] eta: 0:20:33 lr: 1.9775907356998215e-05 loss: 0.0399 (0.0434) time: 3.4791 data: 0.0086 max mem: 33370 +Epoch: [25] [ 970/1319] eta: 0:19:59 lr: 1.976645198647688e-05 loss: 0.0387 (0.0433) time: 3.4812 data: 0.0087 max mem: 33370 +Epoch: [25] [ 980/1319] eta: 0:19:25 lr: 1.9756996113371165e-05 loss: 0.0379 (0.0433) time: 3.4577 data: 0.0087 max mem: 33370 +Epoch: [25] [ 990/1319] eta: 0:18:50 lr: 1.9747539737387077e-05 loss: 0.0423 (0.0434) time: 3.4590 data: 0.0084 max mem: 33370 +Epoch: [25] [1000/1319] eta: 0:18:16 lr: 1.973808285823027e-05 loss: 0.0359 (0.0433) time: 3.4938 data: 0.0080 max mem: 33370 +Epoch: [25] 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33370 +Epoch: [25] [1090/1319] eta: 0:13:07 lr: 1.9652948254317503e-05 loss: 0.0423 (0.0433) time: 3.4693 data: 0.0087 max mem: 33370 +Epoch: [25] [1100/1319] eta: 0:12:33 lr: 1.9643486327172213e-05 loss: 0.0472 (0.0434) time: 3.4682 data: 0.0085 max mem: 33370 +Epoch: [25] [1110/1319] eta: 0:11:59 lr: 1.9634023893594635e-05 loss: 0.0388 (0.0434) time: 3.4417 data: 0.0084 max mem: 33370 +Epoch: [25] [1120/1319] eta: 0:11:24 lr: 1.9624560953286446e-05 loss: 0.0315 (0.0433) time: 3.4658 data: 0.0085 max mem: 33370 +Epoch: [25] [1130/1319] eta: 0:10:50 lr: 1.961509750594899e-05 loss: 0.0405 (0.0434) time: 3.4785 data: 0.0088 max mem: 33370 +Epoch: [25] [1140/1319] eta: 0:10:16 lr: 1.9605633551283273e-05 loss: 0.0405 (0.0433) time: 3.4677 data: 0.0087 max mem: 33370 +Epoch: [25] [1150/1319] eta: 0:09:41 lr: 1.9596169088989948e-05 loss: 0.0378 (0.0433) time: 3.4898 data: 0.0087 max mem: 33370 +Epoch: [25] [1160/1319] eta: 0:09:07 lr: 1.9586704118769358e-05 loss: 0.0372 (0.0433) time: 3.4744 data: 0.0090 max mem: 33370 +Epoch: [25] [1170/1319] eta: 0:08:32 lr: 1.9577238640321492e-05 loss: 0.0375 (0.0433) time: 3.4569 data: 0.0092 max mem: 33370 +Epoch: [25] [1180/1319] eta: 0:07:58 lr: 1.9567772653346e-05 loss: 0.0390 (0.0433) time: 3.4512 data: 0.0091 max mem: 33370 +Epoch: [25] [1190/1319] eta: 0:07:24 lr: 1.9558306157542204e-05 loss: 0.0394 (0.0433) time: 3.4574 data: 0.0085 max mem: 33370 +Epoch: [25] [1200/1319] eta: 0:06:49 lr: 1.9548839152609067e-05 loss: 0.0390 (0.0433) time: 3.4833 data: 0.0086 max mem: 33370 +Epoch: [25] [1210/1319] eta: 0:06:15 lr: 1.9539371638245233e-05 loss: 0.0369 (0.0433) time: 3.4884 data: 0.0089 max mem: 33370 +Epoch: [25] [1220/1319] eta: 0:05:40 lr: 1.952990361414899e-05 loss: 0.0405 (0.0433) time: 3.4886 data: 0.0086 max mem: 33370 +Epoch: [25] [1230/1319] eta: 0:05:06 lr: 1.9520435080018294e-05 loss: 0.0454 (0.0433) time: 3.4522 data: 0.0086 max mem: 33370 +Epoch: [25] [1240/1319] eta: 0:04:32 lr: 1.9510966035550763e-05 loss: 0.0418 (0.0433) time: 3.4340 data: 0.0085 max mem: 33370 +Epoch: [25] [1250/1319] eta: 0:03:57 lr: 1.9501496480443652e-05 loss: 0.0451 (0.0434) time: 3.4320 data: 0.0087 max mem: 33370 +Epoch: [25] [1260/1319] eta: 0:03:23 lr: 1.9492026414393892e-05 loss: 0.0482 (0.0435) time: 3.4448 data: 0.0086 max mem: 33370 +Epoch: [25] [1270/1319] eta: 0:02:48 lr: 1.9482555837098063e-05 loss: 0.0466 (0.0435) time: 3.4525 data: 0.0083 max mem: 33370 +Epoch: [25] [1280/1319] eta: 0:02:14 lr: 1.9473084748252403e-05 loss: 0.0406 (0.0435) time: 3.4225 data: 0.0082 max mem: 33370 +Epoch: [25] [1290/1319] eta: 0:01:39 lr: 1.9463613147552807e-05 loss: 0.0382 (0.0435) time: 3.4020 data: 0.0079 max mem: 33370 +Epoch: [25] [1300/1319] eta: 0:01:05 lr: 1.9454141034694828e-05 loss: 0.0407 (0.0436) time: 3.4264 data: 0.0082 max mem: 33370 +Epoch: [25] [1310/1319] eta: 0:00:30 lr: 1.9444668409373652e-05 loss: 0.0404 (0.0435) time: 3.4364 data: 0.0083 max mem: 33370 +Epoch: [25] Total time: 1:15:41 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 2:25:21 time: 3.3898 data: 3.2533 max mem: 33370 +Test: [ 100/2573] eta: 0:04:33 time: 0.0777 data: 0.0014 max mem: 33370 +Test: [ 200/2573] eta: 0:03:46 time: 0.0798 data: 0.0015 max mem: 33370 +Test: [ 300/2573] eta: 0:03:23 time: 0.0806 data: 0.0014 max mem: 33370 +Test: [ 400/2573] eta: 0:03:08 time: 0.0810 data: 0.0014 max mem: 33370 +Test: [ 500/2573] eta: 0:02:57 time: 0.0802 data: 0.0015 max mem: 33370 +Test: [ 600/2573] eta: 0:02:47 time: 0.0798 data: 0.0014 max mem: 33370 +Test: [ 700/2573] eta: 0:02:38 time: 0.0800 data: 0.0015 max mem: 33370 +Test: [ 800/2573] eta: 0:02:28 time: 0.0838 data: 0.0015 max mem: 33370 +Test: [ 900/2573] eta: 0:02:20 time: 0.0811 data: 0.0015 max mem: 33370 +Test: [1000/2573] eta: 0:02:11 time: 0.0810 data: 0.0015 max mem: 33370 +Test: [1100/2573] eta: 0:02:02 time: 0.0814 data: 0.0016 max mem: 33370 +Test: [1200/2573] eta: 0:01:54 time: 0.0825 data: 0.0017 max mem: 33370 +Test: [1300/2573] eta: 0:01:45 time: 0.0817 data: 0.0016 max mem: 33370 +Test: [1400/2573] eta: 0:01:37 time: 0.0798 data: 0.0015 max mem: 33370 +Test: [1500/2573] eta: 0:01:29 time: 0.0826 data: 0.0017 max mem: 33370 +Test: [1600/2573] eta: 0:01:20 time: 0.0852 data: 0.0018 max mem: 33370 +Test: [1700/2573] eta: 0:01:12 time: 0.0798 data: 0.0014 max mem: 33370 +Test: [1800/2573] eta: 0:01:03 time: 0.0821 data: 0.0015 max mem: 33370 +Test: [1900/2573] eta: 0:00:55 time: 0.0790 data: 0.0015 max mem: 33370 +Test: [2000/2573] eta: 0:00:47 time: 0.0808 data: 0.0015 max mem: 33370 +Test: [2100/2573] eta: 0:00:38 time: 0.0824 data: 0.0015 max mem: 33370 +Test: [2200/2573] eta: 0:00:30 time: 0.0820 data: 0.0014 max mem: 33370 +Test: [2300/2573] eta: 0:00:22 time: 0.0827 data: 0.0016 max mem: 33370 +Test: [2400/2573] eta: 0:00:14 time: 0.0782 data: 0.0015 max mem: 33370 +Test: [2500/2573] eta: 0:00:05 time: 0.0808 data: 0.0015 max mem: 33370 +Test: Total time: 0:03:31 +Final results: +Mean IoU is 63.55 + + precision@0.5 = 71.26 + precision@0.6 = 66.03 + precision@0.7 = 59.80 + precision@0.8 = 48.61 + precision@0.9 = 23.98 + overall IoU = 61.30 + +Average object IoU 63.546331256217904 +Overall IoU 61.29701614379883 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [26] [ 0/1319] eta: 3:36:56 lr: 1.943614260817638e-05 loss: 0.0366 (0.0366) time: 9.8684 data: 2.7964 max mem: 33370 +Epoch: [26] [ 10/1319] eta: 1:28:48 lr: 1.9426669008334188e-05 loss: 0.0366 (0.0407) time: 4.0706 data: 0.2622 max mem: 33370 +Epoch: [26] [ 20/1319] eta: 1:21:25 lr: 1.941719489514293e-05 loss: 0.0371 (0.0405) time: 3.4557 data: 0.0084 max mem: 33370 +Epoch: [26] [ 30/1319] eta: 1:18:28 lr: 1.9407720268296455e-05 loss: 0.0373 (0.0420) time: 3.4230 data: 0.0081 max mem: 33370 +Epoch: [26] [ 40/1319] eta: 1:16:46 lr: 1.9398245127488253e-05 loss: 0.0367 (0.0407) time: 3.4350 data: 0.0082 max mem: 33370 +Epoch: [26] [ 50/1319] eta: 1:15:36 lr: 1.9388769472411493e-05 loss: 0.0356 (0.0403) time: 3.4541 data: 0.0087 max mem: 33370 +Epoch: [26] [ 60/1319] eta: 1:14:35 lr: 1.9379293302758954e-05 loss: 0.0341 (0.0394) time: 3.4583 data: 0.0091 max mem: 33370 +Epoch: [26] [ 70/1319] eta: 1:13:33 lr: 1.936981661822309e-05 loss: 0.0388 (0.0404) time: 3.4280 data: 0.0087 max mem: 33370 +Epoch: [26] [ 80/1319] eta: 1:12:47 lr: 1.9360339418495996e-05 loss: 0.0401 (0.0403) time: 3.4330 data: 0.0084 max mem: 33370 +Epoch: [26] [ 90/1319] eta: 1:12:06 lr: 1.935086170326942e-05 loss: 0.0376 (0.0400) time: 3.4747 data: 0.0083 max mem: 33370 +Epoch: [26] [ 100/1319] eta: 1:11:22 lr: 1.934138347223476e-05 loss: 0.0393 (0.0400) time: 3.4666 data: 0.0080 max mem: 33370 +Epoch: [26] [ 110/1319] eta: 1:10:43 lr: 1.9331904725083057e-05 loss: 0.0408 (0.0401) time: 3.4602 data: 0.0080 max mem: 33370 +Epoch: [26] [ 120/1319] eta: 1:10:06 lr: 1.9322425461504988e-05 loss: 0.0467 (0.0422) time: 3.4824 data: 0.0082 max mem: 33370 +Epoch: [26] [ 130/1319] eta: 1:09:28 lr: 1.931294568119089e-05 loss: 0.0467 (0.0437) time: 3.4868 data: 0.0087 max mem: 33370 +Epoch: [26] [ 140/1319] eta: 1:08:47 lr: 1.930346538383074e-05 loss: 0.0379 (0.0434) time: 3.4560 data: 0.0087 max mem: 33370 +Epoch: [26] [ 150/1319] eta: 1:08:09 lr: 1.9293984569114164e-05 loss: 0.0372 (0.0434) time: 3.4485 data: 0.0087 max mem: 33370 +Epoch: [26] [ 160/1319] eta: 1:07:30 lr: 1.9284503236730435e-05 loss: 0.0412 (0.0437) time: 3.4547 data: 0.0090 max mem: 33370 +Epoch: [26] [ 170/1319] eta: 1:06:52 lr: 1.927502138636845e-05 loss: 0.0446 (0.0442) time: 3.4411 data: 0.0087 max mem: 33370 +Epoch: [26] [ 180/1319] eta: 1:06:18 lr: 1.9265539017716765e-05 loss: 0.0383 (0.0435) time: 3.4739 data: 0.0082 max mem: 33370 +Epoch: [26] [ 190/1319] eta: 1:05:43 lr: 1.9256056130463582e-05 loss: 0.0364 (0.0439) time: 3.4987 data: 0.0083 max mem: 33370 +Epoch: [26] [ 200/1319] eta: 1:05:04 lr: 1.9246572724296735e-05 loss: 0.0378 (0.0437) time: 3.4553 data: 0.0086 max mem: 33370 +Epoch: [26] [ 210/1319] eta: 1:04:25 lr: 1.9237088798903708e-05 loss: 0.0378 (0.0437) time: 3.4204 data: 0.0088 max mem: 33370 +Epoch: [26] [ 220/1319] eta: 1:03:49 lr: 1.922760435397161e-05 loss: 0.0416 (0.0438) time: 3.4393 data: 0.0090 max mem: 33370 +Epoch: [26] [ 230/1319] eta: 1:03:15 lr: 1.9218119389187204e-05 loss: 0.0389 (0.0436) time: 3.4769 data: 0.0090 max mem: 33370 +Epoch: [26] [ 240/1319] eta: 1:02:36 lr: 1.9208633904236885e-05 loss: 0.0389 (0.0436) time: 3.4508 data: 0.0088 max mem: 33370 +Epoch: [26] [ 250/1319] eta: 1:02:00 lr: 1.9199147898806697e-05 loss: 0.0399 (0.0435) time: 3.4318 data: 0.0085 max mem: 33370 +Epoch: [26] [ 260/1319] eta: 1:01:23 lr: 1.9189661372582306e-05 loss: 0.0399 (0.0435) time: 3.4408 data: 0.0084 max mem: 33370 +Epoch: [26] [ 270/1319] eta: 1:00:47 lr: 1.918017432524904e-05 loss: 0.0350 (0.0433) time: 3.4338 data: 0.0084 max mem: 33370 +Epoch: [26] [ 280/1319] eta: 1:00:12 lr: 1.9170686756491828e-05 loss: 0.0345 (0.0432) time: 3.4507 data: 0.0084 max mem: 33370 +Epoch: [26] [ 290/1319] eta: 0:59:37 lr: 1.916119866599526e-05 loss: 0.0404 (0.0432) time: 3.4650 data: 0.0084 max mem: 33370 +Epoch: [26] [ 300/1319] eta: 0:59:02 lr: 1.9151710053443563e-05 loss: 0.0404 (0.0430) time: 3.4795 data: 0.0084 max mem: 33370 +Epoch: [26] [ 310/1319] eta: 0:58:28 lr: 1.9142220918520593e-05 loss: 0.0396 (0.0431) time: 3.4811 data: 0.0084 max mem: 33370 +Epoch: [26] [ 320/1319] eta: 0:57:52 lr: 1.9132731260909836e-05 loss: 0.0363 (0.0428) time: 3.4642 data: 0.0089 max mem: 33370 +Epoch: [26] [ 330/1319] eta: 0:57:17 lr: 1.9123241080294413e-05 loss: 0.0348 (0.0429) time: 3.4655 data: 0.0093 max mem: 33370 +Epoch: [26] [ 340/1319] eta: 0:56:42 lr: 1.9113750376357084e-05 loss: 0.0415 (0.0429) time: 3.4738 data: 0.0084 max mem: 33370 +Epoch: [26] [ 350/1319] eta: 0:56:08 lr: 1.9104259148780233e-05 loss: 0.0412 (0.0426) time: 3.4787 data: 0.0080 max mem: 33370 +Epoch: [26] [ 360/1319] eta: 0:55:33 lr: 1.909476739724589e-05 loss: 0.0344 (0.0427) time: 3.4717 data: 0.0082 max mem: 33370 +Epoch: [26] [ 370/1319] eta: 0:54:58 lr: 1.9085275121435705e-05 loss: 0.0407 (0.0427) time: 3.4605 data: 0.0085 max mem: 33370 +Epoch: [26] [ 380/1319] eta: 0:54:21 lr: 1.907578232103095e-05 loss: 0.0403 (0.0425) time: 3.4289 data: 0.0084 max mem: 33370 +Epoch: [26] [ 390/1319] eta: 0:53:45 lr: 1.906628899571255e-05 loss: 0.0375 (0.0424) time: 3.4044 data: 0.0081 max mem: 33370 +Epoch: [26] [ 400/1319] eta: 0:53:10 lr: 1.9056795145161037e-05 loss: 0.0389 (0.0423) time: 3.4398 data: 0.0083 max mem: 33370 +Epoch: [26] [ 410/1319] eta: 0:52:33 lr: 1.9047300769056588e-05 loss: 0.0396 (0.0430) time: 3.4281 data: 0.0086 max mem: 33370 +Epoch: [26] [ 420/1319] eta: 0:51:58 lr: 1.9037805867078998e-05 loss: 0.0426 (0.0430) time: 3.4246 data: 0.0086 max mem: 33370 +Epoch: [26] [ 430/1319] eta: 0:51:23 lr: 1.9028310438907695e-05 loss: 0.0393 (0.0428) time: 3.4488 data: 0.0084 max mem: 33370 +Epoch: [26] [ 440/1319] eta: 0:50:46 lr: 1.901881448422173e-05 loss: 0.0368 (0.0427) time: 3.3990 data: 0.0082 max mem: 33370 +Epoch: [26] [ 450/1319] eta: 0:50:11 lr: 1.900931800269978e-05 loss: 0.0368 (0.0428) time: 3.3991 data: 0.0086 max mem: 33370 +Epoch: [26] [ 460/1319] eta: 0:49:36 lr: 1.8999820994020145e-05 loss: 0.0359 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data: 0.0084 max mem: 33370 +Epoch: [26] [ 780/1319] eta: 0:30:58 lr: 1.8695636432127905e-05 loss: 0.0365 (0.0426) time: 3.4284 data: 0.0084 max mem: 33370 +Epoch: [26] [ 790/1319] eta: 0:30:24 lr: 1.8686121844283114e-05 loss: 0.0329 (0.0425) time: 3.4458 data: 0.0086 max mem: 33370 +Epoch: [26] [ 800/1319] eta: 0:29:49 lr: 1.8676606718115407e-05 loss: 0.0335 (0.0425) time: 3.4441 data: 0.0087 max mem: 33370 +Epoch: [26] [ 810/1319] eta: 0:29:15 lr: 1.866709105328956e-05 loss: 0.0349 (0.0426) time: 3.4428 data: 0.0086 max mem: 33370 +Epoch: [26] [ 820/1319] eta: 0:28:40 lr: 1.8657574849469954e-05 loss: 0.0339 (0.0426) time: 3.4430 data: 0.0084 max mem: 33370 +Epoch: [26] [ 830/1319] eta: 0:28:06 lr: 1.864805810632056e-05 loss: 0.0376 (0.0425) time: 3.4518 data: 0.0085 max mem: 33370 +Epoch: [26] [ 840/1319] eta: 0:27:31 lr: 1.8638540823504965e-05 loss: 0.0375 (0.0425) time: 3.4406 data: 0.0086 max mem: 33370 +Epoch: [26] [ 850/1319] eta: 0:26:57 lr: 1.8629023000686338e-05 loss: 0.0351 (0.0424) time: 3.4082 data: 0.0086 max mem: 33370 +Epoch: [26] [ 860/1319] eta: 0:26:22 lr: 1.8619504637527467e-05 loss: 0.0354 (0.0424) time: 3.4250 data: 0.0089 max mem: 33370 +Epoch: [26] [ 870/1319] eta: 0:25:48 lr: 1.8609985733690715e-05 loss: 0.0358 (0.0425) time: 3.4508 data: 0.0090 max mem: 33370 +Epoch: [26] [ 880/1319] eta: 0:25:13 lr: 1.860046628883806e-05 loss: 0.0397 (0.0425) time: 3.4199 data: 0.0091 max mem: 33370 +Epoch: [26] [ 890/1319] eta: 0:24:38 lr: 1.859094630263106e-05 loss: 0.0393 (0.0425) time: 3.3755 data: 0.0083 max mem: 33370 +Epoch: [26] [ 900/1319] eta: 0:24:03 lr: 1.8581425774730882e-05 loss: 0.0365 (0.0425) time: 3.3963 data: 0.0083 max mem: 33370 +Epoch: [26] [ 910/1319] eta: 0:23:29 lr: 1.8571904704798292e-05 loss: 0.0388 (0.0425) time: 3.4358 data: 0.0084 max mem: 33370 +Epoch: [26] [ 920/1319] eta: 0:22:54 lr: 1.856238309249363e-05 loss: 0.0428 (0.0425) time: 3.4312 data: 0.0085 max mem: 33370 +Epoch: [26] [ 930/1319] eta: 0:22:20 lr: 1.855286093747684e-05 loss: 0.0383 (0.0425) time: 3.4157 data: 0.0087 max mem: 33370 +Epoch: [26] [ 940/1319] eta: 0:21:45 lr: 1.854333823940747e-05 loss: 0.0383 (0.0425) time: 3.4181 data: 0.0080 max mem: 33370 +Epoch: [26] [ 950/1319] eta: 0:21:11 lr: 1.853381499794464e-05 loss: 0.0385 (0.0425) time: 3.4134 data: 0.0083 max mem: 33370 +Epoch: [26] [ 960/1319] eta: 0:20:36 lr: 1.8524291212747084e-05 loss: 0.0418 (0.0425) time: 3.4224 data: 0.0089 max mem: 33370 +Epoch: [26] [ 970/1319] eta: 0:20:02 lr: 1.85147668834731e-05 loss: 0.0382 (0.0425) time: 3.4209 data: 0.0087 max mem: 33370 +Epoch: [26] [ 980/1319] eta: 0:19:27 lr: 1.8505242009780593e-05 loss: 0.0344 (0.0426) time: 3.4096 data: 0.0082 max mem: 33370 +Epoch: [26] [ 990/1319] eta: 0:18:52 lr: 1.8495716591327057e-05 loss: 0.0402 (0.0427) time: 3.4110 data: 0.0084 max mem: 33370 +Epoch: [26] [1000/1319] eta: 0:18:18 lr: 1.848619062776957e-05 loss: 0.0484 (0.0428) time: 3.3954 data: 0.0088 max mem: 33370 +Epoch: [26] [1010/1319] eta: 0:17:43 lr: 1.8476664118764797e-05 loss: 0.0417 (0.0427) time: 3.4130 data: 0.0088 max mem: 33370 +Epoch: [26] [1020/1319] eta: 0:17:09 lr: 1.8467137063969e-05 loss: 0.0394 (0.0428) time: 3.4121 data: 0.0089 max mem: 33370 +Epoch: [26] [1030/1319] eta: 0:16:34 lr: 1.8457609463038007e-05 loss: 0.0390 (0.0428) time: 3.4078 data: 0.0089 max mem: 33370 +Epoch: [26] [1040/1319] eta: 0:16:00 lr: 1.8448081315627246e-05 loss: 0.0364 (0.0428) time: 3.4592 data: 0.0088 max mem: 33370 +Epoch: [26] [1050/1319] eta: 0:15:25 lr: 1.843855262139173e-05 loss: 0.0304 (0.0427) time: 3.4400 data: 0.0085 max mem: 33370 +Epoch: [26] [1060/1319] eta: 0:14:51 lr: 1.8429023379986053e-05 loss: 0.0366 (0.0427) time: 3.3932 data: 0.0084 max mem: 33370 +Epoch: [26] [1070/1319] eta: 0:14:16 lr: 1.8419493591064395e-05 loss: 0.0410 (0.0429) time: 3.4171 data: 0.0088 max mem: 33370 +Epoch: [26] [1080/1319] eta: 0:13:42 lr: 1.840996325428051e-05 loss: 0.0412 (0.0429) time: 3.4343 data: 0.0085 max mem: 33370 +Epoch: [26] [1090/1319] eta: 0:13:08 lr: 1.840043236928774e-05 loss: 0.0334 (0.0428) time: 3.4257 data: 0.0081 max mem: 33370 +Epoch: [26] [1100/1319] eta: 0:12:33 lr: 1.839090093573901e-05 loss: 0.0363 (0.0429) time: 3.4266 data: 0.0086 max mem: 33370 +Epoch: [26] [1110/1319] eta: 0:11:59 lr: 1.838136895328682e-05 loss: 0.0470 (0.0429) time: 3.4400 data: 0.0086 max mem: 33370 +Epoch: [26] [1120/1319] eta: 0:11:24 lr: 1.8371836421583257e-05 loss: 0.0382 (0.0428) time: 3.4280 data: 0.0086 max mem: 33370 +Epoch: [26] [1130/1319] eta: 0:10:50 lr: 1.836230334027998e-05 loss: 0.0345 (0.0428) time: 3.4344 data: 0.0092 max mem: 33370 +Epoch: [26] [1140/1319] eta: 0:10:15 lr: 1.8352769709028224e-05 loss: 0.0426 (0.0429) time: 3.4245 data: 0.0088 max mem: 33370 +Epoch: [26] [1150/1319] eta: 0:09:41 lr: 1.8343235527478807e-05 loss: 0.0374 (0.0429) time: 3.3947 data: 0.0080 max mem: 33370 +Epoch: [26] [1160/1319] eta: 0:09:07 lr: 1.8333700795282125e-05 loss: 0.0374 (0.0429) time: 3.4418 data: 0.0082 max mem: 33370 +Epoch: [26] [1170/1319] eta: 0:08:32 lr: 1.832416551208814e-05 loss: 0.0441 (0.0429) time: 3.4587 data: 0.0083 max mem: 33370 +Epoch: [26] [1180/1319] eta: 0:07:58 lr: 1.8314629677546413e-05 loss: 0.0391 (0.0429) time: 3.4210 data: 0.0086 max mem: 33370 +Epoch: [26] [1190/1319] eta: 0:07:23 lr: 1.8305093291306038e-05 loss: 0.0398 (0.0429) time: 3.4236 data: 0.0091 max mem: 33370 +Epoch: [26] [1200/1319] eta: 0:06:49 lr: 1.829555635301572e-05 loss: 0.0404 (0.0429) time: 3.4505 data: 0.0089 max mem: 33370 +Epoch: [26] [1210/1319] eta: 0:06:14 lr: 1.8286018862323718e-05 loss: 0.0408 (0.0430) time: 3.4244 data: 0.0089 max mem: 33370 +Epoch: [26] [1220/1319] eta: 0:05:40 lr: 1.8276480818877866e-05 loss: 0.0446 (0.0430) time: 3.3909 data: 0.0088 max mem: 33370 +Epoch: [26] [1230/1319] eta: 0:05:06 lr: 1.8266942222325584e-05 loss: 0.0386 (0.0430) time: 3.4075 data: 0.0084 max mem: 33370 +Epoch: [26] [1240/1319] eta: 0:04:31 lr: 1.8257403072313833e-05 loss: 0.0336 (0.0429) time: 3.4357 data: 0.0083 max mem: 33370 +Epoch: [26] [1250/1319] eta: 0:03:57 lr: 1.8247863368489165e-05 loss: 0.0379 (0.0429) time: 3.4418 data: 0.0080 max mem: 33370 +Epoch: [26] [1260/1319] eta: 0:03:22 lr: 1.8238323110497695e-05 loss: 0.0411 (0.0429) time: 3.4369 data: 0.0082 max mem: 33370 +Epoch: [26] [1270/1319] eta: 0:02:48 lr: 1.822878229798511e-05 loss: 0.0358 (0.0429) time: 3.4372 data: 0.0084 max mem: 33370 +Epoch: [26] [1280/1319] eta: 0:02:14 lr: 1.821924093059666e-05 loss: 0.0352 (0.0428) time: 3.4261 data: 0.0084 max mem: 33370 +Epoch: [26] [1290/1319] eta: 0:01:39 lr: 1.8209699007977167e-05 loss: 0.0363 (0.0428) time: 3.4115 data: 0.0087 max mem: 33370 +Epoch: [26] [1300/1319] eta: 0:01:05 lr: 1.8200156529771002e-05 loss: 0.0353 (0.0428) time: 3.4236 data: 0.0086 max mem: 33370 +Epoch: [26] [1310/1319] eta: 0:00:30 lr: 1.819061349562212e-05 loss: 0.0406 (0.0428) time: 3.4316 data: 0.0084 max mem: 33370 +Epoch: [26] Total time: 1:15:36 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 2:24:19 time: 3.3656 data: 3.2741 max mem: 33370 +Test: [ 100/2573] eta: 0:04:34 time: 0.0785 data: 0.0016 max mem: 33370 +Test: [ 200/2573] eta: 0:03:48 time: 0.0799 data: 0.0016 max mem: 33370 +Test: [ 300/2573] eta: 0:03:25 time: 0.0810 data: 0.0014 max mem: 33370 +Test: [ 400/2573] eta: 0:03:10 time: 0.0810 data: 0.0015 max mem: 33370 +Test: [ 500/2573] eta: 0:02:58 time: 0.0800 data: 0.0015 max mem: 33370 +Test: [ 600/2573] eta: 0:02:48 time: 0.0810 data: 0.0016 max mem: 33370 +Test: [ 700/2573] eta: 0:02:39 time: 0.0803 data: 0.0015 max mem: 33370 +Test: [ 800/2573] eta: 0:02:29 time: 0.0839 data: 0.0014 max mem: 33370 +Test: [ 900/2573] eta: 0:02:21 time: 0.0817 data: 0.0015 max mem: 33370 +Test: [1000/2573] eta: 0:02:12 time: 0.0808 data: 0.0015 max mem: 33370 +Test: [1100/2573] eta: 0:02:03 time: 0.0808 data: 0.0014 max mem: 33370 +Test: [1200/2573] eta: 0:01:54 time: 0.0809 data: 0.0015 max mem: 33370 +Test: [1300/2573] eta: 0:01:46 time: 0.0810 data: 0.0016 max mem: 33370 +Test: [1400/2573] eta: 0:01:37 time: 0.0791 data: 0.0015 max mem: 33370 +Test: [1500/2573] eta: 0:01:28 time: 0.0799 data: 0.0014 max mem: 33370 +Test: [1600/2573] eta: 0:01:20 time: 0.0833 data: 0.0014 max mem: 33370 +Test: [1700/2573] eta: 0:01:12 time: 0.0799 data: 0.0014 max mem: 33370 +Test: [1800/2573] eta: 0:01:03 time: 0.0823 data: 0.0015 max mem: 33370 +Test: [1900/2573] eta: 0:00:55 time: 0.0796 data: 0.0014 max mem: 33370 +Test: [2000/2573] eta: 0:00:47 time: 0.0801 data: 0.0014 max mem: 33370 +Test: [2100/2573] eta: 0:00:38 time: 0.0819 data: 0.0014 max mem: 33370 +Test: [2200/2573] eta: 0:00:30 time: 0.0822 data: 0.0014 max mem: 33370 +Test: [2300/2573] eta: 0:00:22 time: 0.0818 data: 0.0016 max mem: 33370 +Test: [2400/2573] eta: 0:00:14 time: 0.0772 data: 0.0016 max mem: 33370 +Test: [2500/2573] eta: 0:00:05 time: 0.0798 data: 0.0015 max mem: 33370 +Test: Total time: 0:03:31 +Final results: +Mean IoU is 64.38 + + precision@0.5 = 72.49 + precision@0.6 = 66.87 + precision@0.7 = 59.84 + precision@0.8 = 48.39 + precision@0.9 = 23.90 + overall IoU = 61.95 + +Average object IoU 64.37951717820202 +Overall IoU 61.95230484008789 +Better epoch: 26 + +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [27] [ 0/1319] eta: 1:57:10 lr: 1.818202428926248e-05 loss: 0.0370 (0.0370) time: 5.3302 data: 1.8654 max mem: 33370 +Epoch: [27] [ 10/1319] eta: 1:18:46 lr: 1.817248019783995e-05 loss: 0.0370 (0.0402) time: 3.6107 data: 0.1769 max mem: 33370 +Epoch: [27] [ 20/1319] eta: 1:16:07 lr: 1.8162935549439682e-05 loss: 0.0363 (0.0405) time: 3.4251 data: 0.0082 max mem: 33370 +Epoch: [27] [ 30/1319] eta: 1:14:45 lr: 1.8153390343703928e-05 loss: 0.0368 (0.0409) time: 3.4077 data: 0.0083 max mem: 33370 +Epoch: [27] [ 40/1319] eta: 1:13:57 lr: 1.8143844580274487e-05 loss: 0.0369 (0.0400) time: 3.4206 data: 0.0085 max mem: 33370 +Epoch: [27] [ 50/1319] eta: 1:13:11 lr: 1.813429825879272e-05 loss: 0.0369 (0.0414) time: 3.4312 data: 0.0089 max mem: 33370 +Epoch: [27] [ 60/1319] eta: 1:12:28 lr: 1.8124751378899558e-05 loss: 0.0460 (0.0418) time: 3.4224 data: 0.0088 max mem: 33370 +Epoch: [27] [ 70/1319] eta: 1:11:54 lr: 1.811520394023548e-05 loss: 0.0399 (0.0411) time: 3.4395 data: 0.0083 max mem: 33370 +Epoch: [27] [ 80/1319] eta: 1:11:11 lr: 1.8105655942440525e-05 loss: 0.0321 (0.0409) time: 3.4293 data: 0.0085 max mem: 33370 +Epoch: [27] [ 90/1319] eta: 1:10:36 lr: 1.8096107385154294e-05 loss: 0.0321 (0.0407) time: 3.4216 data: 0.0085 max mem: 33370 +Epoch: [27] [ 100/1319] eta: 1:09:56 lr: 1.8086558268015952e-05 loss: 0.0367 (0.0407) time: 3.4223 data: 0.0080 max mem: 33370 +Epoch: [27] [ 110/1319] eta: 1:09:27 lr: 1.807700859066419e-05 loss: 0.0375 (0.0405) time: 3.4454 data: 0.0082 max mem: 33370 +Epoch: [27] [ 120/1319] eta: 1:08:50 lr: 1.8067458352737284e-05 loss: 0.0357 (0.0403) time: 3.4555 data: 0.0082 max mem: 33370 +Epoch: [27] [ 130/1319] eta: 1:08:14 lr: 1.8057907553873043e-05 loss: 0.0364 (0.0403) time: 3.4226 data: 0.0083 max mem: 33370 +Epoch: [27] [ 140/1319] eta: 1:07:37 lr: 1.8048356193708847e-05 loss: 0.0344 (0.0398) time: 3.4188 data: 0.0086 max mem: 33370 +Epoch: [27] [ 150/1319] eta: 1:06:59 lr: 1.803880427188162e-05 loss: 0.0332 (0.0398) time: 3.4042 data: 0.0088 max mem: 33370 +Epoch: [27] [ 160/1319] eta: 1:06:27 lr: 1.802925178802783e-05 loss: 0.0403 (0.0399) time: 3.4361 data: 0.0091 max mem: 33370 +Epoch: [27] [ 170/1319] eta: 1:05:52 lr: 1.8019698741783504e-05 loss: 0.0366 (0.0394) time: 3.4540 data: 0.0086 max mem: 33370 +Epoch: [27] [ 180/1319] eta: 1:05:16 lr: 1.8010145132784217e-05 loss: 0.0336 (0.0399) time: 3.4204 data: 0.0082 max mem: 33370 +Epoch: [27] [ 190/1319] eta: 1:04:42 lr: 1.8000590960665095e-05 loss: 0.0412 (0.0402) time: 3.4328 data: 0.0084 max mem: 33370 +Epoch: [27] [ 200/1319] eta: 1:04:09 lr: 1.7991036225060814e-05 loss: 0.0411 (0.0401) time: 3.4563 data: 0.0084 max mem: 33370 +Epoch: [27] [ 210/1319] eta: 1:03:32 lr: 1.7981480925605583e-05 loss: 0.0411 (0.0408) time: 3.4221 data: 0.0084 max mem: 33370 +Epoch: [27] [ 220/1319] eta: 1:02:56 lr: 1.7971925061933174e-05 loss: 0.0454 (0.0408) time: 3.3976 data: 0.0089 max mem: 33370 +Epoch: [27] [ 230/1319] eta: 1:02:21 lr: 1.7962368633676893e-05 loss: 0.0325 (0.0405) time: 3.4185 data: 0.0088 max mem: 33370 +Epoch: [27] [ 240/1319] eta: 1:01:48 lr: 1.7952811640469606e-05 loss: 0.0325 (0.0406) time: 3.4419 data: 0.0083 max mem: 33370 +Epoch: [27] [ 250/1319] eta: 1:01:13 lr: 1.7943254081943704e-05 loss: 0.0378 (0.0407) time: 3.4469 data: 0.0083 max mem: 33370 +Epoch: [27] [ 260/1319] eta: 1:00:38 lr: 1.7933695957731138e-05 loss: 0.0330 (0.0409) time: 3.4244 data: 0.0081 max mem: 33370 +Epoch: [27] [ 270/1319] eta: 1:00:03 lr: 1.7924137267463387e-05 loss: 0.0330 (0.0407) time: 3.4145 data: 0.0079 max mem: 33370 +Epoch: [27] [ 280/1319] eta: 0:59:27 lr: 1.7914578010771477e-05 loss: 0.0374 (0.0406) time: 3.4093 data: 0.0080 max mem: 33370 +Epoch: [27] [ 290/1319] eta: 0:58:53 lr: 1.7905018187285976e-05 loss: 0.0387 (0.0407) time: 3.4150 data: 0.0082 max mem: 33370 +Epoch: [27] [ 300/1319] eta: 0:58:19 lr: 1.7895457796636998e-05 loss: 0.0437 (0.0408) time: 3.4319 data: 0.0083 max mem: 33370 +Epoch: [27] [ 310/1319] eta: 0:57:45 lr: 1.7885896838454187e-05 loss: 0.0396 (0.0407) time: 3.4389 data: 0.0082 max mem: 33370 +Epoch: [27] [ 320/1319] eta: 0:57:10 lr: 1.787633531236672e-05 loss: 0.0368 (0.0406) time: 3.4394 data: 0.0081 max mem: 33370 +Epoch: [27] [ 330/1319] eta: 0:56:35 lr: 1.786677321800332e-05 loss: 0.0340 (0.0406) time: 3.4245 data: 0.0083 max mem: 33370 +Epoch: [27] [ 340/1319] eta: 0:56:02 lr: 1.7857210554992246e-05 loss: 0.0364 (0.0406) time: 3.4456 data: 0.0083 max mem: 33370 +Epoch: [27] [ 350/1319] eta: 0:55:28 lr: 1.7847647322961293e-05 loss: 0.0364 (0.0404) time: 3.4633 data: 0.0083 max mem: 33370 +Epoch: [27] [ 360/1319] eta: 0:54:55 lr: 1.783808352153779e-05 loss: 0.0408 (0.0406) time: 3.4574 data: 0.0089 max mem: 33370 +Epoch: [27] [ 370/1319] eta: 0:54:21 lr: 1.782851915034859e-05 loss: 0.0429 (0.0406) time: 3.4562 data: 0.0093 max mem: 33370 +Epoch: [27] [ 380/1319] eta: 0:53:46 lr: 1.78189542090201e-05 loss: 0.0350 (0.0405) time: 3.4385 data: 0.0090 max mem: 33370 +Epoch: [27] [ 390/1319] eta: 0:53:12 lr: 1.780938869717823e-05 loss: 0.0378 (0.0407) time: 3.4330 data: 0.0083 max mem: 33370 +Epoch: [27] [ 400/1319] eta: 0:52:37 lr: 1.779982261444845e-05 loss: 0.0385 (0.0406) time: 3.4321 data: 0.0082 max mem: 33370 +Epoch: [27] [ 410/1319] eta: 0:52:03 lr: 1.7790255960455746e-05 loss: 0.0350 (0.0408) time: 3.4436 data: 0.0082 max mem: 33370 +Epoch: [27] [ 420/1319] eta: 0:51:30 lr: 1.7780688734824637e-05 loss: 0.0407 (0.0408) time: 3.4754 data: 0.0081 max mem: 33370 +Epoch: [27] [ 430/1319] eta: 0:50:56 lr: 1.777112093717916e-05 loss: 0.0346 (0.0408) time: 3.4596 data: 0.0083 max mem: 33370 +Epoch: [27] [ 440/1319] eta: 0:50:21 lr: 1.7761552567142895e-05 loss: 0.0348 (0.0409) time: 3.4371 data: 0.0088 max mem: 33370 +Epoch: [27] [ 450/1319] eta: 0:49:47 lr: 1.7751983624338938e-05 loss: 0.0407 (0.0408) time: 3.4419 data: 0.0088 max mem: 33370 +Epoch: [27] [ 460/1319] eta: 0:49:11 lr: 1.7742414108389917e-05 loss: 0.0366 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1.7291993287130824e-05 loss: 0.0315 (0.0410) time: 3.4284 data: 0.0083 max mem: 33370 +Epoch: [27] [ 940/1319] eta: 0:21:39 lr: 1.728239580690995e-05 loss: 0.0311 (0.0411) time: 3.4261 data: 0.0083 max mem: 33370 +Epoch: [27] [ 950/1319] eta: 0:21:05 lr: 1.727279773445306e-05 loss: 0.0319 (0.0411) time: 3.4147 data: 0.0083 max mem: 33370 +Epoch: [27] [ 960/1319] eta: 0:20:30 lr: 1.7263199069357895e-05 loss: 0.0360 (0.0410) time: 3.3838 data: 0.0080 max mem: 33370 +Epoch: [27] [ 970/1319] eta: 0:19:56 lr: 1.725359981122169e-05 loss: 0.0348 (0.0410) time: 3.3766 data: 0.0078 max mem: 33370 +Epoch: [27] [ 980/1319] eta: 0:19:22 lr: 1.7243999959641156e-05 loss: 0.0372 (0.0410) time: 3.4065 data: 0.0081 max mem: 33370 +Epoch: [27] [ 990/1319] eta: 0:18:47 lr: 1.7234399514212475e-05 loss: 0.0287 (0.0409) time: 3.4185 data: 0.0087 max mem: 33370 +Epoch: [27] [1000/1319] eta: 0:18:13 lr: 1.7224798474531302e-05 loss: 0.0375 (0.0410) time: 3.4486 data: 0.0089 max mem: 33370 +Epoch: [27] 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mem: 33370 +Epoch: [27] [1090/1319] eta: 0:13:04 lr: 1.7138362309061432e-05 loss: 0.0308 (0.0409) time: 3.4119 data: 0.0080 max mem: 33370 +Epoch: [27] [1100/1319] eta: 0:12:30 lr: 1.7128755304500424e-05 loss: 0.0358 (0.0409) time: 3.4318 data: 0.0084 max mem: 33370 +Epoch: [27] [1110/1319] eta: 0:11:56 lr: 1.7119147701204254e-05 loss: 0.0399 (0.0410) time: 3.4570 data: 0.0087 max mem: 33370 +Epoch: [27] [1120/1319] eta: 0:11:22 lr: 1.710953949876218e-05 loss: 0.0384 (0.0409) time: 3.4651 data: 0.0092 max mem: 33370 +Epoch: [27] [1130/1319] eta: 0:10:48 lr: 1.709993069676296e-05 loss: 0.0351 (0.0409) time: 3.4518 data: 0.0091 max mem: 33370 +Epoch: [27] [1140/1319] eta: 0:10:13 lr: 1.7090321294794796e-05 loss: 0.0400 (0.0409) time: 3.4688 data: 0.0083 max mem: 33370 +Epoch: [27] [1150/1319] eta: 0:09:39 lr: 1.7080711292445346e-05 loss: 0.0364 (0.0409) time: 3.4758 data: 0.0081 max mem: 33370 +Epoch: [27] [1160/1319] eta: 0:09:05 lr: 1.7071100689301735e-05 loss: 0.0364 (0.0410) time: 3.4429 data: 0.0084 max mem: 33370 +Epoch: [27] [1170/1319] eta: 0:08:31 lr: 1.706148948495055e-05 loss: 0.0384 (0.0410) time: 3.4372 data: 0.0086 max mem: 33370 +Epoch: [27] [1180/1319] eta: 0:07:56 lr: 1.705187767897781e-05 loss: 0.0374 (0.0410) time: 3.3998 data: 0.0082 max mem: 33370 +Epoch: [27] [1190/1319] eta: 0:07:22 lr: 1.704226527096902e-05 loss: 0.0363 (0.0411) time: 3.3940 data: 0.0081 max mem: 33370 +Epoch: [27] [1200/1319] eta: 0:06:48 lr: 1.703265226050912e-05 loss: 0.0318 (0.0410) time: 3.4462 data: 0.0084 max mem: 33370 +Epoch: [27] [1210/1319] eta: 0:06:13 lr: 1.702303864718251e-05 loss: 0.0341 (0.0410) time: 3.4537 data: 0.0083 max mem: 33370 +Epoch: [27] [1220/1319] eta: 0:05:39 lr: 1.7013424430573045e-05 loss: 0.0353 (0.0411) time: 3.4481 data: 0.0080 max mem: 33370 +Epoch: [27] [1230/1319] eta: 0:05:05 lr: 1.7003809610264022e-05 loss: 0.0435 (0.0412) time: 3.4624 data: 0.0082 max mem: 33370 +Epoch: [27] [1240/1319] eta: 0:04:30 lr: 1.6994194185838196e-05 loss: 0.0435 (0.0412) time: 3.4396 data: 0.0085 max mem: 33370 +Epoch: [27] [1250/1319] eta: 0:03:56 lr: 1.698457815687777e-05 loss: 0.0364 (0.0412) time: 3.4232 data: 0.0085 max mem: 33370 +Epoch: [27] [1260/1319] eta: 0:03:22 lr: 1.6974961522964392e-05 loss: 0.0349 (0.0412) time: 3.4372 data: 0.0084 max mem: 33370 +Epoch: [27] [1270/1319] eta: 0:02:48 lr: 1.6965344283679166e-05 loss: 0.0349 (0.0411) time: 3.4086 data: 0.0083 max mem: 33370 +Epoch: [27] [1280/1319] eta: 0:02:13 lr: 1.6955726438602627e-05 loss: 0.0345 (0.0411) time: 3.3908 data: 0.0085 max mem: 33370 +Epoch: [27] [1290/1319] eta: 0:01:39 lr: 1.694610798731476e-05 loss: 0.0345 (0.0411) time: 3.4245 data: 0.0088 max mem: 33370 +Epoch: [27] [1300/1319] eta: 0:01:05 lr: 1.6936488929395006e-05 loss: 0.0334 (0.0410) time: 3.4461 data: 0.0088 max mem: 33370 +Epoch: [27] [1310/1319] eta: 0:00:30 lr: 1.6926869264422233e-05 loss: 0.0358 (0.0411) time: 3.4469 data: 0.0083 max mem: 33370 +Epoch: [27] Total time: 1:15:24 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 2:44:04 time: 3.8262 data: 3.6867 max mem: 33370 +Test: [ 100/2573] eta: 0:04:44 time: 0.0776 data: 0.0014 max mem: 33370 +Test: [ 200/2573] eta: 0:03:52 time: 0.0799 data: 0.0015 max mem: 33370 +Test: [ 300/2573] eta: 0:03:28 time: 0.0816 data: 0.0014 max mem: 33370 +Test: [ 400/2573] eta: 0:03:12 time: 0.0816 data: 0.0015 max mem: 33370 +Test: [ 500/2573] eta: 0:03:00 time: 0.0809 data: 0.0014 max mem: 33370 +Test: [ 600/2573] eta: 0:02:50 time: 0.0809 data: 0.0015 max mem: 33370 +Test: [ 700/2573] eta: 0:02:40 time: 0.0805 data: 0.0016 max mem: 33370 +Test: [ 800/2573] eta: 0:02:31 time: 0.0837 data: 0.0013 max mem: 33370 +Test: [ 900/2573] eta: 0:02:21 time: 0.0804 data: 0.0013 max mem: 33370 +Test: [1000/2573] eta: 0:02:12 time: 0.0805 data: 0.0014 max mem: 33370 +Test: [1100/2573] eta: 0:02:03 time: 0.0801 data: 0.0013 max mem: 33370 +Test: [1200/2573] eta: 0:01:55 time: 0.0805 data: 0.0014 max mem: 33370 +Test: [1300/2573] eta: 0:01:46 time: 0.0803 data: 0.0013 max mem: 33370 +Test: [1400/2573] eta: 0:01:37 time: 0.0788 data: 0.0014 max mem: 33370 +Test: [1500/2573] eta: 0:01:29 time: 0.0802 data: 0.0014 max mem: 33370 +Test: [1600/2573] eta: 0:01:20 time: 0.0834 data: 0.0014 max mem: 33370 +Test: [1700/2573] eta: 0:01:12 time: 0.0789 data: 0.0014 max mem: 33370 +Test: [1800/2573] eta: 0:01:03 time: 0.0830 data: 0.0014 max mem: 33370 +Test: [1900/2573] eta: 0:00:55 time: 0.0788 data: 0.0015 max mem: 33370 +Test: [2000/2573] eta: 0:00:47 time: 0.0803 data: 0.0014 max mem: 33370 +Test: [2100/2573] eta: 0:00:38 time: 0.0822 data: 0.0015 max mem: 33370 +Test: [2200/2573] eta: 0:00:30 time: 0.0816 data: 0.0014 max mem: 33370 +Test: [2300/2573] eta: 0:00:22 time: 0.0813 data: 0.0014 max mem: 33370 +Test: [2400/2573] eta: 0:00:14 time: 0.0768 data: 0.0014 max mem: 33370 +Test: [2500/2573] eta: 0:00:05 time: 0.0811 data: 0.0016 max mem: 33370 +Test: Total time: 0:03:31 +Final results: +Mean IoU is 64.13 + + precision@0.5 = 72.12 + precision@0.6 = 66.71 + precision@0.7 = 59.62 + precision@0.8 = 49.18 + precision@0.9 = 24.71 + overall IoU = 61.36 + +Average object IoU 64.12783435309981 +Overall IoU 61.361976623535156 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [28] [ 0/1319] eta: 3:13:48 lr: 1.69182110465679e-05 loss: 0.0320 (0.0320) time: 8.8165 data: 2.0512 max mem: 33370 +Epoch: [28] [ 10/1319] eta: 1:25:35 lr: 1.690859022703219e-05 loss: 0.0365 (0.0374) time: 3.9230 data: 0.1940 max mem: 33370 +Epoch: [28] [ 20/1319] eta: 1:19:43 lr: 1.6898968799219036e-05 loss: 0.0365 (0.0367) time: 3.4259 data: 0.0080 max mem: 33370 +Epoch: [28] [ 30/1319] eta: 1:17:14 lr: 1.6889346762705132e-05 loss: 0.0381 (0.0384) time: 3.4151 data: 0.0079 max mem: 33370 +Epoch: [28] [ 40/1319] eta: 1:15:43 lr: 1.6879724117066593e-05 loss: 0.0381 (0.0379) time: 3.4160 data: 0.0082 max mem: 33370 +Epoch: [28] [ 50/1319] eta: 1:14:47 lr: 1.6870100861878995e-05 loss: 0.0369 (0.0387) time: 3.4445 data: 0.0081 max mem: 33370 +Epoch: [28] [ 60/1319] eta: 1:13:42 lr: 1.6860476996717327e-05 loss: 0.0351 (0.0376) time: 3.4317 data: 0.0084 max mem: 33370 +Epoch: [28] [ 70/1319] eta: 1:12:52 lr: 1.6850852521156025e-05 loss: 0.0342 (0.0382) time: 3.4113 data: 0.0087 max mem: 33370 +Epoch: [28] [ 80/1319] eta: 1:12:08 lr: 1.684122743476896e-05 loss: 0.0393 (0.0389) time: 3.4348 data: 0.0088 max mem: 33370 +Epoch: [28] [ 90/1319] eta: 1:11:24 lr: 1.6831601737129412e-05 loss: 0.0328 (0.0404) time: 3.4316 data: 0.0088 max mem: 33370 +Epoch: [28] [ 100/1319] eta: 1:10:45 lr: 1.6821975427810122e-05 loss: 0.0376 (0.0401) time: 3.4370 data: 0.0085 max mem: 33370 +Epoch: [28] [ 110/1319] eta: 1:10:02 lr: 1.6812348506383245e-05 loss: 0.0371 (0.0399) time: 3.4297 data: 0.0083 max mem: 33370 +Epoch: [28] [ 120/1319] eta: 1:09:23 lr: 1.680272097242036e-05 loss: 0.0368 (0.0395) time: 3.4209 data: 0.0081 max mem: 33370 +Epoch: [28] [ 130/1319] eta: 1:08:41 lr: 1.6793092825492484e-05 loss: 0.0403 (0.0395) time: 3.4144 data: 0.0079 max mem: 33370 +Epoch: [28] [ 140/1319] eta: 1:08:00 lr: 1.6783464065170062e-05 loss: 0.0378 (0.0392) time: 3.3937 data: 0.0080 max mem: 33370 +Epoch: [28] [ 150/1319] eta: 1:07:23 lr: 1.6773834691022944e-05 loss: 0.0331 (0.0393) time: 3.4117 data: 0.0079 max mem: 33370 +Epoch: [28] [ 160/1319] eta: 1:06:43 lr: 1.6764204702620422e-05 loss: 0.0361 (0.0393) time: 3.4087 data: 0.0081 max mem: 33370 +Epoch: [28] [ 170/1319] eta: 1:06:09 lr: 1.6754574099531206e-05 loss: 0.0357 (0.0392) time: 3.4220 data: 0.0083 max mem: 33370 +Epoch: [28] [ 180/1319] eta: 1:05:32 lr: 1.6744942881323427e-05 loss: 0.0351 (0.0392) time: 3.4336 data: 0.0091 max mem: 33370 +Epoch: [28] [ 190/1319] eta: 1:04:54 lr: 1.6735311047564646e-05 loss: 0.0351 (0.0396) time: 3.4007 data: 0.0093 max mem: 33370 +Epoch: [28] [ 200/1319] eta: 1:04:21 lr: 1.6725678597821815e-05 loss: 0.0346 (0.0395) time: 3.4348 data: 0.0090 max mem: 33370 +Epoch: [28] [ 210/1319] eta: 1:03:44 lr: 1.6716045531661334e-05 loss: 0.0346 (0.0394) time: 3.4434 data: 0.0091 max mem: 33370 +Epoch: [28] [ 220/1319] eta: 1:03:09 lr: 1.6706411848649008e-05 loss: 0.0359 (0.0398) time: 3.4220 data: 0.0087 max mem: 33370 +Epoch: [28] [ 230/1319] eta: 1:02:33 lr: 1.6696777548350058e-05 loss: 0.0355 (0.0396) time: 3.4245 data: 0.0086 max mem: 33370 +Epoch: [28] [ 240/1319] eta: 1:01:58 lr: 1.668714263032912e-05 loss: 0.0343 (0.0397) time: 3.4230 data: 0.0086 max mem: 33370 +Epoch: [28] [ 250/1319] eta: 1:01:21 lr: 1.6677507094150246e-05 loss: 0.0368 (0.0399) time: 3.4148 data: 0.0082 max mem: 33370 +Epoch: [28] [ 260/1319] eta: 1:00:47 lr: 1.6667870939376894e-05 loss: 0.0375 (0.0399) time: 3.4232 data: 0.0083 max mem: 33370 +Epoch: [28] [ 270/1319] eta: 1:00:12 lr: 1.6658234165571935e-05 loss: 0.0380 (0.0399) time: 3.4386 data: 0.0086 max mem: 33370 +Epoch: [28] [ 280/1319] eta: 0:59:38 lr: 1.6648596772297652e-05 loss: 0.0389 (0.0398) time: 3.4441 data: 0.0090 max mem: 33370 +Epoch: [28] [ 290/1319] eta: 0:59:03 lr: 1.6638958759115745e-05 loss: 0.0399 (0.0399) time: 3.4482 data: 0.0087 max mem: 33370 +Epoch: [28] [ 300/1319] eta: 0:58:27 lr: 1.6629320125587307e-05 loss: 0.0324 (0.0398) time: 3.4077 data: 0.0087 max mem: 33370 +Epoch: [28] [ 310/1319] eta: 0:57:53 lr: 1.6619680871272843e-05 loss: 0.0321 (0.0396) time: 3.4205 data: 0.0086 max mem: 33370 +Epoch: [28] [ 320/1319] eta: 0:57:18 lr: 1.6610040995732262e-05 loss: 0.0351 (0.0398) time: 3.4529 data: 0.0084 max mem: 33370 +Epoch: [28] [ 330/1319] eta: 0:56:43 lr: 1.6600400498524878e-05 loss: 0.0341 (0.0397) time: 3.4304 data: 0.0088 max mem: 33370 +Epoch: [28] [ 340/1319] eta: 0:56:08 lr: 1.659075937920942e-05 loss: 0.0344 (0.0397) time: 3.4205 data: 0.0090 max mem: 33370 +Epoch: [28] [ 350/1319] eta: 0:55:33 lr: 1.6581117637343994e-05 loss: 0.0359 (0.0398) time: 3.4209 data: 0.0089 max mem: 33370 +Epoch: [28] [ 360/1319] eta: 0:54:59 lr: 1.657147527248612e-05 loss: 0.0324 (0.0397) time: 3.4228 data: 0.0088 max mem: 33370 +Epoch: [28] [ 370/1319] eta: 0:54:24 lr: 1.6561832284192722e-05 loss: 0.0345 (0.0398) time: 3.4216 data: 0.0085 max mem: 33370 +Epoch: [28] [ 380/1319] eta: 0:53:50 lr: 1.6552188672020112e-05 loss: 0.0352 (0.0397) time: 3.4386 data: 0.0084 max mem: 33370 +Epoch: [28] [ 390/1319] eta: 0:53:15 lr: 1.654254443552401e-05 loss: 0.0309 (0.0396) time: 3.4509 data: 0.0083 max mem: 33370 +Epoch: [28] [ 400/1319] eta: 0:52:40 lr: 1.6532899574259518e-05 loss: 0.0322 (0.0394) time: 3.4283 data: 0.0083 max mem: 33370 +Epoch: [28] [ 410/1319] eta: 0:52:06 lr: 1.6523254087781154e-05 loss: 0.0352 (0.0395) time: 3.4200 data: 0.0085 max mem: 33370 +Epoch: [28] [ 420/1319] eta: 0:51:31 lr: 1.651360797564279e-05 loss: 0.0379 (0.0396) time: 3.4148 data: 0.0090 max mem: 33370 +Epoch: [28] [ 430/1319] eta: 0:50:56 lr: 1.6503961237397734e-05 loss: 0.0344 (0.0394) time: 3.4310 data: 0.0089 max mem: 33370 +Epoch: [28] [ 440/1319] eta: 0:50:23 lr: 1.6494313872598656e-05 loss: 0.0320 (0.0393) time: 3.4643 data: 0.0084 max mem: 33370 +Epoch: [28] [ 450/1319] eta: 0:49:49 lr: 1.6484665880797628e-05 loss: 0.0342 (0.0394) time: 3.4650 data: 0.0081 max mem: 33370 +Epoch: [28] [ 460/1319] eta: 0:49:14 lr: 1.6475017261546112e-05 loss: 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(0.0399) time: 3.4191 data: 0.0083 max mem: 33370 +Epoch: [28] [ 860/1319] eta: 0:26:16 lr: 1.608855275594644e-05 loss: 0.0384 (0.0400) time: 3.4269 data: 0.0087 max mem: 33370 +Epoch: [28] [ 870/1319] eta: 0:25:41 lr: 1.6078878017308325e-05 loss: 0.0413 (0.0401) time: 3.4260 data: 0.0090 max mem: 33370 +Epoch: [28] [ 880/1319] eta: 0:25:07 lr: 1.6069202631811695e-05 loss: 0.0413 (0.0401) time: 3.4311 data: 0.0088 max mem: 33370 +Epoch: [28] [ 890/1319] eta: 0:24:33 lr: 1.6059526598980493e-05 loss: 0.0373 (0.0401) time: 3.4262 data: 0.0082 max mem: 33370 +Epoch: [28] [ 900/1319] eta: 0:23:58 lr: 1.6049849918337977e-05 loss: 0.0383 (0.0401) time: 3.4169 data: 0.0082 max mem: 33370 +Epoch: [28] [ 910/1319] eta: 0:23:24 lr: 1.6040172589406754e-05 loss: 0.0372 (0.0401) time: 3.4110 data: 0.0085 max mem: 33370 +Epoch: [28] [ 920/1319] eta: 0:22:49 lr: 1.603049461170875e-05 loss: 0.0346 (0.0400) time: 3.4140 data: 0.0081 max mem: 33370 +Epoch: [28] [ 930/1319] eta: 0:22:15 lr: 1.602081598476522e-05 loss: 0.0332 (0.0400) time: 3.4239 data: 0.0077 max mem: 33370 +Epoch: [28] [ 940/1319] eta: 0:21:41 lr: 1.6011136708096744e-05 loss: 0.0371 (0.0401) time: 3.4195 data: 0.0083 max mem: 33370 +Epoch: [28] [ 950/1319] eta: 0:21:06 lr: 1.6001456781223216e-05 loss: 0.0371 (0.0400) time: 3.4238 data: 0.0088 max mem: 33370 +Epoch: [28] [ 960/1319] eta: 0:20:32 lr: 1.599177620366387e-05 loss: 0.0323 (0.0400) time: 3.4287 data: 0.0091 max mem: 33370 +Epoch: [28] [ 970/1319] eta: 0:19:58 lr: 1.598209497493724e-05 loss: 0.0350 (0.0400) time: 3.4180 data: 0.0089 max mem: 33370 +Epoch: [28] [ 980/1319] eta: 0:19:23 lr: 1.5972413094561205e-05 loss: 0.0366 (0.0400) time: 3.4170 data: 0.0082 max mem: 33370 +Epoch: [28] [ 990/1319] eta: 0:18:49 lr: 1.5962730562052938e-05 loss: 0.0365 (0.0400) time: 3.4260 data: 0.0080 max mem: 33370 +Epoch: [28] [1000/1319] eta: 0:18:14 lr: 1.5953047376928946e-05 loss: 0.0376 (0.0400) time: 3.4107 data: 0.0079 max mem: 33370 +Epoch: [28] 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mem: 33370 +Epoch: [28] [1090/1319] eta: 0:13:06 lr: 1.5865869262987425e-05 loss: 0.0391 (0.0402) time: 3.4438 data: 0.0082 max mem: 33370 +Epoch: [28] [1100/1319] eta: 0:12:31 lr: 1.5856179524962237e-05 loss: 0.0399 (0.0402) time: 3.4315 data: 0.0079 max mem: 33370 +Epoch: [28] [1110/1319] eta: 0:11:57 lr: 1.5846489128957288e-05 loss: 0.0390 (0.0402) time: 3.4230 data: 0.0084 max mem: 33370 +Epoch: [28] [1120/1319] eta: 0:11:23 lr: 1.5836798074480774e-05 loss: 0.0373 (0.0402) time: 3.4368 data: 0.0090 max mem: 33370 +Epoch: [28] [1130/1319] eta: 0:10:48 lr: 1.582710636104018e-05 loss: 0.0376 (0.0403) time: 3.4329 data: 0.0092 max mem: 33370 +Epoch: [28] [1140/1319] eta: 0:10:14 lr: 1.5817413988142284e-05 loss: 0.0376 (0.0403) time: 3.4008 data: 0.0090 max mem: 33370 +Epoch: [28] [1150/1319] eta: 0:09:39 lr: 1.5807720955293166e-05 loss: 0.0412 (0.0403) time: 3.3950 data: 0.0087 max mem: 33370 +Epoch: [28] [1160/1319] eta: 0:09:05 lr: 1.579802726199819e-05 loss: 0.0345 (0.0403) time: 3.4347 data: 0.0089 max mem: 33370 +Epoch: [28] [1170/1319] eta: 0:08:31 lr: 1.5788332907762015e-05 loss: 0.0338 (0.0402) time: 3.4633 data: 0.0087 max mem: 33370 +Epoch: [28] [1180/1319] eta: 0:07:57 lr: 1.577863789208859e-05 loss: 0.0368 (0.0403) time: 3.4461 data: 0.0092 max mem: 33370 +Epoch: [28] [1190/1319] eta: 0:07:22 lr: 1.576894221448116e-05 loss: 0.0361 (0.0403) time: 3.4396 data: 0.0094 max mem: 33370 +Epoch: [28] [1200/1319] eta: 0:06:48 lr: 1.5759245874442245e-05 loss: 0.0308 (0.0402) time: 3.4180 data: 0.0090 max mem: 33370 +Epoch: [28] [1210/1319] eta: 0:06:14 lr: 1.5749548871473663e-05 loss: 0.0334 (0.0403) time: 3.3968 data: 0.0093 max mem: 33370 +Epoch: [28] [1220/1319] eta: 0:05:39 lr: 1.57398512050765e-05 loss: 0.0410 (0.0403) time: 3.4116 data: 0.0090 max mem: 33370 +Epoch: [28] [1230/1319] eta: 0:05:05 lr: 1.5730152874751144e-05 loss: 0.0396 (0.0402) time: 3.4460 data: 0.0086 max mem: 33370 +Epoch: [28] [1240/1319] eta: 0:04:31 lr: 1.572045387999725e-05 loss: 0.0385 (0.0402) time: 3.4471 data: 0.0091 max mem: 33370 +Epoch: [28] [1250/1319] eta: 0:03:56 lr: 1.5710754220313764e-05 loss: 0.0373 (0.0402) time: 3.4351 data: 0.0092 max mem: 33370 +Epoch: [28] [1260/1319] eta: 0:03:22 lr: 1.5701053895198906e-05 loss: 0.0371 (0.0402) time: 3.4521 data: 0.0089 max mem: 33370 +Epoch: [28] [1270/1319] eta: 0:02:48 lr: 1.5691352904150157e-05 loss: 0.0360 (0.0402) time: 3.4560 data: 0.0091 max mem: 33370 +Epoch: [28] [1280/1319] eta: 0:02:13 lr: 1.5681651246664294e-05 loss: 0.0334 (0.0401) time: 3.4357 data: 0.0090 max mem: 33370 +Epoch: [28] [1290/1319] eta: 0:01:39 lr: 1.5671948922237363e-05 loss: 0.0352 (0.0401) time: 3.4349 data: 0.0083 max mem: 33370 +Epoch: [28] [1300/1319] eta: 0:01:05 lr: 1.5662245930364672e-05 loss: 0.0377 (0.0401) time: 3.4383 data: 0.0083 max mem: 33370 +Epoch: [28] [1310/1319] eta: 0:00:30 lr: 1.5652542270540813e-05 loss: 0.0345 (0.0401) time: 3.4066 data: 0.0081 max mem: 33370 +Epoch: [28] Total time: 1:15:27 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 2:14:43 time: 3.1418 data: 3.0522 max mem: 33370 +Test: [ 100/2573] eta: 0:04:28 time: 0.0777 data: 0.0015 max mem: 33370 +Test: [ 200/2573] eta: 0:03:44 time: 0.0793 data: 0.0014 max mem: 33370 +Test: [ 300/2573] eta: 0:03:22 time: 0.0809 data: 0.0014 max mem: 33370 +Test: [ 400/2573] eta: 0:03:08 time: 0.0817 data: 0.0015 max mem: 33370 +Test: [ 500/2573] eta: 0:02:57 time: 0.0799 data: 0.0014 max mem: 33370 +Test: [ 600/2573] eta: 0:02:47 time: 0.0800 data: 0.0015 max mem: 33370 +Test: [ 700/2573] eta: 0:02:38 time: 0.0813 data: 0.0017 max mem: 33370 +Test: [ 800/2573] eta: 0:02:29 time: 0.0834 data: 0.0014 max mem: 33370 +Test: [ 900/2573] eta: 0:02:20 time: 0.0808 data: 0.0015 max mem: 33370 +Test: [1000/2573] eta: 0:02:11 time: 0.0815 data: 0.0015 max mem: 33370 +Test: [1100/2573] eta: 0:02:02 time: 0.0815 data: 0.0016 max mem: 33370 +Test: [1200/2573] eta: 0:01:54 time: 0.0811 data: 0.0014 max mem: 33370 +Test: [1300/2573] eta: 0:01:45 time: 0.0811 data: 0.0014 max mem: 33370 +Test: [1400/2573] eta: 0:01:37 time: 0.0794 data: 0.0015 max mem: 33370 +Test: [1500/2573] eta: 0:01:28 time: 0.0815 data: 0.0015 max mem: 33370 +Test: [1600/2573] eta: 0:01:20 time: 0.0844 data: 0.0014 max mem: 33370 +Test: [1700/2573] eta: 0:01:12 time: 0.0816 data: 0.0015 max mem: 33370 +Test: [1800/2573] eta: 0:01:03 time: 0.0831 data: 0.0014 max mem: 33370 +Test: [1900/2573] eta: 0:00:55 time: 0.0803 data: 0.0014 max mem: 33370 +Test: [2000/2573] eta: 0:00:47 time: 0.0810 data: 0.0015 max mem: 33370 +Test: [2100/2573] eta: 0:00:38 time: 0.0838 data: 0.0015 max mem: 33370 +Test: [2200/2573] eta: 0:00:30 time: 0.0822 data: 0.0014 max mem: 33370 +Test: [2300/2573] eta: 0:00:22 time: 0.0833 data: 0.0015 max mem: 33370 +Test: [2400/2573] eta: 0:00:14 time: 0.0785 data: 0.0015 max mem: 33370 +Test: [2500/2573] eta: 0:00:05 time: 0.0813 data: 0.0015 max mem: 33370 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: Total time: 0:03:32 +Final results: +Mean IoU is 64.28 + + precision@0.5 = 72.04 + precision@0.6 = 66.81 + precision@0.7 = 60.25 + precision@0.8 = 49.37 + precision@0.9 = 24.69 + overall IoU = 61.47 + +Average object IoU 64.28420505337176 +Overall IoU 61.47380065917969 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [29] [ 0/1319] eta: 2:53:51 lr: 1.5643808405182777e-05 loss: 0.0188 (0.0188) time: 7.9089 data: 2.3591 max mem: 33370 +Epoch: [29] [ 10/1319] eta: 1:23:26 lr: 1.563410347485666e-05 loss: 0.0379 (0.0411) time: 3.8247 data: 0.2224 max mem: 33370 +Epoch: [29] [ 20/1319] eta: 1:18:47 lr: 1.5624397875109532e-05 loss: 0.0425 (0.0417) time: 3.4259 data: 0.0083 max mem: 33370 +Epoch: [29] [ 30/1319] eta: 1:16:57 lr: 1.5614691605433113e-05 loss: 0.0384 (0.0413) time: 3.4490 data: 0.0082 max mem: 33370 +Epoch: [29] [ 40/1319] eta: 1:15:26 lr: 1.5604984665318397e-05 loss: 0.0356 (0.0395) time: 3.4334 data: 0.0083 max mem: 33370 +Epoch: [29] [ 50/1319] eta: 1:14:19 lr: 1.5595277054255625e-05 loss: 0.0356 (0.0403) time: 3.4080 data: 0.0084 max mem: 33370 +Epoch: [29] [ 60/1319] eta: 1:13:16 lr: 1.558556877173431e-05 loss: 0.0354 (0.0396) time: 3.3971 data: 0.0085 max mem: 33370 +Epoch: [29] [ 70/1319] eta: 1:12:21 lr: 1.557585981724323e-05 loss: 0.0352 (0.0397) time: 3.3783 data: 0.0084 max mem: 33370 +Epoch: [29] [ 80/1319] eta: 1:11:40 lr: 1.5566150190270393e-05 loss: 0.0352 (0.0392) time: 3.4041 data: 0.0084 max mem: 33370 +Epoch: [29] [ 90/1319] eta: 1:10:59 lr: 1.5556439890303075e-05 loss: 0.0332 (0.0394) time: 3.4322 data: 0.0086 max mem: 33370 +Epoch: [29] [ 100/1319] eta: 1:10:16 lr: 1.554672891682782e-05 loss: 0.0341 (0.0389) time: 3.4137 data: 0.0084 max mem: 33370 +Epoch: [29] [ 110/1319] eta: 1:09:41 lr: 1.55370172693304e-05 loss: 0.0342 (0.0387) time: 3.4263 data: 0.0084 max mem: 33370 +Epoch: [29] [ 120/1319] eta: 1:09:03 lr: 1.552730494729585e-05 loss: 0.0343 (0.0390) time: 3.4401 data: 0.0086 max mem: 33370 +Epoch: [29] [ 130/1319] eta: 1:08:25 lr: 1.551759195020846e-05 loss: 0.0354 (0.0391) time: 3.4201 data: 0.0093 max mem: 33370 +Epoch: [29] [ 140/1319] eta: 1:07:48 lr: 1.5507878277551742e-05 loss: 0.0379 (0.0397) time: 3.4197 data: 0.0096 max mem: 33370 +Epoch: [29] [ 150/1319] eta: 1:07:07 lr: 1.5498163928808475e-05 loss: 0.0347 (0.0396) time: 3.3964 data: 0.0084 max mem: 33370 +Epoch: [29] [ 160/1319] eta: 1:06:32 lr: 1.548844890346068e-05 loss: 0.0305 (0.0394) time: 3.4002 data: 0.0080 max mem: 33370 +Epoch: [29] [ 170/1319] eta: 1:05:58 lr: 1.547873320098961e-05 loss: 0.0330 (0.0390) time: 3.4405 data: 0.0082 max mem: 33370 +Epoch: [29] [ 180/1319] eta: 1:05:23 lr: 1.546901682087577e-05 loss: 0.0350 (0.0393) time: 3.4443 data: 0.0084 max mem: 33370 +Epoch: [29] [ 190/1319] eta: 1:04:47 lr: 1.5459299762598884e-05 loss: 0.0376 (0.0390) time: 3.4271 data: 0.0083 max mem: 33370 +Epoch: [29] [ 200/1319] eta: 1:04:12 lr: 1.5449582025637935e-05 loss: 0.0328 (0.0397) time: 3.4295 data: 0.0085 max mem: 33370 +Epoch: [29] [ 210/1319] eta: 1:03:38 lr: 1.543986360947113e-05 loss: 0.0335 (0.0396) time: 3.4473 data: 0.0087 max mem: 33370 +Epoch: [29] [ 220/1319] eta: 1:03:06 lr: 1.543014451357591e-05 loss: 0.0366 (0.0397) time: 3.4698 data: 0.0083 max mem: 33370 +Epoch: [29] [ 230/1319] eta: 1:02:31 lr: 1.5420424737428955e-05 loss: 0.0365 (0.0397) time: 3.4610 data: 0.0078 max mem: 33370 +Epoch: [29] [ 240/1319] eta: 1:01:56 lr: 1.541070428050616e-05 loss: 0.0370 (0.0398) time: 3.4355 data: 0.0078 max mem: 33370 +Epoch: [29] [ 250/1319] eta: 1:01:22 lr: 1.5400983142282667e-05 loss: 0.0382 (0.0398) time: 3.4419 data: 0.0082 max mem: 33370 +Epoch: [29] [ 260/1319] eta: 1:00:44 lr: 1.539126132223283e-05 loss: 0.0391 (0.0399) time: 3.4028 data: 0.0085 max mem: 33370 +Epoch: [29] [ 270/1319] eta: 1:00:08 lr: 1.538153881983024e-05 loss: 0.0411 (0.0399) time: 3.3832 data: 0.0085 max mem: 33370 +Epoch: [29] [ 280/1319] eta: 0:59:34 lr: 1.53718156345477e-05 loss: 0.0390 (0.0400) time: 3.4223 data: 0.0087 max mem: 33370 +Epoch: [29] [ 290/1319] eta: 0:58:59 lr: 1.5362091765857252e-05 loss: 0.0310 (0.0400) time: 3.4309 data: 0.0084 max mem: 33370 +Epoch: [29] [ 300/1319] eta: 0:58:26 lr: 1.5352367213230138e-05 loss: 0.0379 (0.0403) time: 3.4493 data: 0.0082 max mem: 33370 +Epoch: [29] [ 310/1319] eta: 0:57:51 lr: 1.5342641976136825e-05 loss: 0.0347 (0.0401) time: 3.4514 data: 0.0082 max mem: 33370 +Epoch: [29] [ 320/1319] eta: 0:57:15 lr: 1.5332916054047e-05 loss: 0.0333 (0.0407) time: 3.4163 data: 0.0082 max mem: 33370 +Epoch: [29] [ 330/1319] eta: 0:56:41 lr: 1.532318944642957e-05 loss: 0.0338 (0.0404) time: 3.4195 data: 0.0086 max mem: 33370 +Epoch: [29] [ 340/1319] eta: 0:56:08 lr: 1.5313462152752656e-05 loss: 0.0327 (0.0403) time: 3.4569 data: 0.0087 max mem: 33370 +Epoch: [29] [ 350/1319] eta: 0:55:34 lr: 1.5303734172483566e-05 loss: 0.0360 (0.0403) time: 3.4712 data: 0.0085 max mem: 33370 +Epoch: [29] [ 360/1319] eta: 0:54:58 lr: 1.529400550508885e-05 loss: 0.0354 (0.0401) time: 3.4350 data: 0.0084 max mem: 33370 +Epoch: [29] [ 370/1319] eta: 0:54:23 lr: 1.528427615003424e-05 loss: 0.0336 (0.0401) time: 3.4079 data: 0.0089 max mem: 33370 +Epoch: [29] [ 380/1319] eta: 0:53:48 lr: 1.5274546106784702e-05 loss: 0.0333 (0.0402) time: 3.4064 data: 0.0090 max mem: 33370 +Epoch: [29] [ 390/1319] eta: 0:53:14 lr: 1.526481537480438e-05 loss: 0.0323 (0.0400) time: 3.4216 data: 0.0086 max mem: 33370 +Epoch: [29] [ 400/1319] eta: 0:52:39 lr: 1.525508395355664e-05 loss: 0.0338 (0.0400) time: 3.4245 data: 0.0084 max mem: 33370 +Epoch: [29] [ 410/1319] eta: 0:52:04 lr: 1.5245351842504036e-05 loss: 0.0345 (0.0399) time: 3.4110 data: 0.0084 max mem: 33370 +Epoch: [29] [ 420/1319] eta: 0:51:30 lr: 1.5235619041108326e-05 loss: 0.0333 (0.0399) time: 3.4465 data: 0.0091 max mem: 33370 +Epoch: [29] [ 430/1319] eta: 0:50:54 lr: 1.5225885548830468e-05 loss: 0.0333 (0.0401) time: 3.4161 data: 0.0090 max mem: 33370 +Epoch: [29] [ 440/1319] eta: 0:50:20 lr: 1.5216151365130616e-05 loss: 0.0313 (0.0399) time: 3.3895 data: 0.0085 max mem: 33370 +Epoch: [29] [ 450/1319] eta: 0:49:44 lr: 1.520641648946812e-05 loss: 0.0348 (0.0400) time: 3.4089 data: 0.0084 max mem: 33370 +Epoch: [29] [ 460/1319] eta: 0:49:09 lr: 1.519668092130151e-05 loss: 0.0391 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1.4738317906666963e-05 loss: 0.0354 (0.0395) time: 3.3674 data: 0.0090 max mem: 33370 +Epoch: [29] [ 940/1319] eta: 0:21:40 lr: 1.4728548445256565e-05 loss: 0.0354 (0.0395) time: 3.3558 data: 0.0085 max mem: 33370 +Epoch: [29] [ 950/1319] eta: 0:21:06 lr: 1.471877826378261e-05 loss: 0.0341 (0.0395) time: 3.3946 data: 0.0082 max mem: 33370 +Epoch: [29] [ 960/1319] eta: 0:20:31 lr: 1.4709007361660864e-05 loss: 0.0341 (0.0396) time: 3.4288 data: 0.0082 max mem: 33370 +Epoch: [29] [ 970/1319] eta: 0:19:57 lr: 1.4699235738306196e-05 loss: 0.0369 (0.0395) time: 3.4270 data: 0.0082 max mem: 33370 +Epoch: [29] [ 980/1319] eta: 0:19:23 lr: 1.4689463393132561e-05 loss: 0.0308 (0.0395) time: 3.4497 data: 0.0081 max mem: 33370 +Epoch: [29] [ 990/1319] eta: 0:18:49 lr: 1.4679690325553006e-05 loss: 0.0281 (0.0395) time: 3.4639 data: 0.0081 max mem: 33370 +Epoch: [29] [1000/1319] eta: 0:18:14 lr: 1.466991653497966e-05 loss: 0.0338 (0.0395) time: 3.4370 data: 0.0080 max mem: 33370 +Epoch: [29] 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3.4689 data: 0.0081 max mem: 33370 +Epoch: [29] [1170/1319] eta: 0:08:31 lr: 1.4503650903081281e-05 loss: 0.0345 (0.0394) time: 3.4393 data: 0.0083 max mem: 33370 +Epoch: [29] [1180/1319] eta: 0:07:57 lr: 1.449386399704267e-05 loss: 0.0348 (0.0394) time: 3.4409 data: 0.0083 max mem: 33370 +Epoch: [29] [1190/1319] eta: 0:07:22 lr: 1.4484076356664761e-05 loss: 0.0324 (0.0394) time: 3.4332 data: 0.0081 max mem: 33370 +Epoch: [29] [1200/1319] eta: 0:06:48 lr: 1.447428798134101e-05 loss: 0.0348 (0.0393) time: 3.3813 data: 0.0081 max mem: 33370 +Epoch: [29] [1210/1319] eta: 0:06:14 lr: 1.4464498870463896e-05 loss: 0.0342 (0.0393) time: 3.4263 data: 0.0085 max mem: 33370 +Epoch: [29] [1220/1319] eta: 0:05:39 lr: 1.4454709023424959e-05 loss: 0.0309 (0.0393) time: 3.4291 data: 0.0086 max mem: 33370 +Epoch: [29] [1230/1319] eta: 0:05:05 lr: 1.444491843961477e-05 loss: 0.0369 (0.0393) time: 3.4133 data: 0.0082 max mem: 33370 +Epoch: [29] [1240/1319] eta: 0:04:31 lr: 1.4435127118422938e-05 loss: 0.0381 (0.0393) time: 3.4092 data: 0.0087 max mem: 33370 +Epoch: [29] [1250/1319] eta: 0:03:56 lr: 1.442533505923811e-05 loss: 0.0399 (0.0393) time: 3.3998 data: 0.0096 max mem: 33370 +Epoch: [29] [1260/1319] eta: 0:03:22 lr: 1.4415542261447945e-05 loss: 0.0398 (0.0393) time: 3.4174 data: 0.0092 max mem: 33370 +Epoch: [29] [1270/1319] eta: 0:02:48 lr: 1.4405748724439155e-05 loss: 0.0355 (0.0394) time: 3.4239 data: 0.0086 max mem: 33370 +Epoch: [29] [1280/1319] eta: 0:02:13 lr: 1.4395954447597464e-05 loss: 0.0346 (0.0394) time: 3.4145 data: 0.0087 max mem: 33370 +Epoch: [29] [1290/1319] eta: 0:01:39 lr: 1.4386159430307632e-05 loss: 0.0348 (0.0395) time: 3.3734 data: 0.0086 max mem: 33370 +Epoch: [29] [1300/1319] eta: 0:01:05 lr: 1.4376363671953435e-05 loss: 0.0354 (0.0395) time: 3.3770 data: 0.0087 max mem: 33370 +Epoch: [29] [1310/1319] eta: 0:00:30 lr: 1.4366567171917672e-05 loss: 0.0337 (0.0395) time: 3.4148 data: 0.0088 max mem: 33370 +Epoch: [29] Total time: 1:15:24 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 2:22:25 time: 3.3213 data: 3.2254 max mem: 33370 +Test: [ 100/2573] eta: 0:04:32 time: 0.0782 data: 0.0015 max mem: 33370 +Test: [ 200/2573] eta: 0:03:46 time: 0.0807 data: 0.0014 max mem: 33370 +Test: [ 300/2573] eta: 0:03:24 time: 0.0826 data: 0.0014 max mem: 33370 +Test: [ 400/2573] eta: 0:03:10 time: 0.0829 data: 0.0015 max mem: 33370 +Test: [ 500/2573] eta: 0:02:59 time: 0.0807 data: 0.0014 max mem: 33370 +Test: [ 600/2573] eta: 0:02:48 time: 0.0803 data: 0.0014 max mem: 33370 +Test: [ 700/2573] eta: 0:02:39 time: 0.0817 data: 0.0015 max mem: 33370 +Test: [ 800/2573] eta: 0:02:30 time: 0.0836 data: 0.0014 max mem: 33370 +Test: [ 900/2573] eta: 0:02:21 time: 0.0813 data: 0.0016 max mem: 33370 +Test: [1000/2573] eta: 0:02:12 time: 0.0800 data: 0.0014 max mem: 33370 +Test: [1100/2573] eta: 0:02:03 time: 0.0800 data: 0.0014 max mem: 33370 +Test: [1200/2573] eta: 0:01:54 time: 0.0818 data: 0.0015 max mem: 33370 +Test: [1300/2573] eta: 0:01:46 time: 0.0800 data: 0.0014 max mem: 33370 +Test: [1400/2573] eta: 0:01:37 time: 0.0796 data: 0.0015 max mem: 33370 +Test: [1500/2573] eta: 0:01:29 time: 0.0816 data: 0.0015 max mem: 33370 +Test: [1600/2573] eta: 0:01:20 time: 0.0843 data: 0.0014 max mem: 33370 +Test: [1700/2573] eta: 0:01:12 time: 0.0793 data: 0.0015 max mem: 33370 +Test: [1800/2573] eta: 0:01:03 time: 0.0817 data: 0.0014 max mem: 33370 +Test: [1900/2573] eta: 0:00:55 time: 0.0798 data: 0.0014 max mem: 33370 +Test: [2000/2573] eta: 0:00:47 time: 0.0800 data: 0.0014 max mem: 33370 +Test: [2100/2573] eta: 0:00:38 time: 0.0820 data: 0.0013 max mem: 33370 +Test: [2200/2573] eta: 0:00:30 time: 0.0815 data: 0.0014 max mem: 33370 +Test: [2300/2573] eta: 0:00:22 time: 0.0825 data: 0.0015 max mem: 33370 +Test: [2400/2573] eta: 0:00:14 time: 0.0776 data: 0.0015 max mem: 33370 +Test: [2500/2573] eta: 0:00:05 time: 0.0801 data: 0.0014 max mem: 33370 +Test: Total time: 0:03:31 +Final results: +Mean IoU is 64.03 + + precision@0.5 = 71.77 + precision@0.6 = 66.85 + precision@0.7 = 60.62 + precision@0.8 = 49.49 + precision@0.9 = 25.08 + overall IoU = 61.59 + +Average object IoU 64.03479416614914 +Overall IoU 61.58808517456055 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [30] [ 0/1319] eta: 3:14:18 lr: 1.4357749687236825e-05 loss: 0.0381 (0.0381) time: 8.8390 data: 2.1063 max mem: 33370 +Epoch: [30] [ 10/1319] eta: 1:25:04 lr: 1.4347951776302166e-05 loss: 0.0373 (0.0376) time: 3.8994 data: 0.1991 max mem: 33370 +Epoch: [30] [ 20/1319] eta: 1:19:34 lr: 1.433815312189048e-05 loss: 0.0368 (0.0392) time: 3.4170 data: 0.0082 max mem: 33370 +Epoch: [30] [ 30/1319] eta: 1:17:14 lr: 1.4328353723380728e-05 loss: 0.0362 (0.0384) time: 3.4280 data: 0.0080 max mem: 33370 +Epoch: [30] [ 40/1319] eta: 1:15:41 lr: 1.431855358015087e-05 loss: 0.0346 (0.0379) time: 3.4208 data: 0.0081 max mem: 33370 +Epoch: [30] [ 50/1319] eta: 1:14:34 lr: 1.4308752691577878e-05 loss: 0.0284 (0.0374) time: 3.4184 data: 0.0086 max mem: 33370 +Epoch: [30] [ 60/1319] eta: 1:13:41 lr: 1.4298951057037729e-05 loss: 0.0321 (0.0378) time: 3.4327 data: 0.0086 max mem: 33370 +Epoch: [30] [ 70/1319] eta: 1:12:54 lr: 1.4289148675905387e-05 loss: 0.0403 (0.0381) time: 3.4430 data: 0.0082 max mem: 33370 +Epoch: [30] [ 80/1319] eta: 1:12:09 lr: 1.4279345547554832e-05 loss: 0.0403 (0.0384) time: 3.4401 data: 0.0086 max mem: 33370 +Epoch: [30] [ 90/1319] eta: 1:11:20 lr: 1.4269541671359036e-05 loss: 0.0346 (0.0386) time: 3.4131 data: 0.0088 max mem: 33370 +Epoch: [30] [ 100/1319] eta: 1:10:39 lr: 1.4259737046689963e-05 loss: 0.0382 (0.0403) time: 3.4089 data: 0.0084 max mem: 33370 +Epoch: [30] [ 110/1319] eta: 1:10:02 lr: 1.424993167291858e-05 loss: 0.0382 (0.0400) time: 3.4431 data: 0.0084 max mem: 33370 +Epoch: [30] [ 120/1319] eta: 1:09:19 lr: 1.4240125549414829e-05 loss: 0.0349 (0.0397) time: 3.4287 data: 0.0086 max mem: 33370 +Epoch: [30] [ 130/1319] eta: 1:08:42 lr: 1.4230318675547643e-05 loss: 0.0378 (0.0402) time: 3.4215 data: 0.0087 max mem: 33370 +Epoch: [30] [ 140/1319] eta: 1:08:08 lr: 1.4220511050684946e-05 loss: 0.0373 (0.0398) time: 3.4598 data: 0.0091 max mem: 33370 +Epoch: [30] [ 150/1319] eta: 1:07:34 lr: 1.4210702674193643e-05 loss: 0.0373 (0.0398) time: 3.4720 data: 0.0089 max mem: 33370 +Epoch: [30] [ 160/1319] eta: 1:06:53 lr: 1.420089354543962e-05 loss: 0.0325 (0.0392) time: 3.4275 data: 0.0085 max mem: 33370 +Epoch: [30] [ 170/1319] eta: 1:06:16 lr: 1.419108366378774e-05 loss: 0.0306 (0.0390) time: 3.4045 data: 0.0085 max mem: 33370 +Epoch: [30] [ 180/1319] eta: 1:05:40 lr: 1.4181273028601838e-05 loss: 0.0328 (0.0387) time: 3.4304 data: 0.0082 max mem: 33370 +Epoch: [30] [ 190/1319] eta: 1:05:02 lr: 1.4171461639244721e-05 loss: 0.0335 (0.0387) time: 3.4199 data: 0.0080 max mem: 33370 +Epoch: [30] [ 200/1319] eta: 1:04:28 lr: 1.4161649495078178e-05 loss: 0.0352 (0.0387) time: 3.4371 data: 0.0081 max mem: 33370 +Epoch: [30] [ 210/1319] eta: 1:03:52 lr: 1.415183659546295e-05 loss: 0.0356 (0.0387) time: 3.4524 data: 0.0082 max mem: 33370 +Epoch: [30] [ 220/1319] eta: 1:03:15 lr: 1.4142022939758767e-05 loss: 0.0349 (0.0385) time: 3.4218 data: 0.0084 max mem: 33370 +Epoch: [30] [ 230/1319] eta: 1:02:39 lr: 1.413220852732429e-05 loss: 0.0361 (0.0385) time: 3.4128 data: 0.0084 max mem: 33370 +Epoch: [30] [ 240/1319] eta: 1:02:02 lr: 1.4122393357517167e-05 loss: 0.0340 (0.0383) time: 3.4097 data: 0.0080 max mem: 33370 +Epoch: [30] [ 250/1319] eta: 1:01:29 lr: 1.4112577429693993e-05 loss: 0.0304 (0.0381) time: 3.4415 data: 0.0081 max mem: 33370 +Epoch: [30] [ 260/1319] eta: 1:00:54 lr: 1.4102760743210322e-05 loss: 0.0293 (0.0382) time: 3.4532 data: 0.0087 max mem: 33370 +Epoch: [30] [ 270/1319] eta: 1:00:18 lr: 1.4092943297420657e-05 loss: 0.0302 (0.0381) time: 3.4239 data: 0.0088 max mem: 33370 +Epoch: [30] [ 280/1319] eta: 0:59:43 lr: 1.4083125091678468e-05 loss: 0.0347 (0.0380) time: 3.4347 data: 0.0084 max mem: 33370 +Epoch: [30] [ 290/1319] eta: 0:59:07 lr: 1.4073306125336142e-05 loss: 0.0379 (0.0380) time: 3.4284 data: 0.0081 max mem: 33370 +Epoch: [30] [ 300/1319] eta: 0:58:32 lr: 1.4063486397745037e-05 loss: 0.0327 (0.0377) time: 3.4144 data: 0.0082 max mem: 33370 +Epoch: [30] [ 310/1319] eta: 0:57:57 lr: 1.4053665908255448e-05 loss: 0.0320 (0.0377) time: 3.4222 data: 0.0081 max mem: 33370 +Epoch: [30] [ 320/1319] eta: 0:57:21 lr: 1.4043844656216607e-05 loss: 0.0383 (0.0379) time: 3.4090 data: 0.0081 max mem: 33370 +Epoch: [30] [ 330/1319] eta: 0:56:46 lr: 1.4034022640976696e-05 loss: 0.0363 (0.0378) time: 3.4157 data: 0.0088 max mem: 33370 +Epoch: [30] [ 340/1319] eta: 0:56:12 lr: 1.4024199861882808e-05 loss: 0.0354 (0.0377) time: 3.4388 data: 0.0086 max mem: 33370 +Epoch: [30] [ 350/1319] eta: 0:55:38 lr: 1.4014376318280992e-05 loss: 0.0322 (0.0377) time: 3.4534 data: 0.0083 max mem: 33370 +Epoch: [30] [ 360/1319] eta: 0:55:02 lr: 1.4004552009516214e-05 loss: 0.0259 (0.0375) time: 3.4359 data: 0.0087 max mem: 33370 +Epoch: [30] [ 370/1319] eta: 0:54:27 lr: 1.3994726934932381e-05 loss: 0.0295 (0.0375) time: 3.4124 data: 0.0088 max mem: 33370 +Epoch: [30] [ 380/1319] eta: 0:53:52 lr: 1.3984901093872316e-05 loss: 0.0366 (0.0375) time: 3.4232 data: 0.0083 max mem: 33370 +Epoch: [30] [ 390/1319] eta: 0:53:17 lr: 1.3975074485677755e-05 loss: 0.0373 (0.0375) time: 3.4261 data: 0.0083 max mem: 33370 +Epoch: [30] [ 400/1319] eta: 0:52:43 lr: 1.3965247109689372e-05 loss: 0.0353 (0.0375) time: 3.4238 data: 0.0084 max mem: 33370 +Epoch: [30] [ 410/1319] eta: 0:52:09 lr: 1.3955418965246752e-05 loss: 0.0334 (0.0373) time: 3.4452 data: 0.0083 max mem: 33370 +Epoch: [30] [ 420/1319] eta: 0:51:34 lr: 1.394559005168839e-05 loss: 0.0331 (0.0373) time: 3.4398 data: 0.0085 max mem: 33370 +Epoch: [30] [ 430/1319] eta: 0:50:59 lr: 1.39357603683517e-05 loss: 0.0346 (0.0373) time: 3.4197 data: 0.0088 max mem: 33370 +Epoch: [30] [ 440/1319] eta: 0:50:24 lr: 1.3925929914573002e-05 loss: 0.0352 (0.0374) time: 3.4329 data: 0.0092 max mem: 33370 +Epoch: [30] [ 450/1319] eta: 0:49:50 lr: 1.3916098689687517e-05 loss: 0.0358 (0.0374) time: 3.4316 data: 0.0089 max mem: 33370 +Epoch: [30] [ 460/1319] eta: 0:49:15 lr: 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1.3136936515041629e-05 loss: 0.0311 (0.0370) time: 3.4322 data: 0.0080 max mem: 33370 +Epoch: [30] [1250/1319] eta: 0:03:56 lr: 1.3127041345777947e-05 loss: 0.0319 (0.0371) time: 3.4217 data: 0.0082 max mem: 33370 +Epoch: [30] [1260/1319] eta: 0:03:22 lr: 1.3117145347668891e-05 loss: 0.0319 (0.0371) time: 3.4285 data: 0.0084 max mem: 33370 +Epoch: [30] [1270/1319] eta: 0:02:48 lr: 1.3107248519950133e-05 loss: 0.0330 (0.0371) time: 3.4176 data: 0.0082 max mem: 33370 +Epoch: [30] [1280/1319] eta: 0:02:13 lr: 1.3097350861856001e-05 loss: 0.0409 (0.0371) time: 3.4232 data: 0.0083 max mem: 33370 +Epoch: [30] [1290/1319] eta: 0:01:39 lr: 1.3087452372619463e-05 loss: 0.0337 (0.0371) time: 3.4024 data: 0.0082 max mem: 33370 +Epoch: [30] [1300/1319] eta: 0:01:05 lr: 1.3077553051472149e-05 loss: 0.0332 (0.0371) time: 3.4082 data: 0.0081 max mem: 33370 +Epoch: [30] [1310/1319] eta: 0:00:30 lr: 1.3067652897644308e-05 loss: 0.0360 (0.0372) time: 3.4323 data: 0.0080 max mem: 33370 +Epoch: [30] Total time: 1:15:29 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 2:34:29 time: 3.6025 data: 3.5101 max mem: 33370 +Test: [ 100/2573] eta: 0:04:40 time: 0.0782 data: 0.0016 max mem: 33370 +Test: [ 200/2573] eta: 0:03:51 time: 0.0816 data: 0.0015 max mem: 33370 +Test: [ 300/2573] eta: 0:03:27 time: 0.0817 data: 0.0014 max mem: 33370 +Test: [ 400/2573] eta: 0:03:12 time: 0.0813 data: 0.0014 max mem: 33370 +Test: [ 500/2573] eta: 0:03:00 time: 0.0806 data: 0.0014 max mem: 33370 +Test: [ 600/2573] eta: 0:02:49 time: 0.0809 data: 0.0015 max mem: 33370 +Test: [ 700/2573] eta: 0:02:40 time: 0.0808 data: 0.0015 max mem: 33370 +Test: [ 800/2573] eta: 0:02:30 time: 0.0834 data: 0.0014 max mem: 33370 +Test: [ 900/2573] eta: 0:02:21 time: 0.0818 data: 0.0015 max mem: 33370 +Test: [1000/2573] eta: 0:02:12 time: 0.0802 data: 0.0015 max mem: 33370 +Test: [1100/2573] eta: 0:02:03 time: 0.0804 data: 0.0014 max mem: 33370 +Test: [1200/2573] eta: 0:01:55 time: 0.0813 data: 0.0014 max mem: 33370 +Test: [1300/2573] eta: 0:01:46 time: 0.0811 data: 0.0014 max mem: 33370 +Test: [1400/2573] eta: 0:01:37 time: 0.0797 data: 0.0014 max mem: 33370 +Test: [1500/2573] eta: 0:01:29 time: 0.0812 data: 0.0014 max mem: 33370 +Test: [1600/2573] eta: 0:01:20 time: 0.0838 data: 0.0015 max mem: 33370 +Test: [1700/2573] eta: 0:01:12 time: 0.0796 data: 0.0014 max mem: 33370 +Test: [1800/2573] eta: 0:01:04 time: 0.0823 data: 0.0015 max mem: 33370 +Test: [1900/2573] eta: 0:00:55 time: 0.0788 data: 0.0014 max mem: 33370 +Test: [2000/2573] eta: 0:00:47 time: 0.0800 data: 0.0015 max mem: 33370 +Test: [2100/2573] eta: 0:00:39 time: 0.0818 data: 0.0013 max mem: 33370 +Test: [2200/2573] eta: 0:00:30 time: 0.0826 data: 0.0015 max mem: 33370 +Test: [2300/2573] eta: 0:00:22 time: 0.0824 data: 0.0014 max mem: 33370 +Test: [2400/2573] eta: 0:00:14 time: 0.0778 data: 0.0014 max mem: 33370 +Test: [2500/2573] eta: 0:00:06 time: 0.0820 data: 0.0017 max mem: 33370 +Test: Total time: 0:03:31 +Final results: +Mean IoU is 64.42 + + precision@0.5 = 72.32 + precision@0.6 = 67.36 + precision@0.7 = 60.72 + precision@0.8 = 49.51 + precision@0.9 = 25.59 + overall IoU = 61.89 + +Average object IoU 64.4246318502274 +Overall IoU 61.88731384277344 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [31] [ 0/1319] eta: 2:56:34 lr: 1.3058742046620123e-05 loss: 0.0509 (0.0509) time: 8.0326 data: 2.9854 max mem: 33370 +Epoch: [31] [ 10/1319] eta: 1:24:19 lr: 1.3048840308573793e-05 loss: 0.0359 (0.0449) time: 3.8652 data: 0.2790 max mem: 33370 +Epoch: [31] [ 20/1319] eta: 1:19:19 lr: 1.3038937735606992e-05 loss: 0.0325 (0.0388) time: 3.4454 data: 0.0078 max mem: 33370 +Epoch: [31] [ 30/1319] eta: 1:16:58 lr: 1.3029034326944665e-05 loss: 0.0308 (0.0376) time: 3.4278 data: 0.0083 max mem: 33370 +Epoch: [31] [ 40/1319] eta: 1:15:28 lr: 1.3019130081810363e-05 loss: 0.0324 (0.0375) time: 3.4109 data: 0.0093 max mem: 33370 +Epoch: [31] [ 50/1319] eta: 1:14:18 lr: 1.3009224999426282e-05 loss: 0.0324 (0.0379) time: 3.4054 data: 0.0091 max mem: 33370 +Epoch: [31] [ 60/1319] eta: 1:13:35 lr: 1.2999319079013207e-05 loss: 0.0343 (0.0381) time: 3.4394 data: 0.0086 max mem: 33370 +Epoch: [31] [ 70/1319] eta: 1:12:38 lr: 1.298941231979056e-05 loss: 0.0362 (0.0379) time: 3.4289 data: 0.0086 max mem: 33370 +Epoch: [31] [ 80/1319] eta: 1:11:51 lr: 1.2979504720976363e-05 loss: 0.0345 (0.0377) time: 3.3960 data: 0.0086 max mem: 33370 +Epoch: [31] [ 90/1319] eta: 1:11:09 lr: 1.2969596281787253e-05 loss: 0.0345 (0.0376) time: 3.4201 data: 0.0086 max mem: 33370 +Epoch: [31] [ 100/1319] eta: 1:10:28 lr: 1.2959687001438464e-05 loss: 0.0330 (0.0376) time: 3.4224 data: 0.0086 max mem: 33370 +Epoch: [31] [ 110/1319] eta: 1:09:47 lr: 1.2949776879143838e-05 loss: 0.0346 (0.0382) time: 3.4172 data: 0.0080 max mem: 33370 +Epoch: [31] [ 120/1319] eta: 1:09:08 lr: 1.2939865914115796e-05 loss: 0.0369 (0.0383) time: 3.4148 data: 0.0081 max mem: 33370 +Epoch: [31] [ 130/1319] eta: 1:08:31 lr: 1.2929954105565368e-05 loss: 0.0338 (0.0386) time: 3.4239 data: 0.0083 max mem: 33370 +Epoch: [31] [ 140/1319] eta: 1:07:53 lr: 1.2920041452702167e-05 loss: 0.0351 (0.0384) time: 3.4251 data: 0.0085 max mem: 33370 +Epoch: [31] [ 150/1319] eta: 1:07:18 lr: 1.2910127954734388e-05 loss: 0.0336 (0.0381) time: 3.4328 data: 0.0087 max mem: 33370 +Epoch: [31] [ 160/1319] eta: 1:06:41 lr: 1.2900213610868823e-05 loss: 0.0336 (0.0380) time: 3.4381 data: 0.0085 max mem: 33370 +Epoch: [31] [ 170/1319] eta: 1:05:59 lr: 1.2890298420310808e-05 loss: 0.0324 (0.0376) time: 3.3823 data: 0.0085 max mem: 33370 +Epoch: [31] [ 180/1319] eta: 1:05:25 lr: 1.2880382382264284e-05 loss: 0.0308 (0.0377) time: 3.3957 data: 0.0087 max mem: 33370 +Epoch: [31] [ 190/1319] eta: 1:04:47 lr: 1.2870465495931752e-05 loss: 0.0279 (0.0372) time: 3.4206 data: 0.0084 max mem: 33370 +Epoch: [31] [ 200/1319] eta: 1:04:12 lr: 1.2860547760514275e-05 loss: 0.0273 (0.0370) time: 3.4092 data: 0.0080 max mem: 33370 +Epoch: [31] [ 210/1319] eta: 1:03:36 lr: 1.285062917521149e-05 loss: 0.0305 (0.0368) time: 3.4263 data: 0.0082 max mem: 33370 +Epoch: [31] [ 220/1319] eta: 1:03:02 lr: 1.2840709739221567e-05 loss: 0.0311 (0.0368) time: 3.4375 data: 0.0083 max mem: 33370 +Epoch: [31] [ 230/1319] eta: 1:02:28 lr: 1.2830789451741262e-05 loss: 0.0346 (0.0371) time: 3.4470 data: 0.0085 max mem: 33370 +Epoch: [31] [ 240/1319] eta: 1:01:53 lr: 1.2820868311965862e-05 loss: 0.0325 (0.0369) time: 3.4352 data: 0.0083 max mem: 33370 +Epoch: [31] [ 250/1319] eta: 1:01:18 lr: 1.2810946319089204e-05 loss: 0.0317 (0.0368) time: 3.4218 data: 0.0084 max mem: 33370 +Epoch: [31] [ 260/1319] eta: 1:00:43 lr: 1.2801023472303672e-05 loss: 0.0350 (0.0367) time: 3.4312 data: 0.0086 max mem: 33370 +Epoch: [31] [ 270/1319] eta: 1:00:09 lr: 1.2791099770800195e-05 loss: 0.0337 (0.0366) time: 3.4484 data: 0.0081 max mem: 33370 +Epoch: [31] [ 280/1319] eta: 0:59:32 lr: 1.2781175213768214e-05 loss: 0.0331 (0.0368) time: 3.4071 data: 0.0086 max mem: 33370 +Epoch: [31] [ 290/1319] eta: 0:58:58 lr: 1.277124980039573e-05 loss: 0.0347 (0.0368) time: 3.4096 data: 0.0090 max mem: 33370 +Epoch: [31] [ 300/1319] eta: 0:58:24 lr: 1.2761323529869248e-05 loss: 0.0352 (0.0371) time: 3.4556 data: 0.0088 max mem: 33370 +Epoch: [31] [ 310/1319] eta: 0:57:50 lr: 1.2751396401373813e-05 loss: 0.0383 (0.0372) time: 3.4445 data: 0.0089 max mem: 33370 +Epoch: [31] [ 320/1319] eta: 0:57:17 lr: 1.2741468414092989e-05 loss: 0.0372 (0.0373) time: 3.4569 data: 0.0088 max mem: 33370 +Epoch: [31] [ 330/1319] eta: 0:56:42 lr: 1.2731539567208833e-05 loss: 0.0352 (0.0373) time: 3.4472 data: 0.0082 max mem: 33370 +Epoch: [31] [ 340/1319] eta: 0:56:06 lr: 1.2721609859901942e-05 loss: 0.0329 (0.0374) time: 3.4070 data: 0.0080 max mem: 33370 +Epoch: [31] [ 350/1319] eta: 0:55:31 lr: 1.2711679291351405e-05 loss: 0.0331 (0.0375) time: 3.4020 data: 0.0081 max mem: 33370 +Epoch: [31] [ 360/1319] eta: 0:54:55 lr: 1.2701747860734819e-05 loss: 0.0406 (0.0375) time: 3.4060 data: 0.0086 max mem: 33370 +Epoch: [31] [ 370/1319] eta: 0:54:19 lr: 1.2691815567228285e-05 loss: 0.0371 (0.0375) time: 3.3882 data: 0.0089 max mem: 33370 +Epoch: [31] [ 380/1319] eta: 0:53:45 lr: 1.2681882410006382e-05 loss: 0.0346 (0.0379) time: 3.4019 data: 0.0085 max mem: 33370 +Epoch: [31] [ 390/1319] eta: 0:53:10 lr: 1.26719483882422e-05 loss: 0.0371 (0.0380) time: 3.4241 data: 0.0084 max mem: 33370 +Epoch: [31] [ 400/1319] eta: 0:52:36 lr: 1.2662013501107303e-05 loss: 0.0323 (0.0378) time: 3.4312 data: 0.0084 max mem: 33370 +Epoch: [31] [ 410/1319] eta: 0:52:02 lr: 1.265207774777175e-05 loss: 0.0295 (0.0379) time: 3.4536 data: 0.0083 max mem: 33370 +Epoch: [31] [ 420/1319] eta: 0:51:27 lr: 1.2642141127404073e-05 loss: 0.0365 (0.0378) time: 3.4230 data: 0.0084 max mem: 33370 +Epoch: [31] [ 430/1319] eta: 0:50:52 lr: 1.2632203639171281e-05 loss: 0.0328 (0.0377) time: 3.3959 data: 0.0084 max mem: 33370 +Epoch: [31] [ 440/1319] eta: 0:50:18 lr: 1.2622265282238837e-05 loss: 0.0355 (0.0378) time: 3.4356 data: 0.0082 max mem: 33370 +Epoch: [31] [ 450/1319] eta: 0:49:44 lr: 1.2612326055770701e-05 loss: 0.0364 (0.0377) time: 3.4560 data: 0.0082 max mem: 33370 +Epoch: [31] [ 460/1319] eta: 0:49:09 lr: 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3.4366 data: 0.0086 max mem: 33370 +Epoch: [31] [1090/1319] eta: 0:13:06 lr: 1.1974367449303851e-05 loss: 0.0346 (0.0377) time: 3.4340 data: 0.0089 max mem: 33370 +Epoch: [31] [1100/1319] eta: 0:12:31 lr: 1.1964369832669236e-05 loss: 0.0380 (0.0378) time: 3.4317 data: 0.0089 max mem: 33370 +Epoch: [31] [1110/1319] eta: 0:11:57 lr: 1.195437128770757e-05 loss: 0.0320 (0.0377) time: 3.4467 data: 0.0089 max mem: 33370 +Epoch: [31] [1120/1319] eta: 0:11:23 lr: 1.194437181346979e-05 loss: 0.0305 (0.0377) time: 3.4482 data: 0.0086 max mem: 33370 +Epoch: [31] [1130/1319] eta: 0:10:48 lr: 1.1934371409004944e-05 loss: 0.0342 (0.0377) time: 3.4526 data: 0.0084 max mem: 33370 +Epoch: [31] [1140/1319] eta: 0:10:14 lr: 1.192437007336025e-05 loss: 0.0346 (0.0377) time: 3.4445 data: 0.0085 max mem: 33370 +Epoch: [31] [1150/1319] eta: 0:09:40 lr: 1.1914367805581053e-05 loss: 0.0346 (0.0377) time: 3.4103 data: 0.0088 max mem: 33370 +Epoch: [31] [1160/1319] eta: 0:09:05 lr: 1.1904364604710826e-05 loss: 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1.1824305291067328e-05 loss: 0.0381 (0.0378) time: 3.4228 data: 0.0087 max mem: 33370 +Epoch: [31] [1250/1319] eta: 0:03:56 lr: 1.1814293649022872e-05 loss: 0.0307 (0.0378) time: 3.4142 data: 0.0080 max mem: 33370 +Epoch: [31] [1260/1319] eta: 0:03:22 lr: 1.180428106421806e-05 loss: 0.0309 (0.0377) time: 3.4397 data: 0.0081 max mem: 33370 +Epoch: [31] [1270/1319] eta: 0:02:48 lr: 1.1794267535675433e-05 loss: 0.0358 (0.0378) time: 3.4532 data: 0.0080 max mem: 33370 +Epoch: [31] [1280/1319] eta: 0:02:13 lr: 1.1784253062415594e-05 loss: 0.0374 (0.0378) time: 3.4539 data: 0.0079 max mem: 33370 +Epoch: [31] [1290/1319] eta: 0:01:39 lr: 1.1774237643457209e-05 loss: 0.0346 (0.0378) time: 3.4241 data: 0.0079 max mem: 33370 +Epoch: [31] [1300/1319] eta: 0:01:05 lr: 1.1764221277816978e-05 loss: 0.0346 (0.0378) time: 3.4017 data: 0.0080 max mem: 33370 +Epoch: [31] [1310/1319] eta: 0:00:30 lr: 1.1754203964509668e-05 loss: 0.0346 (0.0378) time: 3.4253 data: 0.0078 max mem: 33370 +Epoch: [31] Total time: 1:15:27 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 2:22:25 time: 3.3211 data: 3.2352 max mem: 33370 +Test: [ 100/2573] eta: 0:04:33 time: 0.0791 data: 0.0015 max mem: 33370 +Test: [ 200/2573] eta: 0:03:46 time: 0.0798 data: 0.0014 max mem: 33370 +Test: [ 300/2573] eta: 0:03:24 time: 0.0822 data: 0.0015 max mem: 33370 +Test: [ 400/2573] eta: 0:03:10 time: 0.0810 data: 0.0014 max mem: 33370 +Test: [ 500/2573] eta: 0:02:58 time: 0.0804 data: 0.0015 max mem: 33370 +Test: [ 600/2573] eta: 0:02:48 time: 0.0806 data: 0.0014 max mem: 33370 +Test: [ 700/2573] eta: 0:02:38 time: 0.0813 data: 0.0015 max mem: 33370 +Test: [ 800/2573] eta: 0:02:29 time: 0.0842 data: 0.0014 max mem: 33370 +Test: [ 900/2573] eta: 0:02:20 time: 0.0814 data: 0.0014 max mem: 33370 +Test: [1000/2573] eta: 0:02:12 time: 0.0822 data: 0.0015 max mem: 33370 +Test: [1100/2573] eta: 0:02:03 time: 0.0824 data: 0.0015 max mem: 33370 +Test: [1200/2573] eta: 0:01:54 time: 0.0808 data: 0.0013 max mem: 33370 +Test: [1300/2573] eta: 0:01:46 time: 0.0806 data: 0.0013 max mem: 33370 +Test: [1400/2573] eta: 0:01:37 time: 0.0799 data: 0.0014 max mem: 33370 +Test: [1500/2573] eta: 0:01:29 time: 0.0821 data: 0.0015 max mem: 33370 +Test: [1600/2573] eta: 0:01:20 time: 0.0846 data: 0.0014 max mem: 33370 +Test: [1700/2573] eta: 0:01:12 time: 0.0805 data: 0.0014 max mem: 33370 +Test: [1800/2573] eta: 0:01:04 time: 0.0821 data: 0.0015 max mem: 33370 +Test: [1900/2573] eta: 0:00:55 time: 0.0797 data: 0.0015 max mem: 33370 +Test: [2000/2573] eta: 0:00:47 time: 0.0815 data: 0.0014 max mem: 33370 +Test: [2100/2573] eta: 0:00:39 time: 0.0828 data: 0.0014 max mem: 33370 +Test: [2200/2573] eta: 0:00:30 time: 0.0818 data: 0.0014 max mem: 33370 +Test: [2300/2573] eta: 0:00:22 time: 0.0818 data: 0.0015 max mem: 33370 +Test: [2400/2573] eta: 0:00:14 time: 0.0771 data: 0.0015 max mem: 33370 +Test: [2500/2573] eta: 0:00:05 time: 0.0814 data: 0.0014 max mem: 33370 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: Total time: 0:03:31 +Final results: +Mean IoU is 64.31 + + precision@0.5 = 72.04 + precision@0.6 = 67.36 + precision@0.7 = 60.93 + precision@0.8 = 49.86 + precision@0.9 = 26.12 + overall IoU = 61.72 + +Average object IoU 64.31371906517724 +Overall IoU 61.71873092651367 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [32] [ 0/1319] eta: 2:49:58 lr: 1.1745187571461855e-05 loss: 0.0253 (0.0253) time: 7.7317 data: 1.9996 max mem: 33370 +Epoch: [32] [ 10/1319] eta: 1:23:50 lr: 1.1735168454865734e-05 loss: 0.0310 (0.0315) time: 3.8431 data: 0.1892 max mem: 33370 +Epoch: [32] [ 20/1319] eta: 1:18:50 lr: 1.1725148387734231e-05 loss: 0.0310 (0.0351) time: 3.4373 data: 0.0082 max mem: 33370 +Epoch: [32] [ 30/1319] eta: 1:16:44 lr: 1.1715127369074435e-05 loss: 0.0304 (0.0338) time: 3.4231 data: 0.0083 max mem: 33370 +Epoch: [32] [ 40/1319] eta: 1:15:25 lr: 1.1705105397891451e-05 loss: 0.0290 (0.0327) time: 3.4301 data: 0.0088 max mem: 33370 +Epoch: [32] [ 50/1319] eta: 1:14:12 lr: 1.1695082473188386e-05 loss: 0.0318 (0.0342) time: 3.4103 data: 0.0089 max mem: 33370 +Epoch: [32] [ 60/1319] eta: 1:13:12 lr: 1.1685058593966367e-05 loss: 0.0311 (0.0337) time: 3.3881 data: 0.0091 max mem: 33370 +Epoch: [32] [ 70/1319] eta: 1:12:24 lr: 1.1675033759224512e-05 loss: 0.0268 (0.0339) time: 3.4001 data: 0.0088 max mem: 33370 +Epoch: [32] [ 80/1319] eta: 1:11:39 lr: 1.1665007967959945e-05 loss: 0.0282 (0.0338) time: 3.4106 data: 0.0083 max mem: 33370 +Epoch: [32] [ 90/1319] eta: 1:11:03 lr: 1.1654981219167763e-05 loss: 0.0382 (0.0353) time: 3.4381 data: 0.0089 max mem: 33370 +Epoch: [32] [ 100/1319] eta: 1:10:23 lr: 1.1644953511841062e-05 loss: 0.0382 (0.0350) time: 3.4428 data: 0.0088 max mem: 33370 +Epoch: [32] [ 110/1319] eta: 1:09:40 lr: 1.1634924844970898e-05 loss: 0.0319 (0.0348) time: 3.4055 data: 0.0088 max mem: 33370 +Epoch: [32] [ 120/1319] eta: 1:09:04 lr: 1.1624895217546308e-05 loss: 0.0319 (0.0346) time: 3.4193 data: 0.0089 max mem: 33370 +Epoch: [32] [ 130/1319] eta: 1:08:26 lr: 1.1614864628554293e-05 loss: 0.0330 (0.0348) time: 3.4301 data: 0.0085 max mem: 33370 +Epoch: [32] [ 140/1319] eta: 1:07:49 lr: 1.160483307697981e-05 loss: 0.0320 (0.0350) time: 3.4202 data: 0.0084 max mem: 33370 +Epoch: [32] [ 150/1319] eta: 1:07:13 lr: 1.159480056180578e-05 loss: 0.0304 (0.0350) time: 3.4272 data: 0.0086 max mem: 33370 +Epoch: [32] [ 160/1319] eta: 1:06:37 lr: 1.1584767082013038e-05 loss: 0.0307 (0.0349) time: 3.4268 data: 0.0086 max mem: 33370 +Epoch: [32] [ 170/1319] eta: 1:06:01 lr: 1.1574732636580395e-05 loss: 0.0302 (0.0348) time: 3.4275 data: 0.0081 max mem: 33370 +Epoch: [32] [ 180/1319] eta: 1:05:23 lr: 1.1564697224484583e-05 loss: 0.0297 (0.0346) time: 3.4163 data: 0.0078 max mem: 33370 +Epoch: [32] [ 190/1319] eta: 1:04:48 lr: 1.1554660844700256e-05 loss: 0.0285 (0.0349) time: 3.4190 data: 0.0080 max mem: 33370 +Epoch: [32] [ 200/1319] eta: 1:04:12 lr: 1.1544623496200004e-05 loss: 0.0326 (0.0350) time: 3.4188 data: 0.0082 max mem: 33370 +Epoch: [32] [ 210/1319] eta: 1:03:37 lr: 1.153458517795431e-05 loss: 0.0371 (0.0353) time: 3.4219 data: 0.0085 max mem: 33370 +Epoch: [32] [ 220/1319] eta: 1:03:04 lr: 1.1524545888931584e-05 loss: 0.0359 (0.0352) time: 3.4597 data: 0.0087 max mem: 33370 +Epoch: [32] [ 230/1319] eta: 1:02:29 lr: 1.1514505628098139e-05 loss: 0.0334 (0.0355) time: 3.4537 data: 0.0084 max mem: 33370 +Epoch: [32] [ 240/1319] eta: 1:01:54 lr: 1.1504464394418176e-05 loss: 0.0320 (0.0356) time: 3.4298 data: 0.0084 max mem: 33370 +Epoch: [32] [ 250/1319] eta: 1:01:20 lr: 1.149442218685379e-05 loss: 0.0306 (0.0352) time: 3.4341 data: 0.0084 max mem: 33370 +Epoch: [32] [ 260/1319] eta: 1:00:45 lr: 1.1484379004364971e-05 loss: 0.0268 (0.0350) time: 3.4402 data: 0.0083 max mem: 33370 +Epoch: [32] [ 270/1319] eta: 1:00:10 lr: 1.147433484590956e-05 loss: 0.0273 (0.0350) time: 3.4362 data: 0.0084 max mem: 33370 +Epoch: [32] [ 280/1319] eta: 0:59:37 lr: 1.1464289710443295e-05 loss: 0.0274 (0.0349) time: 3.4543 data: 0.0082 max mem: 33370 +Epoch: [32] [ 290/1319] eta: 0:59:02 lr: 1.1454243596919765e-05 loss: 0.0306 (0.0350) time: 3.4499 data: 0.0080 max mem: 33370 +Epoch: [32] [ 300/1319] eta: 0:58:28 lr: 1.144419650429042e-05 loss: 0.0330 (0.0349) time: 3.4346 data: 0.0085 max mem: 33370 +Epoch: [32] [ 310/1319] eta: 0:57:53 lr: 1.1434148431504575e-05 loss: 0.0301 (0.0348) time: 3.4429 data: 0.0085 max mem: 33370 +Epoch: [32] [ 320/1319] eta: 0:57:18 lr: 1.1424099377509363e-05 loss: 0.0300 (0.0348) time: 3.4301 data: 0.0083 max mem: 33370 +Epoch: [32] [ 330/1319] eta: 0:56:43 lr: 1.141404934124978e-05 loss: 0.0316 (0.0347) time: 3.4133 data: 0.0085 max mem: 33370 +Epoch: [32] [ 340/1319] eta: 0:56:07 lr: 1.140399832166864e-05 loss: 0.0286 (0.0346) time: 3.4040 data: 0.0082 max mem: 33370 +Epoch: [32] [ 350/1319] eta: 0:55:33 lr: 1.1393946317706594e-05 loss: 0.0295 (0.0346) time: 3.4272 data: 0.0087 max mem: 33370 +Epoch: [32] [ 360/1319] eta: 0:54:58 lr: 1.138389332830211e-05 loss: 0.0343 (0.0346) time: 3.4286 data: 0.0091 max mem: 33370 +Epoch: [32] [ 370/1319] eta: 0:54:24 lr: 1.1373839352391454e-05 loss: 0.0325 (0.0346) time: 3.4281 data: 0.0092 max mem: 33370 +Epoch: [32] [ 380/1319] eta: 0:53:50 lr: 1.1363784388908714e-05 loss: 0.0327 (0.0347) time: 3.4568 data: 0.0091 max mem: 33370 +Epoch: [32] [ 390/1319] eta: 0:53:16 lr: 1.1353728436785773e-05 loss: 0.0331 (0.0348) time: 3.4673 data: 0.0082 max mem: 33370 +Epoch: [32] [ 400/1319] eta: 0:52:43 lr: 1.1343671494952302e-05 loss: 0.0361 (0.0350) time: 3.4793 data: 0.0082 max mem: 33370 +Epoch: [32] [ 410/1319] eta: 0:52:07 lr: 1.1333613562335765e-05 loss: 0.0345 (0.0351) time: 3.4362 data: 0.0084 max mem: 33370 +Epoch: [32] [ 420/1319] eta: 0:51:32 lr: 1.1323554637861402e-05 loss: 0.0341 (0.0352) time: 3.3966 data: 0.0082 max mem: 33370 +Epoch: [32] [ 430/1319] eta: 0:50:57 lr: 1.1313494720452216e-05 loss: 0.0339 (0.0351) time: 3.4100 data: 0.0082 max mem: 33370 +Epoch: [32] [ 440/1319] eta: 0:50:22 lr: 1.1303433809028986e-05 loss: 0.0319 (0.0351) time: 3.4086 data: 0.0082 max mem: 33370 +Epoch: [32] [ 450/1319] eta: 0:49:46 lr: 1.1293371902510248e-05 loss: 0.0334 (0.0352) time: 3.3916 data: 0.0083 max mem: 33370 +Epoch: [32] [ 460/1319] eta: 0:49:11 lr: 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1.049524038345592e-05 loss: 0.0326 (0.0355) time: 3.4455 data: 0.0087 max mem: 33370 +Epoch: [32] [1250/1319] eta: 0:03:56 lr: 1.048509515332035e-05 loss: 0.0310 (0.0355) time: 3.4120 data: 0.0084 max mem: 33370 +Epoch: [32] [1260/1319] eta: 0:03:22 lr: 1.0474948832358245e-05 loss: 0.0332 (0.0355) time: 3.4229 data: 0.0086 max mem: 33370 +Epoch: [32] [1270/1319] eta: 0:02:48 lr: 1.0464801419278068e-05 loss: 0.0362 (0.0355) time: 3.4290 data: 0.0084 max mem: 33370 +Epoch: [32] [1280/1319] eta: 0:02:13 lr: 1.0454652912785337e-05 loss: 0.0385 (0.0356) time: 3.4394 data: 0.0079 max mem: 33370 +Epoch: [32] [1290/1319] eta: 0:01:39 lr: 1.0444503311582662e-05 loss: 0.0348 (0.0356) time: 3.4704 data: 0.0079 max mem: 33370 +Epoch: [32] [1300/1319] eta: 0:01:05 lr: 1.0434352614369702e-05 loss: 0.0319 (0.0356) time: 3.4453 data: 0.0079 max mem: 33370 +Epoch: [32] [1310/1319] eta: 0:00:30 lr: 1.0424200819843158e-05 loss: 0.0298 (0.0356) time: 3.4156 data: 0.0079 max mem: 33370 +Epoch: [32] Total time: 1:15:27 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 2:29:25 time: 3.4846 data: 3.3424 max mem: 33370 +Test: [ 100/2573] eta: 0:04:37 time: 0.0783 data: 0.0017 max mem: 33370 +Test: [ 200/2573] eta: 0:03:48 time: 0.0792 data: 0.0014 max mem: 33370 +Test: [ 300/2573] eta: 0:03:25 time: 0.0812 data: 0.0014 max mem: 33370 +Test: [ 400/2573] eta: 0:03:10 time: 0.0815 data: 0.0016 max mem: 33370 +Test: [ 500/2573] eta: 0:02:58 time: 0.0795 data: 0.0014 max mem: 33370 +Test: [ 600/2573] eta: 0:02:47 time: 0.0797 data: 0.0014 max mem: 33370 +Test: [ 700/2573] eta: 0:02:38 time: 0.0800 data: 0.0014 max mem: 33370 +Test: [ 800/2573] eta: 0:02:29 time: 0.0831 data: 0.0014 max mem: 33370 +Test: [ 900/2573] eta: 0:02:20 time: 0.0804 data: 0.0014 max mem: 33370 +Test: [1000/2573] eta: 0:02:11 time: 0.0806 data: 0.0014 max mem: 33370 +Test: [1100/2573] eta: 0:02:02 time: 0.0815 data: 0.0014 max mem: 33370 +Test: [1200/2573] eta: 0:01:54 time: 0.0806 data: 0.0013 max mem: 33370 +Test: [1300/2573] eta: 0:01:45 time: 0.0808 data: 0.0014 max mem: 33370 +Test: [1400/2573] eta: 0:01:37 time: 0.0790 data: 0.0014 max mem: 33370 +Test: [1500/2573] eta: 0:01:28 time: 0.0808 data: 0.0014 max mem: 33370 +Test: [1600/2573] eta: 0:01:20 time: 0.0841 data: 0.0014 max mem: 33370 +Test: [1700/2573] eta: 0:01:12 time: 0.0793 data: 0.0013 max mem: 33370 +Test: [1800/2573] eta: 0:01:03 time: 0.0819 data: 0.0014 max mem: 33370 +Test: [1900/2573] eta: 0:00:55 time: 0.0788 data: 0.0014 max mem: 33370 +Test: [2000/2573] eta: 0:00:47 time: 0.0808 data: 0.0015 max mem: 33370 +Test: [2100/2573] eta: 0:00:38 time: 0.0818 data: 0.0014 max mem: 33370 +Test: [2200/2573] eta: 0:00:30 time: 0.0843 data: 0.0015 max mem: 33370 +Test: [2300/2573] eta: 0:00:22 time: 0.0830 data: 0.0014 max mem: 33370 +Test: [2400/2573] eta: 0:00:14 time: 0.0794 data: 0.0016 max mem: 33370 +Test: [2500/2573] eta: 0:00:05 time: 0.0811 data: 0.0016 max mem: 33370 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: Total time: 0:03:31 +Final results: +Mean IoU is 64.68 + + precision@0.5 = 72.43 + precision@0.6 = 67.71 + precision@0.7 = 61.05 + precision@0.8 = 50.20 + precision@0.9 = 25.67 + overall IoU = 61.72 + +Average object IoU 64.68223751075244 +Overall IoU 61.72307205200195 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [33] [ 0/1319] eta: 3:12:51 lr: 1.04150632654866e-05 loss: 0.0293 (0.0293) time: 8.7730 data: 1.7354 max mem: 33370 +Epoch: [33] [ 10/1319] eta: 1:25:01 lr: 1.0404909382463066e-05 loss: 0.0293 (0.0290) time: 3.8976 data: 0.1662 max mem: 33370 +Epoch: [33] [ 20/1319] eta: 1:19:30 lr: 1.0394754398329612e-05 loss: 0.0311 (0.0344) time: 3.4170 data: 0.0089 max mem: 33370 +Epoch: [33] [ 30/1319] eta: 1:17:09 lr: 1.0384598311771345e-05 loss: 0.0311 (0.0332) time: 3.4231 data: 0.0085 max mem: 33370 +Epoch: [33] [ 40/1319] eta: 1:15:47 lr: 1.0374441121470351e-05 loss: 0.0320 (0.0342) time: 3.4326 data: 0.0085 max mem: 33370 +Epoch: [33] [ 50/1319] eta: 1:14:49 lr: 1.0364282826105723e-05 loss: 0.0348 (0.0348) time: 3.4542 data: 0.0087 max mem: 33370 +Epoch: [33] [ 60/1319] eta: 1:13:48 lr: 1.0354123424353528e-05 loss: 0.0330 (0.0351) time: 3.4390 data: 0.0088 max mem: 33370 +Epoch: [33] [ 70/1319] eta: 1:12:55 lr: 1.0343962914886797e-05 loss: 0.0330 (0.0349) time: 3.4147 data: 0.0087 max mem: 33370 +Epoch: [33] [ 80/1319] eta: 1:12:05 lr: 1.033380129637553e-05 loss: 0.0316 (0.0347) time: 3.4122 data: 0.0087 max mem: 33370 +Epoch: [33] [ 90/1319] eta: 1:11:15 lr: 1.0323638567486653e-05 loss: 0.0297 (0.0341) time: 3.3912 data: 0.0084 max mem: 33370 +Epoch: [33] [ 100/1319] eta: 1:10:35 lr: 1.0313474726884054e-05 loss: 0.0320 (0.0348) time: 3.4083 data: 0.0084 max mem: 33370 +Epoch: [33] [ 110/1319] eta: 1:09:53 lr: 1.0303309773228537e-05 loss: 0.0313 (0.0344) time: 3.4239 data: 0.0085 max mem: 33370 +Epoch: [33] [ 120/1319] eta: 1:09:13 lr: 1.0293143705177821e-05 loss: 0.0305 (0.0340) time: 3.4093 data: 0.0082 max mem: 33370 +Epoch: [33] [ 130/1319] eta: 1:08:30 lr: 1.0282976521386539e-05 loss: 0.0307 (0.0341) time: 3.3960 data: 0.0083 max mem: 33370 +Epoch: [33] [ 140/1319] eta: 1:07:52 lr: 1.0272808220506222e-05 loss: 0.0335 (0.0340) time: 3.3957 data: 0.0093 max mem: 33370 +Epoch: [33] [ 150/1319] eta: 1:07:14 lr: 1.026263880118526e-05 loss: 0.0291 (0.0339) time: 3.4097 data: 0.0094 max mem: 33370 +Epoch: [33] [ 160/1319] eta: 1:06:39 lr: 1.0252468262068951e-05 loss: 0.0286 (0.0336) time: 3.4286 data: 0.0088 max mem: 33370 +Epoch: [33] [ 170/1319] eta: 1:06:07 lr: 1.024229660179944e-05 loss: 0.0308 (0.0338) time: 3.4645 data: 0.0087 max mem: 33370 +Epoch: [33] [ 180/1319] eta: 1:05:30 lr: 1.023212381901573e-05 loss: 0.0334 (0.0337) time: 3.4486 data: 0.0088 max mem: 33370 +Epoch: [33] [ 190/1319] eta: 1:04:55 lr: 1.0221949912353669e-05 loss: 0.0334 (0.0339) time: 3.4323 data: 0.0091 max mem: 33370 +Epoch: [33] [ 200/1319] eta: 1:04:20 lr: 1.0211774880445919e-05 loss: 0.0331 (0.0342) time: 3.4458 data: 0.0090 max mem: 33370 +Epoch: [33] [ 210/1319] eta: 1:03:44 lr: 1.0201598721921983e-05 loss: 0.0317 (0.0341) time: 3.4248 data: 0.0089 max mem: 33370 +Epoch: [33] [ 220/1319] eta: 1:03:09 lr: 1.0191421435408169e-05 loss: 0.0371 (0.0345) time: 3.4214 data: 0.0087 max mem: 33370 +Epoch: [33] [ 230/1319] eta: 1:02:32 lr: 1.0181243019527578e-05 loss: 0.0371 (0.0343) time: 3.4250 data: 0.0086 max mem: 33370 +Epoch: [33] [ 240/1319] eta: 1:01:57 lr: 1.0171063472900106e-05 loss: 0.0275 (0.0344) time: 3.4177 data: 0.0089 max mem: 33370 +Epoch: [33] [ 250/1319] eta: 1:01:22 lr: 1.0160882794142423e-05 loss: 0.0295 (0.0344) time: 3.4285 data: 0.0091 max mem: 33370 +Epoch: [33] [ 260/1319] eta: 1:00:46 lr: 1.0150700981867957e-05 loss: 0.0286 (0.0348) time: 3.4174 data: 0.0085 max mem: 33370 +Epoch: [33] [ 270/1319] eta: 1:00:11 lr: 1.01405180346869e-05 loss: 0.0285 (0.0346) time: 3.4128 data: 0.0081 max mem: 33370 +Epoch: [33] [ 280/1319] eta: 0:59:36 lr: 1.0130333951206182e-05 loss: 0.0323 (0.0345) time: 3.4287 data: 0.0088 max mem: 33370 +Epoch: [33] [ 290/1319] eta: 0:59:00 lr: 1.0120148730029472e-05 loss: 0.0310 (0.0345) time: 3.4240 data: 0.0088 max mem: 33370 +Epoch: [33] [ 300/1319] eta: 0:58:25 lr: 1.0109962369757157e-05 loss: 0.0303 (0.0344) time: 3.4085 data: 0.0081 max mem: 33370 +Epoch: [33] [ 310/1319] eta: 0:57:50 lr: 1.0099774868986322e-05 loss: 0.0297 (0.0342) time: 3.4229 data: 0.0079 max mem: 33370 +Epoch: [33] [ 320/1319] eta: 0:57:16 lr: 1.008958622631076e-05 loss: 0.0295 (0.0344) time: 3.4364 data: 0.0080 max mem: 33370 +Epoch: [33] [ 330/1319] eta: 0:56:40 lr: 1.0079396440320953e-05 loss: 0.0342 (0.0345) time: 3.4108 data: 0.0081 max mem: 33370 +Epoch: [33] [ 340/1319] eta: 0:56:06 lr: 1.0069205509604051e-05 loss: 0.0305 (0.0343) time: 3.4210 data: 0.0085 max mem: 33370 +Epoch: [33] [ 350/1319] eta: 0:55:31 lr: 1.0059013432743876e-05 loss: 0.0288 (0.0345) time: 3.4289 data: 0.0084 max mem: 33370 +Epoch: [33] [ 360/1319] eta: 0:54:56 lr: 1.0048820208320883e-05 loss: 0.0323 (0.0345) time: 3.4142 data: 0.0088 max mem: 33370 +Epoch: [33] [ 370/1319] eta: 0:54:21 lr: 1.0038625834912186e-05 loss: 0.0312 (0.0345) time: 3.4306 data: 0.0089 max mem: 33370 +Epoch: [33] [ 380/1319] eta: 0:53:47 lr: 1.0028430311091521e-05 loss: 0.0335 (0.0347) time: 3.4374 data: 0.0082 max mem: 33370 +Epoch: [33] [ 390/1319] eta: 0:53:12 lr: 1.0018233635429235e-05 loss: 0.0336 (0.0347) time: 3.4138 data: 0.0085 max mem: 33370 +Epoch: [33] [ 400/1319] eta: 0:52:37 lr: 1.0008035806492287e-05 loss: 0.0305 (0.0346) time: 3.4081 data: 0.0085 max mem: 33370 +Epoch: [33] [ 410/1319] eta: 0:52:03 lr: 9.99783682284423e-06 loss: 0.0305 (0.0349) time: 3.4292 data: 0.0086 max mem: 33370 +Epoch: [33] [ 420/1319] eta: 0:51:27 lr: 9.987636683045179e-06 loss: 0.0327 (0.0348) time: 3.4032 data: 0.0088 max mem: 33370 +Epoch: [33] [ 430/1319] eta: 0:50:52 lr: 9.977435385651839e-06 loss: 0.0279 (0.0347) time: 3.3855 data: 0.0083 max mem: 33370 +Epoch: [33] [ 440/1319] eta: 0:50:17 lr: 9.967232929217462e-06 loss: 0.0279 (0.0347) time: 3.3953 data: 0.0086 max mem: 33370 +Epoch: [33] [ 450/1319] eta: 0:49:42 lr: 9.957029312291845e-06 loss: 0.0351 (0.0348) time: 3.4015 data: 0.0088 max mem: 33370 +Epoch: [33] [ 460/1319] eta: 0:49:08 lr: 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loss: 0.0291 (0.0348) time: 3.4040 data: 0.0083 max mem: 33370 +Epoch: [33] [ 940/1319] eta: 0:21:41 lr: 9.455599308753445e-06 loss: 0.0300 (0.0347) time: 3.4194 data: 0.0081 max mem: 33370 +Epoch: [33] [ 950/1319] eta: 0:21:07 lr: 9.445335738140192e-06 loss: 0.0322 (0.0348) time: 3.4250 data: 0.0084 max mem: 33370 +Epoch: [33] [ 960/1319] eta: 0:20:32 lr: 9.435070928189476e-06 loss: 0.0334 (0.0348) time: 3.4149 data: 0.0086 max mem: 33370 +Epoch: [33] [ 970/1319] eta: 0:19:58 lr: 9.424804877253139e-06 loss: 0.0317 (0.0347) time: 3.4374 data: 0.0084 max mem: 33370 +Epoch: [33] [ 980/1319] eta: 0:19:24 lr: 9.414537583678836e-06 loss: 0.0313 (0.0347) time: 3.4231 data: 0.0084 max mem: 33370 +Epoch: [33] [ 990/1319] eta: 0:18:49 lr: 9.404269045810016e-06 loss: 0.0312 (0.0347) time: 3.4150 data: 0.0087 max mem: 33370 +Epoch: [33] [1000/1319] eta: 0:18:15 lr: 9.393999261985916e-06 loss: 0.0361 (0.0347) time: 3.4355 data: 0.0091 max mem: 33370 +Epoch: [33] [1010/1319] eta: 0:17:41 lr: 9.383728230541512e-06 loss: 0.0315 (0.0347) time: 3.4146 data: 0.0088 max mem: 33370 +Epoch: [33] [1020/1319] eta: 0:17:06 lr: 9.373455949807552e-06 loss: 0.0293 (0.0346) time: 3.4354 data: 0.0085 max mem: 33370 +Epoch: [33] [1030/1319] eta: 0:16:32 lr: 9.363182418110507e-06 loss: 0.0297 (0.0346) time: 3.4504 data: 0.0085 max mem: 33370 +Epoch: [33] [1040/1319] eta: 0:15:58 lr: 9.352907633772557e-06 loss: 0.0294 (0.0346) time: 3.4110 data: 0.0085 max mem: 33370 +Epoch: [33] [1050/1319] eta: 0:15:23 lr: 9.342631595111597e-06 loss: 0.0323 (0.0346) time: 3.4016 data: 0.0083 max mem: 33370 +Epoch: [33] [1060/1319] eta: 0:14:49 lr: 9.332354300441178e-06 loss: 0.0323 (0.0346) time: 3.3936 data: 0.0084 max mem: 33370 +Epoch: [33] [1070/1319] eta: 0:14:14 lr: 9.322075748070539e-06 loss: 0.0288 (0.0345) time: 3.3773 data: 0.0088 max mem: 33370 +Epoch: [33] [1080/1319] eta: 0:13:40 lr: 9.311795936304561e-06 loss: 0.0308 (0.0345) time: 3.3936 data: 0.0086 max mem: 33370 +Epoch: [33] [1090/1319] eta: 0:13:05 lr: 9.301514863443759e-06 loss: 0.0330 (0.0345) time: 3.3817 data: 0.0081 max mem: 33370 +Epoch: [33] [1100/1319] eta: 0:12:31 lr: 9.291232527784269e-06 loss: 0.0332 (0.0345) time: 3.4107 data: 0.0081 max mem: 33370 +Epoch: [33] [1110/1319] eta: 0:11:57 lr: 9.280948927617811e-06 loss: 0.0332 (0.0345) time: 3.4290 data: 0.0083 max mem: 33370 +Epoch: [33] [1120/1319] eta: 0:11:22 lr: 9.270664061231702e-06 loss: 0.0328 (0.0346) time: 3.4304 data: 0.0082 max mem: 33370 +Epoch: [33] [1130/1319] eta: 0:10:48 lr: 9.260377926908826e-06 loss: 0.0332 (0.0346) time: 3.4538 data: 0.0081 max mem: 33370 +Epoch: [33] [1140/1319] eta: 0:10:14 lr: 9.250090522927605e-06 loss: 0.0302 (0.0346) time: 3.4238 data: 0.0081 max mem: 33370 +Epoch: [33] [1150/1319] eta: 0:09:39 lr: 9.239801847562006e-06 loss: 0.0310 (0.0346) time: 3.4169 data: 0.0082 max mem: 33370 +Epoch: [33] [1160/1319] eta: 0:09:05 lr: 9.229511899081506e-06 loss: 0.0295 (0.0346) time: 3.4274 data: 0.0084 max mem: 33370 +Epoch: [33] [1170/1319] eta: 0:08:31 lr: 9.219220675751069e-06 loss: 0.0295 (0.0346) time: 3.4415 data: 0.0081 max mem: 33370 +Epoch: [33] [1180/1319] eta: 0:07:57 lr: 9.20892817583115e-06 loss: 0.0311 (0.0346) time: 3.4560 data: 0.0087 max mem: 33370 +Epoch: [33] [1190/1319] eta: 0:07:22 lr: 9.19863439757767e-06 loss: 0.0304 (0.0346) time: 3.4618 data: 0.0089 max mem: 33370 +Epoch: [33] [1200/1319] eta: 0:06:48 lr: 9.188339339241987e-06 loss: 0.0300 (0.0346) time: 3.4605 data: 0.0083 max mem: 33370 +Epoch: [33] [1210/1319] eta: 0:06:14 lr: 9.178042999070898e-06 loss: 0.0292 (0.0346) time: 3.4654 data: 0.0082 max mem: 33370 +Epoch: [33] [1220/1319] eta: 0:05:39 lr: 9.16774537530659e-06 loss: 0.0367 (0.0347) time: 3.4364 data: 0.0086 max mem: 33370 +Epoch: [33] [1230/1319] eta: 0:05:05 lr: 9.157446466186662e-06 loss: 0.0375 (0.0347) time: 3.4017 data: 0.0087 max mem: 33370 +Epoch: [33] [1240/1319] eta: 0:04:31 lr: 9.147146269944078e-06 loss: 0.0315 (0.0347) time: 3.4195 data: 0.0085 max mem: 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+/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 2:14:17 time: 3.1314 data: 3.0350 max mem: 33370 +Test: [ 100/2573] eta: 0:04:27 time: 0.0775 data: 0.0014 max mem: 33370 +Test: [ 200/2573] eta: 0:03:44 time: 0.0799 data: 0.0014 max mem: 33370 +Test: [ 300/2573] eta: 0:03:22 time: 0.0814 data: 0.0014 max mem: 33370 +Test: [ 400/2573] eta: 0:03:08 time: 0.0813 data: 0.0014 max mem: 33370 +Test: [ 500/2573] eta: 0:02:57 time: 0.0808 data: 0.0014 max mem: 33370 +Test: [ 600/2573] eta: 0:02:47 time: 0.0802 data: 0.0015 max mem: 33370 +Test: [ 700/2573] eta: 0:02:38 time: 0.0806 data: 0.0014 max mem: 33370 +Test: [ 800/2573] eta: 0:02:29 time: 0.0836 data: 0.0014 max mem: 33370 +Test: [ 900/2573] eta: 0:02:20 time: 0.0811 data: 0.0015 max mem: 33370 +Test: [1000/2573] eta: 0:02:11 time: 0.0803 data: 0.0014 max mem: 33370 +Test: [1100/2573] eta: 0:02:02 time: 0.0806 data: 0.0015 max mem: 33370 +Test: [1200/2573] eta: 0:01:54 time: 0.0811 data: 0.0015 max mem: 33370 +Test: [1300/2573] eta: 0:01:45 time: 0.0804 data: 0.0013 max mem: 33370 +Test: [1400/2573] eta: 0:01:37 time: 0.0801 data: 0.0014 max mem: 33370 +Test: [1500/2573] eta: 0:01:28 time: 0.0819 data: 0.0015 max mem: 33370 +Test: [1600/2573] eta: 0:01:20 time: 0.0845 data: 0.0016 max mem: 33370 +Test: [1700/2573] eta: 0:01:12 time: 0.0790 data: 0.0014 max mem: 33370 +Test: [1800/2573] eta: 0:01:03 time: 0.0821 data: 0.0015 max mem: 33370 +Test: [1900/2573] eta: 0:00:55 time: 0.0785 data: 0.0014 max mem: 33370 +Test: [2000/2573] eta: 0:00:47 time: 0.0801 data: 0.0014 max mem: 33370 +Test: [2100/2573] eta: 0:00:38 time: 0.0819 data: 0.0014 max mem: 33370 +Test: [2200/2573] eta: 0:00:30 time: 0.0829 data: 0.0015 max mem: 33370 +Test: [2300/2573] eta: 0:00:22 time: 0.0820 data: 0.0015 max mem: 33370 +Test: [2400/2573] eta: 0:00:14 time: 0.0774 data: 0.0015 max mem: 33370 +Test: [2500/2573] eta: 0:00:05 time: 0.0808 data: 0.0015 max mem: 33370 +Test: Total time: 0:03:31 +Final results: +Mean IoU is 64.36 + + precision@0.5 = 72.16 + precision@0.6 = 67.40 + precision@0.7 = 61.21 + precision@0.8 = 50.27 + precision@0.9 = 25.37 + overall IoU = 61.73 + +Average object IoU 64.35705950669805 +Overall IoU 61.73014831542969 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [34] [ 0/1319] eta: 3:23:39 lr: 9.065729264358701e-06 loss: 0.0234 (0.0234) time: 9.2643 data: 1.8936 max mem: 33370 +Epoch: [34] [ 10/1319] eta: 1:26:24 lr: 9.05541753412883e-06 loss: 0.0361 (0.0327) time: 3.9604 data: 0.1795 max mem: 33370 +Epoch: [34] [ 20/1319] eta: 1:19:55 lr: 9.045104499029229e-06 loss: 0.0366 (0.0405) time: 3.4133 data: 0.0084 max mem: 33370 +Epoch: [34] [ 30/1319] eta: 1:17:32 lr: 9.03479015724125e-06 loss: 0.0302 (0.0375) time: 3.4160 data: 0.0086 max mem: 33370 +Epoch: [34] [ 40/1319] eta: 1:15:48 lr: 9.024474506941415e-06 loss: 0.0282 (0.0360) time: 3.4147 data: 0.0086 max mem: 33370 +Epoch: [34] [ 50/1319] eta: 1:14:34 lr: 9.014157546301385e-06 loss: 0.0316 (0.0354) time: 3.3969 data: 0.0086 max mem: 33370 +Epoch: [34] [ 60/1319] eta: 1:13:38 lr: 9.003839273487931e-06 loss: 0.0325 (0.0361) time: 3.4120 data: 0.0083 max mem: 33370 +Epoch: [34] [ 70/1319] eta: 1:12:49 lr: 8.99351968666293e-06 loss: 0.0313 (0.0350) time: 3.4274 data: 0.0081 max mem: 33370 +Epoch: [34] [ 80/1319] eta: 1:12:02 lr: 8.983198783983315e-06 loss: 0.0323 (0.0347) time: 3.4264 data: 0.0080 max mem: 33370 +Epoch: [34] [ 90/1319] eta: 1:11:20 lr: 8.972876563601101e-06 loss: 0.0302 (0.0340) time: 3.4306 data: 0.0085 max mem: 33370 +Epoch: [34] [ 100/1319] eta: 1:10:36 lr: 8.962553023663333e-06 loss: 0.0295 (0.0344) time: 3.4216 data: 0.0087 max mem: 33370 +Epoch: [34] [ 110/1319] eta: 1:09:57 lr: 8.952228162312077e-06 loss: 0.0305 (0.0343) time: 3.4185 data: 0.0082 max mem: 33370 +Epoch: [34] [ 120/1319] eta: 1:09:19 lr: 8.941901977684397e-06 loss: 0.0354 (0.0347) time: 3.4360 data: 0.0086 max mem: 33370 +Epoch: [34] [ 130/1319] eta: 1:08:40 lr: 8.93157446791234e-06 loss: 0.0368 (0.0348) time: 3.4315 data: 0.0083 max mem: 33370 +Epoch: [34] [ 140/1319] eta: 1:08:03 lr: 8.9212456311229e-06 loss: 0.0329 (0.0345) time: 3.4278 data: 0.0077 max mem: 33370 +Epoch: [34] [ 150/1319] eta: 1:07:26 lr: 8.910915465438025e-06 loss: 0.0335 (0.0349) time: 3.4380 data: 0.0081 max mem: 33370 +Epoch: [34] [ 160/1319] eta: 1:06:52 lr: 8.900583968974578e-06 loss: 0.0330 (0.0345) time: 3.4522 data: 0.0084 max mem: 33370 +Epoch: [34] [ 170/1319] eta: 1:06:15 lr: 8.89025113984432e-06 loss: 0.0302 (0.0345) time: 3.4432 data: 0.0082 max mem: 33370 +Epoch: [34] [ 180/1319] eta: 1:05:40 lr: 8.879916976153894e-06 loss: 0.0302 (0.0342) time: 3.4417 data: 0.0084 max mem: 33370 +Epoch: [34] [ 190/1319] eta: 1:05:04 lr: 8.869581476004788e-06 loss: 0.0326 (0.0344) time: 3.4504 data: 0.0084 max mem: 33370 +Epoch: [34] [ 200/1319] eta: 1:04:29 lr: 8.859244637493344e-06 loss: 0.0321 (0.0343) time: 3.4415 data: 0.0081 max mem: 33370 +Epoch: [34] [ 210/1319] eta: 1:03:52 lr: 8.84890645871071e-06 loss: 0.0308 (0.0342) time: 3.4273 data: 0.0082 max mem: 33370 +Epoch: [34] [ 220/1319] eta: 1:03:16 lr: 8.838566937742836e-06 loss: 0.0333 (0.0341) time: 3.4221 data: 0.0081 max mem: 33370 +Epoch: [34] [ 230/1319] eta: 1:02:41 lr: 8.828226072670449e-06 loss: 0.0332 (0.0348) time: 3.4333 data: 0.0080 max mem: 33370 +Epoch: [34] [ 240/1319] eta: 1:02:04 lr: 8.817883861569014e-06 loss: 0.0335 (0.0350) time: 3.4274 data: 0.0084 max mem: 33370 +Epoch: [34] [ 250/1319] eta: 1:01:30 lr: 8.807540302508743e-06 loss: 0.0331 (0.0350) time: 3.4317 data: 0.0086 max mem: 33370 +Epoch: [34] [ 260/1319] eta: 1:00:55 lr: 8.797195393554557e-06 loss: 0.0318 (0.0350) time: 3.4515 data: 0.0085 max mem: 33370 +Epoch: [34] [ 270/1319] eta: 1:00:21 lr: 8.786849132766063e-06 loss: 0.0295 (0.0359) time: 3.4531 data: 0.0089 max mem: 33370 +Epoch: [34] [ 280/1319] eta: 0:59:46 lr: 8.776501518197541e-06 loss: 0.0295 (0.0358) time: 3.4420 data: 0.0087 max mem: 33370 +Epoch: [34] [ 290/1319] eta: 0:59:11 lr: 8.76615254789792e-06 loss: 0.0322 (0.0357) time: 3.4429 data: 0.0082 max mem: 33370 +Epoch: [34] [ 300/1319] eta: 0:58:35 lr: 8.755802219910735e-06 loss: 0.0322 (0.0358) time: 3.4352 data: 0.0084 max mem: 33370 +Epoch: [34] [ 310/1319] eta: 0:58:01 lr: 8.745450532274145e-06 loss: 0.0310 (0.0357) time: 3.4281 data: 0.0085 max mem: 33370 +Epoch: [34] [ 320/1319] eta: 0:57:25 lr: 8.735097483020883e-06 loss: 0.0309 (0.0356) time: 3.4232 data: 0.0087 max mem: 33370 +Epoch: [34] [ 330/1319] eta: 0:56:50 lr: 8.724743070178239e-06 loss: 0.0312 (0.0357) time: 3.4233 data: 0.0088 max mem: 33370 +Epoch: [34] [ 340/1319] eta: 0:56:15 lr: 8.714387291768046e-06 loss: 0.0301 (0.0355) time: 3.4295 data: 0.0085 max mem: 33370 +Epoch: [34] [ 350/1319] eta: 0:55:39 lr: 8.704030145806636e-06 loss: 0.0266 (0.0354) time: 3.4042 data: 0.0086 max mem: 33370 +Epoch: [34] [ 360/1319] eta: 0:55:04 lr: 8.693671630304845e-06 loss: 0.0319 (0.0353) time: 3.4108 data: 0.0093 max mem: 33370 +Epoch: [34] [ 370/1319] eta: 0:54:29 lr: 8.683311743267978e-06 loss: 0.0319 (0.0354) time: 3.4315 data: 0.0091 max mem: 33370 +Epoch: [34] [ 380/1319] eta: 0:53:53 lr: 8.672950482695785e-06 loss: 0.0311 (0.0353) time: 3.4102 data: 0.0087 max mem: 33370 +Epoch: [34] [ 390/1319] eta: 0:53:18 lr: 8.662587846582436e-06 loss: 0.0314 (0.0352) time: 3.4058 data: 0.0083 max mem: 33370 +Epoch: [34] [ 400/1319] eta: 0:52:43 lr: 8.65222383291651e-06 loss: 0.0332 (0.0352) time: 3.4255 data: 0.0082 max mem: 33370 +Epoch: [34] [ 410/1319] eta: 0:52:09 lr: 8.641858439680947e-06 loss: 0.0313 (0.0352) time: 3.4377 data: 0.0089 max mem: 33370 +Epoch: [34] [ 420/1319] eta: 0:51:34 lr: 8.631491664853054e-06 loss: 0.0316 (0.0352) time: 3.4317 data: 0.0090 max mem: 33370 +Epoch: [34] [ 430/1319] eta: 0:50:59 lr: 8.621123506404469e-06 loss: 0.0340 (0.0351) time: 3.4183 data: 0.0085 max mem: 33370 +Epoch: [34] [ 440/1319] eta: 0:50:25 lr: 8.610753962301133e-06 loss: 0.0294 (0.0350) time: 3.4362 data: 0.0085 max mem: 33370 +Epoch: [34] [ 450/1319] eta: 0:49:50 lr: 8.600383030503278e-06 loss: 0.0338 (0.0365) time: 3.4457 data: 0.0086 max mem: 33370 +Epoch: [34] [ 460/1319] eta: 0:49:15 lr: 8.590010708965377e-06 loss: 0.0423 (0.0365) time: 3.4152 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0:35:26 lr: 8.340652648571916e-06 loss: 0.0295 (0.0358) time: 3.4264 data: 0.0084 max mem: 33370 +Epoch: [34] [ 710/1319] eta: 0:34:51 lr: 8.330244901449094e-06 loss: 0.0302 (0.0359) time: 3.4135 data: 0.0083 max mem: 33370 +Epoch: [34] [ 720/1319] eta: 0:34:17 lr: 8.319835709307101e-06 loss: 0.0328 (0.0359) time: 3.3908 data: 0.0082 max mem: 33370 +Epoch: [34] [ 730/1319] eta: 0:33:42 lr: 8.309425069935955e-06 loss: 0.0326 (0.0358) time: 3.4243 data: 0.0081 max mem: 33370 +Epoch: [34] [ 740/1319] eta: 0:33:08 lr: 8.299012981119228e-06 loss: 0.0284 (0.0357) time: 3.4572 data: 0.0083 max mem: 33370 +Epoch: [34] [ 750/1319] eta: 0:32:34 lr: 8.288599440633996e-06 loss: 0.0282 (0.0357) time: 3.4600 data: 0.0082 max mem: 33370 +Epoch: [34] [ 760/1319] eta: 0:32:00 lr: 8.278184446250822e-06 loss: 0.0277 (0.0356) time: 3.4420 data: 0.0083 max mem: 33370 +Epoch: [34] [ 770/1319] eta: 0:31:26 lr: 8.267767995733725e-06 loss: 0.0328 (0.0357) time: 3.4482 data: 0.0089 max mem: 33370 +Epoch: [34] [ 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3.4167 data: 0.0084 max mem: 33370 +Epoch: [34] [1020/1319] eta: 0:17:06 lr: 8.006876811544029e-06 loss: 0.0286 (0.0354) time: 3.4539 data: 0.0089 max mem: 33370 +Epoch: [34] [1030/1319] eta: 0:16:32 lr: 7.996421694575264e-06 loss: 0.0260 (0.0354) time: 3.4637 data: 0.0088 max mem: 33370 +Epoch: [34] [1040/1319] eta: 0:15:58 lr: 7.985965058518847e-06 loss: 0.0297 (0.0354) time: 3.4365 data: 0.0080 max mem: 33370 +Epoch: [34] [1050/1319] eta: 0:15:23 lr: 7.97550690094334e-06 loss: 0.0310 (0.0353) time: 3.4032 data: 0.0080 max mem: 33370 +Epoch: [34] [1060/1319] eta: 0:14:49 lr: 7.965047219409881e-06 loss: 0.0309 (0.0353) time: 3.3940 data: 0.0084 max mem: 33370 +Epoch: [34] [1070/1319] eta: 0:14:15 lr: 7.95458601147213e-06 loss: 0.0315 (0.0353) time: 3.4347 data: 0.0085 max mem: 33370 +Epoch: [34] [1080/1319] eta: 0:13:40 lr: 7.944123274676236e-06 loss: 0.0314 (0.0353) time: 3.4625 data: 0.0086 max mem: 33370 +Epoch: [34] [1090/1319] eta: 0:13:06 lr: 7.933659006560817e-06 loss: 0.0329 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7.849889436251218e-06 loss: 0.0287 (0.0352) time: 3.4275 data: 0.0081 max mem: 33370 +Epoch: [34] [1180/1319] eta: 0:07:57 lr: 7.839411274235871e-06 loss: 0.0286 (0.0352) time: 3.4420 data: 0.0085 max mem: 33370 +Epoch: [34] [1190/1319] eta: 0:07:23 lr: 7.82893155586463e-06 loss: 0.0356 (0.0353) time: 3.4396 data: 0.0085 max mem: 33370 +Epoch: [34] [1200/1319] eta: 0:06:48 lr: 7.818450278590844e-06 loss: 0.0356 (0.0352) time: 3.4113 data: 0.0082 max mem: 33370 +Epoch: [34] [1210/1319] eta: 0:06:14 lr: 7.80796743985987e-06 loss: 0.0302 (0.0353) time: 3.4418 data: 0.0082 max mem: 33370 +Epoch: [34] [1220/1319] eta: 0:05:39 lr: 7.797483037109084e-06 loss: 0.0299 (0.0352) time: 3.4375 data: 0.0085 max mem: 33370 +Epoch: [34] [1230/1319] eta: 0:05:05 lr: 7.786997067767811e-06 loss: 0.0273 (0.0353) time: 3.4183 data: 0.0085 max mem: 33370 +Epoch: [34] [1240/1319] eta: 0:04:31 lr: 7.776509529257303e-06 loss: 0.0324 (0.0353) time: 3.4357 data: 0.0081 max mem: 33370 +Epoch: [34] [1250/1319] eta: 0:03:56 lr: 7.766020418990693e-06 loss: 0.0324 (0.0352) time: 3.3998 data: 0.0081 max mem: 33370 +Epoch: [34] [1260/1319] eta: 0:03:22 lr: 7.755529734372952e-06 loss: 0.0295 (0.0352) time: 3.4152 data: 0.0083 max mem: 33370 +Epoch: [34] [1270/1319] eta: 0:02:48 lr: 7.74503747280087e-06 loss: 0.0293 (0.0352) time: 3.4316 data: 0.0082 max mem: 33370 +Epoch: [34] [1280/1319] eta: 0:02:13 lr: 7.734543631663006e-06 loss: 0.0285 (0.0352) time: 3.4308 data: 0.0082 max mem: 33370 +Epoch: [34] [1290/1319] eta: 0:01:39 lr: 7.724048208339646e-06 loss: 0.0320 (0.0352) time: 3.4395 data: 0.0084 max mem: 33370 +Epoch: [34] [1300/1319] eta: 0:01:05 lr: 7.713551200202774e-06 loss: 0.0322 (0.0352) time: 3.4265 data: 0.0086 max mem: 33370 +Epoch: [34] [1310/1319] eta: 0:00:30 lr: 7.703052604616029e-06 loss: 0.0322 (0.0352) time: 3.4398 data: 0.0082 max mem: 33370 +Epoch: [34] Total time: 1:15:29 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 2:11:43 time: 3.0717 data: 2.9513 max mem: 33370 +Test: [ 100/2573] eta: 0:04:27 time: 0.0788 data: 0.0016 max mem: 33370 +Test: [ 200/2573] eta: 0:03:44 time: 0.0798 data: 0.0015 max mem: 33370 +Test: [ 300/2573] eta: 0:03:23 time: 0.0824 data: 0.0015 max mem: 33370 +Test: [ 400/2573] eta: 0:03:10 time: 0.0832 data: 0.0014 max mem: 33370 +Test: [ 500/2573] eta: 0:02:58 time: 0.0803 data: 0.0015 max mem: 33370 +Test: [ 600/2573] eta: 0:02:48 time: 0.0811 data: 0.0015 max mem: 33370 +Test: [ 700/2573] eta: 0:02:39 time: 0.0816 data: 0.0015 max mem: 33370 +Test: [ 800/2573] eta: 0:02:30 time: 0.0848 data: 0.0015 max mem: 33370 +Test: [ 900/2573] eta: 0:02:21 time: 0.0810 data: 0.0016 max mem: 33370 +Test: [1000/2573] eta: 0:02:12 time: 0.0813 data: 0.0015 max mem: 33370 +Test: [1100/2573] eta: 0:02:03 time: 0.0818 data: 0.0014 max mem: 33370 +Test: [1200/2573] eta: 0:01:55 time: 0.0808 data: 0.0015 max mem: 33370 +Test: [1300/2573] eta: 0:01:46 time: 0.0818 data: 0.0015 max mem: 33370 +Test: [1400/2573] eta: 0:01:37 time: 0.0804 data: 0.0015 max mem: 33370 +Test: [1500/2573] eta: 0:01:29 time: 0.0811 data: 0.0014 max mem: 33370 +Test: [1600/2573] eta: 0:01:20 time: 0.0848 data: 0.0015 max mem: 33370 +Test: [1700/2573] eta: 0:01:12 time: 0.0797 data: 0.0015 max mem: 33370 +Test: [1800/2573] eta: 0:01:04 time: 0.0837 data: 0.0016 max mem: 33370 +Test: [1900/2573] eta: 0:00:55 time: 0.0792 data: 0.0015 max mem: 33370 +Test: [2000/2573] eta: 0:00:47 time: 0.0805 data: 0.0015 max mem: 33370 +Test: [2100/2573] eta: 0:00:39 time: 0.0829 data: 0.0015 max mem: 33370 +Test: [2200/2573] eta: 0:00:30 time: 0.0827 data: 0.0016 max mem: 33370 +Test: [2300/2573] eta: 0:00:22 time: 0.0824 data: 0.0015 max mem: 33370 +Test: [2400/2573] eta: 0:00:14 time: 0.0772 data: 0.0014 max mem: 33370 +Test: [2500/2573] eta: 0:00:06 time: 0.0792 data: 0.0014 max mem: 33370 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: Total time: 0:03:32 +Final results: +Mean IoU is 65.01 + + precision@0.5 = 72.81 + precision@0.6 = 67.83 + precision@0.7 = 61.15 + precision@0.8 = 50.25 + precision@0.9 = 25.71 + overall IoU = 62.05 + +Average object IoU 65.0061709883624 +Overall IoU 62.046409606933594 +Better epoch: 34 + +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [35] [ 0/1319] eta: 1:57:41 lr: 7.693602509132593e-06 loss: 0.0434 (0.0434) time: 5.3537 data: 1.6110 max mem: 33370 +Epoch: [35] [ 10/1319] eta: 1:19:29 lr: 7.683100890097833e-06 loss: 0.0331 (0.0383) time: 3.6435 data: 0.1552 max mem: 33370 +Epoch: [35] [ 20/1319] eta: 1:17:24 lr: 7.67259767592017e-06 loss: 0.0331 (0.0361) time: 3.4862 data: 0.0093 max mem: 33370 +Epoch: [35] [ 30/1319] eta: 1:15:38 lr: 7.66209286393032e-06 loss: 0.0331 (0.0347) time: 3.4541 data: 0.0091 max mem: 33370 +Epoch: [35] [ 40/1319] eta: 1:14:38 lr: 7.651586451450453e-06 loss: 0.0321 (0.0351) time: 3.4241 data: 0.0088 max mem: 33370 +Epoch: [35] [ 50/1319] eta: 1:13:41 lr: 7.641078435794154e-06 loss: 0.0307 (0.0346) time: 3.4273 data: 0.0084 max mem: 33370 +Epoch: [35] [ 60/1319] eta: 1:12:58 lr: 7.630568814266394e-06 loss: 0.0311 (0.0356) time: 3.4287 data: 0.0088 max mem: 33370 +Epoch: [35] [ 70/1319] eta: 1:12:07 lr: 7.62005758416347e-06 loss: 0.0362 (0.0355) time: 3.4148 data: 0.0091 max mem: 33370 +Epoch: [35] [ 80/1319] eta: 1:11:24 lr: 7.609544742772985e-06 loss: 0.0321 (0.0350) time: 3.3982 data: 0.0085 max mem: 33370 +Epoch: [35] [ 90/1319] eta: 1:10:41 lr: 7.599030287373793e-06 loss: 0.0343 (0.0355) time: 3.4028 data: 0.0084 max mem: 33370 +Epoch: [35] [ 100/1319] eta: 1:10:03 lr: 7.588514215235963e-06 loss: 0.0310 (0.0347) time: 3.4106 data: 0.0085 max mem: 33370 +Epoch: [35] [ 110/1319] eta: 1:09:25 lr: 7.5779965236207366e-06 loss: 0.0264 (0.0345) time: 3.4184 data: 0.0088 max mem: 33370 +Epoch: [35] [ 120/1319] eta: 1:08:48 lr: 7.5674772097804864e-06 loss: 0.0304 (0.0348) time: 3.4186 data: 0.0092 max mem: 33370 +Epoch: [35] [ 130/1319] eta: 1:08:11 lr: 7.556956270958658e-06 loss: 0.0300 (0.0342) time: 3.4190 data: 0.0089 max mem: 33370 +Epoch: [35] [ 140/1319] eta: 1:07:34 lr: 7.546433704389756e-06 loss: 0.0270 (0.0340) time: 3.4085 data: 0.0084 max mem: 33370 +Epoch: [35] [ 150/1319] eta: 1:06:56 lr: 7.535909507299282e-06 loss: 0.0270 (0.0335) time: 3.4035 data: 0.0081 max mem: 33370 +Epoch: [35] [ 160/1319] eta: 1:06:19 lr: 7.525383676903694e-06 loss: 0.0286 (0.0333) time: 3.3984 data: 0.0083 max mem: 33370 +Epoch: [35] [ 170/1319] eta: 1:05:42 lr: 7.514856210410369e-06 loss: 0.0325 (0.0334) time: 3.3900 data: 0.0085 max mem: 33370 +Epoch: [35] [ 180/1319] eta: 1:05:06 lr: 7.504327105017539e-06 loss: 0.0362 (0.0337) time: 3.4000 data: 0.0083 max mem: 33370 +Epoch: [35] [ 190/1319] eta: 1:04:31 lr: 7.493796357914276e-06 loss: 0.0304 (0.0333) time: 3.4149 data: 0.0085 max mem: 33370 +Epoch: [35] [ 200/1319] eta: 1:03:56 lr: 7.483263966280434e-06 loss: 0.0270 (0.0332) time: 3.4177 data: 0.0085 max mem: 33370 +Epoch: [35] [ 210/1319] eta: 1:03:20 lr: 7.4727299272865964e-06 loss: 0.0310 (0.0334) time: 3.4017 data: 0.0084 max mem: 33370 +Epoch: [35] [ 220/1319] eta: 1:02:45 lr: 7.462194238094052e-06 loss: 0.0338 (0.0332) time: 3.3992 data: 0.0088 max mem: 33370 +Epoch: [35] [ 230/1319] eta: 1:02:10 lr: 7.4516568958547115e-06 loss: 0.0309 (0.0332) time: 3.4176 data: 0.0085 max mem: 33370 +Epoch: [35] [ 240/1319] eta: 1:01:35 lr: 7.4411178977111085e-06 loss: 0.0306 (0.0330) time: 3.4142 data: 0.0082 max mem: 33370 +Epoch: [35] [ 250/1319] eta: 1:01:01 lr: 7.430577240796325e-06 loss: 0.0261 (0.0328) time: 3.4132 data: 0.0082 max mem: 33370 +Epoch: [35] [ 260/1319] eta: 1:00:29 lr: 7.420034922233955e-06 loss: 0.0280 (0.0327) time: 3.4523 data: 0.0082 max mem: 33370 +Epoch: [35] [ 270/1319] eta: 0:59:54 lr: 7.4094909391380505e-06 loss: 0.0298 (0.0328) time: 3.4522 data: 0.0083 max mem: 33370 +Epoch: [35] [ 280/1319] eta: 0:59:19 lr: 7.398945288613088e-06 loss: 0.0342 (0.0329) time: 3.4083 data: 0.0081 max mem: 33370 +Epoch: [35] [ 290/1319] eta: 0:58:44 lr: 7.388397967753893e-06 loss: 0.0339 (0.0333) time: 3.3978 data: 0.0081 max mem: 33370 +Epoch: [35] [ 300/1319] eta: 0:58:10 lr: 7.3778489736456335e-06 loss: 0.0327 (0.0333) time: 3.4259 data: 0.0085 max mem: 33370 +Epoch: [35] [ 310/1319] eta: 0:57:37 lr: 7.367298303363743e-06 loss: 0.0338 (0.0334) time: 3.4490 data: 0.0087 max mem: 33370 +Epoch: [35] [ 320/1319] eta: 0:57:03 lr: 7.35674595397388e-06 loss: 0.0325 (0.0333) time: 3.4368 data: 0.0088 max mem: 33370 +Epoch: [35] [ 330/1319] eta: 0:56:28 lr: 7.34619192253189e-06 loss: 0.0265 (0.0332) time: 3.4242 data: 0.0084 max mem: 33370 +Epoch: [35] [ 340/1319] eta: 0:55:55 lr: 7.335636206083729e-06 loss: 0.0331 (0.0333) time: 3.4349 data: 0.0079 max mem: 33370 +Epoch: [35] [ 350/1319] eta: 0:55:21 lr: 7.325078801665445e-06 loss: 0.0331 (0.0333) time: 3.4539 data: 0.0079 max mem: 33370 +Epoch: [35] [ 360/1319] eta: 0:54:47 lr: 7.31451970630312e-06 loss: 0.0298 (0.0333) time: 3.4395 data: 0.0087 max mem: 33370 +Epoch: [35] [ 370/1319] eta: 0:54:13 lr: 7.303958917012809e-06 loss: 0.0327 (0.0334) time: 3.4359 data: 0.0093 max mem: 33370 +Epoch: [35] [ 380/1319] eta: 0:53:39 lr: 7.293396430800509e-06 loss: 0.0296 (0.0335) time: 3.4518 data: 0.0089 max mem: 33370 +Epoch: [35] [ 390/1319] eta: 0:53:06 lr: 7.282832244662077e-06 loss: 0.0315 (0.0335) time: 3.4663 data: 0.0085 max mem: 33370 +Epoch: [35] [ 400/1319] eta: 0:52:31 lr: 7.272266355583221e-06 loss: 0.0319 (0.0335) time: 3.4292 data: 0.0080 max mem: 33370 +Epoch: [35] [ 410/1319] eta: 0:51:57 lr: 7.261698760539424e-06 loss: 0.0302 (0.0335) time: 3.4075 data: 0.0079 max mem: 33370 +Epoch: [35] [ 420/1319] eta: 0:51:23 lr: 7.2511294564958895e-06 loss: 0.0315 (0.0336) time: 3.4463 data: 0.0080 max mem: 33370 +Epoch: [35] [ 430/1319] eta: 0:50:49 lr: 7.240558440407508e-06 loss: 0.0321 (0.0336) time: 3.4634 data: 0.0081 max mem: 33370 +Epoch: [35] [ 440/1319] eta: 0:50:16 lr: 7.229985709218795e-06 loss: 0.0290 (0.0335) time: 3.4673 data: 0.0083 max mem: 33370 +Epoch: [35] [ 450/1319] eta: 0:49:42 lr: 7.219411259863819e-06 loss: 0.0325 (0.0335) time: 3.4659 data: 0.0083 max mem: 33370 +Epoch: [35] [ 460/1319] eta: 0:49:08 lr: 7.208835089266191e-06 loss: 0.0326 (0.0335) time: 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eta: 0:35:23 lr: 6.954482434226801e-06 loss: 0.0338 (0.0337) time: 3.4475 data: 0.0085 max mem: 33370 +Epoch: [35] [ 710/1319] eta: 0:34:49 lr: 6.9438622009590656e-06 loss: 0.0311 (0.0337) time: 3.4431 data: 0.0086 max mem: 33370 +Epoch: [35] [ 720/1319] eta: 0:34:15 lr: 6.933240162602753e-06 loss: 0.0276 (0.0336) time: 3.4228 data: 0.0083 max mem: 33370 +Epoch: [35] [ 730/1319] eta: 0:33:40 lr: 6.922616315777261e-06 loss: 0.0273 (0.0335) time: 3.4187 data: 0.0080 max mem: 33370 +Epoch: [35] [ 740/1319] eta: 0:33:06 lr: 6.911990657089877e-06 loss: 0.0290 (0.0335) time: 3.4336 data: 0.0081 max mem: 33370 +Epoch: [35] [ 750/1319] eta: 0:32:32 lr: 6.901363183135715e-06 loss: 0.0317 (0.0336) time: 3.4513 data: 0.0084 max mem: 33370 +Epoch: [35] [ 760/1319] eta: 0:31:58 lr: 6.890733890497658e-06 loss: 0.0317 (0.0335) time: 3.4528 data: 0.0086 max mem: 33370 +Epoch: [35] [ 770/1319] eta: 0:31:23 lr: 6.880102775746271e-06 loss: 0.0309 (0.0335) time: 3.4320 data: 0.0086 max mem: 33370 +Epoch: 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(0.0336) time: 3.4024 data: 0.0085 max mem: 33370 +Epoch: [35] [1020/1319] eta: 0:17:05 lr: 6.613722429195618e-06 loss: 0.0303 (0.0336) time: 3.4226 data: 0.0083 max mem: 33370 +Epoch: [35] [1030/1319] eta: 0:16:31 lr: 6.603042693858916e-06 loss: 0.0317 (0.0336) time: 3.4154 data: 0.0083 max mem: 33370 +Epoch: [35] [1040/1319] eta: 0:15:56 lr: 6.5923610389138055e-06 loss: 0.0323 (0.0336) time: 3.4278 data: 0.0087 max mem: 33370 +Epoch: [35] [1050/1319] eta: 0:15:22 lr: 6.581677460558057e-06 loss: 0.0276 (0.0335) time: 3.4410 data: 0.0088 max mem: 33370 +Epoch: [35] [1060/1319] eta: 0:14:48 lr: 6.570991954975031e-06 loss: 0.0299 (0.0335) time: 3.4601 data: 0.0085 max mem: 33370 +Epoch: [35] [1070/1319] eta: 0:14:14 lr: 6.560304518333606e-06 loss: 0.0302 (0.0335) time: 3.4441 data: 0.0085 max mem: 33370 +Epoch: [35] [1080/1319] eta: 0:13:39 lr: 6.549615146788095e-06 loss: 0.0349 (0.0336) time: 3.4379 data: 0.0081 max mem: 33370 +Epoch: [35] [1090/1319] eta: 0:13:05 lr: 6.538923836478152e-06 loss: 0.0295 (0.0335) time: 3.4328 data: 0.0083 max mem: 33370 +Epoch: [35] [1100/1319] eta: 0:12:31 lr: 6.528230583528713e-06 loss: 0.0283 (0.0335) time: 3.4252 data: 0.0088 max mem: 33370 +Epoch: [35] [1110/1319] eta: 0:11:56 lr: 6.5175353840499016e-06 loss: 0.0300 (0.0335) time: 3.4418 data: 0.0087 max mem: 33370 +Epoch: [35] [1120/1319] eta: 0:11:22 lr: 6.506838234136938e-06 loss: 0.0322 (0.0335) time: 3.4386 data: 0.0085 max mem: 33370 +Epoch: [35] [1130/1319] eta: 0:10:48 lr: 6.4961391298700616e-06 loss: 0.0308 (0.0335) time: 3.4330 data: 0.0082 max mem: 33370 +Epoch: [35] [1140/1319] eta: 0:10:13 lr: 6.485438067314456e-06 loss: 0.0308 (0.0335) time: 3.4146 data: 0.0078 max mem: 33370 +Epoch: [35] [1150/1319] eta: 0:09:39 lr: 6.4747350425201315e-06 loss: 0.0307 (0.0335) time: 3.3720 data: 0.0078 max mem: 33370 +Epoch: [35] [1160/1319] eta: 0:09:05 lr: 6.464030051521878e-06 loss: 0.0309 (0.0335) time: 3.3924 data: 0.0080 max mem: 33370 +Epoch: [35] 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+/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 2:27:54 time: 3.4491 data: 3.3453 max mem: 33370 +Test: [ 100/2573] eta: 0:04:35 time: 0.0778 data: 0.0014 max mem: 33370 +Test: [ 200/2573] eta: 0:03:48 time: 0.0798 data: 0.0015 max mem: 33370 +Test: [ 300/2573] eta: 0:03:25 time: 0.0816 data: 0.0015 max mem: 33370 +Test: [ 400/2573] eta: 0:03:11 time: 0.0827 data: 0.0016 max mem: 33370 +Test: [ 500/2573] eta: 0:02:59 time: 0.0803 data: 0.0014 max mem: 33370 +Test: [ 600/2573] eta: 0:02:48 time: 0.0797 data: 0.0014 max mem: 33370 +Test: [ 700/2573] eta: 0:02:39 time: 0.0807 data: 0.0014 max mem: 33370 +Test: [ 800/2573] eta: 0:02:30 time: 0.0837 data: 0.0014 max mem: 33370 +Test: [ 900/2573] eta: 0:02:21 time: 0.0808 data: 0.0015 max mem: 33370 +Test: [1000/2573] eta: 0:02:12 time: 0.0817 data: 0.0017 max mem: 33370 +Test: [1100/2573] eta: 0:02:03 time: 0.0805 data: 0.0015 max mem: 33370 +Test: [1200/2573] eta: 0:01:54 time: 0.0806 data: 0.0015 max mem: 33370 +Test: [1300/2573] eta: 0:01:46 time: 0.0804 data: 0.0014 max mem: 33370 +Test: [1400/2573] eta: 0:01:37 time: 0.0786 data: 0.0015 max mem: 33370 +Test: [1500/2573] eta: 0:01:29 time: 0.0807 data: 0.0015 max mem: 33370 +Test: [1600/2573] eta: 0:01:20 time: 0.0845 data: 0.0014 max mem: 33370 +Test: [1700/2573] eta: 0:01:12 time: 0.0790 data: 0.0014 max mem: 33370 +Test: [1800/2573] eta: 0:01:03 time: 0.0823 data: 0.0014 max mem: 33370 +Test: [1900/2573] eta: 0:00:55 time: 0.0791 data: 0.0015 max mem: 33370 +Test: [2000/2573] eta: 0:00:47 time: 0.0811 data: 0.0014 max mem: 33370 +Test: [2100/2573] eta: 0:00:38 time: 0.0813 data: 0.0014 max mem: 33370 +Test: [2200/2573] eta: 0:00:30 time: 0.0817 data: 0.0014 max mem: 33370 +Test: [2300/2573] eta: 0:00:22 time: 0.0818 data: 0.0015 max mem: 33370 +Test: [2400/2573] eta: 0:00:14 time: 0.0767 data: 0.0014 max mem: 33370 +Test: [2500/2573] eta: 0:00:05 time: 0.0803 data: 0.0014 max mem: 33370 +Test: Total time: 0:03:31 +Final results: +Mean IoU is 64.59 + + precision@0.5 = 72.45 + precision@0.6 = 67.83 + precision@0.7 = 61.44 + precision@0.8 = 50.47 + precision@0.9 = 25.63 + overall IoU = 62.01 + +Average object IoU 64.59398439243101 +Overall IoU 62.01184844970703 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [36] [ 0/1319] eta: 3:12:20 lr: 6.293553287544593e-06 loss: 0.0300 (0.0300) time: 8.7495 data: 1.9061 max mem: 33370 +Epoch: [36] [ 10/1319] eta: 1:24:39 lr: 6.282814452998321e-06 loss: 0.0300 (0.0353) time: 3.8805 data: 0.1809 max mem: 33370 +Epoch: [36] [ 20/1319] eta: 1:19:22 lr: 6.2720735785923675e-06 loss: 0.0327 (0.0365) time: 3.4125 data: 0.0080 max mem: 33370 +Epoch: [36] [ 30/1319] eta: 1:17:17 lr: 6.261330660056396e-06 loss: 0.0321 (0.0349) time: 3.4422 data: 0.0080 max mem: 33370 +Epoch: [36] [ 40/1319] eta: 1:15:44 lr: 6.250585693102968e-06 loss: 0.0332 (0.0360) time: 3.4336 data: 0.0087 max mem: 33370 +Epoch: [36] [ 50/1319] eta: 1:14:28 lr: 6.2398386734274585e-06 loss: 0.0358 (0.0359) time: 3.4026 data: 0.0087 max mem: 33370 +Epoch: [36] [ 60/1319] eta: 1:13:26 lr: 6.229089596707912e-06 loss: 0.0285 (0.0348) time: 3.3920 data: 0.0082 max mem: 33370 +Epoch: [36] [ 70/1319] eta: 1:12:36 lr: 6.218338458604991e-06 loss: 0.0274 (0.0348) time: 3.4046 data: 0.0083 max mem: 33370 +Epoch: [36] [ 80/1319] eta: 1:11:49 lr: 6.207585254761843e-06 loss: 0.0296 (0.0342) time: 3.4097 data: 0.0083 max mem: 33370 +Epoch: [36] [ 90/1319] eta: 1:11:04 lr: 6.196829980804001e-06 loss: 0.0296 (0.0340) time: 3.4058 data: 0.0084 max mem: 33370 +Epoch: [36] [ 100/1319] eta: 1:10:26 lr: 6.1860726323392754e-06 loss: 0.0314 (0.0343) time: 3.4256 data: 0.0086 max mem: 33370 +Epoch: [36] [ 110/1319] eta: 1:09:48 lr: 6.175313204957665e-06 loss: 0.0307 (0.0351) time: 3.4364 data: 0.0084 max mem: 33370 +Epoch: [36] [ 120/1319] eta: 1:09:08 lr: 6.164551694231212e-06 loss: 0.0340 (0.0348) time: 3.4207 data: 0.0079 max mem: 33370 +Epoch: [36] [ 130/1319] eta: 1:08:29 lr: 6.153788095713938e-06 loss: 0.0336 (0.0381) time: 3.4113 data: 0.0078 max mem: 33370 +Epoch: [36] [ 140/1319] eta: 1:07:48 lr: 6.143022404941713e-06 loss: 0.0329 (0.0377) time: 3.3974 data: 0.0085 max mem: 33370 +Epoch: [36] [ 150/1319] eta: 1:07:15 lr: 6.132254617432146e-06 loss: 0.0299 (0.0373) time: 3.4247 data: 0.0086 max mem: 33370 +Epoch: [36] [ 160/1319] eta: 1:06:37 lr: 6.121484728684484e-06 loss: 0.0327 (0.0372) time: 3.4353 data: 0.0085 max mem: 33370 +Epoch: [36] [ 170/1319] eta: 1:05:59 lr: 6.110712734179475e-06 loss: 0.0294 (0.0367) time: 3.4032 data: 0.0087 max mem: 33370 +Epoch: [36] [ 180/1319] eta: 1:05:26 lr: 6.099938629379293e-06 loss: 0.0274 (0.0364) time: 3.4314 data: 0.0085 max mem: 33370 +Epoch: [36] [ 190/1319] eta: 1:04:50 lr: 6.0891624097274035e-06 loss: 0.0279 (0.0361) time: 3.4479 data: 0.0089 max mem: 33370 +Epoch: [36] [ 200/1319] eta: 1:04:19 lr: 6.07838407064845e-06 loss: 0.0303 (0.0360) time: 3.4719 data: 0.0090 max mem: 33370 +Epoch: [36] [ 210/1319] eta: 1:03:46 lr: 6.067603607548146e-06 loss: 0.0316 (0.0356) time: 3.4913 data: 0.0087 max mem: 33370 +Epoch: [36] [ 220/1319] eta: 1:03:08 lr: 6.05682101581314e-06 loss: 0.0300 (0.0355) time: 3.4226 data: 0.0084 max mem: 33370 +Epoch: [36] [ 230/1319] eta: 1:02:33 lr: 6.0460362908109285e-06 loss: 0.0348 (0.0354) time: 3.4095 data: 0.0082 max mem: 33370 +Epoch: [36] [ 240/1319] eta: 1:01:57 lr: 6.035249427889721e-06 loss: 0.0308 (0.0352) time: 3.4263 data: 0.0081 max mem: 33370 +Epoch: [36] [ 250/1319] eta: 1:01:24 lr: 6.024460422378318e-06 loss: 0.0270 (0.0349) time: 3.4409 data: 0.0086 max mem: 33370 +Epoch: [36] [ 260/1319] eta: 1:00:49 lr: 6.013669269586002e-06 loss: 0.0298 (0.0349) time: 3.4565 data: 0.0089 max mem: 33370 +Epoch: [36] [ 270/1319] eta: 1:00:15 lr: 6.002875964802412e-06 loss: 0.0320 (0.0348) time: 3.4458 data: 0.0083 max mem: 33370 +Epoch: [36] [ 280/1319] eta: 0:59:41 lr: 5.992080503297408e-06 loss: 0.0330 (0.0348) time: 3.4551 data: 0.0080 max mem: 33370 +Epoch: [36] [ 290/1319] eta: 0:59:04 lr: 5.981282880320978e-06 loss: 0.0317 (0.0348) time: 3.4134 data: 0.0084 max mem: 33370 +Epoch: [36] [ 300/1319] eta: 0:58:29 lr: 5.97048309110309e-06 loss: 0.0317 (0.0348) time: 3.4081 data: 0.0085 max mem: 33370 +Epoch: [36] [ 310/1319] eta: 0:57:54 lr: 5.959681130853577e-06 loss: 0.0291 (0.0346) time: 3.4260 data: 0.0080 max mem: 33370 +Epoch: [36] [ 320/1319] eta: 0:57:20 lr: 5.948876994762015e-06 loss: 0.0248 (0.0346) time: 3.4472 data: 0.0078 max mem: 33370 +Epoch: [36] [ 330/1319] eta: 0:56:46 lr: 5.938070677997572e-06 loss: 0.0303 (0.0346) time: 3.4613 data: 0.0080 max mem: 33370 +Epoch: [36] [ 340/1319] eta: 0:56:10 lr: 5.927262175708919e-06 loss: 0.0354 (0.0347) time: 3.4208 data: 0.0090 max mem: 33370 +Epoch: [36] [ 350/1319] eta: 0:55:36 lr: 5.916451483024071e-06 loss: 0.0335 (0.0348) time: 3.4332 data: 0.0090 max mem: 33370 +Epoch: [36] [ 360/1319] eta: 0:55:01 lr: 5.905638595050271e-06 loss: 0.0319 (0.0348) time: 3.4427 data: 0.0082 max mem: 33370 +Epoch: [36] [ 370/1319] eta: 0:54:26 lr: 5.894823506873858e-06 loss: 0.0317 (0.0347) time: 3.4159 data: 0.0083 max mem: 33370 +Epoch: [36] [ 380/1319] eta: 0:53:52 lr: 5.884006213560114e-06 loss: 0.0339 (0.0348) time: 3.4352 data: 0.0081 max mem: 33370 +Epoch: [36] [ 390/1319] eta: 0:53:17 lr: 5.873186710153169e-06 loss: 0.0349 (0.0348) time: 3.4326 data: 0.0080 max mem: 33370 +Epoch: [36] [ 400/1319] eta: 0:52:41 lr: 5.862364991675836e-06 loss: 0.0320 (0.0347) time: 3.4005 data: 0.0085 max mem: 33370 +Epoch: [36] [ 410/1319] eta: 0:52:08 lr: 5.85154105312949e-06 loss: 0.0307 (0.0348) time: 3.4345 data: 0.0084 max mem: 33370 +Epoch: [36] [ 420/1319] eta: 0:51:33 lr: 5.840714889493923e-06 loss: 0.0262 (0.0346) time: 3.4592 data: 0.0087 max mem: 33370 +Epoch: [36] [ 430/1319] eta: 0:50:59 lr: 5.829886495727219e-06 loss: 0.0262 (0.0346) time: 3.4520 data: 0.0089 max mem: 33370 +Epoch: [36] [ 440/1319] eta: 0:50:24 lr: 5.819055866765587e-06 loss: 0.0296 (0.0345) time: 3.4349 data: 0.0085 max mem: 33370 +Epoch: [36] [ 450/1319] eta: 0:49:49 lr: 5.808222997523256e-06 loss: 0.0278 (0.0344) time: 3.4167 data: 0.0086 max mem: 33370 +Epoch: [36] [ 460/1319] eta: 0:49:13 lr: 5.797387882892317e-06 loss: 0.0285 (0.0344) time: 3.3896 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5.1100083788515145e-06 loss: 0.0337 (0.0335) time: 3.4336 data: 0.0085 max mem: 33370 +Epoch: [36] [1100/1319] eta: 0:12:31 lr: 5.0990177994339575e-06 loss: 0.0332 (0.0334) time: 3.4123 data: 0.0086 max mem: 33370 +Epoch: [36] [1110/1319] eta: 0:11:57 lr: 5.088024587224353e-06 loss: 0.0321 (0.0335) time: 3.3998 data: 0.0086 max mem: 33370 +Epoch: [36] [1120/1319] eta: 0:11:22 lr: 5.077028735268508e-06 loss: 0.0325 (0.0335) time: 3.4000 data: 0.0082 max mem: 33370 +Epoch: [36] [1130/1319] eta: 0:10:48 lr: 5.066030236577056e-06 loss: 0.0321 (0.0335) time: 3.3985 data: 0.0081 max mem: 33370 +Epoch: [36] [1140/1319] eta: 0:10:14 lr: 5.055029084125236e-06 loss: 0.0294 (0.0334) time: 3.4156 data: 0.0083 max mem: 33370 +Epoch: [36] [1150/1319] eta: 0:09:39 lr: 5.044025270852602e-06 loss: 0.0277 (0.0334) time: 3.4380 data: 0.0085 max mem: 33370 +Epoch: [36] [1160/1319] eta: 0:09:05 lr: 5.033018789662757e-06 loss: 0.0276 (0.0334) time: 3.4440 data: 0.0083 max mem: 33370 +Epoch: [36] [1170/1319] eta: 0:08:31 lr: 5.022009633423085e-06 loss: 0.0276 (0.0333) time: 3.4482 data: 0.0080 max mem: 33370 +Epoch: [36] [1180/1319] eta: 0:07:57 lr: 5.0109977949644845e-06 loss: 0.0290 (0.0333) time: 3.4238 data: 0.0080 max mem: 33370 +Epoch: [36] [1190/1319] eta: 0:07:22 lr: 4.999983267081064e-06 loss: 0.0306 (0.0333) time: 3.4204 data: 0.0081 max mem: 33370 +Epoch: [36] [1200/1319] eta: 0:06:48 lr: 4.988966042529905e-06 loss: 0.0296 (0.0333) time: 3.4408 data: 0.0083 max mem: 33370 +Epoch: [36] [1210/1319] eta: 0:06:14 lr: 4.977946114030749e-06 loss: 0.0283 (0.0333) time: 3.4336 data: 0.0081 max mem: 33370 +Epoch: [36] [1220/1319] eta: 0:05:39 lr: 4.966923474265728e-06 loss: 0.0305 (0.0332) time: 3.4198 data: 0.0081 max mem: 33370 +Epoch: [36] [1230/1319] eta: 0:05:05 lr: 4.9558981158790714e-06 loss: 0.0306 (0.0332) time: 3.4186 data: 0.0084 max mem: 33370 +Epoch: [36] [1240/1319] eta: 0:04:31 lr: 4.944870031476802e-06 loss: 0.0296 (0.0332) time: 3.4495 data: 0.0084 max mem: 33370 +Epoch: [36] [1250/1319] eta: 0:03:56 lr: 4.9338392136264714e-06 loss: 0.0296 (0.0332) time: 3.4488 data: 0.0083 max mem: 33370 +Epoch: [36] [1260/1319] eta: 0:03:22 lr: 4.922805654856843e-06 loss: 0.0305 (0.0332) time: 3.4290 data: 0.0085 max mem: 33370 +Epoch: [36] [1270/1319] eta: 0:02:48 lr: 4.9117693476576e-06 loss: 0.0305 (0.0332) time: 3.4497 data: 0.0087 max mem: 33370 +Epoch: [36] [1280/1319] eta: 0:02:13 lr: 4.9007302844790375e-06 loss: 0.0283 (0.0332) time: 3.4640 data: 0.0088 max mem: 33370 +Epoch: [36] [1290/1319] eta: 0:01:39 lr: 4.889688457731768e-06 loss: 0.0283 (0.0331) time: 3.4171 data: 0.0087 max mem: 33370 +Epoch: [36] [1300/1319] eta: 0:01:05 lr: 4.878643859786385e-06 loss: 0.0301 (0.0331) time: 3.3996 data: 0.0083 max mem: 33370 +Epoch: [36] [1310/1319] eta: 0:00:30 lr: 4.867596482973188e-06 loss: 0.0286 (0.0331) time: 3.4559 data: 0.0078 max mem: 33370 +Epoch: [36] Total time: 1:15:27 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 2:13:49 time: 3.1205 data: 2.9401 max mem: 33370 +Test: [ 100/2573] eta: 0:04:28 time: 0.0784 data: 0.0014 max mem: 33370 +Test: [ 200/2573] eta: 0:03:44 time: 0.0803 data: 0.0014 max mem: 33370 +Test: [ 300/2573] eta: 0:03:22 time: 0.0819 data: 0.0014 max mem: 33370 +Test: [ 400/2573] eta: 0:03:08 time: 0.0822 data: 0.0014 max mem: 33370 +Test: [ 500/2573] eta: 0:02:57 time: 0.0795 data: 0.0014 max mem: 33370 +Test: [ 600/2573] eta: 0:02:46 time: 0.0798 data: 0.0014 max mem: 33370 +Test: [ 700/2573] eta: 0:02:37 time: 0.0801 data: 0.0015 max mem: 33370 +Test: [ 800/2573] eta: 0:02:28 time: 0.0831 data: 0.0014 max mem: 33370 +Test: [ 900/2573] eta: 0:02:19 time: 0.0801 data: 0.0015 max mem: 33370 +Test: [1000/2573] eta: 0:02:10 time: 0.0808 data: 0.0015 max mem: 33370 +Test: [1100/2573] eta: 0:02:02 time: 0.0805 data: 0.0016 max mem: 33370 +Test: [1200/2573] eta: 0:01:53 time: 0.0817 data: 0.0014 max mem: 33370 +Test: [1300/2573] eta: 0:01:45 time: 0.0813 data: 0.0015 max mem: 33370 +Test: [1400/2573] eta: 0:01:36 time: 0.0788 data: 0.0015 max mem: 33370 +Test: [1500/2573] eta: 0:01:28 time: 0.0802 data: 0.0015 max mem: 33370 +Test: [1600/2573] eta: 0:01:20 time: 0.0837 data: 0.0015 max mem: 33370 +Test: [1700/2573] eta: 0:01:11 time: 0.0783 data: 0.0015 max mem: 33370 +Test: [1800/2573] eta: 0:01:03 time: 0.0816 data: 0.0014 max mem: 33370 +Test: [1900/2573] eta: 0:00:55 time: 0.0791 data: 0.0014 max mem: 33370 +Test: [2000/2573] eta: 0:00:46 time: 0.0807 data: 0.0014 max mem: 33370 +Test: [2100/2573] eta: 0:00:38 time: 0.0829 data: 0.0015 max mem: 33370 +Test: [2200/2573] eta: 0:00:30 time: 0.0831 data: 0.0013 max mem: 33370 +Test: [2300/2573] eta: 0:00:22 time: 0.0818 data: 0.0014 max mem: 33370 +Test: [2400/2573] eta: 0:00:14 time: 0.0773 data: 0.0014 max mem: 33370 +Test: [2500/2573] eta: 0:00:05 time: 0.0800 data: 0.0014 max mem: 33370 +Test: Total time: 0:03:30 +Final results: +Mean IoU is 64.92 + + precision@0.5 = 72.90 + precision@0.6 = 67.99 + precision@0.7 = 61.34 + precision@0.8 = 50.59 + precision@0.9 = 25.65 + overall IoU = 62.19 + +Average object IoU 64.92024647715073 +Overall IoU 62.19342041015625 +Better epoch: 36 + +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [37] [ 0/1319] eta: 1:58:28 lr: 4.85765146153759e-06 loss: 0.0224 (0.0224) time: 5.3892 data: 1.8789 max mem: 33370 +Epoch: [37] [ 10/1319] eta: 1:18:46 lr: 4.846598783599751e-06 loss: 0.0274 (0.0283) time: 3.6105 data: 0.1786 max mem: 33370 +Epoch: [37] [ 20/1319] eta: 1:16:15 lr: 4.835543304321068e-06 loss: 0.0283 (0.0297) time: 3.4289 data: 0.0082 max mem: 33370 +Epoch: [37] [ 30/1319] eta: 1:15:29 lr: 4.824485015871577e-06 loss: 0.0283 (0.0302) time: 3.4605 data: 0.0079 max mem: 33370 +Epoch: [37] [ 40/1319] eta: 1:14:16 lr: 4.813423910379438e-06 loss: 0.0303 (0.0311) time: 3.4445 data: 0.0081 max mem: 33370 +Epoch: [37] [ 50/1319] eta: 1:13:16 lr: 4.802359979930566e-06 loss: 0.0317 (0.0310) time: 3.3883 data: 0.0084 max mem: 33370 +Epoch: [37] [ 60/1319] eta: 1:12:43 lr: 4.791293216568347e-06 loss: 0.0247 (0.0303) time: 3.4283 data: 0.0083 max mem: 33370 +Epoch: [37] [ 70/1319] eta: 1:11:59 lr: 4.780223612293264e-06 loss: 0.0279 (0.0308) time: 3.4419 data: 0.0081 max mem: 33370 +Epoch: [37] [ 80/1319] eta: 1:11:20 lr: 4.7691511590625665e-06 loss: 0.0329 (0.0315) time: 3.4222 data: 0.0079 max mem: 33370 +Epoch: [37] [ 90/1319] eta: 1:10:43 lr: 4.75807584878992e-06 loss: 0.0349 (0.0321) time: 3.4334 data: 0.0083 max mem: 33370 +Epoch: [37] [ 100/1319] eta: 1:10:03 lr: 4.7469976733450685e-06 loss: 0.0284 (0.0320) time: 3.4188 data: 0.0087 max mem: 33370 +Epoch: [37] [ 110/1319] eta: 1:09:26 lr: 4.735916624553454e-06 loss: 0.0284 (0.0327) time: 3.4160 data: 0.0086 max mem: 33370 +Epoch: [37] [ 120/1319] eta: 1:08:53 lr: 4.724832694195895e-06 loss: 0.0297 (0.0325) time: 3.4454 data: 0.0085 max mem: 33370 +Epoch: [37] [ 130/1319] eta: 1:08:13 lr: 4.713745874008202e-06 loss: 0.0281 (0.0321) time: 3.4262 data: 0.0082 max mem: 33370 +Epoch: [37] [ 140/1319] eta: 1:07:35 lr: 4.702656155680819e-06 loss: 0.0260 (0.0317) time: 3.3931 data: 0.0082 max mem: 33370 +Epoch: [37] [ 150/1319] eta: 1:07:02 lr: 4.691563530858464e-06 loss: 0.0269 (0.0320) time: 3.4240 data: 0.0081 max mem: 33370 +Epoch: [37] [ 160/1319] eta: 1:06:26 lr: 4.6804679911397265e-06 loss: 0.0289 (0.0319) time: 3.4412 data: 0.0079 max mem: 33370 +Epoch: [37] [ 170/1319] eta: 1:05:50 lr: 4.66936952807673e-06 loss: 0.0286 (0.0319) time: 3.4207 data: 0.0082 max mem: 33370 +Epoch: [37] [ 180/1319] eta: 1:05:15 lr: 4.65826813317473e-06 loss: 0.0277 (0.0317) time: 3.4169 data: 0.0086 max mem: 33370 +Epoch: [37] [ 190/1319] eta: 1:04:38 lr: 4.64716379789173e-06 loss: 0.0282 (0.0317) time: 3.4116 data: 0.0086 max mem: 33370 +Epoch: [37] [ 200/1319] eta: 1:04:05 lr: 4.636056513638103e-06 loss: 0.0307 (0.0315) time: 3.4244 data: 0.0082 max mem: 33370 +Epoch: [37] [ 210/1319] eta: 1:03:32 lr: 4.6249462717761695e-06 loss: 0.0326 (0.0318) time: 3.4618 data: 0.0085 max mem: 33370 +Epoch: [37] [ 220/1319] eta: 1:02:57 lr: 4.6138330636198426e-06 loss: 0.0306 (0.0317) time: 3.4452 data: 0.0091 max mem: 33370 +Epoch: [37] [ 230/1319] eta: 1:02:24 lr: 4.602716880434195e-06 loss: 0.0296 (0.0317) time: 3.4434 data: 0.0087 max mem: 33370 +Epoch: [37] [ 240/1319] eta: 1:01:50 lr: 4.591597713435064e-06 loss: 0.0329 (0.0318) time: 3.4568 data: 0.0082 max mem: 33370 +Epoch: [37] [ 250/1319] eta: 1:01:16 lr: 4.580475553788638e-06 loss: 0.0309 (0.0317) time: 3.4447 data: 0.0079 max mem: 33370 +Epoch: [37] [ 260/1319] eta: 1:00:42 lr: 4.569350392611047e-06 loss: 0.0273 (0.0316) time: 3.4528 data: 0.0081 max mem: 33370 +Epoch: [37] [ 270/1319] eta: 1:00:06 lr: 4.558222220967921e-06 loss: 0.0276 (0.0316) time: 3.4298 data: 0.0084 max mem: 33370 +Epoch: [37] [ 280/1319] eta: 0:59:31 lr: 4.547091029873999e-06 loss: 0.0287 (0.0315) time: 3.4139 data: 0.0084 max mem: 33370 +Epoch: [37] [ 290/1319] eta: 0:58:57 lr: 4.5359568102926745e-06 loss: 0.0310 (0.0319) time: 3.4349 data: 0.0087 max mem: 33370 +Epoch: [37] [ 300/1319] eta: 0:58:24 lr: 4.524819553135574e-06 loss: 0.0310 (0.0318) time: 3.4501 data: 0.0088 max mem: 33370 +Epoch: [37] [ 310/1319] eta: 0:57:48 lr: 4.5136792492621144e-06 loss: 0.0287 (0.0317) time: 3.4312 data: 0.0084 max mem: 33370 +Epoch: [37] [ 320/1319] eta: 0:57:14 lr: 4.502535889479041e-06 loss: 0.0287 (0.0318) time: 3.4236 data: 0.0081 max mem: 33370 +Epoch: [37] [ 330/1319] eta: 0:56:40 lr: 4.491389464540016e-06 loss: 0.0292 (0.0318) time: 3.4511 data: 0.0081 max mem: 33370 +Epoch: [37] [ 340/1319] eta: 0:56:06 lr: 4.480239965145135e-06 loss: 0.0325 (0.0321) time: 3.4540 data: 0.0084 max mem: 33370 +Epoch: [37] [ 350/1319] eta: 0:55:31 lr: 4.469087381940477e-06 loss: 0.0315 (0.0322) time: 3.4387 data: 0.0082 max mem: 33370 +Epoch: [37] [ 360/1319] eta: 0:54:57 lr: 4.457931705517646e-06 loss: 0.0285 (0.0320) time: 3.4436 data: 0.0085 max mem: 33370 +Epoch: [37] [ 370/1319] eta: 0:54:23 lr: 4.446772926413276e-06 loss: 0.0285 (0.0320) time: 3.4505 data: 0.0089 max mem: 33370 +Epoch: [37] [ 380/1319] eta: 0:53:49 lr: 4.435611035108594e-06 loss: 0.0310 (0.0320) time: 3.4424 data: 0.0091 max mem: 33370 +Epoch: [37] [ 390/1319] eta: 0:53:14 lr: 4.424446022028913e-06 loss: 0.0310 (0.0320) time: 3.4311 data: 0.0089 max mem: 33370 +Epoch: [37] [ 400/1319] eta: 0:52:39 lr: 4.413277877543152e-06 loss: 0.0312 (0.0319) time: 3.4213 data: 0.0086 max mem: 33370 +Epoch: [37] [ 410/1319] eta: 0:52:04 lr: 4.40210659196335e-06 loss: 0.0314 (0.0321) time: 3.4103 data: 0.0085 max mem: 33370 +Epoch: [37] [ 420/1319] eta: 0:51:30 lr: 4.390932155544163e-06 loss: 0.0353 (0.0322) time: 3.4247 data: 0.0083 max mem: 33370 +Epoch: [37] [ 430/1319] eta: 0:50:56 lr: 4.379754558482349e-06 loss: 0.0327 (0.0321) time: 3.4466 data: 0.0082 max mem: 33370 +Epoch: [37] [ 440/1319] eta: 0:50:22 lr: 4.368573790916289e-06 loss: 0.0301 (0.0322) time: 3.4633 data: 0.0083 max mem: 33370 +Epoch: [37] [ 450/1319] eta: 0:49:48 lr: 4.357389842925446e-06 loss: 0.0308 (0.0322) time: 3.4572 data: 0.0083 max mem: 33370 +Epoch: [37] [ 460/1319] eta: 0:49:12 lr: 4.346202704529857e-06 loss: 0.0280 (0.0321) time: 3.4129 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eta: 0:35:24 lr: 4.076727216457151e-06 loss: 0.0288 (0.0318) time: 3.4156 data: 0.0084 max mem: 33370 +Epoch: [37] [ 710/1319] eta: 0:34:50 lr: 4.065456889184196e-06 loss: 0.0309 (0.0318) time: 3.4165 data: 0.0083 max mem: 33370 +Epoch: [37] [ 720/1319] eta: 0:34:15 lr: 4.054183089304276e-06 loss: 0.0316 (0.0318) time: 3.4161 data: 0.0083 max mem: 33370 +Epoch: [37] [ 730/1319] eta: 0:33:41 lr: 4.0429058050112415e-06 loss: 0.0317 (0.0318) time: 3.4357 data: 0.0081 max mem: 33370 +Epoch: [37] [ 740/1319] eta: 0:33:06 lr: 4.031625024422082e-06 loss: 0.0296 (0.0318) time: 3.4216 data: 0.0083 max mem: 33370 +Epoch: [37] [ 750/1319] eta: 0:32:32 lr: 4.020340735576163e-06 loss: 0.0280 (0.0318) time: 3.3956 data: 0.0083 max mem: 33370 +Epoch: [37] [ 760/1319] eta: 0:31:58 lr: 4.0090529264345135e-06 loss: 0.0296 (0.0318) time: 3.4151 data: 0.0086 max mem: 33370 +Epoch: [37] [ 770/1319] eta: 0:31:24 lr: 3.997761584879033e-06 loss: 0.0299 (0.0318) time: 3.4588 data: 0.0086 max mem: 33370 +Epoch: 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time: 3.4011 data: 0.0090 max mem: 33370 +Epoch: [37] [1020/1319] eta: 0:17:05 lr: 3.714292849713318e-06 loss: 0.0295 (0.0320) time: 3.4424 data: 0.0091 max mem: 33370 +Epoch: [37] [1030/1319] eta: 0:16:30 lr: 3.7029051332087708e-06 loss: 0.0348 (0.0321) time: 3.4283 data: 0.0084 max mem: 33370 +Epoch: [37] [1040/1319] eta: 0:15:56 lr: 3.691513524125288e-06 loss: 0.0337 (0.0321) time: 3.4239 data: 0.0087 max mem: 33370 +Epoch: [37] [1050/1319] eta: 0:15:22 lr: 3.680118007776355e-06 loss: 0.0299 (0.0321) time: 3.4278 data: 0.0085 max mem: 33370 +Epoch: [37] [1060/1319] eta: 0:14:48 lr: 3.6687185693693123e-06 loss: 0.0322 (0.0321) time: 3.4370 data: 0.0081 max mem: 33370 +Epoch: [37] [1070/1319] eta: 0:14:13 lr: 3.657315194004196e-06 loss: 0.0322 (0.0322) time: 3.4275 data: 0.0083 max mem: 33370 +Epoch: [37] [1080/1319] eta: 0:13:39 lr: 3.6459078666726217e-06 loss: 0.0294 (0.0321) time: 3.3792 data: 0.0083 max mem: 33370 +Epoch: [37] [1090/1319] eta: 0:13:05 lr: 3.6344965722565904e-06 loss: 0.0280 (0.0321) time: 3.4080 data: 0.0080 max mem: 33370 +Epoch: [37] [1100/1319] eta: 0:12:30 lr: 3.6230812955273095e-06 loss: 0.0303 (0.0322) time: 3.4475 data: 0.0082 max mem: 33370 +Epoch: [37] [1110/1319] eta: 0:11:56 lr: 3.6116620211439967e-06 loss: 0.0303 (0.0322) time: 3.4516 data: 0.0085 max mem: 33370 +Epoch: [37] [1120/1319] eta: 0:11:22 lr: 3.6002387336526318e-06 loss: 0.0285 (0.0322) time: 3.4429 data: 0.0085 max mem: 33370 +Epoch: [37] [1130/1319] eta: 0:10:47 lr: 3.588811417484761e-06 loss: 0.0300 (0.0323) time: 3.4161 data: 0.0091 max mem: 33370 +Epoch: [37] [1140/1319] eta: 0:10:13 lr: 3.577380056956213e-06 loss: 0.0311 (0.0323) time: 3.4371 data: 0.0095 max mem: 33370 +Epoch: [37] [1150/1319] eta: 0:09:39 lr: 3.5659446362658317e-06 loss: 0.0291 (0.0323) time: 3.4309 data: 0.0090 max mem: 33370 +Epoch: [37] [1160/1319] eta: 0:09:05 lr: 3.5545051394941854e-06 loss: 0.0291 (0.0323) time: 3.4182 data: 0.0091 max mem: 33370 +Epoch: [37] [1170/1319] eta: 0:08:30 lr: 3.5430615506022587e-06 loss: 0.0311 (0.0323) time: 3.4298 data: 0.0090 max mem: 33370 +Epoch: [37] [1180/1319] eta: 0:07:56 lr: 3.531613853430098e-06 loss: 0.0303 (0.0322) time: 3.4383 data: 0.0087 max mem: 33370 +Epoch: [37] [1190/1319] eta: 0:07:22 lr: 3.5201620316954973e-06 loss: 0.0275 (0.0322) time: 3.4440 data: 0.0085 max mem: 33370 +Epoch: [37] [1200/1319] eta: 0:06:48 lr: 3.5087060689926057e-06 loss: 0.0285 (0.0322) time: 3.4460 data: 0.0081 max mem: 33370 +Epoch: [37] [1210/1319] eta: 0:06:13 lr: 3.4972459487905388e-06 loss: 0.0293 (0.0322) time: 3.4565 data: 0.0084 max mem: 33370 +Epoch: [37] [1220/1319] eta: 0:05:39 lr: 3.485781654431977e-06 loss: 0.0305 (0.0322) time: 3.4466 data: 0.0088 max mem: 33370 +Epoch: [37] [1230/1319] eta: 0:05:05 lr: 3.4743131691317023e-06 loss: 0.0315 (0.0322) time: 3.4050 data: 0.0083 max mem: 33370 +Epoch: [37] [1240/1319] eta: 0:04:30 lr: 3.462840475975186e-06 loss: 0.0298 (0.0322) time: 3.3922 data: 0.0080 max mem: 33370 +Epoch: [37] 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+/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 2:14:51 time: 3.1449 data: 3.0500 max mem: 33370 +Test: [ 100/2573] eta: 0:04:29 time: 0.0789 data: 0.0016 max mem: 33370 +Test: [ 200/2573] eta: 0:03:44 time: 0.0790 data: 0.0015 max mem: 33370 +Test: [ 300/2573] eta: 0:03:22 time: 0.0806 data: 0.0015 max mem: 33370 +Test: [ 400/2573] eta: 0:03:08 time: 0.0809 data: 0.0014 max mem: 33370 +Test: [ 500/2573] eta: 0:02:56 time: 0.0794 data: 0.0015 max mem: 33370 +Test: [ 600/2573] eta: 0:02:46 time: 0.0794 data: 0.0015 max mem: 33370 +Test: [ 700/2573] eta: 0:02:37 time: 0.0795 data: 0.0014 max mem: 33370 +Test: [ 800/2573] eta: 0:02:28 time: 0.0836 data: 0.0014 max mem: 33370 +Test: [ 900/2573] eta: 0:02:19 time: 0.0809 data: 0.0015 max mem: 33370 +Test: [1000/2573] eta: 0:02:10 time: 0.0804 data: 0.0014 max mem: 33370 +Test: [1100/2573] eta: 0:02:02 time: 0.0800 data: 0.0015 max mem: 33370 +Test: [1200/2573] eta: 0:01:53 time: 0.0809 data: 0.0014 max mem: 33370 +Test: [1300/2573] eta: 0:01:45 time: 0.0809 data: 0.0014 max mem: 33370 +Test: [1400/2573] eta: 0:01:36 time: 0.0799 data: 0.0015 max mem: 33370 +Test: [1500/2573] eta: 0:01:28 time: 0.0817 data: 0.0015 max mem: 33370 +Test: [1600/2573] eta: 0:01:20 time: 0.0837 data: 0.0015 max mem: 33370 +Test: [1700/2573] eta: 0:01:11 time: 0.0790 data: 0.0013 max mem: 33370 +Test: [1800/2573] eta: 0:01:03 time: 0.0843 data: 0.0014 max mem: 33370 +Test: [1900/2573] eta: 0:00:55 time: 0.0786 data: 0.0014 max mem: 33370 +Test: [2000/2573] eta: 0:00:46 time: 0.0814 data: 0.0014 max mem: 33370 +Test: [2100/2573] eta: 0:00:38 time: 0.0829 data: 0.0015 max mem: 33370 +Test: [2200/2573] eta: 0:00:30 time: 0.0821 data: 0.0015 max mem: 33370 +Test: [2300/2573] eta: 0:00:22 time: 0.0824 data: 0.0015 max mem: 33370 +Test: [2400/2573] eta: 0:00:14 time: 0.0787 data: 0.0014 max mem: 33370 +Test: [2500/2573] eta: 0:00:05 time: 0.0797 data: 0.0014 max mem: 33370 +Test: Total time: 0:03:30 +Final results: +Mean IoU is 64.77 + + precision@0.5 = 72.67 + precision@0.6 = 67.38 + precision@0.7 = 61.07 + precision@0.8 = 50.29 + precision@0.9 = 25.67 + overall IoU = 62.00 + +Average object IoU 64.77142306107676 +Overall IoU 62.00176239013672 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [38] [ 0/1319] eta: 3:32:00 lr: 3.3720562685558925e-06 loss: 0.0261 (0.0261) time: 9.6438 data: 2.5323 max mem: 33370 +Epoch: [38] [ 10/1319] eta: 1:27:35 lr: 3.3605453588871517e-06 loss: 0.0268 (0.0319) time: 4.0149 data: 0.2378 max mem: 33370 +Epoch: [38] [ 20/1319] eta: 1:21:16 lr: 3.349030066603249e-06 loss: 0.0327 (0.0340) time: 3.4599 data: 0.0082 max mem: 33370 +Epoch: [38] [ 30/1319] eta: 1:18:05 lr: 3.3375103732791936e-06 loss: 0.0293 (0.0337) time: 3.4256 data: 0.0085 max mem: 33370 +Epoch: [38] [ 40/1319] eta: 1:16:07 lr: 3.3259862603415314e-06 loss: 0.0287 (0.0327) time: 3.3790 data: 0.0085 max mem: 33370 +Epoch: [38] [ 50/1319] eta: 1:15:07 lr: 3.314457709066606e-06 loss: 0.0311 (0.0332) time: 3.4239 data: 0.0086 max mem: 33370 +Epoch: [38] [ 60/1319] eta: 1:14:12 lr: 3.302924700578736e-06 loss: 0.0329 (0.0333) time: 3.4657 data: 0.0092 max mem: 33370 +Epoch: [38] [ 70/1319] eta: 1:13:11 lr: 3.2913872158483893e-06 loss: 0.0290 (0.0330) time: 3.4249 data: 0.0094 max mem: 33370 +Epoch: [38] [ 80/1319] eta: 1:12:21 lr: 3.279845235690334e-06 loss: 0.0276 (0.0323) time: 3.4042 data: 0.0091 max mem: 33370 +Epoch: [38] [ 90/1319] eta: 1:11:39 lr: 3.268298740761722e-06 loss: 0.0282 (0.0327) time: 3.4360 data: 0.0085 max mem: 33370 +Epoch: [38] [ 100/1319] eta: 1:11:00 lr: 3.2567477115602124e-06 loss: 0.0320 (0.0326) time: 3.4584 data: 0.0081 max mem: 33370 +Epoch: [38] [ 110/1319] eta: 1:10:16 lr: 3.2451921284219928e-06 loss: 0.0301 (0.0327) time: 3.4380 data: 0.0085 max mem: 33370 +Epoch: [38] [ 120/1319] eta: 1:09:33 lr: 3.233631971519807e-06 loss: 0.0278 (0.0324) time: 3.4091 data: 0.0091 max mem: 33370 +Epoch: [38] [ 130/1319] eta: 1:08:52 lr: 3.2220672208609392e-06 loss: 0.0240 (0.0321) time: 3.4091 data: 0.0089 max mem: 33370 +Epoch: [38] [ 140/1319] eta: 1:08:14 lr: 3.2104978562851772e-06 loss: 0.0253 (0.0318) time: 3.4225 data: 0.0089 max mem: 33370 +Epoch: [38] [ 150/1319] eta: 1:07:34 lr: 3.1989238574627024e-06 loss: 0.0287 (0.0317) time: 3.4222 data: 0.0092 max mem: 33370 +Epoch: [38] [ 160/1319] eta: 1:06:54 lr: 3.18734520389202e-06 loss: 0.0312 (0.0316) time: 3.3995 data: 0.0090 max mem: 33370 +Epoch: [38] [ 170/1319] eta: 1:06:17 lr: 3.175761874897778e-06 loss: 0.0279 (0.0315) time: 3.4074 data: 0.0084 max mem: 33370 +Epoch: [38] [ 180/1319] eta: 1:05:41 lr: 3.1641738496285912e-06 loss: 0.0286 (0.0315) time: 3.4392 data: 0.0082 max mem: 33370 +Epoch: [38] [ 190/1319] eta: 1:05:04 lr: 3.1525811070548283e-06 loss: 0.0324 (0.0316) time: 3.4289 data: 0.0081 max mem: 33370 +Epoch: [38] [ 200/1319] eta: 1:04:26 lr: 3.1409836259663234e-06 loss: 0.0324 (0.0318) time: 3.4056 data: 0.0079 max mem: 33370 +Epoch: [38] [ 210/1319] eta: 1:03:49 lr: 3.1293813849701203e-06 loss: 0.0302 (0.0319) time: 3.4107 data: 0.0082 max mem: 33370 +Epoch: [38] [ 220/1319] eta: 1:03:14 lr: 3.1177743624881108e-06 loss: 0.0288 (0.0316) time: 3.4260 data: 0.0084 max mem: 33370 +Epoch: [38] [ 230/1319] eta: 1:02:37 lr: 3.1061625367546658e-06 loss: 0.0246 (0.0315) time: 3.4177 data: 0.0086 max mem: 33370 +Epoch: [38] [ 240/1319] eta: 1:02:03 lr: 3.0945458858142194e-06 loss: 0.0295 (0.0316) time: 3.4270 data: 0.0086 max mem: 33370 +Epoch: [38] [ 250/1319] eta: 1:01:27 lr: 3.08292438751882e-06 loss: 0.0316 (0.0315) time: 3.4381 data: 0.0082 max mem: 33370 +Epoch: [38] [ 260/1319] eta: 1:00:52 lr: 3.071298019525602e-06 loss: 0.0303 (0.0316) time: 3.4267 data: 0.0083 max mem: 33370 +Epoch: [38] [ 270/1319] eta: 1:00:15 lr: 3.0596667592942867e-06 loss: 0.0303 (0.0317) time: 3.4071 data: 0.0086 max mem: 33370 +Epoch: [38] [ 280/1319] eta: 0:59:40 lr: 3.048030584084566e-06 loss: 0.0316 (0.0320) time: 3.4163 data: 0.0085 max mem: 33370 +Epoch: [38] [ 290/1319] eta: 0:59:07 lr: 3.036389470953479e-06 loss: 0.0340 (0.0320) time: 3.4624 data: 0.0085 max mem: 33370 +Epoch: [38] [ 300/1319] eta: 0:58:33 lr: 3.024743396752744e-06 loss: 0.0296 (0.0321) time: 3.4664 data: 0.0086 max mem: 33370 +Epoch: [38] [ 310/1319] eta: 0:57:58 lr: 3.013092338126003e-06 loss: 0.0302 (0.0321) time: 3.4436 data: 0.0085 max mem: 33370 +Epoch: [38] [ 320/1319] eta: 0:57:23 lr: 3.0014362715060913e-06 loss: 0.0341 (0.0322) time: 3.4387 data: 0.0084 max mem: 33370 +Epoch: [38] [ 330/1319] eta: 0:56:47 lr: 2.9897751731121923e-06 loss: 0.0290 (0.0322) time: 3.4214 data: 0.0082 max mem: 33370 +Epoch: [38] [ 340/1319] eta: 0:56:14 lr: 2.978109018946967e-06 loss: 0.0278 (0.0321) time: 3.4347 data: 0.0082 max mem: 33370 +Epoch: [38] [ 350/1319] eta: 0:55:39 lr: 2.9664377847936435e-06 loss: 0.0259 (0.0319) time: 3.4573 data: 0.0082 max mem: 33370 +Epoch: [38] [ 360/1319] eta: 0:55:04 lr: 2.954761446213011e-06 loss: 0.0265 (0.0319) time: 3.4300 data: 0.0085 max mem: 33370 +Epoch: [38] [ 370/1319] eta: 0:54:29 lr: 2.943079978540434e-06 loss: 0.0270 (0.0318) time: 3.4229 data: 0.0086 max mem: 33370 +Epoch: [38] [ 380/1319] eta: 0:53:54 lr: 2.931393356882739e-06 loss: 0.0292 (0.0319) time: 3.4315 data: 0.0084 max mem: 33370 +Epoch: [38] [ 390/1319] eta: 0:53:20 lr: 2.919701556115084e-06 loss: 0.0331 (0.0319) time: 3.4406 data: 0.0085 max mem: 33370 +Epoch: [38] [ 400/1319] eta: 0:52:45 lr: 2.908004550877762e-06 loss: 0.0311 (0.0319) time: 3.4395 data: 0.0084 max mem: 33370 +Epoch: [38] [ 410/1319] eta: 0:52:10 lr: 2.8963023155729493e-06 loss: 0.0270 (0.0318) time: 3.4208 data: 0.0087 max mem: 33370 +Epoch: [38] [ 420/1319] eta: 0:51:35 lr: 2.884594824361366e-06 loss: 0.0283 (0.0318) time: 3.4292 data: 0.0090 max mem: 33370 +Epoch: [38] [ 430/1319] eta: 0:51:01 lr: 2.8728820511589384e-06 loss: 0.0283 (0.0317) time: 3.4450 data: 0.0086 max mem: 33370 +Epoch: [38] [ 440/1319] eta: 0:50:26 lr: 2.861163969633332e-06 loss: 0.0279 (0.0317) time: 3.4334 data: 0.0084 max mem: 33370 +Epoch: [38] [ 450/1319] eta: 0:49:52 lr: 2.849440553200456e-06 loss: 0.0280 (0.0317) time: 3.4311 data: 0.0082 max mem: 33370 +Epoch: [38] [ 460/1319] eta: 0:49:17 lr: 2.837711775020899e-06 loss: 0.0313 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(0.0319) time: 3.4136 data: 0.0085 max mem: 33370 +Epoch: [38] [ 860/1319] eta: 0:26:17 lr: 2.3638198820602614e-06 loss: 0.0285 (0.0318) time: 3.4203 data: 0.0083 max mem: 33370 +Epoch: [38] [ 870/1319] eta: 0:25:42 lr: 2.351844430532552e-06 loss: 0.0278 (0.0319) time: 3.3857 data: 0.0081 max mem: 33370 +Epoch: [38] [ 880/1319] eta: 0:25:07 lr: 2.339862199770001e-06 loss: 0.0319 (0.0320) time: 3.3808 data: 0.0083 max mem: 33370 +Epoch: [38] [ 890/1319] eta: 0:24:33 lr: 2.327873147317513e-06 loss: 0.0302 (0.0320) time: 3.4051 data: 0.0086 max mem: 33370 +Epoch: [38] [ 900/1319] eta: 0:23:59 lr: 2.315877230209485e-06 loss: 0.0301 (0.0320) time: 3.4393 data: 0.0083 max mem: 33370 +Epoch: [38] [ 910/1319] eta: 0:23:24 lr: 2.303874404960728e-06 loss: 0.0298 (0.0320) time: 3.4054 data: 0.0081 max mem: 33370 +Epoch: [38] [ 920/1319] eta: 0:22:50 lr: 2.291864627557113e-06 loss: 0.0305 (0.0320) time: 3.3979 data: 0.0084 max mem: 33370 +Epoch: [38] [ 930/1319] eta: 0:22:15 lr: 2.2798478534460264e-06 loss: 0.0305 (0.0320) time: 3.4397 data: 0.0084 max mem: 33370 +Epoch: [38] [ 940/1319] eta: 0:21:41 lr: 2.2678240375265906e-06 loss: 0.0271 (0.0319) time: 3.4193 data: 0.0086 max mem: 33370 +Epoch: [38] [ 950/1319] eta: 0:21:07 lr: 2.25579313413962e-06 loss: 0.0281 (0.0319) time: 3.4342 data: 0.0089 max mem: 33370 +Epoch: [38] [ 960/1319] eta: 0:20:32 lr: 2.243755097057401e-06 loss: 0.0288 (0.0319) time: 3.4561 data: 0.0089 max mem: 33370 +Epoch: [38] [ 970/1319] eta: 0:19:58 lr: 2.2317098794731506e-06 loss: 0.0261 (0.0319) time: 3.4231 data: 0.0086 max mem: 33370 +Epoch: [38] [ 980/1319] eta: 0:19:23 lr: 2.2196574339902486e-06 loss: 0.0299 (0.0319) time: 3.3827 data: 0.0087 max mem: 33370 +Epoch: [38] [ 990/1319] eta: 0:18:49 lr: 2.2075977126112046e-06 loss: 0.0320 (0.0319) time: 3.4018 data: 0.0087 max mem: 33370 +Epoch: [38] [1000/1319] eta: 0:18:15 lr: 2.195530666726346e-06 loss: 0.0287 (0.0319) time: 3.4344 data: 0.0085 max mem: 33370 +Epoch: [38] 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3.4545 data: 0.0085 max mem: 33370 +Epoch: [38] [1170/1319] eta: 0:08:31 lr: 1.9892199154733075e-06 loss: 0.0310 (0.0318) time: 3.4403 data: 0.0084 max mem: 33370 +Epoch: [38] [1180/1319] eta: 0:07:57 lr: 1.977011942435173e-06 loss: 0.0275 (0.0318) time: 3.4342 data: 0.0090 max mem: 33370 +Epoch: [38] [1190/1319] eta: 0:07:22 lr: 1.964795587609718e-06 loss: 0.0286 (0.0318) time: 3.4443 data: 0.0090 max mem: 33370 +Epoch: [38] [1200/1319] eta: 0:06:48 lr: 1.9525707872561044e-06 loss: 0.0302 (0.0318) time: 3.4460 data: 0.0088 max mem: 33370 +Epoch: [38] [1210/1319] eta: 0:06:14 lr: 1.9403374767016633e-06 loss: 0.0300 (0.0318) time: 3.4140 data: 0.0084 max mem: 33370 +Epoch: [38] [1220/1319] eta: 0:05:39 lr: 1.928095590321611e-06 loss: 0.0306 (0.0318) time: 3.4503 data: 0.0081 max mem: 33370 +Epoch: [38] [1230/1319] eta: 0:05:05 lr: 1.915845061518256e-06 loss: 0.0296 (0.0318) time: 3.4405 data: 0.0084 max mem: 33370 +Epoch: [38] [1240/1319] eta: 0:04:31 lr: 1.9035858226995284e-06 loss: 0.0311 (0.0319) time: 3.4107 data: 0.0086 max mem: 33370 +Epoch: [38] [1250/1319] eta: 0:03:56 lr: 1.8913178052569088e-06 loss: 0.0316 (0.0319) time: 3.4210 data: 0.0085 max mem: 33370 +Epoch: [38] [1260/1319] eta: 0:03:22 lr: 1.8790409395427117e-06 loss: 0.0303 (0.0319) time: 3.4261 data: 0.0084 max mem: 33370 +Epoch: [38] [1270/1319] eta: 0:02:48 lr: 1.8667551548466507e-06 loss: 0.0270 (0.0319) time: 3.4454 data: 0.0085 max mem: 33370 +Epoch: [38] [1280/1319] eta: 0:02:13 lr: 1.8544603793717773e-06 loss: 0.0310 (0.0319) time: 3.4398 data: 0.0087 max mem: 33370 +Epoch: [38] [1290/1319] eta: 0:01:39 lr: 1.8421565402096163e-06 loss: 0.0310 (0.0319) time: 3.4199 data: 0.0089 max mem: 33370 +Epoch: [38] [1300/1319] eta: 0:01:05 lr: 1.8298435633145817e-06 loss: 0.0276 (0.0319) time: 3.4106 data: 0.0086 max mem: 33370 +Epoch: [38] [1310/1319] eta: 0:00:30 lr: 1.8175213734776007e-06 loss: 0.0266 (0.0318) time: 3.4200 data: 0.0081 max mem: 33370 +Epoch: [38] Total time: 1:15:28 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 2:18:38 time: 3.2329 data: 3.1171 max mem: 33370 +Test: [ 100/2573] eta: 0:04:30 time: 0.0782 data: 0.0015 max mem: 33370 +Test: [ 200/2573] eta: 0:03:45 time: 0.0798 data: 0.0014 max mem: 33370 +Test: [ 300/2573] eta: 0:03:23 time: 0.0815 data: 0.0014 max mem: 33370 +Test: [ 400/2573] eta: 0:03:09 time: 0.0837 data: 0.0014 max mem: 33370 +Test: [ 500/2573] eta: 0:02:57 time: 0.0798 data: 0.0015 max mem: 33370 +Test: [ 600/2573] eta: 0:02:47 time: 0.0801 data: 0.0015 max mem: 33370 +Test: [ 700/2573] eta: 0:02:38 time: 0.0808 data: 0.0015 max mem: 33370 +Test: [ 800/2573] eta: 0:02:29 time: 0.0838 data: 0.0014 max mem: 33370 +Test: [ 900/2573] eta: 0:02:20 time: 0.0807 data: 0.0014 max mem: 33370 +Test: [1000/2573] eta: 0:02:11 time: 0.0818 data: 0.0014 max mem: 33370 +Test: [1100/2573] eta: 0:02:03 time: 0.0821 data: 0.0015 max mem: 33370 +Test: [1200/2573] eta: 0:01:54 time: 0.0814 data: 0.0015 max mem: 33370 +Test: [1300/2573] eta: 0:01:46 time: 0.0808 data: 0.0014 max mem: 33370 +Test: [1400/2573] eta: 0:01:37 time: 0.0798 data: 0.0015 max mem: 33370 +Test: [1500/2573] eta: 0:01:29 time: 0.0803 data: 0.0014 max mem: 33370 +Test: [1600/2573] eta: 0:01:20 time: 0.0835 data: 0.0014 max mem: 33370 +Test: [1700/2573] eta: 0:01:12 time: 0.0784 data: 0.0014 max mem: 33370 +Test: [1800/2573] eta: 0:01:03 time: 0.0825 data: 0.0015 max mem: 33370 +Test: [1900/2573] eta: 0:00:55 time: 0.0792 data: 0.0014 max mem: 33370 +Test: [2000/2573] eta: 0:00:47 time: 0.0808 data: 0.0014 max mem: 33370 +Test: [2100/2573] eta: 0:00:38 time: 0.0826 data: 0.0014 max mem: 33370 +Test: [2200/2573] eta: 0:00:30 time: 0.0820 data: 0.0014 max mem: 33370 +Test: [2300/2573] eta: 0:00:22 time: 0.0837 data: 0.0015 max mem: 33370 +Test: [2400/2573] eta: 0:00:14 time: 0.0775 data: 0.0014 max mem: 33370 +Test: [2500/2573] eta: 0:00:05 time: 0.0804 data: 0.0014 max mem: 33370 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: Total time: 0:03:31 +Final results: +Mean IoU is 64.99 + + precision@0.5 = 73.02 + precision@0.6 = 67.69 + precision@0.7 = 61.27 + precision@0.8 = 50.57 + precision@0.9 = 25.71 + overall IoU = 62.22 + +Average object IoU 64.98541664783306 +Overall IoU 62.2197265625 +Better epoch: 38 + +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [39] [ 0/1319] eta: 1:51:54 lr: 1.8064234624396156e-06 loss: 0.0315 (0.0315) time: 5.0904 data: 1.5211 max mem: 33370 +Epoch: [39] [ 10/1319] eta: 1:18:42 lr: 1.7940835565249508e-06 loss: 0.0249 (0.0280) time: 3.6081 data: 0.1464 max mem: 33370 +Epoch: [39] [ 20/1319] eta: 1:16:32 lr: 1.7817342127276263e-06 loss: 0.0249 (0.0300) time: 3.4575 data: 0.0086 max mem: 33370 +Epoch: [39] [ 30/1319] eta: 1:15:17 lr: 1.7693753510331764e-06 loss: 0.0266 (0.0297) time: 3.4482 data: 0.0085 max mem: 33370 +Epoch: [39] [ 40/1319] eta: 1:14:30 lr: 1.757006890122028e-06 loss: 0.0312 (0.0302) time: 3.4537 data: 0.0086 max mem: 33370 +Epoch: [39] [ 50/1319] eta: 1:13:52 lr: 1.7446287473378005e-06 loss: 0.0313 (0.0303) time: 3.4743 data: 0.0087 max mem: 33370 +Epoch: [39] [ 60/1319] eta: 1:12:59 lr: 1.7322408386546176e-06 loss: 0.0311 (0.0307) time: 3.4428 data: 0.0082 max mem: 33370 +Epoch: [39] [ 70/1319] eta: 1:12:14 lr: 1.7198430786433514e-06 loss: 0.0315 (0.0312) time: 3.4120 data: 0.0077 max mem: 33370 +Epoch: [39] [ 80/1319] eta: 1:11:29 lr: 1.7074353804367206e-06 loss: 0.0327 (0.0311) time: 3.4127 data: 0.0080 max mem: 33370 +Epoch: [39] [ 90/1319] eta: 1:10:51 lr: 1.6950176556933094e-06 loss: 0.0277 (0.0309) time: 3.4227 data: 0.0082 max mem: 33370 +Epoch: [39] [ 100/1319] eta: 1:10:10 lr: 1.682589814560305e-06 loss: 0.0312 (0.0313) time: 3.4205 data: 0.0086 max mem: 33370 +Epoch: [39] [ 110/1319] eta: 1:09:30 lr: 1.6701517656350208e-06 loss: 0.0312 (0.0312) time: 3.4042 data: 0.0087 max mem: 33370 +Epoch: [39] [ 120/1319] eta: 1:08:51 lr: 1.6577034159251048e-06 loss: 0.0279 (0.0308) time: 3.4033 data: 0.0086 max mem: 33370 +Epoch: [39] [ 130/1319] eta: 1:08:13 lr: 1.6452446708073954e-06 loss: 0.0276 (0.0306) time: 3.4058 data: 0.0086 max mem: 33370 +Epoch: [39] [ 140/1319] eta: 1:07:40 lr: 1.632775433985313e-06 loss: 0.0268 (0.0304) time: 3.4351 data: 0.0084 max mem: 33370 +Epoch: [39] [ 150/1319] eta: 1:07:00 lr: 1.62029560744485e-06 loss: 0.0249 (0.0302) time: 3.4137 data: 0.0081 max mem: 33370 +Epoch: [39] [ 160/1319] eta: 1:06:22 lr: 1.6078050914089353e-06 loss: 0.0296 (0.0305) time: 3.3802 data: 0.0084 max mem: 33370 +Epoch: [39] [ 170/1319] eta: 1:05:48 lr: 1.5953037842902214e-06 loss: 0.0329 (0.0308) time: 3.4163 data: 0.0091 max mem: 33370 +Epoch: [39] [ 180/1319] eta: 1:05:14 lr: 1.5827915826421849e-06 loss: 0.0341 (0.0310) time: 3.4397 data: 0.0087 max mem: 33370 +Epoch: [39] [ 190/1319] eta: 1:04:40 lr: 1.5702683811084266e-06 loss: 0.0301 (0.0310) time: 3.4452 data: 0.0085 max mem: 33370 +Epoch: [39] [ 200/1319] eta: 1:04:06 lr: 1.5577340723702017e-06 loss: 0.0280 (0.0309) time: 3.4423 data: 0.0087 max mem: 33370 +Epoch: [39] [ 210/1319] eta: 1:03:31 lr: 1.5451885470919527e-06 loss: 0.0260 (0.0308) time: 3.4303 data: 0.0085 max mem: 33370 +Epoch: [39] [ 220/1319] eta: 1:02:57 lr: 1.5326316938648584e-06 loss: 0.0265 (0.0310) time: 3.4417 data: 0.0087 max mem: 33370 +Epoch: [39] [ 230/1319] eta: 1:02:23 lr: 1.5200633991482792e-06 loss: 0.0296 (0.0309) time: 3.4464 data: 0.0085 max mem: 33370 +Epoch: [39] [ 240/1319] eta: 1:01:50 lr: 1.5074835472089545e-06 loss: 0.0253 (0.0308) time: 3.4535 data: 0.0080 max mem: 33370 +Epoch: [39] [ 250/1319] eta: 1:01:15 lr: 1.4948920200579605e-06 loss: 0.0247 (0.0307) time: 3.4462 data: 0.0081 max mem: 33370 +Epoch: [39] [ 260/1319] eta: 1:00:40 lr: 1.4822886973851744e-06 loss: 0.0279 (0.0306) time: 3.4252 data: 0.0087 max mem: 33370 +Epoch: [39] [ 270/1319] eta: 1:00:05 lr: 1.4696734564912314e-06 loss: 0.0279 (0.0308) time: 3.4270 data: 0.0090 max mem: 33370 +Epoch: [39] [ 280/1319] eta: 0:59:31 lr: 1.457046172216814e-06 loss: 0.0298 (0.0308) time: 3.4274 data: 0.0086 max mem: 33370 +Epoch: [39] [ 290/1319] eta: 0:58:58 lr: 1.444406716869153e-06 loss: 0.0336 (0.0309) time: 3.4543 data: 0.0087 max mem: 33370 +Epoch: [39] [ 300/1319] eta: 0:58:24 lr: 1.4317549601455566e-06 loss: 0.0353 (0.0311) time: 3.4742 data: 0.0089 max mem: 33370 +Epoch: [39] [ 310/1319] eta: 0:57:49 lr: 1.419090769053936e-06 loss: 0.0365 (0.0313) time: 3.4362 data: 0.0087 max mem: 33370 +Epoch: [39] [ 320/1319] eta: 0:57:13 lr: 1.4064140078300187e-06 loss: 0.0329 (0.0314) time: 3.4059 data: 0.0088 max mem: 33370 +Epoch: [39] [ 330/1319] eta: 0:56:38 lr: 1.3937245378511972e-06 loss: 0.0306 (0.0314) time: 3.4101 data: 0.0093 max mem: 33370 +Epoch: [39] [ 340/1319] eta: 0:56:04 lr: 1.3810222175468009e-06 loss: 0.0279 (0.0313) time: 3.4213 data: 0.0089 max mem: 33370 +Epoch: [39] [ 350/1319] eta: 0:55:28 lr: 1.3683069023045655e-06 loss: 0.0284 (0.0314) time: 3.4035 data: 0.0082 max mem: 33370 +Epoch: [39] [ 360/1319] eta: 0:54:53 lr: 1.355578444373217e-06 loss: 0.0284 (0.0313) time: 3.4035 data: 0.0083 max mem: 33370 +Epoch: [39] [ 370/1319] eta: 0:54:19 lr: 1.3428366927608033e-06 loss: 0.0292 (0.0313) time: 3.4292 data: 0.0083 max mem: 33370 +Epoch: [39] [ 380/1319] eta: 0:53:46 lr: 1.330081493128668e-06 loss: 0.0305 (0.0313) time: 3.4530 data: 0.0081 max mem: 33370 +Epoch: [39] [ 390/1319] eta: 0:53:11 lr: 1.3173126876807778e-06 loss: 0.0294 (0.0313) time: 3.4567 data: 0.0084 max mem: 33370 +Epoch: [39] [ 400/1319] eta: 0:52:37 lr: 1.304530115048165e-06 loss: 0.0267 (0.0313) time: 3.4470 data: 0.0088 max mem: 33370 +Epoch: [39] [ 410/1319] eta: 0:52:02 lr: 1.2917336101681678e-06 loss: 0.0304 (0.0314) time: 3.4305 data: 0.0085 max mem: 33370 +Epoch: [39] [ 420/1319] eta: 0:51:28 lr: 1.2789230041582899e-06 loss: 0.0307 (0.0313) time: 3.4309 data: 0.0080 max mem: 33370 +Epoch: [39] [ 430/1319] eta: 0:50:55 lr: 1.2660981241842216e-06 loss: 0.0282 (0.0312) time: 3.4618 data: 0.0081 max mem: 33370 +Epoch: [39] [ 440/1319] eta: 0:50:20 lr: 1.2532587933218004e-06 loss: 0.0261 (0.0311) time: 3.4381 data: 0.0080 max mem: 33370 +Epoch: [39] [ 450/1319] eta: 0:49:45 lr: 1.2404048304125217e-06 loss: 0.0273 (0.0311) time: 3.4058 data: 0.0082 max mem: 33370 +Epoch: [39] [ 460/1319] eta: 0:49:11 lr: 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data: 0.0083 max mem: 33370 +Epoch: [39] [ 700/1319] eta: 0:35:26 lr: 9.136614974653884e-07 loss: 0.0302 (0.0313) time: 3.4367 data: 0.0080 max mem: 33370 +Epoch: [39] [ 710/1319] eta: 0:34:52 lr: 9.003449179133091e-07 loss: 0.0288 (0.0312) time: 3.4345 data: 0.0085 max mem: 33370 +Epoch: [39] [ 720/1319] eta: 0:34:17 lr: 8.870064170319405e-07 loss: 0.0283 (0.0312) time: 3.4220 data: 0.0087 max mem: 33370 +Epoch: [39] [ 730/1319] eta: 0:33:43 lr: 8.736455912114245e-07 loss: 0.0287 (0.0312) time: 3.4187 data: 0.0085 max mem: 33370 +Epoch: [39] [ 740/1319] eta: 0:33:08 lr: 8.602620224130043e-07 loss: 0.0312 (0.0313) time: 3.4199 data: 0.0091 max mem: 33370 +Epoch: [39] [ 750/1319] eta: 0:32:34 lr: 8.468552773943076e-07 loss: 0.0294 (0.0313) time: 3.4203 data: 0.0090 max mem: 33370 +Epoch: [39] [ 760/1319] eta: 0:31:59 lr: 8.334249068786857e-07 loss: 0.0276 (0.0313) time: 3.4368 data: 0.0086 max mem: 33370 +Epoch: [39] [ 770/1319] eta: 0:31:25 lr: 8.199704446634483e-07 loss: 0.0276 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loss: 0.0283 (0.0314) time: 3.4108 data: 0.0087 max mem: 33370 +Epoch: [39] [ 860/1319] eta: 0:26:15 lr: 6.977094839143229e-07 loss: 0.0290 (0.0314) time: 3.4342 data: 0.0086 max mem: 33370 +Epoch: [39] [ 870/1319] eta: 0:25:41 lr: 6.839839465805414e-07 loss: 0.0315 (0.0314) time: 3.4310 data: 0.0085 max mem: 33370 +Epoch: [39] [ 880/1319] eta: 0:25:06 lr: 6.702277349898191e-07 loss: 0.0284 (0.0314) time: 3.4479 data: 0.0084 max mem: 33370 +Epoch: [39] [ 890/1319] eta: 0:24:32 lr: 6.564400777713066e-07 loss: 0.0311 (0.0314) time: 3.4293 data: 0.0083 max mem: 33370 +Epoch: [39] [ 900/1319] eta: 0:23:58 lr: 6.426201656523381e-07 loss: 0.0335 (0.0315) time: 3.4231 data: 0.0088 max mem: 33370 +Epoch: [39] [ 910/1319] eta: 0:23:23 lr: 6.287671486431178e-07 loss: 0.0294 (0.0315) time: 3.4187 data: 0.0089 max mem: 33370 +Epoch: [39] [ 920/1319] eta: 0:22:49 lr: 6.148801329380617e-07 loss: 0.0311 (0.0315) time: 3.4086 data: 0.0088 max mem: 33370 +Epoch: [39] [ 930/1319] eta: 0:22:14 lr: 6.009581774973726e-07 loss: 0.0287 (0.0315) time: 3.4283 data: 0.0087 max mem: 33370 +Epoch: [39] [ 940/1319] eta: 0:21:40 lr: 5.870002902666957e-07 loss: 0.0287 (0.0315) time: 3.4327 data: 0.0087 max mem: 33370 +Epoch: [39] [ 950/1319] eta: 0:21:06 lr: 5.7300542398606e-07 loss: 0.0290 (0.0315) time: 3.4215 data: 0.0086 max mem: 33370 +Epoch: [39] [ 960/1319] eta: 0:20:32 lr: 5.589724715308914e-07 loss: 0.0289 (0.0315) time: 3.4371 data: 0.0086 max mem: 33370 +Epoch: [39] [ 970/1319] eta: 0:19:57 lr: 5.449002607184345e-07 loss: 0.0289 (0.0315) time: 3.4537 data: 0.0086 max mem: 33370 +Epoch: [39] [ 980/1319] eta: 0:19:23 lr: 5.307875485010082e-07 loss: 0.0312 (0.0315) time: 3.4279 data: 0.0084 max mem: 33370 +Epoch: [39] [ 990/1319] eta: 0:18:48 lr: 5.166330144533874e-07 loss: 0.0328 (0.0315) time: 3.3960 data: 0.0083 max mem: 33370 +Epoch: [39] [1000/1319] eta: 0:18:14 lr: 5.024352534442401e-07 loss: 0.0301 (0.0315) time: 3.3916 data: 0.0083 max mem: 33370 +Epoch: [39] [1010/1319] eta: 0:17:40 lr: 4.881927673605746e-07 loss: 0.0286 (0.0315) time: 3.4208 data: 0.0090 max mem: 33370 +Epoch: [39] [1020/1319] eta: 0:17:05 lr: 4.7390395572780197e-07 loss: 0.0269 (0.0315) time: 3.4356 data: 0.0090 max mem: 33370 +Epoch: [39] [1030/1319] eta: 0:16:31 lr: 4.595671050360423e-07 loss: 0.0297 (0.0315) time: 3.4556 data: 0.0087 max mem: 33370 +Epoch: [39] [1040/1319] eta: 0:15:57 lr: 4.4518037654287396e-07 loss: 0.0298 (0.0314) time: 3.4630 data: 0.0087 max mem: 33370 +Epoch: [39] [1050/1319] eta: 0:15:23 lr: 4.3074179227215756e-07 loss: 0.0291 (0.0314) time: 3.4526 data: 0.0085 max mem: 33370 +Epoch: [39] [1060/1319] eta: 0:14:48 lr: 4.162492188647174e-07 loss: 0.0293 (0.0314) time: 3.4571 data: 0.0082 max mem: 33370 +Epoch: [39] [1070/1319] eta: 0:14:14 lr: 4.01700348854669e-07 loss: 0.0286 (0.0314) time: 3.4331 data: 0.0079 max mem: 33370 +Epoch: [39] [1080/1319] eta: 0:13:40 lr: 3.8709267884030336e-07 loss: 0.0268 (0.0314) time: 3.4027 data: 0.0081 max mem: 33370 +Epoch: [39] [1090/1319] eta: 0:13:05 lr: 3.724234838815835e-07 loss: 0.0289 (0.0314) time: 3.4190 data: 0.0082 max mem: 33370 +Epoch: [39] [1100/1319] eta: 0:12:31 lr: 3.5768978727688177e-07 loss: 0.0312 (0.0314) time: 3.4482 data: 0.0079 max mem: 33370 +Epoch: [39] [1110/1319] eta: 0:11:57 lr: 3.428883246336122e-07 loss: 0.0316 (0.0314) time: 3.4298 data: 0.0079 max mem: 33370 +Epoch: [39] [1120/1319] eta: 0:11:22 lr: 3.280155008272766e-07 loss: 0.0279 (0.0314) time: 3.4390 data: 0.0081 max mem: 33370 +Epoch: [39] [1130/1319] eta: 0:10:48 lr: 3.1306733800860497e-07 loss: 0.0279 (0.0314) time: 3.4452 data: 0.0085 max mem: 33370 +Epoch: [39] [1140/1319] eta: 0:10:14 lr: 2.9803941221786203e-07 loss: 0.0286 (0.0314) time: 3.4207 data: 0.0083 max mem: 33370 +Epoch: [39] [1150/1319] eta: 0:09:39 lr: 2.829267753240405e-07 loss: 0.0294 (0.0314) time: 3.4261 data: 0.0080 max mem: 33370 +Epoch: [39] [1160/1319] eta: 0:09:05 lr: 2.677238578071334e-07 loss: 0.0265 (0.0314) time: 3.4236 data: 0.0081 max mem: 33370 +Epoch: [39] [1170/1319] eta: 0:08:31 lr: 2.524243461593822e-07 loss: 0.0255 (0.0314) time: 3.4276 data: 0.0080 max mem: 33370 +Epoch: [39] [1180/1319] eta: 0:07:57 lr: 2.370210260957732e-07 loss: 0.0267 (0.0314) time: 3.4304 data: 0.0081 max mem: 33370 +Epoch: [39] [1190/1319] eta: 0:07:22 lr: 2.2150557883672493e-07 loss: 0.0286 (0.0313) time: 3.4131 data: 0.0080 max mem: 33370 +Epoch: [39] [1200/1319] eta: 0:06:48 lr: 2.058683115970694e-07 loss: 0.0259 (0.0313) time: 3.4369 data: 0.0082 max mem: 33370 +Epoch: [39] [1210/1319] eta: 0:06:14 lr: 1.9009779355624344e-07 loss: 0.0278 (0.0313) time: 3.4589 data: 0.0085 max mem: 33370 +Epoch: [39] [1220/1319] eta: 0:05:39 lr: 1.7418035215766808e-07 loss: 0.0281 (0.0313) time: 3.4099 data: 0.0087 max mem: 33370 +Epoch: [39] [1230/1319] eta: 0:05:05 lr: 1.5809935607220197e-07 loss: 0.0275 (0.0312) time: 3.3924 data: 0.0086 max mem: 33370 +Epoch: [39] [1240/1319] eta: 0:04:31 lr: 1.4183415922236583e-07 loss: 0.0299 (0.0312) time: 3.3853 data: 0.0081 max mem: 33370 +Epoch: [39] [1250/1319] eta: 0:03:56 lr: 1.2535848000328487e-07 loss: 0.0316 (0.0312) time: 3.4243 data: 0.0080 max mem: 33370 +Epoch: [39] [1260/1319] eta: 0:03:22 lr: 1.0863778202227116e-07 loss: 0.0299 (0.0312) time: 3.4527 data: 0.0083 max mem: 33370 +Epoch: [39] [1270/1319] eta: 0:02:48 lr: 9.162475150165058e-08 loss: 0.0299 (0.0312) time: 3.4404 data: 0.0086 max mem: 33370 +Epoch: [39] [1280/1319] eta: 0:02:13 lr: 7.425076510067331e-08 loss: 0.0289 (0.0312) time: 3.4443 data: 0.0090 max mem: 33370 +Epoch: [39] [1290/1319] eta: 0:01:39 lr: 5.640763927216541e-08 loss: 0.0297 (0.0312) time: 3.4446 data: 0.0085 max mem: 33370 +Epoch: [39] [1300/1319] eta: 0:01:05 lr: 3.790015191412361e-08 loss: 0.0298 (0.0312) time: 3.4480 data: 0.0079 max mem: 33370 +Epoch: [39] [1310/1319] eta: 0:00:30 lr: 1.8267397722216235e-08 loss: 0.0286 (0.0312) time: 3.4412 data: 0.0079 max mem: 33370 +Epoch: [39] Total time: 1:15:27 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 2:33:08 time: 3.5710 data: 3.4777 max mem: 33370 +Test: [ 100/2573] eta: 0:04:36 time: 0.0769 data: 0.0015 max mem: 33370 +Test: [ 200/2573] eta: 0:03:47 time: 0.0790 data: 0.0014 max mem: 33370 +Test: [ 300/2573] eta: 0:03:24 time: 0.0814 data: 0.0014 max mem: 33370 +Test: [ 400/2573] eta: 0:03:09 time: 0.0821 data: 0.0016 max mem: 33370 +Test: [ 500/2573] eta: 0:02:58 time: 0.0804 data: 0.0015 max mem: 33370 +Test: [ 600/2573] eta: 0:02:48 time: 0.0810 data: 0.0016 max mem: 33370 +Test: [ 700/2573] eta: 0:02:38 time: 0.0803 data: 0.0015 max mem: 33370 +Test: [ 800/2573] eta: 0:02:29 time: 0.0832 data: 0.0014 max mem: 33370 +Test: [ 900/2573] eta: 0:02:20 time: 0.0810 data: 0.0016 max mem: 33370 +Test: [1000/2573] eta: 0:02:11 time: 0.0808 data: 0.0015 max mem: 33370 +Test: [1100/2573] eta: 0:02:02 time: 0.0799 data: 0.0015 max mem: 33370 +Test: [1200/2573] eta: 0:01:54 time: 0.0799 data: 0.0014 max mem: 33370 +Test: [1300/2573] eta: 0:01:45 time: 0.0808 data: 0.0014 max mem: 33370 +Test: [1400/2573] eta: 0:01:37 time: 0.0790 data: 0.0014 max mem: 33370 +Test: [1500/2573] eta: 0:01:28 time: 0.0807 data: 0.0015 max mem: 33370 +Test: [1600/2573] eta: 0:01:20 time: 0.0844 data: 0.0014 max mem: 33370 +Test: [1700/2573] eta: 0:01:12 time: 0.0784 data: 0.0014 max mem: 33370 +Test: [1800/2573] eta: 0:01:03 time: 0.0820 data: 0.0014 max mem: 33370 +Test: [1900/2573] eta: 0:00:55 time: 0.0788 data: 0.0014 max mem: 33370 +Test: [2000/2573] eta: 0:00:47 time: 0.0807 data: 0.0014 max mem: 33370 +Test: [2100/2573] eta: 0:00:38 time: 0.0828 data: 0.0014 max mem: 33370 +Test: [2200/2573] eta: 0:00:30 time: 0.0824 data: 0.0013 max mem: 33370 +Test: [2300/2573] eta: 0:00:22 time: 0.0818 data: 0.0015 max mem: 33370 +Test: [2400/2573] eta: 0:00:14 time: 0.0773 data: 0.0015 max mem: 33370 +Test: [2500/2573] eta: 0:00:05 time: 0.0801 data: 0.0014 max mem: 33370 +Test: Total time: 0:03:30 +Final results: +Mean IoU is 64.96 + + precision@0.5 = 72.90 + precision@0.6 = 67.73 + precision@0.7 = 61.09 + precision@0.8 = 50.71 + precision@0.9 = 25.82 + overall IoU = 62.17 + +Average object IoU 64.95859999740912 +Overall IoU 62.17071533203125 +Training time 2 days, 4:18:11 diff --git a/LAVT-RIS/logs/gref_m10_tmp005_4gpu_bs32_orig.log b/LAVT-RIS/logs/gref_m10_tmp005_4gpu_bs32_orig.log new file mode 100644 index 0000000000000000000000000000000000000000..ba0de2643e6c7ea0384406322248da67ede1de95 --- /dev/null +++ b/LAVT-RIS/logs/gref_m10_tmp005_4gpu_bs32_orig.log @@ -0,0 +1,12093 @@ +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torch/distributed/launch.py:178: FutureWarning: The module torch.distributed.launch is deprecated +and will be removed in future. Use torchrun. +Note that --use_env is set by default in torchrun. +If your script expects `--local_rank` argument to be set, please +change it to read from `os.environ['LOCAL_RANK']` instead. See +https://pytorch.org/docs/stable/distributed.html#launch-utility for +further instructions + + warnings.warn( +WARNING:torch.distributed.run: +***************************************** +Setting OMP_NUM_THREADS environment variable for each process to be 1 in default, to avoid your system being overloaded, please further tune the variable for optimal performance in your application as needed. +***************************************** +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/timm/models/layers/__init__.py:48: FutureWarning: Importing from timm.models.layers is deprecated, please import via timm.layers + warnings.warn(f"Importing from {__name__} is deprecated, please import via timm.layers", FutureWarning) +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/timm/models/layers/__init__.py:48: FutureWarning: Importing from timm.models.layers is deprecated, please import via timm.layers + warnings.warn(f"Importing from {__name__} is deprecated, please import via timm.layers", FutureWarning) +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/timm/models/layers/__init__.py:48: FutureWarning: Importing from timm.models.layers is deprecated, please import via timm.layers + warnings.warn(f"Importing from {__name__} is deprecated, please import via timm.layers", FutureWarning) +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/timm/models/layers/__init__.py:48: FutureWarning: Importing from timm.models.layers is deprecated, please import via timm.layers + warnings.warn(f"Importing from {__name__} is deprecated, please import via timm.layers", FutureWarning) +RANK and WORLD_SIZE in environment: 2/4 +RANK and WORLD_SIZE in environment: 0/4 +RANK and WORLD_SIZE in environment: 1/4 +RANK and WORLD_SIZE in environment: 3/4 +Image size: 480 +loading dataset refcocog into memory... +creating index... +index created. +DONE (t=5.46s) +loading dataset refcocog into memory... +creating index... +index created. +DONE (t=5.18s) +local rank 0 / global rank 0 successfully built train dataset. +lavt_one +Window size 12! +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torch/functional.py:478: UserWarning: torch.meshgrid: in an upcoming release, it will be required to pass the indexing argument. (Triggered internally at ../aten/src/ATen/native/TensorShape.cpp:2894.) + return _VF.meshgrid(tensors, **kwargs) # type: ignore[attr-defined] +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torch/functional.py:478: UserWarning: torch.meshgrid: in an upcoming release, it will be required to pass the indexing argument. (Triggered internally at ../aten/src/ATen/native/TensorShape.cpp:2894.) + return _VF.meshgrid(tensors, **kwargs) # type: ignore[attr-defined] +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torch/functional.py:478: UserWarning: torch.meshgrid: in an upcoming release, it will be required to pass the indexing argument. (Triggered internally at ../aten/src/ATen/native/TensorShape.cpp:2894.) + return _VF.meshgrid(tensors, **kwargs) # type: ignore[attr-defined] +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torch/functional.py:478: UserWarning: torch.meshgrid: in an upcoming release, it will be required to pass the indexing argument. (Triggered internally at ../aten/src/ATen/native/TensorShape.cpp:2894.) + return _VF.meshgrid(tensors, **kwargs) # type: ignore[attr-defined] +Initializing Multi-modal Swin Transformer weights from ./pretrained_weights/swin_base_patch4_window12_384_22k.pth +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [0] [ 0/1319] eta: 3:18:06 lr: 4.9999147080313756e-05 loss: 0.6065 (0.6065) time: 9.0120 data: 3.6431 max mem: 20156 +Epoch: [0] [ 10/1319] eta: 1:08:44 lr: 4.999061779453083e-05 loss: 0.3894 (0.4026) time: 3.1509 data: 0.3374 max mem: 26588 +Epoch: [0] [ 20/1319] eta: 1:02:37 lr: 4.9982088347050674e-05 loss: 0.3290 (0.3689) time: 2.5869 data: 0.0063 max mem: 28287 +Epoch: [0] [ 30/1319] eta: 1:00:20 lr: 4.9973558737839576e-05 loss: 0.3087 (0.3460) time: 2.6201 data: 0.0058 max mem: 28287 +Epoch: [0] [ 40/1319] eta: 0:59:05 lr: 4.9965028966863786e-05 loss: 0.2771 (0.3312) time: 2.6448 data: 0.0060 max mem: 28287 +Epoch: [0] [ 50/1319] eta: 0:58:09 lr: 4.995649903408956e-05 loss: 0.2744 (0.3240) time: 2.6590 data: 0.0058 max mem: 28287 +Epoch: [0] [ 60/1319] eta: 0:57:12 lr: 4.9947968939483133e-05 loss: 0.2933 (0.3268) time: 2.6327 data: 0.0057 max mem: 28287 +Epoch: [0] [ 70/1319] eta: 0:56:26 lr: 4.993943868301072e-05 loss: 0.2933 (0.3191) time: 2.6133 data: 0.0057 max mem: 29995 +Epoch: [0] [ 80/1319] eta: 0:55:43 lr: 4.993090826463852e-05 loss: 0.2588 (0.3103) time: 2.6126 data: 0.0058 max mem: 29995 +Epoch: [0] [ 90/1319] eta: 0:55:10 lr: 4.9922377684332736e-05 loss: 0.2521 (0.3049) time: 2.6296 data: 0.0057 max mem: 29995 +Epoch: [0] [ 100/1319] eta: 0:54:35 lr: 4.991384694205954e-05 loss: 0.2432 (0.3006) time: 2.6433 data: 0.0058 max mem: 29995 +Epoch: [0] [ 110/1319] eta: 0:53:58 lr: 4.990531603778512e-05 loss: 0.2870 (0.3024) time: 2.6103 data: 0.0057 max mem: 29995 +Epoch: [0] [ 120/1319] eta: 0:53:26 lr: 4.98967849714756e-05 loss: 0.2814 (0.2990) time: 2.6110 data: 0.0056 max mem: 31677 +Epoch: [0] [ 130/1319] eta: 0:52:56 lr: 4.988825374309713e-05 loss: 0.2404 (0.2960) time: 2.6312 data: 0.0057 max mem: 31677 +Epoch: [0] [ 140/1319] eta: 0:52:25 lr: 4.987972235261584e-05 loss: 0.2571 (0.2927) time: 2.6242 data: 0.0058 max mem: 31677 +Epoch: [0] [ 150/1319] eta: 0:51:55 lr: 4.987119079999784e-05 loss: 0.2369 (0.2920) time: 2.6269 data: 0.0057 max mem: 31677 +Epoch: [0] [ 160/1319] eta: 0:51:20 lr: 4.986265908520923e-05 loss: 0.2369 (0.2888) time: 2.5909 data: 0.0057 max mem: 31677 +Epoch: [0] [ 170/1319] eta: 0:50:48 lr: 4.985412720821609e-05 loss: 0.2362 (0.2883) time: 2.5639 data: 0.0056 max mem: 31677 +Epoch: [0] [ 180/1319] eta: 0:50:19 lr: 4.984559516898449e-05 loss: 0.2409 (0.2849) time: 2.5962 data: 0.0057 max mem: 31677 +Epoch: [0] [ 190/1319] eta: 0:49:51 lr: 4.98370629674805e-05 loss: 0.2409 (0.2833) time: 2.6203 data: 0.0058 max mem: 31677 +Epoch: [0] [ 200/1319] eta: 0:49:23 lr: 4.982853060367015e-05 loss: 0.2419 (0.2816) time: 2.6229 data: 0.0057 max mem: 31677 +Epoch: [0] [ 210/1319] eta: 0:48:57 lr: 4.9819998077519475e-05 loss: 0.2333 (0.2808) time: 2.6336 data: 0.0058 max mem: 31677 +Epoch: [0] [ 220/1319] eta: 0:48:28 lr: 4.98114653889945e-05 loss: 0.2237 (0.2783) time: 2.6297 data: 0.0059 max mem: 31677 +Epoch: [0] [ 230/1319] eta: 0:48:01 lr: 4.980293253806122e-05 loss: 0.2300 (0.2769) time: 2.6153 data: 0.0058 max mem: 31677 +Epoch: [0] [ 240/1319] eta: 0:47:31 lr: 4.9794399524685624e-05 loss: 0.2329 (0.2759) time: 2.5970 data: 0.0057 max mem: 31677 +Epoch: [0] [ 250/1319] eta: 0:47:04 lr: 4.97858663488337e-05 loss: 0.2354 (0.2741) time: 2.6002 data: 0.0058 max mem: 31677 +Epoch: [0] [ 260/1319] eta: 0:46:36 lr: 4.977733301047139e-05 loss: 0.2333 (0.2718) time: 2.6192 data: 0.0058 max mem: 31677 +Epoch: [0] [ 270/1319] eta: 0:46:10 lr: 4.9768799509564675e-05 loss: 0.2342 (0.2715) time: 2.6245 data: 0.0057 max mem: 31677 +Epoch: [0] [ 280/1319] eta: 0:45:43 lr: 4.976026584607946e-05 loss: 0.2316 (0.2699) time: 2.6343 data: 0.0058 max mem: 31677 +Epoch: [0] [ 290/1319] eta: 0:45:16 lr: 4.9751732019981684e-05 loss: 0.2316 (0.2696) time: 2.6313 data: 0.0060 max mem: 31677 +Epoch: [0] [ 300/1319] eta: 0:44:50 lr: 4.974319803123725e-05 loss: 0.2483 (0.2695) time: 2.6334 data: 0.0058 max mem: 31677 +Epoch: [0] [ 310/1319] eta: 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mem: 31677 +Epoch: [0] [ 550/1319] eta: 0:33:43 lr: 4.952979535246434e-05 loss: 0.2123 (0.2503) time: 2.6279 data: 0.0060 max mem: 31677 +Epoch: [0] [ 560/1319] eta: 0:33:16 lr: 4.952125712289576e-05 loss: 0.2123 (0.2499) time: 2.6260 data: 0.0058 max mem: 31677 +Epoch: [0] [ 570/1319] eta: 0:32:50 lr: 4.9512718729754866e-05 loss: 0.2204 (0.2498) time: 2.6470 data: 0.0056 max mem: 31677 +Epoch: [0] [ 580/1319] eta: 0:32:24 lr: 4.9504180173007175e-05 loss: 0.2355 (0.2496) time: 2.6394 data: 0.0057 max mem: 31677 +Epoch: [0] [ 590/1319] eta: 0:31:58 lr: 4.9495641452618194e-05 loss: 0.2222 (0.2492) time: 2.6177 data: 0.0059 max mem: 31677 +Epoch: [0] [ 600/1319] eta: 0:31:31 lr: 4.948710256855343e-05 loss: 0.2009 (0.2485) time: 2.6428 data: 0.0058 max mem: 31677 +Epoch: [0] [ 610/1319] eta: 0:31:05 lr: 4.9478563520778356e-05 loss: 0.2578 (0.2495) time: 2.6412 data: 0.0057 max mem: 31677 +Epoch: [0] [ 620/1319] eta: 0:30:39 lr: 4.947002430925844e-05 loss: 0.2621 (0.2497) time: 2.6209 data: 0.0057 max mem: 31677 +Epoch: [0] [ 630/1319] eta: 0:30:12 lr: 4.946148493395914e-05 loss: 0.2492 (0.2496) time: 2.6287 data: 0.0057 max mem: 31677 +Epoch: [0] [ 640/1319] eta: 0:29:46 lr: 4.945294539484589e-05 loss: 0.2206 (0.2491) time: 2.6382 data: 0.0058 max mem: 31677 +Epoch: [0] [ 650/1319] eta: 0:29:20 lr: 4.944440569188412e-05 loss: 0.2080 (0.2484) time: 2.6372 data: 0.0058 max mem: 31677 +Epoch: [0] [ 660/1319] eta: 0:28:54 lr: 4.943586582503924e-05 loss: 0.2080 (0.2484) time: 2.6367 data: 0.0058 max mem: 31677 +Epoch: [0] [ 670/1319] eta: 0:28:27 lr: 4.942732579427665e-05 loss: 0.2385 (0.2482) time: 2.6218 data: 0.0059 max mem: 31677 +Epoch: [0] [ 680/1319] eta: 0:28:00 lr: 4.941878559956172e-05 loss: 0.2197 (0.2475) time: 2.5895 data: 0.0058 max mem: 31677 +Epoch: [0] [ 690/1319] eta: 0:27:33 lr: 4.941024524085985e-05 loss: 0.1924 (0.2473) time: 2.5735 data: 0.0056 max mem: 31677 +Epoch: [0] [ 700/1319] eta: 0:27:07 lr: 4.940170471813637e-05 loss: 0.1927 (0.2470) time: 2.5898 data: 0.0059 max mem: 31677 +Epoch: [0] [ 710/1319] eta: 0:26:40 lr: 4.939316403135663e-05 loss: 0.2061 (0.2468) time: 2.6063 data: 0.0059 max mem: 31677 +Epoch: [0] [ 720/1319] eta: 0:26:14 lr: 4.938462318048596e-05 loss: 0.2179 (0.2464) time: 2.6200 data: 0.0057 max mem: 31677 +Epoch: [0] [ 730/1319] eta: 0:25:48 lr: 4.937608216548967e-05 loss: 0.1886 (0.2457) time: 2.6236 data: 0.0057 max mem: 31677 +Epoch: [0] [ 740/1319] eta: 0:25:22 lr: 4.936754098633307e-05 loss: 0.1886 (0.2456) time: 2.6366 data: 0.0059 max mem: 31677 +Epoch: [0] [ 750/1319] eta: 0:24:56 lr: 4.935899964298143e-05 loss: 0.1815 (0.2447) time: 2.6476 data: 0.0057 max mem: 31677 +Epoch: [0] [ 760/1319] eta: 0:24:29 lr: 4.9350458135400046e-05 loss: 0.1804 (0.2441) time: 2.6130 data: 0.0056 max mem: 31677 +Epoch: [0] [ 770/1319] eta: 0:24:02 lr: 4.934191646355415e-05 loss: 0.2006 (0.2440) time: 2.5968 data: 0.0058 max mem: 31677 +Epoch: [0] [ 780/1319] eta: 0:23:36 lr: 4.9333374627409e-05 loss: 0.2025 (0.2436) time: 2.6035 data: 0.0058 max mem: 31677 +Epoch: [0] [ 790/1319] eta: 0:23:10 lr: 4.932483262692982e-05 loss: 0.2095 (0.2431) time: 2.6070 data: 0.0059 max mem: 31677 +Epoch: [0] [ 800/1319] eta: 0:22:43 lr: 4.931629046208183e-05 loss: 0.1990 (0.2427) time: 2.6195 data: 0.0060 max mem: 31677 +Epoch: [0] [ 810/1319] eta: 0:22:17 lr: 4.9307748132830237e-05 loss: 0.1993 (0.2424) time: 2.6179 data: 0.0059 max mem: 31677 +Epoch: [0] [ 820/1319] eta: 0:21:51 lr: 4.929920563914022e-05 loss: 0.2116 (0.2421) time: 2.6270 data: 0.0056 max mem: 31677 +Epoch: [0] [ 830/1319] eta: 0:21:24 lr: 4.929066298097696e-05 loss: 0.2021 (0.2419) time: 2.6149 data: 0.0056 max mem: 31677 +Epoch: [0] [ 840/1319] eta: 0:20:58 lr: 4.928212015830561e-05 loss: 0.1908 (0.2413) time: 2.6097 data: 0.0058 max mem: 31677 +Epoch: [0] [ 850/1319] eta: 0:20:32 lr: 4.927357717109131e-05 loss: 0.2055 (0.2411) time: 2.6388 data: 0.0058 max mem: 31677 +Epoch: [0] [ 860/1319] eta: 0:20:05 lr: 4.926503401929921e-05 loss: 0.2055 (0.2409) time: 2.6082 data: 0.0058 max mem: 31677 +Epoch: [0] [ 870/1319] eta: 0:19:39 lr: 4.925649070289441e-05 loss: 0.2218 (0.2407) time: 2.5857 data: 0.0059 max mem: 31677 +Epoch: [0] [ 880/1319] eta: 0:19:12 lr: 4.9247947221842024e-05 loss: 0.2196 (0.2405) time: 2.6021 data: 0.0059 max mem: 31677 +Epoch: [0] [ 890/1319] eta: 0:18:46 lr: 4.923940357610714e-05 loss: 0.1953 (0.2399) time: 2.5971 data: 0.0057 max mem: 31677 +Epoch: [0] [ 900/1319] eta: 0:18:20 lr: 4.9230859765654824e-05 loss: 0.1872 (0.2395) time: 2.6172 data: 0.0057 max mem: 31677 +Epoch: [0] [ 910/1319] eta: 0:17:54 lr: 4.922231579045014e-05 loss: 0.1807 (0.2388) time: 2.6270 data: 0.0057 max mem: 31677 +Epoch: [0] [ 920/1319] eta: 0:17:27 lr: 4.921377165045815e-05 loss: 0.1923 (0.2385) time: 2.6296 data: 0.0056 max mem: 31677 +Epoch: [0] [ 930/1319] eta: 0:17:01 lr: 4.9205227345643864e-05 loss: 0.2043 (0.2382) time: 2.6224 data: 0.0056 max mem: 31677 +Epoch: [0] [ 940/1319] eta: 0:16:35 lr: 4.919668287597232e-05 loss: 0.2136 (0.2384) time: 2.6119 data: 0.0056 max mem: 31677 +Epoch: [0] [ 950/1319] eta: 0:16:08 lr: 4.918813824140851e-05 loss: 0.2090 (0.2380) time: 2.6098 data: 0.0057 max mem: 31677 +Epoch: [0] [ 960/1319] eta: 0:15:42 lr: 4.9179593441917424e-05 loss: 0.2018 (0.2376) time: 2.5984 data: 0.0058 max mem: 31677 +Epoch: [0] [ 970/1319] eta: 0:15:16 lr: 4.917104847746404e-05 loss: 0.1955 (0.2372) time: 2.6248 data: 0.0057 max mem: 31677 +Epoch: [0] [ 980/1319] eta: 0:14:49 lr: 4.916250334801333e-05 loss: 0.1955 (0.2368) time: 2.6278 data: 0.0057 max mem: 31677 +Epoch: [0] [ 990/1319] eta: 0:14:23 lr: 4.915395805353022e-05 loss: 0.1900 (0.2363) time: 2.6160 data: 0.0057 max mem: 31677 +Epoch: [0] [1000/1319] eta: 0:13:57 lr: 4.9145412593979664e-05 loss: 0.1909 (0.2360) time: 2.6432 data: 0.0057 max mem: 31677 +Epoch: [0] [1010/1319] eta: 0:13:31 lr: 4.913686696932656e-05 loss: 0.1913 (0.2356) time: 2.6368 data: 0.0057 max mem: 31677 +Epoch: [0] [1020/1319] eta: 0:13:05 lr: 4.9128321179535836e-05 loss: 0.1876 (0.2352) time: 2.6334 data: 0.0056 max mem: 31677 +Epoch: [0] [1030/1319] eta: 0:12:38 lr: 4.911977522457237e-05 loss: 0.1931 (0.2351) time: 2.6389 data: 0.0057 max mem: 31677 +Epoch: [0] [1040/1319] eta: 0:12:12 lr: 4.9111229104401044e-05 loss: 0.2044 (0.2350) time: 2.6161 data: 0.0058 max mem: 31677 +Epoch: [0] [1050/1319] eta: 0:11:46 lr: 4.910268281898671e-05 loss: 0.1934 (0.2349) time: 2.6242 data: 0.0055 max mem: 31677 +Epoch: [0] [1060/1319] eta: 0:11:20 lr: 4.9094136368294215e-05 loss: 0.2138 (0.2347) time: 2.6341 data: 0.0055 max mem: 31677 +Epoch: [0] [1070/1319] eta: 0:10:53 lr: 4.90855897522884e-05 loss: 0.2138 (0.2346) time: 2.6050 data: 0.0055 max mem: 31677 +Epoch: [0] [1080/1319] eta: 0:10:27 lr: 4.907704297093409e-05 loss: 0.1876 (0.2340) time: 2.5820 data: 0.0057 max mem: 31677 +Epoch: [0] [1090/1319] eta: 0:10:01 lr: 4.906849602419608e-05 loss: 0.1784 (0.2339) time: 2.5988 data: 0.0058 max mem: 31677 +Epoch: [0] [1100/1319] eta: 0:09:34 lr: 4.905994891203916e-05 loss: 0.2064 (0.2338) time: 2.6109 data: 0.0056 max mem: 31677 +Epoch: [0] [1110/1319] eta: 0:09:08 lr: 4.905140163442811e-05 loss: 0.2064 (0.2334) time: 2.6014 data: 0.0057 max mem: 31677 +Epoch: [0] [1120/1319] eta: 0:08:42 lr: 4.904285419132769e-05 loss: 0.1796 (0.2331) time: 2.6129 data: 0.0057 max mem: 31677 +Epoch: [0] [1130/1319] eta: 0:08:16 lr: 4.903430658270266e-05 loss: 0.1824 (0.2328) time: 2.6179 data: 0.0056 max mem: 31677 +Epoch: [0] [1140/1319] eta: 0:07:49 lr: 4.902575880851773e-05 loss: 0.1837 (0.2324) time: 2.6044 data: 0.0056 max mem: 31677 +Epoch: [0] [1150/1319] eta: 0:07:23 lr: 4.9017210868737634e-05 loss: 0.1630 (0.2319) time: 2.6275 data: 0.0056 max mem: 31677 +Epoch: [0] [1160/1319] eta: 0:06:57 lr: 4.900866276332707e-05 loss: 0.1680 (0.2316) time: 2.6457 data: 0.0055 max mem: 31677 +Epoch: [0] [1170/1319] eta: 0:06:31 lr: 4.9000114492250734e-05 loss: 0.1750 (0.2313) time: 2.6372 data: 0.0055 max mem: 31677 +Epoch: [0] [1180/1319] eta: 0:06:04 lr: 4.8991566055473306e-05 loss: 0.1750 (0.2308) time: 2.6340 data: 0.0056 max mem: 31677 +Epoch: [0] [1190/1319] eta: 0:05:38 lr: 4.8983017452959435e-05 loss: 0.1701 (0.2304) time: 2.6207 data: 0.0058 max mem: 31677 +Epoch: [0] [1200/1319] eta: 0:05:12 lr: 4.8974468684673776e-05 loss: 0.1884 (0.2303) time: 2.5992 data: 0.0058 max mem: 31677 +Epoch: [0] [1210/1319] eta: 0:04:46 lr: 4.896591975058095e-05 loss: 0.2025 (0.2300) time: 2.5976 data: 0.0057 max mem: 31677 +Epoch: [0] [1220/1319] eta: 0:04:19 lr: 4.89573706506456e-05 loss: 0.1867 (0.2297) time: 2.6315 data: 0.0057 max mem: 31677 +Epoch: [0] [1230/1319] eta: 0:03:53 lr: 4.89488213848323e-05 loss: 0.1867 (0.2296) time: 2.6556 data: 0.0057 max mem: 31677 +Epoch: [0] [1240/1319] eta: 0:03:27 lr: 4.894027195310566e-05 loss: 0.1868 (0.2293) time: 2.6248 data: 0.0057 max mem: 31677 +Epoch: [0] [1250/1319] eta: 0:03:01 lr: 4.893172235543025e-05 loss: 0.1810 (0.2291) time: 2.6020 data: 0.0057 max mem: 31677 +Epoch: [0] [1260/1319] eta: 0:02:34 lr: 4.892317259177062e-05 loss: 0.1857 (0.2290) time: 2.6144 data: 0.0057 max mem: 31677 +Epoch: [0] [1270/1319] eta: 0:02:08 lr: 4.8914622662091334e-05 loss: 0.2061 (0.2289) time: 2.6048 data: 0.0057 max mem: 31677 +Epoch: [0] [1280/1319] eta: 0:01:42 lr: 4.890607256635692e-05 loss: 0.1978 (0.2286) time: 2.5956 data: 0.0059 max mem: 31677 +Epoch: [0] [1290/1319] eta: 0:01:16 lr: 4.8897522304531876e-05 loss: 0.1908 (0.2283) time: 2.6129 data: 0.0059 max mem: 31677 +Epoch: [0] [1300/1319] eta: 0:00:49 lr: 4.888897187658072e-05 loss: 0.1857 (0.2280) time: 2.6108 data: 0.0056 max mem: 31677 +Epoch: [0] [1310/1319] eta: 0:00:23 lr: 4.888042128246795e-05 loss: 0.1857 (0.2278) time: 2.6138 data: 0.0055 max mem: 31677 +Epoch: [0] Total time: 0:57:40 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 2:00:39 time: 2.8136 data: 2.7339 max mem: 31677 +Test: [ 100/2573] eta: 0:04:04 time: 0.0717 data: 0.0011 max mem: 31677 +Test: [ 200/2573] eta: 0:03:25 time: 0.0728 data: 0.0011 max mem: 31677 +Test: [ 300/2573] eta: 0:03:05 time: 0.0744 data: 0.0011 max mem: 31677 +Test: [ 400/2573] eta: 0:02:52 time: 0.0746 data: 0.0011 max mem: 31677 +Test: [ 500/2573] eta: 0:02:41 time: 0.0733 data: 0.0011 max mem: 31677 +Test: [ 600/2573] eta: 0:02:32 time: 0.0733 data: 0.0011 max mem: 31677 +Test: [ 700/2573] eta: 0:02:24 time: 0.0734 data: 0.0011 max mem: 31677 +Test: [ 800/2573] eta: 0:02:16 time: 0.0767 data: 0.0011 max mem: 31677 +Test: [ 900/2573] eta: 0:02:08 time: 0.0733 data: 0.0011 max mem: 31677 +Test: [1000/2573] eta: 0:01:59 time: 0.0734 data: 0.0011 max mem: 31677 +Test: [1100/2573] eta: 0:01:51 time: 0.0735 data: 0.0011 max mem: 31677 +Test: [1200/2573] eta: 0:01:44 time: 0.0736 data: 0.0011 max mem: 31677 +Test: [1300/2573] eta: 0:01:36 time: 0.0734 data: 0.0011 max mem: 31677 +Test: [1400/2573] eta: 0:01:28 time: 0.0718 data: 0.0011 max mem: 31677 +Test: [1500/2573] eta: 0:01:20 time: 0.0734 data: 0.0011 max mem: 31677 +Test: [1600/2573] eta: 0:01:13 time: 0.0768 data: 0.0011 max mem: 31677 +Test: [1700/2573] eta: 0:01:05 time: 0.0719 data: 0.0011 max mem: 31677 +Test: [1800/2573] eta: 0:00:58 time: 0.0752 data: 0.0011 max mem: 31677 +Test: [1900/2573] eta: 0:00:50 time: 0.0719 data: 0.0011 max mem: 31677 +Test: [2000/2573] eta: 0:00:42 time: 0.0735 data: 0.0011 max mem: 31677 +Test: [2100/2573] eta: 0:00:35 time: 0.0752 data: 0.0011 max mem: 31677 +Test: [2200/2573] eta: 0:00:27 time: 0.0752 data: 0.0011 max mem: 31677 +Test: [2300/2573] eta: 0:00:20 time: 0.0752 data: 0.0011 max mem: 31677 +Test: [2400/2573] eta: 0:00:12 time: 0.0704 data: 0.0011 max mem: 31677 +Test: [2500/2573] eta: 0:00:05 time: 0.0735 data: 0.0011 max mem: 31677 +Test: Total time: 0:03:12 +Final results: +Mean IoU is 36.42 + + precision@0.5 = 34.11 + precision@0.6 = 24.33 + precision@0.7 = 15.73 + precision@0.8 = 8.58 + precision@0.9 = 1.61 + overall IoU = 39.92 + +Average object IoU 36.420715163071584 +Overall IoU 39.9150276184082 +Better epoch: 0 + +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [1] [ 0/1319] eta: 1:32:54 lr: 4.8872725605668895e-05 loss: 0.1861 (0.1861) time: 4.2260 data: 1.4622 max mem: 31677 +Epoch: [1] [ 10/1319] eta: 1:00:22 lr: 4.886417469575114e-05 loss: 0.2050 (0.1897) time: 2.7671 data: 0.1377 max mem: 31677 +Epoch: [1] [ 20/1319] eta: 0:58:30 lr: 4.88556236195687e-05 loss: 0.1949 (0.1785) time: 2.6266 data: 0.0052 max mem: 31677 +Epoch: [1] [ 30/1319] eta: 0:57:36 lr: 4.884707237708599e-05 loss: 0.1712 (0.1801) time: 2.6339 data: 0.0056 max mem: 31677 +Epoch: [1] [ 40/1319] eta: 0:56:34 lr: 4.883852096826744e-05 loss: 0.1836 (0.1855) time: 2.6030 data: 0.0060 max mem: 31677 +Epoch: [1] [ 50/1319] eta: 0:55:51 lr: 4.882996939307746e-05 loss: 0.1949 (0.1868) time: 2.5782 data: 0.0062 max mem: 31677 +Epoch: [1] [ 60/1319] eta: 0:55:26 lr: 4.882141765148041e-05 loss: 0.1986 (0.1882) time: 2.6184 data: 0.0063 max mem: 31677 +Epoch: [1] [ 70/1319] eta: 0:54:56 lr: 4.881286574344069e-05 loss: 0.1568 (0.1840) time: 2.6366 data: 0.0063 max mem: 31677 +Epoch: [1] [ 80/1319] eta: 0:54:26 lr: 4.8804313668922646e-05 loss: 0.1546 (0.1846) time: 2.6176 data: 0.0062 max mem: 31677 +Epoch: [1] [ 90/1319] eta: 0:53:50 lr: 4.879576142789063e-05 loss: 0.1479 (0.1831) time: 2.5899 data: 0.0061 max mem: 31677 +Epoch: [1] [ 100/1319] eta: 0:53:24 lr: 4.878720902030896e-05 loss: 0.1719 (0.1844) time: 2.6005 data: 0.0062 max mem: 31677 +Epoch: [1] [ 110/1319] eta: 0:52:56 lr: 4.877865644614197e-05 loss: 0.1745 (0.1831) time: 2.6237 data: 0.0060 max mem: 31677 +Epoch: [1] [ 120/1319] eta: 0:52:30 lr: 4.877010370535394e-05 loss: 0.1760 (0.1849) time: 2.6197 data: 0.0056 max mem: 31677 +Epoch: [1] [ 130/1319] eta: 0:52:06 lr: 4.8761550797909164e-05 loss: 0.1779 (0.1843) time: 2.6369 data: 0.0058 max mem: 31677 +Epoch: [1] [ 140/1319] eta: 0:51:38 lr: 4.875299772377192e-05 loss: 0.1674 (0.1841) time: 2.6282 data: 0.0061 max mem: 31677 +Epoch: [1] [ 150/1319] eta: 0:51:09 lr: 4.874444448290645e-05 loss: 0.1834 (0.1845) time: 2.6036 data: 0.0063 max mem: 31677 +Epoch: [1] [ 160/1319] eta: 0:50:41 lr: 4.873589107527701e-05 loss: 0.1801 (0.1837) time: 2.6019 data: 0.0061 max mem: 31677 +Epoch: [1] [ 170/1319] eta: 0:50:14 lr: 4.872733750084782e-05 loss: 0.1788 (0.1842) time: 2.6052 data: 0.0059 max mem: 31677 +Epoch: [1] [ 180/1319] eta: 0:49:46 lr: 4.871878375958309e-05 loss: 0.1812 (0.1848) time: 2.6055 data: 0.0059 max mem: 31677 +Epoch: [1] [ 190/1319] eta: 0:49:21 lr: 4.871022985144703e-05 loss: 0.1758 (0.1846) time: 2.6236 data: 0.0058 max mem: 31677 +Epoch: [1] [ 200/1319] eta: 0:48:56 lr: 4.870167577640381e-05 loss: 0.1876 (0.1861) time: 2.6370 data: 0.0060 max mem: 31677 +Epoch: [1] [ 210/1319] eta: 0:48:27 lr: 4.869312153441761e-05 loss: 0.1876 (0.1865) time: 2.6102 data: 0.0060 max mem: 31677 +Epoch: [1] [ 220/1319] eta: 0:47:59 lr: 4.868456712545258e-05 loss: 0.1732 (0.1871) time: 2.5860 data: 0.0058 max mem: 31677 +Epoch: [1] [ 230/1319] eta: 0:47:32 lr: 4.8676012549472854e-05 loss: 0.1732 (0.1864) time: 2.5911 data: 0.0058 max mem: 31677 +Epoch: [1] [ 240/1319] eta: 0:47:04 lr: 4.866745780644256e-05 loss: 0.1593 (0.1860) time: 2.5882 data: 0.0059 max mem: 31677 +Epoch: [1] [ 250/1319] eta: 0:46:38 lr: 4.865890289632581e-05 loss: 0.1790 (0.1859) time: 2.5991 data: 0.0059 max mem: 31677 +Epoch: [1] [ 260/1319] eta: 0:46:12 lr: 4.8650347819086694e-05 loss: 0.1790 (0.1853) time: 2.6213 data: 0.0057 max mem: 31677 +Epoch: [1] [ 270/1319] eta: 0:45:45 lr: 4.864179257468931e-05 loss: 0.1705 (0.1854) time: 2.6059 data: 0.0059 max mem: 31677 +Epoch: [1] [ 280/1319] eta: 0:45:21 lr: 4.8633237163097687e-05 loss: 0.1893 (0.1862) time: 2.6410 data: 0.0061 max mem: 31677 +Epoch: [1] [ 290/1319] eta: 0:44:53 lr: 4.862468158427592e-05 loss: 0.1830 (0.1864) time: 2.6255 data: 0.0058 max mem: 31677 +Epoch: [1] [ 300/1319] eta: 0:44:27 lr: 4.861612583818801e-05 loss: 0.1737 (0.1870) time: 2.5923 data: 0.0057 max mem: 31677 +Epoch: [1] [ 310/1319] eta: 0:44:01 lr: 4.860756992479799e-05 loss: 0.1635 (0.1876) time: 2.6204 data: 0.0059 max mem: 31677 +Epoch: [1] [ 320/1319] eta: 0:43:35 lr: 4.859901384406988e-05 loss: 0.1635 (0.1873) time: 2.6157 data: 0.0058 max mem: 31677 +Epoch: [1] [ 330/1319] eta: 0:43:08 lr: 4.8590457595967656e-05 loss: 0.1804 (0.1880) time: 2.6175 data: 0.0059 max mem: 31677 +Epoch: [1] [ 340/1319] eta: 0:42:42 lr: 4.85819011804553e-05 loss: 0.1630 (0.1871) time: 2.6134 data: 0.0061 max mem: 31677 +Epoch: [1] [ 350/1319] eta: 0:42:15 lr: 4.8573344597496775e-05 loss: 0.1601 (0.1870) time: 2.6020 data: 0.0059 max mem: 31677 +Epoch: [1] [ 360/1319] eta: 0:41:49 lr: 4.856478784705602e-05 loss: 0.1794 (0.1869) time: 2.6074 data: 0.0057 max mem: 31677 +Epoch: [1] [ 370/1319] eta: 0:41:23 lr: 4.8556230929096985e-05 loss: 0.1872 (0.1871) time: 2.6221 data: 0.0059 max mem: 31677 +Epoch: [1] [ 380/1319] eta: 0:40:56 lr: 4.854767384358357e-05 loss: 0.1904 (0.1870) time: 2.5955 data: 0.0060 max mem: 31677 +Epoch: [1] [ 390/1319] eta: 0:40:29 lr: 4.8539116590479686e-05 loss: 0.1786 (0.1872) time: 2.5806 data: 0.0060 max mem: 31677 +Epoch: [1] [ 400/1319] eta: 0:40:03 lr: 4.8530559169749225e-05 loss: 0.1648 (0.1874) time: 2.5965 data: 0.0059 max mem: 31677 +Epoch: [1] [ 410/1319] eta: 0:39:37 lr: 4.852200158135605e-05 loss: 0.1715 (0.1872) time: 2.6251 data: 0.0060 max mem: 31677 +Epoch: [1] [ 420/1319] eta: 0:39:12 lr: 4.851344382526403e-05 loss: 0.1614 (0.1867) time: 2.6509 data: 0.0059 max mem: 31677 +Epoch: [1] [ 430/1319] eta: 0:38:46 lr: 4.850488590143701e-05 loss: 0.1614 (0.1870) time: 2.6358 data: 0.0058 max mem: 31677 +Epoch: [1] [ 440/1319] eta: 0:38:20 lr: 4.84963278098388e-05 loss: 0.1652 (0.1871) time: 2.6203 data: 0.0059 max mem: 31677 +Epoch: [1] [ 450/1319] eta: 0:37:54 lr: 4.8487769550433236e-05 loss: 0.1652 (0.1874) time: 2.6319 data: 0.0060 max mem: 31677 +Epoch: [1] [ 460/1319] eta: 0:37:29 lr: 4.84792111231841e-05 loss: 0.1612 (0.1867) time: 2.6554 data: 0.0058 max mem: 31677 +Epoch: [1] [ 470/1319] eta: 0:37:02 lr: 4.847065252805519e-05 loss: 0.1612 (0.1869) time: 2.6191 data: 0.0057 max mem: 31677 +Epoch: [1] [ 480/1319] eta: 0:36:35 lr: 4.846209376501027e-05 loss: 0.1905 (0.1872) time: 2.5801 data: 0.0059 max mem: 31677 +Epoch: [1] [ 490/1319] eta: 0:36:09 lr: 4.8453534834013074e-05 loss: 0.1905 (0.1875) time: 2.6170 data: 0.0060 max mem: 31677 +Epoch: [1] [ 500/1319] eta: 0:35:43 lr: 4.844497573502737e-05 loss: 0.1862 (0.1875) time: 2.6209 data: 0.0057 max mem: 31677 +Epoch: [1] [ 510/1319] eta: 0:35:18 lr: 4.8436416468016874e-05 loss: 0.1712 (0.1874) time: 2.6394 data: 0.0057 max mem: 31677 +Epoch: [1] [ 520/1319] eta: 0:34:52 lr: 4.8427857032945285e-05 loss: 0.1618 (0.1871) time: 2.6536 data: 0.0059 max mem: 31677 +Epoch: [1] [ 530/1319] eta: 0:34:25 lr: 4.841929742977631e-05 loss: 0.1639 (0.1869) time: 2.6217 data: 0.0057 max mem: 31677 +Epoch: [1] [ 540/1319] eta: 0:34:00 lr: 4.841073765847362e-05 loss: 0.1746 (0.1871) time: 2.6369 data: 0.0056 max mem: 31677 +Epoch: [1] [ 550/1319] eta: 0:33:34 lr: 4.840217771900089e-05 loss: 0.1817 (0.1870) time: 2.6524 data: 0.0057 max mem: 31677 +Epoch: [1] [ 560/1319] eta: 0:33:08 lr: 4.8393617611321754e-05 loss: 0.1675 (0.1870) time: 2.6431 data: 0.0057 max mem: 31677 +Epoch: [1] [ 570/1319] eta: 0:32:42 lr: 4.838505733539985e-05 loss: 0.1738 (0.1873) time: 2.6383 data: 0.0057 max mem: 31677 +Epoch: [1] [ 580/1319] eta: 0:32:16 lr: 4.83764968911988e-05 loss: 0.1667 (0.1870) time: 2.6381 data: 0.0057 max mem: 31677 +Epoch: [1] [ 590/1319] eta: 0:31:50 lr: 4.836793627868222e-05 loss: 0.1634 (0.1869) time: 2.6487 data: 0.0057 max mem: 31677 +Epoch: [1] [ 600/1319] eta: 0:31:24 lr: 4.835937549781368e-05 loss: 0.1849 (0.1869) time: 2.6286 data: 0.0058 max mem: 31677 +Epoch: [1] [ 610/1319] eta: 0:30:58 lr: 4.835081454855677e-05 loss: 0.1670 (0.1864) time: 2.6209 data: 0.0059 max mem: 31677 +Epoch: [1] [ 620/1319] eta: 0:30:32 lr: 4.8342253430875026e-05 loss: 0.1648 (0.1864) time: 2.6362 data: 0.0059 max mem: 31677 +Epoch: [1] [ 630/1319] eta: 0:30:05 lr: 4.833369214473202e-05 loss: 0.1642 (0.1862) time: 2.6191 data: 0.0056 max mem: 31677 +Epoch: [1] [ 640/1319] eta: 0:29:39 lr: 4.832513069009127e-05 loss: 0.1561 (0.1857) time: 2.5886 data: 0.0058 max mem: 31677 +Epoch: [1] [ 650/1319] eta: 0:29:13 lr: 4.8316569066916287e-05 loss: 0.1561 (0.1858) time: 2.6161 data: 0.0058 max mem: 31677 +Epoch: [1] [ 660/1319] eta: 0:28:46 lr: 4.8308007275170564e-05 loss: 0.1809 (0.1857) time: 2.6211 data: 0.0056 max mem: 31677 +Epoch: [1] [ 670/1319] eta: 0:28:20 lr: 4.829944531481759e-05 loss: 0.1794 (0.1855) time: 2.5966 data: 0.0058 max mem: 31677 +Epoch: [1] [ 680/1319] eta: 0:27:54 lr: 4.8290883185820843e-05 loss: 0.1712 (0.1854) time: 2.6088 data: 0.0058 max mem: 31677 +Epoch: [1] [ 690/1319] eta: 0:27:27 lr: 4.828232088814377e-05 loss: 0.1853 (0.1856) time: 2.6093 data: 0.0057 max mem: 31677 +Epoch: [1] [ 700/1319] eta: 0:27:01 lr: 4.827375842174981e-05 loss: 0.1650 (0.1854) time: 2.6237 data: 0.0056 max mem: 31677 +Epoch: [1] [ 710/1319] eta: 0:26:35 lr: 4.826519578660238e-05 loss: 0.1708 (0.1855) time: 2.6221 data: 0.0056 max mem: 31677 +Epoch: [1] [ 720/1319] eta: 0:26:08 lr: 4.825663298266489e-05 loss: 0.1921 (0.1855) time: 2.5919 data: 0.0056 max mem: 31677 +Epoch: [1] [ 730/1319] eta: 0:25:42 lr: 4.824807000990074e-05 loss: 0.1757 (0.1853) time: 2.5931 data: 0.0057 max mem: 31677 +Epoch: [1] [ 740/1319] eta: 0:25:16 lr: 4.82395068682733e-05 loss: 0.1605 (0.1852) time: 2.6091 data: 0.0059 max mem: 31677 +Epoch: [1] [ 750/1319] eta: 0:24:50 lr: 4.823094355774595e-05 loss: 0.1604 (0.1855) time: 2.6035 data: 0.0059 max mem: 31677 +Epoch: [1] [ 760/1319] eta: 0:24:23 lr: 4.822238007828201e-05 loss: 0.1806 (0.1855) time: 2.6060 data: 0.0059 max mem: 31677 +Epoch: [1] [ 770/1319] eta: 0:23:57 lr: 4.8213816429844826e-05 loss: 0.1773 (0.1855) time: 2.5949 data: 0.0061 max mem: 31677 +Epoch: [1] [ 780/1319] eta: 0:23:31 lr: 4.8205252612397726e-05 loss: 0.1543 (0.1850) time: 2.6419 data: 0.0059 max mem: 31677 +Epoch: [1] [ 790/1319] eta: 0:23:05 lr: 4.8196688625903984e-05 loss: 0.1537 (0.1854) time: 2.6547 data: 0.0057 max mem: 31677 +Epoch: [1] [ 800/1319] eta: 0:22:39 lr: 4.8188124470326915e-05 loss: 0.1582 (0.1852) time: 2.6228 data: 0.0056 max mem: 31677 +Epoch: [1] [ 810/1319] eta: 0:22:13 lr: 4.8179560145629784e-05 loss: 0.1709 (0.1855) time: 2.6242 data: 0.0055 max mem: 31677 +Epoch: [1] [ 820/1319] eta: 0:21:47 lr: 4.817099565177583e-05 loss: 0.1917 (0.1857) time: 2.6300 data: 0.0057 max mem: 31677 +Epoch: [1] [ 830/1319] eta: 0:21:20 lr: 4.8162430988728305e-05 loss: 0.1822 (0.1856) time: 2.6334 data: 0.0057 max mem: 31677 +Epoch: [1] [ 840/1319] eta: 0:20:54 lr: 4.815386615645044e-05 loss: 0.1566 (0.1852) time: 2.6251 data: 0.0056 max mem: 31677 +Epoch: [1] [ 850/1319] eta: 0:20:28 lr: 4.814530115490545e-05 loss: 0.1686 (0.1854) time: 2.6201 data: 0.0057 max mem: 31677 +Epoch: [1] [ 860/1319] eta: 0:20:02 lr: 4.813673598405651e-05 loss: 0.1742 (0.1852) time: 2.5982 data: 0.0059 max mem: 31677 +Epoch: [1] [ 870/1319] eta: 0:19:36 lr: 4.812817064386682e-05 loss: 0.1611 (0.1851) time: 2.6185 data: 0.0057 max mem: 31677 +Epoch: [1] [ 880/1319] eta: 0:19:10 lr: 4.8119605134299526e-05 loss: 0.1611 (0.1849) time: 2.6700 data: 0.0056 max mem: 31677 +Epoch: [1] [ 890/1319] eta: 0:18:44 lr: 4.81110394553178e-05 loss: 0.1634 (0.1848) time: 2.6657 data: 0.0056 max mem: 31677 +Epoch: [1] [ 900/1319] eta: 0:18:18 lr: 4.810247360688475e-05 loss: 0.1611 (0.1845) time: 2.6323 data: 0.0056 max mem: 31677 +Epoch: [1] [ 910/1319] eta: 0:17:51 lr: 4.809390758896352e-05 loss: 0.1481 (0.1842) time: 2.5942 data: 0.0055 max mem: 31677 +Epoch: [1] [ 920/1319] eta: 0:17:25 lr: 4.808534140151719e-05 loss: 0.1634 (0.1844) time: 2.6160 data: 0.0056 max mem: 31677 +Epoch: [1] [ 930/1319] eta: 0:16:59 lr: 4.807677504450886e-05 loss: 0.1620 (0.1842) time: 2.6268 data: 0.0058 max mem: 31677 +Epoch: [1] [ 940/1319] eta: 0:16:33 lr: 4.806820851790161e-05 loss: 0.1454 (0.1843) time: 2.6140 data: 0.0058 max mem: 31677 +Epoch: [1] [ 950/1319] eta: 0:16:06 lr: 4.805964182165848e-05 loss: 0.1857 (0.1842) time: 2.6305 data: 0.0058 max mem: 31677 +Epoch: [1] [ 960/1319] eta: 0:15:40 lr: 4.8051074955742525e-05 loss: 0.1789 (0.1840) time: 2.6030 data: 0.0059 max mem: 31677 +Epoch: [1] [ 970/1319] eta: 0:15:14 lr: 4.804250792011677e-05 loss: 0.1701 (0.1840) time: 2.5814 data: 0.0059 max mem: 31677 +Epoch: [1] [ 980/1319] eta: 0:14:48 lr: 4.803394071474422e-05 loss: 0.1748 (0.1842) time: 2.5950 data: 0.0057 max mem: 31677 +Epoch: [1] [ 990/1319] eta: 0:14:21 lr: 4.802537333958788e-05 loss: 0.1693 (0.1840) time: 2.6348 data: 0.0057 max mem: 31677 +Epoch: [1] [1000/1319] eta: 0:13:55 lr: 4.801680579461071e-05 loss: 0.1717 (0.1841) time: 2.6380 data: 0.0056 max mem: 31677 +Epoch: [1] [1010/1319] eta: 0:13:29 lr: 4.80082380797757e-05 loss: 0.1825 (0.1841) time: 2.6211 data: 0.0057 max mem: 31677 +Epoch: [1] [1020/1319] eta: 0:13:03 lr: 4.79996701950458e-05 loss: 0.1840 (0.1846) time: 2.6260 data: 0.0058 max mem: 31677 +Epoch: [1] [1030/1319] eta: 0:12:37 lr: 4.799110214038392e-05 loss: 0.2106 (0.1847) time: 2.6404 data: 0.0057 max mem: 31677 +Epoch: [1] [1040/1319] eta: 0:12:11 lr: 4.7982533915752995e-05 loss: 0.1848 (0.1847) time: 2.6452 data: 0.0057 max mem: 31677 +Epoch: [1] [1050/1319] eta: 0:11:44 lr: 4.797396552111593e-05 loss: 0.1799 (0.1846) time: 2.6411 data: 0.0057 max mem: 31677 +Epoch: [1] [1060/1319] eta: 0:11:18 lr: 4.7965396956435596e-05 loss: 0.1551 (0.1844) time: 2.6367 data: 0.0058 max mem: 31677 +Epoch: [1] [1070/1319] eta: 0:10:52 lr: 4.795682822167489e-05 loss: 0.1554 (0.1844) time: 2.6307 data: 0.0059 max mem: 31677 +Epoch: [1] [1080/1319] eta: 0:10:26 lr: 4.794825931679665e-05 loss: 0.1640 (0.1844) time: 2.6058 data: 0.0059 max mem: 31677 +Epoch: [1] [1090/1319] eta: 0:10:00 lr: 4.7939690241763725e-05 loss: 0.1816 (0.1843) time: 2.5871 data: 0.0058 max mem: 31677 +Epoch: [1] [1100/1319] eta: 0:09:33 lr: 4.793112099653894e-05 loss: 0.1617 (0.1843) time: 2.6114 data: 0.0060 max mem: 31677 +Epoch: [1] [1110/1319] eta: 0:09:07 lr: 4.79225515810851e-05 loss: 0.1517 (0.1844) time: 2.6423 data: 0.0060 max mem: 31677 +Epoch: [1] [1120/1319] eta: 0:08:41 lr: 4.791398199536501e-05 loss: 0.1706 (0.1846) time: 2.6286 data: 0.0058 max mem: 31677 +Epoch: [1] [1130/1319] eta: 0:08:15 lr: 4.790541223934144e-05 loss: 0.1978 (0.1847) time: 2.6238 data: 0.0059 max mem: 31677 +Epoch: [1] [1140/1319] eta: 0:07:49 lr: 4.7896842312977156e-05 loss: 0.1978 (0.1848) time: 2.6389 data: 0.0058 max mem: 31677 +Epoch: [1] [1150/1319] eta: 0:07:23 lr: 4.788827221623491e-05 loss: 0.1811 (0.1846) time: 2.6654 data: 0.0057 max mem: 31677 +Epoch: [1] [1160/1319] eta: 0:06:56 lr: 4.787970194907743e-05 loss: 0.1562 (0.1845) time: 2.6454 data: 0.0057 max mem: 31677 +Epoch: [1] [1170/1319] eta: 0:06:30 lr: 4.787113151146744e-05 loss: 0.1636 (0.1845) time: 2.5836 data: 0.0059 max mem: 31677 +Epoch: [1] [1180/1319] eta: 0:06:04 lr: 4.786256090336764e-05 loss: 0.1737 (0.1847) time: 2.6306 data: 0.0059 max mem: 31677 +Epoch: [1] [1190/1319] eta: 0:05:38 lr: 4.7853990124740705e-05 loss: 0.1701 (0.1845) time: 2.6628 data: 0.0059 max mem: 31677 +Epoch: [1] [1200/1319] eta: 0:05:11 lr: 4.784541917554932e-05 loss: 0.1560 (0.1844) time: 2.6423 data: 0.0059 max mem: 31677 +Epoch: [1] [1210/1319] eta: 0:04:45 lr: 4.783684805575612e-05 loss: 0.1573 (0.1845) time: 2.6295 data: 0.0058 max mem: 31677 +Epoch: [1] [1220/1319] eta: 0:04:19 lr: 4.782827676532376e-05 loss: 0.1679 (0.1844) time: 2.6049 data: 0.0059 max mem: 31677 +Epoch: [1] [1230/1319] eta: 0:03:53 lr: 4.781970530421487e-05 loss: 0.1679 (0.1843) time: 2.6301 data: 0.0058 max mem: 31677 +Epoch: [1] [1240/1319] eta: 0:03:27 lr: 4.7811133672392044e-05 loss: 0.1616 (0.1841) time: 2.6408 data: 0.0057 max mem: 31677 +Epoch: [1] [1250/1319] eta: 0:03:00 lr: 4.780256186981787e-05 loss: 0.1683 (0.1841) time: 2.6168 data: 0.0057 max mem: 31677 +Epoch: [1] [1260/1319] eta: 0:02:34 lr: 4.779398989645494e-05 loss: 0.1822 (0.1842) time: 2.6120 data: 0.0057 max mem: 31677 +Epoch: [1] [1270/1319] eta: 0:02:08 lr: 4.778541775226581e-05 loss: 0.1822 (0.1841) time: 2.5975 data: 0.0059 max mem: 31677 +Epoch: [1] [1280/1319] eta: 0:01:42 lr: 4.777684543721302e-05 loss: 0.1569 (0.1840) time: 2.5999 data: 0.0059 max mem: 31677 +Epoch: [1] [1290/1319] eta: 0:01:16 lr: 4.776827295125911e-05 loss: 0.1529 (0.1838) time: 2.6273 data: 0.0057 max mem: 31677 +Epoch: [1] [1300/1319] eta: 0:00:49 lr: 4.775970029436657e-05 loss: 0.1436 (0.1835) time: 2.6293 data: 0.0058 max mem: 31677 +Epoch: [1] [1310/1319] eta: 0:00:23 lr: 4.7751127466497925e-05 loss: 0.1656 (0.1835) time: 2.6179 data: 0.0058 max mem: 31677 +Epoch: [1] Total time: 0:57:37 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 2:17:12 time: 3.1997 data: 3.1216 max mem: 31677 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 100/2573] eta: 0:04:13 time: 0.0715 data: 0.0011 max mem: 31677 +Test: [ 200/2573] eta: 0:03:29 time: 0.0729 data: 0.0011 max mem: 31677 +Test: [ 300/2573] eta: 0:03:07 time: 0.0744 data: 0.0011 max mem: 31677 +Test: [ 400/2573] eta: 0:02:54 time: 0.0744 data: 0.0011 max mem: 31677 +Test: [ 500/2573] eta: 0:02:43 time: 0.0731 data: 0.0011 max mem: 31677 +Test: [ 600/2573] eta: 0:02:33 time: 0.0731 data: 0.0011 max mem: 31677 +Test: [ 700/2573] eta: 0:02:25 time: 0.0732 data: 0.0011 max mem: 31677 +Test: [ 800/2573] eta: 0:02:16 time: 0.0766 data: 0.0011 max mem: 31677 +Test: [ 900/2573] eta: 0:02:08 time: 0.0734 data: 0.0011 max mem: 31677 +Test: [1000/2573] eta: 0:02:00 time: 0.0733 data: 0.0011 max mem: 31677 +Test: [1100/2573] eta: 0:01:52 time: 0.0735 data: 0.0011 max mem: 31677 +Test: [1200/2573] eta: 0:01:44 time: 0.0734 data: 0.0011 max mem: 31677 +Test: [1300/2573] eta: 0:01:36 time: 0.0734 data: 0.0011 max mem: 31677 +Test: [1400/2573] eta: 0:01:28 time: 0.0718 data: 0.0011 max mem: 31677 +Test: [1500/2573] eta: 0:01:21 time: 0.0736 data: 0.0012 max mem: 31677 +Test: [1600/2573] eta: 0:01:13 time: 0.0769 data: 0.0011 max mem: 31677 +Test: [1700/2573] eta: 0:01:05 time: 0.0719 data: 0.0011 max mem: 31677 +Test: [1800/2573] eta: 0:00:58 time: 0.0753 data: 0.0011 max mem: 31677 +Test: [1900/2573] eta: 0:00:50 time: 0.0720 data: 0.0011 max mem: 31677 +Test: [2000/2573] eta: 0:00:42 time: 0.0737 data: 0.0011 max mem: 31677 +Test: [2100/2573] eta: 0:00:35 time: 0.0752 data: 0.0011 max mem: 31677 +Test: [2200/2573] eta: 0:00:27 time: 0.0755 data: 0.0011 max mem: 31677 +Test: [2300/2573] eta: 0:00:20 time: 0.0752 data: 0.0011 max mem: 31677 +Test: [2400/2573] eta: 0:00:12 time: 0.0702 data: 0.0011 max mem: 31677 +Test: [2500/2573] eta: 0:00:05 time: 0.0736 data: 0.0011 max mem: 31677 +Test: Total time: 0:03:12 +Final results: +Mean IoU is 39.67 + + precision@0.5 = 40.07 + precision@0.6 = 30.76 + precision@0.7 = 21.51 + precision@0.8 = 12.95 + precision@0.9 = 3.68 + overall IoU = 43.09 + +Average object IoU 39.66918750511345 +Overall IoU 43.09418487548828 +Better epoch: 1 + +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [2] [ 0/1319] eta: 1:26:10 lr: 4.774341177520056e-05 loss: 0.0933 (0.0933) time: 3.9203 data: 1.2353 max mem: 31677 +Epoch: [2] [ 10/1319] eta: 0:58:35 lr: 4.773483862237391e-05 loss: 0.1706 (0.1770) time: 2.6859 data: 0.1176 max mem: 31677 +Epoch: [2] [ 20/1319] eta: 0:57:23 lr: 4.772626529846231e-05 loss: 0.1706 (0.1766) time: 2.5873 data: 0.0060 max mem: 31677 +Epoch: [2] [ 30/1319] eta: 0:56:33 lr: 4.771769180342819e-05 loss: 0.1682 (0.1758) time: 2.6039 data: 0.0062 max mem: 31677 +Epoch: [2] [ 40/1319] eta: 0:56:14 lr: 4.7709118137233964e-05 loss: 0.1573 (0.1728) time: 2.6256 data: 0.0062 max mem: 31677 +Epoch: [2] [ 50/1319] eta: 0:55:58 lr: 4.770054429984204e-05 loss: 0.1556 (0.1703) time: 2.6682 data: 0.0062 max mem: 31677 +Epoch: [2] [ 60/1319] eta: 0:55:29 lr: 4.769197029121481e-05 loss: 0.1491 (0.1694) time: 2.6574 data: 0.0060 max mem: 31677 +Epoch: [2] [ 70/1319] eta: 0:55:02 lr: 4.7683396111314645e-05 loss: 0.1755 (0.1769) time: 2.6374 data: 0.0058 max mem: 31677 +Epoch: [2] [ 80/1319] eta: 0:54:31 lr: 4.7674821760103904e-05 loss: 0.1701 (0.1738) time: 2.6280 data: 0.0058 max mem: 31677 +Epoch: [2] [ 90/1319] eta: 0:54:05 lr: 4.766624723754494e-05 loss: 0.1463 (0.1713) time: 2.6271 data: 0.0058 max mem: 31677 +Epoch: [2] [ 100/1319] eta: 0:53:34 lr: 4.7657672543600056e-05 loss: 0.1597 (0.1709) time: 2.6237 data: 0.0058 max mem: 31677 +Epoch: [2] [ 110/1319] eta: 0:53:09 lr: 4.764909767823158e-05 loss: 0.1666 (0.1711) time: 2.6263 data: 0.0058 max mem: 31677 +Epoch: [2] [ 120/1319] eta: 0:52:40 lr: 4.76405226414018e-05 loss: 0.1634 (0.1705) time: 2.6316 data: 0.0061 max mem: 31677 +Epoch: [2] [ 130/1319] eta: 0:52:12 lr: 4.7631947433073e-05 loss: 0.1601 (0.1686) time: 2.6139 data: 0.0061 max mem: 31677 +Epoch: [2] [ 140/1319] eta: 0:51:44 lr: 4.762337205320744e-05 loss: 0.1462 (0.1671) time: 2.6171 data: 0.0059 max mem: 31677 +Epoch: [2] [ 150/1319] eta: 0:51:17 lr: 4.7614796501767376e-05 loss: 0.1555 (0.1669) time: 2.6252 data: 0.0060 max mem: 31677 +Epoch: [2] [ 160/1319] eta: 0:50:51 lr: 4.760622077871502e-05 loss: 0.1686 (0.1670) time: 2.6311 data: 0.0060 max mem: 31677 +Epoch: [2] [ 170/1319] eta: 0:50:24 lr: 4.75976448840126e-05 loss: 0.1463 (0.1662) time: 2.6272 data: 0.0059 max mem: 31677 +Epoch: [2] [ 180/1319] eta: 0:49:56 lr: 4.7589068817622304e-05 loss: 0.1463 (0.1657) time: 2.6096 data: 0.0061 max mem: 31677 +Epoch: [2] [ 190/1319] eta: 0:49:29 lr: 4.758049257950633e-05 loss: 0.1478 (0.1651) time: 2.6150 data: 0.0061 max mem: 31677 +Epoch: [2] [ 200/1319] eta: 0:49:02 lr: 4.757191616962685e-05 loss: 0.1523 (0.1648) time: 2.6218 data: 0.0059 max mem: 31677 +Epoch: [2] [ 210/1319] eta: 0:48:35 lr: 4.756333958794601e-05 loss: 0.1527 (0.1644) time: 2.6136 data: 0.0059 max mem: 31677 +Epoch: [2] [ 220/1319] eta: 0:48:07 lr: 4.7554762834425936e-05 loss: 0.1618 (0.1641) time: 2.6014 data: 0.0058 max mem: 31677 +Epoch: [2] [ 230/1319] eta: 0:47:42 lr: 4.7546185909028754e-05 loss: 0.1618 (0.1649) time: 2.6245 data: 0.0058 max mem: 31677 +Epoch: [2] [ 240/1319] eta: 0:47:17 lr: 4.753760881171657e-05 loss: 0.1667 (0.1646) time: 2.6545 data: 0.0058 max mem: 31677 +Epoch: [2] [ 250/1319] eta: 0:46:49 lr: 4.7529031542451477e-05 loss: 0.1667 (0.1651) time: 2.6193 data: 0.0059 max mem: 31677 +Epoch: [2] [ 260/1319] eta: 0:46:24 lr: 4.7520454101195535e-05 loss: 0.1698 (0.1658) time: 2.6339 data: 0.0059 max mem: 31677 +Epoch: [2] [ 270/1319] eta: 0:45:57 lr: 4.751187648791081e-05 loss: 0.1643 (0.1653) time: 2.6428 data: 0.0059 max mem: 31677 +Epoch: [2] [ 280/1319] eta: 0:45:31 lr: 4.7503298702559326e-05 loss: 0.1575 (0.1656) time: 2.6133 data: 0.0058 max mem: 31677 +Epoch: [2] [ 290/1319] eta: 0:45:03 lr: 4.7494720745103136e-05 loss: 0.1599 (0.1659) time: 2.6111 data: 0.0059 max mem: 31677 +Epoch: [2] [ 300/1319] eta: 0:44:38 lr: 4.748614261550422e-05 loss: 0.1416 (0.1651) time: 2.6306 data: 0.0059 max mem: 31677 +Epoch: [2] [ 310/1319] eta: 0:44:12 lr: 4.7477564313724594e-05 loss: 0.1438 (0.1650) time: 2.6435 data: 0.0060 max mem: 31677 +Epoch: [2] [ 320/1319] eta: 0:43:46 lr: 4.746898583972622e-05 loss: 0.1801 (0.1669) time: 2.6346 data: 0.0060 max mem: 31677 +Epoch: [2] [ 330/1319] eta: 0:43:21 lr: 4.746040719347105e-05 loss: 0.1542 (0.1663) time: 2.6656 data: 0.0058 max mem: 31678 +Epoch: [2] [ 340/1319] eta: 0:42:55 lr: 4.745182837492104e-05 loss: 0.1504 (0.1668) time: 2.6631 data: 0.0057 max mem: 31678 +Epoch: [2] [ 350/1319] eta: 0:42:29 lr: 4.744324938403812e-05 loss: 0.1783 (0.1671) time: 2.6414 data: 0.0059 max mem: 31678 +Epoch: [2] [ 360/1319] eta: 0:42:03 lr: 4.7434670220784206e-05 loss: 0.1723 (0.1668) time: 2.6356 data: 0.0059 max mem: 31678 +Epoch: [2] [ 370/1319] eta: 0:41:35 lr: 4.7426090885121175e-05 loss: 0.1624 (0.1665) time: 2.6040 data: 0.0059 max mem: 31678 +Epoch: [2] [ 380/1319] eta: 0:41:10 lr: 4.741751137701092e-05 loss: 0.1624 (0.1666) time: 2.6144 data: 0.0060 max mem: 31678 +Epoch: [2] [ 390/1319] eta: 0:40:44 lr: 4.74089316964153e-05 loss: 0.1735 (0.1673) time: 2.6500 data: 0.0059 max mem: 31678 +Epoch: [2] [ 400/1319] eta: 0:40:18 lr: 4.740035184329618e-05 loss: 0.1700 (0.1674) time: 2.6470 data: 0.0059 max mem: 31678 +Epoch: [2] [ 410/1319] eta: 0:39:50 lr: 4.739177181761536e-05 loss: 0.1505 (0.1670) time: 2.6150 data: 0.0057 max mem: 31678 +Epoch: [2] [ 420/1319] eta: 0:39:24 lr: 4.738319161933468e-05 loss: 0.1429 (0.1668) time: 2.6044 data: 0.0058 max mem: 31678 +Epoch: [2] [ 430/1319] eta: 0:38:57 lr: 4.737461124841593e-05 loss: 0.1356 (0.1663) time: 2.6145 data: 0.0060 max mem: 31678 +Epoch: [2] [ 440/1319] eta: 0:38:30 lr: 4.736603070482089e-05 loss: 0.1387 (0.1659) time: 2.6046 data: 0.0058 max mem: 31678 +Epoch: [2] [ 450/1319] eta: 0:38:03 lr: 4.735744998851133e-05 loss: 0.1437 (0.1654) time: 2.5847 data: 0.0057 max mem: 31678 +Epoch: [2] [ 460/1319] eta: 0:37:36 lr: 4.734886909944901e-05 loss: 0.1488 (0.1657) time: 2.5871 data: 0.0058 max mem: 31678 +Epoch: [2] [ 470/1319] eta: 0:37:10 lr: 4.734028803759565e-05 loss: 0.1692 (0.1654) time: 2.6229 data: 0.0060 max mem: 31678 +Epoch: [2] [ 480/1319] eta: 0:36:43 lr: 4.733170680291298e-05 loss: 0.1373 (0.1649) time: 2.6232 data: 0.0060 max mem: 31678 +Epoch: [2] [ 490/1319] eta: 0:36:17 lr: 4.7323125395362694e-05 loss: 0.1310 (0.1642) time: 2.6169 data: 0.0058 max mem: 31678 +Epoch: [2] [ 500/1319] eta: 0:35:51 lr: 4.731454381490648e-05 loss: 0.1310 (0.1650) time: 2.6402 data: 0.0058 max mem: 31678 +Epoch: [2] [ 510/1319] eta: 0:35:26 lr: 4.730596206150601e-05 loss: 0.1409 (0.1645) time: 2.6625 data: 0.0058 max mem: 33369 +Epoch: [2] [ 520/1319] eta: 0:34:59 lr: 4.729738013512294e-05 loss: 0.1367 (0.1645) time: 2.6400 data: 0.0057 max mem: 33369 +Epoch: [2] [ 530/1319] eta: 0:34:33 lr: 4.72887980357189e-05 loss: 0.1456 (0.1644) time: 2.6072 data: 0.0056 max mem: 33369 +Epoch: [2] [ 540/1319] eta: 0:34:06 lr: 4.7280215763255517e-05 loss: 0.1595 (0.1645) time: 2.5993 data: 0.0057 max mem: 33369 +Epoch: [2] [ 550/1319] eta: 0:33:40 lr: 4.7271633317694384e-05 loss: 0.1465 (0.1642) time: 2.6219 data: 0.0058 max mem: 33369 +Epoch: [2] [ 560/1319] eta: 0:33:14 lr: 4.726305069899711e-05 loss: 0.1465 (0.1644) time: 2.6349 data: 0.0060 max mem: 33369 +Epoch: [2] [ 570/1319] eta: 0:32:47 lr: 4.725446790712525e-05 loss: 0.1537 (0.1644) time: 2.6135 data: 0.0059 max mem: 33369 +Epoch: [2] [ 580/1319] eta: 0:32:20 lr: 4.7245884942040375e-05 loss: 0.1537 (0.1645) time: 2.6080 data: 0.0058 max mem: 33369 +Epoch: [2] [ 590/1319] eta: 0:31:54 lr: 4.7237301803704005e-05 loss: 0.1416 (0.1644) time: 2.6164 data: 0.0057 max mem: 33369 +Epoch: [2] [ 600/1319] eta: 0:31:28 lr: 4.722871849207768e-05 loss: 0.1416 (0.1640) time: 2.6316 data: 0.0057 max mem: 33369 +Epoch: [2] [ 610/1319] eta: 0:31:02 lr: 4.72201350071229e-05 loss: 0.1406 (0.1640) time: 2.6265 data: 0.0058 max mem: 33369 +Epoch: [2] [ 620/1319] eta: 0:30:36 lr: 4.7211551348801154e-05 loss: 0.1612 (0.1639) time: 2.6377 data: 0.0057 max mem: 33369 +Epoch: [2] [ 630/1319] eta: 0:30:09 lr: 4.7202967517073924e-05 loss: 0.1612 (0.1640) time: 2.6363 data: 0.0057 max mem: 33369 +Epoch: [2] [ 640/1319] eta: 0:29:43 lr: 4.719438351190267e-05 loss: 0.1371 (0.1639) time: 2.6302 data: 0.0056 max mem: 33369 +Epoch: [2] [ 650/1319] eta: 0:29:17 lr: 4.718579933324881e-05 loss: 0.1456 (0.1640) time: 2.6360 data: 0.0056 max mem: 33369 +Epoch: [2] [ 660/1319] eta: 0:28:51 lr: 4.71772149810738e-05 loss: 0.1669 (0.1640) time: 2.6290 data: 0.0056 max mem: 33369 +Epoch: [2] [ 670/1319] eta: 0:28:24 lr: 4.716863045533903e-05 loss: 0.1775 (0.1643) time: 2.6019 data: 0.0059 max mem: 33369 +Epoch: [2] [ 680/1319] eta: 0:27:58 lr: 4.71600457560059e-05 loss: 0.1775 (0.1642) time: 2.5925 data: 0.0059 max mem: 33369 +Epoch: [2] [ 690/1319] eta: 0:27:31 lr: 4.7151460883035786e-05 loss: 0.1758 (0.1647) time: 2.6129 data: 0.0057 max mem: 33369 +Epoch: [2] [ 700/1319] eta: 0:27:05 lr: 4.714287583639004e-05 loss: 0.1471 (0.1644) time: 2.6188 data: 0.0057 max mem: 33369 +Epoch: [2] [ 710/1319] eta: 0:26:39 lr: 4.713429061603002e-05 loss: 0.1374 (0.1643) time: 2.6213 data: 0.0057 max mem: 33369 +Epoch: [2] [ 720/1319] eta: 0:26:12 lr: 4.712570522191704e-05 loss: 0.1412 (0.1641) time: 2.6111 data: 0.0058 max mem: 33369 +Epoch: [2] [ 730/1319] eta: 0:25:46 lr: 4.7117119654012416e-05 loss: 0.1412 (0.1637) time: 2.6085 data: 0.0058 max mem: 33369 +Epoch: [2] [ 740/1319] eta: 0:25:20 lr: 4.7108533912277444e-05 loss: 0.1526 (0.1635) time: 2.6336 data: 0.0058 max mem: 33369 +Epoch: [2] [ 750/1319] eta: 0:24:54 lr: 4.709994799667339e-05 loss: 0.1592 (0.1639) time: 2.6506 data: 0.0058 max mem: 33369 +Epoch: [2] [ 760/1319] eta: 0:24:28 lr: 4.709136190716153e-05 loss: 0.1582 (0.1637) time: 2.6438 data: 0.0057 max mem: 33369 +Epoch: [2] [ 770/1319] eta: 0:24:01 lr: 4.708277564370309e-05 loss: 0.1485 (0.1635) time: 2.6342 data: 0.0059 max mem: 33369 +Epoch: [2] [ 780/1319] eta: 0:23:35 lr: 4.707418920625932e-05 loss: 0.1487 (0.1636) time: 2.6059 data: 0.0058 max mem: 33369 +Epoch: [2] [ 790/1319] eta: 0:23:08 lr: 4.706560259479142e-05 loss: 0.1602 (0.1637) time: 2.5928 data: 0.0057 max mem: 33369 +Epoch: [2] [ 800/1319] eta: 0:22:42 lr: 4.705701580926059e-05 loss: 0.1716 (0.1642) time: 2.6143 data: 0.0057 max mem: 33369 +Epoch: [2] [ 810/1319] eta: 0:22:16 lr: 4.7048428849628004e-05 loss: 0.1814 (0.1647) time: 2.6150 data: 0.0057 max mem: 33369 +Epoch: [2] [ 820/1319] eta: 0:21:50 lr: 4.703984171585482e-05 loss: 0.1797 (0.1646) time: 2.6229 data: 0.0057 max mem: 33369 +Epoch: [2] [ 830/1319] eta: 0:21:23 lr: 4.703125440790219e-05 loss: 0.1716 (0.1647) time: 2.6457 data: 0.0056 max mem: 33369 +Epoch: [2] [ 840/1319] eta: 0:20:57 lr: 4.702266692573125e-05 loss: 0.1716 (0.1647) time: 2.6529 data: 0.0056 max mem: 33369 +Epoch: [2] [ 850/1319] eta: 0:20:31 lr: 4.70140792693031e-05 loss: 0.1631 (0.1647) time: 2.6489 data: 0.0057 max mem: 33369 +Epoch: [2] [ 860/1319] eta: 0:20:05 lr: 4.700549143857884e-05 loss: 0.1708 (0.1649) time: 2.6275 data: 0.0057 max mem: 33369 +Epoch: [2] [ 870/1319] eta: 0:19:39 lr: 4.699690343351954e-05 loss: 0.1799 (0.1649) time: 2.6296 data: 0.0056 max mem: 33369 +Epoch: [2] [ 880/1319] eta: 0:19:12 lr: 4.698831525408628e-05 loss: 0.1580 (0.1650) time: 2.6321 data: 0.0056 max mem: 33369 +Epoch: [2] [ 890/1319] eta: 0:18:46 lr: 4.697972690024009e-05 loss: 0.1489 (0.1649) time: 2.6113 data: 0.0056 max mem: 33369 +Epoch: [2] [ 900/1319] eta: 0:18:20 lr: 4.6971138371942025e-05 loss: 0.1438 (0.1646) time: 2.5978 data: 0.0056 max mem: 33369 +Epoch: [2] [ 910/1319] eta: 0:17:53 lr: 4.696254966915307e-05 loss: 0.1521 (0.1646) time: 2.6059 data: 0.0057 max mem: 33369 +Epoch: [2] [ 920/1319] eta: 0:17:27 lr: 4.695396079183423e-05 loss: 0.1521 (0.1645) time: 2.6100 data: 0.0057 max mem: 33369 +Epoch: [2] [ 930/1319] eta: 0:17:01 lr: 4.694537173994649e-05 loss: 0.1506 (0.1645) time: 2.6048 data: 0.0057 max mem: 33369 +Epoch: [2] [ 940/1319] eta: 0:16:34 lr: 4.69367825134508e-05 loss: 0.1506 (0.1644) time: 2.6200 data: 0.0057 max mem: 33369 +Epoch: [2] [ 950/1319] eta: 0:16:08 lr: 4.692819311230812e-05 loss: 0.1560 (0.1646) time: 2.6332 data: 0.0056 max mem: 33369 +Epoch: [2] [ 960/1319] eta: 0:15:42 lr: 4.6919603536479375e-05 loss: 0.1560 (0.1646) time: 2.6257 data: 0.0058 max mem: 33369 +Epoch: [2] [ 970/1319] eta: 0:15:16 lr: 4.691101378592547e-05 loss: 0.1468 (0.1645) time: 2.6184 data: 0.0059 max mem: 33369 +Epoch: [2] [ 980/1319] eta: 0:14:50 lr: 4.690242386060732e-05 loss: 0.1385 (0.1643) time: 2.6401 data: 0.0057 max mem: 33369 +Epoch: [2] [ 990/1319] eta: 0:14:23 lr: 4.6893833760485775e-05 loss: 0.1450 (0.1642) time: 2.6424 data: 0.0058 max mem: 33369 +Epoch: [2] [1000/1319] eta: 0:13:57 lr: 4.688524348552173e-05 loss: 0.1546 (0.1641) time: 2.6330 data: 0.0058 max mem: 33369 +Epoch: [2] [1010/1319] eta: 0:13:31 lr: 4.6876653035676014e-05 loss: 0.1546 (0.1642) time: 2.6503 data: 0.0056 max mem: 33369 +Epoch: [2] [1020/1319] eta: 0:13:05 lr: 4.6868062410909454e-05 loss: 0.1621 (0.1642) time: 2.6341 data: 0.0055 max mem: 33369 +Epoch: [2] [1030/1319] eta: 0:12:38 lr: 4.685947161118287e-05 loss: 0.1462 (0.1641) time: 2.6076 data: 0.0056 max mem: 33369 +Epoch: [2] [1040/1319] eta: 0:12:12 lr: 4.685088063645705e-05 loss: 0.1442 (0.1639) time: 2.6073 data: 0.0057 max mem: 33369 +Epoch: [2] [1050/1319] eta: 0:11:46 lr: 4.684228948669277e-05 loss: 0.1544 (0.1638) time: 2.6105 data: 0.0057 max mem: 33369 +Epoch: [2] [1060/1319] eta: 0:11:19 lr: 4.683369816185082e-05 loss: 0.1184 (0.1633) time: 2.6215 data: 0.0055 max mem: 33369 +Epoch: [2] [1070/1319] eta: 0:10:53 lr: 4.682510666189191e-05 loss: 0.1162 (0.1632) time: 2.6252 data: 0.0056 max mem: 33369 +Epoch: [2] [1080/1319] eta: 0:10:27 lr: 4.681651498677679e-05 loss: 0.1420 (0.1632) time: 2.6184 data: 0.0057 max mem: 33369 +Epoch: [2] [1090/1319] eta: 0:10:01 lr: 4.680792313646616e-05 loss: 0.1570 (0.1632) time: 2.6071 data: 0.0056 max mem: 33369 +Epoch: [2] [1100/1319] eta: 0:09:34 lr: 4.679933111092072e-05 loss: 0.1519 (0.1631) time: 2.5941 data: 0.0056 max mem: 33369 +Epoch: [2] [1110/1319] eta: 0:09:08 lr: 4.6790738910101147e-05 loss: 0.1552 (0.1633) time: 2.5974 data: 0.0056 max mem: 33369 +Epoch: [2] [1120/1319] eta: 0:08:42 lr: 4.67821465339681e-05 loss: 0.1730 (0.1634) time: 2.6130 data: 0.0056 max mem: 33369 +Epoch: [2] [1130/1319] eta: 0:08:16 lr: 4.677355398248223e-05 loss: 0.1730 (0.1637) time: 2.6195 data: 0.0056 max mem: 33369 +Epoch: [2] [1140/1319] eta: 0:07:49 lr: 4.676496125560416e-05 loss: 0.1589 (0.1638) time: 2.6395 data: 0.0055 max mem: 33369 +Epoch: [2] [1150/1319] eta: 0:07:23 lr: 4.6756368353294506e-05 loss: 0.1368 (0.1636) time: 2.6624 data: 0.0057 max mem: 33369 +Epoch: [2] [1160/1319] eta: 0:06:57 lr: 4.6747775275513856e-05 loss: 0.1254 (0.1634) time: 2.6442 data: 0.0057 max mem: 33369 +Epoch: [2] [1170/1319] eta: 0:06:31 lr: 4.6739182022222775e-05 loss: 0.1382 (0.1633) time: 2.6216 data: 0.0056 max mem: 33369 +Epoch: [2] [1180/1319] eta: 0:06:04 lr: 4.6730588593381847e-05 loss: 0.1580 (0.1633) time: 2.6097 data: 0.0058 max mem: 33369 +Epoch: [2] [1190/1319] eta: 0:05:38 lr: 4.67219949889516e-05 loss: 0.1556 (0.1635) time: 2.5959 data: 0.0058 max mem: 33369 +Epoch: [2] [1200/1319] eta: 0:05:12 lr: 4.6713401208892564e-05 loss: 0.1556 (0.1636) time: 2.6103 data: 0.0055 max mem: 33369 +Epoch: [2] [1210/1319] eta: 0:04:46 lr: 4.6704807253165246e-05 loss: 0.1535 (0.1636) time: 2.6221 data: 0.0057 max mem: 33369 +Epoch: [2] [1220/1319] eta: 0:04:19 lr: 4.6696213121730145e-05 loss: 0.1631 (0.1637) time: 2.6142 data: 0.0058 max mem: 33369 +Epoch: [2] [1230/1319] eta: 0:03:53 lr: 4.668761881454772e-05 loss: 0.1631 (0.1637) time: 2.6193 data: 0.0056 max mem: 33369 +Epoch: [2] [1240/1319] eta: 0:03:27 lr: 4.6679024331578444e-05 loss: 0.1598 (0.1638) time: 2.6418 data: 0.0056 max mem: 33369 +Epoch: [2] [1250/1319] eta: 0:03:01 lr: 4.6670429672782765e-05 loss: 0.1596 (0.1636) time: 2.6738 data: 0.0058 max mem: 33369 +Epoch: [2] [1260/1319] eta: 0:02:34 lr: 4.6661834838121084e-05 loss: 0.1454 (0.1637) time: 2.6393 data: 0.0057 max mem: 33369 +Epoch: [2] [1270/1319] eta: 0:02:08 lr: 4.665323982755382e-05 loss: 0.1454 (0.1636) time: 2.5896 data: 0.0055 max mem: 33369 +Epoch: [2] [1280/1319] eta: 0:01:42 lr: 4.664464464104137e-05 loss: 0.1533 (0.1637) time: 2.5832 data: 0.0057 max mem: 33369 +Epoch: [2] [1290/1319] eta: 0:01:16 lr: 4.6636049278544094e-05 loss: 0.1504 (0.1636) time: 2.6080 data: 0.0057 max mem: 33369 +Epoch: [2] [1300/1319] eta: 0:00:49 lr: 4.662745374002236e-05 loss: 0.1563 (0.1637) time: 2.6357 data: 0.0056 max mem: 33369 +Epoch: [2] [1310/1319] eta: 0:00:23 lr: 4.6618858025436495e-05 loss: 0.1647 (0.1640) time: 2.6454 data: 0.0055 max mem: 33369 +Epoch: [2] Total time: 0:57:42 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 2:11:26 time: 3.0651 data: 2.9785 max mem: 33369 +Test: [ 100/2573] eta: 0:04:11 time: 0.0720 data: 0.0011 max mem: 33369 +Test: [ 200/2573] eta: 0:03:28 time: 0.0732 data: 0.0012 max mem: 33369 +Test: [ 300/2573] eta: 0:03:07 time: 0.0748 data: 0.0011 max mem: 33369 +Test: [ 400/2573] eta: 0:02:54 time: 0.0749 data: 0.0012 max mem: 33369 +Test: [ 500/2573] eta: 0:02:43 time: 0.0732 data: 0.0011 max mem: 33369 +Test: [ 600/2573] eta: 0:02:33 time: 0.0731 data: 0.0011 max mem: 33369 +Test: [ 700/2573] eta: 0:02:25 time: 0.0733 data: 0.0011 max mem: 33369 +Test: [ 800/2573] eta: 0:02:16 time: 0.0766 data: 0.0011 max mem: 33369 +Test: [ 900/2573] eta: 0:02:08 time: 0.0734 data: 0.0011 max mem: 33369 +Test: [1000/2573] eta: 0:02:00 time: 0.0734 data: 0.0011 max mem: 33369 +Test: [1100/2573] eta: 0:01:52 time: 0.0735 data: 0.0011 max mem: 33369 +Test: [1200/2573] eta: 0:01:44 time: 0.0734 data: 0.0011 max mem: 33369 +Test: [1300/2573] eta: 0:01:36 time: 0.0736 data: 0.0011 max mem: 33369 +Test: [1400/2573] eta: 0:01:28 time: 0.0718 data: 0.0011 max mem: 33369 +Test: [1500/2573] eta: 0:01:21 time: 0.0734 data: 0.0011 max mem: 33369 +Test: [1600/2573] eta: 0:01:13 time: 0.0768 data: 0.0011 max mem: 33369 +Test: [1700/2573] eta: 0:01:05 time: 0.0717 data: 0.0011 max mem: 33369 +Test: [1800/2573] eta: 0:00:58 time: 0.0752 data: 0.0011 max mem: 33369 +Test: [1900/2573] eta: 0:00:50 time: 0.0718 data: 0.0011 max mem: 33369 +Test: [2000/2573] eta: 0:00:42 time: 0.0735 data: 0.0011 max mem: 33369 +Test: [2100/2573] eta: 0:00:35 time: 0.0751 data: 0.0011 max mem: 33369 +Test: [2200/2573] eta: 0:00:27 time: 0.0752 data: 0.0011 max mem: 33369 +Test: [2300/2573] eta: 0:00:20 time: 0.0752 data: 0.0011 max mem: 33369 +Test: [2400/2573] eta: 0:00:12 time: 0.0704 data: 0.0011 max mem: 33369 +Test: [2500/2573] eta: 0:00:05 time: 0.0735 data: 0.0011 max mem: 33369 +Test: Total time: 0:03:12 +Final results: +Mean IoU is 44.86 + + precision@0.5 = 47.96 + precision@0.6 = 39.50 + precision@0.7 = 30.60 + precision@0.8 = 19.73 + precision@0.9 = 6.29 + overall IoU = 47.08 + +Average object IoU 44.861104744889154 +Overall IoU 47.08278274536133 +Better epoch: 2 + +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [3] [ 0/1319] eta: 1:26:35 lr: 4.661112173174161e-05 loss: 0.1098 (0.1098) time: 3.9388 data: 1.2563 max mem: 33369 +Epoch: [3] [ 10/1319] eta: 0:59:05 lr: 4.660252568252458e-05 loss: 0.1239 (0.1294) time: 2.7084 data: 0.1195 max mem: 33369 +Epoch: [3] [ 20/1319] eta: 0:57:36 lr: 4.6593929457128314e-05 loss: 0.1239 (0.1321) time: 2.5973 data: 0.0059 max mem: 33369 +Epoch: [3] [ 30/1319] eta: 0:56:40 lr: 4.6585333055513096e-05 loss: 0.1271 (0.1347) time: 2.5998 data: 0.0059 max mem: 33369 +Epoch: [3] [ 40/1319] eta: 0:56:12 lr: 4.657673647763916e-05 loss: 0.1447 (0.1456) time: 2.6110 data: 0.0058 max mem: 33369 +Epoch: [3] [ 50/1319] eta: 0:55:52 lr: 4.656813972346675e-05 loss: 0.1447 (0.1445) time: 2.6481 data: 0.0059 max mem: 33369 +Epoch: [3] [ 60/1319] eta: 0:55:16 lr: 4.655954279295608e-05 loss: 0.1257 (0.1444) time: 2.6285 data: 0.0059 max mem: 33369 +Epoch: [3] [ 70/1319] eta: 0:54:50 lr: 4.655094568606738e-05 loss: 0.1420 (0.1453) time: 2.6141 data: 0.0058 max mem: 33369 +Epoch: [3] [ 80/1319] eta: 0:54:24 lr: 4.6542348402760813e-05 loss: 0.1549 (0.1465) time: 2.6366 data: 0.0058 max mem: 33369 +Epoch: [3] [ 90/1319] eta: 0:53:59 lr: 4.653375094299656e-05 loss: 0.1533 (0.1485) time: 2.6407 data: 0.0058 max mem: 33369 +Epoch: [3] [ 100/1319] eta: 0:53:34 lr: 4.652515330673476e-05 loss: 0.1332 (0.1489) time: 2.6447 data: 0.0058 max mem: 33369 +Epoch: [3] [ 110/1319] eta: 0:53:08 lr: 4.651655549393556e-05 loss: 0.1283 (0.1478) time: 2.6437 data: 0.0060 max mem: 33369 +Epoch: [3] [ 120/1319] eta: 0:52:39 lr: 4.650795750455908e-05 loss: 0.1283 (0.1472) time: 2.6278 data: 0.0062 max mem: 33369 +Epoch: [3] [ 130/1319] eta: 0:52:13 lr: 4.649935933856541e-05 loss: 0.1405 (0.1482) time: 2.6242 data: 0.0060 max mem: 33369 +Epoch: [3] [ 140/1319] eta: 0:51:46 lr: 4.6490760995914644e-05 loss: 0.1355 (0.1469) time: 2.6351 data: 0.0060 max mem: 33369 +Epoch: [3] [ 150/1319] eta: 0:51:23 lr: 4.648216247656684e-05 loss: 0.1158 (0.1471) time: 2.6521 data: 0.0061 max mem: 33369 +Epoch: [3] [ 160/1319] eta: 0:50:57 lr: 4.647356378048206e-05 loss: 0.1454 (0.1468) time: 2.6582 data: 0.0059 max mem: 33369 +Epoch: [3] [ 170/1319] eta: 0:50:30 lr: 4.646496490762032e-05 loss: 0.1486 (0.1473) time: 2.6387 data: 0.0058 max mem: 33369 +Epoch: [3] [ 180/1319] eta: 0:50:03 lr: 4.645636585794164e-05 loss: 0.1456 (0.1465) time: 2.6274 data: 0.0060 max mem: 33369 +Epoch: [3] [ 190/1319] eta: 0:49:34 lr: 4.644776663140602e-05 loss: 0.1383 (0.1476) time: 2.6060 data: 0.0060 max mem: 33369 +Epoch: [3] [ 200/1319] eta: 0:49:08 lr: 4.6439167227973446e-05 loss: 0.1623 (0.1484) time: 2.6174 data: 0.0059 max mem: 33369 +Epoch: [3] [ 210/1319] eta: 0:48:39 lr: 4.643056764760387e-05 loss: 0.1480 (0.1491) time: 2.6203 data: 0.0059 max mem: 33369 +Epoch: [3] [ 220/1319] eta: 0:48:14 lr: 4.642196789025724e-05 loss: 0.1494 (0.1493) time: 2.6220 data: 0.0058 max mem: 33369 +Epoch: [3] [ 230/1319] eta: 0:47:47 lr: 4.641336795589349e-05 loss: 0.1525 (0.1492) time: 2.6341 data: 0.0057 max mem: 33369 +Epoch: [3] [ 240/1319] eta: 0:47:20 lr: 4.6404767844472526e-05 loss: 0.1337 (0.1490) time: 2.6159 data: 0.0058 max mem: 33369 +Epoch: [3] [ 250/1319] eta: 0:46:54 lr: 4.639616755595424e-05 loss: 0.1337 (0.1492) time: 2.6343 data: 0.0058 max mem: 33369 +Epoch: [3] [ 260/1319] eta: 0:46:26 lr: 4.638756709029851e-05 loss: 0.1485 (0.1489) time: 2.6253 data: 0.0057 max mem: 33369 +Epoch: [3] [ 270/1319] eta: 0:46:01 lr: 4.6378966447465196e-05 loss: 0.1467 (0.1496) time: 2.6270 data: 0.0056 max mem: 33369 +Epoch: [3] [ 280/1319] eta: 0:45:36 lr: 4.637036562741414e-05 loss: 0.1547 (0.1500) time: 2.6589 data: 0.0057 max mem: 33369 +Epoch: [3] [ 290/1319] eta: 0:45:10 lr: 4.636176463010516e-05 loss: 0.1583 (0.1505) time: 2.6485 data: 0.0058 max mem: 33369 +Epoch: [3] [ 300/1319] eta: 0:44:43 lr: 4.635316345549808e-05 loss: 0.1146 (0.1498) time: 2.6288 data: 0.0058 max mem: 33369 +Epoch: [3] [ 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+Epoch: [3] [ 390/1319] eta: 0:40:43 lr: 4.627574489897873e-05 loss: 0.1198 (0.1489) time: 2.6321 data: 0.0060 max mem: 33369 +Epoch: [3] [ 400/1319] eta: 0:40:17 lr: 4.626714194917605e-05 loss: 0.1274 (0.1487) time: 2.6189 data: 0.0060 max mem: 33369 +Epoch: [3] [ 410/1319] eta: 0:39:51 lr: 4.625853882163199e-05 loss: 0.1368 (0.1486) time: 2.6262 data: 0.0058 max mem: 33369 +Epoch: [3] [ 420/1319] eta: 0:39:24 lr: 4.624993551630613e-05 loss: 0.1439 (0.1487) time: 2.6238 data: 0.0059 max mem: 33369 +Epoch: [3] [ 430/1319] eta: 0:38:57 lr: 4.624133203315806e-05 loss: 0.1321 (0.1485) time: 2.5941 data: 0.0059 max mem: 33369 +Epoch: [3] [ 440/1319] eta: 0:38:30 lr: 4.6232728372147346e-05 loss: 0.1321 (0.1483) time: 2.6110 data: 0.0058 max mem: 33369 +Epoch: [3] [ 450/1319] eta: 0:38:04 lr: 4.6224124533233514e-05 loss: 0.1417 (0.1485) time: 2.6167 data: 0.0058 max mem: 33369 +Epoch: [3] [ 460/1319] eta: 0:37:38 lr: 4.621552051637611e-05 loss: 0.1473 (0.1488) time: 2.6458 data: 0.0058 max mem: 33369 +Epoch: [3] [ 470/1319] eta: 0:37:11 lr: 4.620691632153463e-05 loss: 0.1416 (0.1484) time: 2.6299 data: 0.0057 max mem: 33369 +Epoch: [3] [ 480/1319] eta: 0:36:44 lr: 4.619831194866858e-05 loss: 0.1306 (0.1483) time: 2.5738 data: 0.0057 max mem: 33369 +Epoch: [3] [ 490/1319] eta: 0:36:17 lr: 4.618970739773742e-05 loss: 0.1324 (0.1481) time: 2.5759 data: 0.0057 max mem: 33369 +Epoch: [3] [ 500/1319] eta: 0:35:51 lr: 4.618110266870061e-05 loss: 0.1563 (0.1485) time: 2.6162 data: 0.0058 max mem: 33369 +Epoch: [3] [ 510/1319] eta: 0:35:24 lr: 4.6172497761517596e-05 loss: 0.1621 (0.1486) time: 2.6359 data: 0.0059 max mem: 33369 +Epoch: [3] [ 520/1319] eta: 0:34:59 lr: 4.6163892676147796e-05 loss: 0.1537 (0.1488) time: 2.6299 data: 0.0057 max mem: 33369 +Epoch: [3] [ 530/1319] eta: 0:34:32 lr: 4.615528741255061e-05 loss: 0.1410 (0.1488) time: 2.6175 data: 0.0058 max mem: 33369 +Epoch: [3] [ 540/1319] eta: 0:34:06 lr: 4.6146681970685424e-05 loss: 0.1410 (0.1489) time: 2.6180 data: 0.0058 max mem: 33369 +Epoch: [3] [ 550/1319] eta: 0:33:39 lr: 4.613807635051161e-05 loss: 0.1372 (0.1487) time: 2.6303 data: 0.0059 max mem: 33369 +Epoch: [3] [ 560/1319] eta: 0:33:12 lr: 4.612947055198852e-05 loss: 0.1632 (0.1495) time: 2.5958 data: 0.0060 max mem: 33369 +Epoch: [3] [ 570/1319] eta: 0:32:46 lr: 4.612086457507548e-05 loss: 0.1946 (0.1499) time: 2.6174 data: 0.0058 max mem: 33369 +Epoch: [3] [ 580/1319] eta: 0:32:20 lr: 4.611225841973181e-05 loss: 0.1329 (0.1495) time: 2.6394 data: 0.0057 max mem: 33369 +Epoch: [3] [ 590/1319] eta: 0:31:54 lr: 4.610365208591681e-05 loss: 0.1194 (0.1490) time: 2.6324 data: 0.0058 max mem: 33369 +Epoch: [3] [ 600/1319] eta: 0:31:28 lr: 4.609504557358975e-05 loss: 0.1264 (0.1490) time: 2.6342 data: 0.0061 max mem: 33369 +Epoch: [3] [ 610/1319] eta: 0:31:02 lr: 4.60864388827099e-05 loss: 0.1454 (0.1491) time: 2.6240 data: 0.0061 max mem: 33369 +Epoch: [3] [ 620/1319] eta: 0:30:35 lr: 4.6077832013236505e-05 loss: 0.1645 (0.1492) time: 2.6204 data: 0.0060 max mem: 33369 +Epoch: [3] [ 630/1319] eta: 0:30:09 lr: 4.606922496512879e-05 loss: 0.1647 (0.1497) time: 2.6163 data: 0.0061 max mem: 33369 +Epoch: [3] [ 640/1319] eta: 0:29:42 lr: 4.606061773834596e-05 loss: 0.1475 (0.1500) time: 2.6090 data: 0.0060 max mem: 33369 +Epoch: [3] [ 650/1319] eta: 0:29:16 lr: 4.60520103328472e-05 loss: 0.1425 (0.1502) time: 2.6297 data: 0.0059 max mem: 33369 +Epoch: [3] [ 660/1319] eta: 0:28:49 lr: 4.60434027485917e-05 loss: 0.1416 (0.1502) time: 2.5926 data: 0.0058 max mem: 33369 +Epoch: [3] [ 670/1319] eta: 0:28:23 lr: 4.6034794985538615e-05 loss: 0.1473 (0.1502) time: 2.5602 data: 0.0060 max mem: 33369 +Epoch: [3] [ 680/1319] eta: 0:27:56 lr: 4.602618704364706e-05 loss: 0.1473 (0.1503) time: 2.6024 data: 0.0062 max mem: 33369 +Epoch: [3] [ 690/1319] eta: 0:27:30 lr: 4.601757892287618e-05 loss: 0.1475 (0.1506) time: 2.6267 data: 0.0063 max mem: 33369 +Epoch: [3] [ 700/1319] eta: 0:27:04 lr: 4.600897062318506e-05 loss: 0.1399 (0.1510) time: 2.6348 data: 0.0061 max mem: 33369 +Epoch: [3] [ 710/1319] eta: 0:26:38 lr: 4.600036214453279e-05 loss: 0.1399 (0.1508) time: 2.6226 data: 0.0060 max mem: 33369 +Epoch: [3] [ 720/1319] eta: 0:26:11 lr: 4.599175348687844e-05 loss: 0.1391 (0.1506) time: 2.6187 data: 0.0062 max mem: 33369 +Epoch: [3] [ 730/1319] eta: 0:25:45 lr: 4.598314465018106e-05 loss: 0.1260 (0.1506) time: 2.6379 data: 0.0061 max mem: 33369 +Epoch: [3] [ 740/1319] eta: 0:25:19 lr: 4.5974535634399665e-05 loss: 0.1399 (0.1505) time: 2.6547 data: 0.0060 max mem: 33369 +Epoch: [3] [ 750/1319] eta: 0:24:53 lr: 4.596592643949328e-05 loss: 0.1399 (0.1504) time: 2.6645 data: 0.0061 max mem: 33369 +Epoch: [3] [ 760/1319] eta: 0:24:27 lr: 4.595731706542089e-05 loss: 0.1386 (0.1505) time: 2.6533 data: 0.0059 max mem: 33369 +Epoch: [3] [ 770/1319] eta: 0:24:01 lr: 4.5948707512141485e-05 loss: 0.1467 (0.1505) time: 2.6338 data: 0.0056 max mem: 33369 +Epoch: [3] [ 780/1319] eta: 0:23:34 lr: 4.594009777961402e-05 loss: 0.1274 (0.1501) time: 2.5997 data: 0.0059 max mem: 33369 +Epoch: [3] [ 790/1319] eta: 0:23:08 lr: 4.593148786779743e-05 loss: 0.1281 (0.1507) time: 2.5971 data: 0.0062 max mem: 33369 +Epoch: [3] [ 800/1319] eta: 0:22:42 lr: 4.592287777665063e-05 loss: 0.1515 (0.1506) time: 2.6137 data: 0.0060 max mem: 33369 +Epoch: [3] [ 810/1319] eta: 0:22:16 lr: 4.5914267506132555e-05 loss: 0.1429 (0.1508) time: 2.6191 data: 0.0059 max mem: 33369 +Epoch: [3] [ 820/1319] eta: 0:21:49 lr: 4.590565705620206e-05 loss: 0.1456 (0.1507) time: 2.6275 data: 0.0060 max mem: 33369 +Epoch: [3] [ 830/1319] eta: 0:21:23 lr: 4.589704642681802e-05 loss: 0.1388 (0.1506) time: 2.6407 data: 0.0060 max mem: 33369 +Epoch: [3] [ 840/1319] eta: 0:20:57 lr: 4.58884356179393e-05 loss: 0.1531 (0.1509) time: 2.6330 data: 0.0061 max mem: 33369 +Epoch: [3] [ 850/1319] eta: 0:20:31 lr: 4.5879824629524725e-05 loss: 0.1494 (0.1506) time: 2.6227 data: 0.0060 max mem: 33369 +Epoch: [3] [ 860/1319] eta: 0:20:04 lr: 4.5871213461533106e-05 loss: 0.1437 (0.1506) time: 2.6259 data: 0.0060 max mem: 33369 +Epoch: [3] [ 870/1319] eta: 0:19:38 lr: 4.5862602113923244e-05 loss: 0.1387 (0.1504) time: 2.6097 data: 0.0059 max mem: 33369 +Epoch: [3] [ 880/1319] eta: 0:19:12 lr: 4.585399058665391e-05 loss: 0.1206 (0.1504) time: 2.6152 data: 0.0059 max mem: 33369 +Epoch: [3] [ 890/1319] eta: 0:18:45 lr: 4.5845378879683885e-05 loss: 0.1227 (0.1502) time: 2.6010 data: 0.0061 max mem: 33369 +Epoch: [3] [ 900/1319] eta: 0:18:19 lr: 4.583676699297189e-05 loss: 0.1441 (0.1504) time: 2.5742 data: 0.0061 max mem: 33369 +Epoch: [3] [ 910/1319] eta: 0:17:53 lr: 4.582815492647665e-05 loss: 0.1445 (0.1502) time: 2.6092 data: 0.0061 max mem: 33369 +Epoch: [3] [ 920/1319] eta: 0:17:26 lr: 4.5819542680156885e-05 loss: 0.1448 (0.1507) time: 2.6379 data: 0.0062 max mem: 33369 +Epoch: [3] [ 930/1319] eta: 0:17:00 lr: 4.5810930253971277e-05 loss: 0.1391 (0.1506) time: 2.6069 data: 0.0061 max mem: 33369 +Epoch: [3] [ 940/1319] eta: 0:16:34 lr: 4.580231764787849e-05 loss: 0.1590 (0.1509) time: 2.6020 data: 0.0059 max mem: 33369 +Epoch: [3] [ 950/1319] eta: 0:16:08 lr: 4.579370486183719e-05 loss: 0.1461 (0.1509) time: 2.6299 data: 0.0060 max mem: 33369 +Epoch: [3] [ 960/1319] eta: 0:15:41 lr: 4.5785091895806004e-05 loss: 0.1288 (0.1508) time: 2.6143 data: 0.0061 max mem: 33369 +Epoch: [3] [ 970/1319] eta: 0:15:15 lr: 4.577647874974354e-05 loss: 0.1296 (0.1507) time: 2.5861 data: 0.0061 max mem: 33369 +Epoch: [3] [ 980/1319] eta: 0:14:49 lr: 4.57678654236084e-05 loss: 0.1296 (0.1504) time: 2.6008 data: 0.0062 max mem: 33369 +Epoch: [3] [ 990/1319] eta: 0:14:23 lr: 4.575925191735917e-05 loss: 0.1260 (0.1504) time: 2.6290 data: 0.0061 max mem: 33369 +Epoch: [3] [1000/1319] eta: 0:13:56 lr: 4.57506382309544e-05 loss: 0.1357 (0.1508) time: 2.6282 data: 0.0060 max mem: 33369 +Epoch: [3] [1010/1319] eta: 0:13:30 lr: 4.574202436435264e-05 loss: 0.1482 (0.1509) time: 2.6143 data: 0.0060 max mem: 33369 +Epoch: [3] [1020/1319] eta: 0:13:04 lr: 4.573341031751242e-05 loss: 0.1482 (0.1508) time: 2.6386 data: 0.0059 max mem: 33369 +Epoch: [3] [1030/1319] eta: 0:12:38 lr: 4.5724796090392234e-05 loss: 0.1334 (0.1509) time: 2.6460 data: 0.0059 max mem: 33369 +Epoch: [3] [1040/1319] eta: 0:12:11 lr: 4.571618168295058e-05 loss: 0.1281 (0.1507) time: 2.6133 data: 0.0060 max mem: 33369 +Epoch: [3] [1050/1319] eta: 0:11:45 lr: 4.570756709514592e-05 loss: 0.1208 (0.1505) time: 2.5937 data: 0.0062 max mem: 33369 +Epoch: [3] [1060/1319] eta: 0:11:19 lr: 4.569895232693671e-05 loss: 0.1258 (0.1506) time: 2.6120 data: 0.0061 max mem: 33369 +Epoch: [3] [1070/1319] eta: 0:10:53 lr: 4.569033737828139e-05 loss: 0.1345 (0.1505) time: 2.6262 data: 0.0059 max mem: 33369 +Epoch: [3] [1080/1319] eta: 0:10:26 lr: 4.568172224913836e-05 loss: 0.1210 (0.1502) time: 2.6162 data: 0.0060 max mem: 33369 +Epoch: [3] [1090/1319] eta: 0:10:00 lr: 4.567310693946603e-05 loss: 0.1279 (0.1502) time: 2.6370 data: 0.0059 max mem: 33369 +Epoch: [3] [1100/1319] eta: 0:09:34 lr: 4.566449144922278e-05 loss: 0.1359 (0.1500) time: 2.6441 data: 0.0059 max mem: 33369 +Epoch: [3] [1110/1319] eta: 0:09:08 lr: 4.565587577836695e-05 loss: 0.1257 (0.1499) time: 2.6507 data: 0.0060 max mem: 33369 +Epoch: [3] [1120/1319] eta: 0:08:42 lr: 4.5647259926856906e-05 loss: 0.1505 (0.1500) time: 2.6470 data: 0.0062 max mem: 33369 +Epoch: [3] [1130/1319] eta: 0:08:15 lr: 4.563864389465096e-05 loss: 0.1388 (0.1499) time: 2.6208 data: 0.0064 max mem: 33369 +Epoch: [3] [1140/1319] eta: 0:07:49 lr: 4.563002768170741e-05 loss: 0.1353 (0.1499) time: 2.6303 data: 0.0062 max mem: 33369 +Epoch: [3] [1150/1319] eta: 0:07:23 lr: 4.562141128798457e-05 loss: 0.1433 (0.1499) time: 2.6417 data: 0.0060 max mem: 33369 +Epoch: [3] [1160/1319] eta: 0:06:57 lr: 4.561279471344068e-05 loss: 0.1414 (0.1500) time: 2.6370 data: 0.0060 max mem: 33369 +Epoch: [3] [1170/1319] eta: 0:06:30 lr: 4.5604177958034e-05 loss: 0.1366 (0.1502) time: 2.6242 data: 0.0063 max mem: 33369 +Epoch: [3] [1180/1319] eta: 0:06:04 lr: 4.559556102172276e-05 loss: 0.1457 (0.1501) time: 2.6154 data: 0.0062 max mem: 33369 +Epoch: [3] [1190/1319] eta: 0:05:38 lr: 4.5586943904465176e-05 loss: 0.1358 (0.1501) time: 2.6336 data: 0.0062 max mem: 33369 +Epoch: [3] [1200/1319] eta: 0:05:12 lr: 4.557832660621944e-05 loss: 0.1286 (0.1500) time: 2.6277 data: 0.0062 max mem: 33369 +Epoch: [3] [1210/1319] eta: 0:04:45 lr: 4.556970912694373e-05 loss: 0.1446 (0.1500) time: 2.6106 data: 0.0060 max mem: 33369 +Epoch: [3] [1220/1319] eta: 0:04:19 lr: 4.5561091466596205e-05 loss: 0.1554 (0.1500) time: 2.6224 data: 0.0060 max mem: 33369 +Epoch: [3] [1230/1319] eta: 0:03:53 lr: 4.555247362513501e-05 loss: 0.1490 (0.1499) time: 2.6177 data: 0.0061 max mem: 33369 +Epoch: [3] [1240/1319] eta: 0:03:27 lr: 4.5543855602518245e-05 loss: 0.1361 (0.1499) time: 2.6101 data: 0.0061 max mem: 33369 +Epoch: [3] [1250/1319] eta: 0:03:01 lr: 4.553523739870403e-05 loss: 0.1323 (0.1496) time: 2.6132 data: 0.0059 max mem: 33369 +Epoch: [3] [1260/1319] eta: 0:02:34 lr: 4.552661901365045e-05 loss: 0.1233 (0.1496) time: 2.6216 data: 0.0059 max mem: 33369 +Epoch: [3] [1270/1319] eta: 0:02:08 lr: 4.551800044731557e-05 loss: 0.1298 (0.1494) time: 2.6327 data: 0.0059 max mem: 33369 +Epoch: [3] [1280/1319] eta: 0:01:42 lr: 4.550938169965743e-05 loss: 0.1228 (0.1494) time: 2.6380 data: 0.0059 max mem: 33369 +Epoch: [3] [1290/1319] eta: 0:01:16 lr: 4.550076277063406e-05 loss: 0.1294 (0.1493) time: 2.5920 data: 0.0060 max mem: 33369 +Epoch: [3] [1300/1319] eta: 0:00:49 lr: 4.549214366020347e-05 loss: 0.1441 (0.1496) time: 2.5721 data: 0.0060 max mem: 33369 +Epoch: [3] [1310/1319] eta: 0:00:23 lr: 4.5483524368323656e-05 loss: 0.1503 (0.1497) time: 2.6189 data: 0.0060 max mem: 33369 +Epoch: [3] Total time: 0:57:40 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 2:58:48 time: 4.1696 data: 4.0903 max mem: 33369 +Test: [ 100/2573] eta: 0:04:38 time: 0.0717 data: 0.0011 max mem: 33369 +Test: [ 200/2573] eta: 0:03:41 time: 0.0730 data: 0.0012 max mem: 33369 +Test: [ 300/2573] eta: 0:03:15 time: 0.0748 data: 0.0011 max mem: 33369 +Test: [ 400/2573] eta: 0:03:00 time: 0.0750 data: 0.0011 max mem: 33369 +Test: [ 500/2573] eta: 0:02:47 time: 0.0733 data: 0.0011 max mem: 33369 +Test: [ 600/2573] eta: 0:02:37 time: 0.0733 data: 0.0011 max mem: 33369 +Test: [ 700/2573] eta: 0:02:28 time: 0.0733 data: 0.0011 max mem: 33369 +Test: [ 800/2573] eta: 0:02:19 time: 0.0767 data: 0.0011 max mem: 33369 +Test: [ 900/2573] eta: 0:02:10 time: 0.0736 data: 0.0011 max mem: 33369 +Test: [1000/2573] eta: 0:02:02 time: 0.0737 data: 0.0011 max mem: 33369 +Test: [1100/2573] eta: 0:01:53 time: 0.0737 data: 0.0011 max mem: 33369 +Test: [1200/2573] eta: 0:01:45 time: 0.0737 data: 0.0011 max mem: 33369 +Test: [1300/2573] eta: 0:01:37 time: 0.0739 data: 0.0011 max mem: 33369 +Test: [1400/2573] eta: 0:01:29 time: 0.0721 data: 0.0011 max mem: 33369 +Test: [1500/2573] eta: 0:01:22 time: 0.0739 data: 0.0012 max mem: 33369 +Test: [1600/2573] eta: 0:01:14 time: 0.0772 data: 0.0011 max mem: 33369 +Test: [1700/2573] eta: 0:01:06 time: 0.0723 data: 0.0011 max mem: 33369 +Test: [1800/2573] eta: 0:00:58 time: 0.0756 data: 0.0011 max mem: 33369 +Test: [1900/2573] eta: 0:00:51 time: 0.0722 data: 0.0011 max mem: 33369 +Test: [2000/2573] eta: 0:00:43 time: 0.0739 data: 0.0011 max mem: 33369 +Test: [2100/2573] eta: 0:00:35 time: 0.0755 data: 0.0011 max mem: 33369 +Test: [2200/2573] eta: 0:00:28 time: 0.0755 data: 0.0011 max mem: 33369 +Test: [2300/2573] eta: 0:00:20 time: 0.0755 data: 0.0011 max mem: 33369 +Test: [2400/2573] eta: 0:00:13 time: 0.0707 data: 0.0011 max mem: 33369 +Test: [2500/2573] eta: 0:00:05 time: 0.0738 data: 0.0011 max mem: 33369 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: Total time: 0:03:14 +Final results: +Mean IoU is 48.59 + + precision@0.5 = 52.49 + precision@0.6 = 44.55 + precision@0.7 = 35.05 + precision@0.8 = 23.61 + precision@0.9 = 8.42 + overall IoU = 50.46 + +Average object IoU 48.585875015874706 +Overall IoU 50.45649337768555 +Better epoch: 3 + +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [4] [ 0/1319] eta: 1:32:25 lr: 4.547576685045799e-05 loss: 0.1063 (0.1063) time: 4.2041 data: 1.5875 max mem: 33369 +Epoch: [4] [ 10/1319] eta: 1:00:46 lr: 4.546714721370884e-05 loss: 0.1299 (0.1298) time: 2.7858 data: 0.1501 max mem: 33369 +Epoch: [4] [ 20/1319] eta: 0:58:35 lr: 4.5458527395388535e-05 loss: 0.1273 (0.1214) time: 2.6318 data: 0.0062 max mem: 33369 +Epoch: [4] [ 30/1319] eta: 0:57:23 lr: 4.544990739545498e-05 loss: 0.1273 (0.1277) time: 2.6085 data: 0.0061 max mem: 33369 +Epoch: [4] [ 40/1319] eta: 0:56:30 lr: 4.544128721386609e-05 loss: 0.1350 (0.1290) time: 2.5924 data: 0.0060 max mem: 33369 +Epoch: [4] [ 50/1319] eta: 0:56:12 lr: 4.543266685057974e-05 loss: 0.0970 (0.1241) time: 2.6363 data: 0.0060 max mem: 33369 +Epoch: [4] [ 60/1319] eta: 0:55:34 lr: 4.54240463055538e-05 loss: 0.0996 (0.1229) time: 2.6435 data: 0.0061 max mem: 33369 +Epoch: [4] [ 70/1319] eta: 0:55:00 lr: 4.541542557874611e-05 loss: 0.1071 (0.1211) time: 2.6040 data: 0.0061 max mem: 33369 +Epoch: [4] [ 80/1319] eta: 0:54:39 lr: 4.540680467011449e-05 loss: 0.1211 (0.1271) time: 2.6431 data: 0.0061 max mem: 33369 +Epoch: [4] [ 90/1319] eta: 0:54:09 lr: 4.5398183579616753e-05 loss: 0.1384 (0.1275) time: 2.6498 data: 0.0060 max mem: 33369 +Epoch: [4] [ 100/1319] eta: 0:53:39 lr: 4.5389562307210684e-05 loss: 0.1247 (0.1288) time: 2.6175 data: 0.0060 max mem: 33369 +Epoch: [4] [ 110/1319] eta: 0:53:09 lr: 4.5380940852854056e-05 loss: 0.1247 (0.1303) time: 2.6113 data: 0.0059 max mem: 33369 +Epoch: [4] [ 120/1319] eta: 0:52:45 lr: 4.537231921650461e-05 loss: 0.1246 (0.1302) time: 2.6360 data: 0.0059 max mem: 33369 +Epoch: [4] [ 130/1319] eta: 0:52:16 lr: 4.53636973981201e-05 loss: 0.1323 (0.1312) time: 2.6352 data: 0.0061 max mem: 33369 +Epoch: [4] [ 140/1319] eta: 0:51:44 lr: 4.535507539765821e-05 loss: 0.1378 (0.1322) time: 2.5892 data: 0.0061 max mem: 33369 +Epoch: [4] [ 150/1319] eta: 0:51:16 lr: 4.534645321507665e-05 loss: 0.1346 (0.1333) time: 2.5946 data: 0.0060 max mem: 33369 +Epoch: [4] [ 160/1319] eta: 0:50:50 lr: 4.53378308503331e-05 loss: 0.1168 (0.1325) time: 2.6234 data: 0.0060 max mem: 33369 +Epoch: [4] [ 170/1319] eta: 0:50:24 lr: 4.532920830338521e-05 loss: 0.1344 (0.1340) time: 2.6335 data: 0.0060 max mem: 33369 +Epoch: [4] [ 180/1319] eta: 0:49:56 lr: 4.5320585574190625e-05 loss: 0.1344 (0.1337) time: 2.6229 data: 0.0059 max mem: 33369 +Epoch: [4] [ 190/1319] eta: 0:49:32 lr: 4.5311962662706955e-05 loss: 0.1240 (0.1342) time: 2.6399 data: 0.0060 max mem: 33369 +Epoch: [4] [ 200/1319] eta: 0:49:04 lr: 4.5303339568891794e-05 loss: 0.1159 (0.1327) time: 2.6390 data: 0.0063 max mem: 33369 +Epoch: [4] [ 210/1319] eta: 0:48:39 lr: 4.529471629270274e-05 loss: 0.1176 (0.1324) time: 2.6271 data: 0.0063 max mem: 33369 +Epoch: [4] [ 220/1319] eta: 0:48:12 lr: 4.5286092834097356e-05 loss: 0.1176 (0.1319) time: 2.6306 data: 0.0061 max mem: 33369 +Epoch: [4] [ 230/1319] eta: 0:47:46 lr: 4.527746919303318e-05 loss: 0.1052 (0.1320) time: 2.6266 data: 0.0060 max mem: 33369 +Epoch: [4] [ 240/1319] eta: 0:47:18 lr: 4.5268845369467734e-05 loss: 0.1104 (0.1317) time: 2.6161 data: 0.0060 max mem: 33369 +Epoch: [4] [ 250/1319] eta: 0:46:49 lr: 4.526022136335852e-05 loss: 0.1232 (0.1317) time: 2.5885 data: 0.0060 max mem: 33369 +Epoch: [4] [ 260/1319] eta: 0:46:23 lr: 4.525159717466304e-05 loss: 0.1278 (0.1332) time: 2.6021 data: 0.0061 max mem: 33369 +Epoch: [4] [ 270/1319] eta: 0:45:55 lr: 4.524297280333875e-05 loss: 0.1278 (0.1331) time: 2.6096 data: 0.0062 max mem: 33369 +Epoch: [4] [ 280/1319] eta: 0:45:29 lr: 4.5234348249343114e-05 loss: 0.1176 (0.1332) time: 2.6147 data: 0.0061 max mem: 33369 +Epoch: [4] [ 290/1319] eta: 0:45:04 lr: 4.522572351263354e-05 loss: 0.1176 (0.1330) time: 2.6411 data: 0.0060 max mem: 33369 +Epoch: [4] [ 300/1319] eta: 0:44:37 lr: 4.521709859316746e-05 loss: 0.1398 (0.1332) time: 2.6395 data: 0.0061 max mem: 33369 +Epoch: [4] [ 310/1319] eta: 0:44:11 lr: 4.520847349090225e-05 loss: 0.1278 (0.1328) time: 2.6242 data: 0.0061 max mem: 33369 +Epoch: [4] [ 320/1319] eta: 0:43:44 lr: 4.5199848205795306e-05 loss: 0.1172 (0.1327) time: 2.6105 data: 0.0060 max mem: 33369 +Epoch: [4] [ 330/1319] eta: 0:43:18 lr: 4.519122273780396e-05 loss: 0.1172 (0.1321) time: 2.6137 data: 0.0059 max mem: 33369 +Epoch: [4] [ 340/1319] eta: 0:42:50 lr: 4.518259708688556e-05 loss: 0.1148 (0.1325) time: 2.6124 data: 0.0061 max mem: 33369 +Epoch: [4] [ 350/1319] eta: 0:42:24 lr: 4.5173971252997424e-05 loss: 0.1219 (0.1322) time: 2.6152 data: 0.0061 max mem: 33369 +Epoch: [4] [ 360/1319] eta: 0:41:58 lr: 4.5165345236096837e-05 loss: 0.1253 (0.1326) time: 2.6232 data: 0.0058 max mem: 33369 +Epoch: [4] [ 370/1319] eta: 0:41:30 lr: 4.5156719036141086e-05 loss: 0.1287 (0.1328) time: 2.5867 data: 0.0059 max mem: 33369 +Epoch: [4] [ 380/1319] eta: 0:41:03 lr: 4.5148092653087434e-05 loss: 0.1350 (0.1332) time: 2.5832 data: 0.0061 max mem: 33369 +Epoch: [4] [ 390/1319] eta: 0:40:37 lr: 4.5139466086893116e-05 loss: 0.1400 (0.1332) time: 2.6209 data: 0.0062 max mem: 33369 +Epoch: [4] [ 400/1319] eta: 0:40:12 lr: 4.513083933751536e-05 loss: 0.1278 (0.1333) time: 2.6437 data: 0.0062 max mem: 33369 +Epoch: [4] [ 410/1319] eta: 0:39:46 lr: 4.512221240491136e-05 loss: 0.1167 (0.1333) time: 2.6578 data: 0.0061 max mem: 33369 +Epoch: [4] [ 420/1319] eta: 0:39:20 lr: 4.5113585289038304e-05 loss: 0.1209 (0.1335) time: 2.6501 data: 0.0061 max mem: 33369 +Epoch: [4] [ 430/1319] eta: 0:38:53 lr: 4.510495798985335e-05 loss: 0.1288 (0.1333) time: 2.6147 data: 0.0061 max mem: 33369 +Epoch: [4] [ 440/1319] eta: 0:38:26 lr: 4.509633050731365e-05 loss: 0.1243 (0.1337) time: 2.5859 data: 0.0062 max mem: 33369 +Epoch: [4] [ 450/1319] eta: 0:38:00 lr: 4.5087702841376343e-05 loss: 0.1208 (0.1332) time: 2.5959 data: 0.0061 max mem: 33369 +Epoch: [4] [ 460/1319] eta: 0:37:34 lr: 4.507907499199851e-05 loss: 0.1109 (0.1335) time: 2.6252 data: 0.0059 max mem: 33369 +Epoch: [4] [ 470/1319] eta: 0:37:07 lr: 4.507044695913725e-05 loss: 0.1432 (0.1340) time: 2.6324 data: 0.0059 max mem: 33369 +Epoch: [4] [ 480/1319] eta: 0:36:41 lr: 4.506181874274963e-05 loss: 0.1218 (0.1335) time: 2.6153 data: 0.0058 max mem: 33369 +Epoch: [4] [ 490/1319] eta: 0:36:15 lr: 4.5053190342792706e-05 loss: 0.1091 (0.1337) time: 2.6236 data: 0.0058 max mem: 33369 +Epoch: [4] [ 500/1319] eta: 0:35:48 lr: 4.50445617592235e-05 loss: 0.1053 (0.1337) time: 2.6250 data: 0.0060 max mem: 33369 +Epoch: [4] [ 510/1319] eta: 0:35:22 lr: 4.503593299199903e-05 loss: 0.1367 (0.1336) time: 2.6075 data: 0.0061 max mem: 33369 +Epoch: [4] [ 520/1319] eta: 0:34:56 lr: 4.502730404107628e-05 loss: 0.1289 (0.1332) time: 2.6105 data: 0.0060 max mem: 33369 +Epoch: [4] [ 530/1319] eta: 0:34:29 lr: 4.5018674906412226e-05 loss: 0.1289 (0.1333) time: 2.6115 data: 0.0059 max mem: 33369 +Epoch: [4] [ 540/1319] eta: 0:34:02 lr: 4.5010045587963815e-05 loss: 0.1373 (0.1336) time: 2.5979 data: 0.0061 max mem: 33369 +Epoch: [4] [ 550/1319] eta: 0:33:36 lr: 4.5001416085688e-05 loss: 0.1364 (0.1336) time: 2.6000 data: 0.0060 max mem: 33369 +Epoch: [4] [ 560/1319] eta: 0:33:10 lr: 4.4992786399541676e-05 loss: 0.1282 (0.1334) time: 2.6262 data: 0.0058 max mem: 33369 +Epoch: [4] [ 570/1319] eta: 0:32:44 lr: 4.498415652948174e-05 loss: 0.1239 (0.1335) time: 2.6406 data: 0.0058 max mem: 33369 +Epoch: [4] [ 580/1319] eta: 0:32:18 lr: 4.497552647546508e-05 loss: 0.1436 (0.1336) time: 2.6259 data: 0.0059 max mem: 33369 +Epoch: [4] [ 590/1319] eta: 0:31:52 lr: 4.496689623744855e-05 loss: 0.1300 (0.1334) time: 2.6372 data: 0.0058 max mem: 33369 +Epoch: [4] [ 600/1319] eta: 0:31:26 lr: 4.495826581538897e-05 loss: 0.1221 (0.1334) time: 2.6512 data: 0.0059 max mem: 33369 +Epoch: [4] [ 610/1319] eta: 0:31:00 lr: 4.494963520924318e-05 loss: 0.1100 (0.1332) time: 2.6266 data: 0.0059 max mem: 33369 +Epoch: [4] [ 620/1319] eta: 0:30:33 lr: 4.4941004418967974e-05 loss: 0.1243 (0.1333) time: 2.5916 data: 0.0060 max mem: 33369 +Epoch: [4] [ 630/1319] eta: 0:30:06 lr: 4.493237344452013e-05 loss: 0.1344 (0.1333) time: 2.5878 data: 0.0059 max mem: 33369 +Epoch: [4] [ 640/1319] eta: 0:29:40 lr: 4.4923742285856394e-05 loss: 0.1157 (0.1330) time: 2.6008 data: 0.0058 max mem: 33369 +Epoch: [4] [ 650/1319] eta: 0:29:13 lr: 4.491511094293352e-05 loss: 0.1259 (0.1337) time: 2.6048 data: 0.0059 max mem: 33369 +Epoch: [4] [ 660/1319] eta: 0:28:47 lr: 4.4906479415708236e-05 loss: 0.1259 (0.1334) time: 2.6110 data: 0.0058 max mem: 33369 +Epoch: [4] [ 670/1319] eta: 0:28:21 lr: 4.489784770413723e-05 loss: 0.1314 (0.1336) time: 2.6150 data: 0.0059 max mem: 33369 +Epoch: [4] [ 680/1319] eta: 0:27:54 lr: 4.48892158081772e-05 loss: 0.1550 (0.1337) time: 2.6044 data: 0.0059 max mem: 33369 +Epoch: [4] [ 690/1319] eta: 0:27:28 lr: 4.4880583727784795e-05 loss: 0.1285 (0.1341) time: 2.5987 data: 0.0058 max mem: 33369 +Epoch: [4] [ 700/1319] eta: 0:27:03 lr: 4.487195146291666e-05 loss: 0.1124 (0.1342) time: 2.6644 data: 0.0057 max mem: 33369 +Epoch: [4] [ 710/1319] eta: 0:26:36 lr: 4.486331901352942e-05 loss: 0.1124 (0.1342) time: 2.6561 data: 0.0057 max mem: 33369 +Epoch: [4] [ 720/1319] eta: 0:26:10 lr: 4.4854686379579686e-05 loss: 0.1189 (0.1341) time: 2.6144 data: 0.0058 max mem: 33369 +Epoch: [4] [ 730/1319] eta: 0:25:44 lr: 4.4846053561024035e-05 loss: 0.1165 (0.1340) time: 2.6263 data: 0.0058 max mem: 33369 +Epoch: [4] [ 740/1319] eta: 0:25:18 lr: 4.4837420557819036e-05 loss: 0.1217 (0.1339) time: 2.6444 data: 0.0057 max mem: 33369 +Epoch: [4] [ 750/1319] eta: 0:24:52 lr: 4.482878736992124e-05 loss: 0.1231 (0.1337) time: 2.6708 data: 0.0057 max mem: 33369 +Epoch: [4] [ 760/1319] eta: 0:24:26 lr: 4.4820153997287166e-05 loss: 0.1231 (0.1339) time: 2.6400 data: 0.0057 max mem: 33369 +Epoch: [4] [ 770/1319] eta: 0:24:00 lr: 4.481152043987333e-05 loss: 0.1318 (0.1340) time: 2.6086 data: 0.0058 max mem: 33369 +Epoch: [4] [ 780/1319] eta: 0:23:33 lr: 4.48028866976362e-05 loss: 0.1351 (0.1343) time: 2.6249 data: 0.0060 max mem: 33369 +Epoch: [4] [ 790/1319] eta: 0:23:07 lr: 4.4794252770532266e-05 loss: 0.1349 (0.1342) time: 2.6309 data: 0.0060 max mem: 33369 +Epoch: [4] [ 800/1319] eta: 0:22:41 lr: 4.4785618658517975e-05 loss: 0.1239 (0.1340) time: 2.6103 data: 0.0059 max mem: 33369 +Epoch: [4] [ 810/1319] eta: 0:22:15 lr: 4.477698436154974e-05 loss: 0.1142 (0.1338) time: 2.6093 data: 0.0059 max mem: 33369 +Epoch: [4] [ 820/1319] eta: 0:21:48 lr: 4.476834987958398e-05 loss: 0.1142 (0.1338) time: 2.6150 data: 0.0058 max mem: 33369 +Epoch: [4] [ 830/1319] eta: 0:21:22 lr: 4.4759715212577086e-05 loss: 0.1257 (0.1339) time: 2.6087 data: 0.0059 max mem: 33369 +Epoch: [4] [ 840/1319] eta: 0:20:55 lr: 4.475108036048542e-05 loss: 0.1258 (0.1338) time: 2.5958 data: 0.0060 max mem: 33369 +Epoch: [4] [ 850/1319] eta: 0:20:29 lr: 4.4742445323265344e-05 loss: 0.1333 (0.1339) time: 2.6124 data: 0.0059 max mem: 33369 +Epoch: [4] [ 860/1319] eta: 0:20:03 lr: 4.473381010087318e-05 loss: 0.1435 (0.1340) time: 2.6554 data: 0.0058 max mem: 33369 +Epoch: [4] [ 870/1319] eta: 0:19:37 lr: 4.4725174693265234e-05 loss: 0.1174 (0.1338) time: 2.6252 data: 0.0059 max mem: 33369 +Epoch: [4] [ 880/1319] eta: 0:19:11 lr: 4.471653910039782e-05 loss: 0.1221 (0.1340) time: 2.5860 data: 0.0059 max mem: 33369 +Epoch: [4] [ 890/1319] eta: 0:18:44 lr: 4.4707903322227184e-05 loss: 0.1471 (0.1340) time: 2.5866 data: 0.0059 max mem: 33369 +Epoch: [4] [ 900/1319] eta: 0:18:18 lr: 4.469926735870959e-05 loss: 0.1333 (0.1340) time: 2.5873 data: 0.0060 max mem: 33369 +Epoch: [4] [ 910/1319] eta: 0:17:52 lr: 4.4690631209801266e-05 loss: 0.1155 (0.1338) time: 2.6015 data: 0.0060 max mem: 33369 +Epoch: [4] [ 920/1319] eta: 0:17:25 lr: 4.4681994875458425e-05 loss: 0.1124 (0.1338) time: 2.6308 data: 0.0059 max mem: 33369 +Epoch: [4] [ 930/1319] eta: 0:16:59 lr: 4.467335835563727e-05 loss: 0.1109 (0.1335) time: 2.6527 data: 0.0058 max mem: 33369 +Epoch: [4] [ 940/1319] eta: 0:16:33 lr: 4.466472165029396e-05 loss: 0.1251 (0.1339) time: 2.6560 data: 0.0059 max mem: 33369 +Epoch: [4] [ 950/1319] eta: 0:16:07 lr: 4.4656084759384645e-05 loss: 0.1277 (0.1339) time: 2.6225 data: 0.0060 max mem: 33369 +Epoch: [4] [ 960/1319] eta: 0:15:41 lr: 4.464744768286547e-05 loss: 0.1252 (0.1338) time: 2.6109 data: 0.0059 max mem: 33369 +Epoch: [4] [ 970/1319] eta: 0:15:14 lr: 4.463881042069255e-05 loss: 0.1305 (0.1338) time: 2.6139 data: 0.0059 max mem: 33369 +Epoch: [4] [ 980/1319] eta: 0:14:48 lr: 4.463017297282197e-05 loss: 0.1214 (0.1337) time: 2.5997 data: 0.0060 max mem: 33369 +Epoch: [4] [ 990/1319] eta: 0:14:22 lr: 4.4621535339209816e-05 loss: 0.1215 (0.1337) time: 2.6318 data: 0.0059 max mem: 33369 +Epoch: [4] [1000/1319] eta: 0:13:56 lr: 4.461289751981212e-05 loss: 0.1168 (0.1336) time: 2.6285 data: 0.0058 max mem: 33369 +Epoch: [4] [1010/1319] eta: 0:13:30 lr: 4.460425951458493e-05 loss: 0.1160 (0.1335) time: 2.6143 data: 0.0059 max mem: 33369 +Epoch: [4] [1020/1319] eta: 0:13:03 lr: 4.459562132348427e-05 loss: 0.1208 (0.1334) time: 2.6162 data: 0.0059 max mem: 33369 +Epoch: [4] [1030/1319] eta: 0:12:37 lr: 4.458698294646612e-05 loss: 0.1176 (0.1332) time: 2.6042 data: 0.0058 max mem: 33369 +Epoch: [4] [1040/1319] eta: 0:12:11 lr: 4.457834438348646e-05 loss: 0.0997 (0.1329) time: 2.6018 data: 0.0058 max mem: 33369 +Epoch: [4] [1050/1319] eta: 0:11:45 lr: 4.456970563450125e-05 loss: 0.1205 (0.1329) time: 2.6019 data: 0.0059 max mem: 33369 +Epoch: [4] [1060/1319] eta: 0:11:18 lr: 4.456106669946641e-05 loss: 0.1304 (0.1329) time: 2.6378 data: 0.0059 max mem: 33369 +Epoch: [4] [1070/1319] eta: 0:10:52 lr: 4.4552427578337865e-05 loss: 0.1341 (0.1328) time: 2.6447 data: 0.0059 max mem: 33369 +Epoch: [4] [1080/1319] eta: 0:10:26 lr: 4.45437882710715e-05 loss: 0.1350 (0.1330) time: 2.6064 data: 0.0061 max mem: 33369 +Epoch: [4] [1090/1319] eta: 0:10:00 lr: 4.453514877762321e-05 loss: 0.1244 (0.1331) time: 2.5819 data: 0.0061 max mem: 33369 +Epoch: [4] [1100/1319] eta: 0:09:33 lr: 4.4526509097948836e-05 loss: 0.0997 (0.1331) time: 2.5829 data: 0.0060 max mem: 33369 +Epoch: [4] [1110/1319] eta: 0:09:07 lr: 4.451786923200421e-05 loss: 0.1272 (0.1332) time: 2.5930 data: 0.0060 max mem: 33369 +Epoch: [4] [1120/1319] eta: 0:08:41 lr: 4.450922917974515e-05 loss: 0.1380 (0.1333) time: 2.5756 data: 0.0059 max mem: 33369 +Epoch: [4] [1130/1319] eta: 0:08:15 lr: 4.4500588941127465e-05 loss: 0.1348 (0.1334) time: 2.5970 data: 0.0060 max mem: 33369 +Epoch: [4] [1140/1319] eta: 0:07:48 lr: 4.449194851610691e-05 loss: 0.1348 (0.1335) time: 2.6410 data: 0.0061 max mem: 33369 +Epoch: [4] [1150/1319] eta: 0:07:22 lr: 4.4483307904639245e-05 loss: 0.1303 (0.1335) time: 2.6473 data: 0.0060 max mem: 33369 +Epoch: [4] [1160/1319] eta: 0:06:56 lr: 4.447466710668021e-05 loss: 0.1513 (0.1338) time: 2.6613 data: 0.0058 max mem: 33369 +Epoch: [4] [1170/1319] eta: 0:06:30 lr: 4.4466026122185514e-05 loss: 0.1267 (0.1336) time: 2.6512 data: 0.0058 max mem: 33369 +Epoch: [4] [1180/1319] eta: 0:06:04 lr: 4.4457384951110855e-05 loss: 0.1144 (0.1337) time: 2.6081 data: 0.0058 max mem: 33369 +Epoch: [4] [1190/1319] eta: 0:05:38 lr: 4.44487435934119e-05 loss: 0.1105 (0.1336) time: 2.6094 data: 0.0059 max mem: 33369 +Epoch: [4] [1200/1319] eta: 0:05:11 lr: 4.4440102049044326e-05 loss: 0.1086 (0.1335) time: 2.6317 data: 0.0059 max mem: 33369 +Epoch: [4] [1210/1319] eta: 0:04:45 lr: 4.443146031796374e-05 loss: 0.1003 (0.1333) time: 2.6425 data: 0.0058 max mem: 33369 +Epoch: [4] [1220/1319] eta: 0:04:19 lr: 4.442281840012577e-05 loss: 0.1234 (0.1334) time: 2.6430 data: 0.0058 max mem: 33369 +Epoch: [4] [1230/1319] eta: 0:03:53 lr: 4.441417629548601e-05 loss: 0.1307 (0.1334) time: 2.6300 data: 0.0059 max mem: 33369 +Epoch: [4] [1240/1319] eta: 0:03:27 lr: 4.4405534004000035e-05 loss: 0.1288 (0.1334) time: 2.6439 data: 0.0058 max mem: 33369 +Epoch: [4] [1250/1319] eta: 0:03:00 lr: 4.439689152562339e-05 loss: 0.1387 (0.1335) time: 2.6360 data: 0.0056 max mem: 33369 +Epoch: [4] [1260/1319] eta: 0:02:34 lr: 4.438824886031161e-05 loss: 0.1279 (0.1336) time: 2.6311 data: 0.0058 max mem: 33369 +Epoch: [4] [1270/1319] eta: 0:02:08 lr: 4.437960600802022e-05 loss: 0.1264 (0.1337) time: 2.6494 data: 0.0058 max mem: 33369 +Epoch: [4] [1280/1319] eta: 0:01:42 lr: 4.4370962968704706e-05 loss: 0.1380 (0.1336) time: 2.6534 data: 0.0057 max mem: 33369 +Epoch: [4] [1290/1319] eta: 0:01:16 lr: 4.436231974232054e-05 loss: 0.1235 (0.1335) time: 2.6394 data: 0.0057 max mem: 33369 +Epoch: [4] [1300/1319] eta: 0:00:49 lr: 4.435367632882316e-05 loss: 0.1108 (0.1334) time: 2.6114 data: 0.0057 max mem: 33369 +Epoch: [4] [1310/1319] eta: 0:00:23 lr: 4.434503272816803e-05 loss: 0.1108 (0.1334) time: 2.6131 data: 0.0058 max mem: 33369 +Epoch: [4] Total time: 0:57:38 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 2:25:09 time: 3.3849 data: 3.3058 max mem: 33369 +Test: [ 100/2573] eta: 0:04:18 time: 0.0713 data: 0.0011 max mem: 33369 +Test: [ 200/2573] eta: 0:03:31 time: 0.0730 data: 0.0012 max mem: 33369 +Test: [ 300/2573] eta: 0:03:09 time: 0.0747 data: 0.0011 max mem: 33369 +Test: [ 400/2573] eta: 0:02:55 time: 0.0749 data: 0.0011 max mem: 33369 +Test: [ 500/2573] eta: 0:02:44 time: 0.0734 data: 0.0011 max mem: 33369 +Test: [ 600/2573] eta: 0:02:34 time: 0.0733 data: 0.0011 max mem: 33369 +Test: [ 700/2573] eta: 0:02:26 time: 0.0735 data: 0.0012 max mem: 33369 +Test: [ 800/2573] eta: 0:02:17 time: 0.0769 data: 0.0011 max mem: 33369 +Test: [ 900/2573] eta: 0:02:09 time: 0.0735 data: 0.0011 max mem: 33369 +Test: [1000/2573] eta: 0:02:01 time: 0.0736 data: 0.0011 max mem: 33369 +Test: [1100/2573] eta: 0:01:52 time: 0.0736 data: 0.0012 max mem: 33369 +Test: [1200/2573] eta: 0:01:45 time: 0.0736 data: 0.0011 max mem: 33369 +Test: [1300/2573] eta: 0:01:37 time: 0.0736 data: 0.0011 max mem: 33369 +Test: [1400/2573] eta: 0:01:29 time: 0.0720 data: 0.0012 max mem: 33369 +Test: [1500/2573] eta: 0:01:21 time: 0.0737 data: 0.0012 max mem: 33369 +Test: [1600/2573] eta: 0:01:13 time: 0.0770 data: 0.0012 max mem: 33369 +Test: [1700/2573] eta: 0:01:06 time: 0.0721 data: 0.0011 max mem: 33369 +Test: [1800/2573] eta: 0:00:58 time: 0.0754 data: 0.0011 max mem: 33369 +Test: [1900/2573] eta: 0:00:50 time: 0.0720 data: 0.0012 max mem: 33369 +Test: [2000/2573] eta: 0:00:43 time: 0.0739 data: 0.0012 max mem: 33369 +Test: [2100/2573] eta: 0:00:35 time: 0.0756 data: 0.0011 max mem: 33369 +Test: [2200/2573] eta: 0:00:28 time: 0.0755 data: 0.0011 max mem: 33369 +Test: [2300/2573] eta: 0:00:20 time: 0.0756 data: 0.0011 max mem: 33369 +Test: [2400/2573] eta: 0:00:12 time: 0.0706 data: 0.0011 max mem: 33369 +Test: [2500/2573] eta: 0:00:05 time: 0.0739 data: 0.0012 max mem: 33369 +Test: Total time: 0:03:13 +Final results: +Mean IoU is 51.67 + + precision@0.5 = 57.78 + precision@0.6 = 50.47 + precision@0.7 = 41.24 + precision@0.8 = 29.04 + precision@0.9 = 11.11 + overall IoU = 53.98 + +Average object IoU 51.669964859566264 +Overall IoU 53.977596282958984 +Better epoch: 4 + +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [5] [ 0/1319] eta: 1:30:13 lr: 4.433725332752167e-05 loss: 0.1393 (0.1393) time: 4.1040 data: 1.3780 max mem: 33369 +Epoch: [5] [ 10/1319] eta: 1:00:33 lr: 4.432860937114392e-05 loss: 0.0874 (0.1057) time: 2.7754 data: 0.1309 max mem: 33369 +Epoch: [5] [ 20/1319] eta: 0:58:22 lr: 4.4319965227479046e-05 loss: 0.1123 (0.1244) time: 2.6257 data: 0.0060 max mem: 33369 +Epoch: [5] [ 30/1319] eta: 0:57:17 lr: 4.43113208964824e-05 loss: 0.1187 (0.1244) time: 2.6065 data: 0.0059 max mem: 33369 +Epoch: [5] [ 40/1319] eta: 0:56:41 lr: 4.43026763781093e-05 loss: 0.1087 (0.1209) time: 2.6206 data: 0.0061 max mem: 33369 +Epoch: [5] [ 50/1319] eta: 0:56:07 lr: 4.429403167231508e-05 loss: 0.1193 (0.1247) time: 2.6335 data: 0.0062 max mem: 33369 +Epoch: [5] [ 60/1319] eta: 0:55:43 lr: 4.428538677905502e-05 loss: 0.1174 (0.1234) time: 2.6482 data: 0.0062 max mem: 33369 +Epoch: [5] [ 70/1319] eta: 0:55:09 lr: 4.4276741698284395e-05 loss: 0.1140 (0.1235) time: 2.6397 data: 0.0061 max mem: 33369 +Epoch: [5] [ 80/1319] eta: 0:54:40 lr: 4.4268096429958464e-05 loss: 0.1166 (0.1234) time: 2.6222 data: 0.0062 max mem: 33369 +Epoch: [5] [ 90/1319] eta: 0:54:12 lr: 4.425945097403244e-05 loss: 0.1027 (0.1215) time: 2.6339 data: 0.0063 max mem: 33369 +Epoch: [5] [ 100/1319] eta: 0:53:43 lr: 4.425080533046155e-05 loss: 0.0974 (0.1189) time: 2.6327 data: 0.0062 max mem: 33369 +Epoch: [5] [ 110/1319] eta: 0:53:13 lr: 4.424215949920098e-05 loss: 0.0994 (0.1208) time: 2.6206 data: 0.0059 max mem: 33369 +Epoch: [5] [ 120/1319] eta: 0:52:47 lr: 4.423351348020589e-05 loss: 0.1401 (0.1239) time: 2.6276 data: 0.0059 max mem: 33369 +Epoch: [5] [ 130/1319] eta: 0:52:15 lr: 4.4224867273431445e-05 loss: 0.1069 (0.1220) time: 2.6128 data: 0.0062 max mem: 33369 +Epoch: [5] [ 140/1319] eta: 0:51:44 lr: 4.421622087883277e-05 loss: 0.0970 (0.1225) time: 2.5822 data: 0.0063 max mem: 33369 +Epoch: [5] [ 150/1319] eta: 0:51:15 lr: 4.4207574296364965e-05 loss: 0.0970 (0.1208) time: 2.5918 data: 0.0061 max mem: 33369 +Epoch: [5] [ 160/1319] eta: 0:50:47 lr: 4.419892752598312e-05 loss: 0.0949 (0.1208) time: 2.6056 data: 0.0060 max mem: 33369 +Epoch: [5] [ 170/1319] eta: 0:50:22 lr: 4.419028056764231e-05 loss: 0.1085 (0.1215) time: 2.6250 data: 0.0060 max mem: 33369 +Epoch: [5] [ 180/1319] eta: 0:49:54 lr: 4.418163342129758e-05 loss: 0.1183 (0.1221) time: 2.6236 data: 0.0061 max mem: 33369 +Epoch: [5] [ 190/1319] eta: 0:49:26 lr: 4.417298608690395e-05 loss: 0.1258 (0.1230) time: 2.6045 data: 0.0061 max mem: 33369 +Epoch: [5] [ 200/1319] eta: 0:49:01 lr: 4.416433856441643e-05 loss: 0.1258 (0.1230) time: 2.6243 data: 0.0061 max mem: 33369 +Epoch: [5] [ 210/1319] eta: 0:48:33 lr: 4.415569085379001e-05 loss: 0.1192 (0.1230) time: 2.6196 data: 0.0060 max mem: 33369 +Epoch: [5] [ 220/1319] eta: 0:48:07 lr: 4.4147042954979643e-05 loss: 0.1098 (0.1238) time: 2.6167 data: 0.0059 max mem: 33369 +Epoch: [5] [ 230/1319] eta: 0:47:43 lr: 4.413839486794028e-05 loss: 0.1227 (0.1240) time: 2.6529 data: 0.0058 max mem: 33369 +Epoch: [5] [ 240/1319] eta: 0:47:15 lr: 4.412974659262685e-05 loss: 0.1151 (0.1238) time: 2.6336 data: 0.0058 max mem: 33369 +Epoch: [5] [ 250/1319] eta: 0:46:49 lr: 4.412109812899424e-05 loss: 0.1151 (0.1239) time: 2.6179 data: 0.0057 max mem: 33369 +Epoch: [5] [ 260/1319] eta: 0:46:24 lr: 4.411244947699735e-05 loss: 0.1194 (0.1240) time: 2.6438 data: 0.0058 max mem: 33369 +Epoch: [5] [ 270/1319] eta: 0:45:58 lr: 4.4103800636591036e-05 loss: 0.1194 (0.1241) time: 2.6418 data: 0.0060 max mem: 33369 +Epoch: [5] [ 280/1319] eta: 0:45:30 lr: 4.409515160773014e-05 loss: 0.1422 (0.1243) time: 2.6050 data: 0.0060 max mem: 33369 +Epoch: [5] [ 290/1319] eta: 0:45:03 lr: 4.408650239036947e-05 loss: 0.1203 (0.1240) time: 2.5935 data: 0.0060 max mem: 33369 +Epoch: [5] [ 300/1319] eta: 0:44:37 lr: 4.407785298446384e-05 loss: 0.1051 (0.1235) time: 2.6212 data: 0.0060 max mem: 33369 +Epoch: [5] [ 310/1319] eta: 0:44:11 lr: 4.406920338996803e-05 loss: 0.1051 (0.1238) time: 2.6405 data: 0.0060 max mem: 33369 +Epoch: [5] [ 320/1319] eta: 0:43:43 lr: 4.406055360683679e-05 loss: 0.1074 (0.1237) time: 2.6167 data: 0.0061 max mem: 33369 +Epoch: [5] [ 330/1319] eta: 0:43:18 lr: 4.4051903635024855e-05 loss: 0.1129 (0.1239) time: 2.6156 data: 0.0062 max mem: 33369 +Epoch: [5] [ 340/1319] eta: 0:42:52 lr: 4.404325347448695e-05 loss: 0.1223 (0.1238) time: 2.6435 data: 0.0060 max mem: 33369 +Epoch: [5] [ 350/1319] eta: 0:42:27 lr: 4.403460312517776e-05 loss: 0.1209 (0.1236) time: 2.6537 data: 0.0058 max mem: 33369 +Epoch: [5] [ 360/1319] eta: 0:42:00 lr: 4.402595258705198e-05 loss: 0.1333 (0.1241) time: 2.6495 data: 0.0058 max mem: 33369 +Epoch: [5] [ 370/1319] eta: 0:41:34 lr: 4.401730186006425e-05 loss: 0.1178 (0.1241) time: 2.6271 data: 0.0058 max mem: 33369 +Epoch: [5] [ 380/1319] eta: 0:41:07 lr: 4.40086509441692e-05 loss: 0.1145 (0.1242) time: 2.6187 data: 0.0058 max mem: 33369 +Epoch: [5] [ 390/1319] eta: 0:40:41 lr: 4.399999983932147e-05 loss: 0.1178 (0.1245) time: 2.6282 data: 0.0060 max mem: 33369 +Epoch: [5] [ 400/1319] eta: 0:40:15 lr: 4.399134854547561e-05 loss: 0.1118 (0.1244) time: 2.6375 data: 0.0060 max mem: 33369 +Epoch: [5] [ 410/1319] eta: 0:39:49 lr: 4.3982697062586214e-05 loss: 0.1065 (0.1243) time: 2.6417 data: 0.0058 max mem: 33369 +Epoch: [5] [ 420/1319] eta: 0:39:22 lr: 4.397404539060784e-05 loss: 0.1030 (0.1245) time: 2.6227 data: 0.0059 max mem: 33369 +Epoch: [5] [ 430/1319] eta: 0:38:56 lr: 4.3965393529495005e-05 loss: 0.1009 (0.1239) time: 2.6148 data: 0.0060 max mem: 33369 +Epoch: [5] [ 440/1319] eta: 0:38:31 lr: 4.3956741479202226e-05 loss: 0.0996 (0.1240) time: 2.6611 data: 0.0058 max mem: 33369 +Epoch: [5] [ 450/1319] eta: 0:38:04 lr: 4.3948089239683975e-05 loss: 0.1151 (0.1242) time: 2.6515 data: 0.0059 max mem: 33369 +Epoch: [5] [ 460/1319] eta: 0:37:38 lr: 4.3939436810894734e-05 loss: 0.1244 (0.1243) time: 2.6247 data: 0.0060 max mem: 33369 +Epoch: [5] [ 470/1319] eta: 0:37:12 lr: 4.393078419278895e-05 loss: 0.1211 (0.1239) time: 2.6315 data: 0.0059 max mem: 33369 +Epoch: [5] [ 480/1319] eta: 0:36:46 lr: 4.3922131385321036e-05 loss: 0.1082 (0.1237) time: 2.6288 data: 0.0059 max mem: 33369 +Epoch: [5] [ 490/1319] eta: 0:36:19 lr: 4.3913478388445405e-05 loss: 0.1152 (0.1237) time: 2.6130 data: 0.0060 max mem: 33369 +Epoch: [5] [ 500/1319] eta: 0:35:53 lr: 4.390482520211644e-05 loss: 0.1144 (0.1234) time: 2.6185 data: 0.0059 max mem: 33369 +Epoch: [5] [ 510/1319] eta: 0:35:26 lr: 4.389617182628851e-05 loss: 0.1137 (0.1233) time: 2.6137 data: 0.0058 max mem: 33369 +Epoch: [5] [ 520/1319] eta: 0:35:00 lr: 4.3887518260915935e-05 loss: 0.1167 (0.1233) time: 2.6097 data: 0.0060 max mem: 33369 +Epoch: [5] [ 530/1319] eta: 0:34:33 lr: 4.3878864505953046e-05 loss: 0.0956 (0.1229) time: 2.6367 data: 0.0059 max mem: 33369 +Epoch: [5] [ 540/1319] eta: 0:34:06 lr: 4.387021056135415e-05 loss: 0.1036 (0.1230) time: 2.6092 data: 0.0058 max mem: 33369 +Epoch: [5] [ 550/1319] eta: 0:33:40 lr: 4.386155642707351e-05 loss: 0.1071 (0.1231) time: 2.6024 data: 0.0060 max mem: 33369 +Epoch: [5] [ 560/1319] eta: 0:33:14 lr: 4.3852902103065404e-05 loss: 0.1177 (0.1235) time: 2.6326 data: 0.0061 max mem: 33369 +Epoch: [5] [ 570/1319] eta: 0:32:47 lr: 4.3844247589284045e-05 loss: 0.1177 (0.1232) time: 2.6202 data: 0.0060 max mem: 33369 +Epoch: [5] [ 580/1319] eta: 0:32:21 lr: 4.383559288568366e-05 loss: 0.1257 (0.1234) time: 2.6062 data: 0.0059 max mem: 33369 +Epoch: [5] [ 590/1319] eta: 0:31:55 lr: 4.382693799221843e-05 loss: 0.1359 (0.1235) time: 2.6213 data: 0.0058 max mem: 33369 +Epoch: [5] [ 600/1319] eta: 0:31:28 lr: 4.381828290884256e-05 loss: 0.1163 (0.1236) time: 2.6214 data: 0.0059 max mem: 33369 +Epoch: [5] [ 610/1319] eta: 0:31:02 lr: 4.380962763551017e-05 loss: 0.0957 (0.1233) time: 2.6186 data: 0.0059 max mem: 33369 +Epoch: [5] [ 620/1319] eta: 0:30:36 lr: 4.38009721721754e-05 loss: 0.0992 (0.1233) time: 2.6204 data: 0.0061 max mem: 33369 +Epoch: [5] [ 630/1319] eta: 0:30:09 lr: 4.3792316518792354e-05 loss: 0.1011 (0.1229) time: 2.6161 data: 0.0062 max mem: 33369 +Epoch: [5] [ 640/1319] eta: 0:29:43 lr: 4.378366067531513e-05 loss: 0.1104 (0.1231) time: 2.6275 data: 0.0059 max mem: 33369 +Epoch: [5] [ 650/1319] eta: 0:29:17 lr: 4.37750046416978e-05 loss: 0.1116 (0.1228) time: 2.6347 data: 0.0059 max mem: 33369 +Epoch: [5] [ 660/1319] eta: 0:28:50 lr: 4.376634841789439e-05 loss: 0.1116 (0.1232) time: 2.5934 data: 0.0059 max mem: 33369 +Epoch: [5] [ 670/1319] eta: 0:28:24 lr: 4.375769200385893e-05 loss: 0.1320 (0.1232) time: 2.5875 data: 0.0060 max mem: 33369 +Epoch: [5] [ 680/1319] eta: 0:27:57 lr: 4.3749035399545434e-05 loss: 0.1174 (0.1233) time: 2.5950 data: 0.0059 max mem: 33369 +Epoch: [5] [ 690/1319] eta: 0:27:30 lr: 4.374037860490788e-05 loss: 0.1123 (0.1232) time: 2.5903 data: 0.0058 max mem: 33369 +Epoch: [5] [ 700/1319] eta: 0:27:04 lr: 4.373172161990022e-05 loss: 0.1235 (0.1237) time: 2.6179 data: 0.0059 max mem: 33369 +Epoch: [5] [ 710/1319] eta: 0:26:38 lr: 4.372306444447641e-05 loss: 0.1296 (0.1238) time: 2.6411 data: 0.0059 max mem: 33369 +Epoch: [5] [ 720/1319] eta: 0:26:12 lr: 4.3714407078590355e-05 loss: 0.1083 (0.1236) time: 2.6174 data: 0.0059 max mem: 33369 +Epoch: [5] [ 730/1319] eta: 0:25:46 lr: 4.370574952219595e-05 loss: 0.1083 (0.1238) time: 2.6273 data: 0.0060 max mem: 33369 +Epoch: [5] [ 740/1319] eta: 0:25:19 lr: 4.369709177524708e-05 loss: 0.1213 (0.1238) time: 2.6507 data: 0.0061 max mem: 33369 +Epoch: [5] [ 750/1319] eta: 0:24:53 lr: 4.36884338376976e-05 loss: 0.1201 (0.1239) time: 2.5938 data: 0.0062 max mem: 33369 +Epoch: [5] [ 760/1319] eta: 0:24:26 lr: 4.3679775709501325e-05 loss: 0.1178 (0.1239) time: 2.5874 data: 0.0061 max mem: 33369 +Epoch: [5] [ 770/1319] eta: 0:24:00 lr: 4.3671117390612085e-05 loss: 0.1226 (0.1239) time: 2.6362 data: 0.0061 max mem: 33369 +Epoch: [5] [ 780/1319] eta: 0:23:34 lr: 4.366245888098367e-05 loss: 0.1236 (0.1241) time: 2.6420 data: 0.0060 max mem: 33369 +Epoch: [5] [ 790/1319] eta: 0:23:08 lr: 4.3653800180569845e-05 loss: 0.1204 (0.1241) time: 2.6214 data: 0.0057 max mem: 33369 +Epoch: [5] [ 800/1319] eta: 0:22:42 lr: 4.364514128932435e-05 loss: 0.1189 (0.1241) time: 2.6385 data: 0.0058 max mem: 33369 +Epoch: [5] [ 810/1319] eta: 0:22:16 lr: 4.363648220720092e-05 loss: 0.0986 (0.1237) time: 2.6517 data: 0.0058 max mem: 33369 +Epoch: [5] [ 820/1319] eta: 0:21:50 lr: 4.3627822934153263e-05 loss: 0.0986 (0.1236) time: 2.6507 data: 0.0057 max mem: 33369 +Epoch: [5] [ 830/1319] eta: 0:21:23 lr: 4.361916347013505e-05 loss: 0.1141 (0.1237) time: 2.6233 data: 0.0059 max mem: 33369 +Epoch: [5] [ 840/1319] eta: 0:20:57 lr: 4.361050381509995e-05 loss: 0.1276 (0.1237) time: 2.6169 data: 0.0059 max mem: 33369 +Epoch: [5] [ 850/1319] eta: 0:20:31 lr: 4.3601843969001596e-05 loss: 0.1197 (0.1238) time: 2.6311 data: 0.0057 max mem: 33369 +Epoch: [5] [ 860/1319] eta: 0:20:04 lr: 4.359318393179363e-05 loss: 0.1197 (0.1239) time: 2.6114 data: 0.0060 max mem: 33369 +Epoch: [5] [ 870/1319] eta: 0:19:38 lr: 4.3584523703429616e-05 loss: 0.1211 (0.1241) time: 2.5936 data: 0.0061 max mem: 33369 +Epoch: [5] [ 880/1319] eta: 0:19:11 lr: 4.357586328386315e-05 loss: 0.1186 (0.1242) time: 2.5699 data: 0.0059 max mem: 33369 +Epoch: [5] [ 890/1319] eta: 0:18:45 lr: 4.356720267304778e-05 loss: 0.1112 (0.1242) time: 2.5995 data: 0.0059 max mem: 33369 +Epoch: [5] [ 900/1319] eta: 0:18:19 lr: 4.3558541870937056e-05 loss: 0.1112 (0.1240) time: 2.6559 data: 0.0059 max mem: 33369 +Epoch: [5] [ 910/1319] eta: 0:17:53 lr: 4.354988087748445e-05 loss: 0.1116 (0.1237) time: 2.6495 data: 0.0059 max mem: 33369 +Epoch: [5] [ 920/1319] eta: 0:17:27 lr: 4.35412196926435e-05 loss: 0.1116 (0.1238) time: 2.6096 data: 0.0059 max mem: 33369 +Epoch: [5] [ 930/1319] eta: 0:17:00 lr: 4.353255831636764e-05 loss: 0.1289 (0.1239) time: 2.6038 data: 0.0061 max mem: 33369 +Epoch: [5] [ 940/1319] eta: 0:16:34 lr: 4.352389674861032e-05 loss: 0.1189 (0.1240) time: 2.6310 data: 0.0061 max mem: 33369 +Epoch: [5] [ 950/1319] eta: 0:16:08 lr: 4.3515234989324975e-05 loss: 0.1108 (0.1242) time: 2.6198 data: 0.0061 max mem: 33369 +Epoch: [5] [ 960/1319] eta: 0:15:41 lr: 4.350657303846501e-05 loss: 0.1156 (0.1243) time: 2.6005 data: 0.0059 max mem: 33369 +Epoch: [5] [ 970/1319] eta: 0:15:15 lr: 4.34979108959838e-05 loss: 0.1133 (0.1242) time: 2.6319 data: 0.0058 max mem: 33369 +Epoch: [5] [ 980/1319] eta: 0:14:49 lr: 4.348924856183469e-05 loss: 0.1176 (0.1245) time: 2.6251 data: 0.0059 max mem: 33369 +Epoch: [5] [ 990/1319] eta: 0:14:23 lr: 4.348058603597104e-05 loss: 0.1218 (0.1244) time: 2.6196 data: 0.0059 max mem: 33369 +Epoch: [5] [1000/1319] eta: 0:13:57 lr: 4.347192331834616e-05 loss: 0.1257 (0.1245) time: 2.6291 data: 0.0060 max mem: 33369 +Epoch: [5] [1010/1319] eta: 0:13:30 lr: 4.346326040891335e-05 loss: 0.1333 (0.1245) time: 2.6363 data: 0.0061 max mem: 33369 +Epoch: [5] [1020/1319] eta: 0:13:04 lr: 4.345459730762588e-05 loss: 0.1033 (0.1247) time: 2.6503 data: 0.0060 max mem: 33369 +Epoch: [5] [1030/1319] eta: 0:12:38 lr: 4.344593401443699e-05 loss: 0.1282 (0.1247) time: 2.6347 data: 0.0059 max mem: 33369 +Epoch: [5] [1040/1319] eta: 0:12:12 lr: 4.343727052929992e-05 loss: 0.1180 (0.1246) time: 2.6125 data: 0.0059 max mem: 33369 +Epoch: [5] [1050/1319] eta: 0:11:45 lr: 4.342860685216788e-05 loss: 0.1160 (0.1246) time: 2.6061 data: 0.0058 max mem: 33369 +Epoch: [5] [1060/1319] eta: 0:11:19 lr: 4.341994298299405e-05 loss: 0.1193 (0.1247) time: 2.6156 data: 0.0057 max mem: 33369 +Epoch: [5] [1070/1319] eta: 0:10:53 lr: 4.341127892173159e-05 loss: 0.1193 (0.1247) time: 2.6186 data: 0.0057 max mem: 33369 +Epoch: [5] [1080/1319] eta: 0:10:27 lr: 4.3402614668333656e-05 loss: 0.1226 (0.1246) time: 2.6361 data: 0.0058 max mem: 33369 +Epoch: [5] [1090/1319] eta: 0:10:00 lr: 4.339395022275336e-05 loss: 0.1240 (0.1248) time: 2.6395 data: 0.0057 max mem: 33369 +Epoch: [5] [1100/1319] eta: 0:09:34 lr: 4.33852855849438e-05 loss: 0.1267 (0.1247) time: 2.6404 data: 0.0057 max mem: 33369 +Epoch: [5] [1110/1319] eta: 0:09:08 lr: 4.337662075485806e-05 loss: 0.1180 (0.1247) time: 2.6313 data: 0.0059 max mem: 33369 +Epoch: [5] [1120/1319] eta: 0:08:42 lr: 4.3367955732449175e-05 loss: 0.1145 (0.1246) time: 2.6129 data: 0.0058 max mem: 33369 +Epoch: [5] [1130/1319] eta: 0:08:15 lr: 4.3359290517670206e-05 loss: 0.1217 (0.1247) time: 2.6087 data: 0.0057 max mem: 33369 +Epoch: [5] [1140/1319] eta: 0:07:49 lr: 4.335062511047415e-05 loss: 0.1217 (0.1246) time: 2.6019 data: 0.0058 max mem: 33369 +Epoch: [5] [1150/1319] eta: 0:07:23 lr: 4.3341959510813994e-05 loss: 0.1073 (0.1246) time: 2.6009 data: 0.0058 max mem: 33369 +Epoch: [5] [1160/1319] eta: 0:06:57 lr: 4.33332937186427e-05 loss: 0.1070 (0.1244) time: 2.6220 data: 0.0059 max mem: 33369 +Epoch: [5] [1170/1319] eta: 0:06:30 lr: 4.332462773391324e-05 loss: 0.1048 (0.1243) time: 2.6285 data: 0.0061 max mem: 33369 +Epoch: [5] [1180/1319] eta: 0:06:04 lr: 4.331596155657851e-05 loss: 0.1126 (0.1243) time: 2.6029 data: 0.0060 max mem: 33369 +Epoch: [5] [1190/1319] eta: 0:05:38 lr: 4.3307295186591415e-05 loss: 0.1177 (0.1244) time: 2.6189 data: 0.0060 max mem: 33369 +Epoch: [5] [1200/1319] eta: 0:05:12 lr: 4.329862862390485e-05 loss: 0.1286 (0.1244) time: 2.6253 data: 0.0060 max mem: 33369 +Epoch: [5] [1210/1319] eta: 0:04:45 lr: 4.328996186847165e-05 loss: 0.1286 (0.1246) time: 2.6040 data: 0.0060 max mem: 33369 +Epoch: [5] [1220/1319] eta: 0:04:19 lr: 4.328129492024467e-05 loss: 0.1268 (0.1245) time: 2.6051 data: 0.0058 max mem: 33369 +Epoch: [5] [1230/1319] eta: 0:03:53 lr: 4.3272627779176715e-05 loss: 0.1039 (0.1245) time: 2.6196 data: 0.0059 max mem: 33369 +Epoch: [5] [1240/1319] eta: 0:03:27 lr: 4.326396044522058e-05 loss: 0.1127 (0.1246) time: 2.6083 data: 0.0061 max mem: 33369 +Epoch: [5] [1250/1319] eta: 0:03:00 lr: 4.3255292918329036e-05 loss: 0.1255 (0.1249) time: 2.6099 data: 0.0060 max mem: 33369 +Epoch: [5] [1260/1319] eta: 0:02:34 lr: 4.324662519845482e-05 loss: 0.1379 (0.1250) time: 2.6269 data: 0.0060 max mem: 33369 +Epoch: [5] [1270/1319] eta: 0:02:08 lr: 4.323795728555066e-05 loss: 0.1291 (0.1250) time: 2.6262 data: 0.0058 max mem: 33369 +Epoch: [5] [1280/1319] eta: 0:01:42 lr: 4.322928917956926e-05 loss: 0.1087 (0.1250) time: 2.6234 data: 0.0057 max mem: 33369 +Epoch: [5] [1290/1319] eta: 0:01:16 lr: 4.322062088046332e-05 loss: 0.1101 (0.1249) time: 2.6336 data: 0.0058 max mem: 33369 +Epoch: [5] [1300/1319] eta: 0:00:49 lr: 4.321195238818547e-05 loss: 0.1194 (0.1250) time: 2.6267 data: 0.0058 max mem: 33369 +Epoch: [5] [1310/1319] eta: 0:00:23 lr: 4.3203283702688355e-05 loss: 0.0993 (0.1248) time: 2.6231 data: 0.0057 max mem: 33369 +Epoch: [5] Total time: 0:57:40 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 3:23:00 time: 4.7338 data: 4.6549 max mem: 33369 +Test: [ 100/2573] eta: 0:04:51 time: 0.0715 data: 0.0011 max mem: 33369 +Test: [ 200/2573] eta: 0:03:47 time: 0.0728 data: 0.0011 max mem: 33369 +Test: [ 300/2573] eta: 0:03:19 time: 0.0745 data: 0.0011 max mem: 33369 +Test: [ 400/2573] eta: 0:03:02 time: 0.0746 data: 0.0011 max mem: 33369 +Test: [ 500/2573] eta: 0:02:49 time: 0.0732 data: 0.0011 max mem: 33369 +Test: [ 600/2573] eta: 0:02:38 time: 0.0733 data: 0.0012 max mem: 33369 +Test: [ 700/2573] eta: 0:02:29 time: 0.0734 data: 0.0011 max mem: 33369 +Test: [ 800/2573] eta: 0:02:20 time: 0.0768 data: 0.0011 max mem: 33369 +Test: [ 900/2573] eta: 0:02:11 time: 0.0733 data: 0.0011 max mem: 33369 +Test: [1000/2573] eta: 0:02:02 time: 0.0735 data: 0.0012 max mem: 33369 +Test: [1100/2573] eta: 0:01:54 time: 0.0735 data: 0.0012 max mem: 33369 +Test: [1200/2573] eta: 0:01:46 time: 0.0735 data: 0.0012 max mem: 33369 +Test: [1300/2573] eta: 0:01:38 time: 0.0735 data: 0.0011 max mem: 33369 +Test: [1400/2573] eta: 0:01:30 time: 0.0720 data: 0.0011 max mem: 33369 +Test: [1500/2573] eta: 0:01:22 time: 0.0736 data: 0.0012 max mem: 33369 +Test: [1600/2573] eta: 0:01:14 time: 0.0769 data: 0.0011 max mem: 33369 +Test: [1700/2573] eta: 0:01:06 time: 0.0718 data: 0.0011 max mem: 33369 +Test: [1800/2573] eta: 0:00:58 time: 0.0752 data: 0.0011 max mem: 33369 +Test: [1900/2573] eta: 0:00:51 time: 0.0721 data: 0.0012 max mem: 33369 +Test: [2000/2573] eta: 0:00:43 time: 0.0737 data: 0.0011 max mem: 33369 +Test: [2100/2573] eta: 0:00:35 time: 0.0753 data: 0.0011 max mem: 33369 +Test: [2200/2573] eta: 0:00:28 time: 0.0752 data: 0.0011 max mem: 33369 +Test: [2300/2573] eta: 0:00:20 time: 0.0753 data: 0.0011 max mem: 33369 +Test: [2400/2573] eta: 0:00:13 time: 0.0704 data: 0.0011 max mem: 33369 +Test: [2500/2573] eta: 0:00:05 time: 0.0736 data: 0.0011 max mem: 33369 +Test: Total time: 0:03:14 +Final results: +Mean IoU is 54.83 + + precision@0.5 = 61.36 + precision@0.6 = 53.88 + precision@0.7 = 45.12 + precision@0.8 = 31.96 + precision@0.9 = 13.34 + overall IoU = 54.86 + +Average object IoU 54.82986035104683 +Overall IoU 54.86119842529297 +Better epoch: 5 + +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [6] [ 0/1319] eta: 1:42:52 lr: 4.319548172049932e-05 loss: 0.0821 (0.0821) time: 4.6796 data: 1.7797 max mem: 33369 +Epoch: [6] [ 10/1319] eta: 1:01:22 lr: 4.318681266775505e-05 loss: 0.1235 (0.1192) time: 2.8129 data: 0.1667 max mem: 33369 +Epoch: [6] [ 20/1319] eta: 0:58:40 lr: 4.317814342165404e-05 loss: 0.1108 (0.1135) time: 2.6119 data: 0.0057 max mem: 33369 +Epoch: [6] [ 30/1319] eta: 0:57:39 lr: 4.316947398214883e-05 loss: 0.1071 (0.1080) time: 2.6132 data: 0.0060 max mem: 33369 +Epoch: [6] [ 40/1319] eta: 0:56:54 lr: 4.316080434919196e-05 loss: 0.1015 (0.1097) time: 2.6273 data: 0.0060 max mem: 33369 +Epoch: [6] [ 50/1319] eta: 0:56:16 lr: 4.315213452273593e-05 loss: 0.0973 (0.1063) time: 2.6250 data: 0.0058 max mem: 33369 +Epoch: [6] [ 60/1319] eta: 0:55:49 lr: 4.314346450273323e-05 loss: 0.1099 (0.1137) time: 2.6402 data: 0.0059 max mem: 33369 +Epoch: [6] [ 70/1319] eta: 0:55:17 lr: 4.313479428913631e-05 loss: 0.1286 (0.1146) time: 2.6451 data: 0.0059 max mem: 33369 +Epoch: [6] [ 80/1319] eta: 0:54:43 lr: 4.312612388189762e-05 loss: 0.0947 (0.1114) time: 2.6187 data: 0.0060 max mem: 33369 +Epoch: [6] [ 90/1319] eta: 0:54:17 lr: 4.311745328096956e-05 loss: 0.0947 (0.1111) time: 2.6291 data: 0.0059 max mem: 33369 +Epoch: [6] [ 100/1319] eta: 0:53:50 lr: 4.3108782486304546e-05 loss: 0.0991 (0.1095) time: 2.6510 data: 0.0058 max mem: 33369 +Epoch: [6] [ 110/1319] eta: 0:53:21 lr: 4.310011149785494e-05 loss: 0.0964 (0.1111) time: 2.6369 data: 0.0060 max mem: 33369 +Epoch: [6] [ 120/1319] eta: 0:52:53 lr: 4.309144031557308e-05 loss: 0.1002 (0.1104) time: 2.6314 data: 0.0060 max mem: 33369 +Epoch: [6] [ 130/1319] eta: 0:52:24 lr: 4.308276893941131e-05 loss: 0.1109 (0.1109) time: 2.6260 data: 0.0059 max mem: 33369 +Epoch: [6] [ 140/1319] eta: 0:51:56 lr: 4.307409736932192e-05 loss: 0.1077 (0.1102) time: 2.6236 data: 0.0059 max mem: 33369 +Epoch: [6] [ 150/1319] eta: 0:51:29 lr: 4.306542560525721e-05 loss: 0.1072 (0.1107) time: 2.6333 data: 0.0060 max mem: 33369 +Epoch: [6] [ 160/1319] eta: 0:50:57 lr: 4.305675364716942e-05 loss: 0.1188 (0.1114) time: 2.6005 data: 0.0059 max mem: 33369 +Epoch: [6] [ 170/1319] eta: 0:50:29 lr: 4.3048081495010805e-05 loss: 0.1221 (0.1115) time: 2.5852 data: 0.0058 max mem: 33369 +Epoch: [6] [ 180/1319] eta: 0:50:00 lr: 4.303940914873357e-05 loss: 0.1149 (0.1118) time: 2.6007 data: 0.0059 max mem: 33369 +Epoch: [6] [ 190/1319] eta: 0:49:34 lr: 4.30307366082899e-05 loss: 0.1137 (0.1115) time: 2.6221 data: 0.0058 max mem: 33369 +Epoch: [6] [ 200/1319] eta: 0:49:10 lr: 4.302206387363197e-05 loss: 0.0943 (0.1113) time: 2.6604 data: 0.0057 max mem: 33369 +Epoch: [6] [ 210/1319] eta: 0:48:42 lr: 4.301339094471194e-05 loss: 0.0951 (0.1113) time: 2.6416 data: 0.0058 max mem: 33369 +Epoch: [6] [ 220/1319] eta: 0:48:16 lr: 4.300471782148193e-05 loss: 0.1101 (0.1122) time: 2.6213 data: 0.0058 max mem: 33369 +Epoch: [6] [ 230/1319] eta: 0:47:46 lr: 4.299604450389403e-05 loss: 0.1129 (0.1125) time: 2.6003 data: 0.0058 max mem: 33369 +Epoch: [6] [ 240/1319] eta: 0:47:19 lr: 4.298737099190034e-05 loss: 0.1051 (0.1123) time: 2.5951 data: 0.0059 max mem: 33369 +Epoch: [6] [ 250/1319] eta: 0:46:53 lr: 4.297869728545289e-05 loss: 0.0946 (0.1121) time: 2.6213 data: 0.0059 max mem: 33369 +Epoch: [6] [ 260/1319] eta: 0:46:27 lr: 4.2970023384503735e-05 loss: 0.1036 (0.1120) time: 2.6346 data: 0.0058 max mem: 33369 +Epoch: [6] [ 270/1319] eta: 0:46:00 lr: 4.296134928900489e-05 loss: 0.1036 (0.1119) time: 2.6322 data: 0.0058 max mem: 33369 +Epoch: [6] [ 280/1319] eta: 0:45:33 lr: 4.295267499890832e-05 loss: 0.0998 (0.1116) time: 2.6095 data: 0.0059 max mem: 33369 +Epoch: [6] [ 290/1319] eta: 0:45:06 lr: 4.2944000514166015e-05 loss: 0.0886 (0.1114) time: 2.6115 data: 0.0060 max mem: 33369 +Epoch: [6] [ 300/1319] eta: 0:44:40 lr: 4.293532583472992e-05 loss: 0.0853 (0.1109) time: 2.6286 data: 0.0060 max mem: 33369 +Epoch: [6] [ 310/1319] eta: 0:44:12 lr: 4.292665096055194e-05 loss: 0.0899 (0.1109) time: 2.6048 data: 0.0059 max mem: 33369 +Epoch: [6] [ 320/1319] eta: 0:43:45 lr: 4.2917975891583976e-05 loss: 0.1110 (0.1111) time: 2.5921 data: 0.0059 max mem: 33369 +Epoch: [6] [ 330/1319] eta: 0:43:19 lr: 4.2909300627777926e-05 loss: 0.1026 (0.1110) time: 2.6317 data: 0.0059 max mem: 33369 +Epoch: [6] [ 340/1319] eta: 0:42:53 lr: 4.290062516908562e-05 loss: 0.1069 (0.1114) time: 2.6455 data: 0.0058 max mem: 33369 +Epoch: [6] [ 350/1319] eta: 0:42:27 lr: 4.2891949515458894e-05 loss: 0.1071 (0.1111) time: 2.6253 data: 0.0059 max mem: 33369 +Epoch: [6] [ 360/1319] eta: 0:42:00 lr: 4.288327366684957e-05 loss: 0.1071 (0.1118) time: 2.6089 data: 0.0059 max mem: 33369 +Epoch: [6] [ 370/1319] eta: 0:41:33 lr: 4.287459762320942e-05 loss: 0.0990 (0.1111) time: 2.6157 data: 0.0058 max mem: 33369 +Epoch: [6] [ 380/1319] eta: 0:41:07 lr: 4.28659213844902e-05 loss: 0.0975 (0.1112) time: 2.6285 data: 0.0058 max mem: 33369 +Epoch: [6] [ 390/1319] eta: 0:40:40 lr: 4.285724495064366e-05 loss: 0.1127 (0.1114) time: 2.6186 data: 0.0060 max mem: 33369 +Epoch: [6] [ 400/1319] eta: 0:40:14 lr: 4.2848568321621514e-05 loss: 0.1179 (0.1119) time: 2.6206 data: 0.0060 max mem: 33369 +Epoch: [6] [ 410/1319] eta: 0:39:48 lr: 4.283989149737546e-05 loss: 0.1179 (0.1123) time: 2.6346 data: 0.0058 max mem: 33369 +Epoch: [6] [ 420/1319] eta: 0:39:22 lr: 4.283121447785717e-05 loss: 0.1117 (0.1124) time: 2.6320 data: 0.0058 max mem: 33369 +Epoch: [6] [ 430/1319] eta: 0:38:55 lr: 4.2822537263018285e-05 loss: 0.1055 (0.1124) time: 2.6206 data: 0.0058 max mem: 33369 +Epoch: [6] [ 440/1319] eta: 0:38:30 lr: 4.281385985281043e-05 loss: 0.0924 (0.1121) time: 2.6361 data: 0.0059 max mem: 33369 +Epoch: [6] [ 450/1319] eta: 0:38:03 lr: 4.280518224718522e-05 loss: 0.1035 (0.1127) time: 2.6392 data: 0.0059 max mem: 33369 +Epoch: [6] [ 460/1319] eta: 0:37:37 lr: 4.2796504446094225e-05 loss: 0.1202 (0.1127) time: 2.6315 data: 0.0057 max mem: 33369 +Epoch: [6] [ 470/1319] eta: 0:37:10 lr: 4.278782644948901e-05 loss: 0.0998 (0.1126) time: 2.6218 data: 0.0056 max mem: 33369 +Epoch: [6] [ 480/1319] eta: 0:36:45 lr: 4.27791482573211e-05 loss: 0.0998 (0.1124) time: 2.6267 data: 0.0057 max mem: 33369 +Epoch: [6] [ 490/1319] eta: 0:36:18 lr: 4.2770469869541996e-05 loss: 0.0925 (0.1122) time: 2.6467 data: 0.0057 max mem: 33369 +Epoch: [6] [ 500/1319] eta: 0:35:52 lr: 4.276179128610321e-05 loss: 0.0885 (0.1119) time: 2.6234 data: 0.0059 max mem: 33369 +Epoch: [6] [ 510/1319] eta: 0:35:25 lr: 4.2753112506956194e-05 loss: 0.0885 (0.1116) time: 2.6064 data: 0.0061 max mem: 33369 +Epoch: [6] [ 520/1319] eta: 0:34:59 lr: 4.274443353205239e-05 loss: 0.0912 (0.1116) time: 2.6010 data: 0.0060 max mem: 33369 +Epoch: [6] [ 530/1319] eta: 0:34:32 lr: 4.2735754361343224e-05 loss: 0.0855 (0.1116) time: 2.5967 data: 0.0058 max mem: 33369 +Epoch: [6] [ 540/1319] eta: 0:34:05 lr: 4.2727074994780086e-05 loss: 0.0943 (0.1120) time: 2.6017 data: 0.0056 max mem: 33369 +Epoch: [6] [ 550/1319] eta: 0:33:38 lr: 4.271839543231435e-05 loss: 0.1044 (0.1117) time: 2.5985 data: 0.0058 max mem: 33369 +Epoch: [6] [ 560/1319] eta: 0:33:12 lr: 4.270971567389736e-05 loss: 0.1048 (0.1117) time: 2.6086 data: 0.0059 max mem: 33369 +Epoch: [6] [ 570/1319] eta: 0:32:47 lr: 4.270103571948045e-05 loss: 0.0972 (0.1117) time: 2.6506 data: 0.0059 max mem: 33369 +Epoch: [6] [ 580/1319] eta: 0:32:20 lr: 4.2692355569014936e-05 loss: 0.0972 (0.1118) time: 2.6453 data: 0.0058 max mem: 33369 +Epoch: [6] [ 590/1319] eta: 0:31:54 lr: 4.268367522245208e-05 loss: 0.1086 (0.1123) time: 2.6133 data: 0.0058 max mem: 33369 +Epoch: [6] [ 600/1319] eta: 0:31:28 lr: 4.267499467974314e-05 loss: 0.1079 (0.1123) time: 2.6309 data: 0.0058 max mem: 33369 +Epoch: [6] [ 610/1319] eta: 0:31:01 lr: 4.2666313940839357e-05 loss: 0.1035 (0.1124) time: 2.6164 data: 0.0058 max mem: 33369 +Epoch: [6] [ 620/1319] eta: 0:30:34 lr: 4.2657633005691946e-05 loss: 0.1157 (0.1127) time: 2.5824 data: 0.0058 max mem: 33369 +Epoch: [6] [ 630/1319] eta: 0:30:08 lr: 4.264895187425208e-05 loss: 0.1150 (0.1129) time: 2.6006 data: 0.0058 max mem: 33369 +Epoch: [6] [ 640/1319] eta: 0:29:42 lr: 4.264027054647094e-05 loss: 0.1150 (0.1129) time: 2.6220 data: 0.0058 max mem: 33369 +Epoch: [6] [ 650/1319] eta: 0:29:16 lr: 4.263158902229967e-05 loss: 0.0936 (0.1127) time: 2.6277 data: 0.0057 max mem: 33369 +Epoch: [6] [ 660/1319] eta: 0:28:49 lr: 4.262290730168937e-05 loss: 0.0922 (0.1131) time: 2.6142 data: 0.0057 max mem: 33369 +Epoch: [6] [ 670/1319] eta: 0:28:22 lr: 4.261422538459115e-05 loss: 0.0958 (0.1129) time: 2.5828 data: 0.0057 max mem: 33369 +Epoch: [6] [ 680/1319] eta: 0:27:56 lr: 4.260554327095607e-05 loss: 0.1137 (0.1130) time: 2.5954 data: 0.0057 max mem: 33369 +Epoch: [6] [ 690/1319] eta: 0:27:29 lr: 4.2596860960735204e-05 loss: 0.1168 (0.1132) time: 2.6053 data: 0.0058 max mem: 33369 +Epoch: [6] [ 700/1319] eta: 0:27:03 lr: 4.258817845387955e-05 loss: 0.1081 (0.1132) time: 2.6005 data: 0.0059 max mem: 33369 +Epoch: [6] [ 710/1319] eta: 0:26:37 lr: 4.257949575034011e-05 loss: 0.1048 (0.1131) time: 2.6140 data: 0.0058 max mem: 33369 +Epoch: [6] [ 720/1319] eta: 0:26:10 lr: 4.257081285006789e-05 loss: 0.0993 (0.1133) time: 2.6098 data: 0.0057 max mem: 33369 +Epoch: [6] [ 730/1319] eta: 0:25:44 lr: 4.256212975301382e-05 loss: 0.1126 (0.1133) time: 2.6092 data: 0.0059 max mem: 33369 +Epoch: [6] [ 740/1319] eta: 0:25:18 lr: 4.255344645912884e-05 loss: 0.1122 (0.1133) time: 2.6200 data: 0.0059 max mem: 33369 +Epoch: [6] [ 750/1319] eta: 0:24:52 lr: 4.254476296836386e-05 loss: 0.0838 (0.1130) time: 2.6182 data: 0.0059 max mem: 33369 +Epoch: [6] [ 760/1319] eta: 0:24:25 lr: 4.253607928066978e-05 loss: 0.1120 (0.1133) time: 2.6181 data: 0.0059 max mem: 33369 +Epoch: [6] [ 770/1319] eta: 0:23:59 lr: 4.252739539599743e-05 loss: 0.1195 (0.1137) time: 2.6227 data: 0.0058 max mem: 33369 +Epoch: [6] [ 780/1319] eta: 0:23:33 lr: 4.2518711314297674e-05 loss: 0.1268 (0.1138) time: 2.6120 data: 0.0058 max mem: 33369 +Epoch: [6] [ 790/1319] eta: 0:23:07 lr: 4.2510027035521314e-05 loss: 0.1183 (0.1137) time: 2.6263 data: 0.0060 max mem: 33369 +Epoch: [6] [ 800/1319] eta: 0:22:41 lr: 4.250134255961916e-05 loss: 0.1054 (0.1137) time: 2.6308 data: 0.0062 max mem: 33369 +Epoch: [6] [ 810/1319] eta: 0:22:14 lr: 4.2492657886541955e-05 loss: 0.1008 (0.1137) time: 2.6201 data: 0.0059 max mem: 33369 +Epoch: [6] [ 820/1319] eta: 0:21:48 lr: 4.2483973016240455e-05 loss: 0.1069 (0.1138) time: 2.6090 data: 0.0058 max mem: 33369 +Epoch: [6] [ 830/1319] eta: 0:21:22 lr: 4.247528794866539e-05 loss: 0.1069 (0.1142) time: 2.6099 data: 0.0061 max mem: 33369 +Epoch: [6] [ 840/1319] eta: 0:20:55 lr: 4.2466602683767445e-05 loss: 0.0976 (0.1142) time: 2.6183 data: 0.0060 max mem: 33369 +Epoch: [6] [ 850/1319] eta: 0:20:29 lr: 4.24579172214973e-05 loss: 0.1006 (0.1145) time: 2.6181 data: 0.0058 max mem: 33369 +Epoch: [6] [ 860/1319] eta: 0:20:03 lr: 4.244923156180561e-05 loss: 0.1021 (0.1145) time: 2.6235 data: 0.0057 max mem: 33369 +Epoch: [6] [ 870/1319] eta: 0:19:37 lr: 4.2440545704643e-05 loss: 0.0842 (0.1141) time: 2.6086 data: 0.0056 max mem: 33369 +Epoch: [6] [ 880/1319] eta: 0:19:10 lr: 4.243185964996007e-05 loss: 0.0863 (0.1141) time: 2.5949 data: 0.0057 max mem: 33369 +Epoch: [6] [ 890/1319] eta: 0:18:44 lr: 4.24231733977074e-05 loss: 0.1127 (0.1141) time: 2.5970 data: 0.0058 max mem: 33369 +Epoch: [6] [ 900/1319] eta: 0:18:18 lr: 4.2414486947835554e-05 loss: 0.0965 (0.1141) time: 2.6010 data: 0.0057 max mem: 33369 +Epoch: [6] [ 910/1319] eta: 0:17:51 lr: 4.240580030029505e-05 loss: 0.0965 (0.1140) time: 2.6104 data: 0.0057 max mem: 33369 +Epoch: [6] [ 920/1319] eta: 0:17:25 lr: 4.239711345503641e-05 loss: 0.1257 (0.1141) time: 2.6320 data: 0.0059 max mem: 33369 +Epoch: [6] [ 930/1319] eta: 0:16:59 lr: 4.2388426412010114e-05 loss: 0.1069 (0.1140) time: 2.6284 data: 0.0058 max mem: 33369 +Epoch: [6] [ 940/1319] eta: 0:16:33 lr: 4.237973917116662e-05 loss: 0.0958 (0.1139) time: 2.6110 data: 0.0057 max mem: 33369 +Epoch: [6] [ 950/1319] eta: 0:16:07 lr: 4.237105173245638e-05 loss: 0.0958 (0.1140) time: 2.6177 data: 0.0058 max mem: 33369 +Epoch: [6] [ 960/1319] eta: 0:15:40 lr: 4.23623640958298e-05 loss: 0.1081 (0.1140) time: 2.6296 data: 0.0058 max mem: 33369 +Epoch: [6] [ 970/1319] eta: 0:15:14 lr: 4.235367626123727e-05 loss: 0.1081 (0.1139) time: 2.6085 data: 0.0060 max mem: 33369 +Epoch: [6] [ 980/1319] eta: 0:14:48 lr: 4.234498822862916e-05 loss: 0.1030 (0.1139) time: 2.6029 data: 0.0060 max mem: 33369 +Epoch: [6] [ 990/1319] eta: 0:14:22 lr: 4.23362999979558e-05 loss: 0.0933 (0.1138) time: 2.6237 data: 0.0059 max mem: 33369 +Epoch: [6] [1000/1319] eta: 0:13:55 lr: 4.2327611569167524e-05 loss: 0.0940 (0.1139) time: 2.6047 data: 0.0061 max mem: 33369 +Epoch: [6] [1010/1319] eta: 0:13:29 lr: 4.2318922942214635e-05 loss: 0.1065 (0.1139) time: 2.6024 data: 0.0059 max mem: 33369 +Epoch: [6] [1020/1319] eta: 0:13:03 lr: 4.231023411704738e-05 loss: 0.1132 (0.1139) time: 2.6204 data: 0.0059 max mem: 33369 +Epoch: [6] [1030/1319] eta: 0:12:37 lr: 4.230154509361603e-05 loss: 0.1168 (0.1139) time: 2.6145 data: 0.0059 max mem: 33369 +Epoch: [6] [1040/1319] eta: 0:12:11 lr: 4.229285587187079e-05 loss: 0.1114 (0.1139) time: 2.6273 data: 0.0059 max mem: 33369 +Epoch: [6] [1050/1319] eta: 0:11:44 lr: 4.2284166451761876e-05 loss: 0.1044 (0.1140) time: 2.6363 data: 0.0059 max mem: 33369 +Epoch: [6] [1060/1319] eta: 0:11:18 lr: 4.2275476833239456e-05 loss: 0.1024 (0.1140) time: 2.6105 data: 0.0056 max mem: 33369 +Epoch: [6] [1070/1319] eta: 0:10:52 lr: 4.2266787016253686e-05 loss: 0.0975 (0.1138) time: 2.6243 data: 0.0056 max mem: 33369 +Epoch: [6] [1080/1319] eta: 0:10:26 lr: 4.22580970007547e-05 loss: 0.0978 (0.1138) time: 2.6349 data: 0.0058 max mem: 33369 +Epoch: [6] [1090/1319] eta: 0:10:00 lr: 4.224940678669259e-05 loss: 0.1111 (0.1138) time: 2.6034 data: 0.0058 max mem: 33369 +Epoch: [6] [1100/1319] eta: 0:09:33 lr: 4.2240716374017434e-05 loss: 0.1269 (0.1139) time: 2.6046 data: 0.0059 max mem: 33369 +Epoch: [6] [1110/1319] eta: 0:09:07 lr: 4.2232025762679314e-05 loss: 0.1335 (0.1142) time: 2.6258 data: 0.0059 max mem: 33369 +Epoch: [6] [1120/1319] eta: 0:08:41 lr: 4.2223334952628234e-05 loss: 0.1069 (0.1141) time: 2.6207 data: 0.0058 max mem: 33369 +Epoch: [6] [1130/1319] eta: 0:08:15 lr: 4.221464394381422e-05 loss: 0.0898 (0.1141) time: 2.6179 data: 0.0058 max mem: 33369 +Epoch: [6] [1140/1319] eta: 0:07:49 lr: 4.220595273618725e-05 loss: 0.0943 (0.1139) time: 2.6374 data: 0.0058 max mem: 33369 +Epoch: [6] [1150/1319] eta: 0:07:22 lr: 4.2197261329697285e-05 loss: 0.0947 (0.1139) time: 2.6385 data: 0.0059 max mem: 33369 +Epoch: [6] [1160/1319] eta: 0:06:56 lr: 4.218856972429426e-05 loss: 0.1069 (0.1138) time: 2.6126 data: 0.0058 max mem: 33369 +Epoch: [6] [1170/1319] eta: 0:06:30 lr: 4.2179877919928104e-05 loss: 0.1077 (0.1139) time: 2.6019 data: 0.0058 max mem: 33369 +Epoch: [6] [1180/1319] eta: 0:06:04 lr: 4.217118591654868e-05 loss: 0.1171 (0.1141) time: 2.6191 data: 0.0060 max mem: 33369 +Epoch: [6] [1190/1319] eta: 0:05:38 lr: 4.2162493714105874e-05 loss: 0.1246 (0.1143) time: 2.6134 data: 0.0058 max mem: 33369 +Epoch: [6] [1200/1319] eta: 0:05:11 lr: 4.2153801312549505e-05 loss: 0.1066 (0.1142) time: 2.6004 data: 0.0058 max mem: 33369 +Epoch: [6] [1210/1319] eta: 0:04:45 lr: 4.2145108711829405e-05 loss: 0.0951 (0.1140) time: 2.6137 data: 0.0058 max mem: 33369 +Epoch: [6] [1220/1319] eta: 0:04:19 lr: 4.213641591189537e-05 loss: 0.0828 (0.1139) time: 2.6141 data: 0.0057 max mem: 33369 +Epoch: [6] [1230/1319] eta: 0:03:53 lr: 4.212772291269716e-05 loss: 0.1065 (0.1140) time: 2.6221 data: 0.0057 max mem: 33369 +Epoch: [6] [1240/1319] eta: 0:03:26 lr: 4.2119029714184504e-05 loss: 0.1127 (0.1143) time: 2.6078 data: 0.0057 max mem: 33369 +Epoch: [6] [1250/1319] eta: 0:03:00 lr: 4.211033631630714e-05 loss: 0.1006 (0.1142) time: 2.6054 data: 0.0058 max mem: 33369 +Epoch: [6] [1260/1319] eta: 0:02:34 lr: 4.2101642719014764e-05 loss: 0.0993 (0.1142) time: 2.6461 data: 0.0059 max mem: 33369 +Epoch: [6] [1270/1319] eta: 0:02:08 lr: 4.2092948922257045e-05 loss: 0.1147 (0.1144) time: 2.6238 data: 0.0058 max mem: 33369 +Epoch: [6] [1280/1319] eta: 0:01:42 lr: 4.208425492598362e-05 loss: 0.1234 (0.1145) time: 2.5999 data: 0.0059 max mem: 33369 +Epoch: [6] [1290/1319] eta: 0:01:15 lr: 4.207556073014412e-05 loss: 0.1194 (0.1147) time: 2.6160 data: 0.0062 max mem: 33369 +Epoch: [6] [1300/1319] eta: 0:00:49 lr: 4.2066866334688144e-05 loss: 0.1119 (0.1147) time: 2.6283 data: 0.0061 max mem: 33369 +Epoch: [6] [1310/1319] eta: 0:00:23 lr: 4.205817173956526e-05 loss: 0.0962 (0.1147) time: 2.6473 data: 0.0060 max mem: 33369 +Epoch: [6] Total time: 0:57:37 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 3:09:41 time: 4.4233 data: 4.3436 max mem: 33369 +Test: [ 100/2573] eta: 0:04:47 time: 0.0727 data: 0.0012 max mem: 33369 +Test: [ 200/2573] eta: 0:03:46 time: 0.0738 data: 0.0013 max mem: 33369 +Test: [ 300/2573] eta: 0:03:19 time: 0.0753 data: 0.0012 max mem: 33369 +Test: [ 400/2573] eta: 0:03:03 time: 0.0758 data: 0.0012 max mem: 33369 +Test: [ 500/2573] eta: 0:02:50 time: 0.0733 data: 0.0011 max mem: 33369 +Test: [ 600/2573] eta: 0:02:39 time: 0.0734 data: 0.0011 max mem: 33369 +Test: [ 700/2573] eta: 0:02:30 time: 0.0735 data: 0.0011 max mem: 33369 +Test: [ 800/2573] eta: 0:02:20 time: 0.0768 data: 0.0011 max mem: 33369 +Test: [ 900/2573] eta: 0:02:11 time: 0.0736 data: 0.0011 max mem: 33369 +Test: [1000/2573] eta: 0:02:03 time: 0.0736 data: 0.0012 max mem: 33369 +Test: [1100/2573] eta: 0:01:54 time: 0.0734 data: 0.0011 max mem: 33369 +Test: [1200/2573] eta: 0:01:46 time: 0.0736 data: 0.0011 max mem: 33369 +Test: [1300/2573] eta: 0:01:38 time: 0.0734 data: 0.0011 max mem: 33369 +Test: [1400/2573] eta: 0:01:30 time: 0.0720 data: 0.0012 max mem: 33369 +Test: [1500/2573] eta: 0:01:22 time: 0.0737 data: 0.0012 max mem: 33369 +Test: [1600/2573] eta: 0:01:14 time: 0.0769 data: 0.0011 max mem: 33369 +Test: [1700/2573] eta: 0:01:06 time: 0.0719 data: 0.0011 max mem: 33369 +Test: [1800/2573] eta: 0:00:58 time: 0.0755 data: 0.0011 max mem: 33369 +Test: [1900/2573] eta: 0:00:51 time: 0.0721 data: 0.0011 max mem: 33369 +Test: [2000/2573] eta: 0:00:43 time: 0.0736 data: 0.0011 max mem: 33369 +Test: [2100/2573] eta: 0:00:35 time: 0.0754 data: 0.0011 max mem: 33369 +Test: [2200/2573] eta: 0:00:28 time: 0.0753 data: 0.0011 max mem: 33369 +Test: [2300/2573] eta: 0:00:20 time: 0.0754 data: 0.0011 max mem: 33369 +Test: [2400/2573] eta: 0:00:13 time: 0.0703 data: 0.0011 max mem: 33369 +Test: [2500/2573] eta: 0:00:05 time: 0.0736 data: 0.0011 max mem: 33369 +Test: Total time: 0:03:14 +Final results: +Mean IoU is 57.92 + + precision@0.5 = 63.81 + precision@0.6 = 55.33 + precision@0.7 = 46.08 + precision@0.8 = 34.54 + precision@0.9 = 14.17 + overall IoU = 56.39 + +Average object IoU 57.918502407984576 +Overall IoU 56.392417907714844 +Better epoch: 6 + +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [7] [ 0/1319] eta: 1:33:02 lr: 4.205034643319776e-05 loss: 0.0935 (0.0935) time: 4.2323 data: 1.5219 max mem: 33369 +Epoch: [7] [ 10/1319] eta: 1:01:25 lr: 4.204165145856875e-05 loss: 0.0935 (0.0956) time: 2.8156 data: 0.1440 max mem: 33369 +Epoch: [7] [ 20/1319] eta: 0:58:43 lr: 4.203295628412646e-05 loss: 0.0853 (0.0937) time: 2.6366 data: 0.0060 max mem: 33369 +Epoch: [7] [ 30/1319] eta: 0:57:45 lr: 4.202426090982037e-05 loss: 0.0942 (0.0956) time: 2.6190 data: 0.0059 max mem: 33369 +Epoch: [7] [ 40/1319] eta: 0:56:56 lr: 4.201556533559993e-05 loss: 0.0944 (0.1060) time: 2.6276 data: 0.0060 max mem: 33369 +Epoch: [7] [ 50/1319] eta: 0:56:11 lr: 4.2006869561414584e-05 loss: 0.0994 (0.1047) time: 2.6065 data: 0.0061 max mem: 33369 +Epoch: [7] [ 60/1319] eta: 0:55:28 lr: 4.199817358721372e-05 loss: 0.0994 (0.1033) time: 2.5875 data: 0.0061 max mem: 33369 +Epoch: [7] [ 70/1319] eta: 0:55:03 lr: 4.1989477412946735e-05 loss: 0.1025 (0.1068) time: 2.6161 data: 0.0060 max mem: 33369 +Epoch: [7] [ 80/1319] eta: 0:54:38 lr: 4.1980781038562975e-05 loss: 0.1196 (0.1092) time: 2.6520 data: 0.0060 max mem: 33369 +Epoch: [7] [ 90/1319] eta: 0:54:10 lr: 4.1972084464011784e-05 loss: 0.1100 (0.1071) time: 2.6428 data: 0.0061 max mem: 33369 +Epoch: [7] [ 100/1319] eta: 0:53:39 lr: 4.1963387689242456e-05 loss: 0.0836 (0.1081) time: 2.6236 data: 0.0062 max mem: 33369 +Epoch: [7] [ 110/1319] eta: 0:53:13 lr: 4.1954690714204276e-05 loss: 0.1059 (0.1074) time: 2.6291 data: 0.0061 max mem: 33369 +Epoch: [7] [ 120/1319] eta: 0:52:47 lr: 4.194599353884651e-05 loss: 0.1085 (0.1099) time: 2.6451 data: 0.0060 max mem: 33369 +Epoch: [7] [ 130/1319] eta: 0:52:12 lr: 4.193729616311839e-05 loss: 0.1059 (0.1098) time: 2.5936 data: 0.0061 max mem: 33369 +Epoch: [7] [ 140/1319] eta: 0:51:39 lr: 4.1928598586969124e-05 loss: 0.1017 (0.1099) time: 2.5512 data: 0.0062 max mem: 33369 +Epoch: [7] [ 150/1319] eta: 0:51:12 lr: 4.1919900810347894e-05 loss: 0.1006 (0.1089) time: 2.5850 data: 0.0060 max mem: 33369 +Epoch: [7] [ 160/1319] eta: 0:50:45 lr: 4.191120283320388e-05 loss: 0.0903 (0.1089) time: 2.6193 data: 0.0060 max mem: 33369 +Epoch: [7] [ 170/1319] eta: 0:50:18 lr: 4.190250465548619e-05 loss: 0.0903 (0.1081) time: 2.6236 data: 0.0061 max mem: 33369 +Epoch: [7] [ 180/1319] eta: 0:49:54 lr: 4.189380627714394e-05 loss: 0.0785 (0.1090) time: 2.6349 data: 0.0059 max mem: 33369 +Epoch: [7] [ 190/1319] eta: 0:49:26 lr: 4.188510769812624e-05 loss: 0.0805 (0.1086) time: 2.6250 data: 0.0059 max mem: 33369 +Epoch: [7] [ 200/1319] eta: 0:48:59 lr: 4.1876408918382123e-05 loss: 0.0977 (0.1086) time: 2.6109 data: 0.0059 max mem: 33369 +Epoch: [7] [ 210/1319] eta: 0:48:30 lr: 4.1867709937860646e-05 loss: 0.0977 (0.1083) time: 2.5991 data: 0.0060 max mem: 33369 +Epoch: [7] [ 220/1319] eta: 0:48:01 lr: 4.185901075651081e-05 loss: 0.0876 (0.1077) time: 2.5707 data: 0.0061 max mem: 33369 +Epoch: [7] [ 230/1319] eta: 0:47:34 lr: 4.185031137428161e-05 loss: 0.0835 (0.1071) time: 2.5821 data: 0.0062 max mem: 33369 +Epoch: [7] [ 240/1319] eta: 0:47:07 lr: 4.1841611791121996e-05 loss: 0.0942 (0.1067) time: 2.6053 data: 0.0061 max mem: 33369 +Epoch: [7] [ 250/1319] eta: 0:46:43 lr: 4.183291200698093e-05 loss: 0.0862 (0.1061) time: 2.6428 data: 0.0060 max mem: 33369 +Epoch: [7] [ 260/1319] eta: 0:46:16 lr: 4.182421202180731e-05 loss: 0.0862 (0.1056) time: 2.6352 data: 0.0060 max mem: 33369 +Epoch: [7] [ 270/1319] eta: 0:45:48 lr: 4.181551183555002e-05 loss: 0.0889 (0.1055) time: 2.5904 data: 0.0060 max mem: 33369 +Epoch: [7] [ 280/1319] eta: 0:45:23 lr: 4.180681144815793e-05 loss: 0.1041 (0.1056) time: 2.6107 data: 0.0060 max mem: 33369 +Epoch: [7] [ 290/1319] eta: 0:44:57 lr: 4.179811085957988e-05 loss: 0.0945 (0.1051) time: 2.6328 data: 0.0060 max mem: 33369 +Epoch: [7] [ 300/1319] eta: 0:44:30 lr: 4.178941006976469e-05 loss: 0.0896 (0.1053) time: 2.6184 data: 0.0061 max mem: 33369 +Epoch: [7] [ 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+Epoch: [7] [ 390/1319] eta: 0:40:33 lr: 4.171109389729833e-05 loss: 0.0714 (0.1039) time: 2.6298 data: 0.0060 max mem: 33369 +Epoch: [7] [ 400/1319] eta: 0:40:06 lr: 4.1702391092290966e-05 loss: 0.0844 (0.1044) time: 2.6214 data: 0.0059 max mem: 33369 +Epoch: [7] [ 410/1319] eta: 0:39:39 lr: 4.169368808548177e-05 loss: 0.1149 (0.1048) time: 2.5932 data: 0.0057 max mem: 33369 +Epoch: [7] [ 420/1319] eta: 0:39:12 lr: 4.168498487681925e-05 loss: 0.0884 (0.1042) time: 2.5858 data: 0.0057 max mem: 33369 +Epoch: [7] [ 430/1319] eta: 0:38:46 lr: 4.1676281466251895e-05 loss: 0.0798 (0.1040) time: 2.6032 data: 0.0058 max mem: 33369 +Epoch: [7] [ 440/1319] eta: 0:38:20 lr: 4.166757785372817e-05 loss: 0.0892 (0.1042) time: 2.6288 data: 0.0058 max mem: 33369 +Epoch: [7] [ 450/1319] eta: 0:37:55 lr: 4.1658874039196515e-05 loss: 0.1006 (0.1041) time: 2.6381 data: 0.0058 max mem: 33369 +Epoch: [7] [ 460/1319] eta: 0:37:29 lr: 4.165017002260535e-05 loss: 0.1006 (0.1043) time: 2.6411 data: 0.0060 max mem: 33369 +Epoch: [7] [ 470/1319] eta: 0:37:02 lr: 4.164146580390306e-05 loss: 0.0970 (0.1047) time: 2.6138 data: 0.0060 max mem: 33369 +Epoch: [7] [ 480/1319] eta: 0:36:37 lr: 4.163276138303801e-05 loss: 0.0970 (0.1045) time: 2.6205 data: 0.0058 max mem: 33369 +Epoch: [7] [ 490/1319] eta: 0:36:11 lr: 4.1624056759958536e-05 loss: 0.0983 (0.1047) time: 2.6468 data: 0.0059 max mem: 33369 +Epoch: [7] [ 500/1319] eta: 0:35:45 lr: 4.161535193461295e-05 loss: 0.0983 (0.1045) time: 2.6452 data: 0.0058 max mem: 33369 +Epoch: [7] [ 510/1319] eta: 0:35:19 lr: 4.1606646906949546e-05 loss: 0.1019 (0.1046) time: 2.6475 data: 0.0058 max mem: 33369 +Epoch: [7] [ 520/1319] eta: 0:34:53 lr: 4.159794167691658e-05 loss: 0.1098 (0.1050) time: 2.6374 data: 0.0058 max mem: 33369 +Epoch: [7] [ 530/1319] eta: 0:34:26 lr: 4.158923624446229e-05 loss: 0.1108 (0.1053) time: 2.6024 data: 0.0058 max mem: 33369 +Epoch: [7] [ 540/1319] eta: 0:34:01 lr: 4.15805306095349e-05 loss: 0.1013 (0.1055) time: 2.6132 data: 0.0059 max mem: 33369 +Epoch: [7] [ 550/1319] eta: 0:33:35 lr: 4.1571824772082586e-05 loss: 0.1013 (0.1053) time: 2.6392 data: 0.0058 max mem: 33369 +Epoch: [7] [ 560/1319] eta: 0:33:08 lr: 4.156311873205351e-05 loss: 0.0977 (0.1054) time: 2.6245 data: 0.0059 max mem: 33369 +Epoch: [7] [ 570/1319] eta: 0:32:42 lr: 4.1554412489395805e-05 loss: 0.0875 (0.1050) time: 2.6241 data: 0.0060 max mem: 33369 +Epoch: [7] [ 580/1319] eta: 0:32:16 lr: 4.15457060440576e-05 loss: 0.0736 (0.1047) time: 2.6211 data: 0.0058 max mem: 33369 +Epoch: [7] [ 590/1319] eta: 0:31:50 lr: 4.1536999395986964e-05 loss: 0.0981 (0.1050) time: 2.6294 data: 0.0057 max mem: 33369 +Epoch: [7] [ 600/1319] eta: 0:31:24 lr: 4.152829254513196e-05 loss: 0.1137 (0.1056) time: 2.6225 data: 0.0058 max mem: 33369 +Epoch: [7] [ 610/1319] eta: 0:30:58 lr: 4.151958549144062e-05 loss: 0.1094 (0.1055) time: 2.6147 data: 0.0058 max mem: 33369 +Epoch: [7] [ 620/1319] eta: 0:30:31 lr: 4.151087823486097e-05 loss: 0.0955 (0.1055) time: 2.5976 data: 0.0058 max mem: 33369 +Epoch: [7] [ 630/1319] eta: 0:30:04 lr: 4.1502170775340975e-05 loss: 0.0984 (0.1055) time: 2.5703 data: 0.0058 max mem: 33369 +Epoch: [7] [ 640/1319] eta: 0:29:38 lr: 4.14934631128286e-05 loss: 0.1026 (0.1058) time: 2.5990 data: 0.0058 max mem: 33369 +Epoch: [7] [ 650/1319] eta: 0:29:12 lr: 4.148475524727178e-05 loss: 0.1132 (0.1060) time: 2.6237 data: 0.0058 max mem: 33369 +Epoch: [7] [ 660/1319] eta: 0:28:46 lr: 4.147604717861842e-05 loss: 0.1026 (0.1065) time: 2.6329 data: 0.0061 max mem: 33369 +Epoch: [7] [ 670/1319] eta: 0:28:20 lr: 4.14673389068164e-05 loss: 0.0937 (0.1065) time: 2.6299 data: 0.0063 max mem: 33369 +Epoch: [7] [ 680/1319] eta: 0:27:53 lr: 4.145863043181359e-05 loss: 0.0921 (0.1068) time: 2.6133 data: 0.0061 max mem: 33369 +Epoch: [7] [ 690/1319] eta: 0:27:27 lr: 4.144992175355781e-05 loss: 0.0921 (0.1065) time: 2.6160 data: 0.0058 max mem: 33369 +Epoch: [7] [ 700/1319] eta: 0:27:01 lr: 4.1441212871996857e-05 loss: 0.0805 (0.1065) time: 2.6140 data: 0.0057 max mem: 33369 +Epoch: [7] [ 710/1319] eta: 0:26:34 lr: 4.143250378707853e-05 loss: 0.0906 (0.1064) time: 2.6011 data: 0.0060 max mem: 33369 +Epoch: [7] [ 720/1319] eta: 0:26:08 lr: 4.142379449875057e-05 loss: 0.0933 (0.1066) time: 2.5935 data: 0.0059 max mem: 33369 +Epoch: [7] [ 730/1319] eta: 0:25:42 lr: 4.141508500696071e-05 loss: 0.0998 (0.1066) time: 2.5875 data: 0.0058 max mem: 33369 +Epoch: [7] [ 740/1319] eta: 0:25:15 lr: 4.140637531165665e-05 loss: 0.0972 (0.1066) time: 2.5945 data: 0.0060 max mem: 33369 +Epoch: [7] [ 750/1319] eta: 0:24:49 lr: 4.139766541278606e-05 loss: 0.1072 (0.1070) time: 2.6274 data: 0.0058 max mem: 33369 +Epoch: [7] [ 760/1319] eta: 0:24:23 lr: 4.138895531029661e-05 loss: 0.0980 (0.1069) time: 2.6303 data: 0.0057 max mem: 33369 +Epoch: [7] [ 770/1319] eta: 0:23:56 lr: 4.138024500413592e-05 loss: 0.0970 (0.1068) time: 2.5862 data: 0.0058 max mem: 33369 +Epoch: [7] [ 780/1319] eta: 0:23:30 lr: 4.137153449425158e-05 loss: 0.1003 (0.1067) time: 2.5640 data: 0.0058 max mem: 33369 +Epoch: [7] [ 790/1319] eta: 0:23:03 lr: 4.136282378059117e-05 loss: 0.0996 (0.1065) time: 2.5640 data: 0.0059 max mem: 33369 +Epoch: [7] [ 800/1319] eta: 0:22:37 lr: 4.1354112863102244e-05 loss: 0.0988 (0.1066) time: 2.5760 data: 0.0059 max mem: 33369 +Epoch: [7] [ 810/1319] eta: 0:22:11 lr: 4.134540174173232e-05 loss: 0.1191 (0.1068) time: 2.5979 data: 0.0058 max mem: 33369 +Epoch: [7] [ 820/1319] eta: 0:21:45 lr: 4.1336690416428894e-05 loss: 0.0927 (0.1068) time: 2.6311 data: 0.0058 max mem: 33369 +Epoch: [7] [ 830/1319] eta: 0:21:19 lr: 4.132797888713944e-05 loss: 0.0814 (0.1066) time: 2.6410 data: 0.0057 max mem: 33369 +Epoch: [7] [ 840/1319] eta: 0:20:53 lr: 4.13192671538114e-05 loss: 0.0964 (0.1067) time: 2.6130 data: 0.0058 max mem: 33369 +Epoch: [7] [ 850/1319] eta: 0:20:26 lr: 4.1310555216392185e-05 loss: 0.1056 (0.1069) time: 2.5811 data: 0.0059 max mem: 33369 +Epoch: [7] [ 860/1319] eta: 0:20:00 lr: 4.130184307482921e-05 loss: 0.0919 (0.1070) time: 2.5979 data: 0.0058 max mem: 33369 +Epoch: [7] [ 870/1319] eta: 0:19:34 lr: 4.1293130729069835e-05 loss: 0.0813 (0.1068) time: 2.6300 data: 0.0059 max mem: 33369 +Epoch: [7] [ 880/1319] eta: 0:19:08 lr: 4.128441817906139e-05 loss: 0.0895 (0.1069) time: 2.6238 data: 0.0060 max mem: 33369 +Epoch: [7] [ 890/1319] eta: 0:18:42 lr: 4.1275705424751206e-05 loss: 0.0970 (0.1068) time: 2.6313 data: 0.0058 max mem: 33369 +Epoch: [7] [ 900/1319] eta: 0:18:16 lr: 4.1266992466086555e-05 loss: 0.0905 (0.1066) time: 2.6185 data: 0.0058 max mem: 33369 +Epoch: [7] [ 910/1319] eta: 0:17:50 lr: 4.125827930301473e-05 loss: 0.0898 (0.1066) time: 2.6346 data: 0.0059 max mem: 33369 +Epoch: [7] [ 920/1319] eta: 0:17:24 lr: 4.124956593548294e-05 loss: 0.0984 (0.1067) time: 2.6776 data: 0.0058 max mem: 33369 +Epoch: [7] [ 930/1319] eta: 0:16:58 lr: 4.124085236343841e-05 loss: 0.1070 (0.1067) time: 2.6401 data: 0.0057 max mem: 33369 +Epoch: [7] [ 940/1319] eta: 0:16:31 lr: 4.123213858682832e-05 loss: 0.0982 (0.1066) time: 2.5972 data: 0.0057 max mem: 33369 +Epoch: [7] [ 950/1319] eta: 0:16:05 lr: 4.122342460559985e-05 loss: 0.1011 (0.1066) time: 2.6252 data: 0.0058 max mem: 33369 +Epoch: [7] [ 960/1319] eta: 0:15:39 lr: 4.12147104197001e-05 loss: 0.1011 (0.1066) time: 2.6428 data: 0.0057 max mem: 33369 +Epoch: [7] [ 970/1319] eta: 0:15:13 lr: 4.12059960290762e-05 loss: 0.1077 (0.1066) time: 2.6388 data: 0.0057 max mem: 33369 +Epoch: [7] [ 980/1319] eta: 0:14:47 lr: 4.119728143367523e-05 loss: 0.1076 (0.1066) time: 2.6350 data: 0.0058 max mem: 33369 +Epoch: [7] [ 990/1319] eta: 0:14:21 lr: 4.1188566633444246e-05 loss: 0.1186 (0.1068) time: 2.6310 data: 0.0058 max mem: 33369 +Epoch: [7] [1000/1319] eta: 0:13:55 lr: 4.1179851628330275e-05 loss: 0.1186 (0.1067) time: 2.6214 data: 0.0058 max mem: 33369 +Epoch: [7] [1010/1319] eta: 0:13:28 lr: 4.117113641828032e-05 loss: 0.0957 (0.1068) time: 2.6060 data: 0.0057 max mem: 33369 +Epoch: [7] [1020/1319] eta: 0:13:02 lr: 4.116242100324135e-05 loss: 0.0957 (0.1069) time: 2.6140 data: 0.0059 max mem: 33369 +Epoch: [7] [1030/1319] eta: 0:12:36 lr: 4.1153705383160326e-05 loss: 0.0916 (0.1067) time: 2.6286 data: 0.0060 max mem: 33369 +Epoch: [7] [1040/1319] eta: 0:12:10 lr: 4.114498955798418e-05 loss: 0.0939 (0.1067) time: 2.6228 data: 0.0059 max mem: 33369 +Epoch: [7] [1050/1319] eta: 0:11:44 lr: 4.113627352765979e-05 loss: 0.1026 (0.1065) time: 2.6053 data: 0.0059 max mem: 33369 +Epoch: [7] [1060/1319] eta: 0:11:17 lr: 4.1127557292134045e-05 loss: 0.1050 (0.1065) time: 2.6147 data: 0.0058 max mem: 33369 +Epoch: [7] [1070/1319] eta: 0:10:51 lr: 4.111884085135378e-05 loss: 0.1085 (0.1065) time: 2.6161 data: 0.0058 max mem: 33369 +Epoch: [7] [1080/1319] eta: 0:10:25 lr: 4.111012420526582e-05 loss: 0.0962 (0.1065) time: 2.5920 data: 0.0060 max mem: 33369 +Epoch: [7] [1090/1319] eta: 0:09:59 lr: 4.110140735381696e-05 loss: 0.1073 (0.1066) time: 2.5777 data: 0.0061 max mem: 33369 +Epoch: [7] [1100/1319] eta: 0:09:33 lr: 4.109269029695397e-05 loss: 0.1095 (0.1066) time: 2.6128 data: 0.0058 max mem: 33369 +Epoch: [7] [1110/1319] eta: 0:09:07 lr: 4.108397303462358e-05 loss: 0.1025 (0.1066) time: 2.6402 data: 0.0056 max mem: 33369 +Epoch: [7] [1120/1319] eta: 0:08:40 lr: 4.1075255566772506e-05 loss: 0.1025 (0.1066) time: 2.6188 data: 0.0057 max mem: 33369 +Epoch: [7] [1130/1319] eta: 0:08:14 lr: 4.106653789334745e-05 loss: 0.1025 (0.1066) time: 2.6071 data: 0.0057 max mem: 33369 +Epoch: [7] [1140/1319] eta: 0:07:48 lr: 4.105782001429505e-05 loss: 0.1056 (0.1068) time: 2.6021 data: 0.0057 max mem: 33369 +Epoch: [7] [1150/1319] eta: 0:07:22 lr: 4.104910192956196e-05 loss: 0.1219 (0.1069) time: 2.6024 data: 0.0059 max mem: 33369 +Epoch: [7] [1160/1319] eta: 0:06:56 lr: 4.104038363909479e-05 loss: 0.1000 (0.1067) time: 2.6396 data: 0.0059 max mem: 33369 +Epoch: [7] [1170/1319] eta: 0:06:29 lr: 4.1031665142840106e-05 loss: 0.0955 (0.1067) time: 2.6347 data: 0.0057 max mem: 33369 +Epoch: [7] [1180/1319] eta: 0:06:03 lr: 4.1022946440744476e-05 loss: 0.1075 (0.1069) time: 2.6318 data: 0.0058 max mem: 33369 +Epoch: [7] [1190/1319] eta: 0:05:37 lr: 4.1014227532754415e-05 loss: 0.0989 (0.1068) time: 2.6271 data: 0.0058 max mem: 33369 +Epoch: [7] [1200/1319] eta: 0:05:11 lr: 4.100550841881645e-05 loss: 0.0922 (0.1069) time: 2.6115 data: 0.0058 max mem: 33369 +Epoch: [7] [1210/1319] eta: 0:04:45 lr: 4.099678909887704e-05 loss: 0.0962 (0.1069) time: 2.6367 data: 0.0058 max mem: 33369 +Epoch: [7] [1220/1319] eta: 0:04:19 lr: 4.098806957288263e-05 loss: 0.0912 (0.1069) time: 2.6251 data: 0.0061 max mem: 33369 +Epoch: [7] [1230/1319] eta: 0:03:52 lr: 4.0979349840779665e-05 loss: 0.0908 (0.1068) time: 2.6364 data: 0.0060 max mem: 33369 +Epoch: [7] [1240/1319] eta: 0:03:26 lr: 4.0970629902514516e-05 loss: 0.0921 (0.1068) time: 2.6619 data: 0.0057 max mem: 33369 +Epoch: [7] [1250/1319] eta: 0:03:00 lr: 4.0961909758033565e-05 loss: 0.0950 (0.1069) time: 2.6499 data: 0.0056 max mem: 33369 +Epoch: [7] [1260/1319] eta: 0:02:34 lr: 4.095318940728316e-05 loss: 0.1014 (0.1068) time: 2.6308 data: 0.0058 max mem: 33369 +Epoch: [7] [1270/1319] eta: 0:02:08 lr: 4.0944468850209605e-05 loss: 0.0925 (0.1067) time: 2.5975 data: 0.0058 max mem: 33369 +Epoch: [7] [1280/1319] eta: 0:01:42 lr: 4.093574808675919e-05 loss: 0.0912 (0.1068) time: 2.5869 data: 0.0056 max mem: 33369 +Epoch: [7] [1290/1319] eta: 0:01:15 lr: 4.09270271168782e-05 loss: 0.0912 (0.1067) time: 2.5952 data: 0.0057 max mem: 33369 +Epoch: [7] [1300/1319] eta: 0:00:49 lr: 4.091830594051285e-05 loss: 0.0895 (0.1067) time: 2.5755 data: 0.0059 max mem: 33369 +Epoch: [7] [1310/1319] eta: 0:00:23 lr: 4.090958455760934e-05 loss: 0.0939 (0.1067) time: 2.6002 data: 0.0059 max mem: 33369 +Epoch: [7] Total time: 0:57:32 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 2:00:28 time: 2.8093 data: 2.7308 max mem: 33369 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 100/2573] eta: 0:04:04 time: 0.0714 data: 0.0011 max mem: 33369 +Test: [ 200/2573] eta: 0:03:25 time: 0.0729 data: 0.0011 max mem: 33369 +Test: [ 300/2573] eta: 0:03:05 time: 0.0746 data: 0.0011 max mem: 33369 +Test: [ 400/2573] eta: 0:02:52 time: 0.0748 data: 0.0011 max mem: 33369 +Test: [ 500/2573] eta: 0:02:42 time: 0.0733 data: 0.0011 max mem: 33369 +Test: [ 600/2573] eta: 0:02:32 time: 0.0733 data: 0.0011 max mem: 33369 +Test: [ 700/2573] eta: 0:02:24 time: 0.0735 data: 0.0011 max mem: 33369 +Test: [ 800/2573] eta: 0:02:16 time: 0.0767 data: 0.0011 max mem: 33369 +Test: [ 900/2573] eta: 0:02:08 time: 0.0735 data: 0.0011 max mem: 33369 +Test: [1000/2573] eta: 0:02:00 time: 0.0736 data: 0.0012 max mem: 33369 +Test: [1100/2573] eta: 0:01:52 time: 0.0736 data: 0.0012 max mem: 33369 +Test: [1200/2573] eta: 0:01:44 time: 0.0735 data: 0.0011 max mem: 33369 +Test: [1300/2573] eta: 0:01:36 time: 0.0736 data: 0.0011 max mem: 33369 +Test: [1400/2573] eta: 0:01:28 time: 0.0721 data: 0.0012 max mem: 33369 +Test: [1500/2573] eta: 0:01:20 time: 0.0737 data: 0.0011 max mem: 33369 +Test: [1600/2573] eta: 0:01:13 time: 0.0771 data: 0.0011 max mem: 33369 +Test: [1700/2573] eta: 0:01:05 time: 0.0720 data: 0.0011 max mem: 33369 +Test: [1800/2573] eta: 0:00:58 time: 0.0754 data: 0.0012 max mem: 33369 +Test: [1900/2573] eta: 0:00:50 time: 0.0721 data: 0.0011 max mem: 33369 +Test: [2000/2573] eta: 0:00:42 time: 0.0738 data: 0.0011 max mem: 33369 +Test: [2100/2573] eta: 0:00:35 time: 0.0756 data: 0.0011 max mem: 33369 +Test: [2200/2573] eta: 0:00:27 time: 0.0754 data: 0.0011 max mem: 33369 +Test: [2300/2573] eta: 0:00:20 time: 0.0756 data: 0.0011 max mem: 33369 +Test: [2400/2573] eta: 0:00:12 time: 0.0706 data: 0.0011 max mem: 33369 +Test: [2500/2573] eta: 0:00:05 time: 0.0739 data: 0.0012 max mem: 33369 +Test: Total time: 0:03:12 +Final results: +Mean IoU is 57.85 + + precision@0.5 = 64.71 + precision@0.6 = 57.95 + precision@0.7 = 49.69 + precision@0.8 = 37.30 + precision@0.9 = 16.20 + overall IoU = 57.15 + +Average object IoU 57.850895529362354 +Overall IoU 57.15326690673828 +Better epoch: 7 + +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [8] [ 0/1319] eta: 1:27:53 lr: 4.09017351363616e-05 loss: 0.0935 (0.0935) time: 3.9982 data: 1.2852 max mem: 33369 +Epoch: [8] [ 10/1319] eta: 0:59:29 lr: 4.089301336088734e-05 loss: 0.0730 (0.0853) time: 2.7266 data: 0.1221 max mem: 33369 +Epoch: [8] [ 20/1319] eta: 0:58:06 lr: 4.088429137871879e-05 loss: 0.0918 (0.0937) time: 2.6186 data: 0.0059 max mem: 33369 +Epoch: [8] [ 30/1319] eta: 0:57:13 lr: 4.087556918980205e-05 loss: 0.0918 (0.0963) time: 2.6288 data: 0.0061 max mem: 33369 +Epoch: [8] [ 40/1319] eta: 0:56:25 lr: 4.0866846794083216e-05 loss: 0.0777 (0.0924) time: 2.6073 data: 0.0060 max mem: 33369 +Epoch: [8] [ 50/1319] eta: 0:55:41 lr: 4.0858124191508315e-05 loss: 0.0847 (0.0945) time: 2.5865 data: 0.0063 max mem: 33369 +Epoch: [8] [ 60/1319] eta: 0:55:11 lr: 4.08494013820234e-05 loss: 0.0980 (0.0975) time: 2.5974 data: 0.0063 max mem: 33369 +Epoch: [8] [ 70/1319] eta: 0:54:42 lr: 4.0840678365574436e-05 loss: 0.1047 (0.0995) time: 2.6154 data: 0.0061 max mem: 33369 +Epoch: [8] [ 80/1319] eta: 0:54:09 lr: 4.083195514210742e-05 loss: 0.0888 (0.0991) time: 2.5987 data: 0.0062 max mem: 33369 +Epoch: [8] [ 90/1319] eta: 0:53:49 lr: 4.0823231711568287e-05 loss: 0.0808 (0.0973) time: 2.6275 data: 0.0061 max mem: 33369 +Epoch: [8] [ 100/1319] eta: 0:53:16 lr: 4.081450807390295e-05 loss: 0.0867 (0.0976) time: 2.6203 data: 0.0061 max mem: 33369 +Epoch: [8] [ 110/1319] eta: 0:52:49 lr: 4.0805784229057304e-05 loss: 0.0776 (0.0959) time: 2.5929 data: 0.0061 max mem: 33369 +Epoch: [8] [ 120/1319] eta: 0:52:18 lr: 4.079706017697721e-05 loss: 0.0757 (0.0953) time: 2.5965 data: 0.0062 max mem: 33369 +Epoch: [8] [ 130/1319] eta: 0:51:56 lr: 4.0788335917608504e-05 loss: 0.0778 (0.0979) time: 2.6166 data: 0.0061 max mem: 33369 +Epoch: [8] [ 140/1319] eta: 0:51:32 lr: 4.077961145089699e-05 loss: 0.1084 (0.0984) time: 2.6556 data: 0.0060 max mem: 33369 +Epoch: [8] [ 150/1319] eta: 0:51:08 lr: 4.0770886776788466e-05 loss: 0.0972 (0.0983) time: 2.6494 data: 0.0062 max mem: 33369 +Epoch: [8] [ 160/1319] eta: 0:50:42 lr: 4.076216189522867e-05 loss: 0.1014 (0.0989) time: 2.6405 data: 0.0060 max mem: 33369 +Epoch: [8] [ 170/1319] eta: 0:50:17 lr: 4.075343680616333e-05 loss: 0.0861 (0.0976) time: 2.6379 data: 0.0060 max mem: 33369 +Epoch: [8] [ 180/1319] eta: 0:49:51 lr: 4.074471150953815e-05 loss: 0.0806 (0.0983) time: 2.6310 data: 0.0063 max mem: 33369 +Epoch: [8] [ 190/1319] eta: 0:49:24 lr: 4.0735986005298814e-05 loss: 0.0880 (0.0986) time: 2.6208 data: 0.0062 max mem: 33369 +Epoch: [8] [ 200/1319] eta: 0:48:57 lr: 4.072726029339096e-05 loss: 0.0913 (0.0980) time: 2.6155 data: 0.0061 max mem: 33369 +Epoch: [8] [ 210/1319] eta: 0:48:31 lr: 4.07185343737602e-05 loss: 0.0840 (0.0977) time: 2.6233 data: 0.0063 max mem: 33369 +Epoch: [8] [ 220/1319] eta: 0:48:04 lr: 4.070980824635213e-05 loss: 0.0788 (0.0976) time: 2.6204 data: 0.0064 max mem: 33369 +Epoch: [8] [ 230/1319] eta: 0:47:36 lr: 4.070108191111232e-05 loss: 0.0782 (0.0973) time: 2.6016 data: 0.0060 max mem: 33369 +Epoch: [8] [ 240/1319] eta: 0:47:09 lr: 4.069235536798631e-05 loss: 0.0781 (0.0970) time: 2.6023 data: 0.0059 max mem: 33369 +Epoch: [8] [ 250/1319] eta: 0:46:43 lr: 4.0683628616919596e-05 loss: 0.0777 (0.0961) time: 2.6132 data: 0.0060 max mem: 33369 +Epoch: [8] [ 260/1319] eta: 0:46:16 lr: 4.0674901657857675e-05 loss: 0.0755 (0.0965) time: 2.6113 data: 0.0061 max mem: 33369 +Epoch: [8] [ 270/1319] eta: 0:45:51 lr: 4.066617449074599e-05 loss: 0.0926 (0.0968) time: 2.6216 data: 0.0061 max mem: 33369 +Epoch: [8] [ 280/1319] eta: 0:45:24 lr: 4.065744711552997e-05 loss: 0.0940 (0.0972) time: 2.6260 data: 0.0059 max mem: 33369 +Epoch: [8] [ 290/1319] eta: 0:44:57 lr: 4.064871953215503e-05 loss: 0.0997 (0.0974) time: 2.6102 data: 0.0059 max mem: 33369 +Epoch: [8] [ 300/1319] eta: 0:44:31 lr: 4.063999174056654e-05 loss: 0.0983 (0.0977) time: 2.6097 data: 0.0059 max mem: 33369 +Epoch: [8] [ 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+Epoch: [8] [ 390/1319] eta: 0:40:36 lr: 4.056143223763321e-05 loss: 0.0929 (0.0962) time: 2.6066 data: 0.0062 max mem: 33369 +Epoch: [8] [ 400/1319] eta: 0:40:10 lr: 4.055270236089869e-05 loss: 0.0929 (0.0967) time: 2.6173 data: 0.0061 max mem: 33369 +Epoch: [8] [ 410/1319] eta: 0:39:42 lr: 4.054397227534791e-05 loss: 0.0947 (0.0968) time: 2.6022 data: 0.0062 max mem: 33369 +Epoch: [8] [ 420/1319] eta: 0:39:16 lr: 4.0535241980925915e-05 loss: 0.0915 (0.0972) time: 2.5947 data: 0.0062 max mem: 33369 +Epoch: [8] [ 430/1319] eta: 0:38:51 lr: 4.0526511477577724e-05 loss: 0.0823 (0.0968) time: 2.6599 data: 0.0062 max mem: 33369 +Epoch: [8] [ 440/1319] eta: 0:38:25 lr: 4.051778076524832e-05 loss: 0.0831 (0.0970) time: 2.6628 data: 0.0062 max mem: 33369 +Epoch: [8] [ 450/1319] eta: 0:37:59 lr: 4.050904984388268e-05 loss: 0.0846 (0.0967) time: 2.6269 data: 0.0060 max mem: 33369 +Epoch: [8] [ 460/1319] eta: 0:37:32 lr: 4.0500318713425716e-05 loss: 0.0788 (0.0965) time: 2.6021 data: 0.0060 max mem: 33369 +Epoch: [8] [ 470/1319] eta: 0:37:06 lr: 4.0491587373822346e-05 loss: 0.0831 (0.0963) time: 2.5920 data: 0.0060 max mem: 33369 +Epoch: [8] [ 480/1319] eta: 0:36:39 lr: 4.048285582501745e-05 loss: 0.0821 (0.0967) time: 2.6215 data: 0.0062 max mem: 33369 +Epoch: [8] [ 490/1319] eta: 0:36:13 lr: 4.047412406695587e-05 loss: 0.0867 (0.0970) time: 2.6267 data: 0.0062 max mem: 33369 +Epoch: [8] [ 500/1319] eta: 0:35:47 lr: 4.046539209958243e-05 loss: 0.0862 (0.0968) time: 2.6083 data: 0.0062 max mem: 33369 +Epoch: [8] [ 510/1319] eta: 0:35:20 lr: 4.0456659922841925e-05 loss: 0.0831 (0.0967) time: 2.6029 data: 0.0063 max mem: 33369 +Epoch: [8] [ 520/1319] eta: 0:34:54 lr: 4.044792753667913e-05 loss: 0.0834 (0.0968) time: 2.6259 data: 0.0060 max mem: 33369 +Epoch: [8] [ 530/1319] eta: 0:34:28 lr: 4.0439194941038765e-05 loss: 0.0770 (0.0965) time: 2.6236 data: 0.0060 max mem: 33369 +Epoch: [8] [ 540/1319] eta: 0:34:01 lr: 4.043046213586556e-05 loss: 0.0935 (0.0968) time: 2.5957 data: 0.0061 max mem: 33369 +Epoch: [8] [ 550/1319] eta: 0:33:36 lr: 4.042172912110419e-05 loss: 0.0894 (0.0964) time: 2.6266 data: 0.0061 max mem: 33369 +Epoch: [8] [ 560/1319] eta: 0:33:10 lr: 4.0412995896699314e-05 loss: 0.0855 (0.0965) time: 2.6549 data: 0.0061 max mem: 33369 +Epoch: [8] [ 570/1319] eta: 0:32:44 lr: 4.040426246259555e-05 loss: 0.1000 (0.0966) time: 2.6371 data: 0.0061 max mem: 33369 +Epoch: [8] [ 580/1319] eta: 0:32:17 lr: 4.03955288187375e-05 loss: 0.0799 (0.0965) time: 2.6147 data: 0.0060 max mem: 33369 +Epoch: [8] [ 590/1319] eta: 0:31:51 lr: 4.038679496506974e-05 loss: 0.0802 (0.0964) time: 2.6109 data: 0.0060 max mem: 33369 +Epoch: [8] [ 600/1319] eta: 0:31:25 lr: 4.0378060901536817e-05 loss: 0.0873 (0.0967) time: 2.6376 data: 0.0061 max mem: 33369 +Epoch: [8] [ 610/1319] eta: 0:30:58 lr: 4.0369326628083236e-05 loss: 0.0719 (0.0965) time: 2.6094 data: 0.0060 max mem: 33369 +Epoch: [8] [ 620/1319] eta: 0:30:32 lr: 4.0360592144653494e-05 loss: 0.0833 (0.0964) time: 2.5913 data: 0.0057 max mem: 33369 +Epoch: [8] [ 630/1319] eta: 0:30:06 lr: 4.0351857451192053e-05 loss: 0.0892 (0.0966) time: 2.6196 data: 0.0057 max mem: 33369 +Epoch: [8] [ 640/1319] eta: 0:29:39 lr: 4.034312254764333e-05 loss: 0.0818 (0.0965) time: 2.6102 data: 0.0060 max mem: 33369 +Epoch: [8] [ 650/1319] eta: 0:29:13 lr: 4.033438743395174e-05 loss: 0.0790 (0.0965) time: 2.5897 data: 0.0060 max mem: 33369 +Epoch: [8] [ 660/1319] eta: 0:28:46 lr: 4.032565211006165e-05 loss: 0.0777 (0.0964) time: 2.5721 data: 0.0060 max mem: 33369 +Epoch: [8] [ 670/1319] eta: 0:28:19 lr: 4.031691657591742e-05 loss: 0.1049 (0.0968) time: 2.5736 data: 0.0060 max mem: 33369 +Epoch: [8] [ 680/1319] eta: 0:27:53 lr: 4.030818083146336e-05 loss: 0.1046 (0.0968) time: 2.5887 data: 0.0059 max mem: 33369 +Epoch: [8] [ 690/1319] eta: 0:27:26 lr: 4.029944487664375e-05 loss: 0.0856 (0.0970) time: 2.5903 data: 0.0059 max mem: 33369 +Epoch: [8] [ 700/1319] eta: 0:27:00 lr: 4.0290708711402866e-05 loss: 0.0869 (0.0969) time: 2.5933 data: 0.0060 max mem: 33369 +Epoch: [8] [ 710/1319] eta: 0:26:34 lr: 4.028197233568494e-05 loss: 0.0923 (0.0970) time: 2.6115 data: 0.0061 max mem: 33369 +Epoch: [8] [ 720/1319] eta: 0:26:08 lr: 4.027323574943419e-05 loss: 0.1010 (0.0972) time: 2.6231 data: 0.0060 max mem: 33369 +Epoch: [8] [ 730/1319] eta: 0:25:41 lr: 4.0264498952594776e-05 loss: 0.0818 (0.0970) time: 2.5916 data: 0.0061 max mem: 33369 +Epoch: [8] [ 740/1319] eta: 0:25:15 lr: 4.0255761945110847e-05 loss: 0.0824 (0.0970) time: 2.6116 data: 0.0061 max mem: 33369 +Epoch: [8] [ 750/1319] eta: 0:24:49 lr: 4.0247024726926543e-05 loss: 0.0928 (0.0971) time: 2.6429 data: 0.0060 max mem: 33369 +Epoch: [8] [ 760/1319] eta: 0:24:23 lr: 4.0238287297985935e-05 loss: 0.0946 (0.0974) time: 2.6190 data: 0.0060 max mem: 33369 +Epoch: [8] [ 770/1319] eta: 0:23:57 lr: 4.022954965823311e-05 loss: 0.0930 (0.0974) time: 2.6087 data: 0.0061 max mem: 33369 +Epoch: [8] [ 780/1319] eta: 0:23:30 lr: 4.0220811807612084e-05 loss: 0.0965 (0.0974) time: 2.6081 data: 0.0061 max mem: 33369 +Epoch: [8] [ 790/1319] eta: 0:23:04 lr: 4.021207374606688e-05 loss: 0.0882 (0.0973) time: 2.6035 data: 0.0062 max mem: 33369 +Epoch: [8] [ 800/1319] eta: 0:22:38 lr: 4.0203335473541464e-05 loss: 0.0878 (0.0975) time: 2.5937 data: 0.0061 max mem: 33369 +Epoch: [8] [ 810/1319] eta: 0:22:12 lr: 4.01945969899798e-05 loss: 0.1000 (0.0975) time: 2.6048 data: 0.0059 max mem: 33369 +Epoch: [8] [ 820/1319] eta: 0:21:46 lr: 4.0185858295325805e-05 loss: 0.0926 (0.0975) time: 2.6432 data: 0.0060 max mem: 33369 +Epoch: [8] [ 830/1319] eta: 0:21:20 lr: 4.017711938952337e-05 loss: 0.0926 (0.0977) time: 2.6465 data: 0.0060 max mem: 33369 +Epoch: [8] [ 840/1319] eta: 0:20:53 lr: 4.0168380272516376e-05 loss: 0.1185 (0.0982) time: 2.6134 data: 0.0059 max mem: 33369 +Epoch: [8] [ 850/1319] eta: 0:20:27 lr: 4.0159640944248643e-05 loss: 0.1046 (0.0982) time: 2.6141 data: 0.0060 max mem: 33369 +Epoch: [8] [ 860/1319] eta: 0:20:01 lr: 4.0150901404663985e-05 loss: 0.0913 (0.0982) time: 2.6158 data: 0.0060 max mem: 33369 +Epoch: [8] [ 870/1319] eta: 0:19:35 lr: 4.0142161653706185e-05 loss: 0.0986 (0.0983) time: 2.6101 data: 0.0058 max mem: 33369 +Epoch: [8] [ 880/1319] eta: 0:19:09 lr: 4.013342169131899e-05 loss: 0.0990 (0.0986) time: 2.6397 data: 0.0059 max mem: 33369 +Epoch: [8] [ 890/1319] eta: 0:18:43 lr: 4.012468151744613e-05 loss: 0.0990 (0.0987) time: 2.6581 data: 0.0060 max mem: 33369 +Epoch: [8] [ 900/1319] eta: 0:18:17 lr: 4.01159411320313e-05 loss: 0.0976 (0.0988) time: 2.6257 data: 0.0060 max mem: 33369 +Epoch: [8] [ 910/1319] eta: 0:17:50 lr: 4.010720053501816e-05 loss: 0.0976 (0.0988) time: 2.5925 data: 0.0060 max mem: 33369 +Epoch: [8] [ 920/1319] eta: 0:17:24 lr: 4.009845972635034e-05 loss: 0.0865 (0.0987) time: 2.6056 data: 0.0061 max mem: 33369 +Epoch: [8] [ 930/1319] eta: 0:16:58 lr: 4.008971870597147e-05 loss: 0.0822 (0.0986) time: 2.6262 data: 0.0062 max mem: 33369 +Epoch: [8] [ 940/1319] eta: 0:16:32 lr: 4.008097747382511e-05 loss: 0.0943 (0.0987) time: 2.6510 data: 0.0060 max mem: 33369 +Epoch: [8] [ 950/1319] eta: 0:16:06 lr: 4.0072236029854826e-05 loss: 0.0981 (0.0988) time: 2.6318 data: 0.0059 max mem: 33369 +Epoch: [8] [ 960/1319] eta: 0:15:40 lr: 4.006349437400413e-05 loss: 0.0905 (0.0990) time: 2.6355 data: 0.0059 max mem: 33369 +Epoch: [8] [ 970/1319] eta: 0:15:13 lr: 4.005475250621652e-05 loss: 0.0874 (0.0988) time: 2.6359 data: 0.0060 max mem: 33369 +Epoch: [8] [ 980/1319] eta: 0:14:47 lr: 4.004601042643546e-05 loss: 0.0843 (0.0987) time: 2.6000 data: 0.0059 max mem: 33369 +Epoch: [8] [ 990/1319] eta: 0:14:21 lr: 4.003726813460439e-05 loss: 0.0875 (0.0988) time: 2.6127 data: 0.0058 max mem: 33369 +Epoch: [8] [1000/1319] eta: 0:13:55 lr: 4.0028525630666715e-05 loss: 0.0965 (0.0989) time: 2.6438 data: 0.0058 max mem: 33369 +Epoch: [8] [1010/1319] eta: 0:13:29 lr: 4.00197829145658e-05 loss: 0.1006 (0.0992) time: 2.6490 data: 0.0059 max mem: 33369 +Epoch: [8] [1020/1319] eta: 0:13:03 lr: 4.001103998624502e-05 loss: 0.1024 (0.0991) time: 2.6299 data: 0.0057 max mem: 33369 +Epoch: [8] [1030/1319] eta: 0:12:36 lr: 4.000229684564768e-05 loss: 0.0923 (0.0991) time: 2.6089 data: 0.0057 max mem: 33369 +Epoch: [8] [1040/1319] eta: 0:12:10 lr: 3.9993553492717074e-05 loss: 0.0890 (0.0991) time: 2.5954 data: 0.0059 max mem: 33369 +Epoch: [8] [1050/1319] eta: 0:11:44 lr: 3.998480992739647e-05 loss: 0.0926 (0.0995) time: 2.5942 data: 0.0059 max mem: 33369 +Epoch: [8] [1060/1319] eta: 0:11:18 lr: 3.9976066149629094e-05 loss: 0.0986 (0.0994) time: 2.5978 data: 0.0058 max mem: 33369 +Epoch: [8] [1070/1319] eta: 0:10:51 lr: 3.9967322159358156e-05 loss: 0.0904 (0.0993) time: 2.6143 data: 0.0057 max mem: 33369 +Epoch: [8] [1080/1319] eta: 0:10:25 lr: 3.995857795652683e-05 loss: 0.0907 (0.0995) time: 2.6131 data: 0.0057 max mem: 33369 +Epoch: [8] [1090/1319] eta: 0:09:59 lr: 3.994983354107826e-05 loss: 0.0959 (0.0996) time: 2.6003 data: 0.0058 max mem: 33369 +Epoch: [8] [1100/1319] eta: 0:09:33 lr: 3.994108891295557e-05 loss: 0.0856 (0.0995) time: 2.5864 data: 0.0058 max mem: 33369 +Epoch: [8] [1110/1319] eta: 0:09:07 lr: 3.9932344072101854e-05 loss: 0.0919 (0.0996) time: 2.6031 data: 0.0058 max mem: 33369 +Epoch: [8] [1120/1319] eta: 0:08:40 lr: 3.9923599018460164e-05 loss: 0.0941 (0.0995) time: 2.6235 data: 0.0056 max mem: 33369 +Epoch: [8] [1130/1319] eta: 0:08:14 lr: 3.991485375197353e-05 loss: 0.0973 (0.0995) time: 2.6209 data: 0.0058 max mem: 33369 +Epoch: [8] [1140/1319] eta: 0:07:48 lr: 3.990610827258495e-05 loss: 0.1027 (0.0995) time: 2.6030 data: 0.0060 max mem: 33369 +Epoch: [8] [1150/1319] eta: 0:07:22 lr: 3.9897362580237394e-05 loss: 0.0806 (0.0993) time: 2.6181 data: 0.0061 max mem: 33369 +Epoch: [8] [1160/1319] eta: 0:06:56 lr: 3.988861667487383e-05 loss: 0.0806 (0.0993) time: 2.6480 data: 0.0060 max mem: 33369 +Epoch: [8] [1170/1319] eta: 0:06:30 lr: 3.987987055643715e-05 loss: 0.0821 (0.0994) time: 2.6531 data: 0.0058 max mem: 33369 +Epoch: [8] [1180/1319] eta: 0:06:03 lr: 3.9871124224870237e-05 loss: 0.0953 (0.0994) time: 2.6234 data: 0.0059 max mem: 33369 +Epoch: [8] [1190/1319] eta: 0:05:37 lr: 3.986237768011596e-05 loss: 0.0994 (0.0997) time: 2.5866 data: 0.0060 max mem: 33369 +Epoch: [8] [1200/1319] eta: 0:05:11 lr: 3.985363092211714e-05 loss: 0.0995 (0.0998) time: 2.5817 data: 0.0058 max mem: 33369 +Epoch: [8] [1210/1319] eta: 0:04:45 lr: 3.984488395081657e-05 loss: 0.0992 (0.0999) time: 2.5925 data: 0.0058 max mem: 33369 +Epoch: [8] [1220/1319] eta: 0:04:19 lr: 3.9836136766157016e-05 loss: 0.0956 (0.0998) time: 2.6078 data: 0.0057 max mem: 33369 +Epoch: [8] [1230/1319] eta: 0:03:52 lr: 3.9827389368081224e-05 loss: 0.0912 (0.0998) time: 2.6252 data: 0.0059 max mem: 33369 +Epoch: [8] [1240/1319] eta: 0:03:26 lr: 3.9818641756531906e-05 loss: 0.1034 (0.1000) time: 2.6199 data: 0.0060 max mem: 33369 +Epoch: [8] [1250/1319] eta: 0:03:00 lr: 3.980989393145173e-05 loss: 0.1034 (0.1000) time: 2.6170 data: 0.0060 max mem: 33369 +Epoch: [8] [1260/1319] eta: 0:02:34 lr: 3.9801145892783356e-05 loss: 0.0940 (0.1000) time: 2.6331 data: 0.0058 max mem: 33369 +Epoch: [8] [1270/1319] eta: 0:02:08 lr: 3.97923976404694e-05 loss: 0.0942 (0.1000) time: 2.6204 data: 0.0057 max mem: 33369 +Epoch: [8] [1280/1319] eta: 0:01:42 lr: 3.978364917445246e-05 loss: 0.0905 (0.0999) time: 2.6105 data: 0.0056 max mem: 33369 +Epoch: [8] [1290/1319] eta: 0:01:15 lr: 3.9774900494675086e-05 loss: 0.0905 (0.0999) time: 2.6407 data: 0.0057 max mem: 33369 +Epoch: [8] [1300/1319] eta: 0:00:49 lr: 3.976615160107982e-05 loss: 0.0950 (0.1000) time: 2.6542 data: 0.0057 max mem: 33369 +Epoch: [8] [1310/1319] eta: 0:00:23 lr: 3.975740249360917e-05 loss: 0.0932 (0.1000) time: 2.6431 data: 0.0059 max mem: 33369 +Epoch: [8] Total time: 0:57:33 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 1:50:48 time: 2.5840 data: 2.4901 max mem: 33369 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 100/2573] eta: 0:04:03 time: 0.0717 data: 0.0012 max mem: 33369 +Test: [ 200/2573] eta: 0:03:24 time: 0.0730 data: 0.0011 max mem: 33369 +Test: [ 300/2573] eta: 0:03:04 time: 0.0746 data: 0.0012 max mem: 33369 +Test: [ 400/2573] eta: 0:02:52 time: 0.0748 data: 0.0011 max mem: 33369 +Test: [ 500/2573] eta: 0:02:41 time: 0.0732 data: 0.0011 max mem: 33369 +Test: [ 600/2573] eta: 0:02:32 time: 0.0733 data: 0.0011 max mem: 33369 +Test: [ 700/2573] eta: 0:02:24 time: 0.0733 data: 0.0011 max mem: 33369 +Test: [ 800/2573] eta: 0:02:15 time: 0.0767 data: 0.0011 max mem: 33369 +Test: [ 900/2573] eta: 0:02:07 time: 0.0733 data: 0.0011 max mem: 33369 +Test: [1000/2573] eta: 0:01:59 time: 0.0734 data: 0.0011 max mem: 33369 +Test: [1100/2573] eta: 0:01:51 time: 0.0734 data: 0.0011 max mem: 33369 +Test: [1200/2573] eta: 0:01:44 time: 0.0736 data: 0.0011 max mem: 33369 +Test: [1300/2573] eta: 0:01:36 time: 0.0736 data: 0.0011 max mem: 33369 +Test: [1400/2573] eta: 0:01:28 time: 0.0718 data: 0.0011 max mem: 33369 +Test: [1500/2573] eta: 0:01:20 time: 0.0734 data: 0.0011 max mem: 33369 +Test: [1600/2573] eta: 0:01:13 time: 0.0768 data: 0.0011 max mem: 33369 +Test: [1700/2573] eta: 0:01:05 time: 0.0719 data: 0.0011 max mem: 33369 +Test: [1800/2573] eta: 0:00:58 time: 0.0752 data: 0.0011 max mem: 33369 +Test: [1900/2573] eta: 0:00:50 time: 0.0720 data: 0.0011 max mem: 33369 +Test: [2000/2573] eta: 0:00:42 time: 0.0736 data: 0.0011 max mem: 33369 +Test: [2100/2573] eta: 0:00:35 time: 0.0754 data: 0.0011 max mem: 33369 +Test: [2200/2573] eta: 0:00:27 time: 0.0753 data: 0.0011 max mem: 33369 +Test: [2300/2573] eta: 0:00:20 time: 0.0752 data: 0.0011 max mem: 33369 +Test: [2400/2573] eta: 0:00:12 time: 0.0703 data: 0.0011 max mem: 33369 +Test: [2500/2573] eta: 0:00:05 time: 0.0739 data: 0.0011 max mem: 33369 +Test: Total time: 0:03:12 +Final results: +Mean IoU is 59.38 + + precision@0.5 = 66.38 + precision@0.6 = 59.50 + precision@0.7 = 50.92 + precision@0.8 = 38.56 + precision@0.9 = 16.97 + overall IoU = 57.81 + +Average object IoU 59.383974673553155 +Overall IoU 57.81340408325195 +Better epoch: 8 + +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [9] [ 0/1319] eta: 1:29:32 lr: 3.974952811397457e-05 loss: 0.1253 (0.1253) time: 4.0734 data: 1.3454 max mem: 33369 +Epoch: [9] [ 10/1319] eta: 1:00:23 lr: 3.974077859998216e-05 loss: 0.0919 (0.0959) time: 2.7678 data: 0.1278 max mem: 33369 +Epoch: [9] [ 20/1319] eta: 0:58:21 lr: 3.9732028871947454e-05 loss: 0.0843 (0.0907) time: 2.6264 data: 0.0058 max mem: 33369 +Epoch: [9] [ 30/1319] eta: 0:57:06 lr: 3.972327892981283e-05 loss: 0.0736 (0.0871) time: 2.5983 data: 0.0058 max mem: 33369 +Epoch: [9] [ 40/1319] eta: 0:56:21 lr: 3.971452877352066e-05 loss: 0.0802 (0.0993) time: 2.5895 data: 0.0061 max mem: 33369 +Epoch: [9] [ 50/1319] eta: 0:55:39 lr: 3.9705778403013264e-05 loss: 0.0781 (0.0996) time: 2.5908 data: 0.0061 max mem: 33369 +Epoch: [9] [ 60/1319] eta: 0:55:15 lr: 3.969702781823294e-05 loss: 0.0847 (0.0964) time: 2.6113 data: 0.0061 max mem: 33369 +Epoch: [9] [ 70/1319] eta: 0:54:43 lr: 3.9688277019121967e-05 loss: 0.0888 (0.0980) time: 2.6213 data: 0.0061 max mem: 33369 +Epoch: [9] [ 80/1319] eta: 0:54:13 lr: 3.967952600562257e-05 loss: 0.1000 (0.0984) time: 2.6028 data: 0.0061 max mem: 33369 +Epoch: [9] [ 90/1319] eta: 0:53:47 lr: 3.967077477767697e-05 loss: 0.0987 (0.0997) time: 2.6160 data: 0.0060 max mem: 33369 +Epoch: [9] [ 100/1319] eta: 0:53:18 lr: 3.966202333522733e-05 loss: 0.0957 (0.0986) time: 2.6180 data: 0.0061 max mem: 33369 +Epoch: [9] [ 110/1319] eta: 0:52:54 lr: 3.965327167821583e-05 loss: 0.0731 (0.0982) time: 2.6219 data: 0.0060 max mem: 33369 +Epoch: [9] [ 120/1319] eta: 0:52:28 lr: 3.9644519806584564e-05 loss: 0.0873 (0.0983) time: 2.6348 data: 0.0059 max mem: 33369 +Epoch: [9] [ 130/1319] eta: 0:51:58 lr: 3.963576772027564e-05 loss: 0.0939 (0.0977) time: 2.6082 data: 0.0060 max mem: 33369 +Epoch: [9] [ 140/1319] eta: 0:51:34 lr: 3.96270154192311e-05 loss: 0.0796 (0.0967) time: 2.6173 data: 0.0059 max mem: 33369 +Epoch: [9] [ 150/1319] eta: 0:51:07 lr: 3.9618262903393e-05 loss: 0.0830 (0.0965) time: 2.6320 data: 0.0058 max mem: 33369 +Epoch: [9] [ 160/1319] eta: 0:50:41 lr: 3.960951017270332e-05 loss: 0.0747 (0.0947) time: 2.6221 data: 0.0058 max mem: 33369 +Epoch: [9] [ 170/1319] eta: 0:50:16 lr: 3.9600757227104046e-05 loss: 0.0749 (0.0951) time: 2.6373 data: 0.0059 max mem: 33369 +Epoch: [9] [ 180/1319] eta: 0:49:51 lr: 3.95920040665371e-05 loss: 0.1060 (0.0950) time: 2.6445 data: 0.0059 max mem: 33369 +Epoch: [9] [ 190/1319] eta: 0:49:25 lr: 3.958325069094442e-05 loss: 0.0970 (0.0955) time: 2.6402 data: 0.0061 max mem: 33369 +Epoch: [9] [ 200/1319] eta: 0:48:59 lr: 3.957449710026786e-05 loss: 0.0921 (0.0950) time: 2.6298 data: 0.0059 max mem: 33369 +Epoch: [9] [ 210/1319] eta: 0:48:31 lr: 3.9565743294449283e-05 loss: 0.0812 (0.0943) time: 2.6138 data: 0.0058 max mem: 33369 +Epoch: [9] [ 220/1319] eta: 0:48:05 lr: 3.955698927343052e-05 loss: 0.0656 (0.0935) time: 2.6157 data: 0.0060 max mem: 33369 +Epoch: [9] [ 230/1319] eta: 0:47:37 lr: 3.954823503715335e-05 loss: 0.0656 (0.0926) time: 2.6070 data: 0.0060 max mem: 33369 +Epoch: [9] [ 240/1319] eta: 0:47:09 lr: 3.953948058555954e-05 loss: 0.0668 (0.0917) time: 2.5842 data: 0.0060 max mem: 33369 +Epoch: [9] [ 250/1319] eta: 0:46:43 lr: 3.9530725918590825e-05 loss: 0.0680 (0.0912) time: 2.6029 data: 0.0060 max mem: 33369 +Epoch: [9] [ 260/1319] eta: 0:46:15 lr: 3.952197103618889e-05 loss: 0.0733 (0.0908) time: 2.6000 data: 0.0058 max mem: 33369 +Epoch: [9] [ 270/1319] eta: 0:45:47 lr: 3.951321593829542e-05 loss: 0.0733 (0.0907) time: 2.5840 data: 0.0058 max mem: 33369 +Epoch: [9] [ 280/1319] eta: 0:45:21 lr: 3.9504460624852056e-05 loss: 0.0787 (0.0907) time: 2.5954 data: 0.0059 max mem: 33369 +Epoch: [9] [ 290/1319] eta: 0:44:52 lr: 3.94957050958004e-05 loss: 0.0770 (0.0902) time: 2.5823 data: 0.0061 max mem: 33369 +Epoch: [9] [ 300/1319] eta: 0:44:25 lr: 3.9486949351082035e-05 loss: 0.0746 (0.0898) time: 2.5715 data: 0.0061 max mem: 33369 +Epoch: [9] [ 310/1319] eta: 0:43:57 lr: 3.9478193390638515e-05 loss: 0.0835 (0.0901) time: 2.5707 data: 0.0060 max mem: 33369 +Epoch: [9] [ 320/1319] eta: 0:43:32 lr: 3.946943721441136e-05 loss: 0.0884 (0.0899) time: 2.6078 data: 0.0059 max mem: 33369 +Epoch: [9] [ 330/1319] eta: 0:43:06 lr: 3.946068082234206e-05 loss: 0.0748 (0.0898) time: 2.6399 data: 0.0059 max mem: 33369 +Epoch: [9] [ 340/1319] eta: 0:42:40 lr: 3.945192421437206e-05 loss: 0.0797 (0.0897) time: 2.6232 data: 0.0060 max mem: 33369 +Epoch: [9] [ 350/1319] eta: 0:42:15 lr: 3.944316739044282e-05 loss: 0.0871 (0.0899) time: 2.6273 data: 0.0061 max mem: 33369 +Epoch: [9] [ 360/1319] eta: 0:41:48 lr: 3.94344103504957e-05 loss: 0.0871 (0.0897) time: 2.6154 data: 0.0060 max mem: 33369 +Epoch: [9] [ 370/1319] eta: 0:41:22 lr: 3.94256530944721e-05 loss: 0.0850 (0.0900) time: 2.6014 data: 0.0060 max mem: 33369 +Epoch: [9] [ 380/1319] eta: 0:40:55 lr: 3.9416895622313336e-05 loss: 0.0849 (0.0896) time: 2.5960 data: 0.0060 max mem: 33369 +Epoch: [9] [ 390/1319] eta: 0:40:29 lr: 3.9408137933960734e-05 loss: 0.0814 (0.0894) time: 2.6086 data: 0.0059 max mem: 33369 +Epoch: [9] [ 400/1319] eta: 0:40:03 lr: 3.939938002935556e-05 loss: 0.0848 (0.0895) time: 2.6307 data: 0.0060 max mem: 33369 +Epoch: [9] [ 410/1319] eta: 0:39:37 lr: 3.9390621908439054e-05 loss: 0.0754 (0.0892) time: 2.6234 data: 0.0059 max mem: 33369 +Epoch: [9] [ 420/1319] eta: 0:39:11 lr: 3.938186357115245e-05 loss: 0.0729 (0.0893) time: 2.6137 data: 0.0060 max mem: 33369 +Epoch: [9] [ 430/1319] eta: 0:38:44 lr: 3.937310501743692e-05 loss: 0.0773 (0.0896) time: 2.5965 data: 0.0061 max mem: 33369 +Epoch: [9] [ 440/1319] eta: 0:38:18 lr: 3.936434624723363e-05 loss: 0.0936 (0.0899) time: 2.5983 data: 0.0059 max mem: 33369 +Epoch: [9] [ 450/1319] eta: 0:37:52 lr: 3.9355587260483696e-05 loss: 0.0925 (0.0900) time: 2.6208 data: 0.0060 max mem: 33369 +Epoch: [9] [ 460/1319] eta: 0:37:26 lr: 3.9346828057128216e-05 loss: 0.0855 (0.0901) time: 2.6224 data: 0.0061 max mem: 33369 +Epoch: [9] [ 470/1319] eta: 0:36:59 lr: 3.9338068637108247e-05 loss: 0.0773 (0.0897) time: 2.5930 data: 0.0059 max mem: 33369 +Epoch: [9] [ 480/1319] eta: 0:36:33 lr: 3.932930900036482e-05 loss: 0.0731 (0.0895) time: 2.5951 data: 0.0058 max mem: 33369 +Epoch: [9] [ 490/1319] eta: 0:36:07 lr: 3.932054914683895e-05 loss: 0.0777 (0.0896) time: 2.6144 data: 0.0057 max mem: 33369 +Epoch: [9] [ 500/1319] eta: 0:35:40 lr: 3.9311789076471614e-05 loss: 0.0824 (0.0896) time: 2.6131 data: 0.0059 max mem: 33369 +Epoch: [9] [ 510/1319] eta: 0:35:14 lr: 3.930302878920372e-05 loss: 0.0824 (0.0898) time: 2.6180 data: 0.0059 max mem: 33369 +Epoch: [9] [ 520/1319] eta: 0:34:48 lr: 3.929426828497621e-05 loss: 0.1003 (0.0906) time: 2.6069 data: 0.0058 max mem: 33369 +Epoch: [9] [ 530/1319] eta: 0:34:21 lr: 3.9285507563729945e-05 loss: 0.0994 (0.0906) time: 2.5878 data: 0.0057 max mem: 33369 +Epoch: [9] [ 540/1319] eta: 0:33:55 lr: 3.927674662540578e-05 loss: 0.0802 (0.0904) time: 2.5900 data: 0.0058 max mem: 33369 +Epoch: [9] [ 550/1319] eta: 0:33:29 lr: 3.926798546994454e-05 loss: 0.0802 (0.0908) time: 2.6177 data: 0.0058 max mem: 33369 +Epoch: [9] [ 560/1319] eta: 0:33:03 lr: 3.9259224097287e-05 loss: 0.0848 (0.0908) time: 2.6249 data: 0.0060 max mem: 33369 +Epoch: [9] [ 570/1319] eta: 0:32:37 lr: 3.925046250737393e-05 loss: 0.0848 (0.0908) time: 2.6097 data: 0.0060 max mem: 33369 +Epoch: [9] [ 580/1319] eta: 0:32:11 lr: 3.924170070014604e-05 loss: 0.0933 (0.0911) time: 2.6379 data: 0.0059 max mem: 33369 +Epoch: [9] [ 590/1319] eta: 0:31:46 lr: 3.923293867554403e-05 loss: 0.0971 (0.0912) time: 2.6569 data: 0.0057 max mem: 33369 +Epoch: [9] [ 600/1319] eta: 0:31:20 lr: 3.9224176433508566e-05 loss: 0.0948 (0.0914) time: 2.6357 data: 0.0057 max mem: 33369 +Epoch: [9] [ 610/1319] eta: 0:30:53 lr: 3.9215413973980275e-05 loss: 0.0826 (0.0913) time: 2.6126 data: 0.0059 max mem: 33369 +Epoch: [9] [ 620/1319] eta: 0:30:27 lr: 3.920665129689976e-05 loss: 0.0773 (0.0913) time: 2.6133 data: 0.0059 max mem: 33369 +Epoch: [9] [ 630/1319] eta: 0:30:01 lr: 3.919788840220759e-05 loss: 0.0773 (0.0913) time: 2.5928 data: 0.0059 max mem: 33369 +Epoch: [9] [ 640/1319] eta: 0:29:34 lr: 3.918912528984432e-05 loss: 0.0724 (0.0911) time: 2.5649 data: 0.0061 max mem: 33369 +Epoch: [9] [ 650/1319] eta: 0:29:07 lr: 3.918036195975044e-05 loss: 0.0634 (0.0909) time: 2.5786 data: 0.0061 max mem: 33369 +Epoch: [9] [ 660/1319] eta: 0:28:41 lr: 3.9171598411866434e-05 loss: 0.0685 (0.0910) time: 2.5891 data: 0.0060 max mem: 33369 +Epoch: [9] [ 670/1319] eta: 0:28:15 lr: 3.9162834646132755e-05 loss: 0.0822 (0.0911) time: 2.6233 data: 0.0060 max mem: 33369 +Epoch: [9] [ 680/1319] eta: 0:27:49 lr: 3.915407066248981e-05 loss: 0.0814 (0.0914) time: 2.6106 data: 0.0058 max mem: 33369 +Epoch: [9] [ 690/1319] eta: 0:27:23 lr: 3.914530646087798e-05 loss: 0.0890 (0.0914) time: 2.6042 data: 0.0058 max mem: 33369 +Epoch: [9] [ 700/1319] eta: 0:26:57 lr: 3.9136542041237625e-05 loss: 0.0857 (0.0913) time: 2.6323 data: 0.0058 max mem: 33369 +Epoch: [9] [ 710/1319] eta: 0:26:31 lr: 3.9127777403509066e-05 loss: 0.0829 (0.0913) time: 2.6226 data: 0.0058 max mem: 33369 +Epoch: [9] [ 720/1319] eta: 0:26:05 lr: 3.9119012547632586e-05 loss: 0.0836 (0.0914) time: 2.6203 data: 0.0058 max mem: 33369 +Epoch: [9] [ 730/1319] eta: 0:25:39 lr: 3.911024747354846e-05 loss: 0.0901 (0.0912) time: 2.6331 data: 0.0059 max mem: 33369 +Epoch: [9] [ 740/1319] eta: 0:25:13 lr: 3.9101482181196904e-05 loss: 0.0890 (0.0913) time: 2.6290 data: 0.0059 max mem: 33369 +Epoch: [9] [ 750/1319] eta: 0:24:47 lr: 3.909271667051812e-05 loss: 0.0763 (0.0914) time: 2.6279 data: 0.0058 max mem: 33369 +Epoch: [9] [ 760/1319] eta: 0:24:21 lr: 3.908395094145227e-05 loss: 0.0854 (0.0915) time: 2.6214 data: 0.0060 max mem: 33369 +Epoch: [9] [ 770/1319] eta: 0:23:54 lr: 3.9075184993939487e-05 loss: 0.0854 (0.0915) time: 2.5987 data: 0.0059 max mem: 33369 +Epoch: [9] [ 780/1319] eta: 0:23:28 lr: 3.906641882791989e-05 loss: 0.0905 (0.0916) time: 2.5987 data: 0.0058 max mem: 33369 +Epoch: [9] [ 790/1319] eta: 0:23:02 lr: 3.9057652443333534e-05 loss: 0.0905 (0.0916) time: 2.5949 data: 0.0059 max mem: 33369 +Epoch: [9] [ 800/1319] eta: 0:22:36 lr: 3.904888584012046e-05 loss: 0.0768 (0.0917) time: 2.6027 data: 0.0057 max mem: 33369 +Epoch: [9] [ 810/1319] eta: 0:22:10 lr: 3.904011901822068e-05 loss: 0.0768 (0.0920) time: 2.6126 data: 0.0058 max mem: 33369 +Epoch: [9] [ 820/1319] eta: 0:21:43 lr: 3.9031351977574175e-05 loss: 0.0792 (0.0922) time: 2.6021 data: 0.0059 max mem: 33369 +Epoch: [9] [ 830/1319] eta: 0:21:17 lr: 3.9022584718120886e-05 loss: 0.0819 (0.0924) time: 2.6176 data: 0.0060 max mem: 33369 +Epoch: [9] [ 840/1319] eta: 0:20:51 lr: 3.901381723980073e-05 loss: 0.0953 (0.0925) time: 2.6216 data: 0.0058 max mem: 33369 +Epoch: [9] [ 850/1319] eta: 0:20:25 lr: 3.900504954255358e-05 loss: 0.0897 (0.0926) time: 2.5996 data: 0.0059 max mem: 33369 +Epoch: [9] [ 860/1319] eta: 0:19:59 lr: 3.899628162631931e-05 loss: 0.0835 (0.0926) time: 2.5932 data: 0.0060 max mem: 33369 +Epoch: [9] [ 870/1319] eta: 0:19:33 lr: 3.898751349103772e-05 loss: 0.0822 (0.0926) time: 2.6103 data: 0.0059 max mem: 33369 +Epoch: [9] [ 880/1319] eta: 0:19:07 lr: 3.8978745136648617e-05 loss: 0.0865 (0.0926) time: 2.6236 data: 0.0060 max mem: 33369 +Epoch: [9] [ 890/1319] eta: 0:18:41 lr: 3.896997656309173e-05 loss: 0.0870 (0.0929) time: 2.6305 data: 0.0059 max mem: 33369 +Epoch: [9] [ 900/1319] eta: 0:18:15 lr: 3.896120777030681e-05 loss: 0.0953 (0.0930) time: 2.6323 data: 0.0058 max mem: 33369 +Epoch: [9] [ 910/1319] eta: 0:17:48 lr: 3.895243875823353e-05 loss: 0.0733 (0.0929) time: 2.6106 data: 0.0059 max mem: 33369 +Epoch: [9] [ 920/1319] eta: 0:17:22 lr: 3.894366952681158e-05 loss: 0.0890 (0.0930) time: 2.6021 data: 0.0060 max mem: 33369 +Epoch: [9] [ 930/1319] eta: 0:16:56 lr: 3.8934900075980555e-05 loss: 0.0924 (0.0931) time: 2.6093 data: 0.0058 max mem: 33369 +Epoch: [9] [ 940/1319] eta: 0:16:30 lr: 3.8926130405680076e-05 loss: 0.0903 (0.0930) time: 2.6321 data: 0.0057 max mem: 33369 +Epoch: [9] [ 950/1319] eta: 0:16:04 lr: 3.8917360515849704e-05 loss: 0.0876 (0.0929) time: 2.6406 data: 0.0057 max mem: 33369 +Epoch: [9] [ 960/1319] eta: 0:15:38 lr: 3.8908590406428975e-05 loss: 0.0791 (0.0928) time: 2.6365 data: 0.0058 max mem: 33369 +Epoch: [9] [ 970/1319] eta: 0:15:12 lr: 3.889982007735738e-05 loss: 0.0807 (0.0928) time: 2.6286 data: 0.0059 max mem: 33369 +Epoch: [9] [ 980/1319] eta: 0:14:46 lr: 3.889104952857442e-05 loss: 0.0712 (0.0926) time: 2.6041 data: 0.0062 max mem: 33369 +Epoch: [9] [ 990/1319] eta: 0:14:20 lr: 3.888227876001951e-05 loss: 0.0820 (0.0928) time: 2.6224 data: 0.0062 max mem: 33369 +Epoch: [9] [1000/1319] eta: 0:13:53 lr: 3.887350777163206e-05 loss: 0.0963 (0.0929) time: 2.6332 data: 0.0058 max mem: 33369 +Epoch: [9] [1010/1319] eta: 0:13:27 lr: 3.886473656335145e-05 loss: 0.0757 (0.0928) time: 2.5865 data: 0.0057 max mem: 33369 +Epoch: [9] [1020/1319] eta: 0:13:01 lr: 3.8855965135117015e-05 loss: 0.0790 (0.0928) time: 2.5840 data: 0.0058 max mem: 33369 +Epoch: [9] [1030/1319] eta: 0:12:35 lr: 3.8847193486868084e-05 loss: 0.0828 (0.0931) time: 2.6015 data: 0.0058 max mem: 33369 +Epoch: [9] [1040/1319] eta: 0:12:09 lr: 3.883842161854392e-05 loss: 0.0799 (0.0929) time: 2.6138 data: 0.0057 max mem: 33369 +Epoch: [9] [1050/1319] eta: 0:11:43 lr: 3.8829649530083775e-05 loss: 0.0958 (0.0931) time: 2.6162 data: 0.0057 max mem: 33369 +Epoch: [9] [1060/1319] eta: 0:11:16 lr: 3.882087722142687e-05 loss: 0.0958 (0.0931) time: 2.5993 data: 0.0059 max mem: 33369 +Epoch: [9] [1070/1319] eta: 0:10:50 lr: 3.8812104692512384e-05 loss: 0.0855 (0.0933) time: 2.6199 data: 0.0059 max mem: 33369 +Epoch: [9] [1080/1319] eta: 0:10:24 lr: 3.880333194327947e-05 loss: 0.0977 (0.0934) time: 2.6219 data: 0.0058 max mem: 33369 +Epoch: [9] [1090/1319] eta: 0:09:58 lr: 3.879455897366725e-05 loss: 0.0823 (0.0934) time: 2.6190 data: 0.0058 max mem: 33369 +Epoch: [9] [1100/1319] eta: 0:09:32 lr: 3.878578578361481e-05 loss: 0.0833 (0.0933) time: 2.6435 data: 0.0057 max mem: 33369 +Epoch: [9] [1110/1319] eta: 0:09:06 lr: 3.87770123730612e-05 loss: 0.0833 (0.0933) time: 2.6452 data: 0.0057 max mem: 33369 +Epoch: [9] [1120/1319] eta: 0:08:40 lr: 3.876823874194545e-05 loss: 0.0776 (0.0932) time: 2.6139 data: 0.0057 max mem: 33369 +Epoch: [9] [1130/1319] eta: 0:08:14 lr: 3.8759464890206544e-05 loss: 0.0751 (0.0932) time: 2.5938 data: 0.0058 max mem: 33369 +Epoch: [9] [1140/1319] eta: 0:07:47 lr: 3.875069081778345e-05 loss: 0.0843 (0.0933) time: 2.6038 data: 0.0059 max mem: 33369 +Epoch: [9] [1150/1319] eta: 0:07:21 lr: 3.874191652461509e-05 loss: 0.0956 (0.0932) time: 2.6130 data: 0.0058 max mem: 33369 +Epoch: [9] [1160/1319] eta: 0:06:55 lr: 3.8733142010640345e-05 loss: 0.0822 (0.0933) time: 2.6177 data: 0.0057 max mem: 33369 +Epoch: [9] [1170/1319] eta: 0:06:29 lr: 3.872436727579809e-05 loss: 0.0808 (0.0933) time: 2.6298 data: 0.0059 max mem: 33369 +Epoch: [9] [1180/1319] eta: 0:06:03 lr: 3.871559232002716e-05 loss: 0.0808 (0.0932) time: 2.6079 data: 0.0057 max mem: 33369 +Epoch: [9] [1190/1319] eta: 0:05:37 lr: 3.870681714326634e-05 loss: 0.0878 (0.0933) time: 2.5967 data: 0.0056 max mem: 33369 +Epoch: [9] [1200/1319] eta: 0:05:11 lr: 3.86980417454544e-05 loss: 0.0867 (0.0932) time: 2.5960 data: 0.0058 max mem: 33369 +Epoch: [9] [1210/1319] eta: 0:04:44 lr: 3.8689266126530076e-05 loss: 0.0913 (0.0933) time: 2.6016 data: 0.0058 max mem: 33369 +Epoch: [9] [1220/1319] eta: 0:04:18 lr: 3.868049028643206e-05 loss: 0.0960 (0.0934) time: 2.6168 data: 0.0057 max mem: 33369 +Epoch: [9] [1230/1319] eta: 0:03:52 lr: 3.867171422509902e-05 loss: 0.0777 (0.0933) time: 2.6155 data: 0.0057 max mem: 33369 +Epoch: [9] [1240/1319] eta: 0:03:26 lr: 3.866293794246959e-05 loss: 0.0878 (0.0934) time: 2.6198 data: 0.0059 max mem: 33369 +Epoch: [9] [1250/1319] eta: 0:03:00 lr: 3.8654161438482394e-05 loss: 0.0878 (0.0933) time: 2.6225 data: 0.0057 max mem: 33369 +Epoch: [9] [1260/1319] eta: 0:02:34 lr: 3.864538471307598e-05 loss: 0.0788 (0.0932) time: 2.6404 data: 0.0056 max mem: 33369 +Epoch: [9] [1270/1319] eta: 0:02:08 lr: 3.863660776618888e-05 loss: 0.0788 (0.0932) time: 2.6366 data: 0.0059 max mem: 33369 +Epoch: [9] [1280/1319] eta: 0:01:41 lr: 3.8627830597759606e-05 loss: 0.0901 (0.0932) time: 2.6269 data: 0.0060 max mem: 33369 +Epoch: [9] [1290/1319] eta: 0:01:15 lr: 3.861905320772664e-05 loss: 0.1055 (0.0935) time: 2.6279 data: 0.0061 max mem: 33369 +Epoch: [9] [1300/1319] eta: 0:00:49 lr: 3.861027559602841e-05 loss: 0.0893 (0.0934) time: 2.6364 data: 0.0059 max mem: 33369 +Epoch: [9] [1310/1319] eta: 0:00:23 lr: 3.860149776260333e-05 loss: 0.0912 (0.0935) time: 2.6263 data: 0.0057 max mem: 33369 +Epoch: [9] Total time: 0:57:28 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 3:22:09 time: 4.7141 data: 4.6328 max mem: 33369 +Test: [ 100/2573] eta: 0:04:51 time: 0.0716 data: 0.0012 max mem: 33369 +Test: [ 200/2573] eta: 0:03:47 time: 0.0729 data: 0.0011 max mem: 33369 +Test: [ 300/2573] eta: 0:03:19 time: 0.0745 data: 0.0011 max mem: 33369 +Test: [ 400/2573] eta: 0:03:02 time: 0.0748 data: 0.0011 max mem: 33369 +Test: [ 500/2573] eta: 0:02:49 time: 0.0732 data: 0.0011 max mem: 33369 +Test: [ 600/2573] eta: 0:02:39 time: 0.0733 data: 0.0011 max mem: 33369 +Test: [ 700/2573] eta: 0:02:29 time: 0.0734 data: 0.0011 max mem: 33369 +Test: [ 800/2573] eta: 0:02:20 time: 0.0767 data: 0.0011 max mem: 33369 +Test: [ 900/2573] eta: 0:02:11 time: 0.0734 data: 0.0012 max mem: 33369 +Test: [1000/2573] eta: 0:02:03 time: 0.0736 data: 0.0012 max mem: 33369 +Test: [1100/2573] eta: 0:01:54 time: 0.0736 data: 0.0012 max mem: 33369 +Test: [1200/2573] eta: 0:01:46 time: 0.0734 data: 0.0011 max mem: 33369 +Test: [1300/2573] eta: 0:01:38 time: 0.0734 data: 0.0011 max mem: 33369 +Test: [1400/2573] eta: 0:01:30 time: 0.0720 data: 0.0011 max mem: 33369 +Test: [1500/2573] eta: 0:01:22 time: 0.0736 data: 0.0011 max mem: 33369 +Test: [1600/2573] eta: 0:01:14 time: 0.0768 data: 0.0011 max mem: 33369 +Test: [1700/2573] eta: 0:01:06 time: 0.0719 data: 0.0011 max mem: 33369 +Test: [1800/2573] eta: 0:00:58 time: 0.0751 data: 0.0011 max mem: 33369 +Test: [1900/2573] eta: 0:00:51 time: 0.0719 data: 0.0011 max mem: 33369 +Test: [2000/2573] eta: 0:00:43 time: 0.0736 data: 0.0011 max mem: 33369 +Test: [2100/2573] eta: 0:00:35 time: 0.0752 data: 0.0011 max mem: 33369 +Test: [2200/2573] eta: 0:00:28 time: 0.0752 data: 0.0011 max mem: 33369 +Test: [2300/2573] eta: 0:00:20 time: 0.0752 data: 0.0011 max mem: 33369 +Test: [2400/2573] eta: 0:00:13 time: 0.0704 data: 0.0011 max mem: 33369 +Test: [2500/2573] eta: 0:00:05 time: 0.0737 data: 0.0011 max mem: 33369 +Test: Total time: 0:03:14 +Final results: +Mean IoU is 57.37 + + precision@0.5 = 64.38 + precision@0.6 = 58.74 + precision@0.7 = 50.96 + precision@0.8 = 38.52 + precision@0.9 = 17.97 + overall IoU = 57.49 + +Average object IoU 57.37138054017128 +Overall IoU 57.486106872558594 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [10] [ 0/1319] eta: 3:05:47 lr: 3.859359752289337e-05 loss: 0.1324 (0.1324) time: 8.4515 data: 1.6641 max mem: 33369 +Epoch: [10] [ 10/1319] eta: 1:10:01 lr: 3.858481926801746e-05 loss: 0.0901 (0.0914) time: 3.2097 data: 0.1566 max mem: 33369 +Epoch: [10] [ 20/1319] eta: 1:03:14 lr: 3.857604079123589e-05 loss: 0.0822 (0.0856) time: 2.6447 data: 0.0057 max mem: 33369 +Epoch: [10] [ 30/1319] eta: 1:00:27 lr: 3.856726209248695e-05 loss: 0.0893 (0.0881) time: 2.5968 data: 0.0059 max mem: 33369 +Epoch: [10] [ 40/1319] eta: 0:58:50 lr: 3.855848317170887e-05 loss: 0.0920 (0.0928) time: 2.5909 data: 0.0063 max mem: 33369 +Epoch: [10] [ 50/1319] eta: 0:57:36 lr: 3.854970402883988e-05 loss: 0.0947 (0.0916) time: 2.5841 data: 0.0062 max mem: 33369 +Epoch: [10] [ 60/1319] eta: 0:56:52 lr: 3.854092466381814e-05 loss: 0.0768 (0.0895) time: 2.6086 data: 0.0060 max mem: 33369 +Epoch: [10] [ 70/1319] eta: 0:56:14 lr: 3.853214507658182e-05 loss: 0.0664 (0.0896) time: 2.6454 data: 0.0061 max mem: 33369 +Epoch: [10] [ 80/1319] eta: 0:55:38 lr: 3.852336526706903e-05 loss: 0.0862 (0.0909) time: 2.6450 data: 0.0060 max mem: 33369 +Epoch: [10] [ 90/1319] eta: 0:55:02 lr: 3.8514585235217835e-05 loss: 0.0862 (0.0906) time: 2.6361 data: 0.0060 max mem: 33369 +Epoch: [10] [ 100/1319] eta: 0:54:30 lr: 3.850580498096631e-05 loss: 0.0724 (0.0893) time: 2.6391 data: 0.0061 max mem: 33369 +Epoch: [10] [ 110/1319] eta: 0:53:58 lr: 3.849702450425245e-05 loss: 0.0724 (0.0883) time: 2.6387 data: 0.0060 max mem: 33369 +Epoch: [10] [ 120/1319] eta: 0:53:29 lr: 3.8488243805014244e-05 loss: 0.0728 (0.0871) time: 2.6463 data: 0.0059 max mem: 33369 +Epoch: [10] [ 130/1319] eta: 0:52:58 lr: 3.8479462883189646e-05 loss: 0.0784 (0.0875) time: 2.6441 data: 0.0060 max mem: 33369 +Epoch: [10] [ 140/1319] eta: 0:52:30 lr: 3.8470681738716575e-05 loss: 0.0793 (0.0874) time: 2.6405 data: 0.0061 max mem: 33369 +Epoch: [10] [ 150/1319] eta: 0:51:53 lr: 3.846190037153291e-05 loss: 0.0773 (0.0872) time: 2.6011 data: 0.0060 max mem: 33369 +Epoch: [10] [ 160/1319] eta: 0:51:21 lr: 3.84531187815765e-05 loss: 0.0773 (0.0867) time: 2.5640 data: 0.0060 max mem: 33369 +Epoch: [10] [ 170/1319] eta: 0:50:54 lr: 3.844433696878517e-05 loss: 0.0748 (0.0860) time: 2.6195 data: 0.0059 max mem: 33369 +Epoch: [10] [ 180/1319] eta: 0:50:25 lr: 3.843555493309671e-05 loss: 0.0742 (0.0853) time: 2.6416 data: 0.0060 max mem: 33369 +Epoch: [10] [ 190/1319] eta: 0:49:58 lr: 3.842677267444885e-05 loss: 0.0742 (0.0859) time: 2.6324 data: 0.0059 max mem: 33369 +Epoch: [10] [ 200/1319] eta: 0:49:29 lr: 3.8417990192779335e-05 loss: 0.0754 (0.0855) time: 2.6226 data: 0.0060 max mem: 33369 +Epoch: [10] [ 210/1319] eta: 0:48:58 lr: 3.8409207488025836e-05 loss: 0.0754 (0.0869) time: 2.5953 data: 0.0062 max mem: 33369 +Epoch: [10] [ 220/1319] eta: 0:48:31 lr: 3.8400424560126e-05 loss: 0.0732 (0.0860) time: 2.6039 data: 0.0062 max mem: 33369 +Epoch: [10] [ 230/1319] eta: 0:48:01 lr: 3.839164140901745e-05 loss: 0.0759 (0.0859) time: 2.5985 data: 0.0062 max mem: 33369 +Epoch: [10] [ 240/1319] eta: 0:47:34 lr: 3.838285803463778e-05 loss: 0.0821 (0.0862) time: 2.6042 data: 0.0061 max mem: 33369 +Epoch: [10] [ 250/1319] eta: 0:47:09 lr: 3.8374074436924536e-05 loss: 0.0898 (0.0863) time: 2.6584 data: 0.0060 max mem: 33369 +Epoch: [10] [ 260/1319] eta: 0:46:41 lr: 3.836529061581523e-05 loss: 0.0736 (0.0857) time: 2.6436 data: 0.0060 max mem: 33369 +Epoch: [10] [ 270/1319] eta: 0:46:13 lr: 3.8356506571247355e-05 loss: 0.0818 (0.0863) time: 2.6061 data: 0.0060 max mem: 33369 +Epoch: [10] [ 280/1319] eta: 0:45:44 lr: 3.834772230315837e-05 loss: 0.0871 (0.0861) time: 2.5988 data: 0.0062 max mem: 33369 +Epoch: [10] [ 290/1319] eta: 0:45:17 lr: 3.833893781148568e-05 loss: 0.0768 (0.0857) time: 2.5998 data: 0.0062 max mem: 33369 +Epoch: [10] [ 300/1319] eta: 0:44:50 lr: 3.833015309616668e-05 loss: 0.0791 (0.0857) time: 2.6205 data: 0.0059 max mem: 33369 +Epoch: [10] [ 310/1319] eta: 0:44:23 lr: 3.832136815713871e-05 loss: 0.0791 (0.0859) time: 2.6333 data: 0.0060 max mem: 33369 +Epoch: [10] [ 320/1319] eta: 0:43:57 lr: 3.83125829943391e-05 loss: 0.0859 (0.0863) time: 2.6436 data: 0.0062 max mem: 33369 +Epoch: [10] [ 330/1319] eta: 0:43:30 lr: 3.830379760770512e-05 loss: 0.0859 (0.0860) time: 2.6316 data: 0.0061 max mem: 33369 +Epoch: [10] [ 340/1319] eta: 0:43:04 lr: 3.829501199717404e-05 loss: 0.0821 (0.0860) time: 2.6344 data: 0.0058 max mem: 33369 +Epoch: [10] [ 350/1319] eta: 0:42:38 lr: 3.828622616268306e-05 loss: 0.0844 (0.0858) time: 2.6446 data: 0.0057 max mem: 33369 +Epoch: [10] [ 360/1319] eta: 0:42:10 lr: 3.8277440104169376e-05 loss: 0.0775 (0.0858) time: 2.6097 data: 0.0058 max mem: 33369 +Epoch: [10] [ 370/1319] eta: 0:41:42 lr: 3.826865382157014e-05 loss: 0.0789 (0.0865) time: 2.5874 data: 0.0059 max mem: 33369 +Epoch: [10] [ 380/1319] eta: 0:41:15 lr: 3.8259867314822454e-05 loss: 0.0886 (0.0863) time: 2.6062 data: 0.0059 max mem: 33369 +Epoch: [10] [ 390/1319] eta: 0:40:49 lr: 3.825108058386341e-05 loss: 0.0858 (0.0866) time: 2.6341 data: 0.0059 max mem: 33369 +Epoch: [10] [ 400/1319] eta: 0:40:22 lr: 3.824229362863006e-05 loss: 0.0796 (0.0866) time: 2.6208 data: 0.0059 max mem: 33369 +Epoch: [10] [ 410/1319] eta: 0:39:55 lr: 3.823350644905941e-05 loss: 0.0787 (0.0865) time: 2.6016 data: 0.0059 max mem: 33369 +Epoch: [10] [ 420/1319] eta: 0:39:28 lr: 3.822471904508845e-05 loss: 0.0811 (0.0868) time: 2.5983 data: 0.0060 max mem: 33369 +Epoch: [10] [ 430/1319] eta: 0:39:01 lr: 3.821593141665413e-05 loss: 0.0765 (0.0867) time: 2.6077 data: 0.0059 max mem: 33369 +Epoch: [10] [ 440/1319] eta: 0:38:35 lr: 3.8207143563693345e-05 loss: 0.0763 (0.0863) time: 2.6340 data: 0.0059 max mem: 33369 +Epoch: [10] [ 450/1319] eta: 0:38:09 lr: 3.819835548614299e-05 loss: 0.0884 (0.0871) time: 2.6370 data: 0.0059 max mem: 33369 +Epoch: [10] [ 460/1319] eta: 0:37:41 lr: 3.8189567183939914e-05 loss: 0.1006 (0.0871) time: 2.6127 data: 0.0059 max mem: 33369 +Epoch: [10] [ 470/1319] eta: 0:37:14 lr: 3.8180778657020925e-05 loss: 0.0794 (0.0870) time: 2.5709 data: 0.0060 max mem: 33369 +Epoch: [10] [ 480/1319] eta: 0:36:47 lr: 3.81719899053228e-05 loss: 0.0687 (0.0867) time: 2.5884 data: 0.0060 max mem: 33369 +Epoch: [10] [ 490/1319] eta: 0:36:21 lr: 3.8163200928782287e-05 loss: 0.0748 (0.0867) time: 2.6263 data: 0.0060 max mem: 33369 +Epoch: [10] [ 500/1319] eta: 0:35:54 lr: 3.8154411727336084e-05 loss: 0.0822 (0.0869) time: 2.6271 data: 0.0060 max mem: 33369 +Epoch: [10] [ 510/1319] eta: 0:35:28 lr: 3.814562230092089e-05 loss: 0.0915 (0.0871) time: 2.6386 data: 0.0060 max mem: 33369 +Epoch: [10] [ 520/1319] eta: 0:35:02 lr: 3.8136832649473325e-05 loss: 0.0898 (0.0872) time: 2.6320 data: 0.0060 max mem: 33369 +Epoch: [10] [ 530/1319] eta: 0:34:35 lr: 3.812804277293001e-05 loss: 0.0743 (0.0871) time: 2.6189 data: 0.0059 max mem: 33369 +Epoch: [10] [ 540/1319] eta: 0:34:09 lr: 3.811925267122751e-05 loss: 0.0802 (0.0872) time: 2.6201 data: 0.0059 max mem: 33369 +Epoch: [10] [ 550/1319] eta: 0:33:43 lr: 3.8110462344302376e-05 loss: 0.0771 (0.0869) time: 2.6276 data: 0.0059 max mem: 33369 +Epoch: [10] [ 560/1319] eta: 0:33:16 lr: 3.8101671792091106e-05 loss: 0.0847 (0.0871) time: 2.6215 data: 0.0059 max mem: 33369 +Epoch: [10] [ 570/1319] eta: 0:32:50 lr: 3.809288101453017e-05 loss: 0.0895 (0.0873) time: 2.6210 data: 0.0057 max mem: 33369 +Epoch: [10] [ 580/1319] eta: 0:32:23 lr: 3.808409001155601e-05 loss: 0.0881 (0.0874) time: 2.6240 data: 0.0060 max mem: 33369 +Epoch: [10] [ 590/1319] eta: 0:31:57 lr: 3.807529878310503e-05 loss: 0.0813 (0.0873) time: 2.6305 data: 0.0061 max mem: 33369 +Epoch: [10] [ 600/1319] eta: 0:31:31 lr: 3.806650732911359e-05 loss: 0.0813 (0.0875) time: 2.6511 data: 0.0059 max mem: 33369 +Epoch: [10] [ 610/1319] eta: 0:31:05 lr: 3.8057715649518045e-05 loss: 0.0708 (0.0874) time: 2.6495 data: 0.0058 max mem: 33369 +Epoch: [10] [ 620/1319] eta: 0:30:39 lr: 3.804892374425468e-05 loss: 0.0739 (0.0876) time: 2.6354 data: 0.0060 max mem: 33369 +Epoch: [10] [ 630/1319] eta: 0:30:12 lr: 3.804013161325975e-05 loss: 0.0874 (0.0874) time: 2.6352 data: 0.0061 max mem: 33369 +Epoch: [10] [ 640/1319] eta: 0:29:46 lr: 3.803133925646951e-05 loss: 0.0841 (0.0876) time: 2.6144 data: 0.0059 max mem: 33369 +Epoch: [10] [ 650/1319] eta: 0:29:20 lr: 3.802254667382014e-05 loss: 0.0844 (0.0879) time: 2.6287 data: 0.0058 max mem: 33369 +Epoch: [10] [ 660/1319] eta: 0:28:54 lr: 3.801375386524781e-05 loss: 0.0808 (0.0880) time: 2.6598 data: 0.0059 max mem: 33369 +Epoch: [10] [ 670/1319] eta: 0:28:27 lr: 3.800496083068865e-05 loss: 0.0749 (0.0879) time: 2.6376 data: 0.0058 max mem: 33369 +Epoch: [10] [ 680/1319] eta: 0:28:01 lr: 3.799616757007876e-05 loss: 0.0768 (0.0880) time: 2.6147 data: 0.0057 max mem: 33369 +Epoch: [10] [ 690/1319] eta: 0:27:34 lr: 3.798737408335417e-05 loss: 0.0817 (0.0880) time: 2.6114 data: 0.0059 max mem: 33369 +Epoch: [10] [ 700/1319] eta: 0:27:08 lr: 3.797858037045094e-05 loss: 0.0760 (0.0878) time: 2.6240 data: 0.0059 max mem: 33369 +Epoch: [10] [ 710/1319] eta: 0:26:42 lr: 3.796978643130504e-05 loss: 0.0748 (0.0878) time: 2.6288 data: 0.0057 max mem: 33369 +Epoch: [10] [ 720/1319] eta: 0:26:15 lr: 3.796099226585244e-05 loss: 0.0710 (0.0879) time: 2.6100 data: 0.0057 max mem: 33369 +Epoch: [10] [ 730/1319] eta: 0:25:48 lr: 3.795219787402904e-05 loss: 0.0707 (0.0878) time: 2.5950 data: 0.0058 max mem: 33369 +Epoch: [10] [ 740/1319] eta: 0:25:22 lr: 3.794340325577075e-05 loss: 0.0715 (0.0877) time: 2.6246 data: 0.0059 max mem: 33369 +Epoch: [10] [ 750/1319] eta: 0:24:56 lr: 3.79346084110134e-05 loss: 0.0811 (0.0877) time: 2.6234 data: 0.0059 max mem: 33369 +Epoch: [10] [ 760/1319] eta: 0:24:29 lr: 3.7925813339692824e-05 loss: 0.0811 (0.0880) time: 2.5860 data: 0.0059 max mem: 33369 +Epoch: [10] [ 770/1319] eta: 0:24:03 lr: 3.79170180417448e-05 loss: 0.0778 (0.0881) time: 2.5879 data: 0.0060 max mem: 33369 +Epoch: [10] [ 780/1319] eta: 0:23:36 lr: 3.790822251710506e-05 loss: 0.0780 (0.0880) time: 2.6165 data: 0.0060 max mem: 33369 +Epoch: [10] [ 790/1319] eta: 0:23:10 lr: 3.789942676570934e-05 loss: 0.0708 (0.0878) time: 2.5923 data: 0.0059 max mem: 33369 +Epoch: [10] [ 800/1319] eta: 0:22:44 lr: 3.7890630787493295e-05 loss: 0.0695 (0.0879) time: 2.6125 data: 0.0058 max mem: 33369 +Epoch: [10] [ 810/1319] eta: 0:22:17 lr: 3.788183458239259e-05 loss: 0.0788 (0.0879) time: 2.6628 data: 0.0057 max mem: 33369 +Epoch: [10] [ 820/1319] eta: 0:21:51 lr: 3.7873038150342824e-05 loss: 0.0710 (0.0880) time: 2.6374 data: 0.0058 max mem: 33369 +Epoch: [10] [ 830/1319] eta: 0:21:25 lr: 3.7864241491279565e-05 loss: 0.0794 (0.0879) time: 2.6077 data: 0.0059 max mem: 33369 +Epoch: [10] [ 840/1319] eta: 0:20:58 lr: 3.785544460513836e-05 loss: 0.0759 (0.0877) time: 2.6206 data: 0.0059 max mem: 33369 +Epoch: [10] [ 850/1319] eta: 0:20:32 lr: 3.784664749185471e-05 loss: 0.0711 (0.0879) time: 2.6319 data: 0.0060 max mem: 33369 +Epoch: [10] [ 860/1319] eta: 0:20:06 lr: 3.7837850151364085e-05 loss: 0.0807 (0.0878) time: 2.6102 data: 0.0061 max mem: 33369 +Epoch: [10] [ 870/1319] eta: 0:19:39 lr: 3.78290525836019e-05 loss: 0.0764 (0.0878) time: 2.6096 data: 0.0060 max mem: 33369 +Epoch: [10] [ 880/1319] eta: 0:19:13 lr: 3.782025478850358e-05 loss: 0.0728 (0.0877) time: 2.6009 data: 0.0059 max mem: 33369 +Epoch: [10] [ 890/1319] eta: 0:18:46 lr: 3.7811456766004476e-05 loss: 0.0847 (0.0878) time: 2.5929 data: 0.0058 max mem: 33369 +Epoch: [10] [ 900/1319] eta: 0:18:20 lr: 3.780265851603992e-05 loss: 0.0847 (0.0878) time: 2.6014 data: 0.0058 max mem: 33369 +Epoch: [10] [ 910/1319] eta: 0:17:54 lr: 3.779386003854519e-05 loss: 0.0917 (0.0880) time: 2.6178 data: 0.0058 max mem: 33369 +Epoch: [10] [ 920/1319] eta: 0:17:28 lr: 3.7785061333455565e-05 loss: 0.0980 (0.0881) time: 2.6406 data: 0.0057 max mem: 33369 +Epoch: [10] [ 930/1319] eta: 0:17:01 lr: 3.7776262400706265e-05 loss: 0.0808 (0.0880) time: 2.6289 data: 0.0057 max mem: 33369 +Epoch: [10] [ 940/1319] eta: 0:16:35 lr: 3.776746324023246e-05 loss: 0.0755 (0.0880) time: 2.6089 data: 0.0057 max mem: 33369 +Epoch: [10] [ 950/1319] eta: 0:16:09 lr: 3.775866385196932e-05 loss: 0.0787 (0.0879) time: 2.6153 data: 0.0058 max mem: 33369 +Epoch: [10] [ 960/1319] eta: 0:15:42 lr: 3.774986423585195e-05 loss: 0.0810 (0.0879) time: 2.6119 data: 0.0059 max mem: 33369 +Epoch: [10] [ 970/1319] eta: 0:15:16 lr: 3.7741064391815444e-05 loss: 0.0754 (0.0878) time: 2.6039 data: 0.0058 max mem: 33369 +Epoch: [10] [ 980/1319] eta: 0:14:50 lr: 3.7732264319794836e-05 loss: 0.0679 (0.0878) time: 2.6051 data: 0.0058 max mem: 33369 +Epoch: [10] [ 990/1319] eta: 0:14:23 lr: 3.772346401972514e-05 loss: 0.0767 (0.0877) time: 2.5863 data: 0.0059 max mem: 33369 +Epoch: [10] [1000/1319] eta: 0:13:57 lr: 3.771466349154134e-05 loss: 0.0765 (0.0876) time: 2.5780 data: 0.0059 max mem: 33369 +Epoch: [10] [1010/1319] eta: 0:13:31 lr: 3.7705862735178374e-05 loss: 0.0736 (0.0876) time: 2.6007 data: 0.0059 max mem: 33369 +Epoch: [10] [1020/1319] eta: 0:13:04 lr: 3.7697061750571136e-05 loss: 0.0762 (0.0877) time: 2.6148 data: 0.0059 max mem: 33369 +Epoch: [10] [1030/1319] eta: 0:12:38 lr: 3.768826053765451e-05 loss: 0.0855 (0.0878) time: 2.6348 data: 0.0058 max mem: 33369 +Epoch: [10] [1040/1319] eta: 0:12:12 lr: 3.767945909636332e-05 loss: 0.0936 (0.0881) time: 2.6196 data: 0.0058 max mem: 33369 +Epoch: [10] [1050/1319] eta: 0:11:46 lr: 3.767065742663237e-05 loss: 0.0842 (0.0880) time: 2.6208 data: 0.0059 max mem: 33369 +Epoch: [10] [1060/1319] eta: 0:11:19 lr: 3.7661855528396415e-05 loss: 0.0807 (0.0880) time: 2.6434 data: 0.0057 max mem: 33369 +Epoch: [10] [1070/1319] eta: 0:10:53 lr: 3.765305340159019e-05 loss: 0.0807 (0.0882) time: 2.6130 data: 0.0057 max mem: 33369 +Epoch: [10] [1080/1319] eta: 0:10:27 lr: 3.764425104614838e-05 loss: 0.0841 (0.0883) time: 2.6131 data: 0.0058 max mem: 33369 +Epoch: [10] [1090/1319] eta: 0:10:01 lr: 3.763544846200565e-05 loss: 0.0850 (0.0884) time: 2.6391 data: 0.0057 max mem: 33369 +Epoch: [10] [1100/1319] eta: 0:09:34 lr: 3.7626645649096614e-05 loss: 0.0834 (0.0883) time: 2.6341 data: 0.0058 max mem: 33369 +Epoch: [10] [1110/1319] eta: 0:09:08 lr: 3.761784260735586e-05 loss: 0.0692 (0.0883) time: 2.6045 data: 0.0058 max mem: 33369 +Epoch: [10] [1120/1319] eta: 0:08:42 lr: 3.760903933671793e-05 loss: 0.0704 (0.0882) time: 2.5838 data: 0.0057 max mem: 33369 +Epoch: [10] [1130/1319] eta: 0:08:15 lr: 3.760023583711735e-05 loss: 0.0746 (0.0883) time: 2.6024 data: 0.0059 max mem: 33369 +Epoch: [10] [1140/1319] eta: 0:07:49 lr: 3.7591432108488584e-05 loss: 0.0746 (0.0882) time: 2.6248 data: 0.0060 max mem: 33369 +Epoch: [10] [1150/1319] eta: 0:07:23 lr: 3.758262815076608e-05 loss: 0.0775 (0.0882) time: 2.6221 data: 0.0059 max mem: 33369 +Epoch: [10] [1160/1319] eta: 0:06:57 lr: 3.7573823963884245e-05 loss: 0.0692 (0.0881) time: 2.6106 data: 0.0061 max mem: 33369 +Epoch: [10] [1170/1319] eta: 0:06:30 lr: 3.756501954777745e-05 loss: 0.0796 (0.0883) time: 2.6134 data: 0.0060 max mem: 33369 +Epoch: [10] [1180/1319] eta: 0:06:04 lr: 3.755621490238003e-05 loss: 0.0835 (0.0883) time: 2.6217 data: 0.0059 max mem: 33369 +Epoch: [10] [1190/1319] eta: 0:05:38 lr: 3.754741002762627e-05 loss: 0.0835 (0.0883) time: 2.6099 data: 0.0058 max mem: 33369 +Epoch: [10] [1200/1319] eta: 0:05:12 lr: 3.753860492345044e-05 loss: 0.0796 (0.0883) time: 2.6200 data: 0.0057 max mem: 33369 +Epoch: [10] [1210/1319] eta: 0:04:45 lr: 3.7529799589786776e-05 loss: 0.0751 (0.0882) time: 2.6058 data: 0.0057 max mem: 33369 +Epoch: [10] [1220/1319] eta: 0:04:19 lr: 3.752099402656945e-05 loss: 0.0803 (0.0882) time: 2.5895 data: 0.0059 max mem: 33369 +Epoch: [10] [1230/1319] eta: 0:03:53 lr: 3.751218823373263e-05 loss: 0.0908 (0.0883) time: 2.6049 data: 0.0060 max mem: 33369 +Epoch: [10] [1240/1319] eta: 0:03:27 lr: 3.750338221121043e-05 loss: 0.0831 (0.0883) time: 2.6074 data: 0.0059 max mem: 33369 +Epoch: [10] [1250/1319] eta: 0:03:00 lr: 3.749457595893693e-05 loss: 0.0781 (0.0883) time: 2.6011 data: 0.0061 max mem: 33369 +Epoch: [10] [1260/1319] eta: 0:02:34 lr: 3.748576947684619e-05 loss: 0.0733 (0.0884) time: 2.5987 data: 0.0061 max mem: 33369 +Epoch: [10] [1270/1319] eta: 0:02:08 lr: 3.74769627648722e-05 loss: 0.0752 (0.0883) time: 2.5953 data: 0.0057 max mem: 33369 +Epoch: [10] [1280/1319] eta: 0:01:42 lr: 3.746815582294894e-05 loss: 0.0806 (0.0883) time: 2.5888 data: 0.0056 max mem: 33369 +Epoch: [10] [1290/1319] eta: 0:01:16 lr: 3.745934865101035e-05 loss: 0.0806 (0.0883) time: 2.6067 data: 0.0057 max mem: 33369 +Epoch: [10] [1300/1319] eta: 0:00:49 lr: 3.7450541248990324e-05 loss: 0.0842 (0.0883) time: 2.6307 data: 0.0057 max mem: 33369 +Epoch: [10] [1310/1319] eta: 0:00:23 lr: 3.7441733616822736e-05 loss: 0.0876 (0.0884) time: 2.6268 data: 0.0057 max mem: 33369 +Epoch: [10] Total time: 0:57:38 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 3:09:13 time: 4.4126 data: 4.3336 max mem: 33369 +Test: [ 100/2573] eta: 0:04:44 time: 0.0714 data: 0.0011 max mem: 33369 +Test: [ 200/2573] eta: 0:03:44 time: 0.0730 data: 0.0011 max mem: 33369 +Test: [ 300/2573] eta: 0:03:17 time: 0.0748 data: 0.0011 max mem: 33369 +Test: [ 400/2573] eta: 0:03:01 time: 0.0749 data: 0.0011 max mem: 33369 +Test: [ 500/2573] eta: 0:02:48 time: 0.0735 data: 0.0012 max mem: 33369 +Test: [ 600/2573] eta: 0:02:38 time: 0.0736 data: 0.0012 max mem: 33369 +Test: [ 700/2573] eta: 0:02:28 time: 0.0736 data: 0.0012 max mem: 33369 +Test: [ 800/2573] eta: 0:02:19 time: 0.0769 data: 0.0011 max mem: 33369 +Test: [ 900/2573] eta: 0:02:11 time: 0.0736 data: 0.0012 max mem: 33369 +Test: [1000/2573] eta: 0:02:02 time: 0.0737 data: 0.0012 max mem: 33369 +Test: [1100/2573] eta: 0:01:54 time: 0.0737 data: 0.0012 max mem: 33369 +Test: [1200/2573] eta: 0:01:46 time: 0.0737 data: 0.0011 max mem: 33369 +Test: [1300/2573] eta: 0:01:38 time: 0.0737 data: 0.0011 max mem: 33369 +Test: [1400/2573] eta: 0:01:30 time: 0.0720 data: 0.0011 max mem: 33369 +Test: [1500/2573] eta: 0:01:22 time: 0.0738 data: 0.0012 max mem: 33369 +Test: [1600/2573] eta: 0:01:14 time: 0.0770 data: 0.0012 max mem: 33369 +Test: [1700/2573] eta: 0:01:06 time: 0.0721 data: 0.0011 max mem: 33369 +Test: [1800/2573] eta: 0:00:58 time: 0.0754 data: 0.0011 max mem: 33369 +Test: [1900/2573] eta: 0:00:51 time: 0.0721 data: 0.0011 max mem: 33369 +Test: [2000/2573] eta: 0:00:43 time: 0.0738 data: 0.0012 max mem: 33369 +Test: [2100/2573] eta: 0:00:35 time: 0.0754 data: 0.0011 max mem: 33369 +Test: [2200/2573] eta: 0:00:28 time: 0.0755 data: 0.0011 max mem: 33369 +Test: [2300/2573] eta: 0:00:20 time: 0.0754 data: 0.0011 max mem: 33369 +Test: [2400/2573] eta: 0:00:13 time: 0.0704 data: 0.0011 max mem: 33369 +Test: [2500/2573] eta: 0:00:05 time: 0.0737 data: 0.0011 max mem: 33369 +Test: Total time: 0:03:14 +Final results: +Mean IoU is 59.68 + + precision@0.5 = 66.83 + precision@0.6 = 61.13 + precision@0.7 = 53.27 + precision@0.8 = 40.79 + precision@0.9 = 18.65 + overall IoU = 58.78 + +Average object IoU 59.6826291389461 +Overall IoU 58.77544021606445 +Better epoch: 10 + +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [11] [ 0/1319] eta: 1:34:22 lr: 3.743380655104104e-05 loss: 0.0360 (0.0360) time: 4.2927 data: 1.4749 max mem: 33369 +Epoch: [11] [ 10/1319] eta: 1:01:19 lr: 3.742499848141075e-05 loss: 0.0683 (0.0760) time: 2.8108 data: 0.1393 max mem: 33369 +Epoch: [11] [ 20/1319] eta: 0:58:54 lr: 3.741619018144089e-05 loss: 0.0683 (0.0745) time: 2.6422 data: 0.0059 max mem: 33369 +Epoch: [11] [ 30/1319] eta: 0:57:38 lr: 3.7407381651065185e-05 loss: 0.0731 (0.0790) time: 2.6128 data: 0.0061 max mem: 33369 +Epoch: [11] [ 40/1319] eta: 0:56:41 lr: 3.739857289021734e-05 loss: 0.0759 (0.0779) time: 2.5948 data: 0.0064 max mem: 33369 +Epoch: [11] [ 50/1319] eta: 0:56:09 lr: 3.738976389883098e-05 loss: 0.0628 (0.0831) time: 2.6120 data: 0.0063 max mem: 33369 +Epoch: [11] [ 60/1319] eta: 0:55:40 lr: 3.738095467683973e-05 loss: 0.0634 (0.0829) time: 2.6407 data: 0.0060 max mem: 33369 +Epoch: [11] [ 70/1319] eta: 0:55:12 lr: 3.737214522417717e-05 loss: 0.0650 (0.0820) time: 2.6446 data: 0.0060 max mem: 33369 +Epoch: [11] [ 80/1319] eta: 0:54:39 lr: 3.736333554077684e-05 loss: 0.0768 (0.0835) time: 2.6281 data: 0.0063 max mem: 33369 +Epoch: [11] [ 90/1319] eta: 0:54:10 lr: 3.735452562657224e-05 loss: 0.0853 (0.0841) time: 2.6184 data: 0.0063 max mem: 33369 +Epoch: [11] [ 100/1319] eta: 0:53:37 lr: 3.734571548149683e-05 loss: 0.0853 (0.0846) time: 2.6090 data: 0.0060 max mem: 33369 +Epoch: [11] [ 110/1319] eta: 0:53:06 lr: 3.733690510548406e-05 loss: 0.0790 (0.0845) time: 2.5945 data: 0.0061 max mem: 33369 +Epoch: [11] [ 120/1319] eta: 0:52:41 lr: 3.732809449846732e-05 loss: 0.0762 (0.0851) time: 2.6236 data: 0.0061 max mem: 33369 +Epoch: [11] [ 130/1319] eta: 0:52:11 lr: 3.7319283660379954e-05 loss: 0.0631 (0.0835) time: 2.6206 data: 0.0062 max mem: 33369 +Epoch: [11] [ 140/1319] eta: 0:51:42 lr: 3.7310472591155297e-05 loss: 0.0579 (0.0834) time: 2.5976 data: 0.0063 max mem: 33369 +Epoch: [11] [ 150/1319] eta: 0:51:13 lr: 3.7301661290726626e-05 loss: 0.0685 (0.0831) time: 2.6034 data: 0.0063 max mem: 33369 +Epoch: [11] [ 160/1319] eta: 0:50:45 lr: 3.729284975902719e-05 loss: 0.0773 (0.0835) time: 2.6054 data: 0.0060 max mem: 33369 +Epoch: [11] [ 170/1319] eta: 0:50:20 lr: 3.728403799599019e-05 loss: 0.0726 (0.0834) time: 2.6247 data: 0.0059 max mem: 33369 +Epoch: [11] [ 180/1319] eta: 0:49:52 lr: 3.727522600154881e-05 loss: 0.0713 (0.0831) time: 2.6218 data: 0.0061 max mem: 33369 +Epoch: [11] [ 190/1319] eta: 0:49:29 lr: 3.7266413775636196e-05 loss: 0.0803 (0.0838) time: 2.6391 data: 0.0062 max mem: 33369 +Epoch: [11] [ 200/1319] eta: 0:49:01 lr: 3.725760131818543e-05 loss: 0.0849 (0.0835) time: 2.6381 data: 0.0062 max mem: 33369 +Epoch: [11] [ 210/1319] eta: 0:48:32 lr: 3.724878862912958e-05 loss: 0.0659 (0.0833) time: 2.5932 data: 0.0063 max mem: 33369 +Epoch: [11] [ 220/1319] eta: 0:48:01 lr: 3.723997570840168e-05 loss: 0.0654 (0.0826) time: 2.5605 data: 0.0063 max mem: 33369 +Epoch: [11] [ 230/1319] eta: 0:47:34 lr: 3.723116255593471e-05 loss: 0.0738 (0.0826) time: 2.5696 data: 0.0063 max mem: 33369 +Epoch: [11] [ 240/1319] eta: 0:47:10 lr: 3.7222349171661633e-05 loss: 0.0889 (0.0833) time: 2.6298 data: 0.0061 max mem: 33369 +Epoch: [11] [ 250/1319] eta: 0:46:42 lr: 3.721353555551535e-05 loss: 0.0864 (0.0830) time: 2.6183 data: 0.0061 max mem: 33369 +Epoch: [11] [ 260/1319] eta: 0:46:14 lr: 3.720472170742875e-05 loss: 0.0713 (0.0829) time: 2.5889 data: 0.0061 max mem: 33369 +Epoch: [11] [ 270/1319] eta: 0:45:47 lr: 3.719590762733466e-05 loss: 0.0793 (0.0833) time: 2.5959 data: 0.0060 max mem: 33369 +Epoch: [11] [ 280/1319] eta: 0:45:21 lr: 3.718709331516589e-05 loss: 0.0826 (0.0831) time: 2.6029 data: 0.0060 max mem: 33369 +Epoch: [11] [ 290/1319] eta: 0:44:53 lr: 3.7178278770855225e-05 loss: 0.0826 (0.0831) time: 2.5979 data: 0.0060 max mem: 33369 +Epoch: [11] [ 300/1319] eta: 0:44:28 lr: 3.716946399433537e-05 loss: 0.0772 (0.0833) time: 2.6114 data: 0.0060 max mem: 33369 +Epoch: [11] [ 310/1319] eta: 0:44:02 lr: 3.716064898553902e-05 loss: 0.0772 (0.0832) time: 2.6302 data: 0.0059 max mem: 33369 +Epoch: [11] [ 320/1319] eta: 0:43:35 lr: 3.715183374439884e-05 loss: 0.0745 (0.0831) time: 2.6125 data: 0.0061 max mem: 33369 +Epoch: [11] [ 330/1319] eta: 0:43:09 lr: 3.7143018270847454e-05 loss: 0.0745 (0.0830) time: 2.6081 data: 0.0063 max mem: 33369 +Epoch: [11] [ 340/1319] eta: 0:42:43 lr: 3.713420256481742e-05 loss: 0.0656 (0.0827) time: 2.6231 data: 0.0062 max mem: 33369 +Epoch: [11] [ 350/1319] eta: 0:42:16 lr: 3.712538662624129e-05 loss: 0.0628 (0.0824) time: 2.6108 data: 0.0059 max mem: 33369 +Epoch: [11] [ 360/1319] eta: 0:41:50 lr: 3.7116570455051586e-05 loss: 0.0698 (0.0826) time: 2.6110 data: 0.0058 max mem: 33369 +Epoch: [11] [ 370/1319] eta: 0:41:23 lr: 3.710775405118075e-05 loss: 0.0774 (0.0824) time: 2.6114 data: 0.0059 max mem: 33369 +Epoch: [11] [ 380/1319] eta: 0:40:57 lr: 3.709893741456123e-05 loss: 0.0858 (0.0826) time: 2.5954 data: 0.0057 max mem: 33369 +Epoch: [11] [ 390/1319] eta: 0:40:30 lr: 3.709012054512541e-05 loss: 0.0858 (0.0829) time: 2.6063 data: 0.0058 max mem: 33369 +Epoch: [11] [ 400/1319] eta: 0:40:05 lr: 3.7081303442805645e-05 loss: 0.0823 (0.0840) time: 2.6232 data: 0.0061 max mem: 33369 +Epoch: [11] [ 410/1319] eta: 0:39:38 lr: 3.7072486107534264e-05 loss: 0.0847 (0.0841) time: 2.6114 data: 0.0061 max mem: 33369 +Epoch: [11] [ 420/1319] eta: 0:39:12 lr: 3.706366853924354e-05 loss: 0.0778 (0.0839) time: 2.6097 data: 0.0060 max mem: 33369 +Epoch: [11] [ 430/1319] eta: 0:38:46 lr: 3.705485073786572e-05 loss: 0.0734 (0.0840) time: 2.6235 data: 0.0060 max mem: 33369 +Epoch: [11] [ 440/1319] eta: 0:38:21 lr: 3.704603270333301e-05 loss: 0.0724 (0.0837) time: 2.6535 data: 0.0061 max mem: 33369 +Epoch: [11] [ 450/1319] eta: 0:37:54 lr: 3.703721443557757e-05 loss: 0.0724 (0.0840) time: 2.6383 data: 0.0061 max mem: 33369 +Epoch: [11] [ 460/1319] eta: 0:37:27 lr: 3.702839593453153e-05 loss: 0.0788 (0.0839) time: 2.5758 data: 0.0059 max mem: 33369 +Epoch: [11] [ 470/1319] eta: 0:37:00 lr: 3.7019577200126995e-05 loss: 0.0742 (0.0838) time: 2.5734 data: 0.0059 max mem: 33369 +Epoch: [11] [ 480/1319] eta: 0:36:34 lr: 3.701075823229601e-05 loss: 0.0738 (0.0840) time: 2.5984 data: 0.0059 max mem: 33369 +Epoch: [11] [ 490/1319] eta: 0:36:08 lr: 3.700193903097059e-05 loss: 0.0643 (0.0840) time: 2.6251 data: 0.0058 max mem: 33369 +Epoch: [11] [ 500/1319] eta: 0:35:42 lr: 3.6993119596082715e-05 loss: 0.0636 (0.0838) time: 2.6222 data: 0.0058 max mem: 33369 +Epoch: [11] [ 510/1319] eta: 0:35:16 lr: 3.698429992756433e-05 loss: 0.0705 (0.0836) time: 2.6066 data: 0.0057 max mem: 33369 +Epoch: [11] [ 520/1319] eta: 0:34:49 lr: 3.6975480025347336e-05 loss: 0.0758 (0.0835) time: 2.6045 data: 0.0058 max mem: 33369 +Epoch: [11] [ 530/1319] eta: 0:34:24 lr: 3.69666598893636e-05 loss: 0.0747 (0.0833) time: 2.6312 data: 0.0058 max mem: 33369 +Epoch: [11] [ 540/1319] eta: 0:33:58 lr: 3.695783951954495e-05 loss: 0.0802 (0.0836) time: 2.6322 data: 0.0057 max mem: 33369 +Epoch: [11] [ 550/1319] eta: 0:33:31 lr: 3.694901891582318e-05 loss: 0.0868 (0.0837) time: 2.5989 data: 0.0058 max mem: 33369 +Epoch: [11] [ 560/1319] eta: 0:33:05 lr: 3.694019807813003e-05 loss: 0.0790 (0.0835) time: 2.5997 data: 0.0060 max mem: 33369 +Epoch: [11] [ 570/1319] eta: 0:32:39 lr: 3.6931377006397214e-05 loss: 0.0674 (0.0834) time: 2.6294 data: 0.0060 max mem: 33369 +Epoch: [11] [ 580/1319] eta: 0:32:13 lr: 3.692255570055642e-05 loss: 0.0720 (0.0834) time: 2.6360 data: 0.0060 max mem: 33369 +Epoch: [11] [ 590/1319] eta: 0:31:47 lr: 3.691373416053928e-05 loss: 0.0720 (0.0835) time: 2.6250 data: 0.0060 max mem: 33369 +Epoch: [11] [ 600/1319] eta: 0:31:20 lr: 3.690491238627739e-05 loss: 0.0751 (0.0834) time: 2.6038 data: 0.0058 max mem: 33369 +Epoch: [11] [ 610/1319] eta: 0:30:54 lr: 3.6896090377702305e-05 loss: 0.0774 (0.0836) time: 2.5905 data: 0.0056 max mem: 33369 +Epoch: [11] [ 620/1319] eta: 0:30:28 lr: 3.688726813474555e-05 loss: 0.0750 (0.0834) time: 2.6126 data: 0.0058 max mem: 33369 +Epoch: [11] [ 630/1319] eta: 0:30:02 lr: 3.687844565733862e-05 loss: 0.0730 (0.0836) time: 2.6290 data: 0.0060 max mem: 33369 +Epoch: [11] [ 640/1319] eta: 0:29:36 lr: 3.686962294541296e-05 loss: 0.0810 (0.0835) time: 2.6134 data: 0.0058 max mem: 33369 +Epoch: [11] [ 650/1319] eta: 0:29:10 lr: 3.686079999889997e-05 loss: 0.0801 (0.0839) time: 2.6271 data: 0.0057 max mem: 33369 +Epoch: [11] [ 660/1319] eta: 0:28:44 lr: 3.6851976817731035e-05 loss: 0.0799 (0.0841) time: 2.6358 data: 0.0058 max mem: 33369 +Epoch: [11] [ 670/1319] eta: 0:28:17 lr: 3.684315340183746e-05 loss: 0.0780 (0.0841) time: 2.6003 data: 0.0059 max mem: 33369 +Epoch: [11] [ 680/1319] eta: 0:27:51 lr: 3.683432975115057e-05 loss: 0.0628 (0.0838) time: 2.6005 data: 0.0058 max mem: 33369 +Epoch: [11] [ 690/1319] eta: 0:27:25 lr: 3.682550586560159e-05 loss: 0.0699 (0.0839) time: 2.6006 data: 0.0058 max mem: 33369 +Epoch: [11] [ 700/1319] eta: 0:26:59 lr: 3.6816681745121755e-05 loss: 0.0754 (0.0843) time: 2.6104 data: 0.0059 max mem: 33369 +Epoch: [11] [ 710/1319] eta: 0:26:33 lr: 3.680785738964223e-05 loss: 0.0693 (0.0840) time: 2.6293 data: 0.0057 max mem: 33369 +Epoch: [11] [ 720/1319] eta: 0:26:06 lr: 3.679903279909417e-05 loss: 0.0692 (0.0840) time: 2.6236 data: 0.0059 max mem: 33369 +Epoch: [11] [ 730/1319] eta: 0:25:41 lr: 3.679020797340866e-05 loss: 0.0765 (0.0840) time: 2.6378 data: 0.0059 max mem: 33369 +Epoch: [11] [ 740/1319] eta: 0:25:15 lr: 3.678138291251678e-05 loss: 0.0813 (0.0839) time: 2.6511 data: 0.0058 max mem: 33369 +Epoch: [11] [ 750/1319] eta: 0:24:49 lr: 3.677255761634953e-05 loss: 0.0640 (0.0838) time: 2.6342 data: 0.0058 max mem: 33369 +Epoch: [11] [ 760/1319] eta: 0:24:23 lr: 3.6763732084837915e-05 loss: 0.0675 (0.0837) time: 2.6312 data: 0.0058 max mem: 33369 +Epoch: [11] [ 770/1319] eta: 0:23:56 lr: 3.675490631791288e-05 loss: 0.0797 (0.0838) time: 2.6219 data: 0.0059 max mem: 33369 +Epoch: [11] [ 780/1319] eta: 0:23:30 lr: 3.6746080315505315e-05 loss: 0.0776 (0.0836) time: 2.6156 data: 0.0059 max mem: 33369 +Epoch: [11] [ 790/1319] eta: 0:23:04 lr: 3.6737254077546116e-05 loss: 0.0766 (0.0838) time: 2.6210 data: 0.0058 max mem: 33369 +Epoch: [11] [ 800/1319] eta: 0:22:38 lr: 3.672842760396608e-05 loss: 0.0701 (0.0836) time: 2.6163 data: 0.0058 max mem: 33369 +Epoch: [11] [ 810/1319] eta: 0:22:12 lr: 3.6719600894696026e-05 loss: 0.0598 (0.0835) time: 2.6289 data: 0.0058 max mem: 33369 +Epoch: [11] [ 820/1319] eta: 0:21:46 lr: 3.6710773949666697e-05 loss: 0.0779 (0.0837) time: 2.6270 data: 0.0057 max mem: 33369 +Epoch: [11] [ 830/1319] eta: 0:21:20 lr: 3.6701946768808805e-05 loss: 0.0931 (0.0840) time: 2.6218 data: 0.0056 max mem: 33369 +Epoch: [11] [ 840/1319] eta: 0:20:53 lr: 3.6693119352053024e-05 loss: 0.0743 (0.0838) time: 2.6311 data: 0.0056 max mem: 33369 +Epoch: [11] [ 850/1319] eta: 0:20:27 lr: 3.668429169932999e-05 loss: 0.0743 (0.0839) time: 2.6332 data: 0.0058 max mem: 33369 +Epoch: [11] [ 860/1319] eta: 0:20:01 lr: 3.667546381057031e-05 loss: 0.0714 (0.0838) time: 2.6313 data: 0.0057 max mem: 33369 +Epoch: [11] [ 870/1319] eta: 0:19:35 lr: 3.666663568570454e-05 loss: 0.0711 (0.0839) time: 2.6140 data: 0.0056 max mem: 33369 +Epoch: [11] [ 880/1319] eta: 0:19:09 lr: 3.665780732466318e-05 loss: 0.0798 (0.0839) time: 2.6251 data: 0.0058 max mem: 33369 +Epoch: [11] [ 890/1319] eta: 0:18:43 lr: 3.6648978727376724e-05 loss: 0.0786 (0.0838) time: 2.6289 data: 0.0059 max mem: 33369 +Epoch: [11] [ 900/1319] eta: 0:18:17 lr: 3.664014989377562e-05 loss: 0.0631 (0.0837) time: 2.6338 data: 0.0058 max mem: 33369 +Epoch: [11] [ 910/1319] eta: 0:17:50 lr: 3.663132082379026e-05 loss: 0.0631 (0.0836) time: 2.6331 data: 0.0056 max mem: 33369 +Epoch: [11] [ 920/1319] eta: 0:17:24 lr: 3.6622491517351006e-05 loss: 0.0763 (0.0838) time: 2.5922 data: 0.0056 max mem: 33369 +Epoch: [11] [ 930/1319] eta: 0:16:58 lr: 3.661366197438818e-05 loss: 0.0742 (0.0838) time: 2.6186 data: 0.0057 max mem: 33369 +Epoch: [11] [ 940/1319] eta: 0:16:32 lr: 3.660483219483207e-05 loss: 0.0807 (0.0838) time: 2.6481 data: 0.0059 max mem: 33369 +Epoch: [11] [ 950/1319] eta: 0:16:06 lr: 3.659600217861292e-05 loss: 0.0763 (0.0837) time: 2.6201 data: 0.0058 max mem: 33369 +Epoch: [11] [ 960/1319] eta: 0:15:40 lr: 3.658717192566094e-05 loss: 0.0645 (0.0836) time: 2.6205 data: 0.0056 max mem: 33369 +Epoch: [11] [ 970/1319] eta: 0:15:13 lr: 3.6578341435906296e-05 loss: 0.0685 (0.0836) time: 2.6173 data: 0.0057 max mem: 33369 +Epoch: [11] [ 980/1319] eta: 0:14:47 lr: 3.656951070927911e-05 loss: 0.0685 (0.0837) time: 2.6165 data: 0.0058 max mem: 33369 +Epoch: [11] [ 990/1319] eta: 0:14:21 lr: 3.656067974570946e-05 loss: 0.0808 (0.0836) time: 2.6148 data: 0.0059 max mem: 33369 +Epoch: [11] [1000/1319] eta: 0:13:55 lr: 3.655184854512743e-05 loss: 0.0733 (0.0836) time: 2.6111 data: 0.0059 max mem: 33369 +Epoch: [11] [1010/1319] eta: 0:13:29 lr: 3.654301710746299e-05 loss: 0.0733 (0.0837) time: 2.6308 data: 0.0060 max mem: 33369 +Epoch: [11] [1020/1319] eta: 0:13:02 lr: 3.653418543264612e-05 loss: 0.0787 (0.0836) time: 2.6162 data: 0.0059 max mem: 33369 +Epoch: [11] [1030/1319] eta: 0:12:36 lr: 3.652535352060675e-05 loss: 0.0773 (0.0838) time: 2.5787 data: 0.0058 max mem: 33369 +Epoch: [11] [1040/1319] eta: 0:12:10 lr: 3.651652137127478e-05 loss: 0.0707 (0.0838) time: 2.5867 data: 0.0060 max mem: 33369 +Epoch: [11] [1050/1319] eta: 0:11:44 lr: 3.6507688984580056e-05 loss: 0.0685 (0.0839) time: 2.6211 data: 0.0060 max mem: 33369 +Epoch: [11] [1060/1319] eta: 0:11:18 lr: 3.649885636045239e-05 loss: 0.0630 (0.0837) time: 2.6392 data: 0.0058 max mem: 33369 +Epoch: [11] [1070/1319] eta: 0:10:51 lr: 3.6490023498821546e-05 loss: 0.0658 (0.0837) time: 2.6411 data: 0.0057 max mem: 33369 +Epoch: [11] [1080/1319] eta: 0:10:25 lr: 3.648119039961727e-05 loss: 0.0823 (0.0836) time: 2.6270 data: 0.0058 max mem: 33369 +Epoch: [11] [1090/1319] eta: 0:09:59 lr: 3.647235706276924e-05 loss: 0.0823 (0.0837) time: 2.6228 data: 0.0059 max mem: 33369 +Epoch: [11] [1100/1319] eta: 0:09:33 lr: 3.646352348820711e-05 loss: 0.0727 (0.0836) time: 2.6162 data: 0.0058 max mem: 33369 +Epoch: [11] [1110/1319] eta: 0:09:07 lr: 3.6454689675860496e-05 loss: 0.0706 (0.0836) time: 2.6057 data: 0.0056 max mem: 33369 +Epoch: [11] [1120/1319] eta: 0:08:41 lr: 3.6445855625658975e-05 loss: 0.0931 (0.0838) time: 2.6105 data: 0.0058 max mem: 33369 +Epoch: [11] [1130/1319] eta: 0:08:14 lr: 3.643702133753208e-05 loss: 0.0898 (0.0837) time: 2.6214 data: 0.0059 max mem: 33369 +Epoch: [11] [1140/1319] eta: 0:07:48 lr: 3.6428186811409296e-05 loss: 0.0833 (0.0838) time: 2.6310 data: 0.0060 max mem: 33369 +Epoch: [11] [1150/1319] eta: 0:07:22 lr: 3.641935204722008e-05 loss: 0.0847 (0.0838) time: 2.6338 data: 0.0060 max mem: 33369 +Epoch: [11] [1160/1319] eta: 0:06:56 lr: 3.6410517044893844e-05 loss: 0.0838 (0.0838) time: 2.6295 data: 0.0057 max mem: 33369 +Epoch: [11] [1170/1319] eta: 0:06:30 lr: 3.6401681804359965e-05 loss: 0.0645 (0.0836) time: 2.6178 data: 0.0057 max mem: 33369 +Epoch: [11] [1180/1319] eta: 0:06:03 lr: 3.6392846325547776e-05 loss: 0.0783 (0.0838) time: 2.5923 data: 0.0056 max mem: 33369 +Epoch: [11] [1190/1319] eta: 0:05:37 lr: 3.638401060838657e-05 loss: 0.0935 (0.0839) time: 2.5904 data: 0.0056 max mem: 33369 +Epoch: [11] [1200/1319] eta: 0:05:11 lr: 3.63751746528056e-05 loss: 0.0776 (0.0838) time: 2.6148 data: 0.0056 max mem: 33369 +Epoch: [11] [1210/1319] eta: 0:04:45 lr: 3.636633845873407e-05 loss: 0.0856 (0.0840) time: 2.6108 data: 0.0055 max mem: 33369 +Epoch: [11] [1220/1319] eta: 0:04:19 lr: 3.6357502026101176e-05 loss: 0.1021 (0.0842) time: 2.6189 data: 0.0057 max mem: 33369 +Epoch: [11] [1230/1319] eta: 0:03:52 lr: 3.6348665354836024e-05 loss: 0.0944 (0.0842) time: 2.6171 data: 0.0058 max mem: 33369 +Epoch: [11] [1240/1319] eta: 0:03:26 lr: 3.6339828444867725e-05 loss: 0.0768 (0.0841) time: 2.6188 data: 0.0057 max mem: 33369 +Epoch: [11] [1250/1319] eta: 0:03:00 lr: 3.6330991296125324e-05 loss: 0.0707 (0.0842) time: 2.6419 data: 0.0058 max mem: 33369 +Epoch: [11] [1260/1319] eta: 0:02:34 lr: 3.632215390853783e-05 loss: 0.0692 (0.0841) time: 2.6376 data: 0.0057 max mem: 33369 +Epoch: [11] [1270/1319] eta: 0:02:08 lr: 3.631331628203422e-05 loss: 0.0621 (0.0841) time: 2.6530 data: 0.0056 max mem: 33369 +Epoch: [11] [1280/1319] eta: 0:01:42 lr: 3.630447841654343e-05 loss: 0.0650 (0.0840) time: 2.6575 data: 0.0056 max mem: 33369 +Epoch: [11] [1290/1319] eta: 0:01:15 lr: 3.629564031199434e-05 loss: 0.0655 (0.0840) time: 2.6450 data: 0.0058 max mem: 33369 +Epoch: [11] [1300/1319] eta: 0:00:49 lr: 3.6286801968315816e-05 loss: 0.0655 (0.0839) time: 2.6289 data: 0.0057 max mem: 33369 +Epoch: [11] [1310/1319] eta: 0:00:23 lr: 3.627796338543665e-05 loss: 0.0731 (0.0839) time: 2.6158 data: 0.0057 max mem: 33369 +Epoch: [11] Total time: 0:57:35 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 2:38:48 time: 3.7034 data: 3.6245 max mem: 33369 +Test: [ 100/2573] eta: 0:04:27 time: 0.0720 data: 0.0012 max mem: 33369 +Test: [ 200/2573] eta: 0:03:36 time: 0.0730 data: 0.0011 max mem: 33369 +Test: [ 300/2573] eta: 0:03:12 time: 0.0746 data: 0.0011 max mem: 33369 +Test: [ 400/2573] eta: 0:02:57 time: 0.0749 data: 0.0011 max mem: 33369 +Test: [ 500/2573] eta: 0:02:46 time: 0.0734 data: 0.0011 max mem: 33369 +Test: [ 600/2573] eta: 0:02:36 time: 0.0735 data: 0.0012 max mem: 33369 +Test: [ 700/2573] eta: 0:02:27 time: 0.0735 data: 0.0012 max mem: 33369 +Test: [ 800/2573] eta: 0:02:18 time: 0.0768 data: 0.0011 max mem: 33369 +Test: [ 900/2573] eta: 0:02:10 time: 0.0735 data: 0.0012 max mem: 33369 +Test: [1000/2573] eta: 0:02:01 time: 0.0735 data: 0.0012 max mem: 33369 +Test: [1100/2573] eta: 0:01:53 time: 0.0735 data: 0.0011 max mem: 33369 +Test: [1200/2573] eta: 0:01:45 time: 0.0736 data: 0.0011 max mem: 33369 +Test: [1300/2573] eta: 0:01:37 time: 0.0736 data: 0.0011 max mem: 33369 +Test: [1400/2573] eta: 0:01:29 time: 0.0719 data: 0.0011 max mem: 33369 +Test: [1500/2573] eta: 0:01:21 time: 0.0737 data: 0.0012 max mem: 33369 +Test: [1600/2573] eta: 0:01:13 time: 0.0769 data: 0.0011 max mem: 33369 +Test: [1700/2573] eta: 0:01:06 time: 0.0718 data: 0.0011 max mem: 33369 +Test: [1800/2573] eta: 0:00:58 time: 0.0753 data: 0.0011 max mem: 33369 +Test: [1900/2573] eta: 0:00:50 time: 0.0720 data: 0.0011 max mem: 33369 +Test: [2000/2573] eta: 0:00:43 time: 0.0737 data: 0.0011 max mem: 33369 +Test: [2100/2573] eta: 0:00:35 time: 0.0754 data: 0.0011 max mem: 33369 +Test: [2200/2573] eta: 0:00:28 time: 0.0754 data: 0.0011 max mem: 33369 +Test: [2300/2573] eta: 0:00:20 time: 0.0754 data: 0.0011 max mem: 33369 +Test: [2400/2573] eta: 0:00:12 time: 0.0705 data: 0.0011 max mem: 33369 +Test: [2500/2573] eta: 0:00:05 time: 0.0737 data: 0.0011 max mem: 33369 +Test: Total time: 0:03:13 +Final results: +Mean IoU is 60.32 + + precision@0.5 = 68.26 + precision@0.6 = 62.25 + precision@0.7 = 54.04 + precision@0.8 = 42.18 + precision@0.9 = 19.28 + overall IoU = 58.55 + +Average object IoU 60.32029281871559 +Overall IoU 58.547000885009766 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [12] [ 0/1319] eta: 3:02:00 lr: 3.6270008456269996e-05 loss: 0.0741 (0.0741) time: 8.2795 data: 1.3637 max mem: 33369 +Epoch: [12] [ 10/1319] eta: 1:09:47 lr: 3.6261169418713356e-05 loss: 0.0714 (0.0734) time: 3.1993 data: 0.1288 max mem: 33369 +Epoch: [12] [ 20/1319] eta: 1:03:29 lr: 3.62523301417494e-05 loss: 0.0702 (0.0793) time: 2.6651 data: 0.0056 max mem: 33369 +Epoch: [12] [ 30/1319] eta: 1:00:28 lr: 3.624349062530679e-05 loss: 0.0756 (0.0845) time: 2.6034 data: 0.0060 max mem: 33369 +Epoch: [12] [ 40/1319] eta: 0:59:03 lr: 3.623465086931413e-05 loss: 0.0715 (0.0794) time: 2.6010 data: 0.0062 max mem: 33369 +Epoch: [12] [ 50/1319] eta: 0:57:51 lr: 3.62258108737e-05 loss: 0.0668 (0.0788) time: 2.6127 data: 0.0062 max mem: 33369 +Epoch: [12] [ 60/1319] eta: 0:56:58 lr: 3.621697063839292e-05 loss: 0.0588 (0.0792) time: 2.6013 data: 0.0063 max mem: 33369 +Epoch: [12] [ 70/1319] eta: 0:56:10 lr: 3.6208130163321375e-05 loss: 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3.613739772263389e-05 loss: 0.0719 (0.0772) time: 2.6096 data: 0.0059 max mem: 33369 +Epoch: [12] [ 160/1319] eta: 0:51:18 lr: 3.6128555086457536e-05 loss: 0.0671 (0.0765) time: 2.6296 data: 0.0059 max mem: 33369 +Epoch: [12] [ 170/1319] eta: 0:50:50 lr: 3.6119712209799373e-05 loss: 0.0671 (0.0763) time: 2.6331 data: 0.0061 max mem: 33369 +Epoch: [12] [ 180/1319] eta: 0:50:20 lr: 3.6110869092587446e-05 loss: 0.0670 (0.0757) time: 2.6191 data: 0.0062 max mem: 33369 +Epoch: [12] [ 190/1319] eta: 0:49:51 lr: 3.610202573474975e-05 loss: 0.0619 (0.0750) time: 2.6066 data: 0.0062 max mem: 33369 +Epoch: [12] [ 200/1319] eta: 0:49:23 lr: 3.609318213621424e-05 loss: 0.0562 (0.0742) time: 2.6191 data: 0.0060 max mem: 33369 +Epoch: [12] [ 210/1319] eta: 0:48:55 lr: 3.608433829690883e-05 loss: 0.0649 (0.0748) time: 2.6269 data: 0.0059 max mem: 33369 +Epoch: [12] [ 220/1319] eta: 0:48:30 lr: 3.607549421676141e-05 loss: 0.0758 (0.0747) time: 2.6474 data: 0.0060 max mem: 33369 +Epoch: [12] [ 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data: 0.0063 max mem: 33369 +Epoch: [12] [ 390/1319] eta: 0:40:55 lr: 3.5925107935336354e-05 loss: 0.0719 (0.0766) time: 2.6604 data: 0.0060 max mem: 33369 +Epoch: [12] [ 400/1319] eta: 0:40:28 lr: 3.5916259507651966e-05 loss: 0.0790 (0.0766) time: 2.6233 data: 0.0060 max mem: 33369 +Epoch: [12] [ 410/1319] eta: 0:40:01 lr: 3.59074108377473e-05 loss: 0.0688 (0.0765) time: 2.6322 data: 0.0059 max mem: 33369 +Epoch: [12] [ 420/1319] eta: 0:39:35 lr: 3.58985619255494e-05 loss: 0.0543 (0.0762) time: 2.6562 data: 0.0058 max mem: 33369 +Epoch: [12] [ 430/1319] eta: 0:39:07 lr: 3.588971277098527e-05 loss: 0.0712 (0.0766) time: 2.6169 data: 0.0059 max mem: 33369 +Epoch: [12] [ 440/1319] eta: 0:38:41 lr: 3.588086337398186e-05 loss: 0.0712 (0.0764) time: 2.6036 data: 0.0060 max mem: 33369 +Epoch: [12] [ 450/1319] eta: 0:38:14 lr: 3.58720137344661e-05 loss: 0.0691 (0.0763) time: 2.6338 data: 0.0063 max mem: 33369 +Epoch: [12] [ 460/1319] eta: 0:37:47 lr: 3.5863163852364855e-05 loss: 0.0691 (0.0762) time: 2.6167 data: 0.0062 max mem: 33369 +Epoch: [12] [ 470/1319] eta: 0:37:21 lr: 3.585431372760496e-05 loss: 0.0628 (0.0760) time: 2.6262 data: 0.0059 max mem: 33369 +Epoch: [12] [ 480/1319] eta: 0:36:54 lr: 3.5845463360113225e-05 loss: 0.0628 (0.0758) time: 2.6223 data: 0.0059 max mem: 33369 +Epoch: [12] [ 490/1319] eta: 0:36:28 lr: 3.583661274981637e-05 loss: 0.0689 (0.0759) time: 2.6411 data: 0.0061 max mem: 33369 +Epoch: [12] [ 500/1319] eta: 0:36:01 lr: 3.582776189664111e-05 loss: 0.0699 (0.0758) time: 2.6393 data: 0.0061 max mem: 33369 +Epoch: [12] [ 510/1319] eta: 0:35:34 lr: 3.581891080051412e-05 loss: 0.0664 (0.0759) time: 2.5918 data: 0.0059 max mem: 33369 +Epoch: [12] [ 520/1319] eta: 0:35:08 lr: 3.5810059461362006e-05 loss: 0.0641 (0.0764) time: 2.6173 data: 0.0060 max mem: 33369 +Epoch: [12] [ 530/1319] eta: 0:34:41 lr: 3.580120787911136e-05 loss: 0.0749 (0.0766) time: 2.6459 data: 0.0062 max mem: 33369 +Epoch: [12] [ 540/1319] eta: 0:34:14 lr: 3.579235605368871e-05 loss: 0.0750 (0.0769) time: 2.6153 data: 0.0059 max mem: 33369 +Epoch: [12] [ 550/1319] eta: 0:33:46 lr: 3.578350398502055e-05 loss: 0.0702 (0.0768) time: 2.5578 data: 0.0058 max mem: 33369 +Epoch: [12] [ 560/1319] eta: 0:33:20 lr: 3.5774651673033346e-05 loss: 0.0653 (0.0768) time: 2.5815 data: 0.0059 max mem: 33369 +Epoch: [12] [ 570/1319] eta: 0:32:53 lr: 3.57657991176535e-05 loss: 0.0680 (0.0770) time: 2.6217 data: 0.0061 max mem: 33369 +Epoch: [12] [ 580/1319] eta: 0:32:27 lr: 3.5756946318807374e-05 loss: 0.0856 (0.0773) time: 2.6271 data: 0.0060 max mem: 33369 +Epoch: [12] [ 590/1319] eta: 0:32:00 lr: 3.5748093276421306e-05 loss: 0.0780 (0.0773) time: 2.6155 data: 0.0059 max mem: 33369 +Epoch: [12] [ 600/1319] eta: 0:31:34 lr: 3.573923999042157e-05 loss: 0.0755 (0.0775) time: 2.6058 data: 0.0059 max mem: 33369 +Epoch: [12] [ 610/1319] eta: 0:31:07 lr: 3.573038646073439e-05 loss: 0.0753 (0.0776) time: 2.6329 data: 0.0059 max mem: 33369 +Epoch: [12] [ 620/1319] eta: 0:30:41 lr: 3.5721532687286004e-05 loss: 0.0737 (0.0782) time: 2.6223 data: 0.0060 max mem: 33369 +Epoch: [12] [ 630/1319] eta: 0:30:14 lr: 3.571267867000252e-05 loss: 0.0715 (0.0782) time: 2.6145 data: 0.0059 max mem: 33369 +Epoch: [12] [ 640/1319] eta: 0:29:48 lr: 3.570382440881008e-05 loss: 0.0632 (0.0780) time: 2.6278 data: 0.0058 max mem: 33369 +Epoch: [12] [ 650/1319] eta: 0:29:21 lr: 3.5694969903634736e-05 loss: 0.0608 (0.0779) time: 2.6203 data: 0.0057 max mem: 33369 +Epoch: [12] [ 660/1319] eta: 0:28:55 lr: 3.568611515440253e-05 loss: 0.0608 (0.0779) time: 2.6011 data: 0.0058 max mem: 33369 +Epoch: [12] [ 670/1319] eta: 0:28:28 lr: 3.567726016103943e-05 loss: 0.0636 (0.0779) time: 2.5979 data: 0.0059 max mem: 33369 +Epoch: [12] [ 680/1319] eta: 0:28:01 lr: 3.5668404923471386e-05 loss: 0.0616 (0.0777) time: 2.5906 data: 0.0061 max mem: 33369 +Epoch: [12] [ 690/1319] eta: 0:27:34 lr: 3.565954944162429e-05 loss: 0.0616 (0.0776) time: 2.5921 data: 0.0061 max mem: 33369 +Epoch: [12] [ 700/1319] eta: 0:27:08 lr: 3.5650693715424005e-05 loss: 0.0717 (0.0776) time: 2.6035 data: 0.0058 max mem: 33369 +Epoch: [12] [ 710/1319] eta: 0:26:41 lr: 3.564183774479633e-05 loss: 0.0667 (0.0775) time: 2.6029 data: 0.0058 max mem: 33369 +Epoch: [12] [ 720/1319] eta: 0:26:15 lr: 3.563298152966704e-05 loss: 0.0584 (0.0773) time: 2.6211 data: 0.0058 max mem: 33369 +Epoch: [12] [ 730/1319] eta: 0:25:49 lr: 3.562412506996187e-05 loss: 0.0584 (0.0770) time: 2.6295 data: 0.0060 max mem: 33369 +Epoch: [12] [ 740/1319] eta: 0:25:23 lr: 3.561526836560649e-05 loss: 0.0591 (0.0771) time: 2.6310 data: 0.0059 max mem: 33369 +Epoch: [12] [ 750/1319] eta: 0:24:56 lr: 3.560641141652653e-05 loss: 0.0664 (0.0772) time: 2.6290 data: 0.0057 max mem: 33369 +Epoch: [12] [ 760/1319] eta: 0:24:30 lr: 3.5597554222647605e-05 loss: 0.0664 (0.0770) time: 2.6166 data: 0.0057 max mem: 33369 +Epoch: [12] [ 770/1319] eta: 0:24:04 lr: 3.558869678389526e-05 loss: 0.0692 (0.0771) time: 2.6417 data: 0.0057 max mem: 33369 +Epoch: [12] [ 780/1319] eta: 0:23:37 lr: 3.5579839100195013e-05 loss: 0.0763 (0.0771) time: 2.6445 data: 0.0058 max mem: 33369 +Epoch: [12] [ 790/1319] eta: 0:23:11 lr: 3.5570981171472317e-05 loss: 0.0744 (0.0772) time: 2.6076 data: 0.0059 max mem: 33369 +Epoch: [12] [ 800/1319] eta: 0:22:44 lr: 3.55621229976526e-05 loss: 0.0837 (0.0773) time: 2.5960 data: 0.0057 max mem: 33369 +Epoch: [12] [ 810/1319] eta: 0:22:18 lr: 3.555326457866125e-05 loss: 0.0819 (0.0774) time: 2.5946 data: 0.0058 max mem: 33369 +Epoch: [12] [ 820/1319] eta: 0:21:51 lr: 3.554440591442359e-05 loss: 0.0681 (0.0774) time: 2.5949 data: 0.0060 max mem: 33369 +Epoch: [12] [ 830/1319] eta: 0:21:25 lr: 3.5535547004864924e-05 loss: 0.0612 (0.0772) time: 2.6167 data: 0.0061 max mem: 33369 +Epoch: [12] [ 840/1319] eta: 0:20:58 lr: 3.552668784991049e-05 loss: 0.0685 (0.0775) time: 2.5951 data: 0.0060 max mem: 33369 +Epoch: [12] [ 850/1319] eta: 0:20:32 lr: 3.551782844948551e-05 loss: 0.0806 (0.0775) time: 2.5907 data: 0.0059 max mem: 33369 +Epoch: [12] [ 860/1319] eta: 0:20:06 lr: 3.550896880351513e-05 loss: 0.0735 (0.0775) time: 2.6066 data: 0.0059 max mem: 33369 +Epoch: [12] [ 870/1319] eta: 0:19:39 lr: 3.550010891192448e-05 loss: 0.0724 (0.0775) time: 2.6062 data: 0.0059 max mem: 33369 +Epoch: [12] [ 880/1319] eta: 0:19:13 lr: 3.549124877463863e-05 loss: 0.0701 (0.0777) time: 2.6204 data: 0.0061 max mem: 33369 +Epoch: [12] [ 890/1319] eta: 0:18:47 lr: 3.548238839158261e-05 loss: 0.0651 (0.0776) time: 2.6219 data: 0.0062 max mem: 33369 +Epoch: [12] [ 900/1319] eta: 0:18:20 lr: 3.5473527762681414e-05 loss: 0.0651 (0.0777) time: 2.6177 data: 0.0062 max mem: 33369 +Epoch: [12] [ 910/1319] eta: 0:17:54 lr: 3.546466688785999e-05 loss: 0.0704 (0.0777) time: 2.6201 data: 0.0061 max mem: 33369 +Epoch: [12] [ 920/1319] eta: 0:17:28 lr: 3.545580576704322e-05 loss: 0.0692 (0.0778) time: 2.6091 data: 0.0060 max mem: 33369 +Epoch: [12] [ 930/1319] eta: 0:17:01 lr: 3.544694440015598e-05 loss: 0.0950 (0.0781) time: 2.6188 data: 0.0058 max mem: 33369 +Epoch: [12] [ 940/1319] eta: 0:16:35 lr: 3.543808278712307e-05 loss: 0.0861 (0.0782) time: 2.6201 data: 0.0058 max mem: 33369 +Epoch: [12] [ 950/1319] eta: 0:16:09 lr: 3.542922092786927e-05 loss: 0.0696 (0.0782) time: 2.6022 data: 0.0059 max mem: 33369 +Epoch: [12] [ 960/1319] eta: 0:15:42 lr: 3.542035882231929e-05 loss: 0.0728 (0.0782) time: 2.6258 data: 0.0060 max mem: 33369 +Epoch: [12] [ 970/1319] eta: 0:15:16 lr: 3.541149647039783e-05 loss: 0.0752 (0.0784) time: 2.6506 data: 0.0059 max mem: 33369 +Epoch: [12] [ 980/1319] eta: 0:14:50 lr: 3.540263387202951e-05 loss: 0.0738 (0.0783) time: 2.6440 data: 0.0058 max mem: 33369 +Epoch: [12] [ 990/1319] eta: 0:14:24 lr: 3.5393771027138936e-05 loss: 0.0689 (0.0783) time: 2.6047 data: 0.0060 max mem: 33369 +Epoch: [12] [1000/1319] eta: 0:13:57 lr: 3.5384907935650645e-05 loss: 0.0636 (0.0783) time: 2.5942 data: 0.0060 max mem: 33369 +Epoch: [12] [1010/1319] eta: 0:13:31 lr: 3.5376044597489155e-05 loss: 0.0636 (0.0783) time: 2.5974 data: 0.0058 max mem: 33369 +Epoch: [12] [1020/1319] eta: 0:13:05 lr: 3.536718101257892e-05 loss: 0.0767 (0.0785) time: 2.6077 data: 0.0059 max mem: 33369 +Epoch: [12] [1030/1319] eta: 0:12:38 lr: 3.5358317180844356e-05 loss: 0.0942 (0.0787) time: 2.6368 data: 0.0059 max mem: 33369 +Epoch: [12] [1040/1319] eta: 0:12:12 lr: 3.5349453102209835e-05 loss: 0.0654 (0.0785) time: 2.6324 data: 0.0059 max mem: 33369 +Epoch: [12] [1050/1319] eta: 0:11:46 lr: 3.534058877659969e-05 loss: 0.0591 (0.0784) time: 2.6199 data: 0.0059 max mem: 33369 +Epoch: [12] [1060/1319] eta: 0:11:20 lr: 3.5331724203938196e-05 loss: 0.0687 (0.0783) time: 2.6251 data: 0.0059 max mem: 33369 +Epoch: [12] [1070/1319] eta: 0:10:53 lr: 3.53228593841496e-05 loss: 0.0674 (0.0782) time: 2.6317 data: 0.0059 max mem: 33369 +Epoch: [12] [1080/1319] eta: 0:10:27 lr: 3.53139943171581e-05 loss: 0.0674 (0.0783) time: 2.6127 data: 0.0058 max mem: 33369 +Epoch: [12] [1090/1319] eta: 0:10:01 lr: 3.5305129002887835e-05 loss: 0.0738 (0.0783) time: 2.6081 data: 0.0057 max mem: 33369 +Epoch: [12] [1100/1319] eta: 0:09:35 lr: 3.529626344126292e-05 loss: 0.0674 (0.0782) time: 2.6376 data: 0.0056 max mem: 33369 +Epoch: [12] [1110/1319] eta: 0:09:08 lr: 3.5287397632207417e-05 loss: 0.0611 (0.0781) time: 2.6252 data: 0.0058 max mem: 33369 +Epoch: [12] [1120/1319] eta: 0:08:42 lr: 3.527853157564535e-05 loss: 0.0696 (0.0782) time: 2.6257 data: 0.0059 max mem: 33369 +Epoch: [12] [1130/1319] eta: 0:08:16 lr: 3.526966527150067e-05 loss: 0.0783 (0.0783) time: 2.6482 data: 0.0060 max mem: 33369 +Epoch: [12] [1140/1319] eta: 0:07:50 lr: 3.5260798719697326e-05 loss: 0.0829 (0.0783) time: 2.6234 data: 0.0061 max mem: 33369 +Epoch: [12] [1150/1319] eta: 0:07:23 lr: 3.52519319201592e-05 loss: 0.0716 (0.0782) time: 2.6248 data: 0.0061 max mem: 33369 +Epoch: [12] [1160/1319] eta: 0:06:57 lr: 3.524306487281011e-05 loss: 0.0545 (0.0781) time: 2.6255 data: 0.0060 max mem: 33369 +Epoch: [12] [1170/1319] eta: 0:06:31 lr: 3.523419757757387e-05 loss: 0.0500 (0.0780) time: 2.6003 data: 0.0060 max mem: 33369 +Epoch: [12] [1180/1319] eta: 0:06:04 lr: 3.5225330034374235e-05 loss: 0.0595 (0.0779) time: 2.5965 data: 0.0063 max mem: 33369 +Epoch: [12] [1190/1319] eta: 0:05:38 lr: 3.5216462243134885e-05 loss: 0.0595 (0.0779) time: 2.6202 data: 0.0060 max mem: 33369 +Epoch: [12] [1200/1319] eta: 0:05:12 lr: 3.52075942037795e-05 loss: 0.0710 (0.0779) time: 2.6225 data: 0.0058 max mem: 33369 +Epoch: [12] [1210/1319] eta: 0:04:46 lr: 3.519872591623169e-05 loss: 0.0753 (0.0778) time: 2.6206 data: 0.0058 max mem: 33369 +Epoch: [12] [1220/1319] eta: 0:04:19 lr: 3.518985738041502e-05 loss: 0.0781 (0.0779) time: 2.6162 data: 0.0058 max mem: 33369 +Epoch: [12] [1230/1319] eta: 0:03:53 lr: 3.518098859625303e-05 loss: 0.0769 (0.0779) time: 2.6172 data: 0.0060 max mem: 33369 +Epoch: [12] [1240/1319] eta: 0:03:27 lr: 3.517211956366918e-05 loss: 0.0711 (0.0779) time: 2.6103 data: 0.0061 max mem: 33369 +Epoch: [12] [1250/1319] eta: 0:03:01 lr: 3.5163250282586914e-05 loss: 0.0711 (0.0778) time: 2.5974 data: 0.0061 max mem: 33369 +Epoch: [12] [1260/1319] eta: 0:02:34 lr: 3.515438075292963e-05 loss: 0.0757 (0.0779) time: 2.6230 data: 0.0060 max mem: 33369 +Epoch: [12] [1270/1319] eta: 0:02:08 lr: 3.514551097462066e-05 loss: 0.0784 (0.0780) time: 2.6302 data: 0.0059 max mem: 33369 +Epoch: [12] [1280/1319] eta: 0:01:42 lr: 3.513664094758331e-05 loss: 0.0698 (0.0780) time: 2.6194 data: 0.0058 max mem: 33369 +Epoch: [12] [1290/1319] eta: 0:01:16 lr: 3.512777067174083e-05 loss: 0.0689 (0.0779) time: 2.5949 data: 0.0059 max mem: 33369 +Epoch: [12] [1300/1319] eta: 0:00:49 lr: 3.511890014701643e-05 loss: 0.0689 (0.0779) time: 2.5935 data: 0.0059 max mem: 33369 +Epoch: [12] [1310/1319] eta: 0:00:23 lr: 3.511002937333328e-05 loss: 0.0717 (0.0780) time: 2.6040 data: 0.0058 max mem: 33369 +Epoch: [12] Total time: 0:57:41 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 1:50:56 time: 2.5872 data: 2.4709 max mem: 33369 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 100/2573] eta: 0:03:59 time: 0.0719 data: 0.0011 max mem: 33369 +Test: [ 200/2573] eta: 0:03:22 time: 0.0730 data: 0.0012 max mem: 33369 +Test: [ 300/2573] eta: 0:03:03 time: 0.0747 data: 0.0012 max mem: 33369 +Test: [ 400/2573] eta: 0:02:51 time: 0.0750 data: 0.0011 max mem: 33369 +Test: [ 500/2573] eta: 0:02:41 time: 0.0733 data: 0.0012 max mem: 33369 +Test: [ 600/2573] eta: 0:02:32 time: 0.0733 data: 0.0011 max mem: 33369 +Test: [ 700/2573] eta: 0:02:24 time: 0.0734 data: 0.0011 max mem: 33369 +Test: [ 800/2573] eta: 0:02:15 time: 0.0767 data: 0.0011 max mem: 33369 +Test: [ 900/2573] eta: 0:02:07 time: 0.0735 data: 0.0011 max mem: 33369 +Test: [1000/2573] eta: 0:01:59 time: 0.0737 data: 0.0012 max mem: 33369 +Test: [1100/2573] eta: 0:01:51 time: 0.0735 data: 0.0012 max mem: 33369 +Test: [1200/2573] eta: 0:01:44 time: 0.0734 data: 0.0011 max mem: 33369 +Test: [1300/2573] eta: 0:01:36 time: 0.0736 data: 0.0011 max mem: 33369 +Test: [1400/2573] eta: 0:01:28 time: 0.0720 data: 0.0011 max mem: 33369 +Test: [1500/2573] eta: 0:01:20 time: 0.0736 data: 0.0012 max mem: 33369 +Test: [1600/2573] eta: 0:01:13 time: 0.0772 data: 0.0012 max mem: 33369 +Test: [1700/2573] eta: 0:01:05 time: 0.0721 data: 0.0011 max mem: 33369 +Test: [1800/2573] eta: 0:00:58 time: 0.0754 data: 0.0012 max mem: 33369 +Test: [1900/2573] eta: 0:00:50 time: 0.0721 data: 0.0011 max mem: 33369 +Test: [2000/2573] eta: 0:00:42 time: 0.0738 data: 0.0011 max mem: 33369 +Test: [2100/2573] eta: 0:00:35 time: 0.0754 data: 0.0011 max mem: 33369 +Test: [2200/2573] eta: 0:00:27 time: 0.0754 data: 0.0011 max mem: 33369 +Test: [2300/2573] eta: 0:00:20 time: 0.0755 data: 0.0012 max mem: 33369 +Test: [2400/2573] eta: 0:00:12 time: 0.0703 data: 0.0011 max mem: 33369 +Test: [2500/2573] eta: 0:00:05 time: 0.0736 data: 0.0011 max mem: 33369 +Test: Total time: 0:03:12 +Final results: +Mean IoU is 60.88 + + precision@0.5 = 68.95 + precision@0.6 = 62.56 + precision@0.7 = 54.70 + precision@0.8 = 42.97 + precision@0.9 = 19.93 + overall IoU = 59.17 + +Average object IoU 60.87678666572781 +Overall IoU 59.16983413696289 +Better epoch: 12 + +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [13] [ 0/1319] eta: 1:26:52 lr: 3.510204546409517e-05 loss: 0.0612 (0.0612) time: 3.9522 data: 1.1910 max mem: 33369 +Epoch: [13] [ 10/1319] eta: 0:59:47 lr: 3.509317421717855e-05 loss: 0.0670 (0.0692) time: 2.7410 data: 0.1138 max mem: 33369 +Epoch: [13] [ 20/1319] eta: 0:58:11 lr: 3.50843027210801e-05 loss: 0.0670 (0.0706) time: 2.6247 data: 0.0058 max mem: 33369 +Epoch: [13] [ 30/1319] eta: 0:57:18 lr: 3.5075430975722793e-05 loss: 0.0655 (0.0747) time: 2.6270 data: 0.0059 max mem: 33369 +Epoch: [13] [ 40/1319] eta: 0:56:45 lr: 3.506655898102959e-05 loss: 0.0621 (0.0731) time: 2.6363 data: 0.0063 max mem: 33369 +Epoch: [13] [ 50/1319] eta: 0:55:57 lr: 3.505768673692337e-05 loss: 0.0616 (0.0717) time: 2.6121 data: 0.0063 max mem: 33369 +Epoch: [13] [ 60/1319] eta: 0:55:24 lr: 3.5048814243327e-05 loss: 0.0533 (0.0723) time: 2.5951 data: 0.0062 max mem: 33369 +Epoch: [13] [ 70/1319] eta: 0:54:47 lr: 3.503994150016327e-05 loss: 0.0596 (0.0719) time: 2.5976 data: 0.0063 max mem: 33369 +Epoch: [13] [ 80/1319] eta: 0:54:26 lr: 3.503106850735495e-05 loss: 0.0607 (0.0702) time: 2.6229 data: 0.0063 max mem: 33369 +Epoch: [13] [ 90/1319] eta: 0:54:00 lr: 3.502219526482476e-05 loss: 0.0607 (0.0712) time: 2.6520 data: 0.0060 max mem: 33369 +Epoch: [13] [ 100/1319] eta: 0:53:35 lr: 3.501332177249536e-05 loss: 0.0723 (0.0711) time: 2.6449 data: 0.0059 max mem: 33369 +Epoch: [13] [ 110/1319] eta: 0:53:02 lr: 3.500444803028936e-05 loss: 0.0595 (0.0696) time: 2.6152 data: 0.0060 max mem: 33369 +Epoch: [13] [ 120/1319] eta: 0:52:36 lr: 3.499557403812936e-05 loss: 0.0546 (0.0709) time: 2.6058 data: 0.0061 max mem: 33369 +Epoch: [13] [ 130/1319] eta: 0:52:12 lr: 3.498669979593787e-05 loss: 0.0615 (0.0721) time: 2.6474 data: 0.0060 max mem: 33369 +Epoch: [13] [ 140/1319] eta: 0:51:45 lr: 3.497782530363739e-05 loss: 0.0651 (0.0718) time: 2.6431 data: 0.0062 max mem: 33369 +Epoch: [13] [ 150/1319] eta: 0:51:18 lr: 3.4968950561150356e-05 loss: 0.0703 (0.0722) time: 2.6234 data: 0.0062 max mem: 33369 +Epoch: [13] [ 160/1319] eta: 0:50:49 lr: 3.496007556839915e-05 loss: 0.0792 (0.0733) time: 2.6075 data: 0.0062 max mem: 33369 +Epoch: [13] [ 170/1319] eta: 0:50:20 lr: 3.495120032530614e-05 loss: 0.0779 (0.0734) time: 2.5964 data: 0.0063 max mem: 33369 +Epoch: [13] [ 180/1319] eta: 0:49:53 lr: 3.49423248317936e-05 loss: 0.0713 (0.0739) time: 2.6039 data: 0.0061 max mem: 33369 +Epoch: [13] [ 190/1319] eta: 0:49:26 lr: 3.493344908778381e-05 loss: 0.0685 (0.0739) time: 2.6179 data: 0.0061 max mem: 33369 +Epoch: [13] [ 200/1319] eta: 0:48:58 lr: 3.4924573093198975e-05 loss: 0.0654 (0.0740) time: 2.6137 data: 0.0062 max mem: 33369 +Epoch: [13] [ 210/1319] eta: 0:48:31 lr: 3.491569684796125e-05 loss: 0.0622 (0.0737) time: 2.5994 data: 0.0061 max mem: 33369 +Epoch: [13] [ 220/1319] eta: 0:48:06 lr: 3.490682035199276e-05 loss: 0.0622 (0.0739) time: 2.6262 data: 0.0060 max mem: 33369 +Epoch: [13] [ 230/1319] eta: 0:47:42 lr: 3.4897943605215565e-05 loss: 0.0675 (0.0739) time: 2.6638 data: 0.0060 max mem: 33369 +Epoch: [13] [ 240/1319] eta: 0:47:16 lr: 3.488906660755169e-05 loss: 0.0625 (0.0734) time: 2.6609 data: 0.0059 max mem: 33369 +Epoch: [13] [ 250/1319] eta: 0:46:48 lr: 3.4880189358923125e-05 loss: 0.0584 (0.0735) time: 2.6137 data: 0.0061 max mem: 33369 +Epoch: [13] [ 260/1319] eta: 0:46:23 lr: 3.487131185925179e-05 loss: 0.0614 (0.0730) time: 2.6125 data: 0.0061 max mem: 33369 +Epoch: [13] [ 270/1319] eta: 0:45:57 lr: 3.486243410845958e-05 loss: 0.0632 (0.0728) time: 2.6518 data: 0.0060 max mem: 33369 +Epoch: [13] [ 280/1319] eta: 0:45:31 lr: 3.485355610646832e-05 loss: 0.0688 (0.0733) time: 2.6371 data: 0.0060 max mem: 33369 +Epoch: [13] [ 290/1319] eta: 0:45:04 lr: 3.484467785319982e-05 loss: 0.0657 (0.0729) time: 2.6193 data: 0.0060 max mem: 33369 +Epoch: [13] [ 300/1319] eta: 0:44:38 lr: 3.483579934857581e-05 loss: 0.0657 (0.0734) time: 2.6319 data: 0.0061 max mem: 33369 +Epoch: [13] [ 310/1319] eta: 0:44:11 lr: 3.4826920592518003e-05 loss: 0.0726 (0.0734) time: 2.6115 data: 0.0062 max mem: 33369 +Epoch: [13] [ 320/1319] eta: 0:43:44 lr: 3.481804158494804e-05 loss: 0.0647 (0.0733) time: 2.5985 data: 0.0062 max mem: 33369 +Epoch: [13] [ 330/1319] eta: 0:43:16 lr: 3.4809162325787535e-05 loss: 0.0647 (0.0733) time: 2.6005 data: 0.0060 max mem: 33369 +Epoch: [13] [ 340/1319] eta: 0:42:51 lr: 3.480028281495805e-05 loss: 0.0584 (0.0733) time: 2.6151 data: 0.0059 max mem: 33369 +Epoch: [13] [ 350/1319] eta: 0:42:23 lr: 3.479140305238109e-05 loss: 0.0629 (0.0730) time: 2.6179 data: 0.0059 max mem: 33369 +Epoch: [13] [ 360/1319] eta: 0:41:57 lr: 3.478252303797812e-05 loss: 0.0660 (0.0732) time: 2.6105 data: 0.0058 max mem: 33369 +Epoch: [13] [ 370/1319] eta: 0:41:31 lr: 3.4773642771670566e-05 loss: 0.0535 (0.0730) time: 2.6357 data: 0.0058 max mem: 33369 +Epoch: [13] [ 380/1319] eta: 0:41:05 lr: 3.47647622533798e-05 loss: 0.0534 (0.0728) time: 2.6278 data: 0.0061 max mem: 33369 +Epoch: [13] [ 390/1319] eta: 0:40:39 lr: 3.475588148302715e-05 loss: 0.0605 (0.0727) time: 2.6215 data: 0.0060 max mem: 33369 +Epoch: [13] [ 400/1319] eta: 0:40:12 lr: 3.474700046053388e-05 loss: 0.0605 (0.0724) time: 2.6244 data: 0.0060 max mem: 33369 +Epoch: [13] [ 410/1319] eta: 0:39:47 lr: 3.473811918582123e-05 loss: 0.0686 (0.0725) time: 2.6401 data: 0.0059 max mem: 33369 +Epoch: [13] [ 420/1319] eta: 0:39:20 lr: 3.47292376588104e-05 loss: 0.0715 (0.0723) time: 2.6215 data: 0.0059 max mem: 33369 +Epoch: [13] [ 430/1319] eta: 0:38:52 lr: 3.472035587942251e-05 loss: 0.0602 (0.0723) time: 2.5794 data: 0.0059 max mem: 33369 +Epoch: [13] [ 440/1319] eta: 0:38:26 lr: 3.4711473847578654e-05 loss: 0.0643 (0.0732) time: 2.6088 data: 0.0059 max mem: 33369 +Epoch: [13] [ 450/1319] eta: 0:38:01 lr: 3.470259156319988e-05 loss: 0.0846 (0.0735) time: 2.6400 data: 0.0059 max mem: 33369 +Epoch: [13] [ 460/1319] eta: 0:37:34 lr: 3.469370902620718e-05 loss: 0.0770 (0.0734) time: 2.6209 data: 0.0060 max mem: 33369 +Epoch: [13] [ 470/1319] eta: 0:37:08 lr: 3.4684826236521504e-05 loss: 0.0601 (0.0733) time: 2.6142 data: 0.0061 max mem: 33369 +Epoch: [13] [ 480/1319] eta: 0:36:42 lr: 3.467594319406376e-05 loss: 0.0590 (0.0732) time: 2.6297 data: 0.0059 max mem: 33369 +Epoch: [13] [ 490/1319] eta: 0:36:15 lr: 3.466705989875479e-05 loss: 0.0595 (0.0730) time: 2.6087 data: 0.0060 max mem: 33369 +Epoch: [13] [ 500/1319] eta: 0:35:48 lr: 3.465817635051541e-05 loss: 0.0679 (0.0731) time: 2.6029 data: 0.0060 max mem: 33369 +Epoch: [13] [ 510/1319] eta: 0:35:22 lr: 3.4649292549266374e-05 loss: 0.0681 (0.0730) time: 2.6285 data: 0.0058 max mem: 33369 +Epoch: [13] [ 520/1319] eta: 0:34:56 lr: 3.464040849492841e-05 loss: 0.0642 (0.0729) time: 2.6258 data: 0.0057 max mem: 33369 +Epoch: [13] [ 530/1319] eta: 0:34:29 lr: 3.463152418742217e-05 loss: 0.0642 (0.0731) time: 2.6079 data: 0.0058 max mem: 33369 +Epoch: [13] [ 540/1319] eta: 0:34:03 lr: 3.4622639626668276e-05 loss: 0.0677 (0.0734) time: 2.6229 data: 0.0058 max mem: 33369 +Epoch: [13] [ 550/1319] eta: 0:33:37 lr: 3.461375481258729e-05 loss: 0.0825 (0.0736) time: 2.6438 data: 0.0059 max mem: 33369 +Epoch: [13] [ 560/1319] eta: 0:33:11 lr: 3.460486974509975e-05 loss: 0.0676 (0.0734) time: 2.6334 data: 0.0058 max mem: 33369 +Epoch: [13] [ 570/1319] eta: 0:32:45 lr: 3.4595984424126115e-05 loss: 0.0549 (0.0733) time: 2.6267 data: 0.0058 max mem: 33369 +Epoch: [13] [ 580/1319] eta: 0:32:19 lr: 3.458709884958682e-05 loss: 0.0667 (0.0732) time: 2.6314 data: 0.0057 max mem: 33369 +Epoch: [13] [ 590/1319] eta: 0:31:52 lr: 3.457821302140224e-05 loss: 0.0667 (0.0732) time: 2.6109 data: 0.0057 max mem: 33369 +Epoch: [13] [ 600/1319] eta: 0:31:26 lr: 3.456932693949272e-05 loss: 0.0726 (0.0734) time: 2.6159 data: 0.0060 max mem: 33369 +Epoch: [13] [ 610/1319] eta: 0:31:00 lr: 3.456044060377853e-05 loss: 0.0726 (0.0735) time: 2.6333 data: 0.0060 max mem: 33369 +Epoch: [13] [ 620/1319] eta: 0:30:34 lr: 3.455155401417991e-05 loss: 0.0723 (0.0734) time: 2.6169 data: 0.0059 max mem: 33369 +Epoch: [13] [ 630/1319] eta: 0:30:08 lr: 3.4542667170617054e-05 loss: 0.0617 (0.0734) time: 2.6333 data: 0.0057 max mem: 33369 +Epoch: [13] [ 640/1319] eta: 0:29:41 lr: 3.453378007301009e-05 loss: 0.0752 (0.0735) time: 2.6387 data: 0.0057 max mem: 33369 +Epoch: [13] [ 650/1319] eta: 0:29:15 lr: 3.4524892721279126e-05 loss: 0.0722 (0.0734) time: 2.6000 data: 0.0058 max mem: 33369 +Epoch: [13] [ 660/1319] eta: 0:28:48 lr: 3.4516005115344196e-05 loss: 0.0537 (0.0731) time: 2.5804 data: 0.0058 max mem: 33369 +Epoch: [13] [ 670/1319] eta: 0:28:22 lr: 3.45071172551253e-05 loss: 0.0537 (0.0731) time: 2.5967 data: 0.0059 max mem: 33369 +Epoch: [13] [ 680/1319] eta: 0:27:56 lr: 3.4498229140542384e-05 loss: 0.0678 (0.0732) time: 2.6339 data: 0.0059 max mem: 33369 +Epoch: [13] [ 690/1319] eta: 0:27:29 lr: 3.448934077151535e-05 loss: 0.0682 (0.0732) time: 2.6257 data: 0.0060 max mem: 33369 +Epoch: [13] [ 700/1319] eta: 0:27:03 lr: 3.448045214796405e-05 loss: 0.0662 (0.0732) time: 2.5959 data: 0.0060 max mem: 33369 +Epoch: [13] [ 710/1319] eta: 0:26:36 lr: 3.447156326980829e-05 loss: 0.0667 (0.0731) time: 2.5952 data: 0.0059 max mem: 33369 +Epoch: [13] [ 720/1319] eta: 0:26:10 lr: 3.446267413696782e-05 loss: 0.0663 (0.0730) time: 2.5994 data: 0.0060 max mem: 33369 +Epoch: [13] [ 730/1319] eta: 0:25:44 lr: 3.445378474936235e-05 loss: 0.0645 (0.0732) time: 2.6141 data: 0.0060 max mem: 33369 +Epoch: [13] [ 740/1319] eta: 0:25:17 lr: 3.444489510691154e-05 loss: 0.0613 (0.0731) time: 2.6161 data: 0.0061 max mem: 33369 +Epoch: [13] [ 750/1319] eta: 0:24:51 lr: 3.443600520953501e-05 loss: 0.0613 (0.0732) time: 2.6174 data: 0.0059 max mem: 33369 +Epoch: [13] [ 760/1319] eta: 0:24:25 lr: 3.4427115057152303e-05 loss: 0.0717 (0.0732) time: 2.6032 data: 0.0057 max mem: 33369 +Epoch: [13] [ 770/1319] eta: 0:23:58 lr: 3.441822464968295e-05 loss: 0.0783 (0.0734) time: 2.5683 data: 0.0059 max mem: 33369 +Epoch: [13] [ 780/1319] eta: 0:23:32 lr: 3.44093339870464e-05 loss: 0.0784 (0.0734) time: 2.5846 data: 0.0060 max mem: 33369 +Epoch: [13] [ 790/1319] eta: 0:23:05 lr: 3.4400443069162084e-05 loss: 0.0633 (0.0734) time: 2.6029 data: 0.0059 max mem: 33369 +Epoch: [13] [ 800/1319] eta: 0:22:39 lr: 3.439155189594936e-05 loss: 0.0739 (0.0734) time: 2.6186 data: 0.0058 max mem: 33369 +Epoch: [13] [ 810/1319] eta: 0:22:13 lr: 3.4382660467327555e-05 loss: 0.0702 (0.0733) time: 2.6146 data: 0.0058 max mem: 33369 +Epoch: [13] [ 820/1319] eta: 0:21:47 lr: 3.437376878321594e-05 loss: 0.0671 (0.0735) time: 2.6114 data: 0.0058 max mem: 33369 +Epoch: [13] [ 830/1319] eta: 0:21:21 lr: 3.436487684353372e-05 loss: 0.0676 (0.0735) time: 2.6262 data: 0.0058 max mem: 33369 +Epoch: [13] [ 840/1319] eta: 0:20:55 lr: 3.435598464820009e-05 loss: 0.0676 (0.0734) time: 2.6243 data: 0.0059 max mem: 33369 +Epoch: [13] [ 850/1319] eta: 0:20:28 lr: 3.434709219713417e-05 loss: 0.0629 (0.0733) time: 2.6338 data: 0.0058 max mem: 33369 +Epoch: [13] [ 860/1319] eta: 0:20:02 lr: 3.433819949025503e-05 loss: 0.0588 (0.0733) time: 2.6131 data: 0.0058 max mem: 33369 +Epoch: [13] [ 870/1319] eta: 0:19:36 lr: 3.432930652748169e-05 loss: 0.0638 (0.0733) time: 2.6101 data: 0.0057 max mem: 33369 +Epoch: [13] [ 880/1319] eta: 0:19:10 lr: 3.432041330873315e-05 loss: 0.0695 (0.0734) time: 2.6270 data: 0.0056 max mem: 33369 +Epoch: [13] [ 890/1319] eta: 0:18:43 lr: 3.4311519833928315e-05 loss: 0.0695 (0.0733) time: 2.6093 data: 0.0059 max mem: 33369 +Epoch: [13] [ 900/1319] eta: 0:18:17 lr: 3.430262610298607e-05 loss: 0.0654 (0.0733) time: 2.6108 data: 0.0059 max mem: 33369 +Epoch: [13] [ 910/1319] eta: 0:17:51 lr: 3.429373211582526e-05 loss: 0.0588 (0.0732) time: 2.6283 data: 0.0057 max mem: 33369 +Epoch: [13] [ 920/1319] eta: 0:17:25 lr: 3.428483787236465e-05 loss: 0.0594 (0.0731) time: 2.6257 data: 0.0058 max mem: 33369 +Epoch: [13] [ 930/1319] eta: 0:16:59 lr: 3.4275943372522975e-05 loss: 0.0616 (0.0730) time: 2.6038 data: 0.0059 max mem: 33369 +Epoch: [13] [ 940/1319] eta: 0:16:32 lr: 3.426704861621893e-05 loss: 0.0676 (0.0732) time: 2.5930 data: 0.0058 max mem: 33369 +Epoch: [13] [ 950/1319] eta: 0:16:06 lr: 3.4258153603371135e-05 loss: 0.0736 (0.0732) time: 2.6094 data: 0.0058 max mem: 33369 +Epoch: [13] [ 960/1319] eta: 0:15:40 lr: 3.424925833389819e-05 loss: 0.0634 (0.0732) time: 2.6136 data: 0.0058 max mem: 33369 +Epoch: [13] [ 970/1319] eta: 0:15:14 lr: 3.424036280771861e-05 loss: 0.0603 (0.0733) time: 2.6077 data: 0.0059 max mem: 33369 +Epoch: [13] [ 980/1319] eta: 0:14:47 lr: 3.42314670247509e-05 loss: 0.0678 (0.0734) time: 2.5983 data: 0.0060 max mem: 33369 +Epoch: [13] [ 990/1319] eta: 0:14:21 lr: 3.422257098491348e-05 loss: 0.0704 (0.0735) time: 2.6140 data: 0.0060 max mem: 33369 +Epoch: [13] [1000/1319] eta: 0:13:55 lr: 3.4213674688124745e-05 loss: 0.0671 (0.0733) time: 2.6227 data: 0.0058 max mem: 33369 +Epoch: [13] [1010/1319] eta: 0:13:29 lr: 3.420477813430303e-05 loss: 0.0607 (0.0733) time: 2.6222 data: 0.0059 max mem: 33369 +Epoch: [13] [1020/1319] eta: 0:13:03 lr: 3.419588132336663e-05 loss: 0.0604 (0.0733) time: 2.6275 data: 0.0060 max mem: 33369 +Epoch: [13] [1030/1319] eta: 0:12:36 lr: 3.418698425523378e-05 loss: 0.0583 (0.0732) time: 2.6219 data: 0.0058 max mem: 33369 +Epoch: [13] [1040/1319] eta: 0:12:10 lr: 3.417808692982266e-05 loss: 0.0621 (0.0732) time: 2.6298 data: 0.0058 max mem: 33369 +Epoch: [13] [1050/1319] eta: 0:11:44 lr: 3.4169189347051416e-05 loss: 0.0621 (0.0731) time: 2.6465 data: 0.0059 max mem: 33369 +Epoch: [13] [1060/1319] eta: 0:11:18 lr: 3.416029150683815e-05 loss: 0.0658 (0.0732) time: 2.6517 data: 0.0059 max mem: 33369 +Epoch: [13] [1070/1319] eta: 0:10:52 lr: 3.4151393409100875e-05 loss: 0.0750 (0.0733) time: 2.6114 data: 0.0058 max mem: 33369 +Epoch: [13] [1080/1319] eta: 0:10:26 lr: 3.41424950537576e-05 loss: 0.0816 (0.0736) time: 2.6020 data: 0.0057 max mem: 33369 +Epoch: [13] [1090/1319] eta: 0:09:59 lr: 3.413359644072625e-05 loss: 0.0759 (0.0736) time: 2.6328 data: 0.0058 max mem: 33369 +Epoch: [13] [1100/1319] eta: 0:09:33 lr: 3.412469756992473e-05 loss: 0.0715 (0.0736) time: 2.6503 data: 0.0059 max mem: 33369 +Epoch: [13] [1110/1319] eta: 0:09:07 lr: 3.411579844127087e-05 loss: 0.0722 (0.0736) time: 2.6397 data: 0.0059 max mem: 33369 +Epoch: [13] [1120/1319] eta: 0:08:41 lr: 3.410689905468246e-05 loss: 0.0590 (0.0736) time: 2.6228 data: 0.0058 max mem: 33369 +Epoch: [13] [1130/1319] eta: 0:08:15 lr: 3.409799941007725e-05 loss: 0.0597 (0.0735) time: 2.6310 data: 0.0059 max mem: 33369 +Epoch: [13] [1140/1319] eta: 0:07:49 lr: 3.408909950737292e-05 loss: 0.0695 (0.0736) time: 2.6272 data: 0.0059 max mem: 33369 +Epoch: [13] [1150/1319] eta: 0:07:22 lr: 3.4080199346487104e-05 loss: 0.0695 (0.0736) time: 2.6320 data: 0.0058 max mem: 33369 +Epoch: [13] [1160/1319] eta: 0:06:56 lr: 3.4071298927337405e-05 loss: 0.0686 (0.0737) time: 2.6271 data: 0.0058 max mem: 33369 +Epoch: [13] [1170/1319] eta: 0:06:30 lr: 3.406239824984136e-05 loss: 0.0779 (0.0738) time: 2.6023 data: 0.0057 max mem: 33369 +Epoch: [13] [1180/1319] eta: 0:06:04 lr: 3.405349731391645e-05 loss: 0.0779 (0.0737) time: 2.5863 data: 0.0056 max mem: 33369 +Epoch: [13] [1190/1319] eta: 0:05:37 lr: 3.404459611948011e-05 loss: 0.0702 (0.0737) time: 2.6017 data: 0.0057 max mem: 33369 +Epoch: [13] [1200/1319] eta: 0:05:11 lr: 3.4035694666449745e-05 loss: 0.0662 (0.0737) time: 2.6085 data: 0.0056 max mem: 33369 +Epoch: [13] [1210/1319] eta: 0:04:45 lr: 3.402679295474268e-05 loss: 0.0662 (0.0737) time: 2.5964 data: 0.0056 max mem: 33369 +Epoch: [13] [1220/1319] eta: 0:04:19 lr: 3.401789098427621e-05 loss: 0.0724 (0.0738) time: 2.6048 data: 0.0057 max mem: 33369 +Epoch: [13] [1230/1319] eta: 0:03:53 lr: 3.400898875496756e-05 loss: 0.0682 (0.0738) time: 2.6157 data: 0.0057 max mem: 33369 +Epoch: [13] [1240/1319] eta: 0:03:26 lr: 3.400008626673392e-05 loss: 0.0619 (0.0737) time: 2.6131 data: 0.0056 max mem: 33369 +Epoch: [13] [1250/1319] eta: 0:03:00 lr: 3.399118351949243e-05 loss: 0.0601 (0.0737) time: 2.6143 data: 0.0056 max mem: 33369 +Epoch: [13] [1260/1319] eta: 0:02:34 lr: 3.398228051316017e-05 loss: 0.0698 (0.0737) time: 2.6177 data: 0.0057 max mem: 33369 +Epoch: [13] [1270/1319] eta: 0:02:08 lr: 3.397337724765419e-05 loss: 0.0705 (0.0737) time: 2.5953 data: 0.0056 max mem: 33369 +Epoch: [13] [1280/1319] eta: 0:01:42 lr: 3.396447372289146e-05 loss: 0.0741 (0.0738) time: 2.5898 data: 0.0056 max mem: 33369 +Epoch: [13] [1290/1319] eta: 0:01:15 lr: 3.395556993878891e-05 loss: 0.0688 (0.0738) time: 2.6149 data: 0.0056 max mem: 33369 +Epoch: [13] [1300/1319] eta: 0:00:49 lr: 3.394666589526343e-05 loss: 0.0606 (0.0738) time: 2.6315 data: 0.0057 max mem: 33369 +Epoch: [13] [1310/1319] eta: 0:00:23 lr: 3.393776159223184e-05 loss: 0.0638 (0.0739) time: 2.6370 data: 0.0057 max mem: 33369 +Epoch: [13] Total time: 0:57:34 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 2:37:30 time: 3.6729 data: 3.5944 max mem: 33369 +Test: [ 100/2573] eta: 0:04:25 time: 0.0714 data: 0.0011 max mem: 33369 +Test: [ 200/2573] eta: 0:03:35 time: 0.0730 data: 0.0011 max mem: 33369 +Test: [ 300/2573] eta: 0:03:11 time: 0.0747 data: 0.0011 max mem: 33369 +Test: [ 400/2573] eta: 0:02:57 time: 0.0748 data: 0.0011 max mem: 33369 +Test: [ 500/2573] eta: 0:02:45 time: 0.0734 data: 0.0011 max mem: 33369 +Test: [ 600/2573] eta: 0:02:35 time: 0.0735 data: 0.0011 max mem: 33369 +Test: [ 700/2573] eta: 0:02:27 time: 0.0737 data: 0.0012 max mem: 33369 +Test: [ 800/2573] eta: 0:02:18 time: 0.0771 data: 0.0011 max mem: 33369 +Test: [ 900/2573] eta: 0:02:09 time: 0.0736 data: 0.0012 max mem: 33369 +Test: [1000/2573] eta: 0:02:01 time: 0.0736 data: 0.0012 max mem: 33369 +Test: [1100/2573] eta: 0:01:53 time: 0.0737 data: 0.0012 max mem: 33369 +Test: [1200/2573] eta: 0:01:45 time: 0.0737 data: 0.0011 max mem: 33369 +Test: [1300/2573] eta: 0:01:37 time: 0.0736 data: 0.0011 max mem: 33369 +Test: [1400/2573] eta: 0:01:29 time: 0.0721 data: 0.0011 max mem: 33369 +Test: [1500/2573] eta: 0:01:21 time: 0.0738 data: 0.0012 max mem: 33369 +Test: [1600/2573] eta: 0:01:13 time: 0.0773 data: 0.0012 max mem: 33369 +Test: [1700/2573] eta: 0:01:06 time: 0.0721 data: 0.0011 max mem: 33369 +Test: [1800/2573] eta: 0:00:58 time: 0.0756 data: 0.0012 max mem: 33369 +Test: [1900/2573] eta: 0:00:50 time: 0.0722 data: 0.0011 max mem: 33369 +Test: [2000/2573] eta: 0:00:43 time: 0.0739 data: 0.0011 max mem: 33369 +Test: [2100/2573] eta: 0:00:35 time: 0.0755 data: 0.0011 max mem: 33369 +Test: [2200/2573] eta: 0:00:28 time: 0.0756 data: 0.0011 max mem: 33369 +Test: [2300/2573] eta: 0:00:20 time: 0.0756 data: 0.0012 max mem: 33369 +Test: [2400/2573] eta: 0:00:13 time: 0.0703 data: 0.0011 max mem: 33369 +Test: [2500/2573] eta: 0:00:05 time: 0.0738 data: 0.0011 max mem: 33369 +Test: Total time: 0:03:13 +Final results: +Mean IoU is 60.04 + + precision@0.5 = 67.81 + precision@0.6 = 61.95 + precision@0.7 = 54.11 + precision@0.8 = 41.85 + precision@0.9 = 19.22 + overall IoU = 59.31 + +Average object IoU 60.04073003868471 +Overall IoU 59.307167053222656 +Better epoch: 13 + +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [14] [ 0/1319] eta: 1:27:13 lr: 3.392974749755691e-05 loss: 0.0610 (0.0610) time: 3.9681 data: 1.2536 max mem: 33369 +Epoch: [14] [ 10/1319] eta: 1:00:15 lr: 3.392084270123441e-05 loss: 0.0584 (0.0586) time: 2.7620 data: 0.1194 max mem: 33369 +Epoch: [14] [ 20/1319] eta: 0:58:17 lr: 3.391193764516433e-05 loss: 0.0633 (0.0803) time: 2.6284 data: 0.0058 max mem: 33369 +Epoch: [14] [ 30/1319] eta: 0:57:40 lr: 3.3903032329263314e-05 loss: 0.0748 (0.0794) time: 2.6425 data: 0.0059 max mem: 33369 +Epoch: [14] [ 40/1319] eta: 0:57:01 lr: 3.389412675344791e-05 loss: 0.0694 (0.0784) time: 2.6567 data: 0.0061 max mem: 33369 +Epoch: [14] [ 50/1319] eta: 0:56:31 lr: 3.388522091763468e-05 loss: 0.0665 (0.0787) time: 2.6526 data: 0.0061 max mem: 33369 +Epoch: [14] [ 60/1319] eta: 0:55:57 lr: 3.387631482174009e-05 loss: 0.0695 (0.0772) time: 2.6506 data: 0.0060 max mem: 33369 +Epoch: [14] [ 70/1319] eta: 0:55:20 lr: 3.386740846568057e-05 loss: 0.0590 (0.0747) time: 2.6248 data: 0.0062 max mem: 33369 +Epoch: [14] [ 80/1319] eta: 0:54:45 lr: 3.385850184937249e-05 loss: 0.0644 (0.0755) time: 2.6069 data: 0.0061 max mem: 33369 +Epoch: [14] [ 90/1319] eta: 0:54:13 lr: 3.3849594972732175e-05 loss: 0.0740 (0.0745) time: 2.6075 data: 0.0061 max mem: 33369 +Epoch: [14] [ 100/1319] eta: 0:53:42 lr: 3.38406878356759e-05 loss: 0.0698 (0.0737) time: 2.6092 data: 0.0063 max mem: 33369 +Epoch: [14] [ 110/1319] eta: 0:53:11 lr: 3.3831780438119907e-05 loss: 0.0625 (0.0741) time: 2.6024 data: 0.0061 max mem: 33369 +Epoch: [14] [ 120/1319] eta: 0:52:42 lr: 3.3822872779980336e-05 loss: 0.0641 (0.0737) time: 2.6095 data: 0.0061 max mem: 33369 +Epoch: [14] [ 130/1319] eta: 0:52:17 lr: 3.381396486117332e-05 loss: 0.0641 (0.0735) time: 2.6323 data: 0.0063 max mem: 33369 +Epoch: [14] [ 140/1319] eta: 0:51:50 lr: 3.380505668161494e-05 loss: 0.0667 (0.0734) time: 2.6411 data: 0.0060 max mem: 33369 +Epoch: [14] [ 150/1319] eta: 0:51:21 lr: 3.3796148241221185e-05 loss: 0.0669 (0.0727) time: 2.6175 data: 0.0059 max mem: 33369 +Epoch: [14] [ 160/1319] eta: 0:50:56 lr: 3.378723953990804e-05 loss: 0.0603 (0.0721) time: 2.6252 data: 0.0059 max mem: 33369 +Epoch: [14] [ 170/1319] eta: 0:50:28 lr: 3.3778330577591404e-05 loss: 0.0662 (0.0722) time: 2.6408 data: 0.0058 max mem: 33369 +Epoch: [14] [ 180/1319] eta: 0:49:58 lr: 3.3769421354187145e-05 loss: 0.0662 (0.0718) time: 2.5956 data: 0.0059 max mem: 33369 +Epoch: [14] [ 190/1319] eta: 0:49:30 lr: 3.376051186961107e-05 loss: 0.0642 (0.0717) time: 2.5874 data: 0.0060 max mem: 33369 +Epoch: [14] [ 200/1319] eta: 0:49:02 lr: 3.375160212377894e-05 loss: 0.0702 (0.0720) time: 2.6013 data: 0.0061 max mem: 33369 +Epoch: [14] [ 210/1319] eta: 0:48:33 lr: 3.374269211660646e-05 loss: 0.0615 (0.0714) time: 2.5938 data: 0.0061 max mem: 33369 +Epoch: [14] [ 220/1319] eta: 0:48:07 lr: 3.373378184800928e-05 loss: 0.0592 (0.0708) time: 2.6106 data: 0.0060 max mem: 33369 +Epoch: [14] [ 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33369 +Epoch: [14] [ 310/1319] eta: 0:44:06 lr: 3.365357765258022e-05 loss: 0.0603 (0.0686) time: 2.6064 data: 0.0064 max mem: 33369 +Epoch: [14] [ 320/1319] eta: 0:43:42 lr: 3.364466476508552e-05 loss: 0.0586 (0.0684) time: 2.6369 data: 0.0062 max mem: 33369 +Epoch: [14] [ 330/1319] eta: 0:43:17 lr: 3.363575161523487e-05 loss: 0.0577 (0.0681) time: 2.6714 data: 0.0060 max mem: 33369 +Epoch: [14] [ 340/1319] eta: 0:42:48 lr: 3.362683820294329e-05 loss: 0.0623 (0.0682) time: 2.5947 data: 0.0061 max mem: 33369 +Epoch: [14] [ 350/1319] eta: 0:42:22 lr: 3.361792452812576e-05 loss: 0.0692 (0.0682) time: 2.5835 data: 0.0064 max mem: 33369 +Epoch: [14] [ 360/1319] eta: 0:41:56 lr: 3.36090105906972e-05 loss: 0.0698 (0.0684) time: 2.6386 data: 0.0063 max mem: 33369 +Epoch: [14] [ 370/1319] eta: 0:41:30 lr: 3.3600096390572475e-05 loss: 0.0700 (0.0685) time: 2.6392 data: 0.0061 max mem: 33369 +Epoch: [14] [ 380/1319] eta: 0:41:02 lr: 3.3591181927666404e-05 loss: 0.0627 (0.0682) time: 2.5984 data: 0.0061 max mem: 33369 +Epoch: [14] [ 390/1319] eta: 0:40:36 lr: 3.358226720189375e-05 loss: 0.0543 (0.0680) time: 2.5947 data: 0.0062 max mem: 33369 +Epoch: [14] [ 400/1319] eta: 0:40:10 lr: 3.357335221316921e-05 loss: 0.0544 (0.0683) time: 2.6235 data: 0.0062 max mem: 33369 +Epoch: [14] [ 410/1319] eta: 0:39:43 lr: 3.3564436961407466e-05 loss: 0.0696 (0.0685) time: 2.6070 data: 0.0060 max mem: 33369 +Epoch: [14] [ 420/1319] eta: 0:39:17 lr: 3.35555214465231e-05 loss: 0.0733 (0.0690) time: 2.6059 data: 0.0060 max mem: 33369 +Epoch: [14] [ 430/1319] eta: 0:38:50 lr: 3.354660566843068e-05 loss: 0.0733 (0.0690) time: 2.6150 data: 0.0063 max mem: 33369 +Epoch: [14] [ 440/1319] eta: 0:38:23 lr: 3.353768962704469e-05 loss: 0.0591 (0.0689) time: 2.5953 data: 0.0062 max mem: 33369 +Epoch: [14] [ 450/1319] eta: 0:37:57 lr: 3.352877332227959e-05 loss: 0.0572 (0.0687) time: 2.5880 data: 0.0059 max mem: 33369 +Epoch: [14] [ 460/1319] eta: 0:37:30 lr: 3.351985675404978e-05 loss: 0.0620 (0.0688) time: 2.6001 data: 0.0059 max mem: 33369 +Epoch: [14] [ 470/1319] eta: 0:37:04 lr: 3.3510939922269576e-05 loss: 0.0712 (0.0689) time: 2.6213 data: 0.0060 max mem: 33369 +Epoch: [14] [ 480/1319] eta: 0:36:37 lr: 3.350202282685327e-05 loss: 0.0739 (0.0695) time: 2.6157 data: 0.0060 max mem: 33369 +Epoch: [14] [ 490/1319] eta: 0:36:12 lr: 3.34931054677151e-05 loss: 0.0688 (0.0694) time: 2.6138 data: 0.0060 max mem: 33369 +Epoch: [14] [ 500/1319] eta: 0:35:45 lr: 3.3484187844769246e-05 loss: 0.0558 (0.0692) time: 2.6241 data: 0.0060 max mem: 33369 +Epoch: [14] [ 510/1319] eta: 0:35:19 lr: 3.347526995792984e-05 loss: 0.0617 (0.0693) time: 2.6287 data: 0.0059 max mem: 33369 +Epoch: [14] [ 520/1319] eta: 0:34:53 lr: 3.346635180711094e-05 loss: 0.0647 (0.0692) time: 2.6367 data: 0.0059 max mem: 33369 +Epoch: [14] [ 530/1319] eta: 0:34:27 lr: 3.3457433392226575e-05 loss: 0.0588 (0.0690) time: 2.6131 data: 0.0061 max mem: 33369 +Epoch: [14] [ 540/1319] eta: 0:34:00 lr: 3.344851471319071e-05 loss: 0.0588 (0.0691) time: 2.5962 data: 0.0060 max mem: 33369 +Epoch: [14] [ 550/1319] eta: 0:33:34 lr: 3.343959576991726e-05 loss: 0.0638 (0.0690) time: 2.5908 data: 0.0058 max mem: 33369 +Epoch: [14] [ 560/1319] eta: 0:33:07 lr: 3.343067656232008e-05 loss: 0.0555 (0.0687) time: 2.6043 data: 0.0058 max mem: 33369 +Epoch: [14] [ 570/1319] eta: 0:32:41 lr: 3.342175709031298e-05 loss: 0.0568 (0.0687) time: 2.6268 data: 0.0059 max mem: 33369 +Epoch: [14] [ 580/1319] eta: 0:32:15 lr: 3.341283735380971e-05 loss: 0.0713 (0.0689) time: 2.6329 data: 0.0058 max mem: 33369 +Epoch: [14] [ 590/1319] eta: 0:31:49 lr: 3.3403917352723954e-05 loss: 0.0716 (0.0689) time: 2.6123 data: 0.0059 max mem: 33369 +Epoch: [14] [ 600/1319] eta: 0:31:23 lr: 3.339499708696938e-05 loss: 0.0669 (0.0689) time: 2.5990 data: 0.0060 max mem: 33369 +Epoch: [14] [ 610/1319] eta: 0:30:56 lr: 3.3386076556459565e-05 loss: 0.0821 (0.0693) time: 2.6184 data: 0.0059 max mem: 33369 +Epoch: [14] [ 620/1319] eta: 0:30:30 lr: 3.337715576110804e-05 loss: 0.0616 (0.0691) time: 2.6130 data: 0.0060 max mem: 33369 +Epoch: [14] [ 630/1319] eta: 0:30:04 lr: 3.336823470082831e-05 loss: 0.0580 (0.0690) time: 2.6197 data: 0.0059 max mem: 33369 +Epoch: [14] [ 640/1319] eta: 0:29:38 lr: 3.335931337553377e-05 loss: 0.0586 (0.0689) time: 2.6334 data: 0.0057 max mem: 33369 +Epoch: [14] [ 650/1319] eta: 0:29:12 lr: 3.3350391785137824e-05 loss: 0.0665 (0.0693) time: 2.6266 data: 0.0058 max mem: 33369 +Epoch: [14] [ 660/1319] eta: 0:28:45 lr: 3.334146992955378e-05 loss: 0.0659 (0.0693) time: 2.5973 data: 0.0059 max mem: 33369 +Epoch: [14] [ 670/1319] eta: 0:28:19 lr: 3.33325478086949e-05 loss: 0.0659 (0.0697) time: 2.6096 data: 0.0060 max mem: 33369 +Epoch: [14] [ 680/1319] eta: 0:27:53 lr: 3.332362542247442e-05 loss: 0.0675 (0.0696) time: 2.6322 data: 0.0060 max mem: 33369 +Epoch: [14] [ 690/1319] eta: 0:27:27 lr: 3.3314702770805464e-05 loss: 0.0658 (0.0698) time: 2.6114 data: 0.0059 max mem: 33369 +Epoch: [14] [ 700/1319] eta: 0:27:01 lr: 3.330577985360116e-05 loss: 0.0667 (0.0698) time: 2.6187 data: 0.0059 max mem: 33369 +Epoch: [14] [ 710/1319] eta: 0:26:34 lr: 3.329685667077455e-05 loss: 0.0623 (0.0697) time: 2.6164 data: 0.0060 max mem: 33369 +Epoch: [14] [ 720/1319] eta: 0:26:08 lr: 3.3287933222238623e-05 loss: 0.0602 (0.0697) time: 2.5999 data: 0.0060 max mem: 33369 +Epoch: [14] [ 730/1319] eta: 0:25:42 lr: 3.327900950790632e-05 loss: 0.0602 (0.0697) time: 2.5994 data: 0.0059 max mem: 33369 +Epoch: [14] [ 740/1319] eta: 0:25:15 lr: 3.327008552769054e-05 loss: 0.0556 (0.0697) time: 2.6084 data: 0.0060 max mem: 33369 +Epoch: [14] [ 750/1319] eta: 0:24:49 lr: 3.32611612815041e-05 loss: 0.0602 (0.0697) time: 2.6209 data: 0.0061 max mem: 33369 +Epoch: [14] [ 760/1319] eta: 0:24:23 lr: 3.325223676925979e-05 loss: 0.0525 (0.0695) time: 2.6235 data: 0.0059 max mem: 33369 +Epoch: [14] [ 770/1319] eta: 0:23:57 lr: 3.324331199087032e-05 loss: 0.0549 (0.0697) time: 2.6036 data: 0.0057 max mem: 33369 +Epoch: [14] [ 780/1319] eta: 0:23:31 lr: 3.323438694624837e-05 loss: 0.0679 (0.0699) time: 2.6174 data: 0.0059 max mem: 33369 +Epoch: [14] [ 790/1319] eta: 0:23:05 lr: 3.322546163530654e-05 loss: 0.0570 (0.0697) time: 2.6383 data: 0.0058 max mem: 33369 +Epoch: [14] [ 800/1319] eta: 0:22:38 lr: 3.32165360579574e-05 loss: 0.0633 (0.0698) time: 2.6216 data: 0.0058 max mem: 33369 +Epoch: [14] [ 810/1319] eta: 0:22:12 lr: 3.320761021411345e-05 loss: 0.0713 (0.0699) time: 2.5996 data: 0.0058 max mem: 33369 +Epoch: [14] [ 820/1319] eta: 0:21:46 lr: 3.3198684103687127e-05 loss: 0.0754 (0.0700) time: 2.6052 data: 0.0058 max mem: 33369 +Epoch: [14] [ 830/1319] eta: 0:21:20 lr: 3.318975772659084e-05 loss: 0.0723 (0.0701) time: 2.6181 data: 0.0059 max mem: 33369 +Epoch: [14] [ 840/1319] eta: 0:20:54 lr: 3.3180831082736915e-05 loss: 0.0586 (0.0699) time: 2.6177 data: 0.0061 max mem: 33369 +Epoch: [14] [ 850/1319] eta: 0:20:27 lr: 3.3171904172037654e-05 loss: 0.0528 (0.0698) time: 2.6099 data: 0.0061 max mem: 33369 +Epoch: [14] [ 860/1319] eta: 0:20:01 lr: 3.3162976994405264e-05 loss: 0.0610 (0.0698) time: 2.6035 data: 0.0060 max mem: 33369 +Epoch: [14] [ 870/1319] eta: 0:19:35 lr: 3.315404954975194e-05 loss: 0.0610 (0.0699) time: 2.6089 data: 0.0059 max mem: 33369 +Epoch: [14] [ 880/1319] eta: 0:19:09 lr: 3.314512183798977e-05 loss: 0.0595 (0.0699) time: 2.6038 data: 0.0058 max mem: 33369 +Epoch: [14] [ 890/1319] eta: 0:18:42 lr: 3.3136193859030854e-05 loss: 0.0615 (0.0699) time: 2.5986 data: 0.0058 max mem: 33369 +Epoch: [14] [ 900/1319] eta: 0:18:16 lr: 3.312726561278717e-05 loss: 0.0615 (0.0699) time: 2.6050 data: 0.0059 max mem: 33369 +Epoch: [14] [ 910/1319] eta: 0:17:50 lr: 3.311833709917069e-05 loss: 0.0687 (0.0700) time: 2.6162 data: 0.0061 max mem: 33369 +Epoch: [14] [ 920/1319] eta: 0:17:24 lr: 3.3109408318093296e-05 loss: 0.0639 (0.0700) time: 2.6162 data: 0.0061 max mem: 33369 +Epoch: [14] [ 930/1319] eta: 0:16:57 lr: 3.310047926946684e-05 loss: 0.0604 (0.0699) time: 2.5923 data: 0.0059 max mem: 33369 +Epoch: [14] [ 940/1319] eta: 0:16:31 lr: 3.309154995320309e-05 loss: 0.0664 (0.0699) time: 2.5788 data: 0.0060 max mem: 33369 +Epoch: [14] [ 950/1319] eta: 0:16:05 lr: 3.308262036921381e-05 loss: 0.0694 (0.0699) time: 2.5931 data: 0.0059 max mem: 33369 +Epoch: [14] [ 960/1319] eta: 0:15:39 lr: 3.307369051741064e-05 loss: 0.0694 (0.0701) time: 2.6073 data: 0.0057 max mem: 33369 +Epoch: [14] [ 970/1319] eta: 0:15:13 lr: 3.306476039770522e-05 loss: 0.0601 (0.0700) time: 2.6187 data: 0.0059 max mem: 33369 +Epoch: [14] [ 980/1319] eta: 0:14:46 lr: 3.30558300100091e-05 loss: 0.0662 (0.0702) time: 2.6201 data: 0.0059 max mem: 33369 +Epoch: [14] [ 990/1319] eta: 0:14:20 lr: 3.30468993542338e-05 loss: 0.0662 (0.0701) time: 2.5954 data: 0.0057 max mem: 33369 +Epoch: [14] [1000/1319] eta: 0:13:54 lr: 3.3037968430290776e-05 loss: 0.0618 (0.0700) time: 2.6143 data: 0.0057 max mem: 33369 +Epoch: [14] [1010/1319] eta: 0:13:28 lr: 3.3029037238091407e-05 loss: 0.0672 (0.0701) time: 2.6273 data: 0.0060 max mem: 33369 +Epoch: [14] [1020/1319] eta: 0:13:02 lr: 3.3020105777547046e-05 loss: 0.0704 (0.0701) time: 2.6124 data: 0.0061 max mem: 33369 +Epoch: [14] [1030/1319] eta: 0:12:36 lr: 3.301117404856897e-05 loss: 0.0582 (0.0700) time: 2.6266 data: 0.0058 max mem: 33369 +Epoch: [14] [1040/1319] eta: 0:12:10 lr: 3.300224205106842e-05 loss: 0.0580 (0.0700) time: 2.6425 data: 0.0058 max mem: 33369 +Epoch: [14] [1050/1319] eta: 0:11:43 lr: 3.2993309784956545e-05 loss: 0.0652 (0.0700) time: 2.6346 data: 0.0058 max mem: 33369 +Epoch: [14] [1060/1319] eta: 0:11:17 lr: 3.298437725014447e-05 loss: 0.0615 (0.0700) time: 2.6098 data: 0.0060 max mem: 33369 +Epoch: [14] [1070/1319] eta: 0:10:51 lr: 3.297544444654327e-05 loss: 0.0539 (0.0700) time: 2.6113 data: 0.0060 max mem: 33369 +Epoch: [14] [1080/1319] eta: 0:10:25 lr: 3.296651137406393e-05 loss: 0.0530 (0.0699) time: 2.5938 data: 0.0059 max mem: 33369 +Epoch: [14] [1090/1319] eta: 0:09:59 lr: 3.2957578032617413e-05 loss: 0.0578 (0.0699) time: 2.5831 data: 0.0059 max mem: 33369 +Epoch: [14] [1100/1319] eta: 0:09:32 lr: 3.29486444221146e-05 loss: 0.0608 (0.0699) time: 2.6077 data: 0.0059 max mem: 33369 +Epoch: [14] [1110/1319] eta: 0:09:06 lr: 3.293971054246633e-05 loss: 0.0623 (0.0699) time: 2.6105 data: 0.0059 max mem: 33369 +Epoch: [14] [1120/1319] eta: 0:08:40 lr: 3.293077639358339e-05 loss: 0.0662 (0.0698) time: 2.5932 data: 0.0057 max mem: 33369 +Epoch: [14] [1130/1319] eta: 0:08:14 lr: 3.2921841975376476e-05 loss: 0.0735 (0.0699) time: 2.5893 data: 0.0056 max mem: 33369 +Epoch: [14] [1140/1319] eta: 0:07:48 lr: 3.291290728775627e-05 loss: 0.0637 (0.0698) time: 2.6095 data: 0.0057 max mem: 33369 +Epoch: [14] [1150/1319] eta: 0:07:21 lr: 3.290397233063338e-05 loss: 0.0622 (0.0698) time: 2.6125 data: 0.0058 max mem: 33369 +Epoch: [14] [1160/1319] eta: 0:06:55 lr: 3.2895037103918356e-05 loss: 0.0640 (0.0698) time: 2.6108 data: 0.0058 max mem: 33369 +Epoch: [14] [1170/1319] eta: 0:06:29 lr: 3.2886101607521696e-05 loss: 0.0706 (0.0699) time: 2.6283 data: 0.0058 max mem: 33369 +Epoch: [14] [1180/1319] eta: 0:06:03 lr: 3.287716584135384e-05 loss: 0.0678 (0.0699) time: 2.6394 data: 0.0059 max mem: 33369 +Epoch: [14] [1190/1319] eta: 0:05:37 lr: 3.286822980532516e-05 loss: 0.0620 (0.0701) time: 2.6245 data: 0.0059 max mem: 33369 +Epoch: [14] [1200/1319] eta: 0:05:11 lr: 3.285929349934599e-05 loss: 0.0622 (0.0700) time: 2.6276 data: 0.0058 max mem: 33369 +Epoch: [14] [1210/1319] eta: 0:04:45 lr: 3.28503569233266e-05 loss: 0.0616 (0.0700) time: 2.6373 data: 0.0058 max mem: 33369 +Epoch: [14] [1220/1319] eta: 0:04:18 lr: 3.284142007717719e-05 loss: 0.0672 (0.0700) time: 2.6047 data: 0.0059 max mem: 33369 +Epoch: [14] [1230/1319] eta: 0:03:52 lr: 3.283248296080793e-05 loss: 0.0657 (0.0699) time: 2.6196 data: 0.0059 max mem: 33369 +Epoch: [14] [1240/1319] eta: 0:03:26 lr: 3.2823545574128904e-05 loss: 0.0599 (0.0699) time: 2.6328 data: 0.0057 max mem: 33369 +Epoch: [14] [1250/1319] eta: 0:03:00 lr: 3.2814607917050156e-05 loss: 0.0599 (0.0699) time: 2.6109 data: 0.0058 max mem: 33369 +Epoch: [14] [1260/1319] eta: 0:02:34 lr: 3.280566998948166e-05 loss: 0.0620 (0.0699) time: 2.6134 data: 0.0058 max mem: 33369 +Epoch: [14] [1270/1319] eta: 0:02:08 lr: 3.2796731791333364e-05 loss: 0.0631 (0.0700) time: 2.6233 data: 0.0057 max mem: 33369 +Epoch: [14] [1280/1319] eta: 0:01:42 lr: 3.278779332251511e-05 loss: 0.0647 (0.0700) time: 2.6301 data: 0.0060 max mem: 33369 +Epoch: [14] [1290/1319] eta: 0:01:15 lr: 3.277885458293673e-05 loss: 0.0637 (0.0700) time: 2.6172 data: 0.0060 max mem: 33369 +Epoch: [14] [1300/1319] eta: 0:00:49 lr: 3.276991557250796e-05 loss: 0.0586 (0.0701) time: 2.5986 data: 0.0058 max mem: 33369 +Epoch: [14] [1310/1319] eta: 0:00:23 lr: 3.276097629113851e-05 loss: 0.0737 (0.0701) time: 2.6047 data: 0.0056 max mem: 33369 +Epoch: [14] Total time: 0:57:30 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 2:22:08 time: 3.3145 data: 3.2355 max mem: 33369 +Test: [ 100/2573] eta: 0:04:17 time: 0.0714 data: 0.0011 max mem: 33369 +Test: [ 200/2573] eta: 0:03:31 time: 0.0731 data: 0.0011 max mem: 33369 +Test: [ 300/2573] eta: 0:03:09 time: 0.0748 data: 0.0011 max mem: 33369 +Test: [ 400/2573] eta: 0:02:55 time: 0.0751 data: 0.0011 max mem: 33369 +Test: [ 500/2573] eta: 0:02:44 time: 0.0733 data: 0.0011 max mem: 33369 +Test: [ 600/2573] eta: 0:02:34 time: 0.0734 data: 0.0011 max mem: 33369 +Test: [ 700/2573] eta: 0:02:26 time: 0.0735 data: 0.0011 max mem: 33369 +Test: [ 800/2573] eta: 0:02:17 time: 0.0767 data: 0.0011 max mem: 33369 +Test: [ 900/2573] eta: 0:02:09 time: 0.0735 data: 0.0011 max mem: 33369 +Test: [1000/2573] eta: 0:02:00 time: 0.0736 data: 0.0011 max mem: 33369 +Test: [1100/2573] eta: 0:01:52 time: 0.0736 data: 0.0011 max mem: 33369 +Test: [1200/2573] eta: 0:01:44 time: 0.0736 data: 0.0011 max mem: 33369 +Test: [1300/2573] eta: 0:01:37 time: 0.0737 data: 0.0011 max mem: 33369 +Test: [1400/2573] eta: 0:01:29 time: 0.0722 data: 0.0011 max mem: 33369 +Test: [1500/2573] eta: 0:01:21 time: 0.0738 data: 0.0011 max mem: 33369 +Test: [1600/2573] eta: 0:01:13 time: 0.0772 data: 0.0011 max mem: 33369 +Test: [1700/2573] eta: 0:01:06 time: 0.0722 data: 0.0011 max mem: 33369 +Test: [1800/2573] eta: 0:00:58 time: 0.0756 data: 0.0011 max mem: 33369 +Test: [1900/2573] eta: 0:00:50 time: 0.0724 data: 0.0011 max mem: 33369 +Test: [2000/2573] eta: 0:00:43 time: 0.0741 data: 0.0011 max mem: 33369 +Test: [2100/2573] eta: 0:00:35 time: 0.0758 data: 0.0011 max mem: 33369 +Test: [2200/2573] eta: 0:00:28 time: 0.0757 data: 0.0011 max mem: 33369 +Test: [2300/2573] eta: 0:00:20 time: 0.0757 data: 0.0011 max mem: 33369 +Test: [2400/2573] eta: 0:00:12 time: 0.0707 data: 0.0011 max mem: 33369 +Test: [2500/2573] eta: 0:00:05 time: 0.0741 data: 0.0012 max mem: 33369 +Test: Total time: 0:03:13 +Final results: +Mean IoU is 61.28 + + precision@0.5 = 69.12 + precision@0.6 = 63.13 + precision@0.7 = 55.70 + precision@0.8 = 43.57 + precision@0.9 = 20.92 + overall IoU = 59.40 + +Average object IoU 61.28247470731858 +Overall IoU 59.40028381347656 +Better epoch: 14 + +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [15] [ 0/1319] eta: 1:32:11 lr: 3.275293070617704e-05 loss: 0.2561 (0.2561) time: 4.1940 data: 1.4087 max mem: 33369 +Epoch: [15] [ 10/1319] eta: 1:00:36 lr: 3.274399090977129e-05 loss: 0.0565 (0.0838) time: 2.7781 data: 0.1329 max mem: 33369 +Epoch: [15] [ 20/1319] eta: 0:58:31 lr: 3.2735050842162644e-05 loss: 0.0588 (0.0820) time: 2.6287 data: 0.0055 max mem: 33369 +Epoch: [15] [ 30/1319] eta: 0:57:17 lr: 3.2726110503260586e-05 loss: 0.0598 (0.0793) time: 2.6057 data: 0.0061 max mem: 33369 +Epoch: [15] [ 40/1319] eta: 0:56:42 lr: 3.271716989297451e-05 loss: 0.0500 (0.0714) time: 2.6149 data: 0.0065 max mem: 33369 +Epoch: [15] [ 50/1319] eta: 0:56:05 lr: 3.2708229011213794e-05 loss: 0.0475 (0.0687) time: 2.6295 data: 0.0066 max mem: 33369 +Epoch: [15] [ 60/1319] eta: 0:55:33 lr: 3.269928785788772e-05 loss: 0.0593 (0.0701) time: 2.6223 data: 0.0065 max mem: 33369 +Epoch: [15] [ 70/1319] eta: 0:54:59 lr: 3.2690346432905536e-05 loss: 0.0664 (0.0697) time: 2.6159 data: 0.0064 max mem: 33369 +Epoch: [15] [ 80/1319] eta: 0:54:29 lr: 3.268140473617642e-05 loss: 0.0664 (0.0690) time: 2.6131 data: 0.0064 max mem: 33369 +Epoch: [15] [ 90/1319] eta: 0:53:59 lr: 3.26724627676095e-05 loss: 0.0651 (0.0685) time: 2.6128 data: 0.0064 max mem: 33369 +Epoch: [15] [ 100/1319] eta: 0:53:29 lr: 3.266352052711384e-05 loss: 0.0566 (0.0696) time: 2.6076 data: 0.0061 max mem: 33369 +Epoch: [15] [ 110/1319] eta: 0:53:02 lr: 3.265457801459844e-05 loss: 0.0578 (0.0687) time: 2.6186 data: 0.0061 max mem: 33369 +Epoch: [15] [ 120/1319] eta: 0:52:38 lr: 3.2645635229972264e-05 loss: 0.0610 (0.0682) time: 2.6431 data: 0.0062 max mem: 33369 +Epoch: [15] [ 130/1319] eta: 0:52:15 lr: 3.2636692173144204e-05 loss: 0.0628 (0.0691) time: 2.6644 data: 0.0062 max mem: 33369 +Epoch: [15] [ 140/1319] eta: 0:51:48 lr: 3.2627748844023084e-05 loss: 0.0623 (0.0686) time: 2.6501 data: 0.0062 max mem: 33369 +Epoch: [15] [ 150/1319] eta: 0:51:19 lr: 3.261880524251768e-05 loss: 0.0614 (0.0685) time: 2.6124 data: 0.0062 max mem: 33369 +Epoch: [15] [ 160/1319] eta: 0:50:51 lr: 3.260986136853672e-05 loss: 0.0703 (0.0689) time: 2.6070 data: 0.0063 max mem: 33369 +Epoch: [15] [ 170/1319] eta: 0:50:26 lr: 3.2600917221988844e-05 loss: 0.0703 (0.0689) time: 2.6331 data: 0.0062 max mem: 33369 +Epoch: [15] [ 180/1319] eta: 0:50:00 lr: 3.259197280278268e-05 loss: 0.0619 (0.0685) time: 2.6465 data: 0.0060 max mem: 33369 +Epoch: [15] [ 190/1319] eta: 0:49:33 lr: 3.258302811082674e-05 loss: 0.0583 (0.0681) time: 2.6324 data: 0.0060 max mem: 33369 +Epoch: [15] [ 200/1319] eta: 0:49:04 lr: 3.257408314602953e-05 loss: 0.0496 (0.0679) time: 2.6019 data: 0.0061 max mem: 33369 +Epoch: [15] [ 210/1319] eta: 0:48:35 lr: 3.2565137908299456e-05 loss: 0.0699 (0.0685) time: 2.5861 data: 0.0063 max mem: 33369 +Epoch: [15] [ 220/1319] eta: 0:48:07 lr: 3.25561923975449e-05 loss: 0.0689 (0.0683) time: 2.5893 data: 0.0064 max mem: 33369 +Epoch: [15] [ 230/1319] eta: 0:47:42 lr: 3.2547246613674155e-05 loss: 0.0584 (0.0681) time: 2.6186 data: 0.0062 max mem: 33369 +Epoch: [15] [ 240/1319] eta: 0:47:15 lr: 3.253830055659547e-05 loss: 0.0612 (0.0678) time: 2.6330 data: 0.0060 max mem: 33369 +Epoch: [15] [ 250/1319] eta: 0:46:49 lr: 3.252935422621704e-05 loss: 0.0495 (0.0674) time: 2.6308 data: 0.0060 max mem: 33369 +Epoch: [15] [ 260/1319] eta: 0:46:22 lr: 3.252040762244701e-05 loss: 0.0495 (0.0669) time: 2.6231 data: 0.0060 max mem: 33369 +Epoch: [15] [ 270/1319] eta: 0:45:56 lr: 3.251146074519342e-05 loss: 0.0499 (0.0671) time: 2.6194 data: 0.0062 max mem: 33369 +Epoch: [15] [ 280/1319] eta: 0:45:29 lr: 3.2502513594364305e-05 loss: 0.0670 (0.0672) time: 2.6159 data: 0.0061 max mem: 33369 +Epoch: [15] [ 290/1319] eta: 0:45:05 lr: 3.2493566169867616e-05 loss: 0.0673 (0.0671) time: 2.6443 data: 0.0060 max mem: 33369 +Epoch: [15] [ 300/1319] eta: 0:44:39 lr: 3.248461847161124e-05 loss: 0.0622 (0.0670) time: 2.6630 data: 0.0060 max mem: 33369 +Epoch: [15] [ 310/1319] eta: 0:44:10 lr: 3.247567049950301e-05 loss: 0.0552 (0.0668) time: 2.6025 data: 0.0059 max mem: 33369 +Epoch: [15] [ 320/1319] eta: 0:43:45 lr: 3.246672225345071e-05 loss: 0.0552 (0.0672) time: 2.6104 data: 0.0058 max mem: 33369 +Epoch: [15] [ 330/1319] eta: 0:43:18 lr: 3.245777373336205e-05 loss: 0.0605 (0.0669) time: 2.6308 data: 0.0059 max mem: 33369 +Epoch: [15] [ 340/1319] eta: 0:42:52 lr: 3.244882493914469e-05 loss: 0.0554 (0.0667) time: 2.6148 data: 0.0058 max mem: 33369 +Epoch: [15] [ 350/1319] eta: 0:42:24 lr: 3.243987587070623e-05 loss: 0.0552 (0.0667) time: 2.5963 data: 0.0060 max mem: 33369 +Epoch: [15] [ 360/1319] eta: 0:41:56 lr: 3.24309265279542e-05 loss: 0.0557 (0.0668) time: 2.5757 data: 0.0059 max mem: 33369 +Epoch: [15] [ 370/1319] eta: 0:41:30 lr: 3.2421976910796087e-05 loss: 0.0557 (0.0666) time: 2.6017 data: 0.0058 max mem: 33369 +Epoch: [15] [ 380/1319] eta: 0:41:03 lr: 3.24130270191393e-05 loss: 0.0510 (0.0664) time: 2.6089 data: 0.0060 max mem: 33369 +Epoch: [15] [ 390/1319] eta: 0:40:37 lr: 3.2404076852891215e-05 loss: 0.0510 (0.0665) time: 2.6052 data: 0.0061 max mem: 33369 +Epoch: [15] [ 400/1319] eta: 0:40:12 lr: 3.239512641195912e-05 loss: 0.0676 (0.0666) time: 2.6514 data: 0.0063 max mem: 33369 +Epoch: [15] [ 410/1319] eta: 0:39:45 lr: 3.238617569625025e-05 loss: 0.0685 (0.0667) time: 2.6343 data: 0.0064 max mem: 33369 +Epoch: [15] [ 420/1319] eta: 0:39:19 lr: 3.23772247056718e-05 loss: 0.0558 (0.0666) time: 2.6265 data: 0.0062 max mem: 33369 +Epoch: [15] [ 430/1319] eta: 0:38:53 lr: 3.2368273440130875e-05 loss: 0.0573 (0.0666) time: 2.6357 data: 0.0062 max mem: 33369 +Epoch: [15] [ 440/1319] eta: 0:38:27 lr: 3.235932189953454e-05 loss: 0.0509 (0.0661) time: 2.6259 data: 0.0062 max mem: 33369 +Epoch: [15] [ 450/1319] eta: 0:38:01 lr: 3.23503700837898e-05 loss: 0.0508 (0.0661) time: 2.6354 data: 0.0062 max mem: 33369 +Epoch: [15] [ 460/1319] eta: 0:37:34 lr: 3.234141799280359e-05 loss: 0.0552 (0.0660) time: 2.6054 data: 0.0062 max mem: 33369 +Epoch: [15] [ 470/1319] eta: 0:37:07 lr: 3.2332465626482786e-05 loss: 0.0575 (0.0660) time: 2.6038 data: 0.0061 max mem: 33369 +Epoch: [15] [ 480/1319] eta: 0:36:41 lr: 3.232351298473422e-05 loss: 0.0602 (0.0660) time: 2.6105 data: 0.0058 max mem: 33369 +Epoch: [15] [ 490/1319] eta: 0:36:15 lr: 3.231456006746465e-05 loss: 0.0602 (0.0660) time: 2.6174 data: 0.0057 max mem: 33369 +Epoch: [15] [ 500/1319] eta: 0:35:49 lr: 3.2305606874580764e-05 loss: 0.0542 (0.0658) time: 2.6363 data: 0.0060 max mem: 33369 +Epoch: [15] [ 510/1319] eta: 0:35:22 lr: 3.229665340598921e-05 loss: 0.0546 (0.0659) time: 2.6299 data: 0.0060 max mem: 33369 +Epoch: [15] [ 520/1319] eta: 0:34:55 lr: 3.228769966159657e-05 loss: 0.0674 (0.0662) time: 2.5999 data: 0.0059 max mem: 33369 +Epoch: [15] [ 530/1319] eta: 0:34:29 lr: 3.227874564130935e-05 loss: 0.0729 (0.0668) time: 2.6100 data: 0.0059 max mem: 33369 +Epoch: [15] [ 540/1319] eta: 0:34:03 lr: 3.2269791345034015e-05 loss: 0.0641 (0.0667) time: 2.6280 data: 0.0060 max mem: 33369 +Epoch: [15] [ 550/1319] eta: 0:33:36 lr: 3.226083677267696e-05 loss: 0.0628 (0.0668) time: 2.5995 data: 0.0060 max mem: 33369 +Epoch: [15] [ 560/1319] eta: 0:33:10 lr: 3.225188192414452e-05 loss: 0.0550 (0.0667) time: 2.5884 data: 0.0058 max mem: 33369 +Epoch: [15] [ 570/1319] eta: 0:32:43 lr: 3.224292679934298e-05 loss: 0.0564 (0.0667) time: 2.5893 data: 0.0059 max mem: 33369 +Epoch: [15] [ 580/1319] eta: 0:32:17 lr: 3.2233971398178544e-05 loss: 0.0564 (0.0669) time: 2.6298 data: 0.0060 max mem: 33369 +Epoch: [15] [ 590/1319] eta: 0:31:51 lr: 3.2225015720557374e-05 loss: 0.0560 (0.0670) time: 2.6520 data: 0.0057 max mem: 33369 +Epoch: [15] [ 600/1319] eta: 0:31:25 lr: 3.221605976638556e-05 loss: 0.0596 (0.0673) time: 2.6263 data: 0.0058 max mem: 33369 +Epoch: [15] [ 610/1319] eta: 0:30:59 lr: 3.2207103535569134e-05 loss: 0.0646 (0.0674) time: 2.6112 data: 0.0059 max mem: 33369 +Epoch: [15] [ 620/1319] eta: 0:30:33 lr: 3.219814702801407e-05 loss: 0.0699 (0.0676) time: 2.6185 data: 0.0059 max mem: 33369 +Epoch: [15] [ 630/1319] eta: 0:30:07 lr: 3.218919024362627e-05 loss: 0.0681 (0.0677) time: 2.6475 data: 0.0060 max mem: 33369 +Epoch: [15] [ 640/1319] eta: 0:29:40 lr: 3.21802331823116e-05 loss: 0.0505 (0.0675) time: 2.6365 data: 0.0059 max mem: 33369 +Epoch: [15] [ 650/1319] eta: 0:29:14 lr: 3.2171275843975836e-05 loss: 0.0505 (0.0674) time: 2.6218 data: 0.0059 max mem: 33369 +Epoch: [15] [ 660/1319] eta: 0:28:48 lr: 3.21623182285247e-05 loss: 0.0540 (0.0673) time: 2.6069 data: 0.0059 max mem: 33369 +Epoch: [15] [ 670/1319] eta: 0:28:21 lr: 3.215336033586388e-05 loss: 0.0540 (0.0673) time: 2.5864 data: 0.0058 max mem: 33369 +Epoch: [15] [ 680/1319] eta: 0:27:55 lr: 3.214440216589895e-05 loss: 0.0526 (0.0675) time: 2.5916 data: 0.0059 max mem: 33369 +Epoch: [15] [ 690/1319] eta: 0:27:28 lr: 3.2135443718535476e-05 loss: 0.0519 (0.0674) time: 2.6076 data: 0.0059 max mem: 33369 +Epoch: [15] [ 700/1319] eta: 0:27:02 lr: 3.212648499367893e-05 loss: 0.0567 (0.0674) time: 2.6154 data: 0.0059 max mem: 33369 +Epoch: [15] [ 710/1319] eta: 0:26:36 lr: 3.211752599123473e-05 loss: 0.0573 (0.0673) time: 2.6119 data: 0.0060 max mem: 33369 +Epoch: [15] [ 720/1319] eta: 0:26:09 lr: 3.210856671110825e-05 loss: 0.0566 (0.0674) time: 2.6076 data: 0.0058 max mem: 33369 +Epoch: [15] [ 730/1319] eta: 0:25:43 lr: 3.2099607153204766e-05 loss: 0.0550 (0.0673) time: 2.5874 data: 0.0060 max mem: 33369 +Epoch: [15] [ 740/1319] eta: 0:25:16 lr: 3.209064731742954e-05 loss: 0.0613 (0.0674) time: 2.5871 data: 0.0061 max mem: 33369 +Epoch: [15] [ 750/1319] eta: 0:24:50 lr: 3.208168720368771e-05 loss: 0.0647 (0.0674) time: 2.5951 data: 0.0059 max mem: 33369 +Epoch: [15] [ 760/1319] eta: 0:24:24 lr: 3.2072726811884414e-05 loss: 0.0661 (0.0675) time: 2.6055 data: 0.0058 max mem: 33369 +Epoch: [15] [ 770/1319] eta: 0:23:57 lr: 3.20637661419247e-05 loss: 0.0661 (0.0676) time: 2.6000 data: 0.0058 max mem: 33369 +Epoch: [15] [ 780/1319] eta: 0:23:31 lr: 3.205480519371354e-05 loss: 0.0587 (0.0676) time: 2.6037 data: 0.0059 max mem: 33369 +Epoch: [15] [ 790/1319] eta: 0:23:05 lr: 3.204584396715587e-05 loss: 0.0538 (0.0675) time: 2.6265 data: 0.0058 max mem: 33369 +Epoch: [15] [ 800/1319] eta: 0:22:39 lr: 3.203688246215656e-05 loss: 0.0558 (0.0677) time: 2.6228 data: 0.0057 max mem: 33369 +Epoch: [15] [ 810/1319] eta: 0:22:12 lr: 3.20279206786204e-05 loss: 0.0626 (0.0675) time: 2.6026 data: 0.0057 max mem: 33369 +Epoch: [15] [ 820/1319] eta: 0:21:46 lr: 3.201895861645214e-05 loss: 0.0565 (0.0675) time: 2.6011 data: 0.0056 max mem: 33369 +Epoch: [15] [ 830/1319] eta: 0:21:20 lr: 3.2009996275556456e-05 loss: 0.0518 (0.0675) time: 2.6126 data: 0.0059 max mem: 33369 +Epoch: [15] [ 840/1319] eta: 0:20:54 lr: 3.200103365583796e-05 loss: 0.0625 (0.0675) time: 2.6058 data: 0.0060 max mem: 33369 +Epoch: [15] [ 850/1319] eta: 0:20:28 lr: 3.1992070757201206e-05 loss: 0.0680 (0.0674) time: 2.6221 data: 0.0060 max mem: 33369 +Epoch: [15] [ 860/1319] eta: 0:20:01 lr: 3.198310757955068e-05 loss: 0.0615 (0.0673) time: 2.6246 data: 0.0060 max mem: 33369 +Epoch: [15] [ 870/1319] eta: 0:19:35 lr: 3.197414412279081e-05 loss: 0.0621 (0.0675) time: 2.5927 data: 0.0059 max mem: 33369 +Epoch: [15] [ 880/1319] eta: 0:19:09 lr: 3.196518038682597e-05 loss: 0.0570 (0.0674) time: 2.6157 data: 0.0060 max mem: 33369 +Epoch: [15] [ 890/1319] eta: 0:18:43 lr: 3.1956216371560456e-05 loss: 0.0541 (0.0673) time: 2.6314 data: 0.0059 max mem: 33369 +Epoch: [15] [ 900/1319] eta: 0:18:16 lr: 3.194725207689851e-05 loss: 0.0561 (0.0672) time: 2.5959 data: 0.0059 max mem: 33369 +Epoch: [15] [ 910/1319] eta: 0:17:50 lr: 3.1938287502744314e-05 loss: 0.0575 (0.0672) time: 2.6129 data: 0.0058 max mem: 33369 +Epoch: [15] [ 920/1319] eta: 0:17:24 lr: 3.192932264900198e-05 loss: 0.0591 (0.0672) time: 2.6232 data: 0.0057 max mem: 33369 +Epoch: [15] [ 930/1319] eta: 0:16:58 lr: 3.192035751557555e-05 loss: 0.0591 (0.0673) time: 2.6081 data: 0.0058 max mem: 33369 +Epoch: [15] [ 940/1319] eta: 0:16:32 lr: 3.1911392102369026e-05 loss: 0.0591 (0.0672) time: 2.6059 data: 0.0058 max mem: 33369 +Epoch: [15] [ 950/1319] eta: 0:16:05 lr: 3.1902426409286326e-05 loss: 0.0590 (0.0673) time: 2.5989 data: 0.0058 max mem: 33369 +Epoch: [15] [ 960/1319] eta: 0:15:39 lr: 3.189346043623133e-05 loss: 0.0590 (0.0673) time: 2.5925 data: 0.0059 max mem: 33369 +Epoch: [15] [ 970/1319] eta: 0:15:13 lr: 3.1884494183107815e-05 loss: 0.0542 (0.0673) time: 2.6159 data: 0.0059 max mem: 33369 +Epoch: [15] [ 980/1319] eta: 0:14:47 lr: 3.187552764981953e-05 loss: 0.0661 (0.0674) time: 2.6526 data: 0.0059 max mem: 33369 +Epoch: [15] [ 990/1319] eta: 0:14:21 lr: 3.186656083627014e-05 loss: 0.0688 (0.0674) time: 2.6402 data: 0.0059 max mem: 33369 +Epoch: [15] [1000/1319] eta: 0:13:55 lr: 3.1857593742363276e-05 loss: 0.0597 (0.0673) time: 2.5952 data: 0.0059 max mem: 33369 +Epoch: [15] [1010/1319] eta: 0:13:28 lr: 3.184862636800246e-05 loss: 0.0506 (0.0671) time: 2.5899 data: 0.0059 max mem: 33369 +Epoch: [15] [1020/1319] eta: 0:13:02 lr: 3.183965871309119e-05 loss: 0.0506 (0.0671) time: 2.6002 data: 0.0058 max mem: 33369 +Epoch: [15] [1030/1319] eta: 0:12:36 lr: 3.1830690777532884e-05 loss: 0.0549 (0.0670) time: 2.6089 data: 0.0056 max mem: 33369 +Epoch: [15] [1040/1319] eta: 0:12:10 lr: 3.182172256123091e-05 loss: 0.0591 (0.0670) time: 2.6183 data: 0.0058 max mem: 33369 +Epoch: [15] [1050/1319] eta: 0:11:44 lr: 3.181275406408854e-05 loss: 0.0591 (0.0670) time: 2.6286 data: 0.0059 max mem: 33369 +Epoch: [15] [1060/1319] eta: 0:11:17 lr: 3.180378528600901e-05 loss: 0.0665 (0.0671) time: 2.6184 data: 0.0058 max mem: 33369 +Epoch: [15] [1070/1319] eta: 0:10:51 lr: 3.17948162268955e-05 loss: 0.0670 (0.0671) time: 2.5957 data: 0.0058 max mem: 33369 +Epoch: [15] [1080/1319] eta: 0:10:25 lr: 3.17858468866511e-05 loss: 0.0619 (0.0671) time: 2.6085 data: 0.0057 max mem: 33369 +Epoch: [15] [1090/1319] eta: 0:09:59 lr: 3.177687726517885e-05 loss: 0.0619 (0.0671) time: 2.5914 data: 0.0058 max mem: 33369 +Epoch: [15] [1100/1319] eta: 0:09:33 lr: 3.1767907362381725e-05 loss: 0.0675 (0.0672) time: 2.5944 data: 0.0059 max mem: 33369 +Epoch: [15] [1110/1319] eta: 0:09:06 lr: 3.175893717816263e-05 loss: 0.0695 (0.0674) time: 2.6075 data: 0.0058 max mem: 33369 +Epoch: [15] [1120/1319] eta: 0:08:40 lr: 3.174996671242443e-05 loss: 0.0620 (0.0673) time: 2.6025 data: 0.0060 max mem: 33369 +Epoch: [15] [1130/1319] eta: 0:08:14 lr: 3.1740995965069895e-05 loss: 0.0538 (0.0672) time: 2.6056 data: 0.0059 max mem: 33369 +Epoch: [15] [1140/1319] eta: 0:07:48 lr: 3.173202493600174e-05 loss: 0.0538 (0.0671) time: 2.6322 data: 0.0060 max mem: 33369 +Epoch: [15] [1150/1319] eta: 0:07:22 lr: 3.172305362512263e-05 loss: 0.0678 (0.0671) time: 2.6408 data: 0.0060 max mem: 33369 +Epoch: [15] [1160/1319] eta: 0:06:56 lr: 3.171408203233514e-05 loss: 0.0740 (0.0672) time: 2.6145 data: 0.0057 max mem: 33369 +Epoch: [15] [1170/1319] eta: 0:06:29 lr: 3.170511015754181e-05 loss: 0.0641 (0.0672) time: 2.6176 data: 0.0057 max mem: 33369 +Epoch: [15] [1180/1319] eta: 0:06:03 lr: 3.16961380006451e-05 loss: 0.0549 (0.0671) time: 2.6107 data: 0.0057 max mem: 33369 +Epoch: [15] [1190/1319] eta: 0:05:37 lr: 3.16871655615474e-05 loss: 0.0607 (0.0671) time: 2.6367 data: 0.0056 max mem: 33369 +Epoch: [15] [1200/1319] eta: 0:05:11 lr: 3.1678192840151044e-05 loss: 0.0626 (0.0670) time: 2.6737 data: 0.0056 max mem: 33369 +Epoch: [15] [1210/1319] eta: 0:04:45 lr: 3.16692198363583e-05 loss: 0.0489 (0.0669) time: 2.6538 data: 0.0058 max mem: 33369 +Epoch: [15] [1220/1319] eta: 0:04:19 lr: 3.1660246550071386e-05 loss: 0.0489 (0.0669) time: 2.6355 data: 0.0059 max mem: 33369 +Epoch: [15] [1230/1319] eta: 0:03:52 lr: 3.165127298119242e-05 loss: 0.0627 (0.0670) time: 2.6136 data: 0.0058 max mem: 33369 +Epoch: [15] [1240/1319] eta: 0:03:26 lr: 3.164229912962349e-05 loss: 0.0686 (0.0670) time: 2.6190 data: 0.0059 max mem: 33369 +Epoch: [15] [1250/1319] eta: 0:03:00 lr: 3.163332499526659e-05 loss: 0.0566 (0.0669) time: 2.6459 data: 0.0059 max mem: 33369 +Epoch: [15] [1260/1319] eta: 0:02:34 lr: 3.162435057802369e-05 loss: 0.0533 (0.0669) time: 2.6249 data: 0.0058 max mem: 33369 +Epoch: [15] [1270/1319] eta: 0:02:08 lr: 3.161537587779665e-05 loss: 0.0626 (0.0669) time: 2.6047 data: 0.0060 max mem: 33369 +Epoch: [15] [1280/1319] eta: 0:01:42 lr: 3.1606400894487287e-05 loss: 0.0633 (0.0669) time: 2.5868 data: 0.0060 max mem: 33369 +Epoch: [15] [1290/1319] eta: 0:01:15 lr: 3.159742562799735e-05 loss: 0.0624 (0.0670) time: 2.5910 data: 0.0059 max mem: 33369 +Epoch: [15] [1300/1319] eta: 0:00:49 lr: 3.158845007822852e-05 loss: 0.0612 (0.0670) time: 2.5769 data: 0.0058 max mem: 33369 +Epoch: [15] [1310/1319] eta: 0:00:23 lr: 3.1579474245082424e-05 loss: 0.0547 (0.0670) time: 2.5941 data: 0.0057 max mem: 33369 +Epoch: [15] Total time: 0:57:32 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 2:04:41 time: 2.9079 data: 2.8292 max mem: 33369 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 100/2573] eta: 0:04:06 time: 0.0711 data: 0.0011 max mem: 33369 +Test: [ 200/2573] eta: 0:03:26 time: 0.0729 data: 0.0011 max mem: 33369 +Test: [ 300/2573] eta: 0:03:05 time: 0.0746 data: 0.0011 max mem: 33369 +Test: [ 400/2573] eta: 0:02:52 time: 0.0747 data: 0.0011 max mem: 33369 +Test: [ 500/2573] eta: 0:02:42 time: 0.0732 data: 0.0011 max mem: 33369 +Test: [ 600/2573] eta: 0:02:33 time: 0.0732 data: 0.0011 max mem: 33369 +Test: [ 700/2573] eta: 0:02:24 time: 0.0734 data: 0.0011 max mem: 33369 +Test: [ 800/2573] eta: 0:02:16 time: 0.0766 data: 0.0011 max mem: 33369 +Test: [ 900/2573] eta: 0:02:08 time: 0.0734 data: 0.0011 max mem: 33369 +Test: [1000/2573] eta: 0:02:00 time: 0.0735 data: 0.0011 max mem: 33369 +Test: [1100/2573] eta: 0:01:52 time: 0.0735 data: 0.0011 max mem: 33369 +Test: [1200/2573] eta: 0:01:44 time: 0.0735 data: 0.0011 max mem: 33369 +Test: [1300/2573] eta: 0:01:36 time: 0.0734 data: 0.0011 max mem: 33369 +Test: [1400/2573] eta: 0:01:28 time: 0.0719 data: 0.0011 max mem: 33369 +Test: [1500/2573] eta: 0:01:20 time: 0.0736 data: 0.0011 max mem: 33369 +Test: [1600/2573] eta: 0:01:13 time: 0.0770 data: 0.0011 max mem: 33369 +Test: [1700/2573] eta: 0:01:05 time: 0.0719 data: 0.0011 max mem: 33369 +Test: [1800/2573] eta: 0:00:58 time: 0.0753 data: 0.0011 max mem: 33369 +Test: [1900/2573] eta: 0:00:50 time: 0.0720 data: 0.0011 max mem: 33369 +Test: [2000/2573] eta: 0:00:42 time: 0.0736 data: 0.0011 max mem: 33369 +Test: [2100/2573] eta: 0:00:35 time: 0.0753 data: 0.0011 max mem: 33369 +Test: [2200/2573] eta: 0:00:27 time: 0.0752 data: 0.0011 max mem: 33369 +Test: [2300/2573] eta: 0:00:20 time: 0.0752 data: 0.0011 max mem: 33369 +Test: [2400/2573] eta: 0:00:12 time: 0.0707 data: 0.0012 max mem: 33369 +Test: [2500/2573] eta: 0:00:05 time: 0.0737 data: 0.0011 max mem: 33369 +Test: Total time: 0:03:12 +Final results: +Mean IoU is 61.59 + + precision@0.5 = 69.30 + precision@0.6 = 63.52 + precision@0.7 = 56.11 + precision@0.8 = 43.71 + precision@0.9 = 20.53 + overall IoU = 59.29 + +Average object IoU 61.592127209123525 +Overall IoU 59.28716278076172 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [16] [ 0/1319] eta: 3:15:30 lr: 3.157139575288201e-05 loss: 0.0555 (0.0555) time: 8.8936 data: 1.4851 max mem: 33369 +Epoch: [16] [ 10/1319] eta: 1:09:37 lr: 3.1562419381047834e-05 loss: 0.0502 (0.0559) time: 3.1917 data: 0.1406 max mem: 33369 +Epoch: [16] [ 20/1319] eta: 1:03:11 lr: 3.155344272555071e-05 loss: 0.0600 (0.0610) time: 2.6201 data: 0.0060 max mem: 33369 +Epoch: [16] [ 30/1319] eta: 1:00:45 lr: 3.154446578629201e-05 loss: 0.0630 (0.0629) time: 2.6280 data: 0.0061 max mem: 33369 +Epoch: [16] [ 40/1319] eta: 0:59:06 lr: 3.153548856317304e-05 loss: 0.0523 (0.0597) time: 2.6199 data: 0.0061 max mem: 33369 +Epoch: [16] [ 50/1319] eta: 0:57:56 lr: 3.152651105609501e-05 loss: 0.0488 (0.0577) time: 2.6030 data: 0.0060 max mem: 33369 +Epoch: [16] [ 60/1319] eta: 0:56:58 lr: 3.1517533264959104e-05 loss: 0.0463 (0.0567) time: 2.5964 data: 0.0060 max mem: 33369 +Epoch: [16] [ 70/1319] eta: 0:56:09 lr: 3.150855518966642e-05 loss: 0.0522 (0.0580) time: 2.5910 data: 0.0060 max mem: 33369 +Epoch: [16] [ 80/1319] eta: 0:55:32 lr: 3.1499576830118e-05 loss: 0.0564 (0.0575) time: 2.6106 data: 0.0062 max mem: 33369 +Epoch: [16] [ 90/1319] eta: 0:54:56 lr: 3.14905981862148e-05 loss: 0.0510 (0.0571) time: 2.6271 data: 0.0063 max mem: 33369 +Epoch: [16] [ 100/1319] eta: 0:54:20 lr: 3.1481619257857746e-05 loss: 0.0545 (0.0581) time: 2.6156 data: 0.0063 max mem: 33369 +Epoch: [16] [ 110/1319] eta: 0:53:48 lr: 3.147264004494766e-05 loss: 0.0564 (0.0583) time: 2.6161 data: 0.0062 max mem: 33369 +Epoch: [16] [ 120/1319] eta: 0:53:14 lr: 3.1463660547385324e-05 loss: 0.0572 (0.0583) time: 2.6136 data: 0.0060 max mem: 33369 +Epoch: [16] [ 130/1319] eta: 0:52:40 lr: 3.1454680765071425e-05 loss: 0.0615 (0.0592) time: 2.5897 data: 0.0061 max mem: 33369 +Epoch: [16] [ 140/1319] eta: 0:52:07 lr: 3.1445700697906627e-05 loss: 0.0523 (0.0583) time: 2.5805 data: 0.0061 max mem: 33369 +Epoch: [16] [ 150/1319] eta: 0:51:39 lr: 3.1436720345791495e-05 loss: 0.0506 (0.0586) time: 2.6100 data: 0.0062 max mem: 33369 +Epoch: [16] [ 160/1319] eta: 0:51:10 lr: 3.1427739708626534e-05 loss: 0.0514 (0.0581) time: 2.6272 data: 0.0062 max mem: 33369 +Epoch: [16] [ 170/1319] eta: 0:50:41 lr: 3.141875878631219e-05 loss: 0.0523 (0.0582) time: 2.6094 data: 0.0061 max mem: 33369 +Epoch: [16] [ 180/1319] eta: 0:50:15 lr: 3.140977757874883e-05 loss: 0.0540 (0.0583) time: 2.6287 data: 0.0059 max mem: 33369 +Epoch: [16] [ 190/1319] eta: 0:49:45 lr: 3.140079608583676e-05 loss: 0.0579 (0.0583) time: 2.6260 data: 0.0059 max mem: 33369 +Epoch: [16] [ 200/1319] eta: 0:49:17 lr: 3.1391814307476244e-05 loss: 0.0520 (0.0581) time: 2.6036 data: 0.0061 max mem: 33369 +Epoch: [16] [ 210/1319] eta: 0:48:50 lr: 3.138283224356744e-05 loss: 0.0486 (0.0577) time: 2.6190 data: 0.0063 max mem: 33369 +Epoch: [16] [ 220/1319] eta: 0:48:21 lr: 3.137384989401046e-05 loss: 0.0486 (0.0575) time: 2.6106 data: 0.0062 max mem: 33369 +Epoch: [16] [ 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33369 +Epoch: [16] [ 310/1319] eta: 0:44:15 lr: 3.129299587731458e-05 loss: 0.0595 (0.0591) time: 2.6179 data: 0.0059 max mem: 33369 +Epoch: [16] [ 320/1319] eta: 0:43:48 lr: 3.1284010665767105e-05 loss: 0.0615 (0.0591) time: 2.6128 data: 0.0058 max mem: 33369 +Epoch: [16] [ 330/1319] eta: 0:43:22 lr: 3.1275025167468235e-05 loss: 0.0552 (0.0597) time: 2.6183 data: 0.0060 max mem: 33369 +Epoch: [16] [ 340/1319] eta: 0:42:55 lr: 3.126603938231727e-05 loss: 0.0552 (0.0599) time: 2.6249 data: 0.0060 max mem: 33369 +Epoch: [16] [ 350/1319] eta: 0:42:29 lr: 3.1257053310213444e-05 loss: 0.0563 (0.0601) time: 2.6279 data: 0.0059 max mem: 33369 +Epoch: [16] [ 360/1319] eta: 0:42:02 lr: 3.124806695105593e-05 loss: 0.0519 (0.0599) time: 2.6167 data: 0.0058 max mem: 33369 +Epoch: [16] [ 370/1319] eta: 0:41:36 lr: 3.1239080304743815e-05 loss: 0.0550 (0.0600) time: 2.6256 data: 0.0059 max mem: 33369 +Epoch: [16] [ 380/1319] eta: 0:41:09 lr: 3.123009337117616e-05 loss: 0.0593 (0.0601) time: 2.6195 data: 0.0060 max mem: 33369 +Epoch: [16] [ 390/1319] eta: 0:40:42 lr: 3.12211061502519e-05 loss: 0.0587 (0.0602) time: 2.6101 data: 0.0059 max mem: 33369 +Epoch: [16] [ 400/1319] eta: 0:40:16 lr: 3.121211864186995e-05 loss: 0.0512 (0.0600) time: 2.6160 data: 0.0058 max mem: 33369 +Epoch: [16] [ 410/1319] eta: 0:39:49 lr: 3.120313084592913e-05 loss: 0.0577 (0.0602) time: 2.6124 data: 0.0060 max mem: 33369 +Epoch: [16] [ 420/1319] eta: 0:39:23 lr: 3.119414276232821e-05 loss: 0.0607 (0.0603) time: 2.6383 data: 0.0060 max mem: 33369 +Epoch: [16] [ 430/1319] eta: 0:38:57 lr: 3.118515439096588e-05 loss: 0.0569 (0.0603) time: 2.6389 data: 0.0059 max mem: 33369 +Epoch: [16] [ 440/1319] eta: 0:38:30 lr: 3.117616573174077e-05 loss: 0.0550 (0.0604) time: 2.6208 data: 0.0060 max mem: 33369 +Epoch: [16] [ 450/1319] eta: 0:38:04 lr: 3.116717678455143e-05 loss: 0.0597 (0.0606) time: 2.6301 data: 0.0060 max mem: 33369 +Epoch: [16] [ 460/1319] eta: 0:37:38 lr: 3.115818754929635e-05 loss: 0.0631 (0.0609) time: 2.6269 data: 0.0058 max mem: 33369 +Epoch: [16] [ 470/1319] eta: 0:37:11 lr: 3.1149198025873954e-05 loss: 0.0566 (0.0608) time: 2.6171 data: 0.0057 max mem: 33369 +Epoch: [16] [ 480/1319] eta: 0:36:45 lr: 3.1140208214182586e-05 loss: 0.0534 (0.0608) time: 2.6235 data: 0.0058 max mem: 33369 +Epoch: [16] [ 490/1319] eta: 0:36:19 lr: 3.113121811412054e-05 loss: 0.0499 (0.0606) time: 2.6305 data: 0.0057 max mem: 33369 +Epoch: [16] [ 500/1319] eta: 0:35:52 lr: 3.1122227725586026e-05 loss: 0.0482 (0.0604) time: 2.6163 data: 0.0055 max mem: 33369 +Epoch: [16] [ 510/1319] eta: 0:35:26 lr: 3.1113237048477186e-05 loss: 0.0548 (0.0607) time: 2.6107 data: 0.0056 max mem: 33369 +Epoch: [16] [ 520/1319] eta: 0:34:59 lr: 3.11042460826921e-05 loss: 0.0560 (0.0607) time: 2.6032 data: 0.0058 max mem: 33369 +Epoch: [16] [ 530/1319] eta: 0:34:32 lr: 3.1095254828128786e-05 loss: 0.0561 (0.0608) time: 2.5912 data: 0.0058 max mem: 33369 +Epoch: [16] [ 540/1319] eta: 0:34:06 lr: 3.108626328468517e-05 loss: 0.0622 (0.0608) time: 2.6095 data: 0.0057 max mem: 33369 +Epoch: [16] [ 550/1319] eta: 0:33:39 lr: 3.107727145225915e-05 loss: 0.0597 (0.0610) time: 2.6207 data: 0.0057 max mem: 33369 +Epoch: [16] [ 560/1319] eta: 0:33:12 lr: 3.106827933074849e-05 loss: 0.0582 (0.0612) time: 2.5929 data: 0.0058 max mem: 33369 +Epoch: [16] [ 570/1319] eta: 0:32:46 lr: 3.105928692005095e-05 loss: 0.0587 (0.0612) time: 2.5980 data: 0.0059 max mem: 33369 +Epoch: [16] [ 580/1319] eta: 0:32:20 lr: 3.105029422006419e-05 loss: 0.0589 (0.0613) time: 2.6219 data: 0.0057 max mem: 33369 +Epoch: [16] [ 590/1319] eta: 0:31:53 lr: 3.104130123068579e-05 loss: 0.0695 (0.0617) time: 2.6150 data: 0.0056 max mem: 33369 +Epoch: [16] [ 600/1319] eta: 0:31:27 lr: 3.10323079518133e-05 loss: 0.0583 (0.0616) time: 2.6311 data: 0.0058 max mem: 33369 +Epoch: [16] [ 610/1319] eta: 0:31:01 lr: 3.102331438334416e-05 loss: 0.0669 (0.0621) time: 2.6236 data: 0.0058 max mem: 33369 +Epoch: [16] [ 620/1319] eta: 0:30:35 lr: 3.1014320525175755e-05 loss: 0.0655 (0.0621) time: 2.6276 data: 0.0057 max mem: 33369 +Epoch: [16] [ 630/1319] eta: 0:30:09 lr: 3.100532637720542e-05 loss: 0.0515 (0.0620) time: 2.6526 data: 0.0056 max mem: 33369 +Epoch: [16] [ 640/1319] eta: 0:29:42 lr: 3.099633193933038e-05 loss: 0.0577 (0.0621) time: 2.6292 data: 0.0057 max mem: 33369 +Epoch: [16] [ 650/1319] eta: 0:29:15 lr: 3.098733721144784e-05 loss: 0.0577 (0.0620) time: 2.5834 data: 0.0058 max mem: 33369 +Epoch: [16] [ 660/1319] eta: 0:28:49 lr: 3.097834219345489e-05 loss: 0.0537 (0.0622) time: 2.5732 data: 0.0057 max mem: 33369 +Epoch: [16] [ 670/1319] eta: 0:28:23 lr: 3.0969346885248574e-05 loss: 0.0576 (0.0622) time: 2.6106 data: 0.0057 max mem: 33369 +Epoch: [16] [ 680/1319] eta: 0:27:57 lr: 3.0960351286725865e-05 loss: 0.0477 (0.0621) time: 2.6456 data: 0.0057 max mem: 33369 +Epoch: [16] [ 690/1319] eta: 0:27:30 lr: 3.0951355397783653e-05 loss: 0.0477 (0.0621) time: 2.6359 data: 0.0057 max mem: 33369 +Epoch: [16] [ 700/1319] eta: 0:27:04 lr: 3.0942359218318776e-05 loss: 0.0547 (0.0621) time: 2.6144 data: 0.0056 max mem: 33369 +Epoch: [16] [ 710/1319] eta: 0:26:37 lr: 3.0933362748228e-05 loss: 0.0547 (0.0621) time: 2.5973 data: 0.0057 max mem: 33369 +Epoch: [16] [ 720/1319] eta: 0:26:11 lr: 3.092436598740799e-05 loss: 0.0541 (0.0622) time: 2.5889 data: 0.0059 max mem: 33369 +Epoch: [16] [ 730/1319] eta: 0:25:44 lr: 3.09153689357554e-05 loss: 0.0541 (0.0623) time: 2.5976 data: 0.0057 max mem: 33369 +Epoch: [16] [ 740/1319] eta: 0:25:18 lr: 3.090637159316675e-05 loss: 0.0488 (0.0622) time: 2.6033 data: 0.0056 max mem: 33369 +Epoch: [16] [ 750/1319] eta: 0:24:52 lr: 3.089737395953854e-05 loss: 0.0505 (0.0623) time: 2.5963 data: 0.0059 max mem: 33369 +Epoch: [16] [ 760/1319] eta: 0:24:25 lr: 3.088837603476717e-05 loss: 0.0682 (0.0623) time: 2.6059 data: 0.0061 max mem: 33369 +Epoch: [16] [ 770/1319] eta: 0:23:59 lr: 3.087937781874897e-05 loss: 0.0509 (0.0623) time: 2.6131 data: 0.0059 max mem: 33369 +Epoch: [16] [ 780/1319] eta: 0:23:33 lr: 3.087037931138022e-05 loss: 0.0590 (0.0623) time: 2.6150 data: 0.0057 max mem: 33369 +Epoch: [16] [ 790/1319] eta: 0:23:07 lr: 3.086138051255712e-05 loss: 0.0590 (0.0623) time: 2.6161 data: 0.0056 max mem: 33369 +Epoch: [16] [ 800/1319] eta: 0:22:40 lr: 3.085238142217579e-05 loss: 0.0516 (0.0622) time: 2.6046 data: 0.0057 max mem: 33369 +Epoch: [16] [ 810/1319] eta: 0:22:14 lr: 3.084338204013227e-05 loss: 0.0534 (0.0624) time: 2.6103 data: 0.0057 max mem: 33369 +Epoch: [16] [ 820/1319] eta: 0:21:48 lr: 3.0834382366322574e-05 loss: 0.0624 (0.0624) time: 2.6318 data: 0.0056 max mem: 33369 +Epoch: [16] [ 830/1319] eta: 0:21:22 lr: 3.08253824006426e-05 loss: 0.0626 (0.0625) time: 2.6336 data: 0.0056 max mem: 33369 +Epoch: [16] [ 840/1319] eta: 0:20:56 lr: 3.08163821429882e-05 loss: 0.0666 (0.0626) time: 2.6382 data: 0.0056 max mem: 33369 +Epoch: [16] [ 850/1319] eta: 0:20:29 lr: 3.0807381593255134e-05 loss: 0.0576 (0.0625) time: 2.6407 data: 0.0057 max mem: 33369 +Epoch: [16] [ 860/1319] eta: 0:20:04 lr: 3.079838075133912e-05 loss: 0.0576 (0.0626) time: 2.6627 data: 0.0058 max mem: 33369 +Epoch: [16] [ 870/1319] eta: 0:19:37 lr: 3.0789379617135774e-05 loss: 0.0742 (0.0629) time: 2.6548 data: 0.0058 max mem: 33369 +Epoch: [16] [ 880/1319] eta: 0:19:11 lr: 3.078037819054066e-05 loss: 0.0727 (0.0630) time: 2.6174 data: 0.0058 max mem: 33369 +Epoch: [16] [ 890/1319] eta: 0:18:45 lr: 3.0771376471449264e-05 loss: 0.0538 (0.0629) time: 2.6047 data: 0.0057 max mem: 33369 +Epoch: [16] [ 900/1319] eta: 0:18:19 lr: 3.076237445975701e-05 loss: 0.0552 (0.0629) time: 2.6103 data: 0.0056 max mem: 33369 +Epoch: [16] [ 910/1319] eta: 0:17:52 lr: 3.075337215535924e-05 loss: 0.0555 (0.0628) time: 2.6316 data: 0.0055 max mem: 33369 +Epoch: [16] [ 920/1319] eta: 0:17:26 lr: 3.074436955815122e-05 loss: 0.0518 (0.0627) time: 2.6265 data: 0.0057 max mem: 33369 +Epoch: [16] [ 930/1319] eta: 0:17:00 lr: 3.073536666802816e-05 loss: 0.0559 (0.0628) time: 2.6330 data: 0.0057 max mem: 33369 +Epoch: [16] [ 940/1319] eta: 0:16:34 lr: 3.0726363484885186e-05 loss: 0.0571 (0.0627) time: 2.6651 data: 0.0055 max mem: 33369 +Epoch: [16] [ 950/1319] eta: 0:16:08 lr: 3.0717360008617356e-05 loss: 0.0681 (0.0628) time: 2.6586 data: 0.0056 max mem: 33369 +Epoch: [16] [ 960/1319] eta: 0:15:42 lr: 3.070835623911966e-05 loss: 0.0716 (0.0629) time: 2.6383 data: 0.0057 max mem: 33369 +Epoch: [16] [ 970/1319] eta: 0:15:15 lr: 3.069935217628702e-05 loss: 0.0665 (0.0629) time: 2.6289 data: 0.0056 max mem: 33369 +Epoch: [16] [ 980/1319] eta: 0:14:49 lr: 3.0690347820014265e-05 loss: 0.0645 (0.0630) time: 2.6344 data: 0.0056 max mem: 33369 +Epoch: [16] [ 990/1319] eta: 0:14:23 lr: 3.068134317019618e-05 loss: 0.0616 (0.0630) time: 2.6530 data: 0.0057 max mem: 33369 +Epoch: [16] [1000/1319] eta: 0:13:57 lr: 3.0672338226727455e-05 loss: 0.0558 (0.0630) time: 2.6515 data: 0.0058 max mem: 33369 +Epoch: [16] [1010/1319] eta: 0:13:30 lr: 3.066333298950271e-05 loss: 0.0600 (0.0629) time: 2.6207 data: 0.0056 max mem: 33369 +Epoch: [16] [1020/1319] eta: 0:13:04 lr: 3.065432745841652e-05 loss: 0.0576 (0.0630) time: 2.6025 data: 0.0057 max mem: 33369 +Epoch: [16] [1030/1319] eta: 0:12:38 lr: 3.064532163336335e-05 loss: 0.0651 (0.0631) time: 2.6123 data: 0.0058 max mem: 33369 +Epoch: [16] [1040/1319] eta: 0:12:12 lr: 3.063631551423762e-05 loss: 0.0650 (0.0631) time: 2.6090 data: 0.0057 max mem: 33369 +Epoch: [16] [1050/1319] eta: 0:11:45 lr: 3.062730910093366e-05 loss: 0.0517 (0.0630) time: 2.6247 data: 0.0058 max mem: 33369 +Epoch: [16] [1060/1319] eta: 0:11:19 lr: 3.061830239334574e-05 loss: 0.0463 (0.0629) time: 2.6107 data: 0.0060 max mem: 33369 +Epoch: [16] [1070/1319] eta: 0:10:53 lr: 3.0609295391368055e-05 loss: 0.0514 (0.0630) time: 2.5974 data: 0.0058 max mem: 33369 +Epoch: [16] [1080/1319] eta: 0:10:27 lr: 3.060028809489473e-05 loss: 0.0514 (0.0629) time: 2.6157 data: 0.0058 max mem: 33369 +Epoch: [16] [1090/1319] eta: 0:10:00 lr: 3.059128050381978e-05 loss: 0.0468 (0.0628) time: 2.6137 data: 0.0058 max mem: 33369 +Epoch: [16] [1100/1319] eta: 0:09:34 lr: 3.058227261803723e-05 loss: 0.0527 (0.0629) time: 2.6014 data: 0.0058 max mem: 33369 +Epoch: [16] [1110/1319] eta: 0:09:08 lr: 3.0573264437440946e-05 loss: 0.0628 (0.0630) time: 2.5992 data: 0.0059 max mem: 33369 +Epoch: [16] [1120/1319] eta: 0:08:42 lr: 3.056425596192476e-05 loss: 0.0572 (0.0630) time: 2.6168 data: 0.0059 max mem: 33369 +Epoch: [16] [1130/1319] eta: 0:08:15 lr: 3.0555247191382436e-05 loss: 0.0521 (0.0629) time: 2.6252 data: 0.0057 max mem: 33369 +Epoch: [16] [1140/1319] eta: 0:07:49 lr: 3.054623812570766e-05 loss: 0.0479 (0.0629) time: 2.6143 data: 0.0056 max mem: 33369 +Epoch: [16] [1150/1319] eta: 0:07:23 lr: 3.053722876479403e-05 loss: 0.0518 (0.0629) time: 2.6374 data: 0.0057 max mem: 33369 +Epoch: [16] [1160/1319] eta: 0:06:57 lr: 3.0528219108535084e-05 loss: 0.0576 (0.0629) time: 2.6350 data: 0.0056 max mem: 33369 +Epoch: [16] [1170/1319] eta: 0:06:30 lr: 3.0519209156824297e-05 loss: 0.0698 (0.0630) time: 2.6124 data: 0.0057 max mem: 33369 +Epoch: [16] [1180/1319] eta: 0:06:04 lr: 3.0510198909555044e-05 loss: 0.0579 (0.0631) time: 2.6088 data: 0.0059 max mem: 33369 +Epoch: [16] [1190/1319] eta: 0:05:38 lr: 3.0501188366620653e-05 loss: 0.0507 (0.0631) time: 2.6023 data: 0.0058 max mem: 33369 +Epoch: [16] [1200/1319] eta: 0:05:12 lr: 3.0492177527914355e-05 loss: 0.0583 (0.0632) time: 2.6122 data: 0.0058 max mem: 33369 +Epoch: [16] [1210/1319] eta: 0:04:45 lr: 3.0483166393329327e-05 loss: 0.0593 (0.0631) time: 2.6208 data: 0.0057 max mem: 33369 +Epoch: [16] [1220/1319] eta: 0:04:19 lr: 3.0474154962758662e-05 loss: 0.0571 (0.0632) time: 2.5976 data: 0.0055 max mem: 33369 +Epoch: [16] [1230/1319] eta: 0:03:53 lr: 3.0465143236095372e-05 loss: 0.0582 (0.0632) time: 2.6056 data: 0.0056 max mem: 33369 +Epoch: [16] [1240/1319] eta: 0:03:27 lr: 3.045613121323242e-05 loss: 0.0484 (0.0632) time: 2.6317 data: 0.0057 max mem: 33369 +Epoch: [16] [1250/1319] eta: 0:03:00 lr: 3.044711889406267e-05 loss: 0.0484 (0.0632) time: 2.6181 data: 0.0056 max mem: 33369 +Epoch: [16] [1260/1319] eta: 0:02:34 lr: 3.0438106278478923e-05 loss: 0.0602 (0.0633) time: 2.5942 data: 0.0057 max mem: 33369 +Epoch: [16] [1270/1319] eta: 0:02:08 lr: 3.0429093366373907e-05 loss: 0.0602 (0.0635) time: 2.5990 data: 0.0058 max mem: 33369 +Epoch: [16] [1280/1319] eta: 0:01:42 lr: 3.0420080157640274e-05 loss: 0.0571 (0.0636) time: 2.6313 data: 0.0057 max mem: 33369 +Epoch: [16] [1290/1319] eta: 0:01:16 lr: 3.0411066652170593e-05 loss: 0.0571 (0.0636) time: 2.6253 data: 0.0058 max mem: 33369 +Epoch: [16] [1300/1319] eta: 0:00:49 lr: 3.040205284985739e-05 loss: 0.0553 (0.0636) time: 2.6369 data: 0.0058 max mem: 33369 +Epoch: [16] [1310/1319] eta: 0:00:23 lr: 3.039303875059306e-05 loss: 0.0518 (0.0635) time: 2.6470 data: 0.0056 max mem: 33369 +Epoch: [16] Total time: 0:57:39 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 2:14:35 time: 3.1385 data: 3.0609 max mem: 33369 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 100/2573] eta: 0:04:13 time: 0.0714 data: 0.0011 max mem: 33369 +Test: [ 200/2573] eta: 0:03:29 time: 0.0729 data: 0.0011 max mem: 33369 +Test: [ 300/2573] eta: 0:03:08 time: 0.0745 data: 0.0011 max mem: 33369 +Test: [ 400/2573] eta: 0:02:54 time: 0.0748 data: 0.0011 max mem: 33369 +Test: [ 500/2573] eta: 0:02:43 time: 0.0731 data: 0.0011 max mem: 33369 +Test: [ 600/2573] eta: 0:02:33 time: 0.0734 data: 0.0011 max mem: 33369 +Test: [ 700/2573] eta: 0:02:25 time: 0.0733 data: 0.0011 max mem: 33369 +Test: [ 800/2573] eta: 0:02:16 time: 0.0767 data: 0.0011 max mem: 33369 +Test: [ 900/2573] eta: 0:02:08 time: 0.0734 data: 0.0011 max mem: 33369 +Test: [1000/2573] eta: 0:02:00 time: 0.0733 data: 0.0011 max mem: 33369 +Test: [1100/2573] eta: 0:01:52 time: 0.0735 data: 0.0011 max mem: 33369 +Test: [1200/2573] eta: 0:01:44 time: 0.0734 data: 0.0011 max mem: 33369 +Test: [1300/2573] eta: 0:01:36 time: 0.0735 data: 0.0011 max mem: 33369 +Test: [1400/2573] eta: 0:01:28 time: 0.0718 data: 0.0011 max mem: 33369 +Test: [1500/2573] eta: 0:01:21 time: 0.0735 data: 0.0011 max mem: 33369 +Test: [1600/2573] eta: 0:01:13 time: 0.0768 data: 0.0011 max mem: 33369 +Test: [1700/2573] eta: 0:01:05 time: 0.0719 data: 0.0011 max mem: 33369 +Test: [1800/2573] eta: 0:00:58 time: 0.0753 data: 0.0011 max mem: 33369 +Test: [1900/2573] eta: 0:00:50 time: 0.0720 data: 0.0011 max mem: 33369 +Test: [2000/2573] eta: 0:00:42 time: 0.0736 data: 0.0011 max mem: 33369 +Test: [2100/2573] eta: 0:00:35 time: 0.0753 data: 0.0011 max mem: 33369 +Test: [2200/2573] eta: 0:00:27 time: 0.0753 data: 0.0011 max mem: 33369 +Test: [2300/2573] eta: 0:00:20 time: 0.0753 data: 0.0011 max mem: 33369 +Test: [2400/2573] eta: 0:00:12 time: 0.0704 data: 0.0011 max mem: 33369 +Test: [2500/2573] eta: 0:00:05 time: 0.0737 data: 0.0011 max mem: 33369 +Test: Total time: 0:03:12 +Final results: +Mean IoU is 61.43 + + precision@0.5 = 69.32 + precision@0.6 = 63.71 + precision@0.7 = 56.27 + precision@0.8 = 43.36 + precision@0.9 = 21.36 + overall IoU = 59.95 + +Average object IoU 61.429337832593575 +Overall IoU 59.95465850830078 +Better epoch: 16 + +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [17] [ 0/1319] eta: 1:25:30 lr: 3.0384925807273e-05 loss: 0.0716 (0.0716) time: 3.8896 data: 1.2386 max mem: 33369 +Epoch: [17] [ 10/1319] eta: 0:59:12 lr: 3.0375911143504937e-05 loss: 0.0556 (0.0648) time: 2.7136 data: 0.1184 max mem: 33369 +Epoch: [17] [ 20/1319] eta: 0:58:02 lr: 3.0366896182473385e-05 loss: 0.0547 (0.0632) time: 2.6206 data: 0.0062 max mem: 33369 +Epoch: [17] [ 30/1319] eta: 0:56:53 lr: 3.035788092407048e-05 loss: 0.0530 (0.0623) time: 2.6119 data: 0.0060 max mem: 33369 +Epoch: [17] [ 40/1319] eta: 0:56:19 lr: 3.034886536818829e-05 loss: 0.0530 (0.0620) time: 2.6016 data: 0.0061 max mem: 33369 +Epoch: [17] [ 50/1319] eta: 0:55:47 lr: 3.0339849514718806e-05 loss: 0.0499 (0.0601) time: 2.6232 data: 0.0064 max mem: 33369 +Epoch: [17] [ 60/1319] eta: 0:55:17 lr: 3.033083336355392e-05 loss: 0.0499 (0.0593) time: 2.6212 data: 0.0064 max mem: 33369 +Epoch: [17] [ 70/1319] eta: 0:54:50 lr: 3.03218169145855e-05 loss: 0.0497 (0.0590) time: 2.6253 data: 0.0061 max mem: 33369 +Epoch: [17] [ 80/1319] eta: 0:54:21 lr: 3.0312800167705292e-05 loss: 0.0497 (0.0589) time: 2.6225 data: 0.0061 max mem: 33369 +Epoch: [17] [ 90/1319] eta: 0:53:53 lr: 3.030378312280498e-05 loss: 0.0504 (0.0584) time: 2.6200 data: 0.0061 max mem: 33369 +Epoch: [17] [ 100/1319] eta: 0:53:27 lr: 3.0294765779776184e-05 loss: 0.0554 (0.0595) time: 2.6275 data: 0.0060 max mem: 33369 +Epoch: [17] [ 110/1319] eta: 0:52:58 lr: 3.0285748138510444e-05 loss: 0.0599 (0.0610) time: 2.6174 data: 0.0060 max mem: 33369 +Epoch: [17] [ 120/1319] eta: 0:52:29 lr: 3.0276730198899216e-05 loss: 0.0517 (0.0603) time: 2.6046 data: 0.0060 max mem: 33369 +Epoch: [17] [ 130/1319] eta: 0:52:00 lr: 3.0267711960833896e-05 loss: 0.0507 (0.0604) time: 2.5990 data: 0.0059 max mem: 33369 +Epoch: [17] [ 140/1319] eta: 0:51:30 lr: 3.0258693424205785e-05 loss: 0.0564 (0.0605) time: 2.5886 data: 0.0059 max mem: 33369 +Epoch: [17] [ 150/1319] eta: 0:51:04 lr: 3.024967458890613e-05 loss: 0.0477 (0.0599) time: 2.5999 data: 0.0060 max mem: 33369 +Epoch: [17] [ 160/1319] eta: 0:50:39 lr: 3.0240655454826085e-05 loss: 0.0477 (0.0604) time: 2.6320 data: 0.0060 max mem: 33369 +Epoch: [17] [ 170/1319] eta: 0:50:14 lr: 3.023163602185673e-05 loss: 0.0525 (0.0602) time: 2.6456 data: 0.0059 max mem: 33369 +Epoch: [17] [ 180/1319] eta: 0:49:46 lr: 3.022261628988908e-05 loss: 0.0606 (0.0611) time: 2.6188 data: 0.0057 max mem: 33369 +Epoch: [17] [ 190/1319] eta: 0:49:24 lr: 3.0213596258814065e-05 loss: 0.0606 (0.0611) time: 2.6400 data: 0.0058 max mem: 33369 +Epoch: [17] [ 200/1319] eta: 0:48:56 lr: 3.020457592852254e-05 loss: 0.0530 (0.0609) time: 2.6409 data: 0.0059 max mem: 33369 +Epoch: [17] [ 210/1319] eta: 0:48:30 lr: 3.0195555298905282e-05 loss: 0.0492 (0.0603) time: 2.6127 data: 0.0058 max mem: 33369 +Epoch: [17] [ 220/1319] eta: 0:48:03 lr: 3.0186534369853002e-05 loss: 0.0492 (0.0599) time: 2.6238 data: 0.0058 max mem: 33369 +Epoch: [17] [ 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data: 0.0059 max mem: 33369 +Epoch: [17] [ 390/1319] eta: 0:40:32 lr: 3.0033132656127906e-05 loss: 0.0478 (0.0602) time: 2.6081 data: 0.0059 max mem: 33369 +Epoch: [17] [ 400/1319] eta: 0:40:06 lr: 3.002410631846841e-05 loss: 0.0519 (0.0603) time: 2.5984 data: 0.0060 max mem: 33369 +Epoch: [17] [ 410/1319] eta: 0:39:39 lr: 3.0015079679282703e-05 loss: 0.0540 (0.0605) time: 2.6146 data: 0.0059 max mem: 33369 +Epoch: [17] [ 420/1319] eta: 0:39:13 lr: 3.0006052738459948e-05 loss: 0.0567 (0.0604) time: 2.6127 data: 0.0058 max mem: 33369 +Epoch: [17] [ 430/1319] eta: 0:38:47 lr: 2.999702549588924e-05 loss: 0.0478 (0.0602) time: 2.6188 data: 0.0058 max mem: 33369 +Epoch: [17] [ 440/1319] eta: 0:38:21 lr: 2.998799795145959e-05 loss: 0.0453 (0.0604) time: 2.6172 data: 0.0058 max mem: 33369 +Epoch: [17] [ 450/1319] eta: 0:37:54 lr: 2.9978970105059916e-05 loss: 0.0525 (0.0602) time: 2.6091 data: 0.0059 max mem: 33369 +Epoch: [17] [ 460/1319] eta: 0:37:28 lr: 2.9969941956579083e-05 loss: 0.0536 (0.0600) time: 2.6001 data: 0.0061 max mem: 33369 +Epoch: [17] [ 470/1319] eta: 0:37:02 lr: 2.9960913505905863e-05 loss: 0.0589 (0.0602) time: 2.6085 data: 0.0061 max mem: 33369 +Epoch: [17] [ 480/1319] eta: 0:36:35 lr: 2.995188475292896e-05 loss: 0.0618 (0.0602) time: 2.6181 data: 0.0060 max mem: 33369 +Epoch: [17] [ 490/1319] eta: 0:36:10 lr: 2.9942855697536976e-05 loss: 0.0603 (0.0604) time: 2.6281 data: 0.0057 max mem: 33369 +Epoch: [17] [ 500/1319] eta: 0:35:43 lr: 2.9933826339618466e-05 loss: 0.0603 (0.0605) time: 2.6148 data: 0.0058 max mem: 33369 +Epoch: [17] [ 510/1319] eta: 0:35:17 lr: 2.992479667906189e-05 loss: 0.0602 (0.0605) time: 2.6146 data: 0.0059 max mem: 33369 +Epoch: [17] [ 520/1319] eta: 0:34:51 lr: 2.9915766715755623e-05 loss: 0.0678 (0.0608) time: 2.6363 data: 0.0057 max mem: 33369 +Epoch: [17] [ 530/1319] eta: 0:34:26 lr: 2.990673644958798e-05 loss: 0.0618 (0.0609) time: 2.6397 data: 0.0057 max mem: 33369 +Epoch: [17] [ 540/1319] eta: 0:33:59 lr: 2.989770588044718e-05 loss: 0.0552 (0.0609) time: 2.6357 data: 0.0057 max mem: 33369 +Epoch: [17] [ 550/1319] eta: 0:33:34 lr: 2.9888675008221372e-05 loss: 0.0555 (0.0609) time: 2.6329 data: 0.0056 max mem: 33369 +Epoch: [17] [ 560/1319] eta: 0:33:07 lr: 2.9879643832798625e-05 loss: 0.0570 (0.0609) time: 2.6172 data: 0.0057 max mem: 33369 +Epoch: [17] [ 570/1319] eta: 0:32:41 lr: 2.987061235406693e-05 loss: 0.0519 (0.0609) time: 2.6123 data: 0.0059 max mem: 33369 +Epoch: [17] [ 580/1319] eta: 0:32:15 lr: 2.98615805719142e-05 loss: 0.0479 (0.0607) time: 2.6302 data: 0.0059 max mem: 33369 +Epoch: [17] [ 590/1319] eta: 0:31:49 lr: 2.9852548486228266e-05 loss: 0.0571 (0.0610) time: 2.6225 data: 0.0057 max mem: 33369 +Epoch: [17] [ 600/1319] eta: 0:31:22 lr: 2.9843516096896873e-05 loss: 0.0618 (0.0610) time: 2.6153 data: 0.0056 max mem: 33369 +Epoch: [17] [ 610/1319] eta: 0:30:56 lr: 2.98344834038077e-05 loss: 0.0594 (0.0610) time: 2.6096 data: 0.0059 max mem: 33369 +Epoch: [17] [ 620/1319] eta: 0:30:30 lr: 2.9825450406848343e-05 loss: 0.0609 (0.0610) time: 2.5974 data: 0.0059 max mem: 33369 +Epoch: [17] [ 630/1319] eta: 0:30:03 lr: 2.981641710590631e-05 loss: 0.0627 (0.0611) time: 2.6031 data: 0.0058 max mem: 33369 +Epoch: [17] [ 640/1319] eta: 0:29:37 lr: 2.9807383500869036e-05 loss: 0.0630 (0.0612) time: 2.6062 data: 0.0058 max mem: 33369 +Epoch: [17] [ 650/1319] eta: 0:29:11 lr: 2.9798349591623877e-05 loss: 0.0647 (0.0614) time: 2.6030 data: 0.0058 max mem: 33369 +Epoch: [17] [ 660/1319] eta: 0:28:45 lr: 2.9789315378058107e-05 loss: 0.0701 (0.0615) time: 2.6363 data: 0.0058 max mem: 33369 +Epoch: [17] [ 670/1319] eta: 0:28:19 lr: 2.978028086005893e-05 loss: 0.0577 (0.0615) time: 2.6360 data: 0.0058 max mem: 33369 +Epoch: [17] [ 680/1319] eta: 0:27:53 lr: 2.977124603751345e-05 loss: 0.0506 (0.0614) time: 2.6457 data: 0.0058 max mem: 33369 +Epoch: [17] [ 690/1319] eta: 0:27:27 lr: 2.9762210910308712e-05 loss: 0.0512 (0.0614) time: 2.6528 data: 0.0057 max mem: 33369 +Epoch: [17] [ 700/1319] eta: 0:27:01 lr: 2.9753175478331675e-05 loss: 0.0555 (0.0615) time: 2.6088 data: 0.0058 max mem: 33369 +Epoch: [17] [ 710/1319] eta: 0:26:34 lr: 2.97441397414692e-05 loss: 0.0515 (0.0615) time: 2.5861 data: 0.0060 max mem: 33369 +Epoch: [17] [ 720/1319] eta: 0:26:08 lr: 2.973510369960809e-05 loss: 0.0515 (0.0615) time: 2.5945 data: 0.0060 max mem: 33369 +Epoch: [17] [ 730/1319] eta: 0:25:42 lr: 2.9726067352635072e-05 loss: 0.0522 (0.0615) time: 2.6076 data: 0.0060 max mem: 33369 +Epoch: [17] [ 740/1319] eta: 0:25:15 lr: 2.971703070043676e-05 loss: 0.0514 (0.0615) time: 2.5931 data: 0.0061 max mem: 33369 +Epoch: [17] [ 750/1319] eta: 0:24:49 lr: 2.970799374289972e-05 loss: 0.0561 (0.0615) time: 2.6105 data: 0.0059 max mem: 33369 +Epoch: [17] [ 760/1319] eta: 0:24:23 lr: 2.9698956479910424e-05 loss: 0.0554 (0.0614) time: 2.6379 data: 0.0058 max mem: 33369 +Epoch: [17] [ 770/1319] eta: 0:23:57 lr: 2.9689918911355265e-05 loss: 0.0524 (0.0617) time: 2.6531 data: 0.0060 max mem: 33369 +Epoch: [17] [ 780/1319] eta: 0:23:31 lr: 2.9680881037120552e-05 loss: 0.0654 (0.0618) time: 2.6314 data: 0.0059 max mem: 33369 +Epoch: [17] [ 790/1319] eta: 0:23:04 lr: 2.9671842857092525e-05 loss: 0.0666 (0.0619) time: 2.5837 data: 0.0056 max mem: 33369 +Epoch: [17] [ 800/1319] eta: 0:22:39 lr: 2.9662804371157326e-05 loss: 0.0720 (0.0621) time: 2.6284 data: 0.0057 max mem: 33369 +Epoch: [17] [ 810/1319] eta: 0:22:13 lr: 2.9653765579201043e-05 loss: 0.0719 (0.0621) time: 2.6612 data: 0.0058 max mem: 33369 +Epoch: [17] [ 820/1319] eta: 0:21:46 lr: 2.964472648110964e-05 loss: 0.0581 (0.0621) time: 2.6350 data: 0.0057 max mem: 33369 +Epoch: [17] [ 830/1319] eta: 0:21:20 lr: 2.963568707676905e-05 loss: 0.0594 (0.0621) time: 2.6305 data: 0.0057 max mem: 33369 +Epoch: [17] [ 840/1319] eta: 0:20:54 lr: 2.962664736606507e-05 loss: 0.0582 (0.0621) time: 2.6374 data: 0.0056 max mem: 33369 +Epoch: [17] [ 850/1319] eta: 0:20:28 lr: 2.961760734888347e-05 loss: 0.0439 (0.0620) time: 2.6295 data: 0.0055 max mem: 33369 +Epoch: [17] [ 860/1319] eta: 0:20:02 lr: 2.96085670251099e-05 loss: 0.0513 (0.0620) time: 2.5908 data: 0.0056 max mem: 33369 +Epoch: [17] [ 870/1319] eta: 0:19:35 lr: 2.959952639462995e-05 loss: 0.0690 (0.0623) time: 2.5856 data: 0.0057 max mem: 33369 +Epoch: [17] [ 880/1319] eta: 0:19:09 lr: 2.9590485457329127e-05 loss: 0.0633 (0.0622) time: 2.6162 data: 0.0056 max mem: 33369 +Epoch: [17] [ 890/1319] eta: 0:18:43 lr: 2.9581444213092834e-05 loss: 0.0608 (0.0622) time: 2.6463 data: 0.0056 max mem: 33369 +Epoch: [17] [ 900/1319] eta: 0:18:17 lr: 2.957240266180642e-05 loss: 0.0590 (0.0622) time: 2.6452 data: 0.0057 max mem: 33369 +Epoch: [17] [ 910/1319] eta: 0:17:51 lr: 2.956336080335514e-05 loss: 0.0590 (0.0622) time: 2.6430 data: 0.0057 max mem: 33369 +Epoch: [17] [ 920/1319] eta: 0:17:25 lr: 2.955431863762416e-05 loss: 0.0546 (0.0622) time: 2.6301 data: 0.0057 max mem: 33369 +Epoch: [17] [ 930/1319] eta: 0:16:59 lr: 2.9545276164498587e-05 loss: 0.0498 (0.0621) time: 2.6145 data: 0.0057 max mem: 33369 +Epoch: [17] [ 940/1319] eta: 0:16:32 lr: 2.953623338386342e-05 loss: 0.0569 (0.0621) time: 2.6097 data: 0.0056 max mem: 33369 +Epoch: [17] [ 950/1319] eta: 0:16:06 lr: 2.9527190295603586e-05 loss: 0.0585 (0.0621) time: 2.6003 data: 0.0057 max mem: 33369 +Epoch: [17] [ 960/1319] eta: 0:15:40 lr: 2.9518146899603932e-05 loss: 0.0463 (0.0622) time: 2.6237 data: 0.0056 max mem: 33369 +Epoch: [17] [ 970/1319] eta: 0:15:14 lr: 2.9509103195749226e-05 loss: 0.0463 (0.0622) time: 2.6290 data: 0.0056 max mem: 33369 +Epoch: [17] [ 980/1319] eta: 0:14:47 lr: 2.9500059183924145e-05 loss: 0.0640 (0.0623) time: 2.6181 data: 0.0057 max mem: 33369 +Epoch: [17] [ 990/1319] eta: 0:14:21 lr: 2.9491014864013282e-05 loss: 0.0519 (0.0622) time: 2.6277 data: 0.0056 max mem: 33369 +Epoch: [17] [1000/1319] eta: 0:13:55 lr: 2.9481970235901164e-05 loss: 0.0555 (0.0622) time: 2.6469 data: 0.0057 max mem: 33369 +Epoch: [17] [1010/1319] eta: 0:13:29 lr: 2.9472925299472214e-05 loss: 0.0555 (0.0622) time: 2.6263 data: 0.0058 max mem: 33369 +Epoch: [17] [1020/1319] eta: 0:13:03 lr: 2.9463880054610792e-05 loss: 0.0531 (0.0622) time: 2.6022 data: 0.0058 max mem: 33369 +Epoch: [17] [1030/1319] eta: 0:12:37 lr: 2.9454834501201163e-05 loss: 0.0580 (0.0622) time: 2.6170 data: 0.0056 max mem: 33369 +Epoch: [17] [1040/1319] eta: 0:12:11 lr: 2.9445788639127496e-05 loss: 0.0582 (0.0622) time: 2.6468 data: 0.0056 max mem: 33369 +Epoch: [17] [1050/1319] eta: 0:11:44 lr: 2.943674246827392e-05 loss: 0.0544 (0.0622) time: 2.6469 data: 0.0058 max mem: 33369 +Epoch: [17] [1060/1319] eta: 0:11:18 lr: 2.9427695988524433e-05 loss: 0.0536 (0.0621) time: 2.5953 data: 0.0058 max mem: 33369 +Epoch: [17] [1070/1319] eta: 0:10:52 lr: 2.941864919976297e-05 loss: 0.0522 (0.0622) time: 2.6081 data: 0.0056 max mem: 33369 +Epoch: [17] [1080/1319] eta: 0:10:26 lr: 2.9409602101873397e-05 loss: 0.0670 (0.0622) time: 2.6206 data: 0.0057 max mem: 33369 +Epoch: [17] [1090/1319] eta: 0:09:59 lr: 2.9400554694739468e-05 loss: 0.0580 (0.0623) time: 2.6085 data: 0.0059 max mem: 33369 +Epoch: [17] [1100/1319] eta: 0:09:33 lr: 2.9391506978244877e-05 loss: 0.0554 (0.0623) time: 2.6099 data: 0.0059 max mem: 33369 +Epoch: [17] [1110/1319] eta: 0:09:07 lr: 2.9382458952273217e-05 loss: 0.0547 (0.0624) time: 2.5725 data: 0.0058 max mem: 33369 +Epoch: [17] [1120/1319] eta: 0:08:41 lr: 2.937341061670802e-05 loss: 0.0585 (0.0625) time: 2.5966 data: 0.0057 max mem: 33369 +Epoch: [17] [1130/1319] eta: 0:08:15 lr: 2.9364361971432715e-05 loss: 0.0604 (0.0625) time: 2.6255 data: 0.0058 max mem: 33369 +Epoch: [17] [1140/1319] eta: 0:07:48 lr: 2.9355313016330638e-05 loss: 0.0628 (0.0625) time: 2.6016 data: 0.0057 max mem: 33369 +Epoch: [17] [1150/1319] eta: 0:07:22 lr: 2.934626375128508e-05 loss: 0.0562 (0.0624) time: 2.5931 data: 0.0057 max mem: 33369 +Epoch: [17] [1160/1319] eta: 0:06:56 lr: 2.93372141761792e-05 loss: 0.0562 (0.0623) time: 2.5897 data: 0.0058 max mem: 33369 +Epoch: [17] [1170/1319] eta: 0:06:30 lr: 2.9328164290896108e-05 loss: 0.0601 (0.0624) time: 2.6057 data: 0.0057 max mem: 33369 +Epoch: [17] [1180/1319] eta: 0:06:03 lr: 2.9319114095318817e-05 loss: 0.0555 (0.0623) time: 2.6160 data: 0.0057 max mem: 33369 +Epoch: [17] [1190/1319] eta: 0:05:37 lr: 2.9310063589330256e-05 loss: 0.0519 (0.0623) time: 2.6161 data: 0.0058 max mem: 33369 +Epoch: [17] [1200/1319] eta: 0:05:11 lr: 2.9301012772813273e-05 loss: 0.0596 (0.0623) time: 2.6329 data: 0.0057 max mem: 33369 +Epoch: [17] [1210/1319] eta: 0:04:45 lr: 2.9291961645650624e-05 loss: 0.0554 (0.0623) time: 2.6419 data: 0.0058 max mem: 33369 +Epoch: [17] [1220/1319] eta: 0:04:19 lr: 2.9282910207724996e-05 loss: 0.0512 (0.0622) time: 2.6318 data: 0.0059 max mem: 33369 +Epoch: [17] [1230/1319] eta: 0:03:53 lr: 2.9273858458918974e-05 loss: 0.0564 (0.0622) time: 2.6307 data: 0.0059 max mem: 33369 +Epoch: [17] [1240/1319] eta: 0:03:26 lr: 2.9264806399115058e-05 loss: 0.0561 (0.0621) time: 2.6613 data: 0.0058 max mem: 33369 +Epoch: [17] [1250/1319] eta: 0:03:00 lr: 2.925575402819568e-05 loss: 0.0451 (0.0620) time: 2.6555 data: 0.0058 max mem: 33369 +Epoch: [17] [1260/1319] eta: 0:02:34 lr: 2.9246701346043183e-05 loss: 0.0477 (0.0620) time: 2.6155 data: 0.0058 max mem: 33369 +Epoch: [17] [1270/1319] eta: 0:02:08 lr: 2.9237648352539803e-05 loss: 0.0600 (0.0621) time: 2.6390 data: 0.0058 max mem: 33369 +Epoch: [17] [1280/1319] eta: 0:01:42 lr: 2.9228595047567713e-05 loss: 0.0613 (0.0622) time: 2.6600 data: 0.0057 max mem: 33369 +Epoch: [17] [1290/1319] eta: 0:01:15 lr: 2.9219541431009008e-05 loss: 0.0567 (0.0621) time: 2.6274 data: 0.0056 max mem: 33369 +Epoch: [17] [1300/1319] eta: 0:00:49 lr: 2.921048750274567e-05 loss: 0.0507 (0.0621) time: 2.6195 data: 0.0055 max mem: 33369 +Epoch: [17] [1310/1319] eta: 0:00:23 lr: 2.9201433262659623e-05 loss: 0.0503 (0.0621) time: 2.6221 data: 0.0056 max mem: 33369 +Epoch: [17] Total time: 0:57:35 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 1:52:49 time: 2.6309 data: 2.4714 max mem: 33369 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 100/2573] eta: 0:04:03 time: 0.0714 data: 0.0011 max mem: 33369 +Test: [ 200/2573] eta: 0:03:24 time: 0.0729 data: 0.0011 max mem: 33369 +Test: [ 300/2573] eta: 0:03:04 time: 0.0746 data: 0.0011 max mem: 33369 +Test: [ 400/2573] eta: 0:02:52 time: 0.0748 data: 0.0011 max mem: 33369 +Test: [ 500/2573] eta: 0:02:41 time: 0.0732 data: 0.0011 max mem: 33369 +Test: [ 600/2573] eta: 0:02:32 time: 0.0735 data: 0.0011 max mem: 33369 +Test: [ 700/2573] eta: 0:02:24 time: 0.0735 data: 0.0012 max mem: 33369 +Test: [ 800/2573] eta: 0:02:16 time: 0.0767 data: 0.0011 max mem: 33369 +Test: [ 900/2573] eta: 0:02:08 time: 0.0734 data: 0.0011 max mem: 33369 +Test: [1000/2573] eta: 0:01:59 time: 0.0734 data: 0.0011 max mem: 33369 +Test: [1100/2573] eta: 0:01:51 time: 0.0735 data: 0.0011 max mem: 33369 +Test: [1200/2573] eta: 0:01:44 time: 0.0736 data: 0.0011 max mem: 33369 +Test: [1300/2573] eta: 0:01:36 time: 0.0737 data: 0.0011 max mem: 33369 +Test: [1400/2573] eta: 0:01:28 time: 0.0720 data: 0.0011 max mem: 33369 +Test: [1500/2573] eta: 0:01:20 time: 0.0737 data: 0.0011 max mem: 33369 +Test: [1600/2573] eta: 0:01:13 time: 0.0771 data: 0.0011 max mem: 33369 +Test: [1700/2573] eta: 0:01:05 time: 0.0722 data: 0.0011 max mem: 33369 +Test: [1800/2573] eta: 0:00:58 time: 0.0756 data: 0.0011 max mem: 33369 +Test: [1900/2573] eta: 0:00:50 time: 0.0722 data: 0.0011 max mem: 33369 +Test: [2000/2573] eta: 0:00:42 time: 0.0739 data: 0.0011 max mem: 33369 +Test: [2100/2573] eta: 0:00:35 time: 0.0755 data: 0.0011 max mem: 33369 +Test: [2200/2573] eta: 0:00:27 time: 0.0756 data: 0.0011 max mem: 33369 +Test: [2300/2573] eta: 0:00:20 time: 0.0756 data: 0.0011 max mem: 33369 +Test: [2400/2573] eta: 0:00:12 time: 0.0705 data: 0.0011 max mem: 33369 +Test: [2500/2573] eta: 0:00:05 time: 0.0739 data: 0.0011 max mem: 33369 +Test: Total time: 0:03:12 +Final results: +Mean IoU is 62.94 + + precision@0.5 = 70.71 + precision@0.6 = 65.67 + precision@0.7 = 58.01 + precision@0.8 = 46.41 + precision@0.9 = 22.20 + overall IoU = 60.92 + +Average object IoU 62.93643251077046 +Overall IoU 60.92194747924805 +Better epoch: 17 + +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [18] [ 0/1319] eta: 1:34:41 lr: 2.9193284179876086e-05 loss: 0.0527 (0.0527) time: 4.3076 data: 1.6421 max mem: 33369 +Epoch: [18] [ 10/1319] eta: 1:00:17 lr: 2.9184229347001237e-05 loss: 0.0527 (0.0727) time: 2.7634 data: 0.1542 max mem: 33369 +Epoch: [18] [ 20/1319] eta: 0:58:27 lr: 2.9175174201960736e-05 loss: 0.0507 (0.0634) time: 2.6195 data: 0.0057 max mem: 33369 +Epoch: [18] [ 30/1319] eta: 0:57:34 lr: 2.9166118744636155e-05 loss: 0.0514 (0.0645) time: 2.6336 data: 0.0061 max mem: 33369 +Epoch: [18] [ 40/1319] eta: 0:56:38 lr: 2.9157062974908988e-05 loss: 0.0493 (0.0607) time: 2.6117 data: 0.0062 max mem: 33369 +Epoch: [18] [ 50/1319] eta: 0:55:59 lr: 2.9148006892660646e-05 loss: 0.0461 (0.0579) time: 2.5976 data: 0.0061 max mem: 33369 +Epoch: [18] [ 60/1319] eta: 0:55:26 lr: 2.9138950497772444e-05 loss: 0.0491 (0.0591) time: 2.6115 data: 0.0060 max mem: 33369 +Epoch: [18] [ 70/1319] eta: 0:54:54 lr: 2.9129893790125616e-05 loss: 0.0516 (0.0567) time: 2.6140 data: 0.0062 max mem: 33369 +Epoch: [18] [ 80/1319] eta: 0:54:28 lr: 2.9120836769601318e-05 loss: 0.0469 (0.0564) time: 2.6263 data: 0.0062 max mem: 33369 +Epoch: [18] [ 90/1319] eta: 0:53:58 lr: 2.9111779436080605e-05 loss: 0.0505 (0.0560) time: 2.6231 data: 0.0062 max mem: 33369 +Epoch: [18] [ 100/1319] eta: 0:53:30 lr: 2.910272178944446e-05 loss: 0.0467 (0.0568) time: 2.6142 data: 0.0061 max mem: 33369 +Epoch: [18] [ 110/1319] eta: 0:53:01 lr: 2.9093663829573763e-05 loss: 0.0575 (0.0597) time: 2.6158 data: 0.0061 max mem: 33369 +Epoch: [18] [ 120/1319] eta: 0:52:33 lr: 2.9084605556349322e-05 loss: 0.0702 (0.0602) time: 2.6152 data: 0.0062 max mem: 33369 +Epoch: [18] [ 130/1319] eta: 0:52:08 lr: 2.9075546969651845e-05 loss: 0.0560 (0.0600) time: 2.6323 data: 0.0060 max mem: 33369 +Epoch: [18] [ 140/1319] eta: 0:51:42 lr: 2.906648806936197e-05 loss: 0.0524 (0.0608) time: 2.6407 data: 0.0061 max mem: 33369 +Epoch: [18] [ 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33369 +Epoch: [18] [ 230/1319] eta: 0:47:39 lr: 2.8984943835355838e-05 loss: 0.0567 (0.0583) time: 2.5836 data: 0.0058 max mem: 33369 +Epoch: [18] [ 240/1319] eta: 0:47:12 lr: 2.8975881792557412e-05 loss: 0.0490 (0.0584) time: 2.5942 data: 0.0060 max mem: 33369 +Epoch: [18] [ 250/1319] eta: 0:46:45 lr: 2.8966819434847762e-05 loss: 0.0549 (0.0585) time: 2.6006 data: 0.0061 max mem: 33369 +Epoch: [18] [ 260/1319] eta: 0:46:18 lr: 2.8957756762106468e-05 loss: 0.0549 (0.0586) time: 2.6159 data: 0.0060 max mem: 33369 +Epoch: [18] [ 270/1319] eta: 0:45:53 lr: 2.8948693774213014e-05 loss: 0.0507 (0.0584) time: 2.6296 data: 0.0059 max mem: 33369 +Epoch: [18] [ 280/1319] eta: 0:45:25 lr: 2.8939630471046815e-05 loss: 0.0512 (0.0585) time: 2.6108 data: 0.0059 max mem: 33369 +Epoch: [18] [ 290/1319] eta: 0:44:57 lr: 2.893056685248718e-05 loss: 0.0512 (0.0584) time: 2.5825 data: 0.0061 max mem: 33369 +Epoch: [18] [ 300/1319] eta: 0:44:32 lr: 2.892150291841334e-05 loss: 0.0525 (0.0587) time: 2.6228 data: 0.0061 max mem: 33369 +Epoch: [18] [ 310/1319] eta: 0:44:05 lr: 2.891243866870445e-05 loss: 0.0532 (0.0591) time: 2.6330 data: 0.0060 max mem: 33369 +Epoch: [18] [ 320/1319] eta: 0:43:39 lr: 2.8903374103239537e-05 loss: 0.0529 (0.0592) time: 2.6116 data: 0.0059 max mem: 33369 +Epoch: [18] [ 330/1319] eta: 0:43:12 lr: 2.889430922189758e-05 loss: 0.0483 (0.0588) time: 2.6107 data: 0.0059 max mem: 33369 +Epoch: [18] [ 340/1319] eta: 0:42:47 lr: 2.8885244024557463e-05 loss: 0.0476 (0.0587) time: 2.6300 data: 0.0061 max mem: 33369 +Epoch: [18] [ 350/1319] eta: 0:42:19 lr: 2.8876178511097952e-05 loss: 0.0576 (0.0589) time: 2.6130 data: 0.0061 max mem: 33369 +Epoch: [18] [ 360/1319] eta: 0:41:54 lr: 2.886711268139775e-05 loss: 0.0553 (0.0586) time: 2.6092 data: 0.0060 max mem: 33369 +Epoch: [18] [ 370/1319] eta: 0:41:27 lr: 2.8858046535335475e-05 loss: 0.0468 (0.0585) time: 2.6260 data: 0.0061 max mem: 33369 +Epoch: [18] [ 380/1319] eta: 0:41:00 lr: 2.8848980072789644e-05 loss: 0.0506 (0.0583) time: 2.5989 data: 0.0061 max mem: 33369 +Epoch: [18] [ 390/1319] eta: 0:40:33 lr: 2.8839913293638683e-05 loss: 0.0463 (0.0584) time: 2.5931 data: 0.0059 max mem: 33369 +Epoch: [18] [ 400/1319] eta: 0:40:07 lr: 2.8830846197760937e-05 loss: 0.0579 (0.0587) time: 2.5945 data: 0.0058 max mem: 33369 +Epoch: [18] [ 410/1319] eta: 0:39:42 lr: 2.8821778785034654e-05 loss: 0.0601 (0.0591) time: 2.6341 data: 0.0061 max mem: 33369 +Epoch: [18] [ 420/1319] eta: 0:39:17 lr: 2.8812711055338004e-05 loss: 0.0601 (0.0593) time: 2.6716 data: 0.0061 max mem: 33369 +Epoch: [18] [ 430/1319] eta: 0:38:50 lr: 2.8803643008549054e-05 loss: 0.0582 (0.0593) time: 2.6284 data: 0.0058 max mem: 33369 +Epoch: [18] [ 440/1319] eta: 0:38:24 lr: 2.879457464454579e-05 loss: 0.0507 (0.0590) time: 2.6164 data: 0.0058 max mem: 33369 +Epoch: [18] [ 450/1319] eta: 0:37:57 lr: 2.8785505963206112e-05 loss: 0.0460 (0.0591) time: 2.6283 data: 0.0059 max mem: 33369 +Epoch: [18] [ 460/1319] eta: 0:37:31 lr: 2.877643696440781e-05 loss: 0.0488 (0.0591) time: 2.6074 data: 0.0058 max mem: 33369 +Epoch: [18] [ 470/1319] eta: 0:37:05 lr: 2.876736764802861e-05 loss: 0.0572 (0.0592) time: 2.6215 data: 0.0058 max mem: 33369 +Epoch: [18] [ 480/1319] eta: 0:36:38 lr: 2.8758298013946133e-05 loss: 0.0446 (0.0589) time: 2.6053 data: 0.0059 max mem: 33369 +Epoch: [18] [ 490/1319] eta: 0:36:11 lr: 2.8749228062037915e-05 loss: 0.0502 (0.0589) time: 2.5739 data: 0.0059 max mem: 33369 +Epoch: [18] [ 500/1319] eta: 0:35:44 lr: 2.87401577921814e-05 loss: 0.0567 (0.0590) time: 2.5666 data: 0.0059 max mem: 33369 +Epoch: [18] [ 510/1319] eta: 0:35:17 lr: 2.8731087204253943e-05 loss: 0.0515 (0.0587) time: 2.5805 data: 0.0060 max mem: 33369 +Epoch: [18] [ 520/1319] eta: 0:34:51 lr: 2.8722016298132803e-05 loss: 0.0492 (0.0588) time: 2.5912 data: 0.0059 max mem: 33369 +Epoch: [18] [ 530/1319] eta: 0:34:24 lr: 2.8712945073695164e-05 loss: 0.0590 (0.0588) time: 2.5747 data: 0.0058 max mem: 33369 +Epoch: [18] [ 540/1319] eta: 0:33:58 lr: 2.87038735308181e-05 loss: 0.0519 (0.0586) time: 2.5936 data: 0.0058 max mem: 33369 +Epoch: [18] [ 550/1319] eta: 0:33:32 lr: 2.8694801669378603e-05 loss: 0.0497 (0.0590) time: 2.6276 data: 0.0059 max mem: 33369 +Epoch: [18] [ 560/1319] eta: 0:33:06 lr: 2.8685729489253577e-05 loss: 0.0604 (0.0591) time: 2.6350 data: 0.0060 max mem: 33369 +Epoch: [18] [ 570/1319] eta: 0:32:40 lr: 2.8676656990319828e-05 loss: 0.0545 (0.0591) time: 2.6308 data: 0.0060 max mem: 33369 +Epoch: [18] [ 580/1319] eta: 0:32:14 lr: 2.866758417245408e-05 loss: 0.0470 (0.0589) time: 2.6253 data: 0.0061 max mem: 33369 +Epoch: [18] [ 590/1319] eta: 0:31:48 lr: 2.8658511035532965e-05 loss: 0.0498 (0.0588) time: 2.6237 data: 0.0061 max mem: 33369 +Epoch: [18] [ 600/1319] eta: 0:31:21 lr: 2.8649437579433008e-05 loss: 0.0513 (0.0588) time: 2.6032 data: 0.0058 max mem: 33369 +Epoch: [18] [ 610/1319] eta: 0:30:55 lr: 2.8640363804030673e-05 loss: 0.0582 (0.0590) time: 2.5972 data: 0.0058 max mem: 33369 +Epoch: [18] [ 620/1319] eta: 0:30:29 lr: 2.8631289709202297e-05 loss: 0.0618 (0.0592) time: 2.6281 data: 0.0061 max mem: 33369 +Epoch: [18] [ 630/1319] eta: 0:30:03 lr: 2.8622215294824162e-05 loss: 0.0581 (0.0593) time: 2.6250 data: 0.0060 max mem: 33369 +Epoch: [18] [ 640/1319] eta: 0:29:36 lr: 2.861314056077242e-05 loss: 0.0605 (0.0594) time: 2.5984 data: 0.0057 max mem: 33369 +Epoch: [18] [ 650/1319] eta: 0:29:10 lr: 2.8604065506923168e-05 loss: 0.0605 (0.0593) time: 2.6124 data: 0.0058 max mem: 33369 +Epoch: [18] [ 660/1319] eta: 0:28:44 lr: 2.859499013315239e-05 loss: 0.0538 (0.0593) time: 2.6161 data: 0.0059 max mem: 33369 +Epoch: [18] [ 670/1319] eta: 0:28:17 lr: 2.858591443933597e-05 loss: 0.0552 (0.0594) time: 2.5817 data: 0.0060 max mem: 33369 +Epoch: [18] [ 680/1319] eta: 0:27:51 lr: 2.8576838425349722e-05 loss: 0.0525 (0.0593) time: 2.5905 data: 0.0059 max mem: 33369 +Epoch: [18] [ 690/1319] eta: 0:27:25 lr: 2.8567762091069368e-05 loss: 0.0485 (0.0592) time: 2.6126 data: 0.0060 max mem: 33369 +Epoch: [18] [ 700/1319] eta: 0:26:59 lr: 2.8558685436370514e-05 loss: 0.0478 (0.0590) time: 2.6138 data: 0.0060 max mem: 33369 +Epoch: [18] [ 710/1319] eta: 0:26:33 lr: 2.854960846112869e-05 loss: 0.0478 (0.0590) time: 2.6429 data: 0.0060 max mem: 33369 +Epoch: [18] [ 720/1319] eta: 0:26:07 lr: 2.8540531165219343e-05 loss: 0.0474 (0.0589) time: 2.6392 data: 0.0060 max mem: 33369 +Epoch: [18] [ 730/1319] eta: 0:25:41 lr: 2.8531453548517806e-05 loss: 0.0455 (0.0589) time: 2.6359 data: 0.0059 max mem: 33369 +Epoch: [18] [ 740/1319] eta: 0:25:14 lr: 2.8522375610899337e-05 loss: 0.0464 (0.0589) time: 2.6204 data: 0.0057 max mem: 33369 +Epoch: [18] [ 750/1319] eta: 0:24:48 lr: 2.8513297352239087e-05 loss: 0.0545 (0.0588) time: 2.5960 data: 0.0056 max mem: 33369 +Epoch: [18] [ 760/1319] eta: 0:24:22 lr: 2.850421877241213e-05 loss: 0.0586 (0.0590) time: 2.6018 data: 0.0058 max mem: 33369 +Epoch: [18] [ 770/1319] eta: 0:23:56 lr: 2.8495139871293436e-05 loss: 0.0586 (0.0590) time: 2.5971 data: 0.0059 max mem: 33369 +Epoch: [18] [ 780/1319] eta: 0:23:30 lr: 2.8486060648757875e-05 loss: 0.0505 (0.0589) time: 2.6203 data: 0.0058 max mem: 33369 +Epoch: [18] [ 790/1319] eta: 0:23:04 lr: 2.8476981104680245e-05 loss: 0.0496 (0.0588) time: 2.6397 data: 0.0059 max mem: 33369 +Epoch: [18] [ 800/1319] eta: 0:22:37 lr: 2.846790123893523e-05 loss: 0.0498 (0.0588) time: 2.6272 data: 0.0059 max mem: 33369 +Epoch: [18] [ 810/1319] eta: 0:22:12 lr: 2.8458821051397444e-05 loss: 0.0565 (0.0589) time: 2.6320 data: 0.0059 max mem: 33369 +Epoch: [18] [ 820/1319] eta: 0:21:46 lr: 2.844974054194138e-05 loss: 0.0488 (0.0588) time: 2.6494 data: 0.0060 max mem: 33369 +Epoch: [18] [ 830/1319] eta: 0:21:19 lr: 2.844065971044146e-05 loss: 0.0467 (0.0588) time: 2.6336 data: 0.0059 max mem: 33369 +Epoch: [18] [ 840/1319] eta: 0:20:53 lr: 2.8431578556772e-05 loss: 0.0556 (0.0588) time: 2.6206 data: 0.0058 max mem: 33369 +Epoch: [18] [ 850/1319] eta: 0:20:27 lr: 2.8422497080807237e-05 loss: 0.0498 (0.0587) time: 2.6203 data: 0.0058 max mem: 33369 +Epoch: [18] [ 860/1319] eta: 0:20:01 lr: 2.8413415282421285e-05 loss: 0.0470 (0.0586) time: 2.6098 data: 0.0059 max mem: 33369 +Epoch: [18] [ 870/1319] eta: 0:19:35 lr: 2.840433316148819e-05 loss: 0.0450 (0.0585) time: 2.6277 data: 0.0059 max mem: 33369 +Epoch: [18] [ 880/1319] eta: 0:19:09 lr: 2.8395250717881906e-05 loss: 0.0470 (0.0586) time: 2.6595 data: 0.0058 max mem: 33369 +Epoch: [18] [ 890/1319] eta: 0:18:43 lr: 2.8386167951476273e-05 loss: 0.0501 (0.0586) time: 2.6410 data: 0.0058 max mem: 33369 +Epoch: [18] [ 900/1319] eta: 0:18:17 lr: 2.8377084862145048e-05 loss: 0.0501 (0.0585) time: 2.6272 data: 0.0058 max mem: 33369 +Epoch: [18] [ 910/1319] eta: 0:17:50 lr: 2.8368001449761894e-05 loss: 0.0468 (0.0585) time: 2.6254 data: 0.0059 max mem: 33369 +Epoch: [18] [ 920/1319] eta: 0:17:24 lr: 2.8358917714200377e-05 loss: 0.0467 (0.0584) time: 2.6084 data: 0.0059 max mem: 33369 +Epoch: [18] [ 930/1319] eta: 0:16:58 lr: 2.834983365533398e-05 loss: 0.0504 (0.0584) time: 2.5883 data: 0.0059 max mem: 33369 +Epoch: [18] [ 940/1319] eta: 0:16:31 lr: 2.834074927303607e-05 loss: 0.0531 (0.0585) time: 2.5783 data: 0.0057 max mem: 33369 +Epoch: [18] [ 950/1319] eta: 0:16:05 lr: 2.8331664567179933e-05 loss: 0.0573 (0.0587) time: 2.6000 data: 0.0056 max mem: 33369 +Epoch: [18] [ 960/1319] eta: 0:15:39 lr: 2.8322579537638772e-05 loss: 0.0582 (0.0587) time: 2.6284 data: 0.0058 max mem: 33369 +Epoch: [18] [ 970/1319] eta: 0:15:13 lr: 2.831349418428566e-05 loss: 0.0603 (0.0588) time: 2.6375 data: 0.0059 max mem: 33369 +Epoch: [18] [ 980/1319] eta: 0:14:47 lr: 2.830440850699361e-05 loss: 0.0603 (0.0589) time: 2.6193 data: 0.0058 max mem: 33369 +Epoch: [18] [ 990/1319] eta: 0:14:21 lr: 2.829532250563552e-05 loss: 0.0467 (0.0588) time: 2.6197 data: 0.0059 max mem: 33369 +Epoch: [18] [1000/1319] eta: 0:13:54 lr: 2.828623618008419e-05 loss: 0.0467 (0.0588) time: 2.6004 data: 0.0061 max mem: 33369 +Epoch: [18] [1010/1319] eta: 0:13:28 lr: 2.8277149530212353e-05 loss: 0.0516 (0.0588) time: 2.6012 data: 0.0060 max mem: 33369 +Epoch: [18] [1020/1319] eta: 0:13:02 lr: 2.8268062555892616e-05 loss: 0.0610 (0.0589) time: 2.6331 data: 0.0056 max mem: 33369 +Epoch: [18] [1030/1319] eta: 0:12:36 lr: 2.82589752569975e-05 loss: 0.0512 (0.0588) time: 2.6425 data: 0.0057 max mem: 33369 +Epoch: [18] [1040/1319] eta: 0:12:10 lr: 2.8249887633399437e-05 loss: 0.0512 (0.0588) time: 2.6427 data: 0.0058 max mem: 33369 +Epoch: [18] [1050/1319] eta: 0:11:44 lr: 2.8240799684970753e-05 loss: 0.0539 (0.0588) time: 2.6196 data: 0.0059 max mem: 33369 +Epoch: [18] [1060/1319] eta: 0:11:17 lr: 2.8231711411583693e-05 loss: 0.0565 (0.0588) time: 2.6018 data: 0.0060 max mem: 33369 +Epoch: [18] [1070/1319] eta: 0:10:51 lr: 2.8222622813110382e-05 loss: 0.0521 (0.0588) time: 2.5919 data: 0.0060 max mem: 33369 +Epoch: [18] [1080/1319] eta: 0:10:25 lr: 2.821353388942287e-05 loss: 0.0551 (0.0588) time: 2.5968 data: 0.0059 max mem: 33369 +Epoch: [18] [1090/1319] eta: 0:09:59 lr: 2.820444464039311e-05 loss: 0.0551 (0.0588) time: 2.6018 data: 0.0057 max mem: 33369 +Epoch: [18] [1100/1319] eta: 0:09:33 lr: 2.819535506589294e-05 loss: 0.0479 (0.0587) time: 2.5955 data: 0.0059 max mem: 33369 +Epoch: [18] [1110/1319] eta: 0:09:07 lr: 2.8186265165794125e-05 loss: 0.0479 (0.0588) time: 2.6202 data: 0.0059 max mem: 33369 +Epoch: [18] [1120/1319] eta: 0:08:40 lr: 2.817717493996831e-05 loss: 0.0546 (0.0588) time: 2.6673 data: 0.0057 max mem: 33369 +Epoch: [18] [1130/1319] eta: 0:08:14 lr: 2.816808438828707e-05 loss: 0.0550 (0.0588) time: 2.6429 data: 0.0058 max mem: 33369 +Epoch: [18] [1140/1319] eta: 0:07:48 lr: 2.8158993510621856e-05 loss: 0.0429 (0.0587) time: 2.6111 data: 0.0060 max mem: 33369 +Epoch: [18] [1150/1319] eta: 0:07:22 lr: 2.814990230684405e-05 loss: 0.0407 (0.0587) time: 2.6257 data: 0.0060 max mem: 33369 +Epoch: [18] [1160/1319] eta: 0:06:56 lr: 2.814081077682491e-05 loss: 0.0509 (0.0586) time: 2.6237 data: 0.0057 max mem: 33369 +Epoch: [18] [1170/1319] eta: 0:06:30 lr: 2.8131718920435623e-05 loss: 0.0523 (0.0586) time: 2.6096 data: 0.0056 max mem: 33369 +Epoch: [18] [1180/1319] eta: 0:06:03 lr: 2.812262673754726e-05 loss: 0.0552 (0.0587) time: 2.6007 data: 0.0057 max mem: 33369 +Epoch: [18] [1190/1319] eta: 0:05:37 lr: 2.8113534228030784e-05 loss: 0.0552 (0.0587) time: 2.5941 data: 0.0058 max mem: 33369 +Epoch: [18] [1200/1319] eta: 0:05:11 lr: 2.8104441391757102e-05 loss: 0.0550 (0.0587) time: 2.5939 data: 0.0059 max mem: 33369 +Epoch: [18] [1210/1319] eta: 0:04:45 lr: 2.809534822859698e-05 loss: 0.0506 (0.0587) time: 2.6325 data: 0.0059 max mem: 33369 +Epoch: [18] [1220/1319] eta: 0:04:19 lr: 2.8086254738421114e-05 loss: 0.0556 (0.0587) time: 2.6491 data: 0.0059 max mem: 33369 +Epoch: [18] [1230/1319] eta: 0:03:52 lr: 2.8077160921100087e-05 loss: 0.0522 (0.0587) time: 2.6084 data: 0.0058 max mem: 33369 +Epoch: [18] [1240/1319] eta: 0:03:26 lr: 2.8068066776504393e-05 loss: 0.0434 (0.0586) time: 2.5842 data: 0.0057 max mem: 33369 +Epoch: [18] [1250/1319] eta: 0:03:00 lr: 2.8058972304504428e-05 loss: 0.0478 (0.0587) time: 2.6000 data: 0.0057 max mem: 33369 +Epoch: [18] [1260/1319] eta: 0:02:34 lr: 2.8049877504970483e-05 loss: 0.0542 (0.0586) time: 2.6027 data: 0.0057 max mem: 33369 +Epoch: [18] [1270/1319] eta: 0:02:08 lr: 2.8040782377772763e-05 loss: 0.0533 (0.0587) time: 2.5848 data: 0.0058 max mem: 33369 +Epoch: [18] [1280/1319] eta: 0:01:42 lr: 2.803168692278136e-05 loss: 0.0530 (0.0586) time: 2.5968 data: 0.0058 max mem: 33369 +Epoch: [18] [1290/1319] eta: 0:01:15 lr: 2.8022591139866265e-05 loss: 0.0528 (0.0586) time: 2.6054 data: 0.0056 max mem: 33369 +Epoch: [18] [1300/1319] eta: 0:00:49 lr: 2.80134950288974e-05 loss: 0.0479 (0.0586) time: 2.6136 data: 0.0058 max mem: 33369 +Epoch: [18] [1310/1319] eta: 0:00:23 lr: 2.800439858974456e-05 loss: 0.0531 (0.0586) time: 2.6329 data: 0.0058 max mem: 33369 +Epoch: [18] Total time: 0:57:31 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 2:14:54 time: 3.1459 data: 3.0677 max mem: 33369 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 100/2573] eta: 0:04:12 time: 0.0711 data: 0.0011 max mem: 33369 +Test: [ 200/2573] eta: 0:03:28 time: 0.0728 data: 0.0011 max mem: 33369 +Test: [ 300/2573] eta: 0:03:07 time: 0.0746 data: 0.0011 max mem: 33369 +Test: [ 400/2573] eta: 0:02:53 time: 0.0747 data: 0.0011 max mem: 33369 +Test: [ 500/2573] eta: 0:02:43 time: 0.0731 data: 0.0011 max mem: 33369 +Test: [ 600/2573] eta: 0:02:33 time: 0.0732 data: 0.0011 max mem: 33369 +Test: [ 700/2573] eta: 0:02:25 time: 0.0733 data: 0.0011 max mem: 33369 +Test: [ 800/2573] eta: 0:02:16 time: 0.0766 data: 0.0011 max mem: 33369 +Test: [ 900/2573] eta: 0:02:08 time: 0.0734 data: 0.0011 max mem: 33369 +Test: [1000/2573] eta: 0:02:00 time: 0.0733 data: 0.0011 max mem: 33369 +Test: [1100/2573] eta: 0:01:52 time: 0.0734 data: 0.0011 max mem: 33369 +Test: [1200/2573] eta: 0:01:44 time: 0.0733 data: 0.0011 max mem: 33369 +Test: [1300/2573] eta: 0:01:36 time: 0.0735 data: 0.0011 max mem: 33369 +Test: [1400/2573] eta: 0:01:28 time: 0.0718 data: 0.0011 max mem: 33369 +Test: [1500/2573] eta: 0:01:21 time: 0.0734 data: 0.0011 max mem: 33369 +Test: [1600/2573] eta: 0:01:13 time: 0.0768 data: 0.0011 max mem: 33369 +Test: [1700/2573] eta: 0:01:05 time: 0.0719 data: 0.0011 max mem: 33369 +Test: [1800/2573] eta: 0:00:58 time: 0.0754 data: 0.0011 max mem: 33369 +Test: [1900/2573] eta: 0:00:50 time: 0.0721 data: 0.0011 max mem: 33369 +Test: [2000/2573] eta: 0:00:42 time: 0.0737 data: 0.0011 max mem: 33369 +Test: [2100/2573] eta: 0:00:35 time: 0.0753 data: 0.0011 max mem: 33369 +Test: [2200/2573] eta: 0:00:27 time: 0.0753 data: 0.0011 max mem: 33369 +Test: [2300/2573] eta: 0:00:20 time: 0.0752 data: 0.0011 max mem: 33369 +Test: [2400/2573] eta: 0:00:12 time: 0.0704 data: 0.0011 max mem: 33369 +Test: [2500/2573] eta: 0:00:05 time: 0.0738 data: 0.0011 max mem: 33369 +Test: Total time: 0:03:12 +Final results: +Mean IoU is 62.52 + + precision@0.5 = 70.53 + precision@0.6 = 64.89 + precision@0.7 = 57.76 + precision@0.8 = 45.28 + precision@0.9 = 21.71 + overall IoU = 60.32 + +Average object IoU 62.51569395566372 +Overall IoU 60.32378387451172 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [19] [ 0/1319] eta: 3:16:22 lr: 2.7996211513802005e-05 loss: 0.0372 (0.0372) time: 8.9327 data: 2.7885 max mem: 33369 +Epoch: [19] [ 10/1319] eta: 1:09:41 lr: 2.7987114450740563e-05 loss: 0.0504 (0.0513) time: 3.1945 data: 0.2584 max mem: 33369 +Epoch: [19] [ 20/1319] eta: 1:03:40 lr: 2.7978017059117013e-05 loss: 0.0498 (0.0487) time: 2.6413 data: 0.0054 max mem: 33369 +Epoch: [19] [ 30/1319] eta: 1:01:04 lr: 2.7968919338800786e-05 loss: 0.0448 (0.0490) time: 2.6498 data: 0.0057 max mem: 33369 +Epoch: [19] [ 40/1319] eta: 0:59:30 lr: 2.7959821289661182e-05 loss: 0.0467 (0.0498) time: 2.6354 data: 0.0060 max mem: 33369 +Epoch: [19] [ 50/1319] eta: 0:58:26 lr: 2.795072291156743e-05 loss: 0.0520 (0.0507) time: 2.6391 data: 0.0060 max mem: 33369 +Epoch: [19] [ 60/1319] eta: 0:57:19 lr: 2.7941624204388656e-05 loss: 0.0558 (0.0532) time: 2.6097 data: 0.0060 max mem: 33369 +Epoch: [19] [ 70/1319] eta: 0:56:36 lr: 2.7932525167993873e-05 loss: 0.0510 (0.0525) time: 2.6080 data: 0.0060 max mem: 33369 +Epoch: [19] [ 80/1319] eta: 0:55:54 lr: 2.7923425802252002e-05 loss: 0.0455 (0.0530) time: 2.6335 data: 0.0057 max mem: 33369 +Epoch: [19] [ 90/1319] eta: 0:55:14 lr: 2.791432610703186e-05 loss: 0.0481 (0.0533) time: 2.6176 data: 0.0058 max mem: 33369 +Epoch: [19] [ 100/1319] eta: 0:54:34 lr: 2.790522608220219e-05 loss: 0.0498 (0.0533) time: 2.6002 data: 0.0062 max mem: 33369 +Epoch: [19] [ 110/1319] eta: 0:54:00 lr: 2.789612572763159e-05 loss: 0.0522 (0.0541) time: 2.6022 data: 0.0063 max mem: 33369 +Epoch: [19] [ 120/1319] eta: 0:53:34 lr: 2.7887025043188598e-05 loss: 0.0476 (0.0539) time: 2.6547 data: 0.0061 max mem: 33369 +Epoch: [19] [ 130/1319] eta: 0:53:03 lr: 2.7877924028741625e-05 loss: 0.0470 (0.0537) time: 2.6616 data: 0.0062 max mem: 33369 +Epoch: [19] [ 140/1319] eta: 0:52:32 lr: 2.7868822684159008e-05 loss: 0.0463 (0.0539) time: 2.6290 data: 0.0061 max mem: 33369 +Epoch: [19] [ 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33369 +Epoch: [19] [ 230/1319] eta: 0:48:06 lr: 2.778689570503424e-05 loss: 0.0462 (0.0540) time: 2.6341 data: 0.0059 max mem: 33369 +Epoch: [19] [ 240/1319] eta: 0:47:41 lr: 2.7777791051830626e-05 loss: 0.0489 (0.0540) time: 2.6682 data: 0.0058 max mem: 33369 +Epoch: [19] [ 250/1319] eta: 0:47:12 lr: 2.7768686067036253e-05 loss: 0.0496 (0.0539) time: 2.6377 data: 0.0059 max mem: 33369 +Epoch: [19] [ 260/1319] eta: 0:46:44 lr: 2.775958075051822e-05 loss: 0.0498 (0.0540) time: 2.6047 data: 0.0063 max mem: 33369 +Epoch: [19] [ 270/1319] eta: 0:46:18 lr: 2.7750475102143547e-05 loss: 0.0544 (0.0540) time: 2.6377 data: 0.0060 max mem: 33369 +Epoch: [19] [ 280/1319] eta: 0:45:51 lr: 2.7741369121779126e-05 loss: 0.0495 (0.0539) time: 2.6496 data: 0.0059 max mem: 33369 +Epoch: [19] [ 290/1319] eta: 0:45:24 lr: 2.7732262809291776e-05 loss: 0.0449 (0.0537) time: 2.6381 data: 0.0061 max mem: 33369 +Epoch: [19] [ 300/1319] eta: 0:44:56 lr: 2.7723156164548194e-05 loss: 0.0451 (0.0535) time: 2.6193 data: 0.0060 max mem: 33369 +Epoch: [19] [ 310/1319] eta: 0:44:28 lr: 2.771404918741497e-05 loss: 0.0451 (0.0535) time: 2.6005 data: 0.0060 max mem: 33369 +Epoch: [19] [ 320/1319] eta: 0:44:01 lr: 2.7704941877758615e-05 loss: 0.0451 (0.0536) time: 2.6177 data: 0.0059 max mem: 33369 +Epoch: [19] [ 330/1319] eta: 0:43:34 lr: 2.7695834235445526e-05 loss: 0.0470 (0.0536) time: 2.6184 data: 0.0060 max mem: 33369 +Epoch: [19] [ 340/1319] eta: 0:43:06 lr: 2.7686726260341988e-05 loss: 0.0470 (0.0537) time: 2.6083 data: 0.0060 max mem: 33369 +Epoch: [19] [ 350/1319] eta: 0:42:40 lr: 2.7677617952314193e-05 loss: 0.0502 (0.0537) time: 2.6296 data: 0.0058 max mem: 33369 +Epoch: [19] [ 360/1319] eta: 0:42:12 lr: 2.7668509311228242e-05 loss: 0.0502 (0.0538) time: 2.6138 data: 0.0059 max mem: 33369 +Epoch: [19] [ 370/1319] eta: 0:41:46 lr: 2.7659400336950098e-05 loss: 0.0523 (0.0539) time: 2.6157 data: 0.0060 max mem: 33369 +Epoch: [19] [ 380/1319] eta: 0:41:18 lr: 2.765029102934566e-05 loss: 0.0487 (0.0539) time: 2.6244 data: 0.0062 max mem: 33369 +Epoch: [19] [ 390/1319] eta: 0:40:51 lr: 2.764118138828069e-05 loss: 0.0546 (0.0542) time: 2.6047 data: 0.0064 max mem: 33369 +Epoch: [19] [ 400/1319] eta: 0:40:24 lr: 2.763207141362088e-05 loss: 0.0610 (0.0544) time: 2.5987 data: 0.0061 max mem: 33369 +Epoch: [19] [ 410/1319] eta: 0:39:58 lr: 2.7622961105231792e-05 loss: 0.0589 (0.0545) time: 2.6156 data: 0.0058 max mem: 33369 +Epoch: [19] [ 420/1319] eta: 0:39:31 lr: 2.7613850462978895e-05 loss: 0.0399 (0.0548) time: 2.6478 data: 0.0059 max mem: 33369 +Epoch: [19] [ 430/1319] eta: 0:39:05 lr: 2.7604739486727564e-05 loss: 0.0459 (0.0547) time: 2.6378 data: 0.0060 max mem: 33369 +Epoch: [19] [ 440/1319] eta: 0:38:39 lr: 2.759562817634305e-05 loss: 0.0556 (0.0547) time: 2.6375 data: 0.0059 max mem: 33369 +Epoch: [19] [ 450/1319] eta: 0:38:12 lr: 2.7586516531690514e-05 loss: 0.0538 (0.0548) time: 2.6319 data: 0.0058 max mem: 33369 +Epoch: [19] [ 460/1319] eta: 0:37:45 lr: 2.7577404552635017e-05 loss: 0.0498 (0.0550) time: 2.6211 data: 0.0059 max mem: 33369 +Epoch: [19] [ 470/1319] eta: 0:37:19 lr: 2.7568292239041493e-05 loss: 0.0498 (0.0550) time: 2.6302 data: 0.0058 max mem: 33369 +Epoch: [19] [ 480/1319] eta: 0:36:52 lr: 2.7559179590774802e-05 loss: 0.0495 (0.0549) time: 2.6190 data: 0.0058 max mem: 33369 +Epoch: [19] [ 490/1319] eta: 0:36:26 lr: 2.755006660769968e-05 loss: 0.0526 (0.0550) time: 2.6280 data: 0.0059 max mem: 33369 +Epoch: [19] [ 500/1319] eta: 0:35:59 lr: 2.754095328968076e-05 loss: 0.0507 (0.0550) time: 2.6220 data: 0.0058 max mem: 33369 +Epoch: [19] [ 510/1319] eta: 0:35:32 lr: 2.753183963658258e-05 loss: 0.0561 (0.0554) time: 2.6040 data: 0.0057 max mem: 33369 +Epoch: [19] [ 520/1319] eta: 0:35:05 lr: 2.7522725648269566e-05 loss: 0.0538 (0.0554) time: 2.6204 data: 0.0057 max mem: 33369 +Epoch: [19] [ 530/1319] eta: 0:34:39 lr: 2.7513611324606038e-05 loss: 0.0452 (0.0555) time: 2.6237 data: 0.0057 max mem: 33369 +Epoch: [19] [ 540/1319] eta: 0:34:11 lr: 2.7504496665456215e-05 loss: 0.0418 (0.0555) time: 2.5742 data: 0.0059 max mem: 33369 +Epoch: [19] [ 550/1319] eta: 0:33:45 lr: 2.749538167068421e-05 loss: 0.0561 (0.0555) time: 2.5819 data: 0.0060 max mem: 33369 +Epoch: [19] [ 560/1319] eta: 0:33:18 lr: 2.7486266340154037e-05 loss: 0.0575 (0.0557) time: 2.6232 data: 0.0059 max mem: 33369 +Epoch: [19] [ 570/1319] eta: 0:32:52 lr: 2.74771506737296e-05 loss: 0.0537 (0.0555) time: 2.6227 data: 0.0057 max mem: 33369 +Epoch: [19] [ 580/1319] eta: 0:32:26 lr: 2.7468034671274683e-05 loss: 0.0507 (0.0555) time: 2.6430 data: 0.0056 max mem: 33369 +Epoch: [19] [ 590/1319] eta: 0:31:59 lr: 2.7458918332652984e-05 loss: 0.0462 (0.0554) time: 2.6438 data: 0.0056 max mem: 33369 +Epoch: [19] [ 600/1319] eta: 0:31:32 lr: 2.7449801657728096e-05 loss: 0.0490 (0.0554) time: 2.6105 data: 0.0057 max mem: 33369 +Epoch: [19] [ 610/1319] eta: 0:31:05 lr: 2.7440684646363496e-05 loss: 0.0477 (0.0554) time: 2.5848 data: 0.0062 max mem: 33369 +Epoch: [19] [ 620/1319] eta: 0:30:39 lr: 2.743156729842255e-05 loss: 0.0488 (0.0553) time: 2.6005 data: 0.0063 max mem: 33369 +Epoch: [19] [ 630/1319] eta: 0:30:13 lr: 2.7422449613768535e-05 loss: 0.0482 (0.0552) time: 2.6283 data: 0.0059 max mem: 33369 +Epoch: [19] [ 640/1319] eta: 0:29:46 lr: 2.7413331592264612e-05 loss: 0.0429 (0.0551) time: 2.6189 data: 0.0056 max mem: 33369 +Epoch: [19] [ 650/1319] eta: 0:29:19 lr: 2.740421323377384e-05 loss: 0.0523 (0.0551) time: 2.5917 data: 0.0057 max mem: 33369 +Epoch: [19] [ 660/1319] eta: 0:28:53 lr: 2.7395094538159166e-05 loss: 0.0478 (0.0551) time: 2.6104 data: 0.0058 max mem: 33369 +Epoch: [19] [ 670/1319] eta: 0:28:26 lr: 2.738597550528344e-05 loss: 0.0455 (0.0553) time: 2.6141 data: 0.0058 max mem: 33369 +Epoch: [19] [ 680/1319] eta: 0:28:00 lr: 2.7376856135009393e-05 loss: 0.0569 (0.0553) time: 2.5988 data: 0.0058 max mem: 33369 +Epoch: [19] [ 690/1319] eta: 0:27:34 lr: 2.736773642719965e-05 loss: 0.0506 (0.0553) time: 2.6358 data: 0.0059 max mem: 33369 +Epoch: [19] [ 700/1319] eta: 0:27:08 lr: 2.735861638171675e-05 loss: 0.0496 (0.0554) time: 2.6483 data: 0.0060 max mem: 33369 +Epoch: [19] [ 710/1319] eta: 0:26:41 lr: 2.7349495998423098e-05 loss: 0.0497 (0.0554) time: 2.6005 data: 0.0060 max mem: 33369 +Epoch: [19] [ 720/1319] eta: 0:26:14 lr: 2.7340375277181003e-05 loss: 0.0552 (0.0554) time: 2.5984 data: 0.0059 max mem: 33369 +Epoch: [19] [ 730/1319] eta: 0:25:48 lr: 2.733125421785267e-05 loss: 0.0490 (0.0554) time: 2.6198 data: 0.0058 max mem: 33369 +Epoch: [19] [ 740/1319] eta: 0:25:22 lr: 2.7322132820300196e-05 loss: 0.0488 (0.0554) time: 2.6314 data: 0.0058 max mem: 33369 +Epoch: [19] [ 750/1319] eta: 0:24:56 lr: 2.731301108438557e-05 loss: 0.0514 (0.0554) time: 2.6381 data: 0.0058 max mem: 33369 +Epoch: [19] [ 760/1319] eta: 0:24:29 lr: 2.7303889009970667e-05 loss: 0.0486 (0.0554) time: 2.6431 data: 0.0057 max mem: 33369 +Epoch: [19] [ 770/1319] eta: 0:24:03 lr: 2.7294766596917266e-05 loss: 0.0502 (0.0554) time: 2.6422 data: 0.0057 max mem: 33369 +Epoch: [19] [ 780/1319] eta: 0:23:37 lr: 2.7285643845087027e-05 loss: 0.0506 (0.0555) time: 2.6075 data: 0.0057 max mem: 33369 +Epoch: [19] [ 790/1319] eta: 0:23:10 lr: 2.7276520754341512e-05 loss: 0.0538 (0.0555) time: 2.5935 data: 0.0057 max mem: 33369 +Epoch: [19] [ 800/1319] eta: 0:22:44 lr: 2.726739732454216e-05 loss: 0.0518 (0.0555) time: 2.6111 data: 0.0056 max mem: 33369 +Epoch: [19] [ 810/1319] eta: 0:22:17 lr: 2.7258273555550322e-05 loss: 0.0428 (0.0554) time: 2.6185 data: 0.0056 max mem: 33369 +Epoch: [19] [ 820/1319] eta: 0:21:51 lr: 2.7249149447227223e-05 loss: 0.0440 (0.0555) time: 2.6458 data: 0.0055 max mem: 33369 +Epoch: [19] [ 830/1319] eta: 0:21:25 lr: 2.7240024999433987e-05 loss: 0.0479 (0.0554) time: 2.6607 data: 0.0057 max mem: 33369 +Epoch: [19] [ 840/1319] eta: 0:20:59 lr: 2.723090021203163e-05 loss: 0.0505 (0.0554) time: 2.6242 data: 0.0058 max mem: 33369 +Epoch: [19] [ 850/1319] eta: 0:20:32 lr: 2.7221775084881062e-05 loss: 0.0489 (0.0554) time: 2.6148 data: 0.0056 max mem: 33369 +Epoch: [19] [ 860/1319] eta: 0:20:06 lr: 2.7212649617843082e-05 loss: 0.0408 (0.0554) time: 2.6217 data: 0.0057 max mem: 33369 +Epoch: [19] [ 870/1319] eta: 0:19:40 lr: 2.7203523810778376e-05 loss: 0.0420 (0.0553) time: 2.6241 data: 0.0058 max mem: 33369 +Epoch: [19] [ 880/1319] eta: 0:19:13 lr: 2.7194397663547522e-05 loss: 0.0485 (0.0553) time: 2.6217 data: 0.0057 max mem: 33369 +Epoch: [19] [ 890/1319] eta: 0:18:47 lr: 2.7185271176010996e-05 loss: 0.0511 (0.0553) time: 2.6130 data: 0.0057 max mem: 33369 +Epoch: [19] [ 900/1319] eta: 0:18:21 lr: 2.7176144348029154e-05 loss: 0.0575 (0.0554) time: 2.6297 data: 0.0058 max mem: 33369 +Epoch: [19] [ 910/1319] eta: 0:17:54 lr: 2.7167017179462245e-05 loss: 0.0598 (0.0554) time: 2.6124 data: 0.0059 max mem: 33369 +Epoch: [19] [ 920/1319] eta: 0:17:28 lr: 2.7157889670170428e-05 loss: 0.0598 (0.0553) time: 2.5976 data: 0.0058 max mem: 33369 +Epoch: [19] [ 930/1319] eta: 0:17:02 lr: 2.7148761820013714e-05 loss: 0.0575 (0.0554) time: 2.6062 data: 0.0057 max mem: 33369 +Epoch: [19] [ 940/1319] eta: 0:16:35 lr: 2.7139633628852036e-05 loss: 0.0547 (0.0554) time: 2.5954 data: 0.0058 max mem: 33369 +Epoch: [19] [ 950/1319] eta: 0:16:09 lr: 2.7130505096545213e-05 loss: 0.0428 (0.0553) time: 2.5967 data: 0.0058 max mem: 33369 +Epoch: [19] [ 960/1319] eta: 0:15:42 lr: 2.712137622295293e-05 loss: 0.0417 (0.0553) time: 2.5711 data: 0.0058 max mem: 33369 +Epoch: [19] [ 970/1319] eta: 0:15:16 lr: 2.7112247007934798e-05 loss: 0.0513 (0.0554) time: 2.5812 data: 0.0057 max mem: 33369 +Epoch: [19] [ 980/1319] eta: 0:14:50 lr: 2.7103117451350296e-05 loss: 0.0513 (0.0554) time: 2.6151 data: 0.0058 max mem: 33369 +Epoch: [19] [ 990/1319] eta: 0:14:23 lr: 2.7093987553058785e-05 loss: 0.0461 (0.0554) time: 2.6013 data: 0.0059 max mem: 33369 +Epoch: [19] [1000/1319] eta: 0:13:57 lr: 2.708485731291955e-05 loss: 0.0546 (0.0554) time: 2.5950 data: 0.0058 max mem: 33369 +Epoch: [19] [1010/1319] eta: 0:13:31 lr: 2.7075726730791712e-05 loss: 0.0546 (0.0554) time: 2.6160 data: 0.0058 max mem: 33369 +Epoch: [19] [1020/1319] eta: 0:13:05 lr: 2.706659580653433e-05 loss: 0.0493 (0.0554) time: 2.6436 data: 0.0058 max mem: 33369 +Epoch: [19] [1030/1319] eta: 0:12:38 lr: 2.7057464540006328e-05 loss: 0.0521 (0.0555) time: 2.6460 data: 0.0057 max mem: 33369 +Epoch: [19] [1040/1319] eta: 0:12:12 lr: 2.7048332931066517e-05 loss: 0.0531 (0.0555) time: 2.6021 data: 0.0058 max mem: 33369 +Epoch: [19] [1050/1319] eta: 0:11:46 lr: 2.7039200979573614e-05 loss: 0.0548 (0.0556) time: 2.5750 data: 0.0059 max mem: 33369 +Epoch: [19] [1060/1319] eta: 0:11:19 lr: 2.7030068685386206e-05 loss: 0.0548 (0.0557) time: 2.5666 data: 0.0059 max mem: 33369 +Epoch: [19] [1070/1319] eta: 0:10:53 lr: 2.7020936048362782e-05 loss: 0.0534 (0.0557) time: 2.5538 data: 0.0057 max mem: 33369 +Epoch: [19] [1080/1319] eta: 0:10:27 lr: 2.7011803068361714e-05 loss: 0.0530 (0.0558) time: 2.5897 data: 0.0058 max mem: 33369 +Epoch: [19] [1090/1319] eta: 0:10:00 lr: 2.700266974524126e-05 loss: 0.0552 (0.0558) time: 2.6205 data: 0.0059 max mem: 33369 +Epoch: [19] [1100/1319] eta: 0:09:34 lr: 2.699353607885957e-05 loss: 0.0618 (0.0559) time: 2.5989 data: 0.0059 max mem: 33369 +Epoch: [19] [1110/1319] eta: 0:09:08 lr: 2.6984402069074687e-05 loss: 0.0604 (0.0560) time: 2.6109 data: 0.0059 max mem: 33369 +Epoch: [19] [1120/1319] eta: 0:08:41 lr: 2.6975267715744523e-05 loss: 0.0566 (0.0560) time: 2.6262 data: 0.0059 max mem: 33369 +Epoch: [19] [1130/1319] eta: 0:08:15 lr: 2.6966133018726902e-05 loss: 0.0548 (0.0561) time: 2.6242 data: 0.0060 max mem: 33369 +Epoch: [19] [1140/1319] eta: 0:07:49 lr: 2.6956997977879505e-05 loss: 0.0635 (0.0562) time: 2.6264 data: 0.0060 max mem: 33369 +Epoch: [19] [1150/1319] eta: 0:07:23 lr: 2.6947862593059943e-05 loss: 0.0612 (0.0562) time: 2.6108 data: 0.0057 max mem: 33369 +Epoch: [19] [1160/1319] eta: 0:06:57 lr: 2.6938726864125667e-05 loss: 0.0488 (0.0563) time: 2.6168 data: 0.0056 max mem: 33369 +Epoch: [19] [1170/1319] eta: 0:06:30 lr: 2.6929590790934063e-05 loss: 0.0594 (0.0565) time: 2.6259 data: 0.0057 max mem: 33369 +Epoch: [19] [1180/1319] eta: 0:06:04 lr: 2.6920454373342357e-05 loss: 0.0517 (0.0565) time: 2.6099 data: 0.0058 max mem: 33369 +Epoch: [19] [1190/1319] eta: 0:05:38 lr: 2.6911317611207703e-05 loss: 0.0596 (0.0565) time: 2.5967 data: 0.0058 max mem: 33369 +Epoch: [19] [1200/1319] eta: 0:05:12 lr: 2.6902180504387114e-05 loss: 0.0567 (0.0565) time: 2.5980 data: 0.0056 max mem: 33369 +Epoch: [19] [1210/1319] eta: 0:04:45 lr: 2.689304305273751e-05 loss: 0.0509 (0.0565) time: 2.6086 data: 0.0058 max mem: 33369 +Epoch: [19] [1220/1319] eta: 0:04:19 lr: 2.6883905256115667e-05 loss: 0.0543 (0.0566) time: 2.6051 data: 0.0061 max mem: 33369 +Epoch: [19] [1230/1319] eta: 0:03:53 lr: 2.687476711437828e-05 loss: 0.0543 (0.0567) time: 2.5863 data: 0.0063 max mem: 33369 +Epoch: [19] [1240/1319] eta: 0:03:27 lr: 2.6865628627381928e-05 loss: 0.0558 (0.0567) time: 2.5816 data: 0.0061 max mem: 33369 +Epoch: [19] [1250/1319] eta: 0:03:00 lr: 2.6856489794983043e-05 loss: 0.0509 (0.0566) time: 2.6078 data: 0.0058 max mem: 33369 +Epoch: [19] [1260/1319] eta: 0:02:34 lr: 2.6847350617037976e-05 loss: 0.0494 (0.0567) time: 2.6150 data: 0.0058 max mem: 33369 +Epoch: [19] [1270/1319] eta: 0:02:08 lr: 2.683821109340296e-05 loss: 0.0503 (0.0567) time: 2.6183 data: 0.0058 max mem: 33369 +Epoch: [19] [1280/1319] eta: 0:01:42 lr: 2.68290712239341e-05 loss: 0.0526 (0.0567) time: 2.6334 data: 0.0057 max mem: 33369 +Epoch: [19] [1290/1319] eta: 0:01:16 lr: 2.681993100848739e-05 loss: 0.0572 (0.0568) time: 2.6350 data: 0.0056 max mem: 33369 +Epoch: [19] [1300/1319] eta: 0:00:49 lr: 2.6810790446918727e-05 loss: 0.0669 (0.0570) time: 2.6225 data: 0.0058 max mem: 33369 +Epoch: [19] [1310/1319] eta: 0:00:23 lr: 2.680164953908387e-05 loss: 0.0654 (0.0570) time: 2.6059 data: 0.0060 max mem: 33369 +Epoch: [19] Total time: 0:57:38 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 2:35:40 time: 3.6303 data: 3.5464 max mem: 33369 +Test: [ 100/2573] eta: 0:04:24 time: 0.0714 data: 0.0011 max mem: 33369 +Test: [ 200/2573] eta: 0:03:34 time: 0.0729 data: 0.0011 max mem: 33369 +Test: [ 300/2573] eta: 0:03:11 time: 0.0745 data: 0.0011 max mem: 33369 +Test: [ 400/2573] eta: 0:02:56 time: 0.0748 data: 0.0011 max mem: 33369 +Test: [ 500/2573] eta: 0:02:45 time: 0.0731 data: 0.0011 max mem: 33369 +Test: [ 600/2573] eta: 0:02:35 time: 0.0733 data: 0.0011 max mem: 33369 +Test: [ 700/2573] eta: 0:02:26 time: 0.0734 data: 0.0011 max mem: 33369 +Test: [ 800/2573] eta: 0:02:17 time: 0.0765 data: 0.0011 max mem: 33369 +Test: [ 900/2573] eta: 0:02:09 time: 0.0734 data: 0.0011 max mem: 33369 +Test: [1000/2573] eta: 0:02:01 time: 0.0734 data: 0.0011 max mem: 33369 +Test: [1100/2573] eta: 0:01:52 time: 0.0734 data: 0.0011 max mem: 33369 +Test: [1200/2573] eta: 0:01:45 time: 0.0734 data: 0.0011 max mem: 33369 +Test: [1300/2573] eta: 0:01:37 time: 0.0735 data: 0.0011 max mem: 33369 +Test: [1400/2573] eta: 0:01:29 time: 0.0720 data: 0.0011 max mem: 33369 +Test: [1500/2573] eta: 0:01:21 time: 0.0736 data: 0.0011 max mem: 33369 +Test: [1600/2573] eta: 0:01:13 time: 0.0768 data: 0.0011 max mem: 33369 +Test: [1700/2573] eta: 0:01:06 time: 0.0720 data: 0.0011 max mem: 33369 +Test: [1800/2573] eta: 0:00:58 time: 0.0752 data: 0.0011 max mem: 33369 +Test: [1900/2573] eta: 0:00:50 time: 0.0719 data: 0.0011 max mem: 33369 +Test: [2000/2573] eta: 0:00:43 time: 0.0737 data: 0.0011 max mem: 33369 +Test: [2100/2573] eta: 0:00:35 time: 0.0754 data: 0.0011 max mem: 33369 +Test: [2200/2573] eta: 0:00:27 time: 0.0754 data: 0.0011 max mem: 33369 +Test: [2300/2573] eta: 0:00:20 time: 0.0754 data: 0.0011 max mem: 33369 +Test: [2400/2573] eta: 0:00:12 time: 0.0705 data: 0.0011 max mem: 33369 +Test: [2500/2573] eta: 0:00:05 time: 0.0737 data: 0.0011 max mem: 33369 +Test: Total time: 0:03:13 +Final results: +Mean IoU is 63.40 + + precision@0.5 = 71.41 + precision@0.6 = 65.91 + precision@0.7 = 58.68 + precision@0.8 = 47.04 + precision@0.9 = 23.33 + overall IoU = 60.98 + +Average object IoU 63.39926145852163 +Overall IoU 60.97780227661133 +Better epoch: 19 + +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [20] [ 0/1319] eta: 1:21:51 lr: 2.6793422425855603e-05 loss: 0.0453 (0.0453) time: 3.7235 data: 1.1121 max mem: 33369 +Epoch: [20] [ 10/1319] eta: 0:59:33 lr: 2.678428085971722e-05 loss: 0.0463 (0.0511) time: 2.7302 data: 0.1063 max mem: 33369 +Epoch: [20] [ 20/1319] eta: 0:57:46 lr: 2.6775138946893718e-05 loss: 0.0463 (0.0533) time: 2.6157 data: 0.0060 max mem: 33369 +Epoch: [20] [ 30/1319] eta: 0:57:04 lr: 2.6765996687240426e-05 loss: 0.0463 (0.0514) time: 2.6165 data: 0.0062 max mem: 33369 +Epoch: [20] [ 40/1319] eta: 0:56:16 lr: 2.675685408061254e-05 loss: 0.0460 (0.0506) time: 2.6104 data: 0.0061 max mem: 33369 +Epoch: [20] [ 50/1319] eta: 0:55:52 lr: 2.6747711126865168e-05 loss: 0.0463 (0.0547) time: 2.6193 data: 0.0060 max mem: 33369 +Epoch: [20] [ 60/1319] eta: 0:55:28 lr: 2.6738567825853273e-05 loss: 0.0503 (0.0549) time: 2.6505 data: 0.0059 max mem: 33369 +Epoch: [20] [ 70/1319] eta: 0:54:54 lr: 2.6729424177431713e-05 loss: 0.0475 (0.0539) time: 2.6261 data: 0.0059 max mem: 33369 +Epoch: [20] [ 80/1319] eta: 0:54:19 lr: 2.6720280181455227e-05 loss: 0.0450 (0.0524) time: 2.5914 data: 0.0060 max mem: 33369 +Epoch: [20] [ 90/1319] eta: 0:53:50 lr: 2.671113583777845e-05 loss: 0.0471 (0.0520) time: 2.5956 data: 0.0060 max mem: 33369 +Epoch: [20] [ 100/1319] eta: 0:53:22 lr: 2.670199114625589e-05 loss: 0.0481 (0.0520) time: 2.6134 data: 0.0059 max mem: 33369 +Epoch: [20] [ 110/1319] eta: 0:52:55 lr: 2.6692846106741932e-05 loss: 0.0479 (0.0517) time: 2.6170 data: 0.0058 max mem: 33369 +Epoch: [20] [ 120/1319] eta: 0:52:32 lr: 2.668370071909087e-05 loss: 0.0500 (0.0519) time: 2.6379 data: 0.0058 max mem: 33369 +Epoch: [20] [ 130/1319] eta: 0:52:05 lr: 2.6674554983156852e-05 loss: 0.0500 (0.0515) time: 2.6422 data: 0.0058 max mem: 33369 +Epoch: [20] [ 140/1319] eta: 0:51:35 lr: 2.666540889879393e-05 loss: 0.0497 (0.0520) time: 2.6065 data: 0.0060 max mem: 33369 +Epoch: [20] [ 150/1319] eta: 0:51:07 lr: 2.6656262465856026e-05 loss: 0.0542 (0.0528) time: 2.5941 data: 0.0060 max mem: 33369 +Epoch: [20] [ 160/1319] eta: 0:50:39 lr: 2.6647115684196954e-05 loss: 0.0478 (0.0528) time: 2.5977 data: 0.0059 max mem: 33369 +Epoch: [20] [ 170/1319] eta: 0:50:14 lr: 2.663796855367041e-05 loss: 0.0495 (0.0530) time: 2.6156 data: 0.0059 max mem: 33369 +Epoch: [20] [ 180/1319] eta: 0:49:50 lr: 2.662882107412996e-05 loss: 0.0540 (0.0530) time: 2.6495 data: 0.0058 max mem: 33369 +Epoch: [20] [ 190/1319] eta: 0:49:25 lr: 2.661967324542908e-05 loss: 0.0475 (0.0530) time: 2.6554 data: 0.0059 max mem: 33369 +Epoch: [20] [ 200/1319] eta: 0:48:59 lr: 2.6610525067421092e-05 loss: 0.0440 (0.0531) time: 2.6418 data: 0.0060 max mem: 33369 +Epoch: [20] [ 210/1319] eta: 0:48:33 lr: 2.6601376539959238e-05 loss: 0.0450 (0.0531) time: 2.6374 data: 0.0061 max mem: 33369 +Epoch: [20] [ 220/1319] eta: 0:48:06 lr: 2.6592227662896617e-05 loss: 0.0515 (0.0532) time: 2.6253 data: 0.0059 max mem: 33369 +Epoch: [20] [ 230/1319] eta: 0:47:40 lr: 2.658307843608621e-05 loss: 0.0473 (0.0531) time: 2.6188 data: 0.0058 max mem: 33369 +Epoch: [20] [ 240/1319] eta: 0:47:12 lr: 2.65739288593809e-05 loss: 0.0527 (0.0534) time: 2.6055 data: 0.0058 max mem: 33369 +Epoch: [20] [ 250/1319] eta: 0:46:44 lr: 2.6564778932633426e-05 loss: 0.0476 (0.0531) time: 2.5900 data: 0.0058 max mem: 33369 +Epoch: [20] [ 260/1319] eta: 0:46:17 lr: 2.655562865569643e-05 loss: 0.0411 (0.0533) time: 2.6000 data: 0.0058 max mem: 33369 +Epoch: [20] [ 270/1319] eta: 0:45:52 lr: 2.654647802842242e-05 loss: 0.0560 (0.0536) time: 2.6200 data: 0.0059 max mem: 33369 +Epoch: [20] [ 280/1319] eta: 0:45:26 lr: 2.6537327050663813e-05 loss: 0.0443 (0.0536) time: 2.6354 data: 0.0059 max mem: 33369 +Epoch: [20] [ 290/1319] eta: 0:45:00 lr: 2.6528175722272857e-05 loss: 0.0485 (0.0539) time: 2.6372 data: 0.0059 max mem: 33369 +Epoch: [20] [ 300/1319] eta: 0:44:33 lr: 2.6519024043101733e-05 loss: 0.0514 (0.0540) time: 2.6236 data: 0.0061 max mem: 33369 +Epoch: [20] [ 310/1319] eta: 0:44:06 lr: 2.6509872013002462e-05 loss: 0.0509 (0.0538) time: 2.5991 data: 0.0061 max mem: 33369 +Epoch: [20] [ 320/1319] eta: 0:43:40 lr: 2.6500719631826982e-05 loss: 0.0404 (0.0535) time: 2.6068 data: 0.0059 max mem: 33369 +Epoch: [20] [ 330/1319] eta: 0:43:12 lr: 2.649156689942709e-05 loss: 0.0404 (0.0535) time: 2.6015 data: 0.0058 max mem: 33369 +Epoch: [20] [ 340/1319] eta: 0:42:45 lr: 2.648241381565446e-05 loss: 0.0454 (0.0539) time: 2.5875 data: 0.0058 max mem: 33369 +Epoch: [20] [ 350/1319] eta: 0:42:19 lr: 2.6473260380360663e-05 loss: 0.0566 (0.0545) time: 2.6147 data: 0.0060 max mem: 33369 +Epoch: [20] [ 360/1319] eta: 0:41:52 lr: 2.6464106593397137e-05 loss: 0.0602 (0.0545) time: 2.6107 data: 0.0061 max mem: 33369 +Epoch: [20] [ 370/1319] eta: 0:41:25 lr: 2.6454952454615202e-05 loss: 0.0521 (0.0546) time: 2.5862 data: 0.0060 max mem: 33369 +Epoch: [20] [ 380/1319] eta: 0:40:59 lr: 2.6445797963866064e-05 loss: 0.0521 (0.0546) time: 2.6103 data: 0.0060 max mem: 33369 +Epoch: [20] [ 390/1319] eta: 0:40:32 lr: 2.643664312100081e-05 loss: 0.0523 (0.0545) time: 2.6036 data: 0.0060 max mem: 33369 +Epoch: [20] [ 400/1319] eta: 0:40:06 lr: 2.6427487925870388e-05 loss: 0.0492 (0.0545) time: 2.5889 data: 0.0060 max mem: 33369 +Epoch: [20] [ 410/1319] eta: 0:39:39 lr: 2.641833237832565e-05 loss: 0.0458 (0.0545) time: 2.6017 data: 0.0060 max mem: 33369 +Epoch: [20] [ 420/1319] eta: 0:39:13 lr: 2.6409176478217318e-05 loss: 0.0465 (0.0547) time: 2.6030 data: 0.0060 max mem: 33369 +Epoch: [20] [ 430/1319] eta: 0:38:46 lr: 2.640002022539598e-05 loss: 0.0532 (0.0546) time: 2.5995 data: 0.0061 max mem: 33369 +Epoch: [20] [ 440/1319] eta: 0:38:20 lr: 2.6390863619712137e-05 loss: 0.0482 (0.0546) time: 2.6193 data: 0.0061 max mem: 33369 +Epoch: [20] [ 450/1319] eta: 0:37:55 lr: 2.6381706661016125e-05 loss: 0.0530 (0.0547) time: 2.6443 data: 0.0058 max mem: 33369 +Epoch: [20] [ 460/1319] eta: 0:37:28 lr: 2.637254934915819e-05 loss: 0.0530 (0.0548) time: 2.6165 data: 0.0058 max mem: 33369 +Epoch: [20] [ 470/1319] eta: 0:37:02 lr: 2.6363391683988447e-05 loss: 0.0479 (0.0546) time: 2.5994 data: 0.0059 max mem: 33369 +Epoch: [20] [ 480/1319] eta: 0:36:36 lr: 2.6354233665356892e-05 loss: 0.0479 (0.0548) time: 2.6181 data: 0.0058 max mem: 33369 +Epoch: [20] [ 490/1319] eta: 0:36:10 lr: 2.6345075293113398e-05 loss: 0.0508 (0.0547) time: 2.6259 data: 0.0057 max mem: 33369 +Epoch: [20] [ 500/1319] eta: 0:35:43 lr: 2.633591656710771e-05 loss: 0.0447 (0.0547) time: 2.6087 data: 0.0058 max mem: 33369 +Epoch: [20] [ 510/1319] eta: 0:35:17 lr: 2.6326757487189457e-05 loss: 0.0447 (0.0547) time: 2.6195 data: 0.0057 max mem: 33369 +Epoch: [20] [ 520/1319] eta: 0:34:51 lr: 2.6317598053208148e-05 loss: 0.0491 (0.0546) time: 2.6341 data: 0.0059 max mem: 33369 +Epoch: [20] [ 530/1319] eta: 0:34:25 lr: 2.6308438265013168e-05 loss: 0.0477 (0.0546) time: 2.6264 data: 0.0061 max mem: 33369 +Epoch: [20] [ 540/1319] eta: 0:34:00 lr: 2.6299278122453785e-05 loss: 0.0447 (0.0545) time: 2.6474 data: 0.0058 max mem: 33369 +Epoch: [20] [ 550/1319] eta: 0:33:33 lr: 2.629011762537913e-05 loss: 0.0466 (0.0545) time: 2.6247 data: 0.0056 max mem: 33369 +Epoch: [20] [ 560/1319] eta: 0:33:07 lr: 2.628095677363822e-05 loss: 0.0495 (0.0545) time: 2.6087 data: 0.0057 max mem: 33369 +Epoch: [20] [ 570/1319] eta: 0:32:41 lr: 2.627179556707995e-05 loss: 0.0437 (0.0545) time: 2.6293 data: 0.0058 max mem: 33369 +Epoch: [20] [ 580/1319] eta: 0:32:15 lr: 2.6262634005553095e-05 loss: 0.0422 (0.0543) time: 2.6204 data: 0.0059 max mem: 33369 +Epoch: [20] [ 590/1319] eta: 0:31:48 lr: 2.6253472088906295e-05 loss: 0.0389 (0.0542) time: 2.6109 data: 0.0058 max mem: 33369 +Epoch: [20] [ 600/1319] eta: 0:31:22 lr: 2.624430981698809e-05 loss: 0.0437 (0.0541) time: 2.5880 data: 0.0060 max mem: 33369 +Epoch: [20] [ 610/1319] eta: 0:30:55 lr: 2.6235147189646863e-05 loss: 0.0508 (0.0549) time: 2.5826 data: 0.0062 max mem: 33369 +Epoch: [20] [ 620/1319] eta: 0:30:29 lr: 2.6225984206730902e-05 loss: 0.0479 (0.0547) time: 2.5989 data: 0.0060 max mem: 33369 +Epoch: [20] [ 630/1319] eta: 0:30:02 lr: 2.621682086808836e-05 loss: 0.0387 (0.0546) time: 2.6015 data: 0.0060 max mem: 33369 +Epoch: [20] [ 640/1319] eta: 0:29:36 lr: 2.620765717356726e-05 loss: 0.0466 (0.0545) time: 2.5891 data: 0.0060 max mem: 33369 +Epoch: [20] [ 650/1319] eta: 0:29:10 lr: 2.6198493123015528e-05 loss: 0.0479 (0.0544) time: 2.6007 data: 0.0060 max mem: 33369 +Epoch: [20] [ 660/1319] eta: 0:28:44 lr: 2.6189328716280927e-05 loss: 0.0461 (0.0545) time: 2.6303 data: 0.0059 max mem: 33369 +Epoch: [20] [ 670/1319] eta: 0:28:18 lr: 2.618016395321112e-05 loss: 0.0495 (0.0544) time: 2.6274 data: 0.0059 max mem: 33369 +Epoch: [20] [ 680/1319] eta: 0:27:52 lr: 2.6170998833653637e-05 loss: 0.0495 (0.0545) time: 2.6176 data: 0.0060 max mem: 33369 +Epoch: [20] [ 690/1319] eta: 0:27:25 lr: 2.616183335745589e-05 loss: 0.0477 (0.0544) time: 2.6058 data: 0.0060 max mem: 33369 +Epoch: [20] [ 700/1319] eta: 0:26:59 lr: 2.615266752446517e-05 loss: 0.0423 (0.0543) time: 2.6087 data: 0.0058 max mem: 33369 +Epoch: [20] [ 710/1319] eta: 0:26:33 lr: 2.614350133452863e-05 loss: 0.0405 (0.0542) time: 2.6213 data: 0.0058 max mem: 33369 +Epoch: [20] [ 720/1319] eta: 0:26:07 lr: 2.6134334787493302e-05 loss: 0.0465 (0.0541) time: 2.6224 data: 0.0060 max mem: 33369 +Epoch: [20] [ 730/1319] eta: 0:25:41 lr: 2.6125167883206104e-05 loss: 0.0455 (0.0541) time: 2.6207 data: 0.0060 max mem: 33369 +Epoch: [20] [ 740/1319] eta: 0:25:15 lr: 2.61160006215138e-05 loss: 0.0491 (0.0541) time: 2.6216 data: 0.0059 max mem: 33369 +Epoch: [20] [ 750/1319] eta: 0:24:48 lr: 2.610683300226307e-05 loss: 0.0497 (0.0542) time: 2.6226 data: 0.0057 max mem: 33369 +Epoch: [20] [ 760/1319] eta: 0:24:22 lr: 2.6097665025300437e-05 loss: 0.0452 (0.0541) time: 2.6291 data: 0.0058 max mem: 33369 +Epoch: [20] [ 770/1319] eta: 0:23:56 lr: 2.608849669047231e-05 loss: 0.0409 (0.0540) time: 2.6471 data: 0.0060 max mem: 33369 +Epoch: [20] [ 780/1319] eta: 0:23:30 lr: 2.6079327997624963e-05 loss: 0.0467 (0.0542) time: 2.6160 data: 0.0059 max mem: 33369 +Epoch: [20] [ 790/1319] eta: 0:23:04 lr: 2.6070158946604555e-05 loss: 0.0549 (0.0542) time: 2.5970 data: 0.0058 max mem: 33369 +Epoch: [20] [ 800/1319] eta: 0:22:38 lr: 2.6060989537257118e-05 loss: 0.0549 (0.0542) time: 2.6296 data: 0.0059 max mem: 33369 +Epoch: [20] [ 810/1319] eta: 0:22:12 lr: 2.6051819769428553e-05 loss: 0.0520 (0.0542) time: 2.6217 data: 0.0059 max mem: 33369 +Epoch: [20] [ 820/1319] eta: 0:21:45 lr: 2.604264964296463e-05 loss: 0.0520 (0.0543) time: 2.6064 data: 0.0058 max mem: 33369 +Epoch: [20] [ 830/1319] eta: 0:21:19 lr: 2.6033479157711e-05 loss: 0.0525 (0.0544) time: 2.6341 data: 0.0058 max mem: 33369 +Epoch: [20] [ 840/1319] eta: 0:20:53 lr: 2.6024308313513185e-05 loss: 0.0526 (0.0544) time: 2.6507 data: 0.0060 max mem: 33369 +Epoch: [20] [ 850/1319] eta: 0:20:27 lr: 2.601513711021658e-05 loss: 0.0525 (0.0544) time: 2.6306 data: 0.0060 max mem: 33369 +Epoch: [20] [ 860/1319] eta: 0:20:01 lr: 2.6005965547666454e-05 loss: 0.0514 (0.0544) time: 2.6298 data: 0.0060 max mem: 33369 +Epoch: [20] [ 870/1319] eta: 0:19:35 lr: 2.599679362570795e-05 loss: 0.0455 (0.0543) time: 2.6367 data: 0.0060 max mem: 33369 +Epoch: [20] [ 880/1319] eta: 0:19:09 lr: 2.598762134418607e-05 loss: 0.0441 (0.0542) time: 2.6275 data: 0.0059 max mem: 33369 +Epoch: [20] [ 890/1319] eta: 0:18:43 lr: 2.5978448702945707e-05 loss: 0.0406 (0.0540) time: 2.6388 data: 0.0058 max mem: 33369 +Epoch: [20] [ 900/1319] eta: 0:18:17 lr: 2.596927570183162e-05 loss: 0.0424 (0.0540) time: 2.6423 data: 0.0059 max mem: 33369 +Epoch: [20] [ 910/1319] eta: 0:17:50 lr: 2.5960102340688436e-05 loss: 0.0457 (0.0539) time: 2.6107 data: 0.0058 max mem: 33369 +Epoch: [20] [ 920/1319] eta: 0:17:24 lr: 2.5950928619360655e-05 loss: 0.0446 (0.0540) time: 2.5963 data: 0.0059 max mem: 33369 +Epoch: [20] [ 930/1319] eta: 0:16:58 lr: 2.5941754537692653e-05 loss: 0.0446 (0.0540) time: 2.6201 data: 0.0061 max mem: 33369 +Epoch: [20] [ 940/1319] eta: 0:16:32 lr: 2.5932580095528662e-05 loss: 0.0407 (0.0539) time: 2.6315 data: 0.0060 max mem: 33369 +Epoch: [20] [ 950/1319] eta: 0:16:06 lr: 2.5923405292712815e-05 loss: 0.0408 (0.0539) time: 2.6471 data: 0.0059 max mem: 33369 +Epoch: [20] [ 960/1319] eta: 0:15:40 lr: 2.5914230129089094e-05 loss: 0.0466 (0.0539) time: 2.6448 data: 0.0058 max mem: 33369 +Epoch: [20] [ 970/1319] eta: 0:15:14 lr: 2.590505460450136e-05 loss: 0.0526 (0.0540) time: 2.6192 data: 0.0059 max mem: 33369 +Epoch: [20] [ 980/1319] eta: 0:14:47 lr: 2.589587871879333e-05 loss: 0.0443 (0.0540) time: 2.6250 data: 0.0060 max mem: 33369 +Epoch: [20] [ 990/1319] eta: 0:14:21 lr: 2.5886702471808617e-05 loss: 0.0438 (0.0541) time: 2.6377 data: 0.0057 max mem: 33369 +Epoch: [20] [1000/1319] eta: 0:13:55 lr: 2.5877525863390684e-05 loss: 0.0422 (0.0540) time: 2.6473 data: 0.0059 max mem: 33369 +Epoch: [20] [1010/1319] eta: 0:13:29 lr: 2.586834889338287e-05 loss: 0.0417 (0.0540) time: 2.6418 data: 0.0061 max mem: 33369 +Epoch: [20] [1020/1319] eta: 0:13:03 lr: 2.58591715616284e-05 loss: 0.0443 (0.0540) time: 2.6164 data: 0.0058 max mem: 33369 +Epoch: [20] [1030/1319] eta: 0:12:37 lr: 2.584999386797035e-05 loss: 0.0456 (0.0539) time: 2.6258 data: 0.0057 max mem: 33369 +Epoch: [20] [1040/1319] eta: 0:12:11 lr: 2.5840815812251663e-05 loss: 0.0478 (0.0539) time: 2.6401 data: 0.0058 max mem: 33369 +Epoch: [20] [1050/1319] eta: 0:11:44 lr: 2.583163739431517e-05 loss: 0.0495 (0.0539) time: 2.6316 data: 0.0059 max mem: 33369 +Epoch: [20] [1060/1319] eta: 0:11:18 lr: 2.582245861400355e-05 loss: 0.0449 (0.0538) time: 2.6257 data: 0.0057 max mem: 33369 +Epoch: [20] [1070/1319] eta: 0:10:52 lr: 2.5813279471159375e-05 loss: 0.0408 (0.0537) time: 2.6378 data: 0.0057 max mem: 33369 +Epoch: [20] [1080/1319] eta: 0:10:26 lr: 2.5804099965625085e-05 loss: 0.0486 (0.0537) time: 2.6133 data: 0.0057 max mem: 33369 +Epoch: [20] [1090/1319] eta: 0:10:00 lr: 2.5794920097242954e-05 loss: 0.0511 (0.0538) time: 2.6068 data: 0.0058 max mem: 33369 +Epoch: [20] [1100/1319] eta: 0:09:33 lr: 2.5785739865855164e-05 loss: 0.0481 (0.0537) time: 2.6503 data: 0.0060 max mem: 33369 +Epoch: [20] [1110/1319] eta: 0:09:07 lr: 2.5776559271303753e-05 loss: 0.0450 (0.0537) time: 2.6264 data: 0.0060 max mem: 33369 +Epoch: [20] [1120/1319] eta: 0:08:41 lr: 2.5767378313430623e-05 loss: 0.0450 (0.0537) time: 2.6073 data: 0.0059 max mem: 33369 +Epoch: [20] [1130/1319] eta: 0:08:15 lr: 2.5758196992077554e-05 loss: 0.0528 (0.0539) time: 2.6011 data: 0.0058 max mem: 33369 +Epoch: [20] [1140/1319] eta: 0:07:48 lr: 2.574901530708619e-05 loss: 0.0550 (0.0539) time: 2.5945 data: 0.0059 max mem: 33369 +Epoch: [20] [1150/1319] eta: 0:07:22 lr: 2.573983325829803e-05 loss: 0.0550 (0.0540) time: 2.6254 data: 0.0058 max mem: 33369 +Epoch: [20] [1160/1319] eta: 0:06:56 lr: 2.573065084555446e-05 loss: 0.0513 (0.0540) time: 2.6369 data: 0.0056 max mem: 33369 +Epoch: [20] [1170/1319] eta: 0:06:30 lr: 2.572146806869673e-05 loss: 0.0488 (0.0541) time: 2.6376 data: 0.0058 max mem: 33369 +Epoch: [20] [1180/1319] eta: 0:06:04 lr: 2.5712284927565954e-05 loss: 0.0440 (0.0541) time: 2.6331 data: 0.0061 max mem: 33369 +Epoch: [20] [1190/1319] eta: 0:05:38 lr: 2.5703101422003118e-05 loss: 0.0470 (0.0542) time: 2.6200 data: 0.0059 max mem: 33369 +Epoch: [20] [1200/1319] eta: 0:05:11 lr: 2.569391755184906e-05 loss: 0.0524 (0.0542) time: 2.6034 data: 0.0057 max mem: 33369 +Epoch: [20] [1210/1319] eta: 0:04:45 lr: 2.5684733316944508e-05 loss: 0.0550 (0.0542) time: 2.6024 data: 0.0057 max mem: 33369 +Epoch: [20] [1220/1319] eta: 0:04:19 lr: 2.5675548717130043e-05 loss: 0.0455 (0.0543) time: 2.6129 data: 0.0057 max mem: 33369 +Epoch: [20] [1230/1319] eta: 0:03:53 lr: 2.5666363752246116e-05 loss: 0.0455 (0.0542) time: 2.6214 data: 0.0058 max mem: 33369 +Epoch: [20] [1240/1319] eta: 0:03:26 lr: 2.5657178422133044e-05 loss: 0.0536 (0.0543) time: 2.5976 data: 0.0059 max mem: 33369 +Epoch: [20] [1250/1319] eta: 0:03:00 lr: 2.564799272663101e-05 loss: 0.0587 (0.0544) time: 2.5716 data: 0.0058 max mem: 33369 +Epoch: [20] [1260/1319] eta: 0:02:34 lr: 2.5638806665580068e-05 loss: 0.0518 (0.0544) time: 2.6009 data: 0.0057 max mem: 33369 +Epoch: [20] [1270/1319] eta: 0:02:08 lr: 2.5629620238820134e-05 loss: 0.0470 (0.0544) time: 2.6193 data: 0.0057 max mem: 33369 +Epoch: [20] [1280/1319] eta: 0:01:42 lr: 2.562043344619099e-05 loss: 0.0468 (0.0544) time: 2.6194 data: 0.0058 max mem: 33369 +Epoch: [20] [1290/1319] eta: 0:01:15 lr: 2.5611246287532285e-05 loss: 0.0468 (0.0543) time: 2.6289 data: 0.0059 max mem: 33369 +Epoch: [20] [1300/1319] eta: 0:00:49 lr: 2.560205876268355e-05 loss: 0.0497 (0.0544) time: 2.6253 data: 0.0057 max mem: 33369 +Epoch: [20] [1310/1319] eta: 0:00:23 lr: 2.5592870871484144e-05 loss: 0.0497 (0.0544) time: 2.6328 data: 0.0057 max mem: 33369 +Epoch: [20] Total time: 0:57:36 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 2:02:33 time: 2.8580 data: 2.7801 max mem: 33369 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 100/2573] eta: 0:04:05 time: 0.0711 data: 0.0011 max mem: 33369 +Test: [ 200/2573] eta: 0:03:25 time: 0.0729 data: 0.0012 max mem: 33369 +Test: [ 300/2573] eta: 0:03:05 time: 0.0746 data: 0.0011 max mem: 33369 +Test: [ 400/2573] eta: 0:02:52 time: 0.0748 data: 0.0011 max mem: 33369 +Test: [ 500/2573] eta: 0:02:42 time: 0.0732 data: 0.0011 max mem: 33369 +Test: [ 600/2573] eta: 0:02:32 time: 0.0733 data: 0.0011 max mem: 33369 +Test: [ 700/2573] eta: 0:02:24 time: 0.0735 data: 0.0011 max mem: 33369 +Test: [ 800/2573] eta: 0:02:16 time: 0.0766 data: 0.0011 max mem: 33369 +Test: [ 900/2573] eta: 0:02:08 time: 0.0734 data: 0.0011 max mem: 33369 +Test: [1000/2573] eta: 0:02:00 time: 0.0735 data: 0.0011 max mem: 33369 +Test: [1100/2573] eta: 0:01:52 time: 0.0736 data: 0.0011 max mem: 33369 +Test: [1200/2573] eta: 0:01:44 time: 0.0735 data: 0.0011 max mem: 33369 +Test: [1300/2573] eta: 0:01:36 time: 0.0736 data: 0.0011 max mem: 33369 +Test: [1400/2573] eta: 0:01:28 time: 0.0719 data: 0.0011 max mem: 33369 +Test: [1500/2573] eta: 0:01:20 time: 0.0735 data: 0.0011 max mem: 33369 +Test: [1600/2573] eta: 0:01:13 time: 0.0769 data: 0.0011 max mem: 33369 +Test: [1700/2573] eta: 0:01:05 time: 0.0719 data: 0.0011 max mem: 33369 +Test: [1800/2573] eta: 0:00:58 time: 0.0753 data: 0.0011 max mem: 33369 +Test: [1900/2573] eta: 0:00:50 time: 0.0719 data: 0.0011 max mem: 33369 +Test: [2000/2573] eta: 0:00:42 time: 0.0736 data: 0.0011 max mem: 33369 +Test: [2100/2573] eta: 0:00:35 time: 0.0755 data: 0.0011 max mem: 33369 +Test: [2200/2573] eta: 0:00:27 time: 0.0754 data: 0.0011 max mem: 33369 +Test: [2300/2573] eta: 0:00:20 time: 0.0754 data: 0.0011 max mem: 33369 +Test: [2400/2573] eta: 0:00:12 time: 0.0705 data: 0.0011 max mem: 33369 +Test: [2500/2573] eta: 0:00:05 time: 0.0739 data: 0.0011 max mem: 33369 +Test: Total time: 0:03:12 +Final results: +Mean IoU is 63.23 + + precision@0.5 = 71.16 + precision@0.6 = 65.99 + precision@0.7 = 58.95 + precision@0.8 = 47.08 + precision@0.9 = 23.10 + overall IoU = 60.96 + +Average object IoU 63.23044073267591 +Overall IoU 60.961795806884766 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [21] [ 0/1319] eta: 3:26:22 lr: 2.5584601456041995e-05 loss: 0.0491 (0.0491) time: 9.3878 data: 1.9819 max mem: 33369 +Epoch: [21] [ 10/1319] eta: 1:11:53 lr: 2.5575412868333344e-05 loss: 0.0578 (0.0572) time: 3.2955 data: 0.1855 max mem: 33369 +Epoch: [21] [ 20/1319] eta: 1:04:13 lr: 2.5566223913807464e-05 loss: 0.0520 (0.0564) time: 2.6457 data: 0.0054 max mem: 33369 +Epoch: [21] [ 30/1319] eta: 1:01:06 lr: 2.5557034592303224e-05 loss: 0.0479 (0.0573) time: 2.5968 data: 0.0055 max mem: 33369 +Epoch: [21] [ 40/1319] eta: 0:59:33 lr: 2.5547844903659336e-05 loss: 0.0496 (0.0566) time: 2.6132 data: 0.0059 max mem: 33369 +Epoch: [21] [ 50/1319] eta: 0:58:25 lr: 2.5538654847714393e-05 loss: 0.0417 (0.0547) time: 2.6349 data: 0.0058 max mem: 33369 +Epoch: [21] [ 60/1319] eta: 0:57:34 lr: 2.552946442430683e-05 loss: 0.0477 (0.0541) time: 2.6400 data: 0.0059 max mem: 33369 +Epoch: [21] [ 70/1319] eta: 0:56:44 lr: 2.552027363327497e-05 loss: 0.0517 (0.0554) time: 2.6329 data: 0.0059 max mem: 33369 +Epoch: [21] [ 80/1319] eta: 0:56:03 lr: 2.551108247445699e-05 loss: 0.0442 (0.0544) time: 2.6273 data: 0.0059 max mem: 33369 +Epoch: [21] [ 90/1319] eta: 0:55:14 lr: 2.5501890947690927e-05 loss: 0.0465 (0.0544) time: 2.5929 data: 0.0059 max mem: 33369 +Epoch: [21] [ 100/1319] eta: 0:54:35 lr: 2.5492699052814688e-05 loss: 0.0465 (0.0547) time: 2.5755 data: 0.0059 max mem: 33369 +Epoch: [21] [ 110/1319] eta: 0:53:56 lr: 2.548350678966605e-05 loss: 0.0439 (0.0538) time: 2.5875 data: 0.0059 max mem: 33369 +Epoch: [21] [ 120/1319] eta: 0:53:21 lr: 2.547431415808263e-05 loss: 0.0435 (0.0532) time: 2.5832 data: 0.0058 max mem: 33369 +Epoch: [21] [ 130/1319] eta: 0:52:48 lr: 2.5465121157901932e-05 loss: 0.0427 (0.0521) time: 2.5981 data: 0.0058 max mem: 33369 +Epoch: [21] [ 140/1319] eta: 0:52:15 lr: 2.5455927788961316e-05 loss: 0.0406 (0.0525) time: 2.5920 data: 0.0059 max mem: 33369 +Epoch: [21] [ 150/1319] eta: 0:51:50 lr: 2.5446734051098e-05 loss: 0.0445 (0.0520) time: 2.6315 data: 0.0059 max mem: 33369 +Epoch: [21] [ 160/1319] eta: 0:51:20 lr: 2.5437539944149068e-05 loss: 0.0507 (0.0523) time: 2.6481 data: 0.0058 max mem: 33369 +Epoch: [21] [ 170/1319] eta: 0:50:49 lr: 2.542834546795147e-05 loss: 0.0535 (0.0522) time: 2.6026 data: 0.0059 max mem: 33369 +Epoch: [21] [ 180/1319] eta: 0:50:19 lr: 2.5419150622342014e-05 loss: 0.0535 (0.0529) time: 2.5960 data: 0.0060 max mem: 33369 +Epoch: [21] [ 190/1319] eta: 0:49:48 lr: 2.5409955407157366e-05 loss: 0.0422 (0.0523) time: 2.5900 data: 0.0061 max mem: 33369 +Epoch: [21] [ 200/1319] eta: 0:49:21 lr: 2.5400759822234066e-05 loss: 0.0389 (0.0517) time: 2.6093 data: 0.0061 max mem: 33369 +Epoch: [21] [ 210/1319] eta: 0:48:52 lr: 2.539156386740852e-05 loss: 0.0361 (0.0513) time: 2.6173 data: 0.0060 max mem: 33369 +Epoch: [21] [ 220/1319] eta: 0:48:25 lr: 2.538236754251696e-05 loss: 0.0414 (0.0510) time: 2.6144 data: 0.0060 max mem: 33369 +Epoch: 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2.6164 data: 0.0059 max mem: 33369 +Epoch: [21] [ 390/1319] eta: 0:40:42 lr: 2.5225973239922274e-05 loss: 0.0403 (0.0511) time: 2.6243 data: 0.0056 max mem: 33369 +Epoch: [21] [ 400/1319] eta: 0:40:16 lr: 2.5216770225684038e-05 loss: 0.0403 (0.0512) time: 2.6378 data: 0.0056 max mem: 33369 +Epoch: [21] [ 410/1319] eta: 0:39:50 lr: 2.520756683824219e-05 loss: 0.0424 (0.0513) time: 2.6404 data: 0.0058 max mem: 33369 +Epoch: [21] [ 420/1319] eta: 0:39:23 lr: 2.5198363077430187e-05 loss: 0.0485 (0.0513) time: 2.6396 data: 0.0058 max mem: 33369 +Epoch: [21] [ 430/1319] eta: 0:38:57 lr: 2.5189158943081348e-05 loss: 0.0485 (0.0513) time: 2.6269 data: 0.0057 max mem: 33369 +Epoch: [21] [ 440/1319] eta: 0:38:30 lr: 2.5179954435028824e-05 loss: 0.0513 (0.0517) time: 2.6199 data: 0.0058 max mem: 33369 +Epoch: [21] [ 450/1319] eta: 0:38:03 lr: 2.517074955310566e-05 loss: 0.0424 (0.0515) time: 2.5961 data: 0.0058 max mem: 33369 +Epoch: [21] [ 460/1319] eta: 0:37:37 lr: 2.5161544297144735e-05 loss: 0.0433 (0.0515) time: 2.6134 data: 0.0058 max mem: 33369 +Epoch: [21] [ 470/1319] eta: 0:37:11 lr: 2.5152338666978798e-05 loss: 0.0436 (0.0514) time: 2.6506 data: 0.0058 max mem: 33369 +Epoch: [21] [ 480/1319] eta: 0:36:45 lr: 2.5143132662440454e-05 loss: 0.0448 (0.0514) time: 2.6473 data: 0.0058 max mem: 33369 +Epoch: [21] [ 490/1319] eta: 0:36:18 lr: 2.513392628336215e-05 loss: 0.0526 (0.0516) time: 2.6065 data: 0.0057 max mem: 33369 +Epoch: [21] [ 500/1319] eta: 0:35:52 lr: 2.5124719529576212e-05 loss: 0.0546 (0.0516) time: 2.5978 data: 0.0057 max mem: 33369 +Epoch: [21] [ 510/1319] eta: 0:35:26 lr: 2.51155124009148e-05 loss: 0.0403 (0.0516) time: 2.6352 data: 0.0057 max mem: 33369 +Epoch: [21] [ 520/1319] eta: 0:35:00 lr: 2.5106304897209954e-05 loss: 0.0403 (0.0518) time: 2.6397 data: 0.0057 max mem: 33369 +Epoch: [21] [ 530/1319] eta: 0:34:33 lr: 2.5097097018293553e-05 loss: 0.0465 (0.0516) time: 2.6190 data: 0.0059 max mem: 33369 +Epoch: [21] [ 540/1319] eta: 0:34:07 lr: 2.508788876399733e-05 loss: 0.0438 (0.0516) time: 2.6368 data: 0.0060 max mem: 33369 +Epoch: [21] [ 550/1319] eta: 0:33:40 lr: 2.5078680134152888e-05 loss: 0.0434 (0.0516) time: 2.6244 data: 0.0060 max mem: 33369 +Epoch: [21] [ 560/1319] eta: 0:33:14 lr: 2.5069471128591682e-05 loss: 0.0434 (0.0514) time: 2.6182 data: 0.0059 max mem: 33369 +Epoch: [21] [ 570/1319] eta: 0:32:47 lr: 2.5060261747145013e-05 loss: 0.0452 (0.0514) time: 2.6099 data: 0.0057 max mem: 33369 +Epoch: [21] [ 580/1319] eta: 0:32:21 lr: 2.5051051989644047e-05 loss: 0.0395 (0.0514) time: 2.5889 data: 0.0058 max mem: 33369 +Epoch: [21] [ 590/1319] eta: 0:31:55 lr: 2.504184185591981e-05 loss: 0.0395 (0.0513) time: 2.6277 data: 0.0060 max mem: 33369 +Epoch: [21] [ 600/1319] eta: 0:31:28 lr: 2.503263134580316e-05 loss: 0.0446 (0.0515) time: 2.6025 data: 0.0059 max mem: 33369 +Epoch: [21] [ 610/1319] eta: 0:31:01 lr: 2.502342045912483e-05 loss: 0.0413 (0.0513) time: 2.5797 data: 0.0058 max mem: 33369 +Epoch: [21] [ 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data: 0.0059 max mem: 33369 +Epoch: [21] [ 780/1319] eta: 0:23:33 lr: 2.4866777606924187e-05 loss: 0.0530 (0.0513) time: 2.6155 data: 0.0060 max mem: 33369 +Epoch: [21] [ 790/1319] eta: 0:23:07 lr: 2.4857559913023423e-05 loss: 0.0528 (0.0514) time: 2.6331 data: 0.0062 max mem: 33369 +Epoch: [21] [ 800/1319] eta: 0:22:41 lr: 2.4848341839316978e-05 loss: 0.0477 (0.0514) time: 2.6610 data: 0.0060 max mem: 33369 +Epoch: [21] [ 810/1319] eta: 0:22:15 lr: 2.483912338563262e-05 loss: 0.0425 (0.0514) time: 2.6678 data: 0.0058 max mem: 33369 +Epoch: [21] [ 820/1319] eta: 0:21:49 lr: 2.4829904551797996e-05 loss: 0.0416 (0.0514) time: 2.6299 data: 0.0056 max mem: 33369 +Epoch: [21] [ 830/1319] eta: 0:21:23 lr: 2.4820685337640587e-05 loss: 0.0578 (0.0516) time: 2.6011 data: 0.0057 max mem: 33369 +Epoch: [21] [ 840/1319] eta: 0:20:56 lr: 2.481146574298773e-05 loss: 0.0578 (0.0518) time: 2.5931 data: 0.0057 max mem: 33369 +Epoch: [21] [ 850/1319] eta: 0:20:30 lr: 2.480224576766661e-05 loss: 0.0503 (0.0518) time: 2.5976 data: 0.0057 max mem: 33369 +Epoch: [21] [ 860/1319] eta: 0:20:04 lr: 2.4793025411504282e-05 loss: 0.0453 (0.0518) time: 2.6087 data: 0.0058 max mem: 33369 +Epoch: [21] [ 870/1319] eta: 0:19:37 lr: 2.4783804674327604e-05 loss: 0.0453 (0.0519) time: 2.6035 data: 0.0057 max mem: 33369 +Epoch: [21] [ 880/1319] eta: 0:19:11 lr: 2.4774583555963328e-05 loss: 0.0429 (0.0519) time: 2.6251 data: 0.0057 max mem: 33369 +Epoch: [21] [ 890/1319] eta: 0:18:45 lr: 2.4765362056238035e-05 loss: 0.0416 (0.0518) time: 2.6412 data: 0.0057 max mem: 33369 +Epoch: [21] [ 900/1319] eta: 0:18:19 lr: 2.4756140174978167e-05 loss: 0.0505 (0.0519) time: 2.6320 data: 0.0058 max mem: 33369 +Epoch: [21] [ 910/1319] eta: 0:17:53 lr: 2.4746917912010012e-05 loss: 0.0550 (0.0519) time: 2.6391 data: 0.0058 max mem: 33369 +Epoch: [21] [ 920/1319] eta: 0:17:26 lr: 2.4737695267159685e-05 loss: 0.0487 (0.0520) time: 2.6270 data: 0.0058 max mem: 33369 +Epoch: [21] [ 930/1319] eta: 0:17:00 lr: 2.4728472240253183e-05 loss: 0.0442 (0.0520) time: 2.6345 data: 0.0057 max mem: 33369 +Epoch: [21] [ 940/1319] eta: 0:16:34 lr: 2.4719248831116334e-05 loss: 0.0430 (0.0520) time: 2.6373 data: 0.0056 max mem: 33369 +Epoch: [21] [ 950/1319] eta: 0:16:08 lr: 2.4710025039574813e-05 loss: 0.0507 (0.0520) time: 2.6159 data: 0.0056 max mem: 33369 +Epoch: [21] [ 960/1319] eta: 0:15:42 lr: 2.4700800865454158e-05 loss: 0.0451 (0.0519) time: 2.6302 data: 0.0059 max mem: 33369 +Epoch: [21] [ 970/1319] eta: 0:15:15 lr: 2.469157630857973e-05 loss: 0.0511 (0.0520) time: 2.6080 data: 0.0060 max mem: 33369 +Epoch: [21] [ 980/1319] eta: 0:14:49 lr: 2.4682351368776758e-05 loss: 0.0488 (0.0519) time: 2.6155 data: 0.0058 max mem: 33369 +Epoch: [21] [ 990/1319] eta: 0:14:23 lr: 2.467312604587031e-05 loss: 0.0415 (0.0520) time: 2.6234 data: 0.0058 max mem: 33369 +Epoch: [21] [1000/1319] eta: 0:13:56 lr: 2.4663900339685314e-05 loss: 0.0473 (0.0521) time: 2.6122 data: 0.0059 max mem: 33369 +Epoch: [21] [1010/1319] eta: 0:13:30 lr: 2.4654674250046523e-05 loss: 0.0534 (0.0522) time: 2.5992 data: 0.0059 max mem: 33369 +Epoch: [21] [1020/1319] eta: 0:13:04 lr: 2.464544777677856e-05 loss: 0.0526 (0.0522) time: 2.5843 data: 0.0058 max mem: 33369 +Epoch: [21] [1030/1319] eta: 0:12:38 lr: 2.4636220919705875e-05 loss: 0.0439 (0.0523) time: 2.6444 data: 0.0058 max mem: 33369 +Epoch: [21] [1040/1319] eta: 0:12:11 lr: 2.4626993678652773e-05 loss: 0.0463 (0.0523) time: 2.6416 data: 0.0059 max mem: 33369 +Epoch: [21] [1050/1319] eta: 0:11:45 lr: 2.4617766053443412e-05 loss: 0.0440 (0.0522) time: 2.6016 data: 0.0060 max mem: 33369 +Epoch: [21] [1060/1319] eta: 0:11:19 lr: 2.4608538043901786e-05 loss: 0.0440 (0.0522) time: 2.5987 data: 0.0060 max mem: 33369 +Epoch: [21] [1070/1319] eta: 0:10:52 lr: 2.4599309649851742e-05 loss: 0.0434 (0.0521) time: 2.5947 data: 0.0059 max mem: 33369 +Epoch: [21] [1080/1319] eta: 0:10:26 lr: 2.4590080871116966e-05 loss: 0.0434 (0.0521) time: 2.5959 data: 0.0058 max mem: 33369 +Epoch: [21] [1090/1319] eta: 0:10:00 lr: 2.4580851707520996e-05 loss: 0.0409 (0.0520) time: 2.6226 data: 0.0058 max mem: 33369 +Epoch: [21] [1100/1319] eta: 0:09:34 lr: 2.457162215888721e-05 loss: 0.0392 (0.0520) time: 2.6209 data: 0.0058 max mem: 33369 +Epoch: [21] [1110/1319] eta: 0:09:08 lr: 2.456239222503884e-05 loss: 0.0434 (0.0520) time: 2.6077 data: 0.0058 max mem: 33369 +Epoch: [21] [1120/1319] eta: 0:08:41 lr: 2.455316190579896e-05 loss: 0.0491 (0.0519) time: 2.6344 data: 0.0058 max mem: 33369 +Epoch: [21] [1130/1319] eta: 0:08:15 lr: 2.4543931200990468e-05 loss: 0.0465 (0.0520) time: 2.6399 data: 0.0059 max mem: 33369 +Epoch: [21] [1140/1319] eta: 0:07:49 lr: 2.4534700110436136e-05 loss: 0.0440 (0.0519) time: 2.6098 data: 0.0060 max mem: 33369 +Epoch: [21] [1150/1319] eta: 0:07:23 lr: 2.452546863395857e-05 loss: 0.0414 (0.0520) time: 2.6202 data: 0.0061 max mem: 33369 +Epoch: [21] [1160/1319] eta: 0:06:56 lr: 2.451623677138022e-05 loss: 0.0431 (0.0519) time: 2.6384 data: 0.0060 max mem: 33369 +Epoch: [21] [1170/1319] eta: 0:06:30 lr: 2.4507004522523372e-05 loss: 0.0545 (0.0520) time: 2.6093 data: 0.0058 max mem: 33369 +Epoch: [21] [1180/1319] eta: 0:06:04 lr: 2.4497771887210175e-05 loss: 0.0457 (0.0519) time: 2.5938 data: 0.0057 max mem: 33369 +Epoch: [21] [1190/1319] eta: 0:05:38 lr: 2.4488538865262596e-05 loss: 0.0412 (0.0518) time: 2.6030 data: 0.0055 max mem: 33369 +Epoch: [21] [1200/1319] eta: 0:05:11 lr: 2.4479305456502462e-05 loss: 0.0496 (0.0520) time: 2.6037 data: 0.0057 max mem: 33369 +Epoch: [21] [1210/1319] eta: 0:04:45 lr: 2.4470071660751444e-05 loss: 0.0503 (0.0519) time: 2.5922 data: 0.0060 max mem: 33369 +Epoch: [21] [1220/1319] eta: 0:04:19 lr: 2.446083747783105e-05 loss: 0.0529 (0.0520) time: 2.5870 data: 0.0061 max mem: 33369 +Epoch: [21] [1230/1319] eta: 0:03:53 lr: 2.4451602907562637e-05 loss: 0.0469 (0.0520) time: 2.6017 data: 0.0059 max mem: 33369 +Epoch: [21] [1240/1319] eta: 0:03:27 lr: 2.4442367949767393e-05 loss: 0.0462 (0.0520) time: 2.6274 data: 0.0058 max mem: 33369 +Epoch: [21] [1250/1319] eta: 0:03:00 lr: 2.4433132604266355e-05 loss: 0.0493 (0.0521) time: 2.6190 data: 0.0059 max mem: 33369 +Epoch: [21] [1260/1319] eta: 0:02:34 lr: 2.442389687088041e-05 loss: 0.0443 (0.0521) time: 2.6110 data: 0.0058 max mem: 33369 +Epoch: [21] [1270/1319] eta: 0:02:08 lr: 2.441466074943027e-05 loss: 0.0436 (0.0520) time: 2.6201 data: 0.0059 max mem: 33369 +Epoch: [21] [1280/1319] eta: 0:01:42 lr: 2.440542423973651e-05 loss: 0.0429 (0.0520) time: 2.5979 data: 0.0059 max mem: 33369 +Epoch: [21] [1290/1319] eta: 0:01:15 lr: 2.439618734161953e-05 loss: 0.0383 (0.0520) time: 2.5822 data: 0.0059 max mem: 33369 +Epoch: [21] [1300/1319] eta: 0:00:49 lr: 2.4386950054899575e-05 loss: 0.0464 (0.0520) time: 2.6059 data: 0.0059 max mem: 33369 +Epoch: [21] [1310/1319] eta: 0:00:23 lr: 2.4377712379396728e-05 loss: 0.0494 (0.0520) time: 2.5934 data: 0.0057 max mem: 33369 +Epoch: [21] Total time: 0:57:36 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 2:07:36 time: 2.9758 data: 2.8968 max mem: 33369 +Test: [ 100/2573] eta: 0:04:08 time: 0.0711 data: 0.0011 max mem: 33369 +Test: [ 200/2573] eta: 0:03:26 time: 0.0729 data: 0.0011 max mem: 33369 +Test: [ 300/2573] eta: 0:03:06 time: 0.0746 data: 0.0011 max mem: 33369 +Test: [ 400/2573] eta: 0:02:53 time: 0.0748 data: 0.0011 max mem: 33369 +Test: [ 500/2573] eta: 0:02:42 time: 0.0731 data: 0.0011 max mem: 33369 +Test: [ 600/2573] eta: 0:02:33 time: 0.0733 data: 0.0011 max mem: 33369 +Test: [ 700/2573] eta: 0:02:24 time: 0.0733 data: 0.0011 max mem: 33369 +Test: [ 800/2573] eta: 0:02:16 time: 0.0765 data: 0.0011 max mem: 33369 +Test: [ 900/2573] eta: 0:02:08 time: 0.0732 data: 0.0011 max mem: 33369 +Test: [1000/2573] eta: 0:02:00 time: 0.0733 data: 0.0011 max mem: 33369 +Test: [1100/2573] eta: 0:01:52 time: 0.0734 data: 0.0011 max mem: 33369 +Test: [1200/2573] eta: 0:01:44 time: 0.0735 data: 0.0011 max mem: 33369 +Test: [1300/2573] eta: 0:01:36 time: 0.0735 data: 0.0011 max mem: 33369 +Test: [1400/2573] eta: 0:01:28 time: 0.0718 data: 0.0011 max mem: 33369 +Test: [1500/2573] eta: 0:01:20 time: 0.0736 data: 0.0011 max mem: 33369 +Test: [1600/2573] eta: 0:01:13 time: 0.0769 data: 0.0011 max mem: 33369 +Test: [1700/2573] eta: 0:01:05 time: 0.0719 data: 0.0011 max mem: 33369 +Test: [1800/2573] eta: 0:00:58 time: 0.0752 data: 0.0011 max mem: 33369 +Test: [1900/2573] eta: 0:00:50 time: 0.0720 data: 0.0012 max mem: 33369 +Test: [2000/2573] eta: 0:00:42 time: 0.0736 data: 0.0011 max mem: 33369 +Test: [2100/2573] eta: 0:00:35 time: 0.0752 data: 0.0011 max mem: 33369 +Test: [2200/2573] eta: 0:00:27 time: 0.0752 data: 0.0011 max mem: 33369 +Test: [2300/2573] eta: 0:00:20 time: 0.0752 data: 0.0011 max mem: 33369 +Test: [2400/2573] eta: 0:00:12 time: 0.0703 data: 0.0011 max mem: 33369 +Test: [2500/2573] eta: 0:00:05 time: 0.0737 data: 0.0011 max mem: 33369 +Test: Total time: 0:03:12 +Final results: +Mean IoU is 63.23 + + precision@0.5 = 71.53 + precision@0.6 = 65.91 + precision@0.7 = 59.07 + precision@0.8 = 47.65 + precision@0.9 = 23.00 + overall IoU = 61.19 + +Average object IoU 63.22654640386295 +Overall IoU 61.18701934814453 +Better epoch: 21 + +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [22] [ 0/1319] eta: 1:25:52 lr: 2.4369398138885975e-05 loss: 0.0474 (0.0474) time: 3.9064 data: 1.3090 max mem: 33369 +Epoch: [22] [ 10/1319] eta: 1:00:00 lr: 2.436015972419942e-05 loss: 0.0474 (0.0471) time: 2.7508 data: 0.1240 max mem: 33369 +Epoch: [22] [ 20/1319] eta: 0:58:45 lr: 2.4350920920207323e-05 loss: 0.0444 (0.0474) time: 2.6544 data: 0.0056 max mem: 33369 +Epoch: [22] [ 30/1319] eta: 0:57:23 lr: 2.4341681726729162e-05 loss: 0.0381 (0.0476) time: 2.6281 data: 0.0060 max mem: 33369 +Epoch: [22] [ 40/1319] eta: 0:56:55 lr: 2.4332442143584247e-05 loss: 0.0429 (0.0495) time: 2.6239 data: 0.0063 max mem: 33369 +Epoch: [22] [ 50/1319] eta: 0:56:05 lr: 2.4323202170591704e-05 loss: 0.0481 (0.0500) time: 2.6227 data: 0.0063 max mem: 33369 +Epoch: [22] [ 60/1319] eta: 0:55:33 lr: 2.4313961807570534e-05 loss: 0.0462 (0.0492) time: 2.6009 data: 0.0062 max mem: 33369 +Epoch: [22] [ 70/1319] eta: 0:54:57 lr: 2.430472105433956e-05 loss: 0.0398 (0.0487) time: 2.6080 data: 0.0060 max mem: 33369 +Epoch: [22] [ 80/1319] eta: 0:54:26 lr: 2.4295479910717442e-05 loss: 0.0398 (0.0482) time: 2.6038 data: 0.0060 max mem: 33369 +Epoch: [22] [ 90/1319] eta: 0:53:54 lr: 2.4286238376522685e-05 loss: 0.0390 (0.0515) time: 2.6048 data: 0.0060 max mem: 33369 +Epoch: [22] [ 100/1319] eta: 0:53:26 lr: 2.4276996451573638e-05 loss: 0.0467 (0.0518) time: 2.6065 data: 0.0060 max mem: 33369 +Epoch: [22] [ 110/1319] eta: 0:53:01 lr: 2.426775413568847e-05 loss: 0.0474 (0.0516) time: 2.6286 data: 0.0061 max mem: 33369 +Epoch: [22] [ 120/1319] eta: 0:52:31 lr: 2.4258511428685206e-05 loss: 0.0465 (0.0511) time: 2.6149 data: 0.0060 max mem: 33369 +Epoch: [22] [ 130/1319] eta: 0:52:01 lr: 2.4249268330381702e-05 loss: 0.0465 (0.0519) time: 2.5881 data: 0.0059 max mem: 33369 +Epoch: [22] [ 140/1319] eta: 0:51:35 lr: 2.4240024840595657e-05 loss: 0.0473 (0.0519) time: 2.6096 data: 0.0059 max mem: 33369 +Epoch: [22] [ 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data: 0.0060 max mem: 33369 +Epoch: [22] [ 310/1319] eta: 0:44:06 lr: 2.4082825439961318e-05 loss: 0.0442 (0.0501) time: 2.6369 data: 0.0060 max mem: 33369 +Epoch: [22] [ 320/1319] eta: 0:43:41 lr: 2.4073574872129434e-05 loss: 0.0426 (0.0500) time: 2.6475 data: 0.0058 max mem: 33369 +Epoch: [22] [ 330/1319] eta: 0:43:16 lr: 2.4064323909320154e-05 loss: 0.0426 (0.0502) time: 2.6582 data: 0.0060 max mem: 33369 +Epoch: [22] [ 340/1319] eta: 0:42:50 lr: 2.405507255134789e-05 loss: 0.0467 (0.0504) time: 2.6478 data: 0.0063 max mem: 33369 +Epoch: [22] [ 350/1319] eta: 0:42:24 lr: 2.404582079802688e-05 loss: 0.0438 (0.0502) time: 2.6380 data: 0.0061 max mem: 33369 +Epoch: [22] [ 360/1319] eta: 0:41:59 lr: 2.4036568649171213e-05 loss: 0.0465 (0.0501) time: 2.6583 data: 0.0060 max mem: 33369 +Epoch: [22] [ 370/1319] eta: 0:41:33 lr: 2.402731610459478e-05 loss: 0.0513 (0.0504) time: 2.6596 data: 0.0059 max mem: 33369 +Epoch: [22] [ 380/1319] eta: 0:41:07 lr: 2.401806316411133e-05 loss: 0.0414 (0.0503) time: 2.6337 data: 0.0058 max mem: 33369 +Epoch: [22] [ 390/1319] eta: 0:40:41 lr: 2.400880982753445e-05 loss: 0.0400 (0.0504) time: 2.6384 data: 0.0057 max mem: 33369 +Epoch: [22] [ 400/1319] eta: 0:40:14 lr: 2.399955609467753e-05 loss: 0.0508 (0.0505) time: 2.6268 data: 0.0059 max mem: 33369 +Epoch: [22] [ 410/1319] eta: 0:39:48 lr: 2.3990301965353823e-05 loss: 0.0513 (0.0505) time: 2.6104 data: 0.0060 max mem: 33369 +Epoch: [22] [ 420/1319] eta: 0:39:21 lr: 2.39810474393764e-05 loss: 0.0452 (0.0503) time: 2.6258 data: 0.0058 max mem: 33369 +Epoch: [22] [ 430/1319] eta: 0:38:55 lr: 2.3971792516558155e-05 loss: 0.0355 (0.0502) time: 2.6220 data: 0.0058 max mem: 33369 +Epoch: [22] [ 440/1319] eta: 0:38:28 lr: 2.3962537196711826e-05 loss: 0.0440 (0.0503) time: 2.6068 data: 0.0062 max mem: 33369 +Epoch: [22] [ 450/1319] eta: 0:38:02 lr: 2.3953281479649982e-05 loss: 0.0480 (0.0501) time: 2.6190 data: 0.0061 max mem: 33369 +Epoch: [22] [ 460/1319] eta: 0:37:36 lr: 2.394402536518502e-05 loss: 0.0399 (0.0500) time: 2.6306 data: 0.0059 max mem: 33369 +Epoch: [22] [ 470/1319] eta: 0:37:10 lr: 2.3934768853129168e-05 loss: 0.0376 (0.0498) time: 2.6263 data: 0.0059 max mem: 33369 +Epoch: [22] [ 480/1319] eta: 0:36:44 lr: 2.3925511943294477e-05 loss: 0.0376 (0.0498) time: 2.6378 data: 0.0058 max mem: 33369 +Epoch: [22] [ 490/1319] eta: 0:36:17 lr: 2.3916254635492843e-05 loss: 0.0429 (0.0497) time: 2.6282 data: 0.0057 max mem: 33369 +Epoch: [22] [ 500/1319] eta: 0:35:51 lr: 2.390699692953598e-05 loss: 0.0429 (0.0496) time: 2.6131 data: 0.0059 max mem: 33369 +Epoch: [22] [ 510/1319] eta: 0:35:24 lr: 2.3897738825235443e-05 loss: 0.0438 (0.0496) time: 2.6110 data: 0.0060 max mem: 33369 +Epoch: [22] [ 520/1319] eta: 0:34:57 lr: 2.3888480322402605e-05 loss: 0.0495 (0.0496) time: 2.6036 data: 0.0060 max mem: 33369 +Epoch: [22] [ 530/1319] eta: 0:34:31 lr: 2.3879221420848673e-05 loss: 0.0495 (0.0496) time: 2.6129 data: 0.0059 max mem: 33369 +Epoch: [22] [ 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33369 +Epoch: [22] [ 620/1319] eta: 0:30:33 lr: 2.379587333317862e-05 loss: 0.0480 (0.0493) time: 2.6241 data: 0.0057 max mem: 33369 +Epoch: [22] [ 630/1319] eta: 0:30:07 lr: 2.3786610433992487e-05 loss: 0.0449 (0.0493) time: 2.6284 data: 0.0057 max mem: 33369 +Epoch: [22] [ 640/1319] eta: 0:29:41 lr: 2.3777347133997216e-05 loss: 0.0379 (0.0492) time: 2.6284 data: 0.0057 max mem: 33369 +Epoch: [22] [ 650/1319] eta: 0:29:14 lr: 2.3768083433001952e-05 loss: 0.0410 (0.0494) time: 2.6304 data: 0.0058 max mem: 33369 +Epoch: [22] [ 660/1319] eta: 0:28:48 lr: 2.375881933081567e-05 loss: 0.0415 (0.0493) time: 2.6251 data: 0.0057 max mem: 33369 +Epoch: [22] [ 670/1319] eta: 0:28:22 lr: 2.3749554827247157e-05 loss: 0.0399 (0.0492) time: 2.6044 data: 0.0056 max mem: 33369 +Epoch: [22] [ 680/1319] eta: 0:27:55 lr: 2.3740289922105044e-05 loss: 0.0399 (0.0492) time: 2.6098 data: 0.0059 max mem: 33369 +Epoch: [22] [ 690/1319] eta: 0:27:29 lr: 2.3731024615197766e-05 loss: 0.0399 (0.0490) time: 2.6226 data: 0.0059 max mem: 33369 +Epoch: [22] [ 700/1319] eta: 0:27:03 lr: 2.3721758906333604e-05 loss: 0.0462 (0.0491) time: 2.6171 data: 0.0057 max mem: 33369 +Epoch: [22] [ 710/1319] eta: 0:26:37 lr: 2.3712492795320653e-05 loss: 0.0474 (0.0491) time: 2.6256 data: 0.0059 max mem: 33369 +Epoch: [22] [ 720/1319] eta: 0:26:11 lr: 2.3703226281966838e-05 loss: 0.0458 (0.0492) time: 2.6352 data: 0.0058 max mem: 33369 +Epoch: [22] [ 730/1319] eta: 0:25:44 lr: 2.36939593660799e-05 loss: 0.0477 (0.0492) time: 2.6085 data: 0.0057 max mem: 33369 +Epoch: [22] [ 740/1319] eta: 0:25:18 lr: 2.3684692047467423e-05 loss: 0.0492 (0.0493) time: 2.6392 data: 0.0058 max mem: 33369 +Epoch: [22] [ 750/1319] eta: 0:24:52 lr: 2.3675424325936787e-05 loss: 0.0492 (0.0493) time: 2.6559 data: 0.0059 max mem: 33369 +Epoch: [22] [ 760/1319] eta: 0:24:26 lr: 2.3666156201295225e-05 loss: 0.0431 (0.0492) time: 2.6223 data: 0.0059 max mem: 33369 +Epoch: [22] [ 770/1319] eta: 0:23:59 lr: 2.3656887673349775e-05 loss: 0.0365 (0.0491) time: 2.6061 data: 0.0058 max mem: 33369 +Epoch: [22] [ 780/1319] eta: 0:23:33 lr: 2.364761874190731e-05 loss: 0.0353 (0.0491) time: 2.5974 data: 0.0058 max mem: 33369 +Epoch: [22] [ 790/1319] eta: 0:23:07 lr: 2.363834940677452e-05 loss: 0.0458 (0.0491) time: 2.6079 data: 0.0060 max mem: 33369 +Epoch: [22] [ 800/1319] eta: 0:22:40 lr: 2.3629079667757912e-05 loss: 0.0477 (0.0491) time: 2.5988 data: 0.0059 max mem: 33369 +Epoch: [22] [ 810/1319] eta: 0:22:14 lr: 2.361980952466383e-05 loss: 0.0477 (0.0491) time: 2.6058 data: 0.0059 max mem: 33369 +Epoch: [22] [ 820/1319] eta: 0:21:48 lr: 2.3610538977298433e-05 loss: 0.0426 (0.0490) time: 2.6197 data: 0.0059 max mem: 33369 +Epoch: [22] [ 830/1319] eta: 0:21:22 lr: 2.3601268025467702e-05 loss: 0.0390 (0.0489) time: 2.6234 data: 0.0058 max mem: 33369 +Epoch: [22] [ 840/1319] eta: 0:20:55 lr: 2.3591996668977443e-05 loss: 0.0370 (0.0488) time: 2.6203 data: 0.0059 max mem: 33369 +Epoch: [22] [ 850/1319] eta: 0:20:29 lr: 2.3582724907633285e-05 loss: 0.0420 (0.0488) time: 2.6041 data: 0.0060 max mem: 33369 +Epoch: [22] [ 860/1319] eta: 0:20:03 lr: 2.3573452741240666e-05 loss: 0.0455 (0.0489) time: 2.6202 data: 0.0060 max mem: 33369 +Epoch: [22] [ 870/1319] eta: 0:19:37 lr: 2.3564180169604865e-05 loss: 0.0462 (0.0489) time: 2.6517 data: 0.0059 max mem: 33369 +Epoch: [22] [ 880/1319] eta: 0:19:11 lr: 2.3554907192530968e-05 loss: 0.0504 (0.0491) time: 2.6278 data: 0.0058 max mem: 33369 +Epoch: [22] [ 890/1319] eta: 0:18:44 lr: 2.3545633809823888e-05 loss: 0.0504 (0.0492) time: 2.5990 data: 0.0058 max mem: 33369 +Epoch: [22] [ 900/1319] eta: 0:18:18 lr: 2.353636002128836e-05 loss: 0.0418 (0.0492) time: 2.6186 data: 0.0058 max mem: 33369 +Epoch: [22] [ 910/1319] eta: 0:17:52 lr: 2.3527085826728933e-05 loss: 0.0412 (0.0491) time: 2.6329 data: 0.0057 max mem: 33369 +Epoch: [22] [ 920/1319] eta: 0:17:26 lr: 2.351781122594998e-05 loss: 0.0515 (0.0492) time: 2.6125 data: 0.0058 max mem: 33369 +Epoch: [22] [ 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33369 +Epoch: [22] [1010/1319] eta: 0:13:29 lr: 2.3434321506693e-05 loss: 0.0397 (0.0490) time: 2.5836 data: 0.0057 max mem: 33369 +Epoch: [22] [1020/1319] eta: 0:13:03 lr: 2.342504283291958e-05 loss: 0.0438 (0.0490) time: 2.6048 data: 0.0059 max mem: 33369 +Epoch: [22] [1030/1319] eta: 0:12:36 lr: 2.3415763750762803e-05 loss: 0.0440 (0.0490) time: 2.6260 data: 0.0059 max mem: 33369 +Epoch: [22] [1040/1319] eta: 0:12:10 lr: 2.3406484260024864e-05 loss: 0.0385 (0.0489) time: 2.6272 data: 0.0058 max mem: 33369 +Epoch: [22] [1050/1319] eta: 0:11:44 lr: 2.3397204360507778e-05 loss: 0.0474 (0.0489) time: 2.6166 data: 0.0060 max mem: 33369 +Epoch: [22] [1060/1319] eta: 0:11:18 lr: 2.3387924052013375e-05 loss: 0.0427 (0.0488) time: 2.6057 data: 0.0060 max mem: 33369 +Epoch: [22] [1070/1319] eta: 0:10:52 lr: 2.3378643334343302e-05 loss: 0.0411 (0.0488) time: 2.5957 data: 0.0059 max mem: 33369 +Epoch: [22] [1080/1319] eta: 0:10:25 lr: 2.3369362207299018e-05 loss: 0.0519 (0.0489) time: 2.6051 data: 0.0060 max mem: 33369 +Epoch: [22] [1090/1319] eta: 0:09:59 lr: 2.3360080670681804e-05 loss: 0.0458 (0.0489) time: 2.6297 data: 0.0058 max mem: 33369 +Epoch: [22] [1100/1319] eta: 0:09:33 lr: 2.335079872429276e-05 loss: 0.0378 (0.0488) time: 2.6262 data: 0.0058 max mem: 33369 +Epoch: [22] [1110/1319] eta: 0:09:07 lr: 2.334151636793279e-05 loss: 0.0417 (0.0489) time: 2.6176 data: 0.0058 max mem: 33369 +Epoch: [22] [1120/1319] eta: 0:08:41 lr: 2.333223360140262e-05 loss: 0.0576 (0.0489) time: 2.6355 data: 0.0059 max mem: 33369 +Epoch: [22] [1130/1319] eta: 0:08:15 lr: 2.3322950424502793e-05 loss: 0.0559 (0.0490) time: 2.6337 data: 0.0058 max mem: 33369 +Epoch: [22] [1140/1319] eta: 0:07:48 lr: 2.3313666837033663e-05 loss: 0.0455 (0.0489) time: 2.6099 data: 0.0057 max mem: 33369 +Epoch: [22] [1150/1319] eta: 0:07:22 lr: 2.33043828387954e-05 loss: 0.0417 (0.0489) time: 2.5937 data: 0.0057 max mem: 33369 +Epoch: [22] [1160/1319] eta: 0:06:56 lr: 2.3295098429587987e-05 loss: 0.0404 (0.0488) time: 2.6068 data: 0.0057 max mem: 33369 +Epoch: [22] [1170/1319] eta: 0:06:30 lr: 2.328581360921123e-05 loss: 0.0455 (0.0489) time: 2.6125 data: 0.0058 max mem: 33369 +Epoch: [22] [1180/1319] eta: 0:06:04 lr: 2.327652837746473e-05 loss: 0.0458 (0.0491) time: 2.6181 data: 0.0059 max mem: 33369 +Epoch: [22] [1190/1319] eta: 0:05:37 lr: 2.3267242734147912e-05 loss: 0.0447 (0.0491) time: 2.6209 data: 0.0059 max mem: 33369 +Epoch: [22] [1200/1319] eta: 0:05:11 lr: 2.325795667906002e-05 loss: 0.0368 (0.0491) time: 2.6019 data: 0.0058 max mem: 33369 +Epoch: [22] [1210/1319] eta: 0:04:45 lr: 2.3248670212000107e-05 loss: 0.0502 (0.0492) time: 2.5974 data: 0.0058 max mem: 33369 +Epoch: [22] [1220/1319] eta: 0:04:19 lr: 2.3239383332767037e-05 loss: 0.0522 (0.0492) time: 2.6038 data: 0.0057 max mem: 33369 +Epoch: [22] [1230/1319] eta: 0:03:53 lr: 2.323009604115948e-05 loss: 0.0429 (0.0492) time: 2.6138 data: 0.0058 max mem: 33369 +Epoch: [22] [1240/1319] eta: 0:03:26 lr: 2.322080833697593e-05 loss: 0.0456 (0.0493) time: 2.6281 data: 0.0061 max mem: 33369 +Epoch: [22] [1250/1319] eta: 0:03:00 lr: 2.3211520220014678e-05 loss: 0.0485 (0.0494) time: 2.6124 data: 0.0061 max mem: 33369 +Epoch: [22] [1260/1319] eta: 0:02:34 lr: 2.320223169007385e-05 loss: 0.0437 (0.0494) time: 2.5975 data: 0.0058 max mem: 33369 +Epoch: [22] [1270/1319] eta: 0:02:08 lr: 2.319294274695137e-05 loss: 0.0437 (0.0494) time: 2.6329 data: 0.0058 max mem: 33369 +Epoch: [22] [1280/1319] eta: 0:01:42 lr: 2.318365339044496e-05 loss: 0.0409 (0.0493) time: 2.6303 data: 0.0059 max mem: 33369 +Epoch: [22] [1290/1319] eta: 0:01:15 lr: 2.3174363620352174e-05 loss: 0.0443 (0.0494) time: 2.6126 data: 0.0057 max mem: 33369 +Epoch: [22] [1300/1319] eta: 0:00:49 lr: 2.3165073436470368e-05 loss: 0.0455 (0.0494) time: 2.6235 data: 0.0058 max mem: 33369 +Epoch: [22] [1310/1319] eta: 0:00:23 lr: 2.3155782838596706e-05 loss: 0.0462 (0.0494) time: 2.6092 data: 0.0059 max mem: 33369 +Epoch: [22] Total time: 0:57:33 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 2:09:30 time: 3.0199 data: 2.9416 max mem: 33369 +Test: [ 100/2573] eta: 0:04:09 time: 0.0715 data: 0.0011 max mem: 33369 +Test: [ 200/2573] eta: 0:03:27 time: 0.0729 data: 0.0011 max mem: 33369 +Test: [ 300/2573] eta: 0:03:06 time: 0.0746 data: 0.0011 max mem: 33369 +Test: [ 400/2573] eta: 0:02:53 time: 0.0749 data: 0.0011 max mem: 33369 +Test: [ 500/2573] eta: 0:02:42 time: 0.0732 data: 0.0011 max mem: 33369 +Test: [ 600/2573] eta: 0:02:33 time: 0.0733 data: 0.0011 max mem: 33369 +Test: [ 700/2573] eta: 0:02:25 time: 0.0735 data: 0.0012 max mem: 33369 +Test: [ 800/2573] eta: 0:02:16 time: 0.0766 data: 0.0011 max mem: 33369 +Test: [ 900/2573] eta: 0:02:08 time: 0.0734 data: 0.0011 max mem: 33369 +Test: [1000/2573] eta: 0:02:00 time: 0.0734 data: 0.0011 max mem: 33369 +Test: [1100/2573] eta: 0:01:52 time: 0.0735 data: 0.0011 max mem: 33369 +Test: [1200/2573] eta: 0:01:44 time: 0.0736 data: 0.0011 max mem: 33369 +Test: [1300/2573] eta: 0:01:36 time: 0.0735 data: 0.0011 max mem: 33369 +Test: [1400/2573] eta: 0:01:28 time: 0.0719 data: 0.0011 max mem: 33369 +Test: [1500/2573] eta: 0:01:21 time: 0.0736 data: 0.0011 max mem: 33369 +Test: [1600/2573] eta: 0:01:13 time: 0.0770 data: 0.0011 max mem: 33369 +Test: [1700/2573] eta: 0:01:05 time: 0.0721 data: 0.0011 max mem: 33369 +Test: [1800/2573] eta: 0:00:58 time: 0.0754 data: 0.0011 max mem: 33369 +Test: [1900/2573] eta: 0:00:50 time: 0.0720 data: 0.0011 max mem: 33369 +Test: [2000/2573] eta: 0:00:42 time: 0.0738 data: 0.0011 max mem: 33369 +Test: [2100/2573] eta: 0:00:35 time: 0.0755 data: 0.0011 max mem: 33369 +Test: [2200/2573] eta: 0:00:27 time: 0.0756 data: 0.0011 max mem: 33369 +Test: [2300/2573] eta: 0:00:20 time: 0.0755 data: 0.0011 max mem: 33369 +Test: [2400/2573] eta: 0:00:12 time: 0.0705 data: 0.0011 max mem: 33369 +Test: [2500/2573] eta: 0:00:05 time: 0.0739 data: 0.0011 max mem: 33369 +Test: Total time: 0:03:12 +Final results: +Mean IoU is 64.00 + + precision@0.5 = 71.69 + precision@0.6 = 65.97 + precision@0.7 = 59.19 + precision@0.8 = 47.69 + precision@0.9 = 23.69 + overall IoU = 61.64 + +Average object IoU 63.99657435482587 +Overall IoU 61.63853454589844 +Better epoch: 22 + +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [23] [ 0/1319] eta: 1:32:04 lr: 2.3147420946379584e-05 loss: 0.0744 (0.0744) time: 4.1887 data: 1.6002 max mem: 33369 +Epoch: [23] [ 10/1319] eta: 0:59:43 lr: 2.313812956136191e-05 loss: 0.0389 (0.0455) time: 2.7379 data: 0.1512 max mem: 33369 +Epoch: [23] [ 20/1319] eta: 0:57:46 lr: 2.3128837761763095e-05 loss: 0.0463 (0.0529) time: 2.5926 data: 0.0060 max mem: 33369 +Epoch: [23] [ 30/1319] eta: 0:56:58 lr: 2.3119545547379566e-05 loss: 0.0488 (0.0489) time: 2.6052 data: 0.0060 max mem: 33369 +Epoch: [23] [ 40/1319] eta: 0:56:22 lr: 2.3110252918007542e-05 loss: 0.0366 (0.0464) time: 2.6195 data: 0.0063 max mem: 33369 +Epoch: [23] [ 50/1319] eta: 0:55:54 lr: 2.3100959873443074e-05 loss: 0.0417 (0.0482) time: 2.6295 data: 0.0063 max mem: 33369 +Epoch: [23] [ 60/1319] eta: 0:55:23 lr: 2.3091666413482015e-05 loss: 0.0439 (0.0476) time: 2.6303 data: 0.0061 max mem: 33369 +Epoch: [23] [ 70/1319] eta: 0:54:59 lr: 2.3082372537920018e-05 loss: 0.0420 (0.0477) time: 2.6364 data: 0.0060 max mem: 33369 +Epoch: [23] [ 80/1319] eta: 0:54:32 lr: 2.307307824655256e-05 loss: 0.0468 (0.0476) time: 2.6462 data: 0.0061 max mem: 33369 +Epoch: [23] [ 90/1319] eta: 0:53:58 lr: 2.3063783539174907e-05 loss: 0.0439 (0.0472) time: 2.6138 data: 0.0060 max mem: 33369 +Epoch: [23] [ 100/1319] eta: 0:53:30 lr: 2.3054488415582145e-05 loss: 0.0432 (0.0478) time: 2.6042 data: 0.0060 max mem: 33369 +Epoch: [23] [ 110/1319] eta: 0:53:06 lr: 2.3045192875569164e-05 loss: 0.0522 (0.0496) time: 2.6367 data: 0.0060 max mem: 33369 +Epoch: [23] [ 120/1319] eta: 0:52:36 lr: 2.3035896918930662e-05 loss: 0.0522 (0.0492) time: 2.6252 data: 0.0060 max mem: 33369 +Epoch: [23] [ 130/1319] eta: 0:52:10 lr: 2.3026600545461138e-05 loss: 0.0450 (0.0496) time: 2.6185 data: 0.0059 max mem: 33369 +Epoch: [23] [ 140/1319] eta: 0:51:44 lr: 2.3017303754954915e-05 loss: 0.0389 (0.0494) time: 2.6369 data: 0.0059 max mem: 33369 +Epoch: [23] [ 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data: 0.0060 max mem: 33369 +Epoch: [23] [ 310/1319] eta: 0:44:07 lr: 2.2859194309475363e-05 loss: 0.0410 (0.0487) time: 2.6229 data: 0.0058 max mem: 33369 +Epoch: [23] [ 320/1319] eta: 0:43:40 lr: 2.2849889976913045e-05 loss: 0.0430 (0.0487) time: 2.6191 data: 0.0058 max mem: 33369 +Epoch: [23] [ 330/1319] eta: 0:43:14 lr: 2.2840585223368763e-05 loss: 0.0422 (0.0485) time: 2.6190 data: 0.0059 max mem: 33369 +Epoch: [23] [ 340/1319] eta: 0:42:48 lr: 2.2831280048632893e-05 loss: 0.0470 (0.0486) time: 2.6209 data: 0.0060 max mem: 33369 +Epoch: [23] [ 350/1319] eta: 0:42:21 lr: 2.282197445249563e-05 loss: 0.0459 (0.0486) time: 2.6169 data: 0.0061 max mem: 33369 +Epoch: [23] [ 360/1319] eta: 0:41:56 lr: 2.2812668434746943e-05 loss: 0.0420 (0.0484) time: 2.6355 data: 0.0062 max mem: 33369 +Epoch: [23] [ 370/1319] eta: 0:41:30 lr: 2.2803361995176614e-05 loss: 0.0422 (0.0484) time: 2.6528 data: 0.0061 max mem: 33369 +Epoch: [23] [ 380/1319] eta: 0:41:04 lr: 2.279405513357423e-05 loss: 0.0434 (0.0485) time: 2.6441 data: 0.0060 max mem: 33369 +Epoch: [23] [ 390/1319] eta: 0:40:38 lr: 2.278474784972917e-05 loss: 0.0409 (0.0484) time: 2.6208 data: 0.0060 max mem: 33369 +Epoch: [23] [ 400/1319] eta: 0:40:11 lr: 2.277544014343061e-05 loss: 0.0408 (0.0486) time: 2.6151 data: 0.0061 max mem: 33369 +Epoch: [23] [ 410/1319] eta: 0:39:44 lr: 2.2766132014467546e-05 loss: 0.0463 (0.0485) time: 2.6039 data: 0.0059 max mem: 33369 +Epoch: [23] [ 420/1319] eta: 0:39:18 lr: 2.2756823462628737e-05 loss: 0.0356 (0.0483) time: 2.6051 data: 0.0058 max mem: 33369 +Epoch: [23] [ 430/1319] eta: 0:38:51 lr: 2.2747514487702767e-05 loss: 0.0363 (0.0481) time: 2.6114 data: 0.0059 max mem: 33369 +Epoch: [23] [ 440/1319] eta: 0:38:25 lr: 2.2738205089478008e-05 loss: 0.0406 (0.0480) time: 2.6145 data: 0.0061 max mem: 33369 +Epoch: [23] [ 450/1319] eta: 0:37:59 lr: 2.272889526774264e-05 loss: 0.0406 (0.0479) time: 2.6181 data: 0.0060 max mem: 33369 +Epoch: [23] [ 460/1319] eta: 0:37:33 lr: 2.2719585022284628e-05 loss: 0.0370 (0.0479) time: 2.6213 data: 0.0061 max mem: 33369 +Epoch: [23] [ 470/1319] eta: 0:37:06 lr: 2.2710274352891738e-05 loss: 0.0445 (0.0479) time: 2.6156 data: 0.0062 max mem: 33369 +Epoch: [23] [ 480/1319] eta: 0:36:39 lr: 2.2700963259351535e-05 loss: 0.0436 (0.0477) time: 2.5952 data: 0.0064 max mem: 33369 +Epoch: [23] [ 490/1319] eta: 0:36:13 lr: 2.269165174145138e-05 loss: 0.0368 (0.0479) time: 2.6209 data: 0.0061 max mem: 33369 +Epoch: [23] [ 500/1319] eta: 0:35:47 lr: 2.2682339798978432e-05 loss: 0.0407 (0.0480) time: 2.6385 data: 0.0059 max mem: 33369 +Epoch: [23] [ 510/1319] eta: 0:35:21 lr: 2.2673027431719644e-05 loss: 0.0417 (0.0480) time: 2.6323 data: 0.0059 max mem: 33369 +Epoch: [23] [ 520/1319] eta: 0:34:55 lr: 2.266371463946176e-05 loss: 0.0390 (0.0480) time: 2.6257 data: 0.0058 max mem: 33369 +Epoch: [23] [ 530/1319] eta: 0:34:29 lr: 2.2654401421991334e-05 loss: 0.0463 (0.0481) time: 2.6334 data: 0.0058 max mem: 33369 +Epoch: [23] [ 540/1319] eta: 0:34:04 lr: 2.2645087779094697e-05 loss: 0.0495 (0.0481) time: 2.6616 data: 0.0059 max mem: 33369 +Epoch: [23] [ 550/1319] eta: 0:33:37 lr: 2.263577371055799e-05 loss: 0.0448 (0.0481) time: 2.6408 data: 0.0060 max mem: 33369 +Epoch: [23] [ 560/1319] eta: 0:33:11 lr: 2.262645921616714e-05 loss: 0.0425 (0.0480) time: 2.6150 data: 0.0060 max mem: 33369 +Epoch: [23] [ 570/1319] eta: 0:32:45 lr: 2.2617144295707877e-05 loss: 0.0425 (0.0482) time: 2.6269 data: 0.0061 max mem: 33369 +Epoch: [23] [ 580/1319] eta: 0:32:19 lr: 2.2607828948965706e-05 loss: 0.0414 (0.0482) time: 2.6385 data: 0.0061 max mem: 33369 +Epoch: [23] [ 590/1319] eta: 0:31:52 lr: 2.259851317572595e-05 loss: 0.0397 (0.0481) time: 2.6276 data: 0.0060 max mem: 33369 +Epoch: [23] [ 600/1319] eta: 0:31:26 lr: 2.2589196975773708e-05 loss: 0.0410 (0.0482) time: 2.6001 data: 0.0060 max mem: 33369 +Epoch: [23] [ 610/1319] eta: 0:30:59 lr: 2.257988034889388e-05 loss: 0.0406 (0.0482) time: 2.5930 data: 0.0060 max mem: 33369 +Epoch: [23] [ 620/1319] eta: 0:30:33 lr: 2.2570563294871165e-05 loss: 0.0362 (0.0481) time: 2.5894 data: 0.0059 max mem: 33369 +Epoch: [23] [ 630/1319] eta: 0:30:06 lr: 2.256124581349004e-05 loss: 0.0381 (0.0481) time: 2.6105 data: 0.0060 max mem: 33369 +Epoch: [23] [ 640/1319] eta: 0:29:40 lr: 2.2551927904534776e-05 loss: 0.0446 (0.0483) time: 2.6148 data: 0.0060 max mem: 33369 +Epoch: [23] [ 650/1319] eta: 0:29:13 lr: 2.254260956778945e-05 loss: 0.0466 (0.0482) time: 2.5924 data: 0.0059 max mem: 33369 +Epoch: [23] [ 660/1319] eta: 0:28:47 lr: 2.253329080303792e-05 loss: 0.0437 (0.0483) time: 2.6057 data: 0.0059 max mem: 33369 +Epoch: [23] [ 670/1319] eta: 0:28:22 lr: 2.252397161006384e-05 loss: 0.0460 (0.0482) time: 2.6534 data: 0.0059 max mem: 33369 +Epoch: [23] [ 680/1319] eta: 0:27:55 lr: 2.251465198865064e-05 loss: 0.0402 (0.0481) time: 2.6418 data: 0.0058 max mem: 33369 +Epoch: [23] [ 690/1319] eta: 0:27:28 lr: 2.250533193858157e-05 loss: 0.0394 (0.0481) time: 2.5868 data: 0.0060 max mem: 33369 +Epoch: [23] [ 700/1319] eta: 0:27:02 lr: 2.2496011459639643e-05 loss: 0.0420 (0.0481) time: 2.5939 data: 0.0061 max mem: 33369 +Epoch: [23] [ 710/1319] eta: 0:26:36 lr: 2.2486690551607674e-05 loss: 0.0416 (0.0481) time: 2.6169 data: 0.0059 max mem: 33369 +Epoch: [23] [ 720/1319] eta: 0:26:10 lr: 2.2477369214268278e-05 loss: 0.0398 (0.0482) time: 2.6114 data: 0.0058 max mem: 33369 +Epoch: [23] [ 730/1319] eta: 0:25:43 lr: 2.246804744740384e-05 loss: 0.0398 (0.0481) time: 2.6165 data: 0.0059 max mem: 33369 +Epoch: [23] [ 740/1319] eta: 0:25:17 lr: 2.245872525079654e-05 loss: 0.0403 (0.0480) time: 2.6275 data: 0.0059 max mem: 33369 +Epoch: [23] [ 750/1319] eta: 0:24:51 lr: 2.244940262422835e-05 loss: 0.0401 (0.0480) time: 2.6133 data: 0.0060 max mem: 33369 +Epoch: [23] [ 760/1319] eta: 0:24:25 lr: 2.244007956748104e-05 loss: 0.0413 (0.0479) time: 2.6139 data: 0.0062 max mem: 33369 +Epoch: [23] [ 770/1319] eta: 0:23:58 lr: 2.243075608033615e-05 loss: 0.0448 (0.0480) time: 2.6148 data: 0.0061 max mem: 33369 +Epoch: [23] [ 780/1319] eta: 0:23:32 lr: 2.242143216257503e-05 loss: 0.0453 (0.0482) time: 2.6155 data: 0.0060 max mem: 33369 +Epoch: [23] [ 790/1319] eta: 0:23:06 lr: 2.2412107813978792e-05 loss: 0.0419 (0.0482) time: 2.6152 data: 0.0059 max mem: 33369 +Epoch: [23] [ 800/1319] eta: 0:22:39 lr: 2.240278303432835e-05 loss: 0.0419 (0.0482) time: 2.5939 data: 0.0058 max mem: 33369 +Epoch: [23] [ 810/1319] eta: 0:22:13 lr: 2.2393457823404408e-05 loss: 0.0513 (0.0483) time: 2.5887 data: 0.0059 max mem: 33369 +Epoch: [23] [ 820/1319] eta: 0:21:47 lr: 2.2384132180987457e-05 loss: 0.0421 (0.0481) time: 2.6023 data: 0.0060 max mem: 33369 +Epoch: [23] [ 830/1319] eta: 0:21:21 lr: 2.2374806106857758e-05 loss: 0.0416 (0.0481) time: 2.6135 data: 0.0060 max mem: 33369 +Epoch: [23] [ 840/1319] eta: 0:20:54 lr: 2.2365479600795384e-05 loss: 0.0464 (0.0481) time: 2.6225 data: 0.0059 max mem: 33369 +Epoch: [23] [ 850/1319] eta: 0:20:28 lr: 2.2356152662580173e-05 loss: 0.0464 (0.0481) time: 2.6150 data: 0.0058 max mem: 33369 +Epoch: [23] [ 860/1319] eta: 0:20:02 lr: 2.234682529199176e-05 loss: 0.0359 (0.0480) time: 2.6098 data: 0.0057 max mem: 33369 +Epoch: [23] [ 870/1319] eta: 0:19:36 lr: 2.2337497488809557e-05 loss: 0.0433 (0.0480) time: 2.6248 data: 0.0058 max mem: 33369 +Epoch: [23] [ 880/1319] eta: 0:19:10 lr: 2.232816925281277e-05 loss: 0.0432 (0.0479) time: 2.6218 data: 0.0058 max mem: 33369 +Epoch: [23] [ 890/1319] eta: 0:18:43 lr: 2.2318840583780386e-05 loss: 0.0436 (0.0479) time: 2.6272 data: 0.0058 max mem: 33369 +Epoch: [23] [ 900/1319] eta: 0:18:17 lr: 2.2309511481491173e-05 loss: 0.0436 (0.0479) time: 2.6208 data: 0.0058 max mem: 33369 +Epoch: [23] [ 910/1319] eta: 0:17:51 lr: 2.2300181945723685e-05 loss: 0.0409 (0.0478) time: 2.6137 data: 0.0057 max mem: 33369 +Epoch: [23] [ 920/1319] eta: 0:17:25 lr: 2.2290851976256266e-05 loss: 0.0493 (0.0479) time: 2.6311 data: 0.0057 max mem: 33369 +Epoch: [23] [ 930/1319] eta: 0:16:59 lr: 2.2281521572867038e-05 loss: 0.0539 (0.0480) time: 2.6216 data: 0.0058 max mem: 33369 +Epoch: [23] [ 940/1319] eta: 0:16:33 lr: 2.2272190735333905e-05 loss: 0.0454 (0.0480) time: 2.6228 data: 0.0060 max mem: 33369 +Epoch: [23] [ 950/1319] eta: 0:16:06 lr: 2.2262859463434552e-05 loss: 0.0454 (0.0480) time: 2.6246 data: 0.0060 max mem: 33369 +Epoch: [23] [ 960/1319] eta: 0:15:40 lr: 2.2253527756946453e-05 loss: 0.0444 (0.0481) time: 2.6220 data: 0.0058 max mem: 33369 +Epoch: [23] [ 970/1319] eta: 0:15:14 lr: 2.2244195615646862e-05 loss: 0.0418 (0.0481) time: 2.6057 data: 0.0058 max mem: 33369 +Epoch: [23] [ 980/1319] eta: 0:14:48 lr: 2.2234863039312817e-05 loss: 0.0464 (0.0481) time: 2.5922 data: 0.0058 max mem: 33369 +Epoch: [23] [ 990/1319] eta: 0:14:21 lr: 2.222553002772113e-05 loss: 0.0497 (0.0481) time: 2.6126 data: 0.0059 max mem: 33369 +Epoch: [23] [1000/1319] eta: 0:13:55 lr: 2.2216196580648405e-05 loss: 0.0477 (0.0481) time: 2.6184 data: 0.0059 max mem: 33369 +Epoch: [23] [1010/1319] eta: 0:13:29 lr: 2.2206862697871013e-05 loss: 0.0462 (0.0482) time: 2.6080 data: 0.0059 max mem: 33369 +Epoch: [23] [1020/1319] eta: 0:13:03 lr: 2.2197528379165116e-05 loss: 0.0462 (0.0483) time: 2.5987 data: 0.0059 max mem: 33369 +Epoch: [23] [1030/1319] eta: 0:12:36 lr: 2.218819362430666e-05 loss: 0.0377 (0.0481) time: 2.6190 data: 0.0056 max mem: 33369 +Epoch: [23] [1040/1319] eta: 0:12:10 lr: 2.217885843307136e-05 loss: 0.0358 (0.0481) time: 2.6180 data: 0.0056 max mem: 33369 +Epoch: [23] [1050/1319] eta: 0:11:44 lr: 2.2169522805234726e-05 loss: 0.0449 (0.0481) time: 2.6029 data: 0.0060 max mem: 33369 +Epoch: [23] [1060/1319] eta: 0:11:18 lr: 2.2160186740572026e-05 loss: 0.0449 (0.0481) time: 2.5753 data: 0.0060 max mem: 33369 +Epoch: [23] [1070/1319] eta: 0:10:51 lr: 2.215085023885832e-05 loss: 0.0441 (0.0482) time: 2.5720 data: 0.0059 max mem: 33369 +Epoch: [23] [1080/1319] eta: 0:10:25 lr: 2.2141513299868444e-05 loss: 0.0449 (0.0482) time: 2.6254 data: 0.0059 max mem: 33369 +Epoch: [23] [1090/1319] eta: 0:09:59 lr: 2.2132175923377022e-05 loss: 0.0417 (0.0481) time: 2.6023 data: 0.0060 max mem: 33369 +Epoch: [23] [1100/1319] eta: 0:09:33 lr: 2.2122838109158445e-05 loss: 0.0398 (0.0481) time: 2.5899 data: 0.0061 max mem: 33369 +Epoch: [23] [1110/1319] eta: 0:09:07 lr: 2.211349985698688e-05 loss: 0.0426 (0.0481) time: 2.6318 data: 0.0059 max mem: 33369 +Epoch: [23] [1120/1319] eta: 0:08:41 lr: 2.2104161166636274e-05 loss: 0.0403 (0.0480) time: 2.6338 data: 0.0059 max mem: 33369 +Epoch: [23] [1130/1319] eta: 0:08:14 lr: 2.2094822037880365e-05 loss: 0.0403 (0.0480) time: 2.6032 data: 0.0058 max mem: 33369 +Epoch: [23] [1140/1319] eta: 0:07:48 lr: 2.2085482470492644e-05 loss: 0.0438 (0.0481) time: 2.6100 data: 0.0059 max mem: 33369 +Epoch: [23] [1150/1319] eta: 0:07:22 lr: 2.20761424642464e-05 loss: 0.0436 (0.0480) time: 2.6100 data: 0.0059 max mem: 33369 +Epoch: [23] [1160/1319] eta: 0:06:56 lr: 2.2066802018914685e-05 loss: 0.0382 (0.0480) time: 2.6174 data: 0.0057 max mem: 33369 +Epoch: [23] [1170/1319] eta: 0:06:30 lr: 2.2057461134270328e-05 loss: 0.0412 (0.0480) time: 2.6306 data: 0.0056 max mem: 33369 +Epoch: [23] [1180/1319] eta: 0:06:03 lr: 2.2048119810085938e-05 loss: 0.0502 (0.0482) time: 2.6327 data: 0.0058 max mem: 33369 +Epoch: [23] [1190/1319] eta: 0:05:37 lr: 2.2038778046133896e-05 loss: 0.0517 (0.0484) time: 2.6256 data: 0.0058 max mem: 33369 +Epoch: [23] [1200/1319] eta: 0:05:11 lr: 2.2029435842186362e-05 loss: 0.0510 (0.0484) time: 2.6165 data: 0.0058 max mem: 33369 +Epoch: [23] [1210/1319] eta: 0:04:45 lr: 2.2020093198015273e-05 loss: 0.0433 (0.0483) time: 2.6142 data: 0.0058 max mem: 33369 +Epoch: [23] [1220/1319] eta: 0:04:19 lr: 2.2010750113392324e-05 loss: 0.0375 (0.0483) time: 2.5861 data: 0.0057 max mem: 33369 +Epoch: [23] [1230/1319] eta: 0:03:52 lr: 2.2001406588088997e-05 loss: 0.0385 (0.0482) time: 2.5780 data: 0.0057 max mem: 33369 +Epoch: [23] [1240/1319] eta: 0:03:26 lr: 2.199206262187655e-05 loss: 0.0415 (0.0483) time: 2.5818 data: 0.0059 max mem: 33369 +Epoch: [23] [1250/1319] eta: 0:03:00 lr: 2.1982718214526003e-05 loss: 0.0446 (0.0482) time: 2.5948 data: 0.0058 max mem: 33369 +Epoch: [23] [1260/1319] eta: 0:02:34 lr: 2.1973373365808168e-05 loss: 0.0446 (0.0483) time: 2.6220 data: 0.0058 max mem: 33369 +Epoch: [23] [1270/1319] eta: 0:02:08 lr: 2.1964028075493602e-05 loss: 0.0458 (0.0483) time: 2.6665 data: 0.0058 max mem: 33369 +Epoch: [23] [1280/1319] eta: 0:01:42 lr: 2.1954682343352655e-05 loss: 0.0428 (0.0483) time: 2.6460 data: 0.0059 max mem: 33369 +Epoch: [23] [1290/1319] eta: 0:01:15 lr: 2.1945336169155447e-05 loss: 0.0417 (0.0483) time: 2.6335 data: 0.0058 max mem: 33369 +Epoch: [23] [1300/1319] eta: 0:00:49 lr: 2.1935989552671862e-05 loss: 0.0395 (0.0483) time: 2.6390 data: 0.0057 max mem: 33369 +Epoch: [23] [1310/1319] eta: 0:00:23 lr: 2.192664249367156e-05 loss: 0.0424 (0.0483) time: 2.6303 data: 0.0056 max mem: 33369 +Epoch: [23] Total time: 0:57:33 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 2:31:23 time: 3.5304 data: 3.4515 max mem: 33369 +Test: [ 100/2573] eta: 0:04:21 time: 0.0712 data: 0.0011 max mem: 33369 +Test: [ 200/2573] eta: 0:03:33 time: 0.0731 data: 0.0011 max mem: 33369 +Test: [ 300/2573] eta: 0:03:10 time: 0.0749 data: 0.0011 max mem: 33369 +Test: [ 400/2573] eta: 0:02:56 time: 0.0749 data: 0.0011 max mem: 33369 +Test: [ 500/2573] eta: 0:02:45 time: 0.0733 data: 0.0011 max mem: 33369 +Test: [ 600/2573] eta: 0:02:35 time: 0.0735 data: 0.0011 max mem: 33369 +Test: [ 700/2573] eta: 0:02:26 time: 0.0733 data: 0.0011 max mem: 33369 +Test: [ 800/2573] eta: 0:02:17 time: 0.0767 data: 0.0011 max mem: 33369 +Test: [ 900/2573] eta: 0:02:09 time: 0.0734 data: 0.0010 max mem: 33369 +Test: [1000/2573] eta: 0:02:01 time: 0.0734 data: 0.0011 max mem: 33369 +Test: [1100/2573] eta: 0:01:53 time: 0.0736 data: 0.0011 max mem: 33369 +Test: [1200/2573] eta: 0:01:45 time: 0.0737 data: 0.0011 max mem: 33369 +Test: [1300/2573] eta: 0:01:37 time: 0.0737 data: 0.0011 max mem: 33369 +Test: [1400/2573] eta: 0:01:29 time: 0.0721 data: 0.0011 max mem: 33369 +Test: [1500/2573] eta: 0:01:21 time: 0.0738 data: 0.0011 max mem: 33369 +Test: [1600/2573] eta: 0:01:13 time: 0.0771 data: 0.0011 max mem: 33369 +Test: [1700/2573] eta: 0:01:06 time: 0.0722 data: 0.0011 max mem: 33369 +Test: [1800/2573] eta: 0:00:58 time: 0.0757 data: 0.0011 max mem: 33369 +Test: [1900/2573] eta: 0:00:50 time: 0.0722 data: 0.0011 max mem: 33369 +Test: [2000/2573] eta: 0:00:43 time: 0.0739 data: 0.0011 max mem: 33369 +Test: [2100/2573] eta: 0:00:35 time: 0.0755 data: 0.0011 max mem: 33369 +Test: [2200/2573] eta: 0:00:28 time: 0.0756 data: 0.0011 max mem: 33369 +Test: [2300/2573] eta: 0:00:20 time: 0.0756 data: 0.0011 max mem: 33369 +Test: [2400/2573] eta: 0:00:12 time: 0.0706 data: 0.0011 max mem: 33369 +Test: [2500/2573] eta: 0:00:05 time: 0.0740 data: 0.0011 max mem: 33369 +Test: Total time: 0:03:13 +Final results: +Mean IoU is 63.49 + + precision@0.5 = 71.69 + precision@0.6 = 66.28 + precision@0.7 = 59.35 + precision@0.8 = 47.88 + precision@0.9 = 23.71 + overall IoU = 61.06 + +Average object IoU 63.492251863486906 +Overall IoU 61.05716323852539 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [24] [ 0/1319] eta: 3:03:13 lr: 2.1918229762028934e-05 loss: 0.0687 (0.0687) time: 8.3349 data: 1.3671 max mem: 33369 +Epoch: [24] [ 10/1319] eta: 1:08:07 lr: 2.1908881861611456e-05 loss: 0.0461 (0.0477) time: 3.1228 data: 0.1300 max mem: 33369 +Epoch: [24] [ 20/1319] eta: 1:02:32 lr: 2.1899533518007982e-05 loss: 0.0472 (0.0527) time: 2.6162 data: 0.0061 max mem: 33369 +Epoch: [24] [ 30/1319] eta: 0:59:56 lr: 2.189018473098726e-05 loss: 0.0481 (0.0503) time: 2.6066 data: 0.0060 max mem: 33369 +Epoch: [24] [ 40/1319] eta: 0:58:33 lr: 2.188083550031783e-05 loss: 0.0345 (0.0465) time: 2.5982 data: 0.0060 max mem: 33369 +Epoch: [24] [ 50/1319] eta: 0:57:25 lr: 2.1871485825767997e-05 loss: 0.0366 (0.0485) time: 2.6001 data: 0.0060 max mem: 33369 +Epoch: [24] [ 60/1319] eta: 0:56:34 lr: 2.1862135707105826e-05 loss: 0.0463 (0.0480) time: 2.5922 data: 0.0060 max mem: 33369 +Epoch: [24] [ 70/1319] eta: 0:55:50 lr: 2.1852785144099174e-05 loss: 0.0418 (0.0477) time: 2.5981 data: 0.0060 max mem: 33369 +Epoch: [24] [ 80/1319] eta: 0:55:13 lr: 2.184343413651562e-05 loss: 0.0388 (0.0483) time: 2.6085 data: 0.0061 max mem: 33369 +Epoch: [24] [ 90/1319] eta: 0:54:32 lr: 2.1834082684122557e-05 loss: 0.0355 (0.0475) time: 2.5923 data: 0.0060 max mem: 33369 +Epoch: [24] [ 100/1319] eta: 0:53:57 lr: 2.1824730786687132e-05 loss: 0.0364 (0.0467) time: 2.5817 data: 0.0059 max mem: 33369 +Epoch: [24] [ 110/1319] eta: 0:53:25 lr: 2.181537844397624e-05 loss: 0.0403 (0.0467) time: 2.6010 data: 0.0060 max mem: 33369 +Epoch: [24] [ 120/1319] eta: 0:52:53 lr: 2.1806025655756576e-05 loss: 0.0418 (0.0470) time: 2.6009 data: 0.0060 max mem: 33369 +Epoch: [24] [ 130/1319] eta: 0:52:22 lr: 2.1796672421794575e-05 loss: 0.0430 (0.0473) time: 2.5939 data: 0.0060 max mem: 33369 +Epoch: [24] [ 140/1319] eta: 0:51:53 lr: 2.1787318741856443e-05 loss: 0.0430 (0.0469) time: 2.6037 data: 0.0060 max mem: 33369 +Epoch: [24] [ 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data: 0.0062 max mem: 33369 +Epoch: [24] [ 310/1319] eta: 0:44:19 lr: 2.1628237720877814e-05 loss: 0.0446 (0.0480) time: 2.6219 data: 0.0061 max mem: 33369 +Epoch: [24] [ 320/1319] eta: 0:43:50 lr: 2.161887597312257e-05 loss: 0.0493 (0.0480) time: 2.5962 data: 0.0058 max mem: 33369 +Epoch: [24] [ 330/1319] eta: 0:43:22 lr: 2.160951377490428e-05 loss: 0.0450 (0.0483) time: 2.5689 data: 0.0059 max mem: 33369 +Epoch: [24] [ 340/1319] eta: 0:42:56 lr: 2.160015112598442e-05 loss: 0.0446 (0.0482) time: 2.6024 data: 0.0061 max mem: 33369 +Epoch: [24] [ 350/1319] eta: 0:42:30 lr: 2.1590788026124187e-05 loss: 0.0421 (0.0482) time: 2.6359 data: 0.0061 max mem: 33369 +Epoch: [24] [ 360/1319] eta: 0:42:04 lr: 2.158142447508457e-05 loss: 0.0421 (0.0482) time: 2.6400 data: 0.0059 max mem: 33369 +Epoch: [24] [ 370/1319] eta: 0:41:37 lr: 2.1572060472626296e-05 loss: 0.0406 (0.0481) time: 2.6182 data: 0.0057 max mem: 33369 +Epoch: [24] [ 380/1319] eta: 0:41:10 lr: 2.156269601850986e-05 loss: 0.0417 (0.0480) time: 2.6148 data: 0.0059 max mem: 33369 +Epoch: [24] [ 390/1319] eta: 0:40:44 lr: 2.1553331112495514e-05 loss: 0.0417 (0.0478) time: 2.6250 data: 0.0062 max mem: 33369 +Epoch: [24] [ 400/1319] eta: 0:40:17 lr: 2.1543965754343263e-05 loss: 0.0461 (0.0478) time: 2.6315 data: 0.0061 max mem: 33369 +Epoch: [24] [ 410/1319] eta: 0:39:51 lr: 2.1534599943812868e-05 loss: 0.0422 (0.0477) time: 2.6309 data: 0.0059 max mem: 33369 +Epoch: [24] [ 420/1319] eta: 0:39:25 lr: 2.1525233680663844e-05 loss: 0.0394 (0.0476) time: 2.6374 data: 0.0059 max mem: 33369 +Epoch: [24] [ 430/1319] eta: 0:38:59 lr: 2.151586696465547e-05 loss: 0.0392 (0.0474) time: 2.6475 data: 0.0059 max mem: 33369 +Epoch: [24] [ 440/1319] eta: 0:38:33 lr: 2.1506499795546773e-05 loss: 0.0392 (0.0473) time: 2.6325 data: 0.0056 max mem: 33369 +Epoch: [24] [ 450/1319] eta: 0:38:07 lr: 2.1497132173096545e-05 loss: 0.0397 (0.0474) time: 2.6343 data: 0.0058 max mem: 33369 +Epoch: [24] [ 460/1319] eta: 0:37:40 lr: 2.1487764097063317e-05 loss: 0.0417 (0.0474) time: 2.6249 data: 0.0059 max mem: 33369 +Epoch: [24] [ 470/1319] eta: 0:37:13 lr: 2.1478395567205385e-05 loss: 0.0412 (0.0472) time: 2.6195 data: 0.0059 max mem: 33369 +Epoch: [24] [ 480/1319] eta: 0:36:48 lr: 2.14690265832808e-05 loss: 0.0427 (0.0473) time: 2.6555 data: 0.0058 max mem: 33369 +Epoch: [24] [ 490/1319] eta: 0:36:22 lr: 2.1459657145047365e-05 loss: 0.0484 (0.0475) time: 2.6555 data: 0.0057 max mem: 33369 +Epoch: [24] [ 500/1319] eta: 0:35:55 lr: 2.1450287252262635e-05 loss: 0.0410 (0.0473) time: 2.6144 data: 0.0059 max mem: 33369 +Epoch: [24] [ 510/1319] eta: 0:35:28 lr: 2.144091690468391e-05 loss: 0.0410 (0.0472) time: 2.5942 data: 0.0061 max mem: 33369 +Epoch: [24] [ 520/1319] eta: 0:35:01 lr: 2.1431546102068255e-05 loss: 0.0378 (0.0471) time: 2.6047 data: 0.0061 max mem: 33369 +Epoch: [24] [ 530/1319] eta: 0:34:34 lr: 2.142217484417249e-05 loss: 0.0378 (0.0470) time: 2.5893 data: 0.0058 max mem: 33369 +Epoch: [24] [ 540/1319] eta: 0:34:08 lr: 2.1412803130753163e-05 loss: 0.0409 (0.0471) time: 2.6059 data: 0.0058 max mem: 33369 +Epoch: [24] [ 550/1319] eta: 0:33:41 lr: 2.1403430961566606e-05 loss: 0.0423 (0.0471) time: 2.6035 data: 0.0059 max mem: 33369 +Epoch: [24] [ 560/1319] eta: 0:33:14 lr: 2.1394058336368883e-05 loss: 0.0462 (0.0471) time: 2.5887 data: 0.0058 max mem: 33369 +Epoch: [24] [ 570/1319] eta: 0:32:47 lr: 2.13846852549158e-05 loss: 0.0441 (0.0470) time: 2.6048 data: 0.0059 max mem: 33369 +Epoch: [24] [ 580/1319] eta: 0:32:21 lr: 2.1375311716962932e-05 loss: 0.0426 (0.0469) time: 2.6027 data: 0.0059 max mem: 33369 +Epoch: [24] [ 590/1319] eta: 0:31:54 lr: 2.1365937722265597e-05 loss: 0.0438 (0.0472) time: 2.6029 data: 0.0059 max mem: 33369 +Epoch: [24] [ 600/1319] eta: 0:31:28 lr: 2.135656327057886e-05 loss: 0.0602 (0.0474) time: 2.6256 data: 0.0059 max mem: 33369 +Epoch: [24] [ 610/1319] eta: 0:31:02 lr: 2.1347188361657547e-05 loss: 0.0602 (0.0475) time: 2.6354 data: 0.0058 max mem: 33369 +Epoch: [24] [ 620/1319] eta: 0:30:35 lr: 2.1337812995256205e-05 loss: 0.0525 (0.0478) time: 2.6014 data: 0.0058 max mem: 33369 +Epoch: [24] [ 630/1319] eta: 0:30:09 lr: 2.1328437171129155e-05 loss: 0.0412 (0.0477) time: 2.6026 data: 0.0058 max mem: 33369 +Epoch: [24] [ 640/1319] eta: 0:29:43 lr: 2.1319060889030465e-05 loss: 0.0369 (0.0475) time: 2.6181 data: 0.0057 max mem: 33369 +Epoch: [24] [ 650/1319] eta: 0:29:16 lr: 2.1309684148713934e-05 loss: 0.0397 (0.0477) time: 2.6160 data: 0.0058 max mem: 33369 +Epoch: [24] [ 660/1319] eta: 0:28:50 lr: 2.130030694993313e-05 loss: 0.0454 (0.0477) time: 2.6242 data: 0.0058 max mem: 33369 +Epoch: [24] [ 670/1319] eta: 0:28:24 lr: 2.129092929244134e-05 loss: 0.0391 (0.0475) time: 2.6373 data: 0.0059 max mem: 33369 +Epoch: [24] [ 680/1319] eta: 0:27:58 lr: 2.1281551175991622e-05 loss: 0.0369 (0.0475) time: 2.6256 data: 0.0058 max mem: 33369 +Epoch: [24] [ 690/1319] eta: 0:27:31 lr: 2.127217260033677e-05 loss: 0.0401 (0.0474) time: 2.5895 data: 0.0057 max mem: 33369 +Epoch: [24] [ 700/1319] eta: 0:27:04 lr: 2.126279356522932e-05 loss: 0.0397 (0.0474) time: 2.5796 data: 0.0057 max mem: 33369 +Epoch: [24] [ 710/1319] eta: 0:26:38 lr: 2.1253414070421574e-05 loss: 0.0471 (0.0474) time: 2.6233 data: 0.0057 max mem: 33369 +Epoch: [24] [ 720/1319] eta: 0:26:12 lr: 2.1244034115665552e-05 loss: 0.0501 (0.0474) time: 2.6232 data: 0.0058 max mem: 33369 +Epoch: [24] [ 730/1319] eta: 0:25:46 lr: 2.1234653700713027e-05 loss: 0.0418 (0.0476) time: 2.6194 data: 0.0059 max mem: 33369 +Epoch: [24] [ 740/1319] eta: 0:25:19 lr: 2.122527282531552e-05 loss: 0.0418 (0.0476) time: 2.6427 data: 0.0059 max mem: 33369 +Epoch: [24] [ 750/1319] eta: 0:24:53 lr: 2.12158914892243e-05 loss: 0.0415 (0.0476) time: 2.6246 data: 0.0057 max mem: 33369 +Epoch: [24] [ 760/1319] eta: 0:24:27 lr: 2.120650969219037e-05 loss: 0.0387 (0.0475) time: 2.6122 data: 0.0056 max mem: 33369 +Epoch: [24] [ 770/1319] eta: 0:24:00 lr: 2.1197127433964487e-05 loss: 0.0357 (0.0473) time: 2.6092 data: 0.0058 max mem: 33369 +Epoch: [24] [ 780/1319] eta: 0:23:34 lr: 2.1187744714297132e-05 loss: 0.0385 (0.0475) time: 2.6247 data: 0.0058 max mem: 33369 +Epoch: [24] [ 790/1319] eta: 0:23:08 lr: 2.117836153293854e-05 loss: 0.0404 (0.0475) time: 2.6326 data: 0.0057 max mem: 33369 +Epoch: [24] [ 800/1319] eta: 0:22:42 lr: 2.1168977889638698e-05 loss: 0.0393 (0.0474) time: 2.6198 data: 0.0057 max mem: 33369 +Epoch: [24] [ 810/1319] eta: 0:22:15 lr: 2.1159593784147318e-05 loss: 0.0383 (0.0473) time: 2.6257 data: 0.0058 max mem: 33369 +Epoch: [24] [ 820/1319] eta: 0:21:49 lr: 2.115020921621386e-05 loss: 0.0383 (0.0475) time: 2.6281 data: 0.0058 max mem: 33369 +Epoch: [24] [ 830/1319] eta: 0:21:23 lr: 2.1140824185587522e-05 loss: 0.0410 (0.0474) time: 2.6376 data: 0.0056 max mem: 33369 +Epoch: [24] [ 840/1319] eta: 0:20:57 lr: 2.113143869201724e-05 loss: 0.0432 (0.0474) time: 2.6344 data: 0.0056 max mem: 33369 +Epoch: [24] [ 850/1319] eta: 0:20:30 lr: 2.11220527352517e-05 loss: 0.0439 (0.0474) time: 2.6008 data: 0.0056 max mem: 33369 +Epoch: [24] [ 860/1319] eta: 0:20:04 lr: 2.111266631503932e-05 loss: 0.0414 (0.0473) time: 2.5988 data: 0.0057 max mem: 33369 +Epoch: [24] [ 870/1319] eta: 0:19:38 lr: 2.1103279431128255e-05 loss: 0.0417 (0.0473) time: 2.5910 data: 0.0059 max mem: 33369 +Epoch: [24] [ 880/1319] eta: 0:19:11 lr: 2.1093892083266405e-05 loss: 0.0393 (0.0472) time: 2.5899 data: 0.0060 max mem: 33369 +Epoch: [24] [ 890/1319] eta: 0:18:45 lr: 2.10845042712014e-05 loss: 0.0450 (0.0473) time: 2.6457 data: 0.0059 max mem: 33369 +Epoch: [24] [ 900/1319] eta: 0:18:19 lr: 2.1075115994680607e-05 loss: 0.0463 (0.0473) time: 2.6630 data: 0.0057 max mem: 33369 +Epoch: [24] [ 910/1319] eta: 0:17:53 lr: 2.106572725345115e-05 loss: 0.0392 (0.0472) time: 2.6494 data: 0.0056 max mem: 33369 +Epoch: [24] [ 920/1319] eta: 0:17:27 lr: 2.105633804725987e-05 loss: 0.0372 (0.0471) time: 2.6450 data: 0.0057 max mem: 33369 +Epoch: [24] [ 930/1319] eta: 0:17:01 lr: 2.104694837585335e-05 loss: 0.0378 (0.0470) time: 2.6293 data: 0.0057 max mem: 33369 +Epoch: [24] [ 940/1319] eta: 0:16:34 lr: 2.1037558238977907e-05 loss: 0.0380 (0.0470) time: 2.6249 data: 0.0056 max mem: 33369 +Epoch: [24] [ 950/1319] eta: 0:16:08 lr: 2.1028167636379597e-05 loss: 0.0439 (0.0470) time: 2.6482 data: 0.0058 max mem: 33369 +Epoch: [24] [ 960/1319] eta: 0:15:42 lr: 2.1018776567804213e-05 loss: 0.0437 (0.0469) time: 2.6303 data: 0.0060 max mem: 33369 +Epoch: [24] [ 970/1319] eta: 0:15:16 lr: 2.1009385032997278e-05 loss: 0.0397 (0.0469) time: 2.6086 data: 0.0060 max mem: 33369 +Epoch: [24] [ 980/1319] eta: 0:14:49 lr: 2.0999993031704057e-05 loss: 0.0380 (0.0468) time: 2.5994 data: 0.0060 max mem: 33369 +Epoch: [24] [ 990/1319] eta: 0:14:23 lr: 2.0990600563669546e-05 loss: 0.0415 (0.0468) time: 2.6134 data: 0.0060 max mem: 33369 +Epoch: [24] [1000/1319] eta: 0:13:57 lr: 2.0981207628638462e-05 loss: 0.0471 (0.0468) time: 2.6257 data: 0.0059 max mem: 33369 +Epoch: [24] [1010/1319] eta: 0:13:31 lr: 2.0971814226355274e-05 loss: 0.0462 (0.0469) time: 2.6219 data: 0.0057 max mem: 33369 +Epoch: [24] [1020/1319] eta: 0:13:04 lr: 2.0962420356564173e-05 loss: 0.0414 (0.0469) time: 2.6323 data: 0.0058 max mem: 33369 +Epoch: [24] [1030/1319] eta: 0:12:38 lr: 2.0953026019009095e-05 loss: 0.0511 (0.0470) time: 2.6124 data: 0.0059 max mem: 33369 +Epoch: [24] [1040/1319] eta: 0:12:12 lr: 2.0943631213433694e-05 loss: 0.0505 (0.0470) time: 2.5917 data: 0.0058 max mem: 33369 +Epoch: [24] [1050/1319] eta: 0:11:45 lr: 2.0934235939581352e-05 loss: 0.0452 (0.0470) time: 2.6248 data: 0.0057 max mem: 33369 +Epoch: [24] [1060/1319] eta: 0:11:19 lr: 2.0924840197195202e-05 loss: 0.0412 (0.0470) time: 2.6319 data: 0.0057 max mem: 33369 +Epoch: [24] [1070/1319] eta: 0:10:53 lr: 2.0915443986018095e-05 loss: 0.0384 (0.0471) time: 2.5813 data: 0.0057 max mem: 33369 +Epoch: [24] [1080/1319] eta: 0:10:26 lr: 2.0906047305792607e-05 loss: 0.0428 (0.0472) time: 2.5803 data: 0.0059 max mem: 33369 +Epoch: [24] [1090/1319] eta: 0:10:00 lr: 2.0896650156261064e-05 loss: 0.0428 (0.0472) time: 2.5962 data: 0.0059 max mem: 33369 +Epoch: [24] [1100/1319] eta: 0:09:34 lr: 2.0887252537165494e-05 loss: 0.0495 (0.0474) time: 2.6118 data: 0.0058 max mem: 33369 +Epoch: [24] [1110/1319] eta: 0:09:08 lr: 2.087785444824768e-05 loss: 0.0484 (0.0474) time: 2.6355 data: 0.0060 max mem: 33369 +Epoch: [24] [1120/1319] eta: 0:08:42 lr: 2.086845588924912e-05 loss: 0.0430 (0.0473) time: 2.6489 data: 0.0058 max mem: 33369 +Epoch: [24] [1130/1319] eta: 0:08:15 lr: 2.0859056859911038e-05 loss: 0.0397 (0.0473) time: 2.6380 data: 0.0055 max mem: 33369 +Epoch: [24] [1140/1319] eta: 0:07:49 lr: 2.0849657359974397e-05 loss: 0.0521 (0.0474) time: 2.6251 data: 0.0055 max mem: 33369 +Epoch: [24] [1150/1319] eta: 0:07:23 lr: 2.084025738917989e-05 loss: 0.0437 (0.0473) time: 2.6219 data: 0.0056 max mem: 33369 +Epoch: [24] [1160/1319] eta: 0:06:57 lr: 2.083085694726791e-05 loss: 0.0397 (0.0473) time: 2.6028 data: 0.0057 max mem: 33369 +Epoch: [24] [1170/1319] eta: 0:06:30 lr: 2.0821456033978605e-05 loss: 0.0428 (0.0473) time: 2.6142 data: 0.0057 max mem: 33369 +Epoch: [24] [1180/1319] eta: 0:06:04 lr: 2.0812054649051834e-05 loss: 0.0450 (0.0473) time: 2.6256 data: 0.0058 max mem: 33369 +Epoch: [24] [1190/1319] eta: 0:05:38 lr: 2.0802652792227197e-05 loss: 0.0461 (0.0473) time: 2.6183 data: 0.0057 max mem: 33369 +Epoch: [24] [1200/1319] eta: 0:05:12 lr: 2.0793250463244006e-05 loss: 0.0429 (0.0473) time: 2.6241 data: 0.0057 max mem: 33369 +Epoch: [24] [1210/1319] eta: 0:04:45 lr: 2.07838476618413e-05 loss: 0.0441 (0.0473) time: 2.6189 data: 0.0059 max mem: 33369 +Epoch: [24] [1220/1319] eta: 0:04:19 lr: 2.077444438775784e-05 loss: 0.0439 (0.0473) time: 2.6109 data: 0.0059 max mem: 33369 +Epoch: [24] [1230/1319] eta: 0:03:53 lr: 2.0765040640732118e-05 loss: 0.0413 (0.0473) time: 2.6002 data: 0.0057 max mem: 33369 +Epoch: [24] [1240/1319] eta: 0:03:27 lr: 2.0755636420502354e-05 loss: 0.0431 (0.0473) time: 2.6087 data: 0.0058 max mem: 33369 +Epoch: [24] [1250/1319] eta: 0:03:00 lr: 2.074623172680648e-05 loss: 0.0431 (0.0473) time: 2.6288 data: 0.0057 max mem: 33369 +Epoch: [24] [1260/1319] eta: 0:02:34 lr: 2.0736826559382146e-05 loss: 0.0450 (0.0474) time: 2.6408 data: 0.0057 max mem: 33369 +Epoch: [24] [1270/1319] eta: 0:02:08 lr: 2.072742091796674e-05 loss: 0.0509 (0.0474) time: 2.6369 data: 0.0058 max mem: 33369 +Epoch: [24] [1280/1319] eta: 0:01:42 lr: 2.071801480229737e-05 loss: 0.0471 (0.0473) time: 2.6180 data: 0.0059 max mem: 33369 +Epoch: [24] [1290/1319] eta: 0:01:16 lr: 2.0708608212110852e-05 loss: 0.0445 (0.0473) time: 2.6246 data: 0.0059 max mem: 33369 +Epoch: [24] [1300/1319] eta: 0:00:49 lr: 2.0699201147143737e-05 loss: 0.0445 (0.0473) time: 2.6229 data: 0.0057 max mem: 33369 +Epoch: [24] [1310/1319] eta: 0:00:23 lr: 2.0689793607132295e-05 loss: 0.0412 (0.0473) time: 2.6154 data: 0.0056 max mem: 33369 +Epoch: [24] Total time: 0:57:40 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 2:18:34 time: 3.2315 data: 3.1529 max mem: 33369 +Test: [ 100/2573] eta: 0:04:14 time: 0.0712 data: 0.0011 max mem: 33369 +Test: [ 200/2573] eta: 0:03:29 time: 0.0730 data: 0.0011 max mem: 33369 +Test: [ 300/2573] eta: 0:03:08 time: 0.0743 data: 0.0010 max mem: 33369 +Test: [ 400/2573] eta: 0:02:54 time: 0.0746 data: 0.0011 max mem: 33369 +Test: [ 500/2573] eta: 0:02:43 time: 0.0732 data: 0.0011 max mem: 33369 +Test: [ 600/2573] eta: 0:02:33 time: 0.0732 data: 0.0011 max mem: 33369 +Test: [ 700/2573] eta: 0:02:25 time: 0.0734 data: 0.0011 max mem: 33369 +Test: [ 800/2573] eta: 0:02:16 time: 0.0765 data: 0.0011 max mem: 33369 +Test: [ 900/2573] eta: 0:02:08 time: 0.0733 data: 0.0011 max mem: 33369 +Test: [1000/2573] eta: 0:02:00 time: 0.0735 data: 0.0011 max mem: 33369 +Test: [1100/2573] eta: 0:01:52 time: 0.0734 data: 0.0011 max mem: 33369 +Test: [1200/2573] eta: 0:01:44 time: 0.0733 data: 0.0011 max mem: 33369 +Test: [1300/2573] eta: 0:01:36 time: 0.0735 data: 0.0011 max mem: 33369 +Test: [1400/2573] eta: 0:01:28 time: 0.0719 data: 0.0011 max mem: 33369 +Test: [1500/2573] eta: 0:01:21 time: 0.0735 data: 0.0011 max mem: 33369 +Test: [1600/2573] eta: 0:01:13 time: 0.0769 data: 0.0011 max mem: 33369 +Test: [1700/2573] eta: 0:01:05 time: 0.0718 data: 0.0011 max mem: 33369 +Test: [1800/2573] eta: 0:00:58 time: 0.0752 data: 0.0011 max mem: 33369 +Test: [1900/2573] eta: 0:00:50 time: 0.0720 data: 0.0011 max mem: 33369 +Test: [2000/2573] eta: 0:00:42 time: 0.0737 data: 0.0011 max mem: 33369 +Test: [2100/2573] eta: 0:00:35 time: 0.0754 data: 0.0011 max mem: 33369 +Test: [2200/2573] eta: 0:00:27 time: 0.0756 data: 0.0011 max mem: 33369 +Test: [2300/2573] eta: 0:00:20 time: 0.0755 data: 0.0011 max mem: 33369 +Test: [2400/2573] eta: 0:00:12 time: 0.0705 data: 0.0011 max mem: 33369 +Test: [2500/2573] eta: 0:00:05 time: 0.0739 data: 0.0011 max mem: 33369 +Test: Total time: 0:03:12 +Final results: +Mean IoU is 64.08 + + precision@0.5 = 72.30 + precision@0.6 = 67.05 + precision@0.7 = 60.13 + precision@0.8 = 48.53 + precision@0.9 = 23.63 + overall IoU = 61.64 + +Average object IoU 64.08435019280705 +Overall IoU 61.63978576660156 +Better epoch: 24 + +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [25] [ 0/1319] eta: 1:31:23 lr: 2.0681326414740886e-05 loss: 0.0564 (0.0564) time: 4.1577 data: 1.3901 max mem: 33369 +Epoch: [25] [ 10/1319] eta: 1:01:06 lr: 2.0671917971417626e-05 loss: 0.0419 (0.0490) time: 2.8010 data: 0.1313 max mem: 33369 +Epoch: [25] [ 20/1319] eta: 0:58:53 lr: 2.0662509052283616e-05 loss: 0.0419 (0.0489) time: 2.6483 data: 0.0056 max mem: 33369 +Epoch: [25] [ 30/1319] eta: 0:58:05 lr: 2.0653099657074033e-05 loss: 0.0350 (0.0445) time: 2.6510 data: 0.0059 max mem: 33369 +Epoch: [25] [ 40/1319] eta: 0:57:10 lr: 2.064368978552377e-05 loss: 0.0353 (0.0436) time: 2.6421 data: 0.0060 max mem: 33369 +Epoch: [25] [ 50/1319] eta: 0:56:32 lr: 2.0634279437367437e-05 loss: 0.0354 (0.0427) time: 2.6260 data: 0.0061 max mem: 33369 +Epoch: [25] [ 60/1319] eta: 0:55:54 lr: 2.0624868612339364e-05 loss: 0.0344 (0.0416) time: 2.6272 data: 0.0062 max mem: 33369 +Epoch: [25] [ 70/1319] eta: 0:55:18 lr: 2.0615457310173584e-05 loss: 0.0330 (0.0408) time: 2.6151 data: 0.0061 max mem: 33369 +Epoch: [25] [ 80/1319] eta: 0:54:43 lr: 2.0606045530603866e-05 loss: 0.0406 (0.0411) time: 2.6078 data: 0.0060 max mem: 33369 +Epoch: [25] [ 90/1319] eta: 0:54:08 lr: 2.059663327336368e-05 loss: 0.0436 (0.0417) time: 2.5940 data: 0.0060 max mem: 33369 +Epoch: [25] [ 100/1319] eta: 0:53:39 lr: 2.058722053818622e-05 loss: 0.0378 (0.0411) time: 2.6030 data: 0.0060 max mem: 33369 +Epoch: [25] [ 110/1319] eta: 0:53:12 lr: 2.0577807324804403e-05 loss: 0.0399 (0.0416) time: 2.6269 data: 0.0059 max mem: 33369 +Epoch: [25] [ 120/1319] eta: 0:52:43 lr: 2.0568393632950847e-05 loss: 0.0452 (0.0419) time: 2.6255 data: 0.0061 max mem: 33369 +Epoch: [25] [ 130/1319] eta: 0:52:15 lr: 2.055897946235788e-05 loss: 0.0422 (0.0424) time: 2.6200 data: 0.0060 max mem: 33369 +Epoch: [25] [ 140/1319] eta: 0:51:47 lr: 2.054956481275756e-05 loss: 0.0336 (0.0422) time: 2.6205 data: 0.0057 max mem: 33369 +Epoch: [25] [ 150/1319] eta: 0:51:18 lr: 2.0540149683881653e-05 loss: 0.0368 (0.0424) time: 2.6067 data: 0.0059 max mem: 33369 +Epoch: [25] [ 160/1319] eta: 0:50:53 lr: 2.0530734075461633e-05 loss: 0.0344 (0.0422) time: 2.6267 data: 0.0061 max mem: 33369 +Epoch: [25] [ 170/1319] eta: 0:50:26 lr: 2.05213179872287e-05 loss: 0.0338 (0.0423) time: 2.6412 data: 0.0060 max mem: 33369 +Epoch: [25] [ 180/1319] eta: 0:50:01 lr: 2.051190141891374e-05 loss: 0.0356 (0.0422) time: 2.6417 data: 0.0060 max mem: 33369 +Epoch: [25] [ 190/1319] eta: 0:49:37 lr: 2.050248437024738e-05 loss: 0.0355 (0.0426) time: 2.6626 data: 0.0059 max mem: 33369 +Epoch: [25] [ 200/1319] eta: 0:49:07 lr: 2.049306684095994e-05 loss: 0.0448 (0.0426) time: 2.6257 data: 0.0060 max mem: 33369 +Epoch: [25] [ 210/1319] eta: 0:48:39 lr: 2.048364883078146e-05 loss: 0.0416 (0.0425) time: 2.5849 data: 0.0060 max mem: 33369 +Epoch: [25] [ 220/1319] eta: 0:48:11 lr: 2.0474230339441687e-05 loss: 0.0406 (0.0427) time: 2.5983 data: 0.0059 max mem: 33369 +Epoch: [25] [ 230/1319] eta: 0:47:45 lr: 2.0464811366670074e-05 loss: 0.0403 (0.0425) time: 2.6223 data: 0.0059 max mem: 33369 +Epoch: [25] [ 240/1319] eta: 0:47:17 lr: 2.0455391912195788e-05 loss: 0.0393 (0.0424) time: 2.6115 data: 0.0060 max mem: 33369 +Epoch: [25] [ 250/1319] eta: 0:46:49 lr: 2.0445971975747706e-05 loss: 0.0397 (0.0426) time: 2.5978 data: 0.0059 max mem: 33369 +Epoch: [25] [ 260/1319] eta: 0:46:22 lr: 2.0436551557054405e-05 loss: 0.0369 (0.0424) time: 2.6008 data: 0.0060 max mem: 33369 +Epoch: [25] [ 270/1319] eta: 0:45:54 lr: 2.0427130655844186e-05 loss: 0.0369 (0.0424) time: 2.5889 data: 0.0061 max mem: 33369 +Epoch: [25] [ 280/1319] eta: 0:45:27 lr: 2.041770927184505e-05 loss: 0.0383 (0.0426) time: 2.5979 data: 0.0058 max mem: 33369 +Epoch: [25] [ 290/1319] eta: 0:44:59 lr: 2.0408287404784693e-05 loss: 0.0374 (0.0425) time: 2.5998 data: 0.0059 max mem: 33369 +Epoch: [25] [ 300/1319] eta: 0:44:32 lr: 2.0398865054390533e-05 loss: 0.0364 (0.0427) time: 2.5833 data: 0.0060 max mem: 33369 +Epoch: [25] [ 310/1319] eta: 0:44:06 lr: 2.038944222038969e-05 loss: 0.0373 (0.0425) time: 2.6157 data: 0.0059 max mem: 33369 +Epoch: [25] [ 320/1319] eta: 0:43:40 lr: 2.0380018902508984e-05 loss: 0.0331 (0.0422) time: 2.6343 data: 0.0058 max mem: 33369 +Epoch: [25] [ 330/1319] eta: 0:43:14 lr: 2.0370595100474957e-05 loss: 0.0366 (0.0424) time: 2.6220 data: 0.0058 max mem: 33369 +Epoch: [25] [ 340/1319] eta: 0:42:47 lr: 2.036117081401383e-05 loss: 0.0424 (0.0425) time: 2.6125 data: 0.0059 max mem: 33369 +Epoch: [25] [ 350/1319] eta: 0:42:20 lr: 2.035174604285155e-05 loss: 0.0409 (0.0428) time: 2.5996 data: 0.0058 max mem: 33369 +Epoch: [25] [ 360/1319] eta: 0:41:55 lr: 2.0342320786713757e-05 loss: 0.0376 (0.0425) time: 2.6383 data: 0.0058 max mem: 33369 +Epoch: [25] [ 370/1319] eta: 0:41:28 lr: 2.03328950453258e-05 loss: 0.0330 (0.0424) time: 2.6324 data: 0.0058 max mem: 33369 +Epoch: [25] [ 380/1319] eta: 0:41:02 lr: 2.0323468818412736e-05 loss: 0.0384 (0.0423) time: 2.5977 data: 0.0057 max mem: 33369 +Epoch: [25] [ 390/1319] eta: 0:40:36 lr: 2.03140421056993e-05 loss: 0.0384 (0.0422) time: 2.6250 data: 0.0058 max mem: 33369 +Epoch: [25] [ 400/1319] eta: 0:40:10 lr: 2.0304614906909954e-05 loss: 0.0372 (0.0421) time: 2.6314 data: 0.0059 max mem: 33369 +Epoch: [25] [ 410/1319] eta: 0:39:44 lr: 2.0295187221768858e-05 loss: 0.0440 (0.0423) time: 2.6257 data: 0.0059 max mem: 33369 +Epoch: [25] [ 420/1319] eta: 0:39:17 lr: 2.028575904999986e-05 loss: 0.0440 (0.0423) time: 2.6183 data: 0.0059 max mem: 33369 +Epoch: [25] [ 430/1319] eta: 0:38:50 lr: 2.0276330391326524e-05 loss: 0.0426 (0.0424) time: 2.6020 data: 0.0058 max mem: 33369 +Epoch: [25] [ 440/1319] eta: 0:38:24 lr: 2.026690124547211e-05 loss: 0.0479 (0.0425) time: 2.5988 data: 0.0058 max mem: 33369 +Epoch: [25] [ 450/1319] eta: 0:37:57 lr: 2.025747161215956e-05 loss: 0.0446 (0.0425) time: 2.5953 data: 0.0058 max mem: 33369 +Epoch: [25] [ 460/1319] eta: 0:37:30 lr: 2.0248041491111535e-05 loss: 0.0407 (0.0426) time: 2.5955 data: 0.0059 max mem: 33369 +Epoch: [25] [ 470/1319] eta: 0:37:05 lr: 2.0238610882050398e-05 loss: 0.0448 (0.0427) time: 2.6234 data: 0.0059 max mem: 33369 +Epoch: [25] [ 480/1319] eta: 0:36:38 lr: 2.0229179784698192e-05 loss: 0.0407 (0.0426) time: 2.6236 data: 0.0059 max mem: 33369 +Epoch: [25] [ 490/1319] eta: 0:36:11 lr: 2.0219748198776674e-05 loss: 0.0391 (0.0426) time: 2.5990 data: 0.0058 max mem: 33369 +Epoch: [25] [ 500/1319] eta: 0:35:46 lr: 2.0210316124007283e-05 loss: 0.0418 (0.0428) time: 2.6249 data: 0.0058 max mem: 33369 +Epoch: [25] [ 510/1319] eta: 0:35:19 lr: 2.020088356011117e-05 loss: 0.0408 (0.0428) time: 2.6267 data: 0.0058 max mem: 33369 +Epoch: [25] [ 520/1319] eta: 0:34:53 lr: 2.019145050680917e-05 loss: 0.0381 (0.0427) time: 2.6091 data: 0.0060 max mem: 33369 +Epoch: [25] [ 530/1319] eta: 0:34:26 lr: 2.0182016963821814e-05 loss: 0.0393 (0.0428) time: 2.6059 data: 0.0060 max mem: 33369 +Epoch: [25] [ 540/1319] eta: 0:33:59 lr: 2.0172582930869342e-05 loss: 0.0393 (0.0428) time: 2.5801 data: 0.0059 max mem: 33369 +Epoch: [25] [ 550/1319] eta: 0:33:34 lr: 2.016314840767168e-05 loss: 0.0336 (0.0428) time: 2.6197 data: 0.0058 max mem: 33369 +Epoch: [25] [ 560/1319] eta: 0:33:08 lr: 2.0153713393948443e-05 loss: 0.0350 (0.0427) time: 2.6634 data: 0.0057 max mem: 33369 +Epoch: [25] [ 570/1319] eta: 0:32:41 lr: 2.014427788941894e-05 loss: 0.0387 (0.0427) time: 2.6063 data: 0.0057 max mem: 33369 +Epoch: [25] [ 580/1319] eta: 0:32:15 lr: 2.013484189380218e-05 loss: 0.0390 (0.0428) time: 2.5891 data: 0.0056 max mem: 33369 +Epoch: [25] [ 590/1319] eta: 0:31:49 lr: 2.012540540681687e-05 loss: 0.0452 (0.0429) time: 2.6250 data: 0.0055 max mem: 33369 +Epoch: [25] [ 600/1319] eta: 0:31:23 lr: 2.0115968428181397e-05 loss: 0.0432 (0.0430) time: 2.6139 data: 0.0056 max mem: 33369 +Epoch: [25] [ 610/1319] eta: 0:30:57 lr: 2.0106530957613837e-05 loss: 0.0432 (0.0431) time: 2.6279 data: 0.0059 max mem: 33369 +Epoch: [25] [ 620/1319] eta: 0:30:30 lr: 2.009709299483197e-05 loss: 0.0453 (0.0431) time: 2.6327 data: 0.0060 max mem: 33369 +Epoch: [25] [ 630/1319] eta: 0:30:05 lr: 2.0087654539553264e-05 loss: 0.0436 (0.0431) time: 2.6242 data: 0.0060 max mem: 33369 +Epoch: [25] [ 640/1319] eta: 0:29:38 lr: 2.007821559149487e-05 loss: 0.0436 (0.0432) time: 2.6335 data: 0.0058 max mem: 33369 +Epoch: [25] [ 650/1319] eta: 0:29:12 lr: 2.0068776150373638e-05 loss: 0.0428 (0.0432) time: 2.6228 data: 0.0057 max mem: 33369 +Epoch: [25] [ 660/1319] eta: 0:28:46 lr: 2.0059336215906098e-05 loss: 0.0391 (0.0432) time: 2.6129 data: 0.0057 max mem: 33369 +Epoch: [25] [ 670/1319] eta: 0:28:19 lr: 2.0049895787808467e-05 loss: 0.0420 (0.0433) time: 2.6000 data: 0.0059 max mem: 33369 +Epoch: [25] [ 680/1319] eta: 0:27:53 lr: 2.0040454865796668e-05 loss: 0.0411 (0.0432) time: 2.5965 data: 0.0060 max mem: 33369 +Epoch: [25] [ 690/1319] eta: 0:27:27 lr: 2.0031013449586292e-05 loss: 0.0367 (0.0433) time: 2.5981 data: 0.0058 max mem: 33369 +Epoch: [25] [ 700/1319] eta: 0:27:00 lr: 2.002157153889263e-05 loss: 0.0396 (0.0433) time: 2.5975 data: 0.0057 max mem: 33369 +Epoch: [25] [ 710/1319] eta: 0:26:34 lr: 2.0012129133430658e-05 loss: 0.0406 (0.0433) time: 2.5910 data: 0.0057 max mem: 33369 +Epoch: [25] [ 720/1319] eta: 0:26:08 lr: 2.0002686232915022e-05 loss: 0.0409 (0.0434) time: 2.6038 data: 0.0058 max mem: 33369 +Epoch: [25] [ 730/1319] eta: 0:25:42 lr: 1.9993242837060075e-05 loss: 0.0431 (0.0434) time: 2.6477 data: 0.0057 max mem: 33369 +Epoch: [25] [ 740/1319] eta: 0:25:16 lr: 1.9983798945579848e-05 loss: 0.0372 (0.0434) time: 2.6719 data: 0.0058 max mem: 33369 +Epoch: [25] [ 750/1319] eta: 0:24:50 lr: 1.9974354558188052e-05 loss: 0.0365 (0.0434) time: 2.6447 data: 0.0059 max mem: 33369 +Epoch: [25] [ 760/1319] eta: 0:24:24 lr: 1.9964909674598094e-05 loss: 0.0428 (0.0434) time: 2.6058 data: 0.0059 max mem: 33369 +Epoch: [25] [ 770/1319] eta: 0:23:57 lr: 1.9955464294523043e-05 loss: 0.0420 (0.0434) time: 2.5987 data: 0.0059 max mem: 33369 +Epoch: [25] [ 780/1319] eta: 0:23:31 lr: 1.994601841767567e-05 loss: 0.0425 (0.0434) time: 2.6166 data: 0.0059 max mem: 33369 +Epoch: [25] [ 790/1319] eta: 0:23:05 lr: 1.9936572043768427e-05 loss: 0.0503 (0.0436) time: 2.6187 data: 0.0057 max mem: 33369 +Epoch: [25] [ 800/1319] eta: 0:22:38 lr: 1.9927125172513435e-05 loss: 0.0454 (0.0435) time: 2.5967 data: 0.0059 max mem: 33369 +Epoch: [25] [ 810/1319] eta: 0:22:12 lr: 1.991767780362252e-05 loss: 0.0454 (0.0436) time: 2.5874 data: 0.0059 max mem: 33369 +Epoch: [25] [ 820/1319] eta: 0:21:46 lr: 1.990822993680716e-05 loss: 0.0437 (0.0436) time: 2.5729 data: 0.0057 max mem: 33369 +Epoch: [25] [ 830/1319] eta: 0:21:20 lr: 1.9898781571778537e-05 loss: 0.0406 (0.0436) time: 2.6090 data: 0.0057 max mem: 33369 +Epoch: [25] [ 840/1319] eta: 0:20:54 lr: 1.9889332708247497e-05 loss: 0.0407 (0.0437) time: 2.6465 data: 0.0058 max mem: 33369 +Epoch: [25] [ 850/1319] eta: 0:20:27 lr: 1.9879883345924575e-05 loss: 0.0461 (0.0437) time: 2.6249 data: 0.0058 max mem: 33369 +Epoch: [25] [ 860/1319] eta: 0:20:01 lr: 1.987043348451999e-05 loss: 0.0421 (0.0437) time: 2.6132 data: 0.0060 max mem: 33369 +Epoch: [25] [ 870/1319] eta: 0:19:35 lr: 1.9860983123743625e-05 loss: 0.0342 (0.0436) time: 2.6033 data: 0.0060 max mem: 33369 +Epoch: [25] [ 880/1319] eta: 0:19:09 lr: 1.9851532263305046e-05 loss: 0.0341 (0.0437) time: 2.6155 data: 0.0058 max mem: 33369 +Epoch: [25] [ 890/1319] eta: 0:18:42 lr: 1.98420809029135e-05 loss: 0.0455 (0.0438) time: 2.6002 data: 0.0057 max mem: 33369 +Epoch: [25] [ 900/1319] eta: 0:18:16 lr: 1.9832629042277908e-05 loss: 0.0455 (0.0437) time: 2.5920 data: 0.0056 max mem: 33369 +Epoch: [25] [ 910/1319] eta: 0:17:50 lr: 1.982317668110687e-05 loss: 0.0372 (0.0437) time: 2.6184 data: 0.0056 max mem: 33369 +Epoch: [25] [ 920/1319] eta: 0:17:24 lr: 1.981372381910867e-05 loss: 0.0361 (0.0437) time: 2.6109 data: 0.0057 max mem: 33369 +Epoch: [25] [ 930/1319] eta: 0:16:58 lr: 1.980427045599124e-05 loss: 0.0431 (0.0438) time: 2.6107 data: 0.0057 max mem: 33369 +Epoch: [25] [ 940/1319] eta: 0:16:32 lr: 1.9794816591462205e-05 loss: 0.0415 (0.0438) time: 2.6357 data: 0.0057 max mem: 33369 +Epoch: [25] [ 950/1319] eta: 0:16:05 lr: 1.9785362225228878e-05 loss: 0.0380 (0.0438) time: 2.6444 data: 0.0056 max mem: 33369 +Epoch: [25] [ 960/1319] eta: 0:15:39 lr: 1.9775907356998215e-05 loss: 0.0353 (0.0437) time: 2.6510 data: 0.0056 max mem: 33369 +Epoch: [25] [ 970/1319] eta: 0:15:14 lr: 1.976645198647688e-05 loss: 0.0364 (0.0437) time: 2.6763 data: 0.0055 max mem: 33369 +Epoch: [25] [ 980/1319] eta: 0:14:47 lr: 1.9756996113371165e-05 loss: 0.0409 (0.0437) time: 2.6493 data: 0.0055 max mem: 33369 +Epoch: [25] [ 990/1319] eta: 0:14:21 lr: 1.9747539737387077e-05 loss: 0.0409 (0.0437) time: 2.6096 data: 0.0056 max mem: 33369 +Epoch: [25] [1000/1319] eta: 0:13:55 lr: 1.973808285823027e-05 loss: 0.0378 (0.0437) time: 2.6250 data: 0.0057 max mem: 33369 +Epoch: [25] [1010/1319] eta: 0:13:29 lr: 1.972862547560608e-05 loss: 0.0387 (0.0437) time: 2.6239 data: 0.0057 max mem: 33369 +Epoch: [25] [1020/1319] eta: 0:13:03 lr: 1.9719167589219505e-05 loss: 0.0399 (0.0436) time: 2.6209 data: 0.0055 max mem: 33369 +Epoch: [25] [1030/1319] eta: 0:12:36 lr: 1.9709709198775227e-05 loss: 0.0403 (0.0436) time: 2.6226 data: 0.0055 max mem: 33369 +Epoch: [25] [1040/1319] eta: 0:12:10 lr: 1.9700250303977575e-05 loss: 0.0437 (0.0437) time: 2.6178 data: 0.0056 max mem: 33369 +Epoch: [25] [1050/1319] eta: 0:11:44 lr: 1.969079090453056e-05 loss: 0.0383 (0.0436) time: 2.6080 data: 0.0057 max mem: 33369 +Epoch: [25] [1060/1319] eta: 0:11:18 lr: 1.968133100013787e-05 loss: 0.0359 (0.0436) time: 2.5976 data: 0.0056 max mem: 33369 +Epoch: [25] [1070/1319] eta: 0:10:51 lr: 1.967187059050284e-05 loss: 0.0424 (0.0437) time: 2.6024 data: 0.0057 max mem: 33369 +Epoch: [25] [1080/1319] eta: 0:10:25 lr: 1.9662409675328494e-05 loss: 0.0427 (0.0437) time: 2.6101 data: 0.0057 max mem: 33369 +Epoch: [25] [1090/1319] eta: 0:09:59 lr: 1.9652948254317503e-05 loss: 0.0462 (0.0437) time: 2.6238 data: 0.0057 max mem: 33369 +Epoch: [25] [1100/1319] eta: 0:09:33 lr: 1.9643486327172213e-05 loss: 0.0451 (0.0438) time: 2.6372 data: 0.0057 max mem: 33369 +Epoch: [25] [1110/1319] eta: 0:09:07 lr: 1.9634023893594635e-05 loss: 0.0420 (0.0437) time: 2.6302 data: 0.0058 max mem: 33369 +Epoch: [25] [1120/1319] eta: 0:08:41 lr: 1.9624560953286446e-05 loss: 0.0378 (0.0438) time: 2.6177 data: 0.0061 max mem: 33369 +Epoch: [25] [1130/1319] eta: 0:08:15 lr: 1.961509750594899e-05 loss: 0.0409 (0.0439) time: 2.6442 data: 0.0061 max mem: 33369 +Epoch: [25] [1140/1319] eta: 0:07:48 lr: 1.9605633551283273e-05 loss: 0.0454 (0.0438) time: 2.6344 data: 0.0059 max mem: 33369 +Epoch: [25] [1150/1319] eta: 0:07:22 lr: 1.9596169088989948e-05 loss: 0.0417 (0.0438) time: 2.5953 data: 0.0058 max mem: 33369 +Epoch: [25] [1160/1319] eta: 0:06:56 lr: 1.9586704118769358e-05 loss: 0.0391 (0.0438) time: 2.6077 data: 0.0058 max mem: 33369 +Epoch: [25] [1170/1319] eta: 0:06:30 lr: 1.9577238640321492e-05 loss: 0.0424 (0.0438) time: 2.6194 data: 0.0058 max mem: 33369 +Epoch: [25] [1180/1319] eta: 0:06:04 lr: 1.9567772653346e-05 loss: 0.0423 (0.0439) time: 2.6173 data: 0.0058 max mem: 33369 +Epoch: [25] [1190/1319] eta: 0:05:37 lr: 1.9558306157542204e-05 loss: 0.0394 (0.0439) time: 2.6373 data: 0.0060 max mem: 33369 +Epoch: [25] [1200/1319] eta: 0:05:11 lr: 1.9548839152609067e-05 loss: 0.0441 (0.0440) time: 2.6296 data: 0.0060 max mem: 33369 +Epoch: [25] [1210/1319] eta: 0:04:45 lr: 1.9539371638245233e-05 loss: 0.0408 (0.0439) time: 2.6127 data: 0.0057 max mem: 33369 +Epoch: [25] [1220/1319] eta: 0:04:19 lr: 1.952990361414899e-05 loss: 0.0408 (0.0439) time: 2.6343 data: 0.0056 max mem: 33369 +Epoch: [25] [1230/1319] eta: 0:03:53 lr: 1.9520435080018294e-05 loss: 0.0480 (0.0440) time: 2.6546 data: 0.0057 max mem: 33369 +Epoch: [25] [1240/1319] eta: 0:03:26 lr: 1.9510966035550763e-05 loss: 0.0448 (0.0440) time: 2.6498 data: 0.0058 max mem: 33369 +Epoch: [25] [1250/1319] eta: 0:03:00 lr: 1.9501496480443652e-05 loss: 0.0452 (0.0441) time: 2.6150 data: 0.0059 max mem: 33369 +Epoch: [25] [1260/1319] eta: 0:02:34 lr: 1.9492026414393892e-05 loss: 0.0414 (0.0441) time: 2.5787 data: 0.0059 max mem: 33369 +Epoch: [25] [1270/1319] eta: 0:02:08 lr: 1.9482555837098063e-05 loss: 0.0446 (0.0442) time: 2.6066 data: 0.0057 max mem: 33369 +Epoch: [25] [1280/1319] eta: 0:01:42 lr: 1.9473084748252403e-05 loss: 0.0484 (0.0442) time: 2.6211 data: 0.0058 max mem: 33369 +Epoch: [25] [1290/1319] eta: 0:01:15 lr: 1.9463613147552807e-05 loss: 0.0421 (0.0442) time: 2.5911 data: 0.0060 max mem: 33369 +Epoch: [25] [1300/1319] eta: 0:00:49 lr: 1.9454141034694828e-05 loss: 0.0401 (0.0442) time: 2.5860 data: 0.0060 max mem: 33369 +Epoch: [25] [1310/1319] eta: 0:00:23 lr: 1.9444668409373652e-05 loss: 0.0406 (0.0443) time: 2.5999 data: 0.0057 max mem: 33369 +Epoch: [25] Total time: 0:57:34 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 2:25:20 time: 3.3893 data: 3.3031 max mem: 33369 +Test: [ 100/2573] eta: 0:04:18 time: 0.0711 data: 0.0011 max mem: 33369 +Test: [ 200/2573] eta: 0:03:31 time: 0.0730 data: 0.0011 max mem: 33369 +Test: [ 300/2573] eta: 0:03:09 time: 0.0748 data: 0.0011 max mem: 33369 +Test: [ 400/2573] eta: 0:02:55 time: 0.0748 data: 0.0011 max mem: 33369 +Test: [ 500/2573] eta: 0:02:44 time: 0.0733 data: 0.0011 max mem: 33369 +Test: [ 600/2573] eta: 0:02:34 time: 0.0736 data: 0.0012 max mem: 33369 +Test: [ 700/2573] eta: 0:02:26 time: 0.0735 data: 0.0011 max mem: 33369 +Test: [ 800/2573] eta: 0:02:17 time: 0.0769 data: 0.0010 max mem: 33369 +Test: [ 900/2573] eta: 0:02:09 time: 0.0738 data: 0.0011 max mem: 33369 +Test: [1000/2573] eta: 0:02:01 time: 0.0736 data: 0.0011 max mem: 33369 +Test: [1100/2573] eta: 0:01:52 time: 0.0737 data: 0.0011 max mem: 33369 +Test: [1200/2573] eta: 0:01:45 time: 0.0738 data: 0.0011 max mem: 33369 +Test: [1300/2573] eta: 0:01:37 time: 0.0738 data: 0.0011 max mem: 33369 +Test: [1400/2573] eta: 0:01:29 time: 0.0721 data: 0.0011 max mem: 33369 +Test: [1500/2573] eta: 0:01:21 time: 0.0739 data: 0.0011 max mem: 33369 +Test: [1600/2573] eta: 0:01:13 time: 0.0772 data: 0.0011 max mem: 33369 +Test: [1700/2573] eta: 0:01:06 time: 0.0723 data: 0.0011 max mem: 33369 +Test: [1800/2573] eta: 0:00:58 time: 0.0756 data: 0.0011 max mem: 33369 +Test: [1900/2573] eta: 0:00:50 time: 0.0725 data: 0.0011 max mem: 33369 +Test: [2000/2573] eta: 0:00:43 time: 0.0740 data: 0.0011 max mem: 33369 +Test: [2100/2573] eta: 0:00:35 time: 0.0757 data: 0.0011 max mem: 33369 +Test: [2200/2573] eta: 0:00:28 time: 0.0757 data: 0.0011 max mem: 33369 +Test: [2300/2573] eta: 0:00:20 time: 0.0758 data: 0.0012 max mem: 33369 +Test: [2400/2573] eta: 0:00:12 time: 0.0707 data: 0.0011 max mem: 33369 +Test: [2500/2573] eta: 0:00:05 time: 0.0742 data: 0.0011 max mem: 33369 +Test: Total time: 0:03:13 +Final results: +Mean IoU is 64.15 + + precision@0.5 = 72.02 + precision@0.6 = 66.99 + precision@0.7 = 60.27 + precision@0.8 = 49.18 + precision@0.9 = 24.73 + overall IoU = 61.89 + +Average object IoU 64.1526710786845 +Overall IoU 61.8935661315918 +Better epoch: 25 + +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [26] [ 0/1319] eta: 1:30:48 lr: 1.943614260817638e-05 loss: 0.0389 (0.0389) time: 4.1306 data: 1.3695 max mem: 33369 +Epoch: [26] [ 10/1319] eta: 1:00:48 lr: 1.9426669008334188e-05 loss: 0.0453 (0.0438) time: 2.7869 data: 0.1298 max mem: 33369 +Epoch: [26] [ 20/1319] eta: 0:58:43 lr: 1.941719489514293e-05 loss: 0.0453 (0.0442) time: 2.6420 data: 0.0057 max mem: 33369 +Epoch: [26] [ 30/1319] eta: 0:57:31 lr: 1.9407720268296455e-05 loss: 0.0384 (0.0427) time: 2.6170 data: 0.0059 max mem: 33369 +Epoch: [26] [ 40/1319] eta: 0:56:46 lr: 1.9398245127488253e-05 loss: 0.0364 (0.0418) time: 2.6118 data: 0.0061 max mem: 33369 +Epoch: [26] [ 50/1319] eta: 0:56:07 lr: 1.9388769472411493e-05 loss: 0.0338 (0.0422) time: 2.6177 data: 0.0061 max mem: 33369 +Epoch: [26] [ 60/1319] eta: 0:55:34 lr: 1.9379293302758954e-05 loss: 0.0364 (0.0421) time: 2.6166 data: 0.0062 max mem: 33369 +Epoch: [26] [ 70/1319] eta: 0:54:55 lr: 1.936981661822309e-05 loss: 0.0384 (0.0422) time: 2.5989 data: 0.0061 max mem: 33369 +Epoch: [26] [ 80/1319] eta: 0:54:29 lr: 1.9360339418495996e-05 loss: 0.0384 (0.0426) time: 2.6098 data: 0.0059 max mem: 33369 +Epoch: [26] [ 90/1319] eta: 0:54:01 lr: 1.935086170326942e-05 loss: 0.0374 (0.0427) time: 2.6354 data: 0.0059 max mem: 33369 +Epoch: [26] [ 100/1319] eta: 0:53:34 lr: 1.934138347223476e-05 loss: 0.0412 (0.0432) time: 2.6292 data: 0.0060 max mem: 33369 +Epoch: [26] [ 110/1319] eta: 0:53:08 lr: 1.9331904725083057e-05 loss: 0.0408 (0.0427) time: 2.6336 data: 0.0060 max mem: 33369 +Epoch: [26] [ 120/1319] eta: 0:52:37 lr: 1.9322425461504988e-05 loss: 0.0366 (0.0427) time: 2.6186 data: 0.0060 max mem: 33369 +Epoch: [26] [ 130/1319] eta: 0:52:10 lr: 1.931294568119089e-05 loss: 0.0386 (0.0432) time: 2.6111 data: 0.0059 max mem: 33369 +Epoch: [26] [ 140/1319] eta: 0:51:39 lr: 1.930346538383074e-05 loss: 0.0461 (0.0436) time: 2.6014 data: 0.0059 max mem: 33369 +Epoch: [26] [ 150/1319] eta: 0:51:16 lr: 1.9293984569114164e-05 loss: 0.0404 (0.0434) time: 2.6220 data: 0.0061 max mem: 33369 +Epoch: [26] [ 160/1319] eta: 0:50:49 lr: 1.9284503236730435e-05 loss: 0.0391 (0.0432) time: 2.6416 data: 0.0062 max mem: 33369 +Epoch: [26] [ 170/1319] eta: 0:50:23 lr: 1.927502138636845e-05 loss: 0.0460 (0.0436) time: 2.6272 data: 0.0060 max mem: 33369 +Epoch: [26] [ 180/1319] eta: 0:49:56 lr: 1.9265539017716765e-05 loss: 0.0345 (0.0432) time: 2.6291 data: 0.0058 max mem: 33369 +Epoch: [26] [ 190/1319] eta: 0:49:29 lr: 1.9256056130463582e-05 loss: 0.0369 (0.0437) time: 2.6218 data: 0.0059 max mem: 33369 +Epoch: [26] [ 200/1319] eta: 0:49:02 lr: 1.9246572724296735e-05 loss: 0.0386 (0.0433) time: 2.6249 data: 0.0059 max mem: 33369 +Epoch: [26] [ 210/1319] eta: 0:48:35 lr: 1.9237088798903708e-05 loss: 0.0353 (0.0432) time: 2.6189 data: 0.0060 max mem: 33369 +Epoch: [26] [ 220/1319] eta: 0:48:06 lr: 1.922760435397161e-05 loss: 0.0396 (0.0433) time: 2.5932 data: 0.0060 max mem: 33369 +Epoch: [26] [ 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33369 +Epoch: [26] [ 310/1319] eta: 0:44:07 lr: 1.9142220918520593e-05 loss: 0.0390 (0.0435) time: 2.6471 data: 0.0060 max mem: 33369 +Epoch: [26] [ 320/1319] eta: 0:43:42 lr: 1.9132731260909836e-05 loss: 0.0305 (0.0432) time: 2.6621 data: 0.0060 max mem: 33369 +Epoch: [26] [ 330/1319] eta: 0:43:15 lr: 1.9123241080294413e-05 loss: 0.0369 (0.0433) time: 2.6249 data: 0.0060 max mem: 33369 +Epoch: [26] [ 340/1319] eta: 0:42:48 lr: 1.9113750376357084e-05 loss: 0.0437 (0.0435) time: 2.6061 data: 0.0058 max mem: 33369 +Epoch: [26] [ 350/1319] eta: 0:42:22 lr: 1.9104259148780233e-05 loss: 0.0358 (0.0432) time: 2.6233 data: 0.0057 max mem: 33369 +Epoch: [26] [ 360/1319] eta: 0:41:57 lr: 1.909476739724589e-05 loss: 0.0364 (0.0431) time: 2.6493 data: 0.0058 max mem: 33369 +Epoch: [26] [ 370/1319] eta: 0:41:30 lr: 1.9085275121435705e-05 loss: 0.0433 (0.0432) time: 2.6345 data: 0.0058 max mem: 33369 +Epoch: [26] [ 380/1319] eta: 0:41:04 lr: 1.907578232103095e-05 loss: 0.0409 (0.0431) time: 2.5997 data: 0.0058 max mem: 33369 +Epoch: [26] [ 390/1319] eta: 0:40:37 lr: 1.906628899571255e-05 loss: 0.0401 (0.0430) time: 2.6006 data: 0.0060 max mem: 33369 +Epoch: [26] [ 400/1319] eta: 0:40:10 lr: 1.9056795145161037e-05 loss: 0.0359 (0.0429) time: 2.6125 data: 0.0059 max mem: 33369 +Epoch: [26] [ 410/1319] eta: 0:39:44 lr: 1.9047300769056588e-05 loss: 0.0320 (0.0427) time: 2.6150 data: 0.0057 max mem: 33369 +Epoch: [26] [ 420/1319] eta: 0:39:18 lr: 1.9037805867078998e-05 loss: 0.0357 (0.0429) time: 2.6227 data: 0.0058 max mem: 33369 +Epoch: [26] [ 430/1319] eta: 0:38:52 lr: 1.9028310438907695e-05 loss: 0.0394 (0.0428) time: 2.6364 data: 0.0059 max mem: 33369 +Epoch: [26] [ 440/1319] eta: 0:38:25 lr: 1.901881448422173e-05 loss: 0.0352 (0.0427) time: 2.6044 data: 0.0060 max mem: 33369 +Epoch: [26] [ 450/1319] eta: 0:37:58 lr: 1.900931800269978e-05 loss: 0.0352 (0.0427) time: 2.5938 data: 0.0058 max mem: 33369 +Epoch: [26] [ 460/1319] eta: 0:37:32 lr: 1.8999820994020145e-05 loss: 0.0341 (0.0425) time: 2.6256 data: 0.0059 max mem: 33369 +Epoch: [26] [ 470/1319] eta: 0:37:06 lr: 1.899032345786076e-05 loss: 0.0318 (0.0424) time: 2.6257 data: 0.0060 max mem: 33369 +Epoch: [26] [ 480/1319] eta: 0:36:40 lr: 1.8980825393899182e-05 loss: 0.0329 (0.0424) time: 2.6098 data: 0.0058 max mem: 33369 +Epoch: [26] [ 490/1319] eta: 0:36:13 lr: 1.897132680181258e-05 loss: 0.0413 (0.0424) time: 2.5979 data: 0.0059 max mem: 33369 +Epoch: [26] [ 500/1319] eta: 0:35:46 lr: 1.8961827681277747e-05 loss: 0.0402 (0.0424) time: 2.5830 data: 0.0059 max mem: 33369 +Epoch: [26] [ 510/1319] eta: 0:35:19 lr: 1.8952328031971114e-05 loss: 0.0380 (0.0424) time: 2.5891 data: 0.0058 max mem: 33369 +Epoch: [26] [ 520/1319] eta: 0:34:53 lr: 1.8942827853568723e-05 loss: 0.0380 (0.0424) time: 2.6104 data: 0.0058 max mem: 33369 +Epoch: [26] [ 530/1319] eta: 0:34:27 lr: 1.893332714574624e-05 loss: 0.0439 (0.0424) time: 2.6115 data: 0.0058 max mem: 33369 +Epoch: [26] [ 540/1319] eta: 0:34:01 lr: 1.892382590817894e-05 loss: 0.0362 (0.0423) time: 2.6286 data: 0.0059 max mem: 33369 +Epoch: [26] [ 550/1319] eta: 0:33:34 lr: 1.8914324140541728e-05 loss: 0.0347 (0.0423) time: 2.6099 data: 0.0059 max mem: 33369 +Epoch: [26] [ 560/1319] eta: 0:33:08 lr: 1.8904821842509134e-05 loss: 0.0356 (0.0422) time: 2.5987 data: 0.0058 max mem: 33369 +Epoch: [26] [ 570/1319] eta: 0:32:42 lr: 1.889531901375529e-05 loss: 0.0385 (0.0422) time: 2.6356 data: 0.0058 max mem: 33369 +Epoch: [26] [ 580/1319] eta: 0:32:15 lr: 1.888581565395396e-05 loss: 0.0426 (0.0426) time: 2.6091 data: 0.0058 max mem: 33369 +Epoch: [26] [ 590/1319] eta: 0:31:49 lr: 1.8876311762778523e-05 loss: 0.0355 (0.0426) time: 2.6087 data: 0.0059 max mem: 33369 +Epoch: [26] [ 600/1319] eta: 0:31:23 lr: 1.8866807339901958e-05 loss: 0.0404 (0.0426) time: 2.6283 data: 0.0059 max mem: 33369 +Epoch: [26] [ 610/1319] eta: 0:30:57 lr: 1.885730238499688e-05 loss: 0.0468 (0.0428) time: 2.6289 data: 0.0060 max mem: 33369 +Epoch: [26] [ 620/1319] eta: 0:30:31 lr: 1.8847796897735508e-05 loss: 0.0433 (0.0428) time: 2.6189 data: 0.0061 max mem: 33369 +Epoch: [26] [ 630/1319] eta: 0:30:05 lr: 1.8838290877789684e-05 loss: 0.0402 (0.0428) time: 2.6172 data: 0.0061 max mem: 33369 +Epoch: [26] [ 640/1319] eta: 0:29:38 lr: 1.882878432483085e-05 loss: 0.0378 (0.0428) time: 2.6263 data: 0.0059 max mem: 33369 +Epoch: [26] [ 650/1319] eta: 0:29:12 lr: 1.8819277238530077e-05 loss: 0.0411 (0.0428) time: 2.6146 data: 0.0057 max mem: 33369 +Epoch: [26] [ 660/1319] eta: 0:28:46 lr: 1.880976961855803e-05 loss: 0.0474 (0.0429) time: 2.6020 data: 0.0056 max mem: 33369 +Epoch: [26] [ 670/1319] eta: 0:28:19 lr: 1.8800261464585002e-05 loss: 0.0485 (0.0430) time: 2.6017 data: 0.0057 max mem: 33369 +Epoch: [26] [ 680/1319] eta: 0:27:53 lr: 1.8790752776280883e-05 loss: 0.0434 (0.0430) time: 2.5978 data: 0.0058 max mem: 33369 +Epoch: [26] [ 690/1319] eta: 0:27:26 lr: 1.8781243553315193e-05 loss: 0.0396 (0.0430) time: 2.5873 data: 0.0058 max mem: 33369 +Epoch: [26] [ 700/1319] eta: 0:27:00 lr: 1.8771733795357048e-05 loss: 0.0381 (0.0431) time: 2.6008 data: 0.0058 max mem: 33369 +Epoch: [26] [ 710/1319] eta: 0:26:34 lr: 1.876222350207516e-05 loss: 0.0421 (0.0432) time: 2.5967 data: 0.0061 max mem: 33369 +Epoch: [26] [ 720/1319] eta: 0:26:08 lr: 1.875271267313787e-05 loss: 0.0404 (0.0431) time: 2.6016 data: 0.0059 max mem: 33369 +Epoch: [26] [ 730/1319] eta: 0:25:42 lr: 1.8743201308213124e-05 loss: 0.0386 (0.0431) time: 2.6442 data: 0.0057 max mem: 33369 +Epoch: [26] [ 740/1319] eta: 0:25:16 lr: 1.8733689406968465e-05 loss: 0.0399 (0.0431) time: 2.6468 data: 0.0058 max mem: 33369 +Epoch: [26] [ 750/1319] eta: 0:24:50 lr: 1.872417696907106e-05 loss: 0.0383 (0.0430) time: 2.6485 data: 0.0057 max mem: 33369 +Epoch: [26] [ 760/1319] eta: 0:24:24 lr: 1.871466399418765e-05 loss: 0.0409 (0.0431) time: 2.6436 data: 0.0058 max mem: 33369 +Epoch: [26] [ 770/1319] eta: 0:23:58 lr: 1.870515048198461e-05 loss: 0.0409 (0.0430) time: 2.6381 data: 0.0058 max mem: 33369 +Epoch: [26] [ 780/1319] eta: 0:23:32 lr: 1.8695636432127905e-05 loss: 0.0400 (0.0430) time: 2.6398 data: 0.0058 max mem: 33369 +Epoch: [26] [ 790/1319] eta: 0:23:06 lr: 1.8686121844283114e-05 loss: 0.0360 (0.0429) time: 2.6499 data: 0.0058 max mem: 33369 +Epoch: [26] [ 800/1319] eta: 0:22:39 lr: 1.8676606718115407e-05 loss: 0.0334 (0.0429) time: 2.6436 data: 0.0058 max mem: 33369 +Epoch: [26] [ 810/1319] eta: 0:22:13 lr: 1.866709105328956e-05 loss: 0.0359 (0.0429) time: 2.6098 data: 0.0059 max mem: 33369 +Epoch: [26] [ 820/1319] eta: 0:21:47 lr: 1.8657574849469954e-05 loss: 0.0359 (0.0428) time: 2.6039 data: 0.0058 max mem: 33369 +Epoch: [26] [ 830/1319] eta: 0:21:21 lr: 1.864805810632056e-05 loss: 0.0368 (0.0427) time: 2.6187 data: 0.0058 max mem: 33369 +Epoch: [26] [ 840/1319] eta: 0:20:54 lr: 1.8638540823504965e-05 loss: 0.0367 (0.0428) time: 2.5941 data: 0.0058 max mem: 33369 +Epoch: [26] [ 850/1319] eta: 0:20:28 lr: 1.8629023000686338e-05 loss: 0.0338 (0.0428) time: 2.5707 data: 0.0058 max mem: 33369 +Epoch: [26] [ 860/1319] eta: 0:20:01 lr: 1.8619504637527467e-05 loss: 0.0374 (0.0428) time: 2.5830 data: 0.0059 max mem: 33369 +Epoch: [26] [ 870/1319] eta: 0:19:35 lr: 1.8609985733690715e-05 loss: 0.0374 (0.0428) time: 2.6051 data: 0.0059 max mem: 33369 +Epoch: [26] [ 880/1319] eta: 0:19:09 lr: 1.860046628883806e-05 loss: 0.0388 (0.0428) time: 2.6247 data: 0.0059 max mem: 33369 +Epoch: [26] [ 890/1319] eta: 0:18:43 lr: 1.859094630263106e-05 loss: 0.0398 (0.0428) time: 2.6135 data: 0.0059 max mem: 33369 +Epoch: [26] [ 900/1319] eta: 0:18:17 lr: 1.8581425774730882e-05 loss: 0.0393 (0.0429) time: 2.6117 data: 0.0058 max mem: 33369 +Epoch: [26] [ 910/1319] eta: 0:17:51 lr: 1.8571904704798292e-05 loss: 0.0378 (0.0429) time: 2.6280 data: 0.0057 max mem: 33369 +Epoch: [26] [ 920/1319] eta: 0:17:24 lr: 1.856238309249363e-05 loss: 0.0447 (0.0430) time: 2.6121 data: 0.0060 max mem: 33369 +Epoch: [26] [ 930/1319] eta: 0:16:58 lr: 1.855286093747684e-05 loss: 0.0371 (0.0431) time: 2.6137 data: 0.0062 max mem: 33369 +Epoch: [26] [ 940/1319] eta: 0:16:32 lr: 1.854333823940747e-05 loss: 0.0352 (0.0430) time: 2.6526 data: 0.0059 max mem: 33369 +Epoch: [26] [ 950/1319] eta: 0:16:06 lr: 1.853381499794464e-05 loss: 0.0382 (0.0430) time: 2.6323 data: 0.0058 max mem: 33369 +Epoch: [26] [ 960/1319] eta: 0:15:40 lr: 1.8524291212747084e-05 loss: 0.0394 (0.0430) time: 2.6208 data: 0.0059 max mem: 33369 +Epoch: [26] [ 970/1319] eta: 0:15:14 lr: 1.85147668834731e-05 loss: 0.0390 (0.0429) time: 2.6409 data: 0.0058 max mem: 33369 +Epoch: [26] [ 980/1319] eta: 0:14:47 lr: 1.8505242009780593e-05 loss: 0.0390 (0.0430) time: 2.6291 data: 0.0056 max mem: 33369 +Epoch: [26] [ 990/1319] eta: 0:14:21 lr: 1.8495716591327057e-05 loss: 0.0366 (0.0430) time: 2.6208 data: 0.0057 max mem: 33369 +Epoch: [26] [1000/1319] eta: 0:13:55 lr: 1.848619062776957e-05 loss: 0.0366 (0.0430) time: 2.6073 data: 0.0056 max mem: 33369 +Epoch: [26] [1010/1319] eta: 0:13:29 lr: 1.8476664118764797e-05 loss: 0.0353 (0.0429) time: 2.6037 data: 0.0058 max mem: 33369 +Epoch: [26] [1020/1319] eta: 0:13:03 lr: 1.8467137063969e-05 loss: 0.0352 (0.0432) time: 2.6261 data: 0.0058 max mem: 33369 +Epoch: [26] [1030/1319] eta: 0:12:37 lr: 1.8457609463038007e-05 loss: 0.0388 (0.0431) time: 2.6512 data: 0.0059 max mem: 33369 +Epoch: [26] [1040/1319] eta: 0:12:10 lr: 1.8448081315627246e-05 loss: 0.0371 (0.0431) time: 2.6592 data: 0.0059 max mem: 33369 +Epoch: [26] [1050/1319] eta: 0:11:44 lr: 1.843855262139173e-05 loss: 0.0360 (0.0430) time: 2.6237 data: 0.0057 max mem: 33369 +Epoch: [26] [1060/1319] eta: 0:11:18 lr: 1.8429023379986053e-05 loss: 0.0360 (0.0430) time: 2.5947 data: 0.0057 max mem: 33369 +Epoch: [26] [1070/1319] eta: 0:10:52 lr: 1.8419493591064395e-05 loss: 0.0370 (0.0430) time: 2.6046 data: 0.0057 max mem: 33369 +Epoch: [26] [1080/1319] eta: 0:10:26 lr: 1.840996325428051e-05 loss: 0.0361 (0.0431) time: 2.6219 data: 0.0057 max mem: 33369 +Epoch: [26] [1090/1319] eta: 0:09:59 lr: 1.840043236928774e-05 loss: 0.0368 (0.0430) time: 2.6307 data: 0.0058 max mem: 33369 +Epoch: [26] [1100/1319] eta: 0:09:33 lr: 1.839090093573901e-05 loss: 0.0399 (0.0431) time: 2.6106 data: 0.0057 max mem: 33369 +Epoch: [26] [1110/1319] eta: 0:09:07 lr: 1.838136895328682e-05 loss: 0.0409 (0.0431) time: 2.5912 data: 0.0057 max mem: 33369 +Epoch: [26] [1120/1319] eta: 0:08:41 lr: 1.8371836421583257e-05 loss: 0.0406 (0.0430) time: 2.6348 data: 0.0057 max mem: 33369 +Epoch: [26] [1130/1319] eta: 0:08:15 lr: 1.836230334027998e-05 loss: 0.0376 (0.0430) time: 2.6485 data: 0.0056 max mem: 33369 +Epoch: [26] [1140/1319] eta: 0:07:48 lr: 1.8352769709028224e-05 loss: 0.0390 (0.0430) time: 2.6145 data: 0.0056 max mem: 33369 +Epoch: [26] [1150/1319] eta: 0:07:22 lr: 1.8343235527478807e-05 loss: 0.0360 (0.0429) time: 2.6025 data: 0.0057 max mem: 33369 +Epoch: [26] [1160/1319] eta: 0:06:56 lr: 1.8333700795282125e-05 loss: 0.0360 (0.0429) time: 2.6391 data: 0.0057 max mem: 33369 +Epoch: [26] [1170/1319] eta: 0:06:30 lr: 1.832416551208814e-05 loss: 0.0387 (0.0430) time: 2.6573 data: 0.0056 max mem: 33369 +Epoch: [26] [1180/1319] eta: 0:06:04 lr: 1.8314629677546413e-05 loss: 0.0386 (0.0429) time: 2.6320 data: 0.0056 max mem: 33369 +Epoch: [26] [1190/1319] eta: 0:05:37 lr: 1.8305093291306038e-05 loss: 0.0403 (0.0429) time: 2.6198 data: 0.0057 max mem: 33369 +Epoch: [26] [1200/1319] eta: 0:05:11 lr: 1.829555635301572e-05 loss: 0.0383 (0.0429) time: 2.6091 data: 0.0057 max mem: 33369 +Epoch: [26] [1210/1319] eta: 0:04:45 lr: 1.8286018862323718e-05 loss: 0.0368 (0.0428) time: 2.6185 data: 0.0057 max mem: 33369 +Epoch: [26] [1220/1319] eta: 0:04:19 lr: 1.8276480818877866e-05 loss: 0.0382 (0.0429) time: 2.6239 data: 0.0057 max mem: 33369 +Epoch: [26] [1230/1319] eta: 0:03:53 lr: 1.8266942222325584e-05 loss: 0.0373 (0.0428) time: 2.6023 data: 0.0058 max mem: 33369 +Epoch: [26] [1240/1319] eta: 0:03:26 lr: 1.8257403072313833e-05 loss: 0.0344 (0.0428) time: 2.6160 data: 0.0059 max mem: 33369 +Epoch: [26] [1250/1319] eta: 0:03:00 lr: 1.8247863368489165e-05 loss: 0.0350 (0.0428) time: 2.6277 data: 0.0057 max mem: 33369 +Epoch: [26] [1260/1319] eta: 0:02:34 lr: 1.8238323110497695e-05 loss: 0.0391 (0.0429) time: 2.6247 data: 0.0055 max mem: 33369 +Epoch: [26] [1270/1319] eta: 0:02:08 lr: 1.822878229798511e-05 loss: 0.0411 (0.0429) time: 2.6377 data: 0.0057 max mem: 33369 +Epoch: [26] [1280/1319] eta: 0:01:42 lr: 1.821924093059666e-05 loss: 0.0349 (0.0429) time: 2.6195 data: 0.0057 max mem: 33369 +Epoch: [26] [1290/1319] eta: 0:01:15 lr: 1.8209699007977167e-05 loss: 0.0337 (0.0428) time: 2.6110 data: 0.0057 max mem: 33369 +Epoch: [26] [1300/1319] eta: 0:00:49 lr: 1.8200156529771002e-05 loss: 0.0331 (0.0428) time: 2.6222 data: 0.0058 max mem: 33369 +Epoch: [26] [1310/1319] eta: 0:00:23 lr: 1.819061349562212e-05 loss: 0.0423 (0.0428) time: 2.6024 data: 0.0056 max mem: 33369 +Epoch: [26] Total time: 0:57:36 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 2:09:41 time: 3.0243 data: 2.9460 max mem: 33369 +Test: [ 100/2573] eta: 0:04:10 time: 0.0715 data: 0.0011 max mem: 33369 +Test: [ 200/2573] eta: 0:03:27 time: 0.0729 data: 0.0011 max mem: 33369 +Test: [ 300/2573] eta: 0:03:06 time: 0.0746 data: 0.0011 max mem: 33369 +Test: [ 400/2573] eta: 0:02:53 time: 0.0749 data: 0.0011 max mem: 33369 +Test: [ 500/2573] eta: 0:02:42 time: 0.0733 data: 0.0011 max mem: 33369 +Test: [ 600/2573] eta: 0:02:33 time: 0.0733 data: 0.0011 max mem: 33369 +Test: [ 700/2573] eta: 0:02:25 time: 0.0734 data: 0.0011 max mem: 33369 +Test: [ 800/2573] eta: 0:02:16 time: 0.0769 data: 0.0011 max mem: 33369 +Test: [ 900/2573] eta: 0:02:08 time: 0.0733 data: 0.0011 max mem: 33369 +Test: [1000/2573] eta: 0:02:00 time: 0.0734 data: 0.0011 max mem: 33369 +Test: [1100/2573] eta: 0:01:52 time: 0.0736 data: 0.0011 max mem: 33369 +Test: [1200/2573] eta: 0:01:44 time: 0.0736 data: 0.0011 max mem: 33369 +Test: [1300/2573] eta: 0:01:36 time: 0.0736 data: 0.0011 max mem: 33369 +Test: [1400/2573] eta: 0:01:28 time: 0.0719 data: 0.0011 max mem: 33369 +Test: [1500/2573] eta: 0:01:21 time: 0.0735 data: 0.0011 max mem: 33369 +Test: [1600/2573] eta: 0:01:13 time: 0.0769 data: 0.0011 max mem: 33369 +Test: [1700/2573] eta: 0:01:05 time: 0.0720 data: 0.0011 max mem: 33369 +Test: [1800/2573] eta: 0:00:58 time: 0.0753 data: 0.0011 max mem: 33369 +Test: [1900/2573] eta: 0:00:50 time: 0.0719 data: 0.0011 max mem: 33369 +Test: [2000/2573] eta: 0:00:42 time: 0.0737 data: 0.0012 max mem: 33369 +Test: [2100/2573] eta: 0:00:35 time: 0.0754 data: 0.0011 max mem: 33369 +Test: [2200/2573] eta: 0:00:27 time: 0.0752 data: 0.0011 max mem: 33369 +Test: [2300/2573] eta: 0:00:20 time: 0.0753 data: 0.0011 max mem: 33369 +Test: [2400/2573] eta: 0:00:12 time: 0.0704 data: 0.0011 max mem: 33369 +Test: [2500/2573] eta: 0:00:05 time: 0.0738 data: 0.0011 max mem: 33369 +Test: Total time: 0:03:12 +Final results: +Mean IoU is 64.38 + + precision@0.5 = 72.41 + precision@0.6 = 67.22 + precision@0.7 = 60.38 + precision@0.8 = 48.71 + precision@0.9 = 24.33 + overall IoU = 61.79 + +Average object IoU 64.38186598652099 +Overall IoU 61.78575134277344 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [27] [ 0/1319] eta: 3:06:01 lr: 1.818202428926248e-05 loss: 0.0276 (0.0276) time: 8.4624 data: 1.6263 max mem: 33369 +Epoch: [27] [ 10/1319] eta: 1:08:43 lr: 1.817248019783995e-05 loss: 0.0361 (0.0398) time: 3.1500 data: 0.1527 max mem: 33369 +Epoch: [27] [ 20/1319] eta: 1:02:53 lr: 1.8162935549439682e-05 loss: 0.0464 (0.0491) time: 2.6273 data: 0.0054 max mem: 33369 +Epoch: [27] [ 30/1319] eta: 1:00:20 lr: 1.8153390343703928e-05 loss: 0.0454 (0.0468) time: 2.6206 data: 0.0059 max mem: 33369 +Epoch: [27] [ 40/1319] eta: 0:58:42 lr: 1.8143844580274487e-05 loss: 0.0404 (0.0462) time: 2.5954 data: 0.0064 max mem: 33369 +Epoch: [27] [ 50/1319] eta: 0:57:45 lr: 1.813429825879272e-05 loss: 0.0407 (0.0444) time: 2.6101 data: 0.0062 max mem: 33369 +Epoch: [27] [ 60/1319] eta: 0:57:01 lr: 1.8124751378899558e-05 loss: 0.0361 (0.0433) time: 2.6429 data: 0.0062 max mem: 33369 +Epoch: [27] [ 70/1319] eta: 0:56:16 lr: 1.811520394023548e-05 loss: 0.0361 (0.0429) time: 2.6338 data: 0.0062 max mem: 33369 +Epoch: [27] [ 80/1319] eta: 0:55:32 lr: 1.8105655942440525e-05 loss: 0.0350 (0.0423) time: 2.6034 data: 0.0061 max mem: 33369 +Epoch: [27] [ 90/1319] eta: 0:54:56 lr: 1.8096107385154294e-05 loss: 0.0350 (0.0419) time: 2.6074 data: 0.0061 max mem: 33369 +Epoch: [27] [ 100/1319] eta: 0:54:29 lr: 1.8086558268015952e-05 loss: 0.0358 (0.0419) time: 2.6510 data: 0.0062 max mem: 33369 +Epoch: [27] [ 110/1319] eta: 0:53:56 lr: 1.807700859066419e-05 loss: 0.0385 (0.0422) time: 2.6521 data: 0.0063 max mem: 33369 +Epoch: [27] [ 120/1319] eta: 0:53:21 lr: 1.8067458352737284e-05 loss: 0.0385 (0.0417) time: 2.6132 data: 0.0063 max mem: 33369 +Epoch: [27] [ 130/1319] eta: 0:52:51 lr: 1.8057907553873043e-05 loss: 0.0389 (0.0415) time: 2.6125 data: 0.0063 max mem: 33369 +Epoch: [27] [ 140/1319] eta: 0:52:21 lr: 1.8048356193708847e-05 loss: 0.0362 (0.0414) time: 2.6299 data: 0.0062 max mem: 33369 +Epoch: [27] [ 150/1319] eta: 0:51:50 lr: 1.803880427188162e-05 loss: 0.0337 (0.0410) time: 2.6187 data: 0.0061 max mem: 33369 +Epoch: [27] [ 160/1319] eta: 0:51:22 lr: 1.802925178802783e-05 loss: 0.0344 (0.0411) time: 2.6264 data: 0.0061 max mem: 33369 +Epoch: [27] [ 170/1319] eta: 0:50:52 lr: 1.8019698741783504e-05 loss: 0.0335 (0.0403) time: 2.6279 data: 0.0061 max mem: 33369 +Epoch: [27] [ 180/1319] eta: 0:50:23 lr: 1.8010145132784217e-05 loss: 0.0340 (0.0408) time: 2.6132 data: 0.0058 max mem: 33369 +Epoch: [27] [ 190/1319] eta: 0:49:55 lr: 1.8000590960665095e-05 loss: 0.0427 (0.0409) time: 2.6215 data: 0.0059 max mem: 33369 +Epoch: [27] [ 200/1319] eta: 0:49:26 lr: 1.7991036225060814e-05 loss: 0.0424 (0.0409) time: 2.6210 data: 0.0061 max mem: 33369 +Epoch: [27] [ 210/1319] eta: 0:49:00 lr: 1.7981480925605583e-05 loss: 0.0408 (0.0411) time: 2.6370 data: 0.0060 max mem: 33369 +Epoch: [27] [ 220/1319] eta: 0:48:32 lr: 1.7971925061933174e-05 loss: 0.0388 (0.0411) time: 2.6399 data: 0.0059 max mem: 33369 +Epoch: [27] [ 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mem: 33369 +Epoch: [27] [ 310/1319] eta: 0:44:22 lr: 1.7885896838454187e-05 loss: 0.0391 (0.0418) time: 2.5955 data: 0.0059 max mem: 33369 +Epoch: [27] [ 320/1319] eta: 0:43:54 lr: 1.787633531236672e-05 loss: 0.0376 (0.0416) time: 2.6030 data: 0.0062 max mem: 33369 +Epoch: [27] [ 330/1319] eta: 0:43:26 lr: 1.786677321800332e-05 loss: 0.0358 (0.0415) time: 2.5912 data: 0.0061 max mem: 33369 +Epoch: [27] [ 340/1319] eta: 0:43:01 lr: 1.7857210554992246e-05 loss: 0.0385 (0.0415) time: 2.6352 data: 0.0058 max mem: 33369 +Epoch: [27] [ 350/1319] eta: 0:42:34 lr: 1.7847647322961293e-05 loss: 0.0375 (0.0414) time: 2.6397 data: 0.0058 max mem: 33369 +Epoch: [27] [ 360/1319] eta: 0:42:07 lr: 1.783808352153779e-05 loss: 0.0361 (0.0413) time: 2.6217 data: 0.0058 max mem: 33369 +Epoch: [27] [ 370/1319] eta: 0:41:40 lr: 1.782851915034859e-05 loss: 0.0412 (0.0413) time: 2.6078 data: 0.0058 max mem: 33369 +Epoch: [27] [ 380/1319] eta: 0:41:12 lr: 1.78189542090201e-05 loss: 0.0376 (0.0413) time: 2.5843 data: 0.0057 max mem: 33369 +Epoch: [27] [ 390/1319] eta: 0:40:45 lr: 1.780938869717823e-05 loss: 0.0368 (0.0413) time: 2.5996 data: 0.0057 max mem: 33369 +Epoch: [27] [ 400/1319] eta: 0:40:19 lr: 1.779982261444845e-05 loss: 0.0368 (0.0412) time: 2.6264 data: 0.0058 max mem: 33369 +Epoch: [27] [ 410/1319] eta: 0:39:52 lr: 1.7790255960455746e-05 loss: 0.0341 (0.0412) time: 2.6277 data: 0.0058 max mem: 33369 +Epoch: [27] [ 420/1319] eta: 0:39:27 lr: 1.7780688734824637e-05 loss: 0.0365 (0.0412) time: 2.6366 data: 0.0059 max mem: 33369 +Epoch: [27] [ 430/1319] eta: 0:39:00 lr: 1.777112093717916e-05 loss: 0.0340 (0.0411) time: 2.6341 data: 0.0060 max mem: 33369 +Epoch: [27] [ 440/1319] eta: 0:38:33 lr: 1.7761552567142895e-05 loss: 0.0340 (0.0410) time: 2.6188 data: 0.0061 max mem: 33369 +Epoch: [27] [ 450/1319] eta: 0:38:06 lr: 1.7751983624338938e-05 loss: 0.0370 (0.0410) time: 2.6047 data: 0.0061 max mem: 33369 +Epoch: [27] [ 460/1319] eta: 0:37:39 lr: 1.7742414108389917e-05 loss: 0.0434 (0.0412) time: 2.5760 data: 0.0058 max mem: 33369 +Epoch: [27] [ 470/1319] eta: 0:37:12 lr: 1.7732844018917994e-05 loss: 0.0428 (0.0413) time: 2.5780 data: 0.0058 max mem: 33369 +Epoch: [27] [ 480/1319] eta: 0:36:45 lr: 1.7723273355544827e-05 loss: 0.0400 (0.0413) time: 2.5946 data: 0.0059 max mem: 33369 +Epoch: [27] [ 490/1319] eta: 0:36:19 lr: 1.771370211789162e-05 loss: 0.0351 (0.0413) time: 2.6253 data: 0.0058 max mem: 33369 +Epoch: [27] [ 500/1319] eta: 0:35:52 lr: 1.7704130305579097e-05 loss: 0.0398 (0.0413) time: 2.6268 data: 0.0059 max mem: 33369 +Epoch: [27] [ 510/1319] eta: 0:35:26 lr: 1.76945579182275e-05 loss: 0.0432 (0.0414) time: 2.6263 data: 0.0059 max mem: 33369 +Epoch: [27] [ 520/1319] eta: 0:35:00 lr: 1.7684984955456597e-05 loss: 0.0353 (0.0412) time: 2.6285 data: 0.0056 max mem: 33369 +Epoch: [27] [ 530/1319] eta: 0:34:33 lr: 1.767541141688566e-05 loss: 0.0328 (0.0412) time: 2.6131 data: 0.0057 max mem: 33369 +Epoch: [27] [ 540/1319] eta: 0:34:07 lr: 1.76658373021335e-05 loss: 0.0381 (0.0411) time: 2.6096 data: 0.0058 max mem: 33369 +Epoch: [27] [ 550/1319] eta: 0:33:40 lr: 1.7656262610818425e-05 loss: 0.0339 (0.0410) time: 2.6123 data: 0.0057 max mem: 33369 +Epoch: [27] [ 560/1319] eta: 0:33:13 lr: 1.7646687342558284e-05 loss: 0.0346 (0.0413) time: 2.6012 data: 0.0058 max mem: 33369 +Epoch: [27] [ 570/1319] eta: 0:32:47 lr: 1.7637111496970423e-05 loss: 0.0411 (0.0413) time: 2.5908 data: 0.0059 max mem: 33369 +Epoch: [27] [ 580/1319] eta: 0:32:20 lr: 1.762753507367172e-05 loss: 0.0374 (0.0413) time: 2.6076 data: 0.0058 max mem: 33369 +Epoch: [27] [ 590/1319] eta: 0:31:53 lr: 1.7617958072278543e-05 loss: 0.0361 (0.0412) time: 2.5993 data: 0.0057 max mem: 33369 +Epoch: [27] [ 600/1319] eta: 0:31:28 lr: 1.7608380492406792e-05 loss: 0.0346 (0.0412) time: 2.6187 data: 0.0058 max mem: 33369 +Epoch: [27] [ 610/1319] eta: 0:31:01 lr: 1.759880233367188e-05 loss: 0.0333 (0.0412) time: 2.6476 data: 0.0059 max mem: 33369 +Epoch: [27] [ 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data: 0.0063 max mem: 33369 +Epoch: [27] [ 780/1319] eta: 0:23:45 lr: 1.7435884694063984e-05 loss: 0.0394 (0.0418) time: 2.7562 data: 0.0065 max mem: 33369 +Epoch: [27] [ 790/1319] eta: 0:23:19 lr: 1.7426296049465625e-05 loss: 0.0394 (0.0418) time: 2.7514 data: 0.0064 max mem: 33369 +Epoch: [27] [ 800/1319] eta: 0:22:53 lr: 1.7416706818602993e-05 loss: 0.0371 (0.0418) time: 2.7495 data: 0.0062 max mem: 33369 +Epoch: [27] [ 810/1319] eta: 0:22:27 lr: 1.7407117001081557e-05 loss: 0.0340 (0.0418) time: 2.7369 data: 0.0062 max mem: 33369 +Epoch: [27] [ 820/1319] eta: 0:22:02 lr: 1.7397526596506272e-05 loss: 0.0391 (0.0418) time: 2.7425 data: 0.0064 max mem: 33369 +Epoch: [27] [ 830/1319] eta: 0:21:36 lr: 1.7387935604481586e-05 loss: 0.0391 (0.0419) time: 2.7574 data: 0.0066 max mem: 33369 +Epoch: [27] [ 840/1319] eta: 0:21:09 lr: 1.7378344024611436e-05 loss: 0.0486 (0.0421) time: 2.7177 data: 0.0063 max mem: 33369 +Epoch: [27] [ 850/1319] eta: 0:20:43 lr: 1.7368751856499257e-05 loss: 0.0417 (0.0420) time: 2.6530 data: 0.0061 max mem: 33369 +Epoch: [27] [ 860/1319] eta: 0:20:16 lr: 1.7359159099747958e-05 loss: 0.0350 (0.0420) time: 2.6415 data: 0.0062 max mem: 33369 +Epoch: [27] [ 870/1319] eta: 0:19:50 lr: 1.7349565753959942e-05 loss: 0.0373 (0.0420) time: 2.6991 data: 0.0064 max mem: 33369 +Epoch: [27] [ 880/1319] eta: 0:19:24 lr: 1.7339971818737108e-05 loss: 0.0403 (0.0420) time: 2.7548 data: 0.0064 max mem: 33369 +Epoch: [27] [ 890/1319] eta: 0:18:58 lr: 1.733037729368083e-05 loss: 0.0412 (0.0420) time: 2.7623 data: 0.0065 max mem: 33369 +Epoch: [27] [ 900/1319] eta: 0:18:32 lr: 1.7320782178391982e-05 loss: 0.0408 (0.0420) time: 2.7635 data: 0.0063 max mem: 33369 +Epoch: [27] [ 910/1319] eta: 0:18:06 lr: 1.7311186472470895e-05 loss: 0.0325 (0.0419) time: 2.7650 data: 0.0064 max mem: 33369 +Epoch: [27] [ 920/1319] eta: 0:17:40 lr: 1.7301590175517403e-05 loss: 0.0302 (0.0418) time: 2.7545 data: 0.0065 max mem: 33369 +Epoch: [27] [ 930/1319] eta: 0:17:14 lr: 1.7291993287130824e-05 loss: 0.0347 (0.0418) time: 2.7613 data: 0.0065 max mem: 33369 +Epoch: [27] [ 940/1319] eta: 0:16:48 lr: 1.728239580690995e-05 loss: 0.0358 (0.0418) time: 2.7821 data: 0.0065 max mem: 33369 +Epoch: [27] [ 950/1319] eta: 0:16:22 lr: 1.727279773445306e-05 loss: 0.0358 (0.0418) time: 2.7804 data: 0.0064 max mem: 33369 +Epoch: [27] [ 960/1319] eta: 0:15:55 lr: 1.7263199069357895e-05 loss: 0.0342 (0.0417) time: 2.7470 data: 0.0064 max mem: 33369 +Epoch: [27] [ 970/1319] eta: 0:15:29 lr: 1.725359981122169e-05 loss: 0.0311 (0.0417) time: 2.7492 data: 0.0065 max mem: 33369 +Epoch: [27] [ 980/1319] eta: 0:15:03 lr: 1.7243999959641156e-05 loss: 0.0359 (0.0417) time: 2.7721 data: 0.0066 max mem: 33369 +Epoch: [27] [ 990/1319] eta: 0:14:37 lr: 1.7234399514212475e-05 loss: 0.0359 (0.0416) time: 2.7759 data: 0.0066 max mem: 33369 +Epoch: [27] [1000/1319] eta: 0:14:10 lr: 1.7224798474531302e-05 loss: 0.0371 (0.0417) time: 2.7866 data: 0.0066 max mem: 33369 +Epoch: [27] [1010/1319] eta: 0:13:44 lr: 1.7215196840192783e-05 loss: 0.0405 (0.0417) time: 2.7462 data: 0.0066 max mem: 33369 +Epoch: [27] [1020/1319] eta: 0:13:17 lr: 1.7205594610791508e-05 loss: 0.0395 (0.0417) time: 2.6773 data: 0.0063 max mem: 33369 +Epoch: [27] [1030/1319] eta: 0:12:50 lr: 1.7195991785921565e-05 loss: 0.0395 (0.0417) time: 2.6448 data: 0.0063 max mem: 33369 +Epoch: [27] [1040/1319] eta: 0:12:24 lr: 1.71863883651765e-05 loss: 0.0373 (0.0417) time: 2.6925 data: 0.0066 max mem: 33369 +Epoch: [27] [1050/1319] eta: 0:11:57 lr: 1.7176784348149333e-05 loss: 0.0382 (0.0417) time: 2.7678 data: 0.0066 max mem: 33369 +Epoch: [27] [1060/1319] eta: 0:11:31 lr: 1.7167179734432558e-05 loss: 0.0396 (0.0417) time: 2.7834 data: 0.0063 max mem: 33369 +Epoch: [27] [1070/1319] eta: 0:11:05 lr: 1.7157574523618118e-05 loss: 0.0377 (0.0417) time: 2.7884 data: 0.0063 max mem: 33369 +Epoch: [27] [1080/1319] eta: 0:10:38 lr: 1.7147968715297445e-05 loss: 0.0370 (0.0417) time: 2.7760 data: 0.0063 max mem: 33369 +Epoch: [27] [1090/1319] eta: 0:10:12 lr: 1.7138362309061432e-05 loss: 0.0362 (0.0417) time: 2.7524 data: 0.0064 max mem: 33369 +Epoch: [27] [1100/1319] eta: 0:09:45 lr: 1.7128755304500424e-05 loss: 0.0428 (0.0417) time: 2.7754 data: 0.0064 max mem: 33369 +Epoch: [27] [1110/1319] eta: 0:09:19 lr: 1.7119147701204254e-05 loss: 0.0428 (0.0417) time: 2.7967 data: 0.0063 max mem: 33369 +Epoch: [27] [1120/1319] eta: 0:08:52 lr: 1.710953949876218e-05 loss: 0.0379 (0.0418) time: 2.8134 data: 0.0064 max mem: 33369 +Epoch: [27] [1130/1319] eta: 0:08:25 lr: 1.709993069676296e-05 loss: 0.0315 (0.0417) time: 2.8049 data: 0.0064 max mem: 33369 +Epoch: [27] [1140/1319] eta: 0:07:59 lr: 1.7090321294794796e-05 loss: 0.0366 (0.0417) time: 2.7758 data: 0.0063 max mem: 33369 +Epoch: [27] [1150/1319] eta: 0:07:32 lr: 1.7080711292445346e-05 loss: 0.0388 (0.0417) time: 2.7625 data: 0.0065 max mem: 33369 +Epoch: [27] [1160/1319] eta: 0:07:06 lr: 1.7071100689301735e-05 loss: 0.0349 (0.0417) time: 2.7557 data: 0.0065 max mem: 33369 +Epoch: [27] [1170/1319] eta: 0:06:39 lr: 1.706148948495055e-05 loss: 0.0414 (0.0418) time: 2.7478 data: 0.0064 max mem: 33369 +Epoch: [27] [1180/1319] eta: 0:06:12 lr: 1.705187767897781e-05 loss: 0.0405 (0.0417) time: 2.7131 data: 0.0064 max mem: 33369 +Epoch: [27] [1190/1319] eta: 0:05:45 lr: 1.704226527096902e-05 loss: 0.0366 (0.0417) time: 2.6935 data: 0.0063 max mem: 33369 +Epoch: [27] [1200/1319] eta: 0:05:18 lr: 1.703265226050912e-05 loss: 0.0345 (0.0417) time: 2.6798 data: 0.0063 max mem: 33369 +Epoch: [27] [1210/1319] eta: 0:04:52 lr: 1.702303864718251e-05 loss: 0.0443 (0.0417) time: 2.6921 data: 0.0063 max mem: 33369 +Epoch: [27] [1220/1319] eta: 0:04:25 lr: 1.7013424430573045e-05 loss: 0.0415 (0.0417) time: 2.7467 data: 0.0065 max mem: 33369 +Epoch: [27] [1230/1319] eta: 0:03:58 lr: 1.7003809610264022e-05 loss: 0.0395 (0.0417) time: 2.7777 data: 0.0065 max mem: 33369 +Epoch: [27] [1240/1319] eta: 0:03:31 lr: 1.6994194185838196e-05 loss: 0.0368 (0.0417) time: 2.7841 data: 0.0065 max mem: 33369 +Epoch: [27] [1250/1319] eta: 0:03:05 lr: 1.698457815687777e-05 loss: 0.0337 (0.0416) time: 2.7897 data: 0.0065 max mem: 33369 +Epoch: [27] [1260/1319] eta: 0:02:38 lr: 1.6974961522964392e-05 loss: 0.0371 (0.0416) time: 2.7540 data: 0.0065 max mem: 33369 +Epoch: [27] [1270/1319] eta: 0:02:11 lr: 1.6965344283679166e-05 loss: 0.0372 (0.0416) time: 2.7438 data: 0.0066 max mem: 33369 +Epoch: [27] [1280/1319] eta: 0:01:44 lr: 1.6955726438602627e-05 loss: 0.0370 (0.0418) time: 2.7719 data: 0.0067 max mem: 33369 +Epoch: [27] [1290/1319] eta: 0:01:17 lr: 1.694610798731476e-05 loss: 0.0404 (0.0417) time: 2.7593 data: 0.0068 max mem: 33369 +Epoch: [27] [1300/1319] eta: 0:00:51 lr: 1.6936488929395006e-05 loss: 0.0338 (0.0417) time: 2.7595 data: 0.0067 max mem: 33369 +Epoch: [27] [1310/1319] eta: 0:00:24 lr: 1.6926869264422233e-05 loss: 0.0354 (0.0417) time: 2.7451 data: 0.0066 max mem: 33369 +Epoch: [27] Total time: 0:59:04 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 3:13:06 time: 4.5031 data: 4.4229 max mem: 33369 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 100/2573] eta: 0:04:48 time: 0.0723 data: 0.0012 max mem: 33369 +Test: [ 200/2573] eta: 0:03:47 time: 0.0737 data: 0.0012 max mem: 33369 +Test: [ 300/2573] eta: 0:03:19 time: 0.0755 data: 0.0012 max mem: 33369 +Test: [ 400/2573] eta: 0:03:03 time: 0.0757 data: 0.0012 max mem: 33369 +Test: [ 500/2573] eta: 0:02:50 time: 0.0740 data: 0.0013 max mem: 33369 +Test: [ 600/2573] eta: 0:02:39 time: 0.0741 data: 0.0013 max mem: 33369 +Test: [ 700/2573] eta: 0:02:30 time: 0.0743 data: 0.0012 max mem: 33369 +Test: [ 800/2573] eta: 0:02:21 time: 0.0779 data: 0.0012 max mem: 33369 +Test: [ 900/2573] eta: 0:02:12 time: 0.0742 data: 0.0012 max mem: 33369 +Test: [1000/2573] eta: 0:02:03 time: 0.0744 data: 0.0012 max mem: 33369 +Test: [1100/2573] eta: 0:01:55 time: 0.0738 data: 0.0012 max mem: 33369 +Test: [1200/2573] eta: 0:01:47 time: 0.0736 data: 0.0011 max mem: 33369 +Test: [1300/2573] eta: 0:01:38 time: 0.0737 data: 0.0011 max mem: 33369 +Test: [1400/2573] eta: 0:01:30 time: 0.0722 data: 0.0011 max mem: 33369 +Test: [1500/2573] eta: 0:01:22 time: 0.0737 data: 0.0011 max mem: 33369 +Test: [1600/2573] eta: 0:01:14 time: 0.0772 data: 0.0011 max mem: 33369 +Test: [1700/2573] eta: 0:01:07 time: 0.0724 data: 0.0011 max mem: 33369 +Test: [1800/2573] eta: 0:00:59 time: 0.0758 data: 0.0012 max mem: 33369 +Test: [1900/2573] eta: 0:00:51 time: 0.0727 data: 0.0012 max mem: 33369 +Test: [2000/2573] eta: 0:00:43 time: 0.0741 data: 0.0012 max mem: 33369 +Test: [2100/2573] eta: 0:00:36 time: 0.0760 data: 0.0012 max mem: 33369 +Test: [2200/2573] eta: 0:00:28 time: 0.0761 data: 0.0012 max mem: 33369 +Test: [2300/2573] eta: 0:00:20 time: 0.0759 data: 0.0012 max mem: 33369 +Test: [2400/2573] eta: 0:00:13 time: 0.0711 data: 0.0012 max mem: 33369 +Test: [2500/2573] eta: 0:00:05 time: 0.0744 data: 0.0012 max mem: 33369 +Test: Total time: 0:03:15 +Final results: +Mean IoU is 64.60 + + precision@0.5 = 72.73 + precision@0.6 = 67.26 + precision@0.7 = 60.93 + precision@0.8 = 49.78 + precision@0.9 = 24.90 + overall IoU = 61.89 + +Average object IoU 64.60293059774857 +Overall IoU 61.89323043823242 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [28] [ 0/1319] eta: 3:51:01 lr: 1.69182110465679e-05 loss: 0.0311 (0.0311) time: 10.5088 data: 3.8723 max mem: 33369 +Epoch: [28] [ 10/1319] eta: 1:16:40 lr: 1.690859022703219e-05 loss: 0.0341 (0.0360) time: 3.5147 data: 0.3580 max mem: 33369 +Epoch: [28] [ 20/1319] eta: 1:08:20 lr: 1.6898968799219036e-05 loss: 0.0342 (0.0375) time: 2.7893 data: 0.0061 max mem: 33369 +Epoch: [28] [ 30/1319] eta: 1:05:03 lr: 1.6889346762705132e-05 loss: 0.0384 (0.0409) time: 2.7604 data: 0.0062 max mem: 33369 +Epoch: [28] [ 40/1319] eta: 1:03:16 lr: 1.6879724117066593e-05 loss: 0.0351 (0.0394) time: 2.7697 data: 0.0065 max mem: 33369 +Epoch: [28] [ 50/1319] eta: 1:02:02 lr: 1.6870100861878995e-05 loss: 0.0372 (0.0402) time: 2.7862 data: 0.0064 max mem: 33369 +Epoch: [28] [ 60/1319] eta: 1:01:05 lr: 1.6860476996717327e-05 loss: 0.0418 (0.0401) time: 2.7965 data: 0.0065 max mem: 33369 +Epoch: [28] [ 70/1319] eta: 1:00:10 lr: 1.6850852521156025e-05 loss: 0.0382 (0.0408) time: 2.7834 data: 0.0067 max mem: 33369 +Epoch: [28] [ 80/1319] eta: 0:59:26 lr: 1.684122743476896e-05 loss: 0.0382 (0.0404) time: 2.7762 data: 0.0067 max mem: 33369 +Epoch: [28] [ 90/1319] eta: 0:58:44 lr: 1.6831601737129412e-05 loss: 0.0358 (0.0399) time: 2.7843 data: 0.0065 max mem: 33369 +Epoch: [28] [ 100/1319] eta: 0:58:04 lr: 1.6821975427810122e-05 loss: 0.0374 (0.0399) time: 2.7765 data: 0.0066 max mem: 33369 +Epoch: [28] [ 110/1319] eta: 0:57:21 lr: 1.6812348506383245e-05 loss: 0.0387 (0.0403) time: 2.7513 data: 0.0065 max mem: 33369 +Epoch: [28] [ 120/1319] eta: 0:56:43 lr: 1.680272097242036e-05 loss: 0.0360 (0.0399) time: 2.7421 data: 0.0063 max mem: 33369 +Epoch: [28] [ 130/1319] eta: 0:56:10 lr: 1.6793092825492484e-05 loss: 0.0323 (0.0399) time: 2.7660 data: 0.0064 max mem: 33369 +Epoch: [28] [ 140/1319] eta: 0:55:22 lr: 1.6783464065170062e-05 loss: 0.0330 (0.0396) time: 2.6936 data: 0.0065 max mem: 33369 +Epoch: [28] [ 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mem: 33369 +Epoch: [28] [ 230/1319] eta: 0:50:36 lr: 1.6696777548350058e-05 loss: 0.0402 (0.0402) time: 2.7860 data: 0.0065 max mem: 33369 +Epoch: [28] [ 240/1319] eta: 0:50:09 lr: 1.668714263032912e-05 loss: 0.0346 (0.0400) time: 2.7817 data: 0.0065 max mem: 33369 +Epoch: [28] [ 250/1319] eta: 0:49:39 lr: 1.6677507094150246e-05 loss: 0.0384 (0.0404) time: 2.7754 data: 0.0065 max mem: 33369 +Epoch: [28] [ 260/1319] eta: 0:49:11 lr: 1.6667870939376894e-05 loss: 0.0379 (0.0407) time: 2.7699 data: 0.0065 max mem: 33369 +Epoch: [28] [ 270/1319] eta: 0:48:42 lr: 1.6658234165571935e-05 loss: 0.0399 (0.0407) time: 2.7686 data: 0.0067 max mem: 33369 +Epoch: [28] [ 280/1319] eta: 0:48:12 lr: 1.6648596772297652e-05 loss: 0.0388 (0.0407) time: 2.7438 data: 0.0067 max mem: 33369 +Epoch: [28] [ 290/1319] eta: 0:47:45 lr: 1.6638958759115745e-05 loss: 0.0388 (0.0406) time: 2.7698 data: 0.0066 max mem: 33369 +Epoch: [28] [ 300/1319] eta: 0:47:16 lr: 1.6629320125587307e-05 loss: 0.0407 (0.0407) time: 2.7704 data: 0.0065 max mem: 33369 +Epoch: [28] [ 310/1319] eta: 0:46:48 lr: 1.6619680871272843e-05 loss: 0.0368 (0.0406) time: 2.7675 data: 0.0065 max mem: 33369 +Epoch: [28] [ 320/1319] eta: 0:46:17 lr: 1.6610040995732262e-05 loss: 0.0373 (0.0407) time: 2.7293 data: 0.0065 max mem: 33369 +Epoch: [28] [ 330/1319] eta: 0:45:45 lr: 1.6600400498524878e-05 loss: 0.0376 (0.0406) time: 2.6474 data: 0.0065 max mem: 33369 +Epoch: [28] [ 340/1319] eta: 0:45:14 lr: 1.659075937920942e-05 loss: 0.0351 (0.0407) time: 2.6506 data: 0.0064 max mem: 33369 +Epoch: [28] [ 350/1319] eta: 0:44:43 lr: 1.6581117637343994e-05 loss: 0.0362 (0.0405) time: 2.6719 data: 0.0063 max mem: 33369 +Epoch: [28] [ 360/1319] eta: 0:44:16 lr: 1.657147527248612e-05 loss: 0.0347 (0.0404) time: 2.7342 data: 0.0066 max mem: 33369 +Epoch: [28] [ 370/1319] eta: 0:43:49 lr: 1.6561832284192722e-05 loss: 0.0380 (0.0405) time: 2.7942 data: 0.0066 max mem: 33369 +Epoch: [28] [ 380/1319] eta: 0:43:21 lr: 1.6552188672020112e-05 loss: 0.0389 (0.0406) time: 2.7748 data: 0.0065 max mem: 33369 +Epoch: [28] [ 390/1319] eta: 0:42:49 lr: 1.654254443552401e-05 loss: 0.0348 (0.0404) time: 2.6788 data: 0.0064 max mem: 33369 +Epoch: [28] [ 400/1319] eta: 0:42:19 lr: 1.6532899574259518e-05 loss: 0.0366 (0.0405) time: 2.6174 data: 0.0064 max mem: 33369 +Epoch: [28] [ 410/1319] eta: 0:41:47 lr: 1.6523254087781154e-05 loss: 0.0379 (0.0405) time: 2.6166 data: 0.0063 max mem: 33369 +Epoch: [28] [ 420/1319] eta: 0:41:17 lr: 1.651360797564279e-05 loss: 0.0391 (0.0406) time: 2.6106 data: 0.0063 max mem: 33369 +Epoch: [28] [ 430/1319] eta: 0:40:47 lr: 1.6503961237397734e-05 loss: 0.0353 (0.0405) time: 2.6301 data: 0.0063 max mem: 33369 +Epoch: [28] [ 440/1319] eta: 0:40:17 lr: 1.6494313872598656e-05 loss: 0.0339 (0.0405) time: 2.6368 data: 0.0062 max mem: 33369 +Epoch: [28] [ 450/1319] eta: 0:39:47 lr: 1.6484665880797628e-05 loss: 0.0388 (0.0406) time: 2.6284 data: 0.0063 max mem: 33369 +Epoch: [28] [ 460/1319] eta: 0:39:17 lr: 1.6475017261546112e-05 loss: 0.0388 (0.0408) time: 2.6110 data: 0.0064 max mem: 33369 +Epoch: [28] [ 470/1319] eta: 0:38:48 lr: 1.6465368014394945e-05 loss: 0.0355 (0.0409) time: 2.6228 data: 0.0065 max mem: 33369 +Epoch: [28] [ 480/1319] eta: 0:38:18 lr: 1.6455718138894353e-05 loss: 0.0348 (0.0408) time: 2.6344 data: 0.0063 max mem: 33369 +Epoch: [28] [ 490/1319] eta: 0:37:48 lr: 1.6446067634593955e-05 loss: 0.0355 (0.0410) time: 2.6138 data: 0.0064 max mem: 33369 +Epoch: [28] [ 500/1319] eta: 0:37:19 lr: 1.6436416501042754e-05 loss: 0.0372 (0.0409) time: 2.6118 data: 0.0065 max mem: 33369 +Epoch: [28] [ 510/1319] eta: 0:36:50 lr: 1.6426764737789128e-05 loss: 0.0346 (0.0408) time: 2.6233 data: 0.0064 max mem: 33369 +Epoch: [28] [ 520/1319] eta: 0:36:22 lr: 1.6417112344380827e-05 loss: 0.0361 (0.0410) time: 2.6498 data: 0.0063 max mem: 33369 +Epoch: [28] [ 530/1319] eta: 0:35:53 lr: 1.6407459320365e-05 loss: 0.0451 (0.0411) time: 2.6584 data: 0.0063 max mem: 33369 +Epoch: [28] [ 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33369 +Epoch: [28] [ 620/1319] eta: 0:31:37 lr: 1.632055365185315e-05 loss: 0.0391 (0.0407) time: 2.6018 data: 0.0063 max mem: 33369 +Epoch: [28] [ 630/1319] eta: 0:31:09 lr: 1.6310894296717336e-05 loss: 0.0391 (0.0409) time: 2.6290 data: 0.0062 max mem: 33369 +Epoch: [28] [ 640/1319] eta: 0:30:41 lr: 1.630123430595122e-05 loss: 0.0374 (0.0409) time: 2.6407 data: 0.0063 max mem: 33369 +Epoch: [28] [ 650/1319] eta: 0:30:13 lr: 1.6291573679094406e-05 loss: 0.0357 (0.0410) time: 2.6213 data: 0.0063 max mem: 33369 +Epoch: [28] [ 660/1319] eta: 0:29:45 lr: 1.6281912415685837e-05 loss: 0.0390 (0.0411) time: 2.6141 data: 0.0064 max mem: 33369 +Epoch: [28] [ 670/1319] eta: 0:29:17 lr: 1.6272250515263847e-05 loss: 0.0416 (0.0411) time: 2.6323 data: 0.0064 max mem: 33369 +Epoch: [28] [ 680/1319] eta: 0:28:50 lr: 1.626258797736611e-05 loss: 0.0402 (0.0411) time: 2.6585 data: 0.0062 max mem: 33369 +Epoch: [28] [ 690/1319] eta: 0:28:22 lr: 1.6252924801529664e-05 loss: 0.0330 (0.0410) time: 2.6470 data: 0.0062 max mem: 33369 +Epoch: [28] [ 700/1319] eta: 0:27:54 lr: 1.6243260987290905e-05 loss: 0.0348 (0.0410) time: 2.6204 data: 0.0062 max mem: 33369 +Epoch: [28] [ 710/1319] eta: 0:27:26 lr: 1.6233596534185593e-05 loss: 0.0375 (0.0410) time: 2.5976 data: 0.0063 max mem: 33369 +Epoch: [28] [ 720/1319] eta: 0:26:58 lr: 1.6223931441748828e-05 loss: 0.0387 (0.0411) time: 2.5811 data: 0.0064 max mem: 33369 +Epoch: [28] [ 730/1319] eta: 0:26:30 lr: 1.6214265709515084e-05 loss: 0.0407 (0.0411) time: 2.5998 data: 0.0063 max mem: 33369 +Epoch: [28] [ 740/1319] eta: 0:26:03 lr: 1.620459933701816e-05 loss: 0.0407 (0.0411) time: 2.6325 data: 0.0063 max mem: 33369 +Epoch: [28] [ 750/1319] eta: 0:25:35 lr: 1.6194932323791233e-05 loss: 0.0408 (0.0412) time: 2.6609 data: 0.0061 max mem: 33369 +Epoch: [28] [ 760/1319] eta: 0:25:08 lr: 1.6185264669366818e-05 loss: 0.0411 (0.0412) time: 2.6540 data: 0.0061 max mem: 33369 +Epoch: [28] [ 770/1319] eta: 0:24:40 lr: 1.617559637327677e-05 loss: 0.0382 (0.0412) time: 2.6175 data: 0.0063 max mem: 33369 +Epoch: [28] [ 780/1319] eta: 0:24:13 lr: 1.6165927435052318e-05 loss: 0.0381 (0.0411) time: 2.6377 data: 0.0064 max mem: 33369 +Epoch: [28] [ 790/1319] eta: 0:23:46 lr: 1.6156257854223998e-05 loss: 0.0370 (0.0411) time: 2.6387 data: 0.0063 max mem: 33369 +Epoch: [28] [ 800/1319] eta: 0:23:18 lr: 1.614658763032172e-05 loss: 0.0372 (0.0412) time: 2.6089 data: 0.0064 max mem: 33369 +Epoch: [28] [ 810/1319] eta: 0:22:51 lr: 1.6136916762874727e-05 loss: 0.0421 (0.0413) time: 2.6047 data: 0.0064 max mem: 33369 +Epoch: [28] [ 820/1319] eta: 0:22:23 lr: 1.6127245251411607e-05 loss: 0.0421 (0.0412) time: 2.6110 data: 0.0063 max mem: 33369 +Epoch: [28] [ 830/1319] eta: 0:21:56 lr: 1.6117573095460284e-05 loss: 0.0380 (0.0413) time: 2.6299 data: 0.0063 max mem: 33369 +Epoch: [28] [ 840/1319] eta: 0:21:28 lr: 1.610790029454803e-05 loss: 0.0426 (0.0414) time: 2.6017 data: 0.0063 max mem: 33369 +Epoch: [28] [ 850/1319] eta: 0:21:01 lr: 1.609822684820143e-05 loss: 0.0431 (0.0414) time: 2.5841 data: 0.0063 max mem: 33369 +Epoch: [28] [ 860/1319] eta: 0:20:33 lr: 1.608855275594644e-05 loss: 0.0365 (0.0414) time: 2.5982 data: 0.0064 max mem: 33369 +Epoch: [28] [ 870/1319] eta: 0:20:06 lr: 1.6078878017308325e-05 loss: 0.0383 (0.0414) time: 2.6029 data: 0.0063 max mem: 33369 +Epoch: [28] [ 880/1319] eta: 0:19:39 lr: 1.6069202631811695e-05 loss: 0.0347 (0.0414) time: 2.6202 data: 0.0065 max mem: 33369 +Epoch: [28] [ 890/1319] eta: 0:19:12 lr: 1.6059526598980493e-05 loss: 0.0330 (0.0415) time: 2.6165 data: 0.0066 max mem: 33369 +Epoch: [28] [ 900/1319] eta: 0:18:44 lr: 1.6049849918337977e-05 loss: 0.0406 (0.0416) time: 2.6007 data: 0.0063 max mem: 33369 +Epoch: [28] [ 910/1319] eta: 0:18:17 lr: 1.6040172589406754e-05 loss: 0.0376 (0.0415) time: 2.5885 data: 0.0064 max mem: 33369 +Epoch: [28] [ 920/1319] eta: 0:17:50 lr: 1.603049461170875e-05 loss: 0.0376 (0.0416) time: 2.5971 data: 0.0063 max mem: 33369 +Epoch: [28] [ 930/1319] eta: 0:17:23 lr: 1.602081598476522e-05 loss: 0.0363 (0.0415) time: 2.6089 data: 0.0062 max mem: 33369 +Epoch: [28] [ 940/1319] eta: 0:16:56 lr: 1.6011136708096744e-05 loss: 0.0405 (0.0416) time: 2.5801 data: 0.0064 max mem: 33369 +Epoch: [28] [ 950/1319] eta: 0:16:29 lr: 1.6001456781223216e-05 loss: 0.0499 (0.0417) time: 2.5936 data: 0.0063 max mem: 33369 +Epoch: [28] [ 960/1319] eta: 0:16:01 lr: 1.599177620366387e-05 loss: 0.0398 (0.0416) time: 2.6124 data: 0.0061 max mem: 33369 +Epoch: [28] [ 970/1319] eta: 0:15:34 lr: 1.598209497493724e-05 loss: 0.0343 (0.0416) time: 2.5971 data: 0.0063 max mem: 33369 +Epoch: [28] [ 980/1319] eta: 0:15:07 lr: 1.5972413094561205e-05 loss: 0.0375 (0.0416) time: 2.6119 data: 0.0065 max mem: 33369 +Epoch: [28] [ 990/1319] eta: 0:14:41 lr: 1.5962730562052938e-05 loss: 0.0350 (0.0416) time: 2.6458 data: 0.0065 max mem: 33369 +Epoch: [28] [1000/1319] eta: 0:14:14 lr: 1.5953047376928946e-05 loss: 0.0373 (0.0416) time: 2.6431 data: 0.0064 max mem: 33369 +Epoch: [28] [1010/1319] eta: 0:13:47 lr: 1.5943363538705032e-05 loss: 0.0433 (0.0417) time: 2.6150 data: 0.0062 max mem: 33369 +Epoch: [28] [1020/1319] eta: 0:13:20 lr: 1.5933679046896337e-05 loss: 0.0389 (0.0416) time: 2.6206 data: 0.0062 max mem: 33369 +Epoch: [28] [1030/1319] eta: 0:12:53 lr: 1.592399390101729e-05 loss: 0.0389 (0.0416) time: 2.6283 data: 0.0065 max mem: 33369 +Epoch: [28] [1040/1319] eta: 0:12:26 lr: 1.5914308100581652e-05 loss: 0.0350 (0.0416) time: 2.6222 data: 0.0063 max mem: 33369 +Epoch: [28] [1050/1319] eta: 0:11:59 lr: 1.5904621645102482e-05 loss: 0.0350 (0.0415) time: 2.6197 data: 0.0061 max mem: 33369 +Epoch: [28] [1060/1319] eta: 0:11:32 lr: 1.5894934534092145e-05 loss: 0.0350 (0.0415) time: 2.6022 data: 0.0061 max mem: 33369 +Epoch: [28] [1070/1319] eta: 0:11:05 lr: 1.588524676706232e-05 loss: 0.0350 (0.0414) time: 2.5872 data: 0.0062 max mem: 33369 +Epoch: [28] [1080/1319] eta: 0:10:38 lr: 1.5875558343523986e-05 loss: 0.0413 (0.0414) time: 2.6013 data: 0.0063 max mem: 33369 +Epoch: [28] [1090/1319] eta: 0:10:11 lr: 1.5865869262987425e-05 loss: 0.0437 (0.0415) time: 2.5814 data: 0.0063 max mem: 33369 +Epoch: [28] [1100/1319] eta: 0:09:44 lr: 1.5856179524962237e-05 loss: 0.0391 (0.0415) time: 2.6045 data: 0.0062 max mem: 33369 +Epoch: [28] [1110/1319] eta: 0:09:18 lr: 1.5846489128957288e-05 loss: 0.0389 (0.0416) time: 2.6203 data: 0.0063 max mem: 33369 +Epoch: [28] [1120/1319] eta: 0:08:51 lr: 1.5836798074480774e-05 loss: 0.0379 (0.0416) time: 2.6237 data: 0.0063 max mem: 33369 +Epoch: [28] [1130/1319] eta: 0:08:24 lr: 1.582710636104018e-05 loss: 0.0358 (0.0417) time: 2.6498 data: 0.0062 max mem: 33369 +Epoch: [28] [1140/1319] eta: 0:07:57 lr: 1.5817413988142284e-05 loss: 0.0365 (0.0417) time: 2.6059 data: 0.0063 max mem: 33369 +Epoch: [28] [1150/1319] eta: 0:07:31 lr: 1.5807720955293166e-05 loss: 0.0382 (0.0417) time: 2.5909 data: 0.0064 max mem: 33369 +Epoch: [28] [1160/1319] eta: 0:07:04 lr: 1.579802726199819e-05 loss: 0.0335 (0.0417) time: 2.6122 data: 0.0063 max mem: 33369 +Epoch: [28] [1170/1319] eta: 0:06:37 lr: 1.5788332907762015e-05 loss: 0.0326 (0.0417) time: 2.6182 data: 0.0063 max mem: 33369 +Epoch: [28] [1180/1319] eta: 0:06:10 lr: 1.577863789208859e-05 loss: 0.0366 (0.0417) time: 2.5993 data: 0.0063 max mem: 33369 +Epoch: [28] [1190/1319] eta: 0:05:43 lr: 1.576894221448116e-05 loss: 0.0373 (0.0416) time: 2.5910 data: 0.0063 max mem: 33369 +Epoch: [28] [1200/1319] eta: 0:05:17 lr: 1.5759245874442245e-05 loss: 0.0327 (0.0416) time: 2.6034 data: 0.0066 max mem: 33369 +Epoch: [28] [1210/1319] eta: 0:04:50 lr: 1.5749548871473663e-05 loss: 0.0383 (0.0417) time: 2.6034 data: 0.0065 max mem: 33369 +Epoch: [28] [1220/1319] eta: 0:04:23 lr: 1.57398512050765e-05 loss: 0.0393 (0.0416) time: 2.6068 data: 0.0063 max mem: 33369 +Epoch: [28] [1230/1319] eta: 0:03:57 lr: 1.5730152874751144e-05 loss: 0.0393 (0.0416) time: 2.6181 data: 0.0061 max mem: 33369 +Epoch: [28] [1240/1319] eta: 0:03:30 lr: 1.572045387999725e-05 loss: 0.0383 (0.0416) time: 2.6120 data: 0.0061 max mem: 33369 +Epoch: [28] [1250/1319] eta: 0:03:03 lr: 1.5710754220313764e-05 loss: 0.0381 (0.0416) time: 2.6117 data: 0.0062 max mem: 33369 +Epoch: [28] [1260/1319] eta: 0:02:37 lr: 1.5701053895198906e-05 loss: 0.0377 (0.0416) time: 2.6182 data: 0.0061 max mem: 33369 +Epoch: [28] [1270/1319] eta: 0:02:10 lr: 1.5691352904150157e-05 loss: 0.0363 (0.0415) time: 2.6234 data: 0.0062 max mem: 33369 +Epoch: [28] [1280/1319] eta: 0:01:43 lr: 1.5681651246664294e-05 loss: 0.0353 (0.0415) time: 2.6408 data: 0.0063 max mem: 33369 +Epoch: [28] [1290/1319] eta: 0:01:17 lr: 1.5671948922237363e-05 loss: 0.0331 (0.0415) time: 2.6652 data: 0.0062 max mem: 33369 +Epoch: [28] [1300/1319] eta: 0:00:50 lr: 1.5662245930364672e-05 loss: 0.0331 (0.0414) time: 2.6273 data: 0.0062 max mem: 33369 +Epoch: [28] [1310/1319] eta: 0:00:23 lr: 1.5652542270540813e-05 loss: 0.0356 (0.0415) time: 2.5869 data: 0.0062 max mem: 33369 +Epoch: [28] Total time: 0:58:31 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 1:59:25 time: 2.7849 data: 2.5371 max mem: 33369 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 100/2573] eta: 0:04:04 time: 0.0716 data: 0.0011 max mem: 33369 +Test: [ 200/2573] eta: 0:03:24 time: 0.0729 data: 0.0011 max mem: 33369 +Test: [ 300/2573] eta: 0:03:05 time: 0.0747 data: 0.0011 max mem: 33369 +Test: [ 400/2573] eta: 0:02:52 time: 0.0747 data: 0.0011 max mem: 33369 +Test: [ 500/2573] eta: 0:02:41 time: 0.0733 data: 0.0011 max mem: 33369 +Test: [ 600/2573] eta: 0:02:32 time: 0.0732 data: 0.0011 max mem: 33369 +Test: [ 700/2573] eta: 0:02:24 time: 0.0733 data: 0.0011 max mem: 33369 +Test: [ 800/2573] eta: 0:02:16 time: 0.0767 data: 0.0011 max mem: 33369 +Test: [ 900/2573] eta: 0:02:08 time: 0.0734 data: 0.0011 max mem: 33369 +Test: [1000/2573] eta: 0:01:59 time: 0.0734 data: 0.0011 max mem: 33369 +Test: [1100/2573] eta: 0:01:51 time: 0.0735 data: 0.0012 max mem: 33369 +Test: [1200/2573] eta: 0:01:44 time: 0.0736 data: 0.0011 max mem: 33369 +Test: [1300/2573] eta: 0:01:36 time: 0.0734 data: 0.0011 max mem: 33369 +Test: [1400/2573] eta: 0:01:28 time: 0.0719 data: 0.0011 max mem: 33369 +Test: [1500/2573] eta: 0:01:20 time: 0.0737 data: 0.0011 max mem: 33369 +Test: [1600/2573] eta: 0:01:13 time: 0.0774 data: 0.0011 max mem: 33369 +Test: [1700/2573] eta: 0:01:05 time: 0.0726 data: 0.0011 max mem: 33369 +Test: [1800/2573] eta: 0:00:58 time: 0.0758 data: 0.0011 max mem: 33369 +Test: [1900/2573] eta: 0:00:50 time: 0.0724 data: 0.0011 max mem: 33369 +Test: [2000/2573] eta: 0:00:43 time: 0.0741 data: 0.0011 max mem: 33369 +Test: [2100/2573] eta: 0:00:35 time: 0.0758 data: 0.0011 max mem: 33369 +Test: [2200/2573] eta: 0:00:27 time: 0.0758 data: 0.0011 max mem: 33369 +Test: [2300/2573] eta: 0:00:20 time: 0.0757 data: 0.0011 max mem: 33369 +Test: [2400/2573] eta: 0:00:12 time: 0.0708 data: 0.0011 max mem: 33369 +Test: [2500/2573] eta: 0:00:05 time: 0.0741 data: 0.0011 max mem: 33369 +Test: Total time: 0:03:13 +Final results: +Mean IoU is 64.42 + + precision@0.5 = 72.77 + precision@0.6 = 67.57 + precision@0.7 = 60.89 + precision@0.8 = 49.43 + precision@0.9 = 25.04 + overall IoU = 61.58 + +Average object IoU 64.41807729655294 +Overall IoU 61.58104705810547 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [29] [ 0/1319] eta: 3:00:18 lr: 1.5643808405182777e-05 loss: 0.0234 (0.0234) time: 8.2023 data: 2.0246 max mem: 33369 +Epoch: [29] [ 10/1319] eta: 1:07:45 lr: 1.563410347485666e-05 loss: 0.0463 (0.0445) time: 3.1057 data: 0.1898 max mem: 33369 +Epoch: [29] [ 20/1319] eta: 1:02:15 lr: 1.5624397875109532e-05 loss: 0.0420 (0.0417) time: 2.6093 data: 0.0060 max mem: 33369 +Epoch: [29] [ 30/1319] eta: 1:00:14 lr: 1.5614691605433113e-05 loss: 0.0420 (0.0417) time: 2.6385 data: 0.0060 max mem: 33369 +Epoch: [29] [ 40/1319] eta: 0:59:02 lr: 1.5604984665318397e-05 loss: 0.0368 (0.0425) time: 2.6592 data: 0.0061 max mem: 33369 +Epoch: [29] [ 50/1319] eta: 0:58:02 lr: 1.5595277054255625e-05 loss: 0.0346 (0.0425) time: 2.6509 data: 0.0061 max mem: 33369 +Epoch: [29] [ 60/1319] eta: 0:57:01 lr: 1.558556877173431e-05 loss: 0.0368 (0.0421) time: 2.6110 data: 0.0062 max mem: 33369 +Epoch: [29] [ 70/1319] eta: 0:56:15 lr: 1.557585981724323e-05 loss: 0.0368 (0.0411) time: 2.5976 data: 0.0061 max mem: 33369 +Epoch: [29] [ 80/1319] eta: 0:55:38 lr: 1.5566150190270393e-05 loss: 0.0336 (0.0407) time: 2.6245 data: 0.0062 max mem: 33369 +Epoch: [29] [ 90/1319] eta: 0:55:02 lr: 1.5556439890303075e-05 loss: 0.0335 (0.0403) time: 2.6319 data: 0.0061 max mem: 33369 +Epoch: [29] [ 100/1319] eta: 0:54:29 lr: 1.554672891682782e-05 loss: 0.0346 (0.0411) time: 2.6303 data: 0.0061 max mem: 33369 +Epoch: [29] [ 110/1319] eta: 0:53:55 lr: 1.55370172693304e-05 loss: 0.0385 (0.0410) time: 2.6243 data: 0.0063 max mem: 33369 +Epoch: [29] [ 120/1319] eta: 0:53:20 lr: 1.552730494729585e-05 loss: 0.0344 (0.0403) time: 2.6061 data: 0.0063 max mem: 33369 +Epoch: [29] [ 130/1319] eta: 0:52:52 lr: 1.551759195020846e-05 loss: 0.0323 (0.0401) time: 2.6230 data: 0.0061 max mem: 33369 +Epoch: [29] [ 140/1319] eta: 0:52:23 lr: 1.5507878277551742e-05 loss: 0.0361 (0.0399) time: 2.6471 data: 0.0063 max mem: 33369 +Epoch: [29] [ 150/1319] eta: 0:51:52 lr: 1.5498163928808475e-05 loss: 0.0320 (0.0394) time: 2.6304 data: 0.0063 max mem: 33369 +Epoch: [29] [ 160/1319] eta: 0:51:25 lr: 1.548844890346068e-05 loss: 0.0327 (0.0394) time: 2.6327 data: 0.0061 max mem: 33369 +Epoch: [29] [ 170/1319] eta: 0:50:55 lr: 1.547873320098961e-05 loss: 0.0362 (0.0392) time: 2.6353 data: 0.0062 max mem: 33369 +Epoch: [29] [ 180/1319] eta: 0:50:25 lr: 1.546901682087577e-05 loss: 0.0369 (0.0397) time: 2.6064 data: 0.0063 max mem: 33369 +Epoch: [29] [ 190/1319] eta: 0:49:55 lr: 1.5459299762598884e-05 loss: 0.0445 (0.0398) time: 2.5960 data: 0.0061 max mem: 33369 +Epoch: [29] [ 200/1319] eta: 0:49:27 lr: 1.5449582025637935e-05 loss: 0.0364 (0.0400) time: 2.6109 data: 0.0061 max mem: 33369 +Epoch: [29] [ 210/1319] eta: 0:48:58 lr: 1.543986360947113e-05 loss: 0.0361 (0.0397) time: 2.6177 data: 0.0063 max mem: 33369 +Epoch: [29] [ 220/1319] eta: 0:48:31 lr: 1.543014451357591e-05 loss: 0.0421 (0.0401) time: 2.6246 data: 0.0063 max mem: 33369 +Epoch: [29] [ 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33369 +Epoch: [29] [ 310/1319] eta: 0:44:23 lr: 1.5342641976136825e-05 loss: 0.0391 (0.0406) time: 2.6329 data: 0.0062 max mem: 33369 +Epoch: [29] [ 320/1319] eta: 0:43:56 lr: 1.5332916054047e-05 loss: 0.0337 (0.0408) time: 2.6276 data: 0.0060 max mem: 33369 +Epoch: [29] [ 330/1319] eta: 0:43:30 lr: 1.532318944642957e-05 loss: 0.0337 (0.0405) time: 2.6331 data: 0.0060 max mem: 33369 +Epoch: [29] [ 340/1319] eta: 0:43:03 lr: 1.5313462152752656e-05 loss: 0.0327 (0.0404) time: 2.6311 data: 0.0061 max mem: 33369 +Epoch: [29] [ 350/1319] eta: 0:42:36 lr: 1.5303734172483566e-05 loss: 0.0358 (0.0406) time: 2.6172 data: 0.0061 max mem: 33369 +Epoch: [29] [ 360/1319] eta: 0:42:09 lr: 1.529400550508885e-05 loss: 0.0376 (0.0405) time: 2.6202 data: 0.0061 max mem: 33369 +Epoch: [29] [ 370/1319] eta: 0:41:42 lr: 1.528427615003424e-05 loss: 0.0359 (0.0404) time: 2.6111 data: 0.0062 max mem: 33369 +Epoch: [29] [ 380/1319] eta: 0:41:15 lr: 1.5274546106784702e-05 loss: 0.0332 (0.0403) time: 2.6049 data: 0.0060 max mem: 33369 +Epoch: [29] [ 390/1319] eta: 0:40:48 lr: 1.526481537480438e-05 loss: 0.0298 (0.0401) time: 2.6204 data: 0.0059 max mem: 33369 +Epoch: [29] [ 400/1319] eta: 0:40:21 lr: 1.525508395355664e-05 loss: 0.0335 (0.0402) time: 2.6143 data: 0.0061 max mem: 33369 +Epoch: [29] [ 410/1319] eta: 0:39:55 lr: 1.5245351842504036e-05 loss: 0.0358 (0.0403) time: 2.6149 data: 0.0061 max mem: 33369 +Epoch: [29] [ 420/1319] eta: 0:39:29 lr: 1.5235619041108326e-05 loss: 0.0345 (0.0403) time: 2.6420 data: 0.0060 max mem: 33369 +Epoch: [29] [ 430/1319] eta: 0:39:01 lr: 1.5225885548830468e-05 loss: 0.0369 (0.0406) time: 2.6124 data: 0.0059 max mem: 33369 +Epoch: [29] [ 440/1319] eta: 0:38:34 lr: 1.5216151365130616e-05 loss: 0.0402 (0.0406) time: 2.5902 data: 0.0059 max mem: 33369 +Epoch: [29] [ 450/1319] eta: 0:38:07 lr: 1.520641648946812e-05 loss: 0.0389 (0.0406) time: 2.5984 data: 0.0060 max mem: 33369 +Epoch: [29] [ 460/1319] eta: 0:37:40 lr: 1.519668092130151e-05 loss: 0.0389 (0.0405) time: 2.6027 data: 0.0059 max mem: 33369 +Epoch: [29] [ 470/1319] eta: 0:37:13 lr: 1.5186944660088521e-05 loss: 0.0366 (0.0407) time: 2.5995 data: 0.0059 max mem: 33369 +Epoch: [29] [ 480/1319] eta: 0:36:47 lr: 1.5177207705286068e-05 loss: 0.0403 (0.0408) time: 2.6052 data: 0.0062 max mem: 33369 +Epoch: [29] [ 490/1319] eta: 0:36:20 lr: 1.5167470056350257e-05 loss: 0.0386 (0.0407) time: 2.6048 data: 0.0062 max mem: 33369 +Epoch: [29] [ 500/1319] eta: 0:35:53 lr: 1.5157731712736389e-05 loss: 0.0386 (0.0408) time: 2.6114 data: 0.0061 max mem: 33369 +Epoch: [29] [ 510/1319] eta: 0:35:28 lr: 1.514799267389892e-05 loss: 0.0453 (0.0408) time: 2.6520 data: 0.0061 max mem: 33369 +Epoch: [29] [ 520/1319] eta: 0:35:01 lr: 1.5138252939291514e-05 loss: 0.0328 (0.0406) time: 2.6358 data: 0.0062 max mem: 33369 +Epoch: [29] [ 530/1319] eta: 0:34:34 lr: 1.5128512508367005e-05 loss: 0.0277 (0.0405) time: 2.6082 data: 0.0061 max mem: 33369 +Epoch: [29] [ 540/1319] eta: 0:34:09 lr: 1.5118771380577405e-05 loss: 0.0323 (0.0404) time: 2.6344 data: 0.0060 max mem: 33369 +Epoch: [29] [ 550/1319] eta: 0:33:42 lr: 1.5109029555373904e-05 loss: 0.0359 (0.0404) time: 2.6296 data: 0.0060 max mem: 33369 +Epoch: [29] [ 560/1319] eta: 0:33:16 lr: 1.5099287032206873e-05 loss: 0.0360 (0.0403) time: 2.6144 data: 0.0060 max mem: 33369 +Epoch: [29] [ 570/1319] eta: 0:32:49 lr: 1.5089543810525833e-05 loss: 0.0334 (0.0402) time: 2.6181 data: 0.0059 max mem: 33369 +Epoch: [29] [ 580/1319] eta: 0:32:23 lr: 1.50797998897795e-05 loss: 0.0377 (0.0403) time: 2.6133 data: 0.0060 max mem: 33369 +Epoch: [29] [ 590/1319] eta: 0:31:56 lr: 1.5070055269415744e-05 loss: 0.0385 (0.0403) time: 2.6317 data: 0.0061 max mem: 33369 +Epoch: [29] [ 600/1319] eta: 0:31:30 lr: 1.5060309948881612e-05 loss: 0.0359 (0.0403) time: 2.6182 data: 0.0060 max mem: 33369 +Epoch: [29] [ 610/1319] eta: 0:31:03 lr: 1.5050563927623313e-05 loss: 0.0343 (0.0402) time: 2.6060 data: 0.0062 max mem: 33369 +Epoch: [29] [ 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33369 +Epoch: [29] [ 700/1319] eta: 0:27:07 lr: 1.4962818111919327e-05 loss: 0.0369 (0.0401) time: 2.6169 data: 0.0061 max mem: 33369 +Epoch: [29] [ 710/1319] eta: 0:26:40 lr: 1.4953065052775669e-05 loss: 0.0371 (0.0401) time: 2.5946 data: 0.0062 max mem: 33369 +Epoch: [29] [ 720/1319] eta: 0:26:14 lr: 1.494331128676048e-05 loss: 0.0407 (0.0402) time: 2.5890 data: 0.0061 max mem: 33369 +Epoch: [29] [ 730/1319] eta: 0:25:47 lr: 1.4933556813309787e-05 loss: 0.0437 (0.0402) time: 2.6165 data: 0.0060 max mem: 33369 +Epoch: [29] [ 740/1319] eta: 0:25:21 lr: 1.4923801631858781e-05 loss: 0.0392 (0.0402) time: 2.6381 data: 0.0059 max mem: 33369 +Epoch: [29] [ 750/1319] eta: 0:24:55 lr: 1.4914045741841778e-05 loss: 0.0391 (0.0402) time: 2.6283 data: 0.0059 max mem: 33369 +Epoch: [29] [ 760/1319] eta: 0:24:29 lr: 1.4904289142692235e-05 loss: 0.0376 (0.0401) time: 2.6246 data: 0.0058 max mem: 33369 +Epoch: [29] [ 770/1319] eta: 0:24:02 lr: 1.4894531833842748e-05 loss: 0.0388 (0.0402) time: 2.6429 data: 0.0059 max mem: 33369 +Epoch: [29] [ 780/1319] eta: 0:23:36 lr: 1.4884773814725032e-05 loss: 0.0362 (0.0401) time: 2.6218 data: 0.0060 max mem: 33369 +Epoch: [29] [ 790/1319] eta: 0:23:09 lr: 1.4875015084769944e-05 loss: 0.0292 (0.0401) time: 2.6097 data: 0.0060 max mem: 33369 +Epoch: [29] [ 800/1319] eta: 0:22:43 lr: 1.4865255643407467e-05 loss: 0.0339 (0.0401) time: 2.6301 data: 0.0061 max mem: 33369 +Epoch: [29] [ 810/1319] eta: 0:22:17 lr: 1.4855495490066707e-05 loss: 0.0384 (0.0401) time: 2.6580 data: 0.0062 max mem: 33369 +Epoch: [29] [ 820/1319] eta: 0:21:51 lr: 1.4845734624175911e-05 loss: 0.0322 (0.0402) time: 2.6566 data: 0.0062 max mem: 33369 +Epoch: [29] [ 830/1319] eta: 0:21:25 lr: 1.4835973045162419e-05 loss: 0.0336 (0.0403) time: 2.6401 data: 0.0060 max mem: 33369 +Epoch: [29] [ 840/1319] eta: 0:20:59 lr: 1.4826210752452718e-05 loss: 0.0388 (0.0402) time: 2.6292 data: 0.0059 max mem: 33369 +Epoch: [29] [ 850/1319] eta: 0:20:32 lr: 1.48164477454724e-05 loss: 0.0365 (0.0403) time: 2.6364 data: 0.0060 max mem: 33369 +Epoch: [29] [ 860/1319] eta: 0:20:06 lr: 1.4806684023646183e-05 loss: 0.0336 (0.0403) time: 2.6562 data: 0.0059 max mem: 33369 +Epoch: [29] [ 870/1319] eta: 0:19:40 lr: 1.4796919586397895e-05 loss: 0.0373 (0.0404) time: 2.6512 data: 0.0058 max mem: 33369 +Epoch: [29] [ 880/1319] eta: 0:19:14 lr: 1.4787154433150476e-05 loss: 0.0363 (0.0404) time: 2.6382 data: 0.0059 max mem: 33369 +Epoch: [29] [ 890/1319] eta: 0:18:48 lr: 1.4777388563325976e-05 loss: 0.0351 (0.0404) time: 2.6694 data: 0.0060 max mem: 33369 +Epoch: [29] [ 900/1319] eta: 0:18:22 lr: 1.4767621976345552e-05 loss: 0.0332 (0.0403) time: 2.6637 data: 0.0059 max mem: 33369 +Epoch: [29] [ 910/1319] eta: 0:17:55 lr: 1.4757854671629475e-05 loss: 0.0356 (0.0403) time: 2.6271 data: 0.0060 max mem: 33369 +Epoch: [29] [ 920/1319] eta: 0:17:29 lr: 1.4748086648597121e-05 loss: 0.0377 (0.0404) time: 2.6090 data: 0.0059 max mem: 33369 +Epoch: [29] [ 930/1319] eta: 0:17:02 lr: 1.4738317906666963e-05 loss: 0.0402 (0.0404) time: 2.5912 data: 0.0059 max mem: 33369 +Epoch: [29] [ 940/1319] eta: 0:16:36 lr: 1.4728548445256565e-05 loss: 0.0380 (0.0404) time: 2.5976 data: 0.0061 max mem: 33369 +Epoch: [29] [ 950/1319] eta: 0:16:09 lr: 1.471877826378261e-05 loss: 0.0370 (0.0404) time: 2.5976 data: 0.0061 max mem: 33369 +Epoch: [29] [ 960/1319] eta: 0:15:43 lr: 1.4709007361660864e-05 loss: 0.0363 (0.0403) time: 2.6050 data: 0.0059 max mem: 33369 +Epoch: [29] [ 970/1319] eta: 0:15:17 lr: 1.4699235738306196e-05 loss: 0.0363 (0.0403) time: 2.6063 data: 0.0061 max mem: 33369 +Epoch: [29] [ 980/1319] eta: 0:14:50 lr: 1.4689463393132561e-05 loss: 0.0357 (0.0403) time: 2.6120 data: 0.0061 max mem: 33369 +Epoch: [29] [ 990/1319] eta: 0:14:24 lr: 1.4679690325553006e-05 loss: 0.0342 (0.0403) time: 2.6248 data: 0.0060 max mem: 33369 +Epoch: [29] [1000/1319] eta: 0:13:58 lr: 1.466991653497966e-05 loss: 0.0364 (0.0403) time: 2.5929 data: 0.0060 max mem: 33369 +Epoch: [29] [1010/1319] eta: 0:13:31 lr: 1.466014202082375e-05 loss: 0.0393 (0.0404) time: 2.5935 data: 0.0059 max mem: 33369 +Epoch: [29] [1020/1319] eta: 0:13:05 lr: 1.4650366782495577e-05 loss: 0.0309 (0.0403) time: 2.6381 data: 0.0058 max mem: 33369 +Epoch: [29] [1030/1319] eta: 0:12:39 lr: 1.4640590819404531e-05 loss: 0.0324 (0.0404) time: 2.6192 data: 0.0058 max mem: 33369 +Epoch: [29] [1040/1319] eta: 0:12:12 lr: 1.4630814130959084e-05 loss: 0.0363 (0.0403) time: 2.5989 data: 0.0059 max mem: 33369 +Epoch: [29] [1050/1319] eta: 0:11:46 lr: 1.4621036716566766e-05 loss: 0.0334 (0.0402) time: 2.6103 data: 0.0060 max mem: 33369 +Epoch: [29] [1060/1319] eta: 0:11:20 lr: 1.4611258575634206e-05 loss: 0.0356 (0.0402) time: 2.6060 data: 0.0059 max mem: 33369 +Epoch: [29] [1070/1319] eta: 0:10:54 lr: 1.4601479707567092e-05 loss: 0.0395 (0.0402) time: 2.6279 data: 0.0059 max mem: 33369 +Epoch: [29] [1080/1319] eta: 0:10:27 lr: 1.4591700111770195e-05 loss: 0.0382 (0.0402) time: 2.6519 data: 0.0060 max mem: 33369 +Epoch: [29] [1090/1319] eta: 0:10:01 lr: 1.4581919787647347e-05 loss: 0.0360 (0.0402) time: 2.6355 data: 0.0059 max mem: 33369 +Epoch: [29] [1100/1319] eta: 0:09:35 lr: 1.4572138734601442e-05 loss: 0.0363 (0.0401) time: 2.6151 data: 0.0061 max mem: 33369 +Epoch: [29] [1110/1319] eta: 0:09:09 lr: 1.4562356952034447e-05 loss: 0.0363 (0.0401) time: 2.6171 data: 0.0062 max mem: 33369 +Epoch: [29] [1120/1319] eta: 0:08:42 lr: 1.4552574439347391e-05 loss: 0.0345 (0.0401) time: 2.6177 data: 0.0061 max mem: 33369 +Epoch: [29] [1130/1319] eta: 0:08:16 lr: 1.4542791195940364e-05 loss: 0.0328 (0.0401) time: 2.6092 data: 0.0059 max mem: 33369 +Epoch: [29] [1140/1319] eta: 0:07:50 lr: 1.453300722121251e-05 loss: 0.0347 (0.0400) time: 2.6128 data: 0.0060 max mem: 33369 +Epoch: [29] [1150/1319] eta: 0:07:23 lr: 1.4523222514562035e-05 loss: 0.0347 (0.0400) time: 2.6592 data: 0.0060 max mem: 33369 +Epoch: [29] [1160/1319] eta: 0:06:57 lr: 1.4513437075386188e-05 loss: 0.0341 (0.0400) time: 2.6415 data: 0.0059 max mem: 33369 +Epoch: [29] [1170/1319] eta: 0:06:31 lr: 1.4503650903081281e-05 loss: 0.0365 (0.0400) time: 2.6129 data: 0.0058 max mem: 33369 +Epoch: [29] [1180/1319] eta: 0:06:05 lr: 1.449386399704267e-05 loss: 0.0401 (0.0401) time: 2.6417 data: 0.0059 max mem: 33369 +Epoch: [29] [1190/1319] eta: 0:05:38 lr: 1.4484076356664761e-05 loss: 0.0397 (0.0400) time: 2.6179 data: 0.0060 max mem: 33369 +Epoch: [29] [1200/1319] eta: 0:05:12 lr: 1.447428798134101e-05 loss: 0.0368 (0.0400) time: 2.6114 data: 0.0058 max mem: 33369 +Epoch: [29] [1210/1319] eta: 0:04:46 lr: 1.4464498870463896e-05 loss: 0.0380 (0.0400) time: 2.6192 data: 0.0058 max mem: 33369 +Epoch: [29] [1220/1319] eta: 0:04:20 lr: 1.4454709023424959e-05 loss: 0.0382 (0.0401) time: 2.6102 data: 0.0059 max mem: 33369 +Epoch: [29] [1230/1319] eta: 0:03:53 lr: 1.444491843961477e-05 loss: 0.0349 (0.0401) time: 2.6244 data: 0.0059 max mem: 33369 +Epoch: [29] [1240/1319] eta: 0:03:27 lr: 1.4435127118422938e-05 loss: 0.0354 (0.0401) time: 2.6341 data: 0.0059 max mem: 33369 +Epoch: [29] [1250/1319] eta: 0:03:01 lr: 1.442533505923811e-05 loss: 0.0401 (0.0401) time: 2.6266 data: 0.0060 max mem: 33369 +Epoch: [29] [1260/1319] eta: 0:02:34 lr: 1.4415542261447945e-05 loss: 0.0343 (0.0400) time: 2.6171 data: 0.0060 max mem: 33369 +Epoch: [29] [1270/1319] eta: 0:02:08 lr: 1.4405748724439155e-05 loss: 0.0340 (0.0401) time: 2.6325 data: 0.0060 max mem: 33369 +Epoch: [29] [1280/1319] eta: 0:01:42 lr: 1.4395954447597464e-05 loss: 0.0324 (0.0400) time: 2.6268 data: 0.0058 max mem: 33369 +Epoch: [29] [1290/1319] eta: 0:01:16 lr: 1.4386159430307632e-05 loss: 0.0324 (0.0400) time: 2.5822 data: 0.0058 max mem: 33369 +Epoch: [29] [1300/1319] eta: 0:00:49 lr: 1.4376363671953435e-05 loss: 0.0373 (0.0400) time: 2.5783 data: 0.0060 max mem: 33369 +Epoch: [29] [1310/1319] eta: 0:00:23 lr: 1.4366567171917672e-05 loss: 0.0320 (0.0400) time: 2.6241 data: 0.0061 max mem: 33369 +Epoch: [29] Total time: 0:57:44 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 2:00:43 time: 2.8154 data: 2.7019 max mem: 33369 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 100/2573] eta: 0:04:04 time: 0.0711 data: 0.0011 max mem: 33369 +Test: [ 200/2573] eta: 0:03:25 time: 0.0729 data: 0.0012 max mem: 33369 +Test: [ 300/2573] eta: 0:03:05 time: 0.0747 data: 0.0011 max mem: 33369 +Test: [ 400/2573] eta: 0:02:52 time: 0.0749 data: 0.0011 max mem: 33369 +Test: [ 500/2573] eta: 0:02:42 time: 0.0733 data: 0.0011 max mem: 33369 +Test: [ 600/2573] eta: 0:02:32 time: 0.0734 data: 0.0011 max mem: 33369 +Test: [ 700/2573] eta: 0:02:24 time: 0.0735 data: 0.0012 max mem: 33369 +Test: [ 800/2573] eta: 0:02:16 time: 0.0768 data: 0.0011 max mem: 33369 +Test: [ 900/2573] eta: 0:02:08 time: 0.0734 data: 0.0011 max mem: 33369 +Test: [1000/2573] eta: 0:02:00 time: 0.0735 data: 0.0011 max mem: 33369 +Test: [1100/2573] eta: 0:01:52 time: 0.0736 data: 0.0011 max mem: 33369 +Test: [1200/2573] eta: 0:01:44 time: 0.0736 data: 0.0011 max mem: 33369 +Test: [1300/2573] eta: 0:01:36 time: 0.0735 data: 0.0011 max mem: 33369 +Test: [1400/2573] eta: 0:01:28 time: 0.0720 data: 0.0011 max mem: 33369 +Test: [1500/2573] eta: 0:01:20 time: 0.0737 data: 0.0011 max mem: 33369 +Test: [1600/2573] eta: 0:01:13 time: 0.0769 data: 0.0011 max mem: 33369 +Test: [1700/2573] eta: 0:01:05 time: 0.0720 data: 0.0011 max mem: 33369 +Test: [1800/2573] eta: 0:00:58 time: 0.0755 data: 0.0011 max mem: 33369 +Test: [1900/2573] eta: 0:00:50 time: 0.0722 data: 0.0011 max mem: 33369 +Test: [2000/2573] eta: 0:00:42 time: 0.0737 data: 0.0011 max mem: 33369 +Test: [2100/2573] eta: 0:00:35 time: 0.0754 data: 0.0011 max mem: 33369 +Test: [2200/2573] eta: 0:00:27 time: 0.0753 data: 0.0011 max mem: 33369 +Test: [2300/2573] eta: 0:00:20 time: 0.0753 data: 0.0011 max mem: 33369 +Test: [2400/2573] eta: 0:00:12 time: 0.0705 data: 0.0012 max mem: 33369 +Test: [2500/2573] eta: 0:00:05 time: 0.0737 data: 0.0011 max mem: 33369 +Test: Total time: 0:03:12 +Final results: +Mean IoU is 64.40 + + precision@0.5 = 72.69 + precision@0.6 = 68.01 + precision@0.7 = 60.95 + precision@0.8 = 49.88 + precision@0.9 = 25.22 + overall IoU = 62.01 + +Average object IoU 64.39502005442779 +Overall IoU 62.014984130859375 +Better epoch: 29 + +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [30] [ 0/1319] eta: 1:25:27 lr: 1.4357749687236825e-05 loss: 0.0471 (0.0471) time: 3.8872 data: 1.2367 max mem: 33369 +Epoch: [30] [ 10/1319] eta: 0:59:34 lr: 1.4347951776302166e-05 loss: 0.0414 (0.0396) time: 2.7304 data: 0.1179 max mem: 33369 +Epoch: [30] [ 20/1319] eta: 0:58:19 lr: 1.433815312189048e-05 loss: 0.0379 (0.0397) time: 2.6342 data: 0.0058 max mem: 33369 +Epoch: [30] [ 30/1319] eta: 0:57:21 lr: 1.4328353723380728e-05 loss: 0.0343 (0.0377) time: 2.6368 data: 0.0060 max mem: 33369 +Epoch: [30] [ 40/1319] eta: 0:56:41 lr: 1.431855358015087e-05 loss: 0.0315 (0.0371) time: 2.6242 data: 0.0061 max mem: 33369 +Epoch: [30] [ 50/1319] eta: 0:55:59 lr: 1.4308752691577878e-05 loss: 0.0352 (0.0382) time: 2.6119 data: 0.0060 max mem: 33369 +Epoch: [30] [ 60/1319] eta: 0:55:26 lr: 1.4298951057037729e-05 loss: 0.0365 (0.0382) time: 2.6063 data: 0.0062 max mem: 33369 +Epoch: [30] [ 70/1319] eta: 0:54:59 lr: 1.4289148675905387e-05 loss: 0.0376 (0.0381) time: 2.6279 data: 0.0062 max mem: 33369 +Epoch: [30] [ 80/1319] eta: 0:54:22 lr: 1.4279345547554832e-05 loss: 0.0373 (0.0382) time: 2.6067 data: 0.0062 max mem: 33369 +Epoch: [30] [ 90/1319] eta: 0:53:54 lr: 1.4269541671359036e-05 loss: 0.0324 (0.0383) time: 2.5947 data: 0.0063 max mem: 33369 +Epoch: [30] [ 100/1319] eta: 0:53:31 lr: 1.4259737046689963e-05 loss: 0.0376 (0.0385) time: 2.6366 data: 0.0061 max mem: 33369 +Epoch: [30] [ 110/1319] eta: 0:53:07 lr: 1.424993167291858e-05 loss: 0.0359 (0.0386) time: 2.6597 data: 0.0059 max mem: 33369 +Epoch: [30] [ 120/1319] eta: 0:52:35 lr: 1.4240125549414829e-05 loss: 0.0376 (0.0388) time: 2.6177 data: 0.0059 max mem: 33369 +Epoch: [30] [ 130/1319] eta: 0:52:10 lr: 1.4230318675547643e-05 loss: 0.0397 (0.0392) time: 2.6107 data: 0.0062 max mem: 33369 +Epoch: [30] [ 140/1319] eta: 0:51:45 lr: 1.4220511050684946e-05 loss: 0.0363 (0.0389) time: 2.6514 data: 0.0062 max mem: 33369 +Epoch: [30] [ 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data: 0.0060 max mem: 33369 +Epoch: [30] [ 310/1319] eta: 0:44:15 lr: 1.4053665908255448e-05 loss: 0.0335 (0.0373) time: 2.6198 data: 0.0060 max mem: 33369 +Epoch: [30] [ 320/1319] eta: 0:43:48 lr: 1.4043844656216607e-05 loss: 0.0335 (0.0374) time: 2.6213 data: 0.0060 max mem: 33369 +Epoch: [30] [ 330/1319] eta: 0:43:20 lr: 1.4034022640976696e-05 loss: 0.0332 (0.0373) time: 2.6026 data: 0.0061 max mem: 33369 +Epoch: [30] [ 340/1319] eta: 0:42:54 lr: 1.4024199861882808e-05 loss: 0.0333 (0.0373) time: 2.6065 data: 0.0059 max mem: 33369 +Epoch: [30] [ 350/1319] eta: 0:42:29 lr: 1.4014376318280992e-05 loss: 0.0308 (0.0372) time: 2.6446 data: 0.0058 max mem: 33369 +Epoch: [30] [ 360/1319] eta: 0:42:02 lr: 1.4004552009516214e-05 loss: 0.0292 (0.0376) time: 2.6442 data: 0.0059 max mem: 33369 +Epoch: [30] [ 370/1319] eta: 0:41:35 lr: 1.3994726934932381e-05 loss: 0.0330 (0.0375) time: 2.6184 data: 0.0059 max mem: 33369 +Epoch: [30] [ 380/1319] eta: 0:41:09 lr: 1.3984901093872316e-05 loss: 0.0359 (0.0376) time: 2.6194 data: 0.0060 max mem: 33369 +Epoch: [30] [ 390/1319] eta: 0:40:41 lr: 1.3975074485677755e-05 loss: 0.0365 (0.0378) time: 2.5950 data: 0.0060 max mem: 33369 +Epoch: [30] [ 400/1319] eta: 0:40:15 lr: 1.3965247109689372e-05 loss: 0.0365 (0.0378) time: 2.6091 data: 0.0060 max mem: 33369 +Epoch: [30] [ 410/1319] eta: 0:39:49 lr: 1.3955418965246752e-05 loss: 0.0331 (0.0376) time: 2.6414 data: 0.0061 max mem: 33369 +Epoch: [30] [ 420/1319] eta: 0:39:24 lr: 1.394559005168839e-05 loss: 0.0284 (0.0375) time: 2.6592 data: 0.0059 max mem: 33369 +Epoch: [30] [ 430/1319] eta: 0:38:58 lr: 1.39357603683517e-05 loss: 0.0335 (0.0376) time: 2.6665 data: 0.0058 max mem: 33369 +Epoch: [30] [ 440/1319] eta: 0:38:32 lr: 1.3925929914573002e-05 loss: 0.0358 (0.0377) time: 2.6376 data: 0.0059 max mem: 33369 +Epoch: [30] [ 450/1319] eta: 0:38:05 lr: 1.3916098689687517e-05 loss: 0.0410 (0.0378) time: 2.6265 data: 0.0060 max mem: 33369 +Epoch: [30] [ 460/1319] eta: 0:37:39 lr: 1.3906266693029377e-05 loss: 0.0389 (0.0377) time: 2.6148 data: 0.0060 max mem: 33369 +Epoch: [30] [ 470/1319] eta: 0:37:12 lr: 1.3896433923931618e-05 loss: 0.0386 (0.0379) time: 2.6087 data: 0.0061 max mem: 33369 +Epoch: [30] [ 480/1319] eta: 0:36:46 lr: 1.3886600381726167e-05 loss: 0.0337 (0.0378) time: 2.6332 data: 0.0062 max mem: 33369 +Epoch: [30] [ 490/1319] eta: 0:36:19 lr: 1.3876766065743859e-05 loss: 0.0313 (0.0377) time: 2.6185 data: 0.0061 max mem: 33369 +Epoch: [30] [ 500/1319] eta: 0:35:52 lr: 1.3866930975314405e-05 loss: 0.0366 (0.0378) time: 2.5979 data: 0.0060 max mem: 33369 +Epoch: [30] [ 510/1319] eta: 0:35:26 lr: 1.3857095109766416e-05 loss: 0.0354 (0.0378) time: 2.6219 data: 0.0060 max mem: 33369 +Epoch: [30] [ 520/1319] eta: 0:35:00 lr: 1.3847258468427396e-05 loss: 0.0363 (0.0379) time: 2.6428 data: 0.0059 max mem: 33369 +Epoch: [30] [ 530/1319] eta: 0:34:34 lr: 1.3837421050623725e-05 loss: 0.0424 (0.0381) time: 2.6263 data: 0.0058 max mem: 33369 +Epoch: [30] [ 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data: 0.0060 max mem: 33369 +Epoch: [30] [ 700/1319] eta: 0:27:04 lr: 1.3670065490679108e-05 loss: 0.0323 (0.0375) time: 2.6090 data: 0.0059 max mem: 33369 +Epoch: [30] [ 710/1319] eta: 0:26:38 lr: 1.3660213980036074e-05 loss: 0.0326 (0.0375) time: 2.6227 data: 0.0061 max mem: 33369 +Epoch: [30] [ 720/1319] eta: 0:26:12 lr: 1.3650361679914193e-05 loss: 0.0344 (0.0375) time: 2.6351 data: 0.0060 max mem: 33369 +Epoch: [30] [ 730/1319] eta: 0:25:46 lr: 1.3640508589616971e-05 loss: 0.0347 (0.0375) time: 2.6211 data: 0.0061 max mem: 33369 +Epoch: [30] [ 740/1319] eta: 0:25:19 lr: 1.3630654708446738e-05 loss: 0.0352 (0.0375) time: 2.6031 data: 0.0062 max mem: 33369 +Epoch: [30] [ 750/1319] eta: 0:24:53 lr: 1.3620800035704648e-05 loss: 0.0352 (0.0376) time: 2.5883 data: 0.0060 max mem: 33369 +Epoch: [30] [ 760/1319] eta: 0:24:27 lr: 1.3610944570690678e-05 loss: 0.0395 (0.0377) time: 2.6169 data: 0.0059 max mem: 33369 +Epoch: [30] [ 770/1319] eta: 0:24:00 lr: 1.3601088312703605e-05 loss: 0.0371 (0.0376) time: 2.6239 data: 0.0059 max mem: 33369 +Epoch: [30] [ 780/1319] eta: 0:23:34 lr: 1.3591231261041042e-05 loss: 0.0343 (0.0377) time: 2.6307 data: 0.0059 max mem: 33369 +Epoch: [30] [ 790/1319] eta: 0:23:08 lr: 1.3581373414999401e-05 loss: 0.0394 (0.0377) time: 2.6398 data: 0.0059 max mem: 33369 +Epoch: [30] [ 800/1319] eta: 0:22:42 lr: 1.3571514773873906e-05 loss: 0.0375 (0.0377) time: 2.6338 data: 0.0059 max mem: 33369 +Epoch: [30] [ 810/1319] eta: 0:22:16 lr: 1.3561655336958593e-05 loss: 0.0342 (0.0377) time: 2.6377 data: 0.0061 max mem: 33369 +Epoch: [30] [ 820/1319] eta: 0:21:49 lr: 1.3551795103546277e-05 loss: 0.0322 (0.0377) time: 2.6415 data: 0.0060 max mem: 33369 +Epoch: [30] [ 830/1319] eta: 0:21:23 lr: 1.3541934072928603e-05 loss: 0.0370 (0.0377) time: 2.6210 data: 0.0059 max mem: 33369 +Epoch: [30] [ 840/1319] eta: 0:20:57 lr: 1.3532072244395987e-05 loss: 0.0364 (0.0377) time: 2.6096 data: 0.0060 max mem: 33369 +Epoch: [30] [ 850/1319] eta: 0:20:30 lr: 1.3522209617237661e-05 loss: 0.0353 (0.0378) time: 2.6168 data: 0.0061 max mem: 33369 +Epoch: [30] [ 860/1319] eta: 0:20:05 lr: 1.3512346190741623e-05 loss: 0.0382 (0.0378) time: 2.6638 data: 0.0061 max mem: 33369 +Epoch: [30] [ 870/1319] eta: 0:19:38 lr: 1.3502481964194685e-05 loss: 0.0479 (0.0382) time: 2.6473 data: 0.0060 max mem: 33369 +Epoch: [30] [ 880/1319] eta: 0:19:12 lr: 1.3492616936882415e-05 loss: 0.0439 (0.0381) time: 2.6041 data: 0.0060 max mem: 33369 +Epoch: [30] [ 890/1319] eta: 0:18:46 lr: 1.3482751108089178e-05 loss: 0.0322 (0.0382) time: 2.6310 data: 0.0061 max mem: 33369 +Epoch: [30] [ 900/1319] eta: 0:18:20 lr: 1.3472884477098122e-05 loss: 0.0372 (0.0382) time: 2.6313 data: 0.0061 max mem: 33369 +Epoch: [30] [ 910/1319] eta: 0:17:53 lr: 1.3463017043191156e-05 loss: 0.0361 (0.0382) time: 2.6304 data: 0.0061 max mem: 33369 +Epoch: [30] [ 920/1319] eta: 0:17:27 lr: 1.3453148805648974e-05 loss: 0.0348 (0.0382) time: 2.6283 data: 0.0060 max mem: 33369 +Epoch: [30] [ 930/1319] eta: 0:17:01 lr: 1.3443279763751026e-05 loss: 0.0365 (0.0382) time: 2.6223 data: 0.0058 max mem: 33369 +Epoch: [30] [ 940/1319] eta: 0:16:35 lr: 1.3433409916775535e-05 loss: 0.0350 (0.0384) time: 2.6307 data: 0.0058 max mem: 33369 +Epoch: [30] [ 950/1319] eta: 0:16:08 lr: 1.3423539263999488e-05 loss: 0.0342 (0.0383) time: 2.6285 data: 0.0058 max mem: 33369 +Epoch: [30] [ 960/1319] eta: 0:15:42 lr: 1.341366780469863e-05 loss: 0.0349 (0.0384) time: 2.6122 data: 0.0059 max mem: 33369 +Epoch: [30] [ 970/1319] eta: 0:15:16 lr: 1.340379553814746e-05 loss: 0.0347 (0.0383) time: 2.6038 data: 0.0060 max mem: 33369 +Epoch: [30] [ 980/1319] eta: 0:14:49 lr: 1.3393922463619227e-05 loss: 0.0343 (0.0383) time: 2.6027 data: 0.0059 max mem: 33369 +Epoch: [30] [ 990/1319] eta: 0:14:23 lr: 1.3384048580385938e-05 loss: 0.0373 (0.0384) time: 2.5969 data: 0.0059 max mem: 33369 +Epoch: [30] [1000/1319] eta: 0:13:57 lr: 1.3374173887718341e-05 loss: 0.0365 (0.0384) time: 2.6136 data: 0.0061 max mem: 33369 +Epoch: [30] [1010/1319] eta: 0:13:30 lr: 1.3364298384885935e-05 loss: 0.0349 (0.0383) time: 2.6256 data: 0.0060 max mem: 33369 +Epoch: [30] [1020/1319] eta: 0:13:04 lr: 1.3354422071156945e-05 loss: 0.0292 (0.0383) time: 2.5815 data: 0.0060 max mem: 33369 +Epoch: [30] [1030/1319] eta: 0:12:38 lr: 1.3344544945798354e-05 loss: 0.0354 (0.0383) time: 2.6146 data: 0.0059 max mem: 33369 +Epoch: [30] [1040/1319] eta: 0:12:12 lr: 1.3334667008075852e-05 loss: 0.0351 (0.0383) time: 2.6570 data: 0.0059 max mem: 33369 +Epoch: [30] [1050/1319] eta: 0:11:45 lr: 1.3324788257253885e-05 loss: 0.0314 (0.0383) time: 2.6046 data: 0.0059 max mem: 33369 +Epoch: [30] [1060/1319] eta: 0:11:19 lr: 1.3314908692595609e-05 loss: 0.0341 (0.0383) time: 2.5926 data: 0.0060 max mem: 33369 +Epoch: [30] [1070/1319] eta: 0:10:53 lr: 1.3305028313362919e-05 loss: 0.0355 (0.0383) time: 2.5977 data: 0.0060 max mem: 33369 +Epoch: [30] [1080/1319] eta: 0:10:26 lr: 1.3295147118816423e-05 loss: 0.0359 (0.0383) time: 2.6022 data: 0.0058 max mem: 33369 +Epoch: [30] [1090/1319] eta: 0:10:00 lr: 1.328526510821544e-05 loss: 0.0320 (0.0383) time: 2.6290 data: 0.0058 max mem: 33369 +Epoch: [30] [1100/1319] eta: 0:09:34 lr: 1.3275382280818008e-05 loss: 0.0338 (0.0383) time: 2.6157 data: 0.0059 max mem: 33369 +Epoch: [30] [1110/1319] eta: 0:09:08 lr: 1.3265498635880886e-05 loss: 0.0357 (0.0383) time: 2.6185 data: 0.0059 max mem: 33369 +Epoch: [30] [1120/1319] eta: 0:08:42 lr: 1.325561417265953e-05 loss: 0.0340 (0.0383) time: 2.6591 data: 0.0058 max mem: 33369 +Epoch: [30] [1130/1319] eta: 0:08:15 lr: 1.3245728890408104e-05 loss: 0.0340 (0.0383) time: 2.6330 data: 0.0057 max mem: 33369 +Epoch: [30] [1140/1319] eta: 0:07:49 lr: 1.3235842788379476e-05 loss: 0.0337 (0.0382) time: 2.6191 data: 0.0058 max mem: 33369 +Epoch: [30] [1150/1319] eta: 0:07:23 lr: 1.3225955865825202e-05 loss: 0.0337 (0.0382) time: 2.6289 data: 0.0058 max mem: 33369 +Epoch: [30] [1160/1319] eta: 0:06:57 lr: 1.321606812199554e-05 loss: 0.0383 (0.0382) time: 2.5982 data: 0.0058 max mem: 33369 +Epoch: [30] [1170/1319] eta: 0:06:30 lr: 1.320617955613944e-05 loss: 0.0359 (0.0382) time: 2.5933 data: 0.0059 max mem: 33369 +Epoch: [30] [1180/1319] eta: 0:06:04 lr: 1.3196290167504535e-05 loss: 0.0348 (0.0382) time: 2.6070 data: 0.0059 max mem: 33369 +Epoch: [30] [1190/1319] eta: 0:05:38 lr: 1.3186399955337153e-05 loss: 0.0336 (0.0381) time: 2.6151 data: 0.0058 max mem: 33369 +Epoch: [30] [1200/1319] eta: 0:05:12 lr: 1.3176508918882283e-05 loss: 0.0328 (0.0381) time: 2.6057 data: 0.0059 max mem: 33369 +Epoch: [30] [1210/1319] eta: 0:04:45 lr: 1.3166617057383607e-05 loss: 0.0339 (0.0381) time: 2.5969 data: 0.0059 max mem: 33369 +Epoch: [30] [1220/1319] eta: 0:04:19 lr: 1.3156724370083478e-05 loss: 0.0351 (0.0381) time: 2.5928 data: 0.0058 max mem: 33369 +Epoch: [30] [1230/1319] eta: 0:03:53 lr: 1.3146830856222919e-05 loss: 0.0351 (0.0381) time: 2.6227 data: 0.0060 max mem: 33369 +Epoch: [30] [1240/1319] eta: 0:03:27 lr: 1.3136936515041629e-05 loss: 0.0317 (0.0381) time: 2.6549 data: 0.0060 max mem: 33369 +Epoch: [30] [1250/1319] eta: 0:03:00 lr: 1.3127041345777947e-05 loss: 0.0359 (0.0381) time: 2.6375 data: 0.0059 max mem: 33369 +Epoch: [30] [1260/1319] eta: 0:02:34 lr: 1.3117145347668891e-05 loss: 0.0346 (0.0380) time: 2.6278 data: 0.0059 max mem: 33369 +Epoch: [30] [1270/1319] eta: 0:02:08 lr: 1.3107248519950133e-05 loss: 0.0340 (0.0381) time: 2.6129 data: 0.0059 max mem: 33369 +Epoch: [30] [1280/1319] eta: 0:01:42 lr: 1.3097350861856001e-05 loss: 0.0346 (0.0381) time: 2.6089 data: 0.0058 max mem: 33369 +Epoch: [30] [1290/1319] eta: 0:01:16 lr: 1.3087452372619463e-05 loss: 0.0284 (0.0380) time: 2.6162 data: 0.0058 max mem: 33369 +Epoch: [30] [1300/1319] eta: 0:00:49 lr: 1.3077553051472149e-05 loss: 0.0355 (0.0380) time: 2.6072 data: 0.0059 max mem: 33369 +Epoch: [30] [1310/1319] eta: 0:00:23 lr: 1.3067652897644308e-05 loss: 0.0370 (0.0380) time: 2.5982 data: 0.0060 max mem: 33369 +Epoch: [30] Total time: 0:57:39 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 2:04:34 time: 2.9050 data: 2.8268 max mem: 33369 +Test: [ 100/2573] eta: 0:04:06 time: 0.0715 data: 0.0011 max mem: 33369 +Test: [ 200/2573] eta: 0:03:26 time: 0.0728 data: 0.0011 max mem: 33369 +Test: [ 300/2573] eta: 0:03:05 time: 0.0745 data: 0.0011 max mem: 33369 +Test: [ 400/2573] eta: 0:02:52 time: 0.0748 data: 0.0011 max mem: 33369 +Test: [ 500/2573] eta: 0:02:42 time: 0.0733 data: 0.0011 max mem: 33369 +Test: [ 600/2573] eta: 0:02:33 time: 0.0733 data: 0.0011 max mem: 33369 +Test: [ 700/2573] eta: 0:02:24 time: 0.0734 data: 0.0011 max mem: 33369 +Test: [ 800/2573] eta: 0:02:16 time: 0.0767 data: 0.0011 max mem: 33369 +Test: [ 900/2573] eta: 0:02:08 time: 0.0733 data: 0.0011 max mem: 33369 +Test: [1000/2573] eta: 0:02:00 time: 0.0733 data: 0.0011 max mem: 33369 +Test: [1100/2573] eta: 0:01:52 time: 0.0734 data: 0.0011 max mem: 33369 +Test: [1200/2573] eta: 0:01:44 time: 0.0735 data: 0.0011 max mem: 33369 +Test: [1300/2573] eta: 0:01:36 time: 0.0735 data: 0.0011 max mem: 33369 +Test: [1400/2573] eta: 0:01:28 time: 0.0720 data: 0.0011 max mem: 33369 +Test: [1500/2573] eta: 0:01:20 time: 0.0736 data: 0.0011 max mem: 33369 +Test: [1600/2573] eta: 0:01:13 time: 0.0770 data: 0.0011 max mem: 33369 +Test: [1700/2573] eta: 0:01:05 time: 0.0722 data: 0.0011 max mem: 33369 +Test: [1800/2573] eta: 0:00:58 time: 0.0754 data: 0.0011 max mem: 33369 +Test: [1900/2573] eta: 0:00:50 time: 0.0721 data: 0.0011 max mem: 33369 +Test: [2000/2573] eta: 0:00:42 time: 0.0737 data: 0.0011 max mem: 33369 +Test: [2100/2573] eta: 0:00:35 time: 0.0753 data: 0.0011 max mem: 33369 +Test: [2200/2573] eta: 0:00:27 time: 0.0753 data: 0.0011 max mem: 33369 +Test: [2300/2573] eta: 0:00:20 time: 0.0755 data: 0.0011 max mem: 33369 +Test: [2400/2573] eta: 0:00:12 time: 0.0705 data: 0.0011 max mem: 33369 +Test: [2500/2573] eta: 0:00:05 time: 0.0737 data: 0.0011 max mem: 33369 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: Total time: 0:03:12 +Final results: +Mean IoU is 64.89 + + precision@0.5 = 73.14 + precision@0.6 = 67.73 + precision@0.7 = 60.80 + precision@0.8 = 49.96 + precision@0.9 = 25.45 + overall IoU = 61.77 + +Average object IoU 64.89029699310021 +Overall IoU 61.76689147949219 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [31] [ 0/1319] eta: 2:58:38 lr: 1.3058742046620123e-05 loss: 0.0334 (0.0334) time: 8.1263 data: 1.2661 max mem: 33369 +Epoch: [31] [ 10/1319] eta: 1:08:59 lr: 1.3048840308573793e-05 loss: 0.0358 (0.0359) time: 3.1626 data: 0.1209 max mem: 33369 +Epoch: [31] [ 20/1319] eta: 1:03:02 lr: 1.3038937735606992e-05 loss: 0.0300 (0.0335) time: 2.6514 data: 0.0060 max mem: 33369 +Epoch: [31] [ 30/1319] eta: 1:00:31 lr: 1.3029034326944665e-05 loss: 0.0300 (0.0339) time: 2.6279 data: 0.0060 max mem: 33369 +Epoch: [31] [ 40/1319] eta: 0:59:04 lr: 1.3019130081810363e-05 loss: 0.0326 (0.0357) time: 2.6232 data: 0.0063 max mem: 33369 +Epoch: [31] [ 50/1319] eta: 0:58:08 lr: 1.3009224999426282e-05 loss: 0.0304 (0.0356) time: 2.6418 data: 0.0062 max mem: 33369 +Epoch: [31] [ 60/1319] eta: 0:57:16 lr: 1.2999319079013207e-05 loss: 0.0308 (0.0357) time: 2.6434 data: 0.0061 max mem: 33369 +Epoch: [31] [ 70/1319] eta: 0:56:22 lr: 1.298941231979056e-05 loss: 0.0315 (0.0354) time: 2.6044 data: 0.0061 max mem: 33369 +Epoch: [31] [ 80/1319] eta: 0:55:43 lr: 1.2979504720976363e-05 loss: 0.0308 (0.0356) time: 2.6035 data: 0.0061 max mem: 33369 +Epoch: [31] [ 90/1319] eta: 0:55:14 lr: 1.2969596281787253e-05 loss: 0.0313 (0.0361) time: 2.6572 data: 0.0061 max mem: 33369 +Epoch: [31] [ 100/1319] eta: 0:54:42 lr: 1.2959687001438464e-05 loss: 0.0359 (0.0367) time: 2.6706 data: 0.0062 max mem: 33369 +Epoch: [31] [ 110/1319] eta: 0:54:07 lr: 1.2949776879143838e-05 loss: 0.0370 (0.0368) time: 2.6386 data: 0.0062 max mem: 33369 +Epoch: [31] [ 120/1319] eta: 0:53:28 lr: 1.2939865914115796e-05 loss: 0.0313 (0.0368) time: 2.5924 data: 0.0060 max mem: 33369 +Epoch: [31] [ 130/1319] eta: 0:52:54 lr: 1.2929954105565368e-05 loss: 0.0342 (0.0368) time: 2.5772 data: 0.0060 max mem: 33369 +Epoch: [31] [ 140/1319] eta: 0:52:25 lr: 1.2920041452702167e-05 loss: 0.0336 (0.0368) time: 2.6181 data: 0.0060 max mem: 33369 +Epoch: [31] [ 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mem: 33369 +Epoch: [31] [ 230/1319] eta: 0:48:05 lr: 1.2830789451741262e-05 loss: 0.0314 (0.0363) time: 2.6057 data: 0.0061 max mem: 33369 +Epoch: [31] [ 240/1319] eta: 0:47:37 lr: 1.2820868311965862e-05 loss: 0.0314 (0.0362) time: 2.6040 data: 0.0059 max mem: 33369 +Epoch: [31] [ 250/1319] eta: 0:47:07 lr: 1.2810946319089204e-05 loss: 0.0320 (0.0361) time: 2.5888 data: 0.0061 max mem: 33369 +Epoch: [31] [ 260/1319] eta: 0:46:39 lr: 1.2801023472303672e-05 loss: 0.0348 (0.0363) time: 2.5880 data: 0.0062 max mem: 33369 +Epoch: [31] [ 270/1319] eta: 0:46:09 lr: 1.2791099770800195e-05 loss: 0.0386 (0.0366) time: 2.5849 data: 0.0060 max mem: 33369 +Epoch: [31] [ 280/1319] eta: 0:45:42 lr: 1.2781175213768214e-05 loss: 0.0390 (0.0369) time: 2.5890 data: 0.0061 max mem: 33369 +Epoch: [31] [ 290/1319] eta: 0:45:15 lr: 1.277124980039573e-05 loss: 0.0340 (0.0369) time: 2.6152 data: 0.0060 max mem: 33369 +Epoch: [31] [ 300/1319] eta: 0:44:47 lr: 1.2761323529869248e-05 loss: 0.0349 (0.0371) time: 2.5994 data: 0.0058 max mem: 33369 +Epoch: [31] [ 310/1319] eta: 0:44:20 lr: 1.2751396401373813e-05 loss: 0.0432 (0.0376) time: 2.6075 data: 0.0058 max mem: 33369 +Epoch: [31] [ 320/1319] eta: 0:43:54 lr: 1.2741468414092989e-05 loss: 0.0358 (0.0377) time: 2.6377 data: 0.0058 max mem: 33369 +Epoch: [31] [ 330/1319] eta: 0:43:28 lr: 1.2731539567208833e-05 loss: 0.0359 (0.0378) time: 2.6483 data: 0.0059 max mem: 33369 +Epoch: [31] [ 340/1319] eta: 0:43:01 lr: 1.2721609859901942e-05 loss: 0.0350 (0.0379) time: 2.6331 data: 0.0058 max mem: 33369 +Epoch: [31] [ 350/1319] eta: 0:42:33 lr: 1.2711679291351405e-05 loss: 0.0376 (0.0380) time: 2.6058 data: 0.0057 max mem: 33369 +Epoch: [31] [ 360/1319] eta: 0:42:08 lr: 1.2701747860734819e-05 loss: 0.0415 (0.0380) time: 2.6241 data: 0.0059 max mem: 33369 +Epoch: [31] [ 370/1319] eta: 0:41:39 lr: 1.2691815567228285e-05 loss: 0.0346 (0.0379) time: 2.6010 data: 0.0060 max mem: 33369 +Epoch: [31] [ 380/1319] eta: 0:41:13 lr: 1.2681882410006382e-05 loss: 0.0345 (0.0385) time: 2.6012 data: 0.0060 max mem: 33369 +Epoch: [31] [ 390/1319] eta: 0:40:46 lr: 1.26719483882422e-05 loss: 0.0444 (0.0389) time: 2.6270 data: 0.0060 max mem: 33369 +Epoch: [31] [ 400/1319] eta: 0:40:20 lr: 1.2662013501107303e-05 loss: 0.0345 (0.0388) time: 2.6285 data: 0.0059 max mem: 33369 +Epoch: [31] [ 410/1319] eta: 0:39:54 lr: 1.265207774777175e-05 loss: 0.0306 (0.0388) time: 2.6389 data: 0.0058 max mem: 33369 +Epoch: [31] [ 420/1319] eta: 0:39:27 lr: 1.2642141127404073e-05 loss: 0.0312 (0.0387) time: 2.6304 data: 0.0060 max mem: 33369 +Epoch: [31] [ 430/1319] eta: 0:39:01 lr: 1.2632203639171281e-05 loss: 0.0320 (0.0387) time: 2.6397 data: 0.0060 max mem: 33369 +Epoch: [31] [ 440/1319] eta: 0:38:35 lr: 1.2622265282238837e-05 loss: 0.0377 (0.0388) time: 2.6473 data: 0.0059 max mem: 33369 +Epoch: [31] [ 450/1319] eta: 0:38:09 lr: 1.2612326055770701e-05 loss: 0.0394 (0.0388) time: 2.6591 data: 0.0060 max mem: 33369 +Epoch: [31] [ 460/1319] eta: 0:37:43 lr: 1.2602385958929271e-05 loss: 0.0359 (0.0390) time: 2.6424 data: 0.0059 max mem: 33369 +Epoch: [31] [ 470/1319] eta: 0:37:16 lr: 1.2592444990875415e-05 loss: 0.0402 (0.0391) time: 2.6147 data: 0.0058 max mem: 33369 +Epoch: [31] [ 480/1319] eta: 0:36:49 lr: 1.258250315076846e-05 loss: 0.0398 (0.0390) time: 2.5977 data: 0.0060 max mem: 33369 +Epoch: [31] [ 490/1319] eta: 0:36:23 lr: 1.2572560437766163e-05 loss: 0.0319 (0.0389) time: 2.6308 data: 0.0060 max mem: 33369 +Epoch: [31] [ 500/1319] eta: 0:35:56 lr: 1.2562616851024742e-05 loss: 0.0330 (0.0388) time: 2.6421 data: 0.0060 max mem: 33369 +Epoch: [31] [ 510/1319] eta: 0:35:30 lr: 1.2552672389698855e-05 loss: 0.0342 (0.0388) time: 2.6180 data: 0.0061 max mem: 33369 +Epoch: [31] [ 520/1319] eta: 0:35:03 lr: 1.2542727052941597e-05 loss: 0.0332 (0.0387) time: 2.6109 data: 0.0060 max mem: 33369 +Epoch: [31] [ 530/1319] eta: 0:34:36 lr: 1.2532780839904498e-05 loss: 0.0332 (0.0387) time: 2.5939 data: 0.0060 max mem: 33369 +Epoch: [31] [ 540/1319] eta: 0:34:10 lr: 1.2522833749737507e-05 loss: 0.0351 (0.0387) time: 2.6234 data: 0.0060 max mem: 33369 +Epoch: [31] [ 550/1319] eta: 0:33:44 lr: 1.2512885781589004e-05 loss: 0.0303 (0.0385) time: 2.6452 data: 0.0060 max mem: 33369 +Epoch: [31] [ 560/1319] eta: 0:33:17 lr: 1.2502936934605792e-05 loss: 0.0327 (0.0386) time: 2.6292 data: 0.0060 max mem: 33369 +Epoch: [31] [ 570/1319] eta: 0:32:52 lr: 1.2492987207933083e-05 loss: 0.0325 (0.0384) time: 2.6452 data: 0.0060 max mem: 33369 +Epoch: [31] [ 580/1319] eta: 0:32:25 lr: 1.2483036600714508e-05 loss: 0.0292 (0.0383) time: 2.6391 data: 0.0061 max mem: 33369 +Epoch: [31] [ 590/1319] eta: 0:31:59 lr: 1.2473085112092107e-05 loss: 0.0339 (0.0384) time: 2.6192 data: 0.0062 max mem: 33369 +Epoch: [31] [ 600/1319] eta: 0:31:32 lr: 1.24631327412063e-05 loss: 0.0354 (0.0384) time: 2.6325 data: 0.0061 max mem: 33369 +Epoch: [31] [ 610/1319] eta: 0:31:06 lr: 1.2453179487195933e-05 loss: 0.0332 (0.0383) time: 2.6203 data: 0.0060 max mem: 33369 +Epoch: [31] [ 620/1319] eta: 0:30:39 lr: 1.2443225349198233e-05 loss: 0.0348 (0.0384) time: 2.5913 data: 0.0059 max mem: 33369 +Epoch: [31] [ 630/1319] eta: 0:30:12 lr: 1.2433270326348818e-05 loss: 0.0343 (0.0383) time: 2.6046 data: 0.0059 max mem: 33369 +Epoch: [31] [ 640/1319] eta: 0:29:46 lr: 1.2423314417781696e-05 loss: 0.0335 (0.0383) time: 2.6220 data: 0.0061 max mem: 33369 +Epoch: [31] [ 650/1319] eta: 0:29:20 lr: 1.2413357622629242e-05 loss: 0.0348 (0.0383) time: 2.6272 data: 0.0060 max mem: 33369 +Epoch: [31] [ 660/1319] eta: 0:28:53 lr: 1.240339994002222e-05 loss: 0.0348 (0.0383) time: 2.6372 data: 0.0059 max mem: 33369 +Epoch: [31] [ 670/1319] eta: 0:28:27 lr: 1.2393441369089758e-05 loss: 0.0363 (0.0383) time: 2.6092 data: 0.0059 max mem: 33369 +Epoch: [31] [ 680/1319] eta: 0:28:00 lr: 1.2383481908959357e-05 loss: 0.0377 (0.0383) time: 2.5994 data: 0.0059 max mem: 33369 +Epoch: [31] [ 690/1319] eta: 0:27:34 lr: 1.237352155875688e-05 loss: 0.0366 (0.0383) time: 2.6252 data: 0.0060 max mem: 33369 +Epoch: [31] [ 700/1319] eta: 0:27:08 lr: 1.236356031760655e-05 loss: 0.0370 (0.0386) time: 2.6316 data: 0.0061 max mem: 33369 +Epoch: [31] [ 710/1319] eta: 0:26:41 lr: 1.2353598184630927e-05 loss: 0.0364 (0.0385) time: 2.6256 data: 0.0060 max mem: 33369 +Epoch: [31] [ 720/1319] eta: 0:26:15 lr: 1.2343635158950937e-05 loss: 0.0356 (0.0386) time: 2.6186 data: 0.0059 max mem: 33369 +Epoch: [31] [ 730/1319] eta: 0:25:49 lr: 1.2333671239685849e-05 loss: 0.0356 (0.0385) time: 2.6340 data: 0.0059 max mem: 33369 +Epoch: [31] [ 740/1319] eta: 0:25:22 lr: 1.2323706425953264e-05 loss: 0.0327 (0.0385) time: 2.6490 data: 0.0060 max mem: 33369 +Epoch: [31] [ 750/1319] eta: 0:24:56 lr: 1.2313740716869131e-05 loss: 0.0338 (0.0384) time: 2.6369 data: 0.0059 max mem: 33369 +Epoch: [31] [ 760/1319] eta: 0:24:30 lr: 1.2303774111547706e-05 loss: 0.0335 (0.0384) time: 2.6493 data: 0.0060 max mem: 33369 +Epoch: [31] [ 770/1319] eta: 0:24:04 lr: 1.2293806609101593e-05 loss: 0.0367 (0.0384) time: 2.6471 data: 0.0060 max mem: 33369 +Epoch: [31] [ 780/1319] eta: 0:23:38 lr: 1.2283838208641708e-05 loss: 0.0384 (0.0384) time: 2.6289 data: 0.0059 max mem: 33369 +Epoch: [31] [ 790/1319] eta: 0:23:11 lr: 1.2273868909277286e-05 loss: 0.0424 (0.0384) time: 2.6301 data: 0.0060 max mem: 33369 +Epoch: [31] [ 800/1319] eta: 0:22:44 lr: 1.2263898710115878e-05 loss: 0.0377 (0.0386) time: 2.5911 data: 0.0061 max mem: 33369 +Epoch: [31] [ 810/1319] eta: 0:22:18 lr: 1.2253927610263324e-05 loss: 0.0369 (0.0386) time: 2.6049 data: 0.0059 max mem: 33369 +Epoch: [31] [ 820/1319] eta: 0:21:52 lr: 1.2243955608823781e-05 loss: 0.0377 (0.0386) time: 2.6290 data: 0.0058 max mem: 33369 +Epoch: [31] [ 830/1319] eta: 0:21:25 lr: 1.2233982704899707e-05 loss: 0.0330 (0.0386) time: 2.6023 data: 0.0060 max mem: 33369 +Epoch: [31] [ 840/1319] eta: 0:20:59 lr: 1.2224008897591841e-05 loss: 0.0335 (0.0386) time: 2.6094 data: 0.0060 max mem: 33369 +Epoch: [31] [ 850/1319] eta: 0:20:33 lr: 1.2214034185999218e-05 loss: 0.0310 (0.0385) time: 2.6152 data: 0.0057 max mem: 33369 +Epoch: [31] [ 860/1319] eta: 0:20:06 lr: 1.2204058569219158e-05 loss: 0.0316 (0.0385) time: 2.6160 data: 0.0060 max mem: 33369 +Epoch: [31] [ 870/1319] eta: 0:19:40 lr: 1.2194082046347242e-05 loss: 0.0362 (0.0385) time: 2.6253 data: 0.0063 max mem: 33369 +Epoch: [31] [ 880/1319] eta: 0:19:14 lr: 1.2184104616477345e-05 loss: 0.0358 (0.0385) time: 2.6184 data: 0.0060 max mem: 33369 +Epoch: [31] [ 890/1319] eta: 0:18:47 lr: 1.2174126278701602e-05 loss: 0.0348 (0.0385) time: 2.6304 data: 0.0059 max mem: 33369 +Epoch: [31] [ 900/1319] eta: 0:18:21 lr: 1.2164147032110409e-05 loss: 0.0378 (0.0386) time: 2.6433 data: 0.0061 max mem: 33369 +Epoch: [31] [ 910/1319] eta: 0:17:55 lr: 1.215416687579243e-05 loss: 0.0365 (0.0385) time: 2.6237 data: 0.0060 max mem: 33369 +Epoch: [31] [ 920/1319] eta: 0:17:28 lr: 1.2144185808834565e-05 loss: 0.0353 (0.0385) time: 2.6223 data: 0.0059 max mem: 33369 +Epoch: [31] [ 930/1319] eta: 0:17:02 lr: 1.213420383032198e-05 loss: 0.0347 (0.0384) time: 2.6134 data: 0.0059 max mem: 33369 +Epoch: [31] [ 940/1319] eta: 0:16:36 lr: 1.212422093933808e-05 loss: 0.0312 (0.0385) time: 2.6235 data: 0.0059 max mem: 33369 +Epoch: [31] [ 950/1319] eta: 0:16:10 lr: 1.2114237134964505e-05 loss: 0.0302 (0.0386) time: 2.6397 data: 0.0059 max mem: 33369 +Epoch: [31] [ 960/1319] eta: 0:15:43 lr: 1.210425241628114e-05 loss: 0.0324 (0.0387) time: 2.6005 data: 0.0059 max mem: 33369 +Epoch: [31] [ 970/1319] eta: 0:15:17 lr: 1.2094266782366075e-05 loss: 0.0399 (0.0387) time: 2.5789 data: 0.0059 max mem: 33369 +Epoch: [31] [ 980/1319] eta: 0:14:50 lr: 1.208428023229565e-05 loss: 0.0340 (0.0386) time: 2.6034 data: 0.0061 max mem: 33369 +Epoch: [31] [ 990/1319] eta: 0:14:24 lr: 1.2074292765144408e-05 loss: 0.0296 (0.0386) time: 2.6217 data: 0.0060 max mem: 33369 +Epoch: [31] [1000/1319] eta: 0:13:58 lr: 1.2064304379985111e-05 loss: 0.0328 (0.0386) time: 2.6184 data: 0.0059 max mem: 33369 +Epoch: [31] [1010/1319] eta: 0:13:32 lr: 1.2054315075888731e-05 loss: 0.0380 (0.0386) time: 2.6353 data: 0.0058 max mem: 33369 +Epoch: [31] [1020/1319] eta: 0:13:05 lr: 1.2044324851924447e-05 loss: 0.0362 (0.0385) time: 2.6557 data: 0.0059 max mem: 33369 +Epoch: [31] [1030/1319] eta: 0:12:39 lr: 1.2034333707159618e-05 loss: 0.0362 (0.0386) time: 2.6468 data: 0.0059 max mem: 33369 +Epoch: [31] [1040/1319] eta: 0:12:13 lr: 1.2024341640659817e-05 loss: 0.0401 (0.0386) time: 2.6312 data: 0.0059 max mem: 33369 +Epoch: [31] [1050/1319] eta: 0:11:47 lr: 1.2014348651488794e-05 loss: 0.0335 (0.0385) time: 2.6379 data: 0.0058 max mem: 33369 +Epoch: [31] [1060/1319] eta: 0:11:20 lr: 1.2004354738708488e-05 loss: 0.0317 (0.0385) time: 2.6410 data: 0.0058 max mem: 33369 +Epoch: [31] [1070/1319] eta: 0:10:54 lr: 1.1994359901379014e-05 loss: 0.0360 (0.0385) time: 2.6314 data: 0.0058 max mem: 33369 +Epoch: [31] [1080/1319] eta: 0:10:28 lr: 1.1984364138558649e-05 loss: 0.0339 (0.0385) time: 2.6312 data: 0.0058 max mem: 33369 +Epoch: [31] [1090/1319] eta: 0:10:01 lr: 1.1974367449303851e-05 loss: 0.0363 (0.0385) time: 2.6163 data: 0.0058 max mem: 33369 +Epoch: [31] [1100/1319] eta: 0:09:35 lr: 1.1964369832669236e-05 loss: 0.0363 (0.0386) time: 2.6383 data: 0.0059 max mem: 33369 +Epoch: [31] [1110/1319] eta: 0:09:09 lr: 1.195437128770757e-05 loss: 0.0320 (0.0385) time: 2.6380 data: 0.0059 max mem: 33369 +Epoch: [31] [1120/1319] eta: 0:08:43 lr: 1.194437181346979e-05 loss: 0.0304 (0.0385) time: 2.6084 data: 0.0058 max mem: 33369 +Epoch: [31] [1130/1319] eta: 0:08:16 lr: 1.1934371409004944e-05 loss: 0.0304 (0.0385) time: 2.6234 data: 0.0058 max mem: 33369 +Epoch: [31] [1140/1319] eta: 0:07:50 lr: 1.192437007336025e-05 loss: 0.0350 (0.0384) time: 2.6229 data: 0.0058 max mem: 33369 +Epoch: [31] [1150/1319] eta: 0:07:24 lr: 1.1914367805581053e-05 loss: 0.0336 (0.0384) time: 2.6169 data: 0.0057 max mem: 33369 +Epoch: [31] [1160/1319] eta: 0:06:57 lr: 1.1904364604710826e-05 loss: 0.0336 (0.0384) time: 2.6049 data: 0.0057 max mem: 33369 +Epoch: [31] [1170/1319] eta: 0:06:31 lr: 1.1894360469791169e-05 loss: 0.0335 (0.0383) time: 2.6114 data: 0.0059 max mem: 33369 +Epoch: [31] [1180/1319] eta: 0:06:05 lr: 1.1884355399861802e-05 loss: 0.0332 (0.0383) time: 2.6606 data: 0.0059 max mem: 33369 +Epoch: [31] [1190/1319] eta: 0:05:39 lr: 1.1874349393960545e-05 loss: 0.0356 (0.0384) time: 2.6466 data: 0.0059 max mem: 33369 +Epoch: [31] [1200/1319] eta: 0:05:12 lr: 1.1864342451123342e-05 loss: 0.0365 (0.0384) time: 2.6214 data: 0.0059 max mem: 33369 +Epoch: [31] [1210/1319] eta: 0:04:46 lr: 1.1854334570384235e-05 loss: 0.0323 (0.0383) time: 2.6136 data: 0.0058 max mem: 33369 +Epoch: [31] [1220/1319] eta: 0:04:20 lr: 1.1844325750775364e-05 loss: 0.0312 (0.0383) time: 2.5948 data: 0.0059 max mem: 33369 +Epoch: [31] [1230/1319] eta: 0:03:53 lr: 1.183431599132696e-05 loss: 0.0348 (0.0383) time: 2.6024 data: 0.0059 max mem: 33369 +Epoch: [31] [1240/1319] eta: 0:03:27 lr: 1.1824305291067328e-05 loss: 0.0350 (0.0383) time: 2.6450 data: 0.0060 max mem: 33369 +Epoch: [31] [1250/1319] eta: 0:03:01 lr: 1.1814293649022872e-05 loss: 0.0341 (0.0383) time: 2.6571 data: 0.0059 max mem: 33369 +Epoch: [31] [1260/1319] eta: 0:02:35 lr: 1.180428106421806e-05 loss: 0.0302 (0.0382) time: 2.6526 data: 0.0058 max mem: 33369 +Epoch: [31] [1270/1319] eta: 0:02:08 lr: 1.1794267535675433e-05 loss: 0.0333 (0.0383) time: 2.6359 data: 0.0059 max mem: 33369 +Epoch: [31] [1280/1319] eta: 0:01:42 lr: 1.1784253062415594e-05 loss: 0.0345 (0.0383) time: 2.6085 data: 0.0060 max mem: 33369 +Epoch: [31] [1290/1319] eta: 0:01:16 lr: 1.1774237643457209e-05 loss: 0.0355 (0.0383) time: 2.6359 data: 0.0059 max mem: 33369 +Epoch: [31] [1300/1319] eta: 0:00:49 lr: 1.1764221277816978e-05 loss: 0.0401 (0.0384) time: 2.6216 data: 0.0060 max mem: 33369 +Epoch: [31] [1310/1319] eta: 0:00:23 lr: 1.1754203964509668e-05 loss: 0.0382 (0.0385) time: 2.6399 data: 0.0061 max mem: 33369 +Epoch: [31] Total time: 0:57:47 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 2:14:04 time: 3.1266 data: 3.0479 max mem: 33369 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 100/2573] eta: 0:04:12 time: 0.0717 data: 0.0011 max mem: 33369 +Test: [ 200/2573] eta: 0:03:28 time: 0.0728 data: 0.0011 max mem: 33369 +Test: [ 300/2573] eta: 0:03:07 time: 0.0745 data: 0.0011 max mem: 33369 +Test: [ 400/2573] eta: 0:02:54 time: 0.0748 data: 0.0011 max mem: 33369 +Test: [ 500/2573] eta: 0:02:43 time: 0.0732 data: 0.0011 max mem: 33369 +Test: [ 600/2573] eta: 0:02:33 time: 0.0731 data: 0.0011 max mem: 33369 +Test: [ 700/2573] eta: 0:02:25 time: 0.0733 data: 0.0011 max mem: 33369 +Test: [ 800/2573] eta: 0:02:16 time: 0.0767 data: 0.0011 max mem: 33369 +Test: [ 900/2573] eta: 0:02:08 time: 0.0733 data: 0.0011 max mem: 33369 +Test: [1000/2573] eta: 0:02:00 time: 0.0734 data: 0.0011 max mem: 33369 +Test: [1100/2573] eta: 0:01:52 time: 0.0735 data: 0.0011 max mem: 33369 +Test: [1200/2573] eta: 0:01:44 time: 0.0735 data: 0.0012 max mem: 33369 +Test: [1300/2573] eta: 0:01:36 time: 0.0733 data: 0.0010 max mem: 33369 +Test: [1400/2573] eta: 0:01:28 time: 0.0720 data: 0.0011 max mem: 33369 +Test: [1500/2573] eta: 0:01:21 time: 0.0735 data: 0.0011 max mem: 33369 +Test: [1600/2573] eta: 0:01:13 time: 0.0769 data: 0.0012 max mem: 33369 +Test: [1700/2573] eta: 0:01:05 time: 0.0720 data: 0.0011 max mem: 33369 +Test: [1800/2573] eta: 0:00:58 time: 0.0753 data: 0.0011 max mem: 33369 +Test: [1900/2573] eta: 0:00:50 time: 0.0720 data: 0.0011 max mem: 33369 +Test: [2000/2573] eta: 0:00:42 time: 0.0737 data: 0.0011 max mem: 33369 +Test: [2100/2573] eta: 0:00:35 time: 0.0754 data: 0.0011 max mem: 33369 +Test: [2200/2573] eta: 0:00:27 time: 0.0754 data: 0.0011 max mem: 33369 +Test: [2300/2573] eta: 0:00:20 time: 0.0754 data: 0.0011 max mem: 33369 +Test: [2400/2573] eta: 0:00:12 time: 0.0704 data: 0.0011 max mem: 33369 +Test: [2500/2573] eta: 0:00:05 time: 0.0738 data: 0.0011 max mem: 33369 +Test: Total time: 0:03:12 +Final results: +Mean IoU is 64.48 + + precision@0.5 = 72.96 + precision@0.6 = 67.54 + precision@0.7 = 60.70 + precision@0.8 = 49.29 + precision@0.9 = 25.27 + overall IoU = 61.47 + +Average object IoU 64.47787564286457 +Overall IoU 61.46657180786133 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [32] [ 0/1319] eta: 3:13:21 lr: 1.1745187571461855e-05 loss: 0.0313 (0.0313) time: 8.7959 data: 1.8392 max mem: 33369 +Epoch: [32] [ 10/1319] eta: 1:09:44 lr: 1.1735168454865734e-05 loss: 0.0296 (0.0310) time: 3.1971 data: 0.1730 max mem: 33369 +Epoch: [32] [ 20/1319] eta: 1:03:25 lr: 1.1725148387734231e-05 loss: 0.0339 (0.0340) time: 2.6364 data: 0.0060 max mem: 33369 +Epoch: [32] [ 30/1319] eta: 1:00:40 lr: 1.1715127369074435e-05 loss: 0.0339 (0.0341) time: 2.6194 data: 0.0059 max mem: 33369 +Epoch: [32] [ 40/1319] eta: 0:59:00 lr: 1.1705105397891451e-05 loss: 0.0293 (0.0334) time: 2.5989 data: 0.0062 max mem: 33369 +Epoch: [32] [ 50/1319] eta: 0:57:50 lr: 1.1695082473188386e-05 loss: 0.0307 (0.0338) time: 2.5963 data: 0.0061 max mem: 33369 +Epoch: [32] [ 60/1319] eta: 0:56:57 lr: 1.1685058593966367e-05 loss: 0.0317 (0.0338) time: 2.6029 data: 0.0064 max mem: 33369 +Epoch: [32] [ 70/1319] eta: 0:56:12 lr: 1.1675033759224512e-05 loss: 0.0297 (0.0329) time: 2.6124 data: 0.0065 max mem: 33369 +Epoch: [32] [ 80/1319] eta: 0:55:30 lr: 1.1665007967959945e-05 loss: 0.0295 (0.0332) time: 2.6072 data: 0.0063 max mem: 33369 +Epoch: [32] [ 90/1319] eta: 0:54:59 lr: 1.1654981219167763e-05 loss: 0.0335 (0.0334) time: 2.6273 data: 0.0061 max mem: 33369 +Epoch: [32] [ 100/1319] eta: 0:54:26 lr: 1.1644953511841062e-05 loss: 0.0335 (0.0335) time: 2.6450 data: 0.0061 max mem: 33369 +Epoch: [32] [ 110/1319] eta: 0:53:51 lr: 1.1634924844970898e-05 loss: 0.0318 (0.0337) time: 2.6221 data: 0.0062 max mem: 33369 +Epoch: [32] [ 120/1319] eta: 0:53:25 lr: 1.1624895217546308e-05 loss: 0.0305 (0.0337) time: 2.6429 data: 0.0062 max mem: 33369 +Epoch: [32] [ 130/1319] eta: 0:52:51 lr: 1.1614864628554293e-05 loss: 0.0315 (0.0340) time: 2.6330 data: 0.0062 max mem: 33369 +Epoch: [32] [ 140/1319] eta: 0:52:17 lr: 1.160483307697981e-05 loss: 0.0317 (0.0342) time: 2.5907 data: 0.0062 max mem: 33369 +Epoch: [32] [ 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data: 0.0061 max mem: 33369 +Epoch: [32] [ 310/1319] eta: 0:44:21 lr: 1.1434148431504575e-05 loss: 0.0312 (0.0343) time: 2.6261 data: 0.0063 max mem: 33369 +Epoch: [32] [ 320/1319] eta: 0:43:52 lr: 1.1424099377509363e-05 loss: 0.0320 (0.0344) time: 2.6114 data: 0.0062 max mem: 33369 +Epoch: [32] [ 330/1319] eta: 0:43:25 lr: 1.141404934124978e-05 loss: 0.0358 (0.0343) time: 2.5936 data: 0.0060 max mem: 33369 +Epoch: [32] [ 340/1319] eta: 0:42:58 lr: 1.140399832166864e-05 loss: 0.0307 (0.0342) time: 2.6002 data: 0.0063 max mem: 33369 +Epoch: [32] [ 350/1319] eta: 0:42:32 lr: 1.1393946317706594e-05 loss: 0.0307 (0.0343) time: 2.6316 data: 0.0062 max mem: 33369 +Epoch: [32] [ 360/1319] eta: 0:42:06 lr: 1.138389332830211e-05 loss: 0.0344 (0.0343) time: 2.6438 data: 0.0058 max mem: 33369 +Epoch: [32] [ 370/1319] eta: 0:41:39 lr: 1.1373839352391454e-05 loss: 0.0331 (0.0343) time: 2.6278 data: 0.0059 max mem: 33369 +Epoch: [32] [ 380/1319] eta: 0:41:13 lr: 1.1363784388908714e-05 loss: 0.0362 (0.0346) time: 2.6330 data: 0.0060 max mem: 33369 +Epoch: [32] [ 390/1319] eta: 0:40:47 lr: 1.1353728436785773e-05 loss: 0.0392 (0.0346) time: 2.6330 data: 0.0059 max mem: 33369 +Epoch: [32] [ 400/1319] eta: 0:40:21 lr: 1.1343671494952302e-05 loss: 0.0354 (0.0348) time: 2.6530 data: 0.0060 max mem: 33369 +Epoch: [32] [ 410/1319] eta: 0:39:55 lr: 1.1333613562335765e-05 loss: 0.0358 (0.0350) time: 2.6573 data: 0.0062 max mem: 33369 +Epoch: [32] [ 420/1319] eta: 0:39:27 lr: 1.1323554637861402e-05 loss: 0.0364 (0.0350) time: 2.6038 data: 0.0061 max mem: 33369 +Epoch: [32] [ 430/1319] eta: 0:39:01 lr: 1.1313494720452216e-05 loss: 0.0305 (0.0350) time: 2.5968 data: 0.0059 max mem: 33369 +Epoch: [32] [ 440/1319] eta: 0:38:34 lr: 1.1303433809028986e-05 loss: 0.0305 (0.0350) time: 2.6346 data: 0.0058 max mem: 33369 +Epoch: [32] [ 450/1319] eta: 0:38:08 lr: 1.1293371902510248e-05 loss: 0.0365 (0.0351) time: 2.6230 data: 0.0059 max mem: 33369 +Epoch: [32] [ 460/1319] eta: 0:37:41 lr: 1.1283308999812288e-05 loss: 0.0365 (0.0351) time: 2.6207 data: 0.0059 max mem: 33369 +Epoch: [32] [ 470/1319] eta: 0:37:15 lr: 1.1273245099849142e-05 loss: 0.0330 (0.0350) time: 2.6268 data: 0.0058 max mem: 33369 +Epoch: [32] [ 480/1319] eta: 0:36:48 lr: 1.1263180201532567e-05 loss: 0.0303 (0.0350) time: 2.6128 data: 0.0062 max mem: 33369 +Epoch: [32] [ 490/1319] eta: 0:36:22 lr: 1.1253114303772065e-05 loss: 0.0303 (0.0351) time: 2.6227 data: 0.0063 max mem: 33369 +Epoch: [32] [ 500/1319] eta: 0:35:55 lr: 1.1243047405474862e-05 loss: 0.0281 (0.0350) time: 2.6349 data: 0.0061 max mem: 33369 +Epoch: [32] [ 510/1319] eta: 0:35:29 lr: 1.1232979505545897e-05 loss: 0.0315 (0.0351) time: 2.6378 data: 0.0060 max mem: 33369 +Epoch: [32] [ 520/1319] eta: 0:35:03 lr: 1.1222910602887823e-05 loss: 0.0356 (0.0351) time: 2.6355 data: 0.0059 max mem: 33369 +Epoch: [32] [ 530/1319] eta: 0:34:37 lr: 1.121284069640098e-05 loss: 0.0347 (0.0352) time: 2.6632 data: 0.0058 max mem: 33369 +Epoch: [32] [ 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mem: 33369 +Epoch: [32] [ 620/1319] eta: 0:30:40 lr: 1.112216618313668e-05 loss: 0.0378 (0.0356) time: 2.6566 data: 0.0060 max mem: 33369 +Epoch: [32] [ 630/1319] eta: 0:30:13 lr: 1.1112086177371001e-05 loss: 0.0378 (0.0356) time: 2.6538 data: 0.0059 max mem: 33369 +Epoch: [32] [ 640/1319] eta: 0:29:47 lr: 1.1102005155526735e-05 loss: 0.0324 (0.0356) time: 2.6231 data: 0.0058 max mem: 33369 +Epoch: [32] [ 650/1319] eta: 0:29:20 lr: 1.109192311647611e-05 loss: 0.0347 (0.0356) time: 2.6072 data: 0.0060 max mem: 33369 +Epoch: [32] [ 660/1319] eta: 0:28:54 lr: 1.1081840059088951e-05 loss: 0.0346 (0.0357) time: 2.6299 data: 0.0062 max mem: 33369 +Epoch: [32] [ 670/1319] eta: 0:28:28 lr: 1.1071755982232689e-05 loss: 0.0388 (0.0358) time: 2.6583 data: 0.0060 max mem: 33369 +Epoch: [32] [ 680/1319] eta: 0:28:02 lr: 1.1061670884772347e-05 loss: 0.0355 (0.0358) time: 2.6412 data: 0.0059 max mem: 33369 +Epoch: [32] [ 690/1319] eta: 0:27:36 lr: 1.1051584765570521e-05 loss: 0.0313 (0.0358) time: 2.6418 data: 0.0059 max mem: 33369 +Epoch: [32] [ 700/1319] eta: 0:27:09 lr: 1.1041497623487401e-05 loss: 0.0340 (0.0357) time: 2.6508 data: 0.0058 max mem: 33369 +Epoch: [32] [ 710/1319] eta: 0:26:43 lr: 1.103140945738074e-05 loss: 0.0355 (0.0357) time: 2.6322 data: 0.0059 max mem: 33369 +Epoch: [32] [ 720/1319] eta: 0:26:17 lr: 1.1021320266105851e-05 loss: 0.0355 (0.0357) time: 2.6355 data: 0.0060 max mem: 33369 +Epoch: [32] [ 730/1319] eta: 0:25:50 lr: 1.101123004851561e-05 loss: 0.0342 (0.0357) time: 2.6409 data: 0.0060 max mem: 33369 +Epoch: [32] [ 740/1319] eta: 0:25:24 lr: 1.1001138803460437e-05 loss: 0.0342 (0.0357) time: 2.6237 data: 0.0059 max mem: 33369 +Epoch: [32] [ 750/1319] eta: 0:24:58 lr: 1.099104652978828e-05 loss: 0.0317 (0.0357) time: 2.6238 data: 0.0058 max mem: 33369 +Epoch: [32] [ 760/1319] eta: 0:24:31 lr: 1.0980953226344629e-05 loss: 0.0317 (0.0356) time: 2.6373 data: 0.0059 max mem: 33369 +Epoch: [32] [ 770/1319] eta: 0:24:05 lr: 1.09708588919725e-05 loss: 0.0315 (0.0356) time: 2.6309 data: 0.0061 max mem: 33369 +Epoch: [32] [ 780/1319] eta: 0:23:39 lr: 1.096076352551242e-05 loss: 0.0307 (0.0356) time: 2.6247 data: 0.0060 max mem: 33369 +Epoch: [32] [ 790/1319] eta: 0:23:12 lr: 1.0950667125802427e-05 loss: 0.0312 (0.0357) time: 2.6298 data: 0.0059 max mem: 33369 +Epoch: [32] [ 800/1319] eta: 0:22:46 lr: 1.0940569691678052e-05 loss: 0.0325 (0.0356) time: 2.6285 data: 0.0058 max mem: 33369 +Epoch: [32] [ 810/1319] eta: 0:22:19 lr: 1.0930471221972321e-05 loss: 0.0305 (0.0357) time: 2.6173 data: 0.0060 max mem: 33369 +Epoch: [32] [ 820/1319] eta: 0:21:53 lr: 1.0920371715515753e-05 loss: 0.0318 (0.0357) time: 2.6354 data: 0.0061 max mem: 33369 +Epoch: [32] [ 830/1319] eta: 0:21:27 lr: 1.0910271171136331e-05 loss: 0.0363 (0.0358) time: 2.6427 data: 0.0059 max mem: 33369 +Epoch: [32] [ 840/1319] eta: 0:21:00 lr: 1.0900169587659515e-05 loss: 0.0386 (0.0358) time: 2.6154 data: 0.0059 max mem: 33369 +Epoch: [32] [ 850/1319] eta: 0:20:34 lr: 1.0890066963908222e-05 loss: 0.0300 (0.0357) time: 2.6104 data: 0.0060 max mem: 33369 +Epoch: [32] [ 860/1319] eta: 0:20:08 lr: 1.087996329870281e-05 loss: 0.0276 (0.0357) time: 2.6431 data: 0.0059 max mem: 33369 +Epoch: [32] [ 870/1319] eta: 0:19:42 lr: 1.0869858590861098e-05 loss: 0.0341 (0.0358) time: 2.6562 data: 0.0058 max mem: 33369 +Epoch: [32] [ 880/1319] eta: 0:19:15 lr: 1.085975283919833e-05 loss: 0.0365 (0.0358) time: 2.6312 data: 0.0059 max mem: 33369 +Epoch: [32] [ 890/1319] eta: 0:18:49 lr: 1.0849646042527184e-05 loss: 0.0346 (0.0358) time: 2.6318 data: 0.0059 max mem: 33369 +Epoch: [32] [ 900/1319] eta: 0:18:23 lr: 1.0839538199657755e-05 loss: 0.0311 (0.0358) time: 2.6359 data: 0.0059 max mem: 33369 +Epoch: [32] [ 910/1319] eta: 0:17:56 lr: 1.0829429309397535e-05 loss: 0.0314 (0.0358) time: 2.6428 data: 0.0059 max mem: 33369 +Epoch: [32] [ 920/1319] eta: 0:17:30 lr: 1.0819319370551438e-05 loss: 0.0344 (0.0358) time: 2.6393 data: 0.0060 max mem: 33369 +Epoch: [32] [ 930/1319] eta: 0:17:04 lr: 1.0809208381921764e-05 loss: 0.0327 (0.0358) time: 2.6190 data: 0.0059 max mem: 33369 +Epoch: [32] [ 940/1319] eta: 0:16:37 lr: 1.0799096342308196e-05 loss: 0.0310 (0.0357) time: 2.6348 data: 0.0058 max mem: 33369 +Epoch: [32] [ 950/1319] eta: 0:16:11 lr: 1.0788983250507807e-05 loss: 0.0288 (0.0357) time: 2.6484 data: 0.0059 max mem: 33369 +Epoch: [32] [ 960/1319] eta: 0:15:45 lr: 1.0778869105315014e-05 loss: 0.0336 (0.0357) time: 2.6284 data: 0.0059 max mem: 33369 +Epoch: [32] [ 970/1319] eta: 0:15:18 lr: 1.0768753905521617e-05 loss: 0.0352 (0.0357) time: 2.6237 data: 0.0058 max mem: 33369 +Epoch: [32] [ 980/1319] eta: 0:14:52 lr: 1.0758637649916756e-05 loss: 0.0345 (0.0358) time: 2.6400 data: 0.0060 max mem: 33369 +Epoch: [32] [ 990/1319] eta: 0:14:27 lr: 1.074852033728692e-05 loss: 0.0384 (0.0358) time: 2.7841 data: 0.0060 max mem: 33369 +Epoch: [32] [1000/1319] eta: 0:14:00 lr: 1.073840196641593e-05 loss: 0.0349 (0.0358) time: 2.7779 data: 0.0059 max mem: 33369 +Epoch: [32] [1010/1319] eta: 0:13:34 lr: 1.0728282536084938e-05 loss: 0.0349 (0.0359) time: 2.6337 data: 0.0060 max mem: 33369 +Epoch: [32] [1020/1319] eta: 0:13:07 lr: 1.0718162045072395e-05 loss: 0.0357 (0.0359) time: 2.6072 data: 0.0060 max mem: 33369 +Epoch: [32] [1030/1319] eta: 0:12:41 lr: 1.0708040492154082e-05 loss: 0.0314 (0.0359) time: 2.6363 data: 0.0060 max mem: 33369 +Epoch: [32] [1040/1319] eta: 0:12:15 lr: 1.069791787610307e-05 loss: 0.0283 (0.0359) time: 2.6445 data: 0.0059 max mem: 33369 +Epoch: [32] [1050/1319] eta: 0:11:49 lr: 1.0687794195689722e-05 loss: 0.0312 (0.0359) time: 2.6890 data: 0.0059 max mem: 33369 +Epoch: [32] [1060/1319] eta: 0:11:22 lr: 1.0677669449681687e-05 loss: 0.0325 (0.0359) time: 2.7095 data: 0.0059 max mem: 33369 +Epoch: [32] [1070/1319] eta: 0:10:56 lr: 1.0667543636843873e-05 loss: 0.0345 (0.0359) time: 2.6341 data: 0.0057 max mem: 33369 +Epoch: [32] [1080/1319] eta: 0:10:30 lr: 1.0657416755938468e-05 loss: 0.0358 (0.0360) time: 2.6326 data: 0.0057 max mem: 33369 +Epoch: [32] [1090/1319] eta: 0:10:03 lr: 1.0647288805724908e-05 loss: 0.0347 (0.0360) time: 2.6539 data: 0.0059 max mem: 33369 +Epoch: [32] [1100/1319] eta: 0:09:37 lr: 1.0637159784959879e-05 loss: 0.0347 (0.0360) time: 2.7810 data: 0.0060 max mem: 33369 +Epoch: [32] [1110/1319] eta: 0:09:11 lr: 1.0627029692397306e-05 loss: 0.0370 (0.0361) time: 2.7598 data: 0.0060 max mem: 33369 +Epoch: [32] [1120/1319] eta: 0:08:45 lr: 1.0616898526788328e-05 loss: 0.0338 (0.0360) time: 2.6353 data: 0.0058 max mem: 33369 +Epoch: [32] [1130/1319] eta: 0:08:18 lr: 1.0606766286881316e-05 loss: 0.0338 (0.0361) time: 2.6253 data: 0.0059 max mem: 33369 +Epoch: [32] [1140/1319] eta: 0:07:52 lr: 1.059663297142185e-05 loss: 0.0361 (0.0362) time: 2.6021 data: 0.0060 max mem: 33369 +Epoch: [32] [1150/1319] eta: 0:07:25 lr: 1.058649857915271e-05 loss: 0.0336 (0.0362) time: 2.5972 data: 0.0058 max mem: 33369 +Epoch: [32] [1160/1319] eta: 0:06:59 lr: 1.0576363108813862e-05 loss: 0.0380 (0.0362) time: 2.6137 data: 0.0059 max mem: 33369 +Epoch: [32] [1170/1319] eta: 0:06:33 lr: 1.0566226559142468e-05 loss: 0.0383 (0.0362) time: 2.6173 data: 0.0059 max mem: 33369 +Epoch: [32] [1180/1319] eta: 0:06:06 lr: 1.0556088928872841e-05 loss: 0.0358 (0.0362) time: 2.6412 data: 0.0058 max mem: 33369 +Epoch: [32] [1190/1319] eta: 0:05:40 lr: 1.0545950216736473e-05 loss: 0.0312 (0.0362) time: 2.6620 data: 0.0058 max mem: 33369 +Epoch: [32] [1200/1319] eta: 0:05:13 lr: 1.0535810421462011e-05 loss: 0.0371 (0.0362) time: 2.6348 data: 0.0059 max mem: 33369 +Epoch: [32] [1210/1319] eta: 0:04:47 lr: 1.0525669541775238e-05 loss: 0.0352 (0.0362) time: 2.6174 data: 0.0059 max mem: 33369 +Epoch: [32] [1220/1319] eta: 0:04:21 lr: 1.0515527576399085e-05 loss: 0.0294 (0.0362) time: 2.6224 data: 0.0058 max mem: 33369 +Epoch: [32] [1230/1319] eta: 0:03:54 lr: 1.050538452405359e-05 loss: 0.0342 (0.0362) time: 2.6345 data: 0.0058 max mem: 33369 +Epoch: [32] [1240/1319] eta: 0:03:28 lr: 1.049524038345592e-05 loss: 0.0346 (0.0362) time: 2.6281 data: 0.0058 max mem: 33369 +Epoch: [32] [1250/1319] eta: 0:03:02 lr: 1.048509515332035e-05 loss: 0.0323 (0.0361) time: 2.6288 data: 0.0058 max mem: 33369 +Epoch: [32] [1260/1319] eta: 0:02:35 lr: 1.0474948832358245e-05 loss: 0.0324 (0.0362) time: 2.6227 data: 0.0059 max mem: 33369 +Epoch: [32] [1270/1319] eta: 0:02:09 lr: 1.0464801419278068e-05 loss: 0.0368 (0.0362) time: 2.6343 data: 0.0060 max mem: 33369 +Epoch: [32] [1280/1319] eta: 0:01:42 lr: 1.0454652912785337e-05 loss: 0.0375 (0.0362) time: 2.6657 data: 0.0058 max mem: 33369 +Epoch: [32] [1290/1319] eta: 0:01:16 lr: 1.0444503311582662e-05 loss: 0.0342 (0.0362) time: 2.6747 data: 0.0058 max mem: 33369 +Epoch: [32] [1300/1319] eta: 0:00:50 lr: 1.0434352614369702e-05 loss: 0.0342 (0.0362) time: 2.6556 data: 0.0059 max mem: 33369 +Epoch: [32] [1310/1319] eta: 0:00:23 lr: 1.0424200819843158e-05 loss: 0.0388 (0.0363) time: 2.6212 data: 0.0058 max mem: 33369 +Epoch: [32] Total time: 0:58:00 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 1:56:04 time: 2.7066 data: 2.6145 max mem: 33369 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 100/2573] eta: 0:04:01 time: 0.0716 data: 0.0011 max mem: 33369 +Test: [ 200/2573] eta: 0:03:24 time: 0.0736 data: 0.0012 max mem: 33369 +Test: [ 300/2573] eta: 0:03:05 time: 0.0748 data: 0.0011 max mem: 33369 +Test: [ 400/2573] eta: 0:02:52 time: 0.0751 data: 0.0011 max mem: 33369 +Test: [ 500/2573] eta: 0:02:42 time: 0.0735 data: 0.0011 max mem: 33369 +Test: [ 600/2573] eta: 0:02:33 time: 0.0738 data: 0.0012 max mem: 33369 +Test: [ 700/2573] eta: 0:02:24 time: 0.0737 data: 0.0011 max mem: 33369 +Test: [ 800/2573] eta: 0:02:16 time: 0.0770 data: 0.0011 max mem: 33369 +Test: [ 900/2573] eta: 0:02:08 time: 0.0739 data: 0.0012 max mem: 33369 +Test: [1000/2573] eta: 0:02:00 time: 0.0739 data: 0.0011 max mem: 33369 +Test: [1100/2573] eta: 0:01:52 time: 0.0739 data: 0.0011 max mem: 33369 +Test: [1200/2573] eta: 0:01:44 time: 0.0740 data: 0.0011 max mem: 33369 +Test: [1300/2573] eta: 0:01:36 time: 0.0738 data: 0.0011 max mem: 33369 +Test: [1400/2573] eta: 0:01:28 time: 0.0723 data: 0.0012 max mem: 33369 +Test: [1500/2573] eta: 0:01:21 time: 0.0738 data: 0.0011 max mem: 33369 +Test: [1600/2573] eta: 0:01:13 time: 0.0772 data: 0.0011 max mem: 33369 +Test: [1700/2573] eta: 0:01:05 time: 0.0721 data: 0.0011 max mem: 33369 +Test: [1800/2573] eta: 0:00:58 time: 0.0755 data: 0.0011 max mem: 33369 +Test: [1900/2573] eta: 0:00:50 time: 0.0722 data: 0.0011 max mem: 33369 +Test: [2000/2573] eta: 0:00:43 time: 0.0738 data: 0.0011 max mem: 33369 +Test: [2100/2573] eta: 0:00:35 time: 0.0753 data: 0.0011 max mem: 33369 +Test: [2200/2573] eta: 0:00:27 time: 0.0754 data: 0.0011 max mem: 33369 +Test: [2300/2573] eta: 0:00:20 time: 0.0754 data: 0.0011 max mem: 33369 +Test: [2400/2573] eta: 0:00:12 time: 0.0703 data: 0.0011 max mem: 33369 +Test: [2500/2573] eta: 0:00:05 time: 0.0738 data: 0.0011 max mem: 33369 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: Total time: 0:03:12 +Final results: +Mean IoU is 64.74 + + precision@0.5 = 72.79 + precision@0.6 = 67.59 + precision@0.7 = 60.95 + precision@0.8 = 49.57 + precision@0.9 = 25.45 + overall IoU = 61.72 + +Average object IoU 64.73808244476162 +Overall IoU 61.71879577636719 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [33] [ 0/1319] eta: 3:18:16 lr: 1.04150632654866e-05 loss: 0.0273 (0.0273) time: 9.0194 data: 1.4393 max mem: 33369 +Epoch: [33] [ 10/1319] eta: 1:09:36 lr: 1.0404909382463066e-05 loss: 0.0273 (0.0279) time: 3.1905 data: 0.1368 max mem: 33369 +Epoch: [33] [ 20/1319] eta: 1:03:14 lr: 1.0394754398329612e-05 loss: 0.0311 (0.0329) time: 2.6163 data: 0.0063 max mem: 33369 +Epoch: [33] [ 30/1319] eta: 1:00:52 lr: 1.0384598311771345e-05 loss: 0.0315 (0.0323) time: 2.6376 data: 0.0060 max mem: 33369 +Epoch: [33] [ 40/1319] eta: 0:59:28 lr: 1.0374441121470351e-05 loss: 0.0315 (0.0331) time: 2.6519 data: 0.0060 max mem: 33369 +Epoch: [33] [ 50/1319] eta: 0:58:19 lr: 1.0364282826105723e-05 loss: 0.0356 (0.0351) time: 2.6404 data: 0.0063 max mem: 33369 +Epoch: [33] [ 60/1319] eta: 0:57:29 lr: 1.0354123424353528e-05 loss: 0.0353 (0.0352) time: 2.6378 data: 0.0063 max mem: 33369 +Epoch: [33] [ 70/1319] eta: 0:56:39 lr: 1.0343962914886797e-05 loss: 0.0334 (0.0357) time: 2.6292 data: 0.0061 max mem: 33369 +Epoch: [33] [ 80/1319] eta: 0:55:57 lr: 1.033380129637553e-05 loss: 0.0328 (0.0357) time: 2.6178 data: 0.0060 max mem: 33369 +Epoch: [33] [ 90/1319] eta: 0:55:19 lr: 1.0323638567486653e-05 loss: 0.0308 (0.0356) time: 2.6270 data: 0.0061 max mem: 33369 +Epoch: [33] [ 100/1319] eta: 0:54:47 lr: 1.0313474726884054e-05 loss: 0.0351 (0.0360) time: 2.6449 data: 0.0062 max mem: 33369 +Epoch: [33] [ 110/1319] eta: 0:54:13 lr: 1.0303309773228537e-05 loss: 0.0342 (0.0360) time: 2.6484 data: 0.0062 max mem: 33369 +Epoch: [33] [ 120/1319] eta: 0:53:44 lr: 1.0293143705177821e-05 loss: 0.0340 (0.0357) time: 2.6515 data: 0.0061 max mem: 33369 +Epoch: [33] [ 130/1319] eta: 0:53:13 lr: 1.0282976521386539e-05 loss: 0.0356 (0.0361) time: 2.6570 data: 0.0060 max mem: 33369 +Epoch: [33] [ 140/1319] eta: 0:52:42 lr: 1.0272808220506222e-05 loss: 0.0376 (0.0361) time: 2.6418 data: 0.0062 max mem: 33369 +Epoch: [33] [ 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data: 0.0061 max mem: 33369 +Epoch: [33] [ 310/1319] eta: 0:44:45 lr: 1.0099774868986322e-05 loss: 0.0311 (0.0361) time: 2.6204 data: 0.0060 max mem: 33369 +Epoch: [33] [ 320/1319] eta: 0:44:17 lr: 1.008958622631076e-05 loss: 0.0321 (0.0361) time: 2.6072 data: 0.0061 max mem: 33369 +Epoch: [33] [ 330/1319] eta: 0:43:48 lr: 1.0079396440320953e-05 loss: 0.0361 (0.0361) time: 2.6008 data: 0.0063 max mem: 33369 +Epoch: [33] [ 340/1319] eta: 0:43:21 lr: 1.0069205509604051e-05 loss: 0.0340 (0.0361) time: 2.6130 data: 0.0061 max mem: 33369 +Epoch: [33] [ 350/1319] eta: 0:42:54 lr: 1.0059013432743876e-05 loss: 0.0327 (0.0360) time: 2.6365 data: 0.0060 max mem: 33369 +Epoch: [33] [ 360/1319] eta: 0:42:26 lr: 1.0048820208320883e-05 loss: 0.0331 (0.0360) time: 2.6311 data: 0.0062 max mem: 33369 +Epoch: [33] [ 370/1319] eta: 0:42:00 lr: 1.0038625834912186e-05 loss: 0.0331 (0.0359) time: 2.6469 data: 0.0061 max mem: 33369 +Epoch: [33] [ 380/1319] eta: 0:41:33 lr: 1.0028430311091521e-05 loss: 0.0367 (0.0362) time: 2.6624 data: 0.0059 max mem: 33369 +Epoch: [33] [ 390/1319] eta: 0:41:06 lr: 1.0018233635429235e-05 loss: 0.0360 (0.0363) time: 2.6380 data: 0.0061 max mem: 33369 +Epoch: [33] [ 400/1319] eta: 0:40:38 lr: 1.0008035806492287e-05 loss: 0.0311 (0.0362) time: 2.6052 data: 0.0061 max mem: 33369 +Epoch: [33] [ 410/1319] eta: 0:40:11 lr: 9.99783682284423e-06 loss: 0.0311 (0.0362) time: 2.6194 data: 0.0060 max mem: 33369 +Epoch: [33] [ 420/1319] eta: 0:39:44 lr: 9.987636683045179e-06 loss: 0.0321 (0.0360) time: 2.6354 data: 0.0060 max mem: 33369 +Epoch: [33] [ 430/1319] eta: 0:39:17 lr: 9.977435385651839e-06 loss: 0.0289 (0.0359) time: 2.6222 data: 0.0061 max mem: 33369 +Epoch: [33] [ 440/1319] eta: 0:38:51 lr: 9.967232929217462e-06 loss: 0.0331 (0.0359) time: 2.6403 data: 0.0059 max mem: 33369 +Epoch: [33] [ 450/1319] eta: 0:38:24 lr: 9.957029312291845e-06 loss: 0.0333 (0.0358) time: 2.6529 data: 0.0059 max mem: 33369 +Epoch: [33] [ 460/1319] eta: 0:37:57 lr: 9.946824533421325e-06 loss: 0.0308 (0.0357) time: 2.6490 data: 0.0060 max mem: 33369 +Epoch: [33] [ 470/1319] eta: 0:37:31 lr: 9.936618591148734e-06 loss: 0.0329 (0.0357) time: 2.6438 data: 0.0060 max mem: 33369 +Epoch: [33] [ 480/1319] eta: 0:37:04 lr: 9.92641148401344e-06 loss: 0.0356 (0.0357) time: 2.6545 data: 0.0059 max mem: 33369 +Epoch: [33] [ 490/1319] eta: 0:36:38 lr: 9.916203210551294e-06 loss: 0.0349 (0.0357) time: 2.6590 data: 0.0060 max mem: 33369 +Epoch: [33] [ 500/1319] eta: 0:36:11 lr: 9.905993769294629e-06 loss: 0.0301 (0.0356) time: 2.6342 data: 0.0062 max mem: 33369 +Epoch: [33] [ 510/1319] eta: 0:35:44 lr: 9.895783158772255e-06 loss: 0.0361 (0.0357) time: 2.6191 data: 0.0061 max mem: 33369 +Epoch: [33] [ 520/1319] eta: 0:35:17 lr: 9.885571377509421e-06 loss: 0.0395 (0.0358) time: 2.6144 data: 0.0060 max mem: 33369 +Epoch: [33] [ 530/1319] eta: 0:34:50 lr: 9.875358424027841e-06 loss: 0.0322 (0.0358) time: 2.6349 data: 0.0060 max mem: 33369 +Epoch: [33] [ 540/1319] eta: 0:34:24 lr: 9.865144296845656e-06 loss: 0.0323 (0.0358) time: 2.6574 data: 0.0061 max mem: 33369 +Epoch: [33] [ 550/1319] eta: 0:33:57 lr: 9.85492899447742e-06 loss: 0.0343 (0.0357) time: 2.6538 data: 0.0060 max mem: 33369 +Epoch: [33] [ 560/1319] eta: 0:33:31 lr: 9.844712515434104e-06 loss: 0.0336 (0.0357) time: 2.6359 data: 0.0059 max mem: 33369 +Epoch: [33] [ 570/1319] eta: 0:33:04 lr: 9.83449485822307e-06 loss: 0.0339 (0.0357) time: 2.6369 data: 0.0057 max mem: 33369 +Epoch: [33] [ 580/1319] eta: 0:32:38 lr: 9.824276021348049e-06 loss: 0.0309 (0.0356) time: 2.6574 data: 0.0057 max mem: 33369 +Epoch: [33] [ 590/1319] eta: 0:32:11 lr: 9.814056003309152e-06 loss: 0.0304 (0.0356) time: 2.6501 data: 0.0057 max mem: 33369 +Epoch: [33] [ 600/1319] eta: 0:31:45 lr: 9.803834802602848e-06 loss: 0.0377 (0.0357) time: 2.6460 data: 0.0059 max mem: 33369 +Epoch: [33] [ 610/1319] eta: 0:31:18 lr: 9.793612417721937e-06 loss: 0.0357 (0.0357) time: 2.6474 data: 0.0061 max mem: 33369 +Epoch: [33] [ 620/1319] eta: 0:30:51 lr: 9.783388847155563e-06 loss: 0.0345 (0.0357) time: 2.6315 data: 0.0061 max mem: 33369 +Epoch: [33] [ 630/1319] eta: 0:30:25 lr: 9.773164089389164e-06 loss: 0.0304 (0.0356) time: 2.6388 data: 0.0061 max mem: 33369 +Epoch: [33] [ 640/1319] eta: 0:29:58 lr: 9.762938142904499e-06 loss: 0.0310 (0.0356) time: 2.6460 data: 0.0060 max mem: 33369 +Epoch: [33] [ 650/1319] eta: 0:29:32 lr: 9.752711006179608e-06 loss: 0.0312 (0.0356) time: 2.6333 data: 0.0060 max mem: 33369 +Epoch: [33] [ 660/1319] eta: 0:29:05 lr: 9.742482677688807e-06 loss: 0.0312 (0.0356) time: 2.6429 data: 0.0060 max mem: 33369 +Epoch: [33] [ 670/1319] eta: 0:28:39 lr: 9.732253155902685e-06 loss: 0.0291 (0.0356) time: 2.6560 data: 0.0059 max mem: 33369 +Epoch: [33] [ 680/1319] eta: 0:28:12 lr: 9.722022439288054e-06 loss: 0.0328 (0.0356) time: 2.6291 data: 0.0059 max mem: 33369 +Epoch: [33] [ 690/1319] eta: 0:27:45 lr: 9.711790526307984e-06 loss: 0.0342 (0.0356) time: 2.6291 data: 0.0059 max mem: 33369 +Epoch: [33] [ 700/1319] eta: 0:27:19 lr: 9.701557415421759e-06 loss: 0.0327 (0.0356) time: 2.6439 data: 0.0059 max mem: 33369 +Epoch: [33] [ 710/1319] eta: 0:26:53 lr: 9.69132310508487e-06 loss: 0.0369 (0.0356) time: 2.6582 data: 0.0059 max mem: 33369 +Epoch: [33] [ 720/1319] eta: 0:26:26 lr: 9.681087593749006e-06 loss: 0.0334 (0.0356) time: 2.6650 data: 0.0058 max mem: 33369 +Epoch: [33] [ 730/1319] eta: 0:25:59 lr: 9.670850879862032e-06 loss: 0.0334 (0.0356) time: 2.6436 data: 0.0059 max mem: 33369 +Epoch: [33] [ 740/1319] eta: 0:25:33 lr: 9.660612961867972e-06 loss: 0.0319 (0.0355) time: 2.6491 data: 0.0060 max mem: 33369 +Epoch: [33] [ 750/1319] eta: 0:25:06 lr: 9.650373838207014e-06 loss: 0.0298 (0.0354) time: 2.6409 data: 0.0059 max mem: 33369 +Epoch: [33] [ 760/1319] eta: 0:24:40 lr: 9.640133507315477e-06 loss: 0.0278 (0.0354) time: 2.6183 data: 0.0060 max mem: 33369 +Epoch: [33] [ 770/1319] eta: 0:24:13 lr: 9.62989196762581e-06 loss: 0.0278 (0.0353) time: 2.6408 data: 0.0060 max mem: 33369 +Epoch: [33] [ 780/1319] eta: 0:23:47 lr: 9.61964921756657e-06 loss: 0.0289 (0.0353) time: 2.6518 data: 0.0059 max mem: 33369 +Epoch: [33] [ 790/1319] eta: 0:23:21 lr: 9.609405255562397e-06 loss: 0.0342 (0.0353) time: 2.6756 data: 0.0059 max mem: 33369 +Epoch: [33] [ 800/1319] eta: 0:22:54 lr: 9.599160080034027e-06 loss: 0.0334 (0.0353) time: 2.6676 data: 0.0059 max mem: 33369 +Epoch: [33] [ 810/1319] eta: 0:22:28 lr: 9.588913689398257e-06 loss: 0.0319 (0.0353) time: 2.6331 data: 0.0059 max mem: 33369 +Epoch: [33] [ 820/1319] eta: 0:22:01 lr: 9.578666082067937e-06 loss: 0.0314 (0.0352) time: 2.6392 data: 0.0059 max mem: 33369 +Epoch: [33] [ 830/1319] eta: 0:21:34 lr: 9.568417256451955e-06 loss: 0.0330 (0.0352) time: 2.6325 data: 0.0059 max mem: 33369 +Epoch: [33] [ 840/1319] eta: 0:21:08 lr: 9.558167210955227e-06 loss: 0.0330 (0.0352) time: 2.6352 data: 0.0059 max mem: 33369 +Epoch: [33] [ 850/1319] eta: 0:20:41 lr: 9.547915943978656e-06 loss: 0.0339 (0.0353) time: 2.6163 data: 0.0060 max mem: 33369 +Epoch: [33] [ 860/1319] eta: 0:20:15 lr: 9.537663453919165e-06 loss: 0.0366 (0.0353) time: 2.6397 data: 0.0060 max mem: 33369 +Epoch: [33] [ 870/1319] eta: 0:19:48 lr: 9.52740973916964e-06 loss: 0.0334 (0.0353) time: 2.6593 data: 0.0060 max mem: 33369 +Epoch: [33] [ 880/1319] eta: 0:19:22 lr: 9.517154798118936e-06 loss: 0.0314 (0.0353) time: 2.6528 data: 0.0060 max mem: 33369 +Epoch: [33] [ 890/1319] eta: 0:18:56 lr: 9.506898629151863e-06 loss: 0.0360 (0.0354) time: 2.6779 data: 0.0059 max mem: 33369 +Epoch: [33] [ 900/1319] eta: 0:18:29 lr: 9.496641230649144e-06 loss: 0.0387 (0.0354) time: 2.6890 data: 0.0057 max mem: 33369 +Epoch: [33] [ 910/1319] eta: 0:18:03 lr: 9.48638260098744e-06 loss: 0.0302 (0.0353) time: 2.6536 data: 0.0057 max mem: 33369 +Epoch: [33] [ 920/1319] eta: 0:17:36 lr: 9.476122738539313e-06 loss: 0.0303 (0.0353) time: 2.6344 data: 0.0058 max mem: 33369 +Epoch: [33] [ 930/1319] eta: 0:17:10 lr: 9.465861641673206e-06 loss: 0.0325 (0.0353) time: 2.6414 data: 0.0058 max mem: 33369 +Epoch: [33] [ 940/1319] eta: 0:16:43 lr: 9.455599308753445e-06 loss: 0.0317 (0.0353) time: 2.6464 data: 0.0059 max mem: 33369 +Epoch: [33] [ 950/1319] eta: 0:16:17 lr: 9.445335738140192e-06 loss: 0.0306 (0.0352) time: 2.6661 data: 0.0059 max mem: 33369 +Epoch: [33] [ 960/1319] eta: 0:15:50 lr: 9.435070928189476e-06 loss: 0.0292 (0.0352) time: 2.6512 data: 0.0059 max mem: 33369 +Epoch: [33] [ 970/1319] eta: 0:15:24 lr: 9.424804877253139e-06 loss: 0.0289 (0.0352) time: 2.6414 data: 0.0061 max mem: 33369 +Epoch: [33] [ 980/1319] eta: 0:14:57 lr: 9.414537583678836e-06 loss: 0.0362 (0.0352) time: 2.6280 data: 0.0059 max mem: 33369 +Epoch: [33] [ 990/1319] eta: 0:14:31 lr: 9.404269045810016e-06 loss: 0.0362 (0.0353) time: 2.6314 data: 0.0061 max mem: 33369 +Epoch: [33] [1000/1319] eta: 0:14:04 lr: 9.393999261985916e-06 loss: 0.0331 (0.0352) time: 2.6572 data: 0.0060 max mem: 33369 +Epoch: [33] [1010/1319] eta: 0:13:38 lr: 9.383728230541512e-06 loss: 0.0312 (0.0352) time: 2.6649 data: 0.0059 max mem: 33369 +Epoch: [33] [1020/1319] eta: 0:13:12 lr: 9.373455949807552e-06 loss: 0.0307 (0.0352) time: 2.6861 data: 0.0060 max mem: 33369 +Epoch: [33] [1030/1319] eta: 0:12:45 lr: 9.363182418110507e-06 loss: 0.0307 (0.0351) time: 2.6729 data: 0.0058 max mem: 33369 +Epoch: [33] [1040/1319] eta: 0:12:18 lr: 9.352907633772557e-06 loss: 0.0295 (0.0351) time: 2.6383 data: 0.0058 max mem: 33369 +Epoch: [33] [1050/1319] eta: 0:11:52 lr: 9.342631595111597e-06 loss: 0.0295 (0.0351) time: 2.6356 data: 0.0059 max mem: 33369 +Epoch: [33] [1060/1319] eta: 0:11:25 lr: 9.332354300441178e-06 loss: 0.0326 (0.0351) time: 2.5996 data: 0.0061 max mem: 33369 +Epoch: [33] [1070/1319] eta: 0:10:59 lr: 9.322075748070539e-06 loss: 0.0328 (0.0351) time: 2.5798 data: 0.0059 max mem: 33369 +Epoch: [33] [1080/1319] eta: 0:10:32 lr: 9.311795936304561e-06 loss: 0.0323 (0.0351) time: 2.6335 data: 0.0060 max mem: 33369 +Epoch: [33] [1090/1319] eta: 0:10:06 lr: 9.301514863443759e-06 loss: 0.0351 (0.0351) time: 2.6436 data: 0.0061 max mem: 33369 +Epoch: [33] [1100/1319] eta: 0:09:39 lr: 9.291232527784269e-06 loss: 0.0383 (0.0352) time: 2.6341 data: 0.0060 max mem: 33369 +Epoch: [33] [1110/1319] eta: 0:09:13 lr: 9.280948927617811e-06 loss: 0.0331 (0.0352) time: 2.6199 data: 0.0062 max mem: 33369 +Epoch: [33] [1120/1319] eta: 0:08:46 lr: 9.270664061231702e-06 loss: 0.0317 (0.0352) time: 2.6237 data: 0.0062 max mem: 33369 +Epoch: [33] [1130/1319] eta: 0:08:20 lr: 9.260377926908826e-06 loss: 0.0315 (0.0352) time: 2.6484 data: 0.0060 max mem: 33369 +Epoch: [33] [1140/1319] eta: 0:07:53 lr: 9.250090522927605e-06 loss: 0.0322 (0.0352) time: 2.6545 data: 0.0060 max mem: 33369 +Epoch: [33] [1150/1319] eta: 0:07:27 lr: 9.239801847562006e-06 loss: 0.0350 (0.0352) time: 2.6512 data: 0.0060 max mem: 33369 +Epoch: [33] [1160/1319] eta: 0:07:00 lr: 9.229511899081506e-06 loss: 0.0275 (0.0351) time: 2.6370 data: 0.0060 max mem: 33369 +Epoch: [33] [1170/1319] eta: 0:06:34 lr: 9.219220675751069e-06 loss: 0.0285 (0.0350) time: 2.6402 data: 0.0059 max mem: 33369 +Epoch: [33] [1180/1319] eta: 0:06:07 lr: 9.20892817583115e-06 loss: 0.0301 (0.0350) time: 2.6401 data: 0.0059 max mem: 33369 +Epoch: [33] [1190/1319] eta: 0:05:41 lr: 9.19863439757767e-06 loss: 0.0346 (0.0351) time: 2.6557 data: 0.0059 max mem: 33369 +Epoch: [33] [1200/1319] eta: 0:05:15 lr: 9.188339339241987e-06 loss: 0.0346 (0.0351) time: 2.6760 data: 0.0059 max mem: 33369 +Epoch: [33] [1210/1319] eta: 0:04:48 lr: 9.178042999070898e-06 loss: 0.0305 (0.0351) time: 2.6560 data: 0.0059 max mem: 33369 +Epoch: [33] [1220/1319] eta: 0:04:22 lr: 9.16774537530659e-06 loss: 0.0350 (0.0352) time: 2.6241 data: 0.0059 max mem: 33369 +Epoch: [33] [1230/1319] eta: 0:03:55 lr: 9.157446466186662e-06 loss: 0.0350 (0.0352) time: 2.6175 data: 0.0059 max mem: 33369 +Epoch: [33] [1240/1319] eta: 0:03:29 lr: 9.147146269944078e-06 loss: 0.0345 (0.0353) time: 2.6228 data: 0.0059 max mem: 33369 +Epoch: [33] [1250/1319] eta: 0:03:02 lr: 9.136844784807162e-06 loss: 0.0320 (0.0353) time: 2.6230 data: 0.0059 max mem: 33369 +Epoch: [33] [1260/1319] eta: 0:02:36 lr: 9.126542008999582e-06 loss: 0.0319 (0.0353) time: 2.6307 data: 0.0060 max mem: 33369 +Epoch: [33] [1270/1319] eta: 0:02:09 lr: 9.11623794074031e-06 loss: 0.0348 (0.0353) time: 2.6409 data: 0.0060 max mem: 33369 +Epoch: [33] [1280/1319] eta: 0:01:43 lr: 9.105932578243631e-06 loss: 0.0308 (0.0353) time: 2.6404 data: 0.0059 max mem: 33369 +Epoch: [33] [1290/1319] eta: 0:01:16 lr: 9.095625919719118e-06 loss: 0.0321 (0.0353) time: 2.6406 data: 0.0061 max mem: 33369 +Epoch: [33] [1300/1319] eta: 0:00:50 lr: 9.085317963371604e-06 loss: 0.0372 (0.0353) time: 2.6569 data: 0.0061 max mem: 33369 +Epoch: [33] [1310/1319] eta: 0:00:23 lr: 9.075008707401167e-06 loss: 0.0306 (0.0353) time: 2.6808 data: 0.0060 max mem: 33369 +Epoch: [33] Total time: 0:58:11 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 2:16:10 time: 3.1753 data: 3.0626 max mem: 33369 +Test: [ 100/2573] eta: 0:04:13 time: 0.0717 data: 0.0011 max mem: 33369 +Test: [ 200/2573] eta: 0:03:30 time: 0.0735 data: 0.0012 max mem: 33369 +Test: [ 300/2573] eta: 0:03:08 time: 0.0751 data: 0.0011 max mem: 33369 +Test: [ 400/2573] eta: 0:02:55 time: 0.0752 data: 0.0011 max mem: 33369 +Test: [ 500/2573] eta: 0:02:44 time: 0.0736 data: 0.0011 max mem: 33369 +Test: [ 600/2573] eta: 0:02:34 time: 0.0737 data: 0.0011 max mem: 33369 +Test: [ 700/2573] eta: 0:02:26 time: 0.0737 data: 0.0011 max mem: 33369 +Test: [ 800/2573] eta: 0:02:17 time: 0.0772 data: 0.0011 max mem: 33369 +Test: [ 900/2573] eta: 0:02:09 time: 0.0738 data: 0.0011 max mem: 33369 +Test: [1000/2573] eta: 0:02:01 time: 0.0738 data: 0.0011 max mem: 33369 +Test: [1100/2573] eta: 0:01:53 time: 0.0739 data: 0.0011 max mem: 33369 +Test: [1200/2573] eta: 0:01:45 time: 0.0739 data: 0.0011 max mem: 33369 +Test: [1300/2573] eta: 0:01:37 time: 0.0737 data: 0.0011 max mem: 33369 +Test: [1400/2573] eta: 0:01:29 time: 0.0722 data: 0.0011 max mem: 33369 +Test: [1500/2573] eta: 0:01:21 time: 0.0739 data: 0.0011 max mem: 33369 +Test: [1600/2573] eta: 0:01:13 time: 0.0771 data: 0.0011 max mem: 33369 +Test: [1700/2573] eta: 0:01:06 time: 0.0722 data: 0.0011 max mem: 33369 +Test: [1800/2573] eta: 0:00:58 time: 0.0756 data: 0.0011 max mem: 33369 +Test: [1900/2573] eta: 0:00:50 time: 0.0723 data: 0.0011 max mem: 33369 +Test: [2000/2573] eta: 0:00:43 time: 0.0739 data: 0.0011 max mem: 33369 +Test: [2100/2573] eta: 0:00:35 time: 0.0755 data: 0.0011 max mem: 33369 +Test: [2200/2573] eta: 0:00:28 time: 0.0755 data: 0.0011 max mem: 33369 +Test: [2300/2573] eta: 0:00:20 time: 0.0756 data: 0.0011 max mem: 33369 +Test: [2400/2573] eta: 0:00:12 time: 0.0706 data: 0.0011 max mem: 33369 +Test: [2500/2573] eta: 0:00:05 time: 0.0738 data: 0.0011 max mem: 33369 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: Total time: 0:03:13 +Final results: +Mean IoU is 64.91 + + precision@0.5 = 73.16 + precision@0.6 = 67.77 + precision@0.7 = 61.50 + precision@0.8 = 50.33 + precision@0.9 = 25.59 + overall IoU = 61.95 + +Average object IoU 64.90549684630425 +Overall IoU 61.95033645629883 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [34] [ 0/1319] eta: 3:19:39 lr: 9.065729264358701e-06 loss: 0.0197 (0.0197) time: 9.0823 data: 1.5846 max mem: 33369 +Epoch: [34] [ 10/1319] eta: 1:10:16 lr: 9.05541753412883e-06 loss: 0.0247 (0.0294) time: 3.2211 data: 0.1496 max mem: 33369 +Epoch: [34] [ 20/1319] eta: 1:03:15 lr: 9.045104499029229e-06 loss: 0.0302 (0.0307) time: 2.6142 data: 0.0059 max mem: 33369 +Epoch: [34] [ 30/1319] eta: 1:00:49 lr: 9.03479015724125e-06 loss: 0.0302 (0.0304) time: 2.6167 data: 0.0061 max mem: 33369 +Epoch: [34] [ 40/1319] eta: 0:59:09 lr: 9.024474506941415e-06 loss: 0.0294 (0.0307) time: 2.6206 data: 0.0063 max mem: 33369 +Epoch: [34] [ 50/1319] eta: 0:57:57 lr: 9.014157546301385e-06 loss: 0.0325 (0.0320) time: 2.5991 data: 0.0062 max mem: 33369 +Epoch: [34] [ 60/1319] eta: 0:57:10 lr: 9.003839273487931e-06 loss: 0.0326 (0.0329) time: 2.6210 data: 0.0061 max mem: 33369 +Epoch: [34] [ 70/1319] eta: 0:56:32 lr: 8.99351968666293e-06 loss: 0.0308 (0.0323) time: 2.6544 data: 0.0060 max mem: 33369 +Epoch: [34] [ 80/1319] eta: 0:55:50 lr: 8.983198783983315e-06 loss: 0.0320 (0.0331) time: 2.6429 data: 0.0061 max mem: 33369 +Epoch: [34] [ 90/1319] eta: 0:55:16 lr: 8.972876563601101e-06 loss: 0.0364 (0.0334) time: 2.6366 data: 0.0062 max mem: 33369 +Epoch: [34] [ 100/1319] eta: 0:54:39 lr: 8.962553023663333e-06 loss: 0.0318 (0.0343) time: 2.6327 data: 0.0061 max mem: 33369 +Epoch: [34] [ 110/1319] eta: 0:54:09 lr: 8.952228162312077e-06 loss: 0.0320 (0.0341) time: 2.6393 data: 0.0060 max mem: 33369 +Epoch: [34] [ 120/1319] eta: 0:53:34 lr: 8.941901977684397e-06 loss: 0.0336 (0.0342) time: 2.6324 data: 0.0062 max mem: 33369 +Epoch: [34] [ 130/1319] eta: 0:53:04 lr: 8.93157446791234e-06 loss: 0.0346 (0.0345) time: 2.6243 data: 0.0060 max mem: 33369 +Epoch: [34] [ 140/1319] eta: 0:52:35 lr: 8.9212456311229e-06 loss: 0.0348 (0.0346) time: 2.6489 data: 0.0061 max mem: 33369 +Epoch: [34] [ 150/1319] eta: 0:52:06 lr: 8.910915465438025e-06 loss: 0.0348 (0.0347) time: 2.6524 data: 0.0062 max mem: 33369 +Epoch: [34] [ 160/1319] eta: 0:51:35 lr: 8.900583968974578e-06 loss: 0.0339 (0.0347) time: 2.6333 data: 0.0059 max mem: 33369 +Epoch: [34] [ 170/1319] eta: 0:51:07 lr: 8.89025113984432e-06 loss: 0.0317 (0.0348) time: 2.6344 data: 0.0058 max mem: 33369 +Epoch: [34] [ 180/1319] eta: 0:50:37 lr: 8.879916976153894e-06 loss: 0.0308 (0.0345) time: 2.6381 data: 0.0060 max mem: 33369 +Epoch: [34] [ 190/1319] eta: 0:50:09 lr: 8.869581476004788e-06 loss: 0.0308 (0.0347) time: 2.6306 data: 0.0059 max mem: 33369 +Epoch: [34] [ 200/1319] eta: 0:49:43 lr: 8.859244637493344e-06 loss: 0.0308 (0.0346) time: 2.6592 data: 0.0058 max mem: 33369 +Epoch: [34] [ 210/1319] eta: 0:49:14 lr: 8.84890645871071e-06 loss: 0.0335 (0.0346) time: 2.6438 data: 0.0059 max mem: 33369 +Epoch: [34] [ 220/1319] eta: 0:48:46 lr: 8.838566937742836e-06 loss: 0.0335 (0.0346) time: 2.6229 data: 0.0060 max mem: 33369 +Epoch: [34] [ 230/1319] eta: 0:48:17 lr: 8.828226072670449e-06 loss: 0.0313 (0.0355) time: 2.6289 data: 0.0059 max mem: 33369 +Epoch: [34] [ 240/1319] eta: 0:47:49 lr: 8.817883861569014e-06 loss: 0.0331 (0.0355) time: 2.6277 data: 0.0061 max mem: 33369 +Epoch: [34] [ 250/1319] eta: 0:47:22 lr: 8.807540302508743e-06 loss: 0.0360 (0.0356) time: 2.6413 data: 0.0062 max mem: 33369 +Epoch: [34] [ 260/1319] eta: 0:46:54 lr: 8.797195393554557e-06 loss: 0.0321 (0.0355) time: 2.6331 data: 0.0061 max mem: 33369 +Epoch: [34] [ 270/1319] eta: 0:46:27 lr: 8.786849132766063e-06 loss: 0.0300 (0.0353) time: 2.6309 data: 0.0060 max mem: 33369 +Epoch: [34] [ 280/1319] eta: 0:46:00 lr: 8.776501518197541e-06 loss: 0.0319 (0.0352) time: 2.6457 data: 0.0059 max mem: 33369 +Epoch: [34] [ 290/1319] eta: 0:45:32 lr: 8.76615254789792e-06 loss: 0.0331 (0.0352) time: 2.6342 data: 0.0059 max mem: 33369 +Epoch: [34] [ 300/1319] eta: 0:45:03 lr: 8.755802219910735e-06 loss: 0.0325 (0.0352) time: 2.6065 data: 0.0060 max mem: 33369 +Epoch: [34] [ 310/1319] eta: 0:44:34 lr: 8.745450532274145e-06 loss: 0.0299 (0.0351) time: 2.5851 data: 0.0060 max mem: 33369 +Epoch: [34] [ 320/1319] eta: 0:44:07 lr: 8.735097483020883e-06 loss: 0.0341 (0.0352) time: 2.5973 data: 0.0060 max mem: 33369 +Epoch: [34] [ 330/1319] eta: 0:43:40 lr: 8.724743070178239e-06 loss: 0.0345 (0.0352) time: 2.6302 data: 0.0060 max mem: 33369 +Epoch: [34] [ 340/1319] eta: 0:43:13 lr: 8.714387291768046e-06 loss: 0.0339 (0.0351) time: 2.6399 data: 0.0060 max mem: 33369 +Epoch: [34] [ 350/1319] eta: 0:42:45 lr: 8.704030145806636e-06 loss: 0.0299 (0.0351) time: 2.6168 data: 0.0059 max mem: 33369 +Epoch: [34] [ 360/1319] eta: 0:42:19 lr: 8.693671630304845e-06 loss: 0.0318 (0.0350) time: 2.6261 data: 0.0060 max mem: 33369 +Epoch: [34] [ 370/1319] eta: 0:41:52 lr: 8.683311743267978e-06 loss: 0.0318 (0.0351) time: 2.6380 data: 0.0060 max mem: 33369 +Epoch: [34] [ 380/1319] eta: 0:41:26 lr: 8.672950482695785e-06 loss: 0.0279 (0.0350) time: 2.6385 data: 0.0060 max mem: 33369 +Epoch: [34] [ 390/1319] eta: 0:40:58 lr: 8.662587846582436e-06 loss: 0.0285 (0.0350) time: 2.6384 data: 0.0059 max mem: 33369 +Epoch: [34] [ 400/1319] eta: 0:40:32 lr: 8.65222383291651e-06 loss: 0.0291 (0.0350) time: 2.6315 data: 0.0057 max mem: 33369 +Epoch: [34] [ 410/1319] eta: 0:40:05 lr: 8.641858439680947e-06 loss: 0.0305 (0.0349) time: 2.6281 data: 0.0059 max mem: 33369 +Epoch: [34] [ 420/1319] eta: 0:39:38 lr: 8.631491664853054e-06 loss: 0.0331 (0.0351) time: 2.6218 data: 0.0060 max mem: 33369 +Epoch: [34] [ 430/1319] eta: 0:39:10 lr: 8.621123506404469e-06 loss: 0.0341 (0.0351) time: 2.6104 data: 0.0059 max mem: 33369 +Epoch: [34] [ 440/1319] eta: 0:38:43 lr: 8.610753962301133e-06 loss: 0.0320 (0.0351) time: 2.5898 data: 0.0059 max mem: 33369 +Epoch: [34] [ 450/1319] eta: 0:38:16 lr: 8.600383030503278e-06 loss: 0.0356 (0.0352) time: 2.6006 data: 0.0059 max mem: 33369 +Epoch: [34] [ 460/1319] eta: 0:37:48 lr: 8.590010708965377e-06 loss: 0.0374 (0.0352) time: 2.6047 data: 0.0059 max mem: 33369 +Epoch: [34] [ 470/1319] eta: 0:37:22 lr: 8.579636995636159e-06 loss: 0.0425 (0.0354) time: 2.6152 data: 0.0059 max mem: 33369 +Epoch: [34] [ 480/1319] eta: 0:36:55 lr: 8.569261888458558e-06 loss: 0.0390 (0.0356) time: 2.6292 data: 0.0060 max mem: 33369 +Epoch: [34] [ 490/1319] eta: 0:36:29 lr: 8.558885385369697e-06 loss: 0.0309 (0.0356) time: 2.6288 data: 0.0059 max mem: 33369 +Epoch: [34] [ 500/1319] eta: 0:36:02 lr: 8.548507484300866e-06 loss: 0.0344 (0.0357) time: 2.6386 data: 0.0060 max mem: 33369 +Epoch: [34] [ 510/1319] eta: 0:35:35 lr: 8.538128183177479e-06 loss: 0.0344 (0.0357) time: 2.6129 data: 0.0060 max mem: 33369 +Epoch: [34] [ 520/1319] eta: 0:35:08 lr: 8.527747479919078e-06 loss: 0.0319 (0.0357) time: 2.5827 data: 0.0059 max mem: 33369 +Epoch: [34] [ 530/1319] eta: 0:34:41 lr: 8.517365372439296e-06 loss: 0.0319 (0.0356) time: 2.5969 data: 0.0059 max mem: 33369 +Epoch: [34] [ 540/1319] eta: 0:34:14 lr: 8.506981858645828e-06 loss: 0.0288 (0.0356) time: 2.6014 data: 0.0059 max mem: 33369 +Epoch: [34] [ 550/1319] eta: 0:33:47 lr: 8.496596936440405e-06 loss: 0.0274 (0.0355) time: 2.5955 data: 0.0059 max mem: 33369 +Epoch: [34] [ 560/1319] eta: 0:33:21 lr: 8.486210603718787e-06 loss: 0.0289 (0.0354) time: 2.6277 data: 0.0059 max mem: 33369 +Epoch: [34] [ 570/1319] eta: 0:32:54 lr: 8.475822858370701e-06 loss: 0.0325 (0.0355) time: 2.6277 data: 0.0059 max mem: 33369 +Epoch: [34] [ 580/1319] eta: 0:32:27 lr: 8.465433698279856e-06 loss: 0.0355 (0.0355) time: 2.6035 data: 0.0058 max mem: 33369 +Epoch: [34] [ 590/1319] eta: 0:32:01 lr: 8.455043121323896e-06 loss: 0.0348 (0.0354) time: 2.6169 data: 0.0059 max mem: 33369 +Epoch: [34] [ 600/1319] eta: 0:31:34 lr: 8.444651125374376e-06 loss: 0.0353 (0.0355) time: 2.6121 data: 0.0059 max mem: 33369 +Epoch: [34] [ 610/1319] eta: 0:31:07 lr: 8.43425770829675e-06 loss: 0.0378 (0.0355) time: 2.5925 data: 0.0058 max mem: 33369 +Epoch: [34] [ 620/1319] eta: 0:30:41 lr: 8.423862867950307e-06 loss: 0.0328 (0.0355) time: 2.6152 data: 0.0059 max mem: 33369 +Epoch: [34] [ 630/1319] eta: 0:30:14 lr: 8.413466602188201e-06 loss: 0.0293 (0.0354) time: 2.6099 data: 0.0060 max mem: 33369 +Epoch: [34] [ 640/1319] eta: 0:29:48 lr: 8.403068908857377e-06 loss: 0.0279 (0.0354) time: 2.6042 data: 0.0059 max mem: 33369 +Epoch: [34] [ 650/1319] eta: 0:29:21 lr: 8.39266978579857e-06 loss: 0.0279 (0.0354) time: 2.6278 data: 0.0060 max mem: 33369 +Epoch: [34] [ 660/1319] eta: 0:28:55 lr: 8.382269230846276e-06 loss: 0.0324 (0.0354) time: 2.6249 data: 0.0060 max mem: 33369 +Epoch: [34] [ 670/1319] eta: 0:28:28 lr: 8.371867241828703e-06 loss: 0.0324 (0.0353) time: 2.6132 data: 0.0059 max mem: 33369 +Epoch: [34] [ 680/1319] eta: 0:28:02 lr: 8.361463816567778e-06 loss: 0.0303 (0.0352) time: 2.6296 data: 0.0059 max mem: 33369 +Epoch: [34] [ 690/1319] eta: 0:27:35 lr: 8.3510589528791e-06 loss: 0.0303 (0.0354) time: 2.6287 data: 0.0059 max mem: 33369 +Epoch: [34] [ 700/1319] eta: 0:27:09 lr: 8.340652648571916e-06 loss: 0.0333 (0.0353) time: 2.6304 data: 0.0059 max mem: 33369 +Epoch: [34] [ 710/1319] eta: 0:26:43 lr: 8.330244901449094e-06 loss: 0.0322 (0.0354) time: 2.6395 data: 0.0059 max mem: 33369 +Epoch: [34] [ 720/1319] eta: 0:26:16 lr: 8.319835709307101e-06 loss: 0.0341 (0.0354) time: 2.6110 data: 0.0059 max mem: 33369 +Epoch: [34] [ 730/1319] eta: 0:25:50 lr: 8.309425069935955e-06 loss: 0.0338 (0.0354) time: 2.6221 data: 0.0060 max mem: 33369 +Epoch: [34] [ 740/1319] eta: 0:25:24 lr: 8.299012981119228e-06 loss: 0.0309 (0.0353) time: 2.6550 data: 0.0060 max mem: 33369 +Epoch: [34] [ 750/1319] eta: 0:24:58 lr: 8.288599440633996e-06 loss: 0.0305 (0.0352) time: 2.6545 data: 0.0058 max mem: 33369 +Epoch: [34] [ 760/1319] eta: 0:24:31 lr: 8.278184446250822e-06 loss: 0.0305 (0.0353) time: 2.6397 data: 0.0060 max mem: 33369 +Epoch: [34] [ 770/1319] eta: 0:24:06 lr: 8.267767995733725e-06 loss: 0.0368 (0.0353) time: 2.6691 data: 0.0059 max mem: 33369 +Epoch: [34] [ 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+Epoch: [34] [ 860/1319] eta: 0:20:09 lr: 8.173954042838362e-06 loss: 0.0295 (0.0352) time: 2.6364 data: 0.0059 max mem: 33369 +Epoch: [34] [ 870/1319] eta: 0:19:42 lr: 8.163522906542168e-06 loss: 0.0323 (0.0352) time: 2.6242 data: 0.0059 max mem: 33369 +Epoch: [34] [ 880/1319] eta: 0:19:16 lr: 8.153090289075947e-06 loss: 0.0346 (0.0352) time: 2.6545 data: 0.0059 max mem: 33369 +Epoch: [34] [ 890/1319] eta: 0:18:50 lr: 8.142656188122887e-06 loss: 0.0346 (0.0352) time: 2.6488 data: 0.0059 max mem: 33369 +Epoch: [34] [ 900/1319] eta: 0:18:24 lr: 8.132220601359272e-06 loss: 0.0326 (0.0353) time: 2.6817 data: 0.0059 max mem: 33369 +Epoch: [34] [ 910/1319] eta: 0:17:57 lr: 8.121783526454415e-06 loss: 0.0293 (0.0352) time: 2.6789 data: 0.0059 max mem: 33369 +Epoch: [34] [ 920/1319] eta: 0:17:31 lr: 8.111344961070641e-06 loss: 0.0296 (0.0352) time: 2.6361 data: 0.0059 max mem: 33369 +Epoch: [34] [ 930/1319] eta: 0:17:05 lr: 8.100904902863262e-06 loss: 0.0296 (0.0352) time: 2.6341 data: 0.0059 max mem: 33369 +Epoch: [34] [ 940/1319] eta: 0:16:38 lr: 8.090463349480519e-06 loss: 0.0249 (0.0352) time: 2.6046 data: 0.0060 max mem: 33369 +Epoch: [34] [ 950/1319] eta: 0:16:12 lr: 8.080020298563588e-06 loss: 0.0283 (0.0352) time: 2.6149 data: 0.0058 max mem: 33369 +Epoch: [34] [ 960/1319] eta: 0:15:45 lr: 8.069575747746527e-06 loss: 0.0286 (0.0352) time: 2.6202 data: 0.0059 max mem: 33369 +Epoch: [34] [ 970/1319] eta: 0:15:19 lr: 8.059129694656241e-06 loss: 0.0301 (0.0352) time: 2.6109 data: 0.0060 max mem: 33369 +Epoch: [34] [ 980/1319] eta: 0:14:53 lr: 8.048682136912463e-06 loss: 0.0333 (0.0352) time: 2.6288 data: 0.0059 max mem: 33369 +Epoch: [34] [ 990/1319] eta: 0:14:26 lr: 8.038233072127722e-06 loss: 0.0333 (0.0352) time: 2.6413 data: 0.0059 max mem: 33369 +Epoch: [34] [1000/1319] eta: 0:14:00 lr: 8.027782497907283e-06 loss: 0.0373 (0.0352) time: 2.6443 data: 0.0059 max mem: 33369 +Epoch: [34] [1010/1319] eta: 0:13:34 lr: 8.017330411849153e-06 loss: 0.0312 (0.0352) time: 2.6357 data: 0.0059 max mem: 33369 +Epoch: [34] [1020/1319] eta: 0:13:07 lr: 8.006876811544029e-06 loss: 0.0301 (0.0352) time: 2.6585 data: 0.0060 max mem: 33369 +Epoch: [34] [1030/1319] eta: 0:12:41 lr: 7.996421694575264e-06 loss: 0.0266 (0.0351) time: 2.6877 data: 0.0061 max mem: 33369 +Epoch: [34] [1040/1319] eta: 0:12:15 lr: 7.985965058518847e-06 loss: 0.0306 (0.0351) time: 2.6825 data: 0.0062 max mem: 33369 +Epoch: [34] [1050/1319] eta: 0:11:49 lr: 7.97550690094334e-06 loss: 0.0323 (0.0351) time: 2.6599 data: 0.0060 max mem: 33369 +Epoch: [34] [1060/1319] eta: 0:11:22 lr: 7.965047219409881e-06 loss: 0.0317 (0.0351) time: 2.6495 data: 0.0060 max mem: 33369 +Epoch: [34] [1070/1319] eta: 0:10:56 lr: 7.95458601147213e-06 loss: 0.0323 (0.0351) time: 2.6698 data: 0.0061 max mem: 33369 +Epoch: [34] [1080/1319] eta: 0:10:30 lr: 7.944123274676236e-06 loss: 0.0329 (0.0351) time: 2.6780 data: 0.0060 max mem: 33369 +Epoch: [34] [1090/1319] eta: 0:10:03 lr: 7.933659006560817e-06 loss: 0.0333 (0.0351) time: 2.6743 data: 0.0059 max mem: 33369 +Epoch: [34] [1100/1319] eta: 0:09:37 lr: 7.923193204656895e-06 loss: 0.0321 (0.0351) time: 2.6616 data: 0.0061 max mem: 33369 +Epoch: [34] [1110/1319] eta: 0:09:11 lr: 7.912725866487896e-06 loss: 0.0294 (0.0350) time: 2.6430 data: 0.0061 max mem: 33369 +Epoch: [34] [1120/1319] eta: 0:08:44 lr: 7.902256989569599e-06 loss: 0.0294 (0.0350) time: 2.6434 data: 0.0058 max mem: 33369 +Epoch: [34] [1130/1319] eta: 0:08:18 lr: 7.891786571410098e-06 loss: 0.0333 (0.0350) time: 2.6413 data: 0.0059 max mem: 33369 +Epoch: [34] [1140/1319] eta: 0:07:52 lr: 7.881314609509776e-06 loss: 0.0328 (0.0351) time: 2.6253 data: 0.0060 max mem: 33369 +Epoch: [34] [1150/1319] eta: 0:07:25 lr: 7.870841101361268e-06 loss: 0.0314 (0.0351) time: 2.6251 data: 0.0059 max mem: 33369 +Epoch: [34] [1160/1319] eta: 0:06:59 lr: 7.860366044449406e-06 loss: 0.0311 (0.0351) time: 2.6081 data: 0.0059 max mem: 33369 +Epoch: [34] [1170/1319] eta: 0:06:32 lr: 7.849889436251218e-06 loss: 0.0311 (0.0351) time: 2.6161 data: 0.0059 max mem: 33369 +Epoch: [34] [1180/1319] eta: 0:06:06 lr: 7.839411274235871e-06 loss: 0.0311 (0.0351) time: 2.6325 data: 0.0060 max mem: 33369 +Epoch: [34] [1190/1319] eta: 0:05:40 lr: 7.82893155586463e-06 loss: 0.0321 (0.0351) time: 2.6398 data: 0.0060 max mem: 33369 +Epoch: [34] [1200/1319] eta: 0:05:13 lr: 7.818450278590844e-06 loss: 0.0346 (0.0351) time: 2.6372 data: 0.0058 max mem: 33369 +Epoch: [34] [1210/1319] eta: 0:04:47 lr: 7.80796743985987e-06 loss: 0.0334 (0.0351) time: 2.6501 data: 0.0059 max mem: 33369 +Epoch: [34] [1220/1319] eta: 0:04:21 lr: 7.797483037109084e-06 loss: 0.0316 (0.0351) time: 2.6421 data: 0.0058 max mem: 33369 +Epoch: [34] [1230/1319] eta: 0:03:54 lr: 7.786997067767811e-06 loss: 0.0308 (0.0350) time: 2.6259 data: 0.0060 max mem: 33369 +Epoch: [34] [1240/1319] eta: 0:03:28 lr: 7.776509529257303e-06 loss: 0.0311 (0.0350) time: 2.6463 data: 0.0060 max mem: 33369 +Epoch: [34] [1250/1319] eta: 0:03:01 lr: 7.766020418990693e-06 loss: 0.0303 (0.0350) time: 2.6256 data: 0.0059 max mem: 33369 +Epoch: [34] [1260/1319] eta: 0:02:35 lr: 7.755529734372952e-06 loss: 0.0290 (0.0350) time: 2.6208 data: 0.0058 max mem: 33369 +Epoch: [34] [1270/1319] eta: 0:02:09 lr: 7.74503747280087e-06 loss: 0.0323 (0.0350) time: 2.6373 data: 0.0059 max mem: 33369 +Epoch: [34] [1280/1319] eta: 0:01:42 lr: 7.734543631663006e-06 loss: 0.0328 (0.0351) time: 2.6577 data: 0.0061 max mem: 33369 +Epoch: [34] [1290/1319] eta: 0:01:16 lr: 7.724048208339646e-06 loss: 0.0338 (0.0351) time: 2.6505 data: 0.0062 max mem: 33369 +Epoch: [34] [1300/1319] eta: 0:00:50 lr: 7.713551200202774e-06 loss: 0.0314 (0.0350) time: 2.6242 data: 0.0060 max mem: 33369 +Epoch: [34] [1310/1319] eta: 0:00:23 lr: 7.703052604616029e-06 loss: 0.0317 (0.0350) time: 2.6440 data: 0.0058 max mem: 33369 +Epoch: [34] Total time: 0:57:58 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 2:10:42 time: 3.0481 data: 2.9617 max mem: 33369 +Test: [ 100/2573] eta: 0:04:10 time: 0.0717 data: 0.0011 max mem: 33369 +Test: [ 200/2573] eta: 0:03:28 time: 0.0735 data: 0.0011 max mem: 33369 +Test: [ 300/2573] eta: 0:03:07 time: 0.0751 data: 0.0012 max mem: 33369 +Test: [ 400/2573] eta: 0:02:54 time: 0.0751 data: 0.0011 max mem: 33369 +Test: [ 500/2573] eta: 0:02:43 time: 0.0735 data: 0.0011 max mem: 33369 +Test: [ 600/2573] eta: 0:02:34 time: 0.0735 data: 0.0011 max mem: 33369 +Test: [ 700/2573] eta: 0:02:25 time: 0.0735 data: 0.0011 max mem: 33369 +Test: [ 800/2573] eta: 0:02:17 time: 0.0771 data: 0.0011 max mem: 33369 +Test: [ 900/2573] eta: 0:02:09 time: 0.0737 data: 0.0011 max mem: 33369 +Test: [1000/2573] eta: 0:02:00 time: 0.0738 data: 0.0011 max mem: 33369 +Test: [1100/2573] eta: 0:01:52 time: 0.0738 data: 0.0011 max mem: 33369 +Test: [1200/2573] eta: 0:01:44 time: 0.0738 data: 0.0011 max mem: 33369 +Test: [1300/2573] eta: 0:01:37 time: 0.0738 data: 0.0011 max mem: 33369 +Test: [1400/2573] eta: 0:01:29 time: 0.0722 data: 0.0011 max mem: 33369 +Test: [1500/2573] eta: 0:01:21 time: 0.0738 data: 0.0011 max mem: 33369 +Test: [1600/2573] eta: 0:01:13 time: 0.0772 data: 0.0011 max mem: 33369 +Test: [1700/2573] eta: 0:01:06 time: 0.0722 data: 0.0011 max mem: 33369 +Test: [1800/2573] eta: 0:00:58 time: 0.0756 data: 0.0011 max mem: 33369 +Test: [1900/2573] eta: 0:00:50 time: 0.0722 data: 0.0011 max mem: 33369 +Test: [2000/2573] eta: 0:00:43 time: 0.0738 data: 0.0011 max mem: 33369 +Test: [2100/2573] eta: 0:00:35 time: 0.0755 data: 0.0011 max mem: 33369 +Test: [2200/2573] eta: 0:00:28 time: 0.0756 data: 0.0011 max mem: 33369 +Test: [2300/2573] eta: 0:00:20 time: 0.0756 data: 0.0011 max mem: 33369 +Test: [2400/2573] eta: 0:00:12 time: 0.0705 data: 0.0011 max mem: 33369 +Test: [2500/2573] eta: 0:00:05 time: 0.0738 data: 0.0011 max mem: 33369 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: Total time: 0:03:13 +Final results: +Mean IoU is 64.66 + + precision@0.5 = 72.67 + precision@0.6 = 67.57 + precision@0.7 = 61.23 + precision@0.8 = 50.69 + precision@0.9 = 25.76 + overall IoU = 61.84 + +Average object IoU 64.66367250657171 +Overall IoU 61.83515167236328 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [35] [ 0/1319] eta: 3:13:30 lr: 7.693602509132593e-06 loss: 0.0381 (0.0381) time: 8.8022 data: 1.6265 max mem: 33369 +Epoch: [35] [ 10/1319] eta: 1:09:15 lr: 7.683100890097833e-06 loss: 0.0314 (0.0310) time: 3.1744 data: 0.1537 max mem: 33369 +Epoch: [35] [ 20/1319] eta: 1:03:26 lr: 7.67259767592017e-06 loss: 0.0314 (0.0328) time: 2.6366 data: 0.0059 max mem: 33369 +Epoch: [35] [ 30/1319] eta: 1:00:46 lr: 7.66209286393032e-06 loss: 0.0332 (0.0341) time: 2.6386 data: 0.0060 max mem: 33369 +Epoch: [35] [ 40/1319] eta: 0:59:15 lr: 7.651586451450453e-06 loss: 0.0354 (0.0372) time: 2.6224 data: 0.0064 max mem: 33369 +Epoch: [35] [ 50/1319] eta: 0:58:07 lr: 7.641078435794154e-06 loss: 0.0322 (0.0369) time: 2.6242 data: 0.0062 max mem: 33369 +Epoch: [35] [ 60/1319] eta: 0:57:31 lr: 7.630568814266394e-06 loss: 0.0322 (0.0369) time: 2.6631 data: 0.0060 max mem: 33369 +Epoch: [35] [ 70/1319] eta: 0:56:41 lr: 7.62005758416347e-06 loss: 0.0359 (0.0368) time: 2.6581 data: 0.0060 max mem: 33369 +Epoch: [35] [ 80/1319] eta: 0:55:56 lr: 7.609544742772985e-06 loss: 0.0349 (0.0364) time: 2.6103 data: 0.0062 max mem: 33369 +Epoch: [35] [ 90/1319] eta: 0:55:22 lr: 7.599030287373793e-06 loss: 0.0340 (0.0368) time: 2.6348 data: 0.0061 max mem: 33369 +Epoch: [35] [ 100/1319] eta: 0:54:45 lr: 7.588514215235963e-06 loss: 0.0317 (0.0363) time: 2.6393 data: 0.0060 max mem: 33369 +Epoch: [35] [ 110/1319] eta: 0:54:15 lr: 7.5779965236207366e-06 loss: 0.0279 (0.0359) time: 2.6408 data: 0.0060 max mem: 33369 +Epoch: [35] [ 120/1319] eta: 0:53:40 lr: 7.5674772097804864e-06 loss: 0.0310 (0.0358) time: 2.6393 data: 0.0060 max mem: 33369 +Epoch: [35] [ 130/1319] eta: 0:53:08 lr: 7.556956270958658e-06 loss: 0.0287 (0.0353) time: 2.6245 data: 0.0060 max mem: 33369 +Epoch: [35] [ 140/1319] eta: 0:52:35 lr: 7.546433704389756e-06 loss: 0.0255 (0.0348) time: 2.6181 data: 0.0061 max mem: 33369 +Epoch: [35] [ 150/1319] eta: 0:52:05 lr: 7.535909507299282e-06 loss: 0.0261 (0.0344) time: 2.6191 data: 0.0062 max mem: 33369 +Epoch: [35] [ 160/1319] eta: 0:51:36 lr: 7.525383676903694e-06 loss: 0.0295 (0.0343) time: 2.6370 data: 0.0063 max mem: 33369 +Epoch: [35] [ 170/1319] eta: 0:51:09 lr: 7.514856210410369e-06 loss: 0.0300 (0.0340) time: 2.6514 data: 0.0062 max mem: 33369 +Epoch: [35] [ 180/1319] eta: 0:50:40 lr: 7.504327105017539e-06 loss: 0.0298 (0.0338) time: 2.6527 data: 0.0060 max mem: 33369 +Epoch: [35] [ 190/1319] eta: 0:50:13 lr: 7.493796357914276e-06 loss: 0.0285 (0.0337) time: 2.6507 data: 0.0059 max mem: 33369 +Epoch: [35] [ 200/1319] eta: 0:49:45 lr: 7.483263966280434e-06 loss: 0.0316 (0.0337) time: 2.6523 data: 0.0061 max mem: 33369 +Epoch: [35] [ 210/1319] eta: 0:49:15 lr: 7.4727299272865964e-06 loss: 0.0356 (0.0339) time: 2.6312 data: 0.0061 max mem: 33369 +Epoch: [35] [ 220/1319] eta: 0:48:45 lr: 7.462194238094052e-06 loss: 0.0364 (0.0339) time: 2.6073 data: 0.0061 max mem: 33369 +Epoch: [35] [ 230/1319] eta: 0:48:22 lr: 7.4516568958547115e-06 loss: 0.0314 (0.0340) time: 2.6610 data: 0.0062 max mem: 33369 +Epoch: [35] [ 240/1319] eta: 0:47:54 lr: 7.4411178977111085e-06 loss: 0.0292 (0.0339) time: 2.6880 data: 0.0061 max mem: 33369 +Epoch: [35] [ 250/1319] eta: 0:47:26 lr: 7.430577240796325e-06 loss: 0.0275 (0.0337) time: 2.6343 data: 0.0059 max mem: 33369 +Epoch: [35] [ 260/1319] eta: 0:46:59 lr: 7.420034922233955e-06 loss: 0.0292 (0.0337) time: 2.6341 data: 0.0059 max mem: 33369 +Epoch: [35] [ 270/1319] eta: 0:46:32 lr: 7.4094909391380505e-06 loss: 0.0313 (0.0339) time: 2.6516 data: 0.0060 max mem: 33369 +Epoch: [35] [ 280/1319] eta: 0:46:05 lr: 7.398945288613088e-06 loss: 0.0333 (0.0339) time: 2.6514 data: 0.0059 max mem: 33369 +Epoch: [35] [ 290/1319] eta: 0:45:36 lr: 7.388397967753893e-06 loss: 0.0371 (0.0342) time: 2.6256 data: 0.0058 max mem: 33369 +Epoch: [35] [ 300/1319] eta: 0:45:10 lr: 7.3778489736456335e-06 loss: 0.0381 (0.0342) time: 2.6443 data: 0.0060 max mem: 33369 +Epoch: [35] [ 310/1319] eta: 0:44:44 lr: 7.367298303363743e-06 loss: 0.0327 (0.0345) time: 2.6728 data: 0.0060 max mem: 33369 +Epoch: [35] [ 320/1319] eta: 0:44:16 lr: 7.35674595397388e-06 loss: 0.0292 (0.0344) time: 2.6363 data: 0.0059 max mem: 33369 +Epoch: [35] [ 330/1319] eta: 0:43:48 lr: 7.34619192253189e-06 loss: 0.0249 (0.0343) time: 2.6234 data: 0.0060 max mem: 33369 +Epoch: [35] [ 340/1319] eta: 0:43:20 lr: 7.335636206083729e-06 loss: 0.0322 (0.0344) time: 2.6241 data: 0.0060 max mem: 33369 +Epoch: [35] [ 350/1319] eta: 0:42:55 lr: 7.325078801665445e-06 loss: 0.0354 (0.0343) time: 2.6547 data: 0.0059 max mem: 33369 +Epoch: [35] [ 360/1319] eta: 0:42:28 lr: 7.31451970630312e-06 loss: 0.0306 (0.0344) time: 2.6726 data: 0.0058 max mem: 33369 +Epoch: [35] [ 370/1319] eta: 0:42:01 lr: 7.303958917012809e-06 loss: 0.0310 (0.0343) time: 2.6494 data: 0.0060 max mem: 33369 +Epoch: [35] [ 380/1319] eta: 0:41:34 lr: 7.293396430800509e-06 loss: 0.0310 (0.0345) time: 2.6367 data: 0.0061 max mem: 33369 +Epoch: [35] [ 390/1319] eta: 0:41:09 lr: 7.282832244662077e-06 loss: 0.0318 (0.0344) time: 2.6718 data: 0.0061 max mem: 33369 +Epoch: [35] [ 400/1319] eta: 0:40:42 lr: 7.272266355583221e-06 loss: 0.0328 (0.0346) time: 2.6742 data: 0.0062 max mem: 33369 +Epoch: [35] [ 410/1319] eta: 0:40:15 lr: 7.261698760539424e-06 loss: 0.0331 (0.0346) time: 2.6430 data: 0.0062 max mem: 33369 +Epoch: [35] [ 420/1319] eta: 0:39:48 lr: 7.2511294564958895e-06 loss: 0.0310 (0.0345) time: 2.6512 data: 0.0061 max mem: 33369 +Epoch: [35] [ 430/1319] eta: 0:39:21 lr: 7.240558440407508e-06 loss: 0.0310 (0.0345) time: 2.6491 data: 0.0061 max mem: 33369 +Epoch: [35] [ 440/1319] eta: 0:38:54 lr: 7.229985709218795e-06 loss: 0.0290 (0.0344) time: 2.6421 data: 0.0060 max mem: 33369 +Epoch: [35] [ 450/1319] eta: 0:38:28 lr: 7.219411259863819e-06 loss: 0.0319 (0.0347) time: 2.6449 data: 0.0059 max mem: 33369 +Epoch: [35] [ 460/1319] eta: 0:38:01 lr: 7.208835089266191e-06 loss: 0.0345 (0.0346) time: 2.6443 data: 0.0058 max mem: 33369 +Epoch: [35] [ 470/1319] eta: 0:37:34 lr: 7.198257194338982e-06 loss: 0.0311 (0.0346) time: 2.6312 data: 0.0059 max mem: 33369 +Epoch: [35] [ 480/1319] eta: 0:37:08 lr: 7.187677571984675e-06 loss: 0.0295 (0.0346) time: 2.6551 data: 0.0060 max mem: 33369 +Epoch: [35] [ 490/1319] eta: 0:36:41 lr: 7.177096219095117e-06 loss: 0.0291 (0.0346) time: 2.6502 data: 0.0058 max mem: 33369 +Epoch: [35] [ 500/1319] eta: 0:36:14 lr: 7.166513132551446e-06 loss: 0.0299 (0.0346) time: 2.6516 data: 0.0058 max mem: 33369 +Epoch: [35] [ 510/1319] eta: 0:35:48 lr: 7.15592830922407e-06 loss: 0.0348 (0.0346) time: 2.6690 data: 0.0058 max mem: 33369 +Epoch: [35] [ 520/1319] eta: 0:35:21 lr: 7.145341745972588e-06 loss: 0.0347 (0.0347) time: 2.6517 data: 0.0058 max mem: 33369 +Epoch: [35] [ 530/1319] eta: 0:34:54 lr: 7.134753439645737e-06 loss: 0.0337 (0.0347) time: 2.6459 data: 0.0059 max mem: 33369 +Epoch: [35] [ 540/1319] eta: 0:34:28 lr: 7.124163387081344e-06 loss: 0.0273 (0.0346) time: 2.6582 data: 0.0060 max mem: 33369 +Epoch: [35] [ 550/1319] eta: 0:34:01 lr: 7.1135715851062684e-06 loss: 0.0328 (0.0346) time: 2.6518 data: 0.0060 max mem: 33369 +Epoch: [35] [ 560/1319] eta: 0:33:35 lr: 7.102978030536328e-06 loss: 0.0343 (0.0346) time: 2.6561 data: 0.0059 max mem: 33369 +Epoch: [35] [ 570/1319] eta: 0:33:09 lr: 7.092382720176277e-06 loss: 0.0362 (0.0348) time: 2.6714 data: 0.0059 max mem: 33369 +Epoch: [35] [ 580/1319] eta: 0:32:41 lr: 7.081785650819721e-06 loss: 0.0343 (0.0347) time: 2.6170 data: 0.0060 max mem: 33369 +Epoch: [35] [ 590/1319] eta: 0:32:15 lr: 7.071186819249069e-06 loss: 0.0306 (0.0347) time: 2.6172 data: 0.0059 max mem: 33369 +Epoch: [35] [ 600/1319] eta: 0:31:48 lr: 7.060586222235484e-06 loss: 0.0318 (0.0347) time: 2.6629 data: 0.0058 max mem: 33369 +Epoch: [35] [ 610/1319] eta: 0:31:21 lr: 7.049983856538794e-06 loss: 0.0318 (0.0347) time: 2.6506 data: 0.0061 max mem: 33369 +Epoch: [35] [ 620/1319] eta: 0:30:55 lr: 7.039379718907476e-06 loss: 0.0282 (0.0345) time: 2.6427 data: 0.0061 max mem: 33369 +Epoch: [35] [ 630/1319] eta: 0:30:28 lr: 7.0287738060785644e-06 loss: 0.0275 (0.0346) time: 2.6632 data: 0.0061 max mem: 33369 +Epoch: [35] [ 640/1319] eta: 0:30:02 lr: 7.018166114777613e-06 loss: 0.0308 (0.0346) time: 2.6556 data: 0.0060 max mem: 33369 +Epoch: [35] [ 650/1319] eta: 0:29:35 lr: 7.007556641718624e-06 loss: 0.0308 (0.0345) time: 2.6275 data: 0.0061 max mem: 33369 +Epoch: [35] [ 660/1319] eta: 0:29:08 lr: 6.9969453836039725e-06 loss: 0.0286 (0.0344) time: 2.6128 data: 0.0060 max mem: 33369 +Epoch: [35] [ 670/1319] eta: 0:28:41 lr: 6.986332337124384e-06 loss: 0.0286 (0.0344) time: 2.6257 data: 0.0058 max mem: 33369 +Epoch: [35] [ 680/1319] eta: 0:28:14 lr: 6.975717498958839e-06 loss: 0.0301 (0.0344) time: 2.6365 data: 0.0061 max mem: 33369 +Epoch: [35] [ 690/1319] eta: 0:27:48 lr: 6.965100865774533e-06 loss: 0.0323 (0.0344) time: 2.6282 data: 0.0060 max mem: 33369 +Epoch: [35] [ 700/1319] eta: 0:27:21 lr: 6.954482434226801e-06 loss: 0.0341 (0.0344) time: 2.6294 data: 0.0057 max mem: 33369 +Epoch: [35] [ 710/1319] eta: 0:26:54 lr: 6.9438622009590656e-06 loss: 0.0343 (0.0344) time: 2.6192 data: 0.0060 max mem: 33369 +Epoch: [35] [ 720/1319] eta: 0:26:27 lr: 6.933240162602753e-06 loss: 0.0320 (0.0344) time: 2.6173 data: 0.0060 max mem: 33369 +Epoch: [35] [ 730/1319] eta: 0:26:01 lr: 6.922616315777261e-06 loss: 0.0291 (0.0343) time: 2.6450 data: 0.0058 max mem: 33369 +Epoch: [35] [ 740/1319] eta: 0:25:34 lr: 6.911990657089877e-06 loss: 0.0291 (0.0343) time: 2.6564 data: 0.0059 max mem: 33369 +Epoch: [35] [ 750/1319] eta: 0:25:08 lr: 6.901363183135715e-06 loss: 0.0297 (0.0343) time: 2.6339 data: 0.0060 max mem: 33369 +Epoch: [35] [ 760/1319] eta: 0:24:41 lr: 6.890733890497658e-06 loss: 0.0323 (0.0343) time: 2.6220 data: 0.0058 max mem: 33369 +Epoch: [35] [ 770/1319] eta: 0:24:14 lr: 6.880102775746271e-06 loss: 0.0349 (0.0343) time: 2.6276 data: 0.0057 max mem: 33369 +Epoch: [35] [ 780/1319] eta: 0:23:48 lr: 6.869469835439768e-06 loss: 0.0340 (0.0343) time: 2.6168 data: 0.0059 max mem: 33369 +Epoch: [35] [ 790/1319] eta: 0:23:21 lr: 6.858835066123928e-06 loss: 0.0311 (0.0343) time: 2.6317 data: 0.0060 max mem: 33369 +Epoch: [35] [ 800/1319] eta: 0:22:54 lr: 6.848198464332027e-06 loss: 0.0311 (0.0343) time: 2.6322 data: 0.0059 max mem: 33369 +Epoch: [35] [ 810/1319] eta: 0:22:28 lr: 6.837560026584784e-06 loss: 0.0328 (0.0343) time: 2.6112 data: 0.0060 max mem: 33369 +Epoch: [35] [ 820/1319] eta: 0:22:01 lr: 6.826919749390266e-06 loss: 0.0357 (0.0344) time: 2.6171 data: 0.0059 max mem: 33369 +Epoch: [35] [ 830/1319] eta: 0:21:34 lr: 6.816277629243854e-06 loss: 0.0329 (0.0344) time: 2.6103 data: 0.0058 max mem: 33369 +Epoch: [35] [ 840/1319] eta: 0:21:07 lr: 6.805633662628158e-06 loss: 0.0321 (0.0344) time: 2.6038 data: 0.0059 max mem: 33369 +Epoch: [35] [ 850/1319] eta: 0:20:41 lr: 6.794987846012945e-06 loss: 0.0341 (0.0344) time: 2.6103 data: 0.0059 max mem: 33369 +Epoch: [35] [ 860/1319] eta: 0:20:14 lr: 6.784340175855078e-06 loss: 0.0316 (0.0344) time: 2.6212 data: 0.0060 max mem: 33369 +Epoch: [35] [ 870/1319] eta: 0:19:47 lr: 6.7736906485984466e-06 loss: 0.0272 (0.0343) time: 2.5988 data: 0.0062 max mem: 33369 +Epoch: [35] [ 880/1319] eta: 0:19:21 lr: 6.763039260673876e-06 loss: 0.0245 (0.0342) time: 2.6075 data: 0.0061 max mem: 33369 +Epoch: [35] [ 890/1319] eta: 0:18:55 lr: 6.752386008499089e-06 loss: 0.0247 (0.0342) time: 2.6451 data: 0.0059 max mem: 33369 +Epoch: [35] [ 900/1319] eta: 0:18:28 lr: 6.741730888478615e-06 loss: 0.0276 (0.0342) time: 2.6265 data: 0.0061 max mem: 33369 +Epoch: [35] [ 910/1319] eta: 0:18:01 lr: 6.7310738970037205e-06 loss: 0.0316 (0.0342) time: 2.6129 data: 0.0060 max mem: 33369 +Epoch: [35] [ 920/1319] eta: 0:17:35 lr: 6.7204150304523424e-06 loss: 0.0295 (0.0341) time: 2.6094 data: 0.0058 max mem: 33369 +Epoch: [35] [ 930/1319] eta: 0:17:08 lr: 6.709754285188997e-06 loss: 0.0306 (0.0342) time: 2.6147 data: 0.0058 max mem: 33369 +Epoch: [35] [ 940/1319] eta: 0:16:42 lr: 6.699091657564736e-06 loss: 0.0375 (0.0343) time: 2.6191 data: 0.0058 max mem: 33369 +Epoch: [35] [ 950/1319] eta: 0:16:15 lr: 6.688427143917049e-06 loss: 0.0299 (0.0342) time: 2.6330 data: 0.0058 max mem: 33369 +Epoch: [35] [ 960/1319] eta: 0:15:49 lr: 6.677760740569799e-06 loss: 0.0285 (0.0342) time: 2.6426 data: 0.0057 max mem: 33369 +Epoch: [35] [ 970/1319] eta: 0:15:22 lr: 6.667092443833153e-06 loss: 0.0322 (0.0342) time: 2.6471 data: 0.0057 max mem: 33369 +Epoch: [35] [ 980/1319] eta: 0:14:56 lr: 6.656422250003478e-06 loss: 0.0362 (0.0343) time: 2.6374 data: 0.0058 max mem: 33369 +Epoch: [35] [ 990/1319] eta: 0:14:29 lr: 6.645750155363307e-06 loss: 0.0306 (0.0342) time: 2.6080 data: 0.0062 max mem: 33369 +Epoch: [35] [1000/1319] eta: 0:14:03 lr: 6.635076156181232e-06 loss: 0.0306 (0.0343) time: 2.5888 data: 0.0060 max mem: 33369 +Epoch: [35] [1010/1319] eta: 0:13:36 lr: 6.624400248711836e-06 loss: 0.0370 (0.0344) time: 2.6231 data: 0.0057 max mem: 33369 +Epoch: [35] [1020/1319] eta: 0:13:10 lr: 6.613722429195618e-06 loss: 0.0334 (0.0343) time: 2.6318 data: 0.0058 max mem: 33369 +Epoch: [35] [1030/1319] eta: 0:12:43 lr: 6.603042693858916e-06 loss: 0.0346 (0.0343) time: 2.6008 data: 0.0059 max mem: 33369 +Epoch: [35] [1040/1319] eta: 0:12:17 lr: 6.5923610389138055e-06 loss: 0.0356 (0.0343) time: 2.6167 data: 0.0060 max mem: 33369 +Epoch: [35] [1050/1319] eta: 0:11:50 lr: 6.581677460558057e-06 loss: 0.0297 (0.0343) time: 2.6329 data: 0.0059 max mem: 33369 +Epoch: [35] [1060/1319] eta: 0:11:24 lr: 6.570991954975031e-06 loss: 0.0314 (0.0343) time: 2.6453 data: 0.0059 max mem: 33369 +Epoch: [35] [1070/1319] eta: 0:10:57 lr: 6.560304518333606e-06 loss: 0.0314 (0.0343) time: 2.6570 data: 0.0060 max mem: 33369 +Epoch: [35] [1080/1319] eta: 0:10:31 lr: 6.549615146788095e-06 loss: 0.0314 (0.0343) time: 2.6650 data: 0.0059 max mem: 33369 +Epoch: [35] [1090/1319] eta: 0:10:05 lr: 6.538923836478152e-06 loss: 0.0301 (0.0342) time: 2.6268 data: 0.0058 max mem: 33369 +Epoch: [35] [1100/1319] eta: 0:09:38 lr: 6.528230583528713e-06 loss: 0.0301 (0.0342) time: 2.6081 data: 0.0059 max mem: 33369 +Epoch: [35] [1110/1319] eta: 0:09:12 lr: 6.5175353840499016e-06 loss: 0.0357 (0.0342) time: 2.6238 data: 0.0059 max mem: 33369 +Epoch: [35] [1120/1319] eta: 0:08:45 lr: 6.506838234136938e-06 loss: 0.0348 (0.0342) time: 2.6296 data: 0.0059 max mem: 33369 +Epoch: [35] [1130/1319] eta: 0:08:19 lr: 6.4961391298700616e-06 loss: 0.0279 (0.0342) time: 2.6507 data: 0.0059 max mem: 33369 +Epoch: [35] [1140/1319] eta: 0:07:52 lr: 6.485438067314456e-06 loss: 0.0295 (0.0342) time: 2.6458 data: 0.0059 max mem: 33369 +Epoch: [35] [1150/1319] eta: 0:07:26 lr: 6.4747350425201315e-06 loss: 0.0296 (0.0342) time: 2.5997 data: 0.0060 max mem: 33369 +Epoch: [35] [1160/1319] eta: 0:06:59 lr: 6.464030051521878e-06 loss: 0.0313 (0.0342) time: 2.6087 data: 0.0060 max mem: 33369 +Epoch: [35] [1170/1319] eta: 0:06:33 lr: 6.453323090339156e-06 loss: 0.0276 (0.0341) time: 2.6287 data: 0.0058 max mem: 33369 +Epoch: [35] [1180/1319] eta: 0:06:07 lr: 6.442614154976011e-06 loss: 0.0273 (0.0341) time: 2.6165 data: 0.0058 max mem: 33369 +Epoch: [35] [1190/1319] eta: 0:05:40 lr: 6.431903241420996e-06 loss: 0.0283 (0.0341) time: 2.6111 data: 0.0058 max mem: 33369 +Epoch: [35] [1200/1319] eta: 0:05:14 lr: 6.4211903456470515e-06 loss: 0.0286 (0.0341) time: 2.6128 data: 0.0058 max mem: 33369 +Epoch: [35] [1210/1319] eta: 0:04:47 lr: 6.410475463611462e-06 loss: 0.0303 (0.0341) time: 2.6392 data: 0.0059 max mem: 33369 +Epoch: [35] [1220/1319] eta: 0:04:21 lr: 6.399758591255733e-06 loss: 0.0369 (0.0341) time: 2.6284 data: 0.0060 max mem: 33369 +Epoch: [35] [1230/1319] eta: 0:03:54 lr: 6.389039724505507e-06 loss: 0.0345 (0.0341) time: 2.6152 data: 0.0059 max mem: 33369 +Epoch: [35] [1240/1319] eta: 0:03:28 lr: 6.378318859270487e-06 loss: 0.0304 (0.0341) time: 2.6451 data: 0.0057 max mem: 33369 +Epoch: [35] [1250/1319] eta: 0:03:02 lr: 6.3675959914443046e-06 loss: 0.0312 (0.0341) time: 2.6371 data: 0.0057 max mem: 33369 +Epoch: [35] [1260/1319] eta: 0:02:35 lr: 6.356871116904475e-06 loss: 0.0334 (0.0342) time: 2.6256 data: 0.0059 max mem: 33369 +Epoch: [35] [1270/1319] eta: 0:02:09 lr: 6.34614423151228e-06 loss: 0.0334 (0.0341) time: 2.6510 data: 0.0059 max mem: 33369 +Epoch: [35] [1280/1319] eta: 0:01:42 lr: 6.335415331112665e-06 loss: 0.0306 (0.0341) time: 2.6569 data: 0.0058 max mem: 33369 +Epoch: [35] [1290/1319] eta: 0:01:16 lr: 6.324684411534165e-06 loss: 0.0339 (0.0342) time: 2.6540 data: 0.0059 max mem: 33369 +Epoch: [35] [1300/1319] eta: 0:00:50 lr: 6.313951468588795e-06 loss: 0.0339 (0.0342) time: 2.6408 data: 0.0058 max mem: 33369 +Epoch: [35] [1310/1319] eta: 0:00:23 lr: 6.3032164980719415e-06 loss: 0.0355 (0.0342) time: 2.6140 data: 0.0058 max mem: 33369 +Epoch: [35] Total time: 0:58:02 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 2:22:08 time: 3.3146 data: 3.2223 max mem: 33369 +Test: [ 100/2573] eta: 0:04:17 time: 0.0715 data: 0.0011 max mem: 33369 +Test: [ 200/2573] eta: 0:03:31 time: 0.0735 data: 0.0011 max mem: 33369 +Test: [ 300/2573] eta: 0:03:09 time: 0.0750 data: 0.0011 max mem: 33369 +Test: [ 400/2573] eta: 0:02:55 time: 0.0750 data: 0.0011 max mem: 33369 +Test: [ 500/2573] eta: 0:02:44 time: 0.0734 data: 0.0011 max mem: 33369 +Test: [ 600/2573] eta: 0:02:34 time: 0.0735 data: 0.0011 max mem: 33369 +Test: [ 700/2573] eta: 0:02:26 time: 0.0737 data: 0.0011 max mem: 33369 +Test: [ 800/2573] eta: 0:02:17 time: 0.0771 data: 0.0011 max mem: 33369 +Test: [ 900/2573] eta: 0:02:09 time: 0.0737 data: 0.0011 max mem: 33369 +Test: [1000/2573] eta: 0:02:01 time: 0.0738 data: 0.0011 max mem: 33369 +Test: [1100/2573] eta: 0:01:53 time: 0.0738 data: 0.0011 max mem: 33369 +Test: [1200/2573] eta: 0:01:45 time: 0.0738 data: 0.0011 max mem: 33369 +Test: [1300/2573] eta: 0:01:37 time: 0.0739 data: 0.0011 max mem: 33369 +Test: [1400/2573] eta: 0:01:29 time: 0.0722 data: 0.0011 max mem: 33369 +Test: [1500/2573] eta: 0:01:21 time: 0.0738 data: 0.0011 max mem: 33369 +Test: [1600/2573] eta: 0:01:13 time: 0.0772 data: 0.0012 max mem: 33369 +Test: [1700/2573] eta: 0:01:06 time: 0.0721 data: 0.0010 max mem: 33369 +Test: [1800/2573] eta: 0:00:58 time: 0.0754 data: 0.0011 max mem: 33369 +Test: [1900/2573] eta: 0:00:50 time: 0.0723 data: 0.0011 max mem: 33369 +Test: [2000/2573] eta: 0:00:43 time: 0.0739 data: 0.0012 max mem: 33369 +Test: [2100/2573] eta: 0:00:35 time: 0.0756 data: 0.0011 max mem: 33369 +Test: [2200/2573] eta: 0:00:28 time: 0.0755 data: 0.0011 max mem: 33369 +Test: [2300/2573] eta: 0:00:20 time: 0.0756 data: 0.0011 max mem: 33369 +Test: [2400/2573] eta: 0:00:12 time: 0.0705 data: 0.0011 max mem: 33369 +Test: [2500/2573] eta: 0:00:05 time: 0.0739 data: 0.0012 max mem: 33369 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: Total time: 0:03:13 +Final results: +Mean IoU is 64.95 + + precision@0.5 = 73.12 + precision@0.6 = 67.87 + precision@0.7 = 61.58 + precision@0.8 = 50.55 + precision@0.9 = 26.31 + overall IoU = 61.92 + +Average object IoU 64.95260292118255 +Overall IoU 61.92367172241211 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [36] [ 0/1319] eta: 3:11:44 lr: 6.293553287544593e-06 loss: 0.0312 (0.0312) time: 8.7218 data: 1.6147 max mem: 33369 +Epoch: [36] [ 10/1319] eta: 1:09:13 lr: 6.282814452998321e-06 loss: 0.0319 (0.0396) time: 3.1730 data: 0.1525 max mem: 33369 +Epoch: [36] [ 20/1319] eta: 1:03:37 lr: 6.2720735785923675e-06 loss: 0.0320 (0.0402) time: 2.6499 data: 0.0059 max mem: 33369 +Epoch: [36] [ 30/1319] eta: 1:01:12 lr: 6.261330660056396e-06 loss: 0.0328 (0.0383) time: 2.6712 data: 0.0060 max mem: 33369 +Epoch: [36] [ 40/1319] eta: 0:59:38 lr: 6.250585693102968e-06 loss: 0.0386 (0.0387) time: 2.6490 data: 0.0064 max mem: 33369 +Epoch: [36] [ 50/1319] eta: 0:58:25 lr: 6.2398386734274585e-06 loss: 0.0363 (0.0381) time: 2.6269 data: 0.0062 max mem: 33369 +Epoch: [36] [ 60/1319] eta: 0:57:28 lr: 6.229089596707912e-06 loss: 0.0297 (0.0367) time: 2.6194 data: 0.0061 max mem: 33369 +Epoch: [36] [ 70/1319] eta: 0:56:32 lr: 6.218338458604991e-06 loss: 0.0273 (0.0357) time: 2.5981 data: 0.0062 max mem: 33369 +Epoch: [36] [ 80/1319] eta: 0:55:43 lr: 6.207585254761843e-06 loss: 0.0281 (0.0352) time: 2.5751 data: 0.0061 max mem: 33369 +Epoch: [36] [ 90/1319] eta: 0:55:03 lr: 6.196829980804001e-06 loss: 0.0304 (0.0346) time: 2.5898 data: 0.0060 max mem: 33369 +Epoch: [36] [ 100/1319] eta: 0:54:32 lr: 6.1860726323392754e-06 loss: 0.0304 (0.0344) time: 2.6295 data: 0.0061 max mem: 33369 +Epoch: [36] [ 110/1319] eta: 0:54:01 lr: 6.175313204957665e-06 loss: 0.0355 (0.0352) time: 2.6490 data: 0.0062 max mem: 33369 +Epoch: [36] [ 120/1319] eta: 0:53:28 lr: 6.164551694231212e-06 loss: 0.0361 (0.0352) time: 2.6284 data: 0.0062 max mem: 33369 +Epoch: [36] [ 130/1319] eta: 0:52:55 lr: 6.153788095713938e-06 loss: 0.0360 (0.0354) time: 2.6150 data: 0.0060 max mem: 33369 +Epoch: [36] [ 140/1319] eta: 0:52:23 lr: 6.143022404941713e-06 loss: 0.0360 (0.0352) time: 2.6112 data: 0.0062 max mem: 33369 +Epoch: [36] [ 150/1319] eta: 0:51:52 lr: 6.132254617432146e-06 loss: 0.0282 (0.0350) time: 2.6079 data: 0.0063 max mem: 33369 +Epoch: [36] [ 160/1319] eta: 0:51:23 lr: 6.121484728684484e-06 loss: 0.0303 (0.0352) time: 2.6185 data: 0.0061 max mem: 33369 +Epoch: [36] [ 170/1319] eta: 0:50:56 lr: 6.110712734179475e-06 loss: 0.0294 (0.0348) time: 2.6395 data: 0.0061 max mem: 33369 +Epoch: [36] [ 180/1319] eta: 0:50:28 lr: 6.099938629379293e-06 loss: 0.0276 (0.0346) time: 2.6438 data: 0.0060 max mem: 33369 +Epoch: [36] [ 190/1319] eta: 0:49:58 lr: 6.0891624097274035e-06 loss: 0.0284 (0.0345) time: 2.6183 data: 0.0060 max mem: 33369 +Epoch: [36] [ 200/1319] eta: 0:49:32 lr: 6.07838407064845e-06 loss: 0.0302 (0.0344) time: 2.6364 data: 0.0061 max mem: 33369 +Epoch: [36] [ 210/1319] eta: 0:49:05 lr: 6.067603607548146e-06 loss: 0.0302 (0.0341) time: 2.6585 data: 0.0061 max mem: 33369 +Epoch: [36] [ 220/1319] eta: 0:48:34 lr: 6.05682101581314e-06 loss: 0.0322 (0.0342) time: 2.6038 data: 0.0060 max mem: 33369 +Epoch: [36] [ 230/1319] eta: 0:48:05 lr: 6.0460362908109285e-06 loss: 0.0327 (0.0341) time: 2.5833 data: 0.0060 max mem: 33369 +Epoch: [36] [ 240/1319] eta: 0:47:39 lr: 6.035249427889721e-06 loss: 0.0302 (0.0340) time: 2.6309 data: 0.0058 max mem: 33369 +Epoch: [36] [ 250/1319] eta: 0:47:11 lr: 6.024460422378318e-06 loss: 0.0293 (0.0339) time: 2.6445 data: 0.0059 max mem: 33369 +Epoch: [36] [ 260/1319] eta: 0:46:43 lr: 6.013669269586002e-06 loss: 0.0315 (0.0338) time: 2.6204 data: 0.0058 max mem: 33369 +Epoch: [36] [ 270/1319] eta: 0:46:17 lr: 6.002875964802412e-06 loss: 0.0335 (0.0339) time: 2.6253 data: 0.0060 max mem: 33369 +Epoch: [36] [ 280/1319] eta: 0:45:50 lr: 5.992080503297408e-06 loss: 0.0327 (0.0338) time: 2.6372 data: 0.0061 max mem: 33369 +Epoch: [36] [ 290/1319] eta: 0:45:22 lr: 5.981282880320978e-06 loss: 0.0291 (0.0338) time: 2.6306 data: 0.0061 max mem: 33369 +Epoch: [36] [ 300/1319] eta: 0:44:55 lr: 5.97048309110309e-06 loss: 0.0335 (0.0340) time: 2.6239 data: 0.0061 max mem: 33369 +Epoch: [36] [ 310/1319] eta: 0:44:29 lr: 5.959681130853577e-06 loss: 0.0318 (0.0339) time: 2.6358 data: 0.0058 max mem: 33369 +Epoch: [36] [ 320/1319] eta: 0:44:03 lr: 5.948876994762015e-06 loss: 0.0278 (0.0338) time: 2.6536 data: 0.0059 max mem: 33369 +Epoch: [36] [ 330/1319] eta: 0:43:34 lr: 5.938070677997572e-06 loss: 0.0313 (0.0339) time: 2.6200 data: 0.0060 max mem: 33369 +Epoch: [36] [ 340/1319] eta: 0:43:07 lr: 5.927262175708919e-06 loss: 0.0372 (0.0340) time: 2.5905 data: 0.0061 max mem: 33369 +Epoch: [36] [ 350/1319] eta: 0:42:39 lr: 5.916451483024071e-06 loss: 0.0390 (0.0341) time: 2.6039 data: 0.0061 max mem: 33369 +Epoch: [36] [ 360/1319] eta: 0:42:12 lr: 5.905638595050271e-06 loss: 0.0373 (0.0342) time: 2.6117 data: 0.0060 max mem: 33369 +Epoch: [36] [ 370/1319] eta: 0:41:46 lr: 5.894823506873858e-06 loss: 0.0344 (0.0343) time: 2.6244 data: 0.0058 max mem: 33369 +Epoch: [36] [ 380/1319] eta: 0:41:19 lr: 5.884006213560114e-06 loss: 0.0364 (0.0344) time: 2.6273 data: 0.0059 max mem: 33369 +Epoch: [36] [ 390/1319] eta: 0:40:52 lr: 5.873186710153169e-06 loss: 0.0339 (0.0346) time: 2.6152 data: 0.0061 max mem: 33369 +Epoch: [36] [ 400/1319] eta: 0:40:25 lr: 5.862364991675836e-06 loss: 0.0314 (0.0345) time: 2.6173 data: 0.0059 max mem: 33369 +Epoch: [36] [ 410/1319] eta: 0:39:58 lr: 5.85154105312949e-06 loss: 0.0304 (0.0344) time: 2.6151 data: 0.0059 max mem: 33369 +Epoch: [36] [ 420/1319] eta: 0:39:32 lr: 5.840714889493923e-06 loss: 0.0304 (0.0344) time: 2.6274 data: 0.0059 max mem: 33369 +Epoch: [36] [ 430/1319] eta: 0:39:04 lr: 5.829886495727219e-06 loss: 0.0289 (0.0345) time: 2.6264 data: 0.0059 max mem: 33369 +Epoch: [36] [ 440/1319] eta: 0:38:38 lr: 5.819055866765587e-06 loss: 0.0313 (0.0344) time: 2.6130 data: 0.0059 max mem: 33369 +Epoch: [36] [ 450/1319] eta: 0:38:11 lr: 5.808222997523256e-06 loss: 0.0349 (0.0344) time: 2.6277 data: 0.0059 max mem: 33369 +Epoch: [36] [ 460/1319] eta: 0:37:44 lr: 5.797387882892317e-06 loss: 0.0311 (0.0343) time: 2.6198 data: 0.0060 max mem: 33369 +Epoch: [36] [ 470/1319] eta: 0:37:18 lr: 5.786550517742576e-06 loss: 0.0298 (0.0343) time: 2.6106 data: 0.0059 max mem: 33369 +Epoch: [36] [ 480/1319] eta: 0:36:52 lr: 5.775710896921423e-06 loss: 0.0298 (0.0342) time: 2.6389 data: 0.0059 max mem: 33369 +Epoch: [36] [ 490/1319] eta: 0:36:26 lr: 5.764869015253661e-06 loss: 0.0309 (0.0343) time: 2.6591 data: 0.0059 max mem: 33369 +Epoch: [36] [ 500/1319] eta: 0:35:59 lr: 5.7540248675414e-06 loss: 0.0291 (0.0343) time: 2.6303 data: 0.0061 max mem: 33369 +Epoch: [36] [ 510/1319] eta: 0:35:32 lr: 5.743178448563874e-06 loss: 0.0271 (0.0342) time: 2.5938 data: 0.0061 max mem: 33369 +Epoch: [36] [ 520/1319] eta: 0:35:05 lr: 5.732329753077314e-06 loss: 0.0271 (0.0345) time: 2.5943 data: 0.0060 max mem: 33369 +Epoch: [36] [ 530/1319] eta: 0:34:38 lr: 5.7214787758147914e-06 loss: 0.0302 (0.0345) time: 2.6142 data: 0.0058 max mem: 33369 +Epoch: [36] [ 540/1319] eta: 0:34:11 lr: 5.710625511486047e-06 loss: 0.0354 (0.0346) time: 2.6060 data: 0.0058 max mem: 33369 +Epoch: [36] [ 550/1319] eta: 0:33:45 lr: 5.6997699547773765e-06 loss: 0.0325 (0.0345) time: 2.6003 data: 0.0060 max mem: 33369 +Epoch: [36] [ 560/1319] eta: 0:33:18 lr: 5.68891210035145e-06 loss: 0.0292 (0.0345) time: 2.6197 data: 0.0061 max mem: 33369 +Epoch: [36] [ 570/1319] eta: 0:32:52 lr: 5.678051942847162e-06 loss: 0.0318 (0.0345) time: 2.6292 data: 0.0060 max mem: 33369 +Epoch: [36] [ 580/1319] eta: 0:32:26 lr: 5.667189476879478e-06 loss: 0.0324 (0.0346) time: 2.6390 data: 0.0059 max mem: 33369 +Epoch: [36] [ 590/1319] eta: 0:31:59 lr: 5.656324697039277e-06 loss: 0.0324 (0.0346) time: 2.6469 data: 0.0061 max mem: 33369 +Epoch: [36] [ 600/1319] eta: 0:31:33 lr: 5.645457597893177e-06 loss: 0.0315 (0.0345) time: 2.6499 data: 0.0061 max mem: 33369 +Epoch: [36] [ 610/1319] eta: 0:31:07 lr: 5.634588173983401e-06 loss: 0.0293 (0.0345) time: 2.6359 data: 0.0059 max mem: 33369 +Epoch: [36] [ 620/1319] eta: 0:30:41 lr: 5.623716419827592e-06 loss: 0.0274 (0.0345) time: 2.6439 data: 0.0058 max mem: 33369 +Epoch: [36] [ 630/1319] eta: 0:30:14 lr: 5.612842329918665e-06 loss: 0.0257 (0.0344) time: 2.6476 data: 0.0059 max mem: 33369 +Epoch: [36] [ 640/1319] eta: 0:29:47 lr: 5.6019658987246355e-06 loss: 0.0290 (0.0343) time: 2.5992 data: 0.0059 max mem: 33369 +Epoch: [36] [ 650/1319] eta: 0:29:21 lr: 5.591087120688435e-06 loss: 0.0320 (0.0343) time: 2.5777 data: 0.0058 max mem: 33369 +Epoch: [36] [ 660/1319] eta: 0:28:54 lr: 5.5802059902277785e-06 loss: 0.0326 (0.0344) time: 2.6173 data: 0.0059 max mem: 33369 +Epoch: [36] [ 670/1319] eta: 0:28:28 lr: 5.569322501734972e-06 loss: 0.0347 (0.0344) time: 2.6429 data: 0.0059 max mem: 33369 +Epoch: [36] [ 680/1319] eta: 0:28:02 lr: 5.5584366495767425e-06 loss: 0.0347 (0.0344) time: 2.6489 data: 0.0059 max mem: 33369 +Epoch: [36] [ 690/1319] eta: 0:27:36 lr: 5.547548428094075e-06 loss: 0.0303 (0.0344) time: 2.6392 data: 0.0060 max mem: 33369 +Epoch: [36] [ 700/1319] eta: 0:27:09 lr: 5.536657831602032e-06 loss: 0.0357 (0.0345) time: 2.6046 data: 0.0060 max mem: 33369 +Epoch: [36] [ 710/1319] eta: 0:26:43 lr: 5.525764854389564e-06 loss: 0.0331 (0.0344) time: 2.6160 data: 0.0059 max mem: 33369 +Epoch: [36] [ 720/1319] eta: 0:26:16 lr: 5.514869490719365e-06 loss: 0.0314 (0.0344) time: 2.6324 data: 0.0059 max mem: 33369 +Epoch: [36] [ 730/1319] eta: 0:25:50 lr: 5.503971734827667e-06 loss: 0.0296 (0.0344) time: 2.6261 data: 0.0059 max mem: 33369 +Epoch: [36] [ 740/1319] eta: 0:25:24 lr: 5.493071580924068e-06 loss: 0.0277 (0.0343) time: 2.6279 data: 0.0057 max mem: 33369 +Epoch: [36] [ 750/1319] eta: 0:24:57 lr: 5.482169023191358e-06 loss: 0.0316 (0.0343) time: 2.6351 data: 0.0057 max mem: 33369 +Epoch: [36] [ 760/1319] eta: 0:24:31 lr: 5.471264055785306e-06 loss: 0.0299 (0.0344) time: 2.6330 data: 0.0060 max mem: 33369 +Epoch: [36] [ 770/1319] eta: 0:24:05 lr: 5.4603566728345144e-06 loss: 0.0292 (0.0343) time: 2.6292 data: 0.0060 max mem: 33369 +Epoch: [36] [ 780/1319] eta: 0:23:39 lr: 5.449446868440208e-06 loss: 0.0261 (0.0342) time: 2.6555 data: 0.0059 max mem: 33369 +Epoch: [36] [ 790/1319] eta: 0:23:12 lr: 5.43853463667605e-06 loss: 0.0317 (0.0342) time: 2.6465 data: 0.0059 max mem: 33369 +Epoch: [36] [ 800/1319] eta: 0:22:46 lr: 5.427619971587958e-06 loss: 0.0333 (0.0342) time: 2.6258 data: 0.0060 max mem: 33369 +Epoch: [36] [ 810/1319] eta: 0:22:20 lr: 5.416702867193884e-06 loss: 0.0312 (0.0342) time: 2.6441 data: 0.0059 max mem: 33369 +Epoch: [36] [ 820/1319] eta: 0:21:53 lr: 5.4057833174836655e-06 loss: 0.0296 (0.0342) time: 2.6274 data: 0.0059 max mem: 33369 +Epoch: [36] [ 830/1319] eta: 0:21:27 lr: 5.394861316418795e-06 loss: 0.0305 (0.0342) time: 2.6299 data: 0.0059 max mem: 33369 +Epoch: [36] [ 840/1319] eta: 0:21:01 lr: 5.383936857932236e-06 loss: 0.0335 (0.0342) time: 2.6537 data: 0.0059 max mem: 33369 +Epoch: [36] [ 850/1319] eta: 0:20:34 lr: 5.373009935928221e-06 loss: 0.0379 (0.0343) time: 2.6303 data: 0.0059 max mem: 33369 +Epoch: [36] [ 860/1319] eta: 0:20:08 lr: 5.362080544282056e-06 loss: 0.0333 (0.0343) time: 2.6218 data: 0.0059 max mem: 33369 +Epoch: [36] [ 870/1319] eta: 0:19:42 lr: 5.351148676839889e-06 loss: 0.0299 (0.0343) time: 2.6307 data: 0.0058 max mem: 33369 +Epoch: [36] [ 880/1319] eta: 0:19:15 lr: 5.340214327418554e-06 loss: 0.0299 (0.0343) time: 2.6259 data: 0.0058 max mem: 33369 +Epoch: [36] [ 890/1319] eta: 0:18:49 lr: 5.3292774898053224e-06 loss: 0.0296 (0.0342) time: 2.6426 data: 0.0058 max mem: 33369 +Epoch: [36] [ 900/1319] eta: 0:18:23 lr: 5.3183381577577165e-06 loss: 0.0296 (0.0342) time: 2.6455 data: 0.0058 max mem: 33369 +Epoch: [36] [ 910/1319] eta: 0:17:57 lr: 5.307396325003292e-06 loss: 0.0324 (0.0341) time: 2.6466 data: 0.0059 max mem: 33369 +Epoch: [36] [ 920/1319] eta: 0:17:30 lr: 5.296451985239408e-06 loss: 0.0264 (0.0341) time: 2.6622 data: 0.0058 max mem: 33369 +Epoch: [36] [ 930/1319] eta: 0:17:04 lr: 5.285505132133047e-06 loss: 0.0264 (0.0341) time: 2.6552 data: 0.0059 max mem: 33369 +Epoch: [36] [ 940/1319] eta: 0:16:38 lr: 5.274555759320574e-06 loss: 0.0263 (0.0341) time: 2.6593 data: 0.0060 max mem: 33369 +Epoch: [36] [ 950/1319] eta: 0:16:12 lr: 5.263603860407521e-06 loss: 0.0321 (0.0341) time: 2.6578 data: 0.0058 max mem: 33369 +Epoch: [36] [ 960/1319] eta: 0:15:45 lr: 5.252649428968377e-06 loss: 0.0357 (0.0342) time: 2.6554 data: 0.0058 max mem: 33369 +Epoch: [36] [ 970/1319] eta: 0:15:19 lr: 5.241692458546333e-06 loss: 0.0316 (0.0341) time: 2.6590 data: 0.0058 max mem: 33369 +Epoch: [36] [ 980/1319] eta: 0:14:53 lr: 5.230732942653104e-06 loss: 0.0304 (0.0341) time: 2.6609 data: 0.0058 max mem: 33369 +Epoch: [36] [ 990/1319] eta: 0:14:27 lr: 5.2197708747686676e-06 loss: 0.0323 (0.0341) time: 2.6592 data: 0.0058 max mem: 33369 +Epoch: [36] [1000/1319] eta: 0:14:00 lr: 5.208806248341044e-06 loss: 0.0283 (0.0341) time: 2.6457 data: 0.0058 max mem: 33369 +Epoch: [36] [1010/1319] eta: 0:13:34 lr: 5.197839056786066e-06 loss: 0.0281 (0.0340) time: 2.6477 data: 0.0059 max mem: 33369 +Epoch: [36] [1020/1319] eta: 0:13:08 lr: 5.186869293487148e-06 loss: 0.0287 (0.0340) time: 2.6472 data: 0.0060 max mem: 33369 +Epoch: [36] [1030/1319] eta: 0:12:41 lr: 5.175896951795028e-06 loss: 0.0295 (0.0340) time: 2.6599 data: 0.0059 max mem: 33369 +Epoch: [36] [1040/1319] eta: 0:12:15 lr: 5.164922025027563e-06 loss: 0.0293 (0.0340) time: 2.6834 data: 0.0058 max mem: 33369 +Epoch: [36] [1050/1319] eta: 0:11:49 lr: 5.153944506469468e-06 loss: 0.0331 (0.0340) time: 2.6604 data: 0.0057 max mem: 33369 +Epoch: [36] [1060/1319] eta: 0:11:22 lr: 5.142964389372074e-06 loss: 0.0348 (0.0340) time: 2.6520 data: 0.0057 max mem: 33369 +Epoch: [36] [1070/1319] eta: 0:10:56 lr: 5.13198166695309e-06 loss: 0.0302 (0.0340) time: 2.6294 data: 0.0057 max mem: 33369 +Epoch: [36] [1080/1319] eta: 0:10:30 lr: 5.120996332396334e-06 loss: 0.0294 (0.0340) time: 2.6422 data: 0.0057 max mem: 33369 +Epoch: [36] [1090/1319] eta: 0:10:03 lr: 5.1100083788515145e-06 loss: 0.0325 (0.0340) time: 2.6607 data: 0.0058 max mem: 33369 +Epoch: [36] [1100/1319] eta: 0:09:37 lr: 5.0990177994339575e-06 loss: 0.0326 (0.0340) time: 2.6174 data: 0.0058 max mem: 33369 +Epoch: [36] [1110/1319] eta: 0:09:11 lr: 5.088024587224353e-06 loss: 0.0326 (0.0340) time: 2.6218 data: 0.0058 max mem: 33369 +Epoch: [36] [1120/1319] eta: 0:08:44 lr: 5.077028735268508e-06 loss: 0.0344 (0.0341) time: 2.6201 data: 0.0057 max mem: 33369 +Epoch: [36] [1130/1319] eta: 0:08:18 lr: 5.066030236577056e-06 loss: 0.0344 (0.0341) time: 2.6148 data: 0.0057 max mem: 33369 +Epoch: [36] [1140/1319] eta: 0:07:51 lr: 5.055029084125236e-06 loss: 0.0314 (0.0341) time: 2.6280 data: 0.0058 max mem: 33369 +Epoch: [36] [1150/1319] eta: 0:07:25 lr: 5.044025270852602e-06 loss: 0.0314 (0.0341) time: 2.6381 data: 0.0060 max mem: 33369 +Epoch: [36] [1160/1319] eta: 0:06:59 lr: 5.033018789662757e-06 loss: 0.0289 (0.0340) time: 2.6479 data: 0.0061 max mem: 33369 +Epoch: [36] [1170/1319] eta: 0:06:32 lr: 5.022009633423085e-06 loss: 0.0274 (0.0340) time: 2.6339 data: 0.0058 max mem: 33369 +Epoch: [36] [1180/1319] eta: 0:06:06 lr: 5.0109977949644845e-06 loss: 0.0301 (0.0340) time: 2.6308 data: 0.0057 max mem: 33369 +Epoch: [36] [1190/1319] eta: 0:05:40 lr: 4.999983267081064e-06 loss: 0.0313 (0.0340) time: 2.6561 data: 0.0057 max mem: 33369 +Epoch: [36] [1200/1319] eta: 0:05:13 lr: 4.988966042529905e-06 loss: 0.0285 (0.0340) time: 2.6685 data: 0.0057 max mem: 33369 +Epoch: [36] [1210/1319] eta: 0:04:47 lr: 4.977946114030749e-06 loss: 0.0273 (0.0339) time: 2.6589 data: 0.0057 max mem: 33369 +Epoch: [36] [1220/1319] eta: 0:04:21 lr: 4.966923474265728e-06 loss: 0.0273 (0.0339) time: 2.6529 data: 0.0058 max mem: 33369 +Epoch: [36] [1230/1319] eta: 0:03:54 lr: 4.9558981158790714e-06 loss: 0.0283 (0.0339) time: 2.6461 data: 0.0058 max mem: 33369 +Epoch: [36] [1240/1319] eta: 0:03:28 lr: 4.944870031476802e-06 loss: 0.0284 (0.0339) time: 2.6315 data: 0.0059 max mem: 33369 +Epoch: [36] [1250/1319] eta: 0:03:01 lr: 4.9338392136264714e-06 loss: 0.0296 (0.0339) time: 2.6095 data: 0.0059 max mem: 33369 +Epoch: [36] [1260/1319] eta: 0:02:35 lr: 4.922805654856843e-06 loss: 0.0303 (0.0339) time: 2.6267 data: 0.0057 max mem: 33369 +Epoch: [36] [1270/1319] eta: 0:02:09 lr: 4.9117693476576e-06 loss: 0.0296 (0.0339) time: 2.6654 data: 0.0058 max mem: 33369 +Epoch: [36] [1280/1319] eta: 0:01:42 lr: 4.9007302844790375e-06 loss: 0.0291 (0.0339) time: 2.6610 data: 0.0060 max mem: 33369 +Epoch: [36] [1290/1319] eta: 0:01:16 lr: 4.889688457731768e-06 loss: 0.0291 (0.0338) time: 2.6635 data: 0.0059 max mem: 33369 +Epoch: [36] [1300/1319] eta: 0:00:50 lr: 4.878643859786385e-06 loss: 0.0298 (0.0338) time: 2.6446 data: 0.0059 max mem: 33369 +Epoch: [36] [1310/1319] eta: 0:00:23 lr: 4.867596482973188e-06 loss: 0.0303 (0.0338) time: 2.6126 data: 0.0059 max mem: 33369 +Epoch: [36] Total time: 0:57:58 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 2:06:57 time: 2.9607 data: 2.8536 max mem: 33369 +Test: [ 100/2573] eta: 0:04:08 time: 0.0718 data: 0.0011 max mem: 33369 +Test: [ 200/2573] eta: 0:03:27 time: 0.0734 data: 0.0011 max mem: 33369 +Test: [ 300/2573] eta: 0:03:07 time: 0.0751 data: 0.0011 max mem: 33369 +Test: [ 400/2573] eta: 0:02:54 time: 0.0752 data: 0.0011 max mem: 33369 +Test: [ 500/2573] eta: 0:02:43 time: 0.0737 data: 0.0011 max mem: 33369 +Test: [ 600/2573] eta: 0:02:34 time: 0.0740 data: 0.0011 max mem: 33369 +Test: [ 700/2573] eta: 0:02:25 time: 0.0739 data: 0.0011 max mem: 33369 +Test: [ 800/2573] eta: 0:02:17 time: 0.0771 data: 0.0011 max mem: 33369 +Test: [ 900/2573] eta: 0:02:09 time: 0.0738 data: 0.0011 max mem: 33369 +Test: [1000/2573] eta: 0:02:00 time: 0.0739 data: 0.0011 max mem: 33369 +Test: [1100/2573] eta: 0:01:52 time: 0.0739 data: 0.0011 max mem: 33369 +Test: [1200/2573] eta: 0:01:44 time: 0.0739 data: 0.0011 max mem: 33369 +Test: [1300/2573] eta: 0:01:37 time: 0.0738 data: 0.0011 max mem: 33369 +Test: [1400/2573] eta: 0:01:29 time: 0.0722 data: 0.0011 max mem: 33369 +Test: [1500/2573] eta: 0:01:21 time: 0.0739 data: 0.0011 max mem: 33369 +Test: [1600/2573] eta: 0:01:13 time: 0.0772 data: 0.0012 max mem: 33369 +Test: [1700/2573] eta: 0:01:06 time: 0.0722 data: 0.0011 max mem: 33369 +Test: [1800/2573] eta: 0:00:58 time: 0.0755 data: 0.0011 max mem: 33369 +Test: [1900/2573] eta: 0:00:50 time: 0.0723 data: 0.0011 max mem: 33369 +Test: [2000/2573] eta: 0:00:43 time: 0.0740 data: 0.0012 max mem: 33369 +Test: [2100/2573] eta: 0:00:35 time: 0.0756 data: 0.0011 max mem: 33369 +Test: [2200/2573] eta: 0:00:28 time: 0.0755 data: 0.0011 max mem: 33369 +Test: [2300/2573] eta: 0:00:20 time: 0.0756 data: 0.0011 max mem: 33369 +Test: [2400/2573] eta: 0:00:12 time: 0.0706 data: 0.0011 max mem: 33369 +Test: [2500/2573] eta: 0:00:05 time: 0.0739 data: 0.0011 max mem: 33369 +Test: Total time: 0:03:13 +Final results: +Mean IoU is 65.26 + + precision@0.5 = 73.59 + precision@0.6 = 68.36 + precision@0.7 = 62.03 + precision@0.8 = 50.82 + precision@0.9 = 25.82 + overall IoU = 62.18 + +Average object IoU 65.25995300482492 +Overall IoU 62.18424606323242 +Better epoch: 36 + +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [37] [ 0/1319] eta: 1:21:14 lr: 4.85765146153759e-06 loss: 0.0201 (0.0201) time: 3.6956 data: 1.0874 max mem: 33369 +Epoch: [37] [ 10/1319] eta: 1:00:28 lr: 4.846598783599751e-06 loss: 0.0235 (0.0243) time: 2.7721 data: 0.1042 max mem: 33369 +Epoch: [37] [ 20/1319] eta: 0:58:24 lr: 4.835543304321068e-06 loss: 0.0272 (0.0291) time: 2.6476 data: 0.0059 max mem: 33369 +Epoch: [37] [ 30/1319] eta: 0:57:57 lr: 4.824485015871577e-06 loss: 0.0304 (0.0305) time: 2.6568 data: 0.0062 max mem: 33369 +Epoch: [37] [ 40/1319] eta: 0:56:58 lr: 4.813423910379438e-06 loss: 0.0318 (0.0321) time: 2.6463 data: 0.0062 max mem: 33369 +Epoch: [37] [ 50/1319] eta: 0:56:34 lr: 4.802359979930566e-06 loss: 0.0314 (0.0315) time: 2.6402 data: 0.0061 max mem: 33369 +Epoch: [37] [ 60/1319] eta: 0:55:59 lr: 4.791293216568347e-06 loss: 0.0277 (0.0312) time: 2.6594 data: 0.0061 max mem: 33369 +Epoch: [37] [ 70/1319] eta: 0:55:33 lr: 4.780223612293264e-06 loss: 0.0278 (0.0314) time: 2.6544 data: 0.0060 max mem: 33369 +Epoch: [37] [ 80/1319] eta: 0:55:14 lr: 4.7691511590625665e-06 loss: 0.0335 (0.0318) time: 2.6954 data: 0.0060 max mem: 33369 +Epoch: [37] [ 90/1319] eta: 0:54:45 lr: 4.75807584878992e-06 loss: 0.0329 (0.0320) time: 2.6872 data: 0.0060 max mem: 33369 +Epoch: [37] [ 100/1319] eta: 0:54:15 lr: 4.7469976733450685e-06 loss: 0.0302 (0.0326) time: 2.6545 data: 0.0061 max mem: 33369 +Epoch: [37] [ 110/1319] eta: 0:53:47 lr: 4.735916624553454e-06 loss: 0.0302 (0.0324) time: 2.6508 data: 0.0061 max mem: 33369 +Epoch: [37] [ 120/1319] eta: 0:53:20 lr: 4.724832694195895e-06 loss: 0.0300 (0.0325) time: 2.6596 data: 0.0059 max mem: 33369 +Epoch: [37] [ 130/1319] eta: 0:52:48 lr: 4.713745874008202e-06 loss: 0.0278 (0.0321) time: 2.6410 data: 0.0060 max mem: 33369 +Epoch: [37] [ 140/1319] eta: 0:52:22 lr: 4.702656155680819e-06 loss: 0.0270 (0.0318) time: 2.6433 data: 0.0061 max mem: 33369 +Epoch: [37] [ 150/1319] eta: 0:51:54 lr: 4.691563530858464e-06 loss: 0.0287 (0.0318) time: 2.6611 data: 0.0061 max mem: 33369 +Epoch: [37] [ 160/1319] eta: 0:51:25 lr: 4.6804679911397265e-06 loss: 0.0310 (0.0318) time: 2.6394 data: 0.0061 max mem: 33369 +Epoch: [37] [ 170/1319] eta: 0:50:58 lr: 4.66936952807673e-06 loss: 0.0327 (0.0320) time: 2.6392 data: 0.0062 max mem: 33369 +Epoch: [37] [ 180/1319] eta: 0:50:30 lr: 4.65826813317473e-06 loss: 0.0327 (0.0320) time: 2.6492 data: 0.0061 max mem: 33369 +Epoch: [37] [ 190/1319] eta: 0:50:04 lr: 4.64716379789173e-06 loss: 0.0292 (0.0319) time: 2.6562 data: 0.0061 max mem: 33369 +Epoch: [37] [ 200/1319] eta: 0:49:34 lr: 4.636056513638103e-06 loss: 0.0287 (0.0318) time: 2.6388 data: 0.0061 max mem: 33369 +Epoch: [37] [ 210/1319] eta: 0:49:08 lr: 4.6249462717761695e-06 loss: 0.0320 (0.0322) time: 2.6333 data: 0.0059 max mem: 33369 +Epoch: [37] [ 220/1319] eta: 0:48:39 lr: 4.6138330636198426e-06 loss: 0.0312 (0.0320) time: 2.6352 data: 0.0060 max mem: 33369 +Epoch: [37] [ 230/1319] eta: 0:48:10 lr: 4.602716880434195e-06 loss: 0.0297 (0.0319) time: 2.6158 data: 0.0061 max mem: 33369 +Epoch: [37] [ 240/1319] eta: 0:47:44 lr: 4.591597713435064e-06 loss: 0.0308 (0.0322) time: 2.6389 data: 0.0058 max mem: 33369 +Epoch: [37] [ 250/1319] eta: 0:47:18 lr: 4.580475553788638e-06 loss: 0.0292 (0.0321) time: 2.6591 data: 0.0059 max mem: 33369 +Epoch: [37] [ 260/1319] eta: 0:46:51 lr: 4.569350392611047e-06 loss: 0.0265 (0.0319) time: 2.6534 data: 0.0060 max mem: 33369 +Epoch: [37] [ 270/1319] eta: 0:46:23 lr: 4.558222220967921e-06 loss: 0.0283 (0.0319) time: 2.6293 data: 0.0060 max mem: 33369 +Epoch: [37] [ 280/1319] eta: 0:45:55 lr: 4.547091029873999e-06 loss: 0.0307 (0.0318) time: 2.6173 data: 0.0059 max mem: 33369 +Epoch: [37] [ 290/1319] eta: 0:45:25 lr: 4.5359568102926745e-06 loss: 0.0294 (0.0319) time: 2.5941 data: 0.0059 max mem: 33369 +Epoch: [37] [ 300/1319] eta: 0:45:00 lr: 4.524819553135574e-06 loss: 0.0293 (0.0318) time: 2.6151 data: 0.0059 max mem: 33369 +Epoch: [37] [ 310/1319] eta: 0:44:32 lr: 4.5136792492621144e-06 loss: 0.0311 (0.0318) time: 2.6485 data: 0.0059 max mem: 33369 +Epoch: [37] [ 320/1319] eta: 0:44:05 lr: 4.502535889479041e-06 loss: 0.0326 (0.0319) time: 2.6236 data: 0.0059 max mem: 33369 +Epoch: [37] [ 330/1319] eta: 0:43:38 lr: 4.491389464540016e-06 loss: 0.0274 (0.0318) time: 2.6326 data: 0.0059 max mem: 33369 +Epoch: [37] [ 340/1319] eta: 0:43:11 lr: 4.480239965145135e-06 loss: 0.0304 (0.0319) time: 2.6350 data: 0.0060 max mem: 33369 +Epoch: [37] [ 350/1319] eta: 0:42:45 lr: 4.469087381940477e-06 loss: 0.0359 (0.0321) time: 2.6323 data: 0.0059 max mem: 33369 +Epoch: [37] [ 360/1319] eta: 0:42:18 lr: 4.457931705517646e-06 loss: 0.0262 (0.0319) time: 2.6354 data: 0.0059 max mem: 33369 +Epoch: [37] [ 370/1319] eta: 0:41:51 lr: 4.446772926413276e-06 loss: 0.0265 (0.0319) time: 2.6272 data: 0.0057 max mem: 33369 +Epoch: [37] [ 380/1319] eta: 0:41:23 lr: 4.435611035108594e-06 loss: 0.0299 (0.0319) time: 2.6137 data: 0.0057 max mem: 33369 +Epoch: [37] [ 390/1319] eta: 0:40:56 lr: 4.424446022028913e-06 loss: 0.0299 (0.0319) time: 2.6157 data: 0.0060 max mem: 33369 +Epoch: [37] [ 400/1319] eta: 0:40:29 lr: 4.413277877543152e-06 loss: 0.0282 (0.0319) time: 2.6274 data: 0.0061 max mem: 33369 +Epoch: [37] [ 410/1319] eta: 0:40:03 lr: 4.40210659196335e-06 loss: 0.0287 (0.0320) time: 2.6265 data: 0.0060 max mem: 33369 +Epoch: [37] [ 420/1319] eta: 0:39:37 lr: 4.390932155544163e-06 loss: 0.0388 (0.0321) time: 2.6480 data: 0.0060 max mem: 33369 +Epoch: [37] [ 430/1319] eta: 0:39:10 lr: 4.379754558482349e-06 loss: 0.0332 (0.0320) time: 2.6541 data: 0.0061 max mem: 33369 +Epoch: [37] [ 440/1319] eta: 0:38:43 lr: 4.368573790916289e-06 loss: 0.0296 (0.0322) time: 2.6297 data: 0.0061 max mem: 33369 +Epoch: [37] [ 450/1319] eta: 0:38:16 lr: 4.357389842925446e-06 loss: 0.0311 (0.0322) time: 2.6229 data: 0.0060 max mem: 33369 +Epoch: [37] [ 460/1319] eta: 0:37:50 lr: 4.346202704529857e-06 loss: 0.0311 (0.0321) time: 2.6238 data: 0.0059 max mem: 33369 +Epoch: [37] [ 470/1319] eta: 0:37:22 lr: 4.335012365689605e-06 loss: 0.0314 (0.0322) time: 2.5980 data: 0.0060 max mem: 33369 +Epoch: [37] [ 480/1319] eta: 0:36:55 lr: 4.323818816304266e-06 loss: 0.0314 (0.0321) time: 2.5911 data: 0.0060 max mem: 33369 +Epoch: [37] [ 490/1319] eta: 0:36:28 lr: 4.3126220462124026e-06 loss: 0.0279 (0.0321) time: 2.6180 data: 0.0059 max mem: 33369 +Epoch: [37] [ 500/1319] eta: 0:36:02 lr: 4.3014220451909986e-06 loss: 0.0272 (0.0320) time: 2.6240 data: 0.0059 max mem: 33369 +Epoch: [37] [ 510/1319] eta: 0:35:35 lr: 4.2902188029549045e-06 loss: 0.0269 (0.0320) time: 2.6173 data: 0.0058 max mem: 33369 +Epoch: [37] [ 520/1319] eta: 0:35:08 lr: 4.279012309156296e-06 loss: 0.0284 (0.0320) time: 2.6176 data: 0.0058 max mem: 33369 +Epoch: [37] [ 530/1319] eta: 0:34:42 lr: 4.267802553384072e-06 loss: 0.0304 (0.0320) time: 2.6361 data: 0.0059 max mem: 33369 +Epoch: [37] [ 540/1319] eta: 0:34:15 lr: 4.256589525163327e-06 loss: 0.0314 (0.0321) time: 2.6236 data: 0.0061 max mem: 33369 +Epoch: [37] [ 550/1319] eta: 0:33:48 lr: 4.2453732139547435e-06 loss: 0.0306 (0.0320) time: 2.6070 data: 0.0062 max mem: 33369 +Epoch: [37] [ 560/1319] eta: 0:33:21 lr: 4.234153609154016e-06 loss: 0.0286 (0.0320) time: 2.6039 data: 0.0060 max mem: 33369 +Epoch: [37] [ 570/1319] eta: 0:32:55 lr: 4.222930700091251e-06 loss: 0.0307 (0.0320) time: 2.6341 data: 0.0058 max mem: 33369 +Epoch: [37] [ 580/1319] eta: 0:32:29 lr: 4.211704476030378e-06 loss: 0.0347 (0.0321) time: 2.6476 data: 0.0059 max mem: 33369 +Epoch: [37] [ 590/1319] eta: 0:32:02 lr: 4.200474926168517e-06 loss: 0.0323 (0.0321) time: 2.6306 data: 0.0059 max mem: 33369 +Epoch: [37] [ 600/1319] eta: 0:31:36 lr: 4.189242039635394e-06 loss: 0.0260 (0.0320) time: 2.6470 data: 0.0059 max mem: 33369 +Epoch: [37] [ 610/1319] eta: 0:31:10 lr: 4.178005805492704e-06 loss: 0.0260 (0.0320) time: 2.6574 data: 0.0060 max mem: 33369 +Epoch: [37] [ 620/1319] eta: 0:30:44 lr: 4.166766212733477e-06 loss: 0.0277 (0.0319) time: 2.6749 data: 0.0059 max mem: 33369 +Epoch: [37] [ 630/1319] eta: 0:30:18 lr: 4.15552325028145e-06 loss: 0.0271 (0.0319) time: 2.6603 data: 0.0059 max mem: 33369 +Epoch: [37] [ 640/1319] eta: 0:29:51 lr: 4.1442769069903985e-06 loss: 0.0281 (0.0319) time: 2.6179 data: 0.0059 max mem: 33369 +Epoch: [37] [ 650/1319] eta: 0:29:25 lr: 4.133027171643516e-06 loss: 0.0318 (0.0319) time: 2.6326 data: 0.0059 max mem: 33369 +Epoch: [37] [ 660/1319] eta: 0:28:58 lr: 4.121774032952729e-06 loss: 0.0318 (0.0319) time: 2.6427 data: 0.0061 max mem: 33369 +Epoch: [37] [ 670/1319] eta: 0:28:32 lr: 4.110517479558032e-06 loss: 0.0308 (0.0320) time: 2.6354 data: 0.0060 max mem: 33369 +Epoch: [37] [ 680/1319] eta: 0:28:05 lr: 4.099257500026817e-06 loss: 0.0306 (0.0320) time: 2.6336 data: 0.0058 max mem: 33369 +Epoch: [37] [ 690/1319] eta: 0:27:39 lr: 4.087994082853156e-06 loss: 0.0298 (0.0320) time: 2.6318 data: 0.0059 max mem: 33369 +Epoch: [37] [ 700/1319] eta: 0:27:13 lr: 4.076727216457151e-06 loss: 0.0295 (0.0320) time: 2.6328 data: 0.0061 max mem: 33369 +Epoch: [37] [ 710/1319] eta: 0:26:47 lr: 4.065456889184196e-06 loss: 0.0332 (0.0320) time: 2.6509 data: 0.0061 max mem: 33369 +Epoch: [37] [ 720/1319] eta: 0:26:20 lr: 4.054183089304276e-06 loss: 0.0336 (0.0320) time: 2.6447 data: 0.0058 max mem: 33369 +Epoch: [37] [ 730/1319] eta: 0:25:54 lr: 4.0429058050112415e-06 loss: 0.0335 (0.0321) time: 2.6332 data: 0.0057 max mem: 33369 +Epoch: [37] [ 740/1319] eta: 0:25:27 lr: 4.031625024422082e-06 loss: 0.0295 (0.0320) time: 2.6317 data: 0.0058 max mem: 33369 +Epoch: [37] [ 750/1319] eta: 0:25:01 lr: 4.020340735576163e-06 loss: 0.0295 (0.0320) time: 2.6172 data: 0.0059 max mem: 33369 +Epoch: [37] [ 760/1319] eta: 0:24:34 lr: 4.0090529264345135e-06 loss: 0.0324 (0.0320) time: 2.6199 data: 0.0059 max mem: 33369 +Epoch: [37] [ 770/1319] eta: 0:24:07 lr: 3.997761584879033e-06 loss: 0.0310 (0.0320) time: 2.6053 data: 0.0059 max mem: 33369 +Epoch: [37] [ 780/1319] eta: 0:23:41 lr: 3.986466698711739e-06 loss: 0.0310 (0.0320) time: 2.6167 data: 0.0061 max mem: 33369 +Epoch: [37] [ 790/1319] eta: 0:23:15 lr: 3.975168255653987e-06 loss: 0.0320 (0.0321) time: 2.6316 data: 0.0060 max mem: 33369 +Epoch: [37] [ 800/1319] eta: 0:22:48 lr: 3.963866243345654e-06 loss: 0.0323 (0.0321) time: 2.6439 data: 0.0058 max mem: 33369 +Epoch: [37] [ 810/1319] eta: 0:22:22 lr: 3.952560649344379e-06 loss: 0.0326 (0.0322) time: 2.6428 data: 0.0058 max mem: 33369 +Epoch: [37] [ 820/1319] eta: 0:21:55 lr: 3.94125146112473e-06 loss: 0.0328 (0.0322) time: 2.6132 data: 0.0059 max mem: 33369 +Epoch: [37] [ 830/1319] eta: 0:21:29 lr: 3.929938666077381e-06 loss: 0.0280 (0.0321) time: 2.6033 data: 0.0059 max mem: 33369 +Epoch: [37] [ 840/1319] eta: 0:21:02 lr: 3.918622251508287e-06 loss: 0.0293 (0.0322) time: 2.6153 data: 0.0058 max mem: 33369 +Epoch: [37] [ 850/1319] eta: 0:20:36 lr: 3.907302204637846e-06 loss: 0.0344 (0.0322) time: 2.6349 data: 0.0057 max mem: 33369 +Epoch: [37] [ 860/1319] eta: 0:20:10 lr: 3.895978512600013e-06 loss: 0.0344 (0.0322) time: 2.6323 data: 0.0057 max mem: 33369 +Epoch: [37] [ 870/1319] eta: 0:19:43 lr: 3.8846511624414845e-06 loss: 0.0287 (0.0322) time: 2.6482 data: 0.0058 max mem: 33369 +Epoch: [37] [ 880/1319] eta: 0:19:17 lr: 3.873320141120784e-06 loss: 0.0267 (0.0322) time: 2.6506 data: 0.0058 max mem: 33369 +Epoch: [37] [ 890/1319] eta: 0:18:51 lr: 3.86198543550739e-06 loss: 0.0280 (0.0323) time: 2.6494 data: 0.0059 max mem: 33369 +Epoch: [37] [ 900/1319] eta: 0:18:24 lr: 3.850647032380834e-06 loss: 0.0280 (0.0323) time: 2.6610 data: 0.0060 max mem: 33369 +Epoch: [37] [ 910/1319] eta: 0:17:58 lr: 3.839304918429766e-06 loss: 0.0283 (0.0323) time: 2.6410 data: 0.0061 max mem: 33369 +Epoch: [37] [ 920/1319] eta: 0:17:32 lr: 3.8279590802510684e-06 loss: 0.0307 (0.0324) time: 2.6382 data: 0.0060 max mem: 33369 +Epoch: [37] [ 930/1319] eta: 0:17:05 lr: 3.816609504348892e-06 loss: 0.0307 (0.0323) time: 2.6516 data: 0.0058 max mem: 33369 +Epoch: [37] [ 940/1319] eta: 0:16:39 lr: 3.805256177133712e-06 loss: 0.0297 (0.0323) time: 2.6561 data: 0.0060 max mem: 33369 +Epoch: [37] [ 950/1319] eta: 0:16:13 lr: 3.7938990849213705e-06 loss: 0.0299 (0.0324) time: 2.6478 data: 0.0060 max mem: 33369 +Epoch: [37] [ 960/1319] eta: 0:15:46 lr: 3.782538213932079e-06 loss: 0.0323 (0.0324) time: 2.6421 data: 0.0058 max mem: 33369 +Epoch: [37] [ 970/1319] eta: 0:15:20 lr: 3.771173550289461e-06 loss: 0.0287 (0.0325) time: 2.6537 data: 0.0059 max mem: 33369 +Epoch: [37] [ 980/1319] eta: 0:14:54 lr: 3.7598050800195294e-06 loss: 0.0287 (0.0325) time: 2.6637 data: 0.0058 max mem: 33369 +Epoch: [37] [ 990/1319] eta: 0:14:27 lr: 3.748432789049672e-06 loss: 0.0292 (0.0325) time: 2.6470 data: 0.0057 max mem: 33369 +Epoch: [37] [1000/1319] eta: 0:14:01 lr: 3.7370566632076215e-06 loss: 0.0316 (0.0325) time: 2.6147 data: 0.0058 max mem: 33369 +Epoch: [37] [1010/1319] eta: 0:13:34 lr: 3.725676688220417e-06 loss: 0.0288 (0.0324) time: 2.6022 data: 0.0060 max mem: 33369 +Epoch: [37] [1020/1319] eta: 0:13:08 lr: 3.714292849713318e-06 loss: 0.0288 (0.0324) time: 2.6253 data: 0.0059 max mem: 33369 +Epoch: [37] [1030/1319] eta: 0:12:42 lr: 3.7029051332087708e-06 loss: 0.0308 (0.0324) time: 2.6259 data: 0.0060 max mem: 33369 +Epoch: [37] [1040/1319] eta: 0:12:15 lr: 3.691513524125288e-06 loss: 0.0291 (0.0324) time: 2.6444 data: 0.0060 max mem: 33369 +Epoch: [37] [1050/1319] eta: 0:11:49 lr: 3.680118007776355e-06 loss: 0.0291 (0.0324) time: 2.6540 data: 0.0059 max mem: 33369 +Epoch: [37] [1060/1319] eta: 0:11:23 lr: 3.6687185693693123e-06 loss: 0.0323 (0.0324) time: 2.6294 data: 0.0059 max mem: 33369 +Epoch: [37] [1070/1319] eta: 0:10:56 lr: 3.657315194004196e-06 loss: 0.0331 (0.0325) time: 2.6302 data: 0.0059 max mem: 33369 +Epoch: [37] [1080/1319] eta: 0:10:30 lr: 3.6459078666726217e-06 loss: 0.0330 (0.0325) time: 2.6322 data: 0.0059 max mem: 33369 +Epoch: [37] [1090/1319] eta: 0:10:03 lr: 3.6344965722565904e-06 loss: 0.0284 (0.0324) time: 2.6336 data: 0.0061 max mem: 33369 +Epoch: [37] [1100/1319] eta: 0:09:37 lr: 3.6230812955273095e-06 loss: 0.0329 (0.0326) time: 2.6336 data: 0.0062 max mem: 33369 +Epoch: [37] [1110/1319] eta: 0:09:11 lr: 3.6116620211439967e-06 loss: 0.0338 (0.0327) time: 2.6441 data: 0.0061 max mem: 33369 +Epoch: [37] [1120/1319] eta: 0:08:44 lr: 3.6002387336526318e-06 loss: 0.0335 (0.0327) time: 2.6284 data: 0.0059 max mem: 33369 +Epoch: [37] [1130/1319] eta: 0:08:18 lr: 3.588811417484761e-06 loss: 0.0337 (0.0327) time: 2.6192 data: 0.0059 max mem: 33369 +Epoch: [37] [1140/1319] eta: 0:07:52 lr: 3.577380056956213e-06 loss: 0.0323 (0.0327) time: 2.6246 data: 0.0059 max mem: 33369 +Epoch: [37] [1150/1319] eta: 0:07:25 lr: 3.5659446362658317e-06 loss: 0.0302 (0.0327) time: 2.6059 data: 0.0059 max mem: 33369 +Epoch: [37] [1160/1319] eta: 0:06:59 lr: 3.5545051394941854e-06 loss: 0.0324 (0.0327) time: 2.6367 data: 0.0060 max mem: 33369 +Epoch: [37] [1170/1319] eta: 0:06:32 lr: 3.5430615506022587e-06 loss: 0.0346 (0.0327) time: 2.6590 data: 0.0060 max mem: 33369 +Epoch: [37] [1180/1319] eta: 0:06:06 lr: 3.531613853430098e-06 loss: 0.0325 (0.0327) time: 2.6517 data: 0.0058 max mem: 33369 +Epoch: [37] [1190/1319] eta: 0:05:40 lr: 3.5201620316954973e-06 loss: 0.0325 (0.0327) time: 2.6413 data: 0.0056 max mem: 33369 +Epoch: [37] [1200/1319] eta: 0:05:13 lr: 3.5087060689926057e-06 loss: 0.0308 (0.0327) time: 2.6535 data: 0.0056 max mem: 33369 +Epoch: [37] [1210/1319] eta: 0:04:47 lr: 3.4972459487905388e-06 loss: 0.0326 (0.0328) time: 2.6758 data: 0.0057 max mem: 33369 +Epoch: [37] [1220/1319] eta: 0:04:21 lr: 3.485781654431977e-06 loss: 0.0336 (0.0327) time: 2.6682 data: 0.0060 max mem: 33369 +Epoch: [37] [1230/1319] eta: 0:03:54 lr: 3.4743131691317023e-06 loss: 0.0358 (0.0328) time: 2.6339 data: 0.0059 max mem: 33369 +Epoch: [37] [1240/1319] eta: 0:03:28 lr: 3.462840475975186e-06 loss: 0.0304 (0.0328) time: 2.6178 data: 0.0058 max mem: 33369 +Epoch: [37] [1250/1319] eta: 0:03:01 lr: 3.451363557917087e-06 loss: 0.0299 (0.0328) time: 2.6187 data: 0.0060 max mem: 33369 +Epoch: [37] [1260/1319] eta: 0:02:35 lr: 3.439882397779757e-06 loss: 0.0322 (0.0328) time: 2.6240 data: 0.0060 max mem: 33369 +Epoch: [37] [1270/1319] eta: 0:02:09 lr: 3.4283969782517246e-06 loss: 0.0303 (0.0328) time: 2.6427 data: 0.0060 max mem: 33369 +Epoch: [37] [1280/1319] eta: 0:01:42 lr: 3.416907281886128e-06 loss: 0.0287 (0.0327) time: 2.6359 data: 0.0058 max mem: 33369 +Epoch: [37] [1290/1319] eta: 0:01:16 lr: 3.405413291099184e-06 loss: 0.0273 (0.0327) time: 2.6247 data: 0.0057 max mem: 33369 +Epoch: [37] [1300/1319] eta: 0:00:50 lr: 3.393914988168568e-06 loss: 0.0283 (0.0327) time: 2.6190 data: 0.0058 max mem: 33369 +Epoch: [37] [1310/1319] eta: 0:00:23 lr: 3.3824123552318046e-06 loss: 0.0333 (0.0327) time: 2.6266 data: 0.0060 max mem: 33369 +Epoch: [37] Total time: 0:57:58 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 1:53:20 time: 2.6431 data: 2.4822 max mem: 33369 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 100/2573] eta: 0:04:02 time: 0.0715 data: 0.0011 max mem: 33369 +Test: [ 200/2573] eta: 0:03:24 time: 0.0733 data: 0.0011 max mem: 33369 +Test: [ 300/2573] eta: 0:03:05 time: 0.0750 data: 0.0011 max mem: 33369 +Test: [ 400/2573] eta: 0:02:52 time: 0.0750 data: 0.0011 max mem: 33369 +Test: [ 500/2573] eta: 0:02:42 time: 0.0736 data: 0.0011 max mem: 33369 +Test: [ 600/2573] eta: 0:02:33 time: 0.0735 data: 0.0011 max mem: 33369 +Test: [ 700/2573] eta: 0:02:24 time: 0.0736 data: 0.0011 max mem: 33369 +Test: [ 800/2573] eta: 0:02:16 time: 0.0770 data: 0.0011 max mem: 33369 +Test: [ 900/2573] eta: 0:02:08 time: 0.0738 data: 0.0011 max mem: 33369 +Test: [1000/2573] eta: 0:02:00 time: 0.0739 data: 0.0011 max mem: 33369 +Test: [1100/2573] eta: 0:01:52 time: 0.0738 data: 0.0011 max mem: 33369 +Test: [1200/2573] eta: 0:01:44 time: 0.0738 data: 0.0011 max mem: 33369 +Test: [1300/2573] eta: 0:01:36 time: 0.0738 data: 0.0011 max mem: 33369 +Test: [1400/2573] eta: 0:01:28 time: 0.0721 data: 0.0011 max mem: 33369 +Test: [1500/2573] eta: 0:01:21 time: 0.0738 data: 0.0011 max mem: 33369 +Test: [1600/2573] eta: 0:01:13 time: 0.0771 data: 0.0011 max mem: 33369 +Test: [1700/2573] eta: 0:01:05 time: 0.0721 data: 0.0010 max mem: 33369 +Test: [1800/2573] eta: 0:00:58 time: 0.0754 data: 0.0011 max mem: 33369 +Test: [1900/2573] eta: 0:00:50 time: 0.0721 data: 0.0011 max mem: 33369 +Test: [2000/2573] eta: 0:00:43 time: 0.0739 data: 0.0011 max mem: 33369 +Test: [2100/2573] eta: 0:00:35 time: 0.0754 data: 0.0011 max mem: 33369 +Test: [2200/2573] eta: 0:00:27 time: 0.0754 data: 0.0011 max mem: 33369 +Test: [2300/2573] eta: 0:00:20 time: 0.0754 data: 0.0011 max mem: 33369 +Test: [2400/2573] eta: 0:00:12 time: 0.0706 data: 0.0011 max mem: 33369 +Test: [2500/2573] eta: 0:00:05 time: 0.0738 data: 0.0011 max mem: 33369 +Test: Total time: 0:03:12 +Final results: +Mean IoU is 64.92 + + precision@0.5 = 73.18 + precision@0.6 = 68.12 + precision@0.7 = 61.58 + precision@0.8 = 50.69 + precision@0.9 = 26.08 + overall IoU = 61.90 + +Average object IoU 64.91901973305355 +Overall IoU 61.901676177978516 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [38] [ 0/1319] eta: 3:32:43 lr: 3.3720562685558925e-06 loss: 0.0258 (0.0258) time: 9.6768 data: 2.4584 max mem: 33369 +Epoch: [38] [ 10/1319] eta: 1:11:49 lr: 3.3605453588871517e-06 loss: 0.0297 (0.0349) time: 3.2921 data: 0.2291 max mem: 33369 +Epoch: [38] [ 20/1319] eta: 1:04:49 lr: 3.349030066603249e-06 loss: 0.0297 (0.0338) time: 2.6602 data: 0.0058 max mem: 33369 +Epoch: [38] [ 30/1319] eta: 1:02:01 lr: 3.3375103732791936e-06 loss: 0.0320 (0.0332) time: 2.6644 data: 0.0057 max mem: 33369 +Epoch: [38] [ 40/1319] eta: 0:59:55 lr: 3.3259862603415314e-06 loss: 0.0324 (0.0336) time: 2.6190 data: 0.0059 max mem: 33369 +Epoch: [38] [ 50/1319] eta: 0:58:52 lr: 3.314457709066606e-06 loss: 0.0356 (0.0343) time: 2.6238 data: 0.0060 max mem: 33369 +Epoch: [38] [ 60/1319] eta: 0:57:59 lr: 3.302924700578736e-06 loss: 0.0340 (0.0341) time: 2.6673 data: 0.0060 max mem: 33369 +Epoch: [38] [ 70/1319] eta: 0:57:09 lr: 3.2913872158483893e-06 loss: 0.0313 (0.0337) time: 2.6492 data: 0.0059 max mem: 33369 +Epoch: [38] [ 80/1319] eta: 0:56:20 lr: 3.279845235690334e-06 loss: 0.0292 (0.0329) time: 2.6210 data: 0.0059 max mem: 33369 +Epoch: [38] [ 90/1319] eta: 0:55:39 lr: 3.268298740761722e-06 loss: 0.0285 (0.0326) time: 2.6150 data: 0.0061 max mem: 33369 +Epoch: [38] [ 100/1319] eta: 0:55:00 lr: 3.2567477115602124e-06 loss: 0.0300 (0.0325) time: 2.6227 data: 0.0061 max mem: 33369 +Epoch: [38] [ 110/1319] eta: 0:54:20 lr: 3.2451921284219928e-06 loss: 0.0315 (0.0329) time: 2.6031 data: 0.0059 max mem: 33369 +Epoch: [38] [ 120/1319] eta: 0:53:46 lr: 3.233631971519807e-06 loss: 0.0302 (0.0326) time: 2.6055 data: 0.0060 max mem: 33369 +Epoch: [38] [ 130/1319] eta: 0:53:16 lr: 3.2220672208609392e-06 loss: 0.0283 (0.0325) time: 2.6419 data: 0.0062 max mem: 33369 +Epoch: [38] [ 140/1319] eta: 0:52:40 lr: 3.2104978562851772e-06 loss: 0.0283 (0.0323) time: 2.6213 data: 0.0061 max mem: 33369 +Epoch: [38] [ 150/1319] eta: 0:52:11 lr: 3.1989238574627024e-06 loss: 0.0282 (0.0326) time: 2.6151 data: 0.0061 max mem: 33369 +Epoch: [38] [ 160/1319] eta: 0:51:42 lr: 3.18734520389202e-06 loss: 0.0271 (0.0322) time: 2.6452 data: 0.0062 max mem: 33369 +Epoch: [38] [ 170/1319] eta: 0:51:10 lr: 3.175761874897778e-06 loss: 0.0258 (0.0323) time: 2.6287 data: 0.0060 max mem: 33369 +Epoch: [38] [ 180/1319] eta: 0:50:41 lr: 3.1641738496285912e-06 loss: 0.0310 (0.0324) time: 2.6207 data: 0.0061 max mem: 33369 +Epoch: [38] [ 190/1319] eta: 0:50:13 lr: 3.1525811070548283e-06 loss: 0.0310 (0.0325) time: 2.6406 data: 0.0062 max mem: 33369 +Epoch: [38] [ 200/1319] eta: 0:49:45 lr: 3.1409836259663234e-06 loss: 0.0318 (0.0325) time: 2.6460 data: 0.0061 max mem: 33369 +Epoch: [38] [ 210/1319] eta: 0:49:15 lr: 3.1293813849701203e-06 loss: 0.0324 (0.0325) time: 2.6215 data: 0.0060 max mem: 33369 +Epoch: [38] [ 220/1319] eta: 0:48:46 lr: 3.1177743624881108e-06 loss: 0.0305 (0.0324) time: 2.6116 data: 0.0059 max mem: 33369 +Epoch: [38] [ 230/1319] eta: 0:48:18 lr: 3.1061625367546658e-06 loss: 0.0253 (0.0320) time: 2.6271 data: 0.0059 max mem: 33369 +Epoch: [38] [ 240/1319] eta: 0:47:51 lr: 3.0945458858142194e-06 loss: 0.0275 (0.0320) time: 2.6469 data: 0.0061 max mem: 33369 +Epoch: [38] [ 250/1319] eta: 0:47:22 lr: 3.08292438751882e-06 loss: 0.0300 (0.0320) time: 2.6351 data: 0.0061 max mem: 33369 +Epoch: [38] [ 260/1319] eta: 0:46:55 lr: 3.071298019525602e-06 loss: 0.0304 (0.0321) time: 2.6234 data: 0.0059 max mem: 33369 +Epoch: [38] [ 270/1319] eta: 0:46:26 lr: 3.0596667592942867e-06 loss: 0.0336 (0.0322) time: 2.6168 data: 0.0060 max mem: 33369 +Epoch: [38] [ 280/1319] eta: 0:45:59 lr: 3.048030584084566e-06 loss: 0.0345 (0.0324) time: 2.6178 data: 0.0060 max mem: 33369 +Epoch: [38] [ 290/1319] eta: 0:45:32 lr: 3.036389470953479e-06 loss: 0.0314 (0.0324) time: 2.6415 data: 0.0059 max mem: 33369 +Epoch: [38] [ 300/1319] eta: 0:45:05 lr: 3.024743396752744e-06 loss: 0.0294 (0.0323) time: 2.6462 data: 0.0059 max mem: 33369 +Epoch: [38] [ 310/1319] eta: 0:44:38 lr: 3.013092338126003e-06 loss: 0.0287 (0.0323) time: 2.6523 data: 0.0059 max mem: 33369 +Epoch: [38] [ 320/1319] eta: 0:44:13 lr: 3.0014362715060913e-06 loss: 0.0297 (0.0323) time: 2.6664 data: 0.0059 max mem: 33369 +Epoch: [38] [ 330/1319] eta: 0:43:45 lr: 2.9897751731121923e-06 loss: 0.0313 (0.0324) time: 2.6406 data: 0.0059 max mem: 33369 +Epoch: [38] [ 340/1319] eta: 0:43:20 lr: 2.978109018946967e-06 loss: 0.0295 (0.0324) time: 2.6589 data: 0.0059 max mem: 33369 +Epoch: [38] [ 350/1319] eta: 0:42:53 lr: 2.9664377847936435e-06 loss: 0.0307 (0.0323) time: 2.6798 data: 0.0058 max mem: 33369 +Epoch: [38] [ 360/1319] eta: 0:42:26 lr: 2.954761446213011e-06 loss: 0.0311 (0.0323) time: 2.6490 data: 0.0059 max mem: 33369 +Epoch: [38] [ 370/1319] eta: 0:42:00 lr: 2.943079978540434e-06 loss: 0.0309 (0.0323) time: 2.6576 data: 0.0061 max mem: 33369 +Epoch: [38] [ 380/1319] eta: 0:41:33 lr: 2.931393356882739e-06 loss: 0.0309 (0.0324) time: 2.6584 data: 0.0060 max mem: 33369 +Epoch: [38] [ 390/1319] eta: 0:41:06 lr: 2.919701556115084e-06 loss: 0.0323 (0.0324) time: 2.6376 data: 0.0058 max mem: 33369 +Epoch: [38] [ 400/1319] eta: 0:40:39 lr: 2.908004550877762e-06 loss: 0.0283 (0.0324) time: 2.6381 data: 0.0061 max mem: 33369 +Epoch: [38] [ 410/1319] eta: 0:40:11 lr: 2.8963023155729493e-06 loss: 0.0269 (0.0324) time: 2.6201 data: 0.0062 max mem: 33369 +Epoch: [38] [ 420/1319] eta: 0:39:45 lr: 2.884594824361366e-06 loss: 0.0269 (0.0323) time: 2.6169 data: 0.0061 max mem: 33369 +Epoch: [38] [ 430/1319] eta: 0:39:18 lr: 2.8728820511589384e-06 loss: 0.0294 (0.0324) time: 2.6448 data: 0.0060 max mem: 33369 +Epoch: [38] [ 440/1319] eta: 0:38:51 lr: 2.861163969633332e-06 loss: 0.0294 (0.0323) time: 2.6329 data: 0.0061 max mem: 33369 +Epoch: [38] [ 450/1319] eta: 0:38:24 lr: 2.849440553200456e-06 loss: 0.0275 (0.0322) time: 2.6451 data: 0.0059 max mem: 33369 +Epoch: [38] [ 460/1319] eta: 0:37:58 lr: 2.837711775020899e-06 loss: 0.0297 (0.0322) time: 2.6515 data: 0.0058 max mem: 33369 +Epoch: [38] [ 470/1319] eta: 0:37:31 lr: 2.8259776079962665e-06 loss: 0.0297 (0.0321) time: 2.6336 data: 0.0059 max mem: 33369 +Epoch: [38] [ 480/1319] eta: 0:37:04 lr: 2.814238024765515e-06 loss: 0.0301 (0.0323) time: 2.6421 data: 0.0059 max mem: 33369 +Epoch: [38] [ 490/1319] eta: 0:36:38 lr: 2.8024929977011503e-06 loss: 0.0363 (0.0324) time: 2.6688 data: 0.0060 max mem: 33369 +Epoch: [38] [ 500/1319] eta: 0:36:12 lr: 2.790742498905385e-06 loss: 0.0307 (0.0324) time: 2.6637 data: 0.0060 max mem: 33369 +Epoch: [38] [ 510/1319] eta: 0:35:45 lr: 2.7789865002062234e-06 loss: 0.0299 (0.0323) time: 2.6513 data: 0.0060 max mem: 33369 +Epoch: [38] [ 520/1319] eta: 0:35:18 lr: 2.7672249731534377e-06 loss: 0.0301 (0.0323) time: 2.6455 data: 0.0060 max mem: 33369 +Epoch: [38] [ 530/1319] eta: 0:34:51 lr: 2.7554578890145323e-06 loss: 0.0273 (0.0323) time: 2.6255 data: 0.0060 max mem: 33369 +Epoch: [38] [ 540/1319] eta: 0:34:24 lr: 2.7436852187705646e-06 loss: 0.0254 (0.0321) time: 2.6195 data: 0.0061 max mem: 33369 +Epoch: [38] [ 550/1319] eta: 0:33:57 lr: 2.7319069331119135e-06 loss: 0.0244 (0.0321) time: 2.6081 data: 0.0060 max mem: 33369 +Epoch: [38] [ 560/1319] eta: 0:33:30 lr: 2.7201230024339627e-06 loss: 0.0288 (0.0321) time: 2.6146 data: 0.0059 max mem: 33369 +Epoch: [38] [ 570/1319] eta: 0:33:04 lr: 2.7083333968327037e-06 loss: 0.0296 (0.0321) time: 2.6447 data: 0.0058 max mem: 33369 +Epoch: [38] [ 580/1319] eta: 0:32:37 lr: 2.696538086100214e-06 loss: 0.0289 (0.0320) time: 2.6374 data: 0.0058 max mem: 33369 +Epoch: [38] [ 590/1319] eta: 0:32:10 lr: 2.6847370397201204e-06 loss: 0.0286 (0.0320) time: 2.6247 data: 0.0059 max mem: 33369 +Epoch: [38] [ 600/1319] eta: 0:31:44 lr: 2.6729302268628987e-06 loss: 0.0317 (0.0321) time: 2.6338 data: 0.0059 max mem: 33369 +Epoch: [38] [ 610/1319] eta: 0:31:17 lr: 2.6611176163811112e-06 loss: 0.0386 (0.0322) time: 2.6488 data: 0.0059 max mem: 33369 +Epoch: [38] [ 620/1319] eta: 0:30:51 lr: 2.6492991768045523e-06 loss: 0.0309 (0.0322) time: 2.6599 data: 0.0060 max mem: 33369 +Epoch: [38] [ 630/1319] eta: 0:30:25 lr: 2.637474876335259e-06 loss: 0.0301 (0.0322) time: 2.6621 data: 0.0060 max mem: 33369 +Epoch: [38] [ 640/1319] eta: 0:29:58 lr: 2.6256446828424878e-06 loss: 0.0314 (0.0323) time: 2.6536 data: 0.0059 max mem: 33369 +Epoch: [38] [ 650/1319] eta: 0:29:32 lr: 2.613808563857519e-06 loss: 0.0336 (0.0324) time: 2.6412 data: 0.0059 max mem: 33369 +Epoch: [38] [ 660/1319] eta: 0:29:05 lr: 2.6019664865683917e-06 loss: 0.0333 (0.0324) time: 2.6340 data: 0.0059 max mem: 33369 +Epoch: [38] [ 670/1319] eta: 0:28:39 lr: 2.590118417814524e-06 loss: 0.0290 (0.0323) time: 2.6515 data: 0.0059 max mem: 33369 +Epoch: [38] [ 680/1319] eta: 0:28:12 lr: 2.5782643240811925e-06 loss: 0.0297 (0.0323) time: 2.6644 data: 0.0059 max mem: 33369 +Epoch: [38] [ 690/1319] eta: 0:27:46 lr: 2.566404171493961e-06 loss: 0.0339 (0.0324) time: 2.6455 data: 0.0058 max mem: 33369 +Epoch: [38] [ 700/1319] eta: 0:27:19 lr: 2.5545379258129243e-06 loss: 0.0276 (0.0323) time: 2.6376 data: 0.0058 max mem: 33369 +Epoch: [38] [ 710/1319] eta: 0:26:52 lr: 2.5426655524268633e-06 loss: 0.0262 (0.0323) time: 2.6360 data: 0.0058 max mem: 33369 +Epoch: [38] [ 720/1319] eta: 0:26:26 lr: 2.5307870163472715e-06 loss: 0.0254 (0.0322) time: 2.6251 data: 0.0058 max mem: 33369 +Epoch: [38] [ 730/1319] eta: 0:25:59 lr: 2.5189022822022593e-06 loss: 0.0250 (0.0321) time: 2.6243 data: 0.0058 max mem: 33369 +Epoch: [38] [ 740/1319] eta: 0:25:32 lr: 2.5070113142302914e-06 loss: 0.0269 (0.0321) time: 2.6309 data: 0.0058 max mem: 33369 +Epoch: [38] [ 750/1319] eta: 0:25:06 lr: 2.495114076273858e-06 loss: 0.0288 (0.0321) time: 2.6298 data: 0.0058 max mem: 33369 +Epoch: [38] [ 760/1319] eta: 0:24:39 lr: 2.483210531772943e-06 loss: 0.0295 (0.0321) time: 2.6110 data: 0.0058 max mem: 33369 +Epoch: [38] [ 770/1319] eta: 0:24:12 lr: 2.4713006437583777e-06 loss: 0.0292 (0.0321) time: 2.6104 data: 0.0059 max mem: 33369 +Epoch: [38] [ 780/1319] eta: 0:23:46 lr: 2.4593843748450576e-06 loss: 0.0311 (0.0321) time: 2.6344 data: 0.0059 max mem: 33369 +Epoch: [38] [ 790/1319] eta: 0:23:19 lr: 2.447461687224963e-06 loss: 0.0304 (0.0321) time: 2.6437 data: 0.0059 max mem: 33369 +Epoch: [38] [ 800/1319] eta: 0:22:53 lr: 2.4355325426601037e-06 loss: 0.0304 (0.0321) time: 2.6239 data: 0.0058 max mem: 33369 +Epoch: [38] [ 810/1319] eta: 0:22:27 lr: 2.423596902475233e-06 loss: 0.0316 (0.0321) time: 2.6708 data: 0.0058 max mem: 33369 +Epoch: [38] [ 820/1319] eta: 0:22:00 lr: 2.4116547275504333e-06 loss: 0.0303 (0.0321) time: 2.6735 data: 0.0061 max mem: 33369 +Epoch: [38] [ 830/1319] eta: 0:21:34 lr: 2.3997059783135262e-06 loss: 0.0282 (0.0321) time: 2.6321 data: 0.0061 max mem: 33369 +Epoch: [38] [ 840/1319] eta: 0:21:07 lr: 2.38775061473232e-06 loss: 0.0299 (0.0321) time: 2.6246 data: 0.0060 max mem: 33369 +Epoch: [38] [ 850/1319] eta: 0:20:41 lr: 2.3757885963066428e-06 loss: 0.0315 (0.0321) time: 2.6248 data: 0.0060 max mem: 33369 +Epoch: [38] [ 860/1319] eta: 0:20:14 lr: 2.3638198820602614e-06 loss: 0.0274 (0.0320) time: 2.6289 data: 0.0061 max mem: 33369 +Epoch: [38] [ 870/1319] eta: 0:19:47 lr: 2.351844430532552e-06 loss: 0.0274 (0.0321) time: 2.6283 data: 0.0061 max mem: 33369 +Epoch: [38] [ 880/1319] eta: 0:19:21 lr: 2.339862199770001e-06 loss: 0.0334 (0.0321) time: 2.6434 data: 0.0060 max mem: 33369 +Epoch: [38] [ 890/1319] eta: 0:18:54 lr: 2.327873147317513e-06 loss: 0.0294 (0.0321) time: 2.6415 data: 0.0059 max mem: 33369 +Epoch: [38] [ 900/1319] eta: 0:18:28 lr: 2.315877230209485e-06 loss: 0.0271 (0.0320) time: 2.6544 data: 0.0057 max mem: 33369 +Epoch: [38] [ 910/1319] eta: 0:18:01 lr: 2.303874404960728e-06 loss: 0.0269 (0.0320) time: 2.6393 data: 0.0058 max mem: 33369 +Epoch: [38] [ 920/1319] eta: 0:17:35 lr: 2.291864627557113e-06 loss: 0.0274 (0.0320) time: 2.6606 data: 0.0059 max mem: 33369 +Epoch: [38] [ 930/1319] eta: 0:17:09 lr: 2.2798478534460264e-06 loss: 0.0299 (0.0320) time: 2.6937 data: 0.0057 max mem: 33369 +Epoch: [38] [ 940/1319] eta: 0:16:43 lr: 2.2678240375265906e-06 loss: 0.0295 (0.0320) time: 2.6830 data: 0.0058 max mem: 33369 +Epoch: [38] [ 950/1319] eta: 0:16:16 lr: 2.25579313413962e-06 loss: 0.0300 (0.0320) time: 2.6587 data: 0.0058 max mem: 33369 +Epoch: [38] [ 960/1319] eta: 0:15:50 lr: 2.243755097057401e-06 loss: 0.0286 (0.0319) time: 2.6444 data: 0.0058 max mem: 33369 +Epoch: [38] [ 970/1319] eta: 0:15:23 lr: 2.2317098794731506e-06 loss: 0.0285 (0.0319) time: 2.6311 data: 0.0059 max mem: 33369 +Epoch: [38] [ 980/1319] eta: 0:14:57 lr: 2.2196574339902486e-06 loss: 0.0332 (0.0320) time: 2.6151 data: 0.0060 max mem: 33369 +Epoch: [38] [ 990/1319] eta: 0:14:30 lr: 2.2075977126112046e-06 loss: 0.0345 (0.0320) time: 2.6420 data: 0.0060 max mem: 33369 +Epoch: [38] [1000/1319] eta: 0:14:04 lr: 2.195530666726346e-06 loss: 0.0299 (0.0320) time: 2.6654 data: 0.0058 max mem: 33369 +Epoch: [38] [1010/1319] eta: 0:13:37 lr: 2.183456247102197e-06 loss: 0.0289 (0.0320) time: 2.6425 data: 0.0060 max mem: 33369 +Epoch: [38] [1020/1319] eta: 0:13:11 lr: 2.1713744038696293e-06 loss: 0.0289 (0.0319) time: 2.6393 data: 0.0061 max mem: 33369 +Epoch: [38] [1030/1319] eta: 0:12:44 lr: 2.1592850865116445e-06 loss: 0.0282 (0.0319) time: 2.6725 data: 0.0060 max mem: 33369 +Epoch: [38] [1040/1319] eta: 0:12:18 lr: 2.1471882438508782e-06 loss: 0.0339 (0.0320) time: 2.6664 data: 0.0059 max mem: 33369 +Epoch: [38] [1050/1319] eta: 0:11:51 lr: 2.135083824036786e-06 loss: 0.0358 (0.0321) time: 2.6495 data: 0.0058 max mem: 33369 +Epoch: [38] [1060/1319] eta: 0:11:25 lr: 2.1229717745324578e-06 loss: 0.0333 (0.0321) time: 2.6479 data: 0.0058 max mem: 33369 +Epoch: [38] [1070/1319] eta: 0:10:58 lr: 2.110852042101167e-06 loss: 0.0317 (0.0320) time: 2.6167 data: 0.0059 max mem: 33369 +Epoch: [38] [1080/1319] eta: 0:10:32 lr: 2.0987245727924905e-06 loss: 0.0282 (0.0320) time: 2.6245 data: 0.0060 max mem: 33369 +Epoch: [38] [1090/1319] eta: 0:10:05 lr: 2.086589311928101e-06 loss: 0.0259 (0.0320) time: 2.6396 data: 0.0060 max mem: 33369 +Epoch: [38] [1100/1319] eta: 0:09:39 lr: 2.074446204087186e-06 loss: 0.0287 (0.0320) time: 2.6204 data: 0.0060 max mem: 33369 +Epoch: [38] [1110/1319] eta: 0:09:12 lr: 2.062295193091432e-06 loss: 0.0304 (0.0320) time: 2.6157 data: 0.0061 max mem: 33369 +Epoch: [38] [1120/1319] eta: 0:08:46 lr: 2.050136221989693e-06 loss: 0.0304 (0.0320) time: 2.5935 data: 0.0061 max mem: 33369 +Epoch: [38] [1130/1319] eta: 0:08:19 lr: 2.0379692330421533e-06 loss: 0.0310 (0.0320) time: 2.6319 data: 0.0059 max mem: 33369 +Epoch: [38] [1140/1319] eta: 0:07:53 lr: 2.0257941677041134e-06 loss: 0.0288 (0.0320) time: 2.6522 data: 0.0057 max mem: 33369 +Epoch: [38] [1150/1319] eta: 0:07:27 lr: 2.013610966609312e-06 loss: 0.0285 (0.0320) time: 2.6478 data: 0.0058 max mem: 33369 +Epoch: [38] [1160/1319] eta: 0:07:00 lr: 2.0014195695528014e-06 loss: 0.0292 (0.0320) time: 2.6575 data: 0.0060 max mem: 33369 +Epoch: [38] [1170/1319] eta: 0:06:34 lr: 1.9892199154733075e-06 loss: 0.0295 (0.0321) time: 2.6415 data: 0.0060 max mem: 33369 +Epoch: [38] [1180/1319] eta: 0:06:07 lr: 1.977011942435173e-06 loss: 0.0319 (0.0320) time: 2.6472 data: 0.0058 max mem: 33369 +Epoch: [38] [1190/1319] eta: 0:05:41 lr: 1.964795587609718e-06 loss: 0.0293 (0.0320) time: 2.6499 data: 0.0059 max mem: 33369 +Epoch: [38] [1200/1319] eta: 0:05:14 lr: 1.9525707872561044e-06 loss: 0.0275 (0.0320) time: 2.6694 data: 0.0059 max mem: 33369 +Epoch: [38] [1210/1319] eta: 0:04:48 lr: 1.9403374767016633e-06 loss: 0.0294 (0.0320) time: 2.6558 data: 0.0059 max mem: 33369 +Epoch: [38] [1220/1319] eta: 0:04:21 lr: 1.928095590321611e-06 loss: 0.0322 (0.0320) time: 2.6398 data: 0.0060 max mem: 33369 +Epoch: [38] [1230/1319] eta: 0:03:55 lr: 1.915845061518256e-06 loss: 0.0295 (0.0320) time: 2.6445 data: 0.0059 max mem: 33369 +Epoch: [38] [1240/1319] eta: 0:03:28 lr: 1.9035858226995284e-06 loss: 0.0292 (0.0320) time: 2.6424 data: 0.0057 max mem: 33369 +Epoch: [38] [1250/1319] eta: 0:03:02 lr: 1.8913178052569088e-06 loss: 0.0349 (0.0320) time: 2.6267 data: 0.0059 max mem: 33369 +Epoch: [38] [1260/1319] eta: 0:02:36 lr: 1.8790409395427117e-06 loss: 0.0352 (0.0321) time: 2.6382 data: 0.0058 max mem: 33369 +Epoch: [38] [1270/1319] eta: 0:02:09 lr: 1.8667551548466507e-06 loss: 0.0311 (0.0320) time: 2.6569 data: 0.0058 max mem: 33369 +Epoch: [38] [1280/1319] eta: 0:01:43 lr: 1.8544603793717773e-06 loss: 0.0311 (0.0321) time: 2.6530 data: 0.0058 max mem: 33369 +Epoch: [38] [1290/1319] eta: 0:01:16 lr: 1.8421565402096163e-06 loss: 0.0327 (0.0321) time: 2.6412 data: 0.0057 max mem: 33369 +Epoch: [38] [1300/1319] eta: 0:00:50 lr: 1.8298435633145817e-06 loss: 0.0274 (0.0321) time: 2.6223 data: 0.0057 max mem: 33369 +Epoch: [38] [1310/1319] eta: 0:00:23 lr: 1.8175213734776007e-06 loss: 0.0283 (0.0321) time: 2.6313 data: 0.0058 max mem: 33369 +Epoch: [38] Total time: 0:58:09 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 2:04:45 time: 2.9092 data: 2.8314 max mem: 33369 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 100/2573] eta: 0:04:07 time: 0.0717 data: 0.0011 max mem: 33369 +Test: [ 200/2573] eta: 0:03:27 time: 0.0734 data: 0.0011 max mem: 33369 +Test: [ 300/2573] eta: 0:03:06 time: 0.0750 data: 0.0011 max mem: 33369 +Test: [ 400/2573] eta: 0:02:53 time: 0.0752 data: 0.0011 max mem: 33369 +Test: [ 500/2573] eta: 0:02:43 time: 0.0735 data: 0.0011 max mem: 33369 +Test: [ 600/2573] eta: 0:02:33 time: 0.0737 data: 0.0011 max mem: 33369 +Test: [ 700/2573] eta: 0:02:25 time: 0.0737 data: 0.0011 max mem: 33369 +Test: [ 800/2573] eta: 0:02:17 time: 0.0771 data: 0.0011 max mem: 33369 +Test: [ 900/2573] eta: 0:02:08 time: 0.0739 data: 0.0011 max mem: 33369 +Test: [1000/2573] eta: 0:02:00 time: 0.0739 data: 0.0011 max mem: 33369 +Test: [1100/2573] eta: 0:01:52 time: 0.0739 data: 0.0011 max mem: 33369 +Test: [1200/2573] eta: 0:01:44 time: 0.0737 data: 0.0011 max mem: 33369 +Test: [1300/2573] eta: 0:01:36 time: 0.0739 data: 0.0011 max mem: 33369 +Test: [1400/2573] eta: 0:01:29 time: 0.0721 data: 0.0011 max mem: 33369 +Test: [1500/2573] eta: 0:01:21 time: 0.0739 data: 0.0011 max mem: 33369 +Test: [1600/2573] eta: 0:01:13 time: 0.0773 data: 0.0011 max mem: 33369 +Test: [1700/2573] eta: 0:01:06 time: 0.0722 data: 0.0011 max mem: 33369 +Test: [1800/2573] eta: 0:00:58 time: 0.0756 data: 0.0011 max mem: 33369 +Test: [1900/2573] eta: 0:00:50 time: 0.0722 data: 0.0011 max mem: 33369 +Test: [2000/2573] eta: 0:00:43 time: 0.0739 data: 0.0011 max mem: 33369 +Test: [2100/2573] eta: 0:00:35 time: 0.0754 data: 0.0011 max mem: 33369 +Test: [2200/2573] eta: 0:00:27 time: 0.0756 data: 0.0011 max mem: 33369 +Test: [2300/2573] eta: 0:00:20 time: 0.0755 data: 0.0012 max mem: 33369 +Test: [2400/2573] eta: 0:00:12 time: 0.0707 data: 0.0011 max mem: 33369 +Test: [2500/2573] eta: 0:00:05 time: 0.0741 data: 0.0011 max mem: 33369 +Test: Total time: 0:03:13 +Final results: +Mean IoU is 65.07 + + precision@0.5 = 73.43 + precision@0.6 = 68.24 + precision@0.7 = 62.15 + precision@0.8 = 51.04 + precision@0.9 = 26.37 + overall IoU = 62.13 + +Average object IoU 65.07132977626257 +Overall IoU 62.12703323364258 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [39] [ 0/1319] eta: 3:17:18 lr: 1.8064234624396156e-06 loss: 0.0341 (0.0341) time: 8.9756 data: 1.8098 max mem: 33369 +Epoch: [39] [ 10/1319] eta: 1:10:19 lr: 1.7940835565249508e-06 loss: 0.0334 (0.0340) time: 3.2237 data: 0.1701 max mem: 33369 +Epoch: [39] [ 20/1319] eta: 1:04:35 lr: 1.7817342127276263e-06 loss: 0.0291 (0.0324) time: 2.6837 data: 0.0058 max mem: 33369 +Epoch: [39] [ 30/1319] eta: 1:01:44 lr: 1.7693753510331764e-06 loss: 0.0269 (0.0316) time: 2.6815 data: 0.0057 max mem: 33369 +Epoch: [39] [ 40/1319] eta: 1:00:06 lr: 1.757006890122028e-06 loss: 0.0289 (0.0318) time: 2.6473 data: 0.0060 max mem: 33369 +Epoch: [39] [ 50/1319] eta: 0:58:57 lr: 1.7446287473378005e-06 loss: 0.0289 (0.0316) time: 2.6545 data: 0.0060 max mem: 33369 +Epoch: [39] [ 60/1319] eta: 0:57:56 lr: 1.7322408386546176e-06 loss: 0.0276 (0.0309) time: 2.6433 data: 0.0060 max mem: 33369 +Epoch: [39] [ 70/1319] eta: 0:57:08 lr: 1.7198430786433514e-06 loss: 0.0279 (0.0314) time: 2.6361 data: 0.0060 max mem: 33369 +Epoch: [39] [ 80/1319] eta: 0:56:26 lr: 1.7074353804367206e-06 loss: 0.0317 (0.0317) time: 2.6460 data: 0.0059 max mem: 33369 +Epoch: [39] [ 90/1319] eta: 0:55:49 lr: 1.6950176556933094e-06 loss: 0.0281 (0.0315) time: 2.6559 data: 0.0060 max mem: 33369 +Epoch: [39] [ 100/1319] eta: 0:55:11 lr: 1.682589814560305e-06 loss: 0.0342 (0.0330) time: 2.6485 data: 0.0061 max mem: 33369 +Epoch: [39] [ 110/1319] eta: 0:54:32 lr: 1.6701517656350208e-06 loss: 0.0342 (0.0331) time: 2.6240 data: 0.0060 max mem: 33369 +Epoch: [39] [ 120/1319] eta: 0:53:55 lr: 1.6577034159251048e-06 loss: 0.0301 (0.0331) time: 2.6097 data: 0.0059 max mem: 33369 +Epoch: [39] [ 130/1319] eta: 0:53:31 lr: 1.6452446708073954e-06 loss: 0.0301 (0.0329) time: 2.6647 data: 0.0060 max mem: 33369 +Epoch: [39] [ 140/1319] eta: 0:53:04 lr: 1.632775433985313e-06 loss: 0.0289 (0.0327) time: 2.7130 data: 0.0059 max mem: 33369 +Epoch: [39] [ 150/1319] eta: 0:52:29 lr: 1.62029560744485e-06 loss: 0.0252 (0.0323) time: 2.6512 data: 0.0058 max mem: 33369 +Epoch: [39] [ 160/1319] eta: 0:51:58 lr: 1.6078050914089353e-06 loss: 0.0263 (0.0321) time: 2.6213 data: 0.0060 max mem: 33369 +Epoch: [39] [ 170/1319] eta: 0:51:28 lr: 1.5953037842902214e-06 loss: 0.0323 (0.0324) time: 2.6433 data: 0.0064 max mem: 33369 +Epoch: [39] [ 180/1319] eta: 0:51:01 lr: 1.5827915826421849e-06 loss: 0.0325 (0.0323) time: 2.6653 data: 0.0062 max mem: 33369 +Epoch: [39] [ 190/1319] eta: 0:50:33 lr: 1.5702683811084266e-06 loss: 0.0294 (0.0324) time: 2.6754 data: 0.0060 max mem: 33369 +Epoch: [39] [ 200/1319] eta: 0:50:02 lr: 1.5577340723702017e-06 loss: 0.0283 (0.0322) time: 2.6349 data: 0.0061 max mem: 33369 +Epoch: [39] [ 210/1319] eta: 0:49:32 lr: 1.5451885470919527e-06 loss: 0.0271 (0.0320) time: 2.6176 data: 0.0060 max mem: 33369 +Epoch: [39] [ 220/1319] eta: 0:49:03 lr: 1.5326316938648584e-06 loss: 0.0282 (0.0322) time: 2.6372 data: 0.0059 max mem: 33369 +Epoch: [39] [ 230/1319] eta: 0:48:35 lr: 1.5200633991482792e-06 loss: 0.0325 (0.0320) time: 2.6397 data: 0.0062 max mem: 33369 +Epoch: [39] [ 240/1319] eta: 0:48:08 lr: 1.5074835472089545e-06 loss: 0.0262 (0.0319) time: 2.6623 data: 0.0060 max mem: 33369 +Epoch: [39] [ 250/1319] eta: 0:47:40 lr: 1.4948920200579605e-06 loss: 0.0251 (0.0319) time: 2.6611 data: 0.0058 max mem: 33369 +Epoch: [39] [ 260/1319] eta: 0:47:11 lr: 1.4822886973851744e-06 loss: 0.0305 (0.0320) time: 2.6265 data: 0.0060 max mem: 33369 +Epoch: [39] [ 270/1319] eta: 0:46:42 lr: 1.4696734564912314e-06 loss: 0.0305 (0.0320) time: 2.6250 data: 0.0060 max mem: 33369 +Epoch: [39] [ 280/1319] eta: 0:46:13 lr: 1.457046172216814e-06 loss: 0.0331 (0.0321) time: 2.6240 data: 0.0059 max mem: 33369 +Epoch: [39] [ 290/1319] eta: 0:45:44 lr: 1.444406716869153e-06 loss: 0.0331 (0.0322) time: 2.6015 data: 0.0058 max mem: 33369 +Epoch: [39] [ 300/1319] eta: 0:45:18 lr: 1.4317549601455566e-06 loss: 0.0304 (0.0322) time: 2.6394 data: 0.0060 max mem: 33369 +Epoch: [39] [ 310/1319] eta: 0:44:49 lr: 1.419090769053936e-06 loss: 0.0347 (0.0329) time: 2.6477 data: 0.0061 max mem: 33369 +Epoch: [39] [ 320/1319] eta: 0:44:21 lr: 1.4064140078300187e-06 loss: 0.0352 (0.0329) time: 2.6095 data: 0.0059 max mem: 33369 +Epoch: [39] [ 330/1319] eta: 0:43:54 lr: 1.3937245378511972e-06 loss: 0.0302 (0.0328) time: 2.6331 data: 0.0059 max mem: 33369 +Epoch: [39] [ 340/1319] eta: 0:43:28 lr: 1.3810222175468009e-06 loss: 0.0286 (0.0328) time: 2.6751 data: 0.0059 max mem: 33369 +Epoch: [39] [ 350/1319] eta: 0:43:01 lr: 1.3683069023045655e-06 loss: 0.0276 (0.0327) time: 2.6683 data: 0.0059 max mem: 33369 +Epoch: [39] [ 360/1319] eta: 0:42:34 lr: 1.355578444373217e-06 loss: 0.0273 (0.0325) time: 2.6491 data: 0.0060 max mem: 33369 +Epoch: [39] [ 370/1319] eta: 0:42:07 lr: 1.3428366927608033e-06 loss: 0.0282 (0.0325) time: 2.6539 data: 0.0059 max mem: 33369 +Epoch: [39] [ 380/1319] eta: 0:41:40 lr: 1.330081493128668e-06 loss: 0.0308 (0.0324) time: 2.6418 data: 0.0060 max mem: 33369 +Epoch: [39] [ 390/1319] eta: 0:41:13 lr: 1.3173126876807778e-06 loss: 0.0290 (0.0324) time: 2.6533 data: 0.0061 max mem: 33369 +Epoch: [39] [ 400/1319] eta: 0:40:46 lr: 1.304530115048165e-06 loss: 0.0291 (0.0325) time: 2.6536 data: 0.0059 max mem: 33369 +Epoch: [39] [ 410/1319] eta: 0:40:19 lr: 1.2917336101681678e-06 loss: 0.0299 (0.0325) time: 2.6361 data: 0.0058 max mem: 33369 +Epoch: [39] [ 420/1319] eta: 0:39:52 lr: 1.2789230041582899e-06 loss: 0.0295 (0.0324) time: 2.6343 data: 0.0058 max mem: 33369 +Epoch: [39] [ 430/1319] eta: 0:39:25 lr: 1.2660981241842216e-06 loss: 0.0276 (0.0324) time: 2.6532 data: 0.0059 max mem: 33369 +Epoch: [39] [ 440/1319] eta: 0:38:58 lr: 1.2532587933218004e-06 loss: 0.0276 (0.0323) time: 2.6571 data: 0.0059 max mem: 33369 +Epoch: [39] [ 450/1319] eta: 0:38:31 lr: 1.2404048304125217e-06 loss: 0.0309 (0.0323) time: 2.6372 data: 0.0059 max mem: 33369 +Epoch: [39] [ 460/1319] eta: 0:38:05 lr: 1.2275360499121832e-06 loss: 0.0309 (0.0323) time: 2.6431 data: 0.0060 max mem: 33369 +Epoch: [39] [ 470/1319] eta: 0:37:37 lr: 1.2146522617323656e-06 loss: 0.0307 (0.0323) time: 2.6353 data: 0.0060 max mem: 33369 +Epoch: [39] [ 480/1319] eta: 0:37:10 lr: 1.2017532710741682e-06 loss: 0.0289 (0.0323) time: 2.6321 data: 0.0058 max mem: 33369 +Epoch: [39] [ 490/1319] eta: 0:36:44 lr: 1.1888388782538434e-06 loss: 0.0287 (0.0322) time: 2.6663 data: 0.0058 max mem: 33369 +Epoch: [39] [ 500/1319] eta: 0:36:17 lr: 1.175908878519789e-06 loss: 0.0269 (0.0321) time: 2.6396 data: 0.0058 max mem: 33369 +Epoch: [39] [ 510/1319] eta: 0:35:50 lr: 1.1629630618603247e-06 loss: 0.0283 (0.0321) time: 2.6160 data: 0.0057 max mem: 33369 +Epoch: [39] [ 520/1319] eta: 0:35:22 lr: 1.150001212801783e-06 loss: 0.0282 (0.0321) time: 2.6214 data: 0.0058 max mem: 33369 +Epoch: [39] [ 530/1319] eta: 0:34:55 lr: 1.1370231101961411e-06 loss: 0.0282 (0.0320) time: 2.6087 data: 0.0060 max mem: 33369 +Epoch: [39] [ 540/1319] eta: 0:34:28 lr: 1.1240285269976361e-06 loss: 0.0307 (0.0322) time: 2.6237 data: 0.0059 max mem: 33369 +Epoch: [39] [ 550/1319] eta: 0:34:01 lr: 1.1110172300275867e-06 loss: 0.0307 (0.0322) time: 2.6406 data: 0.0059 max mem: 33369 +Epoch: [39] [ 560/1319] eta: 0:33:35 lr: 1.097988979726662e-06 loss: 0.0319 (0.0323) time: 2.6612 data: 0.0059 max mem: 33369 +Epoch: [39] [ 570/1319] eta: 0:33:08 lr: 1.084943529893699e-06 loss: 0.0317 (0.0322) time: 2.6472 data: 0.0059 max mem: 33369 +Epoch: [39] [ 580/1319] eta: 0:32:42 lr: 1.0718806274102695e-06 loss: 0.0274 (0.0322) time: 2.6390 data: 0.0059 max mem: 33369 +Epoch: [39] [ 590/1319] eta: 0:32:15 lr: 1.0588000119498569e-06 loss: 0.0291 (0.0322) time: 2.6527 data: 0.0058 max mem: 33369 +Epoch: [39] [ 600/1319] eta: 0:31:48 lr: 1.0457014156706775e-06 loss: 0.0295 (0.0321) time: 2.6195 data: 0.0059 max mem: 33369 +Epoch: [39] [ 610/1319] eta: 0:31:21 lr: 1.032584562890946e-06 loss: 0.0295 (0.0321) time: 2.6254 data: 0.0061 max mem: 33369 +Epoch: [39] [ 620/1319] eta: 0:30:54 lr: 1.0194491697452832e-06 loss: 0.0298 (0.0322) time: 2.6394 data: 0.0060 max mem: 33369 +Epoch: [39] [ 630/1319] eta: 0:30:28 lr: 1.0062949438209979e-06 loss: 0.0284 (0.0321) time: 2.6453 data: 0.0058 max mem: 33369 +Epoch: [39] [ 640/1319] eta: 0:30:01 lr: 9.931215837725994e-07 loss: 0.0284 (0.0321) time: 2.6669 data: 0.0058 max mem: 33369 +Epoch: [39] [ 650/1319] eta: 0:29:35 lr: 9.799287789130144e-07 loss: 0.0306 (0.0321) time: 2.6509 data: 0.0059 max mem: 33369 +Epoch: [39] [ 660/1319] eta: 0:29:08 lr: 9.667162087796925e-07 loss: 0.0289 (0.0321) time: 2.6212 data: 0.0059 max mem: 33369 +Epoch: [39] [ 670/1319] eta: 0:28:41 lr: 9.534835426736097e-07 loss: 0.0289 (0.0322) time: 2.6136 data: 0.0058 max mem: 33369 +Epoch: [39] [ 680/1319] eta: 0:28:15 lr: 9.402304391691554e-07 loss: 0.0293 (0.0322) time: 2.6564 data: 0.0059 max mem: 33369 +Epoch: [39] [ 690/1319] eta: 0:27:48 lr: 9.269565455924141e-07 loss: 0.0281 (0.0322) time: 2.6771 data: 0.0059 max mem: 33369 +Epoch: [39] [ 700/1319] eta: 0:27:22 lr: 9.136614974653884e-07 loss: 0.0295 (0.0322) time: 2.6480 data: 0.0058 max mem: 33369 +Epoch: [39] [ 710/1319] eta: 0:26:55 lr: 9.003449179133091e-07 loss: 0.0305 (0.0322) time: 2.6579 data: 0.0059 max mem: 33369 +Epoch: [39] [ 720/1319] eta: 0:26:29 lr: 8.870064170319405e-07 loss: 0.0264 (0.0321) time: 2.6762 data: 0.0059 max mem: 33369 +Epoch: [39] [ 730/1319] eta: 0:26:02 lr: 8.736455912114245e-07 loss: 0.0263 (0.0320) time: 2.6468 data: 0.0059 max mem: 33369 +Epoch: [39] [ 740/1319] eta: 0:25:36 lr: 8.602620224130043e-07 loss: 0.0306 (0.0321) time: 2.6296 data: 0.0060 max mem: 33369 +Epoch: [39] [ 750/1319] eta: 0:25:09 lr: 8.468552773943076e-07 loss: 0.0323 (0.0321) time: 2.6551 data: 0.0058 max mem: 33369 +Epoch: [39] [ 760/1319] eta: 0:24:43 lr: 8.334249068786857e-07 loss: 0.0278 (0.0320) time: 2.6613 data: 0.0058 max mem: 33369 +Epoch: [39] [ 770/1319] eta: 0:24:16 lr: 8.199704446634483e-07 loss: 0.0285 (0.0321) time: 2.6422 data: 0.0061 max mem: 33369 +Epoch: [39] [ 780/1319] eta: 0:23:49 lr: 8.064914066612595e-07 loss: 0.0318 (0.0321) time: 2.6246 data: 0.0062 max mem: 33369 +Epoch: [39] [ 790/1319] eta: 0:23:23 lr: 7.92987289868475e-07 loss: 0.0318 (0.0321) time: 2.6303 data: 0.0059 max mem: 33369 +Epoch: [39] [ 800/1319] eta: 0:22:56 lr: 7.79457571253187e-07 loss: 0.0336 (0.0322) time: 2.6339 data: 0.0058 max mem: 33369 +Epoch: [39] [ 810/1319] eta: 0:22:29 lr: 7.659017065551902e-07 loss: 0.0341 (0.0323) time: 2.6277 data: 0.0059 max mem: 33369 +Epoch: [39] [ 820/1319] eta: 0:22:03 lr: 7.523191289889679e-07 loss: 0.0370 (0.0324) time: 2.6355 data: 0.0059 max mem: 33369 +Epoch: [39] [ 830/1319] eta: 0:21:36 lr: 7.387092478397154e-07 loss: 0.0320 (0.0323) time: 2.6507 data: 0.0059 max mem: 33369 +Epoch: [39] [ 840/1319] eta: 0:21:10 lr: 7.250714469413284e-07 loss: 0.0295 (0.0324) time: 2.6488 data: 0.0059 max mem: 33369 +Epoch: [39] [ 850/1319] eta: 0:20:43 lr: 7.114050830235778e-07 loss: 0.0292 (0.0323) time: 2.6267 data: 0.0058 max mem: 33369 +Epoch: [39] [ 860/1319] eta: 0:20:16 lr: 6.977094839143229e-07 loss: 0.0285 (0.0323) time: 2.6392 data: 0.0059 max mem: 33369 +Epoch: [39] [ 870/1319] eta: 0:19:50 lr: 6.839839465805414e-07 loss: 0.0278 (0.0323) time: 2.6392 data: 0.0060 max mem: 33369 +Epoch: [39] [ 880/1319] eta: 0:19:23 lr: 6.702277349898191e-07 loss: 0.0275 (0.0323) time: 2.6537 data: 0.0058 max mem: 33369 +Epoch: [39] [ 890/1319] eta: 0:18:57 lr: 6.564400777713066e-07 loss: 0.0306 (0.0323) time: 2.6698 data: 0.0059 max mem: 33369 +Epoch: [39] [ 900/1319] eta: 0:18:30 lr: 6.426201656523381e-07 loss: 0.0335 (0.0324) time: 2.6578 data: 0.0061 max mem: 33369 +Epoch: [39] [ 910/1319] eta: 0:18:04 lr: 6.287671486431178e-07 loss: 0.0335 (0.0324) time: 2.6547 data: 0.0059 max mem: 33369 +Epoch: [39] [ 920/1319] eta: 0:17:37 lr: 6.148801329380617e-07 loss: 0.0328 (0.0324) time: 2.6529 data: 0.0057 max mem: 33369 +Epoch: [39] [ 930/1319] eta: 0:17:11 lr: 6.009581774973726e-07 loss: 0.0309 (0.0324) time: 2.6385 data: 0.0058 max mem: 33369 +Epoch: [39] [ 940/1319] eta: 0:16:44 lr: 5.870002902666957e-07 loss: 0.0284 (0.0323) time: 2.6356 data: 0.0060 max mem: 33369 +Epoch: [39] [ 950/1319] eta: 0:16:18 lr: 5.7300542398606e-07 loss: 0.0277 (0.0323) time: 2.6546 data: 0.0060 max mem: 33369 +Epoch: [39] [ 960/1319] eta: 0:15:51 lr: 5.589724715308914e-07 loss: 0.0284 (0.0323) time: 2.6557 data: 0.0060 max mem: 33369 +Epoch: [39] [ 970/1319] eta: 0:15:25 lr: 5.449002607184345e-07 loss: 0.0288 (0.0322) time: 2.6547 data: 0.0058 max mem: 33369 +Epoch: [39] [ 980/1319] eta: 0:14:58 lr: 5.307875485010082e-07 loss: 0.0288 (0.0323) time: 2.6328 data: 0.0060 max mem: 33369 +Epoch: [39] [ 990/1319] eta: 0:14:31 lr: 5.166330144533874e-07 loss: 0.0333 (0.0323) time: 2.6148 data: 0.0061 max mem: 33369 +Epoch: [39] [1000/1319] eta: 0:14:05 lr: 5.024352534442401e-07 loss: 0.0312 (0.0323) time: 2.6276 data: 0.0058 max mem: 33369 +Epoch: [39] [1010/1319] eta: 0:13:38 lr: 4.881927673605746e-07 loss: 0.0312 (0.0323) time: 2.6435 data: 0.0058 max mem: 33369 +Epoch: [39] [1020/1319] eta: 0:13:12 lr: 4.7390395572780197e-07 loss: 0.0312 (0.0323) time: 2.6571 data: 0.0058 max mem: 33369 +Epoch: [39] [1030/1319] eta: 0:12:45 lr: 4.595671050360423e-07 loss: 0.0302 (0.0323) time: 2.6510 data: 0.0060 max mem: 33369 +Epoch: [39] [1040/1319] eta: 0:12:19 lr: 4.4518037654287396e-07 loss: 0.0294 (0.0323) time: 2.6266 data: 0.0060 max mem: 33369 +Epoch: [39] [1050/1319] eta: 0:11:52 lr: 4.3074179227215756e-07 loss: 0.0295 (0.0323) time: 2.6029 data: 0.0061 max mem: 33369 +Epoch: [39] [1060/1319] eta: 0:11:26 lr: 4.162492188647174e-07 loss: 0.0303 (0.0323) time: 2.6358 data: 0.0062 max mem: 33369 +Epoch: [39] [1070/1319] eta: 0:10:59 lr: 4.01700348854669e-07 loss: 0.0303 (0.0323) time: 2.6649 data: 0.0061 max mem: 33369 +Epoch: [39] [1080/1319] eta: 0:10:33 lr: 3.8709267884030336e-07 loss: 0.0275 (0.0322) time: 2.6462 data: 0.0059 max mem: 33369 +Epoch: [39] [1090/1319] eta: 0:10:06 lr: 3.724234838815835e-07 loss: 0.0285 (0.0323) time: 2.6296 data: 0.0058 max mem: 33369 +Epoch: [39] [1100/1319] eta: 0:09:40 lr: 3.5768978727688177e-07 loss: 0.0297 (0.0323) time: 2.6152 data: 0.0058 max mem: 33369 +Epoch: [39] [1110/1319] eta: 0:09:13 lr: 3.428883246336122e-07 loss: 0.0271 (0.0322) time: 2.5820 data: 0.0060 max mem: 33369 +Epoch: [39] [1120/1319] eta: 0:08:46 lr: 3.280155008272766e-07 loss: 0.0308 (0.0322) time: 2.5946 data: 0.0061 max mem: 33369 +Epoch: [39] [1130/1319] eta: 0:08:20 lr: 3.1306733800860497e-07 loss: 0.0318 (0.0322) time: 2.6158 data: 0.0060 max mem: 33369 +Epoch: [39] [1140/1319] eta: 0:07:53 lr: 2.9803941221786203e-07 loss: 0.0287 (0.0322) time: 2.6134 data: 0.0062 max mem: 33369 +Epoch: [39] [1150/1319] eta: 0:07:27 lr: 2.829267753240405e-07 loss: 0.0340 (0.0322) time: 2.6280 data: 0.0060 max mem: 33369 +Epoch: [39] [1160/1319] eta: 0:07:00 lr: 2.677238578071334e-07 loss: 0.0342 (0.0322) time: 2.6183 data: 0.0060 max mem: 33369 +Epoch: [39] [1170/1319] eta: 0:06:34 lr: 2.524243461593822e-07 loss: 0.0276 (0.0322) time: 2.6362 data: 0.0060 max mem: 33369 +Epoch: [39] [1180/1319] eta: 0:06:07 lr: 2.370210260957732e-07 loss: 0.0276 (0.0322) time: 2.6226 data: 0.0059 max mem: 33369 +Epoch: [39] [1190/1319] eta: 0:05:41 lr: 2.2150557883672493e-07 loss: 0.0294 (0.0322) time: 2.6142 data: 0.0061 max mem: 33369 +Epoch: [39] [1200/1319] eta: 0:05:14 lr: 2.058683115970694e-07 loss: 0.0271 (0.0322) time: 2.6483 data: 0.0060 max mem: 33369 +Epoch: [39] [1210/1319] eta: 0:04:48 lr: 1.9009779355624344e-07 loss: 0.0292 (0.0321) time: 2.6370 data: 0.0059 max mem: 33369 +Epoch: [39] [1220/1319] eta: 0:04:21 lr: 1.7418035215766808e-07 loss: 0.0282 (0.0321) time: 2.6278 data: 0.0059 max mem: 33369 +Epoch: [39] [1230/1319] eta: 0:03:55 lr: 1.5809935607220197e-07 loss: 0.0276 (0.0321) time: 2.6275 data: 0.0058 max mem: 33369 +Epoch: [39] [1240/1319] eta: 0:03:29 lr: 1.4183415922236583e-07 loss: 0.0307 (0.0321) time: 2.6172 data: 0.0058 max mem: 33369 +Epoch: [39] [1250/1319] eta: 0:03:02 lr: 1.2535848000328487e-07 loss: 0.0314 (0.0321) time: 2.6328 data: 0.0060 max mem: 33369 +Epoch: [39] [1260/1319] eta: 0:02:36 lr: 1.0863778202227116e-07 loss: 0.0314 (0.0321) time: 2.6391 data: 0.0058 max mem: 33369 +Epoch: [39] [1270/1319] eta: 0:02:09 lr: 9.162475150165058e-08 loss: 0.0303 (0.0321) time: 2.6422 data: 0.0058 max mem: 33369 +Epoch: [39] [1280/1319] eta: 0:01:43 lr: 7.425076510067331e-08 loss: 0.0302 (0.0321) time: 2.6569 data: 0.0059 max mem: 33369 +Epoch: [39] [1290/1319] eta: 0:01:16 lr: 5.640763927216541e-08 loss: 0.0331 (0.0321) time: 2.6454 data: 0.0059 max mem: 33369 +Epoch: [39] [1300/1319] eta: 0:00:50 lr: 3.790015191412361e-08 loss: 0.0332 (0.0321) time: 2.6297 data: 0.0058 max mem: 33369 +Epoch: [39] [1310/1319] eta: 0:00:23 lr: 1.8267397722216235e-08 loss: 0.0293 (0.0321) time: 2.6244 data: 0.0059 max mem: 33369 +Epoch: [39] Total time: 0:58:09 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 1:40:43 time: 2.3487 data: 2.1486 max mem: 33369 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 100/2573] eta: 0:03:58 time: 0.0718 data: 0.0011 max mem: 33369 +Test: [ 200/2573] eta: 0:03:22 time: 0.0734 data: 0.0011 max mem: 33369 +Test: [ 300/2573] eta: 0:03:04 time: 0.0751 data: 0.0011 max mem: 33369 +Test: [ 400/2573] eta: 0:02:51 time: 0.0752 data: 0.0011 max mem: 33369 +Test: [ 500/2573] eta: 0:02:41 time: 0.0736 data: 0.0011 max mem: 33369 +Test: [ 600/2573] eta: 0:02:32 time: 0.0736 data: 0.0011 max mem: 33369 +Test: [ 700/2573] eta: 0:02:24 time: 0.0738 data: 0.0011 max mem: 33369 +Test: [ 800/2573] eta: 0:02:16 time: 0.0771 data: 0.0011 max mem: 33369 +Test: [ 900/2573] eta: 0:02:08 time: 0.0738 data: 0.0011 max mem: 33369 +Test: [1000/2573] eta: 0:02:00 time: 0.0738 data: 0.0011 max mem: 33369 +Test: [1100/2573] eta: 0:01:52 time: 0.0738 data: 0.0011 max mem: 33369 +Test: [1200/2573] eta: 0:01:44 time: 0.0738 data: 0.0011 max mem: 33369 +Test: [1300/2573] eta: 0:01:36 time: 0.0738 data: 0.0011 max mem: 33369 +Test: [1400/2573] eta: 0:01:28 time: 0.0721 data: 0.0011 max mem: 33369 +Test: [1500/2573] eta: 0:01:21 time: 0.0737 data: 0.0011 max mem: 33369 +Test: [1600/2573] eta: 0:01:13 time: 0.0771 data: 0.0011 max mem: 33369 +Test: [1700/2573] eta: 0:01:05 time: 0.0720 data: 0.0011 max mem: 33369 +Test: [1800/2573] eta: 0:00:58 time: 0.0754 data: 0.0011 max mem: 33369 +Test: [1900/2573] eta: 0:00:50 time: 0.0722 data: 0.0011 max mem: 33369 +Test: [2000/2573] eta: 0:00:42 time: 0.0738 data: 0.0011 max mem: 33369 +Test: [2100/2573] eta: 0:00:35 time: 0.0754 data: 0.0011 max mem: 33369 +Test: [2200/2573] eta: 0:00:27 time: 0.0753 data: 0.0011 max mem: 33369 +Test: [2300/2573] eta: 0:00:20 time: 0.0754 data: 0.0011 max mem: 33369 +Test: [2400/2573] eta: 0:00:12 time: 0.0705 data: 0.0011 max mem: 33369 +Test: [2500/2573] eta: 0:00:05 time: 0.0738 data: 0.0011 max mem: 33369 +Test: Total time: 0:03:12 +Final results: +Mean IoU is 65.03 + + precision@0.5 = 73.18 + precision@0.6 = 68.26 + precision@0.7 = 61.76 + precision@0.8 = 50.84 + precision@0.9 = 26.16 + overall IoU = 62.08 + +Average object IoU 65.03272537907864 +Overall IoU 62.08176803588867 +Training time 1 day, 16:43:38 +./scripts/baseline_test_lr.sh: line 65: unexpected EOF while looking for matching `"' +./scripts/baseline_test_lr.sh: line 76: syntax error: unexpected end of file diff --git a/LAVT-RIS/logs/gref_m10_tmp010_4gpu_bs32_orig.log b/LAVT-RIS/logs/gref_m10_tmp010_4gpu_bs32_orig.log new file mode 100644 index 0000000000000000000000000000000000000000..1c3c2f66892566b571ecb92caece8bdb6eaa7858 --- /dev/null +++ b/LAVT-RIS/logs/gref_m10_tmp010_4gpu_bs32_orig.log @@ -0,0 +1,12093 @@ +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torch/distributed/launch.py:178: FutureWarning: The module torch.distributed.launch is deprecated +and will be removed in future. Use torchrun. +Note that --use_env is set by default in torchrun. +If your script expects `--local_rank` argument to be set, please +change it to read from `os.environ['LOCAL_RANK']` instead. See +https://pytorch.org/docs/stable/distributed.html#launch-utility for +further instructions + + warnings.warn( +WARNING:torch.distributed.run: +***************************************** +Setting OMP_NUM_THREADS environment variable for each process to be 1 in default, to avoid your system being overloaded, please further tune the variable for optimal performance in your application as needed. +***************************************** +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/timm/models/layers/__init__.py:48: FutureWarning: Importing from timm.models.layers is deprecated, please import via timm.layers + warnings.warn(f"Importing from {__name__} is deprecated, please import via timm.layers", FutureWarning) +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/timm/models/layers/__init__.py:48: FutureWarning: Importing from timm.models.layers is deprecated, please import via timm.layers + warnings.warn(f"Importing from {__name__} is deprecated, please import via timm.layers", FutureWarning) +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/timm/models/layers/__init__.py:48: FutureWarning: Importing from timm.models.layers is deprecated, please import via timm.layers + warnings.warn(f"Importing from {__name__} is deprecated, please import via timm.layers", FutureWarning) +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/timm/models/layers/__init__.py:48: FutureWarning: Importing from timm.models.layers is deprecated, please import via timm.layers + warnings.warn(f"Importing from {__name__} is deprecated, please import via timm.layers", FutureWarning) +RANK and WORLD_SIZE in environment: 2/4RANK and WORLD_SIZE in environment: 0/4RANK and WORLD_SIZE in environment: 1/4 + + +RANK and WORLD_SIZE in environment: 3/4 +Image size: 480 +loading dataset refcocog into memory... +creating index... +index created. +DONE (t=5.38s) +loading dataset refcocog into memory... +creating index... +index created. +DONE (t=5.15s) +local rank 0 / global rank 0 successfully built train dataset. +lavt_one +Window size 12! +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torch/functional.py:478: UserWarning: torch.meshgrid: in an upcoming release, it will be required to pass the indexing argument. (Triggered internally at ../aten/src/ATen/native/TensorShape.cpp:2894.) + return _VF.meshgrid(tensors, **kwargs) # type: ignore[attr-defined] +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torch/functional.py:478: UserWarning: torch.meshgrid: in an upcoming release, it will be required to pass the indexing argument. (Triggered internally at ../aten/src/ATen/native/TensorShape.cpp:2894.) + return _VF.meshgrid(tensors, **kwargs) # type: ignore[attr-defined] +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torch/functional.py:478: UserWarning: torch.meshgrid: in an upcoming release, it will be required to pass the indexing argument. (Triggered internally at ../aten/src/ATen/native/TensorShape.cpp:2894.) + return _VF.meshgrid(tensors, **kwargs) # type: ignore[attr-defined] +Initializing Multi-modal Swin Transformer weights from ./pretrained_weights/swin_base_patch4_window12_384_22k.pth +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torch/functional.py:478: UserWarning: torch.meshgrid: in an upcoming release, it will be required to pass the indexing argument. (Triggered internally at ../aten/src/ATen/native/TensorShape.cpp:2894.) + return _VF.meshgrid(tensors, **kwargs) # type: ignore[attr-defined] +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [0] [ 0/1319] eta: 5:53:59 lr: 4.9999147080313756e-05 loss: 0.7920 (0.7920) time: 16.1029 data: 2.6305 max mem: 20156 +Epoch: [0] [ 10/1319] eta: 1:23:38 lr: 4.999061779453083e-05 loss: 0.3941 (0.4359) time: 3.8341 data: 0.2464 max mem: 28287 +Epoch: [0] [ 20/1319] eta: 1:10:36 lr: 4.9982088347050674e-05 loss: 0.3302 (0.3851) time: 2.6191 data: 0.0064 max mem: 28287 +Epoch: [0] [ 30/1319] eta: 1:05:57 lr: 4.9973558737839576e-05 loss: 0.3088 (0.3592) time: 2.6503 data: 0.0054 max mem: 29995 +Epoch: [0] [ 40/1319] eta: 1:05:16 lr: 4.9965028966863786e-05 loss: 0.2764 (0.3415) time: 2.8524 data: 0.0057 max mem: 29995 +Epoch: [0] [ 50/1319] eta: 1:03:02 lr: 4.995649903408956e-05 loss: 0.2764 (0.3333) time: 2.8414 data: 0.0058 max mem: 29995 +Epoch: [0] [ 60/1319] eta: 1:01:11 lr: 4.9947968939483133e-05 loss: 0.2887 (0.3339) time: 2.6173 data: 0.0057 max mem: 29995 +Epoch: [0] [ 70/1319] eta: 1:00:44 lr: 4.993943868301072e-05 loss: 0.2905 (0.3269) time: 2.7584 data: 0.0056 max mem: 29995 +Epoch: [0] [ 80/1319] eta: 0:59:28 lr: 4.993090826463852e-05 loss: 0.2623 (0.3194) time: 2.7718 data: 0.0057 max mem: 29995 +Epoch: [0] [ 90/1319] eta: 0:58:28 lr: 4.9922377684332736e-05 loss: 0.2623 (0.3143) time: 2.6304 data: 0.0057 max mem: 29996 +Epoch: [0] [ 100/1319] eta: 0:57:34 lr: 4.991384694205954e-05 loss: 0.2601 (0.3095) time: 2.6471 data: 0.0055 max mem: 29996 +Epoch: [0] [ 110/1319] eta: 0:56:43 lr: 4.990531603778512e-05 loss: 0.2949 (0.3111) time: 2.6364 data: 0.0057 max mem: 29996 +Epoch: [0] [ 120/1319] eta: 0:55:56 lr: 4.98967849714756e-05 loss: 0.2949 (0.3077) time: 2.6260 data: 0.0057 max mem: 29996 +Epoch: [0] [ 130/1319] eta: 0:55:15 lr: 4.988825374309713e-05 loss: 0.2646 (0.3051) time: 2.6363 data: 0.0057 max mem: 29997 +Epoch: [0] [ 140/1319] eta: 0:54:31 lr: 4.987972235261584e-05 loss: 0.2475 (0.3010) time: 2.6206 data: 0.0056 max mem: 29997 +Epoch: [0] [ 150/1319] eta: 0:53:54 lr: 4.987119079999784e-05 loss: 0.2486 (0.3005) time: 2.6296 data: 0.0055 max mem: 29997 +Epoch: [0] [ 160/1319] eta: 0:53:12 lr: 4.986265908520923e-05 loss: 0.2459 (0.2970) time: 2.6126 data: 0.0056 max mem: 29997 +Epoch: [0] [ 170/1319] eta: 0:52:34 lr: 4.985412720821609e-05 loss: 0.2450 (0.2961) time: 2.5817 data: 0.0056 max mem: 29997 +Epoch: [0] [ 180/1319] eta: 0:52:00 lr: 4.984559516898449e-05 loss: 0.2485 (0.2930) time: 2.6190 data: 0.0055 max mem: 29997 +Epoch: [0] [ 190/1319] eta: 0:51:24 lr: 4.98370629674805e-05 loss: 0.2485 (0.2914) time: 2.6193 data: 0.0056 max mem: 29997 +Epoch: [0] [ 200/1319] eta: 0:50:50 lr: 4.982853060367015e-05 loss: 0.2519 (0.2897) time: 2.6078 data: 0.0057 max mem: 29997 +Epoch: [0] [ 210/1319] eta: 0:50:18 lr: 4.9819998077519475e-05 loss: 0.2465 (0.2890) time: 2.6224 data: 0.0056 max mem: 29997 +Epoch: [0] [ 220/1319] eta: 0:49:46 lr: 4.98114653889945e-05 loss: 0.2295 (0.2864) time: 2.6302 data: 0.0055 max mem: 29997 +Epoch: [0] [ 230/1319] eta: 0:49:14 lr: 4.980293253806122e-05 loss: 0.2306 (0.2848) time: 2.6256 data: 0.0055 max mem: 29997 +Epoch: [0] [ 240/1319] eta: 0:48:42 lr: 4.9794399524685624e-05 loss: 0.2306 (0.2835) time: 2.6044 data: 0.0057 max mem: 29997 +Epoch: [0] [ 250/1319] eta: 0:48:10 lr: 4.97858663488337e-05 loss: 0.2369 (0.2816) time: 2.5978 data: 0.0055 max mem: 29997 +Epoch: [0] [ 260/1319] eta: 0:47:40 lr: 4.977733301047139e-05 loss: 0.2209 (0.2790) time: 2.6141 data: 0.0054 max mem: 29997 +Epoch: [0] [ 270/1319] eta: 0:47:11 lr: 4.9768799509564675e-05 loss: 0.2298 (0.2778) time: 2.6402 data: 0.0055 max mem: 29997 +Epoch: [0] [ 280/1319] eta: 0:46:42 lr: 4.976026584607946e-05 loss: 0.2298 (0.2760) time: 2.6439 data: 0.0054 max mem: 29997 +Epoch: [0] [ 290/1319] eta: 0:46:12 lr: 4.9751732019981684e-05 loss: 0.2369 (0.2760) time: 2.6307 data: 0.0056 max mem: 29997 +Epoch: [0] [ 300/1319] eta: 0:45:43 lr: 4.974319803123725e-05 loss: 0.2700 (0.2761) time: 2.6211 data: 0.0056 max mem: 29997 +Epoch: [0] [ 310/1319] eta: 0:45:14 lr: 4.973466387981205e-05 loss: 0.2716 (0.2762) time: 2.6294 data: 0.0055 max mem: 29997 +Epoch: [0] [ 320/1319] eta: 0:44:47 lr: 4.972612956567197e-05 loss: 0.2608 (0.2757) time: 2.6614 data: 0.0056 max mem: 31676 +Epoch: [0] [ 330/1319] eta: 0:44:17 lr: 4.971759508878288e-05 loss: 0.2230 (0.2743) time: 2.6276 data: 0.0057 max mem: 31676 +Epoch: [0] [ 340/1319] eta: 0:43:47 lr: 4.970906044911062e-05 loss: 0.2230 (0.2739) time: 2.5868 data: 0.0056 max mem: 31676 +Epoch: [0] [ 350/1319] eta: 0:43:17 lr: 4.970052564662105e-05 loss: 0.2325 (0.2727) time: 2.5872 data: 0.0054 max mem: 31676 +Epoch: [0] [ 360/1319] eta: 0:42:49 lr: 4.9691990681279974e-05 loss: 0.2164 (0.2714) time: 2.5922 data: 0.0054 max mem: 31676 +Epoch: [0] [ 370/1319] eta: 0:42:21 lr: 4.9683455553053225e-05 loss: 0.2128 (0.2706) time: 2.6259 data: 0.0055 max mem: 31676 +Epoch: [0] [ 380/1319] eta: 0:41:53 lr: 4.9674920261906595e-05 loss: 0.2114 (0.2691) time: 2.6416 data: 0.0055 max mem: 31676 +Epoch: [0] [ 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2.5964 data: 0.0056 max mem: 33368 +Epoch: [0] [ 710/1319] eta: 0:26:56 lr: 4.939316403135663e-05 loss: 0.2117 (0.2500) time: 2.6179 data: 0.0055 max mem: 33368 +Epoch: [0] [ 720/1319] eta: 0:26:29 lr: 4.938462318048596e-05 loss: 0.2117 (0.2494) time: 2.6331 data: 0.0055 max mem: 33368 +Epoch: [0] [ 730/1319] eta: 0:26:02 lr: 4.937608216548967e-05 loss: 0.1894 (0.2487) time: 2.6314 data: 0.0054 max mem: 33368 +Epoch: [0] [ 740/1319] eta: 0:25:36 lr: 4.936754098633307e-05 loss: 0.1894 (0.2486) time: 2.6326 data: 0.0054 max mem: 33368 +Epoch: [0] [ 750/1319] eta: 0:25:09 lr: 4.935899964298143e-05 loss: 0.1891 (0.2478) time: 2.6426 data: 0.0056 max mem: 33368 +Epoch: [0] [ 760/1319] eta: 0:24:42 lr: 4.9350458135400046e-05 loss: 0.1891 (0.2472) time: 2.6199 data: 0.0057 max mem: 33368 +Epoch: [0] [ 770/1319] eta: 0:24:15 lr: 4.934191646355415e-05 loss: 0.1961 (0.2469) time: 2.6097 data: 0.0056 max mem: 33368 +Epoch: [0] [ 780/1319] eta: 0:23:48 lr: 4.9333374627409e-05 loss: 0.2052 (0.2466) time: 2.6189 data: 0.0055 max mem: 33368 +Epoch: [0] [ 790/1319] eta: 0:23:22 lr: 4.932483262692982e-05 loss: 0.2052 (0.2461) time: 2.6059 data: 0.0056 max mem: 33368 +Epoch: [0] [ 800/1319] eta: 0:22:55 lr: 4.931629046208183e-05 loss: 0.1920 (0.2455) time: 2.6260 data: 0.0057 max mem: 33368 +Epoch: [0] [ 810/1319] eta: 0:22:28 lr: 4.9307748132830237e-05 loss: 0.2005 (0.2453) time: 2.6184 data: 0.0057 max mem: 33368 +Epoch: [0] [ 820/1319] eta: 0:22:02 lr: 4.929920563914022e-05 loss: 0.2247 (0.2452) time: 2.6140 data: 0.0057 max mem: 33368 +Epoch: [0] [ 830/1319] eta: 0:21:35 lr: 4.929066298097696e-05 loss: 0.2171 (0.2449) time: 2.6069 data: 0.0057 max mem: 33368 +Epoch: [0] [ 840/1319] eta: 0:21:08 lr: 4.928212015830561e-05 loss: 0.2034 (0.2443) time: 2.5918 data: 0.0056 max mem: 33368 +Epoch: [0] [ 850/1319] eta: 0:20:42 lr: 4.927357717109131e-05 loss: 0.2034 (0.2440) time: 2.6324 data: 0.0057 max mem: 33368 +Epoch: [0] [ 860/1319] eta: 0:20:15 lr: 4.926503401929921e-05 loss: 0.1923 (0.2437) time: 2.6393 data: 0.0057 max mem: 33368 +Epoch: [0] [ 870/1319] eta: 0:19:48 lr: 4.925649070289441e-05 loss: 0.2185 (0.2434) time: 2.6261 data: 0.0058 max mem: 33368 +Epoch: [0] [ 880/1319] eta: 0:19:22 lr: 4.9247947221842024e-05 loss: 0.2119 (0.2432) time: 2.6362 data: 0.0058 max mem: 33368 +Epoch: [0] [ 890/1319] eta: 0:18:55 lr: 4.923940357610714e-05 loss: 0.1966 (0.2429) time: 2.6309 data: 0.0057 max mem: 33368 +Epoch: [0] [ 900/1319] eta: 0:18:29 lr: 4.9230859765654824e-05 loss: 0.1806 (0.2423) time: 2.6270 data: 0.0058 max mem: 33368 +Epoch: [0] [ 910/1319] eta: 0:18:02 lr: 4.922231579045014e-05 loss: 0.1750 (0.2416) time: 2.6392 data: 0.0058 max mem: 33368 +Epoch: [0] [ 920/1319] eta: 0:17:36 lr: 4.921377165045815e-05 loss: 0.1806 (0.2413) time: 2.6479 data: 0.0057 max mem: 33368 +Epoch: [0] [ 930/1319] eta: 0:17:09 lr: 4.9205227345643864e-05 loss: 0.2018 (0.2411) time: 2.6463 data: 0.0059 max mem: 33368 +Epoch: [0] [ 940/1319] eta: 0:16:43 lr: 4.919668287597232e-05 loss: 0.2097 (0.2413) time: 2.6251 data: 0.0059 max mem: 33368 +Epoch: [0] [ 950/1319] eta: 0:16:16 lr: 4.918813824140851e-05 loss: 0.2097 (0.2409) time: 2.5987 data: 0.0059 max mem: 33368 +Epoch: [0] [ 960/1319] eta: 0:15:49 lr: 4.9179593441917424e-05 loss: 0.1915 (0.2405) time: 2.5960 data: 0.0058 max mem: 33368 +Epoch: [0] [ 970/1319] eta: 0:15:23 lr: 4.917104847746404e-05 loss: 0.2053 (0.2401) time: 2.6285 data: 0.0057 max mem: 33368 +Epoch: [0] [ 980/1319] eta: 0:14:56 lr: 4.916250334801333e-05 loss: 0.1932 (0.2395) time: 2.6309 data: 0.0058 max mem: 33368 +Epoch: [0] [ 990/1319] eta: 0:14:30 lr: 4.915395805353022e-05 loss: 0.1932 (0.2391) time: 2.6232 data: 0.0059 max mem: 33368 +Epoch: [0] [1000/1319] eta: 0:14:03 lr: 4.9145412593979664e-05 loss: 0.1936 (0.2388) time: 2.6266 data: 0.0059 max mem: 33368 +Epoch: [0] [1010/1319] eta: 0:13:37 lr: 4.913686696932656e-05 loss: 0.1921 (0.2384) time: 2.6253 data: 0.0060 max mem: 33368 +Epoch: [0] [1020/1319] eta: 0:13:10 lr: 4.9128321179535836e-05 loss: 0.1808 (0.2380) time: 2.6504 data: 0.0060 max mem: 33368 +Epoch: [0] [1030/1319] eta: 0:12:44 lr: 4.911977522457237e-05 loss: 0.2002 (0.2378) time: 2.6520 data: 0.0058 max mem: 33368 +Epoch: [0] [1040/1319] eta: 0:12:17 lr: 4.9111229104401044e-05 loss: 0.2082 (0.2376) time: 2.6289 data: 0.0059 max mem: 33368 +Epoch: [0] [1050/1319] eta: 0:11:51 lr: 4.910268281898671e-05 loss: 0.2082 (0.2374) time: 2.6199 data: 0.0060 max mem: 33368 +Epoch: [0] [1060/1319] eta: 0:11:24 lr: 4.9094136368294215e-05 loss: 0.2075 (0.2372) time: 2.6100 data: 0.0059 max mem: 33368 +Epoch: [0] [1070/1319] eta: 0:10:58 lr: 4.90855897522884e-05 loss: 0.2075 (0.2371) time: 2.6028 data: 0.0060 max mem: 33368 +Epoch: [0] [1080/1319] eta: 0:10:31 lr: 4.907704297093409e-05 loss: 0.1896 (0.2366) time: 2.5872 data: 0.0059 max mem: 33368 +Epoch: [0] [1090/1319] eta: 0:10:05 lr: 4.906849602419608e-05 loss: 0.1896 (0.2366) time: 2.5902 data: 0.0060 max mem: 33368 +Epoch: [0] [1100/1319] eta: 0:09:38 lr: 4.905994891203916e-05 loss: 0.2100 (0.2364) time: 2.6058 data: 0.0059 max mem: 33368 +Epoch: [0] [1110/1319] eta: 0:09:12 lr: 4.905140163442811e-05 loss: 0.2177 (0.2361) time: 2.5902 data: 0.0057 max mem: 33368 +Epoch: [0] [1120/1319] eta: 0:08:45 lr: 4.904285419132769e-05 loss: 0.1970 (0.2358) time: 2.6009 data: 0.0058 max mem: 33368 +Epoch: [0] [1130/1319] eta: 0:08:19 lr: 4.903430658270266e-05 loss: 0.1967 (0.2355) time: 2.6094 data: 0.0060 max mem: 33368 +Epoch: [0] [1140/1319] eta: 0:07:52 lr: 4.902575880851773e-05 loss: 0.1867 (0.2351) time: 2.6030 data: 0.0062 max mem: 33368 +Epoch: [0] [1150/1319] eta: 0:07:26 lr: 4.9017210868737634e-05 loss: 0.1861 (0.2347) time: 2.6193 data: 0.0063 max mem: 33368 +Epoch: [0] [1160/1319] eta: 0:06:59 lr: 4.900866276332707e-05 loss: 0.1590 (0.2342) time: 2.6179 data: 0.0066 max mem: 33368 +Epoch: [0] [1170/1319] eta: 0:06:33 lr: 4.9000114492250734e-05 loss: 0.1787 (0.2338) time: 2.6368 data: 0.0065 max mem: 33368 +Epoch: [0] [1180/1319] eta: 0:06:07 lr: 4.8991566055473306e-05 loss: 0.1787 (0.2334) time: 2.6474 data: 0.0064 max mem: 33368 +Epoch: [0] [1190/1319] eta: 0:05:40 lr: 4.8983017452959435e-05 loss: 0.1754 (0.2331) time: 2.6260 data: 0.0066 max mem: 33368 +Epoch: [0] [1200/1319] eta: 0:05:14 lr: 4.8974468684673776e-05 loss: 0.1795 (0.2329) time: 2.6210 data: 0.0064 max mem: 33368 +Epoch: [0] [1210/1319] eta: 0:04:47 lr: 4.896591975058095e-05 loss: 0.1944 (0.2326) time: 2.6130 data: 0.0065 max mem: 33368 +Epoch: [0] [1220/1319] eta: 0:04:21 lr: 4.89573706506456e-05 loss: 0.1944 (0.2323) time: 2.5925 data: 0.0065 max mem: 33368 +Epoch: [0] [1230/1319] eta: 0:03:54 lr: 4.89488213848323e-05 loss: 0.2042 (0.2322) time: 2.6092 data: 0.0066 max mem: 33368 +Epoch: [0] [1240/1319] eta: 0:03:28 lr: 4.894027195310566e-05 loss: 0.1892 (0.2318) time: 2.6105 data: 0.0065 max mem: 33368 +Epoch: [0] [1250/1319] eta: 0:03:02 lr: 4.893172235543025e-05 loss: 0.1811 (0.2317) time: 2.5977 data: 0.0064 max mem: 33368 +Epoch: [0] [1260/1319] eta: 0:02:35 lr: 4.892317259177062e-05 loss: 0.2012 (0.2316) time: 2.6151 data: 0.0065 max mem: 33368 +Epoch: [0] [1270/1319] eta: 0:02:09 lr: 4.8914622662091334e-05 loss: 0.2037 (0.2314) time: 2.6294 data: 0.0063 max mem: 33368 +Epoch: [0] [1280/1319] eta: 0:01:42 lr: 4.890607256635692e-05 loss: 0.2026 (0.2312) time: 2.6242 data: 0.0065 max mem: 33368 +Epoch: [0] [1290/1319] eta: 0:01:16 lr: 4.8897522304531876e-05 loss: 0.2011 (0.2309) time: 2.6225 data: 0.0067 max mem: 33368 +Epoch: [0] [1300/1319] eta: 0:00:50 lr: 4.888897187658072e-05 loss: 0.1921 (0.2306) time: 2.6043 data: 0.0067 max mem: 33368 +Epoch: [0] [1310/1319] eta: 0:00:23 lr: 4.888042128246795e-05 loss: 0.1921 (0.2304) time: 2.6143 data: 0.0068 max mem: 33368 +Epoch: [0] Total time: 0:58:00 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 2:28:24 time: 3.4607 data: 3.2031 max mem: 33368 +Test: [ 100/2573] eta: 0:04:20 time: 0.0716 data: 0.0011 max mem: 33368 +Test: [ 200/2573] eta: 0:03:33 time: 0.0734 data: 0.0011 max mem: 33368 +Test: [ 300/2573] eta: 0:03:10 time: 0.0751 data: 0.0011 max mem: 33368 +Test: [ 400/2573] eta: 0:02:56 time: 0.0750 data: 0.0011 max mem: 33368 +Test: [ 500/2573] eta: 0:02:45 time: 0.0736 data: 0.0011 max mem: 33368 +Test: [ 600/2573] eta: 0:02:35 time: 0.0734 data: 0.0011 max mem: 33368 +Test: [ 700/2573] eta: 0:02:26 time: 0.0736 data: 0.0011 max mem: 33368 +Test: [ 800/2573] eta: 0:02:18 time: 0.0768 data: 0.0011 max mem: 33368 +Test: [ 900/2573] eta: 0:02:09 time: 0.0736 data: 0.0011 max mem: 33368 +Test: [1000/2573] eta: 0:02:01 time: 0.0736 data: 0.0011 max mem: 33368 +Test: [1100/2573] eta: 0:01:53 time: 0.0737 data: 0.0011 max mem: 33368 +Test: [1200/2573] eta: 0:01:45 time: 0.0735 data: 0.0011 max mem: 33368 +Test: [1300/2573] eta: 0:01:37 time: 0.0735 data: 0.0011 max mem: 33368 +Test: [1400/2573] eta: 0:01:29 time: 0.0718 data: 0.0011 max mem: 33368 +Test: [1500/2573] eta: 0:01:21 time: 0.0735 data: 0.0011 max mem: 33368 +Test: [1600/2573] eta: 0:01:13 time: 0.0768 data: 0.0011 max mem: 33368 +Test: [1700/2573] eta: 0:01:06 time: 0.0718 data: 0.0011 max mem: 33368 +Test: [1800/2573] eta: 0:00:58 time: 0.0752 data: 0.0011 max mem: 33368 +Test: [1900/2573] eta: 0:00:50 time: 0.0721 data: 0.0011 max mem: 33368 +Test: [2000/2573] eta: 0:00:43 time: 0.0737 data: 0.0012 max mem: 33368 +Test: [2100/2573] eta: 0:00:35 time: 0.0752 data: 0.0011 max mem: 33368 +Test: [2200/2573] eta: 0:00:27 time: 0.0753 data: 0.0011 max mem: 33368 +Test: [2300/2573] eta: 0:00:20 time: 0.0752 data: 0.0011 max mem: 33368 +Test: [2400/2573] eta: 0:00:12 time: 0.0703 data: 0.0011 max mem: 33368 +Test: [2500/2573] eta: 0:00:05 time: 0.0737 data: 0.0011 max mem: 33368 +Test: Total time: 0:03:13 +Final results: +Mean IoU is 27.28 + + precision@0.5 = 26.21 + precision@0.6 = 18.95 + precision@0.7 = 12.66 + precision@0.8 = 7.29 + precision@0.9 = 1.23 + overall IoU = 33.05 + +Average object IoU 27.27737711933582 +Overall IoU 33.04948806762695 +Better epoch: 0 + +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [1] [ 0/1319] eta: 1:28:06 lr: 4.8872725605668895e-05 loss: 0.1759 (0.1759) time: 4.0078 data: 1.2956 max mem: 33368 +Epoch: [1] [ 10/1319] eta: 1:00:41 lr: 4.886417469575114e-05 loss: 0.1946 (0.1995) time: 2.7816 data: 0.1224 max mem: 33368 +Epoch: [1] [ 20/1319] eta: 0:58:29 lr: 4.88556236195687e-05 loss: 0.1918 (0.1909) time: 2.6364 data: 0.0051 max mem: 33368 +Epoch: [1] [ 30/1319] eta: 0:57:39 lr: 4.884707237708599e-05 loss: 0.1750 (0.1913) time: 2.6300 data: 0.0056 max mem: 33368 +Epoch: [1] [ 40/1319] eta: 0:56:39 lr: 4.883852096826744e-05 loss: 0.1981 (0.1958) time: 2.6119 data: 0.0061 max mem: 33368 +Epoch: [1] [ 50/1319] eta: 0:55:56 lr: 4.882996939307746e-05 loss: 0.2012 (0.1939) time: 2.5848 data: 0.0060 max mem: 33368 +Epoch: [1] [ 60/1319] eta: 0:55:29 lr: 4.882141765148041e-05 loss: 0.1787 (0.1939) time: 2.6165 data: 0.0060 max mem: 33368 +Epoch: [1] [ 70/1319] eta: 0:54:56 lr: 4.881286574344069e-05 loss: 0.1623 (0.1889) time: 2.6244 data: 0.0060 max mem: 33368 +Epoch: [1] [ 80/1319] eta: 0:54:22 lr: 4.8804313668922646e-05 loss: 0.1623 (0.1898) time: 2.6008 data: 0.0060 max mem: 33368 +Epoch: [1] [ 90/1319] eta: 0:53:55 lr: 4.879576142789063e-05 loss: 0.1556 (0.1875) time: 2.6077 data: 0.0060 max mem: 33368 +Epoch: [1] [ 100/1319] eta: 0:53:29 lr: 4.878720902030896e-05 loss: 0.1641 (0.1878) time: 2.6288 data: 0.0059 max mem: 33368 +Epoch: [1] [ 110/1319] eta: 0:53:00 lr: 4.877865644614197e-05 loss: 0.1750 (0.1867) time: 2.6255 data: 0.0058 max mem: 33368 +Epoch: [1] [ 120/1319] eta: 0:52:28 lr: 4.877010370535394e-05 loss: 0.1868 (0.1886) time: 2.5903 data: 0.0058 max mem: 33368 +Epoch: [1] [ 130/1319] eta: 0:52:03 lr: 4.8761550797909164e-05 loss: 0.1984 (0.1881) time: 2.6033 data: 0.0059 max mem: 33368 +Epoch: [1] [ 140/1319] eta: 0:51:38 lr: 4.875299772377192e-05 loss: 0.1843 (0.1885) time: 2.6434 data: 0.0060 max mem: 33368 +Epoch: [1] [ 150/1319] eta: 0:51:12 lr: 4.874444448290645e-05 loss: 0.1850 (0.1890) time: 2.6372 data: 0.0061 max mem: 33368 +Epoch: [1] [ 160/1319] eta: 0:50:43 lr: 4.873589107527701e-05 loss: 0.1721 (0.1878) time: 2.6137 data: 0.0060 max mem: 33368 +Epoch: [1] [ 170/1319] eta: 0:50:18 lr: 4.872733750084782e-05 loss: 0.1665 (0.1887) time: 2.6216 data: 0.0060 max mem: 33368 +Epoch: [1] [ 180/1319] eta: 0:49:51 lr: 4.871878375958309e-05 loss: 0.1797 (0.1891) time: 2.6300 data: 0.0061 max mem: 33368 +Epoch: [1] [ 190/1319] eta: 0:49:24 lr: 4.871022985144703e-05 loss: 0.1884 (0.1891) time: 2.6144 data: 0.0060 max mem: 33368 +Epoch: [1] [ 200/1319] eta: 0:48:58 lr: 4.870167577640381e-05 loss: 0.1917 (0.1902) time: 2.6148 data: 0.0059 max mem: 33368 +Epoch: [1] [ 210/1319] eta: 0:48:30 lr: 4.869312153441761e-05 loss: 0.1776 (0.1909) time: 2.6117 data: 0.0060 max mem: 33368 +Epoch: [1] [ 220/1319] eta: 0:48:05 lr: 4.868456712545258e-05 loss: 0.1825 (0.1920) time: 2.6245 data: 0.0060 max mem: 33368 +Epoch: [1] [ 230/1319] eta: 0:47:36 lr: 4.8676012549472854e-05 loss: 0.1825 (0.1913) time: 2.6041 data: 0.0060 max mem: 33368 +Epoch: [1] [ 240/1319] eta: 0:47:10 lr: 4.866745780644256e-05 loss: 0.1574 (0.1897) time: 2.5938 data: 0.0060 max mem: 33368 +Epoch: [1] [ 250/1319] eta: 0:46:43 lr: 4.865890289632581e-05 loss: 0.1574 (0.1893) time: 2.6207 data: 0.0059 max mem: 33368 +Epoch: [1] [ 260/1319] eta: 0:46:17 lr: 4.8650347819086694e-05 loss: 0.1805 (0.1889) time: 2.6176 data: 0.0059 max mem: 33368 +Epoch: [1] [ 270/1319] eta: 0:45:50 lr: 4.864179257468931e-05 loss: 0.1725 (0.1887) time: 2.6178 data: 0.0059 max mem: 33368 +Epoch: [1] [ 280/1319] eta: 0:45:26 lr: 4.8633237163097687e-05 loss: 0.1725 (0.1892) time: 2.6491 data: 0.0059 max mem: 33368 +Epoch: [1] [ 290/1319] eta: 0:44:59 lr: 4.862468158427592e-05 loss: 0.1791 (0.1894) time: 2.6390 data: 0.0059 max mem: 33368 +Epoch: [1] [ 300/1319] eta: 0:44:33 lr: 4.861612583818801e-05 loss: 0.1755 (0.1898) time: 2.6129 data: 0.0060 max mem: 33368 +Epoch: [1] [ 310/1319] eta: 0:44:06 lr: 4.860756992479799e-05 loss: 0.1776 (0.1906) time: 2.6092 data: 0.0060 max mem: 33368 +Epoch: [1] [ 320/1319] eta: 0:43:40 lr: 4.859901384406988e-05 loss: 0.1789 (0.1903) time: 2.6166 data: 0.0059 max mem: 33368 +Epoch: [1] [ 330/1319] eta: 0:43:14 lr: 4.8590457595967656e-05 loss: 0.1789 (0.1905) time: 2.6364 data: 0.0060 max mem: 33368 +Epoch: [1] [ 340/1319] eta: 0:42:47 lr: 4.85819011804553e-05 loss: 0.1618 (0.1895) time: 2.6200 data: 0.0061 max mem: 33368 +Epoch: [1] [ 350/1319] eta: 0:42:21 lr: 4.8573344597496775e-05 loss: 0.1631 (0.1897) time: 2.6173 data: 0.0060 max mem: 33368 +Epoch: [1] [ 360/1319] eta: 0:41:55 lr: 4.856478784705602e-05 loss: 0.1711 (0.1895) time: 2.6263 data: 0.0059 max mem: 33368 +Epoch: [1] [ 370/1319] eta: 0:41:29 lr: 4.8556230929096985e-05 loss: 0.1729 (0.1908) time: 2.6316 data: 0.0060 max mem: 33368 +Epoch: [1] [ 380/1319] eta: 0:41:04 lr: 4.854767384358357e-05 loss: 0.1766 (0.1904) time: 2.6424 data: 0.0060 max mem: 33368 +Epoch: [1] [ 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2.5994 data: 0.0060 max mem: 33368 +Epoch: [1] [ 710/1319] eta: 0:26:38 lr: 4.826519578660238e-05 loss: 0.1668 (0.1872) time: 2.6287 data: 0.0061 max mem: 33368 +Epoch: [1] [ 720/1319] eta: 0:26:12 lr: 4.825663298266489e-05 loss: 0.1938 (0.1872) time: 2.6153 data: 0.0062 max mem: 33368 +Epoch: [1] [ 730/1319] eta: 0:25:46 lr: 4.824807000990074e-05 loss: 0.1889 (0.1870) time: 2.6089 data: 0.0060 max mem: 33368 +Epoch: [1] [ 740/1319] eta: 0:25:19 lr: 4.82395068682733e-05 loss: 0.1610 (0.1869) time: 2.6252 data: 0.0060 max mem: 33368 +Epoch: [1] [ 750/1319] eta: 0:24:53 lr: 4.823094355774595e-05 loss: 0.1791 (0.1870) time: 2.6232 data: 0.0061 max mem: 33368 +Epoch: [1] [ 760/1319] eta: 0:24:27 lr: 4.822238007828201e-05 loss: 0.1774 (0.1868) time: 2.6078 data: 0.0061 max mem: 33368 +Epoch: [1] [ 770/1319] eta: 0:24:00 lr: 4.8213816429844826e-05 loss: 0.1650 (0.1867) time: 2.5885 data: 0.0061 max mem: 33368 +Epoch: [1] [ 780/1319] eta: 0:23:34 lr: 4.8205252612397726e-05 loss: 0.1643 (0.1864) time: 2.6186 data: 0.0061 max mem: 33368 +Epoch: [1] [ 790/1319] eta: 0:23:08 lr: 4.8196688625903984e-05 loss: 0.1643 (0.1864) time: 2.6516 data: 0.0061 max mem: 33368 +Epoch: [1] [ 800/1319] eta: 0:22:42 lr: 4.8188124470326915e-05 loss: 0.1594 (0.1861) time: 2.6535 data: 0.0061 max mem: 33368 +Epoch: [1] [ 810/1319] eta: 0:22:15 lr: 4.8179560145629784e-05 loss: 0.1711 (0.1863) time: 2.6302 data: 0.0061 max mem: 33368 +Epoch: [1] [ 820/1319] eta: 0:21:49 lr: 4.817099565177583e-05 loss: 0.1887 (0.1863) time: 2.6311 data: 0.0061 max mem: 33368 +Epoch: [1] [ 830/1319] eta: 0:21:23 lr: 4.8162430988728305e-05 loss: 0.1865 (0.1864) time: 2.6564 data: 0.0061 max mem: 33368 +Epoch: [1] [ 840/1319] eta: 0:20:57 lr: 4.815386615645044e-05 loss: 0.1586 (0.1860) time: 2.6327 data: 0.0061 max mem: 33368 +Epoch: [1] [ 850/1319] eta: 0:20:31 lr: 4.814530115490545e-05 loss: 0.1585 (0.1859) time: 2.6144 data: 0.0061 max mem: 33368 +Epoch: [1] [ 860/1319] eta: 0:20:04 lr: 4.813673598405651e-05 loss: 0.1640 (0.1857) time: 2.5925 data: 0.0061 max mem: 33368 +Epoch: [1] [ 870/1319] eta: 0:19:38 lr: 4.812817064386682e-05 loss: 0.1648 (0.1855) time: 2.5941 data: 0.0061 max mem: 33368 +Epoch: [1] [ 880/1319] eta: 0:19:12 lr: 4.8119605134299526e-05 loss: 0.1579 (0.1852) time: 2.6418 data: 0.0062 max mem: 33368 +Epoch: [1] [ 890/1319] eta: 0:18:46 lr: 4.81110394553178e-05 loss: 0.1571 (0.1850) time: 2.6446 data: 0.0061 max mem: 33368 +Epoch: [1] [ 900/1319] eta: 0:18:19 lr: 4.810247360688475e-05 loss: 0.1620 (0.1849) time: 2.6146 data: 0.0062 max mem: 33368 +Epoch: [1] [ 910/1319] eta: 0:17:53 lr: 4.809390758896352e-05 loss: 0.1570 (0.1845) time: 2.5734 data: 0.0063 max mem: 33368 +Epoch: [1] [ 920/1319] eta: 0:17:26 lr: 4.808534140151719e-05 loss: 0.1592 (0.1847) time: 2.5847 data: 0.0061 max mem: 33368 +Epoch: [1] [ 930/1319] eta: 0:17:00 lr: 4.807677504450886e-05 loss: 0.1698 (0.1845) time: 2.6359 data: 0.0060 max mem: 33368 +Epoch: [1] [ 940/1319] eta: 0:16:34 lr: 4.806820851790161e-05 loss: 0.1602 (0.1844) time: 2.6406 data: 0.0061 max mem: 33368 +Epoch: [1] [ 950/1319] eta: 0:16:08 lr: 4.805964182165848e-05 loss: 0.1602 (0.1843) time: 2.6116 data: 0.0062 max mem: 33368 +Epoch: [1] [ 960/1319] eta: 0:15:41 lr: 4.8051074955742525e-05 loss: 0.1535 (0.1842) time: 2.5841 data: 0.0062 max mem: 33368 +Epoch: [1] [ 970/1319] eta: 0:15:15 lr: 4.804250792011677e-05 loss: 0.1768 (0.1843) time: 2.6011 data: 0.0062 max mem: 33368 +Epoch: [1] [ 980/1319] eta: 0:14:49 lr: 4.803394071474422e-05 loss: 0.1823 (0.1844) time: 2.6163 data: 0.0062 max mem: 33368 +Epoch: [1] [ 990/1319] eta: 0:14:23 lr: 4.802537333958788e-05 loss: 0.1765 (0.1842) time: 2.6213 data: 0.0061 max mem: 33368 +Epoch: [1] [1000/1319] eta: 0:13:56 lr: 4.801680579461071e-05 loss: 0.1949 (0.1844) time: 2.6425 data: 0.0061 max mem: 33368 +Epoch: [1] [1010/1319] eta: 0:13:30 lr: 4.80082380797757e-05 loss: 0.1949 (0.1844) time: 2.6458 data: 0.0061 max mem: 33368 +Epoch: [1] [1020/1319] eta: 0:13:04 lr: 4.79996701950458e-05 loss: 0.1933 (0.1848) time: 2.6303 data: 0.0061 max mem: 33368 +Epoch: [1] [1030/1319] eta: 0:12:38 lr: 4.799110214038392e-05 loss: 0.1898 (0.1849) time: 2.6242 data: 0.0061 max mem: 33368 +Epoch: [1] [1040/1319] eta: 0:12:12 lr: 4.7982533915752995e-05 loss: 0.1898 (0.1849) time: 2.6332 data: 0.0061 max mem: 33368 +Epoch: [1] [1050/1319] eta: 0:11:45 lr: 4.797396552111593e-05 loss: 0.1701 (0.1848) time: 2.6303 data: 0.0062 max mem: 33368 +Epoch: [1] [1060/1319] eta: 0:11:19 lr: 4.7965396956435596e-05 loss: 0.1548 (0.1846) time: 2.6261 data: 0.0062 max mem: 33368 +Epoch: [1] [1070/1319] eta: 0:10:53 lr: 4.795682822167489e-05 loss: 0.1565 (0.1846) time: 2.6110 data: 0.0062 max mem: 33368 +Epoch: [1] [1080/1319] eta: 0:10:27 lr: 4.794825931679665e-05 loss: 0.1754 (0.1847) time: 2.6003 data: 0.0062 max mem: 33368 +Epoch: [1] [1090/1319] eta: 0:10:00 lr: 4.7939690241763725e-05 loss: 0.1654 (0.1844) time: 2.6092 data: 0.0061 max mem: 33368 +Epoch: [1] [1100/1319] eta: 0:09:34 lr: 4.793112099653894e-05 loss: 0.1640 (0.1846) time: 2.6363 data: 0.0061 max mem: 33368 +Epoch: [1] [1110/1319] eta: 0:09:08 lr: 4.79225515810851e-05 loss: 0.1648 (0.1846) time: 2.6603 data: 0.0061 max mem: 33368 +Epoch: [1] [1120/1319] eta: 0:08:42 lr: 4.791398199536501e-05 loss: 0.1590 (0.1845) time: 2.6454 data: 0.0064 max mem: 33368 +Epoch: [1] [1130/1319] eta: 0:08:15 lr: 4.790541223934144e-05 loss: 0.1715 (0.1845) time: 2.6219 data: 0.0064 max mem: 33368 +Epoch: [1] [1140/1319] eta: 0:07:49 lr: 4.7896842312977156e-05 loss: 0.1793 (0.1845) time: 2.6111 data: 0.0062 max mem: 33368 +Epoch: [1] [1150/1319] eta: 0:07:23 lr: 4.788827221623491e-05 loss: 0.1729 (0.1844) time: 2.6414 data: 0.0062 max mem: 33368 +Epoch: [1] [1160/1319] eta: 0:06:57 lr: 4.787970194907743e-05 loss: 0.1636 (0.1843) time: 2.6473 data: 0.0062 max mem: 33368 +Epoch: [1] [1170/1319] eta: 0:06:31 lr: 4.787113151146744e-05 loss: 0.1578 (0.1842) time: 2.6230 data: 0.0063 max mem: 33368 +Epoch: [1] [1180/1319] eta: 0:06:04 lr: 4.786256090336764e-05 loss: 0.1615 (0.1843) time: 2.6427 data: 0.0063 max mem: 33368 +Epoch: [1] [1190/1319] eta: 0:05:38 lr: 4.7853990124740705e-05 loss: 0.1615 (0.1840) time: 2.6458 data: 0.0062 max mem: 33368 +Epoch: [1] [1200/1319] eta: 0:05:12 lr: 4.784541917554932e-05 loss: 0.1592 (0.1839) time: 2.6507 data: 0.0062 max mem: 33368 +Epoch: [1] [1210/1319] eta: 0:04:46 lr: 4.783684805575612e-05 loss: 0.1617 (0.1838) time: 2.6498 data: 0.0061 max mem: 33368 +Epoch: [1] [1220/1319] eta: 0:04:19 lr: 4.782827676532376e-05 loss: 0.1490 (0.1837) time: 2.6168 data: 0.0062 max mem: 33368 +Epoch: [1] [1230/1319] eta: 0:03:53 lr: 4.781970530421487e-05 loss: 0.1679 (0.1835) time: 2.6194 data: 0.0063 max mem: 33368 +Epoch: [1] [1240/1319] eta: 0:03:27 lr: 4.7811133672392044e-05 loss: 0.1478 (0.1832) time: 2.6234 data: 0.0063 max mem: 33368 +Epoch: [1] [1250/1319] eta: 0:03:01 lr: 4.780256186981787e-05 loss: 0.1478 (0.1831) time: 2.6276 data: 0.0063 max mem: 33368 +Epoch: [1] [1260/1319] eta: 0:02:34 lr: 4.779398989645494e-05 loss: 0.1630 (0.1829) time: 2.6195 data: 0.0064 max mem: 33368 +Epoch: [1] [1270/1319] eta: 0:02:08 lr: 4.778541775226581e-05 loss: 0.1586 (0.1829) time: 2.6038 data: 0.0064 max mem: 33368 +Epoch: [1] [1280/1319] eta: 0:01:42 lr: 4.777684543721302e-05 loss: 0.1541 (0.1828) time: 2.6106 data: 0.0063 max mem: 33368 +Epoch: [1] [1290/1319] eta: 0:01:16 lr: 4.776827295125911e-05 loss: 0.1534 (0.1826) time: 2.6244 data: 0.0062 max mem: 33368 +Epoch: [1] [1300/1319] eta: 0:00:49 lr: 4.775970029436657e-05 loss: 0.1465 (0.1824) time: 2.6185 data: 0.0063 max mem: 33368 +Epoch: [1] [1310/1319] eta: 0:00:23 lr: 4.7751127466497925e-05 loss: 0.1643 (0.1824) time: 2.5845 data: 0.0063 max mem: 33368 +Epoch: [1] Total time: 0:57:41 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 1:49:59 time: 2.5650 data: 2.4708 max mem: 33368 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 100/2573] eta: 0:04:00 time: 0.0716 data: 0.0011 max mem: 33368 +Test: [ 200/2573] eta: 0:03:23 time: 0.0729 data: 0.0011 max mem: 33368 +Test: [ 300/2573] eta: 0:03:04 time: 0.0745 data: 0.0011 max mem: 33368 +Test: [ 400/2573] eta: 0:02:51 time: 0.0746 data: 0.0011 max mem: 33368 +Test: [ 500/2573] eta: 0:02:41 time: 0.0732 data: 0.0011 max mem: 33368 +Test: [ 600/2573] eta: 0:02:32 time: 0.0733 data: 0.0011 max mem: 33368 +Test: [ 700/2573] eta: 0:02:24 time: 0.0734 data: 0.0011 max mem: 33368 +Test: [ 800/2573] eta: 0:02:15 time: 0.0768 data: 0.0011 max mem: 33368 +Test: [ 900/2573] eta: 0:02:07 time: 0.0736 data: 0.0011 max mem: 33368 +Test: [1000/2573] eta: 0:01:59 time: 0.0735 data: 0.0011 max mem: 33368 +Test: [1100/2573] eta: 0:01:51 time: 0.0736 data: 0.0011 max mem: 33368 +Test: [1200/2573] eta: 0:01:44 time: 0.0735 data: 0.0011 max mem: 33368 +Test: [1300/2573] eta: 0:01:36 time: 0.0737 data: 0.0011 max mem: 33368 +Test: [1400/2573] eta: 0:01:28 time: 0.0720 data: 0.0011 max mem: 33368 +Test: [1500/2573] eta: 0:01:20 time: 0.0737 data: 0.0011 max mem: 33368 +Test: [1600/2573] eta: 0:01:13 time: 0.0771 data: 0.0011 max mem: 33368 +Test: [1700/2573] eta: 0:01:05 time: 0.0721 data: 0.0011 max mem: 33368 +Test: [1800/2573] eta: 0:00:58 time: 0.0753 data: 0.0011 max mem: 33368 +Test: [1900/2573] eta: 0:00:50 time: 0.0721 data: 0.0011 max mem: 33368 +Test: [2000/2573] eta: 0:00:42 time: 0.0737 data: 0.0011 max mem: 33368 +Test: [2100/2573] eta: 0:00:35 time: 0.0754 data: 0.0011 max mem: 33368 +Test: [2200/2573] eta: 0:00:27 time: 0.0755 data: 0.0011 max mem: 33368 +Test: [2300/2573] eta: 0:00:20 time: 0.0754 data: 0.0011 max mem: 33368 +Test: [2400/2573] eta: 0:00:12 time: 0.0703 data: 0.0011 max mem: 33368 +Test: [2500/2573] eta: 0:00:05 time: 0.0737 data: 0.0011 max mem: 33368 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: Total time: 0:03:12 +Final results: +Mean IoU is 43.88 + + precision@0.5 = 44.30 + precision@0.6 = 34.29 + precision@0.7 = 24.37 + precision@0.8 = 14.99 + precision@0.9 = 4.47 + overall IoU = 45.56 + +Average object IoU 43.88297344599621 +Overall IoU 45.56217575073242 +Better epoch: 1 + +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [2] [ 0/1319] eta: 1:24:54 lr: 4.774341177520056e-05 loss: 0.1045 (0.1045) time: 3.8627 data: 1.1541 max mem: 33368 +Epoch: [2] [ 10/1319] eta: 0:59:41 lr: 4.773483862237391e-05 loss: 0.1467 (0.1709) time: 2.7360 data: 0.1104 max mem: 33368 +Epoch: [2] [ 20/1319] eta: 0:57:45 lr: 4.772626529846231e-05 loss: 0.1573 (0.1685) time: 2.6080 data: 0.0059 max mem: 33368 +Epoch: [2] [ 30/1319] eta: 0:56:42 lr: 4.771769180342819e-05 loss: 0.1432 (0.1620) time: 2.5862 data: 0.0061 max mem: 33368 +Epoch: [2] [ 40/1319] eta: 0:56:02 lr: 4.7709118137233964e-05 loss: 0.1453 (0.1649) time: 2.5889 data: 0.0061 max mem: 33368 +Epoch: [2] [ 50/1319] eta: 0:55:43 lr: 4.770054429984204e-05 loss: 0.1674 (0.1648) time: 2.6271 data: 0.0061 max mem: 33368 +Epoch: [2] [ 60/1319] eta: 0:55:10 lr: 4.769197029121481e-05 loss: 0.1720 (0.1664) time: 2.6287 data: 0.0062 max mem: 33368 +Epoch: [2] [ 70/1319] eta: 0:54:45 lr: 4.7683396111314645e-05 loss: 0.1808 (0.1718) time: 2.6211 data: 0.0061 max mem: 33368 +Epoch: [2] [ 80/1319] eta: 0:54:16 lr: 4.7674821760103904e-05 loss: 0.1661 (0.1696) time: 2.6249 data: 0.0060 max mem: 33368 +Epoch: [2] [ 90/1319] eta: 0:53:47 lr: 4.766624723754494e-05 loss: 0.1402 (0.1664) time: 2.6089 data: 0.0061 max mem: 33368 +Epoch: [2] [ 100/1319] eta: 0:53:24 lr: 4.7657672543600056e-05 loss: 0.1392 (0.1661) time: 2.6305 data: 0.0060 max mem: 33368 +Epoch: [2] [ 110/1319] eta: 0:52:57 lr: 4.764909767823158e-05 loss: 0.1523 (0.1660) time: 2.6361 data: 0.0060 max mem: 33368 +Epoch: [2] [ 120/1319] eta: 0:52:28 lr: 4.76405226414018e-05 loss: 0.1554 (0.1665) time: 2.6143 data: 0.0060 max mem: 33368 +Epoch: [2] [ 130/1319] eta: 0:52:02 lr: 4.7631947433073e-05 loss: 0.1552 (0.1649) time: 2.6189 data: 0.0060 max mem: 33368 +Epoch: [2] [ 140/1319] eta: 0:51:33 lr: 4.762337205320744e-05 loss: 0.1414 (0.1635) time: 2.6085 data: 0.0060 max mem: 33368 +Epoch: [2] [ 150/1319] eta: 0:51:06 lr: 4.7614796501767376e-05 loss: 0.1414 (0.1631) time: 2.6026 data: 0.0061 max mem: 33368 +Epoch: [2] [ 160/1319] eta: 0:50:39 lr: 4.760622077871502e-05 loss: 0.1587 (0.1632) time: 2.6137 data: 0.0061 max mem: 33368 +Epoch: [2] [ 170/1319] eta: 0:50:13 lr: 4.75976448840126e-05 loss: 0.1404 (0.1619) time: 2.6174 data: 0.0062 max mem: 33368 +Epoch: [2] [ 180/1319] eta: 0:49:48 lr: 4.7589068817622304e-05 loss: 0.1391 (0.1611) time: 2.6308 data: 0.0062 max mem: 33368 +Epoch: [2] [ 190/1319] eta: 0:49:23 lr: 4.758049257950633e-05 loss: 0.1482 (0.1609) time: 2.6407 data: 0.0061 max mem: 33368 +Epoch: [2] [ 200/1319] eta: 0:48:57 lr: 4.757191616962685e-05 loss: 0.1700 (0.1620) time: 2.6385 data: 0.0062 max mem: 33368 +Epoch: [2] [ 210/1319] eta: 0:48:30 lr: 4.756333958794601e-05 loss: 0.1652 (0.1613) time: 2.6213 data: 0.0062 max mem: 33368 +Epoch: [2] [ 220/1319] eta: 0:48:02 lr: 4.7554762834425936e-05 loss: 0.1464 (0.1609) time: 2.6050 data: 0.0061 max mem: 33368 +Epoch: [2] [ 230/1319] eta: 0:47:37 lr: 4.7546185909028754e-05 loss: 0.1716 (0.1622) time: 2.6253 data: 0.0061 max mem: 33368 +Epoch: [2] [ 240/1319] eta: 0:47:12 lr: 4.753760881171657e-05 loss: 0.1606 (0.1617) time: 2.6451 data: 0.0061 max mem: 33368 +Epoch: [2] [ 250/1319] eta: 0:46:45 lr: 4.7529031542451477e-05 loss: 0.1600 (0.1629) time: 2.6275 data: 0.0061 max mem: 33368 +Epoch: [2] [ 260/1319] eta: 0:46:20 lr: 4.7520454101195535e-05 loss: 0.1606 (0.1638) time: 2.6383 data: 0.0060 max mem: 33368 +Epoch: [2] [ 270/1319] eta: 0:45:55 lr: 4.751187648791081e-05 loss: 0.1606 (0.1635) time: 2.6533 data: 0.0060 max mem: 33368 +Epoch: [2] [ 280/1319] eta: 0:45:30 lr: 4.7503298702559326e-05 loss: 0.1523 (0.1635) time: 2.6488 data: 0.0061 max mem: 33368 +Epoch: [2] [ 290/1319] eta: 0:45:04 lr: 4.7494720745103136e-05 loss: 0.1525 (0.1643) time: 2.6434 data: 0.0060 max mem: 33368 +Epoch: [2] [ 300/1319] eta: 0:44:38 lr: 4.748614261550422e-05 loss: 0.1422 (0.1637) time: 2.6476 data: 0.0061 max mem: 33368 +Epoch: [2] [ 310/1319] eta: 0:44:12 lr: 4.7477564313724594e-05 loss: 0.1379 (0.1637) time: 2.6480 data: 0.0062 max mem: 33368 +Epoch: [2] [ 320/1319] eta: 0:43:47 lr: 4.746898583972622e-05 loss: 0.1720 (0.1655) time: 2.6556 data: 0.0061 max mem: 33368 +Epoch: [2] [ 330/1319] eta: 0:43:22 lr: 4.746040719347105e-05 loss: 0.1612 (0.1654) time: 2.6677 data: 0.0059 max mem: 33368 +Epoch: [2] [ 340/1319] eta: 0:42:55 lr: 4.745182837492104e-05 loss: 0.1567 (0.1656) time: 2.6334 data: 0.0059 max mem: 33368 +Epoch: [2] [ 350/1319] eta: 0:42:28 lr: 4.744324938403812e-05 loss: 0.1701 (0.1662) time: 2.6152 data: 0.0060 max mem: 33368 +Epoch: [2] [ 360/1319] eta: 0:42:01 lr: 4.7434670220784206e-05 loss: 0.1654 (0.1663) time: 2.6121 data: 0.0061 max mem: 33368 +Epoch: [2] [ 370/1319] eta: 0:41:34 lr: 4.7426090885121175e-05 loss: 0.1587 (0.1657) time: 2.5880 data: 0.0060 max mem: 33368 +Epoch: [2] [ 380/1319] eta: 0:41:07 lr: 4.741751137701092e-05 loss: 0.1594 (0.1662) time: 2.5909 data: 0.0061 max mem: 33368 +Epoch: [2] [ 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+Epoch: [2] [1260/1319] eta: 0:02:34 lr: 4.6661834838121084e-05 loss: 0.1435 (0.1627) time: 2.6143 data: 0.0062 max mem: 33368 +Epoch: [2] [1270/1319] eta: 0:02:08 lr: 4.665323982755382e-05 loss: 0.1435 (0.1625) time: 2.5985 data: 0.0061 max mem: 33368 +Epoch: [2] [1280/1319] eta: 0:01:42 lr: 4.664464464104137e-05 loss: 0.1527 (0.1627) time: 2.5922 data: 0.0063 max mem: 33368 +Epoch: [2] [1290/1319] eta: 0:01:16 lr: 4.6636049278544094e-05 loss: 0.1583 (0.1626) time: 2.6213 data: 0.0064 max mem: 33368 +Epoch: [2] [1300/1319] eta: 0:00:49 lr: 4.662745374002236e-05 loss: 0.1512 (0.1628) time: 2.6310 data: 0.0064 max mem: 33368 +Epoch: [2] [1310/1319] eta: 0:00:23 lr: 4.6618858025436495e-05 loss: 0.1644 (0.1630) time: 2.6314 data: 0.0063 max mem: 33368 +Epoch: [2] Total time: 0:57:40 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 2:06:01 time: 2.9388 data: 2.8598 max mem: 33368 +Test: [ 100/2573] eta: 0:04:07 time: 0.0717 data: 0.0011 max mem: 33368 +Test: [ 200/2573] eta: 0:03:26 time: 0.0728 data: 0.0011 max mem: 33368 +Test: [ 300/2573] eta: 0:03:06 time: 0.0746 data: 0.0011 max mem: 33368 +Test: [ 400/2573] eta: 0:02:53 time: 0.0745 data: 0.0010 max mem: 33368 +Test: [ 500/2573] eta: 0:02:42 time: 0.0729 data: 0.0011 max mem: 33368 +Test: [ 600/2573] eta: 0:02:32 time: 0.0731 data: 0.0011 max mem: 33368 +Test: [ 700/2573] eta: 0:02:24 time: 0.0731 data: 0.0011 max mem: 33368 +Test: [ 800/2573] eta: 0:02:16 time: 0.0764 data: 0.0011 max mem: 33368 +Test: [ 900/2573] eta: 0:02:08 time: 0.0732 data: 0.0011 max mem: 33368 +Test: [1000/2573] eta: 0:01:59 time: 0.0736 data: 0.0011 max mem: 33368 +Test: [1100/2573] eta: 0:01:51 time: 0.0735 data: 0.0011 max mem: 33368 +Test: [1200/2573] eta: 0:01:44 time: 0.0734 data: 0.0011 max mem: 33368 +Test: [1300/2573] eta: 0:01:36 time: 0.0735 data: 0.0011 max mem: 33368 +Test: [1400/2573] eta: 0:01:28 time: 0.0719 data: 0.0011 max mem: 33368 +Test: [1500/2573] eta: 0:01:20 time: 0.0736 data: 0.0011 max mem: 33368 +Test: [1600/2573] eta: 0:01:13 time: 0.0769 data: 0.0011 max mem: 33368 +Test: [1700/2573] eta: 0:01:05 time: 0.0719 data: 0.0011 max mem: 33368 +Test: [1800/2573] eta: 0:00:58 time: 0.0752 data: 0.0011 max mem: 33368 +Test: [1900/2573] eta: 0:00:50 time: 0.0720 data: 0.0011 max mem: 33368 +Test: [2000/2573] eta: 0:00:42 time: 0.0735 data: 0.0011 max mem: 33368 +Test: [2100/2573] eta: 0:00:35 time: 0.0752 data: 0.0011 max mem: 33368 +Test: [2200/2573] eta: 0:00:27 time: 0.0752 data: 0.0011 max mem: 33368 +Test: [2300/2573] eta: 0:00:20 time: 0.0753 data: 0.0011 max mem: 33368 +Test: [2400/2573] eta: 0:00:12 time: 0.0703 data: 0.0011 max mem: 33368 +Test: [2500/2573] eta: 0:00:05 time: 0.0737 data: 0.0011 max mem: 33368 +Test: Total time: 0:03:12 +Final results: +Mean IoU is 44.60 + + precision@0.5 = 48.28 + precision@0.6 = 40.48 + precision@0.7 = 31.17 + precision@0.8 = 20.12 + precision@0.9 = 6.80 + overall IoU = 47.41 + +Average object IoU 44.597893122734526 +Overall IoU 47.410709381103516 +Better epoch: 2 + +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [3] [ 0/1319] eta: 1:26:34 lr: 4.661112173174161e-05 loss: 0.0980 (0.0980) time: 3.9380 data: 1.2377 max mem: 33368 +Epoch: [3] [ 10/1319] eta: 0:59:36 lr: 4.660252568252458e-05 loss: 0.1176 (0.1357) time: 2.7326 data: 0.1177 max mem: 33368 +Epoch: [3] [ 20/1319] eta: 0:58:17 lr: 4.6593929457128314e-05 loss: 0.1239 (0.1336) time: 2.6298 data: 0.0054 max mem: 33368 +Epoch: [3] [ 30/1319] eta: 0:57:09 lr: 4.6585333055513096e-05 loss: 0.1239 (0.1328) time: 2.6211 data: 0.0055 max mem: 33368 +Epoch: [3] [ 40/1319] eta: 0:56:41 lr: 4.657673647763916e-05 loss: 0.1466 (0.1469) time: 2.6246 data: 0.0061 max mem: 33368 +Epoch: [3] [ 50/1319] eta: 0:56:14 lr: 4.656813972346675e-05 loss: 0.1410 (0.1455) time: 2.6567 data: 0.0060 max mem: 33368 +Epoch: [3] [ 60/1319] eta: 0:55:33 lr: 4.655954279295608e-05 loss: 0.1392 (0.1450) time: 2.6239 data: 0.0059 max mem: 33368 +Epoch: [3] [ 70/1319] eta: 0:55:02 lr: 4.655094568606738e-05 loss: 0.1439 (0.1461) time: 2.6064 data: 0.0059 max mem: 33368 +Epoch: [3] [ 80/1319] eta: 0:54:34 lr: 4.6542348402760813e-05 loss: 0.1376 (0.1462) time: 2.6270 data: 0.0058 max mem: 33368 +Epoch: [3] [ 90/1319] eta: 0:54:05 lr: 4.653375094299656e-05 loss: 0.1345 (0.1469) time: 2.6287 data: 0.0060 max mem: 33368 +Epoch: [3] [ 100/1319] eta: 0:53:35 lr: 4.652515330673476e-05 loss: 0.1113 (0.1445) time: 2.6188 data: 0.0062 max mem: 33368 +Epoch: [3] [ 110/1319] eta: 0:53:05 lr: 4.651655549393556e-05 loss: 0.1205 (0.1456) time: 2.6092 data: 0.0061 max mem: 33368 +Epoch: [3] [ 120/1319] eta: 0:52:36 lr: 4.650795750455908e-05 loss: 0.1458 (0.1452) time: 2.6040 data: 0.0060 max mem: 33368 +Epoch: [3] [ 130/1319] eta: 0:52:08 lr: 4.649935933856541e-05 loss: 0.1458 (0.1455) time: 2.6104 data: 0.0061 max mem: 33368 +Epoch: [3] [ 140/1319] eta: 0:51:38 lr: 4.6490760995914644e-05 loss: 0.1318 (0.1441) time: 2.6056 data: 0.0061 max mem: 33368 +Epoch: [3] [ 150/1319] eta: 0:51:14 lr: 4.648216247656684e-05 loss: 0.1214 (0.1439) time: 2.6213 data: 0.0061 max mem: 33368 +Epoch: [3] [ 160/1319] eta: 0:50:48 lr: 4.647356378048206e-05 loss: 0.1251 (0.1430) time: 2.6408 data: 0.0061 max mem: 33368 +Epoch: [3] [ 170/1319] eta: 0:50:21 lr: 4.646496490762032e-05 loss: 0.1399 (0.1449) time: 2.6274 data: 0.0059 max mem: 33368 +Epoch: [3] [ 180/1319] eta: 0:49:51 lr: 4.645636585794164e-05 loss: 0.1443 (0.1440) time: 2.5992 data: 0.0059 max mem: 33368 +Epoch: [3] [ 190/1319] eta: 0:49:22 lr: 4.644776663140602e-05 loss: 0.1271 (0.1442) time: 2.5712 data: 0.0062 max mem: 33368 +Epoch: [3] [ 200/1319] eta: 0:48:54 lr: 4.6439167227973446e-05 loss: 0.1464 (0.1454) time: 2.5869 data: 0.0061 max mem: 33368 +Epoch: [3] [ 210/1319] eta: 0:48:27 lr: 4.643056764760387e-05 loss: 0.1562 (0.1462) time: 2.6041 data: 0.0059 max mem: 33368 +Epoch: [3] [ 220/1319] eta: 0:48:01 lr: 4.642196789025724e-05 loss: 0.1466 (0.1467) time: 2.6173 data: 0.0059 max mem: 33368 +Epoch: [3] [ 230/1319] eta: 0:47:36 lr: 4.641336795589349e-05 loss: 0.1390 (0.1463) time: 2.6328 data: 0.0060 max mem: 33368 +Epoch: [3] [ 240/1319] eta: 0:47:09 lr: 4.6404767844472526e-05 loss: 0.1390 (0.1466) time: 2.6248 data: 0.0061 max mem: 33368 +Epoch: [3] [ 250/1319] eta: 0:46:44 lr: 4.639616755595424e-05 loss: 0.1387 (0.1461) time: 2.6327 data: 0.0061 max mem: 33368 +Epoch: [3] [ 260/1319] eta: 0:46:15 lr: 4.638756709029851e-05 loss: 0.1326 (0.1460) time: 2.6069 data: 0.0060 max mem: 33368 +Epoch: [3] [ 270/1319] eta: 0:45:49 lr: 4.6378966447465196e-05 loss: 0.1412 (0.1468) time: 2.5957 data: 0.0061 max mem: 33368 +Epoch: [3] [ 280/1319] eta: 0:45:26 lr: 4.637036562741414e-05 loss: 0.1465 (0.1466) time: 2.6596 data: 0.0061 max mem: 33368 +Epoch: [3] [ 290/1319] eta: 0:45:00 lr: 4.636176463010516e-05 loss: 0.1339 (0.1468) time: 2.6670 data: 0.0061 max mem: 33368 +Epoch: [3] [ 300/1319] eta: 0:44:35 lr: 4.635316345549808e-05 loss: 0.1120 (0.1460) time: 2.6528 data: 0.0061 max mem: 33368 +Epoch: [3] [ 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(0.1460) time: 2.5928 data: 0.0062 max mem: 33368 +Epoch: [3] [ 790/1319] eta: 0:23:08 lr: 4.593148786779743e-05 loss: 0.1254 (0.1465) time: 2.5964 data: 0.0062 max mem: 33368 +Epoch: [3] [ 800/1319] eta: 0:22:41 lr: 4.592287777665063e-05 loss: 0.1496 (0.1465) time: 2.6186 data: 0.0062 max mem: 33368 +Epoch: [3] [ 810/1319] eta: 0:22:15 lr: 4.5914267506132555e-05 loss: 0.1459 (0.1467) time: 2.6107 data: 0.0061 max mem: 33368 +Epoch: [3] [ 820/1319] eta: 0:21:48 lr: 4.590565705620206e-05 loss: 0.1393 (0.1464) time: 2.5882 data: 0.0061 max mem: 33368 +Epoch: [3] [ 830/1319] eta: 0:21:22 lr: 4.589704642681802e-05 loss: 0.1273 (0.1464) time: 2.5958 data: 0.0063 max mem: 33368 +Epoch: [3] [ 840/1319] eta: 0:20:56 lr: 4.58884356179393e-05 loss: 0.1429 (0.1465) time: 2.6472 data: 0.0062 max mem: 33368 +Epoch: [3] [ 850/1319] eta: 0:20:30 lr: 4.5879824629524725e-05 loss: 0.1428 (0.1462) time: 2.6437 data: 0.0062 max mem: 33368 +Epoch: [3] [ 860/1319] eta: 0:20:04 lr: 4.5871213461533106e-05 loss: 0.1283 (0.1464) time: 2.6112 data: 0.0063 max mem: 33368 +Epoch: [3] [ 870/1319] eta: 0:19:37 lr: 4.5862602113923244e-05 loss: 0.1229 (0.1462) time: 2.5914 data: 0.0063 max mem: 33368 +Epoch: [3] [ 880/1319] eta: 0:19:11 lr: 4.585399058665391e-05 loss: 0.1189 (0.1462) time: 2.5994 data: 0.0062 max mem: 33368 +Epoch: [3] [ 890/1319] eta: 0:18:44 lr: 4.5845378879683885e-05 loss: 0.1189 (0.1460) time: 2.5990 data: 0.0062 max mem: 33368 +Epoch: [3] [ 900/1319] eta: 0:18:18 lr: 4.583676699297189e-05 loss: 0.1182 (0.1459) time: 2.5939 data: 0.0062 max mem: 33368 +Epoch: [3] [ 910/1319] eta: 0:17:52 lr: 4.582815492647665e-05 loss: 0.1415 (0.1460) time: 2.6263 data: 0.0061 max mem: 33368 +Epoch: [3] [ 920/1319] eta: 0:17:26 lr: 4.5819542680156885e-05 loss: 0.1526 (0.1464) time: 2.6162 data: 0.0063 max mem: 33368 +Epoch: [3] [ 930/1319] eta: 0:16:59 lr: 4.5810930253971277e-05 loss: 0.1457 (0.1464) time: 2.6020 data: 0.0063 max mem: 33368 +Epoch: [3] [ 940/1319] eta: 0:16:33 lr: 4.580231764787849e-05 loss: 0.1583 (0.1469) time: 2.6286 data: 0.0063 max mem: 33368 +Epoch: [3] [ 950/1319] eta: 0:16:07 lr: 4.579370486183719e-05 loss: 0.1528 (0.1470) time: 2.6499 data: 0.0063 max mem: 33368 +Epoch: [3] [ 960/1319] eta: 0:15:41 lr: 4.5785091895806004e-05 loss: 0.1201 (0.1468) time: 2.6287 data: 0.0062 max mem: 33368 +Epoch: [3] [ 970/1319] eta: 0:15:15 lr: 4.577647874974354e-05 loss: 0.1315 (0.1467) time: 2.6041 data: 0.0063 max mem: 33368 +Epoch: [3] [ 980/1319] eta: 0:14:48 lr: 4.57678654236084e-05 loss: 0.1363 (0.1465) time: 2.6183 data: 0.0065 max mem: 33368 +Epoch: [3] [ 990/1319] eta: 0:14:22 lr: 4.575925191735917e-05 loss: 0.1098 (0.1464) time: 2.6417 data: 0.0064 max mem: 33368 +Epoch: [3] [1000/1319] eta: 0:13:56 lr: 4.57506382309544e-05 loss: 0.1424 (0.1465) time: 2.6420 data: 0.0062 max mem: 33368 +Epoch: [3] [1010/1319] eta: 0:13:30 lr: 4.574202436435264e-05 loss: 0.1430 (0.1466) time: 2.6417 data: 0.0062 max mem: 33368 +Epoch: [3] [1020/1319] eta: 0:13:04 lr: 4.573341031751242e-05 loss: 0.1276 (0.1465) time: 2.6742 data: 0.0062 max mem: 33368 +Epoch: [3] [1030/1319] eta: 0:12:38 lr: 4.5724796090392234e-05 loss: 0.1276 (0.1465) time: 2.6813 data: 0.0062 max mem: 33368 +Epoch: [3] [1040/1319] eta: 0:12:12 lr: 4.571618168295058e-05 loss: 0.1302 (0.1463) time: 2.6500 data: 0.0063 max mem: 33368 +Epoch: [3] [1050/1319] eta: 0:11:45 lr: 4.570756709514592e-05 loss: 0.1253 (0.1461) time: 2.6129 data: 0.0063 max mem: 33368 +Epoch: [3] [1060/1319] eta: 0:11:19 lr: 4.569895232693671e-05 loss: 0.1370 (0.1462) time: 2.5881 data: 0.0061 max mem: 33368 +Epoch: [3] [1070/1319] eta: 0:10:53 lr: 4.569033737828139e-05 loss: 0.1432 (0.1462) time: 2.6096 data: 0.0060 max mem: 33368 +Epoch: [3] [1080/1319] eta: 0:10:27 lr: 4.568172224913836e-05 loss: 0.1230 (0.1460) time: 2.6381 data: 0.0060 max mem: 33368 +Epoch: [3] [1090/1319] eta: 0:10:00 lr: 4.567310693946603e-05 loss: 0.1274 (0.1460) time: 2.6279 data: 0.0061 max mem: 33368 +Epoch: [3] 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+Epoch: [3] [1180/1319] eta: 0:06:04 lr: 4.559556102172276e-05 loss: 0.1321 (0.1462) time: 2.6067 data: 0.0062 max mem: 33368 +Epoch: [3] [1190/1319] eta: 0:05:38 lr: 4.5586943904465176e-05 loss: 0.1338 (0.1464) time: 2.6181 data: 0.0061 max mem: 33368 +Epoch: [3] [1200/1319] eta: 0:05:12 lr: 4.557832660621944e-05 loss: 0.1312 (0.1462) time: 2.6270 data: 0.0061 max mem: 33368 +Epoch: [3] [1210/1319] eta: 0:04:46 lr: 4.556970912694373e-05 loss: 0.1274 (0.1462) time: 2.6062 data: 0.0061 max mem: 33368 +Epoch: [3] [1220/1319] eta: 0:04:19 lr: 4.5561091466596205e-05 loss: 0.1252 (0.1462) time: 2.6045 data: 0.0063 max mem: 33368 +Epoch: [3] [1230/1319] eta: 0:03:53 lr: 4.555247362513501e-05 loss: 0.1248 (0.1461) time: 2.6220 data: 0.0064 max mem: 33368 +Epoch: [3] [1240/1319] eta: 0:03:27 lr: 4.5543855602518245e-05 loss: 0.1304 (0.1460) time: 2.6267 data: 0.0062 max mem: 33368 +Epoch: [3] [1250/1319] eta: 0:03:01 lr: 4.553523739870403e-05 loss: 0.1297 (0.1459) time: 2.6374 data: 0.0062 max mem: 33368 +Epoch: [3] [1260/1319] eta: 0:02:34 lr: 4.552661901365045e-05 loss: 0.1265 (0.1458) time: 2.6288 data: 0.0062 max mem: 33368 +Epoch: [3] [1270/1319] eta: 0:02:08 lr: 4.551800044731557e-05 loss: 0.1282 (0.1457) time: 2.6244 data: 0.0062 max mem: 33368 +Epoch: [3] [1280/1319] eta: 0:01:42 lr: 4.550938169965743e-05 loss: 0.1282 (0.1457) time: 2.6396 data: 0.0062 max mem: 33368 +Epoch: [3] [1290/1319] eta: 0:01:16 lr: 4.550076277063406e-05 loss: 0.1349 (0.1456) time: 2.5985 data: 0.0062 max mem: 33368 +Epoch: [3] [1300/1319] eta: 0:00:49 lr: 4.549214366020347e-05 loss: 0.1229 (0.1457) time: 2.5840 data: 0.0063 max mem: 33368 +Epoch: [3] [1310/1319] eta: 0:00:23 lr: 4.5483524368323656e-05 loss: 0.1268 (0.1459) time: 2.6240 data: 0.0062 max mem: 33368 +Epoch: [3] Total time: 0:57:41 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 2:08:23 time: 2.9939 data: 2.9158 max mem: 33368 +Test: [ 100/2573] eta: 0:04:07 time: 0.0708 data: 0.0011 max mem: 33368 +Test: [ 200/2573] eta: 0:03:26 time: 0.0728 data: 0.0011 max mem: 33368 +Test: [ 300/2573] eta: 0:03:05 time: 0.0744 data: 0.0011 max mem: 33368 +Test: [ 400/2573] eta: 0:02:52 time: 0.0746 data: 0.0011 max mem: 33368 +Test: [ 500/2573] eta: 0:02:42 time: 0.0729 data: 0.0011 max mem: 33368 +Test: [ 600/2573] eta: 0:02:32 time: 0.0731 data: 0.0011 max mem: 33368 +Test: [ 700/2573] eta: 0:02:24 time: 0.0730 data: 0.0011 max mem: 33368 +Test: [ 800/2573] eta: 0:02:16 time: 0.0764 data: 0.0011 max mem: 33368 +Test: [ 900/2573] eta: 0:02:07 time: 0.0732 data: 0.0011 max mem: 33368 +Test: [1000/2573] eta: 0:01:59 time: 0.0731 data: 0.0011 max mem: 33368 +Test: [1100/2573] eta: 0:01:51 time: 0.0735 data: 0.0011 max mem: 33368 +Test: [1200/2573] eta: 0:01:44 time: 0.0733 data: 0.0011 max mem: 33368 +Test: [1300/2573] eta: 0:01:36 time: 0.0733 data: 0.0011 max mem: 33368 +Test: [1400/2573] eta: 0:01:28 time: 0.0718 data: 0.0011 max mem: 33368 +Test: [1500/2573] eta: 0:01:20 time: 0.0735 data: 0.0011 max mem: 33368 +Test: [1600/2573] eta: 0:01:13 time: 0.0769 data: 0.0011 max mem: 33368 +Test: [1700/2573] eta: 0:01:05 time: 0.0719 data: 0.0011 max mem: 33368 +Test: [1800/2573] eta: 0:00:58 time: 0.0752 data: 0.0011 max mem: 33368 +Test: [1900/2573] eta: 0:00:50 time: 0.0719 data: 0.0011 max mem: 33368 +Test: [2000/2573] eta: 0:00:42 time: 0.0736 data: 0.0011 max mem: 33368 +Test: [2100/2573] eta: 0:00:35 time: 0.0752 data: 0.0011 max mem: 33368 +Test: [2200/2573] eta: 0:00:27 time: 0.0752 data: 0.0011 max mem: 33368 +Test: [2300/2573] eta: 0:00:20 time: 0.0752 data: 0.0011 max mem: 33368 +Test: [2400/2573] eta: 0:00:12 time: 0.0704 data: 0.0011 max mem: 33368 +Test: [2500/2573] eta: 0:00:05 time: 0.0736 data: 0.0011 max mem: 33368 +Test: Total time: 0:03:12 +Final results: +Mean IoU is 50.22 + + precision@0.5 = 54.00 + precision@0.6 = 45.73 + precision@0.7 = 36.87 + precision@0.8 = 24.94 + precision@0.9 = 9.27 + overall IoU = 51.51 + +Average object IoU 50.22492663500097 +Overall IoU 51.510032653808594 +Better epoch: 3 + +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [4] [ 0/1319] eta: 1:24:05 lr: 4.547576685045799e-05 loss: 0.1120 (0.1120) time: 3.8253 data: 1.1338 max mem: 33368 +Epoch: [4] [ 10/1319] eta: 0:59:02 lr: 4.546714721370884e-05 loss: 0.1335 (0.1323) time: 2.7060 data: 0.1085 max mem: 33368 +Epoch: [4] [ 20/1319] eta: 0:57:34 lr: 4.5458527395388535e-05 loss: 0.1283 (0.1248) time: 2.6011 data: 0.0056 max mem: 33368 +Epoch: [4] [ 30/1319] eta: 0:56:38 lr: 4.544990739545498e-05 loss: 0.1220 (0.1300) time: 2.5981 data: 0.0060 max mem: 33368 +Epoch: [4] [ 40/1319] eta: 0:56:00 lr: 4.544128721386609e-05 loss: 0.1067 (0.1260) time: 2.5942 data: 0.0062 max mem: 33368 +Epoch: [4] [ 50/1319] eta: 0:55:39 lr: 4.543266685057974e-05 loss: 0.0939 (0.1221) time: 2.6247 data: 0.0060 max mem: 33368 +Epoch: [4] [ 60/1319] eta: 0:55:17 lr: 4.54240463055538e-05 loss: 0.1164 (0.1245) time: 2.6503 data: 0.0060 max mem: 33368 +Epoch: [4] [ 70/1319] eta: 0:54:51 lr: 4.541542557874611e-05 loss: 0.1196 (0.1236) time: 2.6450 data: 0.0059 max mem: 33368 +Epoch: [4] [ 80/1319] eta: 0:54:24 lr: 4.540680467011449e-05 loss: 0.1212 (0.1266) time: 2.6356 data: 0.0060 max mem: 33368 +Epoch: [4] [ 90/1319] eta: 0:53:49 lr: 4.5398183579616753e-05 loss: 0.1275 (0.1283) time: 2.5984 data: 0.0060 max mem: 33368 +Epoch: [4] [ 100/1319] eta: 0:53:18 lr: 4.5389562307210684e-05 loss: 0.1275 (0.1277) time: 2.5776 data: 0.0062 max mem: 33368 +Epoch: [4] [ 110/1319] eta: 0:52:47 lr: 4.5380940852854056e-05 loss: 0.1255 (0.1296) time: 2.5849 data: 0.0063 max mem: 33368 +Epoch: [4] [ 120/1319] eta: 0:52:26 lr: 4.537231921650461e-05 loss: 0.1201 (0.1291) time: 2.6246 data: 0.0062 max mem: 33368 +Epoch: [4] [ 130/1319] eta: 0:51:56 lr: 4.53636973981201e-05 loss: 0.1278 (0.1306) time: 2.6262 data: 0.0062 max mem: 33368 +Epoch: [4] [ 140/1319] eta: 0:51:25 lr: 4.535507539765821e-05 loss: 0.1455 (0.1309) time: 2.5745 data: 0.0061 max mem: 33368 +Epoch: [4] [ 150/1319] eta: 0:51:00 lr: 4.534645321507665e-05 loss: 0.1330 (0.1336) time: 2.5990 data: 0.0061 max mem: 33368 +Epoch: [4] [ 160/1319] eta: 0:50:34 lr: 4.53378308503331e-05 loss: 0.1248 (0.1334) time: 2.6247 data: 0.0062 max mem: 33368 +Epoch: [4] [ 170/1319] eta: 0:50:07 lr: 4.532920830338521e-05 loss: 0.1369 (0.1345) time: 2.6170 data: 0.0061 max mem: 33368 +Epoch: [4] [ 180/1319] eta: 0:49:42 lr: 4.5320585574190625e-05 loss: 0.1471 (0.1346) time: 2.6253 data: 0.0060 max mem: 33368 +Epoch: [4] [ 190/1319] eta: 0:49:17 lr: 4.5311962662706955e-05 loss: 0.1190 (0.1345) time: 2.6346 data: 0.0062 max mem: 33368 +Epoch: [4] [ 200/1319] eta: 0:48:51 lr: 4.5303339568891794e-05 loss: 0.1012 (0.1329) time: 2.6269 data: 0.0062 max mem: 33368 +Epoch: [4] [ 210/1319] eta: 0:48:28 lr: 4.529471629270274e-05 loss: 0.1122 (0.1323) time: 2.6492 data: 0.0060 max mem: 33368 +Epoch: [4] [ 220/1319] eta: 0:48:02 lr: 4.5286092834097356e-05 loss: 0.1201 (0.1323) time: 2.6571 data: 0.0060 max mem: 33368 +Epoch: [4] [ 230/1319] eta: 0:47:37 lr: 4.527746919303318e-05 loss: 0.1219 (0.1329) time: 2.6444 data: 0.0060 max mem: 33368 +Epoch: [4] [ 240/1319] eta: 0:47:11 lr: 4.5268845369467734e-05 loss: 0.1184 (0.1325) time: 2.6338 data: 0.0061 max mem: 33368 +Epoch: [4] [ 250/1319] eta: 0:46:43 lr: 4.526022136335852e-05 loss: 0.1133 (0.1327) time: 2.6090 data: 0.0062 max mem: 33368 +Epoch: [4] [ 260/1319] eta: 0:46:16 lr: 4.525159717466304e-05 loss: 0.1276 (0.1331) time: 2.5955 data: 0.0062 max mem: 33368 +Epoch: [4] [ 270/1319] eta: 0:45:49 lr: 4.524297280333875e-05 loss: 0.1236 (0.1329) time: 2.5950 data: 0.0061 max mem: 33368 +Epoch: [4] [ 280/1319] eta: 0:45:23 lr: 4.5234348249343114e-05 loss: 0.1187 (0.1334) time: 2.6172 data: 0.0061 max mem: 33368 +Epoch: [4] [ 290/1319] eta: 0:44:57 lr: 4.522572351263354e-05 loss: 0.1232 (0.1334) time: 2.6316 data: 0.0062 max mem: 33368 +Epoch: [4] [ 300/1319] eta: 0:44:31 lr: 4.521709859316746e-05 loss: 0.1242 (0.1336) time: 2.6296 data: 0.0061 max mem: 33368 +Epoch: [4] [ 310/1319] eta: 0:44:03 lr: 4.520847349090225e-05 loss: 0.1124 (0.1331) time: 2.5999 data: 0.0061 max mem: 33368 +Epoch: [4] [ 320/1319] eta: 0:43:37 lr: 4.5199848205795306e-05 loss: 0.1119 (0.1329) time: 2.5877 data: 0.0062 max mem: 33368 +Epoch: [4] [ 330/1319] eta: 0:43:10 lr: 4.519122273780396e-05 loss: 0.1088 (0.1319) time: 2.6041 data: 0.0062 max mem: 33368 +Epoch: [4] [ 340/1319] eta: 0:42:43 lr: 4.518259708688556e-05 loss: 0.1088 (0.1320) time: 2.5968 data: 0.0062 max mem: 33368 +Epoch: [4] [ 350/1319] eta: 0:42:17 lr: 4.5173971252997424e-05 loss: 0.1326 (0.1323) time: 2.6067 data: 0.0062 max mem: 33368 +Epoch: [4] [ 360/1319] eta: 0:41:51 lr: 4.5165345236096837e-05 loss: 0.1340 (0.1327) time: 2.6230 data: 0.0061 max mem: 33368 +Epoch: [4] [ 370/1319] eta: 0:41:24 lr: 4.5156719036141086e-05 loss: 0.1406 (0.1332) time: 2.6136 data: 0.0061 max mem: 33368 +Epoch: [4] [ 380/1319] eta: 0:40:59 lr: 4.5148092653087434e-05 loss: 0.1402 (0.1334) time: 2.6252 data: 0.0062 max mem: 33368 +Epoch: [4] [ 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loss: 0.1237 (0.1324) time: 2.6486 data: 0.0063 max mem: 33368 +Epoch: [4] [ 870/1319] eta: 0:19:36 lr: 4.4725174693265234e-05 loss: 0.1174 (0.1323) time: 2.6339 data: 0.0063 max mem: 33368 +Epoch: [4] [ 880/1319] eta: 0:19:10 lr: 4.471653910039782e-05 loss: 0.1188 (0.1324) time: 2.6327 data: 0.0060 max mem: 33368 +Epoch: [4] [ 890/1319] eta: 0:18:43 lr: 4.4707903322227184e-05 loss: 0.1257 (0.1322) time: 2.6439 data: 0.0060 max mem: 33368 +Epoch: [4] [ 900/1319] eta: 0:18:17 lr: 4.469926735870959e-05 loss: 0.1187 (0.1322) time: 2.6245 data: 0.0062 max mem: 33368 +Epoch: [4] [ 910/1319] eta: 0:17:51 lr: 4.4690631209801266e-05 loss: 0.1187 (0.1322) time: 2.6356 data: 0.0063 max mem: 33368 +Epoch: [4] [ 920/1319] eta: 0:17:25 lr: 4.4681994875458425e-05 loss: 0.1157 (0.1321) time: 2.6579 data: 0.0062 max mem: 33368 +Epoch: [4] [ 930/1319] eta: 0:16:59 lr: 4.467335835563727e-05 loss: 0.1157 (0.1320) time: 2.6572 data: 0.0061 max mem: 33368 +Epoch: [4] [ 940/1319] eta: 0:16:33 lr: 4.466472165029396e-05 loss: 0.1232 (0.1322) time: 2.6412 data: 0.0062 max mem: 33368 +Epoch: [4] [ 950/1319] eta: 0:16:07 lr: 4.4656084759384645e-05 loss: 0.1275 (0.1321) time: 2.6334 data: 0.0063 max mem: 33368 +Epoch: [4] [ 960/1319] eta: 0:15:40 lr: 4.464744768286547e-05 loss: 0.1212 (0.1323) time: 2.6086 data: 0.0063 max mem: 33368 +Epoch: [4] [ 970/1319] eta: 0:15:14 lr: 4.463881042069255e-05 loss: 0.1259 (0.1323) time: 2.6001 data: 0.0063 max mem: 33368 +Epoch: [4] [ 980/1319] eta: 0:14:48 lr: 4.463017297282197e-05 loss: 0.1273 (0.1323) time: 2.6159 data: 0.0062 max mem: 33368 +Epoch: [4] [ 990/1319] eta: 0:14:22 lr: 4.4621535339209816e-05 loss: 0.1280 (0.1323) time: 2.6103 data: 0.0061 max mem: 33368 +Epoch: [4] [1000/1319] eta: 0:13:56 lr: 4.461289751981212e-05 loss: 0.1298 (0.1322) time: 2.6335 data: 0.0062 max mem: 33368 +Epoch: [4] [1010/1319] eta: 0:13:29 lr: 4.460425951458493e-05 loss: 0.1182 (0.1321) time: 2.6312 data: 0.0063 max mem: 33368 +Epoch: [4] [1020/1319] eta: 0:13:03 lr: 4.459562132348427e-05 loss: 0.1234 (0.1322) time: 2.6107 data: 0.0064 max mem: 33368 +Epoch: [4] [1030/1319] eta: 0:12:37 lr: 4.458698294646612e-05 loss: 0.1194 (0.1319) time: 2.6069 data: 0.0064 max mem: 33368 +Epoch: [4] [1040/1319] eta: 0:12:11 lr: 4.457834438348646e-05 loss: 0.0940 (0.1316) time: 2.6072 data: 0.0063 max mem: 33368 +Epoch: [4] [1050/1319] eta: 0:11:44 lr: 4.456970563450125e-05 loss: 0.0961 (0.1317) time: 2.6246 data: 0.0063 max mem: 33368 +Epoch: [4] [1060/1319] eta: 0:11:18 lr: 4.456106669946641e-05 loss: 0.1125 (0.1316) time: 2.6363 data: 0.0063 max mem: 33368 +Epoch: [4] [1070/1319] eta: 0:10:52 lr: 4.4552427578337865e-05 loss: 0.1125 (0.1315) time: 2.6314 data: 0.0062 max mem: 33368 +Epoch: [4] [1080/1319] eta: 0:10:26 lr: 4.45437882710715e-05 loss: 0.1420 (0.1319) time: 2.5924 data: 0.0062 max mem: 33368 +Epoch: [4] [1090/1319] eta: 0:09:59 lr: 4.453514877762321e-05 loss: 0.1420 (0.1319) time: 2.5707 data: 0.0062 max mem: 33368 +Epoch: [4] 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+Epoch: [4] [1180/1319] eta: 0:06:04 lr: 4.4457384951110855e-05 loss: 0.1139 (0.1324) time: 2.5886 data: 0.0064 max mem: 33368 +Epoch: [4] [1190/1319] eta: 0:05:37 lr: 4.44487435934119e-05 loss: 0.1113 (0.1323) time: 2.6027 data: 0.0064 max mem: 33368 +Epoch: [4] [1200/1319] eta: 0:05:11 lr: 4.4440102049044326e-05 loss: 0.1124 (0.1324) time: 2.6361 data: 0.0064 max mem: 33368 +Epoch: [4] [1210/1319] eta: 0:04:45 lr: 4.443146031796374e-05 loss: 0.1124 (0.1323) time: 2.6563 data: 0.0063 max mem: 33368 +Epoch: [4] [1220/1319] eta: 0:04:19 lr: 4.442281840012577e-05 loss: 0.1173 (0.1323) time: 2.6618 data: 0.0062 max mem: 33368 +Epoch: [4] [1230/1319] eta: 0:03:53 lr: 4.441417629548601e-05 loss: 0.1314 (0.1323) time: 2.6548 data: 0.0063 max mem: 33368 +Epoch: [4] [1240/1319] eta: 0:03:27 lr: 4.4405534004000035e-05 loss: 0.1321 (0.1324) time: 2.6222 data: 0.0066 max mem: 33368 +Epoch: [4] [1250/1319] eta: 0:03:00 lr: 4.439689152562339e-05 loss: 0.1537 (0.1328) time: 2.6096 data: 0.0067 max mem: 33368 +Epoch: [4] [1260/1319] eta: 0:02:34 lr: 4.438824886031161e-05 loss: 0.1347 (0.1328) time: 2.6237 data: 0.0066 max mem: 33368 +Epoch: [4] [1270/1319] eta: 0:02:08 lr: 4.437960600802022e-05 loss: 0.1149 (0.1327) time: 2.6504 data: 0.0066 max mem: 33368 +Epoch: [4] [1280/1319] eta: 0:01:42 lr: 4.4370962968704706e-05 loss: 0.1149 (0.1327) time: 2.6549 data: 0.0069 max mem: 33368 +Epoch: [4] [1290/1319] eta: 0:01:16 lr: 4.436231974232054e-05 loss: 0.1165 (0.1326) time: 2.6248 data: 0.0067 max mem: 33368 +Epoch: [4] [1300/1319] eta: 0:00:49 lr: 4.435367632882316e-05 loss: 0.1009 (0.1325) time: 2.6125 data: 0.0068 max mem: 33368 +Epoch: [4] [1310/1319] eta: 0:00:23 lr: 4.434503272816803e-05 loss: 0.0994 (0.1324) time: 2.6280 data: 0.0071 max mem: 33368 +Epoch: [4] Total time: 0:57:38 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 3:04:55 time: 4.3124 data: 4.2327 max mem: 33368 +Test: [ 100/2573] eta: 0:04:40 time: 0.0713 data: 0.0011 max mem: 33368 +Test: [ 200/2573] eta: 0:03:42 time: 0.0735 data: 0.0011 max mem: 33368 +Test: [ 300/2573] eta: 0:03:16 time: 0.0745 data: 0.0008 max mem: 33368 +Test: [ 400/2573] eta: 0:03:00 time: 0.0749 data: 0.0011 max mem: 33368 +Test: [ 500/2573] eta: 0:02:48 time: 0.0735 data: 0.0011 max mem: 33368 +Test: [ 600/2573] eta: 0:02:38 time: 0.0736 data: 0.0011 max mem: 33368 +Test: [ 700/2573] eta: 0:02:28 time: 0.0736 data: 0.0011 max mem: 33368 +Test: [ 800/2573] eta: 0:02:19 time: 0.0770 data: 0.0011 max mem: 33368 +Test: [ 900/2573] eta: 0:02:11 time: 0.0736 data: 0.0011 max mem: 33368 +Test: [1000/2573] eta: 0:02:02 time: 0.0736 data: 0.0011 max mem: 33368 +Test: [1100/2573] eta: 0:01:54 time: 0.0737 data: 0.0011 max mem: 33368 +Test: [1200/2573] eta: 0:01:46 time: 0.0736 data: 0.0011 max mem: 33368 +Test: [1300/2573] eta: 0:01:38 time: 0.0736 data: 0.0011 max mem: 33368 +Test: [1400/2573] eta: 0:01:29 time: 0.0720 data: 0.0011 max mem: 33368 +Test: [1500/2573] eta: 0:01:22 time: 0.0739 data: 0.0009 max mem: 33368 +Test: [1600/2573] eta: 0:01:14 time: 0.0774 data: 0.0011 max mem: 33368 +Test: [1700/2573] eta: 0:01:07 time: 0.0723 data: 0.0011 max mem: 33368 +Test: [1800/2573] eta: 0:00:59 time: 0.0758 data: 0.0011 max mem: 33368 +Test: [1900/2573] eta: 0:00:51 time: 0.0725 data: 0.0011 max mem: 33368 +Test: [2000/2573] eta: 0:00:43 time: 0.0741 data: 0.0011 max mem: 33368 +Test: [2100/2573] eta: 0:00:36 time: 0.0756 data: 0.0009 max mem: 33368 +Test: [2200/2573] eta: 0:00:28 time: 0.0758 data: 0.0011 max mem: 33368 +Test: [2300/2573] eta: 0:00:20 time: 0.0758 data: 0.0011 max mem: 33368 +Test: [2400/2573] eta: 0:00:13 time: 0.0708 data: 0.0011 max mem: 33368 +Test: [2500/2573] eta: 0:00:05 time: 0.0741 data: 0.0011 max mem: 33368 +Test: Total time: 0:03:15 +Final results: +Mean IoU is 53.40 + + precision@0.5 = 59.54 + precision@0.6 = 52.14 + precision@0.7 = 42.65 + precision@0.8 = 30.29 + precision@0.9 = 11.89 + overall IoU = 53.44 + +Average object IoU 53.39542049951442 +Overall IoU 53.44011688232422 +Better epoch: 4 + +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [5] [ 0/1319] eta: 1:26:00 lr: 4.433725332752167e-05 loss: 0.1334 (0.1334) time: 3.9122 data: 1.1811 max mem: 33368 +Epoch: [5] [ 10/1319] eta: 1:00:29 lr: 4.432860937114392e-05 loss: 0.0904 (0.1140) time: 2.7725 data: 0.1129 max mem: 33368 +Epoch: [5] [ 20/1319] eta: 0:58:44 lr: 4.4319965227479046e-05 loss: 0.1019 (0.1181) time: 2.6532 data: 0.0056 max mem: 33368 +Epoch: [5] [ 30/1319] eta: 0:57:43 lr: 4.43113208964824e-05 loss: 0.1165 (0.1197) time: 2.6400 data: 0.0057 max mem: 33368 +Epoch: [5] [ 40/1319] eta: 0:57:00 lr: 4.43026763781093e-05 loss: 0.1020 (0.1165) time: 2.6341 data: 0.0061 max mem: 33368 +Epoch: [5] [ 50/1319] eta: 0:56:26 lr: 4.429403167231508e-05 loss: 0.1106 (0.1237) time: 2.6406 data: 0.0060 max mem: 33368 +Epoch: [5] [ 60/1319] eta: 0:55:54 lr: 4.428538677905502e-05 loss: 0.1271 (0.1225) time: 2.6433 data: 0.0060 max mem: 33368 +Epoch: [5] [ 70/1319] eta: 0:55:19 lr: 4.4276741698284395e-05 loss: 0.1240 (0.1249) time: 2.6288 data: 0.0062 max mem: 33368 +Epoch: [5] [ 80/1319] eta: 0:54:48 lr: 4.4268096429958464e-05 loss: 0.1126 (0.1233) time: 2.6221 data: 0.0062 max mem: 33368 +Epoch: [5] [ 90/1319] eta: 0:54:20 lr: 4.425945097403244e-05 loss: 0.0975 (0.1220) time: 2.6368 data: 0.0062 max mem: 33368 +Epoch: [5] [ 100/1319] eta: 0:53:51 lr: 4.425080533046155e-05 loss: 0.0928 (0.1194) time: 2.6380 data: 0.0061 max mem: 33368 +Epoch: [5] [ 110/1319] eta: 0:53:22 lr: 4.424215949920098e-05 loss: 0.1017 (0.1218) time: 2.6314 data: 0.0059 max mem: 33368 +Epoch: [5] [ 120/1319] eta: 0:52:50 lr: 4.423351348020589e-05 loss: 0.1351 (0.1234) time: 2.6124 data: 0.0059 max mem: 33368 +Epoch: [5] [ 130/1319] eta: 0:52:19 lr: 4.4224867273431445e-05 loss: 0.1192 (0.1224) time: 2.5935 data: 0.0059 max mem: 33368 +Epoch: [5] [ 140/1319] eta: 0:51:48 lr: 4.421622087883277e-05 loss: 0.1101 (0.1226) time: 2.5904 data: 0.0061 max mem: 33368 +Epoch: [5] [ 150/1319] eta: 0:51:19 lr: 4.4207574296364965e-05 loss: 0.1025 (0.1214) time: 2.5959 data: 0.0062 max mem: 33368 +Epoch: [5] [ 160/1319] eta: 0:50:51 lr: 4.419892752598312e-05 loss: 0.1022 (0.1212) time: 2.6081 data: 0.0062 max mem: 33368 +Epoch: [5] [ 170/1319] eta: 0:50:27 lr: 4.419028056764231e-05 loss: 0.1039 (0.1219) time: 2.6333 data: 0.0060 max mem: 33368 +Epoch: [5] [ 180/1319] eta: 0:49:59 lr: 4.418163342129758e-05 loss: 0.1125 (0.1233) time: 2.6363 data: 0.0061 max mem: 33368 +Epoch: [5] [ 190/1319] eta: 0:49:32 lr: 4.417298608690395e-05 loss: 0.1206 (0.1241) time: 2.6199 data: 0.0062 max mem: 33368 +Epoch: [5] [ 200/1319] eta: 0:49:05 lr: 4.416433856441643e-05 loss: 0.1171 (0.1240) time: 2.6209 data: 0.0061 max mem: 33368 +Epoch: [5] [ 210/1319] eta: 0:48:37 lr: 4.415569085379001e-05 loss: 0.1126 (0.1239) time: 2.6122 data: 0.0061 max mem: 33368 +Epoch: [5] [ 220/1319] eta: 0:48:12 lr: 4.4147042954979643e-05 loss: 0.1055 (0.1237) time: 2.6266 data: 0.0061 max mem: 33368 +Epoch: [5] [ 230/1319] eta: 0:47:46 lr: 4.413839486794028e-05 loss: 0.1166 (0.1239) time: 2.6458 data: 0.0061 max mem: 33368 +Epoch: [5] [ 240/1319] eta: 0:47:18 lr: 4.412974659262685e-05 loss: 0.1248 (0.1239) time: 2.6137 data: 0.0061 max mem: 33368 +Epoch: [5] [ 250/1319] eta: 0:46:50 lr: 4.412109812899424e-05 loss: 0.1158 (0.1235) time: 2.5884 data: 0.0060 max mem: 33368 +Epoch: [5] [ 260/1319] eta: 0:46:24 lr: 4.411244947699735e-05 loss: 0.1234 (0.1236) time: 2.6231 data: 0.0062 max mem: 33368 +Epoch: [5] [ 270/1319] eta: 0:45:57 lr: 4.4103800636591036e-05 loss: 0.1282 (0.1239) time: 2.6308 data: 0.0062 max mem: 33368 +Epoch: [5] [ 280/1319] eta: 0:45:32 lr: 4.409515160773014e-05 loss: 0.1309 (0.1244) time: 2.6376 data: 0.0060 max mem: 33368 +Epoch: [5] [ 290/1319] eta: 0:45:04 lr: 4.408650239036947e-05 loss: 0.1214 (0.1238) time: 2.6247 data: 0.0060 max mem: 33368 +Epoch: [5] [ 300/1319] eta: 0:44:37 lr: 4.407785298446384e-05 loss: 0.1081 (0.1236) time: 2.5891 data: 0.0061 max mem: 33368 +Epoch: [5] [ 310/1319] eta: 0:44:12 lr: 4.406920338996803e-05 loss: 0.1012 (0.1235) time: 2.6285 data: 0.0061 max mem: 33368 +Epoch: [5] [ 320/1319] eta: 0:43:45 lr: 4.406055360683679e-05 loss: 0.1012 (0.1238) time: 2.6306 data: 0.0060 max mem: 33368 +Epoch: [5] [ 330/1319] eta: 0:43:19 lr: 4.4051903635024855e-05 loss: 0.1181 (0.1238) time: 2.6166 data: 0.0061 max mem: 33368 +Epoch: [5] [ 340/1319] eta: 0:42:52 lr: 4.404325347448695e-05 loss: 0.0986 (0.1234) time: 2.6210 data: 0.0060 max mem: 33368 +Epoch: [5] [ 350/1319] eta: 0:42:25 lr: 4.403460312517776e-05 loss: 0.0864 (0.1227) time: 2.6088 data: 0.0059 max mem: 33368 +Epoch: [5] [ 360/1319] eta: 0:41:58 lr: 4.402595258705198e-05 loss: 0.0972 (0.1226) time: 2.6106 data: 0.0059 max mem: 33368 +Epoch: [5] [ 370/1319] eta: 0:41:33 lr: 4.401730186006425e-05 loss: 0.1194 (0.1230) time: 2.6298 data: 0.0060 max mem: 33368 +Epoch: [5] [ 380/1319] eta: 0:41:06 lr: 4.40086509441692e-05 loss: 0.1227 (0.1231) time: 2.6426 data: 0.0061 max mem: 33368 +Epoch: [5] [ 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(0.1223) time: 2.6573 data: 0.0061 max mem: 33368 +Epoch: [5] [ 790/1319] eta: 0:23:08 lr: 4.3653800180569845e-05 loss: 0.1044 (0.1222) time: 2.6240 data: 0.0060 max mem: 33368 +Epoch: [5] [ 800/1319] eta: 0:22:42 lr: 4.364514128932435e-05 loss: 0.1094 (0.1220) time: 2.6251 data: 0.0060 max mem: 33368 +Epoch: [5] [ 810/1319] eta: 0:22:16 lr: 4.363648220720092e-05 loss: 0.1028 (0.1219) time: 2.6333 data: 0.0061 max mem: 33368 +Epoch: [5] [ 820/1319] eta: 0:21:50 lr: 4.3627822934153263e-05 loss: 0.1059 (0.1219) time: 2.6643 data: 0.0061 max mem: 33368 +Epoch: [5] [ 830/1319] eta: 0:21:23 lr: 4.361916347013505e-05 loss: 0.0982 (0.1217) time: 2.6377 data: 0.0062 max mem: 33368 +Epoch: [5] [ 840/1319] eta: 0:20:57 lr: 4.361050381509995e-05 loss: 0.1004 (0.1216) time: 2.5970 data: 0.0061 max mem: 33368 +Epoch: [5] [ 850/1319] eta: 0:20:31 lr: 4.3601843969001596e-05 loss: 0.1178 (0.1218) time: 2.6098 data: 0.0061 max mem: 33368 +Epoch: [5] [ 860/1319] eta: 0:20:04 lr: 4.359318393179363e-05 loss: 0.1178 (0.1218) time: 2.6123 data: 0.0061 max mem: 33368 +Epoch: [5] [ 870/1319] eta: 0:19:38 lr: 4.3584523703429616e-05 loss: 0.1264 (0.1221) time: 2.6004 data: 0.0061 max mem: 33368 +Epoch: [5] [ 880/1319] eta: 0:19:12 lr: 4.357586328386315e-05 loss: 0.1121 (0.1219) time: 2.6075 data: 0.0061 max mem: 33368 +Epoch: [5] [ 890/1319] eta: 0:18:45 lr: 4.356720267304778e-05 loss: 0.0991 (0.1218) time: 2.6136 data: 0.0061 max mem: 33368 +Epoch: [5] [ 900/1319] eta: 0:18:19 lr: 4.3558541870937056e-05 loss: 0.0991 (0.1216) time: 2.6206 data: 0.0061 max mem: 33368 +Epoch: [5] [ 910/1319] eta: 0:17:53 lr: 4.354988087748445e-05 loss: 0.0963 (0.1213) time: 2.6362 data: 0.0061 max mem: 33368 +Epoch: [5] [ 920/1319] eta: 0:17:27 lr: 4.35412196926435e-05 loss: 0.1007 (0.1213) time: 2.6074 data: 0.0062 max mem: 33368 +Epoch: [5] [ 930/1319] eta: 0:17:00 lr: 4.353255831636764e-05 loss: 0.1237 (0.1212) time: 2.6227 data: 0.0062 max mem: 33368 +Epoch: [5] [ 940/1319] eta: 0:16:34 lr: 4.352389674861032e-05 loss: 0.1216 (0.1215) time: 2.6411 data: 0.0061 max mem: 33368 +Epoch: [5] [ 950/1319] eta: 0:16:08 lr: 4.3515234989324975e-05 loss: 0.1159 (0.1218) time: 2.6212 data: 0.0060 max mem: 33368 +Epoch: [5] [ 960/1319] eta: 0:15:42 lr: 4.350657303846501e-05 loss: 0.1109 (0.1218) time: 2.6067 data: 0.0062 max mem: 33368 +Epoch: [5] [ 970/1319] eta: 0:15:15 lr: 4.34979108959838e-05 loss: 0.1167 (0.1219) time: 2.6026 data: 0.0062 max mem: 33368 +Epoch: [5] [ 980/1319] eta: 0:14:49 lr: 4.348924856183469e-05 loss: 0.1281 (0.1223) time: 2.6142 data: 0.0063 max mem: 33368 +Epoch: [5] [ 990/1319] eta: 0:14:23 lr: 4.348058603597104e-05 loss: 0.1259 (0.1223) time: 2.6423 data: 0.0063 max mem: 33368 +Epoch: [5] [1000/1319] eta: 0:13:57 lr: 4.347192331834616e-05 loss: 0.1274 (0.1224) time: 2.6520 data: 0.0061 max mem: 33368 +Epoch: [5] [1010/1319] eta: 0:13:31 lr: 4.346326040891335e-05 loss: 0.1154 (0.1225) time: 2.6491 data: 0.0062 max mem: 33368 +Epoch: [5] [1020/1319] eta: 0:13:04 lr: 4.345459730762588e-05 loss: 0.1154 (0.1228) time: 2.6428 data: 0.0062 max mem: 33368 +Epoch: [5] [1030/1319] eta: 0:12:38 lr: 4.344593401443699e-05 loss: 0.1320 (0.1228) time: 2.6304 data: 0.0061 max mem: 33368 +Epoch: [5] [1040/1319] eta: 0:12:12 lr: 4.343727052929992e-05 loss: 0.1151 (0.1228) time: 2.6281 data: 0.0062 max mem: 33368 +Epoch: [5] [1050/1319] eta: 0:11:46 lr: 4.342860685216788e-05 loss: 0.1110 (0.1227) time: 2.6083 data: 0.0062 max mem: 33368 +Epoch: [5] [1060/1319] eta: 0:11:19 lr: 4.341994298299405e-05 loss: 0.1154 (0.1226) time: 2.5927 data: 0.0062 max mem: 33368 +Epoch: [5] [1070/1319] eta: 0:10:53 lr: 4.341127892173159e-05 loss: 0.1206 (0.1228) time: 2.6139 data: 0.0062 max mem: 33368 +Epoch: [5] [1080/1319] eta: 0:10:27 lr: 4.3402614668333656e-05 loss: 0.1194 (0.1228) time: 2.6636 data: 0.0061 max mem: 33368 +Epoch: [5] [1090/1319] eta: 0:10:01 lr: 4.339395022275336e-05 loss: 0.1114 (0.1227) time: 2.6611 data: 0.0061 max mem: 33368 +Epoch: [5] 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+Epoch: [5] [1180/1319] eta: 0:06:04 lr: 4.331596155657851e-05 loss: 0.1044 (0.1222) time: 2.6412 data: 0.0063 max mem: 33368 +Epoch: [5] [1190/1319] eta: 0:05:38 lr: 4.3307295186591415e-05 loss: 0.1086 (0.1221) time: 2.6219 data: 0.0062 max mem: 33368 +Epoch: [5] [1200/1319] eta: 0:05:12 lr: 4.329862862390485e-05 loss: 0.1078 (0.1221) time: 2.6150 data: 0.0062 max mem: 33368 +Epoch: [5] [1210/1319] eta: 0:04:46 lr: 4.328996186847165e-05 loss: 0.1114 (0.1222) time: 2.6224 data: 0.0061 max mem: 33368 +Epoch: [5] [1220/1319] eta: 0:04:19 lr: 4.328129492024467e-05 loss: 0.1171 (0.1223) time: 2.5987 data: 0.0061 max mem: 33368 +Epoch: [5] [1230/1319] eta: 0:03:53 lr: 4.3272627779176715e-05 loss: 0.0989 (0.1222) time: 2.5881 data: 0.0064 max mem: 33368 +Epoch: [5] [1240/1319] eta: 0:03:27 lr: 4.326396044522058e-05 loss: 0.1029 (0.1223) time: 2.5960 data: 0.0064 max mem: 33368 +Epoch: [5] [1250/1319] eta: 0:03:01 lr: 4.3255292918329036e-05 loss: 0.1241 (0.1224) time: 2.6057 data: 0.0062 max mem: 33368 +Epoch: [5] [1260/1319] eta: 0:02:34 lr: 4.324662519845482e-05 loss: 0.1247 (0.1225) time: 2.6249 data: 0.0063 max mem: 33368 +Epoch: [5] [1270/1319] eta: 0:02:08 lr: 4.323795728555066e-05 loss: 0.1265 (0.1226) time: 2.6293 data: 0.0063 max mem: 33368 +Epoch: [5] [1280/1319] eta: 0:01:42 lr: 4.322928917956926e-05 loss: 0.1068 (0.1226) time: 2.6457 data: 0.0063 max mem: 33368 +Epoch: [5] [1290/1319] eta: 0:01:16 lr: 4.322062088046332e-05 loss: 0.1164 (0.1227) time: 2.6424 data: 0.0063 max mem: 33368 +Epoch: [5] [1300/1319] eta: 0:00:49 lr: 4.321195238818547e-05 loss: 0.1266 (0.1227) time: 2.6184 data: 0.0063 max mem: 33368 +Epoch: [5] [1310/1319] eta: 0:00:23 lr: 4.3203283702688355e-05 loss: 0.1068 (0.1226) time: 2.6281 data: 0.0063 max mem: 33368 +Epoch: [5] Total time: 0:57:41 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 2:00:27 time: 2.8091 data: 2.7297 max mem: 33368 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 100/2573] eta: 0:04:04 time: 0.0715 data: 0.0011 max mem: 33368 +Test: [ 200/2573] eta: 0:03:25 time: 0.0728 data: 0.0011 max mem: 33368 +Test: [ 300/2573] eta: 0:03:46 time: 0.0741 data: 0.0010 max mem: 33368 +Test: [ 400/2573] eta: 0:04:16 time: 0.1766 data: 0.1037 max mem: 33368 +Test: [ 500/2573] eta: 0:03:48 time: 0.0728 data: 0.0011 max mem: 33368 +Test: [ 600/2573] eta: 0:03:25 time: 0.0732 data: 0.0011 max mem: 33368 +Test: [ 700/2573] eta: 0:03:07 time: 0.0732 data: 0.0011 max mem: 33368 +Test: [ 800/2573] eta: 0:02:51 time: 0.0765 data: 0.0011 max mem: 33368 +Test: [ 900/2573] eta: 0:02:37 time: 0.0732 data: 0.0011 max mem: 33368 +Test: [1000/2573] eta: 0:02:25 time: 0.0733 data: 0.0011 max mem: 33368 +Test: [1100/2573] eta: 0:02:13 time: 0.0734 data: 0.0011 max mem: 33368 +Test: [1200/2573] eta: 0:02:02 time: 0.0735 data: 0.0011 max mem: 33368 +Test: [1300/2573] eta: 0:01:51 time: 0.0735 data: 0.0011 max mem: 33368 +Test: [1400/2573] eta: 0:01:41 time: 0.0719 data: 0.0010 max mem: 33368 +Test: [1500/2573] eta: 0:01:32 time: 0.0736 data: 0.0011 max mem: 33368 +Test: [1600/2573] eta: 0:01:22 time: 0.0771 data: 0.0011 max mem: 33368 +Test: [1700/2573] eta: 0:01:13 time: 0.0720 data: 0.0011 max mem: 33368 +Test: [1800/2573] eta: 0:01:04 time: 0.0753 data: 0.0011 max mem: 33368 +Test: [1900/2573] eta: 0:00:56 time: 0.0721 data: 0.0010 max mem: 33368 +Test: [2000/2573] eta: 0:00:47 time: 0.0737 data: 0.0011 max mem: 33368 +Test: [2100/2573] eta: 0:00:38 time: 0.0755 data: 0.0011 max mem: 33368 +Test: [2200/2573] eta: 0:00:30 time: 0.0755 data: 0.0011 max mem: 33368 +Test: [2300/2573] eta: 0:00:22 time: 0.0754 data: 0.0011 max mem: 33368 +Test: [2400/2573] eta: 0:00:14 time: 0.0704 data: 0.0011 max mem: 33368 +Test: [2500/2573] eta: 0:00:05 time: 0.0739 data: 0.0011 max mem: 33368 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: Total time: 0:03:28 +Final results: +Mean IoU is 55.41 + + precision@0.5 = 61.66 + precision@0.6 = 55.25 + precision@0.7 = 46.61 + precision@0.8 = 34.11 + precision@0.9 = 14.75 + overall IoU = 55.19 + +Average object IoU 55.413661089517205 +Overall IoU 55.19297790527344 +Better epoch: 5 + +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [6] [ 0/1319] eta: 1:26:01 lr: 4.319548172049932e-05 loss: 0.0656 (0.0656) time: 3.9133 data: 1.1411 max mem: 33368 +Epoch: [6] [ 10/1319] eta: 1:00:16 lr: 4.318681266775505e-05 loss: 0.1048 (0.1197) time: 2.7625 data: 0.1091 max mem: 33368 +Epoch: [6] [ 20/1319] eta: 0:58:12 lr: 4.317814342165404e-05 loss: 0.0998 (0.1110) time: 2.6273 data: 0.0058 max mem: 33368 +Epoch: [6] [ 30/1319] eta: 0:57:42 lr: 4.316947398214883e-05 loss: 0.0970 (0.1069) time: 2.6437 data: 0.0059 max mem: 33368 +Epoch: [6] [ 40/1319] eta: 0:56:53 lr: 4.316080434919196e-05 loss: 0.0991 (0.1078) time: 2.6489 data: 0.0061 max mem: 33368 +Epoch: [6] [ 50/1319] eta: 0:56:23 lr: 4.315213452273593e-05 loss: 0.0858 (0.1048) time: 2.6350 data: 0.0061 max mem: 33368 +Epoch: [6] [ 60/1319] eta: 0:55:47 lr: 4.314346450273323e-05 loss: 0.0896 (0.1100) time: 2.6367 data: 0.0061 max mem: 33368 +Epoch: [6] [ 70/1319] eta: 0:55:17 lr: 4.313479428913631e-05 loss: 0.1240 (0.1098) time: 2.6306 data: 0.0062 max mem: 33368 +Epoch: [6] [ 80/1319] eta: 0:54:39 lr: 4.312612388189762e-05 loss: 0.0773 (0.1067) time: 2.6121 data: 0.0062 max mem: 33368 +Epoch: [6] [ 90/1319] eta: 0:54:13 lr: 4.311745328096956e-05 loss: 0.0834 (0.1064) time: 2.6178 data: 0.0060 max mem: 33368 +Epoch: [6] [ 100/1319] eta: 0:53:50 lr: 4.3108782486304546e-05 loss: 0.0865 (0.1048) time: 2.6605 data: 0.0061 max mem: 33368 +Epoch: [6] [ 110/1319] eta: 0:53:20 lr: 4.310011149785494e-05 loss: 0.0968 (0.1059) time: 2.6476 data: 0.0062 max mem: 33368 +Epoch: [6] [ 120/1319] eta: 0:52:54 lr: 4.309144031557308e-05 loss: 0.1077 (0.1061) time: 2.6360 data: 0.0062 max mem: 33368 +Epoch: [6] [ 130/1319] eta: 0:52:22 lr: 4.308276893941131e-05 loss: 0.1029 (0.1063) time: 2.6189 data: 0.0061 max mem: 33368 +Epoch: [6] [ 140/1319] eta: 0:51:54 lr: 4.307409736932192e-05 loss: 0.0983 (0.1049) time: 2.6046 data: 0.0060 max mem: 33368 +Epoch: [6] [ 150/1319] eta: 0:51:29 lr: 4.306542560525721e-05 loss: 0.0876 (0.1052) time: 2.6415 data: 0.0060 max mem: 33368 +Epoch: [6] [ 160/1319] eta: 0:51:01 lr: 4.305675364716942e-05 loss: 0.1003 (0.1065) time: 2.6435 data: 0.0061 max mem: 33368 +Epoch: [6] [ 170/1319] eta: 0:50:34 lr: 4.3048081495010805e-05 loss: 0.1147 (0.1078) time: 2.6250 data: 0.0061 max mem: 33368 +Epoch: [6] [ 180/1319] eta: 0:50:07 lr: 4.303940914873357e-05 loss: 0.1104 (0.1082) time: 2.6276 data: 0.0061 max mem: 33368 +Epoch: [6] [ 190/1319] eta: 0:49:40 lr: 4.30307366082899e-05 loss: 0.1027 (0.1082) time: 2.6330 data: 0.0060 max mem: 33368 +Epoch: [6] [ 200/1319] eta: 0:49:15 lr: 4.302206387363197e-05 loss: 0.1027 (0.1091) time: 2.6534 data: 0.0060 max mem: 33368 +Epoch: [6] [ 210/1319] eta: 0:48:49 lr: 4.301339094471194e-05 loss: 0.1067 (0.1103) time: 2.6516 data: 0.0061 max mem: 33368 +Epoch: [6] [ 220/1319] eta: 0:48:24 lr: 4.300471782148193e-05 loss: 0.0991 (0.1108) time: 2.6542 data: 0.0060 max mem: 33368 +Epoch: [6] [ 230/1319] eta: 0:47:55 lr: 4.299604450389403e-05 loss: 0.0869 (0.1102) time: 2.6369 data: 0.0060 max mem: 33368 +Epoch: [6] [ 240/1319] eta: 0:47:29 lr: 4.298737099190034e-05 loss: 0.1044 (0.1105) time: 2.6177 data: 0.0061 max mem: 33368 +Epoch: [6] [ 250/1319] eta: 0:47:03 lr: 4.297869728545289e-05 loss: 0.1069 (0.1101) time: 2.6422 data: 0.0061 max mem: 33368 +Epoch: [6] [ 260/1319] eta: 0:46:35 lr: 4.2970023384503735e-05 loss: 0.1030 (0.1101) time: 2.6351 data: 0.0060 max mem: 33368 +Epoch: [6] [ 270/1319] eta: 0:46:08 lr: 4.296134928900489e-05 loss: 0.1030 (0.1101) time: 2.6139 data: 0.0060 max mem: 33368 +Epoch: [6] [ 280/1319] eta: 0:45:41 lr: 4.295267499890832e-05 loss: 0.1004 (0.1100) time: 2.6169 data: 0.0061 max mem: 33368 +Epoch: [6] [ 290/1319] eta: 0:45:13 lr: 4.2944000514166015e-05 loss: 0.1004 (0.1099) time: 2.6158 data: 0.0061 max mem: 33368 +Epoch: [6] [ 300/1319] eta: 0:44:47 lr: 4.293532583472992e-05 loss: 0.0822 (0.1091) time: 2.6235 data: 0.0060 max mem: 33368 +Epoch: [6] [ 310/1319] eta: 0:44:20 lr: 4.292665096055194e-05 loss: 0.0864 (0.1087) time: 2.6237 data: 0.0060 max mem: 33368 +Epoch: [6] [ 320/1319] eta: 0:43:53 lr: 4.2917975891583976e-05 loss: 0.1012 (0.1086) time: 2.6111 data: 0.0061 max mem: 33368 +Epoch: [6] [ 330/1319] eta: 0:43:27 lr: 4.2909300627777926e-05 loss: 0.0999 (0.1083) time: 2.6333 data: 0.0060 max mem: 33368 +Epoch: [6] [ 340/1319] eta: 0:42:59 lr: 4.290062516908562e-05 loss: 0.0998 (0.1084) time: 2.6175 data: 0.0060 max mem: 33368 +Epoch: [6] [ 350/1319] eta: 0:42:32 lr: 4.2891949515458894e-05 loss: 0.1051 (0.1086) time: 2.6024 data: 0.0061 max mem: 33368 +Epoch: [6] [ 360/1319] eta: 0:42:05 lr: 4.288327366684957e-05 loss: 0.1156 (0.1090) time: 2.6210 data: 0.0062 max mem: 33368 +Epoch: [6] [ 370/1319] eta: 0:41:40 lr: 4.287459762320942e-05 loss: 0.0902 (0.1085) time: 2.6350 data: 0.0061 max mem: 33368 +Epoch: [6] [ 380/1319] eta: 0:41:12 lr: 4.28659213844902e-05 loss: 0.0884 (0.1084) time: 2.6258 data: 0.0061 max mem: 33368 +Epoch: [6] [ 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loss: 0.0936 (0.1100) time: 2.6370 data: 0.0062 max mem: 33368 +Epoch: [6] [ 870/1319] eta: 0:19:40 lr: 4.2440545704643e-05 loss: 0.0925 (0.1098) time: 2.6330 data: 0.0061 max mem: 33368 +Epoch: [6] [ 880/1319] eta: 0:19:14 lr: 4.243185964996007e-05 loss: 0.1016 (0.1102) time: 2.6404 data: 0.0061 max mem: 33368 +Epoch: [6] [ 890/1319] eta: 0:18:48 lr: 4.24231733977074e-05 loss: 0.1016 (0.1102) time: 2.6378 data: 0.0062 max mem: 33368 +Epoch: [6] [ 900/1319] eta: 0:18:21 lr: 4.2414486947835554e-05 loss: 0.1010 (0.1102) time: 2.6032 data: 0.0061 max mem: 33368 +Epoch: [6] [ 910/1319] eta: 0:17:55 lr: 4.240580030029505e-05 loss: 0.1088 (0.1102) time: 2.5788 data: 0.0061 max mem: 33368 +Epoch: [6] [ 920/1319] eta: 0:17:28 lr: 4.239711345503641e-05 loss: 0.1179 (0.1103) time: 2.6225 data: 0.0062 max mem: 33368 +Epoch: [6] [ 930/1319] eta: 0:17:02 lr: 4.2388426412010114e-05 loss: 0.1083 (0.1103) time: 2.6387 data: 0.0061 max mem: 33368 +Epoch: [6] [ 940/1319] eta: 0:16:36 lr: 4.237973917116662e-05 loss: 0.0919 (0.1102) time: 2.6047 data: 0.0061 max mem: 33368 +Epoch: [6] [ 950/1319] eta: 0:16:09 lr: 4.237105173245638e-05 loss: 0.0916 (0.1101) time: 2.6037 data: 0.0060 max mem: 33368 +Epoch: [6] [ 960/1319] eta: 0:15:43 lr: 4.23623640958298e-05 loss: 0.0889 (0.1100) time: 2.6135 data: 0.0061 max mem: 33368 +Epoch: [6] [ 970/1319] eta: 0:15:17 lr: 4.235367626123727e-05 loss: 0.0958 (0.1101) time: 2.6090 data: 0.0062 max mem: 33368 +Epoch: [6] [ 980/1319] eta: 0:14:50 lr: 4.234498822862916e-05 loss: 0.1001 (0.1101) time: 2.6165 data: 0.0061 max mem: 33368 +Epoch: [6] [ 990/1319] eta: 0:14:24 lr: 4.23362999979558e-05 loss: 0.0964 (0.1099) time: 2.6346 data: 0.0061 max mem: 33368 +Epoch: [6] [1000/1319] eta: 0:13:58 lr: 4.2327611569167524e-05 loss: 0.0917 (0.1101) time: 2.6255 data: 0.0061 max mem: 33368 +Epoch: [6] [1010/1319] eta: 0:13:32 lr: 4.2318922942214635e-05 loss: 0.0881 (0.1099) time: 2.6282 data: 0.0061 max mem: 33368 +Epoch: [6] [1020/1319] eta: 0:13:05 lr: 4.231023411704738e-05 loss: 0.0974 (0.1099) time: 2.6465 data: 0.0061 max mem: 33368 +Epoch: [6] [1030/1319] eta: 0:12:39 lr: 4.230154509361603e-05 loss: 0.1143 (0.1101) time: 2.6248 data: 0.0063 max mem: 33368 +Epoch: [6] [1040/1319] eta: 0:12:13 lr: 4.229285587187079e-05 loss: 0.1163 (0.1100) time: 2.6150 data: 0.0064 max mem: 33368 +Epoch: [6] [1050/1319] eta: 0:11:46 lr: 4.2284166451761876e-05 loss: 0.1128 (0.1101) time: 2.6158 data: 0.0063 max mem: 33368 +Epoch: [6] [1060/1319] eta: 0:11:20 lr: 4.2275476833239456e-05 loss: 0.1128 (0.1102) time: 2.6050 data: 0.0064 max mem: 33368 +Epoch: [6] [1070/1319] eta: 0:10:54 lr: 4.2266787016253686e-05 loss: 0.1117 (0.1102) time: 2.6257 data: 0.0063 max mem: 33368 +Epoch: [6] [1080/1319] eta: 0:10:27 lr: 4.22580970007547e-05 loss: 0.1117 (0.1102) time: 2.6281 data: 0.0062 max mem: 33368 +Epoch: [6] [1090/1319] eta: 0:10:01 lr: 4.224940678669259e-05 loss: 0.1077 (0.1103) time: 2.6182 data: 0.0061 max mem: 33368 +Epoch: [6] 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+Epoch: [6] [1180/1319] eta: 0:06:05 lr: 4.217118591654868e-05 loss: 0.1236 (0.1106) time: 2.6226 data: 0.0065 max mem: 33368 +Epoch: [6] [1190/1319] eta: 0:05:38 lr: 4.2162493714105874e-05 loss: 0.1199 (0.1107) time: 2.6100 data: 0.0062 max mem: 33368 +Epoch: [6] [1200/1319] eta: 0:05:12 lr: 4.2153801312549505e-05 loss: 0.0983 (0.1107) time: 2.5958 data: 0.0061 max mem: 33368 +Epoch: [6] [1210/1319] eta: 0:04:46 lr: 4.2145108711829405e-05 loss: 0.0848 (0.1105) time: 2.6219 data: 0.0063 max mem: 33368 +Epoch: [6] [1220/1319] eta: 0:04:20 lr: 4.213641591189537e-05 loss: 0.0835 (0.1103) time: 2.6325 data: 0.0063 max mem: 33368 +Epoch: [6] [1230/1319] eta: 0:03:53 lr: 4.212772291269716e-05 loss: 0.0939 (0.1104) time: 2.6021 data: 0.0063 max mem: 33368 +Epoch: [6] [1240/1319] eta: 0:03:27 lr: 4.2119029714184504e-05 loss: 0.1021 (0.1104) time: 2.5910 data: 0.0063 max mem: 33368 +Epoch: [6] [1250/1319] eta: 0:03:01 lr: 4.211033631630714e-05 loss: 0.1158 (0.1106) time: 2.6188 data: 0.0063 max mem: 33368 +Epoch: [6] [1260/1319] eta: 0:02:34 lr: 4.2101642719014764e-05 loss: 0.1099 (0.1105) time: 2.6518 data: 0.0062 max mem: 33368 +Epoch: [6] [1270/1319] eta: 0:02:08 lr: 4.2092948922257045e-05 loss: 0.1078 (0.1105) time: 2.6385 data: 0.0063 max mem: 33368 +Epoch: [6] [1280/1319] eta: 0:01:42 lr: 4.208425492598362e-05 loss: 0.1105 (0.1106) time: 2.6042 data: 0.0064 max mem: 33368 +Epoch: [6] [1290/1319] eta: 0:01:16 lr: 4.207556073014412e-05 loss: 0.1032 (0.1107) time: 2.5956 data: 0.0064 max mem: 33368 +Epoch: [6] [1300/1319] eta: 0:00:49 lr: 4.2066866334688144e-05 loss: 0.0992 (0.1106) time: 2.6117 data: 0.0064 max mem: 33368 +Epoch: [6] [1310/1319] eta: 0:00:23 lr: 4.205817173956526e-05 loss: 0.1011 (0.1108) time: 2.6393 data: 0.0062 max mem: 33368 +Epoch: [6] Total time: 0:57:44 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 2:09:41 time: 3.0242 data: 2.9454 max mem: 33368 +Test: [ 100/2573] eta: 0:04:09 time: 0.0712 data: 0.0011 max mem: 33368 +Test: [ 200/2573] eta: 0:03:27 time: 0.0729 data: 0.0011 max mem: 33368 +Test: [ 300/2573] eta: 0:03:06 time: 0.0745 data: 0.0011 max mem: 33368 +Test: [ 400/2573] eta: 0:02:53 time: 0.0745 data: 0.0011 max mem: 33368 +Test: [ 500/2573] eta: 0:02:42 time: 0.0729 data: 0.0010 max mem: 33368 +Test: [ 600/2573] eta: 0:02:33 time: 0.0731 data: 0.0011 max mem: 33368 +Test: [ 700/2573] eta: 0:02:24 time: 0.0733 data: 0.0011 max mem: 33368 +Test: [ 800/2573] eta: 0:02:16 time: 0.0764 data: 0.0011 max mem: 33368 +Test: [ 900/2573] eta: 0:02:08 time: 0.0733 data: 0.0011 max mem: 33368 +Test: [1000/2573] eta: 0:02:00 time: 0.0735 data: 0.0011 max mem: 33368 +Test: [1100/2573] eta: 0:01:52 time: 0.0734 data: 0.0011 max mem: 33368 +Test: [1200/2573] eta: 0:01:44 time: 0.0736 data: 0.0011 max mem: 33368 +Test: [1300/2573] eta: 0:01:36 time: 0.0737 data: 0.0011 max mem: 33368 +Test: [1400/2573] eta: 0:01:28 time: 0.0717 data: 0.0010 max mem: 33368 +Test: [1500/2573] eta: 0:01:20 time: 0.0736 data: 0.0011 max mem: 33368 +Test: [1600/2573] eta: 0:01:13 time: 0.0769 data: 0.0011 max mem: 33368 +Test: [1700/2573] eta: 0:01:05 time: 0.0719 data: 0.0011 max mem: 33368 +Test: [1800/2573] eta: 0:00:58 time: 0.0753 data: 0.0011 max mem: 33368 +Test: [1900/2573] eta: 0:00:50 time: 0.0720 data: 0.0011 max mem: 33368 +Test: [2000/2573] eta: 0:00:42 time: 0.0737 data: 0.0011 max mem: 33368 +Test: [2100/2573] eta: 0:00:35 time: 0.0753 data: 0.0011 max mem: 33368 +Test: [2200/2573] eta: 0:00:27 time: 0.0753 data: 0.0011 max mem: 33368 +Test: [2300/2573] eta: 0:00:20 time: 0.0754 data: 0.0011 max mem: 33368 +Test: [2400/2573] eta: 0:00:12 time: 0.0704 data: 0.0011 max mem: 33368 +Test: [2500/2573] eta: 0:00:05 time: 0.0738 data: 0.0011 max mem: 33368 +Test: Total time: 0:03:12 +Final results: +Mean IoU is 58.61 + + precision@0.5 = 65.81 + precision@0.6 = 58.13 + precision@0.7 = 48.73 + precision@0.8 = 36.05 + precision@0.9 = 15.44 + overall IoU = 57.66 + +Average object IoU 58.606902518198986 +Overall IoU 57.656951904296875 +Better epoch: 6 + +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [7] [ 0/1319] eta: 1:30:39 lr: 4.205034643319776e-05 loss: 0.1143 (0.1143) time: 4.1237 data: 1.4120 max mem: 33368 +Epoch: [7] [ 10/1319] eta: 1:00:10 lr: 4.204165145856875e-05 loss: 0.0865 (0.0949) time: 2.7584 data: 0.1338 max mem: 33368 +Epoch: [7] [ 20/1319] eta: 0:58:08 lr: 4.203295628412646e-05 loss: 0.0849 (0.0920) time: 2.6133 data: 0.0054 max mem: 33368 +Epoch: [7] [ 30/1319] eta: 0:57:15 lr: 4.202426090982037e-05 loss: 0.0849 (0.0900) time: 2.6145 data: 0.0054 max mem: 33368 +Epoch: [7] [ 40/1319] eta: 0:56:32 lr: 4.201556533559993e-05 loss: 0.0793 (0.0953) time: 2.6176 data: 0.0060 max mem: 33368 +Epoch: [7] [ 50/1319] eta: 0:55:58 lr: 4.2006869561414584e-05 loss: 0.0980 (0.0961) time: 2.6179 data: 0.0060 max mem: 33368 +Epoch: [7] [ 60/1319] eta: 0:55:15 lr: 4.199817358721372e-05 loss: 0.0895 (0.0940) time: 2.5958 data: 0.0061 max mem: 33368 +Epoch: [7] [ 70/1319] eta: 0:54:49 lr: 4.1989477412946735e-05 loss: 0.0895 (0.0989) time: 2.6014 data: 0.0061 max mem: 33368 +Epoch: [7] [ 80/1319] eta: 0:54:22 lr: 4.1980781038562975e-05 loss: 0.1042 (0.1005) time: 2.6327 data: 0.0061 max mem: 33368 +Epoch: [7] [ 90/1319] eta: 0:53:59 lr: 4.1972084464011784e-05 loss: 0.0905 (0.0990) time: 2.6418 data: 0.0061 max mem: 33368 +Epoch: [7] [ 100/1319] eta: 0:53:29 lr: 4.1963387689242456e-05 loss: 0.0786 (0.1014) time: 2.6306 data: 0.0061 max mem: 33368 +Epoch: [7] [ 110/1319] eta: 0:53:03 lr: 4.1954690714204276e-05 loss: 0.0831 (0.1014) time: 2.6229 data: 0.0062 max mem: 33368 +Epoch: [7] [ 120/1319] eta: 0:52:42 lr: 4.194599353884651e-05 loss: 0.1166 (0.1040) time: 2.6624 data: 0.0061 max mem: 33368 +Epoch: [7] [ 130/1319] eta: 0:52:08 lr: 4.193729616311839e-05 loss: 0.1166 (0.1040) time: 2.6191 data: 0.0062 max mem: 33368 +Epoch: [7] [ 140/1319] eta: 0:51:36 lr: 4.1928598586969124e-05 loss: 0.1088 (0.1059) time: 2.5589 data: 0.0060 max mem: 33368 +Epoch: [7] [ 150/1319] eta: 0:51:10 lr: 4.1919900810347894e-05 loss: 0.0980 (0.1041) time: 2.5947 data: 0.0060 max mem: 33368 +Epoch: [7] [ 160/1319] eta: 0:50:42 lr: 4.191120283320388e-05 loss: 0.0823 (0.1035) time: 2.6112 data: 0.0062 max mem: 33368 +Epoch: [7] [ 170/1319] eta: 0:50:16 lr: 4.190250465548619e-05 loss: 0.0898 (0.1032) time: 2.6167 data: 0.0061 max mem: 33368 +Epoch: [7] [ 180/1319] eta: 0:49:50 lr: 4.189380627714394e-05 loss: 0.0809 (0.1040) time: 2.6352 data: 0.0060 max mem: 33368 +Epoch: [7] [ 190/1319] eta: 0:49:25 lr: 4.188510769812624e-05 loss: 0.0848 (0.1035) time: 2.6350 data: 0.0059 max mem: 33368 +Epoch: [7] [ 200/1319] eta: 0:48:58 lr: 4.1876408918382123e-05 loss: 0.0893 (0.1031) time: 2.6306 data: 0.0061 max mem: 33368 +Epoch: [7] [ 210/1319] eta: 0:48:31 lr: 4.1867709937860646e-05 loss: 0.0896 (0.1030) time: 2.6128 data: 0.0061 max mem: 33368 +Epoch: [7] [ 220/1319] eta: 0:48:02 lr: 4.185901075651081e-05 loss: 0.0832 (0.1026) time: 2.5922 data: 0.0060 max mem: 33368 +Epoch: [7] [ 230/1319] eta: 0:47:36 lr: 4.185031137428161e-05 loss: 0.0810 (0.1022) time: 2.6058 data: 0.0061 max mem: 33368 +Epoch: [7] [ 240/1319] eta: 0:47:11 lr: 4.1841611791121996e-05 loss: 0.0766 (0.1020) time: 2.6298 data: 0.0061 max mem: 33368 +Epoch: [7] [ 250/1319] eta: 0:46:46 lr: 4.183291200698093e-05 loss: 0.0836 (0.1017) time: 2.6426 data: 0.0060 max mem: 33368 +Epoch: [7] [ 260/1319] eta: 0:46:19 lr: 4.182421202180731e-05 loss: 0.0852 (0.1012) time: 2.6316 data: 0.0060 max mem: 33368 +Epoch: [7] [ 270/1319] eta: 0:45:51 lr: 4.181551183555002e-05 loss: 0.0897 (0.1015) time: 2.6047 data: 0.0059 max mem: 33368 +Epoch: [7] [ 280/1319] eta: 0:45:26 lr: 4.180681144815793e-05 loss: 0.1067 (0.1024) time: 2.6199 data: 0.0060 max mem: 33368 +Epoch: [7] [ 290/1319] eta: 0:44:59 lr: 4.179811085957988e-05 loss: 0.1067 (0.1022) time: 2.6249 data: 0.0060 max mem: 33368 +Epoch: [7] [ 300/1319] eta: 0:44:33 lr: 4.178941006976469e-05 loss: 0.0893 (0.1019) time: 2.6152 data: 0.0061 max mem: 33368 +Epoch: [7] [ 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+Epoch: [7] [1100/1319] eta: 0:09:34 lr: 4.109269029695397e-05 loss: 0.0965 (0.1048) time: 2.6211 data: 0.0061 max mem: 33368 +Epoch: [7] [1110/1319] eta: 0:09:07 lr: 4.108397303462358e-05 loss: 0.1154 (0.1049) time: 2.6381 data: 0.0061 max mem: 33368 +Epoch: [7] [1120/1319] eta: 0:08:41 lr: 4.1075255566772506e-05 loss: 0.1211 (0.1051) time: 2.6211 data: 0.0062 max mem: 33368 +Epoch: [7] [1130/1319] eta: 0:08:15 lr: 4.106653789334745e-05 loss: 0.1097 (0.1052) time: 2.6221 data: 0.0060 max mem: 33368 +Epoch: [7] [1140/1319] eta: 0:07:49 lr: 4.105782001429505e-05 loss: 0.1060 (0.1054) time: 2.6327 data: 0.0061 max mem: 33368 +Epoch: [7] [1150/1319] eta: 0:07:23 lr: 4.104910192956196e-05 loss: 0.1054 (0.1055) time: 2.6180 data: 0.0063 max mem: 33368 +Epoch: [7] [1160/1319] eta: 0:06:56 lr: 4.104038363909479e-05 loss: 0.0864 (0.1053) time: 2.6281 data: 0.0063 max mem: 33368 +Epoch: [7] [1170/1319] eta: 0:06:30 lr: 4.1031665142840106e-05 loss: 0.0890 (0.1053) time: 2.6414 data: 0.0062 max mem: 33368 +Epoch: [7] [1180/1319] eta: 0:06:04 lr: 4.1022946440744476e-05 loss: 0.0961 (0.1054) time: 2.6447 data: 0.0063 max mem: 33368 +Epoch: [7] [1190/1319] eta: 0:05:38 lr: 4.1014227532754415e-05 loss: 0.0961 (0.1053) time: 2.6256 data: 0.0063 max mem: 33368 +Epoch: [7] [1200/1319] eta: 0:05:12 lr: 4.100550841881645e-05 loss: 0.1006 (0.1054) time: 2.6155 data: 0.0062 max mem: 33368 +Epoch: [7] [1210/1319] eta: 0:04:45 lr: 4.099678909887704e-05 loss: 0.0933 (0.1053) time: 2.6187 data: 0.0063 max mem: 33368 +Epoch: [7] [1220/1319] eta: 0:04:19 lr: 4.098806957288263e-05 loss: 0.0930 (0.1053) time: 2.6268 data: 0.0063 max mem: 33368 +Epoch: [7] [1230/1319] eta: 0:03:53 lr: 4.0979349840779665e-05 loss: 0.0875 (0.1050) time: 2.6646 data: 0.0064 max mem: 33368 +Epoch: [7] [1240/1319] eta: 0:03:27 lr: 4.0970629902514516e-05 loss: 0.0861 (0.1051) time: 2.6666 data: 0.0065 max mem: 33368 +Epoch: [7] [1250/1319] eta: 0:03:00 lr: 4.0961909758033565e-05 loss: 0.0861 (0.1049) time: 2.6368 data: 0.0063 max mem: 33368 +Epoch: [7] [1260/1319] eta: 0:02:34 lr: 4.095318940728316e-05 loss: 0.0915 (0.1048) time: 2.6226 data: 0.0061 max mem: 33368 +Epoch: [7] [1270/1319] eta: 0:02:08 lr: 4.0944468850209605e-05 loss: 0.0915 (0.1047) time: 2.6200 data: 0.0062 max mem: 33368 +Epoch: [7] [1280/1319] eta: 0:01:42 lr: 4.093574808675919e-05 loss: 0.0901 (0.1047) time: 2.6117 data: 0.0063 max mem: 33368 +Epoch: [7] [1290/1319] eta: 0:01:16 lr: 4.09270271168782e-05 loss: 0.1024 (0.1048) time: 2.6129 data: 0.0063 max mem: 33368 +Epoch: [7] [1300/1319] eta: 0:00:49 lr: 4.091830594051285e-05 loss: 0.0956 (0.1049) time: 2.5839 data: 0.0062 max mem: 33368 +Epoch: [7] [1310/1319] eta: 0:00:23 lr: 4.090958455760934e-05 loss: 0.0929 (0.1049) time: 2.5450 data: 0.0061 max mem: 33368 +Epoch: [7] Total time: 0:57:38 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 2:26:40 time: 3.4204 data: 3.3350 max mem: 33368 +Test: [ 100/2573] eta: 0:04:19 time: 0.0713 data: 0.0011 max mem: 33368 +Test: [ 200/2573] eta: 0:03:32 time: 0.0728 data: 0.0011 max mem: 33368 +Test: [ 300/2573] eta: 0:03:09 time: 0.0745 data: 0.0011 max mem: 33368 +Test: [ 400/2573] eta: 0:02:55 time: 0.0745 data: 0.0011 max mem: 33368 +Test: [ 500/2573] eta: 0:02:44 time: 0.0731 data: 0.0011 max mem: 33368 +Test: [ 600/2573] eta: 0:02:34 time: 0.0732 data: 0.0011 max mem: 33368 +Test: [ 700/2573] eta: 0:02:26 time: 0.0732 data: 0.0011 max mem: 33368 +Test: [ 800/2573] eta: 0:02:17 time: 0.0766 data: 0.0011 max mem: 33368 +Test: [ 900/2573] eta: 0:02:09 time: 0.0735 data: 0.0011 max mem: 33368 +Test: [1000/2573] eta: 0:02:00 time: 0.0734 data: 0.0011 max mem: 33368 +Test: [1100/2573] eta: 0:01:52 time: 0.0734 data: 0.0011 max mem: 33368 +Test: [1200/2573] eta: 0:01:44 time: 0.0734 data: 0.0011 max mem: 33368 +Test: [1300/2573] eta: 0:01:36 time: 0.0735 data: 0.0011 max mem: 33368 +Test: [1400/2573] eta: 0:01:28 time: 0.0718 data: 0.0011 max mem: 33368 +Test: [1500/2573] eta: 0:01:21 time: 0.0736 data: 0.0011 max mem: 33368 +Test: [1600/2573] eta: 0:01:13 time: 0.0769 data: 0.0011 max mem: 33368 +Test: [1700/2573] eta: 0:01:05 time: 0.0720 data: 0.0011 max mem: 33368 +Test: [1800/2573] eta: 0:00:58 time: 0.0753 data: 0.0011 max mem: 33368 +Test: [1900/2573] eta: 0:00:50 time: 0.0719 data: 0.0011 max mem: 33368 +Test: [2000/2573] eta: 0:00:43 time: 0.0736 data: 0.0011 max mem: 33368 +Test: [2100/2573] eta: 0:00:35 time: 0.0753 data: 0.0011 max mem: 33368 +Test: [2200/2573] eta: 0:00:27 time: 0.0752 data: 0.0011 max mem: 33368 +Test: [2300/2573] eta: 0:00:20 time: 0.0753 data: 0.0011 max mem: 33368 +Test: [2400/2573] eta: 0:00:12 time: 0.0703 data: 0.0011 max mem: 33368 +Test: [2500/2573] eta: 0:00:05 time: 0.0736 data: 0.0011 max mem: 33368 +Test: Total time: 0:03:12 +Final results: +Mean IoU is 59.63 + + precision@0.5 = 66.58 + precision@0.6 = 59.72 + precision@0.7 = 51.80 + precision@0.8 = 39.42 + precision@0.9 = 17.50 + overall IoU = 58.62 + +Average object IoU 59.63069466356238 +Overall IoU 58.61586380004883 +Better epoch: 7 + +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [8] [ 0/1319] eta: 1:25:21 lr: 4.09017351363616e-05 loss: 0.0800 (0.0800) time: 3.8826 data: 1.1887 max mem: 33368 +Epoch: [8] [ 10/1319] eta: 0:59:21 lr: 4.089301336088734e-05 loss: 0.0795 (0.0877) time: 2.7210 data: 0.1134 max mem: 33368 +Epoch: [8] [ 20/1319] eta: 0:58:00 lr: 4.088429137871879e-05 loss: 0.0795 (0.0870) time: 2.6191 data: 0.0056 max mem: 33368 +Epoch: [8] [ 30/1319] eta: 0:57:02 lr: 4.087556918980205e-05 loss: 0.0962 (0.0911) time: 2.6194 data: 0.0058 max mem: 33368 +Epoch: [8] [ 40/1319] eta: 0:56:16 lr: 4.0866846794083216e-05 loss: 0.0787 (0.0858) time: 2.5992 data: 0.0062 max mem: 33368 +Epoch: [8] [ 50/1319] eta: 0:55:39 lr: 4.0858124191508315e-05 loss: 0.0752 (0.0837) time: 2.5942 data: 0.0061 max mem: 33368 +Epoch: [8] [ 60/1319] eta: 0:55:07 lr: 4.08494013820234e-05 loss: 0.0815 (0.0878) time: 2.5994 data: 0.0061 max mem: 33368 +Epoch: [8] [ 70/1319] eta: 0:54:40 lr: 4.0840678365574436e-05 loss: 0.0958 (0.0906) time: 2.6127 data: 0.0061 max mem: 33368 +Epoch: [8] [ 80/1319] eta: 0:54:10 lr: 4.083195514210742e-05 loss: 0.0817 (0.0897) time: 2.6130 data: 0.0063 max mem: 33368 +Epoch: [8] [ 90/1319] eta: 0:53:48 lr: 4.0823231711568287e-05 loss: 0.0708 (0.0887) time: 2.6289 data: 0.0062 max mem: 33368 +Epoch: [8] [ 100/1319] eta: 0:53:20 lr: 4.081450807390295e-05 loss: 0.0899 (0.0917) time: 2.6333 data: 0.0059 max mem: 33368 +Epoch: [8] [ 110/1319] eta: 0:52:51 lr: 4.0805784229057304e-05 loss: 0.0985 (0.0913) time: 2.6093 data: 0.0060 max mem: 33368 +Epoch: [8] [ 120/1319] eta: 0:52:23 lr: 4.079706017697721e-05 loss: 0.0932 (0.0918) time: 2.6044 data: 0.0060 max mem: 33368 +Epoch: [8] [ 130/1319] eta: 0:52:00 lr: 4.0788335917608504e-05 loss: 0.0883 (0.0917) time: 2.6313 data: 0.0060 max mem: 33368 +Epoch: [8] [ 140/1319] eta: 0:51:36 lr: 4.077961145089699e-05 loss: 0.0815 (0.0913) time: 2.6536 data: 0.0061 max mem: 33368 +Epoch: [8] [ 150/1319] eta: 0:51:10 lr: 4.0770886776788466e-05 loss: 0.0755 (0.0914) time: 2.6361 data: 0.0060 max mem: 33368 +Epoch: [8] [ 160/1319] eta: 0:50:44 lr: 4.076216189522867e-05 loss: 0.0957 (0.0927) time: 2.6270 data: 0.0060 max mem: 33368 +Epoch: [8] [ 170/1319] eta: 0:50:20 lr: 4.075343680616333e-05 loss: 0.0819 (0.0919) time: 2.6516 data: 0.0061 max mem: 33368 +Epoch: [8] [ 180/1319] eta: 0:49:53 lr: 4.074471150953815e-05 loss: 0.0803 (0.0916) time: 2.6386 data: 0.0061 max mem: 33368 +Epoch: [8] [ 190/1319] eta: 0:49:25 lr: 4.0735986005298814e-05 loss: 0.0828 (0.0916) time: 2.6046 data: 0.0061 max mem: 33368 +Epoch: [8] [ 200/1319] eta: 0:48:59 lr: 4.072726029339096e-05 loss: 0.0798 (0.0912) time: 2.6161 data: 0.0062 max mem: 33368 +Epoch: [8] [ 210/1319] eta: 0:48:33 lr: 4.07185343737602e-05 loss: 0.0746 (0.0921) time: 2.6358 data: 0.0063 max mem: 33368 +Epoch: [8] [ 220/1319] eta: 0:48:07 lr: 4.070980824635213e-05 loss: 0.0750 (0.0923) time: 2.6336 data: 0.0063 max mem: 33368 +Epoch: [8] [ 230/1319] eta: 0:47:41 lr: 4.070108191111232e-05 loss: 0.0864 (0.0924) time: 2.6245 data: 0.0061 max mem: 33368 +Epoch: [8] [ 240/1319] eta: 0:47:14 lr: 4.069235536798631e-05 loss: 0.0829 (0.0920) time: 2.6186 data: 0.0062 max mem: 33368 +Epoch: [8] [ 250/1319] eta: 0:46:47 lr: 4.0683628616919596e-05 loss: 0.0734 (0.0911) time: 2.6200 data: 0.0061 max mem: 33368 +Epoch: [8] [ 260/1319] eta: 0:46:21 lr: 4.0674901657857675e-05 loss: 0.0734 (0.0906) time: 2.6284 data: 0.0061 max mem: 33368 +Epoch: [8] [ 270/1319] eta: 0:45:54 lr: 4.066617449074599e-05 loss: 0.0758 (0.0908) time: 2.6171 data: 0.0061 max mem: 33368 +Epoch: [8] [ 280/1319] eta: 0:45:27 lr: 4.065744711552997e-05 loss: 0.0859 (0.0914) time: 2.6008 data: 0.0061 max mem: 33368 +Epoch: [8] [ 290/1319] eta: 0:45:00 lr: 4.064871953215503e-05 loss: 0.0869 (0.0916) time: 2.6071 data: 0.0062 max mem: 33368 +Epoch: [8] [ 300/1319] eta: 0:44:33 lr: 4.063999174056654e-05 loss: 0.0895 (0.0921) time: 2.6021 data: 0.0061 max mem: 33368 +Epoch: [8] [ 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loss: 0.0806 (0.0937) time: 2.6212 data: 0.0063 max mem: 33368 +Epoch: [8] [ 790/1319] eta: 0:23:06 lr: 4.021207374606688e-05 loss: 0.0880 (0.0937) time: 2.6111 data: 0.0062 max mem: 33368 +Epoch: [8] [ 800/1319] eta: 0:22:39 lr: 4.0203335473541464e-05 loss: 0.0749 (0.0935) time: 2.6051 data: 0.0060 max mem: 33368 +Epoch: [8] [ 810/1319] eta: 0:22:13 lr: 4.01945969899798e-05 loss: 0.0773 (0.0935) time: 2.6251 data: 0.0060 max mem: 33368 +Epoch: [8] [ 820/1319] eta: 0:21:47 lr: 4.0185858295325805e-05 loss: 0.0836 (0.0936) time: 2.6381 data: 0.0061 max mem: 33368 +Epoch: [8] [ 830/1319] eta: 0:21:21 lr: 4.017711938952337e-05 loss: 0.0900 (0.0937) time: 2.6243 data: 0.0061 max mem: 33368 +Epoch: [8] [ 840/1319] eta: 0:20:54 lr: 4.0168380272516376e-05 loss: 0.1022 (0.0941) time: 2.5885 data: 0.0060 max mem: 33368 +Epoch: [8] [ 850/1319] eta: 0:20:28 lr: 4.0159640944248643e-05 loss: 0.0940 (0.0941) time: 2.5917 data: 0.0060 max mem: 33368 +Epoch: [8] [ 860/1319] eta: 0:20:02 lr: 4.0150901404663985e-05 loss: 0.0897 (0.0941) time: 2.6319 data: 0.0060 max mem: 33368 +Epoch: [8] [ 870/1319] eta: 0:19:36 lr: 4.0142161653706185e-05 loss: 0.0915 (0.0944) time: 2.6291 data: 0.0062 max mem: 33368 +Epoch: [8] [ 880/1319] eta: 0:19:10 lr: 4.013342169131899e-05 loss: 0.0991 (0.0945) time: 2.6447 data: 0.0062 max mem: 33368 +Epoch: [8] [ 890/1319] eta: 0:18:44 lr: 4.012468151744613e-05 loss: 0.0836 (0.0946) time: 2.6316 data: 0.0061 max mem: 33368 +Epoch: [8] [ 900/1319] eta: 0:18:17 lr: 4.01159411320313e-05 loss: 0.0842 (0.0947) time: 2.6055 data: 0.0061 max mem: 33368 +Epoch: [8] [ 910/1319] eta: 0:17:51 lr: 4.010720053501816e-05 loss: 0.0963 (0.0948) time: 2.6132 data: 0.0060 max mem: 33368 +Epoch: [8] [ 920/1319] eta: 0:17:25 lr: 4.009845972635034e-05 loss: 0.0753 (0.0947) time: 2.6046 data: 0.0062 max mem: 33368 +Epoch: [8] [ 930/1319] eta: 0:16:59 lr: 4.008971870597147e-05 loss: 0.0697 (0.0945) time: 2.6110 data: 0.0062 max mem: 33368 +Epoch: [8] [ 940/1319] eta: 0:16:32 lr: 4.008097747382511e-05 loss: 0.0734 (0.0947) time: 2.6137 data: 0.0062 max mem: 33368 +Epoch: [8] [ 950/1319] eta: 0:16:06 lr: 4.0072236029854826e-05 loss: 0.0967 (0.0947) time: 2.6038 data: 0.0061 max mem: 33368 +Epoch: [8] [ 960/1319] eta: 0:15:40 lr: 4.006349437400413e-05 loss: 0.0840 (0.0947) time: 2.6294 data: 0.0062 max mem: 33368 +Epoch: [8] [ 970/1319] eta: 0:15:14 lr: 4.005475250621652e-05 loss: 0.0738 (0.0947) time: 2.6341 data: 0.0062 max mem: 33368 +Epoch: [8] [ 980/1319] eta: 0:14:48 lr: 4.004601042643546e-05 loss: 0.0877 (0.0948) time: 2.6076 data: 0.0062 max mem: 33368 +Epoch: [8] [ 990/1319] eta: 0:14:21 lr: 4.003726813460439e-05 loss: 0.0943 (0.0949) time: 2.6098 data: 0.0062 max mem: 33368 +Epoch: [8] [1000/1319] eta: 0:13:55 lr: 4.0028525630666715e-05 loss: 0.0943 (0.0950) time: 2.6378 data: 0.0064 max mem: 33368 +Epoch: [8] [1010/1319] eta: 0:13:29 lr: 4.00197829145658e-05 loss: 0.0944 (0.0951) time: 2.6408 data: 0.0064 max mem: 33368 +Epoch: [8] 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+Epoch: [8] [1100/1319] eta: 0:09:33 lr: 3.994108891295557e-05 loss: 0.0857 (0.0951) time: 2.6048 data: 0.0064 max mem: 33368 +Epoch: [8] [1110/1319] eta: 0:09:07 lr: 3.9932344072101854e-05 loss: 0.0841 (0.0952) time: 2.6148 data: 0.0065 max mem: 33368 +Epoch: [8] [1120/1319] eta: 0:08:41 lr: 3.9923599018460164e-05 loss: 0.0909 (0.0953) time: 2.6332 data: 0.0067 max mem: 33368 +Epoch: [8] [1130/1319] eta: 0:08:15 lr: 3.991485375197353e-05 loss: 0.0961 (0.0953) time: 2.6276 data: 0.0069 max mem: 33368 +Epoch: [8] [1140/1319] eta: 0:07:48 lr: 3.990610827258495e-05 loss: 0.0961 (0.0953) time: 2.6290 data: 0.0068 max mem: 33368 +Epoch: [8] [1150/1319] eta: 0:07:22 lr: 3.9897362580237394e-05 loss: 0.0772 (0.0953) time: 2.6535 data: 0.0067 max mem: 33368 +Epoch: [8] [1160/1319] eta: 0:06:56 lr: 3.988861667487383e-05 loss: 0.0809 (0.0953) time: 2.6407 data: 0.0069 max mem: 33368 +Epoch: [8] [1170/1319] eta: 0:06:30 lr: 3.987987055643715e-05 loss: 0.0848 (0.0953) time: 2.6271 data: 0.0069 max mem: 33368 +Epoch: [8] [1180/1319] eta: 0:06:04 lr: 3.9871124224870237e-05 loss: 0.0900 (0.0953) time: 2.6173 data: 0.0068 max mem: 33368 +Epoch: [8] [1190/1319] eta: 0:05:37 lr: 3.986237768011596e-05 loss: 0.0938 (0.0953) time: 2.6127 data: 0.0068 max mem: 33368 +Epoch: [8] [1200/1319] eta: 0:05:11 lr: 3.985363092211714e-05 loss: 0.0933 (0.0955) time: 2.6228 data: 0.0066 max mem: 33368 +Epoch: [8] [1210/1319] eta: 0:04:45 lr: 3.984488395081657e-05 loss: 0.0934 (0.0956) time: 2.6072 data: 0.0066 max mem: 33368 +Epoch: [8] [1220/1319] eta: 0:04:19 lr: 3.9836136766157016e-05 loss: 0.0978 (0.0956) time: 2.5982 data: 0.0066 max mem: 33368 +Epoch: [8] [1230/1319] eta: 0:03:53 lr: 3.9827389368081224e-05 loss: 0.0894 (0.0955) time: 2.6015 data: 0.0067 max mem: 33368 +Epoch: [8] [1240/1319] eta: 0:03:26 lr: 3.9818641756531906e-05 loss: 0.0858 (0.0955) time: 2.6184 data: 0.0069 max mem: 33368 +Epoch: [8] [1250/1319] eta: 0:03:00 lr: 3.980989393145173e-05 loss: 0.0858 (0.0956) time: 2.6299 data: 0.0070 max mem: 33368 +Epoch: [8] [1260/1319] eta: 0:02:34 lr: 3.9801145892783356e-05 loss: 0.0868 (0.0956) time: 2.6419 data: 0.0068 max mem: 33368 +Epoch: [8] [1270/1319] eta: 0:02:08 lr: 3.97923976404694e-05 loss: 0.0868 (0.0956) time: 2.6289 data: 0.0070 max mem: 33368 +Epoch: [8] [1280/1319] eta: 0:01:42 lr: 3.978364917445246e-05 loss: 0.0783 (0.0955) time: 2.6000 data: 0.0070 max mem: 33368 +Epoch: [8] [1290/1319] eta: 0:01:15 lr: 3.9774900494675086e-05 loss: 0.0723 (0.0955) time: 2.6154 data: 0.0068 max mem: 33368 +Epoch: [8] [1300/1319] eta: 0:00:49 lr: 3.976615160107982e-05 loss: 0.0867 (0.0956) time: 2.6167 data: 0.0069 max mem: 33368 +Epoch: [8] [1310/1319] eta: 0:00:23 lr: 3.975740249360917e-05 loss: 0.0883 (0.0955) time: 2.6118 data: 0.0068 max mem: 33368 +Epoch: [8] Total time: 0:57:35 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 2:05:06 time: 2.9175 data: 2.8384 max mem: 33368 +Test: [ 100/2573] eta: 0:04:06 time: 0.0712 data: 0.0011 max mem: 33368 +Test: [ 200/2573] eta: 0:03:26 time: 0.0731 data: 0.0011 max mem: 33368 +Test: [ 300/2573] eta: 0:03:06 time: 0.0749 data: 0.0011 max mem: 33368 +Test: [ 400/2573] eta: 0:02:53 time: 0.0749 data: 0.0011 max mem: 33368 +Test: [ 500/2573] eta: 0:02:42 time: 0.0734 data: 0.0011 max mem: 33368 +Test: [ 600/2573] eta: 0:02:33 time: 0.0735 data: 0.0011 max mem: 33368 +Test: [ 700/2573] eta: 0:02:24 time: 0.0734 data: 0.0011 max mem: 33368 +Test: [ 800/2573] eta: 0:02:16 time: 0.0767 data: 0.0011 max mem: 33368 +Test: [ 900/2573] eta: 0:02:08 time: 0.0734 data: 0.0011 max mem: 33368 +Test: [1000/2573] eta: 0:02:00 time: 0.0734 data: 0.0011 max mem: 33368 +Test: [1100/2573] eta: 0:01:52 time: 0.0735 data: 0.0011 max mem: 33368 +Test: [1200/2573] eta: 0:01:44 time: 0.0735 data: 0.0011 max mem: 33368 +Test: [1300/2573] eta: 0:01:36 time: 0.0736 data: 0.0011 max mem: 33368 +Test: [1400/2573] eta: 0:01:28 time: 0.0719 data: 0.0011 max mem: 33368 +Test: [1500/2573] eta: 0:01:20 time: 0.0735 data: 0.0011 max mem: 33368 +Test: [1600/2573] eta: 0:01:13 time: 0.0768 data: 0.0011 max mem: 33368 +Test: [1700/2573] eta: 0:01:05 time: 0.0719 data: 0.0011 max mem: 33368 +Test: [1800/2573] eta: 0:00:58 time: 0.0752 data: 0.0011 max mem: 33368 +Test: [1900/2573] eta: 0:00:50 time: 0.0720 data: 0.0011 max mem: 33368 +Test: [2000/2573] eta: 0:00:42 time: 0.0738 data: 0.0012 max mem: 33368 +Test: [2100/2573] eta: 0:00:35 time: 0.0754 data: 0.0011 max mem: 33368 +Test: [2200/2573] eta: 0:00:27 time: 0.0754 data: 0.0011 max mem: 33368 +Test: [2300/2573] eta: 0:00:20 time: 0.0755 data: 0.0011 max mem: 33368 +Test: [2400/2573] eta: 0:00:12 time: 0.0705 data: 0.0011 max mem: 33368 +Test: [2500/2573] eta: 0:00:05 time: 0.0739 data: 0.0011 max mem: 33368 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: Total time: 0:03:12 +Final results: +Mean IoU is 59.89 + + precision@0.5 = 67.40 + precision@0.6 = 61.19 + precision@0.7 = 52.72 + precision@0.8 = 40.62 + precision@0.9 = 18.32 + overall IoU = 58.70 + +Average object IoU 59.89070399032435 +Overall IoU 58.6960334777832 +Better epoch: 8 + +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [9] [ 0/1319] eta: 1:34:47 lr: 3.974952811397457e-05 loss: 0.0822 (0.0822) time: 4.3124 data: 1.5259 max mem: 33368 +Epoch: [9] [ 10/1319] eta: 1:00:41 lr: 3.974077859998216e-05 loss: 0.0948 (0.0963) time: 2.7818 data: 0.1436 max mem: 33368 +Epoch: [9] [ 20/1319] eta: 0:58:43 lr: 3.9732028871947454e-05 loss: 0.0834 (0.0889) time: 2.6328 data: 0.0053 max mem: 33368 +Epoch: [9] [ 30/1319] eta: 0:57:34 lr: 3.972327892981283e-05 loss: 0.0746 (0.0905) time: 2.6238 data: 0.0057 max mem: 33368 +Epoch: [9] [ 40/1319] eta: 0:56:52 lr: 3.971452877352066e-05 loss: 0.0746 (0.0878) time: 2.6218 data: 0.0061 max mem: 33368 +Epoch: [9] [ 50/1319] eta: 0:56:02 lr: 3.9705778403013264e-05 loss: 0.0772 (0.0920) time: 2.6026 data: 0.0061 max mem: 33368 +Epoch: [9] [ 60/1319] eta: 0:55:31 lr: 3.969702781823294e-05 loss: 0.0808 (0.0897) time: 2.6003 data: 0.0060 max mem: 33368 +Epoch: [9] [ 70/1319] eta: 0:55:01 lr: 3.9688277019121967e-05 loss: 0.0808 (0.0901) time: 2.6270 data: 0.0061 max mem: 33368 +Epoch: [9] [ 80/1319] eta: 0:54:31 lr: 3.967952600562257e-05 loss: 0.0759 (0.0899) time: 2.6232 data: 0.0062 max mem: 33368 +Epoch: [9] [ 90/1319] eta: 0:54:05 lr: 3.967077477767697e-05 loss: 0.0823 (0.0902) time: 2.6310 data: 0.0062 max mem: 33368 +Epoch: [9] [ 100/1319] eta: 0:53:30 lr: 3.966202333522733e-05 loss: 0.0861 (0.0904) time: 2.6072 data: 0.0060 max mem: 33368 +Epoch: [9] [ 110/1319] eta: 0:53:06 lr: 3.965327167821583e-05 loss: 0.0861 (0.0907) time: 2.6124 data: 0.0060 max mem: 33368 +Epoch: [9] [ 120/1319] eta: 0:52:36 lr: 3.9644519806584564e-05 loss: 0.0768 (0.0902) time: 2.6263 data: 0.0061 max mem: 33368 +Epoch: [9] [ 130/1319] eta: 0:52:04 lr: 3.963576772027564e-05 loss: 0.0698 (0.0893) time: 2.5876 data: 0.0061 max mem: 33368 +Epoch: [9] [ 140/1319] eta: 0:51:37 lr: 3.96270154192311e-05 loss: 0.0758 (0.0891) time: 2.5931 data: 0.0061 max mem: 33368 +Epoch: [9] [ 150/1319] eta: 0:51:11 lr: 3.9618262903393e-05 loss: 0.0769 (0.0890) time: 2.6229 data: 0.0062 max mem: 33368 +Epoch: [9] [ 160/1319] eta: 0:50:43 lr: 3.960951017270332e-05 loss: 0.0733 (0.0881) time: 2.6217 data: 0.0063 max mem: 33368 +Epoch: [9] [ 170/1319] eta: 0:50:16 lr: 3.9600757227104046e-05 loss: 0.0699 (0.0886) time: 2.6061 data: 0.0063 max mem: 33368 +Epoch: [9] [ 180/1319] eta: 0:49:49 lr: 3.95920040665371e-05 loss: 0.0848 (0.0880) time: 2.6151 data: 0.0064 max mem: 33368 +Epoch: [9] [ 190/1319] eta: 0:49:22 lr: 3.958325069094442e-05 loss: 0.0848 (0.0889) time: 2.6129 data: 0.0067 max mem: 33368 +Epoch: [9] [ 200/1319] eta: 0:48:55 lr: 3.957449710026786e-05 loss: 0.0827 (0.0894) time: 2.6100 data: 0.0065 max mem: 33368 +Epoch: [9] [ 210/1319] eta: 0:48:30 lr: 3.9565743294449283e-05 loss: 0.0827 (0.0889) time: 2.6321 data: 0.0066 max mem: 33368 +Epoch: [9] [ 220/1319] eta: 0:48:04 lr: 3.955698927343052e-05 loss: 0.0691 (0.0882) time: 2.6379 data: 0.0064 max mem: 33368 +Epoch: [9] [ 230/1319] eta: 0:47:37 lr: 3.954823503715335e-05 loss: 0.0629 (0.0873) time: 2.6137 data: 0.0063 max mem: 33368 +Epoch: [9] [ 240/1319] eta: 0:47:09 lr: 3.953948058555954e-05 loss: 0.0629 (0.0871) time: 2.5899 data: 0.0064 max mem: 33368 +Epoch: [9] [ 250/1319] eta: 0:46:42 lr: 3.9530725918590825e-05 loss: 0.0673 (0.0874) time: 2.5969 data: 0.0067 max mem: 33368 +Epoch: [9] [ 260/1319] eta: 0:46:14 lr: 3.952197103618889e-05 loss: 0.0782 (0.0872) time: 2.5968 data: 0.0067 max mem: 33368 +Epoch: [9] [ 270/1319] eta: 0:45:48 lr: 3.951321593829542e-05 loss: 0.0826 (0.0876) time: 2.6023 data: 0.0064 max mem: 33368 +Epoch: [9] [ 280/1319] eta: 0:45:22 lr: 3.9504460624852056e-05 loss: 0.0879 (0.0879) time: 2.6189 data: 0.0064 max mem: 33368 +Epoch: [9] [ 290/1319] eta: 0:44:55 lr: 3.94957050958004e-05 loss: 0.0775 (0.0873) time: 2.6064 data: 0.0064 max mem: 33368 +Epoch: [9] [ 300/1319] eta: 0:44:29 lr: 3.9486949351082035e-05 loss: 0.0803 (0.0875) time: 2.6102 data: 0.0065 max mem: 33368 +Epoch: [9] [ 310/1319] eta: 0:44:01 lr: 3.9478193390638515e-05 loss: 0.0906 (0.0877) time: 2.6073 data: 0.0065 max mem: 33368 +Epoch: [9] [ 320/1319] eta: 0:43:36 lr: 3.946943721441136e-05 loss: 0.0906 (0.0880) time: 2.6238 data: 0.0063 max mem: 33368 +Epoch: [9] [ 330/1319] eta: 0:43:10 lr: 3.946068082234206e-05 loss: 0.0736 (0.0877) time: 2.6272 data: 0.0062 max mem: 33368 +Epoch: [9] [ 340/1319] eta: 0:42:42 lr: 3.945192421437206e-05 loss: 0.0735 (0.0875) time: 2.5866 data: 0.0061 max mem: 33368 +Epoch: [9] [ 350/1319] eta: 0:42:15 lr: 3.944316739044282e-05 loss: 0.0878 (0.0874) time: 2.5863 data: 0.0062 max mem: 33368 +Epoch: [9] [ 360/1319] eta: 0:41:50 lr: 3.94344103504957e-05 loss: 0.0891 (0.0873) time: 2.6159 data: 0.0064 max mem: 33368 +Epoch: [9] [ 370/1319] eta: 0:41:24 lr: 3.94256530944721e-05 loss: 0.0677 (0.0870) time: 2.6423 data: 0.0064 max mem: 33368 +Epoch: [9] [ 380/1319] eta: 0:40:57 lr: 3.9416895622313336e-05 loss: 0.0655 (0.0866) time: 2.6101 data: 0.0065 max mem: 33368 +Epoch: [9] [ 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loss: 0.0870 (0.0882) time: 2.6120 data: 0.0069 max mem: 33368 +Epoch: [9] [ 870/1319] eta: 0:19:34 lr: 3.898751349103772e-05 loss: 0.0861 (0.0882) time: 2.6080 data: 0.0068 max mem: 33368 +Epoch: [9] [ 880/1319] eta: 0:19:08 lr: 3.8978745136648617e-05 loss: 0.0805 (0.0881) time: 2.6101 data: 0.0066 max mem: 33368 +Epoch: [9] [ 890/1319] eta: 0:18:42 lr: 3.896997656309173e-05 loss: 0.0804 (0.0882) time: 2.6042 data: 0.0067 max mem: 33368 +Epoch: [9] [ 900/1319] eta: 0:18:16 lr: 3.896120777030681e-05 loss: 0.0766 (0.0881) time: 2.6343 data: 0.0066 max mem: 33368 +Epoch: [9] [ 910/1319] eta: 0:17:50 lr: 3.895243875823353e-05 loss: 0.0706 (0.0880) time: 2.6520 data: 0.0068 max mem: 33368 +Epoch: [9] [ 920/1319] eta: 0:17:24 lr: 3.894366952681158e-05 loss: 0.0858 (0.0882) time: 2.6116 data: 0.0067 max mem: 33368 +Epoch: [9] [ 930/1319] eta: 0:16:58 lr: 3.8934900075980555e-05 loss: 0.0992 (0.0883) time: 2.6222 data: 0.0067 max mem: 33368 +Epoch: [9] [ 940/1319] eta: 0:16:31 lr: 3.8926130405680076e-05 loss: 0.0880 (0.0883) time: 2.6381 data: 0.0070 max mem: 33368 +Epoch: [9] [ 950/1319] eta: 0:16:05 lr: 3.8917360515849704e-05 loss: 0.0738 (0.0882) time: 2.6168 data: 0.0069 max mem: 33368 +Epoch: [9] [ 960/1319] eta: 0:15:39 lr: 3.8908590406428975e-05 loss: 0.0707 (0.0881) time: 2.6059 data: 0.0067 max mem: 33368 +Epoch: [9] [ 970/1319] eta: 0:15:13 lr: 3.889982007735738e-05 loss: 0.0738 (0.0879) time: 2.6209 data: 0.0067 max mem: 33368 +Epoch: [9] [ 980/1319] eta: 0:14:47 lr: 3.889104952857442e-05 loss: 0.0762 (0.0880) time: 2.6175 data: 0.0068 max mem: 33368 +Epoch: [9] [ 990/1319] eta: 0:14:21 lr: 3.888227876001951e-05 loss: 0.0839 (0.0881) time: 2.6157 data: 0.0067 max mem: 33368 +Epoch: [9] [1000/1319] eta: 0:13:54 lr: 3.887350777163206e-05 loss: 0.0934 (0.0882) time: 2.6281 data: 0.0067 max mem: 33368 +Epoch: [9] [1010/1319] eta: 0:13:28 lr: 3.886473656335145e-05 loss: 0.0772 (0.0882) time: 2.6171 data: 0.0069 max mem: 33368 +Epoch: [9] [1020/1319] eta: 0:13:02 lr: 3.8855965135117015e-05 loss: 0.0827 (0.0884) time: 2.6068 data: 0.0068 max mem: 33368 +Epoch: [9] [1030/1319] eta: 0:12:36 lr: 3.8847193486868084e-05 loss: 0.0859 (0.0883) time: 2.5942 data: 0.0068 max mem: 33368 +Epoch: [9] [1040/1319] eta: 0:12:10 lr: 3.883842161854392e-05 loss: 0.0640 (0.0882) time: 2.6221 data: 0.0070 max mem: 33368 +Epoch: [9] [1050/1319] eta: 0:11:43 lr: 3.8829649530083775e-05 loss: 0.0863 (0.0884) time: 2.6394 data: 0.0070 max mem: 33368 +Epoch: [9] [1060/1319] eta: 0:11:17 lr: 3.882087722142687e-05 loss: 0.0982 (0.0886) time: 2.6237 data: 0.0068 max mem: 33368 +Epoch: [9] [1070/1319] eta: 0:10:51 lr: 3.8812104692512384e-05 loss: 0.0879 (0.0887) time: 2.6327 data: 0.0067 max mem: 33368 +Epoch: [9] [1080/1319] eta: 0:10:25 lr: 3.880333194327947e-05 loss: 0.0775 (0.0885) time: 2.6385 data: 0.0069 max mem: 33368 +Epoch: [9] [1090/1319] eta: 0:09:59 lr: 3.879455897366725e-05 loss: 0.0841 (0.0886) time: 2.6289 data: 0.0068 max mem: 33368 +Epoch: [9] 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+Epoch: [9] [1180/1319] eta: 0:06:03 lr: 3.871559232002716e-05 loss: 0.0824 (0.0886) time: 2.6059 data: 0.0067 max mem: 33368 +Epoch: [9] [1190/1319] eta: 0:05:37 lr: 3.870681714326634e-05 loss: 0.0834 (0.0888) time: 2.5867 data: 0.0066 max mem: 33368 +Epoch: [9] [1200/1319] eta: 0:05:11 lr: 3.86980417454544e-05 loss: 0.0972 (0.0888) time: 2.6054 data: 0.0066 max mem: 33368 +Epoch: [9] [1210/1319] eta: 0:04:45 lr: 3.8689266126530076e-05 loss: 0.0879 (0.0889) time: 2.6319 data: 0.0067 max mem: 33368 +Epoch: [9] [1220/1319] eta: 0:04:19 lr: 3.868049028643206e-05 loss: 0.0881 (0.0889) time: 2.6097 data: 0.0068 max mem: 33368 +Epoch: [9] [1230/1319] eta: 0:03:53 lr: 3.867171422509902e-05 loss: 0.0803 (0.0889) time: 2.6101 data: 0.0067 max mem: 33368 +Epoch: [9] [1240/1319] eta: 0:03:26 lr: 3.866293794246959e-05 loss: 0.0803 (0.0890) time: 2.6444 data: 0.0066 max mem: 33368 +Epoch: [9] [1250/1319] eta: 0:03:00 lr: 3.8654161438482394e-05 loss: 0.0794 (0.0889) time: 2.6174 data: 0.0067 max mem: 33368 +Epoch: [9] [1260/1319] eta: 0:02:34 lr: 3.864538471307598e-05 loss: 0.0744 (0.0888) time: 2.6191 data: 0.0069 max mem: 33368 +Epoch: [9] [1270/1319] eta: 0:02:08 lr: 3.863660776618888e-05 loss: 0.0823 (0.0889) time: 3.2719 data: 0.0067 max mem: 33368 +Epoch: [9] [1280/1319] eta: 0:01:42 lr: 3.8627830597759606e-05 loss: 0.0883 (0.0890) time: 3.2560 data: 0.0066 max mem: 33368 +Epoch: [9] [1290/1319] eta: 0:01:16 lr: 3.861905320772664e-05 loss: 0.0990 (0.0895) time: 2.6144 data: 0.0067 max mem: 33368 +Epoch: [9] [1300/1319] eta: 0:00:49 lr: 3.861027559602841e-05 loss: 0.0843 (0.0894) time: 2.6561 data: 0.0066 max mem: 33368 +Epoch: [9] [1310/1319] eta: 0:00:23 lr: 3.860149776260333e-05 loss: 0.0779 (0.0895) time: 2.6657 data: 0.0066 max mem: 33368 +Epoch: [9] Total time: 0:57:47 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 2:05:34 time: 2.9281 data: 2.8494 max mem: 33368 +Test: [ 100/2573] eta: 0:04:07 time: 0.0716 data: 0.0011 max mem: 33368 +Test: [ 200/2573] eta: 0:03:26 time: 0.0730 data: 0.0011 max mem: 33368 +Test: [ 300/2573] eta: 0:03:06 time: 0.0747 data: 0.0011 max mem: 33368 +Test: [ 400/2573] eta: 0:02:53 time: 0.0750 data: 0.0011 max mem: 33368 +Test: [ 500/2573] eta: 0:02:42 time: 0.0732 data: 0.0011 max mem: 33368 +Test: [ 600/2573] eta: 0:02:33 time: 0.0734 data: 0.0011 max mem: 33368 +Test: [ 700/2573] eta: 0:02:24 time: 0.0734 data: 0.0011 max mem: 33368 +Test: [ 800/2573] eta: 0:02:16 time: 0.0767 data: 0.0011 max mem: 33368 +Test: [ 900/2573] eta: 0:02:08 time: 0.0734 data: 0.0011 max mem: 33368 +Test: [1000/2573] eta: 0:02:00 time: 0.0736 data: 0.0011 max mem: 33368 +Test: [1100/2573] eta: 0:01:52 time: 0.0736 data: 0.0012 max mem: 33368 +Test: [1200/2573] eta: 0:01:44 time: 0.0737 data: 0.0011 max mem: 33368 +Test: [1300/2573] eta: 0:01:36 time: 0.0737 data: 0.0011 max mem: 33368 +Test: [1400/2573] eta: 0:01:28 time: 0.0720 data: 0.0011 max mem: 33368 +Test: [1500/2573] eta: 0:01:21 time: 0.0735 data: 0.0011 max mem: 33368 +Test: [1600/2573] eta: 0:01:13 time: 0.0769 data: 0.0012 max mem: 33368 +Test: [1700/2573] eta: 0:01:05 time: 0.0719 data: 0.0011 max mem: 33368 +Test: [1800/2573] eta: 0:00:58 time: 0.0753 data: 0.0011 max mem: 33368 +Test: [1900/2573] eta: 0:00:50 time: 0.0721 data: 0.0011 max mem: 33368 +Test: [2000/2573] eta: 0:00:42 time: 0.0736 data: 0.0011 max mem: 33368 +Test: [2100/2573] eta: 0:00:35 time: 0.0752 data: 0.0011 max mem: 33368 +Test: [2200/2573] eta: 0:00:27 time: 0.0754 data: 0.0011 max mem: 33368 +Test: [2300/2573] eta: 0:00:20 time: 0.0752 data: 0.0011 max mem: 33368 +Test: [2400/2573] eta: 0:00:12 time: 0.0704 data: 0.0011 max mem: 33368 +Test: [2500/2573] eta: 0:00:05 time: 0.0737 data: 0.0011 max mem: 33368 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: Total time: 0:03:12 +Final results: +Mean IoU is 60.11 + + precision@0.5 = 67.10 + precision@0.6 = 60.78 + precision@0.7 = 52.63 + precision@0.8 = 40.44 + precision@0.9 = 18.73 + overall IoU = 58.49 + +Average object IoU 60.112386449496604 +Overall IoU 58.49296188354492 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [10] [ 0/1319] eta: 3:06:05 lr: 3.859359752289337e-05 loss: 0.1306 (0.1306) time: 8.4653 data: 1.3952 max mem: 33368 +Epoch: [10] [ 10/1319] eta: 1:09:45 lr: 3.858481926801746e-05 loss: 0.0958 (0.1007) time: 3.1978 data: 0.1327 max mem: 33368 +Epoch: [10] [ 20/1319] eta: 1:03:07 lr: 3.857604079123589e-05 loss: 0.0786 (0.0859) time: 2.6379 data: 0.0061 max mem: 33368 +Epoch: [10] [ 30/1319] eta: 1:00:32 lr: 3.856726209248695e-05 loss: 0.0711 (0.0842) time: 2.6090 data: 0.0062 max mem: 33368 +Epoch: [10] [ 40/1319] eta: 0:58:59 lr: 3.855848317170887e-05 loss: 0.0760 (0.0851) time: 2.6125 data: 0.0063 max mem: 33368 +Epoch: [10] [ 50/1319] eta: 0:57:57 lr: 3.854970402883988e-05 loss: 0.0737 (0.0822) time: 2.6206 data: 0.0062 max mem: 33368 +Epoch: [10] [ 60/1319] eta: 0:57:13 lr: 3.854092466381814e-05 loss: 0.0626 (0.0802) time: 2.6441 data: 0.0061 max mem: 33368 +Epoch: [10] [ 70/1319] eta: 0:56:28 lr: 3.853214507658182e-05 loss: 0.0718 (0.0797) time: 2.6414 data: 0.0063 max mem: 33368 +Epoch: [10] [ 80/1319] eta: 0:55:50 lr: 3.852336526706903e-05 loss: 0.0760 (0.0794) time: 2.6344 data: 0.0065 max mem: 33368 +Epoch: [10] [ 90/1319] eta: 0:55:11 lr: 3.8514585235217835e-05 loss: 0.0755 (0.0809) time: 2.6301 data: 0.0065 max mem: 33368 +Epoch: [10] [ 100/1319] eta: 0:54:38 lr: 3.850580498096631e-05 loss: 0.0755 (0.0812) time: 2.6314 data: 0.0063 max mem: 33368 +Epoch: [10] [ 110/1319] eta: 0:54:07 lr: 3.849702450425245e-05 loss: 0.0739 (0.0798) time: 2.6473 data: 0.0061 max mem: 33368 +Epoch: [10] [ 120/1319] eta: 0:53:38 lr: 3.8488243805014244e-05 loss: 0.0604 (0.0784) time: 2.6580 data: 0.0063 max mem: 33368 +Epoch: [10] [ 130/1319] eta: 0:53:07 lr: 3.8479462883189646e-05 loss: 0.0772 (0.0802) time: 2.6512 data: 0.0064 max mem: 33368 +Epoch: [10] [ 140/1319] eta: 0:52:40 lr: 3.8470681738716575e-05 loss: 0.0942 (0.0808) time: 2.6599 data: 0.0063 max mem: 33368 +Epoch: [10] [ 150/1319] eta: 0:52:05 lr: 3.846190037153291e-05 loss: 0.0847 (0.0818) time: 2.6250 data: 0.0063 max mem: 33368 +Epoch: [10] [ 160/1319] eta: 0:51:33 lr: 3.84531187815765e-05 loss: 0.0847 (0.0828) time: 2.5825 data: 0.0063 max mem: 33368 +Epoch: [10] [ 170/1319] eta: 0:51:06 lr: 3.844433696878517e-05 loss: 0.0716 (0.0826) time: 2.6342 data: 0.0063 max mem: 33368 +Epoch: [10] [ 180/1319] eta: 0:50:38 lr: 3.843555493309671e-05 loss: 0.0687 (0.0827) time: 2.6599 data: 0.0062 max mem: 33368 +Epoch: [10] [ 190/1319] eta: 0:50:10 lr: 3.842677267444885e-05 loss: 0.0859 (0.0834) time: 2.6461 data: 0.0062 max mem: 33368 +Epoch: [10] [ 200/1319] eta: 0:49:40 lr: 3.8417990192779335e-05 loss: 0.0865 (0.0839) time: 2.6203 data: 0.0062 max mem: 33368 +Epoch: [10] [ 210/1319] eta: 0:49:09 lr: 3.8409207488025836e-05 loss: 0.0865 (0.0846) time: 2.5978 data: 0.0061 max mem: 33368 +Epoch: [10] [ 220/1319] eta: 0:48:42 lr: 3.8400424560126e-05 loss: 0.0842 (0.0844) time: 2.6183 data: 0.0061 max mem: 33368 +Epoch: [10] [ 230/1319] eta: 0:48:12 lr: 3.839164140901745e-05 loss: 0.0731 (0.0842) time: 2.6210 data: 0.0063 max mem: 33368 +Epoch: [10] [ 240/1319] eta: 0:47:44 lr: 3.838285803463778e-05 loss: 0.0731 (0.0840) time: 2.6025 data: 0.0063 max mem: 33368 +Epoch: [10] [ 250/1319] eta: 0:47:17 lr: 3.8374074436924536e-05 loss: 0.0785 (0.0840) time: 2.6344 data: 0.0064 max mem: 33368 +Epoch: [10] [ 260/1319] eta: 0:46:50 lr: 3.836529061581523e-05 loss: 0.0682 (0.0839) time: 2.6450 data: 0.0066 max mem: 33368 +Epoch: [10] [ 270/1319] eta: 0:46:22 lr: 3.8356506571247355e-05 loss: 0.0789 (0.0848) time: 2.6208 data: 0.0063 max mem: 33368 +Epoch: [10] [ 280/1319] eta: 0:45:54 lr: 3.834772230315837e-05 loss: 0.0794 (0.0846) time: 2.6153 data: 0.0062 max mem: 33368 +Epoch: [10] [ 290/1319] eta: 0:45:26 lr: 3.833893781148568e-05 loss: 0.0716 (0.0844) time: 2.6142 data: 0.0063 max mem: 33368 +Epoch: [10] [ 300/1319] eta: 0:44:59 lr: 3.833015309616668e-05 loss: 0.0720 (0.0849) time: 2.6259 data: 0.0062 max mem: 33368 +Epoch: [10] [ 310/1319] eta: 0:44:32 lr: 3.832136815713871e-05 loss: 0.0810 (0.0847) time: 2.6400 data: 0.0061 max mem: 33368 +Epoch: [10] [ 320/1319] eta: 0:44:05 lr: 3.83125829943391e-05 loss: 0.0757 (0.0845) time: 2.6351 data: 0.0061 max mem: 33368 +Epoch: [10] [ 330/1319] eta: 0:43:39 lr: 3.830379760770512e-05 loss: 0.0754 (0.0841) time: 2.6452 data: 0.0062 max mem: 33368 +Epoch: [10] [ 340/1319] eta: 0:43:13 lr: 3.829501199717404e-05 loss: 0.0666 (0.0848) time: 2.6593 data: 0.0061 max mem: 33368 +Epoch: [10] [ 350/1319] eta: 0:42:46 lr: 3.828622616268306e-05 loss: 0.0692 (0.0847) time: 2.6504 data: 0.0061 max mem: 33368 +Epoch: [10] [ 360/1319] eta: 0:42:19 lr: 3.8277440104169376e-05 loss: 0.0702 (0.0846) time: 2.6374 data: 0.0063 max mem: 33368 +Epoch: [10] [ 370/1319] eta: 0:41:52 lr: 3.826865382157014e-05 loss: 0.0728 (0.0845) time: 2.6255 data: 0.0062 max mem: 33368 +Epoch: [10] [ 380/1319] eta: 0:41:26 lr: 3.8259867314822454e-05 loss: 0.0682 (0.0842) time: 2.6327 data: 0.0060 max 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+/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 2:30:38 time: 3.5127 data: 3.4338 max mem: 33368 +Test: [ 100/2573] eta: 0:04:21 time: 0.0712 data: 0.0011 max mem: 33368 +Test: [ 200/2573] eta: 0:03:33 time: 0.0730 data: 0.0011 max mem: 33368 +Test: [ 300/2573] eta: 0:03:10 time: 0.0747 data: 0.0011 max mem: 33368 +Test: [ 400/2573] eta: 0:02:56 time: 0.0747 data: 0.0011 max mem: 33368 +Test: [ 500/2573] eta: 0:02:44 time: 0.0732 data: 0.0011 max mem: 33368 +Test: [ 600/2573] eta: 0:02:34 time: 0.0733 data: 0.0011 max mem: 33368 +Test: [ 700/2573] eta: 0:02:26 time: 0.0734 data: 0.0011 max mem: 33368 +Test: [ 800/2573] eta: 0:02:17 time: 0.0766 data: 0.0011 max mem: 33368 +Test: [ 900/2573] eta: 0:02:09 time: 0.0733 data: 0.0011 max mem: 33368 +Test: [1000/2573] eta: 0:02:00 time: 0.0734 data: 0.0011 max mem: 33368 +Test: [1100/2573] eta: 0:01:52 time: 0.0734 data: 0.0011 max mem: 33368 +Test: [1200/2573] eta: 0:01:44 time: 0.0736 data: 0.0011 max mem: 33368 +Test: [1300/2573] eta: 0:01:37 time: 0.0734 data: 0.0011 max mem: 33368 +Test: [1400/2573] eta: 0:01:29 time: 0.0718 data: 0.0011 max mem: 33368 +Test: [1500/2573] eta: 0:01:21 time: 0.0736 data: 0.0011 max mem: 33368 +Test: [1600/2573] eta: 0:01:13 time: 0.0769 data: 0.0011 max mem: 33368 +Test: [1700/2573] eta: 0:01:06 time: 0.0719 data: 0.0011 max mem: 33368 +Test: [1800/2573] eta: 0:00:58 time: 0.0752 data: 0.0011 max mem: 33368 +Test: [1900/2573] eta: 0:00:50 time: 0.0720 data: 0.0011 max mem: 33368 +Test: [2000/2573] eta: 0:00:43 time: 0.0736 data: 0.0011 max mem: 33368 +Test: [2100/2573] eta: 0:00:35 time: 0.0754 data: 0.0011 max mem: 33368 +Test: [2200/2573] eta: 0:00:27 time: 0.0754 data: 0.0011 max mem: 33368 +Test: [2300/2573] eta: 0:00:20 time: 0.0754 data: 0.0011 max mem: 33368 +Test: [2400/2573] eta: 0:00:12 time: 0.0706 data: 0.0011 max mem: 33368 +Test: [2500/2573] eta: 0:00:05 time: 0.0737 data: 0.0011 max mem: 33368 +Test: Total time: 0:03:13 +Final results: +Mean IoU is 61.28 + + precision@0.5 = 68.46 + precision@0.6 = 62.28 + precision@0.7 = 53.92 + precision@0.8 = 42.38 + precision@0.9 = 19.73 + overall IoU = 58.94 + +Average object IoU 61.28032869399799 +Overall IoU 58.94077682495117 +Better epoch: 10 + +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [11] [ 0/1319] eta: 1:30:13 lr: 3.743380655104104e-05 loss: 0.0737 (0.0737) time: 4.1043 data: 1.3360 max mem: 33368 +Epoch: [11] [ 10/1319] eta: 1:01:50 lr: 3.742499848141075e-05 loss: 0.0686 (0.0699) time: 2.8350 data: 0.1272 max mem: 33368 +Epoch: [11] [ 20/1319] eta: 0:59:20 lr: 3.741619018144089e-05 loss: 0.0711 (0.0771) time: 2.6724 data: 0.0057 max mem: 33368 +Epoch: [11] [ 30/1319] eta: 0:58:17 lr: 3.7407381651065185e-05 loss: 0.0793 (0.0766) time: 2.6470 data: 0.0056 max mem: 33368 +Epoch: [11] [ 40/1319] eta: 0:57:23 lr: 3.739857289021734e-05 loss: 0.0793 (0.0795) time: 2.6421 data: 0.0060 max mem: 33368 +Epoch: [11] [ 50/1319] eta: 0:56:53 lr: 3.738976389883098e-05 loss: 0.0743 (0.0789) time: 2.6523 data: 0.0060 max mem: 33368 +Epoch: [11] [ 60/1319] eta: 0:56:19 lr: 3.738095467683973e-05 loss: 0.0696 (0.0787) time: 2.6681 data: 0.0063 max mem: 33368 +Epoch: [11] [ 70/1319] eta: 0:55:39 lr: 3.737214522417717e-05 loss: 0.0660 (0.0784) time: 2.6342 data: 0.0062 max mem: 33368 +Epoch: [11] [ 80/1319] eta: 0:55:07 lr: 3.736333554077684e-05 loss: 0.0743 (0.0779) time: 2.6225 data: 0.0061 max mem: 33368 +Epoch: [11] [ 90/1319] eta: 0:54:39 lr: 3.735452562657224e-05 loss: 0.0806 (0.0806) time: 2.6493 data: 0.0061 max mem: 33368 +Epoch: [11] [ 100/1319] eta: 0:54:07 lr: 3.734571548149683e-05 loss: 0.0790 (0.0815) time: 2.6427 data: 0.0061 max mem: 33368 +Epoch: [11] [ 110/1319] eta: 0:53:36 lr: 3.733690510548406e-05 loss: 0.0700 (0.0807) time: 2.6218 data: 0.0062 max mem: 33368 +Epoch: [11] [ 120/1319] eta: 0:53:08 lr: 3.732809449846732e-05 loss: 0.0605 (0.0807) time: 2.6339 data: 0.0064 max mem: 33368 +Epoch: [11] [ 130/1319] eta: 0:52:37 lr: 3.7319283660379954e-05 loss: 0.0605 (0.0792) time: 2.6301 data: 0.0064 max mem: 33368 +Epoch: [11] [ 140/1319] eta: 0:52:05 lr: 3.7310472591155297e-05 loss: 0.0681 (0.0796) time: 2.6033 data: 0.0062 max mem: 33368 +Epoch: [11] [ 150/1319] eta: 0:51:35 lr: 3.7301661290726626e-05 loss: 0.0729 (0.0794) time: 2.5964 data: 0.0062 max mem: 33368 +Epoch: [11] [ 160/1319] eta: 0:51:04 lr: 3.729284975902719e-05 loss: 0.0878 (0.0821) time: 2.5950 data: 0.0060 max mem: 33368 +Epoch: [11] [ 170/1319] eta: 0:50:39 lr: 3.728403799599019e-05 loss: 0.0872 (0.0823) time: 2.6282 data: 0.0060 max mem: 33368 +Epoch: [11] [ 180/1319] eta: 0:50:11 lr: 3.727522600154881e-05 loss: 0.0726 (0.0822) time: 2.6459 data: 0.0062 max mem: 33368 +Epoch: [11] [ 190/1319] eta: 0:49:45 lr: 3.7266413775636196e-05 loss: 0.0789 (0.0825) time: 2.6389 data: 0.0062 max mem: 33368 +Epoch: [11] [ 200/1319] eta: 0:49:17 lr: 3.725760131818543e-05 loss: 0.0661 (0.0816) time: 2.6316 data: 0.0062 max mem: 33368 +Epoch: [11] [ 210/1319] eta: 0:48:46 lr: 3.724878862912958e-05 loss: 0.0665 (0.0823) time: 2.5855 data: 0.0061 max mem: 33368 +Epoch: [11] [ 220/1319] eta: 0:48:18 lr: 3.723997570840168e-05 loss: 0.0746 (0.0817) time: 2.5772 data: 0.0060 max mem: 33368 +Epoch: [11] [ 230/1319] eta: 0:47:52 lr: 3.723116255593471e-05 loss: 0.0615 (0.0812) time: 2.6184 data: 0.0061 max mem: 33368 +Epoch: [11] [ 240/1319] eta: 0:47:25 lr: 3.7222349171661633e-05 loss: 0.0741 (0.0820) time: 2.6375 data: 0.0061 max mem: 33368 +Epoch: [11] [ 250/1319] eta: 0:46:58 lr: 3.721353555551535e-05 loss: 0.0808 (0.0817) time: 2.6271 data: 0.0061 max mem: 33368 +Epoch: [11] [ 260/1319] eta: 0:46:32 lr: 3.720472170742875e-05 loss: 0.0698 (0.0821) time: 2.6331 data: 0.0061 max mem: 33368 +Epoch: [11] [ 270/1319] eta: 0:46:03 lr: 3.719590762733466e-05 loss: 0.0769 (0.0817) time: 2.6136 data: 0.0063 max mem: 33368 +Epoch: [11] [ 280/1319] eta: 0:45:37 lr: 3.718709331516589e-05 loss: 0.0706 (0.0813) time: 2.6131 data: 0.0062 max mem: 33368 +Epoch: [11] [ 290/1319] eta: 0:45:11 lr: 3.7178278770855225e-05 loss: 0.0648 (0.0811) time: 2.6371 data: 0.0061 max mem: 33368 +Epoch: [11] [ 300/1319] eta: 0:44:45 lr: 3.716946399433537e-05 loss: 0.0691 (0.0810) time: 2.6371 data: 0.0060 max mem: 33368 +Epoch: [11] [ 310/1319] eta: 0:44:17 lr: 3.716064898553902e-05 loss: 0.0686 (0.0806) time: 2.6186 data: 0.0059 max mem: 33368 +Epoch: [11] [ 320/1319] eta: 0:43:50 lr: 3.715183374439884e-05 loss: 0.0736 (0.0806) time: 2.6028 data: 0.0060 max mem: 33368 +Epoch: [11] [ 330/1319] eta: 0:43:23 lr: 3.7143018270847454e-05 loss: 0.0823 (0.0805) time: 2.6016 data: 0.0061 max mem: 33368 +Epoch: [11] [ 340/1319] eta: 0:42:56 lr: 3.713420256481742e-05 loss: 0.0864 (0.0807) time: 2.5998 data: 0.0061 max mem: 33368 +Epoch: [11] [ 350/1319] eta: 0:42:27 lr: 3.712538662624129e-05 loss: 0.0757 (0.0805) time: 2.5812 data: 0.0061 max mem: 33368 +Epoch: [11] [ 360/1319] eta: 0:42:01 lr: 3.7116570455051586e-05 loss: 0.0575 (0.0802) time: 2.5987 data: 0.0060 max mem: 33368 +Epoch: [11] [ 370/1319] eta: 0:41:34 lr: 3.710775405118075e-05 loss: 0.0661 (0.0800) time: 2.6152 data: 0.0060 max mem: 33368 +Epoch: [11] [ 380/1319] eta: 0:41:07 lr: 3.709893741456123e-05 loss: 0.0650 (0.0798) time: 2.5994 data: 0.0060 max 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+/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 2:11:28 time: 3.0657 data: 2.9803 max mem: 33368 +Test: [ 100/2573] eta: 0:04:11 time: 0.0717 data: 0.0011 max mem: 33368 +Test: [ 200/2573] eta: 0:03:28 time: 0.0729 data: 0.0011 max mem: 33368 +Test: [ 300/2573] eta: 0:03:07 time: 0.0746 data: 0.0011 max mem: 33368 +Test: [ 400/2573] eta: 0:02:53 time: 0.0749 data: 0.0011 max mem: 33368 +Test: [ 500/2573] eta: 0:02:43 time: 0.0734 data: 0.0012 max mem: 33368 +Test: [ 600/2573] eta: 0:02:33 time: 0.0735 data: 0.0011 max mem: 33368 +Test: [ 700/2573] eta: 0:02:25 time: 0.0734 data: 0.0011 max mem: 33368 +Test: [ 800/2573] eta: 0:02:16 time: 0.0768 data: 0.0011 max mem: 33368 +Test: [ 900/2573] eta: 0:02:08 time: 0.0735 data: 0.0011 max mem: 33368 +Test: [1000/2573] eta: 0:02:00 time: 0.0736 data: 0.0011 max mem: 33368 +Test: [1100/2573] eta: 0:01:52 time: 0.0736 data: 0.0011 max mem: 33368 +Test: [1200/2573] eta: 0:01:44 time: 0.0736 data: 0.0011 max mem: 33368 +Test: [1300/2573] eta: 0:01:36 time: 0.0736 data: 0.0011 max mem: 33368 +Test: [1400/2573] eta: 0:01:28 time: 0.0720 data: 0.0011 max mem: 33368 +Test: [1500/2573] eta: 0:01:21 time: 0.0737 data: 0.0011 max mem: 33368 +Test: [1600/2573] eta: 0:01:13 time: 0.0769 data: 0.0011 max mem: 33368 +Test: [1700/2573] eta: 0:01:05 time: 0.0719 data: 0.0011 max mem: 33368 +Test: [1800/2573] eta: 0:00:58 time: 0.0754 data: 0.0011 max mem: 33368 +Test: [1900/2573] eta: 0:00:50 time: 0.0720 data: 0.0011 max mem: 33368 +Test: [2000/2573] eta: 0:00:42 time: 0.0737 data: 0.0012 max mem: 33368 +Test: [2100/2573] eta: 0:00:35 time: 0.0753 data: 0.0011 max mem: 33368 +Test: [2200/2573] eta: 0:00:27 time: 0.0754 data: 0.0011 max mem: 33368 +Test: [2300/2573] eta: 0:00:20 time: 0.0754 data: 0.0011 max mem: 33368 +Test: [2400/2573] eta: 0:00:12 time: 0.0704 data: 0.0011 max mem: 33368 +Test: [2500/2573] eta: 0:00:05 time: 0.0737 data: 0.0011 max mem: 33368 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: Total time: 0:03:12 +Final results: +Mean IoU is 61.29 + + precision@0.5 = 69.20 + precision@0.6 = 62.95 + precision@0.7 = 55.47 + precision@0.8 = 43.57 + precision@0.9 = 19.53 + overall IoU = 59.19 + +Average object IoU 61.28776508250881 +Overall IoU 59.18632507324219 +Better epoch: 11 + +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [12] [ 0/1319] eta: 1:27:29 lr: 3.6270008456269996e-05 loss: 0.0788 (0.0788) time: 3.9801 data: 1.2184 max mem: 33368 +Epoch: [12] [ 10/1319] eta: 0:59:53 lr: 3.6261169418713356e-05 loss: 0.0745 (0.0682) time: 2.7453 data: 0.1164 max mem: 33368 +Epoch: [12] [ 20/1319] eta: 0:58:25 lr: 3.62523301417494e-05 loss: 0.0724 (0.0786) time: 2.6349 data: 0.0060 max mem: 33368 +Epoch: [12] [ 30/1319] eta: 0:57:20 lr: 3.624349062530679e-05 loss: 0.0673 (0.0761) time: 2.6278 data: 0.0063 max mem: 33368 +Epoch: [12] [ 40/1319] eta: 0:56:32 lr: 3.623465086931413e-05 loss: 0.0631 (0.0721) time: 2.6030 data: 0.0064 max mem: 33368 +Epoch: [12] [ 50/1319] eta: 0:55:53 lr: 3.62258108737e-05 loss: 0.0548 (0.0708) time: 2.6016 data: 0.0063 max mem: 33368 +Epoch: [12] [ 60/1319] eta: 0:55:27 lr: 3.621697063839292e-05 loss: 0.0566 (0.0706) time: 2.6234 data: 0.0063 max mem: 33368 +Epoch: [12] [ 70/1319] eta: 0:54:58 lr: 3.6208130163321375e-05 loss: 0.0604 (0.0708) time: 2.6351 data: 0.0060 max mem: 33368 +Epoch: [12] [ 80/1319] eta: 0:54:34 lr: 3.619928944841383e-05 loss: 0.0598 (0.0703) time: 2.6425 data: 0.0062 max mem: 33368 +Epoch: [12] [ 90/1319] eta: 0:54:05 lr: 3.6190448493598675e-05 loss: 0.0597 (0.0713) time: 2.6393 data: 0.0064 max mem: 33368 +Epoch: [12] [ 100/1319] eta: 0:53:45 lr: 3.61816072988043e-05 loss: 0.0653 (0.0710) time: 2.6607 data: 0.0063 max mem: 33368 +Epoch: [12] [ 110/1319] eta: 0:53:13 lr: 3.617276586395901e-05 loss: 0.0550 (0.0702) time: 2.6448 data: 0.0063 max mem: 33368 +Epoch: [12] [ 120/1319] eta: 0:52:42 lr: 3.61639241889911e-05 loss: 0.0550 (0.0691) time: 2.5957 data: 0.0062 max mem: 33368 +Epoch: [12] [ 130/1319] eta: 0:52:12 lr: 3.615508227382881e-05 loss: 0.0627 (0.0694) time: 2.5961 data: 0.0061 max mem: 33368 +Epoch: [12] [ 140/1319] eta: 0:51:44 lr: 3.614624011840035e-05 loss: 0.0653 (0.0697) time: 2.6036 data: 0.0061 max mem: 33368 +Epoch: [12] [ 150/1319] eta: 0:51:19 lr: 3.613739772263389e-05 loss: 0.0638 (0.0695) time: 2.6337 data: 0.0062 max mem: 33368 +Epoch: [12] [ 160/1319] eta: 0:50:51 lr: 3.6128555086457536e-05 loss: 0.0638 (0.0695) time: 2.6343 data: 0.0066 max mem: 33368 +Epoch: [12] [ 170/1319] eta: 0:50:28 lr: 3.6119712209799373e-05 loss: 0.0577 (0.0702) time: 2.6446 data: 0.0066 max mem: 33368 +Epoch: [12] [ 180/1319] eta: 0:50:00 lr: 3.6110869092587446e-05 loss: 0.0594 (0.0703) time: 2.6458 data: 0.0064 max mem: 33368 +Epoch: [12] [ 190/1319] eta: 0:49:35 lr: 3.610202573474975e-05 loss: 0.0604 (0.0702) time: 2.6339 data: 0.0063 max mem: 33368 +Epoch: [12] [ 200/1319] eta: 0:49:09 lr: 3.609318213621424e-05 loss: 0.0558 (0.0696) time: 2.6457 data: 0.0061 max mem: 33368 +Epoch: [12] [ 210/1319] eta: 0:48:41 lr: 3.608433829690883e-05 loss: 0.0591 (0.0704) time: 2.6222 data: 0.0061 max mem: 33368 +Epoch: [12] [ 220/1319] eta: 0:48:13 lr: 3.607549421676141e-05 loss: 0.0786 (0.0716) time: 2.6088 data: 0.0061 max mem: 33368 +Epoch: [12] [ 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eta: 0:30:40 lr: 3.5721532687286004e-05 loss: 0.0704 (0.0732) time: 2.6513 data: 0.0061 max mem: 33368 +Epoch: [12] [ 630/1319] eta: 0:30:13 lr: 3.571267867000252e-05 loss: 0.0660 (0.0732) time: 2.6120 data: 0.0060 max mem: 33368 +Epoch: [12] [ 640/1319] eta: 0:29:48 lr: 3.570382440881008e-05 loss: 0.0608 (0.0732) time: 2.6444 data: 0.0059 max mem: 33368 +Epoch: [12] [ 650/1319] eta: 0:29:21 lr: 3.5694969903634736e-05 loss: 0.0610 (0.0731) time: 2.6512 data: 0.0060 max mem: 33368 +Epoch: [12] [ 660/1319] eta: 0:28:54 lr: 3.568611515440253e-05 loss: 0.0704 (0.0732) time: 2.6074 data: 0.0061 max mem: 33368 +Epoch: [12] [ 670/1319] eta: 0:28:27 lr: 3.567726016103943e-05 loss: 0.0632 (0.0731) time: 2.5908 data: 0.0059 max mem: 33368 +Epoch: [12] [ 680/1319] eta: 0:28:01 lr: 3.5668404923471386e-05 loss: 0.0605 (0.0730) time: 2.5902 data: 0.0059 max mem: 33368 +Epoch: [12] [ 690/1319] eta: 0:27:35 lr: 3.565954944162429e-05 loss: 0.0585 (0.0728) time: 2.6161 data: 0.0061 max mem: 33368 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3.5376044597489155e-05 loss: 0.0757 (0.0749) time: 2.6118 data: 0.0059 max mem: 33368 +Epoch: [12] [1020/1319] eta: 0:13:05 lr: 3.536718101257892e-05 loss: 0.0752 (0.0749) time: 2.6157 data: 0.0058 max mem: 33368 +Epoch: [12] [1030/1319] eta: 0:12:39 lr: 3.5358317180844356e-05 loss: 0.0760 (0.0751) time: 2.6347 data: 0.0059 max mem: 33368 +Epoch: [12] [1040/1319] eta: 0:12:13 lr: 3.5349453102209835e-05 loss: 0.0575 (0.0749) time: 2.6487 data: 0.0059 max mem: 33368 +Epoch: [12] [1050/1319] eta: 0:11:46 lr: 3.534058877659969e-05 loss: 0.0564 (0.0750) time: 2.6311 data: 0.0059 max mem: 33368 +Epoch: [12] [1060/1319] eta: 0:11:20 lr: 3.5331724203938196e-05 loss: 0.0762 (0.0750) time: 2.6141 data: 0.0060 max mem: 33368 +Epoch: [12] [1070/1319] eta: 0:10:54 lr: 3.53228593841496e-05 loss: 0.0729 (0.0750) time: 2.6380 data: 0.0060 max mem: 33368 +Epoch: [12] [1080/1319] eta: 0:10:27 lr: 3.53139943171581e-05 loss: 0.0706 (0.0750) time: 2.6321 data: 0.0059 max mem: 33368 +Epoch: [12] [1090/1319] eta: 0:10:01 lr: 3.5305129002887835e-05 loss: 0.0640 (0.0750) time: 2.6206 data: 0.0059 max mem: 33368 +Epoch: [12] [1100/1319] eta: 0:09:35 lr: 3.529626344126292e-05 loss: 0.0647 (0.0750) time: 2.6538 data: 0.0059 max mem: 33368 +Epoch: [12] [1110/1319] eta: 0:09:09 lr: 3.5287397632207417e-05 loss: 0.0755 (0.0752) time: 2.6273 data: 0.0061 max mem: 33368 +Epoch: [12] [1120/1319] eta: 0:08:42 lr: 3.527853157564535e-05 loss: 0.0696 (0.0751) time: 2.6115 data: 0.0060 max mem: 33368 +Epoch: [12] [1130/1319] eta: 0:08:16 lr: 3.526966527150067e-05 loss: 0.0719 (0.0754) time: 2.6618 data: 0.0062 max mem: 33368 +Epoch: [12] [1140/1319] eta: 0:07:50 lr: 3.5260798719697326e-05 loss: 0.0969 (0.0755) time: 2.6539 data: 0.0062 max mem: 33368 +Epoch: [12] [1150/1319] eta: 0:07:24 lr: 3.52519319201592e-05 loss: 0.0714 (0.0754) time: 2.6356 data: 0.0061 max mem: 33368 +Epoch: [12] [1160/1319] eta: 0:06:57 lr: 3.524306487281011e-05 loss: 0.0601 (0.0753) time: 2.6380 data: 0.0061 max mem: 33368 +Epoch: [12] [1170/1319] eta: 0:06:31 lr: 3.523419757757387e-05 loss: 0.0601 (0.0754) time: 2.6290 data: 0.0061 max mem: 33368 +Epoch: [12] [1180/1319] eta: 0:06:05 lr: 3.5225330034374235e-05 loss: 0.0625 (0.0753) time: 2.6171 data: 0.0059 max mem: 33368 +Epoch: [12] [1190/1319] eta: 0:05:39 lr: 3.5216462243134885e-05 loss: 0.0625 (0.0753) time: 2.6066 data: 0.0058 max mem: 33368 +Epoch: [12] [1200/1319] eta: 0:05:12 lr: 3.52075942037795e-05 loss: 0.0641 (0.0753) time: 2.6254 data: 0.0061 max mem: 33368 +Epoch: [12] [1210/1319] eta: 0:04:46 lr: 3.519872591623169e-05 loss: 0.0620 (0.0752) time: 2.6564 data: 0.0061 max mem: 33368 +Epoch: [12] [1220/1319] eta: 0:04:20 lr: 3.518985738041502e-05 loss: 0.0796 (0.0754) time: 2.6367 data: 0.0060 max mem: 33368 +Epoch: [12] [1230/1319] eta: 0:03:53 lr: 3.518098859625303e-05 loss: 0.0826 (0.0753) time: 2.6352 data: 0.0059 max mem: 33368 +Epoch: [12] [1240/1319] eta: 0:03:27 lr: 3.517211956366918e-05 loss: 0.0687 (0.0754) time: 2.6410 data: 0.0057 max mem: 33368 +Epoch: [12] [1250/1319] eta: 0:03:01 lr: 3.5163250282586914e-05 loss: 0.0739 (0.0754) time: 2.6387 data: 0.0057 max mem: 33368 +Epoch: [12] [1260/1319] eta: 0:02:35 lr: 3.515438075292963e-05 loss: 0.0745 (0.0755) time: 2.6546 data: 0.0059 max mem: 33368 +Epoch: [12] [1270/1319] eta: 0:02:08 lr: 3.514551097462066e-05 loss: 0.0824 (0.0756) time: 2.6295 data: 0.0060 max mem: 33368 +Epoch: [12] [1280/1319] eta: 0:01:42 lr: 3.513664094758331e-05 loss: 0.0911 (0.0758) time: 2.6249 data: 0.0058 max mem: 33368 +Epoch: [12] [1290/1319] eta: 0:01:16 lr: 3.512777067174083e-05 loss: 0.0719 (0.0757) time: 2.6185 data: 0.0059 max mem: 33368 +Epoch: [12] [1300/1319] eta: 0:00:49 lr: 3.511890014701643e-05 loss: 0.0598 (0.0756) time: 2.5944 data: 0.0061 max mem: 33368 +Epoch: [12] [1310/1319] eta: 0:00:23 lr: 3.511002937333328e-05 loss: 0.0579 (0.0755) time: 2.6100 data: 0.0060 max mem: 33368 +Epoch: [12] Total time: 0:57:47 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 2:31:46 time: 3.5393 data: 3.4244 max mem: 33368 +Test: [ 100/2573] eta: 0:04:22 time: 0.0711 data: 0.0011 max mem: 33368 +Test: [ 200/2573] eta: 0:03:33 time: 0.0731 data: 0.0012 max mem: 33368 +Test: [ 300/2573] eta: 0:03:10 time: 0.0747 data: 0.0011 max mem: 33368 +Test: [ 400/2573] eta: 0:02:56 time: 0.0749 data: 0.0011 max mem: 33368 +Test: [ 500/2573] eta: 0:02:45 time: 0.0734 data: 0.0011 max mem: 33368 +Test: [ 600/2573] eta: 0:02:35 time: 0.0735 data: 0.0011 max mem: 33368 +Test: [ 700/2573] eta: 0:02:26 time: 0.0735 data: 0.0011 max mem: 33368 +Test: [ 800/2573] eta: 0:02:17 time: 0.0766 data: 0.0011 max mem: 33368 +Test: [ 900/2573] eta: 0:02:09 time: 0.0734 data: 0.0011 max mem: 33368 +Test: [1000/2573] eta: 0:02:01 time: 0.0734 data: 0.0011 max mem: 33368 +Test: [1100/2573] eta: 0:01:52 time: 0.0734 data: 0.0011 max mem: 33368 +Test: [1200/2573] eta: 0:01:47 time: 0.1838 data: 0.1112 max mem: 33368 +Test: [1300/2573] eta: 0:01:39 time: 0.0740 data: 0.0011 max mem: 33368 +Test: [1400/2573] eta: 0:01:31 time: 0.0724 data: 0.0011 max mem: 33368 +Test: [1500/2573] eta: 0:01:23 time: 0.0741 data: 0.0011 max mem: 33368 +Test: [1600/2573] eta: 0:01:15 time: 0.0775 data: 0.0011 max mem: 33368 +Test: [1700/2573] eta: 0:01:07 time: 0.0725 data: 0.0011 max mem: 33368 +Test: [1800/2573] eta: 0:00:59 time: 0.0757 data: 0.0011 max mem: 33368 +Test: [1900/2573] eta: 0:00:51 time: 0.0725 data: 0.0011 max mem: 33368 +Test: [2000/2573] eta: 0:00:43 time: 0.0742 data: 0.0011 max mem: 33368 +Test: [2100/2573] eta: 0:00:36 time: 0.0758 data: 0.0011 max mem: 33368 +Test: [2200/2573] eta: 0:00:28 time: 0.0757 data: 0.0010 max mem: 33368 +Test: [2300/2573] eta: 0:00:20 time: 0.0759 data: 0.0011 max mem: 33368 +Test: [2400/2573] eta: 0:00:13 time: 0.0707 data: 0.0011 max mem: 33368 +Test: [2500/2573] eta: 0:00:05 time: 0.0742 data: 0.0011 max mem: 33368 +Test: Total time: 0:03:16 +Final results: +Mean IoU is 62.69 + + precision@0.5 = 70.89 + precision@0.6 = 64.54 + precision@0.7 = 57.15 + precision@0.8 = 44.81 + precision@0.9 = 21.02 + overall IoU = 60.46 + +Average object IoU 62.68967569927977 +Overall IoU 60.45709991455078 +Better epoch: 12 + +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [13] [ 0/1319] eta: 1:29:25 lr: 3.510204546409517e-05 loss: 0.0556 (0.0556) time: 4.0676 data: 1.3447 max mem: 33368 +Epoch: [13] [ 10/1319] eta: 0:59:52 lr: 3.509317421717855e-05 loss: 0.0590 (0.0633) time: 2.7442 data: 0.1279 max mem: 33368 +Epoch: [13] [ 20/1319] eta: 0:58:14 lr: 3.50843027210801e-05 loss: 0.0620 (0.0665) time: 2.6211 data: 0.0060 max mem: 33368 +Epoch: [13] [ 30/1319] eta: 0:57:19 lr: 3.5075430975722793e-05 loss: 0.0709 (0.0756) time: 2.6266 data: 0.0062 max mem: 33368 +Epoch: [13] [ 40/1319] eta: 0:56:39 lr: 3.506655898102959e-05 loss: 0.0713 (0.0758) time: 2.6240 data: 0.0063 max mem: 33368 +Epoch: [13] [ 50/1319] eta: 0:56:03 lr: 3.505768673692337e-05 loss: 0.0686 (0.0732) time: 2.6220 data: 0.0062 max mem: 33368 +Epoch: [13] [ 60/1319] eta: 0:55:30 lr: 3.5048814243327e-05 loss: 0.0626 (0.0736) time: 2.6198 data: 0.0063 max mem: 33368 +Epoch: [13] [ 70/1319] eta: 0:54:50 lr: 3.503994150016327e-05 loss: 0.0578 (0.0742) time: 2.5935 data: 0.0063 max mem: 33368 +Epoch: [13] [ 80/1319] eta: 0:54:20 lr: 3.503106850735495e-05 loss: 0.0512 (0.0718) time: 2.5909 data: 0.0063 max mem: 33368 +Epoch: [13] [ 90/1319] eta: 0:53:55 lr: 3.502219526482476e-05 loss: 0.0512 (0.0710) time: 2.6278 data: 0.0063 max mem: 33368 +Epoch: [13] [ 100/1319] eta: 0:53:26 lr: 3.501332177249536e-05 loss: 0.0575 (0.0700) time: 2.6247 data: 0.0063 max mem: 33368 +Epoch: [13] [ 110/1319] eta: 0:52:55 lr: 3.500444803028936e-05 loss: 0.0564 (0.0694) time: 2.5970 data: 0.0063 max mem: 33368 +Epoch: [13] [ 120/1319] eta: 0:52:33 lr: 3.499557403812936e-05 loss: 0.0601 (0.0697) time: 2.6265 data: 0.0062 max mem: 33368 +Epoch: [13] [ 130/1319] eta: 0:52:08 lr: 3.498669979593787e-05 loss: 0.0668 (0.0699) time: 2.6588 data: 0.0062 max mem: 33368 +Epoch: [13] [ 140/1319] eta: 0:51:42 lr: 3.497782530363739e-05 loss: 0.0601 (0.0703) time: 2.6419 data: 0.0062 max mem: 33368 +Epoch: [13] [ 150/1319] eta: 0:51:13 lr: 3.4968950561150356e-05 loss: 0.0570 (0.0701) time: 2.6168 data: 0.0062 max mem: 33368 +Epoch: [13] [ 160/1319] eta: 0:50:44 lr: 3.496007556839915e-05 loss: 0.0795 (0.0724) time: 2.5933 data: 0.0062 max mem: 33368 +Epoch: [13] [ 170/1319] eta: 0:50:19 lr: 3.495120032530614e-05 loss: 0.0681 (0.0716) time: 2.6141 data: 0.0061 max mem: 33368 +Epoch: [13] [ 180/1319] eta: 0:49:51 lr: 3.49423248317936e-05 loss: 0.0637 (0.0719) time: 2.6252 data: 0.0063 max mem: 33368 +Epoch: [13] [ 190/1319] eta: 0:49:25 lr: 3.493344908778381e-05 loss: 0.0642 (0.0722) time: 2.6198 data: 0.0062 max mem: 33368 +Epoch: [13] [ 200/1319] eta: 0:48:58 lr: 3.4924573093198975e-05 loss: 0.0642 (0.0717) time: 2.6195 data: 0.0060 max mem: 33368 +Epoch: [13] [ 210/1319] eta: 0:48:32 lr: 3.491569684796125e-05 loss: 0.0558 (0.0710) time: 2.6178 data: 0.0061 max mem: 33368 +Epoch: [13] [ 220/1319] eta: 0:48:06 lr: 3.490682035199276e-05 loss: 0.0645 (0.0709) time: 2.6313 data: 0.0062 max mem: 33368 +Epoch: [13] [ 230/1319] eta: 0:47:39 lr: 3.4897943605215565e-05 loss: 0.0714 (0.0713) time: 2.6292 data: 0.0063 max mem: 33368 +Epoch: [13] [ 240/1319] eta: 0:47:14 lr: 3.488906660755169e-05 loss: 0.0622 (0.0707) time: 2.6302 data: 0.0063 max mem: 33368 +Epoch: [13] [ 250/1319] eta: 0:46:46 lr: 3.4880189358923125e-05 loss: 0.0542 (0.0703) time: 2.6154 data: 0.0064 max mem: 33368 +Epoch: [13] [ 260/1319] eta: 0:46:21 lr: 3.487131185925179e-05 loss: 0.0521 (0.0702) time: 2.6204 data: 0.0064 max mem: 33368 +Epoch: [13] [ 270/1319] eta: 0:45:55 lr: 3.486243410845958e-05 loss: 0.0495 (0.0700) time: 2.6432 data: 0.0061 max mem: 33368 +Epoch: [13] [ 280/1319] eta: 0:45:28 lr: 3.485355610646832e-05 loss: 0.0619 (0.0702) time: 2.6304 data: 0.0063 max mem: 33368 +Epoch: [13] [ 290/1319] eta: 0:45:02 lr: 3.484467785319982e-05 loss: 0.0621 (0.0698) time: 2.6175 data: 0.0064 max mem: 33368 +Epoch: [13] [ 300/1319] eta: 0:44:35 lr: 3.483579934857581e-05 loss: 0.0621 (0.0703) time: 2.6146 data: 0.0064 max mem: 33368 +Epoch: [13] [ 310/1319] eta: 0:44:09 lr: 3.4826920592518003e-05 loss: 0.0623 (0.0702) time: 2.6160 data: 0.0063 max mem: 33368 +Epoch: [13] [ 320/1319] eta: 0:43:42 lr: 3.481804158494804e-05 loss: 0.0737 (0.0706) time: 2.6102 data: 0.0061 max mem: 33368 +Epoch: [13] [ 330/1319] eta: 0:43:14 lr: 3.4809162325787535e-05 loss: 0.0721 (0.0704) time: 2.5982 data: 0.0061 max mem: 33368 +Epoch: [13] [ 340/1319] eta: 0:42:48 lr: 3.480028281495805e-05 loss: 0.0580 (0.0706) time: 2.6088 data: 0.0062 max mem: 33368 +Epoch: [13] [ 350/1319] eta: 0:42:21 lr: 3.479140305238109e-05 loss: 0.0746 (0.0710) time: 2.6101 data: 0.0062 max mem: 33368 +Epoch: [13] [ 360/1319] eta: 0:41:55 lr: 3.478252303797812e-05 loss: 0.0776 (0.0713) time: 2.6115 data: 0.0062 max mem: 33368 +Epoch: [13] [ 370/1319] eta: 0:41:29 lr: 3.4773642771670566e-05 loss: 0.0638 (0.0710) time: 2.6216 data: 0.0060 max mem: 33368 +Epoch: [13] [ 380/1319] eta: 0:41:03 lr: 3.47647622533798e-05 loss: 0.0564 (0.0706) time: 2.6208 data: 0.0060 max 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3.413359644072625e-05 loss: 0.0625 (0.0712) time: 2.6223 data: 0.0059 max mem: 33368 +Epoch: [13] [1100/1319] eta: 0:09:33 lr: 3.412469756992473e-05 loss: 0.0625 (0.0712) time: 2.6377 data: 0.0058 max mem: 33368 +Epoch: [13] [1110/1319] eta: 0:09:07 lr: 3.411579844127087e-05 loss: 0.0811 (0.0713) time: 2.6130 data: 0.0059 max mem: 33368 +Epoch: [13] [1120/1319] eta: 0:08:41 lr: 3.410689905468246e-05 loss: 0.0580 (0.0713) time: 2.6056 data: 0.0060 max mem: 33368 +Epoch: [13] [1130/1319] eta: 0:08:15 lr: 3.409799941007725e-05 loss: 0.0519 (0.0712) time: 2.6294 data: 0.0059 max mem: 33368 +Epoch: [13] [1140/1319] eta: 0:07:48 lr: 3.408909950737292e-05 loss: 0.0462 (0.0711) time: 2.6234 data: 0.0058 max mem: 33368 +Epoch: [13] [1150/1319] eta: 0:07:22 lr: 3.4080199346487104e-05 loss: 0.0511 (0.0710) time: 2.6103 data: 0.0060 max mem: 33368 +Epoch: [13] [1160/1319] eta: 0:06:56 lr: 3.4071298927337405e-05 loss: 0.0654 (0.0711) time: 2.6100 data: 0.0061 max mem: 33368 +Epoch: [13] [1170/1319] eta: 0:06:30 lr: 3.406239824984136e-05 loss: 0.0824 (0.0714) time: 2.6137 data: 0.0059 max mem: 33368 +Epoch: [13] [1180/1319] eta: 0:06:04 lr: 3.405349731391645e-05 loss: 0.0736 (0.0714) time: 2.6057 data: 0.0058 max mem: 33368 +Epoch: [13] [1190/1319] eta: 0:05:37 lr: 3.404459611948011e-05 loss: 0.0690 (0.0713) time: 2.6098 data: 0.0058 max mem: 33368 +Epoch: [13] [1200/1319] eta: 0:05:11 lr: 3.4035694666449745e-05 loss: 0.0664 (0.0712) time: 2.6240 data: 0.0057 max mem: 33368 +Epoch: [13] [1210/1319] eta: 0:04:45 lr: 3.402679295474268e-05 loss: 0.0668 (0.0712) time: 2.6134 data: 0.0058 max mem: 33368 +Epoch: [13] [1220/1319] eta: 0:04:19 lr: 3.401789098427621e-05 loss: 0.0645 (0.0712) time: 2.6046 data: 0.0060 max mem: 33368 +Epoch: [13] [1230/1319] eta: 0:03:53 lr: 3.400898875496756e-05 loss: 0.0592 (0.0711) time: 2.6107 data: 0.0059 max mem: 33368 +Epoch: [13] [1240/1319] eta: 0:03:26 lr: 3.400008626673392e-05 loss: 0.0592 (0.0710) time: 2.5917 data: 0.0059 max mem: 33368 +Epoch: [13] [1250/1319] eta: 0:03:00 lr: 3.399118351949243e-05 loss: 0.0650 (0.0711) time: 2.5959 data: 0.0061 max mem: 33368 +Epoch: [13] [1260/1319] eta: 0:02:34 lr: 3.398228051316017e-05 loss: 0.0691 (0.0712) time: 2.6190 data: 0.0060 max mem: 33368 +Epoch: [13] [1270/1319] eta: 0:02:08 lr: 3.397337724765419e-05 loss: 0.0807 (0.0715) time: 2.5974 data: 0.0059 max mem: 33368 +Epoch: [13] [1280/1319] eta: 0:01:42 lr: 3.396447372289146e-05 loss: 0.0807 (0.0715) time: 2.6023 data: 0.0059 max mem: 33368 +Epoch: [13] [1290/1319] eta: 0:01:15 lr: 3.395556993878891e-05 loss: 0.0744 (0.0715) time: 2.6249 data: 0.0059 max mem: 33368 +Epoch: [13] [1300/1319] eta: 0:00:49 lr: 3.394666589526343e-05 loss: 0.0581 (0.0715) time: 2.6273 data: 0.0057 max mem: 33368 +Epoch: [13] [1310/1319] eta: 0:00:23 lr: 3.393776159223184e-05 loss: 0.0584 (0.0714) time: 2.6203 data: 0.0057 max mem: 33368 +Epoch: [13] Total time: 0:57:34 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 2:30:33 time: 3.5109 data: 3.4257 max mem: 33368 +Test: [ 100/2573] eta: 0:04:21 time: 0.0713 data: 0.0011 max mem: 33368 +Test: [ 200/2573] eta: 0:03:33 time: 0.0729 data: 0.0011 max mem: 33368 +Test: [ 300/2573] eta: 0:03:10 time: 0.0753 data: 0.0012 max mem: 33368 +Test: [ 400/2573] eta: 0:02:56 time: 0.0749 data: 0.0011 max mem: 33368 +Test: [ 500/2573] eta: 0:02:45 time: 0.0732 data: 0.0011 max mem: 33368 +Test: [ 600/2573] eta: 0:02:35 time: 0.0734 data: 0.0011 max mem: 33368 +Test: [ 700/2573] eta: 0:02:26 time: 0.0737 data: 0.0011 max mem: 33368 +Test: [ 800/2573] eta: 0:02:17 time: 0.0768 data: 0.0010 max mem: 33368 +Test: [ 900/2573] eta: 0:02:09 time: 0.0736 data: 0.0011 max mem: 33368 +Test: [1000/2573] eta: 0:02:01 time: 0.0735 data: 0.0011 max mem: 33368 +Test: [1100/2573] eta: 0:01:53 time: 0.0736 data: 0.0011 max mem: 33368 +Test: [1200/2573] eta: 0:01:45 time: 0.0736 data: 0.0011 max mem: 33368 +Test: [1300/2573] eta: 0:01:37 time: 0.0737 data: 0.0011 max mem: 33368 +Test: [1400/2573] eta: 0:01:29 time: 0.0720 data: 0.0011 max mem: 33368 +Test: [1500/2573] eta: 0:01:21 time: 0.0737 data: 0.0011 max mem: 33368 +Test: [1600/2573] eta: 0:01:13 time: 0.0770 data: 0.0011 max mem: 33368 +Test: [1700/2573] eta: 0:01:06 time: 0.0723 data: 0.0011 max mem: 33368 +Test: [1800/2573] eta: 0:00:58 time: 0.0756 data: 0.0011 max mem: 33368 +Test: [1900/2573] eta: 0:00:50 time: 0.0721 data: 0.0011 max mem: 33368 +Test: [2000/2573] eta: 0:00:43 time: 0.0739 data: 0.0011 max mem: 33368 +Test: [2100/2573] eta: 0:00:35 time: 0.0754 data: 0.0011 max mem: 33368 +Test: [2200/2573] eta: 0:00:28 time: 0.0754 data: 0.0011 max mem: 33368 +Test: [2300/2573] eta: 0:00:20 time: 0.0754 data: 0.0011 max mem: 33368 +Test: [2400/2573] eta: 0:00:12 time: 0.0705 data: 0.0011 max mem: 33368 +Test: [2500/2573] eta: 0:00:05 time: 0.0737 data: 0.0011 max mem: 33368 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: Total time: 0:03:13 +Final results: +Mean IoU is 62.12 + + precision@0.5 = 70.00 + precision@0.6 = 63.99 + precision@0.7 = 56.33 + precision@0.8 = 44.40 + precision@0.9 = 21.98 + overall IoU = 60.58 + +Average object IoU 62.124368317369516 +Overall IoU 60.582496643066406 +Better epoch: 13 + +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [14] [ 0/1319] eta: 1:27:25 lr: 3.392974749755691e-05 loss: 0.1052 (0.1052) time: 3.9766 data: 1.3397 max mem: 33368 +Epoch: [14] [ 10/1319] eta: 1:00:25 lr: 3.392084270123441e-05 loss: 0.0583 (0.0593) time: 2.7693 data: 0.1271 max mem: 33368 +Epoch: [14] [ 20/1319] eta: 0:58:11 lr: 3.391193764516433e-05 loss: 0.0583 (0.0680) time: 2.6232 data: 0.0056 max mem: 33368 +Epoch: [14] [ 30/1319] eta: 0:57:18 lr: 3.3903032329263314e-05 loss: 0.0711 (0.0680) time: 2.6114 data: 0.0060 max mem: 33368 +Epoch: [14] [ 40/1319] eta: 0:56:37 lr: 3.389412675344791e-05 loss: 0.0622 (0.0681) time: 2.6241 data: 0.0064 max mem: 33368 +Epoch: [14] [ 50/1319] eta: 0:56:00 lr: 3.388522091763468e-05 loss: 0.0594 (0.0679) time: 2.6181 data: 0.0062 max mem: 33368 +Epoch: [14] [ 60/1319] eta: 0:55:35 lr: 3.387631482174009e-05 loss: 0.0569 (0.0670) time: 2.6334 data: 0.0062 max mem: 33368 +Epoch: [14] [ 70/1319] eta: 0:55:02 lr: 3.386740846568057e-05 loss: 0.0555 (0.0662) time: 2.6353 data: 0.0062 max mem: 33368 +Epoch: [14] [ 80/1319] eta: 0:54:30 lr: 3.385850184937249e-05 loss: 0.0552 (0.0653) time: 2.6117 data: 0.0063 max mem: 33368 +Epoch: [14] [ 90/1319] eta: 0:53:59 lr: 3.3849594972732175e-05 loss: 0.0540 (0.0643) time: 2.6047 data: 0.0063 max mem: 33368 +Epoch: [14] [ 100/1319] eta: 0:53:30 lr: 3.38406878356759e-05 loss: 0.0512 (0.0648) time: 2.6090 data: 0.0064 max mem: 33368 +Epoch: [14] [ 110/1319] eta: 0:53:05 lr: 3.3831780438119907e-05 loss: 0.0528 (0.0648) time: 2.6310 data: 0.0064 max mem: 33368 +Epoch: [14] [ 120/1319] eta: 0:52:39 lr: 3.3822872779980336e-05 loss: 0.0528 (0.0652) time: 2.6413 data: 0.0063 max mem: 33368 +Epoch: [14] [ 130/1319] eta: 0:52:14 lr: 3.381396486117332e-05 loss: 0.0588 (0.0651) time: 2.6432 data: 0.0063 max mem: 33368 +Epoch: [14] [ 140/1319] eta: 0:51:48 lr: 3.380505668161494e-05 loss: 0.0594 (0.0646) time: 2.6477 data: 0.0063 max mem: 33368 +Epoch: [14] [ 150/1319] eta: 0:51:18 lr: 3.3796148241221185e-05 loss: 0.0601 (0.0649) time: 2.6188 data: 0.0062 max mem: 33368 +Epoch: [14] [ 160/1319] eta: 0:50:51 lr: 3.378723953990804e-05 loss: 0.0663 (0.0652) time: 2.6076 data: 0.0062 max mem: 33368 +Epoch: [14] [ 170/1319] eta: 0:50:27 lr: 3.3778330577591404e-05 loss: 0.0707 (0.0659) time: 2.6402 data: 0.0062 max mem: 33368 +Epoch: [14] [ 180/1319] eta: 0:49:58 lr: 3.3769421354187145e-05 loss: 0.0622 (0.0658) time: 2.6249 data: 0.0061 max mem: 33368 +Epoch: [14] [ 190/1319] eta: 0:49:29 lr: 3.376051186961107e-05 loss: 0.0562 (0.0662) time: 2.5907 data: 0.0060 max mem: 33368 +Epoch: [14] [ 200/1319] eta: 0:49:02 lr: 3.375160212377894e-05 loss: 0.0641 (0.0672) time: 2.6069 data: 0.0060 max mem: 33368 +Epoch: [14] [ 210/1319] eta: 0:48:34 lr: 3.374269211660646e-05 loss: 0.0636 (0.0670) time: 2.6090 data: 0.0061 max mem: 33368 +Epoch: [14] [ 220/1319] eta: 0:48:07 lr: 3.373378184800928e-05 loss: 0.0597 (0.0666) time: 2.6034 data: 0.0060 max mem: 33368 +Epoch: [14] [ 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eta: 0:27:06 lr: 3.330577985360116e-05 loss: 0.0605 (0.0675) time: 2.6489 data: 0.0060 max mem: 33368 +Epoch: [14] [ 710/1319] eta: 0:26:39 lr: 3.329685667077455e-05 loss: 0.0509 (0.0673) time: 2.6405 data: 0.0059 max mem: 33368 +Epoch: [14] [ 720/1319] eta: 0:26:13 lr: 3.3287933222238623e-05 loss: 0.0509 (0.0673) time: 2.6069 data: 0.0060 max mem: 33368 +Epoch: [14] [ 730/1319] eta: 0:25:47 lr: 3.327900950790632e-05 loss: 0.0571 (0.0673) time: 2.6275 data: 0.0060 max mem: 33368 +Epoch: [14] [ 740/1319] eta: 0:25:21 lr: 3.327008552769054e-05 loss: 0.0641 (0.0673) time: 2.6313 data: 0.0060 max mem: 33368 +Epoch: [14] [ 750/1319] eta: 0:24:54 lr: 3.32611612815041e-05 loss: 0.0641 (0.0673) time: 2.6000 data: 0.0061 max mem: 33368 +Epoch: [14] [ 760/1319] eta: 0:24:28 lr: 3.325223676925979e-05 loss: 0.0597 (0.0674) time: 2.5958 data: 0.0059 max mem: 33368 +Epoch: [14] [ 770/1319] eta: 0:24:01 lr: 3.324331199087032e-05 loss: 0.0518 (0.0674) time: 2.5954 data: 0.0060 max mem: 33368 +Epoch: 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(0.0676) time: 2.6533 data: 0.0058 max mem: 33368 +Epoch: [14] [1020/1319] eta: 0:13:05 lr: 3.3020105777547046e-05 loss: 0.0700 (0.0676) time: 2.6237 data: 0.0059 max mem: 33368 +Epoch: [14] [1030/1319] eta: 0:12:38 lr: 3.301117404856897e-05 loss: 0.0596 (0.0676) time: 2.6217 data: 0.0060 max mem: 33368 +Epoch: [14] [1040/1319] eta: 0:12:12 lr: 3.300224205106842e-05 loss: 0.0596 (0.0677) time: 2.6503 data: 0.0058 max mem: 33368 +Epoch: [14] [1050/1319] eta: 0:11:46 lr: 3.2993309784956545e-05 loss: 0.0754 (0.0677) time: 2.6552 data: 0.0058 max mem: 33368 +Epoch: [14] [1060/1319] eta: 0:11:20 lr: 3.298437725014447e-05 loss: 0.0569 (0.0676) time: 2.6513 data: 0.0059 max mem: 33368 +Epoch: [14] [1070/1319] eta: 0:10:54 lr: 3.297544444654327e-05 loss: 0.0477 (0.0675) time: 2.6518 data: 0.0059 max mem: 33368 +Epoch: [14] [1080/1319] eta: 0:10:27 lr: 3.296651137406393e-05 loss: 0.0556 (0.0677) time: 2.6227 data: 0.0058 max mem: 33368 +Epoch: [14] [1090/1319] eta: 0:10:01 lr: 3.2957578032617413e-05 loss: 0.0630 (0.0677) time: 2.5916 data: 0.0057 max mem: 33368 +Epoch: [14] [1100/1319] eta: 0:09:35 lr: 3.29486444221146e-05 loss: 0.0630 (0.0677) time: 2.6149 data: 0.0058 max mem: 33368 +Epoch: [14] [1110/1319] eta: 0:09:08 lr: 3.293971054246633e-05 loss: 0.0663 (0.0677) time: 2.6141 data: 0.0058 max mem: 33368 +Epoch: [14] [1120/1319] eta: 0:08:42 lr: 3.293077639358339e-05 loss: 0.0605 (0.0676) time: 2.5987 data: 0.0060 max mem: 33368 +Epoch: [14] [1130/1319] eta: 0:08:16 lr: 3.2921841975376476e-05 loss: 0.0600 (0.0676) time: 2.6276 data: 0.0060 max mem: 33368 +Epoch: [14] [1140/1319] eta: 0:07:50 lr: 3.291290728775627e-05 loss: 0.0613 (0.0676) time: 2.6514 data: 0.0059 max mem: 33368 +Epoch: [14] [1150/1319] eta: 0:07:23 lr: 3.290397233063338e-05 loss: 0.0646 (0.0676) time: 2.6368 data: 0.0060 max mem: 33368 +Epoch: [14] [1160/1319] eta: 0:06:57 lr: 3.2895037103918356e-05 loss: 0.0600 (0.0677) time: 2.6353 data: 0.0058 max mem: 33368 +Epoch: [14] [1170/1319] eta: 0:06:31 lr: 3.2886101607521696e-05 loss: 0.0600 (0.0677) time: 2.6513 data: 0.0058 max mem: 33368 +Epoch: [14] [1180/1319] eta: 0:06:05 lr: 3.287716584135384e-05 loss: 0.0588 (0.0677) time: 2.6528 data: 0.0059 max mem: 33368 +Epoch: [14] [1190/1319] eta: 0:05:38 lr: 3.286822980532516e-05 loss: 0.0620 (0.0677) time: 2.6389 data: 0.0059 max mem: 33368 +Epoch: [14] [1200/1319] eta: 0:05:12 lr: 3.285929349934599e-05 loss: 0.0582 (0.0676) time: 2.6254 data: 0.0060 max mem: 33368 +Epoch: [14] [1210/1319] eta: 0:04:46 lr: 3.28503569233266e-05 loss: 0.0530 (0.0677) time: 2.6079 data: 0.0059 max mem: 33368 +Epoch: [14] [1220/1319] eta: 0:04:20 lr: 3.284142007717719e-05 loss: 0.0573 (0.0677) time: 2.6055 data: 0.0058 max mem: 33368 +Epoch: [14] [1230/1319] eta: 0:03:53 lr: 3.283248296080793e-05 loss: 0.0562 (0.0677) time: 2.6403 data: 0.0060 max mem: 33368 +Epoch: [14] [1240/1319] eta: 0:03:27 lr: 3.2823545574128904e-05 loss: 0.0562 (0.0676) time: 2.6380 data: 0.0059 max mem: 33368 +Epoch: [14] [1250/1319] eta: 0:03:01 lr: 3.2814607917050156e-05 loss: 0.0581 (0.0676) time: 2.6191 data: 0.0058 max mem: 33368 +Epoch: [14] [1260/1319] eta: 0:02:34 lr: 3.280566998948166e-05 loss: 0.0578 (0.0675) time: 2.6465 data: 0.0059 max mem: 33368 +Epoch: [14] [1270/1319] eta: 0:02:08 lr: 3.2796731791333364e-05 loss: 0.0668 (0.0677) time: 2.6261 data: 0.0060 max mem: 33368 +Epoch: [14] [1280/1319] eta: 0:01:42 lr: 3.278779332251511e-05 loss: 0.0668 (0.0676) time: 2.6130 data: 0.0062 max mem: 33368 +Epoch: [14] [1290/1319] eta: 0:01:16 lr: 3.277885458293673e-05 loss: 0.0613 (0.0677) time: 2.6610 data: 0.0060 max mem: 33368 +Epoch: [14] [1300/1319] eta: 0:00:49 lr: 3.276991557250796e-05 loss: 0.0617 (0.0677) time: 2.6486 data: 0.0058 max mem: 33368 +Epoch: [14] [1310/1319] eta: 0:00:23 lr: 3.276097629113851e-05 loss: 0.0706 (0.0678) time: 2.6310 data: 0.0057 max mem: 33368 +Epoch: [14] Total time: 0:57:45 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 2:01:52 time: 2.8421 data: 2.7447 max mem: 33368 +Test: [ 100/2573] eta: 0:04:05 time: 0.0717 data: 0.0011 max mem: 33368 +Test: [ 200/2573] eta: 0:03:26 time: 0.0735 data: 0.0011 max mem: 33368 +Test: [ 300/2573] eta: 0:03:06 time: 0.0750 data: 0.0011 max mem: 33368 +Test: [ 400/2573] eta: 0:02:53 time: 0.0751 data: 0.0011 max mem: 33368 +Test: [ 500/2573] eta: 0:02:42 time: 0.0736 data: 0.0011 max mem: 33368 +Test: [ 600/2573] eta: 0:02:33 time: 0.0736 data: 0.0011 max mem: 33368 +Test: [ 700/2573] eta: 0:02:25 time: 0.0736 data: 0.0011 max mem: 33368 +Test: [ 800/2573] eta: 0:02:16 time: 0.0769 data: 0.0011 max mem: 33368 +Test: [ 900/2573] eta: 0:02:08 time: 0.0738 data: 0.0011 max mem: 33368 +Test: [1000/2573] eta: 0:02:00 time: 0.0737 data: 0.0011 max mem: 33368 +Test: [1100/2573] eta: 0:01:52 time: 0.0738 data: 0.0011 max mem: 33368 +Test: [1200/2573] eta: 0:01:44 time: 0.0738 data: 0.0011 max mem: 33368 +Test: [1300/2573] eta: 0:01:36 time: 0.0737 data: 0.0011 max mem: 33368 +Test: [1400/2573] eta: 0:01:28 time: 0.0721 data: 0.0011 max mem: 33368 +Test: [1500/2573] eta: 0:01:21 time: 0.0737 data: 0.0011 max mem: 33368 +Test: [1600/2573] eta: 0:01:13 time: 0.0770 data: 0.0011 max mem: 33368 +Test: [1700/2573] eta: 0:01:05 time: 0.0721 data: 0.0011 max mem: 33368 +Test: [1800/2573] eta: 0:00:58 time: 0.0755 data: 0.0011 max mem: 33368 +Test: [1900/2573] eta: 0:00:50 time: 0.0721 data: 0.0011 max mem: 33368 +Test: [2000/2573] eta: 0:00:43 time: 0.0740 data: 0.0011 max mem: 33368 +Test: [2100/2573] eta: 0:00:35 time: 0.0754 data: 0.0011 max mem: 33368 +Test: [2200/2573] eta: 0:00:27 time: 0.0754 data: 0.0011 max mem: 33368 +Test: [2300/2573] eta: 0:00:20 time: 0.0754 data: 0.0011 max mem: 33368 +Test: [2400/2573] eta: 0:00:12 time: 0.0704 data: 0.0011 max mem: 33368 +Test: [2500/2573] eta: 0:00:05 time: 0.0738 data: 0.0011 max mem: 33368 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: Total time: 0:03:12 +Final results: +Mean IoU is 62.09 + + precision@0.5 = 69.77 + precision@0.6 = 64.38 + precision@0.7 = 57.23 + precision@0.8 = 45.47 + precision@0.9 = 21.77 + overall IoU = 60.13 + +Average object IoU 62.087005444341116 +Overall IoU 60.126399993896484 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [15] [ 0/1319] eta: 3:15:12 lr: 3.275293070617704e-05 loss: 0.1602 (0.1602) time: 8.8799 data: 1.2578 max mem: 33368 +Epoch: [15] [ 10/1319] eta: 1:10:41 lr: 3.274399090977129e-05 loss: 0.0599 (0.0686) time: 3.2405 data: 0.1198 max mem: 33368 +Epoch: [15] [ 20/1319] eta: 1:03:30 lr: 3.2735050842162644e-05 loss: 0.0547 (0.0648) time: 2.6359 data: 0.0061 max mem: 33368 +Epoch: [15] [ 30/1319] eta: 1:00:54 lr: 3.2726110503260586e-05 loss: 0.0523 (0.0608) time: 2.6116 data: 0.0063 max mem: 33368 +Epoch: [15] [ 40/1319] eta: 0:59:28 lr: 3.271716989297451e-05 loss: 0.0473 (0.0572) time: 2.6397 data: 0.0063 max mem: 33368 +Epoch: [15] [ 50/1319] eta: 0:58:12 lr: 3.2708229011213794e-05 loss: 0.0502 (0.0577) time: 2.6251 data: 0.0061 max mem: 33368 +Epoch: [15] [ 60/1319] eta: 0:57:13 lr: 3.269928785788772e-05 loss: 0.0591 (0.0591) time: 2.5976 data: 0.0063 max mem: 33368 +Epoch: [15] [ 70/1319] eta: 0:56:31 lr: 3.2690346432905536e-05 loss: 0.0592 (0.0591) time: 2.6204 data: 0.0062 max mem: 33368 +Epoch: [15] [ 80/1319] eta: 0:55:51 lr: 3.268140473617642e-05 loss: 0.0611 (0.0597) time: 2.6379 data: 0.0061 max mem: 33368 +Epoch: [15] [ 90/1319] eta: 0:55:04 lr: 3.26724627676095e-05 loss: 0.0529 (0.0591) time: 2.5930 data: 0.0062 max mem: 33368 +Epoch: [15] [ 100/1319] eta: 0:54:27 lr: 3.266352052711384e-05 loss: 0.0531 (0.0595) time: 2.5808 data: 0.0062 max mem: 33368 +Epoch: [15] [ 110/1319] eta: 0:53:53 lr: 3.265457801459844e-05 loss: 0.0586 (0.0607) time: 2.6101 data: 0.0061 max mem: 33368 +Epoch: [15] [ 120/1319] eta: 0:53:21 lr: 3.2645635229972264e-05 loss: 0.0599 (0.0609) time: 2.6206 data: 0.0063 max mem: 33368 +Epoch: [15] [ 130/1319] eta: 0:52:50 lr: 3.2636692173144204e-05 loss: 0.0599 (0.0622) time: 2.6240 data: 0.0063 max mem: 33368 +Epoch: [15] [ 140/1319] eta: 0:52:21 lr: 3.2627748844023084e-05 loss: 0.0577 (0.0617) time: 2.6293 data: 0.0061 max mem: 33368 +Epoch: [15] [ 150/1319] eta: 0:51:50 lr: 3.261880524251768e-05 loss: 0.0514 (0.0611) time: 2.6201 data: 0.0062 max mem: 33368 +Epoch: [15] [ 160/1319] eta: 0:51:20 lr: 3.260986136853672e-05 loss: 0.0518 (0.0612) time: 2.6132 data: 0.0065 max mem: 33368 +Epoch: [15] [ 170/1319] eta: 0:50:53 lr: 3.2600917221988844e-05 loss: 0.0667 (0.0620) time: 2.6348 data: 0.0064 max mem: 33368 +Epoch: [15] [ 180/1319] eta: 0:50:28 lr: 3.259197280278268e-05 loss: 0.0661 (0.0624) time: 2.6604 data: 0.0063 max mem: 33368 +Epoch: [15] [ 190/1319] eta: 0:49:58 lr: 3.258302811082674e-05 loss: 0.0493 (0.0621) time: 2.6422 data: 0.0062 max mem: 33368 +Epoch: [15] [ 200/1319] eta: 0:49:28 lr: 3.257408314602953e-05 loss: 0.0633 (0.0622) time: 2.6019 data: 0.0061 max mem: 33368 +Epoch: [15] [ 210/1319] eta: 0:48:58 lr: 3.2565137908299456e-05 loss: 0.0638 (0.0635) time: 2.5913 data: 0.0062 max mem: 33368 +Epoch: [15] [ 220/1319] eta: 0:48:31 lr: 3.25561923975449e-05 loss: 0.0602 (0.0636) time: 2.6137 data: 0.0062 max mem: 33368 +Epoch: [15] [ 230/1319] eta: 0:48:06 lr: 3.2547246613674155e-05 loss: 0.0538 (0.0631) time: 2.6574 data: 0.0061 max mem: 33368 +Epoch: [15] [ 240/1319] eta: 0:47:38 lr: 3.253830055659547e-05 loss: 0.0511 (0.0629) time: 2.6445 data: 0.0060 max mem: 33368 +Epoch: [15] [ 250/1319] eta: 0:47:10 lr: 3.252935422621704e-05 loss: 0.0506 (0.0629) time: 2.6201 data: 0.0061 max mem: 33368 +Epoch: [15] [ 260/1319] eta: 0:46:42 lr: 3.252040762244701e-05 loss: 0.0506 (0.0625) time: 2.6173 data: 0.0062 max mem: 33368 +Epoch: [15] [ 270/1319] eta: 0:46:15 lr: 3.251146074519342e-05 loss: 0.0581 (0.0637) time: 2.6170 data: 0.0061 max mem: 33368 +Epoch: [15] [ 280/1319] eta: 0:45:46 lr: 3.2502513594364305e-05 loss: 0.0631 (0.0637) time: 2.6056 data: 0.0060 max mem: 33368 +Epoch: [15] [ 290/1319] eta: 0:45:20 lr: 3.2493566169867616e-05 loss: 0.0610 (0.0636) time: 2.6177 data: 0.0061 max mem: 33368 +Epoch: [15] [ 300/1319] eta: 0:44:53 lr: 3.248461847161124e-05 loss: 0.0536 (0.0633) time: 2.6402 data: 0.0062 max mem: 33368 +Epoch: [15] [ 310/1319] eta: 0:44:26 lr: 3.247567049950301e-05 loss: 0.0572 (0.0635) time: 2.6218 data: 0.0061 max mem: 33368 +Epoch: [15] [ 320/1319] eta: 0:43:59 lr: 3.246672225345071e-05 loss: 0.0595 (0.0638) time: 2.6244 data: 0.0060 max mem: 33368 +Epoch: [15] [ 330/1319] eta: 0:43:33 lr: 3.245777373336205e-05 loss: 0.0664 (0.0647) time: 2.6422 data: 0.0061 max mem: 33368 +Epoch: [15] [ 340/1319] eta: 0:43:05 lr: 3.244882493914469e-05 loss: 0.0706 (0.0649) time: 2.6276 data: 0.0061 max mem: 33368 +Epoch: [15] [ 350/1319] eta: 0:42:38 lr: 3.243987587070623e-05 loss: 0.0587 (0.0649) time: 2.6102 data: 0.0061 max mem: 33368 +Epoch: [15] [ 360/1319] eta: 0:42:11 lr: 3.24309265279542e-05 loss: 0.0579 (0.0648) time: 2.6200 data: 0.0062 max mem: 33369 +Epoch: [15] [ 370/1319] eta: 0:41:44 lr: 3.2421976910796087e-05 loss: 0.0557 (0.0646) time: 2.6205 data: 0.0060 max mem: 33369 +Epoch: [15] [ 380/1319] eta: 0:41:17 lr: 3.24130270191393e-05 loss: 0.0544 (0.0648) time: 2.6148 data: 0.0061 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data: 0.0058 max mem: 33369 +Epoch: [15] [ 940/1319] eta: 0:16:36 lr: 3.1911392102369026e-05 loss: 0.0641 (0.0647) time: 2.5964 data: 0.0058 max mem: 33369 +Epoch: [15] [ 950/1319] eta: 0:16:10 lr: 3.1902426409286326e-05 loss: 0.0665 (0.0648) time: 2.6116 data: 0.0058 max mem: 33369 +Epoch: [15] [ 960/1319] eta: 0:15:43 lr: 3.189346043623133e-05 loss: 0.0665 (0.0648) time: 2.6195 data: 0.0059 max mem: 33369 +Epoch: [15] [ 970/1319] eta: 0:15:17 lr: 3.1884494183107815e-05 loss: 0.0541 (0.0647) time: 2.6231 data: 0.0059 max mem: 33369 +Epoch: [15] [ 980/1319] eta: 0:14:51 lr: 3.187552764981953e-05 loss: 0.0491 (0.0647) time: 2.6542 data: 0.0058 max mem: 33369 +Epoch: [15] [ 990/1319] eta: 0:14:25 lr: 3.186656083627014e-05 loss: 0.0465 (0.0646) time: 2.6538 data: 0.0059 max mem: 33369 +Epoch: [15] [1000/1319] eta: 0:13:58 lr: 3.1857593742363276e-05 loss: 0.0492 (0.0646) time: 2.6184 data: 0.0061 max mem: 33369 +Epoch: [15] [1010/1319] eta: 0:13:32 lr: 3.184862636800246e-05 loss: 0.0492 (0.0645) time: 2.5947 data: 0.0061 max mem: 33369 +Epoch: [15] [1020/1319] eta: 0:13:05 lr: 3.183965871309119e-05 loss: 0.0582 (0.0645) time: 2.5930 data: 0.0060 max mem: 33369 +Epoch: [15] [1030/1319] eta: 0:12:39 lr: 3.1830690777532884e-05 loss: 0.0598 (0.0644) time: 2.6259 data: 0.0058 max mem: 33369 +Epoch: [15] [1040/1319] eta: 0:12:13 lr: 3.182172256123091e-05 loss: 0.0508 (0.0645) time: 2.6402 data: 0.0057 max mem: 33369 +Epoch: [15] [1050/1319] eta: 0:11:47 lr: 3.181275406408854e-05 loss: 0.0508 (0.0646) time: 2.6535 data: 0.0060 max mem: 33369 +Epoch: [15] [1060/1319] eta: 0:11:20 lr: 3.180378528600901e-05 loss: 0.0588 (0.0647) time: 2.6502 data: 0.0060 max mem: 33369 +Epoch: [15] [1070/1319] eta: 0:10:54 lr: 3.17948162268955e-05 loss: 0.0684 (0.0648) time: 2.6223 data: 0.0059 max mem: 33369 +Epoch: [15] [1080/1319] eta: 0:10:28 lr: 3.17858468866511e-05 loss: 0.0682 (0.0648) time: 2.6259 data: 0.0058 max mem: 33369 +Epoch: [15] [1090/1319] eta: 0:10:02 lr: 3.177687726517885e-05 loss: 0.0625 (0.0648) time: 2.6216 data: 0.0058 max mem: 33369 +Epoch: [15] [1100/1319] eta: 0:09:35 lr: 3.1767907362381725e-05 loss: 0.0605 (0.0650) time: 2.6130 data: 0.0059 max mem: 33369 +Epoch: [15] [1110/1319] eta: 0:09:09 lr: 3.175893717816263e-05 loss: 0.0537 (0.0648) time: 2.6260 data: 0.0058 max mem: 33369 +Epoch: [15] [1120/1319] eta: 0:08:43 lr: 3.174996671242443e-05 loss: 0.0548 (0.0649) time: 2.6244 data: 0.0059 max mem: 33369 +Epoch: [15] [1130/1319] eta: 0:08:16 lr: 3.1740995965069895e-05 loss: 0.0506 (0.0647) time: 2.6112 data: 0.0060 max mem: 33369 +Epoch: [15] [1140/1319] eta: 0:07:50 lr: 3.173202493600174e-05 loss: 0.0506 (0.0648) time: 2.6188 data: 0.0058 max mem: 33369 +Epoch: [15] [1150/1319] eta: 0:07:24 lr: 3.172305362512263e-05 loss: 0.0675 (0.0649) time: 2.6096 data: 0.0057 max mem: 33369 +Epoch: [15] [1160/1319] eta: 0:06:57 lr: 3.171408203233514e-05 loss: 0.0704 (0.0649) time: 2.6025 data: 0.0058 max mem: 33369 +Epoch: [15] [1170/1319] eta: 0:06:31 lr: 3.170511015754181e-05 loss: 0.0674 (0.0649) time: 2.6315 data: 0.0058 max mem: 33369 +Epoch: [15] [1180/1319] eta: 0:06:05 lr: 3.16961380006451e-05 loss: 0.0522 (0.0648) time: 2.6311 data: 0.0059 max mem: 33369 +Epoch: [15] [1190/1319] eta: 0:05:39 lr: 3.16871655615474e-05 loss: 0.0473 (0.0647) time: 2.6575 data: 0.0060 max mem: 33369 +Epoch: [15] [1200/1319] eta: 0:05:12 lr: 3.1678192840151044e-05 loss: 0.0567 (0.0647) time: 2.6605 data: 0.0062 max mem: 33369 +Epoch: [15] [1210/1319] eta: 0:04:46 lr: 3.16692198363583e-05 loss: 0.0567 (0.0647) time: 2.6128 data: 0.0061 max mem: 33369 +Epoch: [15] [1220/1319] eta: 0:04:20 lr: 3.1660246550071386e-05 loss: 0.0586 (0.0648) time: 2.6126 data: 0.0061 max mem: 33369 +Epoch: [15] [1230/1319] eta: 0:03:53 lr: 3.165127298119242e-05 loss: 0.0671 (0.0649) time: 2.6198 data: 0.0059 max mem: 33369 +Epoch: [15] [1240/1319] eta: 0:03:27 lr: 3.164229912962349e-05 loss: 0.0630 (0.0650) time: 2.6270 data: 0.0058 max mem: 33369 +Epoch: [15] [1250/1319] eta: 0:03:01 lr: 3.163332499526659e-05 loss: 0.0505 (0.0649) time: 2.6316 data: 0.0059 max mem: 33369 +Epoch: [15] [1260/1319] eta: 0:02:35 lr: 3.162435057802369e-05 loss: 0.0536 (0.0649) time: 2.6210 data: 0.0060 max mem: 33369 +Epoch: [15] [1270/1319] eta: 0:02:08 lr: 3.161537587779665e-05 loss: 0.0547 (0.0649) time: 2.6044 data: 0.0060 max mem: 33369 +Epoch: [15] [1280/1319] eta: 0:01:42 lr: 3.1606400894487287e-05 loss: 0.0609 (0.0650) time: 2.6195 data: 0.0060 max mem: 33369 +Epoch: [15] [1290/1319] eta: 0:01:16 lr: 3.159742562799735e-05 loss: 0.0589 (0.0650) time: 2.6284 data: 0.0061 max mem: 33369 +Epoch: [15] [1300/1319] eta: 0:00:49 lr: 3.158845007822852e-05 loss: 0.0574 (0.0651) time: 2.5743 data: 0.0059 max mem: 33369 +Epoch: [15] [1310/1319] eta: 0:00:23 lr: 3.1579474245082424e-05 loss: 0.0704 (0.0652) time: 2.5761 data: 0.0059 max mem: 33369 +Epoch: [15] Total time: 0:57:46 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 2:04:49 time: 2.9107 data: 2.8319 max mem: 33369 +Test: [ 100/2573] eta: 0:04:07 time: 0.0717 data: 0.0011 max mem: 33369 +Test: [ 200/2573] eta: 0:03:26 time: 0.0733 data: 0.0011 max mem: 33369 +Test: [ 300/2573] eta: 0:03:06 time: 0.0751 data: 0.0011 max mem: 33369 +Test: [ 400/2573] eta: 0:02:53 time: 0.0751 data: 0.0011 max mem: 33369 +Test: [ 500/2573] eta: 0:02:43 time: 0.0735 data: 0.0011 max mem: 33369 +Test: [ 600/2573] eta: 0:02:33 time: 0.0737 data: 0.0011 max mem: 33369 +Test: [ 700/2573] eta: 0:02:25 time: 0.0738 data: 0.0011 max mem: 33369 +Test: [ 800/2573] eta: 0:02:17 time: 0.0769 data: 0.0011 max mem: 33369 +Test: [ 900/2573] eta: 0:02:08 time: 0.0737 data: 0.0011 max mem: 33369 +Test: [1000/2573] eta: 0:02:00 time: 0.0737 data: 0.0011 max mem: 33369 +Test: [1100/2573] eta: 0:01:52 time: 0.0736 data: 0.0011 max mem: 33369 +Test: [1200/2573] eta: 0:01:44 time: 0.0737 data: 0.0011 max mem: 33369 +Test: [1300/2573] eta: 0:01:36 time: 0.0737 data: 0.0011 max mem: 33369 +Test: [1400/2573] eta: 0:01:28 time: 0.0721 data: 0.0011 max mem: 33369 +Test: [1500/2573] eta: 0:01:21 time: 0.0737 data: 0.0011 max mem: 33369 +Test: [1600/2573] eta: 0:01:13 time: 0.0770 data: 0.0011 max mem: 33369 +Test: [1700/2573] eta: 0:01:05 time: 0.0721 data: 0.0011 max mem: 33369 +Test: [1800/2573] eta: 0:00:58 time: 0.0754 data: 0.0011 max mem: 33369 +Test: [1900/2573] eta: 0:00:50 time: 0.0721 data: 0.0011 max mem: 33369 +Test: [2000/2573] eta: 0:00:43 time: 0.0737 data: 0.0011 max mem: 33369 +Test: [2100/2573] eta: 0:00:35 time: 0.0752 data: 0.0011 max mem: 33369 +Test: [2200/2573] eta: 0:00:27 time: 0.0752 data: 0.0011 max mem: 33369 +Test: [2300/2573] eta: 0:00:20 time: 0.0753 data: 0.0011 max mem: 33369 +Test: [2400/2573] eta: 0:00:12 time: 0.0703 data: 0.0011 max mem: 33369 +Test: [2500/2573] eta: 0:00:05 time: 0.0735 data: 0.0011 max mem: 33369 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: Total time: 0:03:12 +Final results: +Mean IoU is 62.93 + + precision@0.5 = 70.87 + precision@0.6 = 65.11 + precision@0.7 = 57.68 + precision@0.8 = 45.55 + precision@0.9 = 21.96 + overall IoU = 60.07 + +Average object IoU 62.930358941465705 +Overall IoU 60.06909942626953 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [16] [ 0/1319] eta: 3:13:08 lr: 3.157139575288201e-05 loss: 0.0546 (0.0546) time: 8.7857 data: 1.3307 max mem: 33369 +Epoch: [16] [ 10/1319] eta: 1:09:02 lr: 3.1562419381047834e-05 loss: 0.0537 (0.0571) time: 3.1646 data: 0.1263 max mem: 33369 +Epoch: [16] [ 20/1319] eta: 1:02:49 lr: 3.155344272555071e-05 loss: 0.0563 (0.0599) time: 2.6079 data: 0.0061 max mem: 33369 +Epoch: [16] [ 30/1319] eta: 1:00:27 lr: 3.154446578629201e-05 loss: 0.0568 (0.0608) time: 2.6212 data: 0.0062 max mem: 33369 +Epoch: [16] [ 40/1319] eta: 0:58:57 lr: 3.153548856317304e-05 loss: 0.0520 (0.0575) time: 2.6229 data: 0.0062 max mem: 33369 +Epoch: [16] [ 50/1319] eta: 0:57:54 lr: 3.152651105609501e-05 loss: 0.0435 (0.0549) time: 2.6200 data: 0.0063 max mem: 33369 +Epoch: [16] [ 60/1319] eta: 0:57:11 lr: 3.1517533264959104e-05 loss: 0.0423 (0.0535) time: 2.6439 data: 0.0062 max mem: 33369 +Epoch: [16] [ 70/1319] eta: 0:56:24 lr: 3.150855518966642e-05 loss: 0.0522 (0.0541) time: 2.6369 data: 0.0062 max mem: 33369 +Epoch: [16] [ 80/1319] eta: 0:55:43 lr: 3.1499576830118e-05 loss: 0.0547 (0.0542) time: 2.6136 data: 0.0062 max mem: 33369 +Epoch: [16] [ 90/1319] eta: 0:55:09 lr: 3.14905981862148e-05 loss: 0.0461 (0.0536) time: 2.6331 data: 0.0063 max mem: 33369 +Epoch: [16] [ 100/1319] eta: 0:54:33 lr: 3.1481619257857746e-05 loss: 0.0528 (0.0557) time: 2.6333 data: 0.0062 max mem: 33369 +Epoch: [16] [ 110/1319] eta: 0:53:59 lr: 3.147264004494766e-05 loss: 0.0617 (0.0562) time: 2.6203 data: 0.0062 max mem: 33369 +Epoch: [16] [ 120/1319] eta: 0:53:26 lr: 3.1463660547385324e-05 loss: 0.0572 (0.0566) time: 2.6201 data: 0.0062 max mem: 33369 +Epoch: [16] [ 130/1319] eta: 0:52:54 lr: 3.1454680765071425e-05 loss: 0.0586 (0.0577) time: 2.6180 data: 0.0061 max mem: 33369 +Epoch: [16] [ 140/1319] eta: 0:52:21 lr: 3.1445700697906627e-05 loss: 0.0529 (0.0577) time: 2.6026 data: 0.0061 max mem: 33369 +Epoch: [16] [ 150/1319] eta: 0:51:52 lr: 3.1436720345791495e-05 loss: 0.0553 (0.0589) time: 2.6142 data: 0.0061 max mem: 33369 +Epoch: [16] [ 160/1319] eta: 0:51:23 lr: 3.1427739708626534e-05 loss: 0.0564 (0.0584) time: 2.6315 data: 0.0061 max mem: 33369 +Epoch: [16] [ 170/1319] eta: 0:50:54 lr: 3.141875878631219e-05 loss: 0.0504 (0.0584) time: 2.6286 data: 0.0061 max mem: 33369 +Epoch: [16] [ 180/1319] eta: 0:50:25 lr: 3.140977757874883e-05 loss: 0.0581 (0.0592) time: 2.6238 data: 0.0061 max mem: 33369 +Epoch: [16] [ 190/1319] eta: 0:49:55 lr: 3.140079608583676e-05 loss: 0.0571 (0.0589) time: 2.6084 data: 0.0060 max mem: 33369 +Epoch: [16] [ 200/1319] eta: 0:49:25 lr: 3.1391814307476244e-05 loss: 0.0491 (0.0590) time: 2.5976 data: 0.0060 max mem: 33369 +Epoch: [16] [ 210/1319] eta: 0:48:58 lr: 3.138283224356744e-05 loss: 0.0491 (0.0590) time: 2.6107 data: 0.0060 max mem: 33369 +Epoch: [16] [ 220/1319] eta: 0:48:31 lr: 3.137384989401046e-05 loss: 0.0487 (0.0610) time: 2.6342 data: 0.0060 max mem: 33369 +Epoch: [16] [ 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eta: 0:30:38 lr: 3.1014320525175755e-05 loss: 0.0503 (0.0608) time: 2.6351 data: 0.0060 max mem: 33369 +Epoch: [16] [ 630/1319] eta: 0:30:12 lr: 3.100532637720542e-05 loss: 0.0496 (0.0609) time: 2.6560 data: 0.0060 max mem: 33369 +Epoch: [16] [ 640/1319] eta: 0:29:46 lr: 3.099633193933038e-05 loss: 0.0552 (0.0609) time: 2.6539 data: 0.0060 max mem: 33369 +Epoch: [16] [ 650/1319] eta: 0:29:19 lr: 3.098733721144784e-05 loss: 0.0514 (0.0608) time: 2.6184 data: 0.0061 max mem: 33369 +Epoch: [16] [ 660/1319] eta: 0:28:52 lr: 3.097834219345489e-05 loss: 0.0493 (0.0608) time: 2.6059 data: 0.0060 max mem: 33369 +Epoch: [16] [ 670/1319] eta: 0:28:26 lr: 3.0969346885248574e-05 loss: 0.0479 (0.0607) time: 2.6072 data: 0.0059 max mem: 33369 +Epoch: [16] [ 680/1319] eta: 0:28:00 lr: 3.0960351286725865e-05 loss: 0.0456 (0.0605) time: 2.6106 data: 0.0061 max mem: 33369 +Epoch: [16] [ 690/1319] eta: 0:27:33 lr: 3.0951355397783653e-05 loss: 0.0566 (0.0608) time: 2.6248 data: 0.0063 max mem: 33369 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3.066333298950271e-05 loss: 0.0542 (0.0613) time: 2.6100 data: 0.0059 max mem: 33369 +Epoch: [16] [1020/1319] eta: 0:13:04 lr: 3.065432745841652e-05 loss: 0.0570 (0.0615) time: 2.5871 data: 0.0059 max mem: 33369 +Epoch: [16] [1030/1319] eta: 0:12:38 lr: 3.064532163336335e-05 loss: 0.0681 (0.0616) time: 2.6047 data: 0.0060 max mem: 33369 +Epoch: [16] [1040/1319] eta: 0:12:12 lr: 3.063631551423762e-05 loss: 0.0681 (0.0616) time: 2.6283 data: 0.0059 max mem: 33369 +Epoch: [16] [1050/1319] eta: 0:11:46 lr: 3.062730910093366e-05 loss: 0.0522 (0.0615) time: 2.6474 data: 0.0059 max mem: 33369 +Epoch: [16] [1060/1319] eta: 0:11:19 lr: 3.061830239334574e-05 loss: 0.0481 (0.0614) time: 2.6201 data: 0.0060 max mem: 33369 +Epoch: [16] [1070/1319] eta: 0:10:53 lr: 3.0609295391368055e-05 loss: 0.0587 (0.0615) time: 2.6011 data: 0.0060 max mem: 33369 +Epoch: [16] [1080/1319] eta: 0:10:27 lr: 3.060028809489473e-05 loss: 0.0624 (0.0614) time: 2.6231 data: 0.0060 max mem: 33369 +Epoch: [16] [1090/1319] eta: 0:10:01 lr: 3.059128050381978e-05 loss: 0.0481 (0.0613) time: 2.6309 data: 0.0060 max mem: 33369 +Epoch: [16] [1100/1319] eta: 0:09:34 lr: 3.058227261803723e-05 loss: 0.0506 (0.0614) time: 2.6213 data: 0.0060 max mem: 33369 +Epoch: [16] [1110/1319] eta: 0:09:08 lr: 3.0573264437440946e-05 loss: 0.0580 (0.0614) time: 2.6087 data: 0.0060 max mem: 33369 +Epoch: [16] [1120/1319] eta: 0:08:42 lr: 3.056425596192476e-05 loss: 0.0581 (0.0614) time: 2.6277 data: 0.0060 max mem: 33369 +Epoch: [16] [1130/1319] eta: 0:08:16 lr: 3.0555247191382436e-05 loss: 0.0532 (0.0614) time: 2.6285 data: 0.0059 max mem: 33369 +Epoch: [16] [1140/1319] eta: 0:07:49 lr: 3.054623812570766e-05 loss: 0.0488 (0.0612) time: 2.6128 data: 0.0058 max mem: 33369 +Epoch: [16] [1150/1319] eta: 0:07:23 lr: 3.053722876479403e-05 loss: 0.0529 (0.0613) time: 2.6478 data: 0.0060 max mem: 33369 +Epoch: [16] [1160/1319] eta: 0:06:57 lr: 3.0528219108535084e-05 loss: 0.0542 (0.0612) time: 2.6567 data: 0.0061 max mem: 33369 +Epoch: [16] [1170/1319] eta: 0:06:31 lr: 3.0519209156824297e-05 loss: 0.0641 (0.0613) time: 2.6418 data: 0.0060 max mem: 33369 +Epoch: [16] [1180/1319] eta: 0:06:04 lr: 3.0510198909555044e-05 loss: 0.0657 (0.0613) time: 2.6305 data: 0.0058 max mem: 33369 +Epoch: [16] [1190/1319] eta: 0:05:38 lr: 3.0501188366620653e-05 loss: 0.0520 (0.0612) time: 2.6125 data: 0.0059 max mem: 33369 +Epoch: [16] [1200/1319] eta: 0:05:12 lr: 3.0492177527914355e-05 loss: 0.0566 (0.0613) time: 2.6199 data: 0.0060 max mem: 33369 +Epoch: [16] [1210/1319] eta: 0:04:46 lr: 3.0483166393329327e-05 loss: 0.0533 (0.0612) time: 2.6113 data: 0.0059 max mem: 33369 +Epoch: [16] [1220/1319] eta: 0:04:19 lr: 3.0474154962758662e-05 loss: 0.0511 (0.0612) time: 2.6002 data: 0.0059 max mem: 33369 +Epoch: [16] [1230/1319] eta: 0:03:53 lr: 3.0465143236095372e-05 loss: 0.0508 (0.0613) time: 2.6134 data: 0.0061 max mem: 33369 +Epoch: [16] [1240/1319] eta: 0:03:27 lr: 3.045613121323242e-05 loss: 0.0533 (0.0614) time: 2.6246 data: 0.0059 max mem: 33369 +Epoch: [16] [1250/1319] eta: 0:03:01 lr: 3.044711889406267e-05 loss: 0.0513 (0.0613) time: 2.6154 data: 0.0059 max mem: 33369 +Epoch: [16] [1260/1319] eta: 0:02:34 lr: 3.0438106278478923e-05 loss: 0.0508 (0.0614) time: 2.5755 data: 0.0059 max mem: 33369 +Epoch: [16] [1270/1319] eta: 0:02:08 lr: 3.0429093366373907e-05 loss: 0.0616 (0.0616) time: 2.5875 data: 0.0059 max mem: 33369 +Epoch: [16] [1280/1319] eta: 0:01:42 lr: 3.0420080157640274e-05 loss: 0.0623 (0.0617) time: 2.6086 data: 0.0059 max mem: 33369 +Epoch: [16] [1290/1319] eta: 0:01:16 lr: 3.0411066652170593e-05 loss: 0.0623 (0.0618) time: 2.6141 data: 0.0060 max mem: 33369 +Epoch: [16] [1300/1319] eta: 0:00:49 lr: 3.040205284985739e-05 loss: 0.0603 (0.0618) time: 2.6318 data: 0.0059 max mem: 33369 +Epoch: [16] [1310/1319] eta: 0:00:23 lr: 3.039303875059306e-05 loss: 0.0480 (0.0617) time: 2.6219 data: 0.0058 max mem: 33369 +Epoch: [16] Total time: 0:57:41 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 2:06:19 time: 2.9457 data: 2.8666 max mem: 33369 +Test: [ 100/2573] eta: 0:04:07 time: 0.0711 data: 0.0011 max mem: 33369 +Test: [ 200/2573] eta: 0:03:26 time: 0.0729 data: 0.0011 max mem: 33369 +Test: [ 300/2573] eta: 0:03:06 time: 0.0747 data: 0.0011 max mem: 33369 +Test: [ 400/2573] eta: 0:02:53 time: 0.0748 data: 0.0011 max mem: 33369 +Test: [ 500/2573] eta: 0:02:42 time: 0.0732 data: 0.0011 max mem: 33369 +Test: [ 600/2573] eta: 0:02:33 time: 0.0734 data: 0.0011 max mem: 33369 +Test: [ 700/2573] eta: 0:02:24 time: 0.0734 data: 0.0011 max mem: 33369 +Test: [ 800/2573] eta: 0:02:16 time: 0.0766 data: 0.0011 max mem: 33369 +Test: [ 900/2573] eta: 0:02:08 time: 0.0733 data: 0.0011 max mem: 33369 +Test: [1000/2573] eta: 0:02:00 time: 0.0734 data: 0.0011 max mem: 33369 +Test: [1100/2573] eta: 0:01:52 time: 0.0737 data: 0.0011 max mem: 33369 +Test: [1200/2573] eta: 0:01:44 time: 0.0734 data: 0.0011 max mem: 33369 +Test: [1300/2573] eta: 0:01:36 time: 0.0736 data: 0.0011 max mem: 33369 +Test: [1400/2573] eta: 0:01:28 time: 0.0719 data: 0.0011 max mem: 33369 +Test: [1500/2573] eta: 0:01:21 time: 0.0736 data: 0.0011 max mem: 33369 +Test: [1600/2573] eta: 0:01:13 time: 0.0770 data: 0.0011 max mem: 33369 +Test: [1700/2573] eta: 0:01:05 time: 0.0720 data: 0.0011 max mem: 33369 +Test: [1800/2573] eta: 0:00:58 time: 0.0754 data: 0.0011 max mem: 33369 +Test: [1900/2573] eta: 0:00:50 time: 0.0720 data: 0.0011 max mem: 33369 +Test: [2000/2573] eta: 0:00:42 time: 0.0738 data: 0.0011 max mem: 33369 +Test: [2100/2573] eta: 0:00:35 time: 0.0752 data: 0.0004 max mem: 33369 +Test: [2200/2573] eta: 0:00:27 time: 0.0758 data: 0.0011 max mem: 33369 +Test: [2300/2573] eta: 0:00:20 time: 0.0758 data: 0.0011 max mem: 33369 +Test: [2400/2573] eta: 0:00:12 time: 0.0708 data: 0.0011 max mem: 33369 +Test: [2500/2573] eta: 0:00:05 time: 0.0743 data: 0.0011 max mem: 33369 +Test: Total time: 0:03:12 +Final results: +Mean IoU is 62.87 + + precision@0.5 = 70.77 + precision@0.6 = 65.91 + precision@0.7 = 58.95 + precision@0.8 = 46.81 + precision@0.9 = 22.49 + overall IoU = 60.82 + +Average object IoU 62.86816435896267 +Overall IoU 60.82417678833008 +Better epoch: 16 + +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [17] [ 0/1319] eta: 1:33:36 lr: 3.0384925807273e-05 loss: 0.0494 (0.0494) time: 4.2583 data: 1.5330 max mem: 33369 +Epoch: [17] [ 10/1319] eta: 1:00:13 lr: 3.0375911143504937e-05 loss: 0.0494 (0.0548) time: 2.7608 data: 0.1442 max mem: 33369 +Epoch: [17] [ 20/1319] eta: 0:58:40 lr: 3.0366896182473385e-05 loss: 0.0499 (0.0606) time: 2.6331 data: 0.0056 max mem: 33369 +Epoch: [17] [ 30/1319] eta: 0:57:31 lr: 3.035788092407048e-05 loss: 0.0604 (0.0591) time: 2.6313 data: 0.0060 max mem: 33369 +Epoch: [17] [ 40/1319] eta: 0:56:57 lr: 3.034886536818829e-05 loss: 0.0548 (0.0576) time: 2.6309 data: 0.0062 max mem: 33369 +Epoch: [17] [ 50/1319] eta: 0:56:09 lr: 3.0339849514718806e-05 loss: 0.0496 (0.0569) time: 2.6206 data: 0.0063 max mem: 33369 +Epoch: [17] [ 60/1319] eta: 0:55:34 lr: 3.033083336355392e-05 loss: 0.0427 (0.0554) time: 2.6016 data: 0.0062 max mem: 33369 +Epoch: [17] [ 70/1319] eta: 0:54:58 lr: 3.03218169145855e-05 loss: 0.0415 (0.0550) time: 2.6050 data: 0.0063 max mem: 33369 +Epoch: [17] [ 80/1319] eta: 0:54:31 lr: 3.0312800167705292e-05 loss: 0.0511 (0.0555) time: 2.6140 data: 0.0063 max mem: 33369 +Epoch: [17] [ 90/1319] eta: 0:54:05 lr: 3.030378312280498e-05 loss: 0.0521 (0.0555) time: 2.6384 data: 0.0062 max mem: 33369 +Epoch: [17] [ 100/1319] eta: 0:53:36 lr: 3.0294765779776184e-05 loss: 0.0577 (0.0560) time: 2.6344 data: 0.0063 max mem: 33369 +Epoch: [17] [ 110/1319] eta: 0:53:07 lr: 3.0285748138510444e-05 loss: 0.0532 (0.0562) time: 2.6184 data: 0.0062 max mem: 33369 +Epoch: [17] [ 120/1319] eta: 0:52:38 lr: 3.0276730198899216e-05 loss: 0.0440 (0.0551) time: 2.6108 data: 0.0062 max mem: 33369 +Epoch: [17] [ 130/1319] eta: 0:52:07 lr: 3.0267711960833896e-05 loss: 0.0416 (0.0558) time: 2.5987 data: 0.0062 max mem: 33369 +Epoch: [17] [ 140/1319] eta: 0:51:37 lr: 3.0258693424205785e-05 loss: 0.0516 (0.0563) time: 2.5870 data: 0.0063 max mem: 33369 +Epoch: [17] [ 150/1319] eta: 0:51:09 lr: 3.024967458890613e-05 loss: 0.0516 (0.0561) time: 2.5947 data: 0.0062 max mem: 33369 +Epoch: [17] [ 160/1319] eta: 0:50:41 lr: 3.0240655454826085e-05 loss: 0.0483 (0.0567) time: 2.5972 data: 0.0063 max mem: 33369 +Epoch: [17] [ 170/1319] eta: 0:50:16 lr: 3.023163602185673e-05 loss: 0.0598 (0.0573) time: 2.6245 data: 0.0065 max mem: 33369 +Epoch: [17] [ 180/1319] eta: 0:49:51 lr: 3.022261628988908e-05 loss: 0.0598 (0.0578) time: 2.6499 data: 0.0062 max mem: 33369 +Epoch: [17] [ 190/1319] eta: 0:49:26 lr: 3.0213596258814065e-05 loss: 0.0553 (0.0582) time: 2.6413 data: 0.0061 max mem: 33369 +Epoch: [17] [ 200/1319] eta: 0:48:59 lr: 3.020457592852254e-05 loss: 0.0550 (0.0588) time: 2.6313 data: 0.0061 max mem: 33369 +Epoch: [17] [ 210/1319] eta: 0:48:33 lr: 3.0195555298905282e-05 loss: 0.0550 (0.0587) time: 2.6218 data: 0.0061 max mem: 33369 +Epoch: [17] [ 220/1319] eta: 0:48:05 lr: 3.0186534369853002e-05 loss: 0.0541 (0.0584) time: 2.6117 data: 0.0061 max mem: 33369 +Epoch: [17] [ 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33369 +Epoch: [17] [ 310/1319] eta: 0:44:06 lr: 3.010533251573493e-05 loss: 0.0474 (0.0573) time: 2.6178 data: 0.0062 max mem: 33369 +Epoch: [17] [ 320/1319] eta: 0:43:39 lr: 3.0096308586304355e-05 loss: 0.0541 (0.0575) time: 2.6248 data: 0.0060 max mem: 33369 +Epoch: [17] [ 330/1319] eta: 0:43:13 lr: 3.0087284356231465e-05 loss: 0.0541 (0.0574) time: 2.6204 data: 0.0060 max mem: 33369 +Epoch: [17] [ 340/1319] eta: 0:42:48 lr: 3.0078259825406035e-05 loss: 0.0451 (0.0573) time: 2.6465 data: 0.0061 max mem: 33369 +Epoch: [17] [ 350/1319] eta: 0:42:23 lr: 3.0069234993717783e-05 loss: 0.0451 (0.0571) time: 2.6630 data: 0.0061 max mem: 33369 +Epoch: [17] [ 360/1319] eta: 0:41:57 lr: 3.006020986105632e-05 loss: 0.0498 (0.0571) time: 2.6436 data: 0.0060 max mem: 33369 +Epoch: [17] [ 370/1319] eta: 0:41:30 lr: 3.005118442731122e-05 loss: 0.0493 (0.0570) time: 2.6256 data: 0.0060 max mem: 33369 +Epoch: [17] [ 380/1319] eta: 0:41:05 lr: 3.004215869237195e-05 loss: 0.0404 (0.0566) time: 2.6429 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2.989770588044718e-05 loss: 0.0569 (0.0580) time: 2.6228 data: 0.0062 max mem: 33369 +Epoch: [17] [ 550/1319] eta: 0:33:39 lr: 2.9888675008221372e-05 loss: 0.0651 (0.0584) time: 2.6259 data: 0.0061 max mem: 33369 +Epoch: [17] [ 560/1319] eta: 0:33:12 lr: 2.9879643832798625e-05 loss: 0.0705 (0.0585) time: 2.6093 data: 0.0062 max mem: 33369 +Epoch: [17] [ 570/1319] eta: 0:32:46 lr: 2.987061235406693e-05 loss: 0.0546 (0.0583) time: 2.6063 data: 0.0062 max mem: 33369 +Epoch: [17] [ 580/1319] eta: 0:32:19 lr: 2.98615805719142e-05 loss: 0.0537 (0.0583) time: 2.6261 data: 0.0061 max mem: 33369 +Epoch: [17] [ 590/1319] eta: 0:31:53 lr: 2.9852548486228266e-05 loss: 0.0591 (0.0584) time: 2.6291 data: 0.0061 max mem: 33369 +Epoch: [17] [ 600/1319] eta: 0:31:27 lr: 2.9843516096896873e-05 loss: 0.0571 (0.0583) time: 2.6264 data: 0.0061 max mem: 33369 +Epoch: [17] [ 610/1319] eta: 0:31:00 lr: 2.98344834038077e-05 loss: 0.0503 (0.0582) time: 2.6140 data: 0.0060 max mem: 33369 +Epoch: [17] [ 620/1319] eta: 0:30:34 lr: 2.9825450406848343e-05 loss: 0.0465 (0.0584) time: 2.6127 data: 0.0060 max mem: 33369 +Epoch: [17] [ 630/1319] eta: 0:30:08 lr: 2.981641710590631e-05 loss: 0.0507 (0.0584) time: 2.6369 data: 0.0060 max mem: 33369 +Epoch: [17] [ 640/1319] eta: 0:29:42 lr: 2.9807383500869036e-05 loss: 0.0622 (0.0584) time: 2.6406 data: 0.0060 max mem: 33369 +Epoch: [17] [ 650/1319] eta: 0:29:16 lr: 2.9798349591623877e-05 loss: 0.0634 (0.0584) time: 2.6202 data: 0.0061 max mem: 33369 +Epoch: [17] [ 660/1319] eta: 0:28:50 lr: 2.9789315378058107e-05 loss: 0.0634 (0.0585) time: 2.6372 data: 0.0061 max mem: 33369 +Epoch: [17] [ 670/1319] eta: 0:28:24 lr: 2.978028086005893e-05 loss: 0.0533 (0.0584) time: 2.6558 data: 0.0060 max mem: 33369 +Epoch: [17] [ 680/1319] eta: 0:27:58 lr: 2.977124603751345e-05 loss: 0.0460 (0.0583) time: 2.6544 data: 0.0060 max mem: 33369 +Epoch: [17] [ 690/1319] eta: 0:27:32 lr: 2.9762210910308712e-05 loss: 0.0522 (0.0583) time: 2.6544 data: 0.0060 max mem: 33369 +Epoch: [17] [ 700/1319] eta: 0:27:05 lr: 2.9753175478331675e-05 loss: 0.0527 (0.0582) time: 2.5973 data: 0.0061 max mem: 33369 +Epoch: [17] [ 710/1319] eta: 0:26:38 lr: 2.97441397414692e-05 loss: 0.0509 (0.0583) time: 2.5806 data: 0.0060 max mem: 33369 +Epoch: [17] [ 720/1319] eta: 0:26:12 lr: 2.973510369960809e-05 loss: 0.0509 (0.0583) time: 2.6196 data: 0.0060 max mem: 33369 +Epoch: [17] [ 730/1319] eta: 0:25:46 lr: 2.9726067352635072e-05 loss: 0.0513 (0.0583) time: 2.6238 data: 0.0059 max mem: 33369 +Epoch: [17] [ 740/1319] eta: 0:25:19 lr: 2.971703070043676e-05 loss: 0.0545 (0.0586) time: 2.6051 data: 0.0060 max mem: 33369 +Epoch: [17] [ 750/1319] eta: 0:24:53 lr: 2.970799374289972e-05 loss: 0.0552 (0.0588) time: 2.6007 data: 0.0060 max mem: 33369 +Epoch: [17] [ 760/1319] eta: 0:24:27 lr: 2.9698956479910424e-05 loss: 0.0490 (0.0586) time: 2.6243 data: 0.0061 max mem: 33369 +Epoch: [17] [ 770/1319] eta: 0:24:01 lr: 2.9689918911355265e-05 loss: 0.0545 (0.0588) time: 2.6448 data: 0.0064 max mem: 33369 +Epoch: [17] [ 780/1319] eta: 0:23:34 lr: 2.9680881037120552e-05 loss: 0.0641 (0.0589) time: 2.6244 data: 0.0061 max mem: 33369 +Epoch: [17] [ 790/1319] eta: 0:23:08 lr: 2.9671842857092525e-05 loss: 0.0596 (0.0589) time: 2.5972 data: 0.0060 max mem: 33369 +Epoch: [17] [ 800/1319] eta: 0:22:42 lr: 2.9662804371157326e-05 loss: 0.0562 (0.0589) time: 2.6376 data: 0.0060 max mem: 33369 +Epoch: [17] [ 810/1319] eta: 0:22:16 lr: 2.9653765579201043e-05 loss: 0.0562 (0.0589) time: 2.6512 data: 0.0061 max mem: 33369 +Epoch: [17] [ 820/1319] eta: 0:21:49 lr: 2.964472648110964e-05 loss: 0.0501 (0.0588) time: 2.6135 data: 0.0062 max mem: 33369 +Epoch: [17] [ 830/1319] eta: 0:21:23 lr: 2.963568707676905e-05 loss: 0.0533 (0.0588) time: 2.6408 data: 0.0061 max mem: 33369 +Epoch: [17] [ 840/1319] eta: 0:20:57 lr: 2.962664736606507e-05 loss: 0.0490 (0.0588) time: 2.6584 data: 0.0061 max mem: 33369 +Epoch: [17] [ 850/1319] eta: 0:20:31 lr: 2.961760734888347e-05 loss: 0.0397 (0.0588) time: 2.6388 data: 0.0062 max mem: 33369 +Epoch: [17] [ 860/1319] eta: 0:20:05 lr: 2.96085670251099e-05 loss: 0.0558 (0.0590) time: 2.6170 data: 0.0060 max mem: 33369 +Epoch: [17] [ 870/1319] eta: 0:19:38 lr: 2.959952639462995e-05 loss: 0.0604 (0.0591) time: 2.6133 data: 0.0060 max mem: 33369 +Epoch: [17] [ 880/1319] eta: 0:19:12 lr: 2.9590485457329127e-05 loss: 0.0593 (0.0591) time: 2.6268 data: 0.0061 max mem: 33369 +Epoch: [17] [ 890/1319] eta: 0:18:46 lr: 2.9581444213092834e-05 loss: 0.0514 (0.0592) time: 2.6308 data: 0.0060 max mem: 33369 +Epoch: [17] [ 900/1319] eta: 0:18:20 lr: 2.957240266180642e-05 loss: 0.0580 (0.0593) time: 2.6345 data: 0.0059 max mem: 33369 +Epoch: [17] [ 910/1319] eta: 0:17:54 lr: 2.956336080335514e-05 loss: 0.0596 (0.0593) time: 2.6369 data: 0.0059 max mem: 33369 +Epoch: [17] [ 920/1319] eta: 0:17:27 lr: 2.955431863762416e-05 loss: 0.0523 (0.0595) time: 2.6268 data: 0.0059 max mem: 33369 +Epoch: [17] [ 930/1319] eta: 0:17:01 lr: 2.9545276164498587e-05 loss: 0.0543 (0.0597) time: 2.6188 data: 0.0061 max mem: 33369 +Epoch: [17] [ 940/1319] eta: 0:16:34 lr: 2.953623338386342e-05 loss: 0.0584 (0.0597) time: 2.6063 data: 0.0062 max mem: 33369 +Epoch: [17] [ 950/1319] eta: 0:16:08 lr: 2.9527190295603586e-05 loss: 0.0615 (0.0597) time: 2.5795 data: 0.0063 max mem: 33369 +Epoch: [17] [ 960/1319] eta: 0:15:42 lr: 2.9518146899603932e-05 loss: 0.0570 (0.0597) time: 2.6109 data: 0.0062 max mem: 33369 +Epoch: [17] [ 970/1319] eta: 0:15:16 lr: 2.9509103195749226e-05 loss: 0.0551 (0.0597) time: 2.6210 data: 0.0059 max mem: 33369 +Epoch: [17] [ 980/1319] eta: 0:14:49 lr: 2.9500059183924145e-05 loss: 0.0525 (0.0596) time: 2.6055 data: 0.0060 max mem: 33369 +Epoch: [17] [ 990/1319] eta: 0:14:23 lr: 2.9491014864013282e-05 loss: 0.0417 (0.0595) time: 2.6270 data: 0.0060 max mem: 33369 +Epoch: [17] [1000/1319] eta: 0:13:57 lr: 2.9481970235901164e-05 loss: 0.0466 (0.0597) time: 2.6335 data: 0.0058 max mem: 33369 +Epoch: [17] [1010/1319] eta: 0:13:31 lr: 2.9472925299472214e-05 loss: 0.0513 (0.0596) time: 2.6246 data: 0.0059 max mem: 33369 +Epoch: [17] [1020/1319] eta: 0:13:04 lr: 2.9463880054610792e-05 loss: 0.0499 (0.0596) time: 2.6199 data: 0.0061 max mem: 33369 +Epoch: [17] [1030/1319] eta: 0:12:38 lr: 2.9454834501201163e-05 loss: 0.0587 (0.0598) time: 2.6188 data: 0.0060 max mem: 33369 +Epoch: [17] [1040/1319] eta: 0:12:12 lr: 2.9445788639127496e-05 loss: 0.0650 (0.0599) time: 2.6350 data: 0.0057 max mem: 33369 +Epoch: [17] [1050/1319] eta: 0:11:46 lr: 2.943674246827392e-05 loss: 0.0570 (0.0600) time: 2.6259 data: 0.0057 max mem: 33369 +Epoch: [17] [1060/1319] eta: 0:11:19 lr: 2.9427695988524433e-05 loss: 0.0558 (0.0600) time: 2.5976 data: 0.0059 max mem: 33369 +Epoch: [17] [1070/1319] eta: 0:10:53 lr: 2.941864919976297e-05 loss: 0.0559 (0.0600) time: 2.6059 data: 0.0061 max mem: 33369 +Epoch: [17] [1080/1319] eta: 0:10:27 lr: 2.9409602101873397e-05 loss: 0.0599 (0.0600) time: 2.6082 data: 0.0061 max mem: 33369 +Epoch: [17] [1090/1319] eta: 0:10:00 lr: 2.9400554694739468e-05 loss: 0.0599 (0.0601) time: 2.6165 data: 0.0059 max mem: 33369 +Epoch: [17] [1100/1319] eta: 0:09:34 lr: 2.9391506978244877e-05 loss: 0.0559 (0.0600) time: 2.6224 data: 0.0059 max mem: 33369 +Epoch: [17] [1110/1319] eta: 0:09:08 lr: 2.9382458952273217e-05 loss: 0.0520 (0.0601) time: 2.6152 data: 0.0059 max mem: 33369 +Epoch: [17] [1120/1319] eta: 0:08:42 lr: 2.937341061670802e-05 loss: 0.0621 (0.0602) time: 2.6185 data: 0.0060 max mem: 33369 +Epoch: [17] [1130/1319] eta: 0:08:15 lr: 2.9364361971432715e-05 loss: 0.0621 (0.0602) time: 2.6063 data: 0.0062 max mem: 33369 +Epoch: [17] [1140/1319] eta: 0:07:49 lr: 2.9355313016330638e-05 loss: 0.0596 (0.0602) time: 2.6136 data: 0.0061 max mem: 33369 +Epoch: [17] [1150/1319] eta: 0:07:23 lr: 2.934626375128508e-05 loss: 0.0561 (0.0602) time: 2.6335 data: 0.0058 max mem: 33369 +Epoch: [17] [1160/1319] eta: 0:06:57 lr: 2.93372141761792e-05 loss: 0.0527 (0.0602) time: 2.6293 data: 0.0059 max mem: 33369 +Epoch: [17] [1170/1319] eta: 0:06:30 lr: 2.9328164290896108e-05 loss: 0.0466 (0.0602) time: 2.6355 data: 0.0061 max mem: 33369 +Epoch: [17] [1180/1319] eta: 0:06:04 lr: 2.9319114095318817e-05 loss: 0.0505 (0.0602) time: 2.6283 data: 0.0060 max mem: 33369 +Epoch: [17] [1190/1319] eta: 0:05:38 lr: 2.9310063589330256e-05 loss: 0.0498 (0.0601) time: 2.6181 data: 0.0059 max mem: 33369 +Epoch: [17] [1200/1319] eta: 0:05:12 lr: 2.9301012772813273e-05 loss: 0.0493 (0.0601) time: 2.6439 data: 0.0058 max mem: 33369 +Epoch: [17] [1210/1319] eta: 0:04:46 lr: 2.9291961645650624e-05 loss: 0.0536 (0.0601) time: 2.6466 data: 0.0058 max mem: 33369 +Epoch: [17] [1220/1319] eta: 0:04:19 lr: 2.9282910207724996e-05 loss: 0.0536 (0.0601) time: 2.6290 data: 0.0058 max mem: 33369 +Epoch: [17] [1230/1319] eta: 0:03:53 lr: 2.9273858458918974e-05 loss: 0.0575 (0.0601) time: 2.6469 data: 0.0057 max mem: 33369 +Epoch: [17] [1240/1319] eta: 0:03:27 lr: 2.9264806399115058e-05 loss: 0.0553 (0.0601) time: 2.6870 data: 0.0057 max mem: 33369 +Epoch: [17] [1250/1319] eta: 0:03:01 lr: 2.925575402819568e-05 loss: 0.0510 (0.0600) time: 2.6755 data: 0.0057 max mem: 33369 +Epoch: [17] [1260/1319] eta: 0:02:34 lr: 2.9246701346043183e-05 loss: 0.0542 (0.0600) time: 2.6401 data: 0.0057 max mem: 33369 +Epoch: [17] [1270/1319] eta: 0:02:08 lr: 2.9237648352539803e-05 loss: 0.0514 (0.0600) time: 2.6362 data: 0.0056 max mem: 33369 +Epoch: [17] [1280/1319] eta: 0:01:42 lr: 2.9228595047567713e-05 loss: 0.0587 (0.0600) time: 2.6456 data: 0.0058 max mem: 33369 +Epoch: [17] [1290/1319] eta: 0:01:16 lr: 2.9219541431009008e-05 loss: 0.0570 (0.0600) time: 2.6298 data: 0.0059 max mem: 33369 +Epoch: [17] [1300/1319] eta: 0:00:49 lr: 2.921048750274567e-05 loss: 0.0529 (0.0600) time: 2.6221 data: 0.0058 max mem: 33369 +Epoch: [17] [1310/1319] eta: 0:00:23 lr: 2.9201433262659623e-05 loss: 0.0485 (0.0601) time: 2.6193 data: 0.0059 max mem: 33369 +Epoch: [17] Total time: 0:57:43 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 2:40:47 time: 3.7495 data: 3.6710 max mem: 33369 +Test: [ 100/2573] eta: 0:04:27 time: 0.0717 data: 0.0011 max mem: 33369 +Test: [ 200/2573] eta: 0:03:36 time: 0.0730 data: 0.0011 max mem: 33369 +Test: [ 300/2573] eta: 0:03:12 time: 0.0747 data: 0.0011 max mem: 33369 +Test: [ 400/2573] eta: 0:02:57 time: 0.0748 data: 0.0011 max mem: 33369 +Test: [ 500/2573] eta: 0:02:46 time: 0.0733 data: 0.0011 max mem: 33369 +Test: [ 600/2573] eta: 0:02:36 time: 0.0735 data: 0.0011 max mem: 33369 +Test: [ 700/2573] eta: 0:02:27 time: 0.0735 data: 0.0011 max mem: 33369 +Test: [ 800/2573] eta: 0:02:18 time: 0.0767 data: 0.0011 max mem: 33369 +Test: [ 900/2573] eta: 0:02:09 time: 0.0733 data: 0.0011 max mem: 33369 +Test: [1000/2573] eta: 0:02:01 time: 0.0734 data: 0.0011 max mem: 33369 +Test: [1100/2573] eta: 0:01:53 time: 0.0735 data: 0.0011 max mem: 33369 +Test: [1200/2573] eta: 0:01:45 time: 0.0737 data: 0.0007 max mem: 33369 +Test: [1300/2573] eta: 0:01:37 time: 0.0742 data: 0.0011 max mem: 33369 +Test: [1400/2573] eta: 0:01:29 time: 0.0726 data: 0.0011 max mem: 33369 +Test: [1500/2573] eta: 0:01:21 time: 0.0743 data: 0.0011 max mem: 33369 +Test: [1600/2573] eta: 0:01:14 time: 0.0771 data: 0.0011 max mem: 33369 +Test: [1700/2573] eta: 0:01:06 time: 0.0721 data: 0.0011 max mem: 33369 +Test: [1800/2573] eta: 0:00:58 time: 0.0756 data: 0.0011 max mem: 33369 +Test: [1900/2573] eta: 0:00:50 time: 0.0721 data: 0.0011 max mem: 33369 +Test: [2000/2573] eta: 0:00:43 time: 0.0738 data: 0.0011 max mem: 33369 +Test: [2100/2573] eta: 0:00:35 time: 0.0755 data: 0.0011 max mem: 33369 +Test: [2200/2573] eta: 0:00:28 time: 0.0755 data: 0.0011 max mem: 33369 +Test: [2300/2573] eta: 0:00:20 time: 0.0755 data: 0.0011 max mem: 33369 +Test: [2400/2573] eta: 0:00:13 time: 0.0705 data: 0.0011 max mem: 33369 +Test: [2500/2573] eta: 0:00:05 time: 0.0739 data: 0.0011 max mem: 33369 +Test: Total time: 0:03:13 +Final results: +Mean IoU is 63.31 + + precision@0.5 = 71.51 + precision@0.6 = 65.65 + precision@0.7 = 57.33 + precision@0.8 = 45.94 + precision@0.9 = 21.59 + overall IoU = 61.19 + +Average object IoU 63.31485362135534 +Overall IoU 61.187660217285156 +Better epoch: 17 + +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [18] [ 0/1319] eta: 1:30:28 lr: 2.9193284179876086e-05 loss: 0.0412 (0.0412) time: 4.1158 data: 1.4214 max mem: 33369 +Epoch: [18] [ 10/1319] eta: 1:00:28 lr: 2.9184229347001237e-05 loss: 0.0477 (0.0529) time: 2.7717 data: 0.1342 max mem: 33369 +Epoch: [18] [ 20/1319] eta: 0:58:31 lr: 2.9175174201960736e-05 loss: 0.0505 (0.0589) time: 2.6325 data: 0.0057 max mem: 33369 +Epoch: [18] [ 30/1319] eta: 0:57:28 lr: 2.9166118744636155e-05 loss: 0.0533 (0.0607) time: 2.6227 data: 0.0060 max mem: 33369 +Epoch: [18] [ 40/1319] eta: 0:56:32 lr: 2.9157062974908988e-05 loss: 0.0581 (0.0609) time: 2.5992 data: 0.0062 max mem: 33369 +Epoch: [18] [ 50/1319] eta: 0:55:48 lr: 2.9148006892660646e-05 loss: 0.0523 (0.0607) time: 2.5812 data: 0.0062 max mem: 33369 +Epoch: [18] [ 60/1319] eta: 0:55:22 lr: 2.9138950497772444e-05 loss: 0.0471 (0.0608) time: 2.6125 data: 0.0061 max mem: 33369 +Epoch: [18] [ 70/1319] eta: 0:54:59 lr: 2.9129893790125616e-05 loss: 0.0421 (0.0584) time: 2.6484 data: 0.0061 max mem: 33369 +Epoch: [18] [ 80/1319] eta: 0:54:31 lr: 2.9120836769601318e-05 loss: 0.0410 (0.0574) time: 2.6444 data: 0.0062 max mem: 33369 +Epoch: [18] [ 90/1319] eta: 0:54:07 lr: 2.9111779436080605e-05 loss: 0.0480 (0.0574) time: 2.6459 data: 0.0063 max mem: 33369 +Epoch: [18] [ 100/1319] eta: 0:53:40 lr: 2.910272178944446e-05 loss: 0.0457 (0.0565) time: 2.6485 data: 0.0062 max mem: 33369 +Epoch: [18] [ 110/1319] eta: 0:53:11 lr: 2.9093663829573763e-05 loss: 0.0464 (0.0573) time: 2.6294 data: 0.0062 max mem: 33369 +Epoch: [18] [ 120/1319] eta: 0:52:41 lr: 2.9084605556349322e-05 loss: 0.0479 (0.0572) time: 2.6091 data: 0.0062 max mem: 33369 +Epoch: [18] [ 130/1319] eta: 0:52:17 lr: 2.9075546969651845e-05 loss: 0.0484 (0.0567) time: 2.6332 data: 0.0061 max mem: 33369 +Epoch: [18] [ 140/1319] eta: 0:51:51 lr: 2.906648806936197e-05 loss: 0.0493 (0.0572) time: 2.6546 data: 0.0060 max mem: 33369 +Epoch: [18] [ 150/1319] eta: 0:51:27 lr: 2.9057428855360237e-05 loss: 0.0471 (0.0570) time: 2.6530 data: 0.0059 max mem: 33369 +Epoch: [18] [ 160/1319] eta: 0:50:55 lr: 2.9048369327527098e-05 loss: 0.0442 (0.0566) time: 2.6170 data: 0.0060 max mem: 33369 +Epoch: [18] [ 170/1319] eta: 0:50:29 lr: 2.903930948574293e-05 loss: 0.0432 (0.0564) time: 2.6031 data: 0.0062 max mem: 33369 +Epoch: [18] [ 180/1319] eta: 0:50:03 lr: 2.9030249329888e-05 loss: 0.0430 (0.0564) time: 2.6390 data: 0.0063 max mem: 33369 +Epoch: [18] [ 190/1319] eta: 0:49:36 lr: 2.9021188859842518e-05 loss: 0.0496 (0.0563) time: 2.6322 data: 0.0063 max mem: 33369 +Epoch: [18] [ 200/1319] eta: 0:49:08 lr: 2.9012128075486583e-05 loss: 0.0504 (0.0559) time: 2.6215 data: 0.0062 max mem: 33369 +Epoch: [18] [ 210/1319] eta: 0:48:41 lr: 2.900306697670022e-05 loss: 0.0487 (0.0558) time: 2.6205 data: 0.0060 max mem: 33369 +Epoch: [18] [ 220/1319] eta: 0:48:14 lr: 2.8994005563363352e-05 loss: 0.0522 (0.0557) time: 2.6149 data: 0.0063 max mem: 33369 +Epoch: [18] [ 230/1319] eta: 0:47:45 lr: 2.8984943835355838e-05 loss: 0.0544 (0.0560) time: 2.5992 data: 0.0065 max mem: 33369 +Epoch: [18] [ 240/1319] eta: 0:47:16 lr: 2.8975881792557412e-05 loss: 0.0527 (0.0559) time: 2.5754 data: 0.0063 max mem: 33369 +Epoch: [18] [ 250/1319] eta: 0:46:48 lr: 2.8966819434847762e-05 loss: 0.0486 (0.0557) time: 2.5797 data: 0.0063 max mem: 33369 +Epoch: [18] [ 260/1319] eta: 0:46:22 lr: 2.8957756762106468e-05 loss: 0.0486 (0.0556) time: 2.6185 data: 0.0065 max mem: 33369 +Epoch: [18] [ 270/1319] eta: 0:45:56 lr: 2.8948693774213014e-05 loss: 0.0436 (0.0554) time: 2.6322 data: 0.0063 max mem: 33369 +Epoch: [18] [ 280/1319] eta: 0:45:29 lr: 2.8939630471046815e-05 loss: 0.0506 (0.0554) time: 2.6130 data: 0.0060 max mem: 33369 +Epoch: [18] [ 290/1319] eta: 0:45:00 lr: 2.893056685248718e-05 loss: 0.0506 (0.0553) time: 2.5733 data: 0.0064 max mem: 33369 +Epoch: [18] [ 300/1319] eta: 0:44:34 lr: 2.892150291841334e-05 loss: 0.0415 (0.0554) time: 2.5973 data: 0.0065 max mem: 33369 +Epoch: [18] [ 310/1319] eta: 0:44:07 lr: 2.891243866870445e-05 loss: 0.0490 (0.0554) time: 2.6265 data: 0.0062 max mem: 33369 +Epoch: [18] [ 320/1319] eta: 0:43:40 lr: 2.8903374103239537e-05 loss: 0.0458 (0.0552) time: 2.6034 data: 0.0061 max mem: 33369 +Epoch: [18] [ 330/1319] eta: 0:43:14 lr: 2.889430922189758e-05 loss: 0.0458 (0.0550) time: 2.6099 data: 0.0062 max mem: 33369 +Epoch: [18] [ 340/1319] eta: 0:42:49 lr: 2.8885244024557463e-05 loss: 0.0461 (0.0547) time: 2.6379 data: 0.0061 max mem: 33369 +Epoch: [18] [ 350/1319] eta: 0:42:22 lr: 2.8876178511097952e-05 loss: 0.0455 (0.0550) time: 2.6384 data: 0.0062 max mem: 33369 +Epoch: [18] [ 360/1319] eta: 0:41:56 lr: 2.886711268139775e-05 loss: 0.0514 (0.0549) time: 2.6200 data: 0.0063 max mem: 33369 +Epoch: [18] [ 370/1319] eta: 0:41:29 lr: 2.8858046535335475e-05 loss: 0.0524 (0.0551) time: 2.6107 data: 0.0063 max mem: 33369 +Epoch: [18] [ 380/1319] eta: 0:41:04 lr: 2.8848980072789644e-05 loss: 0.0498 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2.877643696440781e-05 loss: 0.0494 (0.0560) time: 2.6041 data: 0.0062 max mem: 33369 +Epoch: [18] [ 470/1319] eta: 0:37:06 lr: 2.876736764802861e-05 loss: 0.0570 (0.0563) time: 2.6174 data: 0.0063 max mem: 33369 +Epoch: [18] [ 480/1319] eta: 0:36:39 lr: 2.8758298013946133e-05 loss: 0.0617 (0.0562) time: 2.6136 data: 0.0061 max mem: 33369 +Epoch: [18] [ 490/1319] eta: 0:36:12 lr: 2.8749228062037915e-05 loss: 0.0551 (0.0562) time: 2.5932 data: 0.0059 max mem: 33369 +Epoch: [18] [ 500/1319] eta: 0:35:46 lr: 2.87401577921814e-05 loss: 0.0550 (0.0561) time: 2.5922 data: 0.0061 max mem: 33369 +Epoch: [18] [ 510/1319] eta: 0:35:19 lr: 2.8731087204253943e-05 loss: 0.0507 (0.0561) time: 2.6052 data: 0.0061 max mem: 33369 +Epoch: [18] [ 520/1319] eta: 0:34:53 lr: 2.8722016298132803e-05 loss: 0.0490 (0.0562) time: 2.5964 data: 0.0060 max mem: 33369 +Epoch: [18] [ 530/1319] eta: 0:34:26 lr: 2.8712945073695164e-05 loss: 0.0546 (0.0564) time: 2.5898 data: 0.0061 max mem: 33369 +Epoch: [18] [ 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data: 0.0058 max mem: 33369 +Epoch: [18] [ 700/1319] eta: 0:27:00 lr: 2.8558685436370514e-05 loss: 0.0431 (0.0571) time: 2.6370 data: 0.0058 max mem: 33369 +Epoch: [18] [ 710/1319] eta: 0:26:34 lr: 2.854960846112869e-05 loss: 0.0459 (0.0570) time: 2.6443 data: 0.0060 max mem: 33369 +Epoch: [18] [ 720/1319] eta: 0:26:08 lr: 2.8540531165219343e-05 loss: 0.0492 (0.0571) time: 2.6458 data: 0.0061 max mem: 33369 +Epoch: [18] [ 730/1319] eta: 0:25:43 lr: 2.8531453548517806e-05 loss: 0.0504 (0.0572) time: 2.6527 data: 0.0060 max mem: 33369 +Epoch: [18] [ 740/1319] eta: 0:25:16 lr: 2.8522375610899337e-05 loss: 0.0516 (0.0572) time: 2.6331 data: 0.0061 max mem: 33369 +Epoch: [18] [ 750/1319] eta: 0:24:50 lr: 2.8513297352239087e-05 loss: 0.0512 (0.0571) time: 2.6128 data: 0.0061 max mem: 33369 +Epoch: [18] [ 760/1319] eta: 0:24:24 lr: 2.850421877241213e-05 loss: 0.0513 (0.0571) time: 2.5971 data: 0.0060 max mem: 33369 +Epoch: [18] [ 770/1319] eta: 0:23:57 lr: 2.8495139871293436e-05 loss: 0.0522 (0.0572) time: 2.5763 data: 0.0061 max mem: 33369 +Epoch: [18] [ 780/1319] eta: 0:23:31 lr: 2.8486060648757875e-05 loss: 0.0522 (0.0573) time: 2.6047 data: 0.0060 max mem: 33369 +Epoch: [18] [ 790/1319] eta: 0:23:05 lr: 2.8476981104680245e-05 loss: 0.0532 (0.0573) time: 2.6220 data: 0.0060 max mem: 33369 +Epoch: [18] [ 800/1319] eta: 0:22:38 lr: 2.846790123893523e-05 loss: 0.0505 (0.0573) time: 2.5996 data: 0.0060 max mem: 33369 +Epoch: [18] [ 810/1319] eta: 0:22:12 lr: 2.8458821051397444e-05 loss: 0.0480 (0.0574) time: 2.5970 data: 0.0059 max mem: 33369 +Epoch: [18] [ 820/1319] eta: 0:21:46 lr: 2.844974054194138e-05 loss: 0.0491 (0.0574) time: 2.6510 data: 0.0059 max mem: 33369 +Epoch: [18] [ 830/1319] eta: 0:21:20 lr: 2.844065971044146e-05 loss: 0.0496 (0.0574) time: 2.6569 data: 0.0062 max mem: 33369 +Epoch: [18] [ 840/1319] eta: 0:20:54 lr: 2.8431578556772e-05 loss: 0.0550 (0.0574) time: 2.6335 data: 0.0061 max mem: 33369 +Epoch: [18] [ 850/1319] eta: 0:20:28 lr: 2.8422497080807237e-05 loss: 0.0498 (0.0572) time: 2.6270 data: 0.0060 max mem: 33369 +Epoch: [18] [ 860/1319] eta: 0:20:02 lr: 2.8413415282421285e-05 loss: 0.0451 (0.0572) time: 2.6064 data: 0.0060 max mem: 33369 +Epoch: [18] [ 870/1319] eta: 0:19:36 lr: 2.840433316148819e-05 loss: 0.0479 (0.0572) time: 2.6281 data: 0.0059 max mem: 33369 +Epoch: [18] [ 880/1319] eta: 0:19:10 lr: 2.8395250717881906e-05 loss: 0.0462 (0.0572) time: 2.6453 data: 0.0058 max mem: 33369 +Epoch: [18] [ 890/1319] eta: 0:18:44 lr: 2.8386167951476273e-05 loss: 0.0482 (0.0573) time: 2.6454 data: 0.0058 max mem: 33369 +Epoch: [18] [ 900/1319] eta: 0:18:17 lr: 2.8377084862145048e-05 loss: 0.0518 (0.0572) time: 2.6412 data: 0.0058 max mem: 33369 +Epoch: [18] [ 910/1319] eta: 0:17:51 lr: 2.8368001449761894e-05 loss: 0.0501 (0.0573) time: 2.6199 data: 0.0058 max mem: 33369 +Epoch: [18] [ 920/1319] eta: 0:17:25 lr: 2.8358917714200377e-05 loss: 0.0497 (0.0572) time: 2.6136 data: 0.0058 max mem: 33369 +Epoch: [18] [ 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33369 +Epoch: [18] [1010/1319] eta: 0:13:29 lr: 2.8277149530212353e-05 loss: 0.0513 (0.0576) time: 2.6239 data: 0.0061 max mem: 33369 +Epoch: [18] [1020/1319] eta: 0:13:03 lr: 2.8268062555892616e-05 loss: 0.0455 (0.0575) time: 2.6374 data: 0.0060 max mem: 33369 +Epoch: [18] [1030/1319] eta: 0:12:37 lr: 2.82589752569975e-05 loss: 0.0428 (0.0574) time: 2.6529 data: 0.0059 max mem: 33369 +Epoch: [18] [1040/1319] eta: 0:12:11 lr: 2.8249887633399437e-05 loss: 0.0421 (0.0574) time: 2.6513 data: 0.0059 max mem: 33369 +Epoch: [18] [1050/1319] eta: 0:11:44 lr: 2.8240799684970753e-05 loss: 0.0455 (0.0574) time: 2.6221 data: 0.0058 max mem: 33369 +Epoch: [18] [1060/1319] eta: 0:11:18 lr: 2.8231711411583693e-05 loss: 0.0479 (0.0574) time: 2.6165 data: 0.0060 max mem: 33369 +Epoch: [18] [1070/1319] eta: 0:10:52 lr: 2.8222622813110382e-05 loss: 0.0492 (0.0574) time: 2.6221 data: 0.0062 max mem: 33369 +Epoch: [18] [1080/1319] eta: 0:10:26 lr: 2.821353388942287e-05 loss: 0.0520 (0.0574) time: 2.6074 data: 0.0060 max mem: 33369 +Epoch: [18] [1090/1319] eta: 0:10:00 lr: 2.820444464039311e-05 loss: 0.0544 (0.0574) time: 2.5919 data: 0.0059 max mem: 33369 +Epoch: [18] [1100/1319] eta: 0:09:33 lr: 2.819535506589294e-05 loss: 0.0501 (0.0574) time: 2.5876 data: 0.0059 max mem: 33369 +Epoch: [18] [1110/1319] eta: 0:09:07 lr: 2.8186265165794125e-05 loss: 0.0534 (0.0573) time: 2.6192 data: 0.0058 max mem: 33369 +Epoch: [18] [1120/1319] eta: 0:08:41 lr: 2.817717493996831e-05 loss: 0.0525 (0.0573) time: 2.6641 data: 0.0059 max mem: 33369 +Epoch: [18] [1130/1319] eta: 0:08:15 lr: 2.816808438828707e-05 loss: 0.0554 (0.0574) time: 2.6530 data: 0.0061 max mem: 33369 +Epoch: [18] [1140/1319] eta: 0:07:49 lr: 2.8158993510621856e-05 loss: 0.0505 (0.0573) time: 2.6458 data: 0.0062 max mem: 33369 +Epoch: [18] [1150/1319] eta: 0:07:23 lr: 2.814990230684405e-05 loss: 0.0492 (0.0572) time: 2.6575 data: 0.0060 max mem: 33369 +Epoch: [18] [1160/1319] eta: 0:06:56 lr: 2.814081077682491e-05 loss: 0.0492 (0.0572) time: 2.6413 data: 0.0057 max mem: 33369 +Epoch: [18] [1170/1319] eta: 0:06:30 lr: 2.8131718920435623e-05 loss: 0.0471 (0.0572) time: 2.6165 data: 0.0057 max mem: 33369 +Epoch: [18] [1180/1319] eta: 0:06:04 lr: 2.812262673754726e-05 loss: 0.0525 (0.0572) time: 2.5954 data: 0.0058 max mem: 33369 +Epoch: [18] [1190/1319] eta: 0:05:38 lr: 2.8113534228030784e-05 loss: 0.0460 (0.0571) time: 2.5829 data: 0.0059 max mem: 33369 +Epoch: [18] [1200/1319] eta: 0:05:11 lr: 2.8104441391757102e-05 loss: 0.0474 (0.0571) time: 2.6012 data: 0.0061 max mem: 33369 +Epoch: [18] [1210/1319] eta: 0:04:45 lr: 2.809534822859698e-05 loss: 0.0528 (0.0572) time: 2.6457 data: 0.0061 max mem: 33369 +Epoch: [18] [1220/1319] eta: 0:04:19 lr: 2.8086254738421114e-05 loss: 0.0567 (0.0572) time: 2.6351 data: 0.0060 max mem: 33369 +Epoch: [18] [1230/1319] eta: 0:03:53 lr: 2.8077160921100087e-05 loss: 0.0482 (0.0571) time: 2.5841 data: 0.0062 max mem: 33369 +Epoch: [18] [1240/1319] eta: 0:03:27 lr: 2.8068066776504393e-05 loss: 0.0390 (0.0571) time: 2.5997 data: 0.0061 max mem: 33369 +Epoch: [18] [1250/1319] eta: 0:03:00 lr: 2.8058972304504428e-05 loss: 0.0488 (0.0571) time: 2.6212 data: 0.0061 max mem: 33369 +Epoch: [18] [1260/1319] eta: 0:02:34 lr: 2.8049877504970483e-05 loss: 0.0455 (0.0571) time: 2.5979 data: 0.0060 max mem: 33369 +Epoch: [18] [1270/1319] eta: 0:02:08 lr: 2.8040782377772763e-05 loss: 0.0416 (0.0570) time: 2.6100 data: 0.0059 max mem: 33369 +Epoch: [18] [1280/1319] eta: 0:01:42 lr: 2.803168692278136e-05 loss: 0.0438 (0.0569) time: 2.6416 data: 0.0060 max mem: 33369 +Epoch: [18] [1290/1319] eta: 0:01:15 lr: 2.8022591139866265e-05 loss: 0.0491 (0.0570) time: 2.6389 data: 0.0060 max mem: 33369 +Epoch: [18] [1300/1319] eta: 0:00:49 lr: 2.80134950288974e-05 loss: 0.0491 (0.0569) time: 2.6266 data: 0.0060 max mem: 33369 +Epoch: [18] [1310/1319] eta: 0:00:23 lr: 2.800439858974456e-05 loss: 0.0513 (0.0570) time: 2.6210 data: 0.0059 max mem: 33369 +Epoch: [18] Total time: 0:57:37 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 2:00:00 time: 2.7985 data: 2.5678 max mem: 33369 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 100/2573] eta: 0:04:04 time: 0.0717 data: 0.0011 max mem: 33369 +Test: [ 200/2573] eta: 0:03:25 time: 0.0734 data: 0.0011 max mem: 33369 +Test: [ 300/2573] eta: 0:03:05 time: 0.0750 data: 0.0011 max mem: 33369 +Test: [ 400/2573] eta: 0:02:53 time: 0.0752 data: 0.0011 max mem: 33369 +Test: [ 500/2573] eta: 0:02:42 time: 0.0735 data: 0.0011 max mem: 33369 +Test: [ 600/2573] eta: 0:02:33 time: 0.0736 data: 0.0011 max mem: 33369 +Test: [ 700/2573] eta: 0:02:25 time: 0.0737 data: 0.0011 max mem: 33369 +Test: [ 800/2573] eta: 0:02:16 time: 0.0770 data: 0.0011 max mem: 33369 +Test: [ 900/2573] eta: 0:02:08 time: 0.0737 data: 0.0011 max mem: 33369 +Test: [1000/2573] eta: 0:02:00 time: 0.0738 data: 0.0011 max mem: 33369 +Test: [1100/2573] eta: 0:01:52 time: 0.0738 data: 0.0011 max mem: 33369 +Test: [1200/2573] eta: 0:01:44 time: 0.0734 data: 0.0008 max mem: 33369 +Test: [1300/2573] eta: 0:01:36 time: 0.0738 data: 0.0011 max mem: 33369 +Test: [1400/2573] eta: 0:01:28 time: 0.0722 data: 0.0011 max mem: 33369 +Test: [1500/2573] eta: 0:01:21 time: 0.0740 data: 0.0011 max mem: 33369 +Test: [1600/2573] eta: 0:01:13 time: 0.0772 data: 0.0011 max mem: 33369 +Test: [1700/2573] eta: 0:01:05 time: 0.0723 data: 0.0011 max mem: 33369 +Test: [1800/2573] eta: 0:00:58 time: 0.0755 data: 0.0011 max mem: 33369 +Test: [1900/2573] eta: 0:00:50 time: 0.0723 data: 0.0011 max mem: 33369 +Test: [2000/2573] eta: 0:00:43 time: 0.0738 data: 0.0011 max mem: 33369 +Test: [2100/2573] eta: 0:00:35 time: 0.0755 data: 0.0011 max mem: 33369 +Test: [2200/2573] eta: 0:00:27 time: 0.0756 data: 0.0011 max mem: 33369 +Test: [2300/2573] eta: 0:00:20 time: 0.0755 data: 0.0011 max mem: 33369 +Test: [2400/2573] eta: 0:00:12 time: 0.0705 data: 0.0011 max mem: 33369 +Test: [2500/2573] eta: 0:00:05 time: 0.0738 data: 0.0011 max mem: 33369 +Test: Total time: 0:03:12 +Final results: +Mean IoU is 63.10 + + precision@0.5 = 70.73 + precision@0.6 = 65.11 + precision@0.7 = 58.50 + precision@0.8 = 47.10 + precision@0.9 = 22.94 + overall IoU = 60.67 + +Average object IoU 63.10055268876963 +Overall IoU 60.67268371582031 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [19] [ 0/1319] eta: 3:22:22 lr: 2.7996211513802005e-05 loss: 0.0364 (0.0364) time: 9.2055 data: 2.1805 max mem: 33369 +Epoch: [19] [ 10/1319] eta: 1:09:59 lr: 2.7987114450740563e-05 loss: 0.0472 (0.0461) time: 3.2082 data: 0.2036 max mem: 33369 +Epoch: [19] [ 20/1319] eta: 1:03:58 lr: 2.7978017059117013e-05 loss: 0.0472 (0.0506) time: 2.6427 data: 0.0058 max mem: 33369 +Epoch: [19] [ 30/1319] eta: 1:01:18 lr: 2.7968919338800786e-05 loss: 0.0527 (0.0532) time: 2.6590 data: 0.0060 max mem: 33369 +Epoch: [19] [ 40/1319] eta: 0:59:38 lr: 2.7959821289661182e-05 loss: 0.0527 (0.0561) time: 2.6332 data: 0.0063 max mem: 33369 +Epoch: [19] [ 50/1319] eta: 0:58:28 lr: 2.795072291156743e-05 loss: 0.0534 (0.0564) time: 2.6265 data: 0.0063 max mem: 33369 +Epoch: [19] [ 60/1319] eta: 0:57:34 lr: 2.7941624204388656e-05 loss: 0.0532 (0.0564) time: 2.6336 data: 0.0063 max mem: 33369 +Epoch: [19] [ 70/1319] eta: 0:56:46 lr: 2.7932525167993873e-05 loss: 0.0471 (0.0544) time: 2.6319 data: 0.0062 max mem: 33369 +Epoch: [19] [ 80/1319] eta: 0:56:02 lr: 2.7923425802252002e-05 loss: 0.0382 (0.0534) time: 2.6208 data: 0.0062 max mem: 33369 +Epoch: [19] [ 90/1319] eta: 0:55:20 lr: 2.791432610703186e-05 loss: 0.0424 (0.0541) time: 2.6097 data: 0.0061 max mem: 33369 +Epoch: [19] [ 100/1319] eta: 0:54:45 lr: 2.790522608220219e-05 loss: 0.0424 (0.0547) time: 2.6193 data: 0.0062 max mem: 33369 +Epoch: [19] [ 110/1319] eta: 0:54:12 lr: 2.789612572763159e-05 loss: 0.0434 (0.0544) time: 2.6380 data: 0.0062 max mem: 33369 +Epoch: [19] [ 120/1319] eta: 0:53:41 lr: 2.7887025043188598e-05 loss: 0.0419 (0.0535) time: 2.6480 data: 0.0062 max mem: 33369 +Epoch: [19] [ 130/1319] eta: 0:53:10 lr: 2.7877924028741625e-05 loss: 0.0448 (0.0533) time: 2.6458 data: 0.0061 max mem: 33369 +Epoch: [19] [ 140/1319] eta: 0:52:39 lr: 2.7868822684159008e-05 loss: 0.0448 (0.0526) time: 2.6323 data: 0.0061 max mem: 33369 +Epoch: [19] [ 150/1319] eta: 0:52:06 lr: 2.7859721009308947e-05 loss: 0.0424 (0.0523) time: 2.6200 data: 0.0064 max mem: 33369 +Epoch: [19] [ 160/1319] eta: 0:51:36 lr: 2.7850619004059574e-05 loss: 0.0400 (0.0538) time: 2.6187 data: 0.0064 max mem: 33369 +Epoch: [19] [ 170/1319] eta: 0:51:05 lr: 2.7841516668278917e-05 loss: 0.0431 (0.0536) time: 2.6168 data: 0.0061 max mem: 33369 +Epoch: [19] [ 180/1319] eta: 0:50:36 lr: 2.7832414001834883e-05 loss: 0.0482 (0.0538) time: 2.6198 data: 0.0061 max mem: 33369 +Epoch: [19] [ 190/1319] eta: 0:50:09 lr: 2.782331100459529e-05 loss: 0.0482 (0.0538) time: 2.6438 data: 0.0062 max mem: 33369 +Epoch: [19] [ 200/1319] eta: 0:49:40 lr: 2.781420767642787e-05 loss: 0.0445 (0.0534) time: 2.6376 data: 0.0063 max mem: 33369 +Epoch: [19] [ 210/1319] eta: 0:49:11 lr: 2.7805104017200224e-05 loss: 0.0467 (0.0532) time: 2.6182 data: 0.0063 max mem: 33369 +Epoch: [19] [ 220/1319] eta: 0:48:42 lr: 2.779600002677987e-05 loss: 0.0513 (0.0532) time: 2.6222 data: 0.0063 max mem: 33369 +Epoch: [19] [ 230/1319] eta: 0:48:15 lr: 2.778689570503424e-05 loss: 0.0522 (0.0532) time: 2.6320 data: 0.0062 max mem: 33369 +Epoch: [19] [ 240/1319] eta: 0:47:48 lr: 2.7777791051830626e-05 loss: 0.0475 (0.0530) time: 2.6485 data: 0.0061 max mem: 33369 +Epoch: [19] [ 250/1319] eta: 0:47:20 lr: 2.7768686067036253e-05 loss: 0.0453 (0.0530) time: 2.6462 data: 0.0062 max mem: 33369 +Epoch: [19] [ 260/1319] eta: 0:46:54 lr: 2.775958075051822e-05 loss: 0.0512 (0.0530) time: 2.6453 data: 0.0063 max mem: 33369 +Epoch: [19] [ 270/1319] eta: 0:46:28 lr: 2.7750475102143547e-05 loss: 0.0467 (0.0530) time: 2.6644 data: 0.0062 max mem: 33369 +Epoch: [19] [ 280/1319] eta: 0:46:01 lr: 2.7741369121779126e-05 loss: 0.0438 (0.0528) time: 2.6596 data: 0.0060 max mem: 33369 +Epoch: [19] [ 290/1319] eta: 0:45:33 lr: 2.7732262809291776e-05 loss: 0.0433 (0.0527) time: 2.6346 data: 0.0061 max mem: 33369 +Epoch: [19] [ 300/1319] eta: 0:45:05 lr: 2.7723156164548194e-05 loss: 0.0471 (0.0529) time: 2.6216 data: 0.0063 max mem: 33369 +Epoch: [19] [ 310/1319] eta: 0:44:37 lr: 2.771404918741497e-05 loss: 0.0542 (0.0534) time: 2.6136 data: 0.0063 max mem: 33369 +Epoch: [19] [ 320/1319] eta: 0:44:09 lr: 2.7704941877758615e-05 loss: 0.0485 (0.0532) time: 2.6022 data: 0.0060 max mem: 33369 +Epoch: [19] [ 330/1319] eta: 0:43:41 lr: 2.7695834235445526e-05 loss: 0.0412 (0.0529) time: 2.6003 data: 0.0060 max mem: 33369 +Epoch: [19] [ 340/1319] eta: 0:43:13 lr: 2.7686726260341988e-05 loss: 0.0464 (0.0528) time: 2.6104 data: 0.0062 max mem: 33369 +Epoch: [19] [ 350/1319] eta: 0:42:46 lr: 2.7677617952314193e-05 loss: 0.0463 (0.0529) time: 2.6253 data: 0.0061 max mem: 33369 +Epoch: [19] [ 360/1319] eta: 0:42:20 lr: 2.7668509311228242e-05 loss: 0.0463 (0.0532) time: 2.6343 data: 0.0060 max mem: 33369 +Epoch: [19] [ 370/1319] eta: 0:41:53 lr: 2.7659400336950098e-05 loss: 0.0459 (0.0535) time: 2.6432 data: 0.0061 max mem: 33369 +Epoch: [19] [ 380/1319] eta: 0:41:26 lr: 2.765029102934566e-05 loss: 0.0398 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data: 0.0062 max mem: 33369 +Epoch: [19] [ 700/1319] eta: 0:27:12 lr: 2.735861638171675e-05 loss: 0.0470 (0.0545) time: 2.6123 data: 0.0063 max mem: 33369 +Epoch: [19] [ 710/1319] eta: 0:26:45 lr: 2.7349495998423098e-05 loss: 0.0473 (0.0545) time: 2.5968 data: 0.0062 max mem: 33369 +Epoch: [19] [ 720/1319] eta: 0:26:19 lr: 2.7340375277181003e-05 loss: 0.0495 (0.0544) time: 2.6032 data: 0.0061 max mem: 33369 +Epoch: [19] [ 730/1319] eta: 0:25:52 lr: 2.733125421785267e-05 loss: 0.0495 (0.0545) time: 2.6122 data: 0.0060 max mem: 33369 +Epoch: [19] [ 740/1319] eta: 0:25:26 lr: 2.7322132820300196e-05 loss: 0.0497 (0.0545) time: 2.6270 data: 0.0060 max mem: 33369 +Epoch: [19] [ 750/1319] eta: 0:24:59 lr: 2.731301108438557e-05 loss: 0.0498 (0.0546) time: 2.6321 data: 0.0060 max mem: 33369 +Epoch: [19] [ 760/1319] eta: 0:24:33 lr: 2.7303889009970667e-05 loss: 0.0477 (0.0545) time: 2.6296 data: 0.0060 max mem: 33369 +Epoch: [19] [ 770/1319] eta: 0:24:06 lr: 2.7294766596917266e-05 loss: 0.0475 (0.0546) time: 2.6347 data: 0.0059 max mem: 33369 +Epoch: [19] [ 780/1319] eta: 0:23:40 lr: 2.7285643845087027e-05 loss: 0.0558 (0.0545) time: 2.6445 data: 0.0059 max mem: 33369 +Epoch: [19] [ 790/1319] eta: 0:23:14 lr: 2.7276520754341512e-05 loss: 0.0470 (0.0544) time: 2.6361 data: 0.0059 max mem: 33369 +Epoch: [19] [ 800/1319] eta: 0:22:47 lr: 2.726739732454216e-05 loss: 0.0438 (0.0543) time: 2.6109 data: 0.0058 max mem: 33369 +Epoch: [19] [ 810/1319] eta: 0:22:21 lr: 2.7258273555550322e-05 loss: 0.0451 (0.0542) time: 2.6330 data: 0.0057 max mem: 33369 +Epoch: [19] [ 820/1319] eta: 0:21:55 lr: 2.7249149447227223e-05 loss: 0.0455 (0.0542) time: 2.6430 data: 0.0057 max mem: 33369 +Epoch: [19] [ 830/1319] eta: 0:21:28 lr: 2.7240024999433987e-05 loss: 0.0502 (0.0543) time: 2.6353 data: 0.0058 max mem: 33369 +Epoch: [19] [ 840/1319] eta: 0:21:02 lr: 2.723090021203163e-05 loss: 0.0476 (0.0543) time: 2.6159 data: 0.0058 max mem: 33369 +Epoch: [19] [ 850/1319] eta: 0:20:35 lr: 2.7221775084881062e-05 loss: 0.0502 (0.0543) time: 2.6146 data: 0.0059 max mem: 33369 +Epoch: [19] [ 860/1319] eta: 0:20:09 lr: 2.7212649617843082e-05 loss: 0.0530 (0.0543) time: 2.6244 data: 0.0058 max mem: 33369 +Epoch: [19] [ 870/1319] eta: 0:19:43 lr: 2.7203523810778376e-05 loss: 0.0568 (0.0545) time: 2.6310 data: 0.0058 max mem: 33369 +Epoch: [19] [ 880/1319] eta: 0:19:16 lr: 2.7194397663547522e-05 loss: 0.0602 (0.0546) time: 2.6350 data: 0.0058 max mem: 33369 +Epoch: [19] [ 890/1319] eta: 0:18:50 lr: 2.7185271176010996e-05 loss: 0.0492 (0.0545) time: 2.6328 data: 0.0057 max mem: 33369 +Epoch: [19] [ 900/1319] eta: 0:18:24 lr: 2.7176144348029154e-05 loss: 0.0459 (0.0545) time: 2.6444 data: 0.0059 max mem: 33369 +Epoch: [19] [ 910/1319] eta: 0:17:57 lr: 2.7167017179462245e-05 loss: 0.0527 (0.0545) time: 2.6252 data: 0.0060 max mem: 33369 +Epoch: [19] [ 920/1319] eta: 0:17:31 lr: 2.7157889670170428e-05 loss: 0.0545 (0.0545) time: 2.6209 data: 0.0058 max mem: 33369 +Epoch: [19] [ 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33369 +Epoch: [19] [1010/1319] eta: 0:13:33 lr: 2.7075726730791712e-05 loss: 0.0497 (0.0546) time: 2.6293 data: 0.0058 max mem: 33369 +Epoch: [19] [1020/1319] eta: 0:13:07 lr: 2.706659580653433e-05 loss: 0.0435 (0.0546) time: 2.6471 data: 0.0057 max mem: 33369 +Epoch: [19] [1030/1319] eta: 0:12:40 lr: 2.7057464540006328e-05 loss: 0.0416 (0.0546) time: 2.6465 data: 0.0058 max mem: 33369 +Epoch: [19] [1040/1319] eta: 0:12:14 lr: 2.7048332931066517e-05 loss: 0.0488 (0.0546) time: 2.6091 data: 0.0060 max mem: 33369 +Epoch: [19] [1050/1319] eta: 0:11:48 lr: 2.7039200979573614e-05 loss: 0.0526 (0.0547) time: 2.5843 data: 0.0060 max mem: 33369 +Epoch: [19] [1060/1319] eta: 0:11:21 lr: 2.7030068685386206e-05 loss: 0.0544 (0.0548) time: 2.5739 data: 0.0060 max mem: 33369 +Epoch: [19] [1070/1319] eta: 0:10:55 lr: 2.7020936048362782e-05 loss: 0.0497 (0.0548) time: 2.5867 data: 0.0061 max mem: 33369 +Epoch: [19] [1080/1319] eta: 0:10:28 lr: 2.7011803068361714e-05 loss: 0.0456 (0.0547) time: 2.6121 data: 0.0059 max mem: 33369 +Epoch: [19] [1090/1319] eta: 0:10:02 lr: 2.700266974524126e-05 loss: 0.0546 (0.0549) time: 2.6231 data: 0.0058 max mem: 33369 +Epoch: [19] [1100/1319] eta: 0:09:36 lr: 2.699353607885957e-05 loss: 0.0548 (0.0548) time: 2.6120 data: 0.0058 max mem: 33369 +Epoch: [19] [1110/1319] eta: 0:09:09 lr: 2.6984402069074687e-05 loss: 0.0435 (0.0548) time: 2.6057 data: 0.0058 max mem: 33369 +Epoch: [19] [1120/1319] eta: 0:08:43 lr: 2.6975267715744523e-05 loss: 0.0427 (0.0549) time: 2.6453 data: 0.0057 max mem: 33369 +Epoch: [19] [1130/1319] eta: 0:08:17 lr: 2.6966133018726902e-05 loss: 0.0423 (0.0548) time: 2.6553 data: 0.0060 max mem: 33369 +Epoch: [19] [1140/1319] eta: 0:07:50 lr: 2.6956997977879505e-05 loss: 0.0544 (0.0549) time: 2.6425 data: 0.0061 max mem: 33369 +Epoch: [19] [1150/1319] eta: 0:07:24 lr: 2.6947862593059943e-05 loss: 0.0503 (0.0548) time: 2.6235 data: 0.0059 max mem: 33369 +Epoch: [19] [1160/1319] eta: 0:06:58 lr: 2.6938726864125667e-05 loss: 0.0400 (0.0548) time: 2.6166 data: 0.0060 max mem: 33369 +Epoch: [19] [1170/1319] eta: 0:06:31 lr: 2.6929590790934063e-05 loss: 0.0480 (0.0548) time: 2.6156 data: 0.0061 max mem: 33369 +Epoch: [19] [1180/1319] eta: 0:06:05 lr: 2.6920454373342357e-05 loss: 0.0467 (0.0548) time: 2.6044 data: 0.0059 max mem: 33369 +Epoch: [19] [1190/1319] eta: 0:05:39 lr: 2.6911317611207703e-05 loss: 0.0497 (0.0548) time: 2.6090 data: 0.0058 max mem: 33369 +Epoch: [19] [1200/1319] eta: 0:05:13 lr: 2.6902180504387114e-05 loss: 0.0464 (0.0547) time: 2.6348 data: 0.0058 max mem: 33369 +Epoch: [19] [1210/1319] eta: 0:04:46 lr: 2.689304305273751e-05 loss: 0.0478 (0.0549) time: 2.6457 data: 0.0058 max mem: 33369 +Epoch: [19] [1220/1319] eta: 0:04:20 lr: 2.6883905256115667e-05 loss: 0.0509 (0.0550) time: 2.6396 data: 0.0058 max mem: 33369 +Epoch: [19] [1230/1319] eta: 0:03:54 lr: 2.687476711437828e-05 loss: 0.0509 (0.0550) time: 2.6325 data: 0.0059 max mem: 33369 +Epoch: [19] [1240/1319] eta: 0:03:27 lr: 2.6865628627381928e-05 loss: 0.0520 (0.0550) time: 2.5988 data: 0.0058 max mem: 33369 +Epoch: [19] [1250/1319] eta: 0:03:01 lr: 2.6856489794983043e-05 loss: 0.0470 (0.0550) time: 2.6108 data: 0.0055 max mem: 33369 +Epoch: [19] [1260/1319] eta: 0:02:35 lr: 2.6847350617037976e-05 loss: 0.0459 (0.0549) time: 2.6380 data: 0.0057 max mem: 33369 +Epoch: [19] [1270/1319] eta: 0:02:08 lr: 2.683821109340296e-05 loss: 0.0408 (0.0550) time: 2.6157 data: 0.0058 max mem: 33369 +Epoch: [19] [1280/1319] eta: 0:01:42 lr: 2.68290712239341e-05 loss: 0.0420 (0.0549) time: 2.6238 data: 0.0058 max mem: 33369 +Epoch: [19] [1290/1319] eta: 0:01:16 lr: 2.681993100848739e-05 loss: 0.0443 (0.0550) time: 2.6463 data: 0.0056 max mem: 33369 +Epoch: [19] [1300/1319] eta: 0:00:49 lr: 2.6810790446918727e-05 loss: 0.0580 (0.0550) time: 2.6204 data: 0.0056 max mem: 33369 +Epoch: [19] [1310/1319] eta: 0:00:23 lr: 2.680164953908387e-05 loss: 0.0559 (0.0551) time: 2.6061 data: 0.0058 max mem: 33369 +Epoch: [19] Total time: 0:57:49 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 2:03:16 time: 2.8748 data: 2.7958 max mem: 33369 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 100/2573] eta: 0:04:06 time: 0.0717 data: 0.0011 max mem: 33369 +Test: [ 200/2573] eta: 0:03:26 time: 0.0735 data: 0.0011 max mem: 33369 +Test: [ 300/2573] eta: 0:03:06 time: 0.0749 data: 0.0011 max mem: 33369 +Test: [ 400/2573] eta: 0:02:53 time: 0.0750 data: 0.0011 max mem: 33369 +Test: [ 500/2573] eta: 0:02:42 time: 0.0736 data: 0.0011 max mem: 33369 +Test: [ 600/2573] eta: 0:02:33 time: 0.0735 data: 0.0011 max mem: 33369 +Test: [ 700/2573] eta: 0:02:25 time: 0.0735 data: 0.0011 max mem: 33369 +Test: [ 800/2573] eta: 0:02:16 time: 0.0769 data: 0.0011 max mem: 33369 +Test: [ 900/2573] eta: 0:02:08 time: 0.0738 data: 0.0011 max mem: 33369 +Test: [1000/2573] eta: 0:02:00 time: 0.0737 data: 0.0011 max mem: 33369 +Test: [1100/2573] eta: 0:01:52 time: 0.0736 data: 0.0011 max mem: 33369 +Test: [1200/2573] eta: 0:01:44 time: 0.0737 data: 0.0011 max mem: 33369 +Test: [1300/2573] eta: 0:01:36 time: 0.0737 data: 0.0011 max mem: 33369 +Test: [1400/2573] eta: 0:01:28 time: 0.0720 data: 0.0011 max mem: 33369 +Test: [1500/2573] eta: 0:01:21 time: 0.0737 data: 0.0011 max mem: 33369 +Test: [1600/2573] eta: 0:01:13 time: 0.0770 data: 0.0011 max mem: 33369 +Test: [1700/2573] eta: 0:01:05 time: 0.0721 data: 0.0011 max mem: 33369 +Test: [1800/2573] eta: 0:00:58 time: 0.0754 data: 0.0011 max mem: 33369 +Test: [1900/2573] eta: 0:00:50 time: 0.0721 data: 0.0011 max mem: 33369 +Test: [2000/2573] eta: 0:00:43 time: 0.0737 data: 0.0011 max mem: 33369 +Test: [2100/2573] eta: 0:00:35 time: 0.0753 data: 0.0011 max mem: 33369 +Test: [2200/2573] eta: 0:00:27 time: 0.0753 data: 0.0011 max mem: 33369 +Test: [2300/2573] eta: 0:00:20 time: 0.0753 data: 0.0011 max mem: 33369 +Test: [2400/2573] eta: 0:00:12 time: 0.0704 data: 0.0011 max mem: 33369 +Test: [2500/2573] eta: 0:00:05 time: 0.0735 data: 0.0011 max mem: 33369 +Test: Total time: 0:03:12 +Final results: +Mean IoU is 63.16 + + precision@0.5 = 71.36 + precision@0.6 = 66.07 + precision@0.7 = 58.76 + precision@0.8 = 47.41 + precision@0.9 = 22.86 + overall IoU = 60.44 + +Average object IoU 63.161104676031734 +Overall IoU 60.43696594238281 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [20] [ 0/1319] eta: 3:10:19 lr: 2.6793422425855603e-05 loss: 0.0437 (0.0437) time: 8.6574 data: 1.4395 max mem: 33369 +Epoch: [20] [ 10/1319] eta: 1:09:20 lr: 2.678428085971722e-05 loss: 0.0456 (0.0480) time: 3.1785 data: 0.1370 max mem: 33369 +Epoch: [20] [ 20/1319] eta: 1:03:00 lr: 2.6775138946893718e-05 loss: 0.0464 (0.0509) time: 2.6232 data: 0.0064 max mem: 33369 +Epoch: [20] [ 30/1319] eta: 1:00:25 lr: 2.6765996687240426e-05 loss: 0.0439 (0.0491) time: 2.6116 data: 0.0061 max mem: 33369 +Epoch: [20] [ 40/1319] eta: 0:59:00 lr: 2.675685408061254e-05 loss: 0.0448 (0.0483) time: 2.6182 data: 0.0063 max mem: 33369 +Epoch: [20] [ 50/1319] eta: 0:57:58 lr: 2.6747711126865168e-05 loss: 0.0454 (0.0473) time: 2.6308 data: 0.0063 max mem: 33369 +Epoch: [20] [ 60/1319] eta: 0:57:16 lr: 2.6738567825853273e-05 loss: 0.0533 (0.0496) time: 2.6508 data: 0.0062 max mem: 33369 +Epoch: [20] [ 70/1319] eta: 0:56:23 lr: 2.6729424177431713e-05 loss: 0.0608 (0.0511) time: 2.6266 data: 0.0061 max mem: 33369 +Epoch: [20] [ 80/1319] eta: 0:55:40 lr: 2.6720280181455227e-05 loss: 0.0465 (0.0504) time: 2.5938 data: 0.0061 max mem: 33369 +Epoch: [20] [ 90/1319] eta: 0:54:59 lr: 2.671113583777845e-05 loss: 0.0420 (0.0502) time: 2.5992 data: 0.0063 max mem: 33369 +Epoch: [20] [ 100/1319] eta: 0:54:26 lr: 2.670199114625589e-05 loss: 0.0426 (0.0501) time: 2.6139 data: 0.0062 max mem: 33369 +Epoch: [20] [ 110/1319] eta: 0:53:54 lr: 2.6692846106741932e-05 loss: 0.0476 (0.0501) time: 2.6329 data: 0.0062 max mem: 33369 +Epoch: [20] [ 120/1319] eta: 0:53:23 lr: 2.668370071909087e-05 loss: 0.0496 (0.0502) time: 2.6312 data: 0.0063 max mem: 33369 +Epoch: [20] [ 130/1319] eta: 0:52:56 lr: 2.6674554983156852e-05 loss: 0.0496 (0.0503) time: 2.6507 data: 0.0062 max mem: 33369 +Epoch: [20] [ 140/1319] eta: 0:52:22 lr: 2.666540889879393e-05 loss: 0.0427 (0.0509) time: 2.6266 data: 0.0061 max mem: 33369 +Epoch: [20] [ 150/1319] eta: 0:51:52 lr: 2.6656262465856026e-05 loss: 0.0530 (0.0511) time: 2.6019 data: 0.0062 max mem: 33369 +Epoch: [20] [ 160/1319] eta: 0:51:22 lr: 2.6647115684196954e-05 loss: 0.0470 (0.0507) time: 2.6165 data: 0.0062 max mem: 33369 +Epoch: [20] [ 170/1319] eta: 0:50:54 lr: 2.663796855367041e-05 loss: 0.0452 (0.0504) time: 2.6303 data: 0.0061 max mem: 33369 +Epoch: [20] [ 180/1319] eta: 0:50:27 lr: 2.662882107412996e-05 loss: 0.0460 (0.0504) time: 2.6517 data: 0.0061 max mem: 33369 +Epoch: [20] [ 190/1319] eta: 0:50:01 lr: 2.661967324542908e-05 loss: 0.0492 (0.0505) time: 2.6608 data: 0.0062 max mem: 33369 +Epoch: [20] [ 200/1319] eta: 0:49:34 lr: 2.6610525067421092e-05 loss: 0.0459 (0.0502) time: 2.6577 data: 0.0063 max mem: 33369 +Epoch: [20] [ 210/1319] eta: 0:49:09 lr: 2.6601376539959238e-05 loss: 0.0497 (0.0506) time: 2.6613 data: 0.0063 max mem: 33369 +Epoch: [20] [ 220/1319] eta: 0:48:42 lr: 2.6592227662896617e-05 loss: 0.0568 (0.0509) time: 2.6687 data: 0.0062 max mem: 33369 +Epoch: [20] [ 230/1319] eta: 0:48:13 lr: 2.658307843608621e-05 loss: 0.0541 (0.0508) time: 2.6336 data: 0.0064 max mem: 33369 +Epoch: [20] [ 240/1319] eta: 0:47:45 lr: 2.65739288593809e-05 loss: 0.0483 (0.0507) time: 2.6118 data: 0.0064 max mem: 33369 +Epoch: [20] [ 250/1319] eta: 0:47:17 lr: 2.6564778932633426e-05 loss: 0.0483 (0.0509) time: 2.6188 data: 0.0062 max mem: 33369 +Epoch: [20] [ 260/1319] eta: 0:46:49 lr: 2.655562865569643e-05 loss: 0.0461 (0.0512) time: 2.6208 data: 0.0064 max mem: 33369 +Epoch: [20] [ 270/1319] eta: 0:46:20 lr: 2.654647802842242e-05 loss: 0.0472 (0.0512) time: 2.6153 data: 0.0062 max mem: 33369 +Epoch: [20] [ 280/1319] eta: 0:45:53 lr: 2.6537327050663813e-05 loss: 0.0472 (0.0514) time: 2.6231 data: 0.0062 max mem: 33369 +Epoch: [20] [ 290/1319] eta: 0:45:27 lr: 2.6528175722272857e-05 loss: 0.0504 (0.0516) time: 2.6452 data: 0.0061 max mem: 33369 +Epoch: [20] [ 300/1319] eta: 0:45:00 lr: 2.6519024043101733e-05 loss: 0.0524 (0.0515) time: 2.6397 data: 0.0060 max mem: 33369 +Epoch: [20] [ 310/1319] eta: 0:44:32 lr: 2.6509872013002462e-05 loss: 0.0490 (0.0516) time: 2.6225 data: 0.0061 max mem: 33369 +Epoch: [20] [ 320/1319] eta: 0:44:05 lr: 2.6500719631826982e-05 loss: 0.0466 (0.0514) time: 2.6235 data: 0.0060 max mem: 33369 +Epoch: [20] [ 330/1319] eta: 0:43:37 lr: 2.649156689942709e-05 loss: 0.0410 (0.0513) time: 2.6193 data: 0.0061 max mem: 33369 +Epoch: [20] [ 340/1319] eta: 0:43:10 lr: 2.648241381565446e-05 loss: 0.0440 (0.0513) time: 2.6150 data: 0.0061 max mem: 33369 +Epoch: [20] [ 350/1319] eta: 0:42:44 lr: 2.6473260380360663e-05 loss: 0.0547 (0.0516) time: 2.6290 data: 0.0062 max mem: 33369 +Epoch: [20] [ 360/1319] eta: 0:42:16 lr: 2.6464106593397137e-05 loss: 0.0583 (0.0516) time: 2.6205 data: 0.0063 max mem: 33369 +Epoch: [20] [ 370/1319] eta: 0:41:49 lr: 2.6454952454615202e-05 loss: 0.0428 (0.0514) time: 2.6122 data: 0.0063 max mem: 33369 +Epoch: [20] [ 380/1319] eta: 0:41:22 lr: 2.6445797963866064e-05 loss: 0.0415 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data: 0.0060 max mem: 33369 +Epoch: [20] [ 700/1319] eta: 0:27:13 lr: 2.615266752446517e-05 loss: 0.0462 (0.0522) time: 2.6315 data: 0.0061 max mem: 33369 +Epoch: [20] [ 710/1319] eta: 0:26:46 lr: 2.614350133452863e-05 loss: 0.0462 (0.0521) time: 2.6353 data: 0.0061 max mem: 33369 +Epoch: [20] [ 720/1319] eta: 0:26:20 lr: 2.6134334787493302e-05 loss: 0.0416 (0.0521) time: 2.6247 data: 0.0061 max mem: 33369 +Epoch: [20] [ 730/1319] eta: 0:25:53 lr: 2.6125167883206104e-05 loss: 0.0452 (0.0520) time: 2.6070 data: 0.0062 max mem: 33369 +Epoch: [20] [ 740/1319] eta: 0:25:26 lr: 2.61160006215138e-05 loss: 0.0477 (0.0520) time: 2.6168 data: 0.0060 max mem: 33369 +Epoch: [20] [ 750/1319] eta: 0:25:00 lr: 2.610683300226307e-05 loss: 0.0452 (0.0520) time: 2.6303 data: 0.0059 max mem: 33369 +Epoch: [20] [ 760/1319] eta: 0:24:33 lr: 2.6097665025300437e-05 loss: 0.0404 (0.0519) time: 2.6188 data: 0.0060 max mem: 33369 +Epoch: [20] [ 770/1319] eta: 0:24:07 lr: 2.608849669047231e-05 loss: 0.0496 (0.0519) time: 2.6268 data: 0.0061 max mem: 33369 +Epoch: [20] [ 780/1319] eta: 0:23:41 lr: 2.6079327997624963e-05 loss: 0.0515 (0.0519) time: 2.6277 data: 0.0060 max mem: 33369 +Epoch: [20] [ 790/1319] eta: 0:23:14 lr: 2.6070158946604555e-05 loss: 0.0495 (0.0520) time: 2.6212 data: 0.0062 max mem: 33369 +Epoch: [20] [ 800/1319] eta: 0:22:48 lr: 2.6060989537257118e-05 loss: 0.0540 (0.0520) time: 2.6360 data: 0.0063 max mem: 33369 +Epoch: [20] [ 810/1319] eta: 0:22:21 lr: 2.6051819769428553e-05 loss: 0.0540 (0.0521) time: 2.6303 data: 0.0059 max mem: 33369 +Epoch: [20] [ 820/1319] eta: 0:21:55 lr: 2.604264964296463e-05 loss: 0.0587 (0.0523) time: 2.6209 data: 0.0060 max mem: 33369 +Epoch: [20] [ 830/1319] eta: 0:21:29 lr: 2.6033479157711e-05 loss: 0.0553 (0.0525) time: 2.6250 data: 0.0060 max mem: 33369 +Epoch: [20] [ 840/1319] eta: 0:21:02 lr: 2.6024308313513185e-05 loss: 0.0511 (0.0525) time: 2.6310 data: 0.0060 max mem: 33369 +Epoch: [20] [ 850/1319] eta: 0:20:36 lr: 2.601513711021658e-05 loss: 0.0492 (0.0526) time: 2.6216 data: 0.0060 max mem: 33369 +Epoch: [20] [ 860/1319] eta: 0:20:09 lr: 2.6005965547666454e-05 loss: 0.0464 (0.0525) time: 2.6138 data: 0.0059 max mem: 33369 +Epoch: [20] [ 870/1319] eta: 0:19:43 lr: 2.599679362570795e-05 loss: 0.0398 (0.0523) time: 2.6384 data: 0.0060 max mem: 33369 +Epoch: [20] [ 880/1319] eta: 0:19:17 lr: 2.598762134418607e-05 loss: 0.0389 (0.0522) time: 2.6510 data: 0.0059 max mem: 33369 +Epoch: [20] [ 890/1319] eta: 0:18:50 lr: 2.5978448702945707e-05 loss: 0.0339 (0.0521) time: 2.6323 data: 0.0060 max mem: 33369 +Epoch: [20] [ 900/1319] eta: 0:18:24 lr: 2.596927570183162e-05 loss: 0.0381 (0.0520) time: 2.6263 data: 0.0059 max mem: 33369 +Epoch: [20] [ 910/1319] eta: 0:17:57 lr: 2.5960102340688436e-05 loss: 0.0436 (0.0520) time: 2.6236 data: 0.0059 max mem: 33369 +Epoch: [20] [ 920/1319] eta: 0:17:31 lr: 2.5950928619360655e-05 loss: 0.0482 (0.0519) time: 2.6097 data: 0.0059 max mem: 33369 +Epoch: [20] [ 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33369 +Epoch: [20] [1010/1319] eta: 0:13:33 lr: 2.586834889338287e-05 loss: 0.0537 (0.0518) time: 2.6249 data: 0.0059 max mem: 33369 +Epoch: [20] [1020/1319] eta: 0:13:07 lr: 2.58591715616284e-05 loss: 0.0614 (0.0519) time: 2.6175 data: 0.0058 max mem: 33369 +Epoch: [20] [1030/1319] eta: 0:12:40 lr: 2.584999386797035e-05 loss: 0.0469 (0.0518) time: 2.6250 data: 0.0059 max mem: 33369 +Epoch: [20] [1040/1319] eta: 0:12:14 lr: 2.5840815812251663e-05 loss: 0.0435 (0.0520) time: 2.6246 data: 0.0059 max mem: 33369 +Epoch: [20] [1050/1319] eta: 0:11:48 lr: 2.583163739431517e-05 loss: 0.0488 (0.0519) time: 2.6204 data: 0.0060 max mem: 33369 +Epoch: [20] [1060/1319] eta: 0:11:21 lr: 2.582245861400355e-05 loss: 0.0443 (0.0519) time: 2.6117 data: 0.0060 max mem: 33369 +Epoch: [20] [1070/1319] eta: 0:10:55 lr: 2.5813279471159375e-05 loss: 0.0421 (0.0518) time: 2.6286 data: 0.0058 max mem: 33369 +Epoch: [20] [1080/1319] eta: 0:10:29 lr: 2.5804099965625085e-05 loss: 0.0507 (0.0520) time: 2.6290 data: 0.0060 max mem: 33369 +Epoch: [20] [1090/1319] eta: 0:10:02 lr: 2.5794920097242954e-05 loss: 0.0547 (0.0520) time: 2.6453 data: 0.0061 max mem: 33369 +Epoch: [20] [1100/1319] eta: 0:09:36 lr: 2.5785739865855164e-05 loss: 0.0463 (0.0520) time: 2.6466 data: 0.0062 max mem: 33369 +Epoch: [20] [1110/1319] eta: 0:09:10 lr: 2.5776559271303753e-05 loss: 0.0479 (0.0519) time: 2.6075 data: 0.0064 max mem: 33369 +Epoch: [20] [1120/1319] eta: 0:08:43 lr: 2.5767378313430623e-05 loss: 0.0452 (0.0519) time: 2.6106 data: 0.0062 max mem: 33369 +Epoch: [20] [1130/1319] eta: 0:08:17 lr: 2.5758196992077554e-05 loss: 0.0498 (0.0521) time: 2.6095 data: 0.0061 max mem: 33369 +Epoch: [20] [1140/1319] eta: 0:07:51 lr: 2.574901530708619e-05 loss: 0.0604 (0.0522) time: 2.6084 data: 0.0062 max mem: 33369 +Epoch: [20] [1150/1319] eta: 0:07:24 lr: 2.573983325829803e-05 loss: 0.0494 (0.0522) time: 2.6217 data: 0.0060 max mem: 33369 +Epoch: [20] [1160/1319] eta: 0:06:58 lr: 2.573065084555446e-05 loss: 0.0443 (0.0522) time: 2.6306 data: 0.0062 max mem: 33369 +Epoch: [20] [1170/1319] eta: 0:06:32 lr: 2.572146806869673e-05 loss: 0.0443 (0.0522) time: 2.6326 data: 0.0062 max mem: 33369 +Epoch: [20] [1180/1319] eta: 0:06:05 lr: 2.5712284927565954e-05 loss: 0.0462 (0.0522) time: 2.6523 data: 0.0061 max mem: 33369 +Epoch: [20] [1190/1319] eta: 0:05:39 lr: 2.5703101422003118e-05 loss: 0.0422 (0.0521) time: 2.6534 data: 0.0061 max mem: 33369 +Epoch: [20] [1200/1319] eta: 0:05:13 lr: 2.569391755184906e-05 loss: 0.0425 (0.0521) time: 2.6280 data: 0.0061 max mem: 33369 +Epoch: [20] [1210/1319] eta: 0:04:46 lr: 2.5684733316944508e-05 loss: 0.0456 (0.0522) time: 2.6207 data: 0.0062 max mem: 33369 +Epoch: [20] [1220/1319] eta: 0:04:20 lr: 2.5675548717130043e-05 loss: 0.0621 (0.0524) time: 2.6062 data: 0.0061 max mem: 33369 +Epoch: [20] [1230/1319] eta: 0:03:54 lr: 2.5666363752246116e-05 loss: 0.0492 (0.0524) time: 2.6104 data: 0.0060 max mem: 33369 +Epoch: [20] [1240/1319] eta: 0:03:27 lr: 2.5657178422133044e-05 loss: 0.0532 (0.0525) time: 2.6067 data: 0.0059 max mem: 33369 +Epoch: [20] [1250/1319] eta: 0:03:01 lr: 2.564799272663101e-05 loss: 0.0572 (0.0526) time: 2.5894 data: 0.0058 max mem: 33369 +Epoch: [20] [1260/1319] eta: 0:02:35 lr: 2.5638806665580068e-05 loss: 0.0568 (0.0527) time: 2.6086 data: 0.0058 max mem: 33369 +Epoch: [20] [1270/1319] eta: 0:02:08 lr: 2.5629620238820134e-05 loss: 0.0577 (0.0528) time: 2.6261 data: 0.0058 max mem: 33369 +Epoch: [20] [1280/1319] eta: 0:01:42 lr: 2.562043344619099e-05 loss: 0.0490 (0.0528) time: 2.6017 data: 0.0060 max mem: 33369 +Epoch: [20] [1290/1319] eta: 0:01:16 lr: 2.5611246287532285e-05 loss: 0.0476 (0.0528) time: 2.6046 data: 0.0060 max mem: 33369 +Epoch: [20] [1300/1319] eta: 0:00:49 lr: 2.560205876268355e-05 loss: 0.0493 (0.0529) time: 2.6317 data: 0.0057 max mem: 33369 +Epoch: [20] [1310/1319] eta: 0:00:23 lr: 2.5592870871484144e-05 loss: 0.0523 (0.0529) time: 2.6135 data: 0.0058 max mem: 33369 +Epoch: [20] Total time: 0:57:49 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 2:51:46 time: 4.0057 data: 3.9259 max mem: 33369 +Test: [ 100/2573] eta: 0:04:33 time: 0.0716 data: 0.0011 max mem: 33369 +Test: [ 200/2573] eta: 0:03:39 time: 0.0729 data: 0.0011 max mem: 33369 +Test: [ 300/2573] eta: 0:03:14 time: 0.0744 data: 0.0011 max mem: 33369 +Test: [ 400/2573] eta: 0:02:58 time: 0.0746 data: 0.0011 max mem: 33369 +Test: [ 500/2573] eta: 0:02:46 time: 0.0732 data: 0.0011 max mem: 33369 +Test: [ 600/2573] eta: 0:02:36 time: 0.0734 data: 0.0011 max mem: 33369 +Test: [ 700/2573] eta: 0:02:27 time: 0.0733 data: 0.0011 max mem: 33369 +Test: [ 800/2573] eta: 0:02:18 time: 0.0769 data: 0.0011 max mem: 33369 +Test: [ 900/2573] eta: 0:02:10 time: 0.0734 data: 0.0011 max mem: 33369 +Test: [1000/2573] eta: 0:02:01 time: 0.0734 data: 0.0011 max mem: 33369 +Test: [1100/2573] eta: 0:01:53 time: 0.0734 data: 0.0011 max mem: 33369 +Test: [1200/2573] eta: 0:01:45 time: 0.0735 data: 0.0011 max mem: 33369 +Test: [1300/2573] eta: 0:01:37 time: 0.0734 data: 0.0011 max mem: 33369 +Test: [1400/2573] eta: 0:01:29 time: 0.0719 data: 0.0011 max mem: 33369 +Test: [1500/2573] eta: 0:01:21 time: 0.0738 data: 0.0011 max mem: 33369 +Test: [1600/2573] eta: 0:01:13 time: 0.0769 data: 0.0011 max mem: 33369 +Test: [1700/2573] eta: 0:01:06 time: 0.0719 data: 0.0011 max mem: 33369 +Test: [1800/2573] eta: 0:00:58 time: 0.0753 data: 0.0011 max mem: 33369 +Test: [1900/2573] eta: 0:00:50 time: 0.0720 data: 0.0011 max mem: 33369 +Test: [2000/2573] eta: 0:00:43 time: 0.0737 data: 0.0011 max mem: 33369 +Test: [2100/2573] eta: 0:00:35 time: 0.0753 data: 0.0011 max mem: 33369 +Test: [2200/2573] eta: 0:00:28 time: 0.0753 data: 0.0011 max mem: 33369 +Test: [2300/2573] eta: 0:00:20 time: 0.0755 data: 0.0011 max mem: 33369 +Test: [2400/2573] eta: 0:00:12 time: 0.0705 data: 0.0011 max mem: 33369 +Test: [2500/2573] eta: 0:00:05 time: 0.0736 data: 0.0011 max mem: 33369 +Test: Total time: 0:03:13 +Final results: +Mean IoU is 63.88 + + precision@0.5 = 71.73 + precision@0.6 = 66.44 + precision@0.7 = 59.58 + precision@0.8 = 47.96 + precision@0.9 = 23.82 + overall IoU = 61.46 + +Average object IoU 63.875754518086595 +Overall IoU 61.458763122558594 +Better epoch: 20 + +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [21] [ 0/1319] eta: 1:28:32 lr: 2.5584601456041995e-05 loss: 0.0477 (0.0477) time: 4.0277 data: 1.3785 max mem: 33369 +Epoch: [21] [ 10/1319] eta: 1:00:51 lr: 2.5575412868333344e-05 loss: 0.0477 (0.0561) time: 2.7893 data: 0.1304 max mem: 33369 +Epoch: [21] [ 20/1319] eta: 0:58:18 lr: 2.5566223913807464e-05 loss: 0.0464 (0.0522) time: 2.6267 data: 0.0057 max mem: 33369 +Epoch: [21] [ 30/1319] eta: 0:57:17 lr: 2.5557034592303224e-05 loss: 0.0426 (0.0519) time: 2.5991 data: 0.0060 max mem: 33369 +Epoch: [21] [ 40/1319] eta: 0:56:35 lr: 2.5547844903659336e-05 loss: 0.0426 (0.0502) time: 2.6135 data: 0.0063 max mem: 33369 +Epoch: [21] [ 50/1319] eta: 0:56:00 lr: 2.5538654847714393e-05 loss: 0.0415 (0.0502) time: 2.6192 data: 0.0065 max mem: 33369 +Epoch: [21] [ 60/1319] eta: 0:55:21 lr: 2.552946442430683e-05 loss: 0.0439 (0.0500) time: 2.6045 data: 0.0066 max mem: 33369 +Epoch: [21] [ 70/1319] eta: 0:54:55 lr: 2.552027363327497e-05 loss: 0.0476 (0.0504) time: 2.6134 data: 0.0063 max mem: 33369 +Epoch: [21] [ 80/1319] eta: 0:54:26 lr: 2.551108247445699e-05 loss: 0.0455 (0.0496) time: 2.6311 data: 0.0062 max mem: 33369 +Epoch: [21] [ 90/1319] eta: 0:53:54 lr: 2.5501890947690927e-05 loss: 0.0429 (0.0495) time: 2.6094 data: 0.0060 max mem: 33369 +Epoch: [21] [ 100/1319] eta: 0:53:24 lr: 2.5492699052814688e-05 loss: 0.0443 (0.0496) time: 2.5986 data: 0.0061 max mem: 33369 +Epoch: [21] [ 110/1319] eta: 0:52:55 lr: 2.548350678966605e-05 loss: 0.0443 (0.0490) time: 2.6035 data: 0.0062 max mem: 33369 +Epoch: [21] [ 120/1319] eta: 0:52:26 lr: 2.547431415808263e-05 loss: 0.0386 (0.0487) time: 2.6024 data: 0.0062 max mem: 33369 +Epoch: [21] [ 130/1319] eta: 0:51:59 lr: 2.5465121157901932e-05 loss: 0.0392 (0.0484) time: 2.6085 data: 0.0062 max mem: 33369 +Epoch: [21] [ 140/1319] eta: 0:51:29 lr: 2.5455927788961316e-05 loss: 0.0445 (0.0485) time: 2.5958 data: 0.0064 max mem: 33369 +Epoch: [21] [ 150/1319] eta: 0:51:07 lr: 2.5446734051098e-05 loss: 0.0445 (0.0483) time: 2.6227 data: 0.0065 max mem: 33369 +Epoch: [21] [ 160/1319] eta: 0:50:40 lr: 2.5437539944149068e-05 loss: 0.0490 (0.0483) time: 2.6471 data: 0.0064 max mem: 33369 +Epoch: [21] [ 170/1319] eta: 0:50:12 lr: 2.542834546795147e-05 loss: 0.0484 (0.0487) time: 2.6086 data: 0.0062 max mem: 33369 +Epoch: [21] [ 180/1319] eta: 0:49:43 lr: 2.5419150622342014e-05 loss: 0.0481 (0.0488) time: 2.5828 data: 0.0061 max mem: 33369 +Epoch: [21] [ 190/1319] eta: 0:49:16 lr: 2.5409955407157366e-05 loss: 0.0437 (0.0483) time: 2.5877 data: 0.0062 max mem: 33369 +Epoch: [21] [ 200/1319] eta: 0:48:47 lr: 2.5400759822234066e-05 loss: 0.0360 (0.0480) time: 2.5903 data: 0.0064 max mem: 33369 +Epoch: [21] [ 210/1319] eta: 0:48:20 lr: 2.539156386740852e-05 loss: 0.0363 (0.0480) time: 2.5874 data: 0.0062 max mem: 33369 +Epoch: [21] [ 220/1319] eta: 0:47:57 lr: 2.538236754251696e-05 loss: 0.0420 (0.0478) time: 2.6367 data: 0.0061 max mem: 33369 +Epoch: [21] [ 230/1319] eta: 0:47:30 lr: 2.5373170847395516e-05 loss: 0.0406 (0.0481) time: 2.6389 data: 0.0063 max mem: 33369 +Epoch: [21] [ 240/1319] eta: 0:47:03 lr: 2.536397378188018e-05 loss: 0.0437 (0.0482) time: 2.5986 data: 0.0064 max mem: 33369 +Epoch: [21] [ 250/1319] eta: 0:46:37 lr: 2.5354776345806775e-05 loss: 0.0446 (0.0482) time: 2.6147 data: 0.0063 max mem: 33369 +Epoch: [21] [ 260/1319] eta: 0:46:11 lr: 2.534557853901102e-05 loss: 0.0432 (0.0482) time: 2.6264 data: 0.0062 max mem: 33369 +Epoch: [21] [ 270/1319] eta: 0:45:45 lr: 2.5336380361328465e-05 loss: 0.0432 (0.0480) time: 2.6192 data: 0.0063 max mem: 33369 +Epoch: [21] [ 280/1319] eta: 0:45:18 lr: 2.532718181259454e-05 loss: 0.0424 (0.0478) time: 2.6081 data: 0.0063 max mem: 33369 +Epoch: [21] [ 290/1319] eta: 0:44:53 lr: 2.531798289264453e-05 loss: 0.0465 (0.0481) time: 2.6249 data: 0.0061 max mem: 33369 +Epoch: [21] [ 300/1319] eta: 0:44:27 lr: 2.5308783601313586e-05 loss: 0.0549 (0.0488) time: 2.6345 data: 0.0060 max mem: 33369 +Epoch: [21] [ 310/1319] eta: 0:44:00 lr: 2.52995839384367e-05 loss: 0.0425 (0.0486) time: 2.6001 data: 0.0061 max mem: 33369 +Epoch: [21] [ 320/1319] eta: 0:43:34 lr: 2.5290383903848747e-05 loss: 0.0480 (0.0491) time: 2.6114 data: 0.0061 max mem: 33369 +Epoch: [21] [ 330/1319] eta: 0:43:08 lr: 2.5281183497384443e-05 loss: 0.0563 (0.0494) time: 2.6303 data: 0.0059 max mem: 33369 +Epoch: [21] [ 340/1319] eta: 0:42:42 lr: 2.5271982718878386e-05 loss: 0.0572 (0.0497) time: 2.6175 data: 0.0059 max mem: 33369 +Epoch: [21] [ 350/1319] eta: 0:42:15 lr: 2.5262781568165e-05 loss: 0.0422 (0.0495) time: 2.6065 data: 0.0062 max mem: 33369 +Epoch: [21] [ 360/1319] eta: 0:41:50 lr: 2.5253580045078606e-05 loss: 0.0449 (0.0497) time: 2.6218 data: 0.0063 max mem: 33369 +Epoch: [21] [ 370/1319] eta: 0:41:25 lr: 2.5244378149453368e-05 loss: 0.0454 (0.0495) time: 2.6492 data: 0.0063 max mem: 33369 +Epoch: [21] [ 380/1319] eta: 0:40:58 lr: 2.5235175881123296e-05 loss: 0.0388 (0.0497) time: 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2.6593 data: 0.0060 max mem: 33369 +Epoch: [21] [1170/1319] eta: 0:06:30 lr: 2.4507004522523372e-05 loss: 0.0460 (0.0506) time: 2.6219 data: 0.0058 max mem: 33369 +Epoch: [21] [1180/1319] eta: 0:06:04 lr: 2.4497771887210175e-05 loss: 0.0389 (0.0505) time: 2.6008 data: 0.0060 max mem: 33369 +Epoch: [21] [1190/1319] eta: 0:05:38 lr: 2.4488538865262596e-05 loss: 0.0391 (0.0505) time: 2.6167 data: 0.0059 max mem: 33369 +Epoch: [21] [1200/1319] eta: 0:05:12 lr: 2.4479305456502462e-05 loss: 0.0525 (0.0505) time: 2.6194 data: 0.0060 max mem: 33369 +Epoch: [21] [1210/1319] eta: 0:04:45 lr: 2.4470071660751444e-05 loss: 0.0473 (0.0505) time: 2.6067 data: 0.0061 max mem: 33369 +Epoch: [21] [1220/1319] eta: 0:04:19 lr: 2.446083747783105e-05 loss: 0.0473 (0.0505) time: 2.6289 data: 0.0060 max mem: 33369 +Epoch: [21] [1230/1319] eta: 0:03:53 lr: 2.4451602907562637e-05 loss: 0.0431 (0.0505) time: 2.6044 data: 0.0060 max mem: 33369 +Epoch: [21] [1240/1319] eta: 0:03:27 lr: 2.4442367949767393e-05 loss: 0.0398 (0.0505) time: 2.5867 data: 0.0060 max mem: 33369 +Epoch: [21] [1250/1319] eta: 0:03:00 lr: 2.4433132604266355e-05 loss: 0.0412 (0.0505) time: 2.6420 data: 0.0058 max mem: 33369 +Epoch: [21] [1260/1319] eta: 0:02:34 lr: 2.442389687088041e-05 loss: 0.0428 (0.0507) time: 2.6509 data: 0.0058 max mem: 33369 +Epoch: [21] [1270/1319] eta: 0:02:08 lr: 2.441466074943027e-05 loss: 0.0515 (0.0507) time: 2.6284 data: 0.0059 max mem: 33369 +Epoch: [21] [1280/1319] eta: 0:01:42 lr: 2.440542423973651e-05 loss: 0.0441 (0.0507) time: 2.6193 data: 0.0059 max mem: 33369 +Epoch: [21] [1290/1319] eta: 0:01:16 lr: 2.439618734161953e-05 loss: 0.0492 (0.0507) time: 2.6223 data: 0.0059 max mem: 33369 +Epoch: [21] [1300/1319] eta: 0:00:49 lr: 2.4386950054899575e-05 loss: 0.0498 (0.0507) time: 2.6164 data: 0.0060 max mem: 33369 +Epoch: [21] [1310/1319] eta: 0:00:23 lr: 2.4377712379396728e-05 loss: 0.0522 (0.0507) time: 2.6031 data: 0.0060 max mem: 33369 +Epoch: [21] Total time: 0:57:39 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 1:48:01 time: 2.5192 data: 2.4402 max mem: 33369 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 100/2573] eta: 0:04:03 time: 0.0721 data: 0.0011 max mem: 33369 +Test: [ 200/2573] eta: 0:03:25 time: 0.0734 data: 0.0011 max mem: 33369 +Test: [ 300/2573] eta: 0:03:05 time: 0.0751 data: 0.0011 max mem: 33369 +Test: [ 400/2573] eta: 0:02:52 time: 0.0751 data: 0.0011 max mem: 33369 +Test: [ 500/2573] eta: 0:02:42 time: 0.0737 data: 0.0011 max mem: 33369 +Test: [ 600/2573] eta: 0:02:33 time: 0.0738 data: 0.0011 max mem: 33369 +Test: [ 700/2573] eta: 0:02:25 time: 0.0738 data: 0.0011 max mem: 33369 +Test: [ 800/2573] eta: 0:02:16 time: 0.0772 data: 0.0011 max mem: 33369 +Test: [ 900/2573] eta: 0:02:08 time: 0.0741 data: 0.0011 max mem: 33369 +Test: [1000/2573] eta: 0:02:00 time: 0.0740 data: 0.0011 max mem: 33369 +Test: [1100/2573] eta: 0:01:52 time: 0.0739 data: 0.0011 max mem: 33369 +Test: [1200/2573] eta: 0:01:44 time: 0.0740 data: 0.0011 max mem: 33369 +Test: [1300/2573] eta: 0:01:36 time: 0.0741 data: 0.0011 max mem: 33369 +Test: [1400/2573] eta: 0:01:29 time: 0.0724 data: 0.0011 max mem: 33369 +Test: [1500/2573] eta: 0:01:21 time: 0.0741 data: 0.0011 max mem: 33369 +Test: [1600/2573] eta: 0:01:13 time: 0.0774 data: 0.0011 max mem: 33369 +Test: [1700/2573] eta: 0:01:06 time: 0.0725 data: 0.0011 max mem: 33369 +Test: [1800/2573] eta: 0:00:58 time: 0.0758 data: 0.0011 max mem: 33369 +Test: [1900/2573] eta: 0:00:50 time: 0.0724 data: 0.0011 max mem: 33369 +Test: [2000/2573] eta: 0:00:43 time: 0.0741 data: 0.0011 max mem: 33369 +Test: [2100/2573] eta: 0:00:35 time: 0.0758 data: 0.0011 max mem: 33369 +Test: [2200/2573] eta: 0:00:28 time: 0.0758 data: 0.0011 max mem: 33369 +Test: [2300/2573] eta: 0:00:20 time: 0.0759 data: 0.0011 max mem: 33369 +Test: [2400/2573] eta: 0:00:13 time: 0.0707 data: 0.0011 max mem: 33369 +Test: [2500/2573] eta: 0:00:05 time: 0.0742 data: 0.0011 max mem: 33369 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: Total time: 0:03:13 +Final results: +Mean IoU is 63.63 + + precision@0.5 = 71.65 + precision@0.6 = 66.73 + precision@0.7 = 60.07 + precision@0.8 = 48.90 + precision@0.9 = 23.53 + overall IoU = 61.40 + +Average object IoU 63.627038061164164 +Overall IoU 61.39862060546875 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [22] [ 0/1319] eta: 2:53:33 lr: 2.4369398138885975e-05 loss: 0.0569 (0.0569) time: 7.8947 data: 1.6651 max mem: 33369 +Epoch: [22] [ 10/1319] eta: 1:08:48 lr: 2.436015972419942e-05 loss: 0.0407 (0.0412) time: 3.1541 data: 0.1575 max mem: 33369 +Epoch: [22] [ 20/1319] eta: 1:03:23 lr: 2.4350920920207323e-05 loss: 0.0435 (0.0482) time: 2.6799 data: 0.0062 max mem: 33369 +Epoch: [22] [ 30/1319] eta: 1:00:35 lr: 2.4341681726729162e-05 loss: 0.0438 (0.0469) time: 2.6374 data: 0.0060 max mem: 33369 +Epoch: [22] [ 40/1319] eta: 0:59:06 lr: 2.4332442143584247e-05 loss: 0.0452 (0.0496) time: 2.6104 data: 0.0063 max mem: 33369 +Epoch: [22] [ 50/1319] eta: 0:57:49 lr: 2.4323202170591704e-05 loss: 0.0478 (0.0507) time: 2.6003 data: 0.0063 max mem: 33369 +Epoch: [22] [ 60/1319] eta: 0:56:55 lr: 2.4313961807570534e-05 loss: 0.0519 (0.0514) time: 2.5892 data: 0.0062 max mem: 33369 +Epoch: [22] [ 70/1319] eta: 0:56:13 lr: 2.430472105433956e-05 loss: 0.0454 (0.0501) time: 2.6166 data: 0.0061 max mem: 33369 +Epoch: [22] [ 80/1319] eta: 0:55:38 lr: 2.4295479910717442e-05 loss: 0.0378 (0.0496) time: 2.6401 data: 0.0062 max mem: 33369 +Epoch: [22] [ 90/1319] eta: 0:55:00 lr: 2.4286238376522685e-05 loss: 0.0414 (0.0489) time: 2.6308 data: 0.0063 max mem: 33369 +Epoch: [22] [ 100/1319] eta: 0:54:23 lr: 2.4276996451573638e-05 loss: 0.0471 (0.0497) time: 2.6062 data: 0.0064 max mem: 33369 +Epoch: [22] [ 110/1319] eta: 0:53:52 lr: 2.426775413568847e-05 loss: 0.0447 (0.0495) time: 2.6198 data: 0.0063 max mem: 33369 +Epoch: [22] [ 120/1319] eta: 0:53:13 lr: 2.4258511428685206e-05 loss: 0.0434 (0.0493) time: 2.5949 data: 0.0060 max mem: 33369 +Epoch: [22] [ 130/1319] eta: 0:52:41 lr: 2.4249268330381702e-05 loss: 0.0374 (0.0482) time: 2.5781 data: 0.0062 max mem: 33369 +Epoch: [22] [ 140/1319] eta: 0:52:09 lr: 2.4240024840595657e-05 loss: 0.0408 (0.0484) time: 2.5976 data: 0.0062 max mem: 33369 +Epoch: [22] [ 150/1319] eta: 0:51:39 lr: 2.4230780959144606e-05 loss: 0.0484 (0.0480) time: 2.6029 data: 0.0063 max mem: 33369 +Epoch: [22] [ 160/1319] eta: 0:51:09 lr: 2.4221536685845908e-05 loss: 0.0430 (0.0478) time: 2.6052 data: 0.0062 max mem: 33369 +Epoch: [22] [ 170/1319] eta: 0:50:41 lr: 2.421229202051678e-05 loss: 0.0416 (0.0476) time: 2.6119 data: 0.0061 max mem: 33369 +Epoch: [22] [ 180/1319] eta: 0:50:12 lr: 2.420304696297427e-05 loss: 0.0412 (0.0473) time: 2.6194 data: 0.0063 max mem: 33369 +Epoch: [22] [ 190/1319] eta: 0:49:46 lr: 2.419380151303525e-05 loss: 0.0396 (0.0470) time: 2.6284 data: 0.0063 max mem: 33369 +Epoch: [22] [ 200/1319] eta: 0:49:20 lr: 2.418455567051645e-05 loss: 0.0391 (0.0468) time: 2.6514 data: 0.0061 max mem: 33369 +Epoch: [22] [ 210/1319] eta: 0:48:56 lr: 2.417530943523442e-05 loss: 0.0471 (0.0471) time: 2.6780 data: 0.0060 max mem: 33369 +Epoch: [22] [ 220/1319] eta: 0:48:27 lr: 2.416606280700555e-05 loss: 0.0418 (0.0467) time: 2.6486 data: 0.0059 max mem: 33369 +Epoch: [22] [ 230/1319] eta: 0:48:02 lr: 2.4156815785646067e-05 loss: 0.0418 (0.0470) time: 2.6349 data: 0.0060 max mem: 33369 +Epoch: [22] [ 240/1319] eta: 0:47:34 lr: 2.414756837097204e-05 loss: 0.0464 (0.0471) time: 2.6399 data: 0.0060 max mem: 33369 +Epoch: [22] [ 250/1319] eta: 0:47:08 lr: 2.4138320562799363e-05 loss: 0.0427 (0.0469) time: 2.6302 data: 0.0062 max mem: 33369 +Epoch: [22] [ 260/1319] eta: 0:46:40 lr: 2.412907236094378e-05 loss: 0.0394 (0.0470) time: 2.6361 data: 0.0060 max mem: 33369 +Epoch: [22] [ 270/1319] eta: 0:46:12 lr: 2.411982376522085e-05 loss: 0.0390 (0.0469) time: 2.6062 data: 0.0061 max mem: 33369 +Epoch: [22] [ 280/1319] eta: 0:45:43 lr: 2.411057477544598e-05 loss: 0.0385 (0.0471) time: 2.5826 data: 0.0063 max mem: 33369 +Epoch: [22] [ 290/1319] eta: 0:45:16 lr: 2.4101325391434414e-05 loss: 0.0416 (0.0471) time: 2.6009 data: 0.0061 max mem: 33369 +Epoch: [22] [ 300/1319] eta: 0:44:50 lr: 2.4092075613001218e-05 loss: 0.0418 (0.0470) time: 2.6470 data: 0.0060 max mem: 33369 +Epoch: [22] [ 310/1319] eta: 0:44:25 lr: 2.4082825439961318e-05 loss: 0.0364 (0.0470) time: 2.6614 data: 0.0061 max mem: 33369 +Epoch: [22] [ 320/1319] eta: 0:43:57 lr: 2.4073574872129434e-05 loss: 0.0347 (0.0468) time: 2.6283 data: 0.0060 max mem: 33369 +Epoch: [22] [ 330/1319] eta: 0:43:31 lr: 2.4064323909320154e-05 loss: 0.0388 (0.0468) time: 2.6351 data: 0.0060 max mem: 33369 +Epoch: [22] [ 340/1319] eta: 0:43:04 lr: 2.405507255134789e-05 loss: 0.0496 (0.0470) time: 2.6448 data: 0.0061 max mem: 33369 +Epoch: [22] [ 350/1319] eta: 0:42:38 lr: 2.404582079802688e-05 loss: 0.0511 (0.0475) time: 2.6284 data: 0.0061 max mem: 33369 +Epoch: [22] [ 360/1319] eta: 0:42:11 lr: 2.4036568649171213e-05 loss: 0.0514 (0.0477) time: 2.6288 data: 0.0060 max mem: 33369 +Epoch: [22] [ 370/1319] eta: 0:41:44 lr: 2.402731610459478e-05 loss: 0.0463 (0.0476) time: 2.6178 data: 0.0058 max mem: 33369 +Epoch: [22] [ 380/1319] eta: 0:41:18 lr: 2.401806316411133e-05 loss: 0.0414 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data: 0.0058 max mem: 33369 +Epoch: [22] [ 700/1319] eta: 0:27:06 lr: 2.3721758906333604e-05 loss: 0.0425 (0.0477) time: 2.5895 data: 0.0059 max mem: 33369 +Epoch: [22] [ 710/1319] eta: 0:26:40 lr: 2.3712492795320653e-05 loss: 0.0425 (0.0477) time: 2.6052 data: 0.0060 max mem: 33369 +Epoch: [22] [ 720/1319] eta: 0:26:13 lr: 2.3703226281966838e-05 loss: 0.0414 (0.0478) time: 2.6022 data: 0.0060 max mem: 33369 +Epoch: [22] [ 730/1319] eta: 0:25:47 lr: 2.36939593660799e-05 loss: 0.0395 (0.0478) time: 2.6057 data: 0.0059 max mem: 33369 +Epoch: [22] [ 740/1319] eta: 0:25:21 lr: 2.3684692047467423e-05 loss: 0.0444 (0.0478) time: 2.6435 data: 0.0058 max mem: 33369 +Epoch: [22] [ 750/1319] eta: 0:24:54 lr: 2.3675424325936787e-05 loss: 0.0437 (0.0477) time: 2.6213 data: 0.0059 max mem: 33369 +Epoch: [22] [ 760/1319] eta: 0:24:28 lr: 2.3666156201295225e-05 loss: 0.0340 (0.0476) time: 2.5973 data: 0.0059 max mem: 33369 +Epoch: [22] [ 770/1319] eta: 0:24:02 lr: 2.3656887673349775e-05 loss: 0.0339 (0.0475) time: 2.6078 data: 0.0061 max mem: 33369 +Epoch: [22] [ 780/1319] eta: 0:23:35 lr: 2.364761874190731e-05 loss: 0.0368 (0.0475) time: 2.6160 data: 0.0061 max mem: 33369 +Epoch: [22] [ 790/1319] eta: 0:23:09 lr: 2.363834940677452e-05 loss: 0.0455 (0.0475) time: 2.6112 data: 0.0061 max mem: 33369 +Epoch: [22] [ 800/1319] eta: 0:22:42 lr: 2.3629079667757912e-05 loss: 0.0498 (0.0476) time: 2.5939 data: 0.0062 max mem: 33369 +Epoch: [22] [ 810/1319] eta: 0:22:16 lr: 2.361980952466383e-05 loss: 0.0537 (0.0477) time: 2.6086 data: 0.0061 max mem: 33369 +Epoch: [22] [ 820/1319] eta: 0:21:50 lr: 2.3610538977298433e-05 loss: 0.0437 (0.0476) time: 2.6334 data: 0.0060 max mem: 33369 +Epoch: [22] [ 830/1319] eta: 0:21:24 lr: 2.3601268025467702e-05 loss: 0.0403 (0.0476) time: 2.6361 data: 0.0059 max mem: 33369 +Epoch: [22] [ 840/1319] eta: 0:20:58 lr: 2.3591996668977443e-05 loss: 0.0426 (0.0475) time: 2.6387 data: 0.0059 max mem: 33369 +Epoch: [22] [ 850/1319] eta: 0:20:31 lr: 2.3582724907633285e-05 loss: 0.0372 (0.0474) time: 2.6342 data: 0.0059 max mem: 33369 +Epoch: [22] [ 860/1319] eta: 0:20:05 lr: 2.3573452741240666e-05 loss: 0.0408 (0.0474) time: 2.6382 data: 0.0059 max mem: 33369 +Epoch: [22] [ 870/1319] eta: 0:19:39 lr: 2.3564180169604865e-05 loss: 0.0477 (0.0475) time: 2.6419 data: 0.0059 max mem: 33369 +Epoch: [22] [ 880/1319] eta: 0:19:13 lr: 2.3554907192530968e-05 loss: 0.0517 (0.0475) time: 2.6340 data: 0.0060 max mem: 33369 +Epoch: [22] [ 890/1319] eta: 0:18:46 lr: 2.3545633809823888e-05 loss: 0.0517 (0.0476) time: 2.6220 data: 0.0059 max mem: 33369 +Epoch: [22] [ 900/1319] eta: 0:18:20 lr: 2.353636002128836e-05 loss: 0.0465 (0.0476) time: 2.6247 data: 0.0057 max mem: 33369 +Epoch: [22] [ 910/1319] eta: 0:17:54 lr: 2.3527085826728933e-05 loss: 0.0461 (0.0476) time: 2.6327 data: 0.0059 max mem: 33369 +Epoch: [22] [ 920/1319] eta: 0:17:28 lr: 2.351781122594998e-05 loss: 0.0472 (0.0477) time: 2.6145 data: 0.0061 max mem: 33369 +Epoch: [22] [ 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33369 +Epoch: [22] [1010/1319] eta: 0:13:31 lr: 2.3434321506693e-05 loss: 0.0388 (0.0475) time: 2.6061 data: 0.0058 max mem: 33369 +Epoch: [22] [1020/1319] eta: 0:13:04 lr: 2.342504283291958e-05 loss: 0.0385 (0.0475) time: 2.6303 data: 0.0058 max mem: 33369 +Epoch: [22] [1030/1319] eta: 0:12:38 lr: 2.3415763750762803e-05 loss: 0.0363 (0.0474) time: 2.6521 data: 0.0058 max mem: 33369 +Epoch: [22] [1040/1319] eta: 0:12:12 lr: 2.3406484260024864e-05 loss: 0.0371 (0.0475) time: 2.6378 data: 0.0058 max mem: 33369 +Epoch: [22] [1050/1319] eta: 0:11:46 lr: 2.3397204360507778e-05 loss: 0.0463 (0.0476) time: 2.6203 data: 0.0059 max mem: 33369 +Epoch: [22] [1060/1319] eta: 0:11:19 lr: 2.3387924052013375e-05 loss: 0.0463 (0.0474) time: 2.6191 data: 0.0058 max mem: 33369 +Epoch: [22] [1070/1319] eta: 0:10:53 lr: 2.3378643334343302e-05 loss: 0.0386 (0.0475) time: 2.6046 data: 0.0058 max mem: 33369 +Epoch: [22] [1080/1319] eta: 0:10:27 lr: 2.3369362207299018e-05 loss: 0.0422 (0.0474) time: 2.5835 data: 0.0058 max mem: 33369 +Epoch: [22] [1090/1319] eta: 0:10:00 lr: 2.3360080670681804e-05 loss: 0.0391 (0.0475) time: 2.6020 data: 0.0058 max mem: 33369 +Epoch: [22] [1100/1319] eta: 0:09:34 lr: 2.335079872429276e-05 loss: 0.0374 (0.0475) time: 2.6320 data: 0.0059 max mem: 33369 +Epoch: [22] [1110/1319] eta: 0:09:08 lr: 2.334151636793279e-05 loss: 0.0375 (0.0475) time: 2.6273 data: 0.0059 max mem: 33369 +Epoch: [22] [1120/1319] eta: 0:08:42 lr: 2.333223360140262e-05 loss: 0.0428 (0.0475) time: 2.6153 data: 0.0058 max mem: 33369 +Epoch: [22] [1130/1319] eta: 0:08:16 lr: 2.3322950424502793e-05 loss: 0.0478 (0.0475) time: 2.6256 data: 0.0059 max mem: 33369 +Epoch: [22] [1140/1319] eta: 0:07:49 lr: 2.3313666837033663e-05 loss: 0.0463 (0.0475) time: 2.6141 data: 0.0059 max mem: 33369 +Epoch: [22] [1150/1319] eta: 0:07:23 lr: 2.33043828387954e-05 loss: 0.0402 (0.0474) time: 2.6043 data: 0.0059 max mem: 33369 +Epoch: [22] [1160/1319] eta: 0:06:57 lr: 2.3295098429587987e-05 loss: 0.0392 (0.0474) time: 2.6287 data: 0.0060 max mem: 33369 +Epoch: [22] [1170/1319] eta: 0:06:31 lr: 2.328581360921123e-05 loss: 0.0407 (0.0474) time: 2.6309 data: 0.0059 max mem: 33369 +Epoch: [22] [1180/1319] eta: 0:06:04 lr: 2.327652837746473e-05 loss: 0.0462 (0.0474) time: 2.6072 data: 0.0059 max mem: 33369 +Epoch: [22] [1190/1319] eta: 0:05:38 lr: 2.3267242734147912e-05 loss: 0.0355 (0.0474) time: 2.6159 data: 0.0061 max mem: 33369 +Epoch: [22] [1200/1319] eta: 0:05:12 lr: 2.325795667906002e-05 loss: 0.0386 (0.0474) time: 2.6011 data: 0.0061 max mem: 33369 +Epoch: [22] [1210/1319] eta: 0:04:45 lr: 2.3248670212000107e-05 loss: 0.0504 (0.0475) time: 2.5966 data: 0.0059 max mem: 33369 +Epoch: [22] [1220/1319] eta: 0:04:19 lr: 2.3239383332767037e-05 loss: 0.0507 (0.0475) time: 2.6324 data: 0.0059 max mem: 33369 +Epoch: [22] [1230/1319] eta: 0:03:53 lr: 2.323009604115948e-05 loss: 0.0437 (0.0475) time: 2.6272 data: 0.0060 max mem: 33369 +Epoch: [22] [1240/1319] eta: 0:03:27 lr: 2.322080833697593e-05 loss: 0.0436 (0.0475) time: 2.6106 data: 0.0059 max mem: 33369 +Epoch: [22] [1250/1319] eta: 0:03:01 lr: 2.3211520220014678e-05 loss: 0.0454 (0.0475) time: 2.6041 data: 0.0059 max mem: 33369 +Epoch: [22] [1260/1319] eta: 0:02:34 lr: 2.320223169007385e-05 loss: 0.0409 (0.0475) time: 2.6148 data: 0.0058 max mem: 33369 +Epoch: [22] [1270/1319] eta: 0:02:08 lr: 2.319294274695137e-05 loss: 0.0369 (0.0475) time: 2.6358 data: 0.0057 max mem: 33369 +Epoch: [22] [1280/1319] eta: 0:01:42 lr: 2.318365339044496e-05 loss: 0.0398 (0.0475) time: 2.6288 data: 0.0058 max mem: 33369 +Epoch: [22] [1290/1319] eta: 0:01:16 lr: 2.3174363620352174e-05 loss: 0.0423 (0.0475) time: 2.6263 data: 0.0058 max mem: 33369 +Epoch: [22] [1300/1319] eta: 0:00:49 lr: 2.3165073436470368e-05 loss: 0.0430 (0.0475) time: 2.6359 data: 0.0059 max mem: 33369 +Epoch: [22] [1310/1319] eta: 0:00:23 lr: 2.3155782838596706e-05 loss: 0.0500 (0.0476) time: 2.6271 data: 0.0058 max mem: 33369 +Epoch: [22] Total time: 0:57:41 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 1:54:14 time: 2.6641 data: 2.5698 max mem: 33369 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 100/2573] eta: 0:04:02 time: 0.0715 data: 0.0011 max mem: 33369 +Test: [ 200/2573] eta: 0:03:24 time: 0.0730 data: 0.0011 max mem: 33369 +Test: [ 300/2573] eta: 0:03:04 time: 0.0745 data: 0.0011 max mem: 33369 +Test: [ 400/2573] eta: 0:02:51 time: 0.0746 data: 0.0011 max mem: 33369 +Test: [ 500/2573] eta: 0:02:41 time: 0.0733 data: 0.0011 max mem: 33369 +Test: [ 600/2573] eta: 0:02:32 time: 0.0733 data: 0.0011 max mem: 33369 +Test: [ 700/2573] eta: 0:02:24 time: 0.0733 data: 0.0011 max mem: 33369 +Test: [ 800/2573] eta: 0:02:16 time: 0.0769 data: 0.0011 max mem: 33369 +Test: [ 900/2573] eta: 0:02:07 time: 0.0737 data: 0.0011 max mem: 33369 +Test: [1000/2573] eta: 0:01:59 time: 0.0734 data: 0.0011 max mem: 33369 +Test: [1100/2573] eta: 0:01:51 time: 0.0734 data: 0.0011 max mem: 33369 +Test: [1200/2573] eta: 0:01:44 time: 0.0734 data: 0.0011 max mem: 33369 +Test: [1300/2573] eta: 0:01:36 time: 0.0734 data: 0.0010 max mem: 33369 +Test: [1400/2573] eta: 0:01:28 time: 0.0719 data: 0.0011 max mem: 33369 +Test: [1500/2573] eta: 0:01:20 time: 0.0736 data: 0.0011 max mem: 33369 +Test: [1600/2573] eta: 0:01:13 time: 0.0769 data: 0.0011 max mem: 33369 +Test: [1700/2573] eta: 0:01:05 time: 0.0720 data: 0.0011 max mem: 33369 +Test: [1800/2573] eta: 0:00:58 time: 0.0753 data: 0.0011 max mem: 33369 +Test: [1900/2573] eta: 0:00:50 time: 0.0720 data: 0.0011 max mem: 33369 +Test: [2000/2573] eta: 0:00:42 time: 0.0736 data: 0.0011 max mem: 33369 +Test: [2100/2573] eta: 0:00:35 time: 0.0753 data: 0.0010 max mem: 33369 +Test: [2200/2573] eta: 0:00:27 time: 0.0753 data: 0.0011 max mem: 33369 +Test: [2300/2573] eta: 0:00:20 time: 0.0754 data: 0.0011 max mem: 33369 +Test: [2400/2573] eta: 0:00:12 time: 0.0704 data: 0.0011 max mem: 33369 +Test: [2500/2573] eta: 0:00:05 time: 0.0737 data: 0.0011 max mem: 33369 +Test: Total time: 0:03:12 +Final results: +Mean IoU is 64.35 + + precision@0.5 = 72.55 + precision@0.6 = 67.57 + precision@0.7 = 60.62 + precision@0.8 = 49.61 + precision@0.9 = 24.63 + overall IoU = 61.66 + +Average object IoU 64.351232406239 +Overall IoU 61.657859802246094 +Better epoch: 22 + +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [23] [ 0/1319] eta: 1:30:21 lr: 2.3147420946379584e-05 loss: 0.1074 (0.1074) time: 4.1101 data: 1.4418 max mem: 33369 +Epoch: [23] [ 10/1319] eta: 0:59:20 lr: 2.313812956136191e-05 loss: 0.0387 (0.0449) time: 2.7197 data: 0.1364 max mem: 33369 +Epoch: [23] [ 20/1319] eta: 0:58:09 lr: 2.3128837761763095e-05 loss: 0.0454 (0.0501) time: 2.6154 data: 0.0060 max mem: 33369 +Epoch: [23] [ 30/1319] eta: 0:57:13 lr: 2.3119545547379566e-05 loss: 0.0477 (0.0504) time: 2.6335 data: 0.0062 max mem: 33369 +Epoch: [23] [ 40/1319] eta: 0:56:44 lr: 2.3110252918007542e-05 loss: 0.0400 (0.0476) time: 2.6354 data: 0.0061 max mem: 33369 +Epoch: [23] [ 50/1319] eta: 0:56:10 lr: 2.3100959873443074e-05 loss: 0.0388 (0.0467) time: 2.6445 data: 0.0061 max mem: 33369 +Epoch: [23] [ 60/1319] eta: 0:55:40 lr: 2.3091666413482015e-05 loss: 0.0388 (0.0486) time: 2.6356 data: 0.0061 max mem: 33369 +Epoch: [23] [ 70/1319] eta: 0:55:15 lr: 2.3082372537920018e-05 loss: 0.0400 (0.0477) time: 2.6502 data: 0.0061 max mem: 33369 +Epoch: [23] [ 80/1319] eta: 0:54:53 lr: 2.307307824655256e-05 loss: 0.0440 (0.0474) time: 2.6749 data: 0.0061 max mem: 33369 +Epoch: [23] [ 90/1319] eta: 0:54:20 lr: 2.3063783539174907e-05 loss: 0.0423 (0.0475) time: 2.6484 data: 0.0062 max mem: 33369 +Epoch: [23] [ 100/1319] eta: 0:53:50 lr: 2.3054488415582145e-05 loss: 0.0405 (0.0465) time: 2.6150 data: 0.0062 max mem: 33369 +Epoch: [23] [ 110/1319] eta: 0:53:22 lr: 2.3045192875569164e-05 loss: 0.0368 (0.0460) time: 2.6276 data: 0.0062 max mem: 33369 +Epoch: [23] [ 120/1319] eta: 0:52:51 lr: 2.3035896918930662e-05 loss: 0.0417 (0.0473) time: 2.6206 data: 0.0063 max mem: 33369 +Epoch: [23] [ 130/1319] eta: 0:52:23 lr: 2.3026600545461138e-05 loss: 0.0452 (0.0476) time: 2.6158 data: 0.0063 max mem: 33369 +Epoch: [23] [ 140/1319] eta: 0:51:56 lr: 2.3017303754954915e-05 loss: 0.0362 (0.0472) time: 2.6361 data: 0.0062 max mem: 33369 +Epoch: [23] [ 150/1319] eta: 0:51:30 lr: 2.300800654720609e-05 loss: 0.0350 (0.0466) time: 2.6450 data: 0.0061 max mem: 33369 +Epoch: [23] [ 160/1319] eta: 0:51:03 lr: 2.2998708922008593e-05 loss: 0.0400 (0.0467) time: 2.6412 data: 0.0060 max mem: 33369 +Epoch: [23] [ 170/1319] eta: 0:50:35 lr: 2.2989410879156158e-05 loss: 0.0443 (0.0466) time: 2.6274 data: 0.0062 max mem: 33369 +Epoch: [23] [ 180/1319] eta: 0:50:11 lr: 2.298011241844231e-05 loss: 0.0420 (0.0467) time: 2.6499 data: 0.0062 max mem: 33369 +Epoch: [23] [ 190/1319] eta: 0:49:46 lr: 2.2970813539660394e-05 loss: 0.0358 (0.0461) time: 2.6711 data: 0.0061 max mem: 33369 +Epoch: [23] [ 200/1319] eta: 0:49:18 lr: 2.296151424260354e-05 loss: 0.0362 (0.0459) time: 2.6374 data: 0.0062 max mem: 33369 +Epoch: [23] [ 210/1319] eta: 0:48:51 lr: 2.2952214527064705e-05 loss: 0.0376 (0.0458) time: 2.6264 data: 0.0062 max mem: 33369 +Epoch: [23] [ 220/1319] eta: 0:48:26 lr: 2.294291439283664e-05 loss: 0.0404 (0.0455) time: 2.6588 data: 0.0062 max mem: 33369 +Epoch: [23] [ 230/1319] eta: 0:47:56 lr: 2.2933613839711898e-05 loss: 0.0404 (0.0454) time: 2.6243 data: 0.0062 max mem: 33369 +Epoch: [23] [ 240/1319] eta: 0:47:28 lr: 2.292431286748284e-05 loss: 0.0441 (0.0454) time: 2.5893 data: 0.0061 max mem: 33369 +Epoch: [23] [ 250/1319] eta: 0:47:00 lr: 2.2915011475941626e-05 loss: 0.0406 (0.0453) time: 2.5967 data: 0.0062 max mem: 33369 +Epoch: [23] [ 260/1319] eta: 0:46:31 lr: 2.2905709664880228e-05 loss: 0.0406 (0.0452) time: 2.5864 data: 0.0064 max mem: 33369 +Epoch: [23] [ 270/1319] eta: 0:46:05 lr: 2.28964074340904e-05 loss: 0.0400 (0.0450) time: 2.6210 data: 0.0062 max mem: 33369 +Epoch: [23] [ 280/1319] eta: 0:45:39 lr: 2.2887104783363728e-05 loss: 0.0346 (0.0450) time: 2.6435 data: 0.0060 max mem: 33369 +Epoch: [23] [ 290/1319] eta: 0:45:13 lr: 2.2877801712491578e-05 loss: 0.0393 (0.0449) time: 2.6427 data: 0.0061 max mem: 33369 +Epoch: [23] [ 300/1319] eta: 0:44:46 lr: 2.2868498221265136e-05 loss: 0.0390 (0.0449) time: 2.6312 data: 0.0062 max mem: 33369 +Epoch: [23] [ 310/1319] eta: 0:44:21 lr: 2.2859194309475363e-05 loss: 0.0457 (0.0451) time: 2.6542 data: 0.0062 max mem: 33369 +Epoch: [23] [ 320/1319] eta: 0:43:55 lr: 2.2849889976913045e-05 loss: 0.0476 (0.0456) time: 2.6684 data: 0.0060 max mem: 33369 +Epoch: [23] [ 330/1319] eta: 0:43:30 lr: 2.2840585223368763e-05 loss: 0.0470 (0.0456) time: 2.6518 data: 0.0059 max mem: 33369 +Epoch: [23] [ 340/1319] eta: 0:43:02 lr: 2.2831280048632893e-05 loss: 0.0436 (0.0455) time: 2.6359 data: 0.0060 max mem: 33369 +Epoch: [23] [ 350/1319] eta: 0:42:36 lr: 2.282197445249563e-05 loss: 0.0411 (0.0457) time: 2.6273 data: 0.0061 max mem: 33369 +Epoch: [23] [ 360/1319] eta: 0:42:10 lr: 2.2812668434746943e-05 loss: 0.0416 (0.0458) time: 2.6404 data: 0.0061 max mem: 33369 +Epoch: [23] [ 370/1319] eta: 0:41:43 lr: 2.2803361995176614e-05 loss: 0.0427 (0.0457) time: 2.6402 data: 0.0061 max mem: 33369 +Epoch: [23] [ 380/1319] eta: 0:41:16 lr: 2.279405513357423e-05 loss: 0.0467 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2.2719585022284628e-05 loss: 0.0408 (0.0463) time: 2.6218 data: 0.0061 max mem: 33369 +Epoch: [23] [ 470/1319] eta: 0:37:15 lr: 2.2710274352891738e-05 loss: 0.0448 (0.0465) time: 2.6144 data: 0.0061 max mem: 33369 +Epoch: [23] [ 480/1319] eta: 0:36:49 lr: 2.2700963259351535e-05 loss: 0.0447 (0.0464) time: 2.6170 data: 0.0062 max mem: 33369 +Epoch: [23] [ 490/1319] eta: 0:36:23 lr: 2.269165174145138e-05 loss: 0.0410 (0.0463) time: 2.6343 data: 0.0062 max mem: 33369 +Epoch: [23] [ 500/1319] eta: 0:35:56 lr: 2.2682339798978432e-05 loss: 0.0426 (0.0464) time: 2.6243 data: 0.0061 max mem: 33369 +Epoch: [23] [ 510/1319] eta: 0:35:29 lr: 2.2673027431719644e-05 loss: 0.0445 (0.0464) time: 2.6075 data: 0.0061 max mem: 33369 +Epoch: [23] [ 520/1319] eta: 0:35:02 lr: 2.266371463946176e-05 loss: 0.0445 (0.0469) time: 2.6101 data: 0.0061 max mem: 33369 +Epoch: [23] [ 530/1319] eta: 0:34:36 lr: 2.2654401421991334e-05 loss: 0.0460 (0.0470) time: 2.6287 data: 0.0063 max mem: 33369 +Epoch: [23] [ 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data: 0.0061 max mem: 33369 +Epoch: [23] [ 700/1319] eta: 0:27:07 lr: 2.2496011459639643e-05 loss: 0.0377 (0.0470) time: 2.6071 data: 0.0060 max mem: 33369 +Epoch: [23] [ 710/1319] eta: 0:26:41 lr: 2.2486690551607674e-05 loss: 0.0399 (0.0470) time: 2.5999 data: 0.0060 max mem: 33369 +Epoch: [23] [ 720/1319] eta: 0:26:14 lr: 2.2477369214268278e-05 loss: 0.0407 (0.0469) time: 2.6040 data: 0.0061 max mem: 33369 +Epoch: [23] [ 730/1319] eta: 0:25:48 lr: 2.246804744740384e-05 loss: 0.0426 (0.0469) time: 2.6208 data: 0.0061 max mem: 33369 +Epoch: [23] [ 740/1319] eta: 0:25:22 lr: 2.245872525079654e-05 loss: 0.0403 (0.0469) time: 2.6414 data: 0.0059 max mem: 33369 +Epoch: [23] [ 750/1319] eta: 0:24:56 lr: 2.244940262422835e-05 loss: 0.0395 (0.0470) time: 2.6307 data: 0.0058 max mem: 33369 +Epoch: [23] [ 760/1319] eta: 0:24:29 lr: 2.244007956748104e-05 loss: 0.0423 (0.0471) time: 2.6247 data: 0.0057 max mem: 33369 +Epoch: [23] [ 770/1319] eta: 0:24:03 lr: 2.243075608033615e-05 loss: 0.0427 (0.0471) time: 2.6245 data: 0.0059 max mem: 33369 +Epoch: [23] [ 780/1319] eta: 0:23:37 lr: 2.242143216257503e-05 loss: 0.0451 (0.0471) time: 2.6202 data: 0.0060 max mem: 33369 +Epoch: [23] [ 790/1319] eta: 0:23:10 lr: 2.2412107813978792e-05 loss: 0.0458 (0.0472) time: 2.6315 data: 0.0058 max mem: 33369 +Epoch: [23] [ 800/1319] eta: 0:22:43 lr: 2.240278303432835e-05 loss: 0.0489 (0.0474) time: 2.5841 data: 0.0059 max mem: 33369 +Epoch: [23] [ 810/1319] eta: 0:22:17 lr: 2.2393457823404408e-05 loss: 0.0489 (0.0474) time: 2.5659 data: 0.0062 max mem: 33369 +Epoch: [23] [ 820/1319] eta: 0:21:51 lr: 2.2384132180987457e-05 loss: 0.0426 (0.0474) time: 2.6114 data: 0.0063 max mem: 33369 +Epoch: [23] [ 830/1319] eta: 0:21:24 lr: 2.2374806106857758e-05 loss: 0.0406 (0.0473) time: 2.6227 data: 0.0061 max mem: 33369 +Epoch: [23] [ 840/1319] eta: 0:20:58 lr: 2.2365479600795384e-05 loss: 0.0453 (0.0474) time: 2.6325 data: 0.0060 max mem: 33369 +Epoch: [23] [ 850/1319] eta: 0:20:32 lr: 2.2356152662580173e-05 loss: 0.0442 (0.0473) time: 2.6329 data: 0.0059 max mem: 33369 +Epoch: [23] [ 860/1319] eta: 0:20:05 lr: 2.234682529199176e-05 loss: 0.0363 (0.0472) time: 2.6112 data: 0.0059 max mem: 33369 +Epoch: [23] [ 870/1319] eta: 0:19:39 lr: 2.2337497488809557e-05 loss: 0.0379 (0.0472) time: 2.6253 data: 0.0058 max mem: 33369 +Epoch: [23] [ 880/1319] eta: 0:19:13 lr: 2.232816925281277e-05 loss: 0.0344 (0.0471) time: 2.6329 data: 0.0058 max mem: 33369 +Epoch: [23] [ 890/1319] eta: 0:18:47 lr: 2.2318840583780386e-05 loss: 0.0380 (0.0471) time: 2.6370 data: 0.0060 max mem: 33369 +Epoch: [23] [ 900/1319] eta: 0:18:20 lr: 2.2309511481491173e-05 loss: 0.0428 (0.0470) time: 2.6323 data: 0.0060 max mem: 33369 +Epoch: [23] [ 910/1319] eta: 0:17:54 lr: 2.2300181945723685e-05 loss: 0.0428 (0.0470) time: 2.6284 data: 0.0059 max mem: 33369 +Epoch: [23] [ 920/1319] eta: 0:17:28 lr: 2.2290851976256266e-05 loss: 0.0458 (0.0470) time: 2.6472 data: 0.0060 max mem: 33369 +Epoch: [23] [ 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mem: 33369 +Epoch: [23] [1010/1319] eta: 0:13:32 lr: 2.2206862697871013e-05 loss: 0.0517 (0.0472) time: 2.6294 data: 0.0061 max mem: 33369 +Epoch: [23] [1020/1319] eta: 0:13:05 lr: 2.2197528379165116e-05 loss: 0.0492 (0.0472) time: 2.6058 data: 0.0061 max mem: 33369 +Epoch: [23] [1030/1319] eta: 0:12:39 lr: 2.218819362430666e-05 loss: 0.0404 (0.0472) time: 2.6132 data: 0.0059 max mem: 33369 +Epoch: [23] [1040/1319] eta: 0:12:13 lr: 2.217885843307136e-05 loss: 0.0404 (0.0472) time: 2.6129 data: 0.0061 max mem: 33369 +Epoch: [23] [1050/1319] eta: 0:11:46 lr: 2.2169522805234726e-05 loss: 0.0461 (0.0472) time: 2.6014 data: 0.0061 max mem: 33369 +Epoch: [23] [1060/1319] eta: 0:11:20 lr: 2.2160186740572026e-05 loss: 0.0405 (0.0471) time: 2.6087 data: 0.0059 max mem: 33369 +Epoch: [23] [1070/1319] eta: 0:10:54 lr: 2.215085023885832e-05 loss: 0.0443 (0.0472) time: 2.6201 data: 0.0058 max mem: 33369 +Epoch: [23] [1080/1319] eta: 0:10:27 lr: 2.2141513299868444e-05 loss: 0.0515 (0.0472) time: 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0.0335 (0.0472) time: 2.6416 data: 0.0060 max mem: 33369 +Epoch: [23] [1170/1319] eta: 0:06:31 lr: 2.2057461134270328e-05 loss: 0.0358 (0.0472) time: 2.6568 data: 0.0059 max mem: 33369 +Epoch: [23] [1180/1319] eta: 0:06:05 lr: 2.2048119810085938e-05 loss: 0.0386 (0.0472) time: 2.6451 data: 0.0061 max mem: 33369 +Epoch: [23] [1190/1319] eta: 0:05:39 lr: 2.2038778046133896e-05 loss: 0.0466 (0.0473) time: 2.6177 data: 0.0061 max mem: 33369 +Epoch: [23] [1200/1319] eta: 0:05:12 lr: 2.2029435842186362e-05 loss: 0.0495 (0.0473) time: 2.6227 data: 0.0061 max mem: 33369 +Epoch: [23] [1210/1319] eta: 0:04:46 lr: 2.2020093198015273e-05 loss: 0.0431 (0.0473) time: 2.6219 data: 0.0061 max mem: 33369 +Epoch: [23] [1220/1319] eta: 0:04:20 lr: 2.2010750113392324e-05 loss: 0.0388 (0.0472) time: 2.6115 data: 0.0061 max mem: 33369 +Epoch: [23] [1230/1319] eta: 0:03:53 lr: 2.2001406588088997e-05 loss: 0.0439 (0.0472) time: 2.6215 data: 0.0061 max mem: 33369 +Epoch: [23] [1240/1319] eta: 0:03:27 lr: 2.199206262187655e-05 loss: 0.0431 (0.0473) time: 2.6201 data: 0.0061 max mem: 33369 +Epoch: [23] [1250/1319] eta: 0:03:01 lr: 2.1982718214526003e-05 loss: 0.0398 (0.0473) time: 2.6111 data: 0.0062 max mem: 33369 +Epoch: [23] [1260/1319] eta: 0:02:35 lr: 2.1973373365808168e-05 loss: 0.0428 (0.0472) time: 2.6198 data: 0.0061 max mem: 33369 +Epoch: [23] [1270/1319] eta: 0:02:08 lr: 2.1964028075493602e-05 loss: 0.0451 (0.0474) time: 2.6435 data: 0.0059 max mem: 33369 +Epoch: [23] [1280/1319] eta: 0:01:42 lr: 2.1954682343352655e-05 loss: 0.0400 (0.0474) time: 2.6338 data: 0.0059 max mem: 33369 +Epoch: [23] [1290/1319] eta: 0:01:16 lr: 2.1945336169155447e-05 loss: 0.0400 (0.0473) time: 2.6472 data: 0.0059 max mem: 33369 +Epoch: [23] [1300/1319] eta: 0:00:49 lr: 2.1935989552671862e-05 loss: 0.0391 (0.0473) time: 2.6392 data: 0.0058 max mem: 33369 +Epoch: [23] [1310/1319] eta: 0:00:23 lr: 2.192664249367156e-05 loss: 0.0413 (0.0473) time: 2.6250 data: 0.0058 max mem: 33369 +Epoch: [23] Total time: 0:57:46 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 2:05:46 time: 2.9330 data: 2.8539 max mem: 33369 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 100/2573] eta: 0:04:07 time: 0.0714 data: 0.0011 max mem: 33369 +Test: [ 200/2573] eta: 0:03:26 time: 0.0732 data: 0.0011 max mem: 33369 +Test: [ 300/2573] eta: 0:03:06 time: 0.0751 data: 0.0011 max mem: 33369 +Test: [ 400/2573] eta: 0:02:53 time: 0.0751 data: 0.0011 max mem: 33369 +Test: [ 500/2573] eta: 0:02:42 time: 0.0735 data: 0.0011 max mem: 33369 +Test: [ 600/2573] eta: 0:02:33 time: 0.0735 data: 0.0011 max mem: 33369 +Test: [ 700/2573] eta: 0:02:25 time: 0.0735 data: 0.0011 max mem: 33369 +Test: [ 800/2573] eta: 0:02:16 time: 0.0769 data: 0.0011 max mem: 33369 +Test: [ 900/2573] eta: 0:02:08 time: 0.0737 data: 0.0011 max mem: 33369 +Test: [1000/2573] eta: 0:02:00 time: 0.0737 data: 0.0011 max mem: 33369 +Test: [1100/2573] eta: 0:01:52 time: 0.0737 data: 0.0011 max mem: 33369 +Test: [1200/2573] eta: 0:01:44 time: 0.0736 data: 0.0011 max mem: 33369 +Test: [1300/2573] eta: 0:01:36 time: 0.0736 data: 0.0011 max mem: 33369 +Test: [1400/2573] eta: 0:01:28 time: 0.0721 data: 0.0011 max mem: 33369 +Test: [1500/2573] eta: 0:01:21 time: 0.0738 data: 0.0011 max mem: 33369 +Test: [1600/2573] eta: 0:01:13 time: 0.0771 data: 0.0011 max mem: 33369 +Test: [1700/2573] eta: 0:01:05 time: 0.0721 data: 0.0011 max mem: 33369 +Test: [1800/2573] eta: 0:00:58 time: 0.0755 data: 0.0011 max mem: 33369 +Test: [1900/2573] eta: 0:00:50 time: 0.0722 data: 0.0011 max mem: 33369 +Test: [2000/2573] eta: 0:00:43 time: 0.0739 data: 0.0011 max mem: 33369 +Test: [2100/2573] eta: 0:00:35 time: 0.0755 data: 0.0011 max mem: 33369 +Test: [2200/2573] eta: 0:00:27 time: 0.0755 data: 0.0011 max mem: 33369 +Test: [2300/2573] eta: 0:00:20 time: 0.0755 data: 0.0012 max mem: 33369 +Test: [2400/2573] eta: 0:00:12 time: 0.0708 data: 0.0011 max mem: 33369 +Test: [2500/2573] eta: 0:00:05 time: 0.0739 data: 0.0011 max mem: 33369 +Test: Total time: 0:03:13 +Final results: +Mean IoU is 63.95 + + precision@0.5 = 72.20 + precision@0.6 = 66.63 + precision@0.7 = 60.01 + precision@0.8 = 49.06 + precision@0.9 = 24.61 + overall IoU = 61.32 + +Average object IoU 63.946299588171044 +Overall IoU 61.31767272949219 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [24] [ 0/1319] eta: 3:21:46 lr: 2.1918229762028934e-05 loss: 0.0867 (0.0867) time: 9.1786 data: 1.3894 max mem: 33369 +Epoch: [24] [ 10/1319] eta: 1:09:38 lr: 2.1908881861611456e-05 loss: 0.0496 (0.0551) time: 3.1919 data: 0.1319 max mem: 33369 +Epoch: [24] [ 20/1319] eta: 1:03:33 lr: 2.1899533518007982e-05 loss: 0.0434 (0.0546) time: 2.6234 data: 0.0061 max mem: 33369 +Epoch: [24] [ 30/1319] eta: 1:00:45 lr: 2.189018473098726e-05 loss: 0.0434 (0.0508) time: 2.6284 data: 0.0062 max mem: 33369 +Epoch: [24] [ 40/1319] eta: 0:59:08 lr: 2.188083550031783e-05 loss: 0.0392 (0.0543) time: 2.6057 data: 0.0064 max mem: 33369 +Epoch: [24] [ 50/1319] eta: 0:58:02 lr: 2.1871485825767997e-05 loss: 0.0399 (0.0534) time: 2.6143 data: 0.0062 max mem: 33369 +Epoch: [24] [ 60/1319] eta: 0:57:08 lr: 2.1862135707105826e-05 loss: 0.0377 (0.0512) time: 2.6189 data: 0.0062 max mem: 33369 +Epoch: [24] [ 70/1319] eta: 0:56:28 lr: 2.1852785144099174e-05 loss: 0.0356 (0.0499) time: 2.6333 data: 0.0062 max mem: 33369 +Epoch: [24] [ 80/1319] eta: 0:55:47 lr: 2.184343413651562e-05 loss: 0.0372 (0.0484) time: 2.6350 data: 0.0062 max mem: 33369 +Epoch: [24] [ 90/1319] eta: 0:55:02 lr: 2.1834082684122557e-05 loss: 0.0374 (0.0480) time: 2.5957 data: 0.0063 max mem: 33369 +Epoch: [24] [ 100/1319] eta: 0:54:30 lr: 2.1824730786687132e-05 loss: 0.0391 (0.0482) time: 2.6075 data: 0.0062 max mem: 33369 +Epoch: [24] [ 110/1319] eta: 0:53:55 lr: 2.181537844397624e-05 loss: 0.0404 (0.0476) time: 2.6271 data: 0.0061 max mem: 33369 +Epoch: [24] [ 120/1319] eta: 0:53:22 lr: 2.1806025655756576e-05 loss: 0.0377 (0.0470) time: 2.6094 data: 0.0062 max mem: 33369 +Epoch: [24] [ 130/1319] eta: 0:52:50 lr: 2.1796672421794575e-05 loss: 0.0406 (0.0478) time: 2.6108 data: 0.0063 max mem: 33369 +Epoch: [24] [ 140/1319] eta: 0:52:17 lr: 2.1787318741856443e-05 loss: 0.0406 (0.0476) time: 2.6052 data: 0.0062 max mem: 33369 +Epoch: [24] [ 150/1319] eta: 0:51:50 lr: 2.1777964615708157e-05 loss: 0.0370 (0.0471) time: 2.6228 data: 0.0062 max mem: 33369 +Epoch: [24] [ 160/1319] eta: 0:51:21 lr: 2.1768610043115462e-05 loss: 0.0422 (0.0468) time: 2.6421 data: 0.0061 max mem: 33369 +Epoch: [24] [ 170/1319] eta: 0:50:55 lr: 2.1759255023843863e-05 loss: 0.0403 (0.0465) time: 2.6492 data: 0.0061 max mem: 33369 +Epoch: [24] [ 180/1319] eta: 0:50:28 lr: 2.1749899557658636e-05 loss: 0.0390 (0.0462) time: 2.6552 data: 0.0062 max mem: 33369 +Epoch: [24] [ 190/1319] eta: 0:50:00 lr: 2.17405436443248e-05 loss: 0.0412 (0.0462) time: 2.6444 data: 0.0061 max mem: 33369 +Epoch: [24] [ 200/1319] eta: 0:49:32 lr: 2.1731187283607167e-05 loss: 0.0397 (0.0459) time: 2.6370 data: 0.0062 max mem: 33369 +Epoch: [24] [ 210/1319] eta: 0:49:06 lr: 2.17218304752703e-05 loss: 0.0400 (0.0463) time: 2.6527 data: 0.0062 max mem: 33369 +Epoch: [24] [ 220/1319] eta: 0:48:38 lr: 2.171247321907852e-05 loss: 0.0523 (0.0465) time: 2.6438 data: 0.0061 max mem: 33369 +Epoch: [24] [ 230/1319] eta: 0:48:11 lr: 2.1703115514795925e-05 loss: 0.0523 (0.0476) time: 2.6290 data: 0.0060 max mem: 33369 +Epoch: [24] [ 240/1319] eta: 0:47:45 lr: 2.1693757362186356e-05 loss: 0.0457 (0.0474) time: 2.6550 data: 0.0060 max mem: 33369 +Epoch: [24] [ 250/1319] eta: 0:47:17 lr: 2.1684398761013434e-05 loss: 0.0397 (0.0472) time: 2.6461 data: 0.0060 max mem: 33369 +Epoch: [24] [ 260/1319] eta: 0:46:48 lr: 2.1675039711040532e-05 loss: 0.0397 (0.0470) time: 2.6174 data: 0.0061 max mem: 33369 +Epoch: [24] [ 270/1319] eta: 0:46:21 lr: 2.166568021203079e-05 loss: 0.0422 (0.0474) time: 2.6162 data: 0.0062 max mem: 33369 +Epoch: [24] [ 280/1319] eta: 0:45:53 lr: 2.1656320263747106e-05 loss: 0.0390 (0.0470) time: 2.6206 data: 0.0061 max mem: 33369 +Epoch: [24] [ 290/1319] eta: 0:45:28 lr: 2.164695986595215e-05 loss: 0.0388 (0.0470) time: 2.6504 data: 0.0061 max mem: 33369 +Epoch: [24] [ 300/1319] eta: 0:45:00 lr: 2.163759901840832e-05 loss: 0.0437 (0.0470) time: 2.6536 data: 0.0060 max mem: 33369 +Epoch: [24] [ 310/1319] eta: 0:44:33 lr: 2.1628237720877814e-05 loss: 0.0460 (0.0475) time: 2.6275 data: 0.0061 max mem: 33369 +Epoch: [24] [ 320/1319] eta: 0:44:04 lr: 2.161887597312257e-05 loss: 0.0438 (0.0473) time: 2.5970 data: 0.0064 max mem: 33369 +Epoch: [24] [ 330/1319] eta: 0:43:36 lr: 2.160951377490428e-05 loss: 0.0371 (0.0469) time: 2.5828 data: 0.0063 max mem: 33369 +Epoch: [24] [ 340/1319] eta: 0:43:09 lr: 2.160015112598442e-05 loss: 0.0375 (0.0470) time: 2.6198 data: 0.0063 max mem: 33369 +Epoch: [24] [ 350/1319] eta: 0:42:42 lr: 2.1590788026124187e-05 loss: 0.0408 (0.0467) time: 2.6246 data: 0.0062 max mem: 33369 +Epoch: [24] [ 360/1319] eta: 0:42:16 lr: 2.158142447508457e-05 loss: 0.0408 (0.0466) time: 2.6385 data: 0.0061 max mem: 33369 +Epoch: [24] [ 370/1319] eta: 0:41:48 lr: 2.1572060472626296e-05 loss: 0.0406 (0.0464) time: 2.6314 data: 0.0062 max mem: 33369 +Epoch: [24] [ 380/1319] eta: 0:41:22 lr: 2.156269601850986e-05 loss: 0.0389 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2.1487764097063317e-05 loss: 0.0433 (0.0458) time: 2.6566 data: 0.0061 max mem: 33369 +Epoch: [24] [ 470/1319] eta: 0:37:22 lr: 2.1478395567205385e-05 loss: 0.0408 (0.0457) time: 2.6438 data: 0.0062 max mem: 33369 +Epoch: [24] [ 480/1319] eta: 0:36:56 lr: 2.14690265832808e-05 loss: 0.0444 (0.0460) time: 2.6473 data: 0.0063 max mem: 33369 +Epoch: [24] [ 490/1319] eta: 0:36:29 lr: 2.1459657145047365e-05 loss: 0.0502 (0.0461) time: 2.6329 data: 0.0061 max mem: 33369 +Epoch: [24] [ 500/1319] eta: 0:36:03 lr: 2.1450287252262635e-05 loss: 0.0407 (0.0459) time: 2.6222 data: 0.0059 max mem: 33369 +Epoch: [24] [ 510/1319] eta: 0:35:36 lr: 2.144091690468391e-05 loss: 0.0364 (0.0459) time: 2.6149 data: 0.0060 max mem: 33369 +Epoch: [24] [ 520/1319] eta: 0:35:08 lr: 2.1431546102068255e-05 loss: 0.0412 (0.0458) time: 2.5903 data: 0.0061 max mem: 33369 +Epoch: [24] [ 530/1319] eta: 0:34:41 lr: 2.142217484417249e-05 loss: 0.0428 (0.0458) time: 2.5969 data: 0.0061 max mem: 33369 +Epoch: [24] [ 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data: 0.0059 max mem: 33369 +Epoch: [24] [ 700/1319] eta: 0:27:11 lr: 2.126279356522932e-05 loss: 0.0399 (0.0458) time: 2.6126 data: 0.0060 max mem: 33369 +Epoch: [24] [ 710/1319] eta: 0:26:44 lr: 2.1253414070421574e-05 loss: 0.0445 (0.0458) time: 2.6372 data: 0.0059 max mem: 33369 +Epoch: [24] [ 720/1319] eta: 0:26:18 lr: 2.1244034115665552e-05 loss: 0.0442 (0.0459) time: 2.6291 data: 0.0059 max mem: 33369 +Epoch: [24] [ 730/1319] eta: 0:25:51 lr: 2.1234653700713027e-05 loss: 0.0434 (0.0459) time: 2.6025 data: 0.0060 max mem: 33369 +Epoch: [24] [ 740/1319] eta: 0:25:25 lr: 2.122527282531552e-05 loss: 0.0400 (0.0458) time: 2.6103 data: 0.0060 max mem: 33369 +Epoch: [24] [ 750/1319] eta: 0:24:58 lr: 2.12158914892243e-05 loss: 0.0343 (0.0457) time: 2.6018 data: 0.0060 max mem: 33369 +Epoch: [24] [ 760/1319] eta: 0:24:32 lr: 2.120650969219037e-05 loss: 0.0317 (0.0456) time: 2.6138 data: 0.0059 max mem: 33369 +Epoch: [24] [ 770/1319] eta: 0:24:05 lr: 2.1197127433964487e-05 loss: 0.0333 (0.0455) time: 2.6228 data: 0.0060 max mem: 33369 +Epoch: [24] [ 780/1319] eta: 0:23:39 lr: 2.1187744714297132e-05 loss: 0.0370 (0.0454) time: 2.5961 data: 0.0061 max mem: 33369 +Epoch: [24] [ 790/1319] eta: 0:23:12 lr: 2.117836153293854e-05 loss: 0.0370 (0.0455) time: 2.6030 data: 0.0060 max mem: 33369 +Epoch: [24] [ 800/1319] eta: 0:22:46 lr: 2.1168977889638698e-05 loss: 0.0394 (0.0456) time: 2.6209 data: 0.0062 max mem: 33369 +Epoch: [24] [ 810/1319] eta: 0:22:20 lr: 2.1159593784147318e-05 loss: 0.0394 (0.0455) time: 2.6587 data: 0.0061 max mem: 33369 +Epoch: [24] [ 820/1319] eta: 0:21:53 lr: 2.115020921621386e-05 loss: 0.0398 (0.0456) time: 2.6461 data: 0.0059 max mem: 33369 +Epoch: [24] [ 830/1319] eta: 0:21:27 lr: 2.1140824185587522e-05 loss: 0.0426 (0.0455) time: 2.6189 data: 0.0059 max mem: 33369 +Epoch: [24] [ 840/1319] eta: 0:21:01 lr: 2.113143869201724e-05 loss: 0.0393 (0.0455) time: 2.6409 data: 0.0059 max mem: 33369 +Epoch: [24] [ 850/1319] eta: 0:20:34 lr: 2.11220527352517e-05 loss: 0.0393 (0.0454) time: 2.6225 data: 0.0061 max mem: 33369 +Epoch: [24] [ 860/1319] eta: 0:20:08 lr: 2.111266631503932e-05 loss: 0.0383 (0.0454) time: 2.6122 data: 0.0060 max mem: 33369 +Epoch: [24] [ 870/1319] eta: 0:19:41 lr: 2.1103279431128255e-05 loss: 0.0443 (0.0454) time: 2.5997 data: 0.0060 max mem: 33369 +Epoch: [24] [ 880/1319] eta: 0:19:15 lr: 2.1093892083266405e-05 loss: 0.0429 (0.0454) time: 2.5979 data: 0.0063 max mem: 33369 +Epoch: [24] [ 890/1319] eta: 0:18:49 lr: 2.10845042712014e-05 loss: 0.0429 (0.0456) time: 2.6414 data: 0.0061 max mem: 33369 +Epoch: [24] [ 900/1319] eta: 0:18:22 lr: 2.1075115994680607e-05 loss: 0.0525 (0.0457) time: 2.6294 data: 0.0059 max mem: 33369 +Epoch: [24] [ 910/1319] eta: 0:17:56 lr: 2.106572725345115e-05 loss: 0.0392 (0.0456) time: 2.6093 data: 0.0059 max mem: 33369 +Epoch: [24] [ 920/1319] eta: 0:17:29 lr: 2.105633804725987e-05 loss: 0.0390 (0.0456) time: 2.6152 data: 0.0059 max mem: 33369 +Epoch: [24] [ 930/1319] eta: 0:17:03 lr: 2.104694837585335e-05 loss: 0.0388 (0.0456) time: 2.6129 data: 0.0058 max mem: 33369 +Epoch: [24] [ 940/1319] eta: 0:16:37 lr: 2.1037558238977907e-05 loss: 0.0383 (0.0456) time: 2.6260 data: 0.0059 max mem: 33369 +Epoch: [24] [ 950/1319] eta: 0:16:10 lr: 2.1028167636379597e-05 loss: 0.0339 (0.0455) time: 2.6425 data: 0.0060 max mem: 33369 +Epoch: [24] [ 960/1319] eta: 0:15:44 lr: 2.1018776567804213e-05 loss: 0.0337 (0.0454) time: 2.6226 data: 0.0058 max mem: 33369 +Epoch: [24] [ 970/1319] eta: 0:15:18 lr: 2.1009385032997278e-05 loss: 0.0364 (0.0453) time: 2.6064 data: 0.0061 max mem: 33369 +Epoch: [24] [ 980/1319] eta: 0:14:51 lr: 2.0999993031704057e-05 loss: 0.0364 (0.0453) time: 2.6049 data: 0.0061 max mem: 33369 +Epoch: [24] [ 990/1319] eta: 0:14:25 lr: 2.0990600563669546e-05 loss: 0.0411 (0.0453) time: 2.6096 data: 0.0059 max mem: 33369 +Epoch: [24] [1000/1319] eta: 0:13:59 lr: 2.0981207628638462e-05 loss: 0.0487 (0.0453) time: 2.6214 data: 0.0058 max mem: 33369 +Epoch: [24] [1010/1319] eta: 0:13:32 lr: 2.0971814226355274e-05 loss: 0.0416 (0.0453) time: 2.6315 data: 0.0058 max mem: 33369 +Epoch: [24] [1020/1319] eta: 0:13:06 lr: 2.0962420356564173e-05 loss: 0.0397 (0.0453) time: 2.6267 data: 0.0059 max mem: 33369 +Epoch: [24] [1030/1319] eta: 0:12:40 lr: 2.0953026019009095e-05 loss: 0.0405 (0.0453) time: 2.5947 data: 0.0059 max mem: 33369 +Epoch: [24] [1040/1319] eta: 0:12:13 lr: 2.0943631213433694e-05 loss: 0.0397 (0.0452) time: 2.5616 data: 0.0058 max mem: 33369 +Epoch: [24] [1050/1319] eta: 0:11:47 lr: 2.0934235939581352e-05 loss: 0.0388 (0.0453) time: 2.5969 data: 0.0060 max mem: 33369 +Epoch: [24] [1060/1319] eta: 0:11:20 lr: 2.0924840197195202e-05 loss: 0.0345 (0.0452) time: 2.6123 data: 0.0061 max mem: 33369 +Epoch: [24] [1070/1319] eta: 0:10:54 lr: 2.0915443986018095e-05 loss: 0.0382 (0.0453) time: 2.5968 data: 0.0059 max mem: 33369 +Epoch: [24] [1080/1319] eta: 0:10:28 lr: 2.0906047305792607e-05 loss: 0.0412 (0.0452) time: 2.6332 data: 0.0060 max mem: 33369 +Epoch: [24] [1090/1319] eta: 0:10:01 lr: 2.0896650156261064e-05 loss: 0.0416 (0.0453) time: 2.6275 data: 0.0062 max mem: 33369 +Epoch: [24] [1100/1319] eta: 0:09:35 lr: 2.0887252537165494e-05 loss: 0.0437 (0.0453) time: 2.6242 data: 0.0060 max mem: 33369 +Epoch: [24] [1110/1319] eta: 0:09:09 lr: 2.087785444824768e-05 loss: 0.0446 (0.0453) time: 2.6321 data: 0.0058 max mem: 33369 +Epoch: [24] [1120/1319] eta: 0:08:43 lr: 2.086845588924912e-05 loss: 0.0384 (0.0452) time: 2.6343 data: 0.0061 max mem: 33369 +Epoch: [24] [1130/1319] eta: 0:08:16 lr: 2.0859056859911038e-05 loss: 0.0375 (0.0452) time: 2.6201 data: 0.0062 max mem: 33369 +Epoch: [24] [1140/1319] eta: 0:07:50 lr: 2.0849657359974397e-05 loss: 0.0460 (0.0453) time: 2.6168 data: 0.0059 max mem: 33369 +Epoch: [24] [1150/1319] eta: 0:07:24 lr: 2.084025738917989e-05 loss: 0.0414 (0.0452) time: 2.6390 data: 0.0060 max mem: 33369 +Epoch: [24] [1160/1319] eta: 0:06:57 lr: 2.083085694726791e-05 loss: 0.0377 (0.0452) time: 2.6307 data: 0.0061 max mem: 33369 +Epoch: [24] [1170/1319] eta: 0:06:31 lr: 2.0821456033978605e-05 loss: 0.0455 (0.0452) time: 2.6417 data: 0.0060 max mem: 33369 +Epoch: [24] [1180/1319] eta: 0:06:05 lr: 2.0812054649051834e-05 loss: 0.0455 (0.0453) time: 2.6412 data: 0.0059 max mem: 33369 +Epoch: [24] [1190/1319] eta: 0:05:39 lr: 2.0802652792227197e-05 loss: 0.0444 (0.0454) time: 2.6177 data: 0.0059 max mem: 33369 +Epoch: [24] [1200/1319] eta: 0:05:12 lr: 2.0793250463244006e-05 loss: 0.0437 (0.0454) time: 2.6129 data: 0.0061 max mem: 33369 +Epoch: [24] [1210/1319] eta: 0:04:46 lr: 2.07838476618413e-05 loss: 0.0432 (0.0455) time: 2.6291 data: 0.0062 max mem: 33369 +Epoch: [24] [1220/1319] eta: 0:04:20 lr: 2.077444438775784e-05 loss: 0.0423 (0.0455) time: 2.6486 data: 0.0060 max mem: 33369 +Epoch: [24] [1230/1319] eta: 0:03:53 lr: 2.0765040640732118e-05 loss: 0.0457 (0.0456) time: 2.6367 data: 0.0060 max mem: 33369 +Epoch: [24] [1240/1319] eta: 0:03:27 lr: 2.0755636420502354e-05 loss: 0.0429 (0.0456) time: 2.6165 data: 0.0061 max mem: 33369 +Epoch: [24] [1250/1319] eta: 0:03:01 lr: 2.074623172680648e-05 loss: 0.0409 (0.0456) time: 2.6074 data: 0.0060 max mem: 33369 +Epoch: [24] [1260/1319] eta: 0:02:35 lr: 2.0736826559382146e-05 loss: 0.0485 (0.0457) time: 2.6282 data: 0.0060 max mem: 33369 +Epoch: [24] [1270/1319] eta: 0:02:08 lr: 2.072742091796674e-05 loss: 0.0519 (0.0457) time: 2.6408 data: 0.0061 max mem: 33369 +Epoch: [24] [1280/1319] eta: 0:01:42 lr: 2.071801480229737e-05 loss: 0.0429 (0.0457) time: 2.6354 data: 0.0062 max mem: 33369 +Epoch: [24] [1290/1319] eta: 0:01:16 lr: 2.0708608212110852e-05 loss: 0.0437 (0.0458) time: 2.6336 data: 0.0062 max mem: 33369 +Epoch: [24] [1300/1319] eta: 0:00:49 lr: 2.0699201147143737e-05 loss: 0.0453 (0.0458) time: 2.6141 data: 0.0061 max mem: 33369 +Epoch: [24] [1310/1319] eta: 0:00:23 lr: 2.0689793607132295e-05 loss: 0.0450 (0.0458) time: 2.5851 data: 0.0060 max mem: 33369 +Epoch: [24] Total time: 0:57:46 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 2:33:55 time: 3.5893 data: 3.5110 max mem: 33369 +Test: [ 100/2573] eta: 0:04:23 time: 0.0714 data: 0.0011 max mem: 33369 +Test: [ 200/2573] eta: 0:03:34 time: 0.0732 data: 0.0011 max mem: 33369 +Test: [ 300/2573] eta: 0:03:11 time: 0.0749 data: 0.0011 max mem: 33369 +Test: [ 400/2573] eta: 0:02:56 time: 0.0752 data: 0.0011 max mem: 33369 +Test: [ 500/2573] eta: 0:02:45 time: 0.0735 data: 0.0011 max mem: 33369 +Test: [ 600/2573] eta: 0:02:35 time: 0.0737 data: 0.0011 max mem: 33369 +Test: [ 700/2573] eta: 0:02:27 time: 0.0737 data: 0.0011 max mem: 33369 +Test: [ 800/2573] eta: 0:02:18 time: 0.0769 data: 0.0011 max mem: 33369 +Test: [ 900/2573] eta: 0:02:09 time: 0.0737 data: 0.0011 max mem: 33369 +Test: [1000/2573] eta: 0:02:01 time: 0.0739 data: 0.0011 max mem: 33369 +Test: [1100/2573] eta: 0:01:53 time: 0.0738 data: 0.0011 max mem: 33369 +Test: [1200/2573] eta: 0:01:45 time: 0.0737 data: 0.0011 max mem: 33369 +Test: [1300/2573] eta: 0:01:37 time: 0.0738 data: 0.0011 max mem: 33369 +Test: [1400/2573] eta: 0:01:29 time: 0.0721 data: 0.0011 max mem: 33369 +Test: [1500/2573] eta: 0:01:21 time: 0.0738 data: 0.0011 max mem: 33369 +Test: [1600/2573] eta: 0:01:13 time: 0.0772 data: 0.0011 max mem: 33369 +Test: [1700/2573] eta: 0:01:06 time: 0.0720 data: 0.0011 max mem: 33369 +Test: [1800/2573] eta: 0:00:58 time: 0.0754 data: 0.0011 max mem: 33369 +Test: [1900/2573] eta: 0:00:50 time: 0.0721 data: 0.0011 max mem: 33369 +Test: [2000/2573] eta: 0:00:43 time: 0.0738 data: 0.0011 max mem: 33369 +Test: [2100/2573] eta: 0:00:35 time: 0.0755 data: 0.0010 max mem: 33369 +Test: [2200/2573] eta: 0:00:28 time: 0.0756 data: 0.0011 max mem: 33369 +Test: [2300/2573] eta: 0:00:20 time: 0.0755 data: 0.0011 max mem: 33369 +Test: [2400/2573] eta: 0:00:13 time: 0.0707 data: 0.0011 max mem: 33369 +Test: [2500/2573] eta: 0:00:05 time: 0.0739 data: 0.0011 max mem: 33369 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: Total time: 0:03:13 +Final results: +Mean IoU is 64.15 + + precision@0.5 = 72.45 + precision@0.6 = 66.63 + precision@0.7 = 59.68 + precision@0.8 = 47.98 + precision@0.9 = 24.37 + overall IoU = 61.49 + +Average object IoU 64.15216861443591 +Overall IoU 61.49028778076172 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [25] [ 0/1319] eta: 3:13:26 lr: 2.0681326414740886e-05 loss: 0.0383 (0.0383) time: 8.7997 data: 1.4110 max mem: 33369 +Epoch: [25] [ 10/1319] eta: 1:10:01 lr: 2.0671917971417626e-05 loss: 0.0365 (0.0368) time: 3.2098 data: 0.1338 max mem: 33369 +Epoch: [25] [ 20/1319] eta: 1:03:06 lr: 2.0662509052283616e-05 loss: 0.0365 (0.0381) time: 2.6206 data: 0.0062 max mem: 33369 +Epoch: [25] [ 30/1319] eta: 1:00:52 lr: 2.0653099657074033e-05 loss: 0.0316 (0.0370) time: 2.6271 data: 0.0064 max mem: 33369 +Epoch: [25] [ 40/1319] eta: 0:59:12 lr: 2.064368978552377e-05 loss: 0.0305 (0.0365) time: 2.6333 data: 0.0064 max mem: 33369 +Epoch: [25] [ 50/1319] eta: 0:58:12 lr: 2.0634279437367437e-05 loss: 0.0362 (0.0368) time: 2.6256 data: 0.0063 max mem: 33369 +Epoch: [25] [ 60/1319] eta: 0:57:10 lr: 2.0624868612339364e-05 loss: 0.0361 (0.0370) time: 2.6170 data: 0.0061 max mem: 33369 +Epoch: [25] [ 70/1319] eta: 0:56:21 lr: 2.0615457310173584e-05 loss: 0.0333 (0.0374) time: 2.5922 data: 0.0063 max mem: 33369 +Epoch: [25] [ 80/1319] eta: 0:55:35 lr: 2.0606045530603866e-05 loss: 0.0435 (0.0386) time: 2.5906 data: 0.0065 max mem: 33369 +Epoch: [25] [ 90/1319] eta: 0:54:55 lr: 2.059663327336368e-05 loss: 0.0407 (0.0386) time: 2.5887 data: 0.0063 max mem: 33369 +Epoch: [25] [ 100/1319] eta: 0:54:22 lr: 2.058722053818622e-05 loss: 0.0361 (0.0382) time: 2.6125 data: 0.0062 max mem: 33369 +Epoch: [25] [ 110/1319] eta: 0:53:47 lr: 2.0577807324804403e-05 loss: 0.0333 (0.0384) time: 2.6162 data: 0.0062 max mem: 33369 +Epoch: [25] [ 120/1319] eta: 0:53:15 lr: 2.0568393632950847e-05 loss: 0.0369 (0.0392) time: 2.6089 data: 0.0062 max mem: 33369 +Epoch: [25] [ 130/1319] eta: 0:52:42 lr: 2.055897946235788e-05 loss: 0.0430 (0.0398) time: 2.6062 data: 0.0062 max mem: 33369 +Epoch: [25] [ 140/1319] eta: 0:52:12 lr: 2.054956481275756e-05 loss: 0.0430 (0.0404) time: 2.6112 data: 0.0062 max mem: 33369 +Epoch: [25] [ 150/1319] eta: 0:51:42 lr: 2.0540149683881653e-05 loss: 0.0393 (0.0409) time: 2.6182 data: 0.0062 max mem: 33369 +Epoch: [25] [ 160/1319] eta: 0:51:17 lr: 2.0530734075461633e-05 loss: 0.0365 (0.0408) time: 2.6442 data: 0.0064 max mem: 33369 +Epoch: [25] [ 170/1319] eta: 0:50:49 lr: 2.05213179872287e-05 loss: 0.0386 (0.0410) time: 2.6525 data: 0.0063 max mem: 33369 +Epoch: [25] [ 180/1319] eta: 0:50:22 lr: 2.051190141891374e-05 loss: 0.0386 (0.0409) time: 2.6392 data: 0.0062 max mem: 33369 +Epoch: [25] [ 190/1319] eta: 0:49:55 lr: 2.050248437024738e-05 loss: 0.0349 (0.0408) time: 2.6464 data: 0.0061 max mem: 33369 +Epoch: [25] [ 200/1319] eta: 0:49:25 lr: 2.049306684095994e-05 loss: 0.0369 (0.0406) time: 2.6130 data: 0.0061 max mem: 33369 +Epoch: [25] [ 210/1319] eta: 0:48:56 lr: 2.048364883078146e-05 loss: 0.0433 (0.0412) time: 2.5923 data: 0.0062 max mem: 33369 +Epoch: [25] [ 220/1319] eta: 0:48:27 lr: 2.0474230339441687e-05 loss: 0.0438 (0.0414) time: 2.5987 data: 0.0061 max mem: 33369 +Epoch: [25] [ 230/1319] eta: 0:47:59 lr: 2.0464811366670074e-05 loss: 0.0424 (0.0416) time: 2.6090 data: 0.0061 max mem: 33369 +Epoch: [25] [ 240/1319] eta: 0:47:32 lr: 2.0455391912195788e-05 loss: 0.0424 (0.0416) time: 2.6285 data: 0.0061 max mem: 33369 +Epoch: [25] [ 250/1319] eta: 0:47:04 lr: 2.0445971975747706e-05 loss: 0.0389 (0.0416) time: 2.6190 data: 0.0063 max mem: 33369 +Epoch: [25] [ 260/1319] eta: 0:46:35 lr: 2.0436551557054405e-05 loss: 0.0374 (0.0415) time: 2.5968 data: 0.0064 max mem: 33369 +Epoch: [25] [ 270/1319] eta: 0:46:08 lr: 2.0427130655844186e-05 loss: 0.0378 (0.0416) time: 2.5983 data: 0.0063 max mem: 33369 +Epoch: [25] [ 280/1319] eta: 0:45:42 lr: 2.041770927184505e-05 loss: 0.0354 (0.0414) time: 2.6266 data: 0.0062 max mem: 33369 +Epoch: [25] [ 290/1319] eta: 0:45:13 lr: 2.0408287404784693e-05 loss: 0.0337 (0.0412) time: 2.6142 data: 0.0062 max mem: 33369 +Epoch: [25] [ 300/1319] eta: 0:44:46 lr: 2.0398865054390533e-05 loss: 0.0379 (0.0413) time: 2.5925 data: 0.0061 max mem: 33369 +Epoch: [25] [ 310/1319] eta: 0:44:20 lr: 2.038944222038969e-05 loss: 0.0380 (0.0412) time: 2.6297 data: 0.0060 max mem: 33369 +Epoch: [25] [ 320/1319] eta: 0:43:52 lr: 2.0380018902508984e-05 loss: 0.0305 (0.0409) time: 2.6260 data: 0.0061 max mem: 33369 +Epoch: [25] [ 330/1319] eta: 0:43:26 lr: 2.0370595100474957e-05 loss: 0.0319 (0.0408) time: 2.6162 data: 0.0059 max mem: 33369 +Epoch: [25] [ 340/1319] eta: 0:43:00 lr: 2.036117081401383e-05 loss: 0.0404 (0.0410) time: 2.6344 data: 0.0060 max mem: 33369 +Epoch: [25] [ 350/1319] eta: 0:42:32 lr: 2.035174604285155e-05 loss: 0.0404 (0.0412) time: 2.6140 data: 0.0062 max mem: 33369 +Epoch: [25] [ 360/1319] eta: 0:42:07 lr: 2.0342320786713757e-05 loss: 0.0384 (0.0412) time: 2.6393 data: 0.0062 max mem: 33369 +Epoch: [25] [ 370/1319] eta: 0:41:40 lr: 2.03328950453258e-05 loss: 0.0349 (0.0411) time: 2.6444 data: 0.0061 max mem: 33369 +Epoch: [25] [ 380/1319] eta: 0:41:13 lr: 2.0323468818412736e-05 loss: 0.0371 (0.0412) time: 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(0.0432) time: 2.6282 data: 0.0062 max mem: 33369 +Epoch: [25] [ 860/1319] eta: 0:20:05 lr: 1.987043348451999e-05 loss: 0.0406 (0.0432) time: 2.6157 data: 0.0061 max mem: 33369 +Epoch: [25] [ 870/1319] eta: 0:19:38 lr: 1.9860983123743625e-05 loss: 0.0318 (0.0430) time: 2.5937 data: 0.0061 max mem: 33369 +Epoch: [25] [ 880/1319] eta: 0:19:12 lr: 1.9851532263305046e-05 loss: 0.0323 (0.0432) time: 2.5962 data: 0.0062 max mem: 33369 +Epoch: [25] [ 890/1319] eta: 0:18:46 lr: 1.98420809029135e-05 loss: 0.0459 (0.0432) time: 2.6085 data: 0.0062 max mem: 33369 +Epoch: [25] [ 900/1319] eta: 0:18:19 lr: 1.9832629042277908e-05 loss: 0.0372 (0.0431) time: 2.6025 data: 0.0061 max mem: 33369 +Epoch: [25] [ 910/1319] eta: 0:17:53 lr: 1.982317668110687e-05 loss: 0.0361 (0.0431) time: 2.6127 data: 0.0060 max mem: 33369 +Epoch: [25] [ 920/1319] eta: 0:17:27 lr: 1.981372381910867e-05 loss: 0.0433 (0.0431) time: 2.6061 data: 0.0060 max mem: 33369 +Epoch: [25] [ 930/1319] eta: 0:17:00 lr: 1.980427045599124e-05 loss: 0.0418 (0.0431) time: 2.6074 data: 0.0061 max mem: 33369 +Epoch: [25] [ 940/1319] eta: 0:16:34 lr: 1.9794816591462205e-05 loss: 0.0384 (0.0431) time: 2.6227 data: 0.0060 max mem: 33369 +Epoch: [25] [ 950/1319] eta: 0:16:08 lr: 1.9785362225228878e-05 loss: 0.0377 (0.0430) time: 2.6270 data: 0.0059 max mem: 33369 +Epoch: [25] [ 960/1319] eta: 0:15:42 lr: 1.9775907356998215e-05 loss: 0.0363 (0.0430) time: 2.6444 data: 0.0059 max mem: 33369 +Epoch: [25] [ 970/1319] eta: 0:15:16 lr: 1.976645198647688e-05 loss: 0.0387 (0.0430) time: 2.6594 data: 0.0060 max mem: 33369 +Epoch: [25] [ 980/1319] eta: 0:14:49 lr: 1.9756996113371165e-05 loss: 0.0387 (0.0431) time: 2.6331 data: 0.0061 max mem: 33369 +Epoch: [25] [ 990/1319] eta: 0:14:23 lr: 1.9747539737387077e-05 loss: 0.0415 (0.0432) time: 2.6066 data: 0.0061 max mem: 33369 +Epoch: [25] [1000/1319] eta: 0:13:57 lr: 1.973808285823027e-05 loss: 0.0393 (0.0432) time: 2.6277 data: 0.0060 max mem: 33369 +Epoch: [25] 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33369 +Epoch: [25] [1090/1319] eta: 0:10:00 lr: 1.9652948254317503e-05 loss: 0.0431 (0.0432) time: 2.6096 data: 0.0061 max mem: 33369 +Epoch: [25] [1100/1319] eta: 0:09:34 lr: 1.9643486327172213e-05 loss: 0.0435 (0.0432) time: 2.6274 data: 0.0061 max mem: 33369 +Epoch: [25] [1110/1319] eta: 0:09:08 lr: 1.9634023893594635e-05 loss: 0.0398 (0.0432) time: 2.6315 data: 0.0059 max mem: 33369 +Epoch: [25] [1120/1319] eta: 0:08:42 lr: 1.9624560953286446e-05 loss: 0.0387 (0.0432) time: 2.6097 data: 0.0058 max mem: 33369 +Epoch: [25] [1130/1319] eta: 0:08:15 lr: 1.961509750594899e-05 loss: 0.0390 (0.0432) time: 2.6021 data: 0.0060 max mem: 33369 +Epoch: [25] [1140/1319] eta: 0:07:49 lr: 1.9605633551283273e-05 loss: 0.0493 (0.0432) time: 2.6127 data: 0.0060 max mem: 33369 +Epoch: [25] [1150/1319] eta: 0:07:23 lr: 1.9596169088989948e-05 loss: 0.0443 (0.0433) time: 2.6180 data: 0.0061 max mem: 33369 +Epoch: [25] [1160/1319] eta: 0:06:57 lr: 1.9586704118769358e-05 loss: 0.0425 (0.0433) time: 2.6277 data: 0.0060 max mem: 33369 +Epoch: [25] [1170/1319] eta: 0:06:30 lr: 1.9577238640321492e-05 loss: 0.0401 (0.0433) time: 2.6105 data: 0.0059 max mem: 33369 +Epoch: [25] [1180/1319] eta: 0:06:04 lr: 1.9567772653346e-05 loss: 0.0378 (0.0432) time: 2.5979 data: 0.0060 max mem: 33369 +Epoch: [25] [1190/1319] eta: 0:05:38 lr: 1.9558306157542204e-05 loss: 0.0371 (0.0432) time: 2.6053 data: 0.0060 max mem: 33369 +Epoch: [25] [1200/1319] eta: 0:05:12 lr: 1.9548839152609067e-05 loss: 0.0434 (0.0433) time: 2.6059 data: 0.0061 max mem: 33369 +Epoch: [25] [1210/1319] eta: 0:04:45 lr: 1.9539371638245233e-05 loss: 0.0353 (0.0432) time: 2.6120 data: 0.0061 max mem: 33369 +Epoch: [25] [1220/1319] eta: 0:04:19 lr: 1.952990361414899e-05 loss: 0.0347 (0.0432) time: 2.6301 data: 0.0060 max mem: 33369 +Epoch: [25] [1230/1319] eta: 0:03:53 lr: 1.9520435080018294e-05 loss: 0.0404 (0.0432) time: 2.6406 data: 0.0060 max mem: 33369 +Epoch: [25] [1240/1319] eta: 0:03:27 lr: 1.9510966035550763e-05 loss: 0.0391 (0.0432) time: 2.6323 data: 0.0059 max mem: 33369 +Epoch: [25] [1250/1319] eta: 0:03:00 lr: 1.9501496480443652e-05 loss: 0.0407 (0.0432) time: 2.6175 data: 0.0059 max mem: 33369 +Epoch: [25] [1260/1319] eta: 0:02:34 lr: 1.9492026414393892e-05 loss: 0.0398 (0.0432) time: 2.6062 data: 0.0058 max mem: 33369 +Epoch: [25] [1270/1319] eta: 0:02:08 lr: 1.9482555837098063e-05 loss: 0.0477 (0.0432) time: 2.6272 data: 0.0057 max mem: 33369 +Epoch: [25] [1280/1319] eta: 0:01:42 lr: 1.9473084748252403e-05 loss: 0.0449 (0.0432) time: 2.6277 data: 0.0059 max mem: 33369 +Epoch: [25] [1290/1319] eta: 0:01:16 lr: 1.9463613147552807e-05 loss: 0.0398 (0.0433) time: 2.5903 data: 0.0059 max mem: 33369 +Epoch: [25] [1300/1319] eta: 0:00:49 lr: 1.9454141034694828e-05 loss: 0.0458 (0.0433) time: 2.5872 data: 0.0058 max mem: 33369 +Epoch: [25] [1310/1319] eta: 0:00:23 lr: 1.9444668409373652e-05 loss: 0.0386 (0.0433) time: 2.6080 data: 0.0060 max mem: 33369 +Epoch: [25] Total time: 0:57:39 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 2:09:15 time: 3.0144 data: 2.9367 max mem: 33369 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 100/2573] eta: 0:04:08 time: 0.0711 data: 0.0011 max mem: 33369 +Test: [ 200/2573] eta: 0:03:26 time: 0.0729 data: 0.0011 max mem: 33369 +Test: [ 300/2573] eta: 0:03:06 time: 0.0746 data: 0.0011 max mem: 33369 +Test: [ 400/2573] eta: 0:02:53 time: 0.0747 data: 0.0011 max mem: 33369 +Test: [ 500/2573] eta: 0:02:42 time: 0.0732 data: 0.0011 max mem: 33369 +Test: [ 600/2573] eta: 0:02:33 time: 0.0732 data: 0.0011 max mem: 33369 +Test: [ 700/2573] eta: 0:02:24 time: 0.0733 data: 0.0011 max mem: 33369 +Test: [ 800/2573] eta: 0:02:16 time: 0.0765 data: 0.0011 max mem: 33369 +Test: [ 900/2573] eta: 0:02:08 time: 0.0735 data: 0.0011 max mem: 33369 +Test: [1000/2573] eta: 0:02:00 time: 0.0734 data: 0.0011 max mem: 33369 +Test: [1100/2573] eta: 0:01:52 time: 0.0736 data: 0.0011 max mem: 33369 +Test: [1200/2573] eta: 0:01:44 time: 0.0736 data: 0.0012 max mem: 33369 +Test: [1300/2573] eta: 0:01:36 time: 0.0736 data: 0.0011 max mem: 33369 +Test: [1400/2573] eta: 0:01:28 time: 0.0720 data: 0.0011 max mem: 33369 +Test: [1500/2573] eta: 0:01:20 time: 0.0736 data: 0.0011 max mem: 33369 +Test: [1600/2573] eta: 0:01:13 time: 0.0770 data: 0.0011 max mem: 33369 +Test: [1700/2573] eta: 0:01:05 time: 0.0721 data: 0.0011 max mem: 33369 +Test: [1800/2573] eta: 0:00:58 time: 0.0754 data: 0.0011 max mem: 33369 +Test: [1900/2573] eta: 0:00:50 time: 0.0720 data: 0.0011 max mem: 33369 +Test: [2000/2573] eta: 0:00:42 time: 0.0738 data: 0.0011 max mem: 33369 +Test: [2100/2573] eta: 0:00:35 time: 0.0753 data: 0.0011 max mem: 33369 +Test: [2200/2573] eta: 0:00:27 time: 0.0754 data: 0.0011 max mem: 33369 +Test: [2300/2573] eta: 0:00:20 time: 0.0754 data: 0.0011 max mem: 33369 +Test: [2400/2573] eta: 0:00:12 time: 0.0705 data: 0.0011 max mem: 33369 +Test: [2500/2573] eta: 0:00:05 time: 0.0737 data: 0.0011 max mem: 33369 +Test: Total time: 0:03:12 +Final results: +Mean IoU is 64.61 + + precision@0.5 = 72.43 + precision@0.6 = 67.50 + precision@0.7 = 60.56 + precision@0.8 = 49.16 + precision@0.9 = 24.51 + overall IoU = 61.66 + +Average object IoU 64.606684868609 +Overall IoU 61.65964126586914 +Better epoch: 25 + +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [26] [ 0/1319] eta: 1:38:08 lr: 1.943614260817638e-05 loss: 0.0350 (0.0350) time: 4.4641 data: 1.6015 max mem: 33369 +Epoch: [26] [ 10/1319] eta: 1:01:54 lr: 1.9426669008334188e-05 loss: 0.0404 (0.0445) time: 2.8380 data: 0.1513 max mem: 33369 +Epoch: [26] [ 20/1319] eta: 0:59:14 lr: 1.941719489514293e-05 loss: 0.0400 (0.0422) time: 2.6496 data: 0.0060 max mem: 33369 +Epoch: [26] [ 30/1319] eta: 0:57:48 lr: 1.9407720268296455e-05 loss: 0.0393 (0.0420) time: 2.6097 data: 0.0059 max mem: 33369 +Epoch: [26] [ 40/1319] eta: 0:57:00 lr: 1.9398245127488253e-05 loss: 0.0377 (0.0406) time: 2.6097 data: 0.0061 max mem: 33369 +Epoch: [26] [ 50/1319] eta: 0:56:21 lr: 1.9388769472411493e-05 loss: 0.0335 (0.0405) time: 2.6246 data: 0.0063 max mem: 33369 +Epoch: [26] [ 60/1319] eta: 0:55:45 lr: 1.9379293302758954e-05 loss: 0.0335 (0.0397) time: 2.6233 data: 0.0064 max mem: 33369 +Epoch: [26] [ 70/1319] eta: 0:54:57 lr: 1.936981661822309e-05 loss: 0.0373 (0.0408) time: 2.5778 data: 0.0063 max mem: 33369 +Epoch: [26] [ 80/1319] eta: 0:54:34 lr: 1.9360339418495996e-05 loss: 0.0401 (0.0406) time: 2.5975 data: 0.0062 max mem: 33369 +Epoch: [26] [ 90/1319] eta: 0:54:09 lr: 1.935086170326942e-05 loss: 0.0347 (0.0404) time: 2.6570 data: 0.0062 max mem: 33369 +Epoch: [26] [ 100/1319] eta: 0:53:38 lr: 1.934138347223476e-05 loss: 0.0384 (0.0408) time: 2.6321 data: 0.0063 max mem: 33369 +Epoch: [26] [ 110/1319] eta: 0:53:09 lr: 1.9331904725083057e-05 loss: 0.0405 (0.0413) time: 2.6117 data: 0.0063 max mem: 33369 +Epoch: [26] [ 120/1319] eta: 0:52:38 lr: 1.9322425461504988e-05 loss: 0.0472 (0.0419) time: 2.6015 data: 0.0061 max mem: 33369 +Epoch: [26] [ 130/1319] eta: 0:52:09 lr: 1.931294568119089e-05 loss: 0.0417 (0.0431) time: 2.6005 data: 0.0063 max mem: 33369 +Epoch: [26] [ 140/1319] eta: 0:51:37 lr: 1.930346538383074e-05 loss: 0.0385 (0.0432) time: 2.5850 data: 0.0064 max mem: 33369 +Epoch: [26] [ 150/1319] eta: 0:51:09 lr: 1.9293984569114164e-05 loss: 0.0398 (0.0433) time: 2.5832 data: 0.0063 max mem: 33369 +Epoch: [26] [ 160/1319] eta: 0:50:45 lr: 1.9284503236730435e-05 loss: 0.0398 (0.0431) time: 2.6278 data: 0.0063 max mem: 33369 +Epoch: [26] [ 170/1319] eta: 0:50:18 lr: 1.927502138636845e-05 loss: 0.0384 (0.0432) time: 2.6363 data: 0.0062 max mem: 33369 +Epoch: [26] [ 180/1319] eta: 0:49:53 lr: 1.9265539017716765e-05 loss: 0.0357 (0.0428) time: 2.6383 data: 0.0062 max mem: 33369 +Epoch: [26] [ 190/1319] eta: 0:49:27 lr: 1.9256056130463582e-05 loss: 0.0422 (0.0432) time: 2.6410 data: 0.0060 max mem: 33369 +Epoch: [26] [ 200/1319] eta: 0:49:01 lr: 1.9246572724296735e-05 loss: 0.0391 (0.0428) time: 2.6264 data: 0.0059 max mem: 33369 +Epoch: [26] [ 210/1319] eta: 0:48:34 lr: 1.9237088798903708e-05 loss: 0.0334 (0.0425) time: 2.6194 data: 0.0060 max mem: 33369 +Epoch: [26] [ 220/1319] eta: 0:48:06 lr: 1.922760435397161e-05 loss: 0.0365 (0.0424) time: 2.6045 data: 0.0061 max mem: 33369 +Epoch: [26] [ 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33369 +Epoch: [26] [ 310/1319] eta: 0:44:07 lr: 1.9142220918520593e-05 loss: 0.0344 (0.0421) time: 2.6299 data: 0.0061 max mem: 33369 +Epoch: [26] [ 320/1319] eta: 0:43:41 lr: 1.9132731260909836e-05 loss: 0.0387 (0.0422) time: 2.6357 data: 0.0060 max mem: 33369 +Epoch: [26] [ 330/1319] eta: 0:43:13 lr: 1.9123241080294413e-05 loss: 0.0387 (0.0422) time: 2.6101 data: 0.0064 max mem: 33369 +Epoch: [26] [ 340/1319] eta: 0:42:46 lr: 1.9113750376357084e-05 loss: 0.0382 (0.0423) time: 2.5759 data: 0.0064 max mem: 33369 +Epoch: [26] [ 350/1319] eta: 0:42:20 lr: 1.9104259148780233e-05 loss: 0.0377 (0.0421) time: 2.6063 data: 0.0060 max mem: 33369 +Epoch: [26] [ 360/1319] eta: 0:41:54 lr: 1.909476739724589e-05 loss: 0.0331 (0.0420) time: 2.6310 data: 0.0060 max mem: 33369 +Epoch: [26] [ 370/1319] eta: 0:41:27 lr: 1.9085275121435705e-05 loss: 0.0382 (0.0424) time: 2.6173 data: 0.0061 max mem: 33369 +Epoch: [26] [ 380/1319] eta: 0:41:01 lr: 1.907578232103095e-05 loss: 0.0389 (0.0424) time: 2.6066 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1.892382590817894e-05 loss: 0.0325 (0.0421) time: 2.6194 data: 0.0061 max mem: 33369 +Epoch: [26] [ 550/1319] eta: 0:33:34 lr: 1.8914324140541728e-05 loss: 0.0325 (0.0421) time: 2.5969 data: 0.0058 max mem: 33369 +Epoch: [26] [ 560/1319] eta: 0:33:08 lr: 1.8904821842509134e-05 loss: 0.0428 (0.0424) time: 2.6231 data: 0.0059 max mem: 33369 +Epoch: [26] [ 570/1319] eta: 0:32:42 lr: 1.889531901375529e-05 loss: 0.0447 (0.0426) time: 2.6382 data: 0.0060 max mem: 33369 +Epoch: [26] [ 580/1319] eta: 0:32:16 lr: 1.888581565395396e-05 loss: 0.0417 (0.0425) time: 2.6100 data: 0.0058 max mem: 33369 +Epoch: [26] [ 590/1319] eta: 0:31:50 lr: 1.8876311762778523e-05 loss: 0.0316 (0.0424) time: 2.6124 data: 0.0060 max mem: 33369 +Epoch: [26] [ 600/1319] eta: 0:31:24 lr: 1.8866807339901958e-05 loss: 0.0392 (0.0425) time: 2.6266 data: 0.0060 max mem: 33369 +Epoch: [26] [ 610/1319] eta: 0:30:58 lr: 1.885730238499688e-05 loss: 0.0482 (0.0426) time: 2.6324 data: 0.0061 max mem: 33369 +Epoch: [26] [ 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data: 0.0059 max mem: 33369 +Epoch: [26] [ 780/1319] eta: 0:23:32 lr: 1.8695636432127905e-05 loss: 0.0349 (0.0427) time: 2.6468 data: 0.0059 max mem: 33369 +Epoch: [26] [ 790/1319] eta: 0:23:06 lr: 1.8686121844283114e-05 loss: 0.0349 (0.0426) time: 2.6618 data: 0.0059 max mem: 33369 +Epoch: [26] [ 800/1319] eta: 0:22:40 lr: 1.8676606718115407e-05 loss: 0.0318 (0.0426) time: 2.6481 data: 0.0059 max mem: 33369 +Epoch: [26] [ 810/1319] eta: 0:22:13 lr: 1.866709105328956e-05 loss: 0.0294 (0.0426) time: 2.6122 data: 0.0059 max mem: 33369 +Epoch: [26] [ 820/1319] eta: 0:21:47 lr: 1.8657574849469954e-05 loss: 0.0352 (0.0425) time: 2.6236 data: 0.0059 max mem: 33369 +Epoch: [26] [ 830/1319] eta: 0:21:21 lr: 1.864805810632056e-05 loss: 0.0339 (0.0425) time: 2.6300 data: 0.0059 max mem: 33369 +Epoch: [26] [ 840/1319] eta: 0:20:55 lr: 1.8638540823504965e-05 loss: 0.0339 (0.0425) time: 2.6180 data: 0.0058 max mem: 33369 +Epoch: [26] [ 850/1319] eta: 0:20:29 lr: 1.8629023000686338e-05 loss: 0.0339 (0.0424) time: 2.6155 data: 0.0060 max mem: 33369 +Epoch: [26] [ 860/1319] eta: 0:20:02 lr: 1.8619504637527467e-05 loss: 0.0357 (0.0424) time: 2.6152 data: 0.0061 max mem: 33369 +Epoch: [26] [ 870/1319] eta: 0:19:36 lr: 1.8609985733690715e-05 loss: 0.0382 (0.0424) time: 2.6399 data: 0.0060 max mem: 33369 +Epoch: [26] [ 880/1319] eta: 0:19:10 lr: 1.860046628883806e-05 loss: 0.0351 (0.0424) time: 2.6257 data: 0.0059 max mem: 33369 +Epoch: [26] [ 890/1319] eta: 0:18:44 lr: 1.859094630263106e-05 loss: 0.0363 (0.0424) time: 2.6032 data: 0.0059 max mem: 33369 +Epoch: [26] [ 900/1319] eta: 0:18:18 lr: 1.8581425774730882e-05 loss: 0.0357 (0.0423) time: 2.6313 data: 0.0061 max mem: 33369 +Epoch: [26] [ 910/1319] eta: 0:17:51 lr: 1.8571904704798292e-05 loss: 0.0329 (0.0424) time: 2.6255 data: 0.0060 max mem: 33369 +Epoch: [26] [ 920/1319] eta: 0:17:25 lr: 1.856238309249363e-05 loss: 0.0439 (0.0424) time: 2.6004 data: 0.0060 max mem: 33369 +Epoch: [26] [ 930/1319] eta: 0:16:59 lr: 1.855286093747684e-05 loss: 0.0439 (0.0424) time: 2.6029 data: 0.0060 max mem: 33369 +Epoch: [26] [ 940/1319] eta: 0:16:33 lr: 1.854333823940747e-05 loss: 0.0361 (0.0424) time: 2.6405 data: 0.0058 max mem: 33369 +Epoch: [26] [ 950/1319] eta: 0:16:06 lr: 1.853381499794464e-05 loss: 0.0339 (0.0425) time: 2.6188 data: 0.0060 max mem: 33369 +Epoch: [26] [ 960/1319] eta: 0:15:40 lr: 1.8524291212747084e-05 loss: 0.0403 (0.0426) time: 2.5910 data: 0.0061 max mem: 33369 +Epoch: [26] [ 970/1319] eta: 0:15:14 lr: 1.85147668834731e-05 loss: 0.0355 (0.0425) time: 2.6230 data: 0.0058 max mem: 33369 +Epoch: [26] [ 980/1319] eta: 0:14:48 lr: 1.8505242009780593e-05 loss: 0.0341 (0.0425) time: 2.6275 data: 0.0058 max mem: 33369 +Epoch: [26] [ 990/1319] eta: 0:14:22 lr: 1.8495716591327057e-05 loss: 0.0423 (0.0426) time: 2.6262 data: 0.0060 max mem: 33369 +Epoch: [26] [1000/1319] eta: 0:13:55 lr: 1.848619062776957e-05 loss: 0.0442 (0.0426) time: 2.6131 data: 0.0060 max mem: 33369 +Epoch: [26] [1010/1319] eta: 0:13:29 lr: 1.8476664118764797e-05 loss: 0.0342 (0.0426) time: 2.6199 data: 0.0059 max mem: 33369 +Epoch: [26] [1020/1319] eta: 0:13:03 lr: 1.8467137063969e-05 loss: 0.0341 (0.0427) time: 2.6430 data: 0.0058 max mem: 33369 +Epoch: [26] [1030/1319] eta: 0:12:37 lr: 1.8457609463038007e-05 loss: 0.0375 (0.0427) time: 2.6460 data: 0.0057 max mem: 33369 +Epoch: [26] [1040/1319] eta: 0:12:11 lr: 1.8448081315627246e-05 loss: 0.0380 (0.0427) time: 2.6598 data: 0.0058 max mem: 33369 +Epoch: [26] [1050/1319] eta: 0:11:45 lr: 1.843855262139173e-05 loss: 0.0368 (0.0426) time: 2.6402 data: 0.0058 max mem: 33369 +Epoch: [26] [1060/1319] eta: 0:11:18 lr: 1.8429023379986053e-05 loss: 0.0377 (0.0426) time: 2.6268 data: 0.0059 max mem: 33369 +Epoch: [26] [1070/1319] eta: 0:10:52 lr: 1.8419493591064395e-05 loss: 0.0414 (0.0428) time: 2.6411 data: 0.0059 max mem: 33369 +Epoch: [26] [1080/1319] eta: 0:10:26 lr: 1.840996325428051e-05 loss: 0.0397 (0.0427) time: 2.6365 data: 0.0060 max mem: 33369 +Epoch: [26] [1090/1319] eta: 0:10:00 lr: 1.840043236928774e-05 loss: 0.0393 (0.0427) time: 2.6362 data: 0.0060 max mem: 33369 +Epoch: [26] [1100/1319] eta: 0:09:34 lr: 1.839090093573901e-05 loss: 0.0403 (0.0428) time: 2.6247 data: 0.0059 max mem: 33369 +Epoch: [26] [1110/1319] eta: 0:09:07 lr: 1.838136895328682e-05 loss: 0.0415 (0.0428) time: 2.6166 data: 0.0058 max mem: 33369 +Epoch: [26] [1120/1319] eta: 0:08:41 lr: 1.8371836421583257e-05 loss: 0.0439 (0.0428) time: 2.6190 data: 0.0057 max mem: 33369 +Epoch: [26] [1130/1319] eta: 0:08:15 lr: 1.836230334027998e-05 loss: 0.0400 (0.0428) time: 2.6301 data: 0.0060 max mem: 33369 +Epoch: [26] [1140/1319] eta: 0:07:49 lr: 1.8352769709028224e-05 loss: 0.0391 (0.0428) time: 2.6384 data: 0.0060 max mem: 33369 +Epoch: [26] [1150/1319] eta: 0:07:23 lr: 1.8343235527478807e-05 loss: 0.0390 (0.0429) time: 2.6373 data: 0.0058 max mem: 33369 +Epoch: [26] [1160/1319] eta: 0:06:56 lr: 1.8333700795282125e-05 loss: 0.0377 (0.0429) time: 2.6522 data: 0.0058 max mem: 33369 +Epoch: [26] [1170/1319] eta: 0:06:30 lr: 1.832416551208814e-05 loss: 0.0390 (0.0430) time: 2.6412 data: 0.0058 max mem: 33369 +Epoch: [26] [1180/1319] eta: 0:06:04 lr: 1.8314629677546413e-05 loss: 0.0413 (0.0430) time: 2.6137 data: 0.0059 max mem: 33369 +Epoch: [26] [1190/1319] eta: 0:05:38 lr: 1.8305093291306038e-05 loss: 0.0356 (0.0429) time: 2.6218 data: 0.0059 max mem: 33369 +Epoch: [26] [1200/1319] eta: 0:05:12 lr: 1.829555635301572e-05 loss: 0.0328 (0.0429) time: 2.6407 data: 0.0059 max mem: 33369 +Epoch: [26] [1210/1319] eta: 0:04:45 lr: 1.8286018862323718e-05 loss: 0.0361 (0.0428) time: 2.6466 data: 0.0059 max mem: 33369 +Epoch: [26] [1220/1319] eta: 0:04:19 lr: 1.8276480818877866e-05 loss: 0.0389 (0.0428) time: 2.6477 data: 0.0058 max mem: 33369 +Epoch: [26] [1230/1319] eta: 0:03:53 lr: 1.8266942222325584e-05 loss: 0.0363 (0.0429) time: 2.6330 data: 0.0058 max mem: 33369 +Epoch: [26] [1240/1319] eta: 0:03:27 lr: 1.8257403072313833e-05 loss: 0.0340 (0.0429) time: 2.6304 data: 0.0058 max mem: 33369 +Epoch: [26] [1250/1319] eta: 0:03:01 lr: 1.8247863368489165e-05 loss: 0.0357 (0.0429) time: 2.6283 data: 0.0060 max mem: 33369 +Epoch: [26] [1260/1319] eta: 0:02:34 lr: 1.8238323110497695e-05 loss: 0.0381 (0.0429) time: 2.6261 data: 0.0060 max mem: 33369 +Epoch: [26] [1270/1319] eta: 0:02:08 lr: 1.822878229798511e-05 loss: 0.0372 (0.0430) time: 2.6250 data: 0.0058 max mem: 33369 +Epoch: [26] [1280/1319] eta: 0:01:42 lr: 1.821924093059666e-05 loss: 0.0344 (0.0430) time: 2.6035 data: 0.0057 max mem: 33369 +Epoch: [26] [1290/1319] eta: 0:01:16 lr: 1.8209699007977167e-05 loss: 0.0363 (0.0430) time: 2.5872 data: 0.0058 max mem: 33369 +Epoch: [26] [1300/1319] eta: 0:00:49 lr: 1.8200156529771002e-05 loss: 0.0363 (0.0430) time: 2.6056 data: 0.0059 max mem: 33369 +Epoch: [26] [1310/1319] eta: 0:00:23 lr: 1.819061349562212e-05 loss: 0.0457 (0.0430) time: 2.6230 data: 0.0058 max mem: 33369 +Epoch: [26] Total time: 0:57:39 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 1:59:21 time: 2.7832 data: 2.7053 max mem: 33369 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 100/2573] eta: 0:04:03 time: 0.0714 data: 0.0011 max mem: 33369 +Test: [ 200/2573] eta: 0:03:24 time: 0.0732 data: 0.0011 max mem: 33369 +Test: [ 300/2573] eta: 0:03:05 time: 0.0750 data: 0.0011 max mem: 33369 +Test: [ 400/2573] eta: 0:02:52 time: 0.0752 data: 0.0011 max mem: 33369 +Test: [ 500/2573] eta: 0:02:42 time: 0.0735 data: 0.0011 max mem: 33369 +Test: [ 600/2573] eta: 0:02:33 time: 0.0736 data: 0.0011 max mem: 33369 +Test: [ 700/2573] eta: 0:02:24 time: 0.0736 data: 0.0011 max mem: 33369 +Test: [ 800/2573] eta: 0:02:16 time: 0.0771 data: 0.0011 max mem: 33369 +Test: [ 900/2573] eta: 0:02:08 time: 0.0738 data: 0.0011 max mem: 33369 +Test: [1000/2573] eta: 0:02:00 time: 0.0738 data: 0.0011 max mem: 33369 +Test: [1100/2573] eta: 0:01:52 time: 0.0738 data: 0.0011 max mem: 33369 +Test: [1200/2573] eta: 0:01:44 time: 0.0739 data: 0.0011 max mem: 33369 +Test: [1300/2573] eta: 0:01:36 time: 0.0737 data: 0.0011 max mem: 33369 +Test: [1400/2573] eta: 0:01:28 time: 0.0721 data: 0.0011 max mem: 33369 +Test: [1500/2573] eta: 0:01:21 time: 0.0738 data: 0.0011 max mem: 33369 +Test: [1600/2573] eta: 0:01:13 time: 0.0771 data: 0.0011 max mem: 33369 +Test: [1700/2573] eta: 0:01:05 time: 0.0721 data: 0.0011 max mem: 33369 +Test: [1800/2573] eta: 0:00:58 time: 0.0754 data: 0.0011 max mem: 33369 +Test: [1900/2573] eta: 0:00:50 time: 0.0722 data: 0.0011 max mem: 33369 +Test: [2000/2573] eta: 0:00:43 time: 0.0737 data: 0.0011 max mem: 33369 +Test: [2100/2573] eta: 0:00:35 time: 0.0754 data: 0.0011 max mem: 33369 +Test: [2200/2573] eta: 0:00:27 time: 0.0753 data: 0.0011 max mem: 33369 +Test: [2300/2573] eta: 0:00:20 time: 0.0753 data: 0.0011 max mem: 33369 +Test: [2400/2573] eta: 0:00:12 time: 0.0704 data: 0.0011 max mem: 33369 +Test: [2500/2573] eta: 0:00:05 time: 0.0737 data: 0.0011 max mem: 33369 +Test: Total time: 0:03:12 +Final results: +Mean IoU is 64.41 + + precision@0.5 = 72.47 + precision@0.6 = 66.95 + precision@0.7 = 60.40 + precision@0.8 = 49.43 + precision@0.9 = 24.73 + overall IoU = 61.55 + +Average object IoU 64.40593619274034 +Overall IoU 61.54972457885742 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [27] [ 0/1319] eta: 3:19:14 lr: 1.818202428926248e-05 loss: 0.0291 (0.0291) time: 9.0635 data: 1.3258 max mem: 33369 +Epoch: [27] [ 10/1319] eta: 1:09:59 lr: 1.817248019783995e-05 loss: 0.0331 (0.0375) time: 3.2082 data: 0.1260 max mem: 33369 +Epoch: [27] [ 20/1319] eta: 1:03:18 lr: 1.8162935549439682e-05 loss: 0.0370 (0.0484) time: 2.6171 data: 0.0060 max mem: 33369 +Epoch: [27] [ 30/1319] eta: 1:00:35 lr: 1.8153390343703928e-05 loss: 0.0407 (0.0458) time: 2.6074 data: 0.0061 max mem: 33369 +Epoch: [27] [ 40/1319] eta: 0:59:03 lr: 1.8143844580274487e-05 loss: 0.0369 (0.0447) time: 2.6089 data: 0.0061 max mem: 33369 +Epoch: [27] [ 50/1319] eta: 0:58:02 lr: 1.813429825879272e-05 loss: 0.0339 (0.0429) time: 2.6253 data: 0.0062 max mem: 33369 +Epoch: [27] [ 60/1319] eta: 0:57:19 lr: 1.8124751378899558e-05 loss: 0.0351 (0.0444) time: 2.6543 data: 0.0062 max mem: 33369 +Epoch: [27] [ 70/1319] eta: 0:56:32 lr: 1.811520394023548e-05 loss: 0.0351 (0.0437) time: 2.6441 data: 0.0063 max mem: 33369 +Epoch: [27] [ 80/1319] eta: 0:55:49 lr: 1.8105655942440525e-05 loss: 0.0354 (0.0434) time: 2.6141 data: 0.0061 max mem: 33369 +Epoch: [27] [ 90/1319] eta: 0:55:15 lr: 1.8096107385154294e-05 loss: 0.0402 (0.0429) time: 2.6317 data: 0.0061 max mem: 33369 +Epoch: [27] [ 100/1319] eta: 0:54:44 lr: 1.8086558268015952e-05 loss: 0.0340 (0.0422) time: 2.6574 data: 0.0063 max mem: 33369 +Epoch: [27] [ 110/1319] eta: 0:54:15 lr: 1.807700859066419e-05 loss: 0.0357 (0.0422) time: 2.6698 data: 0.0063 max mem: 33369 +Epoch: [27] [ 120/1319] eta: 0:53:40 lr: 1.8067458352737284e-05 loss: 0.0357 (0.0416) time: 2.6445 data: 0.0061 max mem: 33369 +Epoch: [27] [ 130/1319] eta: 0:53:09 lr: 1.8057907553873043e-05 loss: 0.0370 (0.0415) time: 2.6270 data: 0.0062 max mem: 33369 +Epoch: [27] [ 140/1319] eta: 0:52:39 lr: 1.8048356193708847e-05 loss: 0.0370 (0.0412) time: 2.6442 data: 0.0063 max mem: 33369 +Epoch: [27] [ 150/1319] eta: 0:52:04 lr: 1.803880427188162e-05 loss: 0.0329 (0.0408) time: 2.6128 data: 0.0062 max mem: 33369 +Epoch: [27] [ 160/1319] eta: 0:51:37 lr: 1.802925178802783e-05 loss: 0.0341 (0.0410) time: 2.6214 data: 0.0063 max mem: 33369 +Epoch: [27] [ 170/1319] eta: 0:51:08 lr: 1.8019698741783504e-05 loss: 0.0347 (0.0405) time: 2.6485 data: 0.0063 max mem: 33369 +Epoch: [27] [ 180/1319] eta: 0:50:38 lr: 1.8010145132784217e-05 loss: 0.0305 (0.0403) time: 2.6267 data: 0.0061 max mem: 33369 +Epoch: [27] [ 190/1319] eta: 0:50:11 lr: 1.8000590960665095e-05 loss: 0.0326 (0.0400) time: 2.6424 data: 0.0060 max mem: 33369 +Epoch: [27] [ 200/1319] eta: 0:49:42 lr: 1.7991036225060814e-05 loss: 0.0380 (0.0402) time: 2.6423 data: 0.0061 max mem: 33369 +Epoch: [27] [ 210/1319] eta: 0:49:14 lr: 1.7981480925605583e-05 loss: 0.0409 (0.0407) time: 2.6319 data: 0.0060 max mem: 33369 +Epoch: [27] [ 220/1319] eta: 0:48:46 lr: 1.7971925061933174e-05 loss: 0.0402 (0.0406) time: 2.6442 data: 0.0062 max mem: 33369 +Epoch: [27] [ 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mem: 33369 +Epoch: [27] [ 310/1319] eta: 0:44:38 lr: 1.7885896838454187e-05 loss: 0.0326 (0.0402) time: 2.6212 data: 0.0059 max mem: 33369 +Epoch: [27] [ 320/1319] eta: 0:44:11 lr: 1.787633531236672e-05 loss: 0.0352 (0.0401) time: 2.6390 data: 0.0061 max mem: 33369 +Epoch: [27] [ 330/1319] eta: 0:43:44 lr: 1.786677321800332e-05 loss: 0.0373 (0.0401) time: 2.6471 data: 0.0060 max mem: 33369 +Epoch: [27] [ 340/1319] eta: 0:43:18 lr: 1.7857210554992246e-05 loss: 0.0380 (0.0401) time: 2.6653 data: 0.0059 max mem: 33369 +Epoch: [27] [ 350/1319] eta: 0:42:51 lr: 1.7847647322961293e-05 loss: 0.0357 (0.0399) time: 2.6569 data: 0.0059 max mem: 33369 +Epoch: [27] [ 360/1319] eta: 0:42:24 lr: 1.783808352153779e-05 loss: 0.0311 (0.0399) time: 2.6342 data: 0.0059 max mem: 33369 +Epoch: [27] [ 370/1319] eta: 0:41:56 lr: 1.782851915034859e-05 loss: 0.0374 (0.0399) time: 2.6215 data: 0.0059 max mem: 33369 +Epoch: [27] [ 380/1319] eta: 0:41:29 lr: 1.78189542090201e-05 loss: 0.0343 (0.0399) time: 2.6045 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1.7291993287130824e-05 loss: 0.0327 (0.0410) time: 2.6155 data: 0.0060 max mem: 33369 +Epoch: [27] [ 940/1319] eta: 0:16:37 lr: 1.728239580690995e-05 loss: 0.0327 (0.0410) time: 2.6306 data: 0.0059 max mem: 33369 +Epoch: [27] [ 950/1319] eta: 0:16:11 lr: 1.727279773445306e-05 loss: 0.0358 (0.0409) time: 2.6114 data: 0.0059 max mem: 33369 +Epoch: [27] [ 960/1319] eta: 0:15:44 lr: 1.7263199069357895e-05 loss: 0.0374 (0.0410) time: 2.6005 data: 0.0060 max mem: 33369 +Epoch: [27] [ 970/1319] eta: 0:15:18 lr: 1.725359981122169e-05 loss: 0.0352 (0.0409) time: 2.6032 data: 0.0062 max mem: 33369 +Epoch: [27] [ 980/1319] eta: 0:14:52 lr: 1.7243999959641156e-05 loss: 0.0340 (0.0409) time: 2.6325 data: 0.0061 max mem: 33369 +Epoch: [27] [ 990/1319] eta: 0:14:25 lr: 1.7234399514212475e-05 loss: 0.0335 (0.0409) time: 2.6621 data: 0.0061 max mem: 33369 +Epoch: [27] [1000/1319] eta: 0:13:59 lr: 1.7224798474531302e-05 loss: 0.0419 (0.0410) time: 2.6518 data: 0.0061 max mem: 33369 +Epoch: [27] 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0.0399 (0.0410) time: 2.6544 data: 0.0058 max mem: 33369 +Epoch: [27] [1250/1319] eta: 0:03:01 lr: 1.698457815687777e-05 loss: 0.0367 (0.0410) time: 2.6646 data: 0.0058 max mem: 33369 +Epoch: [27] [1260/1319] eta: 0:02:35 lr: 1.6974961522964392e-05 loss: 0.0367 (0.0410) time: 2.6000 data: 0.0058 max mem: 33369 +Epoch: [27] [1270/1319] eta: 0:02:08 lr: 1.6965344283679166e-05 loss: 0.0338 (0.0410) time: 2.5954 data: 0.0058 max mem: 33369 +Epoch: [27] [1280/1319] eta: 0:01:42 lr: 1.6955726438602627e-05 loss: 0.0330 (0.0410) time: 2.6171 data: 0.0060 max mem: 33369 +Epoch: [27] [1290/1319] eta: 0:01:16 lr: 1.694610798731476e-05 loss: 0.0419 (0.0410) time: 2.6059 data: 0.0060 max mem: 33369 +Epoch: [27] [1300/1319] eta: 0:00:49 lr: 1.6936488929395006e-05 loss: 0.0386 (0.0410) time: 2.6281 data: 0.0058 max mem: 33369 +Epoch: [27] [1310/1319] eta: 0:00:23 lr: 1.6926869264422233e-05 loss: 0.0386 (0.0410) time: 2.6237 data: 0.0058 max mem: 33369 +Epoch: [27] Total time: 0:57:51 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 2:19:46 time: 3.2595 data: 3.1814 max mem: 33369 +Test: [ 100/2573] eta: 0:04:15 time: 0.0715 data: 0.0011 max mem: 33369 +Test: [ 200/2573] eta: 0:03:30 time: 0.0732 data: 0.0011 max mem: 33369 +Test: [ 300/2573] eta: 0:03:08 time: 0.0750 data: 0.0011 max mem: 33369 +Test: [ 400/2573] eta: 0:02:55 time: 0.0751 data: 0.0011 max mem: 33369 +Test: [ 500/2573] eta: 0:02:44 time: 0.0736 data: 0.0011 max mem: 33369 +Test: [ 600/2573] eta: 0:02:34 time: 0.0738 data: 0.0011 max mem: 33369 +Test: [ 700/2573] eta: 0:02:26 time: 0.0737 data: 0.0011 max mem: 33369 +Test: [ 800/2573] eta: 0:02:17 time: 0.0770 data: 0.0011 max mem: 33369 +Test: [ 900/2573] eta: 0:02:09 time: 0.0737 data: 0.0011 max mem: 33369 +Test: [1000/2573] eta: 0:02:01 time: 0.0739 data: 0.0012 max mem: 33369 +Test: [1100/2573] eta: 0:01:52 time: 0.0738 data: 0.0011 max mem: 33369 +Test: [1200/2573] eta: 0:01:45 time: 0.0737 data: 0.0011 max mem: 33369 +Test: [1300/2573] eta: 0:01:37 time: 0.0737 data: 0.0011 max mem: 33369 +Test: [1400/2573] eta: 0:01:29 time: 0.0720 data: 0.0011 max mem: 33369 +Test: [1500/2573] eta: 0:01:21 time: 0.0737 data: 0.0011 max mem: 33369 +Test: [1600/2573] eta: 0:01:13 time: 0.0769 data: 0.0011 max mem: 33369 +Test: [1700/2573] eta: 0:01:06 time: 0.0719 data: 0.0011 max mem: 33369 +Test: [1800/2573] eta: 0:00:58 time: 0.0754 data: 0.0011 max mem: 33369 +Test: [1900/2573] eta: 0:00:50 time: 0.0721 data: 0.0011 max mem: 33369 +Test: [2000/2573] eta: 0:00:43 time: 0.0737 data: 0.0011 max mem: 33369 +Test: [2100/2573] eta: 0:00:35 time: 0.0753 data: 0.0011 max mem: 33369 +Test: [2200/2573] eta: 0:00:28 time: 0.0753 data: 0.0011 max mem: 33369 +Test: [2300/2573] eta: 0:00:20 time: 0.0753 data: 0.0011 max mem: 33369 +Test: [2400/2573] eta: 0:00:12 time: 0.0703 data: 0.0011 max mem: 33369 +Test: [2500/2573] eta: 0:00:05 time: 0.0736 data: 0.0011 max mem: 33369 +Test: Total time: 0:03:13 +Final results: +Mean IoU is 64.65 + + precision@0.5 = 72.90 + precision@0.6 = 67.52 + precision@0.7 = 61.05 + precision@0.8 = 49.73 + precision@0.9 = 24.80 + overall IoU = 61.95 + +Average object IoU 64.65289764922302 +Overall IoU 61.95172882080078 +Better epoch: 27 + +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [28] [ 0/1319] eta: 1:37:46 lr: 1.69182110465679e-05 loss: 0.0376 (0.0376) time: 4.4474 data: 1.7289 max mem: 33369 +Epoch: [28] [ 10/1319] eta: 1:00:32 lr: 1.690859022703219e-05 loss: 0.0376 (0.0366) time: 2.7748 data: 0.1630 max mem: 33369 +Epoch: [28] [ 20/1319] eta: 0:58:16 lr: 1.6898968799219036e-05 loss: 0.0361 (0.0366) time: 2.6042 data: 0.0059 max mem: 33369 +Epoch: [28] [ 30/1319] eta: 0:57:13 lr: 1.6889346762705132e-05 loss: 0.0384 (0.0397) time: 2.6022 data: 0.0059 max mem: 33369 +Epoch: [28] [ 40/1319] eta: 0:56:34 lr: 1.6879724117066593e-05 loss: 0.0368 (0.0387) time: 2.6149 data: 0.0064 max mem: 33369 +Epoch: [28] [ 50/1319] eta: 0:56:09 lr: 1.6870100861878995e-05 loss: 0.0344 (0.0400) time: 2.6423 data: 0.0061 max mem: 33369 +Epoch: [28] [ 60/1319] eta: 0:55:40 lr: 1.6860476996717327e-05 loss: 0.0357 (0.0392) time: 2.6506 data: 0.0064 max mem: 33369 +Epoch: [28] [ 70/1319] eta: 0:55:05 lr: 1.6850852521156025e-05 loss: 0.0387 (0.0397) time: 2.6256 data: 0.0066 max mem: 33369 +Epoch: [28] [ 80/1319] eta: 0:54:33 lr: 1.684122743476896e-05 loss: 0.0394 (0.0392) time: 2.6096 data: 0.0061 max mem: 33369 +Epoch: [28] [ 90/1319] eta: 0:54:03 lr: 1.6831601737129412e-05 loss: 0.0346 (0.0401) time: 2.6106 data: 0.0061 max mem: 33369 +Epoch: [28] [ 100/1319] eta: 0:53:32 lr: 1.6821975427810122e-05 loss: 0.0345 (0.0399) time: 2.6068 data: 0.0061 max mem: 33369 +Epoch: [28] [ 110/1319] eta: 0:53:05 lr: 1.6812348506383245e-05 loss: 0.0343 (0.0394) time: 2.6167 data: 0.0061 max mem: 33369 +Epoch: [28] [ 120/1319] eta: 0:52:32 lr: 1.680272097242036e-05 loss: 0.0306 (0.0390) time: 2.5972 data: 0.0062 max mem: 33369 +Epoch: [28] [ 130/1319] eta: 0:52:05 lr: 1.6793092825492484e-05 loss: 0.0358 (0.0391) time: 2.5948 data: 0.0064 max mem: 33369 +Epoch: [28] [ 140/1319] eta: 0:51:38 lr: 1.6783464065170062e-05 loss: 0.0382 (0.0390) time: 2.6210 data: 0.0062 max mem: 33369 +Epoch: [28] [ 150/1319] eta: 0:51:10 lr: 1.6773834691022944e-05 loss: 0.0355 (0.0391) time: 2.6137 data: 0.0063 max mem: 33369 +Epoch: [28] [ 160/1319] eta: 0:50:44 lr: 1.6764204702620422e-05 loss: 0.0355 (0.0395) time: 2.6188 data: 0.0065 max mem: 33369 +Epoch: [28] [ 170/1319] eta: 0:50:18 lr: 1.6754574099531206e-05 loss: 0.0364 (0.0394) time: 2.6320 data: 0.0063 max mem: 33369 +Epoch: [28] [ 180/1319] eta: 0:49:51 lr: 1.6744942881323427e-05 loss: 0.0359 (0.0393) time: 2.6203 data: 0.0062 max mem: 33369 +Epoch: [28] [ 190/1319] eta: 0:49:25 lr: 1.6735311047564646e-05 loss: 0.0355 (0.0393) time: 2.6232 data: 0.0062 max mem: 33369 +Epoch: [28] [ 200/1319] eta: 0:48:59 lr: 1.6725678597821815e-05 loss: 0.0353 (0.0393) time: 2.6387 data: 0.0063 max mem: 33369 +Epoch: [28] [ 210/1319] eta: 0:48:32 lr: 1.6716045531661334e-05 loss: 0.0365 (0.0399) time: 2.6194 data: 0.0064 max mem: 33369 +Epoch: [28] [ 220/1319] eta: 0:48:07 lr: 1.6706411848649008e-05 loss: 0.0411 (0.0400) time: 2.6241 data: 0.0063 max mem: 33369 +Epoch: [28] [ 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mem: 33369 +Epoch: [28] [ 310/1319] eta: 0:44:13 lr: 1.6619680871272843e-05 loss: 0.0361 (0.0404) time: 2.6527 data: 0.0061 max mem: 33369 +Epoch: [28] [ 320/1319] eta: 0:43:47 lr: 1.6610040995732262e-05 loss: 0.0360 (0.0404) time: 2.6624 data: 0.0062 max mem: 33369 +Epoch: [28] [ 330/1319] eta: 0:43:20 lr: 1.6600400498524878e-05 loss: 0.0354 (0.0403) time: 2.6223 data: 0.0062 max mem: 33369 +Epoch: [28] [ 340/1319] eta: 0:42:54 lr: 1.659075937920942e-05 loss: 0.0387 (0.0404) time: 2.6287 data: 0.0062 max mem: 33369 +Epoch: [28] [ 350/1319] eta: 0:42:28 lr: 1.6581117637343994e-05 loss: 0.0379 (0.0403) time: 2.6396 data: 0.0061 max mem: 33369 +Epoch: [28] [ 360/1319] eta: 0:42:02 lr: 1.657147527248612e-05 loss: 0.0317 (0.0403) time: 2.6272 data: 0.0062 max mem: 33369 +Epoch: [28] [ 370/1319] eta: 0:41:35 lr: 1.6561832284192722e-05 loss: 0.0350 (0.0402) time: 2.6130 data: 0.0065 max mem: 33369 +Epoch: [28] [ 380/1319] eta: 0:41:09 lr: 1.6552188672020112e-05 loss: 0.0344 (0.0400) time: 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1.602081598476522e-05 loss: 0.0392 (0.0400) time: 2.6203 data: 0.0061 max mem: 33369 +Epoch: [28] [ 940/1319] eta: 0:16:35 lr: 1.6011136708096744e-05 loss: 0.0399 (0.0400) time: 2.5999 data: 0.0059 max mem: 33369 +Epoch: [28] [ 950/1319] eta: 0:16:09 lr: 1.6001456781223216e-05 loss: 0.0357 (0.0400) time: 2.5905 data: 0.0058 max mem: 33369 +Epoch: [28] [ 960/1319] eta: 0:15:42 lr: 1.599177620366387e-05 loss: 0.0333 (0.0399) time: 2.6019 data: 0.0059 max mem: 33369 +Epoch: [28] [ 970/1319] eta: 0:15:16 lr: 1.598209497493724e-05 loss: 0.0414 (0.0400) time: 2.5987 data: 0.0060 max mem: 33369 +Epoch: [28] [ 980/1319] eta: 0:14:50 lr: 1.5972413094561205e-05 loss: 0.0392 (0.0399) time: 2.5991 data: 0.0060 max mem: 33369 +Epoch: [28] [ 990/1319] eta: 0:14:23 lr: 1.5962730562052938e-05 loss: 0.0362 (0.0399) time: 2.6276 data: 0.0060 max mem: 33369 +Epoch: [28] [1000/1319] eta: 0:13:57 lr: 1.5953047376928946e-05 loss: 0.0373 (0.0404) time: 2.6431 data: 0.0059 max mem: 33369 +Epoch: [28] 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mem: 33369 +Epoch: [28] [1090/1319] eta: 0:10:01 lr: 1.5865869262987425e-05 loss: 0.0386 (0.0404) time: 2.5982 data: 0.0057 max mem: 33369 +Epoch: [28] [1100/1319] eta: 0:09:34 lr: 1.5856179524962237e-05 loss: 0.0384 (0.0404) time: 2.6328 data: 0.0058 max mem: 33369 +Epoch: [28] [1110/1319] eta: 0:09:08 lr: 1.5846489128957288e-05 loss: 0.0386 (0.0404) time: 2.6291 data: 0.0059 max mem: 33369 +Epoch: [28] [1120/1319] eta: 0:08:42 lr: 1.5836798074480774e-05 loss: 0.0398 (0.0404) time: 2.6069 data: 0.0059 max mem: 33369 +Epoch: [28] [1130/1319] eta: 0:08:16 lr: 1.582710636104018e-05 loss: 0.0396 (0.0404) time: 2.6333 data: 0.0059 max mem: 33369 +Epoch: [28] [1140/1319] eta: 0:07:49 lr: 1.5817413988142284e-05 loss: 0.0425 (0.0405) time: 2.6348 data: 0.0058 max mem: 33369 +Epoch: [28] [1150/1319] eta: 0:07:23 lr: 1.5807720955293166e-05 loss: 0.0420 (0.0405) time: 2.6129 data: 0.0058 max mem: 33369 +Epoch: [28] [1160/1319] eta: 0:06:57 lr: 1.579802726199819e-05 loss: 0.0398 (0.0405) time: 2.6228 data: 0.0059 max mem: 33369 +Epoch: [28] [1170/1319] eta: 0:06:31 lr: 1.5788332907762015e-05 loss: 0.0354 (0.0405) time: 2.6538 data: 0.0060 max mem: 33369 +Epoch: [28] [1180/1319] eta: 0:06:04 lr: 1.577863789208859e-05 loss: 0.0436 (0.0405) time: 2.6437 data: 0.0059 max mem: 33369 +Epoch: [28] [1190/1319] eta: 0:05:38 lr: 1.576894221448116e-05 loss: 0.0396 (0.0405) time: 2.6176 data: 0.0058 max mem: 33369 +Epoch: [28] [1200/1319] eta: 0:05:12 lr: 1.5759245874442245e-05 loss: 0.0336 (0.0405) time: 2.6097 data: 0.0058 max mem: 33369 +Epoch: [28] [1210/1319] eta: 0:04:46 lr: 1.5749548871473663e-05 loss: 0.0400 (0.0405) time: 2.6057 data: 0.0059 max mem: 33369 +Epoch: [28] [1220/1319] eta: 0:04:19 lr: 1.57398512050765e-05 loss: 0.0394 (0.0405) time: 2.6009 data: 0.0059 max mem: 33369 +Epoch: [28] [1230/1319] eta: 0:03:53 lr: 1.5730152874751144e-05 loss: 0.0343 (0.0405) time: 2.6316 data: 0.0059 max mem: 33369 +Epoch: [28] [1240/1319] eta: 0:03:27 lr: 1.572045387999725e-05 loss: 0.0354 (0.0405) time: 2.6351 data: 0.0061 max mem: 33369 +Epoch: [28] [1250/1319] eta: 0:03:01 lr: 1.5710754220313764e-05 loss: 0.0438 (0.0406) time: 2.6319 data: 0.0063 max mem: 33369 +Epoch: [28] [1260/1319] eta: 0:02:34 lr: 1.5701053895198906e-05 loss: 0.0392 (0.0406) time: 2.6415 data: 0.0060 max mem: 33369 +Epoch: [28] [1270/1319] eta: 0:02:08 lr: 1.5691352904150157e-05 loss: 0.0373 (0.0406) time: 2.6453 data: 0.0059 max mem: 33369 +Epoch: [28] [1280/1319] eta: 0:01:42 lr: 1.5681651246664294e-05 loss: 0.0395 (0.0406) time: 2.6330 data: 0.0058 max mem: 33369 +Epoch: [28] [1290/1319] eta: 0:01:16 lr: 1.5671948922237363e-05 loss: 0.0373 (0.0406) time: 2.6336 data: 0.0058 max mem: 33369 +Epoch: [28] [1300/1319] eta: 0:00:49 lr: 1.5662245930364672e-05 loss: 0.0367 (0.0405) time: 2.6306 data: 0.0059 max mem: 33369 +Epoch: [28] [1310/1319] eta: 0:00:23 lr: 1.5652542270540813e-05 loss: 0.0356 (0.0405) time: 2.6197 data: 0.0060 max mem: 33369 +Epoch: [28] Total time: 0:57:43 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 2:13:59 time: 3.1247 data: 3.0464 max mem: 33369 +Test: [ 100/2573] eta: 0:04:11 time: 0.0714 data: 0.0011 max mem: 33369 +Test: [ 200/2573] eta: 0:03:28 time: 0.0730 data: 0.0011 max mem: 33369 +Test: [ 300/2573] eta: 0:03:07 time: 0.0748 data: 0.0011 max mem: 33369 +Test: [ 400/2573] eta: 0:02:54 time: 0.0747 data: 0.0011 max mem: 33369 +Test: [ 500/2573] eta: 0:02:43 time: 0.0732 data: 0.0011 max mem: 33369 +Test: [ 600/2573] eta: 0:02:33 time: 0.0733 data: 0.0011 max mem: 33369 +Test: [ 700/2573] eta: 0:02:25 time: 0.0736 data: 0.0011 max mem: 33369 +Test: [ 800/2573] eta: 0:02:16 time: 0.0770 data: 0.0011 max mem: 33369 +Test: [ 900/2573] eta: 0:02:08 time: 0.0737 data: 0.0011 max mem: 33369 +Test: [1000/2573] eta: 0:02:00 time: 0.0736 data: 0.0011 max mem: 33369 +Test: [1100/2573] eta: 0:01:52 time: 0.0738 data: 0.0011 max mem: 33369 +Test: [1200/2573] eta: 0:01:44 time: 0.0738 data: 0.0011 max mem: 33369 +Test: [1300/2573] eta: 0:01:36 time: 0.0737 data: 0.0011 max mem: 33369 +Test: [1400/2573] eta: 0:01:28 time: 0.0722 data: 0.0011 max mem: 33369 +Test: [1500/2573] eta: 0:01:21 time: 0.0738 data: 0.0011 max mem: 33369 +Test: [1600/2573] eta: 0:01:13 time: 0.0772 data: 0.0011 max mem: 33369 +Test: [1700/2573] eta: 0:01:05 time: 0.0721 data: 0.0011 max mem: 33369 +Test: [1800/2573] eta: 0:00:58 time: 0.0755 data: 0.0011 max mem: 33369 +Test: [1900/2573] eta: 0:00:50 time: 0.0723 data: 0.0011 max mem: 33369 +Test: [2000/2573] eta: 0:00:43 time: 0.0737 data: 0.0011 max mem: 33369 +Test: [2100/2573] eta: 0:00:35 time: 0.0756 data: 0.0011 max mem: 33369 +Test: [2200/2573] eta: 0:00:27 time: 0.0754 data: 0.0011 max mem: 33369 +Test: [2300/2573] eta: 0:00:20 time: 0.0755 data: 0.0011 max mem: 33369 +Test: [2400/2573] eta: 0:00:12 time: 0.0705 data: 0.0011 max mem: 33369 +Test: [2500/2573] eta: 0:00:05 time: 0.0737 data: 0.0011 max mem: 33369 +Test: Total time: 0:03:13 +Final results: +Mean IoU is 64.53 + + precision@0.5 = 72.34 + precision@0.6 = 67.63 + precision@0.7 = 60.91 + precision@0.8 = 49.94 + precision@0.9 = 25.02 + overall IoU = 61.96 + +Average object IoU 64.52742778475512 +Overall IoU 61.96244430541992 +Better epoch: 28 + +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [29] [ 0/1319] eta: 1:40:17 lr: 1.5643808405182777e-05 loss: 0.0227 (0.0227) time: 4.5618 data: 1.7962 max mem: 33369 +Epoch: [29] [ 10/1319] eta: 1:00:30 lr: 1.563410347485666e-05 loss: 0.0404 (0.0419) time: 2.7736 data: 0.1686 max mem: 33369 +Epoch: [29] [ 20/1319] eta: 0:58:08 lr: 1.5624397875109532e-05 loss: 0.0404 (0.0441) time: 2.5918 data: 0.0059 max mem: 33369 +Epoch: [29] [ 30/1319] eta: 0:57:27 lr: 1.5614691605433113e-05 loss: 0.0397 (0.0424) time: 2.6202 data: 0.0060 max mem: 33369 +Epoch: [29] [ 40/1319] eta: 0:56:38 lr: 1.5604984665318397e-05 loss: 0.0363 (0.0409) time: 2.6265 data: 0.0062 max mem: 33369 +Epoch: [29] [ 50/1319] eta: 0:56:03 lr: 1.5595277054255625e-05 loss: 0.0363 (0.0416) time: 2.6135 data: 0.0062 max mem: 33369 +Epoch: [29] [ 60/1319] eta: 0:55:25 lr: 1.558556877173431e-05 loss: 0.0348 (0.0409) time: 2.6090 data: 0.0063 max mem: 33369 +Epoch: [29] [ 70/1319] eta: 0:54:56 lr: 1.557585981724323e-05 loss: 0.0337 (0.0406) time: 2.6102 data: 0.0063 max mem: 33369 +Epoch: [29] [ 80/1319] eta: 0:54:32 lr: 1.5566150190270393e-05 loss: 0.0332 (0.0391) time: 2.6414 data: 0.0062 max mem: 33369 +Epoch: [29] [ 90/1319] eta: 0:54:09 lr: 1.5556439890303075e-05 loss: 0.0296 (0.0386) time: 2.6604 data: 0.0064 max mem: 33369 +Epoch: [29] [ 100/1319] eta: 0:53:39 lr: 1.554672891682782e-05 loss: 0.0324 (0.0380) time: 2.6402 data: 0.0062 max mem: 33369 +Epoch: [29] [ 110/1319] eta: 0:53:07 lr: 1.55370172693304e-05 loss: 0.0315 (0.0374) time: 2.6043 data: 0.0063 max mem: 33369 +Epoch: [29] [ 120/1319] eta: 0:52:39 lr: 1.552730494729585e-05 loss: 0.0321 (0.0372) time: 2.6074 data: 0.0065 max mem: 33369 +Epoch: [29] [ 130/1319] eta: 0:52:10 lr: 1.551759195020846e-05 loss: 0.0330 (0.0370) time: 2.6115 data: 0.0063 max mem: 33369 +Epoch: [29] [ 140/1319] eta: 0:51:45 lr: 1.5507878277551742e-05 loss: 0.0330 (0.0368) time: 2.6233 data: 0.0062 max mem: 33369 +Epoch: [29] [ 150/1319] eta: 0:51:16 lr: 1.5498163928808475e-05 loss: 0.0309 (0.0365) time: 2.6233 data: 0.0062 max mem: 33369 +Epoch: [29] [ 160/1319] eta: 0:50:48 lr: 1.548844890346068e-05 loss: 0.0331 (0.0363) time: 2.6091 data: 0.0063 max mem: 33369 +Epoch: [29] [ 170/1319] eta: 0:50:24 lr: 1.547873320098961e-05 loss: 0.0341 (0.0363) time: 2.6371 data: 0.0063 max mem: 33369 +Epoch: [29] [ 180/1319] eta: 0:49:58 lr: 1.546901682087577e-05 loss: 0.0380 (0.0375) time: 2.6451 data: 0.0063 max mem: 33369 +Epoch: [29] [ 190/1319] eta: 0:49:30 lr: 1.5459299762598884e-05 loss: 0.0384 (0.0375) time: 2.6211 data: 0.0063 max mem: 33369 +Epoch: [29] [ 200/1319] eta: 0:49:01 lr: 1.5449582025637935e-05 loss: 0.0345 (0.0373) time: 2.5987 data: 0.0062 max mem: 33369 +Epoch: [29] [ 210/1319] eta: 0:48:34 lr: 1.543986360947113e-05 loss: 0.0299 (0.0371) time: 2.6004 data: 0.0060 max mem: 33369 +Epoch: [29] [ 220/1319] eta: 0:48:10 lr: 1.543014451357591e-05 loss: 0.0299 (0.0373) time: 2.6425 data: 0.0060 max mem: 33369 +Epoch: [29] [ 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33369 +Epoch: [29] [ 310/1319] eta: 0:44:10 lr: 1.5342641976136825e-05 loss: 0.0335 (0.0379) time: 2.6409 data: 0.0063 max mem: 33369 +Epoch: [29] [ 320/1319] eta: 0:43:44 lr: 1.5332916054047e-05 loss: 0.0353 (0.0383) time: 2.6543 data: 0.0061 max mem: 33369 +Epoch: [29] [ 330/1319] eta: 0:43:19 lr: 1.532318944642957e-05 loss: 0.0397 (0.0381) time: 2.6565 data: 0.0061 max mem: 33369 +Epoch: [29] [ 340/1319] eta: 0:42:53 lr: 1.5313462152752656e-05 loss: 0.0311 (0.0381) time: 2.6532 data: 0.0061 max mem: 33369 +Epoch: [29] [ 350/1319] eta: 0:42:26 lr: 1.5303734172483566e-05 loss: 0.0335 (0.0382) time: 2.6230 data: 0.0059 max mem: 33369 +Epoch: [29] [ 360/1319] eta: 0:42:00 lr: 1.529400550508885e-05 loss: 0.0388 (0.0383) time: 2.6237 data: 0.0059 max mem: 33369 +Epoch: [29] [ 370/1319] eta: 0:41:33 lr: 1.528427615003424e-05 loss: 0.0342 (0.0382) time: 2.6250 data: 0.0061 max mem: 33369 +Epoch: [29] [ 380/1319] eta: 0:41:07 lr: 1.5274546106784702e-05 loss: 0.0342 (0.0382) time: 2.6232 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(0.0399) time: 2.6313 data: 0.0061 max mem: 33369 +Epoch: [29] [ 860/1319] eta: 0:20:04 lr: 1.4806684023646183e-05 loss: 0.0425 (0.0399) time: 2.6657 data: 0.0059 max mem: 33369 +Epoch: [29] [ 870/1319] eta: 0:19:38 lr: 1.4796919586397895e-05 loss: 0.0437 (0.0400) time: 2.6178 data: 0.0057 max mem: 33369 +Epoch: [29] [ 880/1319] eta: 0:19:11 lr: 1.4787154433150476e-05 loss: 0.0437 (0.0400) time: 2.6011 data: 0.0059 max mem: 33369 +Epoch: [29] [ 890/1319] eta: 0:18:45 lr: 1.4777388563325976e-05 loss: 0.0346 (0.0400) time: 2.6455 data: 0.0059 max mem: 33369 +Epoch: [29] [ 900/1319] eta: 0:18:19 lr: 1.4767621976345552e-05 loss: 0.0365 (0.0400) time: 2.6527 data: 0.0059 max mem: 33369 +Epoch: [29] [ 910/1319] eta: 0:17:53 lr: 1.4757854671629475e-05 loss: 0.0343 (0.0400) time: 2.6216 data: 0.0059 max mem: 33369 +Epoch: [29] [ 920/1319] eta: 0:17:26 lr: 1.4748086648597121e-05 loss: 0.0368 (0.0400) time: 2.5830 data: 0.0060 max mem: 33369 +Epoch: [29] [ 930/1319] eta: 0:17:00 lr: 1.4738317906666963e-05 loss: 0.0425 (0.0401) time: 2.5742 data: 0.0060 max mem: 33369 +Epoch: [29] [ 940/1319] eta: 0:16:34 lr: 1.4728548445256565e-05 loss: 0.0374 (0.0401) time: 2.5919 data: 0.0060 max mem: 33369 +Epoch: [29] [ 950/1319] eta: 0:16:07 lr: 1.471877826378261e-05 loss: 0.0341 (0.0400) time: 2.6133 data: 0.0059 max mem: 33369 +Epoch: [29] [ 960/1319] eta: 0:15:41 lr: 1.4709007361660864e-05 loss: 0.0305 (0.0400) time: 2.6330 data: 0.0059 max mem: 33369 +Epoch: [29] [ 970/1319] eta: 0:15:15 lr: 1.4699235738306196e-05 loss: 0.0391 (0.0400) time: 2.5964 data: 0.0060 max mem: 33369 +Epoch: [29] [ 980/1319] eta: 0:14:49 lr: 1.4689463393132561e-05 loss: 0.0328 (0.0399) time: 2.5965 data: 0.0060 max mem: 33369 +Epoch: [29] [ 990/1319] eta: 0:14:22 lr: 1.4679690325553006e-05 loss: 0.0316 (0.0399) time: 2.6263 data: 0.0059 max mem: 33369 +Epoch: [29] [1000/1319] eta: 0:13:56 lr: 1.466991653497966e-05 loss: 0.0371 (0.0399) time: 2.6098 data: 0.0059 max mem: 33369 +Epoch: [29] 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0.0383 (0.0400) time: 2.6209 data: 0.0060 max mem: 33369 +Epoch: [29] [1250/1319] eta: 0:03:00 lr: 1.442533505923811e-05 loss: 0.0383 (0.0399) time: 2.5996 data: 0.0060 max mem: 33369 +Epoch: [29] [1260/1319] eta: 0:02:34 lr: 1.4415542261447945e-05 loss: 0.0362 (0.0399) time: 2.6347 data: 0.0059 max mem: 33369 +Epoch: [29] [1270/1319] eta: 0:02:08 lr: 1.4405748724439155e-05 loss: 0.0365 (0.0400) time: 2.6376 data: 0.0058 max mem: 33369 +Epoch: [29] [1280/1319] eta: 0:01:42 lr: 1.4395954447597464e-05 loss: 0.0347 (0.0399) time: 2.5979 data: 0.0058 max mem: 33369 +Epoch: [29] [1290/1319] eta: 0:01:16 lr: 1.4386159430307632e-05 loss: 0.0343 (0.0399) time: 2.5819 data: 0.0058 max mem: 33369 +Epoch: [29] [1300/1319] eta: 0:00:49 lr: 1.4376363671953435e-05 loss: 0.0368 (0.0398) time: 2.5835 data: 0.0059 max mem: 33369 +Epoch: [29] [1310/1319] eta: 0:00:23 lr: 1.4366567171917672e-05 loss: 0.0347 (0.0398) time: 2.6272 data: 0.0058 max mem: 33369 +Epoch: [29] Total time: 0:57:38 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 2:08:18 time: 2.9920 data: 2.9129 max mem: 33369 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 100/2573] eta: 0:04:09 time: 0.0713 data: 0.0011 max mem: 33369 +Test: [ 200/2573] eta: 0:03:27 time: 0.0730 data: 0.0011 max mem: 33369 +Test: [ 300/2573] eta: 0:03:06 time: 0.0748 data: 0.0011 max mem: 33369 +Test: [ 400/2573] eta: 0:02:53 time: 0.0746 data: 0.0011 max mem: 33369 +Test: [ 500/2573] eta: 0:02:42 time: 0.0731 data: 0.0011 max mem: 33369 +Test: [ 600/2573] eta: 0:02:33 time: 0.0732 data: 0.0011 max mem: 33369 +Test: [ 700/2573] eta: 0:02:24 time: 0.0733 data: 0.0011 max mem: 33369 +Test: [ 800/2573] eta: 0:02:16 time: 0.0765 data: 0.0010 max mem: 33369 +Test: [ 900/2573] eta: 0:02:08 time: 0.0735 data: 0.0011 max mem: 33369 +Test: [1000/2573] eta: 0:02:00 time: 0.0736 data: 0.0011 max mem: 33369 +Test: [1100/2573] eta: 0:01:52 time: 0.0736 data: 0.0011 max mem: 33369 +Test: [1200/2573] eta: 0:01:44 time: 0.0735 data: 0.0011 max mem: 33369 +Test: [1300/2573] eta: 0:01:36 time: 0.0735 data: 0.0011 max mem: 33369 +Test: [1400/2573] eta: 0:01:28 time: 0.0718 data: 0.0011 max mem: 33369 +Test: [1500/2573] eta: 0:01:21 time: 0.0737 data: 0.0011 max mem: 33369 +Test: [1600/2573] eta: 0:01:13 time: 0.0770 data: 0.0011 max mem: 33369 +Test: [1700/2573] eta: 0:01:05 time: 0.0719 data: 0.0011 max mem: 33369 +Test: [1800/2573] eta: 0:00:58 time: 0.0754 data: 0.0011 max mem: 33369 +Test: [1900/2573] eta: 0:00:50 time: 0.0721 data: 0.0011 max mem: 33369 +Test: [2000/2573] eta: 0:00:42 time: 0.0738 data: 0.0011 max mem: 33369 +Test: [2100/2573] eta: 0:00:35 time: 0.0754 data: 0.0011 max mem: 33369 +Test: [2200/2573] eta: 0:00:27 time: 0.0755 data: 0.0011 max mem: 33369 +Test: [2300/2573] eta: 0:00:20 time: 0.0755 data: 0.0011 max mem: 33369 +Test: [2400/2573] eta: 0:00:12 time: 0.0705 data: 0.0011 max mem: 33369 +Test: [2500/2573] eta: 0:00:05 time: 0.0739 data: 0.0011 max mem: 33369 +Test: Total time: 0:03:12 +Final results: +Mean IoU is 64.76 + + precision@0.5 = 72.75 + precision@0.6 = 67.52 + precision@0.7 = 61.09 + precision@0.8 = 49.92 + precision@0.9 = 25.25 + overall IoU = 62.14 + +Average object IoU 64.76044657785735 +Overall IoU 62.14019012451172 +Better epoch: 29 + +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [30] [ 0/1319] eta: 1:28:18 lr: 1.4357749687236825e-05 loss: 0.0372 (0.0372) time: 4.0168 data: 1.3719 max mem: 33369 +Epoch: [30] [ 10/1319] eta: 0:59:25 lr: 1.4347951776302166e-05 loss: 0.0404 (0.0386) time: 2.7237 data: 0.1305 max mem: 33369 +Epoch: [30] [ 20/1319] eta: 0:58:18 lr: 1.433815312189048e-05 loss: 0.0357 (0.0385) time: 2.6274 data: 0.0060 max mem: 33369 +Epoch: [30] [ 30/1319] eta: 0:57:32 lr: 1.4328353723380728e-05 loss: 0.0347 (0.0368) time: 2.6530 data: 0.0060 max mem: 33369 +Epoch: [30] [ 40/1319] eta: 0:56:59 lr: 1.431855358015087e-05 loss: 0.0321 (0.0347) time: 2.6519 data: 0.0063 max mem: 33369 +Epoch: [30] [ 50/1319] eta: 0:56:20 lr: 1.4308752691577878e-05 loss: 0.0245 (0.0342) time: 2.6414 data: 0.0062 max mem: 33369 +Epoch: [30] [ 60/1319] eta: 0:55:47 lr: 1.4298951057037729e-05 loss: 0.0300 (0.0353) time: 2.6301 data: 0.0063 max mem: 33369 +Epoch: [30] [ 70/1319] eta: 0:55:12 lr: 1.4289148675905387e-05 loss: 0.0363 (0.0355) time: 2.6227 data: 0.0064 max mem: 33369 +Epoch: [30] [ 80/1319] eta: 0:54:33 lr: 1.4279345547554832e-05 loss: 0.0363 (0.0356) time: 2.5888 data: 0.0061 max mem: 33369 +Epoch: [30] [ 90/1319] eta: 0:54:00 lr: 1.4269541671359036e-05 loss: 0.0307 (0.0357) time: 2.5824 data: 0.0062 max mem: 33369 +Epoch: [30] [ 100/1319] eta: 0:53:33 lr: 1.4259737046689963e-05 loss: 0.0365 (0.0374) time: 2.6127 data: 0.0063 max mem: 33369 +Epoch: [30] [ 110/1319] eta: 0:53:07 lr: 1.424993167291858e-05 loss: 0.0365 (0.0370) time: 2.6347 data: 0.0061 max mem: 33369 +Epoch: [30] [ 120/1319] eta: 0:52:39 lr: 1.4240125549414829e-05 loss: 0.0351 (0.0372) time: 2.6284 data: 0.0062 max mem: 33369 +Epoch: [30] [ 130/1319] eta: 0:52:13 lr: 1.4230318675547643e-05 loss: 0.0351 (0.0371) time: 2.6280 data: 0.0062 max mem: 33369 +Epoch: [30] [ 140/1319] eta: 0:51:46 lr: 1.4220511050684946e-05 loss: 0.0343 (0.0376) time: 2.6333 data: 0.0061 max mem: 33369 +Epoch: [30] [ 150/1319] eta: 0:51:20 lr: 1.4210702674193643e-05 loss: 0.0362 (0.0375) time: 2.6334 data: 0.0061 max mem: 33369 +Epoch: [30] [ 160/1319] eta: 0:50:51 lr: 1.420089354543962e-05 loss: 0.0351 (0.0372) time: 2.6229 data: 0.0061 max mem: 33369 +Epoch: [30] [ 170/1319] eta: 0:50:25 lr: 1.419108366378774e-05 loss: 0.0313 (0.0370) time: 2.6193 data: 0.0060 max mem: 33369 +Epoch: [30] [ 180/1319] eta: 0:49:56 lr: 1.4181273028601838e-05 loss: 0.0314 (0.0369) time: 2.6094 data: 0.0060 max mem: 33369 +Epoch: [30] [ 190/1319] eta: 0:49:29 lr: 1.4171461639244721e-05 loss: 0.0314 (0.0369) time: 2.6060 data: 0.0061 max mem: 33369 +Epoch: [30] [ 200/1319] eta: 0:49:08 lr: 1.4161649495078178e-05 loss: 0.0385 (0.0370) time: 2.6713 data: 0.0061 max mem: 33369 +Epoch: [30] [ 210/1319] eta: 0:48:42 lr: 1.415183659546295e-05 loss: 0.0389 (0.0372) time: 2.6812 data: 0.0061 max mem: 33369 +Epoch: [30] [ 220/1319] eta: 0:48:14 lr: 1.4142022939758767e-05 loss: 0.0348 (0.0370) time: 2.6246 data: 0.0061 max mem: 33369 +Epoch: [30] [ 230/1319] eta: 0:47:47 lr: 1.413220852732429e-05 loss: 0.0306 (0.0375) time: 2.6181 data: 0.0060 max mem: 33369 +Epoch: [30] [ 240/1319] eta: 0:47:20 lr: 1.4122393357517167e-05 loss: 0.0306 (0.0372) time: 2.6221 data: 0.0061 max mem: 33369 +Epoch: [30] [ 250/1319] eta: 0:46:54 lr: 1.4112577429693993e-05 loss: 0.0286 (0.0371) time: 2.6218 data: 0.0062 max mem: 33369 +Epoch: [30] [ 260/1319] eta: 0:46:26 lr: 1.4102760743210322e-05 loss: 0.0315 (0.0371) time: 2.6134 data: 0.0061 max mem: 33369 +Epoch: [30] [ 270/1319] eta: 0:46:00 lr: 1.4092943297420657e-05 loss: 0.0353 (0.0371) time: 2.6230 data: 0.0060 max mem: 33369 +Epoch: [30] [ 280/1319] eta: 0:45:34 lr: 1.4083125091678468e-05 loss: 0.0335 (0.0372) time: 2.6378 data: 0.0061 max mem: 33369 +Epoch: [30] [ 290/1319] eta: 0:45:07 lr: 1.4073306125336142e-05 loss: 0.0335 (0.0373) time: 2.6273 data: 0.0060 max mem: 33369 +Epoch: [30] [ 300/1319] eta: 0:44:40 lr: 1.4063486397745037e-05 loss: 0.0341 (0.0373) time: 2.6199 data: 0.0059 max mem: 33369 +Epoch: [30] [ 310/1319] eta: 0:44:14 lr: 1.4053665908255448e-05 loss: 0.0333 (0.0377) time: 2.6135 data: 0.0059 max mem: 33369 +Epoch: [30] [ 320/1319] eta: 0:43:47 lr: 1.4043844656216607e-05 loss: 0.0339 (0.0375) time: 2.6243 data: 0.0059 max mem: 33369 +Epoch: [30] [ 330/1319] eta: 0:43:20 lr: 1.4034022640976696e-05 loss: 0.0339 (0.0374) time: 2.6195 data: 0.0060 max mem: 33369 +Epoch: [30] [ 340/1319] eta: 0:42:53 lr: 1.4024199861882808e-05 loss: 0.0326 (0.0374) time: 2.6086 data: 0.0061 max mem: 33369 +Epoch: [30] [ 350/1319] eta: 0:42:28 lr: 1.4014376318280992e-05 loss: 0.0317 (0.0374) time: 2.6378 data: 0.0062 max mem: 33369 +Epoch: [30] [ 360/1319] eta: 0:42:02 lr: 1.4004552009516214e-05 loss: 0.0292 (0.0376) time: 2.6527 data: 0.0062 max mem: 33369 +Epoch: [30] [ 370/1319] eta: 0:41:35 lr: 1.3994726934932381e-05 loss: 0.0299 (0.0375) time: 2.6215 data: 0.0061 max mem: 33369 +Epoch: [30] [ 380/1319] eta: 0:41:08 lr: 1.3984901093872316e-05 loss: 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1.3136936515041629e-05 loss: 0.0337 (0.0376) time: 2.6300 data: 0.0061 max mem: 33369 +Epoch: [30] [1250/1319] eta: 0:03:01 lr: 1.3127041345777947e-05 loss: 0.0337 (0.0377) time: 2.6089 data: 0.0060 max mem: 33369 +Epoch: [30] [1260/1319] eta: 0:02:34 lr: 1.3117145347668891e-05 loss: 0.0352 (0.0378) time: 2.6173 data: 0.0060 max mem: 33369 +Epoch: [30] [1270/1319] eta: 0:02:08 lr: 1.3107248519950133e-05 loss: 0.0366 (0.0378) time: 2.6010 data: 0.0061 max mem: 33369 +Epoch: [30] [1280/1319] eta: 0:01:42 lr: 1.3097350861856001e-05 loss: 0.0366 (0.0378) time: 2.6155 data: 0.0062 max mem: 33369 +Epoch: [30] [1290/1319] eta: 0:01:16 lr: 1.3087452372619463e-05 loss: 0.0352 (0.0378) time: 2.6366 data: 0.0061 max mem: 33369 +Epoch: [30] [1300/1319] eta: 0:00:49 lr: 1.3077553051472149e-05 loss: 0.0345 (0.0378) time: 2.6039 data: 0.0059 max mem: 33369 +Epoch: [30] [1310/1319] eta: 0:00:23 lr: 1.3067652897644308e-05 loss: 0.0345 (0.0378) time: 2.5938 data: 0.0060 max mem: 33369 +Epoch: [30] Total time: 0:57:40 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 2:00:14 time: 2.8040 data: 2.7250 max mem: 33369 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 100/2573] eta: 0:04:04 time: 0.0715 data: 0.0011 max mem: 33369 +Test: [ 200/2573] eta: 0:03:25 time: 0.0734 data: 0.0011 max mem: 33369 +Test: [ 300/2573] eta: 0:03:05 time: 0.0751 data: 0.0011 max mem: 33369 +Test: [ 400/2573] eta: 0:02:53 time: 0.0750 data: 0.0011 max mem: 33369 +Test: [ 500/2573] eta: 0:02:42 time: 0.0734 data: 0.0011 max mem: 33369 +Test: [ 600/2573] eta: 0:02:33 time: 0.0736 data: 0.0011 max mem: 33369 +Test: [ 700/2573] eta: 0:02:25 time: 0.0736 data: 0.0011 max mem: 33369 +Test: [ 800/2573] eta: 0:02:16 time: 0.0769 data: 0.0011 max mem: 33369 +Test: [ 900/2573] eta: 0:02:08 time: 0.0736 data: 0.0011 max mem: 33369 +Test: [1000/2573] eta: 0:02:00 time: 0.0737 data: 0.0011 max mem: 33369 +Test: [1100/2573] eta: 0:01:52 time: 0.0736 data: 0.0011 max mem: 33369 +Test: [1200/2573] eta: 0:01:44 time: 0.0736 data: 0.0011 max mem: 33369 +Test: [1300/2573] eta: 0:01:36 time: 0.0736 data: 0.0011 max mem: 33369 +Test: [1400/2573] eta: 0:01:28 time: 0.0721 data: 0.0011 max mem: 33369 +Test: [1500/2573] eta: 0:01:21 time: 0.0737 data: 0.0011 max mem: 33369 +Test: [1600/2573] eta: 0:01:13 time: 0.0769 data: 0.0011 max mem: 33369 +Test: [1700/2573] eta: 0:01:05 time: 0.0719 data: 0.0010 max mem: 33369 +Test: [1800/2573] eta: 0:00:58 time: 0.0752 data: 0.0011 max mem: 33369 +Test: [1900/2573] eta: 0:00:50 time: 0.0721 data: 0.0011 max mem: 33369 +Test: [2000/2573] eta: 0:00:42 time: 0.0737 data: 0.0011 max mem: 33369 +Test: [2100/2573] eta: 0:00:35 time: 0.0752 data: 0.0011 max mem: 33369 +Test: [2200/2573] eta: 0:00:27 time: 0.0753 data: 0.0011 max mem: 33369 +Test: [2300/2573] eta: 0:00:20 time: 0.0753 data: 0.0011 max mem: 33369 +Test: [2400/2573] eta: 0:00:12 time: 0.0704 data: 0.0011 max mem: 33369 +Test: [2500/2573] eta: 0:00:05 time: 0.0737 data: 0.0011 max mem: 33369 +Test: Total time: 0:03:12 +Final results: +Mean IoU is 64.65 + + precision@0.5 = 72.47 + precision@0.6 = 67.48 + precision@0.7 = 61.01 + precision@0.8 = 49.67 + precision@0.9 = 25.33 + overall IoU = 62.10 + +Average object IoU 64.6486151137698 +Overall IoU 62.097591400146484 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [31] [ 0/1319] eta: 3:14:27 lr: 1.3058742046620123e-05 loss: 0.0372 (0.0372) time: 8.8457 data: 1.4200 max mem: 33369 +Epoch: [31] [ 10/1319] eta: 1:10:15 lr: 1.3048840308573793e-05 loss: 0.0337 (0.0345) time: 3.2207 data: 0.1348 max mem: 33369 +Epoch: [31] [ 20/1319] eta: 1:03:38 lr: 1.3038937735606992e-05 loss: 0.0311 (0.0326) time: 2.6444 data: 0.0062 max mem: 33369 +Epoch: [31] [ 30/1319] eta: 1:01:06 lr: 1.3029034326944665e-05 loss: 0.0335 (0.0339) time: 2.6370 data: 0.0062 max mem: 33369 +Epoch: [31] [ 40/1319] eta: 0:59:27 lr: 1.3019130081810363e-05 loss: 0.0325 (0.0355) time: 2.6319 data: 0.0063 max mem: 33369 +Epoch: [31] [ 50/1319] eta: 0:58:20 lr: 1.3009224999426282e-05 loss: 0.0313 (0.0364) time: 2.6255 data: 0.0062 max mem: 33369 +Epoch: [31] [ 60/1319] eta: 0:57:29 lr: 1.2999319079013207e-05 loss: 0.0405 (0.0371) time: 2.6372 data: 0.0061 max mem: 33369 +Epoch: [31] [ 70/1319] eta: 0:56:40 lr: 1.298941231979056e-05 loss: 0.0407 (0.0386) time: 2.6321 data: 0.0060 max mem: 33369 +Epoch: [31] [ 80/1319] eta: 0:55:56 lr: 1.2979504720976363e-05 loss: 0.0321 (0.0375) time: 2.6174 data: 0.0062 max mem: 33369 +Epoch: [31] [ 90/1319] eta: 0:55:21 lr: 1.2969596281787253e-05 loss: 0.0301 (0.0371) time: 2.6304 data: 0.0063 max mem: 33369 +Epoch: [31] [ 100/1319] eta: 0:54:46 lr: 1.2959687001438464e-05 loss: 0.0301 (0.0369) time: 2.6427 data: 0.0064 max mem: 33369 +Epoch: [31] [ 110/1319] eta: 0:54:12 lr: 1.2949776879143838e-05 loss: 0.0280 (0.0367) time: 2.6343 data: 0.0062 max mem: 33369 +Epoch: [31] [ 120/1319] eta: 0:53:38 lr: 1.2939865914115796e-05 loss: 0.0336 (0.0368) time: 2.6245 data: 0.0061 max mem: 33369 +Epoch: [31] [ 130/1319] eta: 0:53:09 lr: 1.2929954105565368e-05 loss: 0.0345 (0.0403) time: 2.6372 data: 0.0062 max mem: 33369 +Epoch: [31] [ 140/1319] eta: 0:52:39 lr: 1.2920041452702167e-05 loss: 0.0350 (0.0404) time: 2.6526 data: 0.0063 max mem: 33369 +Epoch: [31] [ 150/1319] eta: 0:52:07 lr: 1.2910127954734388e-05 loss: 0.0325 (0.0400) time: 2.6307 data: 0.0064 max mem: 33369 +Epoch: [31] [ 160/1319] eta: 0:51:40 lr: 1.2900213610868823e-05 loss: 0.0304 (0.0400) time: 2.6424 data: 0.0063 max mem: 33369 +Epoch: [31] [ 170/1319] eta: 0:51:06 lr: 1.2890298420310808e-05 loss: 0.0304 (0.0403) time: 2.6177 data: 0.0063 max mem: 33369 +Epoch: [31] [ 180/1319] eta: 0:50:41 lr: 1.2880382382264284e-05 loss: 0.0324 (0.0401) time: 2.6309 data: 0.0063 max mem: 33369 +Epoch: [31] [ 190/1319] eta: 0:50:12 lr: 1.2870465495931752e-05 loss: 0.0266 (0.0400) time: 2.6675 data: 0.0063 max mem: 33369 +Epoch: [31] [ 200/1319] eta: 0:49:43 lr: 1.2860547760514275e-05 loss: 0.0305 (0.0398) time: 2.6329 data: 0.0063 max mem: 33369 +Epoch: [31] [ 210/1319] eta: 0:49:15 lr: 1.285062917521149e-05 loss: 0.0332 (0.0395) time: 2.6338 data: 0.0062 max mem: 33369 +Epoch: [31] [ 220/1319] eta: 0:48:46 lr: 1.2840709739221567e-05 loss: 0.0285 (0.0392) time: 2.6249 data: 0.0062 max mem: 33369 +Epoch: [31] [ 230/1319] eta: 0:48:17 lr: 1.2830789451741262e-05 loss: 0.0281 (0.0389) time: 2.6134 data: 0.0063 max mem: 33369 +Epoch: [31] [ 240/1319] eta: 0:47:47 lr: 1.2820868311965862e-05 loss: 0.0301 (0.0386) time: 2.6040 data: 0.0062 max mem: 33369 +Epoch: [31] [ 250/1319] eta: 0:47:17 lr: 1.2810946319089204e-05 loss: 0.0303 (0.0383) time: 2.5840 data: 0.0062 max mem: 33369 +Epoch: [31] [ 260/1319] eta: 0:46:48 lr: 1.2801023472303672e-05 loss: 0.0327 (0.0382) time: 2.5798 data: 0.0063 max mem: 33369 +Epoch: [31] [ 270/1319] eta: 0:46:19 lr: 1.2791099770800195e-05 loss: 0.0336 (0.0381) time: 2.5919 data: 0.0062 max mem: 33369 +Epoch: [31] [ 280/1319] eta: 0:45:52 lr: 1.2781175213768214e-05 loss: 0.0335 (0.0381) time: 2.6083 data: 0.0061 max mem: 33369 +Epoch: [31] [ 290/1319] eta: 0:45:24 lr: 1.277124980039573e-05 loss: 0.0334 (0.0380) time: 2.6174 data: 0.0061 max mem: 33369 +Epoch: [31] [ 300/1319] eta: 0:44:56 lr: 1.2761323529869248e-05 loss: 0.0373 (0.0383) time: 2.6053 data: 0.0061 max mem: 33369 +Epoch: [31] [ 310/1319] eta: 0:44:29 lr: 1.2751396401373813e-05 loss: 0.0399 (0.0389) time: 2.6169 data: 0.0061 max mem: 33369 +Epoch: [31] [ 320/1319] eta: 0:44:03 lr: 1.2741468414092989e-05 loss: 0.0363 (0.0388) time: 2.6482 data: 0.0060 max mem: 33369 +Epoch: [31] [ 330/1319] eta: 0:43:37 lr: 1.2731539567208833e-05 loss: 0.0347 (0.0387) time: 2.6588 data: 0.0059 max mem: 33369 +Epoch: [31] [ 340/1319] eta: 0:43:09 lr: 1.2721609859901942e-05 loss: 0.0347 (0.0387) time: 2.6293 data: 0.0060 max mem: 33369 +Epoch: [31] [ 350/1319] eta: 0:42:41 lr: 1.2711679291351405e-05 loss: 0.0364 (0.0387) time: 2.5966 data: 0.0060 max mem: 33369 +Epoch: [31] [ 360/1319] eta: 0:42:15 lr: 1.2701747860734819e-05 loss: 0.0395 (0.0388) time: 2.6235 data: 0.0061 max mem: 33369 +Epoch: [31] [ 370/1319] eta: 0:41:46 lr: 1.2691815567228285e-05 loss: 0.0400 (0.0389) time: 2.5973 data: 0.0062 max mem: 33369 +Epoch: [31] [ 380/1319] eta: 0:41:19 lr: 1.2681882410006382e-05 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1.2602385958929271e-05 loss: 0.0339 (0.0389) time: 2.6512 data: 0.0058 max mem: 33369 +Epoch: [31] [ 470/1319] eta: 0:37:21 lr: 1.2592444990875415e-05 loss: 0.0350 (0.0389) time: 2.6253 data: 0.0058 max mem: 33369 +Epoch: [31] [ 480/1319] eta: 0:36:54 lr: 1.258250315076846e-05 loss: 0.0335 (0.0388) time: 2.6229 data: 0.0060 max mem: 33369 +Epoch: [31] [ 490/1319] eta: 0:36:28 lr: 1.2572560437766163e-05 loss: 0.0329 (0.0388) time: 2.6296 data: 0.0060 max mem: 33369 +Epoch: [31] [ 500/1319] eta: 0:36:01 lr: 1.2562616851024742e-05 loss: 0.0363 (0.0389) time: 2.6193 data: 0.0061 max mem: 33369 +Epoch: [31] [ 510/1319] eta: 0:35:35 lr: 1.2552672389698855e-05 loss: 0.0344 (0.0389) time: 2.6272 data: 0.0062 max mem: 33369 +Epoch: [31] [ 520/1319] eta: 0:35:08 lr: 1.2542727052941597e-05 loss: 0.0315 (0.0388) time: 2.6397 data: 0.0063 max mem: 33369 +Epoch: [31] [ 530/1319] eta: 0:34:41 lr: 1.2532780839904498e-05 loss: 0.0315 (0.0388) time: 2.6154 data: 0.0063 max mem: 33369 +Epoch: [31] [ 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data: 0.0059 max mem: 33369 +Epoch: [31] [ 700/1319] eta: 0:27:12 lr: 1.236356031760655e-05 loss: 0.0345 (0.0383) time: 2.6420 data: 0.0060 max mem: 33369 +Epoch: [31] [ 710/1319] eta: 0:26:45 lr: 1.2353598184630927e-05 loss: 0.0363 (0.0382) time: 2.6502 data: 0.0059 max mem: 33369 +Epoch: [31] [ 720/1319] eta: 0:26:19 lr: 1.2343635158950937e-05 loss: 0.0373 (0.0383) time: 2.6449 data: 0.0057 max mem: 33369 +Epoch: [31] [ 730/1319] eta: 0:25:53 lr: 1.2333671239685849e-05 loss: 0.0352 (0.0382) time: 2.6321 data: 0.0059 max mem: 33369 +Epoch: [31] [ 740/1319] eta: 0:25:27 lr: 1.2323706425953264e-05 loss: 0.0311 (0.0382) time: 2.6510 data: 0.0059 max mem: 33369 +Epoch: [31] [ 750/1319] eta: 0:25:00 lr: 1.2313740716869131e-05 loss: 0.0311 (0.0382) time: 2.6410 data: 0.0057 max mem: 33369 +Epoch: [31] [ 760/1319] eta: 0:24:34 lr: 1.2303774111547706e-05 loss: 0.0325 (0.0381) time: 2.6256 data: 0.0057 max mem: 33369 +Epoch: [31] [ 770/1319] eta: 0:24:07 lr: 1.2293806609101593e-05 loss: 0.0339 (0.0382) time: 2.6631 data: 0.0059 max mem: 33369 +Epoch: [31] [ 780/1319] eta: 0:23:41 lr: 1.2283838208641708e-05 loss: 0.0389 (0.0382) time: 2.6573 data: 0.0058 max mem: 33369 +Epoch: [31] [ 790/1319] eta: 0:23:15 lr: 1.2273868909277286e-05 loss: 0.0396 (0.0382) time: 2.6344 data: 0.0058 max mem: 33369 +Epoch: [31] [ 800/1319] eta: 0:22:48 lr: 1.2263898710115878e-05 loss: 0.0373 (0.0382) time: 2.6141 data: 0.0058 max mem: 33369 +Epoch: [31] [ 810/1319] eta: 0:22:22 lr: 1.2253927610263324e-05 loss: 0.0343 (0.0382) time: 2.6179 data: 0.0060 max mem: 33369 +Epoch: [31] [ 820/1319] eta: 0:21:55 lr: 1.2243955608823781e-05 loss: 0.0314 (0.0382) time: 2.6327 data: 0.0059 max mem: 33369 +Epoch: [31] [ 830/1319] eta: 0:21:29 lr: 1.2233982704899707e-05 loss: 0.0334 (0.0381) time: 2.6203 data: 0.0059 max mem: 33369 +Epoch: [31] [ 840/1319] eta: 0:21:02 lr: 1.2224008897591841e-05 loss: 0.0320 (0.0381) time: 2.6309 data: 0.0059 max mem: 33369 +Epoch: [31] [ 850/1319] eta: 0:20:36 lr: 1.2214034185999218e-05 loss: 0.0297 (0.0380) time: 2.6304 data: 0.0059 max mem: 33369 +Epoch: [31] [ 860/1319] eta: 0:20:10 lr: 1.2204058569219158e-05 loss: 0.0298 (0.0380) time: 2.6234 data: 0.0061 max mem: 33369 +Epoch: [31] [ 870/1319] eta: 0:19:43 lr: 1.2194082046347242e-05 loss: 0.0329 (0.0380) time: 2.6346 data: 0.0061 max mem: 33369 +Epoch: [31] [ 880/1319] eta: 0:19:17 lr: 1.2184104616477345e-05 loss: 0.0329 (0.0380) time: 2.6410 data: 0.0059 max mem: 33369 +Epoch: [31] [ 890/1319] eta: 0:18:50 lr: 1.2174126278701602e-05 loss: 0.0307 (0.0379) time: 2.6355 data: 0.0058 max mem: 33369 +Epoch: [31] [ 900/1319] eta: 0:18:24 lr: 1.2164147032110409e-05 loss: 0.0376 (0.0380) time: 2.6277 data: 0.0059 max mem: 33369 +Epoch: [31] [ 910/1319] eta: 0:17:58 lr: 1.215416687579243e-05 loss: 0.0380 (0.0380) time: 2.6155 data: 0.0060 max mem: 33369 +Epoch: [31] [ 920/1319] eta: 0:17:31 lr: 1.2144185808834565e-05 loss: 0.0356 (0.0380) time: 2.5989 data: 0.0059 max mem: 33369 +Epoch: [31] [ 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33369 +Epoch: [31] [1010/1319] eta: 0:13:33 lr: 1.2054315075888731e-05 loss: 0.0312 (0.0378) time: 2.6239 data: 0.0060 max mem: 33369 +Epoch: [31] [1020/1319] eta: 0:13:07 lr: 1.2044324851924447e-05 loss: 0.0302 (0.0378) time: 2.6286 data: 0.0059 max mem: 33369 +Epoch: [31] [1030/1319] eta: 0:12:40 lr: 1.2034333707159618e-05 loss: 0.0345 (0.0378) time: 2.6150 data: 0.0059 max mem: 33369 +Epoch: [31] [1040/1319] eta: 0:12:14 lr: 1.2024341640659817e-05 loss: 0.0380 (0.0379) time: 2.6022 data: 0.0061 max mem: 33369 +Epoch: [31] [1050/1319] eta: 0:11:48 lr: 1.2014348651488794e-05 loss: 0.0329 (0.0378) time: 2.6300 data: 0.0061 max mem: 33369 +Epoch: [31] [1060/1319] eta: 0:11:21 lr: 1.2004354738708488e-05 loss: 0.0316 (0.0378) time: 2.6464 data: 0.0059 max mem: 33369 +Epoch: [31] [1070/1319] eta: 0:10:55 lr: 1.1994359901379014e-05 loss: 0.0323 (0.0378) time: 2.6071 data: 0.0058 max mem: 33369 +Epoch: [31] [1080/1319] eta: 0:10:29 lr: 1.1984364138558649e-05 loss: 0.0316 (0.0378) time: 2.6055 data: 0.0059 max mem: 33369 +Epoch: [31] [1090/1319] eta: 0:10:02 lr: 1.1974367449303851e-05 loss: 0.0330 (0.0378) time: 2.6064 data: 0.0062 max mem: 33369 +Epoch: [31] [1100/1319] eta: 0:09:36 lr: 1.1964369832669236e-05 loss: 0.0330 (0.0378) time: 2.6136 data: 0.0061 max mem: 33369 +Epoch: [31] [1110/1319] eta: 0:09:10 lr: 1.195437128770757e-05 loss: 0.0334 (0.0378) time: 2.6499 data: 0.0058 max mem: 33369 +Epoch: [31] [1120/1319] eta: 0:08:43 lr: 1.194437181346979e-05 loss: 0.0337 (0.0377) time: 2.6500 data: 0.0059 max mem: 33369 +Epoch: [31] [1130/1319] eta: 0:08:17 lr: 1.1934371409004944e-05 loss: 0.0347 (0.0378) time: 2.6374 data: 0.0059 max mem: 33369 +Epoch: [31] [1140/1319] eta: 0:07:51 lr: 1.192437007336025e-05 loss: 0.0347 (0.0378) time: 2.6208 data: 0.0059 max mem: 33369 +Epoch: [31] [1150/1319] eta: 0:07:24 lr: 1.1914367805581053e-05 loss: 0.0352 (0.0378) time: 2.5968 data: 0.0059 max mem: 33369 +Epoch: [31] [1160/1319] eta: 0:06:58 lr: 1.1904364604710826e-05 loss: 0.0352 (0.0378) time: 2.5838 data: 0.0060 max mem: 33369 +Epoch: [31] [1170/1319] eta: 0:06:32 lr: 1.1894360469791169e-05 loss: 0.0349 (0.0378) time: 2.6117 data: 0.0060 max mem: 33369 +Epoch: [31] [1180/1319] eta: 0:06:05 lr: 1.1884355399861802e-05 loss: 0.0300 (0.0377) time: 2.6613 data: 0.0058 max mem: 33369 +Epoch: [31] [1190/1319] eta: 0:05:39 lr: 1.1874349393960545e-05 loss: 0.0347 (0.0377) time: 2.6497 data: 0.0057 max mem: 33369 +Epoch: [31] [1200/1319] eta: 0:05:13 lr: 1.1864342451123342e-05 loss: 0.0358 (0.0377) time: 2.6156 data: 0.0058 max mem: 33369 +Epoch: [31] [1210/1319] eta: 0:04:46 lr: 1.1854334570384235e-05 loss: 0.0309 (0.0376) time: 2.6050 data: 0.0059 max mem: 33369 +Epoch: [31] [1220/1319] eta: 0:04:20 lr: 1.1844325750775364e-05 loss: 0.0276 (0.0376) time: 2.6002 data: 0.0059 max mem: 33369 +Epoch: [31] [1230/1319] eta: 0:03:54 lr: 1.183431599132696e-05 loss: 0.0339 (0.0376) time: 2.5964 data: 0.0058 max mem: 33369 +Epoch: [31] [1240/1319] eta: 0:03:27 lr: 1.1824305291067328e-05 loss: 0.0340 (0.0376) time: 2.6156 data: 0.0058 max mem: 33369 +Epoch: [31] [1250/1319] eta: 0:03:01 lr: 1.1814293649022872e-05 loss: 0.0321 (0.0376) time: 2.6319 data: 0.0059 max mem: 33369 +Epoch: [31] [1260/1319] eta: 0:02:35 lr: 1.180428106421806e-05 loss: 0.0311 (0.0375) time: 2.6472 data: 0.0059 max mem: 33369 +Epoch: [31] [1270/1319] eta: 0:02:08 lr: 1.1794267535675433e-05 loss: 0.0311 (0.0375) time: 2.6472 data: 0.0059 max mem: 33369 +Epoch: [31] [1280/1319] eta: 0:01:42 lr: 1.1784253062415594e-05 loss: 0.0302 (0.0375) time: 2.6338 data: 0.0059 max mem: 33369 +Epoch: [31] [1290/1319] eta: 0:01:16 lr: 1.1774237643457209e-05 loss: 0.0322 (0.0375) time: 2.6347 data: 0.0059 max mem: 33369 +Epoch: [31] [1300/1319] eta: 0:00:49 lr: 1.1764221277816978e-05 loss: 0.0323 (0.0375) time: 2.6200 data: 0.0058 max mem: 33369 +Epoch: [31] [1310/1319] eta: 0:00:23 lr: 1.1754203964509668e-05 loss: 0.0318 (0.0375) time: 2.6284 data: 0.0059 max mem: 33369 +Epoch: [31] Total time: 0:57:50 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 2:12:46 time: 3.0960 data: 3.0178 max mem: 33369 +Test: [ 100/2573] eta: 0:04:12 time: 0.0719 data: 0.0011 max mem: 33369 +Test: [ 200/2573] eta: 0:03:29 time: 0.0738 data: 0.0011 max mem: 33369 +Test: [ 300/2573] eta: 0:03:08 time: 0.0755 data: 0.0011 max mem: 33369 +Test: [ 400/2573] eta: 0:02:55 time: 0.0754 data: 0.0011 max mem: 33369 +Test: [ 500/2573] eta: 0:02:44 time: 0.0738 data: 0.0011 max mem: 33369 +Test: [ 600/2573] eta: 0:02:34 time: 0.0737 data: 0.0011 max mem: 33369 +Test: [ 700/2573] eta: 0:02:26 time: 0.0737 data: 0.0011 max mem: 33369 +Test: [ 800/2573] eta: 0:02:17 time: 0.0770 data: 0.0011 max mem: 33369 +Test: [ 900/2573] eta: 0:02:09 time: 0.0737 data: 0.0011 max mem: 33369 +Test: [1000/2573] eta: 0:02:01 time: 0.0738 data: 0.0011 max mem: 33369 +Test: [1100/2573] eta: 0:01:52 time: 0.0738 data: 0.0011 max mem: 33369 +Test: [1200/2573] eta: 0:01:45 time: 0.0737 data: 0.0011 max mem: 33369 +Test: [1300/2573] eta: 0:01:37 time: 0.0737 data: 0.0011 max mem: 33369 +Test: [1400/2573] eta: 0:01:29 time: 0.0722 data: 0.0011 max mem: 33369 +Test: [1500/2573] eta: 0:01:21 time: 0.0737 data: 0.0011 max mem: 33369 +Test: [1600/2573] eta: 0:01:13 time: 0.0770 data: 0.0011 max mem: 33369 +Test: [1700/2573] eta: 0:01:06 time: 0.0721 data: 0.0011 max mem: 33369 +Test: [1800/2573] eta: 0:00:58 time: 0.0753 data: 0.0011 max mem: 33369 +Test: [1900/2573] eta: 0:00:50 time: 0.0721 data: 0.0011 max mem: 33369 +Test: [2000/2573] eta: 0:00:43 time: 0.0737 data: 0.0011 max mem: 33369 +Test: [2100/2573] eta: 0:00:35 time: 0.0754 data: 0.0011 max mem: 33369 +Test: [2200/2573] eta: 0:00:28 time: 0.0753 data: 0.0011 max mem: 33369 +Test: [2300/2573] eta: 0:00:20 time: 0.0756 data: 0.0011 max mem: 33369 +Test: [2400/2573] eta: 0:00:12 time: 0.0705 data: 0.0011 max mem: 33369 +Test: [2500/2573] eta: 0:00:05 time: 0.0738 data: 0.0011 max mem: 33369 +Test: Total time: 0:03:13 +Final results: +Mean IoU is 64.67 + + precision@0.5 = 72.34 + precision@0.6 = 67.75 + precision@0.7 = 61.29 + precision@0.8 = 50.67 + precision@0.9 = 25.53 + overall IoU = 61.85 + +Average object IoU 64.67328955261794 +Overall IoU 61.84696960449219 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [32] [ 0/1319] eta: 3:14:25 lr: 1.1745187571461855e-05 loss: 0.0297 (0.0297) time: 8.8439 data: 1.7852 max mem: 33369 +Epoch: [32] [ 10/1319] eta: 1:09:48 lr: 1.1735168454865734e-05 loss: 0.0297 (0.0294) time: 3.1998 data: 0.1682 max mem: 33369 +Epoch: [32] [ 20/1319] eta: 1:03:14 lr: 1.1725148387734231e-05 loss: 0.0306 (0.0347) time: 2.6248 data: 0.0060 max mem: 33369 +Epoch: [32] [ 30/1319] eta: 1:00:49 lr: 1.1715127369074435e-05 loss: 0.0315 (0.0370) time: 2.6292 data: 0.0057 max mem: 33369 +Epoch: [32] [ 40/1319] eta: 0:59:19 lr: 1.1705105397891451e-05 loss: 0.0309 (0.0360) time: 2.6374 data: 0.0061 max mem: 33369 +Epoch: [32] [ 50/1319] eta: 0:58:14 lr: 1.1695082473188386e-05 loss: 0.0298 (0.0350) time: 2.6338 data: 0.0060 max mem: 33369 +Epoch: [32] [ 60/1319] eta: 0:57:15 lr: 1.1685058593966367e-05 loss: 0.0295 (0.0345) time: 2.6182 data: 0.0062 max mem: 33369 +Epoch: [32] [ 70/1319] eta: 0:56:27 lr: 1.1675033759224512e-05 loss: 0.0283 (0.0342) time: 2.6048 data: 0.0064 max mem: 33369 +Epoch: [32] [ 80/1319] eta: 0:55:43 lr: 1.1665007967959945e-05 loss: 0.0302 (0.0344) time: 2.6061 data: 0.0063 max mem: 33369 +Epoch: [32] [ 90/1319] eta: 0:55:15 lr: 1.1654981219167763e-05 loss: 0.0311 (0.0341) time: 2.6481 data: 0.0062 max mem: 33369 +Epoch: [32] [ 100/1319] eta: 0:54:41 lr: 1.1644953511841062e-05 loss: 0.0321 (0.0340) time: 2.6645 data: 0.0063 max mem: 33369 +Epoch: [32] [ 110/1319] eta: 0:54:03 lr: 1.1634924844970898e-05 loss: 0.0292 (0.0336) time: 2.6119 data: 0.0061 max mem: 33369 +Epoch: [32] [ 120/1319] eta: 0:53:31 lr: 1.1624895217546308e-05 loss: 0.0301 (0.0336) time: 2.6137 data: 0.0061 max mem: 33369 +Epoch: [32] [ 130/1319] eta: 0:52:55 lr: 1.1614864628554293e-05 loss: 0.0322 (0.0338) time: 2.6043 data: 0.0061 max mem: 33369 +Epoch: [32] [ 140/1319] eta: 0:52:24 lr: 1.160483307697981e-05 loss: 0.0323 (0.0338) time: 2.5934 data: 0.0062 max mem: 33369 +Epoch: [32] [ 150/1319] eta: 0:51:52 lr: 1.159480056180578e-05 loss: 0.0306 (0.0335) time: 2.6128 data: 0.0062 max mem: 33369 +Epoch: [32] [ 160/1319] eta: 0:51:19 lr: 1.1584767082013038e-05 loss: 0.0295 (0.0338) time: 2.5911 data: 0.0064 max mem: 33369 +Epoch: [32] [ 170/1319] eta: 0:50:48 lr: 1.1574732636580395e-05 loss: 0.0350 (0.0340) time: 2.5799 data: 0.0063 max mem: 33369 +Epoch: [32] [ 180/1319] eta: 0:50:19 lr: 1.1564697224484583e-05 loss: 0.0296 (0.0337) time: 2.6019 data: 0.0062 max mem: 33369 +Epoch: [32] [ 190/1319] eta: 0:49:50 lr: 1.1554660844700256e-05 loss: 0.0312 (0.0339) time: 2.6088 data: 0.0062 max mem: 33369 +Epoch: [32] [ 200/1319] eta: 0:49:21 lr: 1.1544623496200004e-05 loss: 0.0370 (0.0340) time: 2.6058 data: 0.0061 max mem: 33369 +Epoch: [32] [ 210/1319] eta: 0:48:53 lr: 1.153458517795431e-05 loss: 0.0340 (0.0341) time: 2.6162 data: 0.0062 max mem: 33369 +Epoch: [32] [ 220/1319] eta: 0:48:26 lr: 1.1524545888931584e-05 loss: 0.0314 (0.0341) time: 2.6212 data: 0.0061 max mem: 33369 +Epoch: [32] [ 230/1319] eta: 0:47:57 lr: 1.1514505628098139e-05 loss: 0.0286 (0.0344) time: 2.6087 data: 0.0061 max mem: 33369 +Epoch: [32] [ 240/1319] eta: 0:47:32 lr: 1.1504464394418176e-05 loss: 0.0336 (0.0344) time: 2.6313 data: 0.0061 max mem: 33369 +Epoch: [32] [ 250/1319] eta: 0:47:05 lr: 1.149442218685379e-05 loss: 0.0313 (0.0343) time: 2.6579 data: 0.0060 max mem: 33369 +Epoch: [32] [ 260/1319] eta: 0:46:37 lr: 1.1484379004364971e-05 loss: 0.0275 (0.0341) time: 2.6163 data: 0.0061 max mem: 33369 +Epoch: [32] [ 270/1319] eta: 0:46:09 lr: 1.147433484590956e-05 loss: 0.0322 (0.0343) time: 2.5962 data: 0.0062 max mem: 33369 +Epoch: [32] [ 280/1319] eta: 0:45:42 lr: 1.1464289710443295e-05 loss: 0.0287 (0.0341) time: 2.6124 data: 0.0061 max mem: 33369 +Epoch: [32] [ 290/1319] eta: 0:45:14 lr: 1.1454243596919765e-05 loss: 0.0287 (0.0342) time: 2.6167 data: 0.0061 max mem: 33369 +Epoch: [32] [ 300/1319] eta: 0:44:47 lr: 1.144419650429042e-05 loss: 0.0320 (0.0342) time: 2.6181 data: 0.0061 max mem: 33369 +Epoch: [32] [ 310/1319] eta: 0:44:22 lr: 1.1434148431504575e-05 loss: 0.0288 (0.0339) time: 2.6445 data: 0.0062 max mem: 33369 +Epoch: [32] [ 320/1319] eta: 0:43:56 lr: 1.1424099377509363e-05 loss: 0.0288 (0.0339) time: 2.6529 data: 0.0061 max mem: 33369 +Epoch: [32] [ 330/1319] eta: 0:43:28 lr: 1.141404934124978e-05 loss: 0.0309 (0.0339) time: 2.6166 data: 0.0062 max mem: 33369 +Epoch: [32] [ 340/1319] eta: 0:43:01 lr: 1.140399832166864e-05 loss: 0.0299 (0.0338) time: 2.5992 data: 0.0063 max mem: 33369 +Epoch: [32] [ 350/1319] eta: 0:42:35 lr: 1.1393946317706594e-05 loss: 0.0316 (0.0339) time: 2.6261 data: 0.0063 max mem: 33369 +Epoch: [32] [ 360/1319] eta: 0:42:08 lr: 1.138389332830211e-05 loss: 0.0323 (0.0339) time: 2.6453 data: 0.0064 max mem: 33369 +Epoch: [32] [ 370/1319] eta: 0:41:40 lr: 1.1373839352391454e-05 loss: 0.0323 (0.0342) time: 2.6022 data: 0.0063 max mem: 33369 +Epoch: [32] [ 380/1319] eta: 0:41:14 lr: 1.1363784388908714e-05 loss: 0.0381 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1.0890066963908222e-05 loss: 0.0330 (0.0347) time: 2.6100 data: 0.0062 max mem: 33369 +Epoch: [32] [ 860/1319] eta: 0:20:06 lr: 1.087996329870281e-05 loss: 0.0328 (0.0347) time: 2.6369 data: 0.0059 max mem: 33369 +Epoch: [32] [ 870/1319] eta: 0:19:39 lr: 1.0869858590861098e-05 loss: 0.0351 (0.0347) time: 2.6456 data: 0.0059 max mem: 33369 +Epoch: [32] [ 880/1319] eta: 0:19:13 lr: 1.085975283919833e-05 loss: 0.0321 (0.0347) time: 2.6196 data: 0.0060 max mem: 33369 +Epoch: [32] [ 890/1319] eta: 0:18:47 lr: 1.0849646042527184e-05 loss: 0.0320 (0.0347) time: 2.6220 data: 0.0059 max mem: 33369 +Epoch: [32] [ 900/1319] eta: 0:18:20 lr: 1.0839538199657755e-05 loss: 0.0317 (0.0346) time: 2.6242 data: 0.0059 max mem: 33369 +Epoch: [32] [ 910/1319] eta: 0:17:54 lr: 1.0829429309397535e-05 loss: 0.0313 (0.0346) time: 2.6268 data: 0.0061 max mem: 33369 +Epoch: [32] [ 920/1319] eta: 0:17:28 lr: 1.0819319370551438e-05 loss: 0.0335 (0.0346) time: 2.6223 data: 0.0061 max mem: 33369 +Epoch: [32] [ 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33369 +Epoch: [32] [1010/1319] eta: 0:13:31 lr: 1.0728282536084938e-05 loss: 0.0362 (0.0347) time: 2.6053 data: 0.0059 max mem: 33369 +Epoch: [32] [1020/1319] eta: 0:13:05 lr: 1.0718162045072395e-05 loss: 0.0338 (0.0347) time: 2.5928 data: 0.0057 max mem: 33369 +Epoch: [32] [1030/1319] eta: 0:12:39 lr: 1.0708040492154082e-05 loss: 0.0285 (0.0347) time: 2.6140 data: 0.0058 max mem: 33369 +Epoch: [32] [1040/1319] eta: 0:12:12 lr: 1.069791787610307e-05 loss: 0.0277 (0.0347) time: 2.6284 data: 0.0059 max mem: 33369 +Epoch: [32] [1050/1319] eta: 0:11:46 lr: 1.0687794195689722e-05 loss: 0.0303 (0.0347) time: 2.5889 data: 0.0059 max mem: 33369 +Epoch: [32] [1060/1319] eta: 0:11:20 lr: 1.0677669449681687e-05 loss: 0.0335 (0.0348) time: 2.5982 data: 0.0060 max mem: 33369 +Epoch: [32] [1070/1319] eta: 0:10:54 lr: 1.0667543636843873e-05 loss: 0.0335 (0.0348) time: 2.6245 data: 0.0059 max mem: 33369 +Epoch: [32] [1080/1319] eta: 0:10:27 lr: 1.0657416755938468e-05 loss: 0.0384 (0.0348) time: 2.6374 data: 0.0059 max mem: 33369 +Epoch: [32] [1090/1319] eta: 0:10:01 lr: 1.0647288805724908e-05 loss: 0.0323 (0.0348) time: 2.6358 data: 0.0060 max mem: 33369 +Epoch: [32] [1100/1319] eta: 0:09:35 lr: 1.0637159784959879e-05 loss: 0.0323 (0.0349) time: 2.6123 data: 0.0060 max mem: 33369 +Epoch: [32] [1110/1319] eta: 0:09:08 lr: 1.0627029692397306e-05 loss: 0.0397 (0.0349) time: 2.6027 data: 0.0059 max mem: 33369 +Epoch: [32] [1120/1319] eta: 0:08:42 lr: 1.0616898526788328e-05 loss: 0.0335 (0.0349) time: 2.6303 data: 0.0057 max mem: 33369 +Epoch: [32] [1130/1319] eta: 0:08:16 lr: 1.0606766286881316e-05 loss: 0.0314 (0.0349) time: 2.6274 data: 0.0058 max mem: 33369 +Epoch: [32] [1140/1319] eta: 0:07:50 lr: 1.059663297142185e-05 loss: 0.0352 (0.0349) time: 2.5982 data: 0.0061 max mem: 33369 +Epoch: [32] [1150/1319] eta: 0:07:23 lr: 1.058649857915271e-05 loss: 0.0368 (0.0349) time: 2.5991 data: 0.0061 max mem: 33369 +Epoch: [32] [1160/1319] eta: 0:06:57 lr: 1.0576363108813862e-05 loss: 0.0348 (0.0349) time: 2.6203 data: 0.0059 max mem: 33369 +Epoch: [32] [1170/1319] eta: 0:06:31 lr: 1.0566226559142468e-05 loss: 0.0343 (0.0349) time: 2.6220 data: 0.0059 max mem: 33369 +Epoch: [32] [1180/1319] eta: 0:06:04 lr: 1.0556088928872841e-05 loss: 0.0310 (0.0349) time: 2.6217 data: 0.0060 max mem: 33369 +Epoch: [32] [1190/1319] eta: 0:05:38 lr: 1.0545950216736473e-05 loss: 0.0310 (0.0349) time: 2.6421 data: 0.0061 max mem: 33369 +Epoch: [32] [1200/1319] eta: 0:05:12 lr: 1.0535810421462011e-05 loss: 0.0369 (0.0349) time: 2.6288 data: 0.0061 max mem: 33369 +Epoch: [32] [1210/1319] eta: 0:04:46 lr: 1.0525669541775238e-05 loss: 0.0338 (0.0349) time: 2.6153 data: 0.0060 max mem: 33369 +Epoch: [32] [1220/1319] eta: 0:04:19 lr: 1.0515527576399085e-05 loss: 0.0305 (0.0349) time: 2.6341 data: 0.0060 max mem: 33369 +Epoch: [32] [1230/1319] eta: 0:03:53 lr: 1.050538452405359e-05 loss: 0.0338 (0.0349) time: 2.6450 data: 0.0060 max mem: 33369 +Epoch: [32] [1240/1319] eta: 0:03:27 lr: 1.049524038345592e-05 loss: 0.0331 (0.0349) time: 2.6317 data: 0.0060 max mem: 33369 +Epoch: [32] [1250/1319] eta: 0:03:01 lr: 1.048509515332035e-05 loss: 0.0316 (0.0349) time: 2.6424 data: 0.0060 max mem: 33369 +Epoch: [32] [1260/1319] eta: 0:02:34 lr: 1.0474948832358245e-05 loss: 0.0326 (0.0349) time: 2.6365 data: 0.0062 max mem: 33369 +Epoch: [32] [1270/1319] eta: 0:02:08 lr: 1.0464801419278068e-05 loss: 0.0326 (0.0350) time: 2.6220 data: 0.0062 max mem: 33369 +Epoch: [32] [1280/1319] eta: 0:01:42 lr: 1.0454652912785337e-05 loss: 0.0362 (0.0351) time: 2.6302 data: 0.0060 max mem: 33369 +Epoch: [32] [1290/1319] eta: 0:01:16 lr: 1.0444503311582662e-05 loss: 0.0364 (0.0351) time: 2.6405 data: 0.0058 max mem: 33369 +Epoch: [32] [1300/1319] eta: 0:00:49 lr: 1.0434352614369702e-05 loss: 0.0353 (0.0351) time: 2.6386 data: 0.0061 max mem: 33369 +Epoch: [32] [1310/1319] eta: 0:00:23 lr: 1.0424200819843158e-05 loss: 0.0312 (0.0351) time: 2.6265 data: 0.0061 max mem: 33369 +Epoch: [32] Total time: 0:57:44 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 2:01:28 time: 2.8327 data: 2.7543 max mem: 33369 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 100/2573] eta: 0:04:04 time: 0.0712 data: 0.0011 max mem: 33369 +Test: [ 200/2573] eta: 0:03:25 time: 0.0730 data: 0.0011 max mem: 33369 +Test: [ 300/2573] eta: 0:03:05 time: 0.0747 data: 0.0011 max mem: 33369 +Test: [ 400/2573] eta: 0:02:52 time: 0.0749 data: 0.0011 max mem: 33369 +Test: [ 500/2573] eta: 0:02:42 time: 0.0732 data: 0.0011 max mem: 33369 +Test: [ 600/2573] eta: 0:02:32 time: 0.0734 data: 0.0011 max mem: 33369 +Test: [ 700/2573] eta: 0:02:24 time: 0.0735 data: 0.0011 max mem: 33369 +Test: [ 800/2573] eta: 0:02:16 time: 0.0767 data: 0.0011 max mem: 33369 +Test: [ 900/2573] eta: 0:02:08 time: 0.0734 data: 0.0011 max mem: 33369 +Test: [1000/2573] eta: 0:02:00 time: 0.0734 data: 0.0011 max mem: 33369 +Test: [1100/2573] eta: 0:01:52 time: 0.0735 data: 0.0011 max mem: 33369 +Test: [1200/2573] eta: 0:01:44 time: 0.0735 data: 0.0011 max mem: 33369 +Test: [1300/2573] eta: 0:01:36 time: 0.0736 data: 0.0011 max mem: 33369 +Test: [1400/2573] eta: 0:01:28 time: 0.0720 data: 0.0011 max mem: 33369 +Test: [1500/2573] eta: 0:01:20 time: 0.0735 data: 0.0011 max mem: 33369 +Test: [1600/2573] eta: 0:01:13 time: 0.0770 data: 0.0011 max mem: 33369 +Test: [1700/2573] eta: 0:01:05 time: 0.0721 data: 0.0011 max mem: 33369 +Test: [1800/2573] eta: 0:00:58 time: 0.0754 data: 0.0011 max mem: 33369 +Test: [1900/2573] eta: 0:00:50 time: 0.0721 data: 0.0011 max mem: 33369 +Test: [2000/2573] eta: 0:00:42 time: 0.0738 data: 0.0011 max mem: 33369 +Test: [2100/2573] eta: 0:00:35 time: 0.0754 data: 0.0011 max mem: 33369 +Test: [2200/2573] eta: 0:00:27 time: 0.0755 data: 0.0011 max mem: 33369 +Test: [2300/2573] eta: 0:00:20 time: 0.0755 data: 0.0011 max mem: 33369 +Test: [2400/2573] eta: 0:00:12 time: 0.0705 data: 0.0011 max mem: 33369 +Test: [2500/2573] eta: 0:00:05 time: 0.0738 data: 0.0011 max mem: 33369 +Test: Total time: 0:03:12 +Final results: +Mean IoU is 64.85 + + precision@0.5 = 72.79 + precision@0.6 = 67.63 + precision@0.7 = 60.99 + precision@0.8 = 49.73 + precision@0.9 = 24.96 + overall IoU = 62.13 + +Average object IoU 64.85406724762349 +Overall IoU 62.13340759277344 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [33] [ 0/1319] eta: 3:10:26 lr: 1.04150632654866e-05 loss: 0.0326 (0.0326) time: 8.6628 data: 1.4275 max mem: 33369 +Epoch: [33] [ 10/1319] eta: 1:08:17 lr: 1.0404909382463066e-05 loss: 0.0297 (0.0313) time: 3.1303 data: 0.1355 max mem: 33369 +Epoch: [33] [ 20/1319] eta: 1:02:11 lr: 1.0394754398329612e-05 loss: 0.0304 (0.0361) time: 2.5834 data: 0.0061 max mem: 33369 +Epoch: [33] [ 30/1319] eta: 1:00:22 lr: 1.0384598311771345e-05 loss: 0.0363 (0.0343) time: 2.6345 data: 0.0060 max mem: 33369 +Epoch: [33] [ 40/1319] eta: 0:59:09 lr: 1.0374441121470351e-05 loss: 0.0342 (0.0339) time: 2.6723 data: 0.0061 max mem: 33369 +Epoch: [33] [ 50/1319] eta: 0:58:04 lr: 1.0364282826105723e-05 loss: 0.0342 (0.0354) time: 2.6461 data: 0.0062 max mem: 33369 +Epoch: [33] [ 60/1319] eta: 0:57:08 lr: 1.0354123424353528e-05 loss: 0.0330 (0.0353) time: 2.6164 data: 0.0062 max mem: 33369 +Epoch: [33] [ 70/1319] eta: 0:56:24 lr: 1.0343962914886797e-05 loss: 0.0330 (0.0351) time: 2.6185 data: 0.0063 max mem: 33369 +Epoch: [33] [ 80/1319] eta: 0:55:42 lr: 1.033380129637553e-05 loss: 0.0350 (0.0350) time: 2.6210 data: 0.0064 max mem: 33369 +Epoch: [33] [ 90/1319] eta: 0:55:04 lr: 1.0323638567486653e-05 loss: 0.0354 (0.0355) time: 2.6113 data: 0.0063 max mem: 33369 +Epoch: [33] [ 100/1319] eta: 0:54:31 lr: 1.0313474726884054e-05 loss: 0.0323 (0.0360) time: 2.6252 data: 0.0063 max mem: 33369 +Epoch: [33] [ 110/1319] eta: 0:53:59 lr: 1.0303309773228537e-05 loss: 0.0300 (0.0355) time: 2.6372 data: 0.0065 max mem: 33369 +Epoch: [33] [ 120/1319] eta: 0:53:28 lr: 1.0293143705177821e-05 loss: 0.0300 (0.0356) time: 2.6395 data: 0.0064 max mem: 33369 +Epoch: [33] [ 130/1319] eta: 0:52:56 lr: 1.0282976521386539e-05 loss: 0.0323 (0.0358) time: 2.6285 data: 0.0062 max mem: 33369 +Epoch: [33] [ 140/1319] eta: 0:52:25 lr: 1.0272808220506222e-05 loss: 0.0323 (0.0355) time: 2.6154 data: 0.0063 max mem: 33369 +Epoch: [33] [ 150/1319] eta: 0:51:54 lr: 1.026263880118526e-05 loss: 0.0305 (0.0353) time: 2.6171 data: 0.0062 max mem: 33369 +Epoch: [33] [ 160/1319] eta: 0:51:27 lr: 1.0252468262068951e-05 loss: 0.0297 (0.0352) time: 2.6375 data: 0.0062 max mem: 33369 +Epoch: [33] [ 170/1319] eta: 0:50:59 lr: 1.024229660179944e-05 loss: 0.0314 (0.0353) time: 2.6551 data: 0.0062 max mem: 33369 +Epoch: [33] [ 180/1319] eta: 0:50:30 lr: 1.023212381901573e-05 loss: 0.0329 (0.0353) time: 2.6366 data: 0.0062 max mem: 33369 +Epoch: [33] [ 190/1319] eta: 0:50:01 lr: 1.0221949912353669e-05 loss: 0.0348 (0.0354) time: 2.6191 data: 0.0063 max mem: 33369 +Epoch: [33] [ 200/1319] eta: 0:49:32 lr: 1.0211774880445919e-05 loss: 0.0320 (0.0353) time: 2.6163 data: 0.0064 max mem: 33369 +Epoch: [33] [ 210/1319] eta: 0:49:03 lr: 1.0201598721921983e-05 loss: 0.0315 (0.0354) time: 2.6173 data: 0.0063 max mem: 33369 +Epoch: [33] [ 220/1319] eta: 0:48:36 lr: 1.0191421435408169e-05 loss: 0.0361 (0.0355) time: 2.6299 data: 0.0064 max mem: 33369 +Epoch: [33] [ 230/1319] eta: 0:48:06 lr: 1.0181243019527578e-05 loss: 0.0300 (0.0353) time: 2.6073 data: 0.0063 max mem: 33369 +Epoch: [33] [ 240/1319] eta: 0:47:38 lr: 1.0171063472900106e-05 loss: 0.0303 (0.0352) time: 2.5909 data: 0.0063 max mem: 33369 +Epoch: [33] [ 250/1319] eta: 0:47:10 lr: 1.0160882794142423e-05 loss: 0.0303 (0.0353) time: 2.6177 data: 0.0062 max mem: 33369 +Epoch: [33] [ 260/1319] eta: 0:46:41 lr: 1.0150700981867957e-05 loss: 0.0344 (0.0354) time: 2.5993 data: 0.0060 max mem: 33369 +Epoch: [33] [ 270/1319] eta: 0:46:13 lr: 1.01405180346869e-05 loss: 0.0320 (0.0353) time: 2.5945 data: 0.0060 max mem: 33369 +Epoch: [33] [ 280/1319] eta: 0:45:47 lr: 1.0130333951206182e-05 loss: 0.0297 (0.0353) time: 2.6303 data: 0.0062 max mem: 33369 +Epoch: [33] [ 290/1319] eta: 0:45:20 lr: 1.0120148730029472e-05 loss: 0.0284 (0.0351) time: 2.6378 data: 0.0061 max mem: 33369 +Epoch: [33] [ 300/1319] eta: 0:44:52 lr: 1.0109962369757157e-05 loss: 0.0284 (0.0352) time: 2.6183 data: 0.0060 max mem: 33369 +Epoch: [33] [ 310/1319] eta: 0:44:25 lr: 1.0099774868986322e-05 loss: 0.0326 (0.0352) time: 2.6223 data: 0.0061 max mem: 33369 +Epoch: [33] [ 320/1319] eta: 0:43:58 lr: 1.008958622631076e-05 loss: 0.0298 (0.0352) time: 2.6225 data: 0.0062 max mem: 33369 +Epoch: [33] [ 330/1319] eta: 0:43:30 lr: 1.0079396440320953e-05 loss: 0.0344 (0.0354) time: 2.5951 data: 0.0062 max mem: 33369 +Epoch: [33] [ 340/1319] eta: 0:43:03 lr: 1.0069205509604051e-05 loss: 0.0354 (0.0354) time: 2.6028 data: 0.0062 max mem: 33369 +Epoch: [33] [ 350/1319] eta: 0:42:35 lr: 1.0059013432743876e-05 loss: 0.0334 (0.0353) time: 2.6110 data: 0.0061 max mem: 33369 +Epoch: [33] [ 360/1319] eta: 0:42:08 lr: 1.0048820208320883e-05 loss: 0.0341 (0.0352) time: 2.6050 data: 0.0061 max mem: 33369 +Epoch: [33] [ 370/1319] eta: 0:41:42 lr: 1.0038625834912186e-05 loss: 0.0310 (0.0351) time: 2.6220 data: 0.0061 max mem: 33369 +Epoch: [33] [ 380/1319] eta: 0:41:17 lr: 1.0028430311091521e-05 loss: 0.0336 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9.946824533421325e-06 loss: 0.0360 (0.0351) time: 2.6299 data: 0.0060 max mem: 33369 +Epoch: [33] [ 470/1319] eta: 0:37:15 lr: 9.936618591148734e-06 loss: 0.0333 (0.0351) time: 2.6293 data: 0.0061 max mem: 33369 +Epoch: [33] [ 480/1319] eta: 0:36:48 lr: 9.92641148401344e-06 loss: 0.0327 (0.0352) time: 2.6191 data: 0.0061 max mem: 33369 +Epoch: [33] [ 490/1319] eta: 0:36:21 lr: 9.916203210551294e-06 loss: 0.0340 (0.0352) time: 2.6037 data: 0.0060 max mem: 33369 +Epoch: [33] [ 500/1319] eta: 0:35:54 lr: 9.905993769294629e-06 loss: 0.0310 (0.0351) time: 2.6047 data: 0.0060 max mem: 33369 +Epoch: [33] [ 510/1319] eta: 0:35:28 lr: 9.895783158772255e-06 loss: 0.0323 (0.0352) time: 2.6086 data: 0.0060 max mem: 33369 +Epoch: [33] [ 520/1319] eta: 0:35:01 lr: 9.885571377509421e-06 loss: 0.0363 (0.0352) time: 2.6077 data: 0.0060 max mem: 33369 +Epoch: [33] [ 530/1319] eta: 0:34:34 lr: 9.875358424027841e-06 loss: 0.0309 (0.0352) time: 2.5960 data: 0.0060 max mem: 33369 +Epoch: [33] [ 540/1319] eta: 0:34:08 lr: 9.865144296845656e-06 loss: 0.0309 (0.0351) time: 2.6205 data: 0.0060 max mem: 33369 +Epoch: [33] [ 550/1319] eta: 0:33:41 lr: 9.85492899447742e-06 loss: 0.0335 (0.0352) time: 2.6279 data: 0.0060 max mem: 33369 +Epoch: [33] [ 560/1319] eta: 0:33:14 lr: 9.844712515434104e-06 loss: 0.0292 (0.0351) time: 2.5949 data: 0.0060 max mem: 33369 +Epoch: [33] [ 570/1319] eta: 0:32:48 lr: 9.83449485822307e-06 loss: 0.0319 (0.0351) time: 2.5924 data: 0.0061 max mem: 33369 +Epoch: [33] [ 580/1319] eta: 0:32:21 lr: 9.824276021348049e-06 loss: 0.0325 (0.0350) time: 2.6038 data: 0.0061 max mem: 33369 +Epoch: [33] [ 590/1319] eta: 0:31:55 lr: 9.814056003309152e-06 loss: 0.0325 (0.0350) time: 2.6050 data: 0.0061 max mem: 33369 +Epoch: [33] [ 600/1319] eta: 0:31:29 lr: 9.803834802602848e-06 loss: 0.0294 (0.0350) time: 2.6281 data: 0.0060 max mem: 33369 +Epoch: [33] [ 610/1319] eta: 0:31:02 lr: 9.793612417721937e-06 loss: 0.0302 (0.0350) time: 2.6291 data: 0.0060 max mem: 33369 +Epoch: 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mem: 33369 +Epoch: [33] [ 700/1319] eta: 0:27:05 lr: 9.701557415421759e-06 loss: 0.0307 (0.0347) time: 2.6306 data: 0.0058 max mem: 33369 +Epoch: [33] [ 710/1319] eta: 0:26:39 lr: 9.69132310508487e-06 loss: 0.0343 (0.0347) time: 2.6286 data: 0.0061 max mem: 33369 +Epoch: [33] [ 720/1319] eta: 0:26:12 lr: 9.681087593749006e-06 loss: 0.0352 (0.0347) time: 2.6115 data: 0.0061 max mem: 33369 +Epoch: [33] [ 730/1319] eta: 0:25:46 lr: 9.670850879862032e-06 loss: 0.0339 (0.0347) time: 2.6226 data: 0.0060 max mem: 33369 +Epoch: [33] [ 740/1319] eta: 0:25:20 lr: 9.660612961867972e-06 loss: 0.0317 (0.0347) time: 2.6360 data: 0.0061 max mem: 33369 +Epoch: [33] [ 750/1319] eta: 0:24:53 lr: 9.650373838207014e-06 loss: 0.0317 (0.0347) time: 2.6218 data: 0.0060 max mem: 33369 +Epoch: [33] [ 760/1319] eta: 0:24:27 lr: 9.640133507315477e-06 loss: 0.0320 (0.0346) time: 2.6149 data: 0.0059 max mem: 33369 +Epoch: [33] [ 770/1319] eta: 0:24:01 lr: 9.62989196762581e-06 loss: 0.0312 (0.0346) time: 2.6302 data: 0.0059 max mem: 33369 +Epoch: [33] [ 780/1319] eta: 0:23:35 lr: 9.61964921756657e-06 loss: 0.0308 (0.0346) time: 2.6244 data: 0.0059 max mem: 33369 +Epoch: [33] [ 790/1319] eta: 0:23:09 lr: 9.609405255562397e-06 loss: 0.0301 (0.0345) time: 2.6368 data: 0.0061 max mem: 33369 +Epoch: [33] [ 800/1319] eta: 0:22:43 lr: 9.599160080034027e-06 loss: 0.0301 (0.0345) time: 2.6592 data: 0.0060 max mem: 33369 +Epoch: [33] [ 810/1319] eta: 0:22:16 lr: 9.588913689398257e-06 loss: 0.0323 (0.0345) time: 2.6495 data: 0.0059 max mem: 33369 +Epoch: [33] [ 820/1319] eta: 0:21:50 lr: 9.578666082067937e-06 loss: 0.0318 (0.0344) time: 2.6324 data: 0.0059 max mem: 33369 +Epoch: [33] [ 830/1319] eta: 0:21:24 lr: 9.568417256451955e-06 loss: 0.0318 (0.0344) time: 2.6256 data: 0.0060 max mem: 33369 +Epoch: [33] [ 840/1319] eta: 0:20:58 lr: 9.558167210955227e-06 loss: 0.0334 (0.0345) time: 2.6393 data: 0.0060 max mem: 33369 +Epoch: [33] [ 850/1319] eta: 0:20:31 lr: 9.547915943978656e-06 loss: 0.0364 (0.0345) time: 2.6054 data: 0.0060 max mem: 33369 +Epoch: [33] [ 860/1319] eta: 0:20:05 lr: 9.537663453919165e-06 loss: 0.0384 (0.0345) time: 2.6217 data: 0.0060 max mem: 33369 +Epoch: [33] [ 870/1319] eta: 0:19:39 lr: 9.52740973916964e-06 loss: 0.0308 (0.0345) time: 2.6460 data: 0.0059 max mem: 33369 +Epoch: [33] [ 880/1319] eta: 0:19:13 lr: 9.517154798118936e-06 loss: 0.0283 (0.0344) time: 2.6440 data: 0.0060 max mem: 33369 +Epoch: [33] [ 890/1319] eta: 0:18:47 lr: 9.506898629151863e-06 loss: 0.0310 (0.0345) time: 2.6639 data: 0.0062 max mem: 33369 +Epoch: [33] [ 900/1319] eta: 0:18:20 lr: 9.496641230649144e-06 loss: 0.0333 (0.0344) time: 2.6478 data: 0.0062 max mem: 33369 +Epoch: [33] [ 910/1319] eta: 0:17:54 lr: 9.48638260098744e-06 loss: 0.0300 (0.0344) time: 2.6213 data: 0.0062 max mem: 33369 +Epoch: [33] [ 920/1319] eta: 0:17:28 lr: 9.476122738539313e-06 loss: 0.0302 (0.0344) time: 2.6233 data: 0.0060 max mem: 33369 +Epoch: [33] [ 930/1319] eta: 0:17:02 lr: 9.465861641673206e-06 loss: 0.0302 (0.0343) time: 2.6397 data: 0.0059 max mem: 33369 +Epoch: [33] [ 940/1319] eta: 0:16:35 lr: 9.455599308753445e-06 loss: 0.0312 (0.0343) time: 2.6222 data: 0.0059 max mem: 33369 +Epoch: [33] [ 950/1319] eta: 0:16:09 lr: 9.445335738140192e-06 loss: 0.0337 (0.0343) time: 2.6302 data: 0.0059 max mem: 33369 +Epoch: [33] [ 960/1319] eta: 0:15:43 lr: 9.435070928189476e-06 loss: 0.0306 (0.0343) time: 2.6435 data: 0.0059 max mem: 33369 +Epoch: [33] [ 970/1319] eta: 0:15:17 lr: 9.424804877253139e-06 loss: 0.0306 (0.0343) time: 2.6321 data: 0.0060 max mem: 33369 +Epoch: [33] [ 980/1319] eta: 0:14:50 lr: 9.414537583678836e-06 loss: 0.0324 (0.0343) time: 2.6117 data: 0.0059 max mem: 33369 +Epoch: [33] [ 990/1319] eta: 0:14:24 lr: 9.404269045810016e-06 loss: 0.0335 (0.0344) time: 2.6166 data: 0.0059 max mem: 33369 +Epoch: [33] [1000/1319] eta: 0:13:58 lr: 9.393999261985916e-06 loss: 0.0342 (0.0345) time: 2.6199 data: 0.0061 max mem: 33369 +Epoch: [33] [1010/1319] eta: 0:13:31 lr: 9.383728230541512e-06 loss: 0.0326 (0.0345) time: 2.6049 data: 0.0060 max mem: 33369 +Epoch: [33] [1020/1319] eta: 0:13:05 lr: 9.373455949807552e-06 loss: 0.0323 (0.0345) time: 2.6087 data: 0.0059 max mem: 33369 +Epoch: [33] [1030/1319] eta: 0:12:39 lr: 9.363182418110507e-06 loss: 0.0304 (0.0344) time: 2.6024 data: 0.0060 max mem: 33369 +Epoch: [33] [1040/1319] eta: 0:12:12 lr: 9.352907633772557e-06 loss: 0.0288 (0.0344) time: 2.6009 data: 0.0060 max mem: 33369 +Epoch: [33] [1050/1319] eta: 0:11:46 lr: 9.342631595111597e-06 loss: 0.0325 (0.0344) time: 2.5961 data: 0.0060 max mem: 33369 +Epoch: [33] [1060/1319] eta: 0:11:19 lr: 9.332354300441178e-06 loss: 0.0366 (0.0345) time: 2.5754 data: 0.0061 max mem: 33369 +Epoch: [33] [1070/1319] eta: 0:10:53 lr: 9.322075748070539e-06 loss: 0.0303 (0.0345) time: 2.5723 data: 0.0061 max mem: 33369 +Epoch: [33] [1080/1319] eta: 0:10:27 lr: 9.311795936304561e-06 loss: 0.0303 (0.0345) time: 2.5868 data: 0.0060 max mem: 33369 +Epoch: [33] [1090/1319] eta: 0:10:00 lr: 9.301514863443759e-06 loss: 0.0333 (0.0345) time: 2.5933 data: 0.0061 max mem: 33369 +Epoch: [33] [1100/1319] eta: 0:09:34 lr: 9.291232527784269e-06 loss: 0.0360 (0.0345) time: 2.6324 data: 0.0062 max mem: 33369 +Epoch: [33] [1110/1319] eta: 0:09:08 lr: 9.280948927617811e-06 loss: 0.0360 (0.0345) time: 2.6291 data: 0.0060 max mem: 33369 +Epoch: [33] [1120/1319] eta: 0:08:42 lr: 9.270664061231702e-06 loss: 0.0318 (0.0346) time: 2.5889 data: 0.0059 max mem: 33369 +Epoch: [33] [1130/1319] eta: 0:08:16 lr: 9.260377926908826e-06 loss: 0.0337 (0.0346) time: 2.6286 data: 0.0060 max mem: 33369 +Epoch: [33] [1140/1319] eta: 0:07:49 lr: 9.250090522927605e-06 loss: 0.0331 (0.0346) time: 2.6458 data: 0.0060 max mem: 33369 +Epoch: [33] [1150/1319] eta: 0:07:23 lr: 9.239801847562006e-06 loss: 0.0324 (0.0346) time: 2.6322 data: 0.0059 max mem: 33369 +Epoch: [33] [1160/1319] eta: 0:06:57 lr: 9.229511899081506e-06 loss: 0.0318 (0.0346) time: 2.6273 data: 0.0058 max mem: 33369 +Epoch: [33] [1170/1319] eta: 0:06:31 lr: 9.219220675751069e-06 loss: 0.0311 (0.0346) time: 2.6177 data: 0.0060 max mem: 33369 +Epoch: [33] [1180/1319] eta: 0:06:04 lr: 9.20892817583115e-06 loss: 0.0322 (0.0347) time: 2.6317 data: 0.0059 max mem: 33369 +Epoch: [33] [1190/1319] eta: 0:05:38 lr: 9.19863439757767e-06 loss: 0.0342 (0.0347) time: 2.6287 data: 0.0059 max mem: 33369 +Epoch: [33] [1200/1319] eta: 0:05:12 lr: 9.188339339241987e-06 loss: 0.0288 (0.0347) time: 2.6340 data: 0.0060 max mem: 33369 +Epoch: [33] [1210/1319] eta: 0:04:46 lr: 9.178042999070898e-06 loss: 0.0302 (0.0347) time: 2.6390 data: 0.0061 max mem: 33369 +Epoch: [33] [1220/1319] eta: 0:04:19 lr: 9.16774537530659e-06 loss: 0.0339 (0.0347) time: 2.6007 data: 0.0060 max mem: 33369 +Epoch: [33] [1230/1319] eta: 0:03:53 lr: 9.157446466186662e-06 loss: 0.0344 (0.0347) time: 2.5928 data: 0.0059 max mem: 33369 +Epoch: [33] [1240/1319] eta: 0:03:27 lr: 9.147146269944078e-06 loss: 0.0304 (0.0347) time: 2.6225 data: 0.0060 max mem: 33369 +Epoch: [33] [1250/1319] eta: 0:03:01 lr: 9.136844784807162e-06 loss: 0.0299 (0.0347) time: 2.6214 data: 0.0060 max mem: 33369 +Epoch: [33] [1260/1319] eta: 0:02:34 lr: 9.126542008999582e-06 loss: 0.0340 (0.0347) time: 2.6090 data: 0.0060 max mem: 33369 +Epoch: [33] [1270/1319] eta: 0:02:08 lr: 9.11623794074031e-06 loss: 0.0350 (0.0347) time: 2.6495 data: 0.0059 max mem: 33369 +Epoch: [33] [1280/1319] eta: 0:01:42 lr: 9.105932578243631e-06 loss: 0.0316 (0.0347) time: 2.6514 data: 0.0058 max mem: 33369 +Epoch: [33] [1290/1319] eta: 0:01:16 lr: 9.095625919719118e-06 loss: 0.0335 (0.0348) time: 2.6422 data: 0.0058 max mem: 33369 +Epoch: [33] [1300/1319] eta: 0:00:49 lr: 9.085317963371604e-06 loss: 0.0383 (0.0348) time: 2.6654 data: 0.0060 max mem: 33369 +Epoch: [33] [1310/1319] eta: 0:00:23 lr: 9.075008707401167e-06 loss: 0.0329 (0.0348) time: 2.6712 data: 0.0060 max mem: 33369 +Epoch: [33] Total time: 0:57:43 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 1:50:49 time: 2.5844 data: 2.4044 max mem: 33369 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 100/2573] eta: 0:04:02 time: 0.0721 data: 0.0011 max mem: 33369 +Test: [ 200/2573] eta: 0:03:24 time: 0.0734 data: 0.0011 max mem: 33369 +Test: [ 300/2573] eta: 0:03:05 time: 0.0751 data: 0.0011 max mem: 33369 +Test: [ 400/2573] eta: 0:02:52 time: 0.0751 data: 0.0011 max mem: 33369 +Test: [ 500/2573] eta: 0:02:42 time: 0.0737 data: 0.0011 max mem: 33369 +Test: [ 600/2573] eta: 0:02:33 time: 0.0737 data: 0.0011 max mem: 33369 +Test: [ 700/2573] eta: 0:02:25 time: 0.0738 data: 0.0011 max mem: 33369 +Test: [ 800/2573] eta: 0:02:16 time: 0.0773 data: 0.0011 max mem: 33369 +Test: [ 900/2573] eta: 0:02:08 time: 0.0739 data: 0.0011 max mem: 33369 +Test: [1000/2573] eta: 0:02:00 time: 0.0740 data: 0.0011 max mem: 33369 +Test: [1100/2573] eta: 0:01:52 time: 0.0739 data: 0.0011 max mem: 33369 +Test: [1200/2573] eta: 0:01:44 time: 0.0740 data: 0.0011 max mem: 33369 +Test: [1300/2573] eta: 0:01:36 time: 0.0740 data: 0.0011 max mem: 33369 +Test: [1400/2573] eta: 0:01:28 time: 0.0725 data: 0.0011 max mem: 33369 +Test: [1500/2573] eta: 0:01:21 time: 0.0742 data: 0.0011 max mem: 33369 +Test: [1600/2573] eta: 0:01:13 time: 0.0776 data: 0.0011 max mem: 33369 +Test: [1700/2573] eta: 0:01:06 time: 0.0726 data: 0.0011 max mem: 33369 +Test: [1800/2573] eta: 0:00:58 time: 0.0759 data: 0.0011 max mem: 33369 +Test: [1900/2573] eta: 0:00:50 time: 0.0726 data: 0.0011 max mem: 33369 +Test: [2000/2573] eta: 0:00:43 time: 0.0742 data: 0.0011 max mem: 33369 +Test: [2100/2573] eta: 0:00:35 time: 0.0759 data: 0.0011 max mem: 33369 +Test: [2200/2573] eta: 0:00:28 time: 0.0758 data: 0.0011 max mem: 33369 +Test: [2300/2573] eta: 0:00:20 time: 0.0759 data: 0.0011 max mem: 33369 +Test: [2400/2573] eta: 0:00:12 time: 0.0709 data: 0.0011 max mem: 33369 +Test: [2500/2573] eta: 0:00:05 time: 0.0743 data: 0.0011 max mem: 33369 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: Total time: 0:03:13 +Final results: +Mean IoU is 65.17 + + precision@0.5 = 73.08 + precision@0.6 = 68.28 + precision@0.7 = 61.87 + precision@0.8 = 50.65 + precision@0.9 = 26.04 + overall IoU = 62.64 + +Average object IoU 65.17143386820229 +Overall IoU 62.63993835449219 +Better epoch: 33 + +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [34] [ 0/1319] eta: 1:34:04 lr: 9.065729264358701e-06 loss: 0.0248 (0.0248) time: 4.2793 data: 1.6130 max mem: 33369 +Epoch: [34] [ 10/1319] eta: 1:00:01 lr: 9.05541753412883e-06 loss: 0.0326 (0.0318) time: 2.7514 data: 0.1524 max mem: 33369 +Epoch: [34] [ 20/1319] eta: 0:57:40 lr: 9.045104499029229e-06 loss: 0.0354 (0.0391) time: 2.5833 data: 0.0059 max mem: 33369 +Epoch: [34] [ 30/1319] eta: 0:57:11 lr: 9.03479015724125e-06 loss: 0.0333 (0.0372) time: 2.6129 data: 0.0059 max mem: 33369 +Epoch: [34] [ 40/1319] eta: 0:56:27 lr: 9.024474506941415e-06 loss: 0.0292 (0.0353) time: 2.6320 data: 0.0062 max mem: 33369 +Epoch: [34] [ 50/1319] eta: 0:55:46 lr: 9.014157546301385e-06 loss: 0.0286 (0.0354) time: 2.5975 data: 0.0062 max mem: 33369 +Epoch: [34] [ 60/1319] eta: 0:55:21 lr: 9.003839273487931e-06 loss: 0.0301 (0.0350) time: 2.6185 data: 0.0062 max mem: 33369 +Epoch: [34] [ 70/1319] eta: 0:54:51 lr: 8.99351968666293e-06 loss: 0.0301 (0.0342) time: 2.6325 data: 0.0063 max mem: 33369 +Epoch: [34] [ 80/1319] eta: 0:54:23 lr: 8.983198783983315e-06 loss: 0.0344 (0.0345) time: 2.6206 data: 0.0064 max mem: 33369 +Epoch: [34] [ 90/1319] eta: 0:53:50 lr: 8.972876563601101e-06 loss: 0.0354 (0.0342) time: 2.6041 data: 0.0063 max mem: 33369 +Epoch: [34] [ 100/1319] eta: 0:53:24 lr: 8.962553023663333e-06 loss: 0.0334 (0.0347) time: 2.6068 data: 0.0061 max mem: 33369 +Epoch: [34] [ 110/1319] eta: 0:52:56 lr: 8.952228162312077e-06 loss: 0.0301 (0.0341) time: 2.6199 data: 0.0060 max mem: 33369 +Epoch: [34] [ 120/1319] eta: 0:52:26 lr: 8.941901977684397e-06 loss: 0.0312 (0.0342) time: 2.6034 data: 0.0061 max mem: 33369 +Epoch: [34] [ 130/1319] eta: 0:51:59 lr: 8.93157446791234e-06 loss: 0.0349 (0.0343) time: 2.6032 data: 0.0062 max mem: 33369 +Epoch: [34] [ 140/1319] eta: 0:51:33 lr: 8.9212456311229e-06 loss: 0.0326 (0.0343) time: 2.6215 data: 0.0063 max mem: 33369 +Epoch: [34] [ 150/1319] eta: 0:51:09 lr: 8.910915465438025e-06 loss: 0.0341 (0.0345) time: 2.6408 data: 0.0063 max mem: 33369 +Epoch: [34] [ 160/1319] eta: 0:50:43 lr: 8.900583968974578e-06 loss: 0.0325 (0.0344) time: 2.6362 data: 0.0062 max mem: 33369 +Epoch: [34] [ 170/1319] eta: 0:50:16 lr: 8.89025113984432e-06 loss: 0.0312 (0.0344) time: 2.6205 data: 0.0062 max mem: 33369 +Epoch: [34] [ 180/1319] eta: 0:49:50 lr: 8.879916976153894e-06 loss: 0.0305 (0.0344) time: 2.6242 data: 0.0061 max mem: 33369 +Epoch: [34] [ 190/1319] eta: 0:49:23 lr: 8.869581476004788e-06 loss: 0.0298 (0.0342) time: 2.6256 data: 0.0061 max mem: 33369 +Epoch: [34] [ 200/1319] eta: 0:48:56 lr: 8.859244637493344e-06 loss: 0.0301 (0.0340) time: 2.6087 data: 0.0062 max mem: 33369 +Epoch: [34] [ 210/1319] eta: 0:48:30 lr: 8.84890645871071e-06 loss: 0.0304 (0.0341) time: 2.6135 data: 0.0065 max mem: 33369 +Epoch: [34] [ 220/1319] eta: 0:48:04 lr: 8.838566937742836e-06 loss: 0.0365 (0.0344) time: 2.6312 data: 0.0063 max mem: 33369 +Epoch: [34] [ 230/1319] eta: 0:47:35 lr: 8.828226072670449e-06 loss: 0.0347 (0.0350) time: 2.6008 data: 0.0061 max mem: 33369 +Epoch: [34] [ 240/1319] eta: 0:47:09 lr: 8.817883861569014e-06 loss: 0.0334 (0.0350) time: 2.5961 data: 0.0061 max mem: 33369 +Epoch: [34] [ 250/1319] eta: 0:46:44 lr: 8.807540302508743e-06 loss: 0.0363 (0.0355) time: 2.6378 data: 0.0061 max mem: 33369 +Epoch: [34] [ 260/1319] eta: 0:46:17 lr: 8.797195393554557e-06 loss: 0.0321 (0.0354) time: 2.6327 data: 0.0061 max mem: 33369 +Epoch: [34] [ 270/1319] eta: 0:45:51 lr: 8.786849132766063e-06 loss: 0.0292 (0.0351) time: 2.6177 data: 0.0060 max mem: 33369 +Epoch: [34] [ 280/1319] eta: 0:45:24 lr: 8.776501518197541e-06 loss: 0.0274 (0.0350) time: 2.6084 data: 0.0060 max mem: 33369 +Epoch: [34] [ 290/1319] eta: 0:44:56 lr: 8.76615254789792e-06 loss: 0.0305 (0.0351) time: 2.5864 data: 0.0063 max mem: 33369 +Epoch: [34] [ 300/1319] eta: 0:44:29 lr: 8.755802219910735e-06 loss: 0.0312 (0.0352) time: 2.5882 data: 0.0062 max mem: 33369 +Epoch: [34] [ 310/1319] eta: 0:44:02 lr: 8.745450532274145e-06 loss: 0.0299 (0.0350) time: 2.5914 data: 0.0060 max mem: 33369 +Epoch: [34] [ 320/1319] eta: 0:43:34 lr: 8.735097483020883e-06 loss: 0.0331 (0.0351) time: 2.5842 data: 0.0061 max mem: 33369 +Epoch: [34] [ 330/1319] eta: 0:43:09 lr: 8.724743070178239e-06 loss: 0.0342 (0.0351) time: 2.6176 data: 0.0062 max mem: 33369 +Epoch: [34] [ 340/1319] eta: 0:42:42 lr: 8.714387291768046e-06 loss: 0.0332 (0.0350) time: 2.6265 data: 0.0061 max mem: 33369 +Epoch: [34] [ 350/1319] eta: 0:42:15 lr: 8.704030145806636e-06 loss: 0.0303 (0.0349) time: 2.5869 data: 0.0061 max mem: 33369 +Epoch: [34] [ 360/1319] eta: 0:41:49 lr: 8.693671630304845e-06 loss: 0.0311 (0.0349) time: 2.5945 data: 0.0061 max mem: 33369 +Epoch: [34] [ 370/1319] eta: 0:41:23 lr: 8.683311743267978e-06 loss: 0.0326 (0.0349) time: 2.6254 data: 0.0061 max mem: 33369 +Epoch: [34] [ 380/1319] eta: 0:40:58 lr: 8.672950482695785e-06 loss: 0.0315 (0.0347) time: 2.6411 data: 0.0059 max 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0:27:00 lr: 8.340652648571916e-06 loss: 0.0342 (0.0348) time: 2.6095 data: 0.0061 max mem: 33369 +Epoch: [34] [ 710/1319] eta: 0:26:33 lr: 8.330244901449094e-06 loss: 0.0362 (0.0349) time: 2.6213 data: 0.0059 max mem: 33369 +Epoch: [34] [ 720/1319] eta: 0:26:07 lr: 8.319835709307101e-06 loss: 0.0348 (0.0350) time: 2.6010 data: 0.0059 max mem: 33369 +Epoch: [34] [ 730/1319] eta: 0:25:41 lr: 8.309425069935955e-06 loss: 0.0348 (0.0350) time: 2.6062 data: 0.0059 max mem: 33369 +Epoch: [34] [ 740/1319] eta: 0:25:15 lr: 8.299012981119228e-06 loss: 0.0271 (0.0349) time: 2.6261 data: 0.0058 max mem: 33369 +Epoch: [34] [ 750/1319] eta: 0:24:49 lr: 8.288599440633996e-06 loss: 0.0258 (0.0348) time: 2.6313 data: 0.0058 max mem: 33369 +Epoch: [34] [ 760/1319] eta: 0:24:22 lr: 8.278184446250822e-06 loss: 0.0288 (0.0348) time: 2.6183 data: 0.0059 max mem: 33369 +Epoch: [34] [ 770/1319] eta: 0:23:57 lr: 8.267767995733725e-06 loss: 0.0329 (0.0348) time: 2.6316 data: 0.0058 max mem: 33369 +Epoch: [34] [ 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+Epoch: [34] [ 860/1319] eta: 0:20:01 lr: 8.173954042838362e-06 loss: 0.0304 (0.0346) time: 2.6215 data: 0.0059 max mem: 33369 +Epoch: [34] [ 870/1319] eta: 0:19:35 lr: 8.163522906542168e-06 loss: 0.0304 (0.0345) time: 2.5977 data: 0.0058 max mem: 33369 +Epoch: [34] [ 880/1319] eta: 0:19:09 lr: 8.153090289075947e-06 loss: 0.0320 (0.0345) time: 2.6079 data: 0.0059 max mem: 33369 +Epoch: [34] [ 890/1319] eta: 0:18:43 lr: 8.142656188122887e-06 loss: 0.0320 (0.0345) time: 2.6501 data: 0.0059 max mem: 33369 +Epoch: [34] [ 900/1319] eta: 0:18:17 lr: 8.132220601359272e-06 loss: 0.0320 (0.0345) time: 2.6488 data: 0.0059 max mem: 33369 +Epoch: [34] [ 910/1319] eta: 0:17:50 lr: 8.121783526454415e-06 loss: 0.0289 (0.0345) time: 2.6120 data: 0.0059 max mem: 33369 +Epoch: [34] [ 920/1319] eta: 0:17:24 lr: 8.111344961070641e-06 loss: 0.0289 (0.0344) time: 2.6102 data: 0.0059 max mem: 33369 +Epoch: [34] [ 930/1319] eta: 0:16:58 lr: 8.100904902863262e-06 loss: 0.0315 (0.0344) time: 2.6281 data: 0.0062 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2.6366 data: 0.0060 max mem: 33369 +Epoch: [34] [1020/1319] eta: 0:13:03 lr: 8.006876811544029e-06 loss: 0.0276 (0.0343) time: 2.6462 data: 0.0058 max mem: 33369 +Epoch: [34] [1030/1319] eta: 0:12:37 lr: 7.996421694575264e-06 loss: 0.0311 (0.0343) time: 2.6714 data: 0.0057 max mem: 33369 +Epoch: [34] [1040/1319] eta: 0:12:11 lr: 7.985965058518847e-06 loss: 0.0311 (0.0343) time: 2.6535 data: 0.0057 max mem: 33369 +Epoch: [34] [1050/1319] eta: 0:11:44 lr: 7.97550690094334e-06 loss: 0.0337 (0.0343) time: 2.6307 data: 0.0057 max mem: 33369 +Epoch: [34] [1060/1319] eta: 0:11:18 lr: 7.965047219409881e-06 loss: 0.0336 (0.0344) time: 2.6201 data: 0.0058 max mem: 33369 +Epoch: [34] [1070/1319] eta: 0:10:52 lr: 7.95458601147213e-06 loss: 0.0336 (0.0343) time: 2.6354 data: 0.0060 max mem: 33369 +Epoch: [34] [1080/1319] eta: 0:10:26 lr: 7.944123274676236e-06 loss: 0.0290 (0.0343) time: 2.6544 data: 0.0059 max mem: 33369 +Epoch: [34] [1090/1319] eta: 0:10:00 lr: 7.933659006560817e-06 loss: 0.0309 (0.0344) time: 2.6697 data: 0.0059 max mem: 33369 +Epoch: [34] [1100/1319] eta: 0:09:34 lr: 7.923193204656895e-06 loss: 0.0307 (0.0343) time: 2.6482 data: 0.0061 max mem: 33369 +Epoch: [34] [1110/1319] eta: 0:09:07 lr: 7.912725866487896e-06 loss: 0.0278 (0.0343) time: 2.6126 data: 0.0061 max mem: 33369 +Epoch: [34] [1120/1319] eta: 0:08:41 lr: 7.902256989569599e-06 loss: 0.0287 (0.0343) time: 2.6223 data: 0.0058 max mem: 33369 +Epoch: [34] [1130/1319] eta: 0:08:15 lr: 7.891786571410098e-06 loss: 0.0322 (0.0343) time: 2.6329 data: 0.0059 max mem: 33369 +Epoch: [34] [1140/1319] eta: 0:07:49 lr: 7.881314609509776e-06 loss: 0.0316 (0.0343) time: 2.6183 data: 0.0060 max mem: 33369 +Epoch: [34] [1150/1319] eta: 0:07:22 lr: 7.870841101361268e-06 loss: 0.0282 (0.0343) time: 2.6044 data: 0.0060 max mem: 33369 +Epoch: [34] [1160/1319] eta: 0:06:56 lr: 7.860366044449406e-06 loss: 0.0327 (0.0343) time: 2.6152 data: 0.0059 max mem: 33369 +Epoch: [34] [1170/1319] eta: 0:06:30 lr: 7.849889436251218e-06 loss: 0.0321 (0.0343) time: 2.6306 data: 0.0060 max mem: 33369 +Epoch: [34] [1180/1319] eta: 0:06:04 lr: 7.839411274235871e-06 loss: 0.0321 (0.0344) time: 2.6224 data: 0.0061 max mem: 33369 +Epoch: [34] [1190/1319] eta: 0:05:38 lr: 7.82893155586463e-06 loss: 0.0348 (0.0344) time: 2.6277 data: 0.0059 max mem: 33369 +Epoch: [34] [1200/1319] eta: 0:05:11 lr: 7.818450278590844e-06 loss: 0.0335 (0.0344) time: 2.6170 data: 0.0058 max mem: 33369 +Epoch: [34] [1210/1319] eta: 0:04:45 lr: 7.80796743985987e-06 loss: 0.0327 (0.0344) time: 2.6378 data: 0.0059 max mem: 33369 +Epoch: [34] [1220/1319] eta: 0:04:19 lr: 7.797483037109084e-06 loss: 0.0313 (0.0344) time: 2.6531 data: 0.0058 max mem: 33369 +Epoch: [34] [1230/1319] eta: 0:03:53 lr: 7.786997067767811e-06 loss: 0.0314 (0.0344) time: 2.6450 data: 0.0058 max mem: 33369 +Epoch: [34] [1240/1319] eta: 0:03:27 lr: 7.776509529257303e-06 loss: 0.0325 (0.0343) time: 2.6445 data: 0.0058 max mem: 33369 +Epoch: [34] [1250/1319] eta: 0:03:00 lr: 7.766020418990693e-06 loss: 0.0325 (0.0343) time: 2.5955 data: 0.0061 max mem: 33369 +Epoch: [34] [1260/1319] eta: 0:02:34 lr: 7.755529734372952e-06 loss: 0.0309 (0.0343) time: 2.5982 data: 0.0061 max mem: 33369 +Epoch: [34] [1270/1319] eta: 0:02:08 lr: 7.74503747280087e-06 loss: 0.0280 (0.0343) time: 2.6085 data: 0.0058 max mem: 33369 +Epoch: [34] [1280/1319] eta: 0:01:42 lr: 7.734543631663006e-06 loss: 0.0283 (0.0343) time: 2.6212 data: 0.0057 max mem: 33369 +Epoch: [34] [1290/1319] eta: 0:01:16 lr: 7.724048208339646e-06 loss: 0.0300 (0.0343) time: 2.6461 data: 0.0059 max mem: 33369 +Epoch: [34] [1300/1319] eta: 0:00:49 lr: 7.713551200202774e-06 loss: 0.0311 (0.0343) time: 2.6231 data: 0.0059 max mem: 33369 +Epoch: [34] [1310/1319] eta: 0:00:23 lr: 7.703052604616029e-06 loss: 0.0316 (0.0343) time: 2.6401 data: 0.0057 max mem: 33369 +Epoch: [34] Total time: 0:57:38 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 2:18:35 time: 3.2318 data: 3.1528 max mem: 33369 +Test: [ 100/2573] eta: 0:04:15 time: 0.0717 data: 0.0011 max mem: 33369 +Test: [ 200/2573] eta: 0:03:30 time: 0.0730 data: 0.0011 max mem: 33369 +Test: [ 300/2573] eta: 0:03:08 time: 0.0746 data: 0.0011 max mem: 33369 +Test: [ 400/2573] eta: 0:02:54 time: 0.0747 data: 0.0011 max mem: 33369 +Test: [ 500/2573] eta: 0:02:43 time: 0.0733 data: 0.0011 max mem: 33369 +Test: [ 600/2573] eta: 0:02:34 time: 0.0733 data: 0.0011 max mem: 33369 +Test: [ 700/2573] eta: 0:02:25 time: 0.0733 data: 0.0011 max mem: 33369 +Test: [ 800/2573] eta: 0:02:17 time: 0.0767 data: 0.0011 max mem: 33369 +Test: [ 900/2573] eta: 0:02:08 time: 0.0733 data: 0.0011 max mem: 33369 +Test: [1000/2573] eta: 0:02:00 time: 0.0736 data: 0.0011 max mem: 33369 +Test: [1100/2573] eta: 0:01:52 time: 0.0735 data: 0.0011 max mem: 33369 +Test: [1200/2573] eta: 0:01:44 time: 0.0735 data: 0.0011 max mem: 33369 +Test: [1300/2573] eta: 0:01:36 time: 0.0735 data: 0.0011 max mem: 33369 +Test: [1400/2573] eta: 0:01:28 time: 0.0721 data: 0.0011 max mem: 33369 +Test: [1500/2573] eta: 0:01:21 time: 0.0737 data: 0.0011 max mem: 33369 +Test: [1600/2573] eta: 0:01:13 time: 0.0770 data: 0.0011 max mem: 33369 +Test: [1700/2573] eta: 0:01:05 time: 0.0721 data: 0.0011 max mem: 33369 +Test: [1800/2573] eta: 0:00:58 time: 0.0754 data: 0.0011 max mem: 33369 +Test: [1900/2573] eta: 0:00:50 time: 0.0722 data: 0.0011 max mem: 33369 +Test: [2000/2573] eta: 0:00:43 time: 0.0738 data: 0.0011 max mem: 33369 +Test: [2100/2573] eta: 0:00:35 time: 0.0755 data: 0.0011 max mem: 33369 +Test: [2200/2573] eta: 0:00:27 time: 0.0756 data: 0.0011 max mem: 33369 +Test: [2300/2573] eta: 0:00:20 time: 0.0755 data: 0.0011 max mem: 33369 +Test: [2400/2573] eta: 0:00:12 time: 0.0703 data: 0.0011 max mem: 33369 +Test: [2500/2573] eta: 0:00:05 time: 0.0737 data: 0.0011 max mem: 33369 +Test: Total time: 0:03:12 +Final results: +Mean IoU is 64.96 + + precision@0.5 = 72.88 + precision@0.6 = 68.08 + precision@0.7 = 61.79 + precision@0.8 = 51.04 + precision@0.9 = 26.08 + overall IoU = 62.34 + +Average object IoU 64.95688955130083 +Overall IoU 62.341983795166016 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [35] [ 0/1319] eta: 3:06:42 lr: 7.693602509132593e-06 loss: 0.0418 (0.0418) time: 8.4932 data: 1.4699 max mem: 33369 +Epoch: [35] [ 10/1319] eta: 1:09:05 lr: 7.683100890097833e-06 loss: 0.0323 (0.0315) time: 3.1666 data: 0.1390 max mem: 33369 +Epoch: [35] [ 20/1319] eta: 1:03:13 lr: 7.67259767592017e-06 loss: 0.0298 (0.0317) time: 2.6415 data: 0.0058 max mem: 33369 +Epoch: [35] [ 30/1319] eta: 1:00:28 lr: 7.66209286393032e-06 loss: 0.0305 (0.0331) time: 2.6220 data: 0.0060 max mem: 33369 +Epoch: [35] [ 40/1319] eta: 0:59:07 lr: 7.651586451450453e-06 loss: 0.0318 (0.0329) time: 2.6200 data: 0.0062 max mem: 33369 +Epoch: [35] [ 50/1319] eta: 0:58:03 lr: 7.641078435794154e-06 loss: 0.0313 (0.0327) time: 2.6362 data: 0.0061 max mem: 33369 +Epoch: [35] [ 60/1319] eta: 0:57:20 lr: 7.630568814266394e-06 loss: 0.0313 (0.0326) time: 2.6485 data: 0.0062 max mem: 33369 +Epoch: [35] [ 70/1319] eta: 0:56:34 lr: 7.62005758416347e-06 loss: 0.0315 (0.0327) time: 2.6485 data: 0.0062 max mem: 33369 +Epoch: [35] [ 80/1319] eta: 0:55:49 lr: 7.609544742772985e-06 loss: 0.0302 (0.0324) time: 2.6153 data: 0.0061 max mem: 33369 +Epoch: [35] [ 90/1319] eta: 0:55:10 lr: 7.599030287373793e-06 loss: 0.0341 (0.0328) time: 2.6068 data: 0.0061 max mem: 33369 +Epoch: [35] [ 100/1319] eta: 0:54:34 lr: 7.588514215235963e-06 loss: 0.0341 (0.0325) time: 2.6163 data: 0.0061 max mem: 33369 +Epoch: [35] [ 110/1319] eta: 0:54:01 lr: 7.5779965236207366e-06 loss: 0.0295 (0.0322) time: 2.6234 data: 0.0061 max mem: 33369 +Epoch: [35] [ 120/1319] eta: 0:53:28 lr: 7.5674772097804864e-06 loss: 0.0328 (0.0329) time: 2.6248 data: 0.0062 max mem: 33369 +Epoch: [35] [ 130/1319] eta: 0:52:53 lr: 7.556956270958658e-06 loss: 0.0303 (0.0325) time: 2.6035 data: 0.0062 max mem: 33369 +Epoch: [35] [ 140/1319] eta: 0:52:20 lr: 7.546433704389756e-06 loss: 0.0261 (0.0322) time: 2.5881 data: 0.0065 max mem: 33369 +Epoch: [35] [ 150/1319] eta: 0:51:47 lr: 7.535909507299282e-06 loss: 0.0263 (0.0322) time: 2.5897 data: 0.0066 max mem: 33369 +Epoch: [35] [ 160/1319] eta: 0:51:18 lr: 7.525383676903694e-06 loss: 0.0290 (0.0323) time: 2.6065 data: 0.0063 max mem: 33369 +Epoch: [35] [ 170/1319] eta: 0:50:48 lr: 7.514856210410369e-06 loss: 0.0304 (0.0327) time: 2.6105 data: 0.0063 max mem: 33369 +Epoch: [35] [ 180/1319] eta: 0:50:20 lr: 7.504327105017539e-06 loss: 0.0304 (0.0329) time: 2.6107 data: 0.0062 max mem: 33369 +Epoch: [35] [ 190/1319] eta: 0:49:54 lr: 7.493796357914276e-06 loss: 0.0280 (0.0328) time: 2.6490 data: 0.0060 max mem: 33369 +Epoch: [35] [ 200/1319] eta: 0:49:27 lr: 7.483263966280434e-06 loss: 0.0322 (0.0328) time: 2.6547 data: 0.0060 max mem: 33369 +Epoch: [35] [ 210/1319] eta: 0:48:58 lr: 7.4727299272865964e-06 loss: 0.0336 (0.0328) time: 2.6208 data: 0.0060 max mem: 33369 +Epoch: [35] [ 220/1319] eta: 0:48:31 lr: 7.462194238094052e-06 loss: 0.0336 (0.0329) time: 2.6203 data: 0.0059 max mem: 33369 +Epoch: [35] [ 230/1319] eta: 0:48:04 lr: 7.4516568958547115e-06 loss: 0.0301 (0.0330) time: 2.6457 data: 0.0060 max mem: 33369 +Epoch: [35] [ 240/1319] eta: 0:47:39 lr: 7.4411178977111085e-06 loss: 0.0295 (0.0331) time: 2.6681 data: 0.0060 max mem: 33369 +Epoch: [35] [ 250/1319] eta: 0:47:10 lr: 7.430577240796325e-06 loss: 0.0281 (0.0330) time: 2.6351 data: 0.0061 max mem: 33369 +Epoch: [35] [ 260/1319] eta: 0:46:45 lr: 7.420034922233955e-06 loss: 0.0282 (0.0329) time: 2.6281 data: 0.0061 max mem: 33369 +Epoch: [35] [ 270/1319] eta: 0:46:17 lr: 7.4094909391380505e-06 loss: 0.0297 (0.0329) time: 2.6497 data: 0.0061 max mem: 33369 +Epoch: [35] [ 280/1319] eta: 0:45:51 lr: 7.398945288613088e-06 loss: 0.0301 (0.0328) time: 2.6368 data: 0.0062 max mem: 33369 +Epoch: [35] [ 290/1319] eta: 0:45:23 lr: 7.388397967753893e-06 loss: 0.0298 (0.0330) time: 2.6222 data: 0.0062 max mem: 33369 +Epoch: [35] [ 300/1319] eta: 0:44:57 lr: 7.3778489736456335e-06 loss: 0.0291 (0.0329) time: 2.6367 data: 0.0062 max mem: 33369 +Epoch: [35] [ 310/1319] eta: 0:44:29 lr: 7.367298303363743e-06 loss: 0.0329 (0.0330) time: 2.6413 data: 0.0060 max mem: 33369 +Epoch: [35] [ 320/1319] eta: 0:44:02 lr: 7.35674595397388e-06 loss: 0.0304 (0.0330) time: 2.6184 data: 0.0060 max mem: 33369 +Epoch: [35] [ 330/1319] eta: 0:43:35 lr: 7.34619192253189e-06 loss: 0.0261 (0.0329) time: 2.6289 data: 0.0061 max mem: 33369 +Epoch: [35] [ 340/1319] eta: 0:43:08 lr: 7.335636206083729e-06 loss: 0.0338 (0.0336) time: 2.6201 data: 0.0061 max mem: 33369 +Epoch: [35] [ 350/1319] eta: 0:42:41 lr: 7.325078801665445e-06 loss: 0.0328 (0.0335) time: 2.6254 data: 0.0061 max mem: 33369 +Epoch: [35] [ 360/1319] eta: 0:42:15 lr: 7.31451970630312e-06 loss: 0.0309 (0.0336) time: 2.6385 data: 0.0059 max mem: 33369 +Epoch: [35] [ 370/1319] eta: 0:41:48 lr: 7.303958917012809e-06 loss: 0.0309 (0.0336) time: 2.6384 data: 0.0059 max mem: 33369 +Epoch: [35] [ 380/1319] eta: 0:41:21 lr: 7.293396430800509e-06 loss: 0.0334 (0.0336) time: 2.6306 data: 0.0059 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7.039379718907476e-06 loss: 0.0285 (0.0343) time: 2.6261 data: 0.0060 max mem: 33369 +Epoch: [35] [ 630/1319] eta: 0:30:20 lr: 7.0287738060785644e-06 loss: 0.0286 (0.0342) time: 2.6627 data: 0.0059 max mem: 33369 +Epoch: [35] [ 640/1319] eta: 0:29:54 lr: 7.018166114777613e-06 loss: 0.0295 (0.0342) time: 2.6505 data: 0.0059 max mem: 33369 +Epoch: [35] [ 650/1319] eta: 0:29:27 lr: 7.007556641718624e-06 loss: 0.0337 (0.0342) time: 2.6120 data: 0.0060 max mem: 33369 +Epoch: [35] [ 660/1319] eta: 0:29:00 lr: 6.9969453836039725e-06 loss: 0.0315 (0.0342) time: 2.6047 data: 0.0061 max mem: 33369 +Epoch: [35] [ 670/1319] eta: 0:28:34 lr: 6.986332337124384e-06 loss: 0.0315 (0.0341) time: 2.6277 data: 0.0060 max mem: 33369 +Epoch: [35] [ 680/1319] eta: 0:28:07 lr: 6.975717498958839e-06 loss: 0.0318 (0.0342) time: 2.6241 data: 0.0060 max mem: 33369 +Epoch: [35] [ 690/1319] eta: 0:27:40 lr: 6.965100865774533e-06 loss: 0.0318 (0.0342) time: 2.6249 data: 0.0060 max mem: 33369 +Epoch: [35] [ 700/1319] eta: 0:27:14 lr: 6.954482434226801e-06 loss: 0.0327 (0.0342) time: 2.6371 data: 0.0060 max mem: 33369 +Epoch: [35] [ 710/1319] eta: 0:26:48 lr: 6.9438622009590656e-06 loss: 0.0331 (0.0342) time: 2.6307 data: 0.0060 max mem: 33369 +Epoch: [35] [ 720/1319] eta: 0:26:21 lr: 6.933240162602753e-06 loss: 0.0302 (0.0342) time: 2.6267 data: 0.0060 max mem: 33369 +Epoch: [35] [ 730/1319] eta: 0:25:55 lr: 6.922616315777261e-06 loss: 0.0277 (0.0342) time: 2.6439 data: 0.0060 max mem: 33369 +Epoch: [35] [ 740/1319] eta: 0:25:28 lr: 6.911990657089877e-06 loss: 0.0272 (0.0341) time: 2.6534 data: 0.0060 max mem: 33369 +Epoch: [35] [ 750/1319] eta: 0:25:02 lr: 6.901363183135715e-06 loss: 0.0294 (0.0341) time: 2.6393 data: 0.0060 max mem: 33369 +Epoch: [35] [ 760/1319] eta: 0:24:35 lr: 6.890733890497658e-06 loss: 0.0312 (0.0341) time: 2.6347 data: 0.0060 max mem: 33369 +Epoch: [35] [ 770/1319] eta: 0:24:09 lr: 6.880102775746271e-06 loss: 0.0327 (0.0340) time: 2.6356 data: 0.0059 max mem: 33369 +Epoch: 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mem: 33369 +Epoch: [35] [ 860/1319] eta: 0:20:10 lr: 6.784340175855078e-06 loss: 0.0292 (0.0339) time: 2.6149 data: 0.0058 max mem: 33369 +Epoch: [35] [ 870/1319] eta: 0:19:44 lr: 6.7736906485984466e-06 loss: 0.0267 (0.0338) time: 2.6004 data: 0.0060 max mem: 33369 +Epoch: [35] [ 880/1319] eta: 0:19:17 lr: 6.763039260673876e-06 loss: 0.0262 (0.0337) time: 2.5868 data: 0.0062 max mem: 33369 +Epoch: [35] [ 890/1319] eta: 0:18:51 lr: 6.752386008499089e-06 loss: 0.0289 (0.0337) time: 2.6015 data: 0.0060 max mem: 33369 +Epoch: [35] [ 900/1319] eta: 0:18:24 lr: 6.741730888478615e-06 loss: 0.0302 (0.0337) time: 2.6013 data: 0.0059 max mem: 33369 +Epoch: [35] [ 910/1319] eta: 0:17:58 lr: 6.7310738970037205e-06 loss: 0.0302 (0.0337) time: 2.6177 data: 0.0061 max mem: 33369 +Epoch: [35] [ 920/1319] eta: 0:17:31 lr: 6.7204150304523424e-06 loss: 0.0304 (0.0337) time: 2.6201 data: 0.0064 max mem: 33369 +Epoch: [35] [ 930/1319] eta: 0:17:05 lr: 6.709754285188997e-06 loss: 0.0336 (0.0338) time: 2.6300 data: 0.0062 max mem: 33369 +Epoch: [35] [ 940/1319] eta: 0:16:38 lr: 6.699091657564736e-06 loss: 0.0392 (0.0339) time: 2.6257 data: 0.0060 max mem: 33369 +Epoch: [35] [ 950/1319] eta: 0:16:12 lr: 6.688427143917049e-06 loss: 0.0347 (0.0339) time: 2.6269 data: 0.0058 max mem: 33369 +Epoch: [35] [ 960/1319] eta: 0:15:46 lr: 6.677760740569799e-06 loss: 0.0278 (0.0339) time: 2.6240 data: 0.0059 max mem: 33369 +Epoch: [35] [ 970/1319] eta: 0:15:19 lr: 6.667092443833153e-06 loss: 0.0293 (0.0339) time: 2.6177 data: 0.0060 max mem: 33369 +Epoch: [35] [ 980/1319] eta: 0:14:53 lr: 6.656422250003478e-06 loss: 0.0320 (0.0339) time: 2.6276 data: 0.0060 max mem: 33369 +Epoch: [35] [ 990/1319] eta: 0:14:26 lr: 6.645750155363307e-06 loss: 0.0314 (0.0338) time: 2.6229 data: 0.0061 max mem: 33369 +Epoch: [35] [1000/1319] eta: 0:14:00 lr: 6.635076156181232e-06 loss: 0.0291 (0.0339) time: 2.6097 data: 0.0062 max mem: 33369 +Epoch: [35] [1010/1319] eta: 0:13:34 lr: 6.624400248711836e-06 loss: 0.0345 (0.0339) time: 2.6169 data: 0.0061 max mem: 33369 +Epoch: [35] [1020/1319] eta: 0:13:07 lr: 6.613722429195618e-06 loss: 0.0327 (0.0339) time: 2.6379 data: 0.0059 max mem: 33369 +Epoch: [35] [1030/1319] eta: 0:12:41 lr: 6.603042693858916e-06 loss: 0.0322 (0.0339) time: 2.6241 data: 0.0060 max mem: 33369 +Epoch: [35] [1040/1319] eta: 0:12:15 lr: 6.5923610389138055e-06 loss: 0.0322 (0.0338) time: 2.6181 data: 0.0060 max mem: 33369 +Epoch: [35] [1050/1319] eta: 0:11:48 lr: 6.581677460558057e-06 loss: 0.0263 (0.0339) time: 2.6358 data: 0.0059 max mem: 33369 +Epoch: [35] [1060/1319] eta: 0:11:22 lr: 6.570991954975031e-06 loss: 0.0263 (0.0338) time: 2.6397 data: 0.0058 max mem: 33369 +Epoch: [35] [1070/1319] eta: 0:10:55 lr: 6.560304518333606e-06 loss: 0.0303 (0.0338) time: 2.6187 data: 0.0059 max mem: 33369 +Epoch: [35] [1080/1319] eta: 0:10:29 lr: 6.549615146788095e-06 loss: 0.0323 (0.0338) time: 2.6193 data: 0.0061 max mem: 33369 +Epoch: [35] [1090/1319] eta: 0:10:03 lr: 6.538923836478152e-06 loss: 0.0331 (0.0339) time: 2.6159 data: 0.0061 max mem: 33369 +Epoch: [35] [1100/1319] eta: 0:09:36 lr: 6.528230583528713e-06 loss: 0.0335 (0.0339) time: 2.6021 data: 0.0062 max mem: 33369 +Epoch: [35] [1110/1319] eta: 0:09:10 lr: 6.5175353840499016e-06 loss: 0.0335 (0.0339) time: 2.6080 data: 0.0063 max mem: 33369 +Epoch: [35] [1120/1319] eta: 0:08:44 lr: 6.506838234136938e-06 loss: 0.0337 (0.0340) time: 2.6239 data: 0.0062 max mem: 33369 +Epoch: [35] [1130/1319] eta: 0:08:17 lr: 6.4961391298700616e-06 loss: 0.0293 (0.0339) time: 2.6393 data: 0.0061 max mem: 33369 +Epoch: [35] [1140/1319] eta: 0:07:51 lr: 6.485438067314456e-06 loss: 0.0275 (0.0339) time: 2.6355 data: 0.0060 max mem: 33369 +Epoch: [35] [1150/1319] eta: 0:07:25 lr: 6.4747350425201315e-06 loss: 0.0315 (0.0339) time: 2.6078 data: 0.0060 max mem: 33369 +Epoch: [35] [1160/1319] eta: 0:06:58 lr: 6.464030051521878e-06 loss: 0.0328 (0.0340) time: 2.6130 data: 0.0061 max mem: 33369 +Epoch: [35] [1170/1319] eta: 0:06:32 lr: 6.453323090339156e-06 loss: 0.0294 (0.0339) time: 2.6300 data: 0.0062 max mem: 33369 +Epoch: [35] [1180/1319] eta: 0:06:05 lr: 6.442614154976011e-06 loss: 0.0285 (0.0339) time: 2.6235 data: 0.0060 max mem: 33369 +Epoch: [35] [1190/1319] eta: 0:05:39 lr: 6.431903241420996e-06 loss: 0.0287 (0.0339) time: 2.6253 data: 0.0059 max mem: 33369 +Epoch: [35] [1200/1319] eta: 0:05:13 lr: 6.4211903456470515e-06 loss: 0.0287 (0.0338) time: 2.5994 data: 0.0060 max mem: 33369 +Epoch: [35] [1210/1319] eta: 0:04:46 lr: 6.410475463611462e-06 loss: 0.0350 (0.0338) time: 2.6191 data: 0.0060 max mem: 33369 +Epoch: [35] [1220/1319] eta: 0:04:20 lr: 6.399758591255733e-06 loss: 0.0356 (0.0338) time: 2.6478 data: 0.0059 max mem: 33369 +Epoch: [35] [1230/1319] eta: 0:03:54 lr: 6.389039724505507e-06 loss: 0.0303 (0.0338) time: 2.6094 data: 0.0060 max mem: 33369 +Epoch: [35] [1240/1319] eta: 0:03:27 lr: 6.378318859270487e-06 loss: 0.0342 (0.0339) time: 2.6194 data: 0.0059 max mem: 33369 +Epoch: [35] [1250/1319] eta: 0:03:01 lr: 6.3675959914443046e-06 loss: 0.0339 (0.0339) time: 2.6341 data: 0.0061 max mem: 33369 +Epoch: [35] [1260/1319] eta: 0:02:35 lr: 6.356871116904475e-06 loss: 0.0331 (0.0339) time: 2.6387 data: 0.0061 max mem: 33369 +Epoch: [35] [1270/1319] eta: 0:02:09 lr: 6.34614423151228e-06 loss: 0.0331 (0.0339) time: 2.6628 data: 0.0060 max mem: 33369 +Epoch: [35] [1280/1319] eta: 0:01:42 lr: 6.335415331112665e-06 loss: 0.0321 (0.0339) time: 2.6448 data: 0.0060 max mem: 33369 +Epoch: [35] [1290/1319] eta: 0:01:16 lr: 6.324684411534165e-06 loss: 0.0323 (0.0339) time: 2.6348 data: 0.0058 max mem: 33369 +Epoch: [35] [1300/1319] eta: 0:00:50 lr: 6.313951468588795e-06 loss: 0.0335 (0.0339) time: 2.6552 data: 0.0058 max mem: 33369 +Epoch: [35] [1310/1319] eta: 0:00:23 lr: 6.3032164980719415e-06 loss: 0.0312 (0.0339) time: 2.6437 data: 0.0057 max mem: 33369 +Epoch: [35] Total time: 0:57:53 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 2:01:58 time: 2.8442 data: 2.7664 max mem: 33369 +Test: [ 100/2573] eta: 0:04:05 time: 0.0714 data: 0.0011 max mem: 33369 +Test: [ 200/2573] eta: 0:03:25 time: 0.0733 data: 0.0011 max mem: 33369 +Test: [ 300/2573] eta: 0:03:06 time: 0.0752 data: 0.0011 max mem: 33369 +Test: [ 400/2573] eta: 0:02:53 time: 0.0752 data: 0.0011 max mem: 33369 +Test: [ 500/2573] eta: 0:02:42 time: 0.0737 data: 0.0011 max mem: 33369 +Test: [ 600/2573] eta: 0:02:33 time: 0.0737 data: 0.0011 max mem: 33369 +Test: [ 700/2573] eta: 0:02:25 time: 0.0738 data: 0.0011 max mem: 33369 +Test: [ 800/2573] eta: 0:02:16 time: 0.0771 data: 0.0011 max mem: 33369 +Test: [ 900/2573] eta: 0:02:08 time: 0.0738 data: 0.0011 max mem: 33369 +Test: [1000/2573] eta: 0:02:00 time: 0.0738 data: 0.0011 max mem: 33369 +Test: [1100/2573] eta: 0:01:52 time: 0.0739 data: 0.0012 max mem: 33369 +Test: [1200/2573] eta: 0:01:44 time: 0.0738 data: 0.0011 max mem: 33369 +Test: [1300/2573] eta: 0:01:36 time: 0.0738 data: 0.0011 max mem: 33369 +Test: [1400/2573] eta: 0:01:29 time: 0.0722 data: 0.0012 max mem: 33369 +Test: [1500/2573] eta: 0:01:21 time: 0.0739 data: 0.0012 max mem: 33369 +Test: [1600/2573] eta: 0:01:13 time: 0.0771 data: 0.0012 max mem: 33369 +Test: [1700/2573] eta: 0:01:06 time: 0.0721 data: 0.0011 max mem: 33369 +Test: [1800/2573] eta: 0:00:58 time: 0.0754 data: 0.0012 max mem: 33369 +Test: [1900/2573] eta: 0:00:50 time: 0.0721 data: 0.0011 max mem: 33369 +Test: [2000/2573] eta: 0:00:43 time: 0.0738 data: 0.0011 max mem: 33369 +Test: [2100/2573] eta: 0:00:35 time: 0.0754 data: 0.0011 max mem: 33369 +Test: [2200/2573] eta: 0:00:27 time: 0.0755 data: 0.0011 max mem: 33369 +Test: [2300/2573] eta: 0:00:20 time: 0.0754 data: 0.0011 max mem: 33369 +Test: [2400/2573] eta: 0:00:12 time: 0.0704 data: 0.0011 max mem: 33369 +Test: [2500/2573] eta: 0:00:05 time: 0.0738 data: 0.0011 max mem: 33369 +Test: Total time: 0:03:13 +Final results: +Mean IoU is 65.08 + + precision@0.5 = 73.22 + precision@0.6 = 67.99 + precision@0.7 = 61.66 + precision@0.8 = 50.84 + precision@0.9 = 25.96 + overall IoU = 62.09 + +Average object IoU 65.08204528508351 +Overall IoU 62.09199142456055 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [36] [ 0/1319] eta: 3:13:20 lr: 6.293553287544593e-06 loss: 0.0281 (0.0281) time: 8.7953 data: 1.6091 max mem: 33369 +Epoch: [36] [ 10/1319] eta: 1:09:37 lr: 6.282814452998321e-06 loss: 0.0281 (0.0354) time: 3.1911 data: 0.1522 max mem: 33369 +Epoch: [36] [ 20/1319] eta: 1:03:24 lr: 6.2720735785923675e-06 loss: 0.0337 (0.0340) time: 2.6354 data: 0.0062 max mem: 33369 +Epoch: [36] [ 30/1319] eta: 1:00:39 lr: 6.261330660056396e-06 loss: 0.0337 (0.0337) time: 2.6214 data: 0.0061 max mem: 33369 +Epoch: [36] [ 40/1319] eta: 0:59:15 lr: 6.250585693102968e-06 loss: 0.0336 (0.0342) time: 2.6242 data: 0.0061 max mem: 33369 +Epoch: [36] [ 50/1319] eta: 0:57:59 lr: 6.2398386734274585e-06 loss: 0.0333 (0.0362) time: 2.6157 data: 0.0063 max mem: 33369 +Epoch: [36] [ 60/1319] eta: 0:57:09 lr: 6.229089596707912e-06 loss: 0.0277 (0.0351) time: 2.6077 data: 0.0063 max mem: 33369 +Epoch: [36] [ 70/1319] eta: 0:56:16 lr: 6.218338458604991e-06 loss: 0.0292 (0.0346) time: 2.6041 data: 0.0061 max mem: 33369 +Epoch: [36] [ 80/1319] eta: 0:55:36 lr: 6.207585254761843e-06 loss: 0.0308 (0.0343) time: 2.6001 data: 0.0060 max mem: 33369 +Epoch: [36] [ 90/1319] eta: 0:55:00 lr: 6.196829980804001e-06 loss: 0.0315 (0.0340) time: 2.6245 data: 0.0060 max mem: 33369 +Epoch: [36] [ 100/1319] eta: 0:54:28 lr: 6.1860726323392754e-06 loss: 0.0328 (0.0345) time: 2.6337 data: 0.0061 max mem: 33369 +Epoch: [36] [ 110/1319] eta: 0:53:53 lr: 6.175313204957665e-06 loss: 0.0363 (0.0345) time: 2.6219 data: 0.0062 max mem: 33369 +Epoch: [36] [ 120/1319] eta: 0:53:21 lr: 6.164551694231212e-06 loss: 0.0376 (0.0351) time: 2.6143 data: 0.0063 max mem: 33369 +Epoch: [36] [ 130/1319] eta: 0:52:49 lr: 6.153788095713938e-06 loss: 0.0367 (0.0354) time: 2.6150 data: 0.0062 max mem: 33369 +Epoch: [36] [ 140/1319] eta: 0:52:16 lr: 6.143022404941713e-06 loss: 0.0357 (0.0354) time: 2.5972 data: 0.0061 max mem: 33369 +Epoch: [36] [ 150/1319] eta: 0:51:48 lr: 6.132254617432146e-06 loss: 0.0330 (0.0354) time: 2.6214 data: 0.0060 max mem: 33369 +Epoch: [36] [ 160/1319] eta: 0:51:20 lr: 6.121484728684484e-06 loss: 0.0333 (0.0353) time: 2.6434 data: 0.0061 max mem: 33369 +Epoch: [36] [ 170/1319] eta: 0:50:51 lr: 6.110712734179475e-06 loss: 0.0308 (0.0349) time: 2.6278 data: 0.0060 max mem: 33369 +Epoch: [36] [ 180/1319] eta: 0:50:22 lr: 6.099938629379293e-06 loss: 0.0286 (0.0346) time: 2.6210 data: 0.0061 max mem: 33369 +Epoch: [36] [ 190/1319] eta: 0:49:52 lr: 6.0891624097274035e-06 loss: 0.0300 (0.0345) time: 2.6096 data: 0.0063 max mem: 33369 +Epoch: [36] [ 200/1319] eta: 0:49:28 lr: 6.07838407064845e-06 loss: 0.0316 (0.0344) time: 2.6403 data: 0.0063 max mem: 33369 +Epoch: [36] [ 210/1319] eta: 0:49:02 lr: 6.067603607548146e-06 loss: 0.0273 (0.0341) time: 2.6735 data: 0.0062 max mem: 33369 +Epoch: [36] [ 220/1319] eta: 0:48:33 lr: 6.05682101581314e-06 loss: 0.0287 (0.0341) time: 2.6335 data: 0.0061 max mem: 33369 +Epoch: [36] [ 230/1319] eta: 0:48:05 lr: 6.0460362908109285e-06 loss: 0.0309 (0.0341) time: 2.6154 data: 0.0060 max mem: 33369 +Epoch: [36] [ 240/1319] eta: 0:47:39 lr: 6.035249427889721e-06 loss: 0.0295 (0.0339) time: 2.6413 data: 0.0062 max mem: 33369 +Epoch: [36] [ 250/1319] eta: 0:47:12 lr: 6.024460422378318e-06 loss: 0.0280 (0.0337) time: 2.6474 data: 0.0063 max mem: 33369 +Epoch: [36] [ 260/1319] eta: 0:46:45 lr: 6.013669269586002e-06 loss: 0.0294 (0.0337) time: 2.6433 data: 0.0061 max mem: 33369 +Epoch: [36] [ 270/1319] eta: 0:46:18 lr: 6.002875964802412e-06 loss: 0.0303 (0.0337) time: 2.6362 data: 0.0061 max mem: 33369 +Epoch: [36] [ 280/1319] eta: 0:45:51 lr: 5.992080503297408e-06 loss: 0.0299 (0.0336) time: 2.6364 data: 0.0062 max mem: 33369 +Epoch: [36] [ 290/1319] eta: 0:45:23 lr: 5.981282880320978e-06 loss: 0.0291 (0.0338) time: 2.6275 data: 0.0061 max mem: 33369 +Epoch: [36] [ 300/1319] eta: 0:44:56 lr: 5.97048309110309e-06 loss: 0.0299 (0.0337) time: 2.6119 data: 0.0060 max mem: 33369 +Epoch: [36] [ 310/1319] eta: 0:44:30 lr: 5.959681130853577e-06 loss: 0.0286 (0.0338) time: 2.6378 data: 0.0061 max mem: 33369 +Epoch: [36] [ 320/1319] eta: 0:44:04 lr: 5.948876994762015e-06 loss: 0.0279 (0.0338) time: 2.6654 data: 0.0063 max mem: 33369 +Epoch: [36] [ 330/1319] eta: 0:43:37 lr: 5.938070677997572e-06 loss: 0.0288 (0.0338) time: 2.6401 data: 0.0061 max mem: 33369 +Epoch: [36] [ 340/1319] eta: 0:43:09 lr: 5.927262175708919e-06 loss: 0.0355 (0.0339) time: 2.6059 data: 0.0060 max mem: 33369 +Epoch: [36] [ 350/1319] eta: 0:42:42 lr: 5.916451483024071e-06 loss: 0.0339 (0.0340) time: 2.6130 data: 0.0061 max mem: 33369 +Epoch: [36] [ 360/1319] eta: 0:42:14 lr: 5.905638595050271e-06 loss: 0.0295 (0.0340) time: 2.6178 data: 0.0060 max mem: 33369 +Epoch: [36] [ 370/1319] eta: 0:41:47 lr: 5.894823506873858e-06 loss: 0.0295 (0.0341) time: 2.5972 data: 0.0061 max mem: 33369 +Epoch: [36] [ 380/1319] eta: 0:41:21 lr: 5.884006213560114e-06 loss: 0.0317 (0.0342) time: 2.6290 data: 0.0061 max 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5.623716419827592e-06 loss: 0.0277 (0.0337) time: 2.6199 data: 0.0060 max mem: 33369 +Epoch: [36] [ 630/1319] eta: 0:30:18 lr: 5.612842329918665e-06 loss: 0.0248 (0.0336) time: 2.6363 data: 0.0060 max mem: 33369 +Epoch: [36] [ 640/1319] eta: 0:29:51 lr: 5.6019658987246355e-06 loss: 0.0272 (0.0335) time: 2.6062 data: 0.0059 max mem: 33369 +Epoch: [36] [ 650/1319] eta: 0:29:24 lr: 5.591087120688435e-06 loss: 0.0291 (0.0335) time: 2.5850 data: 0.0058 max mem: 33369 +Epoch: [36] [ 660/1319] eta: 0:28:57 lr: 5.5802059902277785e-06 loss: 0.0304 (0.0335) time: 2.6189 data: 0.0059 max mem: 33369 +Epoch: [36] [ 670/1319] eta: 0:28:31 lr: 5.569322501734972e-06 loss: 0.0333 (0.0335) time: 2.6409 data: 0.0058 max mem: 33369 +Epoch: [36] [ 680/1319] eta: 0:28:05 lr: 5.5584366495767425e-06 loss: 0.0317 (0.0335) time: 2.6513 data: 0.0057 max mem: 33369 +Epoch: [36] [ 690/1319] eta: 0:27:38 lr: 5.547548428094075e-06 loss: 0.0312 (0.0334) time: 2.6260 data: 0.0058 max mem: 33369 +Epoch: [36] [ 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5.1100083788515145e-06 loss: 0.0291 (0.0331) time: 2.6210 data: 0.0060 max mem: 33369 +Epoch: [36] [1100/1319] eta: 0:09:36 lr: 5.0990177994339575e-06 loss: 0.0308 (0.0330) time: 2.6062 data: 0.0060 max mem: 33369 +Epoch: [36] [1110/1319] eta: 0:09:10 lr: 5.088024587224353e-06 loss: 0.0330 (0.0331) time: 2.6264 data: 0.0059 max mem: 33369 +Epoch: [36] [1120/1319] eta: 0:08:44 lr: 5.077028735268508e-06 loss: 0.0347 (0.0331) time: 2.6166 data: 0.0058 max mem: 33369 +Epoch: [36] [1130/1319] eta: 0:08:17 lr: 5.066030236577056e-06 loss: 0.0365 (0.0331) time: 2.5892 data: 0.0058 max mem: 33369 +Epoch: [36] [1140/1319] eta: 0:07:51 lr: 5.055029084125236e-06 loss: 0.0297 (0.0331) time: 2.6223 data: 0.0058 max mem: 33369 +Epoch: [36] [1150/1319] eta: 0:07:25 lr: 5.044025270852602e-06 loss: 0.0292 (0.0331) time: 2.6533 data: 0.0059 max mem: 33369 +Epoch: [36] [1160/1319] eta: 0:06:58 lr: 5.033018789662757e-06 loss: 0.0298 (0.0331) time: 2.6396 data: 0.0058 max mem: 33369 +Epoch: [36] [1170/1319] eta: 0:06:32 lr: 5.022009633423085e-06 loss: 0.0298 (0.0330) time: 2.6380 data: 0.0059 max mem: 33369 +Epoch: [36] [1180/1319] eta: 0:06:06 lr: 5.0109977949644845e-06 loss: 0.0297 (0.0330) time: 2.6359 data: 0.0060 max mem: 33369 +Epoch: [36] [1190/1319] eta: 0:05:39 lr: 4.999983267081064e-06 loss: 0.0299 (0.0330) time: 2.6185 data: 0.0058 max mem: 33369 +Epoch: [36] [1200/1319] eta: 0:05:13 lr: 4.988966042529905e-06 loss: 0.0288 (0.0330) time: 2.6419 data: 0.0058 max mem: 33369 +Epoch: [36] [1210/1319] eta: 0:04:47 lr: 4.977946114030749e-06 loss: 0.0283 (0.0330) time: 2.6420 data: 0.0058 max mem: 33369 +Epoch: [36] [1220/1319] eta: 0:04:20 lr: 4.966923474265728e-06 loss: 0.0296 (0.0330) time: 2.6271 data: 0.0057 max mem: 33369 +Epoch: [36] [1230/1319] eta: 0:03:54 lr: 4.9558981158790714e-06 loss: 0.0301 (0.0330) time: 2.6150 data: 0.0058 max mem: 33369 +Epoch: [36] [1240/1319] eta: 0:03:28 lr: 4.944870031476802e-06 loss: 0.0308 (0.0330) time: 2.6266 data: 0.0059 max mem: 33369 +Epoch: [36] [1250/1319] eta: 0:03:01 lr: 4.9338392136264714e-06 loss: 0.0313 (0.0329) time: 2.6337 data: 0.0060 max mem: 33369 +Epoch: [36] [1260/1319] eta: 0:02:35 lr: 4.922805654856843e-06 loss: 0.0313 (0.0329) time: 2.6311 data: 0.0060 max mem: 33369 +Epoch: [36] [1270/1319] eta: 0:02:09 lr: 4.9117693476576e-06 loss: 0.0311 (0.0329) time: 2.6513 data: 0.0059 max mem: 33369 +Epoch: [36] [1280/1319] eta: 0:01:42 lr: 4.9007302844790375e-06 loss: 0.0298 (0.0329) time: 2.6446 data: 0.0058 max mem: 33369 +Epoch: [36] [1290/1319] eta: 0:01:16 lr: 4.889688457731768e-06 loss: 0.0270 (0.0329) time: 2.6362 data: 0.0058 max mem: 33369 +Epoch: [36] [1300/1319] eta: 0:00:50 lr: 4.878643859786385e-06 loss: 0.0270 (0.0328) time: 2.6267 data: 0.0058 max mem: 33369 +Epoch: [36] [1310/1319] eta: 0:00:23 lr: 4.867596482973188e-06 loss: 0.0304 (0.0328) time: 2.6238 data: 0.0060 max mem: 33369 +Epoch: [36] Total time: 0:57:53 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 2:34:49 time: 3.6105 data: 3.5325 max mem: 33369 +Test: [ 100/2573] eta: 0:04:24 time: 0.0717 data: 0.0011 max mem: 33369 +Test: [ 200/2573] eta: 0:03:34 time: 0.0729 data: 0.0011 max mem: 33369 +Test: [ 300/2573] eta: 0:03:11 time: 0.0746 data: 0.0011 max mem: 33369 +Test: [ 400/2573] eta: 0:02:56 time: 0.0747 data: 0.0011 max mem: 33369 +Test: [ 500/2573] eta: 0:02:45 time: 0.0732 data: 0.0012 max mem: 33369 +Test: [ 600/2573] eta: 0:02:35 time: 0.0734 data: 0.0011 max mem: 33369 +Test: [ 700/2573] eta: 0:02:26 time: 0.0733 data: 0.0011 max mem: 33369 +Test: [ 800/2573] eta: 0:02:18 time: 0.0768 data: 0.0011 max mem: 33369 +Test: [ 900/2573] eta: 0:02:09 time: 0.0735 data: 0.0011 max mem: 33369 +Test: [1000/2573] eta: 0:02:01 time: 0.0736 data: 0.0011 max mem: 33369 +Test: [1100/2573] eta: 0:01:53 time: 0.0736 data: 0.0011 max mem: 33369 +Test: [1200/2573] eta: 0:01:45 time: 0.0734 data: 0.0011 max mem: 33369 +Test: [1300/2573] eta: 0:01:37 time: 0.0735 data: 0.0011 max mem: 33369 +Test: [1400/2573] eta: 0:01:29 time: 0.0719 data: 0.0011 max mem: 33369 +Test: [1500/2573] eta: 0:01:21 time: 0.0736 data: 0.0011 max mem: 33369 +Test: [1600/2573] eta: 0:01:13 time: 0.0771 data: 0.0011 max mem: 33369 +Test: [1700/2573] eta: 0:01:06 time: 0.0720 data: 0.0011 max mem: 33369 +Test: [1800/2573] eta: 0:00:58 time: 0.0755 data: 0.0011 max mem: 33369 +Test: [1900/2573] eta: 0:00:50 time: 0.0721 data: 0.0011 max mem: 33369 +Test: [2000/2573] eta: 0:00:43 time: 0.0737 data: 0.0011 max mem: 33369 +Test: [2100/2573] eta: 0:00:35 time: 0.0753 data: 0.0011 max mem: 33369 +Test: [2200/2573] eta: 0:00:28 time: 0.0754 data: 0.0011 max mem: 33369 +Test: [2300/2573] eta: 0:00:20 time: 0.0755 data: 0.0012 max mem: 33369 +Test: [2400/2573] eta: 0:00:12 time: 0.0704 data: 0.0011 max mem: 33369 +Test: [2500/2573] eta: 0:00:05 time: 0.0737 data: 0.0013 max mem: 33369 +Test: Total time: 0:03:13 +Final results: +Mean IoU is 65.44 + + precision@0.5 = 73.41 + precision@0.6 = 68.36 + precision@0.7 = 62.25 + precision@0.8 = 51.51 + precision@0.9 = 26.04 + overall IoU = 62.55 + +Average object IoU 65.4446920240666 +Overall IoU 62.55319595336914 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [37] [ 0/1319] eta: 3:02:29 lr: 4.85765146153759e-06 loss: 0.0191 (0.0191) time: 8.3017 data: 1.8531 max mem: 33369 +Epoch: [37] [ 10/1319] eta: 1:08:48 lr: 4.846598783599751e-06 loss: 0.0225 (0.0246) time: 3.1539 data: 0.1745 max mem: 33369 +Epoch: [37] [ 20/1319] eta: 1:02:58 lr: 4.835543304321068e-06 loss: 0.0281 (0.0285) time: 2.6389 data: 0.0059 max mem: 33369 +Epoch: [37] [ 30/1319] eta: 1:00:30 lr: 4.824485015871577e-06 loss: 0.0313 (0.0307) time: 2.6310 data: 0.0058 max mem: 33369 +Epoch: [37] [ 40/1319] eta: 0:58:56 lr: 4.813423910379438e-06 loss: 0.0336 (0.0319) time: 2.6145 data: 0.0063 max mem: 33369 +Epoch: [37] [ 50/1319] eta: 0:57:59 lr: 4.802359979930566e-06 loss: 0.0344 (0.0315) time: 2.6264 data: 0.0062 max mem: 33369 +Epoch: [37] [ 60/1319] eta: 0:57:10 lr: 4.791293216568347e-06 loss: 0.0295 (0.0308) time: 2.6430 data: 0.0062 max mem: 33369 +Epoch: [37] [ 70/1319] eta: 0:56:30 lr: 4.780223612293264e-06 loss: 0.0276 (0.0307) time: 2.6456 data: 0.0062 max mem: 33369 +Epoch: [37] [ 80/1319] eta: 0:55:59 lr: 4.7691511590625665e-06 loss: 0.0309 (0.0311) time: 2.6712 data: 0.0062 max mem: 33369 +Epoch: [37] [ 90/1319] eta: 0:55:24 lr: 4.75807584878992e-06 loss: 0.0337 (0.0318) time: 2.6692 data: 0.0063 max mem: 33369 +Epoch: [37] [ 100/1319] eta: 0:54:48 lr: 4.7469976733450685e-06 loss: 0.0322 (0.0317) time: 2.6392 data: 0.0062 max mem: 33369 +Epoch: [37] [ 110/1319] eta: 0:54:15 lr: 4.735916624553454e-06 loss: 0.0273 (0.0314) time: 2.6369 data: 0.0062 max mem: 33369 +Epoch: [37] [ 120/1319] eta: 0:53:41 lr: 4.724832694195895e-06 loss: 0.0294 (0.0314) time: 2.6337 data: 0.0062 max mem: 33369 +Epoch: [37] [ 130/1319] eta: 0:53:07 lr: 4.713745874008202e-06 loss: 0.0294 (0.0311) time: 2.6142 data: 0.0062 max mem: 33369 +Epoch: [37] [ 140/1319] eta: 0:52:36 lr: 4.702656155680819e-06 loss: 0.0298 (0.0311) time: 2.6220 data: 0.0063 max mem: 33369 +Epoch: [37] [ 150/1319] eta: 0:52:05 lr: 4.691563530858464e-06 loss: 0.0316 (0.0316) time: 2.6272 data: 0.0063 max mem: 33369 +Epoch: [37] [ 160/1319] eta: 0:51:35 lr: 4.6804679911397265e-06 loss: 0.0321 (0.0314) time: 2.6246 data: 0.0063 max mem: 33369 +Epoch: [37] [ 170/1319] eta: 0:51:05 lr: 4.66936952807673e-06 loss: 0.0308 (0.0313) time: 2.6265 data: 0.0062 max mem: 33369 +Epoch: [37] [ 180/1319] eta: 0:50:34 lr: 4.65826813317473e-06 loss: 0.0272 (0.0312) time: 2.6075 data: 0.0061 max mem: 33369 +Epoch: [37] [ 190/1319] eta: 0:50:05 lr: 4.64716379789173e-06 loss: 0.0294 (0.0311) time: 2.6094 data: 0.0060 max mem: 33369 +Epoch: [37] [ 200/1319] eta: 0:49:37 lr: 4.636056513638103e-06 loss: 0.0302 (0.0311) time: 2.6348 data: 0.0060 max mem: 33369 +Epoch: [37] [ 210/1319] eta: 0:49:10 lr: 4.6249462717761695e-06 loss: 0.0317 (0.0314) time: 2.6483 data: 0.0060 max mem: 33369 +Epoch: [37] [ 220/1319] eta: 0:48:40 lr: 4.6138330636198426e-06 loss: 0.0315 (0.0313) time: 2.6213 data: 0.0061 max mem: 33369 +Epoch: [37] [ 230/1319] eta: 0:48:12 lr: 4.602716880434195e-06 loss: 0.0271 (0.0313) time: 2.6055 data: 0.0060 max mem: 33369 +Epoch: [37] [ 240/1319] eta: 0:47:44 lr: 4.591597713435064e-06 loss: 0.0299 (0.0313) time: 2.6268 data: 0.0060 max mem: 33369 +Epoch: [37] [ 250/1319] eta: 0:47:17 lr: 4.580475553788638e-06 loss: 0.0299 (0.0312) time: 2.6348 data: 0.0062 max mem: 33369 +Epoch: [37] [ 260/1319] eta: 0:46:47 lr: 4.569350392611047e-06 loss: 0.0270 (0.0311) time: 2.6042 data: 0.0062 max mem: 33369 +Epoch: [37] [ 270/1319] eta: 0:46:18 lr: 4.558222220967921e-06 loss: 0.0298 (0.0312) time: 2.5808 data: 0.0062 max mem: 33369 +Epoch: [37] [ 280/1319] eta: 0:45:51 lr: 4.547091029873999e-06 loss: 0.0306 (0.0312) time: 2.6053 data: 0.0062 max mem: 33369 +Epoch: [37] [ 290/1319] eta: 0:45:21 lr: 4.5359568102926745e-06 loss: 0.0313 (0.0314) time: 2.5948 data: 0.0061 max mem: 33369 +Epoch: [37] [ 300/1319] eta: 0:44:54 lr: 4.524819553135574e-06 loss: 0.0267 (0.0313) time: 2.5961 data: 0.0062 max mem: 33369 +Epoch: [37] [ 310/1319] eta: 0:44:26 lr: 4.5136792492621144e-06 loss: 0.0315 (0.0314) time: 2.6029 data: 0.0061 max mem: 33369 +Epoch: [37] [ 320/1319] eta: 0:43:58 lr: 4.502535889479041e-06 loss: 0.0313 (0.0313) time: 2.5850 data: 0.0060 max mem: 33369 +Epoch: [37] [ 330/1319] eta: 0:43:30 lr: 4.491389464540016e-06 loss: 0.0272 (0.0313) time: 2.6011 data: 0.0061 max mem: 33369 +Epoch: [37] [ 340/1319] eta: 0:43:04 lr: 4.480239965145135e-06 loss: 0.0289 (0.0314) time: 2.6226 data: 0.0061 max mem: 33369 +Epoch: [37] [ 350/1319] eta: 0:42:35 lr: 4.469087381940477e-06 loss: 0.0312 (0.0314) time: 2.6021 data: 0.0059 max mem: 33369 +Epoch: [37] [ 360/1319] eta: 0:42:09 lr: 4.457931705517646e-06 loss: 0.0293 (0.0313) time: 2.6003 data: 0.0058 max mem: 33369 +Epoch: [37] [ 370/1319] eta: 0:41:43 lr: 4.446772926413276e-06 loss: 0.0274 (0.0313) time: 2.6404 data: 0.0059 max mem: 33369 +Epoch: [37] [ 380/1319] eta: 0:41:16 lr: 4.435611035108594e-06 loss: 0.0298 (0.0313) time: 2.6438 data: 0.0059 max 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data: 0.0061 max mem: 33369 +Epoch: [37] [ 470/1319] eta: 0:37:17 lr: 4.335012365689605e-06 loss: 0.0300 (0.0316) time: 2.6306 data: 0.0059 max mem: 33369 +Epoch: [37] [ 480/1319] eta: 0:36:50 lr: 4.323818816304266e-06 loss: 0.0313 (0.0316) time: 2.6192 data: 0.0058 max mem: 33369 +Epoch: [37] [ 490/1319] eta: 0:36:24 lr: 4.3126220462124026e-06 loss: 0.0307 (0.0316) time: 2.6327 data: 0.0059 max mem: 33369 +Epoch: [37] [ 500/1319] eta: 0:35:57 lr: 4.3014220451909986e-06 loss: 0.0267 (0.0315) time: 2.6265 data: 0.0061 max mem: 33369 +Epoch: [37] [ 510/1319] eta: 0:35:31 lr: 4.2902188029549045e-06 loss: 0.0267 (0.0315) time: 2.6179 data: 0.0064 max mem: 33369 +Epoch: [37] [ 520/1319] eta: 0:35:04 lr: 4.279012309156296e-06 loss: 0.0299 (0.0315) time: 2.6277 data: 0.0065 max mem: 33369 +Epoch: [37] [ 530/1319] eta: 0:34:38 lr: 4.267802553384072e-06 loss: 0.0304 (0.0314) time: 2.6365 data: 0.0061 max mem: 33369 +Epoch: [37] [ 540/1319] eta: 0:34:11 lr: 4.256589525163327e-06 loss: 0.0320 (0.0315) time: 2.6165 data: 0.0060 max mem: 33369 +Epoch: [37] [ 550/1319] eta: 0:33:45 lr: 4.2453732139547435e-06 loss: 0.0290 (0.0314) time: 2.6121 data: 0.0062 max mem: 33369 +Epoch: [37] [ 560/1319] eta: 0:33:19 lr: 4.234153609154016e-06 loss: 0.0291 (0.0314) time: 2.6378 data: 0.0061 max mem: 33369 +Epoch: [37] [ 570/1319] eta: 0:32:53 lr: 4.222930700091251e-06 loss: 0.0306 (0.0316) time: 2.6541 data: 0.0061 max mem: 33369 +Epoch: [37] [ 580/1319] eta: 0:32:26 lr: 4.211704476030378e-06 loss: 0.0303 (0.0316) time: 2.6273 data: 0.0061 max mem: 33369 +Epoch: [37] [ 590/1319] eta: 0:31:59 lr: 4.200474926168517e-06 loss: 0.0300 (0.0316) time: 2.6015 data: 0.0059 max mem: 33369 +Epoch: [37] [ 600/1319] eta: 0:31:33 lr: 4.189242039635394e-06 loss: 0.0299 (0.0316) time: 2.6268 data: 0.0060 max mem: 33369 +Epoch: [37] [ 610/1319] eta: 0:31:07 lr: 4.178005805492704e-06 loss: 0.0266 (0.0315) time: 2.6457 data: 0.0061 max mem: 33369 +Epoch: [37] [ 620/1319] eta: 0:30:41 lr: 4.166766212733477e-06 loss: 0.0261 (0.0315) time: 2.6442 data: 0.0060 max mem: 33369 +Epoch: [37] [ 630/1319] eta: 0:30:14 lr: 4.15552325028145e-06 loss: 0.0269 (0.0315) time: 2.6380 data: 0.0059 max mem: 33369 +Epoch: [37] [ 640/1319] eta: 0:29:47 lr: 4.1442769069903985e-06 loss: 0.0283 (0.0314) time: 2.6099 data: 0.0059 max mem: 33369 +Epoch: [37] [ 650/1319] eta: 0:29:21 lr: 4.133027171643516e-06 loss: 0.0292 (0.0315) time: 2.5932 data: 0.0061 max mem: 33369 +Epoch: [37] [ 660/1319] eta: 0:28:55 lr: 4.121774032952729e-06 loss: 0.0254 (0.0315) time: 2.6278 data: 0.0062 max mem: 33369 +Epoch: [37] [ 670/1319] eta: 0:28:28 lr: 4.110517479558032e-06 loss: 0.0298 (0.0315) time: 2.6464 data: 0.0061 max mem: 33369 +Epoch: [37] [ 680/1319] eta: 0:28:02 lr: 4.099257500026817e-06 loss: 0.0270 (0.0315) time: 2.6563 data: 0.0059 max mem: 33369 +Epoch: [37] [ 690/1319] eta: 0:27:36 lr: 4.087994082853156e-06 loss: 0.0263 (0.0314) time: 2.6409 data: 0.0058 max mem: 33369 +Epoch: [37] [ 700/1319] eta: 0:27:09 lr: 4.076727216457151e-06 loss: 0.0284 (0.0314) time: 2.6017 data: 0.0059 max mem: 33369 +Epoch: [37] [ 710/1319] eta: 0:26:43 lr: 4.065456889184196e-06 loss: 0.0311 (0.0314) time: 2.6069 data: 0.0061 max mem: 33369 +Epoch: [37] [ 720/1319] eta: 0:26:16 lr: 4.054183089304276e-06 loss: 0.0316 (0.0316) time: 2.5978 data: 0.0061 max mem: 33369 +Epoch: [37] [ 730/1319] eta: 0:25:50 lr: 4.0429058050112415e-06 loss: 0.0331 (0.0316) time: 2.6073 data: 0.0059 max mem: 33369 +Epoch: [37] [ 740/1319] eta: 0:25:23 lr: 4.031625024422082e-06 loss: 0.0310 (0.0315) time: 2.6314 data: 0.0062 max mem: 33369 +Epoch: [37] [ 750/1319] eta: 0:24:57 lr: 4.020340735576163e-06 loss: 0.0302 (0.0318) time: 2.6062 data: 0.0062 max mem: 33369 +Epoch: [37] [ 760/1319] eta: 0:24:30 lr: 4.0090529264345135e-06 loss: 0.0304 (0.0317) time: 2.5957 data: 0.0060 max mem: 33369 +Epoch: [37] [ 770/1319] eta: 0:24:04 lr: 3.997761584879033e-06 loss: 0.0291 (0.0317) time: 2.6084 data: 0.0061 max mem: 33369 +Epoch: [37] [ 780/1319] eta: 0:23:37 lr: 3.986466698711739e-06 loss: 0.0263 (0.0316) time: 2.6113 data: 0.0061 max mem: 33369 +Epoch: [37] [ 790/1319] eta: 0:23:11 lr: 3.975168255653987e-06 loss: 0.0289 (0.0317) time: 2.6005 data: 0.0061 max mem: 33369 +Epoch: [37] [ 800/1319] eta: 0:22:44 lr: 3.963866243345654e-06 loss: 0.0313 (0.0317) time: 2.5823 data: 0.0062 max mem: 33369 +Epoch: [37] [ 810/1319] eta: 0:22:18 lr: 3.952560649344379e-06 loss: 0.0291 (0.0316) time: 2.5868 data: 0.0062 max mem: 33369 +Epoch: [37] [ 820/1319] eta: 0:21:51 lr: 3.94125146112473e-06 loss: 0.0291 (0.0316) time: 2.6082 data: 0.0061 max mem: 33369 +Epoch: [37] [ 830/1319] eta: 0:21:25 lr: 3.929938666077381e-06 loss: 0.0297 (0.0316) time: 2.5992 data: 0.0063 max mem: 33369 +Epoch: [37] [ 840/1319] eta: 0:20:58 lr: 3.918622251508287e-06 loss: 0.0321 (0.0317) time: 2.6029 data: 0.0064 max mem: 33369 +Epoch: [37] [ 850/1319] eta: 0:20:32 lr: 3.907302204637846e-06 loss: 0.0317 (0.0317) time: 2.6263 data: 0.0061 max mem: 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0.0057 max mem: 33369 +Epoch: [37] [ 940/1319] eta: 0:16:35 lr: 3.805256177133712e-06 loss: 0.0264 (0.0316) time: 2.6145 data: 0.0058 max mem: 33369 +Epoch: [37] [ 950/1319] eta: 0:16:09 lr: 3.7938990849213705e-06 loss: 0.0301 (0.0316) time: 2.5930 data: 0.0060 max mem: 33369 +Epoch: [37] [ 960/1319] eta: 0:15:43 lr: 3.782538213932079e-06 loss: 0.0288 (0.0316) time: 2.6127 data: 0.0060 max mem: 33369 +Epoch: [37] [ 970/1319] eta: 0:15:16 lr: 3.771173550289461e-06 loss: 0.0284 (0.0316) time: 2.6366 data: 0.0059 max mem: 33369 +Epoch: [37] [ 980/1319] eta: 0:14:50 lr: 3.7598050800195294e-06 loss: 0.0281 (0.0315) time: 2.6213 data: 0.0060 max mem: 33369 +Epoch: [37] [ 990/1319] eta: 0:14:24 lr: 3.748432789049672e-06 loss: 0.0281 (0.0316) time: 2.6174 data: 0.0062 max mem: 33369 +Epoch: [37] [1000/1319] eta: 0:13:57 lr: 3.7370566632076215e-06 loss: 0.0299 (0.0316) time: 2.6067 data: 0.0061 max mem: 33369 +Epoch: [37] [1010/1319] eta: 0:13:31 lr: 3.725676688220417e-06 loss: 0.0267 (0.0316) time: 2.5957 data: 0.0061 max mem: 33369 +Epoch: [37] [1020/1319] eta: 0:13:05 lr: 3.714292849713318e-06 loss: 0.0290 (0.0316) time: 2.6200 data: 0.0060 max mem: 33369 +Epoch: [37] [1030/1319] eta: 0:12:38 lr: 3.7029051332087708e-06 loss: 0.0297 (0.0316) time: 2.6226 data: 0.0059 max mem: 33369 +Epoch: [37] [1040/1319] eta: 0:12:12 lr: 3.691513524125288e-06 loss: 0.0288 (0.0316) time: 2.6328 data: 0.0058 max mem: 33369 +Epoch: [37] [1050/1319] eta: 0:11:46 lr: 3.680118007776355e-06 loss: 0.0307 (0.0317) time: 2.6511 data: 0.0059 max mem: 33369 +Epoch: [37] [1060/1319] eta: 0:11:20 lr: 3.6687185693693123e-06 loss: 0.0317 (0.0317) time: 2.6232 data: 0.0062 max mem: 33369 +Epoch: [37] [1070/1319] eta: 0:10:53 lr: 3.657315194004196e-06 loss: 0.0315 (0.0317) time: 2.6027 data: 0.0061 max mem: 33369 +Epoch: [37] [1080/1319] eta: 0:10:27 lr: 3.6459078666726217e-06 loss: 0.0286 (0.0317) time: 2.6130 data: 0.0060 max mem: 33369 +Epoch: [37] [1090/1319] eta: 0:10:01 lr: 3.6344965722565904e-06 loss: 0.0282 (0.0317) time: 2.6424 data: 0.0061 max mem: 33369 +Epoch: [37] [1100/1319] eta: 0:09:35 lr: 3.6230812955273095e-06 loss: 0.0326 (0.0317) time: 2.6529 data: 0.0060 max mem: 33369 +Epoch: [37] [1110/1319] eta: 0:09:08 lr: 3.6116620211439967e-06 loss: 0.0329 (0.0318) time: 2.6379 data: 0.0059 max mem: 33369 +Epoch: [37] [1120/1319] eta: 0:08:42 lr: 3.6002387336526318e-06 loss: 0.0331 (0.0318) time: 2.6074 data: 0.0060 max mem: 33369 +Epoch: [37] [1130/1319] eta: 0:08:16 lr: 3.588811417484761e-06 loss: 0.0327 (0.0318) time: 2.5965 data: 0.0061 max mem: 33369 +Epoch: [37] [1140/1319] eta: 0:07:50 lr: 3.577380056956213e-06 loss: 0.0289 (0.0318) time: 2.6259 data: 0.0060 max mem: 33369 +Epoch: [37] [1150/1319] eta: 0:07:23 lr: 3.5659446362658317e-06 loss: 0.0285 (0.0318) time: 2.6286 data: 0.0061 max mem: 33369 +Epoch: [37] [1160/1319] eta: 0:06:57 lr: 3.5545051394941854e-06 loss: 0.0307 (0.0319) time: 2.6133 data: 0.0061 max mem: 33369 +Epoch: [37] [1170/1319] eta: 0:06:31 lr: 3.5430615506022587e-06 loss: 0.0312 (0.0319) time: 2.6206 data: 0.0060 max mem: 33369 +Epoch: [37] [1180/1319] eta: 0:06:05 lr: 3.531613853430098e-06 loss: 0.0300 (0.0318) time: 2.6173 data: 0.0060 max mem: 33369 +Epoch: [37] [1190/1319] eta: 0:05:38 lr: 3.5201620316954973e-06 loss: 0.0274 (0.0318) time: 2.6157 data: 0.0062 max mem: 33369 +Epoch: [37] [1200/1319] eta: 0:05:12 lr: 3.5087060689926057e-06 loss: 0.0270 (0.0318) time: 2.6242 data: 0.0061 max mem: 33369 +Epoch: [37] [1210/1319] eta: 0:04:46 lr: 3.4972459487905388e-06 loss: 0.0302 (0.0318) time: 2.6264 data: 0.0061 max mem: 33369 +Epoch: [37] [1220/1319] eta: 0:04:19 lr: 3.485781654431977e-06 loss: 0.0281 (0.0318) time: 2.6317 data: 0.0060 max mem: 33369 +Epoch: [37] [1230/1319] eta: 0:03:53 lr: 3.4743131691317023e-06 loss: 0.0313 (0.0318) time: 2.6226 data: 0.0059 max mem: 33369 +Epoch: [37] [1240/1319] eta: 0:03:27 lr: 3.462840475975186e-06 loss: 0.0305 (0.0318) time: 2.6097 data: 0.0058 max mem: 33369 +Epoch: [37] 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+/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 1:51:28 time: 2.5996 data: 2.5213 max mem: 33369 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 100/2573] eta: 0:03:59 time: 0.0715 data: 0.0011 max mem: 33369 +Test: [ 200/2573] eta: 0:03:22 time: 0.0729 data: 0.0011 max mem: 33369 +Test: [ 300/2573] eta: 0:03:03 time: 0.0745 data: 0.0011 max mem: 33369 +Test: [ 400/2573] eta: 0:02:51 time: 0.0746 data: 0.0011 max mem: 33369 +Test: [ 500/2573] eta: 0:02:41 time: 0.0731 data: 0.0011 max mem: 33369 +Test: [ 600/2573] eta: 0:02:32 time: 0.0734 data: 0.0011 max mem: 33369 +Test: [ 700/2573] eta: 0:02:23 time: 0.0734 data: 0.0011 max mem: 33369 +Test: [ 800/2573] eta: 0:02:15 time: 0.0767 data: 0.0011 max mem: 33369 +Test: [ 900/2573] eta: 0:02:07 time: 0.0735 data: 0.0011 max mem: 33369 +Test: [1000/2573] eta: 0:01:59 time: 0.0733 data: 0.0011 max mem: 33369 +Test: [1100/2573] eta: 0:01:51 time: 0.0735 data: 0.0011 max mem: 33369 +Test: [1200/2573] eta: 0:01:43 time: 0.0734 data: 0.0011 max mem: 33369 +Test: [1300/2573] eta: 0:01:36 time: 0.0735 data: 0.0011 max mem: 33369 +Test: [1400/2573] eta: 0:01:28 time: 0.0718 data: 0.0011 max mem: 33369 +Test: [1500/2573] eta: 0:01:20 time: 0.0736 data: 0.0011 max mem: 33369 +Test: [1600/2573] eta: 0:01:13 time: 0.0769 data: 0.0011 max mem: 33369 +Test: [1700/2573] eta: 0:01:05 time: 0.0719 data: 0.0011 max mem: 33369 +Test: [1800/2573] eta: 0:00:57 time: 0.0752 data: 0.0011 max mem: 33369 +Test: [1900/2573] eta: 0:00:50 time: 0.0721 data: 0.0012 max mem: 33369 +Test: [2000/2573] eta: 0:00:42 time: 0.0737 data: 0.0011 max mem: 33369 +Test: [2100/2573] eta: 0:00:35 time: 0.0753 data: 0.0011 max mem: 33369 +Test: [2200/2573] eta: 0:00:27 time: 0.0754 data: 0.0011 max mem: 33369 +Test: [2300/2573] eta: 0:00:20 time: 0.0753 data: 0.0011 max mem: 33369 +Test: [2400/2573] eta: 0:00:12 time: 0.0703 data: 0.0011 max mem: 33369 +Test: [2500/2573] eta: 0:00:05 time: 0.0738 data: 0.0011 max mem: 33369 +Test: Total time: 0:03:11 +Final results: +Mean IoU is 65.32 + + precision@0.5 = 73.41 + precision@0.6 = 68.40 + precision@0.7 = 62.17 + precision@0.8 = 51.41 + precision@0.9 = 25.65 + overall IoU = 62.32 + +Average object IoU 65.31951722558156 +Overall IoU 62.318702697753906 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [38] [ 0/1319] eta: 3:31:36 lr: 3.3720562685558925e-06 loss: 0.0262 (0.0262) time: 9.6258 data: 1.6782 max mem: 33369 +Epoch: [38] [ 10/1319] eta: 1:11:40 lr: 3.3605453588871517e-06 loss: 0.0330 (0.0335) time: 3.2852 data: 0.1586 max mem: 33369 +Epoch: [38] [ 20/1319] eta: 1:04:16 lr: 3.349030066603249e-06 loss: 0.0320 (0.0343) time: 2.6363 data: 0.0064 max mem: 33369 +Epoch: [38] [ 30/1319] eta: 1:01:43 lr: 3.3375103732791936e-06 loss: 0.0320 (0.0348) time: 2.6471 data: 0.0063 max mem: 33369 +Epoch: [38] [ 40/1319] eta: 0:59:47 lr: 3.3259862603415314e-06 loss: 0.0332 (0.0351) time: 2.6323 data: 0.0064 max mem: 33369 +Epoch: [38] [ 50/1319] eta: 0:58:31 lr: 3.314457709066606e-06 loss: 0.0327 (0.0346) time: 2.6031 data: 0.0064 max mem: 33369 +Epoch: [38] [ 60/1319] eta: 0:57:37 lr: 3.302924700578736e-06 loss: 0.0336 (0.0342) time: 2.6255 data: 0.0063 max mem: 33369 +Epoch: [38] [ 70/1319] eta: 0:56:53 lr: 3.2913872158483893e-06 loss: 0.0299 (0.0342) time: 2.6458 data: 0.0063 max mem: 33369 +Epoch: [38] [ 80/1319] eta: 0:56:04 lr: 3.279845235690334e-06 loss: 0.0263 (0.0331) time: 2.6234 data: 0.0063 max mem: 33369 +Epoch: [38] [ 90/1319] eta: 0:55:24 lr: 3.268298740761722e-06 loss: 0.0271 (0.0328) time: 2.6037 data: 0.0063 max mem: 33369 +Epoch: [38] [ 100/1319] eta: 0:54:49 lr: 3.2567477115602124e-06 loss: 0.0293 (0.0327) time: 2.6271 data: 0.0062 max mem: 33369 +Epoch: [38] [ 110/1319] eta: 0:54:08 lr: 3.2451921284219928e-06 loss: 0.0299 (0.0328) time: 2.6037 data: 0.0062 max mem: 33369 +Epoch: [38] [ 120/1319] eta: 0:53:32 lr: 3.233631971519807e-06 loss: 0.0271 (0.0325) time: 2.5843 data: 0.0061 max mem: 33369 +Epoch: [38] [ 130/1319] eta: 0:53:04 lr: 3.2220672208609392e-06 loss: 0.0248 (0.0321) time: 2.6354 data: 0.0063 max mem: 33369 +Epoch: [38] [ 140/1319] eta: 0:52:34 lr: 3.2104978562851772e-06 loss: 0.0248 (0.0321) time: 2.6541 data: 0.0064 max mem: 33369 +Epoch: [38] [ 150/1319] eta: 0:52:01 lr: 3.1989238574627024e-06 loss: 0.0292 (0.0322) time: 2.6155 data: 0.0063 max mem: 33369 +Epoch: [38] [ 160/1319] eta: 0:51:28 lr: 3.18734520389202e-06 loss: 0.0308 (0.0321) time: 2.5896 data: 0.0063 max mem: 33369 +Epoch: [38] [ 170/1319] eta: 0:50:58 lr: 3.175761874897778e-06 loss: 0.0280 (0.0322) time: 2.5992 data: 0.0063 max mem: 33369 +Epoch: [38] [ 180/1319] eta: 0:50:32 lr: 3.1641738496285912e-06 loss: 0.0322 (0.0325) time: 2.6380 data: 0.0061 max mem: 33369 +Epoch: [38] [ 190/1319] eta: 0:50:03 lr: 3.1525811070548283e-06 loss: 0.0329 (0.0324) time: 2.6490 data: 0.0060 max mem: 33369 +Epoch: [38] [ 200/1319] eta: 0:49:37 lr: 3.1409836259663234e-06 loss: 0.0297 (0.0324) time: 2.6457 data: 0.0060 max mem: 33369 +Epoch: [38] [ 210/1319] eta: 0:49:08 lr: 3.1293813849701203e-06 loss: 0.0297 (0.0325) time: 2.6421 data: 0.0059 max mem: 33369 +Epoch: [38] [ 220/1319] eta: 0:48:38 lr: 3.1177743624881108e-06 loss: 0.0291 (0.0323) time: 2.6041 data: 0.0060 max mem: 33369 +Epoch: [38] [ 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33369 +Epoch: [38] [ 310/1319] eta: 0:44:29 lr: 3.013092338126003e-06 loss: 0.0276 (0.0319) time: 2.6123 data: 0.0060 max mem: 33369 +Epoch: [38] [ 320/1319] eta: 0:44:02 lr: 3.0014362715060913e-06 loss: 0.0295 (0.0319) time: 2.6270 data: 0.0060 max mem: 33369 +Epoch: [38] [ 330/1319] eta: 0:43:34 lr: 2.9897751731121923e-06 loss: 0.0325 (0.0320) time: 2.6143 data: 0.0062 max mem: 33369 +Epoch: [38] [ 340/1319] eta: 0:43:08 lr: 2.978109018946967e-06 loss: 0.0293 (0.0318) time: 2.6184 data: 0.0061 max mem: 33369 +Epoch: [38] [ 350/1319] eta: 0:42:41 lr: 2.9664377847936435e-06 loss: 0.0242 (0.0318) time: 2.6330 data: 0.0062 max mem: 33369 +Epoch: [38] [ 360/1319] eta: 0:42:15 lr: 2.954761446213011e-06 loss: 0.0250 (0.0318) time: 2.6369 data: 0.0063 max mem: 33369 +Epoch: [38] [ 370/1319] eta: 0:41:48 lr: 2.943079978540434e-06 loss: 0.0281 (0.0317) time: 2.6376 data: 0.0062 max mem: 33369 +Epoch: [38] [ 380/1319] eta: 0:41:21 lr: 2.931393356882739e-06 loss: 0.0312 (0.0318) time: 2.6208 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2.2798478534460264e-06 loss: 0.0302 (0.0317) time: 2.6501 data: 0.0059 max mem: 33369 +Epoch: [38] [ 940/1319] eta: 0:16:37 lr: 2.2678240375265906e-06 loss: 0.0309 (0.0317) time: 2.6531 data: 0.0058 max mem: 33369 +Epoch: [38] [ 950/1319] eta: 0:16:11 lr: 2.25579313413962e-06 loss: 0.0309 (0.0317) time: 2.6562 data: 0.0059 max mem: 33369 +Epoch: [38] [ 960/1319] eta: 0:15:44 lr: 2.243755097057401e-06 loss: 0.0270 (0.0316) time: 2.6250 data: 0.0060 max mem: 33369 +Epoch: [38] [ 970/1319] eta: 0:15:18 lr: 2.2317098794731506e-06 loss: 0.0265 (0.0316) time: 2.5973 data: 0.0060 max mem: 33369 +Epoch: [38] [ 980/1319] eta: 0:14:51 lr: 2.2196574339902486e-06 loss: 0.0303 (0.0317) time: 2.5805 data: 0.0061 max mem: 33369 +Epoch: [38] [ 990/1319] eta: 0:14:25 lr: 2.2075977126112046e-06 loss: 0.0346 (0.0317) time: 2.5943 data: 0.0060 max mem: 33369 +Epoch: [38] [1000/1319] eta: 0:13:59 lr: 2.195530666726346e-06 loss: 0.0309 (0.0317) time: 2.6008 data: 0.0059 max mem: 33369 +Epoch: [38] 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2.6368 data: 0.0060 max mem: 33369 +Epoch: [38] [1170/1319] eta: 0:06:31 lr: 1.9892199154733075e-06 loss: 0.0321 (0.0317) time: 2.6217 data: 0.0060 max mem: 33369 +Epoch: [38] [1180/1319] eta: 0:06:05 lr: 1.977011942435173e-06 loss: 0.0295 (0.0317) time: 2.6061 data: 0.0060 max mem: 33369 +Epoch: [38] [1190/1319] eta: 0:05:39 lr: 1.964795587609718e-06 loss: 0.0287 (0.0317) time: 2.6261 data: 0.0060 max mem: 33369 +Epoch: [38] [1200/1319] eta: 0:05:12 lr: 1.9525707872561044e-06 loss: 0.0273 (0.0316) time: 2.6292 data: 0.0060 max mem: 33369 +Epoch: [38] [1210/1319] eta: 0:04:46 lr: 1.9403374767016633e-06 loss: 0.0276 (0.0317) time: 2.6035 data: 0.0059 max mem: 33369 +Epoch: [38] [1220/1319] eta: 0:04:20 lr: 1.928095590321611e-06 loss: 0.0330 (0.0317) time: 2.5964 data: 0.0060 max mem: 33369 +Epoch: [38] [1230/1319] eta: 0:03:53 lr: 1.915845061518256e-06 loss: 0.0286 (0.0316) time: 2.6104 data: 0.0061 max mem: 33369 +Epoch: [38] [1240/1319] eta: 0:03:27 lr: 1.9035858226995284e-06 loss: 0.0255 (0.0316) time: 2.6097 data: 0.0060 max mem: 33369 +Epoch: [38] [1250/1319] eta: 0:03:01 lr: 1.8913178052569088e-06 loss: 0.0299 (0.0316) time: 2.6081 data: 0.0060 max mem: 33369 +Epoch: [38] [1260/1319] eta: 0:02:35 lr: 1.8790409395427117e-06 loss: 0.0314 (0.0316) time: 2.6166 data: 0.0062 max mem: 33369 +Epoch: [38] [1270/1319] eta: 0:02:08 lr: 1.8667551548466507e-06 loss: 0.0304 (0.0316) time: 2.6191 data: 0.0062 max mem: 33369 +Epoch: [38] [1280/1319] eta: 0:01:42 lr: 1.8544603793717773e-06 loss: 0.0325 (0.0317) time: 2.6272 data: 0.0060 max mem: 33369 +Epoch: [38] [1290/1319] eta: 0:01:16 lr: 1.8421565402096163e-06 loss: 0.0327 (0.0317) time: 2.6378 data: 0.0060 max mem: 33369 +Epoch: [38] [1300/1319] eta: 0:00:49 lr: 1.8298435633145817e-06 loss: 0.0292 (0.0317) time: 2.6276 data: 0.0059 max mem: 33369 +Epoch: [38] [1310/1319] eta: 0:00:23 lr: 1.8175213734776007e-06 loss: 0.0285 (0.0317) time: 2.6080 data: 0.0059 max mem: 33369 +Epoch: [38] Total time: 0:57:45 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 2:02:43 time: 2.8617 data: 2.7825 max mem: 33369 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 100/2573] eta: 0:04:06 time: 0.0717 data: 0.0011 max mem: 33369 +Test: [ 200/2573] eta: 0:03:26 time: 0.0730 data: 0.0011 max mem: 33369 +Test: [ 300/2573] eta: 0:03:05 time: 0.0747 data: 0.0011 max mem: 33369 +Test: [ 400/2573] eta: 0:02:52 time: 0.0747 data: 0.0011 max mem: 33369 +Test: [ 500/2573] eta: 0:02:42 time: 0.0733 data: 0.0011 max mem: 33369 +Test: [ 600/2573] eta: 0:02:33 time: 0.0736 data: 0.0012 max mem: 33369 +Test: [ 700/2573] eta: 0:02:24 time: 0.0734 data: 0.0011 max mem: 33369 +Test: [ 800/2573] eta: 0:02:16 time: 0.0769 data: 0.0011 max mem: 33369 +Test: [ 900/2573] eta: 0:02:08 time: 0.0736 data: 0.0011 max mem: 33369 +Test: [1000/2573] eta: 0:02:00 time: 0.0735 data: 0.0012 max mem: 33369 +Test: [1100/2573] eta: 0:01:52 time: 0.0737 data: 0.0011 max mem: 33369 +Test: [1200/2573] eta: 0:01:44 time: 0.0736 data: 0.0011 max mem: 33369 +Test: [1300/2573] eta: 0:01:36 time: 0.0735 data: 0.0011 max mem: 33369 +Test: [1400/2573] eta: 0:01:28 time: 0.0720 data: 0.0011 max mem: 33369 +Test: [1500/2573] eta: 0:01:21 time: 0.0736 data: 0.0011 max mem: 33369 +Test: [1600/2573] eta: 0:01:13 time: 0.0771 data: 0.0012 max mem: 33369 +Test: [1700/2573] eta: 0:01:05 time: 0.0719 data: 0.0011 max mem: 33369 +Test: [1800/2573] eta: 0:00:58 time: 0.0754 data: 0.0011 max mem: 33369 +Test: [1900/2573] eta: 0:00:50 time: 0.0721 data: 0.0011 max mem: 33369 +Test: [2000/2573] eta: 0:00:42 time: 0.0736 data: 0.0011 max mem: 33369 +Test: [2100/2573] eta: 0:00:35 time: 0.0753 data: 0.0011 max mem: 33369 +Test: [2200/2573] eta: 0:00:27 time: 0.0755 data: 0.0011 max mem: 33369 +Test: [2300/2573] eta: 0:00:20 time: 0.0754 data: 0.0011 max mem: 33369 +Test: [2400/2573] eta: 0:00:12 time: 0.0704 data: 0.0011 max mem: 33369 +Test: [2500/2573] eta: 0:00:05 time: 0.0737 data: 0.0011 max mem: 33369 +Test: Total time: 0:03:12 +Final results: +Mean IoU is 65.32 + + precision@0.5 = 73.37 + precision@0.6 = 68.34 + precision@0.7 = 62.30 + precision@0.8 = 51.51 + precision@0.9 = 25.86 + overall IoU = 62.32 + +Average object IoU 65.31718824238641 +Overall IoU 62.31964874267578 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [39] [ 0/1319] eta: 2:59:35 lr: 1.8064234624396156e-06 loss: 0.0364 (0.0364) time: 8.1698 data: 1.5019 max mem: 33369 +Epoch: [39] [ 10/1319] eta: 1:09:17 lr: 1.7940835565249508e-06 loss: 0.0257 (0.0277) time: 3.1762 data: 0.1422 max mem: 33369 +Epoch: [39] [ 20/1319] eta: 1:03:27 lr: 1.7817342127276263e-06 loss: 0.0279 (0.0293) time: 2.6695 data: 0.0060 max mem: 33369 +Epoch: [39] [ 30/1319] eta: 1:00:31 lr: 1.7693753510331764e-06 loss: 0.0279 (0.0286) time: 2.6194 data: 0.0060 max mem: 33369 +Epoch: [39] [ 40/1319] eta: 0:59:04 lr: 1.757006890122028e-06 loss: 0.0273 (0.0293) time: 2.6028 data: 0.0062 max mem: 33369 +Epoch: [39] [ 50/1319] eta: 0:58:04 lr: 1.7446287473378005e-06 loss: 0.0289 (0.0297) time: 2.6351 data: 0.0063 max mem: 33369 +Epoch: [39] [ 60/1319] eta: 0:57:07 lr: 1.7322408386546176e-06 loss: 0.0317 (0.0305) time: 2.6214 data: 0.0064 max mem: 33369 +Epoch: [39] [ 70/1319] eta: 0:56:29 lr: 1.7198430786433514e-06 loss: 0.0323 (0.0303) time: 2.6318 data: 0.0063 max mem: 33369 +Epoch: [39] [ 80/1319] eta: 0:55:54 lr: 1.7074353804367206e-06 loss: 0.0282 (0.0302) time: 2.6616 data: 0.0064 max mem: 33369 +Epoch: [39] [ 90/1319] eta: 0:55:17 lr: 1.6950176556933094e-06 loss: 0.0281 (0.0301) time: 2.6477 data: 0.0063 max mem: 33369 +Epoch: [39] [ 100/1319] eta: 0:54:42 lr: 1.682589814560305e-06 loss: 0.0321 (0.0311) time: 2.6343 data: 0.0061 max mem: 33369 +Epoch: [39] [ 110/1319] eta: 0:54:06 lr: 1.6701517656350208e-06 loss: 0.0331 (0.0314) time: 2.6220 data: 0.0060 max mem: 33369 +Epoch: [39] [ 120/1319] eta: 0:53:31 lr: 1.6577034159251048e-06 loss: 0.0289 (0.0312) time: 2.6063 data: 0.0061 max mem: 33369 +Epoch: [39] [ 130/1319] eta: 0:53:03 lr: 1.6452446708073954e-06 loss: 0.0296 (0.0339) time: 2.6369 data: 0.0061 max mem: 33369 +Epoch: [39] [ 140/1319] eta: 0:52:35 lr: 1.632775433985313e-06 loss: 0.0292 (0.0334) time: 2.6619 data: 0.0061 max mem: 33369 +Epoch: [39] [ 150/1319] eta: 0:52:00 lr: 1.62029560744485e-06 loss: 0.0271 (0.0330) time: 2.6142 data: 0.0062 max mem: 33369 +Epoch: [39] [ 160/1319] eta: 0:51:33 lr: 1.6078050914089353e-06 loss: 0.0295 (0.0329) time: 2.6200 data: 0.0062 max mem: 33369 +Epoch: [39] [ 170/1319] eta: 0:51:03 lr: 1.5953037842902214e-06 loss: 0.0323 (0.0330) time: 2.6459 data: 0.0062 max mem: 33369 +Epoch: [39] [ 180/1319] eta: 0:50:35 lr: 1.5827915826421849e-06 loss: 0.0304 (0.0330) time: 2.6310 data: 0.0062 max mem: 33369 +Epoch: [39] [ 190/1319] eta: 0:50:06 lr: 1.5702683811084266e-06 loss: 0.0301 (0.0328) time: 2.6307 data: 0.0063 max mem: 33369 +Epoch: [39] [ 200/1319] eta: 0:49:35 lr: 1.5577340723702017e-06 loss: 0.0295 (0.0326) time: 2.6031 data: 0.0063 max mem: 33369 +Epoch: [39] [ 210/1319] eta: 0:49:08 lr: 1.5451885470919527e-06 loss: 0.0260 (0.0323) time: 2.6187 data: 0.0062 max mem: 33369 +Epoch: [39] [ 220/1319] eta: 0:48:40 lr: 1.5326316938648584e-06 loss: 0.0266 (0.0322) time: 2.6474 data: 0.0061 max mem: 33369 +Epoch: [39] [ 230/1319] eta: 0:48:13 lr: 1.5200633991482792e-06 loss: 0.0287 (0.0320) time: 2.6362 data: 0.0060 max mem: 33369 +Epoch: [39] [ 240/1319] eta: 0:47:47 lr: 1.5074835472089545e-06 loss: 0.0260 (0.0319) time: 2.6593 data: 0.0061 max mem: 33369 +Epoch: [39] [ 250/1319] eta: 0:47:18 lr: 1.4948920200579605e-06 loss: 0.0255 (0.0319) time: 2.6338 data: 0.0061 max mem: 33369 +Epoch: [39] [ 260/1319] eta: 0:46:50 lr: 1.4822886973851744e-06 loss: 0.0332 (0.0318) time: 2.6042 data: 0.0061 max mem: 33369 +Epoch: [39] [ 270/1319] eta: 0:46:22 lr: 1.4696734564912314e-06 loss: 0.0325 (0.0320) time: 2.6246 data: 0.0062 max mem: 33369 +Epoch: [39] [ 280/1319] eta: 0:45:54 lr: 1.457046172216814e-06 loss: 0.0298 (0.0319) time: 2.6215 data: 0.0061 max mem: 33369 +Epoch: [39] [ 290/1319] eta: 0:45:26 lr: 1.444406716869153e-06 loss: 0.0338 (0.0319) time: 2.6134 data: 0.0060 max mem: 33369 +Epoch: [39] [ 300/1319] eta: 0:45:00 lr: 1.4317549601455566e-06 loss: 0.0329 (0.0319) time: 2.6330 data: 0.0060 max mem: 33369 +Epoch: [39] [ 310/1319] eta: 0:44:33 lr: 1.419090769053936e-06 loss: 0.0314 (0.0320) time: 2.6493 data: 0.0061 max mem: 33369 +Epoch: [39] [ 320/1319] eta: 0:44:06 lr: 1.4064140078300187e-06 loss: 0.0314 (0.0320) time: 2.6304 data: 0.0062 max mem: 33369 +Epoch: [39] [ 330/1319] eta: 0:43:38 lr: 1.3937245378511972e-06 loss: 0.0262 (0.0319) time: 2.6051 data: 0.0061 max mem: 33369 +Epoch: [39] [ 340/1319] eta: 0:43:12 lr: 1.3810222175468009e-06 loss: 0.0269 (0.0318) time: 2.6316 data: 0.0061 max mem: 33369 +Epoch: [39] [ 350/1319] eta: 0:42:44 lr: 1.3683069023045655e-06 loss: 0.0298 (0.0318) time: 2.6418 data: 0.0061 max mem: 33369 +Epoch: [39] [ 360/1319] eta: 0:42:18 lr: 1.355578444373217e-06 loss: 0.0298 (0.0317) time: 2.6276 data: 0.0061 max mem: 33369 +Epoch: [39] [ 370/1319] eta: 0:41:50 lr: 1.3428366927608033e-06 loss: 0.0316 (0.0317) time: 2.6225 data: 0.0061 max mem: 33369 +Epoch: [39] [ 380/1319] eta: 0:41:23 lr: 1.330081493128668e-06 loss: 0.0293 (0.0316) time: 2.6127 data: 0.0062 max mem: 33369 +Epoch: [39] [ 390/1319] eta: 0:40:56 lr: 1.3173126876807778e-06 loss: 0.0265 (0.0316) time: 2.6233 data: 0.0061 max mem: 33369 +Epoch: [39] [ 400/1319] eta: 0:40:29 lr: 1.304530115048165e-06 loss: 0.0252 (0.0316) time: 2.6120 data: 0.0061 max mem: 33369 +Epoch: [39] [ 410/1319] eta: 0:40:02 lr: 1.2917336101681678e-06 loss: 0.0265 (0.0317) time: 2.6098 data: 0.0061 max mem: 33369 +Epoch: [39] [ 420/1319] eta: 0:39:36 lr: 1.2789230041582899e-06 loss: 0.0276 (0.0316) time: 2.6427 data: 0.0060 max mem: 33369 +Epoch: [39] [ 430/1319] eta: 0:39:09 lr: 1.2660981241842216e-06 loss: 0.0282 (0.0316) time: 2.6546 data: 0.0060 max mem: 33369 +Epoch: [39] [ 440/1319] eta: 0:38:42 lr: 1.2532587933218004e-06 loss: 0.0282 (0.0315) time: 2.6287 data: 0.0060 max mem: 33369 +Epoch: [39] [ 450/1319] eta: 0:38:15 lr: 1.2404048304125217e-06 loss: 0.0281 (0.0314) time: 2.6097 data: 0.0060 max mem: 33369 +Epoch: [39] [ 460/1319] eta: 0:37:49 lr: 1.2275360499121832e-06 loss: 0.0284 (0.0315) time: 2.6142 data: 0.0061 max mem: 33369 +Epoch: [39] [ 470/1319] eta: 0:37:22 lr: 1.2146522617323656e-06 loss: 0.0305 (0.0315) time: 2.6200 data: 0.0061 max mem: 33369 +Epoch: [39] [ 480/1319] eta: 0:36:55 lr: 1.2017532710741682e-06 loss: 0.0300 (0.0314) time: 2.6164 data: 0.0063 max mem: 33369 +Epoch: [39] [ 490/1319] eta: 0:36:28 lr: 1.1888388782538434e-06 loss: 0.0258 (0.0314) time: 2.6191 data: 0.0061 max mem: 33369 +Epoch: [39] [ 500/1319] eta: 0:36:01 lr: 1.175908878519789e-06 loss: 0.0265 (0.0313) time: 2.6221 data: 0.0060 max mem: 33369 +Epoch: [39] [ 510/1319] eta: 0:35:35 lr: 1.1629630618603247e-06 loss: 0.0290 (0.0314) time: 2.6320 data: 0.0059 max mem: 33369 +Epoch: [39] [ 520/1319] eta: 0:35:08 lr: 1.150001212801783e-06 loss: 0.0313 (0.0314) time: 2.6211 data: 0.0059 max mem: 33369 +Epoch: [39] [ 530/1319] eta: 0:34:41 lr: 1.1370231101961411e-06 loss: 0.0288 (0.0314) time: 2.6104 data: 0.0061 max mem: 33369 +Epoch: [39] [ 540/1319] eta: 0:34:15 lr: 1.1240285269976361e-06 loss: 0.0287 (0.0315) time: 2.6233 data: 0.0060 max mem: 33369 +Epoch: [39] [ 550/1319] eta: 0:33:48 lr: 1.1110172300275867e-06 loss: 0.0333 (0.0315) time: 2.6337 data: 0.0059 max mem: 33369 +Epoch: [39] [ 560/1319] eta: 0:33:22 lr: 1.097988979726662e-06 loss: 0.0312 (0.0316) time: 2.6270 data: 0.0061 max mem: 33369 +Epoch: [39] [ 570/1319] eta: 0:32:55 lr: 1.084943529893699e-06 loss: 0.0291 (0.0315) time: 2.6110 data: 0.0061 max mem: 33369 +Epoch: [39] [ 580/1319] eta: 0:32:28 lr: 1.0718806274102695e-06 loss: 0.0283 (0.0314) time: 2.6103 data: 0.0060 max mem: 33369 +Epoch: [39] [ 590/1319] eta: 0:32:02 lr: 1.0588000119498569e-06 loss: 0.0294 (0.0314) time: 2.6253 data: 0.0060 max mem: 33369 +Epoch: [39] [ 600/1319] eta: 0:31:35 lr: 1.0457014156706775e-06 loss: 0.0298 (0.0314) time: 2.6190 data: 0.0060 max mem: 33369 +Epoch: [39] [ 610/1319] eta: 0:31:09 lr: 1.032584562890946e-06 loss: 0.0296 (0.0314) time: 2.6100 data: 0.0059 max mem: 33369 +Epoch: [39] [ 620/1319] eta: 0:30:42 lr: 1.0194491697452832e-06 loss: 0.0342 (0.0315) time: 2.6278 data: 0.0059 max mem: 33369 +Epoch: [39] [ 630/1319] eta: 0:30:15 lr: 1.0062949438209979e-06 loss: 0.0291 (0.0314) time: 2.6171 data: 0.0059 max mem: 33369 +Epoch: [39] [ 640/1319] eta: 0:29:49 lr: 9.931215837725994e-07 loss: 0.0289 (0.0314) time: 2.5950 data: 0.0060 max mem: 33369 +Epoch: [39] [ 650/1319] eta: 0:29:22 lr: 9.799287789130144e-07 loss: 0.0306 (0.0315) time: 2.5966 data: 0.0061 max mem: 33369 +Epoch: [39] [ 660/1319] eta: 0:28:55 lr: 9.667162087796925e-07 loss: 0.0311 (0.0315) time: 2.6046 data: 0.0060 max mem: 33369 +Epoch: [39] [ 670/1319] eta: 0:28:29 lr: 9.534835426736097e-07 loss: 0.0311 (0.0314) time: 2.6133 data: 0.0059 max mem: 33369 +Epoch: [39] [ 680/1319] eta: 0:28:03 lr: 9.402304391691554e-07 loss: 0.0292 (0.0314) time: 2.6288 data: 0.0058 max mem: 33369 +Epoch: [39] [ 690/1319] eta: 0:27:36 lr: 9.269565455924141e-07 loss: 0.0292 (0.0315) time: 2.6344 data: 0.0058 max mem: 33369 +Epoch: [39] [ 700/1319] eta: 0:27:10 lr: 9.136614974653884e-07 loss: 0.0321 (0.0315) time: 2.6186 data: 0.0061 max mem: 33369 +Epoch: [39] [ 710/1319] eta: 0:26:43 lr: 9.003449179133091e-07 loss: 0.0298 (0.0315) time: 2.6265 data: 0.0061 max mem: 33369 +Epoch: [39] [ 720/1319] eta: 0:26:17 lr: 8.870064170319405e-07 loss: 0.0269 (0.0314) time: 2.6350 data: 0.0060 max mem: 33369 +Epoch: [39] [ 730/1319] eta: 0:25:51 lr: 8.736455912114245e-07 loss: 0.0264 (0.0314) time: 2.6244 data: 0.0060 max mem: 33369 +Epoch: [39] [ 740/1319] eta: 0:25:24 lr: 8.602620224130043e-07 loss: 0.0325 (0.0314) time: 2.6250 data: 0.0058 max mem: 33369 +Epoch: [39] [ 750/1319] eta: 0:24:58 lr: 8.468552773943076e-07 loss: 0.0333 (0.0315) time: 2.6384 data: 0.0059 max mem: 33369 +Epoch: [39] [ 760/1319] eta: 0:24:31 lr: 8.334249068786857e-07 loss: 0.0279 (0.0314) time: 2.6277 data: 0.0059 max mem: 33369 +Epoch: [39] [ 770/1319] eta: 0:24:05 lr: 8.199704446634483e-07 loss: 0.0279 (0.0314) time: 2.6134 data: 0.0060 max mem: 33369 +Epoch: [39] [ 780/1319] eta: 0:23:38 lr: 8.064914066612595e-07 loss: 0.0293 (0.0313) time: 2.5969 data: 0.0060 max mem: 33369 +Epoch: [39] [ 790/1319] eta: 0:23:12 lr: 7.92987289868475e-07 loss: 0.0293 (0.0314) time: 2.5954 data: 0.0059 max mem: 33369 +Epoch: [39] [ 800/1319] eta: 0:22:45 lr: 7.79457571253187e-07 loss: 0.0327 (0.0314) time: 2.6255 data: 0.0062 max mem: 33369 +Epoch: [39] [ 810/1319] eta: 0:22:19 lr: 7.659017065551902e-07 loss: 0.0348 (0.0315) time: 2.6466 data: 0.0063 max mem: 33369 +Epoch: [39] [ 820/1319] eta: 0:21:53 lr: 7.523191289889679e-07 loss: 0.0342 (0.0315) time: 2.6581 data: 0.0060 max mem: 33369 +Epoch: [39] [ 830/1319] eta: 0:21:27 lr: 7.387092478397154e-07 loss: 0.0303 (0.0315) time: 2.6255 data: 0.0060 max mem: 33369 +Epoch: [39] [ 840/1319] eta: 0:21:00 lr: 7.250714469413284e-07 loss: 0.0318 (0.0316) time: 2.6080 data: 0.0060 max mem: 33369 +Epoch: [39] [ 850/1319] eta: 0:20:34 lr: 7.114050830235778e-07 loss: 0.0310 (0.0316) time: 2.6104 data: 0.0061 max mem: 33369 +Epoch: [39] [ 860/1319] eta: 0:20:07 lr: 6.977094839143229e-07 loss: 0.0306 (0.0317) time: 2.6076 data: 0.0059 max mem: 33369 +Epoch: [39] [ 870/1319] eta: 0:19:41 lr: 6.839839465805414e-07 loss: 0.0306 (0.0316) time: 2.6046 data: 0.0060 max mem: 33369 +Epoch: [39] [ 880/1319] eta: 0:19:15 lr: 6.702277349898191e-07 loss: 0.0305 (0.0317) time: 2.6283 data: 0.0060 max mem: 33369 +Epoch: [39] [ 890/1319] eta: 0:18:48 lr: 6.564400777713066e-07 loss: 0.0345 (0.0318) time: 2.6485 data: 0.0060 max mem: 33369 +Epoch: [39] [ 900/1319] eta: 0:18:22 lr: 6.426201656523381e-07 loss: 0.0382 (0.0318) time: 2.6246 data: 0.0059 max mem: 33369 +Epoch: [39] [ 910/1319] eta: 0:17:55 lr: 6.287671486431178e-07 loss: 0.0327 (0.0318) time: 2.5935 data: 0.0058 max mem: 33369 +Epoch: [39] [ 920/1319] eta: 0:17:29 lr: 6.148801329380617e-07 loss: 0.0296 (0.0318) time: 2.5915 data: 0.0059 max mem: 33369 +Epoch: [39] [ 930/1319] eta: 0:17:03 lr: 6.009581774973726e-07 loss: 0.0280 (0.0318) time: 2.6053 data: 0.0060 max mem: 33369 +Epoch: [39] [ 940/1319] eta: 0:16:36 lr: 5.870002902666957e-07 loss: 0.0283 (0.0318) time: 2.6026 data: 0.0061 max mem: 33369 +Epoch: [39] [ 950/1319] eta: 0:16:10 lr: 5.7300542398606e-07 loss: 0.0267 (0.0318) time: 2.6280 data: 0.0060 max mem: 33369 +Epoch: [39] [ 960/1319] eta: 0:15:44 lr: 5.589724715308914e-07 loss: 0.0258 (0.0317) time: 2.6531 data: 0.0059 max mem: 33369 +Epoch: [39] [ 970/1319] eta: 0:15:17 lr: 5.449002607184345e-07 loss: 0.0258 (0.0317) time: 2.6470 data: 0.0062 max mem: 33369 +Epoch: [39] [ 980/1319] eta: 0:14:51 lr: 5.307875485010082e-07 loss: 0.0255 (0.0317) time: 2.6114 data: 0.0063 max mem: 33369 +Epoch: [39] [ 990/1319] eta: 0:14:25 lr: 5.166330144533874e-07 loss: 0.0285 (0.0317) time: 2.5796 data: 0.0061 max mem: 33369 +Epoch: [39] [1000/1319] eta: 0:13:58 lr: 5.024352534442401e-07 loss: 0.0313 (0.0317) time: 2.6089 data: 0.0059 max mem: 33369 +Epoch: [39] [1010/1319] eta: 0:13:32 lr: 4.881927673605746e-07 loss: 0.0309 (0.0317) time: 2.6360 data: 0.0058 max mem: 33369 +Epoch: [39] [1020/1319] eta: 0:13:06 lr: 4.7390395572780197e-07 loss: 0.0289 (0.0317) time: 2.6307 data: 0.0059 max mem: 33369 +Epoch: [39] [1030/1319] eta: 0:12:40 lr: 4.595671050360423e-07 loss: 0.0305 (0.0316) time: 2.6488 data: 0.0059 max mem: 33369 +Epoch: [39] [1040/1319] eta: 0:12:13 lr: 4.4518037654287396e-07 loss: 0.0309 (0.0316) time: 2.6463 data: 0.0059 max mem: 33369 +Epoch: [39] [1050/1319] eta: 0:11:47 lr: 4.3074179227215756e-07 loss: 0.0275 (0.0316) time: 2.6286 data: 0.0060 max mem: 33369 +Epoch: [39] [1060/1319] eta: 0:11:21 lr: 4.162492188647174e-07 loss: 0.0285 (0.0316) time: 2.6312 data: 0.0061 max mem: 33369 +Epoch: [39] [1070/1319] eta: 0:10:54 lr: 4.01700348854669e-07 loss: 0.0285 (0.0316) time: 2.6378 data: 0.0061 max mem: 33369 +Epoch: [39] [1080/1319] eta: 0:10:28 lr: 3.8709267884030336e-07 loss: 0.0267 (0.0316) time: 2.6465 data: 0.0060 max mem: 33369 +Epoch: [39] [1090/1319] eta: 0:10:02 lr: 3.724234838815835e-07 loss: 0.0324 (0.0316) time: 2.6119 data: 0.0059 max mem: 33369 +Epoch: [39] [1100/1319] eta: 0:09:35 lr: 3.5768978727688177e-07 loss: 0.0322 (0.0316) time: 2.6016 data: 0.0060 max mem: 33369 +Epoch: [39] [1110/1319] eta: 0:09:09 lr: 3.428883246336122e-07 loss: 0.0283 (0.0316) time: 2.6126 data: 0.0061 max mem: 33369 +Epoch: [39] [1120/1319] eta: 0:08:43 lr: 3.280155008272766e-07 loss: 0.0290 (0.0316) time: 2.6156 data: 0.0062 max mem: 33369 +Epoch: [39] [1130/1319] eta: 0:08:16 lr: 3.1306733800860497e-07 loss: 0.0288 (0.0316) time: 2.6245 data: 0.0060 max mem: 33369 +Epoch: [39] [1140/1319] eta: 0:07:50 lr: 2.9803941221786203e-07 loss: 0.0276 (0.0316) time: 2.6251 data: 0.0060 max mem: 33369 +Epoch: [39] [1150/1319] eta: 0:07:24 lr: 2.829267753240405e-07 loss: 0.0305 (0.0316) time: 2.6165 data: 0.0061 max mem: 33369 +Epoch: [39] [1160/1319] eta: 0:06:57 lr: 2.677238578071334e-07 loss: 0.0283 (0.0316) time: 2.5999 data: 0.0059 max mem: 33369 +Epoch: [39] [1170/1319] eta: 0:06:31 lr: 2.524243461593822e-07 loss: 0.0256 (0.0316) time: 2.6137 data: 0.0059 max mem: 33369 +Epoch: [39] [1180/1319] eta: 0:06:05 lr: 2.370210260957732e-07 loss: 0.0290 (0.0316) time: 2.6199 data: 0.0059 max mem: 33369 +Epoch: [39] [1190/1319] eta: 0:05:39 lr: 2.2150557883672493e-07 loss: 0.0302 (0.0316) time: 2.6161 data: 0.0059 max mem: 33369 +Epoch: [39] [1200/1319] eta: 0:05:12 lr: 2.058683115970694e-07 loss: 0.0289 (0.0316) time: 2.6414 data: 0.0058 max mem: 33369 +Epoch: [39] [1210/1319] eta: 0:04:46 lr: 1.9009779355624344e-07 loss: 0.0259 (0.0315) time: 2.6586 data: 0.0058 max mem: 33369 +Epoch: [39] [1220/1319] eta: 0:04:20 lr: 1.7418035215766808e-07 loss: 0.0265 (0.0315) time: 2.6436 data: 0.0058 max mem: 33369 +Epoch: [39] [1230/1319] eta: 0:03:53 lr: 1.5809935607220197e-07 loss: 0.0265 (0.0315) time: 2.6160 data: 0.0058 max mem: 33369 +Epoch: [39] [1240/1319] eta: 0:03:27 lr: 1.4183415922236583e-07 loss: 0.0315 (0.0315) time: 2.6144 data: 0.0059 max mem: 33369 +Epoch: [39] [1250/1319] eta: 0:03:01 lr: 1.2535848000328487e-07 loss: 0.0315 (0.0315) time: 2.6431 data: 0.0060 max mem: 33369 +Epoch: [39] [1260/1319] eta: 0:02:35 lr: 1.0863778202227116e-07 loss: 0.0325 (0.0315) time: 2.6283 data: 0.0060 max mem: 33369 +Epoch: [39] [1270/1319] eta: 0:02:08 lr: 9.162475150165058e-08 loss: 0.0305 (0.0315) time: 2.6239 data: 0.0060 max mem: 33369 +Epoch: [39] [1280/1319] eta: 0:01:42 lr: 7.425076510067331e-08 loss: 0.0293 (0.0315) time: 2.6287 data: 0.0062 max mem: 33369 +Epoch: [39] [1290/1319] eta: 0:01:16 lr: 5.640763927216541e-08 loss: 0.0291 (0.0315) time: 2.6405 data: 0.0060 max mem: 33369 +Epoch: [39] [1300/1319] eta: 0:00:49 lr: 3.790015191412361e-08 loss: 0.0288 (0.0315) time: 2.6484 data: 0.0058 max mem: 33369 +Epoch: [39] [1310/1319] eta: 0:00:23 lr: 1.8267397722216235e-08 loss: 0.0282 (0.0315) time: 2.6251 data: 0.0058 max mem: 33369 +Epoch: [39] Total time: 0:57:48 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 1:51:21 time: 2.5968 data: 2.5019 max mem: 33369 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 100/2573] eta: 0:04:01 time: 0.0713 data: 0.0011 max mem: 33369 +Test: [ 200/2573] eta: 0:03:23 time: 0.0731 data: 0.0012 max mem: 33369 +Test: [ 300/2573] eta: 0:03:04 time: 0.0749 data: 0.0011 max mem: 33369 +Test: [ 400/2573] eta: 0:02:52 time: 0.0749 data: 0.0011 max mem: 33369 +Test: [ 500/2573] eta: 0:02:41 time: 0.0733 data: 0.0011 max mem: 33369 +Test: [ 600/2573] eta: 0:02:32 time: 0.0734 data: 0.0011 max mem: 33369 +Test: [ 700/2573] eta: 0:02:24 time: 0.0735 data: 0.0011 max mem: 33369 +Test: [ 800/2573] eta: 0:02:16 time: 0.0769 data: 0.0011 max mem: 33369 +Test: [ 900/2573] eta: 0:02:08 time: 0.0737 data: 0.0011 max mem: 33369 +Test: [1000/2573] eta: 0:02:00 time: 0.0738 data: 0.0011 max mem: 33369 +Test: [1100/2573] eta: 0:01:52 time: 0.0737 data: 0.0011 max mem: 33369 +Test: [1200/2573] eta: 0:01:44 time: 0.0737 data: 0.0011 max mem: 33369 +Test: [1300/2573] eta: 0:01:36 time: 0.0739 data: 0.0011 max mem: 33369 +Test: [1400/2573] eta: 0:01:28 time: 0.0722 data: 0.0011 max mem: 33369 +Test: [1500/2573] eta: 0:01:21 time: 0.0738 data: 0.0011 max mem: 33369 +Test: [1600/2573] eta: 0:01:13 time: 0.0772 data: 0.0011 max mem: 33369 +Test: [1700/2573] eta: 0:01:05 time: 0.0721 data: 0.0011 max mem: 33369 +Test: [1800/2573] eta: 0:00:58 time: 0.0755 data: 0.0011 max mem: 33369 +Test: [1900/2573] eta: 0:00:50 time: 0.0722 data: 0.0011 max mem: 33369 +Test: [2000/2573] eta: 0:00:42 time: 0.0739 data: 0.0011 max mem: 33369 +Test: [2100/2573] eta: 0:00:35 time: 0.0754 data: 0.0011 max mem: 33369 +Test: [2200/2573] eta: 0:00:27 time: 0.0756 data: 0.0011 max mem: 33369 +Test: [2300/2573] eta: 0:00:20 time: 0.0756 data: 0.0011 max mem: 33369 +Test: [2400/2573] eta: 0:00:12 time: 0.0705 data: 0.0011 max mem: 33369 +Test: [2500/2573] eta: 0:00:05 time: 0.0740 data: 0.0011 max mem: 33369 +Test: Total time: 0:03:12 +Final results: +Mean IoU is 65.38 + + precision@0.5 = 73.51 + precision@0.6 = 68.34 + precision@0.7 = 62.21 + precision@0.8 = 51.47 + precision@0.9 = 26.02 + overall IoU = 62.42 + +Average object IoU 65.3830484219557 +Overall IoU 62.42093276977539 +Training time 1 day, 16:42:30 +./scripts/baseline_test_lr.sh: line 54: unexpected EOF while looking for matching `"' +./scripts/baseline_test_lr.sh: line 65: syntax error: unexpected end of file diff --git a/LAVT-RIS/logs/lavt_gsds_best.txt b/LAVT-RIS/logs/lavt_gsds_best.txt new file mode 100644 index 0000000000000000000000000000000000000000..0d9c9448a2f4acc80c4dd750753f36bc0ba7f41f --- /dev/null +++ b/LAVT-RIS/logs/lavt_gsds_best.txt @@ -0,0 +1,91 @@ +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/timm/models/layers/__init__.py:48: FutureWarning: Importing from timm.models.layers is deprecated, please import via timm.layers + warnings.warn(f"Importing from {__name__} is deprecated, please import via timm.layers", FutureWarning) +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torch/functional.py:478: UserWarning: torch.meshgrid: in an upcoming release, it will be required to pass the indexing argument. (Triggered internally at ../aten/src/ATen/native/TensorShape.cpp:2894.) + return _VF.meshgrid(tensors, **kwargs) # type: ignore[attr-defined] +Image size: 480 +loading dataset refcocog into memory... +creating index... +index created. +DONE (t=6.45s) +lavt_one +Window size 12! +Randomly initialize Multi-modal Swin Transformer weights. +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 2:27:43 time: 3.4448 data: 1.1081 max mem: 1021 +Test: [ 100/2573] eta: 0:07:45 time: 0.1553 data: 0.0019 max mem: 1021 +Test: [ 200/2573] eta: 0:06:55 time: 0.1594 data: 0.0017 max mem: 1021 +Test: [ 300/2573] eta: 0:06:23 time: 0.1637 data: 0.0016 max mem: 1021 +Test: [ 400/2573] eta: 0:06:01 time: 0.1643 data: 0.0017 max mem: 1021 +Test: [ 500/2573] eta: 0:05:42 time: 0.1610 data: 0.0017 max mem: 1021 +Test: [ 600/2573] eta: 0:05:25 time: 0.1616 data: 0.0017 max mem: 1021 +Test: [ 700/2573] eta: 0:05:09 time: 0.1610 data: 0.0017 max mem: 1021 +Test: [ 800/2573] eta: 0:04:52 time: 0.1702 data: 0.0017 max mem: 1021 +Test: [ 900/2573] eta: 0:04:35 time: 0.1617 data: 0.0017 max mem: 1021 +Test: [1000/2573] eta: 0:04:18 time: 0.1618 data: 0.0017 max mem: 1021 +Test: [1100/2573] eta: 0:04:02 time: 0.1623 data: 0.0017 max mem: 1021 +Test: [1200/2573] eta: 0:03:45 time: 0.1617 data: 0.0016 max mem: 1021 +Test: [1300/2573] eta: 0:03:29 time: 0.1617 data: 0.0016 max mem: 1021 +Test: [1400/2573] eta: 0:03:12 time: 0.1584 data: 0.0017 max mem: 1021 +Test: [1500/2573] eta: 0:02:55 time: 0.1628 data: 0.0017 max mem: 1021 +Test: [1600/2573] eta: 0:02:39 time: 0.1711 data: 0.0017 max mem: 1021 +Test: [1700/2573] eta: 0:02:23 time: 0.1580 data: 0.0016 max mem: 1021 +Test: [1800/2573] eta: 0:02:06 time: 0.1667 data: 0.0017 max mem: 1021 +Test: [1900/2573] eta: 0:01:49 time: 0.1574 data: 0.0017 max mem: 1021 +Test: [2000/2573] eta: 0:01:33 time: 0.1618 data: 0.0017 max mem: 1021 +Test: [2100/2573] eta: 0:01:17 time: 0.1664 data: 0.0017 max mem: 1021 +Test: [2200/2573] eta: 0:01:00 time: 0.1665 data: 0.0016 max mem: 1021 +Test: [2300/2573] eta: 0:00:44 time: 0.1663 data: 0.0017 max mem: 1021 +Test: [2400/2573] eta: 0:00:28 time: 0.1534 data: 0.0016 max mem: 1021 +Test: [2500/2573] eta: 0:00:11 time: 0.1630 data: 0.0019 max mem: 1021 +Test: Total time: 0:06:59 +Final results: +Mean IoU is 65.76 + + precision@0.5 = 74.16 + precision@0.6 = 69.46 + precision@0.7 = 63.17 + precision@0.8 = 52.31 + precision@0.9 = 26.49 + overall IoU = 63.22 + +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/timm/models/layers/__init__.py:48: FutureWarning: Importing from timm.models.layers is deprecated, please import via timm.layers + warnings.warn(f"Importing from {__name__} is deprecated, please import via timm.layers", FutureWarning) +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torch/functional.py:478: UserWarning: torch.meshgrid: in an upcoming release, it will be required to pass the indexing argument. (Triggered internally at ../aten/src/ATen/native/TensorShape.cpp:2894.) + return _VF.meshgrid(tensors, **kwargs) # type: ignore[attr-defined] +Image size: 480 +Easy & Hard Example Experiments - dataset : refcocog, split : static +loading dataset refcocog into memory... +creating index... +index created. +DONE (t=6.49s) +lavt_one +Window size 12! +Randomly initialize Multi-modal Swin Transformer weights. +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/151] eta: 0:08:25 time: 3.3473 data: 1.0557 max mem: 1021 +Test: [100/151] eta: 0:00:06 time: 0.0863 data: 0.0017 max mem: 1021 +Test: Total time: 0:00:16 +Final results: +Mean IoU is 73.23 + + precision@0.5 = 83.44 + precision@0.6 = 80.13 + precision@0.7 = 76.82 + precision@0.8 = 72.19 + precision@0.9 = 39.07 + overall IoU = 70.52 + diff --git a/LAVT-RIS/logs/lavt_gsds_best2.txt b/LAVT-RIS/logs/lavt_gsds_best2.txt new file mode 100644 index 0000000000000000000000000000000000000000..820a47a3b47da55cfd56fb133bc816a6b6adf778 --- /dev/null +++ b/LAVT-RIS/logs/lavt_gsds_best2.txt @@ -0,0 +1,116 @@ +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/timm/models/layers/__init__.py:48: FutureWarning: Importing from timm.models.layers is deprecated, please import via timm.layers + warnings.warn(f"Importing from {__name__} is deprecated, please import via timm.layers", FutureWarning) +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torch/functional.py:478: UserWarning: torch.meshgrid: in an upcoming release, it will be required to pass the indexing argument. (Triggered internally at ../aten/src/ATen/native/TensorShape.cpp:2894.) + return _VF.meshgrid(tensors, **kwargs) # type: ignore[attr-defined] +Image size: 480 +loading dataset refcocog into memory... +creating index... +index created. +DONE (t=6.57s) +lavt_one +Window size 12! +Randomly initialize Multi-modal Swin Transformer weights. +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/5023] eta: 4:35:29 time: 3.2908 data: 0.9735 max mem: 1021 +Test: [ 100/5023] eta: 0:15:52 time: 0.1678 data: 0.0017 max mem: 1021 +Test: [ 200/5023] eta: 0:14:13 time: 0.1593 data: 0.0017 max mem: 1021 +Test: [ 300/5023] eta: 0:13:38 time: 0.1646 data: 0.0017 max mem: 1021 +Test: [ 400/5023] eta: 0:13:07 time: 0.1618 data: 0.0017 max mem: 1021 +Test: [ 500/5023] eta: 0:12:44 time: 0.1660 data: 0.0017 max mem: 1021 +Test: [ 600/5023] eta: 0:12:24 time: 0.1698 data: 0.0017 max mem: 1021 +Test: [ 700/5023] eta: 0:12:04 time: 0.1577 data: 0.0017 max mem: 1021 +Test: [ 800/5023] eta: 0:11:47 time: 0.1659 data: 0.0016 max mem: 1021 +Test: [ 900/5023] eta: 0:11:30 time: 0.1665 data: 0.0017 max mem: 1021 +Test: [1000/5023] eta: 0:11:11 time: 0.1666 data: 0.0018 max mem: 1021 +Test: [1100/5023] eta: 0:10:53 time: 0.1623 data: 0.0017 max mem: 1021 +Test: [1200/5023] eta: 0:10:37 time: 0.1665 data: 0.0016 max mem: 1021 +Test: [1300/5023] eta: 0:10:19 time: 0.1634 data: 0.0020 max mem: 1021 +Test: [1400/5023] eta: 0:10:01 time: 0.1546 data: 0.0017 max mem: 1021 +Test: [1500/5023] eta: 0:09:45 time: 0.1664 data: 0.0018 max mem: 1021 +Test: [1600/5023] eta: 0:09:27 time: 0.1630 data: 0.0018 max mem: 1021 +Test: [1700/5023] eta: 0:09:10 time: 0.1624 data: 0.0017 max mem: 1021 +Test: [1800/5023] eta: 0:08:54 time: 0.1672 data: 0.0019 max mem: 1021 +Test: [1900/5023] eta: 0:08:37 time: 0.1668 data: 0.0018 max mem: 1021 +Test: [2000/5023] eta: 0:08:20 time: 0.1706 data: 0.0017 max mem: 1021 +Test: [2100/5023] eta: 0:08:03 time: 0.1546 data: 0.0016 max mem: 1021 +Test: [2200/5023] eta: 0:07:46 time: 0.1504 data: 0.0018 max mem: 1021 +Test: [2300/5023] eta: 0:07:29 time: 0.1715 data: 0.0018 max mem: 1021 +Test: [2400/5023] eta: 0:07:13 time: 0.1628 data: 0.0017 max mem: 1021 +Test: [2500/5023] eta: 0:06:56 time: 0.1668 data: 0.0017 max mem: 1021 +Test: [2600/5023] eta: 0:06:40 time: 0.1626 data: 0.0017 max mem: 1021 +Test: [2700/5023] eta: 0:06:23 time: 0.1672 data: 0.0019 max mem: 1021 +Test: [2800/5023] eta: 0:06:07 time: 0.1666 data: 0.0019 max mem: 1021 +Test: [2900/5023] eta: 0:05:50 time: 0.1693 data: 0.0016 max mem: 1021 +Test: [3000/5023] eta: 0:05:33 time: 0.1656 data: 0.0016 max mem: 1021 +Test: [3100/5023] eta: 0:05:17 time: 0.1689 data: 0.0016 max mem: 1021 +Test: [3200/5023] eta: 0:05:00 time: 0.1612 data: 0.0016 max mem: 1021 +Test: [3300/5023] eta: 0:04:43 time: 0.1610 data: 0.0016 max mem: 1021 +Test: [3400/5023] eta: 0:04:27 time: 0.1450 data: 0.0016 max mem: 1021 +Test: [3500/5023] eta: 0:04:10 time: 0.1572 data: 0.0016 max mem: 1021 +Test: [3600/5023] eta: 0:03:53 time: 0.1648 data: 0.0016 max mem: 1021 +Test: [3700/5023] eta: 0:03:37 time: 0.1651 data: 0.0016 max mem: 1021 +Test: [3800/5023] eta: 0:03:21 time: 0.1691 data: 0.0018 max mem: 1021 +Test: [3900/5023] eta: 0:03:04 time: 0.1574 data: 0.0016 max mem: 1021 +Test: [4000/5023] eta: 0:02:48 time: 0.1526 data: 0.0016 max mem: 1021 +Test: [4100/5023] eta: 0:02:31 time: 0.1569 data: 0.0016 max mem: 1021 +Test: [4200/5023] eta: 0:02:14 time: 0.1611 data: 0.0016 max mem: 1021 +Test: [4300/5023] eta: 0:01:58 time: 0.1651 data: 0.0016 max mem: 1021 +Test: [4400/5023] eta: 0:01:41 time: 0.1569 data: 0.0016 max mem: 1021 +Test: [4500/5023] eta: 0:01:25 time: 0.1529 data: 0.0016 max mem: 1021 +Test: [4600/5023] eta: 0:01:09 time: 0.1493 data: 0.0016 max mem: 1021 +Test: [4700/5023] eta: 0:00:52 time: 0.1653 data: 0.0016 max mem: 1021 +Test: [4800/5023] eta: 0:00:36 time: 0.1614 data: 0.0016 max mem: 1021 +Test: [4900/5023] eta: 0:00:20 time: 0.1609 data: 0.0016 max mem: 1021 +Test: [5000/5023] eta: 0:00:03 time: 0.1655 data: 0.0016 max mem: 1021 +Test: Total time: 0:13:40 +Final results: +Mean IoU is 65.23 + + precision@0.5 = 73.42 + precision@0.6 = 68.66 + precision@0.7 = 61.96 + precision@0.8 = 51.37 + precision@0.9 = 26.91 + overall IoU = 63.21 + +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/timm/models/layers/__init__.py:48: FutureWarning: Importing from timm.models.layers is deprecated, please import via timm.layers + warnings.warn(f"Importing from {__name__} is deprecated, please import via timm.layers", FutureWarning) +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torch/functional.py:478: UserWarning: torch.meshgrid: in an upcoming release, it will be required to pass the indexing argument. (Triggered internally at ../aten/src/ATen/native/TensorShape.cpp:2894.) + return _VF.meshgrid(tensors, **kwargs) # type: ignore[attr-defined] +Image size: 480 +Easy & Hard Example Experiments - dataset : refcocog, split : motion +loading dataset refcocog into memory... +creating index... +index created. +DONE (t=6.31s) +lavt_one +Window size 12! +Randomly initialize Multi-modal Swin Transformer weights. +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/151] eta: 0:08:15 time: 3.2817 data: 1.0697 max mem: 1021 +Test: [100/151] eta: 0:00:05 time: 0.0856 data: 0.0016 max mem: 1021 +Test: Total time: 0:00:16 +Final results: +Mean IoU is 60.97 + + precision@0.5 = 69.54 + precision@0.6 = 65.56 + precision@0.7 = 58.94 + precision@0.8 = 57.62 + precision@0.9 = 33.11 + overall IoU = 57.00 + diff --git a/LAVT-RIS/logs/lavt_motion.txt b/LAVT-RIS/logs/lavt_motion.txt new file mode 100644 index 0000000000000000000000000000000000000000..1ec2a951164706fb90b049f4ed525dcf6d0eff6f --- /dev/null +++ b/LAVT-RIS/logs/lavt_motion.txt @@ -0,0 +1,34 @@ +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/timm/models/layers/__init__.py:48: FutureWarning: Importing from timm.models.layers is deprecated, please import via timm.layers + warnings.warn(f"Importing from {__name__} is deprecated, please import via timm.layers", FutureWarning) +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torch/functional.py:478: UserWarning: torch.meshgrid: in an upcoming release, it will be required to pass the indexing argument. (Triggered internally at ../aten/src/ATen/native/TensorShape.cpp:2894.) + return _VF.meshgrid(tensors, **kwargs) # type: ignore[attr-defined] +Image size: 480 +Easy & Hard Example Experiments - dataset : refcocog, split : motion +loading dataset refcocog into memory... +creating index... +index created. +DONE (t=6.27s) +lavt_one +Window size 12! +Randomly initialize Multi-modal Swin Transformer weights. +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/151] eta: 0:08:12 time: 3.2629 data: 0.9832 max mem: 1021 +Test: [100/151] eta: 0:00:05 time: 0.0850 data: 0.0017 max mem: 1021 +Test: Total time: 0:00:16 +Final results: +Mean IoU is 55.05 + + precision@0.5 = 62.25 + precision@0.6 = 58.28 + precision@0.7 = 54.97 + precision@0.8 = 50.33 + precision@0.9 = 27.15 + overall IoU = 47.50 + diff --git a/LAVT-RIS/logs/lavt_orig_mostat.txt b/LAVT-RIS/logs/lavt_orig_mostat.txt new file mode 100644 index 0000000000000000000000000000000000000000..ebcd1f62cd7dc9a69c869973d8288d2caac508d7 --- /dev/null +++ b/LAVT-RIS/logs/lavt_orig_mostat.txt @@ -0,0 +1,95 @@ +Image size: 480 +Easy & Hard Example Experiments - dataset : refcocog, split : static +loading dataset refcocog into memory... +creating index... +index created. +DONE (t=6.30s) +lavt +Window size 12! +Randomly initialize Multi-modal Swin Transformer weights. +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Traceback (most recent call last): + File "/data2/projects/chaeyun/LAVT-RIS/test_mostat.py", line 139, in + main(args) + File "/data2/projects/chaeyun/LAVT-RIS/test_mostat.py", line 131, in main + evaluate(model, data_loader_test, bert_model, device=device) + File "/data2/projects/chaeyun/LAVT-RIS/test_mostat.py", line 57, in evaluate + output = model(image, embedding, l_mask=attentions[:, :, j].unsqueeze(-1)) + File "/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torch/nn/modules/module.py", line 1130, in _call_impl + return forward_call(*input, **kwargs) +TypeError: forward() got an unexpected keyword argument 'is_train' +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/timm/models/layers/__init__.py:48: FutureWarning: Importing from timm.models.layers is deprecated, please import via timm.layers + warnings.warn(f"Importing from {__name__} is deprecated, please import via timm.layers", FutureWarning) +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torch/functional.py:478: UserWarning: torch.meshgrid: in an upcoming release, it will be required to pass the indexing argument. (Triggered internally at ../aten/src/ATen/native/TensorShape.cpp:2894.) + return _VF.meshgrid(tensors, **kwargs) # type: ignore[attr-defined] +Image size: 480 +Easy & Hard Example Experiments - dataset : refcocog, split : motion +loading dataset refcocog into memory... +creating index... +index created. +DONE (t=6.27s) +lavt +Window size 12! +Randomly initialize Multi-modal Swin Transformer weights. +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/151] eta: 0:08:16 time: 3.2878 data: 1.0710 max mem: 1021 +Test: [100/151] eta: 0:00:05 time: 0.0859 data: 0.0016 max mem: 1021 +Test: Total time: 0:00:16 +Final results: +Mean IoU is 55.93 + + precision@0.5 = 62.25 + precision@0.6 = 58.94 + precision@0.7 = 55.63 + precision@0.8 = 48.34 + precision@0.9 = 25.83 + overall IoU = 49.78 + +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/timm/models/layers/__init__.py:48: FutureWarning: Importing from timm.models.layers is deprecated, please import via timm.layers + warnings.warn(f"Importing from {__name__} is deprecated, please import via timm.layers", FutureWarning) +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torch/functional.py:478: UserWarning: torch.meshgrid: in an upcoming release, it will be required to pass the indexing argument. (Triggered internally at ../aten/src/ATen/native/TensorShape.cpp:2894.) + return _VF.meshgrid(tensors, **kwargs) # type: ignore[attr-defined] +Image size: 480 +Easy & Hard Example Experiments - dataset : refcocog, split : static +loading dataset refcocog into memory... +creating index... +index created. +DONE (t=6.28s) +lavt +Window size 12! +Randomly initialize Multi-modal Swin Transformer weights. +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/151] eta: 0:07:52 time: 3.1324 data: 0.9669 max mem: 1021 +Test: [100/151] eta: 0:00:05 time: 0.0852 data: 0.0016 max mem: 1021 +Test: Total time: 0:00:16 +Final results: +Mean IoU is 72.59 + + precision@0.5 = 82.78 + precision@0.6 = 81.46 + precision@0.7 = 75.50 + precision@0.8 = 66.89 + precision@0.9 = 27.81 + overall IoU = 70.63 + diff --git a/LAVT-RIS/logs/lavt_refzom_repro_bs16.log b/LAVT-RIS/logs/lavt_refzom_repro_bs16.log new file mode 100644 index 0000000000000000000000000000000000000000..1eaabc2f08387e2998dcfd3ff8a5053bf407d9dc --- /dev/null +++ b/LAVT-RIS/logs/lavt_refzom_repro_bs16.log @@ -0,0 +1,22299 @@ +/home/chaeyun/.conda/envs/risall/lib/python3.9/site-packages/timm/models/layers/__init__.py:48: FutureWarning: Importing from timm.models.layers is deprecated, please import via timm.layers + warnings.warn(f"Importing from {__name__} is deprecated, please import via timm.layers", FutureWarning) +Local Rank: 0, World Size: 1 +RANK and WORLD_SIZE in environment: 0/1 +Image size: 480 +metric learning flag : False +Namespace(amsgrad=False, batch_size=16, bert_tokenizer='bert-base-uncased', ck_bert='bert-base-uncased', dataset='ref-zom', ddp_trained_weights=False, device='cuda:0', epochs=40, fusion_drop=0.0, img_size=480, lr=5e-05, mha='', model='lavt_one', model_id='refzom_lavt_bs16_repro', output_dir='./models/refzom_lavt_bs16_repro', pin_mem=False, pretrained_swin_weights='./pretrained_weights/swin_base_patch4_window12_384_22k.pth', print_freq=10, refer_data_root='./refer/data/', resume='', split='test', splitBy='final', swin_type='base', weight_decay=0.01, window12=False, workers=8, metric_learning=False, metric_loss_weight=0.1, metric_mode='hardpos_rev3', exclude_multiobj=False, hn_prob=0.0, hp_selection='naive', margin_value=10, temperature=0.05, addzero=False, local_rank=0) +loading dataset ref-zom into memory... +loading dataset split final +creating index... +index created. +DONE (t=6.09s) +loading dataset ref-zom into memory... +loading dataset split final +creating index... +index created. +DONE (t=6.79s) +local rank 0 / global rank 0 successfully built train dataset. +/home/chaeyun/.conda/envs/risall/lib/python3.9/site-packages/torch/utils/data/dataloader.py:557: UserWarning: This DataLoader will create 8 worker processes in total. Our suggested max number of worker in current system is 4, which is smaller than what this DataLoader is going to create. Please be aware that excessive worker creation might get DataLoader running slow or even freeze, lower the worker number to avoid potential slowness/freeze if necessary. + warnings.warn(_create_warning_msg( +lavt_one +Window size 12! +/home/chaeyun/.conda/envs/risall/lib/python3.9/site-packages/torch/functional.py:504: UserWarning: torch.meshgrid: in an upcoming release, it will be required to pass the indexing argument. (Triggered internally at ../aten/src/ATen/native/TensorShape.cpp:3526.) + return _VF.meshgrid(tensors, **kwargs) # type: ignore[attr-defined] +Initializing Multi-modal Swin Transformer weights from ./pretrained_weights/swin_base_patch4_window12_384_22k.pth +Epoch: [0] [ 0/4276] eta: 11:00:22 lr: 4.999973690357136e-05 loss: 0.8191 (0.8191) time: 9.2662 data: 2.3629 max mem: 31199 +Epoch: [0] [ 10/4276] eta: 4:11:30 lr: 4.9997105930824546e-05 loss: 0.7876 (0.7858) time: 3.5374 data: 0.2208 max mem: 33293 +Epoch: [0] [ 20/4276] eta: 3:51:48 lr: 4.999447494269448e-05 loss: 0.7170 (0.7298) time: 2.9681 data: 0.0064 max mem: 33293 +Epoch: [0] [ 30/4276] eta: 3:44:43 lr: 4.9991843939180193e-05 loss: 0.6004 (0.6728) time: 2.9764 data: 0.0067 max mem: 33293 +Epoch: [0] [ 40/4276] eta: 3:40:47 lr: 4.998921292028069e-05 loss: 0.4740 (0.6149) time: 2.9795 data: 0.0069 max mem: 33293 +Epoch: [0] [ 50/4276] eta: 3:37:53 lr: 4.998658188599496e-05 loss: 0.4142 (0.5703) time: 2.9664 data: 0.0068 max mem: 33293 +Epoch: [0] [ 60/4276] eta: 3:35:42 lr: 4.9983950836322044e-05 loss: 0.3817 (0.5379) time: 2.9524 data: 0.0068 max mem: 33293 +Epoch: [0] [ 70/4276] eta: 3:34:10 lr: 4.998131977126093e-05 loss: 0.3365 (0.5087) time: 2.9577 data: 0.0070 max mem: 33293 +Epoch: [0] [ 80/4276] eta: 3:32:50 lr: 4.997868869081064e-05 loss: 0.3426 (0.4882) time: 2.9632 data: 0.0070 max mem: 33293 +Epoch: [0] [ 90/4276] eta: 3:31:46 lr: 4.997605759497018e-05 loss: 0.3399 (0.4719) time: 2.9650 data: 0.0067 max mem: 33293 +Epoch: [0] [ 100/4276] eta: 3:30:40 lr: 4.997342648373855e-05 loss: 0.3237 (0.4614) time: 2.9590 data: 0.0067 max mem: 33293 +Epoch: [0] [ 110/4276] eta: 3:29:21 lr: 4.997079535711478e-05 loss: 0.3239 (0.4483) time: 2.9232 data: 0.0066 max mem: 33293 +Epoch: [0] [ 120/4276] eta: 3:28:09 lr: 4.996816421509786e-05 loss: 0.2960 (0.4366) time: 2.8957 data: 0.0064 max mem: 33293 +Epoch: [0] [ 130/4276] eta: 3:27:13 lr: 4.996553305768681e-05 loss: 0.2965 (0.4286) time: 2.9090 data: 0.0065 max mem: 33293 +Epoch: [0] [ 140/4276] eta: 3:26:18 lr: 4.996290188488064e-05 loss: 0.3104 (0.4198) time: 2.9178 data: 0.0064 max mem: 33294 +Epoch: [0] [ 150/4276] eta: 3:25:27 lr: 4.996027069667836e-05 loss: 0.2984 (0.4114) time: 2.9146 data: 0.0065 max mem: 33294 +Epoch: [0] [ 160/4276] eta: 3:24:36 lr: 4.9957639493078964e-05 loss: 0.2983 (0.4050) time: 2.9115 data: 0.0066 max mem: 33294 +Epoch: [0] [ 170/4276] eta: 3:23:47 lr: 4.995500827408148e-05 loss: 0.3237 (0.4007) time: 2.9046 data: 0.0066 max mem: 33294 +Epoch: [0] [ 180/4276] eta: 3:23:05 lr: 4.99523770396849e-05 loss: 0.3311 (0.3968) time: 2.9123 data: 0.0065 max mem: 33294 +Epoch: [0] [ 190/4276] eta: 3:22:20 lr: 4.994974578988825e-05 loss: 0.3183 (0.3924) time: 2.9124 data: 0.0066 max mem: 33294 +Epoch: [0] [ 200/4276] eta: 3:21:37 lr: 4.994711452469053e-05 loss: 0.3114 (0.3884) time: 2.9046 data: 0.0066 max mem: 33294 +Epoch: [0] [ 210/4276] eta: 3:20:56 lr: 4.994448324409074e-05 loss: 0.3062 (0.3844) time: 2.9072 data: 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2.9547 data: 0.0066 max mem: 33294 +Epoch: [0] [ 300/4276] eta: 3:15:51 lr: 4.9920801025436183e-05 loss: 0.2614 (0.3556) time: 2.9559 data: 0.0066 max mem: 33295 +Epoch: [0] [ 310/4276] eta: 3:15:15 lr: 4.991816959076121e-05 loss: 0.2614 (0.3534) time: 2.9295 data: 0.0066 max mem: 33295 +Epoch: [0] [ 320/4276] eta: 3:14:44 lr: 4.991553814067325e-05 loss: 0.2774 (0.3518) time: 2.9210 data: 0.0065 max mem: 33295 +Epoch: [0] [ 330/4276] eta: 3:14:10 lr: 4.991290667517133e-05 loss: 0.2774 (0.3494) time: 2.9277 data: 0.0064 max mem: 33295 +Epoch: [0] [ 340/4276] eta: 3:13:40 lr: 4.9910275194254444e-05 loss: 0.2652 (0.3471) time: 2.9336 data: 0.0064 max mem: 33295 +Epoch: [0] [ 350/4276] eta: 3:13:08 lr: 4.990764369792159e-05 loss: 0.2645 (0.3451) time: 2.9404 data: 0.0064 max mem: 33295 +Epoch: [0] [ 360/4276] eta: 3:12:35 lr: 4.990501218617179e-05 loss: 0.2670 (0.3439) time: 2.9270 data: 0.0064 max mem: 33295 +Epoch: [0] [ 370/4276] eta: 3:12:04 lr: 4.9902380659004044e-05 loss: 0.2592 (0.3417) time: 2.9307 data: 0.0064 max mem: 33295 +Epoch: [0] [ 380/4276] eta: 3:11:36 lr: 4.989974911641736e-05 loss: 0.2384 (0.3399) time: 2.9501 data: 0.0064 max mem: 33295 +Epoch: [0] [ 390/4276] eta: 3:11:04 lr: 4.9897117558410747e-05 loss: 0.2829 (0.3387) time: 2.9420 data: 0.0064 max mem: 33295 +Epoch: [0] [ 400/4276] eta: 3:10:31 lr: 4.98944859849832e-05 loss: 0.2791 (0.3372) time: 2.9206 data: 0.0066 max mem: 33295 +Epoch: [0] [ 410/4276] eta: 3:09:59 lr: 4.989185439613374e-05 loss: 0.2606 (0.3355) time: 2.9218 data: 0.0066 max mem: 33295 +Epoch: [0] [ 420/4276] eta: 3:09:27 lr: 4.9889222791861365e-05 loss: 0.2738 (0.3348) time: 2.9215 data: 0.0063 max mem: 33295 +Epoch: [0] [ 430/4276] eta: 3:08:54 lr: 4.988659117216507e-05 loss: 0.2746 (0.3334) time: 2.9149 data: 0.0065 max mem: 33295 +Epoch: [0] [ 440/4276] eta: 3:08:23 lr: 4.988395953704388e-05 loss: 0.2671 (0.3320) time: 2.9166 data: 0.0068 max mem: 33295 +Epoch: [0] [ 450/4276] eta: 3:07:50 lr: 4.988132788649679e-05 loss: 0.2588 (0.3309) time: 2.9128 data: 0.0065 max mem: 33295 +Epoch: [0] [ 460/4276] eta: 3:07:21 lr: 4.98786962205228e-05 loss: 0.2576 (0.3294) time: 2.9295 data: 0.0066 max mem: 33295 +Epoch: [0] [ 470/4276] eta: 3:06:52 lr: 4.987606453912093e-05 loss: 0.2499 (0.3279) time: 2.9538 data: 0.0067 max mem: 33295 +Epoch: [0] [ 480/4276] eta: 3:06:23 lr: 4.9873432842290176e-05 loss: 0.2632 (0.3269) time: 2.9486 data: 0.0064 max mem: 33295 +Epoch: [0] [ 490/4276] eta: 3:05:53 lr: 4.9870801130029545e-05 loss: 0.2707 (0.3258) time: 2.9446 data: 0.0064 max mem: 33295 +Epoch: [0] [ 500/4276] eta: 3:05:23 lr: 4.986816940233804e-05 loss: 0.2794 (0.3250) time: 2.9408 data: 0.0064 max mem: 33295 +Epoch: [0] [ 510/4276] eta: 3:04:54 lr: 4.986553765921467e-05 loss: 0.2553 (0.3235) time: 2.9471 data: 0.0065 max mem: 33295 +Epoch: [0] [ 520/4276] eta: 3:04:25 lr: 4.986290590065843e-05 loss: 0.2514 (0.3225) time: 2.9524 data: 0.0068 max mem: 33296 +Epoch: [0] [ 530/4276] eta: 3:03:56 lr: 4.986027412666833e-05 loss: 0.2751 (0.3216) time: 2.9525 data: 0.0066 max mem: 33296 +Epoch: [0] [ 540/4276] eta: 3:03:27 lr: 4.985764233724338e-05 loss: 0.2597 (0.3206) time: 2.9538 data: 0.0064 max mem: 33296 +Epoch: [0] [ 550/4276] eta: 3:02:58 lr: 4.985501053238258e-05 loss: 0.2672 (0.3200) time: 2.9545 data: 0.0065 max mem: 33296 +Epoch: [0] [ 560/4276] eta: 3:02:29 lr: 4.985237871208492e-05 loss: 0.2754 (0.3193) time: 2.9552 data: 0.0067 max mem: 33296 +Epoch: [0] [ 570/4276] eta: 3:02:00 lr: 4.984974687634943e-05 loss: 0.2663 (0.3182) time: 2.9553 data: 0.0067 max mem: 33296 +Epoch: [0] [ 580/4276] eta: 3:01:30 lr: 4.98471150251751e-05 loss: 0.2662 (0.3173) time: 2.9430 data: 0.0067 max mem: 33297 +Epoch: [0] [ 590/4276] eta: 3:01:01 lr: 4.9844483158560936e-05 loss: 0.2483 (0.3162) time: 2.9392 data: 0.0068 max mem: 33297 +Epoch: [0] [ 600/4276] eta: 3:00:31 lr: 4.984185127650594e-05 loss: 0.2539 (0.3154) time: 2.9426 data: 0.0066 max mem: 33297 +Epoch: [0] [ 610/4276] eta: 3:00:00 lr: 4.983921937900911e-05 loss: 0.2558 (0.3144) time: 2.9300 data: 0.0066 max mem: 33297 +Epoch: [0] [ 620/4276] eta: 2:59:29 lr: 4.983658746606946e-05 loss: 0.2447 (0.3136) time: 2.9264 data: 0.0067 max mem: 33297 +Epoch: [0] [ 630/4276] eta: 2:59:00 lr: 4.9833955537685986e-05 loss: 0.2843 (0.3134) time: 2.9386 data: 0.0066 max mem: 33297 +Epoch: [0] [ 640/4276] eta: 2:58:30 lr: 4.983132359385769e-05 loss: 0.2635 (0.3124) time: 2.9423 data: 0.0065 max mem: 33297 +Epoch: [0] [ 650/4276] eta: 2:58:01 lr: 4.982869163458359e-05 loss: 0.2460 (0.3115) time: 2.9446 data: 0.0065 max mem: 33297 +Epoch: [0] [ 660/4276] eta: 2:57:32 lr: 4.982605965986266e-05 loss: 0.2472 (0.3107) time: 2.9502 data: 0.0066 max mem: 33297 +Epoch: [0] [ 670/4276] eta: 2:57:01 lr: 4.982342766969393e-05 loss: 0.2508 (0.3098) time: 2.9399 data: 0.0069 max mem: 33297 +Epoch: [0] [ 680/4276] eta: 2:56:30 lr: 4.982079566407639e-05 loss: 0.2459 (0.3089) time: 2.9255 data: 0.0069 max mem: 33297 +Epoch: [0] [ 690/4276] eta: 2:56:00 lr: 4.9818163643009045e-05 loss: 0.2459 (0.3081) time: 2.9251 data: 0.0066 max mem: 33297 +Epoch: [0] [ 700/4276] eta: 2:55:30 lr: 4.98155316064909e-05 loss: 0.2499 (0.3075) time: 2.9295 data: 0.0067 max mem: 33297 +Epoch: [0] [ 710/4276] eta: 2:54:59 lr: 4.981289955452095e-05 loss: 0.2535 (0.3071) time: 2.9263 data: 0.0068 max mem: 33297 +Epoch: [0] [ 720/4276] eta: 2:54:29 lr: 4.98102674870982e-05 loss: 0.2593 (0.3064) time: 2.9213 data: 0.0068 max mem: 33297 +Epoch: [0] [ 730/4276] eta: 2:53:58 lr: 4.980763540422166e-05 loss: 0.2648 (0.3061) time: 2.9200 data: 0.0067 max mem: 33297 +Epoch: [0] [ 740/4276] eta: 2:53:29 lr: 4.9805003305890326e-05 loss: 0.2617 (0.3057) time: 2.9310 data: 0.0065 max mem: 33297 +Epoch: [0] [ 750/4276] eta: 2:53:00 lr: 4.98023711921032e-05 loss: 0.2466 (0.3050) time: 2.9544 data: 0.0067 max mem: 33297 +Epoch: [0] [ 760/4276] eta: 2:52:31 lr: 4.9799739062859274e-05 loss: 0.2323 (0.3041) time: 2.9601 data: 0.0068 max mem: 33297 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mem: 33297 +Epoch: [0] [ 850/4276] eta: 2:48:00 lr: 4.977604920394359e-05 loss: 0.2533 (0.3005) time: 2.9436 data: 0.0066 max mem: 33297 +Epoch: [0] [ 860/4276] eta: 2:47:30 lr: 4.9773416920076824e-05 loss: 0.2370 (0.3000) time: 2.9459 data: 0.0065 max mem: 33297 +Epoch: [0] [ 870/4276] eta: 2:47:01 lr: 4.9770784620742265e-05 loss: 0.2456 (0.2997) time: 2.9440 data: 0.0065 max mem: 33297 +Epoch: [0] [ 880/4276] eta: 2:46:32 lr: 4.976815230593893e-05 loss: 0.2593 (0.2993) time: 2.9451 data: 0.0067 max mem: 33297 +Epoch: [0] [ 890/4276] eta: 2:46:03 lr: 4.976551997566581e-05 loss: 0.2593 (0.2989) time: 2.9510 data: 0.0070 max mem: 33297 +Epoch: [0] [ 900/4276] eta: 2:45:34 lr: 4.976288762992192e-05 loss: 0.2581 (0.2985) time: 2.9506 data: 0.0070 max mem: 33297 +Epoch: [0] [ 910/4276] eta: 2:45:04 lr: 4.976025526870624e-05 loss: 0.2618 (0.2981) time: 2.9484 data: 0.0066 max mem: 33297 +Epoch: [0] [ 920/4276] eta: 2:44:35 lr: 4.975762289201778e-05 loss: 0.2618 (0.2976) time: 2.9486 data: 0.0068 max mem: 33297 +Epoch: [0] [ 930/4276] eta: 2:44:06 lr: 4.9754990499855535e-05 loss: 0.2517 (0.2972) time: 2.9530 data: 0.0070 max mem: 33297 +Epoch: [0] [ 940/4276] eta: 2:43:37 lr: 4.975235809221851e-05 loss: 0.2468 (0.2967) time: 2.9533 data: 0.0068 max mem: 33297 +Epoch: [0] [ 950/4276] eta: 2:43:08 lr: 4.97497256691057e-05 loss: 0.2436 (0.2961) time: 2.9510 data: 0.0068 max mem: 33297 +Epoch: [0] [ 960/4276] eta: 2:42:39 lr: 4.97470932305161e-05 loss: 0.2458 (0.2956) time: 2.9502 data: 0.0068 max mem: 33297 +Epoch: [0] [ 970/4276] eta: 2:42:09 lr: 4.974446077644872e-05 loss: 0.2496 (0.2952) time: 2.9493 data: 0.0071 max mem: 33297 +Epoch: [0] [ 980/4276] eta: 2:41:40 lr: 4.974182830690255e-05 loss: 0.2540 (0.2953) time: 2.9483 data: 0.0071 max mem: 33297 +Epoch: [0] [ 990/4276] eta: 2:41:11 lr: 4.97391958218766e-05 loss: 0.2564 (0.2948) time: 2.9488 data: 0.0070 max mem: 33297 +Epoch: [0] [1000/4276] eta: 2:40:42 lr: 4.973656332136985e-05 loss: 0.2580 (0.2945) time: 2.9516 data: 0.0072 max mem: 33297 +Epoch: [0] [1010/4276] eta: 2:40:13 lr: 4.973393080538131e-05 loss: 0.2435 (0.2940) time: 2.9514 data: 0.0068 max mem: 33297 +Epoch: [0] [1020/4276] eta: 2:39:43 lr: 4.973129827390998e-05 loss: 0.2447 (0.2937) time: 2.9430 data: 0.0067 max mem: 33297 +Epoch: [0] [1030/4276] eta: 2:39:13 lr: 4.9728665726954854e-05 loss: 0.2573 (0.2936) time: 2.9376 data: 0.0068 max mem: 33297 +Epoch: [0] [1040/4276] eta: 2:38:44 lr: 4.972603316451494e-05 loss: 0.2459 (0.2931) time: 2.9444 data: 0.0068 max mem: 33297 +Epoch: [0] [1050/4276] eta: 2:38:15 lr: 4.972340058658922e-05 loss: 0.2459 (0.2931) time: 2.9493 data: 0.0066 max mem: 33297 +Epoch: [0] [1060/4276] eta: 2:37:46 lr: 4.97207679931767e-05 loss: 0.2493 (0.2930) time: 2.9553 data: 0.0065 max mem: 33297 +Epoch: [0] [1070/4276] eta: 2:37:17 lr: 4.971813538427638e-05 loss: 0.2410 (0.2925) time: 2.9544 data: 0.0065 max mem: 33297 +Epoch: [0] [1080/4276] eta: 2:36:48 lr: 4.971550275988726e-05 loss: 0.2362 (0.2921) time: 2.9590 data: 0.0067 max mem: 33297 +Epoch: [0] [1090/4276] eta: 2:36:19 lr: 4.971287012000833e-05 loss: 0.2386 (0.2917) time: 2.9576 data: 0.0069 max mem: 33297 +Epoch: [0] [1100/4276] eta: 2:35:49 lr: 4.971023746463858e-05 loss: 0.2389 (0.2913) time: 2.9450 data: 0.0067 max mem: 33297 +Epoch: [0] [1110/4276] eta: 2:35:20 lr: 4.970760479377703e-05 loss: 0.2571 (0.2912) time: 2.9469 data: 0.0066 max mem: 33297 +Epoch: [0] [1120/4276] eta: 2:34:51 lr: 4.970497210742266e-05 loss: 0.2620 (0.2911) time: 2.9501 data: 0.0065 max mem: 33297 +Epoch: [0] [1130/4276] eta: 2:34:21 lr: 4.970233940557447e-05 loss: 0.2468 (0.2908) time: 2.9507 data: 0.0066 max mem: 33297 +Epoch: [0] [1140/4276] eta: 2:33:52 lr: 4.9699706688231465e-05 loss: 0.2450 (0.2904) time: 2.9460 data: 0.0068 max mem: 33297 +Epoch: [0] [1150/4276] eta: 2:33:23 lr: 4.9697073955392634e-05 loss: 0.2669 (0.2903) time: 2.9432 data: 0.0066 max mem: 33297 +Epoch: [0] [1160/4276] eta: 2:32:52 lr: 4.969444120705697e-05 loss: 0.2669 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4.9652315125298596e-05 loss: 0.2378 (0.2857) time: 2.9542 data: 0.0068 max mem: 33297 +Epoch: [0] [1330/4276] eta: 2:24:29 lr: 4.964968211336323e-05 loss: 0.2374 (0.2853) time: 2.9522 data: 0.0069 max mem: 33297 +Epoch: [0] [1340/4276] eta: 2:23:59 lr: 4.964704908591295e-05 loss: 0.2330 (0.2849) time: 2.9516 data: 0.0068 max mem: 33297 +Epoch: [0] [1350/4276] eta: 2:23:30 lr: 4.9644416042946765e-05 loss: 0.2636 (0.2847) time: 2.9523 data: 0.0065 max mem: 33297 +Epoch: [0] [1360/4276] eta: 2:23:01 lr: 4.964178298446365e-05 loss: 0.2394 (0.2845) time: 2.9532 data: 0.0067 max mem: 33297 +Epoch: [0] [1370/4276] eta: 2:22:32 lr: 4.963914991046262e-05 loss: 0.2375 (0.2841) time: 2.9540 data: 0.0070 max mem: 33297 +Epoch: [0] [1380/4276] eta: 2:22:02 lr: 4.963651682094265e-05 loss: 0.2385 (0.2840) time: 2.9531 data: 0.0075 max mem: 33297 +Epoch: [0] [1390/4276] eta: 2:21:32 lr: 4.9633883715902746e-05 loss: 0.2413 (0.2837) time: 2.9308 data: 0.0076 max mem: 33297 +Epoch: [0] [1400/4276] eta: 2:21:02 lr: 4.963125059534189e-05 loss: 0.2413 (0.2836) time: 2.9087 data: 0.0069 max mem: 33297 +Epoch: [0] [1410/4276] eta: 2:20:32 lr: 4.962861745925908e-05 loss: 0.2433 (0.2834) time: 2.9090 data: 0.0067 max mem: 33297 +Epoch: [0] [1420/4276] eta: 2:20:03 lr: 4.962598430765332e-05 loss: 0.2565 (0.2833) time: 2.9282 data: 0.0065 max mem: 33297 +Epoch: [0] [1430/4276] eta: 2:19:34 lr: 4.96233511405236e-05 loss: 0.2446 (0.2830) time: 2.9499 data: 0.0066 max mem: 33297 +Epoch: [0] [1440/4276] eta: 2:19:04 lr: 4.96207179578689e-05 loss: 0.2347 (0.2831) time: 2.9531 data: 0.0067 max mem: 33297 +Epoch: [0] [1450/4276] eta: 2:18:35 lr: 4.961808475968822e-05 loss: 0.2529 (0.2829) time: 2.9556 data: 0.0065 max mem: 33297 +Epoch: [0] [1460/4276] eta: 2:18:06 lr: 4.961545154598057e-05 loss: 0.2529 (0.2828) time: 2.9526 data: 0.0065 max mem: 33297 +Epoch: [0] [1470/4276] eta: 2:17:37 lr: 4.961281831674491e-05 loss: 0.2483 (0.2826) time: 2.9508 data: 0.0066 max mem: 33297 +Epoch: [0] [1480/4276] eta: 2:17:07 lr: 4.961018507198025e-05 loss: 0.2461 (0.2825) time: 2.9503 data: 0.0069 max mem: 33297 +Epoch: [0] [1490/4276] eta: 2:16:38 lr: 4.960755181168559e-05 loss: 0.2453 (0.2822) time: 2.9456 data: 0.0070 max mem: 33297 +Epoch: [0] [1500/4276] eta: 2:16:09 lr: 4.9604918535859916e-05 loss: 0.2324 (0.2819) time: 2.9486 data: 0.0068 max mem: 33297 +Epoch: [0] [1510/4276] eta: 2:15:40 lr: 4.9602285244502217e-05 loss: 0.2318 (0.2818) time: 2.9530 data: 0.0068 max mem: 33297 +Epoch: [0] [1520/4276] eta: 2:15:10 lr: 4.9599651937611484e-05 loss: 0.2382 (0.2815) time: 2.9524 data: 0.0071 max mem: 33297 +Epoch: [0] [1530/4276] eta: 2:14:41 lr: 4.9597018615186716e-05 loss: 0.2382 (0.2814) time: 2.9489 data: 0.0071 max mem: 33297 +Epoch: [0] [1540/4276] eta: 2:14:11 lr: 4.9594385277226904e-05 loss: 0.2406 (0.2811) time: 2.9445 data: 0.0071 max mem: 33297 +Epoch: [0] [1550/4276] eta: 2:13:42 lr: 4.9591751923731036e-05 loss: 0.2432 (0.2809) time: 2.9323 data: 0.0072 max mem: 33297 +Epoch: 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+Epoch: [0] [1640/4276] eta: 2:09:15 lr: 4.9568051042979336e-05 loss: 0.2494 (0.2794) time: 2.9492 data: 0.0069 max mem: 33297 +Epoch: [0] [1650/4276] eta: 2:08:46 lr: 4.9565417534067444e-05 loss: 0.2494 (0.2793) time: 2.9468 data: 0.0067 max mem: 33297 +Epoch: [0] [1660/4276] eta: 2:08:16 lr: 4.95627840096084e-05 loss: 0.2335 (0.2790) time: 2.9463 data: 0.0068 max mem: 33297 +Epoch: [0] [1670/4276] eta: 2:07:47 lr: 4.956015046960119e-05 loss: 0.2361 (0.2789) time: 2.9483 data: 0.0066 max mem: 33297 +Epoch: [0] [1680/4276] eta: 2:07:18 lr: 4.9557516914044805e-05 loss: 0.2649 (0.2789) time: 2.9530 data: 0.0070 max mem: 33297 +Epoch: [0] [1690/4276] eta: 2:06:48 lr: 4.955488334293824e-05 loss: 0.2531 (0.2787) time: 2.9546 data: 0.0069 max mem: 33297 +Epoch: [0] [1700/4276] eta: 2:06:19 lr: 4.9552249756280486e-05 loss: 0.2376 (0.2786) time: 2.9536 data: 0.0069 max mem: 33297 +Epoch: [0] [1710/4276] eta: 2:05:50 lr: 4.954961615407053e-05 loss: 0.2746 (0.2785) time: 2.9517 data: 0.0068 max mem: 33297 +Epoch: [0] [1720/4276] eta: 2:05:20 lr: 4.954698253630735e-05 loss: 0.2704 (0.2786) time: 2.9458 data: 0.0067 max mem: 33297 +Epoch: [0] [1730/4276] eta: 2:04:51 lr: 4.9544348902989954e-05 loss: 0.2485 (0.2783) time: 2.9469 data: 0.0070 max mem: 33297 +Epoch: [0] [1740/4276] eta: 2:04:22 lr: 4.954171525411733e-05 loss: 0.2254 (0.2782) time: 2.9522 data: 0.0071 max mem: 33297 +Epoch: [0] [1750/4276] eta: 2:03:53 lr: 4.953908158968846e-05 loss: 0.2630 (0.2782) time: 2.9511 data: 0.0073 max mem: 33297 +Epoch: [0] [1760/4276] eta: 2:03:23 lr: 4.9536447909702324e-05 loss: 0.2630 (0.2779) time: 2.9466 data: 0.0072 max mem: 33297 +Epoch: [0] [1770/4276] eta: 2:02:54 lr: 4.953381421415793e-05 loss: 0.2362 (0.2777) time: 2.9463 data: 0.0069 max mem: 33297 +Epoch: [0] [1780/4276] eta: 2:02:24 lr: 4.953118050305426e-05 loss: 0.2516 (0.2776) time: 2.9473 data: 0.0068 max mem: 33297 +Epoch: [0] [1790/4276] eta: 2:01:55 lr: 4.9528546776390295e-05 loss: 0.2287 (0.2773) time: 2.9509 data: 0.0070 max mem: 33297 +Epoch: [0] [1800/4276] eta: 2:01:26 lr: 4.9525913034165035e-05 loss: 0.2263 (0.2772) time: 2.9501 data: 0.0070 max mem: 33297 +Epoch: [0] [1810/4276] eta: 2:00:57 lr: 4.952327927637747e-05 loss: 0.2489 (0.2771) time: 2.9503 data: 0.0068 max mem: 33297 +Epoch: [0] [1820/4276] eta: 2:00:27 lr: 4.9520645503026567e-05 loss: 0.2422 (0.2769) time: 2.9501 data: 0.0070 max mem: 33297 +Epoch: [0] [1830/4276] eta: 1:59:58 lr: 4.951801171411133e-05 loss: 0.2422 (0.2768) time: 2.9488 data: 0.0072 max mem: 33297 +Epoch: [0] [1840/4276] eta: 1:59:28 lr: 4.9515377909630756e-05 loss: 0.2343 (0.2767) time: 2.9490 data: 0.0070 max mem: 33297 +Epoch: [0] [1850/4276] eta: 1:58:59 lr: 4.951274408958383e-05 loss: 0.2509 (0.2766) time: 2.9408 data: 0.0067 max mem: 33297 +Epoch: [0] [1860/4276] eta: 1:58:29 lr: 4.951011025396952e-05 loss: 0.2443 (0.2764) time: 2.9291 data: 0.0071 max mem: 33297 +Epoch: [0] [1870/4276] eta: 1:58:00 lr: 4.950747640278683e-05 loss: 0.2373 (0.2764) time: 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4.944425930125363e-05 loss: 0.2346 (0.2724) time: 2.9115 data: 0.0073 max mem: 33297 +Epoch: [0] [2120/4276] eta: 1:45:40 lr: 4.944162506053206e-05 loss: 0.2323 (0.2723) time: 2.9052 data: 0.0071 max mem: 33297 +Epoch: [0] [2130/4276] eta: 1:45:10 lr: 4.943899080421572e-05 loss: 0.2456 (0.2722) time: 2.9237 data: 0.0070 max mem: 33297 +Epoch: [0] [2140/4276] eta: 1:44:41 lr: 4.943635653230363e-05 loss: 0.2497 (0.2721) time: 2.9492 data: 0.0070 max mem: 33297 +Epoch: [0] [2150/4276] eta: 1:44:12 lr: 4.943372224479477e-05 loss: 0.2360 (0.2720) time: 2.9503 data: 0.0073 max mem: 33297 +Epoch: [0] [2160/4276] eta: 1:43:43 lr: 4.9431087941688126e-05 loss: 0.2337 (0.2719) time: 2.9557 data: 0.0074 max mem: 33297 +Epoch: [0] [2170/4276] eta: 1:43:13 lr: 4.942845362298267e-05 loss: 0.2393 (0.2719) time: 2.9566 data: 0.0076 max mem: 33297 +Epoch: [0] [2180/4276] eta: 1:42:44 lr: 4.942581928867738e-05 loss: 0.2517 (0.2718) time: 2.9497 data: 0.0074 max mem: 33297 +Epoch: [0] [2190/4276] eta: 1:42:15 lr: 4.942318493877126e-05 loss: 0.2488 (0.2718) time: 2.9494 data: 0.0072 max mem: 33297 +Epoch: [0] [2200/4276] eta: 1:41:45 lr: 4.942055057326329e-05 loss: 0.2401 (0.2716) time: 2.9460 data: 0.0070 max mem: 33297 +Epoch: [0] [2210/4276] eta: 1:41:16 lr: 4.9417916192152437e-05 loss: 0.2365 (0.2716) time: 2.9506 data: 0.0068 max mem: 33297 +Epoch: [0] [2220/4276] eta: 1:40:47 lr: 4.941528179543769e-05 loss: 0.2389 (0.2714) time: 2.9527 data: 0.0071 max mem: 33297 +Epoch: [0] [2230/4276] eta: 1:40:17 lr: 4.9412647383118054e-05 loss: 0.2323 (0.2713) time: 2.9472 data: 0.0074 max mem: 33297 +Epoch: [0] [2240/4276] eta: 1:39:48 lr: 4.941001295519249e-05 loss: 0.2250 (0.2711) time: 2.9455 data: 0.0073 max mem: 33297 +Epoch: [0] [2250/4276] eta: 1:39:19 lr: 4.9407378511659986e-05 loss: 0.2375 (0.2710) time: 2.9428 data: 0.0071 max mem: 33297 +Epoch: [0] [2260/4276] eta: 1:38:49 lr: 4.9404744052519524e-05 loss: 0.2450 (0.2710) time: 2.9460 data: 0.0071 max mem: 33297 +Epoch: [0] [2270/4276] eta: 1:38:20 lr: 4.940210957777009e-05 loss: 0.2381 (0.2709) time: 2.9479 data: 0.0069 max mem: 33297 +Epoch: [0] [2280/4276] eta: 1:37:50 lr: 4.939947508741067e-05 loss: 0.2237 (0.2707) time: 2.9441 data: 0.0067 max mem: 33297 +Epoch: [0] [2290/4276] eta: 1:37:21 lr: 4.939684058144023e-05 loss: 0.2291 (0.2706) time: 2.9456 data: 0.0069 max mem: 33297 +Epoch: [0] [2300/4276] eta: 1:36:52 lr: 4.939420605985777e-05 loss: 0.2121 (0.2703) time: 2.9479 data: 0.0071 max mem: 33297 +Epoch: [0] [2310/4276] eta: 1:36:22 lr: 4.939157152266227e-05 loss: 0.2182 (0.2702) time: 2.9456 data: 0.0071 max mem: 33297 +Epoch: [0] [2320/4276] eta: 1:35:53 lr: 4.938893696985271e-05 loss: 0.2435 (0.2701) time: 2.9278 data: 0.0074 max mem: 33297 +Epoch: [0] [2330/4276] eta: 1:35:23 lr: 4.938630240142806e-05 loss: 0.2213 (0.2699) time: 2.9185 data: 0.0074 max mem: 33297 +Epoch: [0] [2340/4276] eta: 1:34:54 lr: 4.938366781738731e-05 loss: 0.2339 (0.2698) time: 2.9312 data: 0.0071 max mem: 33297 +Epoch: [0] [2350/4276] eta: 1:34:24 lr: 4.9381033217729464e-05 loss: 0.2290 (0.2696) time: 2.9449 data: 0.0071 max mem: 33297 +Epoch: [0] [2360/4276] eta: 1:33:55 lr: 4.937839860245347e-05 loss: 0.2279 (0.2695) time: 2.9500 data: 0.0070 max mem: 33297 +Epoch: [0] [2370/4276] eta: 1:33:26 lr: 4.937576397155832e-05 loss: 0.2337 (0.2694) time: 2.9463 data: 0.0065 max mem: 33297 +Epoch: [0] [2380/4276] eta: 1:32:56 lr: 4.9373129325043e-05 loss: 0.2150 (0.2692) time: 2.9455 data: 0.0064 max mem: 33297 +Epoch: [0] [2390/4276] eta: 1:32:27 lr: 4.93704946629065e-05 loss: 0.2146 (0.2690) time: 2.9463 data: 0.0063 max mem: 33297 +Epoch: [0] [2400/4276] eta: 1:31:57 lr: 4.936785998514778e-05 loss: 0.2194 (0.2690) time: 2.9485 data: 0.0064 max mem: 33297 +Epoch: [0] [2410/4276] eta: 1:31:28 lr: 4.936522529176583e-05 loss: 0.2382 (0.2688) time: 2.9463 data: 0.0064 max mem: 33297 +Epoch: [0] [2420/4276] eta: 1:30:59 lr: 4.9362590582759643e-05 loss: 0.2317 (0.2686) time: 2.9397 data: 0.0068 max mem: 33297 +Epoch: [0] [2430/4276] eta: 1:30:29 lr: 4.935995585812819e-05 loss: 0.2384 (0.2686) time: 2.9406 data: 0.0068 max mem: 33297 +Epoch: [0] [2440/4276] eta: 1:30:00 lr: 4.935732111787044e-05 loss: 0.2459 (0.2685) time: 2.9450 data: 0.0067 max mem: 33297 +Epoch: [0] [2450/4276] eta: 1:29:31 lr: 4.935468636198539e-05 loss: 0.2321 (0.2683) time: 2.9473 data: 0.0069 max mem: 33298 +Epoch: [0] [2460/4276] eta: 1:29:01 lr: 4.935205159047202e-05 loss: 0.2321 (0.2682) time: 2.9499 data: 0.0067 max mem: 33298 +Epoch: [0] [2470/4276] eta: 1:28:32 lr: 4.9349416803329296e-05 loss: 0.2545 (0.2682) time: 2.9548 data: 0.0065 max mem: 33298 +Epoch: [0] [2480/4276] eta: 1:28:03 lr: 4.934678200055621e-05 loss: 0.2506 (0.2681) time: 2.9532 data: 0.0066 max mem: 33298 +Epoch: [0] [2490/4276] eta: 1:27:33 lr: 4.934414718215174e-05 loss: 0.2395 (0.2680) time: 2.9446 data: 0.0069 max mem: 33298 +Epoch: [0] [2500/4276] eta: 1:27:04 lr: 4.934151234811486e-05 loss: 0.2601 (0.2680) time: 2.9351 data: 0.0066 max mem: 33298 +Epoch: [0] [2510/4276] eta: 1:26:34 lr: 4.933887749844457e-05 loss: 0.2446 (0.2679) time: 2.9384 data: 0.0065 max mem: 33298 +Epoch: [0] [2520/4276] eta: 1:26:05 lr: 4.933624263313982e-05 loss: 0.2271 (0.2677) time: 2.9473 data: 0.0069 max mem: 33298 +Epoch: [0] [2530/4276] eta: 1:25:35 lr: 4.933360775219961e-05 loss: 0.2068 (0.2675) time: 2.9449 data: 0.0069 max mem: 33298 +Epoch: [0] [2540/4276] eta: 1:25:06 lr: 4.933097285562291e-05 loss: 0.2081 (0.2673) time: 2.9444 data: 0.0069 max mem: 33298 +Epoch: [0] [2550/4276] eta: 1:24:37 lr: 4.932833794340871e-05 loss: 0.2390 (0.2673) time: 2.9433 data: 0.0068 max mem: 33298 +Epoch: [0] [2560/4276] eta: 1:24:07 lr: 4.932570301555597e-05 loss: 0.2150 (0.2671) time: 2.9425 data: 0.0066 max mem: 33298 +Epoch: [0] [2570/4276] eta: 1:23:38 lr: 4.932306807206369e-05 loss: 0.2082 (0.2670) time: 2.9431 data: 0.0067 max mem: 33298 +Epoch: [0] [2580/4276] eta: 1:23:08 lr: 4.932043311293083e-05 loss: 0.2260 (0.2669) time: 2.9438 data: 0.0068 max mem: 33298 +Epoch: [0] [2590/4276] eta: 1:22:39 lr: 4.931779813815639e-05 loss: 0.2401 (0.2668) time: 2.9463 data: 0.0068 max mem: 33298 +Epoch: [0] [2600/4276] eta: 1:22:10 lr: 4.931516314773932e-05 loss: 0.2433 (0.2668) time: 2.9511 data: 0.0068 max mem: 33298 +Epoch: [0] [2610/4276] eta: 1:21:40 lr: 4.931252814167863e-05 loss: 0.2419 (0.2667) time: 2.9485 data: 0.0068 max mem: 33298 +Epoch: [0] [2620/4276] eta: 1:21:11 lr: 4.930989311997328e-05 loss: 0.2261 (0.2666) time: 2.9495 data: 0.0069 max mem: 33298 +Epoch: [0] [2630/4276] eta: 1:20:42 lr: 4.930725808262225e-05 loss: 0.2363 (0.2665) time: 2.9521 data: 0.0070 max mem: 33298 +Epoch: [0] [2640/4276] eta: 1:20:12 lr: 4.930462302962452e-05 loss: 0.2201 (0.2663) time: 2.9512 data: 0.0068 max mem: 33298 +Epoch: [0] [2650/4276] eta: 1:19:43 lr: 4.930198796097906e-05 loss: 0.2201 (0.2662) time: 2.9499 data: 0.0068 max mem: 33298 +Epoch: [0] [2660/4276] eta: 1:19:14 lr: 4.929935287668487e-05 loss: 0.2365 (0.2661) time: 2.9474 data: 0.0074 max mem: 33298 +Epoch: [0] [2670/4276] eta: 1:18:44 lr: 4.92967177767409e-05 loss: 0.2451 (0.2661) time: 2.9474 data: 0.0073 max mem: 33298 +Epoch: [0] [2680/4276] eta: 1:18:15 lr: 4.929408266114614e-05 loss: 0.2362 (0.2660) time: 2.9476 data: 0.0066 max mem: 33298 +Epoch: [0] [2690/4276] eta: 1:17:45 lr: 4.929144752989958e-05 loss: 0.2426 (0.2659) time: 2.9466 data: 0.0066 max mem: 33298 +Epoch: [0] [2700/4276] eta: 1:17:16 lr: 4.9288812383000185e-05 loss: 0.2272 (0.2657) time: 2.9473 data: 0.0068 max mem: 33298 +Epoch: [0] [2710/4276] eta: 1:16:47 lr: 4.9286177220446924e-05 loss: 0.2272 (0.2657) time: 2.9491 data: 0.0069 max mem: 33298 +Epoch: [0] [2720/4276] eta: 1:16:17 lr: 4.928354204223878e-05 loss: 0.2600 (0.2656) time: 2.9478 data: 0.0071 max mem: 33298 +Epoch: [0] [2730/4276] eta: 1:15:48 lr: 4.9280906848374736e-05 loss: 0.2353 (0.2656) time: 2.9510 data: 0.0073 max mem: 33298 +Epoch: [0] [2740/4276] eta: 1:15:18 lr: 4.927827163885377e-05 loss: 0.2353 (0.2655) time: 2.9525 data: 0.0074 max mem: 33298 +Epoch: [0] [2750/4276] eta: 1:14:49 lr: 4.927563641367485e-05 loss: 0.2450 (0.2655) time: 2.9546 data: 0.0072 max mem: 33298 +Epoch: [0] [2760/4276] eta: 1:14:20 lr: 4.9273001172836954e-05 loss: 0.2397 (0.2654) time: 2.9384 data: 0.0071 max mem: 33298 +Epoch: [0] [2770/4276] eta: 1:13:50 lr: 4.927036591633906e-05 loss: 0.2265 (0.2653) time: 2.9349 data: 0.0073 max mem: 33298 +Epoch: [0] [2780/4276] eta: 1:13:21 lr: 4.9267730644180155e-05 loss: 0.2332 (0.2651) time: 2.9507 data: 0.0071 max mem: 33298 +Epoch: [0] [2790/4276] eta: 1:12:51 lr: 4.926509535635919e-05 loss: 0.2502 (0.2651) time: 2.9512 data: 0.0067 max mem: 33298 +Epoch: [0] [2800/4276] eta: 1:12:22 lr: 4.926246005287517e-05 loss: 0.2447 (0.2650) time: 2.9496 data: 0.0064 max mem: 33298 +Epoch: [0] [2810/4276] eta: 1:11:53 lr: 4.925982473372705e-05 loss: 0.2210 (0.2649) time: 2.9468 data: 0.0066 max mem: 33298 +Epoch: [0] [2820/4276] eta: 1:11:23 lr: 4.9257189398913815e-05 loss: 0.2337 (0.2648) time: 2.9470 data: 0.0068 max mem: 33298 +Epoch: [0] [2830/4276] eta: 1:10:54 lr: 4.925455404843444e-05 loss: 0.2419 (0.2647) time: 2.9576 data: 0.0066 max mem: 33298 +Epoch: [0] [2840/4276] eta: 1:10:25 lr: 4.9251918682287896e-05 loss: 0.2445 (0.2646) time: 2.9816 data: 0.0064 max mem: 33298 +Epoch: [0] [2850/4276] eta: 1:09:56 lr: 4.924928330047316e-05 loss: 0.2465 (0.2647) time: 3.0116 data: 0.0063 max mem: 33298 +Epoch: [0] [2860/4276] eta: 1:09:27 lr: 4.924664790298922e-05 loss: 0.2449 (0.2645) time: 3.0314 data: 0.0065 max mem: 33298 +Epoch: [0] [2870/4276] eta: 1:08:58 lr: 4.9244012489835024e-05 loss: 0.2395 (0.2645) time: 3.0195 data: 0.0063 max mem: 33298 +Epoch: [0] [2880/4276] eta: 1:08:29 lr: 4.924137706100957e-05 loss: 0.2502 (0.2645) time: 3.0164 data: 0.0061 max mem: 33298 +Epoch: [0] [2890/4276] eta: 1:08:00 lr: 4.9238741616511825e-05 loss: 0.2426 (0.2644) time: 3.0340 data: 0.0061 max mem: 33298 +Epoch: [0] [2900/4276] eta: 1:07:31 lr: 4.9236106156340765e-05 loss: 0.2235 (0.2642) time: 3.0324 data: 0.0059 max mem: 33298 +Epoch: [0] [2910/4276] eta: 1:07:02 lr: 4.923347068049537e-05 loss: 0.2225 (0.2642) time: 3.0300 data: 0.0058 max mem: 33298 +Epoch: [0] [2920/4276] eta: 1:06:33 lr: 4.92308351889746e-05 loss: 0.2284 (0.2641) time: 3.0199 data: 0.0057 max mem: 33298 +Epoch: [0] [2930/4276] eta: 1:06:03 lr: 4.922819968177744e-05 loss: 0.2302 (0.2641) time: 2.9985 data: 0.0057 max mem: 33298 +Epoch: [0] [2940/4276] eta: 1:05:34 lr: 4.9225564158902866e-05 loss: 0.2159 (0.2639) time: 3.0034 data: 0.0056 max mem: 33298 +Epoch: [0] [2950/4276] eta: 1:05:05 lr: 4.9222928620349843e-05 loss: 0.2117 (0.2638) time: 3.0126 data: 0.0056 max mem: 33298 +Epoch: [0] [2960/4276] eta: 1:04:36 lr: 4.9220293066117353e-05 loss: 0.2387 (0.2638) time: 2.9976 data: 0.0056 max mem: 33298 +Epoch: [0] [2970/4276] eta: 1:04:07 lr: 4.9217657496204366e-05 loss: 0.2684 (0.2639) time: 3.0129 data: 0.0057 max mem: 33298 +Epoch: [0] [2980/4276] eta: 1:03:38 lr: 4.921502191060986e-05 loss: 0.2533 (0.2638) time: 3.0288 data: 0.0057 max mem: 33298 +Epoch: [0] [2990/4276] eta: 1:03:08 lr: 4.9212386309332805e-05 loss: 0.2242 (0.2636) time: 3.0313 data: 0.0058 max mem: 33298 +Epoch: [0] [3000/4276] eta: 1:02:39 lr: 4.9209750692372166e-05 loss: 0.2222 (0.2635) time: 3.0350 data: 0.0060 max mem: 33298 +Epoch: [0] [3010/4276] eta: 1:02:10 lr: 4.9207115059726935e-05 loss: 0.2313 (0.2635) time: 3.0344 data: 0.0060 max mem: 33298 +Epoch: [0] [3020/4276] eta: 1:01:41 lr: 4.920447941139607e-05 loss: 0.2382 (0.2634) time: 3.0351 data: 0.0057 max mem: 33298 +Epoch: [0] [3030/4276] eta: 1:01:12 lr: 4.920184374737855e-05 loss: 0.2392 (0.2634) time: 3.0172 data: 0.0055 max mem: 33298 +Epoch: [0] [3040/4276] eta: 1:00:43 lr: 4.9199208067673355e-05 loss: 0.2568 (0.2634) time: 3.0004 data: 0.0057 max mem: 33298 +Epoch: [0] [3050/4276] eta: 1:00:13 lr: 4.919657237227944e-05 loss: 0.2512 (0.2633) time: 2.9978 data: 0.0058 max mem: 33298 +Epoch: [0] [3060/4276] eta: 0:59:44 lr: 4.919393666119579e-05 loss: 0.2274 (0.2632) time: 2.9989 data: 0.0056 max mem: 33298 +Epoch: [0] [3070/4276] eta: 0:59:15 lr: 4.919130093442138e-05 loss: 0.2410 (0.2632) time: 3.0064 data: 0.0056 max mem: 33298 +Epoch: [0] [3080/4276] eta: 0:58:46 lr: 4.918866519195517e-05 loss: 0.2308 (0.2631) time: 3.0260 data: 0.0060 max mem: 33298 +Epoch: [0] [3090/4276] eta: 0:58:17 lr: 4.918602943379615e-05 loss: 0.2254 (0.2631) time: 3.0416 data: 0.0064 max mem: 33298 +Epoch: [0] [3100/4276] eta: 0:57:48 lr: 4.9183393659943286e-05 loss: 0.2379 (0.2630) time: 3.0427 data: 0.0063 max mem: 33298 +Epoch: [0] [3110/4276] eta: 0:57:18 lr: 4.918075787039553e-05 loss: 0.2287 (0.2629) time: 3.0507 data: 0.0062 max mem: 33298 +Epoch: [0] [3120/4276] eta: 0:56:49 lr: 4.917812206515188e-05 loss: 0.2135 (0.2628) time: 3.0571 data: 0.0066 max mem: 33298 +Epoch: [0] [3130/4276] eta: 0:56:20 lr: 4.917548624421131e-05 loss: 0.2276 (0.2627) time: 3.0555 data: 0.0067 max mem: 33298 +Epoch: [0] [3140/4276] eta: 0:55:51 lr: 4.917285040757276e-05 loss: 0.2317 (0.2627) time: 3.0732 data: 0.0070 max mem: 33298 +Epoch: [0] [3150/4276] eta: 0:55:22 lr: 4.917021455523523e-05 loss: 0.2398 (0.2627) time: 3.0841 data: 0.0077 max mem: 33298 +Epoch: [0] [3160/4276] eta: 0:54:53 lr: 4.9167578687197674e-05 loss: 0.2362 (0.2626) time: 3.0868 data: 0.0079 max mem: 33298 +Epoch: [0] [3170/4276] eta: 0:54:24 lr: 4.916494280345909e-05 loss: 0.2238 (0.2626) time: 3.0978 data: 0.0080 max mem: 33298 +Epoch: [0] [3180/4276] eta: 0:53:55 lr: 4.9162306904018415e-05 loss: 0.2415 (0.2626) time: 3.1106 data: 0.0078 max mem: 33298 +Epoch: [0] [3190/4276] eta: 0:53:26 lr: 4.915967098887464e-05 loss: 0.2526 (0.2625) time: 3.1149 data: 0.0074 max mem: 33298 +Epoch: [0] [3200/4276] eta: 0:52:57 lr: 4.915703505802674e-05 loss: 0.2253 (0.2624) time: 3.1197 data: 0.0072 max mem: 33298 +Epoch: [0] [3210/4276] eta: 0:52:28 lr: 4.915439911147367e-05 loss: 0.2203 (0.2624) time: 3.1214 data: 0.0073 max mem: 33298 +Epoch: [0] [3220/4276] eta: 0:51:59 lr: 4.9151763149214406e-05 loss: 0.2369 (0.2623) time: 3.1219 data: 0.0076 max mem: 33298 +Epoch: [0] [3230/4276] eta: 0:51:30 lr: 4.9149127171247925e-05 loss: 0.2399 (0.2623) time: 3.1116 data: 0.0074 max mem: 33298 +Epoch: [0] [3240/4276] eta: 0:51:01 lr: 4.9146491177573196e-05 loss: 0.2399 (0.2622) time: 3.0886 data: 0.0073 max mem: 33298 +Epoch: [0] [3250/4276] eta: 0:50:32 lr: 4.9143855168189185e-05 loss: 0.2350 (0.2621) time: 3.0975 data: 0.0076 max mem: 33298 +Epoch: [0] [3260/4276] eta: 0:50:03 lr: 4.914121914309486e-05 loss: 0.2415 (0.2621) time: 3.1270 data: 0.0080 max mem: 33298 +Epoch: [0] [3270/4276] eta: 0:49:34 lr: 4.91385831022892e-05 loss: 0.2512 (0.2620) time: 3.1189 data: 0.0082 max mem: 33298 +Epoch: [0] [3280/4276] eta: 0:49:05 lr: 4.913594704577117e-05 loss: 0.2512 (0.2620) time: 3.0982 data: 0.0074 max mem: 33298 +Epoch: [0] [3290/4276] eta: 0:48:36 lr: 4.913331097353974e-05 loss: 0.2580 (0.2620) time: 3.1118 data: 0.0077 max mem: 33298 +Epoch: [0] [3300/4276] eta: 0:48:07 lr: 4.9130674885593874e-05 loss: 0.2587 (0.2620) time: 3.1347 data: 0.0084 max mem: 33298 +Epoch: [0] [3310/4276] eta: 0:47:38 lr: 4.912803878193255e-05 loss: 0.2587 (0.2620) time: 3.1400 data: 0.0076 max mem: 33298 +Epoch: [0] [3320/4276] eta: 0:47:09 lr: 4.912540266255473e-05 loss: 0.2582 (0.2620) time: 3.1323 data: 0.0073 max mem: 33298 +Epoch: [0] [3330/4276] eta: 0:46:39 lr: 4.9122766527459394e-05 loss: 0.2351 (0.2619) time: 3.1213 data: 0.0077 max mem: 33298 +Epoch: [0] [3340/4276] eta: 0:46:10 lr: 4.91201303766455e-05 loss: 0.2351 (0.2619) time: 3.1179 data: 0.0076 max mem: 33298 +Epoch: [0] [3350/4276] eta: 0:45:41 lr: 4.9117494210112014e-05 loss: 0.2306 (0.2617) time: 3.1230 data: 0.0073 max mem: 33298 +Epoch: [0] [3360/4276] eta: 0:45:12 lr: 4.911485802785792e-05 loss: 0.2248 (0.2617) time: 3.1222 data: 0.0078 max mem: 33298 +Epoch: [0] [3370/4276] eta: 0:44:43 lr: 4.9112221829882175e-05 loss: 0.2576 (0.2617) time: 3.1281 data: 0.0080 max mem: 33298 +Epoch: [0] [3380/4276] eta: 0:44:13 lr: 4.9109585616183754e-05 loss: 0.2396 (0.2617) time: 3.1007 data: 0.0077 max mem: 33298 +Epoch: [0] [3390/4276] eta: 0:43:44 lr: 4.9106949386761617e-05 loss: 0.2502 (0.2617) time: 3.0963 data: 0.0077 max mem: 33298 +Epoch: [0] [3400/4276] eta: 0:43:15 lr: 4.9104313141614746e-05 loss: 0.2502 (0.2616) time: 3.1380 data: 0.0077 max mem: 33298 +Epoch: [0] [3410/4276] eta: 0:42:46 lr: 4.9101676880742106e-05 loss: 0.2383 (0.2616) time: 3.1380 data: 0.0078 max mem: 33298 +Epoch: [0] [3420/4276] eta: 0:42:17 lr: 4.9099040604142646e-05 loss: 0.2438 (0.2615) time: 3.1266 data: 0.0085 max mem: 33298 +Epoch: [0] [3430/4276] eta: 0:41:47 lr: 4.909640431181535e-05 loss: 0.2447 (0.2615) time: 3.1314 data: 0.0086 max mem: 33298 +Epoch: [0] [3440/4276] eta: 0:41:18 lr: 4.909376800375919e-05 loss: 0.2445 (0.2615) time: 3.1310 data: 0.0080 max mem: 33298 +Epoch: [0] [3450/4276] eta: 0:40:49 lr: 4.909113167997313e-05 loss: 0.2413 (0.2614) time: 3.1238 data: 0.0076 max mem: 33298 +Epoch: [0] [3460/4276] eta: 0:40:20 lr: 4.908849534045613e-05 loss: 0.2413 (0.2613) time: 3.1216 data: 0.0074 max mem: 33298 +Epoch: [0] [3470/4276] eta: 0:39:50 lr: 4.9085858985207164e-05 loss: 0.2130 (0.2612) time: 3.1302 data: 0.0073 max mem: 33298 +Epoch: [0] [3480/4276] eta: 0:39:21 lr: 4.9083222614225194e-05 loss: 0.2436 (0.2612) time: 3.1322 data: 0.0074 max mem: 33298 +Epoch: [0] [3490/4276] eta: 0:38:52 lr: 4.9080586227509195e-05 loss: 0.2456 (0.2611) time: 3.1293 data: 0.0074 max mem: 33298 +Epoch: [0] [3500/4276] eta: 0:38:22 lr: 4.907794982505813e-05 loss: 0.2470 (0.2611) time: 3.1238 data: 0.0074 max mem: 33298 +Epoch: [0] [3510/4276] eta: 0:37:53 lr: 4.907531340687096e-05 loss: 0.2230 (0.2610) time: 3.1078 data: 0.0076 max mem: 33298 +Epoch: [0] [3520/4276] eta: 0:37:24 lr: 4.907267697294666e-05 loss: 0.2329 (0.2610) time: 3.1026 data: 0.0081 max mem: 33298 +Epoch: [0] [3530/4276] eta: 0:36:54 lr: 4.90700405232842e-05 loss: 0.2351 (0.2609) time: 3.1049 data: 0.0081 max mem: 33298 +Epoch: [0] [3540/4276] eta: 0:36:25 lr: 4.906740405788254e-05 loss: 0.2297 (0.2609) time: 3.1262 data: 0.0078 max mem: 33298 +Epoch: [0] [3550/4276] eta: 0:35:56 lr: 4.906476757674064e-05 loss: 0.2418 (0.2608) time: 3.1607 data: 0.0078 max mem: 33298 +Epoch: [0] [3560/4276] eta: 0:35:26 lr: 4.9062131079857484e-05 loss: 0.2401 (0.2608) time: 3.1680 data: 0.0082 max mem: 33298 +Epoch: [0] [3570/4276] eta: 0:34:57 lr: 4.9059494567232015e-05 loss: 0.2352 (0.2607) time: 3.1532 data: 0.0082 max mem: 33298 +Epoch: [0] [3580/4276] eta: 0:34:28 lr: 4.905685803886322e-05 loss: 0.2309 (0.2606) time: 3.1604 data: 0.0079 max mem: 33298 +Epoch: [0] [3590/4276] eta: 0:33:58 lr: 4.905422149475005e-05 loss: 0.2223 (0.2606) time: 3.1749 data: 0.0080 max mem: 33298 +Epoch: [0] [3600/4276] eta: 0:33:29 lr: 4.905158493489148e-05 loss: 0.2400 (0.2605) time: 3.1669 data: 0.0078 max mem: 33298 +Epoch: [0] [3610/4276] eta: 0:33:00 lr: 4.9048948359286475e-05 loss: 0.2559 (0.2605) time: 3.1473 data: 0.0073 max mem: 33298 +Epoch: [0] [3620/4276] eta: 0:32:30 lr: 4.9046311767934e-05 loss: 0.2408 (0.2604) time: 3.1339 data: 0.0072 max mem: 33298 +Epoch: [0] [3630/4276] eta: 0:32:01 lr: 4.9043675160833014e-05 loss: 0.2394 (0.2605) time: 3.1357 data: 0.0072 max mem: 33298 +Epoch: [0] [3640/4276] eta: 0:31:31 lr: 4.9041038537982484e-05 loss: 0.2400 (0.2604) time: 3.1280 data: 0.0071 max mem: 33298 +Epoch: [0] [3650/4276] eta: 0:31:02 lr: 4.903840189938138e-05 loss: 0.2297 (0.2604) time: 3.1177 data: 0.0068 max mem: 33298 +Epoch: [0] [3660/4276] eta: 0:30:32 lr: 4.903576524502866e-05 loss: 0.2278 (0.2603) time: 3.1081 data: 0.0064 max mem: 33298 +Epoch: [0] [3670/4276] eta: 0:30:03 lr: 4.90331285749233e-05 loss: 0.2287 (0.2603) time: 3.1094 data: 0.0072 max mem: 33298 +Epoch: [0] [3680/4276] eta: 0:29:33 lr: 4.903049188906426e-05 loss: 0.2307 (0.2603) time: 3.1226 data: 0.0076 max mem: 33298 +Epoch: [0] [3690/4276] eta: 0:29:04 lr: 4.90278551874505e-05 loss: 0.2311 (0.2602) time: 3.1274 data: 0.0074 max mem: 33298 +Epoch: [0] [3700/4276] eta: 0:28:34 lr: 4.902521847008099e-05 loss: 0.2425 (0.2602) time: 3.1280 data: 0.0077 max mem: 33298 +Epoch: [0] [3710/4276] eta: 0:28:05 lr: 4.902258173695469e-05 loss: 0.2339 (0.2601) time: 3.1241 data: 0.0077 max mem: 33298 +Epoch: [0] [3720/4276] eta: 0:27:35 lr: 4.901994498807056e-05 loss: 0.2233 (0.2600) time: 3.1286 data: 0.0079 max mem: 33298 +Epoch: [0] [3730/4276] eta: 0:27:05 lr: 4.901730822342757e-05 loss: 0.2428 (0.2600) time: 3.1201 data: 0.0081 max mem: 33298 +Epoch: [0] [3740/4276] eta: 0:26:36 lr: 4.9014671443024683e-05 loss: 0.2458 (0.2600) time: 3.1243 data: 0.0078 max mem: 33298 +Epoch: [0] [3750/4276] eta: 0:26:06 lr: 4.901203464686087e-05 loss: 0.2505 (0.2600) time: 3.1503 data: 0.0072 max mem: 33298 +Epoch: [0] [3760/4276] eta: 0:25:37 lr: 4.900939783493509e-05 loss: 0.2442 (0.2599) time: 3.1379 data: 0.0077 max mem: 33298 +Epoch: [0] [3770/4276] eta: 0:25:07 lr: 4.900676100724629e-05 loss: 0.2442 (0.2599) time: 3.0977 data: 0.0077 max mem: 33298 +Epoch: [0] [3780/4276] eta: 0:24:37 lr: 4.9004124163793464e-05 loss: 0.2349 (0.2598) time: 3.0866 data: 0.0071 max mem: 33298 +Epoch: [0] [3790/4276] eta: 0:24:08 lr: 4.900148730457556e-05 loss: 0.2258 (0.2597) time: 3.0993 data: 0.0074 max mem: 33298 +Epoch: [0] [3800/4276] eta: 0:23:38 lr: 4.899885042959152e-05 loss: 0.2301 (0.2598) time: 3.0942 data: 0.0074 max mem: 33298 +Epoch: [0] [3810/4276] eta: 0:23:08 lr: 4.899621353884034e-05 loss: 0.2285 (0.2597) time: 3.0895 data: 0.0072 max mem: 33298 +Epoch: [0] [3820/4276] eta: 0:22:39 lr: 4.899357663232097e-05 loss: 0.2202 (0.2596) time: 3.1084 data: 0.0076 max mem: 33298 +Epoch: [0] [3830/4276] eta: 0:22:09 lr: 4.899093971003238e-05 loss: 0.2269 (0.2596) time: 3.1035 data: 0.0075 max mem: 33298 +Epoch: [0] [3840/4276] eta: 0:21:39 lr: 4.8988302771973514e-05 loss: 0.2316 (0.2595) time: 3.0806 data: 0.0069 max mem: 33298 +Epoch: [0] [3850/4276] eta: 0:21:10 lr: 4.898566581814335e-05 loss: 0.2278 (0.2594) time: 3.1072 data: 0.0076 max mem: 33298 +Epoch: [0] [3860/4276] eta: 0:20:40 lr: 4.898302884854084e-05 loss: 0.2199 (0.2593) time: 3.1248 data: 0.0082 max mem: 33298 +Epoch: [0] [3870/4276] eta: 0:20:10 lr: 4.8980391863164966e-05 loss: 0.2401 (0.2593) time: 3.1143 data: 0.0077 max mem: 33298 +Epoch: [0] [3880/4276] eta: 0:19:41 lr: 4.897775486201467e-05 loss: 0.2383 (0.2592) time: 3.1318 data: 0.0080 max mem: 33298 +Epoch: [0] [3890/4276] eta: 0:19:11 lr: 4.8975117845088916e-05 loss: 0.2321 (0.2592) time: 3.1473 data: 0.0085 max mem: 33298 +Epoch: [0] [3900/4276] eta: 0:18:41 lr: 4.8972480812386675e-05 loss: 0.2560 (0.2592) time: 3.1301 data: 0.0083 max mem: 33298 +Epoch: [0] [3910/4276] eta: 0:18:12 lr: 4.89698437639069e-05 loss: 0.2209 (0.2591) time: 3.1204 data: 0.0081 max mem: 33298 +Epoch: [0] [3920/4276] eta: 0:17:42 lr: 4.896720669964856e-05 loss: 0.2188 (0.2590) time: 3.0960 data: 0.0079 max mem: 33298 +Epoch: [0] [3930/4276] eta: 0:17:12 lr: 4.896456961961061e-05 loss: 0.2274 (0.2590) time: 3.0935 data: 0.0077 max mem: 33298 +Epoch: [0] [3940/4276] eta: 0:16:43 lr: 4.896193252379202e-05 loss: 0.2374 (0.2589) time: 3.1470 data: 0.0081 max mem: 33298 +Epoch: [0] [3950/4276] eta: 0:16:13 lr: 4.895929541219174e-05 loss: 0.2374 (0.2588) time: 3.1737 data: 0.0085 max mem: 33298 +Epoch: [0] [3960/4276] eta: 0:15:43 lr: 4.895665828480874e-05 loss: 0.2495 (0.2588) time: 3.1759 data: 0.0083 max mem: 33298 +Epoch: [0] [3970/4276] eta: 0:15:13 lr: 4.895402114164197e-05 loss: 0.2472 (0.2588) time: 3.1734 data: 0.0080 max mem: 33298 +Epoch: [0] [3980/4276] eta: 0:14:44 lr: 4.895138398269041e-05 loss: 0.2346 (0.2588) time: 3.1671 data: 0.0081 max mem: 33298 +Epoch: [0] [3990/4276] eta: 0:14:14 lr: 4.8948746807953e-05 loss: 0.2253 (0.2587) time: 3.1603 data: 0.0078 max mem: 33298 +Epoch: [0] [4000/4276] eta: 0:13:44 lr: 4.894610961742871e-05 loss: 0.2223 (0.2587) time: 3.1495 data: 0.0075 max mem: 33298 +Epoch: [0] [4010/4276] eta: 0:13:14 lr: 4.89434724111165e-05 loss: 0.2366 (0.2587) time: 3.1359 data: 0.0078 max mem: 33298 +Epoch: [0] [4020/4276] eta: 0:12:45 lr: 4.8940835189015334e-05 loss: 0.2346 (0.2586) time: 3.1331 data: 0.0076 max mem: 33298 +Epoch: [0] [4030/4276] eta: 0:12:15 lr: 4.8938197951124166e-05 loss: 0.2346 (0.2585) time: 3.1505 data: 0.0073 max mem: 33298 +Epoch: [0] [4040/4276] eta: 0:11:45 lr: 4.893556069744196e-05 loss: 0.2396 (0.2585) time: 3.1675 data: 0.0078 max mem: 33298 +Epoch: [0] [4050/4276] eta: 0:11:15 lr: 4.893292342796766e-05 loss: 0.2216 (0.2584) time: 3.1669 data: 0.0083 max mem: 33298 +Epoch: [0] [4060/4276] eta: 0:10:45 lr: 4.893028614270026e-05 loss: 0.2174 (0.2584) time: 3.1742 data: 0.0088 max mem: 33298 +Epoch: [0] [4070/4276] eta: 0:10:16 lr: 4.892764884163869e-05 loss: 0.2208 (0.2583) time: 3.1772 data: 0.0086 max mem: 33298 +Epoch: [0] [4080/4276] eta: 0:09:46 lr: 4.892501152478192e-05 loss: 0.2159 (0.2583) time: 3.1677 data: 0.0084 max mem: 33298 +Epoch: [0] [4090/4276] eta: 0:09:16 lr: 4.89223741921289e-05 loss: 0.2239 (0.2582) time: 3.1687 data: 0.0086 max mem: 33298 +Epoch: [0] [4100/4276] eta: 0:08:46 lr: 4.891973684367861e-05 loss: 0.2435 (0.2582) time: 3.1512 data: 0.0083 max mem: 33298 +Epoch: [0] [4110/4276] eta: 0:08:16 lr: 4.891709947942999e-05 loss: 0.2456 (0.2582) time: 3.1417 data: 0.0088 max mem: 33298 +Epoch: [0] [4120/4276] eta: 0:07:46 lr: 4.8914462099382e-05 loss: 0.2332 (0.2581) time: 3.1582 data: 0.0091 max mem: 33298 +Epoch: [0] [4130/4276] eta: 0:07:17 lr: 4.891182470353361e-05 loss: 0.2264 (0.2581) time: 3.1784 data: 0.0091 max mem: 33298 +Epoch: [0] [4140/4276] eta: 0:06:47 lr: 4.890918729188378e-05 loss: 0.2296 (0.2580) time: 3.1867 data: 0.0096 max mem: 33298 +Epoch: [0] [4150/4276] eta: 0:06:17 lr: 4.8906549864431455e-05 loss: 0.2296 (0.2580) time: 3.1799 data: 0.0092 max mem: 33298 +Epoch: [0] [4160/4276] eta: 0:05:47 lr: 4.89039124211756e-05 loss: 0.2374 (0.2580) time: 3.1747 data: 0.0082 max mem: 33298 +Epoch: [0] [4170/4276] eta: 0:05:17 lr: 4.890127496211517e-05 loss: 0.2529 (0.2580) time: 3.1383 data: 0.0075 max mem: 33298 +Epoch: [0] [4180/4276] eta: 0:04:47 lr: 4.8898637487249124e-05 loss: 0.2503 (0.2579) time: 3.1377 data: 0.0075 max mem: 33298 +Epoch: [0] [4190/4276] eta: 0:04:17 lr: 4.889599999657643e-05 loss: 0.2334 (0.2579) time: 3.1541 data: 0.0085 max mem: 33298 +Epoch: [0] [4200/4276] eta: 0:03:47 lr: 4.889336249009603e-05 loss: 0.2334 (0.2579) time: 3.1428 data: 0.0085 max mem: 33298 +Epoch: [0] [4210/4276] eta: 0:03:17 lr: 4.88907249678069e-05 loss: 0.2422 (0.2579) time: 3.1394 data: 0.0085 max mem: 33298 +Epoch: [0] [4220/4276] eta: 0:02:47 lr: 4.888808742970799e-05 loss: 0.2539 (0.2579) time: 3.1295 data: 0.0086 max mem: 33298 +Epoch: [0] [4230/4276] eta: 0:02:17 lr: 4.888544987579824e-05 loss: 0.2704 (0.2580) time: 3.1302 data: 0.0083 max mem: 33298 +Epoch: [0] [4240/4276] eta: 0:01:47 lr: 4.888281230607663e-05 loss: 0.2662 (0.2580) time: 3.1380 data: 0.0079 max mem: 33298 +Epoch: [0] [4250/4276] eta: 0:01:17 lr: 4.888017472054211e-05 loss: 0.2455 (0.2579) time: 3.1191 data: 0.0078 max mem: 33298 +Epoch: [0] [4260/4276] eta: 0:00:47 lr: 4.887753711919363e-05 loss: 0.2455 (0.2579) time: 3.1022 data: 0.0079 max mem: 33298 +Epoch: [0] [4270/4276] eta: 0:00:17 lr: 4.8874899502030166e-05 loss: 0.2345 (0.2579) time: 3.1047 data: 0.0072 max mem: 33298 +Epoch: [0] Total time: 3:33:41 +Test: [ 0/21770] eta: 9:13:33 time: 1.5256 data: 1.3477 max mem: 33298 +Test: [ 100/21770] eta: 0:19:29 time: 0.0390 data: 0.0012 max mem: 33298 +Test: [ 200/21770] eta: 0:16:43 time: 0.0389 data: 0.0012 max mem: 33298 +Test: [ 300/21770] eta: 0:15:44 time: 0.0390 data: 0.0011 max mem: 33298 +Test: [ 400/21770] eta: 0:15:13 time: 0.0390 data: 0.0012 max mem: 33298 +Test: [ 500/21770] eta: 0:14:54 time: 0.0395 data: 0.0012 max mem: 33298 +Test: [ 600/21770] eta: 0:14:40 time: 0.0392 data: 0.0012 max mem: 33298 +Test: [ 700/21770] eta: 0:14:28 time: 0.0393 data: 0.0012 max mem: 33298 +Test: [ 800/21770] eta: 0:14:19 time: 0.0388 data: 0.0012 max mem: 33298 +Test: [ 900/21770] eta: 0:14:10 time: 0.0389 data: 0.0012 max mem: 33298 +Test: [ 1000/21770] eta: 0:14:02 time: 0.0389 data: 0.0012 max mem: 33298 +Test: [ 1100/21770] eta: 0:13:55 time: 0.0395 data: 0.0012 max mem: 33298 +Test: [ 1200/21770] eta: 0:13:49 time: 0.0387 data: 0.0012 max mem: 33298 +Test: [ 1300/21770] eta: 0:13:42 time: 0.0387 data: 0.0012 max mem: 33298 +Test: [ 1400/21770] eta: 0:13:36 time: 0.0388 data: 0.0012 max mem: 33298 +Test: [ 1500/21770] eta: 0:13:31 time: 0.0386 data: 0.0012 max mem: 33298 +Test: [ 1600/21770] eta: 0:13:25 time: 0.0385 data: 0.0012 max mem: 33298 +Test: [ 1700/21770] eta: 0:13:19 time: 0.0385 data: 0.0011 max mem: 33298 +Test: [ 1800/21770] eta: 0:13:14 time: 0.0389 data: 0.0012 max mem: 33298 +Test: [ 1900/21770] eta: 0:13:10 time: 0.0390 data: 0.0013 max mem: 33298 +Test: [ 2000/21770] eta: 0:13:05 time: 0.0392 data: 0.0012 max mem: 33298 +Test: [ 2100/21770] eta: 0:13:00 time: 0.0389 data: 0.0011 max mem: 33298 +Test: [ 2200/21770] eta: 0:12:56 time: 0.0390 data: 0.0012 max mem: 33298 +Test: [ 2300/21770] eta: 0:12:51 time: 0.0389 data: 0.0012 max mem: 33298 +Test: [ 2400/21770] eta: 0:12:47 time: 0.0392 data: 0.0012 max mem: 33298 +Test: [ 2500/21770] eta: 0:12:43 time: 0.0391 data: 0.0012 max mem: 33298 +Test: [ 2600/21770] eta: 0:12:38 time: 0.0392 data: 0.0012 max mem: 33298 +Test: [ 2700/21770] eta: 0:12:34 time: 0.0388 data: 0.0012 max mem: 33298 +Test: [ 2800/21770] eta: 0:12:30 time: 0.0386 data: 0.0011 max mem: 33298 +Test: [ 2900/21770] eta: 0:12:25 time: 0.0387 data: 0.0011 max mem: 33298 +Test: [ 3000/21770] eta: 0:12:21 time: 0.0390 data: 0.0012 max mem: 33298 +Test: [ 3100/21770] eta: 0:12:17 time: 0.0388 data: 0.0012 max mem: 33298 +Test: [ 3200/21770] eta: 0:12:13 time: 0.0390 data: 0.0012 max mem: 33298 +Test: [ 3300/21770] eta: 0:12:08 time: 0.0392 data: 0.0012 max mem: 33298 +Test: [ 3400/21770] eta: 0:12:04 time: 0.0396 data: 0.0012 max mem: 33298 +Test: [ 3500/21770] eta: 0:12:01 time: 0.0403 data: 0.0012 max mem: 33298 +Test: [ 3600/21770] eta: 0:11:57 time: 0.0400 data: 0.0012 max mem: 33298 +Test: [ 3700/21770] eta: 0:11:53 time: 0.0398 data: 0.0012 max mem: 33298 +Test: [ 3800/21770] eta: 0:11:49 time: 0.0398 data: 0.0012 max mem: 33298 +Test: [ 3900/21770] eta: 0:11:46 time: 0.0394 data: 0.0011 max mem: 33298 +Test: [ 4000/21770] eta: 0:11:42 time: 0.0400 data: 0.0012 max mem: 33298 +Test: [ 4100/21770] eta: 0:11:38 time: 0.0399 data: 0.0012 max mem: 33298 +Test: [ 4200/21770] eta: 0:11:34 time: 0.0399 data: 0.0012 max mem: 33298 +Test: [ 4300/21770] eta: 0:11:30 time: 0.0392 data: 0.0012 max mem: 33298 +Test: [ 4400/21770] eta: 0:11:26 time: 0.0391 data: 0.0013 max mem: 33298 +Test: [ 4500/21770] eta: 0:11:22 time: 0.0391 data: 0.0013 max mem: 33298 +Test: [ 4600/21770] eta: 0:11:18 time: 0.0392 data: 0.0013 max mem: 33298 +Test: [ 4700/21770] eta: 0:11:14 time: 0.0389 data: 0.0012 max mem: 33298 +Test: [ 4800/21770] eta: 0:11:10 time: 0.0389 data: 0.0012 max mem: 33298 +Test: [ 4900/21770] eta: 0:11:06 time: 0.0391 data: 0.0013 max mem: 33298 +Test: [ 5000/21770] eta: 0:11:02 time: 0.0398 data: 0.0012 max mem: 33298 +Test: [ 5100/21770] eta: 0:10:58 time: 0.0391 data: 0.0012 max mem: 33298 +Test: [ 5200/21770] eta: 0:10:54 time: 0.0393 data: 0.0012 max mem: 33298 +Test: [ 5300/21770] eta: 0:10:50 time: 0.0399 data: 0.0012 max mem: 33298 +Test: [ 5400/21770] eta: 0:10:46 time: 0.0400 data: 0.0012 max mem: 33298 +Test: [ 5500/21770] eta: 0:10:42 time: 0.0400 data: 0.0013 max mem: 33298 +Test: [ 5600/21770] eta: 0:10:38 time: 0.0400 data: 0.0012 max mem: 33298 +Test: [ 5700/21770] eta: 0:10:34 time: 0.0399 data: 0.0012 max mem: 33298 +Test: [ 5800/21770] eta: 0:10:31 time: 0.0401 data: 0.0012 max mem: 33298 +Test: [ 5900/21770] eta: 0:10:27 time: 0.0396 data: 0.0012 max mem: 33298 +Test: [ 6000/21770] eta: 0:10:23 time: 0.0394 data: 0.0012 max mem: 33298 +Test: [ 6100/21770] eta: 0:10:19 time: 0.0397 data: 0.0012 max mem: 33298 +Test: [ 6200/21770] eta: 0:10:15 time: 0.0391 data: 0.0012 max mem: 33298 +Test: [ 6300/21770] eta: 0:10:11 time: 0.0393 data: 0.0012 max mem: 33298 +Test: [ 6400/21770] eta: 0:10:07 time: 0.0392 data: 0.0012 max mem: 33298 +Test: [ 6500/21770] eta: 0:10:03 time: 0.0393 data: 0.0011 max mem: 33298 +Test: [ 6600/21770] eta: 0:09:59 time: 0.0392 data: 0.0012 max mem: 33298 +Test: [ 6700/21770] eta: 0:09:55 time: 0.0400 data: 0.0012 max mem: 33298 +Test: [ 6800/21770] eta: 0:09:51 time: 0.0400 data: 0.0012 max mem: 33298 +Test: [ 6900/21770] eta: 0:09:47 time: 0.0396 data: 0.0012 max mem: 33298 +Test: [ 7000/21770] eta: 0:09:43 time: 0.0395 data: 0.0012 max mem: 33298 +Test: [ 7100/21770] eta: 0:09:39 time: 0.0392 data: 0.0012 max mem: 33298 +Test: [ 7200/21770] eta: 0:09:35 time: 0.0393 data: 0.0012 max mem: 33298 +Test: [ 7300/21770] eta: 0:09:31 time: 0.0395 data: 0.0012 max mem: 33298 +Test: [ 7400/21770] eta: 0:09:27 time: 0.0402 data: 0.0013 max mem: 33298 +Test: [ 7500/21770] eta: 0:09:23 time: 0.0390 data: 0.0012 max mem: 33298 +Test: [ 7600/21770] eta: 0:09:19 time: 0.0390 data: 0.0012 max mem: 33298 +Test: [ 7700/21770] eta: 0:09:15 time: 0.0389 data: 0.0012 max mem: 33298 +Test: [ 7800/21770] eta: 0:09:11 time: 0.0397 data: 0.0012 max mem: 33298 +Test: [ 7900/21770] eta: 0:09:07 time: 0.0391 data: 0.0012 max mem: 33298 +Test: [ 8000/21770] eta: 0:09:03 time: 0.0393 data: 0.0012 max mem: 33298 +Test: [ 8100/21770] eta: 0:08:59 time: 0.0389 data: 0.0012 max mem: 33298 +Test: [ 8200/21770] eta: 0:08:55 time: 0.0397 data: 0.0013 max mem: 33298 +Test: [ 8300/21770] eta: 0:08:51 time: 0.0391 data: 0.0011 max mem: 33298 +Test: [ 8400/21770] eta: 0:08:47 time: 0.0391 data: 0.0012 max mem: 33298 +Test: [ 8500/21770] eta: 0:08:43 time: 0.0391 data: 0.0011 max mem: 33298 +Test: [ 8600/21770] eta: 0:08:39 time: 0.0390 data: 0.0012 max mem: 33298 +Test: [ 8700/21770] eta: 0:08:35 time: 0.0391 data: 0.0011 max mem: 33298 +Test: [ 8800/21770] eta: 0:08:31 time: 0.0390 data: 0.0012 max mem: 33298 +Test: [ 8900/21770] eta: 0:08:27 time: 0.0393 data: 0.0012 max mem: 33298 +Test: [ 9000/21770] eta: 0:08:23 time: 0.0387 data: 0.0012 max mem: 33298 +Test: [ 9100/21770] eta: 0:08:19 time: 0.0387 data: 0.0012 max mem: 33298 +Test: [ 9200/21770] eta: 0:08:15 time: 0.0387 data: 0.0011 max mem: 33298 +Test: [ 9300/21770] eta: 0:08:11 time: 0.0391 data: 0.0011 max mem: 33298 +Test: [ 9400/21770] eta: 0:08:07 time: 0.0387 data: 0.0012 max mem: 33298 +Test: [ 9500/21770] eta: 0:08:03 time: 0.0387 data: 0.0012 max mem: 33298 +Test: [ 9600/21770] eta: 0:07:59 time: 0.0388 data: 0.0012 max mem: 33298 +Test: [ 9700/21770] eta: 0:07:55 time: 0.0391 data: 0.0011 max mem: 33298 +Test: [ 9800/21770] eta: 0:07:51 time: 0.0392 data: 0.0012 max mem: 33298 +Test: [ 9900/21770] eta: 0:07:47 time: 0.0394 data: 0.0012 max mem: 33298 +Test: [10000/21770] eta: 0:07:43 time: 0.0387 data: 0.0012 max mem: 33298 +Test: [10100/21770] eta: 0:07:39 time: 0.0388 data: 0.0012 max mem: 33298 +Test: [10200/21770] eta: 0:07:35 time: 0.0390 data: 0.0011 max mem: 33298 +Test: [10300/21770] eta: 0:07:31 time: 0.0394 data: 0.0012 max mem: 33298 +Test: [10400/21770] eta: 0:07:27 time: 0.0390 data: 0.0012 max mem: 33298 +Test: [10500/21770] eta: 0:07:23 time: 0.0392 data: 0.0012 max mem: 33298 +Test: [10600/21770] eta: 0:07:19 time: 0.0389 data: 0.0012 max mem: 33298 +Test: [10700/21770] eta: 0:07:15 time: 0.0387 data: 0.0012 max mem: 33298 +Test: [10800/21770] eta: 0:07:11 time: 0.0387 data: 0.0012 max mem: 33298 +Test: [10900/21770] eta: 0:07:07 time: 0.0388 data: 0.0011 max mem: 33298 +Test: [11000/21770] eta: 0:07:03 time: 0.0389 data: 0.0012 max mem: 33298 +Test: [11100/21770] eta: 0:06:59 time: 0.0389 data: 0.0012 max mem: 33298 +Test: [11200/21770] eta: 0:06:55 time: 0.0390 data: 0.0011 max mem: 33298 +Test: [11300/21770] eta: 0:06:51 time: 0.0393 data: 0.0012 max mem: 33298 +Test: [11400/21770] eta: 0:06:48 time: 0.0389 data: 0.0012 max mem: 33298 +Test: [11500/21770] eta: 0:06:44 time: 0.0396 data: 0.0012 max mem: 33298 +Test: [11600/21770] eta: 0:06:40 time: 0.0397 data: 0.0012 max mem: 33298 +Test: [11700/21770] eta: 0:06:36 time: 0.0397 data: 0.0012 max mem: 33298 +Test: [11800/21770] eta: 0:06:32 time: 0.0394 data: 0.0012 max mem: 33298 +Test: [11900/21770] eta: 0:06:28 time: 0.0394 data: 0.0011 max mem: 33298 +Test: [12000/21770] eta: 0:06:24 time: 0.0392 data: 0.0012 max mem: 33298 +Test: [12100/21770] eta: 0:06:20 time: 0.0398 data: 0.0012 max mem: 33298 +Test: [12200/21770] eta: 0:06:16 time: 0.0389 data: 0.0012 max mem: 33298 +Test: [12300/21770] eta: 0:06:12 time: 0.0388 data: 0.0012 max mem: 33298 +Test: [12400/21770] eta: 0:06:08 time: 0.0388 data: 0.0012 max mem: 33298 +Test: [12500/21770] eta: 0:06:04 time: 0.0387 data: 0.0012 max mem: 33298 +Test: [12600/21770] eta: 0:06:00 time: 0.0387 data: 0.0012 max mem: 33298 +Test: [12700/21770] eta: 0:05:56 time: 0.0388 data: 0.0012 max mem: 33298 +Test: [12800/21770] eta: 0:05:52 time: 0.0387 data: 0.0011 max mem: 33298 +Test: [12900/21770] eta: 0:05:48 time: 0.0387 data: 0.0012 max mem: 33298 +Test: [13000/21770] eta: 0:05:44 time: 0.0395 data: 0.0012 max mem: 33298 +Test: [13100/21770] eta: 0:05:40 time: 0.0391 data: 0.0012 max mem: 33298 +Test: [13200/21770] eta: 0:05:36 time: 0.0398 data: 0.0011 max mem: 33298 +Test: [13300/21770] eta: 0:05:33 time: 0.0402 data: 0.0011 max mem: 33298 +Test: [13400/21770] eta: 0:05:29 time: 0.0398 data: 0.0012 max mem: 33298 +Test: [13500/21770] eta: 0:05:25 time: 0.0403 data: 0.0012 max mem: 33298 +Test: [13600/21770] eta: 0:05:21 time: 0.0397 data: 0.0011 max mem: 33298 +Test: [13700/21770] eta: 0:05:17 time: 0.0389 data: 0.0012 max mem: 33298 +Test: [13800/21770] eta: 0:05:13 time: 0.0393 data: 0.0012 max mem: 33298 +Test: [13900/21770] eta: 0:05:09 time: 0.0394 data: 0.0012 max mem: 33298 +Test: [14000/21770] eta: 0:05:05 time: 0.0403 data: 0.0012 max mem: 33298 +Test: [14100/21770] eta: 0:05:01 time: 0.0395 data: 0.0011 max mem: 33298 +Test: [14200/21770] eta: 0:04:57 time: 0.0397 data: 0.0012 max mem: 33298 +Test: [14300/21770] eta: 0:04:53 time: 0.0387 data: 0.0012 max mem: 33298 +Test: [14400/21770] eta: 0:04:49 time: 0.0391 data: 0.0012 max mem: 33298 +Test: [14500/21770] eta: 0:04:46 time: 0.0387 data: 0.0011 max mem: 33298 +Test: [14600/21770] eta: 0:04:42 time: 0.0386 data: 0.0011 max mem: 33298 +Test: [14700/21770] eta: 0:04:38 time: 0.0386 data: 0.0011 max mem: 33298 +Test: [14800/21770] eta: 0:04:34 time: 0.0398 data: 0.0011 max mem: 33298 +Test: [14900/21770] eta: 0:04:30 time: 0.0397 data: 0.0011 max mem: 33298 +Test: [15000/21770] eta: 0:04:26 time: 0.0391 data: 0.0011 max mem: 33298 +Test: [15100/21770] eta: 0:04:22 time: 0.0400 data: 0.0011 max mem: 33298 +Test: [15200/21770] eta: 0:04:18 time: 0.0401 data: 0.0011 max mem: 33298 +Test: [15300/21770] eta: 0:04:14 time: 0.0388 data: 0.0012 max mem: 33298 +Test: [15400/21770] eta: 0:04:10 time: 0.0389 data: 0.0012 max mem: 33298 +Test: [15500/21770] eta: 0:04:06 time: 0.0389 data: 0.0012 max mem: 33298 +Test: [15600/21770] eta: 0:04:02 time: 0.0388 data: 0.0012 max mem: 33298 +Test: [15700/21770] eta: 0:03:58 time: 0.0388 data: 0.0012 max mem: 33298 +Test: [15800/21770] eta: 0:03:54 time: 0.0387 data: 0.0012 max mem: 33298 +Test: [15900/21770] eta: 0:03:50 time: 0.0390 data: 0.0012 max mem: 33298 +Test: [16000/21770] eta: 0:03:46 time: 0.0392 data: 0.0012 max mem: 33298 +Test: [16100/21770] eta: 0:03:42 time: 0.0391 data: 0.0012 max mem: 33298 +Test: [16200/21770] eta: 0:03:39 time: 0.0392 data: 0.0012 max mem: 33298 +Test: [16300/21770] eta: 0:03:35 time: 0.0390 data: 0.0012 max mem: 33298 +Test: [16400/21770] eta: 0:03:31 time: 0.0394 data: 0.0012 max mem: 33298 +Test: [16500/21770] eta: 0:03:27 time: 0.0398 data: 0.0012 max mem: 33298 +Test: [16600/21770] eta: 0:03:23 time: 0.0387 data: 0.0011 max mem: 33298 +Test: [16700/21770] eta: 0:03:19 time: 0.0387 data: 0.0012 max mem: 33298 +Test: [16800/21770] eta: 0:03:15 time: 0.0393 data: 0.0012 max mem: 33298 +Test: [16900/21770] eta: 0:03:11 time: 0.0387 data: 0.0012 max mem: 33298 +Test: [17000/21770] eta: 0:03:07 time: 0.0386 data: 0.0011 max mem: 33298 +Test: [17100/21770] eta: 0:03:03 time: 0.0392 data: 0.0012 max mem: 33298 +Test: [17200/21770] eta: 0:02:59 time: 0.0389 data: 0.0012 max mem: 33298 +Test: [17300/21770] eta: 0:02:55 time: 0.0390 data: 0.0012 max mem: 33298 +Test: [17400/21770] eta: 0:02:51 time: 0.0392 data: 0.0012 max mem: 33298 +Test: [17500/21770] eta: 0:02:47 time: 0.0391 data: 0.0012 max mem: 33298 +Test: [17600/21770] eta: 0:02:43 time: 0.0390 data: 0.0012 max mem: 33298 +Test: [17700/21770] eta: 0:02:39 time: 0.0391 data: 0.0012 max mem: 33298 +Test: [17800/21770] eta: 0:02:36 time: 0.0390 data: 0.0012 max mem: 33298 +Test: [17900/21770] eta: 0:02:32 time: 0.0390 data: 0.0011 max mem: 33298 +Test: [18000/21770] eta: 0:02:28 time: 0.0393 data: 0.0012 max mem: 33298 +Test: [18100/21770] eta: 0:02:24 time: 0.0395 data: 0.0012 max mem: 33298 +Test: [18200/21770] eta: 0:02:20 time: 0.0393 data: 0.0012 max mem: 33298 +Test: [18300/21770] eta: 0:02:16 time: 0.0396 data: 0.0011 max mem: 33298 +Test: [18400/21770] eta: 0:02:12 time: 0.0392 data: 0.0012 max mem: 33298 +Test: [18500/21770] eta: 0:02:08 time: 0.0392 data: 0.0012 max mem: 33298 +Test: [18600/21770] eta: 0:02:04 time: 0.0390 data: 0.0012 max mem: 33298 +Test: [18700/21770] eta: 0:02:00 time: 0.0390 data: 0.0011 max mem: 33298 +Test: [18800/21770] eta: 0:01:56 time: 0.0388 data: 0.0012 max mem: 33298 +Test: [18900/21770] eta: 0:01:52 time: 0.0387 data: 0.0011 max mem: 33298 +Test: [19000/21770] eta: 0:01:48 time: 0.0387 data: 0.0011 max mem: 33298 +Test: [19100/21770] eta: 0:01:44 time: 0.0390 data: 0.0012 max mem: 33298 +Test: [19200/21770] eta: 0:01:40 time: 0.0387 data: 0.0011 max mem: 33298 +Test: [19300/21770] eta: 0:01:37 time: 0.0390 data: 0.0012 max mem: 33298 +Test: [19400/21770] eta: 0:01:33 time: 0.0390 data: 0.0012 max mem: 33298 +Test: [19500/21770] eta: 0:01:29 time: 0.0389 data: 0.0012 max mem: 33298 +Test: [19600/21770] eta: 0:01:25 time: 0.0392 data: 0.0012 max mem: 33298 +Test: [19700/21770] eta: 0:01:21 time: 0.0394 data: 0.0012 max mem: 33298 +Test: [19800/21770] eta: 0:01:17 time: 0.0400 data: 0.0011 max mem: 33298 +Test: [19900/21770] eta: 0:01:13 time: 0.0397 data: 0.0011 max mem: 33298 +Test: [20000/21770] eta: 0:01:09 time: 0.0390 data: 0.0012 max mem: 33298 +Test: [20100/21770] eta: 0:01:05 time: 0.0398 data: 0.0012 max mem: 33298 +Test: [20200/21770] eta: 0:01:01 time: 0.0391 data: 0.0012 max mem: 33298 +Test: [20300/21770] eta: 0:00:57 time: 0.0390 data: 0.0012 max mem: 33298 +Test: [20400/21770] eta: 0:00:53 time: 0.0390 data: 0.0012 max mem: 33298 +Test: [20500/21770] eta: 0:00:49 time: 0.0390 data: 0.0012 max mem: 33298 +Test: [20600/21770] eta: 0:00:45 time: 0.0390 data: 0.0012 max mem: 33298 +Test: [20700/21770] eta: 0:00:42 time: 0.0390 data: 0.0012 max mem: 33298 +Test: [20800/21770] eta: 0:00:38 time: 0.0390 data: 0.0012 max mem: 33298 +Test: [20900/21770] eta: 0:00:34 time: 0.0391 data: 0.0012 max mem: 33298 +Test: [21000/21770] eta: 0:00:30 time: 0.0390 data: 0.0012 max mem: 33298 +Test: [21100/21770] eta: 0:00:26 time: 0.0388 data: 0.0012 max mem: 33298 +Test: [21200/21770] eta: 0:00:22 time: 0.0389 data: 0.0012 max mem: 33298 +Test: [21300/21770] eta: 0:00:18 time: 0.0390 data: 0.0012 max mem: 33298 +Test: [21400/21770] eta: 0:00:14 time: 0.0393 data: 0.0012 max mem: 33298 +Test: [21500/21770] eta: 0:00:10 time: 0.0394 data: 0.0012 max mem: 33298 +Test: [21600/21770] eta: 0:00:06 time: 0.0391 data: 0.0012 max mem: 33298 +Test: [21700/21770] eta: 0:00:02 time: 0.0391 data: 0.0013 max mem: 33298 +Test: Total time: 0:14:15 +Final results: +Mean IoU is 0.00 + + precision@0.5 = 0.00 + precision@0.6 = 0.00 + precision@0.7 = 0.00 + precision@0.8 = 0.00 + precision@0.9 = 0.00 + overall IoU = 0.00 + mean IoU = 0.00 + +Mean accuracy for one-to-zero sample is 100.00 + +Average object IoU 0.0 +Overall IoU 0.0 +Better epoch: 0 + +Epoch: [1] [ 0/4276] eta: 6:44:18 lr: 4.887331692414045e-05 loss: 0.2073 (0.2073) time: 5.6732 data: 2.1749 max mem: 33298 +Epoch: [1] [ 10/4276] eta: 4:11:40 lr: 4.8870679281670814e-05 loss: 0.2174 (0.2258) time: 3.5397 data: 0.2038 max mem: 33298 +Epoch: [1] [ 20/4276] eta: 4:01:51 lr: 4.886804162338348e-05 loss: 0.2288 (0.2278) time: 3.2965 data: 0.0065 max mem: 33298 +Epoch: [1] [ 30/4276] eta: 3:55:34 lr: 4.886540394927738e-05 loss: 0.2292 (0.2302) time: 3.2131 data: 0.0072 max mem: 33298 +Epoch: [1] [ 40/4276] eta: 3:52:30 lr: 4.886276625935149e-05 loss: 0.2308 (0.2282) time: 3.1709 data: 0.0078 max mem: 33298 +Epoch: [1] [ 50/4276] eta: 3:49:41 lr: 4.8860128553604756e-05 loss: 0.2308 (0.2287) time: 3.1558 data: 0.0073 max mem: 33298 +Epoch: [1] [ 60/4276] eta: 3:48:07 lr: 4.8857490832036145e-05 loss: 0.2173 (0.2312) time: 3.1509 data: 0.0075 max mem: 33298 +Epoch: [1] [ 70/4276] eta: 3:46:42 lr: 4.8854853094644606e-05 loss: 0.2139 (0.2298) time: 3.1657 data: 0.0081 max mem: 33298 +Epoch: [1] [ 80/4276] eta: 3:45:16 lr: 4.8852215341429095e-05 loss: 0.2139 (0.2294) time: 3.1443 data: 0.0083 max mem: 33298 +Epoch: [1] [ 90/4276] eta: 3:43:47 lr: 4.884957757238856e-05 loss: 0.2152 (0.2273) time: 3.1135 data: 0.0080 max mem: 33298 +Epoch: [1] [ 100/4276] eta: 3:42:42 lr: 4.884693978752198e-05 loss: 0.2234 (0.2321) time: 3.1126 data: 0.0075 max mem: 33298 +Epoch: [1] [ 110/4276] eta: 3:41:33 lr: 4.884430198682829e-05 loss: 0.2312 (0.2332) time: 3.1143 data: 0.0070 max mem: 33298 +Epoch: [1] [ 120/4276] eta: 3:40:21 lr: 4.884166417030644e-05 loss: 0.2243 (0.2332) time: 3.0878 data: 0.0073 max mem: 33298 +Epoch: [1] [ 130/4276] eta: 3:39:14 lr: 4.8839026337955394e-05 loss: 0.2293 (0.2347) time: 3.0731 data: 0.0073 max mem: 33298 +Epoch: [1] [ 140/4276] eta: 3:38:27 lr: 4.883638848977413e-05 loss: 0.2549 (0.2351) time: 3.0952 data: 0.0070 max mem: 33298 +Epoch: [1] [ 150/4276] eta: 3:37:45 lr: 4.883375062576156e-05 loss: 0.2175 (0.2338) time: 3.1252 data: 0.0070 max mem: 33298 +Epoch: [1] [ 160/4276] eta: 3:37:08 lr: 4.883111274591667e-05 loss: 0.2180 (0.2340) time: 3.1381 data: 0.0074 max mem: 33298 +Epoch: [1] [ 170/4276] eta: 3:36:38 lr: 4.88284748502384e-05 loss: 0.2302 (0.2346) time: 3.1594 data: 0.0083 max mem: 33298 +Epoch: [1] [ 180/4276] eta: 3:36:04 lr: 4.8825836938725715e-05 loss: 0.2407 (0.2352) time: 3.1656 data: 0.0086 max mem: 33298 +Epoch: [1] [ 190/4276] eta: 3:35:32 lr: 4.8823199011377564e-05 loss: 0.2495 (0.2363) time: 3.1600 data: 0.0084 max mem: 33298 +Epoch: [1] [ 200/4276] eta: 3:35:01 lr: 4.88205610681929e-05 loss: 0.2471 (0.2371) time: 3.1661 data: 0.0085 max mem: 33298 +Epoch: [1] [ 210/4276] eta: 3:34:37 lr: 4.881792310917068e-05 loss: 0.2370 (0.2368) time: 3.1874 data: 0.0090 max mem: 33298 +Epoch: [1] [ 220/4276] eta: 3:34:08 lr: 4.881528513430986e-05 loss: 0.2314 (0.2363) time: 3.1928 data: 0.0091 max mem: 33298 +Epoch: [1] [ 230/4276] eta: 3:33:35 lr: 4.881264714360938e-05 loss: 0.2208 (0.2357) time: 3.1687 data: 0.0091 max mem: 33298 +Epoch: [1] [ 240/4276] eta: 3:33:02 lr: 4.8810009137068206e-05 loss: 0.2228 (0.2362) time: 3.1600 data: 0.0091 max mem: 33298 +Epoch: [1] [ 250/4276] eta: 3:32:30 lr: 4.880737111468529e-05 loss: 0.2637 (0.2372) time: 3.1621 data: 0.0088 max mem: 33298 +Epoch: [1] [ 260/4276] eta: 3:31:55 lr: 4.880473307645959e-05 loss: 0.2593 (0.2378) time: 3.1557 data: 0.0087 max mem: 33298 +Epoch: [1] [ 270/4276] eta: 3:31:22 lr: 4.880209502239005e-05 loss: 0.2593 (0.2382) time: 3.1520 data: 0.0087 max mem: 33298 +Epoch: [1] [ 280/4276] eta: 3:30:46 lr: 4.879945695247563e-05 loss: 0.2296 (0.2378) time: 3.1434 data: 0.0085 max mem: 33298 +Epoch: [1] [ 290/4276] eta: 3:30:11 lr: 4.8796818866715285e-05 loss: 0.2211 (0.2373) time: 3.1389 data: 0.0079 max mem: 33298 +Epoch: [1] [ 300/4276] eta: 3:29:35 lr: 4.879418076510796e-05 loss: 0.2164 (0.2369) time: 3.1391 data: 0.0076 max mem: 33298 +Epoch: [1] [ 310/4276] eta: 3:29:03 lr: 4.879154264765261e-05 loss: 0.2187 (0.2369) time: 3.1438 data: 0.0084 max mem: 33298 +Epoch: [1] [ 320/4276] eta: 3:28:27 lr: 4.878890451434819e-05 loss: 0.2321 (0.2374) time: 3.1409 data: 0.0090 max mem: 33298 +Epoch: [1] [ 330/4276] eta: 3:27:52 lr: 4.878626636519366e-05 loss: 0.2384 (0.2372) time: 3.1330 data: 0.0092 max mem: 33298 +Epoch: [1] [ 340/4276] eta: 3:27:17 lr: 4.8783628200187945e-05 loss: 0.2339 (0.2368) time: 3.1341 data: 0.0091 max mem: 33298 +Epoch: [1] [ 350/4276] eta: 3:26:38 lr: 4.878099001933003e-05 loss: 0.2123 (0.2364) time: 3.1117 data: 0.0081 max mem: 33298 +Epoch: [1] [ 360/4276] eta: 3:26:08 lr: 4.877835182261885e-05 loss: 0.2269 (0.2372) time: 3.1328 data: 0.0083 max mem: 33298 +Epoch: [1] [ 370/4276] eta: 3:25:38 lr: 4.8775713610053366e-05 loss: 0.2269 (0.2368) time: 3.1712 data: 0.0085 max mem: 33298 +Epoch: [1] [ 380/4276] eta: 3:25:07 lr: 4.877307538163252e-05 loss: 0.2092 (0.2368) time: 3.1702 data: 0.0079 max mem: 33298 +Epoch: [1] [ 390/4276] eta: 3:24:37 lr: 4.877043713735526e-05 loss: 0.2407 (0.2372) time: 3.1704 data: 0.0082 max mem: 33298 +Epoch: [1] [ 400/4276] eta: 3:24:06 lr: 4.8767798877220556e-05 loss: 0.2427 (0.2375) time: 3.1677 data: 0.0083 max mem: 33298 +Epoch: [1] [ 410/4276] eta: 3:23:35 lr: 4.8765160601227356e-05 loss: 0.2320 (0.2373) time: 3.1641 data: 0.0080 max mem: 33298 +Epoch: [1] [ 420/4276] eta: 3:22:59 lr: 4.876252230937459e-05 loss: 0.2262 (0.2377) time: 3.1391 data: 0.0080 max mem: 33298 +Epoch: [1] [ 430/4276] eta: 3:22:18 lr: 4.875988400166123e-05 loss: 0.2306 (0.2376) time: 3.0848 data: 0.0073 max mem: 33298 +Epoch: [1] [ 440/4276] eta: 3:21:38 lr: 4.875724567808622e-05 loss: 0.2357 (0.2373) time: 3.0540 data: 0.0068 max mem: 33298 +Epoch: [1] [ 450/4276] eta: 3:21:00 lr: 4.875460733864852e-05 loss: 0.2364 (0.2376) time: 3.0654 data: 0.0075 max mem: 33298 +Epoch: [1] [ 460/4276] eta: 3:20:25 lr: 4.875196898334706e-05 loss: 0.2252 (0.2372) time: 3.0954 data: 0.0078 max mem: 33298 +Epoch: [1] [ 470/4276] eta: 3:19:51 lr: 4.874933061218082e-05 loss: 0.2128 (0.2370) time: 3.1159 data: 0.0081 max mem: 33298 +Epoch: [1] [ 480/4276] eta: 3:19:18 lr: 4.874669222514871e-05 loss: 0.2208 (0.2369) time: 3.1273 data: 0.0084 max mem: 33298 +Epoch: [1] [ 490/4276] eta: 3:18:48 lr: 4.874405382224973e-05 loss: 0.2208 (0.2369) time: 3.1504 data: 0.0092 max mem: 33298 +Epoch: [1] [ 500/4276] eta: 3:18:16 lr: 4.874141540348279e-05 loss: 0.2243 (0.2368) time: 3.1586 data: 0.0098 max mem: 33298 +Epoch: [1] [ 510/4276] eta: 3:17:45 lr: 4.873877696884686e-05 loss: 0.2250 (0.2364) time: 3.1512 data: 0.0092 max mem: 33298 +Epoch: [1] [ 520/4276] eta: 3:17:08 lr: 4.8736138518340883e-05 loss: 0.2228 (0.2364) time: 3.1175 data: 0.0083 max mem: 33298 +Epoch: [1] [ 530/4276] eta: 3:16:33 lr: 4.8733500051963815e-05 loss: 0.2398 (0.2364) time: 3.0919 data: 0.0075 max mem: 33298 +Epoch: [1] [ 540/4276] eta: 3:15:57 lr: 4.8730861569714595e-05 loss: 0.2327 (0.2363) time: 3.0876 data: 0.0073 max mem: 33298 +Epoch: [1] [ 550/4276] eta: 3:15:26 lr: 4.872822307159218e-05 loss: 0.2395 (0.2366) time: 3.1162 data: 0.0080 max mem: 33298 +Epoch: [1] [ 560/4276] eta: 3:14:54 lr: 4.8725584557595524e-05 loss: 0.2499 (0.2369) time: 3.1473 data: 0.0086 max mem: 33298 +Epoch: [1] [ 570/4276] eta: 3:14:23 lr: 4.872294602772358e-05 loss: 0.2345 (0.2369) time: 3.1453 data: 0.0085 max mem: 33298 +Epoch: [1] [ 580/4276] eta: 3:13:53 lr: 4.872030748197527e-05 loss: 0.2411 (0.2368) time: 3.1638 data: 0.0094 max mem: 33298 +Epoch: [1] [ 590/4276] eta: 3:13:23 lr: 4.871766892034957e-05 loss: 0.2251 (0.2364) time: 3.1749 data: 0.0094 max mem: 33298 +Epoch: [1] [ 600/4276] eta: 3:12:53 lr: 4.871503034284543e-05 loss: 0.2192 (0.2364) time: 3.1742 data: 0.0087 max mem: 33300 +Epoch: [1] [ 610/4276] eta: 3:12:22 lr: 4.871239174946177e-05 loss: 0.2133 (0.2360) time: 3.1585 data: 0.0085 max mem: 33300 +Epoch: [1] [ 620/4276] eta: 3:11:50 lr: 4.870975314019757e-05 loss: 0.2077 (0.2359) time: 3.1403 data: 0.0088 max mem: 33300 +Epoch: [1] [ 630/4276] eta: 3:11:17 lr: 4.8707114515051765e-05 loss: 0.2333 (0.2362) time: 3.1346 data: 0.0087 max mem: 33300 +Epoch: [1] [ 640/4276] eta: 3:10:45 lr: 4.8704475874023306e-05 loss: 0.2326 (0.2360) time: 3.1350 data: 0.0089 max mem: 33300 +Epoch: [1] [ 650/4276] eta: 3:10:11 lr: 4.870183721711114e-05 loss: 0.2174 (0.2359) time: 3.1230 data: 0.0094 max mem: 33300 +Epoch: [1] [ 660/4276] eta: 3:09:36 lr: 4.869919854431422e-05 loss: 0.2223 (0.2359) time: 3.0960 data: 0.0091 max mem: 33300 +Epoch: [1] [ 670/4276] eta: 3:09:01 lr: 4.869655985563148e-05 loss: 0.2186 (0.2356) time: 3.0784 data: 0.0085 max mem: 33300 +Epoch: [1] [ 680/4276] eta: 3:08:26 lr: 4.8693921151061884e-05 loss: 0.2162 (0.2354) time: 3.0724 data: 0.0078 max mem: 33300 +Epoch: [1] [ 690/4276] eta: 3:07:55 lr: 4.8691282430604374e-05 loss: 0.2162 (0.2352) time: 3.1136 data: 0.0079 max mem: 33300 +Epoch: [1] [ 700/4276] eta: 3:07:25 lr: 4.868864369425789e-05 loss: 0.2236 (0.2353) time: 3.1700 data: 0.0079 max mem: 33300 +Epoch: [1] [ 710/4276] eta: 3:06:52 lr: 4.868600494202139e-05 loss: 0.2474 (0.2355) time: 3.1451 data: 0.0076 max mem: 33300 +Epoch: [1] [ 720/4276] eta: 3:06:20 lr: 4.868336617389383e-05 loss: 0.2415 (0.2355) time: 3.1145 data: 0.0078 max mem: 33300 +Epoch: [1] [ 730/4276] eta: 3:05:49 lr: 4.868072738987413e-05 loss: 0.2415 (0.2358) time: 3.1389 data: 0.0079 max mem: 33300 +Epoch: [1] [ 740/4276] eta: 3:05:19 lr: 4.867808858996126e-05 loss: 0.2375 (0.2359) time: 3.1685 data: 0.0081 max mem: 33300 +Epoch: [1] [ 750/4276] eta: 3:04:50 lr: 4.867544977415415e-05 loss: 0.2251 (0.2357) time: 3.1891 data: 0.0083 max mem: 33300 +Epoch: [1] [ 760/4276] eta: 3:04:21 lr: 4.867281094245177e-05 loss: 0.2072 (0.2354) time: 3.1969 data: 0.0085 max mem: 33300 +Epoch: [1] [ 770/4276] eta: 3:03:53 lr: 4.867017209485304e-05 loss: 0.2160 (0.2355) time: 3.2055 data: 0.0086 max mem: 33300 +Epoch: [1] [ 780/4276] eta: 3:03:23 lr: 4.8667533231356924e-05 loss: 0.2282 (0.2356) time: 3.2065 data: 0.0085 max mem: 33300 +Epoch: [1] [ 790/4276] eta: 3:02:54 lr: 4.866489435196236e-05 loss: 0.2395 (0.2359) time: 3.1990 data: 0.0088 max mem: 33300 +Epoch: [1] [ 800/4276] eta: 3:02:24 lr: 4.8662255456668307e-05 loss: 0.2398 (0.2359) time: 3.1874 data: 0.0085 max mem: 33300 +Epoch: [1] [ 810/4276] eta: 3:01:52 lr: 4.86596165454737e-05 loss: 0.2342 (0.2359) time: 3.1584 data: 0.0083 max mem: 33300 +Epoch: [1] [ 820/4276] eta: 3:01:18 lr: 4.865697761837748e-05 loss: 0.2450 (0.2359) time: 3.1079 data: 0.0084 max mem: 33300 +Epoch: [1] [ 830/4276] eta: 3:00:44 lr: 4.8654338675378614e-05 loss: 0.2360 (0.2361) time: 3.0917 data: 0.0083 max mem: 33300 +Epoch: [1] [ 840/4276] eta: 3:00:10 lr: 4.865169971647603e-05 loss: 0.2263 (0.2362) time: 3.0913 data: 0.0090 max mem: 33300 +Epoch: [1] [ 850/4276] eta: 2:59:36 lr: 4.8649060741668674e-05 loss: 0.2145 (0.2362) time: 3.0739 data: 0.0091 max mem: 33300 +Epoch: [1] [ 860/4276] eta: 2:59:01 lr: 4.864642175095549e-05 loss: 0.2118 (0.2362) time: 3.0677 data: 0.0083 max mem: 33300 +Epoch: [1] [ 870/4276] eta: 2:58:26 lr: 4.8643782744335434e-05 loss: 0.2287 (0.2363) time: 3.0615 data: 0.0081 max mem: 33300 +Epoch: [1] [ 880/4276] eta: 2:57:51 lr: 4.8641143721807456e-05 loss: 0.2357 (0.2364) time: 3.0600 data: 0.0079 max mem: 33300 +Epoch: [1] [ 890/4276] eta: 2:57:17 lr: 4.863850468337047e-05 loss: 0.2289 (0.2364) time: 3.0609 data: 0.0078 max mem: 33300 +Epoch: [1] [ 900/4276] eta: 2:56:44 lr: 4.8635865629023455e-05 loss: 0.2239 (0.2363) time: 3.0760 data: 0.0084 max mem: 33300 +Epoch: [1] [ 910/4276] eta: 2:56:11 lr: 4.8633226558765346e-05 loss: 0.2339 (0.2364) time: 3.1019 data: 0.0088 max mem: 33300 +Epoch: [1] [ 920/4276] eta: 2:55:39 lr: 4.863058747259508e-05 loss: 0.2410 (0.2365) time: 3.1209 data: 0.0082 max mem: 33300 +Epoch: [1] [ 930/4276] eta: 2:55:06 lr: 4.8627948370511605e-05 loss: 0.2287 (0.2364) time: 3.1029 data: 0.0083 max mem: 33300 +Epoch: [1] [ 940/4276] eta: 2:54:34 lr: 4.8625309252513865e-05 loss: 0.2101 (0.2363) time: 3.1027 data: 0.0087 max mem: 33300 +Epoch: [1] [ 950/4276] eta: 2:54:04 lr: 4.862267011860081e-05 loss: 0.2130 (0.2361) time: 3.1575 data: 0.0090 max mem: 33300 +Epoch: [1] [ 960/4276] eta: 2:53:35 lr: 4.862003096877138e-05 loss: 0.2220 (0.2361) time: 3.2010 data: 0.0088 max mem: 33300 +Epoch: [1] [ 970/4276] eta: 2:53:05 lr: 4.861739180302451e-05 loss: 0.2265 (0.2360) time: 3.1995 data: 0.0080 max mem: 33300 +Epoch: [1] [ 980/4276] eta: 2:52:34 lr: 4.861475262135917e-05 loss: 0.2331 (0.2363) time: 3.1615 data: 0.0083 max mem: 33300 +Epoch: [1] [ 990/4276] eta: 2:52:02 lr: 4.8612113423774274e-05 loss: 0.2281 (0.2362) time: 3.1304 data: 0.0085 max mem: 33300 +Epoch: [1] [1000/4276] eta: 2:51:30 lr: 4.8609474210268785e-05 loss: 0.2278 (0.2362) time: 3.1311 data: 0.0079 max mem: 33300 +Epoch: [1] [1010/4276] eta: 2:50:59 lr: 4.860683498084163e-05 loss: 0.2201 (0.2360) time: 3.1436 data: 0.0076 max mem: 33300 +Epoch: [1] [1020/4276] eta: 2:50:27 lr: 4.860419573549177e-05 loss: 0.2162 (0.2359) time: 3.1395 data: 0.0088 max mem: 33300 +Epoch: [1] [1030/4276] eta: 2:49:56 lr: 4.860155647421814e-05 loss: 0.2278 (0.2361) time: 3.1427 data: 0.0092 max mem: 33300 +Epoch: [1] [1040/4276] eta: 2:49:26 lr: 4.859891719701969e-05 loss: 0.2349 (0.2359) time: 3.1604 data: 0.0087 max mem: 33300 +Epoch: [1] [1050/4276] eta: 2:48:54 lr: 4.859627790389535e-05 loss: 0.2326 (0.2360) time: 3.1532 data: 0.0090 max mem: 33300 +Epoch: [1] [1060/4276] eta: 2:48:22 lr: 4.8593638594844065e-05 loss: 0.2326 (0.2362) time: 3.1319 data: 0.0086 max mem: 33300 +Epoch: [1] [1070/4276] eta: 2:47:50 lr: 4.859099926986479e-05 loss: 0.2267 (0.2361) time: 3.1206 data: 0.0081 max mem: 33300 +Epoch: [1] [1080/4276] eta: 2:47:18 lr: 4.8588359928956454e-05 loss: 0.2189 (0.2359) time: 3.1090 data: 0.0078 max mem: 33300 +Epoch: [1] [1090/4276] eta: 2:46:46 lr: 4.858572057211801e-05 loss: 0.2202 (0.2358) time: 3.1218 data: 0.0083 max mem: 33300 +Epoch: [1] [1100/4276] eta: 2:46:14 lr: 4.858308119934839e-05 loss: 0.2135 (0.2358) time: 3.1344 data: 0.0087 max mem: 33300 +Epoch: [1] [1110/4276] eta: 2:45:43 lr: 4.858044181064655e-05 loss: 0.2191 (0.2359) time: 3.1267 data: 0.0082 max mem: 33300 +Epoch: [1] [1120/4276] eta: 2:45:11 lr: 4.857780240601142e-05 loss: 0.2222 (0.2360) time: 3.1264 data: 0.0080 max mem: 33300 +Epoch: [1] [1130/4276] eta: 2:44:40 lr: 4.8575162985441944e-05 loss: 0.2222 (0.2359) time: 3.1398 data: 0.0084 max mem: 33300 +Epoch: [1] [1140/4276] eta: 2:44:09 lr: 4.857252354893706e-05 loss: 0.2317 (0.2358) time: 3.1585 data: 0.0090 max mem: 33300 +Epoch: [1] [1150/4276] eta: 2:43:38 lr: 4.856988409649573e-05 loss: 0.2376 (0.2358) time: 3.1639 data: 0.0087 max mem: 33300 +Epoch: [1] [1160/4276] eta: 2:43:07 lr: 4.856724462811687e-05 loss: 0.2378 (0.2358) time: 3.1609 data: 0.0084 max mem: 33300 +Epoch: [1] [1170/4276] eta: 2:42:37 lr: 4.856460514379943e-05 loss: 0.2280 (0.2358) time: 3.1719 data: 0.0087 max mem: 33300 +Epoch: [1] [1180/4276] eta: 2:42:06 lr: 4.856196564354236e-05 loss: 0.2273 (0.2356) time: 3.1768 data: 0.0089 max mem: 33300 +Epoch: [1] [1190/4276] eta: 2:41:35 lr: 4.855932612734459e-05 loss: 0.2219 (0.2356) time: 3.1486 data: 0.0087 max mem: 33300 +Epoch: [1] [1200/4276] eta: 2:41:03 lr: 4.855668659520506e-05 loss: 0.2276 (0.2356) time: 3.1392 data: 0.0087 max mem: 33300 +Epoch: [1] [1210/4276] eta: 2:40:32 lr: 4.8554047047122725e-05 loss: 0.2150 (0.2355) time: 3.1559 data: 0.0089 max mem: 33300 +Epoch: [1] [1220/4276] eta: 2:40:01 lr: 4.855140748309652e-05 loss: 0.2110 (0.2354) time: 3.1581 data: 0.0086 max mem: 33300 +Epoch: [1] [1230/4276] eta: 2:39:30 lr: 4.854876790312537e-05 loss: 0.2168 (0.2353) time: 3.1498 data: 0.0080 max mem: 33300 +Epoch: [1] [1240/4276] eta: 2:38:58 lr: 4.8546128307208234e-05 loss: 0.2408 (0.2354) time: 3.1417 data: 0.0076 max mem: 33300 +Epoch: [1] [1250/4276] eta: 2:38:27 lr: 4.854348869534404e-05 loss: 0.2408 (0.2354) time: 3.1481 data: 0.0072 max mem: 33300 +Epoch: [1] [1260/4276] eta: 2:37:56 lr: 4.854084906753174e-05 loss: 0.2129 (0.2353) time: 3.1528 data: 0.0071 max mem: 33300 +Epoch: [1] [1270/4276] eta: 2:37:25 lr: 4.853820942377028e-05 loss: 0.2270 (0.2355) time: 3.1482 data: 0.0074 max mem: 33300 +Epoch: [1] [1280/4276] eta: 2:36:54 lr: 4.853556976405857e-05 loss: 0.2385 (0.2355) time: 3.1470 data: 0.0081 max mem: 33300 +Epoch: [1] [1290/4276] eta: 2:36:22 lr: 4.853293008839557e-05 loss: 0.2385 (0.2356) time: 3.1414 data: 0.0084 max mem: 33300 +Epoch: [1] [1300/4276] eta: 2:35:50 lr: 4.853029039678023e-05 loss: 0.2233 (0.2355) time: 3.1324 data: 0.0083 max mem: 33300 +Epoch: [1] [1310/4276] eta: 2:35:18 lr: 4.852765068921146e-05 loss: 0.2161 (0.2353) time: 3.1265 data: 0.0084 max mem: 33300 +Epoch: [1] [1320/4276] eta: 2:34:46 lr: 4.852501096568823e-05 loss: 0.2334 (0.2355) time: 3.1143 data: 0.0080 max mem: 33300 +Epoch: [1] [1330/4276] eta: 2:34:13 lr: 4.8522371226209455e-05 loss: 0.2201 (0.2353) time: 3.0883 data: 0.0081 max mem: 33300 +Epoch: [1] [1340/4276] eta: 2:33:40 lr: 4.8519731470774096e-05 loss: 0.2098 (0.2352) time: 3.0694 data: 0.0082 max mem: 33300 +Epoch: [1] [1350/4276] eta: 2:33:07 lr: 4.851709169938107e-05 loss: 0.2231 (0.2352) time: 3.0612 data: 0.0076 max mem: 33300 +Epoch: [1] [1360/4276] eta: 2:32:35 lr: 4.8514451912029326e-05 loss: 0.2271 (0.2352) time: 3.0863 data: 0.0089 max mem: 33300 +Epoch: [1] [1370/4276] eta: 2:32:03 lr: 4.851181210871781e-05 loss: 0.2229 (0.2350) time: 3.1105 data: 0.0098 max mem: 33300 +Epoch: [1] [1380/4276] eta: 2:31:30 lr: 4.8509172289445446e-05 loss: 0.2230 (0.2350) time: 3.0811 data: 0.0089 max mem: 33300 +Epoch: [1] [1390/4276] eta: 2:30:57 lr: 4.850653245421119e-05 loss: 0.2230 (0.2350) time: 3.0712 data: 0.0080 max mem: 33300 +Epoch: [1] [1400/4276] eta: 2:30:25 lr: 4.850389260301396e-05 loss: 0.2206 (0.2351) time: 3.0995 data: 0.0080 max mem: 33300 +Epoch: [1] [1410/4276] eta: 2:29:54 lr: 4.850125273585271e-05 loss: 0.2309 (0.2352) time: 3.1160 data: 0.0082 max mem: 33300 +Epoch: [1] [1420/4276] eta: 2:29:22 lr: 4.8498612852726374e-05 loss: 0.2374 (0.2353) time: 3.1206 data: 0.0080 max mem: 33300 +Epoch: [1] [1430/4276] eta: 2:28:50 lr: 4.849597295363388e-05 loss: 0.2203 (0.2352) time: 3.1298 data: 0.0078 max mem: 33300 +Epoch: [1] [1440/4276] eta: 2:28:19 lr: 4.849333303857418e-05 loss: 0.2201 (0.2354) time: 3.1389 data: 0.0076 max mem: 33300 +Epoch: [1] [1450/4276] eta: 2:27:48 lr: 4.84906931075462e-05 loss: 0.2329 (0.2354) time: 3.1407 data: 0.0074 max mem: 33300 +Epoch: [1] [1460/4276] eta: 2:27:17 lr: 4.8488053160548894e-05 loss: 0.2374 (0.2355) time: 3.1512 data: 0.0077 max mem: 33300 +Epoch: [1] [1470/4276] eta: 2:26:46 lr: 4.848541319758118e-05 loss: 0.2374 (0.2355) time: 3.1578 data: 0.0078 max mem: 33300 +Epoch: [1] [1480/4276] eta: 2:26:15 lr: 4.848277321864201e-05 loss: 0.2323 (0.2356) time: 3.1494 data: 0.0077 max mem: 33300 +Epoch: [1] [1490/4276] eta: 2:25:43 lr: 4.848013322373031e-05 loss: 0.2291 (0.2355) time: 3.1443 data: 0.0083 max mem: 33300 +Epoch: [1] [1500/4276] eta: 2:25:12 lr: 4.847749321284502e-05 loss: 0.2107 (0.2354) time: 3.1320 data: 0.0087 max mem: 33300 +Epoch: [1] [1510/4276] eta: 2:24:39 lr: 4.847485318598508e-05 loss: 0.2059 (0.2353) time: 3.0982 data: 0.0079 max mem: 33300 +Epoch: [1] [1520/4276] eta: 2:24:07 lr: 4.847221314314942e-05 loss: 0.2226 (0.2352) time: 3.0903 data: 0.0080 max mem: 33300 +Epoch: [1] [1530/4276] eta: 2:23:35 lr: 4.846957308433699e-05 loss: 0.2234 (0.2353) time: 3.1079 data: 0.0086 max mem: 33300 +Epoch: [1] [1540/4276] eta: 2:23:03 lr: 4.846693300954671e-05 loss: 0.2225 (0.2352) time: 3.1042 data: 0.0088 max mem: 33300 +Epoch: [1] [1550/4276] eta: 2:22:31 lr: 4.846429291877753e-05 loss: 0.2313 (0.2352) time: 3.0963 data: 0.0082 max mem: 33300 +Epoch: [1] [1560/4276] eta: 2:21:58 lr: 4.8461652812028375e-05 loss: 0.2154 (0.2350) time: 3.0775 data: 0.0075 max mem: 33300 +Epoch: [1] [1570/4276] eta: 2:21:26 lr: 4.845901268929819e-05 loss: 0.2028 (0.2349) time: 3.0797 data: 0.0075 max mem: 33300 +Epoch: [1] [1580/4276] eta: 2:20:55 lr: 4.845637255058591e-05 loss: 0.1979 (0.2347) time: 3.1080 data: 0.0078 max mem: 33300 +Epoch: [1] [1590/4276] eta: 2:20:23 lr: 4.845373239589046e-05 loss: 0.2157 (0.2347) time: 3.1145 data: 0.0081 max mem: 33300 +Epoch: [1] [1600/4276] eta: 2:19:51 lr: 4.8451092225210786e-05 loss: 0.2157 (0.2349) time: 3.1067 data: 0.0080 max mem: 33300 +Epoch: [1] [1610/4276] eta: 2:19:18 lr: 4.8448452038545824e-05 loss: 0.2147 (0.2347) time: 3.0791 data: 0.0083 max mem: 33300 +Epoch: [1] [1620/4276] eta: 2:18:46 lr: 4.8445811835894504e-05 loss: 0.2202 (0.2347) time: 3.0718 data: 0.0087 max mem: 33300 +Epoch: [1] [1630/4276] eta: 2:18:14 lr: 4.844317161725576e-05 loss: 0.2440 (0.2350) time: 3.1005 data: 0.0092 max mem: 33300 +Epoch: [1] [1640/4276] eta: 2:17:42 lr: 4.8440531382628536e-05 loss: 0.2372 (0.2351) time: 3.0923 data: 0.0087 max mem: 33300 +Epoch: [1] [1650/4276] eta: 2:17:10 lr: 4.843789113201176e-05 loss: 0.2241 (0.2351) time: 3.0830 data: 0.0086 max mem: 33300 +Epoch: [1] [1660/4276] eta: 2:16:38 lr: 4.8435250865404364e-05 loss: 0.2241 (0.2350) time: 3.0910 data: 0.0089 max mem: 33300 +Epoch: [1] [1670/4276] eta: 2:16:07 lr: 4.8432610582805283e-05 loss: 0.2269 (0.2350) time: 3.1131 data: 0.0084 max mem: 33300 +Epoch: [1] [1680/4276] eta: 2:15:35 lr: 4.842997028421346e-05 loss: 0.2438 (0.2352) time: 3.1405 data: 0.0089 max mem: 33300 +Epoch: [1] [1690/4276] eta: 2:15:04 lr: 4.842732996962783e-05 loss: 0.2386 (0.2351) time: 3.1381 data: 0.0087 max mem: 33300 +Epoch: [1] [1700/4276] eta: 2:14:33 lr: 4.842468963904731e-05 loss: 0.2333 (0.2352) time: 3.1522 data: 0.0084 max mem: 33300 +Epoch: [1] [1710/4276] eta: 2:14:02 lr: 4.842204929247085e-05 loss: 0.2439 (0.2353) time: 3.1567 data: 0.0084 max mem: 33300 +Epoch: [1] [1720/4276] eta: 2:13:31 lr: 4.841940892989738e-05 loss: 0.2508 (0.2355) time: 3.1379 data: 0.0082 max mem: 33300 +Epoch: [1] [1730/4276] eta: 2:12:59 lr: 4.841676855132584e-05 loss: 0.2414 (0.2354) time: 3.1152 data: 0.0081 max mem: 33300 +Epoch: [1] [1740/4276] eta: 2:12:27 lr: 4.8414128156755154e-05 loss: 0.2168 (0.2354) time: 3.1130 data: 0.0081 max mem: 33300 +Epoch: [1] [1750/4276] eta: 2:11:56 lr: 4.841148774618425e-05 loss: 0.2234 (0.2356) time: 3.1309 data: 0.0081 max mem: 33300 +Epoch: [1] [1760/4276] eta: 2:11:25 lr: 4.840884731961207e-05 loss: 0.2366 (0.2355) time: 3.1424 data: 0.0082 max mem: 33300 +Epoch: [1] [1770/4276] eta: 2:10:54 lr: 4.840620687703756e-05 loss: 0.2366 (0.2354) time: 3.1459 data: 0.0079 max mem: 33300 +Epoch: [1] [1780/4276] eta: 2:10:22 lr: 4.840356641845963e-05 loss: 0.2276 (0.2354) time: 3.1255 data: 0.0080 max mem: 33300 +Epoch: [1] [1790/4276] eta: 2:09:50 lr: 4.840092594387722e-05 loss: 0.2192 (0.2354) time: 3.0895 data: 0.0080 max mem: 33300 +Epoch: [1] [1800/4276] eta: 2:09:17 lr: 4.8398285453289275e-05 loss: 0.2247 (0.2354) time: 3.0554 data: 0.0081 max mem: 33300 +Epoch: [1] [1810/4276] eta: 2:08:45 lr: 4.839564494669472e-05 loss: 0.2478 (0.2355) time: 3.0557 data: 0.0079 max mem: 33300 +Epoch: [1] [1820/4276] eta: 2:08:13 lr: 4.839300442409248e-05 loss: 0.2358 (0.2354) time: 3.0710 data: 0.0075 max mem: 33300 +Epoch: [1] [1830/4276] eta: 2:07:41 lr: 4.8390363885481496e-05 loss: 0.2259 (0.2354) time: 3.0898 data: 0.0077 max mem: 33300 +Epoch: [1] [1840/4276] eta: 2:07:10 lr: 4.83877233308607e-05 loss: 0.2259 (0.2354) time: 3.1167 data: 0.0080 max mem: 33300 +Epoch: [1] [1850/4276] eta: 2:06:38 lr: 4.838508276022902e-05 loss: 0.2259 (0.2354) time: 3.1212 data: 0.0083 max mem: 33300 +Epoch: [1] [1860/4276] eta: 2:06:07 lr: 4.838244217358539e-05 loss: 0.2259 (0.2353) time: 3.1283 data: 0.0086 max mem: 33300 +Epoch: [1] [1870/4276] eta: 2:05:36 lr: 4.8379801570928745e-05 loss: 0.2306 (0.2354) time: 3.1267 data: 0.0088 max mem: 33300 +Epoch: [1] [1880/4276] eta: 2:05:04 lr: 4.837716095225801e-05 loss: 0.2362 (0.2354) time: 3.1165 data: 0.0083 max mem: 33300 +Epoch: [1] [1890/4276] eta: 2:04:32 lr: 4.8374520317572124e-05 loss: 0.2241 (0.2353) time: 3.1145 data: 0.0078 max mem: 33300 +Epoch: [1] [1900/4276] eta: 2:04:01 lr: 4.837187966687002e-05 loss: 0.2202 (0.2352) time: 3.1100 data: 0.0084 max mem: 33300 +Epoch: [1] [1910/4276] eta: 2:03:29 lr: 4.836923900015062e-05 loss: 0.2248 (0.2351) time: 3.0900 data: 0.0086 max mem: 33300 +Epoch: [1] [1920/4276] eta: 2:02:57 lr: 4.836659831741286e-05 loss: 0.2119 (0.2350) time: 3.0836 data: 0.0087 max mem: 33300 +Epoch: [1] [1930/4276] eta: 2:02:25 lr: 4.836395761865566e-05 loss: 0.2119 (0.2349) time: 3.0864 data: 0.0089 max mem: 33300 +Epoch: [1] [1940/4276] eta: 2:01:53 lr: 4.8361316903877977e-05 loss: 0.2430 (0.2351) time: 3.0640 data: 0.0081 max mem: 33300 +Epoch: [1] [1950/4276] eta: 2:01:21 lr: 4.8358676173078724e-05 loss: 0.2333 (0.2350) time: 3.0586 data: 0.0077 max mem: 33300 +Epoch: [1] [1960/4276] eta: 2:00:49 lr: 4.8356035426256833e-05 loss: 0.1980 (0.2349) time: 3.0903 data: 0.0079 max mem: 33300 +Epoch: [1] [1970/4276] eta: 2:00:18 lr: 4.8353394663411235e-05 loss: 0.1905 (0.2347) time: 3.1146 data: 0.0081 max mem: 33300 +Epoch: [1] [1980/4276] eta: 1:59:47 lr: 4.8350753884540856e-05 loss: 0.1880 (0.2345) time: 3.1360 data: 0.0085 max mem: 33300 +Epoch: [1] [1990/4276] eta: 1:59:15 lr: 4.8348113089644635e-05 loss: 0.2092 (0.2346) time: 3.1353 data: 0.0084 max mem: 33300 +Epoch: [1] [2000/4276] eta: 1:58:44 lr: 4.834547227872151e-05 loss: 0.2206 (0.2346) time: 3.1087 data: 0.0086 max mem: 33300 +Epoch: [1] [2010/4276] eta: 1:58:12 lr: 4.834283145177039e-05 loss: 0.2186 (0.2345) time: 3.0843 data: 0.0084 max mem: 33300 +Epoch: [1] [2020/4276] eta: 1:57:40 lr: 4.834019060879021e-05 loss: 0.2312 (0.2345) time: 3.0642 data: 0.0077 max mem: 33300 +Epoch: [1] [2030/4276] eta: 1:57:08 lr: 4.833754974977991e-05 loss: 0.2279 (0.2344) time: 3.0707 data: 0.0080 max mem: 33300 +Epoch: [1] [2040/4276] eta: 1:56:36 lr: 4.833490887473842e-05 loss: 0.2131 (0.2344) time: 3.0885 data: 0.0083 max mem: 33300 +Epoch: [1] [2050/4276] eta: 1:56:05 lr: 4.833226798366465e-05 loss: 0.2381 (0.2344) time: 3.1044 data: 0.0085 max mem: 33300 +Epoch: [1] [2060/4276] eta: 1:55:33 lr: 4.832962707655755e-05 loss: 0.2381 (0.2344) time: 3.1067 data: 0.0084 max mem: 33300 +Epoch: [1] [2070/4276] eta: 1:55:01 lr: 4.8326986153416046e-05 loss: 0.2205 (0.2343) time: 3.1040 data: 0.0080 max mem: 33300 +Epoch: [1] [2080/4276] eta: 1:54:30 lr: 4.832434521423905e-05 loss: 0.2149 (0.2343) time: 3.1100 data: 0.0078 max mem: 33300 +Epoch: [1] [2090/4276] eta: 1:53:59 lr: 4.8321704259025514e-05 loss: 0.2149 (0.2343) time: 3.1128 data: 0.0079 max mem: 33300 +Epoch: [1] [2100/4276] eta: 1:53:27 lr: 4.831906328777435e-05 loss: 0.2198 (0.2342) time: 3.1032 data: 0.0078 max mem: 33300 +Epoch: [1] [2110/4276] eta: 1:52:55 lr: 4.83164223004845e-05 loss: 0.2198 (0.2341) time: 3.0912 data: 0.0077 max mem: 33300 +Epoch: [1] [2120/4276] eta: 1:52:24 lr: 4.831378129715488e-05 loss: 0.2232 (0.2341) time: 3.0878 data: 0.0080 max mem: 33300 +Epoch: [1] [2130/4276] eta: 1:51:52 lr: 4.831114027778443e-05 loss: 0.2133 (0.2340) time: 3.1011 data: 0.0079 max mem: 33300 +Epoch: [1] [2140/4276] eta: 1:51:21 lr: 4.830849924237207e-05 loss: 0.2133 (0.2340) time: 3.1129 data: 0.0079 max mem: 33300 +Epoch: [1] [2150/4276] eta: 1:50:49 lr: 4.830585819091673e-05 loss: 0.2203 (0.2339) time: 3.1206 data: 0.0079 max mem: 33300 +Epoch: [1] [2160/4276] eta: 1:50:18 lr: 4.830321712341734e-05 loss: 0.2183 (0.2339) time: 3.1164 data: 0.0075 max mem: 33300 +Epoch: [1] [2170/4276] eta: 1:49:47 lr: 4.830057603987282e-05 loss: 0.2264 (0.2340) time: 3.1213 data: 0.0073 max mem: 33300 +Epoch: [1] [2180/4276] eta: 1:49:15 lr: 4.829793494028211e-05 loss: 0.2264 (0.2340) time: 3.1367 data: 0.0073 max mem: 33300 +Epoch: [1] [2190/4276] eta: 1:48:44 lr: 4.829529382464413e-05 loss: 0.2398 (0.2341) time: 3.1313 data: 0.0072 max mem: 33300 +Epoch: [1] [2200/4276] eta: 1:48:13 lr: 4.8292652692957805e-05 loss: 0.2300 (0.2340) time: 3.1194 data: 0.0071 max mem: 33300 +Epoch: [1] [2210/4276] eta: 1:47:41 lr: 4.829001154522207e-05 loss: 0.2314 (0.2341) time: 3.1141 data: 0.0072 max mem: 33300 +Epoch: [1] [2220/4276] eta: 1:47:10 lr: 4.828737038143585e-05 loss: 0.2348 (0.2340) time: 3.1226 data: 0.0072 max mem: 33300 +Epoch: [1] [2230/4276] eta: 1:46:39 lr: 4.8284729201598064e-05 loss: 0.2242 (0.2340) time: 3.1320 data: 0.0073 max mem: 33300 +Epoch: [1] [2240/4276] eta: 1:46:07 lr: 4.828208800570765e-05 loss: 0.2229 (0.2339) time: 3.0942 data: 0.0082 max mem: 33300 +Epoch: [1] [2250/4276] eta: 1:45:35 lr: 4.827944679376353e-05 loss: 0.2249 (0.2339) time: 3.0638 data: 0.0083 max mem: 33300 +Epoch: [1] [2260/4276] eta: 1:45:03 lr: 4.8276805565764624e-05 loss: 0.2353 (0.2340) time: 3.0719 data: 0.0085 max mem: 33300 +Epoch: [1] [2270/4276] eta: 1:44:32 lr: 4.827416432170988e-05 loss: 0.2163 (0.2339) time: 3.0760 data: 0.0092 max mem: 33300 +Epoch: [1] [2280/4276] eta: 1:44:00 lr: 4.827152306159819e-05 loss: 0.2150 (0.2339) time: 3.0955 data: 0.0091 max mem: 33300 +Epoch: [1] [2290/4276] eta: 1:43:29 lr: 4.826888178542851e-05 loss: 0.2246 (0.2339) time: 3.1046 data: 0.0088 max mem: 33300 +Epoch: [1] [2300/4276] eta: 1:42:58 lr: 4.826624049319975e-05 loss: 0.2040 (0.2337) time: 3.1147 data: 0.0090 max mem: 33300 +Epoch: [1] [2310/4276] eta: 1:42:26 lr: 4.8263599184910844e-05 loss: 0.2040 (0.2336) time: 3.1268 data: 0.0085 max mem: 33300 +Epoch: [1] [2320/4276] eta: 1:41:55 lr: 4.8260957860560714e-05 loss: 0.2187 (0.2336) time: 3.1222 data: 0.0079 max mem: 33300 +Epoch: [1] [2330/4276] eta: 1:41:24 lr: 4.825831652014829e-05 loss: 0.2187 (0.2336) time: 3.1475 data: 0.0089 max mem: 33300 +Epoch: [1] [2340/4276] eta: 1:40:53 lr: 4.8255675163672486e-05 loss: 0.2162 (0.2335) time: 3.1592 data: 0.0089 max mem: 33300 +Epoch: [1] [2350/4276] eta: 1:40:21 lr: 4.8253033791132246e-05 loss: 0.2162 (0.2334) time: 3.1154 data: 0.0086 max mem: 33300 +Epoch: [1] [2360/4276] eta: 1:39:50 lr: 4.825039240252648e-05 loss: 0.2181 (0.2334) time: 3.0861 data: 0.0088 max mem: 33300 +Epoch: [1] [2370/4276] eta: 1:39:18 lr: 4.8247750997854115e-05 loss: 0.2181 (0.2334) time: 3.0862 data: 0.0083 max mem: 33300 +Epoch: [1] [2380/4276] eta: 1:38:47 lr: 4.824510957711408e-05 loss: 0.1940 (0.2333) time: 3.0924 data: 0.0078 max mem: 33300 +Epoch: [1] [2390/4276] eta: 1:38:15 lr: 4.82424681403053e-05 loss: 0.1940 (0.2332) time: 3.0975 data: 0.0080 max mem: 33300 +Epoch: [1] [2400/4276] eta: 1:37:44 lr: 4.8239826687426695e-05 loss: 0.2150 (0.2332) time: 3.0987 data: 0.0084 max mem: 33300 +Epoch: [1] [2410/4276] eta: 1:37:12 lr: 4.823718521847719e-05 loss: 0.2186 (0.2331) time: 3.0938 data: 0.0086 max mem: 33300 +Epoch: [1] [2420/4276] eta: 1:36:41 lr: 4.823454373345572e-05 loss: 0.2143 (0.2330) time: 3.0885 data: 0.0081 max mem: 33300 +Epoch: [1] [2430/4276] eta: 1:36:09 lr: 4.8231902232361195e-05 loss: 0.2182 (0.2331) time: 3.0947 data: 0.0080 max mem: 33300 +Epoch: [1] [2440/4276] eta: 1:35:38 lr: 4.822926071519255e-05 loss: 0.2361 (0.2331) time: 3.0990 data: 0.0082 max mem: 33300 +Epoch: [1] [2450/4276] eta: 1:35:06 lr: 4.82266191819487e-05 loss: 0.2182 (0.2330) time: 3.0944 data: 0.0084 max mem: 33300 +Epoch: [1] [2460/4276] eta: 1:34:35 lr: 4.822397763262858e-05 loss: 0.2182 (0.2330) time: 3.0983 data: 0.0082 max mem: 33300 +Epoch: [1] [2470/4276] eta: 1:34:03 lr: 4.82213360672311e-05 loss: 0.2360 (0.2331) time: 3.0988 data: 0.0079 max mem: 33300 +Epoch: [1] [2480/4276] eta: 1:33:32 lr: 4.82186944857552e-05 loss: 0.2372 (0.2330) time: 3.0782 data: 0.0087 max mem: 33300 +Epoch: [1] [2490/4276] eta: 1:33:00 lr: 4.8216052888199774e-05 loss: 0.2278 (0.2330) time: 3.0808 data: 0.0088 max mem: 33300 +Epoch: [1] [2500/4276] eta: 1:32:29 lr: 4.821341127456378e-05 loss: 0.2355 (0.2331) time: 3.0956 data: 0.0079 max mem: 33300 +Epoch: [1] [2510/4276] eta: 1:31:58 lr: 4.8210769644846126e-05 loss: 0.2311 (0.2330) time: 3.1118 data: 0.0075 max mem: 33300 +Epoch: [1] [2520/4276] eta: 1:31:26 lr: 4.820812799904573e-05 loss: 0.2191 (0.2329) time: 3.1407 data: 0.0078 max mem: 33300 +Epoch: [1] [2530/4276] eta: 1:30:55 lr: 4.8205486337161525e-05 loss: 0.1950 (0.2328) time: 3.1509 data: 0.0085 max mem: 33300 +Epoch: [1] [2540/4276] eta: 1:30:24 lr: 4.820284465919243e-05 loss: 0.1962 (0.2328) time: 3.1560 data: 0.0086 max mem: 33300 +Epoch: [1] [2550/4276] eta: 1:29:53 lr: 4.8200202965137365e-05 loss: 0.2258 (0.2328) time: 3.1497 data: 0.0077 max mem: 33300 +Epoch: [1] [2560/4276] eta: 1:29:22 lr: 4.819756125499525e-05 loss: 0.1979 (0.2326) time: 3.1259 data: 0.0077 max mem: 33300 +Epoch: [1] [2570/4276] eta: 1:28:50 lr: 4.819491952876501e-05 loss: 0.1989 (0.2326) time: 3.0993 data: 0.0082 max mem: 33300 +Epoch: [1] [2580/4276] eta: 1:28:19 lr: 4.8192277786445575e-05 loss: 0.2053 (0.2326) time: 3.0683 data: 0.0079 max mem: 33300 +Epoch: [1] [2590/4276] eta: 1:27:47 lr: 4.818963602803586e-05 loss: 0.2091 (0.2325) time: 3.0888 data: 0.0080 max mem: 33300 +Epoch: [1] [2600/4276] eta: 1:27:17 lr: 4.818699425353478e-05 loss: 0.2219 (0.2326) time: 3.1889 data: 0.0095 max mem: 33300 +Epoch: [1] [2610/4276] eta: 1:26:46 lr: 4.818435246294127e-05 loss: 0.2222 (0.2325) time: 3.2411 data: 0.0101 max mem: 33300 +Epoch: [1] [2620/4276] eta: 1:26:16 lr: 4.818171065625425e-05 loss: 0.2166 (0.2325) time: 3.2392 data: 0.0095 max mem: 33300 +Epoch: [1] [2630/4276] eta: 1:25:45 lr: 4.817906883347262e-05 loss: 0.2166 (0.2325) time: 3.2303 data: 0.0091 max mem: 33300 +Epoch: [1] [2640/4276] eta: 1:25:14 lr: 4.8176426994595336e-05 loss: 0.1977 (0.2324) time: 3.1991 data: 0.0095 max mem: 33300 +Epoch: [1] [2650/4276] eta: 1:24:44 lr: 4.8173785139621294e-05 loss: 0.2047 (0.2323) time: 3.2176 data: 0.0103 max mem: 33300 +Epoch: [1] [2660/4276] eta: 1:24:13 lr: 4.817114326854943e-05 loss: 0.2134 (0.2323) time: 3.2443 data: 0.0103 max mem: 33300 +Epoch: [1] [2670/4276] eta: 1:23:43 lr: 4.816850138137865e-05 loss: 0.2219 (0.2323) time: 3.2319 data: 0.0094 max mem: 33300 +Epoch: [1] [2680/4276] eta: 1:23:12 lr: 4.816585947810788e-05 loss: 0.2172 (0.2323) time: 3.2313 data: 0.0091 max mem: 33300 +Epoch: [1] [2690/4276] eta: 1:22:41 lr: 4.8163217558736054e-05 loss: 0.2221 (0.2322) time: 3.2444 data: 0.0095 max mem: 33300 +Epoch: [1] [2700/4276] eta: 1:22:10 lr: 4.8160575623262075e-05 loss: 0.2171 (0.2321) time: 3.2150 data: 0.0095 max mem: 33300 +Epoch: [1] [2710/4276] eta: 1:21:39 lr: 4.8157933671684874e-05 loss: 0.2080 (0.2322) time: 3.1812 data: 0.0098 max mem: 33300 +Epoch: [1] [2720/4276] eta: 1:21:09 lr: 4.815529170400336e-05 loss: 0.2344 (0.2322) time: 3.2041 data: 0.0099 max mem: 33300 +Epoch: [1] [2730/4276] eta: 1:20:38 lr: 4.8152649720216466e-05 loss: 0.2236 (0.2322) time: 3.2380 data: 0.0098 max mem: 33300 +Epoch: [1] [2740/4276] eta: 1:20:07 lr: 4.815000772032312e-05 loss: 0.2197 (0.2321) time: 3.2516 data: 0.0104 max mem: 33300 +Epoch: [1] [2750/4276] eta: 1:19:37 lr: 4.8147365704322204e-05 loss: 0.2188 (0.2321) time: 3.2645 data: 0.0102 max mem: 33300 +Epoch: [1] [2760/4276] eta: 1:19:07 lr: 4.8144723672212675e-05 loss: 0.2123 (0.2321) time: 3.3060 data: 0.0100 max mem: 33300 +Epoch: [1] [2770/4276] eta: 1:18:36 lr: 4.814208162399344e-05 loss: 0.2183 (0.2321) time: 3.3080 data: 0.0104 max mem: 33300 +Epoch: [1] [2780/4276] eta: 1:18:06 lr: 4.8139439559663415e-05 loss: 0.2262 (0.2321) time: 3.2548 data: 0.0101 max mem: 33300 +Epoch: [1] [2790/4276] eta: 1:17:35 lr: 4.813679747922152e-05 loss: 0.2302 (0.2321) time: 3.2628 data: 0.0100 max mem: 33300 +Epoch: [1] [2800/4276] eta: 1:17:04 lr: 4.8134155382666684e-05 loss: 0.2176 (0.2320) time: 3.2542 data: 0.0106 max mem: 33300 +Epoch: [1] [2810/4276] eta: 1:16:33 lr: 4.813151326999782e-05 loss: 0.1931 (0.2319) time: 3.2278 data: 0.0107 max mem: 33300 +Epoch: [1] [2820/4276] eta: 1:16:03 lr: 4.8128871141213836e-05 loss: 0.2071 (0.2319) time: 3.2450 data: 0.0097 max mem: 33300 +Epoch: [1] [2830/4276] eta: 1:15:32 lr: 4.812622899631366e-05 loss: 0.2081 (0.2318) time: 3.2491 data: 0.0096 max mem: 33300 +Epoch: [1] [2840/4276] eta: 1:15:01 lr: 4.812358683529621e-05 loss: 0.2248 (0.2318) time: 3.2446 data: 0.0094 max mem: 33300 +Epoch: [1] [2850/4276] eta: 1:14:30 lr: 4.8120944658160425e-05 loss: 0.2315 (0.2319) time: 3.2187 data: 0.0094 max mem: 33300 +Epoch: [1] [2860/4276] eta: 1:13:59 lr: 4.811830246490518e-05 loss: 0.2310 (0.2319) time: 3.2045 data: 0.0096 max mem: 33300 +Epoch: [1] [2870/4276] eta: 1:13:28 lr: 4.8115660255529425e-05 loss: 0.2185 (0.2319) time: 3.2163 data: 0.0100 max mem: 33300 +Epoch: [1] [2880/4276] eta: 1:12:57 lr: 4.811301803003207e-05 loss: 0.2274 (0.2319) time: 3.2103 data: 0.0099 max mem: 33300 +Epoch: [1] [2890/4276] eta: 1:12:26 lr: 4.811037578841204e-05 loss: 0.2274 (0.2319) time: 3.2076 data: 0.0099 max mem: 33300 +Epoch: [1] [2900/4276] eta: 1:11:55 lr: 4.810773353066823e-05 loss: 0.2155 (0.2318) time: 3.2030 data: 0.0103 max mem: 33300 +Epoch: [1] [2910/4276] eta: 1:11:24 lr: 4.810509125679958e-05 loss: 0.2150 (0.2318) time: 3.1972 data: 0.0098 max mem: 33300 +Epoch: [1] [2920/4276] eta: 1:10:53 lr: 4.8102448966805005e-05 loss: 0.2102 (0.2318) time: 3.2171 data: 0.0096 max mem: 33300 +Epoch: [1] [2930/4276] eta: 1:10:22 lr: 4.8099806660683415e-05 loss: 0.2088 (0.2318) time: 3.2321 data: 0.0099 max mem: 33300 +Epoch: [1] [2940/4276] eta: 1:09:51 lr: 4.809716433843373e-05 loss: 0.2019 (0.2316) time: 3.2606 data: 0.0099 max mem: 33300 +Epoch: [1] [2950/4276] eta: 1:09:20 lr: 4.809452200005486e-05 loss: 0.1957 (0.2316) time: 3.2547 data: 0.0103 max mem: 33300 +Epoch: [1] [2960/4276] eta: 1:08:50 lr: 4.809187964554573e-05 loss: 0.2260 (0.2316) time: 3.2450 data: 0.0100 max mem: 33300 +Epoch: [1] [2970/4276] eta: 1:08:19 lr: 4.808923727490527e-05 loss: 0.2415 (0.2317) time: 3.2681 data: 0.0095 max mem: 33300 +Epoch: [1] [2980/4276] eta: 1:07:48 lr: 4.8086594888132366e-05 loss: 0.2415 (0.2317) time: 3.2456 data: 0.0102 max mem: 33300 +Epoch: [1] [2990/4276] eta: 1:07:17 lr: 4.8083952485225966e-05 loss: 0.2077 (0.2316) time: 3.2066 data: 0.0103 max mem: 33300 +Epoch: [1] [3000/4276] eta: 1:06:45 lr: 4.808131006618496e-05 loss: 0.1981 (0.2315) time: 3.1341 data: 0.0093 max mem: 33300 +Epoch: [1] [3010/4276] eta: 1:06:14 lr: 4.807866763100828e-05 loss: 0.2106 (0.2315) time: 3.1024 data: 0.0082 max mem: 33300 +Epoch: [1] [3020/4276] eta: 1:05:42 lr: 4.807602517969484e-05 loss: 0.2106 (0.2315) time: 3.1229 data: 0.0081 max mem: 33300 +Epoch: [1] [3030/4276] eta: 1:05:11 lr: 4.807338271224355e-05 loss: 0.2326 (0.2315) time: 3.1106 data: 0.0085 max mem: 33300 +Epoch: [1] [3040/4276] eta: 1:04:39 lr: 4.807074022865332e-05 loss: 0.2444 (0.2317) time: 3.0886 data: 0.0091 max mem: 33300 +Epoch: [1] [3050/4276] eta: 1:04:07 lr: 4.806809772892309e-05 loss: 0.2388 (0.2316) time: 3.0835 data: 0.0090 max mem: 33300 +Epoch: [1] [3060/4276] eta: 1:03:36 lr: 4.806545521305176e-05 loss: 0.1891 (0.2315) time: 3.1104 data: 0.0083 max mem: 33300 +Epoch: [1] [3070/4276] eta: 1:03:04 lr: 4.8062812681038236e-05 loss: 0.2030 (0.2316) time: 3.1270 data: 0.0083 max mem: 33300 +Epoch: [1] [3080/4276] eta: 1:02:33 lr: 4.8060170132881454e-05 loss: 0.2215 (0.2316) time: 3.1233 data: 0.0087 max mem: 33300 +Epoch: [1] [3090/4276] eta: 1:02:01 lr: 4.805752756858031e-05 loss: 0.2258 (0.2316) time: 3.1159 data: 0.0087 max mem: 33300 +Epoch: [1] [3100/4276] eta: 1:01:30 lr: 4.805488498813373e-05 loss: 0.2304 (0.2316) time: 3.1166 data: 0.0084 max mem: 33300 +Epoch: [1] [3110/4276] eta: 1:00:59 lr: 4.805224239154062e-05 loss: 0.2064 (0.2315) time: 3.1189 data: 0.0078 max mem: 33300 +Epoch: [1] [3120/4276] eta: 1:00:27 lr: 4.8049599778799916e-05 loss: 0.1942 (0.2315) time: 3.1186 data: 0.0076 max mem: 33300 +Epoch: [1] [3130/4276] eta: 0:59:56 lr: 4.804695714991051e-05 loss: 0.2194 (0.2314) time: 3.1281 data: 0.0078 max mem: 33300 +Epoch: [1] [3140/4276] eta: 0:59:24 lr: 4.804431450487132e-05 loss: 0.2275 (0.2315) time: 3.1512 data: 0.0078 max mem: 33300 +Epoch: [1] [3150/4276] eta: 0:58:53 lr: 4.804167184368127e-05 loss: 0.2331 (0.2315) time: 3.1608 data: 0.0077 max mem: 33300 +Epoch: [1] [3160/4276] eta: 0:58:22 lr: 4.8039029166339264e-05 loss: 0.2219 (0.2315) time: 3.1550 data: 0.0078 max mem: 33300 +Epoch: [1] [3170/4276] eta: 0:57:50 lr: 4.8036386472844225e-05 loss: 0.2161 (0.2315) time: 3.1545 data: 0.0078 max mem: 33300 +Epoch: [1] [3180/4276] eta: 0:57:19 lr: 4.8033743763195054e-05 loss: 0.2237 (0.2316) time: 3.1426 data: 0.0080 max mem: 33300 +Epoch: [1] [3190/4276] eta: 0:56:48 lr: 4.803110103739068e-05 loss: 0.2400 (0.2316) time: 3.1323 data: 0.0080 max mem: 33300 +Epoch: [1] [3200/4276] eta: 0:56:16 lr: 4.802845829543001e-05 loss: 0.2123 (0.2315) time: 3.1371 data: 0.0078 max mem: 33300 +Epoch: [1] [3210/4276] eta: 0:55:45 lr: 4.802581553731195e-05 loss: 0.2076 (0.2315) time: 3.1364 data: 0.0076 max mem: 33300 +Epoch: [1] [3220/4276] eta: 0:55:13 lr: 4.802317276303542e-05 loss: 0.2189 (0.2315) time: 3.1308 data: 0.0074 max mem: 33300 +Epoch: [1] [3230/4276] eta: 0:54:42 lr: 4.8020529972599346e-05 loss: 0.2196 (0.2315) time: 3.1080 data: 0.0075 max mem: 33300 +Epoch: [1] [3240/4276] eta: 0:54:10 lr: 4.8017887166002626e-05 loss: 0.2258 (0.2315) time: 3.0882 data: 0.0076 max mem: 33300 +Epoch: [1] [3250/4276] eta: 0:53:39 lr: 4.8015244343244165e-05 loss: 0.2258 (0.2315) time: 3.0837 data: 0.0080 max mem: 33300 +Epoch: [1] [3260/4276] eta: 0:53:07 lr: 4.801260150432289e-05 loss: 0.2298 (0.2315) time: 3.0822 data: 0.0084 max mem: 33300 +Epoch: [1] [3270/4276] eta: 0:52:36 lr: 4.8009958649237704e-05 loss: 0.2152 (0.2314) time: 3.1051 data: 0.0081 max mem: 33300 +Epoch: [1] [3280/4276] eta: 0:52:04 lr: 4.8007315777987536e-05 loss: 0.2152 (0.2315) time: 3.1151 data: 0.0081 max mem: 33300 +Epoch: [1] [3290/4276] eta: 0:51:33 lr: 4.800467289057128e-05 loss: 0.2345 (0.2315) time: 3.1116 data: 0.0081 max mem: 33300 +Epoch: [1] [3300/4276] eta: 0:51:02 lr: 4.800202998698786e-05 loss: 0.2373 (0.2315) time: 3.1170 data: 0.0078 max mem: 33300 +Epoch: [1] [3310/4276] eta: 0:50:30 lr: 4.799938706723619e-05 loss: 0.2377 (0.2315) time: 3.1257 data: 0.0079 max mem: 33300 +Epoch: [1] [3320/4276] eta: 0:49:59 lr: 4.7996744131315167e-05 loss: 0.2377 (0.2316) time: 3.1420 data: 0.0080 max mem: 33300 +Epoch: [1] [3330/4276] eta: 0:49:28 lr: 4.799410117922371e-05 loss: 0.2039 (0.2316) time: 3.1591 data: 0.0079 max mem: 33300 +Epoch: [1] [3340/4276] eta: 0:48:56 lr: 4.799145821096074e-05 loss: 0.2127 (0.2316) time: 3.1665 data: 0.0078 max mem: 33300 +Epoch: [1] [3350/4276] eta: 0:48:25 lr: 4.798881522652515e-05 loss: 0.2127 (0.2315) time: 3.1681 data: 0.0078 max mem: 33300 +Epoch: [1] [3360/4276] eta: 0:47:54 lr: 4.798617222591587e-05 loss: 0.2090 (0.2315) time: 3.1564 data: 0.0083 max mem: 33300 +Epoch: [1] [3370/4276] eta: 0:47:22 lr: 4.79835292091318e-05 loss: 0.2344 (0.2315) time: 3.1353 data: 0.0082 max mem: 33300 +Epoch: [1] [3380/4276] eta: 0:46:51 lr: 4.798088617617186e-05 loss: 0.2329 (0.2315) time: 3.1206 data: 0.0081 max mem: 33300 +Epoch: [1] [3390/4276] eta: 0:46:19 lr: 4.797824312703495e-05 loss: 0.2398 (0.2316) time: 3.1105 data: 0.0082 max mem: 33300 +Epoch: [1] [3400/4276] eta: 0:45:48 lr: 4.7975600061719986e-05 loss: 0.2497 (0.2316) time: 3.1132 data: 0.0081 max mem: 33300 +Epoch: [1] [3410/4276] eta: 0:45:16 lr: 4.797295698022587e-05 loss: 0.2361 (0.2316) time: 3.1191 data: 0.0080 max mem: 33300 +Epoch: [1] [3420/4276] eta: 0:44:45 lr: 4.797031388255154e-05 loss: 0.2299 (0.2316) time: 3.1202 data: 0.0082 max mem: 33300 +Epoch: [1] [3430/4276] eta: 0:44:14 lr: 4.7967670768695874e-05 loss: 0.2317 (0.2317) time: 3.1193 data: 0.0083 max mem: 33300 +Epoch: [1] [3440/4276] eta: 0:43:42 lr: 4.79650276386578e-05 loss: 0.2318 (0.2316) time: 3.1158 data: 0.0078 max mem: 33300 +Epoch: [1] [3450/4276] eta: 0:43:11 lr: 4.796238449243623e-05 loss: 0.2314 (0.2316) time: 3.1177 data: 0.0080 max mem: 33300 +Epoch: [1] [3460/4276] eta: 0:42:39 lr: 4.795974133003005e-05 loss: 0.2314 (0.2316) time: 3.1208 data: 0.0085 max mem: 33300 +Epoch: [1] [3470/4276] eta: 0:42:08 lr: 4.79570981514382e-05 loss: 0.2089 (0.2316) time: 3.1088 data: 0.0081 max mem: 33300 +Epoch: [1] [3480/4276] eta: 0:41:36 lr: 4.795445495665958e-05 loss: 0.2190 (0.2316) time: 3.0811 data: 0.0081 max mem: 33300 +Epoch: [1] [3490/4276] eta: 0:41:05 lr: 4.7951811745693086e-05 loss: 0.2323 (0.2316) time: 3.0905 data: 0.0090 max mem: 33300 +Epoch: [1] [3500/4276] eta: 0:40:34 lr: 4.7949168518537643e-05 loss: 0.2324 (0.2316) time: 3.1255 data: 0.0097 max mem: 33300 +Epoch: [1] [3510/4276] eta: 0:40:02 lr: 4.794652527519216e-05 loss: 0.2153 (0.2315) time: 3.1325 data: 0.0092 max mem: 33300 +Epoch: [1] [3520/4276] eta: 0:39:31 lr: 4.794388201565554e-05 loss: 0.2137 (0.2315) time: 3.1266 data: 0.0081 max mem: 33300 +Epoch: [1] [3530/4276] eta: 0:38:59 lr: 4.7941238739926686e-05 loss: 0.2165 (0.2315) time: 3.1378 data: 0.0085 max mem: 33300 +Epoch: [1] [3540/4276] eta: 0:38:28 lr: 4.7938595448004516e-05 loss: 0.2165 (0.2315) time: 3.1566 data: 0.0096 max mem: 33300 +Epoch: [1] [3550/4276] eta: 0:37:57 lr: 4.793595213988795e-05 loss: 0.2307 (0.2315) time: 3.1403 data: 0.0093 max mem: 33300 +Epoch: [1] [3560/4276] eta: 0:37:25 lr: 4.793330881557587e-05 loss: 0.2292 (0.2315) time: 3.1225 data: 0.0091 max mem: 33300 +Epoch: [1] [3570/4276] eta: 0:36:54 lr: 4.7930665475067206e-05 loss: 0.2292 (0.2315) time: 3.1236 data: 0.0099 max mem: 33300 +Epoch: [1] [3580/4276] eta: 0:36:23 lr: 4.7928022118360846e-05 loss: 0.2134 (0.2314) time: 3.1273 data: 0.0100 max mem: 33300 +Epoch: [1] [3590/4276] eta: 0:35:51 lr: 4.7925378745455726e-05 loss: 0.2121 (0.2314) time: 3.1290 data: 0.0095 max mem: 33300 +Epoch: [1] [3600/4276] eta: 0:35:20 lr: 4.7922735356350735e-05 loss: 0.2227 (0.2314) time: 3.1243 data: 0.0093 max mem: 33300 +Epoch: [1] [3610/4276] eta: 0:34:48 lr: 4.7920091951044776e-05 loss: 0.2301 (0.2314) time: 3.1067 data: 0.0088 max mem: 33300 +Epoch: [1] [3620/4276] eta: 0:34:17 lr: 4.7917448529536776e-05 loss: 0.2356 (0.2314) time: 3.0731 data: 0.0080 max mem: 33300 +Epoch: [1] [3630/4276] eta: 0:33:45 lr: 4.791480509182562e-05 loss: 0.2356 (0.2315) time: 3.0519 data: 0.0075 max mem: 33300 +Epoch: [1] [3640/4276] eta: 0:33:14 lr: 4.791216163791023e-05 loss: 0.2245 (0.2315) time: 3.0532 data: 0.0073 max mem: 33300 +Epoch: [1] [3650/4276] eta: 0:32:42 lr: 4.790951816778951e-05 loss: 0.2202 (0.2315) time: 3.0772 data: 0.0080 max mem: 33300 +Epoch: [1] [3660/4276] eta: 0:32:11 lr: 4.790687468146237e-05 loss: 0.2166 (0.2315) time: 3.1041 data: 0.0087 max mem: 33300 +Epoch: [1] [3670/4276] eta: 0:31:40 lr: 4.7904231178927713e-05 loss: 0.2375 (0.2315) time: 3.1172 data: 0.0091 max mem: 33300 +Epoch: [1] [3680/4276] eta: 0:31:08 lr: 4.790158766018445e-05 loss: 0.2338 (0.2315) time: 3.1241 data: 0.0094 max mem: 33300 +Epoch: [1] [3690/4276] eta: 0:30:37 lr: 4.789894412523148e-05 loss: 0.2255 (0.2315) time: 3.1324 data: 0.0094 max mem: 33300 +Epoch: [1] [3700/4276] eta: 0:30:06 lr: 4.789630057406772e-05 loss: 0.2244 (0.2315) time: 3.1415 data: 0.0089 max mem: 33300 +Epoch: [1] [3710/4276] eta: 0:29:34 lr: 4.789365700669207e-05 loss: 0.2219 (0.2314) time: 3.1441 data: 0.0093 max mem: 33300 +Epoch: [1] [3720/4276] eta: 0:29:03 lr: 4.789101342310343e-05 loss: 0.1998 (0.2314) time: 3.1474 data: 0.0094 max mem: 33300 +Epoch: [1] [3730/4276] eta: 0:28:32 lr: 4.788836982330072e-05 loss: 0.2056 (0.2314) time: 3.1449 data: 0.0087 max mem: 33300 +Epoch: [1] [3740/4276] eta: 0:28:00 lr: 4.788572620728284e-05 loss: 0.2097 (0.2314) time: 3.1424 data: 0.0087 max mem: 33300 +Epoch: [1] [3750/4276] eta: 0:27:29 lr: 4.7883082575048696e-05 loss: 0.2187 (0.2314) time: 3.1323 data: 0.0088 max mem: 33300 +Epoch: [1] [3760/4276] eta: 0:26:57 lr: 4.7880438926597185e-05 loss: 0.2187 (0.2314) time: 3.1138 data: 0.0088 max mem: 33300 +Epoch: [1] [3770/4276] eta: 0:26:26 lr: 4.787779526192722e-05 loss: 0.2307 (0.2314) time: 3.0890 data: 0.0084 max mem: 33300 +Epoch: [1] [3780/4276] eta: 0:25:55 lr: 4.787515158103772e-05 loss: 0.2243 (0.2313) time: 3.0804 data: 0.0084 max mem: 33300 +Epoch: [1] [3790/4276] eta: 0:25:23 lr: 4.7872507883927567e-05 loss: 0.2188 (0.2313) time: 3.1097 data: 0.0091 max mem: 33300 +Epoch: [1] [3800/4276] eta: 0:24:52 lr: 4.786986417059568e-05 loss: 0.2240 (0.2314) time: 3.1536 data: 0.0095 max mem: 33300 +Epoch: [1] [3810/4276] eta: 0:24:21 lr: 4.786722044104096e-05 loss: 0.2152 (0.2314) time: 3.1354 data: 0.0089 max mem: 33300 +Epoch: [1] [3820/4276] eta: 0:23:49 lr: 4.786457669526231e-05 loss: 0.2021 (0.2313) time: 3.0761 data: 0.0082 max mem: 33300 +Epoch: [1] [3830/4276] eta: 0:23:18 lr: 4.786193293325865e-05 loss: 0.2198 (0.2313) time: 3.0818 data: 0.0085 max mem: 33300 +Epoch: [1] [3840/4276] eta: 0:22:46 lr: 4.785928915502885e-05 loss: 0.2207 (0.2313) time: 3.0881 data: 0.0088 max mem: 33300 +Epoch: [1] [3850/4276] eta: 0:22:15 lr: 4.785664536057185e-05 loss: 0.2111 (0.2312) time: 3.0581 data: 0.0088 max mem: 33300 +Epoch: [1] [3860/4276] eta: 0:21:43 lr: 4.785400154988654e-05 loss: 0.2119 (0.2312) time: 3.0532 data: 0.0089 max mem: 33300 +Epoch: [1] [3870/4276] eta: 0:21:12 lr: 4.785135772297182e-05 loss: 0.2119 (0.2312) time: 3.0942 data: 0.0087 max mem: 33300 +Epoch: [1] [3880/4276] eta: 0:20:41 lr: 4.7848713879826604e-05 loss: 0.2119 (0.2311) time: 3.1686 data: 0.0088 max mem: 33300 +Epoch: [1] [3890/4276] eta: 0:20:09 lr: 4.784607002044979e-05 loss: 0.2166 (0.2311) time: 3.1949 data: 0.0088 max mem: 33300 +Epoch: [1] [3900/4276] eta: 0:19:38 lr: 4.7843426144840284e-05 loss: 0.2331 (0.2311) time: 3.1792 data: 0.0090 max mem: 33300 +Epoch: [1] [3910/4276] eta: 0:19:07 lr: 4.7840782252996986e-05 loss: 0.2260 (0.2311) time: 3.1856 data: 0.0097 max mem: 33300 +Epoch: [1] [3920/4276] eta: 0:18:36 lr: 4.78381383449188e-05 loss: 0.2135 (0.2310) time: 3.1578 data: 0.0090 max mem: 33300 +Epoch: [1] [3930/4276] eta: 0:18:04 lr: 4.7835494420604635e-05 loss: 0.2136 (0.2310) time: 3.1175 data: 0.0089 max mem: 33300 +Epoch: [1] [3940/4276] eta: 0:17:33 lr: 4.783285048005338e-05 loss: 0.2206 (0.2310) time: 3.1235 data: 0.0094 max mem: 33300 +Epoch: [1] [3950/4276] eta: 0:17:01 lr: 4.783020652326395e-05 loss: 0.2168 (0.2309) time: 3.1295 data: 0.0087 max mem: 33300 +Epoch: [1] [3960/4276] eta: 0:16:30 lr: 4.782756255023526e-05 loss: 0.2236 (0.2310) time: 3.1239 data: 0.0088 max mem: 33300 +Epoch: [1] [3970/4276] eta: 0:15:59 lr: 4.782491856096618e-05 loss: 0.2496 (0.2310) time: 3.1179 data: 0.0091 max mem: 33300 +Epoch: [1] [3980/4276] eta: 0:15:27 lr: 4.782227455545565e-05 loss: 0.2273 (0.2309) time: 3.1227 data: 0.0091 max mem: 33300 +Epoch: [1] [3990/4276] eta: 0:14:56 lr: 4.781963053370254e-05 loss: 0.2143 (0.2309) time: 3.1372 data: 0.0089 max mem: 33300 +Epoch: [1] [4000/4276] eta: 0:14:25 lr: 4.781698649570577e-05 loss: 0.2080 (0.2309) time: 3.1045 data: 0.0079 max mem: 33300 +Epoch: [1] [4010/4276] eta: 0:13:53 lr: 4.781434244146424e-05 loss: 0.2080 (0.2309) time: 3.0705 data: 0.0075 max mem: 33300 +Epoch: [1] [4020/4276] eta: 0:13:22 lr: 4.781169837097685e-05 loss: 0.1984 (0.2309) time: 3.0915 data: 0.0086 max mem: 33300 +Epoch: [1] [4030/4276] eta: 0:12:51 lr: 4.78090542842425e-05 loss: 0.2032 (0.2309) time: 3.0862 data: 0.0083 max mem: 33300 +Epoch: [1] [4040/4276] eta: 0:12:19 lr: 4.78064101812601e-05 loss: 0.2259 (0.2309) time: 3.0663 data: 0.0077 max mem: 33300 +Epoch: [1] [4050/4276] eta: 0:11:48 lr: 4.7803766062028546e-05 loss: 0.2054 (0.2308) time: 3.0651 data: 0.0083 max mem: 33300 +Epoch: [1] [4060/4276] eta: 0:11:16 lr: 4.780112192654674e-05 loss: 0.1975 (0.2308) time: 3.0935 data: 0.0083 max mem: 33300 +Epoch: [1] [4070/4276] eta: 0:10:45 lr: 4.779847777481357e-05 loss: 0.2200 (0.2308) time: 3.1354 data: 0.0088 max mem: 33300 +Epoch: [1] [4080/4276] eta: 0:10:14 lr: 4.779583360682796e-05 loss: 0.2200 (0.2308) time: 3.1352 data: 0.0093 max mem: 33300 +Epoch: [1] [4090/4276] eta: 0:09:42 lr: 4.77931894225888e-05 loss: 0.2206 (0.2308) time: 3.1433 data: 0.0090 max mem: 33300 +Epoch: [1] [4100/4276] eta: 0:09:11 lr: 4.7790545222095e-05 loss: 0.2360 (0.2308) time: 3.1645 data: 0.0089 max mem: 33300 +Epoch: [1] [4110/4276] eta: 0:08:40 lr: 4.7787901005345435e-05 loss: 0.2360 (0.2308) time: 3.1590 data: 0.0088 max mem: 33300 +Epoch: [1] [4120/4276] eta: 0:08:08 lr: 4.778525677233903e-05 loss: 0.2246 (0.2308) time: 3.1360 data: 0.0087 max mem: 33300 +Epoch: [1] [4130/4276] eta: 0:07:37 lr: 4.7782612523074685e-05 loss: 0.2213 (0.2307) time: 3.1225 data: 0.0088 max mem: 33300 +Epoch: [1] [4140/4276] eta: 0:07:06 lr: 4.77799682575513e-05 loss: 0.2213 (0.2307) time: 3.1310 data: 0.0084 max mem: 33300 +Epoch: [1] [4150/4276] eta: 0:06:34 lr: 4.777732397576775e-05 loss: 0.2165 (0.2307) time: 3.1335 data: 0.0082 max mem: 33300 +Epoch: [1] [4160/4276] eta: 0:06:03 lr: 4.7774679677722965e-05 loss: 0.2165 (0.2307) time: 3.1224 data: 0.0079 max mem: 33300 +Epoch: [1] [4170/4276] eta: 0:05:32 lr: 4.777203536341584e-05 loss: 0.2361 (0.2307) time: 3.1212 data: 0.0078 max mem: 33300 +Epoch: [1] [4180/4276] eta: 0:05:00 lr: 4.776939103284526e-05 loss: 0.2361 (0.2307) time: 3.1237 data: 0.0081 max mem: 33300 +Epoch: [1] [4190/4276] eta: 0:04:29 lr: 4.776674668601014e-05 loss: 0.2117 (0.2307) time: 3.1249 data: 0.0084 max mem: 33300 +Epoch: [1] [4200/4276] eta: 0:03:58 lr: 4.776410232290937e-05 loss: 0.2201 (0.2308) time: 3.1234 data: 0.0082 max mem: 33300 +Epoch: [1] [4210/4276] eta: 0:03:26 lr: 4.776145794354185e-05 loss: 0.2292 (0.2308) time: 3.1227 data: 0.0080 max mem: 33300 +Epoch: [1] [4220/4276] eta: 0:02:55 lr: 4.775881354790649e-05 loss: 0.2452 (0.2308) time: 3.1293 data: 0.0087 max mem: 33300 +Epoch: [1] [4230/4276] eta: 0:02:24 lr: 4.775616913600217e-05 loss: 0.2606 (0.2309) time: 3.1291 data: 0.0092 max mem: 33300 +Epoch: [1] [4240/4276] eta: 0:01:52 lr: 4.7753524707827814e-05 loss: 0.2471 (0.2309) time: 3.1239 data: 0.0086 max mem: 33300 +Epoch: [1] [4250/4276] eta: 0:01:21 lr: 4.7750880263382295e-05 loss: 0.2256 (0.2309) time: 3.1010 data: 0.0079 max mem: 33300 +Epoch: [1] [4260/4276] eta: 0:00:50 lr: 4.774823580266453e-05 loss: 0.2305 (0.2309) time: 3.1172 data: 0.0089 max mem: 33300 +Epoch: [1] [4270/4276] eta: 0:00:18 lr: 4.774559132567341e-05 loss: 0.2314 (0.2309) time: 3.1537 data: 0.0088 max mem: 33300 +Epoch: [1] Total time: 3:43:20 +Test: [ 0/21770] eta: 10:18:50 time: 1.7056 data: 1.6626 max mem: 33300 +Test: [ 100/21770] eta: 0:20:13 time: 0.0401 data: 0.0012 max mem: 33300 +Test: [ 200/21770] eta: 0:17:15 time: 0.0399 data: 0.0012 max mem: 33300 +Test: [ 300/21770] eta: 0:16:13 time: 0.0398 data: 0.0011 max mem: 33300 +Test: [ 400/21770] eta: 0:15:40 time: 0.0402 data: 0.0011 max mem: 33300 +Test: [ 500/21770] eta: 0:15:19 time: 0.0399 data: 0.0012 max mem: 33300 +Test: [ 600/21770] eta: 0:15:03 time: 0.0401 data: 0.0012 max mem: 33300 +Test: [ 700/21770] eta: 0:14:51 time: 0.0404 data: 0.0011 max mem: 33300 +Test: [ 800/21770] eta: 0:14:41 time: 0.0400 data: 0.0012 max mem: 33300 +Test: [ 900/21770] eta: 0:14:32 time: 0.0400 data: 0.0012 max mem: 33300 +Test: [ 1000/21770] eta: 0:14:23 time: 0.0387 data: 0.0012 max mem: 33300 +Test: [ 1100/21770] eta: 0:14:14 time: 0.0389 data: 0.0012 max mem: 33300 +Test: [ 1200/21770] eta: 0:14:05 time: 0.0389 data: 0.0012 max mem: 33300 +Test: [ 1300/21770] eta: 0:13:58 time: 0.0389 data: 0.0012 max mem: 33300 +Test: [ 1400/21770] eta: 0:13:51 time: 0.0389 data: 0.0011 max mem: 33300 +Test: [ 1500/21770] eta: 0:13:44 time: 0.0391 data: 0.0012 max mem: 33300 +Test: [ 1600/21770] eta: 0:13:38 time: 0.0392 data: 0.0012 max mem: 33300 +Test: [ 1700/21770] eta: 0:13:33 time: 0.0391 data: 0.0012 max mem: 33300 +Test: [ 1800/21770] eta: 0:13:27 time: 0.0394 data: 0.0012 max mem: 33300 +Test: [ 1900/21770] eta: 0:13:22 time: 0.0391 data: 0.0012 max mem: 33300 +Test: [ 2000/21770] eta: 0:13:17 time: 0.0393 data: 0.0012 max mem: 33300 +Test: [ 2100/21770] eta: 0:13:11 time: 0.0389 data: 0.0011 max mem: 33300 +Test: [ 2200/21770] eta: 0:13:06 time: 0.0392 data: 0.0011 max mem: 33300 +Test: [ 2300/21770] eta: 0:13:02 time: 0.0392 data: 0.0012 max mem: 33300 +Test: [ 2400/21770] eta: 0:12:57 time: 0.0394 data: 0.0012 max mem: 33300 +Test: [ 2500/21770] eta: 0:12:52 time: 0.0394 data: 0.0012 max mem: 33300 +Test: [ 2600/21770] eta: 0:12:48 time: 0.0390 data: 0.0012 max mem: 33300 +Test: [ 2700/21770] eta: 0:12:43 time: 0.0391 data: 0.0012 max mem: 33300 +Test: [ 2800/21770] eta: 0:12:38 time: 0.0389 data: 0.0012 max mem: 33300 +Test: [ 2900/21770] eta: 0:12:34 time: 0.0389 data: 0.0012 max mem: 33300 +Test: [ 3000/21770] eta: 0:12:29 time: 0.0389 data: 0.0012 max mem: 33300 +Test: [ 3100/21770] eta: 0:12:24 time: 0.0389 data: 0.0011 max mem: 33300 +Test: [ 3200/21770] eta: 0:12:20 time: 0.0391 data: 0.0012 max mem: 33300 +Test: [ 3300/21770] eta: 0:12:15 time: 0.0389 data: 0.0012 max mem: 33300 +Test: [ 3400/21770] eta: 0:12:11 time: 0.0388 data: 0.0011 max mem: 33300 +Test: [ 3500/21770] eta: 0:12:06 time: 0.0389 data: 0.0012 max mem: 33300 +Test: [ 3600/21770] eta: 0:12:02 time: 0.0390 data: 0.0012 max mem: 33300 +Test: [ 3700/21770] eta: 0:11:58 time: 0.0387 data: 0.0011 max mem: 33300 +Test: [ 3800/21770] eta: 0:11:53 time: 0.0388 data: 0.0011 max mem: 33300 +Test: [ 3900/21770] eta: 0:11:49 time: 0.0388 data: 0.0011 max mem: 33300 +Test: [ 4000/21770] eta: 0:11:44 time: 0.0388 data: 0.0011 max mem: 33300 +Test: [ 4100/21770] eta: 0:11:40 time: 0.0388 data: 0.0011 max mem: 33300 +Test: [ 4200/21770] eta: 0:11:36 time: 0.0387 data: 0.0011 max mem: 33300 +Test: [ 4300/21770] eta: 0:11:31 time: 0.0388 data: 0.0011 max mem: 33300 +Test: [ 4400/21770] eta: 0:11:27 time: 0.0388 data: 0.0011 max mem: 33300 +Test: [ 4500/21770] eta: 0:11:23 time: 0.0388 data: 0.0011 max mem: 33300 +Test: [ 4600/21770] eta: 0:11:19 time: 0.0393 data: 0.0011 max mem: 33300 +Test: [ 4700/21770] eta: 0:11:15 time: 0.0392 data: 0.0011 max mem: 33300 +Test: [ 4800/21770] eta: 0:11:11 time: 0.0395 data: 0.0011 max mem: 33300 +Test: [ 4900/21770] eta: 0:11:07 time: 0.0398 data: 0.0011 max mem: 33300 +Test: [ 5000/21770] eta: 0:11:03 time: 0.0394 data: 0.0011 max mem: 33300 +Test: [ 5100/21770] eta: 0:10:59 time: 0.0399 data: 0.0011 max mem: 33300 +Test: [ 5200/21770] eta: 0:10:55 time: 0.0396 data: 0.0011 max mem: 33300 +Test: [ 5300/21770] eta: 0:10:51 time: 0.0392 data: 0.0011 max mem: 33300 +Test: [ 5400/21770] eta: 0:10:47 time: 0.0390 data: 0.0011 max mem: 33300 +Test: [ 5500/21770] eta: 0:10:43 time: 0.0392 data: 0.0011 max mem: 33300 +Test: [ 5600/21770] eta: 0:10:39 time: 0.0390 data: 0.0011 max mem: 33300 +Test: [ 5700/21770] eta: 0:10:35 time: 0.0389 data: 0.0012 max mem: 33300 +Test: [ 5800/21770] eta: 0:10:30 time: 0.0388 data: 0.0012 max mem: 33300 +Test: [ 5900/21770] eta: 0:10:26 time: 0.0387 data: 0.0011 max mem: 33300 +Test: [ 6000/21770] eta: 0:10:22 time: 0.0388 data: 0.0011 max mem: 33300 +Test: [ 6100/21770] eta: 0:10:18 time: 0.0388 data: 0.0011 max mem: 33300 +Test: [ 6200/21770] eta: 0:10:14 time: 0.0386 data: 0.0011 max mem: 33300 +Test: [ 6300/21770] eta: 0:10:10 time: 0.0391 data: 0.0011 max mem: 33300 +Test: [ 6400/21770] eta: 0:10:06 time: 0.0389 data: 0.0011 max mem: 33300 +Test: [ 6500/21770] eta: 0:10:02 time: 0.0398 data: 0.0011 max mem: 33300 +Test: [ 6600/21770] eta: 0:09:58 time: 0.0392 data: 0.0011 max mem: 33300 +Test: [ 6700/21770] eta: 0:09:54 time: 0.0394 data: 0.0011 max mem: 33300 +Test: [ 6800/21770] eta: 0:09:50 time: 0.0394 data: 0.0011 max mem: 33300 +Test: [ 6900/21770] eta: 0:09:46 time: 0.0399 data: 0.0011 max mem: 33300 +Test: [ 7000/21770] eta: 0:09:42 time: 0.0395 data: 0.0011 max mem: 33300 +Test: [ 7100/21770] eta: 0:09:38 time: 0.0399 data: 0.0012 max mem: 33300 +Test: [ 7200/21770] eta: 0:09:34 time: 0.0391 data: 0.0011 max mem: 33300 +Test: [ 7300/21770] eta: 0:09:30 time: 0.0388 data: 0.0011 max mem: 33300 +Test: [ 7400/21770] eta: 0:09:26 time: 0.0388 data: 0.0011 max mem: 33300 +Test: [ 7500/21770] eta: 0:09:22 time: 0.0388 data: 0.0011 max mem: 33300 +Test: [ 7600/21770] eta: 0:09:18 time: 0.0388 data: 0.0011 max mem: 33300 +Test: [ 7700/21770] eta: 0:09:14 time: 0.0389 data: 0.0012 max mem: 33300 +Test: [ 7800/21770] eta: 0:09:10 time: 0.0389 data: 0.0012 max mem: 33300 +Test: [ 7900/21770] eta: 0:09:06 time: 0.0389 data: 0.0012 max mem: 33300 +Test: [ 8000/21770] eta: 0:09:02 time: 0.0388 data: 0.0011 max mem: 33300 +Test: [ 8100/21770] eta: 0:08:58 time: 0.0388 data: 0.0011 max mem: 33300 +Test: [ 8200/21770] eta: 0:08:54 time: 0.0388 data: 0.0011 max mem: 33300 +Test: [ 8300/21770] eta: 0:08:50 time: 0.0388 data: 0.0011 max mem: 33300 +Test: [ 8400/21770] eta: 0:08:46 time: 0.0387 data: 0.0011 max mem: 33300 +Test: [ 8500/21770] eta: 0:08:42 time: 0.0387 data: 0.0011 max mem: 33300 +Test: [ 8600/21770] eta: 0:08:38 time: 0.0387 data: 0.0011 max mem: 33300 +Test: [ 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time: 0.0392 data: 0.0011 max mem: 33300 +Test: [10100/21770] eta: 0:07:38 time: 0.0391 data: 0.0011 max mem: 33300 +Test: [10200/21770] eta: 0:07:34 time: 0.0391 data: 0.0011 max mem: 33300 +Test: [10300/21770] eta: 0:07:30 time: 0.0393 data: 0.0011 max mem: 33300 +Test: [10400/21770] eta: 0:07:26 time: 0.0389 data: 0.0011 max mem: 33300 +Test: [10500/21770] eta: 0:07:22 time: 0.0388 data: 0.0011 max mem: 33300 +Test: [10600/21770] eta: 0:07:18 time: 0.0388 data: 0.0011 max mem: 33300 +Test: [10700/21770] eta: 0:07:14 time: 0.0388 data: 0.0011 max mem: 33300 +Test: [10800/21770] eta: 0:07:10 time: 0.0396 data: 0.0011 max mem: 33300 +Test: [10900/21770] eta: 0:07:06 time: 0.0398 data: 0.0011 max mem: 33300 +Test: [11000/21770] eta: 0:07:02 time: 0.0402 data: 0.0011 max mem: 33300 +Test: [11100/21770] eta: 0:06:59 time: 0.0399 data: 0.0011 max mem: 33300 +Test: [11200/21770] eta: 0:06:55 time: 0.0402 data: 0.0011 max mem: 33300 +Test: [11300/21770] eta: 0:06:51 time: 0.0398 data: 0.0011 max mem: 33300 +Test: [11400/21770] eta: 0:06:47 time: 0.0402 data: 0.0011 max mem: 33300 +Test: [11500/21770] eta: 0:06:43 time: 0.0399 data: 0.0012 max mem: 33300 +Test: [11600/21770] eta: 0:06:39 time: 0.0402 data: 0.0011 max mem: 33300 +Test: [11700/21770] eta: 0:06:35 time: 0.0398 data: 0.0011 max mem: 33300 +Test: [11800/21770] eta: 0:06:31 time: 0.0400 data: 0.0011 max mem: 33300 +Test: [11900/21770] eta: 0:06:28 time: 0.0398 data: 0.0011 max mem: 33300 +Test: [12000/21770] eta: 0:06:24 time: 0.0400 data: 0.0012 max mem: 33300 +Test: [12100/21770] eta: 0:06:20 time: 0.0401 data: 0.0011 max mem: 33300 +Test: [12200/21770] eta: 0:06:16 time: 0.0404 data: 0.0011 max mem: 33300 +Test: [12300/21770] eta: 0:06:12 time: 0.0405 data: 0.0011 max mem: 33300 +Test: [12400/21770] eta: 0:06:08 time: 0.0403 data: 0.0011 max mem: 33300 +Test: [12500/21770] eta: 0:06:04 time: 0.0403 data: 0.0011 max mem: 33300 +Test: [12600/21770] eta: 0:06:01 time: 0.0407 data: 0.0011 max mem: 33300 +Test: [12700/21770] eta: 0:05:57 time: 0.0406 data: 0.0012 max mem: 33300 +Test: [12800/21770] eta: 0:05:53 time: 0.0403 data: 0.0011 max mem: 33300 +Test: [12900/21770] eta: 0:05:49 time: 0.0405 data: 0.0011 max mem: 33300 +Test: [13000/21770] eta: 0:05:45 time: 0.0403 data: 0.0011 max mem: 33300 +Test: [13100/21770] eta: 0:05:41 time: 0.0399 data: 0.0012 max mem: 33300 +Test: [13200/21770] eta: 0:05:37 time: 0.0401 data: 0.0012 max mem: 33300 +Test: [13300/21770] eta: 0:05:33 time: 0.0399 data: 0.0012 max mem: 33300 +Test: [13400/21770] eta: 0:05:30 time: 0.0399 data: 0.0012 max mem: 33300 +Test: [13500/21770] eta: 0:05:26 time: 0.0397 data: 0.0012 max mem: 33300 +Test: [13600/21770] eta: 0:05:22 time: 0.0403 data: 0.0011 max mem: 33300 +Test: [13700/21770] eta: 0:05:18 time: 0.0408 data: 0.0011 max mem: 33300 +Test: [13800/21770] eta: 0:05:14 time: 0.0403 data: 0.0012 max mem: 33300 +Test: [13900/21770] eta: 0:05:10 time: 0.0399 data: 0.0012 max mem: 33300 +Test: [14000/21770] eta: 0:05:06 time: 0.0400 data: 0.0012 max mem: 33300 +Test: [14100/21770] eta: 0:05:02 time: 0.0396 data: 0.0012 max mem: 33300 +Test: [14200/21770] eta: 0:04:58 time: 0.0390 data: 0.0012 max mem: 33300 +Test: [14300/21770] eta: 0:04:54 time: 0.0394 data: 0.0012 max mem: 33300 +Test: [14400/21770] eta: 0:04:50 time: 0.0391 data: 0.0012 max mem: 33300 +Test: [14500/21770] eta: 0:04:46 time: 0.0395 data: 0.0012 max mem: 33300 +Test: [14600/21770] eta: 0:04:42 time: 0.0401 data: 0.0012 max mem: 33300 +Test: [14700/21770] eta: 0:04:38 time: 0.0401 data: 0.0012 max mem: 33300 +Test: [14800/21770] eta: 0:04:35 time: 0.0400 data: 0.0012 max mem: 33300 +Test: [14900/21770] eta: 0:04:31 time: 0.0400 data: 0.0011 max mem: 33300 +Test: [15000/21770] eta: 0:04:27 time: 0.0399 data: 0.0012 max mem: 33300 +Test: [15100/21770] eta: 0:04:23 time: 0.0389 data: 0.0012 max mem: 33300 +Test: [15200/21770] eta: 0:04:19 time: 0.0394 data: 0.0012 max mem: 33300 +Test: [15300/21770] eta: 0:04:15 time: 0.0392 data: 0.0011 max mem: 33300 +Test: [15400/21770] eta: 0:04:11 time: 0.0392 data: 0.0011 max mem: 33300 +Test: [15500/21770] eta: 0:04:07 time: 0.0393 data: 0.0012 max mem: 33300 +Test: [15600/21770] eta: 0:04:03 time: 0.0396 data: 0.0012 max mem: 33300 +Test: [15700/21770] eta: 0:03:59 time: 0.0395 data: 0.0012 max mem: 33300 +Test: [15800/21770] eta: 0:03:55 time: 0.0392 data: 0.0012 max mem: 33300 +Test: [15900/21770] eta: 0:03:51 time: 0.0393 data: 0.0011 max mem: 33300 +Test: [16000/21770] eta: 0:03:47 time: 0.0396 data: 0.0011 max mem: 33300 +Test: [16100/21770] eta: 0:03:43 time: 0.0396 data: 0.0011 max mem: 33300 +Test: [16200/21770] eta: 0:03:39 time: 0.0401 data: 0.0012 max mem: 33300 +Test: [16300/21770] eta: 0:03:35 time: 0.0400 data: 0.0011 max mem: 33300 +Test: [16400/21770] eta: 0:03:31 time: 0.0390 data: 0.0009 max mem: 33300 +Test: [16500/21770] eta: 0:03:27 time: 0.0396 data: 0.0010 max mem: 33300 +Test: [16600/21770] eta: 0:03:24 time: 0.0389 data: 0.0010 max mem: 33300 +Test: [16700/21770] eta: 0:03:20 time: 0.0384 data: 0.0010 max mem: 33300 +Test: [16800/21770] eta: 0:03:16 time: 0.0386 data: 0.0011 max mem: 33300 +Test: [16900/21770] eta: 0:03:12 time: 0.0388 data: 0.0012 max mem: 33300 +Test: [17000/21770] eta: 0:03:08 time: 0.0387 data: 0.0011 max mem: 33300 +Test: [17100/21770] eta: 0:03:04 time: 0.0389 data: 0.0011 max mem: 33300 +Test: [17200/21770] eta: 0:03:00 time: 0.0388 data: 0.0011 max mem: 33300 +Test: [17300/21770] eta: 0:02:56 time: 0.0389 data: 0.0011 max mem: 33300 +Test: [17400/21770] eta: 0:02:52 time: 0.0389 data: 0.0012 max mem: 33300 +Test: [17500/21770] eta: 0:02:48 time: 0.0391 data: 0.0011 max mem: 33300 +Test: [17600/21770] eta: 0:02:44 time: 0.0390 data: 0.0011 max mem: 33300 +Test: [17700/21770] eta: 0:02:40 time: 0.0392 data: 0.0011 max mem: 33300 +Test: [17800/21770] eta: 0:02:36 time: 0.0388 data: 0.0012 max mem: 33300 +Test: [17900/21770] eta: 0:02:32 time: 0.0388 data: 0.0011 max mem: 33300 +Test: [18000/21770] eta: 0:02:28 time: 0.0388 data: 0.0011 max mem: 33300 +Test: [18100/21770] eta: 0:02:24 time: 0.0389 data: 0.0011 max mem: 33300 +Test: [18200/21770] eta: 0:02:20 time: 0.0389 data: 0.0011 max mem: 33300 +Test: [18300/21770] eta: 0:02:16 time: 0.0388 data: 0.0011 max mem: 33300 +Test: [18400/21770] eta: 0:02:12 time: 0.0387 data: 0.0011 max mem: 33300 +Test: [18500/21770] eta: 0:02:08 time: 0.0387 data: 0.0011 max mem: 33300 +Test: [18600/21770] eta: 0:02:04 time: 0.0388 data: 0.0011 max mem: 33300 +Test: [18700/21770] eta: 0:02:00 time: 0.0386 data: 0.0011 max mem: 33300 +Test: [18800/21770] eta: 0:01:56 time: 0.0387 data: 0.0011 max mem: 33300 +Test: [18900/21770] eta: 0:01:53 time: 0.0387 data: 0.0011 max mem: 33300 +Test: [19000/21770] eta: 0:01:49 time: 0.0387 data: 0.0011 max mem: 33300 +Test: [19100/21770] eta: 0:01:45 time: 0.0388 data: 0.0011 max mem: 33300 +Test: [19200/21770] eta: 0:01:41 time: 0.0387 data: 0.0011 max mem: 33300 +Test: [19300/21770] eta: 0:01:37 time: 0.0386 data: 0.0011 max mem: 33300 +Test: [19400/21770] eta: 0:01:33 time: 0.0388 data: 0.0012 max mem: 33300 +Test: [19500/21770] eta: 0:01:29 time: 0.0388 data: 0.0011 max mem: 33300 +Test: [19600/21770] eta: 0:01:25 time: 0.0389 data: 0.0011 max mem: 33300 +Test: [19700/21770] eta: 0:01:21 time: 0.0388 data: 0.0011 max mem: 33300 +Test: [19800/21770] eta: 0:01:17 time: 0.0389 data: 0.0012 max mem: 33300 +Test: [19900/21770] eta: 0:01:13 time: 0.0387 data: 0.0011 max mem: 33300 +Test: [20000/21770] eta: 0:01:09 time: 0.0388 data: 0.0011 max mem: 33300 +Test: [20100/21770] eta: 0:01:05 time: 0.0387 data: 0.0011 max mem: 33300 +Test: [20200/21770] eta: 0:01:01 time: 0.0386 data: 0.0011 max mem: 33300 +Test: [20300/21770] eta: 0:00:57 time: 0.0388 data: 0.0012 max mem: 33300 +Test: [20400/21770] eta: 0:00:53 time: 0.0388 data: 0.0011 max mem: 33300 +Test: [20500/21770] eta: 0:00:49 time: 0.0388 data: 0.0012 max mem: 33300 +Test: [20600/21770] eta: 0:00:46 time: 0.0388 data: 0.0011 max mem: 33300 +Test: [20700/21770] eta: 0:00:42 time: 0.0388 data: 0.0011 max mem: 33300 +Test: [20800/21770] eta: 0:00:38 time: 0.0388 data: 0.0012 max mem: 33300 +Test: [20900/21770] eta: 0:00:34 time: 0.0388 data: 0.0012 max mem: 33300 +Test: [21000/21770] eta: 0:00:30 time: 0.0388 data: 0.0012 max mem: 33300 +Test: [21100/21770] eta: 0:00:26 time: 0.0388 data: 0.0011 max mem: 33300 +Test: [21200/21770] eta: 0:00:22 time: 0.0388 data: 0.0012 max mem: 33300 +Test: [21300/21770] eta: 0:00:18 time: 0.0387 data: 0.0012 max mem: 33300 +Test: [21400/21770] eta: 0:00:14 time: 0.0388 data: 0.0011 max mem: 33300 +Test: [21500/21770] eta: 0:00:10 time: 0.0386 data: 0.0011 max mem: 33300 +Test: [21600/21770] eta: 0:00:06 time: 0.0388 data: 0.0011 max mem: 33300 +Test: [21700/21770] eta: 0:00:02 time: 0.0388 data: 0.0011 max mem: 33300 +Test: Total time: 0:14:15 +Final results: +Mean IoU is 0.00 + + precision@0.5 = 0.00 + precision@0.6 = 0.00 + precision@0.7 = 0.00 + precision@0.8 = 0.00 + precision@0.9 = 0.00 + overall IoU = 0.00 + mean IoU = 0.00 + +Mean accuracy for one-to-zero sample is 100.00 + +Average object IoU 0.0 +Overall IoU 0.0 +Epoch: [2] [ 0/4276] eta: 6:16:23 lr: 4.774400463166706e-05 loss: 0.1869 (0.1869) time: 5.2814 data: 2.0109 max mem: 33300 +Epoch: [2] [ 10/4276] eta: 3:52:42 lr: 4.7741360128636285e-05 loss: 0.2215 (0.2167) time: 3.2730 data: 0.1892 max mem: 33300 +Epoch: [2] [ 20/4276] eta: 3:45:35 lr: 4.773871560932929e-05 loss: 0.2215 (0.2166) time: 3.0752 data: 0.0072 max mem: 33300 +Epoch: [2] [ 30/4276] eta: 3:41:39 lr: 4.773607107374497e-05 loss: 0.2188 (0.2187) time: 3.0549 data: 0.0075 max mem: 33300 +Epoch: [2] [ 40/4276] eta: 3:40:15 lr: 4.7733426521882224e-05 loss: 0.2153 (0.2158) time: 3.0561 data: 0.0082 max mem: 33300 +Epoch: [2] [ 50/4276] eta: 3:39:08 lr: 4.773078195373996e-05 loss: 0.2089 (0.2159) time: 3.0790 data: 0.0084 max mem: 33300 +Epoch: [2] [ 60/4276] eta: 3:38:20 lr: 4.772813736931707e-05 loss: 0.2089 (0.2169) time: 3.0817 data: 0.0084 max mem: 33300 +Epoch: [2] [ 70/4276] eta: 3:37:29 lr: 4.772549276861244e-05 loss: 0.1996 (0.2159) time: 3.0806 data: 0.0083 max mem: 33300 +Epoch: [2] [ 80/4276] eta: 3:36:52 lr: 4.7722848151624984e-05 loss: 0.2017 (0.2157) time: 3.0825 data: 0.0082 max mem: 33300 +Epoch: [2] [ 90/4276] eta: 3:35:52 lr: 4.7720203518353595e-05 loss: 0.1987 (0.2134) time: 3.0646 data: 0.0083 max mem: 33300 +Epoch: [2] [ 100/4276] eta: 3:35:13 lr: 4.7717558868797165e-05 loss: 0.1968 (0.2181) time: 3.0570 data: 0.0084 max mem: 33300 +Epoch: [2] [ 110/4276] eta: 3:34:40 lr: 4.771491420295459e-05 loss: 0.2161 (0.2190) time: 3.0807 data: 0.0086 max mem: 33300 +Epoch: [2] [ 120/4276] eta: 3:34:08 lr: 4.771226952082477e-05 loss: 0.2083 (0.2183) time: 3.0872 data: 0.0090 max mem: 33300 +Epoch: [2] [ 130/4276] eta: 3:33:32 lr: 4.770962482240661e-05 loss: 0.2144 (0.2196) time: 3.0813 data: 0.0092 max mem: 33300 +Epoch: [2] [ 140/4276] eta: 3:33:04 lr: 4.770698010769899e-05 loss: 0.2338 (0.2206) time: 3.0881 data: 0.0091 max mem: 33300 +Epoch: [2] [ 150/4276] eta: 3:32:17 lr: 4.770433537670081e-05 loss: 0.2042 (0.2194) time: 3.0660 data: 0.0088 max mem: 33300 +Epoch: [2] [ 160/4276] eta: 3:31:27 lr: 4.7701690629410976e-05 loss: 0.2037 (0.2196) time: 3.0213 data: 0.0081 max mem: 33300 +Epoch: [2] [ 170/4276] eta: 3:30:43 lr: 4.769904586582838e-05 loss: 0.2212 (0.2204) time: 3.0204 data: 0.0077 max mem: 33300 +Epoch: [2] [ 180/4276] eta: 3:30:11 lr: 4.769640108595191e-05 loss: 0.2293 (0.2213) time: 3.0522 data: 0.0083 max mem: 33300 +Epoch: [2] [ 190/4276] eta: 3:29:39 lr: 4.7693756289780475e-05 loss: 0.2352 (0.2226) time: 3.0733 data: 0.0086 max mem: 33300 +Epoch: [2] [ 200/4276] eta: 3:29:07 lr: 4.7691111477312964e-05 loss: 0.2290 (0.2235) time: 3.0730 data: 0.0089 max mem: 33300 +Epoch: [2] [ 210/4276] eta: 3:28:35 lr: 4.768846664854827e-05 loss: 0.2162 (0.2235) time: 3.0729 data: 0.0091 max mem: 33300 +Epoch: [2] [ 220/4276] eta: 3:28:04 lr: 4.7685821803485283e-05 loss: 0.2120 (0.2230) time: 3.0750 data: 0.0089 max mem: 33300 +Epoch: [2] [ 230/4276] eta: 3:27:30 lr: 4.768317694212292e-05 loss: 0.2120 (0.2222) time: 3.0679 data: 0.0087 max mem: 33300 +Epoch: [2] [ 240/4276] eta: 3:27:01 lr: 4.768053206446005e-05 loss: 0.2189 (0.2228) time: 3.0714 data: 0.0080 max mem: 33300 +Epoch: [2] [ 250/4276] eta: 3:26:30 lr: 4.767788717049558e-05 loss: 0.2404 (0.2239) time: 3.0826 data: 0.0080 max mem: 33300 +Epoch: [2] [ 260/4276] eta: 3:25:56 lr: 4.767524226022841e-05 loss: 0.2404 (0.2247) time: 3.0687 data: 0.0080 max mem: 33300 +Epoch: [2] [ 270/4276] eta: 3:25:22 lr: 4.7672597333657425e-05 loss: 0.2354 (0.2253) time: 3.0548 data: 0.0082 max mem: 33300 +Epoch: [2] [ 280/4276] eta: 3:24:42 lr: 4.766995239078152e-05 loss: 0.2211 (0.2252) time: 3.0307 data: 0.0079 max mem: 33300 +Epoch: [2] [ 290/4276] eta: 3:24:04 lr: 4.76673074315996e-05 loss: 0.2140 (0.2248) time: 3.0173 data: 0.0075 max mem: 33300 +Epoch: [2] [ 300/4276] eta: 3:23:35 lr: 4.7664662456110546e-05 loss: 0.2007 (0.2245) time: 3.0529 data: 0.0083 max mem: 33300 +Epoch: [2] [ 310/4276] eta: 3:23:02 lr: 4.766201746431326e-05 loss: 0.2061 (0.2244) time: 3.0682 data: 0.0086 max mem: 33300 +Epoch: [2] [ 320/4276] eta: 3:22:31 lr: 4.765937245620663e-05 loss: 0.2304 (0.2252) time: 3.0646 data: 0.0084 max mem: 33300 +Epoch: [2] [ 330/4276] eta: 3:22:02 lr: 4.7656727431789554e-05 loss: 0.2308 (0.2252) time: 3.0800 data: 0.0087 max mem: 33300 +Epoch: [2] [ 340/4276] eta: 3:21:32 lr: 4.765408239106092e-05 loss: 0.2203 (0.2250) time: 3.0801 data: 0.0086 max mem: 33300 +Epoch: [2] [ 350/4276] eta: 3:21:01 lr: 4.7651437334019634e-05 loss: 0.2137 (0.2245) time: 3.0726 data: 0.0088 max mem: 33300 +Epoch: [2] [ 360/4276] eta: 3:20:31 lr: 4.764879226066458e-05 loss: 0.2199 (0.2253) time: 3.0730 data: 0.0093 max mem: 33300 +Epoch: [2] [ 370/4276] eta: 3:19:59 lr: 4.7646147170994654e-05 loss: 0.2199 (0.2248) time: 3.0710 data: 0.0088 max mem: 33300 +Epoch: [2] [ 380/4276] eta: 3:19:26 lr: 4.764350206500874e-05 loss: 0.2178 (0.2249) time: 3.0558 data: 0.0084 max mem: 33300 +Epoch: [2] [ 390/4276] eta: 3:18:54 lr: 4.764085694270574e-05 loss: 0.2265 (0.2254) time: 3.0514 data: 0.0084 max mem: 33300 +Epoch: [2] [ 400/4276] eta: 3:18:20 lr: 4.763821180408455e-05 loss: 0.2267 (0.2255) time: 3.0470 data: 0.0085 max mem: 33300 +Epoch: [2] [ 410/4276] eta: 3:17:51 lr: 4.763556664914405e-05 loss: 0.2227 (0.2253) time: 3.0663 data: 0.0086 max mem: 33300 +Epoch: [2] [ 420/4276] eta: 3:17:21 lr: 4.763292147788315e-05 loss: 0.2178 (0.2255) time: 3.0852 data: 0.0081 max mem: 33300 +Epoch: [2] [ 430/4276] eta: 3:16:51 lr: 4.763027629030073e-05 loss: 0.2230 (0.2255) time: 3.0764 data: 0.0075 max mem: 33300 +Epoch: [2] [ 440/4276] eta: 3:16:23 lr: 4.762763108639568e-05 loss: 0.2197 (0.2253) time: 3.0923 data: 0.0077 max mem: 33300 +Epoch: [2] [ 450/4276] eta: 3:15:54 lr: 4.762498586616689e-05 loss: 0.2197 (0.2257) time: 3.0980 data: 0.0087 max mem: 33300 +Epoch: [2] [ 460/4276] eta: 3:15:24 lr: 4.7622340629613274e-05 loss: 0.2163 (0.2252) time: 3.0854 data: 0.0092 max mem: 33300 +Epoch: [2] [ 470/4276] eta: 3:14:53 lr: 4.761969537673369e-05 loss: 0.2043 (0.2248) time: 3.0764 data: 0.0089 max mem: 33300 +Epoch: [2] [ 480/4276] eta: 3:14:22 lr: 4.761705010752707e-05 loss: 0.2051 (0.2245) time: 3.0675 data: 0.0082 max mem: 33300 +Epoch: [2] [ 490/4276] eta: 3:13:51 lr: 4.761440482199226e-05 loss: 0.2060 (0.2245) time: 3.0687 data: 0.0079 max mem: 33300 +Epoch: [2] [ 500/4276] eta: 3:13:21 lr: 4.761175952012818e-05 loss: 0.2137 (0.2244) time: 3.0773 data: 0.0082 max mem: 33300 +Epoch: [2] [ 510/4276] eta: 3:12:48 lr: 4.760911420193372e-05 loss: 0.2050 (0.2240) time: 3.0619 data: 0.0082 max mem: 33300 +Epoch: [2] [ 520/4276] eta: 3:12:16 lr: 4.7606468867407774e-05 loss: 0.2050 (0.2240) time: 3.0462 data: 0.0082 max mem: 33300 +Epoch: [2] [ 530/4276] eta: 3:11:45 lr: 4.760382351654921e-05 loss: 0.2248 (0.2239) time: 3.0605 data: 0.0086 max mem: 33300 +Epoch: [2] [ 540/4276] eta: 3:11:15 lr: 4.760117814935695e-05 loss: 0.2050 (0.2236) time: 3.0771 data: 0.0091 max mem: 33300 +Epoch: [2] [ 550/4276] eta: 3:10:44 lr: 4.759853276582985e-05 loss: 0.2154 (0.2238) time: 3.0691 data: 0.0090 max mem: 33300 +Epoch: [2] [ 560/4276] eta: 3:10:10 lr: 4.759588736596683e-05 loss: 0.2165 (0.2240) time: 3.0446 data: 0.0081 max mem: 33300 +Epoch: [2] [ 570/4276] eta: 3:09:39 lr: 4.7593241949766764e-05 loss: 0.2131 (0.2240) time: 3.0489 data: 0.0079 max mem: 33300 +Epoch: [2] [ 580/4276] eta: 3:09:09 lr: 4.7590596517228554e-05 loss: 0.2199 (0.2237) time: 3.0688 data: 0.0082 max mem: 33300 +Epoch: [2] [ 590/4276] eta: 3:08:35 lr: 4.758795106835108e-05 loss: 0.2059 (0.2234) time: 3.0482 data: 0.0080 max mem: 33300 +Epoch: [2] [ 600/4276] eta: 3:08:07 lr: 4.758530560313323e-05 loss: 0.1998 (0.2233) time: 3.0659 data: 0.0081 max mem: 33300 +Epoch: [2] [ 610/4276] eta: 3:07:38 lr: 4.7582660121573905e-05 loss: 0.2086 (0.2231) time: 3.1076 data: 0.0085 max mem: 33300 +Epoch: [2] [ 620/4276] eta: 3:07:08 lr: 4.758001462367198e-05 loss: 0.2140 (0.2231) time: 3.0987 data: 0.0084 max mem: 33300 +Epoch: [2] [ 630/4276] eta: 3:06:40 lr: 4.757736910942637e-05 loss: 0.2283 (0.2232) time: 3.0986 data: 0.0081 max mem: 33300 +Epoch: [2] [ 640/4276] eta: 3:06:10 lr: 4.757472357883593e-05 loss: 0.2121 (0.2231) time: 3.0959 data: 0.0082 max mem: 33300 +Epoch: [2] [ 650/4276] eta: 3:05:39 lr: 4.757207803189957e-05 loss: 0.2098 (0.2230) time: 3.0781 data: 0.0082 max mem: 33300 +Epoch: [2] [ 660/4276] eta: 3:05:09 lr: 4.7569432468616174e-05 loss: 0.2207 (0.2230) time: 3.0756 data: 0.0088 max mem: 33300 +Epoch: [2] [ 670/4276] eta: 3:04:38 lr: 4.7566786888984634e-05 loss: 0.2090 (0.2228) time: 3.0754 data: 0.0093 max mem: 33300 +Epoch: [2] [ 680/4276] eta: 3:04:07 lr: 4.756414129300384e-05 loss: 0.2019 (0.2225) time: 3.0697 data: 0.0089 max mem: 33300 +Epoch: [2] [ 690/4276] eta: 3:03:35 lr: 4.756149568067267e-05 loss: 0.2112 (0.2227) time: 3.0565 data: 0.0090 max mem: 33300 +Epoch: [2] [ 700/4276] eta: 3:03:04 lr: 4.755885005199002e-05 loss: 0.2199 (0.2228) time: 3.0593 data: 0.0088 max mem: 33300 +Epoch: [2] [ 710/4276] eta: 3:02:32 lr: 4.7556204406954785e-05 loss: 0.2343 (0.2230) time: 3.0608 data: 0.0086 max mem: 33300 +Epoch: [2] [ 720/4276] eta: 3:01:59 lr: 4.755355874556584e-05 loss: 0.2268 (0.2229) time: 3.0317 data: 0.0081 max mem: 33300 +Epoch: [2] [ 730/4276] eta: 3:01:26 lr: 4.755091306782208e-05 loss: 0.2252 (0.2232) time: 3.0249 data: 0.0077 max mem: 33300 +Epoch: [2] [ 740/4276] eta: 3:00:56 lr: 4.754826737372239e-05 loss: 0.2250 (0.2232) time: 3.0504 data: 0.0078 max mem: 33300 +Epoch: [2] [ 750/4276] eta: 3:00:23 lr: 4.7545621663265665e-05 loss: 0.2048 (0.2231) time: 3.0483 data: 0.0079 max mem: 33300 +Epoch: [2] [ 760/4276] eta: 2:59:53 lr: 4.754297593645078e-05 loss: 0.1902 (0.2228) time: 3.0552 data: 0.0080 max mem: 33300 +Epoch: [2] [ 770/4276] eta: 2:59:22 lr: 4.754033019327663e-05 loss: 0.1991 (0.2228) time: 3.0731 data: 0.0081 max mem: 33300 +Epoch: [2] [ 780/4276] eta: 2:58:52 lr: 4.75376844337421e-05 loss: 0.2128 (0.2228) time: 3.0814 data: 0.0081 max mem: 33300 +Epoch: [2] [ 790/4276] eta: 2:58:21 lr: 4.753503865784609e-05 loss: 0.2128 (0.2229) time: 3.0709 data: 0.0077 max mem: 33300 +Epoch: [2] [ 800/4276] eta: 2:57:51 lr: 4.753239286558746e-05 loss: 0.2186 (0.2228) time: 3.0742 data: 0.0081 max mem: 33300 +Epoch: [2] [ 810/4276] eta: 2:57:20 lr: 4.7529747056965116e-05 loss: 0.2126 (0.2228) time: 3.0781 data: 0.0078 max mem: 33300 +Epoch: [2] [ 820/4276] eta: 2:56:50 lr: 4.752710123197795e-05 loss: 0.2145 (0.2227) time: 3.0647 data: 0.0074 max mem: 33300 +Epoch: [2] [ 830/4276] eta: 2:56:18 lr: 4.7524455390624835e-05 loss: 0.2347 (0.2231) time: 3.0645 data: 0.0084 max mem: 33300 +Epoch: [2] [ 840/4276] eta: 2:55:47 lr: 4.7521809532904654e-05 loss: 0.2265 (0.2232) time: 3.0611 data: 0.0087 max mem: 33300 +Epoch: [2] [ 850/4276] eta: 2:55:15 lr: 4.751916365881631e-05 loss: 0.2055 (0.2232) time: 3.0467 data: 0.0080 max mem: 33300 +Epoch: [2] [ 860/4276] eta: 2:54:42 lr: 4.751651776835867e-05 loss: 0.1978 (0.2231) time: 3.0135 data: 0.0074 max mem: 33300 +Epoch: [2] [ 870/4276] eta: 2:54:09 lr: 4.751387186153064e-05 loss: 0.2087 (0.2231) time: 3.0144 data: 0.0076 max mem: 33300 +Epoch: [2] [ 880/4276] eta: 2:53:37 lr: 4.751122593833109e-05 loss: 0.2130 (0.2232) time: 3.0285 data: 0.0081 max mem: 33300 +Epoch: [2] [ 890/4276] eta: 2:53:08 lr: 4.7508579998758914e-05 loss: 0.2197 (0.2232) time: 3.0674 data: 0.0081 max mem: 33300 +Epoch: [2] [ 900/4276] eta: 2:52:38 lr: 4.750593404281299e-05 loss: 0.2197 (0.2232) time: 3.0923 data: 0.0084 max mem: 33300 +Epoch: [2] [ 910/4276] eta: 2:52:06 lr: 4.750328807049222e-05 loss: 0.2147 (0.2232) time: 3.0648 data: 0.0083 max mem: 33300 +Epoch: [2] [ 920/4276] eta: 2:51:36 lr: 4.750064208179547e-05 loss: 0.2306 (0.2233) time: 3.0636 data: 0.0080 max mem: 33300 +Epoch: [2] [ 930/4276] eta: 2:51:05 lr: 4.749799607672163e-05 loss: 0.2225 (0.2232) time: 3.0715 data: 0.0081 max mem: 33300 +Epoch: [2] [ 940/4276] eta: 2:50:33 lr: 4.7495350055269594e-05 loss: 0.1986 (0.2230) time: 3.0507 data: 0.0078 max mem: 33300 +Epoch: [2] [ 950/4276] eta: 2:50:01 lr: 4.749270401743824e-05 loss: 0.2004 (0.2229) time: 3.0315 data: 0.0076 max mem: 33300 +Epoch: [2] [ 960/4276] eta: 2:49:31 lr: 4.749005796322645e-05 loss: 0.2084 (0.2230) time: 3.0485 data: 0.0078 max mem: 33300 +Epoch: [2] [ 970/4276] eta: 2:49:01 lr: 4.748741189263311e-05 loss: 0.2167 (0.2229) time: 3.0922 data: 0.0080 max mem: 33300 +Epoch: [2] [ 980/4276] eta: 2:48:33 lr: 4.74847658056571e-05 loss: 0.2216 (0.2232) time: 3.1184 data: 0.0085 max mem: 33300 +Epoch: [2] [ 990/4276] eta: 2:48:04 lr: 4.748211970229732e-05 loss: 0.2226 (0.2231) time: 3.1193 data: 0.0087 max mem: 33300 +Epoch: [2] [1000/4276] eta: 2:47:34 lr: 4.747947358255264e-05 loss: 0.2143 (0.2231) time: 3.1142 data: 0.0084 max mem: 33300 +Epoch: [2] [1010/4276] eta: 2:47:03 lr: 4.7476827446421945e-05 loss: 0.2078 (0.2229) time: 3.0779 data: 0.0081 max mem: 33300 +Epoch: [2] [1020/4276] eta: 2:46:30 lr: 4.747418129390413e-05 loss: 0.2078 (0.2229) time: 3.0305 data: 0.0075 max mem: 33300 +Epoch: [2] [1030/4276] eta: 2:45:58 lr: 4.7471535124998065e-05 loss: 0.2230 (0.2231) time: 3.0172 data: 0.0071 max mem: 33300 +Epoch: [2] [1040/4276] eta: 2:45:28 lr: 4.746888893970264e-05 loss: 0.2330 (0.2230) time: 3.0494 data: 0.0082 max mem: 33300 +Epoch: [2] [1050/4276] eta: 2:44:58 lr: 4.746624273801673e-05 loss: 0.2246 (0.2232) time: 3.0800 data: 0.0090 max mem: 33300 +Epoch: [2] [1060/4276] eta: 2:44:27 lr: 4.7463596519939235e-05 loss: 0.2234 (0.2233) time: 3.0804 data: 0.0089 max mem: 33300 +Epoch: [2] [1070/4276] eta: 2:43:55 lr: 4.7460950285469024e-05 loss: 0.2044 (0.2232) time: 3.0471 data: 0.0081 max mem: 33300 +Epoch: [2] [1080/4276] eta: 2:43:23 lr: 4.7458304034604986e-05 loss: 0.2055 (0.2231) time: 3.0191 data: 0.0071 max mem: 33300 +Epoch: [2] [1090/4276] eta: 2:42:52 lr: 4.7455657767346e-05 loss: 0.2068 (0.2229) time: 3.0385 data: 0.0075 max mem: 33300 +Epoch: [2] [1100/4276] eta: 2:42:21 lr: 4.745301148369095e-05 loss: 0.2060 (0.2229) time: 3.0610 data: 0.0085 max mem: 33300 +Epoch: [2] [1110/4276] eta: 2:41:51 lr: 4.745036518363872e-05 loss: 0.2064 (0.2229) time: 3.0749 data: 0.0085 max mem: 33300 +Epoch: [2] [1120/4276] eta: 2:41:20 lr: 4.74477188671882e-05 loss: 0.2272 (0.2231) time: 3.0718 data: 0.0080 max mem: 33300 +Epoch: [2] [1130/4276] eta: 2:40:50 lr: 4.744507253433825e-05 loss: 0.2262 (0.2230) time: 3.0677 data: 0.0081 max mem: 33300 +Epoch: [2] [1140/4276] eta: 2:40:19 lr: 4.744242618508777e-05 loss: 0.2131 (0.2229) time: 3.0742 data: 0.0084 max mem: 33300 +Epoch: [2] [1150/4276] eta: 2:39:49 lr: 4.743977981943564e-05 loss: 0.2186 (0.2229) time: 3.0807 data: 0.0084 max mem: 33300 +Epoch: [2] [1160/4276] eta: 2:39:19 lr: 4.743713343738073e-05 loss: 0.2187 (0.2230) time: 3.0844 data: 0.0082 max mem: 33300 +Epoch: [2] [1170/4276] eta: 2:38:49 lr: 4.7434487038921935e-05 loss: 0.2310 (0.2231) time: 3.0896 data: 0.0080 max mem: 33300 +Epoch: [2] [1180/4276] eta: 2:38:19 lr: 4.743184062405814e-05 loss: 0.2227 (0.2230) time: 3.0961 data: 0.0080 max mem: 33300 +Epoch: [2] [1190/4276] eta: 2:37:49 lr: 4.742919419278821e-05 loss: 0.2042 (0.2229) time: 3.0913 data: 0.0080 max mem: 33300 +Epoch: [2] [1200/4276] eta: 2:37:18 lr: 4.742654774511104e-05 loss: 0.2207 (0.2229) time: 3.0751 data: 0.0081 max mem: 33300 +Epoch: [2] [1210/4276] eta: 2:36:47 lr: 4.74239012810255e-05 loss: 0.2168 (0.2228) time: 3.0640 data: 0.0084 max mem: 33300 +Epoch: [2] [1220/4276] eta: 2:36:16 lr: 4.7421254800530486e-05 loss: 0.2035 (0.2228) time: 3.0594 data: 0.0082 max mem: 33300 +Epoch: [2] [1230/4276] eta: 2:35:45 lr: 4.7418608303624864e-05 loss: 0.2089 (0.2228) time: 3.0608 data: 0.0081 max mem: 33300 +Epoch: [2] [1240/4276] eta: 2:35:14 lr: 4.741596179030751e-05 loss: 0.2244 (0.2228) time: 3.0619 data: 0.0078 max mem: 33300 +Epoch: [2] [1250/4276] eta: 2:34:44 lr: 4.741331526057733e-05 loss: 0.2244 (0.2229) time: 3.0632 data: 0.0076 max mem: 33300 +Epoch: [2] [1260/4276] eta: 2:34:13 lr: 4.7410668714433174e-05 loss: 0.2007 (0.2227) time: 3.0654 data: 0.0082 max mem: 33300 +Epoch: [2] [1270/4276] eta: 2:33:42 lr: 4.740802215187394e-05 loss: 0.2007 (0.2227) time: 3.0602 data: 0.0083 max mem: 33300 +Epoch: [2] [1280/4276] eta: 2:33:11 lr: 4.740537557289851e-05 loss: 0.2190 (0.2228) time: 3.0594 data: 0.0078 max mem: 33300 +Epoch: [2] [1290/4276] eta: 2:32:40 lr: 4.7402728977505765e-05 loss: 0.2190 (0.2229) time: 3.0626 data: 0.0078 max mem: 33300 +Epoch: [2] [1300/4276] eta: 2:32:10 lr: 4.740008236569456e-05 loss: 0.2086 (0.2228) time: 3.0625 data: 0.0080 max mem: 33300 +Epoch: [2] [1310/4276] eta: 2:31:39 lr: 4.7397435737463805e-05 loss: 0.2014 (0.2227) time: 3.0630 data: 0.0081 max mem: 33300 +Epoch: [2] [1320/4276] eta: 2:31:08 lr: 4.739478909281236e-05 loss: 0.2202 (0.2228) time: 3.0654 data: 0.0081 max mem: 33300 +Epoch: [2] [1330/4276] eta: 2:30:38 lr: 4.7392142431739115e-05 loss: 0.2115 (0.2226) time: 3.0790 data: 0.0079 max mem: 33300 +Epoch: [2] [1340/4276] eta: 2:30:08 lr: 4.738949575424294e-05 loss: 0.1932 (0.2225) time: 3.1004 data: 0.0079 max mem: 33300 +Epoch: [2] [1350/4276] eta: 2:29:38 lr: 4.7386849060322724e-05 loss: 0.2044 (0.2224) time: 3.1038 data: 0.0083 max mem: 33300 +Epoch: [2] [1360/4276] eta: 2:29:08 lr: 4.738420234997734e-05 loss: 0.2144 (0.2224) time: 3.0980 data: 0.0085 max mem: 33300 +Epoch: [2] [1370/4276] eta: 2:28:38 lr: 4.738155562320567e-05 loss: 0.2144 (0.2223) time: 3.0955 data: 0.0083 max mem: 33300 +Epoch: [2] [1380/4276] eta: 2:28:07 lr: 4.737890888000659e-05 loss: 0.2099 (0.2224) time: 3.0795 data: 0.0083 max mem: 33300 +Epoch: [2] [1390/4276] eta: 2:27:36 lr: 4.737626212037897e-05 loss: 0.2208 (0.2223) time: 3.0651 data: 0.0082 max mem: 33300 +Epoch: [2] [1400/4276] eta: 2:27:06 lr: 4.737361534432171e-05 loss: 0.2195 (0.2224) time: 3.0635 data: 0.0084 max mem: 33300 +Epoch: [2] [1410/4276] eta: 2:26:35 lr: 4.737096855183367e-05 loss: 0.2195 (0.2225) time: 3.0688 data: 0.0085 max mem: 33300 +Epoch: [2] [1420/4276] eta: 2:26:04 lr: 4.736832174291373e-05 loss: 0.2162 (0.2226) time: 3.0722 data: 0.0085 max mem: 33300 +Epoch: [2] [1430/4276] eta: 2:25:34 lr: 4.736567491756077e-05 loss: 0.2081 (0.2226) time: 3.0687 data: 0.0083 max mem: 33300 +Epoch: [2] [1440/4276] eta: 2:25:02 lr: 4.736302807577367e-05 loss: 0.2249 (0.2229) time: 3.0546 data: 0.0083 max mem: 33300 +Epoch: [2] [1450/4276] eta: 2:24:31 lr: 4.736038121755131e-05 loss: 0.2308 (0.2229) time: 3.0511 data: 0.0085 max mem: 33300 +Epoch: [2] [1460/4276] eta: 2:24:01 lr: 4.735773434289256e-05 loss: 0.2244 (0.2230) time: 3.0599 data: 0.0085 max mem: 33300 +Epoch: [2] [1470/4276] eta: 2:23:30 lr: 4.7355087451796296e-05 loss: 0.2253 (0.2231) time: 3.0676 data: 0.0082 max mem: 33300 +Epoch: [2] [1480/4276] eta: 2:22:59 lr: 4.735244054426139e-05 loss: 0.2219 (0.2231) time: 3.0671 data: 0.0079 max mem: 33300 +Epoch: [2] [1490/4276] eta: 2:22:28 lr: 4.734979362028675e-05 loss: 0.2133 (0.2230) time: 3.0621 data: 0.0083 max mem: 33300 +Epoch: [2] [1500/4276] eta: 2:21:58 lr: 4.7347146679871224e-05 loss: 0.2133 (0.2229) time: 3.0679 data: 0.0086 max mem: 33300 +Epoch: [2] [1510/4276] eta: 2:21:28 lr: 4.7344499723013694e-05 loss: 0.1963 (0.2229) time: 3.0873 data: 0.0086 max mem: 33300 +Epoch: [2] [1520/4276] eta: 2:20:58 lr: 4.734185274971303e-05 loss: 0.2063 (0.2228) time: 3.1053 data: 0.0085 max mem: 33300 +Epoch: [2] [1530/4276] eta: 2:20:28 lr: 4.733920575996813e-05 loss: 0.2083 (0.2228) time: 3.1076 data: 0.0085 max mem: 33300 +Epoch: [2] [1540/4276] eta: 2:19:58 lr: 4.733655875377785e-05 loss: 0.2178 (0.2228) time: 3.1179 data: 0.0085 max mem: 33300 +Epoch: [2] [1550/4276] eta: 2:19:28 lr: 4.7333911731141074e-05 loss: 0.2178 (0.2228) time: 3.1183 data: 0.0085 max mem: 33300 +Epoch: [2] [1560/4276] eta: 2:18:57 lr: 4.7331264692056676e-05 loss: 0.2062 (0.2227) time: 3.0767 data: 0.0083 max mem: 33300 +Epoch: [2] [1570/4276] eta: 2:18:26 lr: 4.7328617636523534e-05 loss: 0.1894 (0.2226) time: 3.0579 data: 0.0084 max mem: 33300 +Epoch: [2] [1580/4276] eta: 2:17:56 lr: 4.732597056454051e-05 loss: 0.1894 (0.2224) time: 3.0752 data: 0.0089 max mem: 33300 +Epoch: [2] [1590/4276] eta: 2:17:25 lr: 4.7323323476106504e-05 loss: 0.2082 (0.2223) time: 3.0749 data: 0.0086 max mem: 33300 +Epoch: [2] [1600/4276] eta: 2:16:54 lr: 4.732067637122038e-05 loss: 0.2149 (0.2224) time: 3.0743 data: 0.0088 max mem: 33300 +Epoch: [2] [1610/4276] eta: 2:16:24 lr: 4.7318029249881004e-05 loss: 0.2002 (0.2223) time: 3.0707 data: 0.0084 max mem: 33300 +Epoch: [2] [1620/4276] eta: 2:15:53 lr: 4.731538211208726e-05 loss: 0.2096 (0.2223) time: 3.0722 data: 0.0082 max mem: 33300 +Epoch: [2] [1630/4276] eta: 2:15:22 lr: 4.731273495783802e-05 loss: 0.2228 (0.2225) time: 3.0738 data: 0.0090 max mem: 33300 +Epoch: [2] [1640/4276] eta: 2:14:52 lr: 4.731008778713217e-05 loss: 0.2303 (0.2226) time: 3.0618 data: 0.0086 max mem: 33300 +Epoch: [2] [1650/4276] eta: 2:14:21 lr: 4.7307440599968564e-05 loss: 0.2194 (0.2226) time: 3.0596 data: 0.0080 max mem: 33300 +Epoch: [2] [1660/4276] eta: 2:13:50 lr: 4.730479339634609e-05 loss: 0.2145 (0.2225) time: 3.0705 data: 0.0080 max mem: 33300 +Epoch: [2] [1670/4276] eta: 2:13:19 lr: 4.730214617626362e-05 loss: 0.2209 (0.2226) time: 3.0724 data: 0.0079 max mem: 33300 +Epoch: [2] [1680/4276] eta: 2:12:49 lr: 4.729949893972004e-05 loss: 0.2241 (0.2227) time: 3.0756 data: 0.0081 max mem: 33300 +Epoch: [2] [1690/4276] eta: 2:12:18 lr: 4.729685168671419e-05 loss: 0.2221 (0.2226) time: 3.0857 data: 0.0088 max mem: 33300 +Epoch: [2] [1700/4276] eta: 2:11:48 lr: 4.7294204417244984e-05 loss: 0.2153 (0.2226) time: 3.1011 data: 0.0090 max mem: 33300 +Epoch: [2] [1710/4276] eta: 2:11:18 lr: 4.7291557131311264e-05 loss: 0.2254 (0.2227) time: 3.1124 data: 0.0086 max mem: 33300 +Epoch: [2] [1720/4276] eta: 2:10:48 lr: 4.728890982891192e-05 loss: 0.2310 (0.2228) time: 3.1094 data: 0.0089 max mem: 33300 +Epoch: [2] [1730/4276] eta: 2:10:18 lr: 4.728626251004583e-05 loss: 0.2231 (0.2227) time: 3.1122 data: 0.0090 max mem: 33300 +Epoch: [2] [1740/4276] eta: 2:09:48 lr: 4.728361517471185e-05 loss: 0.2104 (0.2227) time: 3.0953 data: 0.0084 max mem: 33300 +Epoch: [2] [1750/4276] eta: 2:09:16 lr: 4.728096782290886e-05 loss: 0.2266 (0.2228) time: 3.0423 data: 0.0077 max mem: 33300 +Epoch: [2] [1760/4276] eta: 2:08:45 lr: 4.7278320454635745e-05 loss: 0.2208 (0.2227) time: 3.0167 data: 0.0074 max mem: 33300 +Epoch: [2] [1770/4276] eta: 2:08:14 lr: 4.727567306989136e-05 loss: 0.2208 (0.2227) time: 3.0479 data: 0.0079 max mem: 33300 +Epoch: [2] [1780/4276] eta: 2:07:43 lr: 4.727302566867459e-05 loss: 0.2153 (0.2227) time: 3.0666 data: 0.0089 max mem: 33300 +Epoch: [2] [1790/4276] eta: 2:07:12 lr: 4.7270378250984306e-05 loss: 0.2128 (0.2227) time: 3.0551 data: 0.0094 max mem: 33300 +Epoch: [2] [1800/4276] eta: 2:06:41 lr: 4.726773081681938e-05 loss: 0.2230 (0.2227) time: 3.0609 data: 0.0086 max mem: 33300 +Epoch: [2] [1810/4276] eta: 2:06:11 lr: 4.726508336617867e-05 loss: 0.2369 (0.2228) time: 3.0714 data: 0.0078 max mem: 33300 +Epoch: [2] [1820/4276] eta: 2:05:40 lr: 4.7262435899061064e-05 loss: 0.2079 (0.2227) time: 3.0734 data: 0.0079 max mem: 33300 +Epoch: [2] [1830/4276] eta: 2:05:09 lr: 4.725978841546543e-05 loss: 0.2035 (0.2227) time: 3.0729 data: 0.0077 max mem: 33300 +Epoch: [2] [1840/4276] eta: 2:04:39 lr: 4.725714091539065e-05 loss: 0.2035 (0.2227) time: 3.0667 data: 0.0080 max mem: 33300 +Epoch: [2] [1850/4276] eta: 2:04:08 lr: 4.725449339883557e-05 loss: 0.2209 (0.2228) time: 3.0711 data: 0.0081 max mem: 33300 +Epoch: [2] [1860/4276] eta: 2:03:37 lr: 4.725184586579908e-05 loss: 0.2256 (0.2228) time: 3.0796 data: 0.0077 max mem: 33300 +Epoch: [2] [1870/4276] eta: 2:03:07 lr: 4.724919831628006e-05 loss: 0.2256 (0.2230) time: 3.0965 data: 0.0079 max mem: 33300 +Epoch: [2] [1880/4276] eta: 2:02:37 lr: 4.7246550750277355e-05 loss: 0.2184 (0.2229) time: 3.1174 data: 0.0077 max mem: 33300 +Epoch: [2] [1890/4276] eta: 2:02:07 lr: 4.724390316778985e-05 loss: 0.2126 (0.2228) time: 3.1168 data: 0.0074 max mem: 33300 +Epoch: [2] [1900/4276] eta: 2:01:37 lr: 4.7241255568816426e-05 loss: 0.2062 (0.2227) time: 3.1102 data: 0.0075 max mem: 33300 +Epoch: [2] [1910/4276] eta: 2:01:07 lr: 4.723860795335594e-05 loss: 0.2062 (0.2227) time: 3.1101 data: 0.0076 max mem: 33300 +Epoch: [2] [1920/4276] eta: 2:00:36 lr: 4.723596032140727e-05 loss: 0.2063 (0.2225) time: 3.1113 data: 0.0077 max mem: 33300 +Epoch: [2] [1930/4276] eta: 2:00:06 lr: 4.7233312672969276e-05 loss: 0.2044 (0.2225) time: 3.0965 data: 0.0077 max mem: 33300 +Epoch: [2] [1940/4276] eta: 1:59:35 lr: 4.7230665008040836e-05 loss: 0.2122 (0.2226) time: 3.0828 data: 0.0076 max mem: 33300 +Epoch: [2] [1950/4276] eta: 1:59:05 lr: 4.722801732662082e-05 loss: 0.2091 (0.2225) time: 3.0821 data: 0.0079 max mem: 33300 +Epoch: [2] [1960/4276] eta: 1:58:34 lr: 4.7225369628708096e-05 loss: 0.2019 (0.2225) time: 3.0809 data: 0.0081 max mem: 33300 +Epoch: [2] [1970/4276] eta: 1:58:03 lr: 4.722272191430154e-05 loss: 0.1903 (0.2224) time: 3.0772 data: 0.0079 max mem: 33300 +Epoch: [2] [1980/4276] eta: 1:57:33 lr: 4.7220074183400015e-05 loss: 0.1874 (0.2222) time: 3.0765 data: 0.0080 max mem: 33300 +Epoch: [2] [1990/4276] eta: 1:57:02 lr: 4.7217426436002394e-05 loss: 0.2045 (0.2222) time: 3.0714 data: 0.0078 max mem: 33300 +Epoch: [2] [2000/4276] eta: 1:56:31 lr: 4.721477867210754e-05 loss: 0.2202 (0.2223) time: 3.0622 data: 0.0073 max mem: 33300 +Epoch: [2] [2010/4276] eta: 1:56:00 lr: 4.721213089171433e-05 loss: 0.2209 (0.2222) time: 3.0637 data: 0.0072 max mem: 33300 +Epoch: [2] [2020/4276] eta: 1:55:30 lr: 4.720948309482163e-05 loss: 0.2221 (0.2223) time: 3.0780 data: 0.0074 max mem: 33300 +Epoch: [2] [2030/4276] eta: 1:54:59 lr: 4.720683528142831e-05 loss: 0.2142 (0.2222) time: 3.0768 data: 0.0075 max mem: 33300 +Epoch: [2] [2040/4276] eta: 1:54:28 lr: 4.7204187451533236e-05 loss: 0.1993 (0.2221) time: 3.0596 data: 0.0073 max mem: 33300 +Epoch: [2] [2050/4276] eta: 1:53:56 lr: 4.720153960513527e-05 loss: 0.2078 (0.2222) time: 3.0302 data: 0.0078 max mem: 33300 +Epoch: [2] [2060/4276] eta: 1:53:25 lr: 4.7198891742233296e-05 loss: 0.2123 (0.2221) time: 3.0072 data: 0.0080 max mem: 33300 +Epoch: [2] [2070/4276] eta: 1:52:54 lr: 4.7196243862826186e-05 loss: 0.2109 (0.2220) time: 3.0336 data: 0.0079 max mem: 33300 +Epoch: [2] [2080/4276] eta: 1:52:24 lr: 4.719359596691278e-05 loss: 0.2034 (0.2221) time: 3.0736 data: 0.0081 max mem: 33300 +Epoch: [2] [2090/4276] eta: 1:51:53 lr: 4.7190948054491974e-05 loss: 0.2117 (0.2220) time: 3.1000 data: 0.0077 max mem: 33300 +Epoch: [2] [2100/4276] eta: 1:51:23 lr: 4.718830012556262e-05 loss: 0.2023 (0.2219) time: 3.1106 data: 0.0075 max mem: 33300 +Epoch: [2] [2110/4276] eta: 1:50:53 lr: 4.71856521801236e-05 loss: 0.2001 (0.2218) time: 3.1126 data: 0.0078 max mem: 33300 +Epoch: [2] [2120/4276] eta: 1:50:22 lr: 4.718300421817376e-05 loss: 0.2030 (0.2218) time: 3.0827 data: 0.0079 max mem: 33300 +Epoch: [2] [2130/4276] eta: 1:49:51 lr: 4.718035623971199e-05 loss: 0.1977 (0.2218) time: 3.0638 data: 0.0077 max mem: 33300 +Epoch: [2] [2140/4276] eta: 1:49:21 lr: 4.717770824473715e-05 loss: 0.2135 (0.2218) time: 3.0778 data: 0.0076 max mem: 33300 +Epoch: [2] [2150/4276] eta: 1:48:50 lr: 4.7175060233248105e-05 loss: 0.2139 (0.2218) time: 3.0771 data: 0.0078 max mem: 33300 +Epoch: [2] [2160/4276] eta: 1:48:19 lr: 4.7172412205243715e-05 loss: 0.2137 (0.2219) time: 3.0806 data: 0.0079 max mem: 33300 +Epoch: [2] [2170/4276] eta: 1:47:49 lr: 4.7169764160722854e-05 loss: 0.2155 (0.2219) time: 3.0792 data: 0.0078 max mem: 33300 +Epoch: [2] [2180/4276] eta: 1:47:18 lr: 4.71671160996844e-05 loss: 0.2332 (0.2220) time: 3.0780 data: 0.0075 max mem: 33300 +Epoch: [2] [2190/4276] eta: 1:46:47 lr: 4.7164468022127195e-05 loss: 0.2332 (0.2220) time: 3.0796 data: 0.0077 max mem: 33300 +Epoch: [2] [2200/4276] eta: 1:46:17 lr: 4.716181992805012e-05 loss: 0.2237 (0.2220) time: 3.0787 data: 0.0076 max mem: 33300 +Epoch: [2] [2210/4276] eta: 1:45:46 lr: 4.7159171817452044e-05 loss: 0.2230 (0.2220) time: 3.0715 data: 0.0078 max mem: 33300 +Epoch: [2] [2220/4276] eta: 1:45:15 lr: 4.715652369033183e-05 loss: 0.2195 (0.2220) time: 3.0623 data: 0.0082 max mem: 33300 +Epoch: [2] [2230/4276] eta: 1:44:44 lr: 4.715387554668834e-05 loss: 0.2195 (0.2220) time: 3.0685 data: 0.0079 max mem: 33300 +Epoch: [2] [2240/4276] eta: 1:44:14 lr: 4.7151227386520443e-05 loss: 0.2104 (0.2219) time: 3.0821 data: 0.0079 max mem: 33300 +Epoch: [2] [2250/4276] eta: 1:43:43 lr: 4.714857920982701e-05 loss: 0.2007 (0.2218) time: 3.0947 data: 0.0080 max mem: 33300 +Epoch: [2] [2260/4276] eta: 1:43:13 lr: 4.71459310166069e-05 loss: 0.2063 (0.2219) time: 3.1048 data: 0.0078 max mem: 33300 +Epoch: [2] [2270/4276] eta: 1:42:43 lr: 4.714328280685897e-05 loss: 0.2063 (0.2219) time: 3.1039 data: 0.0081 max mem: 33300 +Epoch: [2] [2280/4276] eta: 1:42:12 lr: 4.7140634580582105e-05 loss: 0.2045 (0.2218) time: 3.0973 data: 0.0081 max mem: 33300 +Epoch: [2] [2290/4276] eta: 1:41:41 lr: 4.7137986337775154e-05 loss: 0.2086 (0.2218) time: 3.0925 data: 0.0076 max mem: 33300 +Epoch: [2] [2300/4276] eta: 1:41:11 lr: 4.7135338078437e-05 loss: 0.2006 (0.2216) time: 3.0921 data: 0.0074 max mem: 33300 +Epoch: [2] [2310/4276] eta: 1:40:40 lr: 4.7132689802566476e-05 loss: 0.2009 (0.2216) time: 3.0663 data: 0.0074 max mem: 33300 +Epoch: [2] [2320/4276] eta: 1:40:09 lr: 4.713004151016248e-05 loss: 0.2166 (0.2215) time: 3.0490 data: 0.0077 max mem: 33300 +Epoch: [2] [2330/4276] eta: 1:39:38 lr: 4.712739320122386e-05 loss: 0.2094 (0.2214) time: 3.0657 data: 0.0078 max mem: 33300 +Epoch: [2] [2340/4276] eta: 1:39:08 lr: 4.7124744875749485e-05 loss: 0.2094 (0.2214) time: 3.0672 data: 0.0079 max mem: 33300 +Epoch: [2] [2350/4276] eta: 1:38:37 lr: 4.712209653373821e-05 loss: 0.2129 (0.2214) time: 3.0676 data: 0.0081 max mem: 33300 +Epoch: [2] [2360/4276] eta: 1:38:06 lr: 4.711944817518891e-05 loss: 0.2129 (0.2213) time: 3.0668 data: 0.0080 max mem: 33300 +Epoch: [2] [2370/4276] eta: 1:37:35 lr: 4.7116799800100444e-05 loss: 0.2131 (0.2214) time: 3.0688 data: 0.0081 max mem: 33300 +Epoch: [2] [2380/4276] eta: 1:37:04 lr: 4.711415140847169e-05 loss: 0.2041 (0.2213) time: 3.0455 data: 0.0077 max mem: 33300 +Epoch: [2] [2390/4276] eta: 1:36:33 lr: 4.711150300030148e-05 loss: 0.1933 (0.2213) time: 3.0281 data: 0.0082 max mem: 33300 +Epoch: [2] [2400/4276] eta: 1:36:02 lr: 4.71088545755887e-05 loss: 0.2095 (0.2213) time: 3.0381 data: 0.0086 max mem: 33300 +Epoch: [2] [2410/4276] eta: 1:35:31 lr: 4.710620613433222e-05 loss: 0.2123 (0.2213) time: 3.0528 data: 0.0080 max mem: 33300 +Epoch: [2] [2420/4276] eta: 1:35:01 lr: 4.710355767653088e-05 loss: 0.2022 (0.2212) time: 3.0597 data: 0.0081 max mem: 33300 +Epoch: [2] [2430/4276] eta: 1:34:30 lr: 4.7100909202183566e-05 loss: 0.2158 (0.2212) time: 3.0598 data: 0.0080 max mem: 33300 +Epoch: [2] [2440/4276] eta: 1:33:59 lr: 4.709826071128913e-05 loss: 0.2264 (0.2212) time: 3.0948 data: 0.0077 max mem: 33300 +Epoch: [2] [2450/4276] eta: 1:33:29 lr: 4.709561220384643e-05 loss: 0.2121 (0.2212) time: 3.1159 data: 0.0078 max mem: 33300 +Epoch: [2] [2460/4276] eta: 1:32:58 lr: 4.7092963679854336e-05 loss: 0.2088 (0.2212) time: 3.0844 data: 0.0080 max mem: 33300 +Epoch: [2] [2470/4276] eta: 1:32:27 lr: 4.7090315139311705e-05 loss: 0.2113 (0.2212) time: 3.0550 data: 0.0080 max mem: 33300 +Epoch: [2] [2480/4276] eta: 1:31:56 lr: 4.708766658221741e-05 loss: 0.2195 (0.2212) time: 3.0402 data: 0.0077 max mem: 33300 +Epoch: [2] [2490/4276] eta: 1:31:25 lr: 4.7085018008570296e-05 loss: 0.2177 (0.2211) time: 2.9883 data: 0.0081 max mem: 33300 +Epoch: [2] [2500/4276] eta: 1:30:53 lr: 4.708236941836924e-05 loss: 0.2157 (0.2211) time: 2.9386 data: 0.0083 max mem: 33300 +Epoch: [2] [2510/4276] eta: 1:30:21 lr: 4.7079720811613096e-05 loss: 0.2129 (0.2211) time: 2.9364 data: 0.0077 max mem: 33300 +Epoch: [2] [2520/4276] eta: 1:29:50 lr: 4.707707218830073e-05 loss: 0.1953 (0.2209) time: 2.9349 data: 0.0077 max mem: 33300 +Epoch: [2] [2530/4276] eta: 1:29:18 lr: 4.7074423548431005e-05 loss: 0.1726 (0.2208) time: 2.9083 data: 0.0082 max mem: 33300 +Epoch: [2] [2540/4276] eta: 1:28:46 lr: 4.7071774892002775e-05 loss: 0.1852 (0.2207) time: 2.8897 data: 0.0082 max mem: 33300 +Epoch: [2] [2550/4276] eta: 1:28:14 lr: 4.70691262190149e-05 loss: 0.2095 (0.2207) time: 2.9025 data: 0.0078 max mem: 33300 +Epoch: [2] [2560/4276] eta: 1:27:43 lr: 4.706647752946626e-05 loss: 0.1865 (0.2206) time: 2.9302 data: 0.0077 max mem: 33300 +Epoch: [2] [2570/4276] eta: 1:27:11 lr: 4.706382882335569e-05 loss: 0.1865 (0.2206) time: 2.9445 data: 0.0073 max mem: 33300 +Epoch: [2] [2580/4276] eta: 1:26:40 lr: 4.7061180100682064e-05 loss: 0.2048 (0.2206) time: 2.9425 data: 0.0071 max mem: 33300 +Epoch: [2] [2590/4276] eta: 1:26:08 lr: 4.705853136144425e-05 loss: 0.2073 (0.2205) time: 2.9435 data: 0.0072 max mem: 33300 +Epoch: [2] [2600/4276] eta: 1:25:37 lr: 4.7055882605641095e-05 loss: 0.2081 (0.2206) time: 2.9456 data: 0.0072 max mem: 33300 +Epoch: [2] [2610/4276] eta: 1:25:05 lr: 4.705323383327146e-05 loss: 0.2163 (0.2206) time: 2.9455 data: 0.0072 max mem: 33300 +Epoch: [2] [2620/4276] eta: 1:24:34 lr: 4.705058504433422e-05 loss: 0.2148 (0.2206) time: 2.9485 data: 0.0072 max mem: 33300 +Epoch: [2] [2630/4276] eta: 1:24:03 lr: 4.704793623882821e-05 loss: 0.2083 (0.2205) time: 2.9637 data: 0.0072 max mem: 33300 +Epoch: [2] [2640/4276] eta: 1:23:32 lr: 4.704528741675231e-05 loss: 0.1901 (0.2204) time: 2.9697 data: 0.0073 max mem: 33300 +Epoch: [2] [2650/4276] eta: 1:23:00 lr: 4.704263857810539e-05 loss: 0.1908 (0.2204) time: 2.9727 data: 0.0074 max mem: 33300 +Epoch: [2] [2660/4276] eta: 1:22:29 lr: 4.7039989722886276e-05 loss: 0.2208 (0.2204) time: 2.9744 data: 0.0073 max mem: 33300 +Epoch: [2] [2670/4276] eta: 1:21:58 lr: 4.703734085109385e-05 loss: 0.2215 (0.2204) time: 2.9674 data: 0.0071 max mem: 33300 +Epoch: [2] [2680/4276] eta: 1:21:27 lr: 4.703469196272696e-05 loss: 0.1988 (0.2204) time: 2.9663 data: 0.0070 max mem: 33300 +Epoch: [2] [2690/4276] eta: 1:20:56 lr: 4.703204305778448e-05 loss: 0.2201 (0.2204) time: 2.9675 data: 0.0072 max mem: 33300 +Epoch: [2] [2700/4276] eta: 1:20:24 lr: 4.702939413626526e-05 loss: 0.2037 (0.2203) time: 2.9679 data: 0.0070 max mem: 33300 +Epoch: [2] [2710/4276] eta: 1:19:53 lr: 4.7026745198168154e-05 loss: 0.1966 (0.2203) time: 2.9730 data: 0.0065 max mem: 33300 +Epoch: [2] [2720/4276] eta: 1:21:06 lr: 4.702409624349204e-05 loss: 0.2068 (0.2203) time: 12.0791 data: 9.1211 max mem: 33300 +Epoch: [2] [2730/4276] eta: 1:20:34 lr: 4.7021447272235744e-05 loss: 0.2062 (0.2203) time: 12.0557 data: 9.1208 max mem: 33300 +Epoch: [2] [2740/4276] eta: 1:20:01 lr: 4.7018798284398155e-05 loss: 0.2183 (0.2203) time: 2.9080 data: 0.0067 max mem: 33300 +Epoch: [2] [2750/4276] eta: 1:19:29 lr: 4.7016149279978114e-05 loss: 0.2258 (0.2203) time: 2.9202 data: 0.0081 max mem: 33300 +Epoch: [2] [2760/4276] eta: 1:18:57 lr: 4.701350025897448e-05 loss: 0.2026 (0.2203) time: 2.9517 data: 0.0089 max mem: 33300 +Epoch: [2] [2770/4276] eta: 1:18:25 lr: 4.701085122138613e-05 loss: 0.1964 (0.2202) time: 2.9404 data: 0.0089 max mem: 33300 +Epoch: [2] [2780/4276] eta: 1:17:53 lr: 4.7008202167211894e-05 loss: 0.1970 (0.2202) time: 2.9537 data: 0.0086 max mem: 33300 +Epoch: [2] [2790/4276] eta: 1:17:20 lr: 4.7005553096450646e-05 loss: 0.2303 (0.2202) time: 2.9432 data: 0.0085 max mem: 33300 +Epoch: [2] [2800/4276] eta: 1:16:48 lr: 4.700290400910125e-05 loss: 0.2203 (0.2202) time: 2.9379 data: 0.0083 max mem: 33300 +Epoch: [2] [2810/4276] eta: 1:16:16 lr: 4.700025490516254e-05 loss: 0.1877 (0.2201) time: 2.9537 data: 0.0085 max mem: 33300 +Epoch: [2] [2820/4276] eta: 1:15:44 lr: 4.6997605784633384e-05 loss: 0.2024 (0.2200) time: 2.9560 data: 0.0087 max mem: 33300 +Epoch: [2] [2830/4276] eta: 1:15:12 lr: 4.699495664751265e-05 loss: 0.2044 (0.2200) time: 2.9494 data: 0.0088 max mem: 33300 +Epoch: [2] [2840/4276] eta: 1:14:40 lr: 4.699230749379918e-05 loss: 0.2098 (0.2199) time: 2.9260 data: 0.0082 max mem: 33300 +Epoch: [2] [2850/4276] eta: 1:14:07 lr: 4.698965832349185e-05 loss: 0.2197 (0.2201) time: 2.9013 data: 0.0077 max mem: 33300 +Epoch: [2] [2860/4276] eta: 1:13:35 lr: 4.698700913658949e-05 loss: 0.2197 (0.2201) time: 2.8998 data: 0.0082 max mem: 33300 +Epoch: [2] [2870/4276] eta: 1:13:03 lr: 4.698435993309098e-05 loss: 0.2148 (0.2201) time: 2.9112 data: 0.0082 max mem: 33300 +Epoch: [2] [2880/4276] eta: 1:12:31 lr: 4.6981710712995166e-05 loss: 0.2203 (0.2201) time: 2.9196 data: 0.0077 max mem: 33300 +Epoch: [2] [2890/4276] eta: 1:11:59 lr: 4.6979061476300896e-05 loss: 0.2209 (0.2201) time: 2.9386 data: 0.0078 max mem: 33300 +Epoch: [2] [2900/4276] eta: 1:11:27 lr: 4.697641222300704e-05 loss: 0.2050 (0.2201) time: 2.9419 data: 0.0087 max mem: 33300 +Epoch: [2] [2910/4276] eta: 1:10:55 lr: 4.697376295311244e-05 loss: 0.2057 (0.2201) time: 2.9303 data: 0.0087 max mem: 33300 +Epoch: [2] [2920/4276] eta: 1:10:23 lr: 4.697111366661597e-05 loss: 0.2057 (0.2200) time: 2.9376 data: 0.0084 max mem: 33300 +Epoch: [2] [2930/4276] eta: 1:09:51 lr: 4.696846436351648e-05 loss: 0.1928 (0.2200) time: 2.9560 data: 0.0088 max mem: 33300 +Epoch: [2] [2940/4276] eta: 1:09:19 lr: 4.696581504381281e-05 loss: 0.1918 (0.2199) time: 2.9231 data: 0.0088 max mem: 33300 +Epoch: [2] [2950/4276] eta: 1:08:46 lr: 4.6963165707503834e-05 loss: 0.1871 (0.2199) time: 2.8837 data: 0.0086 max mem: 33300 +Epoch: [2] [2960/4276] eta: 1:08:14 lr: 4.69605163545884e-05 loss: 0.2100 (0.2199) time: 2.8946 data: 0.0080 max mem: 33300 +Epoch: [2] [2970/4276] eta: 1:07:43 lr: 4.6957866985065355e-05 loss: 0.2184 (0.2200) time: 2.9155 data: 0.0075 max mem: 33300 +Epoch: [2] [2980/4276] eta: 1:07:10 lr: 4.695521759893356e-05 loss: 0.2186 (0.2199) time: 2.9127 data: 0.0072 max mem: 33300 +Epoch: [2] [2990/4276] eta: 1:06:39 lr: 4.695256819619187e-05 loss: 0.2076 (0.2199) time: 2.9106 data: 0.0070 max mem: 33300 +Epoch: [2] [3000/4276] eta: 1:06:07 lr: 4.694991877683915e-05 loss: 0.2030 (0.2198) time: 2.9121 data: 0.0070 max mem: 33300 +Epoch: [2] [3010/4276] eta: 1:05:35 lr: 4.694726934087424e-05 loss: 0.2104 (0.2198) time: 2.9056 data: 0.0070 max mem: 33300 +Epoch: [2] [3020/4276] eta: 1:05:03 lr: 4.694461988829599e-05 loss: 0.2071 (0.2198) time: 2.8854 data: 0.0072 max mem: 33300 +Epoch: [2] [3030/4276] eta: 1:04:30 lr: 4.694197041910327e-05 loss: 0.1952 (0.2198) time: 2.8668 data: 0.0081 max mem: 33300 +Epoch: [2] [3040/4276] eta: 1:03:58 lr: 4.6939320933294926e-05 loss: 0.2211 (0.2199) time: 2.8684 data: 0.0085 max mem: 33300 +Epoch: [2] [3050/4276] eta: 1:03:26 lr: 4.693667143086982e-05 loss: 0.2278 (0.2198) time: 2.8690 data: 0.0084 max mem: 33300 +Epoch: [2] [3060/4276] eta: 1:02:54 lr: 4.693402191182678e-05 loss: 0.1962 (0.2197) time: 2.8675 data: 0.0080 max mem: 33300 +Epoch: [2] [3070/4276] eta: 1:02:23 lr: 4.693137237616469e-05 loss: 0.1969 (0.2197) time: 2.8924 data: 0.0079 max mem: 33300 +Epoch: [2] [3080/4276] eta: 1:01:51 lr: 4.692872282388239e-05 loss: 0.2033 (0.2197) time: 2.8959 data: 0.0081 max mem: 33300 +Epoch: [2] [3090/4276] eta: 1:01:19 lr: 4.692607325497873e-05 loss: 0.2033 (0.2197) time: 2.8967 data: 0.0083 max mem: 33300 +Epoch: [2] [3100/4276] eta: 1:00:47 lr: 4.6923423669452566e-05 loss: 0.2153 (0.2197) time: 2.9053 data: 0.0086 max mem: 33300 +Epoch: [2] [3110/4276] eta: 1:00:16 lr: 4.692077406730275e-05 loss: 0.2080 (0.2196) time: 2.9109 data: 0.0088 max mem: 33300 +Epoch: [2] [3120/4276] eta: 0:59:44 lr: 4.6918124448528136e-05 loss: 0.1874 (0.2196) time: 2.9476 data: 0.0087 max mem: 33300 +Epoch: [2] [3130/4276] eta: 0:59:12 lr: 4.691547481312758e-05 loss: 0.2016 (0.2195) time: 2.9565 data: 0.0086 max mem: 33300 +Epoch: [2] [3140/4276] eta: 0:58:41 lr: 4.6912825161099925e-05 loss: 0.2121 (0.2196) time: 2.9600 data: 0.0084 max mem: 33300 +Epoch: [2] [3150/4276] eta: 0:58:09 lr: 4.691017549244403e-05 loss: 0.2202 (0.2196) time: 2.9592 data: 0.0080 max mem: 33300 +Epoch: [2] [3160/4276] eta: 0:57:38 lr: 4.6907525807158756e-05 loss: 0.2148 (0.2196) time: 2.9362 data: 0.0079 max mem: 33300 +Epoch: [2] [3170/4276] eta: 0:57:06 lr: 4.6904876105242935e-05 loss: 0.2085 (0.2196) time: 2.9430 data: 0.0078 max mem: 33300 +Epoch: [2] [3180/4276] eta: 0:56:35 lr: 4.690222638669543e-05 loss: 0.2138 (0.2197) time: 2.9464 data: 0.0078 max mem: 33300 +Epoch: [2] [3190/4276] eta: 0:56:03 lr: 4.689957665151509e-05 loss: 0.2261 (0.2197) time: 2.9333 data: 0.0081 max mem: 33300 +Epoch: [2] [3200/4276] eta: 0:55:32 lr: 4.689692689970077e-05 loss: 0.2100 (0.2197) time: 2.9474 data: 0.0081 max mem: 33300 +Epoch: [2] [3210/4276] eta: 0:55:00 lr: 4.689427713125132e-05 loss: 0.1988 (0.2197) time: 2.9601 data: 0.0076 max mem: 33300 +Epoch: [2] [3220/4276] eta: 0:54:29 lr: 4.6891627346165585e-05 loss: 0.2150 (0.2196) time: 2.9469 data: 0.0076 max mem: 33300 +Epoch: [2] [3230/4276] eta: 0:53:57 lr: 4.688897754444242e-05 loss: 0.2150 (0.2196) time: 2.9270 data: 0.0081 max mem: 33300 +Epoch: [2] [3240/4276] eta: 0:53:26 lr: 4.688632772608069e-05 loss: 0.2191 (0.2196) time: 2.8966 data: 0.0081 max mem: 33300 +Epoch: [2] [3250/4276] eta: 0:52:54 lr: 4.688367789107922e-05 loss: 0.2132 (0.2196) time: 2.8699 data: 0.0078 max mem: 33300 +Epoch: [2] [3260/4276] eta: 0:52:23 lr: 4.688102803943687e-05 loss: 0.2091 (0.2196) time: 2.8895 data: 0.0085 max mem: 33300 +Epoch: [2] [3270/4276] eta: 0:51:51 lr: 4.68783781711525e-05 loss: 0.2025 (0.2196) time: 2.9229 data: 0.0085 max mem: 33300 +Epoch: [2] [3280/4276] eta: 0:51:20 lr: 4.6875728286224954e-05 loss: 0.2025 (0.2196) time: 2.9289 data: 0.0080 max mem: 33300 +Epoch: [2] [3290/4276] eta: 0:50:48 lr: 4.687307838465309e-05 loss: 0.2205 (0.2196) time: 2.9218 data: 0.0082 max mem: 33300 +Epoch: [2] [3300/4276] eta: 0:50:17 lr: 4.6870428466435736e-05 loss: 0.2353 (0.2197) time: 2.9492 data: 0.0079 max mem: 33300 +Epoch: [2] [3310/4276] eta: 0:49:46 lr: 4.686777853157176e-05 loss: 0.2353 (0.2197) time: 2.9646 data: 0.0076 max mem: 33300 +Epoch: [2] [3320/4276] eta: 0:49:14 lr: 4.686512858006001e-05 loss: 0.2224 (0.2197) time: 2.9431 data: 0.0075 max mem: 33300 +Epoch: [2] [3330/4276] eta: 0:48:43 lr: 4.6862478611899326e-05 loss: 0.2027 (0.2197) time: 2.9283 data: 0.0077 max mem: 33300 +Epoch: [2] [3340/4276] eta: 0:48:12 lr: 4.685982862708857e-05 loss: 0.2027 (0.2197) time: 2.9410 data: 0.0079 max mem: 33300 +Epoch: [2] [3350/4276] eta: 0:47:40 lr: 4.685717862562658e-05 loss: 0.2046 (0.2196) time: 2.9600 data: 0.0079 max mem: 33300 +Epoch: [2] [3360/4276] eta: 0:47:09 lr: 4.6854528607512216e-05 loss: 0.2034 (0.2196) time: 2.9451 data: 0.0080 max mem: 33300 +Epoch: [2] [3370/4276] eta: 0:46:38 lr: 4.685187857274431e-05 loss: 0.2232 (0.2197) time: 2.9254 data: 0.0080 max mem: 33300 +Epoch: [2] [3380/4276] eta: 0:46:06 lr: 4.684922852132173e-05 loss: 0.2202 (0.2196) time: 2.9294 data: 0.0077 max mem: 33300 +Epoch: [2] [3390/4276] eta: 0:45:35 lr: 4.6846578453243325e-05 loss: 0.2197 (0.2197) time: 2.9277 data: 0.0073 max mem: 33300 +Epoch: [2] [3400/4276] eta: 0:45:04 lr: 4.684392836850792e-05 loss: 0.2196 (0.2197) time: 2.9277 data: 0.0073 max mem: 33300 +Epoch: [2] [3410/4276] eta: 0:44:33 lr: 4.684127826711438e-05 loss: 0.2175 (0.2197) time: 2.9551 data: 0.0072 max mem: 33300 +Epoch: [2] [3420/4276] eta: 0:44:01 lr: 4.683862814906156e-05 loss: 0.2134 (0.2197) time: 2.9645 data: 0.0072 max mem: 33300 +Epoch: [2] [3430/4276] eta: 0:43:30 lr: 4.6835978014348294e-05 loss: 0.2280 (0.2197) time: 2.9174 data: 0.0079 max mem: 33300 +Epoch: [2] [3440/4276] eta: 0:42:59 lr: 4.683332786297343e-05 loss: 0.2235 (0.2197) time: 2.8819 data: 0.0085 max mem: 33300 +Epoch: [2] [3450/4276] eta: 0:42:27 lr: 4.683067769493582e-05 loss: 0.2046 (0.2197) time: 2.9044 data: 0.0081 max mem: 33300 +Epoch: [2] [3460/4276] eta: 0:41:56 lr: 4.682802751023431e-05 loss: 0.2157 (0.2197) time: 2.9136 data: 0.0081 max mem: 33300 +Epoch: [2] [3470/4276] eta: 0:41:25 lr: 4.682537730886776e-05 loss: 0.1994 (0.2197) time: 2.8905 data: 0.0083 max mem: 33300 +Epoch: [2] [3480/4276] eta: 0:40:54 lr: 4.682272709083501e-05 loss: 0.2125 (0.2197) time: 2.8728 data: 0.0082 max mem: 33300 +Epoch: [2] [3490/4276] eta: 0:40:22 lr: 4.682007685613489e-05 loss: 0.2253 (0.2197) time: 2.8950 data: 0.0082 max mem: 33300 +Epoch: [2] [3500/4276] eta: 0:39:51 lr: 4.6817426604766265e-05 loss: 0.2147 (0.2197) time: 2.9132 data: 0.0082 max mem: 33300 +Epoch: [2] [3510/4276] eta: 0:39:20 lr: 4.681477633672798e-05 loss: 0.2017 (0.2196) time: 2.9227 data: 0.0083 max mem: 33300 +Epoch: [2] [3520/4276] eta: 0:38:49 lr: 4.6812126052018865e-05 loss: 0.2068 (0.2196) time: 2.9391 data: 0.0082 max mem: 33300 +Epoch: [2] [3530/4276] eta: 0:38:18 lr: 4.680947575063779e-05 loss: 0.2143 (0.2196) time: 2.9490 data: 0.0079 max mem: 33300 +Epoch: [2] [3540/4276] eta: 0:37:47 lr: 4.68068254325836e-05 loss: 0.2106 (0.2196) time: 2.9648 data: 0.0075 max mem: 33300 +Epoch: [2] [3550/4276] eta: 0:37:16 lr: 4.680417509785512e-05 loss: 0.2311 (0.2196) time: 2.9657 data: 0.0072 max mem: 33300 +Epoch: [2] [3560/4276] eta: 0:36:45 lr: 4.6801524746451215e-05 loss: 0.2203 (0.2196) time: 2.9450 data: 0.0077 max mem: 33300 +Epoch: [2] [3570/4276] eta: 0:36:13 lr: 4.679887437837072e-05 loss: 0.2176 (0.2196) time: 2.9162 data: 0.0083 max mem: 33300 +Epoch: [2] [3580/4276] eta: 0:35:42 lr: 4.6796223993612494e-05 loss: 0.2008 (0.2196) time: 2.9079 data: 0.0084 max mem: 33300 +Epoch: [2] [3590/4276] eta: 0:35:11 lr: 4.679357359217536e-05 loss: 0.1949 (0.2196) time: 2.9215 data: 0.0087 max mem: 33300 +Epoch: [2] [3600/4276] eta: 0:34:40 lr: 4.6790923174058185e-05 loss: 0.2147 (0.2196) time: 2.9336 data: 0.0095 max mem: 33300 +Epoch: [2] [3610/4276] eta: 0:34:09 lr: 4.6788272739259806e-05 loss: 0.2286 (0.2196) time: 2.9423 data: 0.0095 max mem: 33300 +Epoch: [2] [3620/4276] eta: 0:33:38 lr: 4.6785622287779066e-05 loss: 0.2186 (0.2196) time: 2.9505 data: 0.0089 max mem: 33300 +Epoch: [2] [3630/4276] eta: 0:33:07 lr: 4.678297181961481e-05 loss: 0.2186 (0.2196) time: 2.9405 data: 0.0089 max mem: 33300 +Epoch: [2] [3640/4276] eta: 0:32:36 lr: 4.678032133476589e-05 loss: 0.2151 (0.2196) time: 2.9238 data: 0.0092 max mem: 33300 +Epoch: [2] [3650/4276] eta: 0:32:05 lr: 4.6777670833231144e-05 loss: 0.2112 (0.2196) time: 2.9377 data: 0.0090 max mem: 33300 +Epoch: [2] [3660/4276] eta: 0:31:34 lr: 4.677502031500941e-05 loss: 0.2008 (0.2196) time: 2.9576 data: 0.0081 max mem: 33300 +Epoch: [2] [3670/4276] eta: 0:31:03 lr: 4.6772369780099545e-05 loss: 0.2153 (0.2196) time: 2.9519 data: 0.0077 max mem: 33300 +Epoch: [2] [3680/4276] eta: 0:30:32 lr: 4.676971922850039e-05 loss: 0.2262 (0.2197) time: 2.9432 data: 0.0078 max mem: 33300 +Epoch: [2] [3690/4276] eta: 0:30:01 lr: 4.6767068660210785e-05 loss: 0.2164 (0.2197) time: 2.9418 data: 0.0083 max mem: 33300 +Epoch: [2] [3700/4276] eta: 0:29:30 lr: 4.676441807522958e-05 loss: 0.2149 (0.2197) time: 2.9591 data: 0.0081 max mem: 33300 +Epoch: [2] [3710/4276] eta: 0:28:59 lr: 4.676176747355561e-05 loss: 0.2111 (0.2196) time: 2.9714 data: 0.0076 max mem: 33300 +Epoch: [2] [3720/4276] eta: 0:28:29 lr: 4.675911685518773e-05 loss: 0.2041 (0.2196) time: 2.9715 data: 0.0078 max mem: 33300 +Epoch: [2] [3730/4276] eta: 0:27:58 lr: 4.675646622012477e-05 loss: 0.2089 (0.2196) time: 2.9621 data: 0.0078 max mem: 33300 +Epoch: [2] [3740/4276] eta: 0:27:27 lr: 4.6753815568365586e-05 loss: 0.2089 (0.2196) time: 2.9638 data: 0.0077 max mem: 33300 +Epoch: [2] [3750/4276] eta: 0:26:56 lr: 4.675116489990901e-05 loss: 0.2218 (0.2196) time: 2.9730 data: 0.0076 max mem: 33300 +Epoch: [2] [3760/4276] eta: 0:26:25 lr: 4.674851421475389e-05 loss: 0.2218 (0.2196) time: 2.9712 data: 0.0080 max mem: 33300 +Epoch: [2] [3770/4276] eta: 0:25:54 lr: 4.6745863512899064e-05 loss: 0.2295 (0.2196) time: 2.9713 data: 0.0082 max mem: 33300 +Epoch: [2] [3780/4276] eta: 0:25:23 lr: 4.674321279434339e-05 loss: 0.2158 (0.2196) time: 2.9709 data: 0.0081 max mem: 33300 +Epoch: [2] [3790/4276] eta: 0:24:52 lr: 4.674056205908569e-05 loss: 0.2045 (0.2196) time: 2.9733 data: 0.0080 max mem: 33300 +Epoch: [2] [3800/4276] eta: 0:24:22 lr: 4.673791130712482e-05 loss: 0.2101 (0.2196) time: 2.9734 data: 0.0082 max mem: 33300 +Epoch: [2] [3810/4276] eta: 0:23:51 lr: 4.673526053845962e-05 loss: 0.2101 (0.2196) time: 2.9501 data: 0.0084 max mem: 33300 +Epoch: [2] [3820/4276] eta: 0:23:20 lr: 4.673260975308893e-05 loss: 0.2053 (0.2196) time: 2.9249 data: 0.0084 max mem: 33300 +Epoch: [2] [3830/4276] eta: 0:22:49 lr: 4.672995895101159e-05 loss: 0.2059 (0.2196) time: 2.9250 data: 0.0081 max mem: 33300 +Epoch: [2] [3840/4276] eta: 0:22:18 lr: 4.672730813222644e-05 loss: 0.2071 (0.2196) time: 2.9436 data: 0.0084 max mem: 33300 +Epoch: [2] [3850/4276] eta: 0:21:47 lr: 4.672465729673233e-05 loss: 0.2063 (0.2195) time: 2.9595 data: 0.0084 max mem: 33300 +Epoch: [2] [3860/4276] eta: 0:21:17 lr: 4.6722006444528096e-05 loss: 0.2078 (0.2195) time: 2.9529 data: 0.0084 max mem: 33300 +Epoch: [2] [3870/4276] eta: 0:20:46 lr: 4.671935557561258e-05 loss: 0.2078 (0.2195) time: 2.9393 data: 0.0087 max mem: 33300 +Epoch: [2] [3880/4276] eta: 0:20:15 lr: 4.671670468998462e-05 loss: 0.2051 (0.2195) time: 2.9332 data: 0.0085 max mem: 33300 +Epoch: [2] [3890/4276] eta: 0:19:44 lr: 4.671405378764306e-05 loss: 0.2115 (0.2195) time: 2.9320 data: 0.0083 max mem: 33300 +Epoch: [2] [3900/4276] eta: 0:19:13 lr: 4.6711402868586744e-05 loss: 0.2213 (0.2195) time: 2.9365 data: 0.0083 max mem: 33300 +Epoch: [2] [3910/4276] eta: 0:18:42 lr: 4.670875193281451e-05 loss: 0.2098 (0.2195) time: 2.9387 data: 0.0086 max mem: 33300 +Epoch: [2] [3920/4276] eta: 0:18:12 lr: 4.670610098032519e-05 loss: 0.1902 (0.2194) time: 2.9408 data: 0.0086 max mem: 33300 +Epoch: [2] [3930/4276] eta: 0:17:41 lr: 4.670345001111765e-05 loss: 0.1902 (0.2194) time: 2.9381 data: 0.0084 max mem: 33300 +Epoch: [2] [3940/4276] eta: 0:17:10 lr: 4.670079902519069e-05 loss: 0.2076 (0.2194) time: 2.9316 data: 0.0084 max mem: 33300 +Epoch: [2] [3950/4276] eta: 0:16:39 lr: 4.669814802254318e-05 loss: 0.2065 (0.2193) time: 2.9378 data: 0.0082 max mem: 33300 +Epoch: [2] [3960/4276] eta: 0:16:08 lr: 4.669549700317396e-05 loss: 0.2162 (0.2194) time: 2.9496 data: 0.0083 max mem: 33300 +Epoch: [2] [3970/4276] eta: 0:15:38 lr: 4.669284596708185e-05 loss: 0.2314 (0.2194) time: 2.9495 data: 0.0084 max mem: 33300 +Epoch: [2] [3980/4276] eta: 0:15:07 lr: 4.6690194914265706e-05 loss: 0.2114 (0.2193) time: 2.9437 data: 0.0083 max mem: 33300 +Epoch: [2] [3990/4276] eta: 0:14:36 lr: 4.668754384472436e-05 loss: 0.2114 (0.2193) time: 2.9411 data: 0.0087 max mem: 33300 +Epoch: [2] [4000/4276] eta: 0:14:05 lr: 4.668489275845666e-05 loss: 0.2017 (0.2193) time: 2.9274 data: 0.0089 max mem: 33300 +Epoch: [2] [4010/4276] eta: 0:13:35 lr: 4.668224165546144e-05 loss: 0.1947 (0.2193) time: 2.9227 data: 0.0091 max mem: 33300 +Epoch: [2] [4020/4276] eta: 0:13:04 lr: 4.667959053573753e-05 loss: 0.1947 (0.2193) time: 2.9276 data: 0.0092 max mem: 33300 +Epoch: [2] [4030/4276] eta: 0:12:33 lr: 4.667693939928378e-05 loss: 0.1947 (0.2193) time: 2.9595 data: 0.0083 max mem: 33300 +Epoch: [2] [4040/4276] eta: 0:12:03 lr: 4.667428824609903e-05 loss: 0.2100 (0.2193) time: 2.9789 data: 0.0078 max mem: 33300 +Epoch: [2] [4050/4276] eta: 0:11:32 lr: 4.6671637076182106e-05 loss: 0.1979 (0.2192) time: 2.9519 data: 0.0083 max mem: 33300 +Epoch: [2] [4060/4276] eta: 0:11:01 lr: 4.666898588953186e-05 loss: 0.1896 (0.2192) time: 2.9319 data: 0.0085 max mem: 33300 +Epoch: [2] [4070/4276] eta: 0:10:30 lr: 4.666633468614712e-05 loss: 0.2158 (0.2192) time: 2.9315 data: 0.0086 max mem: 33300 +Epoch: [2] [4080/4276] eta: 0:10:00 lr: 4.666368346602673e-05 loss: 0.2047 (0.2192) time: 2.9299 data: 0.0086 max mem: 33300 +Epoch: [2] [4090/4276] eta: 0:09:29 lr: 4.666103222916953e-05 loss: 0.2132 (0.2192) time: 2.9334 data: 0.0083 max mem: 33300 +Epoch: [2] [4100/4276] eta: 0:08:58 lr: 4.665838097557434e-05 loss: 0.2145 (0.2192) time: 2.9405 data: 0.0088 max mem: 33300 +Epoch: [2] [4110/4276] eta: 0:08:28 lr: 4.665572970524002e-05 loss: 0.2184 (0.2192) time: 2.9579 data: 0.0090 max mem: 33300 +Epoch: [2] [4120/4276] eta: 0:07:57 lr: 4.665307841816541e-05 loss: 0.2184 (0.2192) time: 2.9514 data: 0.0093 max mem: 33300 +Epoch: [2] [4130/4276] eta: 0:07:26 lr: 4.665042711434932e-05 loss: 0.2132 (0.2192) time: 2.9368 data: 0.0098 max mem: 33300 +Epoch: [2] [4140/4276] eta: 0:06:56 lr: 4.664777579379061e-05 loss: 0.2137 (0.2191) time: 2.9443 data: 0.0097 max mem: 33300 +Epoch: [2] [4150/4276] eta: 0:06:25 lr: 4.66451244564881e-05 loss: 0.2058 (0.2191) time: 2.9465 data: 0.0087 max mem: 33300 +Epoch: [2] [4160/4276] eta: 0:05:55 lr: 4.664247310244065e-05 loss: 0.2063 (0.2191) time: 2.9308 data: 0.0086 max mem: 33300 +Epoch: [2] [4170/4276] eta: 0:05:24 lr: 4.6639821731647074e-05 loss: 0.2176 (0.2191) time: 2.8977 data: 0.0093 max mem: 33300 +Epoch: [2] [4180/4276] eta: 0:04:53 lr: 4.6637170344106226e-05 loss: 0.2147 (0.2191) time: 2.8810 data: 0.0085 max mem: 33300 +Epoch: [2] [4190/4276] eta: 0:04:23 lr: 4.663451893981693e-05 loss: 0.2045 (0.2191) time: 2.8922 data: 0.0085 max mem: 33300 +Epoch: [2] [4200/4276] eta: 0:03:52 lr: 4.663186751877803e-05 loss: 0.2045 (0.2191) time: 2.9131 data: 0.0088 max mem: 33300 +Epoch: [2] [4210/4276] eta: 0:03:21 lr: 4.6629216080988345e-05 loss: 0.2142 (0.2192) time: 2.9304 data: 0.0088 max mem: 33300 +Epoch: [2] [4220/4276] eta: 0:02:51 lr: 4.6626564626446737e-05 loss: 0.2227 (0.2192) time: 2.9523 data: 0.0093 max mem: 33300 +Epoch: [2] [4230/4276] eta: 0:02:20 lr: 4.662391315515202e-05 loss: 0.2446 (0.2193) time: 2.9579 data: 0.0090 max mem: 33300 +Epoch: [2] [4240/4276] eta: 0:01:50 lr: 4.662126166710305e-05 loss: 0.2403 (0.2193) time: 2.9558 data: 0.0091 max mem: 33300 +Epoch: [2] [4250/4276] eta: 0:01:19 lr: 4.661861016229864e-05 loss: 0.2156 (0.2193) time: 2.9236 data: 0.0092 max mem: 33300 +Epoch: [2] [4260/4276] eta: 0:00:48 lr: 4.661595864073764e-05 loss: 0.2285 (0.2193) time: 2.9316 data: 0.0089 max mem: 33300 +Epoch: [2] [4270/4276] eta: 0:00:18 lr: 4.661330710241888e-05 loss: 0.2214 (0.2193) time: 2.9502 data: 0.0081 max mem: 33300 +Epoch: [2] Total time: 3:37:51 +Test: [ 0/21770] eta: 13:04:05 time: 2.1610 data: 2.1218 max mem: 33300 +Test: [ 100/21770] eta: 0:21:13 time: 0.0383 data: 0.0008 max mem: 33300 +Test: [ 200/21770] eta: 0:17:29 time: 0.0387 data: 0.0008 max mem: 33300 +Test: [ 300/21770] eta: 0:16:12 time: 0.0383 data: 0.0008 max mem: 33300 +Test: [ 400/21770] eta: 0:15:26 time: 0.0374 data: 0.0009 max mem: 33300 +Test: [ 500/21770] eta: 0:14:56 time: 0.0374 data: 0.0009 max mem: 33300 +Test: [ 600/21770] eta: 0:14:36 time: 0.0375 data: 0.0009 max mem: 33300 +Test: [ 700/21770] eta: 0:14:20 time: 0.0374 data: 0.0009 max mem: 33300 +Test: [ 800/21770] eta: 0:14:09 time: 0.0390 data: 0.0009 max mem: 33300 +Test: [ 900/21770] eta: 0:14:02 time: 0.0396 data: 0.0009 max mem: 33300 +Test: [ 1000/21770] eta: 0:13:55 time: 0.0378 data: 0.0009 max mem: 33300 +Test: [ 1100/21770] eta: 0:13:46 time: 0.0377 data: 0.0010 max mem: 33300 +Test: [ 1200/21770] eta: 0:13:39 time: 0.0384 data: 0.0010 max mem: 33300 +Test: [ 1300/21770] eta: 0:13:33 time: 0.0388 data: 0.0009 max mem: 33300 +Test: [ 1400/21770] eta: 0:13:28 time: 0.0387 data: 0.0010 max mem: 33300 +Test: [ 1500/21770] eta: 0:13:23 time: 0.0389 data: 0.0009 max mem: 33300 +Test: [ 1600/21770] eta: 0:13:18 time: 0.0387 data: 0.0009 max mem: 33300 +Test: [ 1700/21770] eta: 0:13:13 time: 0.0387 data: 0.0009 max mem: 33300 +Test: [ 1800/21770] eta: 0:13:08 time: 0.0386 data: 0.0009 max mem: 33300 +Test: [ 1900/21770] eta: 0:13:03 time: 0.0390 data: 0.0009 max mem: 33300 +Test: [ 2000/21770] eta: 0:12:59 time: 0.0387 data: 0.0009 max mem: 33300 +Test: [ 2100/21770] eta: 0:12:54 time: 0.0392 data: 0.0009 max mem: 33300 +Test: [ 2200/21770] eta: 0:12:50 time: 0.0392 data: 0.0009 max mem: 33300 +Test: [ 2300/21770] eta: 0:12:46 time: 0.0391 data: 0.0009 max mem: 33300 +Test: [ 2400/21770] eta: 0:12:42 time: 0.0394 data: 0.0009 max mem: 33300 +Test: [ 2500/21770] eta: 0:12:38 time: 0.0397 data: 0.0009 max mem: 33300 +Test: [ 2600/21770] eta: 0:12:35 time: 0.0400 data: 0.0009 max mem: 33300 +Test: [ 2700/21770] eta: 0:12:31 time: 0.0399 data: 0.0009 max mem: 33300 +Test: [ 2800/21770] eta: 0:12:28 time: 0.0400 data: 0.0009 max mem: 33300 +Test: [ 2900/21770] eta: 0:12:24 time: 0.0400 data: 0.0009 max mem: 33300 +Test: [ 3000/21770] eta: 0:12:20 time: 0.0400 data: 0.0008 max mem: 33300 +Test: [ 3100/21770] eta: 0:12:17 time: 0.0398 data: 0.0009 max mem: 33300 +Test: [ 3200/21770] eta: 0:12:13 time: 0.0400 data: 0.0008 max mem: 33300 +Test: [ 3300/21770] eta: 0:12:09 time: 0.0401 data: 0.0008 max mem: 33300 +Test: [ 3400/21770] eta: 0:12:06 time: 0.0400 data: 0.0008 max mem: 33300 +Test: [ 3500/21770] eta: 0:12:02 time: 0.0401 data: 0.0008 max mem: 33300 +Test: [ 3600/21770] eta: 0:11:58 time: 0.0400 data: 0.0009 max mem: 33300 +Test: [ 3700/21770] eta: 0:11:54 time: 0.0400 data: 0.0009 max mem: 33300 +Test: [ 3800/21770] eta: 0:11:51 time: 0.0401 data: 0.0008 max mem: 33300 +Test: [ 3900/21770] eta: 0:11:47 time: 0.0400 data: 0.0008 max mem: 33300 +Test: [ 4000/21770] eta: 0:11:43 time: 0.0400 data: 0.0008 max mem: 33300 +Test: [ 4100/21770] eta: 0:11:39 time: 0.0402 data: 0.0009 max mem: 33300 +Test: [ 4200/21770] eta: 0:11:36 time: 0.0394 data: 0.0008 max mem: 33300 +Test: [ 4300/21770] eta: 0:11:32 time: 0.0400 data: 0.0008 max mem: 33300 +Test: [ 4400/21770] eta: 0:11:28 time: 0.0378 data: 0.0009 max mem: 33300 +Test: [ 4500/21770] eta: 0:11:23 time: 0.0379 data: 0.0009 max mem: 33300 +Test: [ 4600/21770] eta: 0:11:19 time: 0.0385 data: 0.0008 max mem: 33300 +Test: [ 4700/21770] eta: 0:11:14 time: 0.0385 data: 0.0009 max mem: 33300 +Test: [ 4800/21770] eta: 0:11:10 time: 0.0385 data: 0.0008 max mem: 33300 +Test: [ 4900/21770] eta: 0:11:06 time: 0.0384 data: 0.0008 max mem: 33300 +Test: [ 5000/21770] eta: 0:11:01 time: 0.0385 data: 0.0008 max mem: 33300 +Test: [ 5100/21770] eta: 0:10:57 time: 0.0385 data: 0.0008 max mem: 33300 +Test: [ 5200/21770] eta: 0:10:53 time: 0.0385 data: 0.0008 max mem: 33300 +Test: [ 5300/21770] eta: 0:10:49 time: 0.0385 data: 0.0008 max mem: 33300 +Test: [ 5400/21770] eta: 0:10:44 time: 0.0385 data: 0.0009 max mem: 33300 +Test: [ 5500/21770] eta: 0:10:40 time: 0.0385 data: 0.0008 max mem: 33300 +Test: [ 5600/21770] eta: 0:10:36 time: 0.0384 data: 0.0008 max mem: 33300 +Test: [ 5700/21770] eta: 0:10:32 time: 0.0385 data: 0.0009 max mem: 33300 +Test: [ 5800/21770] eta: 0:10:27 time: 0.0379 data: 0.0009 max mem: 33300 +Test: [ 5900/21770] eta: 0:10:23 time: 0.0379 data: 0.0008 max mem: 33300 +Test: [ 6000/21770] eta: 0:10:19 time: 0.0377 data: 0.0008 max mem: 33300 +Test: [ 6100/21770] eta: 0:10:14 time: 0.0379 data: 0.0009 max mem: 33300 +Test: [ 6200/21770] eta: 0:10:10 time: 0.0379 data: 0.0009 max mem: 33300 +Test: [ 6300/21770] eta: 0:10:06 time: 0.0378 data: 0.0009 max mem: 33300 +Test: [ 6400/21770] eta: 0:10:02 time: 0.0379 data: 0.0008 max mem: 33300 +Test: [ 6500/21770] eta: 0:09:57 time: 0.0379 data: 0.0009 max mem: 33300 +Test: [ 6600/21770] eta: 0:09:53 time: 0.0378 data: 0.0009 max mem: 33300 +Test: [ 6700/21770] eta: 0:09:49 time: 0.0378 data: 0.0009 max mem: 33300 +Test: [ 6800/21770] eta: 0:09:45 time: 0.0379 data: 0.0009 max mem: 33300 +Test: [ 6900/21770] eta: 0:09:41 time: 0.0378 data: 0.0008 max mem: 33300 +Test: [ 7000/21770] eta: 0:09:36 time: 0.0379 data: 0.0009 max mem: 33300 +Test: [ 7100/21770] eta: 0:09:32 time: 0.0378 data: 0.0009 max mem: 33300 +Test: [ 7200/21770] eta: 0:09:28 time: 0.0379 data: 0.0008 max mem: 33300 +Test: [ 7300/21770] eta: 0:09:24 time: 0.0378 data: 0.0009 max mem: 33300 +Test: [ 7400/21770] eta: 0:09:20 time: 0.0381 data: 0.0008 max mem: 33300 +Test: [ 7500/21770] eta: 0:09:16 time: 0.0384 data: 0.0008 max mem: 33300 +Test: [ 7600/21770] eta: 0:09:12 time: 0.0382 data: 0.0008 max mem: 33300 +Test: [ 7700/21770] eta: 0:09:08 time: 0.0382 data: 0.0008 max mem: 33300 +Test: [ 7800/21770] eta: 0:09:04 time: 0.0381 data: 0.0008 max mem: 33300 +Test: [ 7900/21770] eta: 0:09:00 time: 0.0384 data: 0.0008 max mem: 33300 +Test: [ 8000/21770] eta: 0:08:56 time: 0.0382 data: 0.0008 max mem: 33300 +Test: [ 8100/21770] eta: 0:08:52 time: 0.0383 data: 0.0008 max mem: 33300 +Test: [ 8200/21770] eta: 0:08:48 time: 0.0381 data: 0.0008 max mem: 33300 +Test: [ 8300/21770] eta: 0:08:44 time: 0.0384 data: 0.0008 max mem: 33300 +Test: [ 8400/21770] eta: 0:08:40 time: 0.0382 data: 0.0008 max mem: 33300 +Test: [ 8500/21770] eta: 0:08:36 time: 0.0383 data: 0.0008 max mem: 33300 +Test: [ 8600/21770] eta: 0:08:32 time: 0.0381 data: 0.0008 max mem: 33300 +Test: [ 8700/21770] eta: 0:08:28 time: 0.0383 data: 0.0008 max mem: 33300 +Test: [ 8800/21770] eta: 0:08:24 time: 0.0382 data: 0.0008 max mem: 33300 +Test: [ 8900/21770] eta: 0:08:20 time: 0.0382 data: 0.0009 max mem: 33300 +Test: [ 9000/21770] eta: 0:08:16 time: 0.0378 data: 0.0008 max mem: 33300 +Test: [ 9100/21770] eta: 0:08:12 time: 0.0379 data: 0.0008 max mem: 33300 +Test: [ 9200/21770] eta: 0:08:08 time: 0.0379 data: 0.0009 max mem: 33300 +Test: [ 9300/21770] eta: 0:08:04 time: 0.0378 data: 0.0009 max mem: 33300 +Test: [ 9400/21770] eta: 0:08:00 time: 0.0378 data: 0.0009 max mem: 33300 +Test: [ 9500/21770] eta: 0:07:56 time: 0.0379 data: 0.0008 max mem: 33300 +Test: [ 9600/21770] eta: 0:07:52 time: 0.0378 data: 0.0008 max mem: 33300 +Test: [ 9700/21770] eta: 0:07:48 time: 0.0378 data: 0.0008 max mem: 33300 +Test: [ 9800/21770] eta: 0:07:44 time: 0.0379 data: 0.0009 max mem: 33300 +Test: [ 9900/21770] eta: 0:07:40 time: 0.0378 data: 0.0009 max mem: 33300 +Test: [10000/21770] eta: 0:07:36 time: 0.0378 data: 0.0008 max mem: 33300 +Test: [10100/21770] eta: 0:07:32 time: 0.0379 data: 0.0009 max mem: 33300 +Test: [10200/21770] eta: 0:07:28 time: 0.0378 data: 0.0009 max mem: 33300 +Test: [10300/21770] eta: 0:07:24 time: 0.0379 data: 0.0009 max mem: 33300 +Test: [10400/21770] eta: 0:07:20 time: 0.0379 data: 0.0008 max mem: 33300 +Test: [10500/21770] eta: 0:07:16 time: 0.0378 data: 0.0009 max mem: 33300 +Test: [10600/21770] eta: 0:07:12 time: 0.0379 data: 0.0009 max mem: 33300 +Test: [10700/21770] eta: 0:07:08 time: 0.0379 data: 0.0009 max mem: 33300 +Test: [10800/21770] eta: 0:07:04 time: 0.0378 data: 0.0008 max mem: 33300 +Test: [10900/21770] eta: 0:07:00 time: 0.0379 data: 0.0009 max mem: 33300 +Test: [11000/21770] eta: 0:06:56 time: 0.0378 data: 0.0009 max mem: 33300 +Test: [11100/21770] eta: 0:06:52 time: 0.0379 data: 0.0009 max mem: 33300 +Test: [11200/21770] eta: 0:06:48 time: 0.0379 data: 0.0008 max mem: 33300 +Test: [11300/21770] eta: 0:06:44 time: 0.0378 data: 0.0008 max mem: 33300 +Test: [11400/21770] eta: 0:06:40 time: 0.0378 data: 0.0008 max mem: 33300 +Test: [11500/21770] eta: 0:06:36 time: 0.0379 data: 0.0009 max mem: 33300 +Test: [11600/21770] eta: 0:06:32 time: 0.0379 data: 0.0009 max mem: 33300 +Test: [11700/21770] eta: 0:06:29 time: 0.0378 data: 0.0008 max mem: 33300 +Test: [11800/21770] eta: 0:06:25 time: 0.0378 data: 0.0008 max mem: 33300 +Test: [11900/21770] eta: 0:06:21 time: 0.0378 data: 0.0009 max mem: 33300 +Test: [12000/21770] eta: 0:06:17 time: 0.0378 data: 0.0008 max mem: 33300 +Test: [12100/21770] eta: 0:06:13 time: 0.0378 data: 0.0008 max mem: 33300 +Test: [12200/21770] eta: 0:06:09 time: 0.0378 data: 0.0008 max mem: 33300 +Test: [12300/21770] eta: 0:06:05 time: 0.0378 data: 0.0008 max mem: 33300 +Test: [12400/21770] eta: 0:06:01 time: 0.0378 data: 0.0009 max mem: 33300 +Test: [12500/21770] eta: 0:05:57 time: 0.0379 data: 0.0008 max mem: 33300 +Test: [12600/21770] eta: 0:05:53 time: 0.0378 data: 0.0008 max mem: 33300 +Test: [12700/21770] eta: 0:05:49 time: 0.0379 data: 0.0009 max mem: 33300 +Test: [12800/21770] eta: 0:05:45 time: 0.0379 data: 0.0008 max mem: 33300 +Test: [12900/21770] eta: 0:05:42 time: 0.0379 data: 0.0008 max mem: 33300 +Test: [13000/21770] eta: 0:05:38 time: 0.0379 data: 0.0009 max mem: 33300 +Test: [13100/21770] eta: 0:05:34 time: 0.0378 data: 0.0008 max mem: 33300 +Test: [13200/21770] eta: 0:05:30 time: 0.0378 data: 0.0009 max mem: 33300 +Test: [13300/21770] eta: 0:05:26 time: 0.0379 data: 0.0009 max mem: 33300 +Test: [13400/21770] eta: 0:05:22 time: 0.0379 data: 0.0009 max mem: 33300 +Test: [13500/21770] eta: 0:05:18 time: 0.0378 data: 0.0008 max mem: 33300 +Test: [13600/21770] eta: 0:05:14 time: 0.0379 data: 0.0009 max mem: 33300 +Test: [13700/21770] eta: 0:05:10 time: 0.0379 data: 0.0009 max mem: 33300 +Test: [13800/21770] eta: 0:05:06 time: 0.0383 data: 0.0009 max mem: 33300 +Test: [13900/21770] eta: 0:05:03 time: 0.0379 data: 0.0009 max mem: 33300 +Test: [14000/21770] eta: 0:04:59 time: 0.0378 data: 0.0009 max mem: 33300 +Test: [14100/21770] eta: 0:04:55 time: 0.0381 data: 0.0009 max mem: 33300 +Test: [14200/21770] eta: 0:04:51 time: 0.0383 data: 0.0008 max mem: 33300 +Test: [14300/21770] eta: 0:04:47 time: 0.0381 data: 0.0009 max mem: 33300 +Test: [14400/21770] eta: 0:04:43 time: 0.0382 data: 0.0008 max mem: 33300 +Test: [14500/21770] eta: 0:04:39 time: 0.0382 data: 0.0009 max mem: 33300 +Test: [14600/21770] eta: 0:04:35 time: 0.0383 data: 0.0008 max mem: 33300 +Test: [14700/21770] eta: 0:04:32 time: 0.0382 data: 0.0009 max mem: 33300 +Test: [14800/21770] eta: 0:04:28 time: 0.0383 data: 0.0008 max mem: 33300 +Test: [14900/21770] eta: 0:04:24 time: 0.0382 data: 0.0009 max mem: 33300 +Test: [15000/21770] eta: 0:04:20 time: 0.0382 data: 0.0008 max mem: 33300 +Test: [15100/21770] eta: 0:04:16 time: 0.0382 data: 0.0008 max mem: 33300 +Test: [15200/21770] eta: 0:04:12 time: 0.0383 data: 0.0008 max mem: 33300 +Test: [15300/21770] eta: 0:04:08 time: 0.0381 data: 0.0008 max mem: 33300 +Test: [15400/21770] eta: 0:04:05 time: 0.0378 data: 0.0009 max mem: 33300 +Test: [15500/21770] eta: 0:04:01 time: 0.0379 data: 0.0009 max mem: 33300 +Test: [15600/21770] eta: 0:03:57 time: 0.0379 data: 0.0009 max mem: 33300 +Test: [15700/21770] eta: 0:03:53 time: 0.0378 data: 0.0009 max mem: 33300 +Test: [15800/21770] eta: 0:03:49 time: 0.0379 data: 0.0009 max mem: 33300 +Test: [15900/21770] eta: 0:03:45 time: 0.0378 data: 0.0009 max mem: 33300 +Test: [16000/21770] eta: 0:03:41 time: 0.0383 data: 0.0009 max mem: 33300 +Test: [16100/21770] eta: 0:03:38 time: 0.0401 data: 0.0008 max mem: 33300 +Test: [16200/21770] eta: 0:03:34 time: 0.0399 data: 0.0008 max mem: 33300 +Test: [16300/21770] eta: 0:03:30 time: 0.0401 data: 0.0008 max mem: 33300 +Test: [16400/21770] eta: 0:03:26 time: 0.0400 data: 0.0008 max mem: 33300 +Test: [16500/21770] eta: 0:03:22 time: 0.0401 data: 0.0008 max mem: 33300 +Test: [16600/21770] eta: 0:03:19 time: 0.0398 data: 0.0008 max mem: 33300 +Test: [16700/21770] eta: 0:03:15 time: 0.0400 data: 0.0008 max mem: 33300 +Test: [16800/21770] eta: 0:03:11 time: 0.0399 data: 0.0008 max mem: 33300 +Test: [16900/21770] eta: 0:03:07 time: 0.0399 data: 0.0008 max mem: 33300 +Test: [17000/21770] eta: 0:03:03 time: 0.0378 data: 0.0008 max mem: 33300 +Test: [17100/21770] eta: 0:02:59 time: 0.0378 data: 0.0009 max mem: 33300 +Test: [17200/21770] eta: 0:02:56 time: 0.0379 data: 0.0008 max mem: 33300 +Test: [17300/21770] eta: 0:02:52 time: 0.0378 data: 0.0008 max mem: 33300 +Test: [17400/21770] eta: 0:02:48 time: 0.0378 data: 0.0008 max mem: 33300 +Test: [17500/21770] eta: 0:02:44 time: 0.0379 data: 0.0008 max mem: 33300 +Test: [17600/21770] eta: 0:02:40 time: 0.0379 data: 0.0008 max mem: 33300 +Test: [17700/21770] eta: 0:02:36 time: 0.0378 data: 0.0008 max mem: 33300 +Test: [17800/21770] eta: 0:02:32 time: 0.0378 data: 0.0008 max mem: 33300 +Test: [17900/21770] eta: 0:02:29 time: 0.0378 data: 0.0008 max mem: 33300 +Test: [18000/21770] eta: 0:02:25 time: 0.0378 data: 0.0008 max mem: 33300 +Test: [18100/21770] eta: 0:02:21 time: 0.0378 data: 0.0008 max mem: 33300 +Test: [18200/21770] eta: 0:02:17 time: 0.0378 data: 0.0009 max mem: 33300 +Test: [18300/21770] eta: 0:02:13 time: 0.0378 data: 0.0008 max mem: 33300 +Test: [18400/21770] eta: 0:02:09 time: 0.0378 data: 0.0008 max mem: 33300 +Test: [18500/21770] eta: 0:02:05 time: 0.0378 data: 0.0008 max mem: 33300 +Test: [18600/21770] eta: 0:02:01 time: 0.0385 data: 0.0009 max mem: 33300 +Test: [18700/21770] eta: 0:01:58 time: 0.0378 data: 0.0008 max mem: 33300 +Test: [18800/21770] eta: 0:01:54 time: 0.0378 data: 0.0008 max mem: 33300 +Test: [18900/21770] eta: 0:01:50 time: 0.0378 data: 0.0008 max mem: 33300 +Test: [19000/21770] eta: 0:01:46 time: 0.0379 data: 0.0008 max mem: 33300 +Test: [19100/21770] eta: 0:01:42 time: 0.0378 data: 0.0008 max mem: 33300 +Test: [19200/21770] eta: 0:01:38 time: 0.0378 data: 0.0008 max mem: 33300 +Test: [19300/21770] eta: 0:01:34 time: 0.0378 data: 0.0008 max mem: 33300 +Test: [19400/21770] eta: 0:01:31 time: 0.0379 data: 0.0008 max mem: 33300 +Test: [19500/21770] eta: 0:01:27 time: 0.0383 data: 0.0008 max mem: 33300 +Test: [19600/21770] eta: 0:01:23 time: 0.0382 data: 0.0008 max mem: 33300 +Test: [19700/21770] eta: 0:01:19 time: 0.0382 data: 0.0008 max mem: 33300 +Test: [19800/21770] eta: 0:01:15 time: 0.0380 data: 0.0008 max mem: 33300 +Test: [19900/21770] eta: 0:01:11 time: 0.0382 data: 0.0008 max mem: 33300 +Test: [20000/21770] eta: 0:01:08 time: 0.0381 data: 0.0008 max mem: 33300 +Test: [20100/21770] eta: 0:01:04 time: 0.0382 data: 0.0008 max mem: 33300 +Test: [20200/21770] eta: 0:01:00 time: 0.0384 data: 0.0009 max mem: 33300 +Test: [20300/21770] eta: 0:00:56 time: 0.0378 data: 0.0008 max mem: 33300 +Test: [20400/21770] eta: 0:00:52 time: 0.0382 data: 0.0008 max mem: 33300 +Test: [20500/21770] eta: 0:00:48 time: 0.0381 data: 0.0008 max mem: 33300 +Test: [20600/21770] eta: 0:00:44 time: 0.0378 data: 0.0008 max mem: 33300 +Test: [20700/21770] eta: 0:00:41 time: 0.0379 data: 0.0008 max mem: 33300 +Test: [20800/21770] eta: 0:00:37 time: 0.0378 data: 0.0008 max mem: 33300 +Test: [20900/21770] eta: 0:00:33 time: 0.0381 data: 0.0008 max mem: 33300 +Test: [21000/21770] eta: 0:00:29 time: 0.0379 data: 0.0008 max mem: 33300 +Test: [21100/21770] eta: 0:00:25 time: 0.0379 data: 0.0009 max mem: 33300 +Test: [21200/21770] eta: 0:00:21 time: 0.0379 data: 0.0009 max mem: 33300 +Test: [21300/21770] eta: 0:00:18 time: 0.0378 data: 0.0008 max mem: 33300 +Test: [21400/21770] eta: 0:00:14 time: 0.0378 data: 0.0008 max mem: 33300 +Test: [21500/21770] eta: 0:00:10 time: 0.0379 data: 0.0009 max mem: 33300 +Test: [21600/21770] eta: 0:00:06 time: 0.0379 data: 0.0009 max mem: 33300 +Test: [21700/21770] eta: 0:00:02 time: 0.0379 data: 0.0009 max mem: 33300 +Test: Total time: 0:13:56 +Final results: +Mean IoU is 0.00 + + precision@0.5 = 0.00 + precision@0.6 = 0.00 + precision@0.7 = 0.00 + precision@0.8 = 0.00 + precision@0.9 = 0.00 + overall IoU = 0.00 + mean IoU = 0.00 + +Mean accuracy for one-to-zero sample is 100.00 + +Average object IoU 0.0 +Overall IoU 0.0 +Epoch: [3] [ 0/4276] eta: 6:29:51 lr: 4.661171617138342e-05 loss: 0.1767 (0.1767) time: 5.4704 data: 2.4459 max mem: 33300 +Epoch: [3] [ 10/4276] eta: 3:43:19 lr: 4.660906460624983e-05 loss: 0.1969 (0.2049) time: 3.1410 data: 0.2285 max mem: 33300 +Epoch: [3] [ 20/4276] eta: 3:36:36 lr: 4.660641302435543e-05 loss: 0.1960 (0.2046) time: 2.9329 data: 0.0072 max mem: 33300 +Epoch: [3] [ 30/4276] eta: 3:33:20 lr: 4.66037614256991e-05 loss: 0.1896 (0.2064) time: 2.9453 data: 0.0077 max mem: 33300 +Epoch: [3] [ 40/4276] eta: 3:30:55 lr: 4.6601109810279633e-05 loss: 0.1900 (0.2044) time: 2.9183 data: 0.0074 max mem: 33300 +Epoch: [3] [ 50/4276] eta: 3:29:43 lr: 4.65984581780959e-05 loss: 0.1900 (0.2031) time: 2.9199 data: 0.0075 max mem: 33300 +Epoch: [3] [ 60/4276] eta: 3:28:34 lr: 4.6595806529146695e-05 loss: 0.1927 (0.2055) time: 2.9289 data: 0.0078 max mem: 33300 +Epoch: [3] [ 70/4276] eta: 3:27:33 lr: 4.6593154863430875e-05 loss: 0.1927 (0.2054) time: 2.9183 data: 0.0075 max mem: 33300 +Epoch: [3] [ 80/4276] eta: 3:26:31 lr: 4.659050318094728e-05 loss: 0.2069 (0.2065) time: 2.9065 data: 0.0073 max mem: 33300 +Epoch: [3] [ 90/4276] eta: 3:25:38 lr: 4.6587851481694736e-05 loss: 0.1944 (0.2042) time: 2.9007 data: 0.0073 max mem: 33300 +Epoch: [3] [ 100/4276] eta: 3:24:57 lr: 4.6585199765672065e-05 loss: 0.1792 (0.2071) time: 2.9108 data: 0.0072 max mem: 33300 +Epoch: [3] [ 110/4276] eta: 3:24:17 lr: 4.658254803287812e-05 loss: 0.1961 (0.2075) time: 2.9173 data: 0.0074 max mem: 33300 +Epoch: [3] [ 120/4276] eta: 3:23:28 lr: 4.6579896283311725e-05 loss: 0.2026 (0.2079) time: 2.9020 data: 0.0077 max mem: 33300 +Epoch: [3] [ 130/4276] eta: 3:22:38 lr: 4.6577244516971705e-05 loss: 0.2084 (0.2091) time: 2.8795 data: 0.0085 max mem: 33300 +Epoch: [3] [ 140/4276] eta: 3:21:51 lr: 4.65745927338569e-05 loss: 0.2085 (0.2090) time: 2.8723 data: 0.0091 max mem: 33300 +Epoch: [3] [ 150/4276] eta: 3:21:08 lr: 4.6571940933966144e-05 loss: 0.1969 (0.2080) time: 2.8748 data: 0.0090 max mem: 33300 +Epoch: [3] [ 160/4276] eta: 3:20:24 lr: 4.656928911729828e-05 loss: 0.1980 (0.2084) time: 2.8721 data: 0.0090 max mem: 33300 +Epoch: [3] [ 170/4276] eta: 3:19:52 lr: 4.656663728385212e-05 loss: 0.2070 (0.2087) time: 2.8882 data: 0.0095 max mem: 33300 +Epoch: [3] [ 180/4276] eta: 3:19:17 lr: 4.65639854336265e-05 loss: 0.2120 (0.2101) time: 2.9029 data: 0.0093 max mem: 33300 +Epoch: [3] [ 190/4276] eta: 3:18:40 lr: 4.6561333566620265e-05 loss: 0.2279 (0.2110) time: 2.8898 data: 0.0087 max mem: 33300 +Epoch: [3] [ 200/4276] eta: 3:18:03 lr: 4.6558681682832236e-05 loss: 0.2242 (0.2121) time: 2.8791 data: 0.0086 max mem: 33300 +Epoch: [3] [ 210/4276] eta: 3:17:23 lr: 4.655602978226125e-05 loss: 0.2121 (0.2121) time: 2.8699 data: 0.0086 max mem: 33300 +Epoch: [3] [ 220/4276] eta: 3:16:45 lr: 4.655337786490613e-05 loss: 0.2054 (0.2118) time: 2.8624 data: 0.0086 max mem: 33300 +Epoch: [3] [ 230/4276] eta: 3:16:14 lr: 4.655072593076572e-05 loss: 0.2024 (0.2107) time: 2.8824 data: 0.0085 max mem: 33300 +Epoch: [3] [ 240/4276] eta: 3:15:46 lr: 4.6548073979838845e-05 loss: 0.2052 (0.2111) time: 2.9087 data: 0.0087 max mem: 33300 +Epoch: [3] [ 250/4276] eta: 3:15:21 lr: 4.654542201212433e-05 loss: 0.2202 (0.2120) time: 2.9250 data: 0.0090 max mem: 33300 +Epoch: [3] [ 260/4276] eta: 3:14:52 lr: 4.654277002762102e-05 loss: 0.2242 (0.2131) time: 2.9250 data: 0.0087 max mem: 33300 +Epoch: [3] [ 270/4276] eta: 3:14:22 lr: 4.654011802632774e-05 loss: 0.2494 (0.2135) time: 2.9097 data: 0.0078 max mem: 33300 +Epoch: [3] [ 280/4276] eta: 3:13:51 lr: 4.653746600824331e-05 loss: 0.2091 (0.2134) time: 2.9022 data: 0.0074 max mem: 33300 +Epoch: [3] [ 290/4276] eta: 3:13:23 lr: 4.653481397336657e-05 loss: 0.2033 (0.2127) time: 2.9063 data: 0.0077 max mem: 33300 +Epoch: [3] [ 300/4276] eta: 3:12:54 lr: 4.653216192169635e-05 loss: 0.1951 (0.2123) time: 2.9151 data: 0.0074 max mem: 33300 +Epoch: [3] [ 310/4276] eta: 3:12:28 lr: 4.652950985323148e-05 loss: 0.2003 (0.2120) time: 2.9262 data: 0.0071 max mem: 33300 +Epoch: [3] [ 320/4276] eta: 3:12:07 lr: 4.652685776797079e-05 loss: 0.2130 (0.2127) time: 2.9545 data: 0.0081 max mem: 33300 +Epoch: [3] [ 330/4276] eta: 3:11:50 lr: 4.652420566591311e-05 loss: 0.2187 (0.2126) time: 2.9954 data: 0.0086 max mem: 33300 +Epoch: [3] [ 340/4276] eta: 3:11:22 lr: 4.652155354705726e-05 loss: 0.2014 (0.2121) time: 2.9714 data: 0.0085 max mem: 33300 +Epoch: [3] [ 350/4276] eta: 3:10:52 lr: 4.6518901411402095e-05 loss: 0.1942 (0.2115) time: 2.9178 data: 0.0081 max mem: 33300 +Epoch: [3] [ 360/4276] eta: 3:10:22 lr: 4.6516249258946416e-05 loss: 0.2043 (0.2123) time: 2.9108 data: 0.0077 max mem: 33300 +Epoch: [3] [ 370/4276] eta: 3:09:52 lr: 4.6513597089689066e-05 loss: 0.2140 (0.2118) time: 2.9087 data: 0.0076 max mem: 33300 +Epoch: [3] [ 380/4276] eta: 3:09:22 lr: 4.651094490362887e-05 loss: 0.1903 (0.2117) time: 2.9075 data: 0.0074 max mem: 33300 +Epoch: [3] [ 390/4276] eta: 6:40:21 lr: 4.650829270076466e-05 loss: 0.2155 (0.2119) time: 66.7441 data: 63.8357 max mem: 33300 +Epoch: [3] [ 400/4276] eta: 6:34:07 lr: 4.650564048109527e-05 loss: 0.2062 (0.2118) time: 66.7663 data: 63.8354 max mem: 33300 +Epoch: [3] [ 410/4276] eta: 6:28:07 lr: 4.650298824461952e-05 loss: 0.2062 (0.2116) time: 2.9386 data: 0.0067 max mem: 33300 +Epoch: [3] [ 420/4276] eta: 6:22:25 lr: 4.650033599133624e-05 loss: 0.2081 (0.2118) time: 2.9385 data: 0.0070 max mem: 33300 +Epoch: [3] [ 430/4276] eta: 6:16:57 lr: 4.6497683721244266e-05 loss: 0.2142 (0.2119) time: 2.9450 data: 0.0074 max mem: 33300 +Epoch: [3] [ 440/4276] eta: 6:11:42 lr: 4.6495031434342415e-05 loss: 0.2208 (0.2118) time: 2.9364 data: 0.0073 max mem: 33300 +Epoch: [3] [ 450/4276] eta: 6:06:41 lr: 4.649237913062951e-05 loss: 0.2148 (0.2122) time: 2.9432 data: 0.0073 max mem: 33300 +Epoch: [3] [ 460/4276] eta: 6:01:51 lr: 4.648972681010439e-05 loss: 0.1953 (0.2117) time: 2.9466 data: 0.0072 max mem: 33300 +Epoch: [3] [ 470/4276] eta: 5:57:12 lr: 4.648707447276589e-05 loss: 0.1875 (0.2113) time: 2.9450 data: 0.0070 max mem: 33300 +Epoch: [3] [ 480/4276] eta: 5:52:44 lr: 4.648442211861283e-05 loss: 0.1959 (0.2111) time: 2.9450 data: 0.0071 max mem: 33300 +Epoch: [3] [ 490/4276] eta: 5:48:25 lr: 4.6481769747644034e-05 loss: 0.1981 (0.2111) time: 2.9424 data: 0.0073 max mem: 33300 +Epoch: [3] [ 500/4276] eta: 5:44:15 lr: 4.647911735985832e-05 loss: 0.1943 (0.2110) time: 2.9408 data: 0.0073 max mem: 33300 +Epoch: [3] [ 510/4276] eta: 5:40:14 lr: 4.647646495525454e-05 loss: 0.1943 (0.2106) time: 2.9408 data: 0.0071 max mem: 33300 +Epoch: [3] [ 520/4276] eta: 5:36:21 lr: 4.64738125338315e-05 loss: 0.2000 (0.2107) time: 2.9413 data: 0.0070 max mem: 33300 +Epoch: [3] [ 530/4276] eta: 5:32:36 lr: 4.6471160095588034e-05 loss: 0.2040 (0.2105) time: 2.9401 data: 0.0070 max mem: 33300 +Epoch: [3] [ 540/4276] eta: 5:28:57 lr: 4.646850764052297e-05 loss: 0.1933 (0.2103) time: 2.9346 data: 0.0071 max mem: 33300 +Epoch: [3] [ 550/4276] eta: 5:25:25 lr: 4.6465855168635134e-05 loss: 0.1972 (0.2102) time: 2.9303 data: 0.0072 max mem: 33300 +Epoch: [3] [ 560/4276] eta: 5:22:00 lr: 4.6463202679923347e-05 loss: 0.2064 (0.2104) time: 2.9311 data: 0.0073 max mem: 33300 +Epoch: [3] [ 570/4276] eta: 5:18:41 lr: 4.646055017438644e-05 loss: 0.2161 (0.2104) time: 2.9308 data: 0.0075 max mem: 33300 +Epoch: [3] [ 580/4276] eta: 5:15:27 lr: 4.645789765202324e-05 loss: 0.2161 (0.2104) time: 2.9298 data: 0.0077 max mem: 33300 +Epoch: [3] [ 590/4276] eta: 5:12:16 lr: 4.645524511283257e-05 loss: 0.1967 (0.2102) time: 2.9032 data: 0.0089 max mem: 33300 +Epoch: [3] [ 600/4276] eta: 5:09:11 lr: 4.645259255681326e-05 loss: 0.1932 (0.2100) time: 2.8865 data: 0.0093 max mem: 33300 +Epoch: [3] [ 610/4276] eta: 5:06:12 lr: 4.644993998396413e-05 loss: 0.1943 (0.2098) time: 2.8967 data: 0.0086 max mem: 33300 +Epoch: [3] [ 620/4276] eta: 5:03:18 lr: 4.6447287394284e-05 loss: 0.1943 (0.2098) time: 2.9020 data: 0.0087 max mem: 33300 +Epoch: [3] [ 630/4276] eta: 5:00:27 lr: 4.6444634787771716e-05 loss: 0.2089 (0.2098) time: 2.8949 data: 0.0089 max mem: 33300 +Epoch: [3] [ 640/4276] eta: 4:57:40 lr: 4.644198216442608e-05 loss: 0.1991 (0.2096) time: 2.8750 data: 0.0083 max mem: 33300 +Epoch: [3] [ 650/4276] eta: 4:54:58 lr: 4.643932952424593e-05 loss: 0.1989 (0.2096) time: 2.8755 data: 0.0080 max mem: 33300 +Epoch: [3] [ 660/4276] eta: 4:52:19 lr: 4.643667686723009e-05 loss: 0.2063 (0.2096) time: 2.8769 data: 0.0083 max mem: 33300 +Epoch: [3] [ 670/4276] eta: 4:49:44 lr: 4.643402419337737e-05 loss: 0.2017 (0.2095) time: 2.8726 data: 0.0087 max mem: 33300 +Epoch: [3] [ 680/4276] eta: 4:47:14 lr: 4.6431371502686615e-05 loss: 0.1848 (0.2093) time: 2.8841 data: 0.0091 max mem: 33300 +Epoch: [3] [ 690/4276] eta: 4:44:47 lr: 4.642871879515664e-05 loss: 0.1858 (0.2092) time: 2.8833 data: 0.0090 max mem: 33300 +Epoch: [3] [ 700/4276] eta: 4:42:23 lr: 4.6426066070786265e-05 loss: 0.2117 (0.2094) time: 2.8773 data: 0.0089 max mem: 33300 +Epoch: [3] [ 710/4276] eta: 4:40:02 lr: 4.642341332957433e-05 loss: 0.2246 (0.2095) time: 2.8815 data: 0.0091 max mem: 33300 +Epoch: [3] [ 720/4276] eta: 4:37:45 lr: 4.642076057151964e-05 loss: 0.2139 (0.2094) time: 2.8779 data: 0.0090 max mem: 33300 +Epoch: [3] [ 730/4276] eta: 4:35:30 lr: 4.641810779662102e-05 loss: 0.2122 (0.2096) time: 2.8783 data: 0.0094 max mem: 33300 +Epoch: [3] [ 740/4276] eta: 4:33:19 lr: 4.6415455004877304e-05 loss: 0.2096 (0.2097) time: 2.8879 data: 0.0094 max mem: 33300 +Epoch: [3] [ 750/4276] eta: 4:31:10 lr: 4.641280219628731e-05 loss: 0.1933 (0.2096) time: 2.8803 data: 0.0088 max mem: 33300 +Epoch: [3] [ 760/4276] eta: 4:29:02 lr: 4.641014937084987e-05 loss: 0.1840 (0.2093) time: 2.8616 data: 0.0089 max mem: 33300 +Epoch: [3] [ 770/4276] eta: 4:26:57 lr: 4.640749652856378e-05 loss: 0.1909 (0.2093) time: 2.8546 data: 0.0087 max mem: 33300 +Epoch: [3] [ 780/4276] eta: 4:24:56 lr: 4.64048436694279e-05 loss: 0.1997 (0.2094) time: 2.8650 data: 0.0084 max mem: 33300 +Epoch: [3] [ 790/4276] eta: 4:22:57 lr: 4.6402190793441024e-05 loss: 0.1997 (0.2095) time: 2.8741 data: 0.0090 max mem: 33300 +Epoch: [3] [ 800/4276] eta: 4:21:00 lr: 4.6399537900601984e-05 loss: 0.1915 (0.2095) time: 2.8788 data: 0.0094 max mem: 33300 +Epoch: [3] [ 810/4276] eta: 4:19:05 lr: 4.6396884990909604e-05 loss: 0.1879 (0.2094) time: 2.8752 data: 0.0089 max mem: 33300 +Epoch: [3] [ 820/4276] eta: 4:17:13 lr: 4.639423206436271e-05 loss: 0.2076 (0.2093) time: 2.8814 data: 0.0086 max mem: 33300 +Epoch: [3] [ 830/4276] eta: 4:15:23 lr: 4.6391579120960114e-05 loss: 0.2097 (0.2095) time: 2.8883 data: 0.0091 max mem: 33300 +Epoch: [3] [ 840/4276] eta: 4:13:36 lr: 4.6388926160700646e-05 loss: 0.1987 (0.2096) time: 2.8945 data: 0.0095 max mem: 33300 +Epoch: [3] [ 850/4276] eta: 4:11:50 lr: 4.638627318358312e-05 loss: 0.1874 (0.2096) time: 2.9086 data: 0.0091 max mem: 33300 +Epoch: [3] [ 860/4276] eta: 4:10:06 lr: 4.6383620189606376e-05 loss: 0.1893 (0.2097) time: 2.9016 data: 0.0085 max mem: 33300 +Epoch: [3] [ 870/4276] eta: 4:08:24 lr: 4.638096717876921e-05 loss: 0.2051 (0.2097) time: 2.9014 data: 0.0087 max mem: 33300 +Epoch: [3] [ 880/4276] eta: 4:06:42 lr: 4.637831415107045e-05 loss: 0.2076 (0.2098) time: 2.8865 data: 0.0091 max mem: 33300 +Epoch: [3] [ 890/4276] eta: 4:05:01 lr: 4.6375661106508935e-05 loss: 0.2116 (0.2098) time: 2.8594 data: 0.0088 max mem: 33300 +Epoch: [3] [ 900/4276] eta: 4:03:22 lr: 4.6373008045083464e-05 loss: 0.2032 (0.2098) time: 2.8521 data: 0.0090 max mem: 33300 +Epoch: [3] [ 910/4276] eta: 4:01:44 lr: 4.6370354966792876e-05 loss: 0.2092 (0.2099) time: 2.8516 data: 0.0093 max mem: 33300 +Epoch: [3] [ 920/4276] eta: 4:00:09 lr: 4.636770187163597e-05 loss: 0.2092 (0.2100) time: 2.8655 data: 0.0090 max mem: 33300 +Epoch: [3] [ 930/4276] eta: 3:58:35 lr: 4.6365048759611584e-05 loss: 0.2067 (0.2099) time: 2.8808 data: 0.0086 max mem: 33300 +Epoch: [3] [ 940/4276] eta: 3:57:04 lr: 4.636239563071854e-05 loss: 0.1900 (0.2097) time: 2.8904 data: 0.0084 max mem: 33300 +Epoch: [3] [ 950/4276] eta: 3:55:34 lr: 4.635974248495565e-05 loss: 0.1907 (0.2096) time: 2.9063 data: 0.0083 max mem: 33300 +Epoch: [3] [ 960/4276] eta: 3:54:05 lr: 4.6357089322321726e-05 loss: 0.2045 (0.2097) time: 2.9100 data: 0.0081 max mem: 33300 +Epoch: [3] [ 970/4276] eta: 3:52:37 lr: 4.6354436142815606e-05 loss: 0.2062 (0.2097) time: 2.8963 data: 0.0086 max mem: 33300 +Epoch: [3] [ 980/4276] eta: 3:51:09 lr: 4.6351782946436095e-05 loss: 0.2198 (0.2099) time: 2.8818 data: 0.0091 max mem: 33300 +Epoch: [3] [ 990/4276] eta: 3:49:43 lr: 4.634912973318202e-05 loss: 0.2002 (0.2097) time: 2.8776 data: 0.0090 max mem: 33300 +Epoch: [3] [1000/4276] eta: 3:48:18 lr: 4.63464765030522e-05 loss: 0.1933 (0.2097) time: 2.8782 data: 0.0090 max mem: 33300 +Epoch: [3] [1010/4276] eta: 3:46:54 lr: 4.6343823256045454e-05 loss: 0.1967 (0.2097) time: 2.8810 data: 0.0094 max mem: 33300 +Epoch: [3] [1020/4276] eta: 3:45:32 lr: 4.63411699921606e-05 loss: 0.1959 (0.2096) time: 2.8893 data: 0.0095 max mem: 33300 +Epoch: [3] [1030/4276] eta: 3:44:11 lr: 4.633851671139646e-05 loss: 0.1958 (0.2098) time: 2.8937 data: 0.0093 max mem: 33300 +Epoch: [3] [1040/4276] eta: 3:42:51 lr: 4.633586341375184e-05 loss: 0.2046 (0.2097) time: 2.9044 data: 0.0086 max mem: 33300 +Epoch: [3] [1050/4276] eta: 3:41:32 lr: 4.633321009922558e-05 loss: 0.1951 (0.2097) time: 2.9168 data: 0.0079 max mem: 33300 +Epoch: [3] [1060/4276] eta: 3:40:15 lr: 4.633055676781648e-05 loss: 0.1992 (0.2098) time: 2.9234 data: 0.0077 max mem: 33300 +Epoch: [3] [1070/4276] eta: 3:38:58 lr: 4.632790341952336e-05 loss: 0.2033 (0.2098) time: 2.9242 data: 0.0075 max mem: 33300 +Epoch: [3] [1080/4276] eta: 3:37:43 lr: 4.632525005434505e-05 loss: 0.2033 (0.2097) time: 2.9247 data: 0.0075 max mem: 33300 +Epoch: [3] [1090/4276] eta: 3:36:28 lr: 4.632259667228036e-05 loss: 0.2087 (0.2096) time: 2.9259 data: 0.0081 max mem: 33300 +Epoch: [3] [1100/4276] eta: 3:35:13 lr: 4.631994327332811e-05 loss: 0.1920 (0.2096) time: 2.9098 data: 0.0090 max mem: 33300 +Epoch: [3] [1110/4276] eta: 3:33:58 lr: 4.631728985748711e-05 loss: 0.1969 (0.2097) time: 2.8851 data: 0.0093 max mem: 33300 +Epoch: [3] [1120/4276] eta: 3:32:45 lr: 4.631463642475619e-05 loss: 0.2167 (0.2098) time: 2.8874 data: 0.0095 max mem: 33300 +Epoch: [3] [1130/4276] eta: 3:31:33 lr: 4.631198297513417e-05 loss: 0.2054 (0.2098) time: 2.9020 data: 0.0094 max mem: 33300 +Epoch: [3] [1140/4276] eta: 3:30:21 lr: 4.630932950861984e-05 loss: 0.1968 (0.2096) time: 2.8962 data: 0.0084 max mem: 33300 +Epoch: [3] [1150/4276] eta: 3:29:11 lr: 4.630667602521204e-05 loss: 0.1989 (0.2096) time: 2.8953 data: 0.0077 max mem: 33300 +Epoch: [3] [1160/4276] eta: 3:28:01 lr: 4.6304022524909586e-05 loss: 0.2006 (0.2097) time: 2.9017 data: 0.0075 max mem: 33300 +Epoch: [3] [1170/4276] eta: 3:26:52 lr: 4.630136900771129e-05 loss: 0.2119 (0.2098) time: 2.9078 data: 0.0077 max mem: 33300 +Epoch: [3] [1180/4276] eta: 3:25:43 lr: 4.629871547361597e-05 loss: 0.1973 (0.2096) time: 2.9074 data: 0.0077 max mem: 33300 +Epoch: [3] [1190/4276] eta: 3:24:35 lr: 4.6296061922622444e-05 loss: 0.1861 (0.2096) time: 2.9079 data: 0.0075 max mem: 33300 +Epoch: [3] [1200/4276] eta: 3:23:28 lr: 4.6293408354729526e-05 loss: 0.1861 (0.2094) time: 2.9164 data: 0.0075 max mem: 33300 +Epoch: [3] [1210/4276] eta: 3:22:22 lr: 4.629075476993603e-05 loss: 0.1933 (0.2094) time: 2.9266 data: 0.0077 max mem: 33300 +Epoch: [3] [1220/4276] eta: 3:21:17 lr: 4.628810116824077e-05 loss: 0.1932 (0.2093) time: 2.9279 data: 0.0077 max mem: 33300 +Epoch: [3] [1230/4276] eta: 3:20:12 lr: 4.628544754964257e-05 loss: 0.1893 (0.2092) time: 2.9285 data: 0.0076 max mem: 33300 +Epoch: [3] [1240/4276] eta: 3:19:08 lr: 4.6282793914140235e-05 loss: 0.2062 (0.2093) time: 2.9288 data: 0.0076 max mem: 33300 +Epoch: [3] [1250/4276] eta: 3:18:04 lr: 4.62801402617326e-05 loss: 0.2062 (0.2094) time: 2.9196 data: 0.0076 max mem: 33300 +Epoch: [3] [1260/4276] eta: 3:17:00 lr: 4.627748659241845e-05 loss: 0.1928 (0.2093) time: 2.9060 data: 0.0087 max mem: 33300 +Epoch: [3] [1270/4276] eta: 3:15:56 lr: 4.627483290619663e-05 loss: 0.2070 (0.2094) time: 2.8925 data: 0.0096 max mem: 33300 +Epoch: [3] [1280/4276] eta: 3:14:53 lr: 4.6272179203065934e-05 loss: 0.2091 (0.2095) time: 2.8858 data: 0.0091 max mem: 33300 +Epoch: [3] [1290/4276] eta: 3:13:50 lr: 4.626952548302519e-05 loss: 0.2015 (0.2096) time: 2.8827 data: 0.0091 max mem: 33300 +Epoch: [3] [1300/4276] eta: 3:12:48 lr: 4.62668717460732e-05 loss: 0.1846 (0.2094) time: 2.8815 data: 0.0091 max mem: 33300 +Epoch: [3] [1310/4276] eta: 3:11:47 lr: 4.6264217992208794e-05 loss: 0.1876 (0.2093) time: 2.8788 data: 0.0092 max mem: 33300 +Epoch: [3] [1320/4276] eta: 3:10:46 lr: 4.626156422143077e-05 loss: 0.2081 (0.2094) time: 2.8899 data: 0.0097 max mem: 33300 +Epoch: [3] [1330/4276] eta: 3:09:46 lr: 4.625891043373796e-05 loss: 0.2008 (0.2093) time: 2.9004 data: 0.0099 max mem: 33300 +Epoch: [3] [1340/4276] eta: 3:08:46 lr: 4.625625662912916e-05 loss: 0.1897 (0.2092) time: 2.8911 data: 0.0093 max mem: 33300 +Epoch: [3] [1350/4276] eta: 3:07:46 lr: 4.625360280760319e-05 loss: 0.2037 (0.2091) time: 2.8856 data: 0.0093 max mem: 33300 +Epoch: [3] [1360/4276] eta: 3:06:47 lr: 4.625094896915888e-05 loss: 0.2062 (0.2092) time: 2.8873 data: 0.0087 max mem: 33300 +Epoch: [3] [1370/4276] eta: 3:05:49 lr: 4.6248295113795016e-05 loss: 0.1940 (0.2090) time: 2.8999 data: 0.0080 max mem: 33300 +Epoch: [3] [1380/4276] eta: 3:04:51 lr: 4.624564124151043e-05 loss: 0.2034 (0.2090) time: 2.9078 data: 0.0080 max mem: 33300 +Epoch: [3] [1390/4276] eta: 3:03:53 lr: 4.624298735230392e-05 loss: 0.2118 (0.2090) time: 2.8976 data: 0.0084 max mem: 33300 +Epoch: [3] [1400/4276] eta: 3:02:56 lr: 4.624033344617432e-05 loss: 0.1992 (0.2091) time: 2.9102 data: 0.0085 max mem: 33300 +Epoch: [3] [1410/4276] eta: 3:01:59 lr: 4.623767952312043e-05 loss: 0.2094 (0.2092) time: 2.9080 data: 0.0084 max mem: 33300 +Epoch: [3] [1420/4276] eta: 3:01:03 lr: 4.623502558314106e-05 loss: 0.2114 (0.2093) time: 2.8860 data: 0.0086 max mem: 33300 +Epoch: [3] [1430/4276] eta: 3:00:06 lr: 4.623237162623503e-05 loss: 0.2001 (0.2093) time: 2.8853 data: 0.0095 max mem: 33300 +Epoch: [3] [1440/4276] eta: 2:59:11 lr: 4.622971765240115e-05 loss: 0.2040 (0.2096) time: 2.8999 data: 0.0100 max mem: 33300 +Epoch: [3] [1450/4276] eta: 2:58:16 lr: 4.622706366163823e-05 loss: 0.2298 (0.2097) time: 2.9053 data: 0.0088 max mem: 33300 +Epoch: [3] [1460/4276] eta: 2:57:21 lr: 4.622440965394508e-05 loss: 0.2097 (0.2098) time: 2.8956 data: 0.0082 max mem: 33300 +Epoch: [3] [1470/4276] eta: 2:56:27 lr: 4.622175562932052e-05 loss: 0.2124 (0.2099) time: 2.9177 data: 0.0085 max mem: 33300 +Epoch: [3] [1480/4276] eta: 2:55:33 lr: 4.621910158776336e-05 loss: 0.2169 (0.2100) time: 2.9429 data: 0.0082 max mem: 33300 +Epoch: [3] [1490/4276] eta: 2:54:40 lr: 4.62164475292724e-05 loss: 0.2095 (0.2101) time: 2.9464 data: 0.0082 max mem: 33300 +Epoch: [3] [1500/4276] eta: 2:53:48 lr: 4.621379345384646e-05 loss: 0.2061 (0.2100) time: 2.9471 data: 0.0080 max mem: 33300 +Epoch: [3] [1510/4276] eta: 2:52:55 lr: 4.621113936148436e-05 loss: 0.2061 (0.2102) time: 2.9422 data: 0.0077 max mem: 33300 +Epoch: [3] [1520/4276] eta: 2:52:03 lr: 4.62084852521849e-05 loss: 0.2140 (0.2102) time: 2.9339 data: 0.0079 max mem: 33300 +Epoch: [3] [1530/4276] eta: 2:51:10 lr: 4.620583112594689e-05 loss: 0.2154 (0.2103) time: 2.9133 data: 0.0088 max mem: 33300 +Epoch: [3] [1540/4276] eta: 2:50:18 lr: 4.620317698276915e-05 loss: 0.2089 (0.2102) time: 2.9107 data: 0.0089 max mem: 33300 +Epoch: [3] [1550/4276] eta: 2:49:27 lr: 4.620052282265048e-05 loss: 0.2147 (0.2103) time: 2.9383 data: 0.0085 max mem: 33300 +Epoch: [3] [1560/4276] eta: 2:48:36 lr: 4.61978686455897e-05 loss: 0.2043 (0.2102) time: 2.9459 data: 0.0085 max mem: 33300 +Epoch: [3] [1570/4276] eta: 2:47:45 lr: 4.6195214451585613e-05 loss: 0.1921 (0.2101) time: 2.9438 data: 0.0080 max mem: 33300 +Epoch: [3] [1580/4276] eta: 2:46:55 lr: 4.6192560240637025e-05 loss: 0.1870 (0.2100) time: 2.9444 data: 0.0079 max mem: 33300 +Epoch: [3] [1590/4276] eta: 2:46:05 lr: 4.618990601274277e-05 loss: 0.1916 (0.2100) time: 2.9425 data: 0.0079 max mem: 33300 +Epoch: [3] [1600/4276] eta: 2:45:15 lr: 4.618725176790163e-05 loss: 0.1942 (0.2100) time: 2.9572 data: 0.0077 max mem: 33300 +Epoch: [3] [1610/4276] eta: 2:44:26 lr: 4.618459750611243e-05 loss: 0.1891 (0.2098) time: 2.9546 data: 0.0075 max mem: 33300 +Epoch: [3] [1620/4276] eta: 2:43:36 lr: 4.618194322737397e-05 loss: 0.1869 (0.2097) time: 2.9396 data: 0.0076 max mem: 33300 +Epoch: [3] [1630/4276] eta: 2:42:47 lr: 4.617928893168506e-05 loss: 0.1954 (0.2098) time: 2.9413 data: 0.0078 max mem: 33300 +Epoch: [3] [1640/4276] eta: 2:41:58 lr: 4.617663461904453e-05 loss: 0.2097 (0.2099) time: 2.9430 data: 0.0077 max mem: 33300 +Epoch: [3] [1650/4276] eta: 2:41:09 lr: 4.6173980289451156e-05 loss: 0.2000 (0.2100) time: 2.9420 data: 0.0080 max mem: 33300 +Epoch: [3] [1660/4276] eta: 2:40:21 lr: 4.617132594290377e-05 loss: 0.2000 (0.2099) time: 2.9427 data: 0.0082 max mem: 33300 +Epoch: [3] [1670/4276] eta: 2:39:32 lr: 4.6168671579401176e-05 loss: 0.2012 (0.2100) time: 2.9336 data: 0.0077 max mem: 33300 +Epoch: [3] [1680/4276] eta: 2:38:44 lr: 4.6166017198942186e-05 loss: 0.2180 (0.2101) time: 2.9263 data: 0.0076 max mem: 33300 +Epoch: [3] [1690/4276] eta: 2:37:56 lr: 4.6163362801525596e-05 loss: 0.2188 (0.2100) time: 2.9354 data: 0.0075 max mem: 33300 +Epoch: [3] [1700/4276] eta: 2:37:08 lr: 4.616070838715022e-05 loss: 0.2113 (0.2101) time: 2.9360 data: 0.0076 max mem: 33300 +Epoch: [3] [1710/4276] eta: 2:36:20 lr: 4.6158053955814874e-05 loss: 0.2227 (0.2102) time: 2.9095 data: 0.0092 max mem: 33300 +Epoch: [3] [1720/4276] eta: 2:35:32 lr: 4.6155399507518356e-05 loss: 0.2223 (0.2103) time: 2.8872 data: 0.0092 max mem: 33300 +Epoch: [3] [1730/4276] eta: 2:34:45 lr: 4.6152745042259476e-05 loss: 0.2064 (0.2103) time: 2.8852 data: 0.0076 max mem: 33300 +Epoch: [3] [1740/4276] eta: 2:33:57 lr: 4.615009056003704e-05 loss: 0.2037 (0.2103) time: 2.8852 data: 0.0075 max mem: 33300 +Epoch: [3] [1750/4276] eta: 2:33:10 lr: 4.614743606084987e-05 loss: 0.2125 (0.2103) time: 2.8863 data: 0.0073 max mem: 33300 +Epoch: [3] [1760/4276] eta: 2:32:23 lr: 4.6144781544696755e-05 loss: 0.2105 (0.2102) time: 2.8860 data: 0.0071 max mem: 33300 +Epoch: [3] [1770/4276] eta: 2:31:36 lr: 4.61421270115765e-05 loss: 0.2105 (0.2102) time: 2.8841 data: 0.0071 max mem: 33300 +Epoch: [3] [1780/4276] eta: 2:30:49 lr: 4.613947246148793e-05 loss: 0.2068 (0.2103) time: 2.8850 data: 0.0072 max mem: 33300 +Epoch: [3] [1790/4276] eta: 2:30:02 lr: 4.613681789442984e-05 loss: 0.2039 (0.2103) time: 2.8841 data: 0.0072 max mem: 33300 +Epoch: [3] [1800/4276] eta: 2:29:16 lr: 4.6134163310401046e-05 loss: 0.2039 (0.2103) time: 2.8832 data: 0.0071 max mem: 33300 +Epoch: [3] [1810/4276] eta: 2:28:30 lr: 4.6131508709400345e-05 loss: 0.2263 (0.2104) time: 2.8850 data: 0.0071 max mem: 33300 +Epoch: [3] [1820/4276] eta: 2:27:44 lr: 4.6128854091426547e-05 loss: 0.2086 (0.2103) time: 2.8855 data: 0.0071 max mem: 33300 +Epoch: [3] [1830/4276] eta: 2:26:58 lr: 4.612619945647845e-05 loss: 0.1939 (0.2104) time: 2.8869 data: 0.0074 max mem: 33300 +Epoch: [3] [1840/4276] eta: 2:26:13 lr: 4.6123544804554875e-05 loss: 0.1994 (0.2103) time: 2.8871 data: 0.0078 max mem: 33300 +Epoch: [3] [1850/4276] eta: 2:25:27 lr: 4.612089013565461e-05 loss: 0.2068 (0.2104) time: 2.8879 data: 0.0080 max mem: 33300 +Epoch: [3] [1860/4276] eta: 2:24:42 lr: 4.611823544977648e-05 loss: 0.2153 (0.2104) time: 2.8944 data: 0.0088 max mem: 33300 +Epoch: [3] [1870/4276] eta: 2:23:57 lr: 4.611558074691928e-05 loss: 0.2153 (0.2105) time: 2.8976 data: 0.0094 max mem: 33300 +Epoch: [3] [1880/4276] eta: 2:23:12 lr: 4.611292602708181e-05 loss: 0.2157 (0.2105) time: 2.8923 data: 0.0088 max mem: 33300 +Epoch: [3] [1890/4276] eta: 2:22:28 lr: 4.611027129026289e-05 loss: 0.1986 (0.2105) time: 2.8890 data: 0.0086 max mem: 33300 +Epoch: [3] [1900/4276] eta: 2:21:43 lr: 4.610761653646132e-05 loss: 0.1870 (0.2104) time: 2.8971 data: 0.0086 max mem: 33300 +Epoch: [3] [1910/4276] eta: 2:20:59 lr: 4.610496176567589e-05 loss: 0.1993 (0.2104) time: 2.9105 data: 0.0079 max mem: 33300 +Epoch: [3] [1920/4276] eta: 2:20:16 lr: 4.610230697790542e-05 loss: 0.1964 (0.2103) time: 2.9203 data: 0.0079 max mem: 33300 +Epoch: [3] [1930/4276] eta: 2:19:32 lr: 4.609965217314872e-05 loss: 0.1964 (0.2103) time: 2.9350 data: 0.0082 max mem: 33300 +Epoch: [3] [1940/4276] eta: 2:18:49 lr: 4.6096997351404575e-05 loss: 0.2127 (0.2104) time: 2.9427 data: 0.0084 max mem: 33300 +Epoch: [3] [1950/4276] eta: 2:18:06 lr: 4.6094342512671806e-05 loss: 0.2089 (0.2104) time: 2.9434 data: 0.0080 max mem: 33300 +Epoch: [3] [1960/4276] eta: 2:17:23 lr: 4.609168765694921e-05 loss: 0.1953 (0.2103) time: 2.9430 data: 0.0084 max mem: 33300 +Epoch: [3] [1970/4276] eta: 2:16:40 lr: 4.6089032784235584e-05 loss: 0.1846 (0.2102) time: 2.9252 data: 0.0095 max mem: 33300 +Epoch: [3] [1980/4276] eta: 2:15:57 lr: 4.6086377894529754e-05 loss: 0.1846 (0.2101) time: 2.9265 data: 0.0092 max mem: 33300 +Epoch: [3] [1990/4276] eta: 2:15:15 lr: 4.60837229878305e-05 loss: 0.1914 (0.2101) time: 2.9420 data: 0.0083 max mem: 33300 +Epoch: [3] [2000/4276] eta: 2:14:32 lr: 4.608106806413663e-05 loss: 0.2146 (0.2102) time: 2.9401 data: 0.0077 max mem: 33300 +Epoch: [3] [2010/4276] eta: 2:13:50 lr: 4.607841312344696e-05 loss: 0.2025 (0.2101) time: 2.9382 data: 0.0073 max mem: 33300 +Epoch: [3] [2020/4276] eta: 2:13:08 lr: 4.607575816576028e-05 loss: 0.2031 (0.2102) time: 2.9382 data: 0.0072 max mem: 33300 +Epoch: [3] [2030/4276] eta: 2:12:26 lr: 4.60731031910754e-05 loss: 0.1965 (0.2101) time: 2.9393 data: 0.0075 max mem: 33300 +Epoch: [3] [2040/4276] eta: 2:11:44 lr: 4.607044819939112e-05 loss: 0.1825 (0.2100) time: 2.9392 data: 0.0074 max mem: 33300 +Epoch: [3] [2050/4276] eta: 2:11:02 lr: 4.606779319070624e-05 loss: 0.2010 (0.2101) time: 2.9387 data: 0.0071 max mem: 33300 +Epoch: [3] [2060/4276] eta: 2:10:20 lr: 4.606513816501958e-05 loss: 0.2066 (0.2101) time: 2.9392 data: 0.0078 max mem: 33300 +Epoch: [3] [2070/4276] eta: 2:09:39 lr: 4.6062483122329916e-05 loss: 0.2066 (0.2100) time: 2.9430 data: 0.0078 max mem: 33300 +Epoch: [3] [2080/4276] eta: 2:08:57 lr: 4.605982806263606e-05 loss: 0.1990 (0.2101) time: 2.9429 data: 0.0071 max mem: 33300 +Epoch: [3] [2090/4276] eta: 2:08:16 lr: 4.6057172985936817e-05 loss: 0.1956 (0.2100) time: 2.9436 data: 0.0072 max mem: 33300 +Epoch: [3] [2100/4276] eta: 2:07:35 lr: 4.6054517892230995e-05 loss: 0.1909 (0.2100) time: 2.9437 data: 0.0073 max mem: 33300 +Epoch: [3] [2110/4276] eta: 2:06:54 lr: 4.605186278151738e-05 loss: 0.1888 (0.2099) time: 2.9443 data: 0.0072 max mem: 33300 +Epoch: [3] [2120/4276] eta: 2:06:13 lr: 4.604920765379479e-05 loss: 0.1801 (0.2098) time: 2.9443 data: 0.0073 max mem: 33300 +Epoch: [3] [2130/4276] eta: 2:05:32 lr: 4.604655250906202e-05 loss: 0.1799 (0.2097) time: 2.9391 data: 0.0074 max mem: 33300 +Epoch: [3] [2140/4276] eta: 2:04:51 lr: 4.6043897347317864e-05 loss: 0.2023 (0.2098) time: 2.9442 data: 0.0072 max mem: 33300 +Epoch: [3] [2150/4276] eta: 2:04:10 lr: 4.604124216856113e-05 loss: 0.2023 (0.2097) time: 2.9393 data: 0.0077 max mem: 33300 +Epoch: [3] [2160/4276] eta: 2:03:30 lr: 4.603858697279061e-05 loss: 0.1997 (0.2097) time: 2.9277 data: 0.0084 max mem: 33300 +Epoch: [3] [2170/4276] eta: 2:02:49 lr: 4.6035931760005125e-05 loss: 0.2076 (0.2097) time: 2.9318 data: 0.0078 max mem: 33300 +Epoch: [3] [2180/4276] eta: 2:02:09 lr: 4.6033276530203464e-05 loss: 0.2092 (0.2098) time: 2.9396 data: 0.0072 max mem: 33300 +Epoch: [3] [2190/4276] eta: 2:01:29 lr: 4.603062128338442e-05 loss: 0.2156 (0.2098) time: 2.9444 data: 0.0072 max mem: 33300 +Epoch: [3] [2200/4276] eta: 2:00:48 lr: 4.60279660195468e-05 loss: 0.2164 (0.2098) time: 2.9443 data: 0.0072 max mem: 33300 +Epoch: [3] [2210/4276] eta: 2:00:08 lr: 4.6025310738689405e-05 loss: 0.2141 (0.2099) time: 2.9424 data: 0.0072 max mem: 33300 +Epoch: [3] [2220/4276] eta: 1:59:28 lr: 4.602265544081103e-05 loss: 0.2087 (0.2099) time: 2.9320 data: 0.0077 max mem: 33300 +Epoch: [3] [2230/4276] eta: 1:58:48 lr: 4.602000012591048e-05 loss: 0.2026 (0.2098) time: 2.9241 data: 0.0088 max mem: 33300 +Epoch: [3] [2240/4276] eta: 1:58:08 lr: 4.601734479398655e-05 loss: 0.1913 (0.2097) time: 2.9247 data: 0.0091 max mem: 33300 +Epoch: [3] [2250/4276] eta: 1:57:29 lr: 4.6014689445038044e-05 loss: 0.1975 (0.2097) time: 2.9315 data: 0.0086 max mem: 33300 +Epoch: [3] [2260/4276] eta: 1:56:49 lr: 4.601203407906376e-05 loss: 0.2119 (0.2098) time: 2.9399 data: 0.0080 max mem: 33300 +Epoch: [3] [2270/4276] eta: 1:56:09 lr: 4.60093786960625e-05 loss: 0.2076 (0.2098) time: 2.9367 data: 0.0074 max mem: 33300 +Epoch: [3] [2280/4276] eta: 1:55:30 lr: 4.600672329603305e-05 loss: 0.2065 (0.2098) time: 2.9372 data: 0.0072 max mem: 33300 +Epoch: [3] [2290/4276] eta: 1:54:51 lr: 4.600406787897423e-05 loss: 0.1946 (0.2097) time: 2.9407 data: 0.0071 max mem: 33300 +Epoch: [3] [2300/4276] eta: 1:54:11 lr: 4.600141244488482e-05 loss: 0.1874 (0.2096) time: 2.9433 data: 0.0072 max mem: 33300 +Epoch: [3] [2310/4276] eta: 1:53:32 lr: 4.599875699376363e-05 loss: 0.1825 (0.2095) time: 2.9412 data: 0.0071 max mem: 33300 +Epoch: [3] [2320/4276] eta: 1:52:53 lr: 4.5996101525609444e-05 loss: 0.2026 (0.2095) time: 2.9436 data: 0.0071 max mem: 33300 +Epoch: [3] [2330/4276] eta: 1:52:14 lr: 4.599344604042108e-05 loss: 0.2017 (0.2095) time: 2.9436 data: 0.0072 max mem: 33300 +Epoch: [3] [2340/4276] eta: 1:51:35 lr: 4.5990790538197314e-05 loss: 0.1913 (0.2094) time: 2.9434 data: 0.0072 max mem: 33300 +Epoch: [3] [2350/4276] eta: 1:50:57 lr: 4.598813501893696e-05 loss: 0.1914 (0.2094) time: 2.9447 data: 0.0074 max mem: 33300 +Epoch: [3] [2360/4276] eta: 1:50:18 lr: 4.5985479482638816e-05 loss: 0.1939 (0.2093) time: 2.9389 data: 0.0074 max mem: 33300 +Epoch: [3] [2370/4276] eta: 1:49:39 lr: 4.598282392930167e-05 loss: 0.2009 (0.2093) time: 2.9371 data: 0.0072 max mem: 33300 +Epoch: [3] [2380/4276] eta: 1:49:00 lr: 4.5980168358924326e-05 loss: 0.1957 (0.2093) time: 2.9361 data: 0.0072 max mem: 33300 +Epoch: [3] [2390/4276] eta: 1:48:22 lr: 4.597751277150558e-05 loss: 0.1869 (0.2092) time: 2.9359 data: 0.0072 max mem: 33300 +Epoch: [3] [2400/4276] eta: 1:47:43 lr: 4.597485716704422e-05 loss: 0.1945 (0.2093) time: 2.9310 data: 0.0077 max mem: 33300 +Epoch: [3] [2410/4276] eta: 1:47:05 lr: 4.597220154553906e-05 loss: 0.1969 (0.2092) time: 2.9304 data: 0.0079 max mem: 33300 +Epoch: [3] [2420/4276] eta: 1:46:27 lr: 4.5969545906988884e-05 loss: 0.1840 (0.2091) time: 2.9358 data: 0.0077 max mem: 33300 +Epoch: [3] [2430/4276] eta: 1:45:48 lr: 4.596689025139249e-05 loss: 0.1962 (0.2092) time: 2.9372 data: 0.0078 max mem: 33300 +Epoch: [3] [2440/4276] eta: 1:45:10 lr: 4.5964234578748674e-05 loss: 0.1989 (0.2091) time: 2.9281 data: 0.0078 max mem: 33300 +Epoch: [3] [2450/4276] eta: 1:44:32 lr: 4.596157888905624e-05 loss: 0.1992 (0.2091) time: 2.9301 data: 0.0080 max mem: 33300 +Epoch: [3] [2460/4276] eta: 1:43:54 lr: 4.595892318231397e-05 loss: 0.2006 (0.2091) time: 2.9405 data: 0.0079 max mem: 33300 +Epoch: [3] [2470/4276] eta: 1:43:16 lr: 4.5956267458520675e-05 loss: 0.2034 (0.2091) time: 2.9196 data: 0.0083 max mem: 33300 +Epoch: [3] [2480/4276] eta: 1:42:38 lr: 4.595361171767514e-05 loss: 0.2034 (0.2091) time: 2.8929 data: 0.0090 max mem: 33300 +Epoch: [3] [2490/4276] eta: 1:41:59 lr: 4.595095595977617e-05 loss: 0.1989 (0.2091) time: 2.8867 data: 0.0090 max mem: 33300 +Epoch: [3] [2500/4276] eta: 1:41:21 lr: 4.594830018482255e-05 loss: 0.2086 (0.2091) time: 2.8922 data: 0.0096 max mem: 33300 +Epoch: [3] [2510/4276] eta: 1:40:43 lr: 4.5945644392813084e-05 loss: 0.2100 (0.2091) time: 2.8939 data: 0.0095 max mem: 33300 +Epoch: [3] [2520/4276] eta: 1:40:06 lr: 4.594298858374656e-05 loss: 0.1742 (0.2090) time: 2.9150 data: 0.0095 max mem: 33300 +Epoch: [3] [2530/4276] eta: 1:39:28 lr: 4.5940332757621774e-05 loss: 0.1629 (0.2088) time: 2.9463 data: 0.0088 max mem: 33300 +Epoch: [3] [2540/4276] eta: 1:38:51 lr: 4.593767691443752e-05 loss: 0.1709 (0.2087) time: 2.9465 data: 0.0079 max mem: 33300 +Epoch: [3] [2550/4276] eta: 1:38:14 lr: 4.59350210541926e-05 loss: 0.1906 (0.2087) time: 2.9431 data: 0.0081 max mem: 33300 +Epoch: [3] [2560/4276] eta: 1:37:36 lr: 4.593236517688581e-05 loss: 0.1873 (0.2086) time: 2.9443 data: 0.0081 max mem: 33300 +Epoch: [3] [2570/4276] eta: 1:36:59 lr: 4.5929709282515927e-05 loss: 0.1782 (0.2086) time: 2.9300 data: 0.0089 max mem: 33300 +Epoch: [3] [2580/4276] eta: 1:36:22 lr: 4.592705337108176e-05 loss: 0.1830 (0.2085) time: 2.9303 data: 0.0097 max mem: 33300 +Epoch: [3] [2590/4276] eta: 1:35:44 lr: 4.5924397442582096e-05 loss: 0.1870 (0.2085) time: 2.9414 data: 0.0091 max mem: 33300 +Epoch: [3] [2600/4276] eta: 1:35:07 lr: 4.5921741497015735e-05 loss: 0.1927 (0.2085) time: 2.9408 data: 0.0085 max mem: 33300 +Epoch: [3] [2610/4276] eta: 1:34:30 lr: 4.591908553438146e-05 loss: 0.2013 (0.2085) time: 2.9424 data: 0.0082 max mem: 33300 +Epoch: [3] [2620/4276] eta: 1:33:53 lr: 4.5916429554678074e-05 loss: 0.1979 (0.2085) time: 2.9410 data: 0.0080 max mem: 33300 +Epoch: [3] [2630/4276] eta: 1:33:17 lr: 4.591377355790437e-05 loss: 0.1930 (0.2084) time: 2.9500 data: 0.0082 max mem: 33300 +Epoch: [3] [2640/4276] eta: 1:32:40 lr: 4.591111754405914e-05 loss: 0.1770 (0.2083) time: 2.9375 data: 0.0083 max mem: 33300 +Epoch: [3] [2650/4276] eta: 1:32:03 lr: 4.590846151314117e-05 loss: 0.1838 (0.2083) time: 2.9281 data: 0.0085 max mem: 33300 +Epoch: [3] [2660/4276] eta: 1:31:26 lr: 4.5905805465149265e-05 loss: 0.2039 (0.2083) time: 2.9411 data: 0.0087 max mem: 33300 +Epoch: [3] [2670/4276] eta: 1:30:49 lr: 4.590314940008221e-05 loss: 0.2032 (0.2082) time: 2.9382 data: 0.0080 max mem: 33300 +Epoch: [3] [2680/4276] eta: 1:30:13 lr: 4.590049331793879e-05 loss: 0.1955 (0.2082) time: 2.9396 data: 0.0076 max mem: 33300 +Epoch: [3] [2690/4276] eta: 1:29:36 lr: 4.589783721871781e-05 loss: 0.1968 (0.2082) time: 2.9231 data: 0.0081 max mem: 33300 +Epoch: [3] [2700/4276] eta: 1:28:59 lr: 4.589518110241806e-05 loss: 0.1911 (0.2081) time: 2.9145 data: 0.0087 max mem: 33300 +Epoch: [3] [2710/4276] eta: 1:28:23 lr: 4.5892524969038327e-05 loss: 0.1871 (0.2082) time: 2.9312 data: 0.0080 max mem: 33300 +Epoch: [3] [2720/4276] eta: 1:27:46 lr: 4.5889868818577406e-05 loss: 0.2103 (0.2081) time: 2.9386 data: 0.0073 max mem: 33300 +Epoch: [3] [2730/4276] eta: 1:27:10 lr: 4.5887212651034087e-05 loss: 0.2055 (0.2082) time: 2.9254 data: 0.0077 max mem: 33300 +Epoch: [3] [2740/4276] eta: 1:26:33 lr: 4.588455646640717e-05 loss: 0.2141 (0.2082) time: 2.9104 data: 0.0084 max mem: 33300 +Epoch: [3] [2750/4276] eta: 1:25:57 lr: 4.588190026469543e-05 loss: 0.2049 (0.2082) time: 2.9246 data: 0.0081 max mem: 33300 +Epoch: [3] [2760/4276] eta: 1:25:21 lr: 4.5879244045897666e-05 loss: 0.1954 (0.2081) time: 2.9416 data: 0.0071 max mem: 33300 +Epoch: [3] [2770/4276] eta: 1:24:45 lr: 4.587658781001268e-05 loss: 0.1842 (0.2081) time: 2.9412 data: 0.0072 max mem: 33300 +Epoch: [3] [2780/4276] eta: 1:24:09 lr: 4.5873931557039244e-05 loss: 0.1961 (0.2081) time: 2.9305 data: 0.0073 max mem: 33300 +Epoch: [3] [2790/4276] eta: 1:23:33 lr: 4.587127528697615e-05 loss: 0.2118 (0.2081) time: 2.9316 data: 0.0080 max mem: 33300 +Epoch: [3] [2800/4276] eta: 1:22:56 lr: 4.586861899982221e-05 loss: 0.2006 (0.2081) time: 2.9386 data: 0.0078 max mem: 33300 +Epoch: [3] [2810/4276] eta: 1:22:21 lr: 4.586596269557619e-05 loss: 0.1934 (0.2080) time: 2.9438 data: 0.0072 max mem: 33300 +Epoch: [3] [2820/4276] eta: 1:21:45 lr: 4.58633063742369e-05 loss: 0.1911 (0.2080) time: 2.9484 data: 0.0073 max mem: 33300 +Epoch: [3] [2830/4276] eta: 1:21:09 lr: 4.5860650035803116e-05 loss: 0.1910 (0.2079) time: 2.9489 data: 0.0073 max mem: 33300 +Epoch: [3] [2840/4276] eta: 1:20:33 lr: 4.585799368027363e-05 loss: 0.1955 (0.2079) time: 2.9468 data: 0.0073 max mem: 33300 +Epoch: [3] [2850/4276] eta: 1:19:57 lr: 4.585533730764723e-05 loss: 0.2124 (0.2080) time: 2.9421 data: 0.0080 max mem: 33300 +Epoch: [3] [2860/4276] eta: 1:19:21 lr: 4.585268091792271e-05 loss: 0.2105 (0.2080) time: 2.9414 data: 0.0081 max mem: 33300 +Epoch: [3] [2870/4276] eta: 1:18:46 lr: 4.585002451109886e-05 loss: 0.2061 (0.2080) time: 2.9485 data: 0.0079 max mem: 33300 +Epoch: [3] [2880/4276] eta: 1:18:10 lr: 4.584736808717447e-05 loss: 0.2068 (0.2081) time: 2.9411 data: 0.0084 max mem: 33300 +Epoch: [3] [2890/4276] eta: 1:17:35 lr: 4.5844711646148325e-05 loss: 0.2130 (0.2081) time: 2.9356 data: 0.0086 max mem: 33300 +Epoch: [3] [2900/4276] eta: 1:16:59 lr: 4.584205518801921e-05 loss: 0.2011 (0.2080) time: 2.9421 data: 0.0085 max mem: 33300 +Epoch: [3] [2910/4276] eta: 1:16:23 lr: 4.583939871278593e-05 loss: 0.1841 (0.2080) time: 2.9161 data: 0.0091 max mem: 33300 +Epoch: [3] [2920/4276] eta: 1:15:48 lr: 4.583674222044726e-05 loss: 0.1932 (0.2080) time: 2.8949 data: 0.0094 max mem: 33300 +Epoch: [3] [2930/4276] eta: 1:15:12 lr: 4.5834085711001985e-05 loss: 0.1876 (0.2080) time: 2.8939 data: 0.0087 max mem: 33300 +Epoch: [3] [2940/4276] eta: 1:14:36 lr: 4.58314291844489e-05 loss: 0.1845 (0.2079) time: 2.9095 data: 0.0084 max mem: 33300 +Epoch: [3] [2950/4276] eta: 1:14:01 lr: 4.5828772640786795e-05 loss: 0.1764 (0.2079) time: 2.9343 data: 0.0080 max mem: 33300 +Epoch: [3] [2960/4276] eta: 1:13:26 lr: 4.5826116080014454e-05 loss: 0.2115 (0.2079) time: 2.9411 data: 0.0078 max mem: 33300 +Epoch: [3] [2970/4276] eta: 1:12:50 lr: 4.582345950213066e-05 loss: 0.2115 (0.2080) time: 2.9412 data: 0.0080 max mem: 33300 +Epoch: [3] [2980/4276] eta: 1:12:15 lr: 4.5820802907134216e-05 loss: 0.2103 (0.2080) time: 2.9409 data: 0.0078 max mem: 33300 +Epoch: [3] [2990/4276] eta: 1:11:40 lr: 4.581814629502389e-05 loss: 0.1975 (0.2079) time: 2.9404 data: 0.0075 max mem: 33300 +Epoch: [3] [3000/4276] eta: 1:11:05 lr: 4.581548966579848e-05 loss: 0.1879 (0.2078) time: 2.9402 data: 0.0076 max mem: 33300 +Epoch: [3] [3010/4276] eta: 1:10:30 lr: 4.581283301945678e-05 loss: 0.1947 (0.2078) time: 2.9411 data: 0.0078 max mem: 33300 +Epoch: [3] [3020/4276] eta: 1:09:55 lr: 4.581017635599756e-05 loss: 0.1950 (0.2078) time: 2.9448 data: 0.0085 max mem: 33300 +Epoch: [3] [3030/4276] eta: 1:09:20 lr: 4.580751967541962e-05 loss: 0.1892 (0.2078) time: 2.9462 data: 0.0088 max mem: 33300 +Epoch: [3] [3040/4276] eta: 1:08:45 lr: 4.5804862977721744e-05 loss: 0.2053 (0.2079) time: 2.9200 data: 0.0085 max mem: 33300 +Epoch: [3] [3050/4276] eta: 1:08:09 lr: 4.5802206262902706e-05 loss: 0.2104 (0.2079) time: 2.8926 data: 0.0085 max mem: 33300 +Epoch: [3] [3060/4276] eta: 1:07:34 lr: 4.5799549530961304e-05 loss: 0.1801 (0.2078) time: 2.8908 data: 0.0084 max mem: 33300 +Epoch: [3] [3070/4276] eta: 1:06:59 lr: 4.579689278189633e-05 loss: 0.1805 (0.2078) time: 2.8899 data: 0.0078 max mem: 33300 +Epoch: [3] [3080/4276] eta: 1:06:24 lr: 4.579423601570656e-05 loss: 0.1939 (0.2077) time: 2.8887 data: 0.0075 max mem: 33300 +Epoch: [3] [3090/4276] eta: 1:05:49 lr: 4.579157923239078e-05 loss: 0.1834 (0.2077) time: 2.8983 data: 0.0081 max mem: 33300 +Epoch: [3] [3100/4276] eta: 1:05:14 lr: 4.578892243194778e-05 loss: 0.1948 (0.2077) time: 2.9066 data: 0.0088 max mem: 33300 +Epoch: [3] [3110/4276] eta: 1:04:39 lr: 4.5786265614376344e-05 loss: 0.1948 (0.2076) time: 2.8982 data: 0.0088 max mem: 33300 +Epoch: [3] [3120/4276] eta: 1:04:04 lr: 4.578360877967525e-05 loss: 0.1789 (0.2076) time: 2.8893 data: 0.0083 max mem: 33300 +Epoch: [3] [3130/4276] eta: 1:03:29 lr: 4.578095192784329e-05 loss: 0.2010 (0.2076) time: 2.8830 data: 0.0079 max mem: 33300 +Epoch: [3] [3140/4276] eta: 1:02:55 lr: 4.5778295058879254e-05 loss: 0.2050 (0.2076) time: 2.8714 data: 0.0080 max mem: 33300 +Epoch: [3] [3150/4276] eta: 1:02:20 lr: 4.577563817278192e-05 loss: 0.2054 (0.2077) time: 2.8726 data: 0.0082 max mem: 33300 +Epoch: [3] [3160/4276] eta: 1:01:45 lr: 4.577298126955007e-05 loss: 0.2001 (0.2077) time: 2.8830 data: 0.0080 max mem: 33300 +Epoch: [3] [3170/4276] eta: 1:01:10 lr: 4.577032434918249e-05 loss: 0.1799 (0.2077) time: 2.9052 data: 0.0080 max mem: 33300 +Epoch: [3] [3180/4276] eta: 1:00:36 lr: 4.5767667411677964e-05 loss: 0.2035 (0.2077) time: 2.9150 data: 0.0083 max mem: 33300 +Epoch: [3] [3190/4276] eta: 1:00:01 lr: 4.576501045703529e-05 loss: 0.2080 (0.2078) time: 2.9074 data: 0.0084 max mem: 33300 +Epoch: [3] [3200/4276] eta: 0:59:27 lr: 4.576235348525323e-05 loss: 0.1884 (0.2078) time: 2.9036 data: 0.0086 max mem: 33300 +Epoch: [3] [3210/4276] eta: 0:58:52 lr: 4.575969649633058e-05 loss: 0.1920 (0.2078) time: 2.8901 data: 0.0081 max mem: 33300 +Epoch: [3] [3220/4276] eta: 0:58:18 lr: 4.575703949026612e-05 loss: 0.1994 (0.2077) time: 2.8829 data: 0.0078 max mem: 33300 +Epoch: [3] [3230/4276] eta: 0:57:43 lr: 4.575438246705864e-05 loss: 0.2002 (0.2077) time: 2.8829 data: 0.0081 max mem: 33300 +Epoch: [3] [3240/4276] eta: 0:57:09 lr: 4.575172542670691e-05 loss: 0.2034 (0.2077) time: 2.8821 data: 0.0079 max mem: 33300 +Epoch: [3] [3250/4276] eta: 0:56:34 lr: 4.5749068369209727e-05 loss: 0.2028 (0.2077) time: 2.8843 data: 0.0080 max mem: 33300 +Epoch: [3] [3260/4276] eta: 0:56:00 lr: 4.574641129456587e-05 loss: 0.1973 (0.2077) time: 2.8872 data: 0.0084 max mem: 33300 +Epoch: [3] [3270/4276] eta: 0:55:25 lr: 4.574375420277411e-05 loss: 0.2105 (0.2077) time: 2.8867 data: 0.0086 max mem: 33300 +Epoch: [3] [3280/4276] eta: 0:54:51 lr: 4.5741097093833246e-05 loss: 0.2128 (0.2077) time: 2.8870 data: 0.0087 max mem: 33300 +Epoch: [3] [3290/4276] eta: 0:54:17 lr: 4.573843996774205e-05 loss: 0.2134 (0.2078) time: 2.8873 data: 0.0089 max mem: 33300 +Epoch: [3] [3300/4276] eta: 0:53:42 lr: 4.573578282449931e-05 loss: 0.2122 (0.2078) time: 2.8873 data: 0.0091 max mem: 33300 +Epoch: [3] [3310/4276] eta: 0:53:08 lr: 4.573312566410381e-05 loss: 0.2069 (0.2078) time: 2.8873 data: 0.0091 max mem: 33300 +Epoch: [3] [3320/4276] eta: 0:52:34 lr: 4.5730468486554323e-05 loss: 0.2030 (0.2079) time: 2.8929 data: 0.0090 max mem: 33300 +Epoch: [3] [3330/4276] eta: 0:52:00 lr: 4.572781129184964e-05 loss: 0.1963 (0.2078) time: 2.9100 data: 0.0092 max mem: 33300 +Epoch: [3] [3340/4276] eta: 0:51:26 lr: 4.5725154079988535e-05 loss: 0.2062 (0.2079) time: 2.9132 data: 0.0090 max mem: 33300 +Epoch: [3] [3350/4276] eta: 0:50:52 lr: 4.572249685096979e-05 loss: 0.1989 (0.2078) time: 2.9209 data: 0.0087 max mem: 33300 +Epoch: [3] [3360/4276] eta: 0:50:18 lr: 4.571983960479219e-05 loss: 0.1934 (0.2078) time: 2.9393 data: 0.0087 max mem: 33300 +Epoch: [3] [3370/4276] eta: 0:49:44 lr: 4.571718234145452e-05 loss: 0.2195 (0.2079) time: 2.9391 data: 0.0078 max mem: 33300 +Epoch: [3] [3380/4276] eta: 0:49:10 lr: 4.571452506095555e-05 loss: 0.2108 (0.2079) time: 2.9359 data: 0.0071 max mem: 33300 +Epoch: [3] [3390/4276] eta: 0:48:36 lr: 4.571186776329407e-05 loss: 0.2108 (0.2080) time: 2.9368 data: 0.0072 max mem: 33300 +Epoch: [3] [3400/4276] eta: 0:48:02 lr: 4.570921044846886e-05 loss: 0.2119 (0.2080) time: 2.9368 data: 0.0075 max mem: 33300 +Epoch: [3] [3410/4276] eta: 0:47:29 lr: 4.57065531164787e-05 loss: 0.2119 (0.2080) time: 2.9359 data: 0.0076 max mem: 33300 +Epoch: [3] [3420/4276] eta: 0:46:55 lr: 4.5703895767322364e-05 loss: 0.2149 (0.2080) time: 2.9368 data: 0.0077 max mem: 33300 +Epoch: [3] [3430/4276] eta: 0:46:21 lr: 4.570123840099863e-05 loss: 0.2050 (0.2080) time: 2.9363 data: 0.0077 max mem: 33300 +Epoch: [3] [3440/4276] eta: 0:45:47 lr: 4.569858101750629e-05 loss: 0.2050 (0.2080) time: 2.9353 data: 0.0073 max mem: 33300 +Epoch: [3] [3450/4276] eta: 0:45:14 lr: 4.569592361684412e-05 loss: 0.2060 (0.2080) time: 2.9344 data: 0.0072 max mem: 33300 +Epoch: [3] [3460/4276] eta: 0:44:40 lr: 4.56932661990109e-05 loss: 0.2060 (0.2080) time: 2.9334 data: 0.0074 max mem: 33300 +Epoch: [3] [3470/4276] eta: 0:44:06 lr: 4.5690608764005397e-05 loss: 0.1957 (0.2079) time: 2.9330 data: 0.0074 max mem: 33300 +Epoch: [3] [3480/4276] eta: 0:43:33 lr: 4.5687951311826404e-05 loss: 0.1977 (0.2079) time: 2.9340 data: 0.0075 max mem: 33300 +Epoch: [3] [3490/4276] eta: 0:42:59 lr: 4.56852938424727e-05 loss: 0.2025 (0.2079) time: 2.9318 data: 0.0079 max mem: 33300 +Epoch: [3] [3500/4276] eta: 0:42:25 lr: 4.568263635594306e-05 loss: 0.1990 (0.2079) time: 2.9098 data: 0.0089 max mem: 33300 +Epoch: [3] [3510/4276] eta: 0:41:52 lr: 4.567997885223626e-05 loss: 0.1857 (0.2078) time: 2.8941 data: 0.0094 max mem: 33300 +Epoch: [3] [3520/4276] eta: 0:41:18 lr: 4.567732133135108e-05 loss: 0.1940 (0.2078) time: 2.9170 data: 0.0082 max mem: 33300 +Epoch: [3] [3530/4276] eta: 0:40:45 lr: 4.5674663793286305e-05 loss: 0.1992 (0.2078) time: 2.9368 data: 0.0076 max mem: 33300 +Epoch: [3] [3540/4276] eta: 0:40:11 lr: 4.56720062380407e-05 loss: 0.1938 (0.2078) time: 2.9360 data: 0.0077 max mem: 33300 +Epoch: [3] [3550/4276] eta: 0:39:38 lr: 4.5669348665613064e-05 loss: 0.2155 (0.2078) time: 2.9362 data: 0.0076 max mem: 33300 +Epoch: [3] [3560/4276] eta: 0:39:04 lr: 4.5666691076002155e-05 loss: 0.2077 (0.2078) time: 2.9373 data: 0.0078 max mem: 33300 +Epoch: [3] [3570/4276] eta: 0:38:31 lr: 4.5664033469206765e-05 loss: 0.2095 (0.2078) time: 2.9367 data: 0.0080 max mem: 33300 +Epoch: [3] [3580/4276] eta: 0:37:57 lr: 4.566137584522566e-05 loss: 0.1833 (0.2078) time: 2.9370 data: 0.0077 max mem: 33300 +Epoch: [3] [3590/4276] eta: 0:37:24 lr: 4.565871820405762e-05 loss: 0.1806 (0.2078) time: 2.9381 data: 0.0075 max mem: 33300 +Epoch: [3] [3600/4276] eta: 0:36:51 lr: 4.5656060545701426e-05 loss: 0.2181 (0.2078) time: 2.9385 data: 0.0076 max mem: 33300 +Epoch: [3] [3610/4276] eta: 0:36:17 lr: 4.565340287015586e-05 loss: 0.2158 (0.2078) time: 2.9435 data: 0.0077 max mem: 33300 +Epoch: [3] [3620/4276] eta: 0:35:44 lr: 4.565074517741969e-05 loss: 0.1953 (0.2077) time: 2.9357 data: 0.0078 max mem: 33300 +Epoch: [3] [3630/4276] eta: 0:35:11 lr: 4.5648087467491685e-05 loss: 0.2023 (0.2078) time: 2.9370 data: 0.0078 max mem: 33300 +Epoch: [3] [3640/4276] eta: 0:34:38 lr: 4.5645429740370636e-05 loss: 0.2023 (0.2078) time: 2.9447 data: 0.0077 max mem: 33300 +Epoch: [3] [3650/4276] eta: 0:34:04 lr: 4.5642771996055326e-05 loss: 0.1963 (0.2078) time: 2.9421 data: 0.0080 max mem: 33300 +Epoch: [3] [3660/4276] eta: 0:33:31 lr: 4.564011423454451e-05 loss: 0.1984 (0.2078) time: 2.9420 data: 0.0080 max mem: 33300 +Epoch: [3] [3670/4276] eta: 0:32:58 lr: 4.5637456455836985e-05 loss: 0.2159 (0.2078) time: 2.9333 data: 0.0077 max mem: 33300 +Epoch: [3] [3680/4276] eta: 0:32:25 lr: 4.5634798659931514e-05 loss: 0.2159 (0.2078) time: 2.9385 data: 0.0084 max mem: 33300 +Epoch: [3] [3690/4276] eta: 0:31:52 lr: 4.563214084682687e-05 loss: 0.2119 (0.2078) time: 2.9443 data: 0.0087 max mem: 33300 +Epoch: [3] [3700/4276] eta: 0:31:18 lr: 4.562948301652184e-05 loss: 0.2030 (0.2079) time: 2.9383 data: 0.0080 max mem: 33300 +Epoch: [3] [3710/4276] eta: 0:30:45 lr: 4.562682516901519e-05 loss: 0.2004 (0.2078) time: 2.9356 data: 0.0076 max mem: 33300 +Epoch: [3] [3720/4276] eta: 0:30:12 lr: 4.56241673043057e-05 loss: 0.1901 (0.2078) time: 2.9345 data: 0.0078 max mem: 33300 +Epoch: [3] [3730/4276] eta: 0:29:39 lr: 4.562150942239215e-05 loss: 0.1982 (0.2078) time: 2.9360 data: 0.0082 max mem: 33300 +Epoch: [3] [3740/4276] eta: 0:29:06 lr: 4.56188515232733e-05 loss: 0.2011 (0.2078) time: 2.9562 data: 0.0083 max mem: 33300 +Epoch: [3] [3750/4276] eta: 0:28:33 lr: 4.5616193606947936e-05 loss: 0.2031 (0.2078) time: 2.9560 data: 0.0084 max mem: 33300 +Epoch: [3] [3760/4276] eta: 0:28:00 lr: 4.5613535673414844e-05 loss: 0.1998 (0.2078) time: 2.9195 data: 0.0084 max mem: 33300 +Epoch: [3] [3770/4276] eta: 0:27:27 lr: 4.561087772267277e-05 loss: 0.1998 (0.2078) time: 2.9034 data: 0.0077 max mem: 33300 +Epoch: [3] [3780/4276] eta: 0:26:54 lr: 4.5608219754720505e-05 loss: 0.2088 (0.2078) time: 2.9198 data: 0.0074 max mem: 33300 +Epoch: [3] [3790/4276] eta: 0:26:21 lr: 4.5605561769556825e-05 loss: 0.2056 (0.2078) time: 2.9350 data: 0.0074 max mem: 33300 +Epoch: [3] [3800/4276] eta: 0:25:48 lr: 4.56029037671805e-05 loss: 0.2086 (0.2078) time: 2.9358 data: 0.0074 max mem: 33300 +Epoch: [3] [3810/4276] eta: 0:25:15 lr: 4.560024574759031e-05 loss: 0.1969 (0.2078) time: 2.9350 data: 0.0073 max mem: 33300 +Epoch: [3] [3820/4276] eta: 0:24:42 lr: 4.559758771078501e-05 loss: 0.1906 (0.2078) time: 2.9358 data: 0.0074 max mem: 33300 +Epoch: [3] [3830/4276] eta: 0:24:09 lr: 4.55949296567634e-05 loss: 0.1992 (0.2078) time: 2.9366 data: 0.0074 max mem: 33300 +Epoch: [3] [3840/4276] eta: 0:23:37 lr: 4.559227158552423e-05 loss: 0.2085 (0.2078) time: 2.9366 data: 0.0075 max mem: 33300 +Epoch: [3] [3850/4276] eta: 0:23:04 lr: 4.558961349706629e-05 loss: 0.1983 (0.2078) time: 2.9360 data: 0.0075 max mem: 33300 +Epoch: [3] [3860/4276] eta: 0:22:31 lr: 4.5586955391388344e-05 loss: 0.2000 (0.2078) time: 2.9361 data: 0.0072 max mem: 33300 +Epoch: [3] [3870/4276] eta: 0:21:58 lr: 4.558429726848916e-05 loss: 0.2053 (0.2078) time: 2.9375 data: 0.0072 max mem: 33300 +Epoch: [3] [3880/4276] eta: 0:21:25 lr: 4.558163912836753e-05 loss: 0.2018 (0.2078) time: 2.9403 data: 0.0072 max mem: 33300 +Epoch: [3] [3890/4276] eta: 0:20:53 lr: 4.55789809710222e-05 loss: 0.2013 (0.2078) time: 2.9400 data: 0.0072 max mem: 33300 +Epoch: [3] [3900/4276] eta: 0:20:20 lr: 4.557632279645196e-05 loss: 0.2041 (0.2078) time: 2.9406 data: 0.0073 max mem: 33300 +Epoch: [3] [3910/4276] eta: 0:19:47 lr: 4.557366460465558e-05 loss: 0.1963 (0.2078) time: 2.9399 data: 0.0072 max mem: 33300 +Epoch: [3] [3920/4276] eta: 0:19:14 lr: 4.5571006395631835e-05 loss: 0.1947 (0.2078) time: 2.9400 data: 0.0071 max mem: 33300 +Epoch: [3] [3930/4276] eta: 0:18:42 lr: 4.5568348169379484e-05 loss: 0.2035 (0.2077) time: 2.9390 data: 0.0071 max mem: 33300 +Epoch: [3] [3940/4276] eta: 0:18:09 lr: 4.5565689925897305e-05 loss: 0.2015 (0.2077) time: 2.9377 data: 0.0072 max mem: 33300 +Epoch: [3] [3950/4276] eta: 0:17:36 lr: 4.5563031665184076e-05 loss: 0.1931 (0.2077) time: 2.9386 data: 0.0074 max mem: 33300 +Epoch: [3] [3960/4276] eta: 0:17:04 lr: 4.5560373387238565e-05 loss: 0.1986 (0.2077) time: 2.9277 data: 0.0084 max mem: 33300 +Epoch: [3] [3970/4276] eta: 0:16:31 lr: 4.555771509205954e-05 loss: 0.2246 (0.2077) time: 2.9270 data: 0.0084 max mem: 33300 +Epoch: [3] [3980/4276] eta: 0:15:58 lr: 4.5555056779645764e-05 loss: 0.2047 (0.2077) time: 2.9150 data: 0.0084 max mem: 33300 +Epoch: [3] [3990/4276] eta: 0:15:26 lr: 4.5552398449996034e-05 loss: 0.2016 (0.2077) time: 2.8890 data: 0.0086 max mem: 33300 +Epoch: [3] [4000/4276] eta: 0:14:53 lr: 4.554974010310909e-05 loss: 0.1831 (0.2077) time: 2.8982 data: 0.0080 max mem: 33300 +Epoch: [3] [4010/4276] eta: 0:14:20 lr: 4.554708173898372e-05 loss: 0.1851 (0.2077) time: 2.9268 data: 0.0079 max mem: 33300 +Epoch: [3] [4020/4276] eta: 0:13:48 lr: 4.5544423357618686e-05 loss: 0.1998 (0.2077) time: 2.9443 data: 0.0073 max mem: 33300 +Epoch: [3] [4030/4276] eta: 0:13:15 lr: 4.554176495901277e-05 loss: 0.2065 (0.2077) time: 2.9440 data: 0.0072 max mem: 33300 +Epoch: [3] [4040/4276] eta: 0:12:43 lr: 4.553910654316473e-05 loss: 0.2071 (0.2077) time: 2.9352 data: 0.0073 max mem: 33300 +Epoch: [3] [4050/4276] eta: 0:12:10 lr: 4.5536448110073346e-05 loss: 0.1877 (0.2077) time: 2.9219 data: 0.0082 max mem: 33300 +Epoch: [3] [4060/4276] eta: 0:11:38 lr: 4.553378965973737e-05 loss: 0.1877 (0.2077) time: 2.8979 data: 0.0088 max mem: 33300 +Epoch: [3] [4070/4276] eta: 0:11:05 lr: 4.5531131192155604e-05 loss: 0.2049 (0.2077) time: 2.8893 data: 0.0090 max mem: 33300 +Epoch: [3] [4080/4276] eta: 0:10:33 lr: 4.552847270732678e-05 loss: 0.2044 (0.2077) time: 2.9011 data: 0.0091 max mem: 33300 +Epoch: [3] [4090/4276] eta: 0:10:00 lr: 4.552581420524969e-05 loss: 0.2044 (0.2077) time: 2.8980 data: 0.0090 max mem: 33300 +Epoch: [3] [4100/4276] eta: 0:09:28 lr: 4.552315568592309e-05 loss: 0.2077 (0.2077) time: 2.8872 data: 0.0089 max mem: 33300 +Epoch: [3] [4110/4276] eta: 0:08:55 lr: 4.552049714934576e-05 loss: 0.2102 (0.2077) time: 2.8875 data: 0.0090 max mem: 33300 +Epoch: [3] [4120/4276] eta: 0:08:23 lr: 4.5517838595516465e-05 loss: 0.2066 (0.2077) time: 2.8887 data: 0.0095 max mem: 33300 +Epoch: [3] [4130/4276] eta: 0:07:51 lr: 4.551518002443397e-05 loss: 0.2012 (0.2077) time: 2.8895 data: 0.0095 max mem: 33300 +Epoch: [3] [4140/4276] eta: 0:07:18 lr: 4.5512521436097047e-05 loss: 0.1924 (0.2077) time: 2.8895 data: 0.0095 max mem: 33300 +Epoch: [3] [4150/4276] eta: 0:06:46 lr: 4.550986283050447e-05 loss: 0.1904 (0.2077) time: 2.8895 data: 0.0099 max mem: 33300 +Epoch: [3] [4160/4276] eta: 0:06:14 lr: 4.5507204207654994e-05 loss: 0.1904 (0.2077) time: 2.8896 data: 0.0102 max mem: 33300 +Epoch: [3] [4170/4276] eta: 0:05:41 lr: 4.550454556754739e-05 loss: 0.2184 (0.2077) time: 2.8899 data: 0.0100 max mem: 33300 +Epoch: [3] [4180/4276] eta: 0:05:09 lr: 4.5501886910180426e-05 loss: 0.2048 (0.2077) time: 2.8894 data: 0.0098 max mem: 33300 +Epoch: [3] [4190/4276] eta: 0:04:37 lr: 4.549922823555288e-05 loss: 0.1954 (0.2077) time: 2.8886 data: 0.0099 max mem: 33300 +Epoch: [3] [4200/4276] eta: 0:04:04 lr: 4.5496569543663506e-05 loss: 0.2003 (0.2078) time: 2.8908 data: 0.0102 max mem: 33300 +Epoch: [3] [4210/4276] eta: 0:03:32 lr: 4.549391083451107e-05 loss: 0.2128 (0.2078) time: 2.9024 data: 0.0096 max mem: 33300 +Epoch: [3] [4220/4276] eta: 0:03:00 lr: 4.549125210809435e-05 loss: 0.2140 (0.2078) time: 2.9278 data: 0.0081 max mem: 33300 +Epoch: [3] [4230/4276] eta: 0:02:28 lr: 4.548859336441211e-05 loss: 0.2345 (0.2079) time: 2.9421 data: 0.0073 max mem: 33300 +Epoch: [3] [4240/4276] eta: 0:01:55 lr: 4.548593460346312e-05 loss: 0.2225 (0.2079) time: 2.9411 data: 0.0075 max mem: 33300 +Epoch: [3] [4250/4276] eta: 0:01:23 lr: 4.5483275825246125e-05 loss: 0.2051 (0.2079) time: 2.9507 data: 0.0077 max mem: 33300 +Epoch: [3] [4260/4276] eta: 0:00:51 lr: 4.548061702975991e-05 loss: 0.2158 (0.2080) time: 2.9501 data: 0.0082 max mem: 33300 +Epoch: [3] [4270/4276] eta: 0:00:19 lr: 4.5477958217003254e-05 loss: 0.2126 (0.2080) time: 2.9358 data: 0.0077 max mem: 33300 +Epoch: [3] Total time: 3:49:13 +Test: [ 0/21770] eta: 11:04:26 time: 1.8313 data: 1.7931 max mem: 33300 +Test: [ 100/21770] eta: 0:20:54 time: 0.0389 data: 0.0009 max mem: 33300 +Test: [ 200/21770] eta: 0:17:23 time: 0.0387 data: 0.0009 max mem: 33300 +Test: [ 300/21770] eta: 0:16:09 time: 0.0387 data: 0.0008 max mem: 33300 +Test: [ 400/21770] eta: 0:15:31 time: 0.0388 data: 0.0008 max mem: 33300 +Test: [ 500/21770] eta: 0:15:07 time: 0.0389 data: 0.0009 max mem: 33300 +Test: [ 600/21770] eta: 0:14:50 time: 0.0393 data: 0.0009 max mem: 33300 +Test: [ 700/21770] eta: 0:14:36 time: 0.0390 data: 0.0009 max mem: 33300 +Test: [ 800/21770] eta: 0:14:25 time: 0.0388 data: 0.0008 max mem: 33300 +Test: [ 900/21770] eta: 0:14:16 time: 0.0391 data: 0.0008 max mem: 33300 +Test: [ 1000/21770] eta: 0:14:08 time: 0.0392 data: 0.0009 max mem: 33300 +Test: [ 1100/21770] eta: 0:14:01 time: 0.0393 data: 0.0008 max mem: 33300 +Test: [ 1200/21770] eta: 0:13:54 time: 0.0392 data: 0.0009 max mem: 33300 +Test: [ 1300/21770] eta: 0:13:48 time: 0.0394 data: 0.0008 max mem: 33300 +Test: [ 1400/21770] eta: 0:13:43 time: 0.0393 data: 0.0009 max mem: 33300 +Test: [ 1500/21770] eta: 0:13:37 time: 0.0390 data: 0.0009 max mem: 33300 +Test: [ 1600/21770] eta: 0:13:31 time: 0.0392 data: 0.0009 max mem: 33300 +Test: [ 1700/21770] eta: 0:13:26 time: 0.0387 data: 0.0008 max mem: 33300 +Test: [ 1800/21770] eta: 0:13:20 time: 0.0389 data: 0.0009 max mem: 33300 +Test: [ 1900/21770] eta: 0:13:15 time: 0.0389 data: 0.0009 max mem: 33300 +Test: [ 2000/21770] eta: 0:13:10 time: 0.0389 data: 0.0009 max mem: 33300 +Test: [ 2100/21770] eta: 0:13:05 time: 0.0388 data: 0.0008 max mem: 33300 +Test: [ 2200/21770] eta: 0:13:00 time: 0.0388 data: 0.0009 max mem: 33300 +Test: [ 2300/21770] eta: 0:12:55 time: 0.0388 data: 0.0009 max mem: 33300 +Test: [ 2400/21770] eta: 0:12:50 time: 0.0394 data: 0.0009 max mem: 33300 +Test: [ 2500/21770] eta: 0:12:46 time: 0.0391 data: 0.0009 max mem: 33300 +Test: [ 2600/21770] eta: 0:12:41 time: 0.0392 data: 0.0009 max mem: 33300 +Test: [ 2700/21770] eta: 0:12:37 time: 0.0390 data: 0.0009 max mem: 33300 +Test: [ 2800/21770] eta: 0:12:33 time: 0.0392 data: 0.0009 max mem: 33300 +Test: [ 2900/21770] eta: 0:12:29 time: 0.0395 data: 0.0009 max mem: 33300 +Test: [ 3000/21770] eta: 0:12:25 time: 0.0400 data: 0.0008 max mem: 33300 +Test: [ 3100/21770] eta: 0:12:21 time: 0.0400 data: 0.0009 max mem: 33300 +Test: [ 3200/21770] eta: 0:12:17 time: 0.0399 data: 0.0008 max mem: 33300 +Test: [ 3300/21770] eta: 0:12:13 time: 0.0401 data: 0.0008 max mem: 33300 +Test: [ 3400/21770] eta: 0:12:09 time: 0.0399 data: 0.0008 max mem: 33300 +Test: [ 3500/21770] eta: 0:12:05 time: 0.0402 data: 0.0008 max mem: 33300 +Test: [ 3600/21770] eta: 0:12:02 time: 0.0400 data: 0.0009 max mem: 33300 +Test: [ 3700/21770] eta: 0:11:58 time: 0.0400 data: 0.0008 max mem: 33300 +Test: [ 3800/21770] eta: 0:11:54 time: 0.0400 data: 0.0009 max mem: 33300 +Test: [ 3900/21770] eta: 0:11:50 time: 0.0401 data: 0.0008 max mem: 33300 +Test: [ 4000/21770] eta: 0:11:46 time: 0.0399 data: 0.0009 max mem: 33300 +Test: [ 4100/21770] eta: 0:11:42 time: 0.0399 data: 0.0008 max mem: 33300 +Test: [ 4200/21770] eta: 0:11:38 time: 0.0399 data: 0.0009 max mem: 33300 +Test: [ 4300/21770] eta: 0:11:34 time: 0.0401 data: 0.0008 max mem: 33300 +Test: [ 4400/21770] eta: 0:11:31 time: 0.0398 data: 0.0008 max mem: 33300 +Test: [ 4500/21770] eta: 0:11:27 time: 0.0402 data: 0.0009 max mem: 33300 +Test: [ 4600/21770] eta: 0:11:23 time: 0.0398 data: 0.0008 max mem: 33300 +Test: [ 4700/21770] eta: 0:11:19 time: 0.0401 data: 0.0008 max mem: 33300 +Test: [ 4800/21770] eta: 0:11:15 time: 0.0398 data: 0.0009 max mem: 33300 +Test: [ 4900/21770] eta: 0:11:11 time: 0.0400 data: 0.0008 max mem: 33300 +Test: [ 5000/21770] eta: 0:11:07 time: 0.0399 data: 0.0008 max mem: 33300 +Test: [ 5100/21770] eta: 0:11:03 time: 0.0401 data: 0.0008 max mem: 33300 +Test: [ 5200/21770] eta: 0:10:59 time: 0.0400 data: 0.0009 max mem: 33300 +Test: [ 5300/21770] eta: 0:10:55 time: 0.0401 data: 0.0008 max mem: 33300 +Test: [ 5400/21770] eta: 0:10:51 time: 0.0399 data: 0.0008 max mem: 33300 +Test: [ 5500/21770] eta: 0:10:47 time: 0.0400 data: 0.0009 max mem: 33300 +Test: [ 5600/21770] eta: 0:10:43 time: 0.0399 data: 0.0009 max mem: 33300 +Test: [ 5700/21770] eta: 0:10:39 time: 0.0396 data: 0.0009 max mem: 33300 +Test: [ 5800/21770] eta: 0:10:36 time: 0.0400 data: 0.0009 max mem: 33300 +Test: [ 5900/21770] eta: 0:10:32 time: 0.0396 data: 0.0009 max mem: 33300 +Test: [ 6000/21770] eta: 0:10:28 time: 0.0395 data: 0.0009 max mem: 33300 +Test: [ 6100/21770] eta: 0:10:24 time: 0.0398 data: 0.0008 max mem: 33300 +Test: [ 6200/21770] eta: 0:10:20 time: 0.0392 data: 0.0009 max mem: 33300 +Test: [ 6300/21770] eta: 0:10:15 time: 0.0401 data: 0.0009 max mem: 33300 +Test: [ 6400/21770] eta: 0:10:12 time: 0.0398 data: 0.0008 max mem: 33300 +Test: [ 6500/21770] eta: 0:10:08 time: 0.0401 data: 0.0008 max mem: 33300 +Test: [ 6600/21770] eta: 0:10:04 time: 0.0399 data: 0.0008 max mem: 33300 +Test: [ 6700/21770] eta: 0:10:00 time: 0.0401 data: 0.0008 max mem: 33300 +Test: [ 6800/21770] eta: 0:09:56 time: 0.0398 data: 0.0008 max mem: 33300 +Test: [ 6900/21770] eta: 0:09:52 time: 0.0401 data: 0.0008 max mem: 33300 +Test: [ 7000/21770] eta: 0:09:48 time: 0.0399 data: 0.0008 max mem: 33300 +Test: [ 7100/21770] eta: 0:09:44 time: 0.0400 data: 0.0008 max mem: 33300 +Test: [ 7200/21770] eta: 0:09:40 time: 0.0400 data: 0.0008 max mem: 33300 +Test: [ 7300/21770] eta: 0:09:36 time: 0.0401 data: 0.0009 max mem: 33300 +Test: [ 7400/21770] eta: 0:09:32 time: 0.0400 data: 0.0008 max mem: 33300 +Test: [ 7500/21770] eta: 0:09:28 time: 0.0401 data: 0.0008 max mem: 33300 +Test: [ 7600/21770] eta: 0:09:24 time: 0.0400 data: 0.0008 max mem: 33300 +Test: [ 7700/21770] eta: 0:09:20 time: 0.0399 data: 0.0008 max mem: 33300 +Test: [ 7800/21770] eta: 0:09:16 time: 0.0399 data: 0.0008 max mem: 33300 +Test: [ 7900/21770] eta: 0:09:12 time: 0.0401 data: 0.0008 max mem: 33300 +Test: [ 8000/21770] eta: 0:09:08 time: 0.0383 data: 0.0009 max mem: 33300 +Test: [ 8100/21770] eta: 0:09:04 time: 0.0400 data: 0.0008 max mem: 33300 +Test: [ 8200/21770] eta: 0:09:00 time: 0.0397 data: 0.0008 max mem: 33300 +Test: [ 8300/21770] eta: 0:08:56 time: 0.0400 data: 0.0008 max mem: 33300 +Test: [ 8400/21770] eta: 0:08:52 time: 0.0400 data: 0.0008 max mem: 33300 +Test: [ 8500/21770] eta: 0:08:48 time: 0.0401 data: 0.0008 max mem: 33300 +Test: [ 8600/21770] eta: 0:08:44 time: 0.0399 data: 0.0008 max mem: 33300 +Test: [ 8700/21770] eta: 0:08:40 time: 0.0393 data: 0.0008 max mem: 33300 +Test: [ 8800/21770] eta: 0:08:36 time: 0.0399 data: 0.0009 max mem: 33300 +Test: [ 8900/21770] eta: 0:08:32 time: 0.0400 data: 0.0008 max mem: 33300 +Test: [ 9000/21770] eta: 0:08:28 time: 0.0395 data: 0.0008 max mem: 33300 +Test: [ 9100/21770] eta: 0:08:24 time: 0.0399 data: 0.0008 max mem: 33300 +Test: [ 9200/21770] eta: 0:08:20 time: 0.0398 data: 0.0008 max mem: 33300 +Test: [ 9300/21770] eta: 0:08:16 time: 0.0400 data: 0.0008 max mem: 33300 +Test: [ 9400/21770] eta: 0:08:12 time: 0.0400 data: 0.0008 max mem: 33300 +Test: [ 9500/21770] eta: 0:08:09 time: 0.0400 data: 0.0008 max mem: 33300 +Test: [ 9600/21770] eta: 0:08:05 time: 0.0399 data: 0.0008 max mem: 33300 +Test: [ 9700/21770] eta: 0:08:01 time: 0.0400 data: 0.0008 max mem: 33300 +Test: [ 9800/21770] eta: 0:07:57 time: 0.0399 data: 0.0008 max mem: 33300 +Test: [ 9900/21770] eta: 0:07:53 time: 0.0401 data: 0.0008 max mem: 33300 +Test: [10000/21770] eta: 0:07:49 time: 0.0400 data: 0.0008 max mem: 33300 +Test: [10100/21770] eta: 0:07:45 time: 0.0401 data: 0.0008 max mem: 33300 +Test: [10200/21770] eta: 0:07:41 time: 0.0400 data: 0.0008 max mem: 33300 +Test: [10300/21770] eta: 0:07:37 time: 0.0393 data: 0.0008 max mem: 33300 +Test: [10400/21770] eta: 0:07:33 time: 0.0378 data: 0.0009 max mem: 33300 +Test: [10500/21770] eta: 0:07:28 time: 0.0378 data: 0.0009 max mem: 33300 +Test: [10600/21770] eta: 0:07:24 time: 0.0378 data: 0.0008 max mem: 33300 +Test: [10700/21770] eta: 0:07:20 time: 0.0378 data: 0.0009 max mem: 33300 +Test: [10800/21770] eta: 0:07:16 time: 0.0377 data: 0.0009 max mem: 33300 +Test: [10900/21770] eta: 0:07:12 time: 0.0384 data: 0.0008 max mem: 33300 +Test: [11000/21770] eta: 0:07:07 time: 0.0386 data: 0.0008 max mem: 33300 +Test: [11100/21770] eta: 0:07:03 time: 0.0392 data: 0.0009 max mem: 33300 +Test: [11200/21770] eta: 0:06:59 time: 0.0387 data: 0.0009 max mem: 33300 +Test: [11300/21770] eta: 0:06:55 time: 0.0393 data: 0.0009 max mem: 33300 +Test: [11400/21770] eta: 0:06:51 time: 0.0387 data: 0.0008 max mem: 33300 +Test: [11500/21770] eta: 0:06:47 time: 0.0393 data: 0.0009 max mem: 33300 +Test: [11600/21770] eta: 0:06:43 time: 0.0385 data: 0.0009 max mem: 33300 +Test: [11700/21770] eta: 0:06:39 time: 0.0389 data: 0.0009 max mem: 33300 +Test: [11800/21770] eta: 0:06:35 time: 0.0389 data: 0.0008 max mem: 33300 +Test: [11900/21770] eta: 0:06:31 time: 0.0390 data: 0.0008 max mem: 33300 +Test: [12000/21770] eta: 0:06:27 time: 0.0388 data: 0.0008 max mem: 33300 +Test: [12100/21770] eta: 0:06:23 time: 0.0386 data: 0.0009 max mem: 33300 +Test: [12200/21770] eta: 0:06:19 time: 0.0384 data: 0.0009 max mem: 33300 +Test: [12300/21770] eta: 0:06:15 time: 0.0378 data: 0.0009 max mem: 33300 +Test: [12400/21770] eta: 0:06:11 time: 0.0382 data: 0.0009 max mem: 33300 +Test: [12500/21770] eta: 0:06:07 time: 0.0391 data: 0.0009 max mem: 33300 +Test: [12600/21770] eta: 0:06:03 time: 0.0391 data: 0.0009 max mem: 33300 +Test: [12700/21770] eta: 0:05:59 time: 0.0391 data: 0.0009 max mem: 33300 +Test: [12800/21770] eta: 0:05:55 time: 0.0390 data: 0.0009 max mem: 33300 +Test: [12900/21770] eta: 0:05:51 time: 0.0391 data: 0.0009 max mem: 33300 +Test: [13000/21770] eta: 0:05:47 time: 0.0393 data: 0.0009 max mem: 33300 +Test: [13100/21770] eta: 0:05:43 time: 0.0391 data: 0.0009 max mem: 33300 +Test: [13200/21770] eta: 0:05:39 time: 0.0393 data: 0.0009 max mem: 33300 +Test: [13300/21770] eta: 0:05:35 time: 0.0390 data: 0.0009 max mem: 33300 +Test: [13400/21770] eta: 0:05:31 time: 0.0390 data: 0.0008 max mem: 33300 +Test: [13500/21770] eta: 0:05:27 time: 0.0393 data: 0.0009 max mem: 33300 +Test: [13600/21770] eta: 0:05:23 time: 0.0389 data: 0.0009 max mem: 33300 +Test: [13700/21770] eta: 0:05:19 time: 0.0391 data: 0.0009 max mem: 33300 +Test: [13800/21770] eta: 0:05:15 time: 0.0392 data: 0.0009 max mem: 33300 +Test: [13900/21770] eta: 0:05:11 time: 0.0393 data: 0.0008 max mem: 33300 +Test: [14000/21770] eta: 0:05:07 time: 0.0390 data: 0.0009 max mem: 33300 +Test: [14100/21770] eta: 0:05:03 time: 0.0392 data: 0.0009 max mem: 33300 +Test: [14200/21770] eta: 0:04:59 time: 0.0397 data: 0.0008 max mem: 33300 +Test: [14300/21770] eta: 0:04:55 time: 0.0393 data: 0.0009 max mem: 33300 +Test: [14400/21770] eta: 0:04:51 time: 0.0394 data: 0.0008 max mem: 33300 +Test: [14500/21770] eta: 0:04:47 time: 0.0393 data: 0.0009 max mem: 33300 +Test: [14600/21770] eta: 0:04:43 time: 0.0396 data: 0.0008 max mem: 33300 +Test: [14700/21770] eta: 0:04:39 time: 0.0391 data: 0.0009 max mem: 33300 +Test: [14800/21770] eta: 0:04:35 time: 0.0394 data: 0.0009 max mem: 33300 +Test: [14900/21770] eta: 0:04:31 time: 0.0396 data: 0.0009 max mem: 33300 +Test: [15000/21770] eta: 0:04:27 time: 0.0395 data: 0.0008 max mem: 33300 +Test: [15100/21770] eta: 0:04:23 time: 0.0393 data: 0.0009 max mem: 33300 +Test: [15200/21770] eta: 0:04:19 time: 0.0394 data: 0.0008 max mem: 33300 +Test: [15300/21770] eta: 0:04:15 time: 0.0394 data: 0.0008 max mem: 33300 +Test: [15400/21770] eta: 0:04:12 time: 0.0396 data: 0.0009 max mem: 33300 +Test: [15500/21770] eta: 0:04:08 time: 0.0394 data: 0.0008 max mem: 33300 +Test: [15600/21770] eta: 0:04:04 time: 0.0397 data: 0.0009 max mem: 33300 +Test: [15700/21770] eta: 0:04:00 time: 0.0395 data: 0.0009 max mem: 33300 +Test: [15800/21770] eta: 0:03:56 time: 0.0394 data: 0.0009 max mem: 33300 +Test: [15900/21770] eta: 0:03:52 time: 0.0393 data: 0.0009 max mem: 33300 +Test: [16000/21770] eta: 0:03:48 time: 0.0397 data: 0.0008 max mem: 33300 +Test: [16100/21770] eta: 0:03:44 time: 0.0394 data: 0.0008 max mem: 33300 +Test: [16200/21770] eta: 0:03:40 time: 0.0392 data: 0.0008 max mem: 33300 +Test: [16300/21770] eta: 0:03:36 time: 0.0391 data: 0.0008 max mem: 33300 +Test: [16400/21770] eta: 0:03:32 time: 0.0393 data: 0.0008 max mem: 33300 +Test: [16500/21770] eta: 0:03:28 time: 0.0392 data: 0.0008 max mem: 33300 +Test: [16600/21770] eta: 0:03:24 time: 0.0393 data: 0.0008 max mem: 33300 +Test: [16700/21770] eta: 0:03:20 time: 0.0391 data: 0.0009 max mem: 33300 +Test: [16800/21770] eta: 0:03:16 time: 0.0393 data: 0.0008 max mem: 33300 +Test: [16900/21770] eta: 0:03:12 time: 0.0391 data: 0.0008 max mem: 33300 +Test: [17000/21770] eta: 0:03:08 time: 0.0395 data: 0.0008 max mem: 33300 +Test: [17100/21770] eta: 0:03:04 time: 0.0392 data: 0.0008 max mem: 33300 +Test: [17200/21770] eta: 0:03:00 time: 0.0393 data: 0.0008 max mem: 33300 +Test: [17300/21770] eta: 0:02:56 time: 0.0391 data: 0.0008 max mem: 33300 +Test: [17400/21770] eta: 0:02:52 time: 0.0394 data: 0.0008 max mem: 33300 +Test: [17500/21770] eta: 0:02:48 time: 0.0395 data: 0.0008 max mem: 33300 +Test: [17600/21770] eta: 0:02:44 time: 0.0393 data: 0.0008 max mem: 33300 +Test: [17700/21770] eta: 0:02:40 time: 0.0393 data: 0.0008 max mem: 33300 +Test: [17800/21770] eta: 0:02:36 time: 0.0393 data: 0.0008 max mem: 33300 +Test: [17900/21770] eta: 0:02:32 time: 0.0392 data: 0.0008 max mem: 33300 +Test: [18000/21770] eta: 0:02:29 time: 0.0386 data: 0.0009 max mem: 33300 +Test: [18100/21770] eta: 0:02:25 time: 0.0391 data: 0.0009 max mem: 33300 +Test: [18200/21770] eta: 0:02:21 time: 0.0394 data: 0.0008 max mem: 33300 +Test: [18300/21770] eta: 0:02:17 time: 0.0391 data: 0.0008 max mem: 33300 +Test: [18400/21770] eta: 0:02:13 time: 0.0391 data: 0.0008 max mem: 33300 +Test: [18500/21770] eta: 0:02:09 time: 0.0387 data: 0.0009 max mem: 33300 +Test: [18600/21770] eta: 0:02:05 time: 0.0378 data: 0.0008 max mem: 33300 +Test: [18700/21770] eta: 0:02:01 time: 0.0378 data: 0.0008 max mem: 33300 +Test: [18800/21770] eta: 0:01:57 time: 0.0378 data: 0.0008 max mem: 33300 +Test: [18900/21770] eta: 0:01:53 time: 0.0378 data: 0.0008 max mem: 33300 +Test: [19000/21770] eta: 0:01:49 time: 0.0378 data: 0.0009 max mem: 33300 +Test: [19100/21770] eta: 0:01:45 time: 0.0378 data: 0.0008 max mem: 33300 +Test: [19200/21770] eta: 0:01:41 time: 0.0377 data: 0.0008 max mem: 33300 +Test: [19300/21770] eta: 0:01:37 time: 0.0377 data: 0.0008 max mem: 33300 +Test: [19400/21770] eta: 0:01:33 time: 0.0378 data: 0.0008 max mem: 33300 +Test: [19500/21770] eta: 0:01:29 time: 0.0377 data: 0.0008 max mem: 33300 +Test: [19600/21770] eta: 0:01:25 time: 0.0382 data: 0.0008 max mem: 33300 +Test: [19700/21770] eta: 0:01:21 time: 0.0380 data: 0.0008 max mem: 33300 +Test: [19800/21770] eta: 0:01:17 time: 0.0381 data: 0.0008 max mem: 33300 +Test: [19900/21770] eta: 0:01:13 time: 0.0380 data: 0.0008 max mem: 33300 +Test: [20000/21770] eta: 0:01:09 time: 0.0382 data: 0.0008 max mem: 33300 +Test: [20100/21770] eta: 0:01:05 time: 0.0380 data: 0.0008 max mem: 33300 +Test: [20200/21770] eta: 0:01:01 time: 0.0378 data: 0.0008 max mem: 33300 +Test: [20300/21770] eta: 0:00:57 time: 0.0377 data: 0.0008 max mem: 33300 +Test: [20400/21770] eta: 0:00:53 time: 0.0380 data: 0.0008 max mem: 33300 +Test: [20500/21770] eta: 0:00:49 time: 0.0381 data: 0.0008 max mem: 33300 +Test: [20600/21770] eta: 0:00:46 time: 0.0382 data: 0.0008 max mem: 33300 +Test: [20700/21770] eta: 0:00:42 time: 0.0380 data: 0.0008 max mem: 33300 +Test: [20800/21770] eta: 0:00:38 time: 0.0381 data: 0.0008 max mem: 33300 +Test: [20900/21770] eta: 0:00:34 time: 0.0380 data: 0.0009 max mem: 33300 +Test: [21000/21770] eta: 0:00:30 time: 0.0381 data: 0.0008 max mem: 33300 +Test: [21100/21770] eta: 0:00:26 time: 0.0381 data: 0.0009 max mem: 33300 +Test: [21200/21770] eta: 0:00:22 time: 0.0382 data: 0.0009 max mem: 33300 +Test: [21300/21770] eta: 0:00:18 time: 0.0381 data: 0.0009 max mem: 33300 +Test: [21400/21770] eta: 0:00:14 time: 0.0382 data: 0.0009 max mem: 33300 +Test: [21500/21770] eta: 0:00:10 time: 0.0380 data: 0.0009 max mem: 33300 +Test: [21600/21770] eta: 0:00:06 time: 0.0382 data: 0.0009 max mem: 33300 +Test: [21700/21770] eta: 0:00:02 time: 0.0380 data: 0.0009 max mem: 33300 +Test: Total time: 0:14:15 +Final results: +Mean IoU is 0.00 + + precision@0.5 = 0.00 + precision@0.6 = 0.00 + precision@0.7 = 0.00 + precision@0.8 = 0.00 + precision@0.9 = 0.00 + overall IoU = 0.00 + mean IoU = 0.00 + +Mean accuracy for one-to-zero sample is 100.00 + +Average object IoU 0.0 +Overall IoU 0.0 +Epoch: [4] [ 0/4276] eta: 6:33:29 lr: 4.5476362921058924e-05 loss: 0.1850 (0.1850) time: 5.5214 data: 2.4344 max mem: 33300 +Epoch: [4] [ 10/4276] eta: 3:46:14 lr: 4.5473704080666955e-05 loss: 0.1933 (0.1966) time: 3.1819 data: 0.2276 max mem: 33300 +Epoch: [4] [ 20/4276] eta: 3:37:59 lr: 4.547104522300133e-05 loss: 0.1933 (0.2011) time: 2.9507 data: 0.0069 max mem: 33300 +Epoch: [4] [ 30/4276] eta: 3:34:26 lr: 4.5468386348060795e-05 loss: 0.1857 (0.2003) time: 2.9470 data: 0.0075 max mem: 33300 +Epoch: [4] [ 40/4276] eta: 3:32:27 lr: 4.5465727455844124e-05 loss: 0.1857 (0.1991) time: 2.9426 data: 0.0078 max mem: 33300 +Epoch: [4] [ 50/4276] eta: 3:31:06 lr: 4.546306854635009e-05 loss: 0.1938 (0.1987) time: 2.9461 data: 0.0078 max mem: 33300 +Epoch: [4] [ 60/4276] eta: 3:29:56 lr: 4.546040961957745e-05 loss: 0.1938 (0.1997) time: 2.9437 data: 0.0080 max mem: 33300 +Epoch: [4] [ 70/4276] eta: 3:28:59 lr: 4.545775067552497e-05 loss: 0.1909 (0.2001) time: 2.9407 data: 0.0080 max mem: 33300 +Epoch: [4] [ 80/4276] eta: 3:28:09 lr: 4.545509171419141e-05 loss: 0.1966 (0.2002) time: 2.9418 data: 0.0079 max mem: 33300 +Epoch: [4] [ 90/4276] eta: 3:27:20 lr: 4.545243273557555e-05 loss: 0.1865 (0.1976) time: 2.9384 data: 0.0077 max mem: 33300 +Epoch: [4] [ 100/4276] eta: 3:26:15 lr: 4.544977373967613e-05 loss: 0.1800 (0.2001) time: 2.9111 data: 0.0077 max mem: 33300 +Epoch: [4] [ 110/4276] eta: 3:25:09 lr: 4.544711472649193e-05 loss: 0.1897 (0.2007) time: 2.8767 data: 0.0082 max mem: 33300 +Epoch: [4] [ 120/4276] eta: 3:24:17 lr: 4.5444455696021716e-05 loss: 0.1897 (0.2004) time: 2.8783 data: 0.0081 max mem: 33300 +Epoch: [4] [ 130/4276] eta: 3:23:27 lr: 4.544179664826424e-05 loss: 0.2018 (0.2012) time: 2.8868 data: 0.0082 max mem: 33300 +Epoch: [4] [ 140/4276] eta: 3:22:33 lr: 4.543913758321828e-05 loss: 0.2086 (0.2013) time: 2.8721 data: 0.0087 max mem: 33300 +Epoch: [4] [ 150/4276] eta: 3:21:46 lr: 4.543647850088259e-05 loss: 0.1933 (0.2008) time: 2.8678 data: 0.0086 max mem: 33300 +Epoch: [4] [ 160/4276] eta: 3:21:11 lr: 4.543381940125594e-05 loss: 0.1912 (0.2010) time: 2.8919 data: 0.0087 max mem: 33300 +Epoch: [4] [ 170/4276] eta: 3:20:46 lr: 4.543116028433708e-05 loss: 0.2053 (0.2012) time: 2.9312 data: 0.0088 max mem: 33300 +Epoch: [4] [ 180/4276] eta: 3:20:06 lr: 4.542850115012478e-05 loss: 0.2053 (0.2020) time: 2.9187 data: 0.0086 max mem: 33300 +Epoch: [4] [ 190/4276] eta: 3:19:22 lr: 4.542584199861781e-05 loss: 0.2186 (0.2028) time: 2.8750 data: 0.0086 max mem: 33300 +Epoch: [4] [ 200/4276] eta: 3:18:40 lr: 4.542318282981493e-05 loss: 0.2222 (0.2038) time: 2.8648 data: 0.0086 max mem: 33300 +Epoch: [4] [ 210/4276] eta: 3:18:00 lr: 4.54205236437149e-05 loss: 0.2140 (0.2039) time: 2.8662 data: 0.0083 max mem: 33300 +Epoch: [4] [ 220/4276] eta: 3:17:18 lr: 4.541786444031647e-05 loss: 0.1998 (0.2034) time: 2.8614 data: 0.0089 max mem: 33300 +Epoch: [4] [ 230/4276] eta: 3:16:46 lr: 4.5415205219618424e-05 loss: 0.1896 (0.2023) time: 2.8769 data: 0.0098 max mem: 33300 +Epoch: [4] [ 240/4276] eta: 3:16:16 lr: 4.5412545981619505e-05 loss: 0.1871 (0.2022) time: 2.9066 data: 0.0092 max mem: 33300 +Epoch: [4] [ 250/4276] eta: 3:15:42 lr: 4.5409886726318496e-05 loss: 0.2046 (0.2033) time: 2.9023 data: 0.0089 max mem: 33300 +Epoch: [4] [ 260/4276] eta: 3:15:09 lr: 4.5407227453714135e-05 loss: 0.2160 (0.2038) time: 2.8909 data: 0.0094 max mem: 33300 +Epoch: [4] [ 270/4276] eta: 3:14:39 lr: 4.54045681638052e-05 loss: 0.2085 (0.2041) time: 2.9003 data: 0.0094 max mem: 33300 +Epoch: [4] [ 280/4276] eta: 3:14:10 lr: 4.5401908856590445e-05 loss: 0.1974 (0.2040) time: 2.9115 data: 0.0083 max mem: 33300 +Epoch: [4] [ 290/4276] eta: 3:13:39 lr: 4.539924953206863e-05 loss: 0.1974 (0.2036) time: 2.9077 data: 0.0078 max mem: 33300 +Epoch: [4] [ 300/4276] eta: 3:13:09 lr: 4.539659019023852e-05 loss: 0.1876 (0.2034) time: 2.9049 data: 0.0081 max mem: 33300 +Epoch: [4] [ 310/4276] eta: 3:12:37 lr: 4.539393083109888e-05 loss: 0.1877 (0.2029) time: 2.9038 data: 0.0084 max mem: 33300 +Epoch: [4] [ 320/4276] eta: 3:12:07 lr: 4.5391271454648466e-05 loss: 0.2010 (0.2035) time: 2.9022 data: 0.0087 max mem: 33300 +Epoch: [4] [ 330/4276] eta: 3:11:33 lr: 4.538861206088603e-05 loss: 0.2010 (0.2036) time: 2.8882 data: 0.0087 max mem: 33300 +Epoch: [4] [ 340/4276] eta: 3:10:59 lr: 4.538595264981034e-05 loss: 0.1950 (0.2033) time: 2.8732 data: 0.0085 max mem: 33300 +Epoch: [4] [ 350/4276] eta: 3:10:27 lr: 4.538329322142016e-05 loss: 0.1889 (0.2029) time: 2.8787 data: 0.0085 max mem: 33300 +Epoch: [4] [ 360/4276] eta: 3:09:55 lr: 4.538063377571425e-05 loss: 0.1960 (0.2034) time: 2.8811 data: 0.0084 max mem: 33300 +Epoch: [4] [ 370/4276] eta: 3:09:23 lr: 4.5377974312691354e-05 loss: 0.1926 (0.2028) time: 2.8848 data: 0.0085 max mem: 33300 +Epoch: [4] [ 380/4276] eta: 3:08:50 lr: 4.537531483235025e-05 loss: 0.1871 (0.2028) time: 2.8775 data: 0.0080 max mem: 33300 +Epoch: [4] [ 390/4276] eta: 3:08:19 lr: 4.53726553346897e-05 loss: 0.2042 (0.2030) time: 2.8757 data: 0.0076 max mem: 33300 +Epoch: [4] [ 400/4276] eta: 3:07:47 lr: 4.536999581970843e-05 loss: 0.2036 (0.2032) time: 2.8853 data: 0.0078 max mem: 33300 +Epoch: [4] [ 410/4276] eta: 3:07:17 lr: 4.536733628740524e-05 loss: 0.2003 (0.2030) time: 2.8868 data: 0.0075 max mem: 33300 +Epoch: [4] [ 420/4276] eta: 3:06:46 lr: 4.536467673777887e-05 loss: 0.2014 (0.2032) time: 2.8901 data: 0.0075 max mem: 33300 +Epoch: [4] [ 430/4276] eta: 3:06:15 lr: 4.536201717082808e-05 loss: 0.2016 (0.2033) time: 2.8866 data: 0.0077 max mem: 33300 +Epoch: [4] [ 440/4276] eta: 3:05:44 lr: 4.535935758655162e-05 loss: 0.2015 (0.2032) time: 2.8837 data: 0.0077 max mem: 33300 +Epoch: [4] [ 450/4276] eta: 3:05:13 lr: 4.5356697984948265e-05 loss: 0.2045 (0.2036) time: 2.8867 data: 0.0077 max mem: 33300 +Epoch: [4] [ 460/4276] eta: 3:04:43 lr: 4.5354038366016764e-05 loss: 0.1997 (0.2030) time: 2.8864 data: 0.0075 max mem: 33300 +Epoch: [4] [ 470/4276] eta: 3:04:13 lr: 4.5351378729755876e-05 loss: 0.1838 (0.2026) time: 2.8874 data: 0.0075 max mem: 33300 +Epoch: [4] [ 480/4276] eta: 3:03:43 lr: 4.5348719076164356e-05 loss: 0.1759 (0.2023) time: 2.8915 data: 0.0078 max mem: 33300 +Epoch: [4] [ 490/4276] eta: 3:03:12 lr: 4.534605940524097e-05 loss: 0.1790 (0.2022) time: 2.8905 data: 0.0078 max mem: 33300 +Epoch: [4] [ 500/4276] eta: 3:02:42 lr: 4.534339971698447e-05 loss: 0.2061 (0.2023) time: 2.8863 data: 0.0075 max mem: 33300 +Epoch: [4] [ 510/4276] eta: 3:02:12 lr: 4.534074001139362e-05 loss: 0.1917 (0.2019) time: 2.8887 data: 0.0077 max mem: 33300 +Epoch: [4] [ 520/4276] eta: 3:01:42 lr: 4.533808028846716e-05 loss: 0.1855 (0.2020) time: 2.8897 data: 0.0080 max mem: 33300 +Epoch: [4] [ 530/4276] eta: 3:01:12 lr: 4.533542054820386e-05 loss: 0.1906 (0.2019) time: 2.8854 data: 0.0079 max mem: 33300 +Epoch: [4] [ 540/4276] eta: 3:00:42 lr: 4.533276079060248e-05 loss: 0.1919 (0.2018) time: 2.8870 data: 0.0078 max mem: 33300 +Epoch: [4] [ 550/4276] eta: 3:00:11 lr: 4.5330101015661766e-05 loss: 0.2059 (0.2019) time: 2.8850 data: 0.0079 max mem: 33300 +Epoch: [4] [ 560/4276] eta: 2:59:41 lr: 4.5327441223380486e-05 loss: 0.2067 (0.2021) time: 2.8801 data: 0.0079 max mem: 33300 +Epoch: [4] [ 570/4276] eta: 2:59:10 lr: 4.5324781413757385e-05 loss: 0.2022 (0.2021) time: 2.8736 data: 0.0076 max mem: 33300 +Epoch: [4] [ 580/4276] eta: 2:58:43 lr: 4.532212158679123e-05 loss: 0.1887 (0.2020) time: 2.9014 data: 0.0086 max mem: 33300 +Epoch: [4] [ 590/4276] eta: 2:58:16 lr: 4.531946174248077e-05 loss: 0.1863 (0.2016) time: 2.9355 data: 0.0085 max mem: 33300 +Epoch: [4] [ 600/4276] eta: 2:57:49 lr: 4.531680188082476e-05 loss: 0.1863 (0.2016) time: 2.9361 data: 0.0073 max mem: 33300 +Epoch: [4] [ 610/4276] eta: 2:57:22 lr: 4.5314142001821956e-05 loss: 0.1827 (0.2014) time: 2.9363 data: 0.0072 max mem: 33300 +Epoch: [4] [ 620/4276] eta: 2:56:55 lr: 4.5311482105471125e-05 loss: 0.1849 (0.2014) time: 2.9363 data: 0.0072 max mem: 33300 +Epoch: [4] [ 630/4276] eta: 2:56:26 lr: 4.5308822191771006e-05 loss: 0.1977 (0.2014) time: 2.9234 data: 0.0077 max mem: 33300 +Epoch: [4] [ 640/4276] eta: 2:55:57 lr: 4.5306162260720366e-05 loss: 0.1998 (0.2014) time: 2.9063 data: 0.0085 max mem: 33300 +Epoch: [4] [ 650/4276] eta: 2:55:28 lr: 4.5303502312317944e-05 loss: 0.1919 (0.2013) time: 2.9008 data: 0.0087 max mem: 33300 +Epoch: [4] [ 660/4276] eta: 2:54:59 lr: 4.5300842346562514e-05 loss: 0.2075 (0.2016) time: 2.9047 data: 0.0084 max mem: 33300 +Epoch: [4] [ 670/4276] eta: 2:54:32 lr: 4.529818236345282e-05 loss: 0.1950 (0.2014) time: 2.9244 data: 0.0084 max mem: 33300 +Epoch: [4] [ 680/4276] eta: 2:54:04 lr: 4.529552236298762e-05 loss: 0.1793 (0.2011) time: 2.9363 data: 0.0080 max mem: 33300 +Epoch: [4] [ 690/4276] eta: 2:53:36 lr: 4.529286234516568e-05 loss: 0.1914 (0.2010) time: 2.9273 data: 0.0075 max mem: 33300 +Epoch: [4] [ 700/4276] eta: 2:53:07 lr: 4.529020230998572e-05 loss: 0.2060 (0.2012) time: 2.9101 data: 0.0076 max mem: 33300 +Epoch: [4] [ 710/4276] eta: 2:52:37 lr: 4.528754225744653e-05 loss: 0.2228 (0.2014) time: 2.8971 data: 0.0081 max mem: 33300 +Epoch: [4] [ 720/4276] eta: 2:52:09 lr: 4.528488218754684e-05 loss: 0.1983 (0.2013) time: 2.9090 data: 0.0084 max mem: 33300 +Epoch: [4] [ 730/4276] eta: 2:51:40 lr: 4.528222210028541e-05 loss: 0.1921 (0.2016) time: 2.9154 data: 0.0084 max mem: 33300 +Epoch: [4] [ 740/4276] eta: 2:51:12 lr: 4.5279561995661005e-05 loss: 0.1966 (0.2016) time: 2.9171 data: 0.0086 max mem: 33300 +Epoch: [4] [ 750/4276] eta: 2:50:44 lr: 4.5276901873672374e-05 loss: 0.1907 (0.2015) time: 2.9227 data: 0.0086 max mem: 33300 +Epoch: [4] [ 760/4276] eta: 2:50:20 lr: 4.527424173431825e-05 loss: 0.1839 (0.2014) time: 2.9717 data: 0.0081 max mem: 33300 +Epoch: [4] [ 770/4276] eta: 2:50:02 lr: 4.5271581577597415e-05 loss: 0.1864 (0.2015) time: 3.0825 data: 0.0078 max mem: 33300 +Epoch: [4] [ 780/4276] eta: 2:49:47 lr: 4.52689214035086e-05 loss: 0.2050 (0.2014) time: 3.1831 data: 0.0078 max mem: 33300 +Epoch: [4] [ 790/4276] eta: 2:49:29 lr: 4.526626121205057e-05 loss: 0.1992 (0.2014) time: 3.1948 data: 0.0076 max mem: 33300 +Epoch: [4] [ 800/4276] eta: 2:49:15 lr: 4.5263601003222074e-05 loss: 0.1984 (0.2014) time: 3.2229 data: 0.0079 max mem: 33300 +Epoch: [4] [ 810/4276] eta: 2:48:58 lr: 4.5260940777021854e-05 loss: 0.1820 (0.2014) time: 3.2365 data: 0.0083 max mem: 33300 +Epoch: [4] [ 820/4276] eta: 2:48:42 lr: 4.5258280533448684e-05 loss: 0.2011 (0.2013) time: 3.2155 data: 0.0080 max mem: 33300 +Epoch: [4] [ 830/4276] eta: 2:48:25 lr: 4.5255620272501296e-05 loss: 0.1870 (0.2015) time: 3.2316 data: 0.0081 max mem: 33300 +Epoch: [4] [ 840/4276] eta: 2:48:07 lr: 4.525295999417845e-05 loss: 0.1901 (0.2017) time: 3.2167 data: 0.0086 max mem: 33300 +Epoch: [4] [ 850/4276] eta: 2:47:48 lr: 4.5250299698478906e-05 loss: 0.1859 (0.2016) time: 3.2093 data: 0.0083 max mem: 33300 +Epoch: [4] [ 860/4276] eta: 2:47:26 lr: 4.524763938540139e-05 loss: 0.1889 (0.2017) time: 3.1638 data: 0.0075 max mem: 33300 +Epoch: [4] [ 870/4276] eta: 2:47:09 lr: 4.524497905494468e-05 loss: 0.1970 (0.2016) time: 3.1878 data: 0.0077 max mem: 33300 +Epoch: [4] [ 880/4276] eta: 2:46:46 lr: 4.524231870710751e-05 loss: 0.1933 (0.2018) time: 3.1816 data: 0.0081 max mem: 33300 +Epoch: [4] [ 890/4276] eta: 2:46:27 lr: 4.5239658341888645e-05 loss: 0.2103 (0.2019) time: 3.1599 data: 0.0079 max mem: 33300 +Epoch: [4] [ 900/4276] eta: 2:46:04 lr: 4.523699795928682e-05 loss: 0.2179 (0.2019) time: 3.1679 data: 0.0075 max mem: 33300 +Epoch: [4] [ 910/4276] eta: 2:45:43 lr: 4.52343375593008e-05 loss: 0.2004 (0.2020) time: 3.1577 data: 0.0077 max mem: 33300 +Epoch: [4] [ 920/4276] eta: 2:45:22 lr: 4.523167714192932e-05 loss: 0.2004 (0.2020) time: 3.1899 data: 0.0087 max mem: 33300 +Epoch: [4] [ 930/4276] eta: 2:45:02 lr: 4.5229016707171145e-05 loss: 0.1907 (0.2019) time: 3.2015 data: 0.0096 max mem: 33300 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mem: 33300 +Epoch: [4] [1020/4276] eta: 2:41:48 lr: 4.5205072011739716e-05 loss: 0.1892 (0.2015) time: 3.1979 data: 0.0079 max mem: 33300 +Epoch: [4] [1030/4276] eta: 2:41:25 lr: 4.520241140304575e-05 loss: 0.1898 (0.2015) time: 3.1923 data: 0.0080 max mem: 33300 +Epoch: [4] [1040/4276] eta: 2:41:01 lr: 4.519975077695132e-05 loss: 0.1831 (0.2014) time: 3.1871 data: 0.0083 max mem: 33300 +Epoch: [4] [1050/4276] eta: 2:40:40 lr: 4.5197090133455185e-05 loss: 0.1868 (0.2015) time: 3.2273 data: 0.0088 max mem: 33300 +Epoch: [4] [1060/4276] eta: 2:40:16 lr: 4.5194429472556085e-05 loss: 0.1964 (0.2016) time: 3.2172 data: 0.0087 max mem: 33300 +Epoch: [4] [1070/4276] eta: 2:39:54 lr: 4.519176879425276e-05 loss: 0.1878 (0.2015) time: 3.2185 data: 0.0092 max mem: 33300 +Epoch: [4] [1080/4276] eta: 2:39:30 lr: 4.518910809854398e-05 loss: 0.1979 (0.2014) time: 3.2239 data: 0.0095 max mem: 33300 +Epoch: [4] [1090/4276] eta: 2:39:08 lr: 4.518644738542847e-05 loss: 0.1979 (0.2013) time: 3.2134 data: 0.0091 max mem: 33300 +Epoch: [4] [1100/4276] eta: 2:38:43 lr: 4.5183786654904985e-05 loss: 0.1712 (0.2012) time: 3.2299 data: 0.0088 max mem: 33300 +Epoch: [4] [1110/4276] eta: 2:38:16 lr: 4.518112590697228e-05 loss: 0.1889 (0.2012) time: 3.1506 data: 0.0087 max mem: 33300 +Epoch: [4] [1120/4276] eta: 2:37:49 lr: 4.5178465141629085e-05 loss: 0.1974 (0.2012) time: 3.1027 data: 0.0085 max mem: 33300 +Epoch: [4] [1130/4276] eta: 2:37:19 lr: 4.517580435887417e-05 loss: 0.1979 (0.2011) time: 3.0427 data: 0.0087 max mem: 33300 +Epoch: [4] [1140/4276] eta: 2:36:46 lr: 4.517314355870625e-05 loss: 0.1842 (0.2010) time: 2.9493 data: 0.0085 max mem: 33300 +Epoch: [4] [1150/4276] eta: 2:36:14 lr: 4.51704827411241e-05 loss: 0.1899 (0.2010) time: 2.9051 data: 0.0086 max mem: 33300 +Epoch: [4] [1160/4276] eta: 2:35:40 lr: 4.516782190612646e-05 loss: 0.1980 (0.2011) time: 2.8872 data: 0.0087 max mem: 33300 +Epoch: [4] [1170/4276] eta: 2:35:08 lr: 4.5165161053712066e-05 loss: 0.2069 (0.2012) time: 2.8850 data: 0.0084 max mem: 33300 +Epoch: [4] [1180/4276] eta: 2:34:35 lr: 4.516250018387967e-05 loss: 0.2069 (0.2011) time: 2.8896 data: 0.0084 max mem: 33300 +Epoch: [4] [1190/4276] eta: 2:34:02 lr: 4.515983929662801e-05 loss: 0.1943 (0.2011) time: 2.8844 data: 0.0081 max mem: 33300 +Epoch: [4] [1200/4276] eta: 2:33:29 lr: 4.515717839195586e-05 loss: 0.2036 (0.2010) time: 2.8806 data: 0.0082 max mem: 33300 +Epoch: [4] [1210/4276] eta: 2:32:57 lr: 4.515451746986193e-05 loss: 0.1829 (0.2010) time: 2.8899 data: 0.0082 max mem: 33300 +Epoch: [4] [1220/4276] eta: 2:32:26 lr: 4.515185653034498e-05 loss: 0.1848 (0.2009) time: 2.9340 data: 0.0080 max mem: 33300 +Epoch: [4] [1230/4276] eta: 2:31:56 lr: 4.514919557340375e-05 loss: 0.1851 (0.2009) time: 2.9699 data: 0.0087 max mem: 33300 +Epoch: [4] [1240/4276] eta: 2:31:25 lr: 4.5146534599037e-05 loss: 0.1851 (0.2008) time: 2.9648 data: 0.0085 max mem: 33300 +Epoch: [4] [1250/4276] eta: 2:30:53 lr: 4.5143873607243455e-05 loss: 0.1881 (0.2007) time: 2.9425 data: 0.0078 max mem: 33300 +Epoch: [4] [1260/4276] eta: 2:30:23 lr: 4.514121259802187e-05 loss: 0.1738 (0.2006) time: 2.9516 data: 0.0080 max mem: 33300 +Epoch: [4] [1270/4276] eta: 2:29:53 lr: 4.513855157137099e-05 loss: 0.1813 (0.2005) time: 2.9755 data: 0.0076 max mem: 33300 +Epoch: [4] [1280/4276] eta: 2:29:22 lr: 4.513589052728956e-05 loss: 0.1881 (0.2005) time: 2.9567 data: 0.0075 max mem: 33300 +Epoch: [4] [1290/4276] eta: 2:28:49 lr: 4.513322946577632e-05 loss: 0.2089 (0.2006) time: 2.9146 data: 0.0081 max mem: 33300 +Epoch: [4] [1300/4276] eta: 2:28:17 lr: 4.513056838683001e-05 loss: 0.1880 (0.2005) time: 2.8859 data: 0.0085 max mem: 33300 +Epoch: [4] [1310/4276] eta: 2:27:44 lr: 4.5127907290449384e-05 loss: 0.1880 (0.2005) time: 2.8806 data: 0.0083 max mem: 33300 +Epoch: [4] [1320/4276] eta: 2:27:12 lr: 4.5125246176633175e-05 loss: 0.2068 (0.2006) time: 2.8811 data: 0.0085 max mem: 33300 +Epoch: [4] [1330/4276] eta: 2:26:40 lr: 4.5122585045380135e-05 loss: 0.1840 (0.2004) time: 2.8848 data: 0.0084 max mem: 33300 +Epoch: [4] [1340/4276] eta: 2:26:08 lr: 4.5119923896689e-05 loss: 0.1765 (0.2003) time: 2.8947 data: 0.0083 max mem: 33300 +Epoch: [4] [1350/4276] eta: 2:25:37 lr: 4.5117262730558516e-05 loss: 0.1858 (0.2003) time: 2.9167 data: 0.0081 max mem: 33300 +Epoch: [4] [1360/4276] eta: 2:25:07 lr: 4.511460154698743e-05 loss: 0.1967 (0.2003) time: 2.9441 data: 0.0083 max mem: 33300 +Epoch: [4] [1370/4276] eta: 2:24:36 lr: 4.511194034597448e-05 loss: 0.1867 (0.2002) time: 2.9522 data: 0.0090 max mem: 33300 +Epoch: [4] [1380/4276] eta: 2:24:06 lr: 4.5109279127518406e-05 loss: 0.1981 (0.2003) time: 2.9514 data: 0.0096 max mem: 33300 +Epoch: [4] [1390/4276] eta: 2:23:35 lr: 4.5106617891617955e-05 loss: 0.2000 (0.2003) time: 2.9517 data: 0.0092 max mem: 33300 +Epoch: [4] [1400/4276] eta: 2:23:04 lr: 4.510395663827187e-05 loss: 0.2001 (0.2004) time: 2.9471 data: 0.0084 max mem: 33300 +Epoch: [4] [1410/4276] eta: 2:22:34 lr: 4.510129536747888e-05 loss: 0.2001 (0.2004) time: 2.9518 data: 0.0086 max mem: 33300 +Epoch: [4] [1420/4276] eta: 2:22:02 lr: 4.509863407923775e-05 loss: 0.1962 (0.2005) time: 2.9312 data: 0.0089 max mem: 33300 +Epoch: [4] [1430/4276] eta: 2:21:32 lr: 4.50959727735472e-05 loss: 0.1888 (0.2004) time: 2.9276 data: 0.0092 max mem: 33300 +Epoch: [4] [1440/4276] eta: 2:21:01 lr: 4.509331145040599e-05 loss: 0.1974 (0.2006) time: 2.9318 data: 0.0092 max mem: 33300 +Epoch: [4] [1450/4276] eta: 2:20:30 lr: 4.509065010981284e-05 loss: 0.2070 (0.2005) time: 2.9221 data: 0.0084 max mem: 33300 +Epoch: [4] [1460/4276] eta: 2:19:59 lr: 4.5087988751766515e-05 loss: 0.1890 (0.2005) time: 2.9223 data: 0.0078 max mem: 33300 +Epoch: [4] [1470/4276] eta: 2:19:27 lr: 4.508532737626574e-05 loss: 0.2030 (0.2006) time: 2.9014 data: 0.0077 max mem: 33300 +Epoch: [4] [1480/4276] eta: 2:18:55 lr: 4.508266598330925e-05 loss: 0.2042 (0.2006) time: 2.8822 data: 0.0081 max mem: 33300 +Epoch: [4] [1490/4276] eta: 2:18:24 lr: 4.5080004572895795e-05 loss: 0.1844 (0.2005) time: 2.8829 data: 0.0080 max mem: 33300 +Epoch: [4] [1500/4276] eta: 2:17:52 lr: 4.507734314502412e-05 loss: 0.1844 (0.2005) time: 2.8814 data: 0.0075 max mem: 33300 +Epoch: [4] [1510/4276] eta: 2:17:21 lr: 4.507468169969296e-05 loss: 0.1798 (0.2005) time: 2.8909 data: 0.0075 max mem: 33300 +Epoch: [4] [1520/4276] eta: 2:16:50 lr: 4.507202023690106e-05 loss: 0.1806 (0.2004) time: 2.9144 data: 0.0076 max mem: 33300 +Epoch: [4] [1530/4276] eta: 2:16:19 lr: 4.506935875664714e-05 loss: 0.1868 (0.2004) time: 2.9152 data: 0.0078 max mem: 33300 +Epoch: [4] [1540/4276] eta: 2:15:47 lr: 4.506669725892996e-05 loss: 0.1915 (0.2004) time: 2.8972 data: 0.0078 max mem: 33300 +Epoch: [4] [1550/4276] eta: 2:15:16 lr: 4.506403574374827e-05 loss: 0.1993 (0.2005) time: 2.8830 data: 0.0079 max mem: 33300 +Epoch: [4] [1560/4276] eta: 2:14:45 lr: 4.5061374211100774e-05 loss: 0.1835 (0.2004) time: 2.8865 data: 0.0078 max mem: 33300 +Epoch: [4] [1570/4276] eta: 2:14:14 lr: 4.5058712660986235e-05 loss: 0.1830 (0.2003) time: 2.8999 data: 0.0079 max mem: 33300 +Epoch: [4] [1580/4276] eta: 2:13:44 lr: 4.505605109340339e-05 loss: 0.1804 (0.2003) time: 2.9454 data: 0.0083 max mem: 33300 +Epoch: [4] [1590/4276] eta: 2:13:14 lr: 4.505338950835098e-05 loss: 0.1921 (0.2003) time: 2.9646 data: 0.0085 max mem: 33300 +Epoch: [4] [1600/4276] eta: 2:12:44 lr: 4.5050727905827726e-05 loss: 0.1921 (0.2003) time: 2.9612 data: 0.0079 max mem: 33300 +Epoch: [4] [1610/4276] eta: 2:12:14 lr: 4.5048066285832386e-05 loss: 0.1747 (0.2002) time: 2.9574 data: 0.0076 max mem: 33300 +Epoch: [4] [1620/4276] eta: 2:11:43 lr: 4.50454046483637e-05 loss: 0.1832 (0.2001) time: 2.9368 data: 0.0077 max mem: 33300 +Epoch: [4] [1630/4276] eta: 2:11:13 lr: 4.504274299342038e-05 loss: 0.1926 (0.2002) time: 2.9426 data: 0.0079 max mem: 33300 +Epoch: [4] [1640/4276] eta: 2:10:43 lr: 4.504008132100119e-05 loss: 0.1947 (0.2003) time: 2.9561 data: 0.0079 max mem: 33300 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mem: 33300 +Epoch: [4] [1730/4276] eta: 2:06:08 lr: 4.501612548260562e-05 loss: 0.2022 (0.2005) time: 2.9528 data: 0.0085 max mem: 33300 +Epoch: [4] [1740/4276] eta: 2:05:40 lr: 4.501346363535819e-05 loss: 0.2046 (0.2006) time: 3.0219 data: 0.0082 max mem: 33300 +Epoch: [4] [1750/4276] eta: 2:05:12 lr: 4.5010801770620996e-05 loss: 0.2046 (0.2006) time: 3.0810 data: 0.0079 max mem: 33300 +Epoch: [4] [1760/4276] eta: 2:04:43 lr: 4.500813988839276e-05 loss: 0.1946 (0.2005) time: 3.0701 data: 0.0080 max mem: 33300 +Epoch: [4] [1770/4276] eta: 2:04:15 lr: 4.5005477988672216e-05 loss: 0.2000 (0.2005) time: 3.0637 data: 0.0082 max mem: 33300 +Epoch: [4] [1780/4276] eta: 2:03:47 lr: 4.500281607145812e-05 loss: 0.2005 (0.2005) time: 3.0910 data: 0.0081 max mem: 33300 +Epoch: [4] [1790/4276] eta: 2:03:19 lr: 4.500015413674918e-05 loss: 0.1953 (0.2005) time: 3.0991 data: 0.0081 max mem: 33300 +Epoch: [4] [1800/4276] eta: 2:02:51 lr: 4.499749218454414e-05 loss: 0.2034 (0.2005) time: 3.0989 data: 0.0084 max mem: 33300 +Epoch: [4] [1810/4276] eta: 2:02:23 lr: 4.499483021484175e-05 loss: 0.2056 (0.2005) time: 3.1107 data: 0.0083 max mem: 33300 +Epoch: [4] [1820/4276] eta: 2:01:56 lr: 4.499216822764073e-05 loss: 0.1877 (0.2004) time: 3.1507 data: 0.0090 max mem: 33300 +Epoch: [4] [1830/4276] eta: 2:01:31 lr: 4.498950622293983e-05 loss: 0.1830 (0.2005) time: 3.2692 data: 0.0090 max mem: 33300 +Epoch: [4] [1840/4276] eta: 2:01:06 lr: 4.498684420073776e-05 loss: 0.1867 (0.2005) time: 3.3320 data: 0.0085 max mem: 33300 +Epoch: [4] [1850/4276] eta: 2:00:39 lr: 4.498418216103327e-05 loss: 0.1930 (0.2006) time: 3.2579 data: 0.0082 max mem: 33300 +Epoch: [4] [1860/4276] eta: 2:00:15 lr: 4.4981520103825095e-05 loss: 0.2072 (0.2006) time: 3.3164 data: 0.0084 max mem: 33300 +Epoch: [4] [1870/4276] eta: 1:59:48 lr: 4.4978858029111956e-05 loss: 0.2003 (0.2006) time: 3.3107 data: 0.0087 max mem: 33300 +Epoch: [4] [1880/4276] eta: 1:59:22 lr: 4.4976195936892604e-05 loss: 0.1964 (0.2006) time: 3.2672 data: 0.0085 max mem: 33300 +Epoch: [4] [1890/4276] eta: 1:58:56 lr: 4.4973533827165765e-05 loss: 0.1952 (0.2006) time: 3.2917 data: 0.0085 max mem: 33300 +Epoch: [4] [1900/4276] eta: 1:58:29 lr: 4.497087169993018e-05 loss: 0.1811 (0.2004) time: 3.2436 data: 0.0089 max mem: 33300 +Epoch: [4] [1910/4276] eta: 1:58:03 lr: 4.496820955518456e-05 loss: 0.1811 (0.2004) time: 3.2608 data: 0.0097 max mem: 33300 +Epoch: [4] [1920/4276] eta: 1:57:35 lr: 4.496554739292766e-05 loss: 0.1855 (0.2004) time: 3.2480 data: 0.0106 max mem: 33300 +Epoch: [4] [1930/4276] eta: 1:57:09 lr: 4.496288521315821e-05 loss: 0.1908 (0.2004) time: 3.2505 data: 0.0098 max mem: 33300 +Epoch: [4] [1940/4276] eta: 1:56:42 lr: 4.496022301587492e-05 loss: 0.2100 (0.2005) time: 3.2761 data: 0.0087 max mem: 33300 +Epoch: [4] [1950/4276] eta: 1:56:17 lr: 4.495756080107655e-05 loss: 0.1973 (0.2005) time: 3.3241 data: 0.0090 max mem: 33300 +Epoch: [4] [1960/4276] eta: 1:55:55 lr: 4.495489856876183e-05 loss: 0.1933 (0.2004) time: 3.5270 data: 0.0097 max mem: 33300 +Epoch: [4] [1970/4276] eta: 1:55:29 lr: 4.495223631892947e-05 loss: 0.1764 (0.2003) time: 3.5077 data: 0.0095 max mem: 33300 +Epoch: [4] [1980/4276] eta: 1:55:05 lr: 4.494957405157824e-05 loss: 0.1745 (0.2002) time: 3.4372 data: 0.0096 max mem: 33300 +Epoch: [4] [1990/4276] eta: 1:54:40 lr: 4.4946911766706826e-05 loss: 0.1882 (0.2003) time: 3.5182 data: 0.0103 max mem: 33300 +Epoch: [4] [2000/4276] eta: 1:54:16 lr: 4.4944249464313995e-05 loss: 0.2092 (0.2003) time: 3.5189 data: 0.0106 max mem: 33300 +Epoch: [4] [2010/4276] eta: 1:53:52 lr: 4.4941587144398465e-05 loss: 0.2052 (0.2003) time: 3.5123 data: 0.0110 max mem: 33300 +Epoch: [4] [2020/4276] eta: 1:53:27 lr: 4.493892480695896e-05 loss: 0.1934 (0.2003) time: 3.5200 data: 0.0107 max mem: 33300 +Epoch: [4] [2030/4276] eta: 1:53:03 lr: 4.4936262451994224e-05 loss: 0.1883 (0.2002) time: 3.5414 data: 0.0105 max mem: 33300 +Epoch: [4] [2040/4276] eta: 1:52:38 lr: 4.493360007950298e-05 loss: 0.1852 (0.2002) time: 3.5260 data: 0.0103 max mem: 33300 +Epoch: [4] [2050/4276] eta: 1:52:14 lr: 4.493093768948397e-05 loss: 0.1938 (0.2002) time: 3.5302 data: 0.0099 max mem: 33300 +Epoch: [4] [2060/4276] eta: 1:51:48 lr: 4.492827528193591e-05 loss: 0.1947 (0.2002) time: 3.5173 data: 0.0101 max mem: 33300 +Epoch: [4] [2070/4276] eta: 1:51:22 lr: 4.4925612856857535e-05 loss: 0.1895 (0.2001) time: 3.4508 data: 0.0102 max mem: 33300 +Epoch: [4] [2080/4276] eta: 1:50:57 lr: 4.492295041424758e-05 loss: 0.1885 (0.2002) time: 3.4764 data: 0.0106 max mem: 33300 +Epoch: [4] [2090/4276] eta: 1:50:31 lr: 4.492028795410478e-05 loss: 0.1880 (0.2001) time: 3.4702 data: 0.0112 max mem: 33300 +Epoch: [4] [2100/4276] eta: 1:50:06 lr: 4.4917625476427844e-05 loss: 0.1957 (0.2001) time: 3.4747 data: 0.0104 max mem: 33300 +Epoch: [4] [2110/4276] eta: 1:49:39 lr: 4.491496298121552e-05 loss: 0.1853 (0.2001) time: 3.4542 data: 0.0101 max mem: 33300 +Epoch: [4] [2120/4276] eta: 1:49:14 lr: 4.4912300468466534e-05 loss: 0.1853 (0.2000) time: 3.4900 data: 0.0114 max mem: 33300 +Epoch: [4] [2130/4276] eta: 1:48:48 lr: 4.490963793817961e-05 loss: 0.1734 (0.2000) time: 3.5289 data: 0.0119 max mem: 33300 +Epoch: [4] [2140/4276] eta: 1:48:22 lr: 4.490697539035348e-05 loss: 0.1970 (0.2000) time: 3.4492 data: 0.0108 max mem: 33300 +Epoch: [4] [2150/4276] eta: 1:47:57 lr: 4.490431282498688e-05 loss: 0.2005 (0.1999) time: 3.5606 data: 0.0106 max mem: 33300 +Epoch: [4] [2160/4276] eta: 1:47:30 lr: 4.490165024207853e-05 loss: 0.1889 (0.2000) time: 3.5265 data: 0.0098 max mem: 33300 +Epoch: [4] [2170/4276] eta: 1:47:05 lr: 4.489898764162716e-05 loss: 0.1975 (0.2000) time: 3.4748 data: 0.0097 max mem: 33300 +Epoch: [4] [2180/4276] eta: 1:46:39 lr: 4.4896325023631495e-05 loss: 0.2188 (0.2000) time: 3.5408 data: 0.0110 max mem: 33300 +Epoch: [4] [2190/4276] eta: 1:46:12 lr: 4.489366238809027e-05 loss: 0.1973 (0.2001) time: 3.4975 data: 0.0101 max mem: 33300 +Epoch: [4] [2200/4276] eta: 1:45:47 lr: 4.489099973500221e-05 loss: 0.2019 (0.2001) time: 3.5493 data: 0.0092 max mem: 33300 +Epoch: [4] [2210/4276] eta: 1:45:19 lr: 4.488833706436606e-05 loss: 0.2046 (0.2002) time: 3.4856 data: 0.0094 max mem: 33300 +Epoch: [4] [2220/4276] eta: 1:44:52 lr: 4.488567437618052e-05 loss: 0.2047 (0.2002) time: 3.3914 data: 0.0096 max mem: 33300 +Epoch: [4] [2230/4276] eta: 1:44:23 lr: 4.488301167044432e-05 loss: 0.1895 (0.2001) time: 3.3568 data: 0.0096 max mem: 33300 +Epoch: [4] [2240/4276] eta: 1:43:56 lr: 4.488034894715621e-05 loss: 0.1762 (0.2000) time: 3.3319 data: 0.0099 max mem: 33300 +Epoch: [4] [2250/4276] eta: 1:43:27 lr: 4.48776862063149e-05 loss: 0.1899 (0.2000) time: 3.3142 data: 0.0094 max mem: 33300 +Epoch: [4] [2260/4276] eta: 1:42:58 lr: 4.4875023447919116e-05 loss: 0.1943 (0.2001) time: 3.2645 data: 0.0087 max mem: 33300 +Epoch: [4] [2270/4276] eta: 1:42:30 lr: 4.487236067196759e-05 loss: 0.2025 (0.2001) time: 3.3006 data: 0.0088 max mem: 33300 +Epoch: [4] [2280/4276] eta: 1:42:01 lr: 4.4869697878459056e-05 loss: 0.1837 (0.2001) time: 3.2953 data: 0.0082 max mem: 33300 +Epoch: [4] [2290/4276] eta: 1:41:32 lr: 4.486703506739223e-05 loss: 0.1954 (0.2001) time: 3.2980 data: 0.0082 max mem: 33300 +Epoch: [4] [2300/4276] eta: 1:41:03 lr: 4.486437223876584e-05 loss: 0.1714 (0.1999) time: 3.2889 data: 0.0090 max mem: 33300 +Epoch: [4] [2310/4276] eta: 1:40:35 lr: 4.486170939257862e-05 loss: 0.1792 (0.1999) time: 3.3118 data: 0.0098 max mem: 33300 +Epoch: [4] [2320/4276] eta: 1:40:06 lr: 4.485904652882929e-05 loss: 0.1989 (0.1999) time: 3.3177 data: 0.0098 max mem: 33300 +Epoch: [4] [2330/4276] eta: 1:39:37 lr: 4.485638364751657e-05 loss: 0.1962 (0.1999) time: 3.2940 data: 0.0095 max mem: 33300 +Epoch: [4] [2340/4276] eta: 1:39:08 lr: 4.485372074863919e-05 loss: 0.1946 (0.1998) time: 3.2488 data: 0.0094 max mem: 33300 +Epoch: [4] [2350/4276] eta: 1:38:38 lr: 4.4851057832195875e-05 loss: 0.1923 (0.1999) time: 3.1972 data: 0.0088 max mem: 33300 +Epoch: [4] [2360/4276] eta: 1:38:08 lr: 4.4848394898185354e-05 loss: 0.1915 (0.1998) time: 3.1754 data: 0.0087 max mem: 33300 +Epoch: [4] [2370/4276] eta: 1:37:38 lr: 4.4845731946606354e-05 loss: 0.1957 (0.1998) time: 3.1475 data: 0.0084 max mem: 33300 +Epoch: [4] [2380/4276] eta: 1:37:07 lr: 4.48430689774576e-05 loss: 0.2005 (0.1998) time: 3.1376 data: 0.0083 max mem: 33300 +Epoch: [4] [2390/4276] eta: 1:36:37 lr: 4.48404059907378e-05 loss: 0.1891 (0.1997) time: 3.0864 data: 0.0085 max mem: 33300 +Epoch: [4] [2400/4276] eta: 1:36:06 lr: 4.48377429864457e-05 loss: 0.1891 (0.1998) time: 3.0510 data: 0.0083 max mem: 33300 +Epoch: [4] [2410/4276] eta: 1:35:33 lr: 4.4835079964580015e-05 loss: 0.1868 (0.1997) time: 2.9629 data: 0.0085 max mem: 33300 +Epoch: [4] [2420/4276] eta: 1:35:01 lr: 4.4832416925139466e-05 loss: 0.1723 (0.1996) time: 2.8986 data: 0.0091 max mem: 33300 +Epoch: [4] [2430/4276] eta: 1:34:30 lr: 4.482975386812278e-05 loss: 0.1851 (0.1997) time: 2.9247 data: 0.0089 max mem: 33300 +Epoch: [4] [2440/4276] eta: 1:33:58 lr: 4.482709079352869e-05 loss: 0.1932 (0.1996) time: 2.9371 data: 0.0089 max mem: 33300 +Epoch: [4] [2450/4276] eta: 1:33:26 lr: 4.482442770135591e-05 loss: 0.1802 (0.1996) time: 2.9360 data: 0.0092 max mem: 33300 +Epoch: [4] [2460/4276] eta: 1:32:54 lr: 4.482176459160316e-05 loss: 0.1783 (0.1996) time: 2.9272 data: 0.0092 max mem: 33300 +Epoch: [4] [2470/4276] eta: 1:32:23 lr: 4.481910146426917e-05 loss: 0.1950 (0.1996) time: 2.9292 data: 0.0092 max mem: 33300 +Epoch: [4] [2480/4276] eta: 1:31:51 lr: 4.481643831935267e-05 loss: 0.2063 (0.1996) time: 2.9384 data: 0.0096 max mem: 33300 +Epoch: [4] [2490/4276] eta: 1:31:19 lr: 4.481377515685237e-05 loss: 0.2063 (0.1996) time: 2.9368 data: 0.0096 max mem: 33300 +Epoch: [4] [2500/4276] eta: 1:30:48 lr: 4.481111197676699e-05 loss: 0.2058 (0.1996) time: 2.9355 data: 0.0091 max mem: 33300 +Epoch: [4] [2510/4276] eta: 1:30:16 lr: 4.480844877909526e-05 loss: 0.1939 (0.1996) time: 2.9265 data: 0.0094 max mem: 33300 +Epoch: [4] [2520/4276] eta: 1:29:44 lr: 4.4805785563835914e-05 loss: 0.1580 (0.1995) time: 2.9259 data: 0.0096 max mem: 33300 +Epoch: [4] [2530/4276] eta: 1:29:13 lr: 4.4803122330987657e-05 loss: 0.1551 (0.1993) time: 2.9323 data: 0.0090 max mem: 33300 +Epoch: [4] [2540/4276] eta: 1:28:41 lr: 4.4800459080549215e-05 loss: 0.1662 (0.1993) time: 2.9303 data: 0.0083 max mem: 33300 +Epoch: [4] [2550/4276] eta: 1:28:10 lr: 4.4797795812519315e-05 loss: 0.1880 (0.1992) time: 2.9214 data: 0.0088 max mem: 33300 +Epoch: [4] [2560/4276] eta: 1:27:38 lr: 4.479513252689668e-05 loss: 0.1718 (0.1991) time: 2.9235 data: 0.0092 max mem: 33300 +Epoch: [4] [2570/4276] eta: 1:27:07 lr: 4.479246922368002e-05 loss: 0.1687 (0.1991) time: 2.9338 data: 0.0087 max mem: 33300 +Epoch: [4] [2580/4276] eta: 1:26:35 lr: 4.478980590286807e-05 loss: 0.1687 (0.1991) time: 2.9345 data: 0.0084 max mem: 33300 +Epoch: [4] [2590/4276] eta: 1:26:04 lr: 4.4787142564459536e-05 loss: 0.1801 (0.1990) time: 2.9355 data: 0.0088 max mem: 33300 +Epoch: [4] [2600/4276] eta: 1:25:32 lr: 4.4784479208453155e-05 loss: 0.1887 (0.1991) time: 2.9249 data: 0.0087 max mem: 33300 +Epoch: [4] [2610/4276] eta: 1:25:00 lr: 4.478181583484763e-05 loss: 0.2015 (0.1990) time: 2.9189 data: 0.0086 max mem: 33300 +Epoch: [4] [2620/4276] eta: 1:24:29 lr: 4.477915244364171e-05 loss: 0.2045 (0.1991) time: 2.9288 data: 0.0085 max mem: 33300 +Epoch: [4] [2630/4276] eta: 1:23:58 lr: 4.477648903483409e-05 loss: 0.2019 (0.1990) time: 2.9349 data: 0.0084 max mem: 33300 +Epoch: [4] [2640/4276] eta: 1:23:26 lr: 4.47738256084235e-05 loss: 0.1774 (0.1990) time: 2.9330 data: 0.0086 max mem: 33300 +Epoch: [4] [2650/4276] eta: 1:22:55 lr: 4.477116216440865e-05 loss: 0.1762 (0.1990) time: 2.9121 data: 0.0085 max mem: 33300 +Epoch: [4] [2660/4276] eta: 1:22:23 lr: 4.4768498702788276e-05 loss: 0.1918 (0.1990) time: 2.8975 data: 0.0087 max mem: 33300 +Epoch: [4] [2670/4276] eta: 1:21:51 lr: 4.476583522356109e-05 loss: 0.1917 (0.1990) time: 2.8984 data: 0.0084 max mem: 33300 +Epoch: [4] [2680/4276] eta: 1:21:20 lr: 4.4763171726725814e-05 loss: 0.1858 (0.1989) time: 2.9055 data: 0.0084 max mem: 33300 +Epoch: [4] [2690/4276] eta: 1:20:49 lr: 4.476050821228117e-05 loss: 0.1916 (0.1989) time: 2.9216 data: 0.0088 max mem: 33300 +Epoch: [4] [2700/4276] eta: 1:20:17 lr: 4.4757844680225855e-05 loss: 0.1879 (0.1988) time: 2.9305 data: 0.0087 max mem: 33300 +Epoch: [4] [2710/4276] eta: 1:19:46 lr: 4.4755181130558625e-05 loss: 0.1890 (0.1988) time: 2.9084 data: 0.0082 max mem: 33300 +Epoch: [4] [2720/4276] eta: 1:19:14 lr: 4.4752517563278166e-05 loss: 0.1944 (0.1988) time: 2.8843 data: 0.0082 max mem: 33300 +Epoch: [4] [2730/4276] eta: 1:18:43 lr: 4.4749853978383215e-05 loss: 0.1865 (0.1989) time: 2.8980 data: 0.0089 max mem: 33300 +Epoch: [4] [2740/4276] eta: 1:18:11 lr: 4.4747190375872487e-05 loss: 0.2064 (0.1989) time: 2.8968 data: 0.0086 max mem: 33300 +Epoch: [4] [2750/4276] eta: 1:17:40 lr: 4.4744526755744706e-05 loss: 0.2035 (0.1989) time: 2.8814 data: 0.0081 max mem: 33300 +Epoch: [4] [2760/4276] eta: 1:17:08 lr: 4.474186311799858e-05 loss: 0.1917 (0.1989) time: 2.8780 data: 0.0080 max mem: 33300 +Epoch: [4] [2770/4276] eta: 1:16:37 lr: 4.4739199462632825e-05 loss: 0.1784 (0.1988) time: 2.8794 data: 0.0077 max mem: 33300 +Epoch: [4] [2780/4276] eta: 1:16:06 lr: 4.4736535789646164e-05 loss: 0.1773 (0.1988) time: 2.8914 data: 0.0079 max mem: 33300 +Epoch: [4] [2790/4276] eta: 1:15:34 lr: 4.473387209903732e-05 loss: 0.1995 (0.1988) time: 2.9017 data: 0.0086 max mem: 33300 +Epoch: [4] [2800/4276] eta: 1:15:03 lr: 4.473120839080501e-05 loss: 0.1948 (0.1988) time: 2.8948 data: 0.0090 max mem: 33300 +Epoch: [4] [2810/4276] eta: 1:14:32 lr: 4.472854466494794e-05 loss: 0.1802 (0.1987) time: 2.8923 data: 0.0092 max mem: 33300 +Epoch: [4] [2820/4276] eta: 1:14:00 lr: 4.472588092146483e-05 loss: 0.1805 (0.1986) time: 2.9222 data: 0.0095 max mem: 33300 +Epoch: [4] [2830/4276] eta: 1:13:29 lr: 4.472321716035441e-05 loss: 0.1827 (0.1986) time: 2.9363 data: 0.0092 max mem: 33300 +Epoch: [4] [2840/4276] eta: 1:12:58 lr: 4.4720553381615385e-05 loss: 0.1890 (0.1986) time: 2.9050 data: 0.0081 max mem: 33300 +Epoch: [4] [2850/4276] eta: 1:12:27 lr: 4.471788958524647e-05 loss: 0.2004 (0.1987) time: 2.8810 data: 0.0075 max mem: 33300 +Epoch: [4] [2860/4276] eta: 1:11:55 lr: 4.471522577124639e-05 loss: 0.1905 (0.1986) time: 2.8924 data: 0.0080 max mem: 33300 +Epoch: [4] [2870/4276] eta: 1:11:24 lr: 4.4712561939613855e-05 loss: 0.1813 (0.1986) time: 2.9077 data: 0.0090 max mem: 33300 +Epoch: [4] [2880/4276] eta: 1:10:53 lr: 4.470989809034759e-05 loss: 0.1931 (0.1986) time: 2.9221 data: 0.0094 max mem: 33300 +Epoch: [4] [2890/4276] eta: 1:10:22 lr: 4.470723422344629e-05 loss: 0.2049 (0.1987) time: 2.9356 data: 0.0091 max mem: 33300 +Epoch: [4] [2900/4276] eta: 1:09:51 lr: 4.4704570338908694e-05 loss: 0.1897 (0.1986) time: 2.9366 data: 0.0089 max mem: 33300 +Epoch: [4] [2910/4276] eta: 1:09:20 lr: 4.470190643673352e-05 loss: 0.1757 (0.1986) time: 2.9355 data: 0.0086 max mem: 33300 +Epoch: [4] [2920/4276] eta: 1:08:49 lr: 4.4699242516919456e-05 loss: 0.1875 (0.1986) time: 2.9327 data: 0.0082 max mem: 33300 +Epoch: [4] [2930/4276] eta: 1:08:18 lr: 4.469657857946523e-05 loss: 0.1835 (0.1986) time: 2.9378 data: 0.0083 max mem: 33300 +Epoch: [4] [2940/4276] eta: 1:07:47 lr: 4.4693914624369575e-05 loss: 0.1801 (0.1984) time: 2.9392 data: 0.0082 max mem: 33300 +Epoch: [4] [2950/4276] eta: 1:07:17 lr: 4.469125065163118e-05 loss: 0.1801 (0.1984) time: 2.9389 data: 0.0080 max mem: 33300 +Epoch: [4] [2960/4276] eta: 1:06:46 lr: 4.468858666124877e-05 loss: 0.1895 (0.1984) time: 2.9402 data: 0.0081 max mem: 33300 +Epoch: [4] [2970/4276] eta: 1:06:15 lr: 4.468592265322106e-05 loss: 0.1954 (0.1985) time: 2.9413 data: 0.0086 max mem: 33300 +Epoch: [4] [2980/4276] eta: 1:05:44 lr: 4.468325862754677e-05 loss: 0.2033 (0.1985) time: 2.9398 data: 0.0084 max mem: 33300 +Epoch: [4] [2990/4276] eta: 1:05:13 lr: 4.468059458422461e-05 loss: 0.1765 (0.1984) time: 2.9368 data: 0.0080 max mem: 33300 +Epoch: [4] [3000/4276] eta: 1:04:42 lr: 4.467793052325328e-05 loss: 0.1742 (0.1984) time: 2.9383 data: 0.0082 max mem: 33300 +Epoch: [4] [3010/4276] eta: 1:04:11 lr: 4.467526644463151e-05 loss: 0.1908 (0.1984) time: 2.9380 data: 0.0084 max mem: 33300 +Epoch: [4] [3020/4276] eta: 1:03:40 lr: 4.4672602348358016e-05 loss: 0.1854 (0.1983) time: 2.9386 data: 0.0082 max mem: 33300 +Epoch: [4] [3030/4276] eta: 1:03:09 lr: 4.4669938234431494e-05 loss: 0.1763 (0.1984) time: 2.9353 data: 0.0080 max mem: 33300 +Epoch: [4] [3040/4276] eta: 1:02:39 lr: 4.466727410285068e-05 loss: 0.2034 (0.1985) time: 2.9190 data: 0.0083 max mem: 33300 +Epoch: [4] [3050/4276] eta: 1:02:08 lr: 4.466460995361427e-05 loss: 0.2099 (0.1985) time: 2.9066 data: 0.0084 max mem: 33300 +Epoch: [4] [3060/4276] eta: 1:01:37 lr: 4.466194578672098e-05 loss: 0.1703 (0.1984) time: 2.9083 data: 0.0082 max mem: 33300 +Epoch: [4] [3070/4276] eta: 1:01:06 lr: 4.465928160216952e-05 loss: 0.1745 (0.1984) time: 2.8964 data: 0.0082 max mem: 33300 +Epoch: [4] [3080/4276] eta: 1:00:35 lr: 4.465661739995862e-05 loss: 0.1951 (0.1983) time: 2.8836 data: 0.0080 max mem: 33300 +Epoch: [4] [3090/4276] eta: 1:00:04 lr: 4.4653953180086965e-05 loss: 0.1909 (0.1983) time: 2.8798 data: 0.0075 max mem: 33300 +Epoch: [4] [3100/4276] eta: 0:59:33 lr: 4.465128894255329e-05 loss: 0.1950 (0.1983) time: 2.8779 data: 0.0073 max mem: 33300 +Epoch: [4] [3110/4276] eta: 0:59:02 lr: 4.46486246873563e-05 loss: 0.1871 (0.1982) time: 2.8965 data: 0.0075 max mem: 33300 +Epoch: [4] [3120/4276] eta: 0:58:31 lr: 4.4645960414494695e-05 loss: 0.1752 (0.1982) time: 2.8951 data: 0.0073 max mem: 33300 +Epoch: [4] [3130/4276] eta: 0:58:00 lr: 4.4643296123967204e-05 loss: 0.1825 (0.1982) time: 2.8767 data: 0.0071 max mem: 33300 +Epoch: [4] [3140/4276] eta: 0:57:29 lr: 4.464063181577253e-05 loss: 0.1857 (0.1982) time: 2.8780 data: 0.0071 max mem: 33300 +Epoch: [4] [3150/4276] eta: 0:56:58 lr: 4.463796748990939e-05 loss: 0.1917 (0.1983) time: 2.8788 data: 0.0070 max mem: 33300 +Epoch: [4] [3160/4276] eta: 0:56:27 lr: 4.4635303146376486e-05 loss: 0.1917 (0.1983) time: 2.8784 data: 0.0070 max mem: 33300 +Epoch: [4] [3170/4276] eta: 0:55:56 lr: 4.463263878517253e-05 loss: 0.1926 (0.1983) time: 2.8781 data: 0.0071 max mem: 33300 +Epoch: [4] [3180/4276] eta: 0:55:25 lr: 4.4629974406296247e-05 loss: 0.1944 (0.1983) time: 2.8781 data: 0.0072 max mem: 33300 +Epoch: [4] [3190/4276] eta: 0:54:54 lr: 4.462731000974632e-05 loss: 0.1951 (0.1983) time: 2.8835 data: 0.0073 max mem: 33300 +Epoch: [4] [3200/4276] eta: 0:54:24 lr: 4.4624645595521485e-05 loss: 0.1861 (0.1983) time: 2.8829 data: 0.0072 max mem: 33300 +Epoch: [4] [3210/4276] eta: 0:53:53 lr: 4.462198116362044e-05 loss: 0.1948 (0.1983) time: 2.8771 data: 0.0070 max mem: 33300 +Epoch: [4] [3220/4276] eta: 0:53:22 lr: 4.46193167140419e-05 loss: 0.1948 (0.1983) time: 2.8792 data: 0.0073 max mem: 33300 +Epoch: [4] [3230/4276] eta: 0:52:51 lr: 4.461665224678458e-05 loss: 0.1903 (0.1983) time: 2.8917 data: 0.0077 max mem: 33300 +Epoch: [4] [3240/4276] eta: 0:52:20 lr: 4.461398776184717e-05 loss: 0.1977 (0.1983) time: 2.9194 data: 0.0085 max mem: 33300 +Epoch: [4] [3250/4276] eta: 0:51:50 lr: 4.46113232592284e-05 loss: 0.1950 (0.1983) time: 2.9359 data: 0.0089 max mem: 33300 +Epoch: [4] [3260/4276] eta: 0:51:19 lr: 4.460865873892697e-05 loss: 0.1891 (0.1983) time: 2.9357 data: 0.0082 max mem: 33300 +Epoch: [4] [3270/4276] eta: 0:50:49 lr: 4.460599420094159e-05 loss: 0.1900 (0.1983) time: 2.9378 data: 0.0080 max mem: 33300 +Epoch: [4] [3280/4276] eta: 0:50:18 lr: 4.4603329645270966e-05 loss: 0.1856 (0.1983) time: 2.9367 data: 0.0078 max mem: 33300 +Epoch: [4] [3290/4276] eta: 0:49:47 lr: 4.460066507191381e-05 loss: 0.1898 (0.1983) time: 2.9366 data: 0.0077 max mem: 33300 +Epoch: [4] [3300/4276] eta: 0:49:17 lr: 4.459800048086883e-05 loss: 0.2052 (0.1983) time: 2.9356 data: 0.0078 max mem: 33300 +Epoch: [4] [3310/4276] eta: 0:48:46 lr: 4.4595335872134734e-05 loss: 0.2033 (0.1984) time: 2.9377 data: 0.0081 max mem: 33300 +Epoch: [4] [3320/4276] eta: 0:48:16 lr: 4.4592671245710236e-05 loss: 0.1961 (0.1984) time: 2.9392 data: 0.0082 max mem: 33300 +Epoch: [4] [3330/4276] eta: 0:47:45 lr: 4.459000660159404e-05 loss: 0.1861 (0.1984) time: 2.9413 data: 0.0080 max mem: 33300 +Epoch: [4] [3340/4276] eta: 0:47:15 lr: 4.458734193978485e-05 loss: 0.1886 (0.1984) time: 2.9276 data: 0.0081 max mem: 33300 +Epoch: [4] [3350/4276] eta: 0:46:44 lr: 4.458467726028137e-05 loss: 0.1886 (0.1983) time: 2.8968 data: 0.0078 max mem: 33300 +Epoch: [4] [3360/4276] eta: 0:46:13 lr: 4.458201256308232e-05 loss: 0.1844 (0.1983) time: 2.8910 data: 0.0080 max mem: 33300 +Epoch: [4] [3370/4276] eta: 0:45:43 lr: 4.457934784818641e-05 loss: 0.2042 (0.1984) time: 2.9113 data: 0.0083 max mem: 33300 +Epoch: [4] [3380/4276] eta: 0:45:12 lr: 4.457668311559231e-05 loss: 0.2021 (0.1984) time: 2.9245 data: 0.0081 max mem: 33300 +Epoch: [4] [3390/4276] eta: 0:44:42 lr: 4.457401836529878e-05 loss: 0.2056 (0.1984) time: 2.9137 data: 0.0084 max mem: 33300 +Epoch: [4] [3400/4276] eta: 0:44:11 lr: 4.4571353597304496e-05 loss: 0.2118 (0.1984) time: 2.8996 data: 0.0084 max mem: 33300 +Epoch: [4] [3410/4276] eta: 0:43:40 lr: 4.4568688811608165e-05 loss: 0.1914 (0.1984) time: 2.8995 data: 0.0088 max mem: 33300 +Epoch: [4] [3420/4276] eta: 0:43:10 lr: 4.456602400820851e-05 loss: 0.1877 (0.1984) time: 2.9011 data: 0.0090 max mem: 33300 +Epoch: [4] [3430/4276] eta: 0:42:39 lr: 4.4563359187104213e-05 loss: 0.1873 (0.1985) time: 2.9153 data: 0.0086 max mem: 33300 +Epoch: [4] [3440/4276] eta: 0:42:09 lr: 4.4560694348294e-05 loss: 0.1691 (0.1984) time: 2.9347 data: 0.0085 max mem: 33300 +Epoch: [4] [3450/4276] eta: 0:41:38 lr: 4.455802949177657e-05 loss: 0.1913 (0.1984) time: 2.9358 data: 0.0081 max mem: 33300 +Epoch: [4] [3460/4276] eta: 0:41:08 lr: 4.455536461755062e-05 loss: 0.1981 (0.1984) time: 2.9361 data: 0.0079 max mem: 33300 +Epoch: [4] [3470/4276] eta: 0:40:37 lr: 4.455269972561487e-05 loss: 0.1777 (0.1984) time: 2.9367 data: 0.0077 max mem: 33300 +Epoch: [4] [3480/4276] eta: 0:40:07 lr: 4.4550034815968026e-05 loss: 0.1946 (0.1984) time: 2.9284 data: 0.0072 max mem: 33300 +Epoch: [4] [3490/4276] eta: 0:39:36 lr: 4.4547369888608775e-05 loss: 0.2010 (0.1984) time: 2.8956 data: 0.0077 max mem: 33300 +Epoch: [4] [3500/4276] eta: 0:39:06 lr: 4.4544704943535836e-05 loss: 0.1998 (0.1984) time: 2.8886 data: 0.0086 max mem: 33300 +Epoch: [4] [3510/4276] eta: 0:38:35 lr: 4.4542039980747914e-05 loss: 0.1734 (0.1983) time: 2.9096 data: 0.0092 max mem: 33300 +Epoch: [4] [3520/4276] eta: 0:38:05 lr: 4.45393750002437e-05 loss: 0.1975 (0.1983) time: 2.9105 data: 0.0090 max mem: 33300 +Epoch: [4] [3530/4276] eta: 0:37:34 lr: 4.453671000202193e-05 loss: 0.2002 (0.1983) time: 2.9312 data: 0.0087 max mem: 33300 +Epoch: [4] [3540/4276] eta: 0:37:04 lr: 4.453404498608128e-05 loss: 0.1830 (0.1983) time: 2.9456 data: 0.0082 max mem: 33300 +Epoch: [4] [3550/4276] eta: 0:36:34 lr: 4.453137995242045e-05 loss: 0.1921 (0.1983) time: 2.9367 data: 0.0074 max mem: 33300 +Epoch: [4] [3560/4276] eta: 0:36:03 lr: 4.452871490103816e-05 loss: 0.1921 (0.1983) time: 2.9189 data: 0.0075 max mem: 33300 +Epoch: [4] [3570/4276] eta: 0:35:33 lr: 4.452604983193311e-05 loss: 0.2032 (0.1983) time: 2.9080 data: 0.0075 max mem: 33300 +Epoch: [4] [3580/4276] eta: 0:35:02 lr: 4.4523384745104e-05 loss: 0.2000 (0.1983) time: 2.9168 data: 0.0072 max mem: 33300 +Epoch: [4] [3590/4276] eta: 0:34:32 lr: 4.452071964054954e-05 loss: 0.1806 (0.1983) time: 2.9160 data: 0.0072 max mem: 33300 +Epoch: [4] [3600/4276] eta: 0:34:02 lr: 4.451805451826843e-05 loss: 0.1954 (0.1984) time: 2.9145 data: 0.0077 max mem: 33300 +Epoch: [4] [3610/4276] eta: 0:33:31 lr: 4.451538937825936e-05 loss: 0.2052 (0.1984) time: 2.8986 data: 0.0088 max mem: 33300 +Epoch: [4] [3620/4276] eta: 0:33:01 lr: 4.4512724220521054e-05 loss: 0.1946 (0.1984) time: 2.8831 data: 0.0092 max mem: 33300 +Epoch: [4] [3630/4276] eta: 0:32:30 lr: 4.45100590450522e-05 loss: 0.1991 (0.1984) time: 2.8831 data: 0.0089 max mem: 33300 +Epoch: [4] [3640/4276] eta: 0:32:00 lr: 4.450739385185151e-05 loss: 0.2070 (0.1984) time: 2.9027 data: 0.0087 max mem: 33300 +Epoch: [4] [3650/4276] eta: 0:31:29 lr: 4.4504728640917675e-05 loss: 0.1815 (0.1984) time: 2.9324 data: 0.0086 max mem: 33300 +Epoch: [4] [3660/4276] eta: 0:30:59 lr: 4.4502063412249405e-05 loss: 0.1781 (0.1984) time: 2.9372 data: 0.0083 max mem: 33300 +Epoch: [4] [3670/4276] eta: 0:30:29 lr: 4.44993981658454e-05 loss: 0.1970 (0.1984) time: 2.9342 data: 0.0083 max mem: 33300 +Epoch: [4] [3680/4276] eta: 0:29:58 lr: 4.449673290170437e-05 loss: 0.2095 (0.1984) time: 2.9154 data: 0.0088 max mem: 33300 +Epoch: [4] [3690/4276] eta: 0:29:28 lr: 4.4494067619825e-05 loss: 0.2159 (0.1985) time: 2.8906 data: 0.0092 max mem: 33300 +Epoch: [4] [3700/4276] eta: 0:28:58 lr: 4.4491402320206e-05 loss: 0.2017 (0.1985) time: 2.8825 data: 0.0089 max mem: 33300 +Epoch: [4] [3710/4276] eta: 0:28:27 lr: 4.448873700284608e-05 loss: 0.1944 (0.1984) time: 2.8900 data: 0.0083 max mem: 33300 +Epoch: [4] [3720/4276] eta: 0:27:57 lr: 4.4486071667743924e-05 loss: 0.1809 (0.1984) time: 2.9196 data: 0.0086 max mem: 33300 +Epoch: [4] [3730/4276] eta: 0:27:27 lr: 4.448340631489824e-05 loss: 0.1905 (0.1984) time: 2.9374 data: 0.0089 max mem: 33300 +Epoch: [4] [3740/4276] eta: 0:26:56 lr: 4.448074094430773e-05 loss: 0.1931 (0.1984) time: 2.9270 data: 0.0089 max mem: 33300 +Epoch: [4] [3750/4276] eta: 0:26:26 lr: 4.447807555597109e-05 loss: 0.1827 (0.1984) time: 2.9111 data: 0.0090 max mem: 33300 +Epoch: [4] [3760/4276] eta: 0:25:56 lr: 4.447541014988703e-05 loss: 0.1920 (0.1984) time: 2.8843 data: 0.0087 max mem: 33300 +Epoch: [4] [3770/4276] eta: 0:25:25 lr: 4.4472744726054246e-05 loss: 0.1975 (0.1984) time: 2.8707 data: 0.0090 max mem: 33300 +Epoch: [4] [3780/4276] eta: 0:24:55 lr: 4.447007928447143e-05 loss: 0.2012 (0.1984) time: 2.8792 data: 0.0091 max mem: 33300 +Epoch: [4] [3790/4276] eta: 0:24:25 lr: 4.446741382513729e-05 loss: 0.1927 (0.1984) time: 2.8895 data: 0.0087 max mem: 33300 +Epoch: [4] [3800/4276] eta: 0:23:54 lr: 4.446474834805052e-05 loss: 0.1943 (0.1984) time: 2.8960 data: 0.0088 max mem: 33300 +Epoch: [4] [3810/4276] eta: 0:23:24 lr: 4.4462082853209816e-05 loss: 0.1909 (0.1984) time: 2.8949 data: 0.0089 max mem: 33300 +Epoch: [4] [3820/4276] eta: 0:22:54 lr: 4.445941734061389e-05 loss: 0.1821 (0.1984) time: 2.8990 data: 0.0087 max mem: 33300 +Epoch: [4] [3830/4276] eta: 0:22:24 lr: 4.4456751810261435e-05 loss: 0.1821 (0.1984) time: 2.9083 data: 0.0083 max mem: 33300 +Epoch: [4] [3840/4276] eta: 0:21:53 lr: 4.4454086262151154e-05 loss: 0.1837 (0.1984) time: 2.9110 data: 0.0084 max mem: 33300 +Epoch: [4] [3850/4276] eta: 0:21:23 lr: 4.445142069628174e-05 loss: 0.1837 (0.1984) time: 2.9092 data: 0.0087 max mem: 33300 +Epoch: [4] [3860/4276] eta: 0:20:53 lr: 4.444875511265188e-05 loss: 0.1965 (0.1984) time: 2.9131 data: 0.0091 max mem: 33300 +Epoch: [4] [3870/4276] eta: 0:20:23 lr: 4.4446089511260296e-05 loss: 0.1978 (0.1984) time: 2.9142 data: 0.0087 max mem: 33300 +Epoch: [4] [3880/4276] eta: 0:19:52 lr: 4.444342389210567e-05 loss: 0.1875 (0.1984) time: 2.9250 data: 0.0082 max mem: 33300 +Epoch: [4] [3890/4276] eta: 0:19:22 lr: 4.44407582551867e-05 loss: 0.1848 (0.1984) time: 2.9349 data: 0.0080 max mem: 33300 +Epoch: [4] [3900/4276] eta: 0:18:52 lr: 4.443809260050209e-05 loss: 0.1943 (0.1984) time: 2.9328 data: 0.0074 max mem: 33300 +Epoch: [4] [3910/4276] eta: 0:18:22 lr: 4.443542692805054e-05 loss: 0.1875 (0.1984) time: 2.9325 data: 0.0072 max mem: 33300 +Epoch: [4] [3920/4276] eta: 0:17:52 lr: 4.443276123783074e-05 loss: 0.1831 (0.1983) time: 2.9317 data: 0.0074 max mem: 33300 +Epoch: [4] [3930/4276] eta: 0:17:21 lr: 4.443009552984138e-05 loss: 0.1849 (0.1983) time: 2.9321 data: 0.0076 max mem: 33300 +Epoch: [4] [3940/4276] eta: 0:16:51 lr: 4.442742980408118e-05 loss: 0.1864 (0.1983) time: 2.9323 data: 0.0074 max mem: 33300 +Epoch: [4] [3950/4276] eta: 0:16:21 lr: 4.442476406054882e-05 loss: 0.1777 (0.1983) time: 2.9336 data: 0.0073 max mem: 33300 +Epoch: [4] [3960/4276] eta: 0:15:51 lr: 4.4422098299242995e-05 loss: 0.1914 (0.1983) time: 2.9357 data: 0.0073 max mem: 33300 +Epoch: [4] [3970/4276] eta: 0:15:21 lr: 4.441943252016241e-05 loss: 0.2084 (0.1983) time: 2.9345 data: 0.0081 max mem: 33300 +Epoch: [4] [3980/4276] eta: 0:14:51 lr: 4.441676672330575e-05 loss: 0.1913 (0.1983) time: 2.9111 data: 0.0087 max mem: 33300 +Epoch: [4] [3990/4276] eta: 0:14:20 lr: 4.441410090867173e-05 loss: 0.1913 (0.1983) time: 2.9093 data: 0.0085 max mem: 33300 +Epoch: [4] [4000/4276] eta: 0:13:50 lr: 4.441143507625903e-05 loss: 0.1773 (0.1983) time: 2.9179 data: 0.0086 max mem: 33300 +Epoch: [4] [4010/4276] eta: 0:13:20 lr: 4.440876922606635e-05 loss: 0.1747 (0.1983) time: 2.8988 data: 0.0087 max mem: 33300 +Epoch: [4] [4020/4276] eta: 0:12:50 lr: 4.4406103358092384e-05 loss: 0.1834 (0.1983) time: 2.8857 data: 0.0083 max mem: 33300 +Epoch: [4] [4030/4276] eta: 0:12:20 lr: 4.440343747233583e-05 loss: 0.1922 (0.1983) time: 2.8812 data: 0.0078 max mem: 33300 +Epoch: [4] [4040/4276] eta: 0:11:50 lr: 4.440077156879538e-05 loss: 0.1937 (0.1983) time: 2.8824 data: 0.0079 max mem: 33300 +Epoch: [4] [4050/4276] eta: 0:11:19 lr: 4.4398105647469726e-05 loss: 0.1827 (0.1983) time: 2.8746 data: 0.0079 max mem: 33300 +Epoch: [4] [4060/4276] eta: 0:10:49 lr: 4.439543970835758e-05 loss: 0.1738 (0.1983) time: 2.8695 data: 0.0082 max mem: 33300 +Epoch: [4] [4070/4276] eta: 0:10:19 lr: 4.439277375145762e-05 loss: 0.1918 (0.1983) time: 2.8786 data: 0.0084 max mem: 33300 +Epoch: [4] [4080/4276] eta: 0:09:49 lr: 4.439010777676854e-05 loss: 0.1914 (0.1983) time: 2.8857 data: 0.0082 max mem: 33300 +Epoch: [4] [4090/4276] eta: 0:09:19 lr: 4.438744178428904e-05 loss: 0.1951 (0.1983) time: 2.8882 data: 0.0077 max mem: 33300 +Epoch: [4] [4100/4276] eta: 0:08:49 lr: 4.438477577401782e-05 loss: 0.2059 (0.1983) time: 2.8883 data: 0.0075 max mem: 33300 +Epoch: [4] [4110/4276] eta: 0:08:19 lr: 4.438210974595355e-05 loss: 0.2043 (0.1983) time: 2.8859 data: 0.0077 max mem: 33300 +Epoch: [4] [4120/4276] eta: 0:07:48 lr: 4.437944370009496e-05 loss: 0.1954 (0.1983) time: 2.8839 data: 0.0080 max mem: 33300 +Epoch: [4] [4130/4276] eta: 0:07:18 lr: 4.437677763644071e-05 loss: 0.1954 (0.1983) time: 2.8916 data: 0.0085 max mem: 33300 +Epoch: [4] [4140/4276] eta: 0:06:48 lr: 4.437411155498951e-05 loss: 0.1910 (0.1983) time: 2.9165 data: 0.0087 max mem: 33300 +Epoch: [4] [4150/4276] eta: 0:06:18 lr: 4.437144545574005e-05 loss: 0.1824 (0.1983) time: 2.9173 data: 0.0087 max mem: 33300 +Epoch: [4] [4160/4276] eta: 0:05:48 lr: 4.436877933869103e-05 loss: 0.1808 (0.1983) time: 2.9015 data: 0.0088 max mem: 33300 +Epoch: [4] [4170/4276] eta: 0:05:18 lr: 4.4366113203841126e-05 loss: 0.2090 (0.1983) time: 2.9186 data: 0.0084 max mem: 33300 +Epoch: [4] [4180/4276] eta: 0:04:48 lr: 4.4363447051189045e-05 loss: 0.1976 (0.1983) time: 2.9371 data: 0.0081 max mem: 33300 +Epoch: [4] [4190/4276] eta: 0:04:18 lr: 4.436078088073347e-05 loss: 0.1907 (0.1983) time: 2.9399 data: 0.0080 max mem: 33300 +Epoch: [4] [4200/4276] eta: 0:03:48 lr: 4.43581146924731e-05 loss: 0.1973 (0.1983) time: 2.9408 data: 0.0078 max mem: 33300 +Epoch: [4] [4210/4276] eta: 0:03:18 lr: 4.435544848640663e-05 loss: 0.2045 (0.1984) time: 2.9393 data: 0.0077 max mem: 33300 +Epoch: [4] [4220/4276] eta: 0:02:48 lr: 4.435278226253274e-05 loss: 0.2234 (0.1984) time: 2.9391 data: 0.0077 max mem: 33300 +Epoch: [4] [4230/4276] eta: 0:02:18 lr: 4.4350116020850134e-05 loss: 0.2234 (0.1985) time: 2.9379 data: 0.0078 max mem: 33300 +Epoch: [4] [4240/4276] eta: 0:01:48 lr: 4.434744976135749e-05 loss: 0.2180 (0.1985) time: 2.9370 data: 0.0079 max mem: 33300 +Epoch: [4] [4250/4276] eta: 0:01:18 lr: 4.434478348405351e-05 loss: 0.2025 (0.1985) time: 2.9368 data: 0.0077 max mem: 33300 +Epoch: [4] [4260/4276] eta: 0:00:48 lr: 4.434211718893689e-05 loss: 0.1908 (0.1985) time: 2.9352 data: 0.0077 max mem: 33300 +Epoch: [4] [4270/4276] eta: 0:00:18 lr: 4.433945087600631e-05 loss: 0.1951 (0.1985) time: 2.9305 data: 0.0074 max mem: 33300 +Epoch: [4] Total time: 3:34:03 +Test: [ 0/21770] eta: 6:40:12 time: 1.1030 data: 1.0601 max mem: 33300 +Test: [ 100/21770] eta: 0:19:18 time: 0.0387 data: 0.0008 max mem: 33300 +Test: [ 200/21770] eta: 0:16:34 time: 0.0388 data: 0.0009 max mem: 33300 +Test: [ 300/21770] eta: 0:15:37 time: 0.0389 data: 0.0008 max mem: 33300 +Test: [ 400/21770] eta: 0:15:06 time: 0.0388 data: 0.0008 max mem: 33300 +Test: [ 500/21770] eta: 0:14:46 time: 0.0388 data: 0.0008 max mem: 33300 +Test: [ 600/21770] eta: 0:14:32 time: 0.0386 data: 0.0008 max mem: 33300 +Test: [ 700/21770] eta: 0:14:21 time: 0.0388 data: 0.0008 max mem: 33300 +Test: [ 800/21770] eta: 0:14:11 time: 0.0390 data: 0.0008 max mem: 33300 +Test: [ 900/21770] eta: 0:14:03 time: 0.0389 data: 0.0008 max mem: 33300 +Test: [ 1000/21770] eta: 0:13:56 time: 0.0388 data: 0.0008 max mem: 33300 +Test: [ 1100/21770] eta: 0:13:49 time: 0.0389 data: 0.0008 max mem: 33300 +Test: [ 1200/21770] eta: 0:13:43 time: 0.0390 data: 0.0009 max mem: 33300 +Test: [ 1300/21770] eta: 0:13:37 time: 0.0388 data: 0.0008 max mem: 33300 +Test: [ 1400/21770] eta: 0:13:32 time: 0.0389 data: 0.0008 max mem: 33300 +Test: [ 1500/21770] eta: 0:13:27 time: 0.0392 data: 0.0008 max mem: 33300 +Test: [ 1600/21770] eta: 0:13:22 time: 0.0393 data: 0.0008 max mem: 33300 +Test: [ 1700/21770] eta: 0:13:18 time: 0.0393 data: 0.0008 max mem: 33300 +Test: [ 1800/21770] eta: 0:13:13 time: 0.0392 data: 0.0008 max mem: 33300 +Test: [ 1900/21770] eta: 0:13:09 time: 0.0394 data: 0.0008 max mem: 33300 +Test: [ 2000/21770] eta: 0:13:04 time: 0.0392 data: 0.0008 max mem: 33300 +Test: [ 2100/21770] eta: 0:13:00 time: 0.0392 data: 0.0008 max mem: 33300 +Test: [ 2200/21770] eta: 0:12:56 time: 0.0392 data: 0.0008 max mem: 33300 +Test: [ 2300/21770] eta: 0:12:52 time: 0.0393 data: 0.0008 max mem: 33300 +Test: [ 2400/21770] eta: 0:12:48 time: 0.0394 data: 0.0008 max mem: 33300 +Test: [ 2500/21770] eta: 0:12:44 time: 0.0400 data: 0.0008 max mem: 33300 +Test: [ 2600/21770] eta: 0:12:40 time: 0.0399 data: 0.0008 max mem: 33300 +Test: [ 2700/21770] eta: 0:12:36 time: 0.0393 data: 0.0008 max mem: 33300 +Test: [ 2800/21770] eta: 0:12:32 time: 0.0400 data: 0.0009 max mem: 33300 +Test: [ 2900/21770] eta: 0:12:28 time: 0.0400 data: 0.0008 max mem: 33300 +Test: [ 3000/21770] eta: 0:12:24 time: 0.0378 data: 0.0009 max mem: 33300 +Test: [ 3100/21770] eta: 0:12:19 time: 0.0379 data: 0.0009 max mem: 33300 +Test: [ 3200/21770] eta: 0:12:14 time: 0.0379 data: 0.0009 max mem: 33300 +Test: [ 3300/21770] eta: 0:12:09 time: 0.0378 data: 0.0009 max mem: 33300 +Test: [ 3400/21770] eta: 0:12:04 time: 0.0378 data: 0.0009 max mem: 33300 +Test: [ 3500/21770] eta: 0:11:59 time: 0.0378 data: 0.0008 max mem: 33300 +Test: [ 3600/21770] eta: 0:11:54 time: 0.0378 data: 0.0009 max mem: 33300 +Test: [ 3700/21770] eta: 0:11:50 time: 0.0378 data: 0.0009 max mem: 33300 +Test: [ 3800/21770] eta: 0:11:45 time: 0.0390 data: 0.0009 max mem: 33300 +Test: [ 3900/21770] eta: 0:11:41 time: 0.0392 data: 0.0009 max mem: 33300 +Test: [ 4000/21770] eta: 0:11:37 time: 0.0390 data: 0.0009 max mem: 33300 +Test: [ 4100/21770] eta: 0:11:33 time: 0.0391 data: 0.0009 max mem: 33300 +Test: [ 4200/21770] eta: 0:11:29 time: 0.0391 data: 0.0009 max mem: 33300 +Test: [ 4300/21770] eta: 0:11:25 time: 0.0393 data: 0.0009 max mem: 33300 +Test: [ 4400/21770] eta: 0:11:21 time: 0.0394 data: 0.0008 max mem: 33300 +Test: [ 4500/21770] eta: 0:11:18 time: 0.0397 data: 0.0008 max mem: 33300 +Test: [ 4600/21770] eta: 0:11:14 time: 0.0390 data: 0.0009 max mem: 33300 +Test: [ 4700/21770] eta: 0:11:10 time: 0.0384 data: 0.0009 max mem: 33300 +Test: [ 4800/21770] eta: 0:11:05 time: 0.0383 data: 0.0009 max mem: 33300 +Test: [ 4900/21770] eta: 0:11:01 time: 0.0386 data: 0.0009 max mem: 33300 +Test: [ 5000/21770] eta: 0:10:57 time: 0.0385 data: 0.0009 max mem: 33300 +Test: [ 5100/21770] eta: 0:10:53 time: 0.0385 data: 0.0009 max mem: 33300 +Test: [ 5200/21770] eta: 0:10:49 time: 0.0385 data: 0.0009 max mem: 33300 +Test: [ 5300/21770] eta: 0:10:45 time: 0.0384 data: 0.0009 max mem: 33300 +Test: [ 5400/21770] eta: 0:10:40 time: 0.0384 data: 0.0009 max mem: 33300 +Test: [ 5500/21770] eta: 0:10:36 time: 0.0386 data: 0.0009 max mem: 33300 +Test: [ 5600/21770] eta: 0:10:32 time: 0.0385 data: 0.0009 max mem: 33300 +Test: [ 5700/21770] eta: 0:10:28 time: 0.0385 data: 0.0009 max mem: 33300 +Test: [ 5800/21770] eta: 0:10:24 time: 0.0385 data: 0.0009 max mem: 33300 +Test: [ 5900/21770] eta: 0:10:20 time: 0.0383 data: 0.0009 max mem: 33300 +Test: [ 6000/21770] eta: 0:10:16 time: 0.0384 data: 0.0009 max mem: 33300 +Test: [ 6100/21770] eta: 0:10:12 time: 0.0385 data: 0.0009 max mem: 33300 +Test: [ 6200/21770] eta: 0:10:08 time: 0.0383 data: 0.0009 max mem: 33300 +Test: [ 6300/21770] eta: 0:10:04 time: 0.0390 data: 0.0008 max mem: 33300 +Test: [ 6400/21770] eta: 0:10:00 time: 0.0389 data: 0.0009 max mem: 33300 +Test: [ 6500/21770] eta: 0:09:56 time: 0.0390 data: 0.0009 max mem: 33300 +Test: [ 6600/21770] eta: 0:09:52 time: 0.0392 data: 0.0009 max mem: 33300 +Test: [ 6700/21770] eta: 0:09:48 time: 0.0390 data: 0.0009 max mem: 33300 +Test: [ 6800/21770] eta: 0:09:44 time: 0.0392 data: 0.0009 max mem: 33300 +Test: [ 6900/21770] eta: 0:09:40 time: 0.0387 data: 0.0009 max mem: 33300 +Test: [ 7000/21770] eta: 0:09:36 time: 0.0389 data: 0.0009 max mem: 33300 +Test: [ 7100/21770] eta: 0:09:32 time: 0.0388 data: 0.0009 max mem: 33300 +Test: [ 7200/21770] eta: 0:09:29 time: 0.0389 data: 0.0009 max mem: 33300 +Test: [ 7300/21770] eta: 0:09:25 time: 0.0388 data: 0.0009 max mem: 33300 +Test: [ 7400/21770] eta: 0:09:21 time: 0.0389 data: 0.0009 max mem: 33300 +Test: [ 7500/21770] eta: 0:09:17 time: 0.0388 data: 0.0009 max mem: 33300 +Test: [ 7600/21770] eta: 0:09:13 time: 0.0389 data: 0.0009 max mem: 33300 +Test: [ 7700/21770] eta: 0:09:09 time: 0.0388 data: 0.0009 max mem: 33300 +Test: [ 7800/21770] eta: 0:09:05 time: 0.0398 data: 0.0009 max mem: 33300 +Test: [ 7900/21770] eta: 0:09:01 time: 0.0400 data: 0.0009 max mem: 33300 +Test: [ 8000/21770] eta: 0:08:57 time: 0.0399 data: 0.0008 max mem: 33300 +Test: [ 8100/21770] eta: 0:08:54 time: 0.0400 data: 0.0008 max mem: 33300 +Test: [ 8200/21770] eta: 0:08:50 time: 0.0398 data: 0.0008 max mem: 33300 +Test: [ 8300/21770] eta: 0:08:46 time: 0.0400 data: 0.0008 max mem: 33300 +Test: [ 8400/21770] eta: 0:08:42 time: 0.0397 data: 0.0008 max mem: 33300 +Test: [ 8500/21770] eta: 0:08:38 time: 0.0399 data: 0.0008 max mem: 33300 +Test: [ 8600/21770] eta: 0:08:35 time: 0.0400 data: 0.0008 max mem: 33300 +Test: [ 8700/21770] eta: 0:08:31 time: 0.0399 data: 0.0008 max mem: 33300 +Test: [ 8800/21770] eta: 0:08:27 time: 0.0400 data: 0.0008 max mem: 33300 +Test: [ 8900/21770] eta: 0:08:23 time: 0.0401 data: 0.0008 max mem: 33300 +Test: [ 9000/21770] eta: 0:08:20 time: 0.0400 data: 0.0009 max mem: 33300 +Test: [ 9100/21770] eta: 0:08:16 time: 0.0401 data: 0.0009 max mem: 33300 +Test: [ 9200/21770] eta: 0:08:12 time: 0.0399 data: 0.0008 max mem: 33300 +Test: [ 9300/21770] eta: 0:08:08 time: 0.0397 data: 0.0008 max mem: 33300 +Test: [ 9400/21770] eta: 0:08:04 time: 0.0401 data: 0.0008 max mem: 33300 +Test: [ 9500/21770] eta: 0:08:00 time: 0.0383 data: 0.0009 max mem: 33300 +Test: [ 9600/21770] eta: 0:07:56 time: 0.0379 data: 0.0009 max mem: 33300 +Test: [ 9700/21770] eta: 0:07:52 time: 0.0379 data: 0.0008 max mem: 33300 +Test: [ 9800/21770] eta: 0:07:48 time: 0.0379 data: 0.0008 max mem: 33300 +Test: [ 9900/21770] eta: 0:07:44 time: 0.0379 data: 0.0009 max mem: 33300 +Test: [10000/21770] eta: 0:07:40 time: 0.0401 data: 0.0008 max mem: 33300 +Test: [10100/21770] eta: 0:07:36 time: 0.0399 data: 0.0008 max mem: 33300 +Test: [10200/21770] eta: 0:07:33 time: 0.0401 data: 0.0008 max mem: 33300 +Test: [10300/21770] eta: 0:07:29 time: 0.0400 data: 0.0008 max mem: 33300 +Test: [10400/21770] eta: 0:07:25 time: 0.0400 data: 0.0008 max mem: 33300 +Test: [10500/21770] eta: 0:07:21 time: 0.0398 data: 0.0008 max mem: 33300 +Test: [10600/21770] eta: 0:07:17 time: 0.0400 data: 0.0008 max mem: 33300 +Test: [10700/21770] eta: 0:07:13 time: 0.0386 data: 0.0008 max mem: 33300 +Test: [10800/21770] eta: 0:07:09 time: 0.0387 data: 0.0009 max mem: 33300 +Test: [10900/21770] eta: 0:07:05 time: 0.0388 data: 0.0009 max mem: 33300 +Test: [11000/21770] eta: 0:07:01 time: 0.0379 data: 0.0009 max mem: 33300 +Test: [11100/21770] eta: 0:06:57 time: 0.0379 data: 0.0008 max mem: 33300 +Test: [11200/21770] eta: 0:06:53 time: 0.0378 data: 0.0008 max mem: 33300 +Test: [11300/21770] eta: 0:06:49 time: 0.0396 data: 0.0008 max mem: 33300 +Test: [11400/21770] eta: 0:06:45 time: 0.0385 data: 0.0008 max mem: 33300 +Test: [11500/21770] eta: 0:06:41 time: 0.0387 data: 0.0008 max mem: 33300 +Test: [11600/21770] eta: 0:06:37 time: 0.0386 data: 0.0008 max mem: 33300 +Test: [11700/21770] eta: 0:06:34 time: 0.0385 data: 0.0008 max mem: 33300 +Test: [11800/21770] eta: 0:06:30 time: 0.0386 data: 0.0008 max mem: 33300 +Test: [11900/21770] eta: 0:06:26 time: 0.0384 data: 0.0008 max mem: 33300 +Test: [12000/21770] eta: 0:06:22 time: 0.0386 data: 0.0008 max mem: 33300 +Test: [12100/21770] eta: 0:06:18 time: 0.0387 data: 0.0008 max mem: 33300 +Test: [12200/21770] eta: 0:06:14 time: 0.0386 data: 0.0009 max mem: 33300 +Test: [12300/21770] eta: 0:06:10 time: 0.0384 data: 0.0008 max mem: 33300 +Test: [12400/21770] eta: 0:06:06 time: 0.0386 data: 0.0008 max mem: 33300 +Test: [12500/21770] eta: 0:06:02 time: 0.0391 data: 0.0009 max mem: 33300 +Test: [12600/21770] eta: 0:05:58 time: 0.0392 data: 0.0009 max mem: 33300 +Test: [12700/21770] eta: 0:05:54 time: 0.0394 data: 0.0009 max mem: 33300 +Test: [12800/21770] eta: 0:05:50 time: 0.0396 data: 0.0008 max mem: 33300 +Test: [12900/21770] eta: 0:05:46 time: 0.0394 data: 0.0008 max mem: 33300 +Test: [13000/21770] eta: 0:05:42 time: 0.0396 data: 0.0008 max mem: 33300 +Test: [13100/21770] eta: 0:05:39 time: 0.0395 data: 0.0009 max mem: 33300 +Test: [13200/21770] eta: 0:05:35 time: 0.0398 data: 0.0008 max mem: 33300 +Test: [13300/21770] eta: 0:05:31 time: 0.0393 data: 0.0008 max mem: 33300 +Test: [13400/21770] eta: 0:05:27 time: 0.0398 data: 0.0009 max mem: 33300 +Test: [13500/21770] eta: 0:05:23 time: 0.0397 data: 0.0009 max mem: 33300 +Test: [13600/21770] eta: 0:05:19 time: 0.0392 data: 0.0008 max mem: 33300 +Test: [13700/21770] eta: 0:05:15 time: 0.0401 data: 0.0009 max mem: 33300 +Test: [13800/21770] eta: 0:05:11 time: 0.0397 data: 0.0008 max mem: 33300 +Test: [13900/21770] eta: 0:05:07 time: 0.0394 data: 0.0008 max mem: 33300 +Test: [14000/21770] eta: 0:05:04 time: 0.0393 data: 0.0009 max mem: 33300 +Test: [14100/21770] eta: 0:05:00 time: 0.0401 data: 0.0008 max mem: 33300 +Test: [14200/21770] eta: 0:04:56 time: 0.0398 data: 0.0008 max mem: 33300 +Test: [14300/21770] eta: 0:04:52 time: 0.0401 data: 0.0008 max mem: 33300 +Test: [14400/21770] eta: 0:04:48 time: 0.0399 data: 0.0008 max mem: 33300 +Test: [14500/21770] eta: 0:04:44 time: 0.0401 data: 0.0008 max mem: 33300 +Test: [14600/21770] eta: 0:04:40 time: 0.0400 data: 0.0008 max mem: 33300 +Test: [14700/21770] eta: 0:04:36 time: 0.0401 data: 0.0008 max mem: 33300 +Test: [14800/21770] eta: 0:04:33 time: 0.0397 data: 0.0008 max mem: 33300 +Test: [14900/21770] eta: 0:04:29 time: 0.0400 data: 0.0008 max mem: 33300 +Test: [15000/21770] eta: 0:04:25 time: 0.0400 data: 0.0008 max mem: 33300 +Test: [15100/21770] eta: 0:04:21 time: 0.0400 data: 0.0008 max mem: 33300 +Test: [15200/21770] eta: 0:04:17 time: 0.0400 data: 0.0008 max mem: 33300 +Test: [15300/21770] eta: 0:04:13 time: 0.0400 data: 0.0008 max mem: 33300 +Test: [15400/21770] eta: 0:04:09 time: 0.0400 data: 0.0009 max mem: 33300 +Test: [15500/21770] eta: 0:04:05 time: 0.0399 data: 0.0008 max mem: 33300 +Test: [15600/21770] eta: 0:04:01 time: 0.0405 data: 0.0008 max mem: 33300 +Test: [15700/21770] eta: 0:03:58 time: 0.0405 data: 0.0008 max mem: 33300 +Test: [15800/21770] eta: 0:03:54 time: 0.0400 data: 0.0008 max mem: 33300 +Test: [15900/21770] eta: 0:03:50 time: 0.0407 data: 0.0008 max mem: 33300 +Test: [16000/21770] eta: 0:03:46 time: 0.0401 data: 0.0008 max mem: 33300 +Test: [16100/21770] eta: 0:03:42 time: 0.0401 data: 0.0008 max mem: 33300 +Test: [16200/21770] eta: 0:03:38 time: 0.0401 data: 0.0008 max mem: 33300 +Test: [16300/21770] eta: 0:03:34 time: 0.0399 data: 0.0008 max mem: 33300 +Test: [16400/21770] eta: 0:03:30 time: 0.0400 data: 0.0008 max mem: 33300 +Test: [16500/21770] eta: 0:03:26 time: 0.0400 data: 0.0008 max mem: 33300 +Test: [16600/21770] eta: 0:03:23 time: 0.0400 data: 0.0008 max mem: 33300 +Test: [16700/21770] eta: 0:03:19 time: 0.0400 data: 0.0008 max mem: 33300 +Test: [16800/21770] eta: 0:03:15 time: 0.0399 data: 0.0008 max mem: 33300 +Test: [16900/21770] eta: 0:03:11 time: 0.0400 data: 0.0008 max mem: 33300 +Test: [17000/21770] eta: 0:03:07 time: 0.0400 data: 0.0008 max mem: 33300 +Test: [17100/21770] eta: 0:03:03 time: 0.0400 data: 0.0008 max mem: 33300 +Test: [17200/21770] eta: 0:02:59 time: 0.0400 data: 0.0008 max mem: 33300 +Test: [17300/21770] eta: 0:02:55 time: 0.0400 data: 0.0008 max mem: 33300 +Test: [17400/21770] eta: 0:02:51 time: 0.0399 data: 0.0008 max mem: 33300 +Test: [17500/21770] eta: 0:02:47 time: 0.0400 data: 0.0008 max mem: 33300 +Test: [17600/21770] eta: 0:02:43 time: 0.0400 data: 0.0008 max mem: 33300 +Test: [17700/21770] eta: 0:02:40 time: 0.0400 data: 0.0008 max mem: 33300 +Test: [17800/21770] eta: 0:02:36 time: 0.0400 data: 0.0008 max mem: 33300 +Test: [17900/21770] eta: 0:02:32 time: 0.0400 data: 0.0008 max mem: 33300 +Test: [18000/21770] eta: 0:02:28 time: 0.0400 data: 0.0008 max mem: 33300 +Test: [18100/21770] eta: 0:02:24 time: 0.0400 data: 0.0008 max mem: 33300 +Test: [18200/21770] eta: 0:02:20 time: 0.0379 data: 0.0008 max mem: 33300 +Test: [18300/21770] eta: 0:02:16 time: 0.0379 data: 0.0008 max mem: 33300 +Test: [18400/21770] eta: 0:02:12 time: 0.0379 data: 0.0008 max mem: 33300 +Test: [18500/21770] eta: 0:02:08 time: 0.0380 data: 0.0008 max mem: 33300 +Test: [18600/21770] eta: 0:02:04 time: 0.0379 data: 0.0008 max mem: 33300 +Test: [18700/21770] eta: 0:02:00 time: 0.0379 data: 0.0008 max mem: 33300 +Test: [18800/21770] eta: 0:01:56 time: 0.0379 data: 0.0008 max mem: 33300 +Test: [18900/21770] eta: 0:01:52 time: 0.0380 data: 0.0008 max mem: 33300 +Test: [19000/21770] eta: 0:01:48 time: 0.0379 data: 0.0008 max mem: 33300 +Test: [19100/21770] eta: 0:01:44 time: 0.0379 data: 0.0008 max mem: 33300 +Test: [19200/21770] eta: 0:01:40 time: 0.0379 data: 0.0008 max mem: 33300 +Test: [19300/21770] eta: 0:01:36 time: 0.0379 data: 0.0008 max mem: 33300 +Test: [19400/21770] eta: 0:01:33 time: 0.0379 data: 0.0008 max mem: 33300 +Test: [19500/21770] eta: 0:01:29 time: 0.0380 data: 0.0008 max mem: 33300 +Test: [19600/21770] eta: 0:01:25 time: 0.0379 data: 0.0008 max mem: 33300 +Test: [19700/21770] eta: 0:01:21 time: 0.0383 data: 0.0009 max mem: 33300 +Test: [19800/21770] eta: 0:01:17 time: 0.0401 data: 0.0008 max mem: 33300 +Test: [19900/21770] eta: 0:01:13 time: 0.0401 data: 0.0008 max mem: 33300 +Test: [20000/21770] eta: 0:01:09 time: 0.0400 data: 0.0008 max mem: 33300 +Test: [20100/21770] eta: 0:01:05 time: 0.0400 data: 0.0008 max mem: 33300 +Test: [20200/21770] eta: 0:01:01 time: 0.0401 data: 0.0008 max mem: 33300 +Test: [20300/21770] eta: 0:00:57 time: 0.0400 data: 0.0008 max mem: 33300 +Test: [20400/21770] eta: 0:00:53 time: 0.0400 data: 0.0008 max mem: 33300 +Test: [20500/21770] eta: 0:00:49 time: 0.0398 data: 0.0008 max mem: 33300 +Test: [20600/21770] eta: 0:00:45 time: 0.0400 data: 0.0008 max mem: 33300 +Test: [20700/21770] eta: 0:00:42 time: 0.0400 data: 0.0008 max mem: 33300 +Test: [20800/21770] eta: 0:00:38 time: 0.0400 data: 0.0008 max mem: 33300 +Test: [20900/21770] eta: 0:00:34 time: 0.0401 data: 0.0008 max mem: 33300 +Test: [21000/21770] eta: 0:00:30 time: 0.0400 data: 0.0008 max mem: 33300 +Test: [21100/21770] eta: 0:00:26 time: 0.0402 data: 0.0008 max mem: 33300 +Test: [21200/21770] eta: 0:00:22 time: 0.0398 data: 0.0008 max mem: 33300 +Test: [21300/21770] eta: 0:00:18 time: 0.0400 data: 0.0008 max mem: 33300 +Test: [21400/21770] eta: 0:00:14 time: 0.0400 data: 0.0008 max mem: 33300 +Test: [21500/21770] eta: 0:00:10 time: 0.0400 data: 0.0008 max mem: 33300 +Test: [21600/21770] eta: 0:00:06 time: 0.0407 data: 0.0008 max mem: 33300 +Test: [21700/21770] eta: 0:00:02 time: 0.0404 data: 0.0008 max mem: 33300 +Test: Total time: 0:14:15 +Final results: +Mean IoU is 0.00 + + precision@0.5 = 0.00 + precision@0.6 = 0.00 + precision@0.7 = 0.00 + precision@0.8 = 0.00 + precision@0.9 = 0.00 + overall IoU = 0.00 + mean IoU = 0.00 + +Mean accuracy for one-to-zero sample is 100.00 + +Average object IoU 0.0 +Overall IoU 0.0 +Epoch: [5] [ 0/4276] eta: 6:52:14 lr: 4.4337851079696714e-05 loss: 0.1787 (0.1787) time: 5.7845 data: 2.7058 max mem: 33300 +Epoch: [5] [ 10/4276] eta: 3:45:42 lr: 4.4335184738261074e-05 loss: 0.1796 (0.1878) time: 3.1746 data: 0.2535 max mem: 33300 +Epoch: [5] [ 20/4276] eta: 3:36:18 lr: 4.433251837900807e-05 loss: 0.1828 (0.1938) time: 2.9127 data: 0.0086 max mem: 33300 +Epoch: [5] [ 30/4276] eta: 3:32:02 lr: 4.43298520019364e-05 loss: 0.1887 (0.1955) time: 2.8985 data: 0.0081 max mem: 33300 +Epoch: [5] [ 40/4276] eta: 3:29:38 lr: 4.4327185607044746e-05 loss: 0.1771 (0.1924) time: 2.8856 data: 0.0072 max mem: 33300 +Epoch: [5] [ 50/4276] eta: 3:28:01 lr: 4.4324519194331805e-05 loss: 0.1763 (0.1893) time: 2.8872 data: 0.0071 max mem: 33300 +Epoch: [5] [ 60/4276] eta: 3:26:41 lr: 4.4321852763796255e-05 loss: 0.1707 (0.1888) time: 2.8842 data: 0.0073 max mem: 33300 +Epoch: [5] [ 70/4276] eta: 3:25:37 lr: 4.43191863154368e-05 loss: 0.1746 (0.1887) time: 2.8816 data: 0.0075 max mem: 33300 +Epoch: [5] [ 80/4276] eta: 3:24:42 lr: 4.431651984925212e-05 loss: 0.1861 (0.1889) time: 2.8835 data: 0.0079 max mem: 33300 +Epoch: [5] [ 90/4276] eta: 3:23:56 lr: 4.4313853365240906e-05 loss: 0.1821 (0.1872) time: 2.8871 data: 0.0078 max mem: 33300 +Epoch: [5] [ 100/4276] eta: 3:23:29 lr: 4.431118686340185e-05 loss: 0.1737 (0.1892) time: 2.9097 data: 0.0077 max mem: 33300 +Epoch: [5] [ 110/4276] eta: 3:23:02 lr: 4.4308520343733626e-05 loss: 0.1838 (0.1899) time: 2.9289 data: 0.0084 max mem: 33300 +Epoch: [5] [ 120/4276] eta: 3:22:38 lr: 4.4305853806234945e-05 loss: 0.1867 (0.1905) time: 2.9338 data: 0.0086 max mem: 33300 +Epoch: [5] [ 130/4276] eta: 3:22:13 lr: 4.4303187250904485e-05 loss: 0.1997 (0.1919) time: 2.9389 data: 0.0085 max mem: 33300 +Epoch: [5] [ 140/4276] eta: 3:21:47 lr: 4.4300520677740926e-05 loss: 0.1979 (0.1916) time: 2.9389 data: 0.0080 max mem: 33300 +Epoch: [5] [ 150/4276] eta: 3:21:20 lr: 4.429785408674297e-05 loss: 0.1865 (0.1914) time: 2.9382 data: 0.0076 max mem: 33300 +Epoch: [5] [ 160/4276] eta: 3:20:54 lr: 4.42951874779093e-05 loss: 0.1896 (0.1917) time: 2.9389 data: 0.0078 max mem: 33300 +Epoch: [5] [ 170/4276] eta: 3:20:24 lr: 4.42925208512386e-05 loss: 0.1956 (0.1921) time: 2.9329 data: 0.0080 max mem: 33300 +Epoch: [5] [ 180/4276] eta: 3:19:54 lr: 4.428985420672957e-05 loss: 0.1935 (0.1923) time: 2.9243 data: 0.0079 max mem: 33300 +Epoch: [5] [ 190/4276] eta: 3:19:27 lr: 4.4287187544380875e-05 loss: 0.1909 (0.1928) time: 2.9316 data: 0.0079 max mem: 33300 +Epoch: [5] [ 200/4276] eta: 3:19:00 lr: 4.428452086419121e-05 loss: 0.1968 (0.1941) time: 2.9399 data: 0.0080 max mem: 33300 +Epoch: [5] [ 210/4276] eta: 3:18:32 lr: 4.428185416615928e-05 loss: 0.1968 (0.1942) time: 2.9383 data: 0.0080 max mem: 33300 +Epoch: [5] [ 220/4276] eta: 3:18:05 lr: 4.427918745028376e-05 loss: 0.1866 (0.1940) time: 2.9386 data: 0.0077 max mem: 33300 +Epoch: [5] [ 230/4276] eta: 3:17:37 lr: 4.427652071656333e-05 loss: 0.1866 (0.1932) time: 2.9394 data: 0.0079 max mem: 33300 +Epoch: [5] [ 240/4276] eta: 3:17:09 lr: 4.427385396499667e-05 loss: 0.1889 (0.1933) time: 2.9379 data: 0.0083 max mem: 33300 +Epoch: [5] [ 250/4276] eta: 3:16:40 lr: 4.4271187195582484e-05 loss: 0.1988 (0.1942) time: 2.9376 data: 0.0081 max mem: 33300 +Epoch: [5] [ 260/4276] eta: 3:16:10 lr: 4.4268520408319455e-05 loss: 0.2002 (0.1946) time: 2.9305 data: 0.0083 max mem: 33300 +Epoch: [5] [ 270/4276] eta: 3:15:42 lr: 4.4265853603206264e-05 loss: 0.2018 (0.1948) time: 2.9313 data: 0.0087 max mem: 33300 +Epoch: [5] [ 280/4276] eta: 3:15:15 lr: 4.42631867802416e-05 loss: 0.1985 (0.1953) time: 2.9451 data: 0.0088 max mem: 33300 +Epoch: [5] [ 290/4276] eta: 3:14:46 lr: 4.4260519939424136e-05 loss: 0.1976 (0.1948) time: 2.9425 data: 0.0086 max mem: 33300 +Epoch: [5] [ 300/4276] eta: 3:14:19 lr: 4.425785308075258e-05 loss: 0.1783 (0.1946) time: 2.9391 data: 0.0084 max mem: 33300 +Epoch: [5] [ 310/4276] eta: 3:13:50 lr: 4.4255186204225604e-05 loss: 0.1809 (0.1944) time: 2.9406 data: 0.0082 max mem: 33300 +Epoch: [5] [ 320/4276] eta: 3:13:22 lr: 4.425251930984188e-05 loss: 0.1918 (0.1951) time: 2.9428 data: 0.0082 max mem: 33300 +Epoch: [5] [ 330/4276] eta: 3:12:49 lr: 4.424985239760012e-05 loss: 0.1960 (0.1949) time: 2.9242 data: 0.0088 max mem: 33300 +Epoch: [5] [ 340/4276] eta: 3:12:15 lr: 4.424718546749899e-05 loss: 0.1847 (0.1945) time: 2.8935 data: 0.0092 max mem: 33300 +Epoch: [5] [ 350/4276] eta: 3:11:40 lr: 4.4244518519537174e-05 loss: 0.1847 (0.1943) time: 2.8864 data: 0.0086 max mem: 33300 +Epoch: [5] [ 360/4276] eta: 3:11:12 lr: 4.424185155371337e-05 loss: 0.2058 (0.1948) time: 2.9138 data: 0.0086 max mem: 33300 +Epoch: [5] [ 370/4276] eta: 3:10:44 lr: 4.423918457002625e-05 loss: 0.1844 (0.1942) time: 2.9396 data: 0.0087 max mem: 33300 +Epoch: [5] [ 380/4276] eta: 3:10:16 lr: 4.42365175684745e-05 loss: 0.1779 (0.1942) time: 2.9420 data: 0.0082 max mem: 33300 +Epoch: [5] [ 390/4276] eta: 3:09:49 lr: 4.42338505490568e-05 loss: 0.1879 (0.1944) time: 2.9475 data: 0.0081 max mem: 33300 +Epoch: [5] [ 400/4276] eta: 3:09:21 lr: 4.423118351177184e-05 loss: 0.1918 (0.1945) time: 2.9463 data: 0.0082 max mem: 33300 +Epoch: [5] [ 410/4276] eta: 3:08:52 lr: 4.422851645661831e-05 loss: 0.1918 (0.1944) time: 2.9396 data: 0.0082 max mem: 33300 +Epoch: [5] [ 420/4276] eta: 3:08:22 lr: 4.4225849383594876e-05 loss: 0.1964 (0.1952) time: 2.9319 data: 0.0086 max mem: 33300 +Epoch: [5] [ 430/4276] eta: 3:07:49 lr: 4.422318229270023e-05 loss: 0.1891 (0.1953) time: 2.9056 data: 0.0089 max mem: 33300 +Epoch: [5] [ 440/4276] eta: 3:07:18 lr: 4.422051518393305e-05 loss: 0.1827 (0.1951) time: 2.8958 data: 0.0091 max mem: 33300 +Epoch: [5] [ 450/4276] eta: 3:06:48 lr: 4.421784805729202e-05 loss: 0.1916 (0.1952) time: 2.9190 data: 0.0086 max mem: 33300 +Epoch: [5] [ 460/4276] eta: 3:06:19 lr: 4.421518091277584e-05 loss: 0.1740 (0.1947) time: 2.9288 data: 0.0079 max mem: 33300 +Epoch: [5] [ 470/4276] eta: 3:05:51 lr: 4.421251375038316e-05 loss: 0.1727 (0.1945) time: 2.9360 data: 0.0078 max mem: 33300 +Epoch: [5] [ 480/4276] eta: 3:05:22 lr: 4.420984657011269e-05 loss: 0.1703 (0.1940) time: 2.9385 data: 0.0078 max mem: 33300 +Epoch: [5] [ 490/4276] eta: 3:04:53 lr: 4.420717937196309e-05 loss: 0.1750 (0.1939) time: 2.9370 data: 0.0076 max mem: 33300 +Epoch: [5] [ 500/4276] eta: 3:04:24 lr: 4.420451215593306e-05 loss: 0.1811 (0.1939) time: 2.9364 data: 0.0078 max mem: 33300 +Epoch: [5] [ 510/4276] eta: 3:03:55 lr: 4.420184492202127e-05 loss: 0.1758 (0.1936) time: 2.9367 data: 0.0079 max mem: 33300 +Epoch: [5] [ 520/4276] eta: 3:03:26 lr: 4.4199177670226406e-05 loss: 0.1731 (0.1936) time: 2.9365 data: 0.0077 max mem: 33300 +Epoch: [5] [ 530/4276] eta: 3:02:57 lr: 4.419651040054714e-05 loss: 0.1839 (0.1935) time: 2.9323 data: 0.0075 max mem: 33300 +Epoch: [5] [ 540/4276] eta: 3:02:29 lr: 4.419384311298217e-05 loss: 0.1799 (0.1934) time: 2.9392 data: 0.0077 max mem: 33300 +Epoch: [5] [ 550/4276] eta: 3:01:59 lr: 4.419117580753016e-05 loss: 0.1818 (0.1933) time: 2.9332 data: 0.0083 max mem: 33300 +Epoch: [5] [ 560/4276] eta: 3:01:30 lr: 4.41885084841898e-05 loss: 0.1895 (0.1935) time: 2.9264 data: 0.0081 max mem: 33300 +Epoch: [5] [ 570/4276] eta: 3:01:01 lr: 4.418584114295977e-05 loss: 0.1987 (0.1935) time: 2.9382 data: 0.0076 max mem: 33300 +Epoch: [5] [ 580/4276] eta: 3:00:31 lr: 4.418317378383875e-05 loss: 0.1834 (0.1935) time: 2.9333 data: 0.0077 max mem: 33300 +Epoch: [5] [ 590/4276] eta: 3:00:02 lr: 4.41805064068254e-05 loss: 0.1684 (0.1932) time: 2.9277 data: 0.0079 max mem: 33300 +Epoch: [5] [ 600/4276] eta: 2:59:33 lr: 4.4177839011918434e-05 loss: 0.1764 (0.1931) time: 2.9332 data: 0.0082 max mem: 33300 +Epoch: [5] [ 610/4276] eta: 2:59:04 lr: 4.417517159911651e-05 loss: 0.1866 (0.1929) time: 2.9348 data: 0.0084 max mem: 33300 +Epoch: [5] [ 620/4276] eta: 2:58:35 lr: 4.4172504168418314e-05 loss: 0.1810 (0.1929) time: 2.9361 data: 0.0084 max mem: 33300 +Epoch: [5] [ 630/4276] eta: 2:58:06 lr: 4.416983671982252e-05 loss: 0.1802 (0.1929) time: 2.9371 data: 0.0086 max mem: 33300 +Epoch: [5] [ 640/4276] eta: 2:57:37 lr: 4.416716925332781e-05 loss: 0.1783 (0.1927) time: 2.9391 data: 0.0088 max mem: 33300 +Epoch: [5] [ 650/4276] eta: 2:57:09 lr: 4.416450176893287e-05 loss: 0.1802 (0.1928) time: 2.9408 data: 0.0089 max mem: 33300 +Epoch: [5] [ 660/4276] eta: 2:56:39 lr: 4.416183426663636e-05 loss: 0.2002 (0.1929) time: 2.9370 data: 0.0090 max mem: 33300 +Epoch: [5] [ 670/4276] eta: 2:56:10 lr: 4.415916674643697e-05 loss: 0.1895 (0.1929) time: 2.9337 data: 0.0087 max mem: 33300 +Epoch: [5] [ 680/4276] eta: 2:55:41 lr: 4.4156499208333385e-05 loss: 0.1784 (0.1926) time: 2.9336 data: 0.0083 max mem: 33300 +Epoch: [5] [ 690/4276] eta: 2:55:12 lr: 4.415383165232428e-05 loss: 0.1784 (0.1925) time: 2.9327 data: 0.0079 max mem: 33300 +Epoch: [5] [ 700/4276] eta: 2:54:43 lr: 4.415116407840832e-05 loss: 0.1968 (0.1927) time: 2.9422 data: 0.0079 max mem: 33300 +Epoch: [5] [ 710/4276] eta: 2:54:14 lr: 4.41484964865842e-05 loss: 0.1985 (0.1927) time: 2.9426 data: 0.0081 max mem: 33300 +Epoch: [5] [ 720/4276] eta: 2:53:45 lr: 4.4145828876850584e-05 loss: 0.1889 (0.1926) time: 2.9382 data: 0.0080 max mem: 33300 +Epoch: [5] [ 730/4276] eta: 2:53:16 lr: 4.414316124920615e-05 loss: 0.1805 (0.1927) time: 2.9381 data: 0.0079 max mem: 33300 +Epoch: [5] [ 740/4276] eta: 2:52:47 lr: 4.414049360364958e-05 loss: 0.1856 (0.1927) time: 2.9366 data: 0.0076 max mem: 33300 +Epoch: [5] [ 750/4276] eta: 2:52:18 lr: 4.413782594017955e-05 loss: 0.1830 (0.1926) time: 2.9362 data: 0.0078 max mem: 33300 +Epoch: [5] [ 760/4276] eta: 2:51:49 lr: 4.413515825879474e-05 loss: 0.1709 (0.1924) time: 2.9365 data: 0.0078 max mem: 33300 +Epoch: [5] [ 770/4276] eta: 2:51:19 lr: 4.413249055949383e-05 loss: 0.1733 (0.1925) time: 2.9331 data: 0.0082 max mem: 33300 +Epoch: [5] [ 780/4276] eta: 2:50:50 lr: 4.412982284227548e-05 loss: 0.1878 (0.1925) time: 2.9238 data: 0.0085 max mem: 33300 +Epoch: [5] [ 790/4276] eta: 2:50:21 lr: 4.412715510713838e-05 loss: 0.1908 (0.1926) time: 2.9292 data: 0.0081 max mem: 33300 +Epoch: [5] [ 800/4276] eta: 2:49:52 lr: 4.4124487354081204e-05 loss: 0.1908 (0.1926) time: 2.9387 data: 0.0078 max mem: 33300 +Epoch: [5] [ 810/4276] eta: 2:49:22 lr: 4.412181958310262e-05 loss: 0.1816 (0.1926) time: 2.9360 data: 0.0077 max mem: 33300 +Epoch: [5] [ 820/4276] eta: 2:48:53 lr: 4.4119151794201316e-05 loss: 0.1723 (0.1925) time: 2.9343 data: 0.0076 max mem: 33300 +Epoch: [5] [ 830/4276] eta: 2:48:24 lr: 4.411648398737595e-05 loss: 0.1723 (0.1926) time: 2.9353 data: 0.0078 max mem: 33300 +Epoch: [5] [ 840/4276] eta: 2:47:55 lr: 4.411381616262522e-05 loss: 0.1789 (0.1927) time: 2.9346 data: 0.0082 max mem: 33300 +Epoch: [5] [ 850/4276] eta: 2:47:25 lr: 4.411114831994778e-05 loss: 0.1793 (0.1927) time: 2.9318 data: 0.0079 max mem: 33300 +Epoch: [5] [ 860/4276] eta: 2:46:56 lr: 4.410848045934231e-05 loss: 0.1793 (0.1928) time: 2.9273 data: 0.0076 max mem: 33300 +Epoch: [5] [ 870/4276] eta: 2:46:26 lr: 4.4105812580807504e-05 loss: 0.1833 (0.1928) time: 2.9250 data: 0.0080 max mem: 33300 +Epoch: [5] [ 880/4276] eta: 2:45:56 lr: 4.4103144684342016e-05 loss: 0.1833 (0.1928) time: 2.9234 data: 0.0091 max mem: 33300 +Epoch: [5] [ 890/4276] eta: 2:45:27 lr: 4.410047676994452e-05 loss: 0.1959 (0.1929) time: 2.9290 data: 0.0090 max mem: 33300 +Epoch: [5] [ 900/4276] eta: 2:44:58 lr: 4.4097808837613695e-05 loss: 0.1990 (0.1929) time: 2.9331 data: 0.0082 max mem: 33300 +Epoch: [5] [ 910/4276] eta: 2:44:29 lr: 4.409514088734822e-05 loss: 0.1932 (0.1929) time: 2.9343 data: 0.0082 max mem: 33300 +Epoch: [5] [ 920/4276] eta: 2:43:59 lr: 4.409247291914676e-05 loss: 0.1910 (0.1929) time: 2.9365 data: 0.0091 max mem: 33300 +Epoch: [5] [ 930/4276] eta: 2:43:29 lr: 4.4089804933008e-05 loss: 0.1859 (0.1928) time: 2.9172 data: 0.0094 max mem: 33300 +Epoch: [5] [ 940/4276] eta: 2:42:58 lr: 4.40871369289306e-05 loss: 0.1717 (0.1926) time: 2.8959 data: 0.0090 max mem: 33300 +Epoch: [5] [ 950/4276] eta: 2:42:28 lr: 4.408446890691324e-05 loss: 0.1827 (0.1927) time: 2.9030 data: 0.0090 max mem: 33300 +Epoch: [5] [ 960/4276] eta: 2:41:59 lr: 4.4081800866954595e-05 loss: 0.1870 (0.1928) time: 2.9244 data: 0.0084 max mem: 33300 +Epoch: [5] [ 970/4276] eta: 2:41:29 lr: 4.407913280905333e-05 loss: 0.1877 (0.1928) time: 2.9251 data: 0.0079 max mem: 33300 +Epoch: [5] [ 980/4276] eta: 2:40:58 lr: 4.407646473320812e-05 loss: 0.1974 (0.1930) time: 2.8969 data: 0.0079 max mem: 33300 +Epoch: [5] [ 990/4276] eta: 2:40:27 lr: 4.4073796639417644e-05 loss: 0.1929 (0.1929) time: 2.8812 data: 0.0077 max mem: 33300 +Epoch: [5] [1000/4276] eta: 2:39:56 lr: 4.407112852768057e-05 loss: 0.1869 (0.1929) time: 2.8810 data: 0.0078 max mem: 33300 +Epoch: [5] [1010/4276] eta: 2:39:25 lr: 4.406846039799558e-05 loss: 0.1831 (0.1929) time: 2.8790 data: 0.0077 max mem: 33300 +Epoch: [5] [1020/4276] eta: 2:38:55 lr: 4.406579225036132e-05 loss: 0.1831 (0.1928) time: 2.8789 data: 0.0079 max mem: 33300 +Epoch: [5] [1030/4276] eta: 2:38:24 lr: 4.4063124084776486e-05 loss: 0.1930 (0.1929) time: 2.8785 data: 0.0081 max mem: 33300 +Epoch: [5] [1040/4276] eta: 2:37:53 lr: 4.406045590123974e-05 loss: 0.1930 (0.1929) time: 2.8812 data: 0.0084 max mem: 33300 +Epoch: [5] [1050/4276] eta: 2:37:22 lr: 4.405778769974975e-05 loss: 0.1848 (0.1929) time: 2.8827 data: 0.0089 max mem: 33300 +Epoch: [5] [1060/4276] eta: 2:36:52 lr: 4.405511948030519e-05 loss: 0.1861 (0.1930) time: 2.8801 data: 0.0087 max mem: 33300 +Epoch: [5] [1070/4276] eta: 2:36:21 lr: 4.405245124290474e-05 loss: 0.1933 (0.1929) time: 2.8777 data: 0.0083 max mem: 33300 +Epoch: [5] [1080/4276] eta: 2:35:50 lr: 4.4049782987547064e-05 loss: 0.1798 (0.1928) time: 2.8750 data: 0.0081 max mem: 33300 +Epoch: [5] [1090/4276] eta: 2:35:21 lr: 4.4047114714230824e-05 loss: 0.1798 (0.1927) time: 2.8992 data: 0.0088 max mem: 33300 +Epoch: [5] [1100/4276] eta: 2:34:52 lr: 4.40444464229547e-05 loss: 0.1785 (0.1928) time: 2.9277 data: 0.0091 max mem: 33300 +Epoch: [5] [1110/4276] eta: 2:34:23 lr: 4.404177811371737e-05 loss: 0.1785 (0.1927) time: 2.9327 data: 0.0088 max mem: 33300 +Epoch: [5] [1120/4276] eta: 2:33:54 lr: 4.4039109786517486e-05 loss: 0.1882 (0.1929) time: 2.9327 data: 0.0088 max mem: 33300 +Epoch: [5] [1130/4276] eta: 2:33:24 lr: 4.403644144135372e-05 loss: 0.1855 (0.1927) time: 2.9279 data: 0.0087 max mem: 33300 +Epoch: [5] [1140/4276] eta: 2:32:55 lr: 4.403377307822476e-05 loss: 0.1814 (0.1925) time: 2.9207 data: 0.0090 max mem: 33300 +Epoch: [5] [1150/4276] eta: 2:32:26 lr: 4.403110469712925e-05 loss: 0.1849 (0.1925) time: 2.9241 data: 0.0086 max mem: 33300 +Epoch: [5] [1160/4276] eta: 2:31:56 lr: 4.4028436298065885e-05 loss: 0.1909 (0.1926) time: 2.9269 data: 0.0077 max mem: 33300 +Epoch: [5] [1170/4276] eta: 2:31:27 lr: 4.4025767881033315e-05 loss: 0.1949 (0.1928) time: 2.9255 data: 0.0080 max mem: 33300 +Epoch: [5] [1180/4276] eta: 2:30:58 lr: 4.4023099446030216e-05 loss: 0.1943 (0.1926) time: 2.9284 data: 0.0078 max mem: 33300 +Epoch: [5] [1190/4276] eta: 2:30:29 lr: 4.402043099305526e-05 loss: 0.1721 (0.1925) time: 2.9278 data: 0.0076 max mem: 33300 +Epoch: [5] [1200/4276] eta: 2:29:59 lr: 4.40177625221071e-05 loss: 0.1721 (0.1925) time: 2.9276 data: 0.0076 max mem: 33300 +Epoch: [5] [1210/4276] eta: 2:29:30 lr: 4.401509403318442e-05 loss: 0.1718 (0.1924) time: 2.9291 data: 0.0072 max mem: 33300 +Epoch: [5] [1220/4276] eta: 2:29:01 lr: 4.4012425526285884e-05 loss: 0.1706 (0.1923) time: 2.9296 data: 0.0072 max mem: 33300 +Epoch: [5] [1230/4276] eta: 2:28:32 lr: 4.400975700141016e-05 loss: 0.1807 (0.1923) time: 2.9300 data: 0.0080 max mem: 33300 +Epoch: [5] [1240/4276] eta: 2:28:02 lr: 4.400708845855592e-05 loss: 0.1873 (0.1924) time: 2.9112 data: 0.0087 max mem: 33300 +Epoch: [5] [1250/4276] eta: 2:27:32 lr: 4.400441989772182e-05 loss: 0.1873 (0.1923) time: 2.8882 data: 0.0087 max mem: 33300 +Epoch: [5] [1260/4276] eta: 2:27:01 lr: 4.400175131890654e-05 loss: 0.1719 (0.1921) time: 2.8818 data: 0.0083 max mem: 33300 +Epoch: [5] [1270/4276] eta: 2:26:31 lr: 4.3999082722108735e-05 loss: 0.1717 (0.1921) time: 2.8787 data: 0.0079 max mem: 33300 +Epoch: [5] [1280/4276] eta: 2:26:01 lr: 4.399641410732708e-05 loss: 0.1865 (0.1921) time: 2.8772 data: 0.0080 max mem: 33300 +Epoch: [5] [1290/4276] eta: 2:25:30 lr: 4.3993745474560246e-05 loss: 0.1820 (0.1921) time: 2.8789 data: 0.0081 max mem: 33300 +Epoch: [5] [1300/4276] eta: 2:25:00 lr: 4.3991076823806884e-05 loss: 0.1710 (0.1920) time: 2.8790 data: 0.0083 max mem: 33300 +Epoch: [5] [1310/4276] eta: 2:24:30 lr: 4.398840815506568e-05 loss: 0.1658 (0.1918) time: 2.8781 data: 0.0082 max mem: 33300 +Epoch: [5] [1320/4276] eta: 2:24:00 lr: 4.398573946833528e-05 loss: 0.1777 (0.1919) time: 2.8803 data: 0.0080 max mem: 33300 +Epoch: [5] [1330/4276] eta: 2:23:31 lr: 4.3983070763614365e-05 loss: 0.1758 (0.1917) time: 2.9197 data: 0.0089 max mem: 33300 +Epoch: [5] [1340/4276] eta: 2:23:03 lr: 4.39804020409016e-05 loss: 0.1723 (0.1917) time: 2.9634 data: 0.0099 max mem: 33300 +Epoch: [5] [1350/4276] eta: 2:22:34 lr: 4.397773330019564e-05 loss: 0.1838 (0.1916) time: 2.9460 data: 0.0095 max mem: 33300 +Epoch: [5] [1360/4276] eta: 2:22:05 lr: 4.397506454149516e-05 loss: 0.1926 (0.1916) time: 2.9251 data: 0.0088 max mem: 33300 +Epoch: [5] [1370/4276] eta: 2:21:35 lr: 4.397239576479882e-05 loss: 0.1879 (0.1915) time: 2.9297 data: 0.0087 max mem: 33300 +Epoch: [5] [1380/4276] eta: 2:21:06 lr: 4.396972697010529e-05 loss: 0.1889 (0.1916) time: 2.9324 data: 0.0085 max mem: 33300 +Epoch: [5] [1390/4276] eta: 2:20:37 lr: 4.396705815741323e-05 loss: 0.2014 (0.1916) time: 2.9318 data: 0.0087 max mem: 33300 +Epoch: [5] [1400/4276] eta: 2:20:08 lr: 4.396438932672131e-05 loss: 0.1980 (0.1917) time: 2.9318 data: 0.0088 max mem: 33300 +Epoch: [5] [1410/4276] eta: 2:19:38 lr: 4.3961720478028185e-05 loss: 0.1934 (0.1916) time: 2.9099 data: 0.0081 max mem: 33300 +Epoch: [5] [1420/4276] eta: 2:19:08 lr: 4.3959051611332535e-05 loss: 0.1909 (0.1918) time: 2.8846 data: 0.0082 max mem: 33300 +Epoch: [5] [1430/4276] eta: 2:18:38 lr: 4.395638272663301e-05 loss: 0.1829 (0.1917) time: 2.8790 data: 0.0081 max mem: 33300 +Epoch: [5] [1440/4276] eta: 2:18:08 lr: 4.3953713823928275e-05 loss: 0.1879 (0.1919) time: 2.8788 data: 0.0075 max mem: 33300 +Epoch: [5] [1450/4276] eta: 2:17:39 lr: 4.3951044903217e-05 loss: 0.1909 (0.1918) time: 2.9010 data: 0.0085 max mem: 33300 +Epoch: [5] [1460/4276] eta: 2:17:09 lr: 4.394837596449784e-05 loss: 0.1835 (0.1919) time: 2.9193 data: 0.0101 max mem: 33300 +Epoch: [5] [1470/4276] eta: 2:16:40 lr: 4.394570700776948e-05 loss: 0.1861 (0.1918) time: 2.9158 data: 0.0104 max mem: 33300 +Epoch: [5] [1480/4276] eta: 2:16:10 lr: 4.3943038033030565e-05 loss: 0.1909 (0.1918) time: 2.9027 data: 0.0099 max mem: 33300 +Epoch: [5] [1490/4276] eta: 2:15:41 lr: 4.394036904027975e-05 loss: 0.1833 (0.1918) time: 2.8976 data: 0.0094 max mem: 33300 +Epoch: [5] [1500/4276] eta: 2:15:11 lr: 4.393770002951572e-05 loss: 0.1794 (0.1917) time: 2.8920 data: 0.0090 max mem: 33300 +Epoch: [5] [1510/4276] eta: 2:14:41 lr: 4.393503100073712e-05 loss: 0.1823 (0.1918) time: 2.8800 data: 0.0085 max mem: 33300 +Epoch: [5] [1520/4276] eta: 2:14:11 lr: 4.393236195394262e-05 loss: 0.1913 (0.1918) time: 2.8796 data: 0.0079 max mem: 33300 +Epoch: [5] [1530/4276] eta: 2:13:41 lr: 4.3929692889130876e-05 loss: 0.1970 (0.1918) time: 2.8795 data: 0.0079 max mem: 33300 +Epoch: [5] [1540/4276] eta: 2:13:11 lr: 4.3927023806300553e-05 loss: 0.1867 (0.1918) time: 2.8811 data: 0.0085 max mem: 33300 +Epoch: [5] [1550/4276] eta: 2:12:41 lr: 4.392435470545033e-05 loss: 0.1883 (0.1919) time: 2.8818 data: 0.0088 max mem: 33300 +Epoch: [5] [1560/4276] eta: 2:12:11 lr: 4.3921685586578836e-05 loss: 0.1804 (0.1918) time: 2.8916 data: 0.0088 max mem: 33300 +Epoch: [5] [1570/4276] eta: 2:11:42 lr: 4.391901644968476e-05 loss: 0.1713 (0.1917) time: 2.8921 data: 0.0083 max mem: 33300 +Epoch: [5] [1580/4276] eta: 2:11:12 lr: 4.3916347294766754e-05 loss: 0.1635 (0.1916) time: 2.8805 data: 0.0079 max mem: 33300 +Epoch: [5] [1590/4276] eta: 2:10:42 lr: 4.391367812182347e-05 loss: 0.1696 (0.1916) time: 2.8794 data: 0.0083 max mem: 33300 +Epoch: [5] [1600/4276] eta: 2:10:12 lr: 4.391100893085358e-05 loss: 0.1789 (0.1916) time: 2.8927 data: 0.0084 max mem: 33300 +Epoch: [5] [1610/4276] eta: 2:09:43 lr: 4.390833972185574e-05 loss: 0.1794 (0.1915) time: 2.9140 data: 0.0084 max mem: 33300 +Epoch: [5] [1620/4276] eta: 2:09:14 lr: 4.390567049482862e-05 loss: 0.1772 (0.1914) time: 2.9343 data: 0.0087 max mem: 33300 +Epoch: [5] [1630/4276] eta: 2:08:45 lr: 4.390300124977087e-05 loss: 0.1835 (0.1914) time: 2.9404 data: 0.0092 max mem: 33300 +Epoch: [5] [1640/4276] eta: 2:08:16 lr: 4.390033198668115e-05 loss: 0.1812 (0.1915) time: 2.9343 data: 0.0092 max mem: 33300 +Epoch: [5] [1650/4276] eta: 2:07:48 lr: 4.3897662705558124e-05 loss: 0.1724 (0.1915) time: 2.9372 data: 0.0090 max mem: 33300 +Epoch: [5] [1660/4276] eta: 2:07:18 lr: 4.389499340640045e-05 loss: 0.1855 (0.1914) time: 2.9135 data: 0.0089 max mem: 33300 +Epoch: [5] [1670/4276] eta: 2:06:48 lr: 4.3892324089206785e-05 loss: 0.1855 (0.1915) time: 2.8842 data: 0.0081 max mem: 33300 +Epoch: [5] [1680/4276] eta: 2:06:18 lr: 4.3889654753975795e-05 loss: 0.2070 (0.1916) time: 2.8819 data: 0.0081 max mem: 33300 +Epoch: [5] [1690/4276] eta: 2:05:49 lr: 4.3886985400706135e-05 loss: 0.2054 (0.1916) time: 2.8830 data: 0.0080 max mem: 33300 +Epoch: [5] [1700/4276] eta: 2:05:19 lr: 4.388431602939647e-05 loss: 0.1896 (0.1917) time: 2.8838 data: 0.0078 max mem: 33300 +Epoch: [5] [1710/4276] eta: 2:04:49 lr: 4.3881646640045447e-05 loss: 0.2046 (0.1917) time: 2.8831 data: 0.0079 max mem: 33300 +Epoch: [5] [1720/4276] eta: 2:04:20 lr: 4.387897723265173e-05 loss: 0.2065 (0.1918) time: 2.8925 data: 0.0083 max mem: 33300 +Epoch: [5] [1730/4276] eta: 2:03:51 lr: 4.387630780721399e-05 loss: 0.1939 (0.1918) time: 2.9238 data: 0.0090 max mem: 33300 +Epoch: [5] [1740/4276] eta: 2:03:22 lr: 4.387363836373086e-05 loss: 0.1844 (0.1918) time: 2.9418 data: 0.0093 max mem: 33300 +Epoch: [5] [1750/4276] eta: 2:02:53 lr: 4.3870968902201016e-05 loss: 0.1894 (0.1918) time: 2.9393 data: 0.0094 max mem: 33300 +Epoch: [5] [1760/4276] eta: 2:02:24 lr: 4.386829942262311e-05 loss: 0.1894 (0.1918) time: 2.9404 data: 0.0094 max mem: 33300 +Epoch: [5] [1770/4276] eta: 2:01:55 lr: 4.38656299249958e-05 loss: 0.1924 (0.1918) time: 2.9405 data: 0.0094 max mem: 33300 +Epoch: [5] [1780/4276] eta: 2:01:26 lr: 4.3862960409317756e-05 loss: 0.2066 (0.1918) time: 2.9376 data: 0.0096 max mem: 33300 +Epoch: [5] [1790/4276] eta: 2:00:57 lr: 4.386029087558761e-05 loss: 0.1835 (0.1918) time: 2.9380 data: 0.0096 max mem: 33300 +Epoch: [5] [1800/4276] eta: 2:00:29 lr: 4.3857621323804035e-05 loss: 0.1900 (0.1919) time: 2.9390 data: 0.0090 max mem: 33300 +Epoch: [5] [1810/4276] eta: 2:00:00 lr: 4.38549517539657e-05 loss: 0.2116 (0.1920) time: 2.9394 data: 0.0085 max mem: 33300 +Epoch: [5] [1820/4276] eta: 1:59:31 lr: 4.3852282166071236e-05 loss: 0.1825 (0.1919) time: 2.9404 data: 0.0083 max mem: 33300 +Epoch: [5] [1830/4276] eta: 1:59:02 lr: 4.3849612560119314e-05 loss: 0.1673 (0.1919) time: 2.9407 data: 0.0086 max mem: 33300 +Epoch: [5] [1840/4276] eta: 1:58:33 lr: 4.384694293610859e-05 loss: 0.1696 (0.1918) time: 2.9398 data: 0.0086 max mem: 33300 +Epoch: [5] [1850/4276] eta: 1:58:04 lr: 4.3844273294037705e-05 loss: 0.1974 (0.1919) time: 2.9385 data: 0.0085 max mem: 33300 +Epoch: [5] [1860/4276] eta: 1:57:35 lr: 4.384160363390535e-05 loss: 0.1974 (0.1919) time: 2.9434 data: 0.0085 max mem: 33300 +Epoch: [5] [1870/4276] eta: 1:57:06 lr: 4.383893395571014e-05 loss: 0.1984 (0.1920) time: 2.9429 data: 0.0083 max mem: 33300 +Epoch: [5] [1880/4276] eta: 1:56:37 lr: 4.383626425945075e-05 loss: 0.1905 (0.1920) time: 2.9436 data: 0.0084 max mem: 33300 +Epoch: [5] [1890/4276] eta: 1:56:08 lr: 4.383359454512585e-05 loss: 0.1830 (0.1919) time: 2.9400 data: 0.0087 max mem: 33300 +Epoch: [5] [1900/4276] eta: 1:55:39 lr: 4.383092481273407e-05 loss: 0.1754 (0.1919) time: 2.9327 data: 0.0090 max mem: 33300 +Epoch: [5] [1910/4276] eta: 1:55:10 lr: 4.382825506227407e-05 loss: 0.1765 (0.1919) time: 2.9332 data: 0.0083 max mem: 33300 +Epoch: [5] [1920/4276] eta: 1:54:41 lr: 4.3825585293744516e-05 loss: 0.1865 (0.1918) time: 2.9360 data: 0.0076 max mem: 33300 +Epoch: [5] [1930/4276] eta: 1:54:12 lr: 4.3822915507144055e-05 loss: 0.1865 (0.1918) time: 2.9391 data: 0.0079 max mem: 33300 +Epoch: [5] [1940/4276] eta: 1:53:43 lr: 4.382024570247134e-05 loss: 0.1920 (0.1918) time: 2.9359 data: 0.0078 max mem: 33300 +Epoch: [5] [1950/4276] eta: 1:53:14 lr: 4.3817575879725035e-05 loss: 0.1917 (0.1918) time: 2.9330 data: 0.0080 max mem: 33300 +Epoch: [5] [1960/4276] eta: 1:52:45 lr: 4.381490603890378e-05 loss: 0.1694 (0.1918) time: 2.9384 data: 0.0082 max mem: 33300 +Epoch: [5] [1970/4276] eta: 1:52:16 lr: 4.381223618000624e-05 loss: 0.1660 (0.1917) time: 2.9391 data: 0.0081 max mem: 33300 +Epoch: [5] [1980/4276] eta: 1:51:47 lr: 4.380956630303106e-05 loss: 0.1667 (0.1916) time: 2.9337 data: 0.0079 max mem: 33300 +Epoch: [5] [1990/4276] eta: 1:51:18 lr: 4.380689640797689e-05 loss: 0.1956 (0.1917) time: 2.9342 data: 0.0077 max mem: 33300 +Epoch: [5] [2000/4276] eta: 1:50:49 lr: 4.38042264948424e-05 loss: 0.1923 (0.1917) time: 2.9390 data: 0.0077 max mem: 33300 +Epoch: [5] [2010/4276] eta: 1:50:20 lr: 4.380155656362624e-05 loss: 0.1858 (0.1916) time: 2.9359 data: 0.0083 max mem: 33300 +Epoch: [5] [2020/4276] eta: 1:49:51 lr: 4.379888661432705e-05 loss: 0.1832 (0.1916) time: 2.9310 data: 0.0080 max mem: 33300 +Epoch: [5] [2030/4276] eta: 1:49:22 lr: 4.3796216646943494e-05 loss: 0.1832 (0.1916) time: 2.9358 data: 0.0072 max mem: 33300 +Epoch: [5] [2040/4276] eta: 1:48:53 lr: 4.379354666147422e-05 loss: 0.1745 (0.1915) time: 2.9367 data: 0.0075 max mem: 33300 +Epoch: [5] [2050/4276] eta: 1:48:23 lr: 4.3790876657917875e-05 loss: 0.1780 (0.1915) time: 2.9340 data: 0.0075 max mem: 33300 +Epoch: [5] [2060/4276] eta: 1:47:54 lr: 4.378820663627312e-05 loss: 0.1808 (0.1915) time: 2.9330 data: 0.0073 max mem: 33300 +Epoch: [5] [2070/4276] eta: 1:47:25 lr: 4.37855365965386e-05 loss: 0.1826 (0.1914) time: 2.9332 data: 0.0077 max mem: 33300 +Epoch: [5] [2080/4276] eta: 1:46:56 lr: 4.378286653871297e-05 loss: 0.1841 (0.1915) time: 2.9325 data: 0.0079 max mem: 33300 +Epoch: [5] [2090/4276] eta: 1:46:27 lr: 4.378019646279489e-05 loss: 0.1923 (0.1914) time: 2.9351 data: 0.0078 max mem: 33300 +Epoch: [5] [2100/4276] eta: 1:45:58 lr: 4.3777526368783004e-05 loss: 0.1823 (0.1914) time: 2.9380 data: 0.0078 max mem: 33300 +Epoch: [5] [2110/4276] eta: 1:45:29 lr: 4.377485625667595e-05 loss: 0.1770 (0.1914) time: 2.9393 data: 0.0076 max mem: 33300 +Epoch: [5] [2120/4276] eta: 1:45:00 lr: 4.37721861264724e-05 loss: 0.1583 (0.1912) time: 2.9376 data: 0.0076 max mem: 33300 +Epoch: [5] [2130/4276] eta: 1:44:31 lr: 4.376951597817099e-05 loss: 0.1446 (0.1912) time: 2.9221 data: 0.0078 max mem: 33300 +Epoch: [5] [2140/4276] eta: 1:44:01 lr: 4.376684581177038e-05 loss: 0.1796 (0.1912) time: 2.9085 data: 0.0080 max mem: 33300 +Epoch: [5] [2150/4276] eta: 1:43:32 lr: 4.376417562726922e-05 loss: 0.1814 (0.1911) time: 2.9147 data: 0.0080 max mem: 33300 +Epoch: [5] [2160/4276] eta: 1:43:03 lr: 4.376150542466615e-05 loss: 0.1814 (0.1911) time: 2.9211 data: 0.0081 max mem: 33300 +Epoch: [5] [2170/4276] eta: 1:42:33 lr: 4.375883520395984e-05 loss: 0.1908 (0.1912) time: 2.9195 data: 0.0080 max mem: 33300 +Epoch: [5] [2180/4276] eta: 1:42:04 lr: 4.375616496514892e-05 loss: 0.1992 (0.1912) time: 2.9183 data: 0.0078 max mem: 33300 +Epoch: [5] [2190/4276] eta: 1:41:35 lr: 4.3753494708232054e-05 loss: 0.1838 (0.1912) time: 2.9187 data: 0.0078 max mem: 33300 +Epoch: [5] [2200/4276] eta: 1:41:06 lr: 4.375082443320788e-05 loss: 0.1843 (0.1912) time: 2.9200 data: 0.0078 max mem: 33300 +Epoch: [5] [2210/4276] eta: 1:40:36 lr: 4.374815414007504e-05 loss: 0.1910 (0.1913) time: 2.9207 data: 0.0080 max mem: 33300 +Epoch: [5] [2220/4276] eta: 1:40:07 lr: 4.3745483828832205e-05 loss: 0.1910 (0.1913) time: 2.9222 data: 0.0081 max mem: 33300 +Epoch: [5] [2230/4276] eta: 1:39:38 lr: 4.3742813499478015e-05 loss: 0.1801 (0.1912) time: 2.9100 data: 0.0085 max mem: 33300 +Epoch: [5] [2240/4276] eta: 1:39:08 lr: 4.374014315201112e-05 loss: 0.1769 (0.1911) time: 2.9003 data: 0.0090 max mem: 33300 +Epoch: [5] [2250/4276] eta: 1:38:39 lr: 4.3737472786430155e-05 loss: 0.1861 (0.1911) time: 2.9110 data: 0.0089 max mem: 33300 +Epoch: [5] [2260/4276] eta: 1:38:10 lr: 4.373480240273378e-05 loss: 0.1861 (0.1912) time: 2.9208 data: 0.0087 max mem: 33300 +Epoch: [5] [2270/4276] eta: 1:37:41 lr: 4.373213200092065e-05 loss: 0.1911 (0.1912) time: 2.9225 data: 0.0082 max mem: 33300 +Epoch: [5] [2280/4276] eta: 1:37:12 lr: 4.37294615809894e-05 loss: 0.1886 (0.1912) time: 2.9240 data: 0.0085 max mem: 33300 +Epoch: [5] [2290/4276] eta: 1:36:42 lr: 4.3726791142938685e-05 loss: 0.1735 (0.1912) time: 2.9234 data: 0.0087 max mem: 33300 +Epoch: [5] [2300/4276] eta: 1:36:13 lr: 4.372412068676714e-05 loss: 0.1721 (0.1911) time: 2.9184 data: 0.0086 max mem: 33300 +Epoch: [5] [2310/4276] eta: 1:35:44 lr: 4.372145021247343e-05 loss: 0.1818 (0.1910) time: 2.9120 data: 0.0089 max mem: 33300 +Epoch: [5] [2320/4276] eta: 1:35:15 lr: 4.3718779720056205e-05 loss: 0.1838 (0.1910) time: 2.9149 data: 0.0083 max mem: 33300 +Epoch: [5] [2330/4276] eta: 1:34:45 lr: 4.371610920951409e-05 loss: 0.1755 (0.1910) time: 2.9310 data: 0.0078 max mem: 33300 +Epoch: [5] [2340/4276] eta: 1:34:16 lr: 4.3713438680845745e-05 loss: 0.1857 (0.1909) time: 2.9428 data: 0.0080 max mem: 33300 +Epoch: [5] [2350/4276] eta: 1:33:47 lr: 4.371076813404981e-05 loss: 0.1837 (0.1909) time: 2.9422 data: 0.0080 max mem: 33300 +Epoch: [5] [2360/4276] eta: 1:33:18 lr: 4.370809756912494e-05 loss: 0.1770 (0.1908) time: 2.9383 data: 0.0082 max mem: 33300 +Epoch: [5] [2370/4276] eta: 1:32:49 lr: 4.370542698606978e-05 loss: 0.1859 (0.1908) time: 2.9394 data: 0.0084 max mem: 33300 +Epoch: [5] [2380/4276] eta: 1:32:20 lr: 4.370275638488297e-05 loss: 0.1972 (0.1909) time: 2.9404 data: 0.0082 max mem: 33300 +Epoch: [5] [2390/4276] eta: 1:31:51 lr: 4.3700085765563154e-05 loss: 0.1676 (0.1908) time: 2.9395 data: 0.0080 max mem: 33300 +Epoch: [5] [2400/4276] eta: 1:31:22 lr: 4.369741512810899e-05 loss: 0.1696 (0.1909) time: 2.9404 data: 0.0084 max mem: 33300 +Epoch: [5] [2410/4276] eta: 1:30:53 lr: 4.369474447251912e-05 loss: 0.1858 (0.1908) time: 2.9372 data: 0.0087 max mem: 33300 +Epoch: [5] [2420/4276] eta: 1:30:24 lr: 4.369207379879218e-05 loss: 0.1770 (0.1908) time: 2.9295 data: 0.0082 max mem: 33300 +Epoch: [5] [2430/4276] eta: 1:29:54 lr: 4.368940310692682e-05 loss: 0.1848 (0.1908) time: 2.9242 data: 0.0080 max mem: 33300 +Epoch: [5] [2440/4276] eta: 1:29:25 lr: 4.368673239692168e-05 loss: 0.1897 (0.1908) time: 2.9250 data: 0.0081 max mem: 33300 +Epoch: [5] [2450/4276] eta: 1:28:56 lr: 4.3684061668775416e-05 loss: 0.1794 (0.1908) time: 2.9156 data: 0.0087 max mem: 33300 +Epoch: [5] [2460/4276] eta: 1:28:26 lr: 4.368139092248667e-05 loss: 0.1794 (0.1908) time: 2.9060 data: 0.0091 max mem: 33300 +Epoch: [5] [2470/4276] eta: 1:27:57 lr: 4.3678720158054065e-05 loss: 0.1880 (0.1908) time: 2.8957 data: 0.0091 max mem: 33300 +Epoch: [5] [2480/4276] eta: 1:27:28 lr: 4.367604937547628e-05 loss: 0.1880 (0.1908) time: 2.8900 data: 0.0090 max mem: 33300 +Epoch: [5] [2490/4276] eta: 1:26:58 lr: 4.367337857475193e-05 loss: 0.1770 (0.1908) time: 2.9074 data: 0.0088 max mem: 33300 +Epoch: [5] [2500/4276] eta: 1:26:29 lr: 4.3670707755879674e-05 loss: 0.1818 (0.1908) time: 2.9200 data: 0.0083 max mem: 33300 +Epoch: [5] [2510/4276] eta: 1:26:00 lr: 4.366803691885816e-05 loss: 0.1854 (0.1908) time: 2.9227 data: 0.0078 max mem: 33300 +Epoch: [5] [2520/4276] eta: 1:25:31 lr: 4.366536606368601e-05 loss: 0.1593 (0.1907) time: 2.9242 data: 0.0076 max mem: 33300 +Epoch: [5] [2530/4276] eta: 1:25:01 lr: 4.3662695190361884e-05 loss: 0.1473 (0.1905) time: 2.9242 data: 0.0078 max mem: 33300 +Epoch: [5] [2540/4276] eta: 1:24:32 lr: 4.366002429888442e-05 loss: 0.1585 (0.1905) time: 2.9227 data: 0.0078 max mem: 33300 +Epoch: [5] [2550/4276] eta: 1:24:03 lr: 4.365735338925227e-05 loss: 0.1720 (0.1904) time: 2.9226 data: 0.0076 max mem: 33300 +Epoch: [5] [2560/4276] eta: 1:23:34 lr: 4.3654682461464056e-05 loss: 0.1625 (0.1903) time: 2.9232 data: 0.0078 max mem: 33300 +Epoch: [5] [2570/4276] eta: 1:23:05 lr: 4.365201151551843e-05 loss: 0.1592 (0.1903) time: 2.9237 data: 0.0082 max mem: 33300 +Epoch: [5] [2580/4276] eta: 1:22:35 lr: 4.364934055141405e-05 loss: 0.1748 (0.1903) time: 2.9237 data: 0.0079 max mem: 33300 +Epoch: [5] [2590/4276] eta: 1:22:06 lr: 4.364666956914953e-05 loss: 0.1748 (0.1902) time: 2.9230 data: 0.0078 max mem: 33300 +Epoch: [5] [2600/4276] eta: 1:21:37 lr: 4.364399856872353e-05 loss: 0.1855 (0.1903) time: 2.9220 data: 0.0078 max mem: 33300 +Epoch: [5] [2610/4276] eta: 1:21:08 lr: 4.3641327550134684e-05 loss: 0.1808 (0.1902) time: 2.9207 data: 0.0080 max mem: 33300 +Epoch: [5] [2620/4276] eta: 1:20:38 lr: 4.363865651338164e-05 loss: 0.1859 (0.1902) time: 2.9193 data: 0.0079 max mem: 33300 +Epoch: [5] [2630/4276] eta: 1:20:09 lr: 4.363598545846304e-05 loss: 0.1760 (0.1901) time: 2.9234 data: 0.0075 max mem: 33300 +Epoch: [5] [2640/4276] eta: 1:19:40 lr: 4.3633314385377514e-05 loss: 0.1574 (0.1901) time: 2.9258 data: 0.0074 max mem: 33300 +Epoch: [5] [2650/4276] eta: 1:19:11 lr: 4.363064329412371e-05 loss: 0.1732 (0.1901) time: 2.9270 data: 0.0072 max mem: 33300 +Epoch: [5] [2660/4276] eta: 1:18:42 lr: 4.362797218470027e-05 loss: 0.1811 (0.1901) time: 2.9303 data: 0.0077 max mem: 33300 +Epoch: [5] [2670/4276] eta: 1:18:13 lr: 4.362530105710583e-05 loss: 0.1796 (0.1901) time: 2.9306 data: 0.0078 max mem: 33300 +Epoch: [5] [2680/4276] eta: 1:17:43 lr: 4.3622629911339035e-05 loss: 0.1823 (0.1901) time: 2.9271 data: 0.0076 max mem: 33300 +Epoch: [5] [2690/4276] eta: 1:17:14 lr: 4.361995874739852e-05 loss: 0.1868 (0.1901) time: 2.9158 data: 0.0076 max mem: 33300 +Epoch: [5] [2700/4276] eta: 1:16:45 lr: 4.3617287565282926e-05 loss: 0.1790 (0.1900) time: 2.9083 data: 0.0075 max mem: 33300 +Epoch: [5] [2710/4276] eta: 1:16:15 lr: 4.36146163649909e-05 loss: 0.1735 (0.1899) time: 2.9040 data: 0.0073 max mem: 33300 +Epoch: [5] [2720/4276] eta: 1:15:46 lr: 4.361194514652107e-05 loss: 0.1843 (0.1899) time: 2.9122 data: 0.0072 max mem: 33300 +Epoch: [5] [2730/4276] eta: 1:15:17 lr: 4.360927390987208e-05 loss: 0.1867 (0.1899) time: 2.9161 data: 0.0072 max mem: 33300 +Epoch: [5] [2740/4276] eta: 1:14:48 lr: 4.360660265504257e-05 loss: 0.1896 (0.1900) time: 2.9089 data: 0.0075 max mem: 33300 +Epoch: [5] [2750/4276] eta: 1:14:18 lr: 4.360393138203118e-05 loss: 0.1876 (0.1900) time: 2.9156 data: 0.0075 max mem: 33300 +Epoch: [5] [2760/4276] eta: 1:13:49 lr: 4.360126009083654e-05 loss: 0.1833 (0.1900) time: 2.9252 data: 0.0072 max mem: 33300 +Epoch: [5] [2770/4276] eta: 1:13:20 lr: 4.35985887814573e-05 loss: 0.1697 (0.1900) time: 2.9239 data: 0.0072 max mem: 33300 +Epoch: [5] [2780/4276] eta: 1:12:51 lr: 4.359591745389209e-05 loss: 0.1761 (0.1900) time: 2.9235 data: 0.0072 max mem: 33300 +Epoch: [5] [2790/4276] eta: 1:12:22 lr: 4.3593246108139565e-05 loss: 0.1913 (0.1900) time: 2.9231 data: 0.0072 max mem: 33300 +Epoch: [5] [2800/4276] eta: 1:11:52 lr: 4.3590574744198334e-05 loss: 0.1872 (0.1900) time: 2.9228 data: 0.0072 max mem: 33300 +Epoch: [5] [2810/4276] eta: 1:11:23 lr: 4.358790336206706e-05 loss: 0.1638 (0.1898) time: 2.9238 data: 0.0072 max mem: 33300 +Epoch: [5] [2820/4276] eta: 1:10:54 lr: 4.358523196174436e-05 loss: 0.1638 (0.1898) time: 2.9247 data: 0.0071 max mem: 33300 +Epoch: [5] [2830/4276] eta: 1:10:25 lr: 4.358256054322888e-05 loss: 0.1644 (0.1897) time: 2.9260 data: 0.0072 max mem: 33300 +Epoch: [5] [2840/4276] eta: 1:09:56 lr: 4.357988910651927e-05 loss: 0.1741 (0.1897) time: 2.9242 data: 0.0072 max mem: 33300 +Epoch: [5] [2850/4276] eta: 1:09:26 lr: 4.3577217651614145e-05 loss: 0.1911 (0.1897) time: 2.9244 data: 0.0071 max mem: 33300 +Epoch: [5] [2860/4276] eta: 1:08:57 lr: 4.357454617851216e-05 loss: 0.1911 (0.1897) time: 2.9208 data: 0.0072 max mem: 33300 +Epoch: [5] [2870/4276] eta: 1:08:28 lr: 4.3571874687211936e-05 loss: 0.1846 (0.1898) time: 2.9054 data: 0.0085 max mem: 33300 +Epoch: [5] [2880/4276] eta: 1:07:58 lr: 4.356920317771212e-05 loss: 0.1904 (0.1898) time: 2.8875 data: 0.0090 max mem: 33300 +Epoch: [5] [2890/4276] eta: 1:07:29 lr: 4.356653165001135e-05 loss: 0.1895 (0.1898) time: 2.8970 data: 0.0087 max mem: 33300 +Epoch: [5] [2900/4276] eta: 1:07:00 lr: 4.356386010410825e-05 loss: 0.1708 (0.1897) time: 2.9121 data: 0.0087 max mem: 33300 +Epoch: [5] [2910/4276] eta: 1:06:30 lr: 4.356118854000146e-05 loss: 0.1626 (0.1897) time: 2.9088 data: 0.0083 max mem: 33300 +Epoch: [5] [2920/4276] eta: 1:06:01 lr: 4.355851695768962e-05 loss: 0.1731 (0.1896) time: 2.8869 data: 0.0084 max mem: 33300 +Epoch: [5] [2930/4276] eta: 1:05:32 lr: 4.355584535717137e-05 loss: 0.1640 (0.1896) time: 2.8673 data: 0.0080 max mem: 33300 +Epoch: [5] [2940/4276] eta: 1:05:02 lr: 4.355317373844533e-05 loss: 0.1610 (0.1895) time: 2.8656 data: 0.0075 max mem: 33300 +Epoch: [5] [2950/4276] eta: 1:04:33 lr: 4.355050210151015e-05 loss: 0.1642 (0.1895) time: 2.8658 data: 0.0077 max mem: 33300 +Epoch: [5] [2960/4276] eta: 1:04:03 lr: 4.354783044636445e-05 loss: 0.1811 (0.1895) time: 2.8656 data: 0.0077 max mem: 33300 +Epoch: [5] [2970/4276] eta: 1:03:34 lr: 4.354515877300688e-05 loss: 0.1872 (0.1896) time: 2.8654 data: 0.0077 max mem: 33300 +Epoch: [5] [2980/4276] eta: 1:03:05 lr: 4.3542487081436055e-05 loss: 0.1991 (0.1897) time: 2.9184 data: 0.0087 max mem: 33300 +Epoch: [5] [2990/4276] eta: 1:02:36 lr: 4.3539815371650634e-05 loss: 0.1922 (0.1896) time: 2.9480 data: 0.0096 max mem: 33300 +Epoch: [5] [3000/4276] eta: 1:02:06 lr: 4.353714364364923e-05 loss: 0.1743 (0.1896) time: 2.9232 data: 0.0095 max mem: 33300 +Epoch: [5] [3010/4276] eta: 1:01:37 lr: 4.353447189743048e-05 loss: 0.1828 (0.1895) time: 2.9228 data: 0.0092 max mem: 33300 +Epoch: [5] [3020/4276] eta: 1:01:08 lr: 4.353180013299303e-05 loss: 0.1859 (0.1895) time: 2.9242 data: 0.0092 max mem: 33300 +Epoch: [5] [3030/4276] eta: 1:00:39 lr: 4.35291283503355e-05 loss: 0.1921 (0.1896) time: 2.9185 data: 0.0097 max mem: 33300 +Epoch: [5] [3040/4276] eta: 1:00:09 lr: 4.3526456549456534e-05 loss: 0.2054 (0.1897) time: 2.9110 data: 0.0100 max mem: 33300 +Epoch: [5] [3050/4276] eta: 0:59:40 lr: 4.352378473035476e-05 loss: 0.1971 (0.1896) time: 2.9185 data: 0.0091 max mem: 33300 +Epoch: [5] [3060/4276] eta: 0:59:11 lr: 4.352111289302881e-05 loss: 0.1487 (0.1895) time: 2.9260 data: 0.0080 max mem: 33300 +Epoch: [5] [3070/4276] eta: 0:58:42 lr: 4.351844103747731e-05 loss: 0.1677 (0.1895) time: 2.9232 data: 0.0076 max mem: 33300 +Epoch: [5] [3080/4276] eta: 0:58:13 lr: 4.35157691636989e-05 loss: 0.1844 (0.1895) time: 2.9267 data: 0.0078 max mem: 33300 +Epoch: [5] [3090/4276] eta: 0:57:43 lr: 4.351309727169221e-05 loss: 0.1695 (0.1894) time: 2.9194 data: 0.0083 max mem: 33300 +Epoch: [5] [3100/4276] eta: 0:57:14 lr: 4.351042536145588e-05 loss: 0.1757 (0.1894) time: 2.9223 data: 0.0083 max mem: 33300 +Epoch: [5] [3110/4276] eta: 0:56:45 lr: 4.3507753432988526e-05 loss: 0.1731 (0.1893) time: 2.9281 data: 0.0080 max mem: 33300 +Epoch: [5] [3120/4276] eta: 0:56:16 lr: 4.3505081486288804e-05 loss: 0.1589 (0.1893) time: 2.9198 data: 0.0078 max mem: 33300 +Epoch: [5] [3130/4276] eta: 0:55:47 lr: 4.3502409521355315e-05 loss: 0.1743 (0.1892) time: 2.9218 data: 0.0075 max mem: 33300 +Epoch: [5] [3140/4276] eta: 0:55:17 lr: 4.349973753818671e-05 loss: 0.1817 (0.1893) time: 2.9230 data: 0.0073 max mem: 33300 +Epoch: [5] [3150/4276] eta: 0:54:48 lr: 4.349706553678161e-05 loss: 0.1952 (0.1893) time: 2.9224 data: 0.0072 max mem: 33300 +Epoch: [5] [3160/4276] eta: 0:54:19 lr: 4.3494393517138655e-05 loss: 0.1809 (0.1893) time: 2.9289 data: 0.0072 max mem: 33300 +Epoch: [5] [3170/4276] eta: 0:53:50 lr: 4.349172147925647e-05 loss: 0.1764 (0.1894) time: 2.9307 data: 0.0074 max mem: 33300 +Epoch: [5] [3180/4276] eta: 0:53:21 lr: 4.3489049423133686e-05 loss: 0.1768 (0.1894) time: 2.9288 data: 0.0077 max mem: 33300 +Epoch: [5] [3190/4276] eta: 0:52:52 lr: 4.3486377348768934e-05 loss: 0.1806 (0.1894) time: 2.9305 data: 0.0077 max mem: 33300 +Epoch: [5] [3200/4276] eta: 0:52:22 lr: 4.3483705256160855e-05 loss: 0.1822 (0.1894) time: 2.9296 data: 0.0076 max mem: 33300 +Epoch: [5] [3210/4276] eta: 0:51:53 lr: 4.348103314530805e-05 loss: 0.1892 (0.1894) time: 2.9309 data: 0.0078 max mem: 33300 +Epoch: [5] [3220/4276] eta: 0:51:24 lr: 4.347836101620918e-05 loss: 0.1892 (0.1894) time: 2.9301 data: 0.0077 max mem: 33300 +Epoch: [5] [3230/4276] eta: 0:50:55 lr: 4.347568886886285e-05 loss: 0.1886 (0.1894) time: 2.9282 data: 0.0075 max mem: 33300 +Epoch: [5] [3240/4276] eta: 0:50:26 lr: 4.3473016703267704e-05 loss: 0.1931 (0.1894) time: 2.9279 data: 0.0075 max mem: 33300 +Epoch: [5] [3250/4276] eta: 0:49:56 lr: 4.347034451942237e-05 loss: 0.1839 (0.1894) time: 2.9282 data: 0.0080 max mem: 33300 +Epoch: [5] [3260/4276] eta: 0:49:27 lr: 4.346767231732548e-05 loss: 0.1839 (0.1894) time: 2.9285 data: 0.0084 max mem: 33300 +Epoch: [5] [3270/4276] eta: 0:48:58 lr: 4.346500009697564e-05 loss: 0.1906 (0.1894) time: 2.9275 data: 0.0080 max mem: 33300 +Epoch: [5] [3280/4276] eta: 0:48:29 lr: 4.346232785837151e-05 loss: 0.1802 (0.1894) time: 2.9287 data: 0.0079 max mem: 33300 +Epoch: [5] [3290/4276] eta: 0:48:00 lr: 4.3459655601511696e-05 loss: 0.1810 (0.1894) time: 2.9306 data: 0.0083 max mem: 33300 +Epoch: [5] [3300/4276] eta: 0:47:31 lr: 4.345698332639483e-05 loss: 0.1814 (0.1894) time: 2.9305 data: 0.0079 max mem: 33300 +Epoch: [5] [3310/4276] eta: 0:47:01 lr: 4.3454311033019545e-05 loss: 0.1897 (0.1895) time: 2.9271 data: 0.0080 max mem: 33300 +Epoch: [5] [3320/4276] eta: 0:46:32 lr: 4.3451638721384466e-05 loss: 0.1903 (0.1895) time: 2.9144 data: 0.0087 max mem: 33300 +Epoch: [5] [3330/4276] eta: 0:46:03 lr: 4.344896639148823e-05 loss: 0.1827 (0.1895) time: 2.8918 data: 0.0090 max mem: 33300 +Epoch: [5] [3340/4276] eta: 0:45:33 lr: 4.344629404332944e-05 loss: 0.1884 (0.1895) time: 2.8797 data: 0.0088 max mem: 33300 +Epoch: [5] [3350/4276] eta: 0:45:04 lr: 4.344362167690675e-05 loss: 0.1841 (0.1895) time: 2.8868 data: 0.0091 max mem: 33300 +Epoch: [5] [3360/4276] eta: 0:44:35 lr: 4.344094929221878e-05 loss: 0.1716 (0.1895) time: 2.8809 data: 0.0089 max mem: 33300 +Epoch: [5] [3370/4276] eta: 0:44:05 lr: 4.3438276889264135e-05 loss: 0.1891 (0.1895) time: 2.8619 data: 0.0080 max mem: 33300 +Epoch: [5] [3380/4276] eta: 0:43:36 lr: 4.343560446804147e-05 loss: 0.1839 (0.1896) time: 2.8565 data: 0.0078 max mem: 33300 +Epoch: [5] [3390/4276] eta: 0:43:07 lr: 4.34329320285494e-05 loss: 0.1941 (0.1896) time: 2.8572 data: 0.0078 max mem: 33300 +Epoch: [5] [3400/4276] eta: 0:42:37 lr: 4.343025957078653e-05 loss: 0.1969 (0.1896) time: 2.8520 data: 0.0078 max mem: 33300 +Epoch: [5] [3410/4276] eta: 0:42:08 lr: 4.342758709475154e-05 loss: 0.1896 (0.1896) time: 2.8619 data: 0.0080 max mem: 33300 +Epoch: [5] [3420/4276] eta: 0:41:39 lr: 4.3424914600443e-05 loss: 0.1850 (0.1897) time: 2.8817 data: 0.0090 max mem: 33300 +Epoch: [5] [3430/4276] eta: 0:41:09 lr: 4.3422242087859564e-05 loss: 0.1789 (0.1897) time: 2.8894 data: 0.0092 max mem: 33300 +Epoch: [5] [3440/4276] eta: 0:40:40 lr: 4.341956955699985e-05 loss: 0.1711 (0.1896) time: 2.8816 data: 0.0087 max mem: 33300 +Epoch: [5] [3450/4276] eta: 0:40:11 lr: 4.3416897007862485e-05 loss: 0.1729 (0.1897) time: 2.8891 data: 0.0089 max mem: 33300 +Epoch: [5] [3460/4276] eta: 0:39:42 lr: 4.341422444044609e-05 loss: 0.1819 (0.1897) time: 2.9085 data: 0.0087 max mem: 33300 +Epoch: [5] [3470/4276] eta: 0:39:12 lr: 4.341155185474929e-05 loss: 0.1728 (0.1896) time: 2.9039 data: 0.0082 max mem: 33300 +Epoch: [5] [3480/4276] eta: 0:38:43 lr: 4.3408879250770724e-05 loss: 0.1813 (0.1896) time: 2.9016 data: 0.0079 max mem: 33300 +Epoch: [5] [3490/4276] eta: 0:38:14 lr: 4.340620662850899e-05 loss: 0.1929 (0.1896) time: 2.8880 data: 0.0085 max mem: 33300 +Epoch: [5] [3500/4276] eta: 0:37:45 lr: 4.340353398796274e-05 loss: 0.1929 (0.1896) time: 2.8877 data: 0.0087 max mem: 33300 +Epoch: [5] [3510/4276] eta: 0:37:15 lr: 4.3400861329130576e-05 loss: 0.1790 (0.1896) time: 2.9048 data: 0.0082 max mem: 33300 +Epoch: [5] [3520/4276] eta: 0:36:46 lr: 4.339818865201113e-05 loss: 0.1931 (0.1896) time: 2.9017 data: 0.0087 max mem: 33300 +Epoch: [5] [3530/4276] eta: 0:36:17 lr: 4.3395515956603024e-05 loss: 0.1909 (0.1896) time: 2.9008 data: 0.0085 max mem: 33300 +Epoch: [5] [3540/4276] eta: 0:35:48 lr: 4.339284324290489e-05 loss: 0.1839 (0.1896) time: 2.8920 data: 0.0087 max mem: 33300 +Epoch: [5] [3550/4276] eta: 0:35:19 lr: 4.3390170510915333e-05 loss: 0.1904 (0.1896) time: 2.8844 data: 0.0092 max mem: 33300 +Epoch: [5] [3560/4276] eta: 0:34:49 lr: 4.3387497760633e-05 loss: 0.1907 (0.1897) time: 2.8823 data: 0.0092 max mem: 33300 +Epoch: [5] [3570/4276] eta: 0:34:20 lr: 4.338482499205649e-05 loss: 0.2004 (0.1897) time: 2.8860 data: 0.0089 max mem: 33300 +Epoch: [5] [3580/4276] eta: 0:33:51 lr: 4.338215220518444e-05 loss: 0.1798 (0.1897) time: 2.8842 data: 0.0082 max mem: 33300 +Epoch: [5] [3590/4276] eta: 0:33:21 lr: 4.337947940001547e-05 loss: 0.1725 (0.1897) time: 2.8725 data: 0.0081 max mem: 33300 +Epoch: [5] [3600/4276] eta: 0:32:52 lr: 4.33768065765482e-05 loss: 0.1794 (0.1897) time: 2.8705 data: 0.0083 max mem: 33300 +Epoch: [5] [3610/4276] eta: 0:32:23 lr: 4.337413373478125e-05 loss: 0.1838 (0.1897) time: 2.8669 data: 0.0079 max mem: 33300 +Epoch: [5] [3620/4276] eta: 0:31:54 lr: 4.3371460874713246e-05 loss: 0.1842 (0.1897) time: 2.8667 data: 0.0075 max mem: 33300 +Epoch: [5] [3630/4276] eta: 0:31:24 lr: 4.33687879963428e-05 loss: 0.1883 (0.1898) time: 2.8686 data: 0.0073 max mem: 33300 +Epoch: [5] [3640/4276] eta: 0:30:55 lr: 4.336611509966856e-05 loss: 0.1928 (0.1898) time: 2.8762 data: 0.0073 max mem: 33300 +Epoch: [5] [3650/4276] eta: 0:30:26 lr: 4.336344218468911e-05 loss: 0.1695 (0.1897) time: 2.8749 data: 0.0072 max mem: 33300 +Epoch: [5] [3660/4276] eta: 0:29:57 lr: 4.3360769251403094e-05 loss: 0.1809 (0.1897) time: 2.8755 data: 0.0077 max mem: 33300 +Epoch: [5] [3670/4276] eta: 0:29:27 lr: 4.335809629980913e-05 loss: 0.2027 (0.1897) time: 2.8925 data: 0.0087 max mem: 33300 +Epoch: [5] [3680/4276] eta: 0:28:58 lr: 4.335542332990584e-05 loss: 0.2027 (0.1897) time: 2.8884 data: 0.0088 max mem: 33300 +Epoch: [5] [3690/4276] eta: 0:28:29 lr: 4.335275034169183e-05 loss: 0.1848 (0.1897) time: 2.8779 data: 0.0090 max mem: 33300 +Epoch: [5] [3700/4276] eta: 0:28:00 lr: 4.3350077335165734e-05 loss: 0.1885 (0.1897) time: 2.8905 data: 0.0092 max mem: 33300 +Epoch: [5] [3710/4276] eta: 0:27:31 lr: 4.334740431032617e-05 loss: 0.1852 (0.1897) time: 2.9103 data: 0.0089 max mem: 33300 +Epoch: [5] [3720/4276] eta: 0:27:01 lr: 4.334473126717176e-05 loss: 0.1662 (0.1897) time: 2.9205 data: 0.0092 max mem: 33300 +Epoch: [5] [3730/4276] eta: 0:26:32 lr: 4.3342058205701116e-05 loss: 0.1772 (0.1897) time: 2.9216 data: 0.0094 max mem: 33300 +Epoch: [5] [3740/4276] eta: 0:26:03 lr: 4.333938512591286e-05 loss: 0.1979 (0.1898) time: 2.9199 data: 0.0091 max mem: 33300 +Epoch: [5] [3750/4276] eta: 0:25:34 lr: 4.333671202780561e-05 loss: 0.2207 (0.1898) time: 2.9211 data: 0.0092 max mem: 33300 +Epoch: [5] [3760/4276] eta: 0:25:05 lr: 4.3334038911377994e-05 loss: 0.1921 (0.1898) time: 2.9242 data: 0.0094 max mem: 33300 +Epoch: [5] [3770/4276] eta: 0:24:36 lr: 4.333136577662862e-05 loss: 0.1908 (0.1898) time: 2.9246 data: 0.0092 max mem: 33300 +Epoch: [5] [3780/4276] eta: 0:24:06 lr: 4.3328692623556113e-05 loss: 0.1856 (0.1898) time: 2.9236 data: 0.0090 max mem: 33300 +Epoch: [5] [3790/4276] eta: 0:23:37 lr: 4.3326019452159086e-05 loss: 0.1824 (0.1898) time: 2.9248 data: 0.0091 max mem: 33300 +Epoch: [5] [3800/4276] eta: 0:23:08 lr: 4.332334626243616e-05 loss: 0.1926 (0.1898) time: 2.9248 data: 0.0094 max mem: 33300 +Epoch: [5] [3810/4276] eta: 0:22:39 lr: 4.332067305438595e-05 loss: 0.1786 (0.1898) time: 2.9221 data: 0.0092 max mem: 33300 +Epoch: [5] [3820/4276] eta: 0:22:10 lr: 4.331799982800709e-05 loss: 0.1643 (0.1898) time: 2.9216 data: 0.0089 max mem: 33300 +Epoch: [5] [3830/4276] eta: 0:21:41 lr: 4.331532658329817e-05 loss: 0.1693 (0.1898) time: 2.9219 data: 0.0092 max mem: 33300 +Epoch: [5] [3840/4276] eta: 0:21:11 lr: 4.331265332025783e-05 loss: 0.1829 (0.1898) time: 2.9101 data: 0.0094 max mem: 33300 +Epoch: [5] [3850/4276] eta: 0:20:42 lr: 4.3309980038884676e-05 loss: 0.1699 (0.1897) time: 2.8873 data: 0.0092 max mem: 33300 +Epoch: [5] [3860/4276] eta: 0:20:13 lr: 4.330730673917732e-05 loss: 0.1765 (0.1897) time: 2.8747 data: 0.0090 max mem: 33300 +Epoch: [5] [3870/4276] eta: 0:19:44 lr: 4.33046334211344e-05 loss: 0.1859 (0.1897) time: 2.8829 data: 0.0088 max mem: 33300 +Epoch: [5] [3880/4276] eta: 0:19:15 lr: 4.3301960084754513e-05 loss: 0.1866 (0.1897) time: 2.9086 data: 0.0087 max mem: 33300 +Epoch: [5] [3890/4276] eta: 0:18:45 lr: 4.329928673003627e-05 loss: 0.1762 (0.1897) time: 2.9246 data: 0.0084 max mem: 33300 +Epoch: [5] [3900/4276] eta: 0:18:16 lr: 4.329661335697832e-05 loss: 0.1815 (0.1897) time: 2.9260 data: 0.0081 max mem: 33300 +Epoch: [5] [3910/4276] eta: 0:17:47 lr: 4.329393996557924e-05 loss: 0.1790 (0.1897) time: 2.9240 data: 0.0081 max mem: 33300 +Epoch: [5] [3920/4276] eta: 0:17:18 lr: 4.3291266555837674e-05 loss: 0.1812 (0.1897) time: 2.9258 data: 0.0082 max mem: 33300 +Epoch: [5] [3930/4276] eta: 0:16:49 lr: 4.328859312775222e-05 loss: 0.1896 (0.1896) time: 2.9271 data: 0.0082 max mem: 33300 +Epoch: [5] [3940/4276] eta: 0:16:20 lr: 4.32859196813215e-05 loss: 0.1881 (0.1896) time: 2.9301 data: 0.0082 max mem: 33300 +Epoch: [5] [3950/4276] eta: 0:15:50 lr: 4.328324621654414e-05 loss: 0.1702 (0.1896) time: 2.9301 data: 0.0082 max mem: 33300 +Epoch: [5] [3960/4276] eta: 0:15:21 lr: 4.328057273341873e-05 loss: 0.1746 (0.1896) time: 2.9223 data: 0.0083 max mem: 33300 +Epoch: [5] [3970/4276] eta: 0:14:52 lr: 4.3277899231943904e-05 loss: 0.1937 (0.1896) time: 2.9220 data: 0.0085 max mem: 33300 +Epoch: [5] [3980/4276] eta: 0:14:23 lr: 4.3275225712118275e-05 loss: 0.1820 (0.1896) time: 2.9247 data: 0.0086 max mem: 33300 +Epoch: [5] [3990/4276] eta: 0:13:54 lr: 4.327255217394045e-05 loss: 0.1820 (0.1896) time: 2.9112 data: 0.0085 max mem: 33300 +Epoch: [5] [4000/4276] eta: 0:13:25 lr: 4.326987861740905e-05 loss: 0.1672 (0.1896) time: 2.8903 data: 0.0081 max mem: 33300 +Epoch: [5] [4010/4276] eta: 0:12:55 lr: 4.326720504252268e-05 loss: 0.1590 (0.1896) time: 2.8846 data: 0.0085 max mem: 33300 +Epoch: [5] [4020/4276] eta: 0:12:26 lr: 4.326453144927996e-05 loss: 0.1682 (0.1896) time: 2.8995 data: 0.0089 max mem: 33300 +Epoch: [5] [4030/4276] eta: 0:11:57 lr: 4.326185783767952e-05 loss: 0.1868 (0.1896) time: 2.9160 data: 0.0083 max mem: 33300 +Epoch: [5] [4040/4276] eta: 0:11:28 lr: 4.325918420771993e-05 loss: 0.1945 (0.1896) time: 2.9182 data: 0.0081 max mem: 33300 +Epoch: [5] [4050/4276] eta: 0:10:59 lr: 4.325651055939985e-05 loss: 0.1845 (0.1896) time: 2.9178 data: 0.0081 max mem: 33300 +Epoch: [5] [4060/4276] eta: 0:10:30 lr: 4.325383689271787e-05 loss: 0.1795 (0.1896) time: 2.9026 data: 0.0085 max mem: 33300 +Epoch: [5] [4070/4276] eta: 0:10:00 lr: 4.325116320767259e-05 loss: 0.1889 (0.1896) time: 2.8765 data: 0.0087 max mem: 33300 +Epoch: [5] [4080/4276] eta: 0:09:31 lr: 4.3248489504262655e-05 loss: 0.1887 (0.1896) time: 2.8717 data: 0.0088 max mem: 33300 +Epoch: [5] [4090/4276] eta: 0:09:02 lr: 4.324581578248665e-05 loss: 0.1864 (0.1896) time: 2.8709 data: 0.0086 max mem: 33300 +Epoch: [5] [4100/4276] eta: 0:08:33 lr: 4.324314204234321e-05 loss: 0.1864 (0.1896) time: 2.8861 data: 0.0079 max mem: 33300 +Epoch: [5] [4110/4276] eta: 0:08:04 lr: 4.324046828383093e-05 loss: 0.1873 (0.1896) time: 2.8939 data: 0.0086 max mem: 33300 +Epoch: [5] [4120/4276] eta: 0:07:34 lr: 4.323779450694842e-05 loss: 0.1875 (0.1897) time: 2.8789 data: 0.0091 max mem: 33300 +Epoch: [5] [4130/4276] eta: 0:07:05 lr: 4.32351207116943e-05 loss: 0.1875 (0.1896) time: 2.8769 data: 0.0091 max mem: 33300 +Epoch: [5] [4140/4276] eta: 0:06:36 lr: 4.323244689806718e-05 loss: 0.1798 (0.1896) time: 2.8811 data: 0.0088 max mem: 33300 +Epoch: [5] [4150/4276] eta: 0:06:07 lr: 4.322977306606567e-05 loss: 0.1672 (0.1896) time: 2.9096 data: 0.0091 max mem: 33300 +Epoch: [5] [4160/4276] eta: 0:05:38 lr: 4.322709921568838e-05 loss: 0.1777 (0.1896) time: 2.9200 data: 0.0099 max mem: 33300 +Epoch: [5] [4170/4276] eta: 0:05:09 lr: 4.322442534693392e-05 loss: 0.1947 (0.1896) time: 2.9094 data: 0.0096 max mem: 33300 +Epoch: [5] [4180/4276] eta: 0:04:39 lr: 4.322175145980091e-05 loss: 0.1801 (0.1896) time: 2.9184 data: 0.0089 max mem: 33300 +Epoch: [5] [4190/4276] eta: 0:04:10 lr: 4.321907755428795e-05 loss: 0.1744 (0.1896) time: 2.9221 data: 0.0080 max mem: 33300 +Epoch: [5] [4200/4276] eta: 0:03:41 lr: 4.321640363039365e-05 loss: 0.1991 (0.1897) time: 2.9207 data: 0.0076 max mem: 33300 +Epoch: [5] [4210/4276] eta: 0:03:12 lr: 4.3213729688116626e-05 loss: 0.1991 (0.1897) time: 2.9188 data: 0.0076 max mem: 33300 +Epoch: [5] [4220/4276] eta: 0:02:43 lr: 4.3211055727455484e-05 loss: 0.2087 (0.1898) time: 2.9173 data: 0.0076 max mem: 33300 +Epoch: [5] [4230/4276] eta: 0:02:14 lr: 4.3208381748408835e-05 loss: 0.2202 (0.1898) time: 2.9189 data: 0.0077 max mem: 33300 +Epoch: [5] [4240/4276] eta: 0:01:44 lr: 4.320570775097528e-05 loss: 0.2162 (0.1898) time: 2.9185 data: 0.0077 max mem: 33300 +Epoch: [5] [4250/4276] eta: 0:01:15 lr: 4.3203033735153444e-05 loss: 0.1938 (0.1899) time: 2.9165 data: 0.0076 max mem: 33300 +Epoch: [5] [4260/4276] eta: 0:00:46 lr: 4.320035970094193e-05 loss: 0.2018 (0.1899) time: 2.9134 data: 0.0076 max mem: 33300 +Epoch: [5] [4270/4276] eta: 0:00:17 lr: 4.319768564833934e-05 loss: 0.1885 (0.1899) time: 2.9079 data: 0.0073 max mem: 33300 +Epoch: [5] Total time: 3:27:50 +Test: [ 0/21770] eta: 12:00:24 time: 1.9855 data: 1.9467 max mem: 33300 +Test: [ 100/21770] eta: 0:20:53 time: 0.0388 data: 0.0009 max mem: 33300 +Test: [ 200/21770] eta: 0:17:22 time: 0.0387 data: 0.0008 max mem: 33300 +Test: [ 300/21770] eta: 0:16:03 time: 0.0379 data: 0.0008 max mem: 33300 +Test: [ 400/21770] eta: 0:15:22 time: 0.0380 data: 0.0008 max mem: 33300 +Test: [ 500/21770] eta: 0:14:57 time: 0.0384 data: 0.0009 max mem: 33300 +Test: [ 600/21770] eta: 0:14:39 time: 0.0384 data: 0.0008 max mem: 33300 +Test: [ 700/21770] eta: 0:14:25 time: 0.0380 data: 0.0008 max mem: 33300 +Test: [ 800/21770] eta: 0:14:13 time: 0.0384 data: 0.0008 max mem: 33300 +Test: [ 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time: 0.0381 data: 0.0008 max mem: 33300 +Test: [ 2300/21770] eta: 0:12:38 time: 0.0378 data: 0.0008 max mem: 33300 +Test: [ 2400/21770] eta: 0:12:34 time: 0.0380 data: 0.0009 max mem: 33300 +Test: [ 2500/21770] eta: 0:12:29 time: 0.0379 data: 0.0009 max mem: 33300 +Test: [ 2600/21770] eta: 0:12:24 time: 0.0380 data: 0.0008 max mem: 33300 +Test: [ 2700/21770] eta: 0:12:20 time: 0.0380 data: 0.0009 max mem: 33300 +Test: [ 2800/21770] eta: 0:12:16 time: 0.0381 data: 0.0008 max mem: 33300 +Test: [ 2900/21770] eta: 0:12:11 time: 0.0380 data: 0.0009 max mem: 33300 +Test: [ 3000/21770] eta: 0:12:07 time: 0.0381 data: 0.0008 max mem: 33300 +Test: [ 3100/21770] eta: 0:12:03 time: 0.0379 data: 0.0009 max mem: 33300 +Test: [ 3200/21770] eta: 0:11:58 time: 0.0381 data: 0.0009 max mem: 33300 +Test: [ 3300/21770] eta: 0:11:54 time: 0.0377 data: 0.0009 max mem: 33300 +Test: [ 3400/21770] eta: 0:11:50 time: 0.0377 data: 0.0009 max mem: 33300 +Test: [ 3500/21770] eta: 0:11:45 time: 0.0377 data: 0.0008 max mem: 33300 +Test: [ 3600/21770] eta: 0:11:41 time: 0.0378 data: 0.0009 max mem: 33300 +Test: [ 3700/21770] eta: 0:11:37 time: 0.0378 data: 0.0009 max mem: 33300 +Test: [ 3800/21770] eta: 0:11:32 time: 0.0378 data: 0.0009 max mem: 33300 +Test: [ 3900/21770] eta: 0:11:28 time: 0.0378 data: 0.0009 max mem: 33300 +Test: [ 4000/21770] eta: 0:11:24 time: 0.0378 data: 0.0009 max mem: 33300 +Test: [ 4100/21770] eta: 0:11:20 time: 0.0390 data: 0.0009 max mem: 33300 +Test: [ 4200/21770] eta: 0:11:17 time: 0.0397 data: 0.0009 max mem: 33300 +Test: [ 4300/21770] eta: 0:11:13 time: 0.0393 data: 0.0009 max mem: 33300 +Test: [ 4400/21770] eta: 0:11:10 time: 0.0389 data: 0.0009 max mem: 33300 +Test: [ 4500/21770] eta: 0:11:06 time: 0.0391 data: 0.0009 max mem: 33300 +Test: [ 4600/21770] eta: 0:11:02 time: 0.0389 data: 0.0009 max mem: 33300 +Test: [ 4700/21770] eta: 0:10:59 time: 0.0392 data: 0.0009 max mem: 33300 +Test: [ 4800/21770] eta: 0:10:55 time: 0.0387 data: 0.0009 max mem: 33300 +Test: [ 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time: 0.0386 data: 0.0009 max mem: 33300 +Test: [ 6300/21770] eta: 0:09:58 time: 0.0389 data: 0.0009 max mem: 33300 +Test: [ 6400/21770] eta: 0:09:55 time: 0.0387 data: 0.0009 max mem: 33300 +Test: [ 6500/21770] eta: 0:09:51 time: 0.0387 data: 0.0009 max mem: 33300 +Test: [ 6600/21770] eta: 0:09:47 time: 0.0386 data: 0.0009 max mem: 33300 +Test: [ 6700/21770] eta: 0:09:43 time: 0.0385 data: 0.0009 max mem: 33300 +Test: [ 6800/21770] eta: 0:09:39 time: 0.0384 data: 0.0009 max mem: 33300 +Test: [ 6900/21770] eta: 0:09:35 time: 0.0386 data: 0.0009 max mem: 33300 +Test: [ 7000/21770] eta: 0:09:31 time: 0.0385 data: 0.0009 max mem: 33300 +Test: [ 7100/21770] eta: 0:09:27 time: 0.0385 data: 0.0009 max mem: 33300 +Test: [ 7200/21770] eta: 0:09:23 time: 0.0386 data: 0.0009 max mem: 33300 +Test: [ 7300/21770] eta: 0:09:19 time: 0.0384 data: 0.0009 max mem: 33300 +Test: [ 7400/21770] eta: 0:09:16 time: 0.0385 data: 0.0009 max mem: 33300 +Test: [ 7500/21770] eta: 0:09:12 time: 0.0385 data: 0.0009 max mem: 33300 +Test: [ 7600/21770] eta: 0:09:08 time: 0.0388 data: 0.0009 max mem: 33300 +Test: [ 7700/21770] eta: 0:09:04 time: 0.0387 data: 0.0009 max mem: 33300 +Test: [ 7800/21770] eta: 0:09:00 time: 0.0386 data: 0.0009 max mem: 33300 +Test: [ 7900/21770] eta: 0:08:56 time: 0.0392 data: 0.0009 max mem: 33300 +Test: [ 8000/21770] eta: 0:08:52 time: 0.0397 data: 0.0009 max mem: 33300 +Test: [ 8100/21770] eta: 0:08:49 time: 0.0401 data: 0.0008 max mem: 33300 +Test: [ 8200/21770] eta: 0:08:45 time: 0.0398 data: 0.0008 max mem: 33300 +Test: [ 8300/21770] eta: 0:08:41 time: 0.0391 data: 0.0008 max mem: 33300 +Test: [ 8400/21770] eta: 0:08:38 time: 0.0397 data: 0.0008 max mem: 33300 +Test: [ 8500/21770] eta: 0:08:34 time: 0.0394 data: 0.0008 max mem: 33300 +Test: [ 8600/21770] eta: 0:08:30 time: 0.0392 data: 0.0008 max mem: 33300 +Test: [ 8700/21770] eta: 0:08:26 time: 0.0386 data: 0.0009 max mem: 33300 +Test: [ 8800/21770] eta: 0:08:22 time: 0.0392 data: 0.0008 max mem: 33300 +Test: [ 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time: 0.0387 data: 0.0009 max mem: 33300 +Test: [10300/21770] eta: 0:07:24 time: 0.0389 data: 0.0009 max mem: 33300 +Test: [10400/21770] eta: 0:07:20 time: 0.0388 data: 0.0009 max mem: 33300 +Test: [10500/21770] eta: 0:07:17 time: 0.0378 data: 0.0009 max mem: 33300 +Test: [10600/21770] eta: 0:07:13 time: 0.0395 data: 0.0008 max mem: 33300 +Test: [10700/21770] eta: 0:07:09 time: 0.0391 data: 0.0009 max mem: 33300 +Test: [10800/21770] eta: 0:07:05 time: 0.0385 data: 0.0009 max mem: 33300 +Test: [10900/21770] eta: 0:07:01 time: 0.0386 data: 0.0009 max mem: 33300 +Test: [11000/21770] eta: 0:06:57 time: 0.0391 data: 0.0008 max mem: 33300 +Test: [11100/21770] eta: 0:06:54 time: 0.0384 data: 0.0009 max mem: 33300 +Test: [11200/21770] eta: 0:06:50 time: 0.0402 data: 0.0008 max mem: 33300 +Test: [11300/21770] eta: 0:06:46 time: 0.0385 data: 0.0009 max mem: 33300 +Test: [11400/21770] eta: 0:06:42 time: 0.0388 data: 0.0008 max mem: 33300 +Test: [11500/21770] eta: 0:06:38 time: 0.0389 data: 0.0009 max mem: 33300 +Test: [11600/21770] eta: 0:06:34 time: 0.0389 data: 0.0009 max mem: 33300 +Test: [11700/21770] eta: 0:06:30 time: 0.0387 data: 0.0009 max mem: 33300 +Test: [11800/21770] eta: 0:06:26 time: 0.0390 data: 0.0008 max mem: 33300 +Test: [11900/21770] eta: 0:06:23 time: 0.0385 data: 0.0009 max mem: 33300 +Test: [12000/21770] eta: 0:06:19 time: 0.0390 data: 0.0009 max mem: 33300 +Test: [12100/21770] eta: 0:06:15 time: 0.0387 data: 0.0008 max mem: 33300 +Test: [12200/21770] eta: 0:06:11 time: 0.0389 data: 0.0009 max mem: 33300 +Test: [12300/21770] eta: 0:06:07 time: 0.0387 data: 0.0009 max mem: 33300 +Test: [12400/21770] eta: 0:06:03 time: 0.0390 data: 0.0009 max mem: 33300 +Test: [12500/21770] eta: 0:05:59 time: 0.0389 data: 0.0009 max mem: 33300 +Test: [12600/21770] eta: 0:05:55 time: 0.0393 data: 0.0009 max mem: 33300 +Test: [12700/21770] eta: 0:05:52 time: 0.0390 data: 0.0009 max mem: 33300 +Test: [12800/21770] eta: 0:05:48 time: 0.0396 data: 0.0008 max mem: 33300 +Test: [12900/21770] eta: 0:05:44 time: 0.0391 data: 0.0008 max mem: 33300 +Test: [13000/21770] eta: 0:05:40 time: 0.0396 data: 0.0008 max mem: 33300 +Test: [13100/21770] eta: 0:05:36 time: 0.0391 data: 0.0008 max mem: 33300 +Test: [13200/21770] eta: 0:05:32 time: 0.0394 data: 0.0009 max mem: 33300 +Test: [13300/21770] eta: 0:05:28 time: 0.0397 data: 0.0009 max mem: 33300 +Test: [13400/21770] eta: 0:05:25 time: 0.0402 data: 0.0008 max mem: 33300 +Test: [13500/21770] eta: 0:05:21 time: 0.0397 data: 0.0008 max mem: 33300 +Test: [13600/21770] eta: 0:05:17 time: 0.0396 data: 0.0008 max mem: 33300 +Test: [13700/21770] eta: 0:05:13 time: 0.0398 data: 0.0009 max mem: 33300 +Test: [13800/21770] eta: 0:05:09 time: 0.0399 data: 0.0009 max mem: 33300 +Test: [13900/21770] eta: 0:05:05 time: 0.0397 data: 0.0008 max mem: 33300 +Test: [14000/21770] eta: 0:05:02 time: 0.0401 data: 0.0008 max mem: 33300 +Test: [14100/21770] eta: 0:04:58 time: 0.0395 data: 0.0009 max mem: 33300 +Test: [14200/21770] eta: 0:04:54 time: 0.0401 data: 0.0009 max mem: 33300 +Test: [14300/21770] eta: 0:04:50 time: 0.0404 data: 0.0009 max mem: 33300 +Test: [14400/21770] eta: 0:04:46 time: 0.0400 data: 0.0008 max mem: 33300 +Test: [14500/21770] eta: 0:04:42 time: 0.0396 data: 0.0009 max mem: 33300 +Test: [14600/21770] eta: 0:04:39 time: 0.0379 data: 0.0009 max mem: 33300 +Test: [14700/21770] eta: 0:04:35 time: 0.0388 data: 0.0008 max mem: 33300 +Test: [14800/21770] eta: 0:04:31 time: 0.0383 data: 0.0008 max mem: 33300 +Test: [14900/21770] eta: 0:04:27 time: 0.0385 data: 0.0009 max mem: 33300 +Test: [15000/21770] eta: 0:04:23 time: 0.0384 data: 0.0009 max mem: 33300 +Test: [15100/21770] eta: 0:04:19 time: 0.0385 data: 0.0008 max mem: 33300 +Test: [15200/21770] eta: 0:04:15 time: 0.0382 data: 0.0008 max mem: 33300 +Test: [15300/21770] eta: 0:04:11 time: 0.0384 data: 0.0009 max mem: 33300 +Test: [15400/21770] eta: 0:04:07 time: 0.0384 data: 0.0009 max mem: 33300 +Test: [15500/21770] eta: 0:04:03 time: 0.0385 data: 0.0009 max mem: 33300 +Test: [15600/21770] eta: 0:03:59 time: 0.0402 data: 0.0009 max mem: 33300 +Test: [15700/21770] eta: 0:03:56 time: 0.0399 data: 0.0008 max mem: 33300 +Test: [15800/21770] eta: 0:03:52 time: 0.0399 data: 0.0009 max mem: 33300 +Test: [15900/21770] eta: 0:03:48 time: 0.0407 data: 0.0009 max mem: 33300 +Test: [16000/21770] eta: 0:03:44 time: 0.0405 data: 0.0009 max mem: 33300 +Test: [16100/21770] eta: 0:03:40 time: 0.0401 data: 0.0009 max mem: 33300 +Test: [16200/21770] eta: 0:03:36 time: 0.0401 data: 0.0008 max mem: 33300 +Test: [16300/21770] eta: 0:03:33 time: 0.0401 data: 0.0009 max mem: 33300 +Test: [16400/21770] eta: 0:03:29 time: 0.0401 data: 0.0009 max mem: 33300 +Test: [16500/21770] eta: 0:03:25 time: 0.0399 data: 0.0008 max mem: 33300 +Test: [16600/21770] eta: 0:03:21 time: 0.0401 data: 0.0008 max mem: 33300 +Test: [16700/21770] eta: 0:03:17 time: 0.0399 data: 0.0009 max mem: 33300 +Test: [16800/21770] eta: 0:03:13 time: 0.0399 data: 0.0008 max mem: 33300 +Test: [16900/21770] eta: 0:03:09 time: 0.0401 data: 0.0009 max mem: 33300 +Test: [17000/21770] eta: 0:03:05 time: 0.0401 data: 0.0008 max mem: 33300 +Test: [17100/21770] eta: 0:03:02 time: 0.0397 data: 0.0009 max mem: 33300 +Test: [17200/21770] eta: 0:02:58 time: 0.0395 data: 0.0009 max mem: 33300 +Test: [17300/21770] eta: 0:02:54 time: 0.0392 data: 0.0008 max mem: 33300 +Test: [17400/21770] eta: 0:02:50 time: 0.0393 data: 0.0009 max mem: 33300 +Test: [17500/21770] eta: 0:02:46 time: 0.0390 data: 0.0009 max mem: 33300 +Test: [17600/21770] eta: 0:02:42 time: 0.0393 data: 0.0009 max mem: 33300 +Test: [17700/21770] eta: 0:02:38 time: 0.0391 data: 0.0008 max mem: 33300 +Test: [17800/21770] eta: 0:02:34 time: 0.0388 data: 0.0008 max mem: 33300 +Test: [17900/21770] eta: 0:02:30 time: 0.0383 data: 0.0008 max mem: 33300 +Test: [18000/21770] eta: 0:02:27 time: 0.0387 data: 0.0009 max mem: 33300 +Test: [18100/21770] eta: 0:02:23 time: 0.0389 data: 0.0008 max mem: 33300 +Test: [18200/21770] eta: 0:02:19 time: 0.0389 data: 0.0009 max mem: 33300 +Test: [18300/21770] eta: 0:02:15 time: 0.0390 data: 0.0008 max mem: 33300 +Test: [18400/21770] eta: 0:02:11 time: 0.0387 data: 0.0009 max mem: 33300 +Test: [18500/21770] eta: 0:02:07 time: 0.0393 data: 0.0009 max mem: 33300 +Test: [18600/21770] eta: 0:02:03 time: 0.0392 data: 0.0009 max mem: 33300 +Test: [18700/21770] eta: 0:01:59 time: 0.0391 data: 0.0008 max mem: 33300 +Test: [18800/21770] eta: 0:01:55 time: 0.0394 data: 0.0008 max mem: 33300 +Test: [18900/21770] eta: 0:01:51 time: 0.0391 data: 0.0008 max mem: 33300 +Test: [19000/21770] eta: 0:01:48 time: 0.0399 data: 0.0008 max mem: 33300 +Test: [19100/21770] eta: 0:01:44 time: 0.0393 data: 0.0008 max mem: 33300 +Test: [19200/21770] eta: 0:01:40 time: 0.0395 data: 0.0008 max mem: 33300 +Test: [19300/21770] eta: 0:01:36 time: 0.0396 data: 0.0008 max mem: 33300 +Test: [19400/21770] eta: 0:01:32 time: 0.0394 data: 0.0008 max mem: 33300 +Test: [19500/21770] eta: 0:01:28 time: 0.0392 data: 0.0008 max mem: 33300 +Test: [19600/21770] eta: 0:01:24 time: 0.0393 data: 0.0008 max mem: 33300 +Test: [19700/21770] eta: 0:01:20 time: 0.0394 data: 0.0008 max mem: 33300 +Test: [19800/21770] eta: 0:01:16 time: 0.0395 data: 0.0008 max mem: 33300 +Test: [19900/21770] eta: 0:01:12 time: 0.0394 data: 0.0008 max mem: 33300 +Test: [20000/21770] eta: 0:01:09 time: 0.0398 data: 0.0009 max mem: 33300 +Test: [20100/21770] eta: 0:01:05 time: 0.0393 data: 0.0008 max mem: 33300 +Test: [20200/21770] eta: 0:01:01 time: 0.0401 data: 0.0008 max mem: 33300 +Test: [20300/21770] eta: 0:00:57 time: 0.0392 data: 0.0008 max mem: 33300 +Test: [20400/21770] eta: 0:00:53 time: 0.0397 data: 0.0008 max mem: 33300 +Test: [20500/21770] eta: 0:00:49 time: 0.0392 data: 0.0008 max mem: 33300 +Test: [20600/21770] eta: 0:00:45 time: 0.0400 data: 0.0008 max mem: 33300 +Test: [20700/21770] eta: 0:00:41 time: 0.0393 data: 0.0008 max mem: 33300 +Test: [20800/21770] eta: 0:00:37 time: 0.0400 data: 0.0008 max mem: 33300 +Test: [20900/21770] eta: 0:00:33 time: 0.0401 data: 0.0008 max mem: 33300 +Test: [21000/21770] eta: 0:00:30 time: 0.0400 data: 0.0008 max mem: 33300 +Test: [21100/21770] eta: 0:00:26 time: 0.0400 data: 0.0008 max mem: 33300 +Test: [21200/21770] eta: 0:00:22 time: 0.0400 data: 0.0008 max mem: 33300 +Test: [21300/21770] eta: 0:00:18 time: 0.0401 data: 0.0008 max mem: 33300 +Test: [21400/21770] eta: 0:00:14 time: 0.0401 data: 0.0008 max mem: 33300 +Test: [21500/21770] eta: 0:00:10 time: 0.0400 data: 0.0008 max mem: 33300 +Test: [21600/21770] eta: 0:00:06 time: 0.0400 data: 0.0008 max mem: 33300 +Test: [21700/21770] eta: 0:00:02 time: 0.0399 data: 0.0008 max mem: 33300 +Test: Total time: 0:14:11 +Final results: +Mean IoU is 0.00 + + precision@0.5 = 0.00 + precision@0.6 = 0.00 + precision@0.7 = 0.00 + precision@0.8 = 0.00 + precision@0.9 = 0.00 + overall IoU = 0.00 + mean IoU = 0.00 + +Mean accuracy for one-to-zero sample is 100.00 + +Average object IoU 0.0 +Overall IoU 0.0 +Epoch: [6] [ 0/4276] eta: 6:30:03 lr: 4.3196081207949495e-05 loss: 0.1499 (0.1499) time: 5.4732 data: 2.4258 max mem: 33300 +Epoch: [6] [ 10/4276] eta: 3:42:03 lr: 4.3193407125918296e-05 loss: 0.1903 (0.1974) time: 3.1232 data: 0.2264 max mem: 33300 +Epoch: [6] [ 20/4276] eta: 3:34:27 lr: 4.31907330254924e-05 loss: 0.1841 (0.1904) time: 2.9009 data: 0.0072 max mem: 33300 +Epoch: [6] [ 30/4276] eta: 3:30:48 lr: 4.3188058906670436e-05 loss: 0.1748 (0.1913) time: 2.8997 data: 0.0081 max mem: 33300 +Epoch: [6] [ 40/4276] eta: 3:28:29 lr: 4.3185384769450995e-05 loss: 0.1884 (0.1885) time: 2.8794 data: 0.0079 max mem: 33300 +Epoch: [6] [ 50/4276] eta: 3:26:51 lr: 4.3182710613832684e-05 loss: 0.1802 (0.1860) time: 2.8715 data: 0.0075 max mem: 33300 +Epoch: [6] [ 60/4276] eta: 3:25:31 lr: 4.318003643981412e-05 loss: 0.1797 (0.1855) time: 2.8668 data: 0.0074 max mem: 33300 +Epoch: [6] [ 70/4276] eta: 3:24:32 lr: 4.3177362247393896e-05 loss: 0.1762 (0.1849) time: 2.8690 data: 0.0079 max mem: 33300 +Epoch: [6] [ 80/4276] eta: 3:23:36 lr: 4.317468803657063e-05 loss: 0.1950 (0.1858) time: 2.8709 data: 0.0092 max mem: 33300 +Epoch: [6] [ 90/4276] eta: 3:22:49 lr: 4.317201380734292e-05 loss: 0.1595 (0.1833) time: 2.8701 data: 0.0094 max mem: 33300 +Epoch: [6] [ 100/4276] eta: 3:22:13 lr: 4.316933955970939e-05 loss: 0.1623 (0.1867) time: 2.8807 data: 0.0092 max mem: 33300 +Epoch: [6] [ 110/4276] eta: 3:21:34 lr: 4.316666529366863e-05 loss: 0.1885 (0.1882) time: 2.8843 data: 0.0091 max mem: 33300 +Epoch: [6] [ 120/4276] eta: 3:20:56 lr: 4.316399100921926e-05 loss: 0.1885 (0.1881) time: 2.8780 data: 0.0086 max mem: 33300 +Epoch: [6] [ 130/4276] eta: 3:20:21 lr: 4.316131670635987e-05 loss: 0.1906 (0.1889) time: 2.8794 data: 0.0084 max mem: 33300 +Epoch: [6] [ 140/4276] eta: 3:19:45 lr: 4.315864238508907e-05 loss: 0.1909 (0.1886) time: 2.8802 data: 0.0090 max mem: 33300 +Epoch: [6] [ 150/4276] eta: 3:19:19 lr: 4.3155968045405476e-05 loss: 0.1852 (0.1886) time: 2.8924 data: 0.0097 max mem: 33300 +Epoch: [6] [ 160/4276] eta: 3:18:44 lr: 4.315329368730768e-05 loss: 0.1855 (0.1884) time: 2.8907 data: 0.0094 max mem: 33300 +Epoch: [6] [ 170/4276] eta: 3:18:07 lr: 4.3150619310794296e-05 loss: 0.1909 (0.1892) time: 2.8697 data: 0.0082 max mem: 33300 +Epoch: [6] [ 180/4276] eta: 3:17:32 lr: 4.314794491586392e-05 loss: 0.1947 (0.1892) time: 2.8659 data: 0.0085 max mem: 33300 +Epoch: [6] [ 190/4276] eta: 3:16:58 lr: 4.314527050251518e-05 loss: 0.2027 (0.1894) time: 2.8678 data: 0.0089 max mem: 33300 +Epoch: [6] [ 200/4276] eta: 3:16:23 lr: 4.314259607074665e-05 loss: 0.1992 (0.1902) time: 2.8679 data: 0.0087 max mem: 33300 +Epoch: [6] [ 210/4276] eta: 3:15:50 lr: 4.313992162055696e-05 loss: 0.1991 (0.1905) time: 2.8660 data: 0.0085 max mem: 33300 +Epoch: [6] [ 220/4276] eta: 3:15:14 lr: 4.3137247151944686e-05 loss: 0.1902 (0.1902) time: 2.8594 data: 0.0081 max mem: 33300 +Epoch: [6] [ 230/4276] eta: 3:14:38 lr: 4.313457266490846e-05 loss: 0.1810 (0.1893) time: 2.8515 data: 0.0083 max mem: 33300 +Epoch: [6] [ 240/4276] eta: 3:14:03 lr: 4.3131898159446865e-05 loss: 0.1779 (0.1895) time: 2.8474 data: 0.0081 max mem: 33300 +Epoch: [6] [ 250/4276] eta: 3:13:33 lr: 4.312922363555852e-05 loss: 0.1950 (0.1909) time: 2.8625 data: 0.0081 max mem: 33300 +Epoch: [6] [ 260/4276] eta: 3:13:11 lr: 4.3126549093242026e-05 loss: 0.1949 (0.1908) time: 2.9036 data: 0.0086 max mem: 33300 +Epoch: [6] [ 270/4276] eta: 3:12:46 lr: 4.3123874532495974e-05 loss: 0.1921 (0.1908) time: 2.9201 data: 0.0079 max mem: 33300 +Epoch: [6] [ 280/4276] eta: 3:12:25 lr: 4.3121199953318974e-05 loss: 0.1975 (0.1909) time: 2.9292 data: 0.0075 max mem: 33300 +Epoch: [6] [ 290/4276] eta: 3:12:03 lr: 4.311852535570964e-05 loss: 0.1975 (0.1904) time: 2.9407 data: 0.0076 max mem: 33300 +Epoch: [6] [ 300/4276] eta: 3:11:39 lr: 4.311585073966656e-05 loss: 0.1796 (0.1900) time: 2.9353 data: 0.0084 max mem: 33300 +Epoch: [6] [ 310/4276] eta: 3:11:16 lr: 4.311317610518834e-05 loss: 0.1697 (0.1896) time: 2.9339 data: 0.0082 max mem: 33300 +Epoch: [6] [ 320/4276] eta: 3:10:52 lr: 4.3110501452273584e-05 loss: 0.1790 (0.1901) time: 2.9327 data: 0.0077 max mem: 33300 +Epoch: [6] [ 330/4276] eta: 3:10:27 lr: 4.310782678092089e-05 loss: 0.1808 (0.1900) time: 2.9313 data: 0.0075 max mem: 33300 +Epoch: [6] [ 340/4276] eta: 3:10:02 lr: 4.310515209112888e-05 loss: 0.1767 (0.1894) time: 2.9312 data: 0.0071 max mem: 33300 +Epoch: [6] [ 350/4276] eta: 3:09:37 lr: 4.3102477382896114e-05 loss: 0.1701 (0.1893) time: 2.9319 data: 0.0074 max mem: 33300 +Epoch: [6] [ 360/4276] eta: 3:09:11 lr: 4.309980265622123e-05 loss: 0.1872 (0.1897) time: 2.9304 data: 0.0078 max mem: 33300 +Epoch: [6] [ 370/4276] eta: 3:08:46 lr: 4.309712791110282e-05 loss: 0.1718 (0.1890) time: 2.9315 data: 0.0077 max mem: 33300 +Epoch: [6] [ 380/4276] eta: 3:08:20 lr: 4.3094453147539475e-05 loss: 0.1580 (0.1888) time: 2.9314 data: 0.0075 max mem: 33300 +Epoch: [6] [ 390/4276] eta: 3:07:54 lr: 4.3091778365529804e-05 loss: 0.1800 (0.1887) time: 2.9300 data: 0.0073 max mem: 33300 +Epoch: [6] [ 400/4276] eta: 3:07:28 lr: 4.308910356507241e-05 loss: 0.1802 (0.1885) time: 2.9319 data: 0.0074 max mem: 33300 +Epoch: [6] [ 410/4276] eta: 3:07:04 lr: 4.308642874616588e-05 loss: 0.1773 (0.1882) time: 2.9458 data: 0.0076 max mem: 33300 +Epoch: [6] [ 420/4276] eta: 3:06:38 lr: 4.3083753908808836e-05 loss: 0.1773 (0.1885) time: 2.9449 data: 0.0076 max mem: 33300 +Epoch: [6] [ 430/4276] eta: 3:06:11 lr: 4.308107905299986e-05 loss: 0.1800 (0.1885) time: 2.9317 data: 0.0076 max mem: 33300 +Epoch: [6] [ 440/4276] eta: 3:05:44 lr: 4.307840417873757e-05 loss: 0.1800 (0.1886) time: 2.9309 data: 0.0076 max mem: 33300 +Epoch: [6] [ 450/4276] eta: 3:05:16 lr: 4.307572928602054e-05 loss: 0.1731 (0.1887) time: 2.9216 data: 0.0075 max mem: 33300 +Epoch: [6] [ 460/4276] eta: 3:04:49 lr: 4.3073054374847384e-05 loss: 0.1731 (0.1882) time: 2.9185 data: 0.0080 max mem: 33300 +Epoch: [6] [ 470/4276] eta: 3:04:19 lr: 4.3070379445216695e-05 loss: 0.1719 (0.1879) time: 2.9101 data: 0.0084 max mem: 33300 +Epoch: [6] [ 480/4276] eta: 3:03:48 lr: 4.3067704497127084e-05 loss: 0.1678 (0.1874) time: 2.8888 data: 0.0079 max mem: 33300 +Epoch: [6] [ 490/4276] eta: 3:03:18 lr: 4.3065029530577136e-05 loss: 0.1591 (0.1869) time: 2.8893 data: 0.0083 max mem: 33300 +Epoch: [6] [ 500/4276] eta: 3:02:51 lr: 4.306235454556546e-05 loss: 0.1632 (0.1869) time: 2.9141 data: 0.0085 max mem: 33300 +Epoch: [6] [ 510/4276] eta: 3:02:24 lr: 4.305967954209065e-05 loss: 0.1685 (0.1866) time: 2.9307 data: 0.0083 max mem: 33300 +Epoch: [6] [ 520/4276] eta: 3:01:56 lr: 4.305700452015131e-05 loss: 0.1685 (0.1866) time: 2.9300 data: 0.0084 max mem: 33300 +Epoch: [6] [ 530/4276] eta: 3:01:29 lr: 4.305432947974602e-05 loss: 0.1786 (0.1865) time: 2.9280 data: 0.0082 max mem: 33300 +Epoch: [6] [ 540/4276] eta: 3:01:01 lr: 4.305165442087339e-05 loss: 0.1786 (0.1863) time: 2.9280 data: 0.0078 max mem: 33300 +Epoch: [6] [ 550/4276] eta: 3:00:32 lr: 4.304897934353202e-05 loss: 0.1794 (0.1863) time: 2.9194 data: 0.0077 max mem: 33300 +Epoch: [6] [ 560/4276] eta: 3:00:02 lr: 4.304630424772051e-05 loss: 0.1805 (0.1862) time: 2.9008 data: 0.0086 max mem: 33300 +Epoch: [6] [ 570/4276] eta: 2:59:31 lr: 4.3043629133437445e-05 loss: 0.1777 (0.1862) time: 2.8853 data: 0.0088 max mem: 33300 +Epoch: [6] [ 580/4276] eta: 2:59:00 lr: 4.304095400068143e-05 loss: 0.1783 (0.1860) time: 2.8776 data: 0.0081 max mem: 33300 +Epoch: [6] [ 590/4276] eta: 2:58:29 lr: 4.303827884945106e-05 loss: 0.1746 (0.1856) time: 2.8741 data: 0.0078 max mem: 33300 +Epoch: [6] [ 600/4276] eta: 2:58:00 lr: 4.303560367974494e-05 loss: 0.1710 (0.1855) time: 2.8848 data: 0.0077 max mem: 33300 +Epoch: [6] [ 610/4276] eta: 2:57:32 lr: 4.3032928491561655e-05 loss: 0.1721 (0.1854) time: 2.9124 data: 0.0077 max mem: 33300 +Epoch: [6] [ 620/4276] eta: 2:57:03 lr: 4.3030253284899794e-05 loss: 0.1807 (0.1855) time: 2.9200 data: 0.0081 max mem: 33300 +Epoch: [6] [ 630/4276] eta: 2:56:35 lr: 4.302757805975797e-05 loss: 0.1809 (0.1854) time: 2.9210 data: 0.0083 max mem: 33300 +Epoch: [6] [ 640/4276] eta: 2:56:08 lr: 4.302490281613477e-05 loss: 0.1757 (0.1853) time: 2.9314 data: 0.0083 max mem: 33300 +Epoch: [6] [ 650/4276] eta: 2:55:40 lr: 4.30222275540288e-05 loss: 0.1747 (0.1852) time: 2.9316 data: 0.0082 max mem: 33300 +Epoch: [6] [ 660/4276] eta: 2:55:12 lr: 4.301955227343863e-05 loss: 0.1776 (0.1853) time: 2.9287 data: 0.0076 max mem: 33300 +Epoch: [6] [ 670/4276] eta: 2:54:45 lr: 4.301687697436288e-05 loss: 0.1776 (0.1852) time: 2.9305 data: 0.0074 max mem: 33300 +Epoch: [6] [ 680/4276] eta: 2:54:17 lr: 4.3014201656800144e-05 loss: 0.1772 (0.1851) time: 2.9319 data: 0.0074 max mem: 33300 +Epoch: [6] [ 690/4276] eta: 2:53:49 lr: 4.3011526320749e-05 loss: 0.1776 (0.1850) time: 2.9331 data: 0.0076 max mem: 33300 +Epoch: [6] [ 700/4276] eta: 2:53:21 lr: 4.3008850966208054e-05 loss: 0.1822 (0.1849) time: 2.9324 data: 0.0076 max mem: 33300 +Epoch: [6] [ 710/4276] eta: 2:52:53 lr: 4.300617559317589e-05 loss: 0.1839 (0.1849) time: 2.9288 data: 0.0076 max mem: 33300 +Epoch: [6] [ 720/4276] eta: 2:52:25 lr: 4.300350020165112e-05 loss: 0.1801 (0.1848) time: 2.9271 data: 0.0074 max mem: 33300 +Epoch: [6] [ 730/4276] eta: 2:51:56 lr: 4.300082479163232e-05 loss: 0.1686 (0.1849) time: 2.9262 data: 0.0074 max mem: 33300 +Epoch: [6] [ 740/4276] eta: 2:51:28 lr: 4.2998149363118096e-05 loss: 0.1810 (0.1849) time: 2.9263 data: 0.0074 max mem: 33300 +Epoch: [6] [ 750/4276] eta: 2:51:00 lr: 4.299547391610704e-05 loss: 0.1810 (0.1850) time: 2.9272 data: 0.0074 max mem: 33300 +Epoch: [6] [ 760/4276] eta: 2:50:32 lr: 4.299279845059774e-05 loss: 0.1645 (0.1848) time: 2.9282 data: 0.0078 max mem: 33300 +Epoch: [6] [ 770/4276] eta: 2:50:04 lr: 4.299012296658878e-05 loss: 0.1694 (0.1850) time: 2.9298 data: 0.0080 max mem: 33300 +Epoch: [6] [ 780/4276] eta: 2:49:35 lr: 4.298744746407877e-05 loss: 0.1817 (0.1850) time: 2.9319 data: 0.0081 max mem: 33300 +Epoch: [6] [ 790/4276] eta: 2:49:07 lr: 4.29847719430663e-05 loss: 0.1867 (0.1851) time: 2.9316 data: 0.0081 max mem: 33300 +Epoch: [6] [ 800/4276] eta: 2:48:39 lr: 4.298209640354996e-05 loss: 0.1867 (0.1852) time: 2.9296 data: 0.0078 max mem: 33300 +Epoch: [6] [ 810/4276] eta: 2:48:10 lr: 4.297942084552834e-05 loss: 0.1840 (0.1853) time: 2.9290 data: 0.0076 max mem: 33300 +Epoch: [6] [ 820/4276] eta: 2:47:42 lr: 4.2976745269000027e-05 loss: 0.1840 (0.1851) time: 2.9287 data: 0.0080 max mem: 33300 +Epoch: [6] [ 830/4276] eta: 2:47:14 lr: 4.2974069673963626e-05 loss: 0.1682 (0.1853) time: 2.9294 data: 0.0084 max mem: 33300 +Epoch: [6] [ 840/4276] eta: 2:46:45 lr: 4.297139406041771e-05 loss: 0.1826 (0.1854) time: 2.9294 data: 0.0079 max mem: 33300 +Epoch: [6] [ 850/4276] eta: 2:46:17 lr: 4.2968718428360896e-05 loss: 0.1826 (0.1854) time: 2.9286 data: 0.0076 max mem: 33300 +Epoch: [6] [ 860/4276] eta: 2:45:48 lr: 4.296604277779175e-05 loss: 0.1836 (0.1855) time: 2.9283 data: 0.0079 max mem: 33300 +Epoch: [6] [ 870/4276] eta: 2:45:20 lr: 4.296336710870887e-05 loss: 0.1830 (0.1856) time: 2.9307 data: 0.0078 max mem: 33300 +Epoch: [6] [ 880/4276] eta: 2:44:52 lr: 4.2960691421110865e-05 loss: 0.1880 (0.1858) time: 2.9327 data: 0.0076 max mem: 33300 +Epoch: [6] [ 890/4276] eta: 2:44:24 lr: 4.2958015714996305e-05 loss: 0.2035 (0.1859) time: 2.9419 data: 0.0081 max mem: 33300 +Epoch: [6] [ 900/4276] eta: 2:43:55 lr: 4.295533999036378e-05 loss: 0.1935 (0.1859) time: 2.9373 data: 0.0083 max mem: 33300 +Epoch: [6] [ 910/4276] eta: 2:43:27 lr: 4.29526642472119e-05 loss: 0.1824 (0.1860) time: 2.9252 data: 0.0080 max mem: 33300 +Epoch: [6] [ 920/4276] eta: 2:42:57 lr: 4.2949988485539236e-05 loss: 0.1893 (0.1861) time: 2.9197 data: 0.0083 max mem: 33300 +Epoch: [6] [ 930/4276] eta: 2:42:27 lr: 4.294731270534438e-05 loss: 0.1887 (0.1861) time: 2.8984 data: 0.0088 max mem: 33300 +Epoch: [6] [ 940/4276] eta: 2:41:58 lr: 4.294463690662592e-05 loss: 0.1704 (0.1859) time: 2.8994 data: 0.0091 max mem: 33300 +Epoch: [6] [ 950/4276] eta: 2:41:30 lr: 4.294196108938246e-05 loss: 0.1743 (0.1860) time: 2.9226 data: 0.0086 max mem: 33300 +Epoch: [6] [ 960/4276] eta: 2:41:02 lr: 4.293928525361258e-05 loss: 0.1902 (0.1861) time: 2.9383 data: 0.0079 max mem: 33300 +Epoch: [6] [ 970/4276] eta: 2:40:33 lr: 4.293660939931486e-05 loss: 0.1902 (0.1861) time: 2.9381 data: 0.0079 max mem: 33300 +Epoch: [6] [ 980/4276] eta: 2:40:05 lr: 4.293393352648789e-05 loss: 0.1910 (0.1863) time: 2.9321 data: 0.0080 max mem: 33300 +Epoch: [6] [ 990/4276] eta: 2:39:36 lr: 4.293125763513029e-05 loss: 0.1840 (0.1862) time: 2.9315 data: 0.0080 max mem: 33300 +Epoch: [6] [1000/4276] eta: 2:39:07 lr: 4.292858172524061e-05 loss: 0.1740 (0.1861) time: 2.9326 data: 0.0078 max mem: 33300 +Epoch: [6] [1010/4276] eta: 2:38:39 lr: 4.292590579681745e-05 loss: 0.1647 (0.1861) time: 2.9333 data: 0.0075 max mem: 33300 +Epoch: [6] [1020/4276] eta: 2:38:11 lr: 4.29232298498594e-05 loss: 0.1749 (0.1860) time: 2.9378 data: 0.0077 max mem: 33300 +Epoch: [6] [1030/4276] eta: 2:37:42 lr: 4.292055388436505e-05 loss: 0.1749 (0.1861) time: 2.9375 data: 0.0076 max mem: 33300 +Epoch: [6] [1040/4276] eta: 2:37:14 lr: 4.2917877900332985e-05 loss: 0.1880 (0.1861) time: 2.9344 data: 0.0072 max mem: 33300 +Epoch: [6] [1050/4276] eta: 2:36:44 lr: 4.29152018977618e-05 loss: 0.1880 (0.1861) time: 2.9158 data: 0.0077 max mem: 33300 +Epoch: [6] [1060/4276] eta: 2:36:14 lr: 4.2912525876650065e-05 loss: 0.1834 (0.1862) time: 2.8865 data: 0.0083 max mem: 33300 +Epoch: [6] [1070/4276] eta: 2:35:43 lr: 4.290984983699638e-05 loss: 0.1737 (0.1862) time: 2.8802 data: 0.0083 max mem: 33300 +Epoch: [6] [1080/4276] eta: 2:35:13 lr: 4.290717377879932e-05 loss: 0.1737 (0.1861) time: 2.8807 data: 0.0084 max mem: 33300 +Epoch: [6] [1090/4276] eta: 2:34:43 lr: 4.2904497702057486e-05 loss: 0.1823 (0.1860) time: 2.8808 data: 0.0087 max mem: 33300 +Epoch: [6] [1100/4276] eta: 2:34:13 lr: 4.290182160676946e-05 loss: 0.1711 (0.1859) time: 2.8806 data: 0.0087 max mem: 33300 +Epoch: [6] [1110/4276] eta: 2:33:43 lr: 4.2899145492933826e-05 loss: 0.1764 (0.1859) time: 2.8807 data: 0.0085 max mem: 33300 +Epoch: [6] [1120/4276] eta: 2:33:13 lr: 4.289646936054916e-05 loss: 0.1759 (0.1859) time: 2.8844 data: 0.0083 max mem: 33300 +Epoch: [6] [1130/4276] eta: 2:32:45 lr: 4.2893793209614064e-05 loss: 0.1731 (0.1857) time: 2.9160 data: 0.0085 max mem: 33300 +Epoch: [6] [1140/4276] eta: 2:32:16 lr: 4.289111704012712e-05 loss: 0.1751 (0.1855) time: 2.9280 data: 0.0087 max mem: 33300 +Epoch: [6] [1150/4276] eta: 2:31:47 lr: 4.2888440852086905e-05 loss: 0.1747 (0.1855) time: 2.9177 data: 0.0085 max mem: 33300 +Epoch: [6] [1160/4276] eta: 2:31:18 lr: 4.288576464549201e-05 loss: 0.1719 (0.1854) time: 2.9295 data: 0.0082 max mem: 33300 +Epoch: [6] [1170/4276] eta: 2:30:49 lr: 4.288308842034102e-05 loss: 0.1840 (0.1855) time: 2.9243 data: 0.0086 max mem: 33300 +Epoch: [6] [1180/4276] eta: 2:30:19 lr: 4.288041217663251e-05 loss: 0.1858 (0.1855) time: 2.8973 data: 0.0091 max mem: 33300 +Epoch: [6] [1190/4276] eta: 2:29:49 lr: 4.287773591436509e-05 loss: 0.1723 (0.1854) time: 2.8830 data: 0.0089 max mem: 33300 +Epoch: [6] [1200/4276] eta: 2:29:19 lr: 4.287505963353731e-05 loss: 0.1593 (0.1853) time: 2.8835 data: 0.0085 max mem: 33300 +Epoch: [6] [1210/4276] eta: 2:28:49 lr: 4.287238333414778e-05 loss: 0.1692 (0.1853) time: 2.8826 data: 0.0085 max mem: 33300 +Epoch: [6] [1220/4276] eta: 2:28:20 lr: 4.286970701619507e-05 loss: 0.1692 (0.1852) time: 2.8932 data: 0.0088 max mem: 33300 +Epoch: [6] [1230/4276] eta: 2:27:51 lr: 4.286703067967778e-05 loss: 0.1749 (0.1852) time: 2.9061 data: 0.0094 max mem: 33300 +Epoch: [6] [1240/4276] eta: 2:27:22 lr: 4.286435432459447e-05 loss: 0.1765 (0.1852) time: 2.9162 data: 0.0090 max mem: 33300 +Epoch: [6] [1250/4276] eta: 2:26:53 lr: 4.286167795094374e-05 loss: 0.1753 (0.1851) time: 2.9143 data: 0.0083 max mem: 33300 +Epoch: [6] [1260/4276] eta: 2:26:24 lr: 4.2859001558724155e-05 loss: 0.1678 (0.1849) time: 2.9087 data: 0.0083 max mem: 33300 +Epoch: [6] [1270/4276] eta: 2:25:55 lr: 4.2856325147934325e-05 loss: 0.1761 (0.1849) time: 2.9145 data: 0.0085 max mem: 33300 +Epoch: [6] [1280/4276] eta: 2:25:25 lr: 4.2853648718572815e-05 loss: 0.1873 (0.1849) time: 2.9114 data: 0.0091 max mem: 33300 +Epoch: [6] [1290/4276] eta: 2:24:55 lr: 4.2850972270638204e-05 loss: 0.1816 (0.1850) time: 2.8944 data: 0.0091 max mem: 33300 +Epoch: [6] [1300/4276] eta: 2:24:26 lr: 4.284829580412909e-05 loss: 0.1712 (0.1850) time: 2.8813 data: 0.0087 max mem: 33300 +Epoch: [6] [1310/4276] eta: 2:23:56 lr: 4.284561931904404e-05 loss: 0.1673 (0.1849) time: 2.8812 data: 0.0087 max mem: 33300 +Epoch: [6] [1320/4276] eta: 2:23:26 lr: 4.284294281538164e-05 loss: 0.1816 (0.1849) time: 2.8830 data: 0.0085 max mem: 33300 +Epoch: [6] [1330/4276] eta: 2:22:56 lr: 4.2840266293140475e-05 loss: 0.1698 (0.1848) time: 2.8828 data: 0.0085 max mem: 33300 +Epoch: [6] [1340/4276] eta: 2:22:27 lr: 4.283758975231913e-05 loss: 0.1615 (0.1846) time: 2.8829 data: 0.0087 max mem: 33300 +Epoch: [6] [1350/4276] eta: 2:21:57 lr: 4.283491319291617e-05 loss: 0.1681 (0.1846) time: 2.8815 data: 0.0087 max mem: 33300 +Epoch: [6] [1360/4276] eta: 2:21:27 lr: 4.283223661493019e-05 loss: 0.1794 (0.1847) time: 2.8797 data: 0.0085 max mem: 33300 +Epoch: [6] [1370/4276] eta: 2:20:57 lr: 4.282956001835977e-05 loss: 0.1653 (0.1845) time: 2.8801 data: 0.0085 max mem: 33300 +Epoch: [6] [1380/4276] eta: 2:20:29 lr: 4.282688340320348e-05 loss: 0.1748 (0.1846) time: 2.9078 data: 0.0088 max mem: 33300 +Epoch: [6] [1390/4276] eta: 2:20:00 lr: 4.2824206769459914e-05 loss: 0.1947 (0.1846) time: 2.9374 data: 0.0098 max mem: 33300 +Epoch: [6] [1400/4276] eta: 2:19:32 lr: 4.282153011712764e-05 loss: 0.1889 (0.1847) time: 2.9359 data: 0.0095 max mem: 33300 +Epoch: [6] [1410/4276] eta: 2:19:03 lr: 4.281885344620524e-05 loss: 0.1876 (0.1847) time: 2.9356 data: 0.0082 max mem: 33300 +Epoch: [6] [1420/4276] eta: 2:18:34 lr: 4.281617675669131e-05 loss: 0.1780 (0.1848) time: 2.9209 data: 0.0079 max mem: 33300 +Epoch: [6] [1430/4276] eta: 2:18:05 lr: 4.2813500048584406e-05 loss: 0.1765 (0.1848) time: 2.9087 data: 0.0082 max mem: 33300 +Epoch: [6] [1440/4276] eta: 2:17:35 lr: 4.281082332188312e-05 loss: 0.1858 (0.1849) time: 2.9032 data: 0.0094 max mem: 33300 +Epoch: [6] [1450/4276] eta: 2:17:05 lr: 4.280814657658604e-05 loss: 0.1891 (0.1849) time: 2.8858 data: 0.0095 max mem: 33300 +Epoch: [6] [1460/4276] eta: 2:16:36 lr: 4.2805469812691715e-05 loss: 0.1860 (0.1849) time: 2.8789 data: 0.0087 max mem: 33300 +Epoch: [6] [1470/4276] eta: 2:16:06 lr: 4.2802793030198754e-05 loss: 0.1860 (0.1849) time: 2.8783 data: 0.0087 max mem: 33300 +Epoch: [6] [1480/4276] eta: 2:15:36 lr: 4.2800116229105716e-05 loss: 0.1689 (0.1849) time: 2.8776 data: 0.0087 max mem: 33300 +Epoch: [6] [1490/4276] eta: 2:15:07 lr: 4.279743940941119e-05 loss: 0.1578 (0.1848) time: 2.8803 data: 0.0083 max mem: 33300 +Epoch: [6] [1500/4276] eta: 2:14:37 lr: 4.2794762571113755e-05 loss: 0.1711 (0.1848) time: 2.8842 data: 0.0083 max mem: 33300 +Epoch: [6] [1510/4276] eta: 2:14:07 lr: 4.279208571421198e-05 loss: 0.1714 (0.1848) time: 2.8833 data: 0.0087 max mem: 33300 +Epoch: [6] [1520/4276] eta: 2:13:38 lr: 4.278940883870445e-05 loss: 0.1717 (0.1848) time: 2.8810 data: 0.0086 max mem: 33300 +Epoch: [6] [1530/4276] eta: 2:13:09 lr: 4.278673194458974e-05 loss: 0.1747 (0.1848) time: 2.8970 data: 0.0086 max mem: 33300 +Epoch: [6] [1540/4276] eta: 2:12:40 lr: 4.278405503186642e-05 loss: 0.1747 (0.1848) time: 2.9200 data: 0.0092 max mem: 33300 +Epoch: [6] [1550/4276] eta: 2:12:11 lr: 4.278137810053308e-05 loss: 0.1832 (0.1848) time: 2.9312 data: 0.0090 max mem: 33300 +Epoch: [6] [1560/4276] eta: 2:11:43 lr: 4.277870115058828e-05 loss: 0.1706 (0.1847) time: 2.9330 data: 0.0080 max mem: 33300 +Epoch: [6] [1570/4276] eta: 2:11:14 lr: 4.2776024182030624e-05 loss: 0.1710 (0.1848) time: 2.9360 data: 0.0078 max mem: 33300 +Epoch: [6] [1580/4276] eta: 2:10:45 lr: 4.277334719485866e-05 loss: 0.1780 (0.1847) time: 2.9379 data: 0.0078 max mem: 33300 +Epoch: [6] [1590/4276] eta: 2:10:16 lr: 4.277067018907098e-05 loss: 0.1724 (0.1847) time: 2.9163 data: 0.0081 max mem: 33300 +Epoch: [6] [1600/4276] eta: 2:09:47 lr: 4.276799316466615e-05 loss: 0.1724 (0.1846) time: 2.8913 data: 0.0089 max mem: 33300 +Epoch: [6] [1610/4276] eta: 2:09:17 lr: 4.276531612164276e-05 loss: 0.1669 (0.1845) time: 2.8825 data: 0.0092 max mem: 33300 +Epoch: [6] [1620/4276] eta: 2:08:47 lr: 4.2762639059999365e-05 loss: 0.1669 (0.1844) time: 2.8817 data: 0.0094 max mem: 33300 +Epoch: [6] [1630/4276] eta: 2:08:18 lr: 4.275996197973456e-05 loss: 0.1736 (0.1845) time: 2.8955 data: 0.0094 max mem: 33300 +Epoch: [6] [1640/4276] eta: 2:07:50 lr: 4.27572848808469e-05 loss: 0.1790 (0.1845) time: 2.9214 data: 0.0091 max mem: 33300 +Epoch: [6] [1650/4276] eta: 2:07:21 lr: 4.2754607763334984e-05 loss: 0.1790 (0.1846) time: 2.9344 data: 0.0089 max mem: 33300 +Epoch: [6] [1660/4276] eta: 2:06:52 lr: 4.275193062719737e-05 loss: 0.1850 (0.1845) time: 2.9233 data: 0.0089 max mem: 33300 +Epoch: [6] [1670/4276] eta: 2:06:23 lr: 4.274925347243264e-05 loss: 0.1771 (0.1845) time: 2.9119 data: 0.0089 max mem: 33300 +Epoch: [6] [1680/4276] eta: 2:05:54 lr: 4.274657629903937e-05 loss: 0.1801 (0.1846) time: 2.9053 data: 0.0087 max mem: 33300 +Epoch: [6] [1690/4276] eta: 2:05:24 lr: 4.2743899107016114e-05 loss: 0.1890 (0.1846) time: 2.9065 data: 0.0090 max mem: 33300 +Epoch: [6] [1700/4276] eta: 2:04:57 lr: 4.2741221896361463e-05 loss: 0.1852 (0.1847) time: 2.9738 data: 0.0090 max mem: 33300 +Epoch: [6] [1710/4276] eta: 2:04:31 lr: 4.2738544667074e-05 loss: 0.1923 (0.1848) time: 3.0595 data: 0.0086 max mem: 33300 +Epoch: [6] [1720/4276] eta: 2:04:06 lr: 4.2735867419152284e-05 loss: 0.1923 (0.1849) time: 3.1329 data: 0.0084 max mem: 33300 +Epoch: [6] [1730/4276] eta: 2:03:42 lr: 4.273319015259489e-05 loss: 0.1868 (0.1849) time: 3.2398 data: 0.0085 max mem: 33300 +Epoch: [6] [1740/4276] eta: 2:03:16 lr: 4.273051286740038e-05 loss: 0.1835 (0.1849) time: 3.2229 data: 0.0082 max mem: 33300 +Epoch: [6] [1750/4276] eta: 2:02:50 lr: 4.272783556356735e-05 loss: 0.1835 (0.1849) time: 3.1361 data: 0.0077 max mem: 33300 +Epoch: [6] [1760/4276] eta: 2:02:27 lr: 4.272515824109437e-05 loss: 0.1825 (0.1849) time: 3.2269 data: 0.0079 max mem: 33300 +Epoch: [6] [1770/4276] eta: 2:02:01 lr: 4.2722480899979996e-05 loss: 0.1825 (0.1849) time: 3.2568 data: 0.0078 max mem: 33300 +Epoch: [6] [1780/4276] eta: 2:01:36 lr: 4.27198035402228e-05 loss: 0.1856 (0.1850) time: 3.1798 data: 0.0083 max mem: 33300 +Epoch: [6] [1790/4276] eta: 2:01:12 lr: 4.271712616182137e-05 loss: 0.1787 (0.1850) time: 3.2359 data: 0.0090 max mem: 33300 +Epoch: [6] [1800/4276] eta: 2:00:46 lr: 4.271444876477427e-05 loss: 0.1787 (0.1850) time: 3.2338 data: 0.0089 max mem: 33300 +Epoch: [6] [1810/4276] eta: 2:00:20 lr: 4.271177134908007e-05 loss: 0.1933 (0.1851) time: 3.1683 data: 0.0090 max mem: 33300 +Epoch: [6] [1820/4276] eta: 1:59:54 lr: 4.270909391473734e-05 loss: 0.1848 (0.1850) time: 3.1896 data: 0.0092 max mem: 33300 +Epoch: [6] [1830/4276] eta: 1:59:28 lr: 4.2706416461744655e-05 loss: 0.1690 (0.1850) time: 3.1838 data: 0.0093 max mem: 33300 +Epoch: [6] [1840/4276] eta: 1:59:03 lr: 4.2703738990100586e-05 loss: 0.1653 (0.1850) time: 3.1948 data: 0.0090 max mem: 33300 +Epoch: [6] [1850/4276] eta: 1:58:38 lr: 4.270106149980371e-05 loss: 0.1814 (0.1850) time: 3.2422 data: 0.0086 max mem: 33300 +Epoch: [6] [1860/4276] eta: 1:58:11 lr: 4.269838399085257e-05 loss: 0.1820 (0.1850) time: 3.2024 data: 0.0087 max mem: 33300 +Epoch: [6] [1870/4276] eta: 1:57:45 lr: 4.269570646324577e-05 loss: 0.1772 (0.1851) time: 3.1741 data: 0.0093 max mem: 33300 +Epoch: [6] [1880/4276] eta: 1:57:20 lr: 4.2693028916981866e-05 loss: 0.1829 (0.1850) time: 3.2272 data: 0.0093 max mem: 33300 +Epoch: [6] [1890/4276] eta: 1:56:54 lr: 4.269035135205943e-05 loss: 0.1756 (0.1850) time: 3.2370 data: 0.0095 max mem: 33300 +Epoch: [6] [1900/4276] eta: 1:56:28 lr: 4.2687673768477025e-05 loss: 0.1734 (0.1850) time: 3.1937 data: 0.0089 max mem: 33300 +Epoch: [6] [1910/4276] eta: 1:56:02 lr: 4.268499616623323e-05 loss: 0.1755 (0.1850) time: 3.2208 data: 0.0084 max mem: 33300 +Epoch: [6] [1920/4276] eta: 1:55:37 lr: 4.268231854532661e-05 loss: 0.1697 (0.1849) time: 3.2733 data: 0.0092 max mem: 33300 +Epoch: [6] [1930/4276] eta: 1:55:10 lr: 4.267964090575572e-05 loss: 0.1831 (0.1849) time: 3.2291 data: 0.0090 max mem: 33300 +Epoch: [6] [1940/4276] eta: 1:54:44 lr: 4.267696324751915e-05 loss: 0.1849 (0.1850) time: 3.1939 data: 0.0085 max mem: 33300 +Epoch: [6] [1950/4276] eta: 1:54:19 lr: 4.2674285570615466e-05 loss: 0.1784 (0.1850) time: 3.2495 data: 0.0089 max mem: 33300 +Epoch: [6] [1960/4276] eta: 1:53:52 lr: 4.267160787504323e-05 loss: 0.1635 (0.1849) time: 3.2483 data: 0.0090 max mem: 33300 +Epoch: [6] [1970/4276] eta: 1:53:26 lr: 4.266893016080101e-05 loss: 0.1614 (0.1848) time: 3.2056 data: 0.0087 max mem: 33300 +Epoch: [6] [1980/4276] eta: 1:53:00 lr: 4.266625242788737e-05 loss: 0.1667 (0.1847) time: 3.2358 data: 0.0088 max mem: 33300 +Epoch: [6] [1990/4276] eta: 1:52:34 lr: 4.2663574676300885e-05 loss: 0.1756 (0.1847) time: 3.2685 data: 0.0088 max mem: 33300 +Epoch: [6] [2000/4276] eta: 1:52:07 lr: 4.266089690604013e-05 loss: 0.1875 (0.1848) time: 3.2282 data: 0.0085 max mem: 33300 +Epoch: [6] [2010/4276] eta: 1:51:40 lr: 4.2658219117103656e-05 loss: 0.1802 (0.1847) time: 3.2046 data: 0.0082 max mem: 33300 +Epoch: [6] [2020/4276] eta: 1:51:14 lr: 4.2655541309490034e-05 loss: 0.1792 (0.1847) time: 3.2264 data: 0.0089 max mem: 33300 +Epoch: [6] [2030/4276] eta: 1:50:47 lr: 4.265286348319784e-05 loss: 0.1792 (0.1847) time: 3.2141 data: 0.0087 max mem: 33300 +Epoch: [6] [2040/4276] eta: 1:50:20 lr: 4.265018563822563e-05 loss: 0.1726 (0.1846) time: 3.2091 data: 0.0083 max mem: 33300 +Epoch: [6] [2050/4276] eta: 1:49:53 lr: 4.2647507774571976e-05 loss: 0.1756 (0.1846) time: 3.2187 data: 0.0090 max mem: 33300 +Epoch: [6] [2060/4276] eta: 1:49:26 lr: 4.2644829892235445e-05 loss: 0.1803 (0.1846) time: 3.1897 data: 0.0088 max mem: 33300 +Epoch: [6] [2070/4276] eta: 1:48:59 lr: 4.2642151991214607e-05 loss: 0.1720 (0.1845) time: 3.1921 data: 0.0085 max mem: 33300 +Epoch: [6] [2080/4276] eta: 1:48:32 lr: 4.263947407150802e-05 loss: 0.1730 (0.1846) time: 3.2193 data: 0.0088 max mem: 33300 +Epoch: [6] [2090/4276] eta: 1:48:05 lr: 4.263679613311425e-05 loss: 0.1874 (0.1846) time: 3.2061 data: 0.0088 max mem: 33300 +Epoch: [6] [2100/4276] eta: 1:47:38 lr: 4.263411817603186e-05 loss: 0.1874 (0.1846) time: 3.2315 data: 0.0085 max mem: 33300 +Epoch: [6] [2110/4276] eta: 1:47:11 lr: 4.263144020025943e-05 loss: 0.1720 (0.1846) time: 3.2422 data: 0.0083 max mem: 33300 +Epoch: [6] [2120/4276] eta: 1:46:43 lr: 4.262876220579551e-05 loss: 0.1643 (0.1844) time: 3.1888 data: 0.0082 max mem: 33300 +Epoch: [6] [2130/4276] eta: 1:46:17 lr: 4.262608419263867e-05 loss: 0.1591 (0.1844) time: 3.2085 data: 0.0081 max mem: 33300 +Epoch: [6] [2140/4276] eta: 1:45:49 lr: 4.262340616078747e-05 loss: 0.1812 (0.1844) time: 3.2288 data: 0.0085 max mem: 33300 +Epoch: [6] [2150/4276] eta: 1:45:21 lr: 4.2620728110240484e-05 loss: 0.1799 (0.1843) time: 3.1529 data: 0.0084 max mem: 33300 +Epoch: [6] [2160/4276] eta: 1:44:52 lr: 4.2618050040996274e-05 loss: 0.1699 (0.1843) time: 3.1156 data: 0.0078 max mem: 33300 +Epoch: [6] [2170/4276] eta: 1:44:25 lr: 4.26153719530534e-05 loss: 0.1819 (0.1843) time: 3.1434 data: 0.0082 max mem: 33300 +Epoch: [6] [2180/4276] eta: 1:43:56 lr: 4.261269384641042e-05 loss: 0.1829 (0.1844) time: 3.1543 data: 0.0083 max mem: 33300 +Epoch: [6] [2190/4276] eta: 1:43:29 lr: 4.261001572106591e-05 loss: 0.1819 (0.1844) time: 3.1627 data: 0.0084 max mem: 33300 +Epoch: [6] [2200/4276] eta: 1:43:01 lr: 4.260733757701843e-05 loss: 0.1857 (0.1844) time: 3.1946 data: 0.0085 max mem: 33300 +Epoch: [6] [2210/4276] eta: 1:42:34 lr: 4.260465941426653e-05 loss: 0.1929 (0.1844) time: 3.2328 data: 0.0084 max mem: 33300 +Epoch: [6] [2220/4276] eta: 1:42:07 lr: 4.26019812328088e-05 loss: 0.1934 (0.1844) time: 3.2483 data: 0.0084 max mem: 33300 +Epoch: [6] [2230/4276] eta: 1:41:38 lr: 4.259930303264378e-05 loss: 0.1737 (0.1844) time: 3.2009 data: 0.0085 max mem: 33300 +Epoch: [6] [2240/4276] eta: 1:41:11 lr: 4.2596624813770035e-05 loss: 0.1605 (0.1843) time: 3.1981 data: 0.0083 max mem: 33300 +Epoch: [6] [2250/4276] eta: 1:40:43 lr: 4.259394657618613e-05 loss: 0.1605 (0.1842) time: 3.2050 data: 0.0083 max mem: 33300 +Epoch: [6] [2260/4276] eta: 1:40:14 lr: 4.259126831989063e-05 loss: 0.1726 (0.1842) time: 3.1106 data: 0.0085 max mem: 33300 +Epoch: [6] [2270/4276] eta: 1:39:45 lr: 4.25885900448821e-05 loss: 0.1792 (0.1843) time: 3.0885 data: 0.0085 max mem: 33300 +Epoch: [6] [2280/4276] eta: 1:39:17 lr: 4.2585911751159096e-05 loss: 0.1786 (0.1843) time: 3.1618 data: 0.0086 max mem: 33300 +Epoch: [6] [2290/4276] eta: 1:38:48 lr: 4.2583233438720186e-05 loss: 0.1728 (0.1842) time: 3.1104 data: 0.0081 max mem: 33300 +Epoch: [6] [2300/4276] eta: 1:38:18 lr: 4.258055510756392e-05 loss: 0.1661 (0.1841) time: 3.0514 data: 0.0078 max mem: 33300 +Epoch: [6] [2310/4276] eta: 1:37:50 lr: 4.257787675768886e-05 loss: 0.1708 (0.1840) time: 3.0967 data: 0.0082 max mem: 33300 +Epoch: [6] [2320/4276] eta: 1:37:21 lr: 4.2575198389093576e-05 loss: 0.1712 (0.1840) time: 3.0965 data: 0.0080 max mem: 33300 +Epoch: [6] [2330/4276] eta: 1:36:51 lr: 4.257252000177662e-05 loss: 0.1712 (0.1840) time: 3.0628 data: 0.0079 max mem: 33300 +Epoch: [6] [2340/4276] eta: 1:36:22 lr: 4.256984159573656e-05 loss: 0.1735 (0.1839) time: 3.0331 data: 0.0078 max mem: 33300 +Epoch: [6] [2350/4276] eta: 1:35:52 lr: 4.256716317097196e-05 loss: 0.1644 (0.1839) time: 3.0249 data: 0.0080 max mem: 33300 +Epoch: [6] [2360/4276] eta: 1:35:23 lr: 4.256448472748136e-05 loss: 0.1625 (0.1838) time: 3.0307 data: 0.0080 max mem: 33300 +Epoch: [6] [2370/4276] eta: 1:34:53 lr: 4.2561806265263336e-05 loss: 0.1740 (0.1838) time: 3.0052 data: 0.0076 max mem: 33300 +Epoch: [6] [2380/4276] eta: 1:34:23 lr: 4.255912778431646e-05 loss: 0.1703 (0.1838) time: 2.9898 data: 0.0074 max mem: 33300 +Epoch: [6] [2390/4276] eta: 1:33:54 lr: 4.2556449284639254e-05 loss: 0.1600 (0.1837) time: 3.0213 data: 0.0070 max mem: 33300 +Epoch: [6] [2400/4276] eta: 1:33:24 lr: 4.2553770766230304e-05 loss: 0.1613 (0.1838) time: 3.0096 data: 0.0075 max mem: 33300 +Epoch: [6] [2410/4276] eta: 1:32:54 lr: 4.255109222908816e-05 loss: 0.1792 (0.1838) time: 2.9738 data: 0.0084 max mem: 33300 +Epoch: [6] [2420/4276] eta: 1:32:24 lr: 4.2548413673211395e-05 loss: 0.1656 (0.1837) time: 2.9859 data: 0.0086 max mem: 33300 +Epoch: [6] [2430/4276] eta: 1:31:54 lr: 4.2545735098598556e-05 loss: 0.1666 (0.1838) time: 2.9778 data: 0.0082 max mem: 33300 +Epoch: [6] [2440/4276] eta: 1:31:23 lr: 4.2543056505248196e-05 loss: 0.1860 (0.1837) time: 2.9433 data: 0.0083 max mem: 33300 +Epoch: [6] [2450/4276] eta: 1:30:53 lr: 4.254037789315888e-05 loss: 0.1669 (0.1837) time: 2.9343 data: 0.0086 max mem: 33300 +Epoch: [6] [2460/4276] eta: 1:30:23 lr: 4.253769926232917e-05 loss: 0.1773 (0.1837) time: 2.9370 data: 0.0084 max mem: 33300 +Epoch: [6] [2470/4276] eta: 1:29:53 lr: 4.253502061275761e-05 loss: 0.1733 (0.1837) time: 2.9310 data: 0.0080 max mem: 33300 +Epoch: [6] [2480/4276] eta: 1:29:22 lr: 4.253234194444277e-05 loss: 0.1740 (0.1837) time: 2.9317 data: 0.0080 max mem: 33300 +Epoch: [6] [2490/4276] eta: 1:28:52 lr: 4.25296632573832e-05 loss: 0.1740 (0.1837) time: 2.9340 data: 0.0079 max mem: 33300 +Epoch: [6] [2500/4276] eta: 1:28:22 lr: 4.2526984551577465e-05 loss: 0.1688 (0.1837) time: 2.9159 data: 0.0083 max mem: 33300 +Epoch: [6] [2510/4276] eta: 1:27:51 lr: 4.252430582702412e-05 loss: 0.1735 (0.1836) time: 2.9024 data: 0.0087 max mem: 33300 +Epoch: [6] [2520/4276] eta: 1:27:21 lr: 4.2521627083721716e-05 loss: 0.1572 (0.1835) time: 2.9023 data: 0.0094 max mem: 33300 +Epoch: [6] [2530/4276] eta: 1:26:51 lr: 4.251894832166881e-05 loss: 0.1570 (0.1834) time: 2.9094 data: 0.0102 max mem: 33300 +Epoch: [6] [2540/4276] eta: 1:26:20 lr: 4.2516269540863964e-05 loss: 0.1589 (0.1833) time: 2.9141 data: 0.0103 max mem: 33300 +Epoch: [6] [2550/4276] eta: 1:25:50 lr: 4.2513590741305724e-05 loss: 0.1589 (0.1833) time: 2.9078 data: 0.0099 max mem: 33300 +Epoch: [6] [2560/4276] eta: 1:25:19 lr: 4.251091192299265e-05 loss: 0.1583 (0.1832) time: 2.8941 data: 0.0090 max mem: 33300 +Epoch: [6] [2570/4276] eta: 1:24:49 lr: 4.2508233085923304e-05 loss: 0.1583 (0.1832) time: 2.8812 data: 0.0082 max mem: 33300 +Epoch: [6] [2580/4276] eta: 1:24:18 lr: 4.2505554230096245e-05 loss: 0.1776 (0.1832) time: 2.8801 data: 0.0079 max mem: 33300 +Epoch: [6] [2590/4276] eta: 1:23:48 lr: 4.250287535551001e-05 loss: 0.1695 (0.1831) time: 2.9034 data: 0.0077 max mem: 33300 +Epoch: [6] [2600/4276] eta: 1:23:18 lr: 4.2500196462163164e-05 loss: 0.1777 (0.1832) time: 2.9180 data: 0.0080 max mem: 33300 +Epoch: [6] [2610/4276] eta: 1:22:47 lr: 4.249751755005427e-05 loss: 0.1786 (0.1831) time: 2.8977 data: 0.0088 max mem: 33300 +Epoch: [6] [2620/4276] eta: 1:22:17 lr: 4.249483861918186e-05 loss: 0.1789 (0.1832) time: 2.8879 data: 0.0087 max mem: 33300 +Epoch: [6] [2630/4276] eta: 1:21:47 lr: 4.2492159669544505e-05 loss: 0.1751 (0.1831) time: 2.9113 data: 0.0087 max mem: 33300 +Epoch: [6] [2640/4276] eta: 1:21:17 lr: 4.248948070114076e-05 loss: 0.1528 (0.1831) time: 2.9330 data: 0.0087 max mem: 33300 +Epoch: [6] [2650/4276] eta: 1:20:47 lr: 4.248680171396918e-05 loss: 0.1771 (0.1831) time: 2.9358 data: 0.0081 max mem: 33300 +Epoch: [6] [2660/4276] eta: 1:20:16 lr: 4.2484122708028304e-05 loss: 0.1843 (0.1831) time: 2.9142 data: 0.0087 max mem: 33300 +Epoch: [6] [2670/4276] eta: 1:19:46 lr: 4.24814436833167e-05 loss: 0.1748 (0.1831) time: 2.8868 data: 0.0089 max mem: 33300 +Epoch: [6] [2680/4276] eta: 1:19:15 lr: 4.247876463983292e-05 loss: 0.1705 (0.1831) time: 2.8837 data: 0.0081 max mem: 33300 +Epoch: [6] [2690/4276] eta: 1:18:45 lr: 4.247608557757551e-05 loss: 0.1759 (0.1831) time: 2.8885 data: 0.0087 max mem: 33300 +Epoch: [6] [2700/4276] eta: 1:18:15 lr: 4.247340649654302e-05 loss: 0.1633 (0.1830) time: 2.8892 data: 0.0093 max mem: 33300 +Epoch: [6] [2710/4276] eta: 1:17:44 lr: 4.247072739673402e-05 loss: 0.1633 (0.1830) time: 2.8853 data: 0.0083 max mem: 33300 +Epoch: [6] [2720/4276] eta: 1:17:14 lr: 4.246804827814704e-05 loss: 0.1718 (0.1829) time: 2.8848 data: 0.0077 max mem: 33300 +Epoch: [6] [2730/4276] eta: 1:16:44 lr: 4.246536914078064e-05 loss: 0.1671 (0.1829) time: 2.8858 data: 0.0083 max mem: 33300 +Epoch: [6] [2740/4276] eta: 1:16:14 lr: 4.246268998463339e-05 loss: 0.1922 (0.1830) time: 2.8870 data: 0.0087 max mem: 33300 +Epoch: [6] [2750/4276] eta: 1:15:43 lr: 4.2460010809703816e-05 loss: 0.1886 (0.1830) time: 2.8937 data: 0.0086 max mem: 33300 +Epoch: [6] [2760/4276] eta: 1:15:13 lr: 4.245733161599048e-05 loss: 0.1748 (0.1830) time: 2.8904 data: 0.0082 max mem: 33300 +Epoch: [6] [2770/4276] eta: 1:14:43 lr: 4.245465240349194e-05 loss: 0.1690 (0.1830) time: 2.8958 data: 0.0078 max mem: 33300 +Epoch: [6] [2780/4276] eta: 1:14:13 lr: 4.245197317220673e-05 loss: 0.1744 (0.1830) time: 2.9222 data: 0.0083 max mem: 33300 +Epoch: [6] [2790/4276] eta: 1:13:43 lr: 4.2449293922133424e-05 loss: 0.1845 (0.1830) time: 2.9319 data: 0.0085 max mem: 33300 +Epoch: [6] [2800/4276] eta: 1:13:13 lr: 4.244661465327054e-05 loss: 0.1773 (0.1830) time: 2.9329 data: 0.0081 max mem: 33300 +Epoch: [6] [2810/4276] eta: 1:12:43 lr: 4.244393536561667e-05 loss: 0.1626 (0.1829) time: 2.9335 data: 0.0078 max mem: 33300 +Epoch: [6] [2820/4276] eta: 1:12:13 lr: 4.2441256059170336e-05 loss: 0.1604 (0.1828) time: 2.9342 data: 0.0079 max mem: 33300 +Epoch: [6] [2830/4276] eta: 1:11:43 lr: 4.243857673393009e-05 loss: 0.1646 (0.1828) time: 2.9359 data: 0.0083 max mem: 33300 +Epoch: [6] [2840/4276] eta: 1:11:13 lr: 4.2435897389894487e-05 loss: 0.1646 (0.1828) time: 2.9353 data: 0.0079 max mem: 33300 +Epoch: [6] [2850/4276] eta: 1:10:43 lr: 4.2433218027062074e-05 loss: 0.1908 (0.1829) time: 2.9348 data: 0.0074 max mem: 33300 +Epoch: [6] [2860/4276] eta: 1:10:13 lr: 4.243053864543141e-05 loss: 0.1837 (0.1828) time: 2.9345 data: 0.0073 max mem: 33300 +Epoch: [6] [2870/4276] eta: 1:09:43 lr: 4.242785924500103e-05 loss: 0.1793 (0.1828) time: 2.9347 data: 0.0077 max mem: 33300 +Epoch: [6] [2880/4276] eta: 1:09:13 lr: 4.242517982576949e-05 loss: 0.1802 (0.1828) time: 2.9354 data: 0.0080 max mem: 33300 +Epoch: [6] [2890/4276] eta: 1:08:43 lr: 4.2422500387735345e-05 loss: 0.1860 (0.1829) time: 2.9353 data: 0.0078 max mem: 33300 +Epoch: [6] [2900/4276] eta: 1:08:13 lr: 4.241982093089712e-05 loss: 0.1656 (0.1828) time: 2.9283 data: 0.0079 max mem: 33300 +Epoch: [6] [2910/4276] eta: 1:07:43 lr: 4.241714145525339e-05 loss: 0.1582 (0.1828) time: 2.9276 data: 0.0080 max mem: 33300 +Epoch: [6] [2920/4276] eta: 1:07:13 lr: 4.24144619608027e-05 loss: 0.1780 (0.1828) time: 2.9368 data: 0.0080 max mem: 33300 +Epoch: [6] [2930/4276] eta: 1:06:43 lr: 4.241178244754358e-05 loss: 0.1585 (0.1827) time: 2.9368 data: 0.0078 max mem: 33300 +Epoch: [6] [2940/4276] eta: 1:06:13 lr: 4.240910291547459e-05 loss: 0.1560 (0.1827) time: 2.9302 data: 0.0082 max mem: 33300 +Epoch: [6] [2950/4276] eta: 1:05:43 lr: 4.240642336459427e-05 loss: 0.1651 (0.1827) time: 2.9189 data: 0.0089 max mem: 33300 +Epoch: [6] [2960/4276] eta: 1:05:14 lr: 4.240374379490118e-05 loss: 0.1766 (0.1826) time: 2.9253 data: 0.0089 max mem: 33300 +Epoch: [6] [2970/4276] eta: 1:04:44 lr: 4.2401064206393867e-05 loss: 0.1745 (0.1827) time: 2.9388 data: 0.0087 max mem: 33300 +Epoch: [6] [2980/4276] eta: 1:04:14 lr: 4.239838459907086e-05 loss: 0.1745 (0.1827) time: 2.9393 data: 0.0087 max mem: 33300 +Epoch: [6] [2990/4276] eta: 1:03:44 lr: 4.2395704972930716e-05 loss: 0.1689 (0.1826) time: 2.9173 data: 0.0088 max mem: 33300 +Epoch: [6] [3000/4276] eta: 1:03:14 lr: 4.239302532797199e-05 loss: 0.1587 (0.1825) time: 2.9161 data: 0.0087 max mem: 33300 +Epoch: [6] [3010/4276] eta: 1:02:44 lr: 4.239034566419321e-05 loss: 0.1603 (0.1825) time: 2.9360 data: 0.0080 max mem: 33300 +Epoch: [6] [3020/4276] eta: 1:02:14 lr: 4.238766598159294e-05 loss: 0.1646 (0.1825) time: 2.9318 data: 0.0078 max mem: 33300 +Epoch: [6] [3030/4276] eta: 1:01:44 lr: 4.238498628016971e-05 loss: 0.1688 (0.1825) time: 2.9201 data: 0.0082 max mem: 33300 +Epoch: [6] [3040/4276] eta: 1:01:14 lr: 4.2382306559922076e-05 loss: 0.1752 (0.1826) time: 2.9213 data: 0.0082 max mem: 33300 +Epoch: [6] [3050/4276] eta: 1:00:44 lr: 4.237962682084858e-05 loss: 0.1790 (0.1825) time: 2.9358 data: 0.0079 max mem: 33300 +Epoch: [6] [3060/4276] eta: 1:00:14 lr: 4.237694706294776e-05 loss: 0.1533 (0.1825) time: 2.9365 data: 0.0082 max mem: 33300 +Epoch: [6] [3070/4276] eta: 0:59:44 lr: 4.237426728621818e-05 loss: 0.1632 (0.1825) time: 2.9396 data: 0.0082 max mem: 33300 +Epoch: [6] [3080/4276] eta: 0:59:15 lr: 4.2371587490658374e-05 loss: 0.1816 (0.1825) time: 2.9404 data: 0.0079 max mem: 33300 +Epoch: [6] [3090/4276] eta: 0:58:45 lr: 4.2368907676266876e-05 loss: 0.1603 (0.1824) time: 2.9412 data: 0.0079 max mem: 33300 +Epoch: [6] [3100/4276] eta: 0:58:15 lr: 4.236622784304224e-05 loss: 0.1667 (0.1824) time: 2.9405 data: 0.0081 max mem: 33300 +Epoch: [6] [3110/4276] eta: 0:57:45 lr: 4.236354799098301e-05 loss: 0.1645 (0.1823) time: 2.9389 data: 0.0083 max mem: 33300 +Epoch: [6] [3120/4276] eta: 0:57:15 lr: 4.2360868120087725e-05 loss: 0.1539 (0.1822) time: 2.9395 data: 0.0081 max mem: 33300 +Epoch: [6] [3130/4276] eta: 0:56:45 lr: 4.2358188230354944e-05 loss: 0.1539 (0.1822) time: 2.9343 data: 0.0079 max mem: 33300 +Epoch: [6] [3140/4276] eta: 0:56:16 lr: 4.2355508321783195e-05 loss: 0.1685 (0.1822) time: 2.9333 data: 0.0081 max mem: 33300 +Epoch: [6] [3150/4276] eta: 0:55:46 lr: 4.235282839437102e-05 loss: 0.1893 (0.1822) time: 2.9353 data: 0.0084 max mem: 33300 +Epoch: [6] [3160/4276] eta: 0:55:16 lr: 4.235014844811697e-05 loss: 0.1872 (0.1822) time: 2.9351 data: 0.0083 max mem: 33300 +Epoch: [6] [3170/4276] eta: 0:54:46 lr: 4.234746848301959e-05 loss: 0.1712 (0.1822) time: 2.9349 data: 0.0084 max mem: 33300 +Epoch: [6] [3180/4276] eta: 0:54:16 lr: 4.234478849907741e-05 loss: 0.1709 (0.1822) time: 2.9349 data: 0.0085 max mem: 33300 +Epoch: [6] [3190/4276] eta: 0:53:46 lr: 4.234210849628898e-05 loss: 0.1709 (0.1822) time: 2.9347 data: 0.0084 max mem: 33300 +Epoch: [6] [3200/4276] eta: 0:53:16 lr: 4.233942847465284e-05 loss: 0.1757 (0.1822) time: 2.9356 data: 0.0081 max mem: 33300 +Epoch: [6] [3210/4276] eta: 0:52:47 lr: 4.233674843416754e-05 loss: 0.1735 (0.1822) time: 2.9343 data: 0.0079 max mem: 33300 +Epoch: [6] [3220/4276] eta: 0:52:17 lr: 4.2334068374831606e-05 loss: 0.1901 (0.1822) time: 2.9337 data: 0.0081 max mem: 33300 +Epoch: [6] [3230/4276] eta: 0:51:47 lr: 4.2331388296643596e-05 loss: 0.1756 (0.1822) time: 2.9343 data: 0.0085 max mem: 33300 +Epoch: [6] [3240/4276] eta: 0:51:17 lr: 4.232870819960205e-05 loss: 0.1953 (0.1823) time: 2.9375 data: 0.0089 max mem: 33300 +Epoch: [6] [3250/4276] eta: 0:50:47 lr: 4.232602808370549e-05 loss: 0.1924 (0.1823) time: 2.9460 data: 0.0088 max mem: 33300 +Epoch: [6] [3260/4276] eta: 0:50:17 lr: 4.232334794895247e-05 loss: 0.1853 (0.1823) time: 2.9297 data: 0.0084 max mem: 33300 +Epoch: [6] [3270/4276] eta: 0:49:48 lr: 4.232066779534153e-05 loss: 0.1853 (0.1822) time: 2.9122 data: 0.0092 max mem: 33300 +Epoch: [6] [3280/4276] eta: 0:49:18 lr: 4.2317987622871215e-05 loss: 0.1820 (0.1823) time: 2.9281 data: 0.0096 max mem: 33300 +Epoch: [6] [3290/4276] eta: 0:48:48 lr: 4.2315307431540055e-05 loss: 0.1817 (0.1823) time: 2.9396 data: 0.0091 max mem: 33300 +Epoch: [6] [3300/4276] eta: 0:48:18 lr: 4.23126272213466e-05 loss: 0.1817 (0.1823) time: 2.9425 data: 0.0090 max mem: 33300 +Epoch: [6] [3310/4276] eta: 0:47:48 lr: 4.2309946992289386e-05 loss: 0.1889 (0.1824) time: 2.9448 data: 0.0088 max mem: 33300 +Epoch: [6] [3320/4276] eta: 0:47:19 lr: 4.2307266744366944e-05 loss: 0.1890 (0.1824) time: 2.9436 data: 0.0083 max mem: 33300 +Epoch: [6] [3330/4276] eta: 0:46:49 lr: 4.2304586477577826e-05 loss: 0.1731 (0.1824) time: 2.9388 data: 0.0077 max mem: 33300 +Epoch: [6] [3340/4276] eta: 0:46:19 lr: 4.230190619192057e-05 loss: 0.1731 (0.1824) time: 2.9393 data: 0.0079 max mem: 33300 +Epoch: [6] [3350/4276] eta: 0:45:49 lr: 4.22992258873937e-05 loss: 0.1652 (0.1823) time: 2.9392 data: 0.0083 max mem: 33300 +Epoch: [6] [3360/4276] eta: 0:45:20 lr: 4.229654556399578e-05 loss: 0.1724 (0.1823) time: 2.9397 data: 0.0083 max mem: 33300 +Epoch: [6] [3370/4276] eta: 0:44:50 lr: 4.229386522172532e-05 loss: 0.1821 (0.1824) time: 2.9423 data: 0.0081 max mem: 33300 +Epoch: [6] [3380/4276] eta: 0:44:20 lr: 4.2291184860580875e-05 loss: 0.1894 (0.1824) time: 2.9513 data: 0.0077 max mem: 33300 +Epoch: [6] [3390/4276] eta: 0:43:50 lr: 4.228850448056098e-05 loss: 0.1894 (0.1825) time: 2.9508 data: 0.0079 max mem: 33300 +Epoch: [6] [3400/4276] eta: 0:43:21 lr: 4.2285824081664174e-05 loss: 0.2064 (0.1825) time: 2.9383 data: 0.0081 max mem: 33300 +Epoch: [6] [3410/4276] eta: 0:42:51 lr: 4.228314366388899e-05 loss: 0.1869 (0.1825) time: 2.9380 data: 0.0082 max mem: 33300 +Epoch: [6] [3420/4276] eta: 0:42:21 lr: 4.2280463227233964e-05 loss: 0.1834 (0.1826) time: 2.9364 data: 0.0082 max mem: 33300 +Epoch: [6] [3430/4276] eta: 0:41:51 lr: 4.227778277169764e-05 loss: 0.1807 (0.1826) time: 2.9336 data: 0.0078 max mem: 33300 +Epoch: [6] [3440/4276] eta: 0:41:21 lr: 4.227510229727856e-05 loss: 0.1717 (0.1825) time: 2.9320 data: 0.0075 max mem: 33300 +Epoch: [6] [3450/4276] eta: 0:40:52 lr: 4.227242180397525e-05 loss: 0.1702 (0.1825) time: 2.9327 data: 0.0078 max mem: 33300 +Epoch: [6] [3460/4276] eta: 0:40:22 lr: 4.226974129178624e-05 loss: 0.1806 (0.1825) time: 2.9326 data: 0.0078 max mem: 33300 +Epoch: [6] [3470/4276] eta: 0:39:52 lr: 4.226706076071009e-05 loss: 0.1657 (0.1825) time: 2.9321 data: 0.0076 max mem: 33300 +Epoch: [6] [3480/4276] eta: 0:39:22 lr: 4.2264380210745314e-05 loss: 0.1828 (0.1825) time: 2.9322 data: 0.0076 max mem: 33300 +Epoch: [6] [3490/4276] eta: 0:38:53 lr: 4.226169964189045e-05 loss: 0.1916 (0.1825) time: 2.9315 data: 0.0076 max mem: 33300 +Epoch: [6] [3500/4276] eta: 0:38:23 lr: 4.225901905414404e-05 loss: 0.1880 (0.1825) time: 2.9319 data: 0.0073 max mem: 33300 +Epoch: [6] [3510/4276] eta: 0:37:53 lr: 4.225633844750463e-05 loss: 0.1768 (0.1825) time: 2.9460 data: 0.0071 max mem: 33300 +Epoch: [6] [3520/4276] eta: 0:37:23 lr: 4.2253657821970734e-05 loss: 0.1851 (0.1825) time: 2.9449 data: 0.0071 max mem: 33300 +Epoch: [6] [3530/4276] eta: 0:36:54 lr: 4.2250977177540894e-05 loss: 0.1851 (0.1825) time: 2.9313 data: 0.0073 max mem: 33300 +Epoch: [6] [3540/4276] eta: 0:36:24 lr: 4.224829651421366e-05 loss: 0.1837 (0.1825) time: 2.9319 data: 0.0074 max mem: 33300 +Epoch: [6] [3550/4276] eta: 0:35:54 lr: 4.224561583198754e-05 loss: 0.1743 (0.1824) time: 2.9337 data: 0.0074 max mem: 33300 +Epoch: [6] [3560/4276] eta: 0:35:24 lr: 4.2242935130861085e-05 loss: 0.1701 (0.1825) time: 2.9331 data: 0.0073 max mem: 33300 +Epoch: [6] [3570/4276] eta: 0:34:55 lr: 4.224025441083282e-05 loss: 0.1919 (0.1825) time: 2.9225 data: 0.0071 max mem: 33300 +Epoch: [6] [3580/4276] eta: 0:34:25 lr: 4.223757367190129e-05 loss: 0.1770 (0.1825) time: 2.9248 data: 0.0071 max mem: 33300 +Epoch: [6] [3590/4276] eta: 0:33:55 lr: 4.223489291406503e-05 loss: 0.1613 (0.1825) time: 2.9338 data: 0.0071 max mem: 33300 +Epoch: [6] [3600/4276] eta: 0:33:25 lr: 4.2232212137322565e-05 loss: 0.1833 (0.1825) time: 2.9329 data: 0.0071 max mem: 33300 +Epoch: [6] [3610/4276] eta: 0:32:56 lr: 4.222953134167242e-05 loss: 0.1900 (0.1825) time: 2.9351 data: 0.0072 max mem: 33300 +Epoch: [6] [3620/4276] eta: 0:32:26 lr: 4.222685052711315e-05 loss: 0.1906 (0.1825) time: 2.9345 data: 0.0072 max mem: 33300 +Epoch: [6] [3630/4276] eta: 0:31:56 lr: 4.2224169693643266e-05 loss: 0.1922 (0.1825) time: 2.9382 data: 0.0074 max mem: 33300 +Epoch: [6] [3640/4276] eta: 0:31:26 lr: 4.2221488841261315e-05 loss: 0.1772 (0.1825) time: 2.9388 data: 0.0074 max mem: 33300 +Epoch: [6] [3650/4276] eta: 0:30:57 lr: 4.2218807969965816e-05 loss: 0.1562 (0.1825) time: 2.9376 data: 0.0072 max mem: 33300 +Epoch: [6] [3660/4276] eta: 0:30:27 lr: 4.221612707975532e-05 loss: 0.1549 (0.1824) time: 2.9378 data: 0.0074 max mem: 33300 +Epoch: [6] [3670/4276] eta: 0:29:57 lr: 4.221344617062835e-05 loss: 0.1650 (0.1824) time: 2.9391 data: 0.0077 max mem: 33300 +Epoch: [6] [3680/4276] eta: 0:29:28 lr: 4.221076524258343e-05 loss: 0.1919 (0.1824) time: 2.9402 data: 0.0077 max mem: 33300 +Epoch: [6] [3690/4276] eta: 0:28:58 lr: 4.2208084295619096e-05 loss: 0.1830 (0.1824) time: 2.9371 data: 0.0074 max mem: 33300 +Epoch: [6] [3700/4276] eta: 0:28:28 lr: 4.220540332973388e-05 loss: 0.1805 (0.1824) time: 2.9515 data: 0.0073 max mem: 33300 +Epoch: [6] [3710/4276] eta: 0:27:58 lr: 4.220272234492632e-05 loss: 0.1740 (0.1824) time: 2.9494 data: 0.0072 max mem: 33300 +Epoch: [6] [3720/4276] eta: 0:27:29 lr: 4.2200041341194935e-05 loss: 0.1601 (0.1824) time: 2.9325 data: 0.0072 max mem: 33300 +Epoch: [6] [3730/4276] eta: 0:26:59 lr: 4.219736031853827e-05 loss: 0.1772 (0.1824) time: 2.9382 data: 0.0072 max mem: 33300 +Epoch: [6] [3740/4276] eta: 0:26:29 lr: 4.219467927695484e-05 loss: 0.1772 (0.1824) time: 2.9386 data: 0.0072 max mem: 33300 +Epoch: [6] [3750/4276] eta: 0:26:00 lr: 4.219199821644318e-05 loss: 0.1716 (0.1824) time: 2.9295 data: 0.0072 max mem: 33300 +Epoch: [6] [3760/4276] eta: 0:25:30 lr: 4.218931713700182e-05 loss: 0.1716 (0.1824) time: 2.9283 data: 0.0073 max mem: 33300 +Epoch: [6] [3770/4276] eta: 0:25:00 lr: 4.2186636038629295e-05 loss: 0.1817 (0.1824) time: 2.9293 data: 0.0072 max mem: 33300 +Epoch: [6] [3780/4276] eta: 0:24:31 lr: 4.218395492132413e-05 loss: 0.1737 (0.1824) time: 2.9291 data: 0.0073 max mem: 33300 +Epoch: [6] [3790/4276] eta: 0:24:01 lr: 4.2181273785084856e-05 loss: 0.1737 (0.1824) time: 2.9296 data: 0.0077 max mem: 33300 +Epoch: [6] [3800/4276] eta: 0:23:31 lr: 4.2178592629910005e-05 loss: 0.1944 (0.1825) time: 2.9293 data: 0.0077 max mem: 33300 +Epoch: [6] [3810/4276] eta: 0:23:01 lr: 4.217591145579809e-05 loss: 0.1782 (0.1825) time: 2.9283 data: 0.0075 max mem: 33300 +Epoch: [6] [3820/4276] eta: 0:22:32 lr: 4.217323026274766e-05 loss: 0.1561 (0.1824) time: 2.9213 data: 0.0076 max mem: 33300 +Epoch: [6] [3830/4276] eta: 0:22:02 lr: 4.2170549050757236e-05 loss: 0.1637 (0.1824) time: 2.9066 data: 0.0078 max mem: 33300 +Epoch: [6] [3840/4276] eta: 0:21:32 lr: 4.2167867819825344e-05 loss: 0.1694 (0.1824) time: 2.9064 data: 0.0083 max mem: 33300 +Epoch: [6] [3850/4276] eta: 0:21:03 lr: 4.216518656995051e-05 loss: 0.1702 (0.1823) time: 2.9206 data: 0.0081 max mem: 33300 +Epoch: [6] [3860/4276] eta: 0:20:33 lr: 4.216250530113127e-05 loss: 0.1709 (0.1823) time: 2.9182 data: 0.0073 max mem: 33300 +Epoch: [6] [3870/4276] eta: 0:20:03 lr: 4.215982401336614e-05 loss: 0.1741 (0.1823) time: 2.9084 data: 0.0073 max mem: 33300 +Epoch: [6] [3880/4276] eta: 0:19:33 lr: 4.215714270665366e-05 loss: 0.1741 (0.1823) time: 2.9099 data: 0.0075 max mem: 33300 +Epoch: [6] [3890/4276] eta: 0:19:04 lr: 4.215446138099234e-05 loss: 0.1660 (0.1823) time: 2.9106 data: 0.0073 max mem: 33300 +Epoch: [6] [3900/4276] eta: 0:18:34 lr: 4.2151780036380726e-05 loss: 0.1698 (0.1823) time: 2.9153 data: 0.0071 max mem: 33300 +Epoch: [6] [3910/4276] eta: 0:18:04 lr: 4.214909867281734e-05 loss: 0.1680 (0.1822) time: 2.9258 data: 0.0071 max mem: 33300 +Epoch: [6] [3920/4276] eta: 0:17:35 lr: 4.2146417290300695e-05 loss: 0.1645 (0.1822) time: 2.9338 data: 0.0072 max mem: 33300 +Epoch: [6] [3930/4276] eta: 0:17:05 lr: 4.214373588882934e-05 loss: 0.1730 (0.1823) time: 2.9283 data: 0.0072 max mem: 33300 +Epoch: [6] [3940/4276] eta: 0:16:35 lr: 4.2141054468401776e-05 loss: 0.1730 (0.1823) time: 2.9184 data: 0.0072 max mem: 33300 +Epoch: [6] [3950/4276] eta: 0:16:06 lr: 4.213837302901654e-05 loss: 0.1718 (0.1822) time: 2.9198 data: 0.0075 max mem: 33300 +Epoch: [6] [3960/4276] eta: 0:15:36 lr: 4.2135691570672164e-05 loss: 0.1782 (0.1822) time: 2.9201 data: 0.0074 max mem: 33300 +Epoch: [6] [3970/4276] eta: 0:15:06 lr: 4.2133010093367166e-05 loss: 0.1824 (0.1823) time: 2.9230 data: 0.0075 max mem: 33300 +Epoch: [6] [3980/4276] eta: 0:14:37 lr: 4.2130328597100076e-05 loss: 0.1799 (0.1823) time: 2.9220 data: 0.0077 max mem: 33300 +Epoch: [6] [3990/4276] eta: 0:14:07 lr: 4.212764708186941e-05 loss: 0.1799 (0.1823) time: 2.9199 data: 0.0075 max mem: 33300 +Epoch: [6] [4000/4276] eta: 0:13:37 lr: 4.21249655476737e-05 loss: 0.1698 (0.1823) time: 2.9208 data: 0.0073 max mem: 33300 +Epoch: [6] [4010/4276] eta: 0:13:08 lr: 4.2122283994511475e-05 loss: 0.1662 (0.1823) time: 2.9246 data: 0.0072 max mem: 33300 +Epoch: [6] [4020/4276] eta: 0:12:38 lr: 4.211960242238124e-05 loss: 0.1777 (0.1823) time: 2.9200 data: 0.0074 max mem: 33300 +Epoch: [6] [4030/4276] eta: 0:12:08 lr: 4.211692083128154e-05 loss: 0.1829 (0.1823) time: 2.9180 data: 0.0076 max mem: 33300 +Epoch: [6] [4040/4276] eta: 0:11:39 lr: 4.211423922121089e-05 loss: 0.1829 (0.1824) time: 2.9089 data: 0.0081 max mem: 33300 +Epoch: [6] [4050/4276] eta: 0:11:09 lr: 4.211155759216781e-05 loss: 0.1743 (0.1824) time: 2.8775 data: 0.0086 max mem: 33300 +Epoch: [6] [4060/4276] eta: 0:10:39 lr: 4.2108875944150836e-05 loss: 0.1705 (0.1824) time: 2.8628 data: 0.0082 max mem: 33300 +Epoch: [6] [4070/4276] eta: 0:10:10 lr: 4.210619427715848e-05 loss: 0.1798 (0.1824) time: 2.8615 data: 0.0081 max mem: 33300 +Epoch: [6] [4080/4276] eta: 0:09:40 lr: 4.210351259118926e-05 loss: 0.1798 (0.1824) time: 2.8626 data: 0.0083 max mem: 33300 +Epoch: [6] [4090/4276] eta: 0:09:10 lr: 4.210083088624172e-05 loss: 0.1862 (0.1824) time: 2.8611 data: 0.0079 max mem: 33300 +Epoch: [6] [4100/4276] eta: 0:08:41 lr: 4.209814916231436e-05 loss: 0.1862 (0.1824) time: 2.8616 data: 0.0083 max mem: 33300 +Epoch: [6] [4110/4276] eta: 0:08:11 lr: 4.2095467419405714e-05 loss: 0.1843 (0.1824) time: 2.8654 data: 0.0089 max mem: 33300 +Epoch: [6] [4120/4276] eta: 0:07:41 lr: 4.20927856575143e-05 loss: 0.1843 (0.1824) time: 2.8654 data: 0.0085 max mem: 33300 +Epoch: [6] [4130/4276] eta: 0:07:12 lr: 4.209010387663864e-05 loss: 0.1763 (0.1824) time: 2.8982 data: 0.0087 max mem: 33300 +Epoch: [6] [4140/4276] eta: 0:06:42 lr: 4.208742207677726e-05 loss: 0.1719 (0.1824) time: 2.9274 data: 0.0091 max mem: 33300 +Epoch: [6] [4150/4276] eta: 0:06:13 lr: 4.208474025792868e-05 loss: 0.1743 (0.1824) time: 2.9200 data: 0.0089 max mem: 33300 +Epoch: [6] [4160/4276] eta: 0:05:43 lr: 4.208205842009141e-05 loss: 0.1739 (0.1824) time: 2.9280 data: 0.0087 max mem: 33300 +Epoch: [6] [4170/4276] eta: 0:05:13 lr: 4.207937656326399e-05 loss: 0.1813 (0.1824) time: 2.9329 data: 0.0091 max mem: 33300 +Epoch: [6] [4180/4276] eta: 0:04:44 lr: 4.207669468744493e-05 loss: 0.1791 (0.1824) time: 2.9184 data: 0.0100 max mem: 33300 +Epoch: [6] [4190/4276] eta: 0:04:14 lr: 4.207401279263275e-05 loss: 0.1654 (0.1824) time: 2.8993 data: 0.0097 max mem: 33300 +Epoch: [6] [4200/4276] eta: 0:03:44 lr: 4.2071330878825956e-05 loss: 0.1823 (0.1824) time: 2.8912 data: 0.0086 max mem: 33300 +Epoch: [6] [4210/4276] eta: 0:03:15 lr: 4.206864894602311e-05 loss: 0.2089 (0.1825) time: 2.8992 data: 0.0087 max mem: 33300 +Epoch: [6] [4220/4276] eta: 0:02:45 lr: 4.206596699422269e-05 loss: 0.2110 (0.1826) time: 2.9321 data: 0.0092 max mem: 33300 +Epoch: [6] [4230/4276] eta: 0:02:16 lr: 4.206328502342323e-05 loss: 0.2134 (0.1826) time: 2.9516 data: 0.0091 max mem: 33300 +Epoch: [6] [4240/4276] eta: 0:01:46 lr: 4.206060303362326e-05 loss: 0.2100 (0.1827) time: 2.9635 data: 0.0085 max mem: 33300 +Epoch: [6] [4250/4276] eta: 0:01:16 lr: 4.205792102482129e-05 loss: 0.1969 (0.1827) time: 3.0049 data: 0.0085 max mem: 33300 +Epoch: [6] [4260/4276] eta: 0:00:47 lr: 4.2055238997015825e-05 loss: 0.1969 (0.1828) time: 3.0490 data: 0.0084 max mem: 33300 +Epoch: [6] [4270/4276] eta: 0:00:17 lr: 4.205255695020541e-05 loss: 0.1910 (0.1828) time: 3.0689 data: 0.0075 max mem: 33300 +Epoch: [6] Total time: 3:31:00 +Test: [ 0/21770] eta: 13:24:05 time: 2.2161 data: 2.1719 max mem: 33300 +Test: [ 100/21770] eta: 0:21:52 time: 0.0393 data: 0.0011 max mem: 33300 +Test: [ 200/21770] eta: 0:17:52 time: 0.0381 data: 0.0011 max mem: 33300 +Test: [ 300/21770] eta: 0:16:24 time: 0.0381 data: 0.0011 max mem: 33300 +Test: [ 400/21770] eta: 0:15:38 time: 0.0382 data: 0.0011 max mem: 33300 +Test: [ 500/21770] eta: 0:15:09 time: 0.0383 data: 0.0011 max mem: 33300 +Test: [ 600/21770] eta: 0:14:49 time: 0.0383 data: 0.0011 max mem: 33300 +Test: [ 700/21770] eta: 0:14:34 time: 0.0385 data: 0.0011 max mem: 33300 +Test: [ 800/21770] eta: 0:14:22 time: 0.0385 data: 0.0011 max mem: 33300 +Test: [ 900/21770] eta: 0:14:11 time: 0.0381 data: 0.0011 max mem: 33300 +Test: [ 1000/21770] eta: 0:14:02 time: 0.0382 data: 0.0011 max mem: 33300 +Test: [ 1100/21770] eta: 0:13:53 time: 0.0382 data: 0.0011 max mem: 33300 +Test: [ 1200/21770] eta: 0:13:46 time: 0.0384 data: 0.0011 max mem: 33300 +Test: [ 1300/21770] eta: 0:13:40 time: 0.0389 data: 0.0011 max mem: 33300 +Test: [ 1400/21770] eta: 0:13:34 time: 0.0391 data: 0.0011 max mem: 33300 +Test: [ 1500/21770] eta: 0:13:29 time: 0.0396 data: 0.0011 max mem: 33300 +Test: [ 1600/21770] eta: 0:13:24 time: 0.0395 data: 0.0011 max mem: 33300 +Test: [ 1700/21770] eta: 0:13:19 time: 0.0382 data: 0.0011 max mem: 33300 +Test: [ 1800/21770] eta: 0:13:13 time: 0.0383 data: 0.0011 max mem: 33300 +Test: [ 1900/21770] eta: 0:13:08 time: 0.0383 data: 0.0011 max mem: 33300 +Test: [ 2000/21770] eta: 0:13:03 time: 0.0384 data: 0.0011 max mem: 33300 +Test: [ 2100/21770] eta: 0:12:58 time: 0.0384 data: 0.0011 max mem: 33300 +Test: [ 2200/21770] eta: 0:12:53 time: 0.0385 data: 0.0011 max mem: 33300 +Test: [ 2300/21770] eta: 0:12:48 time: 0.0386 data: 0.0011 max mem: 33300 +Test: [ 2400/21770] eta: 0:12:43 time: 0.0385 data: 0.0011 max mem: 33300 +Test: [ 2500/21770] eta: 0:12:39 time: 0.0389 data: 0.0011 max mem: 33300 +Test: [ 2600/21770] eta: 0:12:34 time: 0.0386 data: 0.0011 max mem: 33300 +Test: [ 2700/21770] eta: 0:12:31 time: 0.0399 data: 0.0012 max mem: 33300 +Test: [ 2800/21770] eta: 0:12:27 time: 0.0402 data: 0.0012 max mem: 33300 +Test: [ 2900/21770] eta: 0:12:24 time: 0.0395 data: 0.0011 max mem: 33300 +Test: [ 3000/21770] eta: 0:12:20 time: 0.0399 data: 0.0011 max mem: 33300 +Test: [ 3100/21770] eta: 0:12:15 time: 0.0386 data: 0.0012 max mem: 33300 +Test: [ 3200/21770] eta: 0:12:11 time: 0.0386 data: 0.0011 max mem: 33300 +Test: [ 3300/21770] eta: 0:12:07 time: 0.0392 data: 0.0012 max mem: 33300 +Test: [ 3400/21770] eta: 0:12:03 time: 0.0392 data: 0.0011 max mem: 33300 +Test: [ 3500/21770] eta: 0:11:59 time: 0.0384 data: 0.0011 max mem: 33300 +Test: [ 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time: 0.0388 data: 0.0011 max mem: 33300 +Test: [ 5000/21770] eta: 0:10:56 time: 0.0386 data: 0.0011 max mem: 33300 +Test: [ 5100/21770] eta: 0:10:52 time: 0.0384 data: 0.0011 max mem: 33300 +Test: [ 5200/21770] eta: 0:10:48 time: 0.0383 data: 0.0011 max mem: 33300 +Test: [ 5300/21770] eta: 0:10:44 time: 0.0386 data: 0.0011 max mem: 33300 +Test: [ 5400/21770] eta: 0:10:40 time: 0.0384 data: 0.0011 max mem: 33300 +Test: [ 5500/21770] eta: 0:10:36 time: 0.0387 data: 0.0011 max mem: 33300 +Test: [ 5600/21770] eta: 0:10:32 time: 0.0387 data: 0.0011 max mem: 33300 +Test: [ 5700/21770] eta: 0:10:28 time: 0.0387 data: 0.0011 max mem: 33300 +Test: [ 5800/21770] eta: 0:10:23 time: 0.0384 data: 0.0011 max mem: 33300 +Test: [ 5900/21770] eta: 0:10:19 time: 0.0383 data: 0.0011 max mem: 33300 +Test: [ 6000/21770] eta: 0:10:15 time: 0.0383 data: 0.0011 max mem: 33300 +Test: [ 6100/21770] eta: 0:10:11 time: 0.0386 data: 0.0011 max mem: 33300 +Test: [ 6200/21770] eta: 0:10:07 time: 0.0384 data: 0.0011 max mem: 33300 +Test: [ 6300/21770] eta: 0:10:03 time: 0.0384 data: 0.0011 max mem: 33300 +Test: [ 6400/21770] eta: 0:09:59 time: 0.0397 data: 0.0011 max mem: 33300 +Test: [ 6500/21770] eta: 0:09:56 time: 0.0398 data: 0.0013 max mem: 33300 +Test: [ 6600/21770] eta: 0:09:52 time: 0.0387 data: 0.0011 max mem: 33300 +Test: [ 6700/21770] eta: 0:09:48 time: 0.0385 data: 0.0011 max mem: 33300 +Test: [ 6800/21770] eta: 0:09:44 time: 0.0383 data: 0.0011 max mem: 33300 +Test: [ 6900/21770] eta: 0:09:40 time: 0.0386 data: 0.0011 max mem: 33300 +Test: [ 7000/21770] eta: 0:09:36 time: 0.0391 data: 0.0012 max mem: 33300 +Test: [ 7100/21770] eta: 0:09:32 time: 0.0389 data: 0.0011 max mem: 33300 +Test: [ 7200/21770] eta: 0:09:28 time: 0.0387 data: 0.0011 max mem: 33300 +Test: [ 7300/21770] eta: 0:09:24 time: 0.0390 data: 0.0012 max mem: 33300 +Test: [ 7400/21770] eta: 0:09:20 time: 0.0393 data: 0.0011 max mem: 33300 +Test: [ 7500/21770] eta: 0:09:16 time: 0.0392 data: 0.0011 max mem: 33300 +Test: [ 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time: 0.0387 data: 0.0012 max mem: 33300 +Test: [ 9000/21770] eta: 0:08:17 time: 0.0387 data: 0.0011 max mem: 33300 +Test: [ 9100/21770] eta: 0:08:13 time: 0.0390 data: 0.0011 max mem: 33300 +Test: [ 9200/21770] eta: 0:08:10 time: 0.0385 data: 0.0011 max mem: 33300 +Test: [ 9300/21770] eta: 0:08:06 time: 0.0385 data: 0.0011 max mem: 33300 +Test: [ 9400/21770] eta: 0:08:02 time: 0.0384 data: 0.0010 max mem: 33300 +Test: [ 9500/21770] eta: 0:07:58 time: 0.0382 data: 0.0011 max mem: 33300 +Test: [ 9600/21770] eta: 0:07:54 time: 0.0386 data: 0.0012 max mem: 33300 +Test: [ 9700/21770] eta: 0:07:50 time: 0.0387 data: 0.0012 max mem: 33300 +Test: [ 9800/21770] eta: 0:07:46 time: 0.0390 data: 0.0012 max mem: 33300 +Test: [ 9900/21770] eta: 0:07:42 time: 0.0387 data: 0.0011 max mem: 33300 +Test: [10000/21770] eta: 0:07:38 time: 0.0394 data: 0.0012 max mem: 33300 +Test: [10100/21770] eta: 0:07:34 time: 0.0386 data: 0.0011 max mem: 33300 +Test: [10200/21770] eta: 0:07:30 time: 0.0388 data: 0.0011 max mem: 33300 +Test: [10300/21770] eta: 0:07:26 time: 0.0391 data: 0.0012 max mem: 33300 +Test: [10400/21770] eta: 0:07:22 time: 0.0389 data: 0.0012 max mem: 33300 +Test: [10500/21770] eta: 0:07:18 time: 0.0391 data: 0.0011 max mem: 33300 +Test: [10600/21770] eta: 0:07:15 time: 0.0400 data: 0.0012 max mem: 33300 +Test: [10700/21770] eta: 0:07:11 time: 0.0387 data: 0.0012 max mem: 33300 +Test: [10800/21770] eta: 0:07:07 time: 0.0384 data: 0.0011 max mem: 33300 +Test: [10900/21770] eta: 0:07:03 time: 0.0385 data: 0.0011 max mem: 33300 +Test: [11000/21770] eta: 0:06:59 time: 0.0389 data: 0.0011 max mem: 33300 +Test: [11100/21770] eta: 0:06:55 time: 0.0391 data: 0.0011 max mem: 33300 +Test: [11200/21770] eta: 0:06:51 time: 0.0389 data: 0.0011 max mem: 33300 +Test: [11300/21770] eta: 0:06:47 time: 0.0386 data: 0.0011 max mem: 33300 +Test: [11400/21770] eta: 0:06:43 time: 0.0387 data: 0.0011 max mem: 33300 +Test: [11500/21770] eta: 0:06:39 time: 0.0388 data: 0.0012 max mem: 33300 +Test: [11600/21770] eta: 0:06:36 time: 0.0388 data: 0.0012 max mem: 33300 +Test: [11700/21770] eta: 0:06:32 time: 0.0385 data: 0.0011 max mem: 33300 +Test: [11800/21770] eta: 0:06:28 time: 0.0388 data: 0.0012 max mem: 33300 +Test: [11900/21770] eta: 0:06:24 time: 0.0388 data: 0.0012 max mem: 33300 +Test: [12000/21770] eta: 0:06:20 time: 0.0391 data: 0.0011 max mem: 33300 +Test: [12100/21770] eta: 0:06:16 time: 0.0386 data: 0.0011 max mem: 33300 +Test: [12200/21770] eta: 0:06:12 time: 0.0387 data: 0.0011 max mem: 33300 +Test: [12300/21770] eta: 0:06:08 time: 0.0385 data: 0.0011 max mem: 33300 +Test: [12400/21770] eta: 0:06:04 time: 0.0386 data: 0.0011 max mem: 33300 +Test: [12500/21770] eta: 0:06:00 time: 0.0383 data: 0.0011 max mem: 33300 +Test: [12600/21770] eta: 0:05:56 time: 0.0386 data: 0.0012 max mem: 33300 +Test: [12700/21770] eta: 0:05:52 time: 0.0387 data: 0.0011 max mem: 33300 +Test: [12800/21770] eta: 0:05:49 time: 0.0389 data: 0.0011 max mem: 33300 +Test: [12900/21770] eta: 0:05:45 time: 0.0387 data: 0.0011 max mem: 33300 +Test: [13000/21770] eta: 0:05:41 time: 0.0390 data: 0.0011 max mem: 33300 +Test: [13100/21770] eta: 0:05:37 time: 0.0387 data: 0.0011 max mem: 33300 +Test: [13200/21770] eta: 0:05:33 time: 0.0389 data: 0.0011 max mem: 33300 +Test: [13300/21770] eta: 0:05:29 time: 0.0389 data: 0.0011 max mem: 33300 +Test: [13400/21770] eta: 0:05:25 time: 0.0389 data: 0.0011 max mem: 33300 +Test: [13500/21770] eta: 0:05:21 time: 0.0387 data: 0.0011 max mem: 33300 +Test: [13600/21770] eta: 0:05:17 time: 0.0387 data: 0.0011 max mem: 33300 +Test: [13700/21770] eta: 0:05:13 time: 0.0386 data: 0.0011 max mem: 33300 +Test: [13800/21770] eta: 0:05:10 time: 0.0387 data: 0.0011 max mem: 33300 +Test: [13900/21770] eta: 0:05:06 time: 0.0392 data: 0.0011 max mem: 33300 +Test: [14000/21770] eta: 0:05:02 time: 0.0394 data: 0.0012 max mem: 33300 +Test: [14100/21770] eta: 0:04:58 time: 0.0385 data: 0.0011 max mem: 33300 +Test: [14200/21770] eta: 0:04:54 time: 0.0385 data: 0.0011 max mem: 33300 +Test: [14300/21770] eta: 0:04:50 time: 0.0385 data: 0.0011 max mem: 33300 +Test: [14400/21770] eta: 0:04:46 time: 0.0385 data: 0.0011 max mem: 33300 +Test: [14500/21770] eta: 0:04:42 time: 0.0384 data: 0.0011 max mem: 33300 +Test: [14600/21770] eta: 0:04:38 time: 0.0390 data: 0.0010 max mem: 33300 +Test: [14700/21770] eta: 0:04:35 time: 0.0402 data: 0.0010 max mem: 33300 +Test: [14800/21770] eta: 0:04:31 time: 0.0400 data: 0.0011 max mem: 33300 +Test: [14900/21770] eta: 0:04:27 time: 0.0398 data: 0.0011 max mem: 33300 +Test: [15000/21770] eta: 0:04:23 time: 0.0400 data: 0.0012 max mem: 33300 +Test: [15100/21770] eta: 0:04:19 time: 0.0391 data: 0.0011 max mem: 33300 +Test: [15200/21770] eta: 0:04:15 time: 0.0395 data: 0.0012 max mem: 33300 +Test: [15300/21770] eta: 0:04:11 time: 0.0394 data: 0.0012 max mem: 33300 +Test: [15400/21770] eta: 0:04:08 time: 0.0398 data: 0.0012 max mem: 33300 +Test: [15500/21770] eta: 0:04:04 time: 0.0399 data: 0.0012 max mem: 33300 +Test: [15600/21770] eta: 0:04:00 time: 0.0399 data: 0.0012 max mem: 33300 +Test: [15700/21770] eta: 0:03:56 time: 0.0401 data: 0.0012 max mem: 33300 +Test: [15800/21770] eta: 0:03:52 time: 0.0399 data: 0.0012 max mem: 33300 +Test: [15900/21770] eta: 0:03:48 time: 0.0393 data: 0.0012 max mem: 33300 +Test: [16000/21770] eta: 0:03:44 time: 0.0387 data: 0.0012 max mem: 33300 +Test: [16100/21770] eta: 0:03:40 time: 0.0386 data: 0.0012 max mem: 33300 +Test: [16200/21770] eta: 0:03:37 time: 0.0385 data: 0.0011 max mem: 33300 +Test: [16300/21770] eta: 0:03:33 time: 0.0389 data: 0.0011 max mem: 33300 +Test: [16400/21770] eta: 0:03:29 time: 0.0388 data: 0.0012 max mem: 33300 +Test: [16500/21770] eta: 0:03:25 time: 0.0388 data: 0.0011 max mem: 33300 +Test: [16600/21770] eta: 0:03:21 time: 0.0389 data: 0.0012 max mem: 33300 +Test: [16700/21770] eta: 0:03:17 time: 0.0386 data: 0.0012 max mem: 33300 +Test: [16800/21770] eta: 0:03:13 time: 0.0387 data: 0.0012 max mem: 33300 +Test: [16900/21770] eta: 0:03:09 time: 0.0389 data: 0.0012 max mem: 33300 +Test: [17000/21770] eta: 0:03:05 time: 0.0390 data: 0.0012 max mem: 33300 +Test: [17100/21770] eta: 0:03:01 time: 0.0387 data: 0.0012 max mem: 33300 +Test: [17200/21770] eta: 0:02:58 time: 0.0391 data: 0.0011 max mem: 33300 +Test: [17300/21770] eta: 0:02:54 time: 0.0389 data: 0.0011 max mem: 33300 +Test: [17400/21770] eta: 0:02:50 time: 0.0388 data: 0.0011 max mem: 33300 +Test: [17500/21770] eta: 0:02:46 time: 0.0388 data: 0.0011 max mem: 33300 +Test: [17600/21770] eta: 0:02:42 time: 0.0385 data: 0.0011 max mem: 33300 +Test: [17700/21770] eta: 0:02:38 time: 0.0384 data: 0.0012 max mem: 33300 +Test: [17800/21770] eta: 0:02:34 time: 0.0385 data: 0.0011 max mem: 33300 +Test: [17900/21770] eta: 0:02:30 time: 0.0383 data: 0.0011 max mem: 33300 +Test: [18000/21770] eta: 0:02:26 time: 0.0382 data: 0.0010 max mem: 33300 +Test: [18100/21770] eta: 0:02:22 time: 0.0390 data: 0.0011 max mem: 33300 +Test: [18200/21770] eta: 0:02:19 time: 0.0399 data: 0.0012 max mem: 33300 +Test: [18300/21770] eta: 0:02:15 time: 0.0386 data: 0.0012 max mem: 33300 +Test: [18400/21770] eta: 0:02:11 time: 0.0387 data: 0.0012 max mem: 33300 +Test: [18500/21770] eta: 0:02:07 time: 0.0389 data: 0.0012 max mem: 33300 +Test: [18600/21770] eta: 0:02:03 time: 0.0388 data: 0.0012 max mem: 33300 +Test: [18700/21770] eta: 0:01:59 time: 0.0387 data: 0.0011 max mem: 33300 +Test: [18800/21770] eta: 0:01:55 time: 0.0383 data: 0.0011 max mem: 33300 +Test: [18900/21770] eta: 0:01:51 time: 0.0384 data: 0.0011 max mem: 33300 +Test: [19000/21770] eta: 0:01:47 time: 0.0386 data: 0.0011 max mem: 33300 +Test: [19100/21770] eta: 0:01:43 time: 0.0388 data: 0.0011 max mem: 33300 +Test: [19200/21770] eta: 0:01:40 time: 0.0384 data: 0.0011 max mem: 33300 +Test: [19300/21770] eta: 0:01:36 time: 0.0386 data: 0.0011 max mem: 33300 +Test: [19400/21770] eta: 0:01:32 time: 0.0386 data: 0.0011 max mem: 33300 +Test: [19500/21770] eta: 0:01:28 time: 0.0388 data: 0.0011 max mem: 33300 +Test: [19600/21770] eta: 0:01:24 time: 0.0386 data: 0.0011 max mem: 33300 +Test: [19700/21770] eta: 0:01:20 time: 0.0386 data: 0.0011 max mem: 33300 +Test: [19800/21770] eta: 0:01:16 time: 0.0386 data: 0.0011 max mem: 33300 +Test: [19900/21770] eta: 0:01:12 time: 0.0392 data: 0.0012 max mem: 33300 +Test: [20000/21770] eta: 0:01:08 time: 0.0403 data: 0.0012 max mem: 33300 +Test: [20100/21770] eta: 0:01:05 time: 0.0401 data: 0.0011 max mem: 33300 +Test: [20200/21770] eta: 0:01:01 time: 0.0401 data: 0.0012 max mem: 33300 +Test: [20300/21770] eta: 0:00:57 time: 0.0397 data: 0.0011 max mem: 33300 +Test: [20400/21770] eta: 0:00:53 time: 0.0394 data: 0.0011 max mem: 33300 +Test: [20500/21770] eta: 0:00:49 time: 0.0387 data: 0.0011 max mem: 33300 +Test: [20600/21770] eta: 0:00:45 time: 0.0390 data: 0.0011 max mem: 33300 +Test: [20700/21770] eta: 0:00:41 time: 0.0391 data: 0.0011 max mem: 33300 +Test: [20800/21770] eta: 0:00:37 time: 0.0388 data: 0.0011 max mem: 33300 +Test: [20900/21770] eta: 0:00:33 time: 0.0399 data: 0.0012 max mem: 33300 +Test: [21000/21770] eta: 0:00:29 time: 0.0399 data: 0.0012 max mem: 33300 +Test: [21100/21770] eta: 0:00:26 time: 0.0395 data: 0.0011 max mem: 33300 +Test: [21200/21770] eta: 0:00:22 time: 0.0390 data: 0.0011 max mem: 33300 +Test: [21300/21770] eta: 0:00:18 time: 0.0393 data: 0.0012 max mem: 33300 +Test: [21400/21770] eta: 0:00:14 time: 0.0390 data: 0.0012 max mem: 33300 +Test: [21500/21770] eta: 0:00:10 time: 0.0393 data: 0.0011 max mem: 33300 +Test: [21600/21770] eta: 0:00:06 time: 0.0392 data: 0.0012 max mem: 33300 +Test: [21700/21770] eta: 0:00:02 time: 0.0398 data: 0.0011 max mem: 33300 +Test: Total time: 0:14:08 +Final results: +Mean IoU is 0.00 + + precision@0.5 = 0.00 + precision@0.6 = 0.00 + precision@0.7 = 0.00 + precision@0.8 = 0.00 + precision@0.9 = 0.00 + overall IoU = 0.00 + mean IoU = 0.00 + +Mean accuracy for one-to-zero sample is 100.00 + +Average object IoU 0.0 +Overall IoU 0.0 +Epoch: [7] [ 0/4276] eta: 6:39:41 lr: 4.2050947712996166e-05 loss: 0.1366 (0.1366) time: 5.6084 data: 2.2408 max mem: 33300 +Epoch: [7] [ 10/4276] eta: 3:54:24 lr: 4.2048265635774724e-05 loss: 0.1860 (0.1817) time: 3.2970 data: 0.2112 max mem: 33300 +Epoch: [7] [ 20/4276] eta: 3:45:18 lr: 4.204558353954447e-05 loss: 0.1812 (0.1836) time: 3.0548 data: 0.0078 max mem: 33300 +Epoch: [7] [ 30/4276] eta: 3:40:50 lr: 4.2042901424303916e-05 loss: 0.1666 (0.1839) time: 3.0236 data: 0.0064 max mem: 33300 +Epoch: [7] [ 40/4276] eta: 3:39:45 lr: 4.204021929005158e-05 loss: 0.1686 (0.1811) time: 3.0459 data: 0.0068 max mem: 33300 +Epoch: [7] [ 50/4276] eta: 3:38:13 lr: 4.2037537136785995e-05 loss: 0.1728 (0.1785) time: 3.0636 data: 0.0076 max mem: 33300 +Epoch: [7] [ 60/4276] eta: 3:36:45 lr: 4.203485496450566e-05 loss: 0.1647 (0.1780) time: 3.0275 data: 0.0072 max mem: 33300 +Epoch: [7] [ 70/4276] eta: 3:35:53 lr: 4.20321727732091e-05 loss: 0.1629 (0.1770) time: 3.0326 data: 0.0068 max mem: 33300 +Epoch: [7] [ 80/4276] eta: 3:35:19 lr: 4.2029490562894824e-05 loss: 0.1690 (0.1773) time: 3.0610 data: 0.0069 max mem: 33300 +Epoch: [7] [ 90/4276] eta: 3:34:22 lr: 4.202680833356136e-05 loss: 0.1576 (0.1752) time: 3.0482 data: 0.0072 max mem: 33300 +Epoch: [7] [ 100/4276] eta: 3:34:00 lr: 4.202412608520722e-05 loss: 0.1542 (0.1764) time: 3.0584 data: 0.0073 max mem: 33300 +Epoch: [7] [ 110/4276] eta: 3:33:07 lr: 4.2021443817830905e-05 loss: 0.1619 (0.1779) time: 3.0545 data: 0.0071 max mem: 33300 +Epoch: [7] [ 120/4276] eta: 3:32:44 lr: 4.2018761531430956e-05 loss: 0.1754 (0.1783) time: 3.0529 data: 0.0071 max mem: 33300 +Epoch: [7] [ 130/4276] eta: 3:32:10 lr: 4.2016079226005875e-05 loss: 0.1804 (0.1795) time: 3.0761 data: 0.0075 max mem: 33300 +Epoch: [7] [ 140/4276] eta: 3:31:30 lr: 4.2013396901554184e-05 loss: 0.1780 (0.1790) time: 3.0501 data: 0.0066 max mem: 33300 +Epoch: [7] [ 150/4276] eta: 3:30:59 lr: 4.201071455807439e-05 loss: 0.1737 (0.1784) time: 3.0526 data: 0.0069 max 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+Epoch: [7] [ 790/4276] eta: 2:58:26 lr: 4.18390049288129e-05 loss: 0.1719 (0.1790) time: 3.0673 data: 0.0073 max mem: 33300 +Epoch: [7] [ 800/4276] eta: 2:57:57 lr: 4.1836321345311394e-05 loss: 0.1682 (0.1789) time: 3.0850 data: 0.0074 max mem: 33300 +Epoch: [7] [ 810/4276] eta: 2:57:24 lr: 4.18336377426833e-05 loss: 0.1620 (0.1789) time: 3.0659 data: 0.0071 max mem: 33300 +Epoch: [7] [ 820/4276] eta: 2:56:56 lr: 4.183095412092713e-05 loss: 0.1628 (0.1787) time: 3.0848 data: 0.0073 max mem: 33300 +Epoch: [7] [ 830/4276] eta: 2:56:24 lr: 4.182827048004138e-05 loss: 0.1628 (0.1787) time: 3.0872 data: 0.0072 max mem: 33300 +Epoch: [7] [ 840/4276] eta: 2:55:52 lr: 4.182558682002455e-05 loss: 0.1722 (0.1788) time: 3.0436 data: 0.0074 max mem: 33300 +Epoch: [7] [ 850/4276] eta: 2:55:22 lr: 4.182290314087514e-05 loss: 0.1749 (0.1788) time: 3.0586 data: 0.0076 max mem: 33300 +Epoch: [7] [ 860/4276] eta: 2:54:54 lr: 4.182021944259166e-05 loss: 0.1690 (0.1788) time: 3.1043 data: 0.0073 max mem: 33300 +Epoch: [7] [ 870/4276] eta: 2:54:25 lr: 4.181753572517259e-05 loss: 0.1764 (0.1789) time: 3.1368 data: 0.0079 max mem: 33300 +Epoch: [7] [ 880/4276] eta: 2:53:56 lr: 4.181485198861643e-05 loss: 0.1786 (0.1790) time: 3.1171 data: 0.0077 max mem: 33300 +Epoch: [7] [ 890/4276] eta: 2:53:30 lr: 4.181216823292169e-05 loss: 0.1867 (0.1793) time: 3.1488 data: 0.0083 max mem: 33300 +Epoch: [7] [ 900/4276] eta: 2:53:01 lr: 4.180948445808687e-05 loss: 0.1997 (0.1794) time: 3.1584 data: 0.0088 max mem: 33300 +Epoch: [7] [ 910/4276] eta: 2:52:32 lr: 4.180680066411047e-05 loss: 0.1853 (0.1794) time: 3.1267 data: 0.0080 max mem: 33300 +Epoch: [7] [ 920/4276] eta: 2:52:05 lr: 4.1804116850990975e-05 loss: 0.1835 (0.1796) time: 3.1542 data: 0.0080 max mem: 33300 +Epoch: [7] [ 930/4276] eta: 2:51:35 lr: 4.180143301872689e-05 loss: 0.1826 (0.1796) time: 3.1420 data: 0.0083 max mem: 33300 +Epoch: [7] [ 940/4276] eta: 2:51:08 lr: 4.179874916731671e-05 loss: 0.1693 (0.1794) time: 3.1463 data: 0.0083 max mem: 33300 +Epoch: [7] [ 950/4276] eta: 2:50:39 lr: 4.1796065296758944e-05 loss: 0.1641 (0.1794) time: 3.1551 data: 0.0085 max mem: 33300 +Epoch: [7] [ 960/4276] eta: 2:50:10 lr: 4.179338140705207e-05 loss: 0.1721 (0.1795) time: 3.1270 data: 0.0085 max mem: 33300 +Epoch: [7] [ 970/4276] eta: 2:49:44 lr: 4.179069749819459e-05 loss: 0.1695 (0.1795) time: 3.1657 data: 0.0084 max mem: 33300 +Epoch: [7] [ 980/4276] eta: 2:49:13 lr: 4.1788013570185015e-05 loss: 0.1690 (0.1796) time: 3.1487 data: 0.0084 max mem: 33300 +Epoch: [7] [ 990/4276] eta: 2:48:46 lr: 4.178532962302184e-05 loss: 0.1722 (0.1796) time: 3.1362 data: 0.0083 max mem: 33300 +Epoch: [7] [1000/4276] eta: 2:48:18 lr: 4.178264565670353e-05 loss: 0.1671 (0.1795) time: 3.1785 data: 0.0083 max mem: 33300 +Epoch: [7] [1010/4276] eta: 2:47:46 lr: 4.1779961671228626e-05 loss: 0.1688 (0.1795) time: 3.1057 data: 0.0086 max mem: 33300 +Epoch: [7] [1020/4276] eta: 2:47:17 lr: 4.177727766659559e-05 loss: 0.1755 (0.1794) time: 3.0903 data: 0.0081 max mem: 33300 +Epoch: [7] [1030/4276] eta: 2:46:49 lr: 4.177459364280294e-05 loss: 0.1787 (0.1796) time: 3.1593 data: 0.0077 max mem: 33300 +Epoch: [7] [1040/4276] eta: 2:46:20 lr: 4.177190959984916e-05 loss: 0.1724 (0.1796) time: 3.1566 data: 0.0090 max mem: 33300 +Epoch: [7] [1050/4276] eta: 2:45:51 lr: 4.1769225537732736e-05 loss: 0.1659 (0.1797) time: 3.1422 data: 0.0094 max mem: 33300 +Epoch: [7] [1060/4276] eta: 2:45:23 lr: 4.1766541456452184e-05 loss: 0.1850 (0.1797) time: 3.1640 data: 0.0093 max mem: 33300 +Epoch: [7] [1070/4276] eta: 2:44:55 lr: 4.176385735600599e-05 loss: 0.1714 (0.1797) time: 3.1879 data: 0.0090 max mem: 33300 +Epoch: [7] [1080/4276] eta: 2:44:25 lr: 4.176117323639264e-05 loss: 0.1714 (0.1795) time: 3.1528 data: 0.0087 max mem: 33300 +Epoch: [7] [1090/4276] eta: 2:43:57 lr: 4.175848909761064e-05 loss: 0.1745 (0.1795) time: 3.1422 data: 0.0091 max mem: 33300 +Epoch: [7] [1100/4276] eta: 2:43:29 lr: 4.175580493965848e-05 loss: 0.1729 (0.1796) time: 3.1820 data: 0.0088 max mem: 33300 +Epoch: [7] [1110/4276] eta: 2:42:58 lr: 4.1753120762534655e-05 loss: 0.1761 (0.1796) time: 3.1405 data: 0.0084 max mem: 33300 +Epoch: [7] [1120/4276] eta: 2:42:31 lr: 4.175043656623765e-05 loss: 0.1761 (0.1797) time: 3.1509 data: 0.0087 max mem: 33300 +Epoch: [7] [1130/4276] eta: 2:42:02 lr: 4.174775235076597e-05 loss: 0.1701 (0.1795) time: 3.1899 data: 0.0086 max mem: 33300 +Epoch: [7] [1140/4276] eta: 2:41:30 lr: 4.17450681161181e-05 loss: 0.1590 (0.1793) time: 3.1067 data: 0.0081 max mem: 33300 +Epoch: [7] [1150/4276] eta: 2:41:03 lr: 4.174238386229254e-05 loss: 0.1636 (0.1793) time: 3.1469 data: 0.0089 max mem: 33300 +Epoch: [7] [1160/4276] eta: 2:40:33 lr: 4.1739699589287774e-05 loss: 0.1665 (0.1793) time: 3.1862 data: 0.0097 max mem: 33300 +Epoch: [7] [1170/4276] eta: 2:40:03 lr: 4.173701529710231e-05 loss: 0.1814 (0.1793) time: 3.1173 data: 0.0090 max mem: 33300 +Epoch: [7] [1180/4276] eta: 2:39:36 lr: 4.173433098573462e-05 loss: 0.1809 (0.1792) time: 3.1825 data: 0.0088 max mem: 33300 +Epoch: [7] [1190/4276] eta: 2:39:05 lr: 4.173164665518321e-05 loss: 0.1597 (0.1791) time: 3.1740 data: 0.0091 max mem: 33300 +Epoch: [7] [1200/4276] eta: 2:38:36 lr: 4.172896230544656e-05 loss: 0.1701 (0.1791) time: 3.1278 data: 0.0090 max mem: 33300 +Epoch: [7] [1210/4276] eta: 2:38:08 lr: 4.1726277936523175e-05 loss: 0.1572 (0.1791) time: 3.1953 data: 0.0087 max mem: 33300 +Epoch: [7] [1220/4276] eta: 2:37:37 lr: 4.172359354841155e-05 loss: 0.1644 (0.1790) time: 3.1480 data: 0.0080 max mem: 33300 +Epoch: [7] [1230/4276] eta: 2:37:08 lr: 4.172090914111016e-05 loss: 0.1734 (0.1791) time: 3.1253 data: 0.0084 max mem: 33300 +Epoch: [7] [1240/4276] eta: 2:36:40 lr: 4.17182247146175e-05 loss: 0.1770 (0.1790) time: 3.1977 data: 0.0091 max mem: 33300 +Epoch: [7] [1250/4276] eta: 2:36:09 lr: 4.171554026893206e-05 loss: 0.1732 (0.1790) time: 3.1614 data: 0.0085 max mem: 33300 +Epoch: [7] [1260/4276] eta: 2:35:40 lr: 4.171285580405234e-05 loss: 0.1581 (0.1788) time: 3.1389 data: 0.0082 max mem: 33300 +Epoch: [7] [1270/4276] eta: 2:35:11 lr: 4.1710171319976826e-05 loss: 0.1694 (0.1788) time: 3.1662 data: 0.0083 max mem: 33300 +Epoch: [7] [1280/4276] eta: 2:34:41 lr: 4.1707486816704e-05 loss: 0.1761 (0.1789) time: 3.1637 data: 0.0085 max mem: 33300 +Epoch: [7] [1290/4276] eta: 2:34:11 lr: 4.170480229423236e-05 loss: 0.1794 (0.1790) time: 3.1491 data: 0.0087 max mem: 33300 +Epoch: [7] [1300/4276] eta: 2:33:41 lr: 4.1702117752560396e-05 loss: 0.1789 (0.1789) time: 3.1456 data: 0.0082 max mem: 33300 +Epoch: [7] [1310/4276] eta: 2:33:11 lr: 4.1699433191686584e-05 loss: 0.1569 (0.1788) time: 3.1333 data: 0.0078 max mem: 33300 +Epoch: [7] [1320/4276] eta: 2:32:38 lr: 4.169674861160944e-05 loss: 0.1718 (0.1788) time: 3.0671 data: 0.0076 max mem: 33300 +Epoch: [7] [1330/4276] eta: 2:32:09 lr: 4.1694064012327425e-05 loss: 0.1726 (0.1788) time: 3.1108 data: 0.0084 max mem: 33300 +Epoch: [7] [1340/4276] eta: 2:31:40 lr: 4.169137939383905e-05 loss: 0.1604 (0.1786) time: 3.1772 data: 0.0090 max mem: 33300 +Epoch: [7] [1350/4276] eta: 2:31:08 lr: 4.1688694756142785e-05 loss: 0.1667 (0.1786) time: 3.1140 data: 0.0092 max mem: 33300 +Epoch: [7] [1360/4276] eta: 2:30:40 lr: 4.168601009923712e-05 loss: 0.1760 (0.1787) time: 3.1654 data: 0.0094 max mem: 33300 +Epoch: [7] [1370/4276] eta: 2:30:10 lr: 4.168332542312055e-05 loss: 0.1594 (0.1786) time: 3.1821 data: 0.0086 max mem: 33300 +Epoch: [7] [1380/4276] eta: 2:29:38 lr: 4.168064072779158e-05 loss: 0.1773 (0.1787) time: 3.0942 data: 0.0080 max mem: 33300 +Epoch: [7] [1390/4276] eta: 2:29:08 lr: 4.167795601324866e-05 loss: 0.1870 (0.1788) time: 3.1014 data: 0.0081 max mem: 33300 +Epoch: [7] [1400/4276] eta: 2:28:36 lr: 4.1675271279490296e-05 loss: 0.1956 (0.1788) time: 3.0871 data: 0.0084 max mem: 33300 +Epoch: [7] [1410/4276] eta: 2:28:04 lr: 4.167258652651498e-05 loss: 0.1765 (0.1789) time: 3.0570 data: 0.0083 max mem: 33300 +Epoch: [7] [1420/4276] eta: 2:27:32 lr: 4.16699017543212e-05 loss: 0.1791 (0.1790) time: 3.0667 data: 0.0081 max mem: 33300 +Epoch: [7] [1430/4276] eta: 2:27:00 lr: 4.166721696290743e-05 loss: 0.1641 (0.1790) time: 3.0455 data: 0.0086 max mem: 33300 +Epoch: [7] [1440/4276] eta: 2:26:27 lr: 4.1664532152272165e-05 loss: 0.1747 (0.1791) time: 3.0235 data: 0.0093 max mem: 33300 +Epoch: [7] [1450/4276] eta: 2:25:56 lr: 4.166184732241389e-05 loss: 0.1714 (0.1790) time: 3.0702 data: 0.0087 max mem: 33300 +Epoch: [7] [1460/4276] eta: 2:25:24 lr: 4.165916247333109e-05 loss: 0.1707 (0.1790) time: 3.0588 data: 0.0081 max mem: 33300 +Epoch: [7] [1470/4276] eta: 2:24:52 lr: 4.165647760502225e-05 loss: 0.1735 (0.1790) time: 3.0323 data: 0.0080 max mem: 33300 +Epoch: [7] [1480/4276] eta: 2:24:21 lr: 4.1653792717485854e-05 loss: 0.1719 (0.1789) time: 3.0832 data: 0.0074 max mem: 33300 +Epoch: [7] [1490/4276] eta: 2:23:49 lr: 4.16511078107204e-05 loss: 0.1623 (0.1789) time: 3.0681 data: 0.0078 max mem: 33300 +Epoch: [7] [1500/4276] eta: 2:23:17 lr: 4.164842288472435e-05 loss: 0.1712 (0.1788) time: 3.0359 data: 0.0086 max mem: 33300 +Epoch: [7] [1510/4276] eta: 2:22:46 lr: 4.1645737939496203e-05 loss: 0.1675 (0.1788) time: 3.0785 data: 0.0092 max mem: 33300 +Epoch: [7] [1520/4276] eta: 2:22:14 lr: 4.164305297503444e-05 loss: 0.1691 (0.1789) time: 3.0778 data: 0.0089 max mem: 33300 +Epoch: [7] [1530/4276] eta: 2:21:42 lr: 4.164036799133756e-05 loss: 0.1760 (0.1788) time: 3.0375 data: 0.0085 max mem: 33300 +Epoch: [7] [1540/4276] eta: 2:21:11 lr: 4.163768298840402e-05 loss: 0.1640 (0.1789) time: 3.0611 data: 0.0089 max mem: 33300 +Epoch: [7] [1550/4276] eta: 2:20:39 lr: 4.1634997966232325e-05 loss: 0.1707 (0.1789) time: 3.0501 data: 0.0087 max mem: 33300 +Epoch: [7] [1560/4276] eta: 2:20:06 lr: 4.1632312924820954e-05 loss: 0.1742 (0.1789) time: 3.0037 data: 0.0081 max mem: 33300 +Epoch: [7] [1570/4276] eta: 2:19:35 lr: 4.162962786416838e-05 loss: 0.1678 (0.1789) time: 3.0437 data: 0.0080 max mem: 33300 +Epoch: [7] [1580/4276] eta: 2:19:03 lr: 4.16269427842731e-05 loss: 0.1575 (0.1788) time: 3.0643 data: 0.0088 max mem: 33300 +Epoch: [7] [1590/4276] eta: 2:18:30 lr: 4.162425768513359e-05 loss: 0.1661 (0.1788) time: 3.0172 data: 0.0088 max mem: 33300 +Epoch: [7] [1600/4276] eta: 2:17:59 lr: 4.162157256674833e-05 loss: 0.1755 (0.1787) time: 3.0396 data: 0.0082 max mem: 33300 +Epoch: [7] [1610/4276] eta: 2:17:27 lr: 4.161888742911581e-05 loss: 0.1454 (0.1786) time: 3.0519 data: 0.0083 max mem: 33300 +Epoch: [7] [1620/4276] eta: 2:16:54 lr: 4.161620227223451e-05 loss: 0.1482 (0.1785) time: 2.9860 data: 0.0084 max mem: 33300 +Epoch: [7] [1630/4276] eta: 2:16:21 lr: 4.1613517096102905e-05 loss: 0.1749 (0.1786) time: 2.9486 data: 0.0079 max mem: 33300 +Epoch: [7] [1640/4276] eta: 2:15:47 lr: 4.161083190071949e-05 loss: 0.1825 (0.1786) time: 2.9510 data: 0.0074 max mem: 33300 +Epoch: [7] [1650/4276] eta: 2:15:15 lr: 4.160814668608273e-05 loss: 0.1643 (0.1785) time: 2.9600 data: 0.0077 max mem: 33300 +Epoch: [7] [1660/4276] eta: 2:14:42 lr: 4.160546145219113e-05 loss: 0.1756 (0.1785) time: 2.9641 data: 0.0076 max mem: 33300 +Epoch: [7] [1670/4276] eta: 2:14:09 lr: 4.160277619904314e-05 loss: 0.1838 (0.1785) time: 2.9632 data: 0.0073 max mem: 33300 +Epoch: [7] [1680/4276] eta: 2:13:36 lr: 4.160009092663727e-05 loss: 0.1838 (0.1786) time: 2.9607 data: 0.0072 max mem: 33300 +Epoch: [7] [1690/4276] eta: 2:13:03 lr: 4.1597405634971984e-05 loss: 0.1818 (0.1786) time: 2.9564 data: 0.0073 max mem: 33300 +Epoch: [7] [1700/4276] eta: 2:12:30 lr: 4.159472032404576e-05 loss: 0.1904 (0.1787) time: 2.9567 data: 0.0075 max mem: 33300 +Epoch: [7] [1710/4276] eta: 2:11:57 lr: 4.1592034993857093e-05 loss: 0.1944 (0.1788) time: 2.9610 data: 0.0075 max mem: 33300 +Epoch: [7] [1720/4276] eta: 2:11:25 lr: 4.1589349644404444e-05 loss: 0.1890 (0.1789) time: 2.9598 data: 0.0072 max mem: 33300 +Epoch: [7] [1730/4276] eta: 2:10:52 lr: 4.158666427568631e-05 loss: 0.1795 (0.1789) time: 2.9586 data: 0.0072 max mem: 33300 +Epoch: [7] [1740/4276] eta: 2:10:19 lr: 4.158397888770116e-05 loss: 0.1824 (0.1790) time: 2.9636 data: 0.0074 max mem: 33300 +Epoch: [7] [1750/4276] eta: 2:09:47 lr: 4.1581293480447484e-05 loss: 0.1841 (0.1790) time: 2.9655 data: 0.0075 max mem: 33300 +Epoch: [7] [1760/4276] eta: 2:09:14 lr: 4.1578608053923754e-05 loss: 0.1794 (0.1789) time: 2.9538 data: 0.0082 max mem: 33300 +Epoch: [7] [1770/4276] eta: 2:08:41 lr: 4.1575922608128446e-05 loss: 0.1779 (0.1790) time: 2.9249 data: 0.0088 max mem: 33300 +Epoch: [7] [1780/4276] eta: 2:08:08 lr: 4.157323714306004e-05 loss: 0.1831 (0.1790) time: 2.9116 data: 0.0086 max mem: 33300 +Epoch: [7] [1790/4276] eta: 2:07:35 lr: 4.157055165871702e-05 loss: 0.1657 (0.1790) time: 2.9427 data: 0.0083 max mem: 33300 +Epoch: [7] [1800/4276] eta: 2:07:03 lr: 4.1567866155097864e-05 loss: 0.1677 (0.1790) time: 2.9564 data: 0.0086 max mem: 33300 +Epoch: [7] [1810/4276] eta: 2:06:30 lr: 4.1565180632201036e-05 loss: 0.1913 (0.1791) time: 2.9550 data: 0.0090 max mem: 33300 +Epoch: [7] [1820/4276] eta: 2:05:58 lr: 4.156249509002503e-05 loss: 0.1771 (0.1790) time: 2.9626 data: 0.0083 max mem: 33300 +Epoch: [7] [1830/4276] eta: 2:05:26 lr: 4.155980952856831e-05 loss: 0.1564 (0.1790) time: 2.9722 data: 0.0080 max mem: 33300 +Epoch: [7] [1840/4276] eta: 2:04:54 lr: 4.1557123947829365e-05 loss: 0.1595 (0.1790) time: 2.9749 data: 0.0085 max mem: 33300 +Epoch: [7] [1850/4276] eta: 2:04:21 lr: 4.155443834780667e-05 loss: 0.1606 (0.1790) time: 2.9620 data: 0.0085 max mem: 33300 +Epoch: [7] [1860/4276] eta: 2:03:49 lr: 4.1551752728498695e-05 loss: 0.1760 (0.1790) time: 2.9589 data: 0.0081 max mem: 33300 +Epoch: [7] [1870/4276] eta: 2:03:17 lr: 4.154906708990392e-05 loss: 0.1760 (0.1792) time: 2.9620 data: 0.0080 max mem: 33300 +Epoch: [7] [1880/4276] eta: 2:02:45 lr: 4.1546381432020834e-05 loss: 0.1704 (0.1791) time: 2.9639 data: 0.0077 max mem: 33300 +Epoch: [7] [1890/4276] eta: 2:02:13 lr: 4.1543695754847885e-05 loss: 0.1630 (0.1791) time: 2.9634 data: 0.0075 max mem: 33300 +Epoch: [7] [1900/4276] eta: 2:01:41 lr: 4.154101005838357e-05 loss: 0.1531 (0.1790) time: 2.9651 data: 0.0077 max mem: 33300 +Epoch: [7] [1910/4276] eta: 2:01:09 lr: 4.153832434262635e-05 loss: 0.1637 (0.1790) time: 2.9748 data: 0.0082 max mem: 33300 +Epoch: [7] [1920/4276] eta: 2:00:37 lr: 4.1535638607574734e-05 loss: 0.1722 (0.1789) time: 2.9740 data: 0.0080 max mem: 33300 +Epoch: [7] [1930/4276] eta: 2:00:05 lr: 4.1532952853227156e-05 loss: 0.1661 (0.1790) time: 2.9693 data: 0.0076 max mem: 33300 +Epoch: [7] [1940/4276] eta: 1:59:33 lr: 4.153026707958211e-05 loss: 0.1936 (0.1790) time: 2.9721 data: 0.0075 max mem: 33300 +Epoch: [7] [1950/4276] eta: 1:59:01 lr: 4.152758128663807e-05 loss: 0.1715 (0.1790) time: 2.9665 data: 0.0077 max mem: 33300 +Epoch: [7] [1960/4276] eta: 1:58:28 lr: 4.1524895474393513e-05 loss: 0.1605 (0.1790) time: 2.9473 data: 0.0087 max mem: 33300 +Epoch: [7] [1970/4276] eta: 1:57:57 lr: 4.15222096428469e-05 loss: 0.1644 (0.1789) time: 2.9491 data: 0.0088 max mem: 33300 +Epoch: [7] [1980/4276] eta: 1:57:25 lr: 4.1519523791996715e-05 loss: 0.1560 (0.1788) time: 2.9642 data: 0.0080 max mem: 33300 +Epoch: [7] [1990/4276] eta: 1:56:53 lr: 4.151683792184144e-05 loss: 0.1758 (0.1789) time: 2.9613 data: 0.0077 max mem: 33300 +Epoch: [7] [2000/4276] eta: 1:56:21 lr: 4.151415203237954e-05 loss: 0.1912 (0.1789) time: 2.9610 data: 0.0075 max mem: 33300 +Epoch: [7] [2010/4276] eta: 1:55:49 lr: 4.1511466123609474e-05 loss: 0.1808 (0.1789) time: 2.9638 data: 0.0075 max mem: 33300 +Epoch: [7] [2020/4276] eta: 1:55:17 lr: 4.1508780195529746e-05 loss: 0.1781 (0.1789) time: 2.9583 data: 0.0076 max mem: 33300 +Epoch: [7] [2030/4276] eta: 1:54:45 lr: 4.15060942481388e-05 loss: 0.1723 (0.1788) time: 2.9259 data: 0.0076 max mem: 33300 +Epoch: [7] [2040/4276] eta: 1:54:13 lr: 4.150340828143512e-05 loss: 0.1586 (0.1787) time: 2.9306 data: 0.0074 max mem: 33300 +Epoch: [7] [2050/4276] eta: 1:53:41 lr: 4.150072229541718e-05 loss: 0.1742 (0.1788) time: 2.9600 data: 0.0077 max mem: 33300 +Epoch: [7] [2060/4276] eta: 1:53:09 lr: 4.149803629008346e-05 loss: 0.1773 (0.1788) time: 2.9522 data: 0.0082 max mem: 33300 +Epoch: [7] [2070/4276] eta: 1:52:37 lr: 4.1495350265432417e-05 loss: 0.1714 (0.1787) time: 2.9272 data: 0.0080 max mem: 33300 +Epoch: [7] [2080/4276] eta: 1:52:05 lr: 4.149266422146253e-05 loss: 0.1759 (0.1787) time: 2.9335 data: 0.0076 max mem: 33300 +Epoch: [7] [2090/4276] eta: 1:51:33 lr: 4.148997815817226e-05 loss: 0.1759 (0.1787) time: 2.9622 data: 0.0073 max mem: 33300 +Epoch: [7] [2100/4276] eta: 1:51:02 lr: 4.1487292075560106e-05 loss: 0.1738 (0.1787) time: 2.9739 data: 0.0082 max mem: 33300 +Epoch: [7] [2110/4276] eta: 1:50:30 lr: 4.14846059736245e-05 loss: 0.1577 (0.1786) time: 2.9699 data: 0.0082 max mem: 33300 +Epoch: [7] [2120/4276] eta: 1:49:59 lr: 4.148191985236394e-05 loss: 0.1466 (0.1785) time: 2.9577 data: 0.0076 max mem: 33300 +Epoch: [7] [2130/4276] eta: 1:49:26 lr: 4.1479233711776894e-05 loss: 0.1479 (0.1784) time: 2.9310 data: 0.0079 max mem: 33300 +Epoch: [7] [2140/4276] eta: 1:48:55 lr: 4.147654755186182e-05 loss: 0.1750 (0.1784) time: 2.9245 data: 0.0085 max mem: 33300 +Epoch: [7] [2150/4276] eta: 1:48:23 lr: 4.147386137261721e-05 loss: 0.1747 (0.1784) time: 2.9524 data: 0.0088 max mem: 33300 +Epoch: [7] [2160/4276] eta: 1:47:51 lr: 4.14711751740415e-05 loss: 0.1739 (0.1783) time: 2.9612 data: 0.0081 max mem: 33300 +Epoch: [7] [2170/4276] eta: 1:47:20 lr: 4.1468488956133195e-05 loss: 0.1772 (0.1784) time: 2.9610 data: 0.0080 max mem: 33300 +Epoch: [7] [2180/4276] eta: 1:46:48 lr: 4.1465802718890744e-05 loss: 0.1846 (0.1784) time: 2.9623 data: 0.0083 max mem: 33300 +Epoch: [7] [2190/4276] eta: 1:46:17 lr: 4.1463116462312626e-05 loss: 0.1740 (0.1784) time: 2.9585 data: 0.0080 max mem: 33300 +Epoch: [7] [2200/4276] eta: 1:45:45 lr: 4.1460430186397294e-05 loss: 0.1733 (0.1785) time: 2.9563 data: 0.0083 max mem: 33300 +Epoch: [7] [2210/4276] eta: 1:45:14 lr: 4.145774389114323e-05 loss: 0.1778 (0.1785) time: 2.9578 data: 0.0080 max mem: 33300 +Epoch: [7] [2220/4276] eta: 1:44:42 lr: 4.1455057576548904e-05 loss: 0.1778 (0.1785) time: 2.9300 data: 0.0075 max mem: 33300 +Epoch: [7] [2230/4276] eta: 1:44:10 lr: 4.145237124261278e-05 loss: 0.1736 (0.1784) time: 2.9302 data: 0.0081 max mem: 33300 +Epoch: [7] [2240/4276] eta: 1:43:39 lr: 4.1449684889333326e-05 loss: 0.1609 (0.1783) time: 2.9643 data: 0.0082 max mem: 33300 +Epoch: [7] [2250/4276] eta: 1:43:08 lr: 4.144699851670901e-05 loss: 0.1589 (0.1783) time: 2.9694 data: 0.0083 max mem: 33300 +Epoch: [7] [2260/4276] eta: 1:42:36 lr: 4.1444312124738305e-05 loss: 0.1743 (0.1783) time: 2.9641 data: 0.0085 max mem: 33300 +Epoch: [7] [2270/4276] eta: 1:42:05 lr: 4.144162571341966e-05 loss: 0.1743 (0.1783) time: 2.9625 data: 0.0087 max mem: 33300 +Epoch: [7] [2280/4276] eta: 1:41:34 lr: 4.1438939282751565e-05 loss: 0.1638 (0.1783) time: 2.9629 data: 0.0087 max mem: 33300 +Epoch: [7] [2290/4276] eta: 1:41:03 lr: 4.143625283273247e-05 loss: 0.1719 (0.1783) time: 2.9682 data: 0.0083 max mem: 33300 +Epoch: [7] [2300/4276] eta: 1:40:31 lr: 4.1433566363360854e-05 loss: 0.1644 (0.1782) time: 2.9753 data: 0.0083 max mem: 33300 +Epoch: [7] [2310/4276] eta: 1:40:00 lr: 4.1430879874635175e-05 loss: 0.1596 (0.1782) time: 2.9700 data: 0.0085 max mem: 33300 +Epoch: [7] [2320/4276] eta: 1:39:29 lr: 4.14281933665539e-05 loss: 0.1676 (0.1781) time: 2.9633 data: 0.0081 max mem: 33300 +Epoch: [7] [2330/4276] eta: 1:38:58 lr: 4.142550683911551e-05 loss: 0.1706 (0.1782) time: 2.9620 data: 0.0076 max mem: 33300 +Epoch: [7] [2340/4276] eta: 1:38:26 lr: 4.142282029231844e-05 loss: 0.1706 (0.1782) time: 2.9665 data: 0.0076 max mem: 33300 +Epoch: [7] [2350/4276] eta: 1:37:55 lr: 4.142013372616118e-05 loss: 0.1703 (0.1781) time: 2.9659 data: 0.0075 max mem: 33300 +Epoch: [7] [2360/4276] eta: 1:37:24 lr: 4.141744714064219e-05 loss: 0.1695 (0.1781) time: 2.9589 data: 0.0077 max mem: 33300 +Epoch: [7] [2370/4276] eta: 1:36:53 lr: 4.141476053575992e-05 loss: 0.1699 (0.1781) time: 2.9662 data: 0.0082 max mem: 33300 +Epoch: [7] [2380/4276] eta: 1:36:22 lr: 4.1412073911512865e-05 loss: 0.1788 (0.1781) time: 2.9698 data: 0.0080 max mem: 33300 +Epoch: [7] [2390/4276] eta: 1:35:50 lr: 4.140938726789946e-05 loss: 0.1700 (0.1780) time: 2.9685 data: 0.0075 max mem: 33300 +Epoch: [7] [2400/4276] eta: 1:35:19 lr: 4.140670060491819e-05 loss: 0.1730 (0.1781) time: 2.9693 data: 0.0075 max mem: 33300 +Epoch: [7] [2410/4276] eta: 1:34:48 lr: 4.140401392256751e-05 loss: 0.1625 (0.1780) time: 2.9636 data: 0.0078 max mem: 33300 +Epoch: [7] [2420/4276] eta: 1:34:17 lr: 4.1401327220845884e-05 loss: 0.1517 (0.1779) time: 2.9656 data: 0.0078 max mem: 33300 +Epoch: [7] [2430/4276] eta: 1:33:46 lr: 4.139864049975177e-05 loss: 0.1577 (0.1780) time: 2.9651 data: 0.0074 max mem: 33300 +Epoch: [7] [2440/4276] eta: 1:33:15 lr: 4.139595375928364e-05 loss: 0.1681 (0.1780) time: 2.9656 data: 0.0075 max mem: 33300 +Epoch: [7] [2450/4276] eta: 1:32:44 lr: 4.1393266999439954e-05 loss: 0.1679 (0.1779) time: 2.9708 data: 0.0077 max mem: 33300 +Epoch: [7] [2460/4276] eta: 1:32:13 lr: 4.139058022021918e-05 loss: 0.1727 (0.1779) time: 2.9675 data: 0.0076 max mem: 33300 +Epoch: [7] [2470/4276] eta: 1:31:42 lr: 4.1387893421619775e-05 loss: 0.1727 (0.1779) time: 2.9735 data: 0.0074 max mem: 33300 +Epoch: [7] [2480/4276] eta: 1:31:11 lr: 4.13852066036402e-05 loss: 0.1711 (0.1779) time: 2.9670 data: 0.0076 max mem: 33300 +Epoch: [7] [2490/4276] eta: 1:30:40 lr: 4.1382519766278924e-05 loss: 0.1756 (0.1779) time: 2.9620 data: 0.0079 max mem: 33300 +Epoch: [7] [2500/4276] eta: 1:30:09 lr: 4.13798329095344e-05 loss: 0.1756 (0.1779) time: 2.9709 data: 0.0077 max mem: 33300 +Epoch: [7] [2510/4276] eta: 1:29:38 lr: 4.137714603340509e-05 loss: 0.1760 (0.1779) time: 2.9671 data: 0.0077 max mem: 33300 +Epoch: [7] [2520/4276] eta: 1:29:07 lr: 4.1374459137889465e-05 loss: 0.1610 (0.1778) time: 2.9622 data: 0.0077 max mem: 33300 +Epoch: [7] [2530/4276] eta: 1:28:36 lr: 4.137177222298598e-05 loss: 0.1376 (0.1777) time: 2.9683 data: 0.0075 max mem: 33300 +Epoch: [7] [2540/4276] eta: 1:28:05 lr: 4.1369085288693097e-05 loss: 0.1541 (0.1776) time: 2.9672 data: 0.0076 max mem: 33300 +Epoch: [7] [2550/4276] eta: 1:27:34 lr: 4.136639833500928e-05 loss: 0.1565 (0.1776) time: 2.9613 data: 0.0075 max mem: 33300 +Epoch: [7] [2560/4276] eta: 1:27:03 lr: 4.1363711361932986e-05 loss: 0.1477 (0.1775) time: 2.9698 data: 0.0075 max mem: 33300 +Epoch: [7] [2570/4276] eta: 1:26:31 lr: 4.136102436946268e-05 loss: 0.1348 (0.1775) time: 2.9509 data: 0.0077 max mem: 33300 +Epoch: [7] [2580/4276] eta: 1:26:01 lr: 4.135833735759681e-05 loss: 0.1589 (0.1775) time: 2.9484 data: 0.0083 max mem: 33300 +Epoch: [7] [2590/4276] eta: 1:25:30 lr: 4.135565032633384e-05 loss: 0.1593 (0.1774) time: 2.9660 data: 0.0083 max mem: 33300 +Epoch: [7] [2600/4276] eta: 1:24:59 lr: 4.1352963275672233e-05 loss: 0.1642 (0.1774) time: 2.9691 data: 0.0079 max mem: 33300 +Epoch: [7] [2610/4276] eta: 1:24:28 lr: 4.1350276205610455e-05 loss: 0.1656 (0.1774) time: 2.9695 data: 0.0083 max mem: 33300 +Epoch: [7] [2620/4276] eta: 1:23:57 lr: 4.134758911614696e-05 loss: 0.1747 (0.1774) time: 2.9744 data: 0.0081 max mem: 33300 +Epoch: [7] [2630/4276] eta: 1:23:26 lr: 4.1344902007280204e-05 loss: 0.1636 (0.1774) time: 2.9877 data: 0.0075 max mem: 33300 +Epoch: [7] [2640/4276] eta: 1:22:55 lr: 4.134221487900865e-05 loss: 0.1506 (0.1773) time: 2.9742 data: 0.0074 max mem: 33300 +Epoch: [7] [2650/4276] eta: 1:22:24 lr: 4.1339527731330754e-05 loss: 0.1557 (0.1773) time: 2.9587 data: 0.0082 max mem: 33300 +Epoch: [7] [2660/4276] eta: 1:21:54 lr: 4.133684056424496e-05 loss: 0.1826 (0.1774) time: 2.9736 data: 0.0083 max mem: 33300 +Epoch: [7] [2670/4276] eta: 1:21:23 lr: 4.133415337774976e-05 loss: 0.1764 (0.1774) time: 2.9838 data: 0.0077 max mem: 33300 +Epoch: [7] [2680/4276] eta: 1:20:52 lr: 4.133146617184358e-05 loss: 0.1690 (0.1774) time: 2.9826 data: 0.0077 max mem: 33300 +Epoch: [7] [2690/4276] eta: 1:20:21 lr: 4.132877894652489e-05 loss: 0.1669 (0.1773) time: 2.9799 data: 0.0076 max mem: 33300 +Epoch: [7] [2700/4276] eta: 1:19:51 lr: 4.132609170179215e-05 loss: 0.1571 (0.1773) time: 2.9676 data: 0.0080 max mem: 33300 +Epoch: [7] [2710/4276] eta: 1:19:20 lr: 4.132340443764381e-05 loss: 0.1642 (0.1772) time: 2.9520 data: 0.0087 max mem: 33300 +Epoch: [7] [2720/4276] eta: 1:18:49 lr: 4.132071715407834e-05 loss: 0.1652 (0.1772) time: 2.9543 data: 0.0089 max mem: 33300 +Epoch: [7] [2730/4276] eta: 1:18:18 lr: 4.131802985109418e-05 loss: 0.1649 (0.1772) time: 2.9672 data: 0.0082 max mem: 33300 +Epoch: [7] [2740/4276] eta: 1:17:47 lr: 4.131534252868979e-05 loss: 0.1729 (0.1772) time: 2.9777 data: 0.0077 max mem: 33300 +Epoch: [7] [2750/4276] eta: 1:17:16 lr: 4.131265518686364e-05 loss: 0.1729 (0.1773) time: 2.9744 data: 0.0079 max mem: 33300 +Epoch: [7] [2760/4276] eta: 1:16:46 lr: 4.130996782561416e-05 loss: 0.1635 (0.1773) time: 2.9657 data: 0.0082 max mem: 33300 +Epoch: [7] [2770/4276] eta: 1:16:15 lr: 4.1307280444939836e-05 loss: 0.1523 (0.1772) time: 2.9740 data: 0.0080 max mem: 33300 +Epoch: [7] [2780/4276] eta: 1:15:44 lr: 4.13045930448391e-05 loss: 0.1563 (0.1772) time: 2.9585 data: 0.0083 max mem: 33300 +Epoch: [7] [2790/4276] eta: 1:15:13 lr: 4.130190562531042e-05 loss: 0.1774 (0.1773) time: 2.9610 data: 0.0082 max mem: 33300 +Epoch: [7] [2800/4276] eta: 1:14:43 lr: 4.129921818635224e-05 loss: 0.1728 (0.1772) time: 2.9796 data: 0.0075 max mem: 33300 +Epoch: [7] [2810/4276] eta: 1:14:12 lr: 4.129653072796303e-05 loss: 0.1519 (0.1771) time: 2.9867 data: 0.0074 max mem: 33300 +Epoch: [7] [2820/4276] eta: 1:13:41 lr: 4.129384325014122e-05 loss: 0.1474 (0.1770) time: 2.9820 data: 0.0076 max mem: 33300 +Epoch: [7] [2830/4276] eta: 1:13:11 lr: 4.1291155752885295e-05 loss: 0.1475 (0.1770) time: 2.9724 data: 0.0074 max mem: 33300 +Epoch: [7] [2840/4276] eta: 1:12:40 lr: 4.128846823619369e-05 loss: 0.1581 (0.1769) time: 2.9793 data: 0.0073 max mem: 33300 +Epoch: [7] [2850/4276] eta: 1:12:09 lr: 4.1285780700064866e-05 loss: 0.1844 (0.1771) time: 2.9855 data: 0.0078 max mem: 33300 +Epoch: [7] [2860/4276] eta: 1:11:39 lr: 4.128309314449727e-05 loss: 0.1813 (0.1770) time: 2.9839 data: 0.0077 max mem: 33300 +Epoch: [7] [2870/4276] eta: 1:11:08 lr: 4.1280405569489354e-05 loss: 0.1646 (0.1770) time: 2.9661 data: 0.0073 max mem: 33300 +Epoch: [7] [2880/4276] eta: 1:10:37 lr: 4.127771797503959e-05 loss: 0.1785 (0.1770) time: 2.9723 data: 0.0073 max mem: 33300 +Epoch: [7] [2890/4276] eta: 1:10:07 lr: 4.12750303611464e-05 loss: 0.1788 (0.1771) time: 2.9784 data: 0.0072 max mem: 33300 +Epoch: [7] [2900/4276] eta: 1:09:36 lr: 4.127234272780826e-05 loss: 0.1633 (0.1769) time: 2.9873 data: 0.0070 max mem: 33300 +Epoch: [7] [2910/4276] eta: 1:09:06 lr: 4.126965507502361e-05 loss: 0.1597 (0.1770) time: 3.0219 data: 0.0071 max mem: 33300 +Epoch: [7] [2920/4276] eta: 1:08:36 lr: 4.126696740279091e-05 loss: 0.1608 (0.1770) time: 3.0407 data: 0.0075 max mem: 33300 +Epoch: [7] [2930/4276] eta: 1:08:05 lr: 4.1264279711108615e-05 loss: 0.1539 (0.1769) time: 3.0260 data: 0.0078 max mem: 33300 +Epoch: [7] [2940/4276] eta: 1:07:35 lr: 4.126159199997517e-05 loss: 0.1673 (0.1769) time: 3.0139 data: 0.0076 max mem: 33300 +Epoch: [7] [2950/4276] eta: 1:07:04 lr: 4.125890426938903e-05 loss: 0.1611 (0.1769) time: 3.0260 data: 0.0075 max mem: 33300 +Epoch: [7] [2960/4276] eta: 1:06:34 lr: 4.125621651934863e-05 loss: 0.1698 (0.1769) time: 3.0248 data: 0.0078 max mem: 33300 +Epoch: [7] [2970/4276] eta: 1:06:04 lr: 4.125352874985245e-05 loss: 0.1698 (0.1769) time: 3.0225 data: 0.0082 max mem: 33300 +Epoch: [7] [2980/4276] eta: 1:05:33 lr: 4.125084096089891e-05 loss: 0.1869 (0.1769) time: 3.0219 data: 0.0077 max mem: 33300 +Epoch: [7] [2990/4276] eta: 1:05:03 lr: 4.124815315248649e-05 loss: 0.1673 (0.1769) time: 3.0175 data: 0.0077 max mem: 33300 +Epoch: [7] [3000/4276] eta: 1:04:32 lr: 4.124546532461363e-05 loss: 0.1613 (0.1768) time: 3.0223 data: 0.0082 max mem: 33300 +Epoch: [7] [3010/4276] eta: 1:04:02 lr: 4.1242777477278754e-05 loss: 0.1586 (0.1768) time: 3.0208 data: 0.0084 max mem: 33300 +Epoch: [7] [3020/4276] eta: 1:03:31 lr: 4.124008961048035e-05 loss: 0.1550 (0.1768) time: 3.0050 data: 0.0085 max mem: 33300 +Epoch: [7] [3030/4276] eta: 1:03:01 lr: 4.123740172421685e-05 loss: 0.1538 (0.1768) time: 3.0088 data: 0.0084 max mem: 33300 +Epoch: [7] [3040/4276] eta: 1:02:30 lr: 4.12347138184867e-05 loss: 0.1735 (0.1768) time: 3.0175 data: 0.0087 max mem: 33300 +Epoch: [7] [3050/4276] eta: 1:02:00 lr: 4.1232025893288355e-05 loss: 0.1715 (0.1768) time: 3.0230 data: 0.0085 max mem: 33300 +Epoch: [7] [3060/4276] eta: 1:01:30 lr: 4.122933794862026e-05 loss: 0.1501 (0.1767) time: 3.0238 data: 0.0077 max mem: 33300 +Epoch: [7] [3070/4276] eta: 1:00:59 lr: 4.122664998448087e-05 loss: 0.1527 (0.1767) time: 3.0116 data: 0.0078 max mem: 33300 +Epoch: [7] [3080/4276] eta: 1:00:29 lr: 4.1223962000868635e-05 loss: 0.1566 (0.1767) time: 3.0271 data: 0.0084 max mem: 33300 +Epoch: [7] [3090/4276] eta: 0:59:59 lr: 4.122127399778199e-05 loss: 0.1483 (0.1766) time: 3.0296 data: 0.0084 max mem: 33300 +Epoch: [7] [3100/4276] eta: 0:59:28 lr: 4.121858597521939e-05 loss: 0.1638 (0.1766) time: 3.0062 data: 0.0080 max mem: 33300 +Epoch: [7] [3110/4276] eta: 0:58:58 lr: 4.1215897933179286e-05 loss: 0.1633 (0.1765) time: 3.0050 data: 0.0082 max mem: 33300 +Epoch: [7] [3120/4276] eta: 0:58:27 lr: 4.121320987166012e-05 loss: 0.1494 (0.1764) time: 3.0116 data: 0.0078 max mem: 33300 +Epoch: [7] [3130/4276] eta: 0:57:57 lr: 4.121052179066034e-05 loss: 0.1576 (0.1764) time: 3.0116 data: 0.0072 max mem: 33300 +Epoch: [7] [3140/4276] eta: 0:57:26 lr: 4.1207833690178396e-05 loss: 0.1637 (0.1764) time: 2.9855 data: 0.0071 max mem: 33300 +Epoch: [7] [3150/4276] eta: 0:56:56 lr: 4.1205145570212734e-05 loss: 0.1770 (0.1764) time: 2.9764 data: 0.0068 max mem: 33300 +Epoch: [7] [3160/4276] eta: 0:56:25 lr: 4.1202457430761803e-05 loss: 0.1712 (0.1764) time: 2.9973 data: 0.0072 max mem: 33300 +Epoch: [7] [3170/4276] eta: 0:55:55 lr: 4.119976927182404e-05 loss: 0.1712 (0.1765) time: 2.9959 data: 0.0080 max mem: 33300 +Epoch: [7] [3180/4276] eta: 0:55:24 lr: 4.11970810933979e-05 loss: 0.1748 (0.1765) time: 3.0185 data: 0.0079 max mem: 33300 +Epoch: [7] [3190/4276] eta: 0:54:54 lr: 4.1194392895481834e-05 loss: 0.1663 (0.1765) time: 3.0415 data: 0.0072 max mem: 33300 +Epoch: [7] [3200/4276] eta: 0:54:24 lr: 4.119170467807427e-05 loss: 0.1661 (0.1765) time: 3.0253 data: 0.0068 max mem: 33300 +Epoch: [7] [3210/4276] eta: 0:53:53 lr: 4.118901644117365e-05 loss: 0.1669 (0.1765) time: 3.0057 data: 0.0072 max mem: 33300 +Epoch: [7] [3220/4276] eta: 0:53:23 lr: 4.118632818477845e-05 loss: 0.1828 (0.1765) time: 3.0115 data: 0.0077 max mem: 33300 +Epoch: [7] [3230/4276] eta: 0:52:53 lr: 4.118363990888709e-05 loss: 0.1636 (0.1765) time: 3.0411 data: 0.0075 max mem: 33300 +Epoch: [7] [3240/4276] eta: 0:52:22 lr: 4.1180951613498026e-05 loss: 0.1636 (0.1765) time: 3.0574 data: 0.0074 max mem: 33300 +Epoch: [7] [3250/4276] eta: 0:51:52 lr: 4.117826329860969e-05 loss: 0.1779 (0.1765) time: 3.0699 data: 0.0075 max mem: 33300 +Epoch: [7] [3260/4276] eta: 0:51:22 lr: 4.117557496422054e-05 loss: 0.1852 (0.1765) time: 3.0520 data: 0.0076 max mem: 33300 +Epoch: [7] [3270/4276] eta: 0:50:51 lr: 4.117288661032901e-05 loss: 0.1765 (0.1765) time: 3.0248 data: 0.0079 max mem: 33300 +Epoch: [7] [3280/4276] eta: 0:50:21 lr: 4.117019823693354e-05 loss: 0.1765 (0.1766) time: 3.0466 data: 0.0083 max mem: 33300 +Epoch: [7] [3290/4276] eta: 0:49:51 lr: 4.116750984403259e-05 loss: 0.1857 (0.1766) time: 3.0732 data: 0.0085 max mem: 33300 +Epoch: [7] [3300/4276] eta: 0:49:21 lr: 4.116482143162459e-05 loss: 0.1815 (0.1767) time: 3.0462 data: 0.0082 max mem: 33300 +Epoch: [7] [3310/4276] eta: 0:48:50 lr: 4.1162132999707984e-05 loss: 0.1824 (0.1767) time: 3.0053 data: 0.0074 max mem: 33300 +Epoch: [7] [3320/4276] eta: 0:48:20 lr: 4.115944454828122e-05 loss: 0.1839 (0.1767) time: 3.0008 data: 0.0073 max mem: 33300 +Epoch: [7] [3330/4276] eta: 0:47:50 lr: 4.115675607734273e-05 loss: 0.1580 (0.1767) time: 3.0464 data: 0.0081 max mem: 33300 +Epoch: [7] [3340/4276] eta: 0:47:19 lr: 4.115406758689098e-05 loss: 0.1683 (0.1767) time: 3.0812 data: 0.0083 max mem: 33300 +Epoch: [7] [3350/4276] eta: 0:46:49 lr: 4.1151379076924384e-05 loss: 0.1603 (0.1766) time: 3.0828 data: 0.0080 max mem: 33300 +Epoch: [7] [3360/4276] eta: 0:46:19 lr: 4.114869054744139e-05 loss: 0.1516 (0.1766) time: 3.1106 data: 0.0073 max mem: 33300 +Epoch: [7] [3370/4276] eta: 0:45:49 lr: 4.114600199844045e-05 loss: 0.1878 (0.1767) time: 3.0596 data: 0.0062 max mem: 33300 +Epoch: [7] [3380/4276] eta: 0:45:18 lr: 4.114331342992e-05 loss: 0.1769 (0.1767) time: 2.9846 data: 0.0059 max mem: 33300 +Epoch: [7] [3390/4276] eta: 0:44:48 lr: 4.114062484187849e-05 loss: 0.1789 (0.1767) time: 2.9824 data: 0.0063 max mem: 33300 +Epoch: [7] [3400/4276] eta: 0:44:17 lr: 4.113793623431434e-05 loss: 0.1887 (0.1767) time: 2.9884 data: 0.0064 max mem: 33300 +Epoch: [7] [3410/4276] eta: 0:43:47 lr: 4.1135247607226e-05 loss: 0.1858 (0.1768) time: 2.9808 data: 0.0066 max mem: 33300 +Epoch: [7] [3420/4276] eta: 0:43:16 lr: 4.1132558960611925e-05 loss: 0.1847 (0.1768) time: 2.9692 data: 0.0069 max mem: 33300 +Epoch: [7] [3430/4276] eta: 0:42:46 lr: 4.1129870294470535e-05 loss: 0.1825 (0.1768) time: 3.0349 data: 0.0073 max mem: 33300 +Epoch: [7] [3440/4276] eta: 0:42:16 lr: 4.112718160880027e-05 loss: 0.1731 (0.1768) time: 3.0453 data: 0.0073 max mem: 33300 +Epoch: [7] [3450/4276] eta: 0:41:45 lr: 4.112449290359959e-05 loss: 0.1647 (0.1768) time: 3.0081 data: 0.0069 max mem: 33300 +Epoch: [7] [3460/4276] eta: 0:41:15 lr: 4.112180417886691e-05 loss: 0.1820 (0.1769) time: 2.9925 data: 0.0069 max mem: 33300 +Epoch: [7] [3470/4276] eta: 0:40:44 lr: 4.111911543460069e-05 loss: 0.1644 (0.1768) time: 2.9886 data: 0.0070 max mem: 33300 +Epoch: [7] [3480/4276] eta: 0:40:14 lr: 4.1116426670799356e-05 loss: 0.1681 (0.1768) time: 3.0467 data: 0.0076 max mem: 33300 +Epoch: [7] [3490/4276] eta: 0:39:44 lr: 4.111373788746135e-05 loss: 0.1834 (0.1768) time: 3.0502 data: 0.0078 max mem: 33300 +Epoch: [7] [3500/4276] eta: 0:39:13 lr: 4.111104908458511e-05 loss: 0.1695 (0.1768) time: 3.0348 data: 0.0072 max mem: 33300 +Epoch: [7] [3510/4276] eta: 0:38:43 lr: 4.1108360262169076e-05 loss: 0.1624 (0.1768) time: 3.0575 data: 0.0070 max mem: 33300 +Epoch: [7] [3520/4276] eta: 0:38:13 lr: 4.1105671420211686e-05 loss: 0.1775 (0.1768) time: 3.0580 data: 0.0067 max mem: 33300 +Epoch: [7] [3530/4276] eta: 0:37:43 lr: 4.110298255871137e-05 loss: 0.1757 (0.1768) time: 3.0518 data: 0.0060 max mem: 33300 +Epoch: [7] [3540/4276] eta: 0:37:12 lr: 4.110029367766657e-05 loss: 0.1757 (0.1769) time: 3.0499 data: 0.0060 max mem: 33300 +Epoch: [7] [3550/4276] eta: 0:36:42 lr: 4.109760477707573e-05 loss: 0.1765 (0.1768) time: 2.9984 data: 0.0064 max mem: 33300 +Epoch: [7] [3560/4276] eta: 0:36:11 lr: 4.109491585693728e-05 loss: 0.1690 (0.1768) time: 2.9697 data: 0.0067 max mem: 33300 +Epoch: [7] [3570/4276] eta: 0:35:41 lr: 4.1092226917249665e-05 loss: 0.1761 (0.1769) time: 3.0113 data: 0.0075 max mem: 33300 +Epoch: [7] [3580/4276] eta: 0:35:11 lr: 4.108953795801131e-05 loss: 0.1592 (0.1768) time: 3.0036 data: 0.0075 max mem: 33300 +Epoch: [7] [3590/4276] eta: 0:34:40 lr: 4.108684897922065e-05 loss: 0.1506 (0.1768) time: 2.9881 data: 0.0067 max mem: 33300 +Epoch: [7] [3600/4276] eta: 0:34:10 lr: 4.108415998087613e-05 loss: 0.1764 (0.1768) time: 3.0180 data: 0.0072 max mem: 33300 +Epoch: [7] [3610/4276] eta: 0:33:39 lr: 4.108147096297619e-05 loss: 0.1740 (0.1768) time: 3.0004 data: 0.0074 max mem: 33300 +Epoch: [7] [3620/4276] eta: 0:33:09 lr: 4.107878192551925e-05 loss: 0.1724 (0.1768) time: 2.9906 data: 0.0075 max mem: 33300 +Epoch: [7] 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+Epoch: [7] [3710/4276] eta: 0:28:36 lr: 4.1054579708083935e-05 loss: 0.1635 (0.1767) time: 3.0482 data: 0.0081 max mem: 33300 +Epoch: [7] [3720/4276] eta: 0:28:06 lr: 4.1051890474970986e-05 loss: 0.1541 (0.1767) time: 3.0532 data: 0.0079 max mem: 33300 +Epoch: [7] [3730/4276] eta: 0:27:36 lr: 4.1049201222283817e-05 loss: 0.1667 (0.1767) time: 3.0319 data: 0.0075 max mem: 33300 +Epoch: [7] [3740/4276] eta: 0:27:05 lr: 4.104651195002086e-05 loss: 0.1775 (0.1767) time: 3.0661 data: 0.0076 max mem: 33300 +Epoch: [7] [3750/4276] eta: 0:26:35 lr: 4.104382265818056e-05 loss: 0.1601 (0.1767) time: 3.0541 data: 0.0078 max mem: 33300 +Epoch: [7] [3760/4276] eta: 0:26:05 lr: 4.104113334676133e-05 loss: 0.1601 (0.1767) time: 2.9819 data: 0.0086 max mem: 33300 +Epoch: [7] [3770/4276] eta: 0:25:34 lr: 4.103844401576162e-05 loss: 0.1803 (0.1767) time: 3.0107 data: 0.0087 max mem: 33300 +Epoch: [7] [3780/4276] eta: 0:25:04 lr: 4.103575466517985e-05 loss: 0.1820 (0.1767) time: 3.0324 data: 0.0084 max mem: 33300 +Epoch: [7] [3790/4276] eta: 0:24:34 lr: 4.103306529501446e-05 loss: 0.1683 (0.1767) time: 3.0291 data: 0.0086 max mem: 33300 +Epoch: [7] [3800/4276] eta: 0:24:03 lr: 4.103037590526388e-05 loss: 0.1734 (0.1767) time: 3.0710 data: 0.0083 max mem: 33300 +Epoch: [7] [3810/4276] eta: 0:23:33 lr: 4.102768649592653e-05 loss: 0.1734 (0.1767) time: 3.0419 data: 0.0085 max mem: 33300 +Epoch: [7] [3820/4276] eta: 0:23:03 lr: 4.1024997067000855e-05 loss: 0.1523 (0.1766) time: 3.0234 data: 0.0087 max mem: 33300 +Epoch: [7] [3830/4276] eta: 0:22:32 lr: 4.102230761848527e-05 loss: 0.1563 (0.1766) time: 3.0780 data: 0.0088 max mem: 33300 +Epoch: [7] [3840/4276] eta: 0:22:02 lr: 4.101961815037822e-05 loss: 0.1659 (0.1766) time: 3.0963 data: 0.0088 max mem: 33300 +Epoch: [7] [3850/4276] eta: 0:21:32 lr: 4.101692866267814e-05 loss: 0.1521 (0.1765) time: 3.0658 data: 0.0081 max mem: 33300 +Epoch: [7] [3860/4276] eta: 0:21:01 lr: 4.1014239155383435e-05 loss: 0.1613 (0.1765) time: 3.0520 data: 0.0073 max mem: 33300 +Epoch: [7] [3870/4276] eta: 0:20:31 lr: 4.101154962849255e-05 loss: 0.1822 (0.1765) time: 3.0291 data: 0.0074 max mem: 33300 +Epoch: [7] [3880/4276] eta: 0:20:01 lr: 4.100886008200392e-05 loss: 0.1729 (0.1765) time: 3.0239 data: 0.0081 max mem: 33300 +Epoch: [7] [3890/4276] eta: 0:19:30 lr: 4.100617051591596e-05 loss: 0.1613 (0.1765) time: 3.0455 data: 0.0082 max mem: 33300 +Epoch: [7] [3900/4276] eta: 0:19:00 lr: 4.1003480930227114e-05 loss: 0.1688 (0.1765) time: 3.0037 data: 0.0083 max mem: 33300 +Epoch: [7] [3910/4276] eta: 0:18:30 lr: 4.100079132493579e-05 loss: 0.1608 (0.1764) time: 2.9806 data: 0.0078 max mem: 33300 +Epoch: [7] [3920/4276] eta: 0:17:59 lr: 4.0998101700040434e-05 loss: 0.1487 (0.1764) time: 2.9924 data: 0.0078 max mem: 33300 +Epoch: [7] [3930/4276] eta: 0:17:29 lr: 4.099541205553948e-05 loss: 0.1727 (0.1764) time: 2.9628 data: 0.0075 max mem: 33300 +Epoch: [7] [3940/4276] eta: 0:16:59 lr: 4.099272239143133e-05 loss: 0.1727 (0.1765) time: 2.9734 data: 0.0068 max mem: 33300 +Epoch: [7] [3950/4276] eta: 0:16:28 lr: 4.099003270771443e-05 loss: 0.1654 (0.1764) time: 3.0316 data: 0.0076 max mem: 33300 +Epoch: [7] [3960/4276] eta: 0:15:58 lr: 4.098734300438721e-05 loss: 0.1654 (0.1764) time: 3.0018 data: 0.0078 max mem: 33300 +Epoch: [7] [3970/4276] eta: 0:15:27 lr: 4.098465328144808e-05 loss: 0.1802 (0.1764) time: 2.9690 data: 0.0075 max mem: 33300 +Epoch: [7] [3980/4276] eta: 0:14:57 lr: 4.098196353889549e-05 loss: 0.1684 (0.1764) time: 3.0058 data: 0.0080 max mem: 33300 +Epoch: [7] [3990/4276] eta: 0:14:27 lr: 4.0979273776727846e-05 loss: 0.1661 (0.1764) time: 2.9894 data: 0.0085 max mem: 33300 +Epoch: [7] [4000/4276] eta: 0:13:56 lr: 4.097658399494358e-05 loss: 0.1565 (0.1764) time: 2.9709 data: 0.0083 max mem: 33300 +Epoch: [7] [4010/4276] eta: 0:13:26 lr: 4.097389419354113e-05 loss: 0.1597 (0.1764) time: 2.9930 data: 0.0081 max mem: 33300 +Epoch: [7] [4020/4276] eta: 0:12:56 lr: 4.0971204372518906e-05 loss: 0.1602 (0.1764) time: 3.0294 data: 0.0082 max mem: 33300 +Epoch: [7] [4030/4276] eta: 0:12:25 lr: 4.096851453187534e-05 loss: 0.1785 (0.1764) time: 3.0404 data: 0.0086 max mem: 33300 +Epoch: [7] [4040/4276] eta: 0:11:55 lr: 4.096582467160887e-05 loss: 0.1808 (0.1765) time: 3.0327 data: 0.0087 max mem: 33300 +Epoch: [7] [4050/4276] eta: 0:11:25 lr: 4.09631347917179e-05 loss: 0.1689 (0.1764) time: 3.0544 data: 0.0087 max mem: 33300 +Epoch: [7] [4060/4276] eta: 0:10:55 lr: 4.096044489220086e-05 loss: 0.1651 (0.1765) time: 3.0639 data: 0.0085 max mem: 33300 +Epoch: [7] [4070/4276] eta: 0:10:24 lr: 4.0957754973056187e-05 loss: 0.1724 (0.1765) time: 3.0583 data: 0.0084 max mem: 33300 +Epoch: [7] [4080/4276] eta: 0:09:54 lr: 4.095506503428229e-05 loss: 0.1721 (0.1765) time: 3.0463 data: 0.0082 max mem: 33300 +Epoch: [7] [4090/4276] eta: 0:09:24 lr: 4.095237507587761e-05 loss: 0.1734 (0.1765) time: 3.0225 data: 0.0074 max mem: 33300 +Epoch: [7] [4100/4276] eta: 0:08:53 lr: 4.0949685097840556e-05 loss: 0.1895 (0.1765) time: 3.0088 data: 0.0077 max mem: 33300 +Epoch: [7] [4110/4276] eta: 0:08:23 lr: 4.094699510016955e-05 loss: 0.1756 (0.1765) time: 3.0331 data: 0.0082 max mem: 33300 +Epoch: [7] [4120/4276] eta: 0:07:53 lr: 4.094430508286304e-05 loss: 0.1756 (0.1765) time: 3.0453 data: 0.0087 max mem: 33300 +Epoch: [7] [4130/4276] eta: 0:07:22 lr: 4.094161504591942e-05 loss: 0.1604 (0.1765) time: 3.0297 data: 0.0087 max mem: 33300 +Epoch: [7] [4140/4276] eta: 0:06:52 lr: 4.0938924989337126e-05 loss: 0.1585 (0.1765) time: 3.0360 data: 0.0078 max mem: 33300 +Epoch: [7] [4150/4276] eta: 0:06:22 lr: 4.093623491311458e-05 loss: 0.1675 (0.1765) time: 3.0601 data: 0.0080 max mem: 33300 +Epoch: [7] [4160/4276] eta: 0:05:51 lr: 4.093354481725021e-05 loss: 0.1713 (0.1765) time: 3.0714 data: 0.0084 max mem: 33300 +Epoch: [7] [4170/4276] eta: 0:05:21 lr: 4.093085470174243e-05 loss: 0.1818 (0.1766) time: 3.0524 data: 0.0085 max mem: 33300 +Epoch: [7] [4180/4276] eta: 0:04:51 lr: 4.092816456658966e-05 loss: 0.1818 (0.1765) time: 3.0299 data: 0.0084 max mem: 33300 +Epoch: [7] [4190/4276] eta: 0:04:20 lr: 4.0925474411790334e-05 loss: 0.1610 (0.1765) time: 3.0101 data: 0.0081 max mem: 33300 +Epoch: [7] [4200/4276] eta: 0:03:50 lr: 4.092278423734286e-05 loss: 0.1939 (0.1766) time: 3.0370 data: 0.0086 max mem: 33300 +Epoch: [7] [4210/4276] eta: 0:03:20 lr: 4.0920094043245665e-05 loss: 0.2026 (0.1766) time: 3.0527 data: 0.0087 max mem: 33300 +Epoch: [7] [4220/4276] eta: 0:02:49 lr: 4.0917403829497174e-05 loss: 0.1941 (0.1767) time: 3.0399 data: 0.0085 max mem: 33300 +Epoch: [7] [4230/4276] eta: 0:02:19 lr: 4.09147135960958e-05 loss: 0.1891 (0.1767) time: 3.0330 data: 0.0082 max mem: 33300 +Epoch: [7] [4240/4276] eta: 0:01:49 lr: 4.091202334303998e-05 loss: 0.1881 (0.1767) time: 3.0263 data: 0.0083 max mem: 33300 +Epoch: [7] [4250/4276] eta: 0:01:18 lr: 4.090933307032812e-05 loss: 0.1836 (0.1768) time: 3.0625 data: 0.0078 max mem: 33300 +Epoch: [7] [4260/4276] eta: 0:00:48 lr: 4.090664277795863e-05 loss: 0.1848 (0.1768) time: 3.0738 data: 0.0084 max mem: 33300 +Epoch: [7] [4270/4276] eta: 0:00:18 lr: 4.0903952465929956e-05 loss: 0.1813 (0.1768) time: 3.0573 data: 0.0083 max mem: 33300 +Epoch: [7] Total time: 3:36:09 +Test: [ 0/21770] eta: 8:20:02 time: 1.3782 data: 1.3340 max mem: 33300 +Test: [ 100/21770] eta: 0:18:36 time: 0.0385 data: 0.0011 max mem: 33300 +Test: [ 200/21770] eta: 0:16:15 time: 0.0392 data: 0.0011 max mem: 33300 +Test: [ 300/21770] eta: 0:15:27 time: 0.0390 data: 0.0011 max mem: 33300 +Test: [ 400/21770] eta: 0:15:03 time: 0.0392 data: 0.0012 max mem: 33300 +Test: [ 500/21770] eta: 0:14:48 time: 0.0398 data: 0.0012 max mem: 33300 +Test: [ 600/21770] eta: 0:14:34 time: 0.0393 data: 0.0011 max mem: 33300 +Test: [ 700/21770] eta: 0:14:23 time: 0.0388 data: 0.0011 max mem: 33300 +Test: [ 800/21770] eta: 0:14:13 time: 0.0388 data: 0.0011 max mem: 33300 +Test: [ 900/21770] eta: 0:14:04 time: 0.0385 data: 0.0011 max mem: 33300 +Test: 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0:12:51 time: 0.0387 data: 0.0011 max mem: 33300 +Test: [ 2400/21770] eta: 0:12:47 time: 0.0394 data: 0.0011 max mem: 33300 +Test: [ 2500/21770] eta: 0:12:43 time: 0.0395 data: 0.0012 max mem: 33300 +Test: [ 2600/21770] eta: 0:12:39 time: 0.0395 data: 0.0012 max mem: 33300 +Test: [ 2700/21770] eta: 0:12:34 time: 0.0393 data: 0.0011 max mem: 33300 +Test: [ 2800/21770] eta: 0:12:30 time: 0.0392 data: 0.0011 max mem: 33300 +Test: [ 2900/21770] eta: 0:12:26 time: 0.0395 data: 0.0012 max mem: 33300 +Test: [ 3000/21770] eta: 0:12:22 time: 0.0390 data: 0.0011 max mem: 33300 +Test: [ 3100/21770] eta: 0:12:17 time: 0.0388 data: 0.0011 max mem: 33300 +Test: [ 3200/21770] eta: 0:12:13 time: 0.0393 data: 0.0011 max mem: 33300 +Test: [ 3300/21770] eta: 0:12:09 time: 0.0389 data: 0.0011 max mem: 33300 +Test: [ 3400/21770] eta: 0:12:05 time: 0.0391 data: 0.0011 max mem: 33300 +Test: [ 3500/21770] eta: 0:12:00 time: 0.0386 data: 0.0011 max mem: 33300 +Test: [ 3600/21770] eta: 0:11:56 time: 0.0387 data: 0.0011 max mem: 33300 +Test: [ 3700/21770] eta: 0:11:52 time: 0.0387 data: 0.0011 max mem: 33300 +Test: [ 3800/21770] eta: 0:11:47 time: 0.0387 data: 0.0011 max mem: 33300 +Test: [ 3900/21770] eta: 0:11:43 time: 0.0386 data: 0.0011 max mem: 33300 +Test: [ 4000/21770] eta: 0:11:39 time: 0.0387 data: 0.0011 max mem: 33300 +Test: [ 4100/21770] eta: 0:11:34 time: 0.0387 data: 0.0011 max mem: 33300 +Test: [ 4200/21770] eta: 0:11:30 time: 0.0388 data: 0.0011 max mem: 33300 +Test: [ 4300/21770] eta: 0:11:26 time: 0.0389 data: 0.0011 max mem: 33300 +Test: [ 4400/21770] eta: 0:11:22 time: 0.0392 data: 0.0011 max mem: 33300 +Test: [ 4500/21770] eta: 0:11:18 time: 0.0392 data: 0.0011 max mem: 33300 +Test: [ 4600/21770] eta: 0:11:14 time: 0.0399 data: 0.0011 max mem: 33300 +Test: [ 4700/21770] eta: 0:11:11 time: 0.0400 data: 0.0011 max mem: 33300 +Test: [ 4800/21770] eta: 0:11:07 time: 0.0398 data: 0.0011 max mem: 33300 +Test: [ 4900/21770] eta: 0:11:03 time: 0.0399 data: 0.0011 max mem: 33300 +Test: [ 5000/21770] eta: 0:10:59 time: 0.0388 data: 0.0010 max mem: 33300 +Test: [ 5100/21770] eta: 0:10:55 time: 0.0392 data: 0.0012 max mem: 33300 +Test: [ 5200/21770] eta: 0:10:51 time: 0.0399 data: 0.0012 max mem: 33300 +Test: [ 5300/21770] eta: 0:10:47 time: 0.0387 data: 0.0011 max mem: 33300 +Test: [ 5400/21770] eta: 0:10:43 time: 0.0391 data: 0.0011 max mem: 33300 +Test: [ 5500/21770] eta: 0:10:39 time: 0.0386 data: 0.0011 max mem: 33300 +Test: [ 5600/21770] eta: 0:10:35 time: 0.0391 data: 0.0011 max mem: 33300 +Test: [ 5700/21770] eta: 0:10:31 time: 0.0391 data: 0.0012 max mem: 33300 +Test: [ 5800/21770] eta: 0:10:27 time: 0.0396 data: 0.0012 max mem: 33300 +Test: [ 5900/21770] eta: 0:10:23 time: 0.0390 data: 0.0012 max mem: 33300 +Test: [ 6000/21770] eta: 0:10:19 time: 0.0396 data: 0.0011 max mem: 33300 +Test: [ 6100/21770] eta: 0:10:16 time: 0.0392 data: 0.0012 max mem: 33300 +Test: [ 6200/21770] eta: 0:10:12 time: 0.0390 data: 0.0012 max mem: 33300 +Test: [ 6300/21770] eta: 0:10:08 time: 0.0392 data: 0.0012 max mem: 33300 +Test: [ 6400/21770] eta: 0:10:04 time: 0.0393 data: 0.0011 max mem: 33300 +Test: [ 6500/21770] eta: 0:10:00 time: 0.0387 data: 0.0011 max mem: 33300 +Test: [ 6600/21770] eta: 0:09:56 time: 0.0393 data: 0.0012 max mem: 33300 +Test: [ 6700/21770] eta: 0:09:52 time: 0.0394 data: 0.0012 max mem: 33300 +Test: [ 6800/21770] eta: 0:09:48 time: 0.0391 data: 0.0011 max mem: 33300 +Test: [ 6900/21770] eta: 0:09:44 time: 0.0391 data: 0.0012 max mem: 33300 +Test: [ 7000/21770] eta: 0:09:40 time: 0.0400 data: 0.0012 max mem: 33300 +Test: [ 7100/21770] eta: 0:09:36 time: 0.0400 data: 0.0012 max mem: 33300 +Test: [ 7200/21770] eta: 0:09:32 time: 0.0397 data: 0.0012 max mem: 33300 +Test: [ 7300/21770] eta: 0:09:29 time: 0.0400 data: 0.0012 max mem: 33300 +Test: [ 7400/21770] eta: 0:09:25 time: 0.0401 data: 0.0012 max mem: 33300 +Test: [ 7500/21770] eta: 0:09:21 time: 0.0392 data: 0.0012 max mem: 33300 +Test: [ 7600/21770] eta: 0:09:17 time: 0.0391 data: 0.0012 max mem: 33300 +Test: [ 7700/21770] eta: 0:09:13 time: 0.0394 data: 0.0011 max mem: 33300 +Test: [ 7800/21770] eta: 0:09:09 time: 0.0399 data: 0.0011 max mem: 33300 +Test: [ 7900/21770] eta: 0:09:05 time: 0.0389 data: 0.0012 max mem: 33300 +Test: [ 8000/21770] eta: 0:09:01 time: 0.0399 data: 0.0011 max mem: 33300 +Test: [ 8100/21770] eta: 0:08:57 time: 0.0399 data: 0.0012 max mem: 33300 +Test: [ 8200/21770] eta: 0:08:54 time: 0.0403 data: 0.0011 max mem: 33300 +Test: [ 8300/21770] eta: 0:08:50 time: 0.0400 data: 0.0011 max mem: 33300 +Test: [ 8400/21770] eta: 0:08:46 time: 0.0399 data: 0.0011 max mem: 33300 +Test: [ 8500/21770] eta: 0:08:42 time: 0.0399 data: 0.0011 max mem: 33300 +Test: [ 8600/21770] eta: 0:08:38 time: 0.0397 data: 0.0011 max mem: 33300 +Test: [ 8700/21770] eta: 0:08:34 time: 0.0390 data: 0.0012 max mem: 33300 +Test: [ 8800/21770] eta: 0:08:30 time: 0.0399 data: 0.0011 max mem: 33300 +Test: [ 8900/21770] eta: 0:08:27 time: 0.0401 data: 0.0011 max mem: 33300 +Test: [ 9000/21770] eta: 0:08:23 time: 0.0397 data: 0.0012 max mem: 33300 +Test: [ 9100/21770] eta: 0:08:19 time: 0.0407 data: 0.0012 max mem: 33300 +Test: [ 9200/21770] eta: 0:08:15 time: 0.0400 data: 0.0012 max mem: 33300 +Test: [ 9300/21770] eta: 0:08:11 time: 0.0401 data: 0.0012 max mem: 33300 +Test: [ 9400/21770] eta: 0:08:07 time: 0.0399 data: 0.0012 max mem: 33300 +Test: [ 9500/21770] eta: 0:08:03 time: 0.0400 data: 0.0012 max mem: 33300 +Test: [ 9600/21770] eta: 0:08:00 time: 0.0398 data: 0.0012 max mem: 33300 +Test: [ 9700/21770] eta: 0:07:56 time: 0.0398 data: 0.0012 max mem: 33300 +Test: [ 9800/21770] eta: 0:07:52 time: 0.0398 data: 0.0012 max mem: 33300 +Test: [ 9900/21770] eta: 0:07:48 time: 0.0400 data: 0.0012 max mem: 33300 +Test: [10000/21770] eta: 0:07:44 time: 0.0399 data: 0.0012 max mem: 33300 +Test: [10100/21770] eta: 0:07:40 time: 0.0403 data: 0.0013 max mem: 33300 +Test: [10200/21770] eta: 0:07:36 time: 0.0399 data: 0.0012 max mem: 33300 +Test: [10300/21770] eta: 0:07:32 time: 0.0399 data: 0.0011 max mem: 33300 +Test: [10400/21770] eta: 0:07:28 time: 0.0398 data: 0.0012 max mem: 33300 +Test: [10500/21770] eta: 0:07:24 time: 0.0400 data: 0.0012 max mem: 33300 +Test: [10600/21770] eta: 0:07:21 time: 0.0400 data: 0.0012 max mem: 33300 +Test: [10700/21770] eta: 0:07:17 time: 0.0399 data: 0.0011 max mem: 33300 +Test: [10800/21770] eta: 0:07:13 time: 0.0398 data: 0.0011 max mem: 33300 +Test: [10900/21770] eta: 0:07:09 time: 0.0394 data: 0.0012 max mem: 33300 +Test: [11000/21770] eta: 0:07:05 time: 0.0393 data: 0.0011 max mem: 33300 +Test: [11100/21770] eta: 0:07:01 time: 0.0400 data: 0.0012 max mem: 33300 +Test: [11200/21770] eta: 0:06:57 time: 0.0398 data: 0.0012 max mem: 33300 +Test: [11300/21770] eta: 0:06:53 time: 0.0397 data: 0.0012 max mem: 33300 +Test: [11400/21770] eta: 0:06:49 time: 0.0402 data: 0.0013 max mem: 33300 +Test: [11500/21770] eta: 0:06:45 time: 0.0400 data: 0.0012 max mem: 33300 +Test: [11600/21770] eta: 0:06:41 time: 0.0399 data: 0.0012 max mem: 33300 +Test: [11700/21770] eta: 0:06:37 time: 0.0399 data: 0.0012 max mem: 33300 +Test: [11800/21770] eta: 0:06:33 time: 0.0399 data: 0.0012 max mem: 33300 +Test: [11900/21770] eta: 0:06:30 time: 0.0401 data: 0.0011 max mem: 33300 +Test: [12000/21770] eta: 0:06:26 time: 0.0400 data: 0.0011 max mem: 33300 +Test: [12100/21770] eta: 0:06:22 time: 0.0398 data: 0.0011 max mem: 33300 +Test: [12200/21770] eta: 0:06:18 time: 0.0395 data: 0.0011 max mem: 33300 +Test: [12300/21770] eta: 0:06:14 time: 0.0397 data: 0.0012 max mem: 33300 +Test: [12400/21770] eta: 0:06:10 time: 0.0400 data: 0.0012 max mem: 33300 +Test: [12500/21770] eta: 0:06:06 time: 0.0398 data: 0.0011 max mem: 33300 +Test: [12600/21770] eta: 0:06:02 time: 0.0400 data: 0.0012 max mem: 33300 +Test: [12700/21770] eta: 0:05:58 time: 0.0395 data: 0.0012 max mem: 33300 +Test: [12800/21770] eta: 0:05:54 time: 0.0401 data: 0.0012 max mem: 33300 +Test: [12900/21770] eta: 0:05:50 time: 0.0399 data: 0.0012 max mem: 33300 +Test: [13000/21770] eta: 0:05:46 time: 0.0399 data: 0.0012 max mem: 33300 +Test: [13100/21770] eta: 0:05:42 time: 0.0399 data: 0.0012 max mem: 33300 +Test: [13200/21770] eta: 0:05:39 time: 0.0401 data: 0.0012 max mem: 33300 +Test: [13300/21770] eta: 0:05:35 time: 0.0400 data: 0.0012 max mem: 33300 +Test: [13400/21770] eta: 0:05:31 time: 0.0400 data: 0.0012 max mem: 33300 +Test: [13500/21770] eta: 0:05:27 time: 0.0401 data: 0.0012 max mem: 33300 +Test: [13600/21770] eta: 0:05:23 time: 0.0402 data: 0.0012 max mem: 33300 +Test: [13700/21770] eta: 0:05:19 time: 0.0400 data: 0.0011 max mem: 33300 +Test: [13800/21770] eta: 0:05:15 time: 0.0400 data: 0.0011 max mem: 33300 +Test: [13900/21770] eta: 0:05:11 time: 0.0400 data: 0.0012 max mem: 33300 +Test: [14000/21770] eta: 0:05:07 time: 0.0400 data: 0.0011 max mem: 33300 +Test: [14100/21770] eta: 0:05:03 time: 0.0399 data: 0.0011 max mem: 33300 +Test: [14200/21770] eta: 0:04:59 time: 0.0399 data: 0.0011 max mem: 33300 +Test: [14300/21770] eta: 0:04:55 time: 0.0399 data: 0.0012 max mem: 33300 +Test: [14400/21770] eta: 0:04:51 time: 0.0391 data: 0.0012 max mem: 33300 +Test: [14500/21770] eta: 0:04:47 time: 0.0391 data: 0.0012 max mem: 33300 +Test: [14600/21770] eta: 0:04:43 time: 0.0393 data: 0.0012 max mem: 33300 +Test: [14700/21770] eta: 0:04:39 time: 0.0402 data: 0.0012 max mem: 33300 +Test: [14800/21770] eta: 0:04:35 time: 0.0399 data: 0.0011 max mem: 33300 +Test: [14900/21770] eta: 0:04:32 time: 0.0402 data: 0.0011 max mem: 33300 +Test: [15000/21770] eta: 0:04:28 time: 0.0402 data: 0.0011 max mem: 33300 +Test: [15100/21770] eta: 0:04:24 time: 0.0399 data: 0.0011 max mem: 33300 +Test: [15200/21770] eta: 0:04:20 time: 0.0401 data: 0.0011 max mem: 33300 +Test: [15300/21770] eta: 0:04:16 time: 0.0397 data: 0.0011 max mem: 33300 +Test: [15400/21770] eta: 0:04:12 time: 0.0399 data: 0.0012 max mem: 33300 +Test: [15500/21770] eta: 0:04:08 time: 0.0401 data: 0.0012 max mem: 33300 +Test: [15600/21770] eta: 0:04:04 time: 0.0401 data: 0.0012 max mem: 33300 +Test: [15700/21770] eta: 0:04:00 time: 0.0400 data: 0.0011 max mem: 33300 +Test: [15800/21770] eta: 0:03:56 time: 0.0408 data: 0.0012 max mem: 33300 +Test: [15900/21770] eta: 0:03:52 time: 0.0394 data: 0.0012 max mem: 33300 +Test: [16000/21770] eta: 0:03:48 time: 0.0393 data: 0.0012 max mem: 33300 +Test: [16100/21770] eta: 0:03:44 time: 0.0392 data: 0.0012 max mem: 33300 +Test: [16200/21770] eta: 0:03:40 time: 0.0392 data: 0.0012 max mem: 33300 +Test: [16300/21770] eta: 0:03:36 time: 0.0401 data: 0.0012 max mem: 33300 +Test: [16400/21770] eta: 0:03:32 time: 0.0401 data: 0.0012 max mem: 33300 +Test: [16500/21770] eta: 0:03:28 time: 0.0401 data: 0.0012 max mem: 33300 +Test: [16600/21770] eta: 0:03:24 time: 0.0401 data: 0.0012 max mem: 33300 +Test: [16700/21770] eta: 0:03:20 time: 0.0402 data: 0.0011 max mem: 33300 +Test: [16800/21770] eta: 0:03:16 time: 0.0399 data: 0.0012 max mem: 33300 +Test: [16900/21770] eta: 0:03:13 time: 0.0398 data: 0.0011 max mem: 33300 +Test: [17000/21770] eta: 0:03:09 time: 0.0401 data: 0.0011 max mem: 33300 +Test: [17100/21770] eta: 0:03:05 time: 0.0399 data: 0.0011 max mem: 33300 +Test: [17200/21770] eta: 0:03:01 time: 0.0400 data: 0.0012 max mem: 33300 +Test: [17300/21770] eta: 0:02:57 time: 0.0402 data: 0.0012 max mem: 33300 +Test: [17400/21770] eta: 0:02:53 time: 0.0401 data: 0.0012 max mem: 33300 +Test: [17500/21770] eta: 0:02:49 time: 0.0394 data: 0.0012 max mem: 33300 +Test: [17600/21770] eta: 0:02:45 time: 0.0391 data: 0.0012 max mem: 33300 +Test: [17700/21770] eta: 0:02:41 time: 0.0395 data: 0.0012 max mem: 33300 +Test: [17800/21770] eta: 0:02:37 time: 0.0392 data: 0.0012 max mem: 33300 +Test: [17900/21770] eta: 0:02:33 time: 0.0391 data: 0.0012 max mem: 33300 +Test: [18000/21770] eta: 0:02:29 time: 0.0391 data: 0.0012 max mem: 33300 +Test: [18100/21770] eta: 0:02:25 time: 0.0393 data: 0.0012 max mem: 33300 +Test: [18200/21770] eta: 0:02:21 time: 0.0394 data: 0.0012 max mem: 33300 +Test: [18300/21770] eta: 0:02:17 time: 0.0392 data: 0.0012 max mem: 33300 +Test: [18400/21770] eta: 0:02:13 time: 0.0391 data: 0.0012 max mem: 33300 +Test: [18500/21770] eta: 0:02:09 time: 0.0391 data: 0.0012 max mem: 33300 +Test: [18600/21770] eta: 0:02:05 time: 0.0390 data: 0.0012 max mem: 33300 +Test: [18700/21770] eta: 0:02:01 time: 0.0392 data: 0.0011 max mem: 33300 +Test: [18800/21770] eta: 0:01:57 time: 0.0401 data: 0.0011 max mem: 33300 +Test: [18900/21770] eta: 0:01:53 time: 0.0399 data: 0.0012 max mem: 33300 +Test: [19000/21770] eta: 0:01:49 time: 0.0392 data: 0.0012 max mem: 33300 +Test: [19100/21770] eta: 0:01:45 time: 0.0392 data: 0.0012 max mem: 33300 +Test: [19200/21770] eta: 0:01:41 time: 0.0392 data: 0.0012 max mem: 33300 +Test: [19300/21770] eta: 0:01:37 time: 0.0392 data: 0.0012 max mem: 33300 +Test: [19400/21770] eta: 0:01:33 time: 0.0392 data: 0.0012 max mem: 33300 +Test: [19500/21770] eta: 0:01:29 time: 0.0392 data: 0.0012 max mem: 33300 +Test: [19600/21770] eta: 0:01:25 time: 0.0399 data: 0.0012 max mem: 33300 +Test: [19700/21770] eta: 0:01:22 time: 0.0400 data: 0.0012 max mem: 33300 +Test: [19800/21770] eta: 0:01:18 time: 0.0400 data: 0.0012 max mem: 33300 +Test: [19900/21770] eta: 0:01:14 time: 0.0400 data: 0.0012 max mem: 33300 +Test: [20000/21770] eta: 0:01:10 time: 0.0406 data: 0.0012 max mem: 33300 +Test: [20100/21770] eta: 0:01:06 time: 0.0407 data: 0.0012 max mem: 33300 +Test: [20200/21770] eta: 0:01:02 time: 0.0405 data: 0.0012 max mem: 33300 +Test: [20300/21770] eta: 0:00:58 time: 0.0402 data: 0.0012 max mem: 33300 +Test: [20400/21770] eta: 0:00:54 time: 0.0395 data: 0.0012 max mem: 33300 +Test: [20500/21770] eta: 0:00:50 time: 0.0404 data: 0.0012 max mem: 33300 +Test: [20600/21770] eta: 0:00:46 time: 0.0398 data: 0.0012 max mem: 33300 +Test: [20700/21770] eta: 0:00:42 time: 0.0397 data: 0.0012 max mem: 33300 +Test: [20800/21770] eta: 0:00:38 time: 0.0401 data: 0.0012 max mem: 33300 +Test: [20900/21770] eta: 0:00:34 time: 0.0401 data: 0.0012 max mem: 33300 +Test: [21000/21770] eta: 0:00:30 time: 0.0402 data: 0.0012 max mem: 33300 +Test: [21100/21770] eta: 0:00:26 time: 0.0396 data: 0.0012 max mem: 33300 +Test: [21200/21770] eta: 0:00:22 time: 0.0393 data: 0.0012 max mem: 33300 +Test: [21300/21770] eta: 0:00:18 time: 0.0391 data: 0.0012 max mem: 33300 +Test: [21400/21770] eta: 0:00:14 time: 0.0395 data: 0.0012 max mem: 33300 +Test: [21500/21770] eta: 0:00:10 time: 0.0392 data: 0.0012 max mem: 33300 +Test: [21600/21770] eta: 0:00:06 time: 0.0399 data: 0.0011 max mem: 33300 +Test: [21700/21770] eta: 0:00:02 time: 0.0399 data: 0.0011 max mem: 33300 +Test: Total time: 0:14:23 +Final results: +Mean IoU is 0.00 + + precision@0.5 = 0.00 + precision@0.6 = 0.00 + precision@0.7 = 0.00 + precision@0.8 = 0.00 + precision@0.9 = 0.00 + overall IoU = 0.00 + mean IoU = 0.00 + +Mean accuracy for one-to-zero sample is 100.00 + +Average object IoU 0.0 +Overall IoU 0.0 +Epoch: [8] [ 0/4276] eta: 6:43:59 lr: 4.090233826927567e-05 loss: 0.1393 (0.1393) time: 5.6687 data: 2.3195 max mem: 33300 +Epoch: [8] [ 10/4276] eta: 3:58:27 lr: 4.089964792578899e-05 loss: 0.1784 (0.1802) time: 3.3538 data: 0.2178 max mem: 33300 +Epoch: [8] [ 20/4276] eta: 3:51:38 lr: 4.0896957562639e-05 loss: 0.1643 (0.1753) time: 3.1454 data: 0.0075 max mem: 33300 +Epoch: [8] [ 30/4276] eta: 3:48:20 lr: 4.089426717982412e-05 loss: 0.1575 (0.1772) time: 3.1569 data: 0.0081 max mem: 33300 +Epoch: [8] [ 40/4276] eta: 3:46:19 lr: 4.089157677734278e-05 loss: 0.1679 (0.1761) time: 3.1430 data: 0.0089 max mem: 33300 +Epoch: [8] [ 50/4276] eta: 3:44:50 lr: 4.0888886355193376e-05 loss: 0.1679 (0.1747) time: 3.1387 data: 0.0089 max mem: 33300 +Epoch: [8] [ 60/4276] eta: 3:43:36 lr: 4.0886195913374344e-05 loss: 0.1649 (0.1740) time: 3.1345 data: 0.0085 max mem: 33300 +Epoch: [8] [ 70/4276] eta: 3:42:45 lr: 4.08835054518841e-05 loss: 0.1672 (0.1730) time: 3.1407 data: 0.0089 max mem: 33300 +Epoch: [8] [ 80/4276] eta: 3:41:33 lr: 4.088081497072106e-05 loss: 0.1701 (0.1731) time: 3.1251 data: 0.0093 max mem: 33300 +Epoch: [8] [ 90/4276] eta: 3:40:40 lr: 4.0878124469883636e-05 loss: 0.1607 (0.1715) time: 3.1108 data: 0.0097 max mem: 33300 +Epoch: [8] [ 100/4276] eta: 3:39:57 lr: 4.087543394937026e-05 loss: 0.1607 (0.1731) time: 3.1278 data: 0.0100 max mem: 33300 +Epoch: [8] [ 110/4276] eta: 3:39:03 lr: 4.0872743409179326e-05 loss: 0.1744 (0.1734) time: 3.1179 data: 0.0092 max mem: 33300 +Epoch: [8] [ 120/4276] eta: 3:38:07 lr: 4.087005284930927e-05 loss: 0.1630 (0.1731) time: 3.0930 data: 0.0083 max mem: 33300 +Epoch: [8] [ 130/4276] eta: 3:37:26 lr: 4.086736226975851e-05 loss: 0.1755 (0.1735) time: 3.1010 data: 0.0080 max mem: 33300 +Epoch: [8] [ 140/4276] eta: 3:36:40 lr: 4.086467167052545e-05 loss: 0.1701 (0.1731) time: 3.1075 data: 0.0084 max mem: 33300 +Epoch: [8] [ 150/4276] eta: 3:35:52 lr: 4.086198105160851e-05 loss: 0.1620 (0.1729) time: 3.0900 data: 0.0092 max mem: 33300 +Epoch: [8] [ 160/4276] eta: 3:35:09 lr: 4.08592904130061e-05 loss: 0.1622 (0.1727) time: 3.0882 data: 0.0088 max mem: 33300 +Epoch: [8] [ 170/4276] eta: 3:34:27 lr: 4.085659975471666e-05 loss: 0.1720 (0.1730) time: 3.0940 data: 0.0082 max mem: 33300 +Epoch: [8] [ 180/4276] eta: 3:33:53 lr: 4.085390907673858e-05 loss: 0.1758 (0.1732) time: 3.1072 data: 0.0094 max mem: 33300 +Epoch: [8] [ 190/4276] eta: 3:33:17 lr: 4.085121837907028e-05 loss: 0.1758 (0.1733) time: 3.1169 data: 0.0100 max mem: 33300 +Epoch: [8] [ 200/4276] eta: 3:32:44 lr: 4.0848527661710176e-05 loss: 0.1801 (0.1747) time: 3.1188 data: 0.0090 max mem: 33300 +Epoch: [8] [ 210/4276] eta: 3:32:05 lr: 4.0845836924656686e-05 loss: 0.1883 (0.1751) time: 3.1059 data: 0.0082 max mem: 33300 +Epoch: [8] [ 220/4276] eta: 3:31:33 lr: 4.084314616790822e-05 loss: 0.1882 (0.1752) time: 3.1066 data: 0.0088 max mem: 33300 +Epoch: [8] [ 230/4276] eta: 3:30:56 lr: 4.084045539146321e-05 loss: 0.1683 (0.1747) time: 3.1138 data: 0.0094 max mem: 33300 +Epoch: [8] [ 240/4276] eta: 3:30:25 lr: 4.0837764595320036e-05 loss: 0.1803 (0.1750) time: 3.1154 data: 0.0091 max mem: 33300 +Epoch: [8] [ 250/4276] eta: 3:29:50 lr: 4.083507377947715e-05 loss: 0.1898 (0.1763) time: 3.1167 data: 0.0082 max mem: 33300 +Epoch: [8] [ 260/4276] eta: 3:29:15 lr: 4.083238294393294e-05 loss: 0.1854 (0.1762) time: 3.1037 data: 0.0082 max mem: 33300 +Epoch: [8] [ 270/4276] eta: 3:28:43 lr: 4.082969208868582e-05 loss: 0.1708 (0.1765) time: 3.1125 data: 0.0086 max mem: 33300 +Epoch: [8] [ 280/4276] eta: 3:28:15 lr: 4.0827001213734205e-05 loss: 0.1758 (0.1766) time: 3.1346 data: 0.0088 max mem: 33300 +Epoch: [8] [ 290/4276] eta: 3:27:46 lr: 4.0824310319076514e-05 loss: 0.1671 (0.1763) time: 3.1449 data: 0.0083 max mem: 33300 +Epoch: [8] [ 300/4276] eta: 3:27:15 lr: 4.082161940471116e-05 loss: 0.1605 (0.1761) time: 3.1371 data: 0.0087 max mem: 33300 +Epoch: [8] [ 310/4276] eta: 3:26:42 lr: 4.081892847063655e-05 loss: 0.1640 (0.1758) time: 3.1211 data: 0.0087 max mem: 33300 +Epoch: [8] [ 320/4276] eta: 3:26:12 lr: 4.0816237516851094e-05 loss: 0.1692 (0.1765) time: 3.1254 data: 0.0076 max mem: 33300 +Epoch: [8] [ 330/4276] eta: 3:25:43 lr: 4.0813546543353215e-05 loss: 0.1746 (0.1765) time: 3.1436 data: 0.0079 max mem: 33300 +Epoch: [8] [ 340/4276] eta: 3:25:14 lr: 4.081085555014131e-05 loss: 0.1638 (0.1760) time: 3.1463 data: 0.0082 max mem: 33300 +Epoch: [8] [ 350/4276] eta: 3:24:40 lr: 4.08081645372138e-05 loss: 0.1519 (0.1755) time: 3.1279 data: 0.0080 max mem: 33300 +Epoch: [8] [ 360/4276] eta: 3:24:08 lr: 4.080547350456909e-05 loss: 0.1754 (0.1761) time: 3.1119 data: 0.0080 max mem: 33300 +Epoch: [8] [ 370/4276] eta: 3:23:37 lr: 4.0802782452205594e-05 loss: 0.1551 (0.1753) time: 3.1256 data: 0.0084 max mem: 33300 +Epoch: [8] [ 380/4276] eta: 3:23:02 lr: 4.080009138012173e-05 loss: 0.1520 (0.1755) time: 3.1147 data: 0.0086 max mem: 33300 +Epoch: [8] [ 390/4276] eta: 3:22:27 lr: 4.0797400288315883e-05 loss: 0.1744 (0.1754) time: 3.0874 data: 0.0083 max mem: 33300 +Epoch: [8] [ 400/4276] eta: 3:21:56 lr: 4.079470917678649e-05 loss: 0.1733 (0.1753) time: 3.1079 data: 0.0081 max mem: 33300 +Epoch: [8] [ 410/4276] eta: 3:21:25 lr: 4.079201804553195e-05 loss: 0.1714 (0.1750) time: 3.1310 data: 0.0079 max mem: 33300 +Epoch: [8] [ 420/4276] eta: 3:20:53 lr: 4.078932689455068e-05 loss: 0.1679 (0.1750) time: 3.1213 data: 0.0072 max mem: 33300 +Epoch: [8] [ 430/4276] eta: 3:20:20 lr: 4.078663572384108e-05 loss: 0.1728 (0.1752) time: 3.1108 data: 0.0068 max mem: 33300 +Epoch: [8] [ 440/4276] eta: 3:19:49 lr: 4.078394453340156e-05 loss: 0.1737 (0.1752) time: 3.1176 data: 0.0069 max mem: 33300 +Epoch: [8] [ 450/4276] eta: 3:19:14 lr: 4.078125332323053e-05 loss: 0.1656 (0.1752) time: 3.1079 data: 0.0072 max mem: 33300 +Epoch: [8] [ 460/4276] eta: 3:18:44 lr: 4.0778562093326394e-05 loss: 0.1574 (0.1746) time: 3.1138 data: 0.0077 max mem: 33300 +Epoch: [8] [ 470/4276] eta: 3:18:15 lr: 4.077587084368757e-05 loss: 0.1541 (0.1743) time: 3.1419 data: 0.0080 max mem: 33300 +Epoch: [8] [ 480/4276] eta: 3:17:40 lr: 4.077317957431246e-05 loss: 0.1565 (0.1742) time: 3.1120 data: 0.0075 max mem: 33300 +Epoch: [8] [ 490/4276] eta: 3:17:07 lr: 4.077048828519948e-05 loss: 0.1521 (0.1740) time: 3.0926 data: 0.0075 max mem: 33300 +Epoch: [8] [ 500/4276] eta: 3:16:34 lr: 4.076779697634702e-05 loss: 0.1619 (0.1740) time: 3.1027 data: 0.0076 max mem: 33300 +Epoch: [8] [ 510/4276] eta: 3:15:58 lr: 4.076510564775351e-05 loss: 0.1617 (0.1737) time: 3.0763 data: 0.0071 max mem: 33300 +Epoch: [8] [ 520/4276] eta: 3:15:28 lr: 4.076241429941734e-05 loss: 0.1553 (0.1737) time: 3.0975 data: 0.0077 max mem: 33300 +Epoch: [8] [ 530/4276] eta: 3:14:56 lr: 4.075972293133692e-05 loss: 0.1731 (0.1741) time: 3.1297 data: 0.0078 max mem: 33300 +Epoch: [8] [ 540/4276] eta: 3:14:26 lr: 4.075703154351065e-05 loss: 0.1728 (0.1738) time: 3.1238 data: 0.0072 max mem: 33300 +Epoch: [8] [ 550/4276] eta: 3:13:54 lr: 4.075434013593696e-05 loss: 0.1770 (0.1742) time: 3.1227 data: 0.0076 max mem: 33300 +Epoch: [8] [ 560/4276] eta: 3:13:24 lr: 4.0751648708614234e-05 loss: 0.1875 (0.1744) time: 3.1298 data: 0.0079 max mem: 33300 +Epoch: [8] [ 570/4276] eta: 3:12:47 lr: 4.0748957261540885e-05 loss: 0.1773 (0.1745) time: 3.0889 data: 0.0074 max mem: 33300 +Epoch: [8] [ 580/4276] eta: 3:12:10 lr: 4.0746265794715324e-05 loss: 0.1669 (0.1745) time: 3.0318 data: 0.0071 max mem: 33300 +Epoch: [8] [ 590/4276] eta: 3:11:30 lr: 4.0743574308135946e-05 loss: 0.1574 (0.1743) time: 3.0082 data: 0.0070 max mem: 33300 +Epoch: [8] [ 600/4276] eta: 3:10:52 lr: 4.0740882801801156e-05 loss: 0.1599 (0.1742) time: 2.9886 data: 0.0068 max mem: 33300 +Epoch: [8] [ 610/4276] eta: 3:10:12 lr: 4.0738191275709364e-05 loss: 0.1666 (0.1740) time: 2.9855 data: 0.0068 max mem: 33300 +Epoch: [8] [ 620/4276] eta: 3:09:34 lr: 4.073549972985898e-05 loss: 0.1594 (0.1739) time: 2.9877 data: 0.0069 max mem: 33300 +Epoch: [8] [ 630/4276] eta: 3:08:58 lr: 4.0732808164248395e-05 loss: 0.1605 (0.1739) time: 3.0102 data: 0.0071 max mem: 33300 +Epoch: [8] [ 640/4276] eta: 3:08:25 lr: 4.0730116578876027e-05 loss: 0.1730 (0.1739) time: 3.0478 data: 0.0072 max mem: 33300 +Epoch: [8] [ 650/4276] eta: 3:07:51 lr: 4.072742497374027e-05 loss: 0.1730 (0.1740) time: 3.0670 data: 0.0074 max mem: 33300 +Epoch: [8] [ 660/4276] eta: 3:07:21 lr: 4.072473334883953e-05 loss: 0.1780 (0.1741) time: 3.0969 data: 0.0074 max mem: 33300 +Epoch: [8] [ 670/4276] eta: 3:06:48 lr: 4.072204170417222e-05 loss: 0.1647 (0.1741) time: 3.1020 data: 0.0073 max mem: 33300 +Epoch: [8] [ 680/4276] eta: 3:06:16 lr: 4.0719350039736726e-05 loss: 0.1677 (0.1740) time: 3.0800 data: 0.0072 max mem: 33300 +Epoch: [8] [ 690/4276] eta: 3:05:44 lr: 4.0716658355531456e-05 loss: 0.1700 (0.1740) time: 3.0892 data: 0.0075 max mem: 33300 +Epoch: [8] [ 700/4276] eta: 3:05:12 lr: 4.0713966651554816e-05 loss: 0.1731 (0.1740) time: 3.0935 data: 0.0077 max mem: 33300 +Epoch: [8] [ 710/4276] eta: 3:04:40 lr: 4.071127492780522e-05 loss: 0.1816 (0.1741) time: 3.0893 data: 0.0075 max mem: 33300 +Epoch: [8] [ 720/4276] eta: 3:04:09 lr: 4.070858318428105e-05 loss: 0.1661 (0.1739) time: 3.0909 data: 0.0075 max mem: 33300 +Epoch: [8] [ 730/4276] eta: 3:03:36 lr: 4.0705891420980716e-05 loss: 0.1587 (0.1739) time: 3.0858 data: 0.0078 max mem: 33300 +Epoch: [8] [ 740/4276] eta: 3:03:03 lr: 4.070319963790263e-05 loss: 0.1650 (0.1739) time: 3.0757 data: 0.0076 max mem: 33300 +Epoch: [8] [ 750/4276] eta: 3:02:34 lr: 4.070050783504517e-05 loss: 0.1670 (0.1738) time: 3.1059 data: 0.0076 max mem: 33300 +Epoch: [8] [ 760/4276] eta: 3:02:04 lr: 4.069781601240676e-05 loss: 0.1588 (0.1737) time: 3.1344 data: 0.0076 max mem: 33300 +Epoch: [8] [ 770/4276] eta: 3:01:34 lr: 4.069512416998578e-05 loss: 0.1598 (0.1737) time: 3.1348 data: 0.0071 max mem: 33300 +Epoch: [8] [ 780/4276] eta: 3:01:04 lr: 4.0692432307780654e-05 loss: 0.1715 (0.1737) time: 3.1363 data: 0.0074 max mem: 33300 +Epoch: [8] [ 790/4276] eta: 3:00:33 lr: 4.068974042578977e-05 loss: 0.1717 (0.1738) time: 3.1198 data: 0.0074 max mem: 33300 +Epoch: [8] [ 800/4276] eta: 3:00:02 lr: 4.0687048524011515e-05 loss: 0.1717 (0.1738) time: 3.1105 data: 0.0075 max mem: 33300 +Epoch: [8] [ 810/4276] eta: 2:59:33 lr: 4.068435660244431e-05 loss: 0.1610 (0.1738) time: 3.1283 data: 0.0077 max mem: 33300 +Epoch: [8] [ 820/4276] eta: 2:59:02 lr: 4.068166466108656e-05 loss: 0.1469 (0.1735) time: 3.1332 data: 0.0073 max mem: 33300 +Epoch: [8] [ 830/4276] eta: 2:58:32 lr: 4.0678972699936634e-05 loss: 0.1540 (0.1735) time: 3.1282 data: 0.0070 max mem: 33300 +Epoch: [8] [ 840/4276] eta: 2:57:58 lr: 4.067628071899296e-05 loss: 0.1568 (0.1735) time: 3.0817 data: 0.0071 max mem: 33300 +Epoch: [8] [ 850/4276] eta: 2:58:17 lr: 4.067358871825392e-05 loss: 0.1558 (0.1735) time: 3.6959 data: 0.0070 max mem: 33300 +Epoch: [8] [ 860/4276] eta: 2:57:45 lr: 4.067089669771792e-05 loss: 0.1667 (0.1735) time: 3.7245 data: 0.0071 max mem: 33300 +Epoch: [8] [ 870/4276] eta: 2:57:11 lr: 4.066820465738335e-05 loss: 0.1667 (0.1735) time: 3.0801 data: 0.0071 max mem: 33300 +Epoch: [8] [ 880/4276] eta: 2:56:38 lr: 4.066551259724862e-05 loss: 0.1642 (0.1736) time: 3.0615 data: 0.0075 max mem: 33300 +Epoch: [8] [ 890/4276] eta: 2:56:05 lr: 4.066282051731213e-05 loss: 0.1743 (0.1736) time: 3.0714 data: 0.0077 max mem: 33300 +Epoch: [8] [ 900/4276] eta: 2:55:34 lr: 4.0660128417572265e-05 loss: 0.1789 (0.1735) time: 3.0982 data: 0.0073 max mem: 33300 +Epoch: [8] [ 910/4276] eta: 2:55:02 lr: 4.065743629802743e-05 loss: 0.1775 (0.1736) time: 3.1045 data: 0.0072 max mem: 33300 +Epoch: [8] [ 920/4276] eta: 2:54:31 lr: 4.065474415867601e-05 loss: 0.1716 (0.1736) time: 3.1121 data: 0.0077 max mem: 33300 +Epoch: [8] [ 930/4276] eta: 2:53:59 lr: 4.0652051999516424e-05 loss: 0.1698 (0.1736) time: 3.1198 data: 0.0080 max mem: 33300 +Epoch: [8] [ 940/4276] eta: 2:53:28 lr: 4.064935982054706e-05 loss: 0.1668 (0.1735) time: 3.1176 data: 0.0076 max mem: 33300 +Epoch: [8] [ 950/4276] eta: 2:52:57 lr: 4.06466676217663e-05 loss: 0.1704 (0.1735) time: 3.1255 data: 0.0081 max mem: 33300 +Epoch: [8] [ 960/4276] eta: 2:52:24 lr: 4.064397540317255e-05 loss: 0.1778 (0.1737) time: 3.1036 data: 0.0078 max mem: 33300 +Epoch: [8] [ 970/4276] eta: 2:51:50 lr: 4.064128316476422e-05 loss: 0.1688 (0.1736) time: 3.0519 data: 0.0073 max mem: 33300 +Epoch: [8] [ 980/4276] eta: 2:51:17 lr: 4.063859090653969e-05 loss: 0.1681 (0.1736) time: 3.0372 data: 0.0078 max mem: 33300 +Epoch: [8] [ 990/4276] eta: 2:50:43 lr: 4.0635898628497345e-05 loss: 0.1760 (0.1736) time: 3.0437 data: 0.0079 max mem: 33300 +Epoch: [8] [1000/4276] eta: 2:50:08 lr: 4.06332063306356e-05 loss: 0.1583 (0.1735) time: 3.0176 data: 0.0082 max mem: 33300 +Epoch: [8] [1010/4276] eta: 2:49:33 lr: 4.063051401295285e-05 loss: 0.1585 (0.1735) time: 3.0038 data: 0.0086 max mem: 33300 +Epoch: [8] [1020/4276] eta: 2:48:58 lr: 4.0627821675447486e-05 loss: 0.1661 (0.1734) time: 3.0063 data: 0.0082 max mem: 33300 +Epoch: [8] [1030/4276] eta: 2:48:24 lr: 4.062512931811789e-05 loss: 0.1661 (0.1733) time: 3.0075 data: 0.0079 max mem: 33300 +Epoch: [8] [1040/4276] eta: 2:47:51 lr: 4.0622436940962475e-05 loss: 0.1521 (0.1732) time: 3.0356 data: 0.0081 max mem: 33300 +Epoch: [8] [1050/4276] eta: 2:47:18 lr: 4.061974454397963e-05 loss: 0.1634 (0.1734) time: 3.0469 data: 0.0081 max mem: 33300 +Epoch: [8] [1060/4276] eta: 2:46:45 lr: 4.061705212716773e-05 loss: 0.1639 (0.1734) time: 3.0439 data: 0.0084 max mem: 33300 +Epoch: [8] [1070/4276] eta: 2:46:12 lr: 4.061435969052519e-05 loss: 0.1639 (0.1734) time: 3.0461 data: 0.0084 max mem: 33300 +Epoch: [8] [1080/4276] eta: 2:45:38 lr: 4.0611667234050395e-05 loss: 0.1754 (0.1733) time: 3.0392 data: 0.0082 max mem: 33300 +Epoch: [8] [1090/4276] eta: 2:45:05 lr: 4.060897475774174e-05 loss: 0.1774 (0.1734) time: 3.0324 data: 0.0078 max mem: 33300 +Epoch: [8] [1100/4276] eta: 2:44:31 lr: 4.0606282261597623e-05 loss: 0.1579 (0.1734) time: 3.0257 data: 0.0080 max mem: 33300 +Epoch: [8] [1110/4276] eta: 2:43:59 lr: 4.060358974561643e-05 loss: 0.1632 (0.1734) time: 3.0380 data: 0.0084 max mem: 33300 +Epoch: [8] [1120/4276] eta: 2:43:24 lr: 4.060089720979655e-05 loss: 0.1742 (0.1734) time: 3.0267 data: 0.0078 max mem: 33300 +Epoch: [8] [1130/4276] eta: 2:42:51 lr: 4.059820465413638e-05 loss: 0.1580 (0.1733) time: 3.0128 data: 0.0076 max mem: 33300 +Epoch: [8] [1140/4276] eta: 2:42:18 lr: 4.0595512078634304e-05 loss: 0.1520 (0.1733) time: 3.0275 data: 0.0082 max mem: 33300 +Epoch: [8] [1150/4276] eta: 2:41:45 lr: 4.059281948328873e-05 loss: 0.1663 (0.1732) time: 3.0299 data: 0.0079 max mem: 33300 +Epoch: [8] [1160/4276] eta: 2:41:12 lr: 4.0590126868098034e-05 loss: 0.1715 (0.1733) time: 3.0382 data: 0.0079 max mem: 33300 +Epoch: [8] [1170/4276] eta: 2:40:40 lr: 4.058743423306062e-05 loss: 0.1847 (0.1736) time: 3.0522 data: 0.0082 max mem: 33300 +Epoch: [8] [1180/4276] eta: 2:40:07 lr: 4.058474157817486e-05 loss: 0.1868 (0.1736) time: 3.0485 data: 0.0078 max mem: 33300 +Epoch: [8] [1190/4276] eta: 2:39:36 lr: 4.058204890343916e-05 loss: 0.1715 (0.1737) time: 3.0623 data: 0.0081 max mem: 33300 +Epoch: [8] [1200/4276] eta: 2:39:04 lr: 4.057935620885191e-05 loss: 0.1715 (0.1738) time: 3.0749 data: 0.0077 max mem: 33300 +Epoch: [8] [1210/4276] eta: 2:38:31 lr: 4.057666349441149e-05 loss: 0.1809 (0.1738) time: 3.0540 data: 0.0073 max mem: 33300 +Epoch: [8] [1220/4276] eta: 2:37:59 lr: 4.05739707601163e-05 loss: 0.1734 (0.1738) time: 3.0551 data: 0.0075 max mem: 33300 +Epoch: [8] [1230/4276] eta: 2:37:27 lr: 4.057127800596472e-05 loss: 0.1766 (0.1739) time: 3.0522 data: 0.0077 max mem: 33300 +Epoch: [8] [1240/4276] eta: 2:36:55 lr: 4.056858523195514e-05 loss: 0.1770 (0.1740) time: 3.0604 data: 0.0078 max mem: 33300 +Epoch: [8] [1250/4276] eta: 2:36:23 lr: 4.0565892438085964e-05 loss: 0.1748 (0.1741) time: 3.0692 data: 0.0080 max mem: 33300 +Epoch: [8] [1260/4276] eta: 2:35:50 lr: 4.056319962435557e-05 loss: 0.1583 (0.1740) time: 3.0394 data: 0.0085 max mem: 33300 +Epoch: [8] [1270/4276] eta: 2:35:18 lr: 4.0560506790762335e-05 loss: 0.1605 (0.1740) time: 3.0331 data: 0.0083 max mem: 33300 +Epoch: [8] [1280/4276] eta: 2:34:45 lr: 4.055781393730467e-05 loss: 0.1814 (0.1741) time: 3.0401 data: 0.0080 max mem: 33300 +Epoch: [8] [1290/4276] eta: 2:34:13 lr: 4.055512106398095e-05 loss: 0.1814 (0.1742) time: 3.0374 data: 0.0080 max mem: 33300 +Epoch: [8] [1300/4276] eta: 2:33:42 lr: 4.0552428170789555e-05 loss: 0.1623 (0.1741) time: 3.0611 data: 0.0084 max mem: 33300 +Epoch: [8] [1310/4276] eta: 2:33:10 lr: 4.0549735257728895e-05 loss: 0.1583 (0.1740) time: 3.0767 data: 0.0084 max mem: 33300 +Epoch: [8] [1320/4276] eta: 2:32:38 lr: 4.0547042324797336e-05 loss: 0.1718 (0.1741) time: 3.0698 data: 0.0080 max mem: 33300 +Epoch: [8] [1330/4276] eta: 2:32:07 lr: 4.054434937199328e-05 loss: 0.1680 (0.1740) time: 3.0684 data: 0.0073 max mem: 33300 +Epoch: [8] [1340/4276] eta: 2:31:35 lr: 4.05416563993151e-05 loss: 0.1531 (0.1740) time: 3.0667 data: 0.0080 max mem: 33300 +Epoch: [8] [1350/4276] eta: 2:31:04 lr: 4.053896340676119e-05 loss: 0.1615 (0.1739) time: 3.0732 data: 0.0085 max mem: 33300 +Epoch: [8] [1360/4276] eta: 2:30:31 lr: 4.053627039432994e-05 loss: 0.1619 (0.1740) time: 3.0438 data: 0.0088 max mem: 33300 +Epoch: [8] [1370/4276] eta: 2:29:58 lr: 4.053357736201973e-05 loss: 0.1585 (0.1738) time: 3.0136 data: 0.0091 max mem: 33300 +Epoch: [8] [1380/4276] eta: 2:29:26 lr: 4.053088430982894e-05 loss: 0.1659 (0.1739) time: 3.0273 data: 0.0089 max mem: 33300 +Epoch: [8] [1390/4276] eta: 2:28:53 lr: 4.0528191237755966e-05 loss: 0.1791 (0.1740) time: 3.0315 data: 0.0087 max mem: 33300 +Epoch: [8] [1400/4276] eta: 2:28:22 lr: 4.0525498145799196e-05 loss: 0.1791 (0.1740) time: 3.0502 data: 0.0088 max mem: 33300 +Epoch: [8] [1410/4276] eta: 2:27:50 lr: 4.0522805033957014e-05 loss: 0.1645 (0.1740) time: 3.0587 data: 0.0089 max mem: 33300 +Epoch: [8] [1420/4276] eta: 2:27:18 lr: 4.0520111902227784e-05 loss: 0.1635 (0.1740) time: 3.0459 data: 0.0084 max mem: 33300 +Epoch: [8] [1430/4276] eta: 2:26:46 lr: 4.051741875060992e-05 loss: 0.1606 (0.1740) time: 3.0492 data: 0.0079 max mem: 33300 +Epoch: [8] [1440/4276] eta: 2:26:15 lr: 4.0514725579101785e-05 loss: 0.1660 (0.1740) time: 3.0608 data: 0.0079 max mem: 33300 +Epoch: [8] [1450/4276] eta: 2:25:43 lr: 4.0512032387701775e-05 loss: 0.1752 (0.1740) time: 3.0672 data: 0.0082 max mem: 33300 +Epoch: [8] [1460/4276] eta: 2:25:12 lr: 4.050933917640826e-05 loss: 0.1752 (0.1740) time: 3.0673 data: 0.0082 max mem: 33300 +Epoch: [8] [1470/4276] eta: 2:24:40 lr: 4.050664594521964e-05 loss: 0.1714 (0.1740) time: 3.0542 data: 0.0080 max mem: 33300 +Epoch: [8] [1480/4276] eta: 2:24:08 lr: 4.05039526941343e-05 loss: 0.1675 (0.1739) time: 3.0499 data: 0.0082 max mem: 33300 +Epoch: [8] [1490/4276] eta: 2:23:36 lr: 4.05012594231506e-05 loss: 0.1512 (0.1739) time: 3.0466 data: 0.0085 max mem: 33300 +Epoch: [8] [1500/4276] eta: 2:23:05 lr: 4.049856613226694e-05 loss: 0.1681 (0.1739) time: 3.0404 data: 0.0082 max mem: 33300 +Epoch: [8] [1510/4276] eta: 2:22:33 lr: 4.04958728214817e-05 loss: 0.1606 (0.1739) time: 3.0576 data: 0.0078 max mem: 33300 +Epoch: [8] [1520/4276] eta: 2:22:02 lr: 4.049317949079327e-05 loss: 0.1512 (0.1738) time: 3.0589 data: 0.0075 max mem: 33300 +Epoch: [8] [1530/4276] eta: 2:21:29 lr: 4.049048614020001e-05 loss: 0.1633 (0.1737) time: 3.0347 data: 0.0072 max mem: 33300 +Epoch: [8] [1540/4276] eta: 2:20:57 lr: 4.048779276970032e-05 loss: 0.1667 (0.1738) time: 3.0155 data: 0.0074 max mem: 33300 +Epoch: [8] [1550/4276] eta: 2:20:25 lr: 4.0485099379292565e-05 loss: 0.1744 (0.1738) time: 3.0091 data: 0.0077 max mem: 33300 +Epoch: [8] [1560/4276] eta: 2:19:52 lr: 4.0482405968975155e-05 loss: 0.1592 (0.1738) time: 3.0113 data: 0.0081 max mem: 33300 +Epoch: [8] [1570/4276] eta: 2:19:20 lr: 4.0479712538746454e-05 loss: 0.1592 (0.1737) time: 3.0107 data: 0.0082 max mem: 33300 +Epoch: [8] [1580/4276] eta: 2:18:48 lr: 4.0477019088604834e-05 loss: 0.1588 (0.1736) time: 3.0201 data: 0.0082 max mem: 33300 +Epoch: [8] [1590/4276] eta: 2:18:17 lr: 4.0474325618548684e-05 loss: 0.1637 (0.1736) time: 3.0472 data: 0.0081 max mem: 33300 +Epoch: [8] [1600/4276] eta: 2:17:45 lr: 4.0471632128576384e-05 loss: 0.1644 (0.1735) time: 3.0488 data: 0.0078 max mem: 33300 +Epoch: [8] [1610/4276] eta: 2:17:13 lr: 4.046893861868632e-05 loss: 0.1547 (0.1733) time: 3.0305 data: 0.0076 max mem: 33300 +Epoch: [8] [1620/4276] eta: 2:16:42 lr: 4.046624508887686e-05 loss: 0.1544 (0.1732) time: 3.0356 data: 0.0077 max mem: 33300 +Epoch: [8] [1630/4276] eta: 2:16:10 lr: 4.0463551539146394e-05 loss: 0.1658 (0.1733) time: 3.0395 data: 0.0082 max mem: 33300 +Epoch: [8] [1640/4276] eta: 2:15:38 lr: 4.04608579694933e-05 loss: 0.1707 (0.1733) time: 3.0260 data: 0.0084 max mem: 33300 +Epoch: [8] [1650/4276] eta: 2:15:06 lr: 4.045816437991594e-05 loss: 0.1622 (0.1732) time: 3.0281 data: 0.0076 max mem: 33300 +Epoch: [8] [1660/4276] eta: 2:14:35 lr: 4.0455470770412716e-05 loss: 0.1622 (0.1733) time: 3.0410 data: 0.0077 max mem: 33300 +Epoch: [8] [1670/4276] eta: 2:14:04 lr: 4.0452777140982004e-05 loss: 0.1658 (0.1733) time: 3.0743 data: 0.0086 max mem: 33300 +Epoch: [8] [1680/4276] eta: 2:13:32 lr: 4.045008349162216e-05 loss: 0.1681 (0.1734) time: 3.0602 data: 0.0085 max mem: 33300 +Epoch: [8] [1690/4276] eta: 2:13:00 lr: 4.044738982233158e-05 loss: 0.1681 (0.1734) time: 3.0216 data: 0.0081 max mem: 33300 +Epoch: [8] [1700/4276] eta: 2:12:29 lr: 4.044469613310864e-05 loss: 0.1683 (0.1735) time: 3.0482 data: 0.0081 max mem: 33300 +Epoch: [8] [1710/4276] eta: 2:11:58 lr: 4.044200242395172e-05 loss: 0.1766 (0.1735) time: 3.0723 data: 0.0082 max mem: 33300 +Epoch: [8] [1720/4276] eta: 2:11:27 lr: 4.043930869485919e-05 loss: 0.1766 (0.1735) time: 3.0800 data: 0.0075 max mem: 33300 +Epoch: [8] [1730/4276] eta: 2:10:56 lr: 4.043661494582943e-05 loss: 0.1747 (0.1735) time: 3.0617 data: 0.0077 max mem: 33300 +Epoch: [8] [1740/4276] eta: 2:10:24 lr: 4.0433921176860815e-05 loss: 0.1730 (0.1736) time: 3.0372 data: 0.0081 max mem: 33300 +Epoch: [8] [1750/4276] eta: 2:09:53 lr: 4.043122738795173e-05 loss: 0.1721 (0.1735) time: 3.0408 data: 0.0074 max mem: 33300 +Epoch: [8] [1760/4276] eta: 2:09:22 lr: 4.042853357910054e-05 loss: 0.1556 (0.1734) time: 3.0547 data: 0.0076 max mem: 33300 +Epoch: [8] [1770/4276] eta: 2:08:51 lr: 4.042583975030563e-05 loss: 0.1604 (0.1734) time: 3.0771 data: 0.0087 max mem: 33300 +Epoch: [8] [1780/4276] eta: 2:08:20 lr: 4.042314590156536e-05 loss: 0.1781 (0.1734) time: 3.0808 data: 0.0088 max mem: 33300 +Epoch: [8] [1790/4276] eta: 2:07:48 lr: 4.0420452032878125e-05 loss: 0.1753 (0.1734) time: 3.0511 data: 0.0079 max mem: 33300 +Epoch: [8] [1800/4276] eta: 2:07:16 lr: 4.041775814424229e-05 loss: 0.1703 (0.1734) time: 3.0186 data: 0.0071 max mem: 33300 +Epoch: [8] [1810/4276] eta: 2:06:45 lr: 4.041506423565623e-05 loss: 0.1711 (0.1734) time: 3.0228 data: 0.0071 max mem: 33300 +Epoch: [8] [1820/4276] eta: 2:06:13 lr: 4.041237030711833e-05 loss: 0.1665 (0.1734) time: 3.0455 data: 0.0078 max mem: 33300 +Epoch: [8] [1830/4276] eta: 2:05:42 lr: 4.040967635862695e-05 loss: 0.1640 (0.1734) time: 3.0668 data: 0.0079 max mem: 33300 +Epoch: [8] [1840/4276] eta: 2:05:11 lr: 4.040698239018047e-05 loss: 0.1585 (0.1733) time: 3.0386 data: 0.0076 max mem: 33300 +Epoch: [8] [1850/4276] eta: 2:04:39 lr: 4.0404288401777254e-05 loss: 0.1655 (0.1734) time: 3.0036 data: 0.0076 max mem: 33300 +Epoch: [8] [1860/4276] eta: 2:04:07 lr: 4.0401594393415694e-05 loss: 0.1685 (0.1733) time: 3.0197 data: 0.0084 max mem: 33300 +Epoch: [8] [1870/4276] eta: 2:03:35 lr: 4.0398900365094155e-05 loss: 0.1685 (0.1734) time: 3.0161 data: 0.0084 max mem: 33300 +Epoch: [8] [1880/4276] eta: 2:03:04 lr: 4.039620631681101e-05 loss: 0.1761 (0.1734) time: 3.0364 data: 0.0074 max mem: 33300 +Epoch: [8] [1890/4276] eta: 2:02:33 lr: 4.039351224856463e-05 loss: 0.1720 (0.1734) time: 3.0484 data: 0.0079 max mem: 33300 +Epoch: [8] [1900/4276] eta: 2:02:01 lr: 4.0390818160353395e-05 loss: 0.1555 (0.1733) time: 3.0269 data: 0.0081 max mem: 33300 +Epoch: [8] [1910/4276] eta: 2:01:30 lr: 4.0388124052175664e-05 loss: 0.1682 (0.1733) time: 3.0487 data: 0.0077 max mem: 33300 +Epoch: [8] [1920/4276] eta: 2:00:59 lr: 4.038542992402982e-05 loss: 0.1730 (0.1733) time: 3.0645 data: 0.0077 max mem: 33300 +Epoch: [8] [1930/4276] eta: 2:00:28 lr: 4.038273577591423e-05 loss: 0.1730 (0.1732) time: 3.0522 data: 0.0076 max mem: 33300 +Epoch: [8] [1940/4276] eta: 1:59:57 lr: 4.0380041607827274e-05 loss: 0.1725 (0.1733) time: 3.0578 data: 0.0082 max mem: 33300 +Epoch: [8] [1950/4276] eta: 1:59:26 lr: 4.0377347419767315e-05 loss: 0.1715 (0.1732) time: 3.0714 data: 0.0085 max mem: 33300 +Epoch: [8] [1960/4276] eta: 1:58:55 lr: 4.037465321173273e-05 loss: 0.1592 (0.1732) time: 3.0737 data: 0.0079 max mem: 33300 +Epoch: [8] [1970/4276] eta: 1:58:24 lr: 4.037195898372188e-05 loss: 0.1527 (0.1731) time: 3.0664 data: 0.0076 max mem: 33300 +Epoch: [8] [1980/4276] eta: 1:57:54 lr: 4.0369264735733145e-05 loss: 0.1527 (0.1730) time: 3.0730 data: 0.0077 max mem: 33300 +Epoch: [8] [1990/4276] eta: 1:57:23 lr: 4.0366570467764884e-05 loss: 0.1647 (0.1730) time: 3.0882 data: 0.0076 max mem: 33300 +Epoch: [8] [2000/4276] eta: 1:56:51 lr: 4.036387617981548e-05 loss: 0.1795 (0.1730) time: 3.0603 data: 0.0078 max mem: 33300 +Epoch: [8] [2010/4276] eta: 1:56:21 lr: 4.03611818718833e-05 loss: 0.1696 (0.1729) time: 3.0571 data: 0.0084 max mem: 33300 +Epoch: [8] [2020/4276] eta: 1:55:50 lr: 4.035848754396671e-05 loss: 0.1731 (0.1730) time: 3.0823 data: 0.0085 max mem: 33300 +Epoch: [8] [2030/4276] eta: 1:55:19 lr: 4.0355793196064077e-05 loss: 0.1655 (0.1729) time: 3.0863 data: 0.0085 max mem: 33300 +Epoch: [8] [2040/4276] eta: 1:54:48 lr: 4.035309882817378e-05 loss: 0.1619 (0.1729) time: 3.0895 data: 0.0083 max mem: 33300 +Epoch: [8] [2050/4276] eta: 1:54:16 lr: 4.0350404440294174e-05 loss: 0.1717 (0.1730) time: 3.0317 data: 0.0073 max mem: 33300 +Epoch: [8] [2060/4276] eta: 1:53:45 lr: 4.034771003242365e-05 loss: 0.1658 (0.1729) time: 3.0006 data: 0.0066 max mem: 33300 +Epoch: [8] [2070/4276] eta: 1:53:14 lr: 4.034501560456055e-05 loss: 0.1595 (0.1729) time: 3.0385 data: 0.0066 max mem: 33300 +Epoch: [8] [2080/4276] eta: 1:52:43 lr: 4.0342321156703256e-05 loss: 0.1672 (0.1729) time: 3.0469 data: 0.0071 max mem: 33300 +Epoch: [8] [2090/4276] eta: 1:52:12 lr: 4.0339626688850134e-05 loss: 0.1801 (0.1729) time: 3.0429 data: 0.0074 max mem: 33300 +Epoch: [8] [2100/4276] eta: 1:51:40 lr: 4.0336932200999554e-05 loss: 0.1747 (0.1729) time: 3.0110 data: 0.0070 max mem: 33300 +Epoch: [8] [2110/4276] eta: 1:51:08 lr: 4.033423769314988e-05 loss: 0.1577 (0.1729) time: 2.9815 data: 0.0073 max mem: 33300 +Epoch: [8] [2120/4276] eta: 1:50:36 lr: 4.033154316529948e-05 loss: 0.1422 (0.1727) time: 2.9826 data: 0.0079 max mem: 33300 +Epoch: [8] [2130/4276] eta: 1:50:04 lr: 4.032884861744672e-05 loss: 0.1328 (0.1727) time: 2.9821 data: 0.0081 max mem: 33300 +Epoch: [8] [2140/4276] eta: 1:49:33 lr: 4.0326154049589965e-05 loss: 0.1676 (0.1727) time: 3.0067 data: 0.0082 max mem: 33300 +Epoch: [8] [2150/4276] eta: 1:49:02 lr: 4.032345946172759e-05 loss: 0.1734 (0.1727) time: 3.0195 data: 0.0084 max mem: 33300 +Epoch: [8] [2160/4276] eta: 1:48:30 lr: 4.032076485385794e-05 loss: 0.1588 (0.1727) time: 2.9905 data: 0.0083 max mem: 33300 +Epoch: [8] [2170/4276] eta: 1:47:58 lr: 4.0318070225979406e-05 loss: 0.1648 (0.1727) time: 2.9635 data: 0.0085 max mem: 33300 +Epoch: [8] [2180/4276] eta: 1:47:26 lr: 4.031537557809034e-05 loss: 0.1791 (0.1728) time: 2.9355 data: 0.0089 max mem: 33300 +Epoch: [8] [2190/4276] eta: 1:46:54 lr: 4.031268091018911e-05 loss: 0.1724 (0.1728) time: 2.9525 data: 0.0089 max mem: 33300 +Epoch: [8] [2200/4276] eta: 1:46:22 lr: 4.0309986222274083e-05 loss: 0.1724 (0.1728) time: 2.9740 data: 0.0090 max mem: 33300 +Epoch: [8] [2210/4276] eta: 1:45:51 lr: 4.030729151434362e-05 loss: 0.1745 (0.1728) time: 2.9675 data: 0.0090 max mem: 33300 +Epoch: [8] [2220/4276] eta: 1:45:19 lr: 4.0304596786396084e-05 loss: 0.1763 (0.1729) time: 2.9814 data: 0.0090 max mem: 33300 +Epoch: [8] [2230/4276] eta: 1:44:47 lr: 4.030190203842985e-05 loss: 0.1651 (0.1728) time: 2.9745 data: 0.0088 max mem: 33300 +Epoch: [8] [2240/4276] eta: 1:44:15 lr: 4.029920727044327e-05 loss: 0.1486 (0.1726) time: 2.9526 data: 0.0081 max mem: 33300 +Epoch: [8] [2250/4276] eta: 1:43:44 lr: 4.029651248243471e-05 loss: 0.1470 (0.1726) time: 2.9583 data: 0.0079 max mem: 33300 +Epoch: [8] [2260/4276] eta: 1:43:12 lr: 4.029381767440255e-05 loss: 0.1598 (0.1726) time: 2.9469 data: 0.0078 max mem: 33300 +Epoch: [8] [2270/4276] eta: 1:42:40 lr: 4.029112284634512e-05 loss: 0.1652 (0.1726) time: 2.9319 data: 0.0076 max mem: 33300 +Epoch: [8] [2280/4276] eta: 1:42:08 lr: 4.0288427998260806e-05 loss: 0.1678 (0.1726) time: 2.9329 data: 0.0079 max mem: 33300 +Epoch: [8] [2290/4276] eta: 1:41:36 lr: 4.028573313014798e-05 loss: 0.1692 (0.1726) time: 2.9438 data: 0.0085 max mem: 33300 +Epoch: [8] [2300/4276] eta: 1:41:04 lr: 4.0283038242004975e-05 loss: 0.1577 (0.1725) time: 2.9482 data: 0.0085 max mem: 33300 +Epoch: [8] [2310/4276] eta: 1:40:32 lr: 4.028034333383018e-05 loss: 0.1650 (0.1725) time: 2.9281 data: 0.0078 max mem: 33300 +Epoch: [8] [2320/4276] eta: 1:40:01 lr: 4.027764840562194e-05 loss: 0.1680 (0.1725) time: 2.9240 data: 0.0078 max mem: 33300 +Epoch: [8] [2330/4276] eta: 1:39:29 lr: 4.027495345737862e-05 loss: 0.1627 (0.1725) time: 2.9390 data: 0.0082 max mem: 33300 +Epoch: [8] [2340/4276] eta: 1:38:57 lr: 4.02722584890986e-05 loss: 0.1622 (0.1725) time: 2.9645 data: 0.0086 max mem: 33300 +Epoch: [8] [2350/4276] eta: 1:38:26 lr: 4.0269563500780214e-05 loss: 0.1609 (0.1724) time: 2.9662 data: 0.0086 max mem: 33300 +Epoch: [8] [2360/4276] eta: 1:37:54 lr: 4.0266868492421836e-05 loss: 0.1638 (0.1724) time: 2.9613 data: 0.0084 max mem: 33300 +Epoch: [8] [2370/4276] eta: 1:37:23 lr: 4.0264173464021826e-05 loss: 0.1665 (0.1724) time: 2.9492 data: 0.0087 max mem: 33300 +Epoch: [8] [2380/4276] eta: 1:36:51 lr: 4.026147841557854e-05 loss: 0.1713 (0.1724) time: 2.9387 data: 0.0084 max mem: 33300 +Epoch: [8] [2390/4276] eta: 1:36:20 lr: 4.0258783347090346e-05 loss: 0.1579 (0.1723) time: 2.9669 data: 0.0088 max mem: 33300 +Epoch: [8] [2400/4276] eta: 1:35:49 lr: 4.0256088258555604e-05 loss: 0.1533 (0.1724) time: 2.9954 data: 0.0098 max mem: 33300 +Epoch: [8] [2410/4276] eta: 1:35:17 lr: 4.025339314997267e-05 loss: 0.1546 (0.1723) time: 2.9906 data: 0.0086 max mem: 33300 +Epoch: [8] [2420/4276] eta: 1:34:46 lr: 4.0250698021339896e-05 loss: 0.1520 (0.1722) time: 2.9816 data: 0.0081 max mem: 33300 +Epoch: [8] [2430/4276] eta: 1:34:15 lr: 4.0248002872655643e-05 loss: 0.1596 (0.1723) time: 2.9848 data: 0.0085 max mem: 33300 +Epoch: [8] [2440/4276] eta: 1:33:44 lr: 4.0245307703918286e-05 loss: 0.1619 (0.1722) time: 3.0025 data: 0.0077 max mem: 33300 +Epoch: [8] [2450/4276] eta: 1:33:13 lr: 4.024261251512617e-05 loss: 0.1585 (0.1723) time: 3.0130 data: 0.0080 max mem: 33300 +Epoch: [8] [2460/4276] eta: 1:32:42 lr: 4.0239917306277655e-05 loss: 0.1693 (0.1722) time: 2.9907 data: 0.0084 max mem: 33300 +Epoch: [8] [2470/4276] eta: 1:32:10 lr: 4.0237222077371095e-05 loss: 0.1684 (0.1723) time: 2.9801 data: 0.0084 max mem: 33300 +Epoch: [8] [2480/4276] eta: 1:31:39 lr: 4.0234526828404857e-05 loss: 0.1701 (0.1722) time: 2.9855 data: 0.0082 max mem: 33300 +Epoch: [8] [2490/4276] eta: 1:31:08 lr: 4.02318315593773e-05 loss: 0.1681 (0.1722) time: 2.9993 data: 0.0077 max mem: 33300 +Epoch: [8] [2500/4276] eta: 1:30:37 lr: 4.022913627028677e-05 loss: 0.1654 (0.1722) time: 2.9942 data: 0.0080 max mem: 33300 +Epoch: [8] [2510/4276] eta: 1:30:06 lr: 4.022644096113163e-05 loss: 0.1673 (0.1722) time: 2.9816 data: 0.0085 max mem: 33300 +Epoch: [8] [2520/4276] eta: 1:29:35 lr: 4.0223745631910244e-05 loss: 0.1579 (0.1721) time: 2.9868 data: 0.0080 max mem: 33300 +Epoch: [8] [2530/4276] eta: 1:29:03 lr: 4.0221050282620956e-05 loss: 0.1366 (0.1720) time: 2.9702 data: 0.0079 max mem: 33300 +Epoch: [8] [2540/4276] eta: 1:28:32 lr: 4.021835491326212e-05 loss: 0.1420 (0.1719) time: 2.9766 data: 0.0080 max mem: 33300 +Epoch: [8] [2550/4276] eta: 1:28:01 lr: 4.021565952383211e-05 loss: 0.1483 (0.1718) time: 3.0016 data: 0.0080 max mem: 33300 +Epoch: [8] [2560/4276] eta: 1:27:30 lr: 4.0212964114329266e-05 loss: 0.1412 (0.1718) time: 2.9783 data: 0.0083 max mem: 33300 +Epoch: [8] [2570/4276] eta: 1:26:59 lr: 4.0210268684751954e-05 loss: 0.1391 (0.1717) time: 2.9471 data: 0.0094 max mem: 33300 +Epoch: [8] [2580/4276] eta: 1:26:27 lr: 4.0207573235098525e-05 loss: 0.1580 (0.1717) time: 2.9399 data: 0.0102 max mem: 33300 +Epoch: [8] [2590/4276] eta: 1:25:56 lr: 4.0204877765367325e-05 loss: 0.1552 (0.1716) time: 2.9436 data: 0.0096 max mem: 33300 +Epoch: [8] [2600/4276] eta: 1:25:25 lr: 4.0202182275556735e-05 loss: 0.1654 (0.1717) time: 2.9726 data: 0.0087 max mem: 33300 +Epoch: [8] [2610/4276] eta: 1:24:54 lr: 4.0199486765665074e-05 loss: 0.1733 (0.1716) time: 2.9791 data: 0.0077 max mem: 33300 +Epoch: [8] [2620/4276] eta: 1:24:23 lr: 4.0196791235690715e-05 loss: 0.1645 (0.1716) time: 2.9711 data: 0.0073 max mem: 33300 +Epoch: [8] [2630/4276] eta: 1:23:51 lr: 4.0194095685632013e-05 loss: 0.1590 (0.1716) time: 2.9703 data: 0.0078 max mem: 33300 +Epoch: [8] [2640/4276] eta: 1:23:21 lr: 4.019140011548733e-05 loss: 0.1490 (0.1715) time: 2.9853 data: 0.0079 max mem: 33300 +Epoch: [8] [2650/4276] eta: 1:22:50 lr: 4.0188704525255e-05 loss: 0.1716 (0.1715) time: 2.9934 data: 0.0081 max mem: 33300 +Epoch: [8] [2660/4276] eta: 1:22:19 lr: 4.0186008914933385e-05 loss: 0.1692 (0.1715) time: 2.9775 data: 0.0081 max mem: 33300 +Epoch: [8] [2670/4276] eta: 1:21:47 lr: 4.018331328452085e-05 loss: 0.1684 (0.1715) time: 2.9780 data: 0.0075 max mem: 33300 +Epoch: [8] [2680/4276] eta: 1:21:16 lr: 4.018061763401573e-05 loss: 0.1730 (0.1715) time: 2.9813 data: 0.0078 max mem: 33300 +Epoch: [8] [2690/4276] eta: 1:20:46 lr: 4.0177921963416376e-05 loss: 0.1693 (0.1715) time: 3.0038 data: 0.0080 max mem: 33300 +Epoch: [8] [2700/4276] eta: 1:20:15 lr: 4.017522627272115e-05 loss: 0.1567 (0.1714) time: 3.0013 data: 0.0080 max mem: 33300 +Epoch: [8] [2710/4276] eta: 1:19:44 lr: 4.0172530561928404e-05 loss: 0.1547 (0.1714) time: 2.9708 data: 0.0080 max mem: 33300 +Epoch: [8] [2720/4276] eta: 1:19:13 lr: 4.016983483103649e-05 loss: 0.1482 (0.1713) time: 2.9643 data: 0.0079 max mem: 33300 +Epoch: [8] [2730/4276] eta: 1:18:41 lr: 4.016713908004375e-05 loss: 0.1493 (0.1713) time: 2.9574 data: 0.0085 max mem: 33300 +Epoch: [8] [2740/4276] eta: 1:18:10 lr: 4.0164443308948554e-05 loss: 0.1733 (0.1713) time: 2.9626 data: 0.0088 max mem: 33300 +Epoch: [8] [2750/4276] eta: 1:17:39 lr: 4.0161747517749235e-05 loss: 0.1747 (0.1714) time: 2.9735 data: 0.0091 max mem: 33300 +Epoch: [8] [2760/4276] eta: 1:17:08 lr: 4.015905170644415e-05 loss: 0.1578 (0.1713) time: 2.9458 data: 0.0093 max mem: 33300 +Epoch: [8] [2770/4276] eta: 1:16:37 lr: 4.0156355875031646e-05 loss: 0.1492 (0.1713) time: 2.9419 data: 0.0087 max mem: 33300 +Epoch: [8] [2780/4276] eta: 1:16:06 lr: 4.0153660023510076e-05 loss: 0.1578 (0.1713) time: 2.9521 data: 0.0086 max mem: 33300 +Epoch: [8] [2790/4276] eta: 1:15:35 lr: 4.015096415187779e-05 loss: 0.1721 (0.1713) time: 2.9781 data: 0.0085 max mem: 33300 +Epoch: [8] [2800/4276] eta: 1:15:04 lr: 4.0148268260133145e-05 loss: 0.1670 (0.1713) time: 2.9994 data: 0.0082 max mem: 33300 +Epoch: [8] [2810/4276] eta: 1:14:34 lr: 4.014557234827448e-05 loss: 0.1468 (0.1712) time: 2.9884 data: 0.0075 max mem: 33300 +Epoch: [8] [2820/4276] eta: 1:14:03 lr: 4.014287641630014e-05 loss: 0.1462 (0.1711) time: 2.9850 data: 0.0075 max mem: 33300 +Epoch: [8] [2830/4276] eta: 1:13:32 lr: 4.0140180464208496e-05 loss: 0.1510 (0.1710) time: 2.9821 data: 0.0075 max mem: 33300 +Epoch: [8] [2840/4276] eta: 1:13:01 lr: 4.013748449199787e-05 loss: 0.1697 (0.1711) time: 3.0042 data: 0.0071 max mem: 33300 +Epoch: [8] [2850/4276] eta: 1:12:30 lr: 4.013478849966662e-05 loss: 0.1818 (0.1711) time: 3.0185 data: 0.0074 max mem: 33300 +Epoch: [8] [2860/4276] eta: 1:11:59 lr: 4.0132092487213093e-05 loss: 0.1725 (0.1711) time: 2.9731 data: 0.0077 max mem: 33300 +Epoch: [8] [2870/4276] eta: 1:11:29 lr: 4.012939645463565e-05 loss: 0.1581 (0.1711) time: 2.9698 data: 0.0082 max mem: 33300 +Epoch: [8] [2880/4276] eta: 1:10:58 lr: 4.012670040193263e-05 loss: 0.1636 (0.1711) time: 2.9937 data: 0.0084 max mem: 33300 +Epoch: [8] [2890/4276] eta: 1:10:27 lr: 4.0124004329102375e-05 loss: 0.1686 (0.1712) time: 2.9992 data: 0.0079 max mem: 33300 +Epoch: [8] [2900/4276] eta: 1:09:56 lr: 4.012130823614323e-05 loss: 0.1570 (0.1711) time: 2.9892 data: 0.0084 max mem: 33300 +Epoch: [8] [2910/4276] eta: 1:09:25 lr: 4.011861212305355e-05 loss: 0.1505 (0.1711) time: 2.9635 data: 0.0082 max mem: 33300 +Epoch: [8] [2920/4276] eta: 1:08:54 lr: 4.0115915989831685e-05 loss: 0.1590 (0.1711) time: 2.9628 data: 0.0073 max mem: 33300 +Epoch: [8] [2930/4276] eta: 1:08:24 lr: 4.011321983647597e-05 loss: 0.1590 (0.1710) time: 2.9627 data: 0.0073 max mem: 33300 +Epoch: [8] [2940/4276] eta: 1:07:53 lr: 4.011052366298475e-05 loss: 0.1522 (0.1710) time: 2.9645 data: 0.0074 max mem: 33300 +Epoch: [8] [2950/4276] eta: 1:07:22 lr: 4.010782746935638e-05 loss: 0.1660 (0.1710) time: 2.9488 data: 0.0075 max mem: 33300 +Epoch: [8] [2960/4276] eta: 1:06:51 lr: 4.010513125558922e-05 loss: 0.1711 (0.1710) time: 2.9201 data: 0.0083 max mem: 33300 +Epoch: [8] [2970/4276] eta: 1:06:20 lr: 4.010243502168158e-05 loss: 0.1690 (0.1710) time: 2.9132 data: 0.0086 max mem: 33300 +Epoch: [8] [2980/4276] eta: 1:05:48 lr: 4.0099738767631824e-05 loss: 0.1751 (0.1710) time: 2.9176 data: 0.0084 max mem: 33300 +Epoch: [8] [2990/4276] eta: 1:05:17 lr: 4.0097042493438306e-05 loss: 0.1538 (0.1709) time: 2.9118 data: 0.0078 max mem: 33300 +Epoch: [8] [3000/4276] eta: 1:04:46 lr: 4.009434619909935e-05 loss: 0.1500 (0.1709) time: 2.9172 data: 0.0080 max mem: 33300 +Epoch: [8] [3010/4276] eta: 1:04:15 lr: 4.00916498846133e-05 loss: 0.1601 (0.1709) time: 2.9175 data: 0.0086 max mem: 33300 +Epoch: [8] [3020/4276] eta: 1:03:44 lr: 4.0088953549978527e-05 loss: 0.1531 (0.1708) time: 2.9065 data: 0.0081 max mem: 33300 +Epoch: [8] [3030/4276] eta: 1:03:13 lr: 4.0086257195193354e-05 loss: 0.1544 (0.1708) time: 2.9148 data: 0.0074 max mem: 33300 +Epoch: [8] [3040/4276] eta: 1:02:42 lr: 4.008356082025612e-05 loss: 0.1642 (0.1709) time: 2.9143 data: 0.0072 max mem: 33300 +Epoch: [8] [3050/4276] eta: 1:02:11 lr: 4.0080864425165185e-05 loss: 0.1598 (0.1708) time: 2.9014 data: 0.0070 max mem: 33300 +Epoch: [8] [3060/4276] eta: 1:01:40 lr: 4.007816800991888e-05 loss: 0.1387 (0.1708) time: 2.8963 data: 0.0073 max mem: 33300 +Epoch: [8] [3070/4276] eta: 1:01:09 lr: 4.0075471574515546e-05 loss: 0.1508 (0.1707) time: 2.9038 data: 0.0076 max mem: 33300 +Epoch: [8] [3080/4276] eta: 1:00:38 lr: 4.007277511895354e-05 loss: 0.1636 (0.1707) time: 2.9110 data: 0.0074 max mem: 33300 +Epoch: [8] [3090/4276] eta: 1:00:08 lr: 4.007007864323118e-05 loss: 0.1514 (0.1706) time: 2.9490 data: 0.0082 max mem: 33300 +Epoch: [8] [3100/4276] eta: 0:59:37 lr: 4.0067382147346835e-05 loss: 0.1578 (0.1706) time: 3.0190 data: 0.0086 max mem: 33300 +Epoch: [8] [3110/4276] eta: 0:59:07 lr: 4.006468563129883e-05 loss: 0.1531 (0.1706) time: 3.0429 data: 0.0079 max mem: 33300 +Epoch: [8] [3120/4276] eta: 0:58:37 lr: 4.00619890950855e-05 loss: 0.1475 (0.1706) time: 3.0487 data: 0.0073 max mem: 33300 +Epoch: [8] [3130/4276] eta: 0:58:06 lr: 4.0059292538705205e-05 loss: 0.1539 (0.1705) time: 3.0476 data: 0.0075 max mem: 33300 +Epoch: [8] [3140/4276] eta: 0:57:36 lr: 4.0056595962156277e-05 loss: 0.1644 (0.1705) time: 3.0435 data: 0.0079 max mem: 33300 +Epoch: [8] [3150/4276] eta: 0:57:05 lr: 4.0053899365437054e-05 loss: 0.1706 (0.1705) time: 3.0505 data: 0.0074 max mem: 33300 +Epoch: [8] [3160/4276] eta: 0:56:35 lr: 4.005120274854587e-05 loss: 0.1706 (0.1705) time: 3.0554 data: 0.0071 max mem: 33300 +Epoch: [8] [3170/4276] eta: 0:56:05 lr: 4.004850611148109e-05 loss: 0.1649 (0.1706) time: 3.0539 data: 0.0070 max mem: 33300 +Epoch: [8] [3180/4276] eta: 0:55:34 lr: 4.004580945424102e-05 loss: 0.1649 (0.1705) time: 3.0451 data: 0.0070 max mem: 33300 +Epoch: [8] [3190/4276] eta: 0:55:04 lr: 4.0043112776824035e-05 loss: 0.1609 (0.1705) time: 3.0331 data: 0.0073 max mem: 33300 +Epoch: [8] [3200/4276] eta: 0:54:33 lr: 4.004041607922844e-05 loss: 0.1734 (0.1705) time: 3.0376 data: 0.0075 max mem: 33300 +Epoch: [8] [3210/4276] eta: 0:54:03 lr: 4.003771936145259e-05 loss: 0.1805 (0.1706) time: 3.0425 data: 0.0076 max mem: 33300 +Epoch: [8] [3220/4276] eta: 0:53:32 lr: 4.003502262349484e-05 loss: 0.1837 (0.1706) time: 3.0407 data: 0.0074 max mem: 33300 +Epoch: [8] [3230/4276] eta: 0:53:02 lr: 4.00323258653535e-05 loss: 0.1656 (0.1706) time: 3.0484 data: 0.0072 max mem: 33300 +Epoch: [8] [3240/4276] eta: 0:52:32 lr: 4.0029629087026916e-05 loss: 0.1715 (0.1706) time: 3.0424 data: 0.0072 max mem: 33300 +Epoch: [8] [3250/4276] eta: 0:52:01 lr: 4.002693228851344e-05 loss: 0.1715 (0.1706) time: 3.0309 data: 0.0076 max mem: 33300 +Epoch: [8] [3260/4276] eta: 0:51:31 lr: 4.002423546981139e-05 loss: 0.1666 (0.1706) time: 3.0137 data: 0.0085 max mem: 33300 +Epoch: [8] [3270/4276] eta: 0:51:00 lr: 4.002153863091912e-05 loss: 0.1749 (0.1706) time: 2.9920 data: 0.0089 max mem: 33300 +Epoch: [8] [3280/4276] eta: 0:50:29 lr: 4.001884177183495e-05 loss: 0.1833 (0.1707) time: 2.9825 data: 0.0082 max mem: 33300 +Epoch: [8] [3290/4276] eta: 0:49:59 lr: 4.001614489255724e-05 loss: 0.1670 (0.1707) time: 2.9936 data: 0.0079 max mem: 33300 +Epoch: [8] [3300/4276] eta: 0:49:28 lr: 4.0013447993084305e-05 loss: 0.1650 (0.1707) time: 3.0241 data: 0.0080 max mem: 33300 +Epoch: [8] [3310/4276] eta: 0:48:58 lr: 4.00107510734145e-05 loss: 0.1780 (0.1707) time: 3.0427 data: 0.0084 max mem: 33300 +Epoch: [8] [3320/4276] eta: 0:48:28 lr: 4.000805413354614e-05 loss: 0.1829 (0.1707) time: 3.0495 data: 0.0083 max mem: 33300 +Epoch: [8] [3330/4276] eta: 0:47:57 lr: 4.0005357173477576e-05 loss: 0.1523 (0.1707) time: 3.0447 data: 0.0078 max mem: 33300 +Epoch: [8] [3340/4276] eta: 0:47:27 lr: 4.000266019320715e-05 loss: 0.1635 (0.1707) time: 3.0439 data: 0.0078 max mem: 33300 +Epoch: [8] [3350/4276] eta: 0:46:56 lr: 3.999996319273317e-05 loss: 0.1601 (0.1707) time: 3.0557 data: 0.0077 max mem: 33300 +Epoch: [8] [3360/4276] eta: 0:46:26 lr: 3.999726617205399e-05 loss: 0.1601 (0.1707) time: 3.0513 data: 0.0075 max mem: 33300 +Epoch: [8] [3370/4276] eta: 0:45:56 lr: 3.999456913116796e-05 loss: 0.1704 (0.1707) time: 3.0447 data: 0.0080 max mem: 33300 +Epoch: [8] [3380/4276] eta: 0:45:25 lr: 3.9991872070073385e-05 loss: 0.1664 (0.1707) time: 3.0461 data: 0.0080 max mem: 33300 +Epoch: [8] [3390/4276] eta: 0:44:55 lr: 3.9989174988768606e-05 loss: 0.1706 (0.1707) time: 3.0118 data: 0.0079 max mem: 33300 +Epoch: [8] [3400/4276] eta: 0:44:24 lr: 3.998647788725197e-05 loss: 0.1814 (0.1708) time: 2.9845 data: 0.0079 max mem: 33300 +Epoch: [8] [3410/4276] eta: 0:43:54 lr: 3.9983780765521795e-05 loss: 0.1814 (0.1708) time: 3.0164 data: 0.0078 max mem: 33300 +Epoch: [8] [3420/4276] eta: 0:43:23 lr: 3.998108362357643e-05 loss: 0.1698 (0.1708) time: 3.0257 data: 0.0079 max mem: 33300 +Epoch: [8] [3430/4276] eta: 0:42:53 lr: 3.99783864614142e-05 loss: 0.1706 (0.1709) time: 3.0333 data: 0.0083 max mem: 33300 +Epoch: [8] [3440/4276] eta: 0:42:22 lr: 3.997568927903344e-05 loss: 0.1617 (0.1708) time: 3.0599 data: 0.0088 max mem: 33300 +Epoch: [8] [3450/4276] eta: 0:41:52 lr: 3.997299207643249e-05 loss: 0.1685 (0.1708) time: 3.0627 data: 0.0081 max mem: 33300 +Epoch: [8] [3460/4276] eta: 0:41:22 lr: 3.997029485360966e-05 loss: 0.1759 (0.1708) time: 3.0531 data: 0.0079 max mem: 33300 +Epoch: [8] [3470/4276] eta: 0:40:51 lr: 3.9967597610563295e-05 loss: 0.1455 (0.1708) time: 3.0523 data: 0.0078 max mem: 33300 +Epoch: [8] [3480/4276] eta: 0:40:21 lr: 3.9964900347291736e-05 loss: 0.1644 (0.1708) time: 3.0461 data: 0.0078 max mem: 33300 +Epoch: [8] [3490/4276] eta: 0:39:50 lr: 3.99622030637933e-05 loss: 0.1716 (0.1708) time: 3.0147 data: 0.0087 max mem: 33300 +Epoch: [8] [3500/4276] eta: 0:39:20 lr: 3.9959505760066336e-05 loss: 0.1725 (0.1708) time: 2.9928 data: 0.0086 max mem: 33300 +Epoch: [8] [3510/4276] eta: 0:38:49 lr: 3.995680843610915e-05 loss: 0.1537 (0.1708) time: 3.0187 data: 0.0085 max mem: 33300 +Epoch: [8] [3520/4276] eta: 0:38:19 lr: 3.995411109192009e-05 loss: 0.1615 (0.1708) time: 3.0504 data: 0.0087 max mem: 33300 +Epoch: [8] [3530/4276] eta: 0:37:48 lr: 3.99514137274975e-05 loss: 0.1742 (0.1708) time: 3.0465 data: 0.0078 max mem: 33300 +Epoch: [8] [3540/4276] eta: 0:37:18 lr: 3.994871634283968e-05 loss: 0.1753 (0.1708) time: 3.0338 data: 0.0081 max mem: 33300 +Epoch: [8] [3550/4276] eta: 0:36:48 lr: 3.9946018937944976e-05 loss: 0.1683 (0.1708) time: 3.0350 data: 0.0089 max mem: 33300 +Epoch: [8] [3560/4276] eta: 0:36:17 lr: 3.994332151281171e-05 loss: 0.1683 (0.1708) time: 3.0514 data: 0.0085 max mem: 33300 +Epoch: [8] [3570/4276] eta: 0:35:47 lr: 3.994062406743822e-05 loss: 0.1851 (0.1708) time: 3.0423 data: 0.0080 max mem: 33300 +Epoch: [8] [3580/4276] eta: 0:35:16 lr: 3.993792660182284e-05 loss: 0.1607 (0.1708) time: 3.0036 data: 0.0080 max mem: 33300 +Epoch: [8] [3590/4276] eta: 0:34:46 lr: 3.993522911596388e-05 loss: 0.1459 (0.1708) time: 2.9916 data: 0.0081 max mem: 33300 +Epoch: [8] [3600/4276] eta: 0:34:15 lr: 3.993253160985969e-05 loss: 0.1563 (0.1708) time: 3.0223 data: 0.0083 max mem: 33300 +Epoch: [8] [3610/4276] eta: 0:33:45 lr: 3.992983408350859e-05 loss: 0.1727 (0.1708) time: 3.0485 data: 0.0089 max mem: 33300 +Epoch: [8] [3620/4276] eta: 0:33:15 lr: 3.99271365369089e-05 loss: 0.1663 (0.1707) time: 3.0565 data: 0.0089 max mem: 33300 +Epoch: [8] [3630/4276] eta: 0:32:44 lr: 3.992443897005896e-05 loss: 0.1602 (0.1707) time: 3.0584 data: 0.0081 max mem: 33300 +Epoch: [8] [3640/4276] eta: 0:32:14 lr: 3.992174138295709e-05 loss: 0.1596 (0.1707) time: 3.0579 data: 0.0073 max mem: 33300 +Epoch: [8] [3650/4276] eta: 0:31:43 lr: 3.991904377560162e-05 loss: 0.1595 (0.1707) time: 3.0496 data: 0.0072 max mem: 33300 +Epoch: [8] [3660/4276] eta: 0:31:13 lr: 3.991634614799088e-05 loss: 0.1456 (0.1706) time: 3.0271 data: 0.0077 max mem: 33300 +Epoch: [8] [3670/4276] eta: 0:30:43 lr: 3.9913648500123185e-05 loss: 0.1634 (0.1706) time: 3.0361 data: 0.0084 max mem: 33300 +Epoch: [8] [3680/4276] eta: 0:30:12 lr: 3.991095083199689e-05 loss: 0.1891 (0.1707) time: 3.0543 data: 0.0081 max mem: 33300 +Epoch: [8] [3690/4276] eta: 0:29:42 lr: 3.990825314361028e-05 loss: 0.1703 (0.1706) time: 3.0812 data: 0.0079 max mem: 33300 +Epoch: [8] [3700/4276] eta: 0:29:12 lr: 3.990555543496171e-05 loss: 0.1631 (0.1706) time: 3.1429 data: 0.0080 max mem: 33300 +Epoch: [8] [3710/4276] eta: 0:28:42 lr: 3.99028577060495e-05 loss: 0.1555 (0.1706) time: 3.2170 data: 0.0084 max mem: 33300 +Epoch: [8] [3720/4276] eta: 0:28:11 lr: 3.990015995687198e-05 loss: 0.1462 (0.1705) time: 3.2460 data: 0.0084 max mem: 33300 +Epoch: [8] [3730/4276] eta: 0:27:41 lr: 3.989746218742747e-05 loss: 0.1687 (0.1706) time: 3.2341 data: 0.0082 max mem: 33300 +Epoch: [8] [3740/4276] eta: 0:27:11 lr: 3.989476439771429e-05 loss: 0.1723 (0.1706) time: 3.2294 data: 0.0085 max mem: 33300 +Epoch: [8] [3750/4276] eta: 0:26:41 lr: 3.989206658773077e-05 loss: 0.1704 (0.1706) time: 3.2379 data: 0.0086 max mem: 33300 +Epoch: [8] [3760/4276] eta: 0:26:11 lr: 3.9889368757475236e-05 loss: 0.1678 (0.1706) time: 3.2478 data: 0.0087 max mem: 33300 +Epoch: [8] [3770/4276] eta: 0:25:41 lr: 3.988667090694601e-05 loss: 0.1574 (0.1706) time: 3.2263 data: 0.0087 max mem: 33300 +Epoch: [8] [3780/4276] eta: 0:25:10 lr: 3.988397303614141e-05 loss: 0.1569 (0.1705) time: 3.2236 data: 0.0090 max mem: 33300 +Epoch: [8] [3790/4276] eta: 0:24:40 lr: 3.988127514505978e-05 loss: 0.1569 (0.1705) time: 3.2343 data: 0.0093 max mem: 33300 +Epoch: [8] [3800/4276] eta: 0:24:10 lr: 3.987857723369942e-05 loss: 0.1701 (0.1705) time: 3.2328 data: 0.0091 max mem: 33300 +Epoch: [8] [3810/4276] eta: 0:23:40 lr: 3.987587930205867e-05 loss: 0.1686 (0.1705) time: 3.2372 data: 0.0085 max mem: 33300 +Epoch: [8] [3820/4276] eta: 0:23:09 lr: 3.987318135013584e-05 loss: 0.1524 (0.1705) time: 3.2585 data: 0.0084 max mem: 33300 +Epoch: [8] [3830/4276] eta: 0:22:39 lr: 3.987048337792926e-05 loss: 0.1524 (0.1705) time: 3.2454 data: 0.0084 max mem: 33300 +Epoch: [8] [3840/4276] eta: 0:22:09 lr: 3.986778538543725e-05 loss: 0.1551 (0.1705) time: 3.2318 data: 0.0081 max mem: 33300 +Epoch: [8] [3850/4276] eta: 0:21:39 lr: 3.986508737265813e-05 loss: 0.1576 (0.1704) time: 3.2478 data: 0.0078 max mem: 33300 +Epoch: [8] [3860/4276] eta: 0:21:08 lr: 3.986238933959023e-05 loss: 0.1614 (0.1704) time: 3.2400 data: 0.0082 max mem: 33300 +Epoch: [8] [3870/4276] eta: 0:20:38 lr: 3.985969128623186e-05 loss: 0.1728 (0.1704) time: 3.2373 data: 0.0085 max mem: 33300 +Epoch: [8] [3880/4276] eta: 0:20:08 lr: 3.985699321258136e-05 loss: 0.1701 (0.1704) time: 3.2346 data: 0.0085 max mem: 33300 +Epoch: [8] [3890/4276] eta: 0:19:37 lr: 3.985429511863703e-05 loss: 0.1604 (0.1704) time: 3.2362 data: 0.0086 max mem: 33300 +Epoch: [8] [3900/4276] eta: 0:19:07 lr: 3.98515970043972e-05 loss: 0.1690 (0.1704) time: 3.2121 data: 0.0083 max mem: 33300 +Epoch: [8] [3910/4276] eta: 0:18:37 lr: 3.98488988698602e-05 loss: 0.1601 (0.1704) time: 3.1801 data: 0.0083 max mem: 33300 +Epoch: [8] [3920/4276] eta: 0:18:06 lr: 3.984620071502433e-05 loss: 0.1525 (0.1704) time: 3.1790 data: 0.0087 max mem: 33300 +Epoch: [8] [3930/4276] eta: 0:17:36 lr: 3.984350253988792e-05 loss: 0.1617 (0.1704) time: 3.1963 data: 0.0090 max mem: 33300 +Epoch: [8] [3940/4276] eta: 0:17:05 lr: 3.984080434444929e-05 loss: 0.1615 (0.1704) time: 3.1939 data: 0.0094 max mem: 33300 +Epoch: [8] [3950/4276] eta: 0:16:35 lr: 3.983810612870676e-05 loss: 0.1562 (0.1703) time: 3.2030 data: 0.0093 max mem: 33300 +Epoch: [8] [3960/4276] eta: 0:16:05 lr: 3.983540789265867e-05 loss: 0.1598 (0.1703) time: 3.2303 data: 0.0085 max mem: 33300 +Epoch: [8] [3970/4276] eta: 0:15:34 lr: 3.983270963630329e-05 loss: 0.1676 (0.1704) time: 3.2170 data: 0.0081 max mem: 33300 +Epoch: [8] [3980/4276] eta: 0:15:04 lr: 3.983001135963898e-05 loss: 0.1556 (0.1703) time: 3.2042 data: 0.0084 max mem: 33300 +Epoch: [8] [3990/4276] eta: 0:14:33 lr: 3.9827313062664046e-05 loss: 0.1499 (0.1703) time: 3.2278 data: 0.0087 max mem: 33300 +Epoch: [8] [4000/4276] eta: 0:14:03 lr: 3.98246147453768e-05 loss: 0.1499 (0.1703) time: 3.2399 data: 0.0086 max mem: 33300 +Epoch: [8] [4010/4276] eta: 0:13:32 lr: 3.982191640777557e-05 loss: 0.1442 (0.1703) time: 3.2168 data: 0.0084 max mem: 33300 +Epoch: [8] [4020/4276] eta: 0:13:02 lr: 3.981921804985866e-05 loss: 0.1498 (0.1703) time: 3.1894 data: 0.0081 max mem: 33300 +Epoch: [8] [4030/4276] eta: 0:12:32 lr: 3.9816519671624404e-05 loss: 0.1620 (0.1703) time: 3.2358 data: 0.0079 max mem: 33300 +Epoch: [8] [4040/4276] eta: 0:12:01 lr: 3.981382127307111e-05 loss: 0.1697 (0.1704) time: 3.2966 data: 0.0082 max mem: 33300 +Epoch: [8] [4050/4276] eta: 0:11:31 lr: 3.98111228541971e-05 loss: 0.1634 (0.1703) time: 3.2931 data: 0.0083 max mem: 33300 +Epoch: [8] [4060/4276] eta: 0:11:00 lr: 3.980842441500068e-05 loss: 0.1637 (0.1703) time: 3.2924 data: 0.0085 max mem: 33300 +Epoch: [8] [4070/4276] eta: 0:10:30 lr: 3.980572595548018e-05 loss: 0.1665 (0.1703) time: 3.3369 data: 0.0087 max mem: 33300 +Epoch: [8] [4080/4276] eta: 0:09:59 lr: 3.9803027475633895e-05 loss: 0.1647 (0.1704) time: 3.3752 data: 0.0086 max mem: 33300 +Epoch: [8] [4090/4276] eta: 0:09:29 lr: 3.9800328975460166e-05 loss: 0.1821 (0.1704) time: 3.3874 data: 0.0084 max mem: 33300 +Epoch: [8] [4100/4276] eta: 0:08:58 lr: 3.979763045495729e-05 loss: 0.1821 (0.1704) time: 3.3636 data: 0.0087 max mem: 33300 +Epoch: [8] [4110/4276] eta: 0:08:28 lr: 3.9794931914123593e-05 loss: 0.1744 (0.1704) time: 3.3576 data: 0.0089 max mem: 33300 +Epoch: [8] [4120/4276] eta: 0:07:57 lr: 3.9792233352957394e-05 loss: 0.1744 (0.1704) time: 3.3289 data: 0.0085 max mem: 33300 +Epoch: [8] [4130/4276] eta: 0:07:27 lr: 3.978953477145699e-05 loss: 0.1626 (0.1704) time: 3.2753 data: 0.0091 max mem: 33300 +Epoch: [8] [4140/4276] eta: 0:06:56 lr: 3.9786836169620714e-05 loss: 0.1581 (0.1704) time: 3.3293 data: 0.0094 max mem: 33300 +Epoch: [8] [4150/4276] eta: 0:06:26 lr: 3.978413754744687e-05 loss: 0.1581 (0.1704) time: 3.3876 data: 0.0095 max mem: 33300 +Epoch: [8] [4160/4276] eta: 0:05:55 lr: 3.978143890493377e-05 loss: 0.1614 (0.1704) time: 3.3640 data: 0.0098 max mem: 33300 +Epoch: [8] [4170/4276] eta: 0:05:25 lr: 3.9778740242079735e-05 loss: 0.1651 (0.1704) time: 3.3503 data: 0.0102 max mem: 33300 +Epoch: [8] [4180/4276] eta: 0:04:54 lr: 3.9776041558883064e-05 loss: 0.1640 (0.1704) time: 3.3508 data: 0.0099 max mem: 33300 +Epoch: [8] [4190/4276] eta: 0:04:23 lr: 3.9773342855342085e-05 loss: 0.1569 (0.1704) time: 3.2961 data: 0.0088 max mem: 33300 +Epoch: [8] [4200/4276] eta: 0:03:53 lr: 3.977064413145512e-05 loss: 0.1698 (0.1704) time: 3.2837 data: 0.0095 max mem: 33300 +Epoch: [8] [4210/4276] eta: 0:03:22 lr: 3.9767945387220453e-05 loss: 0.1890 (0.1705) time: 3.2974 data: 0.0100 max mem: 33300 +Epoch: [8] [4220/4276] eta: 0:02:51 lr: 3.976524662263642e-05 loss: 0.1962 (0.1705) time: 3.3285 data: 0.0095 max mem: 33300 +Epoch: [8] [4230/4276] eta: 0:02:21 lr: 3.976254783770132e-05 loss: 0.1962 (0.1706) time: 3.3056 data: 0.0095 max mem: 33300 +Epoch: [8] [4240/4276] eta: 0:01:50 lr: 3.975984903241347e-05 loss: 0.1905 (0.1706) time: 3.3024 data: 0.0098 max mem: 33300 +Epoch: [8] [4250/4276] eta: 0:01:19 lr: 3.975715020677118e-05 loss: 0.1782 (0.1707) time: 3.3262 data: 0.0097 max mem: 33300 +Epoch: [8] [4260/4276] eta: 0:00:49 lr: 3.975445136077276e-05 loss: 0.1760 (0.1707) time: 3.3215 data: 0.0099 max mem: 33300 +Epoch: [8] [4270/4276] eta: 0:00:18 lr: 3.9751752494416536e-05 loss: 0.1781 (0.1707) time: 3.2737 data: 0.0089 max mem: 33300 +Epoch: [8] Total time: 3:38:58 +Test: [ 0/21770] eta: 11:12:23 time: 1.8532 data: 1.8129 max mem: 33300 +Test: [ 100/21770] eta: 0:20:54 time: 0.0398 data: 0.0013 max mem: 33300 +Test: [ 200/21770] eta: 0:17:37 time: 0.0402 data: 0.0013 max mem: 33300 +Test: [ 300/21770] eta: 0:16:30 time: 0.0400 data: 0.0012 max mem: 33300 +Test: [ 400/21770] eta: 0:15:56 time: 0.0408 data: 0.0013 max mem: 33300 +Test: [ 500/21770] eta: 0:15:32 time: 0.0400 data: 0.0013 max mem: 33300 +Test: [ 600/21770] eta: 0:15:14 time: 0.0401 data: 0.0012 max mem: 33300 +Test: [ 700/21770] eta: 0:14:58 time: 0.0393 data: 0.0012 max mem: 33300 +Test: [ 800/21770] eta: 0:14:46 time: 0.0399 data: 0.0013 max mem: 33300 +Test: [ 900/21770] eta: 0:14:36 time: 0.0393 data: 0.0013 max mem: 33300 +Test: [ 1000/21770] eta: 0:14:27 time: 0.0400 data: 0.0013 max mem: 33300 +Test: [ 1100/21770] eta: 0:14:19 time: 0.0400 data: 0.0013 max mem: 33300 +Test: [ 1200/21770] eta: 0:14:13 time: 0.0407 data: 0.0012 max mem: 33300 +Test: [ 1300/21770] eta: 0:14:07 time: 0.0405 data: 0.0012 max mem: 33300 +Test: [ 1400/21770] eta: 0:14:02 time: 0.0406 data: 0.0013 max mem: 33300 +Test: [ 1500/21770] eta: 0:13:57 time: 0.0408 data: 0.0012 max mem: 33300 +Test: [ 1600/21770] eta: 0:13:52 time: 0.0405 data: 0.0013 max mem: 33300 +Test: [ 1700/21770] eta: 0:13:47 time: 0.0410 data: 0.0012 max mem: 33300 +Test: [ 1800/21770] eta: 0:13:42 time: 0.0406 data: 0.0013 max mem: 33300 +Test: [ 1900/21770] eta: 0:13:37 time: 0.0403 data: 0.0012 max mem: 33300 +Test: [ 2000/21770] eta: 0:13:33 time: 0.0416 data: 0.0015 max mem: 33300 +Test: [ 2100/21770] eta: 0:13:27 time: 0.0392 data: 0.0013 max mem: 33300 +Test: [ 2200/21770] eta: 0:13:22 time: 0.0397 data: 0.0012 max mem: 33300 +Test: [ 2300/21770] eta: 0:13:17 time: 0.0402 data: 0.0012 max mem: 33300 +Test: [ 2400/21770] eta: 0:13:12 time: 0.0401 data: 0.0012 max mem: 33300 +Test: [ 2500/21770] eta: 0:13:08 time: 0.0407 data: 0.0012 max mem: 33300 +Test: [ 2600/21770] eta: 0:13:04 time: 0.0401 data: 0.0012 max mem: 33300 +Test: [ 2700/21770] eta: 0:12:59 time: 0.0398 data: 0.0012 max mem: 33300 +Test: [ 2800/21770] eta: 0:12:54 time: 0.0400 data: 0.0012 max mem: 33300 +Test: [ 2900/21770] eta: 0:12:50 time: 0.0400 data: 0.0012 max mem: 33300 +Test: [ 3000/21770] eta: 0:12:45 time: 0.0399 data: 0.0012 max mem: 33300 +Test: [ 3100/21770] eta: 0:12:41 time: 0.0405 data: 0.0012 max mem: 33300 +Test: [ 3200/21770] eta: 0:12:37 time: 0.0405 data: 0.0013 max mem: 33300 +Test: [ 3300/21770] eta: 0:12:32 time: 0.0399 data: 0.0013 max mem: 33300 +Test: [ 3400/21770] eta: 0:12:28 time: 0.0402 data: 0.0013 max mem: 33300 +Test: [ 3500/21770] eta: 0:12:23 time: 0.0400 data: 0.0013 max mem: 33300 +Test: [ 3600/21770] eta: 0:12:19 time: 0.0400 data: 0.0013 max mem: 33300 +Test: [ 3700/21770] eta: 0:12:15 time: 0.0402 data: 0.0013 max mem: 33300 +Test: [ 3800/21770] eta: 0:12:10 time: 0.0399 data: 0.0013 max mem: 33300 +Test: [ 3900/21770] eta: 0:12:06 time: 0.0401 data: 0.0012 max mem: 33300 +Test: [ 4000/21770] eta: 0:12:02 time: 0.0399 data: 0.0012 max mem: 33300 +Test: [ 4100/21770] eta: 0:11:57 time: 0.0400 data: 0.0012 max mem: 33300 +Test: [ 4200/21770] eta: 0:11:53 time: 0.0398 data: 0.0012 max mem: 33300 +Test: [ 4300/21770] eta: 0:11:49 time: 0.0399 data: 0.0012 max mem: 33300 +Test: [ 4400/21770] eta: 0:11:44 time: 0.0398 data: 0.0012 max mem: 33300 +Test: [ 4500/21770] eta: 0:11:40 time: 0.0400 data: 0.0012 max mem: 33300 +Test: [ 4600/21770] eta: 0:11:36 time: 0.0399 data: 0.0012 max mem: 33300 +Test: [ 4700/21770] eta: 0:11:32 time: 0.0407 data: 0.0012 max mem: 33300 +Test: [ 4800/21770] eta: 0:11:28 time: 0.0404 data: 0.0013 max mem: 33300 +Test: [ 4900/21770] eta: 0:11:23 time: 0.0407 data: 0.0012 max mem: 33300 +Test: [ 5000/21770] eta: 0:11:19 time: 0.0408 data: 0.0013 max mem: 33300 +Test: [ 5100/21770] eta: 0:11:15 time: 0.0409 data: 0.0013 max mem: 33300 +Test: [ 5200/21770] eta: 0:11:11 time: 0.0406 data: 0.0012 max mem: 33300 +Test: [ 5300/21770] eta: 0:11:07 time: 0.0403 data: 0.0012 max mem: 33300 +Test: [ 5400/21770] eta: 0:11:03 time: 0.0405 data: 0.0012 max mem: 33300 +Test: [ 5500/21770] eta: 0:10:59 time: 0.0408 data: 0.0013 max mem: 33300 +Test: [ 5600/21770] eta: 0:10:55 time: 0.0407 data: 0.0013 max mem: 33300 +Test: [ 5700/21770] eta: 0:10:51 time: 0.0402 data: 0.0012 max mem: 33300 +Test: [ 5800/21770] eta: 0:10:47 time: 0.0398 data: 0.0013 max mem: 33300 +Test: [ 5900/21770] eta: 0:10:43 time: 0.0395 data: 0.0012 max mem: 33300 +Test: [ 6000/21770] eta: 0:10:38 time: 0.0393 data: 0.0013 max mem: 33300 +Test: [ 6100/21770] eta: 0:10:34 time: 0.0395 data: 0.0012 max mem: 33300 +Test: [ 6200/21770] eta: 0:10:30 time: 0.0401 data: 0.0012 max mem: 33300 +Test: [ 6300/21770] eta: 0:10:26 time: 0.0402 data: 0.0013 max mem: 33300 +Test: [ 6400/21770] eta: 0:10:21 time: 0.0393 data: 0.0013 max mem: 33300 +Test: [ 6500/21770] eta: 0:10:17 time: 0.0393 data: 0.0013 max mem: 33300 +Test: [ 6600/21770] eta: 0:10:13 time: 0.0406 data: 0.0014 max mem: 33300 +Test: [ 6700/21770] eta: 0:10:09 time: 0.0401 data: 0.0013 max mem: 33300 +Test: [ 6800/21770] eta: 0:10:05 time: 0.0399 data: 0.0012 max mem: 33300 +Test: [ 6900/21770] eta: 0:10:01 time: 0.0400 data: 0.0013 max mem: 33300 +Test: [ 7000/21770] eta: 0:09:56 time: 0.0401 data: 0.0013 max mem: 33300 +Test: [ 7100/21770] eta: 0:09:52 time: 0.0400 data: 0.0012 max mem: 33300 +Test: [ 7200/21770] eta: 0:09:48 time: 0.0401 data: 0.0013 max mem: 33300 +Test: [ 7300/21770] eta: 0:09:44 time: 0.0400 data: 0.0013 max mem: 33300 +Test: [ 7400/21770] eta: 0:09:40 time: 0.0406 data: 0.0012 max mem: 33300 +Test: [ 7500/21770] eta: 0:09:36 time: 0.0410 data: 0.0012 max mem: 33300 +Test: [ 7600/21770] eta: 0:09:32 time: 0.0400 data: 0.0013 max mem: 33300 +Test: [ 7700/21770] eta: 0:09:28 time: 0.0397 data: 0.0012 max mem: 33300 +Test: [ 7800/21770] eta: 0:09:24 time: 0.0398 data: 0.0012 max mem: 33300 +Test: [ 7900/21770] eta: 0:09:20 time: 0.0400 data: 0.0012 max mem: 33300 +Test: [ 8000/21770] eta: 0:09:15 time: 0.0397 data: 0.0012 max mem: 33300 +Test: [ 8100/21770] eta: 0:09:11 time: 0.0401 data: 0.0013 max mem: 33300 +Test: [ 8200/21770] eta: 0:09:07 time: 0.0398 data: 0.0013 max mem: 33300 +Test: [ 8300/21770] eta: 0:09:03 time: 0.0400 data: 0.0013 max mem: 33300 +Test: [ 8400/21770] eta: 0:08:59 time: 0.0401 data: 0.0013 max mem: 33300 +Test: [ 8500/21770] eta: 0:08:55 time: 0.0400 data: 0.0013 max mem: 33300 +Test: [ 8600/21770] eta: 0:08:51 time: 0.0400 data: 0.0013 max mem: 33300 +Test: [ 8700/21770] eta: 0:08:47 time: 0.0399 data: 0.0013 max mem: 33300 +Test: [ 8800/21770] eta: 0:08:43 time: 0.0400 data: 0.0013 max mem: 33300 +Test: [ 8900/21770] eta: 0:08:39 time: 0.0402 data: 0.0013 max mem: 33300 +Test: [ 9000/21770] eta: 0:08:34 time: 0.0401 data: 0.0013 max mem: 33300 +Test: [ 9100/21770] eta: 0:08:30 time: 0.0400 data: 0.0013 max mem: 33300 +Test: [ 9200/21770] eta: 0:08:26 time: 0.0398 data: 0.0013 max mem: 33300 +Test: [ 9300/21770] eta: 0:08:22 time: 0.0401 data: 0.0013 max mem: 33300 +Test: [ 9400/21770] eta: 0:08:18 time: 0.0393 data: 0.0013 max mem: 33300 +Test: [ 9500/21770] eta: 0:08:14 time: 0.0393 data: 0.0012 max mem: 33300 +Test: [ 9600/21770] eta: 0:08:10 time: 0.0394 data: 0.0012 max mem: 33300 +Test: [ 9700/21770] eta: 0:08:06 time: 0.0399 data: 0.0012 max mem: 33300 +Test: [ 9800/21770] eta: 0:08:02 time: 0.0400 data: 0.0013 max mem: 33300 +Test: [ 9900/21770] eta: 0:07:58 time: 0.0400 data: 0.0012 max mem: 33300 +Test: [10000/21770] eta: 0:07:54 time: 0.0400 data: 0.0012 max mem: 33300 +Test: [10100/21770] eta: 0:07:50 time: 0.0401 data: 0.0013 max mem: 33300 +Test: [10200/21770] eta: 0:07:46 time: 0.0405 data: 0.0013 max mem: 33300 +Test: [10300/21770] eta: 0:07:42 time: 0.0403 data: 0.0013 max mem: 33300 +Test: [10400/21770] eta: 0:07:37 time: 0.0403 data: 0.0013 max mem: 33300 +Test: [10500/21770] eta: 0:07:33 time: 0.0405 data: 0.0012 max mem: 33300 +Test: [10600/21770] eta: 0:07:29 time: 0.0408 data: 0.0012 max mem: 33300 +Test: [10700/21770] eta: 0:07:25 time: 0.0400 data: 0.0013 max mem: 33300 +Test: [10800/21770] eta: 0:07:21 time: 0.0399 data: 0.0013 max mem: 33300 +Test: [10900/21770] eta: 0:07:17 time: 0.0412 data: 0.0012 max mem: 33300 +Test: [11000/21770] eta: 0:07:13 time: 0.0394 data: 0.0012 max mem: 33300 +Test: [11100/21770] eta: 0:07:09 time: 0.0401 data: 0.0012 max mem: 33300 +Test: [11200/21770] eta: 0:07:05 time: 0.0403 data: 0.0013 max mem: 33300 +Test: [11300/21770] eta: 0:07:01 time: 0.0399 data: 0.0013 max mem: 33300 +Test: [11400/21770] eta: 0:06:57 time: 0.0400 data: 0.0013 max mem: 33300 +Test: [11500/21770] eta: 0:06:53 time: 0.0400 data: 0.0012 max mem: 33300 +Test: [11600/21770] eta: 0:06:49 time: 0.0399 data: 0.0013 max mem: 33300 +Test: [11700/21770] eta: 0:06:45 time: 0.0400 data: 0.0013 max mem: 33300 +Test: [11800/21770] eta: 0:06:41 time: 0.0398 data: 0.0012 max mem: 33300 +Test: [11900/21770] eta: 0:06:37 time: 0.0401 data: 0.0013 max mem: 33300 +Test: [12000/21770] eta: 0:06:33 time: 0.0399 data: 0.0013 max mem: 33300 +Test: [12100/21770] eta: 0:06:29 time: 0.0398 data: 0.0012 max mem: 33300 +Test: [12200/21770] eta: 0:06:25 time: 0.0400 data: 0.0012 max mem: 33300 +Test: [12300/21770] eta: 0:06:21 time: 0.0408 data: 0.0013 max mem: 33300 +Test: [12400/21770] eta: 0:06:17 time: 0.0404 data: 0.0012 max mem: 33300 +Test: [12500/21770] eta: 0:06:13 time: 0.0413 data: 0.0013 max mem: 33300 +Test: [12600/21770] eta: 0:06:09 time: 0.0398 data: 0.0012 max mem: 33300 +Test: [12700/21770] eta: 0:06:05 time: 0.0407 data: 0.0012 max mem: 33300 +Test: [12800/21770] eta: 0:06:01 time: 0.0400 data: 0.0013 max mem: 33300 +Test: [12900/21770] eta: 0:05:57 time: 0.0400 data: 0.0013 max mem: 33300 +Test: [13000/21770] eta: 0:05:53 time: 0.0393 data: 0.0013 max mem: 33300 +Test: [13100/21770] eta: 0:05:49 time: 0.0400 data: 0.0013 max mem: 33300 +Test: [13200/21770] eta: 0:05:45 time: 0.0400 data: 0.0012 max mem: 33300 +Test: [13300/21770] eta: 0:05:40 time: 0.0400 data: 0.0012 max mem: 33300 +Test: [13400/21770] eta: 0:05:36 time: 0.0400 data: 0.0012 max mem: 33300 +Test: [13500/21770] eta: 0:05:32 time: 0.0393 data: 0.0013 max mem: 33300 +Test: [13600/21770] eta: 0:05:28 time: 0.0400 data: 0.0013 max mem: 33300 +Test: [13700/21770] eta: 0:05:24 time: 0.0399 data: 0.0013 max mem: 33300 +Test: [13800/21770] eta: 0:05:20 time: 0.0400 data: 0.0013 max mem: 33300 +Test: [13900/21770] eta: 0:05:16 time: 0.0399 data: 0.0013 max mem: 33300 +Test: [14000/21770] eta: 0:05:12 time: 0.0399 data: 0.0013 max mem: 33300 +Test: [14100/21770] eta: 0:05:08 time: 0.0400 data: 0.0013 max mem: 33300 +Test: [14200/21770] eta: 0:05:04 time: 0.0399 data: 0.0013 max mem: 33300 +Test: [14300/21770] eta: 0:05:00 time: 0.0397 data: 0.0013 max mem: 33300 +Test: [14400/21770] eta: 0:04:56 time: 0.0401 data: 0.0013 max mem: 33300 +Test: [14500/21770] eta: 0:04:52 time: 0.0400 data: 0.0013 max mem: 33300 +Test: [14600/21770] eta: 0:04:48 time: 0.0399 data: 0.0013 max mem: 33300 +Test: [14700/21770] eta: 0:04:44 time: 0.0400 data: 0.0012 max mem: 33300 +Test: [14800/21770] eta: 0:04:40 time: 0.0399 data: 0.0012 max mem: 33300 +Test: [14900/21770] eta: 0:04:36 time: 0.0402 data: 0.0012 max mem: 33300 +Test: [15000/21770] eta: 0:04:32 time: 0.0400 data: 0.0013 max mem: 33300 +Test: [15100/21770] eta: 0:04:28 time: 0.0403 data: 0.0013 max mem: 33300 +Test: [15200/21770] eta: 0:04:24 time: 0.0399 data: 0.0013 max mem: 33300 +Test: [15300/21770] eta: 0:04:20 time: 0.0401 data: 0.0012 max mem: 33300 +Test: [15400/21770] eta: 0:04:16 time: 0.0400 data: 0.0013 max mem: 33300 +Test: [15500/21770] eta: 0:04:12 time: 0.0401 data: 0.0013 max mem: 33300 +Test: [15600/21770] eta: 0:04:08 time: 0.0400 data: 0.0013 max mem: 33300 +Test: [15700/21770] eta: 0:04:04 time: 0.0401 data: 0.0013 max mem: 33300 +Test: [15800/21770] eta: 0:04:00 time: 0.0406 data: 0.0013 max mem: 33300 +Test: [15900/21770] eta: 0:03:56 time: 0.0401 data: 0.0013 max mem: 33300 +Test: [16000/21770] eta: 0:03:52 time: 0.0401 data: 0.0013 max mem: 33300 +Test: [16100/21770] eta: 0:03:47 time: 0.0405 data: 0.0013 max mem: 33300 +Test: [16200/21770] eta: 0:03:43 time: 0.0400 data: 0.0013 max mem: 33300 +Test: [16300/21770] eta: 0:03:39 time: 0.0400 data: 0.0012 max mem: 33300 +Test: [16400/21770] eta: 0:03:35 time: 0.0400 data: 0.0012 max mem: 33300 +Test: [16500/21770] eta: 0:03:31 time: 0.0396 data: 0.0013 max mem: 33300 +Test: [16600/21770] eta: 0:03:27 time: 0.0400 data: 0.0012 max mem: 33300 +Test: [16700/21770] eta: 0:03:23 time: 0.0398 data: 0.0012 max mem: 33300 +Test: [16800/21770] eta: 0:03:19 time: 0.0398 data: 0.0013 max mem: 33300 +Test: [16900/21770] eta: 0:03:15 time: 0.0399 data: 0.0012 max mem: 33300 +Test: [17000/21770] eta: 0:03:11 time: 0.0401 data: 0.0012 max mem: 33300 +Test: [17100/21770] eta: 0:03:07 time: 0.0398 data: 0.0012 max mem: 33300 +Test: [17200/21770] eta: 0:03:03 time: 0.0402 data: 0.0012 max mem: 33300 +Test: [17300/21770] eta: 0:02:59 time: 0.0399 data: 0.0012 max mem: 33300 +Test: [17400/21770] eta: 0:02:55 time: 0.0400 data: 0.0012 max mem: 33300 +Test: [17500/21770] eta: 0:02:51 time: 0.0392 data: 0.0013 max mem: 33300 +Test: [17600/21770] eta: 0:02:47 time: 0.0394 data: 0.0012 max mem: 33300 +Test: [17700/21770] eta: 0:02:43 time: 0.0400 data: 0.0013 max mem: 33300 +Test: [17800/21770] eta: 0:02:39 time: 0.0399 data: 0.0013 max mem: 33300 +Test: [17900/21770] eta: 0:02:35 time: 0.0399 data: 0.0013 max mem: 33300 +Test: [18000/21770] eta: 0:02:31 time: 0.0399 data: 0.0013 max mem: 33300 +Test: [18100/21770] eta: 0:02:27 time: 0.0394 data: 0.0013 max mem: 33300 +Test: [18200/21770] eta: 0:02:23 time: 0.0401 data: 0.0013 max mem: 33300 +Test: [18300/21770] eta: 0:02:19 time: 0.0399 data: 0.0013 max mem: 33300 +Test: [18400/21770] eta: 0:02:15 time: 0.0400 data: 0.0012 max mem: 33300 +Test: [18500/21770] eta: 0:02:11 time: 0.0399 data: 0.0013 max mem: 33300 +Test: [18600/21770] eta: 0:02:07 time: 0.0401 data: 0.0012 max mem: 33300 +Test: [18700/21770] eta: 0:02:03 time: 0.0399 data: 0.0012 max mem: 33300 +Test: [18800/21770] eta: 0:01:59 time: 0.0401 data: 0.0013 max mem: 33300 +Test: [18900/21770] eta: 0:01:55 time: 0.0398 data: 0.0013 max mem: 33300 +Test: [19000/21770] eta: 0:01:51 time: 0.0392 data: 0.0013 max mem: 33300 +Test: [19100/21770] eta: 0:01:47 time: 0.0395 data: 0.0013 max mem: 33300 +Test: [19200/21770] eta: 0:01:43 time: 0.0398 data: 0.0013 max mem: 33300 +Test: [19300/21770] eta: 0:01:39 time: 0.0391 data: 0.0012 max mem: 33300 +Test: [19400/21770] eta: 0:01:35 time: 0.0392 data: 0.0013 max mem: 33300 +Test: [19500/21770] eta: 0:01:31 time: 0.0395 data: 0.0013 max mem: 33300 +Test: [19600/21770] eta: 0:01:27 time: 0.0392 data: 0.0012 max mem: 33300 +Test: [19700/21770] eta: 0:01:23 time: 0.0393 data: 0.0013 max mem: 33300 +Test: [19800/21770] eta: 0:01:19 time: 0.0391 data: 0.0012 max mem: 33300 +Test: [19900/21770] eta: 0:01:15 time: 0.0400 data: 0.0012 max mem: 33300 +Test: [20000/21770] eta: 0:01:11 time: 0.0399 data: 0.0012 max mem: 33300 +Test: [20100/21770] eta: 0:01:06 time: 0.0401 data: 0.0012 max mem: 33300 +Test: [20200/21770] eta: 0:01:02 time: 0.0399 data: 0.0012 max mem: 33300 +Test: [20300/21770] eta: 0:00:58 time: 0.0402 data: 0.0013 max mem: 33300 +Test: [20400/21770] eta: 0:00:54 time: 0.0399 data: 0.0013 max mem: 33300 +Test: [20500/21770] eta: 0:00:50 time: 0.0393 data: 0.0013 max mem: 33300 +Test: [20600/21770] eta: 0:00:46 time: 0.0393 data: 0.0013 max mem: 33300 +Test: [20700/21770] eta: 0:00:42 time: 0.0392 data: 0.0013 max mem: 33300 +Test: [20800/21770] eta: 0:00:38 time: 0.0397 data: 0.0013 max mem: 33300 +Test: [20900/21770] eta: 0:00:34 time: 0.0400 data: 0.0013 max mem: 33300 +Test: [21000/21770] eta: 0:00:30 time: 0.0397 data: 0.0013 max mem: 33300 +Test: [21100/21770] eta: 0:00:26 time: 0.0399 data: 0.0013 max mem: 33300 +Test: [21200/21770] eta: 0:00:22 time: 0.0400 data: 0.0013 max mem: 33300 +Test: [21300/21770] eta: 0:00:18 time: 0.0399 data: 0.0013 max mem: 33300 +Test: [21400/21770] eta: 0:00:14 time: 0.0400 data: 0.0013 max mem: 33300 +Test: [21500/21770] eta: 0:00:10 time: 0.0404 data: 0.0011 max mem: 33300 +Test: [21600/21770] eta: 0:00:06 time: 0.0406 data: 0.0012 max mem: 33300 +Test: [21700/21770] eta: 0:00:02 time: 0.0409 data: 0.0012 max mem: 33300 +Test: Total time: 0:14:33 +Final results: +Mean IoU is 0.00 + + precision@0.5 = 0.00 + precision@0.6 = 0.00 + precision@0.7 = 0.00 + precision@0.8 = 0.00 + precision@0.9 = 0.00 + overall IoU = 0.00 + mean IoU = 0.00 + +Mean accuracy for one-to-zero sample is 100.00 + +Average object IoU 0.0 +Overall IoU 0.0 +Epoch: [9] [ 0/4276] eta: 6:25:28 lr: 3.9750133164830336e-05 loss: 0.1393 (0.1393) time: 5.4089 data: 2.0295 max mem: 33300 +Epoch: [9] [ 10/4276] eta: 4:05:27 lr: 3.9747434265898074e-05 loss: 0.1721 (0.1722) time: 3.4523 data: 0.1924 max mem: 33300 +Epoch: [9] [ 20/4276] eta: 3:59:59 lr: 3.9744735346603614e-05 loss: 0.1561 (0.1701) time: 3.2821 data: 0.0083 max mem: 33300 +Epoch: [9] [ 30/4276] eta: 3:55:31 lr: 3.974203640694524e-05 loss: 0.1546 (0.1716) time: 3.2601 data: 0.0084 max mem: 33300 +Epoch: [9] [ 40/4276] eta: 3:54:22 lr: 3.973933744692129e-05 loss: 0.1569 (0.1689) time: 3.2532 data: 0.0091 max mem: 33300 +Epoch: [9] [ 50/4276] eta: 3:52:41 lr: 3.973663846653005e-05 loss: 0.1569 (0.1684) time: 3.2657 data: 0.0088 max mem: 33300 +Epoch: [9] [ 60/4276] eta: 3:51:13 lr: 3.973393946576984e-05 loss: 0.1510 (0.1675) time: 3.2310 data: 0.0083 max mem: 33300 +Epoch: [9] [ 70/4276] eta: 3:50:32 lr: 3.973124044463898e-05 loss: 0.1464 (0.1662) time: 3.2503 data: 0.0087 max mem: 33300 +Epoch: [9] [ 80/4276] eta: 3:49:34 lr: 3.972854140313575e-05 loss: 0.1550 (0.1674) time: 3.2586 data: 0.0089 max mem: 33300 +Epoch: [9] [ 90/4276] eta: 3:48:18 lr: 3.972584234125848e-05 loss: 0.1506 (0.1655) time: 3.2153 data: 0.0087 max mem: 33300 +Epoch: [9] [ 100/4276] eta: 3:48:05 lr: 3.972314325900547e-05 loss: 0.1506 (0.1671) time: 3.2545 data: 0.0083 max mem: 33300 +Epoch: [9] [ 110/4276] eta: 3:47:10 lr: 3.972044415637503e-05 loss: 0.1755 (0.1673) time: 3.2679 data: 0.0080 max mem: 33300 +Epoch: [9] [ 120/4276] eta: 3:46:47 lr: 3.971774503336547e-05 loss: 0.1542 (0.1664) time: 3.2587 data: 0.0084 max mem: 33300 +Epoch: [9] [ 130/4276] eta: 3:46:14 lr: 3.97150458899751e-05 loss: 0.1572 (0.1674) time: 3.2873 data: 0.0089 max mem: 33300 +Epoch: [9] [ 140/4276] eta: 3:45:38 lr: 3.9712346726202215e-05 loss: 0.1584 (0.1669) time: 3.2681 data: 0.0091 max mem: 33300 +Epoch: [9] [ 150/4276] eta: 3:45:05 lr: 3.970964754204513e-05 loss: 0.1529 (0.1663) time: 3.2673 data: 0.0089 max mem: 33300 +Epoch: [9] [ 160/4276] eta: 3:44:11 lr: 3.970694833750216e-05 loss: 0.1579 (0.1656) time: 3.2312 data: 0.0086 max mem: 33300 +Epoch: [9] [ 170/4276] eta: 3:43:33 lr: 3.970424911257159e-05 loss: 0.1617 (0.1659) time: 3.2189 data: 0.0087 max mem: 33300 +Epoch: [9] [ 180/4276] eta: 3:42:46 lr: 3.970154986725174e-05 loss: 0.1632 (0.1669) time: 3.2253 data: 0.0087 max mem: 33300 +Epoch: [9] [ 190/4276] eta: 3:42:18 lr: 3.9698850601540915e-05 loss: 0.1788 (0.1675) time: 3.2429 data: 0.0086 max mem: 33300 +Epoch: [9] [ 200/4276] eta: 3:42:16 lr: 3.969615131543742e-05 loss: 0.1773 (0.1684) time: 3.3501 data: 0.0085 max mem: 33300 +Epoch: [9] [ 210/4276] eta: 3:41:59 lr: 3.9693452008939556e-05 loss: 0.1773 (0.1687) time: 3.3856 data: 0.0090 max mem: 33300 +Epoch: [9] [ 220/4276] eta: 3:41:52 lr: 3.969075268204563e-05 loss: 0.1784 (0.1692) time: 3.3860 data: 0.0096 max mem: 33300 +Epoch: [9] [ 230/4276] eta: 3:41:47 lr: 3.968805333475396e-05 loss: 0.1711 (0.1686) time: 3.4287 data: 0.0093 max mem: 33300 +Epoch: [9] [ 240/4276] eta: 3:41:26 lr: 3.9685353967062824e-05 loss: 0.1647 (0.1689) time: 3.3982 data: 0.0091 max mem: 33300 +Epoch: [9] [ 250/4276] eta: 3:41:14 lr: 3.9682654578970546e-05 loss: 0.1739 (0.1702) time: 3.3900 data: 0.0093 max mem: 33300 +Epoch: [9] [ 260/4276] eta: 3:40:49 lr: 3.967995517047542e-05 loss: 0.1770 (0.1703) time: 3.3879 data: 0.0092 max mem: 33300 +Epoch: [9] [ 270/4276] eta: 3:40:27 lr: 3.967725574157576e-05 loss: 0.1717 (0.1703) time: 3.3613 data: 0.0090 max mem: 33300 +Epoch: [9] [ 280/4276] eta: 3:40:11 lr: 3.967455629226986e-05 loss: 0.1598 (0.1700) time: 3.3963 data: 0.0096 max mem: 33300 +Epoch: [9] [ 290/4276] eta: 3:39:39 lr: 3.967185682255603e-05 loss: 0.1598 (0.1694) time: 3.3673 data: 0.0100 max mem: 33300 +Epoch: [9] [ 300/4276] eta: 3:39:09 lr: 3.966915733243255e-05 loss: 0.1523 (0.1692) time: 3.3220 data: 0.0094 max mem: 33300 +Epoch: [9] [ 310/4276] eta: 3:38:54 lr: 3.966645782189776e-05 loss: 0.1519 (0.1688) time: 3.3903 data: 0.0089 max mem: 33300 +Epoch: [9] [ 320/4276] eta: 3:38:20 lr: 3.966375829094994e-05 loss: 0.1633 (0.1693) time: 3.3769 data: 0.0086 max mem: 33300 +Epoch: [9] [ 330/4276] eta: 3:37:59 lr: 3.9661058739587384e-05 loss: 0.1713 (0.1693) time: 3.3610 data: 0.0085 max mem: 33300 +Epoch: [9] [ 340/4276] eta: 3:37:35 lr: 3.9658359167808415e-05 loss: 0.1615 (0.1689) time: 3.4014 data: 0.0083 max mem: 33300 +Epoch: [9] [ 350/4276] eta: 3:37:06 lr: 3.9655659575611324e-05 loss: 0.1435 (0.1687) time: 3.3733 data: 0.0083 max mem: 33300 +Epoch: [9] [ 360/4276] eta: 3:36:40 lr: 3.965295996299441e-05 loss: 0.1891 (0.1694) time: 3.3725 data: 0.0086 max mem: 33300 +Epoch: [9] [ 370/4276] eta: 3:36:12 lr: 3.965026032995597e-05 loss: 0.1612 (0.1687) time: 3.3778 data: 0.0085 max mem: 33300 +Epoch: [9] [ 380/4276] eta: 3:35:43 lr: 3.964756067649432e-05 loss: 0.1467 (0.1687) time: 3.3643 data: 0.0087 max mem: 33300 +Epoch: [9] [ 390/4276] eta: 3:35:12 lr: 3.9644861002607754e-05 loss: 0.1520 (0.1686) time: 3.3494 data: 0.0089 max mem: 33300 +Epoch: [9] [ 400/4276] eta: 3:34:43 lr: 3.964216130829456e-05 loss: 0.1560 (0.1687) time: 3.3574 data: 0.0093 max mem: 33300 +Epoch: [9] [ 410/4276] eta: 3:34:09 lr: 3.9639461593553044e-05 loss: 0.1613 (0.1685) time: 3.3429 data: 0.0093 max mem: 33300 +Epoch: [9] [ 420/4276] eta: 3:33:39 lr: 3.9636761858381515e-05 loss: 0.1551 (0.1683) time: 3.3377 data: 0.0091 max mem: 33300 +Epoch: [9] [ 430/4276] eta: 3:32:59 lr: 3.963406210277826e-05 loss: 0.1587 (0.1683) time: 3.3057 data: 0.0092 max mem: 33300 +Epoch: [9] [ 440/4276] eta: 3:32:25 lr: 3.9631362326741595e-05 loss: 0.1587 (0.1682) time: 3.2812 data: 0.0093 max mem: 33300 +Epoch: [9] [ 450/4276] eta: 3:32:00 lr: 3.9628662530269796e-05 loss: 0.1668 (0.1684) time: 3.3678 data: 0.0091 max mem: 33300 +Epoch: [9] [ 460/4276] eta: 3:31:19 lr: 3.962596271336118e-05 loss: 0.1580 (0.1679) time: 3.3206 data: 0.0091 max mem: 33300 +Epoch: [9] [ 470/4276] eta: 3:30:58 lr: 3.962326287601403e-05 loss: 0.1444 (0.1678) time: 3.3510 data: 0.0092 max mem: 33300 +Epoch: [9] [ 480/4276] eta: 3:30:20 lr: 3.9620563018226655e-05 loss: 0.1421 (0.1674) time: 3.3739 data: 0.0092 max mem: 33300 +Epoch: [9] [ 490/4276] eta: 3:29:48 lr: 3.9617863139997346e-05 loss: 0.1364 (0.1669) time: 3.3056 data: 0.0093 max mem: 33300 +Epoch: [9] [ 500/4276] eta: 3:29:15 lr: 3.961516324132441e-05 loss: 0.1364 (0.1667) time: 3.3364 data: 0.0097 max mem: 33300 +Epoch: [9] [ 510/4276] eta: 3:28:41 lr: 3.961246332220614e-05 loss: 0.1510 (0.1664) time: 3.3189 data: 0.0099 max mem: 33300 +Epoch: [9] [ 520/4276] eta: 3:28:11 lr: 3.960976338264082e-05 loss: 0.1540 (0.1665) time: 3.3406 data: 0.0097 max mem: 33300 +Epoch: [9] [ 530/4276] eta: 3:27:33 lr: 3.960706342262676e-05 loss: 0.1700 (0.1664) time: 3.3164 data: 0.0095 max mem: 33300 +Epoch: [9] [ 540/4276] eta: 3:27:04 lr: 3.960436344216226e-05 loss: 0.1513 (0.1661) time: 3.3181 data: 0.0094 max mem: 33300 +Epoch: [9] [ 550/4276] eta: 3:26:29 lr: 3.96016634412456e-05 loss: 0.1581 (0.1662) time: 3.3399 data: 0.0092 max mem: 33300 +Epoch: [9] [ 560/4276] eta: 3:25:58 lr: 3.959896341987509e-05 loss: 0.1679 (0.1662) time: 3.3347 data: 0.0087 max mem: 33300 +Epoch: [9] [ 570/4276] eta: 3:25:25 lr: 3.959626337804902e-05 loss: 0.1677 (0.1662) time: 3.3419 data: 0.0088 max mem: 33300 +Epoch: [9] [ 580/4276] eta: 3:24:50 lr: 3.959356331576568e-05 loss: 0.1596 (0.1661) time: 3.3133 data: 0.0093 max mem: 33300 +Epoch: [9] [ 590/4276] eta: 3:24:20 lr: 3.9590863233023385e-05 loss: 0.1453 (0.1658) time: 3.3404 data: 0.0095 max mem: 33300 +Epoch: [9] [ 600/4276] eta: 3:23:42 lr: 3.9588163129820397e-05 loss: 0.1473 (0.1658) time: 3.3135 data: 0.0095 max mem: 33300 +Epoch: [9] [ 610/4276] eta: 3:23:14 lr: 3.9585463006155044e-05 loss: 0.1626 (0.1657) time: 3.3301 data: 0.0093 max mem: 33300 +Epoch: [9] [ 620/4276] eta: 3:22:37 lr: 3.95827628620256e-05 loss: 0.1541 (0.1656) time: 3.3359 data: 0.0087 max mem: 33300 +Epoch: [9] [ 630/4276] eta: 3:22:01 lr: 3.9580062697430354e-05 loss: 0.1541 (0.1658) time: 3.2681 data: 0.0085 max mem: 33300 +Epoch: [9] [ 640/4276] eta: 3:21:24 lr: 3.9577362512367615e-05 loss: 0.1475 (0.1656) time: 3.2674 data: 0.0087 max mem: 33300 +Epoch: [9] [ 650/4276] eta: 3:20:37 lr: 3.957466230683567e-05 loss: 0.1488 (0.1656) time: 3.1746 data: 0.0091 max mem: 33300 +Epoch: [9] [ 660/4276] eta: 3:19:53 lr: 3.957196208083281e-05 loss: 0.1627 (0.1657) time: 3.0960 data: 0.0087 max mem: 33300 +Epoch: [9] [ 670/4276] eta: 3:19:08 lr: 3.956926183435734e-05 loss: 0.1688 (0.1657) time: 3.1104 data: 0.0081 max mem: 33300 +Epoch: [9] [ 680/4276] eta: 3:18:24 lr: 3.9566561567407525e-05 loss: 0.1648 (0.1655) time: 3.1105 data: 0.0081 max mem: 33300 +Epoch: [9] [ 690/4276] eta: 3:17:41 lr: 3.956386127998169e-05 loss: 0.1648 (0.1656) time: 3.1054 data: 0.0082 max mem: 33300 +Epoch: [9] [ 700/4276] eta: 3:16:58 lr: 3.9561160972078104e-05 loss: 0.1581 (0.1656) time: 3.1084 data: 0.0085 max mem: 33300 +Epoch: [9] [ 710/4276] eta: 3:16:15 lr: 3.9558460643695066e-05 loss: 0.1522 (0.1656) time: 3.1096 data: 0.0087 max mem: 33300 +Epoch: [9] [ 720/4276] eta: 3:15:32 lr: 3.955576029483087e-05 loss: 0.1522 (0.1655) time: 3.1046 data: 0.0087 max mem: 33300 +Epoch: [9] [ 730/4276] eta: 3:14:50 lr: 3.95530599254838e-05 loss: 0.1501 (0.1655) time: 3.1066 data: 0.0084 max mem: 33300 +Epoch: [9] [ 740/4276] eta: 3:14:07 lr: 3.955035953565216e-05 loss: 0.1599 (0.1655) time: 3.1076 data: 0.0081 max mem: 33300 +Epoch: [9] [ 750/4276] eta: 3:13:27 lr: 3.954765912533423e-05 loss: 0.1567 (0.1656) time: 3.1146 data: 0.0080 max mem: 33300 +Epoch: [9] [ 760/4276] eta: 3:12:45 lr: 3.954495869452829e-05 loss: 0.1505 (0.1654) time: 3.1136 data: 0.0083 max mem: 33300 +Epoch: [9] [ 770/4276] eta: 3:12:04 lr: 3.9542258243232654e-05 loss: 0.1543 (0.1655) time: 3.1049 data: 0.0084 max mem: 33300 +Epoch: [9] [ 780/4276] eta: 3:11:22 lr: 3.9539557771445596e-05 loss: 0.1646 (0.1655) time: 3.1026 data: 0.0087 max mem: 33300 +Epoch: [9] [ 790/4276] eta: 3:10:41 lr: 3.953685727916541e-05 loss: 0.1714 (0.1656) time: 3.0948 data: 0.0088 max mem: 33300 +Epoch: [9] [ 800/4276] eta: 3:10:00 lr: 3.953415676639038e-05 loss: 0.1664 (0.1655) time: 3.0952 data: 0.0086 max mem: 33300 +Epoch: [9] [ 810/4276] eta: 3:09:19 lr: 3.95314562331188e-05 loss: 0.1524 (0.1655) time: 3.0914 data: 0.0092 max mem: 33300 +Epoch: [9] [ 820/4276] eta: 3:08:39 lr: 3.952875567934897e-05 loss: 0.1453 (0.1655) time: 3.0943 data: 0.0089 max mem: 33300 +Epoch: [9] [ 830/4276] eta: 3:07:59 lr: 3.952605510507915e-05 loss: 0.1552 (0.1657) time: 3.1069 data: 0.0080 max mem: 33300 +Epoch: [9] [ 840/4276] eta: 3:07:20 lr: 3.952335451030765e-05 loss: 0.1613 (0.1659) time: 3.1087 data: 0.0078 max mem: 33300 +Epoch: [9] [ 850/4276] eta: 3:06:41 lr: 3.952065389503276e-05 loss: 0.1613 (0.1659) time: 3.1143 data: 0.0082 max mem: 33300 +Epoch: [9] [ 860/4276] eta: 3:06:03 lr: 3.951795325925275e-05 loss: 0.1669 (0.1660) time: 3.1228 data: 0.0086 max mem: 33300 +Epoch: [9] [ 870/4276] eta: 3:05:24 lr: 3.9515252602965926e-05 loss: 0.1629 (0.1661) time: 3.1142 data: 0.0081 max mem: 33300 +Epoch: [9] [ 880/4276] eta: 3:04:45 lr: 3.951255192617056e-05 loss: 0.1615 (0.1662) time: 3.1045 data: 0.0077 max mem: 33300 +Epoch: [9] [ 890/4276] eta: 3:04:07 lr: 3.950985122886494e-05 loss: 0.1733 (0.1663) time: 3.1133 data: 0.0081 max mem: 33300 +Epoch: [9] [ 900/4276] eta: 3:03:28 lr: 3.950715051104737e-05 loss: 0.1658 (0.1663) time: 3.1121 data: 0.0083 max mem: 33300 +Epoch: [9] [ 910/4276] eta: 3:02:50 lr: 3.950444977271612e-05 loss: 0.1625 (0.1663) time: 3.1097 data: 0.0080 max mem: 33300 +Epoch: [9] [ 920/4276] eta: 3:02:12 lr: 3.9501749013869476e-05 loss: 0.1625 (0.1664) time: 3.1089 data: 0.0078 max mem: 33300 +Epoch: [9] [ 930/4276] eta: 3:01:34 lr: 3.949904823450573e-05 loss: 0.1669 (0.1663) time: 3.1108 data: 0.0078 max mem: 33300 +Epoch: [9] [ 940/4276] eta: 3:00:56 lr: 3.949634743462316e-05 loss: 0.1633 (0.1661) time: 3.1133 data: 0.0079 max mem: 33300 +Epoch: [9] [ 950/4276] eta: 3:00:19 lr: 3.9493646614220056e-05 loss: 0.1565 (0.1662) time: 3.1162 data: 0.0079 max mem: 33300 +Epoch: [9] [ 960/4276] eta: 2:59:41 lr: 3.94909457732947e-05 loss: 0.1744 (0.1664) time: 3.1045 data: 0.0082 max mem: 33300 +Epoch: [9] [ 970/4276] eta: 2:59:03 lr: 3.948824491184539e-05 loss: 0.1745 (0.1664) time: 3.0818 data: 0.0083 max mem: 33300 +Epoch: [9] [ 980/4276] eta: 2:58:26 lr: 3.9485544029870394e-05 loss: 0.1648 (0.1665) time: 3.0969 data: 0.0078 max mem: 33300 +Epoch: [9] [ 990/4276] eta: 2:57:48 lr: 3.9482843127368e-05 loss: 0.1648 (0.1664) time: 3.1118 data: 0.0079 max mem: 33300 +Epoch: [9] [1000/4276] eta: 2:57:12 lr: 3.948014220433649e-05 loss: 0.1618 (0.1665) time: 3.1155 data: 0.0076 max mem: 33300 +Epoch: [9] [1010/4276] eta: 2:56:36 lr: 3.947744126077415e-05 loss: 0.1585 (0.1665) time: 3.1243 data: 0.0072 max mem: 33300 +Epoch: [9] [1020/4276] eta: 2:55:59 lr: 3.9474740296679266e-05 loss: 0.1530 (0.1664) time: 3.1135 data: 0.0074 max mem: 33300 +Epoch: [9] [1030/4276] eta: 2:55:22 lr: 3.947203931205012e-05 loss: 0.1578 (0.1665) time: 3.1125 data: 0.0076 max mem: 33300 +Epoch: [9] [1040/4276] eta: 2:54:45 lr: 3.9469338306884986e-05 loss: 0.1506 (0.1664) time: 3.1081 data: 0.0081 max mem: 33300 +Epoch: [9] [1050/4276] eta: 2:54:09 lr: 3.946663728118216e-05 loss: 0.1587 (0.1666) time: 3.1019 data: 0.0079 max mem: 33300 +Epoch: [9] [1060/4276] eta: 2:53:32 lr: 3.946393623493992e-05 loss: 0.1633 (0.1666) time: 3.1052 data: 0.0073 max mem: 33300 +Epoch: [9] [1070/4276] eta: 2:52:56 lr: 3.9461235168156535e-05 loss: 0.1670 (0.1666) time: 3.1054 data: 0.0073 max mem: 33300 +Epoch: [9] [1080/4276] eta: 2:52:20 lr: 3.945853408083031e-05 loss: 0.1684 (0.1666) time: 3.1085 data: 0.0074 max mem: 33300 +Epoch: [9] [1090/4276] eta: 2:51:44 lr: 3.94558329729595e-05 loss: 0.1684 (0.1665) time: 3.0998 data: 0.0080 max mem: 33300 +Epoch: [9] [1100/4276] eta: 2:51:07 lr: 3.945313184454241e-05 loss: 0.1610 (0.1666) time: 3.0881 data: 0.0091 max mem: 33300 +Epoch: [9] [1110/4276] eta: 2:50:31 lr: 3.94504306955773e-05 loss: 0.1611 (0.1666) time: 3.0952 data: 0.0087 max mem: 33300 +Epoch: [9] [1120/4276] eta: 2:49:55 lr: 3.944772952606247e-05 loss: 0.1690 (0.1666) time: 3.1098 data: 0.0082 max mem: 33300 +Epoch: [9] [1130/4276] eta: 2:49:20 lr: 3.944502833599619e-05 loss: 0.1588 (0.1663) time: 3.1118 data: 0.0085 max mem: 33300 +Epoch: [9] [1140/4276] eta: 2:48:44 lr: 3.9442327125376727e-05 loss: 0.1486 (0.1662) time: 3.1070 data: 0.0088 max mem: 33300 +Epoch: [9] [1150/4276] eta: 2:48:08 lr: 3.943962589420238e-05 loss: 0.1554 (0.1661) time: 3.1024 data: 0.0086 max mem: 33300 +Epoch: [9] [1160/4276] eta: 2:47:32 lr: 3.943692464247143e-05 loss: 0.1658 (0.1663) time: 3.1017 data: 0.0081 max mem: 33300 +Epoch: [9] [1170/4276] eta: 2:46:57 lr: 3.943422337018214e-05 loss: 0.1875 (0.1665) time: 3.0950 data: 0.0083 max mem: 33300 +Epoch: [9] [1180/4276] eta: 2:46:21 lr: 3.94315220773328e-05 loss: 0.1840 (0.1665) time: 3.0871 data: 0.0082 max mem: 33300 +Epoch: [9] [1190/4276] eta: 2:45:46 lr: 3.942882076392168e-05 loss: 0.1570 (0.1665) time: 3.1006 data: 0.0079 max mem: 33300 +Epoch: [9] [1200/4276] eta: 2:45:10 lr: 3.942611942994707e-05 loss: 0.1570 (0.1664) time: 3.1061 data: 0.0075 max mem: 33300 +Epoch: [9] [1210/4276] eta: 2:44:35 lr: 3.9423418075407246e-05 loss: 0.1600 (0.1665) time: 3.1089 data: 0.0074 max mem: 33300 +Epoch: [9] [1220/4276] eta: 2:44:00 lr: 3.942071670030047e-05 loss: 0.1680 (0.1665) time: 3.1023 data: 0.0074 max mem: 33300 +Epoch: [9] [1230/4276] eta: 2:43:23 lr: 3.941801530462505e-05 loss: 0.1680 (0.1666) time: 3.0672 data: 0.0082 max mem: 33300 +Epoch: [9] [1240/4276] eta: 2:42:47 lr: 3.941531388837922e-05 loss: 0.1581 (0.1667) time: 3.0419 data: 0.0083 max mem: 33300 +Epoch: [9] [1250/4276] eta: 2:42:10 lr: 3.941261245156129e-05 loss: 0.1633 (0.1667) time: 3.0343 data: 0.0078 max mem: 33300 +Epoch: [9] [1260/4276] eta: 2:41:34 lr: 3.940991099416953e-05 loss: 0.1506 (0.1666) time: 3.0428 data: 0.0079 max mem: 33300 +Epoch: [9] [1270/4276] eta: 2:40:58 lr: 3.940720951620221e-05 loss: 0.1506 (0.1665) time: 3.0435 data: 0.0079 max mem: 33300 +Epoch: [9] [1280/4276] eta: 2:40:23 lr: 3.940450801765761e-05 loss: 0.1751 (0.1667) time: 3.0704 data: 0.0085 max mem: 33300 +Epoch: [9] [1290/4276] eta: 2:39:48 lr: 3.9401806498534e-05 loss: 0.1751 (0.1668) time: 3.1055 data: 0.0088 max mem: 33300 +Epoch: [9] [1300/4276] eta: 2:39:14 lr: 3.939910495882967e-05 loss: 0.1543 (0.1667) time: 3.1080 data: 0.0084 max mem: 33300 +Epoch: [9] [1310/4276] eta: 2:38:40 lr: 3.939640339854289e-05 loss: 0.1384 (0.1666) time: 3.1097 data: 0.0080 max mem: 33300 +Epoch: [9] [1320/4276] eta: 2:38:05 lr: 3.9393701817671924e-05 loss: 0.1643 (0.1667) time: 3.1185 data: 0.0083 max mem: 33300 +Epoch: [9] [1330/4276] eta: 2:37:31 lr: 3.939100021621505e-05 loss: 0.1616 (0.1666) time: 3.1137 data: 0.0085 max mem: 33300 +Epoch: [9] [1340/4276] eta: 2:36:56 lr: 3.9388298594170544e-05 loss: 0.1495 (0.1666) time: 3.0917 data: 0.0087 max mem: 33300 +Epoch: [9] [1350/4276] eta: 2:36:22 lr: 3.938559695153669e-05 loss: 0.1683 (0.1666) time: 3.0890 data: 0.0086 max mem: 33300 +Epoch: [9] [1360/4276] eta: 2:35:47 lr: 3.938289528831176e-05 loss: 0.1693 (0.1666) time: 3.0952 data: 0.0078 max mem: 33300 +Epoch: [9] [1370/4276] eta: 2:35:13 lr: 3.938019360449401e-05 loss: 0.1586 (0.1665) time: 3.1002 data: 0.0078 max mem: 33300 +Epoch: [9] [1380/4276] eta: 2:34:39 lr: 3.937749190008173e-05 loss: 0.1684 (0.1667) time: 3.1028 data: 0.0078 max mem: 33300 +Epoch: [9] [1390/4276] eta: 2:34:05 lr: 3.9374790175073186e-05 loss: 0.1763 (0.1667) time: 3.1100 data: 0.0082 max mem: 33300 +Epoch: [9] [1400/4276] eta: 2:33:31 lr: 3.9372088429466645e-05 loss: 0.1684 (0.1668) time: 3.1123 data: 0.0083 max mem: 33300 +Epoch: [9] [1410/4276] eta: 2:32:57 lr: 3.936938666326039e-05 loss: 0.1636 (0.1668) time: 3.1071 data: 0.0078 max mem: 33300 +Epoch: [9] [1420/4276] eta: 2:32:23 lr: 3.93666848764527e-05 loss: 0.1613 (0.1669) time: 3.1083 data: 0.0076 max mem: 33300 +Epoch: [9] [1430/4276] eta: 2:31:49 lr: 3.936398306904183e-05 loss: 0.1613 (0.1669) time: 3.0899 data: 0.0076 max mem: 33300 +Epoch: [9] [1440/4276] eta: 2:31:14 lr: 3.936128124102606e-05 loss: 0.1601 (0.1669) time: 3.0793 data: 0.0075 max mem: 33300 +Epoch: [9] [1450/4276] eta: 2:30:41 lr: 3.9358579392403655e-05 loss: 0.1631 (0.1669) time: 3.0967 data: 0.0075 max mem: 33300 +Epoch: [9] [1460/4276] eta: 2:30:07 lr: 3.93558775231729e-05 loss: 0.1631 (0.1670) time: 3.1108 data: 0.0073 max mem: 33300 +Epoch: [9] [1470/4276] eta: 2:29:33 lr: 3.935317563333205e-05 loss: 0.1663 (0.1670) time: 3.0963 data: 0.0081 max mem: 33300 +Epoch: [9] [1480/4276] eta: 2:28:58 lr: 3.9350473722879386e-05 loss: 0.1613 (0.1670) time: 3.0647 data: 0.0089 max mem: 33300 +Epoch: [9] [1490/4276] eta: 2:28:23 lr: 3.9347771791813165e-05 loss: 0.1500 (0.1670) time: 3.0502 data: 0.0082 max mem: 33300 +Epoch: [9] [1500/4276] eta: 2:27:48 lr: 3.9345069840131674e-05 loss: 0.1514 (0.1670) time: 3.0464 data: 0.0079 max mem: 33300 +Epoch: [9] [1510/4276] eta: 2:27:14 lr: 3.934236786783317e-05 loss: 0.1514 (0.1670) time: 3.0621 data: 0.0083 max mem: 33300 +Epoch: [9] [1520/4276] eta: 2:26:41 lr: 3.933966587491593e-05 loss: 0.1481 (0.1670) time: 3.0887 data: 0.0082 max mem: 33300 +Epoch: [9] [1530/4276] eta: 2:26:07 lr: 3.933696386137822e-05 loss: 0.1464 (0.1669) time: 3.1041 data: 0.0083 max mem: 33300 +Epoch: [9] [1540/4276] eta: 2:25:33 lr: 3.933426182721831e-05 loss: 0.1663 (0.1670) time: 3.0828 data: 0.0084 max mem: 33300 +Epoch: [9] [1550/4276] eta: 2:24:59 lr: 3.9331559772434474e-05 loss: 0.1711 (0.1670) time: 3.0579 data: 0.0081 max mem: 33300 +Epoch: [9] [1560/4276] eta: 2:24:25 lr: 3.932885769702497e-05 loss: 0.1615 (0.1670) time: 3.0727 data: 0.0086 max mem: 33300 +Epoch: [9] [1570/4276] eta: 2:23:52 lr: 3.9326155600988063e-05 loss: 0.1607 (0.1670) time: 3.0999 data: 0.0088 max mem: 33300 +Epoch: [9] [1580/4276] eta: 2:23:18 lr: 3.932345348432204e-05 loss: 0.1645 (0.1669) time: 3.1105 data: 0.0080 max mem: 33300 +Epoch: [9] [1590/4276] eta: 2:22:45 lr: 3.932075134702515e-05 loss: 0.1645 (0.1669) time: 3.1112 data: 0.0076 max mem: 33300 +Epoch: [9] [1600/4276] eta: 2:22:12 lr: 3.931804918909566e-05 loss: 0.1559 (0.1669) time: 3.1146 data: 0.0077 max mem: 33300 +Epoch: [9] [1610/4276] eta: 2:21:39 lr: 3.931534701053185e-05 loss: 0.1430 (0.1668) time: 3.1143 data: 0.0075 max mem: 33300 +Epoch: [9] [1620/4276] eta: 2:21:06 lr: 3.9312644811331986e-05 loss: 0.1411 (0.1667) time: 3.1100 data: 0.0073 max mem: 33300 +Epoch: [9] [1630/4276] eta: 2:20:32 lr: 3.930994259149432e-05 loss: 0.1635 (0.1668) time: 3.1060 data: 0.0076 max mem: 33300 +Epoch: [9] [1640/4276] eta: 2:19:59 lr: 3.9307240351017126e-05 loss: 0.1616 (0.1668) time: 3.1110 data: 0.0080 max mem: 33300 +Epoch: [9] [1650/4276] eta: 2:19:27 lr: 3.930453808989867e-05 loss: 0.1561 (0.1668) time: 3.1188 data: 0.0080 max mem: 33300 +Epoch: [9] [1660/4276] eta: 2:18:54 lr: 3.9301835808137214e-05 loss: 0.1569 (0.1668) time: 3.1232 data: 0.0075 max mem: 33300 +Epoch: [9] [1670/4276] eta: 2:18:21 lr: 3.929913350573104e-05 loss: 0.1634 (0.1667) time: 3.1156 data: 0.0074 max mem: 33300 +Epoch: [9] [1680/4276] eta: 2:17:48 lr: 3.9296431182678386e-05 loss: 0.1644 (0.1668) time: 3.1120 data: 0.0073 max mem: 33300 +Epoch: [9] [1690/4276] eta: 2:17:15 lr: 3.929372883897754e-05 loss: 0.1644 (0.1668) time: 3.1130 data: 0.0075 max mem: 33300 +Epoch: [9] [1700/4276] eta: 2:16:42 lr: 3.929102647462676e-05 loss: 0.1765 (0.1669) time: 3.1068 data: 0.0078 max mem: 33300 +Epoch: [9] [1710/4276] eta: 2:16:09 lr: 3.928832408962429e-05 loss: 0.1917 (0.1670) time: 3.1072 data: 0.0076 max mem: 33300 +Epoch: [9] [1720/4276] eta: 2:15:36 lr: 3.9285621683968425e-05 loss: 0.1917 (0.1671) time: 3.1102 data: 0.0075 max mem: 33300 +Epoch: [9] [1730/4276] eta: 2:15:03 lr: 3.9282919257657416e-05 loss: 0.1769 (0.1671) time: 3.1082 data: 0.0075 max mem: 33300 +Epoch: [9] [1740/4276] eta: 2:14:30 lr: 3.9280216810689516e-05 loss: 0.1701 (0.1672) time: 3.1089 data: 0.0078 max mem: 33300 +Epoch: [9] [1750/4276] eta: 2:13:57 lr: 3.9277514343063e-05 loss: 0.1714 (0.1672) time: 3.1093 data: 0.0080 max mem: 33300 +Epoch: [9] [1760/4276] eta: 2:13:24 lr: 3.9274811854776125e-05 loss: 0.1553 (0.1671) time: 3.1097 data: 0.0077 max mem: 33300 +Epoch: [9] [1770/4276] eta: 2:12:51 lr: 3.927210934582716e-05 loss: 0.1589 (0.1671) time: 3.1045 data: 0.0075 max mem: 33300 +Epoch: [9] [1780/4276] eta: 2:12:18 lr: 3.926940681621436e-05 loss: 0.1655 (0.1671) time: 3.1002 data: 0.0074 max mem: 33300 +Epoch: [9] [1790/4276] eta: 2:11:45 lr: 3.926670426593599e-05 loss: 0.1520 (0.1671) time: 3.1045 data: 0.0076 max mem: 33300 +Epoch: [9] [1800/4276] eta: 2:11:13 lr: 3.926400169499031e-05 loss: 0.1601 (0.1671) time: 3.1032 data: 0.0079 max mem: 33300 +Epoch: [9] [1810/4276] eta: 2:10:40 lr: 3.926129910337559e-05 loss: 0.1746 (0.1672) time: 3.1039 data: 0.0078 max mem: 33300 +Epoch: [9] [1820/4276] eta: 2:10:07 lr: 3.925859649109007e-05 loss: 0.1745 (0.1671) time: 3.1071 data: 0.0077 max mem: 33300 +Epoch: [9] [1830/4276] eta: 2:09:34 lr: 3.925589385813204e-05 loss: 0.1609 (0.1671) time: 3.1052 data: 0.0077 max mem: 33300 +Epoch: [9] [1840/4276] eta: 2:09:01 lr: 3.9253191204499735e-05 loss: 0.1588 (0.1670) time: 3.1078 data: 0.0074 max mem: 33300 +Epoch: [9] [1850/4276] eta: 2:08:28 lr: 3.925048853019143e-05 loss: 0.1657 (0.1671) time: 3.0879 data: 0.0073 max mem: 33300 +Epoch: [9] [1860/4276] eta: 2:07:56 lr: 3.924778583520538e-05 loss: 0.1707 (0.1671) time: 3.1050 data: 0.0074 max mem: 33300 +Epoch: [9] [1870/4276] eta: 2:07:24 lr: 3.924508311953984e-05 loss: 0.1724 (0.1673) time: 3.1490 data: 0.0074 max mem: 33300 +Epoch: [9] [1880/4276] eta: 2:06:51 lr: 3.924238038319307e-05 loss: 0.1739 (0.1673) time: 3.1236 data: 0.0076 max mem: 33300 +Epoch: [9] [1890/4276] eta: 2:06:19 lr: 3.923967762616334e-05 loss: 0.1602 (0.1673) time: 3.1282 data: 0.0080 max mem: 33300 +Epoch: [9] [1900/4276] eta: 2:05:47 lr: 3.923697484844891e-05 loss: 0.1514 (0.1672) time: 3.1438 data: 0.0078 max mem: 33300 +Epoch: [9] [1910/4276] eta: 2:05:14 lr: 3.9234272050048014e-05 loss: 0.1530 (0.1672) time: 3.1141 data: 0.0079 max mem: 33300 +Epoch: [9] [1920/4276] eta: 2:04:42 lr: 3.9231569230958936e-05 loss: 0.1608 (0.1672) time: 3.1219 data: 0.0084 max mem: 33300 +Epoch: [9] [1930/4276] eta: 2:04:09 lr: 3.922886639117993e-05 loss: 0.1608 (0.1672) time: 3.1023 data: 0.0088 max mem: 33300 +Epoch: [9] [1940/4276] eta: 2:03:37 lr: 3.9226163530709245e-05 loss: 0.1604 (0.1672) time: 3.1142 data: 0.0086 max mem: 33300 +Epoch: [9] [1950/4276] eta: 2:03:04 lr: 3.922346064954513e-05 loss: 0.1698 (0.1672) time: 3.1380 data: 0.0081 max mem: 33300 +Epoch: [9] [1960/4276] eta: 2:02:32 lr: 3.922075774768587e-05 loss: 0.1466 (0.1671) time: 3.1261 data: 0.0082 max mem: 33300 +Epoch: [9] [1970/4276] eta: 2:02:00 lr: 3.921805482512969e-05 loss: 0.1463 (0.1671) time: 3.1456 data: 0.0083 max mem: 33300 +Epoch: [9] [1980/4276] eta: 2:01:28 lr: 3.921535188187487e-05 loss: 0.1527 (0.1670) time: 3.1251 data: 0.0080 max mem: 33300 +Epoch: [9] [1990/4276] eta: 2:00:56 lr: 3.921264891791967e-05 loss: 0.1558 (0.1670) time: 3.1292 data: 0.0080 max mem: 33300 +Epoch: [9] [2000/4276] eta: 2:00:23 lr: 3.920994593326231e-05 loss: 0.1771 (0.1671) time: 3.1393 data: 0.0083 max mem: 33300 +Epoch: [9] [2010/4276] eta: 1:59:51 lr: 3.9207242927901095e-05 loss: 0.1608 (0.1670) time: 3.1208 data: 0.0081 max mem: 33300 +Epoch: [9] [2020/4276] eta: 1:59:19 lr: 3.9204539901834245e-05 loss: 0.1623 (0.1671) time: 3.1422 data: 0.0079 max mem: 33300 +Epoch: [9] [2030/4276] eta: 1:58:46 lr: 3.920183685506002e-05 loss: 0.1654 (0.1670) time: 3.1150 data: 0.0080 max mem: 33300 +Epoch: [9] [2040/4276] eta: 1:58:14 lr: 3.919913378757669e-05 loss: 0.1540 (0.1670) time: 3.0897 data: 0.0082 max mem: 33300 +Epoch: [9] [2050/4276] eta: 1:57:41 lr: 3.919643069938249e-05 loss: 0.1594 (0.1670) time: 3.1110 data: 0.0086 max mem: 33300 +Epoch: [9] [2060/4276] eta: 1:57:09 lr: 3.91937275904757e-05 loss: 0.1612 (0.1670) time: 3.1210 data: 0.0091 max mem: 33300 +Epoch: [9] [2070/4276] eta: 1:56:37 lr: 3.919102446085455e-05 loss: 0.1588 (0.1669) time: 3.1319 data: 0.0091 max mem: 33300 +Epoch: [9] [2080/4276] eta: 1:56:04 lr: 3.91883213105173e-05 loss: 0.1644 (0.1670) time: 3.1005 data: 0.0092 max mem: 33300 +Epoch: [9] [2090/4276] eta: 1:55:32 lr: 3.9185618139462215e-05 loss: 0.1539 (0.1669) time: 3.1158 data: 0.0091 max mem: 33300 +Epoch: [9] [2100/4276] eta: 1:55:00 lr: 3.918291494768753e-05 loss: 0.1602 (0.1670) time: 3.1400 data: 0.0089 max mem: 33300 +Epoch: [9] [2110/4276] eta: 1:54:28 lr: 3.918021173519151e-05 loss: 0.1586 (0.1669) time: 3.1211 data: 0.0087 max mem: 33300 +Epoch: [9] [2120/4276] eta: 1:53:56 lr: 3.91775085019724e-05 loss: 0.1364 (0.1667) time: 3.1465 data: 0.0088 max mem: 33300 +Epoch: [9] [2130/4276] eta: 1:53:24 lr: 3.917480524802846e-05 loss: 0.1346 (0.1666) time: 3.1215 data: 0.0087 max mem: 33300 +Epoch: [9] [2140/4276] eta: 1:52:52 lr: 3.917210197335795e-05 loss: 0.1585 (0.1667) time: 3.1338 data: 0.0086 max mem: 33300 +Epoch: [9] [2150/4276] eta: 1:52:20 lr: 3.91693986779591e-05 loss: 0.1692 (0.1667) time: 3.1520 data: 0.0090 max mem: 33300 +Epoch: [9] [2160/4276] eta: 1:51:48 lr: 3.916669536183018e-05 loss: 0.1623 (0.1667) time: 3.1194 data: 0.0093 max mem: 33300 +Epoch: [9] [2170/4276] eta: 1:51:16 lr: 3.9163992024969425e-05 loss: 0.1653 (0.1668) time: 3.1395 data: 0.0095 max mem: 33300 +Epoch: [9] [2180/4276] eta: 1:50:43 lr: 3.91612886673751e-05 loss: 0.1702 (0.1668) time: 3.1248 data: 0.0095 max mem: 33300 +Epoch: [9] [2190/4276] eta: 1:50:12 lr: 3.915858528904544e-05 loss: 0.1702 (0.1668) time: 3.1293 data: 0.0087 max mem: 33300 +Epoch: [9] [2200/4276] eta: 1:49:39 lr: 3.9155881889978714e-05 loss: 0.1560 (0.1668) time: 3.1365 data: 0.0079 max mem: 33300 +Epoch: [9] [2210/4276] eta: 1:49:07 lr: 3.9153178470173166e-05 loss: 0.1575 (0.1668) time: 3.1124 data: 0.0077 max mem: 33300 +Epoch: [9] [2220/4276] eta: 1:48:35 lr: 3.915047502962704e-05 loss: 0.1730 (0.1668) time: 3.1406 data: 0.0081 max mem: 33300 +Epoch: [9] [2230/4276] eta: 1:48:03 lr: 3.9147771568338595e-05 loss: 0.1586 (0.1668) time: 3.1198 data: 0.0082 max mem: 33300 +Epoch: [9] [2240/4276] eta: 1:47:31 lr: 3.914506808630607e-05 loss: 0.1496 (0.1667) time: 3.1214 data: 0.0078 max mem: 33300 +Epoch: [9] [2250/4276] eta: 1:46:59 lr: 3.9142364583527714e-05 loss: 0.1442 (0.1666) time: 3.1391 data: 0.0079 max mem: 33300 +Epoch: [9] [2260/4276] eta: 1:46:27 lr: 3.913966106000178e-05 loss: 0.1559 (0.1666) time: 3.1063 data: 0.0089 max mem: 33300 +Epoch: [9] [2270/4276] eta: 1:45:55 lr: 3.9136957515726524e-05 loss: 0.1537 (0.1666) time: 3.1320 data: 0.0096 max mem: 33300 +Epoch: [9] [2280/4276] eta: 1:45:23 lr: 3.913425395070018e-05 loss: 0.1539 (0.1667) time: 3.1241 data: 0.0086 max mem: 33300 +Epoch: [9] [2290/4276] eta: 1:44:51 lr: 3.913155036492101e-05 loss: 0.1550 (0.1666) time: 3.1326 data: 0.0079 max mem: 33300 +Epoch: [9] [2300/4276] eta: 1:44:19 lr: 3.9128846758387246e-05 loss: 0.1522 (0.1666) time: 3.1504 data: 0.0082 max mem: 33300 +Epoch: [9] [2310/4276] eta: 1:43:47 lr: 3.912614313109714e-05 loss: 0.1575 (0.1665) time: 3.1243 data: 0.0082 max mem: 33300 +Epoch: [9] [2320/4276] eta: 1:43:15 lr: 3.912343948304896e-05 loss: 0.1575 (0.1665) time: 3.1424 data: 0.0082 max mem: 33300 +Epoch: [9] [2330/4276] eta: 1:42:43 lr: 3.9120735814240916e-05 loss: 0.1580 (0.1665) time: 3.1265 data: 0.0083 max mem: 33300 +Epoch: [9] [2340/4276] eta: 1:42:11 lr: 3.911803212467128e-05 loss: 0.1543 (0.1665) time: 3.1055 data: 0.0085 max mem: 33300 +Epoch: [9] [2350/4276] eta: 1:41:38 lr: 3.9115328414338294e-05 loss: 0.1512 (0.1665) time: 3.0958 data: 0.0089 max mem: 33300 +Epoch: [9] [2360/4276] eta: 1:41:06 lr: 3.9112624683240195e-05 loss: 0.1587 (0.1664) time: 3.0717 data: 0.0093 max mem: 33300 +Epoch: [9] [2370/4276] eta: 1:40:34 lr: 3.910992093137524e-05 loss: 0.1648 (0.1664) time: 3.0911 data: 0.0094 max mem: 33300 +Epoch: [9] [2380/4276] eta: 1:40:02 lr: 3.910721715874167e-05 loss: 0.1611 (0.1664) time: 3.1097 data: 0.0091 max mem: 33300 +Epoch: [9] [2390/4276] eta: 1:39:30 lr: 3.9104513365337725e-05 loss: 0.1485 (0.1663) time: 3.1108 data: 0.0084 max mem: 33300 +Epoch: [9] [2400/4276] eta: 1:38:57 lr: 3.910180955116166e-05 loss: 0.1567 (0.1664) time: 3.1036 data: 0.0084 max mem: 33300 +Epoch: [9] [2410/4276] eta: 1:38:25 lr: 3.909910571621171e-05 loss: 0.1447 (0.1664) time: 3.1042 data: 0.0091 max mem: 33300 +Epoch: [9] [2420/4276] eta: 1:37:53 lr: 3.909640186048612e-05 loss: 0.1440 (0.1663) time: 3.1036 data: 0.0090 max mem: 33300 +Epoch: [9] [2430/4276] eta: 1:37:21 lr: 3.909369798398314e-05 loss: 0.1771 (0.1664) time: 3.0997 data: 0.0087 max mem: 33300 +Epoch: [9] [2440/4276] eta: 1:36:49 lr: 3.9090994086701e-05 loss: 0.1771 (0.1664) time: 3.0927 data: 0.0087 max mem: 33300 +Epoch: [9] [2450/4276] eta: 1:36:17 lr: 3.908829016863797e-05 loss: 0.1606 (0.1664) time: 3.0970 data: 0.0087 max mem: 33300 +Epoch: [9] [2460/4276] eta: 1:35:45 lr: 3.9085586229792265e-05 loss: 0.1633 (0.1664) time: 3.1184 data: 0.0083 max mem: 33300 +Epoch: [9] [2470/4276] eta: 1:35:13 lr: 3.908288227016214e-05 loss: 0.1633 (0.1665) time: 3.1163 data: 0.0079 max mem: 33300 +Epoch: [9] [2480/4276] eta: 1:34:41 lr: 3.908017828974584e-05 loss: 0.1666 (0.1665) time: 3.1188 data: 0.0078 max mem: 33300 +Epoch: [9] [2490/4276] eta: 1:34:09 lr: 3.9077474288541606e-05 loss: 0.1572 (0.1664) time: 3.1189 data: 0.0080 max mem: 33300 +Epoch: [9] [2500/4276] eta: 1:33:37 lr: 3.907477026654767e-05 loss: 0.1555 (0.1665) time: 3.1126 data: 0.0080 max mem: 33300 +Epoch: [9] [2510/4276] eta: 1:33:05 lr: 3.907206622376228e-05 loss: 0.1615 (0.1665) time: 3.1082 data: 0.0081 max mem: 33300 +Epoch: [9] [2520/4276] eta: 1:32:33 lr: 3.9069362160183687e-05 loss: 0.1467 (0.1664) time: 3.1082 data: 0.0079 max mem: 33300 +Epoch: [9] [2530/4276] eta: 1:32:01 lr: 3.906665807581012e-05 loss: 0.1333 (0.1662) time: 3.1203 data: 0.0078 max mem: 33300 +Epoch: [9] [2540/4276] eta: 1:31:29 lr: 3.9063953970639824e-05 loss: 0.1414 (0.1662) time: 3.1142 data: 0.0085 max mem: 33300 +Epoch: [9] [2550/4276] eta: 1:30:57 lr: 3.9061249844671045e-05 loss: 0.1475 (0.1662) time: 3.1181 data: 0.0089 max mem: 33300 +Epoch: [9] [2560/4276] eta: 1:30:25 lr: 3.9058545697902004e-05 loss: 0.1378 (0.1661) time: 3.1245 data: 0.0086 max mem: 33300 +Epoch: [9] [2570/4276] eta: 1:29:53 lr: 3.905584153033096e-05 loss: 0.1340 (0.1660) time: 3.1172 data: 0.0085 max mem: 33300 +Epoch: [9] [2580/4276] eta: 1:29:21 lr: 3.905313734195615e-05 loss: 0.1475 (0.1660) time: 3.1094 data: 0.0090 max mem: 33300 +Epoch: [9] [2590/4276] eta: 1:28:49 lr: 3.90504331327758e-05 loss: 0.1684 (0.1660) time: 3.1019 data: 0.0091 max mem: 33300 +Epoch: [9] [2600/4276] eta: 1:28:17 lr: 3.904772890278817e-05 loss: 0.1590 (0.1660) time: 3.1072 data: 0.0085 max mem: 33300 +Epoch: [9] [2610/4276] eta: 1:27:46 lr: 3.904502465199148e-05 loss: 0.1472 (0.1659) time: 3.1188 data: 0.0084 max mem: 33300 +Epoch: [9] [2620/4276] eta: 1:27:14 lr: 3.9042320380383976e-05 loss: 0.1458 (0.1659) time: 3.1215 data: 0.0083 max mem: 33300 +Epoch: [9] [2630/4276] eta: 1:26:42 lr: 3.903961608796391e-05 loss: 0.1476 (0.1658) time: 3.1154 data: 0.0081 max mem: 33300 +Epoch: [9] [2640/4276] eta: 1:26:10 lr: 3.903691177472949e-05 loss: 0.1476 (0.1658) time: 3.1209 data: 0.0081 max mem: 33300 +Epoch: [9] [2650/4276] eta: 1:25:38 lr: 3.903420744067898e-05 loss: 0.1607 (0.1658) time: 3.1147 data: 0.0080 max mem: 33300 +Epoch: [9] [2660/4276] eta: 1:25:06 lr: 3.90315030858106e-05 loss: 0.1620 (0.1658) time: 3.1143 data: 0.0081 max mem: 33300 +Epoch: [9] [2670/4276] eta: 1:24:34 lr: 3.9028798710122597e-05 loss: 0.1600 (0.1658) time: 3.1163 data: 0.0083 max mem: 33300 +Epoch: [9] [2680/4276] eta: 1:24:02 lr: 3.90260943136132e-05 loss: 0.1622 (0.1658) time: 3.1090 data: 0.0083 max mem: 33300 +Epoch: [9] [2690/4276] eta: 1:23:31 lr: 3.902338989628066e-05 loss: 0.1610 (0.1658) time: 3.1156 data: 0.0084 max mem: 33300 +Epoch: [9] [2700/4276] eta: 1:22:59 lr: 3.90206854581232e-05 loss: 0.1492 (0.1657) time: 3.1182 data: 0.0089 max mem: 33300 +Epoch: [9] [2710/4276] eta: 1:22:27 lr: 3.901798099913906e-05 loss: 0.1483 (0.1657) time: 3.1122 data: 0.0085 max mem: 33300 +Epoch: [9] [2720/4276] eta: 1:21:55 lr: 3.901527651932648e-05 loss: 0.1621 (0.1657) time: 3.1076 data: 0.0082 max mem: 33300 +Epoch: [9] [2730/4276] eta: 1:21:23 lr: 3.901257201868368e-05 loss: 0.1642 (0.1657) time: 3.1112 data: 0.0084 max mem: 33300 +Epoch: [9] [2740/4276] eta: 1:20:51 lr: 3.9009867497208906e-05 loss: 0.1651 (0.1657) time: 3.1152 data: 0.0088 max mem: 33300 +Epoch: [9] [2750/4276] eta: 1:20:19 lr: 3.900716295490041e-05 loss: 0.1673 (0.1657) time: 3.1076 data: 0.0089 max mem: 33300 +Epoch: [9] [2760/4276] eta: 1:19:47 lr: 3.9004458391756385e-05 loss: 0.1567 (0.1657) time: 3.0870 data: 0.0082 max mem: 33300 +Epoch: [9] [2770/4276] eta: 1:19:15 lr: 3.9001753807775106e-05 loss: 0.1513 (0.1657) time: 3.0746 data: 0.0084 max mem: 33300 +Epoch: [9] [2780/4276] eta: 1:18:43 lr: 3.8999049202954784e-05 loss: 0.1477 (0.1656) time: 3.0933 data: 0.0097 max mem: 33300 +Epoch: [9] [2790/4276] eta: 1:18:12 lr: 3.8996344577293664e-05 loss: 0.1682 (0.1657) time: 3.1177 data: 0.0101 max mem: 33300 +Epoch: [9] [2800/4276] eta: 1:17:40 lr: 3.899363993078996e-05 loss: 0.1730 (0.1657) time: 3.1152 data: 0.0100 max mem: 33300 +Epoch: [9] [2810/4276] eta: 1:17:08 lr: 3.899093526344193e-05 loss: 0.1412 (0.1656) time: 3.0989 data: 0.0100 max mem: 33300 +Epoch: [9] [2820/4276] eta: 1:16:36 lr: 3.89882305752478e-05 loss: 0.1432 (0.1656) time: 3.0849 data: 0.0096 max mem: 33300 +Epoch: [9] [2830/4276] eta: 1:16:04 lr: 3.89855258662058e-05 loss: 0.1513 (0.1655) time: 3.0738 data: 0.0093 max mem: 33300 +Epoch: [9] [2840/4276] eta: 1:15:32 lr: 3.8982821136314143e-05 loss: 0.1614 (0.1655) time: 3.0777 data: 0.0085 max mem: 33300 +Epoch: [9] [2850/4276] eta: 1:15:00 lr: 3.898011638557109e-05 loss: 0.1749 (0.1656) time: 3.0775 data: 0.0082 max mem: 33300 +Epoch: [9] [2860/4276] eta: 1:14:28 lr: 3.897741161397487e-05 loss: 0.1683 (0.1656) time: 3.0618 data: 0.0091 max mem: 33300 +Epoch: [9] [2870/4276] eta: 1:13:56 lr: 3.897470682152369e-05 loss: 0.1590 (0.1656) time: 3.0776 data: 0.0090 max mem: 33300 +Epoch: [9] [2880/4276] eta: 1:13:24 lr: 3.8972002008215804e-05 loss: 0.1590 (0.1656) time: 3.0987 data: 0.0081 max mem: 33300 +Epoch: [9] [2890/4276] eta: 1:12:52 lr: 3.896929717404943e-05 loss: 0.1520 (0.1656) time: 3.0936 data: 0.0081 max mem: 33300 +Epoch: [9] [2900/4276] eta: 1:12:21 lr: 3.89665923190228e-05 loss: 0.1426 (0.1655) time: 3.0899 data: 0.0081 max mem: 33300 +Epoch: [9] [2910/4276] eta: 1:11:49 lr: 3.896388744313417e-05 loss: 0.1495 (0.1655) time: 3.0734 data: 0.0082 max mem: 33300 +Epoch: [9] [2920/4276] eta: 1:11:16 lr: 3.896118254638173e-05 loss: 0.1495 (0.1655) time: 3.0527 data: 0.0080 max mem: 33300 +Epoch: [9] [2930/4276] eta: 1:10:45 lr: 3.895847762876373e-05 loss: 0.1474 (0.1655) time: 3.0728 data: 0.0081 max mem: 33300 +Epoch: [9] [2940/4276] eta: 1:10:13 lr: 3.8955772690278395e-05 loss: 0.1484 (0.1654) time: 3.0995 data: 0.0080 max mem: 33300 +Epoch: [9] [2950/4276] eta: 1:09:41 lr: 3.895306773092396e-05 loss: 0.1568 (0.1654) time: 3.0979 data: 0.0075 max mem: 33300 +Epoch: [9] [2960/4276] eta: 1:09:09 lr: 3.895036275069865e-05 loss: 0.1552 (0.1653) time: 3.0986 data: 0.0079 max mem: 33300 +Epoch: [9] [2970/4276] eta: 1:08:38 lr: 3.8947657749600694e-05 loss: 0.1612 (0.1654) time: 3.1039 data: 0.0077 max mem: 33300 +Epoch: [9] [2980/4276] eta: 1:08:06 lr: 3.8944952727628315e-05 loss: 0.1660 (0.1654) time: 3.1101 data: 0.0079 max mem: 33300 +Epoch: [9] [2990/4276] eta: 1:07:34 lr: 3.894224768477975e-05 loss: 0.1523 (0.1654) time: 3.1076 data: 0.0087 max mem: 33300 +Epoch: [9] [3000/4276] eta: 1:07:02 lr: 3.8939542621053214e-05 loss: 0.1492 (0.1653) time: 3.0909 data: 0.0084 max mem: 33300 +Epoch: [9] [3010/4276] eta: 1:06:31 lr: 3.893683753644695e-05 loss: 0.1529 (0.1653) time: 3.0869 data: 0.0079 max mem: 33300 +Epoch: [9] [3020/4276] eta: 1:05:59 lr: 3.8934132430959174e-05 loss: 0.1591 (0.1653) time: 3.0767 data: 0.0082 max mem: 33300 +Epoch: [9] [3030/4276] eta: 1:05:27 lr: 3.893142730458812e-05 loss: 0.1492 (0.1653) time: 3.0585 data: 0.0086 max mem: 33300 +Epoch: [9] [3040/4276] eta: 1:04:55 lr: 3.8928722157332005e-05 loss: 0.1672 (0.1654) time: 3.0425 data: 0.0083 max mem: 33300 +Epoch: [9] [3050/4276] eta: 1:04:23 lr: 3.892601698918906e-05 loss: 0.1672 (0.1654) time: 3.0617 data: 0.0082 max mem: 33300 +Epoch: [9] [3060/4276] eta: 1:03:51 lr: 3.892331180015752e-05 loss: 0.1414 (0.1653) time: 3.0961 data: 0.0079 max mem: 33300 +Epoch: [9] [3070/4276] eta: 1:03:19 lr: 3.8920606590235595e-05 loss: 0.1496 (0.1653) time: 3.0983 data: 0.0075 max mem: 33300 +Epoch: [9] [3080/4276] eta: 1:02:48 lr: 3.8917901359421516e-05 loss: 0.1489 (0.1653) time: 3.0979 data: 0.0077 max mem: 33300 +Epoch: [9] [3090/4276] eta: 1:02:16 lr: 3.891519610771352e-05 loss: 0.1489 (0.1652) time: 3.0961 data: 0.0077 max mem: 33300 +Epoch: [9] [3100/4276] eta: 1:01:44 lr: 3.891249083510981e-05 loss: 0.1540 (0.1653) time: 3.1033 data: 0.0081 max mem: 33300 +Epoch: [9] [3110/4276] eta: 1:01:13 lr: 3.8909785541608625e-05 loss: 0.1536 (0.1652) time: 3.1069 data: 0.0082 max mem: 33300 +Epoch: [9] [3120/4276] eta: 1:00:41 lr: 3.890708022720819e-05 loss: 0.1448 (0.1652) time: 3.1039 data: 0.0079 max mem: 33300 +Epoch: [9] [3130/4276] eta: 1:00:09 lr: 3.8904374891906715e-05 loss: 0.1444 (0.1651) time: 3.0851 data: 0.0091 max mem: 33300 +Epoch: [9] [3140/4276] eta: 0:59:37 lr: 3.8901669535702446e-05 loss: 0.1491 (0.1651) time: 3.0680 data: 0.0097 max mem: 33300 +Epoch: [9] [3150/4276] eta: 0:59:06 lr: 3.889896415859358e-05 loss: 0.1718 (0.1651) time: 3.0824 data: 0.0085 max mem: 33300 +Epoch: [9] [3160/4276] eta: 0:58:34 lr: 3.889625876057836e-05 loss: 0.1629 (0.1651) time: 3.0937 data: 0.0078 max mem: 33300 +Epoch: [9] [3170/4276] eta: 0:58:02 lr: 3.889355334165501e-05 loss: 0.1602 (0.1652) time: 3.1054 data: 0.0078 max mem: 33300 +Epoch: [9] [3180/4276] eta: 0:57:31 lr: 3.8890847901821734e-05 loss: 0.1565 (0.1652) time: 3.1027 data: 0.0082 max mem: 33300 +Epoch: [9] [3190/4276] eta: 0:56:59 lr: 3.888814244107677e-05 loss: 0.1536 (0.1652) time: 3.1005 data: 0.0082 max mem: 33300 +Epoch: [9] [3200/4276] eta: 0:56:27 lr: 3.888543695941833e-05 loss: 0.1623 (0.1652) time: 3.1072 data: 0.0083 max mem: 33300 +Epoch: [9] [3210/4276] eta: 0:55:56 lr: 3.888273145684464e-05 loss: 0.1691 (0.1652) time: 3.1104 data: 0.0083 max mem: 33300 +Epoch: [9] [3220/4276] eta: 0:55:24 lr: 3.888002593335393e-05 loss: 0.1704 (0.1652) time: 3.1213 data: 0.0087 max mem: 33300 +Epoch: [9] [3230/4276] eta: 0:54:53 lr: 3.887732038894441e-05 loss: 0.1529 (0.1652) time: 3.1235 data: 0.0091 max mem: 33300 +Epoch: [9] [3240/4276] eta: 0:54:21 lr: 3.88746148236143e-05 loss: 0.1644 (0.1652) time: 3.1160 data: 0.0089 max mem: 33300 +Epoch: [9] [3250/4276] eta: 0:53:50 lr: 3.887190923736183e-05 loss: 0.1773 (0.1652) time: 3.1184 data: 0.0089 max mem: 33300 +Epoch: [9] [3260/4276] eta: 0:53:18 lr: 3.8869203630185207e-05 loss: 0.1670 (0.1652) time: 3.1210 data: 0.0089 max mem: 33300 +Epoch: [9] [3270/4276] eta: 0:52:46 lr: 3.886649800208266e-05 loss: 0.1712 (0.1653) time: 3.0686 data: 0.0083 max mem: 33300 +Epoch: [9] [3280/4276] eta: 0:52:14 lr: 3.88637923530524e-05 loss: 0.1539 (0.1653) time: 3.0174 data: 0.0086 max mem: 33300 +Epoch: [9] [3290/4276] eta: 0:51:42 lr: 3.886108668309266e-05 loss: 0.1620 (0.1653) time: 3.0096 data: 0.0093 max mem: 33300 +Epoch: [9] [3300/4276] eta: 0:51:11 lr: 3.8858380992201654e-05 loss: 0.1620 (0.1653) time: 3.0248 data: 0.0089 max mem: 33300 +Epoch: [9] [3310/4276] eta: 0:50:39 lr: 3.885567528037759e-05 loss: 0.1694 (0.1654) time: 3.0459 data: 0.0086 max mem: 33300 +Epoch: [9] [3320/4276] eta: 0:50:07 lr: 3.8852969547618704e-05 loss: 0.1674 (0.1654) time: 3.0531 data: 0.0083 max mem: 33300 +Epoch: [9] [3330/4276] eta: 0:49:35 lr: 3.88502637939232e-05 loss: 0.1603 (0.1654) time: 3.0481 data: 0.0081 max mem: 33300 +Epoch: [9] [3340/4276] eta: 0:49:04 lr: 3.88475580192893e-05 loss: 0.1648 (0.1654) time: 3.0412 data: 0.0078 max mem: 33300 +Epoch: [9] [3350/4276] eta: 0:48:32 lr: 3.884485222371522e-05 loss: 0.1602 (0.1654) time: 3.0392 data: 0.0076 max mem: 33300 +Epoch: [9] [3360/4276] eta: 0:48:00 lr: 3.8842146407199175e-05 loss: 0.1468 (0.1654) time: 3.0387 data: 0.0076 max mem: 33300 +Epoch: [9] [3370/4276] eta: 0:47:28 lr: 3.88394405697394e-05 loss: 0.1515 (0.1654) time: 3.0149 data: 0.0081 max mem: 33300 +Epoch: [9] [3380/4276] eta: 0:46:56 lr: 3.883673471133408e-05 loss: 0.1515 (0.1654) time: 2.9919 data: 0.0091 max mem: 33300 +Epoch: [9] [3390/4276] eta: 0:46:25 lr: 3.883402883198146e-05 loss: 0.1594 (0.1654) time: 3.0170 data: 0.0091 max mem: 33300 +Epoch: [9] [3400/4276] eta: 0:45:53 lr: 3.883132293167975e-05 loss: 0.1737 (0.1654) time: 3.0354 data: 0.0086 max mem: 33300 +Epoch: [9] [3410/4276] eta: 0:45:21 lr: 3.8828617010427155e-05 loss: 0.1638 (0.1655) time: 3.0340 data: 0.0085 max mem: 33300 +Epoch: [9] [3420/4276] eta: 0:44:50 lr: 3.882591106822189e-05 loss: 0.1611 (0.1655) time: 3.0339 data: 0.0078 max mem: 33300 +Epoch: [9] [3430/4276] eta: 0:44:18 lr: 3.882320510506219e-05 loss: 0.1643 (0.1655) time: 3.0587 data: 0.0074 max mem: 33300 +Epoch: [9] [3440/4276] eta: 0:43:46 lr: 3.8820499120946245e-05 loss: 0.1587 (0.1654) time: 3.0678 data: 0.0079 max mem: 33300 +Epoch: [9] [3450/4276] eta: 0:43:15 lr: 3.881779311587229e-05 loss: 0.1461 (0.1655) time: 3.0648 data: 0.0081 max mem: 33300 +Epoch: [9] [3460/4276] eta: 0:42:43 lr: 3.881508708983853e-05 loss: 0.1727 (0.1655) time: 3.0776 data: 0.0080 max mem: 33300 +Epoch: [9] [3470/4276] eta: 0:42:12 lr: 3.881238104284317e-05 loss: 0.1593 (0.1655) time: 3.0821 data: 0.0084 max mem: 33300 +Epoch: [9] [3480/4276] eta: 0:41:40 lr: 3.8809674974884444e-05 loss: 0.1567 (0.1654) time: 3.0667 data: 0.0086 max mem: 33300 +Epoch: [9] [3490/4276] eta: 0:41:08 lr: 3.880696888596055e-05 loss: 0.1635 (0.1655) time: 3.0633 data: 0.0081 max mem: 33300 +Epoch: [9] [3500/4276] eta: 0:40:37 lr: 3.88042627760697e-05 loss: 0.1685 (0.1655) time: 3.0808 data: 0.0078 max mem: 33300 +Epoch: [9] [3510/4276] eta: 0:40:05 lr: 3.880155664521012e-05 loss: 0.1661 (0.1654) time: 3.0822 data: 0.0076 max mem: 33300 +Epoch: [9] [3520/4276] eta: 0:39:34 lr: 3.879885049338001e-05 loss: 0.1529 (0.1654) time: 3.0801 data: 0.0075 max mem: 33300 +Epoch: [9] [3530/4276] eta: 0:39:02 lr: 3.8796144320577596e-05 loss: 0.1546 (0.1655) time: 3.0767 data: 0.0077 max mem: 33300 +Epoch: [9] [3540/4276] eta: 0:38:31 lr: 3.879343812680108e-05 loss: 0.1556 (0.1655) time: 3.0557 data: 0.0075 max mem: 33300 +Epoch: [9] [3550/4276] eta: 0:37:59 lr: 3.879073191204867e-05 loss: 0.1513 (0.1654) time: 3.0057 data: 0.0072 max mem: 33300 +Epoch: [9] [3560/4276] eta: 0:37:53 lr: 3.878802567631859e-05 loss: 0.1513 (0.1654) time: 9.3442 data: 6.3258 max mem: 33300 +Epoch: [9] [3570/4276] eta: 0:37:21 lr: 3.878531941960903e-05 loss: 0.1747 (0.1655) time: 9.3972 data: 6.3268 max mem: 33300 +Epoch: [9] [3580/4276] eta: 0:36:49 lr: 3.878261314191823e-05 loss: 0.1476 (0.1654) time: 3.0762 data: 0.0090 max mem: 33300 +Epoch: [9] [3590/4276] eta: 0:36:17 lr: 3.877990684324438e-05 loss: 0.1409 (0.1654) time: 3.0726 data: 0.0088 max mem: 33300 +Epoch: [9] [3600/4276] eta: 0:35:45 lr: 3.87772005235857e-05 loss: 0.1567 (0.1654) time: 3.0731 data: 0.0088 max mem: 33300 +Epoch: [9] [3610/4276] eta: 0:35:13 lr: 3.8774494182940383e-05 loss: 0.1649 (0.1654) time: 3.0756 data: 0.0090 max mem: 33300 +Epoch: [9] [3620/4276] eta: 0:34:41 lr: 3.877178782130666e-05 loss: 0.1644 (0.1654) time: 3.0768 data: 0.0085 max mem: 33300 +Epoch: [9] [3630/4276] eta: 0:34:09 lr: 3.876908143868273e-05 loss: 0.1591 (0.1654) time: 3.0740 data: 0.0077 max mem: 33300 +Epoch: [9] [3640/4276] eta: 0:33:37 lr: 3.876637503506681e-05 loss: 0.1498 (0.1653) time: 3.0714 data: 0.0077 max mem: 33300 +Epoch: [9] [3650/4276] eta: 0:33:06 lr: 3.8763668610457094e-05 loss: 0.1404 (0.1653) time: 3.0729 data: 0.0078 max mem: 33300 +Epoch: [9] [3660/4276] eta: 0:32:34 lr: 3.87609621648518e-05 loss: 0.1404 (0.1653) time: 3.0728 data: 0.0079 max mem: 33300 +Epoch: [9] [3670/4276] eta: 0:32:02 lr: 3.875825569824914e-05 loss: 0.1490 (0.1652) time: 3.0736 data: 0.0077 max mem: 33300 +Epoch: [9] [3680/4276] eta: 0:31:30 lr: 3.8755549210647315e-05 loss: 0.1697 (0.1653) time: 3.0766 data: 0.0076 max mem: 33300 +Epoch: [9] [3690/4276] eta: 0:30:58 lr: 3.8752842702044536e-05 loss: 0.1698 (0.1653) time: 3.0761 data: 0.0078 max mem: 33300 +Epoch: [9] [3700/4276] eta: 0:30:26 lr: 3.875013617243901e-05 loss: 0.1578 (0.1652) time: 3.0768 data: 0.0078 max mem: 33300 +Epoch: [9] [3710/4276] eta: 0:29:54 lr: 3.874742962182894e-05 loss: 0.1540 (0.1652) time: 3.0799 data: 0.0076 max mem: 33300 +Epoch: [9] [3720/4276] eta: 0:29:22 lr: 3.874472305021253e-05 loss: 0.1340 (0.1652) time: 3.0798 data: 0.0077 max mem: 33300 +Epoch: [9] [3730/4276] eta: 0:28:51 lr: 3.8742016457588e-05 loss: 0.1518 (0.1652) time: 3.0800 data: 0.0078 max mem: 33300 +Epoch: [9] [3740/4276] eta: 0:28:19 lr: 3.873930984395355e-05 loss: 0.1607 (0.1651) time: 3.0799 data: 0.0079 max mem: 33300 +Epoch: [9] [3750/4276] eta: 0:27:47 lr: 3.873660320930738e-05 loss: 0.1525 (0.1651) time: 3.0756 data: 0.0077 max mem: 33300 +Epoch: [9] [3760/4276] eta: 0:27:15 lr: 3.8733896553647705e-05 loss: 0.1525 (0.1651) time: 3.0730 data: 0.0077 max mem: 33300 +Epoch: [9] [3770/4276] eta: 0:26:43 lr: 3.873118987697272e-05 loss: 0.1623 (0.1651) time: 3.0705 data: 0.0079 max mem: 33300 +Epoch: [9] [3780/4276] eta: 0:26:11 lr: 3.8728483179280636e-05 loss: 0.1636 (0.1651) time: 3.0695 data: 0.0079 max mem: 33300 +Epoch: [9] [3790/4276] eta: 0:25:40 lr: 3.872577646056966e-05 loss: 0.1592 (0.1651) time: 3.0739 data: 0.0077 max mem: 33300 +Epoch: [9] [3800/4276] eta: 0:25:08 lr: 3.872306972083799e-05 loss: 0.1632 (0.1651) time: 3.0779 data: 0.0077 max mem: 33300 +Epoch: [9] [3810/4276] eta: 0:24:36 lr: 3.872036296008383e-05 loss: 0.1591 (0.1651) time: 3.0764 data: 0.0076 max mem: 33300 +Epoch: [9] [3820/4276] eta: 0:24:04 lr: 3.871765617830539e-05 loss: 0.1359 (0.1650) time: 3.0761 data: 0.0077 max mem: 33300 +Epoch: [9] [3830/4276] eta: 0:23:32 lr: 3.871494937550088e-05 loss: 0.1375 (0.1650) time: 3.0739 data: 0.0076 max mem: 33300 +Epoch: [9] [3840/4276] eta: 0:23:01 lr: 3.8712242551668486e-05 loss: 0.1395 (0.1650) time: 3.0636 data: 0.0079 max mem: 33300 +Epoch: [9] [3850/4276] eta: 0:22:29 lr: 3.870953570680642e-05 loss: 0.1302 (0.1649) time: 3.0510 data: 0.0080 max mem: 33300 +Epoch: [9] [3860/4276] eta: 0:21:57 lr: 3.870682884091289e-05 loss: 0.1561 (0.1649) time: 3.0411 data: 0.0078 max mem: 33300 +Epoch: [9] [3870/4276] eta: 0:21:25 lr: 3.870412195398608e-05 loss: 0.1608 (0.1649) time: 3.0370 data: 0.0076 max mem: 33300 +Epoch: [9] [3880/4276] eta: 0:20:53 lr: 3.8701415046024216e-05 loss: 0.1630 (0.1649) time: 3.0356 data: 0.0075 max mem: 33300 +Epoch: [9] [3890/4276] eta: 0:20:22 lr: 3.869870811702548e-05 loss: 0.1499 (0.1649) time: 3.0312 data: 0.0075 max mem: 33300 +Epoch: [9] [3900/4276] eta: 0:19:50 lr: 3.869600116698808e-05 loss: 0.1536 (0.1649) time: 3.0282 data: 0.0075 max mem: 33300 +Epoch: [9] [3910/4276] eta: 0:19:18 lr: 3.8693294195910225e-05 loss: 0.1393 (0.1648) time: 3.0283 data: 0.0072 max mem: 33300 +Epoch: [9] [3920/4276] eta: 0:18:46 lr: 3.8690587203790106e-05 loss: 0.1473 (0.1648) time: 3.0317 data: 0.0072 max mem: 33300 +Epoch: [9] [3930/4276] eta: 0:18:14 lr: 3.868788019062593e-05 loss: 0.1589 (0.1648) time: 3.0279 data: 0.0075 max mem: 33300 +Epoch: [9] [3940/4276] eta: 0:17:43 lr: 3.8685173156415896e-05 loss: 0.1509 (0.1648) time: 3.0045 data: 0.0077 max mem: 33300 +Epoch: [9] [3950/4276] eta: 0:17:11 lr: 3.86824661011582e-05 loss: 0.1455 (0.1648) time: 2.9814 data: 0.0080 max mem: 33300 +Epoch: [9] [3960/4276] eta: 0:16:39 lr: 3.867975902485104e-05 loss: 0.1588 (0.1648) time: 2.9802 data: 0.0079 max mem: 33300 +Epoch: [9] [3970/4276] eta: 0:16:07 lr: 3.867705192749262e-05 loss: 0.1767 (0.1648) time: 2.9795 data: 0.0075 max mem: 33300 +Epoch: [9] [3980/4276] eta: 0:15:36 lr: 3.8674344809081145e-05 loss: 0.1510 (0.1648) time: 2.9759 data: 0.0075 max mem: 33300 +Epoch: [9] [3990/4276] eta: 0:15:04 lr: 3.86716376696148e-05 loss: 0.1375 (0.1647) time: 2.9740 data: 0.0076 max mem: 33300 +Epoch: [9] [4000/4276] eta: 0:14:32 lr: 3.86689305090918e-05 loss: 0.1423 (0.1647) time: 2.9757 data: 0.0076 max mem: 33300 +Epoch: [9] [4010/4276] eta: 0:14:00 lr: 3.8666223327510326e-05 loss: 0.1525 (0.1648) time: 2.9790 data: 0.0075 max mem: 33300 +Epoch: [9] [4020/4276] eta: 0:13:29 lr: 3.866351612486859e-05 loss: 0.1560 (0.1648) time: 2.9780 data: 0.0076 max mem: 33300 +Epoch: [9] [4030/4276] eta: 0:12:57 lr: 3.866080890116478e-05 loss: 0.1560 (0.1648) time: 2.9720 data: 0.0080 max mem: 33300 +Epoch: [9] [4040/4276] eta: 0:12:25 lr: 3.86581016563971e-05 loss: 0.1702 (0.1648) time: 2.9714 data: 0.0084 max mem: 33300 +Epoch: [9] [4050/4276] eta: 0:11:53 lr: 3.865539439056374e-05 loss: 0.1817 (0.1648) time: 2.9590 data: 0.0087 max mem: 33300 +Epoch: [9] [4060/4276] eta: 0:11:22 lr: 3.86526871036629e-05 loss: 0.1739 (0.1649) time: 2.9551 data: 0.0088 max mem: 33300 +Epoch: [9] [4070/4276] eta: 0:10:50 lr: 3.864997979569279e-05 loss: 0.1687 (0.1649) time: 2.9551 data: 0.0087 max mem: 33300 +Epoch: [9] [4080/4276] eta: 0:10:18 lr: 3.864727246665159e-05 loss: 0.1622 (0.1649) time: 2.9420 data: 0.0080 max mem: 33300 +Epoch: [9] [4090/4276] eta: 0:09:47 lr: 3.864456511653749e-05 loss: 0.1675 (0.1649) time: 2.9407 data: 0.0077 max mem: 33300 +Epoch: [9] [4100/4276] eta: 0:09:15 lr: 3.8641857745348704e-05 loss: 0.1675 (0.1649) time: 2.9562 data: 0.0082 max mem: 33300 +Epoch: [9] [4110/4276] eta: 0:08:43 lr: 3.863915035308341e-05 loss: 0.1637 (0.1649) time: 2.9657 data: 0.0082 max mem: 33300 +Epoch: [9] [4120/4276] eta: 0:08:12 lr: 3.863644293973982e-05 loss: 0.1626 (0.1650) time: 2.9610 data: 0.0075 max mem: 33300 +Epoch: [9] [4130/4276] eta: 0:07:40 lr: 3.863373550531612e-05 loss: 0.1501 (0.1649) time: 2.9649 data: 0.0076 max mem: 33300 +Epoch: [9] [4140/4276] eta: 0:07:09 lr: 3.86310280498105e-05 loss: 0.1447 (0.1649) time: 2.9683 data: 0.0078 max mem: 33300 +Epoch: [9] [4150/4276] eta: 0:06:37 lr: 3.8628320573221164e-05 loss: 0.1525 (0.1649) time: 2.9672 data: 0.0075 max mem: 33300 +Epoch: [9] [4160/4276] eta: 0:06:05 lr: 3.862561307554629e-05 loss: 0.1621 (0.1649) time: 2.9637 data: 0.0076 max mem: 33300 +Epoch: [9] [4170/4276] eta: 0:05:34 lr: 3.862290555678409e-05 loss: 0.1890 (0.1650) time: 2.9617 data: 0.0075 max mem: 33300 +Epoch: [9] [4180/4276] eta: 0:05:02 lr: 3.862019801693276e-05 loss: 0.1711 (0.1649) time: 2.9647 data: 0.0072 max mem: 33300 +Epoch: [9] [4190/4276] eta: 0:04:31 lr: 3.861749045599046e-05 loss: 0.1481 (0.1649) time: 2.9660 data: 0.0074 max mem: 33300 +Epoch: [9] [4200/4276] eta: 0:03:59 lr: 3.861478287395542e-05 loss: 0.1603 (0.1650) time: 2.9676 data: 0.0076 max mem: 33300 +Epoch: [9] [4210/4276] eta: 0:03:27 lr: 3.8612075270825816e-05 loss: 0.1804 (0.1650) time: 2.9656 data: 0.0079 max mem: 33300 +Epoch: [9] [4220/4276] eta: 0:02:56 lr: 3.860936764659984e-05 loss: 0.1854 (0.1650) time: 2.9624 data: 0.0079 max mem: 33300 +Epoch: [9] [4230/4276] eta: 0:02:24 lr: 3.860666000127569e-05 loss: 0.1812 (0.1651) time: 2.9629 data: 0.0076 max mem: 33300 +Epoch: [9] [4240/4276] eta: 0:01:53 lr: 3.860395233485154e-05 loss: 0.1812 (0.1651) time: 2.9594 data: 0.0076 max mem: 33300 +Epoch: [9] [4250/4276] eta: 0:01:21 lr: 3.86012446473256e-05 loss: 0.1714 (0.1651) time: 2.9627 data: 0.0077 max mem: 33300 +Epoch: [9] [4260/4276] eta: 0:00:50 lr: 3.859853693869606e-05 loss: 0.1695 (0.1651) time: 2.9656 data: 0.0081 max mem: 33300 +Epoch: [9] [4270/4276] eta: 0:00:18 lr: 3.85958292089611e-05 loss: 0.1673 (0.1652) time: 2.9570 data: 0.0077 max mem: 33300 +Epoch: [9] Total time: 3:44:23 +Test: [ 0/21770] eta: 11:38:37 time: 1.9255 data: 1.8818 max mem: 33300 +Test: [ 100/21770] eta: 0:20:40 time: 0.0386 data: 0.0009 max mem: 33300 +Test: [ 200/21770] eta: 0:17:15 time: 0.0389 data: 0.0008 max mem: 33300 +Test: [ 300/21770] eta: 0:16:04 time: 0.0385 data: 0.0009 max mem: 33300 +Test: [ 400/21770] eta: 0:15:26 time: 0.0388 data: 0.0009 max mem: 33300 +Test: [ 500/21770] eta: 0:15:02 time: 0.0388 data: 0.0009 max mem: 33300 +Test: [ 600/21770] eta: 0:14:45 time: 0.0390 data: 0.0008 max mem: 33300 +Test: [ 700/21770] eta: 0:14:31 time: 0.0383 data: 0.0009 max mem: 33300 +Test: [ 800/21770] eta: 0:14:18 time: 0.0384 data: 0.0009 max mem: 33300 +Test: [ 900/21770] eta: 0:14:08 time: 0.0381 data: 0.0009 max mem: 33300 +Test: [ 1000/21770] eta: 0:13:59 time: 0.0384 data: 0.0008 max mem: 33300 +Test: [ 1100/21770] eta: 0:13:51 time: 0.0380 data: 0.0008 max mem: 33300 +Test: [ 1200/21770] eta: 0:13:44 time: 0.0381 data: 0.0009 max mem: 33300 +Test: [ 1300/21770] eta: 0:13:37 time: 0.0381 data: 0.0009 max mem: 33300 +Test: [ 1400/21770] eta: 0:13:30 time: 0.0382 data: 0.0009 max mem: 33300 +Test: [ 1500/21770] eta: 0:13:24 time: 0.0385 data: 0.0008 max mem: 33300 +Test: [ 1600/21770] eta: 0:13:20 time: 0.0396 data: 0.0008 max mem: 33300 +Test: [ 1700/21770] eta: 0:13:16 time: 0.0397 data: 0.0008 max mem: 33300 +Test: [ 1800/21770] eta: 0:13:12 time: 0.0399 data: 0.0008 max mem: 33300 +Test: [ 1900/21770] eta: 0:13:08 time: 0.0396 data: 0.0008 max mem: 33300 +Test: [ 2000/21770] eta: 0:13:04 time: 0.0395 data: 0.0008 max mem: 33300 +Test: [ 2100/21770] eta: 0:13:00 time: 0.0400 data: 0.0008 max mem: 33300 +Test: [ 2200/21770] eta: 0:12:56 time: 0.0399 data: 0.0008 max mem: 33300 +Test: [ 2300/21770] eta: 0:12:52 time: 0.0396 data: 0.0008 max mem: 33300 +Test: [ 2400/21770] eta: 0:12:48 time: 0.0399 data: 0.0008 max mem: 33300 +Test: [ 2500/21770] eta: 0:12:45 time: 0.0401 data: 0.0008 max mem: 33300 +Test: [ 2600/21770] eta: 0:12:41 time: 0.0399 data: 0.0008 max mem: 33300 +Test: [ 2700/21770] eta: 0:12:37 time: 0.0400 data: 0.0008 max mem: 33300 +Test: [ 2800/21770] eta: 0:12:33 time: 0.0400 data: 0.0008 max mem: 33300 +Test: [ 2900/21770] eta: 0:12:30 time: 0.0401 data: 0.0008 max mem: 33300 +Test: [ 3000/21770] eta: 0:12:26 time: 0.0399 data: 0.0008 max mem: 33300 +Test: [ 3100/21770] eta: 0:12:22 time: 0.0401 data: 0.0009 max mem: 33300 +Test: [ 3200/21770] eta: 0:12:18 time: 0.0399 data: 0.0009 max mem: 33300 +Test: [ 3300/21770] eta: 0:12:14 time: 0.0402 data: 0.0008 max mem: 33300 +Test: [ 3400/21770] eta: 0:12:10 time: 0.0400 data: 0.0008 max mem: 33300 +Test: [ 3500/21770] eta: 0:12:06 time: 0.0401 data: 0.0008 max mem: 33300 +Test: [ 3600/21770] eta: 0:12:03 time: 0.0399 data: 0.0008 max mem: 33300 +Test: [ 3700/21770] eta: 0:11:59 time: 0.0400 data: 0.0008 max mem: 33300 +Test: [ 3800/21770] eta: 0:11:55 time: 0.0399 data: 0.0009 max mem: 33300 +Test: [ 3900/21770] eta: 0:11:51 time: 0.0402 data: 0.0009 max mem: 33300 +Test: [ 4000/21770] eta: 0:11:47 time: 0.0400 data: 0.0008 max mem: 33300 +Test: [ 4100/21770] eta: 0:11:43 time: 0.0400 data: 0.0008 max mem: 33300 +Test: [ 4200/21770] eta: 0:11:39 time: 0.0398 data: 0.0008 max mem: 33300 +Test: [ 4300/21770] eta: 0:11:35 time: 0.0402 data: 0.0009 max mem: 33300 +Test: [ 4400/21770] eta: 0:11:31 time: 0.0398 data: 0.0008 max mem: 33300 +Test: [ 4500/21770] eta: 0:11:27 time: 0.0401 data: 0.0009 max mem: 33300 +Test: [ 4600/21770] eta: 0:11:23 time: 0.0397 data: 0.0009 max mem: 33300 +Test: [ 4700/21770] eta: 0:11:20 time: 0.0400 data: 0.0009 max mem: 33300 +Test: [ 4800/21770] eta: 0:11:16 time: 0.0394 data: 0.0008 max mem: 33300 +Test: [ 4900/21770] eta: 0:11:12 time: 0.0400 data: 0.0009 max mem: 33300 +Test: [ 5000/21770] eta: 0:11:08 time: 0.0400 data: 0.0008 max mem: 33300 +Test: [ 5100/21770] eta: 0:11:04 time: 0.0400 data: 0.0008 max mem: 33300 +Test: [ 5200/21770] eta: 0:11:00 time: 0.0400 data: 0.0008 max mem: 33300 +Test: [ 5300/21770] eta: 0:10:56 time: 0.0400 data: 0.0009 max mem: 33300 +Test: [ 5400/21770] eta: 0:10:52 time: 0.0400 data: 0.0009 max mem: 33300 +Test: [ 5500/21770] eta: 0:10:48 time: 0.0400 data: 0.0008 max mem: 33300 +Test: [ 5600/21770] eta: 0:10:44 time: 0.0399 data: 0.0008 max mem: 33300 +Test: [ 5700/21770] eta: 0:10:40 time: 0.0400 data: 0.0008 max mem: 33300 +Test: [ 5800/21770] eta: 0:10:36 time: 0.0399 data: 0.0009 max mem: 33300 +Test: [ 5900/21770] eta: 0:10:32 time: 0.0399 data: 0.0009 max mem: 33300 +Test: [ 6000/21770] eta: 0:10:28 time: 0.0395 data: 0.0008 max mem: 33300 +Test: [ 6100/21770] eta: 0:10:24 time: 0.0399 data: 0.0009 max mem: 33300 +Test: [ 6200/21770] eta: 0:10:20 time: 0.0398 data: 0.0008 max mem: 33300 +Test: [ 6300/21770] eta: 0:10:16 time: 0.0405 data: 0.0008 max mem: 33300 +Test: [ 6400/21770] eta: 0:10:12 time: 0.0401 data: 0.0008 max mem: 33300 +Test: [ 6500/21770] eta: 0:10:08 time: 0.0400 data: 0.0008 max mem: 33300 +Test: [ 6600/21770] eta: 0:10:04 time: 0.0400 data: 0.0008 max mem: 33300 +Test: [ 6700/21770] eta: 0:10:00 time: 0.0400 data: 0.0008 max mem: 33300 +Test: [ 6800/21770] eta: 0:09:56 time: 0.0399 data: 0.0008 max mem: 33300 +Test: [ 6900/21770] eta: 0:09:52 time: 0.0399 data: 0.0009 max mem: 33300 +Test: [ 7000/21770] eta: 0:09:49 time: 0.0400 data: 0.0008 max mem: 33300 +Test: [ 7100/21770] eta: 0:09:45 time: 0.0399 data: 0.0008 max mem: 33300 +Test: [ 7200/21770] eta: 0:09:41 time: 0.0401 data: 0.0008 max mem: 33300 +Test: [ 7300/21770] eta: 0:09:37 time: 0.0399 data: 0.0008 max mem: 33300 +Test: [ 7400/21770] eta: 0:09:33 time: 0.0400 data: 0.0009 max mem: 33300 +Test: [ 7500/21770] eta: 0:09:28 time: 0.0378 data: 0.0009 max mem: 33300 +Test: [ 7600/21770] eta: 0:09:24 time: 0.0379 data: 0.0009 max mem: 33300 +Test: [ 7700/21770] eta: 0:09:20 time: 0.0405 data: 0.0008 max mem: 33300 +Test: [ 7800/21770] eta: 0:09:16 time: 0.0399 data: 0.0008 max mem: 33300 +Test: [ 7900/21770] eta: 0:09:12 time: 0.0401 data: 0.0008 max mem: 33300 +Test: [ 8000/21770] eta: 0:09:08 time: 0.0404 data: 0.0008 max mem: 33300 +Test: [ 8100/21770] eta: 0:09:04 time: 0.0400 data: 0.0008 max mem: 33300 +Test: [ 8200/21770] eta: 0:09:00 time: 0.0398 data: 0.0008 max mem: 33300 +Test: [ 8300/21770] eta: 0:08:56 time: 0.0399 data: 0.0008 max mem: 33300 +Test: [ 8400/21770] eta: 0:08:52 time: 0.0400 data: 0.0008 max mem: 33300 +Test: [ 8500/21770] eta: 0:08:48 time: 0.0400 data: 0.0008 max mem: 33300 +Test: [ 8600/21770] eta: 0:08:44 time: 0.0399 data: 0.0008 max mem: 33300 +Test: [ 8700/21770] eta: 0:08:40 time: 0.0400 data: 0.0008 max mem: 33300 +Test: [ 8800/21770] eta: 0:08:36 time: 0.0400 data: 0.0008 max mem: 33300 +Test: [ 8900/21770] eta: 0:08:32 time: 0.0401 data: 0.0008 max mem: 33300 +Test: [ 9000/21770] eta: 0:08:28 time: 0.0400 data: 0.0008 max mem: 33300 +Test: [ 9100/21770] eta: 0:08:24 time: 0.0399 data: 0.0008 max mem: 33300 +Test: [ 9200/21770] eta: 0:08:20 time: 0.0398 data: 0.0008 max mem: 33300 +Test: [ 9300/21770] eta: 0:08:17 time: 0.0400 data: 0.0008 max mem: 33300 +Test: [ 9400/21770] eta: 0:08:13 time: 0.0399 data: 0.0008 max mem: 33300 +Test: [ 9500/21770] eta: 0:08:09 time: 0.0400 data: 0.0008 max mem: 33300 +Test: [ 9600/21770] eta: 0:08:05 time: 0.0400 data: 0.0008 max mem: 33300 +Test: [ 9700/21770] eta: 0:08:01 time: 0.0405 data: 0.0008 max mem: 33300 +Test: [ 9800/21770] eta: 0:07:57 time: 0.0400 data: 0.0008 max mem: 33300 +Test: [ 9900/21770] eta: 0:07:53 time: 0.0403 data: 0.0008 max mem: 33300 +Test: [10000/21770] eta: 0:07:49 time: 0.0402 data: 0.0008 max mem: 33300 +Test: [10100/21770] eta: 0:07:45 time: 0.0400 data: 0.0008 max mem: 33300 +Test: [10200/21770] eta: 0:07:41 time: 0.0400 data: 0.0008 max mem: 33300 +Test: [10300/21770] eta: 0:07:37 time: 0.0406 data: 0.0008 max mem: 33300 +Test: [10400/21770] eta: 0:07:33 time: 0.0400 data: 0.0008 max mem: 33300 +Test: [10500/21770] eta: 0:07:29 time: 0.0403 data: 0.0008 max mem: 33300 +Test: [10600/21770] eta: 0:07:25 time: 0.0403 data: 0.0008 max mem: 33300 +Test: [10700/21770] eta: 0:07:21 time: 0.0379 data: 0.0009 max mem: 33300 +Test: [10800/21770] eta: 0:07:17 time: 0.0380 data: 0.0008 max mem: 33300 +Test: [10900/21770] eta: 0:07:13 time: 0.0380 data: 0.0008 max mem: 33300 +Test: [11000/21770] eta: 0:07:09 time: 0.0380 data: 0.0009 max mem: 33300 +Test: [11100/21770] eta: 0:07:04 time: 0.0380 data: 0.0009 max mem: 33300 +Test: [11200/21770] eta: 0:07:00 time: 0.0380 data: 0.0008 max mem: 33300 +Test: [11300/21770] eta: 0:06:56 time: 0.0380 data: 0.0008 max mem: 33300 +Test: [11400/21770] eta: 0:06:52 time: 0.0380 data: 0.0008 max mem: 33300 +Test: [11500/21770] eta: 0:06:48 time: 0.0380 data: 0.0009 max mem: 33300 +Test: [11600/21770] eta: 0:06:44 time: 0.0380 data: 0.0009 max mem: 33300 +Test: [11700/21770] eta: 0:06:40 time: 0.0380 data: 0.0008 max mem: 33300 +Test: [11800/21770] eta: 0:06:35 time: 0.0380 data: 0.0008 max mem: 33300 +Test: [11900/21770] eta: 0:06:31 time: 0.0380 data: 0.0008 max mem: 33300 +Test: [12000/21770] eta: 0:06:27 time: 0.0392 data: 0.0008 max mem: 33300 +Test: [12100/21770] eta: 0:06:23 time: 0.0387 data: 0.0008 max mem: 33300 +Test: [12200/21770] eta: 0:06:19 time: 0.0388 data: 0.0008 max mem: 33300 +Test: [12300/21770] eta: 0:06:15 time: 0.0386 data: 0.0008 max mem: 33300 +Test: [12400/21770] eta: 0:06:11 time: 0.0380 data: 0.0009 max mem: 33300 +Test: [12500/21770] eta: 0:06:07 time: 0.0380 data: 0.0009 max mem: 33300 +Test: [12600/21770] eta: 0:06:03 time: 0.0381 data: 0.0009 max mem: 33300 +Test: [12700/21770] eta: 0:05:59 time: 0.0388 data: 0.0010 max mem: 33300 +Test: [12800/21770] eta: 0:05:55 time: 0.0384 data: 0.0009 max mem: 33300 +Test: [12900/21770] eta: 0:05:51 time: 0.0386 data: 0.0009 max mem: 33300 +Test: [13000/21770] eta: 0:05:47 time: 0.0382 data: 0.0009 max mem: 33300 +Test: [13100/21770] eta: 0:05:43 time: 0.0387 data: 0.0009 max mem: 33300 +Test: [13200/21770] eta: 0:05:39 time: 0.0381 data: 0.0009 max mem: 33300 +Test: [13300/21770] eta: 0:05:35 time: 0.0385 data: 0.0009 max mem: 33300 +Test: [13400/21770] eta: 0:05:31 time: 0.0383 data: 0.0009 max mem: 33300 +Test: [13500/21770] eta: 0:05:27 time: 0.0386 data: 0.0009 max mem: 33300 +Test: [13600/21770] eta: 0:05:23 time: 0.0384 data: 0.0009 max mem: 33300 +Test: [13700/21770] eta: 0:05:19 time: 0.0385 data: 0.0009 max mem: 33300 +Test: [13800/21770] eta: 0:05:15 time: 0.0385 data: 0.0009 max mem: 33300 +Test: [13900/21770] eta: 0:05:10 time: 0.0385 data: 0.0009 max mem: 33300 +Test: [14000/21770] eta: 0:05:06 time: 0.0381 data: 0.0009 max mem: 33300 +Test: [14100/21770] eta: 0:05:02 time: 0.0380 data: 0.0009 max mem: 33300 +Test: [14200/21770] eta: 0:04:58 time: 0.0380 data: 0.0009 max mem: 33300 +Test: [14300/21770] eta: 0:04:54 time: 0.0380 data: 0.0009 max mem: 33300 +Test: [14400/21770] eta: 0:04:50 time: 0.0380 data: 0.0009 max mem: 33300 +Test: [14500/21770] eta: 0:04:46 time: 0.0380 data: 0.0009 max mem: 33300 +Test: [14600/21770] eta: 0:04:42 time: 0.0380 data: 0.0009 max mem: 33300 +Test: [14700/21770] eta: 0:04:38 time: 0.0380 data: 0.0009 max mem: 33300 +Test: [14800/21770] eta: 0:04:34 time: 0.0380 data: 0.0009 max mem: 33300 +Test: [14900/21770] eta: 0:04:30 time: 0.0380 data: 0.0009 max mem: 33300 +Test: [15000/21770] eta: 0:04:26 time: 0.0380 data: 0.0009 max mem: 33300 +Test: [15100/21770] eta: 0:04:22 time: 0.0380 data: 0.0009 max mem: 33300 +Test: [15200/21770] eta: 0:04:18 time: 0.0380 data: 0.0009 max mem: 33300 +Test: [15300/21770] eta: 0:04:14 time: 0.0384 data: 0.0008 max mem: 33300 +Test: [15400/21770] eta: 0:04:10 time: 0.0382 data: 0.0009 max mem: 33300 +Test: [15500/21770] eta: 0:04:06 time: 0.0384 data: 0.0009 max mem: 33300 +Test: [15600/21770] eta: 0:04:02 time: 0.0380 data: 0.0009 max mem: 33300 +Test: [15700/21770] eta: 0:03:58 time: 0.0380 data: 0.0009 max mem: 33300 +Test: [15800/21770] eta: 0:03:54 time: 0.0380 data: 0.0009 max mem: 33300 +Test: [15900/21770] eta: 0:03:50 time: 0.0381 data: 0.0009 max mem: 33300 +Test: [16000/21770] eta: 0:03:46 time: 0.0380 data: 0.0009 max mem: 33300 +Test: [16100/21770] eta: 0:03:42 time: 0.0380 data: 0.0009 max mem: 33300 +Test: [16200/21770] eta: 0:03:38 time: 0.0380 data: 0.0008 max mem: 33300 +Test: [16300/21770] eta: 0:03:34 time: 0.0383 data: 0.0008 max mem: 33300 +Test: [16400/21770] eta: 0:03:31 time: 0.0387 data: 0.0008 max mem: 33300 +Test: [16500/21770] eta: 0:03:27 time: 0.0385 data: 0.0008 max mem: 33300 +Test: [16600/21770] eta: 0:03:23 time: 0.0388 data: 0.0008 max mem: 33300 +Test: [16700/21770] eta: 0:03:19 time: 0.0382 data: 0.0008 max mem: 33300 +Test: [16800/21770] eta: 0:03:15 time: 0.0384 data: 0.0008 max mem: 33300 +Test: [16900/21770] eta: 0:03:11 time: 0.0383 data: 0.0008 max mem: 33300 +Test: [17000/21770] eta: 0:03:07 time: 0.0383 data: 0.0008 max mem: 33300 +Test: [17100/21770] eta: 0:03:03 time: 0.0382 data: 0.0008 max mem: 33300 +Test: [17200/21770] eta: 0:02:59 time: 0.0380 data: 0.0008 max mem: 33300 +Test: [17300/21770] eta: 0:02:55 time: 0.0380 data: 0.0009 max mem: 33300 +Test: [17400/21770] eta: 0:02:51 time: 0.0380 data: 0.0008 max mem: 33300 +Test: [17500/21770] eta: 0:02:47 time: 0.0380 data: 0.0008 max mem: 33300 +Test: [17600/21770] eta: 0:02:43 time: 0.0380 data: 0.0008 max mem: 33300 +Test: [17700/21770] eta: 0:02:39 time: 0.0380 data: 0.0008 max mem: 33300 +Test: [17800/21770] eta: 0:02:35 time: 0.0381 data: 0.0008 max mem: 33300 +Test: [17900/21770] eta: 0:02:31 time: 0.0383 data: 0.0009 max mem: 33300 +Test: [18000/21770] eta: 0:02:27 time: 0.0390 data: 0.0011 max mem: 33300 +Test: [18100/21770] eta: 0:02:23 time: 0.0380 data: 0.0009 max mem: 33300 +Test: [18200/21770] eta: 0:02:19 time: 0.0383 data: 0.0010 max mem: 33300 +Test: [18300/21770] eta: 0:02:16 time: 0.0396 data: 0.0011 max mem: 33300 +Test: [18400/21770] eta: 0:02:12 time: 0.0387 data: 0.0010 max mem: 33300 +Test: [18500/21770] eta: 0:02:08 time: 0.0391 data: 0.0011 max mem: 33300 +Test: [18600/21770] eta: 0:02:04 time: 0.0391 data: 0.0010 max mem: 33300 +Test: [18700/21770] eta: 0:02:00 time: 0.0394 data: 0.0011 max mem: 33300 +Test: [18800/21770] eta: 0:01:56 time: 0.0384 data: 0.0010 max mem: 33300 +Test: [18900/21770] eta: 0:01:52 time: 0.0387 data: 0.0011 max mem: 33300 +Test: [19000/21770] eta: 0:01:48 time: 0.0386 data: 0.0010 max mem: 33300 +Test: [19100/21770] eta: 0:01:44 time: 0.0386 data: 0.0010 max mem: 33300 +Test: [19200/21770] eta: 0:01:40 time: 0.0381 data: 0.0009 max mem: 33300 +Test: [19300/21770] eta: 0:01:36 time: 0.0387 data: 0.0010 max mem: 33300 +Test: [19400/21770] eta: 0:01:32 time: 0.0388 data: 0.0010 max mem: 33300 +Test: [19500/21770] eta: 0:01:28 time: 0.0385 data: 0.0009 max mem: 33300 +Test: [19600/21770] eta: 0:01:25 time: 0.0386 data: 0.0010 max mem: 33300 +Test: [19700/21770] eta: 0:01:21 time: 0.0388 data: 0.0011 max mem: 33300 +Test: [19800/21770] eta: 0:01:17 time: 0.0382 data: 0.0009 max mem: 33300 +Test: [19900/21770] eta: 0:01:13 time: 0.0383 data: 0.0009 max mem: 33300 +Test: [20000/21770] eta: 0:01:09 time: 0.0383 data: 0.0009 max mem: 33300 +Test: [20100/21770] eta: 0:01:05 time: 0.0381 data: 0.0009 max mem: 33300 +Test: [20200/21770] eta: 0:01:01 time: 0.0382 data: 0.0009 max mem: 33300 +Test: [20300/21770] eta: 0:00:57 time: 0.0383 data: 0.0009 max mem: 33300 +Test: [20400/21770] eta: 0:00:53 time: 0.0382 data: 0.0009 max mem: 33300 +Test: [20500/21770] eta: 0:00:49 time: 0.0382 data: 0.0009 max mem: 33300 +Test: [20600/21770] eta: 0:00:45 time: 0.0382 data: 0.0009 max mem: 33300 +Test: [20700/21770] eta: 0:00:41 time: 0.0381 data: 0.0009 max mem: 33300 +Test: [20800/21770] eta: 0:00:37 time: 0.0383 data: 0.0010 max mem: 33300 +Test: [20900/21770] eta: 0:00:34 time: 0.0383 data: 0.0010 max mem: 33300 +Test: [21000/21770] eta: 0:00:30 time: 0.0383 data: 0.0009 max mem: 33300 +Test: [21100/21770] eta: 0:00:26 time: 0.0381 data: 0.0009 max mem: 33300 +Test: [21200/21770] eta: 0:00:22 time: 0.0382 data: 0.0009 max mem: 33300 +Test: [21300/21770] eta: 0:00:18 time: 0.0383 data: 0.0010 max mem: 33300 +Test: [21400/21770] eta: 0:00:14 time: 0.0382 data: 0.0009 max mem: 33300 +Test: [21500/21770] eta: 0:00:10 time: 0.0381 data: 0.0010 max mem: 33300 +Test: [21600/21770] eta: 0:00:06 time: 0.0382 data: 0.0010 max mem: 33300 +Test: [21700/21770] eta: 0:00:02 time: 0.0391 data: 0.0010 max mem: 33300 +Test: Total time: 0:14:11 +Final results: +Mean IoU is 0.00 + + precision@0.5 = 0.00 + precision@0.6 = 0.00 + precision@0.7 = 0.00 + precision@0.8 = 0.00 + precision@0.9 = 0.00 + overall IoU = 0.00 + mean IoU = 0.00 + +Mean accuracy for one-to-zero sample is 100.00 + +Average object IoU 0.0 +Overall IoU 0.0 +Epoch: [10] [ 0/4276] eta: 6:46:32 lr: 3.859420456098877e-05 loss: 0.1311 (0.1311) time: 5.7045 data: 2.5797 max mem: 33300 +Epoch: [10] [ 10/4276] eta: 3:54:16 lr: 3.8591496797481385e-05 loss: 0.1743 (0.1724) time: 3.2950 data: 0.2403 max mem: 33300 +Epoch: [10] [ 20/4276] eta: 3:54:56 lr: 3.858878901286388e-05 loss: 0.1674 (0.1721) time: 3.1926 data: 0.0065 max mem: 33300 +Epoch: [10] [ 30/4276] eta: 3:56:38 lr: 3.858608120713444e-05 loss: 0.1578 (0.1713) time: 3.3709 data: 0.0070 max mem: 33300 +Epoch: [10] [ 40/4276] eta: 3:52:57 lr: 3.858337338029126e-05 loss: 0.1548 (0.1687) time: 3.2863 data: 0.0080 max mem: 33300 +Epoch: [10] [ 50/4276] eta: 3:49:32 lr: 3.858066553233252e-05 loss: 0.1535 (0.1676) time: 3.1271 data: 0.0076 max mem: 33300 +Epoch: [10] [ 60/4276] eta: 3:46:33 lr: 3.857795766325643e-05 loss: 0.1583 (0.1672) time: 3.0699 data: 0.0068 max mem: 33300 +Epoch: [10] [ 70/4276] eta: 3:44:11 lr: 3.857524977306115e-05 loss: 0.1525 (0.1654) time: 3.0437 data: 0.0076 max mem: 33300 +Epoch: [10] [ 80/4276] eta: 3:42:09 lr: 3.8572541861744896e-05 loss: 0.1556 (0.1649) time: 3.0317 data: 0.0078 max mem: 33300 +Epoch: [10] [ 90/4276] eta: 3:40:38 lr: 3.856983392930583e-05 loss: 0.1435 (0.1633) time: 3.0353 data: 0.0074 max mem: 33300 +Epoch: [10] [ 100/4276] eta: 3:39:30 lr: 3.856712597574216e-05 loss: 0.1435 (0.1644) time: 3.0608 data: 0.0071 max mem: 33300 +Epoch: [10] [ 110/4276] eta: 3:38:38 lr: 3.856441800105206e-05 loss: 0.1540 (0.1643) time: 3.0874 data: 0.0074 max mem: 33300 +Epoch: [10] [ 120/4276] eta: 3:37:40 lr: 3.8561710005233716e-05 loss: 0.1511 (0.1632) time: 3.0855 data: 0.0074 max mem: 33300 +Epoch: [10] [ 130/4276] eta: 3:36:46 lr: 3.855900198828532e-05 loss: 0.1543 (0.1641) time: 3.0712 data: 0.0072 max mem: 33300 +Epoch: [10] [ 140/4276] eta: 3:36:07 lr: 3.855629395020506e-05 loss: 0.1543 (0.1634) time: 3.0922 data: 0.0074 max mem: 33300 +Epoch: [10] [ 150/4276] eta: 3:35:10 lr: 3.855358589099112e-05 loss: 0.1578 (0.1629) time: 3.0773 data: 0.0077 max mem: 33300 +Epoch: [10] [ 160/4276] eta: 3:33:57 lr: 3.855087781064169e-05 loss: 0.1578 (0.1626) time: 3.0034 data: 0.0076 max mem: 33300 +Epoch: [10] [ 170/4276] eta: 3:32:32 lr: 3.854816970915494e-05 loss: 0.1586 (0.1626) time: 2.9288 data: 0.0070 max mem: 33300 +Epoch: [10] [ 180/4276] eta: 8:09:34 lr: 3.854546158652908e-05 loss: 0.1666 (0.1635) time: 39.7943 data: 36.8305 max mem: 33300 +Epoch: [10] [ 190/4276] eta: 7:53:41 lr: 3.854275344276227e-05 loss: 0.1621 (0.1638) time: 39.8749 data: 36.8307 max mem: 33300 +Epoch: [10] [ 200/4276] eta: 7:39:18 lr: 3.854004527785271e-05 loss: 0.1509 (0.1644) time: 3.0489 data: 0.0078 max mem: 33300 +Epoch: [10] [ 210/4276] eta: 7:26:14 lr: 3.8537337091798574e-05 loss: 0.1656 (0.1650) time: 3.0431 data: 0.0080 max mem: 33300 +Epoch: [10] [ 220/4276] eta: 7:14:29 lr: 3.853462888459806e-05 loss: 0.1656 (0.1651) time: 3.0717 data: 0.0076 max mem: 33300 +Epoch: [10] [ 230/4276] eta: 7:03:39 lr: 3.853192065624934e-05 loss: 0.1620 (0.1646) time: 3.0922 data: 0.0074 max mem: 33300 +Epoch: [10] [ 240/4276] eta: 6:53:36 lr: 3.852921240675059e-05 loss: 0.1569 (0.1649) time: 3.0709 data: 0.0069 max mem: 33300 +Epoch: [10] [ 250/4276] eta: 6:44:22 lr: 3.8526504136100016e-05 loss: 0.1642 (0.1656) time: 3.0690 data: 0.0070 max mem: 33300 +Epoch: [10] [ 260/4276] eta: 6:35:46 lr: 3.852379584429578e-05 loss: 0.1664 (0.1657) time: 3.0694 data: 0.0070 max mem: 33300 +Epoch: [10] [ 270/4276] eta: 6:27:46 lr: 3.8521087531336074e-05 loss: 0.1586 (0.1657) time: 3.0644 data: 0.0069 max mem: 33300 +Epoch: [10] [ 280/4276] eta: 6:20:16 lr: 3.851837919721908e-05 loss: 0.1630 (0.1654) time: 3.0605 data: 0.0073 max mem: 33300 +Epoch: [10] [ 290/4276] eta: 6:13:15 lr: 3.8515670841942976e-05 loss: 0.1560 (0.1650) time: 3.0523 data: 0.0074 max mem: 33300 +Epoch: [10] [ 300/4276] eta: 6:06:40 lr: 3.851296246550594e-05 loss: 0.1432 (0.1646) time: 3.0515 data: 0.0076 max mem: 33300 +Epoch: [10] [ 310/4276] eta: 6:00:27 lr: 3.851025406790617e-05 loss: 0.1407 (0.1639) time: 3.0485 data: 0.0078 max mem: 33300 +Epoch: [10] [ 320/4276] eta: 5:54:36 lr: 3.8507545649141826e-05 loss: 0.1638 (0.1645) time: 3.0485 data: 0.0074 max mem: 33300 +Epoch: [10] [ 330/4276] eta: 5:49:07 lr: 3.8504837209211106e-05 loss: 0.1665 (0.1646) time: 3.0582 data: 0.0070 max mem: 33300 +Epoch: [10] [ 340/4276] eta: 5:43:58 lr: 3.850212874811217e-05 loss: 0.1570 (0.1645) time: 3.0778 data: 0.0073 max mem: 33300 +Epoch: [10] [ 350/4276] eta: 5:39:10 lr: 3.8499420265843216e-05 loss: 0.1539 (0.1643) time: 3.1142 data: 0.0078 max mem: 33300 +Epoch: [10] [ 360/4276] eta: 5:34:27 lr: 3.849671176240241e-05 loss: 0.1682 (0.1653) time: 3.0979 data: 0.0076 max mem: 33300 +Epoch: [10] [ 370/4276] eta: 5:30:00 lr: 3.849400323778795e-05 loss: 0.1626 (0.1647) time: 3.0626 data: 0.0075 max mem: 33300 +Epoch: [10] [ 380/4276] eta: 5:25:42 lr: 3.8491294691998005e-05 loss: 0.1474 (0.1648) time: 3.0587 data: 0.0083 max mem: 33300 +Epoch: [10] [ 390/4276] eta: 5:21:38 lr: 3.848858612503075e-05 loss: 0.1493 (0.1648) time: 3.0561 data: 0.0086 max mem: 33300 +Epoch: [10] [ 400/4276] eta: 5:17:48 lr: 3.848587753688436e-05 loss: 0.1628 (0.1648) time: 3.0802 data: 0.0083 max mem: 33300 +Epoch: [10] [ 410/4276] eta: 5:14:03 lr: 3.848316892755703e-05 loss: 0.1577 (0.1644) time: 3.0765 data: 0.0081 max mem: 33300 +Epoch: [10] [ 420/4276] eta: 5:10:32 lr: 3.848046029704693e-05 loss: 0.1512 (0.1645) time: 3.0799 data: 0.0081 max mem: 33300 +Epoch: [10] [ 430/4276] eta: 5:07:04 lr: 3.847775164535222e-05 loss: 0.1691 (0.1647) time: 3.0732 data: 0.0080 max mem: 33300 +Epoch: [10] [ 440/4276] eta: 5:03:46 lr: 3.84750429724711e-05 loss: 0.1691 (0.1647) time: 3.0523 data: 0.0075 max mem: 33300 +Epoch: [10] [ 450/4276] eta: 5:00:38 lr: 3.8472334278401746e-05 loss: 0.1596 (0.1647) time: 3.0797 data: 0.0079 max mem: 33300 +Epoch: [10] [ 460/4276] eta: 4:57:36 lr: 3.8469625563142317e-05 loss: 0.1452 (0.1643) time: 3.0889 data: 0.0084 max mem: 33300 +Epoch: [10] [ 470/4276] eta: 4:54:36 lr: 3.846691682669101e-05 loss: 0.1361 (0.1638) time: 3.0554 data: 0.0084 max mem: 33300 +Epoch: [10] [ 480/4276] eta: 4:51:40 lr: 3.8464208069045984e-05 loss: 0.1343 (0.1633) time: 3.0143 data: 0.0082 max mem: 33300 +Epoch: [10] [ 490/4276] eta: 4:48:53 lr: 3.8461499290205436e-05 loss: 0.1353 (0.1629) time: 3.0232 data: 0.0076 max mem: 33300 +Epoch: [10] [ 500/4276] eta: 4:46:13 lr: 3.8458790490167515e-05 loss: 0.1353 (0.1626) time: 3.0537 data: 0.0078 max mem: 33300 +Epoch: [10] [ 510/4276] eta: 4:43:39 lr: 3.845608166893041e-05 loss: 0.1512 (0.1625) time: 3.0715 data: 0.0081 max mem: 33300 +Epoch: [10] [ 520/4276] eta: 4:41:12 lr: 3.84533728264923e-05 loss: 0.1559 (0.1625) time: 3.0947 data: 0.0080 max mem: 33300 +Epoch: [10] [ 530/4276] eta: 4:38:48 lr: 3.845066396285135e-05 loss: 0.1583 (0.1624) time: 3.0949 data: 0.0077 max mem: 33300 +Epoch: [10] [ 540/4276] eta: 4:36:30 lr: 3.844795507800575e-05 loss: 0.1505 (0.1622) time: 3.1019 data: 0.0080 max mem: 33300 +Epoch: [10] [ 550/4276] eta: 4:34:15 lr: 3.8445246171953646e-05 loss: 0.1440 (0.1621) time: 3.1046 data: 0.0082 max mem: 33300 +Epoch: [10] [ 560/4276] eta: 4:32:00 lr: 3.844253724469325e-05 loss: 0.1557 (0.1622) time: 3.0740 data: 0.0079 max mem: 33300 +Epoch: [10] [ 570/4276] eta: 4:29:50 lr: 3.843982829622269e-05 loss: 0.1659 (0.1622) time: 3.0586 data: 0.0080 max mem: 33300 +Epoch: [10] [ 580/4276] eta: 4:27:43 lr: 3.843711932654018e-05 loss: 0.1622 (0.1622) time: 3.0618 data: 0.0082 max mem: 33300 +Epoch: [10] [ 590/4276] eta: 4:25:39 lr: 3.8434410335643866e-05 loss: 0.1485 (0.1619) time: 3.0589 data: 0.0080 max mem: 33300 +Epoch: [10] [ 600/4276] eta: 4:23:41 lr: 3.8431701323531935e-05 loss: 0.1487 (0.1617) time: 3.0777 data: 0.0079 max mem: 33300 +Epoch: [10] [ 610/4276] eta: 4:21:47 lr: 3.8428992290202547e-05 loss: 0.1498 (0.1615) time: 3.1097 data: 0.0080 max mem: 33300 +Epoch: [10] [ 620/4276] eta: 4:19:55 lr: 3.842628323565389e-05 loss: 0.1496 (0.1616) time: 3.1175 data: 0.0082 max mem: 33300 +Epoch: [10] [ 630/4276] eta: 4:18:05 lr: 3.842357415988413e-05 loss: 0.1596 (0.1618) time: 3.1090 data: 0.0083 max mem: 33300 +Epoch: [10] [ 640/4276] eta: 4:16:21 lr: 3.842086506289143e-05 loss: 0.1593 (0.1616) time: 3.1237 data: 0.0087 max mem: 33300 +Epoch: [10] [ 650/4276] eta: 4:14:33 lr: 3.841815594467397e-05 loss: 0.1451 (0.1615) time: 3.1015 data: 0.0085 max mem: 33300 +Epoch: [10] [ 660/4276] eta: 4:12:48 lr: 3.841544680522991e-05 loss: 0.1649 (0.1616) time: 3.0578 data: 0.0082 max mem: 33300 +Epoch: [10] [ 670/4276] eta: 4:11:05 lr: 3.841273764455743e-05 loss: 0.1649 (0.1616) time: 3.0624 data: 0.0083 max mem: 33300 +Epoch: [10] [ 680/4276] eta: 4:09:24 lr: 3.84100284626547e-05 loss: 0.1530 (0.1616) time: 3.0623 data: 0.0083 max mem: 33300 +Epoch: [10] [ 690/4276] eta: 4:07:45 lr: 3.840731925951988e-05 loss: 0.1651 (0.1615) time: 3.0540 data: 0.0079 max mem: 33300 +Epoch: [10] [ 700/4276] eta: 4:06:05 lr: 3.8404610035151165e-05 loss: 0.1570 (0.1615) time: 3.0230 data: 0.0082 max mem: 33300 +Epoch: [10] [ 710/4276] eta: 4:04:28 lr: 3.8401900789546694e-05 loss: 0.1634 (0.1615) time: 3.0109 data: 0.0086 max mem: 33300 +Epoch: [10] [ 720/4276] eta: 4:02:53 lr: 3.839919152270465e-05 loss: 0.1624 (0.1614) time: 3.0213 data: 0.0081 max mem: 33300 +Epoch: [10] [ 730/4276] eta: 4:01:20 lr: 3.8396482234623195e-05 loss: 0.1525 (0.1614) time: 3.0275 data: 0.0076 max mem: 33300 +Epoch: [10] [ 740/4276] eta: 3:59:54 lr: 3.83937729253005e-05 loss: 0.1503 (0.1613) time: 3.0852 data: 0.0077 max mem: 33300 +Epoch: [10] [ 750/4276] eta: 3:58:27 lr: 3.8391063594734736e-05 loss: 0.1503 (0.1613) time: 3.1087 data: 0.0084 max mem: 33300 +Epoch: [10] [ 760/4276] eta: 3:57:00 lr: 3.8388354242924076e-05 loss: 0.1587 (0.1613) time: 3.0693 data: 0.0087 max mem: 33300 +Epoch: [10] [ 770/4276] eta: 3:55:35 lr: 3.838564486986667e-05 loss: 0.1522 (0.1613) time: 3.0510 data: 0.0085 max mem: 33300 +Epoch: [10] [ 780/4276] eta: 3:54:09 lr: 3.838293547556071e-05 loss: 0.1526 (0.1613) time: 3.0382 data: 0.0084 max mem: 33300 +Epoch: [10] [ 790/4276] eta: 3:52:44 lr: 3.8380226060004336e-05 loss: 0.1610 (0.1614) time: 3.0167 data: 0.0082 max mem: 33300 +Epoch: [10] [ 800/4276] eta: 3:51:23 lr: 3.837751662319574e-05 loss: 0.1596 (0.1615) time: 3.0293 data: 0.0084 max mem: 33300 +Epoch: [10] [ 810/4276] eta: 3:50:05 lr: 3.837480716513307e-05 loss: 0.1507 (0.1615) time: 3.0835 data: 0.0087 max mem: 33300 +Epoch: [10] [ 820/4276] eta: 3:48:48 lr: 3.837209768581449e-05 loss: 0.1501 (0.1613) time: 3.1006 data: 0.0088 max mem: 33300 +Epoch: [10] [ 830/4276] eta: 3:47:32 lr: 3.836938818523818e-05 loss: 0.1465 (0.1614) time: 3.0961 data: 0.0084 max mem: 33300 +Epoch: [10] [ 840/4276] eta: 3:46:17 lr: 3.836667866340229e-05 loss: 0.1600 (0.1614) time: 3.0975 data: 0.0081 max mem: 33300 +Epoch: [10] [ 850/4276] eta: 3:45:00 lr: 3.8363969120305e-05 loss: 0.1422 (0.1613) time: 3.0583 data: 0.0084 max mem: 33300 +Epoch: [10] [ 860/4276] eta: 3:43:45 lr: 3.836125955594446e-05 loss: 0.1465 (0.1613) time: 3.0352 data: 0.0082 max mem: 33300 +Epoch: [10] [ 870/4276] eta: 3:42:32 lr: 3.835854997031885e-05 loss: 0.1541 (0.1613) time: 3.0475 data: 0.0084 max mem: 33300 +Epoch: [10] [ 880/4276] eta: 3:41:20 lr: 3.835584036342633e-05 loss: 0.1550 (0.1614) time: 3.0634 data: 0.0084 max mem: 33300 +Epoch: [10] [ 890/4276] eta: 3:40:09 lr: 3.8353130735265045e-05 loss: 0.1795 (0.1616) time: 3.0711 data: 0.0083 max mem: 33300 +Epoch: [10] [ 900/4276] eta: 3:38:58 lr: 3.8350421085833185e-05 loss: 0.1660 (0.1616) time: 3.0656 data: 0.0086 max mem: 33300 +Epoch: [10] [ 910/4276] eta: 3:37:50 lr: 3.834771141512889e-05 loss: 0.1602 (0.1617) time: 3.0805 data: 0.0091 max mem: 33300 +Epoch: [10] [ 920/4276] eta: 3:36:42 lr: 3.834500172315034e-05 loss: 0.1610 (0.1618) time: 3.0856 data: 0.0092 max mem: 33300 +Epoch: [10] [ 930/4276] eta: 3:35:36 lr: 3.8342292009895695e-05 loss: 0.1610 (0.1619) time: 3.1017 data: 0.0086 max mem: 33300 +Epoch: [10] [ 940/4276] eta: 3:34:30 lr: 3.833958227536311e-05 loss: 0.1576 (0.1617) time: 3.1033 data: 0.0084 max mem: 33300 +Epoch: [10] [ 950/4276] eta: 3:33:24 lr: 3.833687251955076e-05 loss: 0.1547 (0.1617) time: 3.0771 data: 0.0087 max mem: 33300 +Epoch: [10] [ 960/4276] eta: 3:32:19 lr: 3.833416274245679e-05 loss: 0.1632 (0.1619) time: 3.0832 data: 0.0085 max mem: 33300 +Epoch: [10] [ 970/4276] eta: 3:31:14 lr: 3.833145294407936e-05 loss: 0.1677 (0.1618) time: 3.0786 data: 0.0079 max mem: 33300 +Epoch: [10] [ 980/4276] eta: 3:30:09 lr: 3.832874312441665e-05 loss: 0.1628 (0.1619) time: 3.0586 data: 0.0079 max mem: 33300 +Epoch: [10] [ 990/4276] eta: 3:29:05 lr: 3.832603328346681e-05 loss: 0.1605 (0.1619) time: 3.0510 data: 0.0081 max mem: 33300 +Epoch: [10] [1000/4276] eta: 3:28:04 lr: 3.832332342122799e-05 loss: 0.1530 (0.1619) time: 3.0706 data: 0.0086 max mem: 33300 +Epoch: [10] [1010/4276] eta: 3:27:02 lr: 3.8320613537698374e-05 loss: 0.1637 (0.1619) time: 3.0920 data: 0.0087 max mem: 33300 +Epoch: [10] [1020/4276] eta: 3:26:02 lr: 3.8317903632876106e-05 loss: 0.1523 (0.1618) time: 3.1072 data: 0.0084 max mem: 33300 +Epoch: [10] [1030/4276] eta: 3:25:04 lr: 3.831519370675935e-05 loss: 0.1503 (0.1618) time: 3.1414 data: 0.0090 max mem: 33300 +Epoch: [10] [1040/4276] eta: 3:24:04 lr: 3.8312483759346256e-05 loss: 0.1546 (0.1619) time: 3.1169 data: 0.0090 max mem: 33300 +Epoch: [10] [1050/4276] eta: 3:23:04 lr: 3.8309773790634996e-05 loss: 0.1550 (0.1619) time: 3.0685 data: 0.0082 max mem: 33300 +Epoch: [10] [1060/4276] eta: 3:22:05 lr: 3.8307063800623724e-05 loss: 0.1580 (0.1619) time: 3.0586 data: 0.0084 max mem: 33300 +Epoch: [10] [1070/4276] eta: 3:21:05 lr: 3.830435378931059e-05 loss: 0.1686 (0.1620) time: 3.0519 data: 0.0088 max mem: 33300 +Epoch: [10] [1080/4276] eta: 3:20:07 lr: 3.830164375669376e-05 loss: 0.1650 (0.1619) time: 3.0504 data: 0.0091 max mem: 33300 +Epoch: [10] [1090/4276] eta: 3:19:09 lr: 3.82989337027714e-05 loss: 0.1628 (0.1619) time: 3.0600 data: 0.0085 max mem: 33300 +Epoch: [10] [1100/4276] eta: 3:18:13 lr: 3.829622362754165e-05 loss: 0.1528 (0.1619) time: 3.0888 data: 0.0081 max mem: 33300 +Epoch: [10] [1110/4276] eta: 3:17:17 lr: 3.829351353100268e-05 loss: 0.1528 (0.1620) time: 3.0964 data: 0.0086 max mem: 33300 +Epoch: [10] [1120/4276] eta: 3:16:22 lr: 3.8290803413152644e-05 loss: 0.1550 (0.1620) time: 3.0968 data: 0.0083 max mem: 33300 +Epoch: [10] [1130/4276] eta: 3:15:27 lr: 3.828809327398969e-05 loss: 0.1403 (0.1618) time: 3.1045 data: 0.0081 max mem: 33300 +Epoch: [10] [1140/4276] eta: 3:14:31 lr: 3.828538311351198e-05 loss: 0.1403 (0.1616) time: 3.0834 data: 0.0086 max mem: 33300 +Epoch: [10] [1150/4276] eta: 3:13:36 lr: 3.828267293171768e-05 loss: 0.1426 (0.1615) time: 3.0623 data: 0.0084 max mem: 33300 +Epoch: [10] [1160/4276] eta: 3:12:42 lr: 3.827996272860493e-05 loss: 0.1617 (0.1615) time: 3.0789 data: 0.0080 max mem: 33300 +Epoch: [10] [1170/4276] eta: 3:11:48 lr: 3.827725250417189e-05 loss: 0.1704 (0.1616) time: 3.0782 data: 0.0086 max mem: 33300 +Epoch: [10] [1180/4276] eta: 3:10:53 lr: 3.8274542258416724e-05 loss: 0.1679 (0.1616) time: 3.0347 data: 0.0085 max mem: 33300 +Epoch: [10] [1190/4276] eta: 3:09:58 lr: 3.827183199133757e-05 loss: 0.1486 (0.1615) time: 3.0210 data: 0.0081 max mem: 33300 +Epoch: [10] [1200/4276] eta: 3:09:06 lr: 3.826912170293259e-05 loss: 0.1473 (0.1615) time: 3.0671 data: 0.0082 max mem: 33300 +Epoch: [10] [1210/4276] eta: 3:08:14 lr: 3.826641139319994e-05 loss: 0.1387 (0.1614) time: 3.1029 data: 0.0079 max mem: 33300 +Epoch: [10] [1220/4276] eta: 3:07:24 lr: 3.826370106213778e-05 loss: 0.1573 (0.1614) time: 3.1203 data: 0.0078 max mem: 33300 +Epoch: [10] [1230/4276] eta: 3:06:33 lr: 3.8260990709744246e-05 loss: 0.1640 (0.1615) time: 3.1312 data: 0.0080 max mem: 33300 +Epoch: [10] [1240/4276] eta: 3:05:42 lr: 3.8258280336017514e-05 loss: 0.1617 (0.1615) time: 3.1044 data: 0.0080 max mem: 33300 +Epoch: [10] [1250/4276] eta: 3:04:51 lr: 3.8255569940955717e-05 loss: 0.1594 (0.1615) time: 3.0758 data: 0.0078 max mem: 33300 +Epoch: [10] [1260/4276] eta: 3:04:00 lr: 3.8252859524557024e-05 loss: 0.1495 (0.1614) time: 3.0712 data: 0.0085 max mem: 33300 +Epoch: [10] [1270/4276] eta: 3:03:09 lr: 3.8250149086819565e-05 loss: 0.1400 (0.1613) time: 3.0714 data: 0.0087 max mem: 33300 +Epoch: [10] [1280/4276] eta: 3:02:19 lr: 3.824743862774151e-05 loss: 0.1617 (0.1613) time: 3.0692 data: 0.0085 max mem: 33300 +Epoch: [10] [1290/4276] eta: 3:01:29 lr: 3.8244728147321005e-05 loss: 0.1663 (0.1614) time: 3.0711 data: 0.0085 max mem: 33300 +Epoch: [10] [1300/4276] eta: 3:00:41 lr: 3.82420176455562e-05 loss: 0.1446 (0.1613) time: 3.0957 data: 0.0088 max mem: 33300 +Epoch: [10] [1310/4276] eta: 2:59:52 lr: 3.8239307122445244e-05 loss: 0.1439 (0.1612) time: 3.1083 data: 0.0088 max mem: 33300 +Epoch: [10] [1320/4276] eta: 2:59:04 lr: 3.82365965779863e-05 loss: 0.1663 (0.1613) time: 3.1070 data: 0.0085 max mem: 33300 +Epoch: [10] [1330/4276] eta: 2:58:15 lr: 3.823388601217751e-05 loss: 0.1554 (0.1612) time: 3.0853 data: 0.0085 max mem: 33300 +Epoch: [10] [1340/4276] eta: 2:57:26 lr: 3.823117542501702e-05 loss: 0.1468 (0.1611) time: 3.0518 data: 0.0087 max mem: 33300 +Epoch: [10] [1350/4276] eta: 2:56:37 lr: 3.822846481650298e-05 loss: 0.1507 (0.1612) time: 3.0603 data: 0.0089 max mem: 33300 +Epoch: [10] [1360/4276] eta: 2:55:49 lr: 3.822575418663355e-05 loss: 0.1690 (0.1612) time: 3.0705 data: 0.0086 max mem: 33300 +Epoch: [10] [1370/4276] eta: 2:55:02 lr: 3.822304353540687e-05 loss: 0.1539 (0.1611) time: 3.0743 data: 0.0080 max mem: 33300 +Epoch: [10] [1380/4276] eta: 2:54:15 lr: 3.822033286282109e-05 loss: 0.1547 (0.1612) time: 3.0906 data: 0.0079 max mem: 33300 +Epoch: [10] [1390/4276] eta: 2:53:28 lr: 3.821762216887436e-05 loss: 0.1706 (0.1613) time: 3.0952 data: 0.0084 max mem: 33300 +Epoch: [10] [1400/4276] eta: 2:52:42 lr: 3.821491145356483e-05 loss: 0.1732 (0.1614) time: 3.0969 data: 0.0083 max mem: 33300 +Epoch: [10] [1410/4276] eta: 2:51:56 lr: 3.821220071689064e-05 loss: 0.1586 (0.1614) time: 3.1226 data: 0.0082 max mem: 33300 +Epoch: [10] [1420/4276] eta: 2:51:11 lr: 3.820948995884995e-05 loss: 0.1423 (0.1615) time: 3.1297 data: 0.0085 max mem: 33300 +Epoch: [10] [1430/4276] eta: 2:50:24 lr: 3.820677917944089e-05 loss: 0.1423 (0.1614) time: 3.0930 data: 0.0087 max mem: 33300 +Epoch: [10] [1440/4276] eta: 2:49:38 lr: 3.820406837866162e-05 loss: 0.1549 (0.1614) time: 3.0817 data: 0.0085 max mem: 33300 +Epoch: [10] [1450/4276] eta: 2:48:52 lr: 3.820135755651029e-05 loss: 0.1669 (0.1614) time: 3.0829 data: 0.0083 max mem: 33300 +Epoch: [10] [1460/4276] eta: 2:48:07 lr: 3.819864671298504e-05 loss: 0.1551 (0.1614) time: 3.0684 data: 0.0085 max mem: 33300 +Epoch: [10] [1470/4276] eta: 2:47:21 lr: 3.8195935848084014e-05 loss: 0.1610 (0.1614) time: 3.0620 data: 0.0093 max mem: 33300 +Epoch: [10] [1480/4276] eta: 2:46:35 lr: 3.819322496180536e-05 loss: 0.1474 (0.1613) time: 3.0587 data: 0.0089 max mem: 33300 +Epoch: [10] [1490/4276] eta: 2:45:50 lr: 3.819051405414722e-05 loss: 0.1397 (0.1613) time: 3.0758 data: 0.0080 max mem: 33300 +Epoch: [10] [1500/4276] eta: 2:45:06 lr: 3.818780312510775e-05 loss: 0.1575 (0.1613) time: 3.0968 data: 0.0082 max mem: 33300 +Epoch: [10] [1510/4276] eta: 2:44:23 lr: 3.818509217468509e-05 loss: 0.1639 (0.1613) time: 3.1395 data: 0.0080 max mem: 33300 +Epoch: [10] [1520/4276] eta: 2:43:39 lr: 3.818238120287737e-05 loss: 0.1567 (0.1613) time: 3.1409 data: 0.0077 max mem: 33300 +Epoch: [10] [1530/4276] eta: 2:42:54 lr: 3.8179670209682756e-05 loss: 0.1559 (0.1612) time: 3.0691 data: 0.0077 max mem: 33300 +Epoch: [10] [1540/4276] eta: 2:42:09 lr: 3.8176959195099374e-05 loss: 0.1686 (0.1613) time: 3.0213 data: 0.0080 max mem: 33300 +Epoch: [10] [1550/4276] eta: 2:41:24 lr: 3.8174248159125394e-05 loss: 0.1706 (0.1614) time: 3.0152 data: 0.0084 max mem: 33300 +Epoch: [10] [1560/4276] eta: 2:40:39 lr: 3.8171537101758926e-05 loss: 0.1554 (0.1613) time: 3.0252 data: 0.0084 max mem: 33300 +Epoch: [10] [1570/4276] eta: 2:39:54 lr: 3.8168826022998134e-05 loss: 0.1554 (0.1613) time: 3.0296 data: 0.0085 max mem: 33300 +Epoch: [10] [1580/4276] eta: 2:39:12 lr: 3.816611492284115e-05 loss: 0.1546 (0.1613) time: 3.0669 data: 0.0083 max mem: 33300 +Epoch: [10] [1590/4276] eta: 2:38:29 lr: 3.8163403801286124e-05 loss: 0.1491 (0.1612) time: 3.1046 data: 0.0080 max mem: 33300 +Epoch: [10] [1600/4276] eta: 2:37:46 lr: 3.816069265833119e-05 loss: 0.1529 (0.1612) time: 3.1094 data: 0.0079 max mem: 33300 +Epoch: [10] [1610/4276] eta: 2:37:04 lr: 3.81579814939745e-05 loss: 0.1442 (0.1611) time: 3.1189 data: 0.0081 max mem: 33300 +Epoch: [10] [1620/4276] eta: 2:36:21 lr: 3.815527030821419e-05 loss: 0.1419 (0.1611) time: 3.1044 data: 0.0086 max mem: 33300 +Epoch: [10] [1630/4276] eta: 2:35:38 lr: 3.8152559101048414e-05 loss: 0.1508 (0.1611) time: 3.0784 data: 0.0087 max mem: 33300 +Epoch: [10] [1640/4276] eta: 2:34:56 lr: 3.814984787247528e-05 loss: 0.1499 (0.1610) time: 3.0675 data: 0.0082 max mem: 33300 +Epoch: [10] [1650/4276] eta: 2:34:14 lr: 3.814713662249297e-05 loss: 0.1428 (0.1610) time: 3.0821 data: 0.0082 max mem: 33300 +Epoch: [10] [1660/4276] eta: 2:33:31 lr: 3.814442535109959e-05 loss: 0.1561 (0.1611) time: 3.0856 data: 0.0081 max mem: 33300 +Epoch: [10] [1670/4276] eta: 2:32:49 lr: 3.8141714058293295e-05 loss: 0.1561 (0.1611) time: 3.0772 data: 0.0080 max mem: 33300 +Epoch: [10] [1680/4276] eta: 2:32:07 lr: 3.8139002744072224e-05 loss: 0.1582 (0.1611) time: 3.0782 data: 0.0081 max mem: 33300 +Epoch: [10] [1690/4276] eta: 2:31:26 lr: 3.813629140843451e-05 loss: 0.1561 (0.1611) time: 3.0916 data: 0.0080 max mem: 33300 +Epoch: [10] [1700/4276] eta: 2:30:45 lr: 3.81335800513783e-05 loss: 0.1552 (0.1612) time: 3.1181 data: 0.0082 max mem: 33300 +Epoch: [10] [1710/4276] eta: 2:30:04 lr: 3.813086867290174e-05 loss: 0.1775 (0.1613) time: 3.1314 data: 0.0084 max mem: 33300 +Epoch: [10] [1720/4276] eta: 2:29:23 lr: 3.812815727300295e-05 loss: 0.1775 (0.1614) time: 3.1291 data: 0.0081 max mem: 33300 +Epoch: [10] [1730/4276] eta: 2:28:42 lr: 3.812544585168008e-05 loss: 0.1643 (0.1614) time: 3.1169 data: 0.0078 max mem: 33300 +Epoch: [10] [1740/4276] eta: 2:28:01 lr: 3.812273440893126e-05 loss: 0.1552 (0.1614) time: 3.1098 data: 0.0081 max mem: 33300 +Epoch: [10] [1750/4276] eta: 2:27:19 lr: 3.8120022944754625e-05 loss: 0.1516 (0.1613) time: 3.0626 data: 0.0080 max mem: 33300 +Epoch: [10] [1760/4276] eta: 2:26:38 lr: 3.811731145914832e-05 loss: 0.1453 (0.1612) time: 3.0342 data: 0.0076 max mem: 33300 +Epoch: [10] [1770/4276] eta: 2:25:57 lr: 3.811459995211049e-05 loss: 0.1458 (0.1613) time: 3.0606 data: 0.0076 max mem: 33300 +Epoch: [10] [1780/4276] eta: 2:25:16 lr: 3.811188842363926e-05 loss: 0.1556 (0.1614) time: 3.0668 data: 0.0080 max mem: 33300 +Epoch: [10] [1790/4276] eta: 2:24:36 lr: 3.810917687373276e-05 loss: 0.1584 (0.1614) time: 3.0865 data: 0.0085 max mem: 33300 +Epoch: [10] [1800/4276] eta: 2:23:56 lr: 3.8106465302389145e-05 loss: 0.1584 (0.1614) time: 3.1354 data: 0.0084 max mem: 33300 +Epoch: [10] [1810/4276] eta: 2:23:17 lr: 3.810375370960653e-05 loss: 0.1702 (0.1615) time: 3.1571 data: 0.0082 max mem: 33300 +Epoch: [10] [1820/4276] eta: 2:22:37 lr: 3.810104209538307e-05 loss: 0.1618 (0.1614) time: 3.1204 data: 0.0079 max mem: 33300 +Epoch: [10] [1830/4276] eta: 2:21:56 lr: 3.8098330459716876e-05 loss: 0.1440 (0.1614) time: 3.0816 data: 0.0079 max mem: 33300 +Epoch: [10] [1840/4276] eta: 2:21:16 lr: 3.80956188026061e-05 loss: 0.1440 (0.1613) time: 3.0785 data: 0.0083 max mem: 33300 +Epoch: [10] [1850/4276] eta: 2:20:36 lr: 3.8092907124048885e-05 loss: 0.1593 (0.1614) time: 3.0754 data: 0.0082 max mem: 33300 +Epoch: [10] [1860/4276] eta: 2:19:56 lr: 3.8090195424043345e-05 loss: 0.1593 (0.1614) time: 3.0741 data: 0.0087 max mem: 33300 +Epoch: [10] [1870/4276] eta: 2:19:16 lr: 3.808748370258762e-05 loss: 0.1477 (0.1615) time: 3.0722 data: 0.0089 max mem: 33300 +Epoch: [10] [1880/4276] eta: 2:18:37 lr: 3.808477195967985e-05 loss: 0.1608 (0.1615) time: 3.0958 data: 0.0088 max mem: 33300 +Epoch: [10] [1890/4276] eta: 2:17:58 lr: 3.808206019531816e-05 loss: 0.1601 (0.1615) time: 3.1348 data: 0.0086 max mem: 33300 +Epoch: [10] [1900/4276] eta: 2:17:19 lr: 3.807934840950068e-05 loss: 0.1419 (0.1615) time: 3.1465 data: 0.0085 max mem: 33300 +Epoch: [10] [1910/4276] eta: 2:16:40 lr: 3.807663660222556e-05 loss: 0.1482 (0.1615) time: 3.1078 data: 0.0084 max mem: 33300 +Epoch: [10] [1920/4276] eta: 2:16:00 lr: 3.807392477349091e-05 loss: 0.1482 (0.1614) time: 3.0605 data: 0.0078 max mem: 33300 +Epoch: [10] [1930/4276] eta: 2:15:21 lr: 3.8071212923294876e-05 loss: 0.1425 (0.1614) time: 3.0583 data: 0.0079 max mem: 33300 +Epoch: [10] [1940/4276] eta: 2:14:41 lr: 3.806850105163559e-05 loss: 0.1570 (0.1614) time: 3.0647 data: 0.0084 max mem: 33300 +Epoch: [10] [1950/4276] eta: 2:14:02 lr: 3.806578915851117e-05 loss: 0.1570 (0.1614) time: 3.0837 data: 0.0084 max mem: 33300 +Epoch: [10] [1960/4276] eta: 2:13:24 lr: 3.806307724391977e-05 loss: 0.1438 (0.1614) time: 3.1000 data: 0.0081 max mem: 33300 +Epoch: [10] [1970/4276] eta: 2:12:44 lr: 3.80603653078595e-05 loss: 0.1364 (0.1612) time: 3.0788 data: 0.0081 max mem: 33300 +Epoch: [10] [1980/4276] eta: 2:12:06 lr: 3.8057653350328495e-05 loss: 0.1386 (0.1612) time: 3.0859 data: 0.0081 max mem: 33300 +Epoch: [10] [1990/4276] eta: 2:11:28 lr: 3.8054941371324884e-05 loss: 0.1500 (0.1612) time: 3.1446 data: 0.0083 max mem: 33300 +Epoch: [10] [2000/4276] eta: 2:10:50 lr: 3.805222937084681e-05 loss: 0.1576 (0.1612) time: 3.1502 data: 0.0082 max mem: 33300 +Epoch: [10] [2010/4276] eta: 2:10:11 lr: 3.8049517348892385e-05 loss: 0.1576 (0.1612) time: 3.1028 data: 0.0079 max mem: 33300 +Epoch: [10] [2020/4276] eta: 2:09:33 lr: 3.804680530545975e-05 loss: 0.1583 (0.1612) time: 3.0750 data: 0.0078 max mem: 33300 +Epoch: [10] [2030/4276] eta: 2:08:54 lr: 3.804409324054702e-05 loss: 0.1567 (0.1611) time: 3.0773 data: 0.0083 max mem: 33300 +Epoch: [10] [2040/4276] eta: 2:08:15 lr: 3.8041381154152345e-05 loss: 0.1472 (0.1611) time: 3.0663 data: 0.0087 max mem: 33300 +Epoch: [10] [2050/4276] eta: 2:07:37 lr: 3.803866904627383e-05 loss: 0.1561 (0.1611) time: 3.0438 data: 0.0081 max mem: 33300 +Epoch: [10] [2060/4276] eta: 2:06:58 lr: 3.803595691690962e-05 loss: 0.1550 (0.1611) time: 3.0556 data: 0.0085 max mem: 33300 +Epoch: [10] [2070/4276] eta: 2:06:20 lr: 3.803324476605783e-05 loss: 0.1465 (0.1610) time: 3.0540 data: 0.0087 max mem: 33300 +Epoch: [10] [2080/4276] eta: 2:05:42 lr: 3.803053259371659e-05 loss: 0.1566 (0.1611) time: 3.0637 data: 0.0084 max mem: 33300 +Epoch: [10] [2090/4276] eta: 2:05:04 lr: 3.802782039988405e-05 loss: 0.1647 (0.1611) time: 3.1221 data: 0.0083 max mem: 33300 +Epoch: [10] [2100/4276] eta: 2:04:27 lr: 3.80251081845583e-05 loss: 0.1635 (0.1611) time: 3.1554 data: 0.0081 max mem: 33300 +Epoch: [10] [2110/4276] eta: 2:03:49 lr: 3.802239594773749e-05 loss: 0.1521 (0.1610) time: 3.1098 data: 0.0083 max mem: 33300 +Epoch: [10] [2120/4276] eta: 2:03:11 lr: 3.801968368941973e-05 loss: 0.1287 (0.1609) time: 3.0638 data: 0.0084 max mem: 33300 +Epoch: [10] [2130/4276] eta: 2:02:33 lr: 3.8016971409603164e-05 loss: 0.1336 (0.1608) time: 3.0653 data: 0.0078 max mem: 33300 +Epoch: [10] [2140/4276] eta: 2:01:55 lr: 3.80142591082859e-05 loss: 0.1488 (0.1607) time: 3.0655 data: 0.0072 max mem: 33300 +Epoch: [10] [2150/4276] eta: 2:01:17 lr: 3.801154678546607e-05 loss: 0.1535 (0.1607) time: 3.0652 data: 0.0074 max mem: 33300 +Epoch: [10] [2160/4276] eta: 2:00:40 lr: 3.800883444114181e-05 loss: 0.1520 (0.1607) time: 3.0688 data: 0.0075 max mem: 33300 +Epoch: [10] [2170/4276] eta: 2:00:03 lr: 3.8006122075311226e-05 loss: 0.1697 (0.1608) time: 3.0973 data: 0.0074 max mem: 33300 +Epoch: [10] [2180/4276] eta: 1:59:26 lr: 3.800340968797245e-05 loss: 0.1697 (0.1608) time: 3.1451 data: 0.0077 max mem: 33300 +Epoch: [10] [2190/4276] eta: 1:58:49 lr: 3.800069727912361e-05 loss: 0.1561 (0.1608) time: 3.1593 data: 0.0080 max mem: 33300 +Epoch: [10] [2200/4276] eta: 1:58:11 lr: 3.7997984848762826e-05 loss: 0.1584 (0.1608) time: 3.0941 data: 0.0086 max mem: 33300 +Epoch: [10] [2210/4276] eta: 1:57:33 lr: 3.799527239688821e-05 loss: 0.1601 (0.1608) time: 3.0248 data: 0.0090 max mem: 33300 +Epoch: [10] [2220/4276] eta: 1:56:56 lr: 3.79925599234979e-05 loss: 0.1709 (0.1609) time: 3.0105 data: 0.0085 max mem: 33300 +Epoch: [10] [2230/4276] eta: 1:56:18 lr: 3.798984742859001e-05 loss: 0.1534 (0.1609) time: 3.0393 data: 0.0087 max mem: 33300 +Epoch: [10] [2240/4276] eta: 1:55:41 lr: 3.798713491216267e-05 loss: 0.1466 (0.1608) time: 3.0780 data: 0.0087 max mem: 33300 +Epoch: [10] [2250/4276] eta: 1:55:05 lr: 3.798442237421401e-05 loss: 0.1466 (0.1608) time: 3.1039 data: 0.0080 max mem: 33300 +Epoch: [10] [2260/4276] eta: 1:54:27 lr: 3.798170981474213e-05 loss: 0.1555 (0.1608) time: 3.0963 data: 0.0077 max mem: 33300 +Epoch: [10] [2270/4276] eta: 1:53:51 lr: 3.797899723374516e-05 loss: 0.1485 (0.1608) time: 3.0777 data: 0.0076 max mem: 33300 +Epoch: [10] [2280/4276] eta: 1:53:14 lr: 3.797628463122122e-05 loss: 0.1475 (0.1608) time: 3.1184 data: 0.0082 max mem: 33300 +Epoch: [10] [2290/4276] eta: 1:52:38 lr: 3.797357200716843e-05 loss: 0.1559 (0.1607) time: 3.1473 data: 0.0083 max mem: 33300 +Epoch: [10] [2300/4276] eta: 1:52:01 lr: 3.7970859361584915e-05 loss: 0.1559 (0.1607) time: 3.1012 data: 0.0079 max mem: 33300 +Epoch: [10] [2310/4276] eta: 1:51:24 lr: 3.7968146694468794e-05 loss: 0.1517 (0.1607) time: 3.0365 data: 0.0083 max mem: 33300 +Epoch: [10] [2320/4276] eta: 1:50:47 lr: 3.796543400581818e-05 loss: 0.1604 (0.1607) time: 3.0619 data: 0.0087 max mem: 33300 +Epoch: [10] [2330/4276] eta: 1:50:11 lr: 3.79627212956312e-05 loss: 0.1604 (0.1607) time: 3.1018 data: 0.0082 max mem: 33300 +Epoch: [10] [2340/4276] eta: 1:49:34 lr: 3.796000856390598e-05 loss: 0.1622 (0.1607) time: 3.0805 data: 0.0084 max mem: 33300 +Epoch: [10] [2350/4276] eta: 1:48:57 lr: 3.795729581064063e-05 loss: 0.1512 (0.1607) time: 3.0712 data: 0.0084 max mem: 33300 +Epoch: [10] [2360/4276] eta: 1:48:21 lr: 3.795458303583325e-05 loss: 0.1471 (0.1607) time: 3.0678 data: 0.0078 max mem: 33300 +Epoch: [10] [2370/4276] eta: 1:47:44 lr: 3.795187023948199e-05 loss: 0.1681 (0.1607) time: 3.0745 data: 0.0077 max mem: 33300 +Epoch: [10] [2380/4276] eta: 1:47:09 lr: 3.794915742158495e-05 loss: 0.1589 (0.1607) time: 3.1304 data: 0.0079 max mem: 33300 +Epoch: [10] [2390/4276] eta: 1:46:33 lr: 3.7946444582140246e-05 loss: 0.1425 (0.1606) time: 3.1644 data: 0.0077 max mem: 33300 +Epoch: [10] [2400/4276] eta: 1:45:57 lr: 3.794373172114601e-05 loss: 0.1543 (0.1606) time: 3.1195 data: 0.0077 max mem: 33300 +Epoch: [10] [2410/4276] eta: 1:45:20 lr: 3.7941018838600345e-05 loss: 0.1459 (0.1606) time: 3.0840 data: 0.0078 max mem: 33300 +Epoch: [10] [2420/4276] eta: 1:44:44 lr: 3.793830593450138e-05 loss: 0.1420 (0.1605) time: 3.0722 data: 0.0082 max mem: 33300 +Epoch: [10] [2430/4276] eta: 1:44:08 lr: 3.793559300884721e-05 loss: 0.1470 (0.1606) time: 3.0647 data: 0.0082 max mem: 33300 +Epoch: [10] [2440/4276] eta: 1:43:32 lr: 3.793288006163597e-05 loss: 0.1530 (0.1605) time: 3.0692 data: 0.0080 max mem: 33300 +Epoch: [10] [2450/4276] eta: 1:42:55 lr: 3.7930167092865766e-05 loss: 0.1557 (0.1605) time: 3.0697 data: 0.0082 max mem: 33300 +Epoch: [10] [2460/4276] eta: 1:42:19 lr: 3.792745410253472e-05 loss: 0.1655 (0.1606) time: 3.0755 data: 0.0081 max mem: 33300 +Epoch: [10] [2470/4276] eta: 1:41:44 lr: 3.792474109064094e-05 loss: 0.1658 (0.1606) time: 3.0970 data: 0.0082 max mem: 33300 +Epoch: [10] [2480/4276] eta: 1:41:08 lr: 3.7922028057182554e-05 loss: 0.1588 (0.1606) time: 3.1521 data: 0.0082 max mem: 33300 +Epoch: [10] [2490/4276] eta: 1:40:33 lr: 3.791931500215766e-05 loss: 0.1462 (0.1605) time: 3.1833 data: 0.0081 max mem: 33300 +Epoch: [10] [2500/4276] eta: 1:39:58 lr: 3.7916601925564385e-05 loss: 0.1584 (0.1606) time: 3.1806 data: 0.0080 max mem: 33300 +Epoch: [10] [2510/4276] eta: 1:39:22 lr: 3.791388882740084e-05 loss: 0.1584 (0.1606) time: 3.1483 data: 0.0079 max mem: 33300 +Epoch: [10] [2520/4276] eta: 1:38:46 lr: 3.791117570766512e-05 loss: 0.1444 (0.1605) time: 3.0883 data: 0.0079 max mem: 33300 +Epoch: [10] [2530/4276] eta: 1:38:11 lr: 3.790846256635537e-05 loss: 0.1286 (0.1604) time: 3.0711 data: 0.0082 max mem: 33300 +Epoch: [10] [2540/4276] eta: 1:37:35 lr: 3.7905749403469676e-05 loss: 0.1297 (0.1603) time: 3.0898 data: 0.0084 max mem: 33300 +Epoch: [10] [2550/4276] eta: 1:36:59 lr: 3.790303621900616e-05 loss: 0.1369 (0.1603) time: 3.0980 data: 0.0087 max mem: 33300 +Epoch: [10] [2560/4276] eta: 1:36:24 lr: 3.790032301296294e-05 loss: 0.1297 (0.1602) time: 3.0746 data: 0.0082 max mem: 33300 +Epoch: [10] [2570/4276] eta: 1:35:48 lr: 3.789760978533812e-05 loss: 0.1309 (0.1602) time: 3.0637 data: 0.0077 max mem: 33300 +Epoch: [10] [2580/4276] eta: 1:35:12 lr: 3.789489653612982e-05 loss: 0.1407 (0.1601) time: 3.0665 data: 0.0082 max mem: 33300 +Epoch: [10] [2590/4276] eta: 1:34:37 lr: 3.789218326533614e-05 loss: 0.1431 (0.1600) time: 3.0889 data: 0.0086 max mem: 33300 +Epoch: [10] [2600/4276] eta: 1:34:02 lr: 3.7889469972955195e-05 loss: 0.1440 (0.1601) time: 3.1381 data: 0.0088 max mem: 33300 +Epoch: [10] [2610/4276] eta: 1:33:27 lr: 3.78867566589851e-05 loss: 0.1532 (0.1600) time: 3.1636 data: 0.0087 max mem: 33300 +Epoch: [10] [2620/4276] eta: 1:32:52 lr: 3.7884043323423955e-05 loss: 0.1532 (0.1600) time: 3.1300 data: 0.0088 max mem: 33300 +Epoch: [10] [2630/4276] eta: 1:32:16 lr: 3.788132996626988e-05 loss: 0.1378 (0.1600) time: 3.0856 data: 0.0091 max mem: 33300 +Epoch: [10] [2640/4276] eta: 1:31:41 lr: 3.787861658752099e-05 loss: 0.1333 (0.1600) time: 3.0695 data: 0.0092 max mem: 33300 +Epoch: [10] [2650/4276] eta: 1:31:05 lr: 3.787590318717538e-05 loss: 0.1502 (0.1600) time: 3.0701 data: 0.0092 max mem: 33300 +Epoch: [10] [2660/4276] eta: 1:30:30 lr: 3.7873189765231166e-05 loss: 0.1527 (0.1600) time: 3.0717 data: 0.0096 max mem: 33300 +Epoch: [10] [2670/4276] eta: 1:29:54 lr: 3.7870476321686454e-05 loss: 0.1625 (0.1600) time: 3.0704 data: 0.0098 max mem: 33300 +Epoch: [10] [2680/4276] eta: 1:29:19 lr: 3.786776285653936e-05 loss: 0.1528 (0.1600) time: 3.0802 data: 0.0094 max mem: 33300 +Epoch: [10] [2690/4276] eta: 1:28:44 lr: 3.786504936978797e-05 loss: 0.1528 (0.1600) time: 3.1133 data: 0.0094 max mem: 33300 +Epoch: [10] [2700/4276] eta: 1:28:10 lr: 3.786233586143042e-05 loss: 0.1480 (0.1599) time: 3.1508 data: 0.0100 max mem: 33300 +Epoch: [10] [2710/4276] eta: 1:27:35 lr: 3.785962233146481e-05 loss: 0.1474 (0.1599) time: 3.1593 data: 0.0100 max mem: 33300 +Epoch: [10] [2720/4276] eta: 1:27:00 lr: 3.785690877988923e-05 loss: 0.1400 (0.1598) time: 3.1145 data: 0.0093 max mem: 33300 +Epoch: [10] [2730/4276] eta: 1:26:25 lr: 3.7854195206701817e-05 loss: 0.1554 (0.1599) time: 3.0731 data: 0.0087 max mem: 33300 +Epoch: [10] [2740/4276] eta: 1:25:49 lr: 3.785148161190065e-05 loss: 0.1663 (0.1599) time: 3.0676 data: 0.0086 max mem: 33300 +Epoch: [10] [2750/4276] eta: 1:25:14 lr: 3.784876799548384e-05 loss: 0.1677 (0.1599) time: 3.0721 data: 0.0086 max mem: 33300 +Epoch: [10] [2760/4276] eta: 1:24:40 lr: 3.7846054357449494e-05 loss: 0.1551 (0.1599) time: 3.0940 data: 0.0086 max mem: 33300 +Epoch: [10] [2770/4276] eta: 1:24:05 lr: 3.7843340697795723e-05 loss: 0.1551 (0.1599) time: 3.0913 data: 0.0086 max mem: 33300 +Epoch: [10] [2780/4276] eta: 1:23:30 lr: 3.784062701652064e-05 loss: 0.1577 (0.1599) time: 3.0762 data: 0.0089 max mem: 33300 +Epoch: [10] [2790/4276] eta: 1:22:55 lr: 3.783791331362234e-05 loss: 0.1577 (0.1599) time: 3.0917 data: 0.0090 max mem: 33300 +Epoch: [10] [2800/4276] eta: 1:22:20 lr: 3.7835199589098916e-05 loss: 0.1513 (0.1599) time: 3.1267 data: 0.0088 max mem: 33300 +Epoch: [10] [2810/4276] eta: 1:21:46 lr: 3.783248584294849e-05 loss: 0.1299 (0.1597) time: 3.1561 data: 0.0091 max mem: 33300 +Epoch: [10] [2820/4276] eta: 1:21:11 lr: 3.7829772075169165e-05 loss: 0.1318 (0.1596) time: 3.1292 data: 0.0094 max mem: 33300 +Epoch: [10] [2830/4276] eta: 1:20:36 lr: 3.7827058285759034e-05 loss: 0.1347 (0.1596) time: 3.0979 data: 0.0091 max mem: 33300 +Epoch: [10] [2840/4276] eta: 1:20:02 lr: 3.7824344474716203e-05 loss: 0.1619 (0.1596) time: 3.0990 data: 0.0086 max mem: 33300 +Epoch: [10] [2850/4276] eta: 1:19:27 lr: 3.782163064203878e-05 loss: 0.1807 (0.1597) time: 3.0835 data: 0.0084 max mem: 33300 +Epoch: [10] [2860/4276] eta: 1:18:52 lr: 3.7818916787724874e-05 loss: 0.1781 (0.1597) time: 3.0688 data: 0.0084 max mem: 33300 +Epoch: [10] [2870/4276] eta: 1:18:17 lr: 3.7816202911772574e-05 loss: 0.1600 (0.1597) time: 3.0684 data: 0.0086 max mem: 33300 +Epoch: [10] [2880/4276] eta: 1:17:42 lr: 3.781348901417998e-05 loss: 0.1635 (0.1597) time: 3.0629 data: 0.0086 max mem: 33300 +Epoch: [10] [2890/4276] eta: 1:17:08 lr: 3.781077509494521e-05 loss: 0.1604 (0.1597) time: 3.0644 data: 0.0084 max mem: 33300 +Epoch: [10] [2900/4276] eta: 1:16:34 lr: 3.780806115406635e-05 loss: 0.1383 (0.1596) time: 3.1216 data: 0.0087 max mem: 33300 +Epoch: [10] [2910/4276] eta: 1:15:59 lr: 3.780534719154151e-05 loss: 0.1466 (0.1596) time: 3.1655 data: 0.0085 max mem: 33300 +Epoch: [10] [2920/4276] eta: 1:15:25 lr: 3.780263320736878e-05 loss: 0.1540 (0.1596) time: 3.0956 data: 0.0086 max mem: 33300 +Epoch: [10] [2930/4276] eta: 1:14:50 lr: 3.7799919201546274e-05 loss: 0.1446 (0.1596) time: 3.0242 data: 0.0088 max mem: 33300 +Epoch: [10] [2940/4276] eta: 1:14:15 lr: 3.7797205174072086e-05 loss: 0.1343 (0.1595) time: 3.0422 data: 0.0090 max mem: 33300 +Epoch: [10] [2950/4276] eta: 1:13:41 lr: 3.779449112494432e-05 loss: 0.1433 (0.1595) time: 3.0720 data: 0.0098 max mem: 33300 +Epoch: [10] [2960/4276] eta: 1:13:06 lr: 3.7791777054161065e-05 loss: 0.1361 (0.1594) time: 3.0678 data: 0.0098 max mem: 33300 +Epoch: [10] [2970/4276] eta: 1:12:31 lr: 3.778906296172043e-05 loss: 0.1370 (0.1595) time: 3.0413 data: 0.0090 max mem: 33300 +Epoch: [10] [2980/4276] eta: 1:11:57 lr: 3.7786348847620516e-05 loss: 0.1504 (0.1594) time: 3.0386 data: 0.0085 max mem: 33300 +Epoch: [10] [2990/4276] eta: 1:11:22 lr: 3.7783634711859406e-05 loss: 0.1504 (0.1594) time: 3.0648 data: 0.0087 max mem: 33300 +Epoch: [10] [3000/4276] eta: 1:10:48 lr: 3.778092055443521e-05 loss: 0.1497 (0.1594) time: 3.1018 data: 0.0091 max mem: 33300 +Epoch: [10] [3010/4276] eta: 1:10:14 lr: 3.777820637534603e-05 loss: 0.1497 (0.1593) time: 3.1499 data: 0.0093 max mem: 33300 +Epoch: [10] [3020/4276] eta: 1:09:40 lr: 3.777549217458995e-05 loss: 0.1556 (0.1593) time: 3.1399 data: 0.0090 max mem: 33300 +Epoch: [10] [3030/4276] eta: 1:09:06 lr: 3.777277795216509e-05 loss: 0.1556 (0.1594) time: 3.0902 data: 0.0087 max mem: 33300 +Epoch: [10] [3040/4276] eta: 1:08:31 lr: 3.777006370806952e-05 loss: 0.1605 (0.1594) time: 3.0717 data: 0.0088 max mem: 33300 +Epoch: [10] [3050/4276] eta: 1:07:57 lr: 3.776734944230135e-05 loss: 0.1615 (0.1594) time: 3.0862 data: 0.0086 max mem: 33300 +Epoch: [10] [3060/4276] eta: 1:07:23 lr: 3.776463515485867e-05 loss: 0.1305 (0.1593) time: 3.0981 data: 0.0085 max mem: 33300 +Epoch: [10] [3070/4276] eta: 1:06:49 lr: 3.776192084573959e-05 loss: 0.1337 (0.1593) time: 3.0856 data: 0.0085 max mem: 33300 +Epoch: [10] [3080/4276] eta: 1:06:15 lr: 3.7759206514942194e-05 loss: 0.1549 (0.1593) time: 3.0736 data: 0.0083 max mem: 33300 +Epoch: [10] [3090/4276] eta: 1:05:40 lr: 3.775649216246457e-05 loss: 0.1397 (0.1592) time: 3.0738 data: 0.0085 max mem: 33300 +Epoch: [10] [3100/4276] eta: 1:05:06 lr: 3.7753777788304834e-05 loss: 0.1502 (0.1592) time: 3.0831 data: 0.0088 max mem: 33300 +Epoch: [10] [3110/4276] eta: 1:04:32 lr: 3.7751063392461065e-05 loss: 0.1419 (0.1591) time: 3.1207 data: 0.0087 max mem: 33300 +Epoch: [10] [3120/4276] eta: 1:03:59 lr: 3.774834897493137e-05 loss: 0.1359 (0.1591) time: 3.1423 data: 0.0082 max mem: 33300 +Epoch: [10] [3130/4276] eta: 1:03:24 lr: 3.774563453571383e-05 loss: 0.1566 (0.1591) time: 3.0837 data: 0.0081 max mem: 33300 +Epoch: [10] [3140/4276] eta: 1:02:50 lr: 3.774292007480654e-05 loss: 0.1590 (0.1592) time: 3.0195 data: 0.0083 max mem: 33300 +Epoch: [10] [3150/4276] eta: 1:02:16 lr: 3.774020559220759e-05 loss: 0.1605 (0.1592) time: 3.0316 data: 0.0084 max mem: 33300 +Epoch: [10] [3160/4276] eta: 1:01:42 lr: 3.7737491087915086e-05 loss: 0.1564 (0.1592) time: 3.0591 data: 0.0086 max mem: 33300 +Epoch: [10] [3170/4276] eta: 1:01:08 lr: 3.773477656192712e-05 loss: 0.1576 (0.1592) time: 3.0580 data: 0.0085 max mem: 33300 +Epoch: [10] [3180/4276] eta: 1:00:34 lr: 3.773206201424178e-05 loss: 0.1556 (0.1592) time: 3.0494 data: 0.0082 max mem: 33300 +Epoch: [10] [3190/4276] eta: 0:59:59 lr: 3.772934744485716e-05 loss: 0.1411 (0.1591) time: 3.0280 data: 0.0085 max mem: 33300 +Epoch: [10] [3200/4276] eta: 0:59:26 lr: 3.7726632853771345e-05 loss: 0.1711 (0.1592) time: 3.0656 data: 0.0087 max mem: 33300 +Epoch: [10] [3210/4276] eta: 0:58:52 lr: 3.772391824098243e-05 loss: 0.1634 (0.1592) time: 3.1400 data: 0.0088 max mem: 33300 +Epoch: [10] [3220/4276] eta: 0:58:18 lr: 3.77212036064885e-05 loss: 0.1634 (0.1592) time: 3.1348 data: 0.0084 max mem: 33300 +Epoch: [10] [3230/4276] eta: 0:57:44 lr: 3.771848895028766e-05 loss: 0.1563 (0.1592) time: 3.0841 data: 0.0083 max mem: 33300 +Epoch: [10] [3240/4276] eta: 0:57:10 lr: 3.7715774272378e-05 loss: 0.1652 (0.1592) time: 3.0621 data: 0.0089 max mem: 33300 +Epoch: [10] [3250/4276] eta: 0:56:36 lr: 3.771305957275759e-05 loss: 0.1648 (0.1592) time: 3.0601 data: 0.0087 max mem: 33300 +Epoch: [10] [3260/4276] eta: 0:56:02 lr: 3.7710344851424546e-05 loss: 0.1582 (0.1592) time: 3.0604 data: 0.0087 max mem: 33300 +Epoch: [10] [3270/4276] eta: 0:55:29 lr: 3.770763010837694e-05 loss: 0.1615 (0.1592) time: 3.0814 data: 0.0091 max mem: 33300 +Epoch: [10] [3280/4276] eta: 0:54:55 lr: 3.770491534361287e-05 loss: 0.1517 (0.1592) time: 3.0877 data: 0.0093 max mem: 33300 +Epoch: [10] [3290/4276] eta: 0:54:21 lr: 3.770220055713041e-05 loss: 0.1517 (0.1592) time: 3.0688 data: 0.0092 max mem: 33300 +Epoch: [10] [3300/4276] eta: 0:53:47 lr: 3.7699485748927666e-05 loss: 0.1565 (0.1592) time: 3.0654 data: 0.0093 max mem: 33300 +Epoch: [10] [3310/4276] eta: 0:53:14 lr: 3.769677091900272e-05 loss: 0.1637 (0.1592) time: 3.1093 data: 0.0098 max mem: 33300 +Epoch: [10] [3320/4276] eta: 0:52:40 lr: 3.769405606735366e-05 loss: 0.1654 (0.1593) time: 3.1179 data: 0.0090 max mem: 33300 +Epoch: [10] [3330/4276] eta: 0:52:06 lr: 3.769134119397858e-05 loss: 0.1545 (0.1593) time: 3.0483 data: 0.0082 max mem: 33300 +Epoch: [10] [3340/4276] eta: 0:51:32 lr: 3.768862629887555e-05 loss: 0.1545 (0.1593) time: 3.0263 data: 0.0082 max mem: 33300 +Epoch: [10] [3350/4276] eta: 0:50:59 lr: 3.7685911382042686e-05 loss: 0.1525 (0.1592) time: 3.0656 data: 0.0088 max mem: 33300 +Epoch: [10] [3360/4276] eta: 0:50:25 lr: 3.768319644347804e-05 loss: 0.1598 (0.1592) time: 3.0809 data: 0.0093 max mem: 33300 +Epoch: [10] [3370/4276] eta: 0:49:51 lr: 3.768048148317972e-05 loss: 0.1682 (0.1593) time: 3.0691 data: 0.0091 max mem: 33300 +Epoch: [10] [3380/4276] eta: 0:49:18 lr: 3.76777665011458e-05 loss: 0.1619 (0.1593) time: 3.0607 data: 0.0093 max mem: 33300 +Epoch: [10] [3390/4276] eta: 0:48:44 lr: 3.767505149737438e-05 loss: 0.1774 (0.1594) time: 3.0597 data: 0.0097 max mem: 33300 +Epoch: [10] [3400/4276] eta: 0:48:10 lr: 3.767233647186354e-05 loss: 0.1716 (0.1594) time: 3.0646 data: 0.0100 max mem: 33300 +Epoch: [10] [3410/4276] eta: 0:47:37 lr: 3.766962142461136e-05 loss: 0.1643 (0.1595) time: 3.1077 data: 0.0091 max mem: 33300 +Epoch: [10] [3420/4276] eta: 0:47:04 lr: 3.7666906355615934e-05 loss: 0.1691 (0.1595) time: 3.1673 data: 0.0086 max mem: 33300 +Epoch: [10] [3430/4276] eta: 0:46:30 lr: 3.7664191264875334e-05 loss: 0.1688 (0.1596) time: 3.1386 data: 0.0088 max mem: 33300 +Epoch: [10] [3440/4276] eta: 0:45:57 lr: 3.766147615238765e-05 loss: 0.1548 (0.1595) time: 3.0765 data: 0.0086 max mem: 33300 +Epoch: [10] [3450/4276] eta: 0:45:23 lr: 3.7658761018150973e-05 loss: 0.1601 (0.1596) time: 3.0611 data: 0.0086 max mem: 33300 +Epoch: [10] [3460/4276] eta: 0:44:50 lr: 3.765604586216337e-05 loss: 0.1717 (0.1596) time: 3.0610 data: 0.0088 max mem: 33300 +Epoch: [10] [3470/4276] eta: 0:44:16 lr: 3.765333068442294e-05 loss: 0.1445 (0.1596) time: 3.0596 data: 0.0091 max mem: 33300 +Epoch: [10] [3480/4276] eta: 0:43:43 lr: 3.765061548492776e-05 loss: 0.1525 (0.1597) time: 3.0647 data: 0.0091 max mem: 33300 +Epoch: [10] [3490/4276] eta: 0:43:09 lr: 3.764790026367591e-05 loss: 0.1630 (0.1597) time: 3.0923 data: 0.0089 max mem: 33300 +Epoch: [10] [3500/4276] eta: 0:42:36 lr: 3.764518502066548e-05 loss: 0.1584 (0.1596) time: 3.0977 data: 0.0091 max mem: 33300 +Epoch: [10] [3510/4276] eta: 0:42:03 lr: 3.7642469755894546e-05 loss: 0.1449 (0.1596) time: 3.1114 data: 0.0096 max mem: 33300 +Epoch: [10] [3520/4276] eta: 0:41:29 lr: 3.763975446936118e-05 loss: 0.1564 (0.1596) time: 3.1574 data: 0.0095 max mem: 33300 +Epoch: [10] [3530/4276] eta: 0:40:56 lr: 3.763703916106348e-05 loss: 0.1564 (0.1596) time: 3.1439 data: 0.0091 max mem: 33300 +Epoch: [10] [3540/4276] eta: 0:40:23 lr: 3.763432383099952e-05 loss: 0.1538 (0.1596) time: 3.0909 data: 0.0088 max mem: 33300 +Epoch: [10] [3550/4276] eta: 0:39:49 lr: 3.763160847916738e-05 loss: 0.1541 (0.1596) time: 3.0674 data: 0.0088 max mem: 33300 +Epoch: [10] [3560/4276] eta: 0:39:16 lr: 3.7628893105565136e-05 loss: 0.1639 (0.1597) time: 3.0862 data: 0.0088 max mem: 33300 +Epoch: [10] [3570/4276] eta: 0:38:43 lr: 3.762617771019088e-05 loss: 0.1745 (0.1597) time: 3.0938 data: 0.0084 max mem: 33300 +Epoch: [10] [3580/4276] eta: 0:38:09 lr: 3.762346229304268e-05 loss: 0.1502 (0.1597) time: 3.0882 data: 0.0086 max mem: 33300 +Epoch: [10] [3590/4276] eta: 0:37:36 lr: 3.762074685411862e-05 loss: 0.1470 (0.1597) time: 3.0795 data: 0.0091 max mem: 33300 +Epoch: [10] [3600/4276] eta: 0:37:03 lr: 3.761803139341678e-05 loss: 0.1611 (0.1597) time: 3.0635 data: 0.0089 max mem: 33300 +Epoch: [10] [3610/4276] eta: 0:36:29 lr: 3.7615315910935234e-05 loss: 0.1595 (0.1597) time: 3.0593 data: 0.0089 max mem: 33300 +Epoch: [10] [3620/4276] eta: 0:35:56 lr: 3.7612600406672064e-05 loss: 0.1488 (0.1597) time: 3.0770 data: 0.0085 max mem: 33300 +Epoch: [10] [3630/4276] eta: 0:35:23 lr: 3.760988488062534e-05 loss: 0.1488 (0.1597) time: 3.0976 data: 0.0075 max mem: 33300 +Epoch: [10] [3640/4276] eta: 0:34:50 lr: 3.760716933279317e-05 loss: 0.1540 (0.1596) time: 3.0765 data: 0.0074 max mem: 33300 +Epoch: [10] [3650/4276] eta: 0:34:16 lr: 3.760445376317359e-05 loss: 0.1540 (0.1596) time: 3.0749 data: 0.0080 max mem: 33300 +Epoch: [10] [3660/4276] eta: 0:33:43 lr: 3.76017381717647e-05 loss: 0.1564 (0.1596) time: 3.0788 data: 0.0084 max mem: 33300 +Epoch: [10] [3670/4276] eta: 0:33:10 lr: 3.7599022558564565e-05 loss: 0.1632 (0.1596) time: 3.0533 data: 0.0081 max mem: 33300 +Epoch: [10] [3680/4276] eta: 0:32:37 lr: 3.759630692357128e-05 loss: 0.1710 (0.1597) time: 3.0439 data: 0.0080 max mem: 33300 +Epoch: [10] [3690/4276] eta: 0:32:04 lr: 3.7593591266782894e-05 loss: 0.1676 (0.1597) time: 3.0423 data: 0.0080 max mem: 33300 +Epoch: [10] [3700/4276] eta: 0:31:30 lr: 3.759087558819751e-05 loss: 0.1636 (0.1597) time: 3.0426 data: 0.0082 max mem: 33300 +Epoch: [10] [3710/4276] eta: 0:30:57 lr: 3.758815988781319e-05 loss: 0.1441 (0.1597) time: 3.0574 data: 0.0085 max mem: 33300 +Epoch: [10] [3720/4276] eta: 0:30:24 lr: 3.758544416562801e-05 loss: 0.1412 (0.1597) time: 3.1188 data: 0.0084 max mem: 33300 +Epoch: [10] [3730/4276] eta: 0:29:51 lr: 3.7582728421640037e-05 loss: 0.1496 (0.1597) time: 3.1475 data: 0.0088 max mem: 33300 +Epoch: [10] [3740/4276] eta: 0:29:18 lr: 3.758001265584736e-05 loss: 0.1576 (0.1597) time: 3.0925 data: 0.0085 max mem: 33300 +Epoch: [10] [3750/4276] eta: 0:28:45 lr: 3.757729686824805e-05 loss: 0.1524 (0.1597) time: 3.0545 data: 0.0083 max mem: 33300 +Epoch: [10] [3760/4276] eta: 0:28:12 lr: 3.7574581058840166e-05 loss: 0.1521 (0.1597) time: 3.0518 data: 0.0086 max mem: 33300 +Epoch: [10] [3770/4276] eta: 0:27:39 lr: 3.7571865227621805e-05 loss: 0.1521 (0.1597) time: 3.0501 data: 0.0084 max mem: 33300 +Epoch: [10] [3780/4276] eta: 0:27:06 lr: 3.7569149374591024e-05 loss: 0.1647 (0.1597) time: 3.0506 data: 0.0083 max mem: 33300 +Epoch: [10] [3790/4276] eta: 0:26:33 lr: 3.75664334997459e-05 loss: 0.1495 (0.1597) time: 3.0635 data: 0.0085 max mem: 33300 +Epoch: [10] [3800/4276] eta: 0:25:59 lr: 3.7563717603084505e-05 loss: 0.1685 (0.1597) time: 3.0646 data: 0.0081 max mem: 33300 +Epoch: [10] [3810/4276] eta: 0:25:26 lr: 3.7561001684604904e-05 loss: 0.1442 (0.1597) time: 3.0663 data: 0.0075 max mem: 33300 +Epoch: [10] [3820/4276] eta: 0:24:54 lr: 3.7558285744305186e-05 loss: 0.1387 (0.1596) time: 3.1107 data: 0.0076 max mem: 33300 +Epoch: [10] [3830/4276] eta: 0:24:21 lr: 3.7555569782183405e-05 loss: 0.1486 (0.1597) time: 3.1366 data: 0.0079 max mem: 33300 +Epoch: [10] [3840/4276] eta: 0:23:48 lr: 3.7552853798237645e-05 loss: 0.1486 (0.1596) time: 3.0998 data: 0.0078 max mem: 33300 +Epoch: [10] [3850/4276] eta: 0:23:15 lr: 3.7550137792465966e-05 loss: 0.1331 (0.1595) time: 3.0653 data: 0.0076 max mem: 33300 +Epoch: [10] [3860/4276] eta: 0:22:42 lr: 3.7547421764866445e-05 loss: 0.1386 (0.1595) time: 3.0767 data: 0.0079 max mem: 33300 +Epoch: [10] [3870/4276] eta: 0:22:09 lr: 3.754470571543715e-05 loss: 0.1601 (0.1595) time: 3.0733 data: 0.0081 max mem: 33300 +Epoch: [10] [3880/4276] eta: 0:21:36 lr: 3.754198964417616e-05 loss: 0.1571 (0.1595) time: 3.0294 data: 0.0083 max mem: 33300 +Epoch: [10] [3890/4276] eta: 0:21:03 lr: 3.753927355108154e-05 loss: 0.1531 (0.1595) time: 3.0014 data: 0.0084 max mem: 33300 +Epoch: [10] [3900/4276] eta: 0:20:30 lr: 3.7536557436151344e-05 loss: 0.1531 (0.1595) time: 3.0136 data: 0.0084 max mem: 33300 +Epoch: [10] [3910/4276] eta: 0:19:57 lr: 3.7533841299383655e-05 loss: 0.1575 (0.1595) time: 3.0503 data: 0.0080 max mem: 33300 +Epoch: [10] [3920/4276] eta: 0:19:24 lr: 3.7531125140776536e-05 loss: 0.1434 (0.1595) time: 3.1048 data: 0.0080 max mem: 33300 +Epoch: [10] [3930/4276] eta: 0:18:51 lr: 3.752840896032806e-05 loss: 0.1415 (0.1595) time: 3.1562 data: 0.0083 max mem: 33300 +Epoch: [10] [3940/4276] eta: 0:18:18 lr: 3.75256927580363e-05 loss: 0.1490 (0.1595) time: 3.1306 data: 0.0079 max mem: 33300 +Epoch: [10] [3950/4276] eta: 0:17:45 lr: 3.752297653389931e-05 loss: 0.1462 (0.1594) time: 3.0670 data: 0.0072 max mem: 33300 +Epoch: [10] [3960/4276] eta: 0:17:13 lr: 3.752026028791516e-05 loss: 0.1473 (0.1595) time: 3.0515 data: 0.0077 max mem: 33300 +Epoch: [10] [3970/4276] eta: 0:16:40 lr: 3.751754402008193e-05 loss: 0.1550 (0.1595) time: 3.0658 data: 0.0086 max mem: 33300 +Epoch: [10] [3980/4276] eta: 0:16:07 lr: 3.751482773039768e-05 loss: 0.1534 (0.1595) time: 3.0654 data: 0.0082 max mem: 33300 +Epoch: [10] [3990/4276] eta: 0:15:34 lr: 3.751211141886046e-05 loss: 0.1409 (0.1594) time: 3.0719 data: 0.0078 max mem: 33300 +Epoch: [10] [4000/4276] eta: 0:15:01 lr: 3.750939508546836e-05 loss: 0.1431 (0.1594) time: 3.0873 data: 0.0077 max mem: 33300 +Epoch: [10] [4010/4276] eta: 0:14:28 lr: 3.750667873021943e-05 loss: 0.1522 (0.1594) time: 3.0781 data: 0.0076 max mem: 33300 +Epoch: [10] [4020/4276] eta: 0:13:56 lr: 3.750396235311174e-05 loss: 0.1556 (0.1595) time: 3.0921 data: 0.0073 max mem: 33300 +Epoch: [10] [4030/4276] eta: 0:13:23 lr: 3.750124595414336e-05 loss: 0.1595 (0.1595) time: 3.1327 data: 0.0074 max mem: 33300 +Epoch: [10] [4040/4276] eta: 0:12:50 lr: 3.749852953331235e-05 loss: 0.1604 (0.1595) time: 3.1254 data: 0.0074 max mem: 33300 +Epoch: [10] [4050/4276] eta: 0:12:17 lr: 3.7495813090616774e-05 loss: 0.1462 (0.1595) time: 3.0811 data: 0.0068 max mem: 33300 +Epoch: [10] [4060/4276] eta: 0:11:45 lr: 3.7493096626054693e-05 loss: 0.1511 (0.1595) time: 3.0663 data: 0.0069 max mem: 33300 +Epoch: [10] [4070/4276] eta: 0:11:12 lr: 3.749038013962418e-05 loss: 0.1594 (0.1595) time: 3.0775 data: 0.0074 max mem: 33300 +Epoch: [10] [4080/4276] eta: 0:10:39 lr: 3.748766363132329e-05 loss: 0.1585 (0.1595) time: 3.0704 data: 0.0074 max mem: 33300 +Epoch: [10] [4090/4276] eta: 0:10:06 lr: 3.7484947101150085e-05 loss: 0.1582 (0.1595) time: 3.0594 data: 0.0074 max mem: 33300 +Epoch: [10] [4100/4276] eta: 0:09:34 lr: 3.7482230549102634e-05 loss: 0.1606 (0.1595) time: 3.0619 data: 0.0076 max mem: 33300 +Epoch: [10] [4110/4276] eta: 0:09:01 lr: 3.7479513975179e-05 loss: 0.1593 (0.1595) time: 3.0632 data: 0.0078 max mem: 33300 +Epoch: [10] [4120/4276] eta: 0:08:28 lr: 3.747679737937723e-05 loss: 0.1586 (0.1595) time: 3.0784 data: 0.0076 max mem: 33300 +Epoch: [10] [4130/4276] eta: 0:07:56 lr: 3.747408076169541e-05 loss: 0.1511 (0.1595) time: 3.1421 data: 0.0076 max mem: 33300 +Epoch: [10] [4140/4276] eta: 0:07:23 lr: 3.747136412213158e-05 loss: 0.1483 (0.1595) time: 3.1724 data: 0.0079 max mem: 33300 +Epoch: [10] [4150/4276] eta: 0:06:50 lr: 3.746864746068381e-05 loss: 0.1630 (0.1595) time: 3.1047 data: 0.0074 max mem: 33300 +Epoch: [10] [4160/4276] eta: 0:06:18 lr: 3.746593077735016e-05 loss: 0.1575 (0.1595) time: 3.0515 data: 0.0073 max mem: 33300 +Epoch: [10] [4170/4276] eta: 0:05:45 lr: 3.7463214072128686e-05 loss: 0.1775 (0.1596) time: 3.0508 data: 0.0077 max mem: 33300 +Epoch: [10] [4180/4276] eta: 0:05:12 lr: 3.746049734501746e-05 loss: 0.1688 (0.1595) time: 3.0533 data: 0.0075 max mem: 33300 +Epoch: [10] [4190/4276] eta: 0:04:40 lr: 3.7457780596014534e-05 loss: 0.1516 (0.1596) time: 3.0586 data: 0.0072 max mem: 33300 +Epoch: [10] [4200/4276] eta: 0:04:07 lr: 3.745506382511797e-05 loss: 0.1516 (0.1596) time: 3.0758 data: 0.0072 max mem: 33300 +Epoch: [10] [4210/4276] eta: 0:03:35 lr: 3.745234703232582e-05 loss: 0.1629 (0.1596) time: 3.0814 data: 0.0073 max mem: 33300 +Epoch: [10] [4220/4276] eta: 0:03:02 lr: 3.744963021763615e-05 loss: 0.1754 (0.1597) time: 3.0781 data: 0.0073 max mem: 33300 +Epoch: [10] [4230/4276] eta: 0:02:29 lr: 3.744691338104701e-05 loss: 0.1769 (0.1597) time: 3.1130 data: 0.0073 max mem: 33300 +Epoch: [10] [4240/4276] eta: 0:01:57 lr: 3.744419652255647e-05 loss: 0.1700 (0.1598) time: 3.1437 data: 0.0073 max mem: 33300 +Epoch: [10] [4250/4276] eta: 0:01:24 lr: 3.744147964216257e-05 loss: 0.1700 (0.1598) time: 3.0989 data: 0.0070 max mem: 33300 +Epoch: [10] [4260/4276] eta: 0:00:52 lr: 3.743876273986339e-05 loss: 0.1702 (0.1598) time: 3.0559 data: 0.0069 max mem: 33300 +Epoch: [10] [4270/4276] eta: 0:00:19 lr: 3.743604581565698e-05 loss: 0.1648 (0.1598) time: 3.0651 data: 0.0071 max mem: 33300 +Epoch: [10] Total time: 3:52:01 +Test: [ 0/21770] eta: 10:24:55 time: 1.7224 data: 1.6796 max mem: 33300 +Test: [ 100/21770] eta: 0:19:54 time: 0.0381 data: 0.0010 max mem: 33300 +Test: [ 200/21770] eta: 0:16:48 time: 0.0386 data: 0.0011 max mem: 33300 +Test: [ 300/21770] eta: 0:15:43 time: 0.0380 data: 0.0010 max mem: 33300 +Test: [ 400/21770] eta: 0:15:08 time: 0.0382 data: 0.0010 max mem: 33300 +Test: [ 500/21770] eta: 0:14:46 time: 0.0384 data: 0.0011 max mem: 33300 +Test: [ 600/21770] eta: 0:14:30 time: 0.0385 data: 0.0011 max mem: 33300 +Test: [ 700/21770] eta: 0:14:18 time: 0.0391 data: 0.0011 max mem: 33300 +Test: [ 800/21770] eta: 0:14:09 time: 0.0389 data: 0.0010 max mem: 33300 +Test: [ 900/21770] eta: 0:14:01 time: 0.0388 data: 0.0010 max mem: 33300 +Test: [ 1000/21770] eta: 0:13:54 time: 0.0386 data: 0.0010 max mem: 33300 +Test: [ 1100/21770] eta: 0:13:47 time: 0.0390 data: 0.0010 max mem: 33300 +Test: [ 1200/21770] eta: 0:13:41 time: 0.0386 data: 0.0010 max mem: 33300 +Test: [ 1300/21770] eta: 0:13:34 time: 0.0385 data: 0.0010 max mem: 33300 +Test: [ 1400/21770] eta: 0:13:28 time: 0.0384 data: 0.0011 max mem: 33300 +Test: [ 1500/21770] eta: 0:13:22 time: 0.0383 data: 0.0011 max mem: 33300 +Test: [ 1600/21770] eta: 0:13:17 time: 0.0386 data: 0.0010 max mem: 33300 +Test: [ 1700/21770] eta: 0:13:11 time: 0.0381 data: 0.0010 max mem: 33300 +Test: [ 1800/21770] eta: 0:13:07 time: 0.0381 data: 0.0010 max mem: 33300 +Test: [ 1900/21770] eta: 0:13:03 time: 0.0391 data: 0.0011 max mem: 33300 +Test: [ 2000/21770] eta: 0:12:58 time: 0.0381 data: 0.0010 max mem: 33300 +Test: [ 2100/21770] eta: 0:12:53 time: 0.0384 data: 0.0011 max mem: 33300 +Test: [ 2200/21770] eta: 0:12:48 time: 0.0383 data: 0.0011 max mem: 33300 +Test: [ 2300/21770] eta: 0:12:44 time: 0.0391 data: 0.0010 max mem: 33300 +Test: [ 2400/21770] eta: 0:12:41 time: 0.0399 data: 0.0010 max mem: 33300 +Test: [ 2500/21770] eta: 0:12:37 time: 0.0390 data: 0.0010 max mem: 33300 +Test: [ 2600/21770] eta: 0:12:33 time: 0.0394 data: 0.0010 max mem: 33300 +Test: [ 2700/21770] eta: 0:12:29 time: 0.0394 data: 0.0011 max mem: 33300 +Test: [ 2800/21770] eta: 0:12:25 time: 0.0381 data: 0.0011 max mem: 33300 +Test: [ 2900/21770] eta: 0:12:20 time: 0.0384 data: 0.0011 max mem: 33300 +Test: [ 3000/21770] eta: 0:12:16 time: 0.0384 data: 0.0011 max mem: 33300 +Test: [ 3100/21770] eta: 0:12:12 time: 0.0387 data: 0.0011 max mem: 33300 +Test: [ 3200/21770] eta: 0:12:07 time: 0.0389 data: 0.0011 max mem: 33300 +Test: [ 3300/21770] eta: 0:12:03 time: 0.0388 data: 0.0011 max mem: 33300 +Test: [ 3400/21770] eta: 0:11:59 time: 0.0397 data: 0.0011 max mem: 33300 +Test: [ 3500/21770] eta: 0:11:55 time: 0.0393 data: 0.0011 max mem: 33300 +Test: [ 3600/21770] eta: 0:11:51 time: 0.0398 data: 0.0011 max mem: 33300 +Test: [ 3700/21770] eta: 0:11:48 time: 0.0398 data: 0.0012 max mem: 33300 +Test: [ 3800/21770] eta: 0:11:44 time: 0.0403 data: 0.0012 max mem: 33300 +Test: [ 3900/21770] eta: 0:11:41 time: 0.0399 data: 0.0012 max mem: 33300 +Test: [ 4000/21770] eta: 0:11:37 time: 0.0403 data: 0.0012 max mem: 33300 +Test: [ 4100/21770] eta: 0:11:33 time: 0.0397 data: 0.0012 max mem: 33300 +Test: [ 4200/21770] eta: 0:11:30 time: 0.0402 data: 0.0012 max mem: 33300 +Test: [ 4300/21770] eta: 0:11:26 time: 0.0396 data: 0.0012 max mem: 33300 +Test: [ 4400/21770] eta: 0:11:23 time: 0.0402 data: 0.0012 max mem: 33300 +Test: [ 4500/21770] eta: 0:11:19 time: 0.0398 data: 0.0012 max mem: 33300 +Test: [ 4600/21770] eta: 0:11:15 time: 0.0404 data: 0.0012 max mem: 33300 +Test: [ 4700/21770] eta: 0:11:12 time: 0.0401 data: 0.0012 max mem: 33300 +Test: [ 4800/21770] eta: 0:11:08 time: 0.0402 data: 0.0012 max mem: 33300 +Test: [ 4900/21770] eta: 0:11:04 time: 0.0398 data: 0.0012 max mem: 33300 +Test: [ 5000/21770] eta: 0:11:01 time: 0.0403 data: 0.0012 max mem: 33300 +Test: [ 5100/21770] eta: 0:10:57 time: 0.0400 data: 0.0012 max mem: 33300 +Test: [ 5200/21770] eta: 0:10:53 time: 0.0403 data: 0.0012 max mem: 33300 +Test: [ 5300/21770] eta: 0:10:49 time: 0.0400 data: 0.0012 max mem: 33300 +Test: [ 5400/21770] eta: 0:10:46 time: 0.0400 data: 0.0011 max mem: 33300 +Test: [ 5500/21770] eta: 0:10:42 time: 0.0391 data: 0.0011 max mem: 33300 +Test: [ 5600/21770] eta: 0:10:38 time: 0.0391 data: 0.0011 max mem: 33300 +Test: [ 5700/21770] eta: 0:10:34 time: 0.0393 data: 0.0011 max mem: 33300 +Test: [ 5800/21770] eta: 0:10:30 time: 0.0394 data: 0.0011 max mem: 33300 +Test: [ 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time: 0.0399 data: 0.0010 max mem: 33300 +Test: [ 7300/21770] eta: 0:09:31 time: 0.0393 data: 0.0010 max mem: 33300 +Test: [ 7400/21770] eta: 0:09:27 time: 0.0401 data: 0.0011 max mem: 33300 +Test: [ 7500/21770] eta: 0:09:24 time: 0.0400 data: 0.0011 max mem: 33300 +Test: [ 7600/21770] eta: 0:09:20 time: 0.0403 data: 0.0011 max mem: 33300 +Test: [ 7700/21770] eta: 0:09:16 time: 0.0398 data: 0.0011 max mem: 33300 +Test: [ 7800/21770] eta: 0:09:12 time: 0.0398 data: 0.0011 max mem: 33300 +Test: [ 7900/21770] eta: 0:09:08 time: 0.0390 data: 0.0010 max mem: 33300 +Test: [ 8000/21770] eta: 0:09:04 time: 0.0391 data: 0.0010 max mem: 33300 +Test: [ 8100/21770] eta: 0:09:00 time: 0.0388 data: 0.0009 max mem: 33300 +Test: [ 8200/21770] eta: 0:08:56 time: 0.0388 data: 0.0010 max mem: 33300 +Test: [ 8300/21770] eta: 0:08:52 time: 0.0386 data: 0.0010 max mem: 33300 +Test: [ 8400/21770] eta: 0:08:48 time: 0.0393 data: 0.0010 max mem: 33300 +Test: [ 8500/21770] eta: 0:08:44 time: 0.0383 data: 0.0010 max mem: 33300 +Test: [ 8600/21770] eta: 0:08:40 time: 0.0394 data: 0.0011 max mem: 33300 +Test: [ 8700/21770] eta: 0:08:36 time: 0.0396 data: 0.0010 max mem: 33300 +Test: [ 8800/21770] eta: 0:08:32 time: 0.0395 data: 0.0011 max mem: 33300 +Test: [ 8900/21770] eta: 0:08:28 time: 0.0401 data: 0.0011 max mem: 33300 +Test: [ 9000/21770] eta: 0:08:24 time: 0.0396 data: 0.0011 max mem: 33300 +Test: [ 9100/21770] eta: 0:08:20 time: 0.0398 data: 0.0011 max mem: 33300 +Test: [ 9200/21770] eta: 0:08:16 time: 0.0393 data: 0.0011 max mem: 33300 +Test: [ 9300/21770] eta: 0:08:12 time: 0.0392 data: 0.0010 max mem: 33300 +Test: [ 9400/21770] eta: 0:08:08 time: 0.0392 data: 0.0010 max mem: 33300 +Test: [ 9500/21770] eta: 0:08:04 time: 0.0392 data: 0.0010 max mem: 33300 +Test: [ 9600/21770] eta: 0:08:00 time: 0.0392 data: 0.0010 max mem: 33300 +Test: [ 9700/21770] eta: 0:07:56 time: 0.0396 data: 0.0010 max mem: 33300 +Test: [ 9800/21770] eta: 0:07:52 time: 0.0389 data: 0.0010 max mem: 33300 +Test: [ 9900/21770] eta: 0:07:48 time: 0.0397 data: 0.0012 max mem: 33300 +Test: [10000/21770] eta: 0:07:44 time: 0.0399 data: 0.0011 max mem: 33300 +Test: [10100/21770] eta: 0:07:41 time: 0.0401 data: 0.0012 max mem: 33300 +Test: [10200/21770] eta: 0:07:37 time: 0.0400 data: 0.0012 max mem: 33300 +Test: [10300/21770] eta: 0:07:33 time: 0.0397 data: 0.0011 max mem: 33300 +Test: [10400/21770] eta: 0:07:29 time: 0.0398 data: 0.0011 max mem: 33300 +Test: [10500/21770] eta: 0:07:25 time: 0.0391 data: 0.0010 max mem: 33300 +Test: [10600/21770] eta: 0:07:21 time: 0.0393 data: 0.0011 max mem: 33300 +Test: [10700/21770] eta: 0:07:17 time: 0.0394 data: 0.0011 max mem: 33300 +Test: [10800/21770] eta: 0:07:13 time: 0.0395 data: 0.0011 max mem: 33300 +Test: [10900/21770] eta: 0:07:09 time: 0.0391 data: 0.0011 max mem: 33300 +Test: [11000/21770] eta: 0:07:05 time: 0.0388 data: 0.0011 max mem: 33300 +Test: [11100/21770] eta: 0:07:01 time: 0.0390 data: 0.0011 max mem: 33300 +Test: [11200/21770] eta: 0:06:57 time: 0.0388 data: 0.0011 max mem: 33300 +Test: [11300/21770] eta: 0:06:53 time: 0.0389 data: 0.0011 max mem: 33300 +Test: [11400/21770] eta: 0:06:49 time: 0.0386 data: 0.0011 max mem: 33300 +Test: [11500/21770] eta: 0:06:45 time: 0.0388 data: 0.0011 max mem: 33300 +Test: [11600/21770] eta: 0:06:41 time: 0.0389 data: 0.0011 max mem: 33300 +Test: [11700/21770] eta: 0:06:37 time: 0.0394 data: 0.0012 max mem: 33300 +Test: [11800/21770] eta: 0:06:33 time: 0.0391 data: 0.0012 max mem: 33300 +Test: [11900/21770] eta: 0:06:29 time: 0.0393 data: 0.0012 max mem: 33300 +Test: [12000/21770] eta: 0:06:25 time: 0.0393 data: 0.0012 max mem: 33300 +Test: [12100/21770] eta: 0:06:21 time: 0.0396 data: 0.0013 max mem: 33300 +Test: [12200/21770] eta: 0:06:17 time: 0.0397 data: 0.0012 max mem: 33300 +Test: [12300/21770] eta: 0:06:13 time: 0.0393 data: 0.0012 max mem: 33300 +Test: [12400/21770] eta: 0:06:09 time: 0.0398 data: 0.0012 max mem: 33300 +Test: [12500/21770] eta: 0:06:05 time: 0.0394 data: 0.0012 max mem: 33300 +Test: [12600/21770] eta: 0:06:01 time: 0.0399 data: 0.0012 max mem: 33300 +Test: [12700/21770] eta: 0:05:58 time: 0.0400 data: 0.0012 max mem: 33300 +Test: [12800/21770] eta: 0:05:54 time: 0.0400 data: 0.0011 max mem: 33300 +Test: [12900/21770] eta: 0:05:50 time: 0.0401 data: 0.0012 max mem: 33300 +Test: [13000/21770] eta: 0:05:46 time: 0.0399 data: 0.0012 max mem: 33300 +Test: [13100/21770] eta: 0:05:42 time: 0.0399 data: 0.0012 max mem: 33300 +Test: [13200/21770] eta: 0:05:38 time: 0.0397 data: 0.0012 max mem: 33300 +Test: [13300/21770] eta: 0:05:34 time: 0.0398 data: 0.0011 max mem: 33300 +Test: [13400/21770] eta: 0:05:30 time: 0.0392 data: 0.0010 max mem: 33300 +Test: [13500/21770] eta: 0:05:26 time: 0.0396 data: 0.0011 max mem: 33300 +Test: [13600/21770] eta: 0:05:22 time: 0.0401 data: 0.0011 max mem: 33300 +Test: [13700/21770] eta: 0:05:18 time: 0.0401 data: 0.0011 max mem: 33300 +Test: [13800/21770] eta: 0:05:14 time: 0.0400 data: 0.0011 max mem: 33300 +Test: [13900/21770] eta: 0:05:10 time: 0.0394 data: 0.0011 max mem: 33300 +Test: [14000/21770] eta: 0:05:06 time: 0.0399 data: 0.0010 max mem: 33300 +Test: [14100/21770] eta: 0:05:03 time: 0.0399 data: 0.0010 max mem: 33300 +Test: [14200/21770] eta: 0:04:59 time: 0.0389 data: 0.0010 max mem: 33300 +Test: [14300/21770] eta: 0:04:55 time: 0.0386 data: 0.0010 max mem: 33300 +Test: [14400/21770] eta: 0:04:51 time: 0.0389 data: 0.0011 max mem: 33300 +Test: [14500/21770] eta: 0:04:47 time: 0.0386 data: 0.0010 max mem: 33300 +Test: [14600/21770] eta: 0:04:43 time: 0.0388 data: 0.0011 max mem: 33300 +Test: [14700/21770] eta: 0:04:39 time: 0.0390 data: 0.0011 max mem: 33300 +Test: [14800/21770] eta: 0:04:35 time: 0.0391 data: 0.0011 max mem: 33300 +Test: [14900/21770] eta: 0:04:31 time: 0.0389 data: 0.0011 max mem: 33300 +Test: [15000/21770] eta: 0:04:27 time: 0.0390 data: 0.0011 max mem: 33300 +Test: [15100/21770] eta: 0:04:23 time: 0.0389 data: 0.0011 max mem: 33300 +Test: [15200/21770] eta: 0:04:19 time: 0.0391 data: 0.0012 max mem: 33300 +Test: [15300/21770] eta: 0:04:15 time: 0.0390 data: 0.0012 max mem: 33300 +Test: [15400/21770] eta: 0:04:11 time: 0.0394 data: 0.0012 max mem: 33300 +Test: [15500/21770] eta: 0:04:07 time: 0.0395 data: 0.0012 max mem: 33300 +Test: [15600/21770] eta: 0:04:03 time: 0.0391 data: 0.0011 max mem: 33300 +Test: [15700/21770] eta: 0:03:59 time: 0.0392 data: 0.0012 max mem: 33300 +Test: [15800/21770] eta: 0:03:55 time: 0.0393 data: 0.0012 max mem: 33300 +Test: [15900/21770] eta: 0:03:51 time: 0.0390 data: 0.0011 max mem: 33300 +Test: [16000/21770] eta: 0:03:47 time: 0.0390 data: 0.0012 max mem: 33300 +Test: [16100/21770] eta: 0:03:43 time: 0.0392 data: 0.0011 max mem: 33300 +Test: [16200/21770] eta: 0:03:39 time: 0.0388 data: 0.0011 max mem: 33300 +Test: [16300/21770] eta: 0:03:35 time: 0.0388 data: 0.0011 max mem: 33300 +Test: [16400/21770] eta: 0:03:31 time: 0.0388 data: 0.0010 max mem: 33300 +Test: [16500/21770] eta: 0:03:27 time: 0.0385 data: 0.0010 max mem: 33300 +Test: [16600/21770] eta: 0:03:23 time: 0.0386 data: 0.0010 max mem: 33300 +Test: [16700/21770] eta: 0:03:19 time: 0.0385 data: 0.0010 max mem: 33300 +Test: [16800/21770] eta: 0:03:15 time: 0.0386 data: 0.0010 max mem: 33300 +Test: [16900/21770] eta: 0:03:11 time: 0.0385 data: 0.0010 max mem: 33300 +Test: [17000/21770] eta: 0:03:07 time: 0.0389 data: 0.0011 max mem: 33300 +Test: [17100/21770] eta: 0:03:04 time: 0.0386 data: 0.0011 max mem: 33300 +Test: [17200/21770] eta: 0:03:00 time: 0.0386 data: 0.0010 max mem: 33300 +Test: [17300/21770] eta: 0:02:56 time: 0.0387 data: 0.0011 max mem: 33300 +Test: [17400/21770] eta: 0:02:52 time: 0.0388 data: 0.0010 max mem: 33300 +Test: [17500/21770] eta: 0:02:48 time: 0.0388 data: 0.0010 max mem: 33300 +Test: [17600/21770] eta: 0:02:44 time: 0.0393 data: 0.0011 max mem: 33300 +Test: [17700/21770] eta: 0:02:40 time: 0.0390 data: 0.0011 max mem: 33300 +Test: [17800/21770] eta: 0:02:36 time: 0.0395 data: 0.0011 max mem: 33300 +Test: [17900/21770] eta: 0:02:32 time: 0.0391 data: 0.0011 max mem: 33300 +Test: [18000/21770] eta: 0:02:28 time: 0.0393 data: 0.0011 max mem: 33300 +Test: [18100/21770] eta: 0:02:24 time: 0.0390 data: 0.0011 max mem: 33300 +Test: [18200/21770] eta: 0:02:20 time: 0.0392 data: 0.0011 max mem: 33300 +Test: [18300/21770] eta: 0:02:16 time: 0.0392 data: 0.0011 max mem: 33300 +Test: [18400/21770] eta: 0:02:12 time: 0.0392 data: 0.0011 max mem: 33300 +Test: [18500/21770] eta: 0:02:08 time: 0.0390 data: 0.0011 max mem: 33300 +Test: [18600/21770] eta: 0:02:04 time: 0.0394 data: 0.0011 max mem: 33300 +Test: [18700/21770] eta: 0:02:00 time: 0.0390 data: 0.0011 max mem: 33300 +Test: [18800/21770] eta: 0:01:56 time: 0.0395 data: 0.0012 max mem: 33300 +Test: [18900/21770] eta: 0:01:53 time: 0.0392 data: 0.0011 max mem: 33300 +Test: [19000/21770] eta: 0:01:49 time: 0.0399 data: 0.0011 max mem: 33300 +Test: [19100/21770] eta: 0:01:45 time: 0.0391 data: 0.0011 max mem: 33300 +Test: [19200/21770] eta: 0:01:41 time: 0.0392 data: 0.0011 max mem: 33300 +Test: [19300/21770] eta: 0:01:37 time: 0.0390 data: 0.0011 max mem: 33300 +Test: [19400/21770] eta: 0:01:33 time: 0.0393 data: 0.0011 max mem: 33300 +Test: [19500/21770] eta: 0:01:29 time: 0.0391 data: 0.0011 max mem: 33300 +Test: [19600/21770] eta: 0:01:25 time: 0.0392 data: 0.0011 max mem: 33300 +Test: [19700/21770] eta: 0:01:21 time: 0.0393 data: 0.0012 max mem: 33300 +Test: [19800/21770] eta: 0:01:17 time: 0.0392 data: 0.0012 max mem: 33300 +Test: [19900/21770] eta: 0:01:13 time: 0.0390 data: 0.0012 max mem: 33300 +Test: [20000/21770] eta: 0:01:09 time: 0.0393 data: 0.0012 max mem: 33300 +Test: [20100/21770] eta: 0:01:05 time: 0.0391 data: 0.0012 max mem: 33300 +Test: [20200/21770] eta: 0:01:01 time: 0.0392 data: 0.0012 max mem: 33300 +Test: [20300/21770] eta: 0:00:57 time: 0.0390 data: 0.0012 max mem: 33300 +Test: [20400/21770] eta: 0:00:53 time: 0.0387 data: 0.0011 max mem: 33300 +Test: [20500/21770] eta: 0:00:49 time: 0.0389 data: 0.0012 max mem: 33300 +Test: [20600/21770] eta: 0:00:46 time: 0.0391 data: 0.0011 max mem: 33300 +Test: [20700/21770] eta: 0:00:42 time: 0.0390 data: 0.0011 max mem: 33300 +Test: [20800/21770] eta: 0:00:38 time: 0.0392 data: 0.0012 max mem: 33300 +Test: [20900/21770] eta: 0:00:34 time: 0.0398 data: 0.0012 max mem: 33300 +Test: [21000/21770] eta: 0:00:30 time: 0.0406 data: 0.0012 max mem: 33300 +Test: [21100/21770] eta: 0:00:26 time: 0.0403 data: 0.0012 max mem: 33300 +Test: [21200/21770] eta: 0:00:22 time: 0.0402 data: 0.0012 max mem: 33300 +Test: [21300/21770] eta: 0:00:18 time: 0.0400 data: 0.0012 max mem: 33300 +Test: [21400/21770] eta: 0:00:14 time: 0.0402 data: 0.0012 max mem: 33300 +Test: [21500/21770] eta: 0:00:10 time: 0.0398 data: 0.0011 max mem: 33300 +Test: [21600/21770] eta: 0:00:06 time: 0.0394 data: 0.0012 max mem: 33300 +Test: [21700/21770] eta: 0:00:02 time: 0.0396 data: 0.0012 max mem: 33300 +Test: Total time: 0:14:17 +Final results: +Mean IoU is 0.00 + + precision@0.5 = 0.00 + precision@0.6 = 0.00 + precision@0.7 = 0.00 + precision@0.8 = 0.00 + precision@0.9 = 0.00 + overall IoU = 0.00 + mean IoU = 0.00 + +Mean accuracy for one-to-zero sample is 100.00 + +Average object IoU 0.0 +Overall IoU 0.0 +Epoch: [11] [ 0/4276] eta: 6:16:57 lr: 3.7434415650616845e-05 loss: 0.1300 (0.1300) time: 5.2894 data: 2.1308 max mem: 33300 +Epoch: [11] [ 10/4276] eta: 3:52:01 lr: 3.743169869135481e-05 loss: 0.1694 (0.1669) time: 3.2634 data: 0.2023 max mem: 33300 +Epoch: [11] [ 20/4276] eta: 3:44:39 lr: 3.742898171018049e-05 loss: 0.1600 (0.1645) time: 3.0610 data: 0.0089 max mem: 33300 +Epoch: [11] [ 30/4276] eta: 3:41:36 lr: 3.742626470709194e-05 loss: 0.1509 (0.1631) time: 3.0590 data: 0.0082 max mem: 33300 +Epoch: [11] [ 40/4276] eta: 3:38:57 lr: 3.742354768208721e-05 loss: 0.1496 (0.1623) time: 3.0323 data: 0.0084 max mem: 33300 +Epoch: [11] [ 50/4276] eta: 3:36:56 lr: 3.7420830635164374e-05 loss: 0.1589 (0.1606) time: 3.0004 data: 0.0086 max mem: 33300 +Epoch: [11] [ 60/4276] eta: 3:35:38 lr: 3.7418113566321454e-05 loss: 0.1502 (0.1599) time: 3.0026 data: 0.0081 max mem: 33300 +Epoch: [11] [ 70/4276] eta: 3:34:52 lr: 3.741539647555653e-05 loss: 0.1441 (0.1581) time: 3.0270 data: 0.0075 max mem: 33300 +Epoch: [11] [ 80/4276] eta: 3:34:08 lr: 3.7412679362867645e-05 loss: 0.1444 (0.1591) time: 3.0412 data: 0.0072 max mem: 33300 +Epoch: [11] [ 90/4276] eta: 3:33:49 lr: 3.740996222825287e-05 loss: 0.1380 (0.1581) time: 3.0637 data: 0.0080 max mem: 33300 +Epoch: [11] [ 100/4276] eta: 3:33:14 lr: 3.740724507171023e-05 loss: 0.1374 (0.1591) time: 3.0704 data: 0.0087 max mem: 33300 +Epoch: [11] [ 110/4276] eta: 3:32:29 lr: 3.7404527893237806e-05 loss: 0.1492 (0.1592) time: 3.0402 data: 0.0083 max mem: 33300 +Epoch: [11] [ 120/4276] eta: 3:31:47 lr: 3.7401810692833634e-05 loss: 0.1516 (0.1592) time: 3.0268 data: 0.0085 max mem: 33300 +Epoch: [11] [ 130/4276] eta: 3:31:20 lr: 3.7399093470495774e-05 loss: 0.1638 (0.1594) time: 3.0486 data: 0.0083 max mem: 33300 +Epoch: [11] [ 140/4276] eta: 3:30:52 lr: 3.739637622622227e-05 loss: 0.1430 (0.1583) time: 3.0674 data: 0.0083 max mem: 33300 +Epoch: [11] [ 150/4276] eta: 3:30:18 lr: 3.7393658960011184e-05 loss: 0.1549 (0.1593) time: 3.0562 data: 0.0089 max mem: 33300 +Epoch: [11] [ 160/4276] eta: 3:29:41 lr: 3.739094167186056e-05 loss: 0.1556 (0.1589) time: 3.0399 data: 0.0085 max mem: 33300 +Epoch: [11] [ 170/4276] eta: 3:29:13 lr: 3.738822436176845e-05 loss: 0.1518 (0.1586) time: 3.0503 data: 0.0083 max mem: 33300 +Epoch: [11] [ 180/4276] eta: 3:28:49 lr: 3.738550702973291e-05 loss: 0.1582 (0.1592) time: 3.0776 data: 0.0086 max mem: 33300 +Epoch: [11] [ 190/4276] eta: 3:28:33 lr: 3.7382789675752e-05 loss: 0.1767 (0.1597) time: 3.1066 data: 0.0082 max mem: 33300 +Epoch: [11] [ 200/4276] eta: 3:28:17 lr: 3.7380072299823746e-05 loss: 0.1563 (0.1599) time: 3.1308 data: 0.0078 max mem: 33300 +Epoch: [11] [ 210/4276] eta: 3:27:45 lr: 3.737735490194622e-05 loss: 0.1589 (0.1602) time: 3.0981 data: 0.0077 max mem: 33300 +Epoch: [11] [ 220/4276] eta: 3:27:12 lr: 3.737463748211745e-05 loss: 0.1654 (0.1604) time: 3.0571 data: 0.0080 max mem: 33300 +Epoch: [11] [ 230/4276] eta: 3:26:31 lr: 3.737192004033551e-05 loss: 0.1456 (0.1598) time: 3.0291 data: 0.0088 max mem: 33300 +Epoch: [11] [ 240/4276] eta: 3:25:46 lr: 3.736920257659843e-05 loss: 0.1513 (0.1600) time: 2.9919 data: 0.0081 max mem: 33300 +Epoch: [11] [ 250/4276] eta: 3:25:05 lr: 3.7366485090904255e-05 loss: 0.1720 (0.1611) time: 2.9858 data: 0.0074 max mem: 33300 +Epoch: [11] [ 260/4276] eta: 3:24:28 lr: 3.736376758325105e-05 loss: 0.1561 (0.1611) time: 3.0041 data: 0.0076 max mem: 33300 +Epoch: [11] [ 270/4276] eta: 3:24:03 lr: 3.736105005363687e-05 loss: 0.1503 (0.1612) time: 3.0524 data: 0.0089 max mem: 33300 +Epoch: [11] [ 280/4276] eta: 3:23:41 lr: 3.735833250205974e-05 loss: 0.1489 (0.1612) time: 3.1016 data: 0.0094 max mem: 33300 +Epoch: [11] [ 290/4276] eta: 3:23:11 lr: 3.735561492851771e-05 loss: 0.1450 (0.1609) time: 3.0917 data: 0.0079 max mem: 33300 +Epoch: [11] [ 300/4276] eta: 3:22:47 lr: 3.735289733300883e-05 loss: 0.1436 (0.1606) time: 3.0884 data: 0.0079 max mem: 33300 +Epoch: [11] [ 310/4276] eta: 3:22:16 lr: 3.7350179715531166e-05 loss: 0.1539 (0.1603) time: 3.0807 data: 0.0087 max mem: 33300 +Epoch: [11] [ 320/4276] eta: 3:21:43 lr: 3.734746207608273e-05 loss: 0.1593 (0.1610) time: 3.0494 data: 0.0084 max mem: 33300 +Epoch: [11] [ 330/4276] eta: 3:21:12 lr: 3.73447444146616e-05 loss: 0.1716 (0.1612) time: 3.0472 data: 0.0080 max mem: 33300 +Epoch: [11] [ 340/4276] eta: 3:20:38 lr: 3.7342026731265804e-05 loss: 0.1501 (0.1611) time: 3.0417 data: 0.0079 max mem: 33300 +Epoch: [11] [ 350/4276] eta: 3:20:02 lr: 3.7339309025893385e-05 loss: 0.1474 (0.1609) time: 3.0218 data: 0.0079 max mem: 33300 +Epoch: [11] [ 360/4276] eta: 3:19:28 lr: 3.7336591298542407e-05 loss: 0.1562 (0.1618) time: 3.0191 data: 0.0080 max mem: 33300 +Epoch: [11] [ 370/4276] eta: 3:18:58 lr: 3.733387354921089e-05 loss: 0.1606 (0.1613) time: 3.0416 data: 0.0085 max mem: 33300 +Epoch: [11] [ 380/4276] eta: 3:18:28 lr: 3.7331155777896895e-05 loss: 0.1421 (0.1613) time: 3.0626 data: 0.0087 max mem: 33300 +Epoch: [11] [ 390/4276] eta: 3:18:03 lr: 3.732843798459846e-05 loss: 0.1492 (0.1611) time: 3.0904 data: 0.0087 max mem: 33300 +Epoch: [11] [ 400/4276] eta: 3:17:38 lr: 3.732572016931362e-05 loss: 0.1571 (0.1609) time: 3.1129 data: 0.0086 max mem: 33300 +Epoch: [11] [ 410/4276] eta: 3:17:11 lr: 3.732300233204044e-05 loss: 0.1498 (0.1605) time: 3.1054 data: 0.0084 max mem: 33300 +Epoch: [11] [ 420/4276] eta: 3:16:40 lr: 3.7320284472776954e-05 loss: 0.1498 (0.1604) time: 3.0748 data: 0.0082 max mem: 33300 +Epoch: [11] [ 430/4276] eta: 3:16:08 lr: 3.731756659152119e-05 loss: 0.1583 (0.1604) time: 3.0516 data: 0.0080 max mem: 33300 +Epoch: [11] [ 440/4276] eta: 3:15:36 lr: 3.7314848688271206e-05 loss: 0.1539 (0.1602) time: 3.0442 data: 0.0078 max mem: 33300 +Epoch: [11] [ 450/4276] eta: 3:15:04 lr: 3.7312130763025046e-05 loss: 0.1502 (0.1602) time: 3.0407 data: 0.0079 max mem: 33300 +Epoch: [11] [ 460/4276] eta: 3:14:31 lr: 3.730941281578074e-05 loss: 0.1502 (0.1602) time: 3.0390 data: 0.0080 max mem: 33300 +Epoch: [11] [ 470/4276] eta: 3:14:00 lr: 3.730669484653633e-05 loss: 0.1406 (0.1599) time: 3.0435 data: 0.0083 max mem: 33300 +Epoch: [11] [ 480/4276] eta: 3:13:34 lr: 3.730397685528987e-05 loss: 0.1348 (0.1595) time: 3.0830 data: 0.0087 max mem: 33300 +Epoch: [11] [ 490/4276] eta: 3:13:07 lr: 3.730125884203939e-05 loss: 0.1314 (0.1591) time: 3.1124 data: 0.0088 max mem: 33300 +Epoch: [11] [ 500/4276] eta: 3:12:41 lr: 3.7298540806782936e-05 loss: 0.1275 (0.1588) time: 3.1122 data: 0.0082 max mem: 33300 +Epoch: [11] [ 510/4276] eta: 3:12:15 lr: 3.729582274951854e-05 loss: 0.1284 (0.1583) time: 3.1202 data: 0.0079 max mem: 33300 +Epoch: [11] [ 520/4276] eta: 3:11:49 lr: 3.729310467024425e-05 loss: 0.1322 (0.1583) time: 3.1268 data: 0.0082 max mem: 33300 +Epoch: [11] [ 530/4276] eta: 3:11:18 lr: 3.7290386568958095e-05 loss: 0.1619 (0.1584) time: 3.0938 data: 0.0079 max mem: 33300 +Epoch: [11] [ 540/4276] eta: 3:10:45 lr: 3.728766844565812e-05 loss: 0.1497 (0.1581) time: 3.0496 data: 0.0075 max mem: 33300 +Epoch: [11] [ 550/4276] eta: 3:10:15 lr: 3.7284950300342375e-05 loss: 0.1463 (0.1581) time: 3.0557 data: 0.0077 max mem: 33300 +Epoch: [11] [ 560/4276] eta: 3:09:44 lr: 3.728223213300888e-05 loss: 0.1485 (0.1580) time: 3.0585 data: 0.0079 max mem: 33300 +Epoch: [11] [ 570/4276] eta: 3:09:11 lr: 3.727951394365568e-05 loss: 0.1485 (0.1580) time: 3.0430 data: 0.0079 max mem: 33300 +Epoch: [11] [ 580/4276] eta: 3:08:38 lr: 3.727679573228082e-05 loss: 0.1456 (0.1579) time: 3.0268 data: 0.0079 max mem: 33300 +Epoch: [11] [ 590/4276] eta: 3:08:04 lr: 3.7274077498882335e-05 loss: 0.1362 (0.1575) time: 3.0113 data: 0.0076 max mem: 33300 +Epoch: [11] [ 600/4276] eta: 3:07:31 lr: 3.7271359243458246e-05 loss: 0.1415 (0.1575) time: 3.0169 data: 0.0075 max mem: 33300 +Epoch: [11] [ 610/4276] eta: 3:07:01 lr: 3.7268640966006606e-05 loss: 0.1486 (0.1573) time: 3.0464 data: 0.0083 max mem: 33300 +Epoch: [11] [ 620/4276] eta: 3:06:36 lr: 3.726592266652545e-05 loss: 0.1460 (0.1573) time: 3.1184 data: 0.0088 max mem: 33300 +Epoch: [11] [ 630/4276] eta: 3:06:04 lr: 3.7263204345012806e-05 loss: 0.1461 (0.1575) time: 3.1003 data: 0.0081 max mem: 33300 +Epoch: [11] [ 640/4276] eta: 3:05:30 lr: 3.726048600146672e-05 loss: 0.1470 (0.1574) time: 3.0205 data: 0.0079 max mem: 33300 +Epoch: [11] [ 650/4276] eta: 3:04:59 lr: 3.7257767635885215e-05 loss: 0.1528 (0.1575) time: 3.0257 data: 0.0086 max mem: 33300 +Epoch: [11] [ 660/4276] eta: 3:04:28 lr: 3.7255049248266335e-05 loss: 0.1625 (0.1576) time: 3.0469 data: 0.0090 max mem: 33300 +Epoch: [11] [ 670/4276] eta: 3:03:54 lr: 3.725233083860811e-05 loss: 0.1564 (0.1575) time: 3.0282 data: 0.0088 max mem: 33300 +Epoch: [11] [ 680/4276] eta: 3:03:21 lr: 3.7249612406908586e-05 loss: 0.1522 (0.1576) time: 3.0071 data: 0.0083 max mem: 33300 +Epoch: [11] [ 690/4276] eta: 3:02:53 lr: 3.724689395316578e-05 loss: 0.1567 (0.1576) time: 3.0663 data: 0.0083 max mem: 33300 +Epoch: [11] [ 700/4276] eta: 3:02:22 lr: 3.724417547737773e-05 loss: 0.1567 (0.1575) time: 3.0844 data: 0.0086 max mem: 33300 +Epoch: [11] [ 710/4276] eta: 3:01:52 lr: 3.7241456979542475e-05 loss: 0.1625 (0.1575) time: 3.0580 data: 0.0085 max mem: 33300 +Epoch: [11] [ 720/4276] eta: 3:01:24 lr: 3.7238738459658045e-05 loss: 0.1508 (0.1573) time: 3.0891 data: 0.0084 max mem: 33300 +Epoch: [11] [ 730/4276] eta: 3:00:52 lr: 3.723601991772248e-05 loss: 0.1441 (0.1574) time: 3.0745 data: 0.0082 max mem: 33300 +Epoch: [11] [ 740/4276] eta: 3:00:21 lr: 3.7233301353733804e-05 loss: 0.1606 (0.1573) time: 3.0425 data: 0.0086 max mem: 33300 +Epoch: [11] [ 750/4276] eta: 2:59:50 lr: 3.723058276769005e-05 loss: 0.1606 (0.1573) time: 3.0519 data: 0.0089 max mem: 33300 +Epoch: [11] [ 760/4276] eta: 2:59:20 lr: 3.7227864159589245e-05 loss: 0.1429 (0.1573) time: 3.0709 data: 0.0088 max mem: 33300 +Epoch: [11] [ 770/4276] eta: 2:58:50 lr: 3.722514552942942e-05 loss: 0.1396 (0.1574) time: 3.0695 data: 0.0085 max mem: 33300 +Epoch: [11] [ 780/4276] eta: 2:58:20 lr: 3.722242687720862e-05 loss: 0.1596 (0.1574) time: 3.0660 data: 0.0091 max mem: 33300 +Epoch: [11] [ 790/4276] eta: 2:57:50 lr: 3.721970820292487e-05 loss: 0.1555 (0.1574) time: 3.0730 data: 0.0097 max mem: 33300 +Epoch: [11] [ 800/4276] eta: 2:57:19 lr: 3.721698950657619e-05 loss: 0.1449 (0.1573) time: 3.0650 data: 0.0089 max mem: 33300 +Epoch: [11] [ 810/4276] eta: 2:56:50 lr: 3.7214270788160625e-05 loss: 0.1456 (0.1574) time: 3.0812 data: 0.0083 max mem: 33300 +Epoch: [11] [ 820/4276] eta: 2:56:19 lr: 3.721155204767619e-05 loss: 0.1456 (0.1571) time: 3.0758 data: 0.0085 max mem: 33300 +Epoch: [11] [ 830/4276] eta: 2:55:48 lr: 3.720883328512093e-05 loss: 0.1363 (0.1571) time: 3.0451 data: 0.0087 max mem: 33300 +Epoch: [11] [ 840/4276] eta: 2:55:17 lr: 3.7206114500492864e-05 loss: 0.1393 (0.1571) time: 3.0514 data: 0.0086 max mem: 33300 +Epoch: [11] [ 850/4276] eta: 2:54:47 lr: 3.720339569379001e-05 loss: 0.1371 (0.1569) time: 3.0696 data: 0.0084 max mem: 33300 +Epoch: [11] [ 860/4276] eta: 2:54:16 lr: 3.7200676865010414e-05 loss: 0.1506 (0.1569) time: 3.0634 data: 0.0083 max mem: 33300 +Epoch: [11] [ 870/4276] eta: 2:53:45 lr: 3.7197958014152095e-05 loss: 0.1491 (0.1569) time: 3.0457 data: 0.0092 max mem: 33300 +Epoch: [11] [ 880/4276] eta: 2:53:14 lr: 3.719523914121309e-05 loss: 0.1454 (0.1569) time: 3.0514 data: 0.0091 max mem: 33300 +Epoch: [11] [ 890/4276] eta: 2:52:44 lr: 3.719252024619142e-05 loss: 0.1523 (0.1572) time: 3.0735 data: 0.0083 max mem: 33300 +Epoch: [11] [ 900/4276] eta: 2:52:14 lr: 3.718980132908511e-05 loss: 0.1716 (0.1572) time: 3.0732 data: 0.0083 max mem: 33300 +Epoch: [11] [ 910/4276] eta: 2:51:46 lr: 3.718708238989219e-05 loss: 0.1647 (0.1574) time: 3.0967 data: 0.0086 max mem: 33300 +Epoch: [11] [ 920/4276] eta: 2:51:16 lr: 3.718436342861068e-05 loss: 0.1647 (0.1575) time: 3.1112 data: 0.0083 max mem: 33300 +Epoch: [11] [ 930/4276] eta: 2:50:45 lr: 3.718164444523861e-05 loss: 0.1686 (0.1576) time: 3.0652 data: 0.0080 max mem: 33300 +Epoch: [11] [ 940/4276] eta: 2:50:13 lr: 3.717892543977401e-05 loss: 0.1541 (0.1575) time: 3.0430 data: 0.0082 max mem: 33300 +Epoch: [11] [ 950/4276] eta: 2:49:42 lr: 3.71762064122149e-05 loss: 0.1508 (0.1576) time: 3.0426 data: 0.0087 max mem: 33300 +Epoch: [11] [ 960/4276] eta: 2:49:11 lr: 3.7173487362559304e-05 loss: 0.1589 (0.1577) time: 3.0415 data: 0.0091 max mem: 33300 +Epoch: [11] [ 970/4276] eta: 2:48:40 lr: 3.7170768290805255e-05 loss: 0.1619 (0.1577) time: 3.0399 data: 0.0092 max mem: 33300 +Epoch: [11] [ 980/4276] eta: 2:48:10 lr: 3.7168049196950774e-05 loss: 0.1609 (0.1578) time: 3.0649 data: 0.0092 max mem: 33300 +Epoch: [11] [ 990/4276] eta: 2:47:40 lr: 3.716533008099387e-05 loss: 0.1609 (0.1578) time: 3.0942 data: 0.0090 max mem: 33300 +Epoch: [11] [1000/4276] eta: 2:47:11 lr: 3.7162610942932584e-05 loss: 0.1579 (0.1578) time: 3.0937 data: 0.0085 max mem: 33300 +Epoch: [11] [1010/4276] eta: 2:46:41 lr: 3.715989178276493e-05 loss: 0.1524 (0.1578) time: 3.0965 data: 0.0081 max mem: 33300 +Epoch: [11] [1020/4276] eta: 2:46:11 lr: 3.715717260048894e-05 loss: 0.1502 (0.1577) time: 3.0785 data: 0.0080 max mem: 33300 +Epoch: [11] [1030/4276] eta: 2:45:39 lr: 3.715445339610263e-05 loss: 0.1446 (0.1577) time: 3.0479 data: 0.0082 max mem: 33300 +Epoch: [11] [1040/4276] eta: 2:45:08 lr: 3.715173416960402e-05 loss: 0.1512 (0.1577) time: 3.0484 data: 0.0082 max mem: 33300 +Epoch: [11] [1050/4276] eta: 2:44:38 lr: 3.7149014920991146e-05 loss: 0.1560 (0.1579) time: 3.0540 data: 0.0079 max mem: 33300 +Epoch: [11] [1060/4276] eta: 2:44:07 lr: 3.714629565026201e-05 loss: 0.1659 (0.1580) time: 3.0663 data: 0.0078 max mem: 33300 +Epoch: [11] [1070/4276] eta: 2:43:36 lr: 3.714357635741464e-05 loss: 0.1634 (0.1580) time: 3.0549 data: 0.0080 max mem: 33300 +Epoch: [11] [1080/4276] eta: 2:43:04 lr: 3.714085704244706e-05 loss: 0.1563 (0.1579) time: 3.0234 data: 0.0082 max mem: 33300 +Epoch: [11] [1090/4276] eta: 2:42:31 lr: 3.713813770535729e-05 loss: 0.1478 (0.1579) time: 3.0016 data: 0.0078 max mem: 33300 +Epoch: [11] [1100/4276] eta: 2:42:01 lr: 3.7135418346143354e-05 loss: 0.1398 (0.1579) time: 3.0364 data: 0.0076 max mem: 33300 +Epoch: [11] [1110/4276] eta: 2:41:32 lr: 3.713269896480326e-05 loss: 0.1571 (0.1579) time: 3.0886 data: 0.0083 max mem: 33300 +Epoch: [11] [1120/4276] eta: 2:41:01 lr: 3.712997956133505e-05 loss: 0.1571 (0.1579) time: 3.0719 data: 0.0084 max mem: 33300 +Epoch: [11] [1130/4276] eta: 2:40:30 lr: 3.7127260135736715e-05 loss: 0.1491 (0.1577) time: 3.0546 data: 0.0081 max mem: 33300 +Epoch: [11] [1140/4276] eta: 2:39:58 lr: 3.7124540688006295e-05 loss: 0.1323 (0.1576) time: 3.0330 data: 0.0078 max mem: 33300 +Epoch: [11] [1150/4276] eta: 2:39:26 lr: 3.712182121814179e-05 loss: 0.1388 (0.1575) time: 3.0195 data: 0.0079 max mem: 33300 +Epoch: [11] [1160/4276] eta: 2:38:56 lr: 3.711910172614123e-05 loss: 0.1489 (0.1575) time: 3.0430 data: 0.0083 max mem: 33300 +Epoch: [11] [1170/4276] eta: 2:38:25 lr: 3.7116382212002636e-05 loss: 0.1597 (0.1576) time: 3.0613 data: 0.0081 max mem: 33300 +Epoch: [11] [1180/4276] eta: 2:37:55 lr: 3.711366267572402e-05 loss: 0.1565 (0.1575) time: 3.0703 data: 0.0077 max mem: 33300 +Epoch: [11] [1190/4276] eta: 2:37:25 lr: 3.71109431173034e-05 loss: 0.1416 (0.1574) time: 3.0704 data: 0.0075 max mem: 33300 +Epoch: [11] [1200/4276] eta: 2:36:57 lr: 3.710822353673879e-05 loss: 0.1359 (0.1573) time: 3.1136 data: 0.0078 max mem: 33300 +Epoch: [11] [1210/4276] eta: 2:36:26 lr: 3.7105503934028226e-05 loss: 0.1359 (0.1572) time: 3.1162 data: 0.0081 max mem: 33300 +Epoch: [11] [1220/4276] eta: 2:35:55 lr: 3.7102784309169685e-05 loss: 0.1485 (0.1572) time: 3.0549 data: 0.0073 max mem: 33300 +Epoch: [11] [1230/4276] eta: 2:35:24 lr: 3.710006466216122e-05 loss: 0.1578 (0.1574) time: 3.0429 data: 0.0070 max mem: 33300 +Epoch: [11] [1240/4276] eta: 2:34:53 lr: 3.709734499300082e-05 loss: 0.1549 (0.1574) time: 3.0434 data: 0.0077 max mem: 33300 +Epoch: [11] [1250/4276] eta: 2:34:22 lr: 3.7094625301686516e-05 loss: 0.1544 (0.1574) time: 3.0371 data: 0.0079 max mem: 33300 +Epoch: [11] [1260/4276] eta: 2:33:50 lr: 3.709190558821632e-05 loss: 0.1490 (0.1573) time: 3.0369 data: 0.0078 max mem: 33300 +Epoch: [11] [1270/4276] eta: 2:33:21 lr: 3.7089185852588246e-05 loss: 0.1423 (0.1572) time: 3.0776 data: 0.0079 max mem: 33300 +Epoch: [11] [1280/4276] eta: 2:32:51 lr: 3.7086466094800305e-05 loss: 0.1504 (0.1572) time: 3.0986 data: 0.0080 max mem: 33300 +Epoch: [11] [1290/4276] eta: 2:32:20 lr: 3.708374631485051e-05 loss: 0.1534 (0.1573) time: 3.0647 data: 0.0077 max mem: 33300 +Epoch: [11] [1300/4276] eta: 2:31:50 lr: 3.708102651273689e-05 loss: 0.1462 (0.1573) time: 3.0706 data: 0.0076 max mem: 33300 +Epoch: [11] [1310/4276] eta: 2:31:18 lr: 3.707830668845743e-05 loss: 0.1366 (0.1572) time: 3.0498 data: 0.0078 max mem: 33300 +Epoch: [11] [1320/4276] eta: 2:30:47 lr: 3.707558684201016e-05 loss: 0.1454 (0.1572) time: 3.0259 data: 0.0084 max mem: 33300 +Epoch: [11] [1330/4276] eta: 2:30:17 lr: 3.7072866973393094e-05 loss: 0.1571 (0.1572) time: 3.0542 data: 0.0093 max mem: 33300 +Epoch: [11] [1340/4276] eta: 2:29:47 lr: 3.7070147082604237e-05 loss: 0.1459 (0.1572) time: 3.0750 data: 0.0087 max mem: 33300 +Epoch: [11] [1350/4276] eta: 2:29:16 lr: 3.7067427169641615e-05 loss: 0.1556 (0.1572) time: 3.0680 data: 0.0085 max mem: 33300 +Epoch: [11] [1360/4276] eta: 2:28:45 lr: 3.706470723450322e-05 loss: 0.1642 (0.1573) time: 3.0505 data: 0.0088 max mem: 33300 +Epoch: [11] [1370/4276] eta: 2:28:15 lr: 3.7061987277187076e-05 loss: 0.1540 (0.1572) time: 3.0634 data: 0.0090 max mem: 33300 +Epoch: [11] [1380/4276] eta: 2:27:44 lr: 3.705926729769119e-05 loss: 0.1612 (0.1573) time: 3.0611 data: 0.0092 max mem: 33300 +Epoch: [11] [1390/4276] eta: 2:27:14 lr: 3.705654729601356e-05 loss: 0.1703 (0.1574) time: 3.0640 data: 0.0089 max mem: 33300 +Epoch: [11] [1400/4276] eta: 2:26:44 lr: 3.7053827272152216e-05 loss: 0.1703 (0.1574) time: 3.0928 data: 0.0096 max mem: 33300 +Epoch: [11] [1410/4276] eta: 2:26:14 lr: 3.705110722610515e-05 loss: 0.1433 (0.1574) time: 3.0930 data: 0.0097 max mem: 33300 +Epoch: [11] [1420/4276] eta: 2:25:43 lr: 3.704838715787039e-05 loss: 0.1451 (0.1574) time: 3.0659 data: 0.0088 max mem: 33300 +Epoch: [11] [1430/4276] eta: 2:25:12 lr: 3.704566706744594e-05 loss: 0.1451 (0.1574) time: 3.0428 data: 0.0085 max mem: 33300 +Epoch: [11] [1440/4276] eta: 2:24:41 lr: 3.704294695482979e-05 loss: 0.1528 (0.1574) time: 3.0367 data: 0.0086 max mem: 33300 +Epoch: [11] [1450/4276] eta: 2:24:10 lr: 3.704022682001997e-05 loss: 0.1585 (0.1575) time: 3.0371 data: 0.0088 max mem: 33300 +Epoch: [11] [1460/4276] eta: 2:23:39 lr: 3.703750666301448e-05 loss: 0.1564 (0.1574) time: 3.0470 data: 0.0090 max mem: 33300 +Epoch: [11] [1470/4276] eta: 2:23:09 lr: 3.703478648381133e-05 loss: 0.1564 (0.1575) time: 3.0685 data: 0.0090 max mem: 33300 +Epoch: [11] [1480/4276] eta: 2:22:39 lr: 3.7032066282408524e-05 loss: 0.1319 (0.1574) time: 3.0859 data: 0.0086 max mem: 33300 +Epoch: [11] [1490/4276] eta: 2:22:09 lr: 3.7029346058804063e-05 loss: 0.1334 (0.1574) time: 3.0880 data: 0.0085 max mem: 33300 +Epoch: [11] [1500/4276] eta: 2:21:38 lr: 3.7026625812995976e-05 loss: 0.1514 (0.1573) time: 3.0825 data: 0.0091 max mem: 33300 +Epoch: [11] [1510/4276] eta: 2:21:07 lr: 3.702390554498224e-05 loss: 0.1474 (0.1574) time: 3.0592 data: 0.0089 max mem: 33300 +Epoch: [11] [1520/4276] eta: 2:20:36 lr: 3.702118525476088e-05 loss: 0.1474 (0.1574) time: 3.0360 data: 0.0086 max mem: 33300 +Epoch: [11] [1530/4276] eta: 2:20:05 lr: 3.70184649423299e-05 loss: 0.1500 (0.1573) time: 3.0330 data: 0.0088 max mem: 33300 +Epoch: [11] [1540/4276] eta: 2:19:34 lr: 3.70157446076873e-05 loss: 0.1544 (0.1574) time: 3.0329 data: 0.0087 max mem: 33300 +Epoch: [11] [1550/4276] eta: 2:19:04 lr: 3.701302425083108e-05 loss: 0.1554 (0.1573) time: 3.0542 data: 0.0084 max mem: 33300 +Epoch: [11] [1560/4276] eta: 2:18:33 lr: 3.701030387175925e-05 loss: 0.1497 (0.1573) time: 3.0784 data: 0.0084 max mem: 33300 +Epoch: [11] [1570/4276] eta: 2:18:02 lr: 3.700758347046982e-05 loss: 0.1569 (0.1574) time: 3.0645 data: 0.0084 max mem: 33300 +Epoch: [11] [1580/4276] eta: 2:17:32 lr: 3.700486304696079e-05 loss: 0.1405 (0.1573) time: 3.0527 data: 0.0084 max mem: 33300 +Epoch: [11] [1590/4276] eta: 2:17:02 lr: 3.7002142601230163e-05 loss: 0.1405 (0.1573) time: 3.0772 data: 0.0085 max mem: 33300 +Epoch: [11] [1600/4276] eta: 2:16:31 lr: 3.699942213327595e-05 loss: 0.1577 (0.1572) time: 3.0791 data: 0.0087 max mem: 33300 +Epoch: [11] [1610/4276] eta: 2:16:00 lr: 3.699670164309613e-05 loss: 0.1408 (0.1571) time: 3.0463 data: 0.0091 max mem: 33300 +Epoch: [11] [1620/4276] eta: 2:15:30 lr: 3.699398113068873e-05 loss: 0.1364 (0.1570) time: 3.0525 data: 0.0090 max mem: 33300 +Epoch: [11] [1630/4276] eta: 2:14:59 lr: 3.6991260596051735e-05 loss: 0.1391 (0.1571) time: 3.0642 data: 0.0085 max mem: 33300 +Epoch: [11] [1640/4276] eta: 2:14:28 lr: 3.698854003918316e-05 loss: 0.1408 (0.1570) time: 3.0469 data: 0.0084 max mem: 33300 +Epoch: [11] [1650/4276] eta: 2:13:57 lr: 3.6985819460081e-05 loss: 0.1412 (0.1570) time: 3.0473 data: 0.0085 max mem: 33300 +Epoch: [11] [1660/4276] eta: 2:13:27 lr: 3.698309885874326e-05 loss: 0.1504 (0.1570) time: 3.0699 data: 0.0085 max mem: 33300 +Epoch: [11] [1670/4276] eta: 2:12:56 lr: 3.698037823516794e-05 loss: 0.1502 (0.1570) time: 3.0636 data: 0.0081 max mem: 33300 +Epoch: [11] [1680/4276] eta: 2:12:26 lr: 3.6977657589353035e-05 loss: 0.1563 (0.1570) time: 3.0604 data: 0.0082 max mem: 33300 +Epoch: [11] [1690/4276] eta: 2:11:56 lr: 3.697493692129655e-05 loss: 0.1567 (0.1570) time: 3.0919 data: 0.0084 max mem: 33300 +Epoch: [11] [1700/4276] eta: 2:11:26 lr: 3.6972216230996485e-05 loss: 0.1566 (0.1571) time: 3.0914 data: 0.0089 max mem: 33300 +Epoch: [11] [1710/4276] eta: 2:10:54 lr: 3.6969495518450834e-05 loss: 0.1694 (0.1571) time: 3.0551 data: 0.0093 max mem: 33300 +Epoch: [11] [1720/4276] eta: 2:10:24 lr: 3.69667747836576e-05 loss: 0.1694 (0.1572) time: 3.0364 data: 0.0094 max mem: 33300 +Epoch: [11] [1730/4276] eta: 2:09:53 lr: 3.696405402661478e-05 loss: 0.1552 (0.1572) time: 3.0377 data: 0.0098 max mem: 33300 +Epoch: [11] [1740/4276] eta: 2:09:22 lr: 3.6961333247320385e-05 loss: 0.1649 (0.1573) time: 3.0369 data: 0.0093 max mem: 33300 +Epoch: [11] [1750/4276] eta: 2:08:51 lr: 3.6958612445772395e-05 loss: 0.1530 (0.1572) time: 3.0487 data: 0.0091 max mem: 33300 +Epoch: [11] [1760/4276] eta: 2:08:21 lr: 3.695589162196882e-05 loss: 0.1394 (0.1571) time: 3.0761 data: 0.0094 max mem: 33300 +Epoch: [11] [1770/4276] eta: 2:07:50 lr: 3.695317077590764e-05 loss: 0.1629 (0.1572) time: 3.0771 data: 0.0093 max mem: 33300 +Epoch: [11] [1780/4276] eta: 2:07:20 lr: 3.695044990758687e-05 loss: 0.1589 (0.1572) time: 3.0798 data: 0.0096 max mem: 33300 +Epoch: [11] [1790/4276] eta: 2:06:50 lr: 3.69477290170045e-05 loss: 0.1497 (0.1571) time: 3.0959 data: 0.0093 max mem: 33300 +Epoch: [11] [1800/4276] eta: 2:06:19 lr: 3.694500810415853e-05 loss: 0.1514 (0.1571) time: 3.0698 data: 0.0088 max mem: 33300 +Epoch: [11] [1810/4276] eta: 2:05:48 lr: 3.694228716904696e-05 loss: 0.1604 (0.1572) time: 3.0431 data: 0.0088 max mem: 33300 +Epoch: [11] [1820/4276] eta: 2:05:17 lr: 3.693956621166776e-05 loss: 0.1535 (0.1572) time: 3.0385 data: 0.0094 max mem: 33300 +Epoch: [11] [1830/4276] eta: 2:04:47 lr: 3.6936845232018965e-05 loss: 0.1508 (0.1571) time: 3.0508 data: 0.0095 max mem: 33300 +Epoch: [11] [1840/4276] eta: 2:04:16 lr: 3.6934124230098535e-05 loss: 0.1462 (0.1571) time: 3.0581 data: 0.0088 max mem: 33300 +Epoch: [11] [1850/4276] eta: 2:03:45 lr: 3.693140320590447e-05 loss: 0.1529 (0.1572) time: 3.0518 data: 0.0088 max mem: 33300 +Epoch: [11] [1860/4276] eta: 2:03:14 lr: 3.692868215943479e-05 loss: 0.1523 (0.1571) time: 3.0243 data: 0.0084 max mem: 33300 +Epoch: [11] [1870/4276] eta: 2:02:43 lr: 3.692596109068746e-05 loss: 0.1516 (0.1573) time: 3.0141 data: 0.0075 max mem: 33300 +Epoch: [11] [1880/4276] eta: 2:02:13 lr: 3.692323999966049e-05 loss: 0.1631 (0.1573) time: 3.0628 data: 0.0081 max mem: 33300 +Epoch: [11] [1890/4276] eta: 2:01:42 lr: 3.6920518886351874e-05 loss: 0.1515 (0.1573) time: 3.0822 data: 0.0088 max mem: 33300 +Epoch: [11] [1900/4276] eta: 2:01:11 lr: 3.691779775075959e-05 loss: 0.1416 (0.1572) time: 3.0520 data: 0.0088 max mem: 33300 +Epoch: [11] [1910/4276] eta: 2:00:40 lr: 3.691507659288164e-05 loss: 0.1499 (0.1573) time: 3.0163 data: 0.0078 max mem: 33300 +Epoch: [11] [1920/4276] eta: 2:00:09 lr: 3.6912355412716024e-05 loss: 0.1597 (0.1572) time: 3.0104 data: 0.0081 max mem: 33300 +Epoch: [11] [1930/4276] eta: 1:59:37 lr: 3.690963421026071e-05 loss: 0.1597 (0.1572) time: 3.0064 data: 0.0085 max mem: 33300 +Epoch: [11] [1940/4276] eta: 1:59:06 lr: 3.690691298551372e-05 loss: 0.1559 (0.1572) time: 2.9950 data: 0.0074 max mem: 33300 +Epoch: [11] [1950/4276] eta: 1:58:36 lr: 3.6904191738473024e-05 loss: 0.1559 (0.1572) time: 3.0382 data: 0.0075 max mem: 33300 +Epoch: [11] [1960/4276] eta: 1:58:05 lr: 3.6901470469136615e-05 loss: 0.1489 (0.1572) time: 3.0451 data: 0.0080 max mem: 33300 +Epoch: [11] [1970/4276] eta: 1:57:34 lr: 3.68987491775025e-05 loss: 0.1274 (0.1571) time: 3.0257 data: 0.0081 max mem: 33300 +Epoch: [11] [1980/4276] eta: 1:57:04 lr: 3.6896027863568644e-05 loss: 0.1283 (0.1570) time: 3.0932 data: 0.0093 max mem: 33300 +Epoch: [11] [1990/4276] eta: 1:56:34 lr: 3.689330652733306e-05 loss: 0.1445 (0.1570) time: 3.1132 data: 0.0100 max mem: 33300 +Epoch: [11] [2000/4276] eta: 1:56:03 lr: 3.689058516879371e-05 loss: 0.1488 (0.1570) time: 3.0625 data: 0.0095 max mem: 33300 +Epoch: [11] [2010/4276] eta: 1:55:32 lr: 3.6887863787948606e-05 loss: 0.1502 (0.1569) time: 3.0435 data: 0.0094 max mem: 33300 +Epoch: [11] [2020/4276] eta: 1:55:01 lr: 3.6885142384795737e-05 loss: 0.1530 (0.1569) time: 3.0380 data: 0.0093 max mem: 33300 +Epoch: [11] [2030/4276] eta: 1:54:31 lr: 3.6882420959333076e-05 loss: 0.1453 (0.1569) time: 3.0405 data: 0.0094 max mem: 33300 +Epoch: [11] [2040/4276] eta: 1:54:00 lr: 3.6879699511558626e-05 loss: 0.1402 (0.1568) time: 3.0619 data: 0.0095 max mem: 33300 +Epoch: [11] [2050/4276] eta: 1:53:30 lr: 3.6876978041470366e-05 loss: 0.1586 (0.1568) time: 3.0999 data: 0.0094 max mem: 33300 +Epoch: [11] [2060/4276] eta: 1:53:00 lr: 3.6874256549066286e-05 loss: 0.1586 (0.1568) time: 3.0819 data: 0.0092 max mem: 33300 +Epoch: [11] [2070/4276] eta: 1:52:29 lr: 3.687153503434438e-05 loss: 0.1448 (0.1567) time: 3.0578 data: 0.0090 max mem: 33300 +Epoch: [11] [2080/4276] eta: 1:51:59 lr: 3.6868813497302615e-05 loss: 0.1457 (0.1568) time: 3.0861 data: 0.0092 max mem: 33300 +Epoch: [11] [2090/4276] eta: 1:51:29 lr: 3.6866091937938994e-05 loss: 0.1615 (0.1568) time: 3.0899 data: 0.0093 max mem: 33300 +Epoch: [11] [2100/4276] eta: 1:50:58 lr: 3.6863370356251495e-05 loss: 0.1549 (0.1568) time: 3.0617 data: 0.0089 max mem: 33300 +Epoch: [11] [2110/4276] eta: 1:50:27 lr: 3.686064875223811e-05 loss: 0.1413 (0.1567) time: 3.0519 data: 0.0086 max mem: 33300 +Epoch: [11] [2120/4276] eta: 1:49:57 lr: 3.685792712589682e-05 loss: 0.1170 (0.1565) time: 3.0728 data: 0.0093 max mem: 33300 +Epoch: [11] [2130/4276] eta: 1:49:26 lr: 3.685520547722562e-05 loss: 0.1284 (0.1564) time: 3.0644 data: 0.0094 max mem: 33300 +Epoch: [11] [2140/4276] eta: 1:48:56 lr: 3.685248380622248e-05 loss: 0.1515 (0.1564) time: 3.0652 data: 0.0093 max mem: 33300 +Epoch: [11] [2150/4276] eta: 1:48:25 lr: 3.6849762112885385e-05 loss: 0.1579 (0.1564) time: 3.0791 data: 0.0095 max mem: 33300 +Epoch: [11] [2160/4276] eta: 1:47:55 lr: 3.684704039721233e-05 loss: 0.1440 (0.1565) time: 3.0658 data: 0.0092 max mem: 33300 +Epoch: [11] [2170/4276] eta: 1:47:24 lr: 3.684431865920128e-05 loss: 0.1547 (0.1565) time: 3.0673 data: 0.0089 max mem: 33300 +Epoch: [11] [2180/4276] eta: 1:46:54 lr: 3.684159689885025e-05 loss: 0.1597 (0.1565) time: 3.0889 data: 0.0088 max mem: 33300 +Epoch: [11] [2190/4276] eta: 1:46:23 lr: 3.683887511615718e-05 loss: 0.1487 (0.1565) time: 3.0781 data: 0.0088 max mem: 33300 +Epoch: [11] [2200/4276] eta: 1:45:53 lr: 3.683615331112009e-05 loss: 0.1530 (0.1565) time: 3.0469 data: 0.0083 max mem: 33300 +Epoch: [11] [2210/4276] eta: 1:45:22 lr: 3.683343148373695e-05 loss: 0.1600 (0.1565) time: 3.0384 data: 0.0089 max mem: 33300 +Epoch: [11] [2220/4276] eta: 1:44:51 lr: 3.683070963400574e-05 loss: 0.1600 (0.1565) time: 3.0355 data: 0.0097 max mem: 33300 +Epoch: [11] [2230/4276] eta: 1:44:20 lr: 3.682798776192443e-05 loss: 0.1509 (0.1565) time: 3.0426 data: 0.0094 max mem: 33300 +Epoch: [11] [2240/4276] eta: 1:43:50 lr: 3.6825265867491014e-05 loss: 0.1305 (0.1564) time: 3.0595 data: 0.0091 max mem: 33300 +Epoch: [11] [2250/4276] eta: 1:43:19 lr: 3.682254395070348e-05 loss: 0.1366 (0.1563) time: 3.0364 data: 0.0087 max mem: 33300 +Epoch: [11] [2260/4276] eta: 1:42:48 lr: 3.6819822011559794e-05 loss: 0.1481 (0.1564) time: 3.0236 data: 0.0080 max mem: 33300 +Epoch: [11] [2270/4276] eta: 1:42:17 lr: 3.6817100050057936e-05 loss: 0.1479 (0.1564) time: 3.0642 data: 0.0085 max mem: 33300 +Epoch: [11] [2280/4276] eta: 1:41:47 lr: 3.68143780661959e-05 loss: 0.1530 (0.1564) time: 3.0798 data: 0.0092 max mem: 33300 +Epoch: [11] [2290/4276] eta: 1:41:16 lr: 3.6811656059971645e-05 loss: 0.1581 (0.1564) time: 3.0519 data: 0.0090 max mem: 33300 +Epoch: [11] [2300/4276] eta: 1:40:45 lr: 3.6808934031383166e-05 loss: 0.1511 (0.1563) time: 3.0390 data: 0.0086 max mem: 33300 +Epoch: [11] [2310/4276] eta: 1:40:15 lr: 3.680621198042844e-05 loss: 0.1406 (0.1563) time: 3.0396 data: 0.0085 max mem: 33300 +Epoch: [11] [2320/4276] eta: 1:39:44 lr: 3.6803489907105436e-05 loss: 0.1612 (0.1564) time: 3.0342 data: 0.0087 max mem: 33300 +Epoch: [11] [2330/4276] eta: 1:39:14 lr: 3.680076781141214e-05 loss: 0.1655 (0.1564) time: 3.0708 data: 0.0085 max mem: 33300 +Epoch: [11] [2340/4276] eta: 1:38:43 lr: 3.679804569334653e-05 loss: 0.1634 (0.1564) time: 3.0945 data: 0.0081 max mem: 33300 +Epoch: [11] [2350/4276] eta: 1:38:12 lr: 3.6795323552906577e-05 loss: 0.1497 (0.1564) time: 3.0644 data: 0.0083 max mem: 33300 +Epoch: [11] [2360/4276] eta: 1:37:42 lr: 3.679260139009027e-05 loss: 0.1492 (0.1564) time: 3.0461 data: 0.0082 max mem: 33300 +Epoch: [11] [2370/4276] eta: 1:37:11 lr: 3.678987920489556e-05 loss: 0.1549 (0.1564) time: 3.0585 data: 0.0082 max mem: 33300 +Epoch: [11] [2380/4276] eta: 1:36:41 lr: 3.678715699732046e-05 loss: 0.1510 (0.1564) time: 3.0763 data: 0.0090 max mem: 33300 +Epoch: [11] [2390/4276] eta: 1:36:10 lr: 3.678443476736292e-05 loss: 0.1467 (0.1563) time: 3.0630 data: 0.0089 max mem: 33300 +Epoch: [11] [2400/4276] eta: 1:35:40 lr: 3.678171251502091e-05 loss: 0.1556 (0.1563) time: 3.0589 data: 0.0086 max mem: 33300 +Epoch: [11] [2410/4276] eta: 1:35:09 lr: 3.6778990240292426e-05 loss: 0.1635 (0.1563) time: 3.0532 data: 0.0083 max mem: 33300 +Epoch: [11] [2420/4276] eta: 1:34:38 lr: 3.677626794317543e-05 loss: 0.1375 (0.1563) time: 3.0324 data: 0.0085 max mem: 33300 +Epoch: [11] [2430/4276] eta: 1:34:08 lr: 3.6773545623667905e-05 loss: 0.1537 (0.1564) time: 3.0534 data: 0.0086 max mem: 33300 +Epoch: [11] [2440/4276] eta: 1:33:37 lr: 3.677082328176782e-05 loss: 0.1582 (0.1563) time: 3.0719 data: 0.0085 max mem: 33300 +Epoch: [11] [2450/4276] eta: 1:33:06 lr: 3.676810091747315e-05 loss: 0.1485 (0.1563) time: 3.0617 data: 0.0081 max mem: 33300 +Epoch: [11] [2460/4276] eta: 1:32:36 lr: 3.676537853078186e-05 loss: 0.1491 (0.1563) time: 3.0775 data: 0.0079 max mem: 33300 +Epoch: [11] [2470/4276] eta: 1:32:06 lr: 3.676265612169193e-05 loss: 0.1613 (0.1564) time: 3.1188 data: 0.0083 max mem: 33300 +Epoch: [11] [2480/4276] eta: 1:31:35 lr: 3.675993369020133e-05 loss: 0.1618 (0.1564) time: 3.1019 data: 0.0083 max mem: 33300 +Epoch: [11] [2490/4276] eta: 1:31:05 lr: 3.675721123630804e-05 loss: 0.1547 (0.1564) time: 3.0504 data: 0.0083 max mem: 33300 +Epoch: [11] [2500/4276] eta: 1:30:34 lr: 3.675448876001003e-05 loss: 0.1479 (0.1564) time: 3.0303 data: 0.0085 max mem: 33300 +Epoch: [11] [2510/4276] eta: 1:30:03 lr: 3.675176626130527e-05 loss: 0.1533 (0.1564) time: 3.0366 data: 0.0084 max mem: 33300 +Epoch: [11] [2520/4276] eta: 1:29:33 lr: 3.674904374019172e-05 loss: 0.1428 (0.1563) time: 3.0491 data: 0.0086 max mem: 33300 +Epoch: [11] [2530/4276] eta: 1:29:02 lr: 3.674632119666737e-05 loss: 0.1225 (0.1562) time: 3.0688 data: 0.0086 max mem: 33300 +Epoch: [11] [2540/4276] eta: 1:28:32 lr: 3.674359863073018e-05 loss: 0.1254 (0.1561) time: 3.0852 data: 0.0083 max mem: 33300 +Epoch: [11] [2550/4276] eta: 1:28:01 lr: 3.674087604237812e-05 loss: 0.1373 (0.1561) time: 3.0707 data: 0.0084 max mem: 33300 +Epoch: [11] [2560/4276] eta: 1:27:31 lr: 3.673815343160916e-05 loss: 0.1334 (0.1560) time: 3.0745 data: 0.0083 max mem: 33300 +Epoch: [11] [2570/4276] eta: 1:27:01 lr: 3.6735430798421275e-05 loss: 0.1242 (0.1559) time: 3.1127 data: 0.0084 max mem: 33300 +Epoch: [11] [2580/4276] eta: 1:26:30 lr: 3.673270814281242e-05 loss: 0.1397 (0.1559) time: 3.1026 data: 0.0088 max mem: 33300 +Epoch: [11] [2590/4276] eta: 1:25:59 lr: 3.672998546478059e-05 loss: 0.1462 (0.1559) time: 3.0360 data: 0.0087 max mem: 33300 +Epoch: [11] [2600/4276] eta: 1:25:28 lr: 3.672726276432373e-05 loss: 0.1462 (0.1558) time: 3.0193 data: 0.0081 max mem: 33300 +Epoch: [11] [2610/4276] eta: 1:24:58 lr: 3.672454004143982e-05 loss: 0.1314 (0.1558) time: 3.0433 data: 0.0081 max mem: 33300 +Epoch: [11] [2620/4276] eta: 1:24:27 lr: 3.6721817296126816e-05 loss: 0.1489 (0.1558) time: 3.0572 data: 0.0086 max mem: 33300 +Epoch: [11] [2630/4276] eta: 1:23:57 lr: 3.671909452838269e-05 loss: 0.1504 (0.1557) time: 3.0766 data: 0.0088 max mem: 33300 +Epoch: [11] [2640/4276] eta: 1:23:26 lr: 3.6716371738205416e-05 loss: 0.1377 (0.1557) time: 3.0785 data: 0.0085 max mem: 33300 +Epoch: [11] [2650/4276] eta: 1:22:56 lr: 3.671364892559296e-05 loss: 0.1419 (0.1557) time: 3.0757 data: 0.0083 max mem: 33300 +Epoch: [11] [2660/4276] eta: 1:22:25 lr: 3.671092609054329e-05 loss: 0.1572 (0.1558) time: 3.0792 data: 0.0079 max mem: 33300 +Epoch: [11] [2670/4276] eta: 1:21:55 lr: 3.6708203233054356e-05 loss: 0.1572 (0.1557) time: 3.0799 data: 0.0078 max mem: 33300 +Epoch: [11] [2680/4276] eta: 1:21:24 lr: 3.670548035312414e-05 loss: 0.1544 (0.1558) time: 3.0607 data: 0.0079 max mem: 33300 +Epoch: [11] [2690/4276] eta: 1:20:53 lr: 3.670275745075061e-05 loss: 0.1516 (0.1557) time: 3.0474 data: 0.0085 max mem: 33300 +Epoch: [11] [2700/4276] eta: 1:20:23 lr: 3.670003452593171e-05 loss: 0.1428 (0.1557) time: 3.0648 data: 0.0088 max mem: 33300 +Epoch: [11] [2710/4276] eta: 1:19:52 lr: 3.6697311578665413e-05 loss: 0.1388 (0.1557) time: 3.0647 data: 0.0084 max mem: 33300 +Epoch: [11] [2720/4276] eta: 1:19:22 lr: 3.6694588608949706e-05 loss: 0.1421 (0.1556) time: 3.0686 data: 0.0080 max mem: 33300 +Epoch: [11] [2730/4276] eta: 1:18:51 lr: 3.6691865616782515e-05 loss: 0.1575 (0.1557) time: 3.0643 data: 0.0079 max mem: 33300 +Epoch: [11] [2740/4276] eta: 1:18:20 lr: 3.6689142602161844e-05 loss: 0.1593 (0.1557) time: 3.0312 data: 0.0080 max mem: 33300 +Epoch: [11] [2750/4276] eta: 1:17:49 lr: 3.6686419565085624e-05 loss: 0.1575 (0.1557) time: 3.0409 data: 0.0079 max mem: 33300 +Epoch: [11] [2760/4276] eta: 1:17:19 lr: 3.668369650555183e-05 loss: 0.1479 (0.1557) time: 3.0746 data: 0.0085 max mem: 33300 +Epoch: [11] [2770/4276] eta: 1:16:49 lr: 3.668097342355842e-05 loss: 0.1410 (0.1557) time: 3.1036 data: 0.0091 max mem: 33300 +Epoch: [11] [2780/4276] eta: 1:16:18 lr: 3.667825031910337e-05 loss: 0.1418 (0.1557) time: 3.0889 data: 0.0091 max mem: 33300 +Epoch: [11] [2790/4276] eta: 1:15:47 lr: 3.6675527192184625e-05 loss: 0.1498 (0.1557) time: 3.0556 data: 0.0089 max mem: 33300 +Epoch: [11] [2800/4276] eta: 1:15:17 lr: 3.6672804042800144e-05 loss: 0.1484 (0.1556) time: 3.0541 data: 0.0090 max mem: 33300 +Epoch: [11] [2810/4276] eta: 1:14:46 lr: 3.667008087094791e-05 loss: 0.1231 (0.1555) time: 3.0600 data: 0.0092 max mem: 33300 +Epoch: [11] [2820/4276] eta: 1:14:16 lr: 3.6667357676625866e-05 loss: 0.1258 (0.1554) time: 3.0795 data: 0.0092 max mem: 33300 +Epoch: [11] [2830/4276] eta: 1:13:45 lr: 3.666463445983198e-05 loss: 0.1354 (0.1554) time: 3.0792 data: 0.0091 max mem: 33300 +Epoch: [11] [2840/4276] eta: 1:13:15 lr: 3.6661911220564214e-05 loss: 0.1483 (0.1554) time: 3.0792 data: 0.0088 max mem: 33300 +Epoch: [11] [2850/4276] eta: 1:12:44 lr: 3.665918795882052e-05 loss: 0.1663 (0.1555) time: 3.0938 data: 0.0085 max mem: 33300 +Epoch: [11] [2860/4276] eta: 1:12:14 lr: 3.665646467459885e-05 loss: 0.1598 (0.1554) time: 3.0621 data: 0.0083 max mem: 33300 +Epoch: [11] [2870/4276] eta: 1:11:43 lr: 3.665374136789718e-05 loss: 0.1414 (0.1554) time: 3.0169 data: 0.0077 max mem: 33300 +Epoch: [11] [2880/4276] eta: 1:11:12 lr: 3.6651018038713466e-05 loss: 0.1436 (0.1554) time: 2.9952 data: 0.0072 max mem: 33300 +Epoch: [11] [2890/4276] eta: 1:10:41 lr: 3.664829468704565e-05 loss: 0.1529 (0.1554) time: 2.9877 data: 0.0076 max mem: 33300 +Epoch: [11] [2900/4276] eta: 1:10:10 lr: 3.664557131289172e-05 loss: 0.1475 (0.1553) time: 3.0298 data: 0.0084 max mem: 33300 +Epoch: [11] [2910/4276] eta: 1:09:40 lr: 3.66428479162496e-05 loss: 0.1442 (0.1553) time: 3.0749 data: 0.0093 max mem: 33300 +Epoch: [11] [2920/4276] eta: 1:09:09 lr: 3.6640124497117275e-05 loss: 0.1446 (0.1553) time: 3.0818 data: 0.0094 max mem: 33300 +Epoch: [11] [2930/4276] eta: 1:08:39 lr: 3.6637401055492685e-05 loss: 0.1343 (0.1552) time: 3.0870 data: 0.0087 max mem: 33300 +Epoch: [11] [2940/4276] eta: 1:08:08 lr: 3.6634677591373786e-05 loss: 0.1257 (0.1552) time: 3.0944 data: 0.0085 max mem: 33300 +Epoch: [11] [2950/4276] eta: 1:07:38 lr: 3.663195410475854e-05 loss: 0.1329 (0.1551) time: 3.0785 data: 0.0080 max mem: 33300 +Epoch: [11] [2960/4276] eta: 1:07:07 lr: 3.6629230595644906e-05 loss: 0.1453 (0.1551) time: 3.0920 data: 0.0084 max mem: 33300 +Epoch: [11] [2970/4276] eta: 1:06:37 lr: 3.6626507064030824e-05 loss: 0.1455 (0.1552) time: 3.1303 data: 0.0092 max mem: 33300 +Epoch: [11] [2980/4276] eta: 1:06:07 lr: 3.6623783509914275e-05 loss: 0.1512 (0.1552) time: 3.1154 data: 0.0086 max mem: 33300 +Epoch: [11] [2990/4276] eta: 1:05:36 lr: 3.662105993329319e-05 loss: 0.1501 (0.1551) time: 3.0829 data: 0.0085 max mem: 33300 +Epoch: [11] [3000/4276] eta: 1:05:06 lr: 3.661833633416554e-05 loss: 0.1349 (0.1551) time: 3.0738 data: 0.0090 max mem: 33300 +Epoch: [11] [3010/4276] eta: 1:04:35 lr: 3.661561271252927e-05 loss: 0.1401 (0.1551) time: 3.0661 data: 0.0086 max mem: 33300 +Epoch: [11] [3020/4276] eta: 1:04:04 lr: 3.6612889068382325e-05 loss: 0.1479 (0.1550) time: 3.0727 data: 0.0082 max mem: 33300 +Epoch: [11] [3030/4276] eta: 1:03:34 lr: 3.6610165401722677e-05 loss: 0.1450 (0.1550) time: 3.0832 data: 0.0086 max mem: 33300 +Epoch: [11] [3040/4276] eta: 1:03:03 lr: 3.660744171254827e-05 loss: 0.1595 (0.1551) time: 3.0863 data: 0.0089 max mem: 33300 +Epoch: [11] [3050/4276] eta: 1:02:33 lr: 3.6604718000857056e-05 loss: 0.1592 (0.1551) time: 3.0823 data: 0.0088 max mem: 33300 +Epoch: [11] [3060/4276] eta: 1:02:02 lr: 3.6601994266646985e-05 loss: 0.1340 (0.1550) time: 3.0880 data: 0.0088 max mem: 33300 +Epoch: [11] [3070/4276] eta: 1:01:32 lr: 3.6599270509916015e-05 loss: 0.1475 (0.1550) time: 3.0839 data: 0.0083 max mem: 33300 +Epoch: [11] [3080/4276] eta: 1:01:01 lr: 3.659654673066209e-05 loss: 0.1393 (0.1549) time: 3.0488 data: 0.0079 max mem: 33300 +Epoch: [11] [3090/4276] eta: 1:00:30 lr: 3.659382292888317e-05 loss: 0.1325 (0.1549) time: 3.0457 data: 0.0082 max mem: 33300 +Epoch: [11] [3100/4276] eta: 1:00:00 lr: 3.65910991045772e-05 loss: 0.1353 (0.1549) time: 3.0744 data: 0.0087 max mem: 33300 +Epoch: [11] [3110/4276] eta: 0:59:29 lr: 3.658837525774213e-05 loss: 0.1353 (0.1548) time: 3.0783 data: 0.0089 max mem: 33300 +Epoch: [11] [3120/4276] eta: 0:58:59 lr: 3.658565138837591e-05 loss: 0.1326 (0.1548) time: 3.0668 data: 0.0090 max mem: 33300 +Epoch: [11] [3130/4276] eta: 0:58:28 lr: 3.6582927496476496e-05 loss: 0.1385 (0.1548) time: 3.0791 data: 0.0088 max mem: 33300 +Epoch: [11] [3140/4276] eta: 0:57:58 lr: 3.6580203582041835e-05 loss: 0.1463 (0.1548) time: 3.0740 data: 0.0087 max mem: 33300 +Epoch: [11] [3150/4276] eta: 0:57:27 lr: 3.657747964506987e-05 loss: 0.1569 (0.1548) time: 3.0692 data: 0.0089 max mem: 33300 +Epoch: [11] [3160/4276] eta: 0:56:56 lr: 3.657475568555856e-05 loss: 0.1538 (0.1548) time: 3.0765 data: 0.0088 max mem: 33300 +Epoch: [11] [3170/4276] eta: 0:56:26 lr: 3.6572031703505836e-05 loss: 0.1455 (0.1548) time: 3.0936 data: 0.0086 max mem: 33300 +Epoch: [11] [3180/4276] eta: 0:55:56 lr: 3.656930769890966e-05 loss: 0.1450 (0.1548) time: 3.1021 data: 0.0088 max mem: 33300 +Epoch: [11] [3190/4276] eta: 0:55:25 lr: 3.6566583671767976e-05 loss: 0.1438 (0.1548) time: 3.0774 data: 0.0089 max mem: 33300 +Epoch: [11] [3200/4276] eta: 0:54:54 lr: 3.6563859622078735e-05 loss: 0.1446 (0.1548) time: 3.0591 data: 0.0086 max mem: 33300 +Epoch: [11] [3210/4276] eta: 0:54:24 lr: 3.656113554983988e-05 loss: 0.1540 (0.1549) time: 3.0556 data: 0.0083 max mem: 33300 +Epoch: [11] [3220/4276] eta: 0:53:53 lr: 3.655841145504936e-05 loss: 0.1545 (0.1549) time: 3.0680 data: 0.0085 max mem: 33300 +Epoch: [11] [3230/4276] eta: 0:53:22 lr: 3.655568733770512e-05 loss: 0.1535 (0.1548) time: 3.0734 data: 0.0084 max mem: 33300 +Epoch: [11] [3240/4276] eta: 0:52:52 lr: 3.6552963197805096e-05 loss: 0.1553 (0.1549) time: 3.0648 data: 0.0084 max mem: 33300 +Epoch: [11] [3250/4276] eta: 0:52:21 lr: 3.655023903534724e-05 loss: 0.1543 (0.1549) time: 3.0698 data: 0.0091 max mem: 33300 +Epoch: [11] [3260/4276] eta: 0:51:51 lr: 3.654751485032951e-05 loss: 0.1514 (0.1549) time: 3.0897 data: 0.0098 max mem: 33300 +Epoch: [11] [3270/4276] eta: 0:51:20 lr: 3.654479064274984e-05 loss: 0.1502 (0.1549) time: 3.0885 data: 0.0100 max mem: 33300 +Epoch: [11] [3280/4276] eta: 0:50:50 lr: 3.654206641260617e-05 loss: 0.1462 (0.1548) time: 3.0857 data: 0.0099 max mem: 33300 +Epoch: [11] [3290/4276] eta: 0:50:19 lr: 3.653934215989645e-05 loss: 0.1459 (0.1549) time: 3.0865 data: 0.0096 max mem: 33300 +Epoch: [11] [3300/4276] eta: 0:49:49 lr: 3.653661788461862e-05 loss: 0.1507 (0.1548) time: 3.0826 data: 0.0096 max mem: 33300 +Epoch: [11] [3310/4276] eta: 0:49:18 lr: 3.6533893586770636e-05 loss: 0.1531 (0.1549) time: 3.0753 data: 0.0099 max mem: 33300 +Epoch: [11] [3320/4276] eta: 0:48:47 lr: 3.653116926635042e-05 loss: 0.1599 (0.1549) time: 3.0742 data: 0.0098 max mem: 33300 +Epoch: [11] [3330/4276] eta: 0:48:17 lr: 3.652844492335592e-05 loss: 0.1474 (0.1549) time: 3.0904 data: 0.0098 max mem: 33300 +Epoch: [11] [3340/4276] eta: 0:47:46 lr: 3.652572055778509e-05 loss: 0.1586 (0.1550) time: 3.0736 data: 0.0097 max mem: 33300 +Epoch: [11] [3350/4276] eta: 0:47:16 lr: 3.652299616963586e-05 loss: 0.1549 (0.1549) time: 3.0677 data: 0.0094 max mem: 33300 +Epoch: [11] [3360/4276] eta: 0:46:45 lr: 3.652027175890619e-05 loss: 0.1398 (0.1549) time: 3.0943 data: 0.0096 max mem: 33300 +Epoch: [11] [3370/4276] eta: 0:46:15 lr: 3.6517547325593996e-05 loss: 0.1521 (0.1550) time: 3.1076 data: 0.0095 max mem: 33300 +Epoch: [11] [3380/4276] eta: 0:45:44 lr: 3.651482286969724e-05 loss: 0.1516 (0.1549) time: 3.1044 data: 0.0092 max mem: 33300 +Epoch: [11] [3390/4276] eta: 0:45:13 lr: 3.651209839121385e-05 loss: 0.1496 (0.1550) time: 3.0703 data: 0.0094 max mem: 33300 +Epoch: [11] [3400/4276] eta: 0:44:43 lr: 3.650937389014176e-05 loss: 0.1613 (0.1550) time: 3.0484 data: 0.0096 max mem: 33300 +Epoch: [11] [3410/4276] eta: 0:44:12 lr: 3.650664936647893e-05 loss: 0.1613 (0.1550) time: 3.0570 data: 0.0093 max mem: 33300 +Epoch: [11] [3420/4276] eta: 0:43:42 lr: 3.650392482022328e-05 loss: 0.1623 (0.1550) time: 3.0766 data: 0.0092 max mem: 33300 +Epoch: [11] [3430/4276] eta: 0:43:11 lr: 3.650120025137276e-05 loss: 0.1623 (0.1551) time: 3.0949 data: 0.0094 max mem: 33300 +Epoch: [11] [3440/4276] eta: 0:42:40 lr: 3.649847565992531e-05 loss: 0.1410 (0.1550) time: 3.0893 data: 0.0092 max mem: 33300 +Epoch: [11] [3450/4276] eta: 0:42:10 lr: 3.649575104587886e-05 loss: 0.1483 (0.1551) time: 3.0857 data: 0.0089 max mem: 33300 +Epoch: [11] [3460/4276] eta: 0:41:39 lr: 3.649302640923135e-05 loss: 0.1696 (0.1551) time: 3.0762 data: 0.0088 max mem: 33300 +Epoch: [11] [3470/4276] eta: 0:41:09 lr: 3.649030174998072e-05 loss: 0.1354 (0.1551) time: 3.0683 data: 0.0087 max mem: 33300 +Epoch: [11] [3480/4276] eta: 0:40:38 lr: 3.648757706812491e-05 loss: 0.1502 (0.1551) time: 3.0845 data: 0.0093 max mem: 33300 +Epoch: [11] [3490/4276] eta: 0:40:07 lr: 3.6484852363661855e-05 loss: 0.1566 (0.1551) time: 3.0782 data: 0.0093 max mem: 33300 +Epoch: [11] [3500/4276] eta: 0:39:37 lr: 3.648212763658948e-05 loss: 0.1546 (0.1551) time: 3.0726 data: 0.0087 max mem: 33300 +Epoch: [11] [3510/4276] eta: 0:39:06 lr: 3.6479402886905736e-05 loss: 0.1461 (0.1550) time: 3.0588 data: 0.0084 max mem: 33300 +Epoch: [11] [3520/4276] eta: 0:38:35 lr: 3.647667811460857e-05 loss: 0.1407 (0.1550) time: 3.0575 data: 0.0082 max mem: 33300 +Epoch: [11] [3530/4276] eta: 0:38:05 lr: 3.647395331969588e-05 loss: 0.1426 (0.1550) time: 3.0750 data: 0.0085 max mem: 33300 +Epoch: [11] [3540/4276] eta: 0:37:34 lr: 3.647122850216563e-05 loss: 0.1363 (0.1550) time: 3.0613 data: 0.0086 max mem: 33300 +Epoch: [11] [3550/4276] eta: 0:37:04 lr: 3.6468503662015744e-05 loss: 0.1361 (0.1550) time: 3.0748 data: 0.0085 max mem: 33300 +Epoch: [11] [3560/4276] eta: 0:36:33 lr: 3.646577879924417e-05 loss: 0.1394 (0.1550) time: 3.0873 data: 0.0087 max mem: 33300 +Epoch: [11] [3570/4276] eta: 0:36:02 lr: 3.6463053913848815e-05 loss: 0.1667 (0.1551) time: 3.0940 data: 0.0090 max mem: 33300 +Epoch: [11] [3580/4276] eta: 0:35:32 lr: 3.6460329005827634e-05 loss: 0.1376 (0.1550) time: 3.0992 data: 0.0090 max mem: 33300 +Epoch: [11] [3590/4276] eta: 0:35:01 lr: 3.645760407517856e-05 loss: 0.1334 (0.1550) time: 3.0761 data: 0.0087 max mem: 33300 +Epoch: [11] [3600/4276] eta: 0:34:31 lr: 3.6454879121899525e-05 loss: 0.1448 (0.1550) time: 3.0665 data: 0.0085 max mem: 33300 +Epoch: [11] [3610/4276] eta: 0:34:00 lr: 3.645215414598845e-05 loss: 0.1448 (0.1550) time: 3.0591 data: 0.0086 max mem: 33300 +Epoch: [11] [3620/4276] eta: 0:33:29 lr: 3.644942914744328e-05 loss: 0.1380 (0.1549) time: 3.0573 data: 0.0091 max mem: 33300 +Epoch: [11] [3630/4276] eta: 0:32:59 lr: 3.644670412626194e-05 loss: 0.1442 (0.1549) time: 3.0710 data: 0.0087 max mem: 33300 +Epoch: [11] [3640/4276] eta: 0:32:28 lr: 3.644397908244236e-05 loss: 0.1418 (0.1549) time: 3.0814 data: 0.0088 max mem: 33300 +Epoch: [11] [3650/4276] eta: 0:31:58 lr: 3.6441254015982475e-05 loss: 0.1249 (0.1548) time: 3.0913 data: 0.0093 max mem: 33300 +Epoch: [11] [3660/4276] eta: 0:31:27 lr: 3.643852892688021e-05 loss: 0.1274 (0.1548) time: 3.0827 data: 0.0092 max mem: 33300 +Epoch: [11] [3670/4276] eta: 0:30:56 lr: 3.643580381513351e-05 loss: 0.1485 (0.1548) time: 3.0795 data: 0.0087 max mem: 33300 +Epoch: [11] [3680/4276] eta: 0:30:26 lr: 3.643307868074029e-05 loss: 0.1679 (0.1548) time: 3.0850 data: 0.0087 max mem: 33300 +Epoch: [11] [3690/4276] eta: 0:29:55 lr: 3.643035352369849e-05 loss: 0.1480 (0.1548) time: 3.0685 data: 0.0086 max mem: 33300 +Epoch: [11] [3700/4276] eta: 0:29:24 lr: 3.6427628344006026e-05 loss: 0.1531 (0.1548) time: 3.0741 data: 0.0085 max mem: 33300 +Epoch: [11] [3710/4276] eta: 0:28:54 lr: 3.642490314166084e-05 loss: 0.1494 (0.1548) time: 3.0840 data: 0.0086 max mem: 33300 +Epoch: [11] [3720/4276] eta: 0:28:23 lr: 3.642217791666085e-05 loss: 0.1392 (0.1548) time: 3.0821 data: 0.0087 max mem: 33300 +Epoch: [11] [3730/4276] eta: 0:27:53 lr: 3.6419452669004e-05 loss: 0.1461 (0.1548) time: 3.0757 data: 0.0086 max mem: 33300 +Epoch: [11] [3740/4276] eta: 0:27:22 lr: 3.64167273986882e-05 loss: 0.1514 (0.1548) time: 3.0687 data: 0.0085 max mem: 33300 +Epoch: [11] [3750/4276] eta: 0:26:51 lr: 3.6414002105711385e-05 loss: 0.1521 (0.1548) time: 3.0821 data: 0.0084 max mem: 33300 +Epoch: [11] [3760/4276] eta: 0:26:21 lr: 3.641127679007148e-05 loss: 0.1415 (0.1548) time: 3.0686 data: 0.0090 max mem: 33300 +Epoch: [11] [3770/4276] eta: 0:25:50 lr: 3.640855145176642e-05 loss: 0.1488 (0.1548) time: 3.0796 data: 0.0092 max mem: 33300 +Epoch: [11] [3780/4276] eta: 0:25:19 lr: 3.640582609079412e-05 loss: 0.1508 (0.1548) time: 3.0963 data: 0.0088 max mem: 33300 +Epoch: [11] [3790/4276] eta: 0:24:49 lr: 3.6403100707152514e-05 loss: 0.1483 (0.1548) time: 3.0575 data: 0.0086 max mem: 33300 +Epoch: [11] [3800/4276] eta: 0:24:18 lr: 3.640037530083952e-05 loss: 0.1544 (0.1548) time: 3.0084 data: 0.0082 max mem: 33300 +Epoch: [11] [3810/4276] eta: 0:23:47 lr: 3.639764987185307e-05 loss: 0.1444 (0.1548) time: 3.0037 data: 0.0077 max mem: 33300 +Epoch: [11] [3820/4276] eta: 0:23:17 lr: 3.6394924420191095e-05 loss: 0.1216 (0.1547) time: 3.0544 data: 0.0084 max mem: 33300 +Epoch: [11] [3830/4276] eta: 0:22:46 lr: 3.6392198945851505e-05 loss: 0.1287 (0.1547) time: 3.0787 data: 0.0093 max mem: 33300 +Epoch: [11] [3840/4276] eta: 0:22:15 lr: 3.6389473448832236e-05 loss: 0.1413 (0.1546) time: 3.0872 data: 0.0093 max mem: 33300 +Epoch: [11] [3850/4276] eta: 0:21:45 lr: 3.6386747929131206e-05 loss: 0.1331 (0.1546) time: 3.1003 data: 0.0087 max mem: 33300 +Epoch: [11] [3860/4276] eta: 0:21:14 lr: 3.6384022386746336e-05 loss: 0.1343 (0.1545) time: 3.0799 data: 0.0083 max mem: 33300 +Epoch: [11] [3870/4276] eta: 0:20:44 lr: 3.6381296821675545e-05 loss: 0.1409 (0.1545) time: 3.0769 data: 0.0085 max mem: 33300 +Epoch: [11] [3880/4276] eta: 0:20:13 lr: 3.637857123391677e-05 loss: 0.1377 (0.1545) time: 3.0882 data: 0.0084 max mem: 33300 +Epoch: [11] [3890/4276] eta: 0:19:42 lr: 3.637584562346793e-05 loss: 0.1454 (0.1545) time: 3.0692 data: 0.0080 max mem: 33300 +Epoch: [11] [3900/4276] eta: 0:19:12 lr: 3.637311999032694e-05 loss: 0.1437 (0.1545) time: 3.0729 data: 0.0082 max mem: 33300 +Epoch: [11] [3910/4276] eta: 0:18:41 lr: 3.637039433449172e-05 loss: 0.1332 (0.1544) time: 3.0895 data: 0.0086 max mem: 33300 +Epoch: [11] [3920/4276] eta: 0:18:10 lr: 3.636766865596021e-05 loss: 0.1296 (0.1544) time: 3.0789 data: 0.0086 max mem: 33300 +Epoch: [11] [3930/4276] eta: 0:17:40 lr: 3.636494295473031e-05 loss: 0.1453 (0.1544) time: 3.0643 data: 0.0082 max mem: 33300 +Epoch: [11] [3940/4276] eta: 0:17:09 lr: 3.6362217230799946e-05 loss: 0.1441 (0.1544) time: 3.0704 data: 0.0079 max mem: 33300 +Epoch: [11] [3950/4276] eta: 0:16:39 lr: 3.635949148416704e-05 loss: 0.1396 (0.1543) time: 3.0894 data: 0.0078 max mem: 33300 +Epoch: [11] [3960/4276] eta: 0:16:08 lr: 3.635676571482951e-05 loss: 0.1435 (0.1543) time: 3.0845 data: 0.0077 max mem: 33300 +Epoch: [11] [3970/4276] eta: 0:15:37 lr: 3.635403992278528e-05 loss: 0.1621 (0.1544) time: 3.0938 data: 0.0076 max mem: 33300 +Epoch: [11] [3980/4276] eta: 0:15:07 lr: 3.6351314108032266e-05 loss: 0.1493 (0.1544) time: 3.0977 data: 0.0076 max mem: 33300 +Epoch: [11] [3990/4276] eta: 0:14:36 lr: 3.634858827056839e-05 loss: 0.1461 (0.1544) time: 3.0639 data: 0.0078 max mem: 33300 +Epoch: [11] [4000/4276] eta: 0:14:05 lr: 3.634586241039157e-05 loss: 0.1437 (0.1543) time: 3.0551 data: 0.0082 max mem: 33300 +Epoch: [11] [4010/4276] eta: 0:13:35 lr: 3.6343136527499715e-05 loss: 0.1437 (0.1544) time: 3.0830 data: 0.0082 max mem: 33300 +Epoch: [11] [4020/4276] eta: 0:13:04 lr: 3.634041062189075e-05 loss: 0.1434 (0.1544) time: 3.0865 data: 0.0077 max mem: 33300 +Epoch: [11] [4030/4276] eta: 0:12:33 lr: 3.63376846935626e-05 loss: 0.1410 (0.1544) time: 3.0822 data: 0.0075 max mem: 33300 +Epoch: [11] [4040/4276] eta: 0:12:03 lr: 3.633495874251316e-05 loss: 0.1453 (0.1544) time: 3.0986 data: 0.0078 max mem: 33300 +Epoch: [11] [4050/4276] eta: 0:11:32 lr: 3.633223276874037e-05 loss: 0.1524 (0.1544) time: 3.0941 data: 0.0078 max mem: 33300 +Epoch: [11] [4060/4276] eta: 0:11:02 lr: 3.632950677224214e-05 loss: 0.1510 (0.1545) time: 3.0797 data: 0.0077 max mem: 33300 +Epoch: [11] [4070/4276] eta: 0:10:31 lr: 3.6326780753016374e-05 loss: 0.1619 (0.1545) time: 3.0820 data: 0.0079 max mem: 33300 +Epoch: [11] [4080/4276] eta: 0:10:00 lr: 3.6324054711061e-05 loss: 0.1634 (0.1545) time: 3.0803 data: 0.0081 max mem: 33300 +Epoch: [11] [4090/4276] eta: 0:09:30 lr: 3.632132864637392e-05 loss: 0.1637 (0.1545) time: 3.0621 data: 0.0081 max mem: 33300 +Epoch: [11] [4100/4276] eta: 0:08:59 lr: 3.631860255895307e-05 loss: 0.1560 (0.1545) time: 3.0825 data: 0.0081 max mem: 33300 +Epoch: [11] [4110/4276] eta: 0:08:28 lr: 3.6315876448796345e-05 loss: 0.1560 (0.1546) time: 3.1001 data: 0.0080 max mem: 33300 +Epoch: [11] [4120/4276] eta: 0:07:58 lr: 3.631315031590166e-05 loss: 0.1609 (0.1546) time: 3.0784 data: 0.0082 max mem: 33300 +Epoch: [11] [4130/4276] eta: 0:07:27 lr: 3.6310424160266944e-05 loss: 0.1478 (0.1545) time: 3.0522 data: 0.0088 max mem: 33300 +Epoch: [11] [4140/4276] eta: 0:06:56 lr: 3.63076979818901e-05 loss: 0.1478 (0.1545) time: 3.0686 data: 0.0085 max mem: 33300 +Epoch: [11] [4150/4276] eta: 0:06:26 lr: 3.6304971780769044e-05 loss: 0.1523 (0.1546) time: 3.0965 data: 0.0088 max mem: 33300 +Epoch: [11] [4160/4276] eta: 0:05:55 lr: 3.630224555690168e-05 loss: 0.1506 (0.1546) time: 3.0879 data: 0.0093 max mem: 33300 +Epoch: [11] [4170/4276] eta: 0:05:24 lr: 3.629951931028593e-05 loss: 0.1816 (0.1547) time: 3.1049 data: 0.0086 max mem: 33300 +Epoch: [11] [4180/4276] eta: 0:04:54 lr: 3.62967930409197e-05 loss: 0.1619 (0.1547) time: 3.1000 data: 0.0087 max mem: 33300 +Epoch: [11] [4190/4276] eta: 0:04:23 lr: 3.6294066748800906e-05 loss: 0.1511 (0.1547) time: 3.0652 data: 0.0090 max mem: 33300 +Epoch: [11] [4200/4276] eta: 0:03:52 lr: 3.629134043392745e-05 loss: 0.1542 (0.1547) time: 3.0683 data: 0.0092 max mem: 33300 +Epoch: [11] [4210/4276] eta: 0:03:22 lr: 3.628861409629726e-05 loss: 0.1747 (0.1548) time: 3.0587 data: 0.0087 max mem: 33300 +Epoch: [11] [4220/4276] eta: 0:02:51 lr: 3.628588773590823e-05 loss: 0.1747 (0.1548) time: 3.0429 data: 0.0083 max mem: 33300 +Epoch: [11] [4230/4276] eta: 0:02:21 lr: 3.6283161352758274e-05 loss: 0.1743 (0.1549) time: 3.0749 data: 0.0091 max mem: 33300 +Epoch: [11] [4240/4276] eta: 0:01:50 lr: 3.6280434946845316e-05 loss: 0.1648 (0.1549) time: 3.1051 data: 0.0100 max mem: 33300 +Epoch: [11] [4250/4276] eta: 0:01:19 lr: 3.6277708518167244e-05 loss: 0.1603 (0.1550) time: 3.0967 data: 0.0095 max mem: 33300 +Epoch: [11] [4260/4276] eta: 0:00:49 lr: 3.627498206672197e-05 loss: 0.1675 (0.1550) time: 3.0788 data: 0.0085 max mem: 33300 +Epoch: [11] [4270/4276] eta: 0:00:18 lr: 3.627225559250741e-05 loss: 0.1644 (0.1550) time: 3.0797 data: 0.0078 max mem: 33300 +Epoch: [11] Total time: 3:38:30 +Test: [ 0/21770] eta: 12:51:10 time: 2.1254 data: 2.0860 max mem: 33300 +Test: [ 100/21770] eta: 0:21:14 time: 0.0384 data: 0.0011 max mem: 33300 +Test: [ 200/21770] eta: 0:17:31 time: 0.0385 data: 0.0010 max mem: 33300 +Test: [ 300/21770] eta: 0:16:13 time: 0.0383 data: 0.0010 max mem: 33300 +Test: [ 400/21770] eta: 0:15:33 time: 0.0388 data: 0.0011 max mem: 33300 +Test: [ 500/21770] eta: 0:15:07 time: 0.0386 data: 0.0010 max mem: 33300 +Test: [ 600/21770] eta: 0:14:49 time: 0.0386 data: 0.0011 max mem: 33300 +Test: [ 700/21770] eta: 0:14:35 time: 0.0386 data: 0.0011 max mem: 33300 +Test: [ 800/21770] eta: 0:14:23 time: 0.0386 data: 0.0011 max mem: 33300 +Test: [ 900/21770] eta: 0:14:12 time: 0.0384 data: 0.0011 max mem: 33300 +Test: [ 1000/21770] eta: 0:14:03 time: 0.0389 data: 0.0011 max mem: 33300 +Test: [ 1100/21770] eta: 0:13:55 time: 0.0387 data: 0.0010 max mem: 33300 +Test: [ 1200/21770] eta: 0:13:48 time: 0.0384 data: 0.0010 max mem: 33300 +Test: [ 1300/21770] eta: 0:13:42 time: 0.0384 data: 0.0010 max mem: 33300 +Test: [ 1400/21770] eta: 0:13:35 time: 0.0385 data: 0.0011 max mem: 33300 +Test: [ 1500/21770] eta: 0:13:30 time: 0.0390 data: 0.0011 max mem: 33300 +Test: [ 1600/21770] eta: 0:13:25 time: 0.0392 data: 0.0012 max mem: 33300 +Test: [ 1700/21770] eta: 0:13:20 time: 0.0391 data: 0.0011 max mem: 33300 +Test: [ 1800/21770] eta: 0:13:15 time: 0.0388 data: 0.0012 max mem: 33300 +Test: [ 1900/21770] eta: 0:13:10 time: 0.0391 data: 0.0011 max mem: 33300 +Test: [ 2000/21770] eta: 0:13:05 time: 0.0385 data: 0.0010 max mem: 33300 +Test: [ 2100/21770] eta: 0:13:00 time: 0.0391 data: 0.0011 max mem: 33300 +Test: [ 2200/21770] eta: 0:12:56 time: 0.0386 data: 0.0011 max mem: 33300 +Test: [ 2300/21770] eta: 0:12:51 time: 0.0385 data: 0.0011 max mem: 33300 +Test: [ 2400/21770] eta: 0:12:47 time: 0.0400 data: 0.0011 max mem: 33300 +Test: [ 2500/21770] eta: 0:12:43 time: 0.0392 data: 0.0011 max mem: 33300 +Test: [ 2600/21770] eta: 0:12:39 time: 0.0392 data: 0.0011 max mem: 33300 +Test: [ 2700/21770] eta: 0:12:35 time: 0.0390 data: 0.0011 max mem: 33300 +Test: [ 2800/21770] eta: 0:12:30 time: 0.0392 data: 0.0012 max mem: 33300 +Test: [ 2900/21770] eta: 0:12:26 time: 0.0394 data: 0.0011 max mem: 33300 +Test: [ 3000/21770] eta: 0:12:22 time: 0.0386 data: 0.0011 max mem: 33300 +Test: [ 3100/21770] eta: 0:12:17 time: 0.0387 data: 0.0011 max mem: 33300 +Test: [ 3200/21770] eta: 0:12:13 time: 0.0390 data: 0.0011 max mem: 33300 +Test: [ 3300/21770] eta: 0:12:09 time: 0.0394 data: 0.0011 max mem: 33300 +Test: [ 3400/21770] eta: 0:12:05 time: 0.0396 data: 0.0010 max mem: 33300 +Test: [ 3500/21770] eta: 0:12:01 time: 0.0395 data: 0.0010 max mem: 33300 +Test: [ 3600/21770] eta: 0:11:57 time: 0.0389 data: 0.0011 max mem: 33300 +Test: [ 3700/21770] eta: 0:11:53 time: 0.0388 data: 0.0011 max mem: 33300 +Test: [ 3800/21770] eta: 0:11:49 time: 0.0389 data: 0.0010 max mem: 33300 +Test: [ 3900/21770] eta: 0:11:45 time: 0.0391 data: 0.0011 max mem: 33300 +Test: [ 4000/21770] eta: 0:11:40 time: 0.0389 data: 0.0011 max mem: 33300 +Test: [ 4100/21770] eta: 0:11:36 time: 0.0391 data: 0.0012 max mem: 33300 +Test: [ 4200/21770] eta: 0:11:32 time: 0.0395 data: 0.0012 max mem: 33300 +Test: [ 4300/21770] eta: 0:11:28 time: 0.0392 data: 0.0011 max mem: 33300 +Test: [ 4400/21770] eta: 0:11:24 time: 0.0398 data: 0.0011 max mem: 33300 +Test: [ 4500/21770] eta: 0:11:21 time: 0.0394 data: 0.0011 max mem: 33300 +Test: [ 4600/21770] eta: 0:11:17 time: 0.0394 data: 0.0011 max mem: 33300 +Test: [ 4700/21770] eta: 0:11:13 time: 0.0398 data: 0.0012 max mem: 33300 +Test: [ 4800/21770] eta: 0:11:09 time: 0.0393 data: 0.0012 max mem: 33300 +Test: [ 4900/21770] eta: 0:11:05 time: 0.0395 data: 0.0011 max mem: 33300 +Test: [ 5000/21770] eta: 0:11:01 time: 0.0399 data: 0.0012 max mem: 33300 +Test: [ 5100/21770] eta: 0:10:57 time: 0.0400 data: 0.0012 max mem: 33300 +Test: [ 5200/21770] eta: 0:10:53 time: 0.0390 data: 0.0012 max mem: 33300 +Test: [ 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time: 0.0393 data: 0.0011 max mem: 33300 +Test: [ 6700/21770] eta: 0:09:53 time: 0.0393 data: 0.0011 max mem: 33300 +Test: [ 6800/21770] eta: 0:09:49 time: 0.0391 data: 0.0012 max mem: 33300 +Test: [ 6900/21770] eta: 0:09:45 time: 0.0394 data: 0.0012 max mem: 33300 +Test: [ 7000/21770] eta: 0:09:41 time: 0.0394 data: 0.0012 max mem: 33300 +Test: [ 7100/21770] eta: 0:09:37 time: 0.0391 data: 0.0012 max mem: 33300 +Test: [ 7200/21770] eta: 0:09:33 time: 0.0392 data: 0.0012 max mem: 33300 +Test: [ 7300/21770] eta: 0:09:29 time: 0.0397 data: 0.0010 max mem: 33300 +Test: [ 7400/21770] eta: 0:09:25 time: 0.0398 data: 0.0011 max mem: 33300 +Test: [ 7500/21770] eta: 0:09:21 time: 0.0392 data: 0.0011 max mem: 33300 +Test: [ 7600/21770] eta: 0:09:17 time: 0.0393 data: 0.0011 max mem: 33300 +Test: [ 7700/21770] eta: 0:09:13 time: 0.0394 data: 0.0012 max mem: 33300 +Test: [ 7800/21770] eta: 0:09:09 time: 0.0396 data: 0.0011 max mem: 33300 +Test: [ 7900/21770] eta: 0:09:05 time: 0.0394 data: 0.0011 max mem: 33300 +Test: [ 8000/21770] eta: 0:09:01 time: 0.0399 data: 0.0011 max mem: 33300 +Test: [ 8100/21770] eta: 0:08:58 time: 0.0393 data: 0.0012 max mem: 33300 +Test: [ 8200/21770] eta: 0:08:54 time: 0.0391 data: 0.0010 max mem: 33300 +Test: [ 8300/21770] eta: 0:08:50 time: 0.0389 data: 0.0010 max mem: 33300 +Test: [ 8400/21770] eta: 0:08:46 time: 0.0389 data: 0.0010 max mem: 33300 +Test: [ 8500/21770] eta: 0:08:42 time: 0.0390 data: 0.0011 max mem: 33300 +Test: [ 8600/21770] eta: 0:08:38 time: 0.0386 data: 0.0010 max mem: 33300 +Test: [ 8700/21770] eta: 0:08:34 time: 0.0384 data: 0.0010 max mem: 33300 +Test: [ 8800/21770] eta: 0:08:30 time: 0.0385 data: 0.0011 max mem: 33300 +Test: [ 8900/21770] eta: 0:08:26 time: 0.0384 data: 0.0010 max mem: 33300 +Test: [ 9000/21770] eta: 0:08:22 time: 0.0385 data: 0.0011 max mem: 33300 +Test: [ 9100/21770] eta: 0:08:18 time: 0.0388 data: 0.0011 max mem: 33300 +Test: [ 9200/21770] eta: 0:08:14 time: 0.0386 data: 0.0011 max mem: 33300 +Test: [ 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time: 0.0398 data: 0.0011 max mem: 33300 +Test: [10700/21770] eta: 0:07:14 time: 0.0394 data: 0.0011 max mem: 33300 +Test: [10800/21770] eta: 0:07:10 time: 0.0395 data: 0.0010 max mem: 33300 +Test: [10900/21770] eta: 0:07:06 time: 0.0393 data: 0.0011 max mem: 33300 +Test: [11000/21770] eta: 0:07:02 time: 0.0391 data: 0.0011 max mem: 33300 +Test: [11100/21770] eta: 0:06:59 time: 0.0387 data: 0.0011 max mem: 33300 +Test: [11200/21770] eta: 0:06:55 time: 0.0388 data: 0.0012 max mem: 33300 +Test: [11300/21770] eta: 0:06:51 time: 0.0389 data: 0.0011 max mem: 33300 +Test: [11400/21770] eta: 0:06:47 time: 0.0387 data: 0.0011 max mem: 33300 +Test: [11500/21770] eta: 0:06:43 time: 0.0389 data: 0.0011 max mem: 33300 +Test: [11600/21770] eta: 0:06:39 time: 0.0387 data: 0.0011 max mem: 33300 +Test: [11700/21770] eta: 0:06:35 time: 0.0388 data: 0.0011 max mem: 33300 +Test: [11800/21770] eta: 0:06:31 time: 0.0385 data: 0.0011 max mem: 33300 +Test: [11900/21770] eta: 0:06:27 time: 0.0390 data: 0.0012 max mem: 33300 +Test: [12000/21770] eta: 0:06:23 time: 0.0390 data: 0.0011 max mem: 33300 +Test: [12100/21770] eta: 0:06:19 time: 0.0391 data: 0.0011 max mem: 33300 +Test: [12200/21770] eta: 0:06:15 time: 0.0391 data: 0.0011 max mem: 33300 +Test: [12300/21770] eta: 0:06:11 time: 0.0388 data: 0.0010 max mem: 33300 +Test: [12400/21770] eta: 0:06:07 time: 0.0388 data: 0.0012 max mem: 33300 +Test: [12500/21770] eta: 0:06:03 time: 0.0392 data: 0.0011 max mem: 33300 +Test: [12600/21770] eta: 0:05:59 time: 0.0392 data: 0.0012 max mem: 33300 +Test: [12700/21770] eta: 0:05:55 time: 0.0395 data: 0.0012 max mem: 33300 +Test: [12800/21770] eta: 0:05:51 time: 0.0396 data: 0.0012 max mem: 33300 +Test: [12900/21770] eta: 0:05:48 time: 0.0397 data: 0.0012 max mem: 33300 +Test: [13000/21770] eta: 0:05:44 time: 0.0395 data: 0.0012 max mem: 33300 +Test: [13100/21770] eta: 0:05:40 time: 0.0396 data: 0.0011 max mem: 33300 +Test: [13200/21770] eta: 0:05:36 time: 0.0399 data: 0.0011 max mem: 33300 +Test: [13300/21770] eta: 0:05:32 time: 0.0396 data: 0.0011 max mem: 33300 +Test: [13400/21770] eta: 0:05:28 time: 0.0396 data: 0.0011 max mem: 33300 +Test: [13500/21770] eta: 0:05:24 time: 0.0401 data: 0.0012 max mem: 33300 +Test: [13600/21770] eta: 0:05:20 time: 0.0390 data: 0.0010 max mem: 33300 +Test: [13700/21770] eta: 0:05:16 time: 0.0395 data: 0.0011 max mem: 33300 +Test: [13800/21770] eta: 0:05:12 time: 0.0392 data: 0.0011 max mem: 33300 +Test: [13900/21770] eta: 0:05:08 time: 0.0396 data: 0.0011 max mem: 33300 +Test: [14000/21770] eta: 0:05:05 time: 0.0396 data: 0.0011 max mem: 33300 +Test: [14100/21770] eta: 0:05:01 time: 0.0401 data: 0.0012 max mem: 33300 +Test: [14200/21770] eta: 0:04:57 time: 0.0395 data: 0.0011 max mem: 33300 +Test: [14300/21770] eta: 0:04:53 time: 0.0402 data: 0.0011 max mem: 33300 +Test: [14400/21770] eta: 0:04:49 time: 0.0391 data: 0.0012 max mem: 33300 +Test: [14500/21770] eta: 0:04:45 time: 0.0396 data: 0.0012 max mem: 33300 +Test: [14600/21770] eta: 0:04:41 time: 0.0390 data: 0.0012 max mem: 33300 +Test: [14700/21770] eta: 0:04:37 time: 0.0401 data: 0.0012 max mem: 33300 +Test: [14800/21770] eta: 0:04:33 time: 0.0395 data: 0.0012 max mem: 33300 +Test: [14900/21770] eta: 0:04:29 time: 0.0395 data: 0.0012 max mem: 33300 +Test: [15000/21770] eta: 0:04:25 time: 0.0394 data: 0.0012 max mem: 33300 +Test: [15100/21770] eta: 0:04:22 time: 0.0391 data: 0.0011 max mem: 33300 +Test: [15200/21770] eta: 0:04:18 time: 0.0392 data: 0.0012 max mem: 33300 +Test: [15300/21770] eta: 0:04:14 time: 0.0391 data: 0.0011 max mem: 33300 +Test: [15400/21770] eta: 0:04:10 time: 0.0388 data: 0.0010 max mem: 33300 +Test: [15500/21770] eta: 0:04:06 time: 0.0393 data: 0.0011 max mem: 33300 +Test: [15600/21770] eta: 0:04:02 time: 0.0397 data: 0.0011 max mem: 33300 +Test: [15700/21770] eta: 0:03:58 time: 0.0392 data: 0.0011 max mem: 33300 +Test: [15800/21770] eta: 0:03:54 time: 0.0393 data: 0.0012 max mem: 33300 +Test: [15900/21770] eta: 0:03:50 time: 0.0399 data: 0.0012 max mem: 33300 +Test: [16000/21770] eta: 0:03:46 time: 0.0395 data: 0.0012 max mem: 33300 +Test: [16100/21770] eta: 0:03:42 time: 0.0397 data: 0.0011 max mem: 33300 +Test: [16200/21770] eta: 0:03:38 time: 0.0388 data: 0.0011 max mem: 33300 +Test: [16300/21770] eta: 0:03:34 time: 0.0388 data: 0.0010 max mem: 33300 +Test: [16400/21770] eta: 0:03:30 time: 0.0386 data: 0.0010 max mem: 33300 +Test: [16500/21770] eta: 0:03:27 time: 0.0393 data: 0.0011 max mem: 33300 +Test: [16600/21770] eta: 0:03:23 time: 0.0388 data: 0.0010 max mem: 33300 +Test: [16700/21770] eta: 0:03:19 time: 0.0389 data: 0.0011 max mem: 33300 +Test: [16800/21770] eta: 0:03:15 time: 0.0392 data: 0.0011 max mem: 33300 +Test: [16900/21770] eta: 0:03:11 time: 0.0389 data: 0.0011 max mem: 33300 +Test: [17000/21770] eta: 0:03:07 time: 0.0389 data: 0.0011 max mem: 33300 +Test: [17100/21770] eta: 0:03:03 time: 0.0388 data: 0.0011 max mem: 33300 +Test: [17200/21770] eta: 0:02:59 time: 0.0391 data: 0.0011 max mem: 33300 +Test: [17300/21770] eta: 0:02:55 time: 0.0391 data: 0.0011 max mem: 33300 +Test: [17400/21770] eta: 0:02:51 time: 0.0389 data: 0.0010 max mem: 33300 +Test: [17500/21770] eta: 0:02:47 time: 0.0393 data: 0.0011 max mem: 33300 +Test: [17600/21770] eta: 0:02:43 time: 0.0391 data: 0.0011 max mem: 33300 +Test: [17700/21770] eta: 0:02:39 time: 0.0393 data: 0.0011 max mem: 33300 +Test: [17800/21770] eta: 0:02:35 time: 0.0392 data: 0.0012 max mem: 33300 +Test: [17900/21770] eta: 0:02:31 time: 0.0391 data: 0.0012 max mem: 33300 +Test: [18000/21770] eta: 0:02:28 time: 0.0390 data: 0.0011 max mem: 33300 +Test: [18100/21770] eta: 0:02:24 time: 0.0388 data: 0.0011 max mem: 33300 +Test: [18200/21770] eta: 0:02:20 time: 0.0390 data: 0.0011 max mem: 33300 +Test: [18300/21770] eta: 0:02:16 time: 0.0390 data: 0.0011 max mem: 33300 +Test: [18400/21770] eta: 0:02:12 time: 0.0382 data: 0.0010 max mem: 33300 +Test: [18500/21770] eta: 0:02:08 time: 0.0389 data: 0.0011 max mem: 33300 +Test: [18600/21770] eta: 0:02:04 time: 0.0388 data: 0.0012 max mem: 33300 +Test: [18700/21770] eta: 0:02:00 time: 0.0389 data: 0.0012 max mem: 33300 +Test: [18800/21770] eta: 0:01:56 time: 0.0392 data: 0.0012 max mem: 33300 +Test: [18900/21770] eta: 0:01:52 time: 0.0387 data: 0.0011 max mem: 33300 +Test: [19000/21770] eta: 0:01:48 time: 0.0388 data: 0.0011 max mem: 33300 +Test: [19100/21770] eta: 0:01:44 time: 0.0389 data: 0.0011 max mem: 33300 +Test: [19200/21770] eta: 0:01:40 time: 0.0384 data: 0.0011 max mem: 33300 +Test: [19300/21770] eta: 0:01:36 time: 0.0389 data: 0.0011 max mem: 33300 +Test: [19400/21770] eta: 0:01:32 time: 0.0387 data: 0.0011 max mem: 33300 +Test: [19500/21770] eta: 0:01:29 time: 0.0385 data: 0.0010 max mem: 33300 +Test: [19600/21770] eta: 0:01:25 time: 0.0394 data: 0.0012 max mem: 33300 +Test: [19700/21770] eta: 0:01:21 time: 0.0389 data: 0.0010 max mem: 33300 +Test: [19800/21770] eta: 0:01:17 time: 0.0390 data: 0.0011 max mem: 33300 +Test: [19900/21770] eta: 0:01:13 time: 0.0391 data: 0.0011 max mem: 33300 +Test: [20000/21770] eta: 0:01:09 time: 0.0389 data: 0.0010 max mem: 33300 +Test: [20100/21770] eta: 0:01:05 time: 0.0391 data: 0.0011 max mem: 33300 +Test: [20200/21770] eta: 0:01:01 time: 0.0391 data: 0.0011 max mem: 33300 +Test: [20300/21770] eta: 0:00:57 time: 0.0394 data: 0.0012 max mem: 33300 +Test: [20400/21770] eta: 0:00:53 time: 0.0393 data: 0.0012 max mem: 33300 +Test: [20500/21770] eta: 0:00:49 time: 0.0395 data: 0.0011 max mem: 33300 +Test: [20600/21770] eta: 0:00:45 time: 0.0391 data: 0.0011 max mem: 33300 +Test: [20700/21770] eta: 0:00:41 time: 0.0393 data: 0.0012 max mem: 33300 +Test: [20800/21770] eta: 0:00:38 time: 0.0395 data: 0.0012 max mem: 33300 +Test: [20900/21770] eta: 0:00:34 time: 0.0390 data: 0.0011 max mem: 33300 +Test: [21000/21770] eta: 0:00:30 time: 0.0395 data: 0.0011 max mem: 33300 +Test: [21100/21770] eta: 0:00:26 time: 0.0392 data: 0.0011 max mem: 33300 +Test: [21200/21770] eta: 0:00:22 time: 0.0395 data: 0.0011 max mem: 33300 +Test: [21300/21770] eta: 0:00:18 time: 0.0393 data: 0.0011 max mem: 33300 +Test: [21400/21770] eta: 0:00:14 time: 0.0396 data: 0.0011 max mem: 33300 +Test: [21500/21770] eta: 0:00:10 time: 0.0394 data: 0.0010 max mem: 33300 +Test: [21600/21770] eta: 0:00:06 time: 0.0400 data: 0.0010 max mem: 33300 +Test: [21700/21770] eta: 0:00:02 time: 0.0394 data: 0.0011 max mem: 33300 +Test: Total time: 0:14:14 +Final results: +Mean IoU is 0.28 + + precision@0.5 = 0.00 + precision@0.6 = 0.00 + precision@0.7 = 0.00 + precision@0.8 = 0.00 + precision@0.9 = 0.00 + overall IoU = 0.27 + mean IoU = 0.28 + +Mean accuracy for one-to-zero sample is 0.00 + +Average object IoU 0.002750891716068778 +Overall IoU 0.2721877694129944 +Better epoch: 11 + +Epoch: [12] [ 0/4276] eta: 7:14:35 lr: 3.6270619697048556e-05 loss: 0.1167 (0.1167) time: 6.0981 data: 2.8400 max mem: 33300 +Epoch: [12] [ 10/4276] eta: 4:00:56 lr: 3.626789318639879e-05 loss: 0.1789 (0.1635) time: 3.3887 data: 0.2635 max mem: 33300 +Epoch: [12] [ 20/4276] eta: 3:50:11 lr: 3.626516665297429e-05 loss: 0.1627 (0.1620) time: 3.1025 data: 0.0060 max mem: 33300 +Epoch: [12] [ 30/4276] eta: 3:46:06 lr: 3.626244009677297e-05 loss: 0.1597 (0.1617) time: 3.0887 data: 0.0070 max mem: 33300 +Epoch: [12] [ 40/4276] eta: 3:43:46 lr: 3.625971351779274e-05 loss: 0.1582 (0.1603) time: 3.0902 data: 0.0076 max mem: 33300 +Epoch: [12] [ 50/4276] eta: 3:41:56 lr: 3.62569869160315e-05 loss: 0.1550 (0.1573) time: 3.0825 data: 0.0073 max mem: 33300 +Epoch: [12] [ 60/4276] eta: 3:40:20 lr: 3.625426029148717e-05 loss: 0.1532 (0.1571) time: 3.0663 data: 0.0073 max mem: 33300 +Epoch: [12] [ 70/4276] eta: 3:39:07 lr: 3.625153364415764e-05 loss: 0.1532 (0.1558) time: 3.0623 data: 0.0074 max mem: 33300 +Epoch: [12] [ 80/4276] eta: 3:38:20 lr: 3.6248806974040815e-05 loss: 0.1509 (0.1558) time: 3.0808 data: 0.0074 max mem: 33300 +Epoch: [12] [ 90/4276] eta: 3:37:24 lr: 3.624608028113461e-05 loss: 0.1427 (0.1538) time: 3.0812 data: 0.0070 max mem: 33300 +Epoch: [12] [ 100/4276] eta: 3:36:40 lr: 3.624335356543692e-05 loss: 0.1443 (0.1552) time: 3.0762 data: 0.0071 max mem: 33300 +Epoch: [12] [ 110/4276] eta: 3:36:01 lr: 3.6240626826945653e-05 loss: 0.1634 (0.1561) time: 3.0885 data: 0.0072 max mem: 33300 +Epoch: [12] [ 120/4276] eta: 3:35:14 lr: 3.623790006565872e-05 loss: 0.1442 (0.1553) time: 3.0794 data: 0.0069 max mem: 33300 +Epoch: [12] [ 130/4276] eta: 3:34:27 lr: 3.623517328157402e-05 loss: 0.1453 (0.1549) time: 3.0612 data: 0.0069 max mem: 33300 +Epoch: [12] [ 140/4276] eta: 3:33:50 lr: 3.623244647468945e-05 loss: 0.1399 (0.1539) time: 3.0697 data: 0.0071 max mem: 33300 +Epoch: [12] [ 150/4276] eta: 3:33:09 lr: 3.6229719645002926e-05 loss: 0.1360 (0.1536) time: 3.0751 data: 0.0071 max mem: 33300 +Epoch: [12] [ 160/4276] eta: 3:32:33 lr: 3.622699279251234e-05 loss: 0.1404 (0.1534) time: 3.0732 data: 0.0070 max mem: 33300 +Epoch: [12] [ 170/4276] eta: 3:31:57 lr: 3.6224265917215586e-05 loss: 0.1422 (0.1527) time: 3.0786 data: 0.0070 max mem: 33300 +Epoch: [12] [ 180/4276] eta: 3:31:19 lr: 3.622153901911058e-05 loss: 0.1494 (0.1530) time: 3.0722 data: 0.0070 max mem: 33300 +Epoch: [12] [ 190/4276] eta: 3:30:40 lr: 3.6218812098195214e-05 loss: 0.1494 (0.1531) time: 3.0625 data: 0.0071 max mem: 33300 +Epoch: [12] [ 200/4276] eta: 3:30:00 lr: 3.62160851544674e-05 loss: 0.1445 (0.1542) time: 3.0531 data: 0.0072 max mem: 33300 +Epoch: [12] [ 210/4276] eta: 3:29:31 lr: 3.621335818792503e-05 loss: 0.1477 (0.1547) time: 3.0753 data: 0.0076 max mem: 33300 +Epoch: [12] [ 220/4276] eta: 3:28:56 lr: 3.621063119856602e-05 loss: 0.1537 (0.1549) time: 3.0849 data: 0.0081 max mem: 33300 +Epoch: [12] [ 230/4276] eta: 3:28:29 lr: 3.620790418638824e-05 loss: 0.1480 (0.1543) time: 3.0899 data: 0.0077 max mem: 33300 +Epoch: [12] [ 240/4276] eta: 3:27:57 lr: 3.6205177151389617e-05 loss: 0.1448 (0.1543) time: 3.0986 data: 0.0072 max mem: 33300 +Epoch: [12] [ 250/4276] eta: 3:27:22 lr: 3.620245009356803e-05 loss: 0.1595 (0.1552) time: 3.0775 data: 0.0072 max mem: 33300 +Epoch: [12] [ 260/4276] eta: 3:26:47 lr: 3.619972301292139e-05 loss: 0.1623 (0.1552) time: 3.0655 data: 0.0076 max mem: 33300 +Epoch: [12] [ 270/4276] eta: 3:26:14 lr: 3.619699590944759e-05 loss: 0.1420 (0.1552) time: 3.0694 data: 0.0077 max mem: 33300 +Epoch: [12] [ 280/4276] eta: 3:25:44 lr: 3.619426878314453e-05 loss: 0.1420 (0.1549) time: 3.0870 data: 0.0076 max mem: 33300 +Epoch: [12] [ 290/4276] eta: 3:25:09 lr: 3.61915416340101e-05 loss: 0.1432 (0.1544) time: 3.0757 data: 0.0075 max mem: 33300 +Epoch: [12] [ 300/4276] eta: 3:24:40 lr: 3.618881446204223e-05 loss: 0.1423 (0.1542) time: 3.0798 data: 0.0076 max mem: 33300 +Epoch: [12] [ 310/4276] eta: 3:24:10 lr: 3.618608726723877e-05 loss: 0.1386 (0.1539) time: 3.1000 data: 0.0075 max mem: 33300 +Epoch: [12] [ 320/4276] eta: 3:23:35 lr: 3.6183360049597656e-05 loss: 0.1409 (0.1541) time: 3.0767 data: 0.0071 max mem: 33300 +Epoch: [12] [ 330/4276] eta: 3:23:02 lr: 3.6180632809116755e-05 loss: 0.1516 (0.1543) time: 3.0630 data: 0.0071 max mem: 33300 +Epoch: [12] [ 340/4276] eta: 3:22:33 lr: 3.617790554579397e-05 loss: 0.1464 (0.1538) time: 3.0859 data: 0.0077 max mem: 33300 +Epoch: [12] [ 350/4276] eta: 3:22:01 lr: 3.6175178259627205e-05 loss: 0.1311 (0.1537) time: 3.0887 data: 0.0076 max mem: 33300 +Epoch: [12] [ 360/4276] eta: 3:21:28 lr: 3.617245095061435e-05 loss: 0.1711 (0.1546) time: 3.0719 data: 0.0072 max mem: 33300 +Epoch: [12] [ 370/4276] eta: 3:21:00 lr: 3.616972361875331e-05 loss: 0.1637 (0.1542) time: 3.0933 data: 0.0075 max mem: 33300 +Epoch: [12] [ 380/4276] eta: 3:20:30 lr: 3.6166996264041966e-05 loss: 0.1304 (0.1541) time: 3.1038 data: 0.0073 max mem: 33300 +Epoch: [12] [ 390/4276] eta: 3:19:58 lr: 3.616426888647821e-05 loss: 0.1338 (0.1541) time: 3.0874 data: 0.0070 max mem: 33300 +Epoch: [12] [ 400/4276] eta: 3:19:28 lr: 3.616154148605994e-05 loss: 0.1448 (0.1539) time: 3.0902 data: 0.0072 max mem: 33300 +Epoch: [12] [ 410/4276] eta: 3:18:59 lr: 3.615881406278506e-05 loss: 0.1448 (0.1535) time: 3.0987 data: 0.0073 max mem: 33300 +Epoch: [12] [ 420/4276] eta: 3:18:24 lr: 3.6156086616651444e-05 loss: 0.1467 (0.1535) time: 3.0738 data: 0.0076 max mem: 33300 +Epoch: [12] [ 430/4276] eta: 3:17:55 lr: 3.615335914765699e-05 loss: 0.1595 (0.1536) time: 3.0750 data: 0.0075 max mem: 33300 +Epoch: [12] [ 440/4276] eta: 3:17:25 lr: 3.61506316557996e-05 loss: 0.1514 (0.1536) time: 3.1037 data: 0.0074 max mem: 33300 +Epoch: [12] [ 450/4276] eta: 3:16:52 lr: 3.6147904141077163e-05 loss: 0.1548 (0.1536) time: 3.0839 data: 0.0075 max mem: 33300 +Epoch: [12] [ 460/4276] eta: 3:16:21 lr: 3.6145176603487565e-05 loss: 0.1406 (0.1533) time: 3.0743 data: 0.0074 max mem: 33300 +Epoch: [12] [ 470/4276] eta: 3:15:52 lr: 3.61424490430287e-05 loss: 0.1279 (0.1529) time: 3.1004 data: 0.0075 max mem: 33300 +Epoch: [12] [ 480/4276] eta: 3:15:22 lr: 3.613972145969845e-05 loss: 0.1276 (0.1527) time: 3.1064 data: 0.0076 max mem: 33300 +Epoch: [12] [ 490/4276] eta: 3:14:51 lr: 3.6136993853494715e-05 loss: 0.1258 (0.1522) time: 3.0870 data: 0.0074 max mem: 33300 +Epoch: [12] [ 500/4276] eta: 3:14:23 lr: 3.613426622441539e-05 loss: 0.1266 (0.1519) time: 3.1031 data: 0.0073 max mem: 33300 +Epoch: [12] [ 510/4276] eta: 3:13:53 lr: 3.613153857245834e-05 loss: 0.1322 (0.1517) time: 3.1144 data: 0.0074 max mem: 33300 +Epoch: [12] [ 520/4276] eta: 3:13:20 lr: 3.612881089762148e-05 loss: 0.1345 (0.1516) time: 3.0853 data: 0.0073 max mem: 33300 +Epoch: [12] [ 530/4276] eta: 3:12:50 lr: 3.61260831999027e-05 loss: 0.1345 (0.1515) time: 3.0843 data: 0.0073 max mem: 33300 +Epoch: [12] [ 540/4276] eta: 3:12:19 lr: 3.6123355479299865e-05 loss: 0.1411 (0.1512) time: 3.0906 data: 0.0072 max mem: 33300 +Epoch: [12] [ 550/4276] eta: 3:11:46 lr: 3.612062773581089e-05 loss: 0.1391 (0.1512) time: 3.0737 data: 0.0072 max mem: 33300 +Epoch: [12] [ 560/4276] eta: 3:11:16 lr: 3.611789996943363e-05 loss: 0.1485 (0.1513) time: 3.0785 data: 0.0073 max mem: 33300 +Epoch: [12] [ 570/4276] eta: 3:10:48 lr: 3.6115172180165994e-05 loss: 0.1552 (0.1514) time: 3.1141 data: 0.0073 max mem: 33300 +Epoch: [12] [ 580/4276] eta: 3:10:17 lr: 3.611244436800587e-05 loss: 0.1567 (0.1515) time: 3.1141 data: 0.0072 max mem: 33300 +Epoch: [12] [ 590/4276] eta: 3:09:44 lr: 3.6109716532951146e-05 loss: 0.1333 (0.1511) time: 3.0743 data: 0.0074 max mem: 33300 +Epoch: [12] [ 600/4276] eta: 3:09:15 lr: 3.6106988674999694e-05 loss: 0.1355 (0.1511) time: 3.0830 data: 0.0076 max mem: 33300 +Epoch: [12] [ 610/4276] eta: 3:08:45 lr: 3.610426079414941e-05 loss: 0.1508 (0.1510) time: 3.1100 data: 0.0074 max mem: 33300 +Epoch: [12] [ 620/4276] eta: 3:08:14 lr: 3.610153289039818e-05 loss: 0.1404 (0.1510) time: 3.1007 data: 0.0073 max mem: 33300 +Epoch: [12] [ 630/4276] eta: 3:07:43 lr: 3.609880496374389e-05 loss: 0.1500 (0.1512) time: 3.0840 data: 0.0078 max mem: 33300 +Epoch: [12] [ 640/4276] eta: 3:07:12 lr: 3.609607701418441e-05 loss: 0.1533 (0.1511) time: 3.0841 data: 0.0080 max mem: 33300 +Epoch: [12] [ 650/4276] eta: 3:06:40 lr: 3.609334904171764e-05 loss: 0.1518 (0.1512) time: 3.0793 data: 0.0074 max mem: 33300 +Epoch: [12] [ 660/4276] eta: 3:06:09 lr: 3.609062104634146e-05 loss: 0.1501 (0.1513) time: 3.0807 data: 0.0072 max mem: 33300 +Epoch: [12] [ 670/4276] eta: 3:05:38 lr: 3.608789302805375e-05 loss: 0.1460 (0.1513) time: 3.0919 data: 0.0078 max mem: 33300 +Epoch: [12] [ 680/4276] eta: 3:05:06 lr: 3.6085164986852404e-05 loss: 0.1353 (0.1511) time: 3.0770 data: 0.0082 max mem: 33300 +Epoch: [12] [ 690/4276] eta: 3:04:33 lr: 3.608243692273529e-05 loss: 0.1380 (0.1511) time: 3.0580 data: 0.0079 max mem: 33300 +Epoch: [12] [ 700/4276] eta: 3:04:04 lr: 3.60797088357003e-05 loss: 0.1469 (0.1510) time: 3.0857 data: 0.0080 max mem: 33300 +Epoch: [12] [ 710/4276] eta: 3:03:33 lr: 3.607698072574531e-05 loss: 0.1452 (0.1510) time: 3.0999 data: 0.0084 max mem: 33300 +Epoch: [12] [ 720/4276] eta: 3:03:02 lr: 3.60742525928682e-05 loss: 0.1349 (0.1508) time: 3.0805 data: 0.0085 max mem: 33300 +Epoch: [12] [ 730/4276] eta: 3:02:31 lr: 3.607152443706686e-05 loss: 0.1253 (0.1508) time: 3.0868 data: 0.0082 max mem: 33300 +Epoch: [12] [ 740/4276] eta: 3:01:59 lr: 3.6068796258339165e-05 loss: 0.1316 (0.1507) time: 3.0831 data: 0.0083 max mem: 33300 +Epoch: [12] [ 750/4276] eta: 3:01:25 lr: 3.6066068056683e-05 loss: 0.1386 (0.1508) time: 3.0471 data: 0.0081 max mem: 33300 +Epoch: [12] [ 760/4276] eta: 3:00:54 lr: 3.6063339832096244e-05 loss: 0.1368 (0.1507) time: 3.0488 data: 0.0081 max mem: 33300 +Epoch: [12] [ 770/4276] eta: 3:00:25 lr: 3.606061158457677e-05 loss: 0.1358 (0.1508) time: 3.0997 data: 0.0080 max mem: 33300 +Epoch: [12] [ 780/4276] eta: 2:59:53 lr: 3.605788331412247e-05 loss: 0.1502 (0.1508) time: 3.0970 data: 0.0077 max mem: 33300 +Epoch: [12] [ 790/4276] eta: 2:59:21 lr: 3.605515502073121e-05 loss: 0.1495 (0.1507) time: 3.0662 data: 0.0077 max mem: 33300 +Epoch: [12] [ 800/4276] eta: 2:58:51 lr: 3.605242670440088e-05 loss: 0.1426 (0.1508) time: 3.0827 data: 0.0079 max mem: 33300 +Epoch: [12] [ 810/4276] eta: 2:58:20 lr: 3.604969836512934e-05 loss: 0.1461 (0.1509) time: 3.0907 data: 0.0078 max mem: 33300 +Epoch: [12] [ 820/4276] eta: 2:57:48 lr: 3.6046970002914485e-05 loss: 0.1407 (0.1507) time: 3.0710 data: 0.0080 max mem: 33300 +Epoch: [12] [ 830/4276] eta: 2:57:17 lr: 3.6044241617754195e-05 loss: 0.1402 (0.1508) time: 3.0756 data: 0.0080 max mem: 33300 +Epoch: [12] [ 840/4276] eta: 2:56:46 lr: 3.604151320964633e-05 loss: 0.1436 (0.1509) time: 3.0906 data: 0.0075 max mem: 33300 +Epoch: [12] [ 850/4276] eta: 2:56:16 lr: 3.603878477858878e-05 loss: 0.1431 (0.1508) time: 3.0966 data: 0.0076 max mem: 33300 +Epoch: [12] [ 860/4276] eta: 2:55:45 lr: 3.603605632457943e-05 loss: 0.1447 (0.1507) time: 3.0936 data: 0.0077 max mem: 33300 +Epoch: [12] [ 870/4276] eta: 2:55:14 lr: 3.603332784761613e-05 loss: 0.1447 (0.1509) time: 3.0846 data: 0.0078 max mem: 33300 +Epoch: [12] [ 880/4276] eta: 2:54:43 lr: 3.6030599347696777e-05 loss: 0.1459 (0.1510) time: 3.0779 data: 0.0082 max mem: 33300 +Epoch: [12] [ 890/4276] eta: 2:54:12 lr: 3.602787082481923e-05 loss: 0.1514 (0.1510) time: 3.0865 data: 0.0079 max mem: 33300 +Epoch: [12] [ 900/4276] eta: 2:53:42 lr: 3.6025142278981384e-05 loss: 0.1500 (0.1509) time: 3.0979 data: 0.0076 max mem: 33300 +Epoch: [12] [ 910/4276] eta: 2:53:12 lr: 3.60224137101811e-05 loss: 0.1521 (0.1511) time: 3.1050 data: 0.0082 max mem: 33300 +Epoch: [12] [ 920/4276] eta: 2:52:42 lr: 3.601968511841625e-05 loss: 0.1607 (0.1513) time: 3.1087 data: 0.0087 max mem: 33300 +Epoch: [12] [ 930/4276] eta: 2:52:10 lr: 3.601695650368472e-05 loss: 0.1607 (0.1513) time: 3.0882 data: 0.0085 max mem: 33300 +Epoch: [12] [ 940/4276] eta: 2:51:40 lr: 3.6014227865984366e-05 loss: 0.1521 (0.1512) time: 3.0894 data: 0.0080 max mem: 33300 +Epoch: [12] [ 950/4276] eta: 2:51:08 lr: 3.601149920531308e-05 loss: 0.1427 (0.1513) time: 3.0862 data: 0.0079 max mem: 33300 +Epoch: [12] [ 960/4276] eta: 2:50:37 lr: 3.600877052166872e-05 loss: 0.1503 (0.1514) time: 3.0632 data: 0.0080 max mem: 33300 +Epoch: [12] [ 970/4276] eta: 2:50:07 lr: 3.6006041815049165e-05 loss: 0.1540 (0.1514) time: 3.0889 data: 0.0078 max mem: 33300 +Epoch: [12] [ 980/4276] eta: 2:49:36 lr: 3.600331308545228e-05 loss: 0.1555 (0.1516) time: 3.1039 data: 0.0076 max mem: 33300 +Epoch: [12] [ 990/4276] eta: 2:49:04 lr: 3.600058433287595e-05 loss: 0.1574 (0.1516) time: 3.0776 data: 0.0073 max mem: 33300 +Epoch: [12] [1000/4276] eta: 2:48:33 lr: 3.599785555731804e-05 loss: 0.1417 (0.1515) time: 3.0668 data: 0.0072 max mem: 33300 +Epoch: [12] [1010/4276] eta: 2:48:02 lr: 3.599512675877641e-05 loss: 0.1367 (0.1516) time: 3.0746 data: 0.0072 max mem: 33300 +Epoch: [12] [1020/4276] eta: 2:47:29 lr: 3.599239793724895e-05 loss: 0.1372 (0.1515) time: 3.0566 data: 0.0076 max mem: 33300 +Epoch: [12] [1030/4276] eta: 2:46:58 lr: 3.5989669092733506e-05 loss: 0.1425 (0.1516) time: 3.0624 data: 0.0082 max mem: 33300 +Epoch: [12] [1040/4276] eta: 2:46:28 lr: 3.5986940225227974e-05 loss: 0.1558 (0.1516) time: 3.1045 data: 0.0084 max mem: 33300 +Epoch: [12] [1050/4276] eta: 2:45:57 lr: 3.59842113347302e-05 loss: 0.1465 (0.1517) time: 3.0925 data: 0.0081 max mem: 33300 +Epoch: [12] [1060/4276] eta: 2:45:26 lr: 3.598148242123807e-05 loss: 0.1465 (0.1517) time: 3.0682 data: 0.0075 max mem: 33300 +Epoch: [12] [1070/4276] eta: 2:44:55 lr: 3.597875348474945e-05 loss: 0.1592 (0.1519) time: 3.0864 data: 0.0073 max mem: 33300 +Epoch: [12] [1080/4276] eta: 2:44:24 lr: 3.5976024525262195e-05 loss: 0.1587 (0.1518) time: 3.0853 data: 0.0072 max mem: 33300 +Epoch: [12] [1090/4276] eta: 2:43:52 lr: 3.597329554277419e-05 loss: 0.1504 (0.1519) time: 3.0680 data: 0.0072 max mem: 33300 +Epoch: [12] [1100/4276] eta: 2:43:21 lr: 3.597056653728328e-05 loss: 0.1437 (0.1518) time: 3.0704 data: 0.0076 max mem: 33300 +Epoch: [12] [1110/4276] eta: 2:42:50 lr: 3.5967837508787354e-05 loss: 0.1437 (0.1519) time: 3.0781 data: 0.0081 max mem: 33300 +Epoch: [12] [1120/4276] eta: 2:42:19 lr: 3.596510845728427e-05 loss: 0.1563 (0.1520) time: 3.0857 data: 0.0082 max mem: 33300 +Epoch: [12] [1130/4276] eta: 2:41:49 lr: 3.5962379382771894e-05 loss: 0.1478 (0.1519) time: 3.0916 data: 0.0079 max mem: 33300 +Epoch: [12] [1140/4276] eta: 2:41:18 lr: 3.595965028524809e-05 loss: 0.1375 (0.1518) time: 3.0846 data: 0.0078 max mem: 33300 +Epoch: [12] [1150/4276] eta: 2:40:46 lr: 3.595692116471073e-05 loss: 0.1395 (0.1517) time: 3.0703 data: 0.0082 max mem: 33300 +Epoch: [12] [1160/4276] eta: 2:40:16 lr: 3.595419202115768e-05 loss: 0.1448 (0.1518) time: 3.0806 data: 0.0079 max mem: 33300 +Epoch: [12] [1170/4276] eta: 2:39:45 lr: 3.59514628545868e-05 loss: 0.1589 (0.1519) time: 3.1039 data: 0.0075 max mem: 33300 +Epoch: [12] [1180/4276] eta: 2:39:15 lr: 3.5948733664995945e-05 loss: 0.1488 (0.1519) time: 3.1003 data: 0.0078 max mem: 33300 +Epoch: [12] [1190/4276] eta: 2:38:43 lr: 3.594600445238299e-05 loss: 0.1396 (0.1517) time: 3.0773 data: 0.0078 max mem: 33300 +Epoch: [12] [1200/4276] eta: 2:38:12 lr: 3.59432752167458e-05 loss: 0.1327 (0.1517) time: 3.0686 data: 0.0082 max mem: 33300 +Epoch: [12] [1210/4276] eta: 2:37:41 lr: 3.5940545958082235e-05 loss: 0.1327 (0.1516) time: 3.0685 data: 0.0087 max mem: 33300 +Epoch: [12] [1220/4276] eta: 2:37:10 lr: 3.5937816676390154e-05 loss: 0.1388 (0.1516) time: 3.0887 data: 0.0081 max mem: 33300 +Epoch: [12] [1230/4276] eta: 2:36:39 lr: 3.5935087371667424e-05 loss: 0.1428 (0.1517) time: 3.0870 data: 0.0080 max mem: 33300 +Epoch: [12] [1240/4276] eta: 2:36:08 lr: 3.593235804391191e-05 loss: 0.1546 (0.1518) time: 3.0785 data: 0.0083 max mem: 33300 +Epoch: [12] [1250/4276] eta: 2:35:37 lr: 3.592962869312147e-05 loss: 0.1456 (0.1518) time: 3.0876 data: 0.0079 max mem: 33300 +Epoch: [12] [1260/4276] eta: 2:35:06 lr: 3.592689931929397e-05 loss: 0.1318 (0.1516) time: 3.0762 data: 0.0079 max mem: 33300 +Epoch: [12] [1270/4276] eta: 2:34:34 lr: 3.5924169922427254e-05 loss: 0.1327 (0.1515) time: 3.0417 data: 0.0084 max mem: 33300 +Epoch: [12] [1280/4276] eta: 2:34:02 lr: 3.59214405025192e-05 loss: 0.1409 (0.1515) time: 3.0297 data: 0.0087 max mem: 33300 +Epoch: [12] [1290/4276] eta: 2:33:31 lr: 3.591871105956766e-05 loss: 0.1474 (0.1516) time: 3.0639 data: 0.0086 max mem: 33300 +Epoch: [12] [1300/4276] eta: 2:33:00 lr: 3.59159815935705e-05 loss: 0.1329 (0.1515) time: 3.0889 data: 0.0081 max mem: 33300 +Epoch: [12] [1310/4276] eta: 2:32:30 lr: 3.591325210452558e-05 loss: 0.1296 (0.1516) time: 3.1079 data: 0.0084 max mem: 33300 +Epoch: [12] [1320/4276] eta: 2:31:59 lr: 3.5910522592430755e-05 loss: 0.1462 (0.1517) time: 3.1012 data: 0.0082 max mem: 33300 +Epoch: [12] [1330/4276] eta: 2:31:28 lr: 3.590779305728388e-05 loss: 0.1489 (0.1516) time: 3.0731 data: 0.0078 max mem: 33300 +Epoch: [12] [1340/4276] eta: 2:30:57 lr: 3.590506349908281e-05 loss: 0.1411 (0.1516) time: 3.0724 data: 0.0080 max mem: 33300 +Epoch: [12] [1350/4276] eta: 2:30:26 lr: 3.590233391782542e-05 loss: 0.1476 (0.1516) time: 3.0889 data: 0.0080 max mem: 33300 +Epoch: [12] [1360/4276] eta: 2:29:55 lr: 3.5899604313509556e-05 loss: 0.1551 (0.1516) time: 3.0836 data: 0.0079 max mem: 33300 +Epoch: [12] [1370/4276] eta: 2:29:24 lr: 3.5896874686133077e-05 loss: 0.1478 (0.1516) time: 3.0721 data: 0.0077 max mem: 33300 +Epoch: [12] [1380/4276] eta: 2:28:54 lr: 3.589414503569384e-05 loss: 0.1495 (0.1517) time: 3.0902 data: 0.0078 max mem: 33300 +Epoch: [12] [1390/4276] eta: 2:28:24 lr: 3.5891415362189704e-05 loss: 0.1618 (0.1518) time: 3.1183 data: 0.0082 max mem: 33300 +Epoch: [12] [1400/4276] eta: 2:27:53 lr: 3.5888685665618514e-05 loss: 0.1578 (0.1517) time: 3.1099 data: 0.0084 max mem: 33300 +Epoch: [12] [1410/4276] eta: 2:27:22 lr: 3.588595594597814e-05 loss: 0.1509 (0.1517) time: 3.0922 data: 0.0084 max mem: 33300 +Epoch: [12] [1420/4276] eta: 2:26:51 lr: 3.588322620326643e-05 loss: 0.1411 (0.1517) time: 3.0845 data: 0.0085 max mem: 33300 +Epoch: [12] [1430/4276] eta: 2:26:20 lr: 3.5880496437481234e-05 loss: 0.1403 (0.1517) time: 3.0722 data: 0.0087 max mem: 33300 +Epoch: [12] [1440/4276] eta: 2:25:50 lr: 3.587776664862041e-05 loss: 0.1437 (0.1517) time: 3.0937 data: 0.0088 max mem: 33300 +Epoch: [12] [1450/4276] eta: 2:25:19 lr: 3.587503683668182e-05 loss: 0.1502 (0.1517) time: 3.0961 data: 0.0085 max mem: 33300 +Epoch: [12] [1460/4276] eta: 2:24:48 lr: 3.587230700166331e-05 loss: 0.1395 (0.1516) time: 3.0896 data: 0.0084 max mem: 33300 +Epoch: [12] [1470/4276] eta: 2:24:17 lr: 3.586957714356274e-05 loss: 0.1347 (0.1515) time: 3.0886 data: 0.0085 max mem: 33300 +Epoch: [12] [1480/4276] eta: 2:23:47 lr: 3.586684726237796e-05 loss: 0.1333 (0.1514) time: 3.0966 data: 0.0082 max mem: 33300 +Epoch: [12] [1490/4276] eta: 2:23:16 lr: 3.586411735810681e-05 loss: 0.1239 (0.1513) time: 3.1033 data: 0.0078 max mem: 33300 +Epoch: [12] [1500/4276] eta: 2:22:46 lr: 3.586138743074715e-05 loss: 0.1422 (0.1513) time: 3.0943 data: 0.0080 max mem: 33300 +Epoch: [12] [1510/4276] eta: 2:22:15 lr: 3.5858657480296845e-05 loss: 0.1461 (0.1513) time: 3.0840 data: 0.0080 max mem: 33300 +Epoch: [12] [1520/4276] eta: 2:21:44 lr: 3.5855927506753734e-05 loss: 0.1434 (0.1512) time: 3.0731 data: 0.0085 max mem: 33300 +Epoch: [12] [1530/4276] eta: 2:21:12 lr: 3.585319751011567e-05 loss: 0.1434 (0.1511) time: 3.0713 data: 0.0089 max mem: 33300 +Epoch: [12] [1540/4276] eta: 2:20:42 lr: 3.5850467490380504e-05 loss: 0.1433 (0.1511) time: 3.0890 data: 0.0086 max mem: 33300 +Epoch: [12] [1550/4276] eta: 2:20:11 lr: 3.584773744754609e-05 loss: 0.1478 (0.1512) time: 3.0999 data: 0.0087 max mem: 33300 +Epoch: [12] [1560/4276] eta: 2:19:41 lr: 3.584500738161027e-05 loss: 0.1451 (0.1511) time: 3.0928 data: 0.0086 max mem: 33300 +Epoch: [12] [1570/4276] eta: 2:19:10 lr: 3.584227729257089e-05 loss: 0.1463 (0.1512) time: 3.1043 data: 0.0081 max mem: 33300 +Epoch: [12] [1580/4276] eta: 2:18:40 lr: 3.5839547180425814e-05 loss: 0.1471 (0.1511) time: 3.1166 data: 0.0080 max mem: 33300 +Epoch: [12] [1590/4276] eta: 2:18:10 lr: 3.5836817045172886e-05 loss: 0.1482 (0.1511) time: 3.1350 data: 0.0084 max mem: 33300 +Epoch: [12] [1600/4276] eta: 2:17:39 lr: 3.5834086886809945e-05 loss: 0.1524 (0.1511) time: 3.1192 data: 0.0083 max mem: 33300 +Epoch: [12] [1610/4276] eta: 2:17:08 lr: 3.583135670533485e-05 loss: 0.1384 (0.1510) time: 3.0837 data: 0.0086 max mem: 33300 +Epoch: [12] [1620/4276] eta: 2:16:37 lr: 3.5828626500745444e-05 loss: 0.1373 (0.1509) time: 3.0679 data: 0.0091 max mem: 33300 +Epoch: [12] [1630/4276] eta: 2:16:07 lr: 3.582589627303958e-05 loss: 0.1373 (0.1509) time: 3.0895 data: 0.0091 max mem: 33300 +Epoch: [12] [1640/4276] eta: 2:15:36 lr: 3.582316602221509e-05 loss: 0.1372 (0.1508) time: 3.1060 data: 0.0088 max mem: 33300 +Epoch: [12] [1650/4276] eta: 2:15:05 lr: 3.582043574826983e-05 loss: 0.1357 (0.1507) time: 3.0955 data: 0.0088 max mem: 33300 +Epoch: [12] [1660/4276] eta: 2:14:35 lr: 3.581770545120165e-05 loss: 0.1357 (0.1507) time: 3.1124 data: 0.0089 max mem: 33300 +Epoch: [12] [1670/4276] eta: 2:14:04 lr: 3.581497513100839e-05 loss: 0.1442 (0.1507) time: 3.1219 data: 0.0087 max mem: 33300 +Epoch: [12] [1680/4276] eta: 2:13:34 lr: 3.58122447876879e-05 loss: 0.1537 (0.1508) time: 3.1158 data: 0.0086 max mem: 33300 +Epoch: [12] [1690/4276] eta: 2:13:03 lr: 3.5809514421238024e-05 loss: 0.1486 (0.1507) time: 3.1072 data: 0.0086 max mem: 33300 +Epoch: [12] [1700/4276] eta: 2:12:33 lr: 3.5806784031656596e-05 loss: 0.1445 (0.1508) time: 3.0954 data: 0.0084 max mem: 33300 +Epoch: [12] [1710/4276] eta: 2:12:02 lr: 3.580405361894147e-05 loss: 0.1668 (0.1509) time: 3.0976 data: 0.0089 max mem: 33300 +Epoch: [12] [1720/4276] eta: 2:11:32 lr: 3.58013231830905e-05 loss: 0.1668 (0.1510) time: 3.1184 data: 0.0091 max mem: 33300 +Epoch: [12] [1730/4276] eta: 2:11:01 lr: 3.57985927241015e-05 loss: 0.1648 (0.1510) time: 3.1235 data: 0.0082 max mem: 33300 +Epoch: [12] [1740/4276] eta: 2:10:30 lr: 3.579586224197234e-05 loss: 0.1536 (0.1511) time: 3.1035 data: 0.0080 max mem: 33300 +Epoch: [12] [1750/4276] eta: 2:09:59 lr: 3.5793131736700854e-05 loss: 0.1500 (0.1510) time: 3.0891 data: 0.0084 max mem: 33300 +Epoch: [12] [1760/4276] eta: 2:09:29 lr: 3.579040120828488e-05 loss: 0.1288 (0.1509) time: 3.0979 data: 0.0085 max mem: 33300 +Epoch: [12] [1770/4276] eta: 2:08:58 lr: 3.578767065672226e-05 loss: 0.1357 (0.1509) time: 3.1002 data: 0.0079 max mem: 33300 +Epoch: [12] [1780/4276] eta: 2:08:27 lr: 3.578494008201085e-05 loss: 0.1464 (0.1509) time: 3.0923 data: 0.0078 max mem: 33300 +Epoch: [12] [1790/4276] eta: 2:07:57 lr: 3.578220948414848e-05 loss: 0.1430 (0.1508) time: 3.1045 data: 0.0080 max mem: 33300 +Epoch: [12] [1800/4276] eta: 2:07:26 lr: 3.577947886313298e-05 loss: 0.1387 (0.1509) time: 3.1000 data: 0.0080 max mem: 33300 +Epoch: [12] [1810/4276] eta: 2:06:55 lr: 3.57767482189622e-05 loss: 0.1661 (0.1510) time: 3.1072 data: 0.0078 max mem: 33300 +Epoch: [12] [1820/4276] eta: 2:06:25 lr: 3.577401755163399e-05 loss: 0.1563 (0.1509) time: 3.1102 data: 0.0083 max mem: 33300 +Epoch: [12] [1830/4276] eta: 2:05:54 lr: 3.577128686114617e-05 loss: 0.1481 (0.1509) time: 3.0922 data: 0.0088 max mem: 33300 +Epoch: [12] [1840/4276] eta: 2:05:23 lr: 3.576855614749659e-05 loss: 0.1481 (0.1508) time: 3.0935 data: 0.0082 max mem: 33300 +Epoch: [12] [1850/4276] eta: 2:04:52 lr: 3.576582541068311e-05 loss: 0.1510 (0.1509) time: 3.1028 data: 0.0078 max mem: 33300 +Epoch: [12] [1860/4276] eta: 2:04:22 lr: 3.5763094650703524e-05 loss: 0.1479 (0.1509) time: 3.1265 data: 0.0079 max mem: 33300 +Epoch: [12] [1870/4276] eta: 2:03:51 lr: 3.5760363867555705e-05 loss: 0.1466 (0.1510) time: 3.1140 data: 0.0086 max mem: 33300 +Epoch: [12] [1880/4276] eta: 2:03:20 lr: 3.5757633061237475e-05 loss: 0.1561 (0.1510) time: 3.0879 data: 0.0091 max mem: 33300 +Epoch: [12] [1890/4276] eta: 2:02:50 lr: 3.575490223174667e-05 loss: 0.1494 (0.1511) time: 3.0919 data: 0.0087 max mem: 33300 +Epoch: [12] [1900/4276] eta: 2:02:19 lr: 3.575217137908113e-05 loss: 0.1459 (0.1511) time: 3.0998 data: 0.0087 max mem: 33300 +Epoch: [12] [1910/4276] eta: 2:01:48 lr: 3.5749440503238696e-05 loss: 0.1552 (0.1512) time: 3.1149 data: 0.0092 max mem: 33300 +Epoch: [12] [1920/4276] eta: 2:01:18 lr: 3.57467096042172e-05 loss: 0.1552 (0.1511) time: 3.1103 data: 0.0095 max mem: 33300 +Epoch: [12] [1930/4276] eta: 2:00:47 lr: 3.5743978682014485e-05 loss: 0.1408 (0.1511) time: 3.1034 data: 0.0097 max mem: 33300 +Epoch: [12] [1940/4276] eta: 2:00:16 lr: 3.574124773662838e-05 loss: 0.1413 (0.1511) time: 3.1049 data: 0.0093 max mem: 33300 +Epoch: [12] [1950/4276] eta: 1:59:46 lr: 3.5738516768056714e-05 loss: 0.1458 (0.1511) time: 3.1116 data: 0.0090 max mem: 33300 +Epoch: [12] [1960/4276] eta: 1:59:15 lr: 3.5735785776297324e-05 loss: 0.1422 (0.1511) time: 3.1186 data: 0.0085 max mem: 33300 +Epoch: [12] [1970/4276] eta: 1:58:44 lr: 3.5733054761348056e-05 loss: 0.1329 (0.1510) time: 3.1012 data: 0.0078 max mem: 33300 +Epoch: [12] [1980/4276] eta: 1:58:13 lr: 3.5730323723206734e-05 loss: 0.1456 (0.1509) time: 3.0874 data: 0.0078 max mem: 33300 +Epoch: [12] [1990/4276] eta: 1:57:43 lr: 3.5727592661871184e-05 loss: 0.1352 (0.1508) time: 3.1030 data: 0.0081 max mem: 33300 +Epoch: [12] [2000/4276] eta: 1:57:12 lr: 3.572486157733926e-05 loss: 0.1441 (0.1509) time: 3.1189 data: 0.0081 max mem: 33300 +Epoch: [12] [2010/4276] eta: 1:56:41 lr: 3.572213046960877e-05 loss: 0.1531 (0.1509) time: 3.1056 data: 0.0076 max mem: 33300 +Epoch: [12] [2020/4276] eta: 1:56:10 lr: 3.571939933867757e-05 loss: 0.1613 (0.1510) time: 3.0884 data: 0.0076 max mem: 33300 +Epoch: [12] [2030/4276] eta: 1:55:40 lr: 3.571666818454348e-05 loss: 0.1505 (0.1509) time: 3.0894 data: 0.0080 max mem: 33300 +Epoch: [12] [2040/4276] eta: 1:55:09 lr: 3.5713937007204325e-05 loss: 0.1340 (0.1509) time: 3.1021 data: 0.0080 max mem: 33300 +Epoch: [12] [2050/4276] eta: 1:54:38 lr: 3.571120580665794e-05 loss: 0.1439 (0.1509) time: 3.1184 data: 0.0078 max mem: 33300 +Epoch: [12] [2060/4276] eta: 1:54:08 lr: 3.570847458290216e-05 loss: 0.1417 (0.1508) time: 3.1138 data: 0.0079 max mem: 33300 +Epoch: [12] [2070/4276] eta: 1:53:37 lr: 3.5705743335934816e-05 loss: 0.1348 (0.1508) time: 3.0976 data: 0.0079 max mem: 33300 +Epoch: [12] [2080/4276] eta: 1:53:06 lr: 3.5703012065753744e-05 loss: 0.1365 (0.1508) time: 3.0911 data: 0.0085 max mem: 33300 +Epoch: [12] [2090/4276] eta: 1:52:35 lr: 3.5700280772356754e-05 loss: 0.1492 (0.1508) time: 3.1025 data: 0.0084 max mem: 33300 +Epoch: [12] [2100/4276] eta: 1:52:04 lr: 3.5697549455741695e-05 loss: 0.1492 (0.1508) time: 3.1009 data: 0.0077 max mem: 33300 +Epoch: [12] [2110/4276] eta: 1:51:33 lr: 3.569481811590638e-05 loss: 0.1389 (0.1507) time: 3.0970 data: 0.0077 max mem: 33300 +Epoch: [12] [2120/4276] eta: 1:51:02 lr: 3.569208675284865e-05 loss: 0.1280 (0.1506) time: 3.0934 data: 0.0081 max mem: 33300 +Epoch: [12] [2130/4276] eta: 1:50:32 lr: 3.5689355366566316e-05 loss: 0.1282 (0.1506) time: 3.1049 data: 0.0084 max mem: 33300 +Epoch: [12] [2140/4276] eta: 1:50:01 lr: 3.568662395705722e-05 loss: 0.1404 (0.1505) time: 3.1224 data: 0.0083 max mem: 33300 +Epoch: [12] [2150/4276] eta: 1:49:30 lr: 3.56838925243192e-05 loss: 0.1404 (0.1505) time: 3.1052 data: 0.0079 max mem: 33300 +Epoch: [12] [2160/4276] eta: 1:48:59 lr: 3.5681161068350056e-05 loss: 0.1368 (0.1505) time: 3.0832 data: 0.0076 max mem: 33300 +Epoch: [12] [2170/4276] eta: 1:48:28 lr: 3.5678429589147634e-05 loss: 0.1368 (0.1505) time: 3.0653 data: 0.0084 max mem: 33300 +Epoch: [12] [2180/4276] eta: 1:47:57 lr: 3.5675698086709756e-05 loss: 0.1468 (0.1506) time: 3.0625 data: 0.0089 max mem: 33300 +Epoch: [12] [2190/4276] eta: 1:47:26 lr: 3.5672966561034233e-05 loss: 0.1633 (0.1506) time: 3.0580 data: 0.0083 max mem: 33300 +Epoch: [12] [2200/4276] eta: 1:46:54 lr: 3.5670235012118905e-05 loss: 0.1631 (0.1506) time: 3.0474 data: 0.0080 max mem: 33300 +Epoch: [12] [2210/4276] eta: 1:46:23 lr: 3.5667503439961596e-05 loss: 0.1533 (0.1506) time: 3.0360 data: 0.0078 max mem: 33300 +Epoch: [12] [2220/4276] eta: 1:45:52 lr: 3.566477184456013e-05 loss: 0.1599 (0.1507) time: 3.0389 data: 0.0078 max mem: 33300 +Epoch: [12] [2230/4276] eta: 1:45:21 lr: 3.566204022591233e-05 loss: 0.1489 (0.1507) time: 3.0579 data: 0.0080 max mem: 33300 +Epoch: [12] [2240/4276] eta: 1:44:49 lr: 3.565930858401602e-05 loss: 0.1313 (0.1506) time: 3.0673 data: 0.0078 max mem: 33300 +Epoch: [12] [2250/4276] eta: 1:44:18 lr: 3.565657691886902e-05 loss: 0.1303 (0.1505) time: 3.0677 data: 0.0078 max mem: 33300 +Epoch: [12] [2260/4276] eta: 1:43:48 lr: 3.565384523046916e-05 loss: 0.1394 (0.1507) time: 3.0917 data: 0.0081 max mem: 33300 +Epoch: [12] [2270/4276] eta: 1:43:17 lr: 3.565111351881425e-05 loss: 0.1394 (0.1507) time: 3.1133 data: 0.0085 max mem: 33300 +Epoch: [12] [2280/4276] eta: 1:42:46 lr: 3.5648381783902115e-05 loss: 0.1377 (0.1507) time: 3.0917 data: 0.0084 max mem: 33300 +Epoch: [12] [2290/4276] eta: 1:42:15 lr: 3.564565002573059e-05 loss: 0.1482 (0.1507) time: 3.0532 data: 0.0084 max mem: 33300 +Epoch: [12] [2300/4276] eta: 1:41:43 lr: 3.564291824429749e-05 loss: 0.1482 (0.1506) time: 3.0314 data: 0.0085 max mem: 33300 +Epoch: [12] [2310/4276] eta: 1:41:12 lr: 3.564018643960064e-05 loss: 0.1427 (0.1507) time: 3.0413 data: 0.0084 max mem: 33300 +Epoch: [12] [2320/4276] eta: 1:40:41 lr: 3.563745461163784e-05 loss: 0.1427 (0.1507) time: 3.0811 data: 0.0083 max mem: 33300 +Epoch: [12] [2330/4276] eta: 1:40:11 lr: 3.563472276040694e-05 loss: 0.1480 (0.1507) time: 3.1275 data: 0.0081 max mem: 33300 +Epoch: [12] [2340/4276] eta: 1:39:40 lr: 3.5631990885905735e-05 loss: 0.1480 (0.1507) time: 3.1076 data: 0.0082 max mem: 33300 +Epoch: [12] [2350/4276] eta: 1:39:08 lr: 3.562925898813206e-05 loss: 0.1430 (0.1507) time: 3.0514 data: 0.0086 max mem: 33300 +Epoch: [12] [2360/4276] eta: 1:38:38 lr: 3.562652706708372e-05 loss: 0.1413 (0.1507) time: 3.0613 data: 0.0086 max mem: 33300 +Epoch: [12] [2370/4276] eta: 1:38:07 lr: 3.562379512275854e-05 loss: 0.1438 (0.1507) time: 3.1045 data: 0.0080 max mem: 33300 +Epoch: [12] [2380/4276] eta: 1:37:36 lr: 3.562106315515434e-05 loss: 0.1495 (0.1507) time: 3.0981 data: 0.0078 max mem: 33300 +Epoch: [12] [2390/4276] eta: 1:37:05 lr: 3.561833116426895e-05 loss: 0.1384 (0.1506) time: 3.0767 data: 0.0082 max mem: 33300 +Epoch: [12] [2400/4276] eta: 1:36:34 lr: 3.561559915010017e-05 loss: 0.1461 (0.1506) time: 3.0916 data: 0.0089 max mem: 33300 +Epoch: [12] [2410/4276] eta: 1:36:03 lr: 3.561286711264582e-05 loss: 0.1410 (0.1506) time: 3.0951 data: 0.0089 max mem: 33300 +Epoch: [12] [2420/4276] eta: 1:35:32 lr: 3.561013505190372e-05 loss: 0.1364 (0.1505) time: 3.0780 data: 0.0087 max mem: 33300 +Epoch: [12] [2430/4276] eta: 1:35:01 lr: 3.560740296787168e-05 loss: 0.1552 (0.1506) time: 3.0546 data: 0.0083 max mem: 33300 +Epoch: [12] [2440/4276] eta: 1:34:30 lr: 3.560467086054753e-05 loss: 0.1477 (0.1506) time: 3.0502 data: 0.0084 max mem: 33300 +Epoch: [12] [2450/4276] eta: 1:33:59 lr: 3.560193872992907e-05 loss: 0.1435 (0.1506) time: 3.0723 data: 0.0085 max mem: 33300 +Epoch: [12] [2460/4276] eta: 1:33:28 lr: 3.559920657601412e-05 loss: 0.1435 (0.1506) time: 3.0968 data: 0.0082 max mem: 33300 +Epoch: [12] [2470/4276] eta: 1:32:58 lr: 3.5596474398800506e-05 loss: 0.1574 (0.1507) time: 3.1115 data: 0.0082 max mem: 33300 +Epoch: [12] [2480/4276] eta: 1:32:27 lr: 3.559374219828603e-05 loss: 0.1574 (0.1507) time: 3.0977 data: 0.0081 max mem: 33300 +Epoch: [12] [2490/4276] eta: 1:31:56 lr: 3.55910099744685e-05 loss: 0.1428 (0.1507) time: 3.0878 data: 0.0077 max mem: 33300 +Epoch: [12] [2500/4276] eta: 1:31:25 lr: 3.5588277727345745e-05 loss: 0.1511 (0.1507) time: 3.0958 data: 0.0076 max mem: 33300 +Epoch: [12] [2510/4276] eta: 1:30:54 lr: 3.558554545691556e-05 loss: 0.1500 (0.1507) time: 3.1168 data: 0.0079 max mem: 33300 +Epoch: [12] [2520/4276] eta: 1:30:24 lr: 3.5582813163175784e-05 loss: 0.1389 (0.1506) time: 3.1216 data: 0.0080 max mem: 33300 +Epoch: [12] [2530/4276] eta: 1:29:53 lr: 3.55800808461242e-05 loss: 0.1171 (0.1505) time: 3.1051 data: 0.0078 max mem: 33300 +Epoch: [12] [2540/4276] eta: 1:29:22 lr: 3.557734850575865e-05 loss: 0.1230 (0.1505) time: 3.0948 data: 0.0079 max mem: 33300 +Epoch: [12] [2550/4276] eta: 1:28:51 lr: 3.557461614207692e-05 loss: 0.1435 (0.1504) time: 3.0916 data: 0.0085 max mem: 33300 +Epoch: [12] [2560/4276] eta: 1:28:20 lr: 3.557188375507684e-05 loss: 0.1303 (0.1503) time: 3.0759 data: 0.0095 max mem: 33300 +Epoch: [12] [2570/4276] eta: 1:27:49 lr: 3.5569151344756203e-05 loss: 0.1208 (0.1503) time: 3.0475 data: 0.0099 max mem: 33300 +Epoch: [12] [2580/4276] eta: 1:27:18 lr: 3.5566418911112834e-05 loss: 0.1311 (0.1503) time: 3.0574 data: 0.0086 max mem: 33300 +Epoch: [12] [2590/4276] eta: 1:26:47 lr: 3.556368645414453e-05 loss: 0.1316 (0.1502) time: 3.0876 data: 0.0084 max mem: 33300 +Epoch: [12] [2600/4276] eta: 1:26:16 lr: 3.5560953973849106e-05 loss: 0.1400 (0.1502) time: 3.1153 data: 0.0094 max mem: 33300 +Epoch: [12] [2610/4276] eta: 1:25:45 lr: 3.555822147022438e-05 loss: 0.1362 (0.1501) time: 3.0997 data: 0.0090 max mem: 33300 +Epoch: [12] [2620/4276] eta: 1:25:14 lr: 3.5555488943268164e-05 loss: 0.1415 (0.1502) time: 3.0750 data: 0.0082 max mem: 33300 +Epoch: [12] [2630/4276] eta: 1:24:43 lr: 3.5552756392978235e-05 loss: 0.1391 (0.1501) time: 3.0707 data: 0.0081 max mem: 33300 +Epoch: [12] [2640/4276] eta: 1:24:12 lr: 3.555002381935244e-05 loss: 0.1275 (0.1501) time: 3.0636 data: 0.0085 max mem: 33300 +Epoch: [12] [2650/4276] eta: 1:23:41 lr: 3.554729122238856e-05 loss: 0.1364 (0.1501) time: 3.0789 data: 0.0089 max mem: 33300 +Epoch: [12] [2660/4276] eta: 1:23:10 lr: 3.554455860208441e-05 loss: 0.1502 (0.1501) time: 3.0685 data: 0.0087 max mem: 33300 +Epoch: [12] [2670/4276] eta: 1:22:40 lr: 3.5541825958437805e-05 loss: 0.1434 (0.1501) time: 3.0855 data: 0.0084 max mem: 33300 +Epoch: [12] [2680/4276] eta: 1:22:09 lr: 3.5539093291446535e-05 loss: 0.1472 (0.1501) time: 3.1012 data: 0.0080 max mem: 33300 +Epoch: [12] [2690/4276] eta: 1:21:38 lr: 3.553636060110842e-05 loss: 0.1480 (0.1501) time: 3.0941 data: 0.0076 max mem: 33300 +Epoch: [12] [2700/4276] eta: 1:21:07 lr: 3.553362788742127e-05 loss: 0.1325 (0.1500) time: 3.1218 data: 0.0080 max mem: 33300 +Epoch: [12] [2710/4276] eta: 1:20:36 lr: 3.553089515038287e-05 loss: 0.1325 (0.1500) time: 3.0904 data: 0.0082 max mem: 33300 +Epoch: [12] [2720/4276] eta: 1:20:05 lr: 3.552816238999105e-05 loss: 0.1357 (0.1500) time: 3.0645 data: 0.0079 max mem: 33300 +Epoch: [12] [2730/4276] eta: 1:19:34 lr: 3.552542960624359e-05 loss: 0.1492 (0.1500) time: 3.0870 data: 0.0075 max mem: 33300 +Epoch: [12] [2740/4276] eta: 1:19:04 lr: 3.55226967991383e-05 loss: 0.1546 (0.1500) time: 3.1155 data: 0.0076 max mem: 33300 +Epoch: [12] [2750/4276] eta: 1:18:33 lr: 3.5519963968672995e-05 loss: 0.1574 (0.1500) time: 3.1157 data: 0.0080 max mem: 33300 +Epoch: [12] [2760/4276] eta: 1:18:02 lr: 3.551723111484548e-05 loss: 0.1425 (0.1500) time: 3.0858 data: 0.0082 max mem: 33300 +Epoch: [12] [2770/4276] eta: 1:17:31 lr: 3.551449823765354e-05 loss: 0.1385 (0.1500) time: 3.0802 data: 0.0082 max mem: 33300 +Epoch: [12] [2780/4276] eta: 1:17:00 lr: 3.5511765337094995e-05 loss: 0.1385 (0.1500) time: 3.0848 data: 0.0085 max mem: 33300 +Epoch: [12] [2790/4276] eta: 1:16:30 lr: 3.5509032413167645e-05 loss: 0.1551 (0.1500) time: 3.1167 data: 0.0089 max mem: 33300 +Epoch: [12] [2800/4276] eta: 1:15:59 lr: 3.550629946586927e-05 loss: 0.1474 (0.1500) time: 3.1242 data: 0.0085 max mem: 33300 +Epoch: [12] [2810/4276] eta: 1:15:28 lr: 3.55035664951977e-05 loss: 0.1259 (0.1499) time: 3.1013 data: 0.0079 max mem: 33300 +Epoch: [12] [2820/4276] eta: 1:14:57 lr: 3.550083350115072e-05 loss: 0.1259 (0.1498) time: 3.0906 data: 0.0078 max mem: 33300 +Epoch: [12] [2830/4276] eta: 1:14:26 lr: 3.549810048372613e-05 loss: 0.1366 (0.1498) time: 3.0961 data: 0.0079 max mem: 33300 +Epoch: [12] [2840/4276] eta: 1:13:55 lr: 3.5495367442921736e-05 loss: 0.1430 (0.1498) time: 3.1135 data: 0.0082 max mem: 33300 +Epoch: [12] [2850/4276] eta: 1:13:25 lr: 3.549263437873534e-05 loss: 0.1661 (0.1499) time: 3.1046 data: 0.0082 max mem: 33300 +Epoch: [12] [2860/4276] eta: 1:12:54 lr: 3.548990129116473e-05 loss: 0.1532 (0.1499) time: 3.0880 data: 0.0082 max mem: 33300 +Epoch: [12] [2870/4276] eta: 1:12:23 lr: 3.548716818020773e-05 loss: 0.1417 (0.1498) time: 3.0980 data: 0.0085 max mem: 33300 +Epoch: [12] [2880/4276] eta: 1:11:52 lr: 3.548443504586211e-05 loss: 0.1454 (0.1498) time: 3.1241 data: 0.0084 max mem: 33300 +Epoch: [12] [2890/4276] eta: 1:11:21 lr: 3.548170188812567e-05 loss: 0.1397 (0.1498) time: 3.1241 data: 0.0076 max mem: 33300 +Epoch: [12] [2900/4276] eta: 1:10:51 lr: 3.547896870699623e-05 loss: 0.1366 (0.1498) time: 3.0979 data: 0.0073 max mem: 33300 +Epoch: [12] [2910/4276] eta: 1:10:20 lr: 3.547623550247157e-05 loss: 0.1315 (0.1497) time: 3.0884 data: 0.0074 max mem: 33300 +Epoch: [12] [2920/4276] eta: 1:09:49 lr: 3.547350227454949e-05 loss: 0.1359 (0.1497) time: 3.0701 data: 0.0087 max mem: 33300 +Epoch: [12] [2930/4276] eta: 1:09:18 lr: 3.54707690232278e-05 loss: 0.1393 (0.1497) time: 3.0527 data: 0.0097 max mem: 33300 +Epoch: [12] [2940/4276] eta: 1:08:46 lr: 3.5468035748504275e-05 loss: 0.1371 (0.1496) time: 3.0513 data: 0.0091 max mem: 33300 +Epoch: [12] [2950/4276] eta: 1:08:16 lr: 3.546530245037673e-05 loss: 0.1360 (0.1496) time: 3.0663 data: 0.0084 max mem: 33300 +Epoch: [12] [2960/4276] eta: 1:07:45 lr: 3.546256912884293e-05 loss: 0.1356 (0.1496) time: 3.0854 data: 0.0079 max mem: 33300 +Epoch: [12] [2970/4276] eta: 1:07:14 lr: 3.54598357839007e-05 loss: 0.1361 (0.1497) time: 3.1099 data: 0.0079 max mem: 33300 +Epoch: [12] [2980/4276] eta: 1:06:43 lr: 3.5457102415547834e-05 loss: 0.1505 (0.1497) time: 3.1315 data: 0.0082 max mem: 33300 +Epoch: [12] [2990/4276] eta: 1:06:12 lr: 3.545436902378211e-05 loss: 0.1416 (0.1496) time: 3.1100 data: 0.0081 max mem: 33300 +Epoch: [12] [3000/4276] eta: 1:05:41 lr: 3.5451635608601325e-05 loss: 0.1415 (0.1496) time: 3.0924 data: 0.0080 max mem: 33300 +Epoch: [12] [3010/4276] eta: 1:05:11 lr: 3.5448902170003284e-05 loss: 0.1415 (0.1496) time: 3.0992 data: 0.0079 max mem: 33300 +Epoch: [12] [3020/4276] eta: 1:04:40 lr: 3.544616870798577e-05 loss: 0.1445 (0.1496) time: 3.1121 data: 0.0076 max mem: 33300 +Epoch: [12] [3030/4276] eta: 1:04:09 lr: 3.5443435222546586e-05 loss: 0.1445 (0.1496) time: 3.1014 data: 0.0079 max mem: 33300 +Epoch: [12] [3040/4276] eta: 1:03:38 lr: 3.5440701713683504e-05 loss: 0.1457 (0.1497) time: 3.0828 data: 0.0083 max mem: 33300 +Epoch: [12] [3050/4276] eta: 1:03:07 lr: 3.543796818139433e-05 loss: 0.1440 (0.1496) time: 3.0860 data: 0.0084 max mem: 33300 +Epoch: [12] [3060/4276] eta: 1:02:36 lr: 3.543523462567686e-05 loss: 0.1225 (0.1496) time: 3.0972 data: 0.0083 max mem: 33300 +Epoch: [12] [3070/4276] eta: 1:02:06 lr: 3.5432501046528874e-05 loss: 0.1358 (0.1496) time: 3.1446 data: 0.0085 max mem: 33300 +Epoch: [12] [3080/4276] eta: 1:01:35 lr: 3.542976744394817e-05 loss: 0.1423 (0.1495) time: 3.1480 data: 0.0090 max mem: 33300 +Epoch: [12] [3090/4276] eta: 1:01:04 lr: 3.542703381793254e-05 loss: 0.1308 (0.1495) time: 3.1069 data: 0.0086 max mem: 33300 +Epoch: [12] [3100/4276] eta: 1:00:33 lr: 3.5424300168479765e-05 loss: 0.1395 (0.1495) time: 3.0874 data: 0.0079 max mem: 33300 +Epoch: [12] [3110/4276] eta: 1:00:02 lr: 3.542156649558764e-05 loss: 0.1393 (0.1494) time: 3.0904 data: 0.0080 max mem: 33300 +Epoch: [12] [3120/4276] eta: 0:59:31 lr: 3.5418832799253955e-05 loss: 0.1264 (0.1494) time: 3.0774 data: 0.0078 max mem: 33300 +Epoch: [12] [3130/4276] eta: 0:59:00 lr: 3.54160990794765e-05 loss: 0.1325 (0.1494) time: 3.0468 data: 0.0086 max mem: 33300 +Epoch: [12] [3140/4276] eta: 0:58:29 lr: 3.5413365336253045e-05 loss: 0.1376 (0.1493) time: 3.0476 data: 0.0092 max mem: 33300 +Epoch: [12] [3150/4276] eta: 0:57:58 lr: 3.5410631569581404e-05 loss: 0.1440 (0.1494) time: 3.0881 data: 0.0085 max mem: 33300 +Epoch: [12] [3160/4276] eta: 0:57:28 lr: 3.540789777945935e-05 loss: 0.1578 (0.1494) time: 3.1538 data: 0.0080 max mem: 33300 +Epoch: [12] [3170/4276] eta: 0:56:57 lr: 3.5405163965884683e-05 loss: 0.1578 (0.1494) time: 3.1340 data: 0.0074 max mem: 33300 +Epoch: [12] [3180/4276] eta: 0:56:26 lr: 3.540243012885517e-05 loss: 0.1599 (0.1494) time: 3.0873 data: 0.0070 max mem: 33300 +Epoch: [12] [3190/4276] eta: 0:55:55 lr: 3.5399696268368615e-05 loss: 0.1457 (0.1493) time: 3.0745 data: 0.0071 max mem: 33300 +Epoch: [12] [3200/4276] eta: 0:55:24 lr: 3.539696238442279e-05 loss: 0.1400 (0.1493) time: 3.0664 data: 0.0072 max mem: 33300 +Epoch: [12] [3210/4276] eta: 0:54:53 lr: 3.5394228477015485e-05 loss: 0.1422 (0.1494) time: 3.0738 data: 0.0081 max mem: 33300 +Epoch: [12] [3220/4276] eta: 0:54:22 lr: 3.539149454614449e-05 loss: 0.1485 (0.1494) time: 3.0890 data: 0.0090 max mem: 33300 +Epoch: [12] [3230/4276] eta: 0:53:51 lr: 3.538876059180759e-05 loss: 0.1485 (0.1494) time: 3.0755 data: 0.0089 max mem: 33300 +Epoch: [12] [3240/4276] eta: 0:53:20 lr: 3.538602661400256e-05 loss: 0.1572 (0.1494) time: 3.0451 data: 0.0082 max mem: 33300 +Epoch: [12] [3250/4276] eta: 0:52:49 lr: 3.538329261272719e-05 loss: 0.1507 (0.1494) time: 3.0387 data: 0.0075 max mem: 33300 +Epoch: [12] [3260/4276] eta: 0:52:18 lr: 3.538055858797927e-05 loss: 0.1396 (0.1494) time: 3.0604 data: 0.0073 max mem: 33300 +Epoch: [12] [3270/4276] eta: 0:51:47 lr: 3.5377824539756564e-05 loss: 0.1518 (0.1494) time: 3.0823 data: 0.0073 max mem: 33300 +Epoch: [12] [3280/4276] eta: 0:51:16 lr: 3.537509046805687e-05 loss: 0.1512 (0.1495) time: 3.0696 data: 0.0070 max mem: 33300 +Epoch: [12] [3290/4276] eta: 0:50:45 lr: 3.537235637287797e-05 loss: 0.1528 (0.1495) time: 3.0504 data: 0.0070 max mem: 33300 +Epoch: [12] [3300/4276] eta: 0:50:14 lr: 3.536962225421765e-05 loss: 0.1538 (0.1495) time: 3.0773 data: 0.0072 max mem: 33300 +Epoch: [12] [3310/4276] eta: 0:49:44 lr: 3.5366888112073676e-05 loss: 0.1537 (0.1495) time: 3.0993 data: 0.0072 max mem: 33300 +Epoch: [12] [3320/4276] eta: 0:49:13 lr: 3.536415394644384e-05 loss: 0.1601 (0.1496) time: 3.0993 data: 0.0070 max mem: 33300 +Epoch: [12] [3330/4276] eta: 0:48:42 lr: 3.536141975732592e-05 loss: 0.1356 (0.1496) time: 3.0945 data: 0.0072 max mem: 33300 +Epoch: [12] [3340/4276] eta: 0:48:11 lr: 3.53586855447177e-05 loss: 0.1357 (0.1495) time: 3.0617 data: 0.0071 max mem: 33300 +Epoch: [12] [3350/4276] eta: 0:47:40 lr: 3.535595130861695e-05 loss: 0.1365 (0.1495) time: 3.0303 data: 0.0071 max mem: 33300 +Epoch: [12] [3360/4276] eta: 0:47:09 lr: 3.535321704902146e-05 loss: 0.1402 (0.1495) time: 3.0260 data: 0.0071 max mem: 33300 +Epoch: [12] [3370/4276] eta: 0:46:38 lr: 3.5350482765929e-05 loss: 0.1483 (0.1496) time: 3.0753 data: 0.0072 max mem: 33300 +Epoch: [12] [3380/4276] eta: 0:46:07 lr: 3.534774845933735e-05 loss: 0.1540 (0.1496) time: 3.0970 data: 0.0070 max mem: 33300 +Epoch: [12] [3390/4276] eta: 0:45:36 lr: 3.5345014129244305e-05 loss: 0.1621 (0.1496) time: 3.0458 data: 0.0067 max mem: 33300 +Epoch: [12] [3400/4276] eta: 0:45:05 lr: 3.5342279775647624e-05 loss: 0.1576 (0.1496) time: 3.0127 data: 0.0068 max mem: 33300 +Epoch: [12] [3410/4276] eta: 0:44:34 lr: 3.5339545398545094e-05 loss: 0.1576 (0.1497) time: 3.0197 data: 0.0071 max mem: 33300 +Epoch: [12] [3420/4276] eta: 0:44:03 lr: 3.533681099793448e-05 loss: 0.1606 (0.1497) time: 3.0284 data: 0.0070 max mem: 33300 +Epoch: [12] [3430/4276] eta: 0:43:32 lr: 3.5334076573813565e-05 loss: 0.1604 (0.1498) time: 3.0344 data: 0.0069 max mem: 33300 +Epoch: [12] [3440/4276] eta: 0:43:01 lr: 3.533134212618013e-05 loss: 0.1471 (0.1497) time: 3.0679 data: 0.0073 max mem: 33300 +Epoch: [12] [3450/4276] eta: 0:42:30 lr: 3.5328607655031956e-05 loss: 0.1534 (0.1498) time: 3.1008 data: 0.0075 max mem: 33300 +Epoch: [12] [3460/4276] eta: 0:41:59 lr: 3.53258731603668e-05 loss: 0.1586 (0.1498) time: 3.0964 data: 0.0072 max mem: 33300 +Epoch: [12] [3470/4276] eta: 0:41:28 lr: 3.532313864218246e-05 loss: 0.1374 (0.1498) time: 3.0862 data: 0.0070 max mem: 33300 +Epoch: [12] [3480/4276] eta: 0:40:57 lr: 3.532040410047669e-05 loss: 0.1533 (0.1498) time: 3.0780 data: 0.0071 max mem: 33300 +Epoch: [12] [3490/4276] eta: 0:40:26 lr: 3.531766953524727e-05 loss: 0.1590 (0.1498) time: 3.0442 data: 0.0072 max mem: 33300 +Epoch: [12] [3500/4276] eta: 0:39:55 lr: 3.531493494649198e-05 loss: 0.1551 (0.1498) time: 3.0409 data: 0.0072 max mem: 33300 +Epoch: [12] [3510/4276] eta: 0:39:24 lr: 3.531220033420858e-05 loss: 0.1397 (0.1498) time: 3.0701 data: 0.0072 max mem: 33300 +Epoch: [12] [3520/4276] eta: 0:38:54 lr: 3.530946569839486e-05 loss: 0.1401 (0.1498) time: 3.1073 data: 0.0073 max mem: 33300 +Epoch: [12] [3530/4276] eta: 0:38:23 lr: 3.530673103904859e-05 loss: 0.1499 (0.1498) time: 3.1269 data: 0.0073 max mem: 33300 +Epoch: [12] [3540/4276] eta: 0:37:52 lr: 3.530399635616753e-05 loss: 0.1443 (0.1498) time: 3.1023 data: 0.0073 max mem: 33300 +Epoch: [12] [3550/4276] eta: 0:37:21 lr: 3.530126164974947e-05 loss: 0.1443 (0.1498) time: 3.1038 data: 0.0074 max mem: 33300 +Epoch: [12] [3560/4276] eta: 0:36:50 lr: 3.5298526919792155e-05 loss: 0.1474 (0.1498) time: 3.1138 data: 0.0073 max mem: 33300 +Epoch: [12] [3570/4276] eta: 0:36:19 lr: 3.5295792166293384e-05 loss: 0.1598 (0.1498) time: 3.0982 data: 0.0071 max mem: 33300 +Epoch: [12] [3580/4276] eta: 0:35:49 lr: 3.529305738925091e-05 loss: 0.1413 (0.1498) time: 3.1017 data: 0.0070 max mem: 33300 +Epoch: [12] [3590/4276] eta: 0:35:18 lr: 3.529032258866251e-05 loss: 0.1330 (0.1498) time: 3.1161 data: 0.0071 max mem: 33300 +Epoch: [12] [3600/4276] eta: 0:34:47 lr: 3.528758776452596e-05 loss: 0.1455 (0.1498) time: 3.1168 data: 0.0072 max mem: 33300 +Epoch: [12] [3610/4276] eta: 0:34:16 lr: 3.5284852916839006e-05 loss: 0.1484 (0.1498) time: 3.1208 data: 0.0069 max mem: 33300 +Epoch: [12] [3620/4276] eta: 0:33:45 lr: 3.5282118045599444e-05 loss: 0.1499 (0.1497) time: 3.0970 data: 0.0067 max mem: 33300 +Epoch: [12] [3630/4276] eta: 0:33:14 lr: 3.527938315080503e-05 loss: 0.1395 (0.1498) time: 3.0721 data: 0.0070 max mem: 33300 +Epoch: [12] [3640/4276] eta: 0:32:43 lr: 3.5276648232453534e-05 loss: 0.1323 (0.1497) time: 3.0649 data: 0.0072 max mem: 33300 +Epoch: [12] [3650/4276] eta: 0:32:13 lr: 3.5273913290542726e-05 loss: 0.1267 (0.1497) time: 3.0710 data: 0.0072 max mem: 33300 +Epoch: [12] [3660/4276] eta: 0:31:42 lr: 3.527117832507036e-05 loss: 0.1267 (0.1497) time: 3.0890 data: 0.0072 max mem: 33300 +Epoch: [12] [3670/4276] eta: 0:31:11 lr: 3.526844333603423e-05 loss: 0.1443 (0.1497) time: 3.1118 data: 0.0071 max mem: 33300 +Epoch: [12] [3680/4276] eta: 0:30:40 lr: 3.5265708323432076e-05 loss: 0.1440 (0.1497) time: 3.1224 data: 0.0073 max mem: 33300 +Epoch: [12] [3690/4276] eta: 0:30:09 lr: 3.5262973287261673e-05 loss: 0.1505 (0.1497) time: 3.0994 data: 0.0073 max mem: 33300 +Epoch: [12] [3700/4276] eta: 0:29:38 lr: 3.52602382275208e-05 loss: 0.1397 (0.1497) time: 3.0865 data: 0.0072 max mem: 33300 +Epoch: [12] [3710/4276] eta: 0:29:07 lr: 3.52575031442072e-05 loss: 0.1320 (0.1496) time: 3.0977 data: 0.0073 max mem: 33300 +Epoch: [12] [3720/4276] eta: 0:28:37 lr: 3.525476803731865e-05 loss: 0.1250 (0.1496) time: 3.0894 data: 0.0074 max mem: 33300 +Epoch: [12] [3730/4276] eta: 0:28:06 lr: 3.5252032906852916e-05 loss: 0.1362 (0.1496) time: 3.0675 data: 0.0077 max mem: 33300 +Epoch: [12] [3740/4276] eta: 0:27:35 lr: 3.524929775280776e-05 loss: 0.1404 (0.1496) time: 3.0767 data: 0.0076 max mem: 33300 +Epoch: [12] [3750/4276] eta: 0:27:04 lr: 3.524656257518095e-05 loss: 0.1444 (0.1496) time: 3.1215 data: 0.0077 max mem: 33300 +Epoch: [12] [3760/4276] eta: 0:26:33 lr: 3.5243827373970234e-05 loss: 0.1379 (0.1496) time: 3.1125 data: 0.0079 max mem: 33300 +Epoch: [12] [3770/4276] eta: 0:26:02 lr: 3.5241092149173387e-05 loss: 0.1407 (0.1496) time: 3.0979 data: 0.0075 max mem: 33300 +Epoch: [12] [3780/4276] eta: 0:25:31 lr: 3.5238356900788176e-05 loss: 0.1442 (0.1496) time: 3.1006 data: 0.0073 max mem: 33300 +Epoch: [12] [3790/4276] eta: 0:25:00 lr: 3.523562162881236e-05 loss: 0.1385 (0.1495) time: 3.0740 data: 0.0079 max mem: 33300 +Epoch: [12] [3800/4276] eta: 0:24:30 lr: 3.5232886333243694e-05 loss: 0.1450 (0.1496) time: 3.0919 data: 0.0081 max mem: 33300 +Epoch: [12] [3810/4276] eta: 0:23:59 lr: 3.5230151014079944e-05 loss: 0.1441 (0.1496) time: 3.1101 data: 0.0078 max mem: 33300 +Epoch: [12] [3820/4276] eta: 0:23:28 lr: 3.522741567131887e-05 loss: 0.1281 (0.1495) time: 3.1298 data: 0.0080 max mem: 33300 +Epoch: [12] [3830/4276] eta: 0:22:57 lr: 3.522468030495823e-05 loss: 0.1277 (0.1495) time: 3.1034 data: 0.0086 max mem: 33300 +Epoch: [12] [3840/4276] eta: 0:22:26 lr: 3.5221944914995784e-05 loss: 0.1251 (0.1495) time: 3.0613 data: 0.0081 max mem: 33300 +Epoch: [12] [3850/4276] eta: 0:21:55 lr: 3.52192095014293e-05 loss: 0.1223 (0.1494) time: 3.0691 data: 0.0078 max mem: 33300 +Epoch: [12] [3860/4276] eta: 0:21:24 lr: 3.5216474064256536e-05 loss: 0.1326 (0.1494) time: 3.0910 data: 0.0081 max mem: 33300 +Epoch: [12] [3870/4276] eta: 0:20:53 lr: 3.5213738603475246e-05 loss: 0.1495 (0.1494) time: 3.1297 data: 0.0083 max mem: 33300 +Epoch: [12] [3880/4276] eta: 0:20:23 lr: 3.521100311908318e-05 loss: 0.1404 (0.1494) time: 3.0885 data: 0.0085 max mem: 33300 +Epoch: [12] [3890/4276] eta: 0:19:52 lr: 3.520826761107812e-05 loss: 0.1380 (0.1494) time: 3.0598 data: 0.0085 max mem: 33300 +Epoch: [12] [3900/4276] eta: 0:19:21 lr: 3.52055320794578e-05 loss: 0.1361 (0.1494) time: 3.0990 data: 0.0083 max mem: 33300 +Epoch: [12] [3910/4276] eta: 0:18:50 lr: 3.520279652421998e-05 loss: 0.1342 (0.1493) time: 3.0839 data: 0.0083 max mem: 33300 +Epoch: [12] [3920/4276] eta: 0:18:19 lr: 3.520006094536243e-05 loss: 0.1342 (0.1493) time: 3.0635 data: 0.0086 max mem: 33300 +Epoch: [12] [3930/4276] eta: 0:17:48 lr: 3.5197325342882906e-05 loss: 0.1405 (0.1493) time: 3.0637 data: 0.0081 max mem: 33300 +Epoch: [12] [3940/4276] eta: 0:17:17 lr: 3.5194589716779155e-05 loss: 0.1328 (0.1494) time: 3.0617 data: 0.0074 max mem: 33300 +Epoch: [12] [3950/4276] eta: 0:16:46 lr: 3.519185406704893e-05 loss: 0.1323 (0.1493) time: 3.0656 data: 0.0077 max mem: 33300 +Epoch: [12] [3960/4276] eta: 0:16:15 lr: 3.518911839369e-05 loss: 0.1439 (0.1494) time: 3.1246 data: 0.0085 max mem: 33300 +Epoch: [12] [3970/4276] eta: 0:15:45 lr: 3.51863826967001e-05 loss: 0.1517 (0.1494) time: 3.1405 data: 0.0088 max mem: 33300 +Epoch: [12] [3980/4276] eta: 0:15:14 lr: 3.5183646976077e-05 loss: 0.1423 (0.1494) time: 3.1028 data: 0.0083 max mem: 33300 +Epoch: [12] [3990/4276] eta: 0:14:43 lr: 3.518091123181845e-05 loss: 0.1398 (0.1493) time: 3.1096 data: 0.0079 max mem: 33300 +Epoch: [12] [4000/4276] eta: 0:14:12 lr: 3.51781754639222e-05 loss: 0.1396 (0.1494) time: 3.0876 data: 0.0079 max mem: 33300 +Epoch: [12] [4010/4276] eta: 0:13:41 lr: 3.517543967238602e-05 loss: 0.1399 (0.1494) time: 3.0671 data: 0.0077 max mem: 33300 +Epoch: [12] [4020/4276] eta: 0:13:10 lr: 3.517270385720764e-05 loss: 0.1438 (0.1494) time: 3.0713 data: 0.0077 max mem: 33300 +Epoch: [12] [4030/4276] eta: 0:12:39 lr: 3.5169968018384826e-05 loss: 0.1422 (0.1494) time: 3.1061 data: 0.0077 max mem: 33300 +Epoch: [12] [4040/4276] eta: 0:12:08 lr: 3.516723215591532e-05 loss: 0.1433 (0.1494) time: 3.1353 data: 0.0077 max mem: 33300 +Epoch: [12] [4050/4276] eta: 0:11:38 lr: 3.516449626979688e-05 loss: 0.1419 (0.1494) time: 3.1003 data: 0.0075 max mem: 33300 +Epoch: [12] [4060/4276] eta: 0:11:07 lr: 3.516176036002726e-05 loss: 0.1419 (0.1494) time: 3.0813 data: 0.0085 max mem: 33300 +Epoch: [12] [4070/4276] eta: 0:10:36 lr: 3.5159024426604206e-05 loss: 0.1488 (0.1494) time: 3.0580 data: 0.0094 max mem: 33300 +Epoch: [12] [4080/4276] eta: 0:10:05 lr: 3.515628846952546e-05 loss: 0.1522 (0.1495) time: 3.0457 data: 0.0085 max mem: 33300 +Epoch: [12] [4090/4276] eta: 0:09:34 lr: 3.5153552488788796e-05 loss: 0.1638 (0.1495) time: 3.0745 data: 0.0077 max mem: 33300 +Epoch: [12] [4100/4276] eta: 0:09:03 lr: 3.5150816484391945e-05 loss: 0.1642 (0.1495) time: 3.1053 data: 0.0076 max mem: 33300 +Epoch: [12] [4110/4276] eta: 0:08:32 lr: 3.5148080456332666e-05 loss: 0.1633 (0.1495) time: 3.1097 data: 0.0078 max mem: 33300 +Epoch: [12] [4120/4276] eta: 0:08:01 lr: 3.514534440460869e-05 loss: 0.1556 (0.1495) time: 3.0735 data: 0.0081 max mem: 33300 +Epoch: [12] [4130/4276] eta: 0:07:30 lr: 3.514260832921778e-05 loss: 0.1500 (0.1495) time: 3.0581 data: 0.0078 max mem: 33300 +Epoch: [12] [4140/4276] eta: 0:06:59 lr: 3.5139872230157685e-05 loss: 0.1426 (0.1495) time: 3.0451 data: 0.0078 max mem: 33300 +Epoch: [12] [4150/4276] eta: 0:06:29 lr: 3.5137136107426144e-05 loss: 0.1426 (0.1495) time: 3.0740 data: 0.0077 max mem: 33300 +Epoch: [12] [4160/4276] eta: 0:05:58 lr: 3.513439996102091e-05 loss: 0.1511 (0.1496) time: 3.0946 data: 0.0072 max mem: 33300 +Epoch: [12] [4170/4276] eta: 0:05:27 lr: 3.5131663790939735e-05 loss: 0.1539 (0.1496) time: 3.0918 data: 0.0072 max mem: 33300 +Epoch: [12] [4180/4276] eta: 0:04:56 lr: 3.5128927597180355e-05 loss: 0.1470 (0.1496) time: 3.1205 data: 0.0073 max mem: 33300 +Epoch: [12] [4190/4276] eta: 0:04:25 lr: 3.512619137974052e-05 loss: 0.1411 (0.1496) time: 3.0790 data: 0.0074 max mem: 33300 +Epoch: [12] [4200/4276] eta: 0:03:54 lr: 3.512345513861797e-05 loss: 0.1418 (0.1496) time: 3.0310 data: 0.0073 max mem: 33300 +Epoch: [12] [4210/4276] eta: 0:03:23 lr: 3.512071887381046e-05 loss: 0.1534 (0.1496) time: 3.0408 data: 0.0073 max mem: 33300 +Epoch: [12] [4220/4276] eta: 0:02:52 lr: 3.511798258531572e-05 loss: 0.1603 (0.1497) time: 3.0400 data: 0.0073 max mem: 33300 +Epoch: [12] [4230/4276] eta: 0:02:22 lr: 3.511524627313151e-05 loss: 0.1682 (0.1497) time: 3.0346 data: 0.0073 max mem: 33300 +Epoch: [12] [4240/4276] eta: 0:01:51 lr: 3.5112509937255574e-05 loss: 0.1653 (0.1497) time: 3.0352 data: 0.0074 max mem: 33300 +Epoch: [12] [4250/4276] eta: 0:01:20 lr: 3.5109773577685645e-05 loss: 0.1617 (0.1498) time: 3.0525 data: 0.0076 max mem: 33300 +Epoch: [12] [4260/4276] eta: 0:00:49 lr: 3.510703719441947e-05 loss: 0.1544 (0.1498) time: 3.0504 data: 0.0080 max mem: 33300 +Epoch: [12] [4270/4276] eta: 0:00:18 lr: 3.5104300787454786e-05 loss: 0.1458 (0.1498) time: 3.0014 data: 0.0076 max mem: 33300 +Epoch: [12] Total time: 3:40:01 +Test: [ 0/21770] eta: 8:55:38 time: 1.4763 data: 1.4363 max mem: 33300 +Test: [ 100/21770] eta: 0:19:20 time: 0.0393 data: 0.0010 max mem: 33300 +Test: [ 200/21770] eta: 0:16:33 time: 0.0387 data: 0.0011 max mem: 33300 +Test: [ 300/21770] eta: 0:15:39 time: 0.0396 data: 0.0010 max mem: 33300 +Test: [ 400/21770] eta: 0:15:04 time: 0.0380 data: 0.0011 max mem: 33300 +Test: [ 500/21770] eta: 0:14:41 time: 0.0380 data: 0.0011 max mem: 33300 +Test: [ 600/21770] eta: 0:14:29 time: 0.0397 data: 0.0010 max mem: 33300 +Test: [ 700/21770] eta: 0:14:21 time: 0.0384 data: 0.0010 max mem: 33300 +Test: [ 800/21770] eta: 0:14:09 time: 0.0381 data: 0.0010 max mem: 33300 +Test: [ 900/21770] eta: 0:14:01 time: 0.0384 data: 0.0010 max mem: 33300 +Test: [ 1000/21770] eta: 0:13:53 time: 0.0381 data: 0.0009 max mem: 33300 +Test: [ 1100/21770] eta: 0:13:45 time: 0.0382 data: 0.0009 max mem: 33300 +Test: [ 1200/21770] eta: 0:13:39 time: 0.0383 data: 0.0010 max mem: 33300 +Test: [ 1300/21770] eta: 0:13:32 time: 0.0382 data: 0.0010 max mem: 33300 +Test: [ 1400/21770] eta: 0:13:27 time: 0.0383 data: 0.0009 max mem: 33300 +Test: [ 1500/21770] eta: 0:13:21 time: 0.0384 data: 0.0010 max mem: 33300 +Test: [ 1600/21770] eta: 0:13:16 time: 0.0382 data: 0.0009 max mem: 33300 +Test: [ 1700/21770] eta: 0:13:10 time: 0.0381 data: 0.0009 max mem: 33300 +Test: [ 1800/21770] eta: 0:13:05 time: 0.0383 data: 0.0010 max mem: 33300 +Test: [ 1900/21770] eta: 0:13:01 time: 0.0383 data: 0.0010 max mem: 33300 +Test: [ 2000/21770] eta: 0:12:56 time: 0.0383 data: 0.0009 max mem: 33300 +Test: [ 2100/21770] eta: 0:12:51 time: 0.0379 data: 0.0009 max mem: 33300 +Test: [ 2200/21770] eta: 0:12:46 time: 0.0379 data: 0.0009 max mem: 33300 +Test: [ 2300/21770] eta: 0:12:41 time: 0.0379 data: 0.0009 max mem: 33300 +Test: [ 2400/21770] eta: 0:12:37 time: 0.0380 data: 0.0009 max mem: 33300 +Test: [ 2500/21770] eta: 0:12:32 time: 0.0382 data: 0.0009 max mem: 33300 +Test: [ 2600/21770] eta: 0:12:28 time: 0.0380 data: 0.0009 max mem: 33300 +Test: [ 2700/21770] eta: 0:12:23 time: 0.0384 data: 0.0010 max mem: 33300 +Test: [ 2800/21770] eta: 0:12:19 time: 0.0382 data: 0.0009 max mem: 33300 +Test: [ 2900/21770] eta: 0:12:15 time: 0.0385 data: 0.0010 max mem: 33300 +Test: [ 3000/21770] eta: 0:12:10 time: 0.0382 data: 0.0009 max mem: 33300 +Test: [ 3100/21770] eta: 0:12:06 time: 0.0383 data: 0.0010 max mem: 33300 +Test: [ 3200/21770] eta: 0:12:02 time: 0.0383 data: 0.0010 max mem: 33300 +Test: [ 3300/21770] eta: 0:11:58 time: 0.0381 data: 0.0010 max mem: 33300 +Test: [ 3400/21770] eta: 0:11:53 time: 0.0382 data: 0.0011 max mem: 33300 +Test: [ 3500/21770] eta: 0:11:49 time: 0.0380 data: 0.0010 max mem: 33300 +Test: [ 3600/21770] eta: 0:11:45 time: 0.0382 data: 0.0011 max mem: 33300 +Test: [ 3700/21770] eta: 0:11:41 time: 0.0382 data: 0.0011 max mem: 33300 +Test: [ 3800/21770] eta: 0:11:36 time: 0.0381 data: 0.0011 max mem: 33300 +Test: [ 3900/21770] eta: 0:11:32 time: 0.0383 data: 0.0011 max mem: 33300 +Test: [ 4000/21770] eta: 0:11:28 time: 0.0382 data: 0.0011 max mem: 33300 +Test: [ 4100/21770] eta: 0:11:24 time: 0.0382 data: 0.0011 max mem: 33300 +Test: [ 4200/21770] eta: 0:11:20 time: 0.0380 data: 0.0010 max mem: 33300 +Test: [ 4300/21770] eta: 0:11:16 time: 0.0381 data: 0.0010 max mem: 33300 +Test: [ 4400/21770] eta: 0:11:12 time: 0.0382 data: 0.0011 max mem: 33300 +Test: [ 4500/21770] eta: 0:11:08 time: 0.0379 data: 0.0010 max mem: 33300 +Test: [ 4600/21770] eta: 0:11:04 time: 0.0383 data: 0.0010 max mem: 33300 +Test: [ 4700/21770] eta: 0:11:00 time: 0.0385 data: 0.0010 max mem: 33300 +Test: [ 4800/21770] eta: 0:10:56 time: 0.0384 data: 0.0010 max mem: 33300 +Test: [ 4900/21770] eta: 0:10:52 time: 0.0389 data: 0.0011 max mem: 33300 +Test: [ 5000/21770] eta: 0:10:48 time: 0.0387 data: 0.0011 max mem: 33300 +Test: [ 5100/21770] eta: 0:10:44 time: 0.0383 data: 0.0010 max mem: 33300 +Test: [ 5200/21770] eta: 0:10:40 time: 0.0383 data: 0.0010 max mem: 33300 +Test: [ 5300/21770] eta: 0:10:36 time: 0.0385 data: 0.0011 max mem: 33300 +Test: [ 5400/21770] eta: 0:10:32 time: 0.0383 data: 0.0011 max mem: 33300 +Test: [ 5500/21770] eta: 0:10:28 time: 0.0383 data: 0.0011 max mem: 33300 +Test: [ 5600/21770] eta: 0:10:24 time: 0.0382 data: 0.0011 max mem: 33300 +Test: [ 5700/21770] eta: 0:10:20 time: 0.0383 data: 0.0011 max mem: 33300 +Test: [ 5800/21770] eta: 0:10:16 time: 0.0382 data: 0.0010 max mem: 33300 +Test: [ 5900/21770] eta: 0:10:12 time: 0.0382 data: 0.0011 max mem: 33300 +Test: [ 6000/21770] eta: 0:10:08 time: 0.0384 data: 0.0011 max mem: 33300 +Test: [ 6100/21770] eta: 0:10:05 time: 0.0383 data: 0.0011 max mem: 33300 +Test: [ 6200/21770] eta: 0:10:01 time: 0.0382 data: 0.0011 max mem: 33300 +Test: [ 6300/21770] eta: 0:09:57 time: 0.0382 data: 0.0011 max mem: 33300 +Test: [ 6400/21770] eta: 0:09:53 time: 0.0383 data: 0.0011 max mem: 33300 +Test: [ 6500/21770] eta: 0:09:49 time: 0.0381 data: 0.0010 max mem: 33300 +Test: [ 6600/21770] eta: 0:09:45 time: 0.0382 data: 0.0011 max mem: 33300 +Test: [ 6700/21770] eta: 0:09:41 time: 0.0383 data: 0.0011 max mem: 33300 +Test: [ 6800/21770] eta: 0:09:37 time: 0.0382 data: 0.0010 max mem: 33300 +Test: [ 6900/21770] eta: 0:09:33 time: 0.0382 data: 0.0010 max mem: 33300 +Test: [ 7000/21770] eta: 0:09:29 time: 0.0383 data: 0.0011 max mem: 33300 +Test: [ 7100/21770] eta: 0:09:25 time: 0.0380 data: 0.0010 max mem: 33300 +Test: [ 7200/21770] eta: 0:09:21 time: 0.0382 data: 0.0010 max mem: 33300 +Test: [ 7300/21770] eta: 0:09:17 time: 0.0381 data: 0.0010 max mem: 33300 +Test: [ 7400/21770] eta: 0:09:13 time: 0.0386 data: 0.0012 max mem: 33300 +Test: [ 7500/21770] eta: 0:09:09 time: 0.0387 data: 0.0012 max mem: 33300 +Test: [ 7600/21770] eta: 0:09:06 time: 0.0383 data: 0.0011 max mem: 33300 +Test: [ 7700/21770] eta: 0:09:02 time: 0.0383 data: 0.0011 max mem: 33300 +Test: [ 7800/21770] eta: 0:08:58 time: 0.0382 data: 0.0011 max mem: 33300 +Test: [ 7900/21770] eta: 0:08:54 time: 0.0383 data: 0.0011 max mem: 33300 +Test: [ 8000/21770] eta: 0:08:50 time: 0.0384 data: 0.0011 max mem: 33300 +Test: [ 8100/21770] eta: 0:08:46 time: 0.0383 data: 0.0011 max mem: 33300 +Test: [ 8200/21770] eta: 0:08:42 time: 0.0385 data: 0.0011 max mem: 33300 +Test: [ 8300/21770] eta: 0:08:38 time: 0.0381 data: 0.0010 max mem: 33300 +Test: [ 8400/21770] eta: 0:08:34 time: 0.0381 data: 0.0010 max mem: 33300 +Test: [ 8500/21770] eta: 0:08:30 time: 0.0382 data: 0.0010 max mem: 33300 +Test: [ 8600/21770] eta: 0:08:26 time: 0.0381 data: 0.0010 max mem: 33300 +Test: [ 8700/21770] eta: 0:08:23 time: 0.0379 data: 0.0010 max mem: 33300 +Test: [ 8800/21770] eta: 0:08:19 time: 0.0381 data: 0.0010 max mem: 33300 +Test: [ 8900/21770] eta: 0:08:15 time: 0.0380 data: 0.0010 max mem: 33300 +Test: [ 9000/21770] eta: 0:08:11 time: 0.0383 data: 0.0010 max mem: 33300 +Test: [ 9100/21770] eta: 0:08:07 time: 0.0384 data: 0.0010 max mem: 33300 +Test: [ 9200/21770] eta: 0:08:03 time: 0.0382 data: 0.0010 max mem: 33300 +Test: [ 9300/21770] eta: 0:07:59 time: 0.0384 data: 0.0010 max mem: 33300 +Test: [ 9400/21770] eta: 0:07:56 time: 0.0385 data: 0.0011 max mem: 33300 +Test: [ 9500/21770] eta: 0:07:52 time: 0.0383 data: 0.0010 max mem: 33300 +Test: [ 9600/21770] eta: 0:07:48 time: 0.0382 data: 0.0010 max mem: 33300 +Test: [ 9700/21770] eta: 0:07:44 time: 0.0384 data: 0.0010 max mem: 33300 +Test: [ 9800/21770] eta: 0:07:40 time: 0.0383 data: 0.0010 max mem: 33300 +Test: [ 9900/21770] eta: 0:07:36 time: 0.0384 data: 0.0010 max mem: 33300 +Test: [10000/21770] eta: 0:07:32 time: 0.0386 data: 0.0010 max mem: 33300 +Test: [10100/21770] eta: 0:07:29 time: 0.0383 data: 0.0010 max mem: 33300 +Test: [10200/21770] eta: 0:07:25 time: 0.0381 data: 0.0010 max mem: 33300 +Test: [10300/21770] eta: 0:07:21 time: 0.0381 data: 0.0010 max mem: 33300 +Test: [10400/21770] eta: 0:07:17 time: 0.0382 data: 0.0010 max mem: 33300 +Test: [10500/21770] eta: 0:07:13 time: 0.0381 data: 0.0010 max mem: 33300 +Test: [10600/21770] eta: 0:07:09 time: 0.0386 data: 0.0010 max mem: 33300 +Test: [10700/21770] eta: 0:07:05 time: 0.0387 data: 0.0011 max mem: 33300 +Test: [10800/21770] eta: 0:07:01 time: 0.0382 data: 0.0010 max mem: 33300 +Test: [10900/21770] eta: 0:06:58 time: 0.0383 data: 0.0010 max mem: 33300 +Test: [11000/21770] eta: 0:06:54 time: 0.0381 data: 0.0010 max mem: 33300 +Test: [11100/21770] eta: 0:06:50 time: 0.0383 data: 0.0010 max mem: 33300 +Test: [11200/21770] eta: 0:06:46 time: 0.0388 data: 0.0010 max mem: 33300 +Test: [11300/21770] eta: 0:06:42 time: 0.0389 data: 0.0010 max mem: 33300 +Test: [11400/21770] eta: 0:06:38 time: 0.0391 data: 0.0010 max mem: 33300 +Test: [11500/21770] eta: 0:06:35 time: 0.0389 data: 0.0010 max mem: 33300 +Test: [11600/21770] eta: 0:06:31 time: 0.0389 data: 0.0011 max mem: 33300 +Test: [11700/21770] eta: 0:06:27 time: 0.0389 data: 0.0010 max mem: 33300 +Test: [11800/21770] eta: 0:06:23 time: 0.0386 data: 0.0010 max mem: 33300 +Test: [11900/21770] eta: 0:06:19 time: 0.0399 data: 0.0010 max mem: 33300 +Test: [12000/21770] eta: 0:06:16 time: 0.0396 data: 0.0010 max mem: 33300 +Test: [12100/21770] eta: 0:06:12 time: 0.0387 data: 0.0011 max mem: 33300 +Test: [12200/21770] eta: 0:06:08 time: 0.0387 data: 0.0011 max mem: 33300 +Test: [12300/21770] eta: 0:06:04 time: 0.0390 data: 0.0010 max mem: 33300 +Test: [12400/21770] eta: 0:06:00 time: 0.0387 data: 0.0010 max mem: 33300 +Test: [12500/21770] eta: 0:05:57 time: 0.0391 data: 0.0010 max mem: 33300 +Test: [12600/21770] eta: 0:05:53 time: 0.0394 data: 0.0011 max mem: 33300 +Test: [12700/21770] eta: 0:05:49 time: 0.0391 data: 0.0010 max mem: 33300 +Test: [12800/21770] eta: 0:05:45 time: 0.0389 data: 0.0011 max mem: 33300 +Test: [12900/21770] eta: 0:05:41 time: 0.0400 data: 0.0012 max mem: 33300 +Test: [13000/21770] eta: 0:05:37 time: 0.0395 data: 0.0011 max mem: 33300 +Test: [13100/21770] eta: 0:05:34 time: 0.0394 data: 0.0010 max mem: 33300 +Test: [13200/21770] eta: 0:05:30 time: 0.0390 data: 0.0009 max mem: 33300 +Test: [13300/21770] eta: 0:05:26 time: 0.0390 data: 0.0009 max mem: 33300 +Test: [13400/21770] eta: 0:05:22 time: 0.0388 data: 0.0009 max mem: 33300 +Test: [13500/21770] eta: 0:05:18 time: 0.0386 data: 0.0009 max mem: 33300 +Test: [13600/21770] eta: 0:05:15 time: 0.0383 data: 0.0010 max mem: 33300 +Test: [13700/21770] eta: 0:05:11 time: 0.0387 data: 0.0010 max mem: 33300 +Test: [13800/21770] eta: 0:05:07 time: 0.0387 data: 0.0010 max mem: 33300 +Test: [13900/21770] eta: 0:05:03 time: 0.0387 data: 0.0010 max mem: 33300 +Test: [14000/21770] eta: 0:04:59 time: 0.0386 data: 0.0010 max mem: 33300 +Test: [14100/21770] eta: 0:04:55 time: 0.0389 data: 0.0010 max mem: 33300 +Test: [14200/21770] eta: 0:04:51 time: 0.0384 data: 0.0010 max mem: 33300 +Test: [14300/21770] eta: 0:04:48 time: 0.0390 data: 0.0010 max mem: 33300 +Test: [14400/21770] eta: 0:04:44 time: 0.0387 data: 0.0010 max mem: 33300 +Test: [14500/21770] eta: 0:04:40 time: 0.0390 data: 0.0010 max mem: 33300 +Test: [14600/21770] eta: 0:04:36 time: 0.0393 data: 0.0012 max mem: 33300 +Test: [14700/21770] eta: 0:04:32 time: 0.0399 data: 0.0011 max mem: 33300 +Test: [14800/21770] eta: 0:04:28 time: 0.0386 data: 0.0011 max mem: 33300 +Test: [14900/21770] eta: 0:04:25 time: 0.0388 data: 0.0011 max mem: 33300 +Test: [15000/21770] eta: 0:04:21 time: 0.0389 data: 0.0012 max mem: 33300 +Test: [15100/21770] eta: 0:04:17 time: 0.0399 data: 0.0011 max mem: 33300 +Test: [15200/21770] eta: 0:04:13 time: 0.0399 data: 0.0010 max mem: 33300 +Test: [15300/21770] eta: 0:04:09 time: 0.0399 data: 0.0010 max mem: 33300 +Test: [15400/21770] eta: 0:04:05 time: 0.0385 data: 0.0010 max mem: 33300 +Test: [15500/21770] eta: 0:04:02 time: 0.0387 data: 0.0011 max mem: 33300 +Test: [15600/21770] eta: 0:03:58 time: 0.0401 data: 0.0010 max mem: 33300 +Test: [15700/21770] eta: 0:03:54 time: 0.0394 data: 0.0010 max mem: 33300 +Test: [15800/21770] eta: 0:03:50 time: 0.0399 data: 0.0010 max mem: 33300 +Test: [15900/21770] eta: 0:03:46 time: 0.0390 data: 0.0010 max mem: 33300 +Test: [16000/21770] eta: 0:03:42 time: 0.0387 data: 0.0010 max mem: 33300 +Test: [16100/21770] eta: 0:03:39 time: 0.0396 data: 0.0010 max mem: 33300 +Test: [16200/21770] eta: 0:03:35 time: 0.0390 data: 0.0009 max mem: 33300 +Test: [16300/21770] eta: 0:03:31 time: 0.0391 data: 0.0010 max mem: 33300 +Test: [16400/21770] eta: 0:03:27 time: 0.0392 data: 0.0010 max mem: 33300 +Test: [16500/21770] eta: 0:03:23 time: 0.0394 data: 0.0010 max mem: 33300 +Test: [16600/21770] eta: 0:03:19 time: 0.0394 data: 0.0010 max mem: 33300 +Test: [16700/21770] eta: 0:03:16 time: 0.0389 data: 0.0011 max mem: 33300 +Test: [16800/21770] eta: 0:03:12 time: 0.0388 data: 0.0011 max mem: 33300 +Test: [16900/21770] eta: 0:03:08 time: 0.0388 data: 0.0011 max mem: 33300 +Test: [17000/21770] eta: 0:03:04 time: 0.0386 data: 0.0011 max mem: 33300 +Test: [17100/21770] eta: 0:03:00 time: 0.0387 data: 0.0010 max mem: 33300 +Test: [17200/21770] eta: 0:02:56 time: 0.0390 data: 0.0011 max mem: 33300 +Test: [17300/21770] eta: 0:02:52 time: 0.0382 data: 0.0011 max mem: 33300 +Test: [17400/21770] eta: 0:02:48 time: 0.0386 data: 0.0011 max mem: 33300 +Test: [17500/21770] eta: 0:02:45 time: 0.0399 data: 0.0010 max mem: 33300 +Test: [17600/21770] eta: 0:02:41 time: 0.0396 data: 0.0011 max mem: 33300 +Test: [17700/21770] eta: 0:02:37 time: 0.0391 data: 0.0010 max mem: 33300 +Test: [17800/21770] eta: 0:02:33 time: 0.0382 data: 0.0011 max mem: 33300 +Test: [17900/21770] eta: 0:02:29 time: 0.0383 data: 0.0011 max mem: 33300 +Test: [18000/21770] eta: 0:02:25 time: 0.0386 data: 0.0009 max mem: 33300 +Test: [18100/21770] eta: 0:02:21 time: 0.0390 data: 0.0010 max mem: 33300 +Test: [18200/21770] eta: 0:02:18 time: 0.0390 data: 0.0010 max mem: 33300 +Test: [18300/21770] eta: 0:02:14 time: 0.0387 data: 0.0010 max mem: 33300 +Test: [18400/21770] eta: 0:02:10 time: 0.0387 data: 0.0010 max mem: 33300 +Test: [18500/21770] eta: 0:02:06 time: 0.0386 data: 0.0009 max mem: 33300 +Test: [18600/21770] eta: 0:02:02 time: 0.0388 data: 0.0010 max mem: 33300 +Test: [18700/21770] eta: 0:01:58 time: 0.0384 data: 0.0009 max mem: 33300 +Test: [18800/21770] eta: 0:01:54 time: 0.0384 data: 0.0010 max mem: 33300 +Test: [18900/21770] eta: 0:01:50 time: 0.0384 data: 0.0009 max mem: 33300 +Test: [19000/21770] eta: 0:01:47 time: 0.0385 data: 0.0010 max mem: 33300 +Test: [19100/21770] eta: 0:01:43 time: 0.0386 data: 0.0010 max mem: 33300 +Test: [19200/21770] eta: 0:01:39 time: 0.0384 data: 0.0010 max mem: 33300 +Test: [19300/21770] eta: 0:01:35 time: 0.0387 data: 0.0010 max mem: 33300 +Test: [19400/21770] eta: 0:01:31 time: 0.0384 data: 0.0010 max mem: 33300 +Test: [19500/21770] eta: 0:01:27 time: 0.0387 data: 0.0010 max mem: 33300 +Test: [19600/21770] eta: 0:01:23 time: 0.0386 data: 0.0010 max mem: 33300 +Test: [19700/21770] eta: 0:01:20 time: 0.0386 data: 0.0010 max mem: 33300 +Test: [19800/21770] eta: 0:01:16 time: 0.0386 data: 0.0009 max mem: 33300 +Test: [19900/21770] eta: 0:01:12 time: 0.0387 data: 0.0010 max mem: 33300 +Test: [20000/21770] eta: 0:01:08 time: 0.0380 data: 0.0010 max mem: 33300 +Test: [20100/21770] eta: 0:01:04 time: 0.0381 data: 0.0010 max mem: 33300 +Test: [20200/21770] eta: 0:01:00 time: 0.0385 data: 0.0009 max mem: 33300 +Test: [20300/21770] eta: 0:00:56 time: 0.0382 data: 0.0010 max mem: 33300 +Test: [20400/21770] eta: 0:00:52 time: 0.0380 data: 0.0009 max mem: 33300 +Test: [20500/21770] eta: 0:00:49 time: 0.0389 data: 0.0011 max mem: 33300 +Test: [20600/21770] eta: 0:00:45 time: 0.0386 data: 0.0011 max mem: 33300 +Test: [20700/21770] eta: 0:00:41 time: 0.0388 data: 0.0010 max mem: 33300 +Test: [20800/21770] eta: 0:00:37 time: 0.0386 data: 0.0010 max mem: 33300 +Test: [20900/21770] eta: 0:00:33 time: 0.0388 data: 0.0011 max mem: 33300 +Test: [21000/21770] eta: 0:00:29 time: 0.0386 data: 0.0010 max mem: 33300 +Test: [21100/21770] eta: 0:00:25 time: 0.0388 data: 0.0010 max mem: 33300 +Test: [21200/21770] eta: 0:00:22 time: 0.0387 data: 0.0010 max mem: 33300 +Test: [21300/21770] eta: 0:00:18 time: 0.0393 data: 0.0011 max mem: 33300 +Test: [21400/21770] eta: 0:00:14 time: 0.0396 data: 0.0010 max mem: 33300 +Test: [21500/21770] eta: 0:00:10 time: 0.0389 data: 0.0009 max mem: 33300 +Test: [21600/21770] eta: 0:00:06 time: 0.0392 data: 0.0009 max mem: 33300 +Test: [21700/21770] eta: 0:00:02 time: 0.0391 data: 0.0010 max mem: 33300 +Test: Total time: 0:14:02 +Final results: +Mean IoU is 0.00 + + precision@0.5 = 0.00 + precision@0.6 = 0.00 + precision@0.7 = 0.00 + precision@0.8 = 0.00 + precision@0.9 = 0.00 + overall IoU = 0.00 + mean IoU = 0.00 + +Mean accuracy for one-to-zero sample is 100.00 + +Average object IoU 0.0 +Overall IoU 0.0 +Epoch: [13] [ 0/4276] eta: 6:45:28 lr: 3.510265893189975e-05 loss: 0.1308 (0.1308) time: 5.6896 data: 2.5855 max mem: 33300 +Epoch: [13] [ 10/4276] eta: 3:54:40 lr: 3.509992248701277e-05 loss: 0.1399 (0.1545) time: 3.3006 data: 0.2416 max mem: 33300 +Epoch: [13] [ 20/4276] eta: 3:45:49 lr: 3.509718601842141e-05 loss: 0.1438 (0.1545) time: 3.0583 data: 0.0073 max mem: 33300 +Epoch: [13] [ 30/4276] eta: 3:41:32 lr: 3.5094449526123424e-05 loss: 0.1474 (0.1553) time: 3.0371 data: 0.0073 max mem: 33300 +Epoch: [13] [ 40/4276] eta: 3:39:13 lr: 3.509171301011654e-05 loss: 0.1544 (0.1551) time: 3.0230 data: 0.0077 max mem: 33300 +Epoch: [13] [ 50/4276] eta: 3:37:41 lr: 3.5088976470398504e-05 loss: 0.1541 (0.1519) time: 3.0290 data: 0.0083 max mem: 33300 +Epoch: [13] [ 60/4276] eta: 3:36:18 lr: 3.508623990696705e-05 loss: 0.1361 (0.1524) time: 3.0234 data: 0.0085 max mem: 33300 +Epoch: [13] [ 70/4276] eta: 3:35:14 lr: 3.508350331981993e-05 loss: 0.1414 (0.1515) time: 3.0191 data: 0.0083 max mem: 33300 +Epoch: [13] [ 80/4276] eta: 3:34:15 lr: 3.5080766708954866e-05 loss: 0.1516 (0.1521) time: 3.0187 data: 0.0084 max mem: 33300 +Epoch: [13] [ 90/4276] eta: 3:33:04 lr: 3.507803007436961e-05 loss: 0.1372 (0.1499) time: 2.9960 data: 0.0084 max mem: 33300 +Epoch: [13] [ 100/4276] eta: 3:31:59 lr: 3.50752934160619e-05 loss: 0.1346 (0.1517) time: 2.9741 data: 0.0083 max mem: 33300 +Epoch: [13] [ 110/4276] eta: 3:31:17 lr: 3.507255673402947e-05 loss: 0.1505 (0.1526) time: 2.9923 data: 0.0087 max mem: 33300 +Epoch: [13] [ 120/4276] eta: 3:30:35 lr: 3.506982002827006e-05 loss: 0.1470 (0.1517) time: 3.0116 data: 0.0090 max mem: 33300 +Epoch: [13] [ 130/4276] eta: 3:29:55 lr: 3.506708329878139e-05 loss: 0.1470 (0.1525) time: 3.0093 data: 0.0088 max mem: 33300 +Epoch: [13] [ 140/4276] eta: 3:29:22 lr: 3.5064346545561224e-05 loss: 0.1441 (0.1517) time: 3.0197 data: 0.0085 max mem: 33300 +Epoch: [13] [ 150/4276] eta: 3:28:48 lr: 3.506160976860728e-05 loss: 0.1347 (0.1515) time: 3.0271 data: 0.0086 max mem: 33300 +Epoch: [13] [ 160/4276] eta: 3:28:13 lr: 3.5058872967917296e-05 loss: 0.1381 (0.1515) time: 3.0221 data: 0.0084 max mem: 33300 +Epoch: [13] [ 170/4276] eta: 3:27:40 lr: 3.505613614348902e-05 loss: 0.1381 (0.1512) time: 3.0204 data: 0.0082 max mem: 33300 +Epoch: [13] [ 180/4276] eta: 3:27:13 lr: 3.505339929532017e-05 loss: 0.1359 (0.1508) time: 3.0361 data: 0.0078 max mem: 33300 +Epoch: [13] [ 190/4276] eta: 3:26:38 lr: 3.505066242340849e-05 loss: 0.1348 (0.1509) time: 3.0319 data: 0.0078 max mem: 33300 +Epoch: [13] [ 200/4276] eta: 3:26:10 lr: 3.5047925527751706e-05 loss: 0.1485 (0.1512) time: 3.0303 data: 0.0084 max mem: 33300 +Epoch: [13] [ 210/4276] eta: 3:25:40 lr: 3.504518860834756e-05 loss: 0.1564 (0.1512) time: 3.0423 data: 0.0086 max mem: 33300 +Epoch: [13] [ 220/4276] eta: 3:25:09 lr: 3.504245166519378e-05 loss: 0.1455 (0.1509) time: 3.0327 data: 0.0080 max mem: 33300 +Epoch: [13] [ 230/4276] eta: 3:24:28 lr: 3.503971469828811e-05 loss: 0.1332 (0.1500) time: 3.0026 data: 0.0078 max mem: 33300 +Epoch: [13] [ 240/4276] eta: 3:23:56 lr: 3.5036977707628265e-05 loss: 0.1387 (0.1501) time: 2.9986 data: 0.0085 max mem: 33300 +Epoch: [13] [ 250/4276] eta: 3:23:22 lr: 3.5034240693211995e-05 loss: 0.1592 (0.1508) time: 3.0166 data: 0.0087 max mem: 33300 +Epoch: [13] [ 260/4276] eta: 3:22:51 lr: 3.503150365503701e-05 loss: 0.1664 (0.1510) time: 3.0169 data: 0.0080 max mem: 33300 +Epoch: [13] [ 270/4276] eta: 3:22:20 lr: 3.502876659310107e-05 loss: 0.1391 (0.1507) time: 3.0267 data: 0.0078 max mem: 33300 +Epoch: [13] [ 280/4276] eta: 3:21:54 lr: 3.502602950740188e-05 loss: 0.1378 (0.1510) time: 3.0434 data: 0.0082 max mem: 33300 +Epoch: [13] [ 290/4276] eta: 3:21:24 lr: 3.502329239793718e-05 loss: 0.1378 (0.1504) time: 3.0450 data: 0.0080 max mem: 33300 +Epoch: [13] [ 300/4276] eta: 3:20:56 lr: 3.50205552647047e-05 loss: 0.1356 (0.1503) time: 3.0441 data: 0.0076 max mem: 33300 +Epoch: [13] [ 310/4276] eta: 3:20:25 lr: 3.501781810770216e-05 loss: 0.1380 (0.1500) time: 3.0395 data: 0.0078 max mem: 33300 +Epoch: [13] [ 320/4276] eta: 3:19:54 lr: 3.5015080926927305e-05 loss: 0.1409 (0.1501) time: 3.0248 data: 0.0080 max mem: 33300 +Epoch: [13] [ 330/4276] eta: 3:19:21 lr: 3.501234372237787e-05 loss: 0.1474 (0.1502) time: 3.0189 data: 0.0082 max mem: 33300 +Epoch: [13] [ 340/4276] eta: 3:18:50 lr: 3.500960649405156e-05 loss: 0.1429 (0.1500) time: 3.0197 data: 0.0082 max mem: 33300 +Epoch: [13] [ 350/4276] eta: 3:18:19 lr: 3.500686924194611e-05 loss: 0.1342 (0.1499) time: 3.0245 data: 0.0078 max mem: 33300 +Epoch: [13] [ 360/4276] eta: 3:17:48 lr: 3.500413196605925e-05 loss: 0.1502 (0.1505) time: 3.0218 data: 0.0075 max mem: 33300 +Epoch: [13] [ 370/4276] eta: 3:17:17 lr: 3.500139466638871e-05 loss: 0.1432 (0.1499) time: 3.0251 data: 0.0077 max mem: 33300 +Epoch: [13] [ 380/4276] eta: 3:16:48 lr: 3.4998657342932215e-05 loss: 0.1415 (0.1500) time: 3.0340 data: 0.0077 max mem: 33300 +Epoch: [13] [ 390/4276] eta: 3:16:17 lr: 3.499591999568749e-05 loss: 0.1416 (0.1500) time: 3.0304 data: 0.0075 max mem: 33300 +Epoch: [13] [ 400/4276] eta: 3:15:48 lr: 3.4993182624652266e-05 loss: 0.1416 (0.1499) time: 3.0369 data: 0.0079 max mem: 33300 +Epoch: [13] [ 410/4276] eta: 3:15:15 lr: 3.4990445229824256e-05 loss: 0.1494 (0.1498) time: 3.0241 data: 0.0081 max mem: 33300 +Epoch: [13] [ 420/4276] eta: 3:14:40 lr: 3.498770781120121e-05 loss: 0.1460 (0.1499) time: 2.9874 data: 0.0081 max mem: 33300 +Epoch: [13] [ 430/4276] eta: 3:14:04 lr: 3.4984970368780814e-05 loss: 0.1374 (0.1498) time: 2.9716 data: 0.0076 max mem: 33300 +Epoch: [13] [ 440/4276] eta: 3:13:29 lr: 3.498223290256082e-05 loss: 0.1397 (0.1496) time: 2.9688 data: 0.0071 max mem: 33300 +Epoch: [13] [ 450/4276] eta: 3:12:57 lr: 3.4979495412538946e-05 loss: 0.1366 (0.1496) time: 2.9913 data: 0.0079 max mem: 33300 +Epoch: [13] [ 460/4276] eta: 3:12:27 lr: 3.497675789871291e-05 loss: 0.1347 (0.1492) time: 3.0179 data: 0.0086 max mem: 33300 +Epoch: [13] [ 470/4276] eta: 3:11:58 lr: 3.497402036108044e-05 loss: 0.1327 (0.1488) time: 3.0360 data: 0.0087 max mem: 33300 +Epoch: [13] [ 480/4276] eta: 3:11:28 lr: 3.4971282799639264e-05 loss: 0.1374 (0.1486) time: 3.0353 data: 0.0089 max mem: 33300 +Epoch: [13] [ 490/4276] eta: 3:11:00 lr: 3.49685452143871e-05 loss: 0.1292 (0.1481) time: 3.0398 data: 0.0090 max mem: 33300 +Epoch: [13] [ 500/4276] eta: 3:10:30 lr: 3.496580760532166e-05 loss: 0.1241 (0.1481) time: 3.0456 data: 0.0087 max mem: 33300 +Epoch: [13] [ 510/4276] eta: 3:10:00 lr: 3.4963069972440674e-05 loss: 0.1307 (0.1478) time: 3.0324 data: 0.0082 max mem: 33300 +Epoch: [13] [ 520/4276] eta: 3:09:30 lr: 3.496033231574187e-05 loss: 0.1307 (0.1478) time: 3.0300 data: 0.0085 max mem: 33300 +Epoch: [13] [ 530/4276] eta: 3:09:01 lr: 3.495759463522294e-05 loss: 0.1396 (0.1477) time: 3.0377 data: 0.0092 max mem: 33300 +Epoch: [13] [ 540/4276] eta: 3:08:35 lr: 3.495485693088164e-05 loss: 0.1413 (0.1475) time: 3.0709 data: 0.0093 max mem: 33300 +Epoch: [13] [ 550/4276] eta: 3:08:11 lr: 3.495211920271567e-05 loss: 0.1517 (0.1478) time: 3.1073 data: 0.0091 max mem: 33300 +Epoch: [13] [ 560/4276] eta: 3:07:46 lr: 3.4949381450722754e-05 loss: 0.1625 (0.1479) time: 3.1170 data: 0.0092 max mem: 33300 +Epoch: [13] [ 570/4276] eta: 3:07:23 lr: 3.494664367490061e-05 loss: 0.1533 (0.1478) time: 3.1287 data: 0.0090 max mem: 33300 +Epoch: [13] [ 580/4276] eta: 3:06:59 lr: 3.494390587524696e-05 loss: 0.1422 (0.1479) time: 3.1321 data: 0.0082 max mem: 33300 +Epoch: [13] [ 590/4276] eta: 3:06:34 lr: 3.494116805175951e-05 loss: 0.1166 (0.1475) time: 3.1228 data: 0.0078 max mem: 33300 +Epoch: [13] [ 600/4276] eta: 3:06:08 lr: 3.493843020443598e-05 loss: 0.1225 (0.1476) time: 3.1182 data: 0.0084 max mem: 33300 +Epoch: [13] [ 610/4276] eta: 3:05:43 lr: 3.49356923332741e-05 loss: 0.1362 (0.1474) time: 3.1203 data: 0.0086 max mem: 33300 +Epoch: [13] [ 620/4276] eta: 3:05:17 lr: 3.493295443827158e-05 loss: 0.1362 (0.1474) time: 3.1184 data: 0.0082 max mem: 33300 +Epoch: [13] [ 630/4276] eta: 3:04:50 lr: 3.4930216519426126e-05 loss: 0.1403 (0.1475) time: 3.1085 data: 0.0082 max mem: 33300 +Epoch: [13] [ 640/4276] eta: 3:04:23 lr: 3.492747857673547e-05 loss: 0.1398 (0.1474) time: 3.1021 data: 0.0087 max mem: 33300 +Epoch: [13] [ 650/4276] eta: 3:03:56 lr: 3.492474061019732e-05 loss: 0.1398 (0.1475) time: 3.1033 data: 0.0087 max mem: 33300 +Epoch: [13] [ 660/4276] eta: 3:03:31 lr: 3.4922002619809394e-05 loss: 0.1517 (0.1476) time: 3.1269 data: 0.0082 max mem: 33300 +Epoch: [13] [ 670/4276] eta: 3:03:04 lr: 3.4919264605569405e-05 loss: 0.1445 (0.1476) time: 3.1298 data: 0.0076 max mem: 33300 +Epoch: [13] [ 680/4276] eta: 3:02:37 lr: 3.491652656747506e-05 loss: 0.1382 (0.1475) time: 3.1120 data: 0.0074 max mem: 33300 +Epoch: [13] [ 690/4276] eta: 3:02:09 lr: 3.4913788505524074e-05 loss: 0.1334 (0.1474) time: 3.1038 data: 0.0073 max mem: 33300 +Epoch: [13] [ 700/4276] eta: 3:01:42 lr: 3.491105041971417e-05 loss: 0.1392 (0.1474) time: 3.1062 data: 0.0072 max mem: 33300 +Epoch: [13] [ 710/4276] eta: 3:01:15 lr: 3.490831231004306e-05 loss: 0.1438 (0.1474) time: 3.1157 data: 0.0072 max mem: 33300 +Epoch: [13] [ 720/4276] eta: 3:00:47 lr: 3.490557417650844e-05 loss: 0.1430 (0.1472) time: 3.1019 data: 0.0072 max mem: 33300 +Epoch: [13] [ 730/4276] eta: 3:00:19 lr: 3.4902836019108046e-05 loss: 0.1398 (0.1472) time: 3.0948 data: 0.0072 max mem: 33300 +Epoch: [13] [ 740/4276] eta: 2:59:51 lr: 3.490009783783958e-05 loss: 0.1393 (0.1472) time: 3.1078 data: 0.0073 max mem: 33300 +Epoch: [13] [ 750/4276] eta: 2:59:24 lr: 3.489735963270074e-05 loss: 0.1393 (0.1472) time: 3.1200 data: 0.0075 max mem: 33300 +Epoch: [13] [ 760/4276] eta: 2:58:57 lr: 3.4894621403689256e-05 loss: 0.1303 (0.1472) time: 3.1315 data: 0.0076 max mem: 33300 +Epoch: [13] [ 770/4276] eta: 2:58:30 lr: 3.489188315080282e-05 loss: 0.1303 (0.1473) time: 3.1255 data: 0.0074 max mem: 33300 +Epoch: [13] [ 780/4276] eta: 2:58:01 lr: 3.488914487403916e-05 loss: 0.1443 (0.1474) time: 3.1103 data: 0.0074 max mem: 33300 +Epoch: [13] [ 790/4276] eta: 2:57:30 lr: 3.488640657339598e-05 loss: 0.1487 (0.1474) time: 3.0710 data: 0.0072 max mem: 33300 +Epoch: [13] [ 800/4276] eta: 2:57:02 lr: 3.4883668248870984e-05 loss: 0.1446 (0.1474) time: 3.0721 data: 0.0072 max mem: 33300 +Epoch: [13] [ 810/4276] eta: 2:56:33 lr: 3.488092990046188e-05 loss: 0.1405 (0.1475) time: 3.1028 data: 0.0073 max mem: 33300 +Epoch: [13] [ 820/4276] eta: 2:56:04 lr: 3.487819152816639e-05 loss: 0.1402 (0.1472) time: 3.0931 data: 0.0072 max mem: 33300 +Epoch: [13] [ 830/4276] eta: 2:55:35 lr: 3.48754531319822e-05 loss: 0.1310 (0.1473) time: 3.0894 data: 0.0070 max mem: 33300 +Epoch: [13] [ 840/4276] eta: 2:55:05 lr: 3.487271471190703e-05 loss: 0.1376 (0.1473) time: 3.0890 data: 0.0072 max mem: 33300 +Epoch: [13] [ 850/4276] eta: 2:54:38 lr: 3.486997626793859e-05 loss: 0.1310 (0.1470) time: 3.1083 data: 0.0073 max mem: 33300 +Epoch: [13] [ 860/4276] eta: 2:54:10 lr: 3.486723780007458e-05 loss: 0.1335 (0.1471) time: 3.1312 data: 0.0072 max mem: 33300 +Epoch: [13] [ 870/4276] eta: 2:53:42 lr: 3.486449930831271e-05 loss: 0.1379 (0.1471) time: 3.1278 data: 0.0070 max mem: 33300 +Epoch: [13] [ 880/4276] eta: 2:53:13 lr: 3.4861760792650684e-05 loss: 0.1374 (0.1472) time: 3.1190 data: 0.0071 max mem: 33300 +Epoch: [13] [ 890/4276] eta: 2:52:44 lr: 3.4859022253086214e-05 loss: 0.1594 (0.1473) time: 3.1028 data: 0.0073 max mem: 33300 +Epoch: [13] [ 900/4276] eta: 2:52:13 lr: 3.485628368961699e-05 loss: 0.1552 (0.1473) time: 3.0795 data: 0.0073 max mem: 33300 +Epoch: [13] [ 910/4276] eta: 2:51:42 lr: 3.485354510224073e-05 loss: 0.1484 (0.1473) time: 3.0577 data: 0.0072 max mem: 33300 +Epoch: [13] [ 920/4276] eta: 2:51:13 lr: 3.485080649095513e-05 loss: 0.1484 (0.1474) time: 3.0654 data: 0.0075 max mem: 33300 +Epoch: [13] [ 930/4276] eta: 2:50:43 lr: 3.48480678557579e-05 loss: 0.1469 (0.1474) time: 3.0874 data: 0.0074 max mem: 33300 +Epoch: [13] [ 940/4276] eta: 2:50:12 lr: 3.484532919664674e-05 loss: 0.1378 (0.1473) time: 3.0635 data: 0.0071 max mem: 33300 +Epoch: [13] [ 950/4276] eta: 2:49:44 lr: 3.484259051361935e-05 loss: 0.1430 (0.1475) time: 3.0897 data: 0.0071 max mem: 33300 +Epoch: [13] [ 960/4276] eta: 2:49:15 lr: 3.483985180667344e-05 loss: 0.1475 (0.1476) time: 3.1250 data: 0.0072 max mem: 33300 +Epoch: [13] [ 970/4276] eta: 2:48:47 lr: 3.4837113075806706e-05 loss: 0.1441 (0.1476) time: 3.1201 data: 0.0073 max mem: 33300 +Epoch: [13] [ 980/4276] eta: 2:48:17 lr: 3.483437432101685e-05 loss: 0.1438 (0.1476) time: 3.1143 data: 0.0072 max mem: 33300 +Epoch: [13] [ 990/4276] eta: 2:47:47 lr: 3.483163554230157e-05 loss: 0.1438 (0.1475) time: 3.0874 data: 0.0072 max mem: 33300 +Epoch: [13] [1000/4276] eta: 2:47:16 lr: 3.4828896739658575e-05 loss: 0.1239 (0.1475) time: 3.0650 data: 0.0071 max mem: 33300 +Epoch: [13] [1010/4276] eta: 2:46:45 lr: 3.4826157913085564e-05 loss: 0.1403 (0.1475) time: 3.0484 data: 0.0070 max mem: 33300 +Epoch: [13] [1020/4276] eta: 2:46:15 lr: 3.4823419062580225e-05 loss: 0.1403 (0.1474) time: 3.0684 data: 0.0071 max mem: 33300 +Epoch: [13] [1030/4276] eta: 2:45:44 lr: 3.482068018814028e-05 loss: 0.1323 (0.1474) time: 3.0804 data: 0.0072 max mem: 33300 +Epoch: [13] [1040/4276] eta: 2:45:14 lr: 3.48179412897634e-05 loss: 0.1357 (0.1473) time: 3.0644 data: 0.0072 max mem: 33300 +Epoch: [13] [1050/4276] eta: 2:44:43 lr: 3.48152023674473e-05 loss: 0.1368 (0.1474) time: 3.0683 data: 0.0072 max mem: 33300 +Epoch: [13] [1060/4276] eta: 2:44:14 lr: 3.4812463421189686e-05 loss: 0.1525 (0.1475) time: 3.0857 data: 0.0071 max mem: 33300 +Epoch: [13] [1070/4276] eta: 2:43:45 lr: 3.480972445098824e-05 loss: 0.1510 (0.1476) time: 3.1117 data: 0.0073 max mem: 33300 +Epoch: [13] [1080/4276] eta: 2:43:14 lr: 3.480698545684066e-05 loss: 0.1510 (0.1475) time: 3.0888 data: 0.0072 max mem: 33300 +Epoch: [13] [1090/4276] eta: 2:42:44 lr: 3.480424643874465e-05 loss: 0.1526 (0.1476) time: 3.0741 data: 0.0070 max mem: 33300 +Epoch: [13] [1100/4276] eta: 2:42:14 lr: 3.480150739669791e-05 loss: 0.1452 (0.1476) time: 3.0954 data: 0.0071 max mem: 33300 +Epoch: [13] [1110/4276] eta: 2:41:45 lr: 3.4798768330698124e-05 loss: 0.1393 (0.1476) time: 3.0946 data: 0.0071 max mem: 33300 +Epoch: [13] [1120/4276] eta: 2:41:15 lr: 3.4796029240743e-05 loss: 0.1358 (0.1476) time: 3.0925 data: 0.0072 max mem: 33300 +Epoch: [13] [1130/4276] eta: 2:40:44 lr: 3.4793290126830225e-05 loss: 0.1300 (0.1474) time: 3.0775 data: 0.0072 max mem: 33300 +Epoch: [13] [1140/4276] eta: 2:40:14 lr: 3.4790550988957494e-05 loss: 0.1251 (0.1472) time: 3.0838 data: 0.0071 max mem: 33300 +Epoch: [13] [1150/4276] eta: 2:39:45 lr: 3.47878118271225e-05 loss: 0.1288 (0.1472) time: 3.1062 data: 0.0071 max mem: 33300 +Epoch: [13] [1160/4276] eta: 2:39:15 lr: 3.478507264132295e-05 loss: 0.1447 (0.1472) time: 3.1061 data: 0.0072 max mem: 33300 +Epoch: [13] [1170/4276] eta: 2:38:45 lr: 3.478233343155652e-05 loss: 0.1508 (0.1473) time: 3.0974 data: 0.0075 max mem: 33300 +Epoch: [13] [1180/4276] eta: 2:38:16 lr: 3.477959419782091e-05 loss: 0.1504 (0.1472) time: 3.1142 data: 0.0075 max mem: 33300 +Epoch: [13] [1190/4276] eta: 2:37:46 lr: 3.4776854940113814e-05 loss: 0.1389 (0.1471) time: 3.1157 data: 0.0072 max mem: 33300 +Epoch: [13] [1200/4276] eta: 2:37:16 lr: 3.4774115658432934e-05 loss: 0.1239 (0.1471) time: 3.0973 data: 0.0077 max mem: 33300 +Epoch: [13] [1210/4276] eta: 2:36:46 lr: 3.4771376352775946e-05 loss: 0.1276 (0.1470) time: 3.0962 data: 0.0078 max mem: 33300 +Epoch: [13] [1220/4276] eta: 2:36:17 lr: 3.4768637023140546e-05 loss: 0.1395 (0.1470) time: 3.1036 data: 0.0075 max mem: 33300 +Epoch: [13] [1230/4276] eta: 2:35:47 lr: 3.4765897669524424e-05 loss: 0.1405 (0.1470) time: 3.1072 data: 0.0077 max mem: 33300 +Epoch: [13] [1240/4276] eta: 2:35:17 lr: 3.476315829192527e-05 loss: 0.1459 (0.1470) time: 3.1006 data: 0.0082 max mem: 33300 +Epoch: [13] [1250/4276] eta: 2:34:47 lr: 3.476041889034078e-05 loss: 0.1490 (0.1471) time: 3.1038 data: 0.0083 max mem: 33300 +Epoch: [13] [1260/4276] eta: 2:34:18 lr: 3.475767946476864e-05 loss: 0.1433 (0.1469) time: 3.1230 data: 0.0082 max mem: 33300 +Epoch: [13] [1270/4276] eta: 2:33:49 lr: 3.475494001520654e-05 loss: 0.1447 (0.1470) time: 3.1232 data: 0.0079 max mem: 33300 +Epoch: [13] [1280/4276] eta: 2:33:19 lr: 3.475220054165218e-05 loss: 0.1534 (0.1470) time: 3.1138 data: 0.0080 max mem: 33300 +Epoch: [13] [1290/4276] eta: 2:32:49 lr: 3.474946104410322e-05 loss: 0.1504 (0.1471) time: 3.1086 data: 0.0081 max mem: 33300 +Epoch: [13] [1300/4276] eta: 2:32:19 lr: 3.4746721522557374e-05 loss: 0.1256 (0.1470) time: 3.1025 data: 0.0080 max mem: 33300 +Epoch: [13] [1310/4276] eta: 2:31:49 lr: 3.4743981977012314e-05 loss: 0.1245 (0.1470) time: 3.1038 data: 0.0082 max mem: 33300 +Epoch: [13] [1320/4276] eta: 2:31:19 lr: 3.4741242407465735e-05 loss: 0.1521 (0.1471) time: 3.1067 data: 0.0085 max mem: 33300 +Epoch: [13] [1330/4276] eta: 2:30:49 lr: 3.473850281391533e-05 loss: 0.1521 (0.1471) time: 3.1083 data: 0.0087 max mem: 33300 +Epoch: [13] [1340/4276] eta: 2:30:19 lr: 3.473576319635877e-05 loss: 0.1442 (0.1470) time: 3.1068 data: 0.0087 max mem: 33300 +Epoch: [13] [1350/4276] eta: 2:29:50 lr: 3.473302355479375e-05 loss: 0.1330 (0.1470) time: 3.1160 data: 0.0083 max mem: 33300 +Epoch: [13] [1360/4276] eta: 2:29:20 lr: 3.4730283889217955e-05 loss: 0.1420 (0.1470) time: 3.1215 data: 0.0084 max mem: 33300 +Epoch: [13] [1370/4276] eta: 2:28:50 lr: 3.472754419962907e-05 loss: 0.1423 (0.1470) time: 3.1242 data: 0.0081 max mem: 33300 +Epoch: [13] [1380/4276] eta: 2:28:20 lr: 3.472480448602477e-05 loss: 0.1569 (0.1472) time: 3.1120 data: 0.0076 max mem: 33300 +Epoch: [13] [1390/4276] eta: 2:27:50 lr: 3.472206474840275e-05 loss: 0.1611 (0.1473) time: 3.1005 data: 0.0078 max mem: 33300 +Epoch: [13] [1400/4276] eta: 2:27:20 lr: 3.471932498676069e-05 loss: 0.1567 (0.1473) time: 3.1111 data: 0.0080 max mem: 33300 +Epoch: [13] [1410/4276] eta: 2:26:50 lr: 3.4716585201096285e-05 loss: 0.1432 (0.1473) time: 3.1153 data: 0.0083 max mem: 33300 +Epoch: [13] [1420/4276] eta: 2:26:20 lr: 3.47138453914072e-05 loss: 0.1418 (0.1473) time: 3.1087 data: 0.0086 max mem: 33300 +Epoch: [13] [1430/4276] eta: 2:25:50 lr: 3.471110555769113e-05 loss: 0.1328 (0.1472) time: 3.1002 data: 0.0084 max mem: 33300 +Epoch: [13] [1440/4276] eta: 2:25:20 lr: 3.470836569994575e-05 loss: 0.1449 (0.1472) time: 3.0985 data: 0.0089 max mem: 33300 +Epoch: [13] [1450/4276] eta: 2:24:49 lr: 3.470562581816874e-05 loss: 0.1479 (0.1472) time: 3.1007 data: 0.0087 max mem: 33300 +Epoch: [13] [1460/4276] eta: 2:24:19 lr: 3.470288591235778e-05 loss: 0.1345 (0.1471) time: 3.1022 data: 0.0079 max mem: 33300 +Epoch: [13] [1470/4276] eta: 2:23:49 lr: 3.470014598251057e-05 loss: 0.1322 (0.1470) time: 3.1021 data: 0.0078 max mem: 33300 +Epoch: [13] [1480/4276] eta: 2:23:20 lr: 3.469740602862476e-05 loss: 0.1211 (0.1469) time: 3.1277 data: 0.0078 max mem: 33300 +Epoch: [13] [1490/4276] eta: 2:22:49 lr: 3.469466605069806e-05 loss: 0.1210 (0.1468) time: 3.1285 data: 0.0080 max mem: 33300 +Epoch: [13] [1500/4276] eta: 2:22:19 lr: 3.469192604872813e-05 loss: 0.1354 (0.1467) time: 3.1065 data: 0.0080 max mem: 33300 +Epoch: [13] [1510/4276] eta: 2:21:49 lr: 3.4689186022712655e-05 loss: 0.1316 (0.1466) time: 3.1168 data: 0.0078 max mem: 33300 +Epoch: [13] [1520/4276] eta: 2:21:20 lr: 3.468644597264931e-05 loss: 0.1197 (0.1466) time: 3.1287 data: 0.0078 max mem: 33300 +Epoch: [13] [1530/4276] eta: 2:20:49 lr: 3.468370589853577e-05 loss: 0.1205 (0.1464) time: 3.1220 data: 0.0080 max mem: 33300 +Epoch: [13] [1540/4276] eta: 2:20:20 lr: 3.468096580036973e-05 loss: 0.1363 (0.1465) time: 3.1186 data: 0.0077 max mem: 33300 +Epoch: [13] [1550/4276] eta: 2:19:50 lr: 3.467822567814885e-05 loss: 0.1576 (0.1466) time: 3.1323 data: 0.0075 max mem: 33300 +Epoch: [13] [1560/4276] eta: 2:19:20 lr: 3.467548553187081e-05 loss: 0.1493 (0.1465) time: 3.1315 data: 0.0079 max mem: 33300 +Epoch: [13] [1570/4276] eta: 2:18:49 lr: 3.46727453615333e-05 loss: 0.1484 (0.1466) time: 3.1116 data: 0.0082 max mem: 33300 +Epoch: [13] [1580/4276] eta: 2:18:19 lr: 3.467000516713397e-05 loss: 0.1281 (0.1465) time: 3.1003 data: 0.0084 max mem: 33300 +Epoch: [13] [1590/4276] eta: 2:17:49 lr: 3.466726494867053e-05 loss: 0.1373 (0.1464) time: 3.1060 data: 0.0084 max mem: 33300 +Epoch: [13] [1600/4276] eta: 2:17:18 lr: 3.466452470614062e-05 loss: 0.1401 (0.1464) time: 3.1085 data: 0.0083 max mem: 33300 +Epoch: [13] [1610/4276] eta: 2:16:48 lr: 3.466178443954194e-05 loss: 0.1352 (0.1463) time: 3.0927 data: 0.0080 max mem: 33300 +Epoch: [13] [1620/4276] eta: 2:16:18 lr: 3.465904414887215e-05 loss: 0.1291 (0.1462) time: 3.0994 data: 0.0081 max mem: 33300 +Epoch: [13] [1630/4276] eta: 2:15:48 lr: 3.4656303834128926e-05 loss: 0.1331 (0.1462) time: 3.1437 data: 0.0082 max mem: 33300 +Epoch: [13] [1640/4276] eta: 2:15:18 lr: 3.465356349530996e-05 loss: 0.1300 (0.1462) time: 3.1454 data: 0.0083 max mem: 33300 +Epoch: [13] [1650/4276] eta: 2:14:48 lr: 3.465082313241289e-05 loss: 0.1413 (0.1461) time: 3.1323 data: 0.0084 max mem: 33300 +Epoch: [13] [1660/4276] eta: 2:14:18 lr: 3.4648082745435427e-05 loss: 0.1424 (0.1462) time: 3.1252 data: 0.0079 max mem: 33300 +Epoch: [13] [1670/4276] eta: 2:13:48 lr: 3.4645342334375214e-05 loss: 0.1384 (0.1461) time: 3.1086 data: 0.0079 max mem: 33300 +Epoch: [13] [1680/4276] eta: 2:13:17 lr: 3.464260189922993e-05 loss: 0.1384 (0.1461) time: 3.1118 data: 0.0083 max mem: 33300 +Epoch: [13] [1690/4276] eta: 2:12:47 lr: 3.4639861439997255e-05 loss: 0.1411 (0.1461) time: 3.1102 data: 0.0085 max mem: 33300 +Epoch: [13] [1700/4276] eta: 2:12:16 lr: 3.463712095667485e-05 loss: 0.1436 (0.1461) time: 3.1071 data: 0.0090 max mem: 33300 +Epoch: [13] [1710/4276] eta: 2:11:46 lr: 3.4634380449260394e-05 loss: 0.1600 (0.1462) time: 3.1045 data: 0.0089 max mem: 33300 +Epoch: [13] [1720/4276] eta: 2:11:16 lr: 3.4631639917751554e-05 loss: 0.1501 (0.1462) time: 3.1056 data: 0.0088 max mem: 33300 +Epoch: [13] [1730/4276] eta: 2:10:46 lr: 3.4628899362145996e-05 loss: 0.1501 (0.1463) time: 3.1250 data: 0.0089 max mem: 33300 +Epoch: [13] [1740/4276] eta: 2:10:16 lr: 3.4626158782441395e-05 loss: 0.1504 (0.1463) time: 3.1364 data: 0.0082 max mem: 33300 +Epoch: [13] [1750/4276] eta: 2:09:45 lr: 3.462341817863541e-05 loss: 0.1451 (0.1462) time: 3.1293 data: 0.0083 max mem: 33300 +Epoch: [13] [1760/4276] eta: 2:09:15 lr: 3.4620677550725714e-05 loss: 0.1349 (0.1461) time: 3.1074 data: 0.0088 max mem: 33300 +Epoch: [13] [1770/4276] eta: 2:08:44 lr: 3.4617936898709985e-05 loss: 0.1335 (0.1461) time: 3.1016 data: 0.0087 max mem: 33300 +Epoch: [13] [1780/4276] eta: 2:08:13 lr: 3.4615196222585875e-05 loss: 0.1335 (0.1460) time: 3.0949 data: 0.0082 max mem: 33300 +Epoch: [13] [1790/4276] eta: 2:07:42 lr: 3.461245552235106e-05 loss: 0.1378 (0.1459) time: 3.0704 data: 0.0080 max mem: 33300 +Epoch: [13] [1800/4276] eta: 2:07:11 lr: 3.4609714798003204e-05 loss: 0.1381 (0.1459) time: 3.0572 data: 0.0082 max mem: 33300 +Epoch: [13] [1810/4276] eta: 2:06:40 lr: 3.460697404953998e-05 loss: 0.1451 (0.1460) time: 3.0659 data: 0.0085 max mem: 33300 +Epoch: [13] [1820/4276] eta: 2:06:09 lr: 3.4604233276959045e-05 loss: 0.1552 (0.1460) time: 3.0836 data: 0.0083 max mem: 33300 +Epoch: [13] [1830/4276] eta: 2:05:38 lr: 3.460149248025806e-05 loss: 0.1385 (0.1460) time: 3.0737 data: 0.0081 max mem: 33300 +Epoch: [13] [1840/4276] eta: 2:05:07 lr: 3.45987516594347e-05 loss: 0.1335 (0.1459) time: 3.0662 data: 0.0080 max mem: 33300 +Epoch: [13] [1850/4276] eta: 2:04:36 lr: 3.459601081448663e-05 loss: 0.1364 (0.1460) time: 3.0608 data: 0.0077 max mem: 33300 +Epoch: [13] [1860/4276] eta: 2:04:06 lr: 3.45932699454115e-05 loss: 0.1412 (0.1459) time: 3.0776 data: 0.0081 max mem: 33300 +Epoch: [13] [1870/4276] eta: 2:03:37 lr: 3.459052905220699e-05 loss: 0.1426 (0.1461) time: 3.1751 data: 0.0083 max mem: 33300 +Epoch: [13] [1880/4276] eta: 2:03:06 lr: 3.458778813487076e-05 loss: 0.1426 (0.1461) time: 3.1573 data: 0.0080 max mem: 33300 +Epoch: [13] [1890/4276] eta: 2:02:35 lr: 3.458504719340047e-05 loss: 0.1480 (0.1461) time: 3.0668 data: 0.0082 max mem: 33300 +Epoch: [13] [1900/4276] eta: 2:02:04 lr: 3.4582306227793776e-05 loss: 0.1478 (0.1461) time: 3.0689 data: 0.0083 max mem: 33300 +Epoch: [13] [1910/4276] eta: 2:01:33 lr: 3.4579565238048345e-05 loss: 0.1466 (0.1462) time: 3.0921 data: 0.0084 max mem: 33300 +Epoch: [13] [1920/4276] eta: 2:01:03 lr: 3.457682422416184e-05 loss: 0.1485 (0.1462) time: 3.0981 data: 0.0085 max mem: 33300 +Epoch: [13] [1930/4276] eta: 2:00:32 lr: 3.457408318613192e-05 loss: 0.1507 (0.1461) time: 3.0894 data: 0.0082 max mem: 33300 +Epoch: [13] [1940/4276] eta: 2:00:01 lr: 3.4571342123956245e-05 loss: 0.1413 (0.1462) time: 3.0763 data: 0.0081 max mem: 33300 +Epoch: [13] [1950/4276] eta: 1:59:30 lr: 3.4568601037632484e-05 loss: 0.1468 (0.1462) time: 3.0817 data: 0.0080 max mem: 33300 +Epoch: [13] [1960/4276] eta: 1:59:00 lr: 3.456585992715828e-05 loss: 0.1523 (0.1462) time: 3.1379 data: 0.0081 max mem: 33300 +Epoch: [13] [1970/4276] eta: 1:58:29 lr: 3.4563118792531314e-05 loss: 0.1210 (0.1461) time: 3.1182 data: 0.0083 max mem: 33300 +Epoch: [13] [1980/4276] eta: 1:57:58 lr: 3.456037763374922e-05 loss: 0.1365 (0.1461) time: 3.0628 data: 0.0084 max mem: 33300 +Epoch: [13] [1990/4276] eta: 1:57:28 lr: 3.455763645080967e-05 loss: 0.1383 (0.1461) time: 3.0747 data: 0.0084 max mem: 33300 +Epoch: [13] [2000/4276] eta: 1:56:57 lr: 3.455489524371032e-05 loss: 0.1514 (0.1461) time: 3.1025 data: 0.0085 max mem: 33300 +Epoch: [13] [2010/4276] eta: 1:56:26 lr: 3.455215401244883e-05 loss: 0.1495 (0.1461) time: 3.0943 data: 0.0089 max mem: 33300 +Epoch: [13] [2020/4276] eta: 1:55:55 lr: 3.454941275702285e-05 loss: 0.1409 (0.1461) time: 3.0579 data: 0.0087 max mem: 33300 +Epoch: [13] [2030/4276] eta: 1:55:24 lr: 3.454667147743005e-05 loss: 0.1298 (0.1460) time: 3.0669 data: 0.0085 max mem: 33300 +Epoch: [13] [2040/4276] eta: 1:54:54 lr: 3.4543930173668075e-05 loss: 0.1310 (0.1460) time: 3.0995 data: 0.0089 max mem: 33300 +Epoch: [13] [2050/4276] eta: 1:54:23 lr: 3.454118884573459e-05 loss: 0.1437 (0.1460) time: 3.1069 data: 0.0094 max mem: 33300 +Epoch: [13] [2060/4276] eta: 1:53:52 lr: 3.453844749362724e-05 loss: 0.1361 (0.1460) time: 3.0814 data: 0.0092 max mem: 33300 +Epoch: [13] [2070/4276] eta: 1:53:21 lr: 3.4535706117343674e-05 loss: 0.1305 (0.1459) time: 3.0579 data: 0.0085 max mem: 33300 +Epoch: [13] [2080/4276] eta: 1:52:50 lr: 3.453296471688156e-05 loss: 0.1413 (0.1460) time: 3.0556 data: 0.0086 max mem: 33300 +Epoch: [13] [2090/4276] eta: 1:52:19 lr: 3.453022329223855e-05 loss: 0.1595 (0.1460) time: 3.0863 data: 0.0090 max mem: 33300 +Epoch: [13] [2100/4276] eta: 1:51:48 lr: 3.4527481843412294e-05 loss: 0.1585 (0.1460) time: 3.1087 data: 0.0092 max mem: 33300 +Epoch: [13] [2110/4276] eta: 1:51:18 lr: 3.452474037040046e-05 loss: 0.1369 (0.1459) time: 3.0889 data: 0.0093 max mem: 33300 +Epoch: [13] [2120/4276] eta: 1:50:47 lr: 3.4521998873200675e-05 loss: 0.1145 (0.1458) time: 3.0989 data: 0.0092 max mem: 33300 +Epoch: [13] [2130/4276] eta: 1:50:16 lr: 3.451925735181061e-05 loss: 0.1145 (0.1457) time: 3.1078 data: 0.0090 max mem: 33300 +Epoch: [13] [2140/4276] eta: 1:49:46 lr: 3.451651580622791e-05 loss: 0.1332 (0.1457) time: 3.1118 data: 0.0091 max mem: 33300 +Epoch: [13] [2150/4276] eta: 1:49:15 lr: 3.451377423645022e-05 loss: 0.1324 (0.1456) time: 3.1041 data: 0.0091 max mem: 33300 +Epoch: [13] [2160/4276] eta: 1:48:44 lr: 3.4511032642475205e-05 loss: 0.1322 (0.1456) time: 3.0772 data: 0.0091 max mem: 33300 +Epoch: [13] [2170/4276] eta: 1:48:13 lr: 3.4508291024300506e-05 loss: 0.1360 (0.1457) time: 3.0556 data: 0.0087 max mem: 33300 +Epoch: [13] [2180/4276] eta: 1:47:42 lr: 3.450554938192377e-05 loss: 0.1530 (0.1456) time: 3.0766 data: 0.0085 max mem: 33300 +Epoch: [13] [2190/4276] eta: 1:47:12 lr: 3.4502807715342665e-05 loss: 0.1482 (0.1457) time: 3.1061 data: 0.0082 max mem: 33300 +Epoch: [13] [2200/4276] eta: 1:46:41 lr: 3.450006602455482e-05 loss: 0.1423 (0.1457) time: 3.0722 data: 0.0081 max mem: 33300 +Epoch: [13] [2210/4276] eta: 1:46:09 lr: 3.44973243095579e-05 loss: 0.1485 (0.1458) time: 3.0443 data: 0.0090 max mem: 33300 +Epoch: [13] [2220/4276] eta: 1:45:39 lr: 3.449458257034954e-05 loss: 0.1522 (0.1458) time: 3.0689 data: 0.0095 max mem: 33300 +Epoch: [13] [2230/4276] eta: 1:45:08 lr: 3.449184080692739e-05 loss: 0.1404 (0.1457) time: 3.1054 data: 0.0090 max mem: 33300 +Epoch: [13] [2240/4276] eta: 1:44:37 lr: 3.44890990192891e-05 loss: 0.1277 (0.1456) time: 3.1072 data: 0.0087 max mem: 33300 +Epoch: [13] [2250/4276] eta: 1:44:06 lr: 3.448635720743232e-05 loss: 0.1223 (0.1456) time: 3.0787 data: 0.0090 max mem: 33300 +Epoch: [13] [2260/4276] eta: 1:43:35 lr: 3.44836153713547e-05 loss: 0.1314 (0.1456) time: 3.0613 data: 0.0086 max mem: 33300 +Epoch: [13] [2270/4276] eta: 1:43:05 lr: 3.4480873511053876e-05 loss: 0.1251 (0.1456) time: 3.0801 data: 0.0087 max mem: 33300 +Epoch: [13] [2280/4276] eta: 1:42:34 lr: 3.44781316265275e-05 loss: 0.1377 (0.1456) time: 3.1053 data: 0.0092 max mem: 33300 +Epoch: [13] [2290/4276] eta: 1:42:03 lr: 3.447538971777321e-05 loss: 0.1377 (0.1456) time: 3.0846 data: 0.0091 max mem: 33300 +Epoch: [13] [2300/4276] eta: 1:41:33 lr: 3.447264778478866e-05 loss: 0.1350 (0.1457) time: 3.0955 data: 0.0094 max mem: 33300 +Epoch: [13] [2310/4276] eta: 1:41:02 lr: 3.4469905827571485e-05 loss: 0.1395 (0.1457) time: 3.1252 data: 0.0093 max mem: 33300 +Epoch: [13] [2320/4276] eta: 1:40:31 lr: 3.446716384611934e-05 loss: 0.1425 (0.1457) time: 3.1160 data: 0.0086 max mem: 33300 +Epoch: [13] [2330/4276] eta: 1:40:00 lr: 3.446442184042986e-05 loss: 0.1476 (0.1457) time: 3.0741 data: 0.0087 max mem: 33300 +Epoch: [13] [2340/4276] eta: 1:39:29 lr: 3.44616798105007e-05 loss: 0.1517 (0.1457) time: 3.0188 data: 0.0088 max mem: 33300 +Epoch: [13] [2350/4276] eta: 1:38:58 lr: 3.4458937756329486e-05 loss: 0.1397 (0.1457) time: 3.0321 data: 0.0084 max mem: 33300 +Epoch: [13] [2360/4276] eta: 1:38:27 lr: 3.445619567791387e-05 loss: 0.1305 (0.1457) time: 3.0686 data: 0.0082 max mem: 33300 +Epoch: [13] [2370/4276] eta: 1:37:56 lr: 3.445345357525149e-05 loss: 0.1413 (0.1457) time: 3.0957 data: 0.0078 max mem: 33300 +Epoch: [13] [2380/4276] eta: 1:37:25 lr: 3.445071144833999e-05 loss: 0.1378 (0.1457) time: 3.0986 data: 0.0079 max mem: 33300 +Epoch: [13] [2390/4276] eta: 1:36:54 lr: 3.444796929717701e-05 loss: 0.1341 (0.1456) time: 3.0706 data: 0.0081 max mem: 33300 +Epoch: [13] [2400/4276] eta: 1:36:24 lr: 3.4445227121760194e-05 loss: 0.1341 (0.1457) time: 3.0770 data: 0.0078 max mem: 33300 +Epoch: [13] [2410/4276] eta: 1:35:53 lr: 3.444248492208718e-05 loss: 0.1392 (0.1457) time: 3.1049 data: 0.0077 max mem: 33300 +Epoch: [13] [2420/4276] eta: 1:35:22 lr: 3.443974269815561e-05 loss: 0.1334 (0.1456) time: 3.1097 data: 0.0082 max mem: 33300 +Epoch: [13] [2430/4276] eta: 1:34:51 lr: 3.443700044996311e-05 loss: 0.1430 (0.1457) time: 3.0904 data: 0.0084 max mem: 33300 +Epoch: [13] [2440/4276] eta: 1:34:20 lr: 3.4434258177507336e-05 loss: 0.1441 (0.1457) time: 3.0676 data: 0.0082 max mem: 33300 +Epoch: [13] [2450/4276] eta: 1:33:49 lr: 3.443151588078592e-05 loss: 0.1358 (0.1457) time: 3.0607 data: 0.0079 max mem: 33300 +Epoch: [13] [2460/4276] eta: 1:33:19 lr: 3.442877355979649e-05 loss: 0.1498 (0.1457) time: 3.0874 data: 0.0076 max mem: 33300 +Epoch: [13] [2470/4276] eta: 1:32:48 lr: 3.44260312145367e-05 loss: 0.1399 (0.1457) time: 3.1086 data: 0.0076 max mem: 33300 +Epoch: [13] [2480/4276] eta: 1:32:17 lr: 3.442328884500417e-05 loss: 0.1423 (0.1458) time: 3.0797 data: 0.0080 max mem: 33300 +Epoch: [13] [2490/4276] eta: 1:31:46 lr: 3.442054645119655e-05 loss: 0.1468 (0.1458) time: 3.0626 data: 0.0082 max mem: 33300 +Epoch: [13] [2500/4276] eta: 1:31:16 lr: 3.441780403311148e-05 loss: 0.1356 (0.1458) time: 3.1021 data: 0.0083 max mem: 33300 +Epoch: [13] [2510/4276] eta: 1:30:45 lr: 3.441506159074658e-05 loss: 0.1447 (0.1458) time: 3.1263 data: 0.0084 max mem: 33300 +Epoch: [13] [2520/4276] eta: 1:30:14 lr: 3.44123191240995e-05 loss: 0.1301 (0.1458) time: 3.0922 data: 0.0081 max mem: 33300 +Epoch: [13] [2530/4276] eta: 1:29:43 lr: 3.440957663316786e-05 loss: 0.1145 (0.1457) time: 3.0626 data: 0.0078 max mem: 33300 +Epoch: [13] [2540/4276] eta: 1:29:12 lr: 3.440683411794931e-05 loss: 0.1184 (0.1456) time: 3.0643 data: 0.0078 max mem: 33300 +Epoch: [13] [2550/4276] eta: 1:28:41 lr: 3.440409157844146e-05 loss: 0.1239 (0.1455) time: 3.0841 data: 0.0078 max mem: 33300 +Epoch: [13] [2560/4276] eta: 1:28:11 lr: 3.4401349014641974e-05 loss: 0.1216 (0.1455) time: 3.0955 data: 0.0079 max mem: 33300 +Epoch: [13] [2570/4276] eta: 1:27:39 lr: 3.439860642654846e-05 loss: 0.1216 (0.1454) time: 3.0516 data: 0.0081 max mem: 33300 +Epoch: [13] [2580/4276] eta: 1:27:08 lr: 3.439586381415857e-05 loss: 0.1316 (0.1454) time: 3.0353 data: 0.0084 max mem: 33300 +Epoch: [13] [2590/4276] eta: 1:26:38 lr: 3.439312117746993e-05 loss: 0.1362 (0.1454) time: 3.0859 data: 0.0079 max mem: 33300 +Epoch: [13] [2600/4276] eta: 1:26:07 lr: 3.439037851648015e-05 loss: 0.1397 (0.1454) time: 3.1227 data: 0.0078 max mem: 33300 +Epoch: [13] [2610/4276] eta: 1:25:36 lr: 3.43876358311869e-05 loss: 0.1340 (0.1453) time: 3.1059 data: 0.0081 max mem: 33300 +Epoch: [13] [2620/4276] eta: 1:25:05 lr: 3.438489312158778e-05 loss: 0.1375 (0.1453) time: 3.0658 data: 0.0081 max mem: 33300 +Epoch: [13] [2630/4276] eta: 1:24:34 lr: 3.4382150387680435e-05 loss: 0.1364 (0.1453) time: 3.0365 data: 0.0076 max mem: 33300 +Epoch: [13] [2640/4276] eta: 1:24:04 lr: 3.437940762946248e-05 loss: 0.1364 (0.1453) time: 3.1100 data: 0.0079 max mem: 33300 +Epoch: [13] [2650/4276] eta: 1:23:33 lr: 3.4376664846931575e-05 loss: 0.1434 (0.1453) time: 3.1583 data: 0.0085 max mem: 33300 +Epoch: [13] [2660/4276] eta: 1:23:02 lr: 3.437392204008532e-05 loss: 0.1482 (0.1453) time: 3.0877 data: 0.0084 max mem: 33300 +Epoch: [13] [2670/4276] eta: 1:22:31 lr: 3.437117920892136e-05 loss: 0.1482 (0.1454) time: 3.0587 data: 0.0083 max mem: 33300 +Epoch: [13] [2680/4276] eta: 1:22:00 lr: 3.4368436353437304e-05 loss: 0.1474 (0.1454) time: 3.0588 data: 0.0080 max mem: 33300 +Epoch: [13] [2690/4276] eta: 1:21:30 lr: 3.43656934736308e-05 loss: 0.1422 (0.1454) time: 3.1147 data: 0.0079 max mem: 33300 +Epoch: [13] [2700/4276] eta: 1:20:59 lr: 3.436295056949947e-05 loss: 0.1306 (0.1453) time: 3.1321 data: 0.0080 max mem: 33300 +Epoch: [13] [2710/4276] eta: 1:20:28 lr: 3.4360207641040934e-05 loss: 0.1347 (0.1453) time: 3.0809 data: 0.0078 max mem: 33300 +Epoch: [13] [2720/4276] eta: 1:19:57 lr: 3.435746468825282e-05 loss: 0.1347 (0.1453) time: 3.0648 data: 0.0082 max mem: 33300 +Epoch: [13] [2730/4276] eta: 1:19:27 lr: 3.435472171113277e-05 loss: 0.1282 (0.1453) time: 3.0625 data: 0.0085 max mem: 33300 +Epoch: [13] [2740/4276] eta: 1:18:56 lr: 3.435197870967838e-05 loss: 0.1476 (0.1453) time: 3.0853 data: 0.0086 max mem: 33300 +Epoch: [13] [2750/4276] eta: 1:18:25 lr: 3.43492356838873e-05 loss: 0.1528 (0.1453) time: 3.0997 data: 0.0084 max mem: 33300 +Epoch: [13] [2760/4276] eta: 1:17:54 lr: 3.434649263375715e-05 loss: 0.1378 (0.1453) time: 3.0703 data: 0.0080 max mem: 33300 +Epoch: [13] [2770/4276] eta: 1:17:23 lr: 3.4343749559285544e-05 loss: 0.1376 (0.1453) time: 3.0535 data: 0.0084 max mem: 33300 +Epoch: [13] [2780/4276] eta: 1:16:52 lr: 3.434100646047011e-05 loss: 0.1374 (0.1453) time: 3.0969 data: 0.0084 max mem: 33300 +Epoch: [13] [2790/4276] eta: 1:16:22 lr: 3.433826333730847e-05 loss: 0.1397 (0.1453) time: 3.1333 data: 0.0081 max mem: 33300 +Epoch: [13] [2800/4276] eta: 1:15:51 lr: 3.433552018979826e-05 loss: 0.1410 (0.1453) time: 3.0988 data: 0.0080 max mem: 33300 +Epoch: [13] [2810/4276] eta: 1:15:20 lr: 3.4332777017937096e-05 loss: 0.1208 (0.1452) time: 3.0642 data: 0.0081 max mem: 33300 +Epoch: [13] [2820/4276] eta: 1:14:49 lr: 3.433003382172259e-05 loss: 0.1171 (0.1451) time: 3.0520 data: 0.0079 max mem: 33300 +Epoch: [13] [2830/4276] eta: 1:14:18 lr: 3.432729060115237e-05 loss: 0.1258 (0.1451) time: 3.0769 data: 0.0082 max mem: 33300 +Epoch: [13] [2840/4276] eta: 1:13:48 lr: 3.432454735622406e-05 loss: 0.1444 (0.1451) time: 3.1026 data: 0.0092 max mem: 33300 +Epoch: [13] [2850/4276] eta: 1:13:17 lr: 3.432180408693528e-05 loss: 0.1508 (0.1452) time: 3.0738 data: 0.0087 max mem: 33300 +Epoch: [13] [2860/4276] eta: 1:12:46 lr: 3.431906079328364e-05 loss: 0.1441 (0.1451) time: 3.0536 data: 0.0080 max mem: 33300 +Epoch: [13] [2870/4276] eta: 1:12:15 lr: 3.431631747526677e-05 loss: 0.1294 (0.1451) time: 3.0678 data: 0.0080 max mem: 33300 +Epoch: [13] [2880/4276] eta: 1:11:44 lr: 3.431357413288229e-05 loss: 0.1369 (0.1451) time: 3.1215 data: 0.0084 max mem: 33300 +Epoch: [13] [2890/4276] eta: 1:11:13 lr: 3.4310830766127815e-05 loss: 0.1369 (0.1451) time: 3.1158 data: 0.0085 max mem: 33300 +Epoch: [13] [2900/4276] eta: 1:10:42 lr: 3.430808737500097e-05 loss: 0.1240 (0.1450) time: 3.0599 data: 0.0082 max mem: 33300 +Epoch: [13] [2910/4276] eta: 1:10:11 lr: 3.430534395949936e-05 loss: 0.1236 (0.1450) time: 3.0523 data: 0.0081 max mem: 33300 +Epoch: [13] [2920/4276] eta: 1:09:41 lr: 3.4302600519620614e-05 loss: 0.1320 (0.1449) time: 3.0717 data: 0.0088 max mem: 33300 +Epoch: [13] [2930/4276] eta: 1:09:10 lr: 3.429985705536235e-05 loss: 0.1227 (0.1449) time: 3.0956 data: 0.0094 max mem: 33300 +Epoch: [13] [2940/4276] eta: 1:08:39 lr: 3.429711356672217e-05 loss: 0.1227 (0.1449) time: 3.0578 data: 0.0089 max mem: 33300 +Epoch: [13] [2950/4276] eta: 1:08:08 lr: 3.42943700536977e-05 loss: 0.1401 (0.1449) time: 3.0304 data: 0.0082 max mem: 33300 +Epoch: [13] [2960/4276] eta: 1:07:37 lr: 3.4291626516286564e-05 loss: 0.1241 (0.1449) time: 3.0799 data: 0.0082 max mem: 33300 +Epoch: [13] [2970/4276] eta: 1:07:06 lr: 3.428888295448637e-05 loss: 0.1408 (0.1449) time: 3.1323 data: 0.0086 max mem: 33300 +Epoch: [13] [2980/4276] eta: 1:06:36 lr: 3.428613936829473e-05 loss: 0.1431 (0.1449) time: 3.1904 data: 0.0086 max mem: 33300 +Epoch: [13] [2990/4276] eta: 1:06:06 lr: 3.4283395757709255e-05 loss: 0.1270 (0.1448) time: 3.1826 data: 0.0087 max mem: 33300 +Epoch: [13] [3000/4276] eta: 1:05:35 lr: 3.4280652122727567e-05 loss: 0.1260 (0.1448) time: 3.1190 data: 0.0086 max mem: 33300 +Epoch: [13] [3010/4276] eta: 1:05:04 lr: 3.427790846334728e-05 loss: 0.1414 (0.1448) time: 3.0804 data: 0.0088 max mem: 33300 +Epoch: [13] [3020/4276] eta: 1:04:33 lr: 3.4275164779566e-05 loss: 0.1414 (0.1448) time: 3.0945 data: 0.0095 max mem: 33300 +Epoch: [13] [3030/4276] eta: 1:04:03 lr: 3.427242107138134e-05 loss: 0.1321 (0.1448) time: 3.1355 data: 0.0098 max mem: 33300 +Epoch: [13] [3040/4276] eta: 1:03:32 lr: 3.426967733879093e-05 loss: 0.1401 (0.1448) time: 3.1269 data: 0.0093 max mem: 33300 +Epoch: [13] [3050/4276] eta: 1:03:01 lr: 3.426693358179235e-05 loss: 0.1401 (0.1448) time: 3.1168 data: 0.0085 max mem: 33300 +Epoch: [13] [3060/4276] eta: 1:02:31 lr: 3.426418980038325e-05 loss: 0.1203 (0.1447) time: 3.1210 data: 0.0082 max mem: 33300 +Epoch: [13] [3070/4276] eta: 1:02:00 lr: 3.426144599456121e-05 loss: 0.1329 (0.1447) time: 3.1415 data: 0.0083 max mem: 33300 +Epoch: [13] [3080/4276] eta: 1:01:29 lr: 3.4258702164323846e-05 loss: 0.1329 (0.1447) time: 3.1365 data: 0.0081 max mem: 33300 +Epoch: [13] [3090/4276] eta: 1:00:58 lr: 3.425595830966877e-05 loss: 0.1199 (0.1446) time: 3.0975 data: 0.0087 max mem: 33300 +Epoch: [13] [3100/4276] eta: 1:00:28 lr: 3.42532144305936e-05 loss: 0.1233 (0.1446) time: 3.0959 data: 0.0088 max mem: 33300 +Epoch: [13] [3110/4276] eta: 0:59:57 lr: 3.425047052709594e-05 loss: 0.1233 (0.1445) time: 3.1108 data: 0.0080 max mem: 33300 +Epoch: [13] [3120/4276] eta: 0:59:26 lr: 3.42477265991734e-05 loss: 0.1218 (0.1445) time: 3.1123 data: 0.0082 max mem: 33300 +Epoch: [13] [3130/4276] eta: 0:58:55 lr: 3.4244982646823584e-05 loss: 0.1294 (0.1444) time: 3.1047 data: 0.0086 max mem: 33300 +Epoch: [13] [3140/4276] eta: 0:58:24 lr: 3.42422386700441e-05 loss: 0.1321 (0.1444) time: 3.0966 data: 0.0082 max mem: 33300 +Epoch: [13] [3150/4276] eta: 0:57:54 lr: 3.423949466883255e-05 loss: 0.1428 (0.1444) time: 3.1031 data: 0.0078 max mem: 33300 +Epoch: [13] [3160/4276] eta: 0:57:23 lr: 3.4236750643186554e-05 loss: 0.1484 (0.1444) time: 3.1463 data: 0.0083 max mem: 33300 +Epoch: [13] [3170/4276] eta: 0:56:52 lr: 3.423400659310371e-05 loss: 0.1402 (0.1445) time: 3.1440 data: 0.0089 max mem: 33300 +Epoch: [13] [3180/4276] eta: 0:56:22 lr: 3.423126251858163e-05 loss: 0.1462 (0.1445) time: 3.1129 data: 0.0085 max mem: 33300 +Epoch: [13] [3190/4276] eta: 0:55:51 lr: 3.4228518419617915e-05 loss: 0.1462 (0.1445) time: 3.0800 data: 0.0084 max mem: 33300 +Epoch: [13] [3200/4276] eta: 0:55:20 lr: 3.422577429621017e-05 loss: 0.1306 (0.1444) time: 3.0741 data: 0.0086 max mem: 33300 +Epoch: [13] [3210/4276] eta: 0:54:49 lr: 3.4223030148356e-05 loss: 0.1358 (0.1445) time: 3.1062 data: 0.0086 max mem: 33300 +Epoch: [13] [3220/4276] eta: 0:54:18 lr: 3.4220285976053006e-05 loss: 0.1435 (0.1445) time: 3.1065 data: 0.0082 max mem: 33300 +Epoch: [13] [3230/4276] eta: 0:53:47 lr: 3.42175417792988e-05 loss: 0.1352 (0.1445) time: 3.1046 data: 0.0076 max mem: 33300 +Epoch: [13] [3240/4276] eta: 0:53:17 lr: 3.4214797558090976e-05 loss: 0.1593 (0.1446) time: 3.0976 data: 0.0078 max mem: 33300 +Epoch: [13] [3250/4276] eta: 0:52:46 lr: 3.421205331242714e-05 loss: 0.1492 (0.1446) time: 3.1076 data: 0.0081 max mem: 33300 +Epoch: [13] [3260/4276] eta: 0:52:15 lr: 3.42093090423049e-05 loss: 0.1484 (0.1446) time: 3.1383 data: 0.0081 max mem: 33300 +Epoch: [13] [3270/4276] eta: 0:51:44 lr: 3.420656474772185e-05 loss: 0.1429 (0.1446) time: 3.1314 data: 0.0076 max mem: 33300 +Epoch: [13] [3280/4276] eta: 0:51:14 lr: 3.4203820428675596e-05 loss: 0.1429 (0.1447) time: 3.1105 data: 0.0076 max mem: 33300 +Epoch: [13] [3290/4276] eta: 0:50:43 lr: 3.420107608516375e-05 loss: 0.1546 (0.1447) time: 3.1050 data: 0.0080 max mem: 33300 +Epoch: [13] [3300/4276] eta: 0:50:12 lr: 3.4198331717183886e-05 loss: 0.1462 (0.1447) time: 3.1025 data: 0.0080 max mem: 33300 +Epoch: [13] [3310/4276] eta: 0:49:41 lr: 3.419558732473362e-05 loss: 0.1462 (0.1448) time: 3.0889 data: 0.0083 max mem: 33300 +Epoch: [13] [3320/4276] eta: 0:49:11 lr: 3.419284290781055e-05 loss: 0.1405 (0.1448) time: 3.1512 data: 0.0091 max mem: 33300 +Epoch: [13] [3330/4276] eta: 0:48:40 lr: 3.419009846641227e-05 loss: 0.1365 (0.1448) time: 3.1648 data: 0.0091 max mem: 33300 +Epoch: [13] [3340/4276] eta: 0:48:09 lr: 3.4187354000536394e-05 loss: 0.1376 (0.1448) time: 3.0995 data: 0.0084 max mem: 33300 +Epoch: [13] [3350/4276] eta: 0:47:38 lr: 3.418460951018051e-05 loss: 0.1365 (0.1447) time: 3.1375 data: 0.0084 max mem: 33300 +Epoch: [13] [3360/4276] eta: 0:47:08 lr: 3.418186499534221e-05 loss: 0.1363 (0.1447) time: 3.1422 data: 0.0087 max mem: 33300 +Epoch: [13] [3370/4276] eta: 0:46:37 lr: 3.417912045601911e-05 loss: 0.1474 (0.1448) time: 3.0899 data: 0.0086 max mem: 33300 +Epoch: [13] [3380/4276] eta: 0:46:06 lr: 3.4176375892208784e-05 loss: 0.1422 (0.1448) time: 3.0831 data: 0.0088 max mem: 33300 +Epoch: [13] [3390/4276] eta: 0:45:35 lr: 3.417363130390884e-05 loss: 0.1422 (0.1448) time: 3.1045 data: 0.0088 max mem: 33300 +Epoch: [13] [3400/4276] eta: 0:45:04 lr: 3.417088669111688e-05 loss: 0.1549 (0.1449) time: 3.1103 data: 0.0088 max mem: 33300 +Epoch: [13] [3410/4276] eta: 0:44:33 lr: 3.416814205383048e-05 loss: 0.1485 (0.1449) time: 3.1122 data: 0.0091 max mem: 33300 +Epoch: [13] [3420/4276] eta: 0:44:03 lr: 3.4165397392047257e-05 loss: 0.1485 (0.1449) time: 3.1106 data: 0.0085 max mem: 33300 +Epoch: [13] [3430/4276] eta: 0:43:32 lr: 3.41626527057648e-05 loss: 0.1492 (0.1450) time: 3.1077 data: 0.0084 max mem: 33300 +Epoch: [13] [3440/4276] eta: 0:43:01 lr: 3.415990799498069e-05 loss: 0.1415 (0.1449) time: 3.1259 data: 0.0090 max mem: 33300 +Epoch: [13] [3450/4276] eta: 0:42:30 lr: 3.415716325969255e-05 loss: 0.1477 (0.1450) time: 3.1558 data: 0.0091 max mem: 33300 +Epoch: [13] [3460/4276] eta: 0:42:00 lr: 3.4154418499897936e-05 loss: 0.1529 (0.1450) time: 3.1654 data: 0.0086 max mem: 33300 +Epoch: [13] [3470/4276] eta: 0:41:29 lr: 3.415167371559446e-05 loss: 0.1312 (0.1450) time: 3.1257 data: 0.0086 max mem: 33300 +Epoch: [13] [3480/4276] eta: 0:40:58 lr: 3.414892890677972e-05 loss: 0.1305 (0.1450) time: 3.0914 data: 0.0085 max mem: 33300 +Epoch: [13] [3490/4276] eta: 0:40:27 lr: 3.41461840734513e-05 loss: 0.1441 (0.1450) time: 3.0940 data: 0.0083 max mem: 33300 +Epoch: [13] [3500/4276] eta: 0:39:56 lr: 3.41434392156068e-05 loss: 0.1465 (0.1450) time: 3.0934 data: 0.0082 max mem: 33300 +Epoch: [13] [3510/4276] eta: 0:39:25 lr: 3.4140694333243795e-05 loss: 0.1282 (0.1449) time: 3.0937 data: 0.0081 max mem: 33300 +Epoch: [13] [3520/4276] eta: 0:38:54 lr: 3.4137949426359887e-05 loss: 0.1350 (0.1449) time: 3.0964 data: 0.0084 max mem: 33300 +Epoch: [13] [3530/4276] eta: 0:38:23 lr: 3.4135204494952667e-05 loss: 0.1462 (0.1449) time: 3.0976 data: 0.0086 max mem: 33300 +Epoch: [13] [3540/4276] eta: 0:37:53 lr: 3.4132459539019716e-05 loss: 0.1314 (0.1449) time: 3.1176 data: 0.0085 max mem: 33300 +Epoch: [13] [3550/4276] eta: 0:37:22 lr: 3.4129714558558636e-05 loss: 0.1271 (0.1449) time: 3.1649 data: 0.0088 max mem: 33300 +Epoch: [13] [3560/4276] eta: 0:36:51 lr: 3.4126969553567e-05 loss: 0.1417 (0.1449) time: 3.1692 data: 0.0089 max mem: 33300 +Epoch: [13] [3570/4276] eta: 0:36:20 lr: 3.412422452404241e-05 loss: 0.1620 (0.1450) time: 3.1132 data: 0.0083 max mem: 33300 +Epoch: [13] [3580/4276] eta: 0:35:49 lr: 3.4121479469982456e-05 loss: 0.1370 (0.1450) time: 3.0800 data: 0.0077 max mem: 33300 +Epoch: [13] [3590/4276] eta: 0:35:19 lr: 3.4118734391384715e-05 loss: 0.1321 (0.1450) time: 3.0788 data: 0.0078 max mem: 33300 +Epoch: [13] [3600/4276] eta: 0:34:48 lr: 3.411598928824678e-05 loss: 0.1421 (0.1450) time: 3.0721 data: 0.0082 max mem: 33300 +Epoch: [13] [3610/4276] eta: 0:34:17 lr: 3.411324416056623e-05 loss: 0.1356 (0.1449) time: 3.0531 data: 0.0087 max mem: 33300 +Epoch: [13] [3620/4276] eta: 0:33:46 lr: 3.4110499008340654e-05 loss: 0.1323 (0.1449) time: 3.0357 data: 0.0097 max mem: 33300 +Epoch: [13] [3630/4276] eta: 0:33:15 lr: 3.4107753831567654e-05 loss: 0.1401 (0.1449) time: 3.0374 data: 0.0099 max mem: 33300 +Epoch: [13] [3640/4276] eta: 0:32:44 lr: 3.4105008630244786e-05 loss: 0.1284 (0.1448) time: 3.0588 data: 0.0085 max mem: 33300 +Epoch: [13] [3650/4276] eta: 0:32:13 lr: 3.410226340436965e-05 loss: 0.1245 (0.1448) time: 3.1206 data: 0.0085 max mem: 33300 +Epoch: [13] [3660/4276] eta: 0:31:42 lr: 3.4099518153939846e-05 loss: 0.1309 (0.1448) time: 3.1840 data: 0.0091 max mem: 33300 +Epoch: [13] [3670/4276] eta: 0:31:11 lr: 3.4096772878952935e-05 loss: 0.1340 (0.1447) time: 3.1632 data: 0.0084 max mem: 33300 +Epoch: [13] [3680/4276] eta: 0:30:41 lr: 3.4094027579406514e-05 loss: 0.1419 (0.1448) time: 3.1252 data: 0.0079 max mem: 33300 +Epoch: [13] [3690/4276] eta: 0:30:10 lr: 3.409128225529815e-05 loss: 0.1428 (0.1447) time: 3.1379 data: 0.0081 max mem: 33300 +Epoch: [13] [3700/4276] eta: 0:29:39 lr: 3.408853690662544e-05 loss: 0.1399 (0.1447) time: 3.1329 data: 0.0085 max mem: 33300 +Epoch: [13] [3710/4276] eta: 0:29:08 lr: 3.408579153338596e-05 loss: 0.1315 (0.1447) time: 3.0977 data: 0.0085 max mem: 33300 +Epoch: [13] [3720/4276] eta: 0:28:37 lr: 3.4083046135577284e-05 loss: 0.1243 (0.1446) time: 3.0795 data: 0.0082 max mem: 33300 +Epoch: [13] [3730/4276] eta: 0:28:06 lr: 3.408030071319701e-05 loss: 0.1352 (0.1446) time: 3.1080 data: 0.0084 max mem: 33300 +Epoch: [13] [3740/4276] eta: 0:27:36 lr: 3.4077555266242714e-05 loss: 0.1321 (0.1446) time: 3.1909 data: 0.0089 max mem: 33300 +Epoch: [13] [3750/4276] eta: 0:27:05 lr: 3.407480979471198e-05 loss: 0.1389 (0.1447) time: 3.2737 data: 0.0092 max mem: 33300 +Epoch: [13] [3760/4276] eta: 0:26:34 lr: 3.407206429860237e-05 loss: 0.1429 (0.1446) time: 3.2240 data: 0.0091 max mem: 33300 +Epoch: [13] [3770/4276] eta: 0:26:03 lr: 3.406931877791147e-05 loss: 0.1249 (0.1446) time: 3.1437 data: 0.0085 max mem: 33300 +Epoch: [13] [3780/4276] eta: 0:25:33 lr: 3.406657323263687e-05 loss: 0.1291 (0.1446) time: 3.1477 data: 0.0084 max mem: 33300 +Epoch: [13] [3790/4276] eta: 0:25:02 lr: 3.406382766277614e-05 loss: 0.1254 (0.1445) time: 3.1482 data: 0.0089 max mem: 33300 +Epoch: [13] [3800/4276] eta: 0:24:31 lr: 3.406108206832686e-05 loss: 0.1324 (0.1445) time: 3.1434 data: 0.0090 max mem: 33300 +Epoch: [13] [3810/4276] eta: 0:24:00 lr: 3.40583364492866e-05 loss: 0.1405 (0.1446) time: 3.1410 data: 0.0090 max mem: 33300 +Epoch: [13] [3820/4276] eta: 0:23:29 lr: 3.4055590805652954e-05 loss: 0.1175 (0.1445) time: 3.1092 data: 0.0088 max mem: 33300 +Epoch: [13] [3830/4276] eta: 0:22:58 lr: 3.405284513742349e-05 loss: 0.1179 (0.1445) time: 3.0894 data: 0.0085 max mem: 33300 +Epoch: [13] [3840/4276] eta: 0:22:28 lr: 3.4050099444595775e-05 loss: 0.1318 (0.1444) time: 3.1844 data: 0.0087 max mem: 33300 +Epoch: [13] [3850/4276] eta: 0:21:57 lr: 3.404735372716739e-05 loss: 0.1270 (0.1444) time: 3.2232 data: 0.0088 max mem: 33300 +Epoch: [13] [3860/4276] eta: 0:21:26 lr: 3.404460798513592e-05 loss: 0.1363 (0.1444) time: 3.1258 data: 0.0085 max mem: 33300 +Epoch: [13] [3870/4276] eta: 0:20:55 lr: 3.4041862218498925e-05 loss: 0.1409 (0.1443) time: 3.0802 data: 0.0084 max mem: 33300 +Epoch: [13] [3880/4276] eta: 0:20:24 lr: 3.4039116427253984e-05 loss: 0.1303 (0.1443) time: 3.0840 data: 0.0088 max mem: 33300 +Epoch: [13] [3890/4276] eta: 0:19:53 lr: 3.403637061139869e-05 loss: 0.1308 (0.1443) time: 3.0842 data: 0.0089 max mem: 33300 +Epoch: [13] [3900/4276] eta: 0:19:22 lr: 3.4033624770930586e-05 loss: 0.1308 (0.1443) time: 3.0784 data: 0.0087 max mem: 33300 +Epoch: [13] [3910/4276] eta: 0:18:51 lr: 3.403087890584726e-05 loss: 0.1330 (0.1443) time: 3.0781 data: 0.0086 max mem: 33300 +Epoch: [13] [3920/4276] eta: 0:18:20 lr: 3.402813301614629e-05 loss: 0.1277 (0.1443) time: 3.0825 data: 0.0088 max mem: 33300 +Epoch: [13] [3930/4276] eta: 0:17:49 lr: 3.402538710182523e-05 loss: 0.1275 (0.1443) time: 3.0881 data: 0.0084 max mem: 33300 +Epoch: [13] [3940/4276] eta: 0:17:18 lr: 3.402264116288167e-05 loss: 0.1284 (0.1443) time: 3.1600 data: 0.0084 max mem: 33300 +Epoch: [13] [3950/4276] eta: 0:16:48 lr: 3.401989519931317e-05 loss: 0.1284 (0.1442) time: 3.1841 data: 0.0088 max mem: 33300 +Epoch: [13] [3960/4276] eta: 0:16:17 lr: 3.401714921111731e-05 loss: 0.1381 (0.1442) time: 3.1124 data: 0.0085 max mem: 33300 +Epoch: [13] [3970/4276] eta: 0:15:46 lr: 3.401440319829166e-05 loss: 0.1501 (0.1442) time: 3.0693 data: 0.0089 max mem: 33300 +Epoch: [13] [3980/4276] eta: 0:15:15 lr: 3.401165716083377e-05 loss: 0.1427 (0.1443) time: 3.0697 data: 0.0088 max mem: 33300 +Epoch: [13] [3990/4276] eta: 0:14:44 lr: 3.400891109874123e-05 loss: 0.1418 (0.1442) time: 3.0745 data: 0.0080 max mem: 33300 +Epoch: [13] [4000/4276] eta: 0:14:13 lr: 3.40061650120116e-05 loss: 0.1198 (0.1442) time: 3.0846 data: 0.0082 max mem: 33300 +Epoch: [13] [4010/4276] eta: 0:13:42 lr: 3.400341890064245e-05 loss: 0.1221 (0.1442) time: 3.0884 data: 0.0083 max mem: 33300 +Epoch: [13] [4020/4276] eta: 0:13:11 lr: 3.400067276463135e-05 loss: 0.1381 (0.1442) time: 3.0731 data: 0.0081 max mem: 33300 +Epoch: [13] [4030/4276] eta: 0:12:40 lr: 3.3997926603975874e-05 loss: 0.1381 (0.1442) time: 3.1048 data: 0.0080 max mem: 33300 +Epoch: [13] [4040/4276] eta: 0:12:09 lr: 3.3995180418673574e-05 loss: 0.1391 (0.1443) time: 3.1687 data: 0.0089 max mem: 33300 +Epoch: [13] [4050/4276] eta: 0:11:38 lr: 3.3992434208722027e-05 loss: 0.1348 (0.1442) time: 3.1513 data: 0.0087 max mem: 33300 +Epoch: [13] [4060/4276] eta: 0:11:07 lr: 3.398968797411879e-05 loss: 0.1324 (0.1443) time: 3.0920 data: 0.0073 max mem: 33300 +Epoch: [13] [4070/4276] eta: 0:10:37 lr: 3.398694171486144e-05 loss: 0.1476 (0.1443) time: 3.0793 data: 0.0075 max mem: 33300 +Epoch: [13] [4080/4276] eta: 0:10:06 lr: 3.398419543094753e-05 loss: 0.1465 (0.1443) time: 3.0747 data: 0.0083 max mem: 33300 +Epoch: [13] [4090/4276] eta: 0:09:35 lr: 3.398144912237464e-05 loss: 0.1521 (0.1443) time: 3.0767 data: 0.0085 max mem: 33300 +Epoch: [13] [4100/4276] eta: 0:09:04 lr: 3.397870278914032e-05 loss: 0.1547 (0.1443) time: 3.0813 data: 0.0082 max mem: 33300 +Epoch: [13] [4110/4276] eta: 0:08:33 lr: 3.397595643124213e-05 loss: 0.1484 (0.1443) time: 3.0818 data: 0.0080 max mem: 33300 +Epoch: [13] [4120/4276] eta: 0:08:02 lr: 3.3973210048677665e-05 loss: 0.1477 (0.1444) time: 3.0805 data: 0.0082 max mem: 33300 +Epoch: [13] [4130/4276] eta: 0:07:31 lr: 3.397046364144445e-05 loss: 0.1456 (0.1444) time: 3.1287 data: 0.0084 max mem: 33300 +Epoch: [13] [4140/4276] eta: 0:07:00 lr: 3.396771720954007e-05 loss: 0.1342 (0.1444) time: 3.1680 data: 0.0081 max mem: 33300 +Epoch: [13] [4150/4276] eta: 0:06:29 lr: 3.3964970752962073e-05 loss: 0.1334 (0.1444) time: 3.1198 data: 0.0080 max mem: 33300 +Epoch: [13] [4160/4276] eta: 0:05:58 lr: 3.396222427170803e-05 loss: 0.1414 (0.1444) time: 3.0880 data: 0.0082 max mem: 33300 +Epoch: [13] [4170/4276] eta: 0:05:27 lr: 3.3959477765775494e-05 loss: 0.1548 (0.1444) time: 3.0731 data: 0.0088 max mem: 33300 +Epoch: [13] [4180/4276] eta: 0:04:56 lr: 3.395673123516203e-05 loss: 0.1417 (0.1444) time: 3.0387 data: 0.0093 max mem: 33300 +Epoch: [13] [4190/4276] eta: 0:04:25 lr: 3.3953984679865205e-05 loss: 0.1417 (0.1445) time: 3.0239 data: 0.0088 max mem: 33300 +Epoch: [13] [4200/4276] eta: 0:03:54 lr: 3.395123809988258e-05 loss: 0.1471 (0.1445) time: 3.0495 data: 0.0079 max mem: 33300 +Epoch: [13] [4210/4276] eta: 0:03:24 lr: 3.3948491495211684e-05 loss: 0.1574 (0.1445) time: 3.0814 data: 0.0079 max mem: 33300 +Epoch: [13] [4220/4276] eta: 0:02:53 lr: 3.394574486585012e-05 loss: 0.1607 (0.1446) time: 3.0813 data: 0.0085 max mem: 33300 +Epoch: [13] [4230/4276] eta: 0:02:22 lr: 3.3942998211795416e-05 loss: 0.1588 (0.1446) time: 3.1139 data: 0.0083 max mem: 33300 +Epoch: [13] [4240/4276] eta: 0:01:51 lr: 3.3940251533045135e-05 loss: 0.1479 (0.1446) time: 3.1312 data: 0.0081 max mem: 33300 +Epoch: [13] [4250/4276] eta: 0:01:20 lr: 3.393750482959684e-05 loss: 0.1484 (0.1447) time: 3.1080 data: 0.0080 max mem: 33300 +Epoch: [13] [4260/4276] eta: 0:00:49 lr: 3.393475810144809e-05 loss: 0.1531 (0.1447) time: 3.0974 data: 0.0081 max mem: 33300 +Epoch: [13] [4270/4276] eta: 0:00:18 lr: 3.3932011348596426e-05 loss: 0.1595 (0.1447) time: 3.0891 data: 0.0077 max mem: 33300 +Epoch: [13] Total time: 3:40:22 +Test: [ 0/21770] eta: 9:04:20 time: 1.5003 data: 1.4577 max mem: 33300 +Test: [ 100/21770] eta: 0:19:06 time: 0.0388 data: 0.0011 max mem: 33300 +Test: [ 200/21770] eta: 0:16:30 time: 0.0389 data: 0.0010 max mem: 33300 +Test: [ 300/21770] eta: 0:15:36 time: 0.0391 data: 0.0010 max mem: 33300 +Test: [ 400/21770] eta: 0:15:09 time: 0.0393 data: 0.0012 max mem: 33300 +Test: [ 500/21770] eta: 0:14:50 time: 0.0392 data: 0.0011 max mem: 33300 +Test: [ 600/21770] eta: 0:14:36 time: 0.0389 data: 0.0011 max mem: 33300 +Test: [ 700/21770] eta: 0:14:24 time: 0.0389 data: 0.0011 max mem: 33300 +Test: [ 800/21770] eta: 0:14:15 time: 0.0388 data: 0.0011 max mem: 33300 +Test: [ 900/21770] eta: 0:14:06 time: 0.0387 data: 0.0010 max mem: 33300 +Test: [ 1000/21770] eta: 0:13:58 time: 0.0391 data: 0.0010 max mem: 33300 +Test: [ 1100/21770] eta: 0:13:52 time: 0.0387 data: 0.0010 max mem: 33300 +Test: [ 1200/21770] eta: 0:13:45 time: 0.0386 data: 0.0010 max mem: 33300 +Test: [ 1300/21770] eta: 0:13:39 time: 0.0391 data: 0.0011 max mem: 33300 +Test: [ 1400/21770] eta: 0:13:33 time: 0.0389 data: 0.0011 max mem: 33300 +Test: [ 1500/21770] eta: 0:13:28 time: 0.0394 data: 0.0011 max mem: 33300 +Test: [ 1600/21770] eta: 0:13:23 time: 0.0390 data: 0.0010 max mem: 33300 +Test: [ 1700/21770] eta: 0:13:19 time: 0.0388 data: 0.0011 max mem: 33300 +Test: [ 1800/21770] eta: 0:13:14 time: 0.0392 data: 0.0011 max mem: 33300 +Test: [ 1900/21770] eta: 0:13:10 time: 0.0397 data: 0.0011 max mem: 33300 +Test: [ 2000/21770] eta: 0:13:05 time: 0.0390 data: 0.0010 max mem: 33300 +Test: [ 2100/21770] eta: 0:13:01 time: 0.0391 data: 0.0011 max mem: 33300 +Test: [ 2200/21770] eta: 0:12:56 time: 0.0385 data: 0.0011 max mem: 33300 +Test: [ 2300/21770] eta: 0:12:51 time: 0.0384 data: 0.0011 max mem: 33300 +Test: [ 2400/21770] eta: 0:12:46 time: 0.0386 data: 0.0011 max mem: 33300 +Test: [ 2500/21770] eta: 0:12:41 time: 0.0396 data: 0.0011 max mem: 33300 +Test: [ 2600/21770] eta: 0:12:37 time: 0.0400 data: 0.0011 max mem: 33300 +Test: [ 2700/21770] eta: 0:12:33 time: 0.0385 data: 0.0011 max mem: 33300 +Test: [ 2800/21770] eta: 0:12:29 time: 0.0392 data: 0.0011 max mem: 33300 +Test: [ 2900/21770] eta: 0:12:25 time: 0.0396 data: 0.0011 max mem: 33300 +Test: [ 3000/21770] eta: 0:12:21 time: 0.0400 data: 0.0011 max mem: 33300 +Test: [ 3100/21770] eta: 0:12:18 time: 0.0397 data: 0.0011 max mem: 33300 +Test: [ 3200/21770] eta: 0:12:14 time: 0.0391 data: 0.0010 max mem: 33300 +Test: [ 3300/21770] eta: 0:12:10 time: 0.0395 data: 0.0011 max mem: 33300 +Test: [ 3400/21770] eta: 0:12:06 time: 0.0393 data: 0.0011 max mem: 33300 +Test: [ 3500/21770] eta: 0:12:01 time: 0.0394 data: 0.0012 max mem: 33300 +Test: [ 3600/21770] eta: 0:11:57 time: 0.0393 data: 0.0012 max mem: 33300 +Test: [ 3700/21770] eta: 0:11:53 time: 0.0390 data: 0.0011 max mem: 33300 +Test: [ 3800/21770] eta: 0:11:49 time: 0.0393 data: 0.0012 max mem: 33300 +Test: [ 3900/21770] eta: 0:11:45 time: 0.0392 data: 0.0012 max mem: 33300 +Test: [ 4000/21770] eta: 0:11:41 time: 0.0400 data: 0.0012 max mem: 33300 +Test: [ 4100/21770] eta: 0:11:38 time: 0.0399 data: 0.0011 max mem: 33300 +Test: [ 4200/21770] eta: 0:11:34 time: 0.0402 data: 0.0012 max mem: 33300 +Test: [ 4300/21770] eta: 0:11:30 time: 0.0401 data: 0.0011 max mem: 33300 +Test: [ 4400/21770] eta: 0:11:26 time: 0.0403 data: 0.0011 max mem: 33300 +Test: [ 4500/21770] eta: 0:11:23 time: 0.0399 data: 0.0011 max mem: 33300 +Test: [ 4600/21770] eta: 0:11:19 time: 0.0400 data: 0.0011 max mem: 33300 +Test: [ 4700/21770] eta: 0:11:15 time: 0.0402 data: 0.0011 max mem: 33300 +Test: [ 4800/21770] eta: 0:11:11 time: 0.0398 data: 0.0011 max mem: 33300 +Test: [ 4900/21770] eta: 0:11:07 time: 0.0401 data: 0.0010 max mem: 33300 +Test: [ 5000/21770] eta: 0:11:03 time: 0.0399 data: 0.0011 max mem: 33300 +Test: [ 5100/21770] eta: 0:11:00 time: 0.0400 data: 0.0011 max mem: 33300 +Test: [ 5200/21770] eta: 0:10:56 time: 0.0393 data: 0.0011 max mem: 33300 +Test: [ 5300/21770] eta: 0:10:52 time: 0.0400 data: 0.0011 max mem: 33300 +Test: [ 5400/21770] eta: 0:10:48 time: 0.0400 data: 0.0011 max mem: 33300 +Test: [ 5500/21770] eta: 0:10:44 time: 0.0399 data: 0.0011 max mem: 33300 +Test: [ 5600/21770] eta: 0:10:40 time: 0.0398 data: 0.0011 max mem: 33300 +Test: [ 5700/21770] eta: 0:10:36 time: 0.0400 data: 0.0010 max mem: 33300 +Test: [ 5800/21770] eta: 0:10:32 time: 0.0394 data: 0.0010 max mem: 33300 +Test: [ 5900/21770] eta: 0:10:28 time: 0.0395 data: 0.0011 max mem: 33300 +Test: [ 6000/21770] eta: 0:10:24 time: 0.0394 data: 0.0011 max mem: 33300 +Test: [ 6100/21770] eta: 0:10:20 time: 0.0399 data: 0.0011 max mem: 33300 +Test: [ 6200/21770] eta: 0:10:17 time: 0.0400 data: 0.0011 max mem: 33300 +Test: [ 6300/21770] eta: 0:10:13 time: 0.0400 data: 0.0011 max mem: 33300 +Test: [ 6400/21770] eta: 0:10:09 time: 0.0396 data: 0.0011 max mem: 33300 +Test: [ 6500/21770] eta: 0:10:05 time: 0.0399 data: 0.0010 max mem: 33300 +Test: [ 6600/21770] eta: 0:10:01 time: 0.0396 data: 0.0011 max mem: 33300 +Test: [ 6700/21770] eta: 0:09:57 time: 0.0401 data: 0.0011 max mem: 33300 +Test: [ 6800/21770] eta: 0:09:53 time: 0.0402 data: 0.0011 max mem: 33300 +Test: [ 6900/21770] eta: 0:09:49 time: 0.0399 data: 0.0011 max mem: 33300 +Test: [ 7000/21770] eta: 0:09:45 time: 0.0400 data: 0.0011 max mem: 33300 +Test: [ 7100/21770] eta: 0:09:41 time: 0.0400 data: 0.0011 max mem: 33300 +Test: [ 7200/21770] eta: 0:09:37 time: 0.0400 data: 0.0011 max mem: 33300 +Test: [ 7300/21770] eta: 0:09:33 time: 0.0385 data: 0.0011 max mem: 33300 +Test: [ 7400/21770] eta: 0:09:29 time: 0.0385 data: 0.0011 max mem: 33300 +Test: [ 7500/21770] eta: 0:09:25 time: 0.0394 data: 0.0010 max mem: 33300 +Test: [ 7600/21770] eta: 0:09:21 time: 0.0400 data: 0.0011 max mem: 33300 +Test: [ 7700/21770] eta: 0:09:17 time: 0.0401 data: 0.0010 max mem: 33300 +Test: [ 7800/21770] eta: 0:09:13 time: 0.0401 data: 0.0011 max mem: 33300 +Test: [ 7900/21770] eta: 0:09:09 time: 0.0396 data: 0.0011 max mem: 33300 +Test: [ 8000/21770] eta: 0:09:05 time: 0.0395 data: 0.0011 max mem: 33300 +Test: [ 8100/21770] eta: 0:09:01 time: 0.0393 data: 0.0011 max mem: 33300 +Test: [ 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time: 0.0394 data: 0.0010 max mem: 33300 +Test: [ 9600/21770] eta: 0:08:02 time: 0.0396 data: 0.0010 max mem: 33300 +Test: [ 9700/21770] eta: 0:07:58 time: 0.0387 data: 0.0011 max mem: 33300 +Test: [ 9800/21770] eta: 0:07:53 time: 0.0387 data: 0.0011 max mem: 33300 +Test: [ 9900/21770] eta: 0:07:49 time: 0.0391 data: 0.0011 max mem: 33300 +Test: [10000/21770] eta: 0:07:45 time: 0.0395 data: 0.0011 max mem: 33300 +Test: [10100/21770] eta: 0:07:41 time: 0.0389 data: 0.0011 max mem: 33300 +Test: [10200/21770] eta: 0:07:37 time: 0.0387 data: 0.0011 max mem: 33300 +Test: [10300/21770] eta: 0:07:33 time: 0.0391 data: 0.0011 max mem: 33300 +Test: [10400/21770] eta: 0:07:29 time: 0.0391 data: 0.0011 max mem: 33300 +Test: [10500/21770] eta: 0:07:25 time: 0.0397 data: 0.0010 max mem: 33300 +Test: [10600/21770] eta: 0:07:21 time: 0.0386 data: 0.0011 max mem: 33300 +Test: [10700/21770] eta: 0:07:17 time: 0.0387 data: 0.0011 max mem: 33300 +Test: [10800/21770] eta: 0:07:13 time: 0.0400 data: 0.0011 max mem: 33300 +Test: [10900/21770] eta: 0:07:09 time: 0.0392 data: 0.0011 max mem: 33300 +Test: [11000/21770] eta: 0:07:05 time: 0.0388 data: 0.0011 max mem: 33300 +Test: [11100/21770] eta: 0:07:01 time: 0.0391 data: 0.0010 max mem: 33300 +Test: [11200/21770] eta: 0:06:57 time: 0.0401 data: 0.0011 max mem: 33300 +Test: [11300/21770] eta: 0:06:53 time: 0.0401 data: 0.0012 max mem: 33300 +Test: [11400/21770] eta: 0:06:50 time: 0.0392 data: 0.0012 max mem: 33300 +Test: [11500/21770] eta: 0:06:46 time: 0.0393 data: 0.0012 max mem: 33300 +Test: [11600/21770] eta: 0:06:42 time: 0.0400 data: 0.0012 max mem: 33300 +Test: [11700/21770] eta: 0:06:38 time: 0.0397 data: 0.0011 max mem: 33300 +Test: [11800/21770] eta: 0:06:34 time: 0.0398 data: 0.0012 max mem: 33300 +Test: [11900/21770] eta: 0:06:30 time: 0.0399 data: 0.0012 max mem: 33300 +Test: [12000/21770] eta: 0:06:26 time: 0.0389 data: 0.0011 max mem: 33300 +Test: [12100/21770] eta: 0:06:22 time: 0.0392 data: 0.0011 max mem: 33300 +Test: [12200/21770] eta: 0:06:18 time: 0.0398 data: 0.0011 max mem: 33300 +Test: [12300/21770] eta: 0:06:14 time: 0.0393 data: 0.0011 max mem: 33300 +Test: [12400/21770] eta: 0:06:10 time: 0.0397 data: 0.0011 max mem: 33300 +Test: [12500/21770] eta: 0:06:06 time: 0.0387 data: 0.0010 max mem: 33300 +Test: [12600/21770] eta: 0:06:02 time: 0.0386 data: 0.0010 max mem: 33300 +Test: [12700/21770] eta: 0:05:58 time: 0.0390 data: 0.0010 max mem: 33300 +Test: [12800/21770] eta: 0:05:54 time: 0.0391 data: 0.0011 max mem: 33300 +Test: [12900/21770] eta: 0:05:50 time: 0.0390 data: 0.0010 max mem: 33300 +Test: [13000/21770] eta: 0:05:46 time: 0.0397 data: 0.0010 max mem: 33300 +Test: [13100/21770] eta: 0:05:42 time: 0.0401 data: 0.0011 max mem: 33300 +Test: [13200/21770] eta: 0:05:38 time: 0.0398 data: 0.0010 max mem: 33300 +Test: [13300/21770] eta: 0:05:34 time: 0.0400 data: 0.0010 max mem: 33300 +Test: [13400/21770] eta: 0:05:30 time: 0.0399 data: 0.0010 max mem: 33300 +Test: [13500/21770] eta: 0:05:27 time: 0.0395 data: 0.0011 max mem: 33300 +Test: [13600/21770] eta: 0:05:23 time: 0.0389 data: 0.0011 max mem: 33300 +Test: [13700/21770] eta: 0:05:19 time: 0.0386 data: 0.0011 max mem: 33300 +Test: [13800/21770] eta: 0:05:15 time: 0.0385 data: 0.0010 max mem: 33300 +Test: [13900/21770] eta: 0:05:11 time: 0.0386 data: 0.0011 max mem: 33300 +Test: [14000/21770] eta: 0:05:07 time: 0.0386 data: 0.0011 max mem: 33300 +Test: [14100/21770] eta: 0:05:03 time: 0.0387 data: 0.0011 max mem: 33300 +Test: [14200/21770] eta: 0:04:59 time: 0.0386 data: 0.0011 max mem: 33300 +Test: [14300/21770] eta: 0:04:55 time: 0.0387 data: 0.0011 max mem: 33300 +Test: [14400/21770] eta: 0:04:51 time: 0.0383 data: 0.0010 max mem: 33300 +Test: [14500/21770] eta: 0:04:47 time: 0.0391 data: 0.0011 max mem: 33300 +Test: [14600/21770] eta: 0:04:43 time: 0.0391 data: 0.0011 max mem: 33300 +Test: [14700/21770] eta: 0:04:39 time: 0.0391 data: 0.0011 max mem: 33300 +Test: [14800/21770] eta: 0:04:35 time: 0.0391 data: 0.0011 max mem: 33300 +Test: [14900/21770] eta: 0:04:31 time: 0.0398 data: 0.0011 max mem: 33300 +Test: [15000/21770] eta: 0:04:27 time: 0.0398 data: 0.0011 max mem: 33300 +Test: [15100/21770] eta: 0:04:23 time: 0.0400 data: 0.0011 max mem: 33300 +Test: [15200/21770] eta: 0:04:19 time: 0.0398 data: 0.0011 max mem: 33300 +Test: [15300/21770] eta: 0:04:15 time: 0.0397 data: 0.0011 max mem: 33300 +Test: [15400/21770] eta: 0:04:11 time: 0.0394 data: 0.0010 max mem: 33300 +Test: [15500/21770] eta: 0:04:07 time: 0.0396 data: 0.0010 max mem: 33300 +Test: [15600/21770] eta: 0:04:03 time: 0.0394 data: 0.0010 max mem: 33300 +Test: [15700/21770] eta: 0:03:59 time: 0.0401 data: 0.0011 max mem: 33300 +Test: [15800/21770] eta: 0:03:55 time: 0.0392 data: 0.0011 max mem: 33300 +Test: [15900/21770] eta: 0:03:51 time: 0.0403 data: 0.0011 max mem: 33300 +Test: [16000/21770] eta: 0:03:47 time: 0.0398 data: 0.0011 max mem: 33300 +Test: [16100/21770] eta: 0:03:43 time: 0.0394 data: 0.0011 max mem: 33300 +Test: [16200/21770] eta: 0:03:39 time: 0.0391 data: 0.0011 max mem: 33300 +Test: [16300/21770] eta: 0:03:35 time: 0.0392 data: 0.0011 max mem: 33300 +Test: [16400/21770] eta: 0:03:31 time: 0.0394 data: 0.0011 max mem: 33300 +Test: [16500/21770] eta: 0:03:28 time: 0.0391 data: 0.0010 max mem: 33300 +Test: [16600/21770] eta: 0:03:24 time: 0.0386 data: 0.0010 max mem: 33300 +Test: [16700/21770] eta: 0:03:20 time: 0.0387 data: 0.0011 max mem: 33300 +Test: [16800/21770] eta: 0:03:16 time: 0.0392 data: 0.0011 max mem: 33300 +Test: [16900/21770] eta: 0:03:12 time: 0.0391 data: 0.0010 max mem: 33300 +Test: [17000/21770] eta: 0:03:08 time: 0.0394 data: 0.0010 max mem: 33300 +Test: [17100/21770] eta: 0:03:04 time: 0.0386 data: 0.0010 max mem: 33300 +Test: [17200/21770] eta: 0:03:00 time: 0.0387 data: 0.0010 max mem: 33300 +Test: [17300/21770] eta: 0:02:56 time: 0.0387 data: 0.0010 max mem: 33300 +Test: [17400/21770] eta: 0:02:52 time: 0.0388 data: 0.0010 max mem: 33300 +Test: [17500/21770] eta: 0:02:48 time: 0.0398 data: 0.0010 max mem: 33300 +Test: [17600/21770] eta: 0:02:44 time: 0.0400 data: 0.0011 max mem: 33300 +Test: [17700/21770] eta: 0:02:40 time: 0.0391 data: 0.0010 max mem: 33300 +Test: [17800/21770] eta: 0:02:36 time: 0.0390 data: 0.0011 max mem: 33300 +Test: [17900/21770] eta: 0:02:32 time: 0.0396 data: 0.0011 max mem: 33300 +Test: [18000/21770] eta: 0:02:28 time: 0.0391 data: 0.0010 max mem: 33300 +Test: [18100/21770] eta: 0:02:24 time: 0.0391 data: 0.0011 max mem: 33300 +Test: [18200/21770] eta: 0:02:20 time: 0.0389 data: 0.0011 max mem: 33300 +Test: [18300/21770] eta: 0:02:16 time: 0.0394 data: 0.0011 max mem: 33300 +Test: [18400/21770] eta: 0:02:12 time: 0.0396 data: 0.0010 max mem: 33300 +Test: [18500/21770] eta: 0:02:08 time: 0.0395 data: 0.0011 max mem: 33300 +Test: [18600/21770] eta: 0:02:05 time: 0.0386 data: 0.0011 max mem: 33300 +Test: [18700/21770] eta: 0:02:01 time: 0.0394 data: 0.0011 max mem: 33300 +Test: [18800/21770] eta: 0:01:57 time: 0.0389 data: 0.0010 max mem: 33300 +Test: [18900/21770] eta: 0:01:53 time: 0.0395 data: 0.0012 max mem: 33300 +Test: [19000/21770] eta: 0:01:49 time: 0.0395 data: 0.0011 max mem: 33300 +Test: [19100/21770] eta: 0:01:45 time: 0.0391 data: 0.0012 max mem: 33300 +Test: [19200/21770] eta: 0:01:41 time: 0.0394 data: 0.0011 max mem: 33300 +Test: [19300/21770] eta: 0:01:37 time: 0.0392 data: 0.0011 max mem: 33300 +Test: [19400/21770] eta: 0:01:33 time: 0.0392 data: 0.0011 max mem: 33300 +Test: [19500/21770] eta: 0:01:29 time: 0.0392 data: 0.0012 max mem: 33300 +Test: [19600/21770] eta: 0:01:25 time: 0.0389 data: 0.0011 max mem: 33300 +Test: [19700/21770] eta: 0:01:21 time: 0.0388 data: 0.0011 max mem: 33300 +Test: [19800/21770] eta: 0:01:17 time: 0.0387 data: 0.0011 max mem: 33300 +Test: [19900/21770] eta: 0:01:13 time: 0.0388 data: 0.0011 max mem: 33300 +Test: [20000/21770] eta: 0:01:09 time: 0.0392 data: 0.0012 max mem: 33300 +Test: [20100/21770] eta: 0:01:05 time: 0.0386 data: 0.0011 max mem: 33300 +Test: [20200/21770] eta: 0:01:01 time: 0.0393 data: 0.0011 max mem: 33300 +Test: [20300/21770] eta: 0:00:57 time: 0.0387 data: 0.0011 max mem: 33300 +Test: [20400/21770] eta: 0:00:53 time: 0.0386 data: 0.0011 max mem: 33300 +Test: [20500/21770] eta: 0:00:50 time: 0.0387 data: 0.0011 max mem: 33300 +Test: [20600/21770] eta: 0:00:46 time: 0.0388 data: 0.0011 max mem: 33300 +Test: [20700/21770] eta: 0:00:42 time: 0.0388 data: 0.0012 max mem: 33300 +Test: [20800/21770] eta: 0:00:38 time: 0.0387 data: 0.0011 max mem: 33300 +Test: [20900/21770] eta: 0:00:34 time: 0.0387 data: 0.0011 max mem: 33300 +Test: [21000/21770] eta: 0:00:30 time: 0.0391 data: 0.0011 max mem: 33300 +Test: [21100/21770] eta: 0:00:26 time: 0.0390 data: 0.0011 max mem: 33300 +Test: [21200/21770] eta: 0:00:22 time: 0.0396 data: 0.0011 max mem: 33300 +Test: [21300/21770] eta: 0:00:18 time: 0.0397 data: 0.0011 max mem: 33300 +Test: [21400/21770] eta: 0:00:14 time: 0.0393 data: 0.0011 max mem: 33300 +Test: [21500/21770] eta: 0:00:10 time: 0.0399 data: 0.0011 max mem: 33300 +Test: [21600/21770] eta: 0:00:06 time: 0.0408 data: 0.0011 max mem: 33300 +Test: [21700/21770] eta: 0:00:02 time: 0.0409 data: 0.0011 max mem: 33300 +Test: Total time: 0:14:18 +Final results: +Mean IoU is 0.00 + + precision@0.5 = 0.00 + precision@0.6 = 0.00 + precision@0.7 = 0.00 + precision@0.8 = 0.00 + precision@0.9 = 0.00 + overall IoU = 0.00 + mean IoU = 0.00 + +Mean accuracy for one-to-zero sample is 100.00 + +Average object IoU 0.0 +Overall IoU 0.0 +Epoch: [14] [ 0/4276] eta: 6:23:14 lr: 3.393036328502703e-05 loss: 0.1173 (0.1173) time: 5.3776 data: 2.1847 max mem: 33300 +Epoch: [14] [ 10/4276] eta: 3:54:45 lr: 3.3927616492645645e-05 loss: 0.1500 (0.1533) time: 3.3018 data: 0.2064 max mem: 33300 +Epoch: [14] [ 20/4276] eta: 3:47:39 lr: 3.3924869675554996e-05 loss: 0.1500 (0.1507) time: 3.1010 data: 0.0084 max mem: 33300 +Epoch: [14] [ 30/4276] eta: 3:44:38 lr: 3.392212283375265e-05 loss: 0.1502 (0.1509) time: 3.1043 data: 0.0084 max mem: 33300 +Epoch: [14] [ 40/4276] eta: 3:42:46 lr: 3.391937596723615e-05 loss: 0.1634 (0.1512) time: 3.0988 data: 0.0087 max mem: 33300 +Epoch: [14] [ 50/4276] eta: 3:41:17 lr: 3.391662907600306e-05 loss: 0.1367 (0.1483) time: 3.0917 data: 0.0085 max mem: 33300 +Epoch: [14] [ 60/4276] eta: 3:40:19 lr: 3.391388216005092e-05 loss: 0.1314 (0.1465) time: 3.0945 data: 0.0079 max mem: 33300 +Epoch: [14] [ 70/4276] eta: 3:40:46 lr: 3.39111352193773e-05 loss: 0.1395 (0.1457) time: 3.1685 data: 0.0079 max mem: 33300 +Epoch: [14] [ 80/4276] eta: 3:40:03 lr: 3.3908388253979735e-05 loss: 0.1427 (0.1481) time: 3.1809 data: 0.0076 max mem: 33300 +Epoch: [14] [ 90/4276] eta: 3:39:04 lr: 3.3905641263855786e-05 loss: 0.1343 (0.1465) time: 3.1072 data: 0.0081 max mem: 33300 +Epoch: [14] [ 100/4276] eta: 3:37:52 lr: 3.3902894249003e-05 loss: 0.1337 (0.1479) time: 3.0638 data: 0.0084 max mem: 33300 +Epoch: [14] [ 110/4276] eta: 3:36:54 lr: 3.3900147209418935e-05 loss: 0.1511 (0.1483) time: 3.0498 data: 0.0081 max mem: 33300 +Epoch: [14] [ 120/4276] eta: 3:36:03 lr: 3.389740014510114e-05 loss: 0.1453 (0.1477) time: 3.0639 data: 0.0080 max mem: 33300 +Epoch: [14] [ 130/4276] eta: 3:35:27 lr: 3.389465305604716e-05 loss: 0.1403 (0.1476) time: 3.0855 data: 0.0083 max mem: 33300 +Epoch: [14] [ 140/4276] eta: 3:34:45 lr: 3.389190594225455e-05 loss: 0.1348 (0.1468) time: 3.0926 data: 0.0087 max mem: 33300 +Epoch: [14] [ 150/4276] eta: 3:34:07 lr: 3.388915880372086e-05 loss: 0.1348 (0.1471) time: 3.0856 data: 0.0085 max mem: 33300 +Epoch: [14] [ 160/4276] eta: 3:33:42 lr: 3.388641164044363e-05 loss: 0.1513 (0.1466) time: 3.1145 data: 0.0081 max mem: 33300 +Epoch: [14] [ 170/4276] eta: 3:33:39 lr: 3.388366445242041e-05 loss: 0.1431 (0.1468) time: 3.1866 data: 0.0083 max mem: 33300 +Epoch: [14] [ 180/4276] eta: 3:33:07 lr: 3.388091723964876e-05 loss: 0.1508 (0.1475) time: 3.1738 data: 0.0084 max mem: 33300 +Epoch: [14] [ 190/4276] eta: 3:32:25 lr: 3.387817000212622e-05 loss: 0.1631 (0.1474) time: 3.0946 data: 0.0078 max mem: 33300 +Epoch: [14] [ 200/4276] eta: 3:31:36 lr: 3.3875422739850324e-05 loss: 0.1395 (0.1473) time: 3.0527 data: 0.0077 max mem: 33300 +Epoch: [14] [ 210/4276] eta: 3:30:53 lr: 3.387267545281864e-05 loss: 0.1395 (0.1475) time: 3.0430 data: 0.0085 max mem: 33300 +Epoch: [14] [ 220/4276] eta: 3:30:18 lr: 3.3869928141028704e-05 loss: 0.1395 (0.1469) time: 3.0728 data: 0.0086 max mem: 33300 +Epoch: [14] [ 230/4276] eta: 3:29:38 lr: 3.386718080447806e-05 loss: 0.1319 (0.1466) time: 3.0745 data: 0.0079 max mem: 33300 +Epoch: [14] [ 240/4276] eta: 3:28:59 lr: 3.3864433443164254e-05 loss: 0.1341 (0.1467) time: 3.0589 data: 0.0081 max mem: 33300 +Epoch: [14] [ 250/4276] eta: 3:28:26 lr: 3.3861686057084826e-05 loss: 0.1482 (0.1474) time: 3.0790 data: 0.0083 max mem: 33300 +Epoch: [14] [ 260/4276] eta: 3:27:59 lr: 3.385893864623733e-05 loss: 0.1591 (0.1474) time: 3.1150 data: 0.0084 max mem: 33300 +Epoch: [14] [ 270/4276] eta: 3:27:40 lr: 3.385619121061931e-05 loss: 0.1220 (0.1473) time: 3.1590 data: 0.0089 max mem: 33300 +Epoch: [14] [ 280/4276] eta: 3:27:07 lr: 3.3853443750228304e-05 loss: 0.1263 (0.1471) time: 3.1422 data: 0.0087 max mem: 33300 +Epoch: [14] [ 290/4276] eta: 3:26:33 lr: 3.385069626506185e-05 loss: 0.1263 (0.1468) time: 3.0943 data: 0.0083 max mem: 33300 +Epoch: [14] [ 300/4276] eta: 3:26:00 lr: 3.3847948755117495e-05 loss: 0.1281 (0.1466) time: 3.0921 data: 0.0083 max mem: 33300 +Epoch: [14] [ 310/4276] eta: 3:25:28 lr: 3.384520122039278e-05 loss: 0.1305 (0.1463) time: 3.0965 data: 0.0085 max mem: 33300 +Epoch: [14] [ 320/4276] eta: 3:24:55 lr: 3.384245366088525e-05 loss: 0.1366 (0.1463) time: 3.0970 data: 0.0084 max mem: 33300 +Epoch: [14] [ 330/4276] eta: 3:24:20 lr: 3.3839706076592436e-05 loss: 0.1367 (0.1462) time: 3.0862 data: 0.0080 max mem: 33300 +Epoch: [14] [ 340/4276] eta: 3:23:46 lr: 3.383695846751189e-05 loss: 0.1319 (0.1460) time: 3.0800 data: 0.0079 max mem: 33300 +Epoch: [14] [ 350/4276] eta: 3:23:14 lr: 3.383421083364114e-05 loss: 0.1176 (0.1458) time: 3.0882 data: 0.0084 max mem: 33300 +Epoch: [14] [ 360/4276] eta: 3:22:53 lr: 3.383146317497775e-05 loss: 0.1510 (0.1465) time: 3.1476 data: 0.0086 max mem: 33300 +Epoch: [14] [ 370/4276] eta: 3:22:22 lr: 3.382871549151923e-05 loss: 0.1362 (0.1461) time: 3.1535 data: 0.0084 max mem: 33300 +Epoch: [14] [ 380/4276] eta: 3:21:45 lr: 3.382596778326314e-05 loss: 0.1317 (0.1465) time: 3.0797 data: 0.0085 max mem: 33300 +Epoch: [14] [ 390/4276] eta: 3:21:10 lr: 3.382322005020699e-05 loss: 0.1389 (0.1467) time: 3.0623 data: 0.0087 max mem: 33300 +Epoch: [14] [ 400/4276] eta: 3:20:36 lr: 3.382047229234834e-05 loss: 0.1495 (0.1466) time: 3.0749 data: 0.0088 max mem: 33300 +Epoch: [14] [ 410/4276] eta: 3:20:03 lr: 3.381772450968473e-05 loss: 0.1416 (0.1465) time: 3.0785 data: 0.0084 max mem: 33300 +Epoch: [14] [ 420/4276] eta: 3:19:24 lr: 3.3814976702213686e-05 loss: 0.1322 (0.1464) time: 3.0480 data: 0.0077 max mem: 33300 +Epoch: [14] [ 430/4276] eta: 3:18:49 lr: 3.3812228869932745e-05 loss: 0.1367 (0.1464) time: 3.0416 data: 0.0078 max mem: 33300 +Epoch: [14] [ 440/4276] eta: 3:18:16 lr: 3.380948101283945e-05 loss: 0.1312 (0.1459) time: 3.0703 data: 0.0084 max mem: 33300 +Epoch: [14] [ 450/4276] eta: 3:17:45 lr: 3.380673313093133e-05 loss: 0.1220 (0.1458) time: 3.0871 data: 0.0088 max mem: 33300 +Epoch: [14] [ 460/4276] eta: 3:17:23 lr: 3.380398522420592e-05 loss: 0.1220 (0.1453) time: 3.1531 data: 0.0089 max mem: 33300 +Epoch: [14] [ 470/4276] eta: 3:16:53 lr: 3.380123729266075e-05 loss: 0.1337 (0.1449) time: 3.1644 data: 0.0089 max mem: 33300 +Epoch: [14] [ 480/4276] eta: 3:16:20 lr: 3.379848933629337e-05 loss: 0.1283 (0.1446) time: 3.0985 data: 0.0084 max mem: 33300 +Epoch: [14] [ 490/4276] eta: 3:15:46 lr: 3.3795741355101295e-05 loss: 0.1166 (0.1442) time: 3.0687 data: 0.0077 max mem: 33300 +Epoch: [14] [ 500/4276] eta: 3:15:13 lr: 3.3792993349082065e-05 loss: 0.1131 (0.1440) time: 3.0687 data: 0.0075 max mem: 33300 +Epoch: [14] [ 510/4276] eta: 3:14:39 lr: 3.3790245318233216e-05 loss: 0.1125 (0.1437) time: 3.0750 data: 0.0073 max mem: 33300 +Epoch: [14] [ 520/4276] eta: 3:14:06 lr: 3.3787497262552275e-05 loss: 0.1153 (0.1435) time: 3.0676 data: 0.0077 max mem: 33300 +Epoch: [14] [ 530/4276] eta: 3:13:31 lr: 3.378474918203678e-05 loss: 0.1355 (0.1435) time: 3.0586 data: 0.0081 max mem: 33300 +Epoch: [14] [ 540/4276] eta: 3:12:55 lr: 3.3782001076684256e-05 loss: 0.1355 (0.1433) time: 3.0401 data: 0.0081 max mem: 33300 +Epoch: [14] [ 550/4276] eta: 3:12:21 lr: 3.377925294649223e-05 loss: 0.1315 (0.1436) time: 3.0388 data: 0.0081 max mem: 33300 +Epoch: [14] [ 560/4276] eta: 3:11:57 lr: 3.3776504791458237e-05 loss: 0.1416 (0.1435) time: 3.1295 data: 0.0085 max mem: 33300 +Epoch: [14] [ 570/4276] eta: 3:11:25 lr: 3.37737566115798e-05 loss: 0.1404 (0.1435) time: 3.1425 data: 0.0085 max mem: 33300 +Epoch: [14] [ 580/4276] eta: 3:10:49 lr: 3.377100840685446e-05 loss: 0.1255 (0.1435) time: 3.0519 data: 0.0083 max mem: 33300 +Epoch: [14] [ 590/4276] eta: 3:10:16 lr: 3.376826017727975e-05 loss: 0.1226 (0.1431) time: 3.0449 data: 0.0077 max mem: 33300 +Epoch: [14] [ 600/4276] eta: 3:09:45 lr: 3.376551192285318e-05 loss: 0.1263 (0.1429) time: 3.0763 data: 0.0075 max mem: 33300 +Epoch: [14] [ 610/4276] eta: 3:09:12 lr: 3.376276364357229e-05 loss: 0.1362 (0.1428) time: 3.0805 data: 0.0080 max mem: 33300 +Epoch: [14] [ 620/4276] eta: 3:08:40 lr: 3.3760015339434606e-05 loss: 0.1307 (0.1427) time: 3.0741 data: 0.0082 max mem: 33300 +Epoch: [14] [ 630/4276] eta: 3:08:08 lr: 3.375726701043764e-05 loss: 0.1258 (0.1430) time: 3.0739 data: 0.0077 max mem: 33300 +Epoch: [14] [ 640/4276] eta: 3:07:34 lr: 3.3754518656578944e-05 loss: 0.1413 (0.1429) time: 3.0584 data: 0.0077 max mem: 33300 +Epoch: [14] [ 650/4276] eta: 3:07:05 lr: 3.375177027785602e-05 loss: 0.1413 (0.1432) time: 3.0893 data: 0.0086 max mem: 33300 +Epoch: [14] [ 660/4276] eta: 3:06:38 lr: 3.374902187426641e-05 loss: 0.1527 (0.1433) time: 3.1555 data: 0.0085 max mem: 33300 +Epoch: [14] [ 670/4276] eta: 3:06:09 lr: 3.374627344580763e-05 loss: 0.1481 (0.1433) time: 3.1489 data: 0.0083 max mem: 33300 +Epoch: [14] [ 680/4276] eta: 3:05:37 lr: 3.3743524992477204e-05 loss: 0.1333 (0.1433) time: 3.0992 data: 0.0084 max mem: 33300 +Epoch: [14] [ 690/4276] eta: 3:05:04 lr: 3.374077651427267e-05 loss: 0.1394 (0.1432) time: 3.0743 data: 0.0084 max mem: 33300 +Epoch: [14] [ 700/4276] eta: 3:04:32 lr: 3.373802801119153e-05 loss: 0.1407 (0.1431) time: 3.0671 data: 0.0082 max mem: 33300 +Epoch: [14] [ 710/4276] eta: 3:03:58 lr: 3.373527948323132e-05 loss: 0.1457 (0.1432) time: 3.0539 data: 0.0085 max mem: 33300 +Epoch: [14] [ 720/4276] eta: 3:03:26 lr: 3.373253093038956e-05 loss: 0.1460 (0.1431) time: 3.0559 data: 0.0086 max mem: 33300 +Epoch: [14] [ 730/4276] eta: 3:02:54 lr: 3.3729782352663775e-05 loss: 0.1396 (0.1432) time: 3.0693 data: 0.0083 max mem: 33300 +Epoch: [14] [ 740/4276] eta: 3:02:22 lr: 3.372703375005148e-05 loss: 0.1238 (0.1430) time: 3.0770 data: 0.0081 max mem: 33300 +Epoch: [14] [ 750/4276] eta: 3:01:54 lr: 3.37242851225502e-05 loss: 0.1300 (0.1431) time: 3.1190 data: 0.0081 max mem: 33300 +Epoch: [14] [ 760/4276] eta: 3:01:22 lr: 3.372153647015746e-05 loss: 0.1272 (0.1430) time: 3.1092 data: 0.0081 max mem: 33300 +Epoch: [14] [ 770/4276] eta: 3:00:45 lr: 3.371878779287078e-05 loss: 0.1354 (0.1430) time: 3.0101 data: 0.0085 max mem: 33300 +Epoch: [14] [ 780/4276] eta: 3:00:06 lr: 3.371603909068767e-05 loss: 0.1372 (0.1430) time: 2.9417 data: 0.0091 max mem: 33300 +Epoch: [14] [ 790/4276] eta: 2:59:28 lr: 3.371329036360565e-05 loss: 0.1311 (0.1429) time: 2.9228 data: 0.0083 max mem: 33300 +Epoch: [14] [ 800/4276] eta: 2:58:50 lr: 3.3710541611622244e-05 loss: 0.1259 (0.1429) time: 2.9264 data: 0.0077 max mem: 33300 +Epoch: [14] [ 810/4276] eta: 2:58:12 lr: 3.370779283473497e-05 loss: 0.1332 (0.1431) time: 2.9237 data: 0.0078 max mem: 33300 +Epoch: [14] [ 820/4276] eta: 2:57:34 lr: 3.370504403294136e-05 loss: 0.1322 (0.1428) time: 2.9199 data: 0.0079 max mem: 33300 +Epoch: [14] [ 830/4276] eta: 2:56:56 lr: 3.3702295206238906e-05 loss: 0.1242 (0.1428) time: 2.9125 data: 0.0078 max mem: 33300 +Epoch: [14] [ 840/4276] eta: 2:56:19 lr: 3.369954635462514e-05 loss: 0.1351 (0.1428) time: 2.9130 data: 0.0074 max mem: 33300 +Epoch: [14] [ 850/4276] eta: 2:55:45 lr: 3.3696797478097567e-05 loss: 0.1259 (0.1427) time: 2.9727 data: 0.0077 max mem: 33300 +Epoch: [14] [ 860/4276] eta: 2:55:15 lr: 3.369404857665371e-05 loss: 0.1259 (0.1427) time: 3.0595 data: 0.0085 max mem: 33300 +Epoch: [14] [ 870/4276] eta: 2:54:42 lr: 3.369129965029109e-05 loss: 0.1319 (0.1426) time: 3.0531 data: 0.0090 max mem: 33300 +Epoch: [14] [ 880/4276] eta: 2:54:07 lr: 3.3688550699007215e-05 loss: 0.1319 (0.1428) time: 2.9852 data: 0.0088 max mem: 33300 +Epoch: [14] [ 890/4276] eta: 2:53:32 lr: 3.36858017227996e-05 loss: 0.1618 (0.1431) time: 2.9630 data: 0.0080 max mem: 33300 +Epoch: [14] [ 900/4276] eta: 2:52:57 lr: 3.368305272166577e-05 loss: 0.1527 (0.1431) time: 2.9701 data: 0.0077 max mem: 33300 +Epoch: [14] [ 910/4276] eta: 2:52:23 lr: 3.3680303695603214e-05 loss: 0.1406 (0.1431) time: 2.9765 data: 0.0079 max mem: 33300 +Epoch: [14] [ 920/4276] eta: 2:51:48 lr: 3.367755464460948e-05 loss: 0.1380 (0.1431) time: 2.9665 data: 0.0079 max mem: 33300 +Epoch: [14] [ 930/4276] eta: 2:51:13 lr: 3.367480556868204e-05 loss: 0.1400 (0.1432) time: 2.9559 data: 0.0080 max mem: 33300 +Epoch: [14] [ 940/4276] eta: 2:50:39 lr: 3.367205646781844e-05 loss: 0.1370 (0.1431) time: 2.9634 data: 0.0081 max mem: 33300 +Epoch: [14] [ 950/4276] eta: 2:50:07 lr: 3.366930734201617e-05 loss: 0.1321 (0.1431) time: 3.0088 data: 0.0080 max mem: 33300 +Epoch: [14] [ 960/4276] eta: 2:49:37 lr: 3.366655819127275e-05 loss: 0.1476 (0.1433) time: 3.0689 data: 0.0081 max mem: 33300 +Epoch: [14] [ 970/4276] eta: 2:49:04 lr: 3.36638090155857e-05 loss: 0.1508 (0.1433) time: 3.0486 data: 0.0081 max mem: 33300 +Epoch: [14] [ 980/4276] eta: 2:48:29 lr: 3.366105981495252e-05 loss: 0.1433 (0.1436) time: 2.9597 data: 0.0083 max mem: 33300 +Epoch: [14] [ 990/4276] eta: 2:47:53 lr: 3.365831058937071e-05 loss: 0.1433 (0.1436) time: 2.9090 data: 0.0082 max mem: 33300 +Epoch: [14] [1000/4276] eta: 2:47:17 lr: 3.36555613388378e-05 loss: 0.1286 (0.1436) time: 2.9053 data: 0.0078 max mem: 33300 +Epoch: [14] [1010/4276] eta: 2:46:42 lr: 3.3652812063351285e-05 loss: 0.1271 (0.1436) time: 2.9200 data: 0.0079 max mem: 33300 +Epoch: [14] [1020/4276] eta: 2:46:07 lr: 3.365006276290867e-05 loss: 0.1266 (0.1435) time: 2.9275 data: 0.0078 max mem: 33300 +Epoch: [14] [1030/4276] eta: 2:45:33 lr: 3.364731343750748e-05 loss: 0.1377 (0.1435) time: 2.9463 data: 0.0080 max mem: 33300 +Epoch: [14] [1040/4276] eta: 2:44:59 lr: 3.364456408714521e-05 loss: 0.1334 (0.1434) time: 2.9587 data: 0.0083 max mem: 33300 +Epoch: [14] [1050/4276] eta: 2:44:27 lr: 3.364181471181937e-05 loss: 0.1334 (0.1436) time: 2.9766 data: 0.0086 max mem: 33300 +Epoch: [14] [1060/4276] eta: 2:43:58 lr: 3.363906531152747e-05 loss: 0.1469 (0.1436) time: 3.0569 data: 0.0091 max mem: 33300 +Epoch: [14] [1070/4276] eta: 2:43:26 lr: 3.363631588626701e-05 loss: 0.1476 (0.1438) time: 3.0627 data: 0.0091 max mem: 33300 +Epoch: [14] [1080/4276] eta: 2:42:53 lr: 3.363356643603549e-05 loss: 0.1476 (0.1437) time: 2.9907 data: 0.0096 max mem: 33300 +Epoch: [14] [1090/4276] eta: 2:42:19 lr: 3.363081696083042e-05 loss: 0.1472 (0.1437) time: 2.9656 data: 0.0097 max mem: 33300 +Epoch: [14] [1100/4276] eta: 2:41:48 lr: 3.3628067460649314e-05 loss: 0.1434 (0.1437) time: 3.0010 data: 0.0094 max mem: 33300 +Epoch: [14] [1110/4276] eta: 2:41:18 lr: 3.3625317935489666e-05 loss: 0.1403 (0.1438) time: 3.0464 data: 0.0094 max mem: 33300 +Epoch: [14] [1120/4276] eta: 2:40:48 lr: 3.3622568385348984e-05 loss: 0.1359 (0.1438) time: 3.0802 data: 0.0099 max mem: 33300 +Epoch: [14] [1130/4276] eta: 2:40:17 lr: 3.361981881022478e-05 loss: 0.1245 (0.1436) time: 3.0671 data: 0.0103 max mem: 33300 +Epoch: [14] [1140/4276] eta: 2:39:44 lr: 3.3617069210114534e-05 loss: 0.1245 (0.1435) time: 3.0001 data: 0.0095 max mem: 33300 +Epoch: [14] [1150/4276] eta: 2:39:13 lr: 3.3614319585015766e-05 loss: 0.1259 (0.1434) time: 3.0111 data: 0.0093 max mem: 33300 +Epoch: [14] [1160/4276] eta: 2:38:44 lr: 3.3611569934925975e-05 loss: 0.1244 (0.1433) time: 3.0766 data: 0.0098 max mem: 33300 +Epoch: [14] [1170/4276] eta: 2:38:13 lr: 3.360882025984265e-05 loss: 0.1410 (0.1435) time: 3.0640 data: 0.0098 max mem: 33300 +Epoch: [14] [1180/4276] eta: 2:37:40 lr: 3.36060705597633e-05 loss: 0.1410 (0.1434) time: 3.0053 data: 0.0092 max mem: 33300 +Epoch: [14] [1190/4276] eta: 2:37:07 lr: 3.3603320834685435e-05 loss: 0.1288 (0.1434) time: 2.9731 data: 0.0092 max mem: 33300 +Epoch: [14] [1200/4276] eta: 2:36:35 lr: 3.360057108460655e-05 loss: 0.1295 (0.1434) time: 2.9778 data: 0.0091 max mem: 33300 +Epoch: [14] [1210/4276] eta: 2:36:02 lr: 3.359782130952414e-05 loss: 0.1246 (0.1433) time: 2.9788 data: 0.0087 max mem: 33300 +Epoch: [14] [1220/4276] eta: 2:35:30 lr: 3.3595071509435695e-05 loss: 0.1201 (0.1432) time: 2.9725 data: 0.0086 max mem: 33300 +Epoch: [14] [1230/4276] eta: 2:34:57 lr: 3.3592321684338726e-05 loss: 0.1325 (0.1434) time: 2.9790 data: 0.0090 max mem: 33300 +Epoch: [14] [1240/4276] eta: 2:34:25 lr: 3.358957183423073e-05 loss: 0.1510 (0.1434) time: 2.9727 data: 0.0094 max mem: 33300 +Epoch: [14] [1250/4276] eta: 2:33:54 lr: 3.35868219591092e-05 loss: 0.1448 (0.1434) time: 3.0047 data: 0.0090 max mem: 33300 +Epoch: [14] [1260/4276] eta: 2:33:24 lr: 3.358407205897163e-05 loss: 0.1310 (0.1434) time: 3.0564 data: 0.0086 max mem: 33300 +Epoch: [14] [1270/4276] eta: 2:32:53 lr: 3.358132213381553e-05 loss: 0.1310 (0.1433) time: 3.0462 data: 0.0090 max mem: 33300 +Epoch: [14] [1280/4276] eta: 2:32:20 lr: 3.3578572183638384e-05 loss: 0.1351 (0.1432) time: 2.9954 data: 0.0094 max mem: 33300 +Epoch: [14] [1290/4276] eta: 2:31:48 lr: 3.3575822208437696e-05 loss: 0.1351 (0.1433) time: 2.9700 data: 0.0089 max mem: 33300 +Epoch: [14] [1300/4276] eta: 2:31:15 lr: 3.357307220821095e-05 loss: 0.1175 (0.1431) time: 2.9649 data: 0.0088 max mem: 33300 +Epoch: [14] [1310/4276] eta: 2:30:42 lr: 3.3570322182955654e-05 loss: 0.1076 (0.1430) time: 2.9336 data: 0.0084 max mem: 33300 +Epoch: [14] [1320/4276] eta: 2:30:08 lr: 3.356757213266929e-05 loss: 0.1417 (0.1431) time: 2.9105 data: 0.0078 max mem: 33300 +Epoch: [14] [1330/4276] eta: 2:29:35 lr: 3.3564822057349356e-05 loss: 0.1431 (0.1431) time: 2.9161 data: 0.0081 max mem: 33300 +Epoch: [14] [1340/4276] eta: 2:29:03 lr: 3.3562071956993344e-05 loss: 0.1361 (0.1430) time: 2.9436 data: 0.0086 max mem: 33300 +Epoch: [14] [1350/4276] eta: 2:28:32 lr: 3.355932183159875e-05 loss: 0.1387 (0.1430) time: 3.0012 data: 0.0089 max mem: 33300 +Epoch: [14] [1360/4276] eta: 2:28:02 lr: 3.355657168116306e-05 loss: 0.1456 (0.1430) time: 3.0614 data: 0.0094 max mem: 33300 +Epoch: [14] [1370/4276] eta: 2:27:33 lr: 3.355382150568378e-05 loss: 0.1328 (0.1430) time: 3.0824 data: 0.0091 max mem: 33300 +Epoch: [14] [1380/4276] eta: 2:27:01 lr: 3.355107130515839e-05 loss: 0.1411 (0.1431) time: 3.0460 data: 0.0086 max mem: 33300 +Epoch: [14] [1390/4276] eta: 2:26:30 lr: 3.354832107958437e-05 loss: 0.1661 (0.1432) time: 3.0090 data: 0.0085 max mem: 33300 +Epoch: [14] [1400/4276] eta: 2:25:59 lr: 3.354557082895923e-05 loss: 0.1518 (0.1433) time: 3.0058 data: 0.0083 max mem: 33300 +Epoch: [14] [1410/4276] eta: 2:25:28 lr: 3.3542820553280445e-05 loss: 0.1361 (0.1432) time: 3.0065 data: 0.0085 max mem: 33300 +Epoch: [14] [1420/4276] eta: 2:24:56 lr: 3.3540070252545515e-05 loss: 0.1299 (0.1432) time: 3.0029 data: 0.0082 max mem: 33300 +Epoch: [14] [1430/4276] eta: 2:24:25 lr: 3.353731992675193e-05 loss: 0.1321 (0.1433) time: 3.0001 data: 0.0085 max mem: 33300 +Epoch: [14] [1440/4276] eta: 2:23:54 lr: 3.353456957589716e-05 loss: 0.1395 (0.1433) time: 3.0011 data: 0.0086 max mem: 33300 +Epoch: [14] [1450/4276] eta: 2:23:22 lr: 3.3531819199978714e-05 loss: 0.1446 (0.1433) time: 3.0022 data: 0.0081 max mem: 33300 +Epoch: [14] [1460/4276] eta: 2:22:52 lr: 3.352906879899408e-05 loss: 0.1448 (0.1433) time: 3.0211 data: 0.0080 max mem: 33300 +Epoch: [14] [1470/4276] eta: 2:22:22 lr: 3.3526318372940726e-05 loss: 0.1372 (0.1433) time: 3.0689 data: 0.0089 max mem: 33300 +Epoch: [14] [1480/4276] eta: 2:21:55 lr: 3.3523567921816146e-05 loss: 0.1269 (0.1432) time: 3.1458 data: 0.0097 max mem: 33300 +Epoch: [14] [1490/4276] eta: 2:21:25 lr: 3.352081744561783e-05 loss: 0.1236 (0.1431) time: 3.1477 data: 0.0093 max mem: 33300 +Epoch: [14] [1500/4276] eta: 2:20:56 lr: 3.351806694434326e-05 loss: 0.1257 (0.1431) time: 3.0953 data: 0.0084 max mem: 33300 +Epoch: [14] [1510/4276] eta: 2:20:26 lr: 3.351531641798992e-05 loss: 0.1295 (0.1431) time: 3.0892 data: 0.0076 max mem: 33300 +Epoch: [14] [1520/4276] eta: 2:19:57 lr: 3.3512565866555314e-05 loss: 0.1286 (0.1430) time: 3.0956 data: 0.0071 max mem: 33300 +Epoch: [14] [1530/4276] eta: 2:19:27 lr: 3.350981529003689e-05 loss: 0.1301 (0.1429) time: 3.1027 data: 0.0068 max mem: 33300 +Epoch: [14] [1540/4276] eta: 2:18:57 lr: 3.3507064688432165e-05 loss: 0.1433 (0.1430) time: 3.0796 data: 0.0069 max mem: 33300 +Epoch: [14] [1550/4276] eta: 2:18:26 lr: 3.3504314061738594e-05 loss: 0.1471 (0.1430) time: 3.0497 data: 0.0072 max mem: 33300 +Epoch: [14] [1560/4276] eta: 2:17:56 lr: 3.3501563409953684e-05 loss: 0.1405 (0.1429) time: 3.0387 data: 0.0074 max mem: 33300 +Epoch: [14] [1570/4276] eta: 2:17:25 lr: 3.3498812733074894e-05 loss: 0.1415 (0.1430) time: 3.0316 data: 0.0075 max mem: 33300 +Epoch: [14] [1580/4276] eta: 2:16:54 lr: 3.349606203109973e-05 loss: 0.1384 (0.1429) time: 3.0343 data: 0.0077 max mem: 33300 +Epoch: [14] [1590/4276] eta: 2:16:25 lr: 3.3493311304025654e-05 loss: 0.1346 (0.1429) time: 3.0735 data: 0.0077 max mem: 33300 +Epoch: [14] [1600/4276] eta: 2:15:55 lr: 3.3490560551850156e-05 loss: 0.1356 (0.1428) time: 3.1017 data: 0.0083 max mem: 33300 +Epoch: [14] [1610/4276] eta: 2:15:25 lr: 3.348780977457071e-05 loss: 0.1282 (0.1427) time: 3.0855 data: 0.0083 max mem: 33300 +Epoch: [14] [1620/4276] eta: 2:14:55 lr: 3.348505897218481e-05 loss: 0.1231 (0.1426) time: 3.0796 data: 0.0084 max mem: 33300 +Epoch: [14] [1630/4276] eta: 2:14:25 lr: 3.348230814468991e-05 loss: 0.1227 (0.1426) time: 3.0790 data: 0.0087 max mem: 33300 +Epoch: [14] [1640/4276] eta: 2:13:55 lr: 3.347955729208351e-05 loss: 0.1227 (0.1425) time: 3.0799 data: 0.0087 max mem: 33300 +Epoch: [14] [1650/4276] eta: 2:13:25 lr: 3.347680641436308e-05 loss: 0.1223 (0.1425) time: 3.0765 data: 0.0085 max mem: 33300 +Epoch: [14] [1660/4276] eta: 2:12:55 lr: 3.347405551152609e-05 loss: 0.1293 (0.1425) time: 3.0762 data: 0.0082 max mem: 33300 +Epoch: [14] [1670/4276] eta: 2:12:25 lr: 3.3471304583570034e-05 loss: 0.1304 (0.1424) time: 3.0761 data: 0.0078 max mem: 33300 +Epoch: [14] [1680/4276] eta: 2:11:55 lr: 3.346855363049238e-05 loss: 0.1338 (0.1423) time: 3.0845 data: 0.0081 max mem: 33300 +Epoch: [14] [1690/4276] eta: 2:11:25 lr: 3.346580265229061e-05 loss: 0.1325 (0.1423) time: 3.0958 data: 0.0084 max mem: 33300 +Epoch: [14] [1700/4276] eta: 2:10:56 lr: 3.3463051648962194e-05 loss: 0.1275 (0.1423) time: 3.0919 data: 0.0076 max mem: 33300 +Epoch: [14] [1710/4276] eta: 2:10:26 lr: 3.3460300620504606e-05 loss: 0.1428 (0.1423) time: 3.0965 data: 0.0080 max mem: 33300 +Epoch: [14] [1720/4276] eta: 2:09:56 lr: 3.345754956691531e-05 loss: 0.1436 (0.1424) time: 3.1058 data: 0.0087 max mem: 33300 +Epoch: [14] [1730/4276] eta: 2:09:26 lr: 3.345479848819181e-05 loss: 0.1569 (0.1425) time: 3.1026 data: 0.0085 max mem: 33300 +Epoch: [14] [1740/4276] eta: 2:08:56 lr: 3.345204738433155e-05 loss: 0.1473 (0.1425) time: 3.0818 data: 0.0084 max mem: 33300 +Epoch: [14] [1750/4276] eta: 2:08:27 lr: 3.344929625533203e-05 loss: 0.1351 (0.1424) time: 3.0941 data: 0.0087 max mem: 33300 +Epoch: [14] [1760/4276] eta: 2:07:56 lr: 3.34465451011907e-05 loss: 0.1237 (0.1424) time: 3.0958 data: 0.0087 max mem: 33300 +Epoch: [14] [1770/4276] eta: 2:07:27 lr: 3.344379392190505e-05 loss: 0.1277 (0.1424) time: 3.0918 data: 0.0085 max mem: 33300 +Epoch: [14] [1780/4276] eta: 2:06:56 lr: 3.344104271747253e-05 loss: 0.1412 (0.1423) time: 3.0802 data: 0.0082 max mem: 33300 +Epoch: [14] [1790/4276] eta: 2:06:25 lr: 3.343829148789063e-05 loss: 0.1335 (0.1423) time: 3.0221 data: 0.0082 max mem: 33300 +Epoch: [14] [1800/4276] eta: 2:05:53 lr: 3.3435540233156815e-05 loss: 0.1335 (0.1423) time: 2.9826 data: 0.0083 max mem: 33300 +Epoch: [14] [1810/4276] eta: 2:05:22 lr: 3.3432788953268555e-05 loss: 0.1440 (0.1424) time: 2.9677 data: 0.0076 max mem: 33300 +Epoch: [14] [1820/4276] eta: 2:04:50 lr: 3.343003764822332e-05 loss: 0.1462 (0.1424) time: 2.9656 data: 0.0074 max mem: 33300 +Epoch: [14] [1830/4276] eta: 2:04:19 lr: 3.3427286318018594e-05 loss: 0.1315 (0.1423) time: 2.9865 data: 0.0076 max mem: 33300 +Epoch: [14] [1840/4276] eta: 2:03:50 lr: 3.342453496265182e-05 loss: 0.1310 (0.1423) time: 3.0802 data: 0.0083 max mem: 33300 +Epoch: [14] [1850/4276] eta: 2:03:20 lr: 3.342178358212048e-05 loss: 0.1339 (0.1423) time: 3.1189 data: 0.0089 max mem: 33300 +Epoch: [14] [1860/4276] eta: 2:02:49 lr: 3.341903217642204e-05 loss: 0.1389 (0.1423) time: 3.0712 data: 0.0090 max mem: 33300 +Epoch: [14] [1870/4276] eta: 2:02:19 lr: 3.341628074555397e-05 loss: 0.1407 (0.1425) time: 3.0453 data: 0.0085 max mem: 33300 +Epoch: [14] [1880/4276] eta: 2:01:49 lr: 3.3413529289513734e-05 loss: 0.1455 (0.1425) time: 3.0649 data: 0.0093 max mem: 33300 +Epoch: [14] [1890/4276] eta: 2:01:17 lr: 3.34107778082988e-05 loss: 0.1333 (0.1424) time: 3.0326 data: 0.0094 max mem: 33300 +Epoch: [14] [1900/4276] eta: 2:00:46 lr: 3.340802630190663e-05 loss: 0.1257 (0.1424) time: 3.0017 data: 0.0085 max mem: 33300 +Epoch: [14] [1910/4276] eta: 2:00:16 lr: 3.34052747703347e-05 loss: 0.1379 (0.1424) time: 3.0330 data: 0.0084 max mem: 33300 +Epoch: [14] [1920/4276] eta: 1:59:45 lr: 3.340252321358047e-05 loss: 0.1326 (0.1423) time: 3.0267 data: 0.0085 max mem: 33300 +Epoch: [14] [1930/4276] eta: 1:59:15 lr: 3.3399771631641406e-05 loss: 0.1221 (0.1423) time: 3.0591 data: 0.0088 max mem: 33300 +Epoch: [14] [1940/4276] eta: 1:58:45 lr: 3.339702002451496e-05 loss: 0.1379 (0.1423) time: 3.0869 data: 0.0088 max mem: 33300 +Epoch: [14] [1950/4276] eta: 1:58:14 lr: 3.339426839219861e-05 loss: 0.1460 (0.1424) time: 3.0561 data: 0.0088 max mem: 33300 +Epoch: [14] [1960/4276] eta: 1:57:44 lr: 3.3391516734689806e-05 loss: 0.1488 (0.1424) time: 3.0644 data: 0.0087 max mem: 33300 +Epoch: [14] [1970/4276] eta: 1:57:13 lr: 3.338876505198603e-05 loss: 0.1320 (0.1423) time: 3.0663 data: 0.0081 max mem: 33300 +Epoch: [14] [1980/4276] eta: 1:56:43 lr: 3.338601334408472e-05 loss: 0.1285 (0.1423) time: 3.0309 data: 0.0078 max mem: 33300 +Epoch: [14] [1990/4276] eta: 1:56:12 lr: 3.338326161098336e-05 loss: 0.1428 (0.1423) time: 3.0363 data: 0.0081 max mem: 33300 +Epoch: [14] [2000/4276] eta: 1:55:41 lr: 3.338050985267941e-05 loss: 0.1494 (0.1423) time: 3.0388 data: 0.0079 max mem: 33300 +Epoch: [14] [2010/4276] eta: 1:55:11 lr: 3.337775806917031e-05 loss: 0.1383 (0.1423) time: 3.0287 data: 0.0076 max mem: 33300 +Epoch: [14] [2020/4276] eta: 1:54:40 lr: 3.337500626045353e-05 loss: 0.1383 (0.1423) time: 3.0272 data: 0.0082 max mem: 33300 +Epoch: [14] [2030/4276] eta: 1:54:09 lr: 3.337225442652654e-05 loss: 0.1367 (0.1423) time: 3.0071 data: 0.0084 max mem: 33300 +Epoch: [14] [2040/4276] eta: 1:53:37 lr: 3.336950256738679e-05 loss: 0.1279 (0.1422) time: 2.9793 data: 0.0075 max mem: 33300 +Epoch: [14] [2050/4276] eta: 1:53:07 lr: 3.336675068303173e-05 loss: 0.1395 (0.1422) time: 3.0057 data: 0.0073 max mem: 33300 +Epoch: [14] [2060/4276] eta: 1:52:36 lr: 3.336399877345884e-05 loss: 0.1472 (0.1422) time: 3.0345 data: 0.0080 max mem: 33300 +Epoch: [14] [2070/4276] eta: 1:52:05 lr: 3.3361246838665564e-05 loss: 0.1278 (0.1422) time: 3.0309 data: 0.0089 max mem: 33300 +Epoch: [14] [2080/4276] eta: 1:51:35 lr: 3.335849487864936e-05 loss: 0.1290 (0.1422) time: 3.0348 data: 0.0090 max mem: 33300 +Epoch: [14] [2090/4276] eta: 1:51:04 lr: 3.335574289340769e-05 loss: 0.1460 (0.1422) time: 3.0313 data: 0.0082 max mem: 33300 +Epoch: [14] [2100/4276] eta: 1:50:33 lr: 3.3352990882938e-05 loss: 0.1423 (0.1422) time: 3.0308 data: 0.0080 max mem: 33300 +Epoch: [14] [2110/4276] eta: 1:50:03 lr: 3.3350238847237755e-05 loss: 0.1274 (0.1421) time: 3.0328 data: 0.0082 max mem: 33300 +Epoch: [14] [2120/4276] eta: 1:49:32 lr: 3.3347486786304406e-05 loss: 0.1131 (0.1420) time: 3.0351 data: 0.0079 max mem: 33300 +Epoch: [14] [2130/4276] eta: 1:49:02 lr: 3.3344734700135404e-05 loss: 0.1119 (0.1419) time: 3.0393 data: 0.0081 max mem: 33300 +Epoch: [14] [2140/4276] eta: 1:48:31 lr: 3.334198258872822e-05 loss: 0.1258 (0.1418) time: 3.0479 data: 0.0084 max mem: 33300 +Epoch: [14] [2150/4276] eta: 1:48:01 lr: 3.33392304520803e-05 loss: 0.1277 (0.1418) time: 3.0514 data: 0.0088 max mem: 33300 +Epoch: [14] [2160/4276] eta: 1:47:30 lr: 3.3336478290189085e-05 loss: 0.1278 (0.1418) time: 3.0401 data: 0.0088 max mem: 33300 +Epoch: [14] [2170/4276] eta: 1:46:59 lr: 3.3333726103052034e-05 loss: 0.1391 (0.1418) time: 3.0353 data: 0.0084 max mem: 33300 +Epoch: [14] [2180/4276] eta: 1:46:29 lr: 3.33309738906666e-05 loss: 0.1450 (0.1418) time: 3.0347 data: 0.0086 max mem: 33300 +Epoch: [14] [2190/4276] eta: 1:45:58 lr: 3.3328221653030243e-05 loss: 0.1450 (0.1419) time: 3.0384 data: 0.0089 max mem: 33300 +Epoch: [14] [2200/4276] eta: 1:45:28 lr: 3.332546939014041e-05 loss: 0.1398 (0.1419) time: 3.0450 data: 0.0091 max mem: 33300 +Epoch: [14] [2210/4276] eta: 1:44:57 lr: 3.332271710199454e-05 loss: 0.1420 (0.1419) time: 3.0517 data: 0.0088 max mem: 33300 +Epoch: [14] [2220/4276] eta: 1:44:27 lr: 3.331996478859011e-05 loss: 0.1420 (0.1419) time: 3.0467 data: 0.0084 max mem: 33300 +Epoch: [14] [2230/4276] eta: 1:43:56 lr: 3.331721244992455e-05 loss: 0.1400 (0.1419) time: 3.0155 data: 0.0084 max mem: 33300 +Epoch: [14] [2240/4276] eta: 1:43:25 lr: 3.33144600859953e-05 loss: 0.1301 (0.1418) time: 2.9969 data: 0.0083 max mem: 33300 +Epoch: [14] [2250/4276] eta: 1:42:54 lr: 3.331170769679983e-05 loss: 0.1301 (0.1418) time: 3.0245 data: 0.0083 max mem: 33300 +Epoch: [14] [2260/4276] eta: 1:42:24 lr: 3.330895528233558e-05 loss: 0.1402 (0.1418) time: 3.0490 data: 0.0083 max mem: 33300 +Epoch: [14] [2270/4276] eta: 1:41:53 lr: 3.33062028426e-05 loss: 0.1338 (0.1418) time: 3.0489 data: 0.0087 max mem: 33300 +Epoch: [14] [2280/4276] eta: 1:41:23 lr: 3.330345037759053e-05 loss: 0.1292 (0.1418) time: 3.0501 data: 0.0092 max mem: 33300 +Epoch: [14] [2290/4276] eta: 1:40:52 lr: 3.330069788730463e-05 loss: 0.1343 (0.1417) time: 3.0414 data: 0.0090 max mem: 33300 +Epoch: [14] [2300/4276] eta: 1:40:22 lr: 3.3297945371739736e-05 loss: 0.1299 (0.1417) time: 3.0370 data: 0.0090 max mem: 33300 +Epoch: [14] [2310/4276] eta: 1:39:52 lr: 3.32951928308933e-05 loss: 0.1338 (0.1418) time: 3.0541 data: 0.0088 max mem: 33300 +Epoch: [14] [2320/4276] eta: 1:39:21 lr: 3.3292440264762756e-05 loss: 0.1550 (0.1418) time: 3.0351 data: 0.0077 max mem: 33300 +Epoch: [14] [2330/4276] eta: 1:38:50 lr: 3.328968767334557e-05 loss: 0.1563 (0.1419) time: 3.0058 data: 0.0078 max mem: 33300 +Epoch: [14] [2340/4276] eta: 1:38:19 lr: 3.328693505663916e-05 loss: 0.1452 (0.1419) time: 2.9969 data: 0.0083 max mem: 33300 +Epoch: [14] [2350/4276] eta: 1:37:48 lr: 3.3284182414640984e-05 loss: 0.1378 (0.1419) time: 2.9863 data: 0.0077 max mem: 33300 +Epoch: [14] [2360/4276] eta: 1:37:17 lr: 3.3281429747348495e-05 loss: 0.1327 (0.1418) time: 3.0011 data: 0.0082 max mem: 33300 +Epoch: [14] [2370/4276] eta: 1:36:47 lr: 3.327867705475913e-05 loss: 0.1326 (0.1419) time: 3.0279 data: 0.0085 max mem: 33300 +Epoch: [14] [2380/4276] eta: 1:36:16 lr: 3.327592433687032e-05 loss: 0.1341 (0.1419) time: 3.0403 data: 0.0085 max mem: 33300 +Epoch: [14] [2390/4276] eta: 1:35:46 lr: 3.327317159367952e-05 loss: 0.1333 (0.1419) time: 3.0448 data: 0.0091 max mem: 33300 +Epoch: [14] [2400/4276] eta: 1:35:15 lr: 3.3270418825184154e-05 loss: 0.1333 (0.1419) time: 3.0615 data: 0.0092 max mem: 33300 +Epoch: [14] [2410/4276] eta: 1:34:45 lr: 3.326766603138169e-05 loss: 0.1317 (0.1419) time: 3.0618 data: 0.0084 max mem: 33300 +Epoch: [14] [2420/4276] eta: 1:34:15 lr: 3.326491321226954e-05 loss: 0.1314 (0.1418) time: 3.0578 data: 0.0081 max mem: 33300 +Epoch: [14] [2430/4276] eta: 1:33:44 lr: 3.326216036784517e-05 loss: 0.1397 (0.1419) time: 3.0568 data: 0.0082 max mem: 33300 +Epoch: [14] [2440/4276] eta: 1:33:14 lr: 3.3259407498106006e-05 loss: 0.1397 (0.1419) time: 3.0497 data: 0.0082 max mem: 33300 +Epoch: [14] [2450/4276] eta: 1:32:43 lr: 3.325665460304949e-05 loss: 0.1379 (0.1419) time: 3.0507 data: 0.0080 max mem: 33300 +Epoch: [14] [2460/4276] eta: 1:32:13 lr: 3.325390168267305e-05 loss: 0.1528 (0.1419) time: 3.0461 data: 0.0078 max mem: 33300 +Epoch: [14] [2470/4276] eta: 1:31:42 lr: 3.325114873697415e-05 loss: 0.1379 (0.1420) time: 3.0436 data: 0.0076 max mem: 33300 +Epoch: [14] [2480/4276] eta: 1:31:12 lr: 3.3248395765950195e-05 loss: 0.1448 (0.1420) time: 3.0492 data: 0.0077 max mem: 33300 +Epoch: [14] [2490/4276] eta: 1:30:42 lr: 3.3245642769598646e-05 loss: 0.1443 (0.1420) time: 3.0575 data: 0.0080 max mem: 33300 +Epoch: [14] [2500/4276] eta: 1:30:11 lr: 3.324288974791693e-05 loss: 0.1333 (0.1420) time: 3.0552 data: 0.0078 max mem: 33300 +Epoch: [14] [2510/4276] eta: 1:29:41 lr: 3.324013670090248e-05 loss: 0.1474 (0.1420) time: 3.0582 data: 0.0074 max mem: 33300 +Epoch: [14] [2520/4276] eta: 1:29:10 lr: 3.323738362855274e-05 loss: 0.1371 (0.1420) time: 3.0584 data: 0.0080 max mem: 33300 +Epoch: [14] [2530/4276] eta: 1:28:40 lr: 3.3234630530865144e-05 loss: 0.1095 (0.1419) time: 3.0456 data: 0.0083 max mem: 33300 +Epoch: [14] [2540/4276] eta: 1:28:09 lr: 3.323187740783712e-05 loss: 0.1210 (0.1419) time: 3.0427 data: 0.0082 max mem: 33300 +Epoch: [14] [2550/4276] eta: 1:27:39 lr: 3.3229124259466116e-05 loss: 0.1222 (0.1418) time: 3.0454 data: 0.0084 max mem: 33300 +Epoch: [14] [2560/4276] eta: 1:27:08 lr: 3.322637108574955e-05 loss: 0.1189 (0.1418) time: 3.0444 data: 0.0088 max mem: 33300 +Epoch: [14] [2570/4276] eta: 1:26:38 lr: 3.3223617886684855e-05 loss: 0.1184 (0.1417) time: 3.0465 data: 0.0088 max mem: 33300 +Epoch: [14] [2580/4276] eta: 1:26:07 lr: 3.322086466226947e-05 loss: 0.1181 (0.1417) time: 3.0344 data: 0.0089 max mem: 33300 +Epoch: [14] [2590/4276] eta: 1:25:37 lr: 3.321811141250083e-05 loss: 0.1207 (0.1416) time: 3.0161 data: 0.0090 max mem: 33300 +Epoch: [14] [2600/4276] eta: 1:25:06 lr: 3.321535813737637e-05 loss: 0.1291 (0.1416) time: 3.0246 data: 0.0087 max mem: 33300 +Epoch: [14] [2610/4276] eta: 1:24:36 lr: 3.32126048368935e-05 loss: 0.1250 (0.1416) time: 3.0460 data: 0.0085 max mem: 33300 +Epoch: [14] [2620/4276] eta: 1:24:05 lr: 3.320985151104968e-05 loss: 0.1328 (0.1416) time: 3.0377 data: 0.0081 max mem: 33300 +Epoch: [14] [2630/4276] eta: 1:23:34 lr: 3.320709815984232e-05 loss: 0.1433 (0.1416) time: 2.9748 data: 0.0081 max mem: 33300 +Epoch: [14] [2640/4276] eta: 1:23:03 lr: 3.3204344783268846e-05 loss: 0.1216 (0.1416) time: 2.9309 data: 0.0079 max mem: 33300 +Epoch: [14] [2650/4276] eta: 1:22:31 lr: 3.3201591381326704e-05 loss: 0.1316 (0.1415) time: 2.9323 data: 0.0079 max mem: 33300 +Epoch: [14] [2660/4276] eta: 1:22:00 lr: 3.319883795401331e-05 loss: 0.1409 (0.1416) time: 2.9330 data: 0.0078 max mem: 33300 +Epoch: [14] [2670/4276] eta: 1:21:29 lr: 3.3196084501326094e-05 loss: 0.1381 (0.1416) time: 2.9340 data: 0.0077 max mem: 33300 +Epoch: [14] [2680/4276] eta: 1:20:58 lr: 3.31933310232625e-05 loss: 0.1381 (0.1416) time: 2.9359 data: 0.0077 max mem: 33300 +Epoch: [14] [2690/4276] eta: 1:20:27 lr: 3.319057751981993e-05 loss: 0.1375 (0.1416) time: 2.9359 data: 0.0076 max mem: 33300 +Epoch: [14] [2700/4276] eta: 1:19:56 lr: 3.318782399099583e-05 loss: 0.1262 (0.1415) time: 2.9336 data: 0.0076 max mem: 33300 +Epoch: [14] [2710/4276] eta: 1:19:25 lr: 3.3185070436787616e-05 loss: 0.1281 (0.1415) time: 2.9343 data: 0.0077 max mem: 33300 +Epoch: [14] [2720/4276] eta: 1:18:54 lr: 3.318231685719271e-05 loss: 0.1261 (0.1415) time: 2.9526 data: 0.0075 max mem: 33300 +Epoch: [14] [2730/4276] eta: 1:18:23 lr: 3.317956325220855e-05 loss: 0.1325 (0.1415) time: 2.9567 data: 0.0075 max mem: 33300 +Epoch: [14] [2740/4276] eta: 1:17:52 lr: 3.317680962183254e-05 loss: 0.1415 (0.1415) time: 2.9399 data: 0.0076 max mem: 33300 +Epoch: [14] [2750/4276] eta: 1:17:21 lr: 3.317405596606213e-05 loss: 0.1459 (0.1416) time: 2.9415 data: 0.0080 max mem: 33300 +Epoch: [14] [2760/4276] eta: 1:16:50 lr: 3.317130228489473e-05 loss: 0.1307 (0.1416) time: 2.9502 data: 0.0082 max mem: 33300 +Epoch: [14] [2770/4276] eta: 1:16:19 lr: 3.316854857832777e-05 loss: 0.1307 (0.1416) time: 2.9553 data: 0.0078 max mem: 33300 +Epoch: [14] [2780/4276] eta: 1:15:48 lr: 3.316579484635866e-05 loss: 0.1412 (0.1416) time: 2.9564 data: 0.0075 max mem: 33300 +Epoch: [14] [2790/4276] eta: 1:15:17 lr: 3.316304108898483e-05 loss: 0.1412 (0.1416) time: 2.9491 data: 0.0078 max mem: 33300 +Epoch: [14] [2800/4276] eta: 1:14:46 lr: 3.3160287306203704e-05 loss: 0.1413 (0.1416) time: 2.9313 data: 0.0085 max mem: 33300 +Epoch: [14] [2810/4276] eta: 1:14:16 lr: 3.31575334980127e-05 loss: 0.1175 (0.1415) time: 2.9379 data: 0.0086 max mem: 33300 +Epoch: [14] [2820/4276] eta: 1:13:45 lr: 3.3154779664409234e-05 loss: 0.1206 (0.1414) time: 2.9564 data: 0.0079 max mem: 33300 +Epoch: [14] [2830/4276] eta: 1:13:14 lr: 3.315202580539073e-05 loss: 0.1330 (0.1414) time: 2.9462 data: 0.0075 max mem: 33300 +Epoch: [14] [2840/4276] eta: 1:12:43 lr: 3.314927192095462e-05 loss: 0.1492 (0.1414) time: 2.9470 data: 0.0075 max mem: 33300 +Epoch: [14] [2850/4276] eta: 1:12:12 lr: 3.31465180110983e-05 loss: 0.1533 (0.1416) time: 2.9559 data: 0.0074 max mem: 33300 +Epoch: [14] [2860/4276] eta: 1:11:41 lr: 3.3143764075819214e-05 loss: 0.1458 (0.1416) time: 2.9498 data: 0.0077 max mem: 33300 +Epoch: [14] [2870/4276] eta: 1:11:11 lr: 3.314101011511476e-05 loss: 0.1343 (0.1416) time: 2.9429 data: 0.0085 max mem: 33300 +Epoch: [14] [2880/4276] eta: 1:10:40 lr: 3.313825612898236e-05 loss: 0.1374 (0.1416) time: 2.9632 data: 0.0083 max mem: 33300 +Epoch: [14] [2890/4276] eta: 1:10:09 lr: 3.3135502117419434e-05 loss: 0.1373 (0.1415) time: 2.9634 data: 0.0081 max mem: 33300 +Epoch: [14] [2900/4276] eta: 1:09:38 lr: 3.313274808042341e-05 loss: 0.1249 (0.1415) time: 2.9407 data: 0.0083 max mem: 33300 +Epoch: [14] [2910/4276] eta: 1:09:08 lr: 3.312999401799168e-05 loss: 0.1253 (0.1415) time: 2.9594 data: 0.0078 max mem: 33300 +Epoch: [14] [2920/4276] eta: 1:08:37 lr: 3.312723993012167e-05 loss: 0.1308 (0.1414) time: 2.9570 data: 0.0077 max mem: 33300 +Epoch: [14] [2930/4276] eta: 1:08:06 lr: 3.312448581681081e-05 loss: 0.1270 (0.1414) time: 2.9348 data: 0.0078 max mem: 33300 +Epoch: [14] [2940/4276] eta: 1:07:35 lr: 3.312173167805649e-05 loss: 0.1282 (0.1414) time: 2.9348 data: 0.0076 max mem: 33300 +Epoch: [14] [2950/4276] eta: 1:07:04 lr: 3.311897751385614e-05 loss: 0.1308 (0.1414) time: 2.9418 data: 0.0075 max mem: 33300 +Epoch: [14] [2960/4276] eta: 1:06:34 lr: 3.311622332420716e-05 loss: 0.1233 (0.1414) time: 2.9391 data: 0.0076 max mem: 33300 +Epoch: [14] [2970/4276] eta: 1:06:03 lr: 3.311346910910699e-05 loss: 0.1255 (0.1414) time: 2.9352 data: 0.0076 max mem: 33300 +Epoch: [14] [2980/4276] eta: 1:05:32 lr: 3.311071486855301e-05 loss: 0.1434 (0.1414) time: 2.9368 data: 0.0076 max mem: 33300 +Epoch: [14] [2990/4276] eta: 1:05:01 lr: 3.3107960602542667e-05 loss: 0.1279 (0.1413) time: 2.9365 data: 0.0075 max mem: 33300 +Epoch: [14] [3000/4276] eta: 1:04:30 lr: 3.310520631107333e-05 loss: 0.1279 (0.1413) time: 2.9370 data: 0.0076 max mem: 33300 +Epoch: [14] [3010/4276] eta: 1:04:00 lr: 3.3102451994142454e-05 loss: 0.1357 (0.1413) time: 2.9456 data: 0.0079 max mem: 33300 +Epoch: [14] [3020/4276] eta: 1:03:29 lr: 3.309969765174742e-05 loss: 0.1341 (0.1413) time: 2.9671 data: 0.0079 max mem: 33300 +Epoch: [14] [3030/4276] eta: 1:02:59 lr: 3.309694328388564e-05 loss: 0.1270 (0.1413) time: 2.9615 data: 0.0074 max mem: 33300 +Epoch: [14] [3040/4276] eta: 1:02:28 lr: 3.309418889055454e-05 loss: 0.1325 (0.1413) time: 2.9503 data: 0.0074 max mem: 33300 +Epoch: [14] [3050/4276] eta: 1:01:57 lr: 3.309143447175152e-05 loss: 0.1493 (0.1413) time: 2.9728 data: 0.0074 max mem: 33300 +Epoch: [14] [3060/4276] eta: 1:01:27 lr: 3.308868002747399e-05 loss: 0.1178 (0.1412) time: 3.0140 data: 0.0075 max mem: 33300 +Epoch: [14] [3070/4276] eta: 1:00:57 lr: 3.3085925557719353e-05 loss: 0.1264 (0.1412) time: 3.0469 data: 0.0075 max mem: 33300 +Epoch: [14] [3080/4276] eta: 1:00:26 lr: 3.308317106248503e-05 loss: 0.1326 (0.1412) time: 3.0323 data: 0.0072 max mem: 33300 +Epoch: [14] [3090/4276] eta: 0:59:56 lr: 3.3080416541768405e-05 loss: 0.1230 (0.1411) time: 2.9923 data: 0.0073 max mem: 33300 +Epoch: [14] [3100/4276] eta: 0:59:25 lr: 3.30776619955669e-05 loss: 0.1173 (0.1411) time: 2.9895 data: 0.0073 max mem: 33300 +Epoch: [14] [3110/4276] eta: 0:58:55 lr: 3.307490742387792e-05 loss: 0.1136 (0.1410) time: 2.9986 data: 0.0075 max mem: 33300 +Epoch: [14] [3120/4276] eta: 0:58:25 lr: 3.307215282669887e-05 loss: 0.1147 (0.1410) time: 2.9870 data: 0.0075 max mem: 33300 +Epoch: [14] [3130/4276] eta: 0:57:54 lr: 3.306939820402716e-05 loss: 0.1333 (0.1409) time: 2.9897 data: 0.0072 max mem: 33300 +Epoch: [14] [3140/4276] eta: 0:57:24 lr: 3.3066643555860185e-05 loss: 0.1338 (0.1409) time: 3.0103 data: 0.0073 max mem: 33300 +Epoch: [14] [3150/4276] eta: 0:56:53 lr: 3.306388888219535e-05 loss: 0.1569 (0.1410) time: 3.0272 data: 0.0075 max mem: 33300 +Epoch: [14] [3160/4276] eta: 0:56:23 lr: 3.306113418303007e-05 loss: 0.1405 (0.1410) time: 3.0239 data: 0.0073 max mem: 33300 +Epoch: [14] [3170/4276] eta: 0:55:53 lr: 3.3058379458361747e-05 loss: 0.1332 (0.1410) time: 3.0132 data: 0.0073 max mem: 33300 +Epoch: [14] [3180/4276] eta: 0:55:22 lr: 3.305562470818776e-05 loss: 0.1278 (0.1409) time: 3.0063 data: 0.0075 max mem: 33300 +Epoch: [14] [3190/4276] eta: 0:54:52 lr: 3.3052869932505536e-05 loss: 0.1330 (0.1409) time: 2.9890 data: 0.0072 max mem: 33300 +Epoch: [14] [3200/4276] eta: 0:54:21 lr: 3.305011513131247e-05 loss: 0.1404 (0.1409) time: 2.9777 data: 0.0071 max mem: 33300 +Epoch: [14] [3210/4276] eta: 0:53:51 lr: 3.304736030460595e-05 loss: 0.1269 (0.1409) time: 2.9856 data: 0.0072 max mem: 33300 +Epoch: [14] [3220/4276] eta: 0:53:20 lr: 3.30446054523834e-05 loss: 0.1269 (0.1409) time: 2.9859 data: 0.0072 max mem: 33300 +Epoch: [14] [3230/4276] eta: 0:52:50 lr: 3.304185057464221e-05 loss: 0.1366 (0.1409) time: 3.0040 data: 0.0071 max mem: 33300 +Epoch: [14] [3240/4276] eta: 0:52:20 lr: 3.3039095671379774e-05 loss: 0.1446 (0.1410) time: 3.0185 data: 0.0075 max mem: 33300 +Epoch: [14] [3250/4276] eta: 0:51:49 lr: 3.303634074259349e-05 loss: 0.1446 (0.1410) time: 3.0116 data: 0.0077 max mem: 33300 +Epoch: [14] [3260/4276] eta: 0:51:19 lr: 3.3033585788280764e-05 loss: 0.1382 (0.1410) time: 3.0047 data: 0.0073 max mem: 33300 +Epoch: [14] [3270/4276] eta: 0:50:48 lr: 3.3030830808438986e-05 loss: 0.1414 (0.1410) time: 2.9928 data: 0.0071 max mem: 33300 +Epoch: [14] [3280/4276] eta: 0:50:18 lr: 3.302807580306557e-05 loss: 0.1323 (0.1410) time: 3.0042 data: 0.0073 max mem: 33300 +Epoch: [14] [3290/4276] eta: 0:49:48 lr: 3.302532077215789e-05 loss: 0.1397 (0.1410) time: 3.0078 data: 0.0073 max mem: 33300 +Epoch: [14] [3300/4276] eta: 0:49:17 lr: 3.3022565715713366e-05 loss: 0.1443 (0.1410) time: 2.9967 data: 0.0071 max mem: 33300 +Epoch: [14] [3310/4276] eta: 0:48:47 lr: 3.3019810633729376e-05 loss: 0.1479 (0.1410) time: 3.0145 data: 0.0072 max mem: 33300 +Epoch: [14] [3320/4276] eta: 0:48:17 lr: 3.3017055526203324e-05 loss: 0.1482 (0.1411) time: 3.0236 data: 0.0073 max mem: 33300 +Epoch: [14] [3330/4276] eta: 0:47:46 lr: 3.30143003931326e-05 loss: 0.1245 (0.1411) time: 3.0030 data: 0.0073 max mem: 33300 +Epoch: [14] [3340/4276] eta: 0:47:16 lr: 3.30115452345146e-05 loss: 0.1308 (0.1411) time: 3.0098 data: 0.0071 max mem: 33300 +Epoch: [14] [3350/4276] eta: 0:46:45 lr: 3.3008790050346724e-05 loss: 0.1323 (0.1410) time: 3.0161 data: 0.0070 max mem: 33300 +Epoch: [14] [3360/4276] eta: 0:46:15 lr: 3.300603484062635e-05 loss: 0.1323 (0.1410) time: 2.9982 data: 0.0072 max mem: 33300 +Epoch: [14] [3370/4276] eta: 0:45:45 lr: 3.300327960535089e-05 loss: 0.1439 (0.1411) time: 2.9719 data: 0.0075 max mem: 33300 +Epoch: [14] [3380/4276] eta: 0:45:14 lr: 3.300052434451774e-05 loss: 0.1369 (0.1411) time: 2.9702 data: 0.0078 max mem: 33300 +Epoch: [14] [3390/4276] eta: 0:44:44 lr: 3.299776905812426e-05 loss: 0.1362 (0.1411) time: 2.9945 data: 0.0077 max mem: 33300 +Epoch: [14] [3400/4276] eta: 0:44:13 lr: 3.299501374616787e-05 loss: 0.1420 (0.1411) time: 3.0114 data: 0.0075 max mem: 33300 +Epoch: [14] [3410/4276] eta: 0:43:43 lr: 3.2992258408645954e-05 loss: 0.1418 (0.1411) time: 3.0080 data: 0.0077 max mem: 33300 +Epoch: [14] [3420/4276] eta: 0:43:13 lr: 3.29895030455559e-05 loss: 0.1399 (0.1412) time: 2.9871 data: 0.0079 max mem: 33300 +Epoch: [14] [3430/4276] eta: 0:42:42 lr: 3.298674765689509e-05 loss: 0.1423 (0.1412) time: 2.9751 data: 0.0080 max mem: 33300 +Epoch: [14] [3440/4276] eta: 0:42:12 lr: 3.298399224266093e-05 loss: 0.1423 (0.1411) time: 2.9610 data: 0.0074 max mem: 33300 +Epoch: [14] [3450/4276] eta: 0:41:41 lr: 3.29812368028508e-05 loss: 0.1417 (0.1412) time: 2.9661 data: 0.0076 max mem: 33300 +Epoch: [14] [3460/4276] eta: 0:41:11 lr: 3.297848133746209e-05 loss: 0.1562 (0.1412) time: 2.9697 data: 0.0080 max mem: 33300 +Epoch: [14] [3470/4276] eta: 0:40:40 lr: 3.2975725846492186e-05 loss: 0.1409 (0.1412) time: 2.9569 data: 0.0077 max mem: 33300 +Epoch: [14] [3480/4276] eta: 0:40:10 lr: 3.2972970329938485e-05 loss: 0.1405 (0.1412) time: 2.9588 data: 0.0075 max mem: 33300 +Epoch: [14] [3490/4276] eta: 0:39:40 lr: 3.297021478779835e-05 loss: 0.1363 (0.1412) time: 2.9615 data: 0.0073 max mem: 33300 +Epoch: [14] [3500/4276] eta: 0:39:09 lr: 3.296745922006919e-05 loss: 0.1345 (0.1412) time: 2.9545 data: 0.0078 max mem: 33300 +Epoch: [14] [3510/4276] eta: 0:38:39 lr: 3.296470362674838e-05 loss: 0.1279 (0.1412) time: 2.9588 data: 0.0080 max mem: 33300 +Epoch: [14] [3520/4276] eta: 0:38:08 lr: 3.296194800783332e-05 loss: 0.1343 (0.1412) time: 2.9738 data: 0.0075 max mem: 33300 +Epoch: [14] [3530/4276] eta: 0:37:38 lr: 3.295919236332138e-05 loss: 0.1473 (0.1412) time: 2.9943 data: 0.0073 max mem: 33300 +Epoch: [14] [3540/4276] eta: 0:37:08 lr: 3.295643669320994e-05 loss: 0.1464 (0.1412) time: 2.9972 data: 0.0075 max mem: 33300 +Epoch: [14] [3550/4276] eta: 0:36:37 lr: 3.29536809974964e-05 loss: 0.1297 (0.1412) time: 2.9834 data: 0.0079 max mem: 33300 +Epoch: [14] [3560/4276] eta: 0:36:07 lr: 3.2950925276178126e-05 loss: 0.1297 (0.1412) time: 3.0052 data: 0.0082 max mem: 33300 +Epoch: [14] [3570/4276] eta: 0:35:37 lr: 3.294816952925252e-05 loss: 0.1558 (0.1413) time: 3.0006 data: 0.0079 max mem: 33300 +Epoch: [14] [3580/4276] eta: 0:35:06 lr: 3.294541375671695e-05 loss: 0.1324 (0.1412) time: 2.9859 data: 0.0079 max mem: 33300 +Epoch: [14] [3590/4276] eta: 0:34:36 lr: 3.29426579585688e-05 loss: 0.1247 (0.1412) time: 3.0045 data: 0.0081 max mem: 33300 +Epoch: [14] [3600/4276] eta: 0:34:06 lr: 3.293990213480545e-05 loss: 0.1247 (0.1412) time: 3.0090 data: 0.0082 max mem: 33300 +Epoch: [14] [3610/4276] eta: 0:33:35 lr: 3.293714628542429e-05 loss: 0.1223 (0.1412) time: 2.9997 data: 0.0080 max mem: 33300 +Epoch: [14] [3620/4276] eta: 0:33:05 lr: 3.2934390410422686e-05 loss: 0.1206 (0.1412) time: 2.9953 data: 0.0080 max mem: 33300 +Epoch: [14] [3630/4276] eta: 0:32:35 lr: 3.293163450979804e-05 loss: 0.1304 (0.1412) time: 2.9885 data: 0.0086 max mem: 33300 +Epoch: [14] [3640/4276] eta: 0:32:04 lr: 3.2928878583547705e-05 loss: 0.1114 (0.1411) time: 2.9979 data: 0.0087 max mem: 33300 +Epoch: [14] [3650/4276] eta: 0:31:34 lr: 3.292612263166908e-05 loss: 0.1114 (0.1411) time: 3.0098 data: 0.0084 max mem: 33300 +Epoch: [14] [3660/4276] eta: 0:31:04 lr: 3.2923366654159524e-05 loss: 0.1184 (0.1411) time: 3.0026 data: 0.0082 max mem: 33300 +Epoch: [14] [3670/4276] eta: 0:30:33 lr: 3.292061065101643e-05 loss: 0.1347 (0.1411) time: 2.9975 data: 0.0083 max mem: 33300 +Epoch: [14] [3680/4276] eta: 0:30:03 lr: 3.291785462223717e-05 loss: 0.1456 (0.1411) time: 2.9859 data: 0.0087 max mem: 33300 +Epoch: [14] [3690/4276] eta: 0:29:33 lr: 3.291509856781913e-05 loss: 0.1483 (0.1411) time: 2.9936 data: 0.0088 max mem: 33300 +Epoch: [14] [3700/4276] eta: 0:29:03 lr: 3.291234248775967e-05 loss: 0.1348 (0.1411) time: 3.0080 data: 0.0083 max mem: 33300 +Epoch: [14] [3710/4276] eta: 0:28:32 lr: 3.290958638205617e-05 loss: 0.1209 (0.1410) time: 3.0002 data: 0.0080 max mem: 33300 +Epoch: [14] [3720/4276] eta: 0:28:02 lr: 3.2906830250706015e-05 loss: 0.1165 (0.1410) time: 3.0018 data: 0.0079 max mem: 33300 +Epoch: [14] [3730/4276] eta: 0:27:32 lr: 3.290407409370657e-05 loss: 0.1361 (0.1411) time: 3.0117 data: 0.0078 max mem: 33300 +Epoch: [14] [3740/4276] eta: 0:27:02 lr: 3.290131791105521e-05 loss: 0.1380 (0.1410) time: 3.0782 data: 0.0083 max mem: 33300 +Epoch: [14] [3750/4276] eta: 0:26:31 lr: 3.289856170274931e-05 loss: 0.1334 (0.1410) time: 3.1384 data: 0.0088 max mem: 33300 +Epoch: [14] [3760/4276] eta: 0:26:01 lr: 3.289580546878624e-05 loss: 0.1203 (0.1410) time: 3.0706 data: 0.0088 max mem: 33300 +Epoch: [14] [3770/4276] eta: 0:25:31 lr: 3.289304920916339e-05 loss: 0.1307 (0.1410) time: 3.0123 data: 0.0081 max mem: 33300 +Epoch: [14] [3780/4276] eta: 0:25:01 lr: 3.2890292923878105e-05 loss: 0.1376 (0.1410) time: 3.0359 data: 0.0084 max mem: 33300 +Epoch: [14] [3790/4276] eta: 0:24:30 lr: 3.288753661292777e-05 loss: 0.1285 (0.1410) time: 3.0657 data: 0.0083 max mem: 33300 +Epoch: [14] [3800/4276] eta: 0:24:00 lr: 3.2884780276309756e-05 loss: 0.1370 (0.1410) time: 3.0544 data: 0.0079 max mem: 33300 +Epoch: [14] [3810/4276] eta: 0:23:30 lr: 3.288202391402143e-05 loss: 0.1370 (0.1409) time: 3.0622 data: 0.0087 max mem: 33300 +Epoch: [14] [3820/4276] eta: 0:23:00 lr: 3.287926752606017e-05 loss: 0.1186 (0.1409) time: 3.0768 data: 0.0086 max mem: 33300 +Epoch: [14] [3830/4276] eta: 0:22:30 lr: 3.2876511112423335e-05 loss: 0.1262 (0.1409) time: 3.0504 data: 0.0079 max mem: 33300 +Epoch: [14] [3840/4276] eta: 0:22:00 lr: 3.287375467310831e-05 loss: 0.1276 (0.1408) time: 3.1562 data: 0.0084 max mem: 33300 +Epoch: [14] [3850/4276] eta: 0:21:29 lr: 3.287099820811245e-05 loss: 0.1184 (0.1408) time: 3.1833 data: 0.0087 max mem: 33300 +Epoch: [14] [3860/4276] eta: 0:20:59 lr: 3.2868241717433115e-05 loss: 0.1253 (0.1408) time: 3.0987 data: 0.0082 max mem: 33300 +Epoch: [14] [3870/4276] eta: 0:20:29 lr: 3.286548520106769e-05 loss: 0.1407 (0.1408) time: 3.0984 data: 0.0077 max mem: 33300 +Epoch: [14] [3880/4276] eta: 0:19:59 lr: 3.286272865901353e-05 loss: 0.1341 (0.1408) time: 3.0958 data: 0.0076 max mem: 33300 +Epoch: [14] [3890/4276] eta: 0:19:28 lr: 3.285997209126801e-05 loss: 0.1273 (0.1408) time: 3.0730 data: 0.0076 max mem: 33300 +Epoch: [14] [3900/4276] eta: 0:18:58 lr: 3.285721549782849e-05 loss: 0.1324 (0.1408) time: 3.0146 data: 0.0073 max mem: 33300 +Epoch: [14] [3910/4276] eta: 0:18:28 lr: 3.2854458878692335e-05 loss: 0.1249 (0.1407) time: 3.0325 data: 0.0080 max mem: 33300 +Epoch: [14] [3920/4276] eta: 0:17:58 lr: 3.285170223385692e-05 loss: 0.1176 (0.1407) time: 3.0574 data: 0.0084 max mem: 33300 +Epoch: [14] [3930/4276] eta: 0:17:27 lr: 3.284894556331959e-05 loss: 0.1176 (0.1407) time: 3.0494 data: 0.0075 max mem: 33300 +Epoch: [14] [3940/4276] eta: 0:16:57 lr: 3.2846188867077736e-05 loss: 0.1280 (0.1407) time: 3.0589 data: 0.0074 max mem: 33300 +Epoch: [14] [3950/4276] eta: 0:16:27 lr: 3.284343214512869e-05 loss: 0.1204 (0.1406) time: 3.0620 data: 0.0080 max mem: 33300 +Epoch: [14] [3960/4276] eta: 0:15:57 lr: 3.284067539746984e-05 loss: 0.1204 (0.1406) time: 3.0890 data: 0.0078 max mem: 33300 +Epoch: [14] [3970/4276] eta: 0:15:26 lr: 3.2837918624098526e-05 loss: 0.1366 (0.1406) time: 3.1122 data: 0.0080 max mem: 33300 +Epoch: [14] [3980/4276] eta: 0:14:56 lr: 3.283516182501213e-05 loss: 0.1347 (0.1406) time: 3.0617 data: 0.0082 max mem: 33300 +Epoch: [14] [3990/4276] eta: 0:14:26 lr: 3.2832405000208005e-05 loss: 0.1331 (0.1406) time: 3.0508 data: 0.0082 max mem: 33300 +Epoch: [14] [4000/4276] eta: 0:13:56 lr: 3.2829648149683515e-05 loss: 0.1205 (0.1406) time: 3.0420 data: 0.0083 max mem: 33300 +Epoch: [14] [4010/4276] eta: 0:13:25 lr: 3.282689127343601e-05 loss: 0.1250 (0.1406) time: 2.9879 data: 0.0081 max mem: 33300 +Epoch: [14] [4020/4276] eta: 0:12:55 lr: 3.2824134371462866e-05 loss: 0.1343 (0.1406) time: 2.9957 data: 0.0082 max mem: 33300 +Epoch: [14] [4030/4276] eta: 0:12:25 lr: 3.282137744376142e-05 loss: 0.1308 (0.1405) time: 2.9957 data: 0.0079 max mem: 33300 +Epoch: [14] [4040/4276] eta: 0:11:54 lr: 3.281862049032905e-05 loss: 0.1342 (0.1406) time: 2.9865 data: 0.0075 max mem: 33300 +Epoch: [14] [4050/4276] eta: 0:11:24 lr: 3.281586351116311e-05 loss: 0.1342 (0.1406) time: 3.0055 data: 0.0075 max mem: 33300 +Epoch: [14] [4060/4276] eta: 0:10:54 lr: 3.281310650626095e-05 loss: 0.1338 (0.1406) time: 3.0108 data: 0.0077 max mem: 33300 +Epoch: [14] [4070/4276] eta: 0:10:23 lr: 3.281034947561993e-05 loss: 0.1403 (0.1406) time: 2.9880 data: 0.0077 max mem: 33300 +Epoch: [14] [4080/4276] eta: 0:09:53 lr: 3.280759241923742e-05 loss: 0.1353 (0.1406) time: 2.9734 data: 0.0079 max mem: 33300 +Epoch: [14] [4090/4276] eta: 0:09:23 lr: 3.280483533711075e-05 loss: 0.1391 (0.1407) time: 2.9637 data: 0.0083 max mem: 33300 +Epoch: [14] [4100/4276] eta: 0:08:52 lr: 3.2802078229237306e-05 loss: 0.1488 (0.1407) time: 2.9689 data: 0.0082 max mem: 33300 +Epoch: [14] [4110/4276] eta: 0:08:22 lr: 3.2799321095614414e-05 loss: 0.1468 (0.1407) time: 2.9782 data: 0.0083 max mem: 33300 +Epoch: [14] [4120/4276] eta: 0:07:52 lr: 3.2796563936239444e-05 loss: 0.1624 (0.1408) time: 2.9853 data: 0.0081 max mem: 33300 +Epoch: [14] [4130/4276] eta: 0:07:22 lr: 3.279380675110975e-05 loss: 0.1480 (0.1408) time: 2.9955 data: 0.0076 max mem: 33300 +Epoch: [14] [4140/4276] eta: 0:06:51 lr: 3.279104954022268e-05 loss: 0.1405 (0.1407) time: 3.0134 data: 0.0080 max mem: 33300 +Epoch: [14] [4150/4276] eta: 0:06:21 lr: 3.2788292303575596e-05 loss: 0.1361 (0.1407) time: 3.0116 data: 0.0083 max mem: 33300 +Epoch: [14] [4160/4276] eta: 0:05:51 lr: 3.278553504116584e-05 loss: 0.1385 (0.1408) time: 2.9691 data: 0.0083 max mem: 33300 +Epoch: [14] [4170/4276] eta: 0:05:20 lr: 3.2782777752990766e-05 loss: 0.1553 (0.1408) time: 2.9393 data: 0.0089 max mem: 33300 +Epoch: [14] [4180/4276] eta: 0:04:50 lr: 3.278002043904773e-05 loss: 0.1391 (0.1408) time: 2.9474 data: 0.0094 max mem: 33300 +Epoch: [14] [4190/4276] eta: 0:04:20 lr: 3.2777263099334075e-05 loss: 0.1285 (0.1408) time: 2.9509 data: 0.0091 max mem: 33300 +Epoch: [14] [4200/4276] eta: 0:03:50 lr: 3.277450573384716e-05 loss: 0.1435 (0.1408) time: 2.9439 data: 0.0085 max mem: 33300 +Epoch: [14] [4210/4276] eta: 0:03:19 lr: 3.277174834258433e-05 loss: 0.1501 (0.1409) time: 2.9713 data: 0.0085 max mem: 33300 +Epoch: [14] [4220/4276] eta: 0:02:49 lr: 3.276899092554294e-05 loss: 0.1464 (0.1409) time: 3.0159 data: 0.0083 max mem: 33300 +Epoch: [14] [4230/4276] eta: 0:02:19 lr: 3.276623348272033e-05 loss: 0.1598 (0.1410) time: 3.0239 data: 0.0081 max mem: 33300 +Epoch: [14] [4240/4276] eta: 0:01:48 lr: 3.276347601411385e-05 loss: 0.1540 (0.1410) time: 3.0141 data: 0.0084 max mem: 33300 +Epoch: [14] [4250/4276] eta: 0:01:18 lr: 3.2760718519720865e-05 loss: 0.1400 (0.1410) time: 3.0051 data: 0.0082 max mem: 33300 +Epoch: [14] [4260/4276] eta: 0:00:48 lr: 3.275796099953869e-05 loss: 0.1318 (0.1410) time: 3.0021 data: 0.0079 max mem: 33300 +Epoch: [14] [4270/4276] eta: 0:00:18 lr: 3.27552034535647e-05 loss: 0.1450 (0.1411) time: 2.9937 data: 0.0075 max mem: 33300 +Epoch: [14] Total time: 3:35:41 +Test: [ 0/21770] eta: 8:51:35 time: 1.4651 data: 1.4219 max mem: 33300 +Test: [ 100/21770] eta: 0:19:08 time: 0.0393 data: 0.0009 max mem: 33300 +Test: [ 200/21770] eta: 0:16:35 time: 0.0392 data: 0.0009 max mem: 33300 +Test: [ 300/21770] eta: 0:15:42 time: 0.0394 data: 0.0009 max mem: 33300 +Test: [ 400/21770] eta: 0:15:13 time: 0.0392 data: 0.0009 max mem: 33300 +Test: [ 500/21770] eta: 0:14:54 time: 0.0393 data: 0.0009 max mem: 33300 +Test: [ 600/21770] eta: 0:14:41 time: 0.0394 data: 0.0009 max mem: 33300 +Test: [ 700/21770] eta: 0:14:31 time: 0.0399 data: 0.0010 max mem: 33300 +Test: [ 800/21770] eta: 0:14:22 time: 0.0398 data: 0.0009 max mem: 33300 +Test: [ 900/21770] eta: 0:14:14 time: 0.0393 data: 0.0009 max mem: 33300 +Test: [ 1000/21770] eta: 0:14:08 time: 0.0400 data: 0.0009 max mem: 33300 +Test: [ 1100/21770] eta: 0:14:02 time: 0.0399 data: 0.0010 max mem: 33300 +Test: [ 1200/21770] eta: 0:13:56 time: 0.0399 data: 0.0010 max mem: 33300 +Test: [ 1300/21770] eta: 0:13:50 time: 0.0394 data: 0.0009 max mem: 33300 +Test: [ 1400/21770] eta: 0:13:45 time: 0.0395 data: 0.0009 max mem: 33300 +Test: [ 1500/21770] eta: 0:13:38 time: 0.0389 data: 0.0009 max mem: 33300 +Test: [ 1600/21770] eta: 0:13:33 time: 0.0400 data: 0.0011 max mem: 33300 +Test: [ 1700/21770] eta: 0:13:27 time: 0.0385 data: 0.0011 max mem: 33300 +Test: [ 1800/21770] eta: 0:13:22 time: 0.0383 data: 0.0009 max mem: 33300 +Test: [ 1900/21770] eta: 0:13:16 time: 0.0384 data: 0.0009 max mem: 33300 +Test: [ 2000/21770] eta: 0:13:10 time: 0.0384 data: 0.0009 max mem: 33300 +Test: [ 2100/21770] eta: 0:13:04 time: 0.0381 data: 0.0009 max mem: 33300 +Test: [ 2200/21770] eta: 0:12:59 time: 0.0382 data: 0.0009 max mem: 33300 +Test: [ 2300/21770] eta: 0:12:53 time: 0.0381 data: 0.0009 max mem: 33300 +Test: [ 2400/21770] eta: 0:12:48 time: 0.0387 data: 0.0010 max mem: 33300 +Test: [ 2500/21770] eta: 0:12:43 time: 0.0383 data: 0.0009 max mem: 33300 +Test: [ 2600/21770] eta: 0:12:38 time: 0.0383 data: 0.0010 max mem: 33300 +Test: [ 2700/21770] eta: 0:12:34 time: 0.0388 data: 0.0010 max mem: 33300 +Test: [ 2800/21770] eta: 0:12:29 time: 0.0386 data: 0.0010 max mem: 33300 +Test: [ 2900/21770] eta: 0:12:25 time: 0.0390 data: 0.0010 max mem: 33300 +Test: [ 3000/21770] eta: 0:12:21 time: 0.0390 data: 0.0009 max mem: 33300 +Test: [ 3100/21770] eta: 0:12:17 time: 0.0397 data: 0.0010 max mem: 33300 +Test: [ 3200/21770] eta: 0:12:13 time: 0.0400 data: 0.0009 max mem: 33300 +Test: [ 3300/21770] eta: 0:12:09 time: 0.0396 data: 0.0010 max mem: 33300 +Test: [ 3400/21770] eta: 0:12:05 time: 0.0389 data: 0.0009 max mem: 33300 +Test: [ 3500/21770] eta: 0:12:01 time: 0.0391 data: 0.0010 max mem: 33300 +Test: [ 3600/21770] eta: 0:11:57 time: 0.0390 data: 0.0010 max mem: 33300 +Test: [ 3700/21770] eta: 0:11:53 time: 0.0387 data: 0.0010 max mem: 33300 +Test: [ 3800/21770] eta: 0:11:48 time: 0.0387 data: 0.0010 max mem: 33300 +Test: [ 3900/21770] eta: 0:11:44 time: 0.0389 data: 0.0010 max mem: 33300 +Test: [ 4000/21770] eta: 0:11:40 time: 0.0398 data: 0.0009 max mem: 33300 +Test: [ 4100/21770] eta: 0:11:36 time: 0.0397 data: 0.0010 max mem: 33300 +Test: [ 4200/21770] eta: 0:11:32 time: 0.0393 data: 0.0009 max mem: 33300 +Test: [ 4300/21770] eta: 0:11:29 time: 0.0392 data: 0.0009 max mem: 33300 +Test: [ 4400/21770] eta: 0:11:25 time: 0.0397 data: 0.0010 max mem: 33300 +Test: [ 4500/21770] eta: 0:11:21 time: 0.0391 data: 0.0010 max mem: 33300 +Test: [ 4600/21770] eta: 0:11:17 time: 0.0391 data: 0.0010 max mem: 33300 +Test: [ 4700/21770] eta: 0:11:12 time: 0.0392 data: 0.0010 max mem: 33300 +Test: [ 4800/21770] eta: 0:11:08 time: 0.0388 data: 0.0009 max mem: 33300 +Test: [ 4900/21770] eta: 0:11:05 time: 0.0399 data: 0.0009 max mem: 33300 +Test: [ 5000/21770] eta: 0:11:01 time: 0.0393 data: 0.0009 max mem: 33300 +Test: [ 5100/21770] eta: 0:10:57 time: 0.0393 data: 0.0009 max mem: 33300 +Test: [ 5200/21770] eta: 0:10:53 time: 0.0395 data: 0.0009 max mem: 33300 +Test: [ 5300/21770] eta: 0:10:49 time: 0.0394 data: 0.0009 max mem: 33300 +Test: [ 5400/21770] eta: 0:10:45 time: 0.0396 data: 0.0009 max mem: 33300 +Test: [ 5500/21770] eta: 0:10:41 time: 0.0397 data: 0.0010 max mem: 33300 +Test: [ 5600/21770] eta: 0:10:37 time: 0.0396 data: 0.0009 max mem: 33300 +Test: [ 5700/21770] eta: 0:10:33 time: 0.0391 data: 0.0009 max mem: 33300 +Test: [ 5800/21770] eta: 0:10:29 time: 0.0401 data: 0.0009 max mem: 33300 +Test: [ 5900/21770] eta: 0:10:25 time: 0.0395 data: 0.0009 max mem: 33300 +Test: [ 6000/21770] eta: 0:10:21 time: 0.0397 data: 0.0009 max mem: 33300 +Test: [ 6100/21770] eta: 0:10:17 time: 0.0395 data: 0.0009 max mem: 33300 +Test: [ 6200/21770] eta: 0:10:14 time: 0.0399 data: 0.0009 max mem: 33300 +Test: [ 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time: 0.0390 data: 0.0009 max mem: 33300 +Test: [ 7700/21770] eta: 0:09:14 time: 0.0391 data: 0.0009 max mem: 33300 +Test: [ 7800/21770] eta: 0:09:10 time: 0.0391 data: 0.0010 max mem: 33300 +Test: [ 7900/21770] eta: 0:09:06 time: 0.0391 data: 0.0010 max mem: 33300 +Test: [ 8000/21770] eta: 0:09:02 time: 0.0392 data: 0.0010 max mem: 33300 +Test: [ 8100/21770] eta: 0:08:58 time: 0.0392 data: 0.0009 max mem: 33300 +Test: [ 8200/21770] eta: 0:08:54 time: 0.0389 data: 0.0009 max mem: 33300 +Test: [ 8300/21770] eta: 0:08:50 time: 0.0396 data: 0.0010 max mem: 33300 +Test: [ 8400/21770] eta: 0:08:46 time: 0.0388 data: 0.0009 max mem: 33300 +Test: [ 8500/21770] eta: 0:08:42 time: 0.0391 data: 0.0009 max mem: 33300 +Test: [ 8600/21770] eta: 0:08:38 time: 0.0390 data: 0.0009 max mem: 33300 +Test: [ 8700/21770] eta: 0:08:34 time: 0.0391 data: 0.0009 max mem: 33300 +Test: [ 8800/21770] eta: 0:08:30 time: 0.0389 data: 0.0009 max mem: 33300 +Test: [ 8900/21770] eta: 0:08:26 time: 0.0391 data: 0.0009 max mem: 33300 +Test: [ 9000/21770] eta: 0:08:22 time: 0.0389 data: 0.0009 max mem: 33300 +Test: [ 9100/21770] eta: 0:08:18 time: 0.0383 data: 0.0009 max mem: 33300 +Test: [ 9200/21770] eta: 0:08:14 time: 0.0386 data: 0.0010 max mem: 33300 +Test: [ 9300/21770] eta: 0:08:10 time: 0.0387 data: 0.0009 max mem: 33300 +Test: [ 9400/21770] eta: 0:08:06 time: 0.0390 data: 0.0010 max mem: 33300 +Test: [ 9500/21770] eta: 0:08:02 time: 0.0386 data: 0.0009 max mem: 33300 +Test: [ 9600/21770] eta: 0:07:58 time: 0.0387 data: 0.0009 max mem: 33300 +Test: [ 9700/21770] eta: 0:07:54 time: 0.0391 data: 0.0010 max mem: 33300 +Test: [ 9800/21770] eta: 0:07:50 time: 0.0388 data: 0.0010 max mem: 33300 +Test: [ 9900/21770] eta: 0:07:46 time: 0.0392 data: 0.0011 max mem: 33300 +Test: [10000/21770] eta: 0:07:42 time: 0.0390 data: 0.0009 max mem: 33300 +Test: [10100/21770] eta: 0:07:39 time: 0.0394 data: 0.0010 max mem: 33300 +Test: [10200/21770] eta: 0:07:35 time: 0.0389 data: 0.0010 max mem: 33300 +Test: [10300/21770] eta: 0:07:31 time: 0.0396 data: 0.0011 max mem: 33300 +Test: [10400/21770] eta: 0:07:27 time: 0.0389 data: 0.0009 max mem: 33300 +Test: [10500/21770] eta: 0:07:23 time: 0.0386 data: 0.0010 max mem: 33300 +Test: [10600/21770] eta: 0:07:19 time: 0.0387 data: 0.0010 max mem: 33300 +Test: [10700/21770] eta: 0:07:15 time: 0.0388 data: 0.0010 max mem: 33300 +Test: [10800/21770] eta: 0:07:11 time: 0.0380 data: 0.0009 max mem: 33300 +Test: [10900/21770] eta: 0:07:07 time: 0.0381 data: 0.0010 max mem: 33300 +Test: [11000/21770] eta: 0:07:03 time: 0.0381 data: 0.0009 max mem: 33300 +Test: [11100/21770] eta: 0:06:59 time: 0.0383 data: 0.0009 max mem: 33300 +Test: [11200/21770] eta: 0:06:55 time: 0.0382 data: 0.0010 max mem: 33300 +Test: [11300/21770] eta: 0:06:51 time: 0.0384 data: 0.0009 max mem: 33300 +Test: [11400/21770] eta: 0:06:47 time: 0.0385 data: 0.0010 max mem: 33300 +Test: [11500/21770] eta: 0:06:43 time: 0.0386 data: 0.0010 max mem: 33300 +Test: [11600/21770] eta: 0:06:39 time: 0.0381 data: 0.0010 max mem: 33300 +Test: [11700/21770] eta: 0:06:35 time: 0.0381 data: 0.0010 max mem: 33300 +Test: [11800/21770] eta: 0:06:31 time: 0.0383 data: 0.0010 max mem: 33300 +Test: [11900/21770] eta: 0:06:27 time: 0.0387 data: 0.0009 max mem: 33300 +Test: [12000/21770] eta: 0:06:23 time: 0.0383 data: 0.0009 max mem: 33300 +Test: [12100/21770] eta: 0:06:19 time: 0.0385 data: 0.0010 max mem: 33300 +Test: [12200/21770] eta: 0:06:15 time: 0.0389 data: 0.0009 max mem: 33300 +Test: [12300/21770] eta: 0:06:11 time: 0.0396 data: 0.0011 max mem: 33300 +Test: [12400/21770] eta: 0:06:07 time: 0.0399 data: 0.0012 max mem: 33300 +Test: [12500/21770] eta: 0:06:03 time: 0.0391 data: 0.0011 max mem: 33300 +Test: [12600/21770] eta: 0:05:59 time: 0.0394 data: 0.0012 max mem: 33300 +Test: [12700/21770] eta: 0:05:55 time: 0.0392 data: 0.0012 max mem: 33300 +Test: [12800/21770] eta: 0:05:51 time: 0.0403 data: 0.0013 max mem: 33300 +Test: [12900/21770] eta: 0:05:47 time: 0.0394 data: 0.0010 max mem: 33300 +Test: [13000/21770] eta: 0:05:43 time: 0.0391 data: 0.0010 max mem: 33300 +Test: [13100/21770] eta: 0:05:40 time: 0.0396 data: 0.0010 max mem: 33300 +Test: [13200/21770] eta: 0:05:36 time: 0.0400 data: 0.0010 max mem: 33300 +Test: [13300/21770] eta: 0:05:32 time: 0.0398 data: 0.0011 max mem: 33300 +Test: [13400/21770] eta: 0:05:28 time: 0.0387 data: 0.0010 max mem: 33300 +Test: [13500/21770] eta: 0:05:24 time: 0.0409 data: 0.0010 max mem: 33300 +Test: [13600/21770] eta: 0:05:20 time: 0.0405 data: 0.0010 max mem: 33300 +Test: [13700/21770] eta: 0:05:16 time: 0.0402 data: 0.0010 max mem: 33300 +Test: [13800/21770] eta: 0:05:12 time: 0.0402 data: 0.0011 max mem: 33300 +Test: [13900/21770] eta: 0:05:09 time: 0.0397 data: 0.0011 max mem: 33300 +Test: [14000/21770] eta: 0:05:05 time: 0.0393 data: 0.0011 max mem: 33300 +Test: [14100/21770] eta: 0:05:01 time: 0.0392 data: 0.0012 max mem: 33300 +Test: [14200/21770] eta: 0:04:57 time: 0.0393 data: 0.0011 max mem: 33300 +Test: [14300/21770] eta: 0:04:53 time: 0.0393 data: 0.0011 max mem: 33300 +Test: [14400/21770] eta: 0:04:49 time: 0.0406 data: 0.0013 max mem: 33300 +Test: [14500/21770] eta: 0:04:45 time: 0.0400 data: 0.0011 max mem: 33300 +Test: [14600/21770] eta: 0:04:41 time: 0.0394 data: 0.0010 max mem: 33300 +Test: [14700/21770] eta: 0:04:37 time: 0.0401 data: 0.0010 max mem: 33300 +Test: [14800/21770] eta: 0:04:33 time: 0.0392 data: 0.0010 max mem: 33300 +Test: [14900/21770] eta: 0:04:29 time: 0.0393 data: 0.0010 max mem: 33300 +Test: [15000/21770] eta: 0:04:26 time: 0.0391 data: 0.0010 max mem: 33300 +Test: [15100/21770] eta: 0:04:22 time: 0.0384 data: 0.0010 max mem: 33300 +Test: [15200/21770] eta: 0:04:18 time: 0.0389 data: 0.0010 max mem: 33300 +Test: [15300/21770] eta: 0:04:14 time: 0.0389 data: 0.0010 max mem: 33300 +Test: [15400/21770] eta: 0:04:10 time: 0.0387 data: 0.0010 max mem: 33300 +Test: [15500/21770] eta: 0:04:06 time: 0.0397 data: 0.0010 max mem: 33300 +Test: [15600/21770] eta: 0:04:02 time: 0.0393 data: 0.0011 max mem: 33300 +Test: [15700/21770] eta: 0:03:58 time: 0.0400 data: 0.0012 max mem: 33300 +Test: [15800/21770] eta: 0:03:54 time: 0.0396 data: 0.0012 max mem: 33300 +Test: [15900/21770] eta: 0:03:50 time: 0.0394 data: 0.0012 max mem: 33300 +Test: [16000/21770] eta: 0:03:46 time: 0.0390 data: 0.0012 max mem: 33300 +Test: [16100/21770] eta: 0:03:42 time: 0.0401 data: 0.0013 max mem: 33300 +Test: [16200/21770] eta: 0:03:38 time: 0.0402 data: 0.0013 max mem: 33300 +Test: [16300/21770] eta: 0:03:34 time: 0.0402 data: 0.0010 max mem: 33300 +Test: [16400/21770] eta: 0:03:31 time: 0.0399 data: 0.0010 max mem: 33300 +Test: [16500/21770] eta: 0:03:27 time: 0.0386 data: 0.0010 max mem: 33300 +Test: [16600/21770] eta: 0:03:23 time: 0.0386 data: 0.0010 max mem: 33300 +Test: [16700/21770] eta: 0:03:19 time: 0.0389 data: 0.0011 max mem: 33300 +Test: [16800/21770] eta: 0:03:15 time: 0.0386 data: 0.0010 max mem: 33300 +Test: [16900/21770] eta: 0:03:11 time: 0.0386 data: 0.0010 max mem: 33300 +Test: [17000/21770] eta: 0:03:07 time: 0.0396 data: 0.0011 max mem: 33300 +Test: [17100/21770] eta: 0:03:03 time: 0.0391 data: 0.0010 max mem: 33300 +Test: [17200/21770] eta: 0:02:59 time: 0.0396 data: 0.0010 max mem: 33300 +Test: [17300/21770] eta: 0:02:55 time: 0.0396 data: 0.0012 max mem: 33300 +Test: [17400/21770] eta: 0:02:51 time: 0.0386 data: 0.0010 max mem: 33300 +Test: [17500/21770] eta: 0:02:47 time: 0.0395 data: 0.0011 max mem: 33300 +Test: [17600/21770] eta: 0:02:43 time: 0.0383 data: 0.0009 max mem: 33300 +Test: [17700/21770] eta: 0:02:39 time: 0.0387 data: 0.0010 max mem: 33300 +Test: [17800/21770] eta: 0:02:35 time: 0.0385 data: 0.0009 max mem: 33300 +Test: [17900/21770] eta: 0:02:31 time: 0.0387 data: 0.0009 max mem: 33300 +Test: [18000/21770] eta: 0:02:28 time: 0.0385 data: 0.0009 max mem: 33300 +Test: [18100/21770] eta: 0:02:24 time: 0.0390 data: 0.0010 max mem: 33300 +Test: [18200/21770] eta: 0:02:20 time: 0.0388 data: 0.0010 max mem: 33300 +Test: [18300/21770] eta: 0:02:16 time: 0.0386 data: 0.0010 max mem: 33300 +Test: [18400/21770] eta: 0:02:12 time: 0.0384 data: 0.0010 max mem: 33300 +Test: [18500/21770] eta: 0:02:08 time: 0.0387 data: 0.0010 max mem: 33300 +Test: [18600/21770] eta: 0:02:04 time: 0.0389 data: 0.0010 max mem: 33300 +Test: [18700/21770] eta: 0:02:00 time: 0.0388 data: 0.0009 max mem: 33300 +Test: [18800/21770] eta: 0:01:56 time: 0.0388 data: 0.0009 max mem: 33300 +Test: [18900/21770] eta: 0:01:52 time: 0.0387 data: 0.0010 max mem: 33300 +Test: [19000/21770] eta: 0:01:48 time: 0.0386 data: 0.0010 max mem: 33300 +Test: [19100/21770] eta: 0:01:44 time: 0.0390 data: 0.0010 max mem: 33300 +Test: [19200/21770] eta: 0:01:40 time: 0.0388 data: 0.0010 max mem: 33300 +Test: [19300/21770] eta: 0:01:36 time: 0.0386 data: 0.0009 max mem: 33300 +Test: [19400/21770] eta: 0:01:32 time: 0.0387 data: 0.0009 max mem: 33300 +Test: [19500/21770] eta: 0:01:29 time: 0.0386 data: 0.0010 max mem: 33300 +Test: [19600/21770] eta: 0:01:25 time: 0.0385 data: 0.0010 max mem: 33300 +Test: [19700/21770] eta: 0:01:21 time: 0.0385 data: 0.0010 max mem: 33300 +Test: [19800/21770] eta: 0:01:17 time: 0.0387 data: 0.0011 max mem: 33300 +Test: [19900/21770] eta: 0:01:13 time: 0.0385 data: 0.0010 max mem: 33300 +Test: [20000/21770] eta: 0:01:09 time: 0.0381 data: 0.0009 max mem: 33300 +Test: [20100/21770] eta: 0:01:05 time: 0.0385 data: 0.0010 max mem: 33300 +Test: [20200/21770] eta: 0:01:01 time: 0.0387 data: 0.0011 max mem: 33300 +Test: [20300/21770] eta: 0:00:57 time: 0.0385 data: 0.0010 max mem: 33300 +Test: [20400/21770] eta: 0:00:53 time: 0.0384 data: 0.0010 max mem: 33300 +Test: [20500/21770] eta: 0:00:49 time: 0.0389 data: 0.0011 max mem: 33300 +Test: [20600/21770] eta: 0:00:45 time: 0.0391 data: 0.0009 max mem: 33300 +Test: [20700/21770] eta: 0:00:41 time: 0.0398 data: 0.0011 max mem: 33300 +Test: [20800/21770] eta: 0:00:38 time: 0.0388 data: 0.0011 max mem: 33300 +Test: [20900/21770] eta: 0:00:34 time: 0.0397 data: 0.0011 max mem: 33300 +Test: [21000/21770] eta: 0:00:30 time: 0.0390 data: 0.0009 max mem: 33300 +Test: [21100/21770] eta: 0:00:26 time: 0.0392 data: 0.0011 max mem: 33300 +Test: [21200/21770] eta: 0:00:22 time: 0.0396 data: 0.0012 max mem: 33300 +Test: [21300/21770] eta: 0:00:18 time: 0.0400 data: 0.0012 max mem: 33300 +Test: [21400/21770] eta: 0:00:14 time: 0.0408 data: 0.0014 max mem: 33300 +Test: [21500/21770] eta: 0:00:10 time: 0.0387 data: 0.0010 max mem: 33300 +Test: [21600/21770] eta: 0:00:06 time: 0.0386 data: 0.0010 max mem: 33300 +Test: [21700/21770] eta: 0:00:02 time: 0.0388 data: 0.0011 max mem: 33300 +Test: Total time: 0:14:13 +Final results: +Mean IoU is 0.00 + + precision@0.5 = 0.00 + precision@0.6 = 0.00 + precision@0.7 = 0.00 + precision@0.8 = 0.00 + precision@0.9 = 0.00 + overall IoU = 0.00 + mean IoU = 0.00 + +Mean accuracy for one-to-zero sample is 100.00 + +Average object IoU 0.0 +Overall IoU 0.0 +Epoch: [15] [ 0/4276] eta: 6:16:59 lr: 3.275354891359912e-05 loss: 0.1102 (0.1102) time: 5.2900 data: 2.1394 max mem: 33300 +Epoch: [15] [ 10/4276] eta: 3:46:10 lr: 3.275079132635268e-05 loss: 0.1318 (0.1391) time: 3.1812 data: 0.2015 max mem: 33300 +Epoch: [15] [ 20/4276] eta: 3:39:55 lr: 3.274803371330752e-05 loss: 0.1343 (0.1490) time: 2.9910 data: 0.0075 max mem: 33300 +Epoch: [15] [ 30/4276] eta: 3:37:25 lr: 3.274527607446097e-05 loss: 0.1385 (0.1459) time: 3.0127 data: 0.0079 max mem: 33300 +Epoch: [15] [ 40/4276] eta: 3:35:39 lr: 3.2742518409810386e-05 loss: 0.1446 (0.1484) time: 3.0064 data: 0.0082 max mem: 33300 +Epoch: [15] [ 50/4276] eta: 3:34:30 lr: 3.273976071935311e-05 loss: 0.1450 (0.1465) time: 3.0039 data: 0.0082 max mem: 33300 +Epoch: [15] [ 60/4276] eta: 3:33:29 lr: 3.2737003003086476e-05 loss: 0.1336 (0.1448) time: 3.0052 data: 0.0079 max mem: 33300 +Epoch: [15] [ 70/4276] eta: 3:32:47 lr: 3.2734245261007835e-05 loss: 0.1303 (0.1435) time: 3.0097 data: 0.0078 max mem: 33300 +Epoch: [15] [ 80/4276] eta: 3:32:03 lr: 3.273148749311453e-05 loss: 0.1303 (0.1444) time: 3.0135 data: 0.0079 max mem: 33300 +Epoch: [15] [ 90/4276] eta: 3:31:11 lr: 3.2728729699403903e-05 loss: 0.1280 (0.1427) time: 2.9975 data: 0.0076 max mem: 33300 +Epoch: [15] [ 100/4276] eta: 3:30:23 lr: 3.272597187987329e-05 loss: 0.1280 (0.1443) time: 2.9855 data: 0.0076 max mem: 33300 +Epoch: [15] [ 110/4276] eta: 3:29:46 lr: 3.272321403452003e-05 loss: 0.1341 (0.1442) time: 2.9950 data: 0.0074 max mem: 33300 +Epoch: [15] [ 120/4276] eta: 3:29:15 lr: 3.2720456163341474e-05 loss: 0.1308 (0.1437) time: 3.0116 data: 0.0074 max mem: 33300 +Epoch: [15] [ 130/4276] eta: 3:28:36 lr: 3.271769826633495e-05 loss: 0.1395 (0.1445) time: 3.0063 data: 0.0076 max mem: 33300 +Epoch: [15] [ 140/4276] eta: 3:28:02 lr: 3.27149403434978e-05 loss: 0.1320 (0.1436) time: 2.9999 data: 0.0075 max mem: 33300 +Epoch: [15] [ 150/4276] eta: 3:27:39 lr: 3.2712182394827365e-05 loss: 0.1315 (0.1434) time: 3.0251 data: 0.0073 max mem: 33300 +Epoch: [15] [ 160/4276] eta: 3:27:00 lr: 3.2709424420320986e-05 loss: 0.1372 (0.1437) time: 3.0136 data: 0.0071 max mem: 33300 +Epoch: [15] [ 170/4276] eta: 3:26:27 lr: 3.2706666419976e-05 loss: 0.1304 (0.1432) time: 2.9939 data: 0.0068 max mem: 33300 +Epoch: [15] [ 180/4276] eta: 3:25:55 lr: 3.270390839378974e-05 loss: 0.1286 (0.1432) time: 3.0078 data: 0.0071 max mem: 33300 +Epoch: [15] [ 190/4276] eta: 3:25:23 lr: 3.270115034175953e-05 loss: 0.1286 (0.1432) time: 3.0082 data: 0.0073 max mem: 33300 +Epoch: [15] [ 200/4276] eta: 3:24:51 lr: 3.269839226388273e-05 loss: 0.1318 (0.1427) time: 3.0087 data: 0.0073 max mem: 33300 +Epoch: [15] [ 210/4276] eta: 3:24:27 lr: 3.269563416015666e-05 loss: 0.1341 (0.1430) time: 3.0274 data: 0.0074 max mem: 33300 +Epoch: [15] [ 220/4276] eta: 3:23:57 lr: 3.269287603057866e-05 loss: 0.1285 (0.1427) time: 3.0322 data: 0.0078 max mem: 33300 +Epoch: [15] [ 230/4276] eta: 3:23:30 lr: 3.269011787514607e-05 loss: 0.1268 (0.1421) time: 3.0262 data: 0.0080 max mem: 33300 +Epoch: [15] [ 240/4276] eta: 3:22:59 lr: 3.268735969385621e-05 loss: 0.1337 (0.1420) time: 3.0236 data: 0.0078 max mem: 33300 +Epoch: [15] [ 250/4276] eta: 3:22:27 lr: 3.268460148670643e-05 loss: 0.1406 (0.1425) time: 3.0102 data: 0.0078 max mem: 33300 +Epoch: [15] [ 260/4276] eta: 3:21:58 lr: 3.268184325369404e-05 loss: 0.1425 (0.1425) time: 3.0143 data: 0.0076 max mem: 33300 +Epoch: [15] [ 270/4276] eta: 3:21:22 lr: 3.267908499481639e-05 loss: 0.1354 (0.1424) time: 3.0036 data: 0.0075 max mem: 33300 +Epoch: [15] [ 280/4276] eta: 3:20:47 lr: 3.267632671007081e-05 loss: 0.1345 (0.1419) time: 2.9827 data: 0.0077 max mem: 33300 +Epoch: [15] [ 290/4276] eta: 3:20:18 lr: 3.267356839945462e-05 loss: 0.1295 (0.1415) time: 3.0015 data: 0.0086 max mem: 33300 +Epoch: [15] [ 300/4276] eta: 3:19:50 lr: 3.267081006296517e-05 loss: 0.1289 (0.1413) time: 3.0261 data: 0.0094 max mem: 33300 +Epoch: [15] [ 310/4276] eta: 3:19:21 lr: 3.2668051700599774e-05 loss: 0.1279 (0.1407) time: 3.0264 data: 0.0093 max mem: 33300 +Epoch: [15] [ 320/4276] eta: 3:18:52 lr: 3.266529331235577e-05 loss: 0.1305 (0.1410) time: 3.0245 data: 0.0091 max mem: 33300 +Epoch: [15] [ 330/4276] eta: 3:18:20 lr: 3.266253489823048e-05 loss: 0.1404 (0.1411) time: 3.0161 data: 0.0089 max mem: 33300 +Epoch: [15] [ 340/4276] eta: 3:17:47 lr: 3.265977645822124e-05 loss: 0.1230 (0.1408) time: 2.9954 data: 0.0088 max mem: 33300 +Epoch: [15] [ 350/4276] eta: 3:17:26 lr: 3.2657017992325365e-05 loss: 0.1166 (0.1404) time: 3.0445 data: 0.0089 max mem: 33300 +Epoch: [15] [ 360/4276] eta: 3:16:56 lr: 3.26542595005402e-05 loss: 0.1395 (0.1413) time: 3.0575 data: 0.0090 max mem: 33300 +Epoch: [15] [ 370/4276] eta: 3:16:21 lr: 3.265150098286305e-05 loss: 0.1378 (0.1409) time: 2.9921 data: 0.0087 max mem: 33300 +Epoch: [15] [ 380/4276] eta: 3:15:51 lr: 3.264874243929127e-05 loss: 0.1281 (0.1408) time: 2.9978 data: 0.0085 max mem: 33300 +Epoch: [15] [ 390/4276] eta: 3:15:24 lr: 3.264598386982217e-05 loss: 0.1321 (0.1411) time: 3.0357 data: 0.0085 max mem: 33300 +Epoch: [15] [ 400/4276] eta: 3:14:57 lr: 3.264322527445307e-05 loss: 0.1416 (0.1411) time: 3.0468 data: 0.0085 max mem: 33300 +Epoch: [15] [ 410/4276] eta: 3:14:24 lr: 3.264046665318131e-05 loss: 0.1357 (0.1410) time: 3.0171 data: 0.0079 max mem: 33300 +Epoch: [15] [ 420/4276] eta: 3:13:51 lr: 3.2637708006004206e-05 loss: 0.1343 (0.1409) time: 2.9901 data: 0.0077 max mem: 33300 +Epoch: [15] [ 430/4276] eta: 3:13:20 lr: 3.2634949332919065e-05 loss: 0.1391 (0.1410) time: 2.9965 data: 0.0081 max mem: 33300 +Epoch: [15] [ 440/4276] eta: 3:12:49 lr: 3.263219063392324e-05 loss: 0.1431 (0.1407) time: 3.0026 data: 0.0081 max mem: 33300 +Epoch: [15] [ 450/4276] eta: 3:12:16 lr: 3.2629431909014035e-05 loss: 0.1340 (0.1406) time: 2.9983 data: 0.0080 max mem: 33300 +Epoch: [15] [ 460/4276] eta: 3:11:44 lr: 3.262667315818878e-05 loss: 0.1264 (0.1401) time: 2.9930 data: 0.0079 max mem: 33300 +Epoch: [15] [ 470/4276] eta: 3:11:16 lr: 3.26239143814448e-05 loss: 0.1142 (0.1398) time: 3.0158 data: 0.0077 max mem: 33300 +Epoch: [15] [ 480/4276] eta: 3:10:49 lr: 3.26211555787794e-05 loss: 0.1142 (0.1394) time: 3.0436 data: 0.0078 max mem: 33300 +Epoch: [15] [ 490/4276] eta: 3:10:17 lr: 3.261839675018992e-05 loss: 0.1133 (0.1389) time: 3.0199 data: 0.0077 max mem: 33300 +Epoch: [15] [ 500/4276] eta: 3:09:45 lr: 3.261563789567366e-05 loss: 0.1109 (0.1385) time: 2.9925 data: 0.0075 max mem: 33300 +Epoch: [15] [ 510/4276] eta: 3:09:13 lr: 3.261287901522796e-05 loss: 0.1109 (0.1383) time: 2.9936 data: 0.0079 max mem: 33300 +Epoch: [15] [ 520/4276] eta: 3:08:40 lr: 3.2610120108850127e-05 loss: 0.1348 (0.1382) time: 2.9871 data: 0.0082 max mem: 33300 +Epoch: [15] [ 530/4276] eta: 3:08:09 lr: 3.2607361176537484e-05 loss: 0.1287 (0.1380) time: 2.9857 data: 0.0079 max mem: 33300 +Epoch: [15] [ 540/4276] eta: 3:07:38 lr: 3.2604602218287345e-05 loss: 0.1206 (0.1376) time: 2.9994 data: 0.0081 max mem: 33300 +Epoch: [15] [ 550/4276] eta: 3:07:08 lr: 3.260184323409703e-05 loss: 0.1260 (0.1376) time: 3.0093 data: 0.0087 max mem: 33300 +Epoch: [15] [ 560/4276] eta: 3:06:40 lr: 3.2599084223963853e-05 loss: 0.1328 (0.1375) time: 3.0289 data: 0.0082 max mem: 33300 +Epoch: [15] [ 570/4276] eta: 3:06:10 lr: 3.2596325187885135e-05 loss: 0.1320 (0.1374) time: 3.0361 data: 0.0075 max mem: 33300 +Epoch: [15] [ 580/4276] eta: 3:05:42 lr: 3.2593566125858186e-05 loss: 0.1287 (0.1374) time: 3.0343 data: 0.0074 max mem: 33300 +Epoch: [15] [ 590/4276] eta: 3:05:11 lr: 3.2590807037880335e-05 loss: 0.1120 (0.1370) time: 3.0222 data: 0.0074 max mem: 33300 +Epoch: [15] [ 600/4276] eta: 3:04:40 lr: 3.258804792394888e-05 loss: 0.1149 (0.1369) time: 3.0025 data: 0.0073 max mem: 33300 +Epoch: [15] [ 610/4276] eta: 3:04:09 lr: 3.258528878406114e-05 loss: 0.1237 (0.1367) time: 2.9962 data: 0.0077 max mem: 33300 +Epoch: [15] [ 620/4276] eta: 3:03:38 lr: 3.258252961821444e-05 loss: 0.1331 (0.1367) time: 2.9972 data: 0.0079 max mem: 33300 +Epoch: [15] [ 630/4276] eta: 3:03:07 lr: 3.257977042640607e-05 loss: 0.1337 (0.1369) time: 3.0006 data: 0.0077 max mem: 33300 +Epoch: [15] [ 640/4276] eta: 3:02:36 lr: 3.257701120863337e-05 loss: 0.1375 (0.1369) time: 3.0023 data: 0.0076 max mem: 33300 +Epoch: [15] [ 650/4276] eta: 3:02:07 lr: 3.2574251964893635e-05 loss: 0.1333 (0.1370) time: 3.0154 data: 0.0075 max mem: 33300 +Epoch: [15] [ 660/4276] eta: 3:01:37 lr: 3.2571492695184175e-05 loss: 0.1372 (0.1372) time: 3.0241 data: 0.0076 max mem: 33300 +Epoch: [15] [ 670/4276] eta: 3:01:08 lr: 3.256873339950231e-05 loss: 0.1363 (0.1371) time: 3.0278 data: 0.0076 max mem: 33300 +Epoch: [15] [ 680/4276] eta: 3:00:37 lr: 3.2565974077845345e-05 loss: 0.1245 (0.1371) time: 3.0080 data: 0.0072 max mem: 33300 +Epoch: [15] [ 690/4276] eta: 3:00:06 lr: 3.256321473021059e-05 loss: 0.1316 (0.1371) time: 2.9990 data: 0.0075 max mem: 33300 +Epoch: [15] [ 700/4276] eta: 2:59:41 lr: 3.2560455356595366e-05 loss: 0.1296 (0.1370) time: 3.0639 data: 0.0084 max mem: 33300 +Epoch: [15] [ 710/4276] eta: 2:59:11 lr: 3.255769595699697e-05 loss: 0.1267 (0.1370) time: 3.0608 data: 0.0083 max mem: 33300 +Epoch: [15] [ 720/4276] eta: 2:58:40 lr: 3.255493653141271e-05 loss: 0.1325 (0.1369) time: 3.0050 data: 0.0080 max mem: 33300 +Epoch: [15] [ 730/4276] eta: 2:58:10 lr: 3.2552177079839896e-05 loss: 0.1325 (0.1369) time: 3.0072 data: 0.0080 max mem: 33300 +Epoch: [15] [ 740/4276] eta: 2:57:39 lr: 3.254941760227584e-05 loss: 0.1221 (0.1367) time: 3.0113 data: 0.0080 max mem: 33300 +Epoch: [15] [ 750/4276] eta: 2:57:11 lr: 3.2546658098717844e-05 loss: 0.1242 (0.1367) time: 3.0372 data: 0.0082 max mem: 33300 +Epoch: [15] [ 760/4276] eta: 2:56:43 lr: 3.254389856916321e-05 loss: 0.1300 (0.1366) time: 3.0514 data: 0.0081 max mem: 33300 +Epoch: [15] [ 770/4276] eta: 2:56:13 lr: 3.254113901360925e-05 loss: 0.1332 (0.1368) time: 3.0351 data: 0.0077 max mem: 33300 +Epoch: [15] [ 780/4276] eta: 2:55:43 lr: 3.253837943205328e-05 loss: 0.1351 (0.1369) time: 3.0209 data: 0.0076 max mem: 33300 +Epoch: [15] [ 790/4276] eta: 2:55:11 lr: 3.253561982449258e-05 loss: 0.1451 (0.1370) time: 2.9996 data: 0.0082 max mem: 33300 +Epoch: [15] [ 800/4276] eta: 2:54:41 lr: 3.253286019092448e-05 loss: 0.1330 (0.1370) time: 2.9976 data: 0.0085 max mem: 33300 +Epoch: [15] [ 810/4276] eta: 2:54:10 lr: 3.253010053134626e-05 loss: 0.1301 (0.1371) time: 3.0001 data: 0.0079 max mem: 33300 +Epoch: [15] [ 820/4276] eta: 2:53:39 lr: 3.2527340845755234e-05 loss: 0.1288 (0.1370) time: 2.9991 data: 0.0076 max mem: 33300 +Epoch: [15] [ 830/4276] eta: 2:53:09 lr: 3.25245811341487e-05 loss: 0.1310 (0.1371) time: 3.0166 data: 0.0080 max mem: 33300 +Epoch: [15] [ 840/4276] eta: 2:52:40 lr: 3.2521821396523975e-05 loss: 0.1404 (0.1372) time: 3.0302 data: 0.0079 max mem: 33300 +Epoch: [15] [ 850/4276] eta: 2:52:09 lr: 3.251906163287835e-05 loss: 0.1217 (0.1371) time: 3.0174 data: 0.0074 max mem: 33300 +Epoch: [15] [ 860/4276] eta: 2:51:38 lr: 3.251630184320912e-05 loss: 0.1293 (0.1371) time: 2.9993 data: 0.0073 max mem: 33300 +Epoch: [15] [ 870/4276] eta: 2:51:08 lr: 3.2513542027513596e-05 loss: 0.1367 (0.1371) time: 3.0053 data: 0.0075 max mem: 33300 +Epoch: [15] [ 880/4276] eta: 2:50:38 lr: 3.2510782185789065e-05 loss: 0.1312 (0.1372) time: 3.0111 data: 0.0074 max mem: 33300 +Epoch: [15] [ 890/4276] eta: 2:50:07 lr: 3.2508022318032846e-05 loss: 0.1520 (0.1374) time: 3.0083 data: 0.0078 max mem: 33300 +Epoch: [15] [ 900/4276] eta: 2:49:36 lr: 3.2505262424242216e-05 loss: 0.1414 (0.1373) time: 2.9995 data: 0.0084 max mem: 33300 +Epoch: [15] [ 910/4276] eta: 2:49:07 lr: 3.250250250441449e-05 loss: 0.1345 (0.1374) time: 3.0104 data: 0.0080 max mem: 33300 +Epoch: [15] [ 920/4276] eta: 2:48:38 lr: 3.2499742558546954e-05 loss: 0.1365 (0.1375) time: 3.0449 data: 0.0080 max mem: 33300 +Epoch: [15] [ 930/4276] eta: 2:48:08 lr: 3.2496982586636915e-05 loss: 0.1365 (0.1375) time: 3.0345 data: 0.0078 max mem: 33300 +Epoch: [15] [ 940/4276] eta: 2:47:37 lr: 3.249422258868167e-05 loss: 0.1291 (0.1374) time: 2.9987 data: 0.0074 max mem: 33300 +Epoch: [15] [ 950/4276] eta: 2:47:05 lr: 3.249146256467851e-05 loss: 0.1392 (0.1375) time: 2.9803 data: 0.0072 max mem: 33300 +Epoch: [15] [ 960/4276] eta: 2:46:33 lr: 3.248870251462472e-05 loss: 0.1447 (0.1375) time: 2.9594 data: 0.0076 max mem: 33300 +Epoch: [15] [ 970/4276] eta: 2:46:01 lr: 3.2485942438517605e-05 loss: 0.1447 (0.1376) time: 2.9604 data: 0.0078 max mem: 33300 +Epoch: [15] [ 980/4276] eta: 2:45:29 lr: 3.248318233635447e-05 loss: 0.1426 (0.1377) time: 2.9586 data: 0.0078 max mem: 33300 +Epoch: [15] [ 990/4276] eta: 2:44:58 lr: 3.248042220813259e-05 loss: 0.1384 (0.1376) time: 2.9658 data: 0.0086 max mem: 33300 +Epoch: [15] [1000/4276] eta: 2:44:28 lr: 3.247766205384928e-05 loss: 0.1342 (0.1377) time: 2.9993 data: 0.0087 max mem: 33300 +Epoch: [15] [1010/4276] eta: 2:43:56 lr: 3.247490187350182e-05 loss: 0.1250 (0.1376) time: 2.9925 data: 0.0076 max mem: 33300 +Epoch: [15] [1020/4276] eta: 2:43:25 lr: 3.2472141667087495e-05 loss: 0.1250 (0.1376) time: 2.9717 data: 0.0075 max mem: 33300 +Epoch: [15] [1030/4276] eta: 2:42:54 lr: 3.246938143460362e-05 loss: 0.1295 (0.1376) time: 2.9803 data: 0.0088 max mem: 33300 +Epoch: [15] [1040/4276] eta: 2:42:24 lr: 3.246662117604746e-05 loss: 0.1297 (0.1376) time: 2.9947 data: 0.0093 max mem: 33300 +Epoch: [15] [1050/4276] eta: 2:41:54 lr: 3.246386089141631e-05 loss: 0.1309 (0.1377) time: 3.0138 data: 0.0087 max mem: 33300 +Epoch: [15] [1060/4276] eta: 2:41:25 lr: 3.246110058070748e-05 loss: 0.1413 (0.1379) time: 3.0423 data: 0.0088 max mem: 33300 +Epoch: [15] [1070/4276] eta: 2:40:57 lr: 3.245834024391824e-05 loss: 0.1694 (0.1382) time: 3.0685 data: 0.0089 max mem: 33300 +Epoch: [15] [1080/4276] eta: 2:40:29 lr: 3.245557988104589e-05 loss: 0.1410 (0.1381) time: 3.0755 data: 0.0089 max mem: 33300 +Epoch: [15] [1090/4276] eta: 2:40:01 lr: 3.2452819492087715e-05 loss: 0.1339 (0.1381) time: 3.0825 data: 0.0088 max mem: 33300 +Epoch: [15] [1100/4276] eta: 2:39:31 lr: 3.2450059077041e-05 loss: 0.1337 (0.1382) time: 3.0503 data: 0.0081 max mem: 33300 +Epoch: [15] [1110/4276] eta: 2:38:59 lr: 3.2447298635903044e-05 loss: 0.1362 (0.1382) time: 2.9901 data: 0.0079 max mem: 33300 +Epoch: [15] [1120/4276] eta: 2:38:29 lr: 3.2444538168671116e-05 loss: 0.1362 (0.1381) time: 2.9882 data: 0.0081 max mem: 33300 +Epoch: [15] [1130/4276] eta: 2:38:00 lr: 3.2441777675342515e-05 loss: 0.1169 (0.1380) time: 3.0263 data: 0.0091 max mem: 33300 +Epoch: [15] [1140/4276] eta: 2:37:30 lr: 3.2439017155914526e-05 loss: 0.1181 (0.1380) time: 3.0440 data: 0.0101 max mem: 33300 +Epoch: [15] [1150/4276] eta: 2:37:02 lr: 3.243625661038442e-05 loss: 0.1289 (0.1378) time: 3.0567 data: 0.0099 max mem: 33300 +Epoch: [15] [1160/4276] eta: 2:36:33 lr: 3.243349603874952e-05 loss: 0.1311 (0.1380) time: 3.0693 data: 0.0097 max mem: 33300 +Epoch: [15] [1170/4276] eta: 2:36:05 lr: 3.2430735441007064e-05 loss: 0.1405 (0.1381) time: 3.0730 data: 0.0098 max mem: 33300 +Epoch: [15] [1180/4276] eta: 2:35:36 lr: 3.2427974817154366e-05 loss: 0.1367 (0.1380) time: 3.0833 data: 0.0101 max mem: 33300 +Epoch: [15] [1190/4276] eta: 2:35:07 lr: 3.242521416718869e-05 loss: 0.1280 (0.1380) time: 3.0562 data: 0.0095 max mem: 33300 +Epoch: [15] [1200/4276] eta: 2:34:37 lr: 3.242245349110733e-05 loss: 0.1215 (0.1379) time: 3.0302 data: 0.0084 max mem: 33300 +Epoch: [15] [1210/4276] eta: 2:34:07 lr: 3.241969278890758e-05 loss: 0.1183 (0.1379) time: 3.0251 data: 0.0088 max mem: 33300 +Epoch: [15] [1220/4276] eta: 2:33:38 lr: 3.2416932060586693e-05 loss: 0.1366 (0.1380) time: 3.0433 data: 0.0093 max mem: 33300 +Epoch: [15] [1230/4276] eta: 2:33:09 lr: 3.2414171306141966e-05 loss: 0.1427 (0.1380) time: 3.0647 data: 0.0093 max mem: 33300 +Epoch: [15] [1240/4276] eta: 2:32:39 lr: 3.241141052557069e-05 loss: 0.1366 (0.1380) time: 3.0375 data: 0.0088 max mem: 33300 +Epoch: [15] [1250/4276] eta: 2:32:06 lr: 3.240864971887012e-05 loss: 0.1359 (0.1381) time: 2.9748 data: 0.0078 max mem: 33300 +Epoch: [15] [1260/4276] eta: 2:31:36 lr: 3.240588888603756e-05 loss: 0.1295 (0.1380) time: 2.9684 data: 0.0076 max mem: 33300 +Epoch: [15] [1270/4276] eta: 2:31:05 lr: 3.240312802707027e-05 loss: 0.1278 (0.1380) time: 2.9837 data: 0.0077 max mem: 33300 +Epoch: [15] [1280/4276] eta: 2:30:36 lr: 3.2400367141965546e-05 loss: 0.1350 (0.1380) time: 3.0296 data: 0.0086 max mem: 33300 +Epoch: [15] [1290/4276] eta: 2:30:05 lr: 3.239760623072065e-05 loss: 0.1350 (0.1380) time: 3.0392 data: 0.0096 max mem: 33300 +Epoch: [15] [1300/4276] eta: 2:29:35 lr: 3.2394845293332856e-05 loss: 0.1213 (0.1379) time: 3.0018 data: 0.0095 max mem: 33300 +Epoch: [15] [1310/4276] eta: 2:29:05 lr: 3.239208432979946e-05 loss: 0.1210 (0.1379) time: 3.0042 data: 0.0091 max mem: 33300 +Epoch: [15] [1320/4276] eta: 2:28:34 lr: 3.238932334011773e-05 loss: 0.1311 (0.1380) time: 2.9933 data: 0.0090 max mem: 33300 +Epoch: [15] [1330/4276] eta: 2:28:04 lr: 3.238656232428493e-05 loss: 0.1334 (0.1380) time: 3.0115 data: 0.0088 max mem: 33300 +Epoch: [15] [1340/4276] eta: 2:27:34 lr: 3.2383801282298364e-05 loss: 0.1334 (0.1380) time: 3.0249 data: 0.0087 max mem: 33300 +Epoch: [15] [1350/4276] eta: 2:27:04 lr: 3.2381040214155276e-05 loss: 0.1333 (0.1379) time: 3.0290 data: 0.0090 max mem: 33300 +Epoch: [15] [1360/4276] eta: 2:26:34 lr: 3.237827911985295e-05 loss: 0.1295 (0.1379) time: 3.0228 data: 0.0089 max mem: 33300 +Epoch: [15] [1370/4276] eta: 2:26:04 lr: 3.2375517999388664e-05 loss: 0.1267 (0.1379) time: 3.0157 data: 0.0092 max mem: 33300 +Epoch: [15] [1380/4276] eta: 2:25:33 lr: 3.2372756852759685e-05 loss: 0.1304 (0.1379) time: 3.0102 data: 0.0093 max mem: 33300 +Epoch: [15] [1390/4276] eta: 2:25:02 lr: 3.236999567996329e-05 loss: 0.1470 (0.1380) time: 2.9852 data: 0.0095 max mem: 33300 +Epoch: [15] [1400/4276] eta: 2:24:33 lr: 3.236723448099676e-05 loss: 0.1470 (0.1381) time: 3.0106 data: 0.0099 max mem: 33300 +Epoch: [15] [1410/4276] eta: 2:24:02 lr: 3.2364473255857345e-05 loss: 0.1360 (0.1381) time: 3.0118 data: 0.0096 max mem: 33300 +Epoch: [15] [1420/4276] eta: 2:23:31 lr: 3.2361712004542324e-05 loss: 0.1265 (0.1381) time: 2.9796 data: 0.0091 max mem: 33300 +Epoch: [15] [1430/4276] eta: 2:23:01 lr: 3.235895072704898e-05 loss: 0.1265 (0.1380) time: 3.0030 data: 0.0093 max mem: 33300 +Epoch: [15] [1440/4276] eta: 2:22:31 lr: 3.235618942337456e-05 loss: 0.1273 (0.1380) time: 3.0180 data: 0.0093 max mem: 33300 +Epoch: [15] [1450/4276] eta: 2:22:01 lr: 3.235342809351635e-05 loss: 0.1289 (0.1380) time: 3.0175 data: 0.0091 max mem: 33300 +Epoch: [15] [1460/4276] eta: 2:21:31 lr: 3.2350666737471616e-05 loss: 0.1343 (0.1380) time: 3.0122 data: 0.0088 max mem: 33300 +Epoch: [15] [1470/4276] eta: 2:21:00 lr: 3.234790535523763e-05 loss: 0.1356 (0.1380) time: 3.0011 data: 0.0087 max mem: 33300 +Epoch: [15] [1480/4276] eta: 2:20:29 lr: 3.234514394681165e-05 loss: 0.1219 (0.1379) time: 2.9868 data: 0.0090 max mem: 33300 +Epoch: [15] [1490/4276] eta: 2:19:59 lr: 3.2342382512190945e-05 loss: 0.1138 (0.1378) time: 2.9837 data: 0.0092 max mem: 33300 +Epoch: [15] [1500/4276] eta: 2:19:28 lr: 3.233962105137278e-05 loss: 0.1138 (0.1377) time: 2.9846 data: 0.0091 max mem: 33300 +Epoch: [15] [1510/4276] eta: 2:18:57 lr: 3.2336859564354424e-05 loss: 0.1178 (0.1376) time: 2.9839 data: 0.0087 max mem: 33300 +Epoch: [15] [1520/4276] eta: 2:18:29 lr: 3.233409805113315e-05 loss: 0.1170 (0.1376) time: 3.0467 data: 0.0093 max mem: 33300 +Epoch: [15] [1530/4276] eta: 2:17:58 lr: 3.233133651170621e-05 loss: 0.1201 (0.1375) time: 3.0478 data: 0.0092 max mem: 33300 +Epoch: [15] [1540/4276] eta: 2:17:27 lr: 3.2328574946070875e-05 loss: 0.1230 (0.1376) time: 2.9877 data: 0.0086 max mem: 33300 +Epoch: [15] [1550/4276] eta: 2:16:57 lr: 3.2325813354224405e-05 loss: 0.1533 (0.1377) time: 2.9922 data: 0.0085 max mem: 33300 +Epoch: [15] [1560/4276] eta: 2:16:26 lr: 3.232305173616407e-05 loss: 0.1402 (0.1376) time: 2.9962 data: 0.0083 max mem: 33300 +Epoch: [15] [1570/4276] eta: 2:15:55 lr: 3.2320290091887126e-05 loss: 0.1393 (0.1376) time: 2.9806 data: 0.0087 max mem: 33300 +Epoch: [15] [1580/4276] eta: 2:15:25 lr: 3.2317528421390834e-05 loss: 0.1233 (0.1376) time: 2.9742 data: 0.0092 max mem: 33300 +Epoch: [15] [1590/4276] eta: 2:14:54 lr: 3.2314766724672456e-05 loss: 0.1273 (0.1376) time: 2.9848 data: 0.0089 max mem: 33300 +Epoch: [15] [1600/4276] eta: 2:14:24 lr: 3.231200500172926e-05 loss: 0.1371 (0.1377) time: 3.0106 data: 0.0084 max mem: 33300 +Epoch: [15] [1610/4276] eta: 2:13:54 lr: 3.23092432525585e-05 loss: 0.1266 (0.1376) time: 3.0145 data: 0.0083 max mem: 33300 +Epoch: [15] [1620/4276] eta: 2:13:23 lr: 3.230648147715744e-05 loss: 0.1223 (0.1375) time: 2.9931 data: 0.0084 max mem: 33300 +Epoch: [15] [1630/4276] eta: 2:12:53 lr: 3.2303719675523343e-05 loss: 0.1244 (0.1375) time: 2.9877 data: 0.0082 max mem: 33300 +Epoch: [15] [1640/4276] eta: 2:12:22 lr: 3.230095784765345e-05 loss: 0.1227 (0.1374) time: 2.9908 data: 0.0082 max mem: 33300 +Epoch: [15] [1650/4276] eta: 2:11:53 lr: 3.2298195993545044e-05 loss: 0.1227 (0.1373) time: 3.0230 data: 0.0084 max mem: 33300 +Epoch: [15] [1660/4276] eta: 2:11:23 lr: 3.229543411319536e-05 loss: 0.1256 (0.1373) time: 3.0514 data: 0.0085 max mem: 33300 +Epoch: [15] [1670/4276] eta: 2:10:54 lr: 3.229267220660166e-05 loss: 0.1222 (0.1372) time: 3.0435 data: 0.0088 max mem: 33300 +Epoch: [15] [1680/4276] eta: 2:10:24 lr: 3.2289910273761216e-05 loss: 0.1343 (0.1373) time: 3.0466 data: 0.0081 max mem: 33300 +Epoch: [15] [1690/4276] eta: 2:09:55 lr: 3.228714831467127e-05 loss: 0.1290 (0.1372) time: 3.0634 data: 0.0073 max mem: 33300 +Epoch: [15] [1700/4276] eta: 2:09:25 lr: 3.228438632932908e-05 loss: 0.1275 (0.1372) time: 3.0555 data: 0.0073 max mem: 33300 +Epoch: [15] [1710/4276] eta: 2:08:55 lr: 3.228162431773191e-05 loss: 0.1403 (0.1372) time: 3.0324 data: 0.0074 max mem: 33300 +Epoch: [15] [1720/4276] eta: 2:08:25 lr: 3.2278862279876995e-05 loss: 0.1363 (0.1373) time: 3.0202 data: 0.0076 max mem: 33300 +Epoch: [15] [1730/4276] eta: 2:07:55 lr: 3.2276100215761614e-05 loss: 0.1358 (0.1373) time: 3.0349 data: 0.0076 max mem: 33300 +Epoch: [15] [1740/4276] eta: 2:07:26 lr: 3.227333812538299e-05 loss: 0.1374 (0.1373) time: 3.0482 data: 0.0074 max mem: 33300 +Epoch: [15] [1750/4276] eta: 2:06:56 lr: 3.227057600873841e-05 loss: 0.1351 (0.1373) time: 3.0548 data: 0.0073 max mem: 33300 +Epoch: [15] [1760/4276] eta: 2:06:27 lr: 3.226781386582509e-05 loss: 0.1228 (0.1372) time: 3.0577 data: 0.0073 max mem: 33300 +Epoch: [15] [1770/4276] eta: 2:05:57 lr: 3.2265051696640306e-05 loss: 0.1225 (0.1372) time: 3.0626 data: 0.0074 max mem: 33300 +Epoch: [15] [1780/4276] eta: 2:05:27 lr: 3.226228950118131e-05 loss: 0.1250 (0.1371) time: 3.0543 data: 0.0074 max mem: 33300 +Epoch: [15] [1790/4276] eta: 2:04:57 lr: 3.225952727944534e-05 loss: 0.1250 (0.1371) time: 3.0330 data: 0.0072 max mem: 33300 +Epoch: [15] [1800/4276] eta: 2:04:28 lr: 3.225676503142966e-05 loss: 0.1260 (0.1370) time: 3.0348 data: 0.0074 max mem: 33300 +Epoch: [15] [1810/4276] eta: 2:03:57 lr: 3.225400275713151e-05 loss: 0.1347 (0.1371) time: 3.0310 data: 0.0074 max mem: 33300 +Epoch: [15] [1820/4276] eta: 2:03:28 lr: 3.225124045654814e-05 loss: 0.1358 (0.1371) time: 3.0455 data: 0.0073 max mem: 33300 +Epoch: [15] [1830/4276] eta: 2:02:58 lr: 3.224847812967679e-05 loss: 0.1310 (0.1371) time: 3.0480 data: 0.0073 max mem: 33300 +Epoch: [15] [1840/4276] eta: 2:02:28 lr: 3.2245715776514727e-05 loss: 0.1310 (0.1370) time: 3.0316 data: 0.0072 max mem: 33300 +Epoch: [15] [1850/4276] eta: 2:01:58 lr: 3.224295339705918e-05 loss: 0.1369 (0.1371) time: 3.0207 data: 0.0071 max mem: 33300 +Epoch: [15] [1860/4276] eta: 2:01:27 lr: 3.224019099130741e-05 loss: 0.1229 (0.1370) time: 3.0072 data: 0.0075 max mem: 33300 +Epoch: [15] [1870/4276] eta: 2:00:57 lr: 3.223742855925665e-05 loss: 0.1305 (0.1372) time: 2.9892 data: 0.0079 max mem: 33300 +Epoch: [15] [1880/4276] eta: 2:00:26 lr: 3.223466610090416e-05 loss: 0.1374 (0.1372) time: 2.9775 data: 0.0078 max mem: 33300 +Epoch: [15] [1890/4276] eta: 1:59:55 lr: 3.223190361624717e-05 loss: 0.1309 (0.1372) time: 2.9740 data: 0.0077 max mem: 33300 +Epoch: [15] [1900/4276] eta: 1:59:25 lr: 3.2229141105282934e-05 loss: 0.1225 (0.1372) time: 2.9763 data: 0.0081 max mem: 33300 +Epoch: [15] [1910/4276] eta: 1:58:54 lr: 3.2226378568008694e-05 loss: 0.1282 (0.1372) time: 2.9829 data: 0.0083 max mem: 33300 +Epoch: [15] [1920/4276] eta: 1:58:24 lr: 3.222361600442169e-05 loss: 0.1310 (0.1371) time: 2.9804 data: 0.0077 max mem: 33300 +Epoch: [15] [1930/4276] eta: 1:57:53 lr: 3.2220853414519174e-05 loss: 0.1310 (0.1370) time: 2.9818 data: 0.0075 max mem: 33300 +Epoch: [15] [1940/4276] eta: 1:57:23 lr: 3.2218090798298387e-05 loss: 0.1323 (0.1371) time: 2.9990 data: 0.0079 max mem: 33300 +Epoch: [15] [1950/4276] eta: 1:56:53 lr: 3.221532815575655e-05 loss: 0.1355 (0.1372) time: 3.0035 data: 0.0079 max mem: 33300 +Epoch: [15] [1960/4276] eta: 1:56:22 lr: 3.221256548689094e-05 loss: 0.1347 (0.1372) time: 2.9763 data: 0.0078 max mem: 33300 +Epoch: [15] [1970/4276] eta: 1:55:51 lr: 3.220980279169877e-05 loss: 0.1160 (0.1371) time: 2.9730 data: 0.0079 max mem: 33300 +Epoch: [15] [1980/4276] eta: 1:55:21 lr: 3.220704007017728e-05 loss: 0.1160 (0.1371) time: 2.9846 data: 0.0080 max mem: 33300 +Epoch: [15] [1990/4276] eta: 1:54:50 lr: 3.220427732232372e-05 loss: 0.1301 (0.1371) time: 2.9805 data: 0.0079 max mem: 33300 +Epoch: [15] [2000/4276] eta: 1:54:20 lr: 3.2201514548135334e-05 loss: 0.1427 (0.1372) time: 2.9811 data: 0.0075 max mem: 33300 +Epoch: [15] [2010/4276] eta: 1:53:49 lr: 3.2198751747609345e-05 loss: 0.1427 (0.1371) time: 2.9792 data: 0.0076 max mem: 33300 +Epoch: [15] [2020/4276] eta: 1:53:22 lr: 3.219598892074302e-05 loss: 0.1363 (0.1372) time: 3.1418 data: 0.0083 max mem: 33300 +Epoch: [15] [2030/4276] eta: 1:52:54 lr: 3.219322606753355e-05 loss: 0.1286 (0.1371) time: 3.2371 data: 0.0089 max mem: 33300 +Epoch: [15] [2040/4276] eta: 1:52:26 lr: 3.219046318797821e-05 loss: 0.1164 (0.1371) time: 3.1904 data: 0.0095 max mem: 33300 +Epoch: [15] [2050/4276] eta: 1:51:55 lr: 3.218770028207422e-05 loss: 0.1370 (0.1371) time: 3.1077 data: 0.0096 max mem: 33300 +Epoch: [15] [2060/4276] eta: 1:51:25 lr: 3.218493734981882e-05 loss: 0.1339 (0.1371) time: 2.9947 data: 0.0096 max mem: 33300 +Epoch: [15] [2070/4276] eta: 1:50:54 lr: 3.218217439120924e-05 loss: 0.1253 (0.1370) time: 2.9874 data: 0.0098 max mem: 33300 +Epoch: [15] [2080/4276] eta: 1:50:24 lr: 3.217941140624272e-05 loss: 0.1368 (0.1370) time: 2.9880 data: 0.0095 max mem: 33300 +Epoch: [15] [2090/4276] eta: 1:49:54 lr: 3.21766483949165e-05 loss: 0.1369 (0.1370) time: 3.0008 data: 0.0087 max mem: 33300 +Epoch: [15] [2100/4276] eta: 1:49:24 lr: 3.21738853572278e-05 loss: 0.1325 (0.1370) time: 3.0194 data: 0.0075 max mem: 33300 +Epoch: [15] [2110/4276] eta: 1:48:53 lr: 3.217112229317386e-05 loss: 0.1272 (0.1370) time: 3.0176 data: 0.0064 max mem: 33300 +Epoch: [15] [2120/4276] eta: 1:48:24 lr: 3.2168359202751915e-05 loss: 0.1081 (0.1368) time: 3.0454 data: 0.0058 max mem: 33300 +Epoch: [15] [2130/4276] eta: 1:47:54 lr: 3.2165596085959185e-05 loss: 0.1081 (0.1368) time: 3.0681 data: 0.0057 max mem: 33300 +Epoch: [15] [2140/4276] eta: 1:47:25 lr: 3.216283294279291e-05 loss: 0.1179 (0.1367) time: 3.0696 data: 0.0057 max mem: 33300 +Epoch: [15] [2150/4276] eta: 1:46:55 lr: 3.2160069773250325e-05 loss: 0.1197 (0.1367) time: 3.0666 data: 0.0059 max mem: 33300 +Epoch: [15] [2160/4276] eta: 1:46:25 lr: 3.215730657732865e-05 loss: 0.1197 (0.1367) time: 3.0649 data: 0.0059 max mem: 33300 +Epoch: [15] [2170/4276] eta: 1:45:55 lr: 3.2154543355025135e-05 loss: 0.1452 (0.1367) time: 3.0408 data: 0.0061 max mem: 33300 +Epoch: [15] [2180/4276] eta: 1:45:25 lr: 3.215178010633699e-05 loss: 0.1471 (0.1367) time: 3.0112 data: 0.0064 max mem: 33300 +Epoch: [15] [2190/4276] eta: 1:44:54 lr: 3.214901683126144e-05 loss: 0.1375 (0.1367) time: 3.0104 data: 0.0062 max mem: 33300 +Epoch: [15] [2200/4276] eta: 1:44:24 lr: 3.214625352979572e-05 loss: 0.1369 (0.1368) time: 3.0135 data: 0.0058 max mem: 33300 +Epoch: [15] [2210/4276] eta: 1:43:54 lr: 3.214349020193706e-05 loss: 0.1398 (0.1368) time: 3.0027 data: 0.0057 max mem: 33300 +Epoch: [15] [2220/4276] eta: 1:43:24 lr: 3.214072684768268e-05 loss: 0.1423 (0.1368) time: 2.9999 data: 0.0057 max mem: 33300 +Epoch: [15] [2230/4276] eta: 1:42:53 lr: 3.213796346702981e-05 loss: 0.1300 (0.1368) time: 3.0082 data: 0.0057 max mem: 33300 +Epoch: [15] [2240/4276] eta: 1:42:23 lr: 3.213520005997568e-05 loss: 0.1264 (0.1368) time: 3.0236 data: 0.0057 max mem: 33300 +Epoch: [15] [2250/4276] eta: 1:41:53 lr: 3.213243662651752e-05 loss: 0.1238 (0.1368) time: 3.0344 data: 0.0057 max mem: 33300 +Epoch: [15] [2260/4276] eta: 1:41:23 lr: 3.212967316665254e-05 loss: 0.1309 (0.1368) time: 3.0071 data: 0.0057 max mem: 33300 +Epoch: [15] [2270/4276] eta: 1:40:52 lr: 3.212690968037797e-05 loss: 0.1263 (0.1367) time: 2.9801 data: 0.0056 max mem: 33300 +Epoch: [15] [2280/4276] eta: 1:40:22 lr: 3.2124146167691035e-05 loss: 0.1227 (0.1367) time: 3.0000 data: 0.0056 max mem: 33300 +Epoch: [15] [2290/4276] eta: 1:39:52 lr: 3.2121382628588955e-05 loss: 0.1225 (0.1366) time: 3.0142 data: 0.0057 max mem: 33300 +Epoch: [15] [2300/4276] eta: 1:39:22 lr: 3.211861906306895e-05 loss: 0.1245 (0.1366) time: 3.0238 data: 0.0057 max mem: 33300 +Epoch: [15] [2310/4276] eta: 1:38:51 lr: 3.211585547112825e-05 loss: 0.1292 (0.1366) time: 3.0203 data: 0.0057 max mem: 33300 +Epoch: [15] [2320/4276] eta: 1:38:21 lr: 3.2113091852764065e-05 loss: 0.1372 (0.1366) time: 3.0076 data: 0.0056 max mem: 33300 +Epoch: [15] [2330/4276] eta: 1:37:51 lr: 3.211032820797363e-05 loss: 0.1435 (0.1367) time: 3.0052 data: 0.0056 max mem: 33300 +Epoch: [15] [2340/4276] eta: 1:37:21 lr: 3.210756453675415e-05 loss: 0.1454 (0.1367) time: 3.0112 data: 0.0057 max mem: 33300 +Epoch: [15] [2350/4276] eta: 1:36:51 lr: 3.210480083910287e-05 loss: 0.1282 (0.1367) time: 3.0455 data: 0.0057 max mem: 33300 +Epoch: [15] [2360/4276] eta: 1:36:22 lr: 3.210203711501698e-05 loss: 0.1175 (0.1366) time: 3.0741 data: 0.0057 max mem: 33300 +Epoch: [15] [2370/4276] eta: 1:35:51 lr: 3.2099273364493706e-05 loss: 0.1326 (0.1366) time: 3.0361 data: 0.0055 max mem: 33300 +Epoch: [15] [2380/4276] eta: 1:35:21 lr: 3.2096509587530267e-05 loss: 0.1396 (0.1366) time: 3.0007 data: 0.0055 max mem: 33300 +Epoch: [15] [2390/4276] eta: 1:34:50 lr: 3.209374578412389e-05 loss: 0.1393 (0.1366) time: 2.9992 data: 0.0055 max mem: 33300 +Epoch: [15] [2400/4276] eta: 1:34:21 lr: 3.209098195427178e-05 loss: 0.1287 (0.1366) time: 3.0154 data: 0.0056 max mem: 33300 +Epoch: [15] [2410/4276] eta: 1:33:50 lr: 3.208821809797116e-05 loss: 0.1229 (0.1365) time: 3.0360 data: 0.0056 max mem: 33300 +Epoch: [15] [2420/4276] eta: 1:33:20 lr: 3.2085454215219244e-05 loss: 0.1154 (0.1365) time: 3.0263 data: 0.0058 max mem: 33300 +Epoch: [15] [2430/4276] eta: 1:32:50 lr: 3.208269030601325e-05 loss: 0.1397 (0.1366) time: 3.0271 data: 0.0057 max mem: 33300 +Epoch: [15] [2440/4276] eta: 1:32:20 lr: 3.2079926370350386e-05 loss: 0.1372 (0.1366) time: 3.0210 data: 0.0055 max mem: 33300 +Epoch: [15] [2450/4276] eta: 1:31:49 lr: 3.207716240822786e-05 loss: 0.1336 (0.1366) time: 2.9990 data: 0.0058 max mem: 33300 +Epoch: [15] [2460/4276] eta: 1:31:20 lr: 3.2074398419642904e-05 loss: 0.1374 (0.1366) time: 3.0071 data: 0.0060 max mem: 33300 +Epoch: [15] [2470/4276] eta: 1:30:49 lr: 3.207163440459272e-05 loss: 0.1422 (0.1366) time: 3.0243 data: 0.0059 max mem: 33300 +Epoch: [15] [2480/4276] eta: 1:30:20 lr: 3.206887036307452e-05 loss: 0.1437 (0.1367) time: 3.0486 data: 0.0059 max mem: 33300 +Epoch: [15] [2490/4276] eta: 1:29:51 lr: 3.206610629508552e-05 loss: 0.1306 (0.1367) time: 3.1557 data: 0.0057 max mem: 33300 +Epoch: [15] [2500/4276] eta: 1:29:21 lr: 3.206334220062293e-05 loss: 0.1411 (0.1367) time: 3.1459 data: 0.0059 max mem: 33300 +Epoch: [15] [2510/4276] eta: 1:28:51 lr: 3.2060578079683956e-05 loss: 0.1510 (0.1368) time: 3.0610 data: 0.0065 max mem: 33300 +Epoch: [15] [2520/4276] eta: 1:28:21 lr: 3.2057813932265806e-05 loss: 0.1288 (0.1367) time: 3.0578 data: 0.0064 max mem: 33300 +Epoch: [15] [2530/4276] eta: 1:27:51 lr: 3.20550497583657e-05 loss: 0.1035 (0.1366) time: 3.0524 data: 0.0066 max mem: 33300 +Epoch: [15] [2540/4276] eta: 1:27:21 lr: 3.205228555798084e-05 loss: 0.1152 (0.1365) time: 3.0342 data: 0.0065 max mem: 33300 +Epoch: [15] [2550/4276] eta: 1:26:51 lr: 3.2049521331108435e-05 loss: 0.1180 (0.1365) time: 3.0069 data: 0.0058 max mem: 33300 +Epoch: [15] [2560/4276] eta: 1:26:21 lr: 3.20467570777457e-05 loss: 0.1177 (0.1364) time: 3.0055 data: 0.0056 max mem: 33300 +Epoch: [15] [2570/4276] eta: 1:25:50 lr: 3.204399279788983e-05 loss: 0.1179 (0.1364) time: 3.0114 data: 0.0057 max mem: 33300 +Epoch: [15] [2580/4276] eta: 1:25:20 lr: 3.204122849153804e-05 loss: 0.1200 (0.1363) time: 3.0128 data: 0.0058 max mem: 33300 +Epoch: [15] [2590/4276] eta: 1:24:50 lr: 3.2038464158687526e-05 loss: 0.1204 (0.1363) time: 3.0408 data: 0.0059 max mem: 33300 +Epoch: [15] [2600/4276] eta: 1:24:20 lr: 3.2035699799335505e-05 loss: 0.1281 (0.1363) time: 3.0307 data: 0.0059 max mem: 33300 +Epoch: [15] [2610/4276] eta: 1:23:49 lr: 3.203293541347918e-05 loss: 0.1267 (0.1362) time: 2.9984 data: 0.0059 max mem: 33300 +Epoch: [15] [2620/4276] eta: 1:23:20 lr: 3.203017100111575e-05 loss: 0.1246 (0.1362) time: 3.0255 data: 0.0059 max mem: 33300 +Epoch: [15] [2630/4276] eta: 1:22:49 lr: 3.2027406562242426e-05 loss: 0.1246 (0.1361) time: 3.0465 data: 0.0059 max mem: 33300 +Epoch: [15] [2640/4276] eta: 1:22:19 lr: 3.202464209685641e-05 loss: 0.1119 (0.1361) time: 3.0187 data: 0.0059 max mem: 33300 +Epoch: [15] [2650/4276] eta: 1:21:49 lr: 3.20218776049549e-05 loss: 0.1201 (0.1361) time: 2.9976 data: 0.0059 max mem: 33300 +Epoch: [15] [2660/4276] eta: 1:21:18 lr: 3.2019113086535104e-05 loss: 0.1280 (0.1361) time: 2.9914 data: 0.0058 max mem: 33300 +Epoch: [15] [2670/4276] eta: 1:20:48 lr: 3.201634854159421e-05 loss: 0.1339 (0.1361) time: 2.9839 data: 0.0058 max mem: 33300 +Epoch: [15] [2680/4276] eta: 1:20:18 lr: 3.2013583970129435e-05 loss: 0.1339 (0.1362) time: 3.0116 data: 0.0062 max mem: 33300 +Epoch: [15] [2690/4276] eta: 1:19:48 lr: 3.201081937213797e-05 loss: 0.1332 (0.1361) time: 3.0447 data: 0.0067 max mem: 33300 +Epoch: [15] [2700/4276] eta: 1:19:18 lr: 3.200805474761702e-05 loss: 0.1211 (0.1361) time: 3.0506 data: 0.0064 max mem: 33300 +Epoch: [15] [2710/4276] eta: 1:18:48 lr: 3.200529009656379e-05 loss: 0.1245 (0.1360) time: 3.0471 data: 0.0057 max mem: 33300 +Epoch: [15] [2720/4276] eta: 1:18:18 lr: 3.200252541897547e-05 loss: 0.1237 (0.1360) time: 3.0415 data: 0.0057 max mem: 33300 +Epoch: [15] [2730/4276] eta: 1:17:48 lr: 3.199976071484925e-05 loss: 0.1337 (0.1360) time: 3.0501 data: 0.0058 max mem: 33300 +Epoch: [15] [2740/4276] eta: 1:17:18 lr: 3.1996995984182345e-05 loss: 0.1421 (0.1361) time: 3.0349 data: 0.0058 max mem: 33300 +Epoch: [15] [2750/4276] eta: 1:16:47 lr: 3.199423122697194e-05 loss: 0.1417 (0.1361) time: 3.0017 data: 0.0062 max mem: 33300 +Epoch: [15] [2760/4276] eta: 1:16:17 lr: 3.199146644321524e-05 loss: 0.1361 (0.1361) time: 3.0008 data: 0.0064 max mem: 33300 +Epoch: [15] [2770/4276] eta: 1:15:47 lr: 3.198870163290943e-05 loss: 0.1312 (0.1361) time: 3.0416 data: 0.0066 max mem: 33300 +Epoch: [15] [2780/4276] eta: 1:15:17 lr: 3.198593679605172e-05 loss: 0.1312 (0.1361) time: 3.0680 data: 0.0068 max mem: 33300 +Epoch: [15] [2790/4276] eta: 1:14:47 lr: 3.19831719326393e-05 loss: 0.1322 (0.1361) time: 3.0324 data: 0.0066 max mem: 33300 +Epoch: [15] [2800/4276] eta: 1:14:17 lr: 3.198040704266936e-05 loss: 0.1322 (0.1361) time: 3.0267 data: 0.0064 max mem: 33300 +Epoch: [15] [2810/4276] eta: 1:13:47 lr: 3.197764212613909e-05 loss: 0.1206 (0.1360) time: 3.0513 data: 0.0065 max mem: 33300 +Epoch: [15] [2820/4276] eta: 1:13:17 lr: 3.197487718304569e-05 loss: 0.1166 (0.1359) time: 3.0647 data: 0.0068 max mem: 33300 +Epoch: [15] [2830/4276] eta: 1:12:47 lr: 3.1972112213386354e-05 loss: 0.1241 (0.1359) time: 3.0792 data: 0.0067 max mem: 33300 +Epoch: [15] [2840/4276] eta: 1:12:17 lr: 3.196934721715826e-05 loss: 0.1321 (0.1359) time: 3.0888 data: 0.0068 max mem: 33300 +Epoch: [15] [2850/4276] eta: 1:11:47 lr: 3.196658219435862e-05 loss: 0.1362 (0.1360) time: 3.0790 data: 0.0069 max mem: 33300 +Epoch: [15] [2860/4276] eta: 1:11:17 lr: 3.196381714498462e-05 loss: 0.1355 (0.1360) time: 3.0411 data: 0.0067 max mem: 33300 +Epoch: [15] [2870/4276] eta: 1:10:47 lr: 3.196105206903344e-05 loss: 0.1331 (0.1360) time: 3.0160 data: 0.0068 max mem: 33300 +Epoch: [15] [2880/4276] eta: 1:10:16 lr: 3.195828696650227e-05 loss: 0.1331 (0.1360) time: 3.0173 data: 0.0070 max mem: 33300 +Epoch: [15] [2890/4276] eta: 1:09:46 lr: 3.1955521837388305e-05 loss: 0.1254 (0.1360) time: 3.0217 data: 0.0070 max mem: 33300 +Epoch: [15] [2900/4276] eta: 1:09:16 lr: 3.195275668168874e-05 loss: 0.1157 (0.1359) time: 3.0159 data: 0.0070 max mem: 33300 +Epoch: [15] [2910/4276] eta: 1:08:46 lr: 3.194999149940075e-05 loss: 0.1160 (0.1359) time: 3.0150 data: 0.0069 max mem: 33300 +Epoch: [15] [2920/4276] eta: 1:08:16 lr: 3.194722629052153e-05 loss: 0.1233 (0.1358) time: 3.0212 data: 0.0069 max mem: 33300 +Epoch: [15] [2930/4276] eta: 1:07:45 lr: 3.1944461055048263e-05 loss: 0.1088 (0.1357) time: 3.0175 data: 0.0069 max mem: 33300 +Epoch: [15] [2940/4276] eta: 1:07:15 lr: 3.194169579297814e-05 loss: 0.1185 (0.1357) time: 3.0144 data: 0.0068 max mem: 33300 +Epoch: [15] [2950/4276] eta: 1:06:45 lr: 3.193893050430835e-05 loss: 0.1223 (0.1357) time: 3.0149 data: 0.0068 max mem: 33300 +Epoch: [15] [2960/4276] eta: 1:06:15 lr: 3.193616518903607e-05 loss: 0.1192 (0.1357) time: 3.0155 data: 0.0068 max mem: 33300 +Epoch: [15] [2970/4276] eta: 1:05:44 lr: 3.193339984715848e-05 loss: 0.1235 (0.1357) time: 3.0225 data: 0.0069 max mem: 33300 +Epoch: [15] [2980/4276] eta: 1:05:14 lr: 3.1930634478672774e-05 loss: 0.1394 (0.1357) time: 3.0303 data: 0.0069 max mem: 33300 +Epoch: [15] [2990/4276] eta: 1:04:44 lr: 3.1927869083576136e-05 loss: 0.1231 (0.1357) time: 3.0268 data: 0.0068 max mem: 33300 +Epoch: [15] [3000/4276] eta: 1:04:14 lr: 3.192510366186574e-05 loss: 0.1216 (0.1356) time: 3.0299 data: 0.0069 max mem: 33300 +Epoch: [15] [3010/4276] eta: 1:03:44 lr: 3.1922338213538776e-05 loss: 0.1301 (0.1357) time: 3.0362 data: 0.0069 max mem: 33300 +Epoch: [15] [3020/4276] eta: 1:03:14 lr: 3.191957273859243e-05 loss: 0.1396 (0.1357) time: 3.0699 data: 0.0068 max mem: 33300 +Epoch: [15] [3030/4276] eta: 1:02:44 lr: 3.191680723702387e-05 loss: 0.1336 (0.1357) time: 3.0782 data: 0.0069 max mem: 33300 +Epoch: [15] [3040/4276] eta: 1:02:13 lr: 3.191404170883029e-05 loss: 0.1483 (0.1358) time: 3.0046 data: 0.0077 max mem: 33300 +Epoch: [15] [3050/4276] eta: 1:01:43 lr: 3.1911276154008853e-05 loss: 0.1483 (0.1357) time: 2.9860 data: 0.0086 max mem: 33300 +Epoch: [15] [3060/4276] eta: 1:01:13 lr: 3.190851057255676e-05 loss: 0.1179 (0.1357) time: 2.9676 data: 0.0080 max mem: 33300 +Epoch: [15] [3070/4276] eta: 1:00:42 lr: 3.190574496447117e-05 loss: 0.1179 (0.1357) time: 2.9677 data: 0.0076 max mem: 33300 +Epoch: [15] [3080/4276] eta: 1:00:12 lr: 3.1902979329749274e-05 loss: 0.1241 (0.1356) time: 2.9704 data: 0.0077 max mem: 33300 +Epoch: [15] [3090/4276] eta: 0:59:41 lr: 3.190021366838824e-05 loss: 0.1186 (0.1356) time: 2.9630 data: 0.0073 max mem: 33300 +Epoch: [15] [3100/4276] eta: 0:59:11 lr: 3.189744798038527e-05 loss: 0.1194 (0.1356) time: 2.9861 data: 0.0081 max mem: 33300 +Epoch: [15] [3110/4276] eta: 0:58:41 lr: 3.18946822657375e-05 loss: 0.1217 (0.1355) time: 2.9787 data: 0.0084 max mem: 33300 +Epoch: [15] [3120/4276] eta: 0:58:10 lr: 3.189191652444214e-05 loss: 0.1169 (0.1355) time: 2.9429 data: 0.0078 max mem: 33300 +Epoch: [15] [3130/4276] eta: 0:57:40 lr: 3.188915075649635e-05 loss: 0.1208 (0.1354) time: 2.9404 data: 0.0075 max mem: 33300 +Epoch: [15] [3140/4276] eta: 0:57:09 lr: 3.1886384961897306e-05 loss: 0.1279 (0.1354) time: 2.9442 data: 0.0078 max mem: 33300 +Epoch: [15] [3150/4276] eta: 0:56:39 lr: 3.1883619140642183e-05 loss: 0.1336 (0.1354) time: 2.9371 data: 0.0082 max mem: 33300 +Epoch: [15] [3160/4276] eta: 0:56:08 lr: 3.188085329272816e-05 loss: 0.1362 (0.1354) time: 2.9470 data: 0.0079 max mem: 33300 +Epoch: [15] [3170/4276] eta: 0:55:38 lr: 3.187808741815241e-05 loss: 0.1472 (0.1355) time: 2.9520 data: 0.0075 max mem: 33300 +Epoch: [15] [3180/4276] eta: 0:55:08 lr: 3.18753215169121e-05 loss: 0.1370 (0.1355) time: 2.9616 data: 0.0074 max mem: 33300 +Epoch: [15] [3190/4276] eta: 0:54:37 lr: 3.18725555890044e-05 loss: 0.1314 (0.1355) time: 2.9563 data: 0.0076 max mem: 33300 +Epoch: [15] [3200/4276] eta: 0:54:07 lr: 3.186978963442649e-05 loss: 0.1346 (0.1355) time: 2.9568 data: 0.0074 max mem: 33300 +Epoch: [15] [3210/4276] eta: 0:53:36 lr: 3.186702365317554e-05 loss: 0.1394 (0.1355) time: 2.9582 data: 0.0075 max mem: 33300 +Epoch: [15] [3220/4276] eta: 0:53:06 lr: 3.1864257645248715e-05 loss: 0.1396 (0.1355) time: 2.9606 data: 0.0078 max mem: 33300 +Epoch: [15] [3230/4276] eta: 0:52:36 lr: 3.186149161064318e-05 loss: 0.1284 (0.1355) time: 2.9818 data: 0.0083 max mem: 33300 +Epoch: [15] [3240/4276] eta: 0:52:05 lr: 3.185872554935611e-05 loss: 0.1284 (0.1356) time: 2.9836 data: 0.0088 max mem: 33300 +Epoch: [15] [3250/4276] eta: 0:51:35 lr: 3.185595946138468e-05 loss: 0.1418 (0.1356) time: 2.9891 data: 0.0085 max mem: 33300 +Epoch: [15] [3260/4276] eta: 0:51:05 lr: 3.1853193346726055e-05 loss: 0.1409 (0.1356) time: 3.0154 data: 0.0079 max mem: 33300 +Epoch: [15] [3270/4276] eta: 0:50:35 lr: 3.1850427205377405e-05 loss: 0.1446 (0.1356) time: 3.0054 data: 0.0078 max mem: 33300 +Epoch: [15] [3280/4276] eta: 0:50:05 lr: 3.184766103733589e-05 loss: 0.1434 (0.1356) time: 2.9990 data: 0.0082 max mem: 33300 +Epoch: [15] [3290/4276] eta: 0:49:34 lr: 3.184489484259866e-05 loss: 0.1443 (0.1357) time: 3.0046 data: 0.0083 max mem: 33300 +Epoch: [15] [3300/4276] eta: 0:49:04 lr: 3.184212862116291e-05 loss: 0.1380 (0.1357) time: 2.9944 data: 0.0080 max mem: 33300 +Epoch: [15] [3310/4276] eta: 0:48:34 lr: 3.18393623730258e-05 loss: 0.1457 (0.1357) time: 3.0078 data: 0.0079 max mem: 33300 +Epoch: [15] [3320/4276] eta: 0:48:04 lr: 3.183659609818448e-05 loss: 0.1592 (0.1358) time: 3.0119 data: 0.0081 max mem: 33300 +Epoch: [15] [3330/4276] eta: 0:47:34 lr: 3.183382979663614e-05 loss: 0.1286 (0.1357) time: 3.0078 data: 0.0081 max mem: 33300 +Epoch: [15] [3340/4276] eta: 0:47:03 lr: 3.183106346837791e-05 loss: 0.1258 (0.1357) time: 3.0046 data: 0.0079 max mem: 33300 +Epoch: [15] [3350/4276] eta: 0:46:33 lr: 3.182829711340698e-05 loss: 0.1217 (0.1357) time: 3.0242 data: 0.0078 max mem: 33300 +Epoch: [15] [3360/4276] eta: 0:46:03 lr: 3.1825530731720495e-05 loss: 0.1194 (0.1357) time: 3.0281 data: 0.0077 max mem: 33300 +Epoch: [15] [3370/4276] eta: 0:45:33 lr: 3.182276432331562e-05 loss: 0.1357 (0.1357) time: 3.0001 data: 0.0077 max mem: 33300 +Epoch: [15] [3380/4276] eta: 0:45:03 lr: 3.181999788818952e-05 loss: 0.1451 (0.1357) time: 2.9940 data: 0.0079 max mem: 33300 +Epoch: [15] [3390/4276] eta: 0:44:32 lr: 3.181723142633935e-05 loss: 0.1372 (0.1357) time: 2.9765 data: 0.0082 max mem: 33300 +Epoch: [15] [3400/4276] eta: 0:44:02 lr: 3.181446493776229e-05 loss: 0.1519 (0.1357) time: 2.9881 data: 0.0085 max mem: 33300 +Epoch: [15] [3410/4276] eta: 0:43:32 lr: 3.181169842245548e-05 loss: 0.1465 (0.1357) time: 3.0149 data: 0.0086 max mem: 33300 +Epoch: [15] [3420/4276] eta: 0:43:02 lr: 3.180893188041608e-05 loss: 0.1463 (0.1358) time: 3.0053 data: 0.0082 max mem: 33300 +Epoch: [15] [3430/4276] eta: 0:42:32 lr: 3.1806165311641254e-05 loss: 0.1509 (0.1359) time: 3.0223 data: 0.0080 max mem: 33300 +Epoch: [15] [3440/4276] eta: 0:42:01 lr: 3.1803398716128155e-05 loss: 0.1302 (0.1358) time: 3.0140 data: 0.0077 max mem: 33300 +Epoch: [15] [3450/4276] eta: 0:41:31 lr: 3.180063209387394e-05 loss: 0.1374 (0.1359) time: 2.9936 data: 0.0072 max mem: 33300 +Epoch: [15] [3460/4276] eta: 0:41:01 lr: 3.179786544487577e-05 loss: 0.1445 (0.1359) time: 2.9975 data: 0.0073 max mem: 33300 +Epoch: [15] [3470/4276] eta: 0:40:31 lr: 3.1795098769130796e-05 loss: 0.1268 (0.1358) time: 2.9930 data: 0.0077 max mem: 33300 +Epoch: [15] [3480/4276] eta: 0:40:01 lr: 3.1792332066636175e-05 loss: 0.1227 (0.1358) time: 2.9980 data: 0.0079 max mem: 33300 +Epoch: [15] [3490/4276] eta: 0:39:30 lr: 3.178956533738907e-05 loss: 0.1308 (0.1359) time: 3.0014 data: 0.0077 max mem: 33300 +Epoch: [15] [3500/4276] eta: 0:39:00 lr: 3.178679858138662e-05 loss: 0.1304 (0.1358) time: 3.0023 data: 0.0072 max mem: 33300 +Epoch: [15] [3510/4276] eta: 0:38:30 lr: 3.1784031798626e-05 loss: 0.1121 (0.1358) time: 2.9996 data: 0.0071 max mem: 33300 +Epoch: [15] [3520/4276] eta: 0:38:00 lr: 3.178126498910434e-05 loss: 0.1238 (0.1358) time: 3.0160 data: 0.0069 max mem: 33300 +Epoch: [15] [3530/4276] eta: 0:37:30 lr: 3.1778498152818806e-05 loss: 0.1435 (0.1358) time: 3.0155 data: 0.0071 max mem: 33300 +Epoch: [15] [3540/4276] eta: 0:36:59 lr: 3.177573128976654e-05 loss: 0.1435 (0.1358) time: 2.9854 data: 0.0073 max mem: 33300 +Epoch: [15] [3550/4276] eta: 0:36:29 lr: 3.17729643999447e-05 loss: 0.1269 (0.1358) time: 2.9881 data: 0.0074 max mem: 33300 +Epoch: [15] [3560/4276] eta: 0:35:59 lr: 3.177019748335044e-05 loss: 0.1224 (0.1358) time: 3.0007 data: 0.0073 max mem: 33300 +Epoch: [15] [3570/4276] eta: 0:35:29 lr: 3.176743053998091e-05 loss: 0.1457 (0.1359) time: 3.0026 data: 0.0071 max mem: 33300 +Epoch: [15] [3580/4276] eta: 0:34:59 lr: 3.176466356983326e-05 loss: 0.1259 (0.1358) time: 3.0021 data: 0.0071 max mem: 33300 +Epoch: [15] [3590/4276] eta: 0:34:28 lr: 3.1761896572904626e-05 loss: 0.1230 (0.1359) time: 3.0009 data: 0.0069 max mem: 33300 +Epoch: [15] [3600/4276] eta: 0:33:58 lr: 3.175912954919216e-05 loss: 0.1368 (0.1359) time: 3.0208 data: 0.0069 max mem: 33300 +Epoch: [15] [3610/4276] eta: 0:33:28 lr: 3.175636249869303e-05 loss: 0.1406 (0.1359) time: 3.0259 data: 0.0072 max mem: 33300 +Epoch: [15] [3620/4276] eta: 0:32:58 lr: 3.175359542140435e-05 loss: 0.1406 (0.1358) time: 3.0078 data: 0.0074 max mem: 33300 +Epoch: [15] [3630/4276] eta: 0:32:28 lr: 3.17508283173233e-05 loss: 0.1267 (0.1359) time: 3.0056 data: 0.0075 max mem: 33300 +Epoch: [15] [3640/4276] eta: 0:31:58 lr: 3.174806118644702e-05 loss: 0.1323 (0.1358) time: 3.0051 data: 0.0077 max mem: 33300 +Epoch: [15] [3650/4276] eta: 0:31:27 lr: 3.1745294028772624e-05 loss: 0.1221 (0.1358) time: 3.0013 data: 0.0079 max mem: 33300 +Epoch: [15] [3660/4276] eta: 0:30:57 lr: 3.1742526844297296e-05 loss: 0.1159 (0.1358) time: 2.9815 data: 0.0074 max mem: 33300 +Epoch: [15] [3670/4276] eta: 0:30:27 lr: 3.173975963301816e-05 loss: 0.1133 (0.1357) time: 2.9817 data: 0.0078 max mem: 33300 +Epoch: [15] [3680/4276] eta: 0:29:57 lr: 3.173699239493236e-05 loss: 0.1403 (0.1358) time: 3.0056 data: 0.0085 max mem: 33300 +Epoch: [15] [3690/4276] eta: 0:29:27 lr: 3.173422513003705e-05 loss: 0.1479 (0.1358) time: 3.0272 data: 0.0083 max mem: 33300 +Epoch: [15] [3700/4276] eta: 0:28:57 lr: 3.173145783832936e-05 loss: 0.1450 (0.1358) time: 3.0394 data: 0.0081 max mem: 33300 +Epoch: [15] [3710/4276] eta: 0:28:26 lr: 3.172869051980644e-05 loss: 0.1252 (0.1357) time: 3.0246 data: 0.0077 max mem: 33300 +Epoch: [15] [3720/4276] eta: 0:27:56 lr: 3.172592317446543e-05 loss: 0.1127 (0.1357) time: 3.0180 data: 0.0076 max mem: 33300 +Epoch: [15] [3730/4276] eta: 0:27:26 lr: 3.1723155802303473e-05 loss: 0.1171 (0.1357) time: 3.0419 data: 0.0074 max mem: 33300 +Epoch: [15] [3740/4276] eta: 0:26:56 lr: 3.172038840331771e-05 loss: 0.1229 (0.1357) time: 3.0561 data: 0.0070 max mem: 33300 +Epoch: [15] [3750/4276] eta: 0:26:26 lr: 3.171762097750527e-05 loss: 0.1302 (0.1357) time: 3.0411 data: 0.0073 max mem: 33300 +Epoch: [15] [3760/4276] eta: 0:25:56 lr: 3.17148535248633e-05 loss: 0.1206 (0.1357) time: 3.0062 data: 0.0076 max mem: 33300 +Epoch: [15] [3770/4276] eta: 0:25:26 lr: 3.171208604538894e-05 loss: 0.1194 (0.1357) time: 3.0016 data: 0.0078 max mem: 33300 +Epoch: [15] [3780/4276] eta: 0:24:55 lr: 3.170931853907933e-05 loss: 0.1298 (0.1357) time: 3.0143 data: 0.0079 max mem: 33300 +Epoch: [15] [3790/4276] eta: 0:24:25 lr: 3.1706551005931594e-05 loss: 0.1256 (0.1357) time: 2.9999 data: 0.0079 max mem: 33300 +Epoch: [15] [3800/4276] eta: 0:23:55 lr: 3.1703783445942884e-05 loss: 0.1410 (0.1357) time: 3.0128 data: 0.0080 max mem: 33300 +Epoch: [15] [3810/4276] eta: 0:23:25 lr: 3.170101585911033e-05 loss: 0.1406 (0.1357) time: 3.0134 data: 0.0076 max mem: 33300 +Epoch: [15] [3820/4276] eta: 0:22:55 lr: 3.1698248245431075e-05 loss: 0.1159 (0.1357) time: 2.9948 data: 0.0075 max mem: 33300 +Epoch: [15] [3830/4276] eta: 0:22:25 lr: 3.169548060490224e-05 loss: 0.1270 (0.1357) time: 3.0323 data: 0.0079 max mem: 33300 +Epoch: [15] [3840/4276] eta: 0:21:55 lr: 3.169271293752097e-05 loss: 0.1287 (0.1356) time: 3.1308 data: 0.0079 max mem: 33300 +Epoch: [15] [3850/4276] eta: 0:21:24 lr: 3.168994524328439e-05 loss: 0.1162 (0.1356) time: 3.0866 data: 0.0080 max mem: 33300 +Epoch: [15] [3860/4276] eta: 0:20:54 lr: 3.168717752218964e-05 loss: 0.1221 (0.1356) time: 3.0571 data: 0.0080 max mem: 33300 +Epoch: [15] [3870/4276] eta: 0:20:24 lr: 3.1684409774233856e-05 loss: 0.1329 (0.1356) time: 3.0817 data: 0.0076 max mem: 33300 +Epoch: [15] [3880/4276] eta: 0:19:54 lr: 3.1681641999414165e-05 loss: 0.1235 (0.1356) time: 3.0285 data: 0.0080 max mem: 33300 +Epoch: [15] [3890/4276] eta: 0:19:24 lr: 3.167887419772771e-05 loss: 0.1251 (0.1356) time: 3.0284 data: 0.0082 max mem: 33300 +Epoch: [15] [3900/4276] eta: 0:18:54 lr: 3.1676106369171595e-05 loss: 0.1324 (0.1356) time: 3.0190 data: 0.0077 max mem: 33300 +Epoch: [15] [3910/4276] eta: 0:18:24 lr: 3.167333851374297e-05 loss: 0.1262 (0.1356) time: 2.9852 data: 0.0074 max mem: 33300 +Epoch: [15] [3920/4276] eta: 0:17:53 lr: 3.167057063143896e-05 loss: 0.1183 (0.1355) time: 2.9554 data: 0.0076 max mem: 33300 +Epoch: [15] [3930/4276] eta: 0:17:23 lr: 3.1667802722256694e-05 loss: 0.1190 (0.1355) time: 2.9629 data: 0.0080 max mem: 33300 +Epoch: [15] [3940/4276] eta: 0:16:53 lr: 3.1665034786193304e-05 loss: 0.1147 (0.1355) time: 2.9794 data: 0.0081 max mem: 33300 +Epoch: [15] [3950/4276] eta: 0:16:23 lr: 3.166226682324593e-05 loss: 0.1187 (0.1355) time: 2.9749 data: 0.0077 max mem: 33300 +Epoch: [15] [3960/4276] eta: 0:15:53 lr: 3.1659498833411673e-05 loss: 0.1226 (0.1355) time: 2.9829 data: 0.0076 max mem: 33300 +Epoch: [15] [3970/4276] eta: 0:15:22 lr: 3.1656730816687673e-05 loss: 0.1351 (0.1355) time: 2.9799 data: 0.0076 max mem: 33300 +Epoch: [15] [3980/4276] eta: 0:14:52 lr: 3.165396277307106e-05 loss: 0.1228 (0.1355) time: 2.9791 data: 0.0075 max mem: 33300 +Epoch: [15] [3990/4276] eta: 0:14:22 lr: 3.165119470255895e-05 loss: 0.1169 (0.1355) time: 2.9726 data: 0.0078 max mem: 33300 +Epoch: [15] [4000/4276] eta: 0:13:52 lr: 3.164842660514848e-05 loss: 0.1220 (0.1354) time: 2.9744 data: 0.0075 max mem: 33300 +Epoch: [15] [4010/4276] eta: 0:13:22 lr: 3.164565848083676e-05 loss: 0.1220 (0.1354) time: 2.9954 data: 0.0076 max mem: 33300 +Epoch: [15] [4020/4276] eta: 0:12:51 lr: 3.164289032962093e-05 loss: 0.1376 (0.1354) time: 3.0025 data: 0.0078 max mem: 33300 +Epoch: [15] [4030/4276] eta: 0:12:21 lr: 3.1640122151498106e-05 loss: 0.1376 (0.1354) time: 3.0278 data: 0.0074 max mem: 33300 +Epoch: [15] [4040/4276] eta: 0:11:51 lr: 3.163735394646541e-05 loss: 0.1395 (0.1355) time: 3.0261 data: 0.0070 max mem: 33300 +Epoch: [15] [4050/4276] eta: 0:11:21 lr: 3.1634585714519965e-05 loss: 0.1228 (0.1355) time: 3.0189 data: 0.0071 max mem: 33300 +Epoch: [15] [4060/4276] eta: 0:10:51 lr: 3.1631817455658884e-05 loss: 0.1273 (0.1355) time: 3.0289 data: 0.0078 max mem: 33300 +Epoch: [15] [4070/4276] eta: 0:10:21 lr: 3.162904916987931e-05 loss: 0.1349 (0.1355) time: 3.0320 data: 0.0084 max mem: 33300 +Epoch: [15] [4080/4276] eta: 0:09:51 lr: 3.162628085717833e-05 loss: 0.1363 (0.1355) time: 3.0214 data: 0.0080 max mem: 33300 +Epoch: [15] [4090/4276] eta: 0:09:20 lr: 3.1623512517553095e-05 loss: 0.1374 (0.1355) time: 2.9980 data: 0.0075 max mem: 33300 +Epoch: [15] [4100/4276] eta: 0:08:50 lr: 3.162074415100071e-05 loss: 0.1351 (0.1356) time: 3.0037 data: 0.0079 max mem: 33300 +Epoch: [15] [4110/4276] eta: 0:08:20 lr: 3.16179757575183e-05 loss: 0.1345 (0.1356) time: 3.0208 data: 0.0078 max mem: 33300 +Epoch: [15] [4120/4276] eta: 0:07:50 lr: 3.161520733710298e-05 loss: 0.1359 (0.1356) time: 3.0234 data: 0.0079 max mem: 33300 +Epoch: [15] [4130/4276] eta: 0:07:20 lr: 3.1612438889751875e-05 loss: 0.1359 (0.1356) time: 3.0076 data: 0.0079 max mem: 33300 +Epoch: [15] [4140/4276] eta: 0:06:50 lr: 3.160967041546208e-05 loss: 0.1251 (0.1356) time: 3.0049 data: 0.0079 max mem: 33300 +Epoch: [15] [4150/4276] eta: 0:06:19 lr: 3.160690191423073e-05 loss: 0.1329 (0.1356) time: 3.0220 data: 0.0079 max mem: 33300 +Epoch: [15] [4160/4276] eta: 0:05:49 lr: 3.160413338605493e-05 loss: 0.1329 (0.1356) time: 3.0190 data: 0.0073 max mem: 33300 +Epoch: [15] [4170/4276] eta: 0:05:19 lr: 3.16013648309318e-05 loss: 0.1391 (0.1356) time: 3.0754 data: 0.0072 max mem: 33300 +Epoch: [15] [4180/4276] eta: 0:04:49 lr: 3.159859624885846e-05 loss: 0.1391 (0.1356) time: 3.0687 data: 0.0076 max mem: 33300 +Epoch: [15] [4190/4276] eta: 0:04:19 lr: 3.1595827639832026e-05 loss: 0.1326 (0.1357) time: 3.0063 data: 0.0076 max mem: 33300 +Epoch: [15] [4200/4276] eta: 0:03:49 lr: 3.1593059003849604e-05 loss: 0.1416 (0.1357) time: 3.0185 data: 0.0076 max mem: 33300 +Epoch: [15] [4210/4276] eta: 0:03:19 lr: 3.15902903409083e-05 loss: 0.1481 (0.1357) time: 3.0053 data: 0.0075 max mem: 33300 +Epoch: [15] [4220/4276] eta: 0:02:48 lr: 3.158752165100523e-05 loss: 0.1492 (0.1357) time: 3.0535 data: 0.0075 max mem: 33300 +Epoch: [15] [4230/4276] eta: 0:02:18 lr: 3.158475293413751e-05 loss: 0.1492 (0.1358) time: 3.0435 data: 0.0080 max mem: 33300 +Epoch: [15] [4240/4276] eta: 0:01:48 lr: 3.1581984190302255e-05 loss: 0.1445 (0.1358) time: 2.9973 data: 0.0085 max mem: 33300 +Epoch: [15] [4250/4276] eta: 0:01:18 lr: 3.157921541949657e-05 loss: 0.1419 (0.1358) time: 3.0139 data: 0.0078 max mem: 33300 +Epoch: [15] [4260/4276] eta: 0:00:48 lr: 3.157644662171757e-05 loss: 0.1478 (0.1359) time: 3.0023 data: 0.0069 max mem: 33300 +Epoch: [15] [4270/4276] eta: 0:00:18 lr: 3.157367779696235e-05 loss: 0.1507 (0.1359) time: 3.0025 data: 0.0071 max mem: 33300 +Epoch: [15] Total time: 3:34:56 +Test: [ 0/21770] eta: 10:04:37 time: 1.6664 data: 1.5804 max mem: 33300 +Test: [ 100/21770] eta: 0:19:42 time: 0.0386 data: 0.0010 max mem: 33300 +Test: [ 200/21770] eta: 0:16:44 time: 0.0391 data: 0.0011 max mem: 33300 +Test: [ 300/21770] eta: 0:15:42 time: 0.0383 data: 0.0010 max mem: 33300 +Test: [ 400/21770] eta: 0:15:08 time: 0.0387 data: 0.0011 max mem: 33300 +Test: [ 500/21770] eta: 0:14:47 time: 0.0384 data: 0.0011 max mem: 33300 +Test: [ 600/21770] eta: 0:14:32 time: 0.0386 data: 0.0011 max mem: 33300 +Test: [ 700/21770] eta: 0:14:19 time: 0.0382 data: 0.0009 max mem: 33300 +Test: [ 800/21770] eta: 0:14:09 time: 0.0383 data: 0.0010 max mem: 33300 +Test: [ 900/21770] eta: 0:14:00 time: 0.0384 data: 0.0010 max mem: 33300 +Test: [ 1000/21770] eta: 0:13:52 time: 0.0381 data: 0.0010 max mem: 33300 +Test: [ 1100/21770] eta: 0:13:45 time: 0.0383 data: 0.0010 max mem: 33300 +Test: [ 1200/21770] eta: 0:13:38 time: 0.0384 data: 0.0010 max mem: 33300 +Test: [ 1300/21770] eta: 0:13:32 time: 0.0387 data: 0.0010 max mem: 33300 +Test: [ 1400/21770] eta: 0:13:26 time: 0.0379 data: 0.0009 max mem: 33300 +Test: [ 1500/21770] eta: 0:13:20 time: 0.0382 data: 0.0010 max mem: 33300 +Test: [ 1600/21770] eta: 0:13:15 time: 0.0384 data: 0.0010 max mem: 33300 +Test: [ 1700/21770] eta: 0:13:09 time: 0.0382 data: 0.0010 max mem: 33300 +Test: [ 1800/21770] eta: 0:13:04 time: 0.0383 data: 0.0010 max mem: 33300 +Test: [ 1900/21770] eta: 0:12:59 time: 0.0382 data: 0.0010 max mem: 33300 +Test: [ 2000/21770] eta: 0:12:54 time: 0.0381 data: 0.0009 max mem: 33300 +Test: [ 2100/21770] eta: 0:12:49 time: 0.0381 data: 0.0009 max mem: 33300 +Test: [ 2200/21770] eta: 0:12:45 time: 0.0384 data: 0.0010 max mem: 33300 +Test: [ 2300/21770] eta: 0:12:40 time: 0.0382 data: 0.0009 max mem: 33300 +Test: [ 2400/21770] eta: 0:12:36 time: 0.0382 data: 0.0010 max mem: 33300 +Test: [ 2500/21770] eta: 0:12:32 time: 0.0402 data: 0.0010 max mem: 33300 +Test: [ 2600/21770] eta: 0:12:29 time: 0.0397 data: 0.0011 max mem: 33300 +Test: [ 2700/21770] eta: 0:12:26 time: 0.0395 data: 0.0010 max mem: 33300 +Test: [ 2800/21770] eta: 0:12:22 time: 0.0402 data: 0.0012 max mem: 33300 +Test: [ 2900/21770] eta: 0:12:18 time: 0.0390 data: 0.0010 max mem: 33300 +Test: [ 3000/21770] eta: 0:12:14 time: 0.0391 data: 0.0010 max mem: 33300 +Test: [ 3100/21770] eta: 0:12:10 time: 0.0391 data: 0.0010 max mem: 33300 +Test: [ 3200/21770] eta: 0:12:06 time: 0.0391 data: 0.0011 max mem: 33300 +Test: [ 3300/21770] eta: 0:12:03 time: 0.0397 data: 0.0010 max mem: 33300 +Test: [ 3400/21770] eta: 0:11:59 time: 0.0393 data: 0.0011 max mem: 33300 +Test: [ 3500/21770] eta: 0:11:55 time: 0.0388 data: 0.0010 max mem: 33300 +Test: [ 3600/21770] eta: 0:11:51 time: 0.0388 data: 0.0011 max mem: 33300 +Test: [ 3700/21770] eta: 0:11:47 time: 0.0388 data: 0.0010 max mem: 33300 +Test: [ 3800/21770] eta: 0:11:42 time: 0.0388 data: 0.0011 max mem: 33300 +Test: [ 3900/21770] eta: 0:11:38 time: 0.0388 data: 0.0010 max mem: 33300 +Test: [ 4000/21770] eta: 0:11:34 time: 0.0389 data: 0.0011 max mem: 33300 +Test: [ 4100/21770] eta: 0:11:30 time: 0.0385 data: 0.0010 max mem: 33300 +Test: [ 4200/21770] eta: 0:11:26 time: 0.0392 data: 0.0010 max mem: 33300 +Test: [ 4300/21770] eta: 0:11:22 time: 0.0389 data: 0.0010 max mem: 33300 +Test: [ 4400/21770] eta: 0:11:18 time: 0.0393 data: 0.0010 max mem: 33300 +Test: [ 4500/21770] eta: 0:11:14 time: 0.0390 data: 0.0010 max mem: 33300 +Test: [ 4600/21770] eta: 0:11:10 time: 0.0388 data: 0.0010 max mem: 33300 +Test: [ 4700/21770] eta: 0:11:06 time: 0.0385 data: 0.0010 max mem: 33300 +Test: [ 4800/21770] eta: 0:11:02 time: 0.0384 data: 0.0009 max mem: 33300 +Test: [ 4900/21770] eta: 0:10:58 time: 0.0382 data: 0.0010 max mem: 33300 +Test: [ 5000/21770] eta: 0:10:54 time: 0.0389 data: 0.0010 max mem: 33300 +Test: [ 5100/21770] eta: 0:10:50 time: 0.0389 data: 0.0010 max mem: 33300 +Test: [ 5200/21770] eta: 0:10:46 time: 0.0393 data: 0.0009 max mem: 33300 +Test: [ 5300/21770] eta: 0:10:42 time: 0.0389 data: 0.0010 max mem: 33300 +Test: [ 5400/21770] eta: 0:10:38 time: 0.0392 data: 0.0010 max mem: 33300 +Test: [ 5500/21770] eta: 0:10:35 time: 0.0399 data: 0.0009 max mem: 33300 +Test: [ 5600/21770] eta: 0:10:31 time: 0.0394 data: 0.0010 max mem: 33300 +Test: [ 5700/21770] eta: 0:10:27 time: 0.0394 data: 0.0010 max mem: 33300 +Test: [ 5800/21770] eta: 0:10:23 time: 0.0391 data: 0.0010 max mem: 33300 +Test: [ 5900/21770] eta: 0:10:19 time: 0.0394 data: 0.0011 max mem: 33300 +Test: [ 6000/21770] eta: 0:10:15 time: 0.0393 data: 0.0010 max mem: 33300 +Test: [ 6100/21770] eta: 0:10:11 time: 0.0391 data: 0.0010 max mem: 33300 +Test: [ 6200/21770] eta: 0:10:08 time: 0.0390 data: 0.0010 max mem: 33300 +Test: [ 6300/21770] eta: 0:10:04 time: 0.0392 data: 0.0009 max mem: 33300 +Test: [ 6400/21770] eta: 0:10:00 time: 0.0390 data: 0.0009 max mem: 33300 +Test: [ 6500/21770] eta: 0:09:56 time: 0.0399 data: 0.0011 max mem: 33300 +Test: [ 6600/21770] eta: 0:09:52 time: 0.0389 data: 0.0010 max mem: 33300 +Test: [ 6700/21770] eta: 0:09:48 time: 0.0393 data: 0.0010 max mem: 33300 +Test: [ 6800/21770] eta: 0:09:45 time: 0.0396 data: 0.0011 max mem: 33300 +Test: [ 6900/21770] eta: 0:09:41 time: 0.0394 data: 0.0010 max mem: 33300 +Test: [ 7000/21770] eta: 0:09:37 time: 0.0397 data: 0.0011 max mem: 33300 +Test: [ 7100/21770] eta: 0:09:33 time: 0.0384 data: 0.0011 max mem: 33300 +Test: [ 7200/21770] eta: 0:09:29 time: 0.0385 data: 0.0011 max mem: 33300 +Test: [ 7300/21770] eta: 0:09:25 time: 0.0390 data: 0.0009 max mem: 33300 +Test: [ 7400/21770] eta: 0:09:21 time: 0.0391 data: 0.0010 max mem: 33300 +Test: [ 7500/21770] eta: 0:09:17 time: 0.0400 data: 0.0010 max mem: 33300 +Test: [ 7600/21770] eta: 0:09:14 time: 0.0398 data: 0.0010 max mem: 33300 +Test: [ 7700/21770] eta: 0:09:10 time: 0.0394 data: 0.0010 max mem: 33300 +Test: [ 7800/21770] eta: 0:09:06 time: 0.0393 data: 0.0010 max mem: 33300 +Test: [ 7900/21770] eta: 0:09:02 time: 0.0398 data: 0.0010 max mem: 33300 +Test: [ 8000/21770] eta: 0:08:58 time: 0.0401 data: 0.0010 max mem: 33300 +Test: [ 8100/21770] eta: 0:08:55 time: 0.0400 data: 0.0010 max mem: 33300 +Test: [ 8200/21770] eta: 0:08:51 time: 0.0396 data: 0.0010 max mem: 33300 +Test: [ 8300/21770] eta: 0:08:47 time: 0.0398 data: 0.0010 max mem: 33300 +Test: [ 8400/21770] eta: 0:08:43 time: 0.0391 data: 0.0010 max mem: 33300 +Test: [ 8500/21770] eta: 0:08:39 time: 0.0391 data: 0.0010 max mem: 33300 +Test: [ 8600/21770] eta: 0:08:35 time: 0.0391 data: 0.0010 max mem: 33300 +Test: [ 8700/21770] eta: 0:08:31 time: 0.0383 data: 0.0010 max mem: 33300 +Test: [ 8800/21770] eta: 0:08:27 time: 0.0388 data: 0.0009 max mem: 33300 +Test: [ 8900/21770] eta: 0:08:23 time: 0.0379 data: 0.0009 max mem: 33300 +Test: [ 9000/21770] eta: 0:08:19 time: 0.0385 data: 0.0010 max mem: 33300 +Test: [ 9100/21770] eta: 0:08:15 time: 0.0386 data: 0.0010 max mem: 33300 +Test: [ 9200/21770] eta: 0:08:11 time: 0.0395 data: 0.0010 max mem: 33300 +Test: [ 9300/21770] eta: 0:08:07 time: 0.0385 data: 0.0010 max mem: 33300 +Test: [ 9400/21770] eta: 0:08:03 time: 0.0386 data: 0.0011 max mem: 33300 +Test: [ 9500/21770] eta: 0:08:00 time: 0.0398 data: 0.0010 max mem: 33300 +Test: [ 9600/21770] eta: 0:07:56 time: 0.0389 data: 0.0009 max mem: 33300 +Test: [ 9700/21770] eta: 0:07:52 time: 0.0392 data: 0.0010 max mem: 33300 +Test: [ 9800/21770] eta: 0:07:48 time: 0.0391 data: 0.0010 max mem: 33300 +Test: [ 9900/21770] eta: 0:07:44 time: 0.0390 data: 0.0010 max mem: 33300 +Test: [10000/21770] eta: 0:07:40 time: 0.0389 data: 0.0011 max mem: 33300 +Test: [10100/21770] eta: 0:07:36 time: 0.0387 data: 0.0010 max mem: 33300 +Test: [10200/21770] eta: 0:07:32 time: 0.0389 data: 0.0011 max mem: 33300 +Test: [10300/21770] eta: 0:07:28 time: 0.0387 data: 0.0011 max mem: 33300 +Test: [10400/21770] eta: 0:07:24 time: 0.0392 data: 0.0010 max mem: 33300 +Test: [10500/21770] eta: 0:07:20 time: 0.0400 data: 0.0012 max mem: 33300 +Test: [10600/21770] eta: 0:07:16 time: 0.0387 data: 0.0011 max mem: 33300 +Test: [10700/21770] eta: 0:07:12 time: 0.0384 data: 0.0010 max mem: 33300 +Test: [10800/21770] eta: 0:07:08 time: 0.0386 data: 0.0010 max mem: 33300 +Test: [10900/21770] eta: 0:07:05 time: 0.0385 data: 0.0010 max mem: 33300 +Test: [11000/21770] eta: 0:07:01 time: 0.0385 data: 0.0010 max mem: 33300 +Test: [11100/21770] eta: 0:06:57 time: 0.0390 data: 0.0010 max mem: 33300 +Test: [11200/21770] eta: 0:06:53 time: 0.0384 data: 0.0010 max mem: 33300 +Test: [11300/21770] eta: 0:06:49 time: 0.0384 data: 0.0009 max mem: 33300 +Test: [11400/21770] eta: 0:06:45 time: 0.0381 data: 0.0010 max mem: 33300 +Test: [11500/21770] eta: 0:06:41 time: 0.0384 data: 0.0010 max mem: 33300 +Test: [11600/21770] eta: 0:06:37 time: 0.0385 data: 0.0010 max mem: 33300 +Test: [11700/21770] eta: 0:06:33 time: 0.0390 data: 0.0010 max mem: 33300 +Test: [11800/21770] eta: 0:06:29 time: 0.0383 data: 0.0010 max mem: 33300 +Test: [11900/21770] eta: 0:06:25 time: 0.0384 data: 0.0010 max mem: 33300 +Test: [12000/21770] eta: 0:06:21 time: 0.0381 data: 0.0010 max mem: 33300 +Test: [12100/21770] eta: 0:06:17 time: 0.0388 data: 0.0009 max mem: 33300 +Test: [12200/21770] eta: 0:06:13 time: 0.0393 data: 0.0010 max mem: 33300 +Test: [12300/21770] eta: 0:06:09 time: 0.0390 data: 0.0010 max mem: 33300 +Test: [12400/21770] eta: 0:06:05 time: 0.0386 data: 0.0010 max mem: 33300 +Test: [12500/21770] eta: 0:06:01 time: 0.0387 data: 0.0010 max mem: 33300 +Test: [12600/21770] eta: 0:05:58 time: 0.0383 data: 0.0010 max mem: 33300 +Test: [12700/21770] eta: 0:05:54 time: 0.0381 data: 0.0009 max mem: 33300 +Test: [12800/21770] eta: 0:05:50 time: 0.0391 data: 0.0010 max mem: 33300 +Test: [12900/21770] eta: 0:05:46 time: 0.0387 data: 0.0009 max mem: 33300 +Test: [13000/21770] eta: 0:05:42 time: 0.0386 data: 0.0009 max mem: 33300 +Test: [13100/21770] eta: 0:05:38 time: 0.0388 data: 0.0011 max mem: 33300 +Test: [13200/21770] eta: 0:05:34 time: 0.0398 data: 0.0011 max mem: 33300 +Test: [13300/21770] eta: 0:05:30 time: 0.0387 data: 0.0010 max mem: 33300 +Test: [13400/21770] eta: 0:05:26 time: 0.0389 data: 0.0011 max mem: 33300 +Test: [13500/21770] eta: 0:05:22 time: 0.0383 data: 0.0010 max mem: 33300 +Test: [13600/21770] eta: 0:05:18 time: 0.0389 data: 0.0011 max mem: 33300 +Test: [13700/21770] eta: 0:05:15 time: 0.0394 data: 0.0010 max mem: 33300 +Test: [13800/21770] eta: 0:05:11 time: 0.0387 data: 0.0011 max mem: 33300 +Test: [13900/21770] eta: 0:05:07 time: 0.0400 data: 0.0010 max mem: 33300 +Test: [14000/21770] eta: 0:05:03 time: 0.0400 data: 0.0010 max mem: 33300 +Test: [14100/21770] eta: 0:04:59 time: 0.0398 data: 0.0010 max mem: 33300 +Test: [14200/21770] eta: 0:04:55 time: 0.0398 data: 0.0010 max mem: 33300 +Test: [14300/21770] eta: 0:04:51 time: 0.0401 data: 0.0010 max mem: 33300 +Test: [14400/21770] eta: 0:04:47 time: 0.0385 data: 0.0010 max mem: 33300 +Test: [14500/21770] eta: 0:04:43 time: 0.0385 data: 0.0010 max mem: 33300 +Test: [14600/21770] eta: 0:04:40 time: 0.0385 data: 0.0010 max mem: 33300 +Test: [14700/21770] eta: 0:04:36 time: 0.0382 data: 0.0010 max mem: 33300 +Test: [14800/21770] eta: 0:04:32 time: 0.0384 data: 0.0010 max mem: 33300 +Test: [14900/21770] eta: 0:04:28 time: 0.0390 data: 0.0010 max mem: 33300 +Test: [15000/21770] eta: 0:04:24 time: 0.0392 data: 0.0011 max mem: 33300 +Test: [15100/21770] eta: 0:04:20 time: 0.0389 data: 0.0010 max mem: 33300 +Test: [15200/21770] eta: 0:04:16 time: 0.0383 data: 0.0010 max mem: 33300 +Test: [15300/21770] eta: 0:04:12 time: 0.0384 data: 0.0010 max mem: 33300 +Test: [15400/21770] eta: 0:04:08 time: 0.0392 data: 0.0011 max mem: 33300 +Test: [15500/21770] eta: 0:04:04 time: 0.0387 data: 0.0010 max mem: 33300 +Test: [15600/21770] eta: 0:04:00 time: 0.0396 data: 0.0011 max mem: 33300 +Test: [15700/21770] eta: 0:03:56 time: 0.0400 data: 0.0011 max mem: 33300 +Test: [15800/21770] eta: 0:03:53 time: 0.0390 data: 0.0009 max mem: 33300 +Test: [15900/21770] eta: 0:03:49 time: 0.0396 data: 0.0010 max mem: 33300 +Test: [16000/21770] eta: 0:03:45 time: 0.0389 data: 0.0010 max mem: 33300 +Test: [16100/21770] eta: 0:03:41 time: 0.0388 data: 0.0010 max mem: 33300 +Test: [16200/21770] eta: 0:03:37 time: 0.0393 data: 0.0011 max mem: 33300 +Test: [16300/21770] eta: 0:03:33 time: 0.0389 data: 0.0010 max mem: 33300 +Test: [16400/21770] eta: 0:03:29 time: 0.0400 data: 0.0011 max mem: 33300 +Test: [16500/21770] eta: 0:03:25 time: 0.0392 data: 0.0011 max mem: 33300 +Test: [16600/21770] eta: 0:03:21 time: 0.0391 data: 0.0010 max mem: 33300 +Test: [16700/21770] eta: 0:03:17 time: 0.0389 data: 0.0010 max mem: 33300 +Test: [16800/21770] eta: 0:03:14 time: 0.0391 data: 0.0010 max mem: 33300 +Test: [16900/21770] eta: 0:03:10 time: 0.0395 data: 0.0010 max mem: 33300 +Test: [17000/21770] eta: 0:03:06 time: 0.0386 data: 0.0011 max mem: 33300 +Test: [17100/21770] eta: 0:03:02 time: 0.0388 data: 0.0010 max mem: 33300 +Test: [17200/21770] eta: 0:02:58 time: 0.0391 data: 0.0010 max mem: 33300 +Test: [17300/21770] eta: 0:02:54 time: 0.0389 data: 0.0010 max mem: 33300 +Test: [17400/21770] eta: 0:02:50 time: 0.0391 data: 0.0010 max mem: 33300 +Test: [17500/21770] eta: 0:02:46 time: 0.0385 data: 0.0010 max mem: 33300 +Test: [17600/21770] eta: 0:02:42 time: 0.0389 data: 0.0011 max mem: 33300 +Test: [17700/21770] eta: 0:02:38 time: 0.0391 data: 0.0010 max mem: 33300 +Test: [17800/21770] eta: 0:02:34 time: 0.0386 data: 0.0009 max mem: 33300 +Test: [17900/21770] eta: 0:02:31 time: 0.0384 data: 0.0010 max mem: 33300 +Test: [18000/21770] eta: 0:02:27 time: 0.0390 data: 0.0010 max mem: 33300 +Test: [18100/21770] eta: 0:02:23 time: 0.0390 data: 0.0010 max mem: 33300 +Test: [18200/21770] eta: 0:02:19 time: 0.0389 data: 0.0010 max mem: 33300 +Test: [18300/21770] eta: 0:02:15 time: 0.0384 data: 0.0009 max mem: 33300 +Test: [18400/21770] eta: 0:02:11 time: 0.0389 data: 0.0010 max mem: 33300 +Test: [18500/21770] eta: 0:02:07 time: 0.0391 data: 0.0010 max mem: 33300 +Test: [18600/21770] eta: 0:02:03 time: 0.0387 data: 0.0010 max mem: 33300 +Test: [18700/21770] eta: 0:01:59 time: 0.0385 data: 0.0010 max mem: 33300 +Test: [18800/21770] eta: 0:01:55 time: 0.0385 data: 0.0010 max mem: 33300 +Test: [18900/21770] eta: 0:01:52 time: 0.0392 data: 0.0010 max mem: 33300 +Test: [19000/21770] eta: 0:01:48 time: 0.0387 data: 0.0010 max mem: 33300 +Test: [19100/21770] eta: 0:01:44 time: 0.0387 data: 0.0010 max mem: 33300 +Test: [19200/21770] eta: 0:01:40 time: 0.0392 data: 0.0009 max mem: 33300 +Test: [19300/21770] eta: 0:01:36 time: 0.0393 data: 0.0010 max mem: 33300 +Test: [19400/21770] eta: 0:01:32 time: 0.0391 data: 0.0010 max mem: 33300 +Test: [19500/21770] eta: 0:01:28 time: 0.0391 data: 0.0010 max mem: 33300 +Test: [19600/21770] eta: 0:01:24 time: 0.0401 data: 0.0010 max mem: 33300 +Test: [19700/21770] eta: 0:01:20 time: 0.0403 data: 0.0011 max mem: 33300 +Test: [19800/21770] eta: 0:01:16 time: 0.0396 data: 0.0011 max mem: 33300 +Test: [19900/21770] eta: 0:01:13 time: 0.0388 data: 0.0010 max mem: 33300 +Test: [20000/21770] eta: 0:01:09 time: 0.0396 data: 0.0011 max mem: 33300 +Test: [20100/21770] eta: 0:01:05 time: 0.0394 data: 0.0010 max mem: 33300 +Test: [20200/21770] eta: 0:01:01 time: 0.0393 data: 0.0011 max mem: 33300 +Test: [20300/21770] eta: 0:00:57 time: 0.0399 data: 0.0011 max mem: 33300 +Test: [20400/21770] eta: 0:00:53 time: 0.0387 data: 0.0011 max mem: 33300 +Test: [20500/21770] eta: 0:00:49 time: 0.0384 data: 0.0009 max mem: 33300 +Test: [20600/21770] eta: 0:00:45 time: 0.0391 data: 0.0010 max mem: 33300 +Test: [20700/21770] eta: 0:00:41 time: 0.0400 data: 0.0010 max mem: 33300 +Test: [20800/21770] eta: 0:00:37 time: 0.0399 data: 0.0010 max mem: 33300 +Test: [20900/21770] eta: 0:00:33 time: 0.0394 data: 0.0010 max mem: 33300 +Test: [21000/21770] eta: 0:00:30 time: 0.0394 data: 0.0010 max mem: 33300 +Test: [21100/21770] eta: 0:00:26 time: 0.0398 data: 0.0010 max mem: 33300 +Test: [21200/21770] eta: 0:00:22 time: 0.0390 data: 0.0010 max mem: 33300 +Test: [21300/21770] eta: 0:00:18 time: 0.0388 data: 0.0010 max mem: 33300 +Test: [21400/21770] eta: 0:00:14 time: 0.0393 data: 0.0010 max mem: 33300 +Test: [21500/21770] eta: 0:00:10 time: 0.0398 data: 0.0011 max mem: 33300 +Test: [21600/21770] eta: 0:00:06 time: 0.0397 data: 0.0010 max mem: 33300 +Test: [21700/21770] eta: 0:00:02 time: 0.0390 data: 0.0010 max mem: 33300 +Test: Total time: 0:14:10 +Final results: +Mean IoU is 0.00 + + precision@0.5 = 0.00 + precision@0.6 = 0.00 + precision@0.7 = 0.00 + precision@0.8 = 0.00 + precision@0.9 = 0.00 + overall IoU = 0.00 + mean IoU = 0.00 + +Mean accuracy for one-to-zero sample is 100.00 + +Average object IoU 0.0 +Overall IoU 0.0 +Epoch: [16] [ 0/4276] eta: 6:49:50 lr: 3.157201648915944e-05 loss: 0.1153 (0.1153) time: 5.7508 data: 2.2581 max mem: 33300 +Epoch: [16] [ 10/4276] eta: 4:17:15 lr: 3.156924762123627e-05 loss: 0.1454 (0.1455) time: 3.6182 data: 0.2130 max mem: 33300 +Epoch: [16] [ 20/4276] eta: 4:09:47 lr: 3.156647872632937e-05 loss: 0.1454 (0.1439) time: 3.4101 data: 0.0087 max mem: 33300 +Epoch: [16] [ 30/4276] eta: 4:07:02 lr: 3.156370980443586e-05 loss: 0.1429 (0.1441) time: 3.4211 data: 0.0087 max mem: 33300 +Epoch: [16] [ 40/4276] eta: 4:04:59 lr: 3.1560940855552826e-05 loss: 0.1496 (0.1444) time: 3.4161 data: 0.0085 max mem: 33300 +Epoch: [16] [ 50/4276] eta: 4:03:34 lr: 3.1558171879677386e-05 loss: 0.1424 (0.1414) time: 3.4076 data: 0.0081 max mem: 33300 +Epoch: [16] [ 60/4276] eta: 4:02:57 lr: 3.1555402876806635e-05 loss: 0.1270 (0.1402) time: 3.4323 data: 0.0081 max mem: 33300 +Epoch: [16] [ 70/4276] eta: 4:01:43 lr: 3.1552633846937684e-05 loss: 0.1304 (0.1399) time: 3.4224 data: 0.0079 max mem: 33300 +Epoch: [16] [ 80/4276] eta: 4:00:45 lr: 3.154986479006764e-05 loss: 0.1402 (0.1397) time: 3.3969 data: 0.0077 max mem: 33300 +Epoch: [16] [ 90/4276] eta: 3:59:44 lr: 3.15470957061936e-05 loss: 0.1388 (0.1393) time: 3.3942 data: 0.0079 max mem: 33300 +Epoch: [16] [ 100/4276] eta: 3:58:53 lr: 3.154432659531268e-05 loss: 0.1388 (0.1407) time: 3.3905 data: 0.0079 max mem: 33300 +Epoch: [16] [ 110/4276] eta: 3:58:04 lr: 3.154155745742197e-05 loss: 0.1432 (0.1411) time: 3.3950 data: 0.0076 max mem: 33300 +Epoch: [16] [ 120/4276] eta: 3:57:10 lr: 3.153878829251857e-05 loss: 0.1302 (0.1402) time: 3.3827 data: 0.0073 max mem: 33300 +Epoch: [16] [ 130/4276] eta: 3:56:27 lr: 3.153601910059959e-05 loss: 0.1372 (0.1404) time: 3.3835 data: 0.0080 max mem: 33300 +Epoch: [16] [ 140/4276] eta: 3:55:56 lr: 3.1533249881662126e-05 loss: 0.1342 (0.1392) time: 3.4142 data: 0.0081 max mem: 33300 +Epoch: [16] [ 150/4276] eta: 3:55:14 lr: 3.153048063570327e-05 loss: 0.1221 (0.1390) time: 3.4139 data: 0.0074 max mem: 33300 +Epoch: [16] [ 160/4276] eta: 3:54:30 lr: 3.152771136272014e-05 loss: 0.1254 (0.1384) time: 3.3877 data: 0.0073 max mem: 33300 +Epoch: [16] [ 170/4276] eta: 3:53:53 lr: 3.1524942062709815e-05 loss: 0.1286 (0.1387) time: 3.3940 data: 0.0076 max mem: 33300 +Epoch: [16] [ 180/4276] eta: 3:53:11 lr: 3.152217273566942e-05 loss: 0.1342 (0.1389) time: 3.3967 data: 0.0077 max mem: 33300 +Epoch: [16] [ 190/4276] eta: 3:52:28 lr: 3.151940338159602e-05 loss: 0.1342 (0.1389) time: 3.3801 data: 0.0072 max mem: 33300 +Epoch: [16] [ 200/4276] eta: 3:51:45 lr: 3.151663400048673e-05 loss: 0.1318 (0.1386) time: 3.3702 data: 0.0074 max mem: 33300 +Epoch: [16] [ 210/4276] eta: 3:51:16 lr: 3.151386459233865e-05 loss: 0.1318 (0.1388) time: 3.4044 data: 0.0075 max mem: 33300 +Epoch: [16] [ 220/4276] eta: 3:50:33 lr: 3.151109515714886e-05 loss: 0.1306 (0.1386) time: 3.4029 data: 0.0070 max mem: 33300 +Epoch: [16] [ 230/4276] eta: 3:49:54 lr: 3.150832569491447e-05 loss: 0.1238 (0.1381) time: 3.3722 data: 0.0068 max mem: 33300 +Epoch: [16] [ 240/4276] eta: 3:49:17 lr: 3.150555620563257e-05 loss: 0.1358 (0.1382) time: 3.3881 data: 0.0074 max mem: 33300 +Epoch: [16] [ 250/4276] eta: 3:48:39 lr: 3.150278668930025e-05 loss: 0.1396 (0.1387) time: 3.3880 data: 0.0077 max mem: 33300 +Epoch: [16] [ 260/4276] eta: 3:47:57 lr: 3.1500017145914605e-05 loss: 0.1458 (0.1388) time: 3.3704 data: 0.0075 max mem: 33300 +Epoch: [16] [ 270/4276] eta: 3:47:20 lr: 3.149724757547274e-05 loss: 0.1254 (0.1384) time: 3.3705 data: 0.0075 max mem: 33300 +Epoch: [16] [ 280/4276] eta: 3:46:47 lr: 3.149447797797173e-05 loss: 0.1254 (0.1383) time: 3.3984 data: 0.0074 max mem: 33300 +Epoch: [16] [ 290/4276] eta: 3:46:15 lr: 3.149170835340868e-05 loss: 0.1171 (0.1380) time: 3.4167 data: 0.0070 max mem: 33300 +Epoch: [16] [ 300/4276] eta: 3:45:37 lr: 3.148893870178066e-05 loss: 0.1250 (0.1379) time: 3.3960 data: 0.0067 max mem: 33300 +Epoch: [16] [ 310/4276] eta: 3:44:59 lr: 3.1486169023084784e-05 loss: 0.1300 (0.1376) time: 3.3753 data: 0.0069 max mem: 33300 +Epoch: [16] [ 320/4276] eta: 3:44:21 lr: 3.148339931731813e-05 loss: 0.1319 (0.1380) time: 3.3755 data: 0.0071 max mem: 33300 +Epoch: [16] [ 330/4276] eta: 3:43:44 lr: 3.148062958447779e-05 loss: 0.1376 (0.1381) time: 3.3768 data: 0.0070 max mem: 33300 +Epoch: [16] [ 340/4276] eta: 3:43:08 lr: 3.147785982456086e-05 loss: 0.1292 (0.1378) time: 3.3804 data: 0.0069 max mem: 33300 +Epoch: [16] [ 350/4276] eta: 3:42:30 lr: 3.147509003756441e-05 loss: 0.1248 (0.1376) time: 3.3714 data: 0.0070 max mem: 33300 +Epoch: [16] [ 360/4276] eta: 3:42:00 lr: 3.1472320223485545e-05 loss: 0.1400 (0.1383) time: 3.4018 data: 0.0082 max mem: 33300 +Epoch: [16] [ 370/4276] eta: 3:41:24 lr: 3.146955038232134e-05 loss: 0.1319 (0.1379) time: 3.4104 data: 0.0081 max mem: 33300 +Epoch: [16] [ 380/4276] eta: 3:40:46 lr: 3.14667805140689e-05 loss: 0.1208 (0.1381) time: 3.3734 data: 0.0074 max mem: 33300 +Epoch: [16] [ 390/4276] eta: 3:40:09 lr: 3.1464010618725275e-05 loss: 0.1399 (0.1384) time: 3.3661 data: 0.0073 max mem: 33300 +Epoch: [16] [ 400/4276] eta: 3:39:31 lr: 3.1461240696287584e-05 loss: 0.1446 (0.1384) time: 3.3624 data: 0.0072 max mem: 33300 +Epoch: [16] [ 410/4276] eta: 3:38:51 lr: 3.1458470746752895e-05 loss: 0.1337 (0.1383) time: 3.3492 data: 0.0074 max mem: 33300 +Epoch: [16] [ 420/4276] eta: 3:38:18 lr: 3.14557007701183e-05 loss: 0.1311 (0.1381) time: 3.3728 data: 0.0078 max mem: 33300 +Epoch: [16] [ 430/4276] eta: 3:37:43 lr: 3.1452930766380876e-05 loss: 0.1311 (0.1386) time: 3.3960 data: 0.0081 max mem: 33300 +Epoch: [16] [ 440/4276] eta: 3:37:09 lr: 3.145016073553771e-05 loss: 0.1330 (0.1384) time: 3.3884 data: 0.0081 max mem: 33300 +Epoch: [16] [ 450/4276] eta: 3:36:34 lr: 3.144739067758588e-05 loss: 0.1330 (0.1384) time: 3.3912 data: 0.0080 max mem: 33300 +Epoch: [16] [ 460/4276] eta: 3:35:58 lr: 3.144462059252247e-05 loss: 0.1298 (0.1380) time: 3.3799 data: 0.0073 max mem: 33300 +Epoch: [16] [ 470/4276] eta: 3:35:22 lr: 3.144185048034456e-05 loss: 0.1071 (0.1375) time: 3.3686 data: 0.0076 max mem: 33300 +Epoch: [16] [ 480/4276] eta: 3:34:48 lr: 3.143908034104923e-05 loss: 0.1156 (0.1373) time: 3.3794 data: 0.0087 max mem: 33300 +Epoch: [16] [ 490/4276] eta: 3:34:15 lr: 3.1436310174633565e-05 loss: 0.1144 (0.1368) time: 3.3993 data: 0.0086 max mem: 33300 +Epoch: [16] [ 500/4276] eta: 3:33:41 lr: 3.143353998109464e-05 loss: 0.1101 (0.1364) time: 3.4053 data: 0.0080 max mem: 33300 +Epoch: [16] [ 510/4276] eta: 3:33:09 lr: 3.1430769760429526e-05 loss: 0.1119 (0.1361) time: 3.4091 data: 0.0079 max mem: 33300 +Epoch: [16] [ 520/4276] eta: 3:32:34 lr: 3.142799951263531e-05 loss: 0.1209 (0.1361) time: 3.3970 data: 0.0073 max mem: 33300 +Epoch: [16] [ 530/4276] eta: 3:31:58 lr: 3.142522923770907e-05 loss: 0.1250 (0.1362) time: 3.3773 data: 0.0069 max mem: 33300 +Epoch: [16] [ 540/4276] eta: 3:31:21 lr: 3.142245893564787e-05 loss: 0.1255 (0.1359) time: 3.3617 data: 0.0077 max mem: 33300 +Epoch: [16] [ 550/4276] eta: 3:30:43 lr: 3.1419688606448804e-05 loss: 0.1324 (0.1360) time: 3.3406 data: 0.0079 max mem: 33300 +Epoch: [16] [ 560/4276] eta: 3:30:08 lr: 3.141691825010894e-05 loss: 0.1365 (0.1361) time: 3.3567 data: 0.0087 max mem: 33300 +Epoch: [16] [ 570/4276] eta: 3:29:34 lr: 3.141414786662535e-05 loss: 0.1369 (0.1360) time: 3.3880 data: 0.0088 max mem: 33300 +Epoch: [16] [ 580/4276] eta: 3:29:02 lr: 3.141137745599511e-05 loss: 0.1303 (0.1360) time: 3.4058 data: 0.0084 max mem: 33300 +Epoch: [16] [ 590/4276] eta: 3:28:30 lr: 3.1408607018215296e-05 loss: 0.1167 (0.1356) time: 3.4253 data: 0.0080 max mem: 33300 +Epoch: [16] [ 600/4276] eta: 3:27:58 lr: 3.140583655328297e-05 loss: 0.1170 (0.1358) time: 3.4248 data: 0.0078 max mem: 33300 +Epoch: [16] [ 610/4276] eta: 3:27:23 lr: 3.140306606119522e-05 loss: 0.1312 (0.1357) time: 3.3934 data: 0.0077 max mem: 33300 +Epoch: [16] [ 620/4276] eta: 3:26:46 lr: 3.140029554194911e-05 loss: 0.1280 (0.1356) time: 3.3593 data: 0.0069 max mem: 33300 +Epoch: [16] [ 630/4276] eta: 3:26:10 lr: 3.1397524995541714e-05 loss: 0.1249 (0.1357) time: 3.3500 data: 0.0075 max mem: 33300 +Epoch: [16] [ 640/4276] eta: 3:25:32 lr: 3.13947544219701e-05 loss: 0.1199 (0.1355) time: 3.3426 data: 0.0080 max mem: 33300 +Epoch: [16] [ 650/4276] eta: 3:24:56 lr: 3.139198382123134e-05 loss: 0.1305 (0.1356) time: 3.3373 data: 0.0073 max mem: 33300 +Epoch: [16] [ 660/4276] eta: 3:24:20 lr: 3.13892131933225e-05 loss: 0.1477 (0.1358) time: 3.3475 data: 0.0071 max mem: 33300 +Epoch: [16] [ 670/4276] eta: 3:23:46 lr: 3.138644253824066e-05 loss: 0.1400 (0.1358) time: 3.3760 data: 0.0071 max mem: 33300 +Epoch: [16] [ 680/4276] eta: 3:23:15 lr: 3.138367185598286e-05 loss: 0.1371 (0.1358) time: 3.4177 data: 0.0069 max mem: 33300 +Epoch: [16] [ 690/4276] eta: 3:22:41 lr: 3.1380901146546206e-05 loss: 0.1299 (0.1356) time: 3.4180 data: 0.0074 max mem: 33300 +Epoch: [16] [ 700/4276] eta: 3:22:06 lr: 3.137813040992773e-05 loss: 0.1236 (0.1355) time: 3.3875 data: 0.0075 max mem: 33300 +Epoch: [16] [ 710/4276] eta: 3:21:31 lr: 3.1375359646124524e-05 loss: 0.1336 (0.1356) time: 3.3641 data: 0.0075 max mem: 33300 +Epoch: [16] [ 720/4276] eta: 3:20:55 lr: 3.1372588855133644e-05 loss: 0.1301 (0.1355) time: 3.3588 data: 0.0072 max mem: 33300 +Epoch: [16] [ 730/4276] eta: 3:20:21 lr: 3.136981803695216e-05 loss: 0.1244 (0.1354) time: 3.3741 data: 0.0071 max mem: 33300 +Epoch: [16] [ 740/4276] eta: 3:19:46 lr: 3.136704719157712e-05 loss: 0.1200 (0.1353) time: 3.3747 data: 0.0074 max mem: 33300 +Epoch: [16] [ 750/4276] eta: 3:19:15 lr: 3.136427631900561e-05 loss: 0.1279 (0.1354) time: 3.4066 data: 0.0074 max mem: 33300 +Epoch: [16] [ 760/4276] eta: 3:18:43 lr: 3.136150541923468e-05 loss: 0.1300 (0.1353) time: 3.4422 data: 0.0080 max mem: 33300 +Epoch: [16] [ 770/4276] eta: 3:18:07 lr: 3.135873449226139e-05 loss: 0.1372 (0.1353) time: 3.3936 data: 0.0082 max mem: 33300 +Epoch: [16] [ 780/4276] eta: 3:17:31 lr: 3.135596353808282e-05 loss: 0.1386 (0.1353) time: 3.3426 data: 0.0080 max mem: 33300 +Epoch: [16] [ 790/4276] eta: 3:16:55 lr: 3.135319255669601e-05 loss: 0.1310 (0.1353) time: 3.3437 data: 0.0076 max mem: 33300 +Epoch: [16] [ 800/4276] eta: 3:16:21 lr: 3.1350421548098033e-05 loss: 0.1310 (0.1352) time: 3.3669 data: 0.0080 max mem: 33300 +Epoch: [16] [ 810/4276] eta: 3:15:47 lr: 3.1347650512285955e-05 loss: 0.1234 (0.1352) time: 3.3884 data: 0.0092 max mem: 33300 +Epoch: [16] [ 820/4276] eta: 3:15:13 lr: 3.134487944925682e-05 loss: 0.1173 (0.1349) time: 3.3842 data: 0.0085 max mem: 33300 +Epoch: [16] [ 830/4276] eta: 3:14:42 lr: 3.13421083590077e-05 loss: 0.1179 (0.1349) time: 3.4225 data: 0.0079 max mem: 33300 +Epoch: [16] [ 840/4276] eta: 3:14:11 lr: 3.133933724153564e-05 loss: 0.1273 (0.1349) time: 3.4575 data: 0.0084 max mem: 33300 +Epoch: [16] [ 850/4276] eta: 3:13:36 lr: 3.1336566096837714e-05 loss: 0.1255 (0.1350) time: 3.4123 data: 0.0081 max mem: 33300 +Epoch: [16] [ 860/4276] eta: 3:13:02 lr: 3.1333794924910964e-05 loss: 0.1270 (0.1351) time: 3.3781 data: 0.0074 max mem: 33300 +Epoch: [16] [ 870/4276] eta: 3:12:28 lr: 3.133102372575246e-05 loss: 0.1282 (0.1351) time: 3.3777 data: 0.0074 max mem: 33300 +Epoch: [16] [ 880/4276] eta: 3:11:53 lr: 3.132825249935925e-05 loss: 0.1315 (0.1352) time: 3.3748 data: 0.0075 max mem: 33300 +Epoch: [16] [ 890/4276] eta: 3:11:19 lr: 3.1325481245728396e-05 loss: 0.1434 (0.1354) time: 3.3797 data: 0.0075 max mem: 33300 +Epoch: [16] [ 900/4276] eta: 3:10:45 lr: 3.132270996485695e-05 loss: 0.1327 (0.1354) time: 3.3918 data: 0.0076 max mem: 33300 +Epoch: [16] [ 910/4276] eta: 3:10:14 lr: 3.131993865674196e-05 loss: 0.1416 (0.1354) time: 3.4354 data: 0.0074 max mem: 33300 +Epoch: [16] [ 920/4276] eta: 3:09:41 lr: 3.1317167321380484e-05 loss: 0.1427 (0.1355) time: 3.4472 data: 0.0074 max mem: 33300 +Epoch: [16] [ 930/4276] eta: 3:09:06 lr: 3.131439595876958e-05 loss: 0.1383 (0.1355) time: 3.3879 data: 0.0073 max mem: 33300 +Epoch: [16] [ 940/4276] eta: 3:08:32 lr: 3.13116245689063e-05 loss: 0.1197 (0.1354) time: 3.3655 data: 0.0080 max mem: 33300 +Epoch: [16] [ 950/4276] eta: 3:07:57 lr: 3.130885315178768e-05 loss: 0.1203 (0.1356) time: 3.3713 data: 0.0081 max mem: 33300 +Epoch: [16] [ 960/4276] eta: 3:07:23 lr: 3.13060817074108e-05 loss: 0.1376 (0.1356) time: 3.3752 data: 0.0077 max mem: 33300 +Epoch: [16] [ 970/4276] eta: 3:06:49 lr: 3.130331023577268e-05 loss: 0.1345 (0.1356) time: 3.3802 data: 0.0075 max mem: 33300 +Epoch: [16] [ 980/4276] eta: 3:06:15 lr: 3.13005387368704e-05 loss: 0.1317 (0.1356) time: 3.3941 data: 0.0074 max mem: 33300 +Epoch: [16] [ 990/4276] eta: 3:05:42 lr: 3.129776721070097e-05 loss: 0.1251 (0.1355) time: 3.4121 data: 0.0073 max mem: 33300 +Epoch: [16] [1000/4276] eta: 3:05:08 lr: 3.129499565726148e-05 loss: 0.1236 (0.1355) time: 3.3963 data: 0.0073 max mem: 33300 +Epoch: [16] [1010/4276] eta: 3:04:33 lr: 3.129222407654895e-05 loss: 0.1339 (0.1354) time: 3.3693 data: 0.0073 max mem: 33300 +Epoch: [16] [1020/4276] eta: 3:03:58 lr: 3.128945246856044e-05 loss: 0.1180 (0.1354) time: 3.3557 data: 0.0076 max mem: 33300 +Epoch: [16] [1030/4276] eta: 3:03:23 lr: 3.1286680833293e-05 loss: 0.1410 (0.1355) time: 3.3555 data: 0.0080 max mem: 33300 +Epoch: [16] [1040/4276] eta: 3:02:48 lr: 3.128390917074367e-05 loss: 0.1352 (0.1353) time: 3.3620 data: 0.0078 max mem: 33300 +Epoch: [16] [1050/4276] eta: 3:02:14 lr: 3.12811374809095e-05 loss: 0.1271 (0.1354) time: 3.3687 data: 0.0073 max mem: 33300 +Epoch: [16] [1060/4276] eta: 3:01:41 lr: 3.127836576378753e-05 loss: 0.1364 (0.1355) time: 3.3998 data: 0.0074 max mem: 33300 +Epoch: [16] [1070/4276] eta: 3:01:08 lr: 3.127559401937481e-05 loss: 0.1559 (0.1358) time: 3.4152 data: 0.0080 max mem: 33300 +Epoch: [16] [1080/4276] eta: 3:00:28 lr: 3.127282224766837e-05 loss: 0.1535 (0.1358) time: 3.2992 data: 0.0078 max mem: 33300 +Epoch: [16] [1090/4276] eta: 2:59:43 lr: 3.1270050448665275e-05 loss: 0.1374 (0.1359) time: 3.1069 data: 0.0076 max mem: 33300 +Epoch: [16] [1100/4276] eta: 2:59:00 lr: 3.126727862236255e-05 loss: 0.1362 (0.1359) time: 3.0354 data: 0.0078 max mem: 33300 +Epoch: [16] [1110/4276] eta: 2:58:16 lr: 3.126450676875724e-05 loss: 0.1314 (0.1360) time: 3.0390 data: 0.0076 max mem: 33300 +Epoch: [16] [1120/4276] eta: 2:57:32 lr: 3.12617348878464e-05 loss: 0.1347 (0.1359) time: 3.0291 data: 0.0075 max mem: 33300 +Epoch: [16] [1130/4276] eta: 2:56:49 lr: 3.125896297962706e-05 loss: 0.1180 (0.1358) time: 3.0296 data: 0.0074 max mem: 33300 +Epoch: [16] [1140/4276] eta: 2:56:06 lr: 3.125619104409626e-05 loss: 0.1257 (0.1358) time: 3.0419 data: 0.0068 max mem: 33300 +Epoch: [16] [1150/4276] eta: 2:55:25 lr: 3.125341908125104e-05 loss: 0.1296 (0.1357) time: 3.0669 data: 0.0070 max mem: 33300 +Epoch: [16] [1160/4276] eta: 2:54:43 lr: 3.1250647091088436e-05 loss: 0.1283 (0.1357) time: 3.0669 data: 0.0071 max mem: 33300 +Epoch: [16] [1170/4276] eta: 2:54:00 lr: 3.124787507360549e-05 loss: 0.1346 (0.1357) time: 3.0278 data: 0.0066 max mem: 33300 +Epoch: [16] [1180/4276] eta: 2:53:18 lr: 3.124510302879925e-05 loss: 0.1247 (0.1358) time: 3.0331 data: 0.0070 max mem: 33300 +Epoch: [16] [1190/4276] eta: 2:52:36 lr: 3.124233095666673e-05 loss: 0.1208 (0.1357) time: 3.0523 data: 0.0077 max mem: 33300 +Epoch: [16] [1200/4276] eta: 2:51:55 lr: 3.123955885720499e-05 loss: 0.1231 (0.1357) time: 3.0377 data: 0.0076 max mem: 33300 +Epoch: [16] [1210/4276] eta: 2:51:13 lr: 3.123678673041105e-05 loss: 0.1232 (0.1356) time: 3.0263 data: 0.0073 max mem: 33300 +Epoch: [16] [1220/4276] eta: 2:50:30 lr: 3.123401457628196e-05 loss: 0.1234 (0.1356) time: 3.0098 data: 0.0073 max mem: 33300 +Epoch: [16] [1230/4276] eta: 2:49:50 lr: 3.123124239481474e-05 loss: 0.1285 (0.1357) time: 3.0396 data: 0.0075 max mem: 33300 +Epoch: [16] [1240/4276] eta: 2:49:10 lr: 3.122847018600643e-05 loss: 0.1268 (0.1356) time: 3.0784 data: 0.0073 max mem: 33300 +Epoch: [16] [1250/4276] eta: 2:48:29 lr: 3.122569794985405e-05 loss: 0.1215 (0.1356) time: 3.0581 data: 0.0071 max mem: 33300 +Epoch: [16] [1260/4276] eta: 2:47:47 lr: 3.1222925686354664e-05 loss: 0.1167 (0.1355) time: 3.0089 data: 0.0073 max mem: 33300 +Epoch: [16] [1270/4276] eta: 2:47:05 lr: 3.1220153395505285e-05 loss: 0.1209 (0.1355) time: 2.9788 data: 0.0074 max mem: 33300 +Epoch: [16] [1280/4276] eta: 2:46:24 lr: 3.121738107730294e-05 loss: 0.1307 (0.1355) time: 2.9810 data: 0.0073 max mem: 33300 +Epoch: [16] [1290/4276] eta: 2:45:42 lr: 3.1214608731744675e-05 loss: 0.1254 (0.1354) time: 2.9865 data: 0.0071 max mem: 33300 +Epoch: [16] [1300/4276] eta: 2:45:02 lr: 3.121183635882751e-05 loss: 0.1182 (0.1353) time: 3.0062 data: 0.0071 max mem: 33300 +Epoch: [16] [1310/4276] eta: 2:44:22 lr: 3.1209063958548465e-05 loss: 0.1180 (0.1352) time: 3.0315 data: 0.0073 max mem: 33300 +Epoch: [16] [1320/4276] eta: 2:43:44 lr: 3.120629153090459e-05 loss: 0.1373 (0.1353) time: 3.0724 data: 0.0076 max mem: 33300 +Epoch: [16] [1330/4276] eta: 2:43:05 lr: 3.12035190758929e-05 loss: 0.1373 (0.1353) time: 3.0851 data: 0.0079 max mem: 33300 +Epoch: [16] [1340/4276] eta: 2:42:26 lr: 3.120074659351043e-05 loss: 0.1317 (0.1352) time: 3.0557 data: 0.0074 max mem: 33300 +Epoch: [16] [1350/4276] eta: 2:41:46 lr: 3.119797408375421e-05 loss: 0.1188 (0.1352) time: 3.0235 data: 0.0071 max mem: 33300 +Epoch: [16] [1360/4276] eta: 2:41:07 lr: 3.119520154662125e-05 loss: 0.1287 (0.1351) time: 3.0173 data: 0.0077 max mem: 33300 +Epoch: [16] [1370/4276] eta: 2:40:28 lr: 3.119242898210859e-05 loss: 0.1224 (0.1351) time: 3.0361 data: 0.0076 max mem: 33300 +Epoch: [16] [1380/4276] eta: 2:39:49 lr: 3.118965639021326e-05 loss: 0.1288 (0.1352) time: 3.0405 data: 0.0076 max mem: 33300 +Epoch: [16] [1390/4276] eta: 2:39:10 lr: 3.118688377093227e-05 loss: 0.1390 (0.1352) time: 3.0370 data: 0.0076 max mem: 33300 +Epoch: [16] [1400/4276] eta: 2:38:32 lr: 3.118411112426266e-05 loss: 0.1369 (0.1352) time: 3.0506 data: 0.0073 max mem: 33300 +Epoch: [16] [1410/4276] eta: 2:37:54 lr: 3.1181338450201437e-05 loss: 0.1250 (0.1352) time: 3.0777 data: 0.0074 max mem: 33300 +Epoch: [16] [1420/4276] eta: 2:37:17 lr: 3.1178565748745634e-05 loss: 0.1222 (0.1352) time: 3.0794 data: 0.0071 max mem: 33300 +Epoch: [16] [1430/4276] eta: 2:36:39 lr: 3.117579301989228e-05 loss: 0.1157 (0.1351) time: 3.0626 data: 0.0078 max mem: 33300 +Epoch: [16] [1440/4276] eta: 2:36:00 lr: 3.117302026363838e-05 loss: 0.1178 (0.1351) time: 3.0438 data: 0.0077 max mem: 33300 +Epoch: [16] [1450/4276] eta: 2:35:22 lr: 3.1170247479980974e-05 loss: 0.1258 (0.1351) time: 3.0407 data: 0.0071 max mem: 33300 +Epoch: [16] [1460/4276] eta: 2:34:44 lr: 3.116747466891706e-05 loss: 0.1320 (0.1350) time: 3.0338 data: 0.0074 max mem: 33300 +Epoch: [16] [1470/4276] eta: 2:34:06 lr: 3.1164701830443684e-05 loss: 0.1340 (0.1350) time: 3.0302 data: 0.0075 max mem: 33300 +Epoch: [16] [1480/4276] eta: 2:33:28 lr: 3.116192896455784e-05 loss: 0.1142 (0.1349) time: 3.0230 data: 0.0074 max mem: 33300 +Epoch: [16] [1490/4276] eta: 2:32:50 lr: 3.115915607125656e-05 loss: 0.1142 (0.1349) time: 3.0355 data: 0.0076 max mem: 33300 +Epoch: [16] [1500/4276] eta: 2:32:13 lr: 3.115638315053687e-05 loss: 0.1284 (0.1349) time: 3.0414 data: 0.0079 max mem: 33300 +Epoch: [16] [1510/4276] eta: 2:31:35 lr: 3.1153610202395765e-05 loss: 0.1267 (0.1348) time: 3.0235 data: 0.0076 max mem: 33300 +Epoch: [16] [1520/4276] eta: 2:30:57 lr: 3.115083722683029e-05 loss: 0.1289 (0.1348) time: 3.0178 data: 0.0072 max mem: 33300 +Epoch: [16] [1530/4276] eta: 2:30:19 lr: 3.114806422383743e-05 loss: 0.1281 (0.1347) time: 3.0025 data: 0.0069 max mem: 33300 +Epoch: [16] [1540/4276] eta: 2:29:41 lr: 3.114529119341423e-05 loss: 0.1171 (0.1347) time: 3.0144 data: 0.0069 max mem: 33300 +Epoch: [16] [1550/4276] eta: 2:29:04 lr: 3.114251813555768e-05 loss: 0.1258 (0.1347) time: 3.0198 data: 0.0073 max mem: 33300 +Epoch: [16] [1560/4276] eta: 2:28:26 lr: 3.113974505026481e-05 loss: 0.1258 (0.1346) time: 3.0152 data: 0.0074 max mem: 33300 +Epoch: [16] [1570/4276] eta: 2:27:49 lr: 3.113697193753263e-05 loss: 0.1332 (0.1347) time: 3.0203 data: 0.0070 max mem: 33300 +Epoch: [16] [1580/4276] eta: 2:27:13 lr: 3.113419879735816e-05 loss: 0.1173 (0.1346) time: 3.0395 data: 0.0072 max mem: 33300 +Epoch: [16] [1590/4276] eta: 2:26:37 lr: 3.1131425629738395e-05 loss: 0.1200 (0.1346) time: 3.0681 data: 0.0072 max mem: 33300 +Epoch: [16] [1600/4276] eta: 2:26:00 lr: 3.112865243467036e-05 loss: 0.1280 (0.1346) time: 3.0643 data: 0.0072 max mem: 33300 +Epoch: [16] [1610/4276] eta: 2:25:24 lr: 3.112587921215107e-05 loss: 0.1195 (0.1345) time: 3.0492 data: 0.0070 max mem: 33300 +Epoch: [16] [1620/4276] eta: 2:24:47 lr: 3.112310596217752e-05 loss: 0.1171 (0.1344) time: 3.0395 data: 0.0070 max mem: 33300 +Epoch: [16] [1630/4276] eta: 2:24:10 lr: 3.1120332684746735e-05 loss: 0.1283 (0.1345) time: 3.0226 data: 0.0074 max mem: 33300 +Epoch: [16] [1640/4276] eta: 2:23:33 lr: 3.1117559379855716e-05 loss: 0.1248 (0.1343) time: 3.0189 data: 0.0073 max mem: 33300 +Epoch: [16] [1650/4276] eta: 2:22:56 lr: 3.111478604750147e-05 loss: 0.1092 (0.1342) time: 3.0084 data: 0.0074 max mem: 33300 +Epoch: [16] [1660/4276] eta: 2:22:20 lr: 3.111201268768102e-05 loss: 0.1169 (0.1342) time: 3.0072 data: 0.0073 max mem: 33300 +Epoch: [16] [1670/4276] eta: 2:21:44 lr: 3.1109239300391355e-05 loss: 0.1211 (0.1341) time: 3.0324 data: 0.0070 max mem: 33300 +Epoch: [16] [1680/4276] eta: 2:21:07 lr: 3.1106465885629496e-05 loss: 0.1337 (0.1342) time: 3.0300 data: 0.0067 max mem: 33300 +Epoch: [16] [1690/4276] eta: 2:20:31 lr: 3.110369244339244e-05 loss: 0.1223 (0.1342) time: 3.0260 data: 0.0067 max mem: 33300 +Epoch: [16] [1700/4276] eta: 2:19:56 lr: 3.110091897367719e-05 loss: 0.1210 (0.1342) time: 3.0445 data: 0.0070 max mem: 33300 +Epoch: [16] [1710/4276] eta: 2:19:19 lr: 3.1098145476480755e-05 loss: 0.1300 (0.1342) time: 3.0364 data: 0.0069 max mem: 33300 +Epoch: [16] [1720/4276] eta: 2:18:42 lr: 3.109537195180015e-05 loss: 0.1300 (0.1342) time: 2.9957 data: 0.0069 max mem: 33300 +Epoch: [16] [1730/4276] eta: 2:18:06 lr: 3.109259839963237e-05 loss: 0.1367 (0.1342) time: 2.9832 data: 0.0071 max mem: 33300 +Epoch: [16] [1740/4276] eta: 2:17:30 lr: 3.108982481997441e-05 loss: 0.1367 (0.1342) time: 2.9917 data: 0.0072 max mem: 33300 +Epoch: [16] [1750/4276] eta: 2:16:55 lr: 3.1087051212823284e-05 loss: 0.1290 (0.1341) time: 3.0331 data: 0.0075 max mem: 33300 +Epoch: [16] [1760/4276] eta: 2:16:20 lr: 3.1084277578176e-05 loss: 0.1128 (0.1340) time: 3.0842 data: 0.0074 max mem: 33300 +Epoch: [16] [1770/4276] eta: 2:15:45 lr: 3.108150391602954e-05 loss: 0.1134 (0.1340) time: 3.0808 data: 0.0071 max mem: 33300 +Epoch: [16] [1780/4276] eta: 2:15:09 lr: 3.107873022638091e-05 loss: 0.1186 (0.1339) time: 3.0517 data: 0.0067 max mem: 33300 +Epoch: [16] [1790/4276] eta: 2:14:33 lr: 3.107595650922712e-05 loss: 0.1186 (0.1339) time: 3.0160 data: 0.0067 max mem: 33300 +Epoch: [16] [1800/4276] eta: 2:13:57 lr: 3.1073182764565166e-05 loss: 0.1188 (0.1339) time: 3.0045 data: 0.0074 max mem: 33300 +Epoch: [16] [1810/4276] eta: 2:13:22 lr: 3.107040899239205e-05 loss: 0.1301 (0.1340) time: 3.0178 data: 0.0075 max mem: 33300 +Epoch: [16] [1820/4276] eta: 2:12:47 lr: 3.1067635192704755e-05 loss: 0.1301 (0.1339) time: 3.0248 data: 0.0070 max mem: 33300 +Epoch: [16] [1830/4276] eta: 2:12:11 lr: 3.1064861365500295e-05 loss: 0.1223 (0.1338) time: 3.0351 data: 0.0071 max mem: 33300 +Epoch: [16] [1840/4276] eta: 2:11:37 lr: 3.106208751077565e-05 loss: 0.1179 (0.1337) time: 3.0663 data: 0.0076 max mem: 33300 +Epoch: [16] [1850/4276] eta: 2:11:02 lr: 3.105931362852784e-05 loss: 0.1252 (0.1338) time: 3.0644 data: 0.0075 max mem: 33300 +Epoch: [16] [1860/4276] eta: 2:10:26 lr: 3.105653971875384e-05 loss: 0.1327 (0.1337) time: 3.0207 data: 0.0072 max mem: 33300 +Epoch: [16] [1870/4276] eta: 2:09:51 lr: 3.105376578145065e-05 loss: 0.1333 (0.1338) time: 3.0138 data: 0.0073 max mem: 33300 +Epoch: [16] [1880/4276] eta: 2:09:16 lr: 3.105099181661527e-05 loss: 0.1306 (0.1338) time: 3.0241 data: 0.0074 max mem: 33300 +Epoch: [16] [1890/4276] eta: 2:08:41 lr: 3.104821782424469e-05 loss: 0.1175 (0.1338) time: 3.0102 data: 0.0074 max mem: 33300 +Epoch: [16] [1900/4276] eta: 2:08:05 lr: 3.1045443804335904e-05 loss: 0.1178 (0.1338) time: 2.9988 data: 0.0073 max mem: 33300 +Epoch: [16] [1910/4276] eta: 2:07:30 lr: 3.104266975688591e-05 loss: 0.1274 (0.1338) time: 2.9927 data: 0.0072 max mem: 33300 +Epoch: [16] [1920/4276] eta: 2:06:55 lr: 3.1039895681891684e-05 loss: 0.1253 (0.1337) time: 3.0129 data: 0.0074 max mem: 33300 +Epoch: [16] [1930/4276] eta: 2:06:21 lr: 3.103712157935023e-05 loss: 0.1193 (0.1336) time: 3.0525 data: 0.0073 max mem: 33300 +Epoch: [16] [1940/4276] eta: 2:05:46 lr: 3.103434744925854e-05 loss: 0.1236 (0.1336) time: 3.0464 data: 0.0069 max mem: 33300 +Epoch: [16] [1950/4276] eta: 2:05:12 lr: 3.103157329161359e-05 loss: 0.1258 (0.1337) time: 3.0567 data: 0.0069 max mem: 33300 +Epoch: [16] [1960/4276] eta: 2:04:38 lr: 3.1028799106412384e-05 loss: 0.1274 (0.1337) time: 3.0758 data: 0.0072 max mem: 33300 +Epoch: [16] [1970/4276] eta: 2:04:03 lr: 3.1026024893651916e-05 loss: 0.1146 (0.1335) time: 3.0354 data: 0.0069 max mem: 33300 +Epoch: [16] [1980/4276] eta: 2:03:28 lr: 3.102325065332916e-05 loss: 0.1071 (0.1335) time: 2.9879 data: 0.0064 max mem: 33300 +Epoch: [16] [1990/4276] eta: 2:02:53 lr: 3.10204763854411e-05 loss: 0.1237 (0.1335) time: 2.9790 data: 0.0064 max mem: 33300 +Epoch: [16] [2000/4276] eta: 2:02:18 lr: 3.101770208998474e-05 loss: 0.1340 (0.1335) time: 2.9987 data: 0.0066 max mem: 33300 +Epoch: [16] [2010/4276] eta: 2:01:44 lr: 3.1014927766957055e-05 loss: 0.1340 (0.1334) time: 3.0325 data: 0.0069 max mem: 33300 +Epoch: [16] [2020/4276] eta: 2:01:09 lr: 3.101215341635502e-05 loss: 0.1259 (0.1335) time: 3.0323 data: 0.0071 max mem: 33300 +Epoch: [16] [2030/4276] eta: 2:00:34 lr: 3.1009379038175644e-05 loss: 0.1227 (0.1334) time: 2.9955 data: 0.0073 max mem: 33300 +Epoch: [16] [2040/4276] eta: 1:59:59 lr: 3.10066046324159e-05 loss: 0.1121 (0.1333) time: 2.9826 data: 0.0071 max mem: 33300 +Epoch: [16] [2050/4276] eta: 1:59:25 lr: 3.100383019907277e-05 loss: 0.1259 (0.1334) time: 2.9831 data: 0.0069 max mem: 33300 +Epoch: [16] [2060/4276] eta: 1:58:51 lr: 3.100105573814324e-05 loss: 0.1236 (0.1334) time: 3.0258 data: 0.0067 max mem: 33300 +Epoch: [16] [2070/4276] eta: 1:58:16 lr: 3.099828124962429e-05 loss: 0.1188 (0.1333) time: 3.0243 data: 0.0068 max mem: 33300 +Epoch: [16] [2080/4276] eta: 1:57:42 lr: 3.09955067335129e-05 loss: 0.1287 (0.1334) time: 2.9855 data: 0.0071 max mem: 33300 +Epoch: [16] [2090/4276] eta: 1:57:07 lr: 3.0992732189806056e-05 loss: 0.1326 (0.1333) time: 3.0058 data: 0.0071 max mem: 33300 +Epoch: [16] [2100/4276] eta: 1:56:33 lr: 3.0989957618500736e-05 loss: 0.1251 (0.1333) time: 3.0219 data: 0.0070 max mem: 33300 +Epoch: [16] [2110/4276] eta: 1:55:59 lr: 3.0987183019593926e-05 loss: 0.1251 (0.1333) time: 3.0357 data: 0.0073 max mem: 33300 +Epoch: [16] [2120/4276] eta: 1:55:25 lr: 3.0984408393082596e-05 loss: 0.1089 (0.1331) time: 3.0397 data: 0.0075 max mem: 33300 +Epoch: [16] [2130/4276] eta: 1:54:51 lr: 3.0981633738963725e-05 loss: 0.1078 (0.1330) time: 3.0078 data: 0.0070 max mem: 33300 +Epoch: [16] [2140/4276] eta: 1:54:17 lr: 3.0978859057234305e-05 loss: 0.1115 (0.1330) time: 2.9847 data: 0.0065 max mem: 33300 +Epoch: [16] [2150/4276] eta: 1:53:42 lr: 3.097608434789129e-05 loss: 0.1115 (0.1329) time: 2.9881 data: 0.0066 max mem: 33300 +Epoch: [16] [2160/4276] eta: 1:53:08 lr: 3.0973309610931676e-05 loss: 0.1081 (0.1329) time: 2.9794 data: 0.0069 max mem: 33300 +Epoch: [16] [2170/4276] eta: 1:52:34 lr: 3.097053484635243e-05 loss: 0.1216 (0.1329) time: 2.9775 data: 0.0070 max mem: 33300 +Epoch: [16] [2180/4276] eta: 1:52:00 lr: 3.096776005415054e-05 loss: 0.1251 (0.1328) time: 3.0215 data: 0.0070 max mem: 33300 +Epoch: [16] [2190/4276] eta: 1:51:27 lr: 3.096498523432296e-05 loss: 0.1250 (0.1328) time: 3.0701 data: 0.0069 max mem: 33300 +Epoch: [16] [2200/4276] eta: 1:50:53 lr: 3.0962210386866693e-05 loss: 0.1250 (0.1328) time: 3.0467 data: 0.0070 max mem: 33300 +Epoch: [16] [2210/4276] eta: 1:50:19 lr: 3.095943551177868e-05 loss: 0.1342 (0.1329) time: 3.0198 data: 0.0072 max mem: 33300 +Epoch: [16] [2220/4276] eta: 1:49:45 lr: 3.0956660609055915e-05 loss: 0.1365 (0.1329) time: 3.0142 data: 0.0076 max mem: 33300 +Epoch: [16] [2230/4276] eta: 1:49:11 lr: 3.095388567869537e-05 loss: 0.1331 (0.1329) time: 2.9982 data: 0.0074 max mem: 33300 +Epoch: [16] [2240/4276] eta: 1:48:38 lr: 3.0951110720694e-05 loss: 0.1226 (0.1329) time: 3.0051 data: 0.0069 max mem: 33300 +Epoch: [16] [2250/4276] eta: 1:48:04 lr: 3.094833573504879e-05 loss: 0.1226 (0.1328) time: 3.0242 data: 0.0068 max mem: 33300 +Epoch: [16] [2260/4276] eta: 1:47:30 lr: 3.094556072175671e-05 loss: 0.1326 (0.1328) time: 3.0109 data: 0.0066 max mem: 33300 +Epoch: [16] [2270/4276] eta: 1:46:57 lr: 3.094278568081473e-05 loss: 0.1251 (0.1328) time: 3.0180 data: 0.0067 max mem: 33300 +Epoch: [16] [2280/4276] eta: 1:46:23 lr: 3.0940010612219815e-05 loss: 0.1237 (0.1329) time: 3.0352 data: 0.0070 max mem: 33300 +Epoch: [16] [2290/4276] eta: 1:45:50 lr: 3.0937235515968936e-05 loss: 0.1237 (0.1328) time: 3.0350 data: 0.0070 max mem: 33300 +Epoch: [16] [2300/4276] eta: 1:45:16 lr: 3.093446039205907e-05 loss: 0.1253 (0.1328) time: 3.0037 data: 0.0071 max mem: 33300 +Epoch: [16] [2310/4276] eta: 1:44:42 lr: 3.093168524048716e-05 loss: 0.1315 (0.1329) time: 2.9752 data: 0.0072 max mem: 33300 +Epoch: [16] [2320/4276] eta: 1:44:09 lr: 3.0928910061250194e-05 loss: 0.1386 (0.1329) time: 2.9817 data: 0.0069 max mem: 33300 +Epoch: [16] [2330/4276] eta: 1:43:35 lr: 3.092613485434513e-05 loss: 0.1312 (0.1329) time: 2.9830 data: 0.0067 max mem: 33300 +Epoch: [16] [2340/4276] eta: 1:43:01 lr: 3.092335961976893e-05 loss: 0.1319 (0.1329) time: 2.9921 data: 0.0067 max mem: 33300 +Epoch: [16] [2350/4276] eta: 1:42:28 lr: 3.092058435751857e-05 loss: 0.1312 (0.1329) time: 2.9920 data: 0.0068 max mem: 33300 +Epoch: [16] [2360/4276] eta: 1:41:55 lr: 3.0917809067591015e-05 loss: 0.1179 (0.1329) time: 3.0108 data: 0.0069 max mem: 33300 +Epoch: [16] [2370/4276] eta: 1:41:21 lr: 3.0915033749983214e-05 loss: 0.1269 (0.1330) time: 3.0128 data: 0.0070 max mem: 33300 +Epoch: [16] [2380/4276] eta: 1:40:47 lr: 3.091225840469214e-05 loss: 0.1389 (0.1330) time: 2.9890 data: 0.0071 max mem: 33300 +Epoch: [16] [2390/4276] eta: 1:40:14 lr: 3.090948303171475e-05 loss: 0.1249 (0.1330) time: 2.9656 data: 0.0072 max mem: 33300 +Epoch: [16] [2400/4276] eta: 1:39:40 lr: 3.0906707631048e-05 loss: 0.1303 (0.1330) time: 2.9529 data: 0.0070 max mem: 33300 +Epoch: [16] [2410/4276] eta: 1:39:07 lr: 3.090393220268887e-05 loss: 0.1276 (0.1330) time: 2.9934 data: 0.0069 max mem: 33300 +Epoch: [16] [2420/4276] eta: 1:38:33 lr: 3.09011567466343e-05 loss: 0.1229 (0.1330) time: 3.0060 data: 0.0070 max mem: 33300 +Epoch: [16] [2430/4276] eta: 1:38:00 lr: 3.089838126288127e-05 loss: 0.1351 (0.1331) time: 2.9879 data: 0.0070 max mem: 33300 +Epoch: [16] [2440/4276] eta: 1:37:27 lr: 3.089560575142672e-05 loss: 0.1320 (0.1331) time: 3.0062 data: 0.0069 max mem: 33300 +Epoch: [16] [2450/4276] eta: 1:36:54 lr: 3.089283021226762e-05 loss: 0.1300 (0.1331) time: 3.0243 data: 0.0074 max mem: 33300 +Epoch: [16] [2460/4276] eta: 1:36:21 lr: 3.089005464540092e-05 loss: 0.1420 (0.1331) time: 3.0362 data: 0.0077 max mem: 33300 +Epoch: [16] [2470/4276] eta: 1:35:48 lr: 3.0887279050823584e-05 loss: 0.1291 (0.1332) time: 3.0251 data: 0.0076 max mem: 33300 +Epoch: [16] [2480/4276] eta: 1:35:15 lr: 3.088450342853256e-05 loss: 0.1483 (0.1333) time: 3.0000 data: 0.0074 max mem: 33300 +Epoch: [16] [2490/4276] eta: 1:34:42 lr: 3.0881727778524814e-05 loss: 0.1510 (0.1333) time: 2.9913 data: 0.0070 max mem: 33300 +Epoch: [16] [2500/4276] eta: 1:34:08 lr: 3.0878952100797296e-05 loss: 0.1385 (0.1334) time: 2.9922 data: 0.0069 max mem: 33300 +Epoch: [16] [2510/4276] eta: 1:33:35 lr: 3.0876176395346965e-05 loss: 0.1414 (0.1334) time: 3.0004 data: 0.0070 max mem: 33300 +Epoch: [16] [2520/4276] eta: 1:33:02 lr: 3.087340066217077e-05 loss: 0.1235 (0.1333) time: 3.0019 data: 0.0076 max mem: 33300 +Epoch: [16] [2530/4276] eta: 1:32:30 lr: 3.087062490126566e-05 loss: 0.1089 (0.1332) time: 3.0207 data: 0.0079 max mem: 33300 +Epoch: [16] [2540/4276] eta: 1:31:57 lr: 3.08678491126286e-05 loss: 0.1196 (0.1333) time: 3.0287 data: 0.0076 max mem: 33300 +Epoch: [16] [2550/4276] eta: 1:31:24 lr: 3.086507329625653e-05 loss: 0.1215 (0.1332) time: 3.0028 data: 0.0072 max mem: 33300 +Epoch: [16] [2560/4276] eta: 1:30:51 lr: 3.0862297452146414e-05 loss: 0.1044 (0.1331) time: 2.9890 data: 0.0074 max mem: 33300 +Epoch: [16] [2570/4276] eta: 1:30:18 lr: 3.085952158029518e-05 loss: 0.1105 (0.1331) time: 2.9907 data: 0.0075 max mem: 33300 +Epoch: [16] [2580/4276] eta: 1:29:45 lr: 3.08567456806998e-05 loss: 0.1168 (0.1330) time: 2.9938 data: 0.0069 max mem: 33300 +Epoch: [16] [2590/4276] eta: 1:29:12 lr: 3.0853969753357224e-05 loss: 0.1210 (0.1330) time: 2.9870 data: 0.0067 max mem: 33300 +Epoch: [16] [2600/4276] eta: 1:28:39 lr: 3.085119379826439e-05 loss: 0.1263 (0.1329) time: 2.9818 data: 0.0069 max mem: 33300 +Epoch: [16] [2610/4276] eta: 1:28:06 lr: 3.084841781541824e-05 loss: 0.1196 (0.1329) time: 2.9876 data: 0.0070 max mem: 33300 +Epoch: [16] [2620/4276] eta: 1:27:33 lr: 3.084564180481574e-05 loss: 0.1249 (0.1329) time: 3.0123 data: 0.0070 max mem: 33300 +Epoch: [16] [2630/4276] eta: 1:27:00 lr: 3.084286576645383e-05 loss: 0.1249 (0.1329) time: 3.0219 data: 0.0073 max mem: 33300 +Epoch: [16] [2640/4276] eta: 1:26:27 lr: 3.084008970032945e-05 loss: 0.1140 (0.1329) time: 2.9890 data: 0.0073 max mem: 33300 +Epoch: [16] [2650/4276] eta: 1:25:54 lr: 3.0837313606439547e-05 loss: 0.1206 (0.1328) time: 2.9692 data: 0.0073 max mem: 33300 +Epoch: [16] [2660/4276] eta: 1:25:22 lr: 3.0834537484781064e-05 loss: 0.1270 (0.1329) time: 2.9856 data: 0.0076 max mem: 33300 +Epoch: [16] [2670/4276] eta: 1:24:49 lr: 3.083176133535097e-05 loss: 0.1321 (0.1328) time: 2.9894 data: 0.0072 max mem: 33300 +Epoch: [16] [2680/4276] eta: 1:24:16 lr: 3.082898515814617e-05 loss: 0.1321 (0.1329) time: 2.9846 data: 0.0068 max mem: 33300 +Epoch: [16] [2690/4276] eta: 1:23:43 lr: 3.0826208953163636e-05 loss: 0.1321 (0.1328) time: 2.9810 data: 0.0068 max mem: 33300 +Epoch: [16] [2700/4276] eta: 1:23:11 lr: 3.0823432720400296e-05 loss: 0.1187 (0.1328) time: 2.9994 data: 0.0071 max mem: 33300 +Epoch: [16] [2710/4276] eta: 1:22:39 lr: 3.08206564598531e-05 loss: 0.1194 (0.1328) time: 3.0575 data: 0.0074 max mem: 33300 +Epoch: [16] [2720/4276] eta: 1:22:06 lr: 3.0817880171518975e-05 loss: 0.1120 (0.1327) time: 3.0546 data: 0.0074 max mem: 33300 +Epoch: [16] [2730/4276] eta: 1:21:33 lr: 3.081510385539488e-05 loss: 0.1242 (0.1328) time: 3.0012 data: 0.0074 max mem: 33300 +Epoch: [16] [2740/4276] eta: 1:21:01 lr: 3.0812327511477745e-05 loss: 0.1389 (0.1328) time: 3.0040 data: 0.0075 max mem: 33300 +Epoch: [16] [2750/4276] eta: 1:20:29 lr: 3.0809551139764505e-05 loss: 0.1407 (0.1329) time: 3.0209 data: 0.0077 max mem: 33300 +Epoch: [16] [2760/4276] eta: 1:19:56 lr: 3.080677474025211e-05 loss: 0.1327 (0.1328) time: 2.9896 data: 0.0074 max mem: 33300 +Epoch: [16] [2770/4276] eta: 1:19:23 lr: 3.0803998312937494e-05 loss: 0.1220 (0.1328) time: 2.9684 data: 0.0072 max mem: 33300 +Epoch: [16] [2780/4276] eta: 1:18:50 lr: 3.080122185781758e-05 loss: 0.1220 (0.1328) time: 2.9748 data: 0.0072 max mem: 33300 +Epoch: [16] [2790/4276] eta: 1:18:18 lr: 3.0798445374889325e-05 loss: 0.1290 (0.1329) time: 2.9746 data: 0.0070 max mem: 33300 +Epoch: [16] [2800/4276] eta: 1:17:45 lr: 3.079566886414966e-05 loss: 0.1305 (0.1328) time: 2.9875 data: 0.0072 max mem: 33300 +Epoch: [16] [2810/4276] eta: 1:17:13 lr: 3.079289232559551e-05 loss: 0.1095 (0.1327) time: 3.0138 data: 0.0073 max mem: 33300 +Epoch: [16] [2820/4276] eta: 1:16:40 lr: 3.079011575922382e-05 loss: 0.1045 (0.1326) time: 2.9929 data: 0.0072 max mem: 33300 +Epoch: [16] [2830/4276] eta: 1:16:08 lr: 3.078733916503152e-05 loss: 0.1152 (0.1326) time: 2.9664 data: 0.0077 max mem: 33300 +Epoch: [16] [2840/4276] eta: 1:15:35 lr: 3.078456254301554e-05 loss: 0.1347 (0.1327) time: 2.9617 data: 0.0079 max mem: 33300 +Epoch: [16] [2850/4276] eta: 1:15:03 lr: 3.078178589317282e-05 loss: 0.1444 (0.1328) time: 2.9538 data: 0.0078 max mem: 33300 +Epoch: [16] [2860/4276] eta: 1:14:30 lr: 3.0779009215500295e-05 loss: 0.1392 (0.1328) time: 2.9691 data: 0.0077 max mem: 33300 +Epoch: [16] [2870/4276] eta: 1:13:58 lr: 3.077623250999488e-05 loss: 0.1307 (0.1328) time: 2.9931 data: 0.0077 max mem: 33300 +Epoch: [16] [2880/4276] eta: 1:13:26 lr: 3.077345577665352e-05 loss: 0.1335 (0.1328) time: 3.0127 data: 0.0075 max mem: 33300 +Epoch: [16] [2890/4276] eta: 1:12:53 lr: 3.077067901547313e-05 loss: 0.1280 (0.1328) time: 3.0254 data: 0.0074 max mem: 33300 +Epoch: [16] [2900/4276] eta: 1:12:21 lr: 3.076790222645067e-05 loss: 0.1228 (0.1327) time: 3.0223 data: 0.0073 max mem: 33300 +Epoch: [16] [2910/4276] eta: 1:11:49 lr: 3.076512540958304e-05 loss: 0.1214 (0.1327) time: 3.0171 data: 0.0075 max mem: 33300 +Epoch: [16] [2920/4276] eta: 1:11:17 lr: 3.0762348564867184e-05 loss: 0.1266 (0.1328) time: 3.0234 data: 0.0075 max mem: 33300 +Epoch: [16] [2930/4276] eta: 1:10:45 lr: 3.0759571692300014e-05 loss: 0.1228 (0.1327) time: 3.0131 data: 0.0071 max mem: 33300 +Epoch: [16] [2940/4276] eta: 1:10:12 lr: 3.0756794791878465e-05 loss: 0.1039 (0.1327) time: 2.9996 data: 0.0072 max mem: 33300 +Epoch: [16] [2950/4276] eta: 1:09:40 lr: 3.075401786359947e-05 loss: 0.1128 (0.1326) time: 2.9956 data: 0.0072 max mem: 33300 +Epoch: [16] [2960/4276] eta: 1:09:08 lr: 3.0751240907459946e-05 loss: 0.1152 (0.1326) time: 2.9969 data: 0.0072 max mem: 33300 +Epoch: [16] [2970/4276] eta: 1:08:36 lr: 3.0748463923456824e-05 loss: 0.1206 (0.1326) time: 3.0081 data: 0.0071 max mem: 33300 +Epoch: [16] [2980/4276] eta: 1:08:04 lr: 3.074568691158703e-05 loss: 0.1276 (0.1326) time: 3.0196 data: 0.0071 max mem: 33300 +Epoch: [16] [2990/4276] eta: 1:07:32 lr: 3.074290987184747e-05 loss: 0.1275 (0.1326) time: 3.0162 data: 0.0074 max mem: 33300 +Epoch: [16] [3000/4276] eta: 1:06:59 lr: 3.074013280423509e-05 loss: 0.1126 (0.1325) time: 2.9772 data: 0.0073 max mem: 33300 +Epoch: [16] [3010/4276] eta: 1:06:27 lr: 3.07373557087468e-05 loss: 0.1155 (0.1325) time: 2.9513 data: 0.0072 max mem: 33300 +Epoch: [16] [3020/4276] eta: 1:05:55 lr: 3.0734578585379525e-05 loss: 0.1268 (0.1325) time: 2.9588 data: 0.0074 max mem: 33300 +Epoch: [16] [3030/4276] eta: 1:05:22 lr: 3.073180143413018e-05 loss: 0.1268 (0.1325) time: 2.9542 data: 0.0071 max mem: 33300 +Epoch: [16] [3040/4276] eta: 1:04:50 lr: 3.072902425499569e-05 loss: 0.1324 (0.1325) time: 2.9760 data: 0.0073 max mem: 33300 +Epoch: [16] [3050/4276] eta: 1:04:18 lr: 3.072624704797299e-05 loss: 0.1203 (0.1325) time: 3.0013 data: 0.0074 max mem: 33300 +Epoch: [16] [3060/4276] eta: 1:03:46 lr: 3.072346981305897e-05 loss: 0.1079 (0.1324) time: 2.9908 data: 0.0071 max mem: 33300 +Epoch: [16] [3070/4276] eta: 1:03:14 lr: 3.072069255025057e-05 loss: 0.1191 (0.1324) time: 2.9823 data: 0.0074 max mem: 33300 +Epoch: [16] [3080/4276] eta: 1:02:42 lr: 3.071791525954469e-05 loss: 0.1191 (0.1324) time: 3.0032 data: 0.0074 max mem: 33300 +Epoch: [16] [3090/4276] eta: 1:02:10 lr: 3.071513794093827e-05 loss: 0.1190 (0.1323) time: 3.0014 data: 0.0074 max mem: 33300 +Epoch: [16] [3100/4276] eta: 1:01:38 lr: 3.0712360594428205e-05 loss: 0.1108 (0.1323) time: 2.9870 data: 0.0074 max mem: 33300 +Epoch: [16] [3110/4276] eta: 1:01:06 lr: 3.070958322001142e-05 loss: 0.1108 (0.1322) time: 2.9824 data: 0.0072 max mem: 33300 +Epoch: [16] [3120/4276] eta: 1:00:34 lr: 3.070680581768484e-05 loss: 0.1123 (0.1322) time: 2.9687 data: 0.0071 max mem: 33300 +Epoch: [16] [3130/4276] eta: 1:00:02 lr: 3.0704028387445365e-05 loss: 0.1177 (0.1322) time: 2.9615 data: 0.0070 max mem: 33300 +Epoch: [16] [3140/4276] eta: 0:59:29 lr: 3.0701250929289916e-05 loss: 0.1312 (0.1322) time: 2.9594 data: 0.0073 max mem: 33300 +Epoch: [16] [3150/4276] eta: 0:58:58 lr: 3.06984734432154e-05 loss: 0.1330 (0.1322) time: 2.9826 data: 0.0077 max mem: 33300 +Epoch: [16] [3160/4276] eta: 0:58:26 lr: 3.0695695929218736e-05 loss: 0.1286 (0.1322) time: 2.9893 data: 0.0074 max mem: 33300 +Epoch: [16] [3170/4276] eta: 0:57:54 lr: 3.069291838729684e-05 loss: 0.1293 (0.1322) time: 2.9783 data: 0.0074 max mem: 33300 +Epoch: [16] [3180/4276] eta: 0:57:22 lr: 3.0690140817446604e-05 loss: 0.1232 (0.1321) time: 2.9782 data: 0.0074 max mem: 33300 +Epoch: [16] [3190/4276] eta: 0:56:50 lr: 3.068736321966496e-05 loss: 0.1232 (0.1321) time: 2.9706 data: 0.0071 max mem: 33300 +Epoch: [16] [3200/4276] eta: 0:56:18 lr: 3.0684585593948806e-05 loss: 0.1246 (0.1321) time: 2.9708 data: 0.0073 max mem: 33300 +Epoch: [16] [3210/4276] eta: 0:55:46 lr: 3.068180794029506e-05 loss: 0.1272 (0.1321) time: 2.9609 data: 0.0078 max mem: 33300 +Epoch: [16] [3220/4276] eta: 0:55:14 lr: 3.0679030258700624e-05 loss: 0.1400 (0.1321) time: 2.9523 data: 0.0075 max mem: 33300 +Epoch: [16] [3230/4276] eta: 0:54:42 lr: 3.067625254916241e-05 loss: 0.1304 (0.1321) time: 2.9613 data: 0.0075 max mem: 33300 +Epoch: [16] [3240/4276] eta: 0:54:10 lr: 3.0673474811677324e-05 loss: 0.1437 (0.1322) time: 2.9675 data: 0.0076 max mem: 33300 +Epoch: [16] [3250/4276] eta: 0:53:38 lr: 3.067069704624226e-05 loss: 0.1377 (0.1322) time: 2.9936 data: 0.0072 max mem: 33300 +Epoch: [16] [3260/4276] eta: 0:53:06 lr: 3.066791925285415e-05 loss: 0.1306 (0.1322) time: 3.0099 data: 0.0070 max mem: 33300 +Epoch: [16] [3270/4276] eta: 0:52:34 lr: 3.0665141431509874e-05 loss: 0.1234 (0.1322) time: 3.0044 data: 0.0070 max mem: 33300 +Epoch: [16] [3280/4276] eta: 0:52:03 lr: 3.066236358220635e-05 loss: 0.1293 (0.1322) time: 2.9833 data: 0.0070 max mem: 33300 +Epoch: [16] [3290/4276] eta: 0:51:31 lr: 3.06595857049405e-05 loss: 0.1315 (0.1323) time: 2.9804 data: 0.0072 max mem: 33300 +Epoch: [16] [3300/4276] eta: 0:50:59 lr: 3.065680779970919e-05 loss: 0.1323 (0.1323) time: 2.9890 data: 0.0072 max mem: 33300 +Epoch: [16] [3310/4276] eta: 0:50:27 lr: 3.0654029866509346e-05 loss: 0.1360 (0.1323) time: 2.9659 data: 0.0069 max mem: 33300 +Epoch: [16] [3320/4276] eta: 0:49:55 lr: 3.0651251905337866e-05 loss: 0.1420 (0.1323) time: 2.9508 data: 0.0073 max mem: 33300 +Epoch: [16] [3330/4276] eta: 0:49:23 lr: 3.0648473916191645e-05 loss: 0.1255 (0.1323) time: 2.9675 data: 0.0081 max mem: 33300 +Epoch: [16] [3340/4276] eta: 0:48:52 lr: 3.064569589906759e-05 loss: 0.1138 (0.1323) time: 2.9744 data: 0.0077 max mem: 33300 +Epoch: [16] [3350/4276] eta: 0:48:20 lr: 3.06429178539626e-05 loss: 0.1171 (0.1322) time: 2.9722 data: 0.0073 max mem: 33300 +Epoch: [16] [3360/4276] eta: 0:47:48 lr: 3.064013978087358e-05 loss: 0.1171 (0.1322) time: 2.9843 data: 0.0076 max mem: 33300 +Epoch: [16] [3370/4276] eta: 0:47:16 lr: 3.0637361679797424e-05 loss: 0.1211 (0.1322) time: 2.9739 data: 0.0075 max mem: 33300 +Epoch: [16] [3380/4276] eta: 0:46:45 lr: 3.063458355073103e-05 loss: 0.1343 (0.1322) time: 2.9580 data: 0.0074 max mem: 33300 +Epoch: [16] [3390/4276] eta: 0:46:13 lr: 3.0631805393671296e-05 loss: 0.1299 (0.1322) time: 2.9707 data: 0.0079 max mem: 33300 +Epoch: [16] [3400/4276] eta: 0:45:41 lr: 3.0629027208615116e-05 loss: 0.1328 (0.1322) time: 2.9974 data: 0.0081 max mem: 33300 +Epoch: [16] [3410/4276] eta: 0:45:10 lr: 3.062624899555938e-05 loss: 0.1199 (0.1322) time: 2.9984 data: 0.0081 max mem: 33300 +Epoch: [16] [3420/4276] eta: 0:44:38 lr: 3.0623470754501e-05 loss: 0.1297 (0.1323) time: 2.9850 data: 0.0080 max mem: 33300 +Epoch: [16] [3430/4276] eta: 0:44:06 lr: 3.062069248543687e-05 loss: 0.1358 (0.1323) time: 3.0021 data: 0.0075 max mem: 33300 +Epoch: [16] [3440/4276] eta: 0:43:35 lr: 3.061791418836387e-05 loss: 0.1249 (0.1322) time: 3.0280 data: 0.0074 max mem: 33300 +Epoch: [16] [3450/4276] eta: 0:43:03 lr: 3.0615135863278904e-05 loss: 0.1320 (0.1323) time: 3.0216 data: 0.0068 max mem: 33300 +Epoch: [16] [3460/4276] eta: 0:42:32 lr: 3.061235751017887e-05 loss: 0.1495 (0.1323) time: 3.0405 data: 0.0062 max mem: 33300 +Epoch: [16] [3470/4276] eta: 0:42:01 lr: 3.0609579129060637e-05 loss: 0.1342 (0.1323) time: 3.0702 data: 0.0072 max mem: 33300 +Epoch: [16] [3480/4276] eta: 0:41:29 lr: 3.0606800719921125e-05 loss: 0.1348 (0.1323) time: 3.0623 data: 0.0077 max mem: 33300 +Epoch: [16] [3490/4276] eta: 0:40:58 lr: 3.06040222827572e-05 loss: 0.1348 (0.1324) time: 3.0618 data: 0.0073 max mem: 33300 +Epoch: [16] [3500/4276] eta: 0:40:26 lr: 3.060124381756578e-05 loss: 0.1288 (0.1323) time: 3.0703 data: 0.0080 max mem: 33300 +Epoch: [16] [3510/4276] eta: 0:39:55 lr: 3.059846532434373e-05 loss: 0.1170 (0.1323) time: 3.0706 data: 0.0083 max mem: 33300 +Epoch: [16] [3520/4276] eta: 0:39:24 lr: 3.0595686803087954e-05 loss: 0.1176 (0.1323) time: 3.0896 data: 0.0081 max mem: 33300 +Epoch: [16] [3530/4276] eta: 0:38:52 lr: 3.059290825379533e-05 loss: 0.1292 (0.1323) time: 3.1006 data: 0.0082 max mem: 33300 +Epoch: [16] [3540/4276] eta: 0:38:21 lr: 3.0590129676462754e-05 loss: 0.1269 (0.1323) time: 3.0798 data: 0.0077 max mem: 33300 +Epoch: [16] [3550/4276] eta: 0:37:49 lr: 3.05873510710871e-05 loss: 0.1282 (0.1323) time: 3.0630 data: 0.0073 max mem: 33300 +Epoch: [16] [3560/4276] eta: 0:37:18 lr: 3.058457243766527e-05 loss: 0.1326 (0.1323) time: 3.0558 data: 0.0074 max mem: 33300 +Epoch: [16] [3570/4276] eta: 0:36:47 lr: 3.0581793776194145e-05 loss: 0.1382 (0.1324) time: 3.0441 data: 0.0075 max mem: 33300 +Epoch: [16] [3580/4276] eta: 0:36:15 lr: 3.057901508667061e-05 loss: 0.1246 (0.1323) time: 3.0535 data: 0.0075 max mem: 33300 +Epoch: [16] [3590/4276] eta: 0:35:44 lr: 3.057623636909154e-05 loss: 0.1165 (0.1324) time: 3.0948 data: 0.0077 max mem: 33300 +Epoch: [16] [3600/4276] eta: 0:35:13 lr: 3.057345762345384e-05 loss: 0.1268 (0.1324) time: 3.1094 data: 0.0080 max mem: 33300 +Epoch: [16] [3610/4276] eta: 0:34:41 lr: 3.057067884975437e-05 loss: 0.1273 (0.1324) time: 3.1074 data: 0.0082 max mem: 33300 +Epoch: [16] [3620/4276] eta: 0:34:10 lr: 3.056790004799003e-05 loss: 0.1273 (0.1324) time: 3.1041 data: 0.0084 max mem: 33300 +Epoch: [16] [3630/4276] eta: 0:33:39 lr: 3.056512121815768e-05 loss: 0.1297 (0.1324) time: 3.0957 data: 0.0082 max mem: 33300 +Epoch: [16] [3640/4276] eta: 0:33:07 lr: 3.0562342360254224e-05 loss: 0.1196 (0.1324) time: 3.0900 data: 0.0078 max mem: 33300 +Epoch: [16] [3650/4276] eta: 0:32:36 lr: 3.055956347427654e-05 loss: 0.1089 (0.1323) time: 3.0716 data: 0.0077 max mem: 33300 +Epoch: [16] [3660/4276] eta: 0:32:05 lr: 3.0556784560221494e-05 loss: 0.1099 (0.1322) time: 3.0623 data: 0.0080 max mem: 33300 +Epoch: [16] [3670/4276] eta: 0:31:33 lr: 3.055400561808597e-05 loss: 0.1171 (0.1323) time: 3.0672 data: 0.0081 max mem: 33300 +Epoch: [16] [3680/4276] eta: 0:31:02 lr: 3.0551226647866856e-05 loss: 0.1256 (0.1323) time: 3.0622 data: 0.0077 max mem: 33300 +Epoch: [16] [3690/4276] eta: 0:30:31 lr: 3.054844764956102e-05 loss: 0.1278 (0.1323) time: 3.0597 data: 0.0075 max mem: 33300 +Epoch: [16] [3700/4276] eta: 0:29:59 lr: 3.054566862316534e-05 loss: 0.1260 (0.1323) time: 3.0733 data: 0.0076 max mem: 33300 +Epoch: [16] [3710/4276] eta: 0:29:28 lr: 3.054288956867669e-05 loss: 0.1206 (0.1322) time: 3.0707 data: 0.0078 max mem: 33300 +Epoch: [16] [3720/4276] eta: 0:28:57 lr: 3.054011048609196e-05 loss: 0.1193 (0.1322) time: 3.0472 data: 0.0077 max mem: 33300 +Epoch: [16] [3730/4276] eta: 0:28:25 lr: 3.0537331375408005e-05 loss: 0.1221 (0.1322) time: 3.0501 data: 0.0081 max mem: 33300 +Epoch: [16] [3740/4276] eta: 0:27:54 lr: 3.0534552236621716e-05 loss: 0.1251 (0.1322) time: 3.0534 data: 0.0082 max mem: 33300 +Epoch: [16] [3750/4276] eta: 0:27:23 lr: 3.0531773069729965e-05 loss: 0.1275 (0.1322) time: 3.0692 data: 0.0081 max mem: 33300 +Epoch: [16] [3760/4276] eta: 0:26:51 lr: 3.052899387472961e-05 loss: 0.1212 (0.1322) time: 3.0750 data: 0.0084 max mem: 33300 +Epoch: [16] [3770/4276] eta: 0:26:20 lr: 3.0526214651617545e-05 loss: 0.1213 (0.1322) time: 3.0626 data: 0.0079 max mem: 33300 +Epoch: [16] [3780/4276] eta: 0:25:49 lr: 3.0523435400390627e-05 loss: 0.1338 (0.1322) time: 3.0655 data: 0.0082 max mem: 33300 +Epoch: [16] [3790/4276] eta: 0:25:17 lr: 3.0520656121045725e-05 loss: 0.1246 (0.1322) time: 3.0644 data: 0.0086 max mem: 33300 +Epoch: [16] [3800/4276] eta: 0:24:46 lr: 3.051787681357972e-05 loss: 0.1292 (0.1322) time: 3.0776 data: 0.0078 max mem: 33300 +Epoch: [16] [3810/4276] eta: 0:24:15 lr: 3.0515097477989475e-05 loss: 0.1292 (0.1322) time: 3.0915 data: 0.0081 max mem: 33300 +Epoch: [16] [3820/4276] eta: 0:23:43 lr: 3.0512318114271865e-05 loss: 0.1071 (0.1321) time: 3.0701 data: 0.0079 max mem: 33300 +Epoch: [16] [3830/4276] eta: 0:23:12 lr: 3.050953872242376e-05 loss: 0.1097 (0.1322) time: 3.0697 data: 0.0074 max mem: 33300 +Epoch: [16] [3840/4276] eta: 0:22:41 lr: 3.0506759302442013e-05 loss: 0.1195 (0.1321) time: 3.0746 data: 0.0080 max mem: 33300 +Epoch: [16] [3850/4276] eta: 0:22:10 lr: 3.0503979854323506e-05 loss: 0.1063 (0.1321) time: 3.0234 data: 0.0083 max mem: 33300 +Epoch: [16] [3860/4276] eta: 0:21:38 lr: 3.0501200378065098e-05 loss: 0.1235 (0.1321) time: 2.9798 data: 0.0085 max mem: 33300 +Epoch: [16] [3870/4276] eta: 0:21:07 lr: 3.0498420873663657e-05 loss: 0.1282 (0.1320) time: 2.9846 data: 0.0080 max mem: 33300 +Epoch: [16] [3880/4276] eta: 0:20:36 lr: 3.049564134111605e-05 loss: 0.1186 (0.1320) time: 3.0245 data: 0.0074 max mem: 33300 +Epoch: [16] [3890/4276] eta: 0:20:04 lr: 3.049286178041914e-05 loss: 0.1186 (0.1320) time: 3.0240 data: 0.0074 max mem: 33300 +Epoch: [16] [3900/4276] eta: 0:19:33 lr: 3.049008219156979e-05 loss: 0.1197 (0.1320) time: 2.9896 data: 0.0071 max mem: 33300 +Epoch: [16] [3910/4276] eta: 0:19:02 lr: 3.0487302574564868e-05 loss: 0.1184 (0.1320) time: 2.9808 data: 0.0073 max mem: 33300 +Epoch: [16] [3920/4276] eta: 0:18:30 lr: 3.0484522929401226e-05 loss: 0.1117 (0.1320) time: 2.9789 data: 0.0082 max mem: 33300 +Epoch: [16] [3930/4276] eta: 0:17:59 lr: 3.048174325607574e-05 loss: 0.1131 (0.1319) time: 2.9793 data: 0.0078 max mem: 33300 +Epoch: [16] [3940/4276] eta: 0:17:28 lr: 3.047896355458526e-05 loss: 0.1225 (0.1319) time: 2.9976 data: 0.0073 max mem: 33300 +Epoch: [16] [3950/4276] eta: 0:16:56 lr: 3.0476183824926646e-05 loss: 0.1112 (0.1319) time: 2.9744 data: 0.0075 max mem: 33300 +Epoch: [16] [3960/4276] eta: 0:16:25 lr: 3.0473404067096766e-05 loss: 0.1144 (0.1319) time: 2.9431 data: 0.0079 max mem: 33300 +Epoch: [16] [3970/4276] eta: 0:15:54 lr: 3.047062428109247e-05 loss: 0.1241 (0.1319) time: 2.9681 data: 0.0083 max mem: 33300 +Epoch: [16] [3980/4276] eta: 0:15:22 lr: 3.046784446691063e-05 loss: 0.1265 (0.1319) time: 2.9883 data: 0.0080 max mem: 33300 +Epoch: [16] [3990/4276] eta: 0:14:51 lr: 3.046506462454809e-05 loss: 0.1265 (0.1319) time: 2.9756 data: 0.0074 max mem: 33300 +Epoch: [16] [4000/4276] eta: 0:14:20 lr: 3.0462284754001714e-05 loss: 0.1223 (0.1319) time: 3.0041 data: 0.0079 max mem: 33300 +Epoch: [16] [4010/4276] eta: 0:13:49 lr: 3.0459504855268357e-05 loss: 0.1237 (0.1319) time: 3.0187 data: 0.0081 max mem: 33300 +Epoch: [16] [4020/4276] eta: 0:13:17 lr: 3.045672492834487e-05 loss: 0.1273 (0.1319) time: 2.9957 data: 0.0070 max mem: 33300 +Epoch: [16] [4030/4276] eta: 0:12:46 lr: 3.0453944973228117e-05 loss: 0.1301 (0.1319) time: 3.0097 data: 0.0074 max mem: 33300 +Epoch: [16] [4040/4276] eta: 0:12:15 lr: 3.0451164989914943e-05 loss: 0.1309 (0.1319) time: 2.9996 data: 0.0078 max mem: 33300 +Epoch: [16] [4050/4276] eta: 0:11:44 lr: 3.0448384978402212e-05 loss: 0.1141 (0.1319) time: 3.0048 data: 0.0078 max mem: 33300 +Epoch: [16] [4060/4276] eta: 0:11:12 lr: 3.0445604938686774e-05 loss: 0.1178 (0.1319) time: 3.0407 data: 0.0083 max mem: 33300 +Epoch: [16] [4070/4276] eta: 0:10:41 lr: 3.0442824870765474e-05 loss: 0.1318 (0.1319) time: 3.0203 data: 0.0080 max mem: 33300 +Epoch: [16] [4080/4276] eta: 0:10:10 lr: 3.0440044774635178e-05 loss: 0.1318 (0.1320) time: 2.9858 data: 0.0077 max mem: 33300 +Epoch: [16] [4090/4276] eta: 0:09:39 lr: 3.043726465029272e-05 loss: 0.1367 (0.1320) time: 2.9893 data: 0.0079 max mem: 33300 +Epoch: [16] [4100/4276] eta: 0:09:08 lr: 3.0434484497734962e-05 loss: 0.1422 (0.1320) time: 3.0237 data: 0.0076 max mem: 33300 +Epoch: [16] [4110/4276] eta: 0:08:36 lr: 3.043170431695875e-05 loss: 0.1317 (0.1320) time: 3.0373 data: 0.0070 max mem: 33300 +Epoch: [16] [4120/4276] eta: 0:08:05 lr: 3.042892410796093e-05 loss: 0.1308 (0.1321) time: 2.9757 data: 0.0070 max mem: 33300 +Epoch: [16] [4130/4276] eta: 0:07:34 lr: 3.042614387073836e-05 loss: 0.1269 (0.1321) time: 2.9616 data: 0.0071 max mem: 33300 +Epoch: [16] [4140/4276] eta: 0:07:03 lr: 3.0423363605287887e-05 loss: 0.1358 (0.1321) time: 2.9829 data: 0.0073 max mem: 33300 +Epoch: [16] [4150/4276] eta: 0:06:32 lr: 3.0420583311606343e-05 loss: 0.1403 (0.1321) time: 2.9572 data: 0.0072 max mem: 33300 +Epoch: [16] [4160/4276] eta: 0:06:01 lr: 3.0417802989690593e-05 loss: 0.1327 (0.1322) time: 2.9603 data: 0.0072 max mem: 33300 +Epoch: [16] [4170/4276] eta: 0:05:29 lr: 3.0415022639537468e-05 loss: 0.1445 (0.1322) time: 2.9627 data: 0.0071 max mem: 33300 +Epoch: [16] [4180/4276] eta: 0:04:58 lr: 3.041224226114382e-05 loss: 0.1317 (0.1322) time: 2.9477 data: 0.0068 max mem: 33300 +Epoch: [16] [4190/4276] eta: 0:04:27 lr: 3.040946185450649e-05 loss: 0.1260 (0.1322) time: 2.9800 data: 0.0070 max mem: 33300 +Epoch: [16] [4200/4276] eta: 0:03:56 lr: 3.0406681419622324e-05 loss: 0.1380 (0.1322) time: 2.9770 data: 0.0071 max mem: 33300 +Epoch: [16] [4210/4276] eta: 0:03:25 lr: 3.040390095648817e-05 loss: 0.1394 (0.1322) time: 2.9473 data: 0.0074 max mem: 33300 +Epoch: [16] [4220/4276] eta: 0:02:54 lr: 3.040112046510087e-05 loss: 0.1394 (0.1323) time: 2.9809 data: 0.0081 max mem: 33300 +Epoch: [16] [4230/4276] eta: 0:02:23 lr: 3.0398339945457254e-05 loss: 0.1412 (0.1323) time: 2.9782 data: 0.0080 max mem: 33300 +Epoch: [16] [4240/4276] eta: 0:01:51 lr: 3.039555939755418e-05 loss: 0.1386 (0.1323) time: 2.9646 data: 0.0072 max mem: 33300 +Epoch: [16] [4250/4276] eta: 0:01:20 lr: 3.0392778821388467e-05 loss: 0.1390 (0.1324) time: 3.0096 data: 0.0072 max mem: 33300 +Epoch: [16] [4260/4276] eta: 0:00:49 lr: 3.0389998216956973e-05 loss: 0.1274 (0.1324) time: 3.0322 data: 0.0072 max mem: 33300 +Epoch: [16] [4270/4276] eta: 0:00:18 lr: 3.0387217584256526e-05 loss: 0.1350 (0.1324) time: 3.0068 data: 0.0071 max mem: 33300 +Epoch: [16] Total time: 3:41:34 +Test: [ 0/21770] eta: 11:00:42 time: 1.8210 data: 1.7333 max mem: 33300 +Test: [ 100/21770] eta: 0:20:01 time: 0.0378 data: 0.0010 max mem: 33300 +Test: [ 200/21770] eta: 0:16:47 time: 0.0376 data: 0.0008 max mem: 33300 +Test: [ 300/21770] eta: 0:15:40 time: 0.0385 data: 0.0010 max mem: 33300 +Test: [ 400/21770] eta: 0:15:06 time: 0.0386 data: 0.0010 max mem: 33300 +Test: [ 500/21770] eta: 0:14:43 time: 0.0380 data: 0.0010 max mem: 33300 +Test: [ 600/21770] eta: 0:14:26 time: 0.0379 data: 0.0010 max mem: 33300 +Test: [ 700/21770] eta: 0:14:13 time: 0.0383 data: 0.0011 max mem: 33300 +Test: [ 800/21770] eta: 0:14:02 time: 0.0379 data: 0.0008 max mem: 33300 +Test: [ 900/21770] eta: 0:13:52 time: 0.0377 data: 0.0009 max mem: 33300 +Test: [ 1000/21770] eta: 0:13:44 time: 0.0379 data: 0.0009 max mem: 33300 +Test: [ 1100/21770] eta: 0:13:37 time: 0.0379 data: 0.0009 max mem: 33300 +Test: [ 1200/21770] eta: 0:13:30 time: 0.0378 data: 0.0008 max mem: 33300 +Test: [ 1300/21770] eta: 0:13:24 time: 0.0379 data: 0.0009 max mem: 33300 +Test: [ 1400/21770] eta: 0:13:19 time: 0.0382 data: 0.0010 max mem: 33300 +Test: [ 1500/21770] eta: 0:13:13 time: 0.0379 data: 0.0010 max mem: 33300 +Test: [ 1600/21770] eta: 0:13:07 time: 0.0381 data: 0.0010 max mem: 33300 +Test: [ 1700/21770] eta: 0:13:02 time: 0.0378 data: 0.0009 max mem: 33300 +Test: [ 1800/21770] eta: 0:12:58 time: 0.0381 data: 0.0009 max mem: 33300 +Test: [ 1900/21770] eta: 0:12:53 time: 0.0379 data: 0.0009 max mem: 33300 +Test: [ 2000/21770] eta: 0:12:48 time: 0.0381 data: 0.0009 max mem: 33300 +Test: [ 2100/21770] eta: 0:12:44 time: 0.0381 data: 0.0009 max mem: 33300 +Test: [ 2200/21770] eta: 0:12:39 time: 0.0381 data: 0.0009 max mem: 33300 +Test: [ 2300/21770] eta: 0:12:35 time: 0.0380 data: 0.0009 max mem: 33300 +Test: [ 2400/21770] eta: 0:12:31 time: 0.0387 data: 0.0009 max mem: 33300 +Test: [ 2500/21770] eta: 0:12:27 time: 0.0392 data: 0.0009 max mem: 33300 +Test: [ 2600/21770] eta: 0:12:23 time: 0.0385 data: 0.0009 max mem: 33300 +Test: [ 2700/21770] eta: 0:12:19 time: 0.0386 data: 0.0009 max mem: 33300 +Test: [ 2800/21770] eta: 0:12:15 time: 0.0385 data: 0.0009 max mem: 33300 +Test: [ 2900/21770] eta: 0:12:11 time: 0.0389 data: 0.0009 max mem: 33300 +Test: [ 3000/21770] eta: 0:12:07 time: 0.0383 data: 0.0009 max mem: 33300 +Test: [ 3100/21770] eta: 0:12:03 time: 0.0383 data: 0.0009 max mem: 33300 +Test: [ 3200/21770] eta: 0:11:58 time: 0.0384 data: 0.0010 max mem: 33300 +Test: [ 3300/21770] eta: 0:11:55 time: 0.0386 data: 0.0009 max mem: 33300 +Test: [ 3400/21770] eta: 0:11:51 time: 0.0387 data: 0.0009 max mem: 33300 +Test: [ 3500/21770] eta: 0:11:47 time: 0.0389 data: 0.0009 max mem: 33300 +Test: [ 3600/21770] eta: 0:11:43 time: 0.0388 data: 0.0009 max mem: 33300 +Test: [ 3700/21770] eta: 0:11:39 time: 0.0387 data: 0.0009 max mem: 33300 +Test: [ 3800/21770] eta: 0:11:35 time: 0.0389 data: 0.0010 max mem: 33300 +Test: [ 3900/21770] eta: 0:11:31 time: 0.0390 data: 0.0009 max mem: 33300 +Test: [ 4000/21770] eta: 0:11:27 time: 0.0383 data: 0.0009 max mem: 33300 +Test: [ 4100/21770] eta: 0:11:23 time: 0.0384 data: 0.0009 max mem: 33300 +Test: [ 4200/21770] eta: 0:11:19 time: 0.0387 data: 0.0010 max mem: 33300 +Test: [ 4300/21770] eta: 0:11:15 time: 0.0380 data: 0.0008 max mem: 33300 +Test: [ 4400/21770] eta: 0:11:11 time: 0.0384 data: 0.0009 max mem: 33300 +Test: [ 4500/21770] eta: 0:11:07 time: 0.0385 data: 0.0009 max mem: 33300 +Test: [ 4600/21770] eta: 0:11:03 time: 0.0383 data: 0.0009 max mem: 33300 +Test: [ 4700/21770] eta: 0:11:00 time: 0.0382 data: 0.0009 max mem: 33300 +Test: [ 4800/21770] eta: 0:10:56 time: 0.0381 data: 0.0009 max mem: 33300 +Test: [ 4900/21770] eta: 0:10:52 time: 0.0384 data: 0.0009 max mem: 33300 +Test: [ 5000/21770] eta: 0:10:48 time: 0.0386 data: 0.0010 max mem: 33300 +Test: [ 5100/21770] eta: 0:10:44 time: 0.0390 data: 0.0009 max mem: 33300 +Test: [ 5200/21770] eta: 0:10:40 time: 0.0387 data: 0.0009 max mem: 33300 +Test: [ 5300/21770] eta: 0:10:36 time: 0.0388 data: 0.0010 max mem: 33300 +Test: [ 5400/21770] eta: 0:10:32 time: 0.0391 data: 0.0010 max mem: 33300 +Test: [ 5500/21770] eta: 0:10:29 time: 0.0388 data: 0.0009 max mem: 33300 +Test: [ 5600/21770] eta: 0:10:25 time: 0.0381 data: 0.0009 max mem: 33300 +Test: [ 5700/21770] eta: 0:10:21 time: 0.0380 data: 0.0009 max mem: 33300 +Test: [ 5800/21770] eta: 0:10:17 time: 0.0383 data: 0.0009 max mem: 33300 +Test: [ 5900/21770] eta: 0:10:13 time: 0.0385 data: 0.0009 max mem: 33300 +Test: [ 6000/21770] eta: 0:10:09 time: 0.0383 data: 0.0009 max mem: 33300 +Test: [ 6100/21770] eta: 0:10:05 time: 0.0386 data: 0.0009 max mem: 33300 +Test: [ 6200/21770] eta: 0:10:01 time: 0.0386 data: 0.0009 max mem: 33300 +Test: [ 6300/21770] eta: 0:09:57 time: 0.0386 data: 0.0009 max mem: 33300 +Test: [ 6400/21770] eta: 0:09:53 time: 0.0388 data: 0.0009 max mem: 33300 +Test: [ 6500/21770] eta: 0:09:50 time: 0.0390 data: 0.0009 max mem: 33300 +Test: [ 6600/21770] eta: 0:09:46 time: 0.0391 data: 0.0009 max mem: 33300 +Test: [ 6700/21770] eta: 0:09:42 time: 0.0390 data: 0.0009 max mem: 33300 +Test: [ 6800/21770] eta: 0:09:38 time: 0.0385 data: 0.0010 max mem: 33300 +Test: [ 6900/21770] eta: 0:09:34 time: 0.0385 data: 0.0009 max mem: 33300 +Test: [ 7000/21770] eta: 0:09:30 time: 0.0386 data: 0.0009 max mem: 33300 +Test: [ 7100/21770] eta: 0:09:26 time: 0.0384 data: 0.0009 max mem: 33300 +Test: [ 7200/21770] eta: 0:09:23 time: 0.0383 data: 0.0009 max mem: 33300 +Test: [ 7300/21770] eta: 0:09:19 time: 0.0388 data: 0.0009 max mem: 33300 +Test: [ 7400/21770] eta: 0:09:15 time: 0.0377 data: 0.0009 max mem: 33300 +Test: [ 7500/21770] eta: 0:09:11 time: 0.0381 data: 0.0009 max mem: 33300 +Test: [ 7600/21770] eta: 0:09:07 time: 0.0380 data: 0.0009 max mem: 33300 +Test: [ 7700/21770] eta: 0:09:03 time: 0.0386 data: 0.0009 max mem: 33300 +Test: [ 7800/21770] eta: 0:08:59 time: 0.0382 data: 0.0009 max mem: 33300 +Test: [ 7900/21770] eta: 0:08:55 time: 0.0392 data: 0.0008 max mem: 33300 +Test: [ 8000/21770] eta: 0:08:51 time: 0.0387 data: 0.0008 max mem: 33300 +Test: [ 8100/21770] eta: 0:08:47 time: 0.0386 data: 0.0008 max mem: 33300 +Test: [ 8200/21770] eta: 0:08:43 time: 0.0381 data: 0.0008 max mem: 33300 +Test: [ 8300/21770] eta: 0:08:40 time: 0.0384 data: 0.0008 max mem: 33300 +Test: [ 8400/21770] eta: 0:08:36 time: 0.0384 data: 0.0009 max mem: 33300 +Test: [ 8500/21770] eta: 0:08:32 time: 0.0379 data: 0.0009 max mem: 33300 +Test: [ 8600/21770] eta: 0:08:28 time: 0.0388 data: 0.0010 max mem: 33300 +Test: [ 8700/21770] eta: 0:08:24 time: 0.0383 data: 0.0009 max mem: 33300 +Test: [ 8800/21770] eta: 0:08:20 time: 0.0387 data: 0.0009 max mem: 33300 +Test: [ 8900/21770] eta: 0:08:16 time: 0.0385 data: 0.0009 max mem: 33300 +Test: [ 9000/21770] eta: 0:08:12 time: 0.0379 data: 0.0009 max mem: 33300 +Test: [ 9100/21770] eta: 0:08:09 time: 0.0392 data: 0.0010 max mem: 33300 +Test: [ 9200/21770] eta: 0:08:05 time: 0.0383 data: 0.0009 max mem: 33300 +Test: [ 9300/21770] eta: 0:08:01 time: 0.0384 data: 0.0009 max mem: 33300 +Test: [ 9400/21770] eta: 0:07:57 time: 0.0386 data: 0.0010 max mem: 33300 +Test: [ 9500/21770] eta: 0:07:53 time: 0.0390 data: 0.0009 max mem: 33300 +Test: [ 9600/21770] eta: 0:07:49 time: 0.0385 data: 0.0009 max mem: 33300 +Test: [ 9700/21770] eta: 0:07:45 time: 0.0383 data: 0.0009 max mem: 33300 +Test: [ 9800/21770] eta: 0:07:42 time: 0.0385 data: 0.0009 max mem: 33300 +Test: [ 9900/21770] eta: 0:07:38 time: 0.0382 data: 0.0010 max mem: 33300 +Test: [10000/21770] eta: 0:07:34 time: 0.0388 data: 0.0009 max mem: 33300 +Test: [10100/21770] eta: 0:07:30 time: 0.0387 data: 0.0010 max mem: 33300 +Test: [10200/21770] eta: 0:07:26 time: 0.0392 data: 0.0010 max mem: 33300 +Test: [10300/21770] eta: 0:07:22 time: 0.0389 data: 0.0009 max mem: 33300 +Test: [10400/21770] eta: 0:07:19 time: 0.0398 data: 0.0009 max mem: 33300 +Test: [10500/21770] eta: 0:07:15 time: 0.0389 data: 0.0010 max mem: 33300 +Test: [10600/21770] eta: 0:07:11 time: 0.0382 data: 0.0009 max mem: 33300 +Test: [10700/21770] eta: 0:07:07 time: 0.0380 data: 0.0009 max mem: 33300 +Test: [10800/21770] eta: 0:07:03 time: 0.0378 data: 0.0008 max mem: 33300 +Test: [10900/21770] eta: 0:06:59 time: 0.0381 data: 0.0009 max mem: 33300 +Test: [11000/21770] eta: 0:06:55 time: 0.0379 data: 0.0009 max mem: 33300 +Test: [11100/21770] eta: 0:06:51 time: 0.0381 data: 0.0009 max mem: 33300 +Test: [11200/21770] eta: 0:06:47 time: 0.0379 data: 0.0009 max mem: 33300 +Test: [11300/21770] eta: 0:06:43 time: 0.0380 data: 0.0009 max mem: 33300 +Test: [11400/21770] eta: 0:06:39 time: 0.0379 data: 0.0008 max mem: 33300 +Test: [11500/21770] eta: 0:06:36 time: 0.0381 data: 0.0009 max mem: 33300 +Test: [11600/21770] eta: 0:06:32 time: 0.0381 data: 0.0009 max mem: 33300 +Test: [11700/21770] eta: 0:06:28 time: 0.0384 data: 0.0009 max mem: 33300 +Test: [11800/21770] eta: 0:06:24 time: 0.0382 data: 0.0009 max mem: 33300 +Test: [11900/21770] eta: 0:06:20 time: 0.0383 data: 0.0009 max mem: 33300 +Test: [12000/21770] eta: 0:06:16 time: 0.0380 data: 0.0008 max mem: 33300 +Test: [12100/21770] eta: 0:06:12 time: 0.0378 data: 0.0008 max mem: 33300 +Test: [12200/21770] eta: 0:06:08 time: 0.0380 data: 0.0009 max mem: 33300 +Test: [12300/21770] eta: 0:06:04 time: 0.0381 data: 0.0009 max mem: 33300 +Test: [12400/21770] eta: 0:06:01 time: 0.0381 data: 0.0009 max mem: 33300 +Test: [12500/21770] eta: 0:05:57 time: 0.0382 data: 0.0009 max mem: 33300 +Test: [12600/21770] eta: 0:05:53 time: 0.0380 data: 0.0009 max mem: 33300 +Test: [12700/21770] eta: 0:05:49 time: 0.0381 data: 0.0009 max mem: 33300 +Test: [12800/21770] eta: 0:05:45 time: 0.0379 data: 0.0009 max mem: 33300 +Test: [12900/21770] eta: 0:05:41 time: 0.0380 data: 0.0009 max mem: 33300 +Test: [13000/21770] eta: 0:05:37 time: 0.0381 data: 0.0009 max mem: 33300 +Test: [13100/21770] eta: 0:05:33 time: 0.0382 data: 0.0009 max mem: 33300 +Test: [13200/21770] eta: 0:05:30 time: 0.0387 data: 0.0009 max mem: 33300 +Test: [13300/21770] eta: 0:05:26 time: 0.0396 data: 0.0010 max mem: 33300 +Test: [13400/21770] eta: 0:05:22 time: 0.0391 data: 0.0010 max mem: 33300 +Test: [13500/21770] eta: 0:05:18 time: 0.0390 data: 0.0010 max mem: 33300 +Test: [13600/21770] eta: 0:05:14 time: 0.0383 data: 0.0009 max mem: 33300 +Test: [13700/21770] eta: 0:05:10 time: 0.0390 data: 0.0009 max mem: 33300 +Test: [13800/21770] eta: 0:05:07 time: 0.0389 data: 0.0009 max mem: 33300 +Test: [13900/21770] eta: 0:05:03 time: 0.0390 data: 0.0009 max mem: 33300 +Test: [14000/21770] eta: 0:04:59 time: 0.0389 data: 0.0009 max mem: 33300 +Test: [14100/21770] eta: 0:04:55 time: 0.0392 data: 0.0009 max mem: 33300 +Test: [14200/21770] eta: 0:04:51 time: 0.0389 data: 0.0009 max mem: 33300 +Test: [14300/21770] eta: 0:04:47 time: 0.0394 data: 0.0010 max mem: 33300 +Test: [14400/21770] eta: 0:04:44 time: 0.0389 data: 0.0009 max mem: 33300 +Test: [14500/21770] eta: 0:04:40 time: 0.0389 data: 0.0010 max mem: 33300 +Test: [14600/21770] eta: 0:04:36 time: 0.0384 data: 0.0008 max mem: 33300 +Test: [14700/21770] eta: 0:04:32 time: 0.0386 data: 0.0008 max mem: 33300 +Test: [14800/21770] eta: 0:04:28 time: 0.0382 data: 0.0008 max mem: 33300 +Test: [14900/21770] eta: 0:04:24 time: 0.0393 data: 0.0008 max mem: 33300 +Test: [15000/21770] eta: 0:04:20 time: 0.0385 data: 0.0009 max mem: 33300 +Test: [15100/21770] eta: 0:04:17 time: 0.0390 data: 0.0008 max mem: 33300 +Test: [15200/21770] eta: 0:04:13 time: 0.0388 data: 0.0008 max mem: 33300 +Test: [15300/21770] eta: 0:04:09 time: 0.0387 data: 0.0008 max mem: 33300 +Test: [15400/21770] eta: 0:04:05 time: 0.0382 data: 0.0008 max mem: 33300 +Test: [15500/21770] eta: 0:04:01 time: 0.0383 data: 0.0008 max mem: 33300 +Test: [15600/21770] eta: 0:03:57 time: 0.0384 data: 0.0009 max mem: 33300 +Test: [15700/21770] eta: 0:03:54 time: 0.0394 data: 0.0009 max mem: 33300 +Test: [15800/21770] eta: 0:03:50 time: 0.0396 data: 0.0009 max mem: 33300 +Test: [15900/21770] eta: 0:03:46 time: 0.0395 data: 0.0009 max mem: 33300 +Test: [16000/21770] eta: 0:03:42 time: 0.0396 data: 0.0010 max mem: 33300 +Test: [16100/21770] eta: 0:03:38 time: 0.0388 data: 0.0009 max mem: 33300 +Test: [16200/21770] eta: 0:03:34 time: 0.0382 data: 0.0009 max mem: 33300 +Test: [16300/21770] eta: 0:03:31 time: 0.0382 data: 0.0009 max mem: 33300 +Test: [16400/21770] eta: 0:03:27 time: 0.0380 data: 0.0009 max mem: 33300 +Test: [16500/21770] eta: 0:03:23 time: 0.0383 data: 0.0009 max mem: 33300 +Test: [16600/21770] eta: 0:03:19 time: 0.0381 data: 0.0009 max mem: 33300 +Test: [16700/21770] eta: 0:03:15 time: 0.0378 data: 0.0008 max mem: 33300 +Test: [16800/21770] eta: 0:03:11 time: 0.0380 data: 0.0009 max mem: 33300 +Test: [16900/21770] eta: 0:03:07 time: 0.0382 data: 0.0009 max mem: 33300 +Test: [17000/21770] eta: 0:03:03 time: 0.0378 data: 0.0008 max mem: 33300 +Test: [17100/21770] eta: 0:03:00 time: 0.0382 data: 0.0008 max mem: 33300 +Test: [17200/21770] eta: 0:02:56 time: 0.0382 data: 0.0009 max mem: 33300 +Test: [17300/21770] eta: 0:02:52 time: 0.0380 data: 0.0008 max mem: 33300 +Test: [17400/21770] eta: 0:02:48 time: 0.0379 data: 0.0008 max mem: 33300 +Test: [17500/21770] eta: 0:02:44 time: 0.0381 data: 0.0008 max mem: 33300 +Test: [17600/21770] eta: 0:02:40 time: 0.0378 data: 0.0008 max mem: 33300 +Test: [17700/21770] eta: 0:02:36 time: 0.0380 data: 0.0008 max mem: 33300 +Test: [17800/21770] eta: 0:02:32 time: 0.0379 data: 0.0008 max mem: 33300 +Test: [17900/21770] eta: 0:02:29 time: 0.0381 data: 0.0009 max mem: 33300 +Test: [18000/21770] eta: 0:02:25 time: 0.0385 data: 0.0010 max mem: 33300 +Test: [18100/21770] eta: 0:02:21 time: 0.0384 data: 0.0009 max mem: 33300 +Test: [18200/21770] eta: 0:02:17 time: 0.0382 data: 0.0009 max mem: 33300 +Test: [18300/21770] eta: 0:02:13 time: 0.0382 data: 0.0008 max mem: 33300 +Test: [18400/21770] eta: 0:02:09 time: 0.0379 data: 0.0008 max mem: 33300 +Test: [18500/21770] eta: 0:02:05 time: 0.0379 data: 0.0009 max mem: 33300 +Test: [18600/21770] eta: 0:02:02 time: 0.0377 data: 0.0008 max mem: 33300 +Test: [18700/21770] eta: 0:01:58 time: 0.0377 data: 0.0008 max mem: 33300 +Test: [18800/21770] eta: 0:01:54 time: 0.0378 data: 0.0008 max mem: 33300 +Test: [18900/21770] eta: 0:01:50 time: 0.0379 data: 0.0009 max mem: 33300 +Test: [19000/21770] eta: 0:01:46 time: 0.0379 data: 0.0008 max mem: 33300 +Test: [19100/21770] eta: 0:01:42 time: 0.0377 data: 0.0009 max mem: 33300 +Test: [19200/21770] eta: 0:01:38 time: 0.0377 data: 0.0009 max mem: 33300 +Test: [19300/21770] eta: 0:01:35 time: 0.0381 data: 0.0008 max mem: 33300 +Test: [19400/21770] eta: 0:01:31 time: 0.0382 data: 0.0009 max mem: 33300 +Test: [19500/21770] eta: 0:01:27 time: 0.0380 data: 0.0008 max mem: 33300 +Test: [19600/21770] eta: 0:01:23 time: 0.0381 data: 0.0009 max mem: 33300 +Test: [19700/21770] eta: 0:01:19 time: 0.0378 data: 0.0008 max mem: 33300 +Test: [19800/21770] eta: 0:01:15 time: 0.0381 data: 0.0009 max mem: 33300 +Test: [19900/21770] eta: 0:01:11 time: 0.0378 data: 0.0008 max mem: 33300 +Test: [20000/21770] eta: 0:01:08 time: 0.0380 data: 0.0009 max mem: 33300 +Test: [20100/21770] eta: 0:01:04 time: 0.0383 data: 0.0009 max mem: 33300 +Test: [20200/21770] eta: 0:01:00 time: 0.0380 data: 0.0008 max mem: 33300 +Test: [20300/21770] eta: 0:00:56 time: 0.0380 data: 0.0008 max mem: 33300 +Test: [20400/21770] eta: 0:00:52 time: 0.0382 data: 0.0009 max mem: 33300 +Test: [20500/21770] eta: 0:00:48 time: 0.0377 data: 0.0008 max mem: 33300 +Test: [20600/21770] eta: 0:00:44 time: 0.0380 data: 0.0009 max mem: 33300 +Test: [20700/21770] eta: 0:00:41 time: 0.0378 data: 0.0008 max mem: 33300 +Test: [20800/21770] eta: 0:00:37 time: 0.0378 data: 0.0008 max mem: 33300 +Test: [20900/21770] eta: 0:00:33 time: 0.0387 data: 0.0008 max mem: 33300 +Test: [21000/21770] eta: 0:00:29 time: 0.0394 data: 0.0008 max mem: 33300 +Test: [21100/21770] eta: 0:00:25 time: 0.0391 data: 0.0008 max mem: 33300 +Test: [21200/21770] eta: 0:00:21 time: 0.0395 data: 0.0008 max mem: 33300 +Test: [21300/21770] eta: 0:00:18 time: 0.0393 data: 0.0008 max mem: 33300 +Test: [21400/21770] eta: 0:00:14 time: 0.0391 data: 0.0009 max mem: 33300 +Test: [21500/21770] eta: 0:00:10 time: 0.0391 data: 0.0008 max mem: 33300 +Test: [21600/21770] eta: 0:00:06 time: 0.0392 data: 0.0008 max mem: 33300 +Test: [21700/21770] eta: 0:00:02 time: 0.0392 data: 0.0008 max mem: 33300 +Test: Total time: 0:13:57 +Final results: +Mean IoU is 0.00 + + precision@0.5 = 0.00 + precision@0.6 = 0.00 + precision@0.7 = 0.00 + precision@0.8 = 0.00 + precision@0.9 = 0.00 + overall IoU = 0.00 + mean IoU = 0.00 + +Mean accuracy for one-to-zero sample is 100.00 + +Average object IoU 0.0 +Overall IoU 0.0 +Epoch: [17] [ 0/4276] eta: 6:03:33 lr: 3.038554919106585e-05 loss: 0.0995 (0.0995) time: 5.1015 data: 2.0752 max mem: 33300 +Epoch: [17] [ 10/4276] eta: 3:42:07 lr: 3.0382768513128516e-05 loss: 0.1260 (0.1377) time: 3.1240 data: 0.1947 max mem: 33300 +Epoch: [17] [ 20/4276] eta: 3:34:52 lr: 3.0379987806914006e-05 loss: 0.1260 (0.1357) time: 2.9257 data: 0.0071 max mem: 33300 +Epoch: [17] [ 30/4276] eta: 3:31:40 lr: 3.0377207072419166e-05 loss: 0.1232 (0.1361) time: 2.9182 data: 0.0073 max mem: 33300 +Epoch: [17] [ 40/4276] eta: 3:29:43 lr: 3.0374426309640825e-05 loss: 0.1253 (0.1355) time: 2.9088 data: 0.0069 max mem: 33300 +Epoch: [17] [ 50/4276] eta: 3:28:14 lr: 3.0371645518575826e-05 loss: 0.1277 (0.1331) time: 2.9027 data: 0.0070 max mem: 33300 +Epoch: [17] [ 60/4276] eta: 3:26:54 lr: 3.0368864699220993e-05 loss: 0.1148 (0.1329) time: 2.8914 data: 0.0072 max mem: 33300 +Epoch: [17] [ 70/4276] eta: 3:25:54 lr: 3.0366083851573173e-05 loss: 0.1217 (0.1314) time: 2.8889 data: 0.0070 max mem: 33300 +Epoch: [17] [ 80/4276] eta: 3:24:58 lr: 3.0363302975629194e-05 loss: 0.1283 (0.1318) time: 2.8899 data: 0.0069 max mem: 33300 +Epoch: [17] [ 90/4276] eta: 3:24:09 lr: 3.036052207138588e-05 loss: 0.1300 (0.1308) time: 2.8868 data: 0.0071 max mem: 33300 +Epoch: [17] [ 100/4276] eta: 3:23:24 lr: 3.035774113884007e-05 loss: 0.1310 (0.1326) time: 2.8878 data: 0.0071 max mem: 33300 +Epoch: [17] [ 110/4276] eta: 3:22:41 lr: 3.035496017798859e-05 loss: 0.1481 (0.1335) time: 2.8868 data: 0.0074 max mem: 33300 +Epoch: [17] [ 120/4276] eta: 3:22:09 lr: 3.0352179188828282e-05 loss: 0.1309 (0.1332) time: 2.8985 data: 0.0073 max mem: 33300 +Epoch: [17] [ 130/4276] eta: 3:21:30 lr: 3.0349398171355964e-05 loss: 0.1195 (0.1338) time: 2.9001 data: 0.0071 max mem: 33300 +Epoch: [17] [ 140/4276] eta: 3:21:05 lr: 3.034661712556848e-05 loss: 0.1195 (0.1331) time: 2.9090 data: 0.0072 max mem: 33300 +Epoch: [17] [ 150/4276] eta: 3:20:44 lr: 3.0343836051462643e-05 loss: 0.1200 (0.1328) time: 2.9383 data: 0.0069 max mem: 33300 +Epoch: [17] [ 160/4276] eta: 3:20:22 lr: 3.0341054949035285e-05 loss: 0.1200 (0.1324) time: 2.9482 data: 0.0071 max mem: 33300 +Epoch: [17] [ 170/4276] eta: 3:20:13 lr: 3.0338273818283236e-05 loss: 0.1178 (0.1322) time: 2.9760 data: 0.0073 max mem: 33300 +Epoch: [17] [ 180/4276] eta: 3:20:06 lr: 3.033549265920332e-05 loss: 0.1334 (0.1323) time: 3.0129 data: 0.0073 max mem: 33300 +Epoch: [17] [ 190/4276] eta: 3:19:47 lr: 3.0332711471792356e-05 loss: 0.1378 (0.1326) time: 3.0024 data: 0.0067 max mem: 33300 +Epoch: [17] [ 200/4276] eta: 3:19:06 lr: 3.0329930256047185e-05 loss: 0.1453 (0.1329) time: 2.9294 data: 0.0058 max mem: 33300 +Epoch: [17] [ 210/4276] eta: 3:18:33 lr: 3.0327149011964622e-05 loss: 0.1337 (0.1328) time: 2.8923 data: 0.0064 max mem: 33300 +Epoch: [17] [ 220/4276] eta: 3:18:05 lr: 3.0324367739541492e-05 loss: 0.1305 (0.1330) time: 2.9234 data: 0.0076 max mem: 33300 +Epoch: [17] [ 230/4276] eta: 3:17:30 lr: 3.032158643877462e-05 loss: 0.1137 (0.1323) time: 2.9186 data: 0.0076 max mem: 33300 +Epoch: [17] [ 240/4276] eta: 3:16:56 lr: 3.0318805109660825e-05 loss: 0.1254 (0.1327) time: 2.8999 data: 0.0073 max mem: 33300 +Epoch: [17] [ 250/4276] eta: 3:16:54 lr: 3.0316023752196925e-05 loss: 0.1539 (0.1336) time: 2.9977 data: 0.0073 max mem: 33300 +Epoch: [17] [ 260/4276] eta: 3:16:28 lr: 3.0313242366379746e-05 loss: 0.1395 (0.1337) time: 3.0278 data: 0.0071 max mem: 33300 +Epoch: [17] [ 270/4276] eta: 3:16:23 lr: 3.031046095220611e-05 loss: 0.1312 (0.1332) time: 3.0293 data: 0.0076 max mem: 33300 +Epoch: [17] [ 280/4276] eta: 3:15:48 lr: 3.0307679509672837e-05 loss: 0.1198 (0.1331) time: 3.0009 data: 0.0078 max mem: 33300 +Epoch: [17] [ 290/4276] eta: 3:15:17 lr: 3.0304898038776734e-05 loss: 0.1198 (0.1333) time: 2.9143 data: 0.0072 max mem: 33300 +Epoch: [17] [ 300/4276] eta: 3:14:40 lr: 3.0302116539514647e-05 loss: 0.1261 (0.1332) time: 2.9057 data: 0.0070 max mem: 33300 +Epoch: [17] [ 310/4276] eta: 3:14:09 lr: 3.0299335011883363e-05 loss: 0.1233 (0.1327) time: 2.9046 data: 0.0072 max mem: 33300 +Epoch: [17] [ 320/4276] eta: 3:13:35 lr: 3.029655345587971e-05 loss: 0.1233 (0.1329) time: 2.9102 data: 0.0076 max mem: 33300 +Epoch: [17] [ 330/4276] eta: 3:13:00 lr: 3.029377187150051e-05 loss: 0.1329 (0.1330) time: 2.8929 data: 0.0073 max mem: 33300 +Epoch: [17] [ 340/4276] eta: 3:12:30 lr: 3.029099025874257e-05 loss: 0.1244 (0.1327) time: 2.9117 data: 0.0072 max mem: 33300 +Epoch: [17] [ 350/4276] eta: 3:12:02 lr: 3.028820861760271e-05 loss: 0.1244 (0.1325) time: 2.9411 data: 0.0079 max mem: 33300 +Epoch: [17] [ 360/4276] eta: 3:11:35 lr: 3.0285426948077745e-05 loss: 0.1366 (0.1331) time: 2.9483 data: 0.0077 max mem: 33300 +Epoch: [17] [ 370/4276] eta: 3:11:18 lr: 3.0282645250164486e-05 loss: 0.1393 (0.1328) time: 3.0048 data: 0.0074 max mem: 33300 +Epoch: [17] [ 380/4276] eta: 3:10:47 lr: 3.027986352385974e-05 loss: 0.1228 (0.1328) time: 2.9915 data: 0.0073 max mem: 33300 +Epoch: [17] [ 390/4276] eta: 3:10:19 lr: 3.0277081769160336e-05 loss: 0.1308 (0.1329) time: 2.9354 data: 0.0070 max mem: 33300 +Epoch: [17] [ 400/4276] eta: 3:10:04 lr: 3.027429998606307e-05 loss: 0.1317 (0.1330) time: 3.0190 data: 0.0079 max mem: 33300 +Epoch: [17] [ 410/4276] eta: 3:09:35 lr: 3.0271518174564755e-05 loss: 0.1193 (0.1328) time: 3.0155 data: 0.0080 max mem: 33300 +Epoch: [17] [ 420/4276] eta: 3:09:10 lr: 3.0268736334662208e-05 loss: 0.1193 (0.1328) time: 2.9691 data: 0.0073 max mem: 33300 +Epoch: [17] [ 430/4276] eta: 3:08:47 lr: 3.0265954466352226e-05 loss: 0.1238 (0.1328) time: 3.0052 data: 0.0074 max mem: 33300 +Epoch: [17] [ 440/4276] eta: 3:08:13 lr: 3.026317256963163e-05 loss: 0.1144 (0.1325) time: 2.9541 data: 0.0076 max mem: 33300 +Epoch: [17] [ 450/4276] eta: 3:07:41 lr: 3.0260390644497227e-05 loss: 0.1178 (0.1324) time: 2.9018 data: 0.0075 max mem: 33300 +Epoch: [17] [ 460/4276] eta: 3:07:07 lr: 3.025760869094582e-05 loss: 0.1176 (0.1320) time: 2.8993 data: 0.0074 max mem: 33300 +Epoch: [17] [ 470/4276] eta: 3:06:33 lr: 3.0254826708974215e-05 loss: 0.1112 (0.1316) time: 2.8898 data: 0.0072 max mem: 33300 +Epoch: [17] [ 480/4276] eta: 3:06:00 lr: 3.0252044698579217e-05 loss: 0.1207 (0.1315) time: 2.8902 data: 0.0072 max mem: 33300 +Epoch: [17] [ 490/4276] eta: 3:05:27 lr: 3.0249262659757637e-05 loss: 0.1171 (0.1311) time: 2.8938 data: 0.0074 max mem: 33300 +Epoch: [17] [ 500/4276] eta: 3:04:54 lr: 3.0246480592506277e-05 loss: 0.1097 (0.1309) time: 2.8908 data: 0.0072 max mem: 33300 +Epoch: [17] [ 510/4276] eta: 3:04:20 lr: 3.0243698496821938e-05 loss: 0.1077 (0.1306) time: 2.8840 data: 0.0074 max mem: 33300 +Epoch: [17] [ 520/4276] eta: 3:03:48 lr: 3.0240916372701423e-05 loss: 0.1125 (0.1304) time: 2.8871 data: 0.0076 max mem: 33300 +Epoch: [17] [ 530/4276] eta: 3:03:15 lr: 3.0238134220141546e-05 loss: 0.1270 (0.1303) time: 2.8898 data: 0.0072 max mem: 33300 +Epoch: [17] [ 540/4276] eta: 3:02:43 lr: 3.0235352039139093e-05 loss: 0.1250 (0.1301) time: 2.8965 data: 0.0072 max mem: 33300 +Epoch: [17] [ 550/4276] eta: 3:02:14 lr: 3.0232569829690877e-05 loss: 0.1250 (0.1301) time: 2.9168 data: 0.0074 max mem: 33300 +Epoch: [17] [ 560/4276] eta: 3:01:43 lr: 3.022978759179369e-05 loss: 0.1337 (0.1300) time: 2.9230 data: 0.0071 max mem: 33300 +Epoch: [17] [ 570/4276] eta: 3:01:15 lr: 3.022700532544433e-05 loss: 0.1295 (0.1300) time: 2.9372 data: 0.0070 max mem: 33300 +Epoch: [17] [ 580/4276] eta: 3:00:43 lr: 3.0224223030639608e-05 loss: 0.1251 (0.1300) time: 2.9219 data: 0.0072 max mem: 33300 +Epoch: [17] [ 590/4276] eta: 3:00:10 lr: 3.0221440707376314e-05 loss: 0.1105 (0.1296) time: 2.8795 data: 0.0071 max mem: 33300 +Epoch: [17] [ 600/4276] eta: 2:59:36 lr: 3.0218658355651243e-05 loss: 0.1105 (0.1295) time: 2.8700 data: 0.0069 max mem: 33300 +Epoch: [17] [ 610/4276] eta: 2:59:04 lr: 3.0215875975461206e-05 loss: 0.1274 (0.1293) time: 2.8712 data: 0.0069 max mem: 33300 +Epoch: [17] [ 620/4276] eta: 2:58:31 lr: 3.0213093566802987e-05 loss: 0.1159 (0.1294) time: 2.8769 data: 0.0071 max mem: 33300 +Epoch: [17] [ 630/4276] eta: 2:58:00 lr: 3.021031112967338e-05 loss: 0.1176 (0.1295) time: 2.8855 data: 0.0072 max mem: 33300 +Epoch: [17] [ 640/4276] eta: 2:57:29 lr: 3.020752866406919e-05 loss: 0.1343 (0.1295) time: 2.8997 data: 0.0075 max mem: 33300 +Epoch: [17] [ 650/4276] eta: 2:56:58 lr: 3.0204746169987198e-05 loss: 0.1295 (0.1295) time: 2.9047 data: 0.0076 max mem: 33300 +Epoch: [17] [ 660/4276] eta: 2:56:27 lr: 3.0201963647424207e-05 loss: 0.1295 (0.1297) time: 2.8988 data: 0.0072 max mem: 33300 +Epoch: [17] [ 670/4276] eta: 2:55:56 lr: 3.019918109637701e-05 loss: 0.1269 (0.1297) time: 2.8928 data: 0.0072 max mem: 33300 +Epoch: [17] [ 680/4276] eta: 2:55:25 lr: 3.0196398516842407e-05 loss: 0.1182 (0.1296) time: 2.8949 data: 0.0076 max mem: 33300 +Epoch: [17] [ 690/4276] eta: 2:54:55 lr: 3.019361590881717e-05 loss: 0.1153 (0.1295) time: 2.9015 data: 0.0074 max mem: 33300 +Epoch: [17] [ 700/4276] eta: 2:54:26 lr: 3.0190833272298103e-05 loss: 0.1133 (0.1293) time: 2.9145 data: 0.0074 max mem: 33300 +Epoch: [17] [ 710/4276] eta: 2:53:55 lr: 3.0188050607281986e-05 loss: 0.1189 (0.1294) time: 2.9098 data: 0.0076 max mem: 33300 +Epoch: [17] [ 720/4276] eta: 2:53:23 lr: 3.0185267913765618e-05 loss: 0.1251 (0.1292) time: 2.8867 data: 0.0073 max mem: 33300 +Epoch: [17] [ 730/4276] eta: 2:52:52 lr: 3.018248519174579e-05 loss: 0.1156 (0.1291) time: 2.8851 data: 0.0070 max mem: 33300 +Epoch: [17] [ 740/4276] eta: 2:52:21 lr: 3.0179702441219283e-05 loss: 0.1233 (0.1290) time: 2.8869 data: 0.0069 max mem: 33300 +Epoch: [17] [ 750/4276] eta: 2:51:50 lr: 3.0176919662182878e-05 loss: 0.1162 (0.1291) time: 2.8899 data: 0.0071 max mem: 33300 +Epoch: [17] [ 760/4276] eta: 2:51:19 lr: 3.0174136854633382e-05 loss: 0.1126 (0.1290) time: 2.8880 data: 0.0072 max mem: 33300 +Epoch: [17] [ 770/4276] eta: 2:50:48 lr: 3.0171354018567567e-05 loss: 0.1172 (0.1290) time: 2.8816 data: 0.0070 max mem: 33300 +Epoch: [17] [ 780/4276] eta: 2:50:17 lr: 3.0168571153982223e-05 loss: 0.1308 (0.1291) time: 2.8821 data: 0.0069 max mem: 33300 +Epoch: [17] [ 790/4276] eta: 2:49:46 lr: 3.0165788260874122e-05 loss: 0.1338 (0.1292) time: 2.8805 data: 0.0069 max mem: 33300 +Epoch: [17] [ 800/4276] eta: 2:49:16 lr: 3.0163005339240063e-05 loss: 0.1290 (0.1292) time: 2.8933 data: 0.0070 max mem: 33300 +Epoch: [17] [ 810/4276] eta: 2:48:47 lr: 3.0160222389076825e-05 loss: 0.1290 (0.1292) time: 2.9226 data: 0.0078 max mem: 33300 +Epoch: [17] [ 820/4276] eta: 2:48:19 lr: 3.015743941038119e-05 loss: 0.1224 (0.1290) time: 2.9363 data: 0.0083 max mem: 33300 +Epoch: [17] [ 830/4276] eta: 2:47:50 lr: 3.0154656403149933e-05 loss: 0.1174 (0.1292) time: 2.9333 data: 0.0080 max mem: 33300 +Epoch: [17] [ 840/4276] eta: 2:47:21 lr: 3.015187336737985e-05 loss: 0.1276 (0.1292) time: 2.9312 data: 0.0082 max mem: 33300 +Epoch: [17] [ 850/4276] eta: 2:46:51 lr: 3.0149090303067713e-05 loss: 0.1207 (0.1291) time: 2.9193 data: 0.0079 max mem: 33300 +Epoch: [17] [ 860/4276] eta: 2:46:21 lr: 3.01463072102103e-05 loss: 0.1233 (0.1291) time: 2.9009 data: 0.0072 max mem: 33300 +Epoch: [17] [ 870/4276] eta: 2:45:51 lr: 3.0143524088804394e-05 loss: 0.1233 (0.1291) time: 2.9047 data: 0.0069 max mem: 33300 +Epoch: [17] [ 880/4276] eta: 2:45:21 lr: 3.014074093884677e-05 loss: 0.1311 (0.1293) time: 2.9024 data: 0.0075 max mem: 33300 +Epoch: [17] [ 890/4276] eta: 2:44:50 lr: 3.01379577603342e-05 loss: 0.1370 (0.1293) time: 2.8849 data: 0.0080 max mem: 33300 +Epoch: [17] [ 900/4276] eta: 2:44:20 lr: 3.0135174553263474e-05 loss: 0.1264 (0.1293) time: 2.8874 data: 0.0077 max mem: 33300 +Epoch: [17] [ 910/4276] eta: 2:43:50 lr: 3.013239131763136e-05 loss: 0.1369 (0.1295) time: 2.8944 data: 0.0075 max mem: 33300 +Epoch: [17] [ 920/4276] eta: 2:43:20 lr: 3.0129608053434642e-05 loss: 0.1369 (0.1296) time: 2.8988 data: 0.0081 max mem: 33300 +Epoch: [17] [ 930/4276] eta: 2:42:51 lr: 3.0126824760670085e-05 loss: 0.1244 (0.1295) time: 2.9196 data: 0.0082 max mem: 33300 +Epoch: [17] [ 940/4276] eta: 2:42:22 lr: 3.0124041439334472e-05 loss: 0.1222 (0.1294) time: 2.9358 data: 0.0075 max mem: 33300 +Epoch: [17] [ 950/4276] eta: 2:41:54 lr: 3.0121258089424566e-05 loss: 0.1240 (0.1295) time: 2.9352 data: 0.0078 max mem: 33300 +Epoch: [17] [ 960/4276] eta: 2:41:25 lr: 3.011847471093714e-05 loss: 0.1284 (0.1295) time: 2.9348 data: 0.0080 max mem: 33300 +Epoch: [17] [ 970/4276] eta: 2:40:56 lr: 3.0115691303868976e-05 loss: 0.1257 (0.1295) time: 2.9267 data: 0.0074 max mem: 33300 +Epoch: [17] [ 980/4276] eta: 2:40:25 lr: 3.0112907868216838e-05 loss: 0.1245 (0.1295) time: 2.9006 data: 0.0073 max mem: 33300 +Epoch: [17] [ 990/4276] eta: 2:39:55 lr: 3.0110124403977508e-05 loss: 0.1240 (0.1295) time: 2.8821 data: 0.0071 max mem: 33300 +Epoch: [17] [1000/4276] eta: 2:39:24 lr: 3.0107340911147742e-05 loss: 0.1191 (0.1295) time: 2.8798 data: 0.0071 max mem: 33300 +Epoch: [17] [1010/4276] eta: 2:38:54 lr: 3.010455738972432e-05 loss: 0.1179 (0.1295) time: 2.8814 data: 0.0073 max mem: 33300 +Epoch: [17] [1020/4276] eta: 2:38:23 lr: 3.0101773839703995e-05 loss: 0.1219 (0.1295) time: 2.8805 data: 0.0071 max mem: 33300 +Epoch: [17] [1030/4276] eta: 2:37:53 lr: 3.0098990261083554e-05 loss: 0.1375 (0.1296) time: 2.8792 data: 0.0072 max mem: 33300 +Epoch: [17] [1040/4276] eta: 2:37:22 lr: 3.009620665385975e-05 loss: 0.1348 (0.1296) time: 2.8794 data: 0.0076 max mem: 33300 +Epoch: [17] [1050/4276] eta: 2:36:53 lr: 3.0093423018029356e-05 loss: 0.1301 (0.1297) time: 2.8883 data: 0.0075 max mem: 33300 +Epoch: [17] [1060/4276] eta: 2:36:23 lr: 3.009063935358914e-05 loss: 0.1301 (0.1297) time: 2.8955 data: 0.0071 max mem: 33300 +Epoch: [17] [1070/4276] eta: 2:35:52 lr: 3.0087855660535863e-05 loss: 0.1482 (0.1300) time: 2.8843 data: 0.0071 max mem: 33300 +Epoch: [17] [1080/4276] eta: 2:35:22 lr: 3.0085071938866293e-05 loss: 0.1455 (0.1300) time: 2.8766 data: 0.0073 max mem: 33300 +Epoch: [17] [1090/4276] eta: 2:34:51 lr: 3.008228818857719e-05 loss: 0.1362 (0.1301) time: 2.8723 data: 0.0073 max mem: 33300 +Epoch: [17] [1100/4276] eta: 2:34:21 lr: 3.007950440966532e-05 loss: 0.1296 (0.1301) time: 2.8688 data: 0.0075 max mem: 33300 +Epoch: [17] [1110/4276] eta: 2:33:51 lr: 3.007672060212744e-05 loss: 0.1266 (0.1302) time: 2.8875 data: 0.0073 max mem: 33300 +Epoch: [17] [1120/4276] eta: 2:33:23 lr: 3.0073936765960316e-05 loss: 0.1165 (0.1301) time: 2.9175 data: 0.0073 max mem: 33300 +Epoch: [17] [1130/4276] eta: 2:32:54 lr: 3.0071152901160704e-05 loss: 0.1173 (0.1300) time: 2.9280 data: 0.0076 max mem: 33300 +Epoch: [17] [1140/4276] eta: 2:32:25 lr: 3.006836900772537e-05 loss: 0.1184 (0.1299) time: 2.9269 data: 0.0075 max mem: 33300 +Epoch: [17] [1150/4276] eta: 2:31:56 lr: 3.0065585085651082e-05 loss: 0.1254 (0.1299) time: 2.9293 data: 0.0077 max mem: 33300 +Epoch: [17] [1160/4276] eta: 2:31:28 lr: 3.006280113493458e-05 loss: 0.1272 (0.1299) time: 2.9347 data: 0.0078 max mem: 33300 +Epoch: [17] [1170/4276] eta: 2:30:59 lr: 3.006001715557264e-05 loss: 0.1311 (0.1299) time: 2.9347 data: 0.0076 max mem: 33300 +Epoch: [17] [1180/4276] eta: 2:30:30 lr: 3.0057233147562004e-05 loss: 0.1228 (0.1298) time: 2.9328 data: 0.0075 max mem: 33300 +Epoch: [17] [1190/4276] eta: 2:30:00 lr: 3.0054449110899434e-05 loss: 0.1204 (0.1298) time: 2.9107 data: 0.0077 max mem: 33300 +Epoch: [17] [1200/4276] eta: 2:29:30 lr: 3.005166504558169e-05 loss: 0.1195 (0.1298) time: 2.8840 data: 0.0078 max mem: 33300 +Epoch: [17] [1210/4276] eta: 2:29:01 lr: 3.0048880951605522e-05 loss: 0.1119 (0.1297) time: 2.8965 data: 0.0074 max mem: 33300 +Epoch: [17] [1220/4276] eta: 2:28:32 lr: 3.0046096828967685e-05 loss: 0.1294 (0.1298) time: 2.9137 data: 0.0072 max mem: 33300 +Epoch: [17] [1230/4276] eta: 2:28:03 lr: 3.004331267766495e-05 loss: 0.1209 (0.1298) time: 2.9268 data: 0.0074 max mem: 33300 +Epoch: [17] [1240/4276] eta: 2:27:34 lr: 3.0040528497694037e-05 loss: 0.1218 (0.1298) time: 2.9382 data: 0.0078 max mem: 33300 +Epoch: [17] [1250/4276] eta: 2:27:06 lr: 3.0037744289051734e-05 loss: 0.1277 (0.1299) time: 2.9366 data: 0.0082 max mem: 33300 +Epoch: [17] [1260/4276] eta: 2:26:36 lr: 3.0034960051734763e-05 loss: 0.1154 (0.1299) time: 2.9240 data: 0.0080 max mem: 33300 +Epoch: [17] [1270/4276] eta: 2:26:07 lr: 3.003217578573989e-05 loss: 0.1191 (0.1298) time: 2.8999 data: 0.0078 max mem: 33300 +Epoch: [17] [1280/4276] eta: 2:25:38 lr: 3.0029391491063868e-05 loss: 0.1245 (0.1299) time: 2.9086 data: 0.0077 max mem: 33300 +Epoch: [17] [1290/4276] eta: 2:25:09 lr: 3.0026607167703434e-05 loss: 0.1320 (0.1299) time: 2.9319 data: 0.0075 max mem: 33300 +Epoch: [17] [1300/4276] eta: 2:24:40 lr: 3.0023822815655356e-05 loss: 0.1190 (0.1299) time: 2.9213 data: 0.0072 max mem: 33300 +Epoch: [17] [1310/4276] eta: 2:24:10 lr: 3.0021038434916365e-05 loss: 0.1091 (0.1298) time: 2.9096 data: 0.0071 max mem: 33300 +Epoch: [17] [1320/4276] eta: 2:23:41 lr: 3.001825402548322e-05 loss: 0.1112 (0.1299) time: 2.9233 data: 0.0079 max mem: 33300 +Epoch: [17] [1330/4276] eta: 2:23:12 lr: 3.0015469587352662e-05 loss: 0.1422 (0.1299) time: 2.9175 data: 0.0083 max mem: 33300 +Epoch: [17] [1340/4276] eta: 2:22:42 lr: 3.0012685120521432e-05 loss: 0.1203 (0.1298) time: 2.8881 data: 0.0075 max mem: 33300 +Epoch: [17] [1350/4276] eta: 2:22:12 lr: 3.0009900624986288e-05 loss: 0.1184 (0.1298) time: 2.8752 data: 0.0071 max mem: 33300 +Epoch: [17] [1360/4276] eta: 2:21:42 lr: 3.0007116100743964e-05 loss: 0.1209 (0.1298) time: 2.8766 data: 0.0073 max mem: 33300 +Epoch: [17] [1370/4276] eta: 2:21:12 lr: 3.0004331547791208e-05 loss: 0.1180 (0.1298) time: 2.8833 data: 0.0073 max mem: 33300 +Epoch: [17] [1380/4276] eta: 2:20:43 lr: 3.0001546966124773e-05 loss: 0.1284 (0.1298) time: 2.8968 data: 0.0074 max mem: 33300 +Epoch: [17] [1390/4276] eta: 2:20:14 lr: 2.9998762355741384e-05 loss: 0.1499 (0.1299) time: 2.9136 data: 0.0077 max mem: 33300 +Epoch: [17] [1400/4276] eta: 2:19:45 lr: 2.99959777166378e-05 loss: 0.1326 (0.1299) time: 2.9346 data: 0.0076 max mem: 33300 +Epoch: [17] [1410/4276] eta: 2:19:17 lr: 2.9993193048810748e-05 loss: 0.1183 (0.1298) time: 2.9441 data: 0.0076 max mem: 33300 +Epoch: [17] [1420/4276] eta: 2:18:47 lr: 2.9990408352256973e-05 loss: 0.1098 (0.1297) time: 2.9212 data: 0.0079 max mem: 33300 +Epoch: [17] [1430/4276] eta: 2:18:18 lr: 2.9987623626973215e-05 loss: 0.1197 (0.1297) time: 2.9004 data: 0.0078 max mem: 33300 +Epoch: [17] [1440/4276] eta: 2:17:48 lr: 2.9984838872956223e-05 loss: 0.1241 (0.1297) time: 2.9064 data: 0.0078 max mem: 33300 +Epoch: [17] [1450/4276] eta: 2:17:20 lr: 2.9982054090202717e-05 loss: 0.1252 (0.1298) time: 2.9295 data: 0.0082 max mem: 33300 +Epoch: [17] [1460/4276] eta: 2:16:51 lr: 2.9979269278709454e-05 loss: 0.1252 (0.1297) time: 2.9442 data: 0.0082 max mem: 33300 +Epoch: [17] [1470/4276] eta: 2:16:23 lr: 2.9976484438473157e-05 loss: 0.1199 (0.1297) time: 2.9450 data: 0.0081 max mem: 33300 +Epoch: [17] [1480/4276] eta: 2:15:54 lr: 2.9973699569490572e-05 loss: 0.1186 (0.1297) time: 2.9499 data: 0.0087 max mem: 33300 +Epoch: [17] [1490/4276] eta: 2:15:26 lr: 2.9970914671758428e-05 loss: 0.1167 (0.1296) time: 2.9503 data: 0.0086 max mem: 33300 +Epoch: [17] [1500/4276] eta: 2:14:57 lr: 2.9968129745273453e-05 loss: 0.1167 (0.1296) time: 2.9471 data: 0.0081 max mem: 33300 +Epoch: [17] [1510/4276] eta: 2:14:28 lr: 2.9965344790032397e-05 loss: 0.1159 (0.1295) time: 2.9470 data: 0.0082 max mem: 33300 +Epoch: [17] [1520/4276] eta: 2:14:00 lr: 2.9962559806031987e-05 loss: 0.1083 (0.1294) time: 2.9453 data: 0.0082 max mem: 33300 +Epoch: [17] [1530/4276] eta: 2:13:31 lr: 2.9959774793268954e-05 loss: 0.1083 (0.1293) time: 2.9442 data: 0.0082 max mem: 33300 +Epoch: [17] [1540/4276] eta: 2:13:02 lr: 2.9956989751740034e-05 loss: 0.1148 (0.1293) time: 2.9445 data: 0.0089 max mem: 33300 +Epoch: [17] [1550/4276] eta: 2:12:34 lr: 2.995420468144195e-05 loss: 0.1197 (0.1293) time: 2.9439 data: 0.0089 max mem: 33300 +Epoch: [17] [1560/4276] eta: 2:12:05 lr: 2.9951419582371443e-05 loss: 0.1206 (0.1292) time: 2.9455 data: 0.0087 max mem: 33300 +Epoch: [17] [1570/4276] eta: 2:11:36 lr: 2.994863445452523e-05 loss: 0.1266 (0.1292) time: 2.9443 data: 0.0084 max mem: 33300 +Epoch: [17] [1580/4276] eta: 2:11:07 lr: 2.994584929790006e-05 loss: 0.1174 (0.1291) time: 2.9416 data: 0.0081 max mem: 33300 +Epoch: [17] [1590/4276] eta: 2:10:39 lr: 2.9943064112492643e-05 loss: 0.1174 (0.1292) time: 2.9410 data: 0.0082 max mem: 33300 +Epoch: [17] [1600/4276] eta: 2:10:09 lr: 2.9940278898299713e-05 loss: 0.1406 (0.1292) time: 2.9115 data: 0.0078 max mem: 33300 +Epoch: [17] [1610/4276] eta: 2:09:39 lr: 2.9937493655318004e-05 loss: 0.1208 (0.1291) time: 2.8867 data: 0.0077 max mem: 33300 +Epoch: [17] [1620/4276] eta: 2:09:09 lr: 2.993470838354423e-05 loss: 0.1198 (0.1291) time: 2.8897 data: 0.0079 max mem: 33300 +Epoch: [17] [1630/4276] eta: 2:08:41 lr: 2.9931923082975127e-05 loss: 0.1230 (0.1291) time: 2.9118 data: 0.0082 max mem: 33300 +Epoch: [17] [1640/4276] eta: 2:08:12 lr: 2.9929137753607418e-05 loss: 0.1289 (0.1290) time: 2.9317 data: 0.0082 max mem: 33300 +Epoch: [17] [1650/4276] eta: 2:07:43 lr: 2.9926352395437817e-05 loss: 0.1095 (0.1290) time: 2.9353 data: 0.0084 max mem: 33300 +Epoch: [17] [1660/4276] eta: 2:07:14 lr: 2.992356700846306e-05 loss: 0.1145 (0.1289) time: 2.9427 data: 0.0086 max mem: 33300 +Epoch: [17] [1670/4276] eta: 2:06:45 lr: 2.9920781592679864e-05 loss: 0.1160 (0.1288) time: 2.9440 data: 0.0079 max mem: 33300 +Epoch: [17] [1680/4276] eta: 2:06:16 lr: 2.9917996148084954e-05 loss: 0.1267 (0.1289) time: 2.9446 data: 0.0081 max mem: 33300 +Epoch: [17] [1690/4276] eta: 2:05:48 lr: 2.9915210674675053e-05 loss: 0.1192 (0.1288) time: 2.9424 data: 0.0084 max mem: 33300 +Epoch: [17] [1700/4276] eta: 2:05:19 lr: 2.991242517244688e-05 loss: 0.1156 (0.1288) time: 2.9403 data: 0.0080 max mem: 33300 +Epoch: [17] [1710/4276] eta: 2:04:50 lr: 2.9909639641397152e-05 loss: 0.1346 (0.1288) time: 2.9412 data: 0.0080 max mem: 33300 +Epoch: [17] [1720/4276] eta: 2:04:21 lr: 2.990685408152259e-05 loss: 0.1267 (0.1288) time: 2.9442 data: 0.0083 max mem: 33300 +Epoch: [17] [1730/4276] eta: 2:03:52 lr: 2.990406849281991e-05 loss: 0.1249 (0.1288) time: 2.9464 data: 0.0085 max mem: 33300 +Epoch: [17] [1740/4276] eta: 2:03:23 lr: 2.990128287528583e-05 loss: 0.1205 (0.1288) time: 2.9450 data: 0.0083 max mem: 33300 +Epoch: [17] [1750/4276] eta: 2:02:55 lr: 2.989849722891707e-05 loss: 0.1160 (0.1288) time: 2.9457 data: 0.0081 max mem: 33300 +Epoch: [17] [1760/4276] eta: 2:02:26 lr: 2.9895711553710353e-05 loss: 0.1160 (0.1288) time: 2.9462 data: 0.0080 max mem: 33300 +Epoch: [17] [1770/4276] eta: 2:01:57 lr: 2.989292584966239e-05 loss: 0.1203 (0.1287) time: 2.9439 data: 0.0080 max mem: 33300 +Epoch: [17] [1780/4276] eta: 2:01:28 lr: 2.989014011676988e-05 loss: 0.1203 (0.1287) time: 2.9414 data: 0.0082 max mem: 33300 +Epoch: [17] [1790/4276] eta: 2:00:59 lr: 2.988735435502957e-05 loss: 0.1257 (0.1287) time: 2.9399 data: 0.0085 max mem: 33300 +Epoch: [17] [1800/4276] eta: 2:00:30 lr: 2.9884568564438142e-05 loss: 0.1321 (0.1287) time: 2.9381 data: 0.0085 max mem: 33300 +Epoch: [17] [1810/4276] eta: 2:00:01 lr: 2.9881782744992325e-05 loss: 0.1266 (0.1288) time: 2.9379 data: 0.0081 max mem: 33300 +Epoch: [17] [1820/4276] eta: 1:59:32 lr: 2.9878996896688826e-05 loss: 0.1287 (0.1288) time: 2.9400 data: 0.0081 max mem: 33300 +Epoch: [17] [1830/4276] eta: 1:59:03 lr: 2.9876211019524357e-05 loss: 0.1270 (0.1287) time: 2.9414 data: 0.0079 max mem: 33300 +Epoch: [17] [1840/4276] eta: 1:58:34 lr: 2.9873425113495628e-05 loss: 0.1127 (0.1286) time: 2.9382 data: 0.0083 max mem: 33300 +Epoch: [17] [1850/4276] eta: 1:58:05 lr: 2.9870639178599362e-05 loss: 0.1103 (0.1287) time: 2.9365 data: 0.0085 max mem: 33300 +Epoch: [17] [1860/4276] eta: 1:57:36 lr: 2.986785321483225e-05 loss: 0.1236 (0.1287) time: 2.9370 data: 0.0082 max mem: 33300 +Epoch: [17] [1870/4276] eta: 1:57:07 lr: 2.9865067222191006e-05 loss: 0.1337 (0.1288) time: 2.9388 data: 0.0082 max mem: 33300 +Epoch: [17] [1880/4276] eta: 1:56:38 lr: 2.9862281200672342e-05 loss: 0.1263 (0.1287) time: 2.9396 data: 0.0078 max mem: 33300 +Epoch: [17] [1890/4276] eta: 1:56:09 lr: 2.9859495150272966e-05 loss: 0.1263 (0.1288) time: 2.9375 data: 0.0078 max mem: 33300 +Epoch: [17] [1900/4276] eta: 1:55:40 lr: 2.9856709070989573e-05 loss: 0.1192 (0.1288) time: 2.9380 data: 0.0084 max mem: 33300 +Epoch: [17] [1910/4276] eta: 1:55:11 lr: 2.985392296281888e-05 loss: 0.1195 (0.1288) time: 2.9389 data: 0.0083 max mem: 33300 +Epoch: [17] [1920/4276] eta: 1:54:42 lr: 2.9851136825757592e-05 loss: 0.1224 (0.1287) time: 2.9411 data: 0.0077 max mem: 33300 +Epoch: [17] [1930/4276] eta: 1:54:13 lr: 2.9848350659802403e-05 loss: 0.1269 (0.1287) time: 2.9429 data: 0.0076 max mem: 33300 +Epoch: [17] [1940/4276] eta: 1:53:44 lr: 2.9845564464950038e-05 loss: 0.1269 (0.1287) time: 2.9414 data: 0.0079 max mem: 33300 +Epoch: [17] [1950/4276] eta: 1:53:15 lr: 2.9842778241197173e-05 loss: 0.1280 (0.1288) time: 2.9389 data: 0.0081 max mem: 33300 +Epoch: [17] [1960/4276] eta: 1:52:46 lr: 2.9839991988540522e-05 loss: 0.1313 (0.1287) time: 2.9381 data: 0.0079 max mem: 33300 +Epoch: [17] [1970/4276] eta: 1:52:17 lr: 2.983720570697679e-05 loss: 0.1067 (0.1287) time: 2.9335 data: 0.0079 max mem: 33300 +Epoch: [17] [1980/4276] eta: 1:51:48 lr: 2.983441939650267e-05 loss: 0.1146 (0.1286) time: 2.9369 data: 0.0080 max mem: 33300 +Epoch: [17] [1990/4276] eta: 1:51:19 lr: 2.983163305711487e-05 loss: 0.1188 (0.1286) time: 2.9446 data: 0.0082 max mem: 33300 +Epoch: [17] [2000/4276] eta: 1:50:50 lr: 2.9828846688810097e-05 loss: 0.1252 (0.1286) time: 2.9444 data: 0.0083 max mem: 33300 +Epoch: [17] [2010/4276] eta: 1:50:21 lr: 2.9826060291585023e-05 loss: 0.1342 (0.1286) time: 2.9426 data: 0.0083 max mem: 33300 +Epoch: [17] [2020/4276] eta: 1:49:52 lr: 2.9823273865436374e-05 loss: 0.1354 (0.1287) time: 2.9158 data: 0.0084 max mem: 33300 +Epoch: [17] [2030/4276] eta: 1:49:22 lr: 2.982048741036082e-05 loss: 0.1196 (0.1286) time: 2.8882 data: 0.0079 max mem: 33300 +Epoch: [17] [2040/4276] eta: 1:48:53 lr: 2.981770092635508e-05 loss: 0.1151 (0.1286) time: 2.8865 data: 0.0076 max mem: 33300 +Epoch: [17] [2050/4276] eta: 1:48:23 lr: 2.9814914413415836e-05 loss: 0.1228 (0.1286) time: 2.8865 data: 0.0074 max mem: 33300 +Epoch: [17] [2060/4276] eta: 1:47:53 lr: 2.981212787153979e-05 loss: 0.1233 (0.1286) time: 2.8867 data: 0.0076 max mem: 33300 +Epoch: [17] [2070/4276] eta: 1:47:24 lr: 2.9809341300723637e-05 loss: 0.1122 (0.1285) time: 2.9083 data: 0.0077 max mem: 33300 +Epoch: [17] [2080/4276] eta: 1:46:55 lr: 2.9806554700964068e-05 loss: 0.1122 (0.1285) time: 2.9358 data: 0.0075 max mem: 33300 +Epoch: [17] [2090/4276] eta: 1:46:26 lr: 2.9803768072257772e-05 loss: 0.1248 (0.1285) time: 2.9440 data: 0.0077 max mem: 33300 +Epoch: [17] [2100/4276] eta: 1:45:57 lr: 2.9800981414601448e-05 loss: 0.1248 (0.1286) time: 2.9460 data: 0.0081 max mem: 33300 +Epoch: [17] [2110/4276] eta: 1:45:28 lr: 2.979819472799178e-05 loss: 0.1175 (0.1285) time: 2.9484 data: 0.0079 max mem: 33300 +Epoch: [17] [2120/4276] eta: 1:44:59 lr: 2.9795408012425463e-05 loss: 0.1046 (0.1284) time: 2.9500 data: 0.0075 max mem: 33300 +Epoch: [17] [2130/4276] eta: 1:44:31 lr: 2.9792621267899185e-05 loss: 0.1043 (0.1283) time: 2.9498 data: 0.0076 max mem: 33300 +Epoch: [17] [2140/4276] eta: 1:44:02 lr: 2.9789834494409642e-05 loss: 0.1099 (0.1283) time: 2.9455 data: 0.0077 max mem: 33300 +Epoch: [17] [2150/4276] eta: 1:43:32 lr: 2.9787047691953507e-05 loss: 0.1099 (0.1282) time: 2.9137 data: 0.0077 max mem: 33300 +Epoch: [17] [2160/4276] eta: 1:43:02 lr: 2.978426086052749e-05 loss: 0.1117 (0.1281) time: 2.8857 data: 0.0077 max mem: 33300 +Epoch: [17] [2170/4276] eta: 1:42:33 lr: 2.9781474000128263e-05 loss: 0.1330 (0.1282) time: 2.8879 data: 0.0076 max mem: 33300 +Epoch: [17] [2180/4276] eta: 1:42:03 lr: 2.9778687110752507e-05 loss: 0.1407 (0.1283) time: 2.8906 data: 0.0076 max mem: 33300 +Epoch: [17] [2190/4276] eta: 1:41:34 lr: 2.977590019239692e-05 loss: 0.1341 (0.1283) time: 2.8974 data: 0.0076 max mem: 33300 +Epoch: [17] [2200/4276] eta: 1:41:04 lr: 2.9773113245058175e-05 loss: 0.1255 (0.1283) time: 2.8949 data: 0.0070 max mem: 33300 +Epoch: [17] [2210/4276] eta: 1:40:35 lr: 2.9770326268732973e-05 loss: 0.1265 (0.1283) time: 2.8849 data: 0.0072 max mem: 33300 +Epoch: [17] [2220/4276] eta: 1:40:05 lr: 2.9767539263417983e-05 loss: 0.1317 (0.1283) time: 2.8792 data: 0.0076 max mem: 33300 +Epoch: [17] [2230/4276] eta: 1:39:36 lr: 2.9764752229109892e-05 loss: 0.1219 (0.1283) time: 2.8930 data: 0.0073 max mem: 33300 +Epoch: [17] [2240/4276] eta: 1:39:06 lr: 2.9761965165805383e-05 loss: 0.1138 (0.1282) time: 2.8974 data: 0.0072 max mem: 33300 +Epoch: [17] [2250/4276] eta: 1:38:37 lr: 2.9759178073501136e-05 loss: 0.1114 (0.1282) time: 2.8876 data: 0.0073 max mem: 33300 +Epoch: [17] [2260/4276] eta: 1:38:08 lr: 2.975639095219383e-05 loss: 0.1310 (0.1282) time: 2.9022 data: 0.0074 max mem: 33300 +Epoch: [17] [2270/4276] eta: 1:37:39 lr: 2.975360380188015e-05 loss: 0.1253 (0.1282) time: 2.9281 data: 0.0079 max mem: 33300 +Epoch: [17] [2280/4276] eta: 1:37:10 lr: 2.9750816622556765e-05 loss: 0.1253 (0.1283) time: 2.9425 data: 0.0080 max mem: 33300 +Epoch: [17] [2290/4276] eta: 1:36:40 lr: 2.9748029414220365e-05 loss: 0.1258 (0.1282) time: 2.9404 data: 0.0079 max mem: 33300 +Epoch: [17] [2300/4276] eta: 1:36:11 lr: 2.9745242176867617e-05 loss: 0.1199 (0.1282) time: 2.9397 data: 0.0084 max mem: 33300 +Epoch: [17] [2310/4276] eta: 1:35:42 lr: 2.974245491049521e-05 loss: 0.1246 (0.1283) time: 2.9282 data: 0.0082 max mem: 33300 +Epoch: [17] [2320/4276] eta: 1:35:13 lr: 2.9739667615099808e-05 loss: 0.1246 (0.1283) time: 2.9036 data: 0.0075 max mem: 33300 +Epoch: [17] [2330/4276] eta: 1:34:44 lr: 2.9736880290678094e-05 loss: 0.1286 (0.1283) time: 2.9151 data: 0.0073 max mem: 33300 +Epoch: [17] [2340/4276] eta: 1:34:15 lr: 2.973409293722674e-05 loss: 0.1320 (0.1284) time: 2.9410 data: 0.0074 max mem: 33300 +Epoch: [17] [2350/4276] eta: 1:33:46 lr: 2.9731305554742417e-05 loss: 0.1222 (0.1284) time: 2.9446 data: 0.0077 max mem: 33300 +Epoch: [17] [2360/4276] eta: 1:33:17 lr: 2.97285181432218e-05 loss: 0.1131 (0.1284) time: 2.9462 data: 0.0077 max mem: 33300 +Epoch: [17] [2370/4276] eta: 1:32:48 lr: 2.9725730702661563e-05 loss: 0.1294 (0.1284) time: 2.9441 data: 0.0074 max mem: 33300 +Epoch: [17] [2380/4276] eta: 1:32:19 lr: 2.9722943233058382e-05 loss: 0.1299 (0.1284) time: 2.9429 data: 0.0074 max mem: 33300 +Epoch: [17] [2390/4276] eta: 1:31:49 lr: 2.9720155734408923e-05 loss: 0.1212 (0.1284) time: 2.9398 data: 0.0075 max mem: 33300 +Epoch: [17] [2400/4276] eta: 1:31:20 lr: 2.971736820670985e-05 loss: 0.1304 (0.1284) time: 2.9360 data: 0.0075 max mem: 33300 +Epoch: [17] [2410/4276] eta: 1:30:51 lr: 2.971458064995785e-05 loss: 0.1311 (0.1284) time: 2.9356 data: 0.0075 max mem: 33300 +Epoch: [17] [2420/4276] eta: 1:30:22 lr: 2.9711793064149573e-05 loss: 0.1217 (0.1284) time: 2.9299 data: 0.0072 max mem: 33300 +Epoch: [17] [2430/4276] eta: 1:29:53 lr: 2.9709005449281695e-05 loss: 0.1271 (0.1284) time: 2.9277 data: 0.0070 max mem: 33300 +Epoch: [17] [2440/4276] eta: 1:29:24 lr: 2.9706217805350883e-05 loss: 0.1358 (0.1284) time: 2.9222 data: 0.0070 max mem: 33300 +Epoch: [17] [2450/4276] eta: 1:28:54 lr: 2.9703430132353804e-05 loss: 0.1193 (0.1284) time: 2.9038 data: 0.0071 max mem: 33300 +Epoch: [17] [2460/4276] eta: 1:28:25 lr: 2.9700642430287123e-05 loss: 0.1219 (0.1284) time: 2.8863 data: 0.0070 max mem: 33300 +Epoch: [17] [2470/4276] eta: 1:27:55 lr: 2.9697854699147513e-05 loss: 0.1272 (0.1284) time: 2.8849 data: 0.0075 max mem: 33300 +Epoch: [17] [2480/4276] eta: 1:27:26 lr: 2.969506693893163e-05 loss: 0.1360 (0.1285) time: 2.8991 data: 0.0078 max mem: 33300 +Epoch: [17] [2490/4276] eta: 1:26:57 lr: 2.969227914963614e-05 loss: 0.1360 (0.1285) time: 2.9057 data: 0.0076 max mem: 33300 +Epoch: [17] [2500/4276] eta: 1:26:27 lr: 2.9689491331257695e-05 loss: 0.1195 (0.1285) time: 2.8931 data: 0.0071 max mem: 33300 +Epoch: [17] [2510/4276] eta: 1:25:58 lr: 2.9686703483792978e-05 loss: 0.1361 (0.1286) time: 2.8889 data: 0.0071 max mem: 33300 +Epoch: [17] [2520/4276] eta: 1:25:28 lr: 2.968391560723863e-05 loss: 0.1223 (0.1285) time: 2.8917 data: 0.0081 max mem: 33300 +Epoch: [17] [2530/4276] eta: 1:24:59 lr: 2.9681127701591325e-05 loss: 0.1100 (0.1285) time: 2.8843 data: 0.0084 max mem: 33300 +Epoch: [17] [2540/4276] eta: 1:24:29 lr: 2.967833976684773e-05 loss: 0.1126 (0.1285) time: 2.8810 data: 0.0077 max mem: 33300 +Epoch: [17] [2550/4276] eta: 1:24:00 lr: 2.9675551803004487e-05 loss: 0.1094 (0.1284) time: 2.8801 data: 0.0073 max mem: 33300 +Epoch: [17] [2560/4276] eta: 1:23:30 lr: 2.9672763810058262e-05 loss: 0.1017 (0.1284) time: 2.8877 data: 0.0075 max mem: 33300 +Epoch: [17] [2570/4276] eta: 1:23:01 lr: 2.9669975788005712e-05 loss: 0.1070 (0.1283) time: 2.8912 data: 0.0075 max mem: 33300 +Epoch: [17] [2580/4276] eta: 1:22:32 lr: 2.9667187736843492e-05 loss: 0.1070 (0.1283) time: 2.8836 data: 0.0070 max mem: 33300 +Epoch: [17] [2590/4276] eta: 1:22:02 lr: 2.9664399656568266e-05 loss: 0.1086 (0.1282) time: 2.8827 data: 0.0071 max mem: 33300 +Epoch: [17] [2600/4276] eta: 1:21:33 lr: 2.9661611547176678e-05 loss: 0.1192 (0.1282) time: 2.8998 data: 0.0070 max mem: 33300 +Epoch: [17] [2610/4276] eta: 1:21:04 lr: 2.9658823408665392e-05 loss: 0.1134 (0.1281) time: 2.9024 data: 0.0072 max mem: 33300 +Epoch: [17] [2620/4276] eta: 1:20:34 lr: 2.9656035241031066e-05 loss: 0.1121 (0.1282) time: 2.8929 data: 0.0075 max mem: 33300 +Epoch: [17] [2630/4276] eta: 1:20:05 lr: 2.9653247044270337e-05 loss: 0.1121 (0.1281) time: 2.9126 data: 0.0079 max mem: 33300 +Epoch: [17] [2640/4276] eta: 1:19:36 lr: 2.9650458818379878e-05 loss: 0.1154 (0.1281) time: 2.9071 data: 0.0078 max mem: 33300 +Epoch: [17] [2650/4276] eta: 1:19:06 lr: 2.9647670563356326e-05 loss: 0.1120 (0.1281) time: 2.8853 data: 0.0069 max mem: 33300 +Epoch: [17] [2660/4276] eta: 1:18:37 lr: 2.9644882279196336e-05 loss: 0.1188 (0.1281) time: 2.8894 data: 0.0071 max mem: 33300 +Epoch: [17] [2670/4276] eta: 1:18:07 lr: 2.9642093965896562e-05 loss: 0.1202 (0.1281) time: 2.8877 data: 0.0073 max mem: 33300 +Epoch: [17] [2680/4276] eta: 1:17:38 lr: 2.963930562345365e-05 loss: 0.1193 (0.1281) time: 2.9023 data: 0.0073 max mem: 33300 +Epoch: [17] [2690/4276] eta: 1:17:09 lr: 2.9636517251864247e-05 loss: 0.1206 (0.1281) time: 2.9029 data: 0.0074 max mem: 33300 +Epoch: [17] [2700/4276] eta: 1:16:39 lr: 2.9633728851125015e-05 loss: 0.1153 (0.1280) time: 2.8821 data: 0.0076 max mem: 33300 +Epoch: [17] [2710/4276] eta: 1:16:10 lr: 2.9630940421232582e-05 loss: 0.1100 (0.1280) time: 2.8832 data: 0.0078 max mem: 33300 +Epoch: [17] [2720/4276] eta: 1:15:41 lr: 2.962815196218361e-05 loss: 0.1099 (0.1279) time: 2.8919 data: 0.0074 max mem: 33300 +Epoch: [17] [2730/4276] eta: 1:15:11 lr: 2.9625363473974736e-05 loss: 0.1198 (0.1280) time: 2.8964 data: 0.0071 max mem: 33300 +Epoch: [17] [2740/4276] eta: 1:14:42 lr: 2.962257495660261e-05 loss: 0.1252 (0.1280) time: 2.8890 data: 0.0070 max mem: 33300 +Epoch: [17] [2750/4276] eta: 1:14:13 lr: 2.961978641006387e-05 loss: 0.1334 (0.1281) time: 2.8807 data: 0.0071 max mem: 33300 +Epoch: [17] [2760/4276] eta: 1:13:43 lr: 2.961699783435517e-05 loss: 0.1221 (0.1281) time: 2.8798 data: 0.0070 max mem: 33300 +Epoch: [17] [2770/4276] eta: 1:13:14 lr: 2.961420922947315e-05 loss: 0.1148 (0.1281) time: 2.8938 data: 0.0070 max mem: 33300 +Epoch: [17] [2780/4276] eta: 1:12:45 lr: 2.9611420595414452e-05 loss: 0.1226 (0.1281) time: 2.9082 data: 0.0072 max mem: 33300 +Epoch: [17] [2790/4276] eta: 1:12:16 lr: 2.9608631932175718e-05 loss: 0.1275 (0.1281) time: 2.9249 data: 0.0073 max mem: 33300 +Epoch: [17] [2800/4276] eta: 1:11:47 lr: 2.9605843239753578e-05 loss: 0.1264 (0.1281) time: 2.9395 data: 0.0076 max mem: 33300 +Epoch: [17] [2810/4276] eta: 1:11:18 lr: 2.9603054518144686e-05 loss: 0.1103 (0.1280) time: 2.9380 data: 0.0076 max mem: 33300 +Epoch: [17] [2820/4276] eta: 1:10:49 lr: 2.9600265767345676e-05 loss: 0.1026 (0.1279) time: 2.9387 data: 0.0082 max mem: 33300 +Epoch: [17] [2830/4276] eta: 1:10:19 lr: 2.9597476987353184e-05 loss: 0.1128 (0.1279) time: 2.9387 data: 0.0086 max mem: 33300 +Epoch: [17] [2840/4276] eta: 1:09:50 lr: 2.9594688178163853e-05 loss: 0.1286 (0.1280) time: 2.9389 data: 0.0080 max mem: 33300 +Epoch: [17] [2850/4276] eta: 1:09:21 lr: 2.9591899339774332e-05 loss: 0.1427 (0.1280) time: 2.9399 data: 0.0076 max mem: 33300 +Epoch: [17] [2860/4276] eta: 1:08:52 lr: 2.9589110472181232e-05 loss: 0.1367 (0.1280) time: 2.9310 data: 0.0077 max mem: 33300 +Epoch: [17] [2870/4276] eta: 1:08:23 lr: 2.958632157538121e-05 loss: 0.1235 (0.1281) time: 2.8986 data: 0.0076 max mem: 33300 +Epoch: [17] [2880/4276] eta: 1:07:54 lr: 2.9583532649370883e-05 loss: 0.1344 (0.1281) time: 2.8890 data: 0.0075 max mem: 33300 +Epoch: [17] [2890/4276] eta: 1:07:24 lr: 2.9580743694146896e-05 loss: 0.1282 (0.1281) time: 2.8979 data: 0.0079 max mem: 33300 +Epoch: [17] [2900/4276] eta: 1:06:55 lr: 2.957795470970588e-05 loss: 0.1173 (0.1280) time: 2.8916 data: 0.0081 max mem: 33300 +Epoch: [17] [2910/4276] eta: 1:06:26 lr: 2.957516569604447e-05 loss: 0.1194 (0.1280) time: 2.8888 data: 0.0075 max mem: 33300 +Epoch: [17] [2920/4276] eta: 1:05:56 lr: 2.95723766531593e-05 loss: 0.1330 (0.1281) time: 2.8891 data: 0.0074 max mem: 33300 +Epoch: [17] [2930/4276] eta: 1:05:27 lr: 2.9569587581046997e-05 loss: 0.1132 (0.1280) time: 2.8924 data: 0.0075 max mem: 33300 +Epoch: [17] [2940/4276] eta: 1:04:58 lr: 2.9566798479704195e-05 loss: 0.1116 (0.1280) time: 2.9174 data: 0.0073 max mem: 33300 +Epoch: [17] [2950/4276] eta: 1:04:29 lr: 2.956400934912752e-05 loss: 0.1131 (0.1280) time: 2.9410 data: 0.0073 max mem: 33300 +Epoch: [17] [2960/4276] eta: 1:04:00 lr: 2.9561220189313597e-05 loss: 0.1103 (0.1280) time: 2.9416 data: 0.0074 max mem: 33300 +Epoch: [17] [2970/4276] eta: 1:03:31 lr: 2.955843100025907e-05 loss: 0.1241 (0.1280) time: 2.9394 data: 0.0071 max mem: 33300 +Epoch: [17] [2980/4276] eta: 1:03:02 lr: 2.9555641781960547e-05 loss: 0.1306 (0.1280) time: 2.9427 data: 0.0069 max mem: 33300 +Epoch: [17] [2990/4276] eta: 1:02:33 lr: 2.955285253441467e-05 loss: 0.1133 (0.1279) time: 2.9516 data: 0.0073 max mem: 33300 +Epoch: [17] [3000/4276] eta: 1:02:03 lr: 2.9550063257618053e-05 loss: 0.1133 (0.1279) time: 2.9493 data: 0.0078 max mem: 33300 +Epoch: [17] [3010/4276] eta: 1:01:34 lr: 2.954727395156734e-05 loss: 0.1186 (0.1279) time: 2.9430 data: 0.0080 max mem: 33300 +Epoch: [17] [3020/4276] eta: 1:01:05 lr: 2.9544484616259137e-05 loss: 0.1219 (0.1279) time: 2.9234 data: 0.0077 max mem: 33300 +Epoch: [17] [3030/4276] eta: 1:00:36 lr: 2.9541695251690082e-05 loss: 0.1225 (0.1280) time: 2.9112 data: 0.0074 max mem: 33300 +Epoch: [17] [3040/4276] eta: 1:00:07 lr: 2.953890585785678e-05 loss: 0.1273 (0.1281) time: 2.9071 data: 0.0074 max mem: 33300 +Epoch: [17] [3050/4276] eta: 0:59:37 lr: 2.9536116434755866e-05 loss: 0.1250 (0.1280) time: 2.8883 data: 0.0071 max mem: 33300 +Epoch: [17] [3060/4276] eta: 0:59:08 lr: 2.9533326982383962e-05 loss: 0.1076 (0.1280) time: 2.8781 data: 0.0069 max mem: 33300 +Epoch: [17] [3070/4276] eta: 0:58:39 lr: 2.9530537500737688e-05 loss: 0.1149 (0.1280) time: 2.8802 data: 0.0074 max mem: 33300 +Epoch: [17] [3080/4276] eta: 0:58:09 lr: 2.952774798981366e-05 loss: 0.1155 (0.1280) time: 2.8832 data: 0.0076 max mem: 33300 +Epoch: [17] [3090/4276] eta: 0:57:40 lr: 2.95249584496085e-05 loss: 0.1095 (0.1279) time: 2.9046 data: 0.0079 max mem: 33300 +Epoch: [17] [3100/4276] eta: 0:57:11 lr: 2.952216888011884e-05 loss: 0.1147 (0.1279) time: 2.9061 data: 0.0080 max mem: 33300 +Epoch: [17] [3110/4276] eta: 0:56:42 lr: 2.9519379281341268e-05 loss: 0.1098 (0.1279) time: 2.8875 data: 0.0078 max mem: 33300 +Epoch: [17] [3120/4276] eta: 0:56:12 lr: 2.9516589653272424e-05 loss: 0.1074 (0.1278) time: 2.8854 data: 0.0076 max mem: 33300 +Epoch: [17] [3130/4276] eta: 0:55:43 lr: 2.951379999590892e-05 loss: 0.1119 (0.1278) time: 2.8822 data: 0.0072 max mem: 33300 +Epoch: [17] [3140/4276] eta: 0:55:14 lr: 2.9511010309247365e-05 loss: 0.1109 (0.1277) time: 2.8849 data: 0.0075 max mem: 33300 +Epoch: [17] [3150/4276] eta: 0:54:44 lr: 2.950822059328438e-05 loss: 0.1250 (0.1277) time: 2.8837 data: 0.0073 max mem: 33300 +Epoch: [17] [3160/4276] eta: 0:54:15 lr: 2.9505430848016585e-05 loss: 0.1272 (0.1277) time: 2.8850 data: 0.0071 max mem: 33300 +Epoch: [17] [3170/4276] eta: 0:53:46 lr: 2.9502641073440586e-05 loss: 0.1254 (0.1277) time: 2.8820 data: 0.0070 max mem: 33300 +Epoch: [17] [3180/4276] eta: 0:53:17 lr: 2.9499851269552997e-05 loss: 0.1248 (0.1277) time: 2.9096 data: 0.0078 max mem: 33300 +Epoch: [17] [3190/4276] eta: 0:52:48 lr: 2.9497061436350425e-05 loss: 0.1248 (0.1277) time: 2.9391 data: 0.0083 max mem: 33300 +Epoch: [17] [3200/4276] eta: 0:52:19 lr: 2.9494271573829484e-05 loss: 0.1248 (0.1277) time: 2.9382 data: 0.0073 max mem: 33300 +Epoch: [17] [3210/4276] eta: 0:51:49 lr: 2.9491481681986794e-05 loss: 0.1248 (0.1277) time: 2.9419 data: 0.0073 max mem: 33300 +Epoch: [17] [3220/4276] eta: 0:51:20 lr: 2.948869176081895e-05 loss: 0.1343 (0.1277) time: 2.9407 data: 0.0072 max mem: 33300 +Epoch: [17] [3230/4276] eta: 0:50:51 lr: 2.948590181032257e-05 loss: 0.1136 (0.1277) time: 2.9253 data: 0.0071 max mem: 33300 +Epoch: [17] [3240/4276] eta: 0:50:22 lr: 2.9483111830494266e-05 loss: 0.1394 (0.1278) time: 2.9020 data: 0.0075 max mem: 33300 +Epoch: [17] [3250/4276] eta: 0:49:53 lr: 2.948032182133063e-05 loss: 0.1387 (0.1277) time: 2.9167 data: 0.0082 max mem: 33300 +Epoch: [17] [3260/4276] eta: 0:49:24 lr: 2.947753178282829e-05 loss: 0.1197 (0.1277) time: 2.9382 data: 0.0077 max mem: 33300 +Epoch: [17] [3270/4276] eta: 0:48:54 lr: 2.9474741714983827e-05 loss: 0.1244 (0.1277) time: 2.9159 data: 0.0075 max mem: 33300 +Epoch: [17] [3280/4276] eta: 0:48:25 lr: 2.947195161779387e-05 loss: 0.1162 (0.1277) time: 2.8977 data: 0.0077 max mem: 33300 +Epoch: [17] [3290/4276] eta: 0:47:56 lr: 2.9469161491255005e-05 loss: 0.1260 (0.1277) time: 2.9058 data: 0.0072 max mem: 33300 +Epoch: [17] [3300/4276] eta: 0:47:27 lr: 2.9466371335363848e-05 loss: 0.1260 (0.1277) time: 2.9063 data: 0.0072 max mem: 33300 +Epoch: [17] [3310/4276] eta: 0:46:58 lr: 2.946358115011699e-05 loss: 0.1341 (0.1278) time: 2.9087 data: 0.0077 max mem: 33300 +Epoch: [17] [3320/4276] eta: 0:46:28 lr: 2.9460790935511058e-05 loss: 0.1427 (0.1278) time: 2.9050 data: 0.0076 max mem: 33300 +Epoch: [17] [3330/4276] eta: 0:45:59 lr: 2.9458000691542626e-05 loss: 0.1293 (0.1278) time: 2.8985 data: 0.0070 max mem: 33300 +Epoch: [17] [3340/4276] eta: 0:45:30 lr: 2.9455210418208307e-05 loss: 0.1293 (0.1278) time: 2.9240 data: 0.0077 max mem: 33300 +Epoch: [17] [3350/4276] eta: 0:45:01 lr: 2.9452420115504697e-05 loss: 0.1142 (0.1278) time: 2.9446 data: 0.0084 max mem: 33300 +Epoch: [17] [3360/4276] eta: 0:44:32 lr: 2.9449629783428402e-05 loss: 0.1122 (0.1278) time: 2.9436 data: 0.0077 max mem: 33300 +Epoch: [17] [3370/4276] eta: 0:44:03 lr: 2.944683942197601e-05 loss: 0.1281 (0.1278) time: 2.9139 data: 0.0076 max mem: 33300 +Epoch: [17] [3380/4276] eta: 0:43:33 lr: 2.9444049031144126e-05 loss: 0.1263 (0.1278) time: 2.8826 data: 0.0078 max mem: 33300 +Epoch: [17] [3390/4276] eta: 0:43:04 lr: 2.944125861092935e-05 loss: 0.1151 (0.1278) time: 2.8895 data: 0.0076 max mem: 33300 +Epoch: [17] [3400/4276] eta: 0:42:35 lr: 2.943846816132827e-05 loss: 0.1183 (0.1278) time: 2.8939 data: 0.0074 max mem: 33300 +Epoch: [17] [3410/4276] eta: 0:42:06 lr: 2.9435677682337488e-05 loss: 0.1243 (0.1279) time: 2.8962 data: 0.0071 max mem: 33300 +Epoch: [17] [3420/4276] eta: 0:41:36 lr: 2.9432887173953593e-05 loss: 0.1295 (0.1279) time: 2.8965 data: 0.0073 max mem: 33300 +Epoch: [17] [3430/4276] eta: 0:41:07 lr: 2.9430096636173182e-05 loss: 0.1254 (0.1279) time: 2.9091 data: 0.0074 max mem: 33300 +Epoch: [17] [3440/4276] eta: 0:40:38 lr: 2.9427306068992848e-05 loss: 0.1174 (0.1279) time: 2.9314 data: 0.0076 max mem: 33300 +Epoch: [17] [3450/4276] eta: 0:40:09 lr: 2.942451547240918e-05 loss: 0.1279 (0.1280) time: 2.9353 data: 0.0079 max mem: 33300 +Epoch: [17] [3460/4276] eta: 0:39:40 lr: 2.942172484641878e-05 loss: 0.1334 (0.1280) time: 2.9366 data: 0.0078 max mem: 33300 +Epoch: [17] [3470/4276] eta: 0:39:11 lr: 2.9418934191018232e-05 loss: 0.1188 (0.1280) time: 2.9369 data: 0.0077 max mem: 33300 +Epoch: [17] [3480/4276] eta: 0:38:42 lr: 2.941614350620412e-05 loss: 0.1163 (0.1280) time: 2.9372 data: 0.0074 max mem: 33300 +Epoch: [17] [3490/4276] eta: 0:38:13 lr: 2.941335279197305e-05 loss: 0.1163 (0.1280) time: 2.9395 data: 0.0077 max mem: 33300 +Epoch: [17] [3500/4276] eta: 0:37:43 lr: 2.9410562048321595e-05 loss: 0.1147 (0.1279) time: 2.9400 data: 0.0078 max mem: 33300 +Epoch: [17] [3510/4276] eta: 0:37:14 lr: 2.9407771275246342e-05 loss: 0.1113 (0.1279) time: 2.9330 data: 0.0077 max mem: 33300 +Epoch: [17] [3520/4276] eta: 0:36:45 lr: 2.9404980472743886e-05 loss: 0.1180 (0.1279) time: 2.9059 data: 0.0079 max mem: 33300 +Epoch: [17] [3530/4276] eta: 0:36:16 lr: 2.9402189640810817e-05 loss: 0.1343 (0.1279) time: 2.8853 data: 0.0079 max mem: 33300 +Epoch: [17] [3540/4276] eta: 0:35:47 lr: 2.9399398779443716e-05 loss: 0.1330 (0.1279) time: 2.9069 data: 0.0079 max mem: 33300 +Epoch: [17] [3550/4276] eta: 0:35:18 lr: 2.9396607888639167e-05 loss: 0.1233 (0.1279) time: 2.9355 data: 0.0081 max mem: 33300 +Epoch: [17] [3560/4276] eta: 0:34:48 lr: 2.939381696839375e-05 loss: 0.1137 (0.1279) time: 2.9259 data: 0.0081 max mem: 33300 +Epoch: [17] [3570/4276] eta: 0:34:19 lr: 2.939102601870406e-05 loss: 0.1367 (0.1280) time: 2.8958 data: 0.0076 max mem: 33300 +Epoch: [17] [3580/4276] eta: 0:33:50 lr: 2.938823503956667e-05 loss: 0.1163 (0.1279) time: 2.9085 data: 0.0077 max mem: 33300 +Epoch: [17] [3590/4276] eta: 0:33:21 lr: 2.938544403097816e-05 loss: 0.1131 (0.1279) time: 2.9362 data: 0.0080 max mem: 33300 +Epoch: [17] [3600/4276] eta: 0:32:52 lr: 2.9382652992935116e-05 loss: 0.1268 (0.1279) time: 2.9382 data: 0.0075 max mem: 33300 +Epoch: [17] [3610/4276] eta: 0:32:23 lr: 2.937986192543412e-05 loss: 0.1356 (0.1279) time: 2.9407 data: 0.0071 max mem: 33300 +Epoch: [17] [3620/4276] eta: 0:31:53 lr: 2.9377070828471747e-05 loss: 0.1301 (0.1279) time: 2.9433 data: 0.0072 max mem: 33300 +Epoch: [17] [3630/4276] eta: 0:31:24 lr: 2.9374279702044587e-05 loss: 0.1193 (0.1279) time: 2.9416 data: 0.0072 max mem: 33300 +Epoch: [17] [3640/4276] eta: 0:30:55 lr: 2.9371488546149205e-05 loss: 0.1157 (0.1278) time: 2.9419 data: 0.0072 max mem: 33300 +Epoch: [17] [3650/4276] eta: 0:30:26 lr: 2.9368697360782182e-05 loss: 0.1023 (0.1278) time: 2.9409 data: 0.0072 max mem: 33300 +Epoch: [17] [3660/4276] eta: 0:29:57 lr: 2.9365906145940097e-05 loss: 0.1134 (0.1278) time: 2.9385 data: 0.0075 max mem: 33300 +Epoch: [17] [3670/4276] eta: 0:29:28 lr: 2.936311490161952e-05 loss: 0.1186 (0.1278) time: 2.9302 data: 0.0076 max mem: 33300 +Epoch: [17] [3680/4276] eta: 0:28:58 lr: 2.9360323627817026e-05 loss: 0.1188 (0.1278) time: 2.9023 data: 0.0075 max mem: 33300 +Epoch: [17] [3690/4276] eta: 0:28:29 lr: 2.9357532324529204e-05 loss: 0.1245 (0.1278) time: 2.8915 data: 0.0078 max mem: 33300 +Epoch: [17] [3700/4276] eta: 0:28:00 lr: 2.9354740991752617e-05 loss: 0.1225 (0.1278) time: 2.9187 data: 0.0077 max mem: 33300 +Epoch: [17] [3710/4276] eta: 0:27:31 lr: 2.9351949629483827e-05 loss: 0.1178 (0.1278) time: 2.9382 data: 0.0072 max mem: 33300 +Epoch: [17] [3720/4276] eta: 0:27:02 lr: 2.9349158237719426e-05 loss: 0.1112 (0.1277) time: 2.9371 data: 0.0069 max mem: 33300 +Epoch: [17] [3730/4276] eta: 0:26:33 lr: 2.9346366816455974e-05 loss: 0.1229 (0.1277) time: 2.9428 data: 0.0069 max mem: 33300 +Epoch: [17] [3740/4276] eta: 0:26:04 lr: 2.934357536569004e-05 loss: 0.1180 (0.1277) time: 2.9443 data: 0.0071 max mem: 33300 +Epoch: [17] [3750/4276] eta: 0:25:34 lr: 2.93407838854182e-05 loss: 0.1096 (0.1277) time: 2.9391 data: 0.0070 max mem: 33300 +Epoch: [17] [3760/4276] eta: 0:25:05 lr: 2.9337992375637012e-05 loss: 0.1085 (0.1277) time: 2.9401 data: 0.0070 max mem: 33300 +Epoch: [17] [3770/4276] eta: 0:24:36 lr: 2.9335200836343063e-05 loss: 0.1141 (0.1278) time: 2.9377 data: 0.0075 max mem: 33300 +Epoch: [17] [3780/4276] eta: 0:24:07 lr: 2.9332409267532905e-05 loss: 0.1181 (0.1277) time: 2.9193 data: 0.0078 max mem: 33300 +Epoch: [17] [3790/4276] eta: 0:23:38 lr: 2.9329617669203114e-05 loss: 0.1103 (0.1277) time: 2.9138 data: 0.0078 max mem: 33300 +Epoch: [17] [3800/4276] eta: 0:23:09 lr: 2.9326826041350247e-05 loss: 0.1295 (0.1277) time: 2.9327 data: 0.0075 max mem: 33300 +Epoch: [17] [3810/4276] eta: 0:22:39 lr: 2.9324034383970872e-05 loss: 0.1186 (0.1277) time: 2.9392 data: 0.0073 max mem: 33300 +Epoch: [17] [3820/4276] eta: 0:22:10 lr: 2.9321242697061557e-05 loss: 0.1075 (0.1277) time: 2.9101 data: 0.0076 max mem: 33300 +Epoch: [17] [3830/4276] eta: 0:21:41 lr: 2.9318450980618863e-05 loss: 0.1107 (0.1277) time: 2.9048 data: 0.0079 max mem: 33300 +Epoch: [17] [3840/4276] eta: 0:21:12 lr: 2.9315659234639354e-05 loss: 0.1206 (0.1276) time: 2.9340 data: 0.0082 max mem: 33300 +Epoch: [17] [3850/4276] eta: 0:20:43 lr: 2.9312867459119587e-05 loss: 0.1128 (0.1276) time: 2.9378 data: 0.0079 max mem: 33300 +Epoch: [17] [3860/4276] eta: 0:20:14 lr: 2.9310075654056135e-05 loss: 0.1151 (0.1276) time: 2.9384 data: 0.0078 max mem: 33300 +Epoch: [17] [3870/4276] eta: 0:19:44 lr: 2.9307283819445548e-05 loss: 0.1197 (0.1275) time: 2.9419 data: 0.0084 max mem: 33300 +Epoch: [17] [3880/4276] eta: 0:19:15 lr: 2.930449195528439e-05 loss: 0.1153 (0.1275) time: 2.9402 data: 0.0085 max mem: 33300 +Epoch: [17] [3890/4276] eta: 0:18:46 lr: 2.9301700061569217e-05 loss: 0.1153 (0.1275) time: 2.9386 data: 0.0082 max mem: 33300 +Epoch: [17] [3900/4276] eta: 0:18:17 lr: 2.9298908138296587e-05 loss: 0.1222 (0.1275) time: 2.9402 data: 0.0082 max mem: 33300 +Epoch: [17] [3910/4276] eta: 0:17:48 lr: 2.9296116185463064e-05 loss: 0.1146 (0.1275) time: 2.9415 data: 0.0080 max mem: 33300 +Epoch: [17] [3920/4276] eta: 0:17:19 lr: 2.9293324203065194e-05 loss: 0.1079 (0.1275) time: 2.9409 data: 0.0080 max mem: 33300 +Epoch: [17] [3930/4276] eta: 0:16:49 lr: 2.9290532191099545e-05 loss: 0.1173 (0.1274) time: 2.9415 data: 0.0084 max mem: 33300 +Epoch: [17] [3940/4276] eta: 0:16:20 lr: 2.928774014956267e-05 loss: 0.1195 (0.1275) time: 2.9419 data: 0.0085 max mem: 33300 +Epoch: [17] [3950/4276] eta: 0:15:51 lr: 2.9284948078451114e-05 loss: 0.1195 (0.1274) time: 2.9418 data: 0.0082 max mem: 33300 +Epoch: [17] [3960/4276] eta: 0:15:22 lr: 2.9282155977761443e-05 loss: 0.1132 (0.1274) time: 2.9443 data: 0.0080 max mem: 33300 +Epoch: [17] [3970/4276] eta: 0:14:53 lr: 2.9279363847490198e-05 loss: 0.1242 (0.1274) time: 2.9423 data: 0.0082 max mem: 33300 +Epoch: [17] [3980/4276] eta: 0:14:24 lr: 2.9276571687633934e-05 loss: 0.1240 (0.1274) time: 2.9385 data: 0.0079 max mem: 33300 +Epoch: [17] [3990/4276] eta: 0:13:54 lr: 2.9273779498189214e-05 loss: 0.1217 (0.1274) time: 2.9123 data: 0.0072 max mem: 33300 +Epoch: [17] [4000/4276] eta: 0:13:25 lr: 2.9270987279152572e-05 loss: 0.1151 (0.1274) time: 2.8924 data: 0.0071 max mem: 33300 +Epoch: [17] [4010/4276] eta: 0:12:56 lr: 2.9268195030520574e-05 loss: 0.1167 (0.1274) time: 2.9048 data: 0.0075 max mem: 33300 +Epoch: [17] [4020/4276] eta: 0:12:27 lr: 2.9265402752289756e-05 loss: 0.1190 (0.1274) time: 2.9242 data: 0.0079 max mem: 33300 +Epoch: [17] [4030/4276] eta: 0:11:58 lr: 2.9262610444456674e-05 loss: 0.1230 (0.1274) time: 2.9368 data: 0.0077 max mem: 33300 +Epoch: [17] [4040/4276] eta: 0:11:28 lr: 2.9259818107017866e-05 loss: 0.1303 (0.1274) time: 2.9380 data: 0.0075 max mem: 33300 +Epoch: [17] [4050/4276] eta: 0:10:59 lr: 2.925702573996989e-05 loss: 0.1219 (0.1274) time: 2.9419 data: 0.0078 max mem: 33300 +Epoch: [17] [4060/4276] eta: 0:10:30 lr: 2.9254233343309283e-05 loss: 0.1175 (0.1274) time: 2.9270 data: 0.0076 max mem: 33300 +Epoch: [17] [4070/4276] eta: 0:10:01 lr: 2.9251440917032596e-05 loss: 0.1384 (0.1275) time: 2.8970 data: 0.0075 max mem: 33300 +Epoch: [17] [4080/4276] eta: 0:09:32 lr: 2.9248648461136376e-05 loss: 0.1326 (0.1275) time: 2.9123 data: 0.0080 max mem: 33300 +Epoch: [17] [4090/4276] eta: 0:09:02 lr: 2.9245855975617164e-05 loss: 0.1226 (0.1275) time: 2.9398 data: 0.0082 max mem: 33300 +Epoch: [17] [4100/4276] eta: 0:08:33 lr: 2.924306346047149e-05 loss: 0.1398 (0.1275) time: 2.9413 data: 0.0080 max mem: 33300 +Epoch: [17] [4110/4276] eta: 0:08:04 lr: 2.924027091569592e-05 loss: 0.1210 (0.1275) time: 2.9406 data: 0.0080 max mem: 33300 +Epoch: [17] [4120/4276] eta: 0:07:35 lr: 2.9237478341286985e-05 loss: 0.1259 (0.1276) time: 2.9387 data: 0.0081 max mem: 33300 +Epoch: [17] [4130/4276] eta: 0:07:06 lr: 2.9234685737241213e-05 loss: 0.1318 (0.1275) time: 2.9393 data: 0.0081 max mem: 33300 +Epoch: [17] [4140/4276] eta: 0:06:37 lr: 2.923189310355516e-05 loss: 0.1302 (0.1275) time: 2.9383 data: 0.0080 max mem: 33300 +Epoch: [17] [4150/4276] eta: 0:06:07 lr: 2.9229100440225355e-05 loss: 0.1302 (0.1276) time: 2.9373 data: 0.0079 max mem: 33300 +Epoch: [17] [4160/4276] eta: 0:05:38 lr: 2.9226307747248344e-05 loss: 0.1301 (0.1276) time: 2.9375 data: 0.0079 max mem: 33300 +Epoch: [17] [4170/4276] eta: 0:05:09 lr: 2.9223515024620663e-05 loss: 0.1316 (0.1276) time: 2.9355 data: 0.0082 max mem: 33300 +Epoch: [17] [4180/4276] eta: 0:04:40 lr: 2.9220722272338846e-05 loss: 0.1307 (0.1276) time: 2.9338 data: 0.0077 max mem: 33300 +Epoch: [17] [4190/4276] eta: 0:04:11 lr: 2.921792949039943e-05 loss: 0.1204 (0.1276) time: 2.9361 data: 0.0071 max mem: 33300 +Epoch: [17] [4200/4276] eta: 0:03:41 lr: 2.9215136678798956e-05 loss: 0.1270 (0.1276) time: 2.9380 data: 0.0074 max mem: 33300 +Epoch: [17] [4210/4276] eta: 0:03:12 lr: 2.9212343837533946e-05 loss: 0.1371 (0.1277) time: 2.9386 data: 0.0073 max mem: 33300 +Epoch: [17] [4220/4276] eta: 0:02:43 lr: 2.9209550966600933e-05 loss: 0.1382 (0.1277) time: 2.9380 data: 0.0071 max mem: 33300 +Epoch: [17] [4230/4276] eta: 0:02:14 lr: 2.920675806599647e-05 loss: 0.1384 (0.1277) time: 2.9371 data: 0.0070 max mem: 33300 +Epoch: [17] [4240/4276] eta: 0:01:45 lr: 2.920396513571707e-05 loss: 0.1384 (0.1277) time: 2.9346 data: 0.0071 max mem: 33300 +Epoch: [17] [4250/4276] eta: 0:01:15 lr: 2.9201172175759277e-05 loss: 0.1335 (0.1278) time: 2.9285 data: 0.0072 max mem: 33300 +Epoch: [17] [4260/4276] eta: 0:00:46 lr: 2.9198379186119607e-05 loss: 0.1376 (0.1279) time: 2.9216 data: 0.0070 max mem: 33300 +Epoch: [17] [4270/4276] eta: 0:00:17 lr: 2.9195586166794608e-05 loss: 0.1376 (0.1279) time: 2.9182 data: 0.0069 max mem: 33300 +Epoch: [17] Total time: 3:28:05 +Test: [ 0/21770] eta: 7:26:47 time: 1.2314 data: 1.1765 max mem: 33300 +Test: [ 100/21770] eta: 0:18:22 time: 0.0385 data: 0.0008 max mem: 33300 +Test: [ 200/21770] eta: 0:16:05 time: 0.0387 data: 0.0008 max mem: 33300 +Test: [ 300/21770] eta: 0:15:18 time: 0.0386 data: 0.0008 max mem: 33300 +Test: [ 400/21770] eta: 0:14:52 time: 0.0388 data: 0.0008 max mem: 33300 +Test: [ 500/21770] eta: 0:14:35 time: 0.0388 data: 0.0008 max mem: 33300 +Test: [ 600/21770] eta: 0:14:23 time: 0.0388 data: 0.0008 max mem: 33300 +Test: [ 700/21770] eta: 0:14:13 time: 0.0390 data: 0.0008 max mem: 33300 +Test: [ 800/21770] eta: 0:14:06 time: 0.0393 data: 0.0008 max mem: 33300 +Test: [ 900/21770] eta: 0:13:59 time: 0.0392 data: 0.0008 max mem: 33300 +Test: [ 1000/21770] eta: 0:13:53 time: 0.0391 data: 0.0008 max mem: 33300 +Test: [ 1100/21770] eta: 0:13:47 time: 0.0391 data: 0.0008 max mem: 33300 +Test: [ 1200/21770] eta: 0:13:41 time: 0.0392 data: 0.0008 max mem: 33300 +Test: [ 1300/21770] eta: 0:13:36 time: 0.0393 data: 0.0008 max mem: 33300 +Test: [ 1400/21770] eta: 0:13:31 time: 0.0393 data: 0.0008 max mem: 33300 +Test: [ 1500/21770] eta: 0:13:26 time: 0.0393 data: 0.0008 max mem: 33300 +Test: [ 1600/21770] eta: 0:13:22 time: 0.0392 data: 0.0008 max mem: 33300 +Test: [ 1700/21770] eta: 0:13:17 time: 0.0390 data: 0.0008 max mem: 33300 +Test: [ 1800/21770] eta: 0:13:12 time: 0.0393 data: 0.0008 max mem: 33300 +Test: [ 1900/21770] eta: 0:13:08 time: 0.0394 data: 0.0008 max mem: 33300 +Test: [ 2000/21770] eta: 0:13:03 time: 0.0394 data: 0.0008 max mem: 33300 +Test: [ 2100/21770] eta: 0:12:59 time: 0.0394 data: 0.0008 max mem: 33300 +Test: [ 2200/21770] eta: 0:12:55 time: 0.0391 data: 0.0008 max mem: 33300 +Test: [ 2300/21770] eta: 0:12:51 time: 0.0398 data: 0.0009 max mem: 33300 +Test: [ 2400/21770] eta: 0:12:47 time: 0.0395 data: 0.0008 max mem: 33300 +Test: [ 2500/21770] eta: 0:12:43 time: 0.0395 data: 0.0008 max mem: 33300 +Test: [ 2600/21770] eta: 0:12:39 time: 0.0395 data: 0.0008 max mem: 33300 +Test: [ 2700/21770] eta: 0:12:35 time: 0.0392 data: 0.0008 max mem: 33300 +Test: [ 2800/21770] eta: 0:12:31 time: 0.0399 data: 0.0008 max mem: 33300 +Test: [ 2900/21770] eta: 0:12:27 time: 0.0394 data: 0.0008 max mem: 33300 +Test: [ 3000/21770] eta: 0:12:23 time: 0.0394 data: 0.0008 max mem: 33300 +Test: [ 3100/21770] eta: 0:12:19 time: 0.0400 data: 0.0008 max mem: 33300 +Test: [ 3200/21770] eta: 0:12:16 time: 0.0400 data: 0.0008 max mem: 33300 +Test: [ 3300/21770] eta: 0:12:12 time: 0.0397 data: 0.0008 max mem: 33300 +Test: [ 3400/21770] eta: 0:12:08 time: 0.0399 data: 0.0008 max mem: 33300 +Test: [ 3500/21770] eta: 0:12:04 time: 0.0392 data: 0.0008 max mem: 33300 +Test: [ 3600/21770] eta: 0:12:00 time: 0.0394 data: 0.0008 max mem: 33300 +Test: [ 3700/21770] eta: 0:11:56 time: 0.0400 data: 0.0008 max mem: 33300 +Test: [ 3800/21770] eta: 0:11:52 time: 0.0392 data: 0.0008 max mem: 33300 +Test: [ 3900/21770] eta: 0:11:48 time: 0.0393 data: 0.0009 max mem: 33300 +Test: [ 4000/21770] eta: 0:11:44 time: 0.0394 data: 0.0008 max mem: 33300 +Test: [ 4100/21770] eta: 0:11:40 time: 0.0392 data: 0.0008 max mem: 33300 +Test: [ 4200/21770] eta: 0:11:36 time: 0.0392 data: 0.0008 max mem: 33300 +Test: [ 4300/21770] eta: 0:11:32 time: 0.0392 data: 0.0008 max mem: 33300 +Test: [ 4400/21770] eta: 0:11:28 time: 0.0393 data: 0.0008 max mem: 33300 +Test: [ 4500/21770] eta: 0:11:24 time: 0.0393 data: 0.0008 max mem: 33300 +Test: [ 4600/21770] eta: 0:11:19 time: 0.0392 data: 0.0008 max mem: 33300 +Test: [ 4700/21770] eta: 0:11:16 time: 0.0400 data: 0.0008 max mem: 33300 +Test: [ 4800/21770] eta: 0:11:12 time: 0.0393 data: 0.0008 max mem: 33300 +Test: [ 4900/21770] eta: 0:11:08 time: 0.0400 data: 0.0008 max mem: 33300 +Test: [ 5000/21770] eta: 0:11:04 time: 0.0400 data: 0.0008 max mem: 33300 +Test: [ 5100/21770] eta: 0:11:00 time: 0.0399 data: 0.0008 max mem: 33300 +Test: [ 5200/21770] eta: 0:10:56 time: 0.0400 data: 0.0008 max mem: 33300 +Test: [ 5300/21770] eta: 0:10:52 time: 0.0394 data: 0.0008 max mem: 33300 +Test: [ 5400/21770] eta: 0:10:49 time: 0.0399 data: 0.0009 max mem: 33300 +Test: [ 5500/21770] eta: 0:10:45 time: 0.0400 data: 0.0008 max mem: 33300 +Test: [ 5600/21770] eta: 0:10:41 time: 0.0400 data: 0.0008 max mem: 33300 +Test: [ 5700/21770] eta: 0:10:37 time: 0.0395 data: 0.0008 max mem: 33300 +Test: [ 5800/21770] eta: 0:10:33 time: 0.0400 data: 0.0008 max mem: 33300 +Test: [ 5900/21770] eta: 0:10:29 time: 0.0398 data: 0.0008 max mem: 33300 +Test: [ 6000/21770] eta: 0:10:25 time: 0.0394 data: 0.0008 max mem: 33300 +Test: [ 6100/21770] eta: 0:10:21 time: 0.0398 data: 0.0008 max mem: 33300 +Test: [ 6200/21770] eta: 0:10:17 time: 0.0399 data: 0.0008 max mem: 33300 +Test: [ 6300/21770] eta: 0:10:13 time: 0.0401 data: 0.0008 max mem: 33300 +Test: [ 6400/21770] eta: 0:10:09 time: 0.0401 data: 0.0008 max mem: 33300 +Test: [ 6500/21770] eta: 0:10:05 time: 0.0400 data: 0.0008 max mem: 33300 +Test: [ 6600/21770] eta: 0:10:02 time: 0.0400 data: 0.0008 max mem: 33300 +Test: [ 6700/21770] eta: 0:09:58 time: 0.0394 data: 0.0008 max mem: 33300 +Test: [ 6800/21770] eta: 0:09:54 time: 0.0399 data: 0.0008 max mem: 33300 +Test: [ 6900/21770] eta: 0:09:50 time: 0.0399 data: 0.0008 max mem: 33300 +Test: [ 7000/21770] eta: 0:09:46 time: 0.0399 data: 0.0008 max mem: 33300 +Test: [ 7100/21770] eta: 0:09:42 time: 0.0391 data: 0.0008 max mem: 33300 +Test: [ 7200/21770] eta: 0:09:38 time: 0.0395 data: 0.0008 max mem: 33300 +Test: [ 7300/21770] eta: 0:09:34 time: 0.0392 data: 0.0008 max mem: 33300 +Test: [ 7400/21770] eta: 0:09:30 time: 0.0393 data: 0.0008 max mem: 33300 +Test: [ 7500/21770] eta: 0:09:26 time: 0.0393 data: 0.0008 max mem: 33300 +Test: [ 7600/21770] eta: 0:09:22 time: 0.0397 data: 0.0008 max mem: 33300 +Test: [ 7700/21770] eta: 0:09:18 time: 0.0394 data: 0.0008 max mem: 33300 +Test: [ 7800/21770] eta: 0:09:14 time: 0.0393 data: 0.0008 max mem: 33300 +Test: [ 7900/21770] eta: 0:09:10 time: 0.0395 data: 0.0008 max mem: 33300 +Test: [ 8000/21770] eta: 0:09:06 time: 0.0396 data: 0.0008 max mem: 33300 +Test: [ 8100/21770] eta: 0:09:02 time: 0.0396 data: 0.0008 max mem: 33300 +Test: [ 8200/21770] eta: 0:08:57 time: 0.0393 data: 0.0008 max mem: 33300 +Test: [ 8300/21770] eta: 0:08:53 time: 0.0393 data: 0.0008 max mem: 33300 +Test: [ 8400/21770] eta: 0:08:49 time: 0.0396 data: 0.0008 max mem: 33300 +Test: [ 8500/21770] eta: 0:08:45 time: 0.0396 data: 0.0009 max mem: 33300 +Test: [ 8600/21770] eta: 0:08:41 time: 0.0393 data: 0.0008 max mem: 33300 +Test: [ 8700/21770] eta: 0:08:37 time: 0.0392 data: 0.0008 max mem: 33300 +Test: [ 8800/21770] eta: 0:08:33 time: 0.0393 data: 0.0008 max mem: 33300 +Test: [ 8900/21770] eta: 0:08:29 time: 0.0395 data: 0.0008 max mem: 33300 +Test: [ 9000/21770] eta: 0:08:25 time: 0.0396 data: 0.0008 max mem: 33300 +Test: [ 9100/21770] eta: 0:08:21 time: 0.0394 data: 0.0008 max mem: 33300 +Test: [ 9200/21770] eta: 0:08:17 time: 0.0391 data: 0.0008 max mem: 33300 +Test: [ 9300/21770] eta: 0:08:13 time: 0.0388 data: 0.0008 max mem: 33300 +Test: [ 9400/21770] eta: 0:08:09 time: 0.0391 data: 0.0008 max mem: 33300 +Test: [ 9500/21770] eta: 0:08:05 time: 0.0389 data: 0.0008 max mem: 33300 +Test: [ 9600/21770] eta: 0:08:01 time: 0.0391 data: 0.0008 max mem: 33300 +Test: [ 9700/21770] eta: 0:07:57 time: 0.0389 data: 0.0008 max mem: 33300 +Test: [ 9800/21770] eta: 0:07:53 time: 0.0390 data: 0.0008 max mem: 33300 +Test: [ 9900/21770] eta: 0:07:49 time: 0.0390 data: 0.0008 max mem: 33300 +Test: [10000/21770] eta: 0:07:45 time: 0.0391 data: 0.0008 max mem: 33300 +Test: [10100/21770] eta: 0:07:41 time: 0.0390 data: 0.0008 max mem: 33300 +Test: [10200/21770] eta: 0:07:37 time: 0.0393 data: 0.0008 max mem: 33300 +Test: [10300/21770] eta: 0:07:33 time: 0.0391 data: 0.0008 max mem: 33300 +Test: [10400/21770] eta: 0:07:29 time: 0.0390 data: 0.0008 max mem: 33300 +Test: [10500/21770] eta: 0:07:25 time: 0.0390 data: 0.0008 max mem: 33300 +Test: [10600/21770] eta: 0:07:21 time: 0.0393 data: 0.0008 max mem: 33300 +Test: [10700/21770] eta: 0:07:17 time: 0.0388 data: 0.0008 max mem: 33300 +Test: [10800/21770] eta: 0:07:13 time: 0.0392 data: 0.0008 max mem: 33300 +Test: [10900/21770] eta: 0:07:09 time: 0.0390 data: 0.0008 max mem: 33300 +Test: [11000/21770] eta: 0:07:05 time: 0.0392 data: 0.0008 max mem: 33300 +Test: [11100/21770] eta: 0:07:01 time: 0.0390 data: 0.0008 max mem: 33300 +Test: [11200/21770] eta: 0:06:57 time: 0.0395 data: 0.0008 max mem: 33300 +Test: [11300/21770] eta: 0:06:53 time: 0.0397 data: 0.0008 max mem: 33300 +Test: [11400/21770] eta: 0:06:49 time: 0.0394 data: 0.0008 max mem: 33300 +Test: [11500/21770] eta: 0:06:45 time: 0.0394 data: 0.0008 max mem: 33300 +Test: [11600/21770] eta: 0:06:41 time: 0.0394 data: 0.0008 max mem: 33300 +Test: [11700/21770] eta: 0:06:37 time: 0.0392 data: 0.0008 max mem: 33300 +Test: [11800/21770] eta: 0:06:33 time: 0.0394 data: 0.0008 max mem: 33300 +Test: [11900/21770] eta: 0:06:29 time: 0.0396 data: 0.0008 max mem: 33300 +Test: [12000/21770] eta: 0:06:25 time: 0.0395 data: 0.0008 max mem: 33300 +Test: [12100/21770] eta: 0:06:22 time: 0.0393 data: 0.0008 max mem: 33300 +Test: [12200/21770] eta: 0:06:18 time: 0.0393 data: 0.0008 max mem: 33300 +Test: [12300/21770] eta: 0:06:14 time: 0.0391 data: 0.0008 max mem: 33300 +Test: [12400/21770] eta: 0:06:10 time: 0.0393 data: 0.0008 max mem: 33300 +Test: [12500/21770] eta: 0:06:06 time: 0.0392 data: 0.0008 max mem: 33300 +Test: [12600/21770] eta: 0:06:02 time: 0.0397 data: 0.0008 max mem: 33300 +Test: [12700/21770] eta: 0:05:58 time: 0.0395 data: 0.0008 max mem: 33300 +Test: [12800/21770] eta: 0:05:54 time: 0.0393 data: 0.0008 max mem: 33300 +Test: [12900/21770] eta: 0:05:50 time: 0.0395 data: 0.0008 max mem: 33300 +Test: [13000/21770] eta: 0:05:46 time: 0.0397 data: 0.0008 max mem: 33300 +Test: [13100/21770] eta: 0:05:42 time: 0.0395 data: 0.0008 max mem: 33300 +Test: [13200/21770] eta: 0:05:38 time: 0.0395 data: 0.0009 max mem: 33300 +Test: [13300/21770] eta: 0:05:34 time: 0.0392 data: 0.0008 max mem: 33300 +Test: [13400/21770] eta: 0:05:30 time: 0.0397 data: 0.0008 max mem: 33300 +Test: [13500/21770] eta: 0:05:26 time: 0.0395 data: 0.0008 max mem: 33300 +Test: [13600/21770] eta: 0:05:22 time: 0.0395 data: 0.0008 max mem: 33300 +Test: [13700/21770] eta: 0:05:18 time: 0.0393 data: 0.0008 max mem: 33300 +Test: [13800/21770] eta: 0:05:14 time: 0.0395 data: 0.0008 max mem: 33300 +Test: [13900/21770] eta: 0:05:10 time: 0.0393 data: 0.0008 max mem: 33300 +Test: [14000/21770] eta: 0:05:06 time: 0.0396 data: 0.0008 max mem: 33300 +Test: [14100/21770] eta: 0:05:02 time: 0.0395 data: 0.0008 max mem: 33300 +Test: [14200/21770] eta: 0:04:58 time: 0.0398 data: 0.0008 max mem: 33300 +Test: [14300/21770] eta: 0:04:55 time: 0.0394 data: 0.0008 max mem: 33300 +Test: [14400/21770] eta: 0:04:51 time: 0.0395 data: 0.0008 max mem: 33300 +Test: [14500/21770] eta: 0:04:47 time: 0.0394 data: 0.0008 max mem: 33300 +Test: [14600/21770] eta: 0:04:43 time: 0.0396 data: 0.0008 max mem: 33300 +Test: [14700/21770] eta: 0:04:39 time: 0.0397 data: 0.0008 max mem: 33300 +Test: [14800/21770] eta: 0:04:35 time: 0.0394 data: 0.0008 max mem: 33300 +Test: [14900/21770] eta: 0:04:31 time: 0.0397 data: 0.0008 max mem: 33300 +Test: [15000/21770] eta: 0:04:27 time: 0.0395 data: 0.0008 max mem: 33300 +Test: [15100/21770] eta: 0:04:23 time: 0.0393 data: 0.0008 max mem: 33300 +Test: [15200/21770] eta: 0:04:19 time: 0.0397 data: 0.0008 max mem: 33300 +Test: [15300/21770] eta: 0:04:15 time: 0.0395 data: 0.0008 max mem: 33300 +Test: [15400/21770] eta: 0:04:11 time: 0.0394 data: 0.0008 max mem: 33300 +Test: [15500/21770] eta: 0:04:07 time: 0.0393 data: 0.0008 max mem: 33300 +Test: [15600/21770] eta: 0:04:03 time: 0.0396 data: 0.0008 max mem: 33300 +Test: [15700/21770] eta: 0:03:59 time: 0.0393 data: 0.0008 max mem: 33300 +Test: [15800/21770] eta: 0:03:55 time: 0.0398 data: 0.0008 max mem: 33300 +Test: [15900/21770] eta: 0:03:51 time: 0.0397 data: 0.0008 max mem: 33300 +Test: [16000/21770] eta: 0:03:47 time: 0.0397 data: 0.0008 max mem: 33300 +Test: [16100/21770] eta: 0:03:43 time: 0.0393 data: 0.0008 max mem: 33300 +Test: [16200/21770] eta: 0:03:40 time: 0.0393 data: 0.0008 max mem: 33300 +Test: [16300/21770] eta: 0:03:36 time: 0.0395 data: 0.0009 max mem: 33300 +Test: [16400/21770] eta: 0:03:32 time: 0.0395 data: 0.0008 max mem: 33300 +Test: [16500/21770] eta: 0:03:28 time: 0.0393 data: 0.0008 max mem: 33300 +Test: [16600/21770] eta: 0:03:24 time: 0.0390 data: 0.0008 max mem: 33300 +Test: [16700/21770] eta: 0:03:20 time: 0.0390 data: 0.0008 max mem: 33300 +Test: [16800/21770] eta: 0:03:16 time: 0.0389 data: 0.0008 max mem: 33300 +Test: [16900/21770] eta: 0:03:12 time: 0.0391 data: 0.0008 max mem: 33300 +Test: [17000/21770] eta: 0:03:08 time: 0.0390 data: 0.0008 max mem: 33300 +Test: [17100/21770] eta: 0:03:04 time: 0.0390 data: 0.0008 max mem: 33300 +Test: [17200/21770] eta: 0:03:00 time: 0.0390 data: 0.0008 max mem: 33300 +Test: [17300/21770] eta: 0:02:56 time: 0.0389 data: 0.0008 max mem: 33300 +Test: [17400/21770] eta: 0:02:52 time: 0.0386 data: 0.0008 max mem: 33300 +Test: [17500/21770] eta: 0:02:48 time: 0.0384 data: 0.0008 max mem: 33300 +Test: [17600/21770] eta: 0:02:44 time: 0.0385 data: 0.0008 max mem: 33300 +Test: [17700/21770] eta: 0:02:40 time: 0.0384 data: 0.0008 max mem: 33300 +Test: [17800/21770] eta: 0:02:36 time: 0.0380 data: 0.0008 max mem: 33300 +Test: [17900/21770] eta: 0:02:32 time: 0.0383 data: 0.0009 max mem: 33300 +Test: [18000/21770] eta: 0:02:28 time: 0.0383 data: 0.0008 max mem: 33300 +Test: [18100/21770] eta: 0:02:24 time: 0.0383 data: 0.0008 max mem: 33300 +Test: [18200/21770] eta: 0:02:20 time: 0.0384 data: 0.0008 max mem: 33300 +Test: [18300/21770] eta: 0:02:16 time: 0.0384 data: 0.0008 max mem: 33300 +Test: [18400/21770] eta: 0:02:12 time: 0.0384 data: 0.0008 max mem: 33300 +Test: [18500/21770] eta: 0:02:08 time: 0.0384 data: 0.0008 max mem: 33300 +Test: [18600/21770] eta: 0:02:04 time: 0.0384 data: 0.0008 max mem: 33300 +Test: [18700/21770] eta: 0:02:00 time: 0.0383 data: 0.0008 max mem: 33300 +Test: [18800/21770] eta: 0:01:56 time: 0.0383 data: 0.0008 max mem: 33300 +Test: [18900/21770] eta: 0:01:53 time: 0.0383 data: 0.0008 max mem: 33300 +Test: [19000/21770] eta: 0:01:49 time: 0.0383 data: 0.0008 max mem: 33300 +Test: [19100/21770] eta: 0:01:45 time: 0.0383 data: 0.0008 max mem: 33300 +Test: [19200/21770] eta: 0:01:41 time: 0.0383 data: 0.0008 max mem: 33300 +Test: [19300/21770] eta: 0:01:37 time: 0.0383 data: 0.0008 max mem: 33300 +Test: [19400/21770] eta: 0:01:33 time: 0.0384 data: 0.0008 max mem: 33300 +Test: [19500/21770] eta: 0:01:29 time: 0.0387 data: 0.0008 max mem: 33300 +Test: [19600/21770] eta: 0:01:25 time: 0.0388 data: 0.0008 max mem: 33300 +Test: [19700/21770] eta: 0:01:21 time: 0.0390 data: 0.0008 max mem: 33300 +Test: [19800/21770] eta: 0:01:17 time: 0.0391 data: 0.0008 max mem: 33300 +Test: [19900/21770] eta: 0:01:13 time: 0.0390 data: 0.0008 max mem: 33300 +Test: [20000/21770] eta: 0:01:09 time: 0.0392 data: 0.0008 max mem: 33300 +Test: [20100/21770] eta: 0:01:05 time: 0.0388 data: 0.0008 max mem: 33300 +Test: [20200/21770] eta: 0:01:01 time: 0.0392 data: 0.0008 max mem: 33300 +Test: [20300/21770] eta: 0:00:57 time: 0.0389 data: 0.0008 max mem: 33300 +Test: [20400/21770] eta: 0:00:53 time: 0.0389 data: 0.0008 max mem: 33300 +Test: [20500/21770] eta: 0:00:49 time: 0.0392 data: 0.0008 max mem: 33300 +Test: [20600/21770] eta: 0:00:46 time: 0.0393 data: 0.0008 max mem: 33300 +Test: [20700/21770] eta: 0:00:42 time: 0.0392 data: 0.0008 max mem: 33300 +Test: [20800/21770] eta: 0:00:38 time: 0.0393 data: 0.0008 max mem: 33300 +Test: [20900/21770] eta: 0:00:34 time: 0.0389 data: 0.0008 max mem: 33300 +Test: [21000/21770] eta: 0:00:30 time: 0.0395 data: 0.0008 max mem: 33300 +Test: [21100/21770] eta: 0:00:26 time: 0.0394 data: 0.0008 max mem: 33300 +Test: [21200/21770] eta: 0:00:22 time: 0.0398 data: 0.0008 max mem: 33300 +Test: [21300/21770] eta: 0:00:18 time: 0.0394 data: 0.0008 max mem: 33300 +Test: [21400/21770] eta: 0:00:14 time: 0.0400 data: 0.0008 max mem: 33300 +Test: [21500/21770] eta: 0:00:10 time: 0.0395 data: 0.0008 max mem: 33300 +Test: [21600/21770] eta: 0:00:06 time: 0.0395 data: 0.0008 max mem: 33300 +Test: [21700/21770] eta: 0:00:02 time: 0.0393 data: 0.0008 max mem: 33300 +Test: Total time: 0:14:16 +Final results: +Mean IoU is 0.00 + + precision@0.5 = 0.00 + precision@0.6 = 0.00 + precision@0.7 = 0.00 + precision@0.8 = 0.00 + precision@0.9 = 0.00 + overall IoU = 0.00 + mean IoU = 0.00 + +Mean accuracy for one-to-zero sample is 100.00 + +Average object IoU 0.0 +Overall IoU 0.0 +Epoch: [18] [ 0/4276] eta: 6:01:32 lr: 2.9193910340949192e-05 loss: 0.1046 (0.1046) time: 5.0731 data: 1.9851 max mem: 33300 +Epoch: [18] [ 10/4276] eta: 3:42:58 lr: 2.9191117274120423e-05 loss: 0.1226 (0.1229) time: 3.1360 data: 0.1866 max mem: 33300 +Epoch: [18] [ 20/4276] eta: 3:35:25 lr: 2.91883241775973e-05 loss: 0.1234 (0.1334) time: 2.9351 data: 0.0068 max mem: 33300 +Epoch: [18] [ 30/4276] eta: 3:32:19 lr: 2.9185531051376324e-05 loss: 0.1241 (0.1305) time: 2.9257 data: 0.0072 max mem: 33300 +Epoch: [18] [ 40/4276] eta: 3:30:34 lr: 2.9182737895454042e-05 loss: 0.1241 (0.1291) time: 2.9255 data: 0.0077 max mem: 33300 +Epoch: [18] [ 50/4276] eta: 3:29:14 lr: 2.9179944709826975e-05 loss: 0.1215 (0.1264) time: 2.9249 data: 0.0077 max mem: 33300 +Epoch: [18] [ 60/4276] eta: 3:28:14 lr: 2.9177151494491646e-05 loss: 0.1102 (0.1264) time: 2.9246 data: 0.0077 max mem: 33300 +Epoch: [18] [ 70/4276] eta: 3:27:20 lr: 2.917435824944457e-05 loss: 0.1242 (0.1255) time: 2.9245 data: 0.0077 max mem: 33300 +Epoch: [18] [ 80/4276] eta: 3:26:39 lr: 2.9171564974682285e-05 loss: 0.1239 (0.1259) time: 2.9291 data: 0.0075 max mem: 33300 +Epoch: [18] [ 90/4276] eta: 3:25:55 lr: 2.9168771670201313e-05 loss: 0.1185 (0.1255) time: 2.9301 data: 0.0075 max mem: 33300 +Epoch: [18] [ 100/4276] eta: 3:25:18 lr: 2.9165978335998168e-05 loss: 0.1199 (0.1277) time: 2.9292 data: 0.0077 max mem: 33300 +Epoch: [18] [ 110/4276] eta: 3:24:42 lr: 2.9163184972069374e-05 loss: 0.1304 (0.1291) time: 2.9331 data: 0.0077 max mem: 33300 +Epoch: [18] [ 120/4276] eta: 3:24:08 lr: 2.9160391578411445e-05 loss: 0.1214 (0.1281) time: 2.9338 data: 0.0075 max mem: 33300 +Epoch: [18] [ 130/4276] eta: 3:23:35 lr: 2.9157598155020905e-05 loss: 0.1249 (0.1291) time: 2.9355 data: 0.0075 max mem: 33300 +Epoch: [18] [ 140/4276] eta: 3:23:03 lr: 2.9154804701894274e-05 loss: 0.1249 (0.1286) time: 2.9365 data: 0.0077 max mem: 33300 +Epoch: [18] [ 150/4276] eta: 3:22:32 lr: 2.9152011219028065e-05 loss: 0.1199 (0.1280) time: 2.9387 data: 0.0077 max mem: 33300 +Epoch: [18] [ 160/4276] eta: 3:22:01 lr: 2.9149217706418795e-05 loss: 0.1204 (0.1281) time: 2.9393 data: 0.0075 max mem: 33300 +Epoch: [18] [ 170/4276] eta: 3:21:31 lr: 2.9146424164062996e-05 loss: 0.1175 (0.1275) time: 2.9413 data: 0.0076 max mem: 33300 +Epoch: [18] [ 180/4276] eta: 3:21:02 lr: 2.9143630591957166e-05 loss: 0.1175 (0.1279) time: 2.9442 data: 0.0078 max mem: 33300 +Epoch: [18] [ 190/4276] eta: 3:20:32 lr: 2.9140836990097824e-05 loss: 0.1309 (0.1273) time: 2.9439 data: 0.0077 max mem: 33300 +Epoch: [18] [ 200/4276] eta: 3:20:02 lr: 2.9138043358481483e-05 loss: 0.1130 (0.1276) time: 2.9434 data: 0.0075 max mem: 33300 +Epoch: [18] [ 210/4276] eta: 3:19:32 lr: 2.9135249697104655e-05 loss: 0.1147 (0.1278) time: 2.9411 data: 0.0075 max mem: 33300 +Epoch: [18] [ 220/4276] eta: 3:19:02 lr: 2.913245600596385e-05 loss: 0.1356 (0.1282) time: 2.9417 data: 0.0077 max mem: 33300 +Epoch: [18] [ 230/4276] eta: 3:18:32 lr: 2.9129662285055585e-05 loss: 0.1289 (0.1276) time: 2.9436 data: 0.0077 max mem: 33300 +Epoch: [18] [ 240/4276] eta: 3:18:02 lr: 2.9126868534376372e-05 loss: 0.1229 (0.1274) time: 2.9409 data: 0.0075 max mem: 33300 +Epoch: [18] [ 250/4276] eta: 3:17:32 lr: 2.9124074753922725e-05 loss: 0.1265 (0.1278) time: 2.9384 data: 0.0075 max mem: 33300 +Epoch: [18] [ 260/4276] eta: 3:17:00 lr: 2.9121280943691137e-05 loss: 0.1268 (0.1281) time: 2.9352 data: 0.0079 max mem: 33300 +Epoch: [18] [ 270/4276] eta: 3:16:29 lr: 2.9118487103678134e-05 loss: 0.1219 (0.1281) time: 2.9311 data: 0.0078 max mem: 33300 +Epoch: [18] [ 280/4276] eta: 3:15:58 lr: 2.911569323388021e-05 loss: 0.1222 (0.1279) time: 2.9323 data: 0.0075 max mem: 33300 +Epoch: [18] [ 290/4276] eta: 3:15:28 lr: 2.911289933429387e-05 loss: 0.1219 (0.1276) time: 2.9361 data: 0.0079 max mem: 33300 +Epoch: [18] [ 300/4276] eta: 3:14:52 lr: 2.911010540491563e-05 loss: 0.1219 (0.1274) time: 2.9158 data: 0.0084 max mem: 33300 +Epoch: [18] [ 310/4276] eta: 3:14:23 lr: 2.9107311445741997e-05 loss: 0.1288 (0.1274) time: 2.9161 data: 0.0084 max mem: 33300 +Epoch: [18] [ 320/4276] eta: 3:13:53 lr: 2.9104517456769465e-05 loss: 0.1331 (0.1278) time: 2.9400 data: 0.0080 max mem: 33300 +Epoch: [18] [ 330/4276] eta: 3:13:23 lr: 2.910172343799455e-05 loss: 0.1380 (0.1284) time: 2.9392 data: 0.0080 max mem: 33300 +Epoch: [18] [ 340/4276] eta: 3:12:54 lr: 2.9098929389413737e-05 loss: 0.1256 (0.1283) time: 2.9362 data: 0.0080 max mem: 33300 +Epoch: [18] [ 350/4276] eta: 3:12:24 lr: 2.909613531102355e-05 loss: 0.1106 (0.1283) time: 2.9371 data: 0.0080 max mem: 33300 +Epoch: [18] [ 360/4276] eta: 3:11:52 lr: 2.9093341202820474e-05 loss: 0.1292 (0.1290) time: 2.9304 data: 0.0079 max mem: 33300 +Epoch: [18] [ 370/4276] eta: 3:11:21 lr: 2.909054706480101e-05 loss: 0.1206 (0.1287) time: 2.9238 data: 0.0078 max mem: 33300 +Epoch: [18] [ 380/4276] eta: 3:10:51 lr: 2.908775289696167e-05 loss: 0.1179 (0.1291) time: 2.9282 data: 0.0077 max mem: 33300 +Epoch: [18] [ 390/4276] eta: 3:10:22 lr: 2.9084958699298938e-05 loss: 0.1378 (0.1294) time: 2.9343 data: 0.0075 max mem: 33300 +Epoch: [18] [ 400/4276] eta: 3:09:52 lr: 2.9082164471809324e-05 loss: 0.1378 (0.1297) time: 2.9346 data: 0.0076 max mem: 33300 +Epoch: [18] [ 410/4276] eta: 3:09:21 lr: 2.907937021448932e-05 loss: 0.1291 (0.1297) time: 2.9277 data: 0.0077 max mem: 33300 +Epoch: [18] [ 420/4276] eta: 3:08:47 lr: 2.9076575927335425e-05 loss: 0.1234 (0.1296) time: 2.9098 data: 0.0078 max mem: 33300 +Epoch: [18] [ 430/4276] eta: 3:08:18 lr: 2.907378161034413e-05 loss: 0.1279 (0.1298) time: 2.9167 data: 0.0080 max mem: 33300 +Epoch: [18] [ 440/4276] eta: 3:07:48 lr: 2.9070987263511927e-05 loss: 0.1241 (0.1294) time: 2.9364 data: 0.0081 max mem: 33300 +Epoch: [18] [ 450/4276] eta: 3:07:19 lr: 2.9068192886835322e-05 loss: 0.1206 (0.1294) time: 2.9353 data: 0.0077 max mem: 33300 +Epoch: [18] [ 460/4276] eta: 3:06:50 lr: 2.90653984803108e-05 loss: 0.1204 (0.1289) time: 2.9373 data: 0.0078 max mem: 33300 +Epoch: [18] [ 470/4276] eta: 3:06:20 lr: 2.906260404393486e-05 loss: 0.0999 (0.1284) time: 2.9359 data: 0.0079 max mem: 33300 +Epoch: [18] [ 480/4276] eta: 3:05:51 lr: 2.9059809577703996e-05 loss: 0.1006 (0.1282) time: 2.9376 data: 0.0080 max mem: 33300 +Epoch: [18] [ 490/4276] eta: 3:05:22 lr: 2.905701508161468e-05 loss: 0.1012 (0.1276) time: 2.9408 data: 0.0079 max mem: 33300 +Epoch: [18] [ 500/4276] eta: 3:04:52 lr: 2.9054220555663424e-05 loss: 0.1059 (0.1275) time: 2.9367 data: 0.0078 max mem: 33300 +Epoch: [18] [ 510/4276] eta: 3:04:23 lr: 2.9051425999846703e-05 loss: 0.1104 (0.1272) time: 2.9378 data: 0.0082 max mem: 33300 +Epoch: [18] [ 520/4276] eta: 3:03:53 lr: 2.9048631414161015e-05 loss: 0.1160 (0.1271) time: 2.9394 data: 0.0080 max mem: 33300 +Epoch: [18] [ 530/4276] eta: 3:03:24 lr: 2.9045836798602843e-05 loss: 0.1160 (0.1270) time: 2.9389 data: 0.0076 max mem: 33300 +Epoch: [18] [ 540/4276] eta: 3:02:55 lr: 2.9043042153168674e-05 loss: 0.1137 (0.1268) time: 2.9393 data: 0.0081 max mem: 33300 +Epoch: [18] [ 550/4276] eta: 3:02:26 lr: 2.904024747785499e-05 loss: 0.1203 (0.1268) time: 2.9417 data: 0.0087 max mem: 33300 +Epoch: [18] [ 560/4276] eta: 3:01:57 lr: 2.9037452772658298e-05 loss: 0.1227 (0.1268) time: 2.9440 data: 0.0086 max mem: 33300 +Epoch: [18] [ 570/4276] eta: 3:01:28 lr: 2.903465803757506e-05 loss: 0.1227 (0.1267) time: 2.9414 data: 0.0082 max mem: 33300 +Epoch: [18] [ 580/4276] eta: 3:00:59 lr: 2.9031863272601767e-05 loss: 0.1185 (0.1266) time: 2.9405 data: 0.0083 max mem: 33300 +Epoch: [18] [ 590/4276] eta: 3:00:29 lr: 2.90290684777349e-05 loss: 0.1056 (0.1262) time: 2.9399 data: 0.0087 max mem: 33300 +Epoch: [18] [ 600/4276] eta: 3:00:00 lr: 2.9026273652970943e-05 loss: 0.1106 (0.1262) time: 2.9392 data: 0.0085 max mem: 33300 +Epoch: [18] [ 610/4276] eta: 2:59:31 lr: 2.902347879830638e-05 loss: 0.1229 (0.1262) time: 2.9400 data: 0.0081 max mem: 33300 +Epoch: [18] [ 620/4276] eta: 2:59:01 lr: 2.9020683913737685e-05 loss: 0.1184 (0.1262) time: 2.9392 data: 0.0083 max mem: 33300 +Epoch: [18] [ 630/4276] eta: 2:58:32 lr: 2.901788899926135e-05 loss: 0.1245 (0.1263) time: 2.9405 data: 0.0087 max mem: 33300 +Epoch: [18] [ 640/4276] eta: 2:58:03 lr: 2.9015094054873847e-05 loss: 0.1228 (0.1263) time: 2.9430 data: 0.0085 max mem: 33300 +Epoch: [18] [ 650/4276] eta: 2:57:34 lr: 2.9012299080571648e-05 loss: 0.1151 (0.1264) time: 2.9414 data: 0.0081 max mem: 33300 +Epoch: [18] [ 660/4276] eta: 2:57:04 lr: 2.9009504076351247e-05 loss: 0.1352 (0.1267) time: 2.9357 data: 0.0083 max mem: 33300 +Epoch: [18] [ 670/4276] eta: 2:56:34 lr: 2.90067090422091e-05 loss: 0.1352 (0.1268) time: 2.9329 data: 0.0086 max mem: 33300 +Epoch: [18] [ 680/4276] eta: 2:56:04 lr: 2.9003913978141702e-05 loss: 0.1262 (0.1267) time: 2.9269 data: 0.0082 max mem: 33300 +Epoch: [18] [ 690/4276] eta: 2:55:34 lr: 2.9001118884145518e-05 loss: 0.1283 (0.1269) time: 2.9253 data: 0.0075 max mem: 33300 +Epoch: [18] [ 700/4276] eta: 2:55:05 lr: 2.8998323760217023e-05 loss: 0.1321 (0.1270) time: 2.9360 data: 0.0075 max mem: 33300 +Epoch: [18] [ 710/4276] eta: 2:54:35 lr: 2.8995528606352696e-05 loss: 0.1270 (0.1270) time: 2.9370 data: 0.0075 max mem: 33300 +Epoch: [18] [ 720/4276] eta: 2:54:06 lr: 2.8992733422549e-05 loss: 0.1105 (0.1269) time: 2.9341 data: 0.0073 max mem: 33300 +Epoch: [18] [ 730/4276] eta: 2:53:36 lr: 2.8989938208802426e-05 loss: 0.1022 (0.1268) time: 2.9297 data: 0.0074 max mem: 33300 +Epoch: [18] [ 740/4276] eta: 2:53:07 lr: 2.8987142965109422e-05 loss: 0.1081 (0.1266) time: 2.9326 data: 0.0076 max mem: 33300 +Epoch: [18] [ 750/4276] eta: 2:52:37 lr: 2.8984347691466468e-05 loss: 0.1172 (0.1266) time: 2.9319 data: 0.0076 max mem: 33300 +Epoch: [18] [ 760/4276] eta: 2:52:07 lr: 2.8981552387870036e-05 loss: 0.1108 (0.1265) time: 2.9224 data: 0.0074 max mem: 33300 +Epoch: [18] [ 770/4276] eta: 2:51:37 lr: 2.8978757054316598e-05 loss: 0.1129 (0.1265) time: 2.9247 data: 0.0075 max mem: 33300 +Epoch: [18] [ 780/4276] eta: 2:51:07 lr: 2.897596169080261e-05 loss: 0.1190 (0.1266) time: 2.9269 data: 0.0076 max mem: 33300 +Epoch: [18] [ 790/4276] eta: 2:50:37 lr: 2.8973166297324563e-05 loss: 0.1327 (0.1266) time: 2.9288 data: 0.0076 max mem: 33300 +Epoch: [18] [ 800/4276] eta: 2:50:08 lr: 2.8970370873878895e-05 loss: 0.1242 (0.1266) time: 2.9344 data: 0.0074 max mem: 33300 +Epoch: [18] [ 810/4276] eta: 2:49:39 lr: 2.8967575420462088e-05 loss: 0.1242 (0.1267) time: 2.9439 data: 0.0074 max mem: 33300 +Epoch: [18] [ 820/4276] eta: 2:49:10 lr: 2.89647799370706e-05 loss: 0.1195 (0.1265) time: 2.9443 data: 0.0077 max mem: 33300 +Epoch: [18] [ 830/4276] eta: 2:48:41 lr: 2.89619844237009e-05 loss: 0.1189 (0.1266) time: 2.9383 data: 0.0079 max mem: 33300 +Epoch: [18] [ 840/4276] eta: 2:48:11 lr: 2.8959188880349453e-05 loss: 0.1194 (0.1266) time: 2.9365 data: 0.0076 max mem: 33300 +Epoch: [18] [ 850/4276] eta: 2:47:42 lr: 2.8956393307012713e-05 loss: 0.1167 (0.1265) time: 2.9347 data: 0.0073 max mem: 33300 +Epoch: [18] [ 860/4276] eta: 2:47:12 lr: 2.8953597703687148e-05 loss: 0.1101 (0.1265) time: 2.9338 data: 0.0075 max mem: 33300 +Epoch: [18] [ 870/4276] eta: 2:46:43 lr: 2.8950802070369227e-05 loss: 0.1101 (0.1264) time: 2.9329 data: 0.0076 max mem: 33300 +Epoch: [18] [ 880/4276] eta: 2:46:13 lr: 2.8948006407055396e-05 loss: 0.1182 (0.1265) time: 2.9303 data: 0.0073 max mem: 33300 +Epoch: [18] [ 890/4276] eta: 2:45:43 lr: 2.8945210713742117e-05 loss: 0.1338 (0.1267) time: 2.9257 data: 0.0075 max mem: 33300 +Epoch: [18] [ 900/4276] eta: 2:45:13 lr: 2.8942414990425855e-05 loss: 0.1294 (0.1266) time: 2.9283 data: 0.0078 max mem: 33300 +Epoch: [18] [ 910/4276] eta: 2:44:44 lr: 2.8939619237103054e-05 loss: 0.1234 (0.1267) time: 2.9383 data: 0.0076 max mem: 33300 +Epoch: [18] [ 920/4276] eta: 2:44:15 lr: 2.893682345377019e-05 loss: 0.1237 (0.1267) time: 2.9379 data: 0.0073 max mem: 33300 +Epoch: [18] [ 930/4276] eta: 2:43:45 lr: 2.8934027640423707e-05 loss: 0.1355 (0.1268) time: 2.9335 data: 0.0074 max mem: 33300 +Epoch: [18] [ 940/4276] eta: 2:43:16 lr: 2.8931231797060067e-05 loss: 0.1141 (0.1267) time: 2.9398 data: 0.0076 max mem: 33300 +Epoch: [18] [ 950/4276] eta: 2:42:47 lr: 2.892843592367572e-05 loss: 0.1156 (0.1269) time: 2.9390 data: 0.0078 max mem: 33300 +Epoch: [18] [ 960/4276] eta: 2:42:17 lr: 2.8925640020267116e-05 loss: 0.1324 (0.1270) time: 2.9207 data: 0.0086 max mem: 33300 +Epoch: [18] [ 970/4276] eta: 2:41:45 lr: 2.892284408683072e-05 loss: 0.1324 (0.1270) time: 2.8976 data: 0.0090 max mem: 33300 +Epoch: [18] [ 980/4276] eta: 2:41:14 lr: 2.8920048123362968e-05 loss: 0.1234 (0.1269) time: 2.8842 data: 0.0088 max mem: 33300 +Epoch: [18] [ 990/4276] eta: 2:40:43 lr: 2.891725212986033e-05 loss: 0.1168 (0.1268) time: 2.8870 data: 0.0087 max mem: 33300 +Epoch: [18] [1000/4276] eta: 2:40:14 lr: 2.891445610631924e-05 loss: 0.1105 (0.1268) time: 2.9166 data: 0.0085 max mem: 33300 +Epoch: [18] [1010/4276] eta: 2:39:45 lr: 2.891166005273615e-05 loss: 0.1130 (0.1267) time: 2.9382 data: 0.0078 max mem: 33300 +Epoch: [18] [1020/4276] eta: 2:39:16 lr: 2.8908863969107524e-05 loss: 0.1155 (0.1267) time: 2.9361 data: 0.0075 max mem: 33300 +Epoch: [18] [1030/4276] eta: 2:38:46 lr: 2.8906067855429792e-05 loss: 0.1196 (0.1268) time: 2.9344 data: 0.0074 max mem: 33300 +Epoch: [18] [1040/4276] eta: 2:38:16 lr: 2.8903271711699416e-05 loss: 0.1262 (0.1267) time: 2.9244 data: 0.0073 max mem: 33300 +Epoch: [18] [1050/4276] eta: 2:37:46 lr: 2.890047553791283e-05 loss: 0.1172 (0.1268) time: 2.9077 data: 0.0082 max mem: 33300 +Epoch: [18] [1060/4276] eta: 2:37:15 lr: 2.8897679334066486e-05 loss: 0.1322 (0.1269) time: 2.8867 data: 0.0092 max mem: 33300 +Epoch: [18] [1070/4276] eta: 2:36:43 lr: 2.889488310015683e-05 loss: 0.1521 (0.1271) time: 2.8685 data: 0.0094 max mem: 33300 +Epoch: [18] [1080/4276] eta: 2:36:14 lr: 2.88920868361803e-05 loss: 0.1325 (0.1271) time: 2.8965 data: 0.0087 max mem: 33300 +Epoch: [18] [1090/4276] eta: 2:35:44 lr: 2.8889290542133342e-05 loss: 0.1303 (0.1272) time: 2.9214 data: 0.0076 max mem: 33300 +Epoch: [18] [1100/4276] eta: 2:35:14 lr: 2.8886494218012412e-05 loss: 0.1307 (0.1272) time: 2.9135 data: 0.0075 max mem: 33300 +Epoch: [18] [1110/4276] eta: 2:34:44 lr: 2.888369786381393e-05 loss: 0.1308 (0.1273) time: 2.9027 data: 0.0080 max mem: 33300 +Epoch: [18] [1120/4276] eta: 2:34:13 lr: 2.888090147953435e-05 loss: 0.1353 (0.1274) time: 2.8892 data: 0.0092 max mem: 33300 +Epoch: [18] [1130/4276] eta: 2:33:43 lr: 2.887810506517011e-05 loss: 0.1128 (0.1272) time: 2.8912 data: 0.0090 max mem: 33300 +Epoch: [18] [1140/4276] eta: 2:33:13 lr: 2.8875308620717646e-05 loss: 0.1105 (0.1271) time: 2.9045 data: 0.0078 max mem: 33300 +Epoch: [18] [1150/4276] eta: 2:32:43 lr: 2.88725121461734e-05 loss: 0.1122 (0.1270) time: 2.9117 data: 0.0075 max mem: 33300 +Epoch: [18] [1160/4276] eta: 2:32:13 lr: 2.88697156415338e-05 loss: 0.1194 (0.1270) time: 2.9116 data: 0.0076 max mem: 33300 +Epoch: [18] [1170/4276] eta: 2:31:43 lr: 2.8866919106795298e-05 loss: 0.1262 (0.1269) time: 2.9139 data: 0.0074 max mem: 33300 +Epoch: [18] [1180/4276] eta: 2:31:14 lr: 2.886412254195433e-05 loss: 0.1268 (0.1269) time: 2.9137 data: 0.0074 max mem: 33300 +Epoch: [18] [1190/4276] eta: 2:30:44 lr: 2.8861325947007317e-05 loss: 0.1072 (0.1268) time: 2.9139 data: 0.0074 max mem: 33300 +Epoch: [18] [1200/4276] eta: 2:30:14 lr: 2.8858529321950712e-05 loss: 0.1155 (0.1267) time: 2.9147 data: 0.0073 max mem: 33300 +Epoch: [18] [1210/4276] eta: 2:29:45 lr: 2.8855732666780927e-05 loss: 0.1113 (0.1266) time: 2.9174 data: 0.0073 max mem: 33300 +Epoch: [18] [1220/4276] eta: 2:29:15 lr: 2.8852935981494405e-05 loss: 0.1181 (0.1268) time: 2.9177 data: 0.0075 max mem: 33300 +Epoch: [18] [1230/4276] eta: 2:28:45 lr: 2.8850139266087584e-05 loss: 0.1329 (0.1268) time: 2.9168 data: 0.0075 max mem: 33300 +Epoch: [18] [1240/4276] eta: 2:28:15 lr: 2.8847342520556887e-05 loss: 0.1267 (0.1269) time: 2.9135 data: 0.0074 max mem: 33300 +Epoch: [18] [1250/4276] eta: 2:27:46 lr: 2.884454574489875e-05 loss: 0.1248 (0.1269) time: 2.9073 data: 0.0076 max mem: 33300 +Epoch: [18] [1260/4276] eta: 2:27:16 lr: 2.8841748939109603e-05 loss: 0.1136 (0.1268) time: 2.9075 data: 0.0075 max mem: 33300 +Epoch: [18] [1270/4276] eta: 2:26:46 lr: 2.8838952103185867e-05 loss: 0.1152 (0.1267) time: 2.9120 data: 0.0072 max mem: 33300 +Epoch: [18] [1280/4276] eta: 2:26:16 lr: 2.883615523712398e-05 loss: 0.1250 (0.1267) time: 2.9147 data: 0.0069 max mem: 33300 +Epoch: [18] [1290/4276] eta: 2:25:47 lr: 2.8833358340920362e-05 loss: 0.1250 (0.1268) time: 2.9170 data: 0.0069 max mem: 33300 +Epoch: [18] [1300/4276] eta: 2:25:17 lr: 2.8830561414571438e-05 loss: 0.1077 (0.1267) time: 2.9169 data: 0.0069 max mem: 33300 +Epoch: [18] [1310/4276] eta: 2:24:48 lr: 2.8827764458073643e-05 loss: 0.1077 (0.1267) time: 2.9129 data: 0.0070 max mem: 33300 +Epoch: [18] [1320/4276] eta: 2:24:18 lr: 2.8824967471423392e-05 loss: 0.1170 (0.1268) time: 2.9190 data: 0.0072 max mem: 33300 +Epoch: [18] [1330/4276] eta: 2:23:49 lr: 2.882217045461712e-05 loss: 0.1240 (0.1268) time: 2.9326 data: 0.0071 max mem: 33300 +Epoch: [18] [1340/4276] eta: 2:23:20 lr: 2.8819373407651235e-05 loss: 0.1181 (0.1268) time: 2.9358 data: 0.0069 max mem: 33300 +Epoch: [18] [1350/4276] eta: 2:22:51 lr: 2.8816576330522175e-05 loss: 0.1221 (0.1268) time: 2.9340 data: 0.0069 max mem: 33300 +Epoch: [18] [1360/4276] eta: 2:22:21 lr: 2.881377922322635e-05 loss: 0.1231 (0.1267) time: 2.9306 data: 0.0069 max mem: 33300 +Epoch: [18] [1370/4276] eta: 2:21:52 lr: 2.8810982085760185e-05 loss: 0.1108 (0.1267) time: 2.9279 data: 0.0070 max mem: 33300 +Epoch: [18] [1380/4276] eta: 2:21:23 lr: 2.8808184918120102e-05 loss: 0.1202 (0.1267) time: 2.9267 data: 0.0070 max mem: 33300 +Epoch: [18] [1390/4276] eta: 2:20:53 lr: 2.8805387720302512e-05 loss: 0.1318 (0.1268) time: 2.9261 data: 0.0070 max mem: 33300 +Epoch: [18] [1400/4276] eta: 2:20:24 lr: 2.8802590492303843e-05 loss: 0.1288 (0.1268) time: 2.9276 data: 0.0069 max mem: 33300 +Epoch: [18] [1410/4276] eta: 2:19:55 lr: 2.8799793234120516e-05 loss: 0.1108 (0.1267) time: 2.9306 data: 0.0071 max mem: 33300 +Epoch: [18] [1420/4276] eta: 2:19:26 lr: 2.8796995945748934e-05 loss: 0.1108 (0.1267) time: 2.9358 data: 0.0072 max mem: 33300 +Epoch: [18] [1430/4276] eta: 2:18:56 lr: 2.8794198627185526e-05 loss: 0.1197 (0.1267) time: 2.9307 data: 0.0070 max mem: 33300 +Epoch: [18] [1440/4276] eta: 2:18:27 lr: 2.8791401278426695e-05 loss: 0.1233 (0.1267) time: 2.9240 data: 0.0071 max mem: 33300 +Epoch: [18] [1450/4276] eta: 2:17:57 lr: 2.8788603899468856e-05 loss: 0.1146 (0.1266) time: 2.9201 data: 0.0078 max mem: 33300 +Epoch: [18] [1460/4276] eta: 2:17:28 lr: 2.878580649030843e-05 loss: 0.1146 (0.1266) time: 2.9252 data: 0.0078 max mem: 33300 +Epoch: [18] [1470/4276] eta: 2:16:59 lr: 2.878300905094183e-05 loss: 0.1173 (0.1265) time: 2.9298 data: 0.0074 max mem: 33300 +Epoch: [18] [1480/4276] eta: 2:16:29 lr: 2.8780211581365464e-05 loss: 0.1101 (0.1265) time: 2.9250 data: 0.0075 max mem: 33300 +Epoch: [18] [1490/4276] eta: 2:16:00 lr: 2.8777414081575742e-05 loss: 0.1089 (0.1265) time: 2.9247 data: 0.0077 max mem: 33300 +Epoch: [18] [1500/4276] eta: 2:15:31 lr: 2.877461655156908e-05 loss: 0.1089 (0.1265) time: 2.9252 data: 0.0075 max mem: 33300 +Epoch: [18] [1510/4276] eta: 2:15:01 lr: 2.877181899134188e-05 loss: 0.1080 (0.1264) time: 2.9281 data: 0.0075 max mem: 33300 +Epoch: [18] [1520/4276] eta: 2:14:32 lr: 2.8769021400890556e-05 loss: 0.1070 (0.1263) time: 2.9297 data: 0.0075 max mem: 33300 +Epoch: [18] [1530/4276] eta: 2:14:03 lr: 2.876622378021151e-05 loss: 0.1107 (0.1262) time: 2.9295 data: 0.0075 max mem: 33300 +Epoch: [18] [1540/4276] eta: 2:13:34 lr: 2.8763426129301152e-05 loss: 0.1198 (0.1262) time: 2.9280 data: 0.0075 max mem: 33300 +Epoch: [18] [1550/4276] eta: 2:13:04 lr: 2.876062844815589e-05 loss: 0.1282 (0.1262) time: 2.9250 data: 0.0073 max mem: 33300 +Epoch: [18] [1560/4276] eta: 2:12:35 lr: 2.875783073677213e-05 loss: 0.1304 (0.1263) time: 2.9166 data: 0.0075 max mem: 33300 +Epoch: [18] [1570/4276] eta: 2:12:05 lr: 2.8755032995146276e-05 loss: 0.1233 (0.1263) time: 2.9175 data: 0.0077 max mem: 33300 +Epoch: [18] [1580/4276] eta: 2:11:36 lr: 2.8752235223274725e-05 loss: 0.1177 (0.1262) time: 2.9334 data: 0.0075 max mem: 33300 +Epoch: [18] [1590/4276] eta: 2:11:07 lr: 2.874943742115389e-05 loss: 0.1297 (0.1262) time: 2.9391 data: 0.0073 max mem: 33300 +Epoch: [18] [1600/4276] eta: 2:10:38 lr: 2.8746639588780168e-05 loss: 0.1224 (0.1263) time: 2.9376 data: 0.0073 max mem: 33300 +Epoch: [18] [1610/4276] eta: 2:10:08 lr: 2.874384172614995e-05 loss: 0.1207 (0.1262) time: 2.9309 data: 0.0075 max mem: 33300 +Epoch: [18] [1620/4276] eta: 2:09:39 lr: 2.8741043833259652e-05 loss: 0.1094 (0.1261) time: 2.9170 data: 0.0074 max mem: 33300 +Epoch: [18] [1630/4276] eta: 2:09:09 lr: 2.8738245910105672e-05 loss: 0.1268 (0.1262) time: 2.9125 data: 0.0072 max mem: 33300 +Epoch: [18] [1640/4276] eta: 2:08:40 lr: 2.8735447956684403e-05 loss: 0.1101 (0.1260) time: 2.9235 data: 0.0072 max mem: 33300 +Epoch: [18] [1650/4276] eta: 2:08:11 lr: 2.8732649972992243e-05 loss: 0.0978 (0.1259) time: 2.9358 data: 0.0074 max mem: 33300 +Epoch: [18] [1660/4276] eta: 2:07:42 lr: 2.8729851959025594e-05 loss: 0.1067 (0.1258) time: 2.9361 data: 0.0075 max mem: 33300 +Epoch: [18] [1670/4276] eta: 2:07:13 lr: 2.8727053914780848e-05 loss: 0.1178 (0.1258) time: 2.9405 data: 0.0073 max mem: 33300 +Epoch: [18] [1680/4276] eta: 2:06:44 lr: 2.87242558402544e-05 loss: 0.1296 (0.1258) time: 2.9431 data: 0.0075 max mem: 33300 +Epoch: [18] [1690/4276] eta: 2:06:14 lr: 2.8721457735442647e-05 loss: 0.1277 (0.1258) time: 2.9319 data: 0.0077 max mem: 33300 +Epoch: [18] [1700/4276] eta: 2:05:45 lr: 2.871865960034198e-05 loss: 0.1261 (0.1258) time: 2.9139 data: 0.0084 max mem: 33300 +Epoch: [18] [1710/4276] eta: 2:05:14 lr: 2.8715861434948793e-05 loss: 0.1235 (0.1258) time: 2.8911 data: 0.0085 max mem: 33300 +Epoch: [18] [1720/4276] eta: 2:04:44 lr: 2.8713063239259493e-05 loss: 0.1205 (0.1258) time: 2.8782 data: 0.0078 max mem: 33300 +Epoch: [18] [1730/4276] eta: 2:04:15 lr: 2.8710265013270444e-05 loss: 0.1117 (0.1258) time: 2.8895 data: 0.0081 max mem: 33300 +Epoch: [18] [1740/4276] eta: 2:03:45 lr: 2.8707466756978057e-05 loss: 0.1273 (0.1258) time: 2.9159 data: 0.0079 max mem: 33300 +Epoch: [18] [1750/4276] eta: 2:03:16 lr: 2.870466847037871e-05 loss: 0.1286 (0.1258) time: 2.9298 data: 0.0075 max mem: 33300 +Epoch: [18] [1760/4276] eta: 2:02:47 lr: 2.8701870153468796e-05 loss: 0.1137 (0.1257) time: 2.9306 data: 0.0074 max mem: 33300 +Epoch: [18] [1770/4276] eta: 2:02:18 lr: 2.869907180624471e-05 loss: 0.1094 (0.1257) time: 2.9317 data: 0.0072 max mem: 33300 +Epoch: [18] [1780/4276] eta: 2:01:48 lr: 2.869627342870283e-05 loss: 0.1122 (0.1256) time: 2.9296 data: 0.0071 max mem: 33300 +Epoch: [18] [1790/4276] eta: 2:01:19 lr: 2.8693475020839545e-05 loss: 0.1190 (0.1256) time: 2.9294 data: 0.0073 max mem: 33300 +Epoch: [18] [1800/4276] eta: 2:00:50 lr: 2.8690676582651244e-05 loss: 0.1190 (0.1256) time: 2.9336 data: 0.0073 max mem: 33300 +Epoch: [18] [1810/4276] eta: 2:00:21 lr: 2.868787811413431e-05 loss: 0.1243 (0.1256) time: 2.9350 data: 0.0071 max mem: 33300 +Epoch: [18] [1820/4276] eta: 1:59:52 lr: 2.8685079615285126e-05 loss: 0.1339 (0.1257) time: 2.9341 data: 0.0072 max mem: 33300 +Epoch: [18] [1830/4276] eta: 1:59:22 lr: 2.8682281086100075e-05 loss: 0.1257 (0.1257) time: 2.9356 data: 0.0073 max mem: 33300 +Epoch: [18] [1840/4276] eta: 1:58:53 lr: 2.867948252657554e-05 loss: 0.1141 (0.1256) time: 2.9372 data: 0.0073 max mem: 33300 +Epoch: [18] [1850/4276] eta: 1:58:24 lr: 2.8676683936707898e-05 loss: 0.1188 (0.1256) time: 2.9368 data: 0.0071 max mem: 33300 +Epoch: [18] [1860/4276] eta: 1:57:55 lr: 2.8673885316493538e-05 loss: 0.1156 (0.1255) time: 2.9369 data: 0.0071 max mem: 33300 +Epoch: [18] [1870/4276] eta: 1:57:26 lr: 2.8671086665928832e-05 loss: 0.1167 (0.1256) time: 2.9301 data: 0.0072 max mem: 33300 +Epoch: [18] [1880/4276] eta: 1:56:56 lr: 2.866828798501017e-05 loss: 0.1237 (0.1256) time: 2.9265 data: 0.0078 max mem: 33300 +Epoch: [18] [1890/4276] eta: 1:56:27 lr: 2.8665489273733918e-05 loss: 0.1176 (0.1255) time: 2.9296 data: 0.0077 max mem: 33300 +Epoch: [18] [1900/4276] eta: 1:55:58 lr: 2.8662690532096463e-05 loss: 0.1036 (0.1255) time: 2.9316 data: 0.0073 max mem: 33300 +Epoch: [18] [1910/4276] eta: 1:55:29 lr: 2.8659891760094175e-05 loss: 0.1093 (0.1255) time: 2.9310 data: 0.0072 max mem: 33300 +Epoch: [18] [1920/4276] eta: 1:54:59 lr: 2.865709295772343e-05 loss: 0.1187 (0.1254) time: 2.9295 data: 0.0070 max mem: 33300 +Epoch: [18] [1930/4276] eta: 1:54:30 lr: 2.8654294124980607e-05 loss: 0.1088 (0.1254) time: 2.9309 data: 0.0071 max mem: 33300 +Epoch: [18] [1940/4276] eta: 1:54:01 lr: 2.865149526186207e-05 loss: 0.1155 (0.1254) time: 2.9313 data: 0.0072 max mem: 33300 +Epoch: [18] [1950/4276] eta: 1:53:32 lr: 2.8648696368364215e-05 loss: 0.1247 (0.1254) time: 2.9349 data: 0.0072 max mem: 33300 +Epoch: [18] [1960/4276] eta: 1:53:02 lr: 2.864589744448339e-05 loss: 0.1114 (0.1253) time: 2.9357 data: 0.0071 max mem: 33300 +Epoch: [18] [1970/4276] eta: 1:52:33 lr: 2.864309849021598e-05 loss: 0.1052 (0.1253) time: 2.9343 data: 0.0071 max mem: 33300 +Epoch: [18] [1980/4276] eta: 1:52:04 lr: 2.8640299505558348e-05 loss: 0.1052 (0.1252) time: 2.9347 data: 0.0071 max mem: 33300 +Epoch: [18] [1990/4276] eta: 1:51:35 lr: 2.8637500490506868e-05 loss: 0.1067 (0.1252) time: 2.9327 data: 0.0070 max mem: 33300 +Epoch: [18] [2000/4276] eta: 1:51:05 lr: 2.863470144505791e-05 loss: 0.1212 (0.1252) time: 2.9309 data: 0.0071 max mem: 33300 +Epoch: [18] [2010/4276] eta: 1:50:36 lr: 2.8631902369207843e-05 loss: 0.1279 (0.1252) time: 2.9314 data: 0.0071 max mem: 33300 +Epoch: [18] [2020/4276] eta: 1:50:07 lr: 2.8629103262953032e-05 loss: 0.1205 (0.1252) time: 2.9332 data: 0.0072 max mem: 33300 +Epoch: [18] [2030/4276] eta: 1:49:38 lr: 2.862630412628985e-05 loss: 0.1096 (0.1251) time: 2.9333 data: 0.0072 max mem: 33300 +Epoch: [18] [2040/4276] eta: 1:49:08 lr: 2.8623504959214647e-05 loss: 0.1078 (0.1251) time: 2.9319 data: 0.0070 max mem: 33300 +Epoch: [18] [2050/4276] eta: 1:48:39 lr: 2.862070576172381e-05 loss: 0.1232 (0.1251) time: 2.9311 data: 0.0071 max mem: 33300 +Epoch: [18] [2060/4276] eta: 1:48:10 lr: 2.861790653381368e-05 loss: 0.1259 (0.1251) time: 2.9318 data: 0.0073 max mem: 33300 +Epoch: [18] [2070/4276] eta: 1:47:40 lr: 2.8615107275480636e-05 loss: 0.1105 (0.1251) time: 2.9237 data: 0.0075 max mem: 33300 +Epoch: [18] [2080/4276] eta: 1:47:11 lr: 2.8612307986721036e-05 loss: 0.1105 (0.1251) time: 2.9004 data: 0.0084 max mem: 33300 +Epoch: [18] [2090/4276] eta: 1:46:41 lr: 2.8609508667531243e-05 loss: 0.1263 (0.1251) time: 2.9080 data: 0.0087 max mem: 33300 +Epoch: [18] [2100/4276] eta: 1:46:12 lr: 2.8606709317907616e-05 loss: 0.1285 (0.1251) time: 2.9216 data: 0.0083 max mem: 33300 +Epoch: [18] [2110/4276] eta: 1:45:43 lr: 2.8603909937846518e-05 loss: 0.1173 (0.1250) time: 2.9209 data: 0.0081 max mem: 33300 +Epoch: [18] [2120/4276] eta: 1:45:13 lr: 2.8601110527344306e-05 loss: 0.1069 (0.1249) time: 2.9283 data: 0.0075 max mem: 33300 +Epoch: [18] [2130/4276] eta: 1:44:44 lr: 2.859831108639734e-05 loss: 0.0954 (0.1248) time: 2.9304 data: 0.0075 max mem: 33300 +Epoch: [18] [2140/4276] eta: 1:44:15 lr: 2.8595511615001967e-05 loss: 0.1136 (0.1248) time: 2.9296 data: 0.0076 max mem: 33300 +Epoch: [18] [2150/4276] eta: 1:43:46 lr: 2.8592712113154556e-05 loss: 0.1064 (0.1247) time: 2.9261 data: 0.0074 max mem: 33300 +Epoch: [18] [2160/4276] eta: 1:43:16 lr: 2.8589912580851463e-05 loss: 0.1064 (0.1247) time: 2.9256 data: 0.0073 max mem: 33300 +Epoch: [18] [2170/4276] eta: 1:42:47 lr: 2.8587113018089034e-05 loss: 0.1147 (0.1247) time: 2.9277 data: 0.0075 max mem: 33300 +Epoch: [18] [2180/4276] eta: 1:42:18 lr: 2.8584313424863634e-05 loss: 0.1201 (0.1246) time: 2.9298 data: 0.0077 max mem: 33300 +Epoch: [18] [2190/4276] eta: 1:41:48 lr: 2.858151380117161e-05 loss: 0.1279 (0.1247) time: 2.9310 data: 0.0076 max mem: 33300 +Epoch: [18] [2200/4276] eta: 1:41:19 lr: 2.8578714147009317e-05 loss: 0.1279 (0.1247) time: 2.9308 data: 0.0076 max mem: 33300 +Epoch: [18] [2210/4276] eta: 1:40:50 lr: 2.8575914462373104e-05 loss: 0.1268 (0.1247) time: 2.9309 data: 0.0078 max mem: 33300 +Epoch: [18] [2220/4276] eta: 1:40:20 lr: 2.857311474725932e-05 loss: 0.1261 (0.1248) time: 2.9133 data: 0.0081 max mem: 33300 +Epoch: [18] [2230/4276] eta: 1:39:51 lr: 2.8570315001664316e-05 loss: 0.1190 (0.1248) time: 2.9027 data: 0.0082 max mem: 33300 +Epoch: [18] [2240/4276] eta: 1:39:21 lr: 2.8567515225584445e-05 loss: 0.1153 (0.1247) time: 2.9097 data: 0.0076 max mem: 33300 +Epoch: [18] [2250/4276] eta: 1:38:52 lr: 2.8564715419016058e-05 loss: 0.1202 (0.1247) time: 2.9083 data: 0.0075 max mem: 33300 +Epoch: [18] [2260/4276] eta: 1:38:23 lr: 2.8561915581955494e-05 loss: 0.1267 (0.1248) time: 2.9147 data: 0.0078 max mem: 33300 +Epoch: [18] [2270/4276] eta: 1:37:53 lr: 2.8559115714399104e-05 loss: 0.1267 (0.1248) time: 2.9260 data: 0.0076 max mem: 33300 +Epoch: [18] [2280/4276] eta: 1:37:24 lr: 2.8556315816343237e-05 loss: 0.1217 (0.1248) time: 2.9251 data: 0.0073 max mem: 33300 +Epoch: [18] [2290/4276] eta: 1:36:55 lr: 2.8553515887784232e-05 loss: 0.1254 (0.1248) time: 2.9197 data: 0.0075 max mem: 33300 +Epoch: [18] [2300/4276] eta: 1:36:25 lr: 2.8550715928718435e-05 loss: 0.1237 (0.1248) time: 2.9194 data: 0.0077 max mem: 33300 +Epoch: [18] [2310/4276] eta: 1:35:56 lr: 2.854791593914219e-05 loss: 0.1266 (0.1249) time: 2.9199 data: 0.0075 max mem: 33300 +Epoch: [18] [2320/4276] eta: 1:35:27 lr: 2.8545115919051835e-05 loss: 0.1304 (0.1249) time: 2.9276 data: 0.0072 max mem: 33300 +Epoch: [18] [2330/4276] eta: 1:34:57 lr: 2.8542315868443718e-05 loss: 0.1310 (0.1249) time: 2.9333 data: 0.0075 max mem: 33300 +Epoch: [18] [2340/4276] eta: 1:34:28 lr: 2.8539515787314185e-05 loss: 0.1323 (0.1250) time: 2.9308 data: 0.0078 max mem: 33300 +Epoch: [18] [2350/4276] eta: 1:33:59 lr: 2.8536715675659566e-05 loss: 0.1250 (0.1250) time: 2.9303 data: 0.0075 max mem: 33300 +Epoch: [18] [2360/4276] eta: 1:33:30 lr: 2.8533915533476206e-05 loss: 0.1171 (0.1249) time: 2.9316 data: 0.0073 max mem: 33300 +Epoch: [18] [2370/4276] eta: 1:33:00 lr: 2.8531115360760436e-05 loss: 0.1226 (0.1250) time: 2.9304 data: 0.0075 max mem: 33300 +Epoch: [18] [2380/4276] eta: 1:32:31 lr: 2.8528315157508596e-05 loss: 0.1261 (0.1250) time: 2.9305 data: 0.0077 max mem: 33300 +Epoch: [18] [2390/4276] eta: 1:32:02 lr: 2.8525514923717023e-05 loss: 0.1216 (0.1250) time: 2.9294 data: 0.0073 max mem: 33300 +Epoch: [18] [2400/4276] eta: 1:31:33 lr: 2.8522714659382056e-05 loss: 0.1225 (0.1250) time: 2.9293 data: 0.0070 max mem: 33300 +Epoch: [18] [2410/4276] eta: 1:31:03 lr: 2.851991436450003e-05 loss: 0.1216 (0.1250) time: 2.9290 data: 0.0071 max mem: 33300 +Epoch: [18] [2420/4276] eta: 1:30:34 lr: 2.8517114039067277e-05 loss: 0.1118 (0.1250) time: 2.9249 data: 0.0073 max mem: 33300 +Epoch: [18] [2430/4276] eta: 1:30:05 lr: 2.851431368308013e-05 loss: 0.1250 (0.1250) time: 2.9284 data: 0.0073 max mem: 33300 +Epoch: [18] [2440/4276] eta: 1:29:36 lr: 2.8511513296534924e-05 loss: 0.1250 (0.1250) time: 2.9336 data: 0.0071 max mem: 33300 +Epoch: [18] [2450/4276] eta: 1:29:06 lr: 2.850871287942799e-05 loss: 0.1196 (0.1250) time: 2.9300 data: 0.0072 max mem: 33300 +Epoch: [18] [2460/4276] eta: 1:28:37 lr: 2.8505912431755655e-05 loss: 0.1246 (0.1251) time: 2.9261 data: 0.0074 max mem: 33300 +Epoch: [18] [2470/4276] eta: 1:28:08 lr: 2.8503111953514243e-05 loss: 0.1281 (0.1251) time: 2.9250 data: 0.0072 max mem: 33300 +Epoch: [18] [2480/4276] eta: 1:27:38 lr: 2.85003114447001e-05 loss: 0.1322 (0.1252) time: 2.9233 data: 0.0071 max mem: 33300 +Epoch: [18] [2490/4276] eta: 1:27:09 lr: 2.8497510905309543e-05 loss: 0.1312 (0.1252) time: 2.9267 data: 0.0073 max mem: 33300 +Epoch: [18] [2500/4276] eta: 1:26:40 lr: 2.8494710335338908e-05 loss: 0.1163 (0.1252) time: 2.9282 data: 0.0073 max mem: 33300 +Epoch: [18] [2510/4276] eta: 1:26:10 lr: 2.8491909734784506e-05 loss: 0.1293 (0.1252) time: 2.9279 data: 0.0072 max mem: 33300 +Epoch: [18] [2520/4276] eta: 1:25:41 lr: 2.848910910364268e-05 loss: 0.1081 (0.1252) time: 2.9304 data: 0.0072 max mem: 33300 +Epoch: [18] [2530/4276] eta: 1:25:12 lr: 2.8486308441909744e-05 loss: 0.0984 (0.1251) time: 2.9314 data: 0.0073 max mem: 33300 +Epoch: [18] [2540/4276] eta: 1:24:43 lr: 2.8483507749582022e-05 loss: 0.1056 (0.1251) time: 2.9296 data: 0.0074 max mem: 33300 +Epoch: [18] [2550/4276] eta: 1:24:14 lr: 2.8480707026655838e-05 loss: 0.1094 (0.1250) time: 2.9347 data: 0.0073 max mem: 33300 +Epoch: [18] [2560/4276] eta: 1:23:44 lr: 2.8477906273127526e-05 loss: 0.1056 (0.1250) time: 2.9352 data: 0.0072 max mem: 33300 +Epoch: [18] [2570/4276] eta: 1:23:15 lr: 2.8475105488993393e-05 loss: 0.1131 (0.1249) time: 2.9278 data: 0.0073 max mem: 33300 +Epoch: [18] [2580/4276] eta: 1:22:46 lr: 2.8472304674249762e-05 loss: 0.1155 (0.1249) time: 2.9283 data: 0.0073 max mem: 33300 +Epoch: [18] [2590/4276] eta: 1:22:16 lr: 2.846950382889296e-05 loss: 0.1149 (0.1249) time: 2.9287 data: 0.0071 max mem: 33300 +Epoch: [18] [2600/4276] eta: 1:21:47 lr: 2.84667029529193e-05 loss: 0.1136 (0.1249) time: 2.9278 data: 0.0071 max mem: 33300 +Epoch: [18] [2610/4276] eta: 1:21:18 lr: 2.84639020463251e-05 loss: 0.1134 (0.1248) time: 2.9291 data: 0.0073 max mem: 33300 +Epoch: [18] [2620/4276] eta: 1:20:49 lr: 2.8461101109106673e-05 loss: 0.1070 (0.1248) time: 2.9338 data: 0.0072 max mem: 33300 +Epoch: [18] [2630/4276] eta: 1:20:19 lr: 2.8458300141260347e-05 loss: 0.1070 (0.1248) time: 2.9331 data: 0.0071 max mem: 33300 +Epoch: [18] [2640/4276] eta: 1:19:50 lr: 2.8455499142782432e-05 loss: 0.1112 (0.1247) time: 2.9308 data: 0.0071 max mem: 33300 +Epoch: [18] [2650/4276] eta: 1:19:21 lr: 2.8452698113669247e-05 loss: 0.1112 (0.1247) time: 2.9309 data: 0.0073 max mem: 33300 +Epoch: [18] [2660/4276] eta: 1:18:51 lr: 2.844989705391709e-05 loss: 0.1174 (0.1247) time: 2.9269 data: 0.0072 max mem: 33300 +Epoch: [18] [2670/4276] eta: 1:18:22 lr: 2.8447095963522296e-05 loss: 0.1243 (0.1248) time: 2.9234 data: 0.0070 max mem: 33300 +Epoch: [18] [2680/4276] eta: 1:17:53 lr: 2.8444294842481163e-05 loss: 0.1234 (0.1248) time: 2.9197 data: 0.0075 max mem: 33300 +Epoch: [18] [2690/4276] eta: 1:17:24 lr: 2.844149369079e-05 loss: 0.1174 (0.1248) time: 2.9629 data: 0.0078 max mem: 33300 +Epoch: [18] [2700/4276] eta: 1:16:55 lr: 2.8438692508445124e-05 loss: 0.1081 (0.1248) time: 3.0109 data: 0.0077 max mem: 33300 +Epoch: [18] [2710/4276] eta: 1:16:26 lr: 2.843589129544285e-05 loss: 0.1081 (0.1247) time: 2.9768 data: 0.0077 max mem: 33300 +Epoch: [18] [2720/4276] eta: 1:15:57 lr: 2.8433090051779476e-05 loss: 0.1048 (0.1247) time: 2.9341 data: 0.0077 max mem: 33300 +Epoch: [18] [2730/4276] eta: 1:15:27 lr: 2.843028877745132e-05 loss: 0.1155 (0.1247) time: 2.9259 data: 0.0079 max mem: 33300 +Epoch: [18] [2740/4276] eta: 1:14:58 lr: 2.842748747245468e-05 loss: 0.1236 (0.1247) time: 2.9258 data: 0.0080 max mem: 33300 +Epoch: [18] [2750/4276] eta: 1:14:29 lr: 2.8424686136785867e-05 loss: 0.1258 (0.1248) time: 2.9255 data: 0.0078 max mem: 33300 +Epoch: [18] [2760/4276] eta: 1:14:00 lr: 2.842188477044118e-05 loss: 0.1268 (0.1248) time: 2.9267 data: 0.0078 max mem: 33300 +Epoch: [18] [2770/4276] eta: 1:13:30 lr: 2.8419083373416932e-05 loss: 0.1247 (0.1247) time: 2.9302 data: 0.0080 max mem: 33300 +Epoch: [18] [2780/4276] eta: 1:13:01 lr: 2.841628194570942e-05 loss: 0.1179 (0.1247) time: 2.9339 data: 0.0080 max mem: 33300 +Epoch: [18] [2790/4276] eta: 1:12:32 lr: 2.8413480487314958e-05 loss: 0.1166 (0.1248) time: 2.9335 data: 0.0077 max mem: 33300 +Epoch: [18] [2800/4276] eta: 1:12:02 lr: 2.8410678998229835e-05 loss: 0.1160 (0.1247) time: 2.9308 data: 0.0077 max mem: 33300 +Epoch: [18] [2810/4276] eta: 1:11:33 lr: 2.840787747845036e-05 loss: 0.1001 (0.1246) time: 2.9315 data: 0.0079 max mem: 33300 +Epoch: [18] [2820/4276] eta: 1:11:04 lr: 2.840507592797283e-05 loss: 0.0989 (0.1245) time: 2.9371 data: 0.0079 max mem: 33300 +Epoch: [18] [2830/4276] eta: 1:10:35 lr: 2.840227434679355e-05 loss: 0.1017 (0.1245) time: 2.9338 data: 0.0077 max mem: 33300 +Epoch: [18] [2840/4276] eta: 1:10:05 lr: 2.8399472734908806e-05 loss: 0.1169 (0.1245) time: 2.9289 data: 0.0078 max mem: 33300 +Epoch: [18] [2850/4276] eta: 1:09:36 lr: 2.83966710923149e-05 loss: 0.1300 (0.1246) time: 2.9316 data: 0.0076 max mem: 33300 +Epoch: [18] [2860/4276] eta: 1:09:07 lr: 2.839386941900814e-05 loss: 0.1317 (0.1246) time: 2.9305 data: 0.0073 max mem: 33300 +Epoch: [18] [2870/4276] eta: 1:08:38 lr: 2.8391067714984813e-05 loss: 0.1214 (0.1245) time: 2.9302 data: 0.0073 max mem: 33300 +Epoch: [18] [2880/4276] eta: 1:08:08 lr: 2.838826598024122e-05 loss: 0.1234 (0.1246) time: 2.9287 data: 0.0073 max mem: 33300 +Epoch: [18] [2890/4276] eta: 1:07:39 lr: 2.8385464214773643e-05 loss: 0.1200 (0.1245) time: 2.9282 data: 0.0073 max mem: 33300 +Epoch: [18] [2900/4276] eta: 1:07:10 lr: 2.8382662418578388e-05 loss: 0.1134 (0.1245) time: 2.9292 data: 0.0073 max mem: 33300 +Epoch: [18] [2910/4276] eta: 1:06:40 lr: 2.837986059165174e-05 loss: 0.1039 (0.1244) time: 2.9314 data: 0.0073 max mem: 33300 +Epoch: [18] [2920/4276] eta: 1:06:11 lr: 2.837705873399e-05 loss: 0.1102 (0.1244) time: 2.9319 data: 0.0073 max mem: 33300 +Epoch: [18] [2930/4276] eta: 1:05:42 lr: 2.837425684558944e-05 loss: 0.1102 (0.1244) time: 2.9312 data: 0.0074 max mem: 33300 +Epoch: [18] [2940/4276] eta: 1:05:13 lr: 2.8371454926446367e-05 loss: 0.1142 (0.1244) time: 2.9321 data: 0.0074 max mem: 33300 +Epoch: [18] [2950/4276] eta: 1:04:43 lr: 2.836865297655707e-05 loss: 0.1126 (0.1244) time: 2.9312 data: 0.0074 max mem: 33300 +Epoch: [18] [2960/4276] eta: 1:04:14 lr: 2.8365850995917838e-05 loss: 0.1143 (0.1244) time: 2.9292 data: 0.0074 max mem: 33300 +Epoch: [18] [2970/4276] eta: 1:03:45 lr: 2.8363048984524942e-05 loss: 0.1145 (0.1244) time: 2.9309 data: 0.0074 max mem: 33300 +Epoch: [18] [2980/4276] eta: 1:03:15 lr: 2.836024694237469e-05 loss: 0.1217 (0.1244) time: 2.9322 data: 0.0074 max mem: 33300 +Epoch: [18] [2990/4276] eta: 1:02:46 lr: 2.835744486946335e-05 loss: 0.1107 (0.1244) time: 2.9310 data: 0.0073 max mem: 33300 +Epoch: [18] [3000/4276] eta: 1:02:17 lr: 2.835464276578722e-05 loss: 0.1116 (0.1244) time: 2.9334 data: 0.0082 max mem: 33300 +Epoch: [18] [3010/4276] eta: 1:01:48 lr: 2.8351840631342575e-05 loss: 0.1145 (0.1244) time: 2.9309 data: 0.0089 max mem: 33300 +Epoch: [18] [3020/4276] eta: 1:01:18 lr: 2.8349038466125703e-05 loss: 0.1208 (0.1243) time: 2.9289 data: 0.0083 max mem: 33300 +Epoch: [18] [3030/4276] eta: 1:00:49 lr: 2.8346236270132886e-05 loss: 0.1193 (0.1243) time: 2.9244 data: 0.0079 max mem: 33300 +Epoch: [18] [3040/4276] eta: 1:00:20 lr: 2.8343434043360413e-05 loss: 0.1251 (0.1244) time: 2.9084 data: 0.0083 max mem: 33300 +Epoch: [18] [3050/4276] eta: 0:59:50 lr: 2.834063178580455e-05 loss: 0.1158 (0.1244) time: 2.8860 data: 0.0095 max mem: 33300 +Epoch: [18] [3060/4276] eta: 0:59:21 lr: 2.8337829497461587e-05 loss: 0.1118 (0.1243) time: 2.8786 data: 0.0099 max mem: 33300 +Epoch: [18] [3070/4276] eta: 0:58:51 lr: 2.8335027178327794e-05 loss: 0.1107 (0.1243) time: 2.8933 data: 0.0089 max mem: 33300 +Epoch: [18] [3080/4276] eta: 0:58:22 lr: 2.8332224828399458e-05 loss: 0.1107 (0.1243) time: 2.8822 data: 0.0088 max mem: 33300 +Epoch: [18] [3090/4276] eta: 0:57:52 lr: 2.8329422447672844e-05 loss: 0.1053 (0.1242) time: 2.8723 data: 0.0099 max mem: 33300 +Epoch: [18] [3100/4276] eta: 0:57:23 lr: 2.832662003614424e-05 loss: 0.1149 (0.1242) time: 2.8809 data: 0.0102 max mem: 33300 +Epoch: [18] [3110/4276] eta: 0:56:53 lr: 2.8323817593809925e-05 loss: 0.1097 (0.1241) time: 2.8830 data: 0.0094 max mem: 33300 +Epoch: [18] [3120/4276] eta: 0:56:24 lr: 2.8321015120666165e-05 loss: 0.1081 (0.1241) time: 2.8819 data: 0.0093 max mem: 33300 +Epoch: [18] [3130/4276] eta: 0:55:54 lr: 2.8318212616709234e-05 loss: 0.1098 (0.1241) time: 2.8824 data: 0.0096 max mem: 33300 +Epoch: [18] [3140/4276] eta: 0:55:25 lr: 2.8315410081935412e-05 loss: 0.1192 (0.1241) time: 2.9022 data: 0.0094 max mem: 33300 +Epoch: [18] [3150/4276] eta: 0:54:56 lr: 2.831260751634096e-05 loss: 0.1195 (0.1241) time: 2.9202 data: 0.0089 max mem: 33300 +Epoch: [18] [3160/4276] eta: 0:54:27 lr: 2.8309804919922157e-05 loss: 0.1121 (0.1240) time: 2.9313 data: 0.0086 max mem: 33300 +Epoch: [18] [3170/4276] eta: 0:53:57 lr: 2.8307002292675268e-05 loss: 0.1140 (0.1241) time: 2.9547 data: 0.0079 max mem: 33300 +Epoch: [18] [3180/4276] eta: 0:53:28 lr: 2.8304199634596562e-05 loss: 0.1142 (0.1240) time: 2.9608 data: 0.0072 max mem: 33300 +Epoch: [18] [3190/4276] eta: 0:52:59 lr: 2.8301396945682323e-05 loss: 0.1202 (0.1241) time: 2.9382 data: 0.0079 max mem: 33300 +Epoch: [18] [3200/4276] eta: 0:52:30 lr: 2.8298594225928797e-05 loss: 0.1337 (0.1241) time: 2.9109 data: 0.0087 max mem: 33300 +Epoch: [18] [3210/4276] eta: 0:52:00 lr: 2.8295791475332274e-05 loss: 0.1245 (0.1241) time: 2.9196 data: 0.0093 max mem: 33300 +Epoch: [18] [3220/4276] eta: 0:51:31 lr: 2.8292988693888993e-05 loss: 0.1232 (0.1241) time: 2.9382 data: 0.0093 max mem: 33300 +Epoch: [18] [3230/4276] eta: 0:51:03 lr: 2.8290185881595237e-05 loss: 0.1154 (0.1241) time: 3.0840 data: 0.0090 max mem: 33300 +Epoch: [18] [3240/4276] eta: 0:50:35 lr: 2.8287383038447262e-05 loss: 0.1372 (0.1241) time: 3.2514 data: 0.0090 max mem: 33300 +Epoch: [18] [3250/4276] eta: 0:50:06 lr: 2.8284580164441342e-05 loss: 0.1344 (0.1241) time: 3.2685 data: 0.0088 max mem: 33300 +Epoch: [18] [3260/4276] eta: 0:49:38 lr: 2.8281777259573726e-05 loss: 0.1193 (0.1241) time: 3.2592 data: 0.0089 max mem: 33300 +Epoch: [18] [3270/4276] eta: 0:49:10 lr: 2.8278974323840696e-05 loss: 0.1234 (0.1241) time: 3.2583 data: 0.0089 max mem: 33300 +Epoch: [18] [3280/4276] eta: 0:48:41 lr: 2.827617135723849e-05 loss: 0.1309 (0.1242) time: 3.2665 data: 0.0089 max mem: 33300 +Epoch: [18] [3290/4276] eta: 0:48:13 lr: 2.827336835976338e-05 loss: 0.1317 (0.1242) time: 3.2665 data: 0.0089 max mem: 33300 +Epoch: [18] [3300/4276] eta: 0:47:45 lr: 2.8270565331411626e-05 loss: 0.1386 (0.1242) time: 3.2635 data: 0.0094 max mem: 33300 +Epoch: [18] [3310/4276] eta: 0:47:16 lr: 2.8267762272179475e-05 loss: 0.1383 (0.1243) time: 3.2636 data: 0.0093 max mem: 33300 +Epoch: [18] [3320/4276] eta: 0:46:48 lr: 2.8264959182063195e-05 loss: 0.1326 (0.1243) time: 3.2645 data: 0.0094 max mem: 33300 +Epoch: [18] [3330/4276] eta: 0:46:19 lr: 2.8262156061059042e-05 loss: 0.1137 (0.1242) time: 3.2446 data: 0.0092 max mem: 33300 +Epoch: [18] [3340/4276] eta: 0:45:51 lr: 2.8259352909163266e-05 loss: 0.1149 (0.1242) time: 3.2234 data: 0.0089 max mem: 33300 +Epoch: [18] [3350/4276] eta: 0:45:22 lr: 2.825654972637213e-05 loss: 0.1149 (0.1242) time: 3.2215 data: 0.0087 max mem: 33300 +Epoch: [18] [3360/4276] eta: 0:44:54 lr: 2.8253746512681876e-05 loss: 0.1042 (0.1241) time: 3.2246 data: 0.0081 max mem: 33300 +Epoch: [18] [3370/4276] eta: 0:44:25 lr: 2.8250943268088776e-05 loss: 0.1097 (0.1242) time: 3.2474 data: 0.0080 max mem: 33300 +Epoch: [18] [3380/4276] eta: 0:43:56 lr: 2.8248139992589062e-05 loss: 0.1213 (0.1242) time: 3.2517 data: 0.0079 max mem: 33300 +Epoch: [18] [3390/4276] eta: 0:43:28 lr: 2.8245336686178992e-05 loss: 0.1225 (0.1242) time: 3.2150 data: 0.0077 max mem: 33300 +Epoch: [18] [3400/4276] eta: 0:42:59 lr: 2.8242533348854822e-05 loss: 0.1325 (0.1242) time: 3.2051 data: 0.0078 max mem: 33300 +Epoch: [18] [3410/4276] eta: 0:42:30 lr: 2.823972998061279e-05 loss: 0.1228 (0.1242) time: 3.2170 data: 0.0085 max mem: 33300 +Epoch: [18] [3420/4276] eta: 0:42:01 lr: 2.8236926581449157e-05 loss: 0.1248 (0.1242) time: 3.2078 data: 0.0089 max mem: 33300 +Epoch: [18] [3430/4276] eta: 0:41:33 lr: 2.823412315136017e-05 loss: 0.1289 (0.1242) time: 3.2257 data: 0.0086 max mem: 33300 +Epoch: [18] [3440/4276] eta: 0:41:04 lr: 2.8231319690342068e-05 loss: 0.1251 (0.1242) time: 3.2414 data: 0.0086 max mem: 33300 +Epoch: [18] [3450/4276] eta: 0:40:35 lr: 2.8228516198391108e-05 loss: 0.1235 (0.1242) time: 3.2187 data: 0.0089 max mem: 33300 +Epoch: [18] [3460/4276] eta: 0:40:06 lr: 2.822571267550352e-05 loss: 0.1449 (0.1243) time: 3.2123 data: 0.0085 max mem: 33300 +Epoch: [18] [3470/4276] eta: 0:39:37 lr: 2.8222909121675556e-05 loss: 0.1225 (0.1242) time: 3.1652 data: 0.0078 max mem: 33300 +Epoch: [18] [3480/4276] eta: 0:39:08 lr: 2.8220105536903463e-05 loss: 0.1225 (0.1243) time: 3.0578 data: 0.0074 max mem: 33300 +Epoch: [18] [3490/4276] eta: 0:38:38 lr: 2.8217301921183476e-05 loss: 0.1250 (0.1243) time: 3.0280 data: 0.0075 max mem: 33300 +Epoch: [18] [3500/4276] eta: 0:38:09 lr: 2.821449827451185e-05 loss: 0.1176 (0.1242) time: 2.9855 data: 0.0080 max mem: 33300 +Epoch: [18] [3510/4276] eta: 0:37:39 lr: 2.821169459688481e-05 loss: 0.1063 (0.1242) time: 2.9327 data: 0.0077 max mem: 33300 +Epoch: [18] [3520/4276] eta: 0:37:10 lr: 2.820889088829861e-05 loss: 0.1197 (0.1242) time: 2.9543 data: 0.0072 max mem: 33300 +Epoch: [18] [3530/4276] eta: 0:36:40 lr: 2.8206087148749477e-05 loss: 0.1197 (0.1242) time: 2.9440 data: 0.0076 max mem: 33300 +Epoch: [18] [3540/4276] eta: 0:36:11 lr: 2.8203283378233653e-05 loss: 0.1222 (0.1243) time: 2.9337 data: 0.0076 max mem: 33300 +Epoch: [18] [3550/4276] eta: 0:35:41 lr: 2.8200479576747374e-05 loss: 0.1171 (0.1243) time: 2.9565 data: 0.0074 max mem: 33300 +Epoch: [18] [3560/4276] eta: 0:35:12 lr: 2.8197675744286883e-05 loss: 0.1171 (0.1243) time: 2.9590 data: 0.0071 max mem: 33300 +Epoch: [18] [3570/4276] eta: 0:34:42 lr: 2.819487188084841e-05 loss: 0.1316 (0.1243) time: 2.9433 data: 0.0072 max mem: 33300 +Epoch: [18] [3580/4276] eta: 0:34:13 lr: 2.81920679864282e-05 loss: 0.1230 (0.1243) time: 2.9466 data: 0.0071 max mem: 33300 +Epoch: [18] [3590/4276] eta: 0:33:43 lr: 2.8189264061022476e-05 loss: 0.1216 (0.1243) time: 2.9448 data: 0.0068 max mem: 33300 +Epoch: [18] [3600/4276] eta: 0:33:14 lr: 2.818646010462747e-05 loss: 0.1205 (0.1243) time: 2.9407 data: 0.0068 max mem: 33300 +Epoch: [18] [3610/4276] eta: 0:32:44 lr: 2.818365611723942e-05 loss: 0.1205 (0.1243) time: 2.9512 data: 0.0068 max mem: 33300 +Epoch: [18] [3620/4276] eta: 0:32:15 lr: 2.8180852098854554e-05 loss: 0.1172 (0.1243) time: 2.9307 data: 0.0073 max mem: 33300 +Epoch: [18] [3630/4276] eta: 0:31:45 lr: 2.8178048049469097e-05 loss: 0.1197 (0.1243) time: 2.8987 data: 0.0078 max mem: 33300 +Epoch: [18] [3640/4276] eta: 0:31:16 lr: 2.817524396907929e-05 loss: 0.1175 (0.1243) time: 2.9210 data: 0.0075 max mem: 33300 +Epoch: [18] [3650/4276] eta: 0:30:46 lr: 2.8172439857681356e-05 loss: 0.1106 (0.1243) time: 2.9441 data: 0.0066 max mem: 33300 +Epoch: [18] [3660/4276] eta: 0:30:17 lr: 2.8169635715271532e-05 loss: 0.1141 (0.1242) time: 2.9424 data: 0.0062 max mem: 33300 +Epoch: [18] [3670/4276] eta: 0:29:47 lr: 2.8166831541846022e-05 loss: 0.1146 (0.1242) time: 2.9653 data: 0.0061 max mem: 33300 +Epoch: [18] [3680/4276] eta: 0:29:18 lr: 2.8164027337401077e-05 loss: 0.1146 (0.1242) time: 2.9650 data: 0.0063 max mem: 33300 +Epoch: [18] [3690/4276] eta: 0:28:48 lr: 2.8161223101932904e-05 loss: 0.1198 (0.1242) time: 2.9433 data: 0.0065 max mem: 33300 +Epoch: [18] [3700/4276] eta: 0:28:19 lr: 2.8158418835437734e-05 loss: 0.1169 (0.1242) time: 2.9450 data: 0.0064 max mem: 33300 +Epoch: [18] [3710/4276] eta: 0:27:49 lr: 2.815561453791179e-05 loss: 0.1054 (0.1242) time: 2.9389 data: 0.0062 max mem: 33300 +Epoch: [18] [3720/4276] eta: 0:27:19 lr: 2.8152810209351298e-05 loss: 0.1037 (0.1241) time: 2.9245 data: 0.0067 max mem: 33300 +Epoch: [18] [3730/4276] eta: 0:26:50 lr: 2.8150005849752475e-05 loss: 0.1053 (0.1241) time: 2.9145 data: 0.0068 max mem: 33300 +Epoch: [18] [3740/4276] eta: 0:26:20 lr: 2.814720145911155e-05 loss: 0.1154 (0.1241) time: 2.9229 data: 0.0069 max mem: 33300 +Epoch: [18] [3750/4276] eta: 0:25:51 lr: 2.814439703742473e-05 loss: 0.1258 (0.1241) time: 2.9382 data: 0.0073 max mem: 33300 +Epoch: [18] [3760/4276] eta: 0:25:21 lr: 2.814159258468825e-05 loss: 0.1204 (0.1241) time: 2.9437 data: 0.0073 max mem: 33300 +Epoch: [18] [3770/4276] eta: 0:24:52 lr: 2.8138788100898307e-05 loss: 0.1004 (0.1241) time: 2.9426 data: 0.0075 max mem: 33300 +Epoch: [18] [3780/4276] eta: 0:24:22 lr: 2.813598358605113e-05 loss: 0.1134 (0.1240) time: 2.9502 data: 0.0078 max mem: 33300 +Epoch: [18] [3790/4276] eta: 0:23:53 lr: 2.8133179040142937e-05 loss: 0.1088 (0.1240) time: 2.9602 data: 0.0078 max mem: 33300 +Epoch: [18] [3800/4276] eta: 0:23:23 lr: 2.8130374463169938e-05 loss: 0.1096 (0.1241) time: 2.9504 data: 0.0075 max mem: 33300 +Epoch: [18] [3810/4276] eta: 0:22:54 lr: 2.812756985512836e-05 loss: 0.1096 (0.1240) time: 2.9395 data: 0.0074 max mem: 33300 +Epoch: [18] [3820/4276] eta: 0:22:24 lr: 2.8124765216014398e-05 loss: 0.1035 (0.1240) time: 2.9410 data: 0.0076 max mem: 33300 +Epoch: [18] [3830/4276] eta: 0:21:55 lr: 2.8121960545824284e-05 loss: 0.1035 (0.1240) time: 2.9545 data: 0.0076 max mem: 33300 +Epoch: [18] [3840/4276] eta: 0:21:25 lr: 2.8119155844554214e-05 loss: 0.1141 (0.1239) time: 2.9273 data: 0.0073 max mem: 33300 +Epoch: [18] [3850/4276] eta: 0:20:56 lr: 2.8116351112200407e-05 loss: 0.1027 (0.1239) time: 2.8824 data: 0.0070 max mem: 33300 +Epoch: [18] [3860/4276] eta: 0:20:26 lr: 2.8113546348759067e-05 loss: 0.1056 (0.1239) time: 2.8749 data: 0.0069 max mem: 33300 +Epoch: [18] [3870/4276] eta: 0:19:57 lr: 2.811074155422641e-05 loss: 0.1160 (0.1238) time: 2.8818 data: 0.0067 max mem: 33300 +Epoch: [18] [3880/4276] eta: 0:19:27 lr: 2.8107936728598643e-05 loss: 0.1115 (0.1238) time: 2.8890 data: 0.0062 max mem: 33300 +Epoch: [18] [3890/4276] eta: 0:18:58 lr: 2.8105131871871983e-05 loss: 0.1232 (0.1239) time: 2.8858 data: 0.0061 max mem: 33300 +Epoch: [18] [3900/4276] eta: 0:18:28 lr: 2.8102326984042615e-05 loss: 0.1247 (0.1239) time: 2.8878 data: 0.0063 max mem: 33300 +Epoch: [18] [3910/4276] eta: 0:17:59 lr: 2.8099522065106758e-05 loss: 0.1013 (0.1238) time: 2.9429 data: 0.0065 max mem: 33300 +Epoch: [18] [3920/4276] eta: 0:17:29 lr: 2.8096717115060618e-05 loss: 0.1013 (0.1238) time: 2.9747 data: 0.0074 max mem: 33300 +Epoch: [18] [3930/4276] eta: 0:17:00 lr: 2.809391213390039e-05 loss: 0.1091 (0.1238) time: 2.9273 data: 0.0079 max mem: 33300 +Epoch: [18] [3940/4276] eta: 0:16:30 lr: 2.8091107121622288e-05 loss: 0.1306 (0.1238) time: 2.8964 data: 0.0073 max mem: 33300 +Epoch: [18] [3950/4276] eta: 0:16:01 lr: 2.8088302078222506e-05 loss: 0.1221 (0.1238) time: 2.8913 data: 0.0065 max mem: 33300 +Epoch: [18] [3960/4276] eta: 0:15:31 lr: 2.8085497003697247e-05 loss: 0.1221 (0.1238) time: 2.8889 data: 0.0062 max mem: 33300 +Epoch: [18] [3970/4276] eta: 0:15:02 lr: 2.8082691898042725e-05 loss: 0.1262 (0.1238) time: 2.9050 data: 0.0064 max mem: 33300 +Epoch: [18] [3980/4276] eta: 0:14:32 lr: 2.8079886761255114e-05 loss: 0.1194 (0.1238) time: 2.9251 data: 0.0068 max mem: 33300 +Epoch: [18] [3990/4276] eta: 0:14:03 lr: 2.8077081593330636e-05 loss: 0.1063 (0.1238) time: 2.9442 data: 0.0069 max mem: 33300 +Epoch: [18] [4000/4276] eta: 0:13:33 lr: 2.8074276394265476e-05 loss: 0.1094 (0.1238) time: 2.9294 data: 0.0068 max mem: 33300 +Epoch: [18] [4010/4276] eta: 0:13:04 lr: 2.807147116405583e-05 loss: 0.1222 (0.1238) time: 2.9207 data: 0.0069 max mem: 33300 +Epoch: [18] [4020/4276] eta: 0:12:34 lr: 2.8068665902697898e-05 loss: 0.1188 (0.1238) time: 2.9441 data: 0.0066 max mem: 33300 +Epoch: [18] [4030/4276] eta: 0:12:05 lr: 2.8065860610187877e-05 loss: 0.1131 (0.1238) time: 2.9610 data: 0.0065 max mem: 33300 +Epoch: [18] [4040/4276] eta: 0:11:35 lr: 2.8063055286521955e-05 loss: 0.1131 (0.1238) time: 2.9637 data: 0.0064 max mem: 33300 +Epoch: [18] [4050/4276] eta: 0:11:06 lr: 2.8060249931696344e-05 loss: 0.1136 (0.1238) time: 2.9519 data: 0.0062 max mem: 33300 +Epoch: [18] [4060/4276] eta: 0:10:36 lr: 2.8057444545707207e-05 loss: 0.1235 (0.1238) time: 2.9546 data: 0.0066 max mem: 33300 +Epoch: [18] [4070/4276] eta: 0:10:07 lr: 2.8054639128550762e-05 loss: 0.1259 (0.1238) time: 2.9509 data: 0.0064 max mem: 33300 +Epoch: [18] [4080/4276] eta: 0:09:37 lr: 2.8051833680223176e-05 loss: 0.1259 (0.1238) time: 2.9453 data: 0.0062 max mem: 33300 +Epoch: [18] [4090/4276] eta: 0:09:08 lr: 2.804902820072066e-05 loss: 0.1255 (0.1238) time: 2.9459 data: 0.0061 max mem: 33300 +Epoch: [18] [4100/4276] eta: 0:08:38 lr: 2.804622269003939e-05 loss: 0.1222 (0.1238) time: 2.9616 data: 0.0060 max mem: 33300 +Epoch: [18] [4110/4276] eta: 0:08:09 lr: 2.804341714817556e-05 loss: 0.1173 (0.1238) time: 2.9643 data: 0.0062 max mem: 33300 +Epoch: [18] [4120/4276] eta: 0:07:39 lr: 2.804061157512536e-05 loss: 0.1164 (0.1238) time: 2.9529 data: 0.0064 max mem: 33300 +Epoch: [18] [4130/4276] eta: 0:07:10 lr: 2.803780597088496e-05 loss: 0.1140 (0.1238) time: 2.9550 data: 0.0066 max mem: 33300 +Epoch: [18] [4140/4276] eta: 0:06:40 lr: 2.8035000335450572e-05 loss: 0.1088 (0.1238) time: 2.9314 data: 0.0069 max mem: 33300 +Epoch: [18] [4150/4276] eta: 0:06:11 lr: 2.8032194668818353e-05 loss: 0.1200 (0.1238) time: 2.9323 data: 0.0065 max mem: 33300 +Epoch: [18] [4160/4276] eta: 0:05:41 lr: 2.80293889709845e-05 loss: 0.1319 (0.1239) time: 2.9695 data: 0.0061 max mem: 33300 +Epoch: [18] [4170/4276] eta: 0:05:12 lr: 2.8026583241945197e-05 loss: 0.1300 (0.1239) time: 2.9401 data: 0.0061 max mem: 33300 +Epoch: [18] [4180/4276] eta: 0:04:42 lr: 2.8023777481696624e-05 loss: 0.1274 (0.1239) time: 2.8973 data: 0.0060 max mem: 33300 +Epoch: [18] [4190/4276] eta: 0:04:13 lr: 2.8020971690234954e-05 loss: 0.1176 (0.1239) time: 2.8994 data: 0.0059 max mem: 33300 +Epoch: [18] [4200/4276] eta: 0:03:44 lr: 2.801816586755639e-05 loss: 0.1180 (0.1240) time: 2.9026 data: 0.0059 max mem: 33300 +Epoch: [18] [4210/4276] eta: 0:03:14 lr: 2.801536001365708e-05 loss: 0.1330 (0.1240) time: 2.9155 data: 0.0060 max mem: 33300 +Epoch: [18] [4220/4276] eta: 0:02:45 lr: 2.801255412853323e-05 loss: 0.1359 (0.1241) time: 2.9437 data: 0.0061 max mem: 33300 +Epoch: [18] [4230/4276] eta: 0:02:15 lr: 2.8009748212180993e-05 loss: 0.1350 (0.1241) time: 2.9459 data: 0.0064 max mem: 33300 +Epoch: [18] [4240/4276] eta: 0:01:46 lr: 2.8006942264596565e-05 loss: 0.1303 (0.1241) time: 2.9411 data: 0.0068 max mem: 33300 +Epoch: [18] [4250/4276] eta: 0:01:16 lr: 2.8004136285776106e-05 loss: 0.1273 (0.1242) time: 2.9477 data: 0.0065 max mem: 33300 +Epoch: [18] [4260/4276] eta: 0:00:47 lr: 2.8001330275715805e-05 loss: 0.1273 (0.1242) time: 2.9515 data: 0.0063 max mem: 33300 +Epoch: [18] [4270/4276] eta: 0:00:17 lr: 2.799852423441182e-05 loss: 0.1299 (0.1242) time: 2.9703 data: 0.0062 max mem: 33300 +Epoch: [18] Total time: 3:30:03 +Test: [ 0/21770] eta: 11:01:12 time: 1.8224 data: 1.7838 max mem: 33300 +Test: [ 100/21770] eta: 0:19:56 time: 0.0378 data: 0.0009 max mem: 33300 +Test: [ 200/21770] eta: 0:16:41 time: 0.0376 data: 0.0008 max mem: 33300 +Test: [ 300/21770] eta: 0:15:33 time: 0.0375 data: 0.0008 max mem: 33300 +Test: [ 400/21770] eta: 0:14:57 time: 0.0376 data: 0.0008 max mem: 33300 +Test: [ 500/21770] eta: 0:14:34 time: 0.0376 data: 0.0008 max mem: 33300 +Test: [ 600/21770] eta: 0:14:18 time: 0.0379 data: 0.0010 max mem: 33300 +Test: [ 700/21770] eta: 0:14:06 time: 0.0377 data: 0.0009 max mem: 33300 +Test: [ 800/21770] eta: 0:13:56 time: 0.0379 data: 0.0010 max mem: 33300 +Test: [ 900/21770] eta: 0:13:48 time: 0.0383 data: 0.0010 max mem: 33300 +Test: [ 1000/21770] eta: 0:13:41 time: 0.0385 data: 0.0009 max mem: 33300 +Test: [ 1100/21770] eta: 0:13:34 time: 0.0380 data: 0.0010 max mem: 33300 +Test: [ 1200/21770] eta: 0:13:27 time: 0.0375 data: 0.0008 max mem: 33300 +Test: [ 1300/21770] eta: 0:13:21 time: 0.0377 data: 0.0008 max mem: 33300 +Test: [ 1400/21770] eta: 0:13:14 time: 0.0376 data: 0.0008 max mem: 33300 +Test: [ 1500/21770] eta: 0:13:09 time: 0.0376 data: 0.0008 max mem: 33300 +Test: [ 1600/21770] eta: 0:13:03 time: 0.0375 data: 0.0008 max mem: 33300 +Test: [ 1700/21770] eta: 0:12:58 time: 0.0376 data: 0.0008 max mem: 33300 +Test: [ 1800/21770] eta: 0:12:52 time: 0.0376 data: 0.0008 max mem: 33300 +Test: [ 1900/21770] eta: 0:12:47 time: 0.0375 data: 0.0008 max mem: 33300 +Test: [ 2000/21770] eta: 0:12:42 time: 0.0376 data: 0.0009 max mem: 33300 +Test: [ 2100/21770] eta: 0:12:38 time: 0.0374 data: 0.0008 max mem: 33300 +Test: [ 2200/21770] eta: 0:12:33 time: 0.0377 data: 0.0008 max mem: 33300 +Test: [ 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time: 0.0379 data: 0.0008 max mem: 33300 +Test: [ 3700/21770] eta: 0:11:32 time: 0.0380 data: 0.0008 max mem: 33300 +Test: [ 3800/21770] eta: 0:11:28 time: 0.0377 data: 0.0008 max mem: 33300 +Test: [ 3900/21770] eta: 0:11:24 time: 0.0377 data: 0.0009 max mem: 33300 +Test: [ 4000/21770] eta: 0:11:20 time: 0.0377 data: 0.0008 max mem: 33300 +Test: [ 4100/21770] eta: 0:11:16 time: 0.0377 data: 0.0009 max mem: 33300 +Test: [ 4200/21770] eta: 0:11:12 time: 0.0377 data: 0.0008 max mem: 33300 +Test: [ 4300/21770] eta: 0:11:07 time: 0.0377 data: 0.0008 max mem: 33300 +Test: [ 4400/21770] eta: 0:11:03 time: 0.0380 data: 0.0008 max mem: 33300 +Test: [ 4500/21770] eta: 0:11:00 time: 0.0380 data: 0.0008 max mem: 33300 +Test: [ 4600/21770] eta: 0:10:56 time: 0.0379 data: 0.0009 max mem: 33300 +Test: [ 4700/21770] eta: 0:10:52 time: 0.0381 data: 0.0008 max mem: 33300 +Test: [ 4800/21770] eta: 0:10:48 time: 0.0378 data: 0.0008 max mem: 33300 +Test: [ 4900/21770] eta: 0:10:44 time: 0.0382 data: 0.0008 max mem: 33300 +Test: [ 5000/21770] eta: 0:10:40 time: 0.0384 data: 0.0008 max mem: 33300 +Test: [ 5100/21770] eta: 0:10:36 time: 0.0383 data: 0.0008 max mem: 33300 +Test: [ 5200/21770] eta: 0:10:33 time: 0.0386 data: 0.0009 max mem: 33300 +Test: [ 5300/21770] eta: 0:10:29 time: 0.0391 data: 0.0010 max mem: 33300 +Test: [ 5400/21770] eta: 0:10:25 time: 0.0389 data: 0.0010 max mem: 33300 +Test: [ 5500/21770] eta: 0:10:22 time: 0.0387 data: 0.0009 max mem: 33300 +Test: [ 5600/21770] eta: 0:10:18 time: 0.0388 data: 0.0009 max mem: 33300 +Test: [ 5700/21770] eta: 0:10:14 time: 0.0388 data: 0.0009 max mem: 33300 +Test: [ 5800/21770] eta: 0:10:11 time: 0.0388 data: 0.0008 max mem: 33300 +Test: [ 5900/21770] eta: 0:10:07 time: 0.0387 data: 0.0008 max mem: 33300 +Test: [ 6000/21770] eta: 0:10:03 time: 0.0387 data: 0.0008 max mem: 33300 +Test: [ 6100/21770] eta: 0:10:00 time: 0.0387 data: 0.0008 max mem: 33300 +Test: [ 6200/21770] eta: 0:09:56 time: 0.0382 data: 0.0008 max mem: 33300 +Test: [ 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time: 0.0377 data: 0.0008 max mem: 33300 +Test: [ 7700/21770] eta: 0:08:58 time: 0.0378 data: 0.0008 max mem: 33300 +Test: [ 7800/21770] eta: 0:08:54 time: 0.0377 data: 0.0008 max mem: 33300 +Test: [ 7900/21770] eta: 0:08:50 time: 0.0377 data: 0.0009 max mem: 33300 +Test: [ 8000/21770] eta: 0:08:46 time: 0.0377 data: 0.0008 max mem: 33300 +Test: [ 8100/21770] eta: 0:08:42 time: 0.0376 data: 0.0008 max mem: 33300 +Test: [ 8200/21770] eta: 0:08:38 time: 0.0376 data: 0.0008 max mem: 33300 +Test: [ 8300/21770] eta: 0:08:34 time: 0.0378 data: 0.0008 max mem: 33300 +Test: [ 8400/21770] eta: 0:08:30 time: 0.0380 data: 0.0009 max mem: 33300 +Test: [ 8500/21770] eta: 0:08:26 time: 0.0380 data: 0.0008 max mem: 33300 +Test: [ 8600/21770] eta: 0:08:23 time: 0.0379 data: 0.0008 max mem: 33300 +Test: [ 8700/21770] eta: 0:08:19 time: 0.0381 data: 0.0008 max mem: 33300 +Test: [ 8800/21770] eta: 0:08:15 time: 0.0381 data: 0.0008 max mem: 33300 +Test: [ 8900/21770] eta: 0:08:11 time: 0.0383 data: 0.0009 max mem: 33300 +Test: [ 9000/21770] eta: 0:08:07 time: 0.0381 data: 0.0009 max mem: 33300 +Test: [ 9100/21770] eta: 0:08:03 time: 0.0381 data: 0.0009 max mem: 33300 +Test: [ 9200/21770] eta: 0:08:00 time: 0.0380 data: 0.0009 max mem: 33300 +Test: [ 9300/21770] eta: 0:07:56 time: 0.0385 data: 0.0010 max mem: 33300 +Test: [ 9400/21770] eta: 0:07:52 time: 0.0388 data: 0.0011 max mem: 33300 +Test: [ 9500/21770] eta: 0:07:48 time: 0.0383 data: 0.0010 max mem: 33300 +Test: [ 9600/21770] eta: 0:07:44 time: 0.0380 data: 0.0010 max mem: 33300 +Test: [ 9700/21770] eta: 0:07:41 time: 0.0382 data: 0.0010 max mem: 33300 +Test: [ 9800/21770] eta: 0:07:37 time: 0.0380 data: 0.0009 max mem: 33300 +Test: [ 9900/21770] eta: 0:07:33 time: 0.0380 data: 0.0009 max mem: 33300 +Test: [10000/21770] eta: 0:07:29 time: 0.0379 data: 0.0009 max mem: 33300 +Test: [10100/21770] eta: 0:07:25 time: 0.0381 data: 0.0009 max mem: 33300 +Test: [10200/21770] eta: 0:07:21 time: 0.0380 data: 0.0009 max mem: 33300 +Test: [10300/21770] eta: 0:07:18 time: 0.0380 data: 0.0009 max mem: 33300 +Test: [10400/21770] eta: 0:07:14 time: 0.0382 data: 0.0009 max mem: 33300 +Test: [10500/21770] eta: 0:07:10 time: 0.0378 data: 0.0009 max mem: 33300 +Test: [10600/21770] eta: 0:07:06 time: 0.0378 data: 0.0009 max mem: 33300 +Test: [10700/21770] eta: 0:07:02 time: 0.0378 data: 0.0009 max mem: 33300 +Test: [10800/21770] eta: 0:06:58 time: 0.0376 data: 0.0009 max mem: 33300 +Test: [10900/21770] eta: 0:06:54 time: 0.0377 data: 0.0009 max mem: 33300 +Test: [11000/21770] eta: 0:06:51 time: 0.0380 data: 0.0009 max mem: 33300 +Test: [11100/21770] eta: 0:06:47 time: 0.0379 data: 0.0009 max mem: 33300 +Test: [11200/21770] eta: 0:06:43 time: 0.0378 data: 0.0008 max mem: 33300 +Test: [11300/21770] eta: 0:06:39 time: 0.0378 data: 0.0009 max mem: 33300 +Test: [11400/21770] eta: 0:06:35 time: 0.0378 data: 0.0008 max mem: 33300 +Test: [11500/21770] eta: 0:06:31 time: 0.0376 data: 0.0009 max mem: 33300 +Test: [11600/21770] eta: 0:06:28 time: 0.0380 data: 0.0009 max mem: 33300 +Test: [11700/21770] eta: 0:06:24 time: 0.0379 data: 0.0009 max mem: 33300 +Test: [11800/21770] eta: 0:06:20 time: 0.0376 data: 0.0009 max mem: 33300 +Test: [11900/21770] eta: 0:06:16 time: 0.0377 data: 0.0009 max mem: 33300 +Test: [12000/21770] eta: 0:06:12 time: 0.0380 data: 0.0009 max mem: 33300 +Test: [12100/21770] eta: 0:06:08 time: 0.0379 data: 0.0009 max mem: 33300 +Test: [12200/21770] eta: 0:06:04 time: 0.0377 data: 0.0009 max mem: 33300 +Test: [12300/21770] eta: 0:06:01 time: 0.0377 data: 0.0009 max mem: 33300 +Test: [12400/21770] eta: 0:05:57 time: 0.0377 data: 0.0008 max mem: 33300 +Test: [12500/21770] eta: 0:05:53 time: 0.0379 data: 0.0009 max mem: 33300 +Test: [12600/21770] eta: 0:05:49 time: 0.0376 data: 0.0009 max mem: 33300 +Test: [12700/21770] eta: 0:05:45 time: 0.0377 data: 0.0009 max mem: 33300 +Test: [12800/21770] eta: 0:05:41 time: 0.0378 data: 0.0009 max mem: 33300 +Test: [12900/21770] eta: 0:05:38 time: 0.0376 data: 0.0008 max mem: 33300 +Test: [13000/21770] eta: 0:05:34 time: 0.0377 data: 0.0009 max mem: 33300 +Test: [13100/21770] eta: 0:05:30 time: 0.0383 data: 0.0009 max mem: 33300 +Test: [13200/21770] eta: 0:05:26 time: 0.0382 data: 0.0009 max mem: 33300 +Test: [13300/21770] eta: 0:05:22 time: 0.0376 data: 0.0009 max mem: 33300 +Test: [13400/21770] eta: 0:05:18 time: 0.0377 data: 0.0009 max mem: 33300 +Test: [13500/21770] eta: 0:05:15 time: 0.0377 data: 0.0009 max mem: 33300 +Test: [13600/21770] eta: 0:05:11 time: 0.0377 data: 0.0009 max mem: 33300 +Test: [13700/21770] eta: 0:05:07 time: 0.0377 data: 0.0009 max mem: 33300 +Test: [13800/21770] eta: 0:05:03 time: 0.0376 data: 0.0009 max mem: 33300 +Test: [13900/21770] eta: 0:04:59 time: 0.0377 data: 0.0009 max mem: 33300 +Test: [14000/21770] eta: 0:04:55 time: 0.0376 data: 0.0009 max mem: 33300 +Test: [14100/21770] eta: 0:04:52 time: 0.0376 data: 0.0009 max mem: 33300 +Test: [14200/21770] eta: 0:04:48 time: 0.0377 data: 0.0009 max mem: 33300 +Test: [14300/21770] eta: 0:04:44 time: 0.0376 data: 0.0009 max mem: 33300 +Test: [14400/21770] eta: 0:04:40 time: 0.0384 data: 0.0010 max mem: 33300 +Test: [14500/21770] eta: 0:04:36 time: 0.0383 data: 0.0010 max mem: 33300 +Test: [14600/21770] eta: 0:04:33 time: 0.0382 data: 0.0009 max mem: 33300 +Test: [14700/21770] eta: 0:04:29 time: 0.0384 data: 0.0010 max mem: 33300 +Test: [14800/21770] eta: 0:04:25 time: 0.0385 data: 0.0010 max mem: 33300 +Test: [14900/21770] eta: 0:04:21 time: 0.0384 data: 0.0009 max mem: 33300 +Test: [15000/21770] eta: 0:04:17 time: 0.0380 data: 0.0009 max mem: 33300 +Test: [15100/21770] eta: 0:04:14 time: 0.0383 data: 0.0009 max mem: 33300 +Test: [15200/21770] eta: 0:04:10 time: 0.0386 data: 0.0009 max mem: 33300 +Test: [15300/21770] eta: 0:04:06 time: 0.0390 data: 0.0009 max mem: 33300 +Test: [15400/21770] eta: 0:04:02 time: 0.0387 data: 0.0009 max mem: 33300 +Test: [15500/21770] eta: 0:03:58 time: 0.0391 data: 0.0009 max mem: 33300 +Test: [15600/21770] eta: 0:03:55 time: 0.0392 data: 0.0009 max mem: 33300 +Test: [15700/21770] eta: 0:03:51 time: 0.0397 data: 0.0009 max mem: 33300 +Test: [15800/21770] eta: 0:03:47 time: 0.0387 data: 0.0009 max mem: 33300 +Test: [15900/21770] eta: 0:03:43 time: 0.0390 data: 0.0009 max mem: 33300 +Test: [16000/21770] eta: 0:03:40 time: 0.0386 data: 0.0009 max mem: 33300 +Test: [16100/21770] eta: 0:03:36 time: 0.0389 data: 0.0009 max mem: 33300 +Test: [16200/21770] eta: 0:03:32 time: 0.0378 data: 0.0009 max mem: 33300 +Test: [16300/21770] eta: 0:03:28 time: 0.0381 data: 0.0009 max mem: 33300 +Test: [16400/21770] eta: 0:03:24 time: 0.0381 data: 0.0009 max mem: 33300 +Test: [16500/21770] eta: 0:03:20 time: 0.0378 data: 0.0009 max mem: 33300 +Test: [16600/21770] eta: 0:03:17 time: 0.0380 data: 0.0009 max mem: 33300 +Test: [16700/21770] eta: 0:03:13 time: 0.0378 data: 0.0009 max mem: 33300 +Test: [16800/21770] eta: 0:03:09 time: 0.0380 data: 0.0009 max mem: 33300 +Test: [16900/21770] eta: 0:03:05 time: 0.0379 data: 0.0008 max mem: 33300 +Test: [17000/21770] eta: 0:03:01 time: 0.0378 data: 0.0009 max mem: 33300 +Test: [17100/21770] eta: 0:02:58 time: 0.0382 data: 0.0008 max mem: 33300 +Test: [17200/21770] eta: 0:02:54 time: 0.0379 data: 0.0009 max mem: 33300 +Test: [17300/21770] eta: 0:02:50 time: 0.0380 data: 0.0009 max mem: 33300 +Test: [17400/21770] eta: 0:02:46 time: 0.0378 data: 0.0008 max mem: 33300 +Test: [17500/21770] eta: 0:02:42 time: 0.0378 data: 0.0009 max mem: 33300 +Test: [17600/21770] eta: 0:02:38 time: 0.0377 data: 0.0008 max mem: 33300 +Test: [17700/21770] eta: 0:02:35 time: 0.0379 data: 0.0009 max mem: 33300 +Test: [17800/21770] eta: 0:02:31 time: 0.0379 data: 0.0009 max mem: 33300 +Test: [17900/21770] eta: 0:02:27 time: 0.0380 data: 0.0009 max mem: 33300 +Test: [18000/21770] eta: 0:02:23 time: 0.0378 data: 0.0009 max mem: 33300 +Test: [18100/21770] eta: 0:02:19 time: 0.0376 data: 0.0009 max mem: 33300 +Test: [18200/21770] eta: 0:02:16 time: 0.0377 data: 0.0009 max mem: 33300 +Test: [18300/21770] eta: 0:02:12 time: 0.0378 data: 0.0009 max mem: 33300 +Test: [18400/21770] eta: 0:02:08 time: 0.0381 data: 0.0009 max mem: 33300 +Test: [18500/21770] eta: 0:02:04 time: 0.0379 data: 0.0009 max mem: 33300 +Test: [18600/21770] eta: 0:02:00 time: 0.0379 data: 0.0008 max mem: 33300 +Test: [18700/21770] eta: 0:01:56 time: 0.0381 data: 0.0008 max mem: 33300 +Test: [18800/21770] eta: 0:01:53 time: 0.0377 data: 0.0008 max mem: 33300 +Test: [18900/21770] eta: 0:01:49 time: 0.0377 data: 0.0008 max mem: 33300 +Test: [19000/21770] eta: 0:01:45 time: 0.0384 data: 0.0009 max mem: 33300 +Test: [19100/21770] eta: 0:01:41 time: 0.0380 data: 0.0009 max mem: 33300 +Test: [19200/21770] eta: 0:01:37 time: 0.0383 data: 0.0010 max mem: 33300 +Test: [19300/21770] eta: 0:01:34 time: 0.0384 data: 0.0009 max mem: 33300 +Test: [19400/21770] eta: 0:01:30 time: 0.0382 data: 0.0008 max mem: 33300 +Test: [19500/21770] eta: 0:01:26 time: 0.0384 data: 0.0009 max mem: 33300 +Test: [19600/21770] eta: 0:01:22 time: 0.0378 data: 0.0009 max mem: 33300 +Test: [19700/21770] eta: 0:01:18 time: 0.0378 data: 0.0008 max mem: 33300 +Test: [19800/21770] eta: 0:01:15 time: 0.0379 data: 0.0008 max mem: 33300 +Test: [19900/21770] eta: 0:01:11 time: 0.0379 data: 0.0009 max mem: 33300 +Test: [20000/21770] eta: 0:01:07 time: 0.0381 data: 0.0009 max mem: 33300 +Test: [20100/21770] eta: 0:01:03 time: 0.0382 data: 0.0008 max mem: 33300 +Test: [20200/21770] eta: 0:00:59 time: 0.0381 data: 0.0008 max mem: 33300 +Test: [20300/21770] eta: 0:00:56 time: 0.0380 data: 0.0009 max mem: 33300 +Test: [20400/21770] eta: 0:00:52 time: 0.0378 data: 0.0008 max mem: 33300 +Test: [20500/21770] eta: 0:00:48 time: 0.0379 data: 0.0008 max mem: 33300 +Test: [20600/21770] eta: 0:00:44 time: 0.0378 data: 0.0008 max mem: 33300 +Test: [20700/21770] eta: 0:00:40 time: 0.0378 data: 0.0008 max mem: 33300 +Test: [20800/21770] eta: 0:00:36 time: 0.0377 data: 0.0008 max mem: 33300 +Test: [20900/21770] eta: 0:00:33 time: 0.0386 data: 0.0008 max mem: 33300 +Test: [21000/21770] eta: 0:00:29 time: 0.0390 data: 0.0008 max mem: 33300 +Test: [21100/21770] eta: 0:00:25 time: 0.0389 data: 0.0009 max mem: 33300 +Test: [21200/21770] eta: 0:00:21 time: 0.0390 data: 0.0008 max mem: 33300 +Test: [21300/21770] eta: 0:00:17 time: 0.0386 data: 0.0008 max mem: 33300 +Test: [21400/21770] eta: 0:00:14 time: 0.0391 data: 0.0008 max mem: 33300 +Test: [21500/21770] eta: 0:00:10 time: 0.0387 data: 0.0008 max mem: 33300 +Test: [21600/21770] eta: 0:00:06 time: 0.0391 data: 0.0008 max mem: 33300 +Test: [21700/21770] eta: 0:00:02 time: 0.0385 data: 0.0008 max mem: 33300 +Test: Total time: 0:13:50 +Final results: +Mean IoU is 0.00 + + precision@0.5 = 0.00 + precision@0.6 = 0.00 + precision@0.7 = 0.00 + precision@0.8 = 0.00 + precision@0.9 = 0.00 + overall IoU = 0.00 + mean IoU = 0.00 + +Mean accuracy for one-to-zero sample is 100.00 + +Average object IoU 0.0 +Overall IoU 0.0 +Epoch: [19] [ 0/4276] eta: 6:12:54 lr: 2.7996840594630887e-05 loss: 0.1021 (0.1021) time: 5.2327 data: 2.1159 max mem: 33300 +Epoch: [19] [ 10/4276] eta: 3:45:29 lr: 2.7994034503329064e-05 loss: 0.1166 (0.1206) time: 3.1715 data: 0.1985 max mem: 33300 +Epoch: [19] [ 20/4276] eta: 3:38:01 lr: 2.7991228380773616e-05 loss: 0.1166 (0.1239) time: 2.9656 data: 0.0062 max mem: 33300 +Epoch: [19] [ 30/4276] eta: 3:35:50 lr: 2.7988422226960714e-05 loss: 0.1100 (0.1226) time: 2.9832 data: 0.0064 max mem: 33300 +Epoch: [19] [ 40/4276] eta: 3:33:49 lr: 2.798561604188652e-05 loss: 0.1163 (0.1231) time: 2.9817 data: 0.0068 max mem: 33300 +Epoch: [19] [ 50/4276] eta: 3:32:25 lr: 2.798280982554722e-05 loss: 0.1204 (0.1225) time: 2.9631 data: 0.0065 max mem: 33300 +Epoch: [19] [ 60/4276] eta: 3:31:16 lr: 2.7980003577938957e-05 loss: 0.1135 (0.1208) time: 2.9616 data: 0.0068 max mem: 33300 +Epoch: [19] [ 70/4276] eta: 3:30:16 lr: 2.7977197299057917e-05 loss: 0.1091 (0.1198) time: 2.9584 data: 0.0069 max mem: 33300 +Epoch: [19] [ 80/4276] eta: 3:29:25 lr: 2.7974390988900256e-05 loss: 0.1109 (0.1201) time: 2.9576 data: 0.0067 max mem: 33300 +Epoch: [19] [ 90/4276] eta: 3:28:45 lr: 2.797158464746214e-05 loss: 0.1132 (0.1198) time: 2.9651 data: 0.0065 max mem: 33300 +Epoch: [19] [ 100/4276] eta: 3:28:07 lr: 2.7968778274739736e-05 loss: 0.1178 (0.1224) time: 2.9734 data: 0.0063 max mem: 33300 +Epoch: [19] [ 110/4276] eta: 3:27:17 lr: 2.7965971870729206e-05 loss: 0.1294 (0.1230) time: 2.9548 data: 0.0068 max mem: 33300 +Epoch: [19] [ 120/4276] eta: 3:26:39 lr: 2.796316543542672e-05 loss: 0.1210 (0.1233) time: 2.9486 data: 0.0067 max mem: 33300 +Epoch: [19] [ 130/4276] eta: 3:26:03 lr: 2.796035896882843e-05 loss: 0.1228 (0.1242) time: 2.9627 data: 0.0067 max mem: 33300 +Epoch: [19] [ 140/4276] eta: 3:25:26 lr: 2.7957552470930498e-05 loss: 0.1158 (0.1234) time: 2.9614 data: 0.0072 max mem: 33300 +Epoch: [19] [ 150/4276] eta: 3:24:56 lr: 2.7954745941729095e-05 loss: 0.1074 (0.1234) time: 2.9699 data: 0.0074 max mem: 33300 +Epoch: [19] [ 160/4276] eta: 3:24:16 lr: 2.7951939381220354e-05 loss: 0.1158 (0.1231) time: 2.9589 data: 0.0076 max mem: 33300 +Epoch: [19] [ 170/4276] eta: 3:23:40 lr: 2.7949132789400457e-05 loss: 0.1135 (0.1229) time: 2.9448 data: 0.0076 max mem: 33300 +Epoch: [19] [ 180/4276] eta: 3:23:07 lr: 2.7946326166265552e-05 loss: 0.1223 (0.1232) time: 2.9577 data: 0.0078 max mem: 33300 +Epoch: [19] [ 190/4276] eta: 3:22:33 lr: 2.79435195118118e-05 loss: 0.1325 (0.1238) time: 2.9605 data: 0.0071 max mem: 33300 +Epoch: [19] [ 200/4276] eta: 3:22:01 lr: 2.7940712826035354e-05 loss: 0.1207 (0.1239) time: 2.9584 data: 0.0067 max mem: 33300 +Epoch: [19] [ 210/4276] eta: 3:21:29 lr: 2.793790610893236e-05 loss: 0.1224 (0.1244) time: 2.9623 data: 0.0068 max mem: 33300 +Epoch: [19] [ 220/4276] eta: 3:21:04 lr: 2.7935099360498984e-05 loss: 0.1222 (0.1240) time: 2.9812 data: 0.0067 max mem: 33300 +Epoch: [19] [ 230/4276] eta: 3:20:32 lr: 2.7932292580731367e-05 loss: 0.1087 (0.1236) time: 2.9791 data: 0.0067 max mem: 33300 +Epoch: [19] [ 240/4276] eta: 3:20:00 lr: 2.792948576962567e-05 loss: 0.1122 (0.1235) time: 2.9622 data: 0.0064 max mem: 33300 +Epoch: [19] [ 250/4276] eta: 3:19:28 lr: 2.792667892717804e-05 loss: 0.1256 (0.1241) time: 2.9617 data: 0.0068 max mem: 33300 +Epoch: [19] [ 260/4276] eta: 3:18:56 lr: 2.7923872053384626e-05 loss: 0.1336 (0.1242) time: 2.9592 data: 0.0069 max mem: 33300 +Epoch: [19] [ 270/4276] eta: 3:18:25 lr: 2.7921065148241578e-05 loss: 0.1207 (0.1239) time: 2.9594 data: 0.0069 max mem: 33300 +Epoch: [19] [ 280/4276] eta: 3:17:58 lr: 2.7918258211745052e-05 loss: 0.1128 (0.1237) time: 2.9759 data: 0.0070 max mem: 33300 +Epoch: [19] [ 290/4276] eta: 3:17:26 lr: 2.7915451243891177e-05 loss: 0.1128 (0.1234) time: 2.9745 data: 0.0067 max mem: 33300 +Epoch: [19] [ 300/4276] eta: 3:16:55 lr: 2.7912644244676117e-05 loss: 0.1115 (0.1231) time: 2.9600 data: 0.0067 max mem: 33300 +Epoch: [19] [ 310/4276] eta: 3:16:24 lr: 2.7909837214096003e-05 loss: 0.1112 (0.1228) time: 2.9616 data: 0.0072 max mem: 33300 +Epoch: [19] [ 320/4276] eta: 3:15:52 lr: 2.790703015214699e-05 loss: 0.1152 (0.1231) time: 2.9580 data: 0.0074 max mem: 33300 +Epoch: [19] [ 330/4276] eta: 3:15:20 lr: 2.7904223058825214e-05 loss: 0.1236 (0.1234) time: 2.9528 data: 0.0072 max mem: 33300 +Epoch: [19] [ 340/4276] eta: 3:14:50 lr: 2.7901415934126824e-05 loss: 0.1235 (0.1233) time: 2.9577 data: 0.0070 max mem: 33300 +Epoch: [19] [ 350/4276] eta: 3:14:20 lr: 2.7898608778047958e-05 loss: 0.1141 (0.1233) time: 2.9654 data: 0.0069 max mem: 33300 +Epoch: [19] [ 360/4276] eta: 3:13:42 lr: 2.7895801590584765e-05 loss: 0.1256 (0.1239) time: 2.9310 data: 0.0070 max mem: 33300 +Epoch: [19] [ 370/4276] eta: 3:13:04 lr: 2.7892994371733368e-05 loss: 0.1127 (0.1235) time: 2.8942 data: 0.0069 max mem: 33300 +Epoch: [19] [ 380/4276] eta: 3:12:29 lr: 2.789018712148992e-05 loss: 0.1071 (0.1234) time: 2.8991 data: 0.0072 max mem: 33300 +Epoch: [19] [ 390/4276] eta: 3:11:54 lr: 2.788737983985055e-05 loss: 0.1101 (0.1237) time: 2.9082 data: 0.0072 max mem: 33300 +Epoch: [19] [ 400/4276] eta: 3:11:25 lr: 2.7884572526811404e-05 loss: 0.1395 (0.1241) time: 2.9407 data: 0.0067 max mem: 33300 +Epoch: [19] [ 410/4276] eta: 3:10:55 lr: 2.7881765182368615e-05 loss: 0.1333 (0.1241) time: 2.9685 data: 0.0066 max mem: 33300 +Epoch: [19] [ 420/4276] eta: 3:10:28 lr: 2.7878957806518312e-05 loss: 0.1154 (0.1241) time: 2.9761 data: 0.0063 max mem: 33300 +Epoch: [19] [ 430/4276] eta: 3:09:53 lr: 2.787615039925664e-05 loss: 0.1157 (0.1242) time: 2.9452 data: 0.0063 max mem: 33300 +Epoch: [19] [ 440/4276] eta: 3:09:23 lr: 2.7873342960579728e-05 loss: 0.1129 (0.1239) time: 2.9291 data: 0.0066 max mem: 33300 +Epoch: [19] [ 450/4276] eta: 3:08:53 lr: 2.7870535490483707e-05 loss: 0.1173 (0.1240) time: 2.9560 data: 0.0071 max mem: 33300 +Epoch: [19] [ 460/4276] eta: 3:08:22 lr: 2.7867727988964713e-05 loss: 0.1136 (0.1235) time: 2.9570 data: 0.0077 max mem: 33300 +Epoch: [19] [ 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33300 +Epoch: [19] [ 550/4276] eta: 3:03:57 lr: 2.784245906062108e-05 loss: 0.1086 (0.1212) time: 2.9685 data: 0.0069 max mem: 33300 +Epoch: [19] [ 560/4276] eta: 3:03:28 lr: 2.7839651244659365e-05 loss: 0.1149 (0.1213) time: 2.9579 data: 0.0072 max mem: 33300 +Epoch: [19] [ 570/4276] eta: 3:02:58 lr: 2.7836843397232054e-05 loss: 0.1229 (0.1212) time: 2.9620 data: 0.0078 max mem: 33300 +Epoch: [19] [ 580/4276] eta: 3:02:28 lr: 2.7834035518335284e-05 loss: 0.1097 (0.1211) time: 2.9583 data: 0.0074 max mem: 33300 +Epoch: [19] [ 590/4276] eta: 3:01:58 lr: 2.783122760796517e-05 loss: 0.1054 (0.1209) time: 2.9587 data: 0.0069 max mem: 33300 +Epoch: [19] [ 600/4276] eta: 3:01:29 lr: 2.782841966611782e-05 loss: 0.1137 (0.1209) time: 2.9625 data: 0.0065 max mem: 33300 +Epoch: [19] [ 610/4276] eta: 3:01:02 lr: 2.7825611692789373e-05 loss: 0.1140 (0.1207) time: 2.9832 data: 0.0064 max mem: 33300 +Epoch: [19] [ 620/4276] eta: 3:00:31 lr: 2.7822803687975924e-05 loss: 0.1100 (0.1206) time: 2.9713 data: 0.0066 max mem: 33300 +Epoch: [19] [ 630/4276] eta: 3:00:01 lr: 2.7819995651673598e-05 loss: 0.1120 (0.1211) time: 2.9477 data: 0.0067 max mem: 33300 +Epoch: [19] [ 640/4276] eta: 2:59:31 lr: 2.7817187583878513e-05 loss: 0.1145 (0.1212) time: 2.9571 data: 0.0073 max mem: 33300 +Epoch: [19] [ 650/4276] eta: 2:58:59 lr: 2.781437948458678e-05 loss: 0.1145 (0.1216) time: 2.9397 data: 0.0072 max mem: 33300 +Epoch: [19] [ 660/4276] eta: 2:58:26 lr: 2.781157135379451e-05 loss: 0.1345 (0.1219) time: 2.9103 data: 0.0069 max mem: 33300 +Epoch: [19] [ 670/4276] eta: 2:57:55 lr: 2.7808763191497828e-05 loss: 0.1292 (0.1219) time: 2.9229 data: 0.0070 max mem: 33300 +Epoch: [19] [ 680/4276] eta: 2:57:27 lr: 2.780595499769283e-05 loss: 0.1261 (0.1219) time: 2.9616 data: 0.0067 max mem: 33300 +Epoch: [19] [ 690/4276] eta: 2:56:57 lr: 2.7803146772375637e-05 loss: 0.1208 (0.1220) time: 2.9658 data: 0.0069 max mem: 33300 +Epoch: [19] [ 700/4276] eta: 2:56:26 lr: 2.780033851554235e-05 loss: 0.1208 (0.1219) time: 2.9417 data: 0.0071 max mem: 33300 +Epoch: [19] [ 710/4276] eta: 2:55:53 lr: 2.7797530227189088e-05 loss: 0.1092 (0.1219) time: 2.9176 data: 0.0070 max mem: 33300 +Epoch: [19] [ 720/4276] eta: 2:55:21 lr: 2.7794721907311956e-05 loss: 0.1005 (0.1217) time: 2.9064 data: 0.0071 max mem: 33300 +Epoch: [19] [ 730/4276] eta: 2:54:50 lr: 2.7791913555907052e-05 loss: 0.1011 (0.1217) time: 2.9161 data: 0.0068 max mem: 33300 +Epoch: [19] [ 740/4276] eta: 2:54:19 lr: 2.7789105172970492e-05 loss: 0.1064 (0.1216) time: 2.9293 data: 0.0071 max mem: 33300 +Epoch: [19] [ 750/4276] eta: 2:53:50 lr: 2.7786296758498388e-05 loss: 0.1071 (0.1216) time: 2.9467 data: 0.0069 max mem: 33300 +Epoch: [19] [ 760/4276] eta: 2:53:20 lr: 2.7783488312486822e-05 loss: 0.1070 (0.1215) time: 2.9613 data: 0.0064 max mem: 33300 +Epoch: [19] [ 770/4276] eta: 2:52:51 lr: 2.7780679834931922e-05 loss: 0.1057 (0.1215) time: 2.9629 data: 0.0071 max mem: 33300 +Epoch: [19] [ 780/4276] eta: 2:52:21 lr: 2.7777871325829768e-05 loss: 0.1231 (0.1215) time: 2.9622 data: 0.0073 max mem: 33300 +Epoch: [19] [ 790/4276] eta: 2:51:51 lr: 2.7775062785176476e-05 loss: 0.1236 (0.1216) time: 2.9457 data: 0.0075 max mem: 33300 +Epoch: [19] [ 800/4276] eta: 2:51:20 lr: 2.777225421296814e-05 loss: 0.1187 (0.1216) time: 2.9295 data: 0.0075 max mem: 33300 +Epoch: [19] [ 810/4276] eta: 2:50:51 lr: 2.7769445609200866e-05 loss: 0.1220 (0.1218) time: 2.9501 data: 0.0073 max mem: 33300 +Epoch: [19] [ 820/4276] eta: 2:50:19 lr: 2.7766636973870752e-05 loss: 0.1195 (0.1216) time: 2.9403 data: 0.0073 max mem: 33300 +Epoch: [19] [ 830/4276] eta: 2:49:48 lr: 2.7763828306973888e-05 loss: 0.1135 (0.1218) time: 2.9127 data: 0.0076 max mem: 33300 +Epoch: [19] [ 840/4276] eta: 2:49:17 lr: 2.7761019608506385e-05 loss: 0.1203 (0.1219) time: 2.9252 data: 0.0076 max mem: 33300 +Epoch: [19] [ 850/4276] eta: 2:48:47 lr: 2.775821087846432e-05 loss: 0.1189 (0.1218) time: 2.9339 data: 0.0071 max mem: 33300 +Epoch: [19] [ 860/4276] eta: 2:48:16 lr: 2.7755402116843805e-05 loss: 0.1124 (0.1218) time: 2.9231 data: 0.0078 max mem: 33300 +Epoch: [19] [ 870/4276] eta: 2:47:45 lr: 2.7752593323640918e-05 loss: 0.1155 (0.1219) time: 2.9149 data: 0.0075 max mem: 33300 +Epoch: [19] [ 880/4276] eta: 2:47:13 lr: 2.7749784498851766e-05 loss: 0.1200 (0.1220) time: 2.9121 data: 0.0068 max mem: 33300 +Epoch: [19] [ 890/4276] eta: 2:46:41 lr: 2.774697564247244e-05 loss: 0.1264 (0.1221) time: 2.8983 data: 0.0073 max mem: 33300 +Epoch: [19] [ 900/4276] eta: 2:46:10 lr: 2.7744166754499028e-05 loss: 0.1213 (0.1221) time: 2.8991 data: 0.0077 max mem: 33300 +Epoch: [19] [ 910/4276] eta: 2:45:38 lr: 2.7741357834927624e-05 loss: 0.1183 (0.1221) time: 2.9046 data: 0.0078 max mem: 33300 +Epoch: [19] [ 920/4276] eta: 2:45:07 lr: 2.7738548883754313e-05 loss: 0.1164 (0.1223) time: 2.8961 data: 0.0079 max mem: 33300 +Epoch: [19] [ 930/4276] eta: 2:44:35 lr: 2.7735739900975176e-05 loss: 0.1164 (0.1223) time: 2.8940 data: 0.0074 max mem: 33300 +Epoch: [19] [ 940/4276] eta: 2:44:04 lr: 2.773293088658632e-05 loss: 0.1151 (0.1223) time: 2.9069 data: 0.0068 max mem: 33300 +Epoch: [19] [ 950/4276] eta: 2:43:35 lr: 2.7730121840583816e-05 loss: 0.1168 (0.1224) time: 2.9312 data: 0.0068 max mem: 33300 +Epoch: [19] [ 960/4276] eta: 2:43:05 lr: 2.7727312762963752e-05 loss: 0.1295 (0.1226) time: 2.9475 data: 0.0067 max mem: 33300 +Epoch: [19] [ 970/4276] eta: 2:42:35 lr: 2.772450365372222e-05 loss: 0.1231 (0.1226) time: 2.9400 data: 0.0071 max mem: 33300 +Epoch: [19] [ 980/4276] eta: 2:42:04 lr: 2.7721694512855305e-05 loss: 0.1230 (0.1226) time: 2.9241 data: 0.0078 max mem: 33300 +Epoch: [19] [ 990/4276] eta: 2:41:35 lr: 2.7718885340359084e-05 loss: 0.1229 (0.1226) time: 2.9312 data: 0.0080 max mem: 33300 +Epoch: [19] [1000/4276] eta: 2:41:05 lr: 2.7716076136229642e-05 loss: 0.1159 (0.1226) time: 2.9424 data: 0.0077 max mem: 33300 +Epoch: [19] [1010/4276] eta: 2:40:35 lr: 2.7713266900463052e-05 loss: 0.1145 (0.1225) time: 2.9417 data: 0.0077 max mem: 33300 +Epoch: [19] [1020/4276] eta: 2:40:05 lr: 2.771045763305541e-05 loss: 0.1154 (0.1226) time: 2.9409 data: 0.0078 max mem: 33300 +Epoch: [19] [1030/4276] eta: 2:39:36 lr: 2.7707648334002777e-05 loss: 0.1204 (0.1225) time: 2.9421 data: 0.0077 max mem: 33300 +Epoch: [19] [1040/4276] eta: 2:39:06 lr: 2.7704839003301243e-05 loss: 0.1232 (0.1225) time: 2.9467 data: 0.0076 max mem: 33300 +Epoch: [19] [1050/4276] eta: 2:38:37 lr: 2.7702029640946886e-05 loss: 0.1192 (0.1226) time: 2.9590 data: 0.0075 max mem: 33300 +Epoch: [19] [1060/4276] eta: 2:38:06 lr: 2.769922024693578e-05 loss: 0.1192 (0.1227) time: 2.9294 data: 0.0075 max mem: 33300 +Epoch: [19] [1070/4276] eta: 2:37:34 lr: 2.7696410821264008e-05 loss: 0.1344 (0.1228) time: 2.8840 data: 0.0081 max mem: 33300 +Epoch: [19] [1080/4276] eta: 2:37:04 lr: 2.7693601363927622e-05 loss: 0.1279 (0.1229) time: 2.9102 data: 0.0087 max mem: 33300 +Epoch: [19] [1090/4276] eta: 2:36:35 lr: 2.769079187492272e-05 loss: 0.1279 (0.1230) time: 2.9437 data: 0.0087 max mem: 33300 +Epoch: [19] [1100/4276] eta: 2:36:05 lr: 2.768798235424536e-05 loss: 0.1320 (0.1231) time: 2.9466 data: 0.0083 max mem: 33300 +Epoch: [19] [1110/4276] eta: 2:35:36 lr: 2.7685172801891628e-05 loss: 0.1281 (0.1232) time: 2.9449 data: 0.0079 max mem: 33300 +Epoch: [19] [1120/4276] eta: 2:35:06 lr: 2.7682363217857582e-05 loss: 0.1252 (0.1232) time: 2.9428 data: 0.0084 max mem: 33300 +Epoch: [19] [1130/4276] eta: 2:34:36 lr: 2.7679553602139303e-05 loss: 0.1197 (0.1232) time: 2.9404 data: 0.0085 max mem: 33300 +Epoch: [19] [1140/4276] eta: 2:34:06 lr: 2.7676743954732847e-05 loss: 0.1273 (0.1232) time: 2.9402 data: 0.0083 max mem: 33300 +Epoch: [19] [1150/4276] eta: 2:33:37 lr: 2.76739342756343e-05 loss: 0.1276 (0.1232) time: 2.9420 data: 0.0082 max mem: 33300 +Epoch: [19] [1160/4276] eta: 2:33:07 lr: 2.7671124564839705e-05 loss: 0.1164 (0.1233) time: 2.9414 data: 0.0080 max mem: 33300 +Epoch: [19] [1170/4276] eta: 2:32:37 lr: 2.7668314822345148e-05 loss: 0.1165 (0.1232) time: 2.9412 data: 0.0082 max mem: 33300 +Epoch: [19] [1180/4276] eta: 2:32:08 lr: 2.766550504814669e-05 loss: 0.1181 (0.1232) time: 2.9422 data: 0.0082 max mem: 33300 +Epoch: [19] [1190/4276] eta: 2:31:38 lr: 2.7662695242240393e-05 loss: 0.1058 (0.1231) time: 2.9438 data: 0.0080 max mem: 33300 +Epoch: [19] [1200/4276] eta: 2:31:09 lr: 2.765988540462232e-05 loss: 0.1118 (0.1231) time: 2.9464 data: 0.0080 max mem: 33300 +Epoch: [19] [1210/4276] eta: 2:30:39 lr: 2.765707553528854e-05 loss: 0.1134 (0.1230) time: 2.9468 data: 0.0084 max mem: 33300 +Epoch: [19] [1220/4276] eta: 2:30:09 lr: 2.7654265634235104e-05 loss: 0.1134 (0.1230) time: 2.9309 data: 0.0083 max mem: 33300 +Epoch: [19] [1230/4276] eta: 2:29:38 lr: 2.765145570145809e-05 loss: 0.1134 (0.1231) time: 2.9082 data: 0.0085 max mem: 33300 +Epoch: [19] [1240/4276] eta: 2:29:09 lr: 2.764864573695354e-05 loss: 0.1207 (0.1231) time: 2.9298 data: 0.0090 max mem: 33300 +Epoch: [19] [1250/4276] eta: 2:28:39 lr: 2.7645835740717513e-05 loss: 0.1299 (0.1232) time: 2.9391 data: 0.0086 max mem: 33300 +Epoch: [19] [1260/4276] eta: 2:28:08 lr: 2.764302571274608e-05 loss: 0.1070 (0.1230) time: 2.9109 data: 0.0084 max mem: 33300 +Epoch: [19] [1270/4276] eta: 2:27:38 lr: 2.7640215653035285e-05 loss: 0.1045 (0.1230) time: 2.9039 data: 0.0085 max mem: 33300 +Epoch: [19] [1280/4276] eta: 2:27:07 lr: 2.763740556158119e-05 loss: 0.1213 (0.1230) time: 2.9045 data: 0.0084 max mem: 33300 +Epoch: [19] [1290/4276] eta: 2:26:37 lr: 2.7634595438379863e-05 loss: 0.1213 (0.1231) time: 2.9039 data: 0.0081 max mem: 33300 +Epoch: [19] [1300/4276] eta: 2:26:07 lr: 2.7631785283427335e-05 loss: 0.1072 (0.1230) time: 2.9074 data: 0.0085 max mem: 33300 +Epoch: [19] [1310/4276] eta: 2:25:37 lr: 2.7628975096719678e-05 loss: 0.0982 (0.1229) time: 2.9134 data: 0.0092 max mem: 33300 +Epoch: [19] [1320/4276] eta: 2:25:06 lr: 2.762616487825293e-05 loss: 0.1133 (0.1230) time: 2.9086 data: 0.0091 max mem: 33300 +Epoch: [19] [1330/4276] eta: 2:24:36 lr: 2.762335462802315e-05 loss: 0.1226 (0.1230) time: 2.9057 data: 0.0090 max mem: 33300 +Epoch: [19] [1340/4276] eta: 2:24:06 lr: 2.7620544346026387e-05 loss: 0.1155 (0.1229) time: 2.9077 data: 0.0087 max mem: 33300 +Epoch: [19] [1350/4276] eta: 2:23:35 lr: 2.7617734032258695e-05 loss: 0.1225 (0.1230) time: 2.9043 data: 0.0085 max mem: 33300 +Epoch: [19] [1360/4276] eta: 2:23:05 lr: 2.7614923686716114e-05 loss: 0.1169 (0.1229) time: 2.9040 data: 0.0090 max mem: 33300 +Epoch: [19] [1370/4276] eta: 2:22:35 lr: 2.76121133093947e-05 loss: 0.1045 (0.1229) time: 2.9060 data: 0.0090 max mem: 33300 +Epoch: [19] [1380/4276] eta: 2:22:04 lr: 2.7609302900290502e-05 loss: 0.1121 (0.1230) time: 2.9042 data: 0.0088 max mem: 33300 +Epoch: [19] [1390/4276] eta: 2:21:34 lr: 2.7606492459399546e-05 loss: 0.1244 (0.1229) time: 2.9082 data: 0.0087 max mem: 33300 +Epoch: [19] [1400/4276] eta: 2:21:04 lr: 2.7603681986717895e-05 loss: 0.1231 (0.1230) time: 2.9175 data: 0.0083 max mem: 33300 +Epoch: [19] [1410/4276] eta: 2:20:34 lr: 2.7600871482241586e-05 loss: 0.1060 (0.1229) time: 2.9155 data: 0.0083 max mem: 33300 +Epoch: [19] [1420/4276] eta: 2:20:04 lr: 2.759806094596667e-05 loss: 0.1112 (0.1229) time: 2.9107 data: 0.0087 max mem: 33300 +Epoch: [19] [1430/4276] eta: 2:19:34 lr: 2.7595250377889177e-05 loss: 0.1146 (0.1228) time: 2.9077 data: 0.0087 max mem: 33300 +Epoch: [19] [1440/4276] eta: 2:19:04 lr: 2.7592439778005163e-05 loss: 0.1173 (0.1228) time: 2.9079 data: 0.0089 max mem: 33300 +Epoch: [19] [1450/4276] eta: 2:18:34 lr: 2.7589629146310654e-05 loss: 0.1146 (0.1228) time: 2.9144 data: 0.0089 max mem: 33300 +Epoch: [19] [1460/4276] eta: 2:18:04 lr: 2.7586818482801703e-05 loss: 0.1063 (0.1228) time: 2.9133 data: 0.0090 max mem: 33300 +Epoch: [19] [1470/4276] eta: 2:17:34 lr: 2.7584007787474325e-05 loss: 0.1137 (0.1228) time: 2.9160 data: 0.0090 max mem: 33300 +Epoch: [19] [1480/4276] eta: 2:17:05 lr: 2.7581197060324583e-05 loss: 0.1228 (0.1228) time: 2.9411 data: 0.0086 max mem: 33300 +Epoch: [19] [1490/4276] eta: 2:16:36 lr: 2.7578386301348497e-05 loss: 0.1104 (0.1228) time: 2.9575 data: 0.0082 max mem: 33300 +Epoch: [19] [1500/4276] eta: 2:16:07 lr: 2.7575575510542108e-05 loss: 0.1160 (0.1227) time: 2.9556 data: 0.0083 max mem: 33300 +Epoch: [19] [1510/4276] eta: 2:15:38 lr: 2.7572764687901453e-05 loss: 0.1064 (0.1226) time: 2.9536 data: 0.0082 max mem: 33300 +Epoch: [19] [1520/4276] eta: 2:15:08 lr: 2.7569953833422568e-05 loss: 0.0994 (0.1225) time: 2.9500 data: 0.0080 max mem: 33300 +Epoch: [19] [1530/4276] eta: 2:14:39 lr: 2.7567142947101478e-05 loss: 0.1000 (0.1224) time: 2.9505 data: 0.0078 max mem: 33300 +Epoch: [19] [1540/4276] eta: 2:14:10 lr: 2.7564332028934216e-05 loss: 0.1100 (0.1224) time: 2.9533 data: 0.0078 max mem: 33300 +Epoch: [19] [1550/4276] eta: 2:13:41 lr: 2.7561521078916814e-05 loss: 0.1102 (0.1224) time: 2.9536 data: 0.0080 max mem: 33300 +Epoch: [19] [1560/4276] eta: 2:13:11 lr: 2.7558710097045298e-05 loss: 0.1181 (0.1224) time: 2.9464 data: 0.0084 max mem: 33300 +Epoch: [19] [1570/4276] eta: 2:12:41 lr: 2.75558990833157e-05 loss: 0.1181 (0.1224) time: 2.9360 data: 0.0083 max mem: 33300 +Epoch: [19] [1580/4276] eta: 2:12:12 lr: 2.7553088037724055e-05 loss: 0.1067 (0.1223) time: 2.9422 data: 0.0082 max mem: 33300 +Epoch: [19] [1590/4276] eta: 2:11:43 lr: 2.755027696026638e-05 loss: 0.1064 (0.1223) time: 2.9515 data: 0.0079 max mem: 33300 +Epoch: [19] [1600/4276] eta: 2:11:14 lr: 2.754746585093871e-05 loss: 0.1188 (0.1223) time: 2.9528 data: 0.0083 max mem: 33300 +Epoch: [19] [1610/4276] eta: 2:10:44 lr: 2.7544654709737057e-05 loss: 0.1065 (0.1223) time: 2.9497 data: 0.0091 max mem: 33300 +Epoch: [19] [1620/4276] eta: 2:10:15 lr: 2.754184353665746e-05 loss: 0.1084 (0.1222) time: 2.9462 data: 0.0087 max mem: 33300 +Epoch: [19] [1630/4276] eta: 2:09:46 lr: 2.753903233169593e-05 loss: 0.1189 (0.1222) time: 2.9449 data: 0.0087 max mem: 33300 +Epoch: [19] [1640/4276] eta: 2:09:16 lr: 2.7536221094848493e-05 loss: 0.1082 (0.1220) time: 2.9535 data: 0.0088 max mem: 33300 +Epoch: [19] [1650/4276] eta: 2:08:47 lr: 2.7533409826111167e-05 loss: 0.1077 (0.1220) time: 2.9530 data: 0.0086 max mem: 33300 +Epoch: [19] [1660/4276] eta: 2:08:18 lr: 2.7530598525479984e-05 loss: 0.1127 (0.1220) time: 2.9431 data: 0.0089 max mem: 33300 +Epoch: [19] [1670/4276] eta: 2:07:48 lr: 2.752778719295095e-05 loss: 0.0990 (0.1219) time: 2.9428 data: 0.0086 max mem: 33300 +Epoch: [19] [1680/4276] eta: 2:07:19 lr: 2.75249758285201e-05 loss: 0.1033 (0.1219) time: 2.9438 data: 0.0086 max mem: 33300 +Epoch: [19] [1690/4276] eta: 2:06:49 lr: 2.7522164432183434e-05 loss: 0.1140 (0.1219) time: 2.9442 data: 0.0084 max mem: 33300 +Epoch: [19] [1700/4276] eta: 2:06:20 lr: 2.7519353003936976e-05 loss: 0.1062 (0.1218) time: 2.9429 data: 0.0082 max mem: 33300 +Epoch: [19] [1710/4276] eta: 2:05:51 lr: 2.7516541543776736e-05 loss: 0.1189 (0.1218) time: 2.9448 data: 0.0086 max mem: 33300 +Epoch: [19] [1720/4276] eta: 2:05:21 lr: 2.7513730051698733e-05 loss: 0.1189 (0.1218) time: 2.9451 data: 0.0090 max mem: 33300 +Epoch: [19] [1730/4276] eta: 2:04:52 lr: 2.7510918527698985e-05 loss: 0.1124 (0.1217) time: 2.9443 data: 0.0088 max mem: 33300 +Epoch: [19] [1740/4276] eta: 2:04:22 lr: 2.7508106971773502e-05 loss: 0.1095 (0.1217) time: 2.9461 data: 0.0081 max mem: 33300 +Epoch: [19] [1750/4276] eta: 2:03:53 lr: 2.7505295383918295e-05 loss: 0.1095 (0.1217) time: 2.9485 data: 0.0079 max mem: 33300 +Epoch: [19] [1760/4276] eta: 2:03:24 lr: 2.750248376412937e-05 loss: 0.0913 (0.1216) time: 2.9484 data: 0.0082 max mem: 33300 +Epoch: [19] [1770/4276] eta: 2:02:54 lr: 2.7499672112402746e-05 loss: 0.1145 (0.1216) time: 2.9470 data: 0.0085 max mem: 33300 +Epoch: [19] [1780/4276] eta: 2:02:25 lr: 2.7496860428734422e-05 loss: 0.1177 (0.1215) time: 2.9445 data: 0.0082 max mem: 33300 +Epoch: [19] [1790/4276] eta: 2:01:56 lr: 2.7494048713120412e-05 loss: 0.1122 (0.1215) time: 2.9448 data: 0.0081 max mem: 33300 +Epoch: [19] [1800/4276] eta: 2:01:26 lr: 2.7491236965556723e-05 loss: 0.1094 (0.1214) time: 2.9481 data: 0.0081 max mem: 33300 +Epoch: [19] [1810/4276] eta: 2:00:57 lr: 2.7488425186039356e-05 loss: 0.1177 (0.1215) time: 2.9433 data: 0.0080 max mem: 33300 +Epoch: [19] [1820/4276] eta: 2:00:27 lr: 2.7485613374564324e-05 loss: 0.1264 (0.1215) time: 2.9473 data: 0.0080 max mem: 33300 +Epoch: [19] [1830/4276] eta: 1:59:58 lr: 2.7482801531127632e-05 loss: 0.1154 (0.1215) time: 2.9503 data: 0.0083 max mem: 33300 +Epoch: [19] [1840/4276] eta: 1:59:28 lr: 2.7479989655725275e-05 loss: 0.1128 (0.1215) time: 2.9353 data: 0.0083 max mem: 33300 +Epoch: [19] [1850/4276] eta: 1:58:59 lr: 2.7477177748353262e-05 loss: 0.1139 (0.1215) time: 2.9183 data: 0.0085 max mem: 33300 +Epoch: [19] [1860/4276] eta: 1:58:29 lr: 2.7474365809007578e-05 loss: 0.1174 (0.1215) time: 2.9079 data: 0.0087 max mem: 33300 +Epoch: [19] [1870/4276] eta: 1:57:59 lr: 2.7471553837684242e-05 loss: 0.1283 (0.1216) time: 2.9022 data: 0.0088 max mem: 33300 +Epoch: [19] [1880/4276] eta: 1:57:29 lr: 2.7468741834379253e-05 loss: 0.1226 (0.1216) time: 2.9029 data: 0.0086 max mem: 33300 +Epoch: [19] [1890/4276] eta: 1:56:59 lr: 2.7465929799088596e-05 loss: 0.1160 (0.1216) time: 2.9057 data: 0.0086 max mem: 33300 +Epoch: [19] [1900/4276] eta: 1:56:29 lr: 2.746311773180828e-05 loss: 0.1160 (0.1216) time: 2.9056 data: 0.0085 max mem: 33300 +Epoch: [19] [1910/4276] eta: 1:55:59 lr: 2.7460305632534307e-05 loss: 0.1074 (0.1216) time: 2.9074 data: 0.0086 max mem: 33300 +Epoch: [19] [1920/4276] eta: 1:55:29 lr: 2.7457493501262653e-05 loss: 0.1074 (0.1216) time: 2.9068 data: 0.0082 max mem: 33300 +Epoch: [19] [1930/4276] eta: 1:54:59 lr: 2.745468133798933e-05 loss: 0.1143 (0.1216) time: 2.9007 data: 0.0079 max mem: 33300 +Epoch: [19] [1940/4276] eta: 1:54:30 lr: 2.745186914271032e-05 loss: 0.1170 (0.1215) time: 2.9031 data: 0.0080 max mem: 33300 +Epoch: [19] [1950/4276] eta: 1:54:00 lr: 2.7449056915421616e-05 loss: 0.1195 (0.1216) time: 2.9213 data: 0.0083 max mem: 33300 +Epoch: [19] [1960/4276] eta: 1:53:31 lr: 2.7446244656119217e-05 loss: 0.1215 (0.1215) time: 2.9304 data: 0.0084 max mem: 33300 +Epoch: [19] [1970/4276] eta: 1:53:01 lr: 2.744343236479911e-05 loss: 0.0973 (0.1214) time: 2.9161 data: 0.0085 max mem: 33300 +Epoch: [19] [1980/4276] eta: 1:52:31 lr: 2.7440620041457286e-05 loss: 0.0939 (0.1214) time: 2.9163 data: 0.0087 max mem: 33300 +Epoch: [19] [1990/4276] eta: 1:52:02 lr: 2.743780768608974e-05 loss: 0.1062 (0.1214) time: 2.9432 data: 0.0083 max mem: 33300 +Epoch: [19] [2000/4276] eta: 1:51:32 lr: 2.743499529869245e-05 loss: 0.1114 (0.1214) time: 2.9368 data: 0.0083 max mem: 33300 +Epoch: [19] [2010/4276] eta: 1:51:03 lr: 2.7432182879261404e-05 loss: 0.1228 (0.1214) time: 2.9157 data: 0.0090 max mem: 33300 +Epoch: [19] [2020/4276] eta: 1:50:33 lr: 2.7429370427792587e-05 loss: 0.1264 (0.1214) time: 2.9059 data: 0.0093 max mem: 33300 +Epoch: [19] [2030/4276] eta: 1:50:03 lr: 2.7426557944281987e-05 loss: 0.1064 (0.1213) time: 2.9041 data: 0.0094 max mem: 33300 +Epoch: [19] [2040/4276] eta: 1:49:33 lr: 2.7423745428725594e-05 loss: 0.1064 (0.1212) time: 2.9138 data: 0.0093 max mem: 33300 +Epoch: [19] [2050/4276] eta: 1:49:03 lr: 2.7420932881119384e-05 loss: 0.1129 (0.1212) time: 2.9114 data: 0.0087 max mem: 33300 +Epoch: [19] [2060/4276] eta: 1:48:35 lr: 2.7418120301459337e-05 loss: 0.1153 (0.1212) time: 2.9856 data: 0.0089 max mem: 33300 +Epoch: [19] [2070/4276] eta: 1:48:08 lr: 2.7415307689741437e-05 loss: 0.1114 (0.1212) time: 3.0779 data: 0.0087 max mem: 33300 +Epoch: [19] [2080/4276] eta: 1:47:39 lr: 2.7412495045961673e-05 loss: 0.1139 (0.1212) time: 3.0753 data: 0.0078 max mem: 33300 +Epoch: [19] [2090/4276] eta: 1:47:11 lr: 2.7409682370116007e-05 loss: 0.1212 (0.1212) time: 3.0487 data: 0.0083 max mem: 33300 +Epoch: [19] [2100/4276] eta: 1:46:43 lr: 2.740686966220043e-05 loss: 0.1155 (0.1212) time: 3.0372 data: 0.0091 max mem: 33300 +Epoch: [19] [2110/4276] eta: 1:46:14 lr: 2.7404056922210913e-05 loss: 0.1099 (0.1211) time: 3.0493 data: 0.0086 max mem: 33300 +Epoch: [19] [2120/4276] eta: 1:45:47 lr: 2.7401244150143435e-05 loss: 0.0962 (0.1210) time: 3.0789 data: 0.0080 max mem: 33300 +Epoch: [19] [2130/4276] eta: 1:45:18 lr: 2.739843134599397e-05 loss: 0.1054 (0.1209) time: 3.0657 data: 0.0083 max mem: 33300 +Epoch: [19] [2140/4276] eta: 1:44:50 lr: 2.7395618509758497e-05 loss: 0.1071 (0.1209) time: 3.0389 data: 0.0081 max mem: 33300 +Epoch: [19] [2150/4276] eta: 1:44:21 lr: 2.7392805641432982e-05 loss: 0.1058 (0.1208) time: 3.0389 data: 0.0080 max mem: 33300 +Epoch: [19] [2160/4276] eta: 1:43:53 lr: 2.738999274101341e-05 loss: 0.1002 (0.1208) time: 3.0539 data: 0.0079 max mem: 33300 +Epoch: [19] [2170/4276] eta: 1:43:25 lr: 2.738717980849574e-05 loss: 0.1161 (0.1207) time: 3.0808 data: 0.0075 max mem: 33300 +Epoch: [19] [2180/4276] eta: 1:42:56 lr: 2.7384366843875942e-05 loss: 0.1212 (0.1207) time: 3.0674 data: 0.0075 max mem: 33300 +Epoch: [19] [2190/4276] eta: 1:42:28 lr: 2.7381553847149987e-05 loss: 0.1205 (0.1207) time: 3.0386 data: 0.0078 max mem: 33300 +Epoch: [19] [2200/4276] eta: 1:41:59 lr: 2.7378740818313853e-05 loss: 0.1109 (0.1208) time: 3.0284 data: 0.0080 max mem: 33300 +Epoch: [19] [2210/4276] eta: 1:41:30 lr: 2.7375927757363502e-05 loss: 0.1150 (0.1208) time: 3.0360 data: 0.0075 max mem: 33300 +Epoch: [19] [2220/4276] eta: 1:41:02 lr: 2.7373114664294895e-05 loss: 0.1248 (0.1209) time: 3.0443 data: 0.0078 max mem: 33300 +Epoch: [19] [2230/4276] eta: 1:40:33 lr: 2.737030153910401e-05 loss: 0.1078 (0.1208) time: 3.0323 data: 0.0074 max mem: 33300 +Epoch: [19] [2240/4276] eta: 1:40:04 lr: 2.7367488381786805e-05 loss: 0.1063 (0.1208) time: 3.0232 data: 0.0070 max mem: 33300 +Epoch: [19] [2250/4276] eta: 1:39:35 lr: 2.7364675192339235e-05 loss: 0.1029 (0.1207) time: 3.0266 data: 0.0073 max mem: 33300 +Epoch: [19] [2260/4276] eta: 1:39:07 lr: 2.7361861970757274e-05 loss: 0.1082 (0.1207) time: 3.0300 data: 0.0074 max mem: 33300 +Epoch: [19] [2270/4276] eta: 1:38:38 lr: 2.7359048717036878e-05 loss: 0.1159 (0.1207) time: 3.0281 data: 0.0073 max mem: 33300 +Epoch: [19] [2280/4276] eta: 1:38:09 lr: 2.7356235431174014e-05 loss: 0.1045 (0.1207) time: 3.0266 data: 0.0073 max mem: 33300 +Epoch: [19] [2290/4276] eta: 1:37:40 lr: 2.7353422113164643e-05 loss: 0.1104 (0.1206) time: 3.0295 data: 0.0073 max mem: 33300 +Epoch: [19] [2300/4276] eta: 1:37:11 lr: 2.7350608763004715e-05 loss: 0.1117 (0.1206) time: 3.0304 data: 0.0074 max mem: 33300 +Epoch: [19] [2310/4276] eta: 1:36:43 lr: 2.7347795380690195e-05 loss: 0.1222 (0.1208) time: 3.0452 data: 0.0074 max mem: 33300 +Epoch: [19] [2320/4276] eta: 1:36:14 lr: 2.7344981966217037e-05 loss: 0.1266 (0.1208) time: 3.0625 data: 0.0074 max mem: 33300 +Epoch: [19] [2330/4276] eta: 1:35:45 lr: 2.734216851958119e-05 loss: 0.1301 (0.1208) time: 3.0581 data: 0.0076 max mem: 33300 +Epoch: [19] [2340/4276] eta: 1:35:16 lr: 2.7339355040778624e-05 loss: 0.1301 (0.1208) time: 3.0411 data: 0.0074 max mem: 33300 +Epoch: [19] [2350/4276] eta: 1:34:48 lr: 2.7336541529805282e-05 loss: 0.1250 (0.1209) time: 3.0413 data: 0.0068 max mem: 33300 +Epoch: [19] [2360/4276] eta: 1:34:19 lr: 2.733372798665712e-05 loss: 0.1164 (0.1208) time: 3.0415 data: 0.0066 max mem: 33300 +Epoch: [19] [2370/4276] eta: 1:33:50 lr: 2.73309144113301e-05 loss: 0.1166 (0.1209) time: 3.0317 data: 0.0065 max mem: 33300 +Epoch: [19] [2380/4276] eta: 1:33:21 lr: 2.7328100803820156e-05 loss: 0.1238 (0.1209) time: 3.0329 data: 0.0063 max mem: 33300 +Epoch: [19] [2390/4276] eta: 1:32:52 lr: 2.7325287164123254e-05 loss: 0.1206 (0.1209) time: 3.0367 data: 0.0065 max mem: 33300 +Epoch: [19] [2400/4276] eta: 1:32:23 lr: 2.732247349223533e-05 loss: 0.1147 (0.1209) time: 3.0442 data: 0.0066 max mem: 33300 +Epoch: [19] [2410/4276] eta: 1:31:55 lr: 2.731965978815233e-05 loss: 0.1147 (0.1209) time: 3.0688 data: 0.0069 max mem: 33300 +Epoch: [19] [2420/4276] eta: 1:31:26 lr: 2.7316846051870216e-05 loss: 0.1059 (0.1208) time: 3.0897 data: 0.0073 max mem: 33300 +Epoch: [19] [2430/4276] eta: 1:30:58 lr: 2.7314032283384926e-05 loss: 0.1241 (0.1209) time: 3.0876 data: 0.0077 max mem: 33300 +Epoch: [19] [2440/4276] eta: 1:30:29 lr: 2.7311218482692407e-05 loss: 0.1272 (0.1209) time: 3.0727 data: 0.0080 max mem: 33300 +Epoch: [19] [2450/4276] eta: 1:30:00 lr: 2.7308404649788612e-05 loss: 0.1272 (0.1209) time: 3.0735 data: 0.0075 max mem: 33300 +Epoch: [19] [2460/4276] eta: 1:29:32 lr: 2.7305590784669466e-05 loss: 0.1405 (0.1210) time: 3.0862 data: 0.0071 max mem: 33300 +Epoch: [19] [2470/4276] eta: 1:29:03 lr: 2.7302776887330922e-05 loss: 0.1246 (0.1211) time: 3.0701 data: 0.0071 max mem: 33300 +Epoch: [19] [2480/4276] eta: 1:28:33 lr: 2.729996295776892e-05 loss: 0.1226 (0.1211) time: 3.0209 data: 0.0066 max mem: 33300 +Epoch: [19] [2490/4276] eta: 1:28:04 lr: 2.72971489959794e-05 loss: 0.1169 (0.1211) time: 3.0049 data: 0.0064 max mem: 33300 +Epoch: [19] [2500/4276] eta: 1:27:35 lr: 2.7294335001958306e-05 loss: 0.1153 (0.1211) time: 3.0414 data: 0.0062 max mem: 33300 +Epoch: [19] [2510/4276] eta: 1:27:06 lr: 2.7291520975701568e-05 loss: 0.1242 (0.1211) time: 3.0547 data: 0.0072 max mem: 33300 +Epoch: [19] [2520/4276] eta: 1:26:37 lr: 2.7288706917205126e-05 loss: 0.1093 (0.1211) time: 3.0380 data: 0.0081 max mem: 33300 +Epoch: [19] [2530/4276] eta: 1:26:08 lr: 2.7285892826464924e-05 loss: 0.0955 (0.1210) time: 3.0282 data: 0.0082 max mem: 33300 +Epoch: [19] [2540/4276] eta: 1:25:39 lr: 2.7283078703476888e-05 loss: 0.1031 (0.1210) time: 3.0306 data: 0.0087 max mem: 33300 +Epoch: [19] [2550/4276] eta: 1:25:10 lr: 2.7280264548236968e-05 loss: 0.1067 (0.1210) time: 3.0449 data: 0.0083 max mem: 33300 +Epoch: [19] [2560/4276] eta: 1:24:41 lr: 2.7277450360741074e-05 loss: 0.0969 (0.1209) time: 3.0737 data: 0.0078 max mem: 33300 +Epoch: [19] [2570/4276] eta: 1:24:13 lr: 2.7274636140985154e-05 loss: 0.0990 (0.1209) time: 3.0897 data: 0.0077 max mem: 33300 +Epoch: [19] [2580/4276] eta: 1:23:44 lr: 2.7271821888965137e-05 loss: 0.1087 (0.1208) time: 3.0903 data: 0.0076 max mem: 33300 +Epoch: [19] [2590/4276] eta: 1:23:15 lr: 2.7269007604676948e-05 loss: 0.1104 (0.1208) time: 3.0905 data: 0.0076 max mem: 33300 +Epoch: [19] [2600/4276] eta: 1:22:46 lr: 2.7266193288116533e-05 loss: 0.1079 (0.1208) time: 3.0925 data: 0.0077 max mem: 33300 +Epoch: [19] [2610/4276] eta: 1:22:17 lr: 2.7263378939279806e-05 loss: 0.1038 (0.1207) time: 3.0912 data: 0.0077 max mem: 33300 +Epoch: [19] [2620/4276] eta: 1:21:49 lr: 2.72605645581627e-05 loss: 0.1151 (0.1207) time: 3.0848 data: 0.0076 max mem: 33300 +Epoch: [19] [2630/4276] eta: 1:21:20 lr: 2.7257750144761134e-05 loss: 0.1129 (0.1207) time: 3.0857 data: 0.0074 max mem: 33300 +Epoch: [19] [2640/4276] eta: 1:20:51 lr: 2.7254935699071038e-05 loss: 0.1052 (0.1207) time: 3.0837 data: 0.0074 max mem: 33300 +Epoch: [19] [2650/4276] eta: 1:20:22 lr: 2.7252121221088346e-05 loss: 0.1156 (0.1206) time: 3.0834 data: 0.0074 max mem: 33300 +Epoch: [19] [2660/4276] eta: 1:19:53 lr: 2.7249306710808968e-05 loss: 0.1173 (0.1206) time: 3.0893 data: 0.0071 max mem: 33300 +Epoch: [19] [2670/4276] eta: 1:19:24 lr: 2.7246492168228836e-05 loss: 0.1235 (0.1207) time: 3.0866 data: 0.0071 max mem: 33300 +Epoch: [19] [2680/4276] eta: 1:18:55 lr: 2.7243677593343874e-05 loss: 0.1368 (0.1207) time: 3.0851 data: 0.0071 max mem: 33300 +Epoch: [19] [2690/4276] eta: 1:18:26 lr: 2.7240862986149996e-05 loss: 0.1147 (0.1206) time: 3.0842 data: 0.0071 max mem: 33300 +Epoch: [19] [2700/4276] eta: 1:17:57 lr: 2.7238048346643125e-05 loss: 0.1081 (0.1206) time: 3.0885 data: 0.0073 max mem: 33300 +Epoch: [19] [2710/4276] eta: 1:17:28 lr: 2.7235233674819172e-05 loss: 0.1061 (0.1206) time: 3.0904 data: 0.0071 max mem: 33300 +Epoch: [19] [2720/4276] eta: 1:16:59 lr: 2.723241897067406e-05 loss: 0.0970 (0.1205) time: 3.0878 data: 0.0070 max mem: 33300 +Epoch: [19] [2730/4276] eta: 1:16:30 lr: 2.7229604234203714e-05 loss: 0.1075 (0.1206) time: 3.0866 data: 0.0072 max mem: 33300 +Epoch: [19] [2740/4276] eta: 1:16:01 lr: 2.722678946540404e-05 loss: 0.1217 (0.1206) time: 3.0851 data: 0.0069 max mem: 33300 +Epoch: [19] [2750/4276] eta: 1:15:32 lr: 2.7223974664270957e-05 loss: 0.1192 (0.1206) time: 3.0585 data: 0.0075 max mem: 33300 +Epoch: [19] [2760/4276] eta: 1:15:02 lr: 2.7221159830800385e-05 loss: 0.1170 (0.1205) time: 3.0442 data: 0.0079 max mem: 33300 +Epoch: [19] [2770/4276] eta: 1:14:33 lr: 2.7218344964988225e-05 loss: 0.1099 (0.1205) time: 3.0722 data: 0.0076 max mem: 33300 +Epoch: [19] [2780/4276] eta: 1:14:04 lr: 2.7215530066830397e-05 loss: 0.1114 (0.1205) time: 3.0893 data: 0.0077 max mem: 33300 +Epoch: [19] [2790/4276] eta: 1:13:35 lr: 2.721271513632281e-05 loss: 0.1116 (0.1205) time: 3.0915 data: 0.0072 max mem: 33300 +Epoch: [19] [2800/4276] eta: 1:13:06 lr: 2.7209900173461365e-05 loss: 0.1076 (0.1205) time: 3.0792 data: 0.0071 max mem: 33300 +Epoch: [19] [2810/4276] eta: 1:12:37 lr: 2.7207085178241988e-05 loss: 0.0972 (0.1204) time: 3.0515 data: 0.0073 max mem: 33300 +Epoch: [19] [2820/4276] eta: 1:12:07 lr: 2.7204270150660572e-05 loss: 0.0972 (0.1203) time: 3.0501 data: 0.0077 max mem: 33300 +Epoch: [19] [2830/4276] eta: 1:11:38 lr: 2.7201455090713028e-05 loss: 0.1107 (0.1203) time: 3.0764 data: 0.0075 max mem: 33300 +Epoch: [19] [2840/4276] eta: 1:11:09 lr: 2.7198639998395276e-05 loss: 0.1261 (0.1204) time: 3.0881 data: 0.0072 max mem: 33300 +Epoch: [19] [2850/4276] eta: 1:10:40 lr: 2.7195824873703203e-05 loss: 0.1322 (0.1204) time: 3.0891 data: 0.0076 max mem: 33300 +Epoch: [19] [2860/4276] eta: 1:10:11 lr: 2.7193009716632723e-05 loss: 0.1202 (0.1204) time: 3.0909 data: 0.0073 max mem: 33300 +Epoch: [19] [2870/4276] eta: 1:09:42 lr: 2.719019452717973e-05 loss: 0.1104 (0.1204) time: 3.0921 data: 0.0071 max mem: 33300 +Epoch: [19] [2880/4276] eta: 1:09:13 lr: 2.7187379305340133e-05 loss: 0.1121 (0.1204) time: 3.0908 data: 0.0069 max mem: 33300 +Epoch: [19] [2890/4276] eta: 1:08:44 lr: 2.7184564051109835e-05 loss: 0.1150 (0.1204) time: 3.1178 data: 0.0069 max mem: 33300 +Epoch: [19] [2900/4276] eta: 1:08:14 lr: 2.7181748764484734e-05 loss: 0.1118 (0.1203) time: 3.1268 data: 0.0073 max mem: 33300 +Epoch: [19] [2910/4276] eta: 1:07:45 lr: 2.7178933445460724e-05 loss: 0.1052 (0.1203) time: 3.0709 data: 0.0071 max mem: 33300 +Epoch: [19] [2920/4276] eta: 1:07:15 lr: 2.717611809403371e-05 loss: 0.1220 (0.1203) time: 3.0203 data: 0.0070 max mem: 33300 +Epoch: [19] [2930/4276] eta: 1:06:46 lr: 2.7173302710199587e-05 loss: 0.1088 (0.1202) time: 3.0416 data: 0.0076 max mem: 33300 +Epoch: [19] [2940/4276] eta: 1:06:17 lr: 2.717048729395425e-05 loss: 0.1086 (0.1203) time: 3.0872 data: 0.0079 max mem: 33300 +Epoch: [19] [2950/4276] eta: 1:05:47 lr: 2.7167671845293597e-05 loss: 0.1126 (0.1203) time: 3.0709 data: 0.0078 max mem: 33300 +Epoch: [19] [2960/4276] eta: 1:05:18 lr: 2.7164856364213516e-05 loss: 0.1169 (0.1203) time: 3.0705 data: 0.0078 max mem: 33300 +Epoch: [19] [2970/4276] eta: 1:04:49 lr: 2.71620408507099e-05 loss: 0.1210 (0.1203) time: 3.0932 data: 0.0080 max mem: 33300 +Epoch: [19] [2980/4276] eta: 1:04:19 lr: 2.715922530477865e-05 loss: 0.1147 (0.1203) time: 3.0134 data: 0.0075 max mem: 33300 +Epoch: [19] [2990/4276] eta: 1:03:49 lr: 2.715640972641566e-05 loss: 0.1110 (0.1203) time: 2.9454 data: 0.0072 max mem: 33300 +Epoch: [19] [3000/4276] eta: 1:03:19 lr: 2.7153594115616803e-05 loss: 0.1102 (0.1202) time: 2.9859 data: 0.0083 max mem: 33300 +Epoch: [19] [3010/4276] eta: 1:02:50 lr: 2.7150778472377987e-05 loss: 0.1121 (0.1202) time: 3.0218 data: 0.0087 max mem: 33300 +Epoch: [19] [3020/4276] eta: 1:02:20 lr: 2.714796279669508e-05 loss: 0.1261 (0.1202) time: 3.0434 data: 0.0085 max mem: 33300 +Epoch: [19] [3030/4276] eta: 1:01:51 lr: 2.7145147088563987e-05 loss: 0.1150 (0.1202) time: 3.0171 data: 0.0081 max mem: 33300 +Epoch: [19] [3040/4276] eta: 1:01:21 lr: 2.7142331347980583e-05 loss: 0.1213 (0.1203) time: 2.9634 data: 0.0084 max mem: 33300 +Epoch: [19] [3050/4276] eta: 1:00:51 lr: 2.713951557494076e-05 loss: 0.1213 (0.1202) time: 2.9633 data: 0.0085 max mem: 33300 +Epoch: [19] [3060/4276] eta: 1:00:21 lr: 2.71366997694404e-05 loss: 0.0999 (0.1202) time: 2.9705 data: 0.0074 max mem: 33300 +Epoch: [19] [3070/4276] eta: 0:59:51 lr: 2.713388393147539e-05 loss: 0.1036 (0.1202) time: 2.9909 data: 0.0073 max mem: 33300 +Epoch: [19] [3080/4276] eta: 0:59:22 lr: 2.713106806104161e-05 loss: 0.1060 (0.1201) time: 2.9938 data: 0.0076 max mem: 33300 +Epoch: [19] [3090/4276] eta: 0:58:52 lr: 2.7128252158134937e-05 loss: 0.1046 (0.1201) time: 2.9711 data: 0.0075 max mem: 33300 +Epoch: [19] [3100/4276] eta: 0:58:22 lr: 2.712543622275125e-05 loss: 0.1019 (0.1200) time: 2.9629 data: 0.0072 max mem: 33300 +Epoch: [19] [3110/4276] eta: 0:57:52 lr: 2.7122620254886432e-05 loss: 0.0982 (0.1200) time: 2.9650 data: 0.0072 max mem: 33300 +Epoch: [19] [3120/4276] eta: 0:57:22 lr: 2.7119804254536367e-05 loss: 0.0982 (0.1199) time: 2.9736 data: 0.0072 max mem: 33300 +Epoch: [19] [3130/4276] eta: 0:56:53 lr: 2.711698822169692e-05 loss: 0.1022 (0.1199) time: 2.9720 data: 0.0070 max mem: 33300 +Epoch: [19] [3140/4276] eta: 0:56:23 lr: 2.711417215636398e-05 loss: 0.1112 (0.1199) time: 2.9688 data: 0.0069 max mem: 33300 +Epoch: [19] [3150/4276] eta: 0:55:53 lr: 2.7111356058533415e-05 loss: 0.1131 (0.1199) time: 2.9687 data: 0.0069 max mem: 33300 +Epoch: [19] [3160/4276] eta: 0:55:23 lr: 2.7108539928201106e-05 loss: 0.1229 (0.1200) time: 2.9695 data: 0.0069 max mem: 33300 +Epoch: [19] [3170/4276] eta: 0:54:53 lr: 2.7105723765362918e-05 loss: 0.1255 (0.1200) time: 2.9610 data: 0.0071 max mem: 33300 +Epoch: [19] [3180/4276] eta: 0:54:23 lr: 2.710290757001472e-05 loss: 0.1188 (0.1200) time: 2.9461 data: 0.0071 max mem: 33300 +Epoch: [19] [3190/4276] eta: 0:53:53 lr: 2.710009134215239e-05 loss: 0.1188 (0.1200) time: 2.9414 data: 0.0071 max mem: 33300 +Epoch: [19] [3200/4276] eta: 0:53:24 lr: 2.7097275081771796e-05 loss: 0.1189 (0.1200) time: 2.9645 data: 0.0071 max mem: 33300 +Epoch: [19] [3210/4276] eta: 0:52:54 lr: 2.709445878886881e-05 loss: 0.1164 (0.1200) time: 2.9815 data: 0.0068 max mem: 33300 +Epoch: [19] [3220/4276] eta: 0:52:24 lr: 2.7091642463439303e-05 loss: 0.1164 (0.1200) time: 2.9747 data: 0.0079 max mem: 33300 +Epoch: [19] [3230/4276] eta: 0:51:54 lr: 2.7088826105479138e-05 loss: 0.1178 (0.1200) time: 2.9705 data: 0.0079 max mem: 33300 +Epoch: [19] [3240/4276] eta: 0:51:24 lr: 2.7086009714984183e-05 loss: 0.1200 (0.1200) time: 2.9645 data: 0.0072 max mem: 33300 +Epoch: [19] [3250/4276] eta: 0:50:54 lr: 2.7083193291950298e-05 loss: 0.1241 (0.1200) time: 2.9383 data: 0.0079 max mem: 33300 +Epoch: [19] [3260/4276] eta: 0:50:24 lr: 2.708037683637335e-05 loss: 0.1183 (0.1201) time: 2.9129 data: 0.0078 max mem: 33300 +Epoch: [19] [3270/4276] eta: 0:49:54 lr: 2.7077560348249204e-05 loss: 0.1150 (0.1201) time: 2.9099 data: 0.0074 max mem: 33300 +Epoch: [19] [3280/4276] eta: 0:49:25 lr: 2.7074743827573718e-05 loss: 0.1226 (0.1201) time: 2.9424 data: 0.0076 max mem: 33300 +Epoch: [19] [3290/4276] eta: 0:48:55 lr: 2.7071927274342758e-05 loss: 0.1226 (0.1201) time: 2.9685 data: 0.0077 max mem: 33300 +Epoch: [19] [3300/4276] eta: 0:48:25 lr: 2.706911068855219e-05 loss: 0.1188 (0.1202) time: 2.9610 data: 0.0076 max mem: 33300 +Epoch: [19] [3310/4276] eta: 0:47:55 lr: 2.7066294070197858e-05 loss: 0.1326 (0.1202) time: 2.9601 data: 0.0072 max mem: 33300 +Epoch: [19] [3320/4276] eta: 0:47:25 lr: 2.7063477419275634e-05 loss: 0.1326 (0.1202) time: 2.9622 data: 0.0074 max mem: 33300 +Epoch: [19] [3330/4276] eta: 0:46:56 lr: 2.7060660735781367e-05 loss: 0.1208 (0.1202) time: 2.9708 data: 0.0076 max mem: 33300 +Epoch: [19] [3340/4276] eta: 0:46:26 lr: 2.7057844019710915e-05 loss: 0.1122 (0.1202) time: 2.9746 data: 0.0073 max mem: 33300 +Epoch: [19] [3350/4276] eta: 0:45:56 lr: 2.705502727106013e-05 loss: 0.1119 (0.1202) time: 2.9655 data: 0.0074 max mem: 33300 +Epoch: [19] [3360/4276] eta: 0:45:26 lr: 2.7052210489824868e-05 loss: 0.1071 (0.1201) time: 2.9615 data: 0.0074 max mem: 33300 +Epoch: [19] [3370/4276] eta: 0:44:56 lr: 2.704939367600099e-05 loss: 0.1096 (0.1202) time: 2.9621 data: 0.0073 max mem: 33300 +Epoch: [19] [3380/4276] eta: 0:44:27 lr: 2.7046576829584347e-05 loss: 0.1170 (0.1202) time: 2.9571 data: 0.0071 max mem: 33300 +Epoch: [19] [3390/4276] eta: 0:43:57 lr: 2.704375995057078e-05 loss: 0.1147 (0.1202) time: 2.9609 data: 0.0070 max mem: 33300 +Epoch: [19] [3400/4276] eta: 0:43:27 lr: 2.7040943038956145e-05 loss: 0.1301 (0.1202) time: 2.9769 data: 0.0071 max mem: 33300 +Epoch: [19] [3410/4276] eta: 0:42:57 lr: 2.7038126094736294e-05 loss: 0.1301 (0.1203) time: 2.9789 data: 0.0072 max mem: 33300 +Epoch: [19] [3420/4276] eta: 0:42:28 lr: 2.7035309117907064e-05 loss: 0.1162 (0.1203) time: 2.9678 data: 0.0071 max mem: 33300 +Epoch: [19] [3430/4276] eta: 0:41:58 lr: 2.7032492108464314e-05 loss: 0.1295 (0.1203) time: 2.9705 data: 0.0073 max mem: 33300 +Epoch: [19] [3440/4276] eta: 0:41:28 lr: 2.7029675066403888e-05 loss: 0.1222 (0.1203) time: 2.9677 data: 0.0079 max mem: 33300 +Epoch: [19] [3450/4276] eta: 0:40:58 lr: 2.702685799172162e-05 loss: 0.1022 (0.1203) time: 2.9634 data: 0.0082 max mem: 33300 +Epoch: [19] [3460/4276] eta: 0:40:28 lr: 2.7024040884413375e-05 loss: 0.1321 (0.1203) time: 2.9707 data: 0.0080 max mem: 33300 +Epoch: [19] [3470/4276] eta: 0:39:59 lr: 2.7021223744474978e-05 loss: 0.1202 (0.1203) time: 2.9691 data: 0.0077 max mem: 33300 +Epoch: [19] [3480/4276] eta: 0:39:29 lr: 2.7018406571902282e-05 loss: 0.1249 (0.1203) time: 2.9586 data: 0.0081 max mem: 33300 +Epoch: [19] [3490/4276] eta: 0:38:59 lr: 2.7015589366691123e-05 loss: 0.1287 (0.1203) time: 2.9630 data: 0.0081 max mem: 33300 +Epoch: [19] [3500/4276] eta: 0:38:29 lr: 2.7012772128837337e-05 loss: 0.1179 (0.1203) time: 2.9678 data: 0.0076 max mem: 33300 +Epoch: [19] [3510/4276] eta: 0:37:59 lr: 2.7009954858336766e-05 loss: 0.1070 (0.1203) time: 2.9596 data: 0.0075 max mem: 33300 +Epoch: [19] [3520/4276] eta: 0:37:30 lr: 2.7007137555185254e-05 loss: 0.1049 (0.1203) time: 2.9606 data: 0.0078 max mem: 33300 +Epoch: [19] [3530/4276] eta: 0:37:00 lr: 2.7004320219378636e-05 loss: 0.1295 (0.1203) time: 2.9415 data: 0.0078 max mem: 33300 +Epoch: [19] [3540/4276] eta: 0:36:30 lr: 2.7001502850912742e-05 loss: 0.1295 (0.1203) time: 2.9192 data: 0.0076 max mem: 33300 +Epoch: [19] [3550/4276] eta: 0:36:00 lr: 2.699868544978341e-05 loss: 0.1144 (0.1203) time: 2.9179 data: 0.0077 max mem: 33300 +Epoch: [19] [3560/4276] eta: 0:35:30 lr: 2.6995868015986476e-05 loss: 0.1135 (0.1203) time: 2.9152 data: 0.0077 max mem: 33300 +Epoch: [19] [3570/4276] eta: 0:35:00 lr: 2.699305054951777e-05 loss: 0.1292 (0.1204) time: 2.9159 data: 0.0076 max mem: 33300 +Epoch: [19] [3580/4276] eta: 0:34:30 lr: 2.6990233050373122e-05 loss: 0.1083 (0.1203) time: 2.9245 data: 0.0076 max mem: 33300 +Epoch: [19] [3590/4276] eta: 0:34:01 lr: 2.698741551854837e-05 loss: 0.1067 (0.1203) time: 2.9622 data: 0.0082 max mem: 33300 +Epoch: [19] [3600/4276] eta: 0:33:31 lr: 2.6984597954039335e-05 loss: 0.1212 (0.1204) time: 2.9870 data: 0.0082 max mem: 33300 +Epoch: [19] [3610/4276] eta: 0:33:01 lr: 2.6981780356841864e-05 loss: 0.1212 (0.1204) time: 2.9736 data: 0.0076 max mem: 33300 +Epoch: [19] [3620/4276] eta: 0:32:31 lr: 2.6978962726951763e-05 loss: 0.1206 (0.1204) time: 2.9719 data: 0.0078 max mem: 33300 +Epoch: [19] [3630/4276] eta: 0:32:02 lr: 2.6976145064364872e-05 loss: 0.1168 (0.1204) time: 2.9716 data: 0.0077 max mem: 33300 +Epoch: [19] [3640/4276] eta: 0:31:32 lr: 2.6973327369077007e-05 loss: 0.1083 (0.1203) time: 2.9669 data: 0.0076 max mem: 33300 +Epoch: [19] [3650/4276] eta: 0:31:02 lr: 2.6970509641083998e-05 loss: 0.0961 (0.1203) time: 2.9658 data: 0.0076 max mem: 33300 +Epoch: [19] [3660/4276] eta: 0:30:32 lr: 2.696769188038167e-05 loss: 0.1059 (0.1203) time: 2.9633 data: 0.0075 max mem: 33300 +Epoch: [19] [3670/4276] eta: 0:30:03 lr: 2.6964874086965847e-05 loss: 0.1137 (0.1203) time: 2.9657 data: 0.0075 max mem: 33300 +Epoch: [19] [3680/4276] eta: 0:29:33 lr: 2.6962056260832348e-05 loss: 0.1170 (0.1203) time: 2.9630 data: 0.0079 max mem: 33300 +Epoch: [19] [3690/4276] eta: 0:29:03 lr: 2.6959238401976993e-05 loss: 0.1191 (0.1204) time: 2.9578 data: 0.0079 max mem: 33300 +Epoch: [19] [3700/4276] eta: 0:28:33 lr: 2.695642051039561e-05 loss: 0.1140 (0.1204) time: 2.9570 data: 0.0075 max mem: 33300 +Epoch: [19] [3710/4276] eta: 0:28:03 lr: 2.695360258608401e-05 loss: 0.1074 (0.1203) time: 2.9547 data: 0.0075 max mem: 33300 +Epoch: [19] [3720/4276] eta: 0:27:34 lr: 2.6950784629038e-05 loss: 0.1057 (0.1203) time: 2.9994 data: 0.0075 max mem: 33300 +Epoch: [19] [3730/4276] eta: 0:27:04 lr: 2.6947966639253418e-05 loss: 0.1082 (0.1203) time: 3.0264 data: 0.0075 max mem: 33300 +Epoch: [19] [3740/4276] eta: 0:26:34 lr: 2.6945148616726066e-05 loss: 0.1067 (0.1203) time: 2.9867 data: 0.0077 max mem: 33300 +Epoch: [19] [3750/4276] eta: 0:26:05 lr: 2.694233056145176e-05 loss: 0.1182 (0.1203) time: 2.9668 data: 0.0077 max mem: 33300 +Epoch: [19] [3760/4276] eta: 0:25:35 lr: 2.693951247342632e-05 loss: 0.1110 (0.1203) time: 2.9701 data: 0.0077 max mem: 33300 +Epoch: [19] [3770/4276] eta: 0:25:05 lr: 2.6936694352645565e-05 loss: 0.1106 (0.1203) time: 2.9728 data: 0.0078 max mem: 33300 +Epoch: [19] [3780/4276] eta: 0:24:35 lr: 2.6933876199105283e-05 loss: 0.1122 (0.1202) time: 2.9703 data: 0.0080 max mem: 33300 +Epoch: [19] [3790/4276] eta: 0:24:05 lr: 2.6931058012801303e-05 loss: 0.1037 (0.1202) time: 2.9698 data: 0.0081 max mem: 33300 +Epoch: [19] [3800/4276] eta: 0:23:36 lr: 2.6928239793729426e-05 loss: 0.1116 (0.1202) time: 2.9722 data: 0.0080 max mem: 33300 +Epoch: [19] [3810/4276] eta: 0:23:06 lr: 2.6925421541885464e-05 loss: 0.1116 (0.1202) time: 2.9711 data: 0.0080 max mem: 33300 +Epoch: [19] [3820/4276] eta: 0:22:36 lr: 2.6922603257265228e-05 loss: 0.1002 (0.1201) time: 2.9652 data: 0.0084 max mem: 33300 +Epoch: [19] [3830/4276] eta: 0:22:07 lr: 2.6919784939864518e-05 loss: 0.1107 (0.1202) time: 2.9999 data: 0.0083 max mem: 33300 +Epoch: [19] [3840/4276] eta: 0:21:37 lr: 2.6916966589679144e-05 loss: 0.1107 (0.1201) time: 3.0045 data: 0.0078 max mem: 33300 +Epoch: [19] [3850/4276] eta: 0:21:07 lr: 2.6914148206704904e-05 loss: 0.0980 (0.1201) time: 2.9673 data: 0.0075 max mem: 33300 +Epoch: [19] [3860/4276] eta: 0:20:37 lr: 2.6911329790937618e-05 loss: 0.1084 (0.1201) time: 2.9633 data: 0.0075 max mem: 33300 +Epoch: [19] [3870/4276] eta: 0:20:07 lr: 2.690851134237306e-05 loss: 0.1157 (0.1201) time: 2.9630 data: 0.0074 max mem: 33300 +Epoch: [19] [3880/4276] eta: 0:19:38 lr: 2.690569286100706e-05 loss: 0.1152 (0.1201) time: 2.9639 data: 0.0075 max mem: 33300 +Epoch: [19] [3890/4276] eta: 0:19:08 lr: 2.6902874346835392e-05 loss: 0.1113 (0.1201) time: 2.9624 data: 0.0072 max mem: 33300 +Epoch: [19] [3900/4276] eta: 0:18:38 lr: 2.690005579985388e-05 loss: 0.1113 (0.1201) time: 2.9688 data: 0.0070 max mem: 33300 +Epoch: [19] [3910/4276] eta: 0:18:08 lr: 2.6897237220058308e-05 loss: 0.1060 (0.1200) time: 2.9667 data: 0.0070 max mem: 33300 +Epoch: [19] [3920/4276] eta: 0:17:39 lr: 2.689441860744448e-05 loss: 0.0930 (0.1200) time: 2.9575 data: 0.0072 max mem: 33300 +Epoch: [19] [3930/4276] eta: 0:17:09 lr: 2.689159996200819e-05 loss: 0.0953 (0.1199) time: 2.9551 data: 0.0077 max mem: 33300 +Epoch: [19] [3940/4276] eta: 0:16:39 lr: 2.688878128374523e-05 loss: 0.1076 (0.1200) time: 2.9534 data: 0.0075 max mem: 33300 +Epoch: [19] [3950/4276] eta: 0:16:09 lr: 2.6885962572651395e-05 loss: 0.1115 (0.1199) time: 2.9528 data: 0.0075 max mem: 33300 +Epoch: [19] [3960/4276] eta: 0:15:40 lr: 2.6883143828722475e-05 loss: 0.1059 (0.1199) time: 2.9478 data: 0.0078 max mem: 33300 +Epoch: [19] [3970/4276] eta: 0:15:10 lr: 2.688032505195427e-05 loss: 0.1157 (0.1200) time: 2.9465 data: 0.0081 max mem: 33300 +Epoch: [19] [3980/4276] eta: 0:14:40 lr: 2.6877506242342565e-05 loss: 0.1249 (0.1200) time: 2.9471 data: 0.0079 max mem: 33300 +Epoch: [19] [3990/4276] eta: 0:14:10 lr: 2.6874687399883153e-05 loss: 0.1166 (0.1200) time: 2.9497 data: 0.0075 max mem: 33300 +Epoch: [19] [4000/4276] eta: 0:13:41 lr: 2.687186852457183e-05 loss: 0.1144 (0.1200) time: 2.9630 data: 0.0076 max mem: 33300 +Epoch: [19] [4010/4276] eta: 0:13:11 lr: 2.686904961640437e-05 loss: 0.1127 (0.1200) time: 2.9806 data: 0.0076 max mem: 33300 +Epoch: [19] [4020/4276] eta: 0:12:41 lr: 2.6866230675376563e-05 loss: 0.1108 (0.1199) time: 2.9809 data: 0.0077 max mem: 33300 +Epoch: [19] [4030/4276] eta: 0:12:11 lr: 2.6863411701484204e-05 loss: 0.1125 (0.1199) time: 2.9703 data: 0.0078 max mem: 33300 +Epoch: [19] [4040/4276] eta: 0:11:42 lr: 2.6860592694723064e-05 loss: 0.1131 (0.1199) time: 2.9701 data: 0.0081 max mem: 33300 +Epoch: [19] [4050/4276] eta: 0:11:12 lr: 2.685777365508894e-05 loss: 0.1094 (0.1199) time: 2.9707 data: 0.0079 max mem: 33300 +Epoch: [19] [4060/4276] eta: 0:10:42 lr: 2.6854954582577606e-05 loss: 0.1207 (0.1200) time: 2.9709 data: 0.0073 max mem: 33300 +Epoch: [19] [4070/4276] eta: 0:10:12 lr: 2.6852135477184846e-05 loss: 0.1269 (0.1200) time: 2.9716 data: 0.0072 max mem: 33300 +Epoch: [19] [4080/4276] eta: 0:09:43 lr: 2.684931633890645e-05 loss: 0.1280 (0.1200) time: 2.9746 data: 0.0079 max mem: 33300 +Epoch: [19] [4090/4276] eta: 0:09:13 lr: 2.684649716773819e-05 loss: 0.1279 (0.1200) time: 2.9848 data: 0.0082 max mem: 33300 +Epoch: [19] [4100/4276] eta: 0:08:43 lr: 2.684367796367584e-05 loss: 0.1239 (0.1201) time: 2.9831 data: 0.0079 max mem: 33300 +Epoch: [19] [4110/4276] eta: 0:08:13 lr: 2.6840858726715177e-05 loss: 0.1190 (0.1201) time: 2.9732 data: 0.0078 max mem: 33300 +Epoch: [19] [4120/4276] eta: 0:07:44 lr: 2.6838039456851987e-05 loss: 0.1105 (0.1200) time: 2.9741 data: 0.0076 max mem: 33300 +Epoch: [19] [4130/4276] eta: 0:07:14 lr: 2.683522015408204e-05 loss: 0.1046 (0.1200) time: 2.9730 data: 0.0076 max mem: 33300 +Epoch: [19] [4140/4276] eta: 0:06:44 lr: 2.683240081840111e-05 loss: 0.1119 (0.1200) time: 2.9681 data: 0.0074 max mem: 33300 +Epoch: [19] [4150/4276] eta: 0:06:14 lr: 2.682958144980498e-05 loss: 0.1147 (0.1200) time: 2.9640 data: 0.0072 max mem: 33300 +Epoch: [19] [4160/4276] eta: 0:05:45 lr: 2.6826762048289404e-05 loss: 0.1229 (0.1201) time: 2.9882 data: 0.0075 max mem: 33300 +Epoch: [19] [4170/4276] eta: 0:05:15 lr: 2.682394261385017e-05 loss: 0.1278 (0.1201) time: 2.9955 data: 0.0083 max mem: 33300 +Epoch: [19] [4180/4276] eta: 0:04:45 lr: 2.682112314648304e-05 loss: 0.1278 (0.1201) time: 2.9768 data: 0.0081 max mem: 33300 +Epoch: [19] [4190/4276] eta: 0:04:15 lr: 2.6818303646183785e-05 loss: 0.1136 (0.1201) time: 2.9804 data: 0.0076 max mem: 33300 +Epoch: [19] [4200/4276] eta: 0:03:46 lr: 2.6815484112948175e-05 loss: 0.1169 (0.1201) time: 2.9789 data: 0.0078 max mem: 33300 +Epoch: [19] [4210/4276] eta: 0:03:16 lr: 2.6812664546771975e-05 loss: 0.1191 (0.1201) time: 2.9727 data: 0.0077 max mem: 33300 +Epoch: [19] [4220/4276] eta: 0:02:46 lr: 2.6809844947650953e-05 loss: 0.1233 (0.1202) time: 2.9747 data: 0.0074 max mem: 33300 +Epoch: [19] [4230/4276] eta: 0:02:16 lr: 2.6807025315580875e-05 loss: 0.1277 (0.1202) time: 2.9785 data: 0.0074 max mem: 33300 +Epoch: [19] [4240/4276] eta: 0:01:47 lr: 2.6804205650557503e-05 loss: 0.1251 (0.1203) time: 2.9780 data: 0.0076 max mem: 33300 +Epoch: [19] [4250/4276] eta: 0:01:17 lr: 2.6801385952576603e-05 loss: 0.1208 (0.1203) time: 2.9750 data: 0.0077 max mem: 33300 +Epoch: [19] [4260/4276] eta: 0:00:47 lr: 2.679856622163393e-05 loss: 0.1208 (0.1203) time: 2.9719 data: 0.0074 max mem: 33300 +Epoch: [19] [4270/4276] eta: 0:00:17 lr: 2.6795746457725245e-05 loss: 0.1283 (0.1203) time: 2.9803 data: 0.0072 max mem: 33300 +Epoch: [19] Total time: 3:32:00 +Test: [ 0/21770] eta: 9:52:02 time: 1.6317 data: 1.5898 max mem: 33300 +Test: [ 100/21770] eta: 0:19:37 time: 0.0387 data: 0.0009 max mem: 33300 +Test: [ 200/21770] eta: 0:16:43 time: 0.0386 data: 0.0009 max mem: 33300 +Test: [ 300/21770] eta: 0:15:43 time: 0.0387 data: 0.0009 max mem: 33300 +Test: [ 400/21770] eta: 0:15:11 time: 0.0389 data: 0.0008 max mem: 33300 +Test: [ 500/21770] eta: 0:14:51 time: 0.0388 data: 0.0009 max mem: 33300 +Test: [ 600/21770] eta: 0:14:36 time: 0.0379 data: 0.0009 max mem: 33300 +Test: [ 700/21770] eta: 0:14:24 time: 0.0389 data: 0.0009 max mem: 33300 +Test: [ 800/21770] eta: 0:14:14 time: 0.0389 data: 0.0009 max mem: 33300 +Test: [ 900/21770] eta: 0:14:05 time: 0.0387 data: 0.0009 max mem: 33300 +Test: [ 1000/21770] eta: 0:13:58 time: 0.0388 data: 0.0009 max mem: 33300 +Test: [ 1100/21770] eta: 0:13:50 time: 0.0386 data: 0.0009 max mem: 33300 +Test: [ 1200/21770] eta: 0:13:43 time: 0.0386 data: 0.0008 max mem: 33300 +Test: [ 1300/21770] eta: 0:13:37 time: 0.0385 data: 0.0008 max mem: 33300 +Test: [ 1400/21770] eta: 0:13:31 time: 0.0389 data: 0.0009 max mem: 33300 +Test: [ 1500/21770] eta: 0:13:25 time: 0.0381 data: 0.0009 max mem: 33300 +Test: [ 1600/21770] eta: 0:13:20 time: 0.0386 data: 0.0009 max mem: 33300 +Test: [ 1700/21770] eta: 0:13:15 time: 0.0387 data: 0.0009 max mem: 33300 +Test: [ 1800/21770] eta: 0:13:10 time: 0.0387 data: 0.0009 max mem: 33300 +Test: [ 1900/21770] eta: 0:13:05 time: 0.0386 data: 0.0009 max mem: 33300 +Test: [ 2000/21770] eta: 0:13:00 time: 0.0387 data: 0.0009 max mem: 33300 +Test: [ 2100/21770] eta: 0:12:56 time: 0.0388 data: 0.0009 max mem: 33300 +Test: [ 2200/21770] eta: 0:12:51 time: 0.0387 data: 0.0009 max mem: 33300 +Test: [ 2300/21770] eta: 0:12:46 time: 0.0384 data: 0.0009 max mem: 33300 +Test: [ 2400/21770] eta: 0:12:42 time: 0.0392 data: 0.0010 max mem: 33300 +Test: [ 2500/21770] eta: 0:12:37 time: 0.0385 data: 0.0009 max mem: 33300 +Test: [ 2600/21770] eta: 0:12:32 time: 0.0383 data: 0.0009 max mem: 33300 +Test: [ 2700/21770] eta: 0:12:28 time: 0.0384 data: 0.0009 max mem: 33300 +Test: [ 2800/21770] eta: 0:12:23 time: 0.0383 data: 0.0009 max mem: 33300 +Test: [ 2900/21770] eta: 0:12:19 time: 0.0385 data: 0.0009 max mem: 33300 +Test: [ 3000/21770] eta: 0:12:14 time: 0.0382 data: 0.0009 max mem: 33300 +Test: [ 3100/21770] eta: 0:12:10 time: 0.0384 data: 0.0009 max mem: 33300 +Test: [ 3200/21770] eta: 0:12:06 time: 0.0381 data: 0.0009 max mem: 33300 +Test: [ 3300/21770] eta: 0:12:01 time: 0.0385 data: 0.0009 max mem: 33300 +Test: [ 3400/21770] eta: 0:11:57 time: 0.0383 data: 0.0009 max mem: 33300 +Test: [ 3500/21770] eta: 0:11:53 time: 0.0382 data: 0.0009 max mem: 33300 +Test: [ 3600/21770] eta: 0:11:49 time: 0.0384 data: 0.0009 max mem: 33300 +Test: [ 3700/21770] eta: 0:11:45 time: 0.0385 data: 0.0009 max mem: 33300 +Test: [ 3800/21770] eta: 0:11:40 time: 0.0382 data: 0.0009 max mem: 33300 +Test: [ 3900/21770] eta: 0:11:36 time: 0.0386 data: 0.0009 max mem: 33300 +Test: [ 4000/21770] eta: 0:11:32 time: 0.0384 data: 0.0009 max mem: 33300 +Test: [ 4100/21770] eta: 0:11:28 time: 0.0386 data: 0.0009 max mem: 33300 +Test: [ 4200/21770] eta: 0:11:24 time: 0.0383 data: 0.0009 max mem: 33300 +Test: [ 4300/21770] eta: 0:11:20 time: 0.0389 data: 0.0010 max mem: 33300 +Test: [ 4400/21770] eta: 0:11:16 time: 0.0388 data: 0.0010 max mem: 33300 +Test: [ 4500/21770] eta: 0:11:12 time: 0.0387 data: 0.0009 max mem: 33300 +Test: [ 4600/21770] eta: 0:11:08 time: 0.0383 data: 0.0009 max mem: 33300 +Test: [ 4700/21770] eta: 0:11:04 time: 0.0387 data: 0.0009 max mem: 33300 +Test: [ 4800/21770] eta: 0:11:00 time: 0.0384 data: 0.0009 max mem: 33300 +Test: [ 4900/21770] eta: 0:10:56 time: 0.0387 data: 0.0009 max mem: 33300 +Test: [ 5000/21770] eta: 0:10:52 time: 0.0386 data: 0.0009 max mem: 33300 +Test: [ 5100/21770] eta: 0:10:48 time: 0.0388 data: 0.0009 max mem: 33300 +Test: [ 5200/21770] eta: 0:10:44 time: 0.0383 data: 0.0009 max mem: 33300 +Test: [ 5300/21770] eta: 0:10:40 time: 0.0387 data: 0.0009 max mem: 33300 +Test: [ 5400/21770] eta: 0:10:36 time: 0.0387 data: 0.0010 max mem: 33300 +Test: [ 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time: 0.0386 data: 0.0009 max mem: 33300 +Test: [ 6900/21770] eta: 0:09:37 time: 0.0390 data: 0.0009 max mem: 33300 +Test: [ 7000/21770] eta: 0:09:33 time: 0.0388 data: 0.0009 max mem: 33300 +Test: [ 7100/21770] eta: 0:09:29 time: 0.0389 data: 0.0009 max mem: 33300 +Test: [ 7200/21770] eta: 0:09:26 time: 0.0388 data: 0.0009 max mem: 33300 +Test: [ 7300/21770] eta: 0:09:22 time: 0.0382 data: 0.0009 max mem: 33300 +Test: [ 7400/21770] eta: 0:09:18 time: 0.0387 data: 0.0009 max mem: 33300 +Test: [ 7500/21770] eta: 0:09:14 time: 0.0385 data: 0.0009 max mem: 33300 +Test: [ 7600/21770] eta: 0:09:10 time: 0.0383 data: 0.0009 max mem: 33300 +Test: [ 7700/21770] eta: 0:09:06 time: 0.0387 data: 0.0009 max mem: 33300 +Test: [ 7800/21770] eta: 0:09:02 time: 0.0388 data: 0.0009 max mem: 33300 +Test: [ 7900/21770] eta: 0:08:58 time: 0.0390 data: 0.0009 max mem: 33300 +Test: [ 8000/21770] eta: 0:08:54 time: 0.0387 data: 0.0009 max mem: 33300 +Test: [ 8100/21770] eta: 0:08:50 time: 0.0396 data: 0.0010 max mem: 33300 +Test: [ 8200/21770] eta: 0:08:47 time: 0.0392 data: 0.0009 max mem: 33300 +Test: [ 8300/21770] eta: 0:08:43 time: 0.0392 data: 0.0009 max mem: 33300 +Test: [ 8400/21770] eta: 0:08:39 time: 0.0389 data: 0.0009 max mem: 33300 +Test: [ 8500/21770] eta: 0:08:35 time: 0.0387 data: 0.0009 max mem: 33300 +Test: [ 8600/21770] eta: 0:08:31 time: 0.0388 data: 0.0009 max mem: 33300 +Test: [ 8700/21770] eta: 0:08:27 time: 0.0392 data: 0.0009 max mem: 33300 +Test: [ 8800/21770] eta: 0:08:23 time: 0.0389 data: 0.0009 max mem: 33300 +Test: [ 8900/21770] eta: 0:08:20 time: 0.0392 data: 0.0009 max mem: 33300 +Test: [ 9000/21770] eta: 0:08:16 time: 0.0391 data: 0.0010 max mem: 33300 +Test: [ 9100/21770] eta: 0:08:12 time: 0.0387 data: 0.0009 max mem: 33300 +Test: [ 9200/21770] eta: 0:08:08 time: 0.0390 data: 0.0010 max mem: 33300 +Test: [ 9300/21770] eta: 0:08:04 time: 0.0383 data: 0.0009 max mem: 33300 +Test: [ 9400/21770] eta: 0:08:00 time: 0.0387 data: 0.0009 max mem: 33300 +Test: [ 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time: 0.0393 data: 0.0010 max mem: 33300 +Test: [10900/21770] eta: 0:07:01 time: 0.0382 data: 0.0009 max mem: 33300 +Test: [11000/21770] eta: 0:06:57 time: 0.0383 data: 0.0009 max mem: 33300 +Test: [11100/21770] eta: 0:06:53 time: 0.0386 data: 0.0009 max mem: 33300 +Test: [11200/21770] eta: 0:06:50 time: 0.0385 data: 0.0009 max mem: 33300 +Test: [11300/21770] eta: 0:06:46 time: 0.0380 data: 0.0009 max mem: 33300 +Test: [11400/21770] eta: 0:06:42 time: 0.0383 data: 0.0009 max mem: 33300 +Test: [11500/21770] eta: 0:06:38 time: 0.0382 data: 0.0009 max mem: 33300 +Test: [11600/21770] eta: 0:06:34 time: 0.0389 data: 0.0009 max mem: 33300 +Test: [11700/21770] eta: 0:06:30 time: 0.0380 data: 0.0009 max mem: 33300 +Test: [11800/21770] eta: 0:06:26 time: 0.0382 data: 0.0010 max mem: 33300 +Test: [11900/21770] eta: 0:06:22 time: 0.0386 data: 0.0011 max mem: 33300 +Test: [12000/21770] eta: 0:06:18 time: 0.0386 data: 0.0009 max mem: 33300 +Test: [12100/21770] eta: 0:06:14 time: 0.0386 data: 0.0009 max mem: 33300 +Test: [12200/21770] eta: 0:06:10 time: 0.0385 data: 0.0009 max mem: 33300 +Test: [12300/21770] eta: 0:06:07 time: 0.0380 data: 0.0009 max mem: 33300 +Test: [12400/21770] eta: 0:06:03 time: 0.0384 data: 0.0009 max mem: 33300 +Test: [12500/21770] eta: 0:05:59 time: 0.0380 data: 0.0009 max mem: 33300 +Test: [12600/21770] eta: 0:05:55 time: 0.0382 data: 0.0009 max mem: 33300 +Test: [12700/21770] eta: 0:05:51 time: 0.0397 data: 0.0009 max mem: 33300 +Test: [12800/21770] eta: 0:05:47 time: 0.0400 data: 0.0010 max mem: 33300 +Test: [12900/21770] eta: 0:05:43 time: 0.0387 data: 0.0009 max mem: 33300 +Test: [13000/21770] eta: 0:05:39 time: 0.0390 data: 0.0009 max mem: 33300 +Test: [13100/21770] eta: 0:05:36 time: 0.0390 data: 0.0009 max mem: 33300 +Test: [13200/21770] eta: 0:05:32 time: 0.0392 data: 0.0009 max mem: 33300 +Test: [13300/21770] eta: 0:05:28 time: 0.0392 data: 0.0009 max mem: 33300 +Test: [13400/21770] eta: 0:05:24 time: 0.0398 data: 0.0009 max mem: 33300 +Test: [13500/21770] eta: 0:05:20 time: 0.0393 data: 0.0009 max mem: 33300 +Test: [13600/21770] eta: 0:05:16 time: 0.0389 data: 0.0009 max mem: 33300 +Test: [13700/21770] eta: 0:05:12 time: 0.0398 data: 0.0009 max mem: 33300 +Test: [13800/21770] eta: 0:05:09 time: 0.0388 data: 0.0010 max mem: 33300 +Test: [13900/21770] eta: 0:05:05 time: 0.0390 data: 0.0010 max mem: 33300 +Test: [14000/21770] eta: 0:05:01 time: 0.0390 data: 0.0009 max mem: 33300 +Test: [14100/21770] eta: 0:04:57 time: 0.0389 data: 0.0009 max mem: 33300 +Test: [14200/21770] eta: 0:04:53 time: 0.0390 data: 0.0009 max mem: 33300 +Test: [14300/21770] eta: 0:04:49 time: 0.0389 data: 0.0009 max mem: 33300 +Test: [14400/21770] eta: 0:04:45 time: 0.0388 data: 0.0009 max mem: 33300 +Test: [14500/21770] eta: 0:04:41 time: 0.0387 data: 0.0009 max mem: 33300 +Test: [14600/21770] eta: 0:04:38 time: 0.0389 data: 0.0008 max mem: 33300 +Test: [14700/21770] eta: 0:04:34 time: 0.0388 data: 0.0009 max mem: 33300 +Test: [14800/21770] eta: 0:04:30 time: 0.0388 data: 0.0009 max mem: 33300 +Test: [14900/21770] eta: 0:04:26 time: 0.0382 data: 0.0009 max mem: 33300 +Test: [15000/21770] eta: 0:04:22 time: 0.0391 data: 0.0009 max mem: 33300 +Test: [15100/21770] eta: 0:04:18 time: 0.0388 data: 0.0010 max mem: 33300 +Test: [15200/21770] eta: 0:04:14 time: 0.0385 data: 0.0009 max mem: 33300 +Test: [15300/21770] eta: 0:04:10 time: 0.0386 data: 0.0008 max mem: 33300 +Test: [15400/21770] eta: 0:04:07 time: 0.0389 data: 0.0008 max mem: 33300 +Test: [15500/21770] eta: 0:04:03 time: 0.0382 data: 0.0009 max mem: 33300 +Test: [15600/21770] eta: 0:03:59 time: 0.0385 data: 0.0009 max mem: 33300 +Test: [15700/21770] eta: 0:03:55 time: 0.0382 data: 0.0009 max mem: 33300 +Test: [15800/21770] eta: 0:03:51 time: 0.0386 data: 0.0009 max mem: 33300 +Test: [15900/21770] eta: 0:03:47 time: 0.0381 data: 0.0010 max mem: 33300 +Test: [16000/21770] eta: 0:03:43 time: 0.0394 data: 0.0009 max mem: 33300 +Test: [16100/21770] eta: 0:03:39 time: 0.0392 data: 0.0008 max mem: 33300 +Test: [16200/21770] eta: 0:03:36 time: 0.0388 data: 0.0008 max mem: 33300 +Test: [16300/21770] eta: 0:03:32 time: 0.0389 data: 0.0009 max mem: 33300 +Test: [16400/21770] eta: 0:03:28 time: 0.0398 data: 0.0009 max mem: 33300 +Test: [16500/21770] eta: 0:03:24 time: 0.0394 data: 0.0009 max mem: 33300 +Test: [16600/21770] eta: 0:03:20 time: 0.0396 data: 0.0009 max mem: 33300 +Test: [16700/21770] eta: 0:03:16 time: 0.0398 data: 0.0009 max mem: 33300 +Test: [16800/21770] eta: 0:03:12 time: 0.0392 data: 0.0009 max mem: 33300 +Test: [16900/21770] eta: 0:03:09 time: 0.0394 data: 0.0009 max mem: 33300 +Test: [17000/21770] eta: 0:03:05 time: 0.0394 data: 0.0009 max mem: 33300 +Test: [17100/21770] eta: 0:03:01 time: 0.0382 data: 0.0009 max mem: 33300 +Test: [17200/21770] eta: 0:02:57 time: 0.0381 data: 0.0009 max mem: 33300 +Test: [17300/21770] eta: 0:02:53 time: 0.0383 data: 0.0009 max mem: 33300 +Test: [17400/21770] eta: 0:02:49 time: 0.0379 data: 0.0009 max mem: 33300 +Test: [17500/21770] eta: 0:02:45 time: 0.0382 data: 0.0009 max mem: 33300 +Test: [17600/21770] eta: 0:02:41 time: 0.0380 data: 0.0009 max mem: 33300 +Test: [17700/21770] eta: 0:02:37 time: 0.0381 data: 0.0009 max mem: 33300 +Test: [17800/21770] eta: 0:02:33 time: 0.0381 data: 0.0009 max mem: 33300 +Test: [17900/21770] eta: 0:02:30 time: 0.0381 data: 0.0008 max mem: 33300 +Test: [18000/21770] eta: 0:02:26 time: 0.0382 data: 0.0009 max mem: 33300 +Test: [18100/21770] eta: 0:02:22 time: 0.0381 data: 0.0009 max mem: 33300 +Test: [18200/21770] eta: 0:02:18 time: 0.0379 data: 0.0008 max mem: 33300 +Test: [18300/21770] eta: 0:02:14 time: 0.0383 data: 0.0009 max mem: 33300 +Test: [18400/21770] eta: 0:02:10 time: 0.0381 data: 0.0009 max mem: 33300 +Test: [18500/21770] eta: 0:02:06 time: 0.0383 data: 0.0009 max mem: 33300 +Test: [18600/21770] eta: 0:02:02 time: 0.0383 data: 0.0009 max mem: 33300 +Test: [18700/21770] eta: 0:01:58 time: 0.0385 data: 0.0009 max mem: 33300 +Test: [18800/21770] eta: 0:01:55 time: 0.0381 data: 0.0009 max mem: 33300 +Test: [18900/21770] eta: 0:01:51 time: 0.0381 data: 0.0010 max mem: 33300 +Test: [19000/21770] eta: 0:01:47 time: 0.0383 data: 0.0009 max mem: 33300 +Test: [19100/21770] eta: 0:01:43 time: 0.0389 data: 0.0009 max mem: 33300 +Test: [19200/21770] eta: 0:01:39 time: 0.0391 data: 0.0009 max mem: 33300 +Test: [19300/21770] eta: 0:01:35 time: 0.0390 data: 0.0009 max mem: 33300 +Test: [19400/21770] eta: 0:01:31 time: 0.0390 data: 0.0009 max mem: 33300 +Test: [19500/21770] eta: 0:01:27 time: 0.0389 data: 0.0009 max mem: 33300 +Test: [19600/21770] eta: 0:01:24 time: 0.0390 data: 0.0009 max mem: 33300 +Test: [19700/21770] eta: 0:01:20 time: 0.0390 data: 0.0010 max mem: 33300 +Test: [19800/21770] eta: 0:01:16 time: 0.0390 data: 0.0009 max mem: 33300 +Test: [19900/21770] eta: 0:01:12 time: 0.0382 data: 0.0009 max mem: 33300 +Test: [20000/21770] eta: 0:01:08 time: 0.0389 data: 0.0009 max mem: 33300 +Test: [20100/21770] eta: 0:01:04 time: 0.0388 data: 0.0009 max mem: 33300 +Test: [20200/21770] eta: 0:01:00 time: 0.0389 data: 0.0009 max mem: 33300 +Test: [20300/21770] eta: 0:00:56 time: 0.0385 data: 0.0010 max mem: 33300 +Test: [20400/21770] eta: 0:00:53 time: 0.0387 data: 0.0009 max mem: 33300 +Test: [20500/21770] eta: 0:00:49 time: 0.0387 data: 0.0010 max mem: 33300 +Test: [20600/21770] eta: 0:00:45 time: 0.0389 data: 0.0009 max mem: 33300 +Test: [20700/21770] eta: 0:00:41 time: 0.0384 data: 0.0009 max mem: 33300 +Test: [20800/21770] eta: 0:00:37 time: 0.0386 data: 0.0009 max mem: 33300 +Test: [20900/21770] eta: 0:00:33 time: 0.0386 data: 0.0009 max mem: 33300 +Test: [21000/21770] eta: 0:00:29 time: 0.0391 data: 0.0010 max mem: 33300 +Test: [21100/21770] eta: 0:00:25 time: 0.0383 data: 0.0010 max mem: 33300 +Test: [21200/21770] eta: 0:00:22 time: 0.0382 data: 0.0009 max mem: 33300 +Test: [21300/21770] eta: 0:00:18 time: 0.0388 data: 0.0010 max mem: 33300 +Test: [21400/21770] eta: 0:00:14 time: 0.0383 data: 0.0010 max mem: 33300 +Test: [21500/21770] eta: 0:00:10 time: 0.0383 data: 0.0009 max mem: 33300 +Test: [21600/21770] eta: 0:00:06 time: 0.0385 data: 0.0009 max mem: 33300 +Test: [21700/21770] eta: 0:00:02 time: 0.0385 data: 0.0009 max mem: 33300 +Test: Total time: 0:14:03 +Final results: +Mean IoU is 4.13 + + precision@0.5 = 0.00 + precision@0.6 = 0.00 + precision@0.7 = 0.00 + precision@0.8 = 0.00 + precision@0.9 = 0.00 + overall IoU = 4.38 + mean IoU = 4.13 + +Mean accuracy for one-to-zero sample is 0.00 + +Average object IoU 0.04128493680487747 +Overall IoU 4.3831377029418945 +Better epoch: 19 + +Epoch: [20] [ 0/4276] eta: 6:41:22 lr: 2.6794054583554596e-05 loss: 0.1133 (0.1133) time: 5.6319 data: 2.1165 max mem: 33300 +Epoch: [20] [ 10/4276] eta: 4:14:59 lr: 2.6791234766891482e-05 loss: 0.1460 (0.1299) time: 3.5864 data: 0.1992 max mem: 33300 +Epoch: [20] [ 20/4276] eta: 4:03:50 lr: 2.6788414917251336e-05 loss: 0.1300 (0.1273) time: 3.3278 data: 0.0069 max mem: 33300 +Epoch: [20] [ 30/4276] eta: 3:57:08 lr: 2.6785595034629918e-05 loss: 0.1083 (0.1260) time: 3.2214 data: 0.0066 max mem: 33300 +Epoch: [20] [ 40/4276] eta: 3:53:00 lr: 2.6782775119022978e-05 loss: 0.1207 (0.1254) time: 3.1563 data: 0.0068 max mem: 33300 +Epoch: [20] [ 50/4276] eta: 3:50:25 lr: 2.6779955170426273e-05 loss: 0.1200 (0.1236) time: 3.1484 data: 0.0069 max mem: 33300 +Epoch: [20] [ 60/4276] eta: 3:48:25 lr: 2.6777135188835557e-05 loss: 0.1155 (0.1236) time: 3.1492 data: 0.0073 max mem: 33300 +Epoch: [20] [ 70/4276] eta: 3:46:48 lr: 2.6774315174246583e-05 loss: 0.1167 (0.1228) time: 3.1437 data: 0.0078 max mem: 33300 +Epoch: [20] [ 80/4276] eta: 3:45:22 lr: 2.6771495126655104e-05 loss: 0.1196 (0.1227) time: 3.1367 data: 0.0082 max mem: 33300 +Epoch: [20] [ 90/4276] eta: 3:44:03 lr: 2.6768675046056873e-05 loss: 0.1144 (0.1210) time: 3.1264 data: 0.0081 max mem: 33300 +Epoch: [20] [ 100/4276] eta: 3:42:47 lr: 2.6765854932447633e-05 loss: 0.1167 (0.1224) time: 3.1136 data: 0.0076 max mem: 33300 +Epoch: [20] [ 110/4276] eta: 3:41:53 lr: 2.6763034785823142e-05 loss: 0.1365 (0.1233) time: 3.1241 data: 0.0076 max mem: 33300 +Epoch: [20] [ 120/4276] eta: 3:40:55 lr: 2.676021460617914e-05 loss: 0.1209 (0.1231) time: 3.1309 data: 0.0080 max mem: 33300 +Epoch: [20] [ 130/4276] eta: 3:39:56 lr: 2.6757394393511374e-05 loss: 0.1215 (0.1240) time: 3.1113 data: 0.0085 max mem: 33300 +Epoch: [20] [ 140/4276] eta: 3:38:40 lr: 2.6754574147815596e-05 loss: 0.1209 (0.1235) time: 3.0691 data: 0.0085 max mem: 33300 +Epoch: [20] [ 150/4276] eta: 3:37:19 lr: 2.6751753869087552e-05 loss: 0.1061 (0.1224) time: 3.0123 data: 0.0080 max mem: 33300 +Epoch: [20] [ 160/4276] eta: 3:35:53 lr: 2.6748933557322974e-05 loss: 0.1122 (0.1227) time: 2.9691 data: 0.0078 max mem: 33300 +Epoch: [20] [ 170/4276] eta: 3:34:38 lr: 2.6746113212517616e-05 loss: 0.1122 (0.1217) time: 2.9562 data: 0.0077 max mem: 33300 +Epoch: [20] [ 180/4276] eta: 3:33:24 lr: 2.6743292834667215e-05 loss: 0.1063 (0.1218) time: 2.9574 data: 0.0080 max mem: 33300 +Epoch: [20] [ 190/4276] eta: 3:32:14 lr: 2.6740472423767517e-05 loss: 0.1145 (0.1221) time: 2.9481 data: 0.0081 max mem: 33300 +Epoch: [20] [ 200/4276] eta: 3:31:17 lr: 2.6737651979814248e-05 loss: 0.1013 (0.1215) time: 2.9666 data: 0.0075 max mem: 33300 +Epoch: [20] [ 210/4276] eta: 3:30:24 lr: 2.6734831502803154e-05 loss: 0.1189 (0.1219) time: 2.9934 data: 0.0075 max mem: 33300 +Epoch: [20] [ 220/4276] eta: 3:29:35 lr: 2.6732010992729985e-05 loss: 0.1213 (0.1219) time: 3.0009 data: 0.0075 max mem: 33300 +Epoch: [20] [ 230/4276] eta: 3:28:45 lr: 2.672919044959046e-05 loss: 0.1024 (0.1211) time: 2.9977 data: 0.0071 max mem: 33300 +Epoch: [20] [ 240/4276] eta: 3:27:57 lr: 2.6726369873380314e-05 loss: 0.1034 (0.1209) time: 2.9942 data: 0.0070 max mem: 33300 +Epoch: [20] [ 250/4276] eta: 3:27:11 lr: 2.6723549264095288e-05 loss: 0.1230 (0.1214) time: 2.9976 data: 0.0069 max mem: 33300 +Epoch: [20] [ 260/4276] eta: 3:26:27 lr: 2.672072862173112e-05 loss: 0.1357 (0.1214) time: 2.9985 data: 0.0066 max mem: 33300 +Epoch: [20] [ 270/4276] eta: 3:25:43 lr: 2.671790794628353e-05 loss: 0.1059 (0.1211) time: 2.9979 data: 0.0069 max mem: 33300 +Epoch: [20] [ 280/4276] eta: 3:25:01 lr: 2.6715087237748266e-05 loss: 0.1010 (0.1209) time: 3.0000 data: 0.0072 max mem: 33300 +Epoch: [20] [ 290/4276] eta: 3:24:18 lr: 2.671226649612104e-05 loss: 0.1143 (0.1208) time: 2.9970 data: 0.0070 max mem: 33300 +Epoch: [20] [ 300/4276] eta: 3:23:37 lr: 2.670944572139759e-05 loss: 0.1143 (0.1207) time: 2.9920 data: 0.0069 max mem: 33300 +Epoch: [20] [ 310/4276] eta: 3:22:56 lr: 2.6706624913573648e-05 loss: 0.1196 (0.1206) time: 2.9948 data: 0.0070 max mem: 33300 +Epoch: [20] [ 320/4276] eta: 3:22:18 lr: 2.6703804072644928e-05 loss: 0.1070 (0.1208) time: 3.0037 data: 0.0070 max mem: 33300 +Epoch: [20] [ 330/4276] eta: 3:21:39 lr: 2.6700983198607167e-05 loss: 0.1193 (0.1210) time: 3.0053 data: 0.0072 max mem: 33300 +Epoch: [20] [ 340/4276] eta: 3:21:02 lr: 2.6698162291456086e-05 loss: 0.1165 (0.1208) time: 3.0029 data: 0.0074 max mem: 33300 +Epoch: [20] [ 350/4276] eta: 3:20:24 lr: 2.669534135118741e-05 loss: 0.1046 (0.1206) time: 3.0048 data: 0.0072 max mem: 33300 +Epoch: [20] [ 360/4276] eta: 3:19:48 lr: 2.6692520377796854e-05 loss: 0.1191 (0.1211) time: 3.0070 data: 0.0072 max mem: 33300 +Epoch: [20] [ 370/4276] eta: 3:19:11 lr: 2.6689699371280152e-05 loss: 0.1210 (0.1211) time: 3.0041 data: 0.0072 max mem: 33300 +Epoch: [20] [ 380/4276] eta: 3:18:35 lr: 2.668687833163302e-05 loss: 0.1134 (0.1210) time: 3.0066 data: 0.0075 max mem: 33300 +Epoch: [20] [ 390/4276] eta: 3:17:59 lr: 2.6684057258851175e-05 loss: 0.1213 (0.1212) time: 3.0066 data: 0.0076 max mem: 33300 +Epoch: [20] [ 400/4276] eta: 3:17:22 lr: 2.6681236152930335e-05 loss: 0.1376 (0.1218) time: 2.9955 data: 0.0073 max mem: 33300 +Epoch: [20] [ 410/4276] eta: 3:16:46 lr: 2.667841501386622e-05 loss: 0.1298 (0.1217) time: 2.9946 data: 0.0075 max mem: 33300 +Epoch: [20] [ 420/4276] eta: 3:16:10 lr: 2.667559384165455e-05 loss: 0.1237 (0.1218) time: 2.9984 data: 0.0071 max mem: 33300 +Epoch: [20] [ 430/4276] eta: 3:15:35 lr: 2.6672772636291028e-05 loss: 0.1254 (0.1220) time: 2.9993 data: 0.0072 max mem: 33300 +Epoch: [20] [ 440/4276] eta: 3:14:56 lr: 2.6669951397771374e-05 loss: 0.1095 (0.1216) time: 2.9728 data: 0.0078 max mem: 33300 +Epoch: [20] [ 450/4276] eta: 3:14:15 lr: 2.666713012609131e-05 loss: 0.1106 (0.1216) time: 2.9374 data: 0.0076 max mem: 33300 +Epoch: [20] [ 460/4276] eta: 3:13:35 lr: 2.666430882124654e-05 loss: 0.1103 (0.1212) time: 2.9296 data: 0.0077 max mem: 33300 +Epoch: [20] [ 470/4276] eta: 3:12:57 lr: 2.6661487483232777e-05 loss: 0.0898 (0.1207) time: 2.9398 data: 0.0078 max mem: 33300 +Epoch: [20] [ 480/4276] eta: 3:12:24 lr: 2.665866611204573e-05 loss: 0.1034 (0.1206) time: 2.9788 data: 0.0078 max mem: 33300 +Epoch: [20] [ 490/4276] eta: 3:11:49 lr: 2.6655844707681106e-05 loss: 0.1034 (0.1201) time: 2.9979 data: 0.0080 max mem: 33300 +Epoch: [20] [ 500/4276] eta: 3:11:15 lr: 2.665302327013462e-05 loss: 0.1039 (0.1199) time: 2.9871 data: 0.0077 max mem: 33300 +Epoch: [20] [ 510/4276] eta: 3:10:40 lr: 2.6650201799401968e-05 loss: 0.1078 (0.1198) time: 2.9861 data: 0.0069 max mem: 33300 +Epoch: [20] [ 520/4276] eta: 3:10:06 lr: 2.6647380295478862e-05 loss: 0.1093 (0.1197) time: 2.9855 data: 0.0069 max mem: 33300 +Epoch: [20] [ 530/4276] eta: 3:09:30 lr: 2.6644558758361016e-05 loss: 0.1097 (0.1196) time: 2.9696 data: 0.0073 max mem: 33300 +Epoch: [20] [ 540/4276] eta: 3:08:51 lr: 2.6641737188044114e-05 loss: 0.1064 (0.1192) time: 2.9296 data: 0.0079 max mem: 33300 +Epoch: [20] [ 550/4276] eta: 3:08:12 lr: 2.6638915584523872e-05 loss: 0.1004 (0.1192) time: 2.9067 data: 0.0083 max mem: 33300 +Epoch: [20] [ 560/4276] eta: 3:07:38 lr: 2.663609394779598e-05 loss: 0.1141 (0.1191) time: 2.9410 data: 0.0093 max mem: 33300 +Epoch: [20] [ 570/4276] eta: 3:07:04 lr: 2.663327227785616e-05 loss: 0.1083 (0.1189) time: 2.9770 data: 0.0092 max mem: 33300 +Epoch: [20] [ 580/4276] eta: 3:06:30 lr: 2.663045057470009e-05 loss: 0.1083 (0.1188) time: 2.9752 data: 0.0086 max mem: 33300 +Epoch: [20] [ 590/4276] eta: 3:05:56 lr: 2.6627628838323476e-05 loss: 0.1026 (0.1184) time: 2.9703 data: 0.0093 max mem: 33300 +Epoch: [20] [ 600/4276] eta: 3:05:23 lr: 2.6624807068722018e-05 loss: 0.0928 (0.1180) time: 2.9690 data: 0.0091 max mem: 33300 +Epoch: [20] [ 610/4276] eta: 3:04:56 lr: 2.6621985265891414e-05 loss: 0.0970 (0.1178) time: 3.0289 data: 0.0086 max mem: 33300 +Epoch: [20] [ 620/4276] eta: 3:04:30 lr: 2.6619163429827343e-05 loss: 0.1091 (0.1180) time: 3.0939 data: 0.0084 max mem: 33300 +Epoch: [20] [ 630/4276] eta: 3:04:04 lr: 2.6616341560525517e-05 loss: 0.1157 (0.1182) time: 3.0995 data: 0.0082 max mem: 33300 +Epoch: [20] [ 640/4276] eta: 3:03:37 lr: 2.661351965798162e-05 loss: 0.1111 (0.1182) time: 3.0970 data: 0.0078 max mem: 33300 +Epoch: [20] [ 650/4276] eta: 3:03:10 lr: 2.6610697722191357e-05 loss: 0.1127 (0.1183) time: 3.0919 data: 0.0076 max mem: 33300 +Epoch: [20] [ 660/4276] eta: 3:02:43 lr: 2.6607875753150395e-05 loss: 0.1171 (0.1185) time: 3.0917 data: 0.0076 max mem: 33300 +Epoch: [20] [ 670/4276] eta: 3:02:16 lr: 2.660505375085445e-05 loss: 0.1244 (0.1186) time: 3.0874 data: 0.0084 max mem: 33300 +Epoch: [20] [ 680/4276] eta: 3:01:49 lr: 2.6602231715299187e-05 loss: 0.1236 (0.1185) time: 3.0865 data: 0.0085 max mem: 33300 +Epoch: [20] [ 690/4276] eta: 3:01:16 lr: 2.6599409646480312e-05 loss: 0.1077 (0.1185) time: 3.0452 data: 0.0079 max mem: 33300 +Epoch: [20] [ 700/4276] eta: 3:00:48 lr: 2.6596587544393496e-05 loss: 0.1117 (0.1184) time: 3.0349 data: 0.0079 max mem: 33300 +Epoch: [20] [ 710/4276] eta: 3:00:21 lr: 2.6593765409034437e-05 loss: 0.1144 (0.1184) time: 3.0834 data: 0.0082 max mem: 33300 +Epoch: [20] [ 720/4276] eta: 2:59:54 lr: 2.659094324039882e-05 loss: 0.1144 (0.1185) time: 3.0999 data: 0.0085 max mem: 33300 +Epoch: [20] [ 730/4276] eta: 2:59:26 lr: 2.658812103848232e-05 loss: 0.1095 (0.1185) time: 3.0988 data: 0.0081 max mem: 33300 +Epoch: [20] [ 740/4276] eta: 2:58:59 lr: 2.658529880328062e-05 loss: 0.1045 (0.1184) time: 3.0938 data: 0.0076 max mem: 33300 +Epoch: [20] [ 750/4276] eta: 2:58:31 lr: 2.6582476534789412e-05 loss: 0.1074 (0.1184) time: 3.0945 data: 0.0078 max mem: 33300 +Epoch: [20] [ 760/4276] eta: 2:58:03 lr: 2.6579654233004364e-05 loss: 0.1051 (0.1184) time: 3.0933 data: 0.0079 max mem: 33300 +Epoch: [20] [ 770/4276] eta: 2:57:35 lr: 2.6576831897921163e-05 loss: 0.1054 (0.1184) time: 3.0880 data: 0.0076 max mem: 33300 +Epoch: [20] [ 780/4276] eta: 2:57:03 lr: 2.6574009529535476e-05 loss: 0.1145 (0.1183) time: 3.0422 data: 0.0081 max mem: 33300 +Epoch: [20] [ 790/4276] eta: 2:56:35 lr: 2.6571187127842996e-05 loss: 0.1173 (0.1183) time: 3.0502 data: 0.0090 max mem: 33300 +Epoch: [20] [ 800/4276] eta: 2:56:07 lr: 2.656836469283938e-05 loss: 0.1161 (0.1184) time: 3.0927 data: 0.0089 max mem: 33300 +Epoch: [20] [ 810/4276] eta: 2:55:38 lr: 2.6565542224520323e-05 loss: 0.1161 (0.1187) time: 3.0836 data: 0.0081 max mem: 33300 +Epoch: [20] [ 820/4276] eta: 2:55:10 lr: 2.6562719722881486e-05 loss: 0.1161 (0.1185) time: 3.0841 data: 0.0080 max mem: 33300 +Epoch: [20] [ 830/4276] eta: 2:54:41 lr: 2.6559897187918543e-05 loss: 0.1028 (0.1187) time: 3.0842 data: 0.0081 max mem: 33300 +Epoch: [20] [ 840/4276] eta: 2:54:12 lr: 2.6557074619627175e-05 loss: 0.1176 (0.1187) time: 3.0846 data: 0.0079 max mem: 33300 +Epoch: [20] [ 850/4276] eta: 2:53:44 lr: 2.6554252018003034e-05 loss: 0.1132 (0.1187) time: 3.0863 data: 0.0078 max mem: 33300 +Epoch: [20] [ 860/4276] eta: 2:53:15 lr: 2.6551429383041804e-05 loss: 0.1128 (0.1188) time: 3.0839 data: 0.0077 max mem: 33300 +Epoch: [20] [ 870/4276] eta: 2:52:43 lr: 2.654860671473915e-05 loss: 0.1129 (0.1187) time: 3.0515 data: 0.0077 max mem: 33300 +Epoch: [20] [ 880/4276] eta: 2:52:15 lr: 2.6545784013090747e-05 loss: 0.1081 (0.1187) time: 3.0556 data: 0.0074 max mem: 33300 +Epoch: [20] [ 890/4276] eta: 2:51:46 lr: 2.6542961278092243e-05 loss: 0.1241 (0.1189) time: 3.0886 data: 0.0074 max mem: 33300 +Epoch: [20] [ 900/4276] eta: 2:51:18 lr: 2.6540138509739316e-05 loss: 0.1254 (0.1189) time: 3.0914 data: 0.0073 max mem: 33300 +Epoch: [20] [ 910/4276] eta: 2:50:49 lr: 2.6537315708027626e-05 loss: 0.1225 (0.1190) time: 3.0919 data: 0.0073 max mem: 33300 +Epoch: [20] [ 920/4276] eta: 2:50:20 lr: 2.6534492872952843e-05 loss: 0.1178 (0.1191) time: 3.0857 data: 0.0073 max mem: 33300 +Epoch: [20] [ 930/4276] eta: 2:49:51 lr: 2.6531670004510616e-05 loss: 0.1134 (0.1191) time: 3.0842 data: 0.0072 max mem: 33300 +Epoch: [20] [ 940/4276] eta: 2:49:22 lr: 2.652884710269662e-05 loss: 0.1158 (0.1191) time: 3.0853 data: 0.0073 max mem: 33300 +Epoch: [20] [ 950/4276] eta: 2:48:52 lr: 2.6526024167506504e-05 loss: 0.1158 (0.1192) time: 3.0851 data: 0.0072 max mem: 33300 +Epoch: [20] [ 960/4276] eta: 2:48:21 lr: 2.6523201198935933e-05 loss: 0.1260 (0.1193) time: 3.0567 data: 0.0073 max mem: 33300 +Epoch: [20] [ 970/4276] eta: 2:47:52 lr: 2.6520378196980562e-05 loss: 0.1284 (0.1194) time: 3.0544 data: 0.0075 max mem: 33300 +Epoch: [20] [ 980/4276] eta: 2:47:22 lr: 2.6517555161636043e-05 loss: 0.1186 (0.1194) time: 3.0664 data: 0.0073 max mem: 33300 +Epoch: [20] [ 990/4276] eta: 2:46:52 lr: 2.6514732092898043e-05 loss: 0.1108 (0.1193) time: 3.0522 data: 0.0077 max mem: 33300 +Epoch: [20] [1000/4276] eta: 2:46:20 lr: 2.651190899076221e-05 loss: 0.1163 (0.1193) time: 3.0377 data: 0.0080 max mem: 33300 +Epoch: [20] [1010/4276] eta: 2:45:49 lr: 2.6509085855224192e-05 loss: 0.1163 (0.1192) time: 3.0214 data: 0.0074 max mem: 33300 +Epoch: [20] [1020/4276] eta: 2:45:18 lr: 2.650626268627965e-05 loss: 0.1111 (0.1192) time: 3.0203 data: 0.0072 max mem: 33300 +Epoch: [20] [1030/4276] eta: 2:44:46 lr: 2.6503439483924225e-05 loss: 0.1090 (0.1192) time: 3.0203 data: 0.0071 max mem: 33300 +Epoch: [20] [1040/4276] eta: 2:44:15 lr: 2.6500616248153588e-05 loss: 0.1113 (0.1192) time: 3.0224 data: 0.0072 max mem: 33300 +Epoch: [20] [1050/4276] eta: 2:43:43 lr: 2.649779297896336e-05 loss: 0.1146 (0.1193) time: 3.0023 data: 0.0076 max mem: 33300 +Epoch: [20] [1060/4276] eta: 2:43:13 lr: 2.6494969676349206e-05 loss: 0.1154 (0.1193) time: 3.0180 data: 0.0078 max mem: 33300 +Epoch: [20] [1070/4276] eta: 2:42:44 lr: 2.6492146340306768e-05 loss: 0.1237 (0.1195) time: 3.0737 data: 0.0086 max mem: 33300 +Epoch: [20] [1080/4276] eta: 2:42:14 lr: 2.64893229708317e-05 loss: 0.1295 (0.1196) time: 3.0876 data: 0.0088 max mem: 33300 +Epoch: [20] [1090/4276] eta: 2:41:45 lr: 2.648649956791963e-05 loss: 0.1207 (0.1197) time: 3.0844 data: 0.0084 max mem: 33300 +Epoch: [20] [1100/4276] eta: 2:41:16 lr: 2.6483676131566215e-05 loss: 0.1255 (0.1198) time: 3.0857 data: 0.0085 max mem: 33300 +Epoch: [20] [1110/4276] eta: 2:40:46 lr: 2.6480852661767097e-05 loss: 0.1255 (0.1199) time: 3.0870 data: 0.0088 max mem: 33300 +Epoch: [20] [1120/4276] eta: 2:40:16 lr: 2.6478029158517915e-05 loss: 0.1169 (0.1198) time: 3.0632 data: 0.0084 max mem: 33300 +Epoch: [20] [1130/4276] eta: 2:39:44 lr: 2.6475205621814304e-05 loss: 0.1079 (0.1197) time: 3.0302 data: 0.0075 max mem: 33300 +Epoch: [20] [1140/4276] eta: 2:39:12 lr: 2.6472382051651905e-05 loss: 0.1122 (0.1197) time: 3.0066 data: 0.0073 max mem: 33300 +Epoch: [20] [1150/4276] eta: 2:38:41 lr: 2.6469558448026365e-05 loss: 0.1172 (0.1197) time: 3.0042 data: 0.0072 max mem: 33300 +Epoch: [20] [1160/4276] eta: 2:38:12 lr: 2.6466734810933313e-05 loss: 0.1143 (0.1197) time: 3.0509 data: 0.0082 max mem: 33300 +Epoch: [20] [1170/4276] eta: 2:37:42 lr: 2.6463911140368385e-05 loss: 0.1090 (0.1197) time: 3.0860 data: 0.0090 max mem: 33300 +Epoch: [20] [1180/4276] eta: 2:37:13 lr: 2.6461087436327214e-05 loss: 0.1090 (0.1196) time: 3.0806 data: 0.0088 max mem: 33300 +Epoch: [20] [1190/4276] eta: 2:36:42 lr: 2.6458263698805447e-05 loss: 0.1147 (0.1196) time: 3.0522 data: 0.0086 max mem: 33300 +Epoch: [20] [1200/4276] eta: 2:36:12 lr: 2.6455439927798702e-05 loss: 0.1160 (0.1195) time: 3.0465 data: 0.0086 max mem: 33300 +Epoch: [20] [1210/4276] eta: 2:35:42 lr: 2.6452616123302615e-05 loss: 0.1113 (0.1194) time: 3.0742 data: 0.0087 max mem: 33300 +Epoch: [20] [1220/4276] eta: 2:35:13 lr: 2.644979228531282e-05 loss: 0.1123 (0.1195) time: 3.0841 data: 0.0082 max mem: 33300 +Epoch: [20] [1230/4276] eta: 2:34:42 lr: 2.6446968413824945e-05 loss: 0.1201 (0.1195) time: 3.0690 data: 0.0079 max mem: 33300 +Epoch: [20] [1240/4276] eta: 2:34:12 lr: 2.6444144508834613e-05 loss: 0.1143 (0.1195) time: 3.0626 data: 0.0085 max mem: 33300 +Epoch: [20] [1250/4276] eta: 2:33:43 lr: 2.6441320570337453e-05 loss: 0.1144 (0.1195) time: 3.0782 data: 0.0084 max mem: 33300 +Epoch: [20] [1260/4276] eta: 2:33:13 lr: 2.64384965983291e-05 loss: 0.1086 (0.1194) time: 3.0861 data: 0.0078 max mem: 33300 +Epoch: [20] [1270/4276] eta: 2:32:44 lr: 2.643567259280517e-05 loss: 0.0958 (0.1193) time: 3.0856 data: 0.0077 max mem: 33300 +Epoch: [20] [1280/4276] eta: 2:32:14 lr: 2.643284855376129e-05 loss: 0.1142 (0.1193) time: 3.0856 data: 0.0075 max mem: 33300 +Epoch: [20] [1290/4276] eta: 2:31:44 lr: 2.6430024481193083e-05 loss: 0.1233 (0.1193) time: 3.0858 data: 0.0074 max mem: 33300 +Epoch: [20] [1300/4276] eta: 2:31:15 lr: 2.6427200375096167e-05 loss: 0.0988 (0.1192) time: 3.0886 data: 0.0071 max mem: 33300 +Epoch: [20] [1310/4276] eta: 2:30:45 lr: 2.6424376235466176e-05 loss: 0.0979 (0.1191) time: 3.0831 data: 0.0072 max mem: 33300 +Epoch: [20] [1320/4276] eta: 2:30:15 lr: 2.642155206229871e-05 loss: 0.1041 (0.1192) time: 3.0645 data: 0.0074 max mem: 33300 +Epoch: [20] [1330/4276] eta: 2:29:44 lr: 2.64187278555894e-05 loss: 0.1112 (0.1191) time: 3.0543 data: 0.0074 max mem: 33300 +Epoch: [20] [1340/4276] eta: 2:29:15 lr: 2.6415903615333858e-05 loss: 0.1041 (0.1190) time: 3.0713 data: 0.0074 max mem: 33300 +Epoch: [20] [1350/4276] eta: 2:28:45 lr: 2.6413079341527715e-05 loss: 0.1131 (0.1191) time: 3.0868 data: 0.0073 max mem: 33300 +Epoch: [20] [1360/4276] eta: 2:28:15 lr: 2.641025503416656e-05 loss: 0.1164 (0.1191) time: 3.0863 data: 0.0074 max mem: 33300 +Epoch: [20] [1370/4276] eta: 2:27:45 lr: 2.6407430693246028e-05 loss: 0.1109 (0.1190) time: 3.0883 data: 0.0074 max mem: 33300 +Epoch: [20] [1380/4276] eta: 2:27:15 lr: 2.640460631876172e-05 loss: 0.1145 (0.1191) time: 3.0720 data: 0.0074 max mem: 33300 +Epoch: [20] [1390/4276] eta: 2:26:42 lr: 2.6401781910709266e-05 loss: 0.1293 (0.1192) time: 2.9984 data: 0.0071 max mem: 33300 +Epoch: [20] [1400/4276] eta: 2:26:10 lr: 2.6398957469084256e-05 loss: 0.1267 (0.1193) time: 2.9425 data: 0.0071 max mem: 33300 +Epoch: [20] [1410/4276] eta: 2:25:36 lr: 2.6396132993882304e-05 loss: 0.1172 (0.1192) time: 2.9194 data: 0.0079 max mem: 33300 +Epoch: [20] [1420/4276] eta: 2:25:03 lr: 2.6393308485099034e-05 loss: 0.1077 (0.1192) time: 2.9112 data: 0.0083 max mem: 33300 +Epoch: [20] [1430/4276] eta: 2:24:30 lr: 2.6390483942730036e-05 loss: 0.1113 (0.1192) time: 2.9250 data: 0.0085 max mem: 33300 +Epoch: [20] [1440/4276] eta: 2:23:57 lr: 2.6387659366770924e-05 loss: 0.1148 (0.1192) time: 2.9316 data: 0.0086 max mem: 33300 +Epoch: [20] [1450/4276] eta: 2:23:25 lr: 2.6384834757217302e-05 loss: 0.1148 (0.1192) time: 2.9399 data: 0.0086 max mem: 33300 +Epoch: [20] [1460/4276] eta: 2:22:53 lr: 2.638201011406478e-05 loss: 0.1036 (0.1191) time: 2.9456 data: 0.0087 max mem: 33300 +Epoch: [20] [1470/4276] eta: 2:22:20 lr: 2.637918543730895e-05 loss: 0.0993 (0.1190) time: 2.9448 data: 0.0083 max mem: 33300 +Epoch: [20] [1480/4276] eta: 2:21:48 lr: 2.637636072694542e-05 loss: 0.1042 (0.1189) time: 2.9364 data: 0.0082 max mem: 33300 +Epoch: [20] [1490/4276] eta: 2:21:15 lr: 2.6373535982969792e-05 loss: 0.1042 (0.1188) time: 2.9349 data: 0.0086 max mem: 33300 +Epoch: [20] [1500/4276] eta: 2:20:43 lr: 2.6370711205377668e-05 loss: 0.1082 (0.1188) time: 2.9359 data: 0.0085 max mem: 33300 +Epoch: [20] [1510/4276] eta: 2:20:11 lr: 2.636788639416464e-05 loss: 0.1048 (0.1188) time: 2.9421 data: 0.0084 max mem: 33300 +Epoch: [20] [1520/4276] eta: 2:19:39 lr: 2.6365061549326314e-05 loss: 0.1078 (0.1188) time: 2.9441 data: 0.0081 max mem: 33300 +Epoch: [20] [1530/4276] eta: 2:19:06 lr: 2.6362236670858275e-05 loss: 0.1008 (0.1187) time: 2.9418 data: 0.0084 max mem: 33300 +Epoch: [20] [1540/4276] eta: 2:18:34 lr: 2.6359411758756136e-05 loss: 0.1005 (0.1187) time: 2.9465 data: 0.0090 max mem: 33300 +Epoch: [20] [1550/4276] eta: 2:18:02 lr: 2.635658681301547e-05 loss: 0.1098 (0.1186) time: 2.9419 data: 0.0090 max mem: 33300 +Epoch: [20] [1560/4276] eta: 2:17:30 lr: 2.635376183363189e-05 loss: 0.1086 (0.1185) time: 2.9367 data: 0.0086 max mem: 33300 +Epoch: [20] [1570/4276] eta: 2:16:58 lr: 2.6350936820600973e-05 loss: 0.1095 (0.1185) time: 2.9406 data: 0.0083 max mem: 33300 +Epoch: [20] [1580/4276] eta: 2:16:26 lr: 2.6348111773918326e-05 loss: 0.0995 (0.1185) time: 2.9433 data: 0.0083 max mem: 33300 +Epoch: [20] [1590/4276] eta: 2:15:54 lr: 2.6345286693579524e-05 loss: 0.1016 (0.1185) time: 2.9440 data: 0.0084 max mem: 33300 +Epoch: [20] [1600/4276] eta: 2:15:22 lr: 2.6342461579580157e-05 loss: 0.1209 (0.1185) time: 2.9318 data: 0.0087 max mem: 33300 +Epoch: [20] [1610/4276] eta: 2:14:50 lr: 2.633963643191582e-05 loss: 0.1099 (0.1184) time: 2.9308 data: 0.0087 max mem: 33300 +Epoch: [20] [1620/4276] eta: 2:14:18 lr: 2.6336811250582106e-05 loss: 0.1099 (0.1184) time: 2.9463 data: 0.0086 max mem: 33300 +Epoch: [20] [1630/4276] eta: 2:13:46 lr: 2.633398603557458e-05 loss: 0.1106 (0.1184) time: 2.9491 data: 0.0082 max mem: 33300 +Epoch: [20] [1640/4276] eta: 2:13:15 lr: 2.633116078688884e-05 loss: 0.1025 (0.1183) time: 2.9508 data: 0.0077 max mem: 33300 +Epoch: [20] [1650/4276] eta: 2:12:43 lr: 2.632833550452047e-05 loss: 0.1026 (0.1182) time: 2.9504 data: 0.0077 max mem: 33300 +Epoch: [20] [1660/4276] eta: 2:12:11 lr: 2.6325510188465052e-05 loss: 0.1060 (0.1182) time: 2.9454 data: 0.0077 max mem: 33300 +Epoch: [20] [1670/4276] eta: 2:11:40 lr: 2.6322684838718164e-05 loss: 0.1059 (0.1181) time: 2.9443 data: 0.0075 max mem: 33300 +Epoch: [20] [1680/4276] eta: 2:11:08 lr: 2.631985945527538e-05 loss: 0.1059 (0.1181) time: 2.9391 data: 0.0076 max mem: 33300 +Epoch: [20] [1690/4276] eta: 2:10:36 lr: 2.6317034038132294e-05 loss: 0.1013 (0.1180) time: 2.9364 data: 0.0078 max mem: 33300 +Epoch: [20] [1700/4276] eta: 2:10:04 lr: 2.6314208587284478e-05 loss: 0.1038 (0.1180) time: 2.9270 data: 0.0077 max mem: 33300 +Epoch: [20] [1710/4276] eta: 2:09:32 lr: 2.63113831027275e-05 loss: 0.1121 (0.1180) time: 2.9243 data: 0.0078 max mem: 33300 +Epoch: [20] [1720/4276] eta: 2:09:01 lr: 2.6308557584456938e-05 loss: 0.1113 (0.1180) time: 2.9343 data: 0.0082 max mem: 33300 +Epoch: [20] [1730/4276] eta: 2:08:29 lr: 2.6305732032468378e-05 loss: 0.1235 (0.1180) time: 2.9342 data: 0.0080 max mem: 33300 +Epoch: [20] [1740/4276] eta: 2:07:57 lr: 2.6302906446757386e-05 loss: 0.1143 (0.1180) time: 2.9358 data: 0.0077 max mem: 33300 +Epoch: [20] [1750/4276] eta: 2:07:26 lr: 2.6300080827319534e-05 loss: 0.1048 (0.1179) time: 2.9404 data: 0.0075 max mem: 33300 +Epoch: [20] [1760/4276] eta: 2:06:54 lr: 2.6297255174150387e-05 loss: 0.0984 (0.1178) time: 2.9401 data: 0.0075 max mem: 33300 +Epoch: [20] [1770/4276] eta: 2:06:23 lr: 2.629442948724553e-05 loss: 0.1025 (0.1177) time: 2.9428 data: 0.0077 max mem: 33300 +Epoch: [20] [1780/4276] eta: 2:05:52 lr: 2.629160376660052e-05 loss: 0.1025 (0.1177) time: 2.9473 data: 0.0077 max mem: 33300 +Epoch: [20] [1790/4276] eta: 2:05:20 lr: 2.6288778012210923e-05 loss: 0.0966 (0.1176) time: 2.9415 data: 0.0075 max mem: 33300 +Epoch: [20] [1800/4276] eta: 2:04:49 lr: 2.6285952224072318e-05 loss: 0.1034 (0.1176) time: 2.9330 data: 0.0075 max mem: 33300 +Epoch: [20] [1810/4276] eta: 2:04:17 lr: 2.6283126402180263e-05 loss: 0.1171 (0.1177) time: 2.9326 data: 0.0077 max mem: 33300 +Epoch: [20] [1820/4276] eta: 2:03:46 lr: 2.6280300546530323e-05 loss: 0.1273 (0.1177) time: 2.9343 data: 0.0077 max mem: 33300 +Epoch: [20] [1830/4276] eta: 2:03:14 lr: 2.6277474657118063e-05 loss: 0.1134 (0.1177) time: 2.9213 data: 0.0077 max mem: 33300 +Epoch: [20] [1840/4276] eta: 2:02:42 lr: 2.6274648733939038e-05 loss: 0.1102 (0.1176) time: 2.9219 data: 0.0081 max mem: 33300 +Epoch: [20] [1850/4276] eta: 2:02:11 lr: 2.6271822776988823e-05 loss: 0.1120 (0.1176) time: 2.9340 data: 0.0083 max mem: 33300 +Epoch: [20] [1860/4276] eta: 2:01:40 lr: 2.6268996786262963e-05 loss: 0.1110 (0.1176) time: 2.9330 data: 0.0081 max mem: 33300 +Epoch: [20] [1870/4276] eta: 2:01:08 lr: 2.6266170761757025e-05 loss: 0.1064 (0.1176) time: 2.9354 data: 0.0078 max mem: 33300 +Epoch: [20] [1880/4276] eta: 2:00:37 lr: 2.626334470346657e-05 loss: 0.1083 (0.1176) time: 2.9380 data: 0.0081 max mem: 33300 +Epoch: [20] [1890/4276] eta: 2:00:06 lr: 2.626051861138715e-05 loss: 0.1103 (0.1176) time: 2.9377 data: 0.0082 max mem: 33300 +Epoch: [20] [1900/4276] eta: 1:59:35 lr: 2.6257692485514317e-05 loss: 0.1048 (0.1176) time: 2.9346 data: 0.0080 max mem: 33300 +Epoch: [20] [1910/4276] eta: 1:59:03 lr: 2.625486632584363e-05 loss: 0.1081 (0.1175) time: 2.9322 data: 0.0078 max mem: 33300 +Epoch: [20] [1920/4276] eta: 1:58:32 lr: 2.6252040132370648e-05 loss: 0.1100 (0.1175) time: 2.9432 data: 0.0080 max mem: 33300 +Epoch: [20] [1930/4276] eta: 1:58:01 lr: 2.6249213905090915e-05 loss: 0.1035 (0.1174) time: 2.9471 data: 0.0083 max mem: 33300 +Epoch: [20] [1940/4276] eta: 1:57:30 lr: 2.624638764399998e-05 loss: 0.1035 (0.1174) time: 2.9387 data: 0.0080 max mem: 33300 +Epoch: [20] [1950/4276] eta: 1:56:59 lr: 2.6243561349093398e-05 loss: 0.1222 (0.1175) time: 2.9389 data: 0.0082 max mem: 33300 +Epoch: [20] [1960/4276] eta: 1:56:28 lr: 2.6240735020366718e-05 loss: 0.1234 (0.1174) time: 2.9329 data: 0.0095 max mem: 33300 +Epoch: [20] [1970/4276] eta: 1:55:57 lr: 2.6237908657815497e-05 loss: 0.1025 (0.1174) time: 2.9383 data: 0.0096 max mem: 33300 +Epoch: [20] [1980/4276] eta: 1:55:26 lr: 2.6235082261435262e-05 loss: 0.1047 (0.1173) time: 2.9477 data: 0.0087 max mem: 33300 +Epoch: [20] [1990/4276] eta: 1:54:55 lr: 2.623225583122157e-05 loss: 0.1047 (0.1173) time: 2.9406 data: 0.0082 max mem: 33300 +Epoch: [20] [2000/4276] eta: 1:54:24 lr: 2.622942936716996e-05 loss: 0.1118 (0.1173) time: 2.9372 data: 0.0082 max mem: 33300 +Epoch: [20] [2010/4276] eta: 1:53:52 lr: 2.622660286927599e-05 loss: 0.1144 (0.1172) time: 2.9381 data: 0.0083 max mem: 33300 +Epoch: [20] [2020/4276] eta: 1:53:21 lr: 2.6223776337535185e-05 loss: 0.1164 (0.1172) time: 2.9397 data: 0.0080 max mem: 33300 +Epoch: [20] [2030/4276] eta: 1:52:51 lr: 2.6220949771943086e-05 loss: 0.1058 (0.1172) time: 2.9439 data: 0.0082 max mem: 33300 +Epoch: [20] [2040/4276] eta: 1:52:20 lr: 2.6218123172495246e-05 loss: 0.0929 (0.1170) time: 2.9381 data: 0.0088 max mem: 33300 +Epoch: [20] [2050/4276] eta: 1:51:49 lr: 2.6215296539187197e-05 loss: 0.0967 (0.1170) time: 2.9377 data: 0.0090 max mem: 33300 +Epoch: [20] [2060/4276] eta: 1:51:18 lr: 2.6212469872014472e-05 loss: 0.1014 (0.1170) time: 2.9424 data: 0.0084 max mem: 33300 +Epoch: [20] [2070/4276] eta: 1:50:54 lr: 2.620964317097262e-05 loss: 0.1022 (0.1169) time: 3.2788 data: 0.0078 max mem: 33300 +Epoch: [20] [2080/4276] eta: 1:50:29 lr: 2.6206816436057164e-05 loss: 0.1024 (0.1170) time: 3.5440 data: 0.0073 max mem: 33300 +Epoch: [20] [2090/4276] eta: 1:49:58 lr: 2.6203989667263647e-05 loss: 0.1058 (0.1169) time: 3.2051 data: 0.0075 max mem: 33300 +Epoch: [20] [2100/4276] eta: 1:49:27 lr: 2.6201162864587592e-05 loss: 0.1097 (0.1169) time: 2.9388 data: 0.0078 max mem: 33300 +Epoch: [20] [2110/4276] eta: 1:48:56 lr: 2.619833602802454e-05 loss: 0.1206 (0.1169) time: 2.9381 data: 0.0079 max mem: 33300 +Epoch: [20] [2120/4276] eta: 1:48:25 lr: 2.619550915757002e-05 loss: 0.0914 (0.1168) time: 2.9431 data: 0.0079 max mem: 33300 +Epoch: [20] [2130/4276] eta: 1:47:54 lr: 2.619268225321956e-05 loss: 0.0856 (0.1167) time: 2.9465 data: 0.0077 max mem: 33300 +Epoch: [20] [2140/4276] eta: 1:47:23 lr: 2.6189855314968688e-05 loss: 0.0997 (0.1166) time: 2.9482 data: 0.0075 max mem: 33300 +Epoch: [20] [2150/4276] eta: 1:46:52 lr: 2.6187028342812935e-05 loss: 0.0997 (0.1166) time: 2.9512 data: 0.0073 max mem: 33300 +Epoch: [20] [2160/4276] eta: 1:46:21 lr: 2.6184201336747833e-05 loss: 0.0987 (0.1165) time: 2.9530 data: 0.0073 max mem: 33300 +Epoch: [20] [2170/4276] eta: 1:45:51 lr: 2.618137429676889e-05 loss: 0.1130 (0.1166) time: 2.9537 data: 0.0075 max mem: 33300 +Epoch: [20] [2180/4276] eta: 1:45:20 lr: 2.617854722287164e-05 loss: 0.1134 (0.1166) time: 2.9489 data: 0.0073 max mem: 33300 +Epoch: [20] [2190/4276] eta: 1:44:49 lr: 2.617572011505161e-05 loss: 0.1080 (0.1167) time: 2.9407 data: 0.0072 max mem: 33300 +Epoch: [20] [2200/4276] eta: 1:44:18 lr: 2.6172892973304326e-05 loss: 0.1175 (0.1167) time: 2.9387 data: 0.0071 max mem: 33300 +Epoch: [20] [2210/4276] eta: 1:43:47 lr: 2.6170065797625288e-05 loss: 0.1252 (0.1168) time: 2.9407 data: 0.0072 max mem: 33300 +Epoch: [20] [2220/4276] eta: 1:43:16 lr: 2.6167238588010035e-05 loss: 0.1231 (0.1168) time: 2.9437 data: 0.0072 max mem: 33300 +Epoch: [20] [2230/4276] eta: 1:42:46 lr: 2.6164411344454076e-05 loss: 0.1092 (0.1168) time: 2.9466 data: 0.0071 max mem: 33300 +Epoch: [20] [2240/4276] eta: 1:42:15 lr: 2.6161584066952937e-05 loss: 0.1077 (0.1168) time: 2.9505 data: 0.0074 max mem: 33300 +Epoch: [20] [2250/4276] eta: 1:41:44 lr: 2.6158756755502127e-05 loss: 0.1026 (0.1168) time: 2.9548 data: 0.0076 max mem: 33300 +Epoch: [20] [2260/4276] eta: 1:41:14 lr: 2.615592941009716e-05 loss: 0.1027 (0.1168) time: 2.9547 data: 0.0076 max mem: 33300 +Epoch: [20] [2270/4276] eta: 1:40:43 lr: 2.6153102030733555e-05 loss: 0.1085 (0.1167) time: 2.9507 data: 0.0076 max mem: 33300 +Epoch: [20] [2280/4276] eta: 1:40:12 lr: 2.6150274617406826e-05 loss: 0.1117 (0.1168) time: 2.9528 data: 0.0077 max mem: 33300 +Epoch: [20] [2290/4276] eta: 1:39:42 lr: 2.6147447170112478e-05 loss: 0.1153 (0.1168) time: 2.9555 data: 0.0076 max mem: 33300 +Epoch: [20] [2300/4276] eta: 1:39:11 lr: 2.614461968884603e-05 loss: 0.1153 (0.1168) time: 2.9551 data: 0.0078 max mem: 33300 +Epoch: [20] [2310/4276] eta: 1:38:40 lr: 2.614179217360298e-05 loss: 0.1180 (0.1169) time: 2.9545 data: 0.0079 max mem: 33300 +Epoch: [20] [2320/4276] eta: 1:38:10 lr: 2.6138964624378854e-05 loss: 0.1180 (0.1169) time: 2.9551 data: 0.0079 max mem: 33300 +Epoch: [20] [2330/4276] eta: 1:37:39 lr: 2.613613704116914e-05 loss: 0.1185 (0.1169) time: 2.9581 data: 0.0079 max mem: 33300 +Epoch: [20] [2340/4276] eta: 1:37:09 lr: 2.613330942396935e-05 loss: 0.1175 (0.1169) time: 2.9553 data: 0.0077 max mem: 33300 +Epoch: [20] [2350/4276] eta: 1:36:38 lr: 2.6130481772774996e-05 loss: 0.1084 (0.1169) time: 2.9516 data: 0.0077 max mem: 33300 +Epoch: [20] [2360/4276] eta: 1:36:08 lr: 2.6127654087581582e-05 loss: 0.1084 (0.1169) time: 2.9517 data: 0.0079 max mem: 33300 +Epoch: [20] [2370/4276] eta: 1:35:37 lr: 2.6124826368384602e-05 loss: 0.1194 (0.1169) time: 2.9534 data: 0.0082 max mem: 33300 +Epoch: [20] [2380/4276] eta: 1:35:06 lr: 2.612199861517956e-05 loss: 0.1194 (0.1170) time: 2.9548 data: 0.0084 max mem: 33300 +Epoch: [20] [2390/4276] eta: 1:34:36 lr: 2.6119170827961963e-05 loss: 0.1167 (0.1170) time: 2.9535 data: 0.0082 max mem: 33300 +Epoch: [20] [2400/4276] eta: 1:34:05 lr: 2.6116343006727302e-05 loss: 0.1232 (0.1171) time: 2.9383 data: 0.0080 max mem: 33300 +Epoch: [20] [2410/4276] eta: 1:33:35 lr: 2.6113515151471074e-05 loss: 0.1210 (0.1171) time: 2.9334 data: 0.0082 max mem: 33300 +Epoch: [20] [2420/4276] eta: 1:33:04 lr: 2.611068726218878e-05 loss: 0.1129 (0.1170) time: 2.9465 data: 0.0083 max mem: 33300 +Epoch: [20] [2430/4276] eta: 1:32:34 lr: 2.610785933887593e-05 loss: 0.1129 (0.1171) time: 2.9652 data: 0.0082 max mem: 33300 +Epoch: [20] [2440/4276] eta: 1:32:03 lr: 2.6105031381527993e-05 loss: 0.1094 (0.1171) time: 2.9869 data: 0.0074 max mem: 33300 +Epoch: [20] [2450/4276] eta: 1:31:33 lr: 2.610220339014048e-05 loss: 0.1029 (0.1170) time: 2.9937 data: 0.0068 max mem: 33300 +Epoch: [20] [2460/4276] eta: 1:31:03 lr: 2.609937536470887e-05 loss: 0.1289 (0.1171) time: 2.9554 data: 0.0069 max mem: 33300 +Epoch: [20] [2470/4276] eta: 1:30:32 lr: 2.6096547305228673e-05 loss: 0.1365 (0.1172) time: 2.9145 data: 0.0077 max mem: 33300 +Epoch: [20] [2480/4276] eta: 1:30:01 lr: 2.6093719211695366e-05 loss: 0.1250 (0.1172) time: 2.9102 data: 0.0084 max mem: 33300 +Epoch: [20] [2490/4276] eta: 1:29:30 lr: 2.6090891084104436e-05 loss: 0.1221 (0.1173) time: 2.9229 data: 0.0081 max mem: 33300 +Epoch: [20] [2500/4276] eta: 1:29:00 lr: 2.608806292245138e-05 loss: 0.1248 (0.1173) time: 2.9409 data: 0.0079 max mem: 33300 +Epoch: [20] [2510/4276] eta: 1:28:30 lr: 2.6085234726731682e-05 loss: 0.1231 (0.1173) time: 2.9950 data: 0.0081 max mem: 33300 +Epoch: [20] [2520/4276] eta: 1:28:00 lr: 2.608240649694082e-05 loss: 0.1005 (0.1172) time: 3.0628 data: 0.0082 max mem: 33300 +Epoch: [20] [2530/4276] eta: 1:27:31 lr: 2.6079578233074285e-05 loss: 0.0966 (0.1172) time: 3.0840 data: 0.0082 max mem: 33300 +Epoch: [20] [2540/4276] eta: 1:27:01 lr: 2.6076749935127563e-05 loss: 0.0976 (0.1172) time: 3.0870 data: 0.0086 max mem: 33300 +Epoch: [20] [2550/4276] eta: 1:26:32 lr: 2.6073921603096134e-05 loss: 0.1046 (0.1171) time: 3.0847 data: 0.0087 max mem: 33300 +Epoch: [20] [2560/4276] eta: 1:26:02 lr: 2.6071093236975474e-05 loss: 0.0953 (0.1171) time: 3.0588 data: 0.0086 max mem: 33300 +Epoch: [20] [2570/4276] eta: 1:25:32 lr: 2.606826483676107e-05 loss: 0.0958 (0.1170) time: 3.0627 data: 0.0087 max mem: 33300 +Epoch: [20] [2580/4276] eta: 1:25:03 lr: 2.6065436402448394e-05 loss: 0.1043 (0.1170) time: 3.0893 data: 0.0086 max mem: 33300 +Epoch: [20] [2590/4276] eta: 1:24:33 lr: 2.6062607934032934e-05 loss: 0.1137 (0.1170) time: 3.0951 data: 0.0086 max mem: 33300 +Epoch: [20] [2600/4276] eta: 1:24:04 lr: 2.605977943151015e-05 loss: 0.1030 (0.1169) time: 3.0946 data: 0.0087 max mem: 33300 +Epoch: [20] [2610/4276] eta: 1:23:34 lr: 2.605695089487553e-05 loss: 0.1030 (0.1169) time: 3.0879 data: 0.0086 max mem: 33300 +Epoch: [20] [2620/4276] eta: 1:23:05 lr: 2.6054122324124545e-05 loss: 0.1068 (0.1169) time: 3.0834 data: 0.0085 max mem: 33300 +Epoch: [20] [2630/4276] eta: 1:22:35 lr: 2.6051293719252674e-05 loss: 0.1047 (0.1168) time: 3.0576 data: 0.0086 max mem: 33300 +Epoch: [20] [2640/4276] eta: 1:22:05 lr: 2.604846508025538e-05 loss: 0.1018 (0.1168) time: 3.0522 data: 0.0087 max mem: 33300 +Epoch: [20] [2650/4276] eta: 1:21:35 lr: 2.6045636407128133e-05 loss: 0.1014 (0.1168) time: 3.0500 data: 0.0085 max mem: 33300 +Epoch: [20] [2660/4276] eta: 1:21:05 lr: 2.604280769986641e-05 loss: 0.1014 (0.1168) time: 3.0296 data: 0.0087 max mem: 33300 +Epoch: [20] [2670/4276] eta: 1:20:35 lr: 2.6039978958465676e-05 loss: 0.1180 (0.1168) time: 3.0378 data: 0.0089 max mem: 33300 +Epoch: [20] [2680/4276] eta: 1:20:05 lr: 2.6037150182921395e-05 loss: 0.1213 (0.1168) time: 3.0681 data: 0.0085 max mem: 33300 +Epoch: [20] [2690/4276] eta: 1:19:36 lr: 2.6034321373229035e-05 loss: 0.1132 (0.1168) time: 3.0887 data: 0.0085 max mem: 33300 +Epoch: [20] [2700/4276] eta: 1:19:06 lr: 2.603149252938407e-05 loss: 0.1013 (0.1168) time: 3.0855 data: 0.0085 max mem: 33300 +Epoch: [20] [2710/4276] eta: 1:18:36 lr: 2.6028663651381946e-05 loss: 0.1023 (0.1167) time: 3.0793 data: 0.0077 max mem: 33300 +Epoch: [20] [2720/4276] eta: 1:18:06 lr: 2.6025834739218142e-05 loss: 0.0954 (0.1167) time: 3.0773 data: 0.0073 max mem: 33300 +Epoch: [20] [2730/4276] eta: 1:17:37 lr: 2.602300579288811e-05 loss: 0.1100 (0.1167) time: 3.0721 data: 0.0077 max mem: 33300 +Epoch: [20] [2740/4276] eta: 1:17:07 lr: 2.6020176812387314e-05 loss: 0.1105 (0.1167) time: 3.0450 data: 0.0083 max mem: 33300 +Epoch: [20] [2750/4276] eta: 1:16:37 lr: 2.6017347797711216e-05 loss: 0.1137 (0.1168) time: 3.0246 data: 0.0086 max mem: 33300 +Epoch: [20] [2760/4276] eta: 1:16:06 lr: 2.6014518748855265e-05 loss: 0.1117 (0.1168) time: 3.0261 data: 0.0088 max mem: 33300 +Epoch: [20] [2770/4276] eta: 1:15:36 lr: 2.6011689665814924e-05 loss: 0.1071 (0.1168) time: 3.0256 data: 0.0090 max mem: 33300 +Epoch: [20] [2780/4276] eta: 1:15:07 lr: 2.6008860548585657e-05 loss: 0.1058 (0.1168) time: 3.0368 data: 0.0091 max mem: 33300 +Epoch: [20] [2790/4276] eta: 1:14:37 lr: 2.6006031397162906e-05 loss: 0.1111 (0.1168) time: 3.0620 data: 0.0092 max mem: 33300 +Epoch: [20] [2800/4276] eta: 1:14:07 lr: 2.6003202211542122e-05 loss: 0.1087 (0.1167) time: 3.0851 data: 0.0090 max mem: 33300 +Epoch: [20] [2810/4276] eta: 1:13:37 lr: 2.6000372991718768e-05 loss: 0.0868 (0.1166) time: 3.0728 data: 0.0085 max mem: 33300 +Epoch: [20] [2820/4276] eta: 1:13:07 lr: 2.5997543737688296e-05 loss: 0.0946 (0.1166) time: 3.0710 data: 0.0090 max mem: 33300 +Epoch: [20] [2830/4276] eta: 1:12:38 lr: 2.5994714449446146e-05 loss: 0.1014 (0.1166) time: 3.0954 data: 0.0098 max mem: 33300 +Epoch: [20] [2840/4276] eta: 1:12:08 lr: 2.599188512698777e-05 loss: 0.1263 (0.1166) time: 3.0948 data: 0.0099 max mem: 33300 +Epoch: [20] [2850/4276] eta: 1:11:38 lr: 2.5989055770308617e-05 loss: 0.1317 (0.1166) time: 3.0910 data: 0.0094 max mem: 33300 +Epoch: [20] [2860/4276] eta: 1:11:08 lr: 2.5986226379404143e-05 loss: 0.1170 (0.1166) time: 3.0915 data: 0.0092 max mem: 33300 +Epoch: [20] [2870/4276] eta: 1:10:39 lr: 2.598339695426978e-05 loss: 0.0989 (0.1166) time: 3.0894 data: 0.0099 max mem: 33300 +Epoch: [20] [2880/4276] eta: 1:10:09 lr: 2.5980567494900974e-05 loss: 0.1071 (0.1166) time: 3.0913 data: 0.0102 max mem: 33300 +Epoch: [20] [2890/4276] eta: 1:09:39 lr: 2.5977738001293173e-05 loss: 0.1078 (0.1165) time: 3.0989 data: 0.0100 max mem: 33300 +Epoch: [20] [2900/4276] eta: 1:09:09 lr: 2.5974908473441818e-05 loss: 0.1104 (0.1165) time: 3.1014 data: 0.0097 max mem: 33300 +Epoch: [20] [2910/4276] eta: 1:08:40 lr: 2.5972078911342346e-05 loss: 0.1160 (0.1165) time: 3.1002 data: 0.0098 max mem: 33300 +Epoch: [20] [2920/4276] eta: 1:08:10 lr: 2.5969249314990197e-05 loss: 0.1168 (0.1165) time: 3.0892 data: 0.0096 max mem: 33300 +Epoch: [20] [2930/4276] eta: 1:07:39 lr: 2.596641968438081e-05 loss: 0.1043 (0.1165) time: 3.0397 data: 0.0086 max mem: 33300 +Epoch: [20] [2940/4276] eta: 1:07:09 lr: 2.596359001950963e-05 loss: 0.0967 (0.1165) time: 3.0105 data: 0.0089 max mem: 33300 +Epoch: [20] [2950/4276] eta: 1:06:39 lr: 2.5960760320372084e-05 loss: 0.0993 (0.1165) time: 3.0194 data: 0.0096 max mem: 33300 +Epoch: [20] [2960/4276] eta: 1:06:09 lr: 2.5957930586963607e-05 loss: 0.1044 (0.1165) time: 2.9995 data: 0.0088 max mem: 33300 +Epoch: [20] [2970/4276] eta: 1:05:39 lr: 2.5955100819279643e-05 loss: 0.1124 (0.1165) time: 2.9862 data: 0.0084 max mem: 33300 +Epoch: [20] [2980/4276] eta: 1:05:08 lr: 2.595227101731561e-05 loss: 0.1192 (0.1165) time: 2.9846 data: 0.0085 max mem: 33300 +Epoch: [20] [2990/4276] eta: 1:04:38 lr: 2.5949441181066948e-05 loss: 0.1082 (0.1165) time: 2.9586 data: 0.0081 max mem: 33300 +Epoch: [20] [3000/4276] eta: 1:04:07 lr: 2.5946611310529085e-05 loss: 0.1039 (0.1165) time: 2.9378 data: 0.0084 max mem: 33300 +Epoch: [20] [3010/4276] eta: 1:03:37 lr: 2.594378140569746e-05 loss: 0.1051 (0.1164) time: 2.9363 data: 0.0086 max mem: 33300 +Epoch: [20] [3020/4276] eta: 1:03:06 lr: 2.5940951466567483e-05 loss: 0.1073 (0.1164) time: 2.9214 data: 0.0085 max mem: 33300 +Epoch: [20] [3030/4276] eta: 1:02:36 lr: 2.5938121493134588e-05 loss: 0.1115 (0.1164) time: 2.9032 data: 0.0086 max mem: 33300 +Epoch: [20] [3040/4276] eta: 1:02:05 lr: 2.5935291485394203e-05 loss: 0.1222 (0.1164) time: 2.9005 data: 0.0088 max mem: 33300 +Epoch: [20] [3050/4276] eta: 1:01:34 lr: 2.593246144334176e-05 loss: 0.1208 (0.1164) time: 2.9168 data: 0.0089 max mem: 33300 +Epoch: [20] [3060/4276] eta: 1:01:04 lr: 2.592963136697267e-05 loss: 0.1007 (0.1164) time: 2.9387 data: 0.0086 max mem: 33300 +Epoch: [20] [3070/4276] eta: 1:00:34 lr: 2.592680125628235e-05 loss: 0.1011 (0.1164) time: 2.9440 data: 0.0085 max mem: 33300 +Epoch: [20] [3080/4276] eta: 1:00:03 lr: 2.5923971111266236e-05 loss: 0.1252 (0.1164) time: 2.9459 data: 0.0087 max mem: 33300 +Epoch: [20] [3090/4276] eta: 0:59:33 lr: 2.592114093191975e-05 loss: 0.1097 (0.1164) time: 2.9449 data: 0.0087 max mem: 33300 +Epoch: [20] [3100/4276] eta: 0:59:02 lr: 2.5918310718238297e-05 loss: 0.1053 (0.1163) time: 2.9396 data: 0.0085 max mem: 33300 +Epoch: [20] [3110/4276] eta: 0:58:32 lr: 2.59154804702173e-05 loss: 0.1068 (0.1163) time: 2.9373 data: 0.0085 max mem: 33300 +Epoch: [20] [3120/4276] eta: 0:58:02 lr: 2.5912650187852172e-05 loss: 0.1106 (0.1163) time: 2.9402 data: 0.0087 max mem: 33300 +Epoch: [20] [3130/4276] eta: 0:57:31 lr: 2.5909819871138342e-05 loss: 0.1152 (0.1163) time: 2.9430 data: 0.0087 max mem: 33300 +Epoch: [20] [3140/4276] eta: 0:57:01 lr: 2.5906989520071207e-05 loss: 0.1152 (0.1163) time: 2.9420 data: 0.0085 max mem: 33300 +Epoch: [20] [3150/4276] eta: 0:56:31 lr: 2.5904159134646183e-05 loss: 0.1174 (0.1163) time: 2.9404 data: 0.0085 max mem: 33300 +Epoch: [20] [3160/4276] eta: 0:56:00 lr: 2.5901328714858686e-05 loss: 0.1148 (0.1163) time: 2.9340 data: 0.0090 max mem: 33300 +Epoch: [20] [3170/4276] eta: 0:55:30 lr: 2.5898498260704135e-05 loss: 0.1148 (0.1163) time: 2.9310 data: 0.0092 max mem: 33300 +Epoch: [20] [3180/4276] eta: 0:54:59 lr: 2.589566777217792e-05 loss: 0.1153 (0.1163) time: 2.9338 data: 0.0085 max mem: 33300 +Epoch: [20] [3190/4276] eta: 0:54:29 lr: 2.589283724927546e-05 loss: 0.1176 (0.1163) time: 2.9337 data: 0.0077 max mem: 33300 +Epoch: [20] [3200/4276] eta: 0:53:59 lr: 2.5890006691992163e-05 loss: 0.1183 (0.1163) time: 2.9370 data: 0.0075 max mem: 33300 +Epoch: [20] [3210/4276] eta: 0:53:28 lr: 2.5887176100323436e-05 loss: 0.1220 (0.1164) time: 2.9386 data: 0.0075 max mem: 33300 +Epoch: [20] [3220/4276] eta: 0:52:58 lr: 2.5884345474264676e-05 loss: 0.1301 (0.1164) time: 2.9380 data: 0.0074 max mem: 33300 +Epoch: [20] [3230/4276] eta: 0:52:28 lr: 2.5881514813811293e-05 loss: 0.1099 (0.1164) time: 2.9383 data: 0.0072 max mem: 33300 +Epoch: [20] [3240/4276] eta: 0:51:57 lr: 2.587868411895868e-05 loss: 0.1128 (0.1164) time: 2.9369 data: 0.0072 max mem: 33300 +Epoch: [20] [3250/4276] eta: 0:51:27 lr: 2.587585338970226e-05 loss: 0.1194 (0.1164) time: 2.9365 data: 0.0071 max mem: 33300 +Epoch: [20] [3260/4276] eta: 0:50:57 lr: 2.58730226260374e-05 loss: 0.1160 (0.1164) time: 2.9373 data: 0.0070 max mem: 33300 +Epoch: [20] [3270/4276] eta: 0:50:26 lr: 2.5870191827959528e-05 loss: 0.1135 (0.1164) time: 2.9363 data: 0.0071 max mem: 33300 +Epoch: [20] [3280/4276] eta: 0:49:56 lr: 2.5867360995464036e-05 loss: 0.1118 (0.1165) time: 2.9369 data: 0.0071 max mem: 33300 +Epoch: [20] [3290/4276] eta: 0:49:26 lr: 2.58645301285463e-05 loss: 0.1201 (0.1165) time: 2.9393 data: 0.0071 max mem: 33300 +Epoch: [20] [3300/4276] eta: 0:48:55 lr: 2.5861699227201735e-05 loss: 0.1223 (0.1165) time: 2.9382 data: 0.0071 max mem: 33300 +Epoch: [20] [3310/4276] eta: 0:48:25 lr: 2.585886829142573e-05 loss: 0.1255 (0.1166) time: 2.9369 data: 0.0071 max mem: 33300 +Epoch: [20] [3320/4276] eta: 0:47:55 lr: 2.5856037321213683e-05 loss: 0.1255 (0.1166) time: 2.9369 data: 0.0071 max mem: 33300 +Epoch: [20] [3330/4276] eta: 0:47:25 lr: 2.585320631656098e-05 loss: 0.1130 (0.1166) time: 2.9389 data: 0.0071 max mem: 33300 +Epoch: [20] [3340/4276] eta: 0:46:54 lr: 2.5850375277463007e-05 loss: 0.1054 (0.1166) time: 2.9382 data: 0.0071 max mem: 33300 +Epoch: [20] [3350/4276] eta: 0:46:24 lr: 2.584754420391516e-05 loss: 0.1050 (0.1165) time: 2.9359 data: 0.0071 max mem: 33300 +Epoch: [20] [3360/4276] eta: 0:45:54 lr: 2.5844713095912826e-05 loss: 0.1052 (0.1165) time: 2.9357 data: 0.0072 max mem: 33300 +Epoch: [20] [3370/4276] eta: 0:45:24 lr: 2.584188195345139e-05 loss: 0.1208 (0.1165) time: 2.9366 data: 0.0074 max mem: 33300 +Epoch: [20] [3380/4276] eta: 0:44:53 lr: 2.583905077652624e-05 loss: 0.1208 (0.1165) time: 2.9338 data: 0.0073 max mem: 33300 +Epoch: [20] [3390/4276] eta: 0:44:23 lr: 2.5836219565132756e-05 loss: 0.1167 (0.1165) time: 2.9252 data: 0.0071 max mem: 33300 +Epoch: [20] [3400/4276] eta: 0:43:53 lr: 2.5833388319266338e-05 loss: 0.1161 (0.1165) time: 2.9281 data: 0.0072 max mem: 33300 +Epoch: [20] [3410/4276] eta: 0:43:22 lr: 2.583055703892235e-05 loss: 0.1177 (0.1166) time: 2.9320 data: 0.0074 max mem: 33300 +Epoch: [20] [3420/4276] eta: 0:42:52 lr: 2.582772572409617e-05 loss: 0.1179 (0.1166) time: 2.9264 data: 0.0075 max mem: 33300 +Epoch: [20] [3430/4276] eta: 0:42:23 lr: 2.5824894374783193e-05 loss: 0.1179 (0.1166) time: 3.1135 data: 0.0075 max mem: 33300 +Epoch: [20] [3440/4276] eta: 0:41:54 lr: 2.5822062990978794e-05 loss: 0.1029 (0.1166) time: 3.2954 data: 0.0072 max mem: 33300 +Epoch: [20] [3450/4276] eta: 0:41:23 lr: 2.5819231572678342e-05 loss: 0.1087 (0.1166) time: 3.1110 data: 0.0071 max mem: 33300 +Epoch: [20] [3460/4276] eta: 0:40:53 lr: 2.581640011987722e-05 loss: 0.1178 (0.1166) time: 2.9339 data: 0.0074 max mem: 33300 +Epoch: [20] [3470/4276] eta: 0:40:23 lr: 2.5813568632570807e-05 loss: 0.1070 (0.1166) time: 2.9376 data: 0.0074 max mem: 33300 +Epoch: [20] [3480/4276] eta: 0:39:53 lr: 2.581073711075447e-05 loss: 0.1117 (0.1166) time: 2.9381 data: 0.0071 max mem: 33300 +Epoch: [20] [3490/4276] eta: 0:39:22 lr: 2.5807905554423584e-05 loss: 0.1097 (0.1166) time: 2.9346 data: 0.0071 max mem: 33300 +Epoch: [20] [3500/4276] eta: 0:38:52 lr: 2.5805073963573518e-05 loss: 0.1076 (0.1166) time: 2.9356 data: 0.0071 max mem: 33300 +Epoch: [20] [3510/4276] eta: 0:38:22 lr: 2.5802242338199646e-05 loss: 0.1016 (0.1166) time: 2.9399 data: 0.0071 max mem: 33300 +Epoch: [20] [3520/4276] eta: 0:37:52 lr: 2.5799410678297343e-05 loss: 0.1016 (0.1165) time: 2.9408 data: 0.0072 max mem: 33300 +Epoch: [20] [3530/4276] eta: 0:37:22 lr: 2.5796578983861965e-05 loss: 0.1065 (0.1165) time: 2.9379 data: 0.0073 max mem: 33300 +Epoch: [20] [3540/4276] eta: 0:36:51 lr: 2.579374725488888e-05 loss: 0.1168 (0.1165) time: 2.9367 data: 0.0072 max mem: 33300 +Epoch: [20] [3550/4276] eta: 0:36:21 lr: 2.5790915491373457e-05 loss: 0.1090 (0.1165) time: 2.9401 data: 0.0071 max mem: 33300 +Epoch: [20] [3560/4276] eta: 0:35:51 lr: 2.578808369331107e-05 loss: 0.1090 (0.1166) time: 3.0429 data: 0.0071 max mem: 33300 +Epoch: [20] [3570/4276] eta: 0:35:21 lr: 2.5785251860697067e-05 loss: 0.1265 (0.1166) time: 3.0360 data: 0.0072 max mem: 33300 +Epoch: [20] [3580/4276] eta: 0:34:51 lr: 2.5782419993526826e-05 loss: 0.1110 (0.1166) time: 2.9286 data: 0.0071 max mem: 33300 +Epoch: [20] [3590/4276] eta: 0:34:21 lr: 2.577958809179569e-05 loss: 0.1031 (0.1166) time: 2.9227 data: 0.0073 max mem: 33300 +Epoch: [20] [3600/4276] eta: 0:33:51 lr: 2.5776756155499033e-05 loss: 0.1124 (0.1166) time: 2.9156 data: 0.0081 max mem: 33300 +Epoch: [20] [3610/4276] eta: 0:33:20 lr: 2.5773924184632203e-05 loss: 0.1103 (0.1166) time: 2.9046 data: 0.0091 max mem: 33300 +Epoch: [20] [3620/4276] eta: 0:32:50 lr: 2.5771092179190565e-05 loss: 0.1103 (0.1165) time: 2.9136 data: 0.0089 max mem: 33300 +Epoch: [20] [3630/4276] eta: 0:32:20 lr: 2.5768260139169474e-05 loss: 0.1101 (0.1165) time: 2.9369 data: 0.0082 max mem: 33300 +Epoch: [20] [3640/4276] eta: 0:31:50 lr: 2.576542806456428e-05 loss: 0.1086 (0.1165) time: 2.9469 data: 0.0083 max mem: 33300 +Epoch: [20] [3650/4276] eta: 0:31:20 lr: 2.5762595955370338e-05 loss: 0.1086 (0.1165) time: 2.9425 data: 0.0087 max mem: 33300 +Epoch: [20] [3660/4276] eta: 0:30:50 lr: 2.575976381158301e-05 loss: 0.1100 (0.1165) time: 2.9359 data: 0.0085 max mem: 33300 +Epoch: [20] [3670/4276] eta: 0:30:19 lr: 2.575693163319764e-05 loss: 0.1024 (0.1164) time: 2.9354 data: 0.0085 max mem: 33300 +Epoch: [20] [3680/4276] eta: 0:29:49 lr: 2.5754099420209578e-05 loss: 0.1015 (0.1164) time: 2.9354 data: 0.0087 max mem: 33300 +Epoch: [20] [3690/4276] eta: 0:29:19 lr: 2.575126717261417e-05 loss: 0.1140 (0.1164) time: 2.9380 data: 0.0087 max mem: 33300 +Epoch: [20] [3700/4276] eta: 0:28:49 lr: 2.5748434890406766e-05 loss: 0.1153 (0.1164) time: 2.9382 data: 0.0085 max mem: 33300 +Epoch: [20] [3710/4276] eta: 0:28:19 lr: 2.5745602573582718e-05 loss: 0.1005 (0.1164) time: 2.9389 data: 0.0086 max mem: 33300 +Epoch: [20] [3720/4276] eta: 0:27:49 lr: 2.5742770222137363e-05 loss: 0.0937 (0.1164) time: 2.9399 data: 0.0088 max mem: 33300 +Epoch: [20] [3730/4276] eta: 0:27:19 lr: 2.573993783606605e-05 loss: 0.1164 (0.1164) time: 2.9405 data: 0.0087 max mem: 33300 +Epoch: [20] [3740/4276] eta: 0:26:49 lr: 2.5737105415364125e-05 loss: 0.1158 (0.1164) time: 2.9398 data: 0.0085 max mem: 33300 +Epoch: [20] [3750/4276] eta: 0:26:18 lr: 2.5734272960026934e-05 loss: 0.1129 (0.1164) time: 2.9382 data: 0.0085 max mem: 33300 +Epoch: [20] [3760/4276] eta: 0:25:48 lr: 2.57314404700498e-05 loss: 0.1073 (0.1163) time: 2.9133 data: 0.0085 max mem: 33300 +Epoch: [20] [3770/4276] eta: 0:25:18 lr: 2.5728607945428074e-05 loss: 0.0995 (0.1163) time: 2.8944 data: 0.0085 max mem: 33300 +Epoch: [20] [3780/4276] eta: 0:24:48 lr: 2.572577538615709e-05 loss: 0.1061 (0.1163) time: 2.9189 data: 0.0082 max mem: 33300 +Epoch: [20] [3790/4276] eta: 0:24:18 lr: 2.5722942792232198e-05 loss: 0.1055 (0.1163) time: 2.9408 data: 0.0080 max mem: 33300 +Epoch: [20] [3800/4276] eta: 0:23:48 lr: 2.5720110163648716e-05 loss: 0.1034 (0.1163) time: 2.9394 data: 0.0080 max mem: 33300 +Epoch: [20] [3810/4276] eta: 0:23:18 lr: 2.571727750040199e-05 loss: 0.1044 (0.1163) time: 2.9340 data: 0.0080 max mem: 33300 +Epoch: [20] [3820/4276] eta: 0:22:48 lr: 2.571444480248734e-05 loss: 0.0975 (0.1162) time: 2.9334 data: 0.0083 max mem: 33300 +Epoch: [20] [3830/4276] eta: 0:22:18 lr: 2.571161206990012e-05 loss: 0.0952 (0.1162) time: 2.9360 data: 0.0081 max mem: 33300 +Epoch: [20] [3840/4276] eta: 0:21:48 lr: 2.570877930263565e-05 loss: 0.1076 (0.1162) time: 2.9361 data: 0.0079 max mem: 33300 +Epoch: [20] [3850/4276] eta: 0:21:17 lr: 2.570594650068925e-05 loss: 0.0997 (0.1162) time: 2.9334 data: 0.0081 max mem: 33300 +Epoch: [20] [3860/4276] eta: 0:20:47 lr: 2.570311366405626e-05 loss: 0.1060 (0.1162) time: 2.9346 data: 0.0083 max mem: 33300 +Epoch: [20] [3870/4276] eta: 0:20:17 lr: 2.5700280792732014e-05 loss: 0.1091 (0.1161) time: 2.9360 data: 0.0081 max mem: 33300 +Epoch: [20] [3880/4276] eta: 0:19:47 lr: 2.5697447886711824e-05 loss: 0.1033 (0.1161) time: 2.9341 data: 0.0080 max mem: 33300 +Epoch: [20] [3890/4276] eta: 0:19:17 lr: 2.5694614945991018e-05 loss: 0.0957 (0.1161) time: 2.9278 data: 0.0085 max mem: 33300 +Epoch: [20] [3900/4276] eta: 0:18:47 lr: 2.5691781970564925e-05 loss: 0.1028 (0.1161) time: 2.9293 data: 0.0086 max mem: 33300 +Epoch: [20] [3910/4276] eta: 0:18:17 lr: 2.5688948960428865e-05 loss: 0.0987 (0.1160) time: 2.9343 data: 0.0081 max mem: 33300 +Epoch: [20] [3920/4276] eta: 0:17:47 lr: 2.5686115915578156e-05 loss: 0.0976 (0.1160) time: 2.9337 data: 0.0078 max mem: 33300 +Epoch: [20] [3930/4276] eta: 0:17:17 lr: 2.568328283600813e-05 loss: 0.0942 (0.1160) time: 2.9343 data: 0.0083 max mem: 33300 +Epoch: [20] [3940/4276] eta: 0:16:47 lr: 2.5680449721714094e-05 loss: 0.1070 (0.1160) time: 2.9343 data: 0.0087 max mem: 33300 +Epoch: [20] [3950/4276] eta: 0:16:17 lr: 2.5677616572691366e-05 loss: 0.1075 (0.1160) time: 2.9340 data: 0.0085 max mem: 33300 +Epoch: [20] [3960/4276] eta: 0:15:47 lr: 2.567478338893527e-05 loss: 0.1094 (0.1160) time: 2.9344 data: 0.0086 max mem: 33300 +Epoch: [20] [3970/4276] eta: 0:15:17 lr: 2.5671950170441112e-05 loss: 0.1281 (0.1160) time: 2.9349 data: 0.0086 max mem: 33300 +Epoch: [20] [3980/4276] eta: 0:14:47 lr: 2.566911691720422e-05 loss: 0.1134 (0.1160) time: 2.9349 data: 0.0084 max mem: 33300 +Epoch: [20] [3990/4276] eta: 0:14:17 lr: 2.5666283629219894e-05 loss: 0.1076 (0.1160) time: 2.9315 data: 0.0083 max mem: 33300 +Epoch: [20] [4000/4276] eta: 0:13:47 lr: 2.5663450306483448e-05 loss: 0.1023 (0.1160) time: 2.9322 data: 0.0083 max mem: 33300 +Epoch: [20] [4010/4276] eta: 0:13:17 lr: 2.56606169489902e-05 loss: 0.1001 (0.1160) time: 2.9355 data: 0.0083 max mem: 33300 +Epoch: [20] [4020/4276] eta: 0:12:47 lr: 2.565778355673546e-05 loss: 0.1030 (0.1160) time: 2.9364 data: 0.0083 max mem: 33300 +Epoch: [20] [4030/4276] eta: 0:12:17 lr: 2.565495012971452e-05 loss: 0.1044 (0.1160) time: 2.9375 data: 0.0081 max mem: 33300 +Epoch: [20] [4040/4276] eta: 0:11:47 lr: 2.5652116667922703e-05 loss: 0.1092 (0.1160) time: 2.9353 data: 0.0079 max mem: 33300 +Epoch: [20] [4050/4276] eta: 0:11:17 lr: 2.564928317135531e-05 loss: 0.1134 (0.1160) time: 2.9347 data: 0.0081 max mem: 33300 +Epoch: [20] [4060/4276] eta: 0:10:47 lr: 2.5646449640007646e-05 loss: 0.1093 (0.1160) time: 2.9350 data: 0.0083 max mem: 33300 +Epoch: [20] [4070/4276] eta: 0:10:17 lr: 2.5643616073875015e-05 loss: 0.1177 (0.1160) time: 2.9359 data: 0.0081 max mem: 33300 +Epoch: [20] [4080/4276] eta: 0:09:47 lr: 2.5640782472952712e-05 loss: 0.1215 (0.1161) time: 2.9384 data: 0.0081 max mem: 33300 +Epoch: [20] [4090/4276] eta: 0:09:17 lr: 2.563794883723604e-05 loss: 0.1267 (0.1161) time: 2.9435 data: 0.0083 max mem: 33300 +Epoch: [20] [4100/4276] eta: 0:08:47 lr: 2.5635115166720318e-05 loss: 0.1233 (0.1161) time: 2.9430 data: 0.0086 max mem: 33300 +Epoch: [20] [4110/4276] eta: 0:08:17 lr: 2.5632281461400815e-05 loss: 0.1197 (0.1161) time: 2.9374 data: 0.0084 max mem: 33300 +Epoch: [20] [4120/4276] eta: 0:07:47 lr: 2.562944772127285e-05 loss: 0.1142 (0.1161) time: 2.9364 data: 0.0084 max mem: 33300 +Epoch: [20] [4130/4276] eta: 0:07:17 lr: 2.5626613946331702e-05 loss: 0.1091 (0.1161) time: 2.9429 data: 0.0088 max mem: 33300 +Epoch: [20] [4140/4276] eta: 0:06:47 lr: 2.5623780136572684e-05 loss: 0.1070 (0.1161) time: 2.9436 data: 0.0087 max mem: 33300 +Epoch: [20] [4150/4276] eta: 0:06:17 lr: 2.5620946291991078e-05 loss: 0.1076 (0.1161) time: 2.9364 data: 0.0085 max mem: 33300 +Epoch: [20] [4160/4276] eta: 0:05:47 lr: 2.561811241258218e-05 loss: 0.1117 (0.1161) time: 2.9382 data: 0.0085 max mem: 33300 +Epoch: [20] [4170/4276] eta: 0:05:17 lr: 2.5615278498341272e-05 loss: 0.1262 (0.1161) time: 2.9496 data: 0.0088 max mem: 33300 +Epoch: [20] [4180/4276] eta: 0:04:47 lr: 2.5612444549263664e-05 loss: 0.1171 (0.1161) time: 2.9510 data: 0.0087 max mem: 33300 +Epoch: [20] [4190/4276] eta: 0:04:17 lr: 2.5609610565344626e-05 loss: 0.1159 (0.1162) time: 2.9406 data: 0.0086 max mem: 33300 +Epoch: [20] [4200/4276] eta: 0:03:47 lr: 2.5606776546579452e-05 loss: 0.1277 (0.1162) time: 2.9363 data: 0.0088 max mem: 33300 +Epoch: [20] [4210/4276] eta: 0:03:17 lr: 2.5603942492963433e-05 loss: 0.1289 (0.1162) time: 2.9354 data: 0.0089 max mem: 33300 +Epoch: [20] [4220/4276] eta: 0:02:47 lr: 2.5601108404491853e-05 loss: 0.1317 (0.1163) time: 2.9384 data: 0.0088 max mem: 33300 +Epoch: [20] [4230/4276] eta: 0:02:17 lr: 2.5598274281159984e-05 loss: 0.1302 (0.1163) time: 2.9371 data: 0.0086 max mem: 33300 +Epoch: [20] [4240/4276] eta: 0:01:47 lr: 2.559544012296312e-05 loss: 0.1263 (0.1163) time: 2.9328 data: 0.0085 max mem: 33300 +Epoch: [20] [4250/4276] eta: 0:01:17 lr: 2.5592605929896547e-05 loss: 0.1246 (0.1164) time: 2.9385 data: 0.0088 max mem: 33300 +Epoch: [20] [4260/4276] eta: 0:00:47 lr: 2.5589771701955527e-05 loss: 0.1118 (0.1164) time: 2.9396 data: 0.0087 max mem: 33300 +Epoch: [20] [4270/4276] eta: 0:00:17 lr: 2.5586937439135356e-05 loss: 0.1280 (0.1164) time: 2.9292 data: 0.0079 max mem: 33300 +Epoch: [20] Total time: 3:33:20 +Test: [ 0/21770] eta: 8:00:37 time: 1.3246 data: 1.2833 max mem: 33300 +Test: [ 100/21770] eta: 0:18:15 time: 0.0383 data: 0.0009 max mem: 33300 +Test: [ 200/21770] eta: 0:15:54 time: 0.0378 data: 0.0009 max mem: 33300 +Test: [ 300/21770] eta: 0:15:04 time: 0.0380 data: 0.0009 max mem: 33300 +Test: [ 400/21770] eta: 0:14:38 time: 0.0379 data: 0.0008 max mem: 33300 +Test: [ 500/21770] eta: 0:14:21 time: 0.0382 data: 0.0009 max mem: 33300 +Test: [ 600/21770] eta: 0:14:08 time: 0.0380 data: 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0:11:52 time: 0.0390 data: 0.0009 max mem: 33300 +Test: [ 3400/21770] eta: 0:11:49 time: 0.0391 data: 0.0009 max mem: 33300 +Test: [ 3500/21770] eta: 0:11:45 time: 0.0395 data: 0.0008 max mem: 33300 +Test: [ 3600/21770] eta: 0:11:42 time: 0.0395 data: 0.0008 max mem: 33300 +Test: [ 3700/21770] eta: 0:11:38 time: 0.0395 data: 0.0008 max mem: 33300 +Test: [ 3800/21770] eta: 0:11:35 time: 0.0392 data: 0.0008 max mem: 33300 +Test: [ 3900/21770] eta: 0:11:31 time: 0.0394 data: 0.0008 max mem: 33300 +Test: [ 4000/21770] eta: 0:11:27 time: 0.0390 data: 0.0009 max mem: 33300 +Test: [ 4100/21770] eta: 0:11:24 time: 0.0390 data: 0.0009 max mem: 33300 +Test: [ 4200/21770] eta: 0:11:20 time: 0.0391 data: 0.0009 max mem: 33300 +Test: [ 4300/21770] eta: 0:11:16 time: 0.0390 data: 0.0009 max mem: 33300 +Test: [ 4400/21770] eta: 0:11:12 time: 0.0389 data: 0.0009 max mem: 33300 +Test: [ 4500/21770] eta: 0:11:08 time: 0.0388 data: 0.0009 max mem: 33300 +Test: [ 4600/21770] eta: 0:11:05 time: 0.0384 data: 0.0009 max mem: 33300 +Test: [ 4700/21770] eta: 0:11:01 time: 0.0389 data: 0.0009 max mem: 33300 +Test: [ 4800/21770] eta: 0:10:57 time: 0.0386 data: 0.0009 max mem: 33300 +Test: [ 4900/21770] eta: 0:10:53 time: 0.0388 data: 0.0008 max mem: 33300 +Test: [ 5000/21770] eta: 0:10:49 time: 0.0389 data: 0.0009 max mem: 33300 +Test: [ 5100/21770] eta: 0:10:45 time: 0.0387 data: 0.0008 max mem: 33300 +Test: [ 5200/21770] eta: 0:10:41 time: 0.0389 data: 0.0009 max mem: 33300 +Test: [ 5300/21770] eta: 0:10:38 time: 0.0388 data: 0.0009 max mem: 33300 +Test: [ 5400/21770] eta: 0:10:34 time: 0.0389 data: 0.0009 max mem: 33300 +Test: [ 5500/21770] eta: 0:10:30 time: 0.0387 data: 0.0009 max mem: 33300 +Test: [ 5600/21770] eta: 0:10:26 time: 0.0386 data: 0.0009 max mem: 33300 +Test: [ 5700/21770] eta: 0:10:22 time: 0.0388 data: 0.0009 max mem: 33300 +Test: [ 5800/21770] eta: 0:10:18 time: 0.0387 data: 0.0009 max mem: 33300 +Test: [ 5900/21770] eta: 0:10:14 time: 0.0387 data: 0.0009 max mem: 33300 +Test: [ 6000/21770] eta: 0:10:10 time: 0.0387 data: 0.0009 max mem: 33300 +Test: [ 6100/21770] eta: 0:10:07 time: 0.0388 data: 0.0009 max mem: 33300 +Test: [ 6200/21770] eta: 0:10:03 time: 0.0386 data: 0.0009 max mem: 33300 +Test: [ 6300/21770] eta: 0:09:59 time: 0.0388 data: 0.0009 max mem: 33300 +Test: [ 6400/21770] eta: 0:09:55 time: 0.0386 data: 0.0009 max mem: 33300 +Test: [ 6500/21770] eta: 0:09:51 time: 0.0387 data: 0.0009 max mem: 33300 +Test: [ 6600/21770] eta: 0:09:47 time: 0.0386 data: 0.0009 max mem: 33300 +Test: [ 6700/21770] eta: 0:09:43 time: 0.0388 data: 0.0009 max mem: 33300 +Test: [ 6800/21770] eta: 0:09:39 time: 0.0386 data: 0.0009 max mem: 33300 +Test: [ 6900/21770] eta: 0:09:36 time: 0.0387 data: 0.0009 max mem: 33300 +Test: [ 7000/21770] eta: 0:09:32 time: 0.0386 data: 0.0009 max mem: 33300 +Test: [ 7100/21770] eta: 0:09:28 time: 0.0390 data: 0.0009 max mem: 33300 +Test: [ 7200/21770] eta: 0:09:24 time: 0.0391 data: 0.0009 max mem: 33300 +Test: [ 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time: 0.0388 data: 0.0009 max mem: 33300 +Test: [ 8700/21770] eta: 0:08:26 time: 0.0387 data: 0.0009 max mem: 33300 +Test: [ 8800/21770] eta: 0:08:22 time: 0.0388 data: 0.0009 max mem: 33300 +Test: [ 8900/21770] eta: 0:08:18 time: 0.0387 data: 0.0009 max mem: 33300 +Test: [ 9000/21770] eta: 0:08:15 time: 0.0388 data: 0.0009 max mem: 33300 +Test: [ 9100/21770] eta: 0:08:11 time: 0.0392 data: 0.0009 max mem: 33300 +Test: [ 9200/21770] eta: 0:08:07 time: 0.0390 data: 0.0009 max mem: 33300 +Test: [ 9300/21770] eta: 0:08:03 time: 0.0392 data: 0.0009 max mem: 33300 +Test: [ 9400/21770] eta: 0:07:59 time: 0.0391 data: 0.0009 max mem: 33300 +Test: [ 9500/21770] eta: 0:07:55 time: 0.0388 data: 0.0009 max mem: 33300 +Test: [ 9600/21770] eta: 0:07:51 time: 0.0387 data: 0.0009 max mem: 33300 +Test: [ 9700/21770] eta: 0:07:48 time: 0.0389 data: 0.0009 max mem: 33300 +Test: [ 9800/21770] eta: 0:07:44 time: 0.0388 data: 0.0009 max mem: 33300 +Test: [ 9900/21770] eta: 0:07:40 time: 0.0389 data: 0.0009 max mem: 33300 +Test: [10000/21770] eta: 0:07:36 time: 0.0389 data: 0.0009 max mem: 33300 +Test: [10100/21770] eta: 0:07:32 time: 0.0389 data: 0.0008 max mem: 33300 +Test: [10200/21770] eta: 0:07:28 time: 0.0388 data: 0.0009 max mem: 33300 +Test: [10300/21770] eta: 0:07:24 time: 0.0390 data: 0.0009 max mem: 33300 +Test: [10400/21770] eta: 0:07:20 time: 0.0387 data: 0.0009 max mem: 33300 +Test: [10500/21770] eta: 0:07:17 time: 0.0390 data: 0.0009 max mem: 33300 +Test: [10600/21770] eta: 0:07:13 time: 0.0388 data: 0.0009 max mem: 33300 +Test: [10700/21770] eta: 0:07:09 time: 0.0388 data: 0.0009 max mem: 33300 +Test: [10800/21770] eta: 0:07:05 time: 0.0387 data: 0.0009 max mem: 33300 +Test: [10900/21770] eta: 0:07:01 time: 0.0388 data: 0.0009 max mem: 33300 +Test: [11000/21770] eta: 0:06:57 time: 0.0384 data: 0.0009 max mem: 33300 +Test: [11100/21770] eta: 0:06:53 time: 0.0385 data: 0.0009 max mem: 33300 +Test: [11200/21770] eta: 0:06:49 time: 0.0384 data: 0.0009 max mem: 33300 +Test: [11300/21770] eta: 0:06:45 time: 0.0385 data: 0.0009 max mem: 33300 +Test: [11400/21770] eta: 0:06:42 time: 0.0385 data: 0.0009 max mem: 33300 +Test: [11500/21770] eta: 0:06:38 time: 0.0386 data: 0.0009 max mem: 33300 +Test: [11600/21770] eta: 0:06:34 time: 0.0386 data: 0.0009 max mem: 33300 +Test: [11700/21770] eta: 0:06:30 time: 0.0385 data: 0.0009 max mem: 33300 +Test: [11800/21770] eta: 0:06:26 time: 0.0384 data: 0.0009 max mem: 33300 +Test: [11900/21770] eta: 0:06:22 time: 0.0383 data: 0.0009 max mem: 33300 +Test: [12000/21770] eta: 0:06:18 time: 0.0384 data: 0.0009 max mem: 33300 +Test: [12100/21770] eta: 0:06:14 time: 0.0388 data: 0.0009 max mem: 33300 +Test: [12200/21770] eta: 0:06:10 time: 0.0389 data: 0.0009 max mem: 33300 +Test: [12300/21770] eta: 0:06:07 time: 0.0391 data: 0.0009 max mem: 33300 +Test: [12400/21770] eta: 0:06:03 time: 0.0390 data: 0.0009 max mem: 33300 +Test: [12500/21770] eta: 0:05:59 time: 0.0394 data: 0.0009 max mem: 33300 +Test: [12600/21770] eta: 0:05:55 time: 0.0391 data: 0.0009 max mem: 33300 +Test: [12700/21770] eta: 0:05:51 time: 0.0392 data: 0.0009 max mem: 33300 +Test: [12800/21770] eta: 0:05:47 time: 0.0390 data: 0.0009 max mem: 33300 +Test: [12900/21770] eta: 0:05:43 time: 0.0395 data: 0.0009 max mem: 33300 +Test: [13000/21770] eta: 0:05:40 time: 0.0390 data: 0.0009 max mem: 33300 +Test: [13100/21770] eta: 0:05:36 time: 0.0392 data: 0.0009 max mem: 33300 +Test: [13200/21770] eta: 0:05:32 time: 0.0390 data: 0.0009 max mem: 33300 +Test: [13300/21770] eta: 0:05:28 time: 0.0391 data: 0.0009 max mem: 33300 +Test: [13400/21770] eta: 0:05:24 time: 0.0390 data: 0.0008 max mem: 33300 +Test: [13500/21770] eta: 0:05:20 time: 0.0391 data: 0.0008 max mem: 33300 +Test: [13600/21770] eta: 0:05:16 time: 0.0392 data: 0.0008 max mem: 33300 +Test: [13700/21770] eta: 0:05:13 time: 0.0391 data: 0.0008 max mem: 33300 +Test: [13800/21770] eta: 0:05:09 time: 0.0390 data: 0.0008 max mem: 33300 +Test: [13900/21770] eta: 0:05:05 time: 0.0392 data: 0.0008 max mem: 33300 +Test: [14000/21770] eta: 0:05:01 time: 0.0392 data: 0.0008 max mem: 33300 +Test: [14100/21770] eta: 0:04:57 time: 0.0395 data: 0.0008 max mem: 33300 +Test: [14200/21770] eta: 0:04:53 time: 0.0393 data: 0.0009 max mem: 33300 +Test: [14300/21770] eta: 0:04:49 time: 0.0393 data: 0.0009 max mem: 33300 +Test: [14400/21770] eta: 0:04:46 time: 0.0394 data: 0.0009 max mem: 33300 +Test: [14500/21770] eta: 0:04:42 time: 0.0401 data: 0.0009 max mem: 33300 +Test: [14600/21770] eta: 0:04:38 time: 0.0392 data: 0.0009 max mem: 33300 +Test: [14700/21770] eta: 0:04:34 time: 0.0396 data: 0.0009 max mem: 33300 +Test: [14800/21770] eta: 0:04:30 time: 0.0394 data: 0.0008 max mem: 33300 +Test: [14900/21770] eta: 0:04:26 time: 0.0397 data: 0.0008 max mem: 33300 +Test: [15000/21770] eta: 0:04:22 time: 0.0390 data: 0.0008 max mem: 33300 +Test: [15100/21770] eta: 0:04:19 time: 0.0401 data: 0.0008 max mem: 33300 +Test: [15200/21770] eta: 0:04:15 time: 0.0398 data: 0.0008 max mem: 33300 +Test: [15300/21770] eta: 0:04:11 time: 0.0401 data: 0.0008 max mem: 33300 +Test: [15400/21770] eta: 0:04:07 time: 0.0392 data: 0.0008 max mem: 33300 +Test: [15500/21770] eta: 0:04:03 time: 0.0396 data: 0.0008 max mem: 33300 +Test: [15600/21770] eta: 0:03:59 time: 0.0395 data: 0.0009 max mem: 33300 +Test: [15700/21770] eta: 0:03:56 time: 0.0401 data: 0.0008 max mem: 33300 +Test: [15800/21770] eta: 0:03:52 time: 0.0398 data: 0.0008 max mem: 33300 +Test: [15900/21770] eta: 0:03:48 time: 0.0401 data: 0.0008 max mem: 33300 +Test: [16000/21770] eta: 0:03:44 time: 0.0399 data: 0.0008 max mem: 33300 +Test: [16100/21770] eta: 0:03:40 time: 0.0401 data: 0.0008 max mem: 33300 +Test: [16200/21770] eta: 0:03:36 time: 0.0390 data: 0.0008 max mem: 33300 +Test: [16300/21770] eta: 0:03:32 time: 0.0396 data: 0.0008 max mem: 33300 +Test: [16400/21770] eta: 0:03:28 time: 0.0396 data: 0.0008 max mem: 33300 +Test: [16500/21770] eta: 0:03:25 time: 0.0399 data: 0.0008 max mem: 33300 +Test: [16600/21770] eta: 0:03:21 time: 0.0398 data: 0.0008 max mem: 33300 +Test: [16700/21770] eta: 0:03:17 time: 0.0395 data: 0.0008 max mem: 33300 +Test: [16800/21770] eta: 0:03:13 time: 0.0398 data: 0.0008 max mem: 33300 +Test: [16900/21770] eta: 0:03:09 time: 0.0396 data: 0.0008 max mem: 33300 +Test: [17000/21770] eta: 0:03:05 time: 0.0398 data: 0.0008 max mem: 33300 +Test: [17100/21770] eta: 0:03:01 time: 0.0401 data: 0.0008 max mem: 33300 +Test: [17200/21770] eta: 0:02:58 time: 0.0395 data: 0.0008 max mem: 33300 +Test: [17300/21770] eta: 0:02:54 time: 0.0401 data: 0.0008 max mem: 33300 +Test: [17400/21770] eta: 0:02:50 time: 0.0393 data: 0.0008 max mem: 33300 +Test: [17500/21770] eta: 0:02:46 time: 0.0380 data: 0.0009 max mem: 33300 +Test: [17600/21770] eta: 0:02:42 time: 0.0394 data: 0.0008 max mem: 33300 +Test: [17700/21770] eta: 0:02:38 time: 0.0393 data: 0.0008 max mem: 33300 +Test: [17800/21770] eta: 0:02:34 time: 0.0400 data: 0.0008 max mem: 33300 +Test: [17900/21770] eta: 0:02:30 time: 0.0399 data: 0.0008 max mem: 33300 +Test: [18000/21770] eta: 0:02:26 time: 0.0399 data: 0.0008 max mem: 33300 +Test: [18100/21770] eta: 0:02:23 time: 0.0400 data: 0.0008 max mem: 33300 +Test: [18200/21770] eta: 0:02:19 time: 0.0399 data: 0.0008 max mem: 33300 +Test: [18300/21770] eta: 0:02:15 time: 0.0400 data: 0.0008 max mem: 33300 +Test: [18400/21770] eta: 0:02:11 time: 0.0399 data: 0.0008 max mem: 33300 +Test: [18500/21770] eta: 0:02:07 time: 0.0400 data: 0.0008 max mem: 33300 +Test: [18600/21770] eta: 0:02:03 time: 0.0399 data: 0.0008 max mem: 33300 +Test: [18700/21770] eta: 0:01:59 time: 0.0401 data: 0.0008 max mem: 33300 +Test: [18800/21770] eta: 0:01:55 time: 0.0399 data: 0.0008 max mem: 33300 +Test: [18900/21770] eta: 0:01:52 time: 0.0400 data: 0.0008 max mem: 33300 +Test: [19000/21770] eta: 0:01:48 time: 0.0400 data: 0.0008 max mem: 33300 +Test: [19100/21770] eta: 0:01:44 time: 0.0401 data: 0.0008 max mem: 33300 +Test: [19200/21770] eta: 0:01:40 time: 0.0399 data: 0.0008 max mem: 33300 +Test: [19300/21770] eta: 0:01:36 time: 0.0400 data: 0.0008 max mem: 33300 +Test: [19400/21770] eta: 0:01:32 time: 0.0400 data: 0.0008 max mem: 33300 +Test: [19500/21770] eta: 0:01:28 time: 0.0401 data: 0.0008 max mem: 33300 +Test: [19600/21770] eta: 0:01:24 time: 0.0399 data: 0.0008 max mem: 33300 +Test: [19700/21770] eta: 0:01:20 time: 0.0401 data: 0.0008 max mem: 33300 +Test: [19800/21770] eta: 0:01:16 time: 0.0399 data: 0.0008 max mem: 33300 +Test: [19900/21770] eta: 0:01:13 time: 0.0401 data: 0.0008 max mem: 33300 +Test: [20000/21770] eta: 0:01:09 time: 0.0399 data: 0.0008 max mem: 33300 +Test: [20100/21770] eta: 0:01:05 time: 0.0400 data: 0.0008 max mem: 33300 +Test: [20200/21770] eta: 0:01:01 time: 0.0399 data: 0.0008 max mem: 33300 +Test: [20300/21770] eta: 0:00:57 time: 0.0401 data: 0.0008 max mem: 33300 +Test: [20400/21770] eta: 0:00:53 time: 0.0399 data: 0.0008 max mem: 33300 +Test: [20500/21770] eta: 0:00:49 time: 0.0400 data: 0.0008 max mem: 33300 +Test: [20600/21770] eta: 0:00:45 time: 0.0399 data: 0.0008 max mem: 33300 +Test: [20700/21770] eta: 0:00:41 time: 0.0401 data: 0.0008 max mem: 33300 +Test: [20800/21770] eta: 0:00:37 time: 0.0399 data: 0.0008 max mem: 33300 +Test: [20900/21770] eta: 0:00:34 time: 0.0402 data: 0.0008 max mem: 33300 +Test: [21000/21770] eta: 0:00:30 time: 0.0399 data: 0.0008 max mem: 33300 +Test: [21100/21770] eta: 0:00:26 time: 0.0402 data: 0.0008 max mem: 33300 +Test: [21200/21770] eta: 0:00:22 time: 0.0399 data: 0.0008 max mem: 33300 +Test: [21300/21770] eta: 0:00:18 time: 0.0401 data: 0.0008 max mem: 33300 +Test: [21400/21770] eta: 0:00:14 time: 0.0400 data: 0.0008 max mem: 33300 +Test: [21500/21770] eta: 0:00:10 time: 0.0400 data: 0.0008 max mem: 33300 +Test: [21600/21770] eta: 0:00:06 time: 0.0399 data: 0.0008 max mem: 33300 +Test: [21700/21770] eta: 0:00:02 time: 0.0400 data: 0.0008 max mem: 33300 +Test: Total time: 0:14:12 +Final results: +Mean IoU is 0.00 + + precision@0.5 = 0.00 + precision@0.6 = 0.00 + precision@0.7 = 0.00 + precision@0.8 = 0.00 + precision@0.9 = 0.00 + overall IoU = 0.00 + mean IoU = 0.00 + +Mean accuracy for one-to-zero sample is 100.00 + +Average object IoU 0.0 +Overall IoU 0.0 +Epoch: [21] [ 0/4276] eta: 6:08:33 lr: 2.5585236864699295e-05 loss: 0.1035 (0.1035) time: 5.1715 data: 2.0479 max mem: 33300 +Epoch: [21] [ 10/4276] eta: 3:40:35 lr: 2.558240254606265e-05 loss: 0.1102 (0.1162) time: 3.1027 data: 0.1926 max mem: 33300 +Epoch: [21] [ 20/4276] eta: 3:33:20 lr: 2.5579568192534574e-05 loss: 0.1061 (0.1200) time: 2.8993 data: 0.0074 max mem: 33300 +Epoch: [21] [ 30/4276] eta: 3:30:22 lr: 2.557673380411033e-05 loss: 0.1061 (0.1201) time: 2.9015 data: 0.0078 max mem: 33300 +Epoch: [21] [ 40/4276] eta: 3:29:43 lr: 2.55738993807852e-05 loss: 0.1140 (0.1187) time: 2.9316 data: 0.0084 max mem: 33300 +Epoch: [21] [ 50/4276] eta: 3:28:45 lr: 2.557106492255445e-05 loss: 0.1097 (0.1144) time: 2.9500 data: 0.0087 max mem: 33300 +Epoch: [21] [ 60/4276] eta: 3:27:53 lr: 2.556823042941336e-05 loss: 0.0982 (0.1124) time: 2.9342 data: 0.0080 max mem: 33300 +Epoch: [21] [ 70/4276] eta: 3:27:10 lr: 2.5565395901357186e-05 loss: 0.1031 (0.1118) time: 2.9339 data: 0.0075 max mem: 33300 +Epoch: [21] [ 80/4276] eta: 3:26:29 lr: 2.5562561338381207e-05 loss: 0.1159 (0.1141) time: 2.9350 data: 0.0077 max mem: 33300 +Epoch: [21] [ 90/4276] eta: 3:25:50 lr: 2.5559726740480688e-05 loss: 0.1159 (0.1136) time: 2.9326 data: 0.0078 max mem: 33300 +Epoch: [21] [ 100/4276] eta: 3:25:15 lr: 2.5556892107650905e-05 loss: 0.1080 (0.1147) time: 2.9340 data: 0.0076 max mem: 33300 +Epoch: [21] [ 110/4276] eta: 3:24:38 lr: 2.5554057439887102e-05 loss: 0.1169 (0.1151) time: 2.9335 data: 0.0075 max mem: 33300 +Epoch: [21] [ 120/4276] eta: 3:24:03 lr: 2.5551222737184555e-05 loss: 0.1122 (0.1150) time: 2.9306 data: 0.0078 max mem: 33300 +Epoch: [21] [ 130/4276] eta: 3:23:27 lr: 2.554838799953852e-05 loss: 0.1142 (0.1153) time: 2.9278 data: 0.0078 max mem: 33300 +Epoch: [21] [ 140/4276] eta: 3:22:51 lr: 2.5545553226944273e-05 loss: 0.1080 (0.1147) time: 2.9238 data: 0.0075 max mem: 33300 +Epoch: [21] [ 150/4276] eta: 3:22:15 lr: 2.554271841939706e-05 loss: 0.1001 (0.1144) time: 2.9208 data: 0.0075 max mem: 33300 +Epoch: [21] [ 160/4276] eta: 3:21:37 lr: 2.5539883576892144e-05 loss: 0.1051 (0.1143) time: 2.9124 data: 0.0078 max mem: 33300 +Epoch: [21] [ 170/4276] eta: 3:21:06 lr: 2.5537048699424782e-05 loss: 0.1119 (0.1142) time: 2.9190 data: 0.0080 max mem: 33300 +Epoch: [21] [ 180/4276] eta: 3:20:34 lr: 2.553421378699023e-05 loss: 0.1132 (0.1144) time: 2.9299 data: 0.0077 max mem: 33300 +Epoch: [21] [ 190/4276] eta: 3:20:03 lr: 2.5531378839583747e-05 loss: 0.1036 (0.1141) time: 2.9289 data: 0.0072 max mem: 33300 +Epoch: [21] [ 200/4276] eta: 3:19:31 lr: 2.5528543857200577e-05 loss: 0.0971 (0.1142) time: 2.9289 data: 0.0072 max mem: 33300 +Epoch: [21] [ 210/4276] eta: 3:19:00 lr: 2.5525708839835983e-05 loss: 0.1075 (0.1139) time: 2.9283 data: 0.0072 max mem: 33300 +Epoch: [21] [ 220/4276] eta: 3:18:30 lr: 2.5522873787485212e-05 loss: 0.1028 (0.1136) time: 2.9290 data: 0.0072 max mem: 33300 +Epoch: [21] [ 230/4276] eta: 3:17:59 lr: 2.5520038700143513e-05 loss: 0.0994 (0.1131) time: 2.9309 data: 0.0073 max mem: 33300 +Epoch: [21] [ 240/4276] eta: 3:17:30 lr: 2.5517203577806132e-05 loss: 0.1073 (0.1135) time: 2.9336 data: 0.0074 max mem: 33300 +Epoch: [21] [ 250/4276] eta: 3:17:00 lr: 2.5514368420468327e-05 loss: 0.1166 (0.1141) time: 2.9323 data: 0.0072 max mem: 33300 +Epoch: [21] [ 260/4276] eta: 3:16:29 lr: 2.551153322812534e-05 loss: 0.1171 (0.1141) time: 2.9285 data: 0.0071 max mem: 33300 +Epoch: [21] [ 270/4276] eta: 3:15:58 lr: 2.550869800077241e-05 loss: 0.1037 (0.1140) time: 2.9274 data: 0.0071 max mem: 33300 +Epoch: [21] [ 280/4276] eta: 3:15:28 lr: 2.5505862738404785e-05 loss: 0.1013 (0.1138) time: 2.9290 data: 0.0074 max mem: 33300 +Epoch: [21] [ 290/4276] eta: 3:14:58 lr: 2.5503027441017713e-05 loss: 0.1100 (0.1138) time: 2.9304 data: 0.0074 max mem: 33300 +Epoch: [21] [ 300/4276] eta: 3:14:28 lr: 2.5500192108606424e-05 loss: 0.1082 (0.1136) time: 2.9305 data: 0.0076 max mem: 33300 +Epoch: [21] [ 310/4276] eta: 3:13:58 lr: 2.549735674116617e-05 loss: 0.0987 (0.1133) time: 2.9301 data: 0.0076 max mem: 33300 +Epoch: [21] [ 320/4276] eta: 3:13:29 lr: 2.5494521338692177e-05 loss: 0.1085 (0.1134) time: 2.9308 data: 0.0072 max mem: 33300 +Epoch: [21] [ 330/4276] eta: 3:12:59 lr: 2.5491685901179702e-05 loss: 0.1169 (0.1138) time: 2.9302 data: 0.0072 max mem: 33300 +Epoch: [21] [ 340/4276] eta: 3:12:29 lr: 2.5488850428623966e-05 loss: 0.1076 (0.1134) time: 2.9305 data: 0.0072 max mem: 33300 +Epoch: [21] [ 350/4276] eta: 3:12:00 lr: 2.5486014921020202e-05 loss: 0.0943 (0.1133) time: 2.9346 data: 0.0072 max mem: 33300 +Epoch: [21] [ 360/4276] eta: 3:11:31 lr: 2.5483179378363657e-05 loss: 0.1163 (0.1140) time: 2.9358 data: 0.0072 max mem: 33300 +Epoch: [21] [ 370/4276] eta: 3:11:01 lr: 2.548034380064956e-05 loss: 0.1100 (0.1138) time: 2.9336 data: 0.0072 max mem: 33300 +Epoch: [21] [ 380/4276] eta: 3:10:32 lr: 2.5477508187873134e-05 loss: 0.1017 (0.1140) time: 2.9329 data: 0.0072 max mem: 33300 +Epoch: [21] [ 390/4276] eta: 3:10:04 lr: 2.5474672540029615e-05 loss: 0.1248 (0.1146) time: 2.9441 data: 0.0073 max mem: 33300 +Epoch: [21] [ 400/4276] eta: 3:09:35 lr: 2.5471836857114233e-05 loss: 0.1290 (0.1152) time: 2.9445 data: 0.0073 max mem: 33300 +Epoch: [21] [ 410/4276] eta: 3:09:05 lr: 2.5469001139122223e-05 loss: 0.1188 (0.1153) time: 2.9326 data: 0.0072 max mem: 33300 +Epoch: [21] [ 420/4276] eta: 3:08:36 lr: 2.5466165386048796e-05 loss: 0.1091 (0.1153) time: 2.9340 data: 0.0072 max mem: 33300 +Epoch: [21] [ 430/4276] eta: 3:08:07 lr: 2.5463329597889187e-05 loss: 0.1165 (0.1156) time: 2.9374 data: 0.0071 max mem: 33300 +Epoch: [21] [ 440/4276] eta: 3:07:38 lr: 2.5460493774638615e-05 loss: 0.1097 (0.1154) time: 2.9377 data: 0.0071 max mem: 33300 +Epoch: [21] [ 450/4276] eta: 3:07:09 lr: 2.5457657916292315e-05 loss: 0.1049 (0.1155) time: 2.9362 data: 0.0072 max mem: 33300 +Epoch: [21] [ 460/4276] eta: 3:06:39 lr: 2.5454822022845494e-05 loss: 0.1098 (0.1153) time: 2.9343 data: 0.0072 max mem: 33300 +Epoch: [21] [ 470/4276] eta: 3:06:10 lr: 2.5451986094293373e-05 loss: 0.0976 (0.1149) time: 2.9340 data: 0.0072 max mem: 33300 +Epoch: [21] [ 480/4276] eta: 3:05:41 lr: 2.5449150130631183e-05 loss: 0.0976 (0.1147) time: 2.9413 data: 0.0072 max mem: 33300 +Epoch: [21] [ 490/4276] eta: 3:05:12 lr: 2.544631413185414e-05 loss: 0.0979 (0.1143) time: 2.9408 data: 0.0072 max mem: 33300 +Epoch: [21] [ 500/4276] eta: 3:04:42 lr: 2.544347809795745e-05 loss: 0.0967 (0.1140) time: 2.9336 data: 0.0073 max mem: 33300 +Epoch: [21] [ 510/4276] eta: 3:04:13 lr: 2.5440642028936336e-05 loss: 0.1068 (0.1140) time: 2.9360 data: 0.0074 max mem: 33300 +Epoch: [21] [ 520/4276] eta: 3:03:44 lr: 2.543780592478601e-05 loss: 0.1225 (0.1142) time: 2.9347 data: 0.0074 max mem: 33300 +Epoch: [21] [ 530/4276] eta: 3:03:14 lr: 2.5434969785501694e-05 loss: 0.1134 (0.1142) time: 2.9338 data: 0.0074 max mem: 33300 +Epoch: [21] [ 540/4276] eta: 3:02:45 lr: 2.5432133611078584e-05 loss: 0.1049 (0.1140) time: 2.9343 data: 0.0074 max mem: 33300 +Epoch: [21] [ 550/4276] eta: 3:02:16 lr: 2.54292974015119e-05 loss: 0.1049 (0.1142) time: 2.9398 data: 0.0071 max mem: 33300 +Epoch: [21] [ 560/4276] eta: 3:01:47 lr: 2.5426461156796845e-05 loss: 0.1126 (0.1142) time: 2.9402 data: 0.0072 max mem: 33300 +Epoch: [21] [ 570/4276] eta: 3:01:18 lr: 2.5423624876928637e-05 loss: 0.1264 (0.1143) time: 2.9349 data: 0.0072 max mem: 33300 +Epoch: [21] [ 580/4276] eta: 3:00:49 lr: 2.5420788561902476e-05 loss: 0.1093 (0.1143) time: 2.9411 data: 0.0072 max mem: 33300 +Epoch: [21] [ 590/4276] eta: 3:00:20 lr: 2.5417952211713563e-05 loss: 0.0984 (0.1140) time: 2.9418 data: 0.0072 max mem: 33300 +Epoch: [21] [ 600/4276] eta: 2:59:50 lr: 2.541511582635712e-05 loss: 0.0941 (0.1138) time: 2.9336 data: 0.0073 max mem: 33300 +Epoch: [21] [ 610/4276] eta: 2:59:20 lr: 2.5412279405828325e-05 loss: 0.0963 (0.1138) time: 2.9292 data: 0.0072 max mem: 33300 +Epoch: [21] [ 620/4276] eta: 2:58:51 lr: 2.5409442950122403e-05 loss: 0.0952 (0.1136) time: 2.9319 data: 0.0072 max mem: 33300 +Epoch: [21] [ 630/4276] eta: 2:58:22 lr: 2.5406606459234533e-05 loss: 0.1035 (0.1136) time: 2.9371 data: 0.0074 max mem: 33300 +Epoch: [21] [ 640/4276] eta: 2:57:52 lr: 2.540376993315994e-05 loss: 0.1134 (0.1137) time: 2.9377 data: 0.0074 max mem: 33300 +Epoch: [21] [ 650/4276] eta: 2:57:23 lr: 2.5400933371893793e-05 loss: 0.1076 (0.1137) time: 2.9386 data: 0.0074 max mem: 33300 +Epoch: [21] [ 660/4276] eta: 2:56:54 lr: 2.5398096775431306e-05 loss: 0.1132 (0.1139) time: 2.9412 data: 0.0074 max mem: 33300 +Epoch: [21] [ 670/4276] eta: 2:56:25 lr: 2.5395260143767672e-05 loss: 0.1152 (0.1139) time: 2.9396 data: 0.0072 max mem: 33300 +Epoch: [21] [ 680/4276] eta: 2:55:56 lr: 2.5392423476898097e-05 loss: 0.1140 (0.1140) time: 2.9374 data: 0.0073 max mem: 33300 +Epoch: [21] [ 690/4276] eta: 2:55:27 lr: 2.5389586774817747e-05 loss: 0.1078 (0.1139) time: 2.9374 data: 0.0073 max mem: 33300 +Epoch: [21] [ 700/4276] eta: 2:54:57 lr: 2.5386750037521834e-05 loss: 0.1020 (0.1137) time: 2.9377 data: 0.0072 max mem: 33300 +Epoch: [21] [ 710/4276] eta: 2:54:28 lr: 2.5383913265005538e-05 loss: 0.1058 (0.1139) time: 2.9410 data: 0.0072 max mem: 33300 +Epoch: [21] [ 720/4276] eta: 2:53:59 lr: 2.5381076457264063e-05 loss: 0.1115 (0.1139) time: 2.9376 data: 0.0072 max mem: 33300 +Epoch: [21] [ 730/4276] eta: 2:53:27 lr: 2.5378239614292576e-05 loss: 0.1074 (0.1138) time: 2.9055 data: 0.0081 max mem: 33300 +Epoch: [21] [ 740/4276] eta: 2:52:57 lr: 2.5375402736086278e-05 loss: 0.1027 (0.1138) time: 2.9071 data: 0.0092 max mem: 33300 +Epoch: [21] [ 750/4276] eta: 2:52:28 lr: 2.5372565822640353e-05 loss: 0.1081 (0.1138) time: 2.9337 data: 0.0089 max mem: 33300 +Epoch: [21] [ 760/4276] eta: 2:51:59 lr: 2.536972887394999e-05 loss: 0.1007 (0.1137) time: 2.9344 data: 0.0084 max mem: 33300 +Epoch: [21] [ 770/4276] eta: 2:51:29 lr: 2.5366891890010357e-05 loss: 0.1024 (0.1137) time: 2.9346 data: 0.0082 max mem: 33300 +Epoch: [21] [ 780/4276] eta: 2:51:00 lr: 2.5364054870816644e-05 loss: 0.1082 (0.1136) time: 2.9364 data: 0.0079 max mem: 33300 +Epoch: [21] [ 790/4276] eta: 2:50:31 lr: 2.536121781636403e-05 loss: 0.1123 (0.1137) time: 2.9442 data: 0.0082 max mem: 33300 +Epoch: [21] [ 800/4276] eta: 2:50:02 lr: 2.5358380726647708e-05 loss: 0.1025 (0.1136) time: 2.9429 data: 0.0084 max mem: 33300 +Epoch: [21] [ 810/4276] eta: 2:49:33 lr: 2.535554360166283e-05 loss: 0.1009 (0.1138) time: 2.9357 data: 0.0082 max mem: 33300 +Epoch: [21] [ 820/4276] eta: 2:49:04 lr: 2.5352706441404588e-05 loss: 0.1002 (0.1137) time: 2.9371 data: 0.0079 max mem: 33300 +Epoch: [21] [ 830/4276] eta: 2:48:34 lr: 2.5349869245868157e-05 loss: 0.0978 (0.1138) time: 2.9397 data: 0.0081 max mem: 33300 +Epoch: [21] [ 840/4276] eta: 2:48:05 lr: 2.5347032015048717e-05 loss: 0.1131 (0.1139) time: 2.9406 data: 0.0084 max mem: 33300 +Epoch: [21] [ 850/4276] eta: 2:47:36 lr: 2.5344194748941423e-05 loss: 0.1072 (0.1137) time: 2.9404 data: 0.0081 max mem: 33300 +Epoch: [21] [ 860/4276] eta: 2:47:07 lr: 2.5341357447541465e-05 loss: 0.1030 (0.1138) time: 2.9387 data: 0.0079 max mem: 33300 +Epoch: [21] [ 870/4276] eta: 2:46:37 lr: 2.5338520110843998e-05 loss: 0.1066 (0.1138) time: 2.9332 data: 0.0086 max mem: 33300 +Epoch: [21] [ 880/4276] eta: 2:46:06 lr: 2.5335682738844207e-05 loss: 0.1098 (0.1139) time: 2.9066 data: 0.0088 max mem: 33300 +Epoch: [21] [ 890/4276] eta: 2:45:37 lr: 2.5332845331537246e-05 loss: 0.1210 (0.1140) time: 2.9150 data: 0.0081 max mem: 33300 +Epoch: [21] [ 900/4276] eta: 2:45:08 lr: 2.5330007888918288e-05 loss: 0.1115 (0.1139) time: 2.9403 data: 0.0085 max mem: 33300 +Epoch: [21] [ 910/4276] eta: 2:44:38 lr: 2.5327170410982505e-05 loss: 0.1157 (0.1140) time: 2.9375 data: 0.0093 max mem: 33300 +Epoch: [21] [ 920/4276] eta: 2:44:09 lr: 2.5324332897725045e-05 loss: 0.1166 (0.1140) time: 2.9386 data: 0.0089 max mem: 33300 +Epoch: [21] [ 930/4276] eta: 2:43:40 lr: 2.5321495349141076e-05 loss: 0.1135 (0.1140) time: 2.9324 data: 0.0083 max mem: 33300 +Epoch: [21] [ 940/4276] eta: 2:43:10 lr: 2.5318657765225768e-05 loss: 0.1131 (0.1140) time: 2.9320 data: 0.0083 max mem: 33300 +Epoch: [21] [ 950/4276] eta: 2:42:41 lr: 2.5315820145974277e-05 loss: 0.1131 (0.1142) time: 2.9360 data: 0.0083 max mem: 33300 +Epoch: [21] [ 960/4276] eta: 2:42:11 lr: 2.531298249138176e-05 loss: 0.1181 (0.1143) time: 2.9267 data: 0.0084 max mem: 33300 +Epoch: [21] [ 970/4276] eta: 2:41:42 lr: 2.5310144801443375e-05 loss: 0.1148 (0.1143) time: 2.9279 data: 0.0082 max mem: 33300 +Epoch: [21] [ 980/4276] eta: 2:41:13 lr: 2.530730707615428e-05 loss: 0.1083 (0.1142) time: 2.9379 data: 0.0080 max mem: 33300 +Epoch: [21] [ 990/4276] eta: 2:40:43 lr: 2.5304469315509632e-05 loss: 0.1123 (0.1142) time: 2.9393 data: 0.0081 max mem: 33300 +Epoch: [21] [1000/4276] eta: 2:40:14 lr: 2.5301631519504575e-05 loss: 0.1123 (0.1143) time: 2.9353 data: 0.0083 max mem: 33300 +Epoch: [21] [1010/4276] eta: 2:39:45 lr: 2.529879368813427e-05 loss: 0.1071 (0.1143) time: 2.9356 data: 0.0082 max mem: 33300 +Epoch: [21] [1020/4276] eta: 2:39:16 lr: 2.529595582139387e-05 loss: 0.1080 (0.1143) time: 2.9426 data: 0.0080 max mem: 33300 +Epoch: [21] [1030/4276] eta: 2:38:46 lr: 2.5293117919278525e-05 loss: 0.1080 (0.1144) time: 2.9395 data: 0.0082 max mem: 33300 +Epoch: [21] [1040/4276] eta: 2:38:17 lr: 2.5290279981783377e-05 loss: 0.1117 (0.1143) time: 2.9356 data: 0.0084 max mem: 33300 +Epoch: [21] [1050/4276] eta: 2:37:48 lr: 2.5287442008903573e-05 loss: 0.1086 (0.1144) time: 2.9350 data: 0.0082 max mem: 33300 +Epoch: [21] [1060/4276] eta: 2:37:18 lr: 2.528460400063427e-05 loss: 0.1086 (0.1145) time: 2.9317 data: 0.0082 max mem: 33300 +Epoch: [21] [1070/4276] eta: 2:36:49 lr: 2.528176595697061e-05 loss: 0.1155 (0.1147) time: 2.9336 data: 0.0084 max mem: 33300 +Epoch: [21] [1080/4276] eta: 2:36:20 lr: 2.5278927877907725e-05 loss: 0.1148 (0.1148) time: 2.9369 data: 0.0084 max mem: 33300 +Epoch: [21] [1090/4276] eta: 2:35:50 lr: 2.527608976344077e-05 loss: 0.1198 (0.1149) time: 2.9366 data: 0.0082 max mem: 33300 +Epoch: [21] [1100/4276] eta: 2:35:21 lr: 2.527325161356488e-05 loss: 0.1178 (0.1150) time: 2.9324 data: 0.0079 max mem: 33300 +Epoch: [21] [1110/4276] eta: 2:34:52 lr: 2.5270413428275206e-05 loss: 0.1129 (0.1150) time: 2.9379 data: 0.0079 max mem: 33300 +Epoch: [21] [1120/4276] eta: 2:34:22 lr: 2.5267575207566874e-05 loss: 0.1102 (0.1151) time: 2.9401 data: 0.0078 max mem: 33300 +Epoch: [21] [1130/4276] eta: 2:33:53 lr: 2.526473695143502e-05 loss: 0.1081 (0.1149) time: 2.9323 data: 0.0076 max mem: 33300 +Epoch: [21] [1140/4276] eta: 2:33:23 lr: 2.5261898659874787e-05 loss: 0.1069 (0.1149) time: 2.9300 data: 0.0076 max mem: 33300 +Epoch: [21] [1150/4276] eta: 2:32:54 lr: 2.5259060332881313e-05 loss: 0.1128 (0.1149) time: 2.9318 data: 0.0078 max mem: 33300 +Epoch: [21] [1160/4276] eta: 2:32:25 lr: 2.525622197044972e-05 loss: 0.1122 (0.1149) time: 2.9361 data: 0.0078 max mem: 33300 +Epoch: [21] [1170/4276] eta: 2:31:55 lr: 2.525338357257515e-05 loss: 0.1122 (0.1150) time: 2.9331 data: 0.0078 max mem: 33300 +Epoch: [21] [1180/4276] eta: 2:31:26 lr: 2.5250545139252736e-05 loss: 0.1116 (0.1149) time: 2.9313 data: 0.0078 max mem: 33300 +Epoch: [21] [1190/4276] eta: 2:30:56 lr: 2.52477066704776e-05 loss: 0.0976 (0.1148) time: 2.9312 data: 0.0077 max mem: 33300 +Epoch: [21] [1200/4276] eta: 2:30:27 lr: 2.524486816624487e-05 loss: 0.0976 (0.1148) time: 2.9308 data: 0.0077 max mem: 33300 +Epoch: [21] [1210/4276] eta: 2:29:58 lr: 2.524202962654968e-05 loss: 0.1058 (0.1147) time: 2.9343 data: 0.0076 max mem: 33300 +Epoch: [21] [1220/4276] eta: 2:29:28 lr: 2.523919105138715e-05 loss: 0.1058 (0.1147) time: 2.9350 data: 0.0076 max mem: 33300 +Epoch: [21] [1230/4276] eta: 2:28:59 lr: 2.5236352440752408e-05 loss: 0.1118 (0.1148) time: 2.9322 data: 0.0078 max mem: 33300 +Epoch: [21] [1240/4276] eta: 2:28:29 lr: 2.523351379464058e-05 loss: 0.1095 (0.1147) time: 2.9309 data: 0.0078 max mem: 33300 +Epoch: [21] [1250/4276] eta: 2:28:00 lr: 2.5230675113046776e-05 loss: 0.1095 (0.1148) time: 2.9319 data: 0.0078 max mem: 33300 +Epoch: [21] [1260/4276] eta: 2:27:31 lr: 2.5227836395966132e-05 loss: 0.1059 (0.1147) time: 2.9328 data: 0.0080 max mem: 33300 +Epoch: [21] [1270/4276] eta: 2:27:01 lr: 2.522499764339376e-05 loss: 0.0993 (0.1146) time: 2.9318 data: 0.0081 max mem: 33300 +Epoch: [21] [1280/4276] eta: 2:26:32 lr: 2.5222158855324772e-05 loss: 0.1059 (0.1146) time: 2.9322 data: 0.0083 max mem: 33300 +Epoch: [21] [1290/4276] eta: 2:26:02 lr: 2.5219320031754295e-05 loss: 0.1126 (0.1146) time: 2.9331 data: 0.0081 max mem: 33300 +Epoch: [21] [1300/4276] eta: 2:25:33 lr: 2.5216481172677447e-05 loss: 0.0981 (0.1145) time: 2.9325 data: 0.0079 max mem: 33300 +Epoch: [21] [1310/4276] eta: 2:25:04 lr: 2.5213642278089333e-05 loss: 0.0950 (0.1144) time: 2.9331 data: 0.0081 max mem: 33300 +Epoch: [21] [1320/4276] eta: 2:24:34 lr: 2.521080334798507e-05 loss: 0.1096 (0.1144) time: 2.9339 data: 0.0082 max mem: 33300 +Epoch: [21] [1330/4276] eta: 2:24:05 lr: 2.5207964382359768e-05 loss: 0.1128 (0.1144) time: 2.9332 data: 0.0081 max mem: 33300 +Epoch: [21] [1340/4276] eta: 2:23:35 lr: 2.5205125381208545e-05 loss: 0.1135 (0.1144) time: 2.9323 data: 0.0080 max mem: 33300 +Epoch: [21] [1350/4276] eta: 2:23:06 lr: 2.5202286344526493e-05 loss: 0.1179 (0.1145) time: 2.9329 data: 0.0081 max mem: 33300 +Epoch: [21] [1360/4276] eta: 2:22:37 lr: 2.519944727230874e-05 loss: 0.1217 (0.1145) time: 2.9343 data: 0.0083 max mem: 33300 +Epoch: [21] [1370/4276] eta: 2:22:07 lr: 2.5196608164550377e-05 loss: 0.1108 (0.1145) time: 2.9340 data: 0.0082 max mem: 33300 +Epoch: [21] [1380/4276] eta: 2:21:38 lr: 2.519376902124653e-05 loss: 0.1155 (0.1147) time: 2.9330 data: 0.0079 max mem: 33300 +Epoch: [21] [1390/4276] eta: 2:21:09 lr: 2.5190929842392273e-05 loss: 0.1310 (0.1148) time: 2.9320 data: 0.0081 max mem: 33300 +Epoch: [21] [1400/4276] eta: 2:20:39 lr: 2.5188090627982736e-05 loss: 0.1219 (0.1148) time: 2.9318 data: 0.0083 max mem: 33300 +Epoch: [21] [1410/4276] eta: 2:20:10 lr: 2.5185251378013003e-05 loss: 0.1041 (0.1148) time: 2.9333 data: 0.0082 max mem: 33300 +Epoch: [21] [1420/4276] eta: 2:19:40 lr: 2.5182412092478187e-05 loss: 0.1005 (0.1147) time: 2.9319 data: 0.0080 max mem: 33300 +Epoch: [21] [1430/4276] eta: 2:19:11 lr: 2.5179572771373378e-05 loss: 0.1030 (0.1147) time: 2.9295 data: 0.0081 max mem: 33300 +Epoch: [21] [1440/4276] eta: 2:18:41 lr: 2.5176733414693676e-05 loss: 0.1114 (0.1147) time: 2.9279 data: 0.0083 max mem: 33300 +Epoch: [21] [1450/4276] eta: 2:18:12 lr: 2.5173894022434176e-05 loss: 0.1114 (0.1147) time: 2.9344 data: 0.0081 max mem: 33300 +Epoch: [21] [1460/4276] eta: 2:17:43 lr: 2.517105459458998e-05 loss: 0.1031 (0.1148) time: 2.9322 data: 0.0079 max mem: 33300 +Epoch: [21] [1470/4276] eta: 2:17:13 lr: 2.516821513115617e-05 loss: 0.1006 (0.1147) time: 2.9206 data: 0.0081 max mem: 33300 +Epoch: [21] [1480/4276] eta: 2:16:43 lr: 2.5165375632127854e-05 loss: 0.1009 (0.1147) time: 2.9211 data: 0.0083 max mem: 33300 +Epoch: [21] [1490/4276] eta: 2:16:14 lr: 2.5162536097500106e-05 loss: 0.1009 (0.1146) time: 2.9269 data: 0.0081 max mem: 33300 +Epoch: [21] [1500/4276] eta: 2:15:45 lr: 2.515969652726803e-05 loss: 0.1034 (0.1146) time: 2.9312 data: 0.0080 max mem: 33300 +Epoch: [21] [1510/4276] eta: 2:15:16 lr: 2.5156856921426702e-05 loss: 0.1061 (0.1145) time: 2.9399 data: 0.0082 max mem: 33300 +Epoch: [21] [1520/4276] eta: 2:14:46 lr: 2.515401727997122e-05 loss: 0.0995 (0.1145) time: 2.9399 data: 0.0083 max mem: 33300 +Epoch: [21] [1530/4276] eta: 2:14:17 lr: 2.515117760289667e-05 loss: 0.1025 (0.1145) time: 2.9312 data: 0.0081 max mem: 33300 +Epoch: [21] [1540/4276] eta: 2:13:47 lr: 2.5148337890198125e-05 loss: 0.1115 (0.1146) time: 2.9283 data: 0.0079 max mem: 33300 +Epoch: [21] [1550/4276] eta: 2:13:18 lr: 2.5145498141870676e-05 loss: 0.1140 (0.1146) time: 2.9279 data: 0.0081 max mem: 33300 +Epoch: [21] [1560/4276] eta: 2:12:49 lr: 2.514265835790941e-05 loss: 0.1080 (0.1145) time: 2.9316 data: 0.0083 max mem: 33300 +Epoch: [21] [1570/4276] eta: 2:12:19 lr: 2.5139818538309406e-05 loss: 0.1067 (0.1145) time: 2.9299 data: 0.0082 max mem: 33300 +Epoch: [21] [1580/4276] eta: 2:11:50 lr: 2.5136978683065736e-05 loss: 0.1024 (0.1143) time: 2.9283 data: 0.0080 max mem: 33300 +Epoch: [21] [1590/4276] eta: 2:11:20 lr: 2.5134138792173484e-05 loss: 0.1048 (0.1144) time: 2.9297 data: 0.0081 max mem: 33300 +Epoch: [21] [1600/4276] eta: 2:10:51 lr: 2.513129886562772e-05 loss: 0.1139 (0.1144) time: 2.9321 data: 0.0083 max mem: 33300 +Epoch: [21] [1610/4276] eta: 2:10:22 lr: 2.512845890342354e-05 loss: 0.1087 (0.1144) time: 2.9345 data: 0.0081 max mem: 33300 +Epoch: [21] [1620/4276] eta: 2:09:52 lr: 2.5125618905555993e-05 loss: 0.0986 (0.1143) time: 2.9340 data: 0.0080 max mem: 33300 +Epoch: [21] [1630/4276] eta: 2:09:23 lr: 2.5122778872020164e-05 loss: 0.1046 (0.1144) time: 2.9310 data: 0.0083 max mem: 33300 +Epoch: [21] [1640/4276] eta: 2:08:53 lr: 2.5119938802811123e-05 loss: 0.1030 (0.1143) time: 2.9280 data: 0.0084 max mem: 33300 +Epoch: [21] [1650/4276] eta: 2:08:24 lr: 2.5117098697923946e-05 loss: 0.0963 (0.1142) time: 2.9267 data: 0.0081 max mem: 33300 +Epoch: [21] [1660/4276] eta: 2:07:54 lr: 2.5114258557353693e-05 loss: 0.0987 (0.1141) time: 2.9248 data: 0.0080 max mem: 33300 +Epoch: [21] [1670/4276] eta: 2:07:25 lr: 2.511141838109543e-05 loss: 0.0915 (0.1140) time: 2.9206 data: 0.0081 max mem: 33300 +Epoch: [21] [1680/4276] eta: 2:06:55 lr: 2.5108578169144238e-05 loss: 0.0960 (0.1141) time: 2.9208 data: 0.0083 max mem: 33300 +Epoch: [21] [1690/4276] eta: 2:06:26 lr: 2.5105737921495177e-05 loss: 0.0978 (0.1140) time: 2.9279 data: 0.0081 max mem: 33300 +Epoch: [21] [1700/4276] eta: 2:05:57 lr: 2.51028976381433e-05 loss: 0.0971 (0.1139) time: 2.9337 data: 0.0080 max mem: 33300 +Epoch: [21] [1710/4276] eta: 2:05:27 lr: 2.510005731908368e-05 loss: 0.1088 (0.1139) time: 2.9299 data: 0.0086 max mem: 33300 +Epoch: [21] [1720/4276] eta: 2:04:58 lr: 2.5097216964311372e-05 loss: 0.1061 (0.1138) time: 2.9292 data: 0.0087 max mem: 33300 +Epoch: [21] [1730/4276] eta: 2:04:28 lr: 2.509437657382145e-05 loss: 0.1060 (0.1138) time: 2.9325 data: 0.0081 max mem: 33300 +Epoch: [21] [1740/4276] eta: 2:03:59 lr: 2.5091536147608952e-05 loss: 0.1089 (0.1138) time: 2.9330 data: 0.0080 max mem: 33300 +Epoch: [21] [1750/4276] eta: 2:03:30 lr: 2.508869568566895e-05 loss: 0.1116 (0.1138) time: 2.9337 data: 0.0083 max mem: 33300 +Epoch: [21] [1760/4276] eta: 2:03:00 lr: 2.5085855187996493e-05 loss: 0.0956 (0.1137) time: 2.9319 data: 0.0085 max mem: 33300 +Epoch: [21] [1770/4276] eta: 2:02:31 lr: 2.5083014654586647e-05 loss: 0.1025 (0.1137) time: 2.9350 data: 0.0082 max mem: 33300 +Epoch: [21] [1780/4276] eta: 2:02:02 lr: 2.508017408543445e-05 loss: 0.1019 (0.1136) time: 2.9362 data: 0.0080 max mem: 33300 +Epoch: [21] [1790/4276] eta: 2:01:32 lr: 2.507733348053496e-05 loss: 0.0943 (0.1135) time: 2.9327 data: 0.0082 max mem: 33300 +Epoch: [21] [1800/4276] eta: 2:01:03 lr: 2.507449283988323e-05 loss: 0.0970 (0.1135) time: 2.9334 data: 0.0083 max mem: 33300 +Epoch: [21] [1810/4276] eta: 2:00:34 lr: 2.5071652163474314e-05 loss: 0.1023 (0.1135) time: 2.9327 data: 0.0081 max mem: 33300 +Epoch: [21] [1820/4276] eta: 2:00:04 lr: 2.5068811451303247e-05 loss: 0.1114 (0.1135) time: 2.9159 data: 0.0082 max mem: 33300 +Epoch: [21] [1830/4276] eta: 1:59:34 lr: 2.506597070336509e-05 loss: 0.1100 (0.1135) time: 2.8842 data: 0.0088 max mem: 33300 +Epoch: [21] [1840/4276] eta: 1:59:04 lr: 2.506312991965489e-05 loss: 0.1009 (0.1134) time: 2.8940 data: 0.0092 max mem: 33300 +Epoch: [21] [1850/4276] eta: 1:58:35 lr: 2.506028910016767e-05 loss: 0.0957 (0.1134) time: 2.9266 data: 0.0091 max mem: 33300 +Epoch: [21] [1860/4276] eta: 1:58:06 lr: 2.5057448244898492e-05 loss: 0.1083 (0.1134) time: 2.9315 data: 0.0083 max mem: 33300 +Epoch: [21] [1870/4276] eta: 1:57:36 lr: 2.505460735384239e-05 loss: 0.1083 (0.1134) time: 2.9305 data: 0.0081 max mem: 33300 +Epoch: [21] [1880/4276] eta: 1:57:07 lr: 2.5051766426994418e-05 loss: 0.1074 (0.1134) time: 2.9310 data: 0.0083 max mem: 33300 +Epoch: [21] [1890/4276] eta: 1:56:38 lr: 2.5048925464349593e-05 loss: 0.0996 (0.1134) time: 2.9326 data: 0.0081 max mem: 33300 +Epoch: [21] [1900/4276] eta: 1:56:08 lr: 2.5046084465902968e-05 loss: 0.0988 (0.1134) time: 2.9308 data: 0.0078 max mem: 33300 +Epoch: [21] [1910/4276] eta: 1:55:39 lr: 2.504324343164957e-05 loss: 0.0985 (0.1133) time: 2.9305 data: 0.0081 max mem: 33300 +Epoch: [21] [1920/4276] eta: 1:55:09 lr: 2.5040402361584454e-05 loss: 0.0950 (0.1133) time: 2.9315 data: 0.0084 max mem: 33300 +Epoch: [21] [1930/4276] eta: 1:54:40 lr: 2.5037561255702624e-05 loss: 0.0931 (0.1132) time: 2.9333 data: 0.0084 max mem: 33300 +Epoch: [21] [1940/4276] eta: 1:54:11 lr: 2.5034720113999133e-05 loss: 0.0961 (0.1132) time: 2.9353 data: 0.0083 max mem: 33300 +Epoch: [21] [1950/4276] eta: 1:53:42 lr: 2.503187893646901e-05 loss: 0.1052 (0.1132) time: 2.9334 data: 0.0083 max mem: 33300 +Epoch: [21] [1960/4276] eta: 1:53:12 lr: 2.5029037723107285e-05 loss: 0.1020 (0.1131) time: 2.9327 data: 0.0083 max mem: 33300 +Epoch: [21] [1970/4276] eta: 1:52:43 lr: 2.5026196473908974e-05 loss: 0.0921 (0.1130) time: 2.9319 data: 0.0081 max mem: 33300 +Epoch: [21] [1980/4276] eta: 1:52:14 lr: 2.5023355188869118e-05 loss: 0.0940 (0.1130) time: 2.9325 data: 0.0079 max mem: 33300 +Epoch: [21] [1990/4276] eta: 1:51:44 lr: 2.5020513867982736e-05 loss: 0.1104 (0.1131) time: 2.9310 data: 0.0081 max mem: 33300 +Epoch: [21] [2000/4276] eta: 1:51:15 lr: 2.5017672511244865e-05 loss: 0.1104 (0.1131) time: 2.9329 data: 0.0084 max mem: 33300 +Epoch: [21] [2010/4276] eta: 1:50:46 lr: 2.501483111865051e-05 loss: 0.1103 (0.1131) time: 2.9342 data: 0.0082 max mem: 33300 +Epoch: [21] [2020/4276] eta: 1:50:16 lr: 2.5011989690194704e-05 loss: 0.1134 (0.1131) time: 2.9264 data: 0.0080 max mem: 33300 +Epoch: [21] [2030/4276] eta: 1:49:46 lr: 2.5009148225872464e-05 loss: 0.0965 (0.1130) time: 2.9129 data: 0.0085 max mem: 33300 +Epoch: [21] [2040/4276] eta: 1:49:17 lr: 2.500630672567882e-05 loss: 0.0904 (0.1130) time: 2.9191 data: 0.0092 max mem: 33300 +Epoch: [21] [2050/4276] eta: 1:48:48 lr: 2.5003465189608765e-05 loss: 0.1029 (0.1130) time: 2.9329 data: 0.0091 max mem: 33300 +Epoch: [21] [2060/4276] eta: 1:48:18 lr: 2.500062361765734e-05 loss: 0.1067 (0.1130) time: 2.9321 data: 0.0085 max mem: 33300 +Epoch: [21] [2070/4276] eta: 1:47:49 lr: 2.499778200981955e-05 loss: 0.1054 (0.1130) time: 2.9197 data: 0.0086 max mem: 33300 +Epoch: [21] [2080/4276] eta: 1:47:19 lr: 2.4994940366090418e-05 loss: 0.1054 (0.1131) time: 2.9199 data: 0.0088 max mem: 33300 +Epoch: [21] [2090/4276] eta: 1:46:50 lr: 2.499209868646494e-05 loss: 0.1057 (0.1131) time: 2.9328 data: 0.0081 max mem: 33300 +Epoch: [21] [2100/4276] eta: 1:46:21 lr: 2.4989256970938137e-05 loss: 0.1128 (0.1131) time: 2.9328 data: 0.0076 max mem: 33300 +Epoch: [21] [2110/4276] eta: 1:45:52 lr: 2.4986415219505027e-05 loss: 0.1086 (0.1131) time: 2.9325 data: 0.0077 max mem: 33300 +Epoch: [21] [2120/4276] eta: 1:45:22 lr: 2.4983573432160603e-05 loss: 0.0980 (0.1130) time: 2.9317 data: 0.0077 max mem: 33300 +Epoch: [21] [2130/4276] eta: 1:44:53 lr: 2.498073160889988e-05 loss: 0.0870 (0.1129) time: 2.9318 data: 0.0075 max mem: 33300 +Epoch: [21] [2140/4276] eta: 1:44:24 lr: 2.4977889749717867e-05 loss: 0.1019 (0.1129) time: 2.9322 data: 0.0076 max mem: 33300 +Epoch: [21] [2150/4276] eta: 1:43:54 lr: 2.497504785460957e-05 loss: 0.1071 (0.1128) time: 2.9377 data: 0.0078 max mem: 33300 +Epoch: [21] [2160/4276] eta: 1:43:25 lr: 2.4972205923569985e-05 loss: 0.0940 (0.1128) time: 2.9377 data: 0.0077 max mem: 33300 +Epoch: [21] [2170/4276] eta: 1:42:56 lr: 2.4969363956594115e-05 loss: 0.1067 (0.1128) time: 2.9323 data: 0.0075 max mem: 33300 +Epoch: [21] [2180/4276] eta: 1:42:26 lr: 2.4966521953676967e-05 loss: 0.1067 (0.1127) time: 2.9323 data: 0.0073 max mem: 33300 +Epoch: [21] [2190/4276] eta: 1:41:57 lr: 2.496367991481354e-05 loss: 0.1003 (0.1127) time: 2.9349 data: 0.0073 max mem: 33300 +Epoch: [21] [2200/4276] eta: 1:41:28 lr: 2.4960837839998824e-05 loss: 0.1135 (0.1128) time: 2.9363 data: 0.0076 max mem: 33300 +Epoch: [21] [2210/4276] eta: 1:40:58 lr: 2.4957995729227822e-05 loss: 0.1142 (0.1128) time: 2.9333 data: 0.0076 max mem: 33300 +Epoch: [21] [2220/4276] eta: 1:40:29 lr: 2.4955153582495524e-05 loss: 0.1081 (0.1128) time: 2.9311 data: 0.0074 max mem: 33300 +Epoch: [21] [2230/4276] eta: 1:40:00 lr: 2.4952311399796937e-05 loss: 0.1095 (0.1128) time: 2.9323 data: 0.0079 max mem: 33300 +Epoch: [21] [2240/4276] eta: 1:39:30 lr: 2.4949469181127043e-05 loss: 0.0920 (0.1127) time: 2.9321 data: 0.0082 max mem: 33300 +Epoch: [21] [2250/4276] eta: 1:39:01 lr: 2.4946626926480833e-05 loss: 0.0933 (0.1127) time: 2.9311 data: 0.0077 max mem: 33300 +Epoch: [21] [2260/4276] eta: 1:38:32 lr: 2.4943784635853298e-05 loss: 0.1110 (0.1127) time: 2.9332 data: 0.0076 max mem: 33300 +Epoch: [21] [2270/4276] eta: 1:38:02 lr: 2.4940942309239435e-05 loss: 0.1023 (0.1127) time: 2.9342 data: 0.0078 max mem: 33300 +Epoch: [21] [2280/4276] eta: 1:37:33 lr: 2.493809994663422e-05 loss: 0.1036 (0.1127) time: 2.9377 data: 0.0078 max mem: 33300 +Epoch: [21] [2290/4276] eta: 1:37:04 lr: 2.493525754803265e-05 loss: 0.1050 (0.1127) time: 2.9364 data: 0.0075 max mem: 33300 +Epoch: [21] [2300/4276] eta: 1:36:34 lr: 2.4932415113429695e-05 loss: 0.1036 (0.1126) time: 2.9314 data: 0.0075 max mem: 33300 +Epoch: [21] [2310/4276] eta: 1:36:05 lr: 2.492957264282036e-05 loss: 0.1068 (0.1127) time: 2.9321 data: 0.0077 max mem: 33300 +Epoch: [21] [2320/4276] eta: 1:35:36 lr: 2.4926730136199606e-05 loss: 0.1123 (0.1127) time: 2.9327 data: 0.0078 max mem: 33300 +Epoch: [21] [2330/4276] eta: 1:35:07 lr: 2.492388759356243e-05 loss: 0.1215 (0.1128) time: 2.9341 data: 0.0077 max mem: 33300 +Epoch: [21] [2340/4276] eta: 1:34:37 lr: 2.4921045014903796e-05 loss: 0.1145 (0.1128) time: 2.9343 data: 0.0075 max mem: 33300 +Epoch: [21] [2350/4276] eta: 1:34:08 lr: 2.4918202400218697e-05 loss: 0.1113 (0.1128) time: 2.9345 data: 0.0077 max mem: 33300 +Epoch: [21] [2360/4276] eta: 1:33:39 lr: 2.49153597495021e-05 loss: 0.1178 (0.1128) time: 2.9336 data: 0.0077 max mem: 33300 +Epoch: [21] [2370/4276] eta: 1:33:09 lr: 2.4912517062748986e-05 loss: 0.1178 (0.1129) time: 2.9323 data: 0.0076 max mem: 33300 +Epoch: [21] [2380/4276] eta: 1:32:40 lr: 2.4909674339954324e-05 loss: 0.1197 (0.1129) time: 2.9346 data: 0.0076 max mem: 33300 +Epoch: [21] [2390/4276] eta: 1:32:11 lr: 2.4906831581113098e-05 loss: 0.1099 (0.1129) time: 2.9419 data: 0.0075 max mem: 33300 +Epoch: [21] [2400/4276] eta: 1:31:41 lr: 2.4903988786220262e-05 loss: 0.1160 (0.1130) time: 2.9430 data: 0.0076 max mem: 33300 +Epoch: [21] [2410/4276] eta: 1:31:12 lr: 2.4901145955270796e-05 loss: 0.1124 (0.1129) time: 2.9347 data: 0.0076 max mem: 33300 +Epoch: [21] [2420/4276] eta: 1:30:43 lr: 2.4898303088259674e-05 loss: 0.1016 (0.1129) time: 2.9317 data: 0.0077 max mem: 33300 +Epoch: [21] [2430/4276] eta: 1:30:13 lr: 2.4895460185181853e-05 loss: 0.1112 (0.1130) time: 2.9307 data: 0.0079 max mem: 33300 +Epoch: [21] [2440/4276] eta: 1:29:44 lr: 2.4892617246032303e-05 loss: 0.1136 (0.1129) time: 2.9304 data: 0.0077 max mem: 33300 +Epoch: [21] [2450/4276] eta: 1:29:15 lr: 2.4889774270805994e-05 loss: 0.1062 (0.1129) time: 2.9325 data: 0.0075 max mem: 33300 +Epoch: [21] [2460/4276] eta: 1:28:45 lr: 2.4886931259497883e-05 loss: 0.1174 (0.1130) time: 2.9348 data: 0.0076 max mem: 33300 +Epoch: [21] [2470/4276] eta: 1:28:16 lr: 2.4884088212102933e-05 loss: 0.1203 (0.1130) time: 2.9387 data: 0.0078 max mem: 33300 +Epoch: [21] [2480/4276] eta: 1:27:47 lr: 2.4881245128616103e-05 loss: 0.1203 (0.1131) time: 2.9368 data: 0.0079 max mem: 33300 +Epoch: [21] [2490/4276] eta: 1:27:18 lr: 2.4878402009032357e-05 loss: 0.1066 (0.1130) time: 2.9309 data: 0.0076 max mem: 33300 +Epoch: [21] [2500/4276] eta: 1:26:48 lr: 2.4875558853346658e-05 loss: 0.1057 (0.1131) time: 2.9207 data: 0.0074 max mem: 33300 +Epoch: [21] [2510/4276] eta: 1:26:19 lr: 2.487271566155395e-05 loss: 0.1168 (0.1131) time: 2.9218 data: 0.0072 max mem: 33300 +Epoch: [21] [2520/4276] eta: 1:25:49 lr: 2.486987243364919e-05 loss: 0.1026 (0.1130) time: 2.9322 data: 0.0072 max mem: 33300 +Epoch: [21] [2530/4276] eta: 1:25:20 lr: 2.4867029169627343e-05 loss: 0.0880 (0.1130) time: 2.9318 data: 0.0072 max mem: 33300 +Epoch: [21] [2540/4276] eta: 1:24:51 lr: 2.4864185869483356e-05 loss: 0.1028 (0.1130) time: 2.9333 data: 0.0072 max mem: 33300 +Epoch: [21] [2550/4276] eta: 1:24:21 lr: 2.4861342533212174e-05 loss: 0.1001 (0.1129) time: 2.9343 data: 0.0072 max mem: 33300 +Epoch: [21] [2560/4276] eta: 1:23:52 lr: 2.485849916080875e-05 loss: 0.0923 (0.1129) time: 2.9327 data: 0.0071 max mem: 33300 +Epoch: [21] [2570/4276] eta: 1:23:23 lr: 2.485565575226804e-05 loss: 0.0879 (0.1128) time: 2.9328 data: 0.0072 max mem: 33300 +Epoch: [21] [2580/4276] eta: 1:22:53 lr: 2.4852812307584988e-05 loss: 0.0906 (0.1128) time: 2.9346 data: 0.0072 max mem: 33300 +Epoch: [21] [2590/4276] eta: 1:22:24 lr: 2.4849968826754535e-05 loss: 0.0980 (0.1127) time: 2.9329 data: 0.0072 max mem: 33300 +Epoch: [21] [2600/4276] eta: 1:21:55 lr: 2.4847125309771627e-05 loss: 0.0980 (0.1127) time: 2.9378 data: 0.0072 max mem: 33300 +Epoch: [21] [2610/4276] eta: 1:21:26 lr: 2.484428175663121e-05 loss: 0.0876 (0.1126) time: 2.9407 data: 0.0071 max mem: 33300 +Epoch: [21] [2620/4276] eta: 1:20:56 lr: 2.4841438167328228e-05 loss: 0.0914 (0.1126) time: 2.9336 data: 0.0072 max mem: 33300 +Epoch: [21] [2630/4276] eta: 1:20:27 lr: 2.4838594541857615e-05 loss: 0.0989 (0.1126) time: 2.9299 data: 0.0074 max mem: 33300 +Epoch: [21] [2640/4276] eta: 1:19:58 lr: 2.483575088021431e-05 loss: 0.0991 (0.1125) time: 2.9313 data: 0.0073 max mem: 33300 +Epoch: [21] [2650/4276] eta: 1:19:28 lr: 2.4832907182393258e-05 loss: 0.1004 (0.1125) time: 2.9379 data: 0.0072 max mem: 33300 +Epoch: [21] [2660/4276] eta: 1:18:59 lr: 2.48300634483894e-05 loss: 0.1118 (0.1126) time: 2.9398 data: 0.0072 max mem: 33300 +Epoch: [21] [2670/4276] eta: 1:18:30 lr: 2.482721967819765e-05 loss: 0.1215 (0.1126) time: 2.9363 data: 0.0075 max mem: 33300 +Epoch: [21] [2680/4276] eta: 1:18:00 lr: 2.482437587181296e-05 loss: 0.1239 (0.1127) time: 2.9341 data: 0.0074 max mem: 33300 +Epoch: [21] [2690/4276] eta: 1:17:31 lr: 2.4821532029230254e-05 loss: 0.1117 (0.1126) time: 2.9333 data: 0.0072 max mem: 33300 +Epoch: [21] [2700/4276] eta: 1:17:02 lr: 2.4818688150444473e-05 loss: 0.1043 (0.1126) time: 2.9345 data: 0.0072 max mem: 33300 +Epoch: [21] [2710/4276] eta: 1:16:32 lr: 2.4815844235450532e-05 loss: 0.1035 (0.1126) time: 2.9336 data: 0.0074 max mem: 33300 +Epoch: [21] [2720/4276] eta: 1:16:03 lr: 2.481300028424337e-05 loss: 0.0917 (0.1126) time: 2.9325 data: 0.0077 max mem: 33300 +Epoch: [21] [2730/4276] eta: 1:15:34 lr: 2.4810156296817917e-05 loss: 0.1022 (0.1126) time: 2.9316 data: 0.0075 max mem: 33300 +Epoch: [21] [2740/4276] eta: 1:15:04 lr: 2.4807312273169086e-05 loss: 0.1174 (0.1126) time: 2.9277 data: 0.0073 max mem: 33300 +Epoch: [21] [2750/4276] eta: 1:14:35 lr: 2.480446821329181e-05 loss: 0.1186 (0.1127) time: 2.9303 data: 0.0075 max mem: 33300 +Epoch: [21] [2760/4276] eta: 1:14:06 lr: 2.4801624117181007e-05 loss: 0.1124 (0.1127) time: 2.9355 data: 0.0077 max mem: 33300 +Epoch: [21] [2770/4276] eta: 1:13:36 lr: 2.4798779984831608e-05 loss: 0.1098 (0.1127) time: 2.9351 data: 0.0078 max mem: 33300 +Epoch: [21] [2780/4276] eta: 1:13:07 lr: 2.4795935816238522e-05 loss: 0.1092 (0.1127) time: 2.9360 data: 0.0076 max mem: 33300 +Epoch: [21] [2790/4276] eta: 1:12:38 lr: 2.4793091611396672e-05 loss: 0.1187 (0.1128) time: 2.9352 data: 0.0076 max mem: 33300 +Epoch: [21] [2800/4276] eta: 1:12:08 lr: 2.4790247370300975e-05 loss: 0.1110 (0.1127) time: 2.9334 data: 0.0077 max mem: 33300 +Epoch: [21] [2810/4276] eta: 1:11:39 lr: 2.4787403092946352e-05 loss: 0.0913 (0.1126) time: 2.9360 data: 0.0077 max mem: 33300 +Epoch: [21] [2820/4276] eta: 1:11:10 lr: 2.4784558779327715e-05 loss: 0.0913 (0.1126) time: 2.9377 data: 0.0076 max mem: 33300 +Epoch: [21] [2830/4276] eta: 1:10:40 lr: 2.4781714429439973e-05 loss: 0.0993 (0.1126) time: 2.9372 data: 0.0076 max mem: 33300 +Epoch: [21] [2840/4276] eta: 1:10:11 lr: 2.477887004327804e-05 loss: 0.1249 (0.1127) time: 2.9374 data: 0.0077 max mem: 33300 +Epoch: [21] [2850/4276] eta: 1:09:42 lr: 2.4776025620836834e-05 loss: 0.1220 (0.1127) time: 2.9384 data: 0.0077 max mem: 33300 +Epoch: [21] [2860/4276] eta: 1:09:13 lr: 2.4773181162111254e-05 loss: 0.1093 (0.1127) time: 2.9378 data: 0.0075 max mem: 33300 +Epoch: [21] [2870/4276] eta: 1:08:43 lr: 2.477033666709621e-05 loss: 0.0986 (0.1127) time: 2.9351 data: 0.0075 max mem: 33300 +Epoch: [21] [2880/4276] eta: 1:08:14 lr: 2.4767492135786613e-05 loss: 0.1033 (0.1127) time: 2.9342 data: 0.0075 max mem: 33300 +Epoch: [21] [2890/4276] eta: 1:07:45 lr: 2.476464756817737e-05 loss: 0.1033 (0.1127) time: 2.9357 data: 0.0075 max mem: 33300 +Epoch: [21] [2900/4276] eta: 1:07:15 lr: 2.4761802964263377e-05 loss: 0.0967 (0.1126) time: 2.9355 data: 0.0078 max mem: 33300 +Epoch: [21] [2910/4276] eta: 1:06:46 lr: 2.4758958324039538e-05 loss: 0.1027 (0.1126) time: 2.9358 data: 0.0078 max mem: 33300 +Epoch: [21] [2920/4276] eta: 1:06:17 lr: 2.4756113647500757e-05 loss: 0.1052 (0.1126) time: 2.9352 data: 0.0077 max mem: 33300 +Epoch: [21] [2930/4276] eta: 1:05:47 lr: 2.4753268934641943e-05 loss: 0.0987 (0.1126) time: 2.9335 data: 0.0077 max mem: 33300 +Epoch: [21] [2940/4276] eta: 1:05:18 lr: 2.4750424185457977e-05 loss: 0.0956 (0.1126) time: 2.9315 data: 0.0076 max mem: 33300 +Epoch: [21] [2950/4276] eta: 1:04:49 lr: 2.4747579399943763e-05 loss: 0.0991 (0.1126) time: 2.9264 data: 0.0077 max mem: 33300 +Epoch: [21] [2960/4276] eta: 1:04:19 lr: 2.4744734578094196e-05 loss: 0.1093 (0.1126) time: 2.9297 data: 0.0079 max mem: 33300 +Epoch: [21] [2970/4276] eta: 1:03:50 lr: 2.4741889719904175e-05 loss: 0.1116 (0.1126) time: 2.9378 data: 0.0077 max mem: 33300 +Epoch: [21] [2980/4276] eta: 1:03:21 lr: 2.473904482536859e-05 loss: 0.1176 (0.1126) time: 2.9387 data: 0.0076 max mem: 33300 +Epoch: [21] [2990/4276] eta: 1:02:51 lr: 2.473619989448233e-05 loss: 0.1087 (0.1126) time: 2.9327 data: 0.0075 max mem: 33300 +Epoch: [21] [3000/4276] eta: 1:02:22 lr: 2.4733354927240286e-05 loss: 0.0955 (0.1126) time: 2.9289 data: 0.0077 max mem: 33300 +Epoch: [21] [3010/4276] eta: 1:01:53 lr: 2.4730509923637354e-05 loss: 0.1061 (0.1126) time: 2.9313 data: 0.0078 max mem: 33300 +Epoch: [21] [3020/4276] eta: 1:01:23 lr: 2.472766488366841e-05 loss: 0.1152 (0.1126) time: 2.9320 data: 0.0076 max mem: 33300 +Epoch: [21] [3030/4276] eta: 1:00:54 lr: 2.4724819807328345e-05 loss: 0.1147 (0.1126) time: 2.9323 data: 0.0076 max mem: 33300 +Epoch: [21] [3040/4276] eta: 1:00:25 lr: 2.472197469461205e-05 loss: 0.1163 (0.1127) time: 2.9382 data: 0.0078 max mem: 33300 +Epoch: [21] [3050/4276] eta: 0:59:55 lr: 2.4719129545514396e-05 loss: 0.1096 (0.1126) time: 2.9391 data: 0.0079 max mem: 33300 +Epoch: [21] [3060/4276] eta: 0:59:26 lr: 2.4716284360030272e-05 loss: 0.0941 (0.1126) time: 2.9359 data: 0.0077 max mem: 33300 +Epoch: [21] [3070/4276] eta: 0:58:57 lr: 2.471343913815456e-05 loss: 0.0989 (0.1126) time: 2.9370 data: 0.0075 max mem: 33300 +Epoch: [21] [3080/4276] eta: 0:58:27 lr: 2.4710593879882136e-05 loss: 0.1075 (0.1125) time: 2.9370 data: 0.0077 max mem: 33300 +Epoch: [21] [3090/4276] eta: 0:57:58 lr: 2.4707748585207882e-05 loss: 0.0986 (0.1125) time: 2.9338 data: 0.0078 max mem: 33300 +Epoch: [21] [3100/4276] eta: 0:57:29 lr: 2.4704903254126665e-05 loss: 0.0974 (0.1124) time: 2.9327 data: 0.0076 max mem: 33300 +Epoch: [21] [3110/4276] eta: 0:56:59 lr: 2.470205788663337e-05 loss: 0.0969 (0.1124) time: 2.9344 data: 0.0075 max mem: 33300 +Epoch: [21] [3120/4276] eta: 0:56:30 lr: 2.4699212482722872e-05 loss: 0.1038 (0.1124) time: 2.9336 data: 0.0077 max mem: 33300 +Epoch: [21] [3130/4276] eta: 0:56:01 lr: 2.469636704239003e-05 loss: 0.1096 (0.1124) time: 2.9322 data: 0.0078 max mem: 33300 +Epoch: [21] [3140/4276] eta: 0:55:31 lr: 2.4693521565629728e-05 loss: 0.1108 (0.1124) time: 2.9324 data: 0.0076 max mem: 33300 +Epoch: [21] [3150/4276] eta: 0:55:02 lr: 2.4690676052436826e-05 loss: 0.1149 (0.1124) time: 2.9326 data: 0.0076 max mem: 33300 +Epoch: [21] [3160/4276] eta: 0:54:33 lr: 2.4687830502806204e-05 loss: 0.1134 (0.1124) time: 2.9323 data: 0.0078 max mem: 33300 +Epoch: [21] [3170/4276] eta: 0:54:03 lr: 2.4684984916732718e-05 loss: 0.1065 (0.1124) time: 2.9371 data: 0.0077 max mem: 33300 +Epoch: [21] [3180/4276] eta: 0:53:34 lr: 2.4682139294211235e-05 loss: 0.1066 (0.1124) time: 2.9373 data: 0.0075 max mem: 33300 +Epoch: [21] [3190/4276] eta: 0:53:05 lr: 2.467929363523662e-05 loss: 0.1129 (0.1125) time: 2.9332 data: 0.0076 max mem: 33300 +Epoch: [21] [3200/4276] eta: 0:52:35 lr: 2.4676447939803745e-05 loss: 0.1129 (0.1125) time: 2.9348 data: 0.0077 max mem: 33300 +Epoch: [21] [3210/4276] eta: 0:52:06 lr: 2.4673602207907458e-05 loss: 0.1156 (0.1125) time: 2.9346 data: 0.0077 max mem: 33300 +Epoch: [21] [3220/4276] eta: 0:51:37 lr: 2.4670756439542622e-05 loss: 0.1050 (0.1125) time: 2.9333 data: 0.0076 max mem: 33300 +Epoch: [21] [3230/4276] eta: 0:51:08 lr: 2.46679106347041e-05 loss: 0.1105 (0.1125) time: 2.9330 data: 0.0076 max mem: 33300 +Epoch: [21] [3240/4276] eta: 0:50:38 lr: 2.466506479338675e-05 loss: 0.1208 (0.1126) time: 2.9327 data: 0.0077 max mem: 33300 +Epoch: [21] [3250/4276] eta: 0:50:09 lr: 2.4662218915585416e-05 loss: 0.1261 (0.1127) time: 2.9323 data: 0.0077 max mem: 33300 +Epoch: [21] [3260/4276] eta: 0:49:39 lr: 2.4659373001294964e-05 loss: 0.1161 (0.1127) time: 2.9304 data: 0.0076 max mem: 33300 +Epoch: [21] [3270/4276] eta: 0:49:10 lr: 2.4656527050510242e-05 loss: 0.1158 (0.1127) time: 2.9360 data: 0.0075 max mem: 33300 +Epoch: [21] [3280/4276] eta: 0:48:41 lr: 2.465368106322611e-05 loss: 0.1137 (0.1127) time: 2.9481 data: 0.0077 max mem: 33300 +Epoch: [21] [3290/4276] eta: 0:48:12 lr: 2.4650835039437404e-05 loss: 0.1082 (0.1127) time: 2.9528 data: 0.0076 max mem: 33300 +Epoch: [21] [3300/4276] eta: 0:47:42 lr: 2.464798897913898e-05 loss: 0.1193 (0.1128) time: 2.9513 data: 0.0073 max mem: 33300 +Epoch: [21] [3310/4276] eta: 0:47:13 lr: 2.4645142882325687e-05 loss: 0.1349 (0.1128) time: 2.9667 data: 0.0073 max mem: 33300 +Epoch: [21] [3320/4276] eta: 0:46:44 lr: 2.4642296748992372e-05 loss: 0.1282 (0.1128) time: 2.9575 data: 0.0074 max mem: 33300 +Epoch: [21] [3330/4276] eta: 0:46:15 lr: 2.4639450579133875e-05 loss: 0.1140 (0.1128) time: 2.9634 data: 0.0076 max mem: 33300 +Epoch: [21] [3340/4276] eta: 0:45:46 lr: 2.4636604372745036e-05 loss: 0.1124 (0.1128) time: 3.0351 data: 0.0079 max mem: 33300 +Epoch: [21] [3350/4276] eta: 0:45:17 lr: 2.4633758129820714e-05 loss: 0.1043 (0.1128) time: 3.0826 data: 0.0080 max mem: 33300 +Epoch: [21] [3360/4276] eta: 0:44:48 lr: 2.4630911850355727e-05 loss: 0.0987 (0.1128) time: 3.0520 data: 0.0079 max mem: 33300 +Epoch: [21] [3370/4276] eta: 0:44:18 lr: 2.4628065534344927e-05 loss: 0.1052 (0.1128) time: 2.9776 data: 0.0078 max mem: 33300 +Epoch: [21] [3380/4276] eta: 0:43:49 lr: 2.4625219181783148e-05 loss: 0.1029 (0.1128) time: 2.9367 data: 0.0075 max mem: 33300 +Epoch: [21] [3390/4276] eta: 0:43:20 lr: 2.4622372792665236e-05 loss: 0.1030 (0.1128) time: 2.9328 data: 0.0075 max mem: 33300 +Epoch: [21] [3400/4276] eta: 0:42:50 lr: 2.4619526366986008e-05 loss: 0.1126 (0.1128) time: 2.9331 data: 0.0077 max mem: 33300 +Epoch: [21] [3410/4276] eta: 0:42:21 lr: 2.461667990474031e-05 loss: 0.1065 (0.1128) time: 2.9316 data: 0.0077 max mem: 33300 +Epoch: [21] [3420/4276] eta: 0:41:52 lr: 2.4613833405922967e-05 loss: 0.1074 (0.1129) time: 2.9294 data: 0.0076 max mem: 33300 +Epoch: [21] [3430/4276] eta: 0:41:22 lr: 2.461098687052882e-05 loss: 0.1155 (0.1129) time: 2.9297 data: 0.0077 max mem: 33300 +Epoch: [21] [3440/4276] eta: 0:40:53 lr: 2.460814029855269e-05 loss: 0.1034 (0.1129) time: 2.9309 data: 0.0078 max mem: 33300 +Epoch: [21] [3450/4276] eta: 0:40:24 lr: 2.4605293689989404e-05 loss: 0.1034 (0.1130) time: 2.9302 data: 0.0080 max mem: 33300 +Epoch: [21] [3460/4276] eta: 0:39:54 lr: 2.460244704483379e-05 loss: 0.1250 (0.1130) time: 2.9241 data: 0.0079 max mem: 33300 +Epoch: [21] [3470/4276] eta: 0:39:25 lr: 2.4599600363080684e-05 loss: 0.1051 (0.1130) time: 2.9234 data: 0.0075 max mem: 33300 +Epoch: [21] [3480/4276] eta: 0:38:55 lr: 2.4596753644724894e-05 loss: 0.1028 (0.1130) time: 2.9300 data: 0.0076 max mem: 33300 +Epoch: [21] [3490/4276] eta: 0:38:26 lr: 2.4593906889761245e-05 loss: 0.1117 (0.1130) time: 2.9705 data: 0.0080 max mem: 33300 +Epoch: [21] [3500/4276] eta: 0:37:57 lr: 2.4591060098184562e-05 loss: 0.1036 (0.1130) time: 2.9670 data: 0.0080 max mem: 33300 +Epoch: [21] [3510/4276] eta: 0:37:27 lr: 2.458821326998967e-05 loss: 0.0998 (0.1130) time: 2.9184 data: 0.0077 max mem: 33300 +Epoch: [21] [3520/4276] eta: 0:36:58 lr: 2.4585366405171377e-05 loss: 0.0998 (0.1129) time: 2.9155 data: 0.0078 max mem: 33300 +Epoch: [21] [3530/4276] eta: 0:36:29 lr: 2.4582519503724506e-05 loss: 0.1028 (0.1129) time: 2.9236 data: 0.0078 max mem: 33300 +Epoch: [21] [3540/4276] eta: 0:36:00 lr: 2.4579672565643867e-05 loss: 0.1216 (0.1130) time: 2.9651 data: 0.0075 max mem: 33300 +Epoch: [21] [3550/4276] eta: 0:35:30 lr: 2.4576825590924282e-05 loss: 0.1145 (0.1129) time: 3.0419 data: 0.0075 max mem: 33300 +Epoch: [21] [3560/4276] eta: 0:35:01 lr: 2.457397857956055e-05 loss: 0.0998 (0.1130) time: 3.0807 data: 0.0075 max mem: 33300 +Epoch: [21] [3570/4276] eta: 0:34:32 lr: 2.4571131531547497e-05 loss: 0.1126 (0.1130) time: 3.0749 data: 0.0078 max mem: 33300 +Epoch: [21] [3580/4276] eta: 0:34:03 lr: 2.4568284446879925e-05 loss: 0.0998 (0.1130) time: 3.0755 data: 0.0079 max mem: 33300 +Epoch: [21] [3590/4276] eta: 0:33:34 lr: 2.456543732555265e-05 loss: 0.0998 (0.1130) time: 3.0807 data: 0.0081 max mem: 33300 +Epoch: [21] [3600/4276] eta: 0:33:05 lr: 2.456259016756046e-05 loss: 0.1221 (0.1130) time: 3.0800 data: 0.0082 max mem: 33300 +Epoch: [21] [3610/4276] eta: 0:32:36 lr: 2.455974297289818e-05 loss: 0.1110 (0.1130) time: 3.0791 data: 0.0080 max mem: 33300 +Epoch: [21] [3620/4276] eta: 0:32:07 lr: 2.4556895741560606e-05 loss: 0.1098 (0.1130) time: 3.0782 data: 0.0079 max mem: 33300 +Epoch: [21] [3630/4276] eta: 0:31:38 lr: 2.4554048473542545e-05 loss: 0.1049 (0.1130) time: 3.0796 data: 0.0081 max mem: 33300 +Epoch: [21] [3640/4276] eta: 0:31:09 lr: 2.4551201168838795e-05 loss: 0.0980 (0.1129) time: 3.0790 data: 0.0081 max mem: 33300 +Epoch: [21] [3650/4276] eta: 0:30:39 lr: 2.454835382744415e-05 loss: 0.0968 (0.1129) time: 3.0595 data: 0.0079 max mem: 33300 +Epoch: [21] [3660/4276] eta: 0:30:10 lr: 2.4545506449353422e-05 loss: 0.1021 (0.1129) time: 3.0309 data: 0.0082 max mem: 33300 +Epoch: [21] [3670/4276] eta: 0:29:41 lr: 2.4542659034561396e-05 loss: 0.1070 (0.1129) time: 3.0448 data: 0.0085 max mem: 33300 +Epoch: [21] [3680/4276] eta: 0:29:12 lr: 2.4539811583062873e-05 loss: 0.1128 (0.1129) time: 3.0755 data: 0.0084 max mem: 33300 +Epoch: [21] [3690/4276] eta: 0:28:43 lr: 2.4536964094852644e-05 loss: 0.1238 (0.1129) time: 3.0823 data: 0.0081 max mem: 33300 +Epoch: [21] [3700/4276] eta: 0:28:13 lr: 2.4534116569925512e-05 loss: 0.1199 (0.1129) time: 3.0753 data: 0.0080 max mem: 33300 +Epoch: [21] [3710/4276] eta: 0:27:44 lr: 2.4531269008276252e-05 loss: 0.1002 (0.1129) time: 3.0768 data: 0.0083 max mem: 33300 +Epoch: [21] [3720/4276] eta: 0:27:15 lr: 2.4528421409899665e-05 loss: 0.0980 (0.1129) time: 3.0839 data: 0.0082 max mem: 33300 +Epoch: [21] [3730/4276] eta: 0:26:46 lr: 2.4525573774790538e-05 loss: 0.1114 (0.1129) time: 3.0817 data: 0.0081 max mem: 33300 +Epoch: [21] [3740/4276] eta: 0:26:17 lr: 2.452272610294366e-05 loss: 0.1192 (0.1129) time: 3.0761 data: 0.0080 max mem: 33300 +Epoch: [21] [3750/4276] eta: 0:25:47 lr: 2.4519878394353812e-05 loss: 0.1090 (0.1129) time: 3.0756 data: 0.0079 max mem: 33300 +Epoch: [21] [3760/4276] eta: 0:25:18 lr: 2.4517030649015778e-05 loss: 0.0960 (0.1128) time: 3.0700 data: 0.0080 max mem: 33300 +Epoch: [21] [3770/4276] eta: 0:24:49 lr: 2.4514182866924344e-05 loss: 0.1018 (0.1129) time: 3.0665 data: 0.0085 max mem: 33300 +Epoch: [21] [3780/4276] eta: 0:24:20 lr: 2.45113350480743e-05 loss: 0.1018 (0.1128) time: 3.0799 data: 0.0089 max mem: 33300 +Epoch: [21] [3790/4276] eta: 0:23:50 lr: 2.4508487192460413e-05 loss: 0.0976 (0.1128) time: 3.0694 data: 0.0088 max mem: 33300 +Epoch: [21] [3800/4276] eta: 0:23:21 lr: 2.450563930007746e-05 loss: 0.1062 (0.1128) time: 3.0679 data: 0.0090 max mem: 33300 +Epoch: [21] [3810/4276] eta: 0:22:52 lr: 2.4502791370920224e-05 loss: 0.1062 (0.1128) time: 3.0835 data: 0.0085 max mem: 33300 +Epoch: [21] [3820/4276] eta: 0:22:22 lr: 2.449994340498349e-05 loss: 0.0985 (0.1128) time: 3.0644 data: 0.0082 max mem: 33300 +Epoch: [21] [3830/4276] eta: 0:21:53 lr: 2.4497095402262017e-05 loss: 0.0996 (0.1128) time: 3.0648 data: 0.0085 max mem: 33300 +Epoch: [21] [3840/4276] eta: 0:21:24 lr: 2.4494247362750586e-05 loss: 0.0975 (0.1127) time: 3.0833 data: 0.0085 max mem: 33300 +Epoch: [21] [3850/4276] eta: 0:20:55 lr: 2.4491399286443966e-05 loss: 0.0955 (0.1127) time: 3.0842 data: 0.0085 max mem: 33300 +Epoch: [21] [3860/4276] eta: 0:20:25 lr: 2.4488551173336935e-05 loss: 0.1185 (0.1127) time: 3.0859 data: 0.0085 max mem: 33300 +Epoch: [21] [3870/4276] eta: 0:19:56 lr: 2.448570302342425e-05 loss: 0.1185 (0.1127) time: 3.0918 data: 0.0084 max mem: 33300 +Epoch: [21] [3880/4276] eta: 0:19:27 lr: 2.4482854836700683e-05 loss: 0.1065 (0.1127) time: 3.0915 data: 0.0087 max mem: 33300 +Epoch: [21] [3890/4276] eta: 0:18:57 lr: 2.4480006613161e-05 loss: 0.1089 (0.1127) time: 3.0930 data: 0.0085 max mem: 33300 +Epoch: [21] [3900/4276] eta: 0:18:28 lr: 2.447715835279997e-05 loss: 0.1014 (0.1127) time: 3.0903 data: 0.0080 max mem: 33300 +Epoch: [21] [3910/4276] eta: 0:17:59 lr: 2.4474310055612352e-05 loss: 0.0892 (0.1127) time: 3.0815 data: 0.0079 max mem: 33300 +Epoch: [21] [3920/4276] eta: 0:17:29 lr: 2.44714617215929e-05 loss: 0.0898 (0.1126) time: 3.0838 data: 0.0080 max mem: 33300 +Epoch: [21] [3930/4276] eta: 0:17:00 lr: 2.4468613350736388e-05 loss: 0.0927 (0.1126) time: 3.0853 data: 0.0079 max mem: 33300 +Epoch: [21] [3940/4276] eta: 0:16:30 lr: 2.4465764943037573e-05 loss: 0.0970 (0.1126) time: 3.0841 data: 0.0077 max mem: 33300 +Epoch: [21] [3950/4276] eta: 0:16:01 lr: 2.4462916498491205e-05 loss: 0.0970 (0.1126) time: 3.0763 data: 0.0077 max mem: 33300 +Epoch: [21] [3960/4276] eta: 0:15:32 lr: 2.446006801709204e-05 loss: 0.1006 (0.1126) time: 3.0214 data: 0.0077 max mem: 33300 +Epoch: [21] [3970/4276] eta: 0:15:02 lr: 2.4457219498834842e-05 loss: 0.1121 (0.1126) time: 2.9945 data: 0.0074 max mem: 33300 +Epoch: [21] [3980/4276] eta: 0:14:33 lr: 2.4454370943714354e-05 loss: 0.0996 (0.1126) time: 3.0269 data: 0.0073 max mem: 33300 +Epoch: [21] [3990/4276] eta: 0:14:03 lr: 2.4451522351725327e-05 loss: 0.1018 (0.1126) time: 3.0133 data: 0.0075 max mem: 33300 +Epoch: [21] [4000/4276] eta: 0:13:34 lr: 2.4448673722862523e-05 loss: 0.1021 (0.1126) time: 2.9329 data: 0.0083 max mem: 33300 +Epoch: [21] [4010/4276] eta: 0:13:04 lr: 2.4445825057120684e-05 loss: 0.1021 (0.1126) time: 2.8987 data: 0.0086 max mem: 33300 +Epoch: [21] [4020/4276] eta: 0:12:35 lr: 2.4442976354494555e-05 loss: 0.1099 (0.1126) time: 2.9253 data: 0.0079 max mem: 33300 +Epoch: [21] [4030/4276] eta: 0:12:05 lr: 2.4440127614978883e-05 loss: 0.1028 (0.1125) time: 2.9293 data: 0.0075 max mem: 33300 +Epoch: [21] [4040/4276] eta: 0:11:36 lr: 2.4437278838568415e-05 loss: 0.1073 (0.1126) time: 2.9356 data: 0.0080 max mem: 33300 +Epoch: [21] [4050/4276] eta: 0:11:06 lr: 2.4434430025257895e-05 loss: 0.1077 (0.1125) time: 2.9360 data: 0.0081 max mem: 33300 +Epoch: [21] [4060/4276] eta: 0:10:37 lr: 2.443158117504206e-05 loss: 0.0949 (0.1126) time: 2.9279 data: 0.0073 max mem: 33300 +Epoch: [21] [4070/4276] eta: 0:10:07 lr: 2.4428732287915653e-05 loss: 0.1142 (0.1126) time: 2.9270 data: 0.0073 max mem: 33300 +Epoch: [21] [4080/4276] eta: 0:09:38 lr: 2.442588336387341e-05 loss: 0.1142 (0.1126) time: 2.9285 data: 0.0075 max mem: 33300 +Epoch: [21] [4090/4276] eta: 0:09:08 lr: 2.442303440291008e-05 loss: 0.1242 (0.1126) time: 2.9290 data: 0.0077 max mem: 33300 +Epoch: [21] [4100/4276] eta: 0:08:39 lr: 2.4420185405020384e-05 loss: 0.1225 (0.1126) time: 2.9291 data: 0.0081 max mem: 33300 +Epoch: [21] [4110/4276] eta: 0:08:09 lr: 2.4417336370199066e-05 loss: 0.1086 (0.1126) time: 2.9303 data: 0.0084 max mem: 33300 +Epoch: [21] [4120/4276] eta: 0:07:40 lr: 2.4414487298440854e-05 loss: 0.1080 (0.1126) time: 2.9323 data: 0.0082 max mem: 33300 +Epoch: [21] [4130/4276] eta: 0:07:10 lr: 2.4411638189740482e-05 loss: 0.1052 (0.1126) time: 2.9304 data: 0.0075 max mem: 33300 +Epoch: [21] [4140/4276] eta: 0:06:41 lr: 2.440878904409268e-05 loss: 0.1027 (0.1126) time: 2.9282 data: 0.0073 max mem: 33300 +Epoch: [21] [4150/4276] eta: 0:06:11 lr: 2.4405939861492175e-05 loss: 0.0984 (0.1126) time: 2.9301 data: 0.0075 max mem: 33300 +Epoch: [21] [4160/4276] eta: 0:05:42 lr: 2.4403090641933697e-05 loss: 0.1071 (0.1126) time: 2.9314 data: 0.0075 max mem: 33300 +Epoch: [21] [4170/4276] eta: 0:05:12 lr: 2.4400241385411974e-05 loss: 0.1103 (0.1126) time: 2.9304 data: 0.0075 max mem: 33300 +Epoch: [21] [4180/4276] eta: 0:04:43 lr: 2.4397392091921722e-05 loss: 0.1075 (0.1126) time: 2.9172 data: 0.0074 max mem: 33300 +Epoch: [21] [4190/4276] eta: 0:04:13 lr: 2.439454276145767e-05 loss: 0.1052 (0.1126) time: 2.9154 data: 0.0076 max mem: 33300 +Epoch: [21] [4200/4276] eta: 0:03:44 lr: 2.4391693394014543e-05 loss: 0.1052 (0.1127) time: 2.9271 data: 0.0079 max mem: 33300 +Epoch: [21] [4210/4276] eta: 0:03:14 lr: 2.4388843989587058e-05 loss: 0.1180 (0.1127) time: 2.9297 data: 0.0078 max mem: 33300 +Epoch: [21] [4220/4276] eta: 0:02:45 lr: 2.438599454816993e-05 loss: 0.1229 (0.1128) time: 2.9298 data: 0.0075 max mem: 33300 +Epoch: [21] [4230/4276] eta: 0:02:15 lr: 2.438314506975788e-05 loss: 0.1219 (0.1128) time: 2.9378 data: 0.0077 max mem: 33300 +Epoch: [21] [4240/4276] eta: 0:01:46 lr: 2.438029555434562e-05 loss: 0.1161 (0.1128) time: 2.9250 data: 0.0084 max mem: 33300 +Epoch: [21] [4250/4276] eta: 0:01:16 lr: 2.4377446001927875e-05 loss: 0.1149 (0.1128) time: 2.9114 data: 0.0082 max mem: 33300 +Epoch: [21] [4260/4276] eta: 0:00:47 lr: 2.4374596412499344e-05 loss: 0.1174 (0.1128) time: 2.9240 data: 0.0076 max mem: 33300 +Epoch: [21] [4270/4276] eta: 0:00:17 lr: 2.4371746786054745e-05 loss: 0.1204 (0.1129) time: 2.9260 data: 0.0074 max mem: 33300 +Epoch: [21] Total time: 3:30:08 +Test: [ 0/21770] eta: 8:36:13 time: 1.4227 data: 1.3799 max mem: 33300 +Test: [ 100/21770] eta: 0:18:51 time: 0.0387 data: 0.0009 max mem: 33300 +Test: [ 200/21770] eta: 0:16:17 time: 0.0382 data: 0.0009 max mem: 33300 +Test: [ 300/21770] eta: 0:15:22 time: 0.0381 data: 0.0009 max mem: 33300 +Test: [ 400/21770] eta: 0:14:53 time: 0.0381 data: 0.0008 max mem: 33300 +Test: [ 500/21770] eta: 0:14:35 time: 0.0386 data: 0.0008 max mem: 33300 +Test: [ 600/21770] eta: 0:14:21 time: 0.0384 data: 0.0009 max mem: 33300 +Test: [ 700/21770] eta: 0:14:09 time: 0.0380 data: 0.0009 max mem: 33300 +Test: [ 800/21770] eta: 0:13:59 time: 0.0379 data: 0.0009 max mem: 33300 +Test: [ 900/21770] eta: 0:13:50 time: 0.0379 data: 0.0009 max mem: 33300 +Test: [ 1000/21770] eta: 0:13:43 time: 0.0397 data: 0.0009 max mem: 33300 +Test: [ 1100/21770] eta: 0:13:38 time: 0.0394 data: 0.0009 max mem: 33300 +Test: [ 1200/21770] eta: 0:13:33 time: 0.0397 data: 0.0009 max mem: 33300 +Test: [ 1300/21770] eta: 0:13:29 time: 0.0393 data: 0.0009 max mem: 33300 +Test: [ 1400/21770] eta: 0:13:24 time: 0.0390 data: 0.0009 max mem: 33300 +Test: [ 1500/21770] eta: 0:13:18 time: 0.0379 data: 0.0008 max mem: 33300 +Test: [ 1600/21770] eta: 0:13:12 time: 0.0377 data: 0.0009 max mem: 33300 +Test: [ 1700/21770] eta: 0:13:06 time: 0.0378 data: 0.0009 max mem: 33300 +Test: [ 1800/21770] eta: 0:13:01 time: 0.0378 data: 0.0009 max mem: 33300 +Test: [ 1900/21770] eta: 0:12:56 time: 0.0380 data: 0.0009 max mem: 33300 +Test: [ 2000/21770] eta: 0:12:51 time: 0.0378 data: 0.0009 max mem: 33300 +Test: [ 2100/21770] eta: 0:12:46 time: 0.0379 data: 0.0009 max mem: 33300 +Test: [ 2200/21770] eta: 0:12:42 time: 0.0398 data: 0.0009 max mem: 33300 +Test: [ 2300/21770] eta: 0:12:39 time: 0.0397 data: 0.0009 max mem: 33300 +Test: [ 2400/21770] eta: 0:12:36 time: 0.0400 data: 0.0009 max mem: 33300 +Test: [ 2500/21770] eta: 0:12:33 time: 0.0398 data: 0.0009 max mem: 33300 +Test: [ 2600/21770] eta: 0:12:29 time: 0.0399 data: 0.0009 max mem: 33300 +Test: [ 2700/21770] eta: 0:12:26 time: 0.0399 data: 0.0008 max mem: 33300 +Test: [ 2800/21770] eta: 0:12:23 time: 0.0400 data: 0.0008 max mem: 33300 +Test: [ 2900/21770] eta: 0:12:19 time: 0.0400 data: 0.0008 max mem: 33300 +Test: [ 3000/21770] eta: 0:12:16 time: 0.0401 data: 0.0008 max mem: 33300 +Test: [ 3100/21770] eta: 0:12:12 time: 0.0400 data: 0.0008 max mem: 33300 +Test: [ 3200/21770] eta: 0:12:09 time: 0.0400 data: 0.0008 max mem: 33300 +Test: [ 3300/21770] eta: 0:12:05 time: 0.0400 data: 0.0008 max mem: 33300 +Test: [ 3400/21770] eta: 0:12:02 time: 0.0401 data: 0.0008 max mem: 33300 +Test: [ 3500/21770] eta: 0:11:58 time: 0.0394 data: 0.0008 max mem: 33300 +Test: [ 3600/21770] eta: 0:11:54 time: 0.0395 data: 0.0008 max mem: 33300 +Test: [ 3700/21770] eta: 0:11:50 time: 0.0390 data: 0.0009 max mem: 33300 +Test: [ 3800/21770] eta: 0:11:46 time: 0.0391 data: 0.0008 max mem: 33300 +Test: [ 3900/21770] eta: 0:11:42 time: 0.0391 data: 0.0008 max mem: 33300 +Test: [ 4000/21770] eta: 0:11:38 time: 0.0392 data: 0.0008 max mem: 33300 +Test: [ 4100/21770] eta: 0:11:34 time: 0.0394 data: 0.0009 max mem: 33300 +Test: [ 4200/21770] eta: 0:11:30 time: 0.0395 data: 0.0009 max mem: 33300 +Test: [ 4300/21770] eta: 0:11:26 time: 0.0390 data: 0.0008 max mem: 33300 +Test: [ 4400/21770] eta: 0:11:22 time: 0.0395 data: 0.0008 max mem: 33300 +Test: [ 4500/21770] eta: 0:11:19 time: 0.0395 data: 0.0008 max mem: 33300 +Test: [ 4600/21770] eta: 0:11:15 time: 0.0389 data: 0.0008 max mem: 33300 +Test: [ 4700/21770] eta: 0:11:11 time: 0.0397 data: 0.0008 max mem: 33300 +Test: [ 4800/21770] eta: 0:11:07 time: 0.0389 data: 0.0008 max mem: 33300 +Test: [ 4900/21770] eta: 0:11:03 time: 0.0393 data: 0.0008 max mem: 33300 +Test: [ 5000/21770] eta: 0:10:59 time: 0.0392 data: 0.0008 max mem: 33300 +Test: [ 5100/21770] eta: 0:10:55 time: 0.0392 data: 0.0008 max mem: 33300 +Test: [ 5200/21770] eta: 0:10:51 time: 0.0393 data: 0.0008 max mem: 33300 +Test: [ 5300/21770] eta: 0:10:47 time: 0.0393 data: 0.0008 max mem: 33300 +Test: [ 5400/21770] eta: 0:10:43 time: 0.0392 data: 0.0008 max mem: 33300 +Test: [ 5500/21770] eta: 0:10:39 time: 0.0393 data: 0.0008 max mem: 33300 +Test: [ 5600/21770] eta: 0:10:35 time: 0.0393 data: 0.0008 max mem: 33300 +Test: [ 5700/21770] eta: 0:10:31 time: 0.0396 data: 0.0009 max mem: 33300 +Test: [ 5800/21770] eta: 0:10:28 time: 0.0400 data: 0.0008 max mem: 33300 +Test: [ 5900/21770] eta: 0:10:24 time: 0.0395 data: 0.0008 max mem: 33300 +Test: [ 6000/21770] eta: 0:10:20 time: 0.0395 data: 0.0008 max mem: 33300 +Test: [ 6100/21770] eta: 0:10:16 time: 0.0396 data: 0.0008 max mem: 33300 +Test: [ 6200/21770] eta: 0:10:12 time: 0.0398 data: 0.0008 max mem: 33300 +Test: [ 6300/21770] eta: 0:10:09 time: 0.0393 data: 0.0008 max mem: 33300 +Test: [ 6400/21770] eta: 0:10:05 time: 0.0400 data: 0.0008 max mem: 33300 +Test: [ 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time: 0.0397 data: 0.0008 max mem: 33300 +Test: [ 7900/21770] eta: 0:09:06 time: 0.0394 data: 0.0008 max mem: 33300 +Test: [ 8000/21770] eta: 0:09:02 time: 0.0392 data: 0.0008 max mem: 33300 +Test: [ 8100/21770] eta: 0:08:59 time: 0.0392 data: 0.0008 max mem: 33300 +Test: [ 8200/21770] eta: 0:08:55 time: 0.0392 data: 0.0008 max mem: 33300 +Test: [ 8300/21770] eta: 0:08:51 time: 0.0392 data: 0.0008 max mem: 33300 +Test: [ 8400/21770] eta: 0:08:47 time: 0.0393 data: 0.0008 max mem: 33300 +Test: [ 8500/21770] eta: 0:08:43 time: 0.0392 data: 0.0008 max mem: 33300 +Test: [ 8600/21770] eta: 0:08:39 time: 0.0391 data: 0.0008 max mem: 33300 +Test: [ 8700/21770] eta: 0:08:35 time: 0.0389 data: 0.0008 max mem: 33300 +Test: [ 8800/21770] eta: 0:08:31 time: 0.0388 data: 0.0009 max mem: 33300 +Test: [ 8900/21770] eta: 0:08:27 time: 0.0391 data: 0.0008 max mem: 33300 +Test: [ 9000/21770] eta: 0:08:23 time: 0.0390 data: 0.0008 max mem: 33300 +Test: [ 9100/21770] eta: 0:08:19 time: 0.0390 data: 0.0008 max mem: 33300 +Test: [ 9200/21770] eta: 0:08:15 time: 0.0389 data: 0.0008 max mem: 33300 +Test: [ 9300/21770] eta: 0:08:11 time: 0.0390 data: 0.0008 max mem: 33300 +Test: [ 9400/21770] eta: 0:08:07 time: 0.0389 data: 0.0008 max mem: 33300 +Test: [ 9500/21770] eta: 0:08:03 time: 0.0390 data: 0.0008 max mem: 33300 +Test: [ 9600/21770] eta: 0:07:59 time: 0.0390 data: 0.0008 max mem: 33300 +Test: [ 9700/21770] eta: 0:07:55 time: 0.0388 data: 0.0008 max mem: 33300 +Test: [ 9800/21770] eta: 0:07:51 time: 0.0386 data: 0.0008 max mem: 33300 +Test: [ 9900/21770] eta: 0:07:47 time: 0.0383 data: 0.0008 max mem: 33300 +Test: [10000/21770] eta: 0:07:43 time: 0.0388 data: 0.0009 max mem: 33300 +Test: [10100/21770] eta: 0:07:39 time: 0.0390 data: 0.0009 max mem: 33300 +Test: [10200/21770] eta: 0:07:35 time: 0.0391 data: 0.0009 max mem: 33300 +Test: [10300/21770] eta: 0:07:31 time: 0.0391 data: 0.0008 max mem: 33300 +Test: [10400/21770] eta: 0:07:27 time: 0.0391 data: 0.0009 max mem: 33300 +Test: [10500/21770] eta: 0:07:23 time: 0.0389 data: 0.0008 max mem: 33300 +Test: [10600/21770] eta: 0:07:19 time: 0.0391 data: 0.0008 max mem: 33300 +Test: [10700/21770] eta: 0:07:15 time: 0.0388 data: 0.0008 max mem: 33300 +Test: [10800/21770] eta: 0:07:11 time: 0.0390 data: 0.0008 max mem: 33300 +Test: [10900/21770] eta: 0:07:07 time: 0.0389 data: 0.0008 max mem: 33300 +Test: [11000/21770] eta: 0:07:03 time: 0.0386 data: 0.0008 max mem: 33300 +Test: [11100/21770] eta: 0:06:59 time: 0.0385 data: 0.0008 max mem: 33300 +Test: [11200/21770] eta: 0:06:55 time: 0.0390 data: 0.0008 max mem: 33300 +Test: [11300/21770] eta: 0:06:51 time: 0.0391 data: 0.0008 max mem: 33300 +Test: [11400/21770] eta: 0:06:47 time: 0.0390 data: 0.0008 max mem: 33300 +Test: [11500/21770] eta: 0:06:43 time: 0.0391 data: 0.0008 max mem: 33300 +Test: [11600/21770] eta: 0:06:39 time: 0.0387 data: 0.0008 max mem: 33300 +Test: [11700/21770] eta: 0:06:35 time: 0.0385 data: 0.0008 max mem: 33300 +Test: [11800/21770] eta: 0:06:31 time: 0.0387 data: 0.0008 max mem: 33300 +Test: [11900/21770] eta: 0:06:27 time: 0.0386 data: 0.0008 max mem: 33300 +Test: [12000/21770] eta: 0:06:23 time: 0.0389 data: 0.0009 max mem: 33300 +Test: [12100/21770] eta: 0:06:19 time: 0.0387 data: 0.0008 max mem: 33300 +Test: [12200/21770] eta: 0:06:15 time: 0.0385 data: 0.0008 max mem: 33300 +Test: [12300/21770] eta: 0:06:11 time: 0.0380 data: 0.0008 max mem: 33300 +Test: [12400/21770] eta: 0:06:07 time: 0.0384 data: 0.0008 max mem: 33300 +Test: [12500/21770] eta: 0:06:03 time: 0.0382 data: 0.0008 max mem: 33300 +Test: [12600/21770] eta: 0:05:59 time: 0.0383 data: 0.0008 max mem: 33300 +Test: [12700/21770] eta: 0:05:55 time: 0.0382 data: 0.0008 max mem: 33300 +Test: [12800/21770] eta: 0:05:51 time: 0.0384 data: 0.0008 max mem: 33300 +Test: [12900/21770] eta: 0:05:47 time: 0.0380 data: 0.0008 max mem: 33300 +Test: [13000/21770] eta: 0:05:43 time: 0.0387 data: 0.0008 max mem: 33300 +Test: [13100/21770] eta: 0:05:39 time: 0.0385 data: 0.0008 max mem: 33300 +Test: [13200/21770] eta: 0:05:35 time: 0.0393 data: 0.0008 max mem: 33300 +Test: [13300/21770] eta: 0:05:31 time: 0.0392 data: 0.0008 max mem: 33300 +Test: [13400/21770] eta: 0:05:27 time: 0.0393 data: 0.0008 max mem: 33300 +Test: [13500/21770] eta: 0:05:24 time: 0.0391 data: 0.0008 max mem: 33300 +Test: [13600/21770] eta: 0:05:20 time: 0.0388 data: 0.0009 max mem: 33300 +Test: [13700/21770] eta: 0:05:16 time: 0.0386 data: 0.0009 max mem: 33300 +Test: [13800/21770] eta: 0:05:12 time: 0.0390 data: 0.0008 max mem: 33300 +Test: [13900/21770] eta: 0:05:08 time: 0.0386 data: 0.0008 max mem: 33300 +Test: [14000/21770] eta: 0:05:04 time: 0.0389 data: 0.0008 max mem: 33300 +Test: [14100/21770] eta: 0:05:00 time: 0.0385 data: 0.0008 max mem: 33300 +Test: [14200/21770] eta: 0:04:56 time: 0.0390 data: 0.0008 max mem: 33300 +Test: [14300/21770] eta: 0:04:52 time: 0.0386 data: 0.0008 max mem: 33300 +Test: [14400/21770] eta: 0:04:48 time: 0.0389 data: 0.0008 max mem: 33300 +Test: [14500/21770] eta: 0:04:44 time: 0.0386 data: 0.0008 max mem: 33300 +Test: [14600/21770] eta: 0:04:40 time: 0.0390 data: 0.0008 max mem: 33300 +Test: [14700/21770] eta: 0:04:36 time: 0.0385 data: 0.0008 max mem: 33300 +Test: [14800/21770] eta: 0:04:32 time: 0.0388 data: 0.0008 max mem: 33300 +Test: [14900/21770] eta: 0:04:28 time: 0.0386 data: 0.0008 max mem: 33300 +Test: [15000/21770] eta: 0:04:24 time: 0.0388 data: 0.0008 max mem: 33300 +Test: [15100/21770] eta: 0:04:21 time: 0.0385 data: 0.0008 max mem: 33300 +Test: [15200/21770] eta: 0:04:17 time: 0.0387 data: 0.0009 max mem: 33300 +Test: [15300/21770] eta: 0:04:13 time: 0.0383 data: 0.0008 max mem: 33300 +Test: [15400/21770] eta: 0:04:09 time: 0.0385 data: 0.0008 max mem: 33300 +Test: [15500/21770] eta: 0:04:05 time: 0.0383 data: 0.0008 max mem: 33300 +Test: [15600/21770] eta: 0:04:01 time: 0.0386 data: 0.0008 max mem: 33300 +Test: [15700/21770] eta: 0:03:57 time: 0.0383 data: 0.0008 max mem: 33300 +Test: [15800/21770] eta: 0:03:53 time: 0.0386 data: 0.0008 max mem: 33300 +Test: [15900/21770] eta: 0:03:49 time: 0.0383 data: 0.0008 max mem: 33300 +Test: [16000/21770] eta: 0:03:45 time: 0.0389 data: 0.0008 max mem: 33300 +Test: [16100/21770] eta: 0:03:41 time: 0.0386 data: 0.0008 max mem: 33300 +Test: [16200/21770] eta: 0:03:37 time: 0.0387 data: 0.0008 max mem: 33300 +Test: [16300/21770] eta: 0:03:33 time: 0.0385 data: 0.0008 max mem: 33300 +Test: [16400/21770] eta: 0:03:29 time: 0.0385 data: 0.0008 max mem: 33300 +Test: [16500/21770] eta: 0:03:25 time: 0.0381 data: 0.0008 max mem: 33300 +Test: [16600/21770] eta: 0:03:22 time: 0.0384 data: 0.0008 max mem: 33300 +Test: [16700/21770] eta: 0:03:18 time: 0.0383 data: 0.0008 max mem: 33300 +Test: [16800/21770] eta: 0:03:14 time: 0.0388 data: 0.0008 max mem: 33300 +Test: [16900/21770] eta: 0:03:10 time: 0.0384 data: 0.0008 max mem: 33300 +Test: [17000/21770] eta: 0:03:06 time: 0.0387 data: 0.0008 max mem: 33300 +Test: [17100/21770] eta: 0:03:02 time: 0.0384 data: 0.0008 max mem: 33300 +Test: [17200/21770] eta: 0:02:58 time: 0.0389 data: 0.0008 max mem: 33300 +Test: [17300/21770] eta: 0:02:54 time: 0.0385 data: 0.0008 max mem: 33300 +Test: [17400/21770] eta: 0:02:50 time: 0.0386 data: 0.0008 max mem: 33300 +Test: [17500/21770] eta: 0:02:46 time: 0.0379 data: 0.0008 max mem: 33300 +Test: [17600/21770] eta: 0:02:42 time: 0.0385 data: 0.0008 max mem: 33300 +Test: [17700/21770] eta: 0:02:38 time: 0.0384 data: 0.0009 max mem: 33300 +Test: [17800/21770] eta: 0:02:34 time: 0.0391 data: 0.0010 max mem: 33300 +Test: [17900/21770] eta: 0:02:31 time: 0.0386 data: 0.0010 max mem: 33300 +Test: [18000/21770] eta: 0:02:27 time: 0.0390 data: 0.0010 max mem: 33300 +Test: [18100/21770] eta: 0:02:23 time: 0.0387 data: 0.0010 max mem: 33300 +Test: [18200/21770] eta: 0:02:19 time: 0.0390 data: 0.0010 max mem: 33300 +Test: [18300/21770] eta: 0:02:15 time: 0.0386 data: 0.0010 max mem: 33300 +Test: [18400/21770] eta: 0:02:11 time: 0.0394 data: 0.0010 max mem: 33300 +Test: [18500/21770] eta: 0:02:07 time: 0.0386 data: 0.0010 max mem: 33300 +Test: [18600/21770] eta: 0:02:03 time: 0.0394 data: 0.0009 max mem: 33300 +Test: [18700/21770] eta: 0:01:59 time: 0.0391 data: 0.0009 max mem: 33300 +Test: [18800/21770] eta: 0:01:55 time: 0.0394 data: 0.0009 max mem: 33300 +Test: [18900/21770] eta: 0:01:52 time: 0.0382 data: 0.0009 max mem: 33300 +Test: [19000/21770] eta: 0:01:48 time: 0.0384 data: 0.0009 max mem: 33300 +Test: [19100/21770] eta: 0:01:44 time: 0.0385 data: 0.0009 max mem: 33300 +Test: [19200/21770] eta: 0:01:40 time: 0.0381 data: 0.0009 max mem: 33300 +Test: [19300/21770] eta: 0:01:36 time: 0.0381 data: 0.0009 max mem: 33300 +Test: [19400/21770] eta: 0:01:32 time: 0.0386 data: 0.0009 max mem: 33300 +Test: [19500/21770] eta: 0:01:28 time: 0.0384 data: 0.0009 max mem: 33300 +Test: [19600/21770] eta: 0:01:24 time: 0.0386 data: 0.0009 max mem: 33300 +Test: [19700/21770] eta: 0:01:20 time: 0.0380 data: 0.0009 max mem: 33300 +Test: [19800/21770] eta: 0:01:16 time: 0.0382 data: 0.0009 max mem: 33300 +Test: [19900/21770] eta: 0:01:12 time: 0.0381 data: 0.0009 max mem: 33300 +Test: [20000/21770] eta: 0:01:09 time: 0.0383 data: 0.0009 max mem: 33300 +Test: [20100/21770] eta: 0:01:05 time: 0.0380 data: 0.0008 max mem: 33300 +Test: [20200/21770] eta: 0:01:01 time: 0.0382 data: 0.0009 max mem: 33300 +Test: [20300/21770] eta: 0:00:57 time: 0.0381 data: 0.0009 max mem: 33300 +Test: [20400/21770] eta: 0:00:53 time: 0.0382 data: 0.0009 max mem: 33300 +Test: [20500/21770] eta: 0:00:49 time: 0.0381 data: 0.0009 max mem: 33300 +Test: [20600/21770] eta: 0:00:45 time: 0.0382 data: 0.0009 max mem: 33300 +Test: [20700/21770] eta: 0:00:41 time: 0.0381 data: 0.0009 max mem: 33300 +Test: [20800/21770] eta: 0:00:37 time: 0.0382 data: 0.0009 max mem: 33300 +Test: [20900/21770] eta: 0:00:33 time: 0.0381 data: 0.0009 max mem: 33300 +Test: [21000/21770] eta: 0:00:29 time: 0.0383 data: 0.0009 max mem: 33300 +Test: [21100/21770] eta: 0:00:26 time: 0.0382 data: 0.0009 max mem: 33300 +Test: [21200/21770] eta: 0:00:22 time: 0.0384 data: 0.0009 max mem: 33300 +Test: [21300/21770] eta: 0:00:18 time: 0.0382 data: 0.0009 max mem: 33300 +Test: [21400/21770] eta: 0:00:14 time: 0.0383 data: 0.0009 max mem: 33300 +Test: [21500/21770] eta: 0:00:10 time: 0.0382 data: 0.0009 max mem: 33300 +Test: [21600/21770] eta: 0:00:06 time: 0.0384 data: 0.0009 max mem: 33300 +Test: [21700/21770] eta: 0:00:02 time: 0.0381 data: 0.0009 max mem: 33300 +Test: Total time: 0:14:07 +Final results: +Mean IoU is 0.00 + + precision@0.5 = 0.00 + precision@0.6 = 0.00 + precision@0.7 = 0.00 + precision@0.8 = 0.00 + precision@0.9 = 0.00 + overall IoU = 0.00 + mean IoU = 0.00 + +Mean accuracy for one-to-zero sample is 100.00 + +Average object IoU 0.0 +Overall IoU 0.0 +Epoch: [22] [ 0/4276] eta: 5:40:01 lr: 2.4370036992418076e-05 loss: 0.0903 (0.0903) time: 4.7713 data: 1.7489 max mem: 33300 +Epoch: [22] [ 10/4276] eta: 3:40:47 lr: 2.436718730673677e-05 loss: 0.1216 (0.1233) time: 3.1054 data: 0.1662 max mem: 33300 +Epoch: [22] [ 20/4276] eta: 3:34:17 lr: 2.436433758402564e-05 loss: 0.1146 (0.1171) time: 2.9335 data: 0.0079 max mem: 33300 +Epoch: [22] [ 30/4276] eta: 3:32:06 lr: 2.4361487824279387e-05 loss: 0.1031 (0.1162) time: 2.9377 data: 0.0084 max mem: 33300 +Epoch: [22] [ 40/4276] eta: 3:30:28 lr: 2.4358638027492722e-05 loss: 0.1064 (0.1144) time: 2.9394 data: 0.0086 max mem: 33300 +Epoch: [22] [ 50/4276] eta: 3:29:13 lr: 2.4355788193660353e-05 loss: 0.1064 (0.1122) time: 2.9294 data: 0.0081 max mem: 33300 +Epoch: [22] [ 60/4276] eta: 3:28:17 lr: 2.435293832277697e-05 loss: 0.1002 (0.1115) time: 2.9295 data: 0.0081 max mem: 33300 +Epoch: [22] [ 70/4276] eta: 3:27:24 lr: 2.435008841483728e-05 loss: 0.0964 (0.1090) time: 2.9284 data: 0.0081 max mem: 33300 +Epoch: [22] [ 80/4276] eta: 3:26:39 lr: 2.4347238469835983e-05 loss: 0.0964 (0.1099) time: 2.9270 data: 0.0079 max mem: 33300 +Epoch: [22] [ 90/4276] eta: 3:25:55 lr: 2.434438848776778e-05 loss: 0.1078 (0.1098) time: 2.9268 data: 0.0079 max mem: 33300 +Epoch: [22] [ 100/4276] eta: 3:25:15 lr: 2.4341538468627356e-05 loss: 0.1081 (0.1104) time: 2.9257 data: 0.0082 max mem: 33300 +Epoch: [22] [ 110/4276] eta: 3:24:37 lr: 2.4338688412409414e-05 loss: 0.1159 (0.1112) time: 2.9261 data: 0.0081 max mem: 33300 +Epoch: [22] [ 120/4276] eta: 3:24:00 lr: 2.4335838319108644e-05 loss: 0.1060 (0.1107) time: 2.9255 data: 0.0085 max mem: 33300 +Epoch: [22] [ 130/4276] eta: 3:23:26 lr: 2.4332988188719746e-05 loss: 0.1060 (0.1112) time: 2.9284 data: 0.0088 max mem: 33300 +Epoch: [22] [ 140/4276] eta: 3:22:52 lr: 2.43301380212374e-05 loss: 0.1093 (0.1105) time: 2.9302 data: 0.0086 max mem: 33300 +Epoch: [22] [ 150/4276] eta: 3:22:19 lr: 2.43272878166563e-05 loss: 0.1042 (0.1103) time: 2.9294 data: 0.0083 max mem: 33300 +Epoch: [22] [ 160/4276] eta: 3:21:46 lr: 2.4324437574971133e-05 loss: 0.1071 (0.1102) time: 2.9293 data: 0.0079 max mem: 33300 +Epoch: [22] [ 170/4276] eta: 3:21:15 lr: 2.432158729617659e-05 loss: 0.1027 (0.1096) time: 2.9300 data: 0.0079 max mem: 33300 +Epoch: [22] [ 180/4276] eta: 3:20:43 lr: 2.431873698026734e-05 loss: 0.0990 (0.1097) time: 2.9310 data: 0.0081 max mem: 33300 +Epoch: [22] [ 190/4276] eta: 3:20:11 lr: 2.431588662723808e-05 loss: 0.1016 (0.1094) time: 2.9307 data: 0.0082 max mem: 33300 +Epoch: [22] [ 200/4276] eta: 3:19:40 lr: 2.4313036237083486e-05 loss: 0.0948 (0.1093) time: 2.9298 data: 0.0080 max mem: 33300 +Epoch: [22] [ 210/4276] eta: 3:19:09 lr: 2.431018580979825e-05 loss: 0.0983 (0.1092) time: 2.9299 data: 0.0080 max mem: 33300 +Epoch: [22] [ 220/4276] eta: 3:18:37 lr: 2.4307335345377033e-05 loss: 0.0983 (0.1097) time: 2.9273 data: 0.0080 max mem: 33300 +Epoch: [22] [ 230/4276] eta: 3:17:58 lr: 2.430448484381452e-05 loss: 0.0875 (0.1090) time: 2.9031 data: 0.0086 max mem: 33300 +Epoch: [22] [ 240/4276] eta: 3:17:18 lr: 2.430163430510539e-05 loss: 0.0918 (0.1088) time: 2.8790 data: 0.0088 max mem: 33300 +Epoch: [22] [ 250/4276] eta: 3:16:40 lr: 2.4298783729244317e-05 loss: 0.1093 (0.1095) time: 2.8765 data: 0.0080 max mem: 33300 +Epoch: [22] [ 260/4276] eta: 3:16:02 lr: 2.429593311622597e-05 loss: 0.1049 (0.1094) time: 2.8761 data: 0.0076 max mem: 33300 +Epoch: [22] [ 270/4276] eta: 3:15:25 lr: 2.429308246604502e-05 loss: 0.0948 (0.1095) time: 2.8760 data: 0.0074 max mem: 33300 +Epoch: [22] [ 280/4276] eta: 3:14:48 lr: 2.429023177869614e-05 loss: 0.1052 (0.1094) time: 2.8761 data: 0.0076 max mem: 33300 +Epoch: [22] [ 290/4276] eta: 3:14:18 lr: 2.4287381054174003e-05 loss: 0.1001 (0.1089) time: 2.8953 data: 0.0081 max mem: 33300 +Epoch: [22] [ 300/4276] eta: 3:13:45 lr: 2.4284530292473266e-05 loss: 0.0999 (0.1089) time: 2.9073 data: 0.0091 max mem: 33300 +Epoch: [22] [ 310/4276] eta: 3:13:17 lr: 2.4281679493588603e-05 loss: 0.1047 (0.1092) time: 2.9155 data: 0.0092 max mem: 33300 +Epoch: [22] [ 320/4276] eta: 3:12:50 lr: 2.427882865751467e-05 loss: 0.1027 (0.1095) time: 2.9365 data: 0.0092 max mem: 33300 +Epoch: [22] [ 330/4276] eta: 3:12:21 lr: 2.4275977784246142e-05 loss: 0.1254 (0.1103) time: 2.9370 data: 0.0090 max mem: 33300 +Epoch: [22] [ 340/4276] eta: 3:11:54 lr: 2.4273126873777668e-05 loss: 0.1151 (0.1103) time: 2.9366 data: 0.0082 max mem: 33300 +Epoch: [22] [ 350/4276] eta: 3:11:26 lr: 2.4270275926103912e-05 loss: 0.1094 (0.1104) time: 2.9407 data: 0.0084 max mem: 33300 +Epoch: [22] [ 360/4276] eta: 3:11:02 lr: 2.426742494121954e-05 loss: 0.1205 (0.1114) time: 2.9561 data: 0.0081 max mem: 33300 +Epoch: [22] [ 370/4276] eta: 3:10:29 lr: 2.4264573919119196e-05 loss: 0.1146 (0.1113) time: 2.9291 data: 0.0080 max mem: 33300 +Epoch: [22] [ 380/4276] eta: 3:10:21 lr: 2.4261722859797543e-05 loss: 0.1046 (0.1113) time: 3.0105 data: 0.0084 max mem: 33300 +Epoch: [22] [ 390/4276] eta: 3:10:22 lr: 2.425887176324923e-05 loss: 0.1085 (0.1117) time: 3.1884 data: 0.0090 max mem: 33300 +Epoch: [22] [ 400/4276] eta: 3:10:24 lr: 2.425602062946892e-05 loss: 0.1236 (0.1120) time: 3.2534 data: 0.0099 max mem: 33300 +Epoch: [22] [ 410/4276] eta: 3:10:25 lr: 2.4253169458451252e-05 loss: 0.1309 (0.1124) time: 3.2682 data: 0.0098 max mem: 33300 +Epoch: [22] [ 420/4276] eta: 3:10:25 lr: 2.4250318250190883e-05 loss: 0.1205 (0.1124) time: 3.2730 data: 0.0098 max mem: 33300 +Epoch: [22] [ 430/4276] eta: 3:10:22 lr: 2.4247467004682453e-05 loss: 0.1195 (0.1126) time: 3.2702 data: 0.0095 max mem: 33300 +Epoch: [22] [ 440/4276] eta: 3:10:19 lr: 2.4244615721920624e-05 loss: 0.1116 (0.1125) time: 3.2680 data: 0.0088 max mem: 33300 +Epoch: [22] [ 450/4276] eta: 3:10:13 lr: 2.4241764401900024e-05 loss: 0.1086 (0.1124) time: 3.2660 data: 0.0097 max mem: 33300 +Epoch: [22] [ 460/4276] eta: 3:10:04 lr: 2.4238913044615304e-05 loss: 0.1085 (0.1123) time: 3.2486 data: 0.0103 max mem: 33300 +Epoch: [22] [ 470/4276] eta: 3:09:56 lr: 2.4236061650061107e-05 loss: 0.0971 (0.1122) time: 3.2445 data: 0.0100 max mem: 33300 +Epoch: [22] [ 480/4276] eta: 3:09:47 lr: 2.423321021823208e-05 loss: 0.0981 (0.1121) time: 3.2612 data: 0.0095 max mem: 33300 +Epoch: [22] [ 490/4276] eta: 3:09:38 lr: 2.4230358749122846e-05 loss: 0.0991 (0.1117) time: 3.2656 data: 0.0088 max mem: 33300 +Epoch: [22] [ 500/4276] eta: 3:09:27 lr: 2.4227507242728056e-05 loss: 0.0991 (0.1115) time: 3.2597 data: 0.0088 max mem: 33300 +Epoch: [22] [ 510/4276] eta: 3:09:15 lr: 2.422465569904234e-05 loss: 0.1022 (0.1114) time: 3.2567 data: 0.0090 max mem: 33300 +Epoch: [22] [ 520/4276] eta: 3:09:00 lr: 2.4221804118060347e-05 loss: 0.1043 (0.1113) time: 3.2469 data: 0.0091 max mem: 33300 +Epoch: [22] [ 530/4276] eta: 3:08:43 lr: 2.4218952499776685e-05 loss: 0.1070 (0.1113) time: 3.2176 data: 0.0097 max mem: 33300 +Epoch: [22] [ 540/4276] eta: 3:08:25 lr: 2.4216100844186005e-05 loss: 0.1026 (0.1111) time: 3.1967 data: 0.0093 max mem: 33300 +Epoch: [22] [ 550/4276] eta: 3:08:06 lr: 2.4213249151282928e-05 loss: 0.1012 (0.1111) time: 3.1948 data: 0.0086 max mem: 33300 +Epoch: [22] [ 560/4276] eta: 3:07:51 lr: 2.4210397421062094e-05 loss: 0.1106 (0.1112) time: 3.2290 data: 0.0095 max mem: 33300 +Epoch: [22] [ 570/4276] eta: 3:07:36 lr: 2.4207545653518118e-05 loss: 0.1106 (0.1111) time: 3.2702 data: 0.0106 max mem: 33300 +Epoch: [22] [ 580/4276] eta: 3:07:20 lr: 2.4204693848645633e-05 loss: 0.1053 (0.1111) time: 3.2704 data: 0.0102 max mem: 33300 +Epoch: [22] [ 590/4276] eta: 3:07:04 lr: 2.4201842006439264e-05 loss: 0.1034 (0.1110) time: 3.2616 data: 0.0090 max mem: 33300 +Epoch: [22] [ 600/4276] eta: 3:06:47 lr: 2.4198990126893632e-05 loss: 0.0979 (0.1109) time: 3.2675 data: 0.0097 max mem: 33300 +Epoch: [22] [ 610/4276] eta: 3:06:30 lr: 2.4196138210003355e-05 loss: 0.0959 (0.1108) time: 3.2717 data: 0.0105 max mem: 33300 +Epoch: [22] [ 620/4276] eta: 3:05:59 lr: 2.4193286255763058e-05 loss: 0.0959 (0.1107) time: 3.1555 data: 0.0095 max mem: 33300 +Epoch: [22] [ 630/4276] eta: 3:05:27 lr: 2.4190434264167358e-05 loss: 0.1046 (0.1109) time: 3.0355 data: 0.0090 max mem: 33300 +Epoch: [22] [ 640/4276] eta: 3:04:55 lr: 2.4187582235210878e-05 loss: 0.1031 (0.1107) time: 3.0295 data: 0.0091 max mem: 33300 +Epoch: [22] [ 650/4276] eta: 3:04:18 lr: 2.4184730168888223e-05 loss: 0.0911 (0.1106) time: 2.9818 data: 0.0088 max mem: 33300 +Epoch: [22] [ 660/4276] eta: 3:03:41 lr: 2.418187806519401e-05 loss: 0.1063 (0.1108) time: 2.9334 data: 0.0085 max mem: 33300 +Epoch: [22] [ 670/4276] eta: 3:03:04 lr: 2.417902592412286e-05 loss: 0.1086 (0.1107) time: 2.9330 data: 0.0085 max mem: 33300 +Epoch: [22] [ 680/4276] eta: 3:02:28 lr: 2.4176173745669375e-05 loss: 0.1028 (0.1107) time: 2.9322 data: 0.0085 max mem: 33300 +Epoch: [22] [ 690/4276] eta: 3:01:52 lr: 2.4173321529828167e-05 loss: 0.1028 (0.1108) time: 2.9336 data: 0.0085 max mem: 33300 +Epoch: [22] [ 700/4276] eta: 3:01:16 lr: 2.4170469276593845e-05 loss: 0.1011 (0.1107) time: 2.9322 data: 0.0085 max mem: 33300 +Epoch: [22] [ 710/4276] eta: 3:00:40 lr: 2.4167616985961024e-05 loss: 0.1043 (0.1109) time: 2.9318 data: 0.0086 max mem: 33300 +Epoch: [22] [ 720/4276] eta: 3:00:04 lr: 2.416476465792429e-05 loss: 0.1050 (0.1108) time: 2.9318 data: 0.0087 max mem: 33300 +Epoch: [22] [ 730/4276] eta: 2:59:28 lr: 2.416191229247826e-05 loss: 0.0997 (0.1106) time: 2.9290 data: 0.0085 max mem: 33300 +Epoch: [22] [ 740/4276] eta: 2:58:53 lr: 2.4159059889617537e-05 loss: 0.0950 (0.1105) time: 2.9284 data: 0.0083 max mem: 33300 +Epoch: [22] [ 750/4276] eta: 2:58:17 lr: 2.415620744933672e-05 loss: 0.0982 (0.1105) time: 2.9283 data: 0.0083 max mem: 33300 +Epoch: [22] [ 760/4276] eta: 2:57:42 lr: 2.415335497163041e-05 loss: 0.1011 (0.1105) time: 2.9288 data: 0.0083 max mem: 33300 +Epoch: [22] [ 770/4276] eta: 2:57:07 lr: 2.415050245649319e-05 loss: 0.1086 (0.1105) time: 2.9279 data: 0.0084 max mem: 33300 +Epoch: [22] [ 780/4276] eta: 2:56:32 lr: 2.4147649903919676e-05 loss: 0.1086 (0.1105) time: 2.9269 data: 0.0084 max mem: 33300 +Epoch: [22] [ 790/4276] eta: 2:55:57 lr: 2.4144797313904462e-05 loss: 0.1013 (0.1106) time: 2.9295 data: 0.0085 max mem: 33300 +Epoch: [22] [ 800/4276] eta: 2:55:23 lr: 2.4141944686442128e-05 loss: 0.1016 (0.1105) time: 2.9333 data: 0.0085 max mem: 33300 +Epoch: [22] [ 810/4276] eta: 2:54:49 lr: 2.413909202152727e-05 loss: 0.1041 (0.1108) time: 2.9350 data: 0.0085 max mem: 33300 +Epoch: [22] [ 820/4276] eta: 2:54:13 lr: 2.4136239319154484e-05 loss: 0.1054 (0.1106) time: 2.9135 data: 0.0086 max mem: 33300 +Epoch: [22] [ 830/4276] eta: 2:53:37 lr: 2.413338657931836e-05 loss: 0.1054 (0.1109) time: 2.8862 data: 0.0088 max mem: 33300 +Epoch: [22] [ 840/4276] eta: 2:53:01 lr: 2.4130533802013477e-05 loss: 0.1123 (0.1110) time: 2.8788 data: 0.0083 max mem: 33300 +Epoch: [22] [ 850/4276] eta: 2:52:24 lr: 2.4127680987234425e-05 loss: 0.1064 (0.1109) time: 2.8758 data: 0.0078 max mem: 33300 +Epoch: [22] [ 860/4276] eta: 2:51:48 lr: 2.4124828134975784e-05 loss: 0.1046 (0.1109) time: 2.8743 data: 0.0078 max mem: 33300 +Epoch: [22] [ 870/4276] eta: 2:51:13 lr: 2.4121975245232154e-05 loss: 0.1046 (0.1109) time: 2.8743 data: 0.0080 max mem: 33300 +Epoch: [22] [ 880/4276] eta: 2:50:37 lr: 2.4119122317998094e-05 loss: 0.1081 (0.1110) time: 2.8751 data: 0.0082 max mem: 33300 +Epoch: [22] [ 890/4276] eta: 2:50:02 lr: 2.4116269353268196e-05 loss: 0.1145 (0.1111) time: 2.8749 data: 0.0080 max mem: 33300 +Epoch: [22] [ 900/4276] eta: 2:49:26 lr: 2.4113416351037036e-05 loss: 0.1164 (0.1112) time: 2.8744 data: 0.0078 max mem: 33300 +Epoch: [22] [ 910/4276] eta: 2:48:52 lr: 2.4110563311299195e-05 loss: 0.1104 (0.1113) time: 2.8871 data: 0.0084 max mem: 33300 +Epoch: [22] [ 920/4276] eta: 2:48:18 lr: 2.4107710234049237e-05 loss: 0.1112 (0.1113) time: 2.9074 data: 0.0094 max mem: 33300 +Epoch: [22] [ 930/4276] eta: 2:47:46 lr: 2.4104857119281747e-05 loss: 0.1140 (0.1114) time: 2.9252 data: 0.0098 max mem: 33300 +Epoch: [22] [ 940/4276] eta: 2:47:13 lr: 2.4102003966991297e-05 loss: 0.1082 (0.1114) time: 2.9379 data: 0.0096 max mem: 33300 +Epoch: [22] [ 950/4276] eta: 2:46:41 lr: 2.4099150777172456e-05 loss: 0.1138 (0.1115) time: 2.9402 data: 0.0091 max mem: 33300 +Epoch: [22] [ 960/4276] eta: 2:46:08 lr: 2.409629754981979e-05 loss: 0.1133 (0.1115) time: 2.9317 data: 0.0090 max mem: 33300 +Epoch: [22] [ 970/4276] eta: 2:45:36 lr: 2.4093444284927862e-05 loss: 0.1117 (0.1115) time: 2.9323 data: 0.0088 max mem: 33300 +Epoch: [22] [ 980/4276] eta: 2:45:03 lr: 2.409059098249126e-05 loss: 0.1113 (0.1115) time: 2.9436 data: 0.0084 max mem: 33300 +Epoch: [22] [ 990/4276] eta: 2:44:31 lr: 2.4087737642504524e-05 loss: 0.1045 (0.1114) time: 2.9360 data: 0.0083 max mem: 33300 +Epoch: [22] [1000/4276] eta: 2:43:58 lr: 2.408488426496223e-05 loss: 0.0991 (0.1114) time: 2.9199 data: 0.0083 max mem: 33300 +Epoch: [22] [1010/4276] eta: 2:43:24 lr: 2.408203084985894e-05 loss: 0.1043 (0.1114) time: 2.9051 data: 0.0090 max mem: 33300 +Epoch: [22] [1020/4276] eta: 2:42:52 lr: 2.4079177397189214e-05 loss: 0.1043 (0.1114) time: 2.9118 data: 0.0094 max mem: 33300 +Epoch: [22] [1030/4276] eta: 2:42:20 lr: 2.4076323906947607e-05 loss: 0.1050 (0.1114) time: 2.9280 data: 0.0084 max mem: 33300 +Epoch: [22] [1040/4276] eta: 2:41:47 lr: 2.4073470379128678e-05 loss: 0.1162 (0.1113) time: 2.9292 data: 0.0075 max mem: 33300 +Epoch: [22] [1050/4276] eta: 2:41:15 lr: 2.407061681372698e-05 loss: 0.0964 (0.1115) time: 2.9283 data: 0.0076 max mem: 33300 +Epoch: [22] [1060/4276] eta: 2:40:43 lr: 2.4067763210737083e-05 loss: 0.1268 (0.1116) time: 2.9280 data: 0.0075 max mem: 33300 +Epoch: [22] [1070/4276] eta: 2:40:11 lr: 2.406490957015352e-05 loss: 0.1229 (0.1118) time: 2.9287 data: 0.0075 max mem: 33300 +Epoch: [22] [1080/4276] eta: 2:39:39 lr: 2.406205589197085e-05 loss: 0.1148 (0.1118) time: 2.9275 data: 0.0076 max mem: 33300 +Epoch: [22] [1090/4276] eta: 2:39:07 lr: 2.405920217618362e-05 loss: 0.1232 (0.1119) time: 2.9283 data: 0.0075 max mem: 33300 +Epoch: [22] [1100/4276] eta: 2:38:35 lr: 2.405634842278639e-05 loss: 0.1138 (0.1120) time: 2.9287 data: 0.0074 max mem: 33300 +Epoch: [22] [1110/4276] eta: 2:38:03 lr: 2.4053494631773692e-05 loss: 0.1101 (0.1121) time: 2.9280 data: 0.0074 max mem: 33300 +Epoch: [22] [1120/4276] eta: 2:37:31 lr: 2.4050640803140082e-05 loss: 0.1112 (0.1121) time: 2.9282 data: 0.0075 max mem: 33300 +Epoch: [22] [1130/4276] eta: 2:36:59 lr: 2.4047786936880096e-05 loss: 0.1039 (0.1120) time: 2.9256 data: 0.0074 max mem: 33300 +Epoch: [22] [1140/4276] eta: 2:36:27 lr: 2.404493303298829e-05 loss: 0.1027 (0.1120) time: 2.9242 data: 0.0074 max mem: 33300 +Epoch: [22] [1150/4276] eta: 2:35:56 lr: 2.4042079091459183e-05 loss: 0.1037 (0.1119) time: 2.9288 data: 0.0075 max mem: 33300 +Epoch: [22] [1160/4276] eta: 2:35:24 lr: 2.403922511228733e-05 loss: 0.1071 (0.1119) time: 2.9315 data: 0.0077 max mem: 33300 +Epoch: [22] [1170/4276] eta: 2:34:53 lr: 2.4036371095467264e-05 loss: 0.1156 (0.1120) time: 2.9301 data: 0.0077 max mem: 33300 +Epoch: [22] [1180/4276] eta: 2:34:21 lr: 2.4033517040993528e-05 loss: 0.1156 (0.1121) time: 2.9276 data: 0.0075 max mem: 33300 +Epoch: [22] [1190/4276] eta: 2:33:49 lr: 2.4030662948860646e-05 loss: 0.0953 (0.1120) time: 2.9274 data: 0.0075 max mem: 33300 +Epoch: [22] [1200/4276] eta: 2:33:18 lr: 2.4027808819063156e-05 loss: 0.0925 (0.1119) time: 2.9287 data: 0.0075 max mem: 33300 +Epoch: [22] [1210/4276] eta: 2:32:46 lr: 2.402495465159559e-05 loss: 0.0925 (0.1118) time: 2.9282 data: 0.0075 max mem: 33300 +Epoch: [22] [1220/4276] eta: 2:32:15 lr: 2.4022100446452484e-05 loss: 0.1000 (0.1118) time: 2.9266 data: 0.0075 max mem: 33300 +Epoch: [22] [1230/4276] eta: 2:31:44 lr: 2.4019246203628358e-05 loss: 0.1065 (0.1118) time: 2.9266 data: 0.0075 max mem: 33300 +Epoch: [22] [1240/4276] eta: 2:31:12 lr: 2.4016391923117737e-05 loss: 0.1031 (0.1118) time: 2.9277 data: 0.0075 max mem: 33300 +Epoch: [22] [1250/4276] eta: 2:30:41 lr: 2.4013537604915157e-05 loss: 0.1055 (0.1119) time: 2.9283 data: 0.0075 max mem: 33300 +Epoch: [22] [1260/4276] eta: 2:30:10 lr: 2.401068324901514e-05 loss: 0.1055 (0.1118) time: 2.9285 data: 0.0075 max mem: 33301 +Epoch: [22] [1270/4276] eta: 2:29:39 lr: 2.4007828855412198e-05 loss: 0.0933 (0.1117) time: 2.9377 data: 0.0075 max mem: 33301 +Epoch: [22] [1280/4276] eta: 2:29:07 lr: 2.4004974424100862e-05 loss: 0.1078 (0.1118) time: 2.9376 data: 0.0075 max mem: 33301 +Epoch: [22] [1290/4276] eta: 2:28:36 lr: 2.4002119955075656e-05 loss: 0.1134 (0.1117) time: 2.9280 data: 0.0075 max mem: 33301 +Epoch: [22] [1300/4276] eta: 2:28:05 lr: 2.3999265448331083e-05 loss: 0.0934 (0.1116) time: 2.9353 data: 0.0075 max mem: 33301 +Epoch: [22] [1310/4276] eta: 2:27:34 lr: 2.3996410903861675e-05 loss: 0.0899 (0.1115) time: 2.9357 data: 0.0075 max mem: 33301 +Epoch: [22] [1320/4276] eta: 2:27:03 lr: 2.3993556321661934e-05 loss: 0.1086 (0.1115) time: 2.9299 data: 0.0075 max mem: 33301 +Epoch: [22] [1330/4276] eta: 2:26:32 lr: 2.3990701701726386e-05 loss: 0.1104 (0.1115) time: 2.9314 data: 0.0076 max mem: 33301 +Epoch: [22] [1340/4276] eta: 2:26:01 lr: 2.398784704404953e-05 loss: 0.1038 (0.1114) time: 2.9331 data: 0.0075 max mem: 33301 +Epoch: [22] [1350/4276] eta: 2:25:30 lr: 2.3984992348625886e-05 loss: 0.1023 (0.1114) time: 2.9326 data: 0.0076 max mem: 33301 +Epoch: [22] [1360/4276] eta: 2:24:59 lr: 2.398213761544996e-05 loss: 0.1025 (0.1114) time: 2.9307 data: 0.0075 max mem: 33301 +Epoch: [22] [1370/4276] eta: 2:24:28 lr: 2.3979282844516263e-05 loss: 0.1076 (0.1114) time: 2.9292 data: 0.0075 max mem: 33301 +Epoch: [22] [1380/4276] eta: 2:23:57 lr: 2.397642803581929e-05 loss: 0.1151 (0.1115) time: 2.9245 data: 0.0076 max mem: 33301 +Epoch: [22] [1390/4276] eta: 2:23:26 lr: 2.3973573189353558e-05 loss: 0.1151 (0.1115) time: 2.9156 data: 0.0080 max mem: 33301 +Epoch: [22] [1400/4276] eta: 2:22:55 lr: 2.397071830511356e-05 loss: 0.1068 (0.1115) time: 2.9170 data: 0.0080 max mem: 33301 +Epoch: [22] [1410/4276] eta: 2:22:24 lr: 2.396786338309381e-05 loss: 0.1068 (0.1116) time: 2.9264 data: 0.0081 max mem: 33301 +Epoch: [22] [1420/4276] eta: 2:21:53 lr: 2.396500842328879e-05 loss: 0.1046 (0.1116) time: 2.9296 data: 0.0079 max mem: 33301 +Epoch: [22] [1430/4276] eta: 2:21:22 lr: 2.3962153425693013e-05 loss: 0.0997 (0.1115) time: 2.9293 data: 0.0075 max mem: 33301 +Epoch: [22] [1440/4276] eta: 2:20:51 lr: 2.3959298390300965e-05 loss: 0.1053 (0.1115) time: 2.9295 data: 0.0076 max mem: 33301 +Epoch: [22] [1450/4276] eta: 2:20:21 lr: 2.3956443317107157e-05 loss: 0.1059 (0.1114) time: 2.9309 data: 0.0076 max mem: 33301 +Epoch: [22] [1460/4276] eta: 2:19:50 lr: 2.3953588206106065e-05 loss: 0.0887 (0.1114) time: 2.9361 data: 0.0077 max mem: 33301 +Epoch: [22] [1470/4276] eta: 2:19:19 lr: 2.3950733057292188e-05 loss: 0.1063 (0.1113) time: 2.9352 data: 0.0079 max mem: 33301 +Epoch: [22] [1480/4276] eta: 2:18:48 lr: 2.394787787066002e-05 loss: 0.1007 (0.1113) time: 2.9274 data: 0.0082 max mem: 33301 +Epoch: [22] [1490/4276] eta: 2:18:18 lr: 2.394502264620405e-05 loss: 0.0905 (0.1112) time: 2.9292 data: 0.0080 max mem: 33301 +Epoch: [22] [1500/4276] eta: 2:17:46 lr: 2.3942167383918756e-05 loss: 0.0949 (0.1111) time: 2.9043 data: 0.0080 max mem: 33301 +Epoch: [22] [1510/4276] eta: 2:17:15 lr: 2.3939312083798636e-05 loss: 0.0968 (0.1110) time: 2.8769 data: 0.0083 max mem: 33301 +Epoch: [22] [1520/4276] eta: 2:16:43 lr: 2.3936456745838165e-05 loss: 0.0977 (0.1110) time: 2.8781 data: 0.0082 max mem: 33301 +Epoch: [22] [1530/4276] eta: 2:16:12 lr: 2.3933601370031835e-05 loss: 0.0935 (0.1109) time: 2.8982 data: 0.0087 max mem: 33301 +Epoch: [22] [1540/4276] eta: 2:15:42 lr: 2.393074595637412e-05 loss: 0.1026 (0.1109) time: 2.9245 data: 0.0093 max mem: 33301 +Epoch: [22] [1550/4276] eta: 2:15:11 lr: 2.39278905048595e-05 loss: 0.1131 (0.1110) time: 2.9359 data: 0.0091 max mem: 33301 +Epoch: [22] [1560/4276] eta: 2:14:40 lr: 2.3925035015482462e-05 loss: 0.0964 (0.1109) time: 2.9091 data: 0.0092 max mem: 33301 +Epoch: [22] [1570/4276] eta: 2:14:08 lr: 2.3922179488237474e-05 loss: 0.0979 (0.1108) time: 2.8777 data: 0.0090 max mem: 33301 +Epoch: [22] [1580/4276] eta: 2:13:38 lr: 2.391932392311901e-05 loss: 0.0996 (0.1107) time: 2.8970 data: 0.0086 max mem: 33301 +Epoch: [22] [1590/4276] eta: 2:13:07 lr: 2.3916468320121547e-05 loss: 0.1030 (0.1108) time: 2.9236 data: 0.0096 max mem: 33301 +Epoch: [22] [1600/4276] eta: 2:12:37 lr: 2.3913612679239563e-05 loss: 0.1043 (0.1108) time: 2.9330 data: 0.0108 max mem: 33301 +Epoch: [22] [1610/4276] eta: 2:12:06 lr: 2.3910757000467522e-05 loss: 0.0963 (0.1108) time: 2.9348 data: 0.0105 max mem: 33301 +Epoch: [22] [1620/4276] eta: 2:11:36 lr: 2.3907901283799888e-05 loss: 0.1015 (0.1107) time: 2.9327 data: 0.0094 max mem: 33301 +Epoch: [22] [1630/4276] eta: 2:11:06 lr: 2.3905045529231138e-05 loss: 0.1033 (0.1108) time: 2.9310 data: 0.0085 max mem: 33301 +Epoch: [22] [1640/4276] eta: 2:10:35 lr: 2.3902189736755742e-05 loss: 0.0985 (0.1106) time: 2.9300 data: 0.0083 max mem: 33301 +Epoch: [22] [1650/4276] eta: 2:10:05 lr: 2.3899333906368148e-05 loss: 0.0973 (0.1106) time: 2.9315 data: 0.0085 max mem: 33301 +Epoch: [22] [1660/4276] eta: 2:09:34 lr: 2.3896478038062832e-05 loss: 0.0973 (0.1105) time: 2.9320 data: 0.0087 max mem: 33301 +Epoch: [22] [1670/4276] eta: 2:09:04 lr: 2.389362213183425e-05 loss: 0.0911 (0.1104) time: 2.9317 data: 0.0085 max mem: 33301 +Epoch: [22] [1680/4276] eta: 2:08:34 lr: 2.389076618767687e-05 loss: 0.0911 (0.1104) time: 2.9324 data: 0.0083 max mem: 33301 +Epoch: [22] [1690/4276] eta: 2:08:03 lr: 2.3887910205585135e-05 loss: 0.0967 (0.1103) time: 2.9199 data: 0.0086 max mem: 33301 +Epoch: [22] [1700/4276] eta: 2:07:33 lr: 2.388505418555351e-05 loss: 0.1007 (0.1103) time: 2.9154 data: 0.0091 max mem: 33301 +Epoch: [22] [1710/4276] eta: 2:07:02 lr: 2.3882198127576455e-05 loss: 0.1012 (0.1103) time: 2.9223 data: 0.0090 max mem: 33301 +Epoch: [22] [1720/4276] eta: 2:06:32 lr: 2.3879342031648422e-05 loss: 0.1009 (0.1102) time: 2.9268 data: 0.0087 max mem: 33301 +Epoch: [22] [1730/4276] eta: 2:06:02 lr: 2.3876485897763858e-05 loss: 0.0978 (0.1102) time: 2.9313 data: 0.0089 max mem: 33301 +Epoch: [22] [1740/4276] eta: 2:05:31 lr: 2.387362972591721e-05 loss: 0.0978 (0.1102) time: 2.9322 data: 0.0093 max mem: 33301 +Epoch: [22] [1750/4276] eta: 2:05:01 lr: 2.3870773516102936e-05 loss: 0.1074 (0.1102) time: 2.9312 data: 0.0092 max mem: 33301 +Epoch: [22] [1760/4276] eta: 2:04:31 lr: 2.3867917268315486e-05 loss: 0.1035 (0.1101) time: 2.9315 data: 0.0088 max mem: 33301 +Epoch: [22] [1770/4276] eta: 2:04:01 lr: 2.3865060982549295e-05 loss: 0.1011 (0.1101) time: 2.9332 data: 0.0089 max mem: 33301 +Epoch: [22] [1780/4276] eta: 2:03:30 lr: 2.3862204658798812e-05 loss: 0.0991 (0.1101) time: 2.9348 data: 0.0093 max mem: 33301 +Epoch: [22] [1790/4276] eta: 2:03:00 lr: 2.385934829705848e-05 loss: 0.0991 (0.1100) time: 2.9340 data: 0.0091 max mem: 33301 +Epoch: [22] [1800/4276] eta: 2:02:30 lr: 2.3856491897322747e-05 loss: 0.1009 (0.1100) time: 2.9313 data: 0.0087 max mem: 33301 +Epoch: [22] [1810/4276] eta: 2:02:00 lr: 2.385363545958604e-05 loss: 0.1042 (0.1100) time: 2.9315 data: 0.0089 max mem: 33301 +Epoch: [22] [1820/4276] eta: 2:01:30 lr: 2.3850778983842804e-05 loss: 0.1081 (0.1101) time: 2.9326 data: 0.0093 max mem: 33301 +Epoch: [22] [1830/4276] eta: 2:00:59 lr: 2.3847922470087476e-05 loss: 0.0993 (0.1101) time: 2.9324 data: 0.0090 max mem: 33301 +Epoch: [22] [1840/4276] eta: 2:00:30 lr: 2.384506591831449e-05 loss: 0.0911 (0.1100) time: 2.9385 data: 0.0088 max mem: 33301 +Epoch: [22] [1850/4276] eta: 1:59:59 lr: 2.3842209328518278e-05 loss: 0.0975 (0.1100) time: 2.9381 data: 0.0090 max mem: 33301 +Epoch: [22] [1860/4276] eta: 1:59:29 lr: 2.3839352700693274e-05 loss: 0.1026 (0.1100) time: 2.9315 data: 0.0096 max mem: 33301 +Epoch: [22] [1870/4276] eta: 1:58:59 lr: 2.3836496034833912e-05 loss: 0.1036 (0.1101) time: 2.9306 data: 0.0093 max mem: 33301 +Epoch: [22] [1880/4276] eta: 1:58:29 lr: 2.3833639330934612e-05 loss: 0.1088 (0.1101) time: 2.9292 data: 0.0088 max mem: 33301 +Epoch: [22] [1890/4276] eta: 1:57:59 lr: 2.3830782588989804e-05 loss: 0.0996 (0.1101) time: 2.9302 data: 0.0091 max mem: 33301 +Epoch: [22] [1900/4276] eta: 1:57:29 lr: 2.382792580899392e-05 loss: 0.1020 (0.1101) time: 2.9312 data: 0.0096 max mem: 33301 +Epoch: [22] [1910/4276] eta: 1:56:59 lr: 2.3825068990941378e-05 loss: 0.1060 (0.1101) time: 2.9316 data: 0.0093 max mem: 33301 +Epoch: [22] [1920/4276] eta: 1:56:28 lr: 2.3822212134826598e-05 loss: 0.0990 (0.1100) time: 2.9317 data: 0.0087 max mem: 33301 +Epoch: [22] [1930/4276] eta: 1:55:58 lr: 2.381935524064401e-05 loss: 0.0936 (0.1099) time: 2.9309 data: 0.0089 max mem: 33301 +Epoch: [22] [1940/4276] eta: 1:55:28 lr: 2.3816498308388026e-05 loss: 0.0961 (0.1099) time: 2.9317 data: 0.0093 max mem: 33301 +Epoch: [22] [1950/4276] eta: 1:54:58 lr: 2.381364133805307e-05 loss: 0.1079 (0.1100) time: 2.9104 data: 0.0088 max mem: 33301 +Epoch: [22] [1960/4276] eta: 1:54:27 lr: 2.381078432963355e-05 loss: 0.1078 (0.1099) time: 2.8803 data: 0.0082 max mem: 33301 +Epoch: [22] [1970/4276] eta: 1:53:56 lr: 2.3807927283123883e-05 loss: 0.0842 (0.1098) time: 2.8747 data: 0.0080 max mem: 33301 +Epoch: [22] [1980/4276] eta: 1:53:26 lr: 2.380507019851849e-05 loss: 0.0943 (0.1097) time: 2.8776 data: 0.0078 max mem: 33301 +Epoch: [22] [1990/4276] eta: 1:52:55 lr: 2.380221307581178e-05 loss: 0.0946 (0.1097) time: 2.8807 data: 0.0080 max mem: 33301 +Epoch: [22] [2000/4276] eta: 1:52:24 lr: 2.3799355914998157e-05 loss: 0.1037 (0.1098) time: 2.8832 data: 0.0080 max mem: 33301 +Epoch: [22] [2010/4276] eta: 1:51:54 lr: 2.379649871607203e-05 loss: 0.1037 (0.1098) time: 2.8952 data: 0.0080 max mem: 33301 +Epoch: [22] [2020/4276] eta: 1:51:24 lr: 2.379364147902781e-05 loss: 0.0951 (0.1098) time: 2.9199 data: 0.0091 max mem: 33301 +Epoch: [22] [2030/4276] eta: 1:50:54 lr: 2.3790784203859904e-05 loss: 0.0938 (0.1097) time: 2.9343 data: 0.0095 max mem: 33301 +Epoch: [22] [2040/4276] eta: 1:50:24 lr: 2.378792689056271e-05 loss: 0.0878 (0.1097) time: 2.9357 data: 0.0091 max mem: 33301 +Epoch: [22] [2050/4276] eta: 1:49:54 lr: 2.3785069539130632e-05 loss: 0.1059 (0.1097) time: 2.9357 data: 0.0095 max mem: 33301 +Epoch: [22] [2060/4276] eta: 1:49:24 lr: 2.3782212149558073e-05 loss: 0.1084 (0.1097) time: 2.9346 data: 0.0100 max mem: 33301 +Epoch: [22] [2070/4276] eta: 1:48:55 lr: 2.3779354721839437e-05 loss: 0.0958 (0.1097) time: 2.9365 data: 0.0097 max mem: 33301 +Epoch: [22] [2080/4276] eta: 1:48:25 lr: 2.3776497255969108e-05 loss: 0.1025 (0.1098) time: 2.9336 data: 0.0092 max mem: 33301 +Epoch: [22] [2090/4276] eta: 1:47:55 lr: 2.3773639751941487e-05 loss: 0.1084 (0.1098) time: 2.9291 data: 0.0084 max mem: 33301 +Epoch: [22] [2100/4276] eta: 1:47:24 lr: 2.3770782209750976e-05 loss: 0.1026 (0.1097) time: 2.9164 data: 0.0083 max mem: 33301 +Epoch: [22] [2110/4276] eta: 1:46:54 lr: 2.3767924629391964e-05 loss: 0.0992 (0.1097) time: 2.8911 data: 0.0092 max mem: 33301 +Epoch: [22] [2120/4276] eta: 1:46:24 lr: 2.3765067010858834e-05 loss: 0.0825 (0.1095) time: 2.8825 data: 0.0090 max mem: 33301 +Epoch: [22] [2130/4276] eta: 1:45:53 lr: 2.3762209354145985e-05 loss: 0.0898 (0.1095) time: 2.8848 data: 0.0083 max mem: 33301 +Epoch: [22] [2140/4276] eta: 1:45:23 lr: 2.3759351659247804e-05 loss: 0.0928 (0.1094) time: 2.8846 data: 0.0083 max mem: 33301 +Epoch: [22] [2150/4276] eta: 1:44:52 lr: 2.3756493926158675e-05 loss: 0.1021 (0.1094) time: 2.8857 data: 0.0091 max mem: 33301 +Epoch: [22] [2160/4276] eta: 1:44:22 lr: 2.3753636154872986e-05 loss: 0.1063 (0.1094) time: 2.8840 data: 0.0090 max mem: 33301 +Epoch: [22] [2170/4276] eta: 1:43:52 lr: 2.3750778345385114e-05 loss: 0.0974 (0.1094) time: 2.8855 data: 0.0090 max mem: 33301 +Epoch: [22] [2180/4276] eta: 1:43:22 lr: 2.3747920497689453e-05 loss: 0.1019 (0.1094) time: 2.9071 data: 0.0098 max mem: 33301 +Epoch: [22] [2190/4276] eta: 1:42:52 lr: 2.3745062611780368e-05 loss: 0.0996 (0.1094) time: 2.9300 data: 0.0102 max mem: 33301 +Epoch: [22] [2200/4276] eta: 1:42:22 lr: 2.374220468765224e-05 loss: 0.1159 (0.1094) time: 2.9355 data: 0.0104 max mem: 33301 +Epoch: [22] [2210/4276] eta: 1:41:53 lr: 2.3739346725299456e-05 loss: 0.1180 (0.1094) time: 2.9372 data: 0.0104 max mem: 33301 +Epoch: [22] [2220/4276] eta: 1:41:23 lr: 2.373648872471639e-05 loss: 0.1107 (0.1095) time: 2.9373 data: 0.0104 max mem: 33301 +Epoch: [22] [2230/4276] eta: 1:40:53 lr: 2.373363068589741e-05 loss: 0.1107 (0.1094) time: 2.9425 data: 0.0100 max mem: 33301 +Epoch: [22] [2240/4276] eta: 1:40:23 lr: 2.3730772608836884e-05 loss: 0.1012 (0.1094) time: 2.9373 data: 0.0096 max mem: 33301 +Epoch: [22] [2250/4276] eta: 1:39:53 lr: 2.3727914493529193e-05 loss: 0.0924 (0.1094) time: 2.9308 data: 0.0095 max mem: 33301 +Epoch: [22] [2260/4276] eta: 1:39:24 lr: 2.372505633996871e-05 loss: 0.0963 (0.1093) time: 2.9347 data: 0.0097 max mem: 33301 +Epoch: [22] [2270/4276] eta: 1:38:54 lr: 2.3722198148149785e-05 loss: 0.0987 (0.1093) time: 2.9228 data: 0.0097 max mem: 33301 +Epoch: [22] [2280/4276] eta: 1:38:23 lr: 2.3719339918066796e-05 loss: 0.1040 (0.1093) time: 2.8965 data: 0.0087 max mem: 33301 +Epoch: [22] [2290/4276] eta: 1:37:53 lr: 2.3716481649714102e-05 loss: 0.1082 (0.1093) time: 2.8803 data: 0.0079 max mem: 33301 +Epoch: [22] [2300/4276] eta: 1:37:23 lr: 2.3713623343086076e-05 loss: 0.1081 (0.1093) time: 2.8790 data: 0.0076 max mem: 33301 +Epoch: [22] [2310/4276] eta: 1:36:53 lr: 2.371076499817707e-05 loss: 0.1081 (0.1094) time: 2.8783 data: 0.0074 max mem: 33301 +Epoch: [22] [2320/4276] eta: 1:36:22 lr: 2.370790661498144e-05 loss: 0.1172 (0.1094) time: 2.8776 data: 0.0074 max mem: 33301 +Epoch: [22] [2330/4276] eta: 1:35:52 lr: 2.3705048193493556e-05 loss: 0.1169 (0.1094) time: 2.8778 data: 0.0073 max mem: 33301 +Epoch: [22] [2340/4276] eta: 1:35:22 lr: 2.370218973370777e-05 loss: 0.1139 (0.1095) time: 2.8940 data: 0.0082 max mem: 33301 +Epoch: [22] [2350/4276] eta: 1:34:52 lr: 2.369933123561843e-05 loss: 0.1021 (0.1095) time: 2.9152 data: 0.0089 max mem: 33301 +Epoch: [22] [2360/4276] eta: 1:34:23 lr: 2.3696472699219897e-05 loss: 0.0980 (0.1094) time: 2.9339 data: 0.0089 max mem: 33301 +Epoch: [22] [2370/4276] eta: 1:33:53 lr: 2.3693614124506516e-05 loss: 0.1020 (0.1095) time: 2.9369 data: 0.0095 max mem: 33301 +Epoch: [22] [2380/4276] eta: 1:33:23 lr: 2.369075551147265e-05 loss: 0.1158 (0.1095) time: 2.9294 data: 0.0093 max mem: 33301 +Epoch: [22] [2390/4276] eta: 1:32:53 lr: 2.368789686011263e-05 loss: 0.1151 (0.1095) time: 2.9334 data: 0.0087 max mem: 33301 +Epoch: [22] [2400/4276] eta: 1:32:24 lr: 2.368503817042081e-05 loss: 0.1027 (0.1095) time: 2.9339 data: 0.0087 max mem: 33301 +Epoch: [22] [2410/4276] eta: 1:31:54 lr: 2.3682179442391543e-05 loss: 0.1061 (0.1095) time: 2.9346 data: 0.0089 max mem: 33301 +Epoch: [22] [2420/4276] eta: 1:31:24 lr: 2.3679320676019164e-05 loss: 0.1061 (0.1095) time: 2.9333 data: 0.0089 max mem: 33301 +Epoch: [22] [2430/4276] eta: 1:30:54 lr: 2.3676461871298018e-05 loss: 0.1078 (0.1095) time: 2.9287 data: 0.0085 max mem: 33301 +Epoch: [22] [2440/4276] eta: 1:30:25 lr: 2.3673603028222448e-05 loss: 0.1142 (0.1095) time: 2.9275 data: 0.0081 max mem: 33301 +Epoch: [22] [2450/4276] eta: 1:29:55 lr: 2.3670744146786782e-05 loss: 0.1059 (0.1095) time: 2.9244 data: 0.0088 max mem: 33301 +Epoch: [22] [2460/4276] eta: 1:29:25 lr: 2.3667885226985375e-05 loss: 0.1082 (0.1095) time: 2.9265 data: 0.0088 max mem: 33301 +Epoch: [22] [2470/4276] eta: 1:28:56 lr: 2.366502626881255e-05 loss: 0.1169 (0.1096) time: 2.9328 data: 0.0080 max mem: 33301 +Epoch: [22] [2480/4276] eta: 1:28:26 lr: 2.3662167272262642e-05 loss: 0.1202 (0.1096) time: 2.9331 data: 0.0079 max mem: 33301 +Epoch: [22] [2490/4276] eta: 1:27:56 lr: 2.365930823732999e-05 loss: 0.1105 (0.1096) time: 2.9327 data: 0.0078 max mem: 33301 +Epoch: [22] [2500/4276] eta: 1:27:26 lr: 2.365644916400892e-05 loss: 0.1123 (0.1096) time: 2.9327 data: 0.0076 max mem: 33301 +Epoch: [22] [2510/4276] eta: 1:26:57 lr: 2.365359005229376e-05 loss: 0.1197 (0.1096) time: 2.9324 data: 0.0079 max mem: 33301 +Epoch: [22] [2520/4276] eta: 1:26:27 lr: 2.365073090217884e-05 loss: 0.1008 (0.1096) time: 2.9282 data: 0.0078 max mem: 33301 +Epoch: [22] [2530/4276] eta: 1:25:57 lr: 2.364787171365849e-05 loss: 0.0882 (0.1095) time: 2.9279 data: 0.0074 max mem: 33301 +Epoch: [22] [2540/4276] eta: 1:25:28 lr: 2.3645012486727027e-05 loss: 0.0975 (0.1095) time: 2.9396 data: 0.0075 max mem: 33301 +Epoch: [22] [2550/4276] eta: 1:24:58 lr: 2.3642153221378776e-05 loss: 0.1017 (0.1095) time: 2.9415 data: 0.0074 max mem: 33301 +Epoch: [22] [2560/4276] eta: 1:24:28 lr: 2.3639293917608064e-05 loss: 0.0941 (0.1094) time: 2.9351 data: 0.0075 max mem: 33301 +Epoch: [22] [2570/4276] eta: 1:23:59 lr: 2.363643457540921e-05 loss: 0.0956 (0.1094) time: 2.9343 data: 0.0075 max mem: 33301 +Epoch: [22] [2580/4276] eta: 1:23:29 lr: 2.3633575194776526e-05 loss: 0.1017 (0.1094) time: 2.9268 data: 0.0087 max mem: 33301 +Epoch: [22] [2590/4276] eta: 1:22:59 lr: 2.3630715775704325e-05 loss: 0.0910 (0.1093) time: 2.9269 data: 0.0087 max mem: 33301 +Epoch: [22] [2600/4276] eta: 1:22:30 lr: 2.3627856318186935e-05 loss: 0.0905 (0.1093) time: 2.9307 data: 0.0074 max mem: 33301 +Epoch: [22] [2610/4276] eta: 1:22:00 lr: 2.3624996822218664e-05 loss: 0.0931 (0.1092) time: 2.9219 data: 0.0081 max mem: 33301 +Epoch: [22] [2620/4276] eta: 1:21:30 lr: 2.3622137287793823e-05 loss: 0.1074 (0.1093) time: 2.9239 data: 0.0082 max mem: 33301 +Epoch: [22] [2630/4276] eta: 1:21:00 lr: 2.3619277714906714e-05 loss: 0.1019 (0.1092) time: 2.9312 data: 0.0075 max mem: 33301 +Epoch: [22] [2640/4276] eta: 1:20:31 lr: 2.361641810355166e-05 loss: 0.0974 (0.1092) time: 2.9320 data: 0.0075 max mem: 33301 +Epoch: [22] [2650/4276] eta: 1:20:01 lr: 2.3613558453722965e-05 loss: 0.0945 (0.1092) time: 2.9324 data: 0.0075 max mem: 33301 +Epoch: [22] [2660/4276] eta: 1:19:31 lr: 2.361069876541492e-05 loss: 0.1013 (0.1092) time: 2.9318 data: 0.0076 max mem: 33301 +Epoch: [22] [2670/4276] eta: 1:19:02 lr: 2.3607839038621844e-05 loss: 0.1070 (0.1092) time: 2.9323 data: 0.0075 max mem: 33301 +Epoch: [22] [2680/4276] eta: 1:18:32 lr: 2.3604979273338035e-05 loss: 0.1078 (0.1092) time: 2.9320 data: 0.0075 max mem: 33301 +Epoch: [22] [2690/4276] eta: 1:18:02 lr: 2.3602119469557797e-05 loss: 0.1057 (0.1092) time: 2.9313 data: 0.0075 max mem: 33301 +Epoch: [22] [2700/4276] eta: 1:17:33 lr: 2.3599259627275417e-05 loss: 0.0987 (0.1092) time: 2.9306 data: 0.0080 max mem: 33301 +Epoch: [22] [2710/4276] eta: 1:17:03 lr: 2.35963997464852e-05 loss: 0.1046 (0.1092) time: 2.9305 data: 0.0080 max mem: 33301 +Epoch: [22] [2720/4276] eta: 1:16:34 lr: 2.3593539827181443e-05 loss: 0.1012 (0.1091) time: 2.9380 data: 0.0075 max mem: 33301 +Epoch: [22] [2730/4276] eta: 1:16:04 lr: 2.3590679869358446e-05 loss: 0.1037 (0.1092) time: 2.9385 data: 0.0075 max mem: 33301 +Epoch: [22] [2740/4276] eta: 1:15:34 lr: 2.3587819873010482e-05 loss: 0.1092 (0.1092) time: 2.9336 data: 0.0078 max mem: 33301 +Epoch: [22] [2750/4276] eta: 1:15:05 lr: 2.358495983813186e-05 loss: 0.1095 (0.1092) time: 2.9342 data: 0.0077 max mem: 33301 +Epoch: [22] [2760/4276] eta: 1:14:35 lr: 2.3582099764716862e-05 loss: 0.0990 (0.1092) time: 2.9280 data: 0.0074 max mem: 33301 +Epoch: [22] [2770/4276] eta: 1:14:06 lr: 2.357923965275978e-05 loss: 0.0990 (0.1092) time: 2.9430 data: 0.0074 max mem: 33301 +Epoch: [22] [2780/4276] eta: 1:13:36 lr: 2.357637950225489e-05 loss: 0.1003 (0.1092) time: 2.9486 data: 0.0077 max mem: 33301 +Epoch: [22] [2790/4276] eta: 1:13:06 lr: 2.3573519313196486e-05 loss: 0.1049 (0.1092) time: 2.9319 data: 0.0077 max mem: 33301 +Epoch: [22] [2800/4276] eta: 1:12:37 lr: 2.357065908557885e-05 loss: 0.0999 (0.1092) time: 2.9294 data: 0.0075 max mem: 33301 +Epoch: [22] [2810/4276] eta: 1:12:07 lr: 2.3567798819396257e-05 loss: 0.0857 (0.1091) time: 2.9297 data: 0.0075 max mem: 33301 +Epoch: [22] [2820/4276] eta: 1:11:37 lr: 2.3564938514642988e-05 loss: 0.0843 (0.1090) time: 2.9325 data: 0.0075 max mem: 33301 +Epoch: [22] [2830/4276] eta: 1:11:08 lr: 2.356207817131332e-05 loss: 0.0944 (0.1090) time: 2.9377 data: 0.0075 max mem: 33301 +Epoch: [22] [2840/4276] eta: 1:10:38 lr: 2.355921778940154e-05 loss: 0.1085 (0.1090) time: 2.9390 data: 0.0076 max mem: 33301 +Epoch: [22] [2850/4276] eta: 1:10:09 lr: 2.3556357368901913e-05 loss: 0.1110 (0.1091) time: 2.9358 data: 0.0076 max mem: 33301 +Epoch: [22] [2860/4276] eta: 1:09:39 lr: 2.355349690980871e-05 loss: 0.1082 (0.1091) time: 2.9348 data: 0.0075 max mem: 33301 +Epoch: [22] [2870/4276] eta: 1:09:09 lr: 2.3550636412116206e-05 loss: 0.1026 (0.1091) time: 2.9364 data: 0.0077 max mem: 33301 +Epoch: [22] [2880/4276] eta: 1:08:40 lr: 2.3547775875818678e-05 loss: 0.1117 (0.1091) time: 2.9362 data: 0.0080 max mem: 33301 +Epoch: [22] [2890/4276] eta: 1:08:10 lr: 2.3544915300910382e-05 loss: 0.1117 (0.1091) time: 2.9336 data: 0.0082 max mem: 33301 +Epoch: [22] [2900/4276] eta: 1:07:41 lr: 2.3542054687385584e-05 loss: 0.0958 (0.1091) time: 2.9316 data: 0.0082 max mem: 33301 +Epoch: [22] [2910/4276] eta: 1:07:11 lr: 2.353919403523856e-05 loss: 0.1039 (0.1091) time: 2.9323 data: 0.0079 max mem: 33301 +Epoch: [22] [2920/4276] eta: 1:06:42 lr: 2.3536333344463567e-05 loss: 0.1112 (0.1091) time: 2.9417 data: 0.0082 max mem: 33301 +Epoch: [22] [2930/4276] eta: 1:06:12 lr: 2.3533472615054866e-05 loss: 0.1001 (0.1091) time: 2.9413 data: 0.0083 max mem: 33301 +Epoch: [22] [2940/4276] eta: 1:05:42 lr: 2.3530611847006718e-05 loss: 0.1001 (0.1091) time: 2.9486 data: 0.0080 max mem: 33301 +Epoch: [22] [2950/4276] eta: 1:05:13 lr: 2.3527751040313382e-05 loss: 0.1057 (0.1091) time: 2.9517 data: 0.0079 max mem: 33301 +Epoch: [22] [2960/4276] eta: 1:04:43 lr: 2.3524890194969114e-05 loss: 0.0979 (0.1090) time: 2.9387 data: 0.0082 max mem: 33301 +Epoch: [22] [2970/4276] eta: 1:04:14 lr: 2.352202931096817e-05 loss: 0.1126 (0.1091) time: 2.9445 data: 0.0082 max mem: 33301 +Epoch: [22] [2980/4276] eta: 1:03:44 lr: 2.3519168388304798e-05 loss: 0.1126 (0.1091) time: 2.9306 data: 0.0085 max mem: 33301 +Epoch: [22] [2990/4276] eta: 1:03:15 lr: 2.351630742697326e-05 loss: 0.1054 (0.1090) time: 2.9233 data: 0.0086 max mem: 33301 +Epoch: [22] [3000/4276] eta: 1:02:45 lr: 2.3513446426967804e-05 loss: 0.1019 (0.1090) time: 2.9343 data: 0.0084 max mem: 33301 +Epoch: [22] [3010/4276] eta: 1:02:15 lr: 2.3510585388282665e-05 loss: 0.1044 (0.1090) time: 2.9335 data: 0.0080 max mem: 33301 +Epoch: [22] [3020/4276] eta: 1:01:46 lr: 2.3507724310912104e-05 loss: 0.1044 (0.1090) time: 2.9329 data: 0.0076 max mem: 33301 +Epoch: [22] [3030/4276] eta: 1:01:16 lr: 2.3504863194850363e-05 loss: 0.0999 (0.1090) time: 2.9301 data: 0.0078 max mem: 33301 +Epoch: [22] [3040/4276] eta: 1:00:47 lr: 2.350200204009169e-05 loss: 0.1058 (0.1090) time: 2.9264 data: 0.0083 max mem: 33301 +Epoch: [22] [3050/4276] eta: 1:00:17 lr: 2.3499140846630318e-05 loss: 0.1061 (0.1090) time: 2.9280 data: 0.0080 max mem: 33301 +Epoch: [22] [3060/4276] eta: 0:59:47 lr: 2.349627961446049e-05 loss: 0.0893 (0.1090) time: 2.9320 data: 0.0075 max mem: 33301 +Epoch: [22] [3070/4276] eta: 0:59:18 lr: 2.3493418343576445e-05 loss: 0.0949 (0.1090) time: 2.9307 data: 0.0078 max mem: 33301 +Epoch: [22] [3080/4276] eta: 0:58:48 lr: 2.349055703397243e-05 loss: 0.1007 (0.1090) time: 2.9275 data: 0.0079 max mem: 33301 +Epoch: [22] [3090/4276] eta: 0:58:19 lr: 2.3487695685642666e-05 loss: 0.0920 (0.1089) time: 2.9295 data: 0.0076 max mem: 33301 +Epoch: [22] [3100/4276] eta: 0:57:49 lr: 2.348483429858139e-05 loss: 0.0873 (0.1089) time: 2.9306 data: 0.0075 max mem: 33301 +Epoch: [22] [3110/4276] eta: 0:57:19 lr: 2.3481972872782847e-05 loss: 0.0954 (0.1088) time: 2.9280 data: 0.0076 max mem: 33301 +Epoch: [22] [3120/4276] eta: 0:56:50 lr: 2.3479111408241248e-05 loss: 0.0910 (0.1088) time: 2.9313 data: 0.0075 max mem: 33301 +Epoch: [22] [3130/4276] eta: 0:56:20 lr: 2.3476249904950836e-05 loss: 0.0924 (0.1088) time: 2.9307 data: 0.0075 max mem: 33301 +Epoch: [22] [3140/4276] eta: 0:55:51 lr: 2.3473388362905827e-05 loss: 0.0965 (0.1088) time: 2.9269 data: 0.0075 max mem: 33301 +Epoch: [22] [3150/4276] eta: 0:55:21 lr: 2.3470526782100465e-05 loss: 0.1001 (0.1087) time: 2.9261 data: 0.0075 max mem: 33301 +Epoch: [22] [3160/4276] eta: 0:54:52 lr: 2.3467665162528953e-05 loss: 0.0976 (0.1087) time: 2.9242 data: 0.0074 max mem: 33301 +Epoch: [22] [3170/4276] eta: 0:54:22 lr: 2.3464803504185524e-05 loss: 0.1021 (0.1087) time: 2.9219 data: 0.0073 max mem: 33301 +Epoch: [22] [3180/4276] eta: 0:53:52 lr: 2.34619418070644e-05 loss: 0.1033 (0.1087) time: 2.9209 data: 0.0073 max mem: 33301 +Epoch: [22] [3190/4276] eta: 0:53:23 lr: 2.34590800711598e-05 loss: 0.0990 (0.1087) time: 2.9231 data: 0.0074 max mem: 33301 +Epoch: [22] [3200/4276] eta: 0:52:53 lr: 2.3456218296465933e-05 loss: 0.0999 (0.1087) time: 2.9270 data: 0.0075 max mem: 33301 +Epoch: [22] [3210/4276] eta: 0:52:24 lr: 2.3453356482977022e-05 loss: 0.1045 (0.1087) time: 2.9476 data: 0.0075 max mem: 33301 +Epoch: [22] [3220/4276] eta: 0:51:54 lr: 2.345049463068728e-05 loss: 0.1086 (0.1087) time: 2.9481 data: 0.0075 max mem: 33301 +Epoch: [22] [3230/4276] eta: 0:51:25 lr: 2.3447632739590927e-05 loss: 0.1084 (0.1087) time: 2.9281 data: 0.0075 max mem: 33301 +Epoch: [22] [3240/4276] eta: 0:50:55 lr: 2.344477080968216e-05 loss: 0.1115 (0.1088) time: 2.9274 data: 0.0075 max mem: 33301 +Epoch: [22] [3250/4276] eta: 0:50:26 lr: 2.3441908840955193e-05 loss: 0.1076 (0.1088) time: 2.9282 data: 0.0074 max mem: 33301 +Epoch: [22] [3260/4276] eta: 0:49:56 lr: 2.3439046833404234e-05 loss: 0.1070 (0.1089) time: 2.9272 data: 0.0075 max mem: 33301 +Epoch: [22] [3270/4276] eta: 0:49:26 lr: 2.3436184787023496e-05 loss: 0.1073 (0.1089) time: 2.9256 data: 0.0075 max mem: 33301 +Epoch: [22] [3280/4276] eta: 0:48:57 lr: 2.343332270180717e-05 loss: 0.1031 (0.1089) time: 2.9227 data: 0.0078 max mem: 33301 +Epoch: [22] 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2.334171543492955e-05 loss: 0.0973 (0.1092) time: 2.9350 data: 0.0088 max mem: 33301 +Epoch: [22] [3610/4276] eta: 0:32:42 lr: 2.3338852064876784e-05 loss: 0.0996 (0.1091) time: 2.9348 data: 0.0089 max mem: 33301 +Epoch: [22] [3620/4276] eta: 0:32:13 lr: 2.33359886557904e-05 loss: 0.0986 (0.1091) time: 2.9369 data: 0.0088 max mem: 33301 +Epoch: [22] [3630/4276] eta: 0:31:43 lr: 2.333312520766453e-05 loss: 0.0998 (0.1091) time: 2.9368 data: 0.0083 max mem: 33301 +Epoch: [22] [3640/4276] eta: 0:31:14 lr: 2.3330261720493326e-05 loss: 0.0960 (0.1091) time: 2.9384 data: 0.0084 max mem: 33301 +Epoch: [22] [3650/4276] eta: 0:30:44 lr: 2.3327398194270934e-05 loss: 0.0860 (0.1090) time: 2.9379 data: 0.0081 max mem: 33301 +Epoch: [22] [3660/4276] eta: 0:30:15 lr: 2.3324534628991494e-05 loss: 0.0883 (0.1090) time: 2.9349 data: 0.0079 max mem: 33301 +Epoch: [22] [3670/4276] eta: 0:29:45 lr: 2.3321671024649138e-05 loss: 0.0934 (0.1090) time: 2.9281 data: 0.0081 max mem: 33301 +Epoch: [22] 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33301 +Epoch: [22] [3760/4276] eta: 0:25:20 lr: 2.3295896826769108e-05 loss: 0.0920 (0.1089) time: 2.9257 data: 0.0082 max mem: 33301 +Epoch: [22] [3770/4276] eta: 0:24:50 lr: 2.3293032831474937e-05 loss: 0.1007 (0.1089) time: 2.9110 data: 0.0093 max mem: 33301 +Epoch: [22] [3780/4276] eta: 0:24:21 lr: 2.3290168797053275e-05 loss: 0.1066 (0.1089) time: 2.9176 data: 0.0091 max mem: 33301 +Epoch: [22] [3790/4276] eta: 0:23:51 lr: 2.3287304723498238e-05 loss: 0.0973 (0.1089) time: 2.9324 data: 0.0084 max mem: 33301 +Epoch: [22] [3800/4276] eta: 0:23:22 lr: 2.3284440610803952e-05 loss: 0.1037 (0.1089) time: 2.9347 data: 0.0083 max mem: 33301 +Epoch: [22] [3810/4276] eta: 0:22:52 lr: 2.328157645896453e-05 loss: 0.1093 (0.1089) time: 2.9353 data: 0.0079 max mem: 33301 +Epoch: [22] [3820/4276] eta: 0:22:23 lr: 2.3278712267974083e-05 loss: 0.0967 (0.1089) time: 2.9366 data: 0.0079 max mem: 33301 +Epoch: [22] [3830/4276] eta: 0:21:53 lr: 2.3275848037826722e-05 loss: 0.0932 (0.1089) time: 2.9377 data: 0.0081 max mem: 33301 +Epoch: [22] [3840/4276] eta: 0:21:24 lr: 2.3272983768516563e-05 loss: 0.0974 (0.1088) time: 2.9363 data: 0.0079 max mem: 33301 +Epoch: [22] [3850/4276] eta: 0:20:55 lr: 2.3270119460037713e-05 loss: 0.0918 (0.1088) time: 2.9363 data: 0.0079 max mem: 33301 +Epoch: [22] [3860/4276] eta: 0:20:25 lr: 2.3267255112384277e-05 loss: 0.1031 (0.1088) time: 2.9366 data: 0.0077 max mem: 33301 +Epoch: [22] [3870/4276] eta: 0:19:56 lr: 2.3264390725550364e-05 loss: 0.1079 (0.1088) time: 2.9360 data: 0.0075 max mem: 33301 +Epoch: [22] [3880/4276] eta: 0:19:26 lr: 2.3261526299530073e-05 loss: 0.0993 (0.1088) time: 2.9346 data: 0.0075 max mem: 33301 +Epoch: [22] [3890/4276] eta: 0:18:57 lr: 2.3258661834317517e-05 loss: 0.1000 (0.1088) time: 2.9329 data: 0.0074 max mem: 33301 +Epoch: [22] [3900/4276] eta: 0:18:27 lr: 2.3255797329906784e-05 loss: 0.1014 (0.1088) time: 2.9319 data: 0.0074 max mem: 33301 +Epoch: [22] [3910/4276] eta: 0:17:58 lr: 2.3252932786291974e-05 loss: 0.0944 (0.1087) time: 2.9304 data: 0.0075 max mem: 33301 +Epoch: [22] [3920/4276] eta: 0:17:28 lr: 2.325006820346719e-05 loss: 0.0917 (0.1087) time: 2.9302 data: 0.0075 max mem: 33301 +Epoch: [22] [3930/4276] eta: 0:16:59 lr: 2.3247203581426534e-05 loss: 0.0954 (0.1087) time: 2.9307 data: 0.0075 max mem: 33301 +Epoch: [22] [3940/4276] eta: 0:16:29 lr: 2.324433892016408e-05 loss: 0.0927 (0.1087) time: 2.9317 data: 0.0075 max mem: 33301 +Epoch: [22] [3950/4276] eta: 0:16:00 lr: 2.3241474219673932e-05 loss: 0.0980 (0.1087) time: 2.9365 data: 0.0078 max mem: 33301 +Epoch: [22] [3960/4276] eta: 0:15:30 lr: 2.3238609479950182e-05 loss: 0.0980 (0.1087) time: 2.9297 data: 0.0081 max mem: 33301 +Epoch: [22] [3970/4276] eta: 0:15:01 lr: 2.323574470098692e-05 loss: 0.0966 (0.1087) time: 2.9248 data: 0.0080 max mem: 33301 +Epoch: [22] [3980/4276] eta: 0:14:31 lr: 2.3232879882778224e-05 loss: 0.1012 (0.1087) time: 2.9304 data: 0.0077 max mem: 33301 +Epoch: [22] [3990/4276] eta: 0:14:02 lr: 2.3230015025318185e-05 loss: 0.0999 (0.1087) time: 2.9293 data: 0.0075 max mem: 33301 +Epoch: [22] [4000/4276] eta: 0:13:32 lr: 2.3227150128600882e-05 loss: 0.0917 (0.1086) time: 2.9289 data: 0.0075 max mem: 33301 +Epoch: [22] [4010/4276] eta: 0:13:03 lr: 2.3224285192620408e-05 loss: 0.0918 (0.1086) time: 2.9298 data: 0.0075 max mem: 33301 +Epoch: [22] [4020/4276] eta: 0:12:34 lr: 2.322142021737083e-05 loss: 0.0987 (0.1086) time: 2.9259 data: 0.0078 max mem: 33301 +Epoch: [22] [4030/4276] eta: 0:12:04 lr: 2.3218555202846232e-05 loss: 0.1032 (0.1086) time: 2.9210 data: 0.0086 max mem: 33301 +Epoch: [22] [4040/4276] eta: 0:11:35 lr: 2.3215690149040693e-05 loss: 0.1070 (0.1087) time: 2.9241 data: 0.0085 max mem: 33301 +Epoch: [22] [4050/4276] eta: 0:11:05 lr: 2.3212825055948285e-05 loss: 0.1031 (0.1087) time: 2.9285 data: 0.0077 max mem: 33301 +Epoch: [22] [4060/4276] eta: 0:10:36 lr: 2.3209959923563076e-05 loss: 0.0987 (0.1088) time: 2.9305 data: 0.0075 max mem: 33301 +Epoch: [22] 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33301 +Epoch: [22] [4150/4276] eta: 0:06:11 lr: 2.3184171962941696e-05 loss: 0.1037 (0.1088) time: 2.9293 data: 0.0077 max mem: 33301 +Epoch: [22] [4160/4276] eta: 0:05:41 lr: 2.31813064373022e-05 loss: 0.1093 (0.1088) time: 2.9322 data: 0.0080 max mem: 33301 +Epoch: [22] [4170/4276] eta: 0:05:12 lr: 2.3178440872304593e-05 loss: 0.1117 (0.1088) time: 2.9329 data: 0.0077 max mem: 33301 +Epoch: [22] [4180/4276] eta: 0:04:42 lr: 2.317557526794294e-05 loss: 0.1068 (0.1088) time: 2.9213 data: 0.0081 max mem: 33301 +Epoch: [22] [4190/4276] eta: 0:04:13 lr: 2.317270962421129e-05 loss: 0.1047 (0.1088) time: 2.9126 data: 0.0089 max mem: 33301 +Epoch: [22] [4200/4276] eta: 0:03:43 lr: 2.3169843941103692e-05 loss: 0.1158 (0.1088) time: 2.8980 data: 0.0091 max mem: 33301 +Epoch: [22] [4210/4276] eta: 0:03:14 lr: 2.316697821861419e-05 loss: 0.1095 (0.1088) time: 2.8804 data: 0.0087 max mem: 33301 +Epoch: [22] [4220/4276] eta: 0:02:44 lr: 2.316411245673683e-05 loss: 0.1117 (0.1089) time: 2.8796 data: 0.0087 max mem: 33301 +Epoch: [22] [4230/4276] eta: 0:02:15 lr: 2.3161246655465662e-05 loss: 0.1125 (0.1089) time: 2.8935 data: 0.0091 max mem: 33301 +Epoch: [22] [4240/4276] eta: 0:01:45 lr: 2.315838081479473e-05 loss: 0.1125 (0.1089) time: 2.8946 data: 0.0090 max mem: 33301 +Epoch: [22] [4250/4276] eta: 0:01:16 lr: 2.3155514934718066e-05 loss: 0.1186 (0.1089) time: 2.8827 data: 0.0086 max mem: 33301 +Epoch: [22] [4260/4276] eta: 0:00:47 lr: 2.3152649015229707e-05 loss: 0.1186 (0.1089) time: 2.8810 data: 0.0088 max mem: 33301 +Epoch: [22] [4270/4276] eta: 0:00:17 lr: 2.31497830563237e-05 loss: 0.1130 (0.1090) time: 2.8744 data: 0.0082 max mem: 33301 +Epoch: [22] Total time: 3:29:46 +Test: [ 0/21770] eta: 8:53:34 time: 1.4706 data: 1.4283 max mem: 33301 +Test: [ 100/21770] eta: 0:18:47 time: 0.0378 data: 0.0009 max mem: 33301 +Test: [ 200/21770] eta: 0:16:11 time: 0.0381 data: 0.0009 max mem: 33301 +Test: [ 300/21770] eta: 0:15:15 time: 0.0377 data: 0.0009 max mem: 33301 +Test: [ 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mem: 33301 +Test: [ 3100/21770] eta: 0:12:08 time: 0.0391 data: 0.0009 max mem: 33301 +Test: [ 3200/21770] eta: 0:12:04 time: 0.0392 data: 0.0009 max mem: 33301 +Test: [ 3300/21770] eta: 0:12:00 time: 0.0394 data: 0.0009 max mem: 33301 +Test: [ 3400/21770] eta: 0:11:56 time: 0.0384 data: 0.0008 max mem: 33301 +Test: [ 3500/21770] eta: 0:11:52 time: 0.0386 data: 0.0009 max mem: 33301 +Test: [ 3600/21770] eta: 0:11:48 time: 0.0390 data: 0.0009 max mem: 33301 +Test: [ 3700/21770] eta: 0:11:44 time: 0.0388 data: 0.0008 max mem: 33301 +Test: [ 3800/21770] eta: 0:11:40 time: 0.0386 data: 0.0008 max mem: 33301 +Test: [ 3900/21770] eta: 0:11:36 time: 0.0386 data: 0.0009 max mem: 33301 +Test: [ 4000/21770] eta: 0:11:32 time: 0.0384 data: 0.0008 max mem: 33301 +Test: [ 4100/21770] eta: 0:11:28 time: 0.0385 data: 0.0009 max mem: 33301 +Test: [ 4200/21770] eta: 0:11:24 time: 0.0383 data: 0.0009 max mem: 33301 +Test: [ 4300/21770] eta: 0:11:19 time: 0.0382 data: 0.0009 max mem: 33301 +Test: [ 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time: 0.0382 data: 0.0009 max mem: 33301 +Test: [ 5800/21770] eta: 0:10:19 time: 0.0379 data: 0.0009 max mem: 33301 +Test: [ 5900/21770] eta: 0:10:15 time: 0.0379 data: 0.0009 max mem: 33301 +Test: [ 6000/21770] eta: 0:10:11 time: 0.0382 data: 0.0009 max mem: 33301 +Test: [ 6100/21770] eta: 0:10:07 time: 0.0383 data: 0.0009 max mem: 33301 +Test: [ 6200/21770] eta: 0:10:03 time: 0.0382 data: 0.0008 max mem: 33301 +Test: [ 6300/21770] eta: 0:09:59 time: 0.0383 data: 0.0009 max mem: 33301 +Test: [ 6400/21770] eta: 0:09:55 time: 0.0382 data: 0.0009 max mem: 33301 +Test: [ 6500/21770] eta: 0:09:51 time: 0.0382 data: 0.0009 max mem: 33301 +Test: [ 6600/21770] eta: 0:09:47 time: 0.0382 data: 0.0009 max mem: 33301 +Test: [ 6700/21770] eta: 0:09:43 time: 0.0384 data: 0.0009 max mem: 33301 +Test: [ 6800/21770] eta: 0:09:39 time: 0.0383 data: 0.0009 max mem: 33301 +Test: [ 6900/21770] eta: 0:09:35 time: 0.0387 data: 0.0008 max mem: 33301 +Test: [ 7000/21770] eta: 0:09:31 time: 0.0384 data: 0.0009 max mem: 33301 +Test: [ 7100/21770] eta: 0:09:28 time: 0.0387 data: 0.0009 max mem: 33301 +Test: [ 7200/21770] eta: 0:09:24 time: 0.0385 data: 0.0009 max mem: 33301 +Test: [ 7300/21770] eta: 0:09:20 time: 0.0388 data: 0.0009 max mem: 33301 +Test: [ 7400/21770] eta: 0:09:16 time: 0.0382 data: 0.0009 max mem: 33301 +Test: [ 7500/21770] eta: 0:09:12 time: 0.0383 data: 0.0009 max mem: 33301 +Test: [ 7600/21770] eta: 0:09:08 time: 0.0382 data: 0.0009 max mem: 33301 +Test: [ 7700/21770] eta: 0:09:04 time: 0.0382 data: 0.0009 max mem: 33301 +Test: [ 7800/21770] eta: 0:09:00 time: 0.0381 data: 0.0009 max mem: 33301 +Test: [ 7900/21770] eta: 0:08:56 time: 0.0384 data: 0.0009 max mem: 33301 +Test: [ 8000/21770] eta: 0:08:52 time: 0.0382 data: 0.0009 max mem: 33301 +Test: [ 8100/21770] eta: 0:08:48 time: 0.0383 data: 0.0009 max mem: 33301 +Test: [ 8200/21770] eta: 0:08:44 time: 0.0382 data: 0.0009 max mem: 33301 +Test: [ 8300/21770] eta: 0:08:40 time: 0.0383 data: 0.0009 max mem: 33301 +Test: [ 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time: 0.0386 data: 0.0009 max mem: 33301 +Test: [ 9800/21770] eta: 0:07:42 time: 0.0396 data: 0.0009 max mem: 33301 +Test: [ 9900/21770] eta: 0:07:38 time: 0.0400 data: 0.0009 max mem: 33301 +Test: [10000/21770] eta: 0:07:34 time: 0.0394 data: 0.0009 max mem: 33301 +Test: [10100/21770] eta: 0:07:30 time: 0.0394 data: 0.0009 max mem: 33301 +Test: [10200/21770] eta: 0:07:27 time: 0.0397 data: 0.0009 max mem: 33301 +Test: [10300/21770] eta: 0:07:23 time: 0.0401 data: 0.0009 max mem: 33301 +Test: [10400/21770] eta: 0:07:19 time: 0.0391 data: 0.0009 max mem: 33301 +Test: [10500/21770] eta: 0:07:15 time: 0.0392 data: 0.0009 max mem: 33301 +Test: [10600/21770] eta: 0:07:11 time: 0.0392 data: 0.0009 max mem: 33301 +Test: [10700/21770] eta: 0:07:08 time: 0.0389 data: 0.0009 max mem: 33301 +Test: [10800/21770] eta: 0:07:04 time: 0.0387 data: 0.0009 max mem: 33301 +Test: [10900/21770] eta: 0:07:00 time: 0.0390 data: 0.0009 max mem: 33301 +Test: [11000/21770] eta: 0:06:56 time: 0.0388 data: 0.0009 max mem: 33301 +Test: [11100/21770] eta: 0:06:52 time: 0.0390 data: 0.0009 max mem: 33301 +Test: [11200/21770] eta: 0:06:48 time: 0.0388 data: 0.0009 max mem: 33301 +Test: [11300/21770] eta: 0:06:45 time: 0.0387 data: 0.0009 max mem: 33301 +Test: [11400/21770] eta: 0:06:41 time: 0.0388 data: 0.0009 max mem: 33301 +Test: [11500/21770] eta: 0:06:37 time: 0.0389 data: 0.0009 max mem: 33301 +Test: [11600/21770] eta: 0:06:33 time: 0.0387 data: 0.0009 max mem: 33301 +Test: [11700/21770] eta: 0:06:29 time: 0.0381 data: 0.0009 max mem: 33301 +Test: [11800/21770] eta: 0:06:25 time: 0.0381 data: 0.0009 max mem: 33301 +Test: [11900/21770] eta: 0:06:21 time: 0.0396 data: 0.0009 max mem: 33301 +Test: [12000/21770] eta: 0:06:18 time: 0.0400 data: 0.0009 max mem: 33301 +Test: [12100/21770] eta: 0:06:14 time: 0.0398 data: 0.0009 max mem: 33301 +Test: [12200/21770] eta: 0:06:10 time: 0.0400 data: 0.0009 max mem: 33301 +Test: [12300/21770] eta: 0:06:06 time: 0.0399 data: 0.0009 max mem: 33301 +Test: 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0:05:13 time: 0.0397 data: 0.0008 max mem: 33301 +Test: [13800/21770] eta: 0:05:09 time: 0.0392 data: 0.0008 max mem: 33301 +Test: [13900/21770] eta: 0:05:05 time: 0.0388 data: 0.0009 max mem: 33301 +Test: [14000/21770] eta: 0:05:01 time: 0.0382 data: 0.0009 max mem: 33301 +Test: [14100/21770] eta: 0:04:57 time: 0.0382 data: 0.0009 max mem: 33301 +Test: [14200/21770] eta: 0:04:53 time: 0.0383 data: 0.0009 max mem: 33301 +Test: [14300/21770] eta: 0:04:49 time: 0.0384 data: 0.0009 max mem: 33301 +Test: [14400/21770] eta: 0:04:45 time: 0.0386 data: 0.0009 max mem: 33301 +Test: [14500/21770] eta: 0:04:42 time: 0.0388 data: 0.0009 max mem: 33301 +Test: [14600/21770] eta: 0:04:38 time: 0.0386 data: 0.0009 max mem: 33301 +Test: [14700/21770] eta: 0:04:34 time: 0.0386 data: 0.0009 max mem: 33301 +Test: [14800/21770] eta: 0:04:30 time: 0.0387 data: 0.0009 max mem: 33301 +Test: [14900/21770] eta: 0:04:26 time: 0.0387 data: 0.0009 max mem: 33301 +Test: [15000/21770] eta: 0:04:22 time: 0.0390 data: 0.0009 max mem: 33301 +Test: [15100/21770] eta: 0:04:18 time: 0.0386 data: 0.0009 max mem: 33301 +Test: [15200/21770] eta: 0:04:14 time: 0.0390 data: 0.0009 max mem: 33301 +Test: [15300/21770] eta: 0:04:11 time: 0.0385 data: 0.0009 max mem: 33301 +Test: [15400/21770] eta: 0:04:07 time: 0.0392 data: 0.0009 max mem: 33301 +Test: [15500/21770] eta: 0:04:03 time: 0.0382 data: 0.0009 max mem: 33301 +Test: [15600/21770] eta: 0:03:59 time: 0.0388 data: 0.0009 max mem: 33301 +Test: [15700/21770] eta: 0:03:55 time: 0.0385 data: 0.0009 max mem: 33301 +Test: [15800/21770] eta: 0:03:51 time: 0.0388 data: 0.0009 max mem: 33301 +Test: [15900/21770] eta: 0:03:47 time: 0.0385 data: 0.0009 max mem: 33301 +Test: [16000/21770] eta: 0:03:43 time: 0.0390 data: 0.0009 max mem: 33301 +Test: [16100/21770] eta: 0:03:39 time: 0.0390 data: 0.0009 max mem: 33301 +Test: [16200/21770] eta: 0:03:36 time: 0.0387 data: 0.0009 max mem: 33301 +Test: [16300/21770] eta: 0:03:32 time: 0.0390 data: 0.0009 max mem: 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0:01:47 time: 0.0382 data: 0.0009 max mem: 33301 +Test: [19100/21770] eta: 0:01:43 time: 0.0382 data: 0.0008 max mem: 33301 +Test: [19200/21770] eta: 0:01:39 time: 0.0385 data: 0.0009 max mem: 33301 +Test: [19300/21770] eta: 0:01:35 time: 0.0384 data: 0.0009 max mem: 33301 +Test: [19400/21770] eta: 0:01:31 time: 0.0386 data: 0.0009 max mem: 33301 +Test: [19500/21770] eta: 0:01:27 time: 0.0383 data: 0.0009 max mem: 33301 +Test: [19600/21770] eta: 0:01:24 time: 0.0386 data: 0.0009 max mem: 33301 +Test: [19700/21770] eta: 0:01:20 time: 0.0385 data: 0.0009 max mem: 33301 +Test: [19800/21770] eta: 0:01:16 time: 0.0391 data: 0.0008 max mem: 33301 +Test: [19900/21770] eta: 0:01:12 time: 0.0383 data: 0.0009 max mem: 33301 +Test: [20000/21770] eta: 0:01:08 time: 0.0385 data: 0.0009 max mem: 33301 +Test: [20100/21770] eta: 0:01:04 time: 0.0383 data: 0.0009 max mem: 33301 +Test: [20200/21770] eta: 0:01:00 time: 0.0387 data: 0.0009 max mem: 33301 +Test: [20300/21770] eta: 0:00:56 time: 0.0381 data: 0.0009 max mem: 33301 +Test: [20400/21770] eta: 0:00:53 time: 0.0382 data: 0.0008 max mem: 33301 +Test: [20500/21770] eta: 0:00:49 time: 0.0381 data: 0.0009 max mem: 33301 +Test: [20600/21770] eta: 0:00:45 time: 0.0382 data: 0.0009 max mem: 33301 +Test: [20700/21770] eta: 0:00:41 time: 0.0380 data: 0.0009 max mem: 33301 +Test: [20800/21770] eta: 0:00:37 time: 0.0384 data: 0.0009 max mem: 33301 +Test: [20900/21770] eta: 0:00:33 time: 0.0385 data: 0.0009 max mem: 33301 +Test: [21000/21770] eta: 0:00:29 time: 0.0385 data: 0.0009 max mem: 33301 +Test: [21100/21770] eta: 0:00:25 time: 0.0384 data: 0.0009 max mem: 33301 +Test: [21200/21770] eta: 0:00:22 time: 0.0387 data: 0.0009 max mem: 33301 +Test: [21300/21770] eta: 0:00:18 time: 0.0386 data: 0.0009 max mem: 33301 +Test: [21400/21770] eta: 0:00:14 time: 0.0395 data: 0.0010 max mem: 33301 +Test: [21500/21770] eta: 0:00:10 time: 0.0393 data: 0.0010 max mem: 33301 +Test: [21600/21770] eta: 0:00:06 time: 0.0396 data: 0.0010 max mem: 33301 +Test: [21700/21770] eta: 0:00:02 time: 0.0385 data: 0.0009 max mem: 33301 +Test: Total time: 0:14:03 +Final results: +Mean IoU is 15.77 + + precision@0.5 = 2.83 + precision@0.6 = 1.25 + precision@0.7 = 0.44 + precision@0.8 = 0.10 + precision@0.9 = 0.00 + overall IoU = 15.84 + mean IoU = 15.77 + +Mean accuracy for one-to-zero sample is 0.00 + +Average object IoU 0.15767904766376536 +Overall IoU 15.836902618408203 +Better epoch: 22 + +Epoch: [23] [ 0/4276] eta: 6:06:48 lr: 2.3148063462057145e-05 loss: 0.0895 (0.0895) time: 5.1470 data: 2.0617 max mem: 33301 +Epoch: [23] [ 10/4276] eta: 3:43:54 lr: 2.3145197440070494e-05 loss: 0.1044 (0.1073) time: 3.1492 data: 0.1931 max mem: 33301 +Epoch: [23] [ 20/4276] eta: 3:36:31 lr: 2.3142331378650675e-05 loss: 0.1016 (0.1068) time: 2.9479 data: 0.0063 max mem: 33301 +Epoch: [23] [ 30/4276] eta: 3:33:35 lr: 2.313946527779172e-05 loss: 0.1016 (0.1075) time: 2.9463 data: 0.0068 max mem: 33301 +Epoch: [23] [ 40/4276] eta: 3:31:49 lr: 2.313659913748767e-05 loss: 0.1043 (0.1074) time: 2.9455 data: 0.0071 max mem: 33301 +Epoch: [23] [ 50/4276] eta: 3:30:27 lr: 2.3133732957732546e-05 loss: 0.1020 (0.1067) time: 2.9413 data: 0.0068 max mem: 33301 +Epoch: [23] [ 60/4276] eta: 3:29:19 lr: 2.313086673852037e-05 loss: 0.0923 (0.1047) time: 2.9353 data: 0.0068 max mem: 33301 +Epoch: [23] [ 70/4276] eta: 3:28:23 lr: 2.3128000479845167e-05 loss: 0.0919 (0.1029) time: 2.9339 data: 0.0070 max mem: 33301 +Epoch: [23] [ 80/4276] eta: 3:27:33 lr: 2.3125134181700964e-05 loss: 0.0957 (0.1044) time: 2.9346 data: 0.0074 max mem: 33301 +Epoch: [23] [ 90/4276] eta: 3:26:48 lr: 2.3122267844081783e-05 loss: 0.1009 (0.1041) time: 2.9334 data: 0.0071 max mem: 33301 +Epoch: [23] [ 100/4276] eta: 3:26:04 lr: 2.3119401466981634e-05 loss: 0.1024 (0.1049) time: 2.9311 data: 0.0065 max mem: 33301 +Epoch: [23] [ 110/4276] eta: 3:25:23 lr: 2.3116535050394537e-05 loss: 0.1177 (0.1063) time: 2.9310 data: 0.0067 max mem: 33301 +Epoch: [23] [ 120/4276] eta: 3:24:44 lr: 2.311366859431452e-05 loss: 0.0887 (0.1053) time: 2.9308 data: 0.0069 max mem: 33301 +Epoch: [23] [ 130/4276] eta: 3:24:06 lr: 2.311080209873558e-05 loss: 0.0893 (0.1059) time: 2.9292 data: 0.0066 max mem: 33301 +Epoch: [23] [ 140/4276] eta: 3:23:30 lr: 2.3107935563651737e-05 loss: 0.0982 (0.1054) time: 2.9305 data: 0.0065 max mem: 33301 +Epoch: [23] [ 150/4276] eta: 3:22:51 lr: 2.3105068989056997e-05 loss: 0.0894 (0.1053) time: 2.9258 data: 0.0068 max mem: 33301 +Epoch: [23] [ 160/4276] eta: 3:22:17 lr: 2.310220237494538e-05 loss: 0.0978 (0.1051) time: 2.9255 data: 0.0070 max mem: 33301 +Epoch: [23] [ 170/4276] eta: 3:21:43 lr: 2.309933572131088e-05 loss: 0.1035 (0.1052) time: 2.9313 data: 0.0067 max mem: 33301 +Epoch: [23] [ 180/4276] eta: 3:21:11 lr: 2.3096469028147505e-05 loss: 0.1053 (0.1060) time: 2.9324 data: 0.0067 max mem: 33301 +Epoch: [23] [ 190/4276] eta: 3:20:39 lr: 2.309360229544926e-05 loss: 0.1096 (0.1062) time: 2.9347 data: 0.0070 max mem: 33301 +Epoch: [23] [ 200/4276] eta: 3:20:07 lr: 2.3090735523210156e-05 loss: 0.1016 (0.1057) time: 2.9347 data: 0.0070 max mem: 33301 +Epoch: [23] [ 210/4276] eta: 3:19:27 lr: 2.3087868711424174e-05 loss: 0.1009 (0.1057) time: 2.9138 data: 0.0065 max mem: 33301 +Epoch: [23] [ 220/4276] eta: 3:18:53 lr: 2.3085001860085325e-05 loss: 0.0967 (0.1056) time: 2.9052 data: 0.0060 max mem: 33301 +Epoch: [23] [ 230/4276] eta: 3:18:22 lr: 2.30821349691876e-05 loss: 0.0873 (0.1049) time: 2.9239 data: 0.0067 max mem: 33301 +Epoch: [23] [ 240/4276] eta: 3:17:47 lr: 2.3079268038725e-05 loss: 0.0925 (0.1048) time: 2.9222 data: 0.0068 max mem: 33301 +Epoch: [23] [ 250/4276] eta: 3:17:16 lr: 2.3076401068691513e-05 loss: 0.1048 (0.1050) time: 2.9217 data: 0.0062 max mem: 33301 +Epoch: [23] [ 260/4276] eta: 3:16:45 lr: 2.307353405908113e-05 loss: 0.1048 (0.1047) time: 2.9306 data: 0.0061 max mem: 33301 +Epoch: [23] [ 270/4276] eta: 3:16:15 lr: 2.3070667009887838e-05 loss: 0.0841 (0.1046) time: 2.9306 data: 0.0061 max mem: 33301 +Epoch: [23] [ 280/4276] eta: 3:15:43 lr: 2.306779992110564e-05 loss: 0.0933 (0.1044) time: 2.9284 data: 0.0064 max mem: 33301 +Epoch: [23] [ 290/4276] eta: 3:15:11 lr: 2.3064932792728504e-05 loss: 0.0933 (0.1040) time: 2.9226 data: 0.0064 max mem: 33301 +Epoch: [23] [ 300/4276] eta: 3:14:38 lr: 2.3062065624750416e-05 loss: 0.0963 (0.1038) time: 2.9128 data: 0.0061 max mem: 33301 +Epoch: [23] [ 310/4276] eta: 3:14:07 lr: 2.3059198417165365e-05 loss: 0.0973 (0.1035) time: 2.9178 data: 0.0063 max mem: 33301 +Epoch: [23] [ 320/4276] eta: 3:13:37 lr: 2.305633116996734e-05 loss: 0.0973 (0.1036) time: 2.9309 data: 0.0065 max mem: 33301 +Epoch: [23] [ 330/4276] eta: 3:13:06 lr: 2.3053463883150297e-05 loss: 0.1070 (0.1039) time: 2.9273 data: 0.0065 max mem: 33301 +Epoch: [23] [ 340/4276] eta: 3:12:31 lr: 2.3050596556708232e-05 loss: 0.1091 (0.1039) time: 2.9022 data: 0.0067 max mem: 33301 +Epoch: [23] [ 350/4276] eta: 3:11:55 lr: 2.304772919063511e-05 loss: 0.1096 (0.1042) time: 2.8812 data: 0.0069 max mem: 33301 +Epoch: [23] [ 360/4276] eta: 3:11:24 lr: 2.3044861784924917e-05 loss: 0.1182 (0.1049) time: 2.8978 data: 0.0069 max mem: 33301 +Epoch: [23] [ 370/4276] eta: 3:10:53 lr: 2.3041994339571613e-05 loss: 0.0996 (0.1048) time: 2.9158 data: 0.0068 max mem: 33301 +Epoch: [23] [ 380/4276] eta: 3:10:23 lr: 2.3039126854569174e-05 loss: 0.0996 (0.1050) time: 2.9229 data: 0.0064 max mem: 33301 +Epoch: [23] [ 390/4276] eta: 3:09:54 lr: 2.3036259329911563e-05 loss: 0.1098 (0.1053) time: 2.9310 data: 0.0062 max mem: 33301 +Epoch: [23] [ 400/4276] eta: 3:09:25 lr: 2.303339176559276e-05 loss: 0.1194 (0.1056) time: 2.9327 data: 0.0061 max mem: 33301 +Epoch: [23] [ 410/4276] eta: 3:08:56 lr: 2.3030524161606715e-05 loss: 0.1142 (0.1057) time: 2.9350 data: 0.0062 max mem: 33301 +Epoch: [23] [ 420/4276] eta: 3:08:26 lr: 2.3027656517947396e-05 loss: 0.0979 (0.1057) time: 2.9327 data: 0.0069 max mem: 33301 +Epoch: [23] [ 430/4276] eta: 3:07:57 lr: 2.302478883460877e-05 loss: 0.1018 (0.1060) time: 2.9294 data: 0.0068 max mem: 33301 +Epoch: [23] [ 440/4276] eta: 3:07:27 lr: 2.302192111158479e-05 loss: 0.1061 (0.1058) time: 2.9304 data: 0.0062 max mem: 33301 +Epoch: [23] [ 450/4276] eta: 3:06:58 lr: 2.3019053348869414e-05 loss: 0.0954 (0.1059) time: 2.9310 data: 0.0061 max mem: 33301 +Epoch: [23] [ 460/4276] eta: 3:06:29 lr: 2.30161855464566e-05 loss: 0.0929 (0.1056) time: 2.9326 data: 0.0062 max mem: 33301 +Epoch: [23] [ 470/4276] eta: 3:05:59 lr: 2.3013317704340312e-05 loss: 0.0866 (0.1052) time: 2.9319 data: 0.0065 max mem: 33301 +Epoch: [23] [ 480/4276] eta: 3:05:29 lr: 2.3010449822514484e-05 loss: 0.0910 (0.1051) time: 2.9275 data: 0.0063 max mem: 33301 +Epoch: [23] [ 490/4276] eta: 3:04:59 lr: 2.300758190097308e-05 loss: 0.0865 (0.1047) time: 2.9215 data: 0.0059 max mem: 33301 +Epoch: [23] [ 500/4276] eta: 3:04:30 lr: 2.3004713939710047e-05 loss: 0.0862 (0.1044) time: 2.9252 data: 0.0059 max mem: 33301 +Epoch: [23] [ 510/4276] eta: 3:04:00 lr: 2.300184593871933e-05 loss: 0.0928 (0.1045) time: 2.9316 data: 0.0062 max mem: 33301 +Epoch: [23] [ 520/4276] eta: 3:03:32 lr: 2.299897789799488e-05 loss: 0.0898 (0.1044) time: 2.9366 data: 0.0062 max mem: 33301 +Epoch: [23] [ 530/4276] eta: 3:03:02 lr: 2.299610981753063e-05 loss: 0.0898 (0.1043) time: 2.9355 data: 0.0060 max mem: 33301 +Epoch: [23] [ 540/4276] eta: 3:02:33 lr: 2.2993241697320532e-05 loss: 0.0934 (0.1041) time: 2.9293 data: 0.0060 max mem: 33301 +Epoch: [23] [ 550/4276] eta: 3:02:04 lr: 2.2990373537358527e-05 loss: 0.1002 (0.1043) time: 2.9366 data: 0.0062 max mem: 33301 +Epoch: [23] [ 560/4276] eta: 3:01:35 lr: 2.2987505337638548e-05 loss: 0.1111 (0.1043) time: 2.9362 data: 0.0062 max mem: 33301 +Epoch: [23] [ 570/4276] eta: 3:01:05 lr: 2.298463709815453e-05 loss: 0.0946 (0.1043) time: 2.9288 data: 0.0061 max mem: 33301 +Epoch: [23] [ 580/4276] eta: 3:00:36 lr: 2.2981768818900418e-05 loss: 0.1020 (0.1044) time: 2.9337 data: 0.0061 max mem: 33301 +Epoch: [23] [ 590/4276] eta: 3:00:07 lr: 2.297890049987014e-05 loss: 0.0898 (0.1042) time: 2.9341 data: 0.0063 max mem: 33301 +Epoch: [23] [ 600/4276] eta: 2:59:37 lr: 2.2976032141057622e-05 loss: 0.0876 (0.1041) time: 2.9283 data: 0.0065 max mem: 33301 +Epoch: [23] [ 610/4276] eta: 2:59:08 lr: 2.29731637424568e-05 loss: 0.0890 (0.1042) time: 2.9290 data: 0.0063 max mem: 33301 +Epoch: [23] [ 620/4276] eta: 2:58:38 lr: 2.2970295304061598e-05 loss: 0.0937 (0.1041) time: 2.9306 data: 0.0062 max mem: 33301 +Epoch: [23] [ 630/4276] eta: 2:58:10 lr: 2.2967426825865954e-05 loss: 0.1048 (0.1043) time: 2.9359 data: 0.0063 max mem: 33301 +Epoch: [23] [ 640/4276] eta: 2:57:40 lr: 2.2964558307863776e-05 loss: 0.1048 (0.1044) time: 2.9375 data: 0.0065 max mem: 33301 +Epoch: [23] [ 650/4276] eta: 2:57:11 lr: 2.2961689750048997e-05 loss: 0.1018 (0.1045) time: 2.9314 data: 0.0064 max mem: 33301 +Epoch: [23] [ 660/4276] eta: 2:56:42 lr: 2.295882115241553e-05 loss: 0.1121 (0.1048) time: 2.9312 data: 0.0064 max mem: 33301 +Epoch: [23] [ 670/4276] eta: 2:56:12 lr: 2.2955952514957306e-05 loss: 0.1020 (0.1047) time: 2.9329 data: 0.0066 max mem: 33301 +Epoch: [23] [ 680/4276] eta: 2:55:43 lr: 2.295308383766823e-05 loss: 0.1020 (0.1047) time: 2.9341 data: 0.0065 max mem: 33301 +Epoch: [23] [ 690/4276] eta: 2:55:15 lr: 2.2950215120542225e-05 loss: 0.1033 (0.1047) time: 2.9407 data: 0.0063 max mem: 33301 +Epoch: [23] [ 700/4276] eta: 2:54:46 lr: 2.2947346363573204e-05 loss: 0.1019 (0.1046) time: 2.9455 data: 0.0063 max mem: 33301 +Epoch: [23] [ 710/4276] eta: 2:54:17 lr: 2.2944477566755085e-05 loss: 0.0952 (0.1047) time: 2.9396 data: 0.0064 max mem: 33301 +Epoch: [23] [ 720/4276] eta: 2:53:47 lr: 2.2941608730081762e-05 loss: 0.0924 (0.1045) time: 2.9334 data: 0.0064 max mem: 33301 +Epoch: [23] [ 730/4276] eta: 2:53:18 lr: 2.2938739853547157e-05 loss: 0.0985 (0.1045) time: 2.9343 data: 0.0063 max mem: 33301 +Epoch: [23] [ 740/4276] eta: 2:52:49 lr: 2.2935870937145174e-05 loss: 0.0973 (0.1044) time: 2.9347 data: 0.0065 max mem: 33301 +Epoch: [23] [ 750/4276] eta: 2:52:20 lr: 2.2933001980869714e-05 loss: 0.0973 (0.1044) time: 2.9342 data: 0.0066 max mem: 33301 +Epoch: [23] [ 760/4276] eta: 2:51:51 lr: 2.293013298471468e-05 loss: 0.0926 (0.1044) time: 2.9384 data: 0.0065 max mem: 33301 +Epoch: [23] [ 770/4276] eta: 2:51:22 lr: 2.292726394867398e-05 loss: 0.0958 (0.1044) time: 2.9371 data: 0.0064 max mem: 33301 +Epoch: [23] [ 780/4276] eta: 2:50:52 lr: 2.2924394872741516e-05 loss: 0.1021 (0.1045) time: 2.9324 data: 0.0064 max mem: 33301 +Epoch: [23] [ 790/4276] eta: 2:50:23 lr: 2.2921525756911168e-05 loss: 0.1104 (0.1046) time: 2.9332 data: 0.0066 max mem: 33301 +Epoch: [23] [ 800/4276] eta: 2:49:54 lr: 2.2918656601176848e-05 loss: 0.1044 (0.1047) time: 2.9347 data: 0.0067 max mem: 33301 +Epoch: [23] [ 810/4276] eta: 2:49:24 lr: 2.2915787405532446e-05 loss: 0.1086 (0.1050) time: 2.9338 data: 0.0064 max mem: 33301 +Epoch: [23] [ 820/4276] eta: 2:48:55 lr: 2.291291816997186e-05 loss: 0.0992 (0.1049) time: 2.9325 data: 0.0063 max mem: 33301 +Epoch: [23] [ 830/4276] eta: 2:48:26 lr: 2.2910048894488968e-05 loss: 0.0932 (0.1050) time: 2.9329 data: 0.0066 max mem: 33301 +Epoch: [23] [ 840/4276] eta: 2:47:56 lr: 2.290717957907767e-05 loss: 0.1014 (0.1051) time: 2.9336 data: 0.0067 max mem: 33301 +Epoch: [23] [ 850/4276] eta: 2:47:27 lr: 2.2904310223731848e-05 loss: 0.1014 (0.1052) time: 2.9336 data: 0.0066 max mem: 33301 +Epoch: [23] [ 860/4276] eta: 2:46:58 lr: 2.2901440828445395e-05 loss: 0.1043 (0.1053) time: 2.9367 data: 0.0065 max mem: 33301 +Epoch: [23] [ 870/4276] eta: 2:46:29 lr: 2.2898571393212178e-05 loss: 0.1043 (0.1052) time: 2.9356 data: 0.0067 max mem: 33301 +Epoch: [23] [ 880/4276] eta: 2:45:59 lr: 2.2895701918026093e-05 loss: 0.0997 (0.1053) time: 2.9309 data: 0.0067 max mem: 33301 +Epoch: [23] [ 890/4276] eta: 2:45:30 lr: 2.2892832402881016e-05 loss: 0.1073 (0.1054) time: 2.9316 data: 0.0065 max mem: 33301 +Epoch: [23] [ 900/4276] eta: 2:45:01 lr: 2.288996284777083e-05 loss: 0.1069 (0.1055) time: 2.9312 data: 0.0065 max mem: 33301 +Epoch: [23] [ 910/4276] eta: 2:44:31 lr: 2.28870932526894e-05 loss: 0.1081 (0.1057) time: 2.9314 data: 0.0067 max mem: 33301 +Epoch: [23] [ 920/4276] eta: 2:44:02 lr: 2.288422361763061e-05 loss: 0.1139 (0.1057) time: 2.9316 data: 0.0067 max mem: 33301 +Epoch: [23] [ 930/4276] eta: 2:43:32 lr: 2.2881353942588325e-05 loss: 0.1110 (0.1057) time: 2.9314 data: 0.0066 max mem: 33301 +Epoch: [23] [ 940/4276] eta: 2:43:03 lr: 2.2878484227556432e-05 loss: 0.1037 (0.1058) time: 2.9337 data: 0.0066 max mem: 33301 +Epoch: [23] [ 950/4276] eta: 2:42:34 lr: 2.287561447252878e-05 loss: 0.1037 (0.1059) time: 2.9352 data: 0.0068 max mem: 33301 +Epoch: [23] [ 960/4276] eta: 2:42:05 lr: 2.2872744677499248e-05 loss: 0.1039 (0.1059) time: 2.9370 data: 0.0069 max mem: 33301 +Epoch: [23] [ 970/4276] eta: 2:41:36 lr: 2.28698748424617e-05 loss: 0.1025 (0.1059) time: 2.9385 data: 0.0066 max mem: 33301 +Epoch: [23] [ 980/4276] eta: 2:41:05 lr: 2.286700496741e-05 loss: 0.1102 (0.1060) time: 2.9107 data: 0.0064 max mem: 33301 +Epoch: [23] [ 990/4276] eta: 2:40:34 lr: 2.286413505233801e-05 loss: 0.1014 (0.1058) time: 2.8896 data: 0.0067 max mem: 33301 +Epoch: [23] [1000/4276] eta: 2:40:05 lr: 2.2861265097239584e-05 loss: 0.0966 (0.1058) time: 2.9170 data: 0.0075 max mem: 33301 +Epoch: [23] [1010/4276] eta: 2:39:36 lr: 2.2858395102108596e-05 loss: 0.1044 (0.1058) time: 2.9395 data: 0.0079 max mem: 33301 +Epoch: [23] [1020/4276] eta: 2:39:07 lr: 2.2855525066938886e-05 loss: 0.1010 (0.1058) time: 2.9400 data: 0.0079 max mem: 33301 +Epoch: [23] [1030/4276] eta: 2:38:38 lr: 2.285265499172431e-05 loss: 0.1094 (0.1059) time: 2.9401 data: 0.0083 max mem: 33301 +Epoch: [23] [1040/4276] eta: 2:38:09 lr: 2.2849784876458732e-05 loss: 0.0978 (0.1058) time: 2.9421 data: 0.0083 max mem: 33301 +Epoch: [23] [1050/4276] eta: 2:37:40 lr: 2.2846914721136002e-05 loss: 0.0971 (0.1060) time: 2.9426 data: 0.0082 max mem: 33301 +Epoch: [23] [1060/4276] eta: 2:37:11 lr: 2.284404452574996e-05 loss: 0.1114 (0.1061) time: 2.9377 data: 0.0083 max mem: 33301 +Epoch: [23] [1070/4276] eta: 2:36:41 lr: 2.284117429029446e-05 loss: 0.1114 (0.1062) time: 2.9359 data: 0.0081 max mem: 33301 +Epoch: [23] [1080/4276] eta: 2:36:12 lr: 2.2838304014763346e-05 loss: 0.1064 (0.1062) time: 2.9376 data: 0.0078 max mem: 33301 +Epoch: [23] [1090/4276] eta: 2:35:43 lr: 2.2835433699150466e-05 loss: 0.1064 (0.1064) time: 2.9355 data: 0.0079 max mem: 33301 +Epoch: [23] [1100/4276] eta: 2:35:14 lr: 2.2832563343449652e-05 loss: 0.1098 (0.1064) time: 2.9337 data: 0.0079 max mem: 33301 +Epoch: [23] [1110/4276] eta: 2:34:44 lr: 2.2829692947654757e-05 loss: 0.1176 (0.1065) time: 2.9302 data: 0.0078 max mem: 33301 +Epoch: [23] [1120/4276] eta: 2:34:15 lr: 2.282682251175961e-05 loss: 0.1097 (0.1065) time: 2.9299 data: 0.0078 max mem: 33301 +Epoch: [23] [1130/4276] eta: 2:33:45 lr: 2.2823952035758057e-05 loss: 0.1023 (0.1065) time: 2.9333 data: 0.0078 max mem: 33301 +Epoch: [23] [1140/4276] eta: 2:33:16 lr: 2.2821081519643924e-05 loss: 0.1084 (0.1066) time: 2.9332 data: 0.0078 max mem: 33301 +Epoch: [23] [1150/4276] eta: 2:32:47 lr: 2.2818210963411048e-05 loss: 0.1145 (0.1067) time: 2.9347 data: 0.0077 max mem: 33301 +Epoch: [23] [1160/4276] eta: 2:32:18 lr: 2.2815340367053262e-05 loss: 0.1226 (0.1067) time: 2.9388 data: 0.0079 max mem: 33301 +Epoch: [23] [1170/4276] eta: 2:31:49 lr: 2.2812469730564396e-05 loss: 0.1008 (0.1067) time: 2.9375 data: 0.0081 max mem: 33301 +Epoch: [23] [1180/4276] eta: 2:31:19 lr: 2.2809599053938272e-05 loss: 0.1008 (0.1067) time: 2.9340 data: 0.0078 max mem: 33301 +Epoch: [23] [1190/4276] eta: 2:30:50 lr: 2.280672833716872e-05 loss: 0.1019 (0.1066) time: 2.9353 data: 0.0079 max mem: 33301 +Epoch: [23] [1200/4276] eta: 2:30:21 lr: 2.2803857580249562e-05 loss: 0.0949 (0.1066) time: 2.9369 data: 0.0082 max mem: 33301 +Epoch: [23] [1210/4276] eta: 2:29:52 lr: 2.280098678317463e-05 loss: 0.0958 (0.1065) time: 2.9382 data: 0.0083 max mem: 33301 +Epoch: [23] [1220/4276] eta: 2:29:23 lr: 2.2798115945937727e-05 loss: 0.0960 (0.1066) time: 2.9460 data: 0.0081 max mem: 33301 +Epoch: [23] [1230/4276] eta: 2:28:54 lr: 2.2795245068532685e-05 loss: 0.1016 (0.1066) time: 2.9473 data: 0.0077 max mem: 33301 +Epoch: [23] [1240/4276] eta: 2:28:25 lr: 2.2792374150953317e-05 loss: 0.1048 (0.1067) time: 2.9400 data: 0.0080 max mem: 33301 +Epoch: [23] [1250/4276] eta: 2:27:55 lr: 2.278950319319344e-05 loss: 0.1083 (0.1067) time: 2.9374 data: 0.0081 max mem: 33301 +Epoch: [23] [1260/4276] eta: 2:27:26 lr: 2.278663219524686e-05 loss: 0.0972 (0.1066) time: 2.9362 data: 0.0078 max mem: 33301 +Epoch: [23] [1270/4276] eta: 2:26:57 lr: 2.27837611571074e-05 loss: 0.0953 (0.1065) time: 2.9371 data: 0.0079 max mem: 33301 +Epoch: [23] [1280/4276] eta: 2:26:27 lr: 2.278089007876886e-05 loss: 0.0967 (0.1065) time: 2.9355 data: 0.0081 max mem: 33301 +Epoch: [23] [1290/4276] eta: 2:25:58 lr: 2.2778018960225057e-05 loss: 0.0996 (0.1065) time: 2.9364 data: 0.0082 max mem: 33301 +Epoch: [23] [1300/4276] eta: 2:25:29 lr: 2.2775147801469785e-05 loss: 0.0911 (0.1065) time: 2.9415 data: 0.0080 max mem: 33301 +Epoch: [23] [1310/4276] eta: 2:25:00 lr: 2.2772276602496853e-05 loss: 0.0870 (0.1063) time: 2.9389 data: 0.0079 max mem: 33301 +Epoch: [23] [1320/4276] eta: 2:24:31 lr: 2.276940536330007e-05 loss: 0.0959 (0.1063) time: 2.9345 data: 0.0080 max mem: 33301 +Epoch: [23] [1330/4276] eta: 2:24:01 lr: 2.276653408387323e-05 loss: 0.1064 (0.1063) time: 2.9351 data: 0.0082 max mem: 33301 +Epoch: [23] [1340/4276] eta: 2:23:32 lr: 2.276366276421013e-05 loss: 0.0967 (0.1063) time: 2.9406 data: 0.0080 max mem: 33301 +Epoch: [23] [1350/4276] eta: 2:23:03 lr: 2.276079140430457e-05 loss: 0.0993 (0.1064) time: 2.9396 data: 0.0078 max mem: 33301 +Epoch: [23] [1360/4276] eta: 2:22:34 lr: 2.2757920004150345e-05 loss: 0.1019 (0.1063) time: 2.9367 data: 0.0080 max mem: 33301 +Epoch: [23] [1370/4276] eta: 2:22:04 lr: 2.275504856374125e-05 loss: 0.1019 (0.1064) time: 2.9379 data: 0.0082 max mem: 33301 +Epoch: [23] [1380/4276] eta: 2:21:35 lr: 2.2752177083071068e-05 loss: 0.1218 (0.1065) time: 2.9349 data: 0.0079 max mem: 33301 +Epoch: [23] [1390/4276] eta: 2:21:06 lr: 2.2749305562133598e-05 loss: 0.1218 (0.1066) time: 2.9347 data: 0.0078 max mem: 33301 +Epoch: [23] [1400/4276] eta: 2:20:36 lr: 2.2746434000922628e-05 loss: 0.1181 (0.1066) time: 2.9358 data: 0.0080 max mem: 33301 +Epoch: [23] [1410/4276] eta: 2:20:07 lr: 2.2743562399431935e-05 loss: 0.1022 (0.1066) time: 2.9343 data: 0.0082 max mem: 33301 +Epoch: [23] [1420/4276] eta: 2:19:38 lr: 2.274069075765531e-05 loss: 0.0953 (0.1066) time: 2.9330 data: 0.0079 max mem: 33301 +Epoch: [23] [1430/4276] eta: 2:19:08 lr: 2.2737819075586533e-05 loss: 0.1008 (0.1066) time: 2.9334 data: 0.0077 max mem: 33301 +Epoch: [23] [1440/4276] eta: 2:18:39 lr: 2.273494735321939e-05 loss: 0.1073 (0.1066) time: 2.9338 data: 0.0079 max mem: 33301 +Epoch: [23] [1450/4276] eta: 2:18:10 lr: 2.273207559054765e-05 loss: 0.1026 (0.1066) time: 2.9351 data: 0.0082 max mem: 33301 +Epoch: [23] [1460/4276] eta: 2:17:40 lr: 2.2729203787565092e-05 loss: 0.1026 (0.1065) time: 2.9347 data: 0.0081 max mem: 33301 +Epoch: [23] [1470/4276] eta: 2:17:11 lr: 2.2726331944265493e-05 loss: 0.1035 (0.1065) time: 2.9334 data: 0.0078 max mem: 33301 +Epoch: [23] [1480/4276] eta: 2:16:42 lr: 2.2723460060642633e-05 loss: 0.1098 (0.1065) time: 2.9335 data: 0.0081 max mem: 33301 +Epoch: [23] [1490/4276] eta: 2:16:12 lr: 2.272058813669027e-05 loss: 0.0995 (0.1065) time: 2.9340 data: 0.0080 max mem: 33301 +Epoch: [23] [1500/4276] eta: 2:15:43 lr: 2.271771617240218e-05 loss: 0.0883 (0.1065) time: 2.9344 data: 0.0078 max mem: 33301 +Epoch: [23] [1510/4276] eta: 2:15:14 lr: 2.271484416777213e-05 loss: 0.0957 (0.1065) time: 2.9332 data: 0.0078 max mem: 33301 +Epoch: [23] [1520/4276] eta: 2:14:45 lr: 2.271197212279389e-05 loss: 0.1006 (0.1065) time: 2.9339 data: 0.0078 max mem: 33301 +Epoch: [23] [1530/4276] eta: 2:14:15 lr: 2.2709100037461214e-05 loss: 0.0944 (0.1064) time: 2.9361 data: 0.0079 max mem: 33301 +Epoch: [23] [1540/4276] eta: 2:13:45 lr: 2.270622791176787e-05 loss: 0.0944 (0.1065) time: 2.9157 data: 0.0075 max mem: 33301 +Epoch: [23] [1550/4276] eta: 2:13:16 lr: 2.270335574570762e-05 loss: 0.1014 (0.1065) time: 2.9212 data: 0.0073 max mem: 33301 +Epoch: [23] [1560/4276] eta: 2:12:47 lr: 2.2700483539274226e-05 loss: 0.0986 (0.1064) time: 2.9431 data: 0.0078 max mem: 33301 +Epoch: [23] [1570/4276] eta: 2:12:18 lr: 2.269761129246143e-05 loss: 0.0979 (0.1064) time: 2.9377 data: 0.0081 max mem: 33301 +Epoch: [23] [1580/4276] eta: 2:11:48 lr: 2.2694739005262997e-05 loss: 0.0936 (0.1063) time: 2.9376 data: 0.0080 max mem: 33301 +Epoch: [23] [1590/4276] eta: 2:11:19 lr: 2.2691866677672676e-05 loss: 0.0945 (0.1063) time: 2.9373 data: 0.0078 max mem: 33301 +Epoch: [23] [1600/4276] eta: 2:10:50 lr: 2.2688994309684227e-05 loss: 0.1038 (0.1063) time: 2.9346 data: 0.0077 max mem: 33301 +Epoch: [23] [1610/4276] eta: 2:10:20 lr: 2.2686121901291388e-05 loss: 0.0968 (0.1062) time: 2.9278 data: 0.0075 max mem: 33301 +Epoch: [23] [1620/4276] eta: 2:09:51 lr: 2.2683249452487905e-05 loss: 0.0950 (0.1062) time: 2.9275 data: 0.0073 max mem: 33301 +Epoch: [23] [1630/4276] eta: 2:09:21 lr: 2.268037696326754e-05 loss: 0.0952 (0.1062) time: 2.9327 data: 0.0073 max mem: 33301 +Epoch: [23] [1640/4276] eta: 2:08:52 lr: 2.2677504433624018e-05 loss: 0.0836 (0.1060) time: 2.9331 data: 0.0076 max mem: 33301 +Epoch: [23] [1650/4276] eta: 2:08:23 lr: 2.267463186355109e-05 loss: 0.0859 (0.1060) time: 2.9327 data: 0.0076 max mem: 33301 +Epoch: [23] [1660/4276] eta: 2:07:53 lr: 2.267175925304249e-05 loss: 0.0930 (0.1059) time: 2.9317 data: 0.0073 max mem: 33301 +Epoch: [23] [1670/4276] eta: 2:07:24 lr: 2.2668886602091965e-05 loss: 0.1002 (0.1059) time: 2.9321 data: 0.0073 max mem: 33301 +Epoch: [23] [1680/4276] eta: 2:06:55 lr: 2.266601391069324e-05 loss: 0.0996 (0.1059) time: 2.9336 data: 0.0076 max mem: 33301 +Epoch: [23] [1690/4276] eta: 2:06:25 lr: 2.2663141178840062e-05 loss: 0.0912 (0.1058) time: 2.9336 data: 0.0078 max mem: 33301 +Epoch: [23] [1700/4276] eta: 2:05:56 lr: 2.266026840652615e-05 loss: 0.0877 (0.1058) time: 2.9337 data: 0.0076 max mem: 33301 +Epoch: [23] [1710/4276] eta: 2:05:27 lr: 2.265739559374525e-05 loss: 0.0866 (0.1057) time: 2.9340 data: 0.0074 max mem: 33301 +Epoch: [23] [1720/4276] eta: 2:04:57 lr: 2.2654522740491078e-05 loss: 0.0876 (0.1057) time: 2.9324 data: 0.0074 max mem: 33301 +Epoch: [23] [1730/4276] eta: 2:04:28 lr: 2.2651649846757363e-05 loss: 0.0916 (0.1057) time: 2.9142 data: 0.0071 max mem: 33301 +Epoch: [23] [1740/4276] eta: 2:03:58 lr: 2.264877691253783e-05 loss: 0.0843 (0.1056) time: 2.8924 data: 0.0068 max mem: 33301 +Epoch: [23] [1750/4276] eta: 2:03:28 lr: 2.2645903937826213e-05 loss: 0.0865 (0.1055) time: 2.9128 data: 0.0073 max mem: 33301 +Epoch: [23] [1760/4276] eta: 2:02:59 lr: 2.2643030922616216e-05 loss: 0.0894 (0.1054) time: 2.9366 data: 0.0080 max mem: 33301 +Epoch: [23] [1770/4276] eta: 2:02:30 lr: 2.264015786690157e-05 loss: 0.0855 (0.1054) time: 2.9345 data: 0.0079 max mem: 33301 +Epoch: [23] [1780/4276] eta: 2:02:00 lr: 2.263728477067599e-05 loss: 0.0929 (0.1054) time: 2.9326 data: 0.0076 max mem: 33301 +Epoch: [23] [1790/4276] eta: 2:01:31 lr: 2.2634411633933195e-05 loss: 0.0939 (0.1053) time: 2.9327 data: 0.0074 max mem: 33301 +Epoch: [23] [1800/4276] eta: 2:01:02 lr: 2.263153845666689e-05 loss: 0.0939 (0.1053) time: 2.9338 data: 0.0076 max mem: 33301 +Epoch: [23] [1810/4276] eta: 2:00:32 lr: 2.2628665238870792e-05 loss: 0.1085 (0.1054) time: 2.9257 data: 0.0075 max mem: 33301 +Epoch: [23] [1820/4276] eta: 2:00:03 lr: 2.262579198053861e-05 loss: 0.1210 (0.1054) time: 2.9197 data: 0.0076 max mem: 33301 +Epoch: [23] [1830/4276] eta: 1:59:33 lr: 2.262291868166406e-05 loss: 0.1070 (0.1054) time: 2.9266 data: 0.0076 max mem: 33301 +Epoch: [23] [1840/4276] eta: 1:59:04 lr: 2.262004534224084e-05 loss: 0.0939 (0.1053) time: 2.9262 data: 0.0072 max mem: 33301 +Epoch: [23] [1850/4276] eta: 1:58:34 lr: 2.261717196226265e-05 loss: 0.0953 (0.1054) time: 2.8998 data: 0.0072 max mem: 33301 +Epoch: [23] [1860/4276] eta: 1:58:04 lr: 2.2614298541723207e-05 loss: 0.0982 (0.1054) time: 2.9005 data: 0.0075 max mem: 33301 +Epoch: [23] [1870/4276] eta: 1:57:35 lr: 2.26114250806162e-05 loss: 0.0997 (0.1054) time: 2.9270 data: 0.0079 max mem: 33301 +Epoch: [23] [1880/4276] eta: 1:57:06 lr: 2.2608551578935335e-05 loss: 0.0937 (0.1053) time: 2.9352 data: 0.0077 max mem: 33301 +Epoch: [23] [1890/4276] eta: 1:56:36 lr: 2.2605678036674303e-05 loss: 0.1004 (0.1053) time: 2.9367 data: 0.0075 max mem: 33301 +Epoch: [23] [1900/4276] eta: 1:56:07 lr: 2.2602804453826803e-05 loss: 0.1004 (0.1053) time: 2.9342 data: 0.0075 max mem: 33301 +Epoch: [23] [1910/4276] eta: 1:55:38 lr: 2.2599930830386533e-05 loss: 0.0971 (0.1054) time: 2.9272 data: 0.0076 max mem: 33301 +Epoch: [23] [1920/4276] eta: 1:55:08 lr: 2.2597057166347174e-05 loss: 0.0923 (0.1053) time: 2.9269 data: 0.0074 max mem: 33301 +Epoch: [23] [1930/4276] eta: 1:54:39 lr: 2.259418346170242e-05 loss: 0.0879 (0.1053) time: 2.9313 data: 0.0073 max mem: 33301 +Epoch: [23] [1940/4276] eta: 1:54:10 lr: 2.259130971644597e-05 loss: 0.0970 (0.1053) time: 2.9330 data: 0.0073 max mem: 33301 +Epoch: [23] [1950/4276] eta: 1:53:40 lr: 2.2588435930571485e-05 loss: 0.0998 (0.1053) time: 2.9352 data: 0.0072 max mem: 33301 +Epoch: [23] [1960/4276] eta: 1:53:11 lr: 2.258556210407267e-05 loss: 0.0887 (0.1053) time: 2.9331 data: 0.0070 max mem: 33301 +Epoch: [23] [1970/4276] eta: 1:52:42 lr: 2.2582688236943196e-05 loss: 0.0848 (0.1052) time: 2.9352 data: 0.0072 max mem: 33301 +Epoch: [23] [1980/4276] eta: 1:52:13 lr: 2.2579814329176758e-05 loss: 0.0848 (0.1051) time: 2.9375 data: 0.0073 max mem: 33301 +Epoch: [23] [1990/4276] eta: 1:51:43 lr: 2.2576940380767016e-05 loss: 0.0953 (0.1051) time: 2.9357 data: 0.0072 max mem: 33301 +Epoch: [23] [2000/4276] eta: 1:51:14 lr: 2.2574066391707654e-05 loss: 0.1018 (0.1052) time: 2.9337 data: 0.0072 max mem: 33301 +Epoch: [23] [2010/4276] eta: 1:50:45 lr: 2.257119236199235e-05 loss: 0.0989 (0.1051) time: 2.9368 data: 0.0071 max mem: 33301 +Epoch: [23] [2020/4276] eta: 1:50:15 lr: 2.2568318291614776e-05 loss: 0.0979 (0.1052) time: 2.9383 data: 0.0071 max mem: 33301 +Epoch: [23] [2030/4276] eta: 1:49:46 lr: 2.2565444180568596e-05 loss: 0.0979 (0.1051) time: 2.9370 data: 0.0071 max mem: 33301 +Epoch: [23] [2040/4276] eta: 1:49:17 lr: 2.2562570028847483e-05 loss: 0.0961 (0.1051) time: 2.9371 data: 0.0071 max mem: 33301 +Epoch: [23] [2050/4276] eta: 1:48:48 lr: 2.2559695836445106e-05 loss: 0.0991 (0.1051) time: 2.9340 data: 0.0074 max mem: 33301 +Epoch: [23] [2060/4276] eta: 1:48:18 lr: 2.2556821603355136e-05 loss: 0.1045 (0.1052) time: 2.9335 data: 0.0075 max mem: 33301 +Epoch: [23] [2070/4276] eta: 1:47:49 lr: 2.255394732957122e-05 loss: 0.0927 (0.1051) time: 2.9294 data: 0.0074 max mem: 33301 +Epoch: [23] [2080/4276] eta: 1:47:19 lr: 2.2551073015087033e-05 loss: 0.1001 (0.1052) time: 2.9297 data: 0.0071 max mem: 33301 +Epoch: [23] [2090/4276] eta: 1:46:50 lr: 2.2548198659896227e-05 loss: 0.1045 (0.1052) time: 2.9341 data: 0.0070 max mem: 33301 +Epoch: [23] [2100/4276] eta: 1:46:21 lr: 2.254532426399247e-05 loss: 0.1069 (0.1052) time: 2.9333 data: 0.0069 max mem: 33301 +Epoch: [23] [2110/4276] eta: 1:45:52 lr: 2.2542449827369406e-05 loss: 0.1063 (0.1052) time: 2.9338 data: 0.0068 max mem: 33301 +Epoch: [23] [2120/4276] eta: 1:45:22 lr: 2.253957535002069e-05 loss: 0.0842 (0.1050) time: 2.9342 data: 0.0067 max mem: 33301 +Epoch: [23] [2130/4276] eta: 1:44:53 lr: 2.253670083193998e-05 loss: 0.0810 (0.1050) time: 2.9412 data: 0.0067 max mem: 33301 +Epoch: [23] [2140/4276] eta: 1:44:24 lr: 2.2533826273120928e-05 loss: 0.0863 (0.1049) time: 2.9403 data: 0.0068 max mem: 33301 +Epoch: [23] [2150/4276] eta: 1:43:54 lr: 2.2530951673557175e-05 loss: 0.0886 (0.1049) time: 2.9337 data: 0.0066 max mem: 33301 +Epoch: [23] [2160/4276] eta: 1:43:25 lr: 2.2528077033242366e-05 loss: 0.0910 (0.1049) time: 2.9355 data: 0.0067 max mem: 33301 +Epoch: [23] [2170/4276] eta: 1:42:56 lr: 2.252520235217015e-05 loss: 0.0975 (0.1049) time: 2.9367 data: 0.0070 max mem: 33301 +Epoch: [23] [2180/4276] eta: 1:42:27 lr: 2.2522327630334177e-05 loss: 0.1084 (0.1049) time: 2.9353 data: 0.0069 max mem: 33301 +Epoch: [23] [2190/4276] eta: 1:41:57 lr: 2.2519452867728075e-05 loss: 0.1109 (0.1049) time: 2.9069 data: 0.0067 max mem: 33301 +Epoch: [23] [2200/4276] eta: 1:41:27 lr: 2.2516578064345485e-05 loss: 0.1119 (0.1050) time: 2.8807 data: 0.0069 max mem: 33301 +Epoch: [23] [2210/4276] eta: 1:40:57 lr: 2.2513703220180047e-05 loss: 0.1013 (0.1049) time: 2.8799 data: 0.0070 max mem: 33301 +Epoch: [23] [2220/4276] eta: 1:40:27 lr: 2.25108283352254e-05 loss: 0.1048 (0.1050) time: 2.8844 data: 0.0073 max mem: 33301 +Epoch: [23] [2230/4276] eta: 1:39:58 lr: 2.2507953409475168e-05 loss: 0.0998 (0.1049) time: 2.8968 data: 0.0080 max mem: 33301 +Epoch: [23] [2240/4276] eta: 1:39:29 lr: 2.250507844292299e-05 loss: 0.0889 (0.1049) time: 2.9229 data: 0.0082 max mem: 33301 +Epoch: [23] [2250/4276] eta: 1:38:59 lr: 2.2502203435562493e-05 loss: 0.0940 (0.1048) time: 2.9394 data: 0.0078 max mem: 33301 +Epoch: [23] [2260/4276] eta: 1:38:30 lr: 2.2499328387387296e-05 loss: 0.1022 (0.1049) time: 2.9350 data: 0.0075 max mem: 33301 +Epoch: [23] [2270/4276] eta: 1:38:01 lr: 2.2496453298391034e-05 loss: 0.1062 (0.1049) time: 2.9331 data: 0.0074 max mem: 33301 +Epoch: [23] [2280/4276] eta: 1:37:31 lr: 2.249357816856733e-05 loss: 0.0969 (0.1048) time: 2.9332 data: 0.0074 max mem: 33301 +Epoch: [23] [2290/4276] eta: 1:37:02 lr: 2.2490702997909807e-05 loss: 0.0969 (0.1048) time: 2.9327 data: 0.0076 max mem: 33301 +Epoch: [23] [2300/4276] eta: 1:36:33 lr: 2.248782778641208e-05 loss: 0.1007 (0.1049) time: 2.9205 data: 0.0075 max mem: 33301 +Epoch: [23] [2310/4276] eta: 1:36:03 lr: 2.2484952534067762e-05 loss: 0.1052 (0.1049) time: 2.9212 data: 0.0069 max mem: 33301 +Epoch: [23] [2320/4276] eta: 1:35:34 lr: 2.2482077240870478e-05 loss: 0.1095 (0.1049) time: 2.9335 data: 0.0067 max mem: 33301 +Epoch: [23] [2330/4276] eta: 1:35:05 lr: 2.2479201906813845e-05 loss: 0.1207 (0.1050) time: 2.9345 data: 0.0067 max mem: 33301 +Epoch: [23] [2340/4276] eta: 1:34:35 lr: 2.2476326531891468e-05 loss: 0.1168 (0.1050) time: 2.9277 data: 0.0071 max mem: 33301 +Epoch: [23] [2350/4276] eta: 1:34:06 lr: 2.2473451116096955e-05 loss: 0.1055 (0.1050) time: 2.9254 data: 0.0071 max mem: 33301 +Epoch: [23] [2360/4276] eta: 1:33:37 lr: 2.2470575659423917e-05 loss: 0.1036 (0.1050) time: 2.9330 data: 0.0067 max mem: 33301 +Epoch: [23] [2370/4276] eta: 1:33:07 lr: 2.2467700161865972e-05 loss: 0.1050 (0.1050) time: 2.9352 data: 0.0068 max mem: 33301 +Epoch: [23] [2380/4276] eta: 1:32:38 lr: 2.24648246234167e-05 loss: 0.1101 (0.1051) time: 2.9351 data: 0.0069 max mem: 33301 +Epoch: [23] [2390/4276] eta: 1:32:08 lr: 2.2461949044069728e-05 loss: 0.1101 (0.1051) time: 2.9137 data: 0.0068 max mem: 33301 +Epoch: [23] [2400/4276] eta: 1:31:39 lr: 2.245907342381864e-05 loss: 0.1140 (0.1051) time: 2.8846 data: 0.0070 max mem: 33301 +Epoch: [23] [2410/4276] eta: 1:31:09 lr: 2.245619776265705e-05 loss: 0.1109 (0.1051) time: 2.9021 data: 0.0076 max mem: 33301 +Epoch: [23] [2420/4276] eta: 1:30:40 lr: 2.2453322060578537e-05 loss: 0.1010 (0.1051) time: 2.9322 data: 0.0078 max mem: 33301 +Epoch: [23] [2430/4276] eta: 1:30:11 lr: 2.2450446317576708e-05 loss: 0.1068 (0.1052) time: 2.9370 data: 0.0076 max mem: 33301 +Epoch: [23] [2440/4276] eta: 1:29:42 lr: 2.2447570533645153e-05 loss: 0.1077 (0.1051) time: 2.9383 data: 0.0075 max mem: 33301 +Epoch: [23] [2450/4276] eta: 1:29:12 lr: 2.2444694708777467e-05 loss: 0.1052 (0.1052) time: 2.9397 data: 0.0074 max mem: 33301 +Epoch: [23] [2460/4276] eta: 1:28:43 lr: 2.244181884296723e-05 loss: 0.1096 (0.1052) time: 2.9391 data: 0.0075 max mem: 33301 +Epoch: [23] [2470/4276] eta: 1:28:14 lr: 2.2438942936208035e-05 loss: 0.1061 (0.1052) time: 2.9373 data: 0.0075 max mem: 33301 +Epoch: [23] [2480/4276] eta: 1:27:44 lr: 2.2436066988493464e-05 loss: 0.1061 (0.1053) time: 2.9378 data: 0.0075 max mem: 33301 +Epoch: [23] [2490/4276] eta: 1:27:15 lr: 2.2433190999817115e-05 loss: 0.1029 (0.1053) time: 2.9374 data: 0.0075 max mem: 33301 +Epoch: [23] [2500/4276] eta: 1:26:46 lr: 2.2430314970172547e-05 loss: 0.1029 (0.1053) time: 2.9360 data: 0.0074 max mem: 33301 +Epoch: [23] [2510/4276] eta: 1:26:16 lr: 2.2427438899553356e-05 loss: 0.1089 (0.1053) time: 2.9260 data: 0.0074 max mem: 33301 +Epoch: [23] [2520/4276] eta: 1:25:47 lr: 2.242456278795311e-05 loss: 0.0956 (0.1052) time: 2.9281 data: 0.0074 max mem: 33301 +Epoch: [23] [2530/4276] eta: 1:25:18 lr: 2.2421686635365398e-05 loss: 0.0831 (0.1052) time: 2.9387 data: 0.0076 max mem: 33301 +Epoch: [23] [2540/4276] eta: 1:24:49 lr: 2.2418810441783776e-05 loss: 0.0881 (0.1052) time: 2.9359 data: 0.0074 max mem: 33301 +Epoch: [23] [2550/4276] eta: 1:24:19 lr: 2.2415934207201826e-05 loss: 0.0985 (0.1051) time: 2.9365 data: 0.0074 max mem: 33301 +Epoch: [23] [2560/4276] eta: 1:23:50 lr: 2.241305793161312e-05 loss: 0.0818 (0.1051) time: 2.9370 data: 0.0076 max mem: 33301 +Epoch: [23] [2570/4276] eta: 1:23:21 lr: 2.241018161501122e-05 loss: 0.0884 (0.1051) time: 2.9351 data: 0.0075 max mem: 33301 +Epoch: [23] [2580/4276] eta: 1:22:52 lr: 2.2407305257389696e-05 loss: 0.0962 (0.1051) time: 2.9347 data: 0.0074 max mem: 33301 +Epoch: [23] [2590/4276] eta: 1:22:22 lr: 2.240442885874211e-05 loss: 0.0962 (0.1051) time: 2.9348 data: 0.0075 max mem: 33301 +Epoch: [23] [2600/4276] eta: 1:21:53 lr: 2.240155241906203e-05 loss: 0.0984 (0.1050) time: 2.9235 data: 0.0075 max mem: 33301 +Epoch: [23] [2610/4276] eta: 1:21:23 lr: 2.239867593834301e-05 loss: 0.0952 (0.1050) time: 2.9211 data: 0.0074 max mem: 33301 +Epoch: [23] [2620/4276] eta: 1:20:54 lr: 2.2395799416578607e-05 loss: 0.1062 (0.1050) time: 2.9317 data: 0.0074 max mem: 33301 +Epoch: [23] [2630/4276] eta: 1:20:25 lr: 2.2392922853762384e-05 loss: 0.0968 (0.1050) time: 2.9493 data: 0.0073 max mem: 33301 +Epoch: [23] [2640/4276] eta: 1:19:56 lr: 2.2390046249887896e-05 loss: 0.0900 (0.1050) time: 2.9499 data: 0.0073 max mem: 33301 +Epoch: [23] [2650/4276] eta: 1:19:26 lr: 2.238716960494868e-05 loss: 0.0960 (0.1050) time: 2.9362 data: 0.0073 max mem: 33301 +Epoch: [23] [2660/4276] eta: 1:18:57 lr: 2.2384292918938306e-05 loss: 0.1006 (0.1050) time: 2.9375 data: 0.0072 max mem: 33301 +Epoch: [23] [2670/4276] eta: 1:18:28 lr: 2.2381416191850316e-05 loss: 0.1046 (0.1050) time: 2.9374 data: 0.0071 max mem: 33301 +Epoch: [23] [2680/4276] eta: 1:17:59 lr: 2.237853942367826e-05 loss: 0.1084 (0.1050) time: 2.9376 data: 0.0070 max mem: 33301 +Epoch: [23] [2690/4276] eta: 1:17:29 lr: 2.2375662614415673e-05 loss: 0.1058 (0.1050) time: 2.9352 data: 0.0072 max mem: 33301 +Epoch: [23] [2700/4276] eta: 1:17:00 lr: 2.2372785764056108e-05 loss: 0.0962 (0.1049) time: 2.9278 data: 0.0072 max mem: 33301 +Epoch: [23] [2710/4276] eta: 1:16:31 lr: 2.2369908872593097e-05 loss: 0.0953 (0.1049) time: 2.9296 data: 0.0070 max mem: 33301 +Epoch: [23] [2720/4276] eta: 1:16:01 lr: 2.2367031940020193e-05 loss: 0.0888 (0.1048) time: 2.9364 data: 0.0073 max mem: 33301 +Epoch: [23] [2730/4276] eta: 1:15:32 lr: 2.236415496633092e-05 loss: 0.0935 (0.1049) time: 2.9367 data: 0.0074 max mem: 33301 +Epoch: [23] [2740/4276] eta: 1:15:03 lr: 2.2361277951518818e-05 loss: 0.1048 (0.1049) time: 2.9350 data: 0.0072 max mem: 33301 +Epoch: [23] [2750/4276] eta: 1:14:33 lr: 2.2358400895577418e-05 loss: 0.1081 (0.1049) time: 2.9333 data: 0.0070 max mem: 33301 +Epoch: [23] [2760/4276] eta: 1:14:04 lr: 2.235552379850026e-05 loss: 0.1081 (0.1049) time: 2.9339 data: 0.0070 max mem: 33301 +Epoch: [23] [2770/4276] eta: 1:13:35 lr: 2.2352646660280857e-05 loss: 0.1048 (0.1049) time: 2.9348 data: 0.0072 max mem: 33301 +Epoch: [23] [2780/4276] eta: 1:13:06 lr: 2.234976948091275e-05 loss: 0.0960 (0.1049) time: 2.9339 data: 0.0072 max mem: 33301 +Epoch: [23] [2790/4276] eta: 1:12:36 lr: 2.234689226038946e-05 loss: 0.0972 (0.1049) time: 2.9302 data: 0.0070 max mem: 33301 +Epoch: [23] [2800/4276] eta: 1:12:07 lr: 2.2344014998704517e-05 loss: 0.0942 (0.1049) time: 2.9314 data: 0.0072 max mem: 33301 +Epoch: [23] [2810/4276] eta: 1:11:38 lr: 2.234113769585143e-05 loss: 0.0800 (0.1048) time: 2.9351 data: 0.0074 max mem: 33301 +Epoch: [23] [2820/4276] eta: 1:11:08 lr: 2.2338260351823727e-05 loss: 0.0861 (0.1047) time: 2.9356 data: 0.0073 max mem: 33301 +Epoch: [23] [2830/4276] eta: 1:10:39 lr: 2.233538296661492e-05 loss: 0.0925 (0.1047) time: 2.9351 data: 0.0071 max mem: 33301 +Epoch: [23] [2840/4276] eta: 1:10:10 lr: 2.233250554021854e-05 loss: 0.1036 (0.1047) time: 2.9354 data: 0.0073 max mem: 33301 +Epoch: [23] [2850/4276] eta: 1:09:40 lr: 2.232962807262808e-05 loss: 0.1001 (0.1047) time: 2.9389 data: 0.0075 max mem: 33301 +Epoch: [23] [2860/4276] eta: 1:09:11 lr: 2.2326750563837064e-05 loss: 0.0980 (0.1047) time: 2.9413 data: 0.0072 max mem: 33301 +Epoch: [23] [2870/4276] eta: 1:08:42 lr: 2.2323873013839005e-05 loss: 0.0980 (0.1047) time: 2.9416 data: 0.0071 max mem: 33301 +Epoch: [23] [2880/4276] eta: 1:08:13 lr: 2.23209954226274e-05 loss: 0.0966 (0.1047) time: 2.9404 data: 0.0073 max mem: 33301 +Epoch: [23] [2890/4276] eta: 1:07:43 lr: 2.2318117790195758e-05 loss: 0.0926 (0.1047) time: 2.9389 data: 0.0075 max mem: 33301 +Epoch: [23] [2900/4276] eta: 1:07:14 lr: 2.231524011653759e-05 loss: 0.0911 (0.1047) time: 2.9355 data: 0.0073 max mem: 33301 +Epoch: [23] [2910/4276] eta: 1:06:45 lr: 2.2312362401646394e-05 loss: 0.0911 (0.1047) time: 2.9351 data: 0.0071 max mem: 33301 +Epoch: [23] [2920/4276] eta: 1:06:15 lr: 2.2309484645515667e-05 loss: 0.1022 (0.1047) time: 2.9363 data: 0.0073 max mem: 33301 +Epoch: [23] [2930/4276] eta: 1:05:46 lr: 2.2306606848138912e-05 loss: 0.0911 (0.1046) time: 2.9367 data: 0.0077 max mem: 33301 +Epoch: [23] [2940/4276] eta: 1:05:17 lr: 2.230372900950962e-05 loss: 0.0910 (0.1046) time: 2.9370 data: 0.0077 max mem: 33301 +Epoch: [23] [2950/4276] eta: 1:04:47 lr: 2.2300851129621294e-05 loss: 0.1017 (0.1046) time: 2.9349 data: 0.0073 max mem: 33301 +Epoch: [23] [2960/4276] eta: 1:04:18 lr: 2.2297973208467414e-05 loss: 0.0974 (0.1046) time: 2.9348 data: 0.0073 max mem: 33301 +Epoch: [23] [2970/4276] eta: 1:03:49 lr: 2.229509524604148e-05 loss: 0.0994 (0.1046) time: 2.9421 data: 0.0075 max mem: 33301 +Epoch: [23] [2980/4276] eta: 1:03:20 lr: 2.2292217242336976e-05 loss: 0.1035 (0.1047) time: 2.9422 data: 0.0073 max mem: 33301 +Epoch: [23] [2990/4276] eta: 1:02:50 lr: 2.2289339197347398e-05 loss: 0.0924 (0.1046) time: 2.9495 data: 0.0072 max mem: 33301 +Epoch: [23] [3000/4276] eta: 1:02:21 lr: 2.2286461111066213e-05 loss: 0.0929 (0.1046) time: 2.9501 data: 0.0075 max mem: 33301 +Epoch: [23] [3010/4276] eta: 1:01:52 lr: 2.2283582983486918e-05 loss: 0.1027 (0.1046) time: 2.9362 data: 0.0077 max mem: 33301 +Epoch: [23] [3020/4276] eta: 1:01:23 lr: 2.2280704814602982e-05 loss: 0.1029 (0.1046) time: 2.9425 data: 0.0073 max mem: 33301 +Epoch: [23] [3030/4276] eta: 1:00:53 lr: 2.22778266044079e-05 loss: 0.0973 (0.1046) time: 2.9430 data: 0.0071 max mem: 33301 +Epoch: [23] [3040/4276] eta: 1:00:24 lr: 2.227494835289513e-05 loss: 0.0992 (0.1046) time: 2.9398 data: 0.0073 max mem: 33301 +Epoch: [23] [3050/4276] eta: 0:59:55 lr: 2.2272070060058157e-05 loss: 0.0968 (0.1046) time: 2.9374 data: 0.0074 max mem: 33301 +Epoch: [23] [3060/4276] eta: 0:59:25 lr: 2.2269191725890453e-05 loss: 0.0892 (0.1045) time: 2.9323 data: 0.0073 max mem: 33301 +Epoch: [23] [3070/4276] eta: 0:58:56 lr: 2.226631335038549e-05 loss: 0.0916 (0.1045) time: 2.9351 data: 0.0071 max mem: 33301 +Epoch: [23] [3080/4276] eta: 0:58:27 lr: 2.2263434933536733e-05 loss: 0.0962 (0.1045) time: 2.9394 data: 0.0072 max mem: 33301 +Epoch: [23] [3090/4276] eta: 0:57:57 lr: 2.226055647533765e-05 loss: 0.0928 (0.1045) time: 2.9402 data: 0.0074 max mem: 33301 +Epoch: [23] [3100/4276] eta: 0:57:28 lr: 2.22576779757817e-05 loss: 0.0930 (0.1045) time: 2.9409 data: 0.0072 max mem: 33301 +Epoch: [23] [3110/4276] eta: 0:56:59 lr: 2.2254799434862364e-05 loss: 0.0926 (0.1044) time: 2.9408 data: 0.0071 max mem: 33301 +Epoch: [23] [3120/4276] eta: 0:56:30 lr: 2.2251920852573082e-05 loss: 0.0871 (0.1044) time: 2.9393 data: 0.0073 max mem: 33301 +Epoch: [23] [3130/4276] eta: 0:56:00 lr: 2.224904222890732e-05 loss: 0.0939 (0.1044) time: 2.9390 data: 0.0073 max mem: 33301 +Epoch: [23] [3140/4276] eta: 0:55:31 lr: 2.224616356385854e-05 loss: 0.1021 (0.1044) time: 2.9361 data: 0.0071 max mem: 33301 +Epoch: [23] [3150/4276] eta: 0:55:02 lr: 2.2243284857420198e-05 loss: 0.1052 (0.1043) time: 2.9324 data: 0.0070 max mem: 33301 +Epoch: [23] [3160/4276] eta: 0:54:32 lr: 2.2240406109585736e-05 loss: 0.0992 (0.1043) time: 2.9314 data: 0.0071 max mem: 33301 +Epoch: [23] [3170/4276] eta: 0:54:03 lr: 2.223752732034861e-05 loss: 0.0992 (0.1043) time: 2.9326 data: 0.0073 max mem: 33301 +Epoch: [23] [3180/4276] eta: 0:53:34 lr: 2.2234648489702276e-05 loss: 0.0984 (0.1043) time: 2.9333 data: 0.0072 max mem: 33301 +Epoch: [23] [3190/4276] eta: 0:53:04 lr: 2.223176961764017e-05 loss: 0.0984 (0.1043) time: 2.9321 data: 0.0070 max mem: 33301 +Epoch: [23] [3200/4276] eta: 0:52:35 lr: 2.222889070415574e-05 loss: 0.1008 (0.1043) time: 2.9327 data: 0.0072 max mem: 33301 +Epoch: [23] [3210/4276] eta: 0:52:06 lr: 2.2226011749242438e-05 loss: 0.0983 (0.1044) time: 2.9366 data: 0.0075 max mem: 33301 +Epoch: [23] [3220/4276] eta: 0:51:36 lr: 2.2223132752893697e-05 loss: 0.1006 (0.1044) time: 2.9360 data: 0.0073 max mem: 33301 +Epoch: [23] [3230/4276] eta: 0:51:07 lr: 2.2220253715102954e-05 loss: 0.0961 (0.1043) time: 2.9344 data: 0.0071 max mem: 33301 +Epoch: [23] [3240/4276] eta: 0:50:38 lr: 2.2217374635863653e-05 loss: 0.1080 (0.1044) time: 2.9352 data: 0.0073 max mem: 33301 +Epoch: [23] [3250/4276] eta: 0:50:08 lr: 2.221449551516922e-05 loss: 0.1153 (0.1044) time: 2.9345 data: 0.0075 max mem: 33301 +Epoch: [23] [3260/4276] eta: 0:49:39 lr: 2.2211616353013103e-05 loss: 0.0994 (0.1044) time: 2.9365 data: 0.0074 max mem: 33301 +Epoch: [23] [3270/4276] eta: 0:49:10 lr: 2.2208737149388718e-05 loss: 0.1027 (0.1044) time: 2.9343 data: 0.0070 max mem: 33301 +Epoch: [23] [3280/4276] eta: 0:48:40 lr: 2.22058579042895e-05 loss: 0.1042 (0.1044) time: 2.9302 data: 0.0070 max mem: 33301 +Epoch: [23] [3290/4276] eta: 0:48:11 lr: 2.2202978617708877e-05 loss: 0.1092 (0.1044) time: 2.9326 data: 0.0073 max mem: 33301 +Epoch: [23] [3300/4276] eta: 0:47:42 lr: 2.220009928964028e-05 loss: 0.1113 (0.1045) time: 2.9346 data: 0.0072 max mem: 33301 +Epoch: [23] [3310/4276] eta: 0:47:12 lr: 2.2197219920077118e-05 loss: 0.1221 (0.1045) time: 2.9355 data: 0.0071 max mem: 33301 +Epoch: [23] 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mem: 33301 +Epoch: [23] [3400/4276] eta: 0:42:49 lr: 2.2171303725667435e-05 loss: 0.1058 (0.1046) time: 2.9337 data: 0.0071 max mem: 33301 +Epoch: [23] [3410/4276] eta: 0:42:19 lr: 2.2168423940796536e-05 loss: 0.1015 (0.1046) time: 2.9360 data: 0.0074 max mem: 33301 +Epoch: [23] [3420/4276] eta: 0:41:50 lr: 2.216554411435861e-05 loss: 0.1108 (0.1046) time: 2.9428 data: 0.0072 max mem: 33301 +Epoch: [23] [3430/4276] eta: 0:41:21 lr: 2.2162664246347046e-05 loss: 0.1188 (0.1047) time: 2.9433 data: 0.0072 max mem: 33301 +Epoch: [23] [3440/4276] eta: 0:40:51 lr: 2.215978433675524e-05 loss: 0.1072 (0.1047) time: 2.9364 data: 0.0074 max mem: 33301 +Epoch: [23] [3450/4276] eta: 0:40:22 lr: 2.21569043855766e-05 loss: 0.0998 (0.1047) time: 2.9362 data: 0.0075 max mem: 33301 +Epoch: [23] [3460/4276] eta: 0:39:53 lr: 2.215402439280451e-05 loss: 0.1060 (0.1047) time: 2.9339 data: 0.0074 max mem: 33301 +Epoch: [23] [3470/4276] eta: 0:39:23 lr: 2.2151144358432362e-05 loss: 0.0985 (0.1047) time: 2.9327 data: 0.0070 max mem: 33301 +Epoch: [23] [3480/4276] eta: 0:38:54 lr: 2.214826428245354e-05 loss: 0.0950 (0.1047) time: 2.9356 data: 0.0071 max mem: 33301 +Epoch: [23] [3490/4276] eta: 0:38:25 lr: 2.2145384164861444e-05 loss: 0.0950 (0.1047) time: 2.9391 data: 0.0076 max mem: 33301 +Epoch: [23] [3500/4276] eta: 0:37:55 lr: 2.2142504005649447e-05 loss: 0.0932 (0.1047) time: 2.9301 data: 0.0074 max mem: 33301 +Epoch: [23] [3510/4276] eta: 0:37:26 lr: 2.2139623804810937e-05 loss: 0.0919 (0.1047) time: 2.9119 data: 0.0073 max mem: 33301 +Epoch: [23] [3520/4276] eta: 0:36:57 lr: 2.2136743562339297e-05 loss: 0.0909 (0.1047) time: 2.9180 data: 0.0071 max mem: 33301 +Epoch: [23] [3530/4276] eta: 0:36:27 lr: 2.213386327822791e-05 loss: 0.0962 (0.1047) time: 2.9330 data: 0.0069 max mem: 33301 +Epoch: [23] [3540/4276] eta: 0:35:58 lr: 2.2130982952470144e-05 loss: 0.1051 (0.1047) time: 2.9351 data: 0.0070 max mem: 33301 +Epoch: [23] [3550/4276] eta: 0:35:29 lr: 2.2128102585059376e-05 loss: 0.1051 (0.1047) time: 2.9345 data: 0.0069 max mem: 33301 +Epoch: [23] [3560/4276] eta: 0:34:59 lr: 2.2125222175988984e-05 loss: 0.1049 (0.1047) time: 2.9340 data: 0.0069 max mem: 33301 +Epoch: [23] [3570/4276] eta: 0:34:30 lr: 2.212234172525234e-05 loss: 0.1213 (0.1048) time: 2.9347 data: 0.0070 max mem: 33301 +Epoch: [23] [3580/4276] eta: 0:34:01 lr: 2.2119461232842802e-05 loss: 0.0914 (0.1047) time: 2.9350 data: 0.0070 max mem: 33301 +Epoch: [23] [3590/4276] eta: 0:33:31 lr: 2.2116580698753744e-05 loss: 0.0909 (0.1047) time: 2.9349 data: 0.0068 max mem: 33301 +Epoch: [23] [3600/4276] eta: 0:33:02 lr: 2.2113700122978536e-05 loss: 0.1015 (0.1047) time: 2.9336 data: 0.0066 max mem: 33301 +Epoch: [23] [3610/4276] eta: 0:32:33 lr: 2.211081950551054e-05 loss: 0.0985 (0.1048) time: 2.9292 data: 0.0068 max mem: 33301 +Epoch: [23] [3620/4276] eta: 0:32:03 lr: 2.210793884634311e-05 loss: 0.0917 (0.1047) time: 2.9260 data: 0.0070 max mem: 33301 +Epoch: [23] [3630/4276] eta: 0:31:34 lr: 2.2105058145469606e-05 loss: 0.1005 (0.1047) time: 2.9307 data: 0.0068 max mem: 33301 +Epoch: [23] [3640/4276] eta: 0:31:05 lr: 2.2102177402883392e-05 loss: 0.1025 (0.1047) time: 2.9346 data: 0.0068 max mem: 33301 +Epoch: [23] [3650/4276] eta: 0:30:35 lr: 2.2099296618577824e-05 loss: 0.0982 (0.1047) time: 2.9342 data: 0.0069 max mem: 33301 +Epoch: [23] [3660/4276] eta: 0:30:06 lr: 2.209641579254624e-05 loss: 0.0951 (0.1047) time: 2.9336 data: 0.0068 max mem: 33301 +Epoch: [23] [3670/4276] eta: 0:29:37 lr: 2.2093534924782004e-05 loss: 0.0989 (0.1047) time: 2.9335 data: 0.0067 max mem: 33301 +Epoch: [23] [3680/4276] eta: 0:29:07 lr: 2.209065401527846e-05 loss: 0.1079 (0.1047) time: 2.9365 data: 0.0068 max mem: 33301 +Epoch: [23] [3690/4276] eta: 0:28:38 lr: 2.2087773064028967e-05 loss: 0.1117 (0.1047) time: 2.9366 data: 0.0070 max mem: 33301 +Epoch: [23] [3700/4276] eta: 0:28:09 lr: 2.208489207102685e-05 loss: 0.1117 (0.1047) time: 2.9351 data: 0.0072 max mem: 33301 +Epoch: [23] [3710/4276] eta: 0:27:39 lr: 2.2082011036265465e-05 loss: 0.0959 (0.1046) time: 2.9366 data: 0.0071 max mem: 33301 +Epoch: [23] [3720/4276] eta: 0:27:10 lr: 2.2079129959738144e-05 loss: 0.0927 (0.1046) time: 2.9350 data: 0.0072 max mem: 33301 +Epoch: [23] [3730/4276] eta: 0:26:41 lr: 2.2076248841438242e-05 loss: 0.1029 (0.1046) time: 2.9349 data: 0.0072 max mem: 33301 +Epoch: [23] [3740/4276] eta: 0:26:11 lr: 2.2073367681359077e-05 loss: 0.0956 (0.1046) time: 2.9344 data: 0.0072 max mem: 33301 +Epoch: [23] [3750/4276] eta: 0:25:42 lr: 2.2070486479493994e-05 loss: 0.0992 (0.1046) time: 2.9331 data: 0.0073 max mem: 33301 +Epoch: [23] [3760/4276] eta: 0:25:13 lr: 2.2067605235836326e-05 loss: 0.0992 (0.1046) time: 2.9336 data: 0.0073 max mem: 33301 +Epoch: [23] [3770/4276] eta: 0:24:43 lr: 2.20647239503794e-05 loss: 0.0953 (0.1046) time: 2.9346 data: 0.0072 max mem: 33301 +Epoch: [23] [3780/4276] eta: 0:24:14 lr: 2.2061842623116543e-05 loss: 0.0945 (0.1046) time: 2.9354 data: 0.0072 max mem: 33301 +Epoch: [23] [3790/4276] eta: 0:23:45 lr: 2.2058961254041085e-05 loss: 0.0945 (0.1046) time: 2.9367 data: 0.0073 max mem: 33301 +Epoch: [23] [3800/4276] eta: 0:23:16 lr: 2.2056079843146353e-05 loss: 0.0996 (0.1046) time: 2.9371 data: 0.0073 max mem: 33301 +Epoch: [23] [3810/4276] eta: 0:22:46 lr: 2.2053198390425667e-05 loss: 0.0995 (0.1046) time: 2.9358 data: 0.0073 max mem: 33301 +Epoch: [23] [3820/4276] eta: 0:22:17 lr: 2.2050316895872344e-05 loss: 0.0860 (0.1045) time: 2.9356 data: 0.0073 max mem: 33301 +Epoch: [23] [3830/4276] eta: 0:21:48 lr: 2.2047435359479703e-05 loss: 0.0873 (0.1045) time: 2.9374 data: 0.0071 max mem: 33301 +Epoch: [23] [3840/4276] eta: 0:21:18 lr: 2.2044553781241073e-05 loss: 0.1005 (0.1045) time: 2.9384 data: 0.0072 max mem: 33301 +Epoch: [23] [3850/4276] eta: 0:20:49 lr: 2.2041672161149752e-05 loss: 0.0842 (0.1045) time: 2.9386 data: 0.0074 max mem: 33301 +Epoch: [23] [3860/4276] eta: 0:20:20 lr: 2.2038790499199056e-05 loss: 0.0946 (0.1045) time: 2.9384 data: 0.0074 max mem: 33301 +Epoch: [23] [3870/4276] eta: 0:19:50 lr: 2.20359087953823e-05 loss: 0.1051 (0.1045) time: 2.9328 data: 0.0076 max mem: 33301 +Epoch: [23] [3880/4276] eta: 0:19:21 lr: 2.2033027049692802e-05 loss: 0.1008 (0.1045) time: 2.9265 data: 0.0078 max mem: 33301 +Epoch: [23] [3890/4276] eta: 0:18:52 lr: 2.2030145262123843e-05 loss: 0.0972 (0.1045) time: 2.9261 data: 0.0075 max mem: 33301 +Epoch: [23] [3900/4276] eta: 0:18:22 lr: 2.2027263432668743e-05 loss: 0.0969 (0.1045) time: 2.9268 data: 0.0073 max mem: 33301 +Epoch: [23] [3910/4276] eta: 0:17:53 lr: 2.2024381561320803e-05 loss: 0.0872 (0.1044) time: 2.9313 data: 0.0074 max mem: 33301 +Epoch: [23] [3920/4276] eta: 0:17:24 lr: 2.202149964807333e-05 loss: 0.0850 (0.1044) time: 2.9359 data: 0.0075 max mem: 33301 +Epoch: [23] [3930/4276] eta: 0:16:54 lr: 2.2018617692919608e-05 loss: 0.0976 (0.1044) time: 2.9361 data: 0.0074 max mem: 33301 +Epoch: [23] [3940/4276] eta: 0:16:25 lr: 2.2015735695852937e-05 loss: 0.1059 (0.1044) time: 2.9363 data: 0.0073 max mem: 33301 +Epoch: [23] [3950/4276] eta: 0:15:56 lr: 2.2012853656866612e-05 loss: 0.0988 (0.1044) time: 2.9350 data: 0.0073 max mem: 33301 +Epoch: [23] [3960/4276] eta: 0:15:26 lr: 2.2009971575953935e-05 loss: 0.0937 (0.1044) time: 2.9354 data: 0.0073 max mem: 33301 +Epoch: [23] [3970/4276] eta: 0:14:57 lr: 2.200708945310818e-05 loss: 0.0925 (0.1044) time: 2.9357 data: 0.0073 max mem: 33301 +Epoch: [23] [3980/4276] eta: 0:14:28 lr: 2.2004207288322644e-05 loss: 0.0986 (0.1044) time: 2.9352 data: 0.0072 max mem: 33301 +Epoch: [23] [3990/4276] eta: 0:13:58 lr: 2.2001325081590612e-05 loss: 0.0986 (0.1044) time: 2.9351 data: 0.0072 max mem: 33301 +Epoch: [23] [4000/4276] eta: 0:13:29 lr: 2.199844283290537e-05 loss: 0.0949 (0.1044) time: 2.9359 data: 0.0072 max mem: 33301 +Epoch: [23] [4010/4276] eta: 0:13:00 lr: 2.199556054226019e-05 loss: 0.0952 (0.1044) time: 2.9338 data: 0.0074 max mem: 33301 +Epoch: [23] [4020/4276] eta: 0:12:30 lr: 2.199267820964836e-05 loss: 0.1042 (0.1044) time: 2.9347 data: 0.0076 max mem: 33301 +Epoch: [23] [4030/4276] eta: 0:12:01 lr: 2.1989795835063152e-05 loss: 0.0994 (0.1044) time: 2.9376 data: 0.0075 max mem: 33301 +Epoch: [23] [4040/4276] eta: 0:11:32 lr: 2.1986913418497854e-05 loss: 0.1085 (0.1045) time: 2.9372 data: 0.0073 max mem: 33301 +Epoch: [23] [4050/4276] eta: 0:11:02 lr: 2.1984030959945723e-05 loss: 0.1202 (0.1045) time: 2.9353 data: 0.0073 max mem: 33301 +Epoch: [23] [4060/4276] eta: 0:10:33 lr: 2.1981148459400035e-05 loss: 0.1014 (0.1045) time: 2.9416 data: 0.0073 max mem: 33301 +Epoch: [23] [4070/4276] eta: 0:10:04 lr: 2.1978265916854073e-05 loss: 0.1036 (0.1045) time: 2.9427 data: 0.0075 max mem: 33301 +Epoch: [23] [4080/4276] eta: 0:09:34 lr: 2.1975383332301084e-05 loss: 0.1075 (0.1045) time: 2.9363 data: 0.0075 max mem: 33301 +Epoch: [23] [4090/4276] eta: 0:09:05 lr: 2.1972500705734343e-05 loss: 0.1187 (0.1046) time: 2.9372 data: 0.0073 max mem: 33301 +Epoch: [23] 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33301 +Epoch: [23] [4180/4276] eta: 0:04:41 lr: 2.194655517490257e-05 loss: 0.1034 (0.1047) time: 2.9386 data: 0.0078 max mem: 33301 +Epoch: [23] [4190/4276] eta: 0:04:12 lr: 2.1943672127827444e-05 loss: 0.1055 (0.1047) time: 2.9341 data: 0.0071 max mem: 33301 +Epoch: [23] [4200/4276] eta: 0:03:42 lr: 2.194078903866434e-05 loss: 0.1108 (0.1047) time: 2.9285 data: 0.0072 max mem: 33301 +Epoch: [23] [4210/4276] eta: 0:03:13 lr: 2.1937905907406507e-05 loss: 0.1092 (0.1048) time: 2.9280 data: 0.0069 max mem: 33301 +Epoch: [23] [4220/4276] eta: 0:02:44 lr: 2.1935022734047178e-05 loss: 0.1154 (0.1048) time: 2.9319 data: 0.0065 max mem: 33301 +Epoch: [23] [4230/4276] eta: 0:02:14 lr: 2.19321395185796e-05 loss: 0.1186 (0.1048) time: 2.9325 data: 0.0065 max mem: 33301 +Epoch: [23] [4240/4276] eta: 0:01:45 lr: 2.1929256260996994e-05 loss: 0.1092 (0.1048) time: 2.9349 data: 0.0065 max mem: 33301 +Epoch: [23] [4250/4276] eta: 0:01:16 lr: 2.1926372961292597e-05 loss: 0.1092 (0.1049) time: 2.9328 data: 0.0065 max mem: 33301 +Epoch: [23] [4260/4276] eta: 0:00:46 lr: 2.192348961945964e-05 loss: 0.1146 (0.1049) time: 2.9307 data: 0.0067 max mem: 33301 +Epoch: [23] [4270/4276] eta: 0:00:17 lr: 2.192060623549136e-05 loss: 0.1146 (0.1050) time: 2.9309 data: 0.0066 max mem: 33301 +Epoch: [23] Total time: 3:29:01 +Test: [ 0/21770] eta: 8:09:22 time: 1.3487 data: 1.2866 max mem: 33301 +Test: [ 100/21770] eta: 0:18:53 time: 0.0391 data: 0.0009 max mem: 33301 +Test: [ 200/21770] eta: 0:16:26 time: 0.0391 data: 0.0008 max mem: 33301 +Test: [ 300/21770] eta: 0:15:35 time: 0.0392 data: 0.0009 max mem: 33301 +Test: [ 400/21770] eta: 0:15:08 time: 0.0392 data: 0.0009 max mem: 33301 +Test: [ 500/21770] eta: 0:14:50 time: 0.0392 data: 0.0009 max mem: 33301 +Test: [ 600/21770] eta: 0:14:37 time: 0.0394 data: 0.0008 max mem: 33301 +Test: [ 700/21770] eta: 0:14:26 time: 0.0392 data: 0.0008 max mem: 33301 +Test: [ 800/21770] eta: 0:14:17 time: 0.0393 data: 0.0008 max mem: 33301 +Test: [ 900/21770] eta: 0:14:09 time: 0.0393 data: 0.0008 max mem: 33301 +Test: [ 1000/21770] eta: 0:14:02 time: 0.0392 data: 0.0008 max mem: 33301 +Test: [ 1100/21770] eta: 0:13:55 time: 0.0392 data: 0.0008 max mem: 33301 +Test: [ 1200/21770] eta: 0:13:49 time: 0.0393 data: 0.0008 max mem: 33301 +Test: [ 1300/21770] eta: 0:13:43 time: 0.0392 data: 0.0008 max mem: 33301 +Test: [ 1400/21770] eta: 0:13:38 time: 0.0392 data: 0.0008 max mem: 33301 +Test: [ 1500/21770] eta: 0:13:33 time: 0.0392 data: 0.0008 max mem: 33301 +Test: [ 1600/21770] eta: 0:13:28 time: 0.0393 data: 0.0008 max mem: 33301 +Test: [ 1700/21770] eta: 0:13:23 time: 0.0392 data: 0.0008 max mem: 33301 +Test: [ 1800/21770] eta: 0:13:18 time: 0.0393 data: 0.0008 max mem: 33301 +Test: [ 1900/21770] eta: 0:13:13 time: 0.0392 data: 0.0008 max mem: 33301 +Test: [ 2000/21770] eta: 0:13:08 time: 0.0390 data: 0.0008 max mem: 33301 +Test: [ 2100/21770] eta: 0:13:03 time: 0.0389 data: 0.0008 max mem: 33301 +Test: [ 2200/21770] eta: 0:12:59 time: 0.0390 data: 0.0008 max mem: 33301 +Test: [ 2300/21770] eta: 0:12:54 time: 0.0390 data: 0.0008 max mem: 33301 +Test: [ 2400/21770] eta: 0:12:50 time: 0.0397 data: 0.0008 max mem: 33301 +Test: [ 2500/21770] eta: 0:12:46 time: 0.0393 data: 0.0009 max mem: 33301 +Test: [ 2600/21770] eta: 0:12:41 time: 0.0393 data: 0.0008 max mem: 33301 +Test: [ 2700/21770] eta: 0:12:37 time: 0.0394 data: 0.0008 max mem: 33301 +Test: [ 2800/21770] eta: 0:12:33 time: 0.0394 data: 0.0008 max mem: 33301 +Test: [ 2900/21770] eta: 0:12:29 time: 0.0392 data: 0.0008 max mem: 33301 +Test: [ 3000/21770] eta: 0:12:24 time: 0.0389 data: 0.0009 max mem: 33301 +Test: [ 3100/21770] eta: 0:12:20 time: 0.0388 data: 0.0009 max mem: 33301 +Test: [ 3200/21770] eta: 0:12:15 time: 0.0389 data: 0.0009 max mem: 33301 +Test: [ 3300/21770] eta: 0:12:11 time: 0.0389 data: 0.0009 max mem: 33301 +Test: [ 3400/21770] eta: 0:12:06 time: 0.0388 data: 0.0009 max mem: 33301 +Test: [ 3500/21770] eta: 0:12:02 time: 0.0388 data: 0.0009 max mem: 33301 +Test: [ 3600/21770] eta: 0:11:58 time: 0.0385 data: 0.0009 max mem: 33301 +Test: [ 3700/21770] eta: 0:11:53 time: 0.0383 data: 0.0009 max mem: 33301 +Test: [ 3800/21770] eta: 0:11:49 time: 0.0386 data: 0.0009 max mem: 33301 +Test: [ 3900/21770] eta: 0:11:44 time: 0.0380 data: 0.0009 max mem: 33301 +Test: [ 4000/21770] eta: 0:11:40 time: 0.0382 data: 0.0009 max mem: 33301 +Test: [ 4100/21770] eta: 0:11:35 time: 0.0381 data: 0.0009 max mem: 33301 +Test: [ 4200/21770] eta: 0:11:31 time: 0.0382 data: 0.0009 max mem: 33301 +Test: [ 4300/21770] eta: 0:11:26 time: 0.0380 data: 0.0009 max mem: 33301 +Test: [ 4400/21770] eta: 0:11:22 time: 0.0382 data: 0.0009 max mem: 33301 +Test: [ 4500/21770] eta: 0:11:17 time: 0.0381 data: 0.0009 max mem: 33301 +Test: [ 4600/21770] eta: 0:11:13 time: 0.0382 data: 0.0009 max mem: 33301 +Test: [ 4700/21770] eta: 0:11:09 time: 0.0381 data: 0.0009 max mem: 33301 +Test: [ 4800/21770] eta: 0:11:04 time: 0.0381 data: 0.0009 max mem: 33301 +Test: [ 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time: 0.0388 data: 0.0009 max mem: 33301 +Test: [ 6300/21770] eta: 0:10:03 time: 0.0385 data: 0.0009 max mem: 33301 +Test: [ 6400/21770] eta: 0:09:59 time: 0.0390 data: 0.0009 max mem: 33301 +Test: [ 6500/21770] eta: 0:09:55 time: 0.0386 data: 0.0009 max mem: 33301 +Test: [ 6600/21770] eta: 0:09:51 time: 0.0388 data: 0.0009 max mem: 33301 +Test: [ 6700/21770] eta: 0:09:47 time: 0.0389 data: 0.0009 max mem: 33301 +Test: [ 6800/21770] eta: 0:09:43 time: 0.0382 data: 0.0009 max mem: 33301 +Test: [ 6900/21770] eta: 0:09:39 time: 0.0381 data: 0.0009 max mem: 33301 +Test: [ 7000/21770] eta: 0:09:35 time: 0.0382 data: 0.0009 max mem: 33301 +Test: [ 7100/21770] eta: 0:09:31 time: 0.0380 data: 0.0009 max mem: 33301 +Test: [ 7200/21770] eta: 0:09:27 time: 0.0382 data: 0.0009 max mem: 33301 +Test: [ 7300/21770] eta: 0:09:23 time: 0.0380 data: 0.0009 max mem: 33301 +Test: [ 7400/21770] eta: 0:09:19 time: 0.0382 data: 0.0009 max mem: 33301 +Test: [ 7500/21770] eta: 0:09:15 time: 0.0380 data: 0.0009 max mem: 33301 +Test: [ 7600/21770] eta: 0:09:11 time: 0.0381 data: 0.0009 max mem: 33301 +Test: [ 7700/21770] eta: 0:09:07 time: 0.0384 data: 0.0009 max mem: 33301 +Test: [ 7800/21770] eta: 0:09:03 time: 0.0390 data: 0.0009 max mem: 33301 +Test: [ 7900/21770] eta: 0:08:59 time: 0.0391 data: 0.0009 max mem: 33301 +Test: [ 8000/21770] eta: 0:08:55 time: 0.0391 data: 0.0009 max mem: 33301 +Test: [ 8100/21770] eta: 0:08:51 time: 0.0391 data: 0.0009 max mem: 33301 +Test: [ 8200/21770] eta: 0:08:47 time: 0.0389 data: 0.0009 max mem: 33301 +Test: [ 8300/21770] eta: 0:08:43 time: 0.0390 data: 0.0009 max mem: 33301 +Test: [ 8400/21770] eta: 0:08:40 time: 0.0393 data: 0.0009 max mem: 33301 +Test: [ 8500/21770] eta: 0:08:36 time: 0.0399 data: 0.0009 max mem: 33301 +Test: [ 8600/21770] eta: 0:08:32 time: 0.0383 data: 0.0009 max mem: 33301 +Test: [ 8700/21770] eta: 0:08:28 time: 0.0390 data: 0.0009 max mem: 33301 +Test: [ 8800/21770] eta: 0:08:24 time: 0.0389 data: 0.0009 max mem: 33301 +Test: [ 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time: 0.0393 data: 0.0008 max mem: 33301 +Test: [10300/21770] eta: 0:07:26 time: 0.0391 data: 0.0008 max mem: 33301 +Test: [10400/21770] eta: 0:07:22 time: 0.0391 data: 0.0008 max mem: 33301 +Test: [10500/21770] eta: 0:07:18 time: 0.0388 data: 0.0008 max mem: 33301 +Test: [10600/21770] eta: 0:07:14 time: 0.0390 data: 0.0008 max mem: 33301 +Test: [10700/21770] eta: 0:07:10 time: 0.0385 data: 0.0009 max mem: 33301 +Test: [10800/21770] eta: 0:07:06 time: 0.0388 data: 0.0013 max mem: 33301 +Test: [10900/21770] eta: 0:07:03 time: 0.0386 data: 0.0009 max mem: 33301 +Test: [11000/21770] eta: 0:06:59 time: 0.0398 data: 0.0008 max mem: 33301 +Test: [11100/21770] eta: 0:06:55 time: 0.0400 data: 0.0008 max mem: 33301 +Test: [11200/21770] eta: 0:06:51 time: 0.0400 data: 0.0008 max mem: 33301 +Test: [11300/21770] eta: 0:06:47 time: 0.0401 data: 0.0008 max mem: 33301 +Test: [11400/21770] eta: 0:06:44 time: 0.0398 data: 0.0008 max mem: 33301 +Test: [11500/21770] eta: 0:06:40 time: 0.0399 data: 0.0008 max mem: 33301 +Test: [11600/21770] eta: 0:06:36 time: 0.0389 data: 0.0008 max mem: 33301 +Test: [11700/21770] eta: 0:06:32 time: 0.0389 data: 0.0008 max mem: 33301 +Test: [11800/21770] eta: 0:06:28 time: 0.0392 data: 0.0008 max mem: 33301 +Test: [11900/21770] eta: 0:06:24 time: 0.0391 data: 0.0008 max mem: 33301 +Test: [12000/21770] eta: 0:06:20 time: 0.0393 data: 0.0008 max mem: 33301 +Test: [12100/21770] eta: 0:06:16 time: 0.0391 data: 0.0008 max mem: 33301 +Test: [12200/21770] eta: 0:06:13 time: 0.0390 data: 0.0008 max mem: 33301 +Test: [12300/21770] eta: 0:06:09 time: 0.0388 data: 0.0008 max mem: 33301 +Test: [12400/21770] eta: 0:06:05 time: 0.0388 data: 0.0008 max mem: 33301 +Test: [12500/21770] eta: 0:06:01 time: 0.0382 data: 0.0008 max mem: 33301 +Test: [12600/21770] eta: 0:05:57 time: 0.0381 data: 0.0009 max mem: 33301 +Test: [12700/21770] eta: 0:05:53 time: 0.0380 data: 0.0009 max mem: 33301 +Test: [12800/21770] eta: 0:05:49 time: 0.0380 data: 0.0008 max mem: 33301 +Test: [12900/21770] eta: 0:05:45 time: 0.0380 data: 0.0007 max mem: 33301 +Test: [13000/21770] eta: 0:05:41 time: 0.0390 data: 0.0009 max mem: 33301 +Test: [13100/21770] eta: 0:05:37 time: 0.0381 data: 0.0009 max mem: 33301 +Test: [13200/21770] eta: 0:05:33 time: 0.0382 data: 0.0010 max mem: 33301 +Test: [13300/21770] eta: 0:05:29 time: 0.0381 data: 0.0009 max mem: 33301 +Test: [13400/21770] eta: 0:05:25 time: 0.0380 data: 0.0009 max mem: 33301 +Test: [13500/21770] eta: 0:05:21 time: 0.0381 data: 0.0009 max mem: 33301 +Test: [13600/21770] eta: 0:05:17 time: 0.0379 data: 0.0009 max mem: 33301 +Test: [13700/21770] eta: 0:05:14 time: 0.0401 data: 0.0008 max mem: 33301 +Test: [13800/21770] eta: 0:05:10 time: 0.0399 data: 0.0008 max mem: 33301 +Test: [13900/21770] eta: 0:05:06 time: 0.0377 data: 0.0009 max mem: 33301 +Test: [14000/21770] eta: 0:05:02 time: 0.0377 data: 0.0009 max mem: 33301 +Test: [14100/21770] eta: 0:04:58 time: 0.0378 data: 0.0009 max mem: 33301 +Test: [14200/21770] eta: 0:04:54 time: 0.0378 data: 0.0009 max mem: 33301 +Test: [14300/21770] eta: 0:04:50 time: 0.0378 data: 0.0009 max mem: 33301 +Test: [14400/21770] eta: 0:04:46 time: 0.0377 data: 0.0009 max mem: 33301 +Test: [14500/21770] eta: 0:04:42 time: 0.0378 data: 0.0009 max mem: 33301 +Test: [14600/21770] eta: 0:04:38 time: 0.0377 data: 0.0009 max mem: 33301 +Test: [14700/21770] eta: 0:04:34 time: 0.0380 data: 0.0009 max mem: 33301 +Test: [14800/21770] eta: 0:04:30 time: 0.0381 data: 0.0009 max mem: 33301 +Test: [14900/21770] eta: 0:04:26 time: 0.0381 data: 0.0009 max mem: 33301 +Test: [15000/21770] eta: 0:04:22 time: 0.0381 data: 0.0009 max mem: 33301 +Test: [15100/21770] eta: 0:04:19 time: 0.0380 data: 0.0009 max mem: 33301 +Test: [15200/21770] eta: 0:04:15 time: 0.0382 data: 0.0009 max mem: 33301 +Test: [15300/21770] eta: 0:04:11 time: 0.0380 data: 0.0009 max mem: 33301 +Test: [15400/21770] eta: 0:04:07 time: 0.0382 data: 0.0009 max mem: 33301 +Test: [15500/21770] eta: 0:04:03 time: 0.0383 data: 0.0009 max mem: 33301 +Test: [15600/21770] eta: 0:03:59 time: 0.0386 data: 0.0009 max mem: 33301 +Test: [15700/21770] eta: 0:03:55 time: 0.0383 data: 0.0009 max mem: 33301 +Test: [15800/21770] eta: 0:03:51 time: 0.0388 data: 0.0009 max mem: 33301 +Test: [15900/21770] eta: 0:03:47 time: 0.0386 data: 0.0009 max mem: 33301 +Test: [16000/21770] eta: 0:03:43 time: 0.0389 data: 0.0009 max mem: 33301 +Test: [16100/21770] eta: 0:03:40 time: 0.0385 data: 0.0009 max mem: 33301 +Test: [16200/21770] eta: 0:03:36 time: 0.0387 data: 0.0009 max mem: 33301 +Test: [16300/21770] eta: 0:03:32 time: 0.0386 data: 0.0009 max mem: 33301 +Test: [16400/21770] eta: 0:03:28 time: 0.0389 data: 0.0009 max mem: 33301 +Test: [16500/21770] eta: 0:03:24 time: 0.0384 data: 0.0009 max mem: 33301 +Test: [16600/21770] eta: 0:03:20 time: 0.0390 data: 0.0009 max mem: 33301 +Test: [16700/21770] eta: 0:03:16 time: 0.0383 data: 0.0009 max mem: 33301 +Test: [16800/21770] eta: 0:03:12 time: 0.0386 data: 0.0009 max mem: 33301 +Test: [16900/21770] eta: 0:03:08 time: 0.0383 data: 0.0009 max mem: 33301 +Test: [17000/21770] eta: 0:03:05 time: 0.0384 data: 0.0009 max mem: 33301 +Test: [17100/21770] eta: 0:03:01 time: 0.0381 data: 0.0009 max mem: 33301 +Test: [17200/21770] eta: 0:02:57 time: 0.0384 data: 0.0009 max mem: 33301 +Test: [17300/21770] eta: 0:02:53 time: 0.0380 data: 0.0009 max mem: 33301 +Test: [17400/21770] eta: 0:02:49 time: 0.0384 data: 0.0009 max mem: 33301 +Test: [17500/21770] eta: 0:02:45 time: 0.0381 data: 0.0009 max mem: 33301 +Test: [17600/21770] eta: 0:02:41 time: 0.0384 data: 0.0009 max mem: 33301 +Test: [17700/21770] eta: 0:02:37 time: 0.0383 data: 0.0009 max mem: 33301 +Test: [17800/21770] eta: 0:02:33 time: 0.0385 data: 0.0009 max mem: 33301 +Test: [17900/21770] eta: 0:02:30 time: 0.0381 data: 0.0009 max mem: 33301 +Test: [18000/21770] eta: 0:02:26 time: 0.0385 data: 0.0009 max mem: 33301 +Test: [18100/21770] eta: 0:02:22 time: 0.0381 data: 0.0009 max mem: 33301 +Test: [18200/21770] eta: 0:02:18 time: 0.0384 data: 0.0009 max mem: 33301 +Test: [18300/21770] eta: 0:02:14 time: 0.0380 data: 0.0009 max mem: 33301 +Test: [18400/21770] eta: 0:02:10 time: 0.0384 data: 0.0009 max mem: 33301 +Test: [18500/21770] eta: 0:02:06 time: 0.0383 data: 0.0009 max mem: 33301 +Test: [18600/21770] eta: 0:02:02 time: 0.0386 data: 0.0009 max mem: 33301 +Test: [18700/21770] eta: 0:01:58 time: 0.0381 data: 0.0009 max mem: 33301 +Test: [18800/21770] eta: 0:01:55 time: 0.0385 data: 0.0009 max mem: 33301 +Test: [18900/21770] eta: 0:01:51 time: 0.0381 data: 0.0009 max mem: 33301 +Test: [19000/21770] eta: 0:01:47 time: 0.0385 data: 0.0009 max mem: 33301 +Test: [19100/21770] eta: 0:01:43 time: 0.0381 data: 0.0009 max mem: 33301 +Test: [19200/21770] eta: 0:01:39 time: 0.0384 data: 0.0009 max mem: 33301 +Test: [19300/21770] eta: 0:01:35 time: 0.0381 data: 0.0009 max mem: 33301 +Test: [19400/21770] eta: 0:01:31 time: 0.0384 data: 0.0009 max mem: 33301 +Test: [19500/21770] eta: 0:01:27 time: 0.0382 data: 0.0009 max mem: 33301 +Test: [19600/21770] eta: 0:01:24 time: 0.0385 data: 0.0009 max mem: 33301 +Test: [19700/21770] eta: 0:01:20 time: 0.0382 data: 0.0009 max mem: 33301 +Test: [19800/21770] eta: 0:01:16 time: 0.0385 data: 0.0009 max mem: 33301 +Test: [19900/21770] eta: 0:01:12 time: 0.0382 data: 0.0009 max mem: 33301 +Test: [20000/21770] eta: 0:01:08 time: 0.0384 data: 0.0009 max mem: 33301 +Test: [20100/21770] eta: 0:01:04 time: 0.0380 data: 0.0009 max mem: 33301 +Test: [20200/21770] eta: 0:01:00 time: 0.0381 data: 0.0009 max mem: 33301 +Test: [20300/21770] eta: 0:00:56 time: 0.0380 data: 0.0009 max mem: 33301 +Test: [20400/21770] eta: 0:00:53 time: 0.0381 data: 0.0009 max mem: 33301 +Test: [20500/21770] eta: 0:00:49 time: 0.0380 data: 0.0009 max mem: 33301 +Test: [20600/21770] eta: 0:00:45 time: 0.0381 data: 0.0009 max mem: 33301 +Test: [20700/21770] eta: 0:00:41 time: 0.0382 data: 0.0009 max mem: 33301 +Test: [20800/21770] eta: 0:00:37 time: 0.0384 data: 0.0009 max mem: 33301 +Test: [20900/21770] eta: 0:00:33 time: 0.0382 data: 0.0009 max mem: 33301 +Test: [21000/21770] eta: 0:00:29 time: 0.0387 data: 0.0009 max mem: 33301 +Test: [21100/21770] eta: 0:00:25 time: 0.0382 data: 0.0009 max mem: 33301 +Test: [21200/21770] eta: 0:00:22 time: 0.0384 data: 0.0009 max mem: 33301 +Test: [21300/21770] eta: 0:00:18 time: 0.0380 data: 0.0009 max mem: 33301 +Test: [21400/21770] eta: 0:00:14 time: 0.0381 data: 0.0009 max mem: 33301 +Test: [21500/21770] eta: 0:00:10 time: 0.0391 data: 0.0009 max mem: 33301 +Test: [21600/21770] eta: 0:00:06 time: 0.0398 data: 0.0009 max mem: 33301 +Test: [21700/21770] eta: 0:00:02 time: 0.0398 data: 0.0009 max mem: 33301 +Test: Total time: 0:14:02 +Final results: +Mean IoU is 0.68 + + precision@0.5 = 0.00 + precision@0.6 = 0.00 + precision@0.7 = 0.00 + precision@0.8 = 0.00 + precision@0.9 = 0.00 + overall IoU = 0.67 + mean IoU = 0.68 + +Mean accuracy for one-to-zero sample is 0.00 + +Average object IoU 0.006830634277886781 +Overall IoU 0.6675364971160889 +Epoch: [24] [ 0/4276] eta: 6:03:37 lr: 2.191887618488261e-05 loss: 0.0987 (0.0987) time: 5.1023 data: 2.0087 max mem: 33301 +Epoch: [24] [ 10/4276] eta: 3:42:19 lr: 2.1915992733483698e-05 loss: 0.1112 (0.1150) time: 3.1269 data: 0.1895 max mem: 33301 +Epoch: [24] [ 20/4276] eta: 3:35:21 lr: 2.191310923993184e-05 loss: 0.1089 (0.1145) time: 2.9327 data: 0.0071 max mem: 33301 +Epoch: [24] [ 30/4276] eta: 3:32:44 lr: 2.191022570422025e-05 loss: 0.1046 (0.1125) time: 2.9397 data: 0.0072 max mem: 33301 +Epoch: [24] [ 40/4276] eta: 3:31:01 lr: 2.1907342126342155e-05 loss: 0.1005 (0.1113) time: 2.9397 data: 0.0076 max mem: 33301 +Epoch: [24] [ 50/4276] eta: 3:29:45 lr: 2.1904458506290765e-05 loss: 0.1030 (0.1083) time: 2.9347 data: 0.0072 max mem: 33301 +Epoch: [24] [ 60/4276] eta: 3:28:44 lr: 2.1901574844059292e-05 loss: 0.1005 (0.1057) time: 2.9330 data: 0.0069 max mem: 33301 +Epoch: [24] [ 70/4276] eta: 3:27:52 lr: 2.189869113964095e-05 loss: 0.0833 (0.1034) time: 2.9331 data: 0.0068 max mem: 33301 +Epoch: [24] [ 80/4276] eta: 3:27:06 lr: 2.189580739302896e-05 loss: 0.0904 (0.1027) time: 2.9341 data: 0.0069 max mem: 33301 +Epoch: [24] [ 90/4276] eta: 3:26:26 lr: 2.189292360421651e-05 loss: 0.0946 (0.1025) time: 2.9360 data: 0.0068 max mem: 33301 +Epoch: [24] [ 100/4276] eta: 3:25:46 lr: 2.1890039773196823e-05 loss: 0.0946 (0.1034) time: 2.9358 data: 0.0067 max mem: 33301 +Epoch: [24] [ 110/4276] eta: 3:25:08 lr: 2.188715589996309e-05 loss: 0.1121 (0.1055) time: 2.9340 data: 0.0067 max mem: 33301 +Epoch: [24] [ 120/4276] eta: 3:24:34 lr: 2.1884271984508526e-05 loss: 0.1083 (0.1053) time: 2.9380 data: 0.0068 max mem: 33301 +Epoch: [24] [ 130/4276] eta: 3:23:58 lr: 2.188138802682632e-05 loss: 0.1056 (0.1051) time: 2.9371 data: 0.0068 max mem: 33301 +Epoch: [24] [ 140/4276] eta: 3:23:24 lr: 2.187850402690967e-05 loss: 0.0917 (0.1044) time: 2.9339 data: 0.0066 max mem: 33301 +Epoch: [24] [ 150/4276] eta: 3:22:50 lr: 2.1875619984751773e-05 loss: 0.0917 (0.1038) time: 2.9365 data: 0.0067 max mem: 33301 +Epoch: [24] [ 160/4276] eta: 3:22:18 lr: 2.1872735900345835e-05 loss: 0.0954 (0.1034) time: 2.9373 data: 0.0067 max mem: 33301 +Epoch: [24] [ 170/4276] eta: 3:21:44 lr: 2.1869851773685025e-05 loss: 0.0980 (0.1034) time: 2.9355 data: 0.0066 max mem: 33301 +Epoch: [24] [ 180/4276] eta: 3:21:12 lr: 2.1866967604762546e-05 loss: 0.0980 (0.1036) time: 2.9345 data: 0.0066 max mem: 33301 +Epoch: [24] [ 190/4276] eta: 3:20:39 lr: 2.1864083393571585e-05 loss: 0.0916 (0.1033) time: 2.9340 data: 0.0066 max mem: 33301 +Epoch: [24] [ 200/4276] eta: 3:19:58 lr: 2.186119914010532e-05 loss: 0.0883 (0.1024) time: 2.9089 data: 0.0075 max mem: 33301 +Epoch: [24] [ 210/4276] eta: 3:19:17 lr: 2.185831484435694e-05 loss: 0.0962 (0.1024) time: 2.8851 data: 0.0082 max mem: 33301 +Epoch: [24] [ 220/4276] eta: 3:18:45 lr: 2.1855430506319622e-05 loss: 0.0931 (0.1018) time: 2.9055 data: 0.0087 max mem: 33301 +Epoch: [24] [ 230/4276] eta: 3:18:12 lr: 2.185254612598655e-05 loss: 0.0863 (0.1011) time: 2.9250 data: 0.0085 max mem: 33301 +Epoch: [24] [ 240/4276] eta: 3:17:37 lr: 2.1849661703350893e-05 loss: 0.0874 (0.1009) time: 2.9135 data: 0.0073 max mem: 33301 +Epoch: [24] [ 250/4276] eta: 3:17:07 lr: 2.1846777238405832e-05 loss: 0.0984 (0.1016) time: 2.9199 data: 0.0072 max mem: 33301 +Epoch: [24] [ 260/4276] eta: 3:16:38 lr: 2.1843892731144533e-05 loss: 0.0984 (0.1015) time: 2.9388 data: 0.0070 max mem: 33301 +Epoch: [24] [ 270/4276] eta: 3:16:09 lr: 2.1841008181560176e-05 loss: 0.0930 (0.1015) time: 2.9386 data: 0.0068 max mem: 33301 +Epoch: [24] [ 280/4276] eta: 3:15:39 lr: 2.1838123589645916e-05 loss: 0.0839 (0.1013) time: 2.9369 data: 0.0070 max mem: 33301 +Epoch: [24] [ 290/4276] eta: 3:15:09 lr: 2.183523895539493e-05 loss: 0.0906 (0.1015) time: 2.9355 data: 0.0069 max mem: 33301 +Epoch: [24] [ 300/4276] eta: 3:14:40 lr: 2.1832354278800375e-05 loss: 0.0974 (0.1015) time: 2.9355 data: 0.0071 max mem: 33301 +Epoch: [24] [ 310/4276] eta: 3:14:10 lr: 2.1829469559855422e-05 loss: 0.0951 (0.1013) time: 2.9366 data: 0.0071 max mem: 33301 +Epoch: [24] [ 320/4276] eta: 3:13:38 lr: 2.182658479855322e-05 loss: 0.0946 (0.1017) time: 2.9265 data: 0.0071 max mem: 33301 +Epoch: [24] [ 330/4276] eta: 3:13:09 lr: 2.182369999488693e-05 loss: 0.1089 (0.1020) time: 2.9263 data: 0.0070 max mem: 33301 +Epoch: [24] [ 340/4276] eta: 3:12:39 lr: 2.1820815148849707e-05 loss: 0.0991 (0.1018) time: 2.9356 data: 0.0066 max mem: 33301 +Epoch: [24] [ 350/4276] eta: 3:12:10 lr: 2.1817930260434715e-05 loss: 0.0991 (0.1020) time: 2.9371 data: 0.0065 max mem: 33301 +Epoch: [24] [ 360/4276] eta: 3:11:39 lr: 2.181504532963509e-05 loss: 0.1013 (0.1028) time: 2.9281 data: 0.0066 max mem: 33301 +Epoch: [24] [ 370/4276] eta: 3:11:05 lr: 2.1812160356443985e-05 loss: 0.0991 (0.1028) time: 2.9075 data: 0.0075 max mem: 33301 +Epoch: [24] [ 380/4276] eta: 3:10:36 lr: 2.180927534085455e-05 loss: 0.0991 (0.1028) time: 2.9176 data: 0.0074 max mem: 33301 +Epoch: [24] [ 390/4276] eta: 3:10:07 lr: 2.180639028285994e-05 loss: 0.1025 (0.1028) time: 2.9357 data: 0.0064 max mem: 33301 +Epoch: [24] [ 400/4276] eta: 3:09:37 lr: 2.1803505182453278e-05 loss: 0.1010 (0.1029) time: 2.9351 data: 0.0060 max mem: 33301 +Epoch: [24] [ 410/4276] eta: 3:09:10 lr: 2.1800620039627712e-05 loss: 0.1041 (0.1030) time: 2.9469 data: 0.0060 max mem: 33301 +Epoch: [24] [ 420/4276] eta: 3:08:40 lr: 2.1797734854376383e-05 loss: 0.1041 (0.1032) time: 2.9428 data: 0.0063 max mem: 33301 +Epoch: [24] [ 430/4276] eta: 3:08:07 lr: 2.1794849626692435e-05 loss: 0.1049 (0.1035) time: 2.9122 data: 0.0071 max mem: 33301 +Epoch: [24] [ 440/4276] eta: 3:07:38 lr: 2.1791964356568987e-05 loss: 0.1005 (0.1034) time: 2.9160 data: 0.0076 max mem: 33301 +Epoch: [24] [ 450/4276] eta: 3:07:09 lr: 2.1789079043999178e-05 loss: 0.0956 (0.1034) time: 2.9358 data: 0.0071 max mem: 33301 +Epoch: [24] [ 460/4276] eta: 3:06:39 lr: 2.1786193688976144e-05 loss: 0.0956 (0.1031) time: 2.9359 data: 0.0066 max mem: 33301 +Epoch: [24] [ 470/4276] eta: 3:06:10 lr: 2.1783308291493003e-05 loss: 0.0834 (0.1028) time: 2.9374 data: 0.0065 max mem: 33301 +Epoch: [24] [ 480/4276] eta: 3:05:41 lr: 2.1780422851542885e-05 loss: 0.0917 (0.1029) time: 2.9390 data: 0.0065 max mem: 33301 +Epoch: [24] [ 490/4276] eta: 3:05:12 lr: 2.1777537369118917e-05 loss: 0.0984 (0.1028) time: 2.9385 data: 0.0063 max mem: 33301 +Epoch: [24] [ 500/4276] eta: 3:04:43 lr: 2.177465184421422e-05 loss: 0.0925 (0.1027) time: 2.9371 data: 0.0060 max mem: 33301 +Epoch: [24] [ 510/4276] eta: 3:04:13 lr: 2.1771766276821905e-05 loss: 0.0904 (0.1028) time: 2.9328 data: 0.0060 max mem: 33301 +Epoch: [24] [ 520/4276] eta: 3:03:43 lr: 2.1768880666935097e-05 loss: 0.0922 (0.1028) time: 2.9298 data: 0.0060 max mem: 33301 +Epoch: [24] [ 530/4276] eta: 3:03:14 lr: 2.1765995014546908e-05 loss: 0.1004 (0.1027) time: 2.9324 data: 0.0061 max mem: 33301 +Epoch: [24] [ 540/4276] eta: 3:02:44 lr: 2.176310931965046e-05 loss: 0.0950 (0.1026) time: 2.9335 data: 0.0061 max mem: 33301 +Epoch: [24] [ 550/4276] eta: 3:02:15 lr: 2.1760223582238852e-05 loss: 0.0981 (0.1029) time: 2.9306 data: 0.0061 max mem: 33301 +Epoch: [24] [ 560/4276] eta: 3:01:45 lr: 2.1757337802305197e-05 loss: 0.1133 (0.1029) time: 2.9310 data: 0.0061 max mem: 33301 +Epoch: [24] [ 570/4276] eta: 3:01:16 lr: 2.17544519798426e-05 loss: 0.1037 (0.1029) time: 2.9350 data: 0.0061 max mem: 33301 +Epoch: [24] [ 580/4276] eta: 3:00:45 lr: 2.1751566114844173e-05 loss: 0.0959 (0.1030) time: 2.9191 data: 0.0066 max mem: 33301 +Epoch: [24] [ 590/4276] eta: 3:00:16 lr: 2.1748680207303012e-05 loss: 0.0855 (0.1028) time: 2.9230 data: 0.0076 max mem: 33301 +Epoch: [24] [ 600/4276] eta: 2:59:46 lr: 2.1745794257212215e-05 loss: 0.0862 (0.1026) time: 2.9385 data: 0.0073 max mem: 33301 +Epoch: [24] [ 610/4276] eta: 2:59:17 lr: 2.1742908264564883e-05 loss: 0.1005 (0.1026) time: 2.9343 data: 0.0068 max mem: 33301 +Epoch: [24] [ 620/4276] eta: 2:58:48 lr: 2.1740022229354122e-05 loss: 0.0974 (0.1025) time: 2.9338 data: 0.0065 max mem: 33301 +Epoch: [24] [ 630/4276] eta: 2:58:18 lr: 2.173713615157301e-05 loss: 0.0993 (0.1027) time: 2.9321 data: 0.0061 max mem: 33301 +Epoch: [24] [ 640/4276] eta: 2:57:49 lr: 2.173425003121464e-05 loss: 0.1014 (0.1026) time: 2.9329 data: 0.0061 max mem: 33301 +Epoch: [24] [ 650/4276] eta: 2:57:19 lr: 2.173136386827211e-05 loss: 0.0973 (0.1027) time: 2.9337 data: 0.0061 max mem: 33301 +Epoch: [24] [ 660/4276] eta: 2:56:50 lr: 2.1728477662738515e-05 loss: 0.1071 (0.1028) time: 2.9333 data: 0.0061 max mem: 33301 +Epoch: [24] [ 670/4276] eta: 2:56:21 lr: 2.1725591414606916e-05 loss: 0.1087 (0.1029) time: 2.9352 data: 0.0062 max mem: 33301 +Epoch: [24] [ 680/4276] eta: 2:55:51 lr: 2.1722705123870415e-05 loss: 0.1056 (0.1029) time: 2.9360 data: 0.0063 max mem: 33301 +Epoch: [24] [ 690/4276] eta: 2:55:22 lr: 2.1719818790522088e-05 loss: 0.0914 (0.1029) time: 2.9331 data: 0.0061 max mem: 33301 +Epoch: [24] [ 700/4276] eta: 2:54:52 lr: 2.1716932414555014e-05 loss: 0.0914 (0.1029) time: 2.9319 data: 0.0062 max mem: 33301 +Epoch: [24] [ 710/4276] eta: 2:54:23 lr: 2.1714045995962267e-05 loss: 0.0978 (0.1030) time: 2.9327 data: 0.0062 max mem: 33301 +Epoch: [24] [ 720/4276] eta: 2:53:54 lr: 2.1711159534736925e-05 loss: 0.0918 (0.1028) time: 2.9327 data: 0.0062 max mem: 33301 +Epoch: [24] [ 730/4276] eta: 2:53:24 lr: 2.1708273030872057e-05 loss: 0.0953 (0.1027) time: 2.9323 data: 0.0062 max mem: 33301 +Epoch: [24] [ 740/4276] eta: 2:52:55 lr: 2.170538648436074e-05 loss: 0.1002 (0.1027) time: 2.9335 data: 0.0061 max mem: 33301 +Epoch: [24] [ 750/4276] eta: 2:52:26 lr: 2.1702499895196035e-05 loss: 0.0995 (0.1028) time: 2.9340 data: 0.0062 max mem: 33301 +Epoch: [24] [ 760/4276] eta: 2:51:56 lr: 2.169961326337101e-05 loss: 0.0952 (0.1027) time: 2.9326 data: 0.0061 max mem: 33301 +Epoch: [24] [ 770/4276] eta: 2:51:27 lr: 2.1696726588878734e-05 loss: 0.0922 (0.1026) time: 2.9329 data: 0.0062 max mem: 33301 +Epoch: [24] [ 780/4276] eta: 2:50:57 lr: 2.169383987171226e-05 loss: 0.0943 (0.1025) time: 2.9326 data: 0.0061 max mem: 33301 +Epoch: [24] [ 790/4276] eta: 2:50:28 lr: 2.1690953111864654e-05 loss: 0.1003 (0.1030) time: 2.9324 data: 0.0061 max mem: 33301 +Epoch: [24] [ 800/4276] eta: 2:49:58 lr: 2.1688066309328965e-05 loss: 0.1046 (0.1030) time: 2.9323 data: 0.0062 max mem: 33301 +Epoch: [24] [ 810/4276] eta: 2:49:29 lr: 2.1685179464098266e-05 loss: 0.1059 (0.1031) time: 2.9324 data: 0.0062 max mem: 33301 +Epoch: [24] [ 820/4276] eta: 2:49:00 lr: 2.168229257616559e-05 loss: 0.0996 (0.1030) time: 2.9336 data: 0.0061 max mem: 33301 +Epoch: [24] [ 830/4276] eta: 2:48:30 lr: 2.1679405645523994e-05 loss: 0.0999 (0.1030) time: 2.9337 data: 0.0061 max mem: 33301 +Epoch: [24] [ 840/4276] eta: 2:48:01 lr: 2.1676518672166533e-05 loss: 0.1012 (0.1030) time: 2.9332 data: 0.0061 max mem: 33301 +Epoch: [24] [ 850/4276] eta: 2:47:32 lr: 2.1673631656086252e-05 loss: 0.0917 (0.1028) time: 2.9326 data: 0.0062 max mem: 33301 +Epoch: [24] [ 860/4276] eta: 2:47:02 lr: 2.167074459727619e-05 loss: 0.0929 (0.1030) time: 2.9265 data: 0.0062 max mem: 33301 +Epoch: [24] [ 870/4276] eta: 2:46:32 lr: 2.1667857495729392e-05 loss: 0.1004 (0.1029) time: 2.9230 data: 0.0062 max mem: 33301 +Epoch: [24] [ 880/4276] eta: 2:46:03 lr: 2.1664970351438894e-05 loss: 0.1002 (0.1031) time: 2.9295 data: 0.0061 max mem: 33301 +Epoch: [24] [ 890/4276] eta: 2:45:33 lr: 2.166208316439775e-05 loss: 0.1178 (0.1034) time: 2.9327 data: 0.0061 max mem: 33301 +Epoch: [24] [ 900/4276] eta: 2:45:04 lr: 2.1659195934598973e-05 loss: 0.1068 (0.1034) time: 2.9315 data: 0.0061 max mem: 33301 +Epoch: [24] [ 910/4276] eta: 2:44:34 lr: 2.165630866203561e-05 loss: 0.1068 (0.1034) time: 2.9314 data: 0.0061 max mem: 33301 +Epoch: [24] [ 920/4276] eta: 2:44:05 lr: 2.1653421346700688e-05 loss: 0.1081 (0.1035) time: 2.9314 data: 0.0063 max mem: 33301 +Epoch: [24] [ 930/4276] eta: 2:43:36 lr: 2.1650533988587246e-05 loss: 0.1022 (0.1035) time: 2.9378 data: 0.0062 max mem: 33301 +Epoch: [24] [ 940/4276] eta: 2:43:07 lr: 2.1647646587688296e-05 loss: 0.0947 (0.1034) time: 2.9384 data: 0.0063 max mem: 33301 +Epoch: [24] [ 950/4276] eta: 2:42:38 lr: 2.164475914399687e-05 loss: 0.0970 (0.1036) time: 2.9393 data: 0.0064 max mem: 33301 +Epoch: [24] [ 960/4276] eta: 2:42:08 lr: 2.1641871657505992e-05 loss: 0.1079 (0.1036) time: 2.9388 data: 0.0062 max mem: 33301 +Epoch: [24] [ 970/4276] eta: 2:41:37 lr: 2.163898412820869e-05 loss: 0.1027 (0.1036) time: 2.9091 data: 0.0071 max mem: 33301 +Epoch: [24] [ 980/4276] eta: 2:41:08 lr: 2.1636096556097964e-05 loss: 0.1027 (0.1036) time: 2.9096 data: 0.0074 max mem: 33301 +Epoch: [24] [ 990/4276] eta: 2:40:37 lr: 2.1633208941166843e-05 loss: 0.1022 (0.1036) time: 2.9138 data: 0.0070 max mem: 33301 +Epoch: [24] [1000/4276] eta: 2:40:07 lr: 2.1630321283408333e-05 loss: 0.0953 (0.1036) time: 2.9037 data: 0.0072 max mem: 33301 +Epoch: [24] [1010/4276] eta: 2:39:37 lr: 2.1627433582815462e-05 loss: 0.0941 (0.1035) time: 2.9049 data: 0.0078 max mem: 33301 +Epoch: [24] [1020/4276] eta: 2:39:08 lr: 2.162454583938122e-05 loss: 0.0941 (0.1035) time: 2.9195 data: 0.0080 max mem: 33301 +Epoch: [24] [1030/4276] eta: 2:38:39 lr: 2.1621658053098627e-05 loss: 0.1051 (0.1036) time: 2.9372 data: 0.0071 max mem: 33301 +Epoch: [24] [1040/4276] eta: 2:38:09 lr: 2.161877022396068e-05 loss: 0.0970 (0.1035) time: 2.9340 data: 0.0067 max mem: 33301 +Epoch: [24] [1050/4276] eta: 2:37:40 lr: 2.1615882351960396e-05 loss: 0.0954 (0.1036) time: 2.9340 data: 0.0067 max mem: 33301 +Epoch: [24] [1060/4276] eta: 2:37:11 lr: 2.1612994437090758e-05 loss: 0.0977 (0.1036) time: 2.9355 data: 0.0065 max mem: 33301 +Epoch: [24] [1070/4276] eta: 2:36:42 lr: 2.1610106479344776e-05 loss: 0.1112 (0.1038) time: 2.9377 data: 0.0065 max mem: 33301 +Epoch: [24] [1080/4276] eta: 2:36:12 lr: 2.160721847871545e-05 loss: 0.1083 (0.1039) time: 2.9369 data: 0.0068 max mem: 33301 +Epoch: [24] [1090/4276] eta: 2:35:43 lr: 2.160433043519576e-05 loss: 0.1105 (0.1040) time: 2.9339 data: 0.0068 max mem: 33301 +Epoch: [24] [1100/4276] eta: 2:35:14 lr: 2.160144234877871e-05 loss: 0.1093 (0.1041) time: 2.9327 data: 0.0065 max mem: 33301 +Epoch: [24] [1110/4276] eta: 2:34:45 lr: 2.1598554219457283e-05 loss: 0.1081 (0.1042) time: 2.9370 data: 0.0065 max mem: 33301 +Epoch: [24] [1120/4276] eta: 2:34:15 lr: 2.159566604722448e-05 loss: 0.1004 (0.1042) time: 2.9354 data: 0.0066 max mem: 33301 +Epoch: [24] [1130/4276] eta: 2:33:46 lr: 2.159277783207327e-05 loss: 0.0988 (0.1042) time: 2.9318 data: 0.0066 max mem: 33301 +Epoch: [24] [1140/4276] eta: 2:33:17 lr: 2.1589889573996645e-05 loss: 0.1038 (0.1043) time: 2.9311 data: 0.0064 max mem: 33301 +Epoch: [24] [1150/4276] eta: 2:32:47 lr: 2.1587001272987583e-05 loss: 0.1005 (0.1043) time: 2.9295 data: 0.0063 max mem: 33301 +Epoch: [24] [1160/4276] eta: 2:32:18 lr: 2.1584112929039074e-05 loss: 0.0961 (0.1044) time: 2.9314 data: 0.0062 max mem: 33301 +Epoch: [24] [1170/4276] eta: 2:31:48 lr: 2.1581224542144077e-05 loss: 0.1085 (0.1044) time: 2.9168 data: 0.0062 max mem: 33301 +Epoch: [24] [1180/4276] eta: 2:31:17 lr: 2.1578336112295578e-05 loss: 0.1047 (0.1044) time: 2.8914 data: 0.0072 max mem: 33301 +Epoch: [24] [1190/4276] eta: 2:30:48 lr: 2.157544763948655e-05 loss: 0.0883 (0.1043) time: 2.9098 data: 0.0075 max mem: 33301 +Epoch: [24] [1200/4276] eta: 2:30:18 lr: 2.1572559123709964e-05 loss: 0.0994 (0.1044) time: 2.9346 data: 0.0068 max mem: 33301 +Epoch: [24] [1210/4276] eta: 2:29:49 lr: 2.1569670564958778e-05 loss: 0.0994 (0.1043) time: 2.9303 data: 0.0069 max mem: 33301 +Epoch: [24] [1220/4276] eta: 2:29:20 lr: 2.1566781963225962e-05 loss: 0.1038 (0.1043) time: 2.9296 data: 0.0068 max mem: 33301 +Epoch: [24] [1230/4276] eta: 2:28:50 lr: 2.156389331850449e-05 loss: 0.1043 (0.1044) time: 2.9307 data: 0.0068 max mem: 33301 +Epoch: [24] [1240/4276] eta: 2:28:21 lr: 2.1561004630787316e-05 loss: 0.1004 (0.1043) time: 2.9318 data: 0.0069 max mem: 33301 +Epoch: [24] [1250/4276] eta: 2:27:51 lr: 2.1558115900067395e-05 loss: 0.0950 (0.1044) time: 2.9127 data: 0.0068 max mem: 33301 +Epoch: [24] [1260/4276] eta: 2:27:22 lr: 2.1555227126337692e-05 loss: 0.0949 (0.1043) time: 2.9147 data: 0.0068 max mem: 33301 +Epoch: [24] [1270/4276] eta: 2:26:52 lr: 2.1552338309591156e-05 loss: 0.0948 (0.1042) time: 2.9350 data: 0.0070 max mem: 33301 +Epoch: [24] [1280/4276] eta: 2:26:23 lr: 2.1549449449820748e-05 loss: 0.0949 (0.1043) time: 2.9330 data: 0.0072 max mem: 33301 +Epoch: [24] [1290/4276] eta: 2:25:53 lr: 2.1546560547019405e-05 loss: 0.0987 (0.1042) time: 2.9206 data: 0.0069 max mem: 33301 +Epoch: [24] [1300/4276] eta: 2:25:23 lr: 2.1543671601180085e-05 loss: 0.0951 (0.1042) time: 2.9100 data: 0.0068 max mem: 33301 +Epoch: [24] [1310/4276] eta: 2:24:53 lr: 2.1540782612295733e-05 loss: 0.0822 (0.1040) time: 2.9045 data: 0.0073 max mem: 33301 +Epoch: [24] [1320/4276] eta: 2:24:23 lr: 2.1537893580359298e-05 loss: 0.0838 (0.1040) time: 2.8887 data: 0.0072 max mem: 33301 +Epoch: [24] [1330/4276] eta: 2:23:53 lr: 2.153500450536371e-05 loss: 0.0985 (0.1040) time: 2.8931 data: 0.0070 max mem: 33301 +Epoch: [24] [1340/4276] eta: 2:23:24 lr: 2.1532115387301913e-05 loss: 0.0934 (0.1040) time: 2.9314 data: 0.0071 max mem: 33301 +Epoch: [24] [1350/4276] eta: 2:22:55 lr: 2.1529226226166845e-05 loss: 0.1002 (0.1040) time: 2.9460 data: 0.0071 max mem: 33301 +Epoch: [24] [1360/4276] eta: 2:22:26 lr: 2.152633702195145e-05 loss: 0.1077 (0.1040) time: 2.9360 data: 0.0068 max mem: 33301 +Epoch: [24] [1370/4276] eta: 2:21:57 lr: 2.1523447774648645e-05 loss: 0.0962 (0.1039) time: 2.9402 data: 0.0065 max mem: 33301 +Epoch: [24] [1380/4276] eta: 2:21:28 lr: 2.152055848425137e-05 loss: 0.0962 (0.1040) time: 2.9400 data: 0.0064 max mem: 33301 +Epoch: [24] [1390/4276] eta: 2:20:59 lr: 2.1517669150752557e-05 loss: 0.1071 (0.1041) time: 2.9382 data: 0.0062 max mem: 33301 +Epoch: [24] [1400/4276] eta: 2:20:29 lr: 2.151477977414512e-05 loss: 0.1017 (0.1041) time: 2.9385 data: 0.0065 max mem: 33301 +Epoch: [24] [1410/4276] eta: 2:20:00 lr: 2.151189035442199e-05 loss: 0.1010 (0.1041) time: 2.9390 data: 0.0066 max mem: 33301 +Epoch: [24] [1420/4276] eta: 2:19:31 lr: 2.150900089157609e-05 loss: 0.0947 (0.1041) time: 2.9383 data: 0.0064 max mem: 33301 +Epoch: [24] [1430/4276] eta: 2:19:02 lr: 2.1506111385600342e-05 loss: 0.0947 (0.1041) time: 2.9356 data: 0.0065 max mem: 33301 +Epoch: [24] [1440/4276] eta: 2:18:32 lr: 2.1503221836487653e-05 loss: 0.0944 (0.1040) time: 2.9299 data: 0.0065 max mem: 33301 +Epoch: [24] [1450/4276] eta: 2:18:03 lr: 2.1500332244230948e-05 loss: 0.0881 (0.1039) time: 2.9192 data: 0.0068 max mem: 33301 +Epoch: [24] [1460/4276] eta: 2:17:33 lr: 2.1497442608823135e-05 loss: 0.0991 (0.1039) time: 2.9238 data: 0.0065 max mem: 33301 +Epoch: [24] [1470/4276] eta: 2:17:04 lr: 2.149455293025713e-05 loss: 0.1075 (0.1039) time: 2.9340 data: 0.0062 max mem: 33301 +Epoch: [24] [1480/4276] eta: 2:16:35 lr: 2.1491663208525832e-05 loss: 0.1112 (0.1040) time: 2.9348 data: 0.0062 max mem: 33301 +Epoch: [24] [1490/4276] eta: 2:16:06 lr: 2.1488773443622155e-05 loss: 0.0979 (0.1039) time: 2.9357 data: 0.0061 max mem: 33301 +Epoch: [24] [1500/4276] eta: 2:15:37 lr: 2.1485883635539002e-05 loss: 0.0928 (0.1039) time: 2.9369 data: 0.0064 max mem: 33301 +Epoch: [24] [1510/4276] eta: 2:15:07 lr: 2.1482993784269278e-05 loss: 0.1043 (0.1039) time: 2.9364 data: 0.0066 max mem: 33301 +Epoch: [24] [1520/4276] eta: 2:14:38 lr: 2.148010388980587e-05 loss: 0.0942 (0.1038) time: 2.9256 data: 0.0069 max mem: 33301 +Epoch: [24] [1530/4276] eta: 2:14:09 lr: 2.147721395214169e-05 loss: 0.0942 (0.1038) time: 2.9270 data: 0.0068 max mem: 33301 +Epoch: [24] [1540/4276] eta: 2:13:39 lr: 2.1474323971269623e-05 loss: 0.0956 (0.1037) time: 2.9374 data: 0.0065 max mem: 33301 +Epoch: [24] [1550/4276] eta: 2:13:10 lr: 2.147143394718257e-05 loss: 0.0939 (0.1037) time: 2.9360 data: 0.0064 max mem: 33301 +Epoch: [24] [1560/4276] eta: 2:12:41 lr: 2.146854387987341e-05 loss: 0.0925 (0.1036) time: 2.9354 data: 0.0062 max mem: 33301 +Epoch: [24] [1570/4276] eta: 2:12:12 lr: 2.1465653769335044e-05 loss: 0.0908 (0.1036) time: 2.9362 data: 0.0062 max mem: 33301 +Epoch: [24] [1580/4276] eta: 2:11:42 lr: 2.1462763615560347e-05 loss: 0.0881 (0.1035) time: 2.9365 data: 0.0062 max mem: 33301 +Epoch: [24] [1590/4276] eta: 2:11:13 lr: 2.145987341854222e-05 loss: 0.0892 (0.1035) time: 2.9342 data: 0.0062 max mem: 33301 +Epoch: [24] [1600/4276] eta: 2:10:44 lr: 2.145698317827352e-05 loss: 0.1092 (0.1035) time: 2.9318 data: 0.0062 max mem: 33301 +Epoch: [24] [1610/4276] eta: 2:10:14 lr: 2.1454092894747147e-05 loss: 0.1044 (0.1035) time: 2.9319 data: 0.0062 max mem: 33301 +Epoch: [24] [1620/4276] eta: 2:09:45 lr: 2.1451202567955965e-05 loss: 0.0921 (0.1034) time: 2.9321 data: 0.0062 max mem: 33301 +Epoch: [24] [1630/4276] eta: 2:09:16 lr: 2.1448312197892865e-05 loss: 0.0924 (0.1035) time: 2.9330 data: 0.0062 max mem: 33301 +Epoch: [24] [1640/4276] eta: 2:08:46 lr: 2.1445421784550702e-05 loss: 0.1026 (0.1034) time: 2.9304 data: 0.0062 max mem: 33301 +Epoch: [24] [1650/4276] eta: 2:08:17 lr: 2.1442531327922356e-05 loss: 0.0914 (0.1033) time: 2.9301 data: 0.0062 max mem: 33301 +Epoch: [24] [1660/4276] eta: 2:07:48 lr: 2.143964082800069e-05 loss: 0.0914 (0.1033) time: 2.9328 data: 0.0061 max mem: 33301 +Epoch: [24] [1670/4276] eta: 2:07:19 lr: 2.143675028477858e-05 loss: 0.0924 (0.1032) time: 2.9332 data: 0.0062 max mem: 33301 +Epoch: [24] [1680/4276] eta: 2:06:49 lr: 2.143385969824888e-05 loss: 0.0948 (0.1033) time: 2.9322 data: 0.0062 max mem: 33301 +Epoch: [24] [1690/4276] eta: 2:06:20 lr: 2.1430969068404453e-05 loss: 0.0832 (0.1032) time: 2.9318 data: 0.0062 max mem: 33301 +Epoch: [24] [1700/4276] eta: 2:05:51 lr: 2.1428078395238162e-05 loss: 0.0832 (0.1031) time: 2.9482 data: 0.0065 max mem: 33301 +Epoch: [24] [1710/4276] eta: 2:05:22 lr: 2.142518767874286e-05 loss: 0.1021 (0.1031) time: 2.9481 data: 0.0066 max mem: 33301 +Epoch: [24] [1720/4276] eta: 2:04:53 lr: 2.1422296918911407e-05 loss: 0.0994 (0.1031) time: 2.9330 data: 0.0064 max mem: 33301 +Epoch: [24] [1730/4276] eta: 2:04:23 lr: 2.1419406115736644e-05 loss: 0.0928 (0.1030) time: 2.9325 data: 0.0062 max mem: 33301 +Epoch: [24] [1740/4276] eta: 2:03:54 lr: 2.1416515269211443e-05 loss: 0.0965 (0.1031) time: 2.9328 data: 0.0062 max mem: 33301 +Epoch: [24] [1750/4276] eta: 2:03:25 lr: 2.141362437932863e-05 loss: 0.0890 (0.1030) time: 2.9391 data: 0.0062 max mem: 33301 +Epoch: [24] [1760/4276] eta: 2:02:56 lr: 2.1410733446081057e-05 loss: 0.0850 (0.1029) time: 2.9385 data: 0.0063 max mem: 33301 +Epoch: [24] [1770/4276] eta: 2:02:26 lr: 2.1407842469461574e-05 loss: 0.0850 (0.1028) time: 2.9318 data: 0.0062 max mem: 33301 +Epoch: [24] [1780/4276] eta: 2:01:57 lr: 2.140495144946302e-05 loss: 0.0890 (0.1028) time: 2.9237 data: 0.0062 max mem: 33301 +Epoch: [24] [1790/4276] eta: 2:01:27 lr: 2.1402060386078227e-05 loss: 0.0898 (0.1028) time: 2.9241 data: 0.0066 max mem: 33301 +Epoch: [24] [1800/4276] eta: 2:00:58 lr: 2.1399169279300036e-05 loss: 0.0948 (0.1029) time: 2.9324 data: 0.0066 max mem: 33301 +Epoch: [24] [1810/4276] eta: 2:00:29 lr: 2.1396278129121283e-05 loss: 0.1024 (0.1029) time: 2.9315 data: 0.0063 max mem: 33301 +Epoch: [24] [1820/4276] eta: 2:00:00 lr: 2.1393386935534808e-05 loss: 0.1035 (0.1029) time: 2.9331 data: 0.0063 max mem: 33301 +Epoch: [24] [1830/4276] eta: 1:59:30 lr: 2.1390495698533422e-05 loss: 0.0955 (0.1029) time: 2.9339 data: 0.0062 max mem: 33301 +Epoch: [24] [1840/4276] eta: 1:59:01 lr: 2.1387604418109967e-05 loss: 0.0872 (0.1028) time: 2.9324 data: 0.0062 max mem: 33301 +Epoch: [24] [1850/4276] eta: 1:58:32 lr: 2.138471309425726e-05 loss: 0.0892 (0.1028) time: 2.9313 data: 0.0062 max mem: 33301 +Epoch: [24] [1860/4276] eta: 1:58:02 lr: 2.1381821726968138e-05 loss: 0.0989 (0.1027) time: 2.9310 data: 0.0062 max mem: 33301 +Epoch: [24] [1870/4276] eta: 1:57:32 lr: 2.1378930316235406e-05 loss: 0.1013 (0.1027) time: 2.9114 data: 0.0070 max mem: 33301 +Epoch: [24] [1880/4276] eta: 1:57:03 lr: 2.137603886205189e-05 loss: 0.0975 (0.1027) time: 2.9182 data: 0.0073 max mem: 33301 +Epoch: [24] [1890/4276] eta: 1:56:34 lr: 2.1373147364410405e-05 loss: 0.0916 (0.1027) time: 2.9414 data: 0.0068 max mem: 33301 +Epoch: [24] [1900/4276] eta: 1:56:05 lr: 2.137025582330377e-05 loss: 0.0893 (0.1026) time: 2.9327 data: 0.0066 max mem: 33301 +Epoch: [24] [1910/4276] eta: 1:55:35 lr: 2.136736423872479e-05 loss: 0.0968 (0.1026) time: 2.9316 data: 0.0068 max mem: 33301 +Epoch: [24] [1920/4276] eta: 1:55:06 lr: 2.1364472610666274e-05 loss: 0.0986 (0.1025) time: 2.9323 data: 0.0072 max mem: 33301 +Epoch: [24] [1930/4276] eta: 1:54:37 lr: 2.1361580939121035e-05 loss: 0.0825 (0.1025) time: 2.9293 data: 0.0071 max mem: 33301 +Epoch: [24] [1940/4276] eta: 1:54:07 lr: 2.1358689224081878e-05 loss: 0.0893 (0.1025) time: 2.9304 data: 0.0070 max mem: 33301 +Epoch: [24] [1950/4276] eta: 1:53:38 lr: 2.13557974655416e-05 loss: 0.0931 (0.1025) time: 2.9306 data: 0.0068 max mem: 33301 +Epoch: [24] [1960/4276] eta: 1:53:09 lr: 2.1352905663493007e-05 loss: 0.0930 (0.1024) time: 2.9321 data: 0.0068 max mem: 33301 +Epoch: [24] [1970/4276] eta: 1:52:40 lr: 2.1350013817928895e-05 loss: 0.0889 (0.1024) time: 2.9340 data: 0.0069 max mem: 33301 +Epoch: [24] [1980/4276] eta: 1:52:10 lr: 2.134712192884206e-05 loss: 0.0969 (0.1024) time: 2.9361 data: 0.0070 max mem: 33301 +Epoch: [24] [1990/4276] eta: 1:51:41 lr: 2.1344229996225293e-05 loss: 0.0969 (0.1024) time: 2.9356 data: 0.0070 max mem: 33301 +Epoch: [24] [2000/4276] eta: 1:51:12 lr: 2.134133802007139e-05 loss: 0.1036 (0.1024) time: 2.9339 data: 0.0070 max mem: 33301 +Epoch: [24] [2010/4276] eta: 1:50:42 lr: 2.133844600037314e-05 loss: 0.1162 (0.1025) time: 2.9358 data: 0.0070 max mem: 33301 +Epoch: [24] [2020/4276] eta: 1:50:13 lr: 2.133555393712332e-05 loss: 0.1188 (0.1025) time: 2.9337 data: 0.0070 max mem: 33301 +Epoch: [24] [2030/4276] eta: 1:49:44 lr: 2.1332661830314733e-05 loss: 0.0906 (0.1025) time: 2.9337 data: 0.0071 max mem: 33301 +Epoch: [24] [2040/4276] eta: 1:49:15 lr: 2.1329769679940142e-05 loss: 0.0826 (0.1024) time: 2.9358 data: 0.0070 max mem: 33301 +Epoch: [24] [2050/4276] eta: 1:48:45 lr: 2.132687748599234e-05 loss: 0.0985 (0.1025) time: 2.9367 data: 0.0070 max mem: 33301 +Epoch: [24] [2060/4276] eta: 1:48:16 lr: 2.13239852484641e-05 loss: 0.0912 (0.1024) time: 2.9363 data: 0.0069 max mem: 33301 +Epoch: [24] [2070/4276] eta: 1:47:47 lr: 2.1321092967348197e-05 loss: 0.0879 (0.1024) time: 2.9345 data: 0.0069 max mem: 33301 +Epoch: [24] [2080/4276] eta: 1:47:17 lr: 2.13182006426374e-05 loss: 0.0934 (0.1025) time: 2.9346 data: 0.0070 max mem: 33301 +Epoch: [24] [2090/4276] eta: 1:46:48 lr: 2.1315308274324496e-05 loss: 0.1084 (0.1025) time: 2.9354 data: 0.0069 max mem: 33301 +Epoch: [24] [2100/4276] eta: 1:46:19 lr: 2.1312415862402232e-05 loss: 0.0913 (0.1025) time: 2.9368 data: 0.0069 max mem: 33301 +Epoch: [24] [2110/4276] eta: 1:45:50 lr: 2.130952340686339e-05 loss: 0.0913 (0.1025) time: 2.9378 data: 0.0069 max mem: 33301 +Epoch: [24] [2120/4276] eta: 1:45:21 lr: 2.1306630907700722e-05 loss: 0.0840 (0.1023) time: 2.9459 data: 0.0070 max mem: 33301 +Epoch: [24] [2130/4276] eta: 1:44:51 lr: 2.1303738364907006e-05 loss: 0.0821 (0.1023) time: 2.9448 data: 0.0071 max mem: 33301 +Epoch: [24] [2140/4276] eta: 1:44:22 lr: 2.1300845778474982e-05 loss: 0.0865 (0.1022) time: 2.9365 data: 0.0071 max mem: 33301 +Epoch: [24] [2150/4276] eta: 1:43:53 lr: 2.1297953148397418e-05 loss: 0.0916 (0.1022) time: 2.9348 data: 0.0069 max mem: 33301 +Epoch: [24] [2160/4276] eta: 1:43:23 lr: 2.1295060474667068e-05 loss: 0.0925 (0.1022) time: 2.9353 data: 0.0069 max mem: 33301 +Epoch: [24] [2170/4276] eta: 1:42:54 lr: 2.129216775727669e-05 loss: 0.0986 (0.1022) time: 2.9371 data: 0.0069 max mem: 33301 +Epoch: [24] [2180/4276] eta: 1:42:25 lr: 2.1289274996219022e-05 loss: 0.1009 (0.1022) time: 2.9353 data: 0.0070 max mem: 33301 +Epoch: [24] [2190/4276] eta: 1:41:56 lr: 2.1286382191486818e-05 loss: 0.1048 (0.1022) time: 2.9347 data: 0.0070 max mem: 33301 +Epoch: [24] [2200/4276] eta: 1:41:26 lr: 2.128348934307282e-05 loss: 0.1090 (0.1022) time: 2.9387 data: 0.0069 max mem: 33301 +Epoch: [24] [2210/4276] eta: 1:40:57 lr: 2.1280596450969784e-05 loss: 0.1119 (0.1022) time: 2.9375 data: 0.0069 max mem: 33301 +Epoch: [24] [2220/4276] eta: 1:40:28 lr: 2.1277703515170432e-05 loss: 0.1095 (0.1023) time: 2.9339 data: 0.0070 max mem: 33301 +Epoch: [24] [2230/4276] eta: 1:39:59 lr: 2.1274810535667518e-05 loss: 0.1090 (0.1023) time: 2.9348 data: 0.0070 max mem: 33301 +Epoch: [24] [2240/4276] eta: 1:39:29 lr: 2.127191751245377e-05 loss: 0.0891 (0.1022) time: 2.9353 data: 0.0070 max mem: 33301 +Epoch: [24] [2250/4276] eta: 1:39:00 lr: 2.126902444552193e-05 loss: 0.0891 (0.1022) time: 2.9340 data: 0.0071 max mem: 33301 +Epoch: [24] [2260/4276] eta: 1:38:31 lr: 2.126613133486472e-05 loss: 0.0991 (0.1022) time: 2.9333 data: 0.0068 max mem: 33301 +Epoch: [24] [2270/4276] eta: 1:38:01 lr: 2.126323818047487e-05 loss: 0.0931 (0.1022) time: 2.9328 data: 0.0068 max mem: 33301 +Epoch: [24] [2280/4276] eta: 1:37:32 lr: 2.1260344982345116e-05 loss: 0.0931 (0.1022) time: 2.9314 data: 0.0069 max mem: 33301 +Epoch: [24] [2290/4276] eta: 1:37:03 lr: 2.1257451740468183e-05 loss: 0.1025 (0.1022) time: 2.9314 data: 0.0070 max mem: 33301 +Epoch: [24] [2300/4276] eta: 1:36:33 lr: 2.125455845483678e-05 loss: 0.0889 (0.1022) time: 2.9337 data: 0.0070 max mem: 33301 +Epoch: [24] [2310/4276] eta: 1:36:04 lr: 2.1251665125443638e-05 loss: 0.1071 (0.1023) time: 2.9351 data: 0.0070 max mem: 33301 +Epoch: [24] [2320/4276] eta: 1:35:35 lr: 2.1248771752281476e-05 loss: 0.1091 (0.1023) time: 2.9274 data: 0.0073 max mem: 33301 +Epoch: [24] [2330/4276] eta: 1:35:05 lr: 2.1245878335343003e-05 loss: 0.1048 (0.1023) time: 2.9272 data: 0.0073 max mem: 33301 +Epoch: [24] [2340/4276] eta: 1:34:36 lr: 2.1242984874620935e-05 loss: 0.1137 (0.1024) time: 2.9334 data: 0.0069 max mem: 33301 +Epoch: [24] [2350/4276] eta: 1:34:07 lr: 2.1240091370107986e-05 loss: 0.1107 (0.1024) time: 2.9322 data: 0.0070 max mem: 33301 +Epoch: [24] [2360/4276] eta: 1:33:37 lr: 2.1237197821796863e-05 loss: 0.1000 (0.1024) time: 2.9340 data: 0.0072 max mem: 33301 +Epoch: [24] [2370/4276] eta: 1:33:08 lr: 2.123430422968027e-05 loss: 0.1046 (0.1025) time: 2.9352 data: 0.0072 max mem: 33301 +Epoch: [24] [2380/4276] eta: 1:32:39 lr: 2.1231410593750908e-05 loss: 0.1088 (0.1025) time: 2.9328 data: 0.0069 max mem: 33301 +Epoch: [24] [2390/4276] eta: 1:32:09 lr: 2.1228516914001485e-05 loss: 0.0996 (0.1025) time: 2.9322 data: 0.0069 max mem: 33301 +Epoch: [24] [2400/4276] eta: 1:31:40 lr: 2.1225623190424708e-05 loss: 0.1068 (0.1026) time: 2.9333 data: 0.0070 max mem: 33301 +Epoch: [24] [2410/4276] eta: 1:31:11 lr: 2.1222729423013253e-05 loss: 0.1172 (0.1026) time: 2.9353 data: 0.0069 max mem: 33301 +Epoch: [24] [2420/4276] eta: 1:30:42 lr: 2.1219835611759828e-05 loss: 0.0974 (0.1026) time: 2.9358 data: 0.0069 max mem: 33301 +Epoch: [24] [2430/4276] eta: 1:30:12 lr: 2.1216941756657126e-05 loss: 0.1028 (0.1027) time: 2.9351 data: 0.0069 max mem: 33301 +Epoch: [24] [2440/4276] eta: 1:29:43 lr: 2.121404785769784e-05 loss: 0.1077 (0.1027) time: 2.9341 data: 0.0069 max mem: 33301 +Epoch: [24] [2450/4276] eta: 1:29:14 lr: 2.1211153914874644e-05 loss: 0.1014 (0.1027) time: 2.9325 data: 0.0069 max mem: 33301 +Epoch: [24] [2460/4276] eta: 1:28:44 lr: 2.120825992818023e-05 loss: 0.1008 (0.1027) time: 2.9311 data: 0.0070 max mem: 33301 +Epoch: [24] [2470/4276] eta: 1:28:15 lr: 2.1205365897607292e-05 loss: 0.1008 (0.1027) time: 2.9319 data: 0.0070 max mem: 33301 +Epoch: [24] [2480/4276] eta: 1:27:46 lr: 2.12024718231485e-05 loss: 0.1113 (0.1028) time: 2.9323 data: 0.0070 max mem: 33301 +Epoch: [24] [2490/4276] eta: 1:27:16 lr: 2.1199577704796532e-05 loss: 0.1071 (0.1028) time: 2.9324 data: 0.0070 max mem: 33301 +Epoch: [24] [2500/4276] eta: 1:26:47 lr: 2.1196683542544064e-05 loss: 0.0987 (0.1028) time: 2.9316 data: 0.0069 max mem: 33301 +Epoch: [24] [2510/4276] eta: 1:26:18 lr: 2.119378933638377e-05 loss: 0.1000 (0.1028) time: 2.9314 data: 0.0069 max mem: 33301 +Epoch: [24] [2520/4276] eta: 1:25:48 lr: 2.119089508630833e-05 loss: 0.1000 (0.1028) time: 2.9320 data: 0.0069 max mem: 33301 +Epoch: [24] [2530/4276] eta: 1:25:19 lr: 2.1188000792310405e-05 loss: 0.0887 (0.1027) time: 2.9342 data: 0.0069 max mem: 33301 +Epoch: [24] [2540/4276] eta: 1:24:50 lr: 2.118510645438266e-05 loss: 0.0897 (0.1028) time: 2.9350 data: 0.0070 max mem: 33301 +Epoch: [24] [2550/4276] eta: 1:24:20 lr: 2.1182212072517765e-05 loss: 0.0973 (0.1027) time: 2.9325 data: 0.0070 max mem: 33301 +Epoch: [24] [2560/4276] eta: 1:23:51 lr: 2.1179317646708387e-05 loss: 0.0872 (0.1027) time: 2.9315 data: 0.0069 max mem: 33301 +Epoch: [24] [2570/4276] eta: 1:23:22 lr: 2.117642317694717e-05 loss: 0.0872 (0.1027) time: 2.9307 data: 0.0068 max mem: 33301 +Epoch: [24] [2580/4276] eta: 1:22:52 lr: 2.1173528663226777e-05 loss: 0.0895 (0.1026) time: 2.9313 data: 0.0069 max mem: 33301 +Epoch: [24] [2590/4276] eta: 1:22:23 lr: 2.1170634105539868e-05 loss: 0.0889 (0.1026) time: 2.9329 data: 0.0070 max mem: 33301 +Epoch: [24] [2600/4276] eta: 1:21:54 lr: 2.11677395038791e-05 loss: 0.0870 (0.1025) time: 2.9341 data: 0.0070 max mem: 33301 +Epoch: [24] [2610/4276] eta: 1:21:25 lr: 2.116484485823711e-05 loss: 0.0869 (0.1025) time: 2.9359 data: 0.0070 max mem: 33301 +Epoch: [24] [2620/4276] eta: 1:20:55 lr: 2.1161950168606558e-05 loss: 0.0869 (0.1025) time: 2.9421 data: 0.0071 max mem: 33301 +Epoch: [24] [2630/4276] eta: 1:20:26 lr: 2.1159055434980088e-05 loss: 0.0905 (0.1024) time: 2.9421 data: 0.0071 max mem: 33301 +Epoch: [24] [2640/4276] eta: 1:19:57 lr: 2.1156160657350334e-05 loss: 0.0848 (0.1024) time: 2.9416 data: 0.0070 max mem: 33301 +Epoch: [24] [2650/4276] eta: 1:19:27 lr: 2.115326583570994e-05 loss: 0.0905 (0.1024) time: 2.9406 data: 0.0070 max mem: 33301 +Epoch: [24] [2660/4276] eta: 1:18:58 lr: 2.115037097005155e-05 loss: 0.0918 (0.1024) time: 2.9361 data: 0.0070 max mem: 33301 +Epoch: [24] [2670/4276] eta: 1:18:29 lr: 2.1147476060367806e-05 loss: 0.0978 (0.1024) time: 2.9349 data: 0.0069 max mem: 33301 +Epoch: [24] [2680/4276] eta: 1:18:00 lr: 2.1144581106651323e-05 loss: 0.1022 (0.1024) time: 2.9344 data: 0.0069 max mem: 33301 +Epoch: [24] [2690/4276] eta: 1:17:30 lr: 2.114168610889475e-05 loss: 0.0997 (0.1024) time: 2.9352 data: 0.0070 max mem: 33301 +Epoch: [24] [2700/4276] eta: 1:17:01 lr: 2.1138791067090702e-05 loss: 0.0933 (0.1024) time: 2.9367 data: 0.0070 max mem: 33301 +Epoch: [24] [2710/4276] eta: 1:16:32 lr: 2.1135895981231825e-05 loss: 0.0923 (0.1024) time: 2.9380 data: 0.0071 max mem: 33301 +Epoch: [24] [2720/4276] eta: 1:16:02 lr: 2.1133000851310724e-05 loss: 0.0915 (0.1024) time: 2.9385 data: 0.0071 max mem: 33301 +Epoch: [24] [2730/4276] eta: 1:15:33 lr: 2.1130105677320027e-05 loss: 0.0948 (0.1024) time: 2.9365 data: 0.0071 max mem: 33301 +Epoch: [24] [2740/4276] eta: 1:15:04 lr: 2.112721045925236e-05 loss: 0.1056 (0.1024) time: 2.9341 data: 0.0070 max mem: 33301 +Epoch: [24] [2750/4276] eta: 1:14:34 lr: 2.1124315197100343e-05 loss: 0.1056 (0.1024) time: 2.9225 data: 0.0069 max mem: 33301 +Epoch: [24] [2760/4276] eta: 1:14:05 lr: 2.1121419890856575e-05 loss: 0.0982 (0.1023) time: 2.9235 data: 0.0070 max mem: 33301 +Epoch: [24] [2770/4276] eta: 1:13:36 lr: 2.111852454051368e-05 loss: 0.0924 (0.1023) time: 2.9354 data: 0.0070 max mem: 33301 +Epoch: [24] [2780/4276] eta: 1:13:06 lr: 2.1115629146064263e-05 loss: 0.0924 (0.1023) time: 2.9353 data: 0.0070 max mem: 33301 +Epoch: [24] [2790/4276] eta: 1:12:37 lr: 2.1112733707500944e-05 loss: 0.1053 (0.1024) time: 2.9334 data: 0.0070 max mem: 33301 +Epoch: [24] [2800/4276] eta: 1:12:08 lr: 2.1109838224816317e-05 loss: 0.0937 (0.1023) time: 2.9326 data: 0.0069 max mem: 33301 +Epoch: [24] [2810/4276] eta: 1:11:38 lr: 2.1106942698002987e-05 loss: 0.0764 (0.1022) time: 2.9142 data: 0.0070 max mem: 33301 +Epoch: [24] [2820/4276] eta: 1:11:09 lr: 2.110404712705355e-05 loss: 0.0753 (0.1022) time: 2.9143 data: 0.0073 max mem: 33301 +Epoch: [24] [2830/4276] eta: 1:10:40 lr: 2.1101151511960625e-05 loss: 0.0898 (0.1022) time: 2.9336 data: 0.0072 max mem: 33301 +Epoch: [24] [2840/4276] eta: 1:10:10 lr: 2.1098255852716783e-05 loss: 0.1013 (0.1022) time: 2.9299 data: 0.0065 max mem: 33301 +Epoch: [24] [2850/4276] eta: 1:09:41 lr: 2.109536014931463e-05 loss: 0.1218 (0.1023) time: 2.9280 data: 0.0065 max mem: 33301 +Epoch: [24] [2860/4276] eta: 1:09:12 lr: 2.1092464401746758e-05 loss: 0.1013 (0.1023) time: 2.9310 data: 0.0068 max mem: 33301 +Epoch: [24] [2870/4276] eta: 1:08:42 lr: 2.1089568610005757e-05 loss: 0.0927 (0.1023) time: 2.9297 data: 0.0067 max mem: 33301 +Epoch: [24] [2880/4276] eta: 1:08:13 lr: 2.1086672774084206e-05 loss: 0.0988 (0.1023) time: 2.9253 data: 0.0066 max mem: 33301 +Epoch: [24] [2890/4276] eta: 1:07:43 lr: 2.1083776893974694e-05 loss: 0.0986 (0.1023) time: 2.9236 data: 0.0065 max mem: 33301 +Epoch: [24] [2900/4276] eta: 1:07:14 lr: 2.10808809696698e-05 loss: 0.0956 (0.1023) time: 2.9222 data: 0.0066 max mem: 33301 +Epoch: [24] [2910/4276] eta: 1:06:45 lr: 2.107798500116212e-05 loss: 0.0978 (0.1023) time: 2.9202 data: 0.0066 max mem: 33301 +Epoch: [24] [2920/4276] eta: 1:06:15 lr: 2.1075088988444205e-05 loss: 0.0914 (0.1023) time: 2.9221 data: 0.0064 max mem: 33301 +Epoch: [24] [2930/4276] eta: 1:05:46 lr: 2.1072192931508644e-05 loss: 0.0989 (0.1023) time: 2.9253 data: 0.0065 max mem: 33301 +Epoch: [24] [2940/4276] eta: 1:05:17 lr: 2.1069296830348012e-05 loss: 0.1024 (0.1023) time: 2.9211 data: 0.0069 max mem: 33301 +Epoch: [24] [2950/4276] eta: 1:04:47 lr: 2.1066400684954872e-05 loss: 0.1029 (0.1023) time: 2.9216 data: 0.0069 max mem: 33301 +Epoch: [24] [2960/4276] eta: 1:04:18 lr: 2.106350449532179e-05 loss: 0.0931 (0.1023) time: 2.9109 data: 0.0072 max mem: 33301 +Epoch: [24] [2970/4276] eta: 1:03:48 lr: 2.106060826144134e-05 loss: 0.0939 (0.1024) time: 2.8991 data: 0.0075 max mem: 33301 +Epoch: [24] [2980/4276] eta: 1:03:19 lr: 2.1057711983306085e-05 loss: 0.1021 (0.1024) time: 2.9130 data: 0.0070 max mem: 33301 +Epoch: [24] [2990/4276] eta: 1:02:50 lr: 2.105481566090857e-05 loss: 0.0979 (0.1023) time: 2.9244 data: 0.0067 max mem: 33301 +Epoch: [24] [3000/4276] eta: 1:02:20 lr: 2.105191929424137e-05 loss: 0.0893 (0.1023) time: 2.9150 data: 0.0070 max mem: 33301 +Epoch: [24] [3010/4276] eta: 1:01:51 lr: 2.104902288329703e-05 loss: 0.0905 (0.1023) time: 2.8973 data: 0.0074 max mem: 33301 +Epoch: [24] [3020/4276] eta: 1:01:21 lr: 2.1046126428068116e-05 loss: 0.0972 (0.1022) time: 2.9074 data: 0.0075 max mem: 33301 +Epoch: [24] [3030/4276] eta: 1:00:52 lr: 2.1043229928547168e-05 loss: 0.1073 (0.1023) time: 2.9239 data: 0.0070 max mem: 33301 +Epoch: [24] [3040/4276] eta: 1:00:23 lr: 2.104033338472673e-05 loss: 0.1091 (0.1023) time: 2.9221 data: 0.0066 max mem: 33301 +Epoch: [24] [3050/4276] eta: 0:59:53 lr: 2.103743679659936e-05 loss: 0.0989 (0.1023) time: 2.9148 data: 0.0072 max mem: 33301 +Epoch: [24] [3060/4276] eta: 0:59:24 lr: 2.1034540164157604e-05 loss: 0.0817 (0.1022) time: 2.9159 data: 0.0074 max mem: 33301 +Epoch: [24] [3070/4276] eta: 0:58:55 lr: 2.1031643487393987e-05 loss: 0.0817 (0.1022) time: 2.9231 data: 0.0073 max mem: 33301 +Epoch: [24] [3080/4276] eta: 0:58:25 lr: 2.102874676630106e-05 loss: 0.0917 (0.1022) time: 2.9148 data: 0.0071 max mem: 33301 +Epoch: [24] [3090/4276] eta: 0:57:56 lr: 2.1025850000871354e-05 loss: 0.0870 (0.1022) time: 2.9155 data: 0.0068 max mem: 33301 +Epoch: [24] [3100/4276] eta: 0:57:27 lr: 2.1022953191097412e-05 loss: 0.0870 (0.1021) time: 2.9249 data: 0.0068 max mem: 33301 +Epoch: [24] [3110/4276] eta: 0:56:57 lr: 2.1020056336971758e-05 loss: 0.0832 (0.1021) time: 2.9152 data: 0.0073 max mem: 33301 +Epoch: [24] [3120/4276] eta: 0:56:28 lr: 2.101715943848692e-05 loss: 0.0822 (0.1020) time: 2.9171 data: 0.0074 max mem: 33301 +Epoch: [24] [3130/4276] eta: 0:55:58 lr: 2.101426249563543e-05 loss: 0.0922 (0.1020) time: 2.9314 data: 0.0068 max mem: 33301 +Epoch: [24] [3140/4276] eta: 0:55:29 lr: 2.1011365508409813e-05 loss: 0.0937 (0.1020) time: 2.9293 data: 0.0067 max mem: 33301 +Epoch: [24] [3150/4276] eta: 0:55:00 lr: 2.1008468476802584e-05 loss: 0.0909 (0.1020) time: 2.9259 data: 0.0068 max mem: 33301 +Epoch: [24] [3160/4276] eta: 0:54:31 lr: 2.100557140080627e-05 loss: 0.0910 (0.1020) time: 2.9271 data: 0.0068 max mem: 33301 +Epoch: [24] [3170/4276] eta: 0:54:01 lr: 2.100267428041338e-05 loss: 0.0919 (0.1020) time: 2.9261 data: 0.0068 max mem: 33301 +Epoch: [24] [3180/4276] eta: 0:53:32 lr: 2.0999777115616442e-05 loss: 0.0925 (0.1019) time: 2.9215 data: 0.0068 max mem: 33301 +Epoch: [24] [3190/4276] eta: 0:53:02 lr: 2.0996879906407956e-05 loss: 0.1004 (0.1019) time: 2.9220 data: 0.0068 max mem: 33301 +Epoch: [24] [3200/4276] eta: 0:52:33 lr: 2.099398265278044e-05 loss: 0.1000 (0.1019) time: 2.9239 data: 0.0065 max mem: 33301 +Epoch: [24] [3210/4276] eta: 0:52:04 lr: 2.09910853547264e-05 loss: 0.0946 (0.1020) time: 2.9219 data: 0.0065 max mem: 33301 +Epoch: [24] [3220/4276] eta: 0:51:34 lr: 2.0988188012238336e-05 loss: 0.0999 (0.1020) time: 2.9224 data: 0.0067 max mem: 33301 +Epoch: [24] [3230/4276] eta: 0:51:05 lr: 2.0985290625308754e-05 loss: 0.0917 (0.1019) time: 2.9226 data: 0.0067 max mem: 33301 +Epoch: [24] [3240/4276] eta: 0:50:36 lr: 2.0982393193930157e-05 loss: 0.0931 (0.1020) time: 2.9233 data: 0.0066 max mem: 33301 +Epoch: [24] [3250/4276] eta: 0:50:06 lr: 2.0979495718095045e-05 loss: 0.1088 (0.1020) time: 2.9245 data: 0.0067 max mem: 33301 +Epoch: [24] [3260/4276] eta: 0:49:37 lr: 2.09765981977959e-05 loss: 0.0996 (0.1019) time: 2.9261 data: 0.0067 max mem: 33301 +Epoch: [24] [3270/4276] eta: 0:49:08 lr: 2.097370063302523e-05 loss: 0.0996 (0.1020) time: 2.9286 data: 0.0068 max mem: 33301 +Epoch: [24] [3280/4276] eta: 0:48:39 lr: 2.0970803023775524e-05 loss: 0.1072 (0.1020) time: 2.9240 data: 0.0068 max mem: 33301 +Epoch: [24] [3290/4276] eta: 0:48:09 lr: 2.096790537003927e-05 loss: 0.1072 (0.1020) time: 2.9230 data: 0.0067 max mem: 33301 +Epoch: [24] [3300/4276] eta: 0:47:40 lr: 2.0965007671808938e-05 loss: 0.1080 (0.1021) time: 2.9270 data: 0.0067 max mem: 33301 +Epoch: [24] [3310/4276] eta: 0:47:11 lr: 2.096210992907703e-05 loss: 0.1109 (0.1021) time: 2.9279 data: 0.0067 max mem: 33301 +Epoch: [24] [3320/4276] eta: 0:46:41 lr: 2.0959212141836023e-05 loss: 0.1093 (0.1022) time: 2.9282 data: 0.0066 max mem: 33301 +Epoch: [24] [3330/4276] eta: 0:46:12 lr: 2.09563143100784e-05 loss: 0.0982 (0.1021) time: 2.9265 data: 0.0066 max mem: 33301 +Epoch: [24] [3340/4276] eta: 0:45:43 lr: 2.095341643379662e-05 loss: 0.0917 (0.1021) time: 2.9260 data: 0.0067 max mem: 33301 +Epoch: [24] [3350/4276] eta: 0:45:13 lr: 2.095051851298317e-05 loss: 0.0848 (0.1021) time: 2.9224 data: 0.0068 max mem: 33301 +Epoch: [24] [3360/4276] eta: 0:44:44 lr: 2.094762054763052e-05 loss: 0.0923 (0.1021) time: 2.9231 data: 0.0068 max mem: 33301 +Epoch: [24] [3370/4276] eta: 0:44:15 lr: 2.0944722537731145e-05 loss: 0.1049 (0.1021) time: 2.9272 data: 0.0067 max mem: 33301 +Epoch: [24] [3380/4276] eta: 0:43:45 lr: 2.09418244832775e-05 loss: 0.1037 (0.1021) time: 2.9195 data: 0.0066 max mem: 33301 +Epoch: [24] [3390/4276] eta: 0:43:16 lr: 2.093892638426205e-05 loss: 0.0939 (0.1021) time: 2.9120 data: 0.0067 max mem: 33301 +Epoch: [24] [3400/4276] eta: 0:42:47 lr: 2.0936028240677264e-05 loss: 0.0999 (0.1022) time: 2.9202 data: 0.0066 max mem: 33301 +Epoch: [24] [3410/4276] eta: 0:42:17 lr: 2.0933130052515602e-05 loss: 0.1022 (0.1022) time: 2.9271 data: 0.0066 max mem: 33301 +Epoch: [24] [3420/4276] eta: 0:41:48 lr: 2.0930231819769508e-05 loss: 0.1007 (0.1022) time: 2.9264 data: 0.0068 max mem: 33301 +Epoch: [24] [3430/4276] eta: 0:41:19 lr: 2.092733354243145e-05 loss: 0.1024 (0.1022) time: 2.9273 data: 0.0067 max mem: 33301 +Epoch: [24] [3440/4276] eta: 0:40:49 lr: 2.092443522049387e-05 loss: 0.0986 (0.1022) time: 2.9289 data: 0.0066 max mem: 33301 +Epoch: [24] [3450/4276] eta: 0:40:20 lr: 2.0921536853949227e-05 loss: 0.1046 (0.1022) time: 2.9077 data: 0.0070 max mem: 33301 +Epoch: [24] [3460/4276] eta: 0:39:51 lr: 2.091863844278996e-05 loss: 0.1085 (0.1023) time: 2.9053 data: 0.0076 max mem: 33301 +Epoch: [24] [3470/4276] eta: 0:39:21 lr: 2.0915739987008513e-05 loss: 0.0954 (0.1023) time: 2.9253 data: 0.0072 max mem: 33301 +Epoch: [24] [3480/4276] eta: 0:38:52 lr: 2.0912841486597334e-05 loss: 0.0962 (0.1023) time: 2.9249 data: 0.0071 max mem: 33301 +Epoch: [24] [3490/4276] eta: 0:38:23 lr: 2.0909942941548867e-05 loss: 0.1035 (0.1023) time: 2.9268 data: 0.0072 max mem: 33301 +Epoch: [24] [3500/4276] eta: 0:37:53 lr: 2.0907044351855533e-05 loss: 0.1031 (0.1023) time: 2.9341 data: 0.0070 max mem: 33301 +Epoch: [24] [3510/4276] eta: 0:37:24 lr: 2.090414571750978e-05 loss: 0.0960 (0.1023) time: 2.9337 data: 0.0071 max mem: 33301 +Epoch: [24] [3520/4276] eta: 0:36:55 lr: 2.0901247038504042e-05 loss: 0.0929 (0.1023) time: 2.9285 data: 0.0070 max mem: 33301 +Epoch: [24] [3530/4276] eta: 0:36:25 lr: 2.0898348314830736e-05 loss: 0.0929 (0.1023) time: 2.9290 data: 0.0071 max mem: 33301 +Epoch: [24] [3540/4276] eta: 0:35:56 lr: 2.0895449546482294e-05 loss: 0.0975 (0.1023) time: 2.9290 data: 0.0071 max mem: 33301 +Epoch: [24] [3550/4276] eta: 0:35:27 lr: 2.0892550733451145e-05 loss: 0.0962 (0.1022) time: 2.9291 data: 0.0071 max mem: 33301 +Epoch: [24] [3560/4276] eta: 0:34:58 lr: 2.088965187572972e-05 loss: 0.0947 (0.1023) time: 2.9279 data: 0.0072 max mem: 33301 +Epoch: [24] [3570/4276] eta: 0:34:28 lr: 2.0886752973310418e-05 loss: 0.1110 (0.1023) time: 2.9332 data: 0.0071 max mem: 33301 +Epoch: [24] [3580/4276] eta: 0:33:59 lr: 2.0883854026185674e-05 loss: 0.0909 (0.1023) time: 2.9350 data: 0.0070 max mem: 33301 +Epoch: [24] [3590/4276] eta: 0:33:30 lr: 2.0880955034347893e-05 loss: 0.0894 (0.1023) time: 2.9280 data: 0.0070 max mem: 33301 +Epoch: [24] [3600/4276] eta: 0:33:00 lr: 2.0878055997789497e-05 loss: 0.0985 (0.1023) time: 2.9261 data: 0.0071 max mem: 33301 +Epoch: [24] [3610/4276] eta: 0:32:31 lr: 2.0875156916502886e-05 loss: 0.0938 (0.1023) time: 2.9268 data: 0.0071 max mem: 33301 +Epoch: [24] [3620/4276] eta: 0:32:02 lr: 2.0872257790480473e-05 loss: 0.0976 (0.1023) time: 2.9275 data: 0.0070 max mem: 33301 +Epoch: [24] [3630/4276] eta: 0:31:32 lr: 2.0869358619714663e-05 loss: 0.1001 (0.1023) time: 2.9270 data: 0.0071 max mem: 33301 +Epoch: [24] [3640/4276] eta: 0:31:03 lr: 2.0866459404197867e-05 loss: 0.0952 (0.1023) time: 2.9254 data: 0.0070 max mem: 33301 +Epoch: [24] [3650/4276] eta: 0:30:34 lr: 2.0863560143922467e-05 loss: 0.0910 (0.1022) time: 2.9117 data: 0.0071 max mem: 33301 +Epoch: [24] [3660/4276] eta: 0:30:04 lr: 2.0860660838880874e-05 loss: 0.0946 (0.1022) time: 2.9063 data: 0.0072 max mem: 33301 +Epoch: [24] [3670/4276] eta: 0:29:35 lr: 2.085776148906548e-05 loss: 0.0968 (0.1023) time: 2.9045 data: 0.0072 max mem: 33301 +Epoch: [24] [3680/4276] eta: 0:29:06 lr: 2.0854862094468685e-05 loss: 0.0940 (0.1022) time: 2.9109 data: 0.0070 max mem: 33301 +Epoch: [24] [3690/4276] eta: 0:28:36 lr: 2.0851962655082866e-05 loss: 0.0966 (0.1023) time: 2.9277 data: 0.0068 max mem: 33301 +Epoch: [24] [3700/4276] eta: 0:28:07 lr: 2.0849063170900422e-05 loss: 0.0966 (0.1022) time: 2.9278 data: 0.0067 max mem: 33301 +Epoch: [24] [3710/4276] eta: 0:27:38 lr: 2.084616364191373e-05 loss: 0.0956 (0.1022) time: 2.9275 data: 0.0066 max mem: 33301 +Epoch: [24] [3720/4276] eta: 0:27:09 lr: 2.0843264068115187e-05 loss: 0.0956 (0.1022) time: 2.9286 data: 0.0065 max mem: 33301 +Epoch: [24] [3730/4276] eta: 0:26:39 lr: 2.084036444949716e-05 loss: 0.0981 (0.1022) time: 2.9230 data: 0.0067 max mem: 33301 +Epoch: [24] [3740/4276] eta: 0:26:10 lr: 2.0837464786052023e-05 loss: 0.0981 (0.1022) time: 2.9199 data: 0.0071 max mem: 33301 +Epoch: [24] [3750/4276] eta: 0:25:41 lr: 2.083456507777217e-05 loss: 0.0974 (0.1022) time: 2.9250 data: 0.0070 max mem: 33301 +Epoch: [24] [3760/4276] eta: 0:25:11 lr: 2.0831665324649965e-05 loss: 0.0909 (0.1022) time: 2.9201 data: 0.0065 max mem: 33301 +Epoch: [24] [3770/4276] eta: 0:24:42 lr: 2.0828765526677775e-05 loss: 0.0927 (0.1022) time: 2.9195 data: 0.0065 max mem: 33301 +Epoch: [24] [3780/4276] eta: 0:24:13 lr: 2.082586568384797e-05 loss: 0.0951 (0.1022) time: 2.9259 data: 0.0065 max mem: 33301 +Epoch: [24] [3790/4276] eta: 0:23:43 lr: 2.0822965796152923e-05 loss: 0.0873 (0.1022) time: 2.9041 data: 0.0070 max mem: 33301 +Epoch: [24] [3800/4276] eta: 0:23:14 lr: 2.0820065863584993e-05 loss: 0.0934 (0.1022) time: 2.8855 data: 0.0072 max mem: 33301 +Epoch: [24] [3810/4276] eta: 0:22:45 lr: 2.0817165886136534e-05 loss: 0.0918 (0.1022) time: 2.9124 data: 0.0074 max mem: 33301 +Epoch: [24] [3820/4276] eta: 0:22:15 lr: 2.0814265863799913e-05 loss: 0.0903 (0.1021) time: 2.9317 data: 0.0075 max mem: 33301 +Epoch: [24] [3830/4276] eta: 0:21:46 lr: 2.0811365796567483e-05 loss: 0.0910 (0.1022) time: 2.9274 data: 0.0067 max mem: 33301 +Epoch: [24] [3840/4276] eta: 0:21:17 lr: 2.0808465684431593e-05 loss: 0.0879 (0.1021) time: 2.9261 data: 0.0066 max mem: 33301 +Epoch: [24] [3850/4276] eta: 0:20:47 lr: 2.08055655273846e-05 loss: 0.0833 (0.1021) time: 2.9197 data: 0.0066 max mem: 33301 +Epoch: [24] [3860/4276] eta: 0:20:18 lr: 2.080266532541885e-05 loss: 0.0985 (0.1021) time: 2.9185 data: 0.0068 max mem: 33301 +Epoch: [24] [3870/4276] eta: 0:19:49 lr: 2.0799765078526694e-05 loss: 0.0965 (0.1021) time: 2.9229 data: 0.0069 max mem: 33301 +Epoch: [24] [3880/4276] eta: 0:19:20 lr: 2.0796864786700466e-05 loss: 0.0897 (0.1021) time: 2.9078 data: 0.0067 max mem: 33301 +Epoch: [24] [3890/4276] eta: 0:18:50 lr: 2.0793964449932513e-05 loss: 0.0872 (0.1021) time: 2.8941 data: 0.0071 max mem: 33301 +Epoch: [24] [3900/4276] eta: 0:18:21 lr: 2.079106406821517e-05 loss: 0.0944 (0.1021) time: 2.8963 data: 0.0071 max mem: 33301 +Epoch: [24] [3910/4276] eta: 0:17:52 lr: 2.078816364154078e-05 loss: 0.0893 (0.1020) time: 2.9249 data: 0.0073 max mem: 33301 +Epoch: [24] [3920/4276] eta: 0:17:22 lr: 2.078526316990167e-05 loss: 0.0889 (0.1020) time: 2.9393 data: 0.0075 max mem: 33301 +Epoch: [24] [3930/4276] eta: 0:16:53 lr: 2.0782362653290168e-05 loss: 0.0902 (0.1020) time: 2.9242 data: 0.0069 max mem: 33301 +Epoch: [24] [3940/4276] eta: 0:16:24 lr: 2.077946209169861e-05 loss: 0.0911 (0.1020) time: 2.9234 data: 0.0069 max mem: 33301 +Epoch: [24] [3950/4276] eta: 0:15:54 lr: 2.0776561485119323e-05 loss: 0.0911 (0.1020) time: 2.9288 data: 0.0068 max mem: 33301 +Epoch: [24] [3960/4276] eta: 0:15:25 lr: 2.077366083354462e-05 loss: 0.0975 (0.1020) time: 2.9305 data: 0.0069 max mem: 33301 +Epoch: [24] [3970/4276] eta: 0:14:56 lr: 2.077076013696683e-05 loss: 0.1070 (0.1020) time: 2.9333 data: 0.0069 max mem: 33301 +Epoch: [24] [3980/4276] eta: 0:14:27 lr: 2.0767859395378265e-05 loss: 0.0931 (0.1020) time: 2.9336 data: 0.0068 max mem: 33301 +Epoch: [24] [3990/4276] eta: 0:13:57 lr: 2.0764958608771253e-05 loss: 0.0931 (0.1020) time: 2.9271 data: 0.0069 max mem: 33301 +Epoch: [24] [4000/4276] eta: 0:13:28 lr: 2.0762057777138097e-05 loss: 0.0953 (0.1020) time: 2.9272 data: 0.0068 max mem: 33301 +Epoch: [24] [4010/4276] eta: 0:12:59 lr: 2.075915690047111e-05 loss: 0.0891 (0.1019) time: 2.9280 data: 0.0070 max mem: 33301 +Epoch: [24] [4020/4276] eta: 0:12:29 lr: 2.07562559787626e-05 loss: 0.0939 (0.1020) time: 2.9274 data: 0.0069 max mem: 33301 +Epoch: [24] [4030/4276] eta: 0:12:00 lr: 2.0753355012004883e-05 loss: 0.0971 (0.1019) time: 2.9271 data: 0.0070 max mem: 33301 +Epoch: [24] [4040/4276] eta: 0:11:31 lr: 2.0750454000190245e-05 loss: 0.0921 (0.1020) time: 2.9267 data: 0.0071 max mem: 33301 +Epoch: [24] [4050/4276] eta: 0:11:02 lr: 2.0747552943310998e-05 loss: 0.0925 (0.1019) time: 2.9251 data: 0.0069 max mem: 33301 +Epoch: [24] [4060/4276] eta: 0:10:32 lr: 2.0744651841359437e-05 loss: 0.0978 (0.1019) time: 2.9265 data: 0.0070 max mem: 33301 +Epoch: [24] [4070/4276] eta: 0:10:03 lr: 2.0741750694327864e-05 loss: 0.1056 (0.1020) time: 2.9287 data: 0.0069 max mem: 33301 +Epoch: [24] [4080/4276] eta: 0:09:34 lr: 2.073884950220856e-05 loss: 0.0996 (0.1020) time: 2.9231 data: 0.0071 max mem: 33301 +Epoch: [24] [4090/4276] eta: 0:09:04 lr: 2.0735948264993828e-05 loss: 0.1070 (0.1020) time: 2.9134 data: 0.0071 max mem: 33301 +Epoch: [24] [4100/4276] eta: 0:08:35 lr: 2.0733046982675945e-05 loss: 0.1075 (0.1020) time: 2.9185 data: 0.0068 max mem: 33301 +Epoch: [24] [4110/4276] eta: 0:08:06 lr: 2.0730145655247212e-05 loss: 0.1101 (0.1020) time: 2.9295 data: 0.0071 max mem: 33301 +Epoch: [24] [4120/4276] eta: 0:07:36 lr: 2.07272442826999e-05 loss: 0.1035 (0.1020) time: 2.9315 data: 0.0070 max mem: 33301 +Epoch: [24] [4130/4276] eta: 0:07:07 lr: 2.072434286502629e-05 loss: 0.0958 (0.1020) time: 2.9304 data: 0.0070 max mem: 33301 +Epoch: [24] [4140/4276] eta: 0:06:38 lr: 2.072144140221867e-05 loss: 0.0958 (0.1020) time: 2.9241 data: 0.0068 max mem: 33301 +Epoch: [24] [4150/4276] eta: 0:06:09 lr: 2.0718539894269303e-05 loss: 0.0992 (0.1020) time: 2.9136 data: 0.0076 max mem: 33301 +Epoch: [24] [4160/4276] eta: 0:05:39 lr: 2.071563834117047e-05 loss: 0.1033 (0.1020) time: 2.9131 data: 0.0080 max mem: 33301 +Epoch: [24] [4170/4276] eta: 0:05:10 lr: 2.0712736742914442e-05 loss: 0.1077 (0.1021) time: 2.9177 data: 0.0073 max mem: 33301 +Epoch: [24] [4180/4276] eta: 0:04:41 lr: 2.0709835099493485e-05 loss: 0.0996 (0.1020) time: 2.9226 data: 0.0069 max mem: 33301 +Epoch: [24] [4190/4276] eta: 0:04:11 lr: 2.070693341089986e-05 loss: 0.0933 (0.1021) time: 2.9281 data: 0.0065 max mem: 33301 +Epoch: [24] [4200/4276] eta: 0:03:42 lr: 2.070403167712584e-05 loss: 0.1026 (0.1021) time: 2.9292 data: 0.0067 max mem: 33301 +Epoch: [24] [4210/4276] eta: 0:03:13 lr: 2.0701129898163678e-05 loss: 0.1026 (0.1021) time: 2.9252 data: 0.0068 max mem: 33301 +Epoch: [24] [4220/4276] eta: 0:02:44 lr: 2.069822807400564e-05 loss: 0.1105 (0.1021) time: 2.9261 data: 0.0069 max mem: 33301 +Epoch: [24] [4230/4276] eta: 0:02:14 lr: 2.069532620464397e-05 loss: 0.1082 (0.1022) time: 2.9301 data: 0.0070 max mem: 33301 +Epoch: [24] [4240/4276] eta: 0:01:45 lr: 2.0692424290070926e-05 loss: 0.1048 (0.1022) time: 2.9302 data: 0.0068 max mem: 33301 +Epoch: [24] [4250/4276] eta: 0:01:16 lr: 2.068952233027876e-05 loss: 0.1084 (0.1022) time: 2.9261 data: 0.0067 max mem: 33301 +Epoch: [24] [4260/4276] eta: 0:00:46 lr: 2.0686620325259724e-05 loss: 0.1141 (0.1022) time: 2.9204 data: 0.0065 max mem: 33301 +Epoch: [24] [4270/4276] eta: 0:00:17 lr: 2.0683718275006057e-05 loss: 0.1103 (0.1022) time: 2.9249 data: 0.0064 max mem: 33301 +Epoch: [24] Total time: 3:28:45 +Test: [ 0/21770] eta: 8:20:48 time: 1.3803 data: 1.3384 max mem: 33301 +Test: [ 100/21770] eta: 0:18:57 time: 0.0390 data: 0.0009 max mem: 33301 +Test: [ 200/21770] eta: 0:16:27 time: 0.0390 data: 0.0008 max mem: 33301 +Test: [ 300/21770] eta: 0:15:34 time: 0.0390 data: 0.0009 max mem: 33301 +Test: [ 400/21770] eta: 0:15:02 time: 0.0377 data: 0.0009 max mem: 33301 +Test: [ 500/21770] eta: 0:14:40 time: 0.0381 data: 0.0009 max mem: 33301 +Test: [ 600/21770] eta: 0:14:24 time: 0.0379 data: 0.0009 max mem: 33301 +Test: [ 700/21770] eta: 0:14:11 time: 0.0380 data: 0.0009 max mem: 33301 +Test: [ 800/21770] eta: 0:14:01 time: 0.0381 data: 0.0009 max mem: 33301 +Test: [ 900/21770] eta: 0:13:52 time: 0.0380 data: 0.0009 max mem: 33301 +Test: [ 1000/21770] eta: 0:13:44 time: 0.0381 data: 0.0009 max mem: 33301 +Test: [ 1100/21770] eta: 0:13:37 time: 0.0380 data: 0.0008 max mem: 33301 +Test: [ 1200/21770] eta: 0:13:31 time: 0.0381 data: 0.0009 max mem: 33301 +Test: [ 1300/21770] eta: 0:13:25 time: 0.0385 data: 0.0009 max mem: 33301 +Test: [ 1400/21770] eta: 0:13:20 time: 0.0383 data: 0.0008 max mem: 33301 +Test: [ 1500/21770] eta: 0:13:14 time: 0.0384 data: 0.0008 max mem: 33301 +Test: [ 1600/21770] eta: 0:13:09 time: 0.0380 data: 0.0009 max mem: 33301 +Test: [ 1700/21770] eta: 0:13:04 time: 0.0380 data: 0.0008 max mem: 33301 +Test: [ 1800/21770] eta: 0:12:59 time: 0.0381 data: 0.0008 max mem: 33301 +Test: [ 1900/21770] eta: 0:12:54 time: 0.0381 data: 0.0008 max mem: 33301 +Test: [ 2000/21770] eta: 0:12:49 time: 0.0380 data: 0.0008 max mem: 33301 +Test: [ 2100/21770] eta: 0:12:44 time: 0.0380 data: 0.0008 max mem: 33301 +Test: [ 2200/21770] eta: 0:12:40 time: 0.0381 data: 0.0008 max mem: 33301 +Test: [ 2300/21770] eta: 0:12:35 time: 0.0380 data: 0.0008 max mem: 33301 +Test: [ 2400/21770] eta: 0:12:31 time: 0.0383 data: 0.0009 max mem: 33301 +Test: [ 2500/21770] eta: 0:12:27 time: 0.0383 data: 0.0009 max mem: 33301 +Test: [ 2600/21770] eta: 0:12:23 time: 0.0383 data: 0.0009 max mem: 33301 +Test: [ 2700/21770] eta: 0:12:18 time: 0.0382 data: 0.0009 max mem: 33301 +Test: [ 2800/21770] eta: 0:12:14 time: 0.0383 data: 0.0009 max mem: 33301 +Test: [ 2900/21770] eta: 0:12:10 time: 0.0383 data: 0.0008 max mem: 33301 +Test: [ 3000/21770] eta: 0:12:06 time: 0.0383 data: 0.0009 max mem: 33301 +Test: [ 3100/21770] eta: 0:12:02 time: 0.0387 data: 0.0009 max mem: 33301 +Test: [ 3200/21770] eta: 0:11:58 time: 0.0387 data: 0.0009 max mem: 33301 +Test: [ 3300/21770] eta: 0:11:54 time: 0.0392 data: 0.0009 max mem: 33301 +Test: [ 3400/21770] eta: 0:11:50 time: 0.0388 data: 0.0009 max mem: 33301 +Test: [ 3500/21770] eta: 0:11:47 time: 0.0391 data: 0.0009 max mem: 33301 +Test: [ 3600/21770] eta: 0:11:43 time: 0.0394 data: 0.0009 max mem: 33301 +Test: [ 3700/21770] eta: 0:11:39 time: 0.0392 data: 0.0008 max mem: 33301 +Test: [ 3800/21770] eta: 0:11:36 time: 0.0393 data: 0.0009 max mem: 33301 +Test: [ 3900/21770] eta: 0:11:32 time: 0.0394 data: 0.0009 max mem: 33301 +Test: [ 4000/21770] eta: 0:11:29 time: 0.0392 data: 0.0008 max mem: 33301 +Test: [ 4100/21770] eta: 0:11:25 time: 0.0392 data: 0.0008 max mem: 33301 +Test: [ 4200/21770] eta: 0:11:21 time: 0.0394 data: 0.0009 max mem: 33301 +Test: [ 4300/21770] eta: 0:11:18 time: 0.0392 data: 0.0008 max mem: 33301 +Test: [ 4400/21770] eta: 0:11:14 time: 0.0393 data: 0.0008 max mem: 33301 +Test: [ 4500/21770] eta: 0:11:10 time: 0.0401 data: 0.0008 max mem: 33301 +Test: [ 4600/21770] eta: 0:11:07 time: 0.0393 data: 0.0008 max mem: 33301 +Test: [ 4700/21770] eta: 0:11:03 time: 0.0402 data: 0.0008 max mem: 33301 +Test: [ 4800/21770] eta: 0:11:00 time: 0.0391 data: 0.0008 max mem: 33301 +Test: [ 4900/21770] eta: 0:10:56 time: 0.0400 data: 0.0008 max mem: 33301 +Test: [ 5000/21770] eta: 0:10:52 time: 0.0393 data: 0.0008 max mem: 33301 +Test: [ 5100/21770] eta: 0:10:49 time: 0.0395 data: 0.0008 max mem: 33301 +Test: [ 5200/21770] eta: 0:10:45 time: 0.0399 data: 0.0008 max mem: 33301 +Test: [ 5300/21770] eta: 0:10:42 time: 0.0399 data: 0.0008 max mem: 33301 +Test: [ 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time: 0.0393 data: 0.0008 max mem: 33301 +Test: [ 6800/21770] eta: 0:09:45 time: 0.0392 data: 0.0008 max mem: 33301 +Test: [ 6900/21770] eta: 0:09:42 time: 0.0391 data: 0.0008 max mem: 33301 +Test: [ 7000/21770] eta: 0:09:38 time: 0.0393 data: 0.0008 max mem: 33301 +Test: [ 7100/21770] eta: 0:09:34 time: 0.0393 data: 0.0008 max mem: 33301 +Test: [ 7200/21770] eta: 0:09:30 time: 0.0394 data: 0.0008 max mem: 33301 +Test: [ 7300/21770] eta: 0:09:26 time: 0.0377 data: 0.0009 max mem: 33301 +Test: [ 7400/21770] eta: 0:09:22 time: 0.0377 data: 0.0009 max mem: 33301 +Test: [ 7500/21770] eta: 0:09:18 time: 0.0391 data: 0.0009 max mem: 33301 +Test: [ 7600/21770] eta: 0:09:14 time: 0.0388 data: 0.0009 max mem: 33301 +Test: [ 7700/21770] eta: 0:09:10 time: 0.0392 data: 0.0009 max mem: 33301 +Test: [ 7800/21770] eta: 0:09:06 time: 0.0386 data: 0.0009 max mem: 33301 +Test: [ 7900/21770] eta: 0:09:02 time: 0.0391 data: 0.0008 max mem: 33301 +Test: [ 8000/21770] eta: 0:08:58 time: 0.0388 data: 0.0008 max mem: 33301 +Test: [ 8100/21770] eta: 0:08:54 time: 0.0391 data: 0.0008 max mem: 33301 +Test: [ 8200/21770] eta: 0:08:50 time: 0.0388 data: 0.0008 max mem: 33301 +Test: [ 8300/21770] eta: 0:08:46 time: 0.0389 data: 0.0008 max mem: 33301 +Test: [ 8400/21770] eta: 0:08:42 time: 0.0392 data: 0.0008 max mem: 33301 +Test: [ 8500/21770] eta: 0:08:38 time: 0.0393 data: 0.0008 max mem: 33301 +Test: [ 8600/21770] eta: 0:08:34 time: 0.0391 data: 0.0008 max mem: 33301 +Test: [ 8700/21770] eta: 0:08:30 time: 0.0392 data: 0.0008 max mem: 33301 +Test: [ 8800/21770] eta: 0:08:26 time: 0.0392 data: 0.0008 max mem: 33301 +Test: [ 8900/21770] eta: 0:08:23 time: 0.0394 data: 0.0008 max mem: 33301 +Test: [ 9000/21770] eta: 0:08:19 time: 0.0393 data: 0.0008 max mem: 33301 +Test: [ 9100/21770] eta: 0:08:15 time: 0.0393 data: 0.0008 max mem: 33301 +Test: [ 9200/21770] eta: 0:08:11 time: 0.0390 data: 0.0008 max mem: 33301 +Test: [ 9300/21770] eta: 0:08:07 time: 0.0392 data: 0.0008 max mem: 33301 +Test: [ 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time: 0.0399 data: 0.0008 max mem: 33301 +Test: [10800/21770] eta: 0:07:09 time: 0.0401 data: 0.0008 max mem: 33301 +Test: [10900/21770] eta: 0:07:06 time: 0.0400 data: 0.0008 max mem: 33301 +Test: [11000/21770] eta: 0:07:02 time: 0.0401 data: 0.0008 max mem: 33301 +Test: [11100/21770] eta: 0:06:58 time: 0.0398 data: 0.0008 max mem: 33301 +Test: [11200/21770] eta: 0:06:54 time: 0.0387 data: 0.0008 max mem: 33301 +Test: [11300/21770] eta: 0:06:50 time: 0.0388 data: 0.0008 max mem: 33301 +Test: [11400/21770] eta: 0:06:46 time: 0.0385 data: 0.0008 max mem: 33301 +Test: [11500/21770] eta: 0:06:42 time: 0.0387 data: 0.0008 max mem: 33301 +Test: [11600/21770] eta: 0:06:38 time: 0.0386 data: 0.0008 max mem: 33301 +Test: [11700/21770] eta: 0:06:34 time: 0.0386 data: 0.0008 max mem: 33301 +Test: [11800/21770] eta: 0:06:30 time: 0.0386 data: 0.0008 max mem: 33301 +Test: [11900/21770] eta: 0:06:26 time: 0.0386 data: 0.0008 max mem: 33301 +Test: [12000/21770] eta: 0:06:22 time: 0.0386 data: 0.0008 max mem: 33301 +Test: [12100/21770] eta: 0:06:18 time: 0.0388 data: 0.0008 max mem: 33301 +Test: [12200/21770] eta: 0:06:14 time: 0.0387 data: 0.0008 max mem: 33301 +Test: [12300/21770] eta: 0:06:10 time: 0.0389 data: 0.0008 max mem: 33301 +Test: [12400/21770] eta: 0:06:06 time: 0.0391 data: 0.0008 max mem: 33301 +Test: [12500/21770] eta: 0:06:02 time: 0.0389 data: 0.0008 max mem: 33301 +Test: [12600/21770] eta: 0:05:59 time: 0.0389 data: 0.0008 max mem: 33301 +Test: [12700/21770] eta: 0:05:55 time: 0.0389 data: 0.0008 max mem: 33301 +Test: [12800/21770] eta: 0:05:51 time: 0.0385 data: 0.0008 max mem: 33301 +Test: [12900/21770] eta: 0:05:47 time: 0.0388 data: 0.0008 max mem: 33301 +Test: [13000/21770] eta: 0:05:43 time: 0.0385 data: 0.0008 max mem: 33301 +Test: [13100/21770] eta: 0:05:39 time: 0.0387 data: 0.0008 max mem: 33301 +Test: [13200/21770] eta: 0:05:35 time: 0.0387 data: 0.0009 max mem: 33301 +Test: [13300/21770] eta: 0:05:31 time: 0.0386 data: 0.0008 max mem: 33301 +Test: [13400/21770] eta: 0:05:27 time: 0.0385 data: 0.0008 max mem: 33301 +Test: [13500/21770] eta: 0:05:23 time: 0.0387 data: 0.0008 max mem: 33301 +Test: [13600/21770] eta: 0:05:19 time: 0.0390 data: 0.0008 max mem: 33301 +Test: [13700/21770] eta: 0:05:15 time: 0.0390 data: 0.0008 max mem: 33301 +Test: [13800/21770] eta: 0:05:11 time: 0.0390 data: 0.0008 max mem: 33301 +Test: [13900/21770] eta: 0:05:07 time: 0.0390 data: 0.0008 max mem: 33301 +Test: [14000/21770] eta: 0:05:03 time: 0.0391 data: 0.0008 max mem: 33301 +Test: [14100/21770] eta: 0:04:59 time: 0.0389 data: 0.0008 max mem: 33301 +Test: [14200/21770] eta: 0:04:56 time: 0.0389 data: 0.0008 max mem: 33301 +Test: [14300/21770] eta: 0:04:52 time: 0.0388 data: 0.0008 max mem: 33301 +Test: [14400/21770] eta: 0:04:48 time: 0.0388 data: 0.0009 max mem: 33301 +Test: [14500/21770] eta: 0:04:44 time: 0.0391 data: 0.0008 max mem: 33301 +Test: [14600/21770] eta: 0:04:40 time: 0.0390 data: 0.0008 max mem: 33301 +Test: [14700/21770] eta: 0:04:36 time: 0.0391 data: 0.0008 max mem: 33301 +Test: [14800/21770] eta: 0:04:32 time: 0.0393 data: 0.0009 max mem: 33301 +Test: [14900/21770] eta: 0:04:28 time: 0.0392 data: 0.0008 max mem: 33301 +Test: [15000/21770] eta: 0:04:24 time: 0.0394 data: 0.0008 max mem: 33301 +Test: [15100/21770] eta: 0:04:20 time: 0.0392 data: 0.0008 max mem: 33301 +Test: [15200/21770] eta: 0:04:16 time: 0.0395 data: 0.0008 max mem: 33301 +Test: [15300/21770] eta: 0:04:13 time: 0.0391 data: 0.0008 max mem: 33301 +Test: [15400/21770] eta: 0:04:09 time: 0.0395 data: 0.0008 max mem: 33301 +Test: [15500/21770] eta: 0:04:05 time: 0.0394 data: 0.0008 max mem: 33301 +Test: [15600/21770] eta: 0:04:01 time: 0.0393 data: 0.0008 max mem: 33301 +Test: [15700/21770] eta: 0:03:57 time: 0.0394 data: 0.0008 max mem: 33301 +Test: [15800/21770] eta: 0:03:53 time: 0.0391 data: 0.0008 max mem: 33301 +Test: [15900/21770] eta: 0:03:49 time: 0.0394 data: 0.0008 max mem: 33301 +Test: [16000/21770] eta: 0:03:45 time: 0.0393 data: 0.0008 max mem: 33301 +Test: [16100/21770] eta: 0:03:41 time: 0.0392 data: 0.0008 max mem: 33301 +Test: [16200/21770] eta: 0:03:37 time: 0.0392 data: 0.0008 max mem: 33301 +Test: [16300/21770] eta: 0:03:33 time: 0.0397 data: 0.0008 max mem: 33301 +Test: [16400/21770] eta: 0:03:30 time: 0.0392 data: 0.0008 max mem: 33301 +Test: [16500/21770] eta: 0:03:26 time: 0.0390 data: 0.0008 max mem: 33301 +Test: [16600/21770] eta: 0:03:22 time: 0.0395 data: 0.0008 max mem: 33301 +Test: [16700/21770] eta: 0:03:18 time: 0.0392 data: 0.0008 max mem: 33301 +Test: [16800/21770] eta: 0:03:14 time: 0.0394 data: 0.0008 max mem: 33301 +Test: [16900/21770] eta: 0:03:10 time: 0.0390 data: 0.0008 max mem: 33301 +Test: [17000/21770] eta: 0:03:06 time: 0.0392 data: 0.0008 max mem: 33301 +Test: [17100/21770] eta: 0:03:02 time: 0.0390 data: 0.0008 max mem: 33301 +Test: [17200/21770] eta: 0:02:58 time: 0.0391 data: 0.0008 max mem: 33301 +Test: [17300/21770] eta: 0:02:54 time: 0.0391 data: 0.0008 max mem: 33301 +Test: [17400/21770] eta: 0:02:50 time: 0.0391 data: 0.0008 max mem: 33301 +Test: [17500/21770] eta: 0:02:47 time: 0.0391 data: 0.0008 max mem: 33301 +Test: [17600/21770] eta: 0:02:43 time: 0.0391 data: 0.0008 max mem: 33301 +Test: [17700/21770] eta: 0:02:39 time: 0.0391 data: 0.0008 max mem: 33301 +Test: [17800/21770] eta: 0:02:35 time: 0.0393 data: 0.0008 max mem: 33301 +Test: [17900/21770] eta: 0:02:31 time: 0.0392 data: 0.0008 max mem: 33301 +Test: [18000/21770] eta: 0:02:27 time: 0.0391 data: 0.0008 max mem: 33301 +Test: [18100/21770] eta: 0:02:23 time: 0.0392 data: 0.0008 max mem: 33301 +Test: [18200/21770] eta: 0:02:19 time: 0.0391 data: 0.0008 max mem: 33301 +Test: [18300/21770] eta: 0:02:15 time: 0.0391 data: 0.0008 max mem: 33301 +Test: [18400/21770] eta: 0:02:11 time: 0.0392 data: 0.0008 max mem: 33301 +Test: [18500/21770] eta: 0:02:07 time: 0.0390 data: 0.0008 max mem: 33301 +Test: [18600/21770] eta: 0:02:04 time: 0.0393 data: 0.0008 max mem: 33301 +Test: [18700/21770] eta: 0:02:00 time: 0.0392 data: 0.0008 max mem: 33301 +Test: [18800/21770] eta: 0:01:56 time: 0.0393 data: 0.0008 max mem: 33301 +Test: [18900/21770] eta: 0:01:52 time: 0.0392 data: 0.0008 max mem: 33301 +Test: [19000/21770] eta: 0:01:48 time: 0.0393 data: 0.0008 max mem: 33301 +Test: [19100/21770] eta: 0:01:44 time: 0.0391 data: 0.0008 max mem: 33301 +Test: [19200/21770] eta: 0:01:40 time: 0.0391 data: 0.0008 max mem: 33301 +Test: [19300/21770] eta: 0:01:36 time: 0.0390 data: 0.0008 max mem: 33301 +Test: [19400/21770] eta: 0:01:32 time: 0.0393 data: 0.0008 max mem: 33301 +Test: [19500/21770] eta: 0:01:28 time: 0.0393 data: 0.0008 max mem: 33301 +Test: [19600/21770] eta: 0:01:24 time: 0.0394 data: 0.0008 max mem: 33301 +Test: [19700/21770] eta: 0:01:21 time: 0.0391 data: 0.0008 max mem: 33301 +Test: [19800/21770] eta: 0:01:17 time: 0.0391 data: 0.0008 max mem: 33301 +Test: [19900/21770] eta: 0:01:13 time: 0.0391 data: 0.0008 max mem: 33301 +Test: [20000/21770] eta: 0:01:09 time: 0.0392 data: 0.0008 max mem: 33301 +Test: [20100/21770] eta: 0:01:05 time: 0.0390 data: 0.0008 max mem: 33301 +Test: [20200/21770] eta: 0:01:01 time: 0.0389 data: 0.0008 max mem: 33301 +Test: [20300/21770] eta: 0:00:57 time: 0.0389 data: 0.0008 max mem: 33301 +Test: [20400/21770] eta: 0:00:53 time: 0.0388 data: 0.0008 max mem: 33301 +Test: [20500/21770] eta: 0:00:49 time: 0.0388 data: 0.0008 max mem: 33301 +Test: [20600/21770] eta: 0:00:45 time: 0.0388 data: 0.0008 max mem: 33301 +Test: [20700/21770] eta: 0:00:41 time: 0.0386 data: 0.0008 max mem: 33301 +Test: [20800/21770] eta: 0:00:37 time: 0.0388 data: 0.0008 max mem: 33301 +Test: [20900/21770] eta: 0:00:34 time: 0.0389 data: 0.0008 max mem: 33301 +Test: [21000/21770] eta: 0:00:30 time: 0.0388 data: 0.0008 max mem: 33301 +Test: [21100/21770] eta: 0:00:26 time: 0.0393 data: 0.0009 max mem: 33301 +Test: [21200/21770] eta: 0:00:22 time: 0.0389 data: 0.0008 max mem: 33301 +Test: [21300/21770] eta: 0:00:18 time: 0.0389 data: 0.0008 max mem: 33301 +Test: [21400/21770] eta: 0:00:14 time: 0.0389 data: 0.0009 max mem: 33301 +Test: [21500/21770] eta: 0:00:10 time: 0.0387 data: 0.0008 max mem: 33301 +Test: [21600/21770] eta: 0:00:06 time: 0.0387 data: 0.0008 max mem: 33301 +Test: [21700/21770] eta: 0:00:02 time: 0.0390 data: 0.0008 max mem: 33301 +Test: Total time: 0:14:11 +Final results: +Mean IoU is 16.31 + + precision@0.5 = 2.99 + precision@0.6 = 1.34 + precision@0.7 = 0.38 + precision@0.8 = 0.03 + precision@0.9 = 0.00 + overall IoU = 16.43 + mean IoU = 16.31 + +Mean accuracy for one-to-zero sample is 0.00 + +Average object IoU 0.1631097177556786 +Overall IoU 16.432435989379883 +Better epoch: 24 + +Epoch: [25] [ 0/4276] eta: 6:08:13 lr: 2.068197702313801e-05 loss: 0.1300 (0.1300) time: 5.1669 data: 2.0707 max mem: 33301 +Epoch: [25] [ 10/4276] eta: 3:43:13 lr: 2.0679074900492794e-05 loss: 0.0951 (0.1006) time: 3.1395 data: 0.1958 max mem: 33301 +Epoch: [25] [ 20/4276] eta: 3:36:05 lr: 2.0676172732592776e-05 loss: 0.0964 (0.1037) time: 2.9404 data: 0.0079 max mem: 33301 +Epoch: [25] [ 30/4276] eta: 3:33:15 lr: 2.06732705194302e-05 loss: 0.0983 (0.1051) time: 2.9443 data: 0.0078 max mem: 33301 +Epoch: [25] [ 40/4276] eta: 3:31:28 lr: 2.0670368260997282e-05 loss: 0.0983 (0.1042) time: 2.9418 data: 0.0083 max mem: 33301 +Epoch: [25] [ 50/4276] eta: 3:30:05 lr: 2.0667465957286265e-05 loss: 0.0930 (0.1026) time: 2.9355 data: 0.0084 max mem: 33301 +Epoch: [25] [ 60/4276] eta: 3:28:59 lr: 2.066456360828937e-05 loss: 0.0894 (0.1071) time: 2.9311 data: 0.0082 max mem: 33301 +Epoch: [25] [ 70/4276] eta: 3:28:06 lr: 2.0661661213998834e-05 loss: 0.0882 (0.1045) time: 2.9326 data: 0.0078 max mem: 33301 +Epoch: [25] [ 80/4276] eta: 3:27:19 lr: 2.065875877440687e-05 loss: 0.0976 (0.1067) time: 2.9353 data: 0.0079 max mem: 33301 +Epoch: [25] [ 90/4276] eta: 3:26:35 lr: 2.06558562895057e-05 loss: 0.1090 (0.1073) time: 2.9345 data: 0.0080 max mem: 33301 +Epoch: [25] [ 100/4276] eta: 3:25:55 lr: 2.065295375928755e-05 loss: 0.1111 (0.1076) time: 2.9340 data: 0.0079 max mem: 33301 +Epoch: [25] [ 110/4276] eta: 3:25:15 lr: 2.065005118374463e-05 loss: 0.1032 (0.1074) time: 2.9337 data: 0.0078 max mem: 33301 +Epoch: [25] [ 120/4276] eta: 3:24:40 lr: 2.0647148562869154e-05 loss: 0.1006 (0.1068) time: 2.9361 data: 0.0078 max mem: 33301 +Epoch: [25] [ 130/4276] eta: 3:24:06 lr: 2.064424589665333e-05 loss: 0.0943 (0.1070) time: 2.9401 data: 0.0082 max mem: 33301 +Epoch: [25] [ 140/4276] eta: 3:23:32 lr: 2.0641343185089367e-05 loss: 0.1001 (0.1061) time: 2.9391 data: 0.0079 max mem: 33301 +Epoch: [25] [ 150/4276] eta: 3:22:58 lr: 2.063844042816948e-05 loss: 0.1026 (0.1060) time: 2.9375 data: 0.0077 max mem: 33301 +Epoch: [25] [ 160/4276] eta: 3:22:28 lr: 2.0635537625885862e-05 loss: 0.1007 (0.1054) time: 2.9437 data: 0.0078 max mem: 33301 +Epoch: [25] [ 170/4276] eta: 3:21:56 lr: 2.0632634778230713e-05 loss: 0.0967 (0.1046) time: 2.9451 data: 0.0077 max mem: 33301 +Epoch: [25] [ 180/4276] eta: 3:21:24 lr: 2.0629731885196235e-05 loss: 0.1010 (0.1053) time: 2.9401 data: 0.0076 max mem: 33301 +Epoch: [25] [ 190/4276] eta: 3:20:52 lr: 2.0626828946774625e-05 loss: 0.1038 (0.1049) time: 2.9398 data: 0.0074 max mem: 33301 +Epoch: [25] [ 200/4276] eta: 3:20:21 lr: 2.0623925962958076e-05 loss: 0.0899 (0.1043) time: 2.9404 data: 0.0073 max mem: 33301 +Epoch: [25] [ 210/4276] eta: 3:19:45 lr: 2.0621022933738768e-05 loss: 0.0899 (0.1042) time: 2.9287 data: 0.0071 max mem: 33301 +Epoch: [25] [ 220/4276] eta: 3:19:04 lr: 2.0618119859108903e-05 loss: 0.0861 (0.1036) time: 2.9000 data: 0.0068 max mem: 33301 +Epoch: [25] [ 230/4276] eta: 3:18:23 lr: 2.0615216739060654e-05 loss: 0.0826 (0.1033) time: 2.8823 data: 0.0071 max mem: 33301 +Epoch: [25] [ 240/4276] eta: 3:17:42 lr: 2.061231357358621e-05 loss: 0.0949 (0.1031) time: 2.8758 data: 0.0071 max mem: 33301 +Epoch: [25] [ 250/4276] eta: 3:17:01 lr: 2.0609410362677746e-05 loss: 0.1002 (0.1034) time: 2.8700 data: 0.0068 max mem: 33301 +Epoch: [25] [ 260/4276] eta: 3:16:23 lr: 2.0606507106327452e-05 loss: 0.1068 (0.1033) time: 2.8731 data: 0.0067 max mem: 33301 +Epoch: [25] [ 270/4276] eta: 3:15:51 lr: 2.0603603804527487e-05 loss: 0.0988 (0.1034) time: 2.8962 data: 0.0070 max mem: 33301 +Epoch: [25] [ 280/4276] eta: 3:15:15 lr: 2.0600700457270033e-05 loss: 0.0895 (0.1028) time: 2.9027 data: 0.0071 max mem: 33301 +Epoch: [25] [ 290/4276] eta: 3:14:39 lr: 2.0597797064547254e-05 loss: 0.0895 (0.1025) time: 2.8876 data: 0.0067 max mem: 33301 +Epoch: [25] [ 300/4276] eta: 3:14:06 lr: 2.0594893626351326e-05 loss: 0.0963 (0.1025) time: 2.8907 data: 0.0069 max mem: 33301 +Epoch: [25] [ 310/4276] eta: 3:13:38 lr: 2.0591990142674404e-05 loss: 0.0977 (0.1022) time: 2.9190 data: 0.0071 max mem: 33301 +Epoch: [25] [ 320/4276] eta: 3:13:10 lr: 2.058908661350865e-05 loss: 0.0994 (0.1026) time: 2.9413 data: 0.0072 max mem: 33301 +Epoch: [25] [ 330/4276] eta: 3:12:42 lr: 2.058618303884623e-05 loss: 0.1023 (0.1028) time: 2.9419 data: 0.0074 max mem: 33301 +Epoch: [25] [ 340/4276] eta: 3:12:13 lr: 2.0583279418679305e-05 loss: 0.0990 (0.1027) time: 2.9389 data: 0.0075 max mem: 33301 +Epoch: [25] [ 350/4276] eta: 3:11:39 lr: 2.058037575300001e-05 loss: 0.0972 (0.1026) time: 2.9094 data: 0.0073 max mem: 33301 +Epoch: [25] [ 360/4276] eta: 3:11:05 lr: 2.0577472041800514e-05 loss: 0.0975 (0.1031) time: 2.8845 data: 0.0070 max mem: 33301 +Epoch: [25] [ 370/4276] eta: 3:10:31 lr: 2.057456828507296e-05 loss: 0.0967 (0.1028) time: 2.8866 data: 0.0068 max mem: 33301 +Epoch: [25] [ 380/4276] eta: 3:09:59 lr: 2.0571664482809498e-05 loss: 0.0894 (0.1029) time: 2.8935 data: 0.0071 max mem: 33301 +Epoch: [25] [ 390/4276] eta: 3:09:27 lr: 2.0568760635002267e-05 loss: 0.0978 (0.1030) time: 2.8945 data: 0.0071 max mem: 33301 +Epoch: [25] [ 400/4276] eta: 3:08:57 lr: 2.0565856741643406e-05 loss: 0.1141 (0.1035) time: 2.9047 data: 0.0070 max mem: 33301 +Epoch: [25] [ 410/4276] eta: 3:08:25 lr: 2.056295280272506e-05 loss: 0.1160 (0.1036) time: 2.9075 data: 0.0073 max mem: 33301 +Epoch: [25] [ 420/4276] eta: 3:07:52 lr: 2.0560048818239368e-05 loss: 0.0982 (0.1036) time: 2.8898 data: 0.0069 max mem: 33301 +Epoch: [25] [ 430/4276] eta: 3:07:19 lr: 2.055714478817845e-05 loss: 0.1023 (0.1037) time: 2.8832 data: 0.0067 max mem: 33301 +Epoch: [25] [ 440/4276] eta: 3:06:51 lr: 2.055424071253445e-05 loss: 0.0978 (0.1035) time: 2.9103 data: 0.0073 max mem: 33301 +Epoch: [25] [ 450/4276] eta: 3:06:23 lr: 2.055133659129949e-05 loss: 0.0942 (0.1034) time: 2.9389 data: 0.0074 max mem: 33301 +Epoch: [25] [ 460/4276] eta: 3:05:55 lr: 2.05484324244657e-05 loss: 0.0945 (0.1030) time: 2.9352 data: 0.0073 max mem: 33301 +Epoch: [25] [ 470/4276] eta: 3:05:24 lr: 2.0545528212025203e-05 loss: 0.0790 (0.1026) time: 2.9210 data: 0.0071 max mem: 33301 +Epoch: [25] [ 480/4276] eta: 3:04:56 lr: 2.054262395397011e-05 loss: 0.0790 (0.1024) time: 2.9244 data: 0.0068 max mem: 33301 +Epoch: [25] [ 490/4276] eta: 3:04:29 lr: 2.0539719650292548e-05 loss: 0.0888 (0.1022) time: 2.9410 data: 0.0069 max mem: 33301 +Epoch: [25] [ 500/4276] eta: 3:04:00 lr: 2.0536815300984637e-05 loss: 0.0901 (0.1020) time: 2.9405 data: 0.0068 max mem: 33301 +Epoch: [25] [ 510/4276] eta: 3:03:32 lr: 2.053391090603848e-05 loss: 0.0938 (0.1019) time: 2.9367 data: 0.0064 max mem: 33301 +Epoch: [25] [ 520/4276] eta: 3:03:04 lr: 2.0531006465446184e-05 loss: 0.0998 (0.1020) time: 2.9388 data: 0.0064 max mem: 33301 +Epoch: [25] [ 530/4276] eta: 3:02:35 lr: 2.0528101979199872e-05 loss: 0.1009 (0.1019) time: 2.9366 data: 0.0067 max mem: 33301 +Epoch: [25] [ 540/4276] eta: 3:02:07 lr: 2.0525197447291634e-05 loss: 0.0972 (0.1018) time: 2.9319 data: 0.0071 max mem: 33301 +Epoch: [25] [ 550/4276] eta: 3:01:37 lr: 2.052229286971358e-05 loss: 0.0970 (0.1017) time: 2.9285 data: 0.0065 max mem: 33301 +Epoch: [25] [ 560/4276] eta: 3:01:09 lr: 2.05193882464578e-05 loss: 0.0971 (0.1016) time: 2.9331 data: 0.0062 max mem: 33301 +Epoch: [25] [ 570/4276] eta: 3:00:41 lr: 2.051648357751641e-05 loss: 0.1013 (0.1016) time: 2.9403 data: 0.0063 max mem: 33301 +Epoch: [25] [ 580/4276] eta: 3:00:13 lr: 2.051357886288149e-05 loss: 0.1013 (0.1015) time: 2.9400 data: 0.0062 max mem: 33301 +Epoch: [25] [ 590/4276] eta: 2:59:44 lr: 2.051067410254513e-05 loss: 0.0843 (0.1014) time: 2.9389 data: 0.0062 max mem: 33301 +Epoch: [25] [ 600/4276] eta: 2:59:16 lr: 2.0507769296499427e-05 loss: 0.0951 (0.1013) time: 2.9381 data: 0.0062 max mem: 33301 +Epoch: [25] [ 610/4276] eta: 2:58:47 lr: 2.050486444473647e-05 loss: 0.0947 (0.1011) time: 2.9390 data: 0.0065 max mem: 33301 +Epoch: [25] [ 620/4276] eta: 2:58:19 lr: 2.0501959547248335e-05 loss: 0.0897 (0.1010) time: 2.9387 data: 0.0065 max mem: 33301 +Epoch: [25] [ 630/4276] eta: 2:57:50 lr: 2.0499054604027102e-05 loss: 0.0958 (0.1013) time: 2.9377 data: 0.0062 max mem: 33301 +Epoch: [25] [ 640/4276] eta: 2:57:21 lr: 2.049614961506486e-05 loss: 0.0986 (0.1011) time: 2.9388 data: 0.0065 max mem: 33301 +Epoch: [25] [ 650/4276] eta: 2:56:53 lr: 2.049324458035368e-05 loss: 0.0904 (0.1012) time: 2.9401 data: 0.0069 max mem: 33301 +Epoch: [25] [ 660/4276] eta: 2:56:24 lr: 2.049033949988563e-05 loss: 0.1016 (0.1014) time: 2.9405 data: 0.0069 max mem: 33301 +Epoch: [25] [ 670/4276] eta: 2:55:55 lr: 2.0487434373652785e-05 loss: 0.1028 (0.1014) time: 2.9366 data: 0.0066 max mem: 33301 +Epoch: [25] [ 680/4276] eta: 2:55:27 lr: 2.0484529201647218e-05 loss: 0.1040 (0.1014) time: 2.9368 data: 0.0067 max mem: 33301 +Epoch: [25] [ 690/4276] eta: 2:54:58 lr: 2.0481623983860996e-05 loss: 0.0914 (0.1013) time: 2.9419 data: 0.0066 max mem: 33301 +Epoch: [25] [ 700/4276] eta: 2:54:30 lr: 2.047871872028617e-05 loss: 0.0880 (0.1011) time: 2.9417 data: 0.0064 max mem: 33301 +Epoch: [25] [ 710/4276] eta: 2:54:01 lr: 2.0475813410914806e-05 loss: 0.0915 (0.1011) time: 2.9405 data: 0.0063 max mem: 33301 +Epoch: [25] [ 720/4276] eta: 2:53:32 lr: 2.0472908055738966e-05 loss: 0.0955 (0.1011) time: 2.9401 data: 0.0065 max mem: 33301 +Epoch: [25] [ 730/4276] eta: 2:53:04 lr: 2.0470002654750706e-05 loss: 0.0947 (0.1011) time: 2.9397 data: 0.0067 max mem: 33301 +Epoch: [25] [ 740/4276] eta: 2:52:35 lr: 2.0467097207942066e-05 loss: 0.0881 (0.1009) time: 2.9383 data: 0.0065 max mem: 33301 +Epoch: [25] [ 750/4276] eta: 2:52:06 lr: 2.0464191715305112e-05 loss: 0.0892 (0.1008) time: 2.9381 data: 0.0063 max mem: 33301 +Epoch: [25] [ 760/4276] eta: 2:51:37 lr: 2.0461286176831882e-05 loss: 0.0903 (0.1008) time: 2.9394 data: 0.0063 max mem: 33301 +Epoch: [25] [ 770/4276] eta: 2:51:08 lr: 2.0458380592514426e-05 loss: 0.0903 (0.1007) time: 2.9387 data: 0.0064 max mem: 33301 +Epoch: [25] [ 780/4276] eta: 2:50:39 lr: 2.0455474962344777e-05 loss: 0.0874 (0.1006) time: 2.9377 data: 0.0066 max mem: 33301 +Epoch: [25] [ 790/4276] eta: 2:50:11 lr: 2.045256928631498e-05 loss: 0.0945 (0.1007) time: 2.9452 data: 0.0065 max mem: 33301 +Epoch: [25] [ 800/4276] eta: 2:49:41 lr: 2.0449663564417074e-05 loss: 0.1011 (0.1007) time: 2.9336 data: 0.0065 max mem: 33301 +Epoch: [25] [ 810/4276] eta: 2:49:12 lr: 2.0446757796643097e-05 loss: 0.1060 (0.1009) time: 2.9163 data: 0.0069 max mem: 33301 +Epoch: [25] [ 820/4276] eta: 2:48:41 lr: 2.0443851982985064e-05 loss: 0.0999 (0.1008) time: 2.9135 data: 0.0069 max mem: 33301 +Epoch: [25] [ 830/4276] eta: 2:48:12 lr: 2.044094612343502e-05 loss: 0.0942 (0.1009) time: 2.9186 data: 0.0068 max mem: 33301 +Epoch: [25] [ 840/4276] eta: 2:47:43 lr: 2.043804021798499e-05 loss: 0.0991 (0.1012) time: 2.9323 data: 0.0066 max mem: 33301 +Epoch: [25] [ 850/4276] eta: 2:47:14 lr: 2.0435134266626985e-05 loss: 0.0958 (0.1010) time: 2.9374 data: 0.0067 max mem: 33301 +Epoch: [25] [ 860/4276] eta: 2:46:45 lr: 2.0432228269353032e-05 loss: 0.0888 (0.1011) time: 2.9380 data: 0.0067 max mem: 33301 +Epoch: [25] [ 870/4276] eta: 2:46:16 lr: 2.0429322226155152e-05 loss: 0.0982 (0.1010) time: 2.9371 data: 0.0067 max mem: 33301 +Epoch: [25] [ 880/4276] eta: 2:45:47 lr: 2.0426416137025365e-05 loss: 0.0982 (0.1011) time: 2.9379 data: 0.0068 max mem: 33301 +Epoch: [25] [ 890/4276] eta: 2:45:18 lr: 2.0423510001955676e-05 loss: 0.1085 (0.1013) time: 2.9392 data: 0.0065 max mem: 33301 +Epoch: [25] [ 900/4276] eta: 2:44:49 lr: 2.0420603820938095e-05 loss: 0.1039 (0.1013) time: 2.9386 data: 0.0064 max mem: 33301 +Epoch: [25] [ 910/4276] eta: 2:44:20 lr: 2.0417697593964634e-05 loss: 0.0989 (0.1013) time: 2.9341 data: 0.0065 max mem: 33301 +Epoch: [25] [ 920/4276] eta: 2:43:51 lr: 2.0414791321027298e-05 loss: 0.0969 (0.1014) time: 2.9343 data: 0.0065 max mem: 33301 +Epoch: [25] [ 930/4276] eta: 2:43:22 lr: 2.0411885002118086e-05 loss: 0.0969 (0.1013) time: 2.9381 data: 0.0063 max mem: 33301 +Epoch: [25] [ 940/4276] eta: 2:42:53 lr: 2.0408978637229e-05 loss: 0.0920 (0.1012) time: 2.9379 data: 0.0063 max mem: 33301 +Epoch: [25] [ 950/4276] eta: 2:42:24 lr: 2.040607222635203e-05 loss: 0.0922 (0.1013) time: 2.9391 data: 0.0066 max mem: 33301 +Epoch: [25] [ 960/4276] eta: 2:41:55 lr: 2.0403165769479186e-05 loss: 0.1023 (0.1013) time: 2.9380 data: 0.0066 max mem: 33301 +Epoch: [25] [ 970/4276] eta: 2:41:26 lr: 2.0400259266602444e-05 loss: 0.0994 (0.1013) time: 2.9410 data: 0.0063 max mem: 33301 +Epoch: [25] [ 980/4276] eta: 2:40:57 lr: 2.03973527177138e-05 loss: 0.1025 (0.1013) time: 2.9432 data: 0.0065 max mem: 33301 +Epoch: [25] [ 990/4276] eta: 2:40:28 lr: 2.0394446122805237e-05 loss: 0.1029 (0.1013) time: 2.9398 data: 0.0068 max mem: 33301 +Epoch: [25] [1000/4276] eta: 2:39:59 lr: 2.039153948186875e-05 loss: 0.0954 (0.1012) time: 2.9393 data: 0.0071 max mem: 33301 +Epoch: [25] [1010/4276] eta: 2:39:30 lr: 2.03886327948963e-05 loss: 0.0988 (0.1013) time: 2.9387 data: 0.0068 max mem: 33301 +Epoch: [25] [1020/4276] eta: 2:39:01 lr: 2.038572606187988e-05 loss: 0.0984 (0.1013) time: 2.9387 data: 0.0066 max mem: 33301 +Epoch: [25] [1030/4276] eta: 2:38:32 lr: 2.0382819282811463e-05 loss: 0.1002 (0.1014) time: 2.9395 data: 0.0067 max mem: 33301 +Epoch: [25] [1040/4276] eta: 2:38:04 lr: 2.0379912457683025e-05 loss: 0.0974 (0.1013) time: 2.9458 data: 0.0068 max mem: 33301 +Epoch: [25] [1050/4276] eta: 2:37:35 lr: 2.037700558648653e-05 loss: 0.0959 (0.1014) time: 2.9446 data: 0.0068 max mem: 33301 +Epoch: [25] [1060/4276] eta: 2:37:06 lr: 2.0374098669213945e-05 loss: 0.0994 (0.1015) time: 2.9377 data: 0.0067 max mem: 33301 +Epoch: [25] [1070/4276] eta: 2:36:36 lr: 2.037119170585724e-05 loss: 0.1148 (0.1017) time: 2.9345 data: 0.0069 max mem: 33301 +Epoch: [25] [1080/4276] eta: 2:36:07 lr: 2.036828469640838e-05 loss: 0.1077 (0.1018) time: 2.9350 data: 0.0069 max mem: 33301 +Epoch: [25] [1090/4276] eta: 2:35:38 lr: 2.036537764085931e-05 loss: 0.1157 (0.1019) time: 2.9379 data: 0.0067 max mem: 33301 +Epoch: [25] [1100/4276] eta: 2:35:09 lr: 2.0362470539202006e-05 loss: 0.1178 (0.1020) time: 2.9369 data: 0.0065 max mem: 33301 +Epoch: [25] [1110/4276] eta: 2:34:40 lr: 2.035956339142841e-05 loss: 0.1175 (0.1022) time: 2.9391 data: 0.0067 max mem: 33301 +Epoch: [25] [1120/4276] eta: 2:34:11 lr: 2.0356656197530476e-05 loss: 0.1075 (0.1021) time: 2.9410 data: 0.0071 max mem: 33301 +Epoch: [25] [1130/4276] eta: 2:33:42 lr: 2.0353748957500154e-05 loss: 0.0838 (0.1020) time: 2.9384 data: 0.0070 max mem: 33301 +Epoch: [25] [1140/4276] eta: 2:33:13 lr: 2.035084167132939e-05 loss: 0.0872 (0.1020) time: 2.9379 data: 0.0066 max mem: 33301 +Epoch: [25] [1150/4276] eta: 2:32:43 lr: 2.0347934339010133e-05 loss: 0.0966 (0.1021) time: 2.9362 data: 0.0067 max mem: 33301 +Epoch: [25] [1160/4276] eta: 2:32:14 lr: 2.0345026960534312e-05 loss: 0.1138 (0.1021) time: 2.9348 data: 0.0071 max mem: 33301 +Epoch: [25] [1170/4276] eta: 2:31:45 lr: 2.0342119535893868e-05 loss: 0.0962 (0.1021) time: 2.9370 data: 0.0069 max mem: 33301 +Epoch: [25] [1180/4276] eta: 2:31:16 lr: 2.0339212065080746e-05 loss: 0.0962 (0.1020) time: 2.9359 data: 0.0065 max mem: 33301 +Epoch: [25] [1190/4276] eta: 2:30:46 lr: 2.0336304548086873e-05 loss: 0.0818 (0.1019) time: 2.9352 data: 0.0066 max mem: 33301 +Epoch: [25] [1200/4276] eta: 2:30:17 lr: 2.0333396984904178e-05 loss: 0.0818 (0.1019) time: 2.9365 data: 0.0068 max mem: 33301 +Epoch: [25] [1210/4276] eta: 2:29:48 lr: 2.0330489375524588e-05 loss: 0.0830 (0.1018) time: 2.9371 data: 0.0067 max mem: 33301 +Epoch: [25] [1220/4276] eta: 2:29:19 lr: 2.0327581719940024e-05 loss: 0.0930 (0.1018) time: 2.9419 data: 0.0064 max mem: 33301 +Epoch: [25] [1230/4276] eta: 2:28:50 lr: 2.0324674018142427e-05 loss: 0.0957 (0.1018) time: 2.9398 data: 0.0063 max mem: 33301 +Epoch: [25] [1240/4276] eta: 2:28:21 lr: 2.0321766270123692e-05 loss: 0.0961 (0.1018) time: 2.9330 data: 0.0065 max mem: 33301 +Epoch: [25] [1250/4276] eta: 2:27:51 lr: 2.0318858475875745e-05 loss: 0.0948 (0.1018) time: 2.9337 data: 0.0065 max mem: 33301 +Epoch: [25] [1260/4276] eta: 2:27:22 lr: 2.0315950635390503e-05 loss: 0.0948 (0.1018) time: 2.9340 data: 0.0063 max mem: 33301 +Epoch: [25] [1270/4276] eta: 2:26:53 lr: 2.031304274865988e-05 loss: 0.0974 (0.1018) time: 2.9353 data: 0.0063 max mem: 33301 +Epoch: [25] [1280/4276] eta: 2:26:24 lr: 2.0310134815675774e-05 loss: 0.1072 (0.1018) time: 2.9422 data: 0.0064 max mem: 33301 +Epoch: [25] [1290/4276] eta: 2:25:55 lr: 2.0307226836430096e-05 loss: 0.1037 (0.1019) time: 2.9473 data: 0.0065 max mem: 33301 +Epoch: [25] [1300/4276] eta: 2:25:26 lr: 2.0304318810914748e-05 loss: 0.0925 (0.1018) time: 2.9431 data: 0.0063 max mem: 33301 +Epoch: [25] [1310/4276] eta: 2:24:57 lr: 2.030141073912164e-05 loss: 0.0903 (0.1018) time: 2.9384 data: 0.0063 max mem: 33301 +Epoch: [25] [1320/4276] eta: 2:24:27 lr: 2.0298502621042657e-05 loss: 0.1018 (0.1019) time: 2.9358 data: 0.0065 max mem: 33301 +Epoch: [25] [1330/4276] eta: 2:23:58 lr: 2.02955944566697e-05 loss: 0.0892 (0.1018) time: 2.9349 data: 0.0064 max mem: 33301 +Epoch: [25] [1340/4276] eta: 2:23:29 lr: 2.0292686245994656e-05 loss: 0.0871 (0.1018) time: 2.9461 data: 0.0064 max mem: 33301 +Epoch: [25] [1350/4276] eta: 2:23:00 lr: 2.0289777989009422e-05 loss: 0.0891 (0.1018) time: 2.9427 data: 0.0063 max mem: 33301 +Epoch: [25] [1360/4276] eta: 2:22:30 lr: 2.028686968570588e-05 loss: 0.0939 (0.1017) time: 2.9161 data: 0.0068 max mem: 33301 +Epoch: [25] [1370/4276] eta: 2:22:01 lr: 2.028396133607591e-05 loss: 0.0955 (0.1018) time: 2.9200 data: 0.0069 max mem: 33301 +Epoch: [25] [1380/4276] eta: 2:21:31 lr: 2.0281052940111406e-05 loss: 0.0958 (0.1018) time: 2.9353 data: 0.0063 max mem: 33301 +Epoch: [25] [1390/4276] eta: 2:21:02 lr: 2.0278144497804243e-05 loss: 0.1000 (0.1019) time: 2.9374 data: 0.0060 max mem: 33301 +Epoch: [25] [1400/4276] eta: 2:20:33 lr: 2.0275236009146286e-05 loss: 0.1126 (0.1020) time: 2.9385 data: 0.0061 max mem: 33301 +Epoch: [25] [1410/4276] eta: 2:20:04 lr: 2.027232747412942e-05 loss: 0.1018 (0.1020) time: 2.9367 data: 0.0062 max mem: 33301 +Epoch: [25] [1420/4276] eta: 2:19:35 lr: 2.0269418892745508e-05 loss: 0.0985 (0.1020) time: 2.9379 data: 0.0060 max mem: 33301 +Epoch: [25] [1430/4276] eta: 2:19:05 lr: 2.0266510264986428e-05 loss: 0.1116 (0.1021) time: 2.9369 data: 0.0061 max mem: 33301 +Epoch: [25] [1440/4276] eta: 2:18:36 lr: 2.026360159084403e-05 loss: 0.0963 (0.1021) time: 2.9341 data: 0.0060 max mem: 33301 +Epoch: [25] [1450/4276] eta: 2:18:07 lr: 2.0260692870310187e-05 loss: 0.0932 (0.1021) time: 2.9416 data: 0.0060 max mem: 33301 +Epoch: [25] [1460/4276] eta: 2:17:38 lr: 2.0257784103376764e-05 loss: 0.0871 (0.1020) time: 2.9423 data: 0.0061 max mem: 33301 +Epoch: [25] [1470/4276] eta: 2:17:08 lr: 2.02548752900356e-05 loss: 0.0964 (0.1020) time: 2.9333 data: 0.0061 max mem: 33301 +Epoch: [25] [1480/4276] eta: 2:16:38 lr: 2.0251966430278567e-05 loss: 0.0964 (0.1020) time: 2.9155 data: 0.0063 max mem: 33301 +Epoch: [25] [1490/4276] eta: 2:16:08 lr: 2.0249057524097504e-05 loss: 0.0897 (0.1019) time: 2.8883 data: 0.0064 max mem: 33301 +Epoch: [25] [1500/4276] eta: 2:15:38 lr: 2.024614857148427e-05 loss: 0.0956 (0.1020) time: 2.8781 data: 0.0064 max mem: 33301 +Epoch: [25] [1510/4276] eta: 2:15:07 lr: 2.02432395724307e-05 loss: 0.0956 (0.1019) time: 2.8778 data: 0.0066 max mem: 33301 +Epoch: [25] [1520/4276] eta: 2:14:37 lr: 2.0240330526928645e-05 loss: 0.0931 (0.1019) time: 2.8860 data: 0.0067 max mem: 33301 +Epoch: [25] [1530/4276] eta: 2:14:08 lr: 2.0237421434969943e-05 loss: 0.0876 (0.1018) time: 2.9053 data: 0.0069 max mem: 33301 +Epoch: [25] [1540/4276] eta: 2:13:39 lr: 2.023451229654644e-05 loss: 0.0901 (0.1018) time: 2.9281 data: 0.0074 max mem: 33301 +Epoch: [25] [1550/4276] eta: 2:13:10 lr: 2.0231603111649953e-05 loss: 0.0951 (0.1017) time: 2.9387 data: 0.0073 max mem: 33301 +Epoch: [25] [1560/4276] eta: 2:12:40 lr: 2.0228693880272325e-05 loss: 0.0972 (0.1018) time: 2.9374 data: 0.0070 max mem: 33301 +Epoch: [25] [1570/4276] eta: 2:12:11 lr: 2.022578460240539e-05 loss: 0.0986 (0.1018) time: 2.9372 data: 0.0073 max mem: 33301 +Epoch: [25] [1580/4276] eta: 2:11:42 lr: 2.022287527804097e-05 loss: 0.1009 (0.1018) time: 2.9371 data: 0.0075 max mem: 33301 +Epoch: [25] [1590/4276] eta: 2:11:13 lr: 2.0219965907170888e-05 loss: 0.0995 (0.1018) time: 2.9362 data: 0.0073 max mem: 33301 +Epoch: [25] [1600/4276] eta: 2:10:43 lr: 2.0217056489786966e-05 loss: 0.0995 (0.1018) time: 2.9354 data: 0.0071 max mem: 33301 +Epoch: [25] [1610/4276] eta: 2:10:14 lr: 2.0214147025881023e-05 loss: 0.1007 (0.1018) time: 2.9340 data: 0.0074 max mem: 33301 +Epoch: [25] [1620/4276] eta: 2:09:45 lr: 2.021123751544488e-05 loss: 0.0972 (0.1018) time: 2.9252 data: 0.0077 max mem: 33301 +Epoch: [25] [1630/4276] eta: 2:09:15 lr: 2.0208327958470338e-05 loss: 0.0967 (0.1018) time: 2.9198 data: 0.0073 max mem: 33301 +Epoch: [25] [1640/4276] eta: 2:08:46 lr: 2.0205418354949218e-05 loss: 0.0911 (0.1016) time: 2.9229 data: 0.0072 max mem: 33301 +Epoch: [25] [1650/4276] eta: 2:08:16 lr: 2.020250870487332e-05 loss: 0.0880 (0.1016) time: 2.9231 data: 0.0075 max mem: 33301 +Epoch: [25] [1660/4276] eta: 2:07:46 lr: 2.0199599008234464e-05 loss: 0.0902 (0.1016) time: 2.9017 data: 0.0072 max mem: 33301 +Epoch: [25] [1670/4276] eta: 2:07:16 lr: 2.019668926502443e-05 loss: 0.0902 (0.1015) time: 2.8744 data: 0.0067 max mem: 33301 +Epoch: [25] [1680/4276] eta: 2:06:46 lr: 2.0193779475235034e-05 loss: 0.0941 (0.1015) time: 2.8658 data: 0.0066 max mem: 33301 +Epoch: [25] [1690/4276] eta: 2:06:16 lr: 2.0190869638858065e-05 loss: 0.0941 (0.1014) time: 2.8727 data: 0.0068 max mem: 33301 +Epoch: [25] [1700/4276] eta: 2:05:45 lr: 2.0187959755885323e-05 loss: 0.0927 (0.1014) time: 2.8731 data: 0.0066 max mem: 33301 +Epoch: [25] [1710/4276] eta: 2:05:15 lr: 2.018504982630859e-05 loss: 0.0886 (0.1013) time: 2.8654 data: 0.0062 max mem: 33301 +Epoch: [25] [1720/4276] eta: 2:04:45 lr: 2.018213985011966e-05 loss: 0.0886 (0.1013) time: 2.8666 data: 0.0064 max mem: 33301 +Epoch: [25] [1730/4276] eta: 2:04:15 lr: 2.0179229827310314e-05 loss: 0.0887 (0.1012) time: 2.8811 data: 0.0069 max mem: 33301 +Epoch: [25] [1740/4276] eta: 2:03:46 lr: 2.017631975787235e-05 loss: 0.0870 (0.1012) time: 2.9086 data: 0.0074 max mem: 33301 +Epoch: [25] [1750/4276] eta: 2:03:16 lr: 2.0173409641797525e-05 loss: 0.0933 (0.1011) time: 2.9225 data: 0.0074 max mem: 33301 +Epoch: [25] [1760/4276] eta: 2:02:47 lr: 2.017049947907763e-05 loss: 0.0894 (0.1011) time: 2.9242 data: 0.0075 max mem: 33301 +Epoch: [25] [1770/4276] eta: 2:02:18 lr: 2.0167589269704445e-05 loss: 0.0890 (0.1010) time: 2.9223 data: 0.0079 max mem: 33301 +Epoch: [25] [1780/4276] eta: 2:01:48 lr: 2.0164679013669725e-05 loss: 0.0890 (0.1011) time: 2.9231 data: 0.0079 max mem: 33301 +Epoch: [25] [1790/4276] eta: 2:01:19 lr: 2.0161768710965253e-05 loss: 0.0862 (0.1010) time: 2.9258 data: 0.0076 max mem: 33301 +Epoch: [25] [1800/4276] eta: 2:00:50 lr: 2.0158858361582786e-05 loss: 0.0840 (0.1009) time: 2.9216 data: 0.0072 max mem: 33301 +Epoch: [25] [1810/4276] eta: 2:00:20 lr: 2.0155947965514096e-05 loss: 0.0921 (0.1010) time: 2.9181 data: 0.0073 max mem: 33301 +Epoch: [25] [1820/4276] eta: 1:59:51 lr: 2.0153037522750937e-05 loss: 0.0989 (0.1009) time: 2.9284 data: 0.0075 max mem: 33301 +Epoch: [25] [1830/4276] eta: 1:59:22 lr: 2.0150127033285067e-05 loss: 0.0904 (0.1009) time: 2.9307 data: 0.0074 max mem: 33301 +Epoch: [25] [1840/4276] eta: 1:58:52 lr: 2.0147216497108244e-05 loss: 0.0863 (0.1009) time: 2.9232 data: 0.0074 max mem: 33301 +Epoch: [25] [1850/4276] eta: 1:58:23 lr: 2.014430591421222e-05 loss: 0.0873 (0.1009) time: 2.9243 data: 0.0075 max mem: 33301 +Epoch: [25] [1860/4276] eta: 1:57:54 lr: 2.0141395284588745e-05 loss: 0.0984 (0.1009) time: 2.9238 data: 0.0076 max mem: 33301 +Epoch: [25] [1870/4276] eta: 1:57:24 lr: 2.013848460822956e-05 loss: 0.0993 (0.1010) time: 2.9229 data: 0.0073 max mem: 33301 +Epoch: [25] [1880/4276] eta: 1:56:55 lr: 2.0135573885126418e-05 loss: 0.0898 (0.1009) time: 2.9234 data: 0.0071 max mem: 33301 +Epoch: [25] [1890/4276] eta: 1:56:26 lr: 2.0132663115271057e-05 loss: 0.0918 (0.1009) time: 2.9240 data: 0.0074 max mem: 33301 +Epoch: [25] [1900/4276] eta: 1:55:56 lr: 2.012975229865521e-05 loss: 0.0948 (0.1009) time: 2.9251 data: 0.0076 max mem: 33301 +Epoch: [25] [1910/4276] eta: 1:55:27 lr: 2.0126841435270615e-05 loss: 0.0912 (0.1009) time: 2.9245 data: 0.0071 max mem: 33301 +Epoch: [25] [1920/4276] eta: 1:54:58 lr: 2.0123930525109007e-05 loss: 0.0892 (0.1009) time: 2.9243 data: 0.0068 max mem: 33301 +Epoch: [25] [1930/4276] eta: 1:54:28 lr: 2.0121019568162123e-05 loss: 0.0874 (0.1008) time: 2.9190 data: 0.0071 max mem: 33301 +Epoch: [25] [1940/4276] eta: 1:53:59 lr: 2.0118108564421677e-05 loss: 0.0950 (0.1008) time: 2.9181 data: 0.0073 max mem: 33301 +Epoch: [25] [1950/4276] eta: 1:53:30 lr: 2.0115197513879397e-05 loss: 0.1042 (0.1008) time: 2.9230 data: 0.0071 max mem: 33301 +Epoch: [25] [1960/4276] eta: 1:53:00 lr: 2.0112286416527004e-05 loss: 0.1042 (0.1008) time: 2.9232 data: 0.0068 max mem: 33301 +Epoch: [25] [1970/4276] eta: 1:52:31 lr: 2.010937527235623e-05 loss: 0.0826 (0.1007) time: 2.9252 data: 0.0070 max mem: 33301 +Epoch: [25] [1980/4276] eta: 1:52:02 lr: 2.010646408135877e-05 loss: 0.0844 (0.1007) time: 2.9273 data: 0.0071 max mem: 33301 +Epoch: [25] [1990/4276] eta: 1:51:32 lr: 2.0103552843526353e-05 loss: 0.0977 (0.1007) time: 2.9262 data: 0.0069 max mem: 33301 +Epoch: [25] [2000/4276] eta: 1:51:03 lr: 2.010064155885068e-05 loss: 0.0981 (0.1007) time: 2.9206 data: 0.0068 max mem: 33301 +Epoch: [25] [2010/4276] eta: 1:50:34 lr: 2.0097730227323468e-05 loss: 0.0928 (0.1007) time: 2.9224 data: 0.0070 max mem: 33301 +Epoch: [25] [2020/4276] eta: 1:50:04 lr: 2.0094818848936412e-05 loss: 0.1065 (0.1007) time: 2.9270 data: 0.0070 max mem: 33301 +Epoch: [25] [2030/4276] eta: 1:49:35 lr: 2.009190742368122e-05 loss: 0.0971 (0.1007) time: 2.9249 data: 0.0066 max mem: 33301 +Epoch: [25] [2040/4276] eta: 1:49:06 lr: 2.008899595154959e-05 loss: 0.0872 (0.1007) time: 2.9235 data: 0.0066 max mem: 33301 +Epoch: [25] [2050/4276] eta: 1:48:36 lr: 2.008608443253322e-05 loss: 0.1059 (0.1007) time: 2.9246 data: 0.0068 max mem: 33301 +Epoch: [25] [2060/4276] eta: 1:48:07 lr: 2.0083172866623797e-05 loss: 0.1001 (0.1007) time: 2.9279 data: 0.0069 max mem: 33301 +Epoch: [25] [2070/4276] eta: 1:47:38 lr: 2.0080261253813018e-05 loss: 0.0881 (0.1007) time: 2.9225 data: 0.0067 max mem: 33301 +Epoch: [25] [2080/4276] eta: 1:47:08 lr: 2.0077349594092574e-05 loss: 0.0939 (0.1007) time: 2.9203 data: 0.0067 max mem: 33301 +Epoch: [25] [2090/4276] eta: 1:46:39 lr: 2.0074437887454142e-05 loss: 0.1026 (0.1008) time: 2.9294 data: 0.0069 max mem: 33301 +Epoch: [25] [2100/4276] eta: 1:46:10 lr: 2.0071526133889407e-05 loss: 0.1026 (0.1008) time: 2.9281 data: 0.0068 max mem: 33301 +Epoch: [25] [2110/4276] eta: 1:45:41 lr: 2.006861433339005e-05 loss: 0.0940 (0.1007) time: 2.9234 data: 0.0066 max mem: 33301 +Epoch: [25] [2120/4276] eta: 1:45:11 lr: 2.0065702485947747e-05 loss: 0.0881 (0.1006) time: 2.9246 data: 0.0065 max mem: 33301 +Epoch: [25] [2130/4276] eta: 1:44:42 lr: 2.0062790591554173e-05 loss: 0.0827 (0.1006) time: 2.9246 data: 0.0066 max mem: 33301 +Epoch: [25] [2140/4276] eta: 1:44:13 lr: 2.0059878650200997e-05 loss: 0.0884 (0.1005) time: 2.9237 data: 0.0068 max mem: 33301 +Epoch: [25] [2150/4276] eta: 1:43:43 lr: 2.0056966661879888e-05 loss: 0.0884 (0.1005) time: 2.9257 data: 0.0066 max mem: 33301 +Epoch: [25] [2160/4276] eta: 1:43:14 lr: 2.005405462658252e-05 loss: 0.0910 (0.1004) time: 2.9284 data: 0.0065 max mem: 33301 +Epoch: [25] [2170/4276] eta: 1:42:45 lr: 2.005114254430054e-05 loss: 0.0910 (0.1004) time: 2.9297 data: 0.0068 max mem: 33301 +Epoch: [25] [2180/4276] eta: 1:42:16 lr: 2.0048230415025613e-05 loss: 0.0883 (0.1004) time: 2.9281 data: 0.0069 max mem: 33301 +Epoch: [25] [2190/4276] eta: 1:41:46 lr: 2.00453182387494e-05 loss: 0.0878 (0.1003) time: 2.9268 data: 0.0068 max mem: 33301 +Epoch: [25] [2200/4276] eta: 1:41:17 lr: 2.004240601546356e-05 loss: 0.0973 (0.1004) time: 2.9274 data: 0.0069 max mem: 33301 +Epoch: [25] [2210/4276] eta: 1:40:48 lr: 2.003949374515973e-05 loss: 0.1092 (0.1004) time: 2.9274 data: 0.0071 max mem: 33301 +Epoch: [25] [2220/4276] eta: 1:40:18 lr: 2.0036581427829567e-05 loss: 0.1029 (0.1004) time: 2.9273 data: 0.0071 max mem: 33301 +Epoch: [25] [2230/4276] eta: 1:39:49 lr: 2.0033669063464716e-05 loss: 0.0902 (0.1004) time: 2.9273 data: 0.0070 max mem: 33301 +Epoch: [25] [2240/4276] eta: 1:39:20 lr: 2.0030756652056826e-05 loss: 0.0876 (0.1004) time: 2.9268 data: 0.0070 max mem: 33301 +Epoch: [25] [2250/4276] eta: 1:38:50 lr: 2.0027844193597524e-05 loss: 0.0824 (0.1003) time: 2.9066 data: 0.0073 max mem: 33301 +Epoch: [25] [2260/4276] eta: 1:38:21 lr: 2.0024931688078453e-05 loss: 0.0889 (0.1003) time: 2.8982 data: 0.0070 max mem: 33301 +Epoch: [25] [2270/4276] eta: 1:37:52 lr: 2.002201913549125e-05 loss: 0.0895 (0.1003) time: 2.9198 data: 0.0065 max mem: 33301 +Epoch: [25] [2280/4276] eta: 1:37:22 lr: 2.0019106535827546e-05 loss: 0.0934 (0.1003) time: 2.9295 data: 0.0063 max mem: 33301 +Epoch: [25] [2290/4276] eta: 1:36:53 lr: 2.0016193889078966e-05 loss: 0.0923 (0.1003) time: 2.9272 data: 0.0060 max mem: 33301 +Epoch: [25] [2300/4276] eta: 1:36:24 lr: 2.0013281195237135e-05 loss: 0.0884 (0.1003) time: 2.9272 data: 0.0060 max mem: 33301 +Epoch: [25] [2310/4276] eta: 1:35:55 lr: 2.0010368454293683e-05 loss: 0.0928 (0.1003) time: 2.9287 data: 0.0060 max mem: 33301 +Epoch: [25] [2320/4276] eta: 1:35:25 lr: 2.0007455666240227e-05 loss: 0.1042 (0.1003) time: 2.9278 data: 0.0060 max mem: 33301 +Epoch: [25] [2330/4276] eta: 1:34:56 lr: 2.0004542831068378e-05 loss: 0.1093 (0.1004) time: 2.9253 data: 0.0060 max mem: 33301 +Epoch: [25] [2340/4276] eta: 1:34:27 lr: 2.000162994876976e-05 loss: 0.1077 (0.1004) time: 2.9231 data: 0.0062 max mem: 33301 +Epoch: [25] [2350/4276] eta: 1:33:57 lr: 1.9998717019335975e-05 loss: 0.0882 (0.1004) time: 2.9238 data: 0.0062 max mem: 33301 +Epoch: [25] [2360/4276] eta: 1:33:28 lr: 1.9995804042758647e-05 loss: 0.0829 (0.1003) time: 2.9267 data: 0.0060 max mem: 33301 +Epoch: [25] [2370/4276] eta: 1:32:59 lr: 1.9992891019029363e-05 loss: 0.0938 (0.1004) time: 2.9274 data: 0.0060 max mem: 33301 +Epoch: [25] [2380/4276] eta: 1:32:30 lr: 1.9989977948139733e-05 loss: 0.1071 (0.1004) time: 2.9278 data: 0.0060 max mem: 33301 +Epoch: [25] [2390/4276] eta: 1:32:00 lr: 1.9987064830081364e-05 loss: 0.1034 (0.1004) time: 2.9224 data: 0.0062 max mem: 33301 +Epoch: [25] [2400/4276] eta: 1:31:31 lr: 1.9984151664845844e-05 loss: 0.1164 (0.1005) time: 2.9246 data: 0.0063 max mem: 33301 +Epoch: [25] [2410/4276] eta: 1:31:02 lr: 1.998123845242477e-05 loss: 0.1057 (0.1005) time: 2.9298 data: 0.0060 max mem: 33301 +Epoch: [25] [2420/4276] eta: 1:30:32 lr: 1.9978325192809737e-05 loss: 0.0933 (0.1005) time: 2.9283 data: 0.0060 max mem: 33301 +Epoch: [25] [2430/4276] eta: 1:30:03 lr: 1.9975411885992335e-05 loss: 0.0988 (0.1005) time: 2.9283 data: 0.0061 max mem: 33301 +Epoch: [25] [2440/4276] eta: 1:29:34 lr: 1.997249853196414e-05 loss: 0.1082 (0.1005) time: 2.9250 data: 0.0062 max mem: 33301 +Epoch: [25] [2450/4276] eta: 1:29:05 lr: 1.9969585130716745e-05 loss: 0.0903 (0.1005) time: 2.9252 data: 0.0062 max mem: 33301 +Epoch: [25] [2460/4276] eta: 1:28:35 lr: 1.9966671682241726e-05 loss: 0.0944 (0.1005) time: 2.9242 data: 0.0060 max mem: 33301 +Epoch: [25] [2470/4276] eta: 1:28:06 lr: 1.9963758186530664e-05 loss: 0.1005 (0.1005) time: 2.8967 data: 0.0067 max mem: 33301 +Epoch: [25] [2480/4276] eta: 1:27:36 lr: 1.9960844643575126e-05 loss: 0.1012 (0.1005) time: 2.8920 data: 0.0075 max mem: 33301 +Epoch: [25] [2490/4276] eta: 1:27:07 lr: 1.9957931053366683e-05 loss: 0.1029 (0.1006) time: 2.9039 data: 0.0079 max mem: 33301 +Epoch: [25] [2500/4276] eta: 1:26:37 lr: 1.9955017415896912e-05 loss: 0.1017 (0.1006) time: 2.9121 data: 0.0072 max mem: 33301 +Epoch: [25] [2510/4276] eta: 1:26:08 lr: 1.995210373115738e-05 loss: 0.0969 (0.1005) time: 2.9278 data: 0.0064 max mem: 33301 +Epoch: [25] [2520/4276] eta: 1:25:39 lr: 1.994918999913964e-05 loss: 0.0910 (0.1005) time: 2.9290 data: 0.0065 max mem: 33301 +Epoch: [25] [2530/4276] eta: 1:25:10 lr: 1.9946276219835252e-05 loss: 0.0837 (0.1004) time: 2.9210 data: 0.0064 max mem: 33301 +Epoch: [25] [2540/4276] eta: 1:24:40 lr: 1.9943362393235783e-05 loss: 0.0890 (0.1004) time: 2.9199 data: 0.0065 max mem: 33301 +Epoch: [25] [2550/4276] eta: 1:24:11 lr: 1.9940448519332784e-05 loss: 0.0923 (0.1003) time: 2.9272 data: 0.0065 max mem: 33301 +Epoch: [25] [2560/4276] eta: 1:23:42 lr: 1.99375345981178e-05 loss: 0.0789 (0.1003) time: 2.9268 data: 0.0063 max mem: 33301 +Epoch: [25] [2570/4276] eta: 1:23:13 lr: 1.9934620629582387e-05 loss: 0.0790 (0.1003) time: 2.9280 data: 0.0065 max mem: 33301 +Epoch: [25] [2580/4276] eta: 1:22:43 lr: 1.9931706613718085e-05 loss: 0.0837 (0.1002) time: 2.9269 data: 0.0064 max mem: 33301 +Epoch: [25] [2590/4276] eta: 1:22:14 lr: 1.9928792550516446e-05 loss: 0.0886 (0.1002) time: 2.9257 data: 0.0063 max mem: 33301 +Epoch: [25] [2600/4276] eta: 1:21:45 lr: 1.9925878439968996e-05 loss: 0.0886 (0.1002) time: 2.9270 data: 0.0064 max mem: 33301 +Epoch: [25] [2610/4276] eta: 1:21:15 lr: 1.9922964282067278e-05 loss: 0.0899 (0.1001) time: 2.9289 data: 0.0065 max mem: 33301 +Epoch: [25] [2620/4276] eta: 1:20:46 lr: 1.9920050076802828e-05 loss: 0.0899 (0.1001) time: 2.9285 data: 0.0064 max mem: 33301 +Epoch: [25] [2630/4276] eta: 1:20:17 lr: 1.9917135824167183e-05 loss: 0.0905 (0.1001) time: 2.9291 data: 0.0063 max mem: 33301 +Epoch: [25] [2640/4276] eta: 1:19:48 lr: 1.991422152415186e-05 loss: 0.0853 (0.1000) time: 2.9295 data: 0.0063 max mem: 33301 +Epoch: [25] [2650/4276] eta: 1:19:18 lr: 1.9911307176748382e-05 loss: 0.0825 (0.1000) time: 2.9297 data: 0.0064 max mem: 33301 +Epoch: [25] [2660/4276] eta: 1:18:49 lr: 1.990839278194829e-05 loss: 0.0850 (0.1000) time: 2.9325 data: 0.0064 max mem: 33301 +Epoch: [25] [2670/4276] eta: 1:18:20 lr: 1.9905478339743086e-05 loss: 0.1092 (0.1000) time: 2.9296 data: 0.0062 max mem: 33301 +Epoch: [25] [2680/4276] eta: 1:17:51 lr: 1.9902563850124293e-05 loss: 0.1035 (0.1000) time: 2.9268 data: 0.0063 max mem: 33301 +Epoch: [25] [2690/4276] eta: 1:17:21 lr: 1.989964931308342e-05 loss: 0.0937 (0.1000) time: 2.9288 data: 0.0065 max mem: 33301 +Epoch: [25] [2700/4276] eta: 1:16:52 lr: 1.9896734728611993e-05 loss: 0.0886 (0.1000) time: 2.9298 data: 0.0066 max mem: 33301 +Epoch: [25] [2710/4276] eta: 1:16:23 lr: 1.98938200967015e-05 loss: 0.0845 (0.0999) time: 2.9285 data: 0.0066 max mem: 33301 +Epoch: [25] [2720/4276] eta: 1:15:54 lr: 1.9890905417343457e-05 loss: 0.0778 (0.0998) time: 2.9272 data: 0.0065 max mem: 33301 +Epoch: [25] [2730/4276] eta: 1:15:24 lr: 1.988799069052937e-05 loss: 0.1015 (0.0999) time: 2.9283 data: 0.0066 max mem: 33301 +Epoch: [25] [2740/4276] eta: 1:14:55 lr: 1.988507591625073e-05 loss: 0.1078 (0.0999) time: 2.9261 data: 0.0067 max mem: 33301 +Epoch: [25] [2750/4276] eta: 1:14:26 lr: 1.988216109449903e-05 loss: 0.0906 (0.0999) time: 2.8977 data: 0.0065 max mem: 33301 +Epoch: [25] [2760/4276] eta: 1:13:56 lr: 1.9879246225265777e-05 loss: 0.0906 (0.0999) time: 2.9019 data: 0.0073 max mem: 33301 +Epoch: [25] [2770/4276] eta: 1:13:27 lr: 1.987633130854245e-05 loss: 0.0963 (0.0999) time: 2.9303 data: 0.0081 max mem: 33301 +Epoch: [25] [2780/4276] eta: 1:12:58 lr: 1.987341634432055e-05 loss: 0.1006 (0.0999) time: 2.9234 data: 0.0079 max mem: 33301 +Epoch: [25] [2790/4276] eta: 1:12:29 lr: 1.9870501332591544e-05 loss: 0.1036 (0.0999) time: 2.9244 data: 0.0076 max mem: 33301 +Epoch: [25] [2800/4276] eta: 1:11:59 lr: 1.986758627334692e-05 loss: 0.0918 (0.0999) time: 2.9206 data: 0.0074 max mem: 33301 +Epoch: [25] [2810/4276] eta: 1:11:30 lr: 1.9864671166578164e-05 loss: 0.0799 (0.0998) time: 2.9104 data: 0.0075 max mem: 33301 +Epoch: [25] [2820/4276] eta: 1:11:01 lr: 1.986175601227675e-05 loss: 0.0789 (0.0997) time: 2.9208 data: 0.0075 max mem: 33301 +Epoch: [25] [2830/4276] eta: 1:10:31 lr: 1.9858840810434144e-05 loss: 0.0884 (0.0997) time: 2.9305 data: 0.0073 max mem: 33301 +Epoch: [25] [2840/4276] eta: 1:10:02 lr: 1.985592556104182e-05 loss: 0.0927 (0.0997) time: 2.9303 data: 0.0072 max mem: 33301 +Epoch: [25] [2850/4276] eta: 1:09:33 lr: 1.9853010264091244e-05 loss: 0.1021 (0.0998) time: 2.9303 data: 0.0074 max mem: 33301 +Epoch: [25] [2860/4276] eta: 1:09:04 lr: 1.985009491957389e-05 loss: 0.0952 (0.0998) time: 2.9308 data: 0.0074 max mem: 33301 +Epoch: [25] [2870/4276] eta: 1:08:34 lr: 1.9847179527481204e-05 loss: 0.0998 (0.0998) time: 2.9305 data: 0.0072 max mem: 33301 +Epoch: [25] [2880/4276] eta: 1:08:05 lr: 1.9844264087804656e-05 loss: 0.0949 (0.0998) time: 2.9314 data: 0.0073 max mem: 33301 +Epoch: [25] [2890/4276] eta: 1:07:36 lr: 1.9841348600535694e-05 loss: 0.0868 (0.0998) time: 2.9331 data: 0.0076 max mem: 33301 +Epoch: [25] [2900/4276] eta: 1:07:07 lr: 1.983843306566578e-05 loss: 0.0829 (0.0997) time: 2.9313 data: 0.0075 max mem: 33301 +Epoch: [25] [2910/4276] eta: 1:06:37 lr: 1.983551748318635e-05 loss: 0.0873 (0.0997) time: 2.9289 data: 0.0072 max mem: 33301 +Epoch: [25] [2920/4276] eta: 1:06:08 lr: 1.983260185308886e-05 loss: 0.0960 (0.0997) time: 2.9310 data: 0.0073 max mem: 33301 +Epoch: [25] [2930/4276] eta: 1:05:39 lr: 1.9829686175364754e-05 loss: 0.0930 (0.0997) time: 2.9328 data: 0.0076 max mem: 33301 +Epoch: [25] [2940/4276] eta: 1:05:10 lr: 1.9826770450005473e-05 loss: 0.0921 (0.0997) time: 2.9334 data: 0.0076 max mem: 33301 +Epoch: [25] [2950/4276] eta: 1:04:40 lr: 1.982385467700245e-05 loss: 0.0937 (0.0997) time: 2.9343 data: 0.0073 max mem: 33301 +Epoch: [25] [2960/4276] eta: 1:04:11 lr: 1.982093885634712e-05 loss: 0.0929 (0.0997) time: 2.9354 data: 0.0073 max mem: 33301 +Epoch: [25] [2970/4276] eta: 1:03:42 lr: 1.9818022988030925e-05 loss: 0.0949 (0.0997) time: 2.9335 data: 0.0075 max mem: 33301 +Epoch: [25] [2980/4276] eta: 1:03:13 lr: 1.9815107072045284e-05 loss: 0.1007 (0.0997) time: 2.9289 data: 0.0075 max mem: 33301 +Epoch: [25] [2990/4276] eta: 1:02:43 lr: 1.981219110838162e-05 loss: 0.1007 (0.0997) time: 2.9289 data: 0.0073 max mem: 33301 +Epoch: [25] [3000/4276] eta: 1:02:14 lr: 1.9809275097031366e-05 loss: 0.0956 (0.0997) time: 2.9280 data: 0.0071 max mem: 33301 +Epoch: [25] [3010/4276] eta: 1:01:45 lr: 1.9806359037985943e-05 loss: 0.0956 (0.0997) time: 2.9293 data: 0.0070 max mem: 33301 +Epoch: [25] [3020/4276] eta: 1:01:16 lr: 1.980344293123676e-05 loss: 0.1102 (0.0997) time: 2.9246 data: 0.0068 max mem: 33301 +Epoch: [25] [3030/4276] eta: 1:00:46 lr: 1.9800526776775236e-05 loss: 0.0928 (0.0997) time: 2.9251 data: 0.0069 max mem: 33301 +Epoch: [25] [3040/4276] eta: 1:00:17 lr: 1.9797610574592778e-05 loss: 0.1048 (0.0997) time: 2.9326 data: 0.0067 max mem: 33301 +Epoch: [25] [3050/4276] eta: 0:59:48 lr: 1.9794694324680806e-05 loss: 0.0969 (0.0997) time: 2.9244 data: 0.0064 max mem: 33301 +Epoch: [25] [3060/4276] eta: 0:59:18 lr: 1.979177802703071e-05 loss: 0.0762 (0.0996) time: 2.9025 data: 0.0063 max mem: 33301 +Epoch: [25] [3070/4276] eta: 0:58:49 lr: 1.9788861681633904e-05 loss: 0.0840 (0.0996) time: 2.9036 data: 0.0067 max mem: 33301 +Epoch: [25] [3080/4276] eta: 0:58:20 lr: 1.978594528848178e-05 loss: 0.0874 (0.0996) time: 2.9228 data: 0.0070 max mem: 33301 +Epoch: [25] [3090/4276] eta: 0:57:51 lr: 1.9783028847565745e-05 loss: 0.0822 (0.0996) time: 2.9275 data: 0.0067 max mem: 33301 +Epoch: [25] [3100/4276] eta: 0:57:21 lr: 1.978011235887718e-05 loss: 0.0912 (0.0996) time: 2.9280 data: 0.0066 max mem: 33301 +Epoch: [25] [3110/4276] eta: 0:56:52 lr: 1.977719582240748e-05 loss: 0.0831 (0.0995) time: 2.9272 data: 0.0066 max mem: 33301 +Epoch: [25] [3120/4276] eta: 0:56:23 lr: 1.977427923814804e-05 loss: 0.0798 (0.0995) time: 2.9275 data: 0.0067 max mem: 33301 +Epoch: [25] [3130/4276] eta: 0:55:53 lr: 1.9771362606090242e-05 loss: 0.0814 (0.0995) time: 2.9291 data: 0.0069 max mem: 33301 +Epoch: [25] [3140/4276] eta: 0:55:24 lr: 1.9768445926225458e-05 loss: 0.0866 (0.0994) time: 2.9290 data: 0.0068 max mem: 33301 +Epoch: [25] [3150/4276] eta: 0:54:55 lr: 1.9765529198545073e-05 loss: 0.0918 (0.0995) time: 2.9268 data: 0.0066 max mem: 33301 +Epoch: [25] [3160/4276] eta: 0:54:26 lr: 1.976261242304047e-05 loss: 0.0935 (0.0995) time: 2.9268 data: 0.0068 max mem: 33301 +Epoch: [25] [3170/4276] eta: 0:53:56 lr: 1.9759695599703016e-05 loss: 0.0943 (0.0995) time: 2.9280 data: 0.0070 max mem: 33301 +Epoch: [25] [3180/4276] eta: 0:53:27 lr: 1.9756778728524076e-05 loss: 0.1026 (0.0995) time: 2.9289 data: 0.0068 max mem: 33301 +Epoch: [25] [3190/4276] eta: 0:52:58 lr: 1.9753861809495023e-05 loss: 0.1025 (0.0995) time: 2.9289 data: 0.0066 max mem: 33301 +Epoch: [25] [3200/4276] eta: 0:52:29 lr: 1.975094484260722e-05 loss: 0.0936 (0.0995) time: 2.9270 data: 0.0066 max mem: 33301 +Epoch: [25] [3210/4276] eta: 0:51:59 lr: 1.974802782785203e-05 loss: 0.0937 (0.0995) time: 2.9263 data: 0.0066 max mem: 33301 +Epoch: [25] [3220/4276] eta: 0:51:30 lr: 1.9745110765220805e-05 loss: 0.1036 (0.0995) time: 2.9274 data: 0.0064 max mem: 33301 +Epoch: [25] [3230/4276] eta: 0:51:01 lr: 1.9742193654704904e-05 loss: 0.0952 (0.0995) time: 2.9267 data: 0.0064 max mem: 33301 +Epoch: [25] [3240/4276] eta: 0:50:32 lr: 1.973927649629568e-05 loss: 0.1041 (0.0996) time: 2.9161 data: 0.0067 max mem: 33301 +Epoch: [25] [3250/4276] eta: 0:50:02 lr: 1.9736359289984485e-05 loss: 0.1025 (0.0995) time: 2.9111 data: 0.0069 max mem: 33301 +Epoch: [25] [3260/4276] eta: 0:49:33 lr: 1.9733442035762657e-05 loss: 0.0933 (0.0995) time: 2.9214 data: 0.0066 max mem: 33301 +Epoch: [25] [3270/4276] eta: 0:49:04 lr: 1.9730524733621544e-05 loss: 0.1055 (0.0995) time: 2.9234 data: 0.0064 max mem: 33301 +Epoch: [25] [3280/4276] eta: 0:48:34 lr: 1.9727607383552487e-05 loss: 0.1055 (0.0995) time: 2.9258 data: 0.0067 max mem: 33301 +Epoch: [25] [3290/4276] eta: 0:48:05 lr: 1.972468998554682e-05 loss: 0.0938 (0.0995) time: 2.9300 data: 0.0068 max mem: 33301 +Epoch: [25] [3300/4276] eta: 0:47:36 lr: 1.972177253959588e-05 loss: 0.1030 (0.0996) time: 2.9266 data: 0.0065 max mem: 33301 +Epoch: [25] [3310/4276] eta: 0:47:07 lr: 1.9718855045690992e-05 loss: 0.1086 (0.0996) time: 2.9224 data: 0.0063 max mem: 33301 +Epoch: [25] [3320/4276] eta: 0:46:37 lr: 1.9715937503823498e-05 loss: 0.1053 (0.0996) time: 2.9273 data: 0.0062 max mem: 33301 +Epoch: [25] [3330/4276] eta: 0:46:08 lr: 1.9713019913984706e-05 loss: 0.1033 (0.0996) time: 2.9378 data: 0.0064 max mem: 33301 +Epoch: [25] [3340/4276] eta: 0:45:39 lr: 1.971010227616595e-05 loss: 0.0999 (0.0996) time: 2.9401 data: 0.0063 max mem: 33301 +Epoch: [25] [3350/4276] eta: 0:45:10 lr: 1.9707184590358545e-05 loss: 0.0942 (0.0996) time: 2.9379 data: 0.0062 max mem: 33301 +Epoch: [25] [3360/4276] eta: 0:44:40 lr: 1.9704266856553812e-05 loss: 0.0873 (0.0996) time: 2.9380 data: 0.0063 max mem: 33301 +Epoch: [25] [3370/4276] eta: 0:44:11 lr: 1.9701349074743056e-05 loss: 0.1062 (0.0997) time: 2.9402 data: 0.0064 max mem: 33301 +Epoch: [25] [3380/4276] eta: 0:43:42 lr: 1.969843124491759e-05 loss: 0.1044 (0.0997) time: 2.9396 data: 0.0066 max mem: 33301 +Epoch: [25] [3390/4276] eta: 0:43:13 lr: 1.969551336706872e-05 loss: 0.0992 (0.0997) time: 2.9356 data: 0.0063 max mem: 33301 +Epoch: [25] [3400/4276] eta: 0:42:43 lr: 1.9692595441187764e-05 loss: 0.1029 (0.0998) time: 2.9337 data: 0.0062 max mem: 33301 +Epoch: [25] [3410/4276] eta: 0:42:14 lr: 1.9689677467266002e-05 loss: 0.1003 (0.0998) time: 2.9356 data: 0.0063 max mem: 33301 +Epoch: [25] [3420/4276] eta: 0:41:45 lr: 1.9686759445294745e-05 loss: 0.1009 (0.0998) time: 2.9356 data: 0.0062 max mem: 33301 +Epoch: [25] [3430/4276] eta: 0:41:16 lr: 1.9683841375265284e-05 loss: 0.1027 (0.0998) time: 2.9364 data: 0.0061 max mem: 33301 +Epoch: [25] [3440/4276] eta: 0:40:46 lr: 1.968092325716892e-05 loss: 0.0948 (0.0998) time: 2.9376 data: 0.0061 max mem: 33301 +Epoch: [25] [3450/4276] eta: 0:40:17 lr: 1.9678005090996923e-05 loss: 0.0929 (0.0998) time: 2.9146 data: 0.0066 max mem: 33301 +Epoch: [25] [3460/4276] eta: 0:39:48 lr: 1.9675086876740594e-05 loss: 0.1144 (0.0999) time: 2.9075 data: 0.0073 max mem: 33301 +Epoch: [25] [3470/4276] eta: 0:39:19 lr: 1.9672168614391215e-05 loss: 0.0915 (0.0998) time: 2.9320 data: 0.0075 max mem: 33301 +Epoch: [25] [3480/4276] eta: 0:38:49 lr: 1.9669250303940068e-05 loss: 0.0860 (0.0998) time: 2.9407 data: 0.0070 max mem: 33301 +Epoch: [25] [3490/4276] eta: 0:38:20 lr: 1.966633194537842e-05 loss: 0.0987 (0.0998) time: 2.9409 data: 0.0067 max mem: 33301 +Epoch: [25] [3500/4276] eta: 0:37:51 lr: 1.966341353869755e-05 loss: 0.0851 (0.0998) time: 2.9461 data: 0.0072 max mem: 33301 +Epoch: [25] [3510/4276] eta: 0:37:22 lr: 1.966049508388873e-05 loss: 0.0851 (0.0998) time: 2.9443 data: 0.0070 max mem: 33301 +Epoch: [25] [3520/4276] eta: 0:36:52 lr: 1.9657576580943236e-05 loss: 0.0882 (0.0998) time: 2.9222 data: 0.0071 max mem: 33301 +Epoch: [25] [3530/4276] eta: 0:36:23 lr: 1.9654658029852316e-05 loss: 0.0931 (0.0997) time: 2.9222 data: 0.0073 max mem: 33301 +Epoch: [25] [3540/4276] eta: 0:35:54 lr: 1.9651739430607244e-05 loss: 0.0954 (0.0998) time: 2.9391 data: 0.0070 max mem: 33301 +Epoch: [25] [3550/4276] eta: 0:35:25 lr: 1.9648820783199272e-05 loss: 0.0914 (0.0997) time: 2.9396 data: 0.0069 max mem: 33301 +Epoch: [25] [3560/4276] eta: 0:34:55 lr: 1.9645902087619673e-05 loss: 0.0875 (0.0998) time: 2.9387 data: 0.0068 max mem: 33301 +Epoch: [25] [3570/4276] eta: 0:34:26 lr: 1.9642983343859674e-05 loss: 0.0955 (0.0998) time: 2.9390 data: 0.0069 max mem: 33301 +Epoch: [25] [3580/4276] eta: 0:33:57 lr: 1.9640064551910538e-05 loss: 0.0935 (0.0998) time: 2.9388 data: 0.0068 max mem: 33301 +Epoch: [25] [3590/4276] eta: 0:33:28 lr: 1.9637145711763522e-05 loss: 0.0935 (0.0998) time: 2.9370 data: 0.0069 max mem: 33301 +Epoch: [25] [3600/4276] eta: 0:32:58 lr: 1.963422682340985e-05 loss: 0.0909 (0.0998) time: 2.9361 data: 0.0069 max mem: 33301 +Epoch: [25] [3610/4276] eta: 0:32:29 lr: 1.963130788684077e-05 loss: 0.0883 (0.0998) time: 2.9377 data: 0.0069 max mem: 33301 +Epoch: [25] [3620/4276] eta: 0:32:00 lr: 1.9628388902047524e-05 loss: 0.0929 (0.0998) time: 2.9395 data: 0.0070 max mem: 33301 +Epoch: [25] [3630/4276] eta: 0:31:31 lr: 1.9625469869021352e-05 loss: 0.0964 (0.0998) time: 2.9384 data: 0.0069 max mem: 33301 +Epoch: [25] [3640/4276] eta: 0:31:01 lr: 1.962255078775347e-05 loss: 0.0873 (0.0997) time: 2.9386 data: 0.0069 max mem: 33301 +Epoch: [25] [3650/4276] eta: 0:30:32 lr: 1.961963165823511e-05 loss: 0.0819 (0.0997) time: 2.9386 data: 0.0069 max mem: 33301 +Epoch: [25] [3660/4276] eta: 0:30:03 lr: 1.961671248045751e-05 loss: 0.0879 (0.0997) time: 2.9376 data: 0.0069 max mem: 33301 +Epoch: [25] [3670/4276] eta: 0:29:34 lr: 1.9613793254411885e-05 loss: 0.0961 (0.0997) time: 2.9406 data: 0.0069 max mem: 33301 +Epoch: [25] [3680/4276] eta: 0:29:04 lr: 1.9610873980089448e-05 loss: 0.1076 (0.0997) time: 2.9408 data: 0.0068 max mem: 33301 +Epoch: [25] [3690/4276] eta: 0:28:35 lr: 1.960795465748142e-05 loss: 0.1017 (0.0997) time: 2.9381 data: 0.0069 max mem: 33301 +Epoch: [25] [3700/4276] eta: 0:28:06 lr: 1.9605035286579017e-05 loss: 0.0886 (0.0997) time: 2.9367 data: 0.0068 max mem: 33301 +Epoch: [25] [3710/4276] eta: 0:27:37 lr: 1.9602115867373455e-05 loss: 0.0886 (0.0997) time: 2.9380 data: 0.0069 max mem: 33301 +Epoch: [25] [3720/4276] eta: 0:27:07 lr: 1.9599196399855926e-05 loss: 0.0919 (0.0997) time: 2.9418 data: 0.0073 max mem: 33301 +Epoch: [25] [3730/4276] eta: 0:26:38 lr: 1.9596276884017643e-05 loss: 0.0938 (0.0997) time: 2.9301 data: 0.0074 max mem: 33301 +Epoch: [25] [3740/4276] eta: 0:26:09 lr: 1.9593357319849805e-05 loss: 0.0959 (0.0997) time: 2.8999 data: 0.0073 max mem: 33301 +Epoch: [25] [3750/4276] eta: 0:25:39 lr: 1.9590437707343617e-05 loss: 0.1015 (0.0997) time: 2.8831 data: 0.0072 max mem: 33301 +Epoch: [25] [3760/4276] eta: 0:25:10 lr: 1.9587518046490265e-05 loss: 0.0884 (0.0997) time: 2.8838 data: 0.0071 max mem: 33301 +Epoch: [25] [3770/4276] eta: 0:24:41 lr: 1.9584598337280944e-05 loss: 0.0885 (0.0997) time: 2.9060 data: 0.0072 max mem: 33301 +Epoch: [25] [3780/4276] eta: 0:24:11 lr: 1.958167857970684e-05 loss: 0.0808 (0.0997) time: 2.9353 data: 0.0078 max mem: 33301 +Epoch: [25] [3790/4276] eta: 0:23:42 lr: 1.9578758773759147e-05 loss: 0.0859 (0.0997) time: 2.9416 data: 0.0083 max mem: 33301 +Epoch: [25] [3800/4276] eta: 0:23:13 lr: 1.957583891942904e-05 loss: 0.0964 (0.0997) time: 2.9409 data: 0.0083 max mem: 33301 +Epoch: [25] [3810/4276] eta: 0:22:44 lr: 1.9572919016707703e-05 loss: 0.0910 (0.0997) time: 2.9403 data: 0.0085 max mem: 33301 +Epoch: [25] [3820/4276] eta: 0:22:14 lr: 1.9569999065586304e-05 loss: 0.0872 (0.0996) time: 2.9458 data: 0.0084 max mem: 33301 +Epoch: [25] [3830/4276] eta: 0:21:45 lr: 1.9567079066056034e-05 loss: 0.0857 (0.0996) time: 2.9464 data: 0.0083 max mem: 33301 +Epoch: [25] [3840/4276] eta: 0:21:16 lr: 1.9564159018108046e-05 loss: 0.0838 (0.0996) time: 2.9295 data: 0.0082 max mem: 33301 +Epoch: [25] [3850/4276] eta: 0:20:47 lr: 1.9561238921733514e-05 loss: 0.0794 (0.0995) time: 2.9172 data: 0.0079 max mem: 33301 +Epoch: [25] [3860/4276] eta: 0:20:17 lr: 1.95583187769236e-05 loss: 0.0825 (0.0995) time: 2.9221 data: 0.0078 max mem: 33301 +Epoch: [25] [3870/4276] eta: 0:19:48 lr: 1.9555398583669476e-05 loss: 0.0939 (0.0995) time: 2.9335 data: 0.0074 max mem: 33301 +Epoch: [25] [3880/4276] eta: 0:19:19 lr: 1.9552478341962284e-05 loss: 0.0842 (0.0995) time: 2.9384 data: 0.0071 max mem: 33301 +Epoch: [25] [3890/4276] eta: 0:18:50 lr: 1.954955805179319e-05 loss: 0.0943 (0.0995) time: 2.9390 data: 0.0074 max mem: 33301 +Epoch: [25] [3900/4276] eta: 0:18:20 lr: 1.9546637713153347e-05 loss: 0.1021 (0.0995) time: 2.9399 data: 0.0073 max mem: 33301 +Epoch: [25] [3910/4276] eta: 0:17:51 lr: 1.954371732603389e-05 loss: 0.0821 (0.0995) time: 2.9211 data: 0.0070 max mem: 33301 +Epoch: [25] [3920/4276] eta: 0:17:22 lr: 1.9540796890425978e-05 loss: 0.0808 (0.0994) time: 2.9083 data: 0.0074 max mem: 33301 +Epoch: [25] [3930/4276] eta: 0:16:52 lr: 1.953787640632075e-05 loss: 0.0861 (0.0994) time: 2.9276 data: 0.0080 max mem: 33301 +Epoch: [25] [3940/4276] eta: 0:16:23 lr: 1.953495587370935e-05 loss: 0.0932 (0.0994) time: 2.9405 data: 0.0079 max mem: 33301 +Epoch: [25] [3950/4276] eta: 0:15:54 lr: 1.9532035292582908e-05 loss: 0.0962 (0.0995) time: 2.9381 data: 0.0078 max mem: 33301 +Epoch: [25] [3960/4276] eta: 0:15:25 lr: 1.9529114662932553e-05 loss: 0.1009 (0.0995) time: 2.9401 data: 0.0079 max mem: 33301 +Epoch: [25] [3970/4276] eta: 0:14:55 lr: 1.952619398474943e-05 loss: 0.1102 (0.0995) time: 2.9409 data: 0.0082 max mem: 33301 +Epoch: [25] [3980/4276] eta: 0:14:26 lr: 1.9523273258024656e-05 loss: 0.0919 (0.0995) time: 2.9127 data: 0.0081 max mem: 33301 +Epoch: [25] [3990/4276] eta: 0:13:57 lr: 1.9520352482749354e-05 loss: 0.0899 (0.0995) time: 2.8834 data: 0.0073 max mem: 33301 +Epoch: [25] [4000/4276] eta: 0:13:27 lr: 1.951743165891465e-05 loss: 0.0884 (0.0994) time: 2.8803 data: 0.0070 max mem: 33301 +Epoch: [25] [4010/4276] eta: 0:12:58 lr: 1.9514510786511662e-05 loss: 0.0940 (0.0995) time: 2.9088 data: 0.0075 max mem: 33301 +Epoch: [25] [4020/4276] eta: 0:12:29 lr: 1.9511589865531504e-05 loss: 0.1007 (0.0994) time: 2.9380 data: 0.0077 max mem: 33301 +Epoch: [25] [4030/4276] eta: 0:12:00 lr: 1.9508668895965286e-05 loss: 0.0972 (0.0994) time: 2.9375 data: 0.0075 max mem: 33301 +Epoch: [25] [4040/4276] eta: 0:11:30 lr: 1.9505747877804113e-05 loss: 0.0924 (0.0994) time: 2.9368 data: 0.0074 max mem: 33301 +Epoch: [25] [4050/4276] eta: 0:11:01 lr: 1.95028268110391e-05 loss: 0.0888 (0.0994) time: 2.9397 data: 0.0076 max mem: 33301 +Epoch: [25] [4060/4276] eta: 0:10:32 lr: 1.9499905695661346e-05 loss: 0.0878 (0.0994) time: 2.9432 data: 0.0076 max mem: 33301 +Epoch: [25] [4070/4276] eta: 0:10:03 lr: 1.9496984531661947e-05 loss: 0.0968 (0.0994) time: 2.9384 data: 0.0074 max mem: 33301 +Epoch: [25] [4080/4276] eta: 0:09:33 lr: 1.9494063319031997e-05 loss: 0.0929 (0.0994) time: 2.9388 data: 0.0069 max mem: 33301 +Epoch: [25] [4090/4276] eta: 0:09:04 lr: 1.9491142057762597e-05 loss: 0.0998 (0.0995) time: 2.9421 data: 0.0068 max mem: 33301 +Epoch: [25] [4100/4276] eta: 0:08:35 lr: 1.9488220747844836e-05 loss: 0.1060 (0.0995) time: 2.9378 data: 0.0071 max mem: 33301 +Epoch: [25] [4110/4276] eta: 0:08:05 lr: 1.9485299389269788e-05 loss: 0.1001 (0.0995) time: 2.9361 data: 0.0069 max mem: 33301 +Epoch: [25] [4120/4276] eta: 0:07:36 lr: 1.9482377982028554e-05 loss: 0.0997 (0.0995) time: 2.9362 data: 0.0073 max mem: 33301 +Epoch: [25] [4130/4276] eta: 0:07:07 lr: 1.9479456526112206e-05 loss: 0.0962 (0.0995) time: 2.9349 data: 0.0073 max mem: 33301 +Epoch: [25] [4140/4276] eta: 0:06:38 lr: 1.9476535021511823e-05 loss: 0.0904 (0.0995) time: 2.9242 data: 0.0070 max mem: 33301 +Epoch: [25] [4150/4276] eta: 0:06:08 lr: 1.947361346821848e-05 loss: 0.0910 (0.0995) time: 2.9201 data: 0.0074 max mem: 33301 +Epoch: [25] [4160/4276] eta: 0:05:39 lr: 1.9470691866223246e-05 loss: 0.0919 (0.0995) time: 2.9318 data: 0.0070 max mem: 33301 +Epoch: [25] [4170/4276] eta: 0:05:10 lr: 1.9467770215517188e-05 loss: 0.1101 (0.0995) time: 2.9313 data: 0.0066 max mem: 33301 +Epoch: [25] [4180/4276] eta: 0:04:41 lr: 1.946484851609138e-05 loss: 0.1020 (0.0995) time: 2.9289 data: 0.0066 max mem: 33301 +Epoch: [25] [4190/4276] eta: 0:04:11 lr: 1.9461926767936874e-05 loss: 0.0949 (0.0995) time: 2.9352 data: 0.0065 max mem: 33301 +Epoch: [25] [4200/4276] eta: 0:03:42 lr: 1.945900497104473e-05 loss: 0.1009 (0.0995) time: 2.9374 data: 0.0065 max mem: 33301 +Epoch: [25] [4210/4276] eta: 0:03:13 lr: 1.945608312540601e-05 loss: 0.1010 (0.0995) time: 2.9386 data: 0.0065 max mem: 33301 +Epoch: [25] [4220/4276] eta: 0:02:43 lr: 1.945316123101176e-05 loss: 0.1018 (0.0996) time: 2.9392 data: 0.0064 max mem: 33301 +Epoch: [25] [4230/4276] eta: 0:02:14 lr: 1.9450239287853026e-05 loss: 0.1072 (0.0997) time: 2.9387 data: 0.0064 max mem: 33301 +Epoch: [25] [4240/4276] eta: 0:01:45 lr: 1.9447317295920863e-05 loss: 0.1072 (0.0997) time: 2.9321 data: 0.0065 max mem: 33301 +Epoch: [25] [4250/4276] eta: 0:01:16 lr: 1.9444395255206317e-05 loss: 0.1166 (0.0997) time: 2.9338 data: 0.0065 max mem: 33301 +Epoch: [25] [4260/4276] eta: 0:00:46 lr: 1.9441473165700413e-05 loss: 0.1102 (0.0998) time: 2.9457 data: 0.0064 max mem: 33301 +Epoch: [25] [4270/4276] eta: 0:00:17 lr: 1.94385510273942e-05 loss: 0.1000 (0.0998) time: 2.9441 data: 0.0064 max mem: 33301 +Epoch: [25] Total time: 3:28:40 +Test: [ 0/21770] eta: 7:38:22 time: 1.2633 data: 1.2250 max mem: 33301 +Test: [ 100/21770] eta: 0:18:11 time: 0.0382 data: 0.0009 max mem: 33301 +Test: [ 200/21770] eta: 0:16:00 time: 0.0388 data: 0.0008 max mem: 33301 +Test: [ 300/21770] eta: 0:15:14 time: 0.0385 data: 0.0008 max mem: 33301 +Test: [ 400/21770] eta: 0:14:50 time: 0.0389 data: 0.0008 max mem: 33301 +Test: [ 500/21770] eta: 0:14:35 time: 0.0389 data: 0.0008 max mem: 33301 +Test: [ 600/21770] eta: 0:14:23 time: 0.0387 data: 0.0008 max mem: 33301 +Test: [ 700/21770] eta: 0:14:13 time: 0.0387 data: 0.0008 max mem: 33301 +Test: [ 800/21770] eta: 0:14:05 time: 0.0390 data: 0.0008 max mem: 33301 +Test: [ 900/21770] eta: 0:13:58 time: 0.0387 data: 0.0008 max mem: 33301 +Test: [ 1000/21770] eta: 0:13:51 time: 0.0391 data: 0.0009 max mem: 33301 +Test: [ 1100/21770] eta: 0:13:45 time: 0.0389 data: 0.0009 max mem: 33301 +Test: [ 1200/21770] eta: 0:13:39 time: 0.0390 data: 0.0009 max mem: 33301 +Test: [ 1300/21770] eta: 0:13:34 time: 0.0388 data: 0.0008 max mem: 33301 +Test: [ 1400/21770] eta: 0:13:27 time: 0.0379 data: 0.0009 max mem: 33301 +Test: [ 1500/21770] eta: 0:13:21 time: 0.0381 data: 0.0009 max mem: 33301 +Test: [ 1600/21770] eta: 0:13:15 time: 0.0378 data: 0.0009 max mem: 33301 +Test: [ 1700/21770] eta: 0:13:09 time: 0.0380 data: 0.0009 max mem: 33301 +Test: [ 1800/21770] eta: 0:13:04 time: 0.0386 data: 0.0009 max mem: 33301 +Test: [ 1900/21770] eta: 0:12:59 time: 0.0380 data: 0.0008 max mem: 33301 +Test: [ 2000/21770] eta: 0:12:54 time: 0.0380 data: 0.0009 max mem: 33301 +Test: [ 2100/21770] eta: 0:12:49 time: 0.0379 data: 0.0008 max mem: 33301 +Test: [ 2200/21770] eta: 0:12:44 time: 0.0380 data: 0.0008 max mem: 33301 +Test: [ 2300/21770] eta: 0:12:39 time: 0.0380 data: 0.0008 max mem: 33301 +Test: [ 2400/21770] eta: 0:12:35 time: 0.0381 data: 0.0009 max mem: 33301 +Test: [ 2500/21770] eta: 0:12:30 time: 0.0380 data: 0.0009 max mem: 33301 +Test: [ 2600/21770] eta: 0:12:26 time: 0.0381 data: 0.0009 max mem: 33301 +Test: [ 2700/21770] eta: 0:12:21 time: 0.0381 data: 0.0009 max mem: 33301 +Test: [ 2800/21770] eta: 0:12:17 time: 0.0382 data: 0.0009 max mem: 33301 +Test: [ 2900/21770] eta: 0:12:12 time: 0.0385 data: 0.0009 max mem: 33301 +Test: [ 3000/21770] eta: 0:12:08 time: 0.0389 data: 0.0009 max mem: 33301 +Test: [ 3100/21770] eta: 0:12:05 time: 0.0390 data: 0.0008 max mem: 33301 +Test: [ 3200/21770] eta: 0:12:01 time: 0.0389 data: 0.0008 max mem: 33301 +Test: [ 3300/21770] eta: 0:11:57 time: 0.0393 data: 0.0008 max mem: 33301 +Test: [ 3400/21770] eta: 0:11:53 time: 0.0393 data: 0.0008 max mem: 33301 +Test: [ 3500/21770] eta: 0:11:50 time: 0.0394 data: 0.0008 max mem: 33301 +Test: [ 3600/21770] eta: 0:11:46 time: 0.0392 data: 0.0009 max mem: 33301 +Test: [ 3700/21770] eta: 0:11:43 time: 0.0396 data: 0.0009 max mem: 33301 +Test: [ 3800/21770] eta: 0:11:39 time: 0.0394 data: 0.0009 max mem: 33301 +Test: [ 3900/21770] eta: 0:11:35 time: 0.0396 data: 0.0008 max mem: 33301 +Test: [ 4000/21770] eta: 0:11:32 time: 0.0391 data: 0.0008 max mem: 33301 +Test: [ 4100/21770] eta: 0:11:28 time: 0.0392 data: 0.0008 max mem: 33301 +Test: [ 4200/21770] eta: 0:11:24 time: 0.0391 data: 0.0008 max mem: 33301 +Test: [ 4300/21770] eta: 0:11:20 time: 0.0392 data: 0.0008 max mem: 33301 +Test: [ 4400/21770] eta: 0:11:17 time: 0.0392 data: 0.0008 max mem: 33301 +Test: [ 4500/21770] eta: 0:11:13 time: 0.0379 data: 0.0009 max mem: 33301 +Test: [ 4600/21770] eta: 0:11:09 time: 0.0389 data: 0.0009 max mem: 33301 +Test: [ 4700/21770] eta: 0:11:05 time: 0.0399 data: 0.0008 max mem: 33301 +Test: [ 4800/21770] eta: 0:11:01 time: 0.0389 data: 0.0008 max mem: 33301 +Test: [ 4900/21770] eta: 0:10:57 time: 0.0394 data: 0.0008 max mem: 33301 +Test: [ 5000/21770] eta: 0:10:54 time: 0.0390 data: 0.0009 max mem: 33301 +Test: [ 5100/21770] eta: 0:10:50 time: 0.0397 data: 0.0009 max mem: 33301 +Test: [ 5200/21770] eta: 0:10:46 time: 0.0393 data: 0.0009 max mem: 33301 +Test: [ 5300/21770] eta: 0:10:42 time: 0.0395 data: 0.0009 max mem: 33301 +Test: [ 5400/21770] eta: 0:10:38 time: 0.0395 data: 0.0008 max mem: 33301 +Test: [ 5500/21770] eta: 0:10:35 time: 0.0393 data: 0.0008 max mem: 33301 +Test: [ 5600/21770] eta: 0:10:31 time: 0.0379 data: 0.0009 max mem: 33301 +Test: [ 5700/21770] eta: 0:10:26 time: 0.0381 data: 0.0009 max mem: 33301 +Test: [ 5800/21770] eta: 0:10:22 time: 0.0382 data: 0.0009 max mem: 33301 +Test: [ 5900/21770] eta: 0:10:18 time: 0.0382 data: 0.0009 max mem: 33301 +Test: [ 6000/21770] eta: 0:10:14 time: 0.0379 data: 0.0009 max mem: 33301 +Test: [ 6100/21770] eta: 0:10:10 time: 0.0382 data: 0.0009 max mem: 33301 +Test: [ 6200/21770] eta: 0:10:06 time: 0.0380 data: 0.0008 max mem: 33301 +Test: [ 6300/21770] eta: 0:10:02 time: 0.0382 data: 0.0009 max mem: 33301 +Test: [ 6400/21770] eta: 0:09:58 time: 0.0381 data: 0.0009 max mem: 33301 +Test: [ 6500/21770] eta: 0:09:54 time: 0.0382 data: 0.0009 max mem: 33301 +Test: [ 6600/21770] eta: 0:09:49 time: 0.0380 data: 0.0009 max mem: 33301 +Test: [ 6700/21770] eta: 0:09:45 time: 0.0381 data: 0.0009 max mem: 33301 +Test: [ 6800/21770] eta: 0:09:41 time: 0.0380 data: 0.0009 max mem: 33301 +Test: [ 6900/21770] eta: 0:09:37 time: 0.0382 data: 0.0009 max mem: 33301 +Test: [ 7000/21770] eta: 0:09:33 time: 0.0380 data: 0.0009 max mem: 33301 +Test: [ 7100/21770] eta: 0:09:29 time: 0.0382 data: 0.0009 max mem: 33301 +Test: [ 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time: 0.0387 data: 0.0009 max mem: 33301 +Test: [ 8600/21770] eta: 0:08:30 time: 0.0384 data: 0.0008 max mem: 33301 +Test: [ 8700/21770] eta: 0:08:26 time: 0.0386 data: 0.0008 max mem: 33301 +Test: [ 8800/21770] eta: 0:08:22 time: 0.0381 data: 0.0009 max mem: 33301 +Test: [ 8900/21770] eta: 0:08:18 time: 0.0386 data: 0.0009 max mem: 33301 +Test: [ 9000/21770] eta: 0:08:14 time: 0.0383 data: 0.0009 max mem: 33301 +Test: [ 9100/21770] eta: 0:08:10 time: 0.0386 data: 0.0009 max mem: 33301 +Test: [ 9200/21770] eta: 0:08:06 time: 0.0382 data: 0.0009 max mem: 33301 +Test: [ 9300/21770] eta: 0:08:02 time: 0.0386 data: 0.0009 max mem: 33301 +Test: [ 9400/21770] eta: 0:07:58 time: 0.0381 data: 0.0009 max mem: 33301 +Test: [ 9500/21770] eta: 0:07:54 time: 0.0382 data: 0.0009 max mem: 33301 +Test: [ 9600/21770] eta: 0:07:50 time: 0.0385 data: 0.0009 max mem: 33301 +Test: [ 9700/21770] eta: 0:07:47 time: 0.0386 data: 0.0009 max mem: 33301 +Test: [ 9800/21770] eta: 0:07:43 time: 0.0394 data: 0.0008 max mem: 33301 +Test: [ 9900/21770] eta: 0:07:39 time: 0.0392 data: 0.0008 max mem: 33301 +Test: [10000/21770] eta: 0:07:35 time: 0.0395 data: 0.0008 max mem: 33301 +Test: [10100/21770] eta: 0:07:31 time: 0.0395 data: 0.0008 max mem: 33301 +Test: [10200/21770] eta: 0:07:28 time: 0.0391 data: 0.0008 max mem: 33301 +Test: [10300/21770] eta: 0:07:24 time: 0.0402 data: 0.0008 max mem: 33301 +Test: [10400/21770] eta: 0:07:20 time: 0.0396 data: 0.0008 max mem: 33301 +Test: [10500/21770] eta: 0:07:16 time: 0.0400 data: 0.0008 max mem: 33301 +Test: [10600/21770] eta: 0:07:13 time: 0.0398 data: 0.0008 max mem: 33301 +Test: [10700/21770] eta: 0:07:09 time: 0.0392 data: 0.0008 max mem: 33301 +Test: [10800/21770] eta: 0:07:05 time: 0.0391 data: 0.0008 max mem: 33301 +Test: [10900/21770] eta: 0:07:01 time: 0.0401 data: 0.0008 max mem: 33301 +Test: [11000/21770] eta: 0:06:57 time: 0.0394 data: 0.0008 max mem: 33301 +Test: [11100/21770] eta: 0:06:53 time: 0.0395 data: 0.0008 max mem: 33301 +Test: [11200/21770] eta: 0:06:50 time: 0.0391 data: 0.0008 max mem: 33301 +Test: [11300/21770] eta: 0:06:46 time: 0.0399 data: 0.0008 max mem: 33301 +Test: [11400/21770] eta: 0:06:42 time: 0.0377 data: 0.0009 max mem: 33301 +Test: [11500/21770] eta: 0:06:38 time: 0.0378 data: 0.0009 max mem: 33301 +Test: [11600/21770] eta: 0:06:34 time: 0.0378 data: 0.0009 max mem: 33301 +Test: [11700/21770] eta: 0:06:30 time: 0.0379 data: 0.0009 max mem: 33301 +Test: [11800/21770] eta: 0:06:26 time: 0.0378 data: 0.0009 max mem: 33301 +Test: [11900/21770] eta: 0:06:22 time: 0.0385 data: 0.0009 max mem: 33301 +Test: [12000/21770] eta: 0:06:18 time: 0.0386 data: 0.0009 max mem: 33301 +Test: [12100/21770] eta: 0:06:14 time: 0.0387 data: 0.0009 max mem: 33301 +Test: [12200/21770] eta: 0:06:11 time: 0.0386 data: 0.0009 max mem: 33301 +Test: [12300/21770] eta: 0:06:07 time: 0.0387 data: 0.0009 max mem: 33301 +Test: [12400/21770] eta: 0:06:03 time: 0.0387 data: 0.0009 max mem: 33301 +Test: [12500/21770] eta: 0:05:59 time: 0.0389 data: 0.0009 max mem: 33301 +Test: [12600/21770] eta: 0:05:55 time: 0.0386 data: 0.0009 max mem: 33301 +Test: [12700/21770] eta: 0:05:51 time: 0.0388 data: 0.0009 max mem: 33301 +Test: [12800/21770] eta: 0:05:47 time: 0.0384 data: 0.0009 max mem: 33301 +Test: [12900/21770] eta: 0:05:43 time: 0.0394 data: 0.0008 max mem: 33301 +Test: [13000/21770] eta: 0:05:40 time: 0.0393 data: 0.0008 max mem: 33301 +Test: [13100/21770] eta: 0:05:36 time: 0.0399 data: 0.0008 max mem: 33301 +Test: [13200/21770] eta: 0:05:32 time: 0.0399 data: 0.0008 max mem: 33301 +Test: [13300/21770] eta: 0:05:28 time: 0.0399 data: 0.0008 max mem: 33301 +Test: [13400/21770] eta: 0:05:24 time: 0.0378 data: 0.0009 max mem: 33301 +Test: [13500/21770] eta: 0:05:20 time: 0.0378 data: 0.0009 max mem: 33301 +Test: [13600/21770] eta: 0:05:16 time: 0.0379 data: 0.0009 max mem: 33301 +Test: [13700/21770] eta: 0:05:12 time: 0.0377 data: 0.0008 max mem: 33301 +Test: [13800/21770] eta: 0:05:08 time: 0.0379 data: 0.0009 max mem: 33301 +Test: [13900/21770] eta: 0:05:05 time: 0.0379 data: 0.0009 max mem: 33301 +Test: [14000/21770] eta: 0:05:01 time: 0.0378 data: 0.0009 max mem: 33301 +Test: [14100/21770] eta: 0:04:57 time: 0.0379 data: 0.0009 max mem: 33301 +Test: [14200/21770] eta: 0:04:53 time: 0.0378 data: 0.0009 max mem: 33301 +Test: [14300/21770] eta: 0:04:49 time: 0.0379 data: 0.0009 max mem: 33301 +Test: [14400/21770] eta: 0:04:45 time: 0.0379 data: 0.0009 max mem: 33301 +Test: [14500/21770] eta: 0:04:41 time: 0.0383 data: 0.0009 max mem: 33301 +Test: [14600/21770] eta: 0:04:37 time: 0.0382 data: 0.0009 max mem: 33301 +Test: [14700/21770] eta: 0:04:33 time: 0.0381 data: 0.0009 max mem: 33301 +Test: [14800/21770] eta: 0:04:29 time: 0.0382 data: 0.0009 max mem: 33301 +Test: [14900/21770] eta: 0:04:25 time: 0.0383 data: 0.0009 max mem: 33301 +Test: [15000/21770] eta: 0:04:22 time: 0.0382 data: 0.0009 max mem: 33301 +Test: [15100/21770] eta: 0:04:18 time: 0.0382 data: 0.0009 max mem: 33301 +Test: [15200/21770] eta: 0:04:14 time: 0.0381 data: 0.0009 max mem: 33301 +Test: [15300/21770] eta: 0:04:10 time: 0.0382 data: 0.0009 max mem: 33301 +Test: [15400/21770] eta: 0:04:06 time: 0.0381 data: 0.0009 max mem: 33301 +Test: [15500/21770] eta: 0:04:02 time: 0.0383 data: 0.0009 max mem: 33301 +Test: [15600/21770] eta: 0:03:58 time: 0.0385 data: 0.0009 max mem: 33301 +Test: [15700/21770] eta: 0:03:54 time: 0.0388 data: 0.0009 max mem: 33301 +Test: [15800/21770] eta: 0:03:50 time: 0.0384 data: 0.0009 max mem: 33301 +Test: [15900/21770] eta: 0:03:47 time: 0.0386 data: 0.0009 max mem: 33301 +Test: [16000/21770] eta: 0:03:43 time: 0.0387 data: 0.0009 max mem: 33301 +Test: [16100/21770] eta: 0:03:39 time: 0.0390 data: 0.0009 max mem: 33301 +Test: [16200/21770] eta: 0:03:35 time: 0.0386 data: 0.0009 max mem: 33301 +Test: [16300/21770] eta: 0:03:31 time: 0.0389 data: 0.0009 max mem: 33301 +Test: [16400/21770] eta: 0:03:27 time: 0.0386 data: 0.0009 max mem: 33301 +Test: [16500/21770] eta: 0:03:23 time: 0.0389 data: 0.0009 max mem: 33301 +Test: [16600/21770] eta: 0:03:20 time: 0.0387 data: 0.0009 max mem: 33301 +Test: [16700/21770] eta: 0:03:16 time: 0.0389 data: 0.0009 max mem: 33301 +Test: [16800/21770] eta: 0:03:12 time: 0.0384 data: 0.0009 max mem: 33301 +Test: [16900/21770] eta: 0:03:08 time: 0.0387 data: 0.0009 max mem: 33301 +Test: [17000/21770] eta: 0:03:04 time: 0.0379 data: 0.0009 max mem: 33301 +Test: [17100/21770] eta: 0:03:00 time: 0.0381 data: 0.0009 max mem: 33301 +Test: [17200/21770] eta: 0:02:56 time: 0.0381 data: 0.0009 max mem: 33301 +Test: [17300/21770] eta: 0:02:52 time: 0.0383 data: 0.0009 max mem: 33301 +Test: [17400/21770] eta: 0:02:49 time: 0.0381 data: 0.0009 max mem: 33301 +Test: [17500/21770] eta: 0:02:45 time: 0.0383 data: 0.0009 max mem: 33301 +Test: [17600/21770] eta: 0:02:41 time: 0.0381 data: 0.0009 max mem: 33301 +Test: [17700/21770] eta: 0:02:37 time: 0.0382 data: 0.0009 max mem: 33301 +Test: [17800/21770] eta: 0:02:33 time: 0.0381 data: 0.0009 max mem: 33301 +Test: [17900/21770] eta: 0:02:29 time: 0.0383 data: 0.0009 max mem: 33301 +Test: [18000/21770] eta: 0:02:25 time: 0.0381 data: 0.0009 max mem: 33301 +Test: [18100/21770] eta: 0:02:21 time: 0.0387 data: 0.0009 max mem: 33301 +Test: [18200/21770] eta: 0:02:18 time: 0.0387 data: 0.0009 max mem: 33301 +Test: [18300/21770] eta: 0:02:14 time: 0.0383 data: 0.0009 max mem: 33301 +Test: [18400/21770] eta: 0:02:10 time: 0.0386 data: 0.0009 max mem: 33301 +Test: [18500/21770] eta: 0:02:06 time: 0.0385 data: 0.0009 max mem: 33301 +Test: [18600/21770] eta: 0:02:02 time: 0.0385 data: 0.0009 max mem: 33301 +Test: [18700/21770] eta: 0:01:58 time: 0.0385 data: 0.0009 max mem: 33301 +Test: [18800/21770] eta: 0:01:54 time: 0.0385 data: 0.0009 max mem: 33301 +Test: [18900/21770] eta: 0:01:50 time: 0.0384 data: 0.0009 max mem: 33301 +Test: [19000/21770] eta: 0:01:47 time: 0.0385 data: 0.0009 max mem: 33301 +Test: [19100/21770] eta: 0:01:43 time: 0.0384 data: 0.0009 max mem: 33301 +Test: [19200/21770] eta: 0:01:39 time: 0.0385 data: 0.0009 max mem: 33301 +Test: [19300/21770] eta: 0:01:35 time: 0.0386 data: 0.0009 max mem: 33301 +Test: [19400/21770] eta: 0:01:31 time: 0.0384 data: 0.0009 max mem: 33301 +Test: [19500/21770] eta: 0:01:27 time: 0.0385 data: 0.0009 max mem: 33301 +Test: [19600/21770] eta: 0:01:23 time: 0.0381 data: 0.0009 max mem: 33301 +Test: [19700/21770] eta: 0:01:19 time: 0.0383 data: 0.0009 max mem: 33301 +Test: [19800/21770] eta: 0:01:16 time: 0.0378 data: 0.0009 max mem: 33301 +Test: [19900/21770] eta: 0:01:12 time: 0.0379 data: 0.0009 max mem: 33301 +Test: [20000/21770] eta: 0:01:08 time: 0.0378 data: 0.0009 max mem: 33301 +Test: [20100/21770] eta: 0:01:04 time: 0.0379 data: 0.0009 max mem: 33301 +Test: [20200/21770] eta: 0:01:00 time: 0.0378 data: 0.0009 max mem: 33301 +Test: [20300/21770] eta: 0:00:56 time: 0.0378 data: 0.0009 max mem: 33301 +Test: [20400/21770] eta: 0:00:52 time: 0.0378 data: 0.0009 max mem: 33301 +Test: [20500/21770] eta: 0:00:49 time: 0.0378 data: 0.0009 max mem: 33301 +Test: [20600/21770] eta: 0:00:45 time: 0.0378 data: 0.0009 max mem: 33301 +Test: [20700/21770] eta: 0:00:41 time: 0.0378 data: 0.0009 max mem: 33301 +Test: [20800/21770] eta: 0:00:37 time: 0.0379 data: 0.0009 max mem: 33301 +Test: [20900/21770] eta: 0:00:33 time: 0.0379 data: 0.0009 max mem: 33301 +Test: [21000/21770] eta: 0:00:29 time: 0.0378 data: 0.0009 max mem: 33301 +Test: [21100/21770] eta: 0:00:25 time: 0.0378 data: 0.0009 max mem: 33301 +Test: [21200/21770] eta: 0:00:21 time: 0.0379 data: 0.0009 max mem: 33301 +Test: [21300/21770] eta: 0:00:18 time: 0.0378 data: 0.0009 max mem: 33301 +Test: [21400/21770] eta: 0:00:14 time: 0.0378 data: 0.0009 max mem: 33301 +Test: [21500/21770] eta: 0:00:10 time: 0.0378 data: 0.0009 max mem: 33301 +Test: [21600/21770] eta: 0:00:06 time: 0.0379 data: 0.0009 max mem: 33301 +Test: [21700/21770] eta: 0:00:02 time: 0.0378 data: 0.0009 max mem: 33301 +Test: Total time: 0:13:59 +Final results: +Mean IoU is 0.00 + + precision@0.5 = 0.00 + precision@0.6 = 0.00 + precision@0.7 = 0.00 + precision@0.8 = 0.00 + precision@0.9 = 0.00 + overall IoU = 0.00 + mean IoU = 0.00 + +Mean accuracy for one-to-zero sample is 100.00 + +Average object IoU 0.0 +Overall IoU 0.0 +Epoch: [26] [ 0/4276] eta: 5:59:27 lr: 1.943679772098259e-05 loss: 0.0954 (0.0954) time: 5.0438 data: 2.0314 max mem: 33301 +Epoch: [26] [ 10/4276] eta: 3:42:51 lr: 1.9433875504577227e-05 loss: 0.0954 (0.0972) time: 3.1344 data: 0.1916 max mem: 33301 +Epoch: [26] [ 20/4276] eta: 3:35:46 lr: 1.9430953239348233e-05 loss: 0.0918 (0.0969) time: 2.9418 data: 0.0071 max mem: 33301 +Epoch: [26] [ 30/4276] eta: 3:32:35 lr: 1.942803092528663e-05 loss: 0.0967 (0.0989) time: 2.9327 data: 0.0076 max mem: 33301 +Epoch: [26] [ 40/4276] eta: 3:31:04 lr: 1.9425108562383443e-05 loss: 0.0970 (0.0978) time: 2.9349 data: 0.0076 max mem: 33301 +Epoch: [26] [ 50/4276] eta: 3:29:55 lr: 1.942218615062969e-05 loss: 0.0939 (0.0957) time: 2.9437 data: 0.0068 max mem: 33301 +Epoch: [26] [ 60/4276] eta: 3:29:01 lr: 1.9419263690016394e-05 loss: 0.0845 (0.0941) time: 2.9437 data: 0.0070 max mem: 33301 +Epoch: [26] [ 70/4276] eta: 3:28:12 lr: 1.9416341180534554e-05 loss: 0.0839 (0.0927) time: 2.9436 data: 0.0069 max mem: 33301 +Epoch: [26] [ 80/4276] eta: 3:27:28 lr: 1.941341862217519e-05 loss: 0.0839 (0.0934) time: 2.9430 data: 0.0068 max mem: 33301 +Epoch: [26] [ 90/4276] eta: 3:26:50 lr: 1.9410496014929304e-05 loss: 0.0912 (0.0929) time: 2.9456 data: 0.0068 max mem: 33301 +Epoch: [26] [ 100/4276] eta: 3:26:10 lr: 1.9407573358787913e-05 loss: 0.0902 (0.0936) time: 2.9435 data: 0.0068 max mem: 33301 +Epoch: [26] [ 110/4276] eta: 3:25:31 lr: 1.9404650653741994e-05 loss: 0.0915 (0.0949) time: 2.9383 data: 0.0067 max mem: 33301 +Epoch: [26] [ 120/4276] eta: 3:24:54 lr: 1.9401727899782556e-05 loss: 0.1094 (0.0957) time: 2.9388 data: 0.0066 max mem: 33301 +Epoch: [26] [ 130/4276] eta: 3:24:18 lr: 1.9398805096900598e-05 loss: 0.0982 (0.0960) time: 2.9394 data: 0.0066 max mem: 33301 +Epoch: [26] [ 140/4276] eta: 3:23:42 lr: 1.9395882245087105e-05 loss: 0.0905 (0.0957) time: 2.9357 data: 0.0066 max mem: 33301 +Epoch: [26] [ 150/4276] eta: 3:23:06 lr: 1.9392959344333062e-05 loss: 0.0905 (0.0957) time: 2.9331 data: 0.0066 max mem: 33301 +Epoch: [26] [ 160/4276] eta: 3:22:33 lr: 1.9390036394629456e-05 loss: 0.0869 (0.0953) time: 2.9353 data: 0.0067 max mem: 33301 +Epoch: [26] [ 170/4276] eta: 3:21:58 lr: 1.9387113395967264e-05 loss: 0.0839 (0.0951) time: 2.9338 data: 0.0068 max mem: 33301 +Epoch: [26] [ 180/4276] eta: 3:21:26 lr: 1.938419034833748e-05 loss: 0.0900 (0.0957) time: 2.9351 data: 0.0067 max mem: 33301 +Epoch: [26] [ 190/4276] eta: 3:20:53 lr: 1.938126725173106e-05 loss: 0.0900 (0.0958) time: 2.9389 data: 0.0065 max mem: 33301 +Epoch: [26] [ 200/4276] eta: 3:20:19 lr: 1.9378344106138982e-05 loss: 0.0814 (0.0958) time: 2.9329 data: 0.0064 max mem: 33301 +Epoch: [26] [ 210/4276] eta: 3:19:45 lr: 1.9375420911552218e-05 loss: 0.0916 (0.0958) time: 2.9254 data: 0.0075 max mem: 33301 +Epoch: [26] [ 220/4276] eta: 3:19:14 lr: 1.9372497667961735e-05 loss: 0.0965 (0.0958) time: 2.9316 data: 0.0079 max mem: 33301 +Epoch: [26] [ 230/4276] eta: 3:18:39 lr: 1.9369574375358484e-05 loss: 0.0877 (0.0955) time: 2.9287 data: 0.0074 max mem: 33301 +Epoch: [26] [ 240/4276] eta: 3:18:08 lr: 1.936665103373343e-05 loss: 0.0877 (0.0955) time: 2.9270 data: 0.0072 max mem: 33301 +Epoch: [26] [ 250/4276] eta: 3:17:37 lr: 1.9363727643077533e-05 loss: 0.1046 (0.0970) time: 2.9360 data: 0.0071 max mem: 33301 +Epoch: [26] [ 260/4276] eta: 3:17:06 lr: 1.9360804203381745e-05 loss: 0.1046 (0.0971) time: 2.9364 data: 0.0070 max mem: 33301 +Epoch: [26] [ 270/4276] eta: 3:16:34 lr: 1.9357880714637007e-05 loss: 0.0924 (0.0975) time: 2.9294 data: 0.0071 max mem: 33301 +Epoch: [26] [ 280/4276] eta: 3:16:04 lr: 1.9354957176834275e-05 loss: 0.1028 (0.0976) time: 2.9307 data: 0.0072 max mem: 33301 +Epoch: [26] [ 290/4276] eta: 3:15:33 lr: 1.935203358996449e-05 loss: 0.0917 (0.0976) time: 2.9392 data: 0.0071 max mem: 33301 +Epoch: [26] [ 300/4276] eta: 3:15:03 lr: 1.934910995401858e-05 loss: 0.0887 (0.0974) time: 2.9390 data: 0.0072 max mem: 33301 +Epoch: [26] [ 310/4276] eta: 3:14:33 lr: 1.93461862689875e-05 loss: 0.0892 (0.0973) time: 2.9397 data: 0.0070 max mem: 33301 +Epoch: [26] [ 320/4276] eta: 3:14:03 lr: 1.9343262534862168e-05 loss: 0.0951 (0.0975) time: 2.9391 data: 0.0069 max mem: 33301 +Epoch: [26] [ 330/4276] eta: 3:13:33 lr: 1.9340338751633526e-05 loss: 0.1005 (0.0978) time: 2.9385 data: 0.0072 max mem: 33301 +Epoch: [26] [ 340/4276] eta: 3:13:04 lr: 1.9337414919292495e-05 loss: 0.0993 (0.0979) time: 2.9392 data: 0.0071 max mem: 33301 +Epoch: [26] [ 350/4276] eta: 3:12:36 lr: 1.9334491037829997e-05 loss: 0.0993 (0.0980) time: 2.9480 data: 0.0072 max mem: 33301 +Epoch: [26] [ 360/4276] eta: 3:12:06 lr: 1.9331567107236956e-05 loss: 0.1054 (0.0985) time: 2.9482 data: 0.0069 max mem: 33301 +Epoch: [26] [ 370/4276] eta: 3:11:36 lr: 1.9328643127504294e-05 loss: 0.1007 (0.0986) time: 2.9383 data: 0.0066 max mem: 33301 +Epoch: [26] [ 380/4276] eta: 3:11:06 lr: 1.9325719098622915e-05 loss: 0.0984 (0.0987) time: 2.9387 data: 0.0065 max mem: 33301 +Epoch: [26] [ 390/4276] eta: 3:10:35 lr: 1.9322795020583738e-05 loss: 0.1019 (0.0988) time: 2.9347 data: 0.0064 max mem: 33301 +Epoch: [26] [ 400/4276] eta: 3:10:02 lr: 1.9319870893377663e-05 loss: 0.1044 (0.0989) time: 2.9192 data: 0.0071 max mem: 33301 +Epoch: [26] [ 410/4276] eta: 3:09:33 lr: 1.9316946716995606e-05 loss: 0.1044 (0.0992) time: 2.9242 data: 0.0073 max mem: 33301 +Epoch: [26] [ 420/4276] eta: 3:09:03 lr: 1.9314022491428457e-05 loss: 0.1076 (0.0995) time: 2.9378 data: 0.0069 max mem: 33301 +Epoch: [26] [ 430/4276] eta: 3:08:33 lr: 1.931109821666712e-05 loss: 0.1076 (0.0997) time: 2.9351 data: 0.0066 max mem: 33301 +Epoch: [26] [ 440/4276] eta: 3:08:04 lr: 1.9308173892702486e-05 loss: 0.0968 (0.0997) time: 2.9393 data: 0.0071 max mem: 33301 +Epoch: [26] [ 450/4276] eta: 3:07:34 lr: 1.930524951952546e-05 loss: 0.0932 (0.0997) time: 2.9411 data: 0.0072 max mem: 33301 +Epoch: [26] [ 460/4276] eta: 3:07:04 lr: 1.930232509712691e-05 loss: 0.0888 (0.0993) time: 2.9343 data: 0.0067 max mem: 33301 +Epoch: [26] [ 470/4276] eta: 3:06:34 lr: 1.929940062549773e-05 loss: 0.0880 (0.0992) time: 2.9341 data: 0.0067 max mem: 33301 +Epoch: [26] [ 480/4276] eta: 3:06:04 lr: 1.9296476104628808e-05 loss: 0.0843 (0.0988) time: 2.9355 data: 0.0067 max mem: 33301 +Epoch: [26] [ 490/4276] eta: 3:05:34 lr: 1.9293551534511024e-05 loss: 0.0815 (0.0985) time: 2.9343 data: 0.0066 max mem: 33301 +Epoch: [26] [ 500/4276] eta: 3:05:04 lr: 1.929062691513524e-05 loss: 0.0843 (0.0982) time: 2.9358 data: 0.0066 max mem: 33301 +Epoch: [26] [ 510/4276] eta: 3:04:34 lr: 1.9287702246492338e-05 loss: 0.0899 (0.0984) time: 2.9345 data: 0.0067 max mem: 33301 +Epoch: [26] [ 520/4276] eta: 3:04:04 lr: 1.9284777528573183e-05 loss: 0.0994 (0.0984) time: 2.9344 data: 0.0072 max mem: 33301 +Epoch: [26] [ 530/4276] eta: 3:03:34 lr: 1.928185276136865e-05 loss: 0.0947 (0.0983) time: 2.9342 data: 0.0072 max mem: 33301 +Epoch: [26] [ 540/4276] eta: 3:03:05 lr: 1.9278927944869593e-05 loss: 0.0879 (0.0982) time: 2.9346 data: 0.0070 max mem: 33301 +Epoch: [26] [ 550/4276] eta: 3:02:35 lr: 1.927600307906687e-05 loss: 0.0979 (0.0984) time: 2.9371 data: 0.0067 max mem: 33301 +Epoch: [26] [ 560/4276] eta: 3:02:06 lr: 1.927307816395134e-05 loss: 0.1048 (0.0984) time: 2.9405 data: 0.0067 max mem: 33301 +Epoch: [26] [ 570/4276] eta: 3:01:37 lr: 1.9270153199513866e-05 loss: 0.0974 (0.0983) time: 2.9434 data: 0.0068 max mem: 33301 +Epoch: [26] [ 580/4276] eta: 3:01:07 lr: 1.926722818574528e-05 loss: 0.0974 (0.0986) time: 2.9409 data: 0.0066 max mem: 33301 +Epoch: [26] [ 590/4276] eta: 3:00:36 lr: 1.926430312263644e-05 loss: 0.0908 (0.0985) time: 2.9256 data: 0.0074 max mem: 33301 +Epoch: [26] [ 600/4276] eta: 3:00:03 lr: 1.926137801017819e-05 loss: 0.0889 (0.0984) time: 2.8966 data: 0.0079 max mem: 33301 +Epoch: [26] [ 610/4276] eta: 2:59:32 lr: 1.925845284836136e-05 loss: 0.0879 (0.0982) time: 2.8949 data: 0.0077 max mem: 33301 +Epoch: [26] [ 620/4276] eta: 2:59:02 lr: 1.9255527637176793e-05 loss: 0.0847 (0.0981) time: 2.9232 data: 0.0077 max mem: 33301 +Epoch: [26] [ 630/4276] eta: 2:58:32 lr: 1.9252602376615326e-05 loss: 0.0926 (0.0983) time: 2.9288 data: 0.0076 max mem: 33301 +Epoch: [26] [ 640/4276] eta: 2:58:03 lr: 1.9249677066667788e-05 loss: 0.1036 (0.0983) time: 2.9294 data: 0.0078 max mem: 33301 +Epoch: [26] [ 650/4276] eta: 2:57:33 lr: 1.9246751707324996e-05 loss: 0.0900 (0.0983) time: 2.9371 data: 0.0078 max mem: 33301 +Epoch: [26] [ 660/4276] eta: 2:57:04 lr: 1.9243826298577787e-05 loss: 0.1021 (0.0986) time: 2.9371 data: 0.0078 max mem: 33301 +Epoch: [26] [ 670/4276] eta: 2:56:34 lr: 1.9240900840416974e-05 loss: 0.0964 (0.0985) time: 2.9385 data: 0.0076 max mem: 33301 +Epoch: [26] [ 680/4276] eta: 2:56:05 lr: 1.9237975332833383e-05 loss: 0.0909 (0.0984) time: 2.9373 data: 0.0078 max mem: 33301 +Epoch: [26] [ 690/4276] eta: 2:55:35 lr: 1.9235049775817814e-05 loss: 0.0975 (0.0985) time: 2.9361 data: 0.0079 max mem: 33301 +Epoch: [26] [ 700/4276] eta: 2:55:06 lr: 1.9232124169361084e-05 loss: 0.0929 (0.0984) time: 2.9365 data: 0.0076 max mem: 33301 +Epoch: [26] [ 710/4276] eta: 2:54:36 lr: 1.9229198513454005e-05 loss: 0.0916 (0.0984) time: 2.9368 data: 0.0075 max mem: 33301 +Epoch: [26] [ 720/4276] eta: 2:54:07 lr: 1.9226272808087385e-05 loss: 0.0943 (0.0983) time: 2.9366 data: 0.0077 max mem: 33301 +Epoch: [26] [ 730/4276] eta: 2:53:36 lr: 1.9223347053252007e-05 loss: 0.0889 (0.0982) time: 2.9238 data: 0.0076 max mem: 33301 +Epoch: [26] [ 740/4276] eta: 2:53:07 lr: 1.9220421248938684e-05 loss: 0.0898 (0.0981) time: 2.9208 data: 0.0077 max mem: 33301 +Epoch: [26] [ 750/4276] eta: 2:52:37 lr: 1.9217495395138203e-05 loss: 0.0900 (0.0981) time: 2.9274 data: 0.0076 max mem: 33301 +Epoch: [26] [ 760/4276] eta: 2:52:07 lr: 1.9214569491841362e-05 loss: 0.0955 (0.0980) time: 2.9290 data: 0.0074 max mem: 33301 +Epoch: [26] [ 770/4276] eta: 2:51:38 lr: 1.9211643539038942e-05 loss: 0.0895 (0.0980) time: 2.9357 data: 0.0076 max mem: 33301 +Epoch: [26] [ 780/4276] eta: 2:51:08 lr: 1.9208717536721734e-05 loss: 0.0892 (0.0979) time: 2.9294 data: 0.0073 max mem: 33301 +Epoch: [26] [ 790/4276] eta: 2:50:38 lr: 1.9205791484880508e-05 loss: 0.0892 (0.0980) time: 2.9245 data: 0.0068 max mem: 33301 +Epoch: [26] [ 800/4276] eta: 2:50:08 lr: 1.9202865383506062e-05 loss: 0.0938 (0.0980) time: 2.9225 data: 0.0067 max mem: 33301 +Epoch: [26] [ 810/4276] eta: 2:49:37 lr: 1.9199939232589148e-05 loss: 0.0938 (0.0980) time: 2.9172 data: 0.0074 max mem: 33301 +Epoch: [26] [ 820/4276] eta: 2:49:07 lr: 1.919701303212055e-05 loss: 0.1042 (0.0982) time: 2.9134 data: 0.0079 max mem: 33301 +Epoch: [26] [ 830/4276] eta: 2:48:38 lr: 1.9194086782091038e-05 loss: 0.1045 (0.0982) time: 2.9256 data: 0.0077 max mem: 33301 +Epoch: [26] [ 840/4276] eta: 2:48:09 lr: 1.9191160482491374e-05 loss: 0.1047 (0.0984) time: 2.9425 data: 0.0072 max mem: 33301 +Epoch: [26] [ 850/4276] eta: 2:47:40 lr: 1.9188234133312313e-05 loss: 0.0955 (0.0983) time: 2.9427 data: 0.0069 max mem: 33301 +Epoch: [26] [ 860/4276] eta: 2:47:10 lr: 1.918530773454462e-05 loss: 0.0978 (0.0984) time: 2.9378 data: 0.0068 max mem: 33301 +Epoch: [26] [ 870/4276] eta: 2:46:41 lr: 1.9182381286179052e-05 loss: 0.0931 (0.0983) time: 2.9345 data: 0.0065 max mem: 33301 +Epoch: [26] [ 880/4276] eta: 2:46:12 lr: 1.9179454788206362e-05 loss: 0.0897 (0.0983) time: 2.9394 data: 0.0067 max mem: 33301 +Epoch: [26] [ 890/4276] eta: 2:45:42 lr: 1.9176528240617288e-05 loss: 0.1066 (0.0986) time: 2.9396 data: 0.0069 max mem: 33301 +Epoch: [26] [ 900/4276] eta: 2:45:13 lr: 1.9173601643402583e-05 loss: 0.1066 (0.0985) time: 2.9342 data: 0.0069 max mem: 33301 +Epoch: [26] [ 910/4276] eta: 2:44:43 lr: 1.9170674996552994e-05 loss: 0.0948 (0.0987) time: 2.9362 data: 0.0068 max mem: 33301 +Epoch: [26] [ 920/4276] eta: 2:44:14 lr: 1.9167748300059247e-05 loss: 0.1058 (0.0987) time: 2.9360 data: 0.0071 max mem: 33301 +Epoch: [26] [ 930/4276] eta: 2:43:45 lr: 1.9164821553912084e-05 loss: 0.0947 (0.0987) time: 2.9342 data: 0.0073 max mem: 33301 +Epoch: [26] [ 940/4276] eta: 2:43:14 lr: 1.9161894758102234e-05 loss: 0.0904 (0.0987) time: 2.9114 data: 0.0073 max mem: 33301 +Epoch: [26] [ 950/4276] eta: 2:42:42 lr: 1.9158967912620433e-05 loss: 0.1003 (0.0988) time: 2.8851 data: 0.0072 max mem: 33301 +Epoch: [26] [ 960/4276] eta: 2:42:11 lr: 1.9156041017457396e-05 loss: 0.1027 (0.0989) time: 2.8780 data: 0.0072 max mem: 33301 +Epoch: [26] [ 970/4276] eta: 2:41:41 lr: 1.9153114072603852e-05 loss: 0.1014 (0.0989) time: 2.8989 data: 0.0075 max mem: 33301 +Epoch: [26] [ 980/4276] eta: 2:41:12 lr: 1.9150187078050518e-05 loss: 0.1011 (0.0989) time: 2.9310 data: 0.0079 max mem: 33301 +Epoch: [26] [ 990/4276] eta: 2:40:43 lr: 1.9147260033788117e-05 loss: 0.0945 (0.0989) time: 2.9378 data: 0.0080 max mem: 33301 +Epoch: [26] [1000/4276] eta: 2:40:13 lr: 1.9144332939807348e-05 loss: 0.0944 (0.0989) time: 2.9374 data: 0.0083 max mem: 33301 +Epoch: [26] [1010/4276] eta: 2:39:44 lr: 1.914140579609892e-05 loss: 0.0967 (0.0988) time: 2.9379 data: 0.0081 max mem: 33301 +Epoch: [26] [1020/4276] eta: 2:39:15 lr: 1.913847860265355e-05 loss: 0.0963 (0.0989) time: 2.9388 data: 0.0079 max mem: 33301 +Epoch: [26] [1030/4276] eta: 2:38:46 lr: 1.913555135946194e-05 loss: 0.1050 (0.0990) time: 2.9384 data: 0.0082 max mem: 33301 +Epoch: [26] [1040/4276] eta: 2:38:15 lr: 1.9132624066514776e-05 loss: 0.1050 (0.0990) time: 2.9087 data: 0.0078 max mem: 33301 +Epoch: [26] [1050/4276] eta: 2:37:44 lr: 1.912969672380276e-05 loss: 0.0928 (0.0991) time: 2.8931 data: 0.0074 max mem: 33301 +Epoch: [26] [1060/4276] eta: 2:37:15 lr: 1.9126769331316585e-05 loss: 0.0983 (0.0991) time: 2.9208 data: 0.0075 max mem: 33301 +Epoch: [26] [1070/4276] eta: 2:36:46 lr: 1.9123841889046944e-05 loss: 0.1027 (0.0992) time: 2.9347 data: 0.0071 max mem: 33301 +Epoch: [26] [1080/4276] eta: 2:36:17 lr: 1.912091439698452e-05 loss: 0.1094 (0.0992) time: 2.9388 data: 0.0069 max mem: 33301 +Epoch: [26] [1090/4276] eta: 2:35:46 lr: 1.9117986855119985e-05 loss: 0.1017 (0.0994) time: 2.9206 data: 0.0074 max mem: 33301 +Epoch: [26] [1100/4276] eta: 2:35:17 lr: 1.9115059263444032e-05 loss: 0.0985 (0.0995) time: 2.9136 data: 0.0075 max mem: 33301 +Epoch: [26] [1110/4276] eta: 2:34:48 lr: 1.9112131621947336e-05 loss: 0.1041 (0.0996) time: 2.9334 data: 0.0069 max mem: 33301 +Epoch: [26] [1120/4276] eta: 2:34:18 lr: 1.9109203930620555e-05 loss: 0.1022 (0.0996) time: 2.9363 data: 0.0066 max mem: 33301 +Epoch: [26] [1130/4276] eta: 2:33:49 lr: 1.9106276189454373e-05 loss: 0.0846 (0.0995) time: 2.9361 data: 0.0068 max mem: 33301 +Epoch: [26] [1140/4276] eta: 2:33:20 lr: 1.910334839843945e-05 loss: 0.0898 (0.0995) time: 2.9362 data: 0.0067 max mem: 33301 +Epoch: [26] [1150/4276] eta: 2:32:50 lr: 1.9100420557566447e-05 loss: 0.1004 (0.0995) time: 2.9174 data: 0.0070 max mem: 33301 +Epoch: [26] [1160/4276] eta: 2:32:20 lr: 1.9097492666826027e-05 loss: 0.0924 (0.0995) time: 2.9085 data: 0.0074 max mem: 33301 +Epoch: [26] [1170/4276] eta: 2:31:51 lr: 1.9094564726208837e-05 loss: 0.0903 (0.0995) time: 2.9269 data: 0.0072 max mem: 33301 +Epoch: [26] [1180/4276] eta: 2:31:21 lr: 1.9091636735705537e-05 loss: 0.0902 (0.0995) time: 2.9246 data: 0.0072 max mem: 33301 +Epoch: [26] [1190/4276] eta: 2:30:51 lr: 1.908870869530678e-05 loss: 0.0828 (0.0994) time: 2.9177 data: 0.0070 max mem: 33301 +Epoch: [26] [1200/4276] eta: 2:30:21 lr: 1.9085780605003198e-05 loss: 0.0828 (0.0993) time: 2.9209 data: 0.0072 max mem: 33301 +Epoch: [26] [1210/4276] eta: 2:29:52 lr: 1.908285246478544e-05 loss: 0.0822 (0.0992) time: 2.9268 data: 0.0072 max mem: 33301 +Epoch: [26] [1220/4276] eta: 2:29:23 lr: 1.907992427464415e-05 loss: 0.0953 (0.0993) time: 2.9418 data: 0.0066 max mem: 33301 +Epoch: [26] [1230/4276] eta: 2:28:53 lr: 1.907699603456996e-05 loss: 0.0956 (0.0993) time: 2.9222 data: 0.0072 max mem: 33301 +Epoch: [26] [1240/4276] eta: 2:28:23 lr: 1.9074067744553494e-05 loss: 0.0868 (0.0992) time: 2.9057 data: 0.0078 max mem: 33301 +Epoch: [26] [1250/4276] eta: 2:27:53 lr: 1.907113940458539e-05 loss: 0.0860 (0.0993) time: 2.9027 data: 0.0080 max mem: 33301 +Epoch: [26] [1260/4276] eta: 2:27:23 lr: 1.9068211014656277e-05 loss: 0.0932 (0.0993) time: 2.8914 data: 0.0085 max mem: 33301 +Epoch: [26] [1270/4276] eta: 2:26:53 lr: 1.9065282574756764e-05 loss: 0.0932 (0.0992) time: 2.9022 data: 0.0085 max mem: 33301 +Epoch: [26] [1280/4276] eta: 2:26:23 lr: 1.906235408487748e-05 loss: 0.0923 (0.0992) time: 2.9232 data: 0.0076 max mem: 33301 +Epoch: [26] [1290/4276] eta: 2:25:54 lr: 1.9059425545009036e-05 loss: 0.1055 (0.0992) time: 2.9362 data: 0.0072 max mem: 33301 +Epoch: [26] [1300/4276] eta: 2:25:25 lr: 1.905649695514205e-05 loss: 0.0889 (0.0992) time: 2.9383 data: 0.0070 max mem: 33301 +Epoch: [26] [1310/4276] eta: 2:24:56 lr: 1.905356831526712e-05 loss: 0.0805 (0.0991) time: 2.9458 data: 0.0070 max mem: 33301 +Epoch: [26] [1320/4276] eta: 2:24:27 lr: 1.9050639625374857e-05 loss: 0.0843 (0.0991) time: 2.9539 data: 0.0074 max mem: 33301 +Epoch: [26] [1330/4276] eta: 2:23:58 lr: 1.9047710885455867e-05 loss: 0.0981 (0.0990) time: 2.9514 data: 0.0075 max mem: 33301 +Epoch: [26] [1340/4276] eta: 2:23:29 lr: 1.9044782095500747e-05 loss: 0.0816 (0.0990) time: 2.9441 data: 0.0072 max mem: 33301 +Epoch: [26] [1350/4276] eta: 2:23:00 lr: 1.904185325550008e-05 loss: 0.0897 (0.0990) time: 2.9424 data: 0.0068 max mem: 33301 +Epoch: [26] [1360/4276] eta: 2:22:31 lr: 1.903892436544447e-05 loss: 0.0980 (0.0990) time: 2.9417 data: 0.0068 max mem: 33301 +Epoch: [26] [1370/4276] eta: 2:22:02 lr: 1.9035995425324504e-05 loss: 0.0847 (0.0989) time: 2.9410 data: 0.0071 max mem: 33301 +Epoch: [26] [1380/4276] eta: 2:21:33 lr: 1.9033066435130772e-05 loss: 0.0948 (0.0990) time: 2.9409 data: 0.0070 max mem: 33301 +Epoch: [26] [1390/4276] eta: 2:21:04 lr: 1.903013739485384e-05 loss: 0.1004 (0.0991) time: 2.9392 data: 0.0069 max mem: 33301 +Epoch: [26] [1400/4276] eta: 2:20:34 lr: 1.9027208304484297e-05 loss: 0.1069 (0.0991) time: 2.9337 data: 0.0070 max mem: 33301 +Epoch: [26] [1410/4276] eta: 2:20:05 lr: 1.9024279164012717e-05 loss: 0.0944 (0.0990) time: 2.9354 data: 0.0076 max mem: 33301 +Epoch: [26] [1420/4276] eta: 2:19:36 lr: 1.9021349973429675e-05 loss: 0.0869 (0.0990) time: 2.9413 data: 0.0076 max mem: 33301 +Epoch: [26] [1430/4276] eta: 2:19:07 lr: 1.901842073272573e-05 loss: 0.0869 (0.0990) time: 2.9410 data: 0.0072 max mem: 33301 +Epoch: [26] [1440/4276] eta: 2:18:37 lr: 1.9015491441891454e-05 loss: 0.0955 (0.0989) time: 2.9401 data: 0.0070 max mem: 33301 +Epoch: [26] [1450/4276] eta: 2:18:08 lr: 1.9012562100917404e-05 loss: 0.0955 (0.0989) time: 2.9388 data: 0.0071 max mem: 33301 +Epoch: [26] [1460/4276] eta: 2:17:39 lr: 1.900963270979414e-05 loss: 0.0906 (0.0988) time: 2.9390 data: 0.0073 max mem: 33301 +Epoch: [26] [1470/4276] eta: 2:17:10 lr: 1.9006703268512216e-05 loss: 0.0827 (0.0987) time: 2.9396 data: 0.0073 max mem: 33301 +Epoch: [26] [1480/4276] eta: 2:16:41 lr: 1.900377377706218e-05 loss: 0.0895 (0.0987) time: 2.9406 data: 0.0072 max mem: 33301 +Epoch: [26] [1490/4276] eta: 2:16:11 lr: 1.9000844235434586e-05 loss: 0.0910 (0.0986) time: 2.9418 data: 0.0074 max mem: 33301 +Epoch: [26] [1500/4276] eta: 2:15:42 lr: 1.899791464361998e-05 loss: 0.0875 (0.0986) time: 2.9426 data: 0.0077 max mem: 33301 +Epoch: [26] [1510/4276] eta: 2:15:13 lr: 1.899498500160889e-05 loss: 0.0799 (0.0985) time: 2.9414 data: 0.0077 max mem: 33301 +Epoch: [26] [1520/4276] eta: 2:14:43 lr: 1.8992055309391863e-05 loss: 0.0813 (0.0984) time: 2.9245 data: 0.0074 max mem: 33301 +Epoch: [26] [1530/4276] eta: 2:14:14 lr: 1.8989125566959436e-05 loss: 0.0884 (0.0984) time: 2.9182 data: 0.0076 max mem: 33301 +Epoch: [26] [1540/4276] eta: 2:13:44 lr: 1.8986195774302132e-05 loss: 0.0901 (0.0983) time: 2.9130 data: 0.0081 max mem: 33301 +Epoch: [26] [1550/4276] eta: 2:13:14 lr: 1.8983265931410483e-05 loss: 0.0901 (0.0983) time: 2.9072 data: 0.0078 max mem: 33301 +Epoch: [26] [1560/4276] eta: 2:12:45 lr: 1.8980336038275007e-05 loss: 0.0847 (0.0982) time: 2.9288 data: 0.0076 max mem: 33301 +Epoch: [26] [1570/4276] eta: 2:12:16 lr: 1.8977406094886235e-05 loss: 0.0881 (0.0982) time: 2.9409 data: 0.0072 max mem: 33301 +Epoch: [26] [1580/4276] eta: 2:11:47 lr: 1.8974476101234675e-05 loss: 0.0825 (0.0981) time: 2.9404 data: 0.0068 max mem: 33301 +Epoch: [26] [1590/4276] eta: 2:11:18 lr: 1.897154605731084e-05 loss: 0.0876 (0.0981) time: 2.9400 data: 0.0068 max mem: 33301 +Epoch: [26] [1600/4276] eta: 2:10:48 lr: 1.8968615963105248e-05 loss: 0.1005 (0.0981) time: 2.9400 data: 0.0069 max mem: 33301 +Epoch: [26] [1610/4276] eta: 2:10:19 lr: 1.8965685818608405e-05 loss: 0.0870 (0.0981) time: 2.9404 data: 0.0069 max mem: 33301 +Epoch: [26] [1620/4276] eta: 2:09:50 lr: 1.8962755623810805e-05 loss: 0.0858 (0.0981) time: 2.9329 data: 0.0071 max mem: 33301 +Epoch: [26] [1630/4276] eta: 2:09:20 lr: 1.895982537870295e-05 loss: 0.0862 (0.0981) time: 2.9079 data: 0.0079 max mem: 33301 +Epoch: [26] [1640/4276] eta: 2:08:50 lr: 1.8956895083275344e-05 loss: 0.0862 (0.0980) time: 2.8951 data: 0.0077 max mem: 33301 +Epoch: [26] [1650/4276] eta: 2:08:21 lr: 1.8953964737518482e-05 loss: 0.0787 (0.0979) time: 2.9275 data: 0.0078 max mem: 33301 +Epoch: [26] [1660/4276] eta: 2:07:51 lr: 1.8951034341422845e-05 loss: 0.0837 (0.0979) time: 2.9322 data: 0.0085 max mem: 33301 +Epoch: [26] [1670/4276] eta: 2:07:22 lr: 1.8948103894978916e-05 loss: 0.0851 (0.0978) time: 2.9233 data: 0.0081 max mem: 33301 +Epoch: [26] [1680/4276] eta: 2:06:53 lr: 1.8945173398177187e-05 loss: 0.0860 (0.0978) time: 2.9382 data: 0.0075 max mem: 33301 +Epoch: [26] [1690/4276] eta: 2:06:23 lr: 1.894224285100814e-05 loss: 0.0860 (0.0978) time: 2.9391 data: 0.0072 max mem: 33301 +Epoch: [26] [1700/4276] eta: 2:05:54 lr: 1.893931225346224e-05 loss: 0.1008 (0.0978) time: 2.9397 data: 0.0074 max mem: 33301 +Epoch: [26] [1710/4276] eta: 2:05:25 lr: 1.893638160552996e-05 loss: 0.0978 (0.0978) time: 2.9281 data: 0.0077 max mem: 33301 +Epoch: [26] [1720/4276] eta: 2:04:55 lr: 1.893345090720178e-05 loss: 0.0894 (0.0978) time: 2.9025 data: 0.0078 max mem: 33301 +Epoch: [26] [1730/4276] eta: 2:04:25 lr: 1.893052015846816e-05 loss: 0.0849 (0.0977) time: 2.9109 data: 0.0080 max mem: 33301 +Epoch: [26] [1740/4276] eta: 2:03:56 lr: 1.892758935931956e-05 loss: 0.0798 (0.0976) time: 2.9353 data: 0.0079 max mem: 33301 +Epoch: [26] [1750/4276] eta: 2:03:27 lr: 1.8924658509746437e-05 loss: 0.0806 (0.0976) time: 2.9404 data: 0.0079 max mem: 33301 +Epoch: [26] [1760/4276] eta: 2:02:58 lr: 1.8921727609739248e-05 loss: 0.0812 (0.0976) time: 2.9411 data: 0.0078 max mem: 33301 +Epoch: [26] [1770/4276] eta: 2:02:29 lr: 1.8918796659288455e-05 loss: 0.0824 (0.0976) time: 2.9417 data: 0.0080 max mem: 33301 +Epoch: [26] [1780/4276] eta: 2:01:59 lr: 1.891586565838449e-05 loss: 0.0894 (0.0976) time: 2.9422 data: 0.0079 max mem: 33301 +Epoch: [26] [1790/4276] eta: 2:01:30 lr: 1.8912934607017803e-05 loss: 0.0875 (0.0976) time: 2.9420 data: 0.0075 max mem: 33301 +Epoch: [26] [1800/4276] eta: 2:01:01 lr: 1.891000350517884e-05 loss: 0.0875 (0.0975) time: 2.9416 data: 0.0075 max mem: 33301 +Epoch: [26] [1810/4276] eta: 2:00:32 lr: 1.8907072352858043e-05 loss: 0.0960 (0.0976) time: 2.9417 data: 0.0076 max mem: 33301 +Epoch: [26] [1820/4276] eta: 2:00:03 lr: 1.890414115004584e-05 loss: 0.0947 (0.0976) time: 2.9444 data: 0.0077 max mem: 33301 +Epoch: [26] [1830/4276] eta: 1:59:33 lr: 1.8901209896732652e-05 loss: 0.0896 (0.0975) time: 2.9434 data: 0.0078 max mem: 33301 +Epoch: [26] [1840/4276] eta: 1:59:04 lr: 1.8898278592908926e-05 loss: 0.0818 (0.0975) time: 2.9409 data: 0.0076 max mem: 33301 +Epoch: [26] [1850/4276] eta: 1:58:35 lr: 1.889534723856507e-05 loss: 0.0855 (0.0975) time: 2.9411 data: 0.0076 max mem: 33301 +Epoch: [26] [1860/4276] eta: 1:58:06 lr: 1.8892415833691518e-05 loss: 0.0905 (0.0975) time: 2.9402 data: 0.0075 max mem: 33301 +Epoch: [26] [1870/4276] eta: 1:57:36 lr: 1.8889484378278676e-05 loss: 0.0886 (0.0976) time: 2.9403 data: 0.0075 max mem: 33301 +Epoch: [26] [1880/4276] eta: 1:57:07 lr: 1.8886552872316967e-05 loss: 0.0835 (0.0975) time: 2.9404 data: 0.0075 max mem: 33301 +Epoch: [26] [1890/4276] eta: 1:56:38 lr: 1.8883621315796794e-05 loss: 0.0852 (0.0975) time: 2.9407 data: 0.0077 max mem: 33301 +Epoch: [26] [1900/4276] eta: 1:56:09 lr: 1.8880689708708564e-05 loss: 0.0852 (0.0975) time: 2.9427 data: 0.0078 max mem: 33301 +Epoch: [26] [1910/4276] eta: 1:55:40 lr: 1.8877758051042686e-05 loss: 0.0851 (0.0975) time: 2.9434 data: 0.0075 max mem: 33301 +Epoch: [26] [1920/4276] eta: 1:55:10 lr: 1.887482634278956e-05 loss: 0.0829 (0.0975) time: 2.9433 data: 0.0075 max mem: 33301 +Epoch: [26] [1930/4276] eta: 1:54:41 lr: 1.8871894583939576e-05 loss: 0.0822 (0.0975) time: 2.9424 data: 0.0076 max mem: 33301 +Epoch: [26] [1940/4276] eta: 1:54:12 lr: 1.8868962774483126e-05 loss: 0.0907 (0.0975) time: 2.9403 data: 0.0079 max mem: 33301 +Epoch: [26] [1950/4276] eta: 1:53:43 lr: 1.8866030914410607e-05 loss: 0.1054 (0.0976) time: 2.9396 data: 0.0078 max mem: 33301 +Epoch: [26] [1960/4276] eta: 1:53:13 lr: 1.8863099003712403e-05 loss: 0.1027 (0.0976) time: 2.9399 data: 0.0075 max mem: 33301 +Epoch: [26] [1970/4276] eta: 1:52:44 lr: 1.8860167042378894e-05 loss: 0.0834 (0.0976) time: 2.9417 data: 0.0077 max mem: 33301 +Epoch: [26] [1980/4276] eta: 1:52:15 lr: 1.8857235030400455e-05 loss: 0.0823 (0.0975) time: 2.9448 data: 0.0077 max mem: 33301 +Epoch: [26] [1990/4276] eta: 1:51:46 lr: 1.8854302967767467e-05 loss: 0.0853 (0.0975) time: 2.9437 data: 0.0076 max mem: 33301 +Epoch: [26] [2000/4276] eta: 1:51:17 lr: 1.8851370854470308e-05 loss: 0.0931 (0.0975) time: 2.9440 data: 0.0080 max mem: 33301 +Epoch: [26] [2010/4276] eta: 1:50:47 lr: 1.8848438690499332e-05 loss: 0.0943 (0.0975) time: 2.9304 data: 0.0080 max mem: 33301 +Epoch: [26] [2020/4276] eta: 1:50:18 lr: 1.8845506475844913e-05 loss: 0.1014 (0.0975) time: 2.9296 data: 0.0081 max mem: 33301 +Epoch: [26] [2030/4276] eta: 1:49:49 lr: 1.8842574210497408e-05 loss: 0.0863 (0.0974) time: 2.9437 data: 0.0080 max mem: 33301 +Epoch: [26] [2040/4276] eta: 1:49:19 lr: 1.8839641894447186e-05 loss: 0.0837 (0.0974) time: 2.9445 data: 0.0079 max mem: 33301 +Epoch: [26] [2050/4276] eta: 1:48:50 lr: 1.8836709527684586e-05 loss: 0.0990 (0.0975) time: 2.9437 data: 0.0081 max mem: 33301 +Epoch: [26] [2060/4276] eta: 1:48:21 lr: 1.8833777110199965e-05 loss: 0.0990 (0.0975) time: 2.9387 data: 0.0080 max mem: 33301 +Epoch: [26] [2070/4276] eta: 1:47:52 lr: 1.8830844641983675e-05 loss: 0.0853 (0.0975) time: 2.9405 data: 0.0079 max mem: 33301 +Epoch: [26] [2080/4276] eta: 1:47:22 lr: 1.882791212302606e-05 loss: 0.0895 (0.0975) time: 2.9420 data: 0.0077 max mem: 33301 +Epoch: [26] [2090/4276] eta: 1:46:53 lr: 1.8824979553317452e-05 loss: 0.0934 (0.0975) time: 2.9371 data: 0.0074 max mem: 33301 +Epoch: [26] [2100/4276] eta: 1:46:24 lr: 1.8822046932848192e-05 loss: 0.0844 (0.0975) time: 2.9378 data: 0.0070 max mem: 33301 +Epoch: [26] [2110/4276] eta: 1:45:54 lr: 1.881911426160862e-05 loss: 0.0844 (0.0975) time: 2.9428 data: 0.0069 max mem: 33301 +Epoch: [26] [2120/4276] eta: 1:45:25 lr: 1.8816181539589053e-05 loss: 0.0795 (0.0974) time: 2.9422 data: 0.0070 max mem: 33301 +Epoch: [26] [2130/4276] eta: 1:44:56 lr: 1.8813248766779824e-05 loss: 0.0798 (0.0973) time: 2.9372 data: 0.0069 max mem: 33301 +Epoch: [26] [2140/4276] eta: 1:44:27 lr: 1.8810315943171257e-05 loss: 0.0901 (0.0973) time: 2.9385 data: 0.0068 max mem: 33301 +Epoch: [26] [2150/4276] eta: 1:43:57 lr: 1.8807383068753677e-05 loss: 0.0849 (0.0972) time: 2.9426 data: 0.0067 max mem: 33301 +Epoch: [26] [2160/4276] eta: 1:43:28 lr: 1.8804450143517393e-05 loss: 0.0784 (0.0972) time: 2.9416 data: 0.0071 max mem: 33301 +Epoch: [26] [2170/4276] eta: 1:42:59 lr: 1.880151716745271e-05 loss: 0.0879 (0.0972) time: 2.9412 data: 0.0071 max mem: 33301 +Epoch: [26] [2180/4276] eta: 1:42:29 lr: 1.8798584140549945e-05 loss: 0.1002 (0.0972) time: 2.9399 data: 0.0068 max mem: 33301 +Epoch: [26] [2190/4276] eta: 1:42:00 lr: 1.8795651062799412e-05 loss: 0.0949 (0.0972) time: 2.9381 data: 0.0069 max mem: 33301 +Epoch: [26] [2200/4276] eta: 1:41:31 lr: 1.8792717934191394e-05 loss: 0.0918 (0.0972) time: 2.9376 data: 0.0069 max mem: 33301 +Epoch: [26] [2210/4276] eta: 1:41:02 lr: 1.8789784754716202e-05 loss: 0.0926 (0.0972) time: 2.9393 data: 0.0069 max mem: 33301 +Epoch: [26] [2220/4276] eta: 1:40:32 lr: 1.8786851524364125e-05 loss: 0.0926 (0.0972) time: 2.9409 data: 0.0066 max mem: 33301 +Epoch: [26] [2230/4276] eta: 1:40:03 lr: 1.8783918243125463e-05 loss: 0.0865 (0.0972) time: 2.9413 data: 0.0066 max mem: 33301 +Epoch: [26] [2240/4276] eta: 1:39:34 lr: 1.878098491099049e-05 loss: 0.0778 (0.0971) time: 2.9495 data: 0.0066 max mem: 33301 +Epoch: [26] [2250/4276] eta: 1:39:04 lr: 1.87780515279495e-05 loss: 0.0837 (0.0971) time: 2.9387 data: 0.0068 max mem: 33301 +Epoch: [26] [2260/4276] eta: 1:38:35 lr: 1.8775118093992768e-05 loss: 0.0955 (0.0971) time: 2.9339 data: 0.0072 max mem: 33301 +Epoch: [26] [2270/4276] eta: 1:38:06 lr: 1.8772184609110573e-05 loss: 0.0966 (0.0971) time: 2.9427 data: 0.0070 max mem: 33301 +Epoch: [26] [2280/4276] eta: 1:37:37 lr: 1.876925107329319e-05 loss: 0.0966 (0.0971) time: 2.9396 data: 0.0067 max mem: 33301 +Epoch: [26] [2290/4276] eta: 1:37:07 lr: 1.8766317486530883e-05 loss: 0.0943 (0.0971) time: 2.9392 data: 0.0067 max mem: 33301 +Epoch: [26] [2300/4276] eta: 1:36:38 lr: 1.876338384881393e-05 loss: 0.0914 (0.0971) time: 2.9385 data: 0.0067 max mem: 33301 +Epoch: [26] [2310/4276] eta: 1:36:09 lr: 1.8760450160132586e-05 loss: 0.0973 (0.0971) time: 2.9411 data: 0.0067 max mem: 33301 +Epoch: [26] [2320/4276] eta: 1:35:39 lr: 1.8757516420477104e-05 loss: 0.0986 (0.0971) time: 2.9377 data: 0.0066 max mem: 33301 +Epoch: [26] [2330/4276] eta: 1:35:10 lr: 1.875458262983775e-05 loss: 0.1056 (0.0971) time: 2.9341 data: 0.0066 max mem: 33301 +Epoch: [26] [2340/4276] eta: 1:34:41 lr: 1.875164878820477e-05 loss: 0.1012 (0.0971) time: 2.9381 data: 0.0067 max mem: 33301 +Epoch: [26] [2350/4276] eta: 1:34:11 lr: 1.8748714895568424e-05 loss: 0.0821 (0.0971) time: 2.9200 data: 0.0070 max mem: 33301 +Epoch: [26] [2360/4276] eta: 1:33:41 lr: 1.874578095191894e-05 loss: 0.0838 (0.0971) time: 2.9010 data: 0.0077 max mem: 33301 +Epoch: [26] [2370/4276] eta: 1:33:12 lr: 1.8742846957246566e-05 loss: 0.0898 (0.0971) time: 2.9105 data: 0.0078 max mem: 33301 +Epoch: [26] [2380/4276] eta: 1:32:43 lr: 1.873991291154154e-05 loss: 0.0970 (0.0971) time: 2.9248 data: 0.0074 max mem: 33301 +Epoch: [26] [2390/4276] eta: 1:32:13 lr: 1.8736978814794104e-05 loss: 0.0970 (0.0971) time: 2.9333 data: 0.0071 max mem: 33301 +Epoch: [26] [2400/4276] eta: 1:31:44 lr: 1.8734044666994476e-05 loss: 0.0978 (0.0972) time: 2.9323 data: 0.0070 max mem: 33301 +Epoch: [26] [2410/4276] eta: 1:31:14 lr: 1.8731110468132892e-05 loss: 0.0973 (0.0972) time: 2.9191 data: 0.0072 max mem: 33301 +Epoch: [26] [2420/4276] eta: 1:30:45 lr: 1.8728176218199576e-05 loss: 0.0973 (0.0972) time: 2.9253 data: 0.0071 max mem: 33301 +Epoch: [26] [2430/4276] eta: 1:30:16 lr: 1.8725241917184738e-05 loss: 0.1017 (0.0972) time: 2.9408 data: 0.0067 max mem: 33301 +Epoch: [26] [2440/4276] eta: 1:29:46 lr: 1.8722307565078604e-05 loss: 0.1007 (0.0972) time: 2.9387 data: 0.0066 max mem: 33301 +Epoch: [26] [2450/4276] eta: 1:29:17 lr: 1.8719373161871383e-05 loss: 0.0927 (0.0972) time: 2.9389 data: 0.0066 max mem: 33301 +Epoch: [26] [2460/4276] eta: 1:28:48 lr: 1.871643870755329e-05 loss: 0.0875 (0.0972) time: 2.9403 data: 0.0065 max mem: 33301 +Epoch: [26] [2470/4276] eta: 1:28:19 lr: 1.8713504202114517e-05 loss: 0.0853 (0.0972) time: 2.9378 data: 0.0066 max mem: 33301 +Epoch: [26] [2480/4276] eta: 1:27:49 lr: 1.8710569645545278e-05 loss: 0.1080 (0.0973) time: 2.9284 data: 0.0068 max mem: 33301 +Epoch: [26] [2490/4276] eta: 1:27:19 lr: 1.870763503783577e-05 loss: 0.0991 (0.0973) time: 2.9028 data: 0.0074 max mem: 33301 +Epoch: [26] [2500/4276] eta: 1:26:50 lr: 1.8704700378976185e-05 loss: 0.1051 (0.0973) time: 2.8836 data: 0.0078 max mem: 33301 +Epoch: [26] [2510/4276] eta: 1:26:20 lr: 1.8701765668956717e-05 loss: 0.1120 (0.0974) time: 2.8796 data: 0.0076 max mem: 33301 +Epoch: [26] [2520/4276] eta: 1:25:50 lr: 1.869883090776755e-05 loss: 0.0866 (0.0973) time: 2.8788 data: 0.0077 max mem: 33301 +Epoch: [26] [2530/4276] eta: 1:25:21 lr: 1.8695896095398872e-05 loss: 0.0761 (0.0972) time: 2.8795 data: 0.0075 max mem: 33301 +Epoch: [26] [2540/4276] eta: 1:24:51 lr: 1.8692961231840865e-05 loss: 0.0840 (0.0973) time: 2.8815 data: 0.0075 max mem: 33301 +Epoch: [26] [2550/4276] eta: 1:24:22 lr: 1.8690026317083694e-05 loss: 0.0892 (0.0972) time: 2.9089 data: 0.0073 max mem: 33301 +Epoch: [26] [2560/4276] eta: 1:23:52 lr: 1.8687091351117547e-05 loss: 0.0830 (0.0972) time: 2.9345 data: 0.0070 max mem: 33301 +Epoch: [26] [2570/4276] eta: 1:23:23 lr: 1.8684156333932585e-05 loss: 0.0901 (0.0972) time: 2.9384 data: 0.0074 max mem: 33301 +Epoch: [26] [2580/4276] eta: 1:22:54 lr: 1.868122126551898e-05 loss: 0.0901 (0.0972) time: 2.9382 data: 0.0076 max mem: 33301 +Epoch: [26] [2590/4276] eta: 1:22:24 lr: 1.8678286145866895e-05 loss: 0.0912 (0.0972) time: 2.9113 data: 0.0075 max mem: 33301 +Epoch: [26] [2600/4276] eta: 1:21:55 lr: 1.8675350974966477e-05 loss: 0.0902 (0.0972) time: 2.9070 data: 0.0076 max mem: 33301 +Epoch: [26] [2610/4276] eta: 1:21:25 lr: 1.8672415752807893e-05 loss: 0.0805 (0.0971) time: 2.9214 data: 0.0076 max mem: 33301 +Epoch: [26] [2620/4276] eta: 1:20:56 lr: 1.8669480479381295e-05 loss: 0.0882 (0.0972) time: 2.9184 data: 0.0075 max mem: 33301 +Epoch: [26] [2630/4276] eta: 1:20:27 lr: 1.8666545154676827e-05 loss: 0.0994 (0.0972) time: 2.9275 data: 0.0079 max mem: 33301 +Epoch: [26] [2640/4276] eta: 1:19:57 lr: 1.866360977868463e-05 loss: 0.0924 (0.0972) time: 2.9364 data: 0.0075 max mem: 33301 +Epoch: [26] [2650/4276] eta: 1:19:28 lr: 1.866067435139485e-05 loss: 0.0900 (0.0971) time: 2.9423 data: 0.0068 max mem: 33301 +Epoch: [26] [2660/4276] eta: 1:18:59 lr: 1.8657738872797626e-05 loss: 0.0898 (0.0971) time: 2.9599 data: 0.0066 max mem: 33301 +Epoch: [26] [2670/4276] eta: 1:18:30 lr: 1.8654803342883085e-05 loss: 0.0921 (0.0971) time: 2.9634 data: 0.0063 max mem: 33301 +Epoch: [26] [2680/4276] eta: 1:18:01 lr: 1.865186776164136e-05 loss: 0.1034 (0.0971) time: 2.9582 data: 0.0063 max mem: 33301 +Epoch: [26] [2690/4276] eta: 1:17:31 lr: 1.864893212906258e-05 loss: 0.0910 (0.0971) time: 2.9573 data: 0.0065 max mem: 33301 +Epoch: [26] [2700/4276] eta: 1:17:02 lr: 1.864599644513687e-05 loss: 0.0808 (0.0970) time: 2.9502 data: 0.0065 max mem: 33301 +Epoch: [26] [2710/4276] eta: 1:16:33 lr: 1.864306070985434e-05 loss: 0.0798 (0.0970) time: 2.9527 data: 0.0064 max mem: 33301 +Epoch: [26] [2720/4276] eta: 1:16:04 lr: 1.864012492320511e-05 loss: 0.0798 (0.0970) time: 2.9559 data: 0.0064 max mem: 33301 +Epoch: [26] [2730/4276] eta: 1:15:35 lr: 1.86371890851793e-05 loss: 0.0843 (0.0970) time: 2.9587 data: 0.0065 max mem: 33301 +Epoch: [26] [2740/4276] eta: 1:15:05 lr: 1.8634253195767e-05 loss: 0.1040 (0.0970) time: 2.9614 data: 0.0065 max mem: 33301 +Epoch: [26] [2750/4276] eta: 1:14:36 lr: 1.863131725495833e-05 loss: 0.1108 (0.0971) time: 2.9577 data: 0.0064 max mem: 33301 +Epoch: [26] [2760/4276] eta: 1:14:07 lr: 1.8628381262743383e-05 loss: 0.1006 (0.0971) time: 2.9529 data: 0.0066 max mem: 33301 +Epoch: [26] [2770/4276] eta: 1:13:38 lr: 1.8625445219112268e-05 loss: 0.0995 (0.0971) time: 2.9554 data: 0.0065 max mem: 33301 +Epoch: [26] [2780/4276] eta: 1:13:08 lr: 1.862250912405506e-05 loss: 0.0912 (0.0971) time: 2.9569 data: 0.0065 max mem: 33301 +Epoch: [26] [2790/4276] eta: 1:12:39 lr: 1.861957297756186e-05 loss: 0.0917 (0.0971) time: 2.9503 data: 0.0068 max mem: 33301 +Epoch: [26] [2800/4276] eta: 1:12:10 lr: 1.8616636779622758e-05 loss: 0.0916 (0.0971) time: 2.9494 data: 0.0065 max mem: 33301 +Epoch: [26] [2810/4276] eta: 1:11:41 lr: 1.861370053022783e-05 loss: 0.0819 (0.0971) time: 2.9538 data: 0.0063 max mem: 33301 +Epoch: [26] [2820/4276] eta: 1:11:12 lr: 1.8610764229367157e-05 loss: 0.0809 (0.0970) time: 2.9540 data: 0.0063 max mem: 33301 +Epoch: [26] [2830/4276] eta: 1:10:42 lr: 1.860782787703081e-05 loss: 0.0905 (0.0970) time: 2.9522 data: 0.0062 max mem: 33301 +Epoch: [26] [2840/4276] eta: 1:10:13 lr: 1.8604891473208872e-05 loss: 0.0967 (0.0970) time: 2.9555 data: 0.0062 max mem: 33301 +Epoch: [26] [2850/4276] eta: 1:09:44 lr: 1.8601955017891405e-05 loss: 0.0967 (0.0970) time: 2.9574 data: 0.0062 max mem: 33301 +Epoch: [26] [2860/4276] eta: 1:09:15 lr: 1.859901851106847e-05 loss: 0.0781 (0.0970) time: 2.9573 data: 0.0062 max mem: 33301 +Epoch: [26] [2870/4276] eta: 1:08:45 lr: 1.859608195273013e-05 loss: 0.0891 (0.0970) time: 2.9595 data: 0.0062 max mem: 33301 +Epoch: [26] [2880/4276] eta: 1:08:16 lr: 1.859314534286644e-05 loss: 0.0925 (0.0970) time: 2.9628 data: 0.0064 max mem: 33301 +Epoch: [26] [2890/4276] eta: 1:07:47 lr: 1.8590208681467465e-05 loss: 0.0928 (0.0971) time: 2.9542 data: 0.0066 max mem: 33301 +Epoch: [26] [2900/4276] eta: 1:07:18 lr: 1.8587271968523237e-05 loss: 0.0882 (0.0970) time: 2.9415 data: 0.0068 max mem: 33301 +Epoch: [26] [2910/4276] eta: 1:06:48 lr: 1.8584335204023813e-05 loss: 0.0979 (0.0971) time: 2.9393 data: 0.0065 max mem: 33301 +Epoch: [26] [2920/4276] eta: 1:06:19 lr: 1.8581398387959232e-05 loss: 0.1096 (0.0971) time: 2.9390 data: 0.0062 max mem: 33301 +Epoch: [26] [2930/4276] eta: 1:05:50 lr: 1.8578461520319544e-05 loss: 0.1052 (0.0972) time: 2.9407 data: 0.0064 max mem: 33301 +Epoch: [26] [2940/4276] eta: 1:05:20 lr: 1.8575524601094767e-05 loss: 0.1007 (0.0972) time: 2.9396 data: 0.0065 max mem: 33301 +Epoch: [26] [2950/4276] eta: 1:04:51 lr: 1.857258763027494e-05 loss: 0.1008 (0.0972) time: 2.9373 data: 0.0065 max mem: 33301 +Epoch: [26] [2960/4276] eta: 1:04:22 lr: 1.856965060785009e-05 loss: 0.0993 (0.0972) time: 2.9364 data: 0.0066 max mem: 33301 +Epoch: [26] [2970/4276] eta: 1:03:52 lr: 1.856671353381025e-05 loss: 0.0973 (0.0972) time: 2.9376 data: 0.0066 max mem: 33301 +Epoch: [26] [2980/4276] eta: 1:03:23 lr: 1.8563776408145422e-05 loss: 0.0973 (0.0972) time: 2.9421 data: 0.0067 max mem: 33301 +Epoch: [26] [2990/4276] eta: 1:02:54 lr: 1.8560839230845633e-05 loss: 0.0915 (0.0972) time: 2.9422 data: 0.0065 max mem: 33301 +Epoch: [26] [3000/4276] eta: 1:02:24 lr: 1.8557902001900897e-05 loss: 0.0886 (0.0971) time: 2.9442 data: 0.0066 max mem: 33301 +Epoch: [26] [3010/4276] eta: 1:01:55 lr: 1.855496472130123e-05 loss: 0.0934 (0.0972) time: 2.9446 data: 0.0066 max mem: 33301 +Epoch: [26] [3020/4276] eta: 1:01:26 lr: 1.855202738903662e-05 loss: 0.0940 (0.0971) time: 2.9415 data: 0.0066 max mem: 33301 +Epoch: [26] [3030/4276] eta: 1:00:56 lr: 1.8549090005097083e-05 loss: 0.0895 (0.0971) time: 2.9413 data: 0.0066 max mem: 33301 +Epoch: [26] [3040/4276] eta: 1:00:27 lr: 1.8546152569472618e-05 loss: 0.0920 (0.0971) time: 2.9405 data: 0.0066 max mem: 33301 +Epoch: [26] [3050/4276] eta: 0:59:58 lr: 1.8543215082153207e-05 loss: 0.0960 (0.0971) time: 2.9386 data: 0.0066 max mem: 33301 +Epoch: [26] [3060/4276] eta: 0:59:28 lr: 1.854027754312885e-05 loss: 0.0907 (0.0971) time: 2.9437 data: 0.0066 max mem: 33301 +Epoch: [26] [3070/4276] eta: 0:58:59 lr: 1.853733995238953e-05 loss: 0.0883 (0.0971) time: 2.9454 data: 0.0067 max mem: 33301 +Epoch: [26] [3080/4276] eta: 0:58:30 lr: 1.8534402309925238e-05 loss: 0.0839 (0.0971) time: 2.9374 data: 0.0069 max mem: 33301 +Epoch: [26] [3090/4276] eta: 0:58:00 lr: 1.8531464615725947e-05 loss: 0.0829 (0.0970) time: 2.9377 data: 0.0067 max mem: 33301 +Epoch: [26] [3100/4276] eta: 0:57:31 lr: 1.8528526869781635e-05 loss: 0.0865 (0.0970) time: 2.9459 data: 0.0066 max mem: 33301 +Epoch: [26] [3110/4276] eta: 0:57:02 lr: 1.852558907208227e-05 loss: 0.0984 (0.0970) time: 2.9432 data: 0.0067 max mem: 33301 +Epoch: [26] [3120/4276] eta: 0:56:32 lr: 1.8522651222617833e-05 loss: 0.1001 (0.0970) time: 2.9377 data: 0.0068 max mem: 33301 +Epoch: [26] [3130/4276] eta: 0:56:03 lr: 1.8519713321378277e-05 loss: 0.0803 (0.0970) time: 2.9388 data: 0.0066 max mem: 33301 +Epoch: [26] [3140/4276] eta: 0:55:34 lr: 1.8516775368353565e-05 loss: 0.0815 (0.0970) time: 2.9361 data: 0.0065 max mem: 33301 +Epoch: [26] [3150/4276] eta: 0:55:04 lr: 1.8513837363533653e-05 loss: 0.0882 (0.0970) time: 2.9380 data: 0.0066 max mem: 33301 +Epoch: [26] [3160/4276] eta: 0:54:35 lr: 1.8510899306908507e-05 loss: 0.0887 (0.0969) time: 2.9223 data: 0.0070 max mem: 33301 +Epoch: [26] [3170/4276] eta: 0:54:06 lr: 1.8507961198468063e-05 loss: 0.0841 (0.0969) time: 2.9215 data: 0.0083 max mem: 33301 +Epoch: [26] [3180/4276] eta: 0:53:36 lr: 1.8505023038202273e-05 loss: 0.0841 (0.0969) time: 2.9415 data: 0.0078 max mem: 33301 +Epoch: [26] [3190/4276] eta: 0:53:07 lr: 1.850208482610108e-05 loss: 0.0906 (0.0969) time: 2.9473 data: 0.0068 max mem: 33301 +Epoch: [26] [3200/4276] eta: 0:52:38 lr: 1.8499146562154425e-05 loss: 0.0906 (0.0969) time: 2.9381 data: 0.0079 max mem: 33301 +Epoch: [26] [3210/4276] eta: 0:52:08 lr: 1.8496208246352234e-05 loss: 0.0898 (0.0969) time: 2.9387 data: 0.0080 max mem: 33301 +Epoch: [26] [3220/4276] eta: 0:51:39 lr: 1.8493269878684447e-05 loss: 0.0900 (0.0969) time: 2.9466 data: 0.0074 max mem: 33301 +Epoch: [26] [3230/4276] eta: 0:51:10 lr: 1.8490331459140985e-05 loss: 0.0842 (0.0969) time: 2.9403 data: 0.0074 max mem: 33301 +Epoch: [26] [3240/4276] eta: 0:50:40 lr: 1.8487392987711784e-05 loss: 0.0943 (0.0969) time: 2.9401 data: 0.0076 max mem: 33301 +Epoch: [26] [3250/4276] eta: 0:50:11 lr: 1.848445446438675e-05 loss: 0.0945 (0.0969) time: 2.9411 data: 0.0074 max mem: 33301 +Epoch: [26] [3260/4276] eta: 0:49:42 lr: 1.8481515889155808e-05 loss: 0.0964 (0.0970) time: 2.9235 data: 0.0078 max mem: 33301 +Epoch: [26] [3270/4276] eta: 0:49:12 lr: 1.847857726200887e-05 loss: 0.0964 (0.0970) time: 2.9227 data: 0.0078 max mem: 33301 +Epoch: [26] [3280/4276] eta: 0:48:43 lr: 1.8475638582935847e-05 loss: 0.0995 (0.0970) time: 2.9393 data: 0.0069 max mem: 33301 +Epoch: [26] [3290/4276] eta: 0:48:14 lr: 1.8472699851926633e-05 loss: 0.1083 (0.0970) time: 2.9384 data: 0.0067 max mem: 33301 +Epoch: [26] [3300/4276] eta: 0:47:44 lr: 1.846976106897114e-05 loss: 0.0984 (0.0971) time: 2.9423 data: 0.0067 max mem: 33301 +Epoch: [26] [3310/4276] eta: 0:47:15 lr: 1.8466822234059263e-05 loss: 0.0992 (0.0971) time: 2.9410 data: 0.0068 max mem: 33301 +Epoch: [26] [3320/4276] eta: 0:46:46 lr: 1.84638833471809e-05 loss: 0.1196 (0.0972) time: 2.9363 data: 0.0068 max mem: 33301 +Epoch: [26] [3330/4276] eta: 0:46:16 lr: 1.8460944408325932e-05 loss: 0.0955 (0.0972) time: 2.9385 data: 0.0067 max mem: 33301 +Epoch: [26] [3340/4276] eta: 0:45:47 lr: 1.845800541748425e-05 loss: 0.0847 (0.0972) time: 2.9426 data: 0.0068 max mem: 33301 +Epoch: [26] [3350/4276] eta: 0:45:18 lr: 1.8455066374645745e-05 loss: 0.0947 (0.0972) time: 2.9420 data: 0.0068 max mem: 33301 +Epoch: [26] [3360/4276] eta: 0:44:48 lr: 1.845212727980028e-05 loss: 0.0892 (0.0971) time: 2.9378 data: 0.0067 max mem: 33301 +Epoch: [26] [3370/4276] eta: 0:44:19 lr: 1.8449188132937742e-05 loss: 0.0873 (0.0972) time: 2.9306 data: 0.0070 max mem: 33301 +Epoch: [26] [3380/4276] eta: 0:43:49 lr: 1.8446248934047996e-05 loss: 0.1082 (0.0972) time: 2.9214 data: 0.0078 max mem: 33301 +Epoch: [26] [3390/4276] eta: 0:43:20 lr: 1.844330968312092e-05 loss: 0.0853 (0.0972) time: 2.9273 data: 0.0077 max mem: 33301 +Epoch: [26] [3400/4276] eta: 0:42:51 lr: 1.8440370380146366e-05 loss: 0.0948 (0.0972) time: 2.9318 data: 0.0070 max mem: 33301 +Epoch: [26] [3410/4276] eta: 0:42:21 lr: 1.8437431025114197e-05 loss: 0.1004 (0.0972) time: 2.9319 data: 0.0070 max mem: 33301 +Epoch: [26] [3420/4276] eta: 0:41:52 lr: 1.8434491618014273e-05 loss: 0.0950 (0.0973) time: 2.9368 data: 0.0069 max mem: 33301 +Epoch: [26] [3430/4276] eta: 0:41:23 lr: 1.8431552158836445e-05 loss: 0.1008 (0.0973) time: 2.9374 data: 0.0067 max mem: 33301 +Epoch: [26] [3440/4276] eta: 0:40:53 lr: 1.842861264757056e-05 loss: 0.0937 (0.0973) time: 2.9386 data: 0.0068 max mem: 33301 +Epoch: [26] [3450/4276] eta: 0:40:24 lr: 1.8425673084206464e-05 loss: 0.0882 (0.0973) time: 2.9373 data: 0.0067 max mem: 33301 +Epoch: [26] [3460/4276] eta: 0:39:55 lr: 1.8422733468734e-05 loss: 0.1025 (0.0974) time: 2.9400 data: 0.0068 max mem: 33301 +Epoch: [26] [3470/4276] eta: 0:39:25 lr: 1.8419793801143006e-05 loss: 0.0918 (0.0974) time: 2.9416 data: 0.0067 max mem: 33301 +Epoch: [26] [3480/4276] eta: 0:38:56 lr: 1.8416854081423313e-05 loss: 0.0916 (0.0974) time: 2.9400 data: 0.0067 max mem: 33301 +Epoch: [26] [3490/4276] eta: 0:38:27 lr: 1.841391430956475e-05 loss: 0.0939 (0.0974) time: 2.9424 data: 0.0069 max mem: 33301 +Epoch: [26] [3500/4276] eta: 0:37:57 lr: 1.8410974485557144e-05 loss: 0.0939 (0.0974) time: 2.9407 data: 0.0069 max mem: 33301 +Epoch: [26] [3510/4276] eta: 0:37:28 lr: 1.8408034609390322e-05 loss: 0.0905 (0.0974) time: 2.9364 data: 0.0068 max mem: 33301 +Epoch: [26] [3520/4276] eta: 0:36:59 lr: 1.8405094681054098e-05 loss: 0.0936 (0.0974) time: 2.9348 data: 0.0068 max mem: 33301 +Epoch: [26] [3530/4276] eta: 0:36:29 lr: 1.8402154700538286e-05 loss: 0.0995 (0.0974) time: 2.9356 data: 0.0071 max mem: 33301 +Epoch: [26] [3540/4276] eta: 0:36:00 lr: 1.8399214667832695e-05 loss: 0.0982 (0.0974) time: 2.9371 data: 0.0071 max mem: 33301 +Epoch: [26] [3550/4276] eta: 0:35:30 lr: 1.8396274582927143e-05 loss: 0.0936 (0.0974) time: 2.9354 data: 0.0067 max mem: 33301 +Epoch: [26] [3560/4276] eta: 0:35:01 lr: 1.8393334445811423e-05 loss: 0.0932 (0.0975) time: 2.9321 data: 0.0070 max mem: 33301 +Epoch: [26] [3570/4276] eta: 0:34:32 lr: 1.8390394256475335e-05 loss: 0.0980 (0.0975) time: 2.9338 data: 0.0071 max mem: 33301 +Epoch: [26] [3580/4276] eta: 0:34:02 lr: 1.8387454014908678e-05 loss: 0.0871 (0.0975) time: 2.9463 data: 0.0073 max mem: 33301 +Epoch: [26] [3590/4276] eta: 0:33:33 lr: 1.8384513721101248e-05 loss: 0.0871 (0.0975) time: 2.9510 data: 0.0073 max mem: 33301 +Epoch: [26] [3600/4276] eta: 0:33:04 lr: 1.8381573375042824e-05 loss: 0.0974 (0.0975) time: 2.9438 data: 0.0073 max mem: 33301 +Epoch: [26] [3610/4276] eta: 0:32:34 lr: 1.8378632976723193e-05 loss: 0.0893 (0.0975) time: 2.9390 data: 0.0075 max mem: 33301 +Epoch: [26] [3620/4276] eta: 0:32:05 lr: 1.8375692526132136e-05 loss: 0.0895 (0.0974) time: 2.9395 data: 0.0074 max mem: 33301 +Epoch: [26] [3630/4276] eta: 0:31:36 lr: 1.8372752023259437e-05 loss: 0.0913 (0.0975) time: 2.9266 data: 0.0075 max mem: 33301 +Epoch: [26] [3640/4276] eta: 0:31:06 lr: 1.8369811468094857e-05 loss: 0.0943 (0.0974) time: 2.9290 data: 0.0079 max mem: 33301 +Epoch: [26] [3650/4276] eta: 0:30:37 lr: 1.836687086062817e-05 loss: 0.0806 (0.0974) time: 2.9357 data: 0.0080 max mem: 33301 +Epoch: [26] [3660/4276] eta: 0:30:08 lr: 1.836393020084915e-05 loss: 0.0869 (0.0974) time: 2.9343 data: 0.0073 max mem: 33301 +Epoch: [26] [3670/4276] eta: 0:29:38 lr: 1.8360989488747544e-05 loss: 0.1006 (0.0974) time: 2.9415 data: 0.0067 max mem: 33301 +Epoch: [26] [3680/4276] eta: 0:29:09 lr: 1.8358048724313114e-05 loss: 0.1066 (0.0974) time: 2.9411 data: 0.0068 max mem: 33301 +Epoch: [26] [3690/4276] eta: 0:28:40 lr: 1.8355107907535615e-05 loss: 0.0955 (0.0974) time: 2.9435 data: 0.0067 max mem: 33301 +Epoch: [26] [3700/4276] eta: 0:28:10 lr: 1.8352167038404806e-05 loss: 0.0906 (0.0974) time: 2.9410 data: 0.0068 max mem: 33301 +Epoch: [26] [3710/4276] eta: 0:27:41 lr: 1.8349226116910413e-05 loss: 0.0914 (0.0974) time: 2.9393 data: 0.0067 max mem: 33301 +Epoch: [26] [3720/4276] eta: 0:27:12 lr: 1.8346285143042197e-05 loss: 0.1008 (0.0974) time: 2.9394 data: 0.0068 max mem: 33301 +Epoch: [26] [3730/4276] eta: 0:26:42 lr: 1.8343344116789883e-05 loss: 0.0922 (0.0974) time: 2.9397 data: 0.0067 max mem: 33301 +Epoch: [26] [3740/4276] eta: 0:26:13 lr: 1.8340403038143218e-05 loss: 0.0903 (0.0974) time: 2.9412 data: 0.0068 max mem: 33301 +Epoch: [26] [3750/4276] eta: 0:25:44 lr: 1.8337461907091925e-05 loss: 0.0940 (0.0974) time: 2.9419 data: 0.0068 max mem: 33301 +Epoch: [26] [3760/4276] eta: 0:25:14 lr: 1.833452072362573e-05 loss: 0.0899 (0.0974) time: 2.9416 data: 0.0067 max mem: 33301 +Epoch: [26] [3770/4276] eta: 0:24:45 lr: 1.8331579487734356e-05 loss: 0.0871 (0.0974) time: 2.9423 data: 0.0067 max mem: 33301 +Epoch: [26] [3780/4276] eta: 0:24:16 lr: 1.832863819940753e-05 loss: 0.0831 (0.0974) time: 2.9402 data: 0.0067 max mem: 33301 +Epoch: [26] [3790/4276] eta: 0:23:46 lr: 1.832569685863496e-05 loss: 0.0772 (0.0973) time: 2.9375 data: 0.0067 max mem: 33301 +Epoch: [26] [3800/4276] eta: 0:23:17 lr: 1.8322755465406356e-05 loss: 0.0787 (0.0973) time: 2.9382 data: 0.0068 max mem: 33301 +Epoch: [26] [3810/4276] eta: 0:22:47 lr: 1.8319814019711428e-05 loss: 0.0829 (0.0973) time: 2.9456 data: 0.0068 max mem: 33301 +Epoch: [26] [3820/4276] eta: 0:22:18 lr: 1.8316872521539887e-05 loss: 0.0852 (0.0972) time: 2.9464 data: 0.0068 max mem: 33301 +Epoch: [26] [3830/4276] eta: 0:21:49 lr: 1.8313930970881425e-05 loss: 0.0883 (0.0972) time: 2.9378 data: 0.0069 max mem: 33301 +Epoch: [26] [3840/4276] eta: 0:21:19 lr: 1.8310989367725735e-05 loss: 0.0846 (0.0972) time: 2.9432 data: 0.0070 max mem: 33301 +Epoch: [26] [3850/4276] eta: 0:20:50 lr: 1.8308047712062516e-05 loss: 0.0782 (0.0972) time: 2.9441 data: 0.0070 max mem: 33301 +Epoch: [26] [3860/4276] eta: 0:20:21 lr: 1.8305106003881456e-05 loss: 0.0875 (0.0972) time: 2.9393 data: 0.0070 max mem: 33301 +Epoch: [26] [3870/4276] eta: 0:19:51 lr: 1.8302164243172233e-05 loss: 0.0961 (0.0972) time: 2.9408 data: 0.0068 max mem: 33301 +Epoch: [26] [3880/4276] eta: 0:19:22 lr: 1.8299222429924535e-05 loss: 0.0858 (0.0972) time: 2.9381 data: 0.0067 max mem: 33301 +Epoch: [26] [3890/4276] eta: 0:18:53 lr: 1.8296280564128034e-05 loss: 0.0845 (0.0972) time: 2.9424 data: 0.0068 max mem: 33301 +Epoch: [26] [3900/4276] eta: 0:18:23 lr: 1.829333864577241e-05 loss: 0.0843 (0.0972) time: 2.9382 data: 0.0072 max mem: 33301 +Epoch: [26] [3910/4276] eta: 0:17:54 lr: 1.829039667484732e-05 loss: 0.0841 (0.0971) time: 2.9347 data: 0.0071 max mem: 33301 +Epoch: [26] [3920/4276] eta: 0:17:25 lr: 1.828745465134244e-05 loss: 0.0800 (0.0971) time: 2.9424 data: 0.0070 max mem: 33301 +Epoch: [26] [3930/4276] eta: 0:16:55 lr: 1.8284512575247424e-05 loss: 0.0843 (0.0972) time: 2.9380 data: 0.0073 max mem: 33301 +Epoch: [26] [3940/4276] eta: 0:16:26 lr: 1.8281570446551934e-05 loss: 0.0992 (0.0972) time: 2.9399 data: 0.0071 max mem: 33301 +Epoch: [26] [3950/4276] eta: 0:15:57 lr: 1.8278628265245624e-05 loss: 0.0880 (0.0971) time: 2.9472 data: 0.0067 max mem: 33301 +Epoch: [26] [3960/4276] eta: 0:15:27 lr: 1.8275686031318135e-05 loss: 0.0821 (0.0971) time: 2.9464 data: 0.0068 max mem: 33301 +Epoch: [26] [3970/4276] eta: 0:14:58 lr: 1.8272743744759126e-05 loss: 0.0971 (0.0971) time: 2.9430 data: 0.0068 max mem: 33301 +Epoch: [26] [3980/4276] eta: 0:14:28 lr: 1.8269801405558225e-05 loss: 0.1042 (0.0971) time: 2.9360 data: 0.0069 max mem: 33301 +Epoch: [26] [3990/4276] eta: 0:13:59 lr: 1.8266859013705082e-05 loss: 0.0915 (0.0971) time: 2.9369 data: 0.0071 max mem: 33301 +Epoch: [26] [4000/4276] eta: 0:13:30 lr: 1.8263916569189322e-05 loss: 0.0896 (0.0971) time: 2.9545 data: 0.0069 max mem: 33301 +Epoch: [26] [4010/4276] eta: 0:13:00 lr: 1.826097407200058e-05 loss: 0.0948 (0.0971) time: 2.9508 data: 0.0068 max mem: 33301 +Epoch: [26] [4020/4276] eta: 0:12:31 lr: 1.8258031522128478e-05 loss: 0.0948 (0.0971) time: 2.9289 data: 0.0076 max mem: 33301 +Epoch: [26] [4030/4276] eta: 0:12:02 lr: 1.8255088919562645e-05 loss: 0.0891 (0.0971) time: 2.9313 data: 0.0075 max mem: 33301 +Epoch: [26] [4040/4276] eta: 0:11:32 lr: 1.8252146264292694e-05 loss: 0.0910 (0.0971) time: 2.9390 data: 0.0068 max mem: 33301 +Epoch: [26] [4050/4276] eta: 0:11:03 lr: 1.8249203556308244e-05 loss: 0.0870 (0.0971) time: 2.9394 data: 0.0070 max mem: 33301 +Epoch: [26] [4060/4276] eta: 0:10:34 lr: 1.82462607955989e-05 loss: 0.0820 (0.0971) time: 2.9399 data: 0.0070 max mem: 33301 +Epoch: [26] [4070/4276] eta: 0:10:04 lr: 1.824331798215427e-05 loss: 0.0885 (0.0971) time: 2.9396 data: 0.0068 max mem: 33301 +Epoch: [26] [4080/4276] eta: 0:09:35 lr: 1.8240375115963958e-05 loss: 0.0928 (0.0971) time: 2.9404 data: 0.0068 max mem: 33301 +Epoch: [26] [4090/4276] eta: 0:09:06 lr: 1.8237432197017566e-05 loss: 0.0970 (0.0971) time: 2.9414 data: 0.0068 max mem: 33301 +Epoch: [26] [4100/4276] eta: 0:08:36 lr: 1.8234489225304685e-05 loss: 0.0981 (0.0971) time: 2.9409 data: 0.0070 max mem: 33301 +Epoch: [26] [4110/4276] eta: 0:08:07 lr: 1.8231546200814902e-05 loss: 0.1055 (0.0972) time: 2.9386 data: 0.0073 max mem: 33301 +Epoch: [26] [4120/4276] eta: 0:07:38 lr: 1.8228603123537812e-05 loss: 0.0972 (0.0972) time: 2.9391 data: 0.0071 max mem: 33301 +Epoch: [26] [4130/4276] eta: 0:07:08 lr: 1.8225659993463e-05 loss: 0.0844 (0.0971) time: 2.9349 data: 0.0073 max mem: 33301 +Epoch: [26] [4140/4276] eta: 0:06:39 lr: 1.8222716810580035e-05 loss: 0.0844 (0.0971) time: 2.9335 data: 0.0073 max mem: 33301 +Epoch: [26] [4150/4276] eta: 0:06:09 lr: 1.8219773574878497e-05 loss: 0.0901 (0.0971) time: 2.9445 data: 0.0068 max mem: 33301 +Epoch: [26] [4160/4276] eta: 0:05:40 lr: 1.821683028634796e-05 loss: 0.0933 (0.0972) time: 2.9427 data: 0.0068 max mem: 33301 +Epoch: [26] [4170/4276] eta: 0:05:11 lr: 1.8213886944977993e-05 loss: 0.0953 (0.0972) time: 2.9316 data: 0.0071 max mem: 33301 +Epoch: [26] [4180/4276] eta: 0:04:41 lr: 1.821094355075815e-05 loss: 0.0921 (0.0972) time: 2.9309 data: 0.0071 max mem: 33301 +Epoch: [26] [4190/4276] eta: 0:04:12 lr: 1.8208000103677997e-05 loss: 0.0929 (0.0972) time: 2.9339 data: 0.0067 max mem: 33301 +Epoch: [26] [4200/4276] eta: 0:03:43 lr: 1.820505660372709e-05 loss: 0.1111 (0.0972) time: 2.9326 data: 0.0069 max mem: 33301 +Epoch: [26] [4210/4276] eta: 0:03:13 lr: 1.8202113050894983e-05 loss: 0.1111 (0.0972) time: 2.9333 data: 0.0070 max mem: 33301 +Epoch: [26] [4220/4276] eta: 0:02:44 lr: 1.819916944517122e-05 loss: 0.1029 (0.0973) time: 2.9361 data: 0.0069 max mem: 33301 +Epoch: [26] [4230/4276] eta: 0:02:15 lr: 1.819622578654534e-05 loss: 0.1031 (0.0973) time: 2.9376 data: 0.0069 max mem: 33301 +Epoch: [26] [4240/4276] eta: 0:01:45 lr: 1.819328207500689e-05 loss: 0.1034 (0.0973) time: 2.9291 data: 0.0074 max mem: 33301 +Epoch: [26] [4250/4276] eta: 0:01:16 lr: 1.8190338310545414e-05 loss: 0.1076 (0.0974) time: 2.9337 data: 0.0075 max mem: 33301 +Epoch: [26] [4260/4276] eta: 0:00:46 lr: 1.8187394493150424e-05 loss: 0.1010 (0.0974) time: 2.9435 data: 0.0070 max mem: 33301 +Epoch: [26] [4270/4276] eta: 0:00:17 lr: 1.818445062281146e-05 loss: 0.0957 (0.0974) time: 2.9342 data: 0.0069 max mem: 33301 +Epoch: [26] Total time: 3:29:14 +Test: [ 0/21770] eta: 8:52:49 time: 1.4685 data: 1.4299 max mem: 33301 +Test: [ 100/21770] eta: 0:19:01 time: 0.0386 data: 0.0009 max mem: 33301 +Test: [ 200/21770] eta: 0:16:24 time: 0.0385 data: 0.0009 max mem: 33301 +Test: [ 300/21770] eta: 0:15:30 time: 0.0389 data: 0.0009 max mem: 33301 +Test: [ 400/21770] eta: 0:15:01 time: 0.0387 data: 0.0009 max mem: 33301 +Test: [ 500/21770] eta: 0:14:42 time: 0.0388 data: 0.0009 max mem: 33301 +Test: [ 600/21770] eta: 0:14:28 time: 0.0385 data: 0.0009 max mem: 33301 +Test: [ 700/21770] eta: 0:14:17 time: 0.0388 data: 0.0009 max mem: 33301 +Test: [ 800/21770] eta: 0:14:08 time: 0.0389 data: 0.0009 max mem: 33301 +Test: [ 900/21770] eta: 0:14:01 time: 0.0391 data: 0.0009 max mem: 33301 +Test: [ 1000/21770] eta: 0:13:53 time: 0.0382 data: 0.0009 max mem: 33301 +Test: [ 1100/21770] eta: 0:13:45 time: 0.0380 data: 0.0009 max mem: 33301 +Test: [ 1200/21770] eta: 0:13:37 time: 0.0374 data: 0.0009 max mem: 33301 +Test: [ 1300/21770] eta: 0:13:30 time: 0.0376 data: 0.0009 max mem: 33301 +Test: [ 1400/21770] eta: 0:13:23 time: 0.0376 data: 0.0009 max mem: 33301 +Test: [ 1500/21770] eta: 0:13:16 time: 0.0375 data: 0.0009 max mem: 33301 +Test: [ 1600/21770] eta: 0:13:11 time: 0.0388 data: 0.0009 max mem: 33301 +Test: [ 1700/21770] eta: 0:13:07 time: 0.0390 data: 0.0008 max mem: 33301 +Test: [ 1800/21770] eta: 0:13:02 time: 0.0390 data: 0.0009 max mem: 33301 +Test: [ 1900/21770] eta: 0:12:58 time: 0.0391 data: 0.0009 max mem: 33301 +Test: [ 2000/21770] eta: 0:12:54 time: 0.0389 data: 0.0009 max mem: 33301 +Test: [ 2100/21770] eta: 0:12:50 time: 0.0392 data: 0.0009 max mem: 33301 +Test: [ 2200/21770] eta: 0:12:46 time: 0.0391 data: 0.0009 max mem: 33301 +Test: [ 2300/21770] eta: 0:12:42 time: 0.0389 data: 0.0009 max mem: 33301 +Test: [ 2400/21770] eta: 0:12:38 time: 0.0399 data: 0.0009 max mem: 33301 +Test: [ 2500/21770] eta: 0:12:35 time: 0.0400 data: 0.0008 max mem: 33301 +Test: [ 2600/21770] eta: 0:12:32 time: 0.0399 data: 0.0008 max mem: 33301 +Test: [ 2700/21770] eta: 0:12:28 time: 0.0397 data: 0.0009 max mem: 33301 +Test: [ 2800/21770] eta: 0:12:25 time: 0.0397 data: 0.0008 max mem: 33301 +Test: [ 2900/21770] eta: 0:12:21 time: 0.0395 data: 0.0008 max mem: 33301 +Test: [ 3000/21770] eta: 0:12:17 time: 0.0395 data: 0.0008 max mem: 33301 +Test: [ 3100/21770] eta: 0:12:13 time: 0.0396 data: 0.0008 max mem: 33301 +Test: [ 3200/21770] eta: 0:12:10 time: 0.0397 data: 0.0008 max mem: 33301 +Test: [ 3300/21770] eta: 0:12:06 time: 0.0396 data: 0.0008 max mem: 33301 +Test: [ 3400/21770] eta: 0:12:02 time: 0.0392 data: 0.0008 max mem: 33301 +Test: [ 3500/21770] eta: 0:11:58 time: 0.0393 data: 0.0008 max mem: 33301 +Test: [ 3600/21770] eta: 0:11:54 time: 0.0394 data: 0.0008 max mem: 33301 +Test: [ 3700/21770] eta: 0:11:50 time: 0.0393 data: 0.0008 max mem: 33301 +Test: [ 3800/21770] eta: 0:11:46 time: 0.0392 data: 0.0008 max mem: 33301 +Test: [ 3900/21770] eta: 0:11:42 time: 0.0396 data: 0.0009 max mem: 33301 +Test: [ 4000/21770] eta: 0:11:38 time: 0.0391 data: 0.0008 max mem: 33301 +Test: [ 4100/21770] eta: 0:11:34 time: 0.0393 data: 0.0008 max mem: 33301 +Test: [ 4200/21770] eta: 0:11:30 time: 0.0394 data: 0.0009 max mem: 33301 +Test: [ 4300/21770] eta: 0:11:27 time: 0.0393 data: 0.0008 max mem: 33301 +Test: [ 4400/21770] eta: 0:11:23 time: 0.0391 data: 0.0008 max mem: 33301 +Test: [ 4500/21770] eta: 0:11:19 time: 0.0391 data: 0.0008 max mem: 33301 +Test: [ 4600/21770] eta: 0:11:15 time: 0.0387 data: 0.0008 max mem: 33301 +Test: [ 4700/21770] eta: 0:11:11 time: 0.0392 data: 0.0008 max mem: 33301 +Test: [ 4800/21770] eta: 0:11:06 time: 0.0387 data: 0.0008 max mem: 33301 +Test: [ 4900/21770] eta: 0:11:02 time: 0.0392 data: 0.0008 max mem: 33301 +Test: [ 5000/21770] eta: 0:10:58 time: 0.0388 data: 0.0008 max mem: 33301 +Test: [ 5100/21770] eta: 0:10:54 time: 0.0393 data: 0.0008 max mem: 33301 +Test: [ 5200/21770] eta: 0:10:50 time: 0.0389 data: 0.0008 max mem: 33301 +Test: [ 5300/21770] eta: 0:10:46 time: 0.0392 data: 0.0008 max mem: 33301 +Test: [ 5400/21770] eta: 0:10:42 time: 0.0389 data: 0.0008 max mem: 33301 +Test: [ 5500/21770] eta: 0:10:38 time: 0.0390 data: 0.0008 max mem: 33301 +Test: [ 5600/21770] eta: 0:10:34 time: 0.0388 data: 0.0008 max mem: 33301 +Test: [ 5700/21770] eta: 0:10:30 time: 0.0392 data: 0.0008 max mem: 33301 +Test: [ 5800/21770] eta: 0:10:26 time: 0.0389 data: 0.0009 max mem: 33301 +Test: [ 5900/21770] eta: 0:10:22 time: 0.0390 data: 0.0008 max mem: 33301 +Test: [ 6000/21770] eta: 0:10:18 time: 0.0388 data: 0.0008 max mem: 33301 +Test: [ 6100/21770] eta: 0:10:14 time: 0.0390 data: 0.0008 max mem: 33301 +Test: [ 6200/21770] eta: 0:10:10 time: 0.0387 data: 0.0008 max mem: 33301 +Test: [ 6300/21770] eta: 0:10:06 time: 0.0392 data: 0.0008 max mem: 33301 +Test: [ 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time: 0.0384 data: 0.0008 max mem: 33301 +Test: [ 7800/21770] eta: 0:09:05 time: 0.0381 data: 0.0008 max mem: 33301 +Test: [ 7900/21770] eta: 0:09:01 time: 0.0385 data: 0.0008 max mem: 33301 +Test: [ 8000/21770] eta: 0:08:57 time: 0.0385 data: 0.0008 max mem: 33301 +Test: [ 8100/21770] eta: 0:08:53 time: 0.0389 data: 0.0008 max mem: 33301 +Test: [ 8200/21770] eta: 0:08:49 time: 0.0385 data: 0.0008 max mem: 33301 +Test: [ 8300/21770] eta: 0:08:45 time: 0.0390 data: 0.0008 max mem: 33301 +Test: [ 8400/21770] eta: 0:08:42 time: 0.0388 data: 0.0008 max mem: 33301 +Test: [ 8500/21770] eta: 0:08:38 time: 0.0391 data: 0.0008 max mem: 33301 +Test: [ 8600/21770] eta: 0:08:34 time: 0.0389 data: 0.0008 max mem: 33301 +Test: [ 8700/21770] eta: 0:08:30 time: 0.0390 data: 0.0008 max mem: 33301 +Test: [ 8800/21770] eta: 0:08:26 time: 0.0383 data: 0.0008 max mem: 33301 +Test: [ 8900/21770] eta: 0:08:22 time: 0.0387 data: 0.0008 max mem: 33301 +Test: [ 9000/21770] eta: 0:08:18 time: 0.0391 data: 0.0008 max mem: 33301 +Test: [ 9100/21770] eta: 0:08:14 time: 0.0393 data: 0.0008 max mem: 33301 +Test: [ 9200/21770] eta: 0:08:10 time: 0.0389 data: 0.0009 max mem: 33301 +Test: [ 9300/21770] eta: 0:08:06 time: 0.0375 data: 0.0009 max mem: 33301 +Test: [ 9400/21770] eta: 0:08:02 time: 0.0380 data: 0.0009 max mem: 33301 +Test: [ 9500/21770] eta: 0:07:58 time: 0.0390 data: 0.0008 max mem: 33301 +Test: [ 9600/21770] eta: 0:07:54 time: 0.0388 data: 0.0008 max mem: 33301 +Test: [ 9700/21770] eta: 0:07:50 time: 0.0391 data: 0.0008 max mem: 33301 +Test: [ 9800/21770] eta: 0:07:46 time: 0.0388 data: 0.0008 max mem: 33301 +Test: [ 9900/21770] eta: 0:07:42 time: 0.0392 data: 0.0008 max mem: 33301 +Test: [10000/21770] eta: 0:07:39 time: 0.0389 data: 0.0008 max mem: 33301 +Test: [10100/21770] eta: 0:07:35 time: 0.0393 data: 0.0008 max mem: 33301 +Test: [10200/21770] eta: 0:07:31 time: 0.0389 data: 0.0008 max mem: 33301 +Test: [10300/21770] eta: 0:07:27 time: 0.0391 data: 0.0008 max mem: 33301 +Test: [10400/21770] eta: 0:07:23 time: 0.0387 data: 0.0008 max mem: 33301 +Test: [10500/21770] eta: 0:07:19 time: 0.0390 data: 0.0008 max mem: 33301 +Test: [10600/21770] eta: 0:07:15 time: 0.0389 data: 0.0008 max mem: 33301 +Test: [10700/21770] eta: 0:07:11 time: 0.0391 data: 0.0008 max mem: 33301 +Test: [10800/21770] eta: 0:07:07 time: 0.0388 data: 0.0008 max mem: 33301 +Test: [10900/21770] eta: 0:07:03 time: 0.0391 data: 0.0008 max mem: 33301 +Test: [11000/21770] eta: 0:07:00 time: 0.0388 data: 0.0008 max mem: 33301 +Test: [11100/21770] eta: 0:06:56 time: 0.0390 data: 0.0008 max mem: 33301 +Test: [11200/21770] eta: 0:06:52 time: 0.0389 data: 0.0008 max mem: 33301 +Test: [11300/21770] eta: 0:06:48 time: 0.0392 data: 0.0008 max mem: 33301 +Test: [11400/21770] eta: 0:06:44 time: 0.0389 data: 0.0008 max mem: 33301 +Test: [11500/21770] eta: 0:06:40 time: 0.0392 data: 0.0008 max mem: 33301 +Test: [11600/21770] eta: 0:06:36 time: 0.0389 data: 0.0008 max mem: 33301 +Test: [11700/21770] eta: 0:06:32 time: 0.0391 data: 0.0008 max mem: 33301 +Test: [11800/21770] eta: 0:06:28 time: 0.0388 data: 0.0008 max mem: 33301 +Test: [11900/21770] eta: 0:06:24 time: 0.0391 data: 0.0008 max mem: 33301 +Test: [12000/21770] eta: 0:06:21 time: 0.0389 data: 0.0008 max mem: 33301 +Test: [12100/21770] eta: 0:06:17 time: 0.0392 data: 0.0008 max mem: 33301 +Test: [12200/21770] eta: 0:06:13 time: 0.0389 data: 0.0008 max mem: 33301 +Test: [12300/21770] eta: 0:06:09 time: 0.0390 data: 0.0008 max mem: 33301 +Test: [12400/21770] eta: 0:06:05 time: 0.0389 data: 0.0008 max mem: 33301 +Test: [12500/21770] eta: 0:06:01 time: 0.0391 data: 0.0008 max mem: 33301 +Test: [12600/21770] eta: 0:05:57 time: 0.0389 data: 0.0008 max mem: 33301 +Test: [12700/21770] eta: 0:05:53 time: 0.0392 data: 0.0008 max mem: 33301 +Test: [12800/21770] eta: 0:05:49 time: 0.0389 data: 0.0008 max mem: 33301 +Test: [12900/21770] eta: 0:05:45 time: 0.0390 data: 0.0008 max mem: 33301 +Test: [13000/21770] eta: 0:05:42 time: 0.0388 data: 0.0008 max mem: 33301 +Test: [13100/21770] eta: 0:05:38 time: 0.0391 data: 0.0008 max mem: 33301 +Test: [13200/21770] eta: 0:05:34 time: 0.0388 data: 0.0008 max mem: 33301 +Test: [13300/21770] eta: 0:05:30 time: 0.0390 data: 0.0008 max mem: 33301 +Test: [13400/21770] eta: 0:05:26 time: 0.0388 data: 0.0008 max mem: 33301 +Test: [13500/21770] eta: 0:05:22 time: 0.0391 data: 0.0008 max mem: 33301 +Test: [13600/21770] eta: 0:05:18 time: 0.0388 data: 0.0008 max mem: 33301 +Test: [13700/21770] eta: 0:05:14 time: 0.0393 data: 0.0009 max mem: 33301 +Test: [13800/21770] eta: 0:05:10 time: 0.0389 data: 0.0008 max mem: 33301 +Test: [13900/21770] eta: 0:05:06 time: 0.0391 data: 0.0008 max mem: 33301 +Test: [14000/21770] eta: 0:05:02 time: 0.0389 data: 0.0008 max mem: 33301 +Test: [14100/21770] eta: 0:04:59 time: 0.0391 data: 0.0008 max mem: 33301 +Test: [14200/21770] eta: 0:04:55 time: 0.0388 data: 0.0008 max mem: 33301 +Test: [14300/21770] eta: 0:04:51 time: 0.0392 data: 0.0008 max mem: 33301 +Test: [14400/21770] eta: 0:04:47 time: 0.0387 data: 0.0008 max mem: 33301 +Test: [14500/21770] eta: 0:04:43 time: 0.0392 data: 0.0008 max mem: 33301 +Test: [14600/21770] eta: 0:04:39 time: 0.0389 data: 0.0008 max mem: 33301 +Test: [14700/21770] eta: 0:04:35 time: 0.0393 data: 0.0008 max mem: 33301 +Test: [14800/21770] eta: 0:04:31 time: 0.0388 data: 0.0008 max mem: 33301 +Test: [14900/21770] eta: 0:04:27 time: 0.0392 data: 0.0008 max mem: 33301 +Test: [15000/21770] eta: 0:04:23 time: 0.0388 data: 0.0008 max mem: 33301 +Test: [15100/21770] eta: 0:04:20 time: 0.0392 data: 0.0008 max mem: 33301 +Test: [15200/21770] eta: 0:04:16 time: 0.0388 data: 0.0008 max mem: 33301 +Test: [15300/21770] eta: 0:04:12 time: 0.0394 data: 0.0009 max mem: 33301 +Test: [15400/21770] eta: 0:04:08 time: 0.0387 data: 0.0008 max mem: 33301 +Test: [15500/21770] eta: 0:04:04 time: 0.0391 data: 0.0008 max mem: 33301 +Test: [15600/21770] eta: 0:04:00 time: 0.0388 data: 0.0008 max mem: 33301 +Test: [15700/21770] eta: 0:03:56 time: 0.0386 data: 0.0009 max mem: 33301 +Test: [15800/21770] eta: 0:03:52 time: 0.0386 data: 0.0008 max mem: 33301 +Test: [15900/21770] eta: 0:03:49 time: 0.0388 data: 0.0008 max mem: 33301 +Test: [16000/21770] eta: 0:03:45 time: 0.0387 data: 0.0008 max mem: 33301 +Test: [16100/21770] eta: 0:03:41 time: 0.0387 data: 0.0008 max mem: 33301 +Test: [16200/21770] eta: 0:03:37 time: 0.0391 data: 0.0008 max mem: 33301 +Test: [16300/21770] eta: 0:03:33 time: 0.0387 data: 0.0008 max mem: 33301 +Test: [16400/21770] eta: 0:03:29 time: 0.0389 data: 0.0008 max mem: 33301 +Test: [16500/21770] eta: 0:03:25 time: 0.0388 data: 0.0008 max mem: 33301 +Test: [16600/21770] eta: 0:03:21 time: 0.0390 data: 0.0008 max mem: 33301 +Test: [16700/21770] eta: 0:03:17 time: 0.0392 data: 0.0008 max mem: 33301 +Test: [16800/21770] eta: 0:03:13 time: 0.0390 data: 0.0008 max mem: 33301 +Test: [16900/21770] eta: 0:03:09 time: 0.0392 data: 0.0008 max mem: 33301 +Test: [17000/21770] eta: 0:03:06 time: 0.0390 data: 0.0008 max mem: 33301 +Test: [17100/21770] eta: 0:03:02 time: 0.0389 data: 0.0008 max mem: 33301 +Test: [17200/21770] eta: 0:02:58 time: 0.0386 data: 0.0008 max mem: 33301 +Test: [17300/21770] eta: 0:02:54 time: 0.0389 data: 0.0008 max mem: 33301 +Test: [17400/21770] eta: 0:02:50 time: 0.0387 data: 0.0008 max mem: 33301 +Test: [17500/21770] eta: 0:02:46 time: 0.0389 data: 0.0008 max mem: 33301 +Test: [17600/21770] eta: 0:02:42 time: 0.0386 data: 0.0008 max mem: 33301 +Test: [17700/21770] eta: 0:02:38 time: 0.0390 data: 0.0008 max mem: 33301 +Test: [17800/21770] eta: 0:02:34 time: 0.0387 data: 0.0008 max mem: 33301 +Test: [17900/21770] eta: 0:02:30 time: 0.0391 data: 0.0008 max mem: 33301 +Test: [18000/21770] eta: 0:02:27 time: 0.0386 data: 0.0008 max mem: 33301 +Test: [18100/21770] eta: 0:02:23 time: 0.0390 data: 0.0008 max mem: 33301 +Test: [18200/21770] eta: 0:02:19 time: 0.0387 data: 0.0008 max mem: 33301 +Test: [18300/21770] eta: 0:02:15 time: 0.0390 data: 0.0008 max mem: 33301 +Test: [18400/21770] eta: 0:02:11 time: 0.0388 data: 0.0008 max mem: 33301 +Test: [18500/21770] eta: 0:02:07 time: 0.0391 data: 0.0008 max mem: 33301 +Test: [18600/21770] eta: 0:02:03 time: 0.0389 data: 0.0008 max mem: 33301 +Test: [18700/21770] eta: 0:01:59 time: 0.0390 data: 0.0008 max mem: 33301 +Test: [18800/21770] eta: 0:01:55 time: 0.0386 data: 0.0008 max mem: 33301 +Test: [18900/21770] eta: 0:01:51 time: 0.0388 data: 0.0008 max mem: 33301 +Test: [19000/21770] eta: 0:01:47 time: 0.0379 data: 0.0009 max mem: 33301 +Test: [19100/21770] eta: 0:01:44 time: 0.0389 data: 0.0009 max mem: 33301 +Test: [19200/21770] eta: 0:01:40 time: 0.0386 data: 0.0009 max mem: 33301 +Test: [19300/21770] eta: 0:01:36 time: 0.0387 data: 0.0008 max mem: 33301 +Test: [19400/21770] eta: 0:01:32 time: 0.0384 data: 0.0008 max mem: 33301 +Test: [19500/21770] eta: 0:01:28 time: 0.0387 data: 0.0008 max mem: 33301 +Test: [19600/21770] eta: 0:01:24 time: 0.0386 data: 0.0008 max mem: 33301 +Test: [19700/21770] eta: 0:01:20 time: 0.0391 data: 0.0008 max mem: 33301 +Test: [19800/21770] eta: 0:01:16 time: 0.0386 data: 0.0008 max mem: 33301 +Test: [19900/21770] eta: 0:01:12 time: 0.0393 data: 0.0008 max mem: 33301 +Test: [20000/21770] eta: 0:01:08 time: 0.0390 data: 0.0008 max mem: 33301 +Test: [20100/21770] eta: 0:01:05 time: 0.0394 data: 0.0008 max mem: 33301 +Test: [20200/21770] eta: 0:01:01 time: 0.0389 data: 0.0008 max mem: 33301 +Test: [20300/21770] eta: 0:00:57 time: 0.0393 data: 0.0008 max mem: 33301 +Test: [20400/21770] eta: 0:00:53 time: 0.0388 data: 0.0008 max mem: 33301 +Test: [20500/21770] eta: 0:00:49 time: 0.0393 data: 0.0008 max mem: 33301 +Test: [20600/21770] eta: 0:00:45 time: 0.0389 data: 0.0008 max mem: 33301 +Test: [20700/21770] eta: 0:00:41 time: 0.0393 data: 0.0008 max mem: 33301 +Test: [20800/21770] eta: 0:00:37 time: 0.0389 data: 0.0008 max mem: 33301 +Test: [20900/21770] eta: 0:00:33 time: 0.0389 data: 0.0008 max mem: 33301 +Test: [21000/21770] eta: 0:00:30 time: 0.0386 data: 0.0008 max mem: 33301 +Test: [21100/21770] eta: 0:00:26 time: 0.0390 data: 0.0008 max mem: 33301 +Test: [21200/21770] eta: 0:00:22 time: 0.0387 data: 0.0008 max mem: 33301 +Test: [21300/21770] eta: 0:00:18 time: 0.0393 data: 0.0008 max mem: 33301 +Test: [21400/21770] eta: 0:00:14 time: 0.0391 data: 0.0008 max mem: 33301 +Test: [21500/21770] eta: 0:00:10 time: 0.0393 data: 0.0008 max mem: 33301 +Test: [21600/21770] eta: 0:00:06 time: 0.0380 data: 0.0009 max mem: 33301 +Test: [21700/21770] eta: 0:00:02 time: 0.0382 data: 0.0009 max mem: 33301 +Test: Total time: 0:14:08 +Final results: +Mean IoU is 0.00 + + precision@0.5 = 0.00 + precision@0.6 = 0.00 + precision@0.7 = 0.00 + precision@0.8 = 0.00 + precision@0.9 = 0.00 + overall IoU = 0.00 + mean IoU = 0.00 + +Mean accuracy for one-to-zero sample is 100.00 + +Average object IoU 0.0 +Overall IoU 0.0 +Epoch: [27] [ 0/4276] eta: 5:49:03 lr: 1.8182684275190614e-05 loss: 0.1300 (0.1300) time: 4.8980 data: 1.8027 max mem: 33301 +Epoch: [27] [ 10/4276] eta: 3:39:24 lr: 1.8179740320119498e-05 loss: 0.0953 (0.0950) time: 3.0858 data: 0.1716 max mem: 33301 +Epoch: [27] [ 20/4276] eta: 3:32:26 lr: 1.8176796312077164e-05 loss: 0.0855 (0.0967) time: 2.8998 data: 0.0078 max mem: 33301 +Epoch: [27] [ 30/4276] eta: 3:29:40 lr: 1.817385225105312e-05 loss: 0.0898 (0.0963) time: 2.8953 data: 0.0078 max mem: 33301 +Epoch: [27] [ 40/4276] eta: 3:28:04 lr: 1.8170908137036874e-05 loss: 0.0925 (0.0955) time: 2.8970 data: 0.0079 max mem: 33301 +Epoch: [27] [ 50/4276] eta: 3:26:42 lr: 1.8167963970017942e-05 loss: 0.0906 (0.0941) time: 2.8910 data: 0.0076 max mem: 33301 +Epoch: [27] [ 60/4276] eta: 3:25:48 lr: 1.8165019749985816e-05 loss: 0.0856 (0.0925) time: 2.8915 data: 0.0081 max mem: 33301 +Epoch: [27] [ 70/4276] eta: 3:25:10 lr: 1.816207547693e-05 loss: 0.0827 (0.0912) time: 2.9067 data: 0.0078 max mem: 33301 +Epoch: [27] [ 80/4276] eta: 3:24:45 lr: 1.815913115083998e-05 loss: 0.0835 (0.0926) time: 2.9252 data: 0.0078 max mem: 33301 +Epoch: [27] [ 90/4276] eta: 3:24:20 lr: 1.815618677170526e-05 loss: 0.0894 (0.0921) time: 2.9361 data: 0.0074 max mem: 33301 +Epoch: [27] [ 100/4276] eta: 3:23:47 lr: 1.8153242339515314e-05 loss: 0.0832 (0.0935) time: 2.9288 data: 0.0075 max mem: 33301 +Epoch: [27] [ 110/4276] eta: 3:23:22 lr: 1.8150297854259625e-05 loss: 0.0898 (0.0940) time: 2.9304 data: 0.0077 max mem: 33301 +Epoch: [27] [ 120/4276] eta: 3:22:56 lr: 1.8147353315927677e-05 loss: 0.0872 (0.0935) time: 2.9381 data: 0.0071 max mem: 33301 +Epoch: [27] [ 130/4276] eta: 3:22:29 lr: 1.814440872450894e-05 loss: 0.0858 (0.0940) time: 2.9373 data: 0.0071 max mem: 33301 +Epoch: [27] [ 140/4276] eta: 3:22:01 lr: 1.8141464079992884e-05 loss: 0.0899 (0.0944) time: 2.9361 data: 0.0073 max mem: 33301 +Epoch: [27] [ 150/4276] eta: 3:21:33 lr: 1.8138519382368973e-05 loss: 0.1006 (0.0950) time: 2.9360 data: 0.0070 max mem: 33301 +Epoch: [27] [ 160/4276] eta: 3:21:06 lr: 1.8135574631626674e-05 loss: 0.0990 (0.0945) time: 2.9388 data: 0.0069 max mem: 33301 +Epoch: [27] [ 170/4276] eta: 3:20:37 lr: 1.813262982775545e-05 loss: 0.0867 (0.0943) time: 2.9365 data: 0.0069 max mem: 33301 +Epoch: [27] [ 180/4276] eta: 3:20:13 lr: 1.8129684970744738e-05 loss: 0.0910 (0.0949) time: 2.9426 data: 0.0072 max mem: 33301 +Epoch: [27] [ 190/4276] eta: 3:19:44 lr: 1.8126740060584e-05 loss: 0.0859 (0.0945) time: 2.9453 data: 0.0073 max mem: 33301 +Epoch: [27] [ 200/4276] eta: 3:19:17 lr: 1.8123795097262676e-05 loss: 0.0859 (0.0947) time: 2.9402 data: 0.0070 max mem: 33301 +Epoch: [27] [ 210/4276] eta: 3:18:49 lr: 1.8120850080770224e-05 loss: 0.0897 (0.0949) time: 2.9407 data: 0.0069 max mem: 33301 +Epoch: [27] [ 220/4276] eta: 3:18:20 lr: 1.8117905011096062e-05 loss: 0.0855 (0.0947) time: 2.9383 data: 0.0070 max mem: 33301 +Epoch: [27] [ 230/4276] eta: 3:17:51 lr: 1.811495988822963e-05 loss: 0.0855 (0.0944) time: 2.9363 data: 0.0071 max mem: 33301 +Epoch: [27] [ 240/4276] eta: 3:17:22 lr: 1.8112014712160366e-05 loss: 0.0904 (0.0942) time: 2.9349 data: 0.0068 max mem: 33301 +Epoch: [27] [ 250/4276] eta: 3:16:53 lr: 1.8109069482877692e-05 loss: 0.0924 (0.0961) time: 2.9359 data: 0.0069 max mem: 33301 +Epoch: [27] [ 260/4276] eta: 3:16:24 lr: 1.8106124200371026e-05 loss: 0.0886 (0.0957) time: 2.9372 data: 0.0072 max mem: 33301 +Epoch: [27] [ 270/4276] eta: 3:15:55 lr: 1.8103178864629782e-05 loss: 0.0878 (0.0957) time: 2.9379 data: 0.0072 max mem: 33301 +Epoch: [27] [ 280/4276] eta: 3:15:27 lr: 1.8100233475643386e-05 loss: 0.0840 (0.0956) time: 2.9395 data: 0.0071 max mem: 33301 +Epoch: [27] [ 290/4276] eta: 3:14:58 lr: 1.8097288033401248e-05 loss: 0.0840 (0.0954) time: 2.9402 data: 0.0068 max mem: 33301 +Epoch: [27] [ 300/4276] eta: 3:14:30 lr: 1.809434253789276e-05 loss: 0.0908 (0.0953) time: 2.9407 data: 0.0071 max mem: 33301 +Epoch: [27] [ 310/4276] eta: 3:14:01 lr: 1.8091396989107335e-05 loss: 0.0854 (0.0949) time: 2.9406 data: 0.0075 max mem: 33301 +Epoch: [27] [ 320/4276] eta: 3:13:32 lr: 1.8088451387034365e-05 loss: 0.0865 (0.0952) time: 2.9390 data: 0.0071 max mem: 33301 +Epoch: [27] [ 330/4276] eta: 3:13:03 lr: 1.8085505731663254e-05 loss: 0.0994 (0.0955) time: 2.9374 data: 0.0066 max mem: 33301 +Epoch: [27] [ 340/4276] eta: 3:12:34 lr: 1.808256002298338e-05 loss: 0.0991 (0.0956) time: 2.9377 data: 0.0068 max mem: 33301 +Epoch: [27] [ 350/4276] eta: 3:12:05 lr: 1.8079614260984133e-05 loss: 0.0810 (0.0954) time: 2.9388 data: 0.0066 max mem: 33301 +Epoch: [27] [ 360/4276] eta: 3:11:36 lr: 1.8076668445654905e-05 loss: 0.0926 (0.0958) time: 2.9384 data: 0.0062 max mem: 33301 +Epoch: [27] [ 370/4276] eta: 3:11:03 lr: 1.8073722576985054e-05 loss: 0.0891 (0.0956) time: 2.9239 data: 0.0062 max mem: 33301 +Epoch: [27] [ 380/4276] eta: 3:10:31 lr: 1.807077665496397e-05 loss: 0.0863 (0.0957) time: 2.9054 data: 0.0069 max mem: 33301 +Epoch: [27] [ 390/4276] eta: 3:09:59 lr: 1.8067830679581007e-05 loss: 0.0994 (0.0960) time: 2.9037 data: 0.0074 max mem: 33301 +Epoch: [27] [ 400/4276] eta: 3:09:28 lr: 1.8064884650825554e-05 loss: 0.0957 (0.0961) time: 2.9111 data: 0.0072 max mem: 33301 +Epoch: [27] [ 410/4276] eta: 3:08:59 lr: 1.8061938568686948e-05 loss: 0.0930 (0.0960) time: 2.9313 data: 0.0071 max mem: 33301 +Epoch: [27] [ 420/4276] eta: 3:08:30 lr: 1.8058992433154563e-05 loss: 0.0918 (0.0961) time: 2.9409 data: 0.0071 max mem: 33301 +Epoch: [27] [ 430/4276] eta: 3:08:01 lr: 1.8056046244217743e-05 loss: 0.0922 (0.0963) time: 2.9353 data: 0.0073 max mem: 33301 +Epoch: [27] [ 440/4276] eta: 3:07:33 lr: 1.8053100001865846e-05 loss: 0.0846 (0.0960) time: 2.9384 data: 0.0075 max mem: 33301 +Epoch: [27] [ 450/4276] eta: 3:07:00 lr: 1.8050153706088207e-05 loss: 0.0871 (0.0964) time: 2.9156 data: 0.0074 max mem: 33301 +Epoch: [27] [ 460/4276] eta: 3:06:30 lr: 1.8047207356874176e-05 loss: 0.0934 (0.0959) time: 2.9087 data: 0.0076 max mem: 33301 +Epoch: [27] [ 470/4276] eta: 3:06:01 lr: 1.8044260954213084e-05 loss: 0.0762 (0.0957) time: 2.9318 data: 0.0075 max mem: 33301 +Epoch: [27] [ 480/4276] eta: 3:05:32 lr: 1.8041314498094277e-05 loss: 0.0829 (0.0958) time: 2.9386 data: 0.0073 max mem: 33301 +Epoch: [27] [ 490/4276] eta: 3:05:01 lr: 1.803836798850707e-05 loss: 0.0829 (0.0955) time: 2.9233 data: 0.0075 max mem: 33301 +Epoch: [27] [ 500/4276] eta: 3:04:28 lr: 1.8035421425440788e-05 loss: 0.0858 (0.0954) time: 2.8937 data: 0.0075 max mem: 33301 +Epoch: [27] [ 510/4276] eta: 3:03:56 lr: 1.8032474808884755e-05 loss: 0.0906 (0.0954) time: 2.8930 data: 0.0070 max mem: 33301 +Epoch: [27] [ 520/4276] eta: 3:03:28 lr: 1.80295281388283e-05 loss: 0.0938 (0.0955) time: 2.9229 data: 0.0070 max mem: 33301 +Epoch: [27] [ 530/4276] eta: 3:02:59 lr: 1.8026581415260717e-05 loss: 0.0922 (0.0956) time: 2.9377 data: 0.0075 max mem: 33301 +Epoch: [27] [ 540/4276] eta: 3:02:26 lr: 1.8023634638171324e-05 loss: 0.0804 (0.0954) time: 2.9066 data: 0.0073 max mem: 33301 +Epoch: [27] [ 550/4276] eta: 3:01:54 lr: 1.8020687807549424e-05 loss: 0.0942 (0.0958) time: 2.8841 data: 0.0076 max mem: 33301 +Epoch: [27] [ 560/4276] eta: 3:01:21 lr: 1.8017740923384326e-05 loss: 0.0958 (0.0959) time: 2.8869 data: 0.0074 max mem: 33301 +Epoch: [27] [ 570/4276] eta: 3:00:50 lr: 1.801479398566531e-05 loss: 0.0922 (0.0958) time: 2.8867 data: 0.0070 max mem: 33301 +Epoch: [27] [ 580/4276] eta: 3:00:18 lr: 1.801184699438168e-05 loss: 0.0922 (0.0959) time: 2.8904 data: 0.0072 max mem: 33301 +Epoch: [27] [ 590/4276] eta: 2:59:49 lr: 1.800889994952272e-05 loss: 0.0813 (0.0956) time: 2.9089 data: 0.0075 max mem: 33301 +Epoch: [27] [ 600/4276] eta: 2:59:18 lr: 1.800595285107772e-05 loss: 0.0785 (0.0954) time: 2.9148 data: 0.0077 max mem: 33301 +Epoch: [27] [ 610/4276] eta: 2:58:47 lr: 1.8003005699035953e-05 loss: 0.0836 (0.0953) time: 2.9004 data: 0.0074 max mem: 33301 +Epoch: [27] [ 620/4276] eta: 2:58:16 lr: 1.80000584933867e-05 loss: 0.0867 (0.0952) time: 2.8973 data: 0.0071 max mem: 33301 +Epoch: [27] [ 630/4276] eta: 2:57:45 lr: 1.799711123411923e-05 loss: 0.0963 (0.0955) time: 2.9001 data: 0.0074 max mem: 33301 +Epoch: [27] [ 640/4276] eta: 2:57:14 lr: 1.7994163921222815e-05 loss: 0.1028 (0.0956) time: 2.8959 data: 0.0073 max mem: 33301 +Epoch: [27] [ 650/4276] eta: 2:56:43 lr: 1.799121655468671e-05 loss: 0.0907 (0.0956) time: 2.8890 data: 0.0071 max mem: 33301 +Epoch: [27] [ 660/4276] eta: 2:56:15 lr: 1.7988269134500183e-05 loss: 0.0961 (0.0957) time: 2.9219 data: 0.0073 max mem: 33301 +Epoch: [27] [ 670/4276] eta: 2:55:46 lr: 1.798532166065249e-05 loss: 0.0978 (0.0956) time: 2.9371 data: 0.0078 max mem: 33301 +Epoch: [27] [ 680/4276] eta: 2:55:19 lr: 1.7982374133132876e-05 loss: 0.0871 (0.0956) time: 2.9468 data: 0.0073 max mem: 33301 +Epoch: [27] [ 690/4276] eta: 2:54:48 lr: 1.797942655193059e-05 loss: 0.0871 (0.0956) time: 2.9335 data: 0.0065 max mem: 33301 +Epoch: [27] [ 700/4276] eta: 2:54:17 lr: 1.7976478917034877e-05 loss: 0.0850 (0.0954) time: 2.8892 data: 0.0067 max mem: 33301 +Epoch: [27] [ 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33301 +Epoch: [27] [ 790/4276] eta: 2:49:50 lr: 1.794994778499236e-05 loss: 0.0954 (0.0953) time: 2.8913 data: 0.0098 max mem: 33301 +Epoch: [27] [ 800/4276] eta: 2:49:19 lr: 1.7946999612569847e-05 loss: 0.0974 (0.0955) time: 2.8912 data: 0.0098 max mem: 33301 +Epoch: [27] [ 810/4276] eta: 2:48:48 lr: 1.7944051386335308e-05 loss: 0.0951 (0.0955) time: 2.8904 data: 0.0098 max mem: 33301 +Epoch: [27] [ 820/4276] eta: 2:48:18 lr: 1.7941103106277944e-05 loss: 0.0871 (0.0954) time: 2.8905 data: 0.0100 max mem: 33301 +Epoch: [27] [ 830/4276] eta: 2:47:48 lr: 1.7938154772386944e-05 loss: 0.0865 (0.0954) time: 2.8940 data: 0.0101 max mem: 33301 +Epoch: [27] [ 840/4276] eta: 2:47:17 lr: 1.793520638465148e-05 loss: 0.1011 (0.0955) time: 2.8968 data: 0.0099 max mem: 33301 +Epoch: [27] [ 850/4276] eta: 2:46:47 lr: 1.7932257943060744e-05 loss: 0.0960 (0.0955) time: 2.8948 data: 0.0098 max mem: 33301 +Epoch: [27] [ 860/4276] eta: 2:46:17 lr: 1.7929309447603908e-05 loss: 0.0946 (0.0956) time: 2.9019 data: 0.0103 max mem: 33301 +Epoch: [27] [ 870/4276] eta: 2:45:49 lr: 1.792636089827016e-05 loss: 0.0855 (0.0954) time: 2.9275 data: 0.0099 max mem: 33301 +Epoch: [27] [ 880/4276] eta: 2:45:20 lr: 1.7923412295048648e-05 loss: 0.0755 (0.0954) time: 2.9353 data: 0.0095 max mem: 33301 +Epoch: [27] [ 890/4276] eta: 2:44:52 lr: 1.7920463637928544e-05 loss: 0.0998 (0.0956) time: 2.9340 data: 0.0086 max mem: 33301 +Epoch: [27] [ 900/4276] eta: 2:44:23 lr: 1.7917514926899014e-05 loss: 0.0959 (0.0956) time: 2.9420 data: 0.0080 max mem: 33301 +Epoch: [27] [ 910/4276] eta: 2:43:55 lr: 1.7914566161949213e-05 loss: 0.0914 (0.0957) time: 2.9415 data: 0.0081 max mem: 33301 +Epoch: [27] [ 920/4276] eta: 2:43:26 lr: 1.7911617343068286e-05 loss: 0.0951 (0.0959) time: 2.9363 data: 0.0085 max mem: 33301 +Epoch: [27] [ 930/4276] eta: 2:42:56 lr: 1.7908668470245387e-05 loss: 0.1000 (0.0958) time: 2.9241 data: 0.0090 max mem: 33301 +Epoch: [27] [ 940/4276] eta: 2:42:28 lr: 1.7905719543469653e-05 loss: 0.0897 (0.0958) time: 2.9291 data: 0.0089 max mem: 33301 +Epoch: [27] [ 950/4276] eta: 2:41:59 lr: 1.790277056273024e-05 loss: 0.1007 (0.0960) time: 2.9332 data: 0.0094 max mem: 33301 +Epoch: [27] [ 960/4276] eta: 2:41:30 lr: 1.7899821528016265e-05 loss: 0.0968 (0.0959) time: 2.9292 data: 0.0095 max mem: 33301 +Epoch: [27] [ 970/4276] eta: 2:41:01 lr: 1.7896872439316865e-05 loss: 0.0935 (0.0960) time: 2.9359 data: 0.0083 max mem: 33301 +Epoch: [27] [ 980/4276] eta: 2:40:33 lr: 1.7893923296621175e-05 loss: 0.0978 (0.0961) time: 2.9369 data: 0.0080 max mem: 33301 +Epoch: [27] [ 990/4276] eta: 2:40:03 lr: 1.7890974099918308e-05 loss: 0.0875 (0.0959) time: 2.9252 data: 0.0083 max mem: 33301 +Epoch: [27] [1000/4276] eta: 2:39:33 lr: 1.7888024849197385e-05 loss: 0.0807 (0.0959) time: 2.9065 data: 0.0084 max mem: 33301 +Epoch: [27] [1010/4276] eta: 2:39:04 lr: 1.788507554444752e-05 loss: 0.0963 (0.0960) time: 2.9127 data: 0.0088 max mem: 33301 +Epoch: [27] [1020/4276] eta: 2:38:35 lr: 1.7882126185657832e-05 loss: 0.0950 (0.0959) time: 2.9286 data: 0.0083 max mem: 33301 +Epoch: [27] [1030/4276] eta: 2:38:06 lr: 1.7879176772817415e-05 loss: 0.0950 (0.0960) time: 2.9310 data: 0.0080 max mem: 33301 +Epoch: [27] [1040/4276] eta: 2:37:37 lr: 1.787622730591538e-05 loss: 0.1045 (0.0961) time: 2.9311 data: 0.0080 max mem: 33301 +Epoch: [27] [1050/4276] eta: 2:37:08 lr: 1.787327778494082e-05 loss: 0.0954 (0.0962) time: 2.9334 data: 0.0078 max mem: 33301 +Epoch: [27] [1060/4276] eta: 2:36:39 lr: 1.7870328209882832e-05 loss: 0.0992 (0.0964) time: 2.9333 data: 0.0078 max mem: 33301 +Epoch: [27] [1070/4276] eta: 2:36:11 lr: 1.78673785807305e-05 loss: 0.1001 (0.0965) time: 2.9357 data: 0.0076 max mem: 33301 +Epoch: [27] [1080/4276] eta: 2:35:42 lr: 1.786442889747291e-05 loss: 0.0992 (0.0965) time: 2.9399 data: 0.0074 max mem: 33301 +Epoch: [27] [1090/4276] eta: 2:35:13 lr: 1.7861479160099145e-05 loss: 0.1021 (0.0966) time: 2.9409 data: 0.0075 max mem: 33301 +Epoch: [27] [1100/4276] eta: 2:34:44 lr: 1.785852936859829e-05 loss: 0.1021 (0.0967) time: 2.9393 data: 0.0075 max mem: 33301 +Epoch: [27] [1110/4276] eta: 2:34:16 lr: 1.7855579522959404e-05 loss: 0.1012 (0.0968) time: 2.9397 data: 0.0074 max mem: 33301 +Epoch: [27] [1120/4276] eta: 2:33:47 lr: 1.785262962317156e-05 loss: 0.0974 (0.0969) time: 2.9454 data: 0.0074 max mem: 33301 +Epoch: [27] [1130/4276] eta: 2:33:19 lr: 1.7849679669223824e-05 loss: 0.0885 (0.0968) time: 2.9493 data: 0.0077 max mem: 33301 +Epoch: [27] [1140/4276] eta: 2:32:50 lr: 1.784672966110526e-05 loss: 0.0905 (0.0969) time: 2.9454 data: 0.0077 max mem: 33301 +Epoch: [27] [1150/4276] eta: 2:32:21 lr: 1.7843779598804913e-05 loss: 0.0969 (0.0969) time: 2.9415 data: 0.0074 max mem: 33301 +Epoch: [27] [1160/4276] eta: 2:31:52 lr: 1.7840829482311842e-05 loss: 0.1021 (0.0970) time: 2.9437 data: 0.0075 max mem: 33301 +Epoch: [27] [1170/4276] eta: 2:31:24 lr: 1.783787931161509e-05 loss: 0.1086 (0.0970) time: 2.9445 data: 0.0075 max mem: 33301 +Epoch: [27] [1180/4276] eta: 2:30:55 lr: 1.783492908670371e-05 loss: 0.0919 (0.0970) time: 2.9403 data: 0.0075 max mem: 33301 +Epoch: [27] [1190/4276] eta: 2:30:26 lr: 1.7831978807566726e-05 loss: 0.0882 (0.0969) time: 2.9386 data: 0.0075 max mem: 33301 +Epoch: [27] [1200/4276] eta: 2:29:57 lr: 1.782902847419318e-05 loss: 0.0844 (0.0969) time: 2.9414 data: 0.0074 max mem: 33301 +Epoch: [27] [1210/4276] eta: 2:29:28 lr: 1.7826078086572105e-05 loss: 0.0825 (0.0967) time: 2.9432 data: 0.0075 max mem: 33301 +Epoch: [27] [1220/4276] eta: 2:28:59 lr: 1.7823127644692524e-05 loss: 0.0845 (0.0968) time: 2.9441 data: 0.0075 max mem: 33301 +Epoch: [27] [1230/4276] eta: 2:28:31 lr: 1.782017714854346e-05 loss: 0.0887 (0.0967) time: 2.9523 data: 0.0077 max mem: 33301 +Epoch: [27] [1240/4276] eta: 2:28:03 lr: 1.7817226598113925e-05 loss: 0.0867 (0.0966) time: 2.9595 data: 0.0087 max mem: 33301 +Epoch: [27] [1250/4276] eta: 2:27:34 lr: 1.781427599339294e-05 loss: 0.0867 (0.0967) time: 2.9513 data: 0.0089 max mem: 33301 +Epoch: [27] [1260/4276] eta: 2:27:04 lr: 1.7811325334369514e-05 loss: 0.0854 (0.0966) time: 2.9289 data: 0.0084 max mem: 33301 +Epoch: [27] [1270/4276] eta: 2:26:34 lr: 1.7808374621032644e-05 loss: 0.0785 (0.0965) time: 2.9018 data: 0.0088 max mem: 33301 +Epoch: [27] [1280/4276] eta: 2:26:04 lr: 1.780542385337134e-05 loss: 0.0915 (0.0965) time: 2.8892 data: 0.0088 max mem: 33301 +Epoch: [27] [1290/4276] eta: 2:25:34 lr: 1.7802473031374596e-05 loss: 0.1072 (0.0966) time: 2.8915 data: 0.0086 max mem: 33301 +Epoch: [27] [1300/4276] eta: 2:25:04 lr: 1.7799522155031395e-05 loss: 0.0837 (0.0966) time: 2.8944 data: 0.0088 max mem: 33301 +Epoch: [27] [1310/4276] eta: 2:24:34 lr: 1.7796571224330736e-05 loss: 0.0815 (0.0965) time: 2.8906 data: 0.0086 max mem: 33301 +Epoch: [27] [1320/4276] eta: 2:24:04 lr: 1.7793620239261596e-05 loss: 0.0948 (0.0965) time: 2.8886 data: 0.0084 max mem: 33301 +Epoch: [27] [1330/4276] eta: 2:23:34 lr: 1.7790669199812962e-05 loss: 0.0905 (0.0964) time: 2.8896 data: 0.0089 max mem: 33301 +Epoch: [27] [1340/4276] eta: 2:23:04 lr: 1.7787718105973798e-05 loss: 0.0864 (0.0964) time: 2.8918 data: 0.0091 max mem: 33301 +Epoch: [27] [1350/4276] eta: 2:22:34 lr: 1.7784766957733086e-05 loss: 0.0887 (0.0964) time: 2.8916 data: 0.0086 max mem: 33301 +Epoch: [27] [1360/4276] eta: 2:22:04 lr: 1.778181575507978e-05 loss: 0.0917 (0.0965) time: 2.8910 data: 0.0082 max mem: 33301 +Epoch: [27] [1370/4276] eta: 2:21:35 lr: 1.7778864498002862e-05 loss: 0.1007 (0.0966) time: 2.9086 data: 0.0085 max mem: 33301 +Epoch: [27] [1380/4276] eta: 2:21:05 lr: 1.7775913186491267e-05 loss: 0.0955 (0.0967) time: 2.9168 data: 0.0090 max mem: 33301 +Epoch: [27] [1390/4276] eta: 2:20:35 lr: 1.7772961820533963e-05 loss: 0.1046 (0.0967) time: 2.8933 data: 0.0087 max mem: 33301 +Epoch: [27] [1400/4276] eta: 2:20:05 lr: 1.777001040011989e-05 loss: 0.1017 (0.0968) time: 2.8752 data: 0.0090 max mem: 33301 +Epoch: [27] [1410/4276] eta: 2:19:35 lr: 1.7767058925238008e-05 loss: 0.0916 (0.0968) time: 2.8760 data: 0.0093 max mem: 33301 +Epoch: [27] [1420/4276] eta: 2:19:05 lr: 1.7764107395877244e-05 loss: 0.0877 (0.0967) time: 2.8783 data: 0.0089 max mem: 33301 +Epoch: [27] [1430/4276] eta: 2:18:35 lr: 1.7761155812026538e-05 loss: 0.0930 (0.0968) time: 2.8773 data: 0.0089 max mem: 33301 +Epoch: [27] [1440/4276] eta: 2:18:05 lr: 1.7758204173674826e-05 loss: 0.0932 (0.0967) time: 2.8793 data: 0.0089 max mem: 33301 +Epoch: [27] [1450/4276] eta: 2:17:35 lr: 1.7755252480811037e-05 loss: 0.0880 (0.0967) time: 2.8811 data: 0.0093 max mem: 33301 +Epoch: [27] [1460/4276] eta: 2:17:05 lr: 1.7752300733424083e-05 loss: 0.0844 (0.0967) time: 2.8829 data: 0.0095 max mem: 33301 +Epoch: [27] [1470/4276] eta: 2:16:36 lr: 1.7749348931502892e-05 loss: 0.0848 (0.0966) time: 2.9043 data: 0.0096 max mem: 33301 +Epoch: [27] [1480/4276] eta: 2:16:06 lr: 1.7746397075036384e-05 loss: 0.0917 (0.0966) time: 2.9192 data: 0.0097 max mem: 33301 +Epoch: [27] [1490/4276] eta: 2:15:37 lr: 1.7743445164013463e-05 loss: 0.0862 (0.0965) time: 2.9113 data: 0.0092 max mem: 33301 +Epoch: [27] [1500/4276] eta: 2:15:08 lr: 1.7740493198423036e-05 loss: 0.0861 (0.0965) time: 2.9130 data: 0.0091 max mem: 33301 +Epoch: [27] [1510/4276] eta: 2:14:39 lr: 1.7737541178254004e-05 loss: 0.0948 (0.0965) time: 2.9413 data: 0.0089 max mem: 33301 +Epoch: [27] [1520/4276] eta: 2:14:10 lr: 1.773458910349527e-05 loss: 0.0918 (0.0965) time: 2.9527 data: 0.0087 max mem: 33301 +Epoch: [27] [1530/4276] eta: 2:13:41 lr: 1.7731636974135726e-05 loss: 0.0826 (0.0964) time: 2.9344 data: 0.0085 max mem: 33301 +Epoch: [27] [1540/4276] eta: 2:13:12 lr: 1.7728684790164258e-05 loss: 0.0823 (0.0964) time: 2.9280 data: 0.0080 max mem: 33301 +Epoch: [27] [1550/4276] eta: 2:12:43 lr: 1.772573255156975e-05 loss: 0.0856 (0.0964) time: 2.9269 data: 0.0080 max mem: 33301 +Epoch: [27] [1560/4276] eta: 2:12:14 lr: 1.772278025834109e-05 loss: 0.0867 (0.0964) time: 2.9238 data: 0.0080 max mem: 33301 +Epoch: [27] [1570/4276] eta: 2:11:45 lr: 1.7719827910467146e-05 loss: 0.0942 (0.0963) time: 2.9226 data: 0.0078 max mem: 33301 +Epoch: [27] [1580/4276] eta: 2:11:15 lr: 1.7716875507936793e-05 loss: 0.0872 (0.0963) time: 2.9226 data: 0.0078 max mem: 33301 +Epoch: [27] [1590/4276] eta: 2:10:46 lr: 1.77139230507389e-05 loss: 0.0872 (0.0962) time: 2.9225 data: 0.0079 max mem: 33301 +Epoch: [27] [1600/4276] eta: 2:10:17 lr: 1.7710970538862332e-05 loss: 0.0904 (0.0963) time: 2.9114 data: 0.0090 max mem: 33301 +Epoch: [27] [1610/4276] eta: 2:09:47 lr: 1.770801797229594e-05 loss: 0.0816 (0.0962) time: 2.9113 data: 0.0093 max mem: 33301 +Epoch: [27] [1620/4276] eta: 2:09:18 lr: 1.7705065351028585e-05 loss: 0.0818 (0.0962) time: 2.9240 data: 0.0080 max mem: 33301 +Epoch: [27] [1630/4276] eta: 2:08:49 lr: 1.770211267504912e-05 loss: 0.0897 (0.0962) time: 2.9252 data: 0.0074 max mem: 33301 +Epoch: [27] [1640/4276] eta: 2:08:20 lr: 1.769915994434639e-05 loss: 0.0802 (0.0961) time: 2.9237 data: 0.0074 max mem: 33301 +Epoch: [27] [1650/4276] eta: 2:07:51 lr: 1.7696207158909226e-05 loss: 0.0768 (0.0960) time: 2.9179 data: 0.0073 max mem: 33301 +Epoch: [27] [1660/4276] eta: 2:07:21 lr: 1.7693254318726473e-05 loss: 0.0816 (0.0960) time: 2.9160 data: 0.0082 max mem: 33301 +Epoch: [27] [1670/4276] eta: 2:06:52 lr: 1.7690301423786967e-05 loss: 0.0824 (0.0959) time: 2.9264 data: 0.0083 max mem: 33301 +Epoch: [27] [1680/4276] eta: 2:06:24 lr: 1.768734847407954e-05 loss: 0.0777 (0.0958) time: 2.9416 data: 0.0076 max mem: 33301 +Epoch: [27] [1690/4276] eta: 2:05:54 lr: 1.7684395469593002e-05 loss: 0.0777 (0.0957) time: 2.9360 data: 0.0075 max mem: 33301 +Epoch: [27] [1700/4276] eta: 2:05:25 lr: 1.768144241031618e-05 loss: 0.0815 (0.0957) time: 2.9221 data: 0.0073 max mem: 33301 +Epoch: [27] [1710/4276] eta: 2:04:56 lr: 1.767848929623789e-05 loss: 0.0821 (0.0957) time: 2.9214 data: 0.0073 max mem: 33301 +Epoch: [27] [1720/4276] eta: 2:04:27 lr: 1.7675536127346954e-05 loss: 0.0806 (0.0956) time: 2.9266 data: 0.0082 max mem: 33301 +Epoch: [27] [1730/4276] eta: 2:03:58 lr: 1.7672582903632158e-05 loss: 0.0762 (0.0955) time: 2.9271 data: 0.0087 max mem: 33301 +Epoch: [27] [1740/4276] eta: 2:03:28 lr: 1.7669629625082316e-05 loss: 0.0813 (0.0954) time: 2.9223 data: 0.0083 max mem: 33301 +Epoch: [27] [1750/4276] eta: 2:02:59 lr: 1.7666676291686223e-05 loss: 0.0851 (0.0954) time: 2.9230 data: 0.0083 max mem: 33301 +Epoch: [27] [1760/4276] eta: 2:02:30 lr: 1.7663722903432682e-05 loss: 0.0851 (0.0953) time: 2.9208 data: 0.0086 max mem: 33301 +Epoch: [27] [1770/4276] eta: 2:02:01 lr: 1.7660769460310467e-05 loss: 0.0885 (0.0953) time: 2.9201 data: 0.0084 max mem: 33301 +Epoch: [27] [1780/4276] eta: 2:01:32 lr: 1.765781596230837e-05 loss: 0.0885 (0.0953) time: 2.9228 data: 0.0078 max mem: 33301 +Epoch: [27] [1790/4276] eta: 2:01:02 lr: 1.7654862409415173e-05 loss: 0.0896 (0.0952) time: 2.9221 data: 0.0078 max mem: 33301 +Epoch: [27] [1800/4276] eta: 2:00:33 lr: 1.765190880161966e-05 loss: 0.0865 (0.0952) time: 2.9229 data: 0.0086 max mem: 33301 +Epoch: [27] [1810/4276] eta: 2:00:04 lr: 1.7648955138910585e-05 loss: 0.0999 (0.0953) time: 2.9231 data: 0.0093 max mem: 33301 +Epoch: [27] [1820/4276] eta: 1:59:35 lr: 1.7646001421276725e-05 loss: 0.0999 (0.0952) time: 2.9174 data: 0.0086 max mem: 33301 +Epoch: [27] [1830/4276] eta: 1:59:05 lr: 1.7643047648706843e-05 loss: 0.0948 (0.0952) time: 2.9184 data: 0.0083 max mem: 33301 +Epoch: [27] [1840/4276] eta: 1:58:36 lr: 1.7640093821189706e-05 loss: 0.0859 (0.0951) time: 2.9230 data: 0.0084 max mem: 33301 +Epoch: [27] [1850/4276] eta: 1:58:07 lr: 1.763713993871405e-05 loss: 0.0773 (0.0951) time: 2.9228 data: 0.0080 max mem: 33301 +Epoch: [27] [1860/4276] eta: 1:57:38 lr: 1.763418600126863e-05 loss: 0.0934 (0.0951) time: 2.9221 data: 0.0078 max mem: 33301 +Epoch: [27] [1870/4276] eta: 1:57:09 lr: 1.7631232008842206e-05 loss: 0.0934 (0.0951) time: 2.9219 data: 0.0078 max mem: 33301 +Epoch: [27] [1880/4276] eta: 1:56:39 lr: 1.7628277961423506e-05 loss: 0.0900 (0.0951) time: 2.9227 data: 0.0078 max mem: 33301 +Epoch: [27] [1890/4276] eta: 1:56:10 lr: 1.7625323859001267e-05 loss: 0.0865 (0.0951) time: 2.9238 data: 0.0079 max mem: 33301 +Epoch: [27] [1900/4276] eta: 1:55:41 lr: 1.762236970156422e-05 loss: 0.0762 (0.0950) time: 2.9252 data: 0.0082 max mem: 33301 +Epoch: [27] [1910/4276] eta: 1:55:12 lr: 1.761941548910111e-05 loss: 0.0885 (0.0950) time: 2.9258 data: 0.0085 max mem: 33301 +Epoch: [27] [1920/4276] eta: 1:54:43 lr: 1.7616461221600637e-05 loss: 0.0885 (0.0950) time: 2.9262 data: 0.0087 max mem: 33301 +Epoch: [27] [1930/4276] eta: 1:54:14 lr: 1.761350689905153e-05 loss: 0.0870 (0.0949) time: 2.9286 data: 0.0085 max mem: 33301 +Epoch: [27] [1940/4276] eta: 1:53:45 lr: 1.7610552521442504e-05 loss: 0.0925 (0.0950) time: 2.9306 data: 0.0083 max mem: 33301 +Epoch: [27] [1950/4276] eta: 1:53:16 lr: 1.760759808876227e-05 loss: 0.0946 (0.0950) time: 2.9311 data: 0.0085 max mem: 33301 +Epoch: [27] [1960/4276] eta: 1:52:46 lr: 1.7604643600999534e-05 loss: 0.0929 (0.0950) time: 2.9335 data: 0.0089 max mem: 33301 +Epoch: [27] [1970/4276] eta: 1:52:17 lr: 1.7601689058142992e-05 loss: 0.0836 (0.0949) time: 2.9339 data: 0.0090 max mem: 33301 +Epoch: [27] [1980/4276] eta: 1:51:48 lr: 1.7598734460181346e-05 loss: 0.0765 (0.0949) time: 2.9332 data: 0.0088 max mem: 33301 +Epoch: [27] [1990/4276] eta: 1:51:19 lr: 1.759577980710329e-05 loss: 0.0867 (0.0949) time: 2.9326 data: 0.0087 max mem: 33301 +Epoch: [27] [2000/4276] eta: 1:50:50 lr: 1.7592825098897507e-05 loss: 0.0993 (0.0949) time: 2.9323 data: 0.0086 max mem: 33301 +Epoch: [27] [2010/4276] eta: 1:50:21 lr: 1.7589870335552682e-05 loss: 0.0929 (0.0949) time: 2.9326 data: 0.0087 max mem: 33301 +Epoch: [27] [2020/4276] eta: 1:49:52 lr: 1.7586915517057494e-05 loss: 0.0903 (0.0949) time: 2.9333 data: 0.0087 max mem: 33301 +Epoch: [27] [2030/4276] eta: 1:49:23 lr: 1.7583960643400626e-05 loss: 0.0864 (0.0948) time: 2.9343 data: 0.0087 max mem: 33301 +Epoch: [27] [2040/4276] eta: 1:48:54 lr: 1.7581005714570737e-05 loss: 0.0803 (0.0947) time: 2.9384 data: 0.0085 max mem: 33301 +Epoch: [27] [2050/4276] eta: 1:48:25 lr: 1.7578050730556495e-05 loss: 0.0892 (0.0948) time: 2.9435 data: 0.0081 max mem: 33301 +Epoch: [27] [2060/4276] eta: 1:47:56 lr: 1.7575095691346564e-05 loss: 0.0918 (0.0948) time: 2.9434 data: 0.0077 max mem: 33301 +Epoch: [27] [2070/4276] eta: 1:47:27 lr: 1.7572140596929607e-05 loss: 0.0854 (0.0947) time: 2.9599 data: 0.0077 max mem: 33301 +Epoch: [27] [2080/4276] eta: 1:46:58 lr: 1.756918544729426e-05 loss: 0.0838 (0.0948) time: 2.9601 data: 0.0075 max mem: 33301 +Epoch: [27] [2090/4276] eta: 1:46:29 lr: 1.7566230242429185e-05 loss: 0.0896 (0.0948) time: 2.9360 data: 0.0070 max mem: 33301 +Epoch: [27] [2100/4276] eta: 1:46:02 lr: 1.7563274982323022e-05 loss: 0.0904 (0.0948) time: 3.0449 data: 0.0077 max mem: 33301 +Epoch: [27] [2110/4276] eta: 1:45:36 lr: 1.7560319666964416e-05 loss: 0.0969 (0.0948) time: 3.2024 data: 0.0084 max mem: 33301 +Epoch: [27] [2120/4276] eta: 1:45:10 lr: 1.7557364296341985e-05 loss: 0.0892 (0.0947) time: 3.2437 data: 0.0084 max mem: 33301 +Epoch: [27] [2130/4276] eta: 1:44:44 lr: 1.7554408870444373e-05 loss: 0.0845 (0.0947) time: 3.2512 data: 0.0083 max mem: 33301 +Epoch: [27] [2140/4276] eta: 1:44:18 lr: 1.7551453389260202e-05 loss: 0.0829 (0.0946) time: 3.2669 data: 0.0084 max mem: 33301 +Epoch: [27] [2150/4276] eta: 1:43:53 lr: 1.7548497852778102e-05 loss: 0.0761 (0.0945) time: 3.2719 data: 0.0083 max mem: 33301 +Epoch: [27] [2160/4276] eta: 1:43:26 lr: 1.7545542260986672e-05 loss: 0.0747 (0.0944) time: 3.2661 data: 0.0082 max mem: 33301 +Epoch: [27] [2170/4276] eta: 1:43:00 lr: 1.7542586613874534e-05 loss: 0.0821 (0.0944) time: 3.2630 data: 0.0083 max mem: 33301 +Epoch: [27] [2180/4276] eta: 1:42:34 lr: 1.7539630911430304e-05 loss: 0.0917 (0.0944) time: 3.2647 data: 0.0083 max mem: 33301 +Epoch: [27] [2190/4276] eta: 1:42:08 lr: 1.753667515364257e-05 loss: 0.0852 (0.0944) time: 3.2695 data: 0.0084 max mem: 33301 +Epoch: [27] [2200/4276] eta: 1:41:42 lr: 1.753371934049994e-05 loss: 0.0903 (0.0944) time: 3.2746 data: 0.0084 max mem: 33301 +Epoch: [27] [2210/4276] eta: 1:41:16 lr: 1.7530763471991004e-05 loss: 0.0974 (0.0944) time: 3.2750 data: 0.0084 max mem: 33301 +Epoch: [27] [2220/4276] eta: 1:40:49 lr: 1.7527807548104362e-05 loss: 0.0855 (0.0944) time: 3.2655 data: 0.0082 max mem: 33301 +Epoch: [27] [2230/4276] eta: 1:40:22 lr: 1.7524851568828586e-05 loss: 0.0804 (0.0944) time: 3.2496 data: 0.0094 max mem: 33301 +Epoch: [27] [2240/4276] eta: 1:39:55 lr: 1.752189553415226e-05 loss: 0.0751 (0.0943) time: 3.2213 data: 0.0103 max mem: 33301 +Epoch: [27] [2250/4276] eta: 1:39:29 lr: 1.7518939444063968e-05 loss: 0.0770 (0.0942) time: 3.2254 data: 0.0102 max mem: 33301 +Epoch: [27] [2260/4276] eta: 1:39:01 lr: 1.751598329855228e-05 loss: 0.0820 (0.0943) time: 3.2170 data: 0.0109 max mem: 33301 +Epoch: [27] [2270/4276] eta: 1:38:34 lr: 1.7513027097605755e-05 loss: 0.0874 (0.0942) time: 3.1729 data: 0.0103 max mem: 33301 +Epoch: [27] [2280/4276] eta: 1:38:06 lr: 1.7510070841212965e-05 loss: 0.0820 (0.0942) time: 3.1779 data: 0.0104 max mem: 33301 +Epoch: [27] [2290/4276] eta: 1:37:39 lr: 1.750711452936246e-05 loss: 0.0899 (0.0942) time: 3.1987 data: 0.0110 max mem: 33301 +Epoch: [27] [2300/4276] eta: 1:37:12 lr: 1.750415816204281e-05 loss: 0.0934 (0.0942) time: 3.2278 data: 0.0104 max mem: 33301 +Epoch: [27] [2310/4276] eta: 1:36:45 lr: 1.7501201739242544e-05 loss: 0.0933 (0.0943) time: 3.2221 data: 0.0111 max mem: 33301 +Epoch: [27] [2320/4276] eta: 1:36:17 lr: 1.7498245260950215e-05 loss: 0.0967 (0.0943) time: 3.1853 data: 0.0114 max mem: 33301 +Epoch: [27] [2330/4276] eta: 1:35:49 lr: 1.749528872715437e-05 loss: 0.0945 (0.0943) time: 3.1818 data: 0.0099 max mem: 33301 +Epoch: [27] [2340/4276] eta: 1:35:21 lr: 1.7492332137843543e-05 loss: 0.0945 (0.0943) time: 3.1240 data: 0.0089 max mem: 33301 +Epoch: [27] [2350/4276] eta: 1:34:51 lr: 1.7489375493006254e-05 loss: 0.0932 (0.0943) time: 2.9890 data: 0.0078 max mem: 33301 +Epoch: [27] [2360/4276] eta: 1:34:21 lr: 1.748641879263104e-05 loss: 0.0806 (0.0943) time: 2.9358 data: 0.0076 max mem: 33301 +Epoch: [27] [2370/4276] eta: 1:33:51 lr: 1.7483462036706422e-05 loss: 0.0976 (0.0943) time: 2.9070 data: 0.0083 max mem: 33301 +Epoch: [27] [2380/4276] eta: 1:33:21 lr: 1.748050522522092e-05 loss: 0.0966 (0.0943) time: 2.8564 data: 0.0085 max mem: 33301 +Epoch: [27] [2390/4276] eta: 1:32:50 lr: 1.747754835816304e-05 loss: 0.0943 (0.0943) time: 2.8564 data: 0.0084 max mem: 33301 +Epoch: [27] [2400/4276] eta: 1:32:20 lr: 1.7474591435521298e-05 loss: 0.0908 (0.0943) time: 2.8582 data: 0.0086 max mem: 33301 +Epoch: [27] [2410/4276] eta: 1:31:50 lr: 1.747163445728419e-05 loss: 0.1001 (0.0943) time: 2.8713 data: 0.0092 max mem: 33301 +Epoch: [27] [2420/4276] eta: 1:31:20 lr: 1.7468677423440232e-05 loss: 0.0897 (0.0943) time: 2.8827 data: 0.0091 max mem: 33301 +Epoch: [27] [2430/4276] eta: 1:30:50 lr: 1.74657203339779e-05 loss: 0.0955 (0.0944) time: 2.8755 data: 0.0089 max mem: 33301 +Epoch: [27] [2440/4276] eta: 1:30:20 lr: 1.746276318888569e-05 loss: 0.0967 (0.0944) time: 2.8645 data: 0.0085 max mem: 33301 +Epoch: [27] [2450/4276] eta: 1:29:49 lr: 1.745980598815209e-05 loss: 0.0947 (0.0944) time: 2.8612 data: 0.0081 max mem: 33301 +Epoch: [27] [2460/4276] eta: 1:29:19 lr: 1.7456848731765593e-05 loss: 0.0961 (0.0944) time: 2.8614 data: 0.0083 max mem: 33301 +Epoch: [27] [2470/4276] eta: 1:28:49 lr: 1.7453891419714655e-05 loss: 0.0978 (0.0945) time: 2.8617 data: 0.0085 max mem: 33301 +Epoch: [27] [2480/4276] eta: 1:28:19 lr: 1.745093405198776e-05 loss: 0.1008 (0.0945) time: 2.8662 data: 0.0083 max mem: 33301 +Epoch: [27] [2490/4276] eta: 1:27:49 lr: 1.744797662857338e-05 loss: 0.0951 (0.0945) time: 2.8802 data: 0.0086 max mem: 33301 +Epoch: [27] [2500/4276] eta: 1:27:19 lr: 1.744501914945996e-05 loss: 0.0918 (0.0945) time: 2.8940 data: 0.0087 max mem: 33301 +Epoch: [27] [2510/4276] eta: 1:26:49 lr: 1.744206161463598e-05 loss: 0.0903 (0.0945) time: 2.8973 data: 0.0082 max mem: 33301 +Epoch: [27] [2520/4276] eta: 1:26:19 lr: 1.743910402408988e-05 loss: 0.0889 (0.0945) time: 2.8960 data: 0.0080 max mem: 33301 +Epoch: [27] [2530/4276] eta: 1:25:50 lr: 1.7436146377810118e-05 loss: 0.0771 (0.0944) time: 2.9113 data: 0.0078 max mem: 33301 +Epoch: [27] [2540/4276] eta: 1:25:20 lr: 1.7433188675785133e-05 loss: 0.0821 (0.0945) time: 2.9071 data: 0.0083 max mem: 33301 +Epoch: [27] [2550/4276] eta: 1:24:50 lr: 1.743023091800337e-05 loss: 0.0802 (0.0944) time: 2.8761 data: 0.0089 max mem: 33301 +Epoch: [27] [2560/4276] eta: 1:24:20 lr: 1.7427273104453258e-05 loss: 0.0709 (0.0943) time: 2.8634 data: 0.0087 max mem: 33301 +Epoch: [27] [2570/4276] eta: 1:23:50 lr: 1.7424315235123244e-05 loss: 0.0739 (0.0943) time: 2.8602 data: 0.0087 max mem: 33301 +Epoch: [27] [2580/4276] eta: 1:23:20 lr: 1.742135731000173e-05 loss: 0.0773 (0.0942) time: 2.8765 data: 0.0082 max mem: 33301 +Epoch: [27] [2590/4276] eta: 1:22:50 lr: 1.7418399329077155e-05 loss: 0.0796 (0.0942) time: 2.9044 data: 0.0076 max mem: 33301 +Epoch: [27] [2600/4276] eta: 1:22:20 lr: 1.7415441292337936e-05 loss: 0.0804 (0.0942) time: 2.9170 data: 0.0081 max mem: 33301 +Epoch: [27] [2610/4276] eta: 1:21:51 lr: 1.7412483199772487e-05 loss: 0.0742 (0.0941) time: 2.9174 data: 0.0081 max mem: 33301 +Epoch: [27] [2620/4276] eta: 1:21:21 lr: 1.7409525051369206e-05 loss: 0.0799 (0.0941) time: 2.8969 data: 0.0081 max mem: 33301 +Epoch: [27] [2630/4276] eta: 1:20:51 lr: 1.7406566847116503e-05 loss: 0.0956 (0.0941) time: 2.8720 data: 0.0087 max mem: 33301 +Epoch: [27] [2640/4276] eta: 1:20:21 lr: 1.7403608587002773e-05 loss: 0.0808 (0.0940) time: 2.8654 data: 0.0087 max mem: 33301 +Epoch: [27] [2650/4276] eta: 1:19:51 lr: 1.7400650271016422e-05 loss: 0.0798 (0.0940) time: 2.8599 data: 0.0087 max mem: 33301 +Epoch: [27] [2660/4276] eta: 1:19:21 lr: 1.739769189914583e-05 loss: 0.0799 (0.0940) time: 2.8562 data: 0.0089 max mem: 33301 +Epoch: [27] [2670/4276] eta: 1:18:51 lr: 1.7394733471379383e-05 loss: 0.0817 (0.0940) time: 2.8598 data: 0.0085 max mem: 33301 +Epoch: [27] [2680/4276] eta: 1:18:21 lr: 1.7391774987705462e-05 loss: 0.1025 (0.0940) time: 2.8622 data: 0.0079 max mem: 33301 +Epoch: [27] [2690/4276] eta: 1:17:51 lr: 1.738881644811245e-05 loss: 0.0807 (0.0940) time: 2.8574 data: 0.0077 max mem: 33301 +Epoch: [27] [2700/4276] eta: 1:17:21 lr: 1.7385857852588706e-05 loss: 0.0801 (0.0940) time: 2.8689 data: 0.0085 max mem: 33301 +Epoch: [27] [2710/4276] eta: 1:16:51 lr: 1.7382899201122603e-05 loss: 0.0795 (0.0939) time: 2.8891 data: 0.0093 max mem: 33301 +Epoch: [27] [2720/4276] eta: 1:16:22 lr: 1.7379940493702507e-05 loss: 0.0760 (0.0938) time: 2.8985 data: 0.0097 max mem: 33301 +Epoch: [27] [2730/4276] eta: 1:15:52 lr: 1.7376981730316775e-05 loss: 0.0790 (0.0938) time: 2.8961 data: 0.0098 max mem: 33301 +Epoch: [27] [2740/4276] eta: 1:15:22 lr: 1.7374022910953753e-05 loss: 0.0916 (0.0938) time: 2.8752 data: 0.0092 max mem: 33301 +Epoch: [27] [2750/4276] eta: 1:14:52 lr: 1.7371064035601793e-05 loss: 0.0923 (0.0939) time: 2.8624 data: 0.0087 max mem: 33301 +Epoch: [27] [2760/4276] eta: 1:14:22 lr: 1.7368105104249245e-05 loss: 0.0878 (0.0939) time: 2.8644 data: 0.0085 max mem: 33301 +Epoch: [27] [2770/4276] eta: 1:13:52 lr: 1.736514611688444e-05 loss: 0.0809 (0.0938) time: 2.8669 data: 0.0085 max mem: 33301 +Epoch: [27] [2780/4276] eta: 1:13:22 lr: 1.7362187073495713e-05 loss: 0.0883 (0.0939) time: 2.8686 data: 0.0090 max mem: 33301 +Epoch: [27] [2790/4276] eta: 1:12:53 lr: 1.7359227974071395e-05 loss: 0.0913 (0.0939) time: 2.8708 data: 0.0092 max mem: 33301 +Epoch: [27] [2800/4276] eta: 1:12:23 lr: 1.7356268818599817e-05 loss: 0.0847 (0.0938) time: 2.8723 data: 0.0092 max mem: 33301 +Epoch: [27] [2810/4276] eta: 1:11:53 lr: 1.7353309607069286e-05 loss: 0.0716 (0.0938) time: 2.8973 data: 0.0095 max mem: 33301 +Epoch: [27] [2820/4276] eta: 1:11:24 lr: 1.735035033946813e-05 loss: 0.0779 (0.0937) time: 2.9174 data: 0.0093 max mem: 33301 +Epoch: [27] [2830/4276] eta: 1:10:54 lr: 1.7347391015784657e-05 loss: 0.0870 (0.0938) time: 2.9145 data: 0.0092 max mem: 33301 +Epoch: [27] [2840/4276] eta: 1:10:25 lr: 1.7344431636007175e-05 loss: 0.0975 (0.0938) time: 2.9169 data: 0.0095 max mem: 33301 +Epoch: [27] [2850/4276] eta: 1:09:55 lr: 1.734147220012398e-05 loss: 0.0975 (0.0938) time: 2.9310 data: 0.0096 max mem: 33301 +Epoch: [27] [2860/4276] eta: 1:09:26 lr: 1.733851270812337e-05 loss: 0.0968 (0.0938) time: 2.9626 data: 0.0096 max mem: 33301 +Epoch: [27] [2870/4276] eta: 1:08:56 lr: 1.7335553159993643e-05 loss: 0.0896 (0.0938) time: 2.9478 data: 0.0100 max mem: 33301 +Epoch: [27] [2880/4276] eta: 1:08:27 lr: 1.733259355572309e-05 loss: 0.0896 (0.0938) time: 2.9214 data: 0.0099 max mem: 33301 +Epoch: [27] [2890/4276] eta: 1:07:57 lr: 1.7329633895299983e-05 loss: 0.0884 (0.0938) time: 2.9188 data: 0.0093 max mem: 33301 +Epoch: [27] [2900/4276] eta: 1:07:28 lr: 1.7326674178712605e-05 loss: 0.0757 (0.0937) time: 2.9067 data: 0.0092 max mem: 33301 +Epoch: [27] [2910/4276] eta: 1:06:58 lr: 1.732371440594923e-05 loss: 0.0771 (0.0938) time: 2.9023 data: 0.0090 max mem: 33301 +Epoch: [27] [2920/4276] eta: 1:06:28 lr: 1.732075457699814e-05 loss: 0.0908 (0.0938) time: 2.8990 data: 0.0087 max mem: 33301 +Epoch: [27] [2930/4276] eta: 1:05:59 lr: 1.731779469184758e-05 loss: 0.0890 (0.0938) time: 2.9041 data: 0.0089 max mem: 33301 +Epoch: [27] [2940/4276] eta: 1:05:29 lr: 1.7314834750485813e-05 loss: 0.0875 (0.0938) time: 2.9053 data: 0.0091 max mem: 33301 +Epoch: [27] [2950/4276] eta: 1:05:00 lr: 1.7311874752901103e-05 loss: 0.0950 (0.0938) time: 2.8975 data: 0.0090 max mem: 33301 +Epoch: [27] [2960/4276] eta: 1:04:30 lr: 1.7308914699081704e-05 loss: 0.0861 (0.0938) time: 2.8944 data: 0.0089 max mem: 33301 +Epoch: [27] [2970/4276] eta: 1:04:00 lr: 1.7305954589015843e-05 loss: 0.0813 (0.0938) time: 2.8909 data: 0.0088 max mem: 33301 +Epoch: [27] [2980/4276] eta: 1:03:31 lr: 1.7302994422691776e-05 loss: 0.0798 (0.0938) time: 2.8894 data: 0.0084 max mem: 33301 +Epoch: [27] [2990/4276] eta: 1:03:01 lr: 1.7300034200097734e-05 loss: 0.0782 (0.0938) time: 2.9122 data: 0.0084 max mem: 33301 +Epoch: [27] [3000/4276] eta: 1:02:32 lr: 1.7297073921221958e-05 loss: 0.0796 (0.0937) time: 2.9383 data: 0.0088 max mem: 33301 +Epoch: [27] [3010/4276] eta: 1:02:03 lr: 1.729411358605266e-05 loss: 0.0831 (0.0937) time: 2.9435 data: 0.0087 max mem: 33301 +Epoch: [27] [3020/4276] eta: 1:01:33 lr: 1.729115319457807e-05 loss: 0.0912 (0.0937) time: 2.9323 data: 0.0088 max mem: 33301 +Epoch: [27] [3030/4276] eta: 1:01:03 lr: 1.728819274678641e-05 loss: 0.0958 (0.0938) time: 2.9057 data: 0.0091 max mem: 33301 +Epoch: [27] [3040/4276] eta: 1:00:34 lr: 1.7285232242665892e-05 loss: 0.1041 (0.0938) time: 2.8898 data: 0.0088 max mem: 33301 +Epoch: [27] [3050/4276] eta: 1:00:04 lr: 1.7282271682204713e-05 loss: 0.0892 (0.0938) time: 2.8887 data: 0.0089 max mem: 33301 +Epoch: [27] [3060/4276] eta: 0:59:35 lr: 1.7279311065391085e-05 loss: 0.0749 (0.0938) time: 2.8897 data: 0.0091 max mem: 33301 +Epoch: [27] [3070/4276] eta: 0:59:05 lr: 1.7276350392213205e-05 loss: 0.0766 (0.0937) time: 2.8894 data: 0.0090 max mem: 33301 +Epoch: [27] [3080/4276] eta: 0:58:35 lr: 1.7273389662659275e-05 loss: 0.0841 (0.0937) time: 2.8922 data: 0.0088 max mem: 33301 +Epoch: [27] [3090/4276] eta: 0:58:06 lr: 1.7270428876717474e-05 loss: 0.0812 (0.0937) time: 2.9012 data: 0.0088 max mem: 33301 +Epoch: [27] [3100/4276] eta: 0:57:36 lr: 1.7267468034375985e-05 loss: 0.0804 (0.0936) time: 2.9069 data: 0.0089 max mem: 33301 +Epoch: [27] [3110/4276] eta: 0:57:07 lr: 1.7264507135623002e-05 loss: 0.0871 (0.0936) time: 2.9235 data: 0.0090 max mem: 33301 +Epoch: [27] [3120/4276] eta: 0:56:38 lr: 1.7261546180446685e-05 loss: 0.0836 (0.0936) time: 2.9388 data: 0.0091 max mem: 33301 +Epoch: [27] [3130/4276] eta: 0:56:08 lr: 1.7258585168835208e-05 loss: 0.0871 (0.0936) time: 2.9383 data: 0.0086 max mem: 33301 +Epoch: [27] [3140/4276] eta: 0:55:39 lr: 1.7255624100776745e-05 loss: 0.0886 (0.0936) time: 2.9389 data: 0.0083 max mem: 33301 +Epoch: [27] [3150/4276] eta: 0:55:09 lr: 1.7252662976259452e-05 loss: 0.0999 (0.0936) time: 2.9394 data: 0.0087 max mem: 33301 +Epoch: [27] [3160/4276] eta: 0:54:40 lr: 1.7249701795271477e-05 loss: 0.0999 (0.0936) time: 2.9388 data: 0.0091 max mem: 33301 +Epoch: [27] [3170/4276] eta: 0:54:11 lr: 1.724674055780098e-05 loss: 0.0916 (0.0937) time: 2.9366 data: 0.0088 max mem: 33301 +Epoch: [27] [3180/4276] eta: 0:53:41 lr: 1.7243779263836108e-05 loss: 0.0906 (0.0937) time: 2.9358 data: 0.0085 max mem: 33301 +Epoch: [27] [3190/4276] eta: 0:53:12 lr: 1.7240817913365008e-05 loss: 0.0982 (0.0937) time: 2.9379 data: 0.0087 max mem: 33301 +Epoch: [27] [3200/4276] eta: 0:52:42 lr: 1.72378565063758e-05 loss: 0.1051 (0.0938) time: 2.9384 data: 0.0086 max mem: 33301 +Epoch: [27] [3210/4276] eta: 0:52:13 lr: 1.7234895042856634e-05 loss: 0.0892 (0.0938) time: 2.9394 data: 0.0084 max mem: 33301 +Epoch: [27] [3220/4276] eta: 0:51:44 lr: 1.7231933522795627e-05 loss: 0.0848 (0.0938) time: 2.9401 data: 0.0083 max mem: 33301 +Epoch: [27] [3230/4276] eta: 0:51:14 lr: 1.722897194618091e-05 loss: 0.0899 (0.0938) time: 2.9399 data: 0.0085 max mem: 33301 +Epoch: [27] [3240/4276] eta: 0:50:45 lr: 1.7226010313000593e-05 loss: 0.0977 (0.0938) time: 2.9411 data: 0.0087 max mem: 33301 +Epoch: [27] [3250/4276] eta: 0:50:15 lr: 1.7223048623242793e-05 loss: 0.1022 (0.0939) time: 2.9407 data: 0.0085 max mem: 33301 +Epoch: [27] [3260/4276] eta: 0:49:46 lr: 1.722008687689562e-05 loss: 0.1025 (0.0939) time: 2.9413 data: 0.0082 max mem: 33301 +Epoch: [27] [3270/4276] eta: 0:49:17 lr: 1.7217125073947182e-05 loss: 0.0968 (0.0939) time: 2.9480 data: 0.0086 max mem: 33301 +Epoch: [27] [3280/4276] eta: 0:48:47 lr: 1.7214163214385564e-05 loss: 0.0950 (0.0939) time: 2.9430 data: 0.0088 max mem: 33301 +Epoch: [27] [3290/4276] eta: 0:48:18 lr: 1.7211201298198872e-05 loss: 0.0953 (0.0939) time: 2.9445 data: 0.0084 max mem: 33301 +Epoch: [27] [3300/4276] eta: 0:47:49 lr: 1.7208239325375193e-05 loss: 0.0961 (0.0940) time: 2.9567 data: 0.0082 max mem: 33301 +Epoch: [27] [3310/4276] eta: 0:47:19 lr: 1.720527729590262e-05 loss: 0.1010 (0.0940) time: 2.9527 data: 0.0085 max mem: 33301 +Epoch: [27] [3320/4276] eta: 0:46:50 lr: 1.720231520976921e-05 loss: 0.1041 (0.0941) time: 2.9540 data: 0.0089 max mem: 33301 +Epoch: [27] [3330/4276] eta: 0:46:21 lr: 1.7199353066963062e-05 loss: 0.0954 (0.0941) time: 2.9605 data: 0.0085 max mem: 33301 +Epoch: [27] [3340/4276] eta: 0:45:51 lr: 1.7196390867472235e-05 loss: 0.0937 (0.0941) time: 2.9619 data: 0.0081 max mem: 33301 +Epoch: [27] [3350/4276] eta: 0:45:22 lr: 1.71934286112848e-05 loss: 0.0938 (0.0941) time: 2.9617 data: 0.0084 max mem: 33301 +Epoch: [27] [3360/4276] eta: 0:44:53 lr: 1.7190466298388807e-05 loss: 0.0938 (0.0941) time: 2.9603 data: 0.0088 max mem: 33301 +Epoch: [27] [3370/4276] eta: 0:44:23 lr: 1.7187503928772324e-05 loss: 0.0960 (0.0941) time: 2.9602 data: 0.0090 max mem: 33301 +Epoch: [27] [3380/4276] eta: 0:43:54 lr: 1.7184541502423393e-05 loss: 0.0841 (0.0940) time: 2.9618 data: 0.0088 max mem: 33301 +Epoch: [27] [3390/4276] eta: 0:43:24 lr: 1.7181579019330072e-05 loss: 0.0786 (0.0940) time: 2.9608 data: 0.0086 max mem: 33301 +Epoch: [27] [3400/4276] eta: 0:42:55 lr: 1.717861647948039e-05 loss: 0.0991 (0.0941) time: 2.9599 data: 0.0091 max mem: 33301 +Epoch: [27] [3410/4276] eta: 0:42:26 lr: 1.7175653882862387e-05 loss: 0.0930 (0.0941) time: 2.9612 data: 0.0094 max mem: 33301 +Epoch: [27] [3420/4276] eta: 0:41:56 lr: 1.7172691229464106e-05 loss: 0.0911 (0.0941) time: 2.9610 data: 0.0090 max mem: 33301 +Epoch: [27] [3430/4276] eta: 0:41:27 lr: 1.7169728519273558e-05 loss: 0.0991 (0.0941) time: 2.9600 data: 0.0088 max mem: 33301 +Epoch: [27] [3440/4276] eta: 0:40:58 lr: 1.7166765752278774e-05 loss: 0.0875 (0.0941) time: 2.9578 data: 0.0092 max mem: 33301 +Epoch: [27] [3450/4276] eta: 0:40:28 lr: 1.716380292846777e-05 loss: 0.0875 (0.0942) time: 2.9565 data: 0.0090 max mem: 33301 +Epoch: [27] [3460/4276] eta: 0:39:59 lr: 1.7160840047828562e-05 loss: 0.1034 (0.0942) time: 2.9516 data: 0.0080 max mem: 33301 +Epoch: [27] [3470/4276] eta: 0:39:30 lr: 1.7157877110349153e-05 loss: 0.0863 (0.0941) time: 2.9411 data: 0.0073 max mem: 33301 +Epoch: [27] [3480/4276] eta: 0:42:35 lr: 1.7154914116017546e-05 loss: 0.0866 (0.0942) time: 49.9892 data: 47.0606 max mem: 33301 +Epoch: [27] [3490/4276] eta: 0:42:03 lr: 1.7151951064821738e-05 loss: 0.0959 (0.0942) time: 49.9934 data: 47.0612 max mem: 33301 +Epoch: [27] [3500/4276] eta: 0:41:30 lr: 1.714898795674973e-05 loss: 0.0923 (0.0942) time: 2.9445 data: 0.0087 max mem: 33301 +Epoch: [27] [3510/4276] eta: 0:40:57 lr: 1.7146024791789506e-05 loss: 0.0803 (0.0942) time: 2.9433 data: 0.0087 max mem: 33301 +Epoch: [27] [3520/4276] eta: 0:40:25 lr: 1.7143061569929044e-05 loss: 0.0928 (0.0942) time: 2.9402 data: 0.0088 max mem: 33301 +Epoch: [27] [3530/4276] eta: 0:39:52 lr: 1.7140098291156327e-05 loss: 0.0960 (0.0942) time: 2.9397 data: 0.0088 max mem: 33301 +Epoch: [27] [3540/4276] eta: 0:39:19 lr: 1.713713495545934e-05 loss: 0.0868 (0.0942) time: 2.9412 data: 0.0084 max mem: 33301 +Epoch: [27] [3550/4276] eta: 0:38:47 lr: 1.7134171562826034e-05 loss: 0.0868 (0.0942) time: 2.9415 data: 0.0085 max mem: 33301 +Epoch: [27] [3560/4276] eta: 0:38:14 lr: 1.7131208113244383e-05 loss: 0.0910 (0.0942) time: 2.9414 data: 0.0089 max mem: 33301 +Epoch: [27] [3570/4276] eta: 0:37:42 lr: 1.712824460670234e-05 loss: 0.1018 (0.0942) time: 2.9429 data: 0.0091 max mem: 33301 +Epoch: [27] [3580/4276] eta: 0:37:09 lr: 1.712528104318787e-05 loss: 0.0862 (0.0942) time: 2.9440 data: 0.0087 max mem: 33301 +Epoch: [27] [3590/4276] eta: 0:36:36 lr: 1.7122317422688916e-05 loss: 0.0862 (0.0942) time: 2.9438 data: 0.0085 max mem: 33301 +Epoch: [27] [3600/4276] eta: 0:36:04 lr: 1.711935374519342e-05 loss: 0.0907 (0.0942) time: 2.9413 data: 0.0088 max mem: 33301 +Epoch: [27] [3610/4276] eta: 0:35:31 lr: 1.7116390010689326e-05 loss: 0.0897 (0.0942) time: 2.9425 data: 0.0090 max mem: 33301 +Epoch: [27] [3620/4276] eta: 0:34:59 lr: 1.7113426219164573e-05 loss: 0.0821 (0.0942) time: 2.9449 data: 0.0087 max mem: 33301 +Epoch: [27] [3630/4276] eta: 0:34:27 lr: 1.7110462370607083e-05 loss: 0.0821 (0.0942) time: 2.9439 data: 0.0083 max mem: 33301 +Epoch: [27] [3640/4276] eta: 0:33:54 lr: 1.7107498465004784e-05 loss: 0.0765 (0.0941) time: 2.9437 data: 0.0083 max mem: 33301 +Epoch: [27] [3650/4276] eta: 0:33:22 lr: 1.7104534502345597e-05 loss: 0.0813 (0.0941) time: 2.9436 data: 0.0084 max mem: 33301 +Epoch: [27] [3660/4276] eta: 0:32:49 lr: 1.710157048261744e-05 loss: 0.0880 (0.0941) time: 2.9430 data: 0.0082 max mem: 33301 +Epoch: [27] [3670/4276] eta: 0:32:17 lr: 1.7098606405808222e-05 loss: 0.0880 (0.0941) time: 2.9423 data: 0.0080 max mem: 33301 +Epoch: [27] [3680/4276] eta: 0:31:44 lr: 1.7095642271905844e-05 loss: 0.0915 (0.0941) time: 2.9428 data: 0.0081 max mem: 33301 +Epoch: [27] [3690/4276] eta: 0:31:12 lr: 1.7092678080898212e-05 loss: 0.0988 (0.0941) time: 2.9438 data: 0.0083 max mem: 33301 +Epoch: [27] [3700/4276] eta: 0:30:40 lr: 1.7089713832773228e-05 loss: 0.0872 (0.0941) time: 2.9427 data: 0.0084 max mem: 33301 +Epoch: [27] [3710/4276] eta: 0:30:07 lr: 1.7086749527518768e-05 loss: 0.0776 (0.0941) time: 2.9368 data: 0.0081 max mem: 33301 +Epoch: [27] [3720/4276] eta: 0:29:35 lr: 1.7083785165122727e-05 loss: 0.0943 (0.0941) time: 2.9249 data: 0.0082 max mem: 33301 +Epoch: [27] [3730/4276] eta: 0:29:03 lr: 1.708082074557299e-05 loss: 0.0957 (0.0941) time: 2.9197 data: 0.0084 max mem: 33301 +Epoch: [27] [3740/4276] eta: 0:28:30 lr: 1.7077856268857423e-05 loss: 0.0874 (0.0941) time: 2.9251 data: 0.0086 max mem: 33301 +Epoch: [27] [3750/4276] eta: 0:27:58 lr: 1.7074891734963905e-05 loss: 0.0908 (0.0941) time: 2.9350 data: 0.0083 max mem: 33301 +Epoch: [27] [3760/4276] eta: 0:27:26 lr: 1.70719271438803e-05 loss: 0.0908 (0.0941) time: 2.9413 data: 0.0080 max mem: 33301 +Epoch: [27] [3770/4276] eta: 0:26:54 lr: 1.7068962495594473e-05 loss: 0.0783 (0.0941) time: 2.9419 data: 0.0079 max mem: 33301 +Epoch: [27] [3780/4276] eta: 0:26:21 lr: 1.7065997790094275e-05 loss: 0.0783 (0.0941) time: 2.9408 data: 0.0077 max mem: 33301 +Epoch: [27] [3790/4276] eta: 0:25:49 lr: 1.7063033027367563e-05 loss: 0.0809 (0.0940) time: 2.9402 data: 0.0076 max mem: 33301 +Epoch: [27] [3800/4276] eta: 0:25:17 lr: 1.706006820740218e-05 loss: 0.0813 (0.0940) time: 2.9427 data: 0.0076 max mem: 33301 +Epoch: [27] [3810/4276] eta: 0:24:45 lr: 1.7057103330185973e-05 loss: 0.0806 (0.0940) time: 2.9439 data: 0.0076 max mem: 33301 +Epoch: [27] [3820/4276] eta: 0:24:13 lr: 1.705413839570677e-05 loss: 0.0848 (0.0940) time: 2.9445 data: 0.0077 max mem: 33301 +Epoch: [27] [3830/4276] eta: 0:23:41 lr: 1.7051173403952408e-05 loss: 0.0878 (0.0940) time: 2.9453 data: 0.0077 max mem: 33301 +Epoch: [27] [3840/4276] eta: 0:23:08 lr: 1.7048208354910717e-05 loss: 0.0871 (0.0940) time: 2.9452 data: 0.0079 max mem: 33301 +Epoch: [27] [3850/4276] eta: 0:22:36 lr: 1.704524324856952e-05 loss: 0.0828 (0.0939) time: 2.9567 data: 0.0082 max mem: 33301 +Epoch: [27] [3860/4276] eta: 0:22:04 lr: 1.7042278084916623e-05 loss: 0.0848 (0.0940) time: 2.9617 data: 0.0086 max mem: 33301 +Epoch: [27] [3870/4276] eta: 0:21:32 lr: 1.703931286393985e-05 loss: 0.0880 (0.0939) time: 2.9610 data: 0.0089 max mem: 33301 +Epoch: [27] [3880/4276] eta: 0:21:00 lr: 1.7036347585627006e-05 loss: 0.0839 (0.0939) time: 2.9756 data: 0.0081 max mem: 33301 +Epoch: [27] [3890/4276] eta: 0:22:19 lr: 1.7033382249965893e-05 loss: 0.0914 (0.0939) time: 59.1112 data: 56.1521 max mem: 33301 +Epoch: [27] [3900/4276] eta: 0:21:44 lr: 1.7030416856944303e-05 loss: 0.0945 (0.0939) time: 59.0882 data: 56.1530 max mem: 33301 +Epoch: [27] [3910/4276] eta: 0:21:09 lr: 1.7027451406550036e-05 loss: 0.0855 (0.0939) time: 2.9432 data: 0.0096 max mem: 33301 +Epoch: [27] [3920/4276] eta: 0:20:34 lr: 1.7024485898770873e-05 loss: 0.0798 (0.0939) time: 2.9470 data: 0.0094 max mem: 33301 +Epoch: [27] [3930/4276] eta: 0:19:59 lr: 1.7021520333594603e-05 loss: 0.0923 (0.0939) time: 2.9456 data: 0.0084 max mem: 33301 +Epoch: [27] [3940/4276] eta: 0:19:24 lr: 1.7018554711008998e-05 loss: 0.0910 (0.0939) time: 2.9467 data: 0.0084 max mem: 33301 +Epoch: [27] [3950/4276] eta: 0:18:49 lr: 1.7015589031001833e-05 loss: 0.0788 (0.0939) time: 2.9475 data: 0.0088 max mem: 33301 +Epoch: [27] [3960/4276] eta: 0:18:13 lr: 1.7012623293560874e-05 loss: 0.0788 (0.0939) time: 2.9494 data: 0.0087 max mem: 33301 +Epoch: [27] [3970/4276] eta: 0:17:38 lr: 1.7009657498673893e-05 loss: 0.0879 (0.0939) time: 2.9340 data: 0.0080 max mem: 33301 +Epoch: [27] [3980/4276] eta: 0:17:03 lr: 1.7006691646328632e-05 loss: 0.0923 (0.0939) time: 2.9076 data: 0.0081 max mem: 33301 +Epoch: [27] [3990/4276] eta: 0:16:28 lr: 1.700372573651285e-05 loss: 0.0915 (0.0939) time: 2.9052 data: 0.0082 max mem: 33301 +Epoch: [27] [4000/4276] eta: 0:15:53 lr: 1.70007597692143e-05 loss: 0.0828 (0.0939) time: 2.9081 data: 0.0079 max mem: 33301 +Epoch: [27] [4010/4276] eta: 0:15:19 lr: 1.6997793744420726e-05 loss: 0.0800 (0.0939) time: 2.9137 data: 0.0082 max mem: 33301 +Epoch: [27] [4020/4276] eta: 0:14:44 lr: 1.6994827662119854e-05 loss: 0.0914 (0.0939) time: 2.9238 data: 0.0085 max mem: 33301 +Epoch: [27] [4030/4276] eta: 0:14:09 lr: 1.6991861522299423e-05 loss: 0.0808 (0.0939) time: 2.9137 data: 0.0082 max mem: 33301 +Epoch: [27] [4040/4276] eta: 0:13:34 lr: 1.6988895324947167e-05 loss: 0.0898 (0.0939) time: 2.9047 data: 0.0080 max mem: 33301 +Epoch: [27] [4050/4276] eta: 0:12:59 lr: 1.69859290700508e-05 loss: 0.0838 (0.0939) time: 2.9018 data: 0.0082 max mem: 33301 +Epoch: [27] [4060/4276] eta: 0:12:24 lr: 1.6982962757598038e-05 loss: 0.0884 (0.0939) time: 2.9016 data: 0.0085 max mem: 33301 +Epoch: [27] [4070/4276] eta: 0:11:50 lr: 1.69799963875766e-05 loss: 0.0912 (0.0939) time: 2.9260 data: 0.0086 max mem: 33301 +Epoch: [27] [4080/4276] eta: 0:11:15 lr: 1.6977029959974196e-05 loss: 0.0843 (0.0939) time: 2.9281 data: 0.0090 max mem: 33301 +Epoch: [27] [4090/4276] eta: 0:10:40 lr: 1.6974063474778524e-05 loss: 0.0913 (0.0939) time: 2.9265 data: 0.0093 max mem: 33301 +Epoch: [27] [4100/4276] eta: 0:10:06 lr: 1.697109693197728e-05 loss: 0.1029 (0.0939) time: 2.9224 data: 0.0097 max mem: 33301 +Epoch: [27] [4110/4276] eta: 0:09:31 lr: 1.6968130331558155e-05 loss: 0.1029 (0.0940) time: 2.9228 data: 0.0095 max mem: 33301 +Epoch: [27] [4120/4276] eta: 0:08:56 lr: 1.696516367350885e-05 loss: 0.0968 (0.0940) time: 2.9258 data: 0.0091 max mem: 33301 +Epoch: [27] [4130/4276] eta: 0:08:22 lr: 1.6962196957817034e-05 loss: 0.0830 (0.0939) time: 2.9277 data: 0.0093 max mem: 33301 +Epoch: [27] [4140/4276] eta: 0:07:47 lr: 1.6959230184470387e-05 loss: 0.0830 (0.0939) time: 2.9395 data: 0.0092 max mem: 33301 +Epoch: [27] [4150/4276] eta: 0:07:13 lr: 1.6956263353456584e-05 loss: 0.0868 (0.0939) time: 2.9171 data: 0.0089 max mem: 33301 +Epoch: [27] [4160/4276] eta: 0:06:38 lr: 1.6953296464763297e-05 loss: 0.0835 (0.0939) time: 2.9156 data: 0.0088 max mem: 33301 +Epoch: [27] [4170/4276] eta: 0:06:04 lr: 1.695032951837818e-05 loss: 0.0908 (0.0940) time: 2.9538 data: 0.0090 max mem: 33301 +Epoch: [27] [4180/4276] eta: 0:05:29 lr: 1.694736251428889e-05 loss: 0.0848 (0.0939) time: 2.9748 data: 0.0090 max mem: 33301 +Epoch: [27] [4190/4276] eta: 0:04:55 lr: 1.6944395452483086e-05 loss: 0.0818 (0.0940) time: 2.9634 data: 0.0087 max mem: 33301 +Epoch: [27] [4200/4276] eta: 0:04:20 lr: 1.694142833294842e-05 loss: 0.0989 (0.0940) time: 2.9516 data: 0.0084 max mem: 33301 +Epoch: [27] [4210/4276] eta: 0:03:46 lr: 1.693846115567252e-05 loss: 0.0970 (0.0940) time: 2.9639 data: 0.0082 max mem: 33301 +Epoch: [27] [4220/4276] eta: 0:03:12 lr: 1.693549392064303e-05 loss: 0.0970 (0.0940) time: 2.9784 data: 0.0084 max mem: 33301 +Epoch: [27] [4230/4276] eta: 0:02:37 lr: 1.6932526627847582e-05 loss: 0.1013 (0.0941) time: 2.9637 data: 0.0087 max mem: 33301 +Epoch: [27] [4240/4276] eta: 0:02:03 lr: 1.692955927727381e-05 loss: 0.1013 (0.0941) time: 2.9486 data: 0.0086 max mem: 33301 +Epoch: [27] [4250/4276] eta: 0:01:29 lr: 1.6926591868909325e-05 loss: 0.0947 (0.0941) time: 2.9607 data: 0.0085 max mem: 33301 +Epoch: [27] [4260/4276] eta: 0:00:54 lr: 1.6923624402741748e-05 loss: 0.0871 (0.0941) time: 2.9879 data: 0.0085 max mem: 33301 +Epoch: [27] [4270/4276] eta: 0:00:20 lr: 1.6920656878758693e-05 loss: 0.0960 (0.0941) time: 2.9740 data: 0.0079 max mem: 33301 +Epoch: [27] Total time: 4:03:58 +Test: [ 0/21770] eta: 8:38:12 time: 1.4282 data: 1.3899 max mem: 33301 +Test: [ 100/21770] eta: 0:19:00 time: 0.0391 data: 0.0009 max mem: 33301 +Test: [ 200/21770] eta: 0:16:28 time: 0.0389 data: 0.0009 max mem: 33301 +Test: [ 300/21770] eta: 0:15:27 time: 0.0378 data: 0.0010 max mem: 33301 +Test: [ 400/21770] eta: 0:14:54 time: 0.0379 data: 0.0009 max mem: 33301 +Test: [ 500/21770] eta: 0:14:33 time: 0.0377 data: 0.0009 max mem: 33301 +Test: [ 600/21770] eta: 0:14:17 time: 0.0379 data: 0.0009 max mem: 33301 +Test: [ 700/21770] eta: 0:14:05 time: 0.0378 data: 0.0009 max mem: 33301 +Test: [ 800/21770] eta: 0:13:56 time: 0.0382 data: 0.0009 max mem: 33301 +Test: [ 900/21770] eta: 0:13:49 time: 0.0384 data: 0.0009 max mem: 33301 +Test: [ 1000/21770] eta: 0:13:42 time: 0.0383 data: 0.0009 max mem: 33301 +Test: [ 1100/21770] eta: 0:13:36 time: 0.0385 data: 0.0009 max mem: 33301 +Test: [ 1200/21770] eta: 0:13:30 time: 0.0384 data: 0.0009 max mem: 33301 +Test: [ 1300/21770] eta: 0:13:25 time: 0.0383 data: 0.0009 max mem: 33301 +Test: [ 1400/21770] eta: 0:13:19 time: 0.0385 data: 0.0009 max mem: 33301 +Test: [ 1500/21770] eta: 0:13:14 time: 0.0385 data: 0.0009 max mem: 33301 +Test: [ 1600/21770] eta: 0:13:09 time: 0.0383 data: 0.0009 max mem: 33301 +Test: [ 1700/21770] eta: 0:13:04 time: 0.0382 data: 0.0009 max mem: 33301 +Test: [ 1800/21770] eta: 0:12:59 time: 0.0383 data: 0.0009 max mem: 33301 +Test: [ 1900/21770] eta: 0:12:55 time: 0.0382 data: 0.0009 max mem: 33301 +Test: [ 2000/21770] eta: 0:12:50 time: 0.0382 data: 0.0009 max mem: 33301 +Test: [ 2100/21770] eta: 0:12:45 time: 0.0381 data: 0.0009 max mem: 33301 +Test: [ 2200/21770] eta: 0:12:41 time: 0.0383 data: 0.0009 max mem: 33301 +Test: [ 2300/21770] eta: 0:12:36 time: 0.0382 data: 0.0009 max mem: 33301 +Test: [ 2400/21770] eta: 0:12:32 time: 0.0386 data: 0.0009 max mem: 33301 +Test: [ 2500/21770] eta: 0:12:28 time: 0.0384 data: 0.0009 max mem: 33301 +Test: [ 2600/21770] eta: 0:12:24 time: 0.0386 data: 0.0009 max mem: 33301 +Test: [ 2700/21770] eta: 0:12:20 time: 0.0384 data: 0.0009 max mem: 33301 +Test: [ 2800/21770] eta: 0:12:16 time: 0.0388 data: 0.0009 max mem: 33301 +Test: [ 2900/21770] eta: 0:12:12 time: 0.0390 data: 0.0009 max mem: 33301 +Test: [ 3000/21770] eta: 0:12:08 time: 0.0388 data: 0.0009 max mem: 33301 +Test: [ 3100/21770] eta: 0:12:04 time: 0.0389 data: 0.0009 max mem: 33301 +Test: [ 3200/21770] eta: 0:12:00 time: 0.0388 data: 0.0009 max mem: 33301 +Test: [ 3300/21770] eta: 0:11:56 time: 0.0389 data: 0.0009 max mem: 33301 +Test: [ 3400/21770] eta: 0:11:53 time: 0.0388 data: 0.0009 max mem: 33301 +Test: [ 3500/21770] eta: 0:11:49 time: 0.0388 data: 0.0009 max mem: 33301 +Test: [ 3600/21770] eta: 0:11:45 time: 0.0385 data: 0.0009 max mem: 33301 +Test: [ 3700/21770] eta: 0:11:41 time: 0.0385 data: 0.0009 max mem: 33301 +Test: [ 3800/21770] eta: 0:11:37 time: 0.0388 data: 0.0009 max mem: 33301 +Test: [ 3900/21770] eta: 0:11:33 time: 0.0390 data: 0.0009 max mem: 33301 +Test: [ 4000/21770] eta: 0:11:29 time: 0.0388 data: 0.0009 max mem: 33301 +Test: [ 4100/21770] eta: 0:11:25 time: 0.0389 data: 0.0009 max mem: 33301 +Test: [ 4200/21770] eta: 0:11:21 time: 0.0388 data: 0.0009 max mem: 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time: 0.0392 data: 0.0009 max mem: 33301 +Test: [ 7000/21770] eta: 0:09:33 time: 0.0392 data: 0.0009 max mem: 33301 +Test: [ 7100/21770] eta: 0:09:29 time: 0.0388 data: 0.0009 max mem: 33301 +Test: [ 7200/21770] eta: 0:09:25 time: 0.0388 data: 0.0009 max mem: 33301 +Test: [ 7300/21770] eta: 0:09:21 time: 0.0390 data: 0.0009 max mem: 33301 +Test: [ 7400/21770] eta: 0:09:17 time: 0.0387 data: 0.0009 max mem: 33301 +Test: [ 7500/21770] eta: 0:09:13 time: 0.0390 data: 0.0009 max mem: 33301 +Test: [ 7600/21770] eta: 0:09:09 time: 0.0388 data: 0.0009 max mem: 33301 +Test: [ 7700/21770] eta: 0:09:05 time: 0.0389 data: 0.0009 max mem: 33301 +Test: [ 7800/21770] eta: 0:09:02 time: 0.0392 data: 0.0009 max mem: 33301 +Test: [ 7900/21770] eta: 0:08:58 time: 0.0391 data: 0.0009 max mem: 33301 +Test: [ 8000/21770] eta: 0:08:54 time: 0.0391 data: 0.0009 max mem: 33301 +Test: [ 8100/21770] eta: 0:08:50 time: 0.0391 data: 0.0009 max mem: 33301 +Test: [ 8200/21770] eta: 0:08:46 time: 0.0395 data: 0.0009 max mem: 33301 +Test: [ 8300/21770] eta: 0:08:43 time: 0.0391 data: 0.0008 max mem: 33301 +Test: [ 8400/21770] eta: 0:08:39 time: 0.0390 data: 0.0008 max mem: 33301 +Test: [ 8500/21770] eta: 0:08:35 time: 0.0390 data: 0.0008 max mem: 33301 +Test: [ 8600/21770] eta: 0:08:31 time: 0.0387 data: 0.0009 max mem: 33301 +Test: [ 8700/21770] eta: 0:08:27 time: 0.0392 data: 0.0008 max mem: 33301 +Test: [ 8800/21770] eta: 0:08:23 time: 0.0390 data: 0.0009 max mem: 33301 +Test: [ 8900/21770] eta: 0:08:19 time: 0.0390 data: 0.0009 max mem: 33301 +Test: [ 9000/21770] eta: 0:08:16 time: 0.0388 data: 0.0009 max mem: 33301 +Test: [ 9100/21770] eta: 0:08:12 time: 0.0392 data: 0.0009 max mem: 33301 +Test: [ 9200/21770] eta: 0:08:08 time: 0.0389 data: 0.0009 max mem: 33301 +Test: [ 9300/21770] eta: 0:08:04 time: 0.0390 data: 0.0008 max mem: 33301 +Test: [ 9400/21770] eta: 0:08:00 time: 0.0391 data: 0.0008 max mem: 33301 +Test: [ 9500/21770] eta: 0:07:56 time: 0.0391 data: 0.0008 max mem: 33301 +Test: [ 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time: 0.0398 data: 0.0009 max mem: 33301 +Test: [11000/21770] eta: 0:06:58 time: 0.0391 data: 0.0009 max mem: 33301 +Test: [11100/21770] eta: 0:06:54 time: 0.0386 data: 0.0009 max mem: 33301 +Test: [11200/21770] eta: 0:06:50 time: 0.0389 data: 0.0009 max mem: 33301 +Test: [11300/21770] eta: 0:06:46 time: 0.0394 data: 0.0009 max mem: 33301 +Test: [11400/21770] eta: 0:06:42 time: 0.0389 data: 0.0008 max mem: 33301 +Test: [11500/21770] eta: 0:06:38 time: 0.0392 data: 0.0009 max mem: 33301 +Test: [11600/21770] eta: 0:06:35 time: 0.0396 data: 0.0009 max mem: 33301 +Test: [11700/21770] eta: 0:06:31 time: 0.0394 data: 0.0009 max mem: 33301 +Test: [11800/21770] eta: 0:06:27 time: 0.0393 data: 0.0008 max mem: 33301 +Test: [11900/21770] eta: 0:06:23 time: 0.0390 data: 0.0008 max mem: 33301 +Test: [12000/21770] eta: 0:06:19 time: 0.0381 data: 0.0009 max mem: 33301 +Test: [12100/21770] eta: 0:06:15 time: 0.0383 data: 0.0009 max mem: 33301 +Test: [12200/21770] eta: 0:06:11 time: 0.0383 data: 0.0009 max mem: 33301 +Test: [12300/21770] eta: 0:06:07 time: 0.0388 data: 0.0008 max mem: 33301 +Test: [12400/21770] eta: 0:06:03 time: 0.0388 data: 0.0008 max mem: 33301 +Test: [12500/21770] eta: 0:06:00 time: 0.0389 data: 0.0008 max mem: 33301 +Test: [12600/21770] eta: 0:05:56 time: 0.0386 data: 0.0008 max mem: 33301 +Test: [12700/21770] eta: 0:05:52 time: 0.0382 data: 0.0008 max mem: 33301 +Test: [12800/21770] eta: 0:05:48 time: 0.0378 data: 0.0008 max mem: 33301 +Test: [12900/21770] eta: 0:05:44 time: 0.0379 data: 0.0009 max mem: 33301 +Test: [13000/21770] eta: 0:05:40 time: 0.0379 data: 0.0008 max mem: 33301 +Test: [13100/21770] eta: 0:05:36 time: 0.0378 data: 0.0009 max mem: 33301 +Test: [13200/21770] eta: 0:05:32 time: 0.0378 data: 0.0009 max mem: 33301 +Test: [13300/21770] eta: 0:05:28 time: 0.0379 data: 0.0009 max mem: 33301 +Test: [13400/21770] eta: 0:05:24 time: 0.0379 data: 0.0009 max mem: 33301 +Test: [13500/21770] eta: 0:05:20 time: 0.0378 data: 0.0009 max mem: 33301 +Test: 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0:04:25 time: 0.0382 data: 0.0009 max mem: 33301 +Test: [15000/21770] eta: 0:04:22 time: 0.0381 data: 0.0008 max mem: 33301 +Test: [15100/21770] eta: 0:04:18 time: 0.0382 data: 0.0008 max mem: 33301 +Test: [15200/21770] eta: 0:04:14 time: 0.0382 data: 0.0009 max mem: 33301 +Test: [15300/21770] eta: 0:04:10 time: 0.0381 data: 0.0009 max mem: 33301 +Test: [15400/21770] eta: 0:04:06 time: 0.0380 data: 0.0009 max mem: 33301 +Test: [15500/21770] eta: 0:04:02 time: 0.0382 data: 0.0008 max mem: 33301 +Test: [15600/21770] eta: 0:03:58 time: 0.0381 data: 0.0009 max mem: 33301 +Test: [15700/21770] eta: 0:03:54 time: 0.0383 data: 0.0009 max mem: 33301 +Test: [15800/21770] eta: 0:03:50 time: 0.0381 data: 0.0009 max mem: 33301 +Test: [15900/21770] eta: 0:03:47 time: 0.0382 data: 0.0008 max mem: 33301 +Test: [16000/21770] eta: 0:03:43 time: 0.0382 data: 0.0009 max mem: 33301 +Test: [16100/21770] eta: 0:03:39 time: 0.0382 data: 0.0009 max mem: 33301 +Test: [16200/21770] eta: 0:03:35 time: 0.0380 data: 0.0008 max mem: 33301 +Test: [16300/21770] eta: 0:03:31 time: 0.0382 data: 0.0008 max mem: 33301 +Test: [16400/21770] eta: 0:03:27 time: 0.0380 data: 0.0008 max mem: 33301 +Test: [16500/21770] eta: 0:03:23 time: 0.0385 data: 0.0009 max mem: 33301 +Test: [16600/21770] eta: 0:03:19 time: 0.0388 data: 0.0009 max mem: 33301 +Test: [16700/21770] eta: 0:03:16 time: 0.0385 data: 0.0009 max mem: 33301 +Test: [16800/21770] eta: 0:03:12 time: 0.0386 data: 0.0008 max mem: 33301 +Test: [16900/21770] eta: 0:03:08 time: 0.0384 data: 0.0009 max mem: 33301 +Test: [17000/21770] eta: 0:03:04 time: 0.0385 data: 0.0009 max mem: 33301 +Test: [17100/21770] eta: 0:03:00 time: 0.0387 data: 0.0009 max mem: 33301 +Test: [17200/21770] eta: 0:02:56 time: 0.0388 data: 0.0008 max mem: 33301 +Test: [17300/21770] eta: 0:02:52 time: 0.0381 data: 0.0009 max mem: 33301 +Test: [17400/21770] eta: 0:02:48 time: 0.0385 data: 0.0009 max mem: 33301 +Test: [17500/21770] eta: 0:02:45 time: 0.0381 data: 0.0009 max mem: 33301 +Test: [17600/21770] eta: 0:02:41 time: 0.0384 data: 0.0009 max mem: 33301 +Test: [17700/21770] eta: 0:02:37 time: 0.0383 data: 0.0009 max mem: 33301 +Test: [17800/21770] eta: 0:02:33 time: 0.0386 data: 0.0009 max mem: 33301 +Test: [17900/21770] eta: 0:02:29 time: 0.0383 data: 0.0009 max mem: 33301 +Test: [18000/21770] eta: 0:02:25 time: 0.0385 data: 0.0009 max mem: 33301 +Test: [18100/21770] eta: 0:02:21 time: 0.0383 data: 0.0009 max mem: 33301 +Test: [18200/21770] eta: 0:02:17 time: 0.0385 data: 0.0009 max mem: 33301 +Test: [18300/21770] eta: 0:02:14 time: 0.0380 data: 0.0008 max mem: 33301 +Test: [18400/21770] eta: 0:02:10 time: 0.0387 data: 0.0008 max mem: 33301 +Test: [18500/21770] eta: 0:02:06 time: 0.0388 data: 0.0008 max mem: 33301 +Test: [18600/21770] eta: 0:02:02 time: 0.0385 data: 0.0008 max mem: 33301 +Test: [18700/21770] eta: 0:01:58 time: 0.0388 data: 0.0008 max mem: 33301 +Test: [18800/21770] eta: 0:01:54 time: 0.0390 data: 0.0008 max mem: 33301 +Test: [18900/21770] eta: 0:01:50 time: 0.0389 data: 0.0008 max mem: 33301 +Test: [19000/21770] eta: 0:01:47 time: 0.0390 data: 0.0008 max mem: 33301 +Test: [19100/21770] eta: 0:01:43 time: 0.0388 data: 0.0008 max mem: 33301 +Test: [19200/21770] eta: 0:01:39 time: 0.0387 data: 0.0008 max mem: 33301 +Test: [19300/21770] eta: 0:01:35 time: 0.0387 data: 0.0008 max mem: 33301 +Test: [19400/21770] eta: 0:01:31 time: 0.0389 data: 0.0008 max mem: 33301 +Test: [19500/21770] eta: 0:01:27 time: 0.0384 data: 0.0008 max mem: 33301 +Test: [19600/21770] eta: 0:01:23 time: 0.0393 data: 0.0008 max mem: 33301 +Test: [19700/21770] eta: 0:01:20 time: 0.0389 data: 0.0008 max mem: 33301 +Test: [19800/21770] eta: 0:01:16 time: 0.0392 data: 0.0008 max mem: 33301 +Test: [19900/21770] eta: 0:01:12 time: 0.0388 data: 0.0008 max mem: 33301 +Test: [20000/21770] eta: 0:01:08 time: 0.0388 data: 0.0008 max mem: 33301 +Test: [20100/21770] eta: 0:01:04 time: 0.0383 data: 0.0008 max mem: 33301 +Test: [20200/21770] eta: 0:01:00 time: 0.0384 data: 0.0008 max mem: 33301 +Test: [20300/21770] eta: 0:00:56 time: 0.0385 data: 0.0008 max mem: 33301 +Test: [20400/21770] eta: 0:00:52 time: 0.0386 data: 0.0008 max mem: 33301 +Test: [20500/21770] eta: 0:00:49 time: 0.0384 data: 0.0008 max mem: 33301 +Test: [20600/21770] eta: 0:00:45 time: 0.0386 data: 0.0008 max mem: 33301 +Test: [20700/21770] eta: 0:00:41 time: 0.0384 data: 0.0008 max mem: 33301 +Test: [20800/21770] eta: 0:00:37 time: 0.0386 data: 0.0008 max mem: 33301 +Test: [20900/21770] eta: 0:00:33 time: 0.0387 data: 0.0008 max mem: 33301 +Test: [21000/21770] eta: 0:00:29 time: 0.0390 data: 0.0008 max mem: 33301 +Test: [21100/21770] eta: 0:00:25 time: 0.0389 data: 0.0008 max mem: 33301 +Test: [21200/21770] eta: 0:00:22 time: 0.0391 data: 0.0009 max mem: 33301 +Test: [21300/21770] eta: 0:00:18 time: 0.0397 data: 0.0009 max mem: 33301 +Test: [21400/21770] eta: 0:00:14 time: 0.0387 data: 0.0008 max mem: 33301 +Test: [21500/21770] eta: 0:00:10 time: 0.0389 data: 0.0008 max mem: 33301 +Test: [21600/21770] eta: 0:00:06 time: 0.0387 data: 0.0008 max mem: 33301 +Test: [21700/21770] eta: 0:00:02 time: 0.0387 data: 0.0008 max mem: 33301 +Test: Total time: 0:14:01 +Final results: +Mean IoU is 0.00 + + precision@0.5 = 0.00 + precision@0.6 = 0.00 + precision@0.7 = 0.00 + precision@0.8 = 0.00 + precision@0.9 = 0.00 + overall IoU = 0.00 + mean IoU = 0.00 + +Mean accuracy for one-to-zero sample is 100.00 + +Average object IoU 0.0 +Overall IoU 0.0 +Epoch: [28] [ 0/4276] eta: 6:29:24 lr: 1.6918876336612275e-05 loss: 0.0710 (0.0710) time: 5.4641 data: 2.4603 max mem: 33301 +Epoch: [28] [ 10/4276] eta: 3:43:28 lr: 1.6915908720098677e-05 loss: 0.1066 (0.0965) time: 3.1431 data: 0.2303 max mem: 33301 +Epoch: [28] [ 20/4276] eta: 3:35:40 lr: 1.6912941045737364e-05 loss: 0.0900 (0.0960) time: 2.9193 data: 0.0073 max mem: 33301 +Epoch: [28] [ 30/4276] eta: 3:33:27 lr: 1.6909973313515935e-05 loss: 0.0902 (0.0945) time: 2.9468 data: 0.0079 max mem: 33301 +Epoch: [28] [ 40/4276] eta: 3:32:16 lr: 1.6907005523421973e-05 loss: 0.0891 (0.0914) time: 2.9714 data: 0.0082 max mem: 33301 +Epoch: [28] [ 50/4276] eta: 3:31:10 lr: 1.690403767544307e-05 loss: 0.0831 (0.0902) time: 2.9700 data: 0.0077 max mem: 33301 +Epoch: [28] [ 60/4276] eta: 3:30:00 lr: 1.69010697695668e-05 loss: 0.0774 (0.0886) time: 2.9519 data: 0.0075 max mem: 33301 +Epoch: [28] [ 70/4276] eta: 3:29:08 lr: 1.689810180578073e-05 loss: 0.0746 (0.0869) time: 2.9460 data: 0.0073 max mem: 33301 +Epoch: [28] [ 80/4276] eta: 3:28:23 lr: 1.6895133784072437e-05 loss: 0.0705 (0.0870) time: 2.9524 data: 0.0072 max mem: 33301 +Epoch: [28] [ 90/4276] eta: 3:27:41 lr: 1.6892165704429487e-05 loss: 0.0772 (0.0871) time: 2.9536 data: 0.0077 max mem: 33301 +Epoch: [28] [ 100/4276] eta: 3:27:00 lr: 1.6889197566839425e-05 loss: 0.0913 (0.0893) time: 2.9523 data: 0.0079 max mem: 33301 +Epoch: [28] [ 110/4276] eta: 3:26:30 lr: 1.6886229371289815e-05 loss: 0.0983 (0.0900) time: 2.9614 data: 0.0077 max mem: 33301 +Epoch: [28] [ 120/4276] eta: 3:25:45 lr: 1.6883261117768203e-05 loss: 0.0847 (0.0896) time: 2.9516 data: 0.0078 max mem: 33301 +Epoch: [28] [ 130/4276] eta: 3:25:46 lr: 1.6880292806262127e-05 loss: 0.0849 (0.0902) time: 2.9996 data: 0.0078 max mem: 33301 +Epoch: [28] [ 140/4276] eta: 3:25:09 lr: 1.6877324436759126e-05 loss: 0.0834 (0.0899) time: 3.0100 data: 0.0076 max mem: 33301 +Epoch: [28] [ 150/4276] eta: 10:01:49 lr: 1.6874356009246735e-05 loss: 0.0915 (0.0905) time: 46.5688 data: 43.6053 max mem: 33301 +Epoch: [28] [ 160/4276] eta: 9:35:39 lr: 1.687138752371249e-05 loss: 0.0938 (0.0904) time: 46.5708 data: 43.6053 max mem: 33301 +Epoch: [28] [ 170/4276] eta: 9:12:31 lr: 1.6868418980143892e-05 loss: 0.0843 (0.0906) time: 2.9561 data: 0.0077 max mem: 33301 +Epoch: [28] [ 180/4276] eta: 8:51:48 lr: 1.6865450378528476e-05 loss: 0.0843 (0.0908) time: 2.9492 data: 0.0083 max mem: 33301 +Epoch: [28] [ 190/4276] eta: 8:33:18 lr: 1.686248171885375e-05 loss: 0.0842 (0.0904) time: 2.9537 data: 0.0079 max mem: 33301 +Epoch: [28] [ 200/4276] eta: 8:16:33 lr: 1.685951300110722e-05 loss: 0.0821 (0.0902) time: 2.9596 data: 0.0072 max mem: 33301 +Epoch: [28] [ 210/4276] eta: 8:01:23 lr: 1.685654422527638e-05 loss: 0.0867 (0.0903) time: 2.9586 data: 0.0070 max mem: 33301 +Epoch: [28] [ 220/4276] eta: 7:47:32 lr: 1.6853575391348736e-05 loss: 0.0810 (0.0899) time: 2.9647 data: 0.0071 max mem: 33301 +Epoch: [28] [ 230/4276] eta: 7:34:51 lr: 1.6850606499311778e-05 loss: 0.0776 (0.0895) time: 2.9638 data: 0.0071 max mem: 33301 +Epoch: [28] [ 240/4276] eta: 7:23:09 lr: 1.6847637549152997e-05 loss: 0.0849 (0.0903) time: 2.9597 data: 0.0073 max mem: 33301 +Epoch: [28] [ 250/4276] eta: 7:12:24 lr: 1.6844668540859862e-05 loss: 0.0971 (0.0911) time: 2.9676 data: 0.0072 max mem: 33301 +Epoch: [28] [ 260/4276] eta: 7:02:25 lr: 1.684169947441986e-05 loss: 0.0919 (0.0910) time: 2.9729 data: 0.0071 max mem: 33301 +Epoch: [28] [ 270/4276] eta: 6:52:59 lr: 1.6838730349820454e-05 loss: 0.0670 (0.0909) time: 2.9393 data: 0.0076 max mem: 33301 +Epoch: [28] [ 280/4276] eta: 6:44:33 lr: 1.683576116704912e-05 loss: 0.0683 (0.0905) time: 2.9878 data: 0.0077 max mem: 33301 +Epoch: [28] [ 290/4276] eta: 10:09:53 lr: 1.6832791926093306e-05 loss: 0.0770 (0.0903) time: 49.7612 data: 46.7245 max mem: 33301 +Epoch: [28] [ 300/4276] eta: 9:54:36 lr: 1.682982262694047e-05 loss: 0.0818 (0.0903) time: 49.6951 data: 46.7247 max mem: 33301 +Epoch: [28] [ 310/4276] eta: 9:40:17 lr: 1.6826853269578072e-05 loss: 0.0798 (0.0900) time: 2.9366 data: 0.0072 max mem: 33301 +Epoch: [28] [ 320/4276] eta: 9:26:50 lr: 1.6823883853993556e-05 loss: 0.0844 (0.0903) time: 2.9440 data: 0.0071 max mem: 33301 +Epoch: [28] [ 330/4276] eta: 9:14:11 lr: 1.682091438017435e-05 loss: 0.0947 (0.0904) time: 2.9477 data: 0.0077 max mem: 33301 +Epoch: [28] [ 340/4276] eta: 9:02:15 lr: 1.6817944848107894e-05 loss: 0.0856 (0.0910) time: 2.9502 data: 0.0078 max mem: 33301 +Epoch: [28] [ 350/4276] eta: 8:50:56 lr: 1.6814975257781622e-05 loss: 0.0916 (0.0912) time: 2.9459 data: 0.0075 max mem: 33301 +Epoch: [28] [ 360/4276] eta: 8:40:14 lr: 1.681200560918296e-05 loss: 0.0947 (0.0919) time: 2.9406 data: 0.0074 max mem: 33301 +Epoch: [28] [ 370/4276] eta: 8:30:06 lr: 1.6809035902299316e-05 loss: 0.0986 (0.0923) time: 2.9458 data: 0.0076 max mem: 33301 +Epoch: [28] [ 380/4276] eta: 8:20:28 lr: 1.6806066137118116e-05 loss: 0.0986 (0.0925) time: 2.9499 data: 0.0076 max mem: 33301 +Epoch: [28] [ 390/4276] eta: 8:11:18 lr: 1.680309631362676e-05 loss: 0.1011 (0.0927) time: 2.9539 data: 0.0074 max mem: 33301 +Epoch: [28] [ 400/4276] eta: 8:02:31 lr: 1.680012643181266e-05 loss: 0.1033 (0.0931) time: 2.9352 data: 0.0071 max mem: 33301 +Epoch: [28] [ 410/4276] eta: 7:54:10 lr: 1.6797156491663207e-05 loss: 0.1033 (0.0934) time: 2.9266 data: 0.0074 max mem: 33301 +Epoch: [28] [ 420/4276] eta: 7:46:08 lr: 1.67941864931658e-05 loss: 0.0996 (0.0935) time: 2.9194 data: 0.0079 max mem: 33301 +Epoch: [28] [ 430/4276] eta: 7:38:32 lr: 1.6791216436307823e-05 loss: 0.0947 (0.0936) time: 2.9283 data: 0.0081 max mem: 33301 +Epoch: [28] [ 440/4276] eta: 7:31:15 lr: 1.678824632107666e-05 loss: 0.0904 (0.0934) time: 2.9541 data: 0.0079 max mem: 33301 +Epoch: [28] [ 450/4276] eta: 7:24:16 lr: 1.6785276147459686e-05 loss: 0.0923 (0.0936) time: 2.9506 data: 0.0079 max mem: 33301 +Epoch: [28] [ 460/4276] eta: 7:17:33 lr: 1.6782305915444275e-05 loss: 0.0929 (0.0935) time: 2.9454 data: 0.0078 max mem: 33301 +Epoch: [28] [ 470/4276] eta: 7:11:07 lr: 1.6779335625017805e-05 loss: 0.0894 (0.0934) time: 2.9459 data: 0.0076 max mem: 33301 +Epoch: [28] [ 480/4276] eta: 7:04:55 lr: 1.677636527616762e-05 loss: 0.0870 (0.0933) time: 2.9524 data: 0.0079 max mem: 33301 +Epoch: [28] [ 490/4276] eta: 6:59:01 lr: 1.677339486888109e-05 loss: 0.0838 (0.0930) time: 2.9688 data: 0.0078 max mem: 33301 +Epoch: [28] [ 500/4276] eta: 6:53:18 lr: 1.677042440314556e-05 loss: 0.0838 (0.0929) time: 2.9818 data: 0.0079 max mem: 33301 +Epoch: [28] [ 510/4276] eta: 6:47:43 lr: 1.676745387894838e-05 loss: 0.0937 (0.0933) time: 2.9447 data: 0.0085 max mem: 33301 +Epoch: [28] [ 520/4276] eta: 6:42:21 lr: 1.6764483296276887e-05 loss: 0.0977 (0.0934) time: 2.9211 data: 0.0087 max mem: 33301 +Epoch: [28] [ 530/4276] eta: 6:37:12 lr: 1.676151265511842e-05 loss: 0.0894 (0.0937) time: 2.9474 data: 0.0086 max mem: 33301 +Epoch: [28] [ 540/4276] eta: 6:32:15 lr: 1.6758541955460308e-05 loss: 0.0894 (0.0936) time: 2.9720 data: 0.0087 max mem: 33301 +Epoch: [28] [ 550/4276] eta: 6:27:25 lr: 1.675557119728988e-05 loss: 0.0894 (0.0936) time: 2.9608 data: 0.0089 max mem: 33301 +Epoch: [28] [ 560/4276] eta: 6:22:44 lr: 1.675260038059445e-05 loss: 0.0904 (0.0936) time: 2.9353 data: 0.0087 max mem: 33301 +Epoch: [28] [ 570/4276] eta: 6:18:10 lr: 1.674962950536134e-05 loss: 0.0923 (0.0935) time: 2.9236 data: 0.0082 max mem: 33301 +Epoch: [28] [ 580/4276] eta: 6:13:43 lr: 1.674665857157785e-05 loss: 0.0867 (0.0935) time: 2.8987 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(0.0933) time: 2.9612 data: 0.0087 max mem: 33301 +Epoch: [28] [ 670/4276] eta: 5:39:24 lr: 1.6719917530663142e-05 loss: 0.0963 (0.0931) time: 2.9637 data: 0.0084 max mem: 33301 +Epoch: [28] [ 680/4276] eta: 5:36:04 lr: 1.6716946010676788e-05 loss: 0.0854 (0.0929) time: 2.9392 data: 0.0091 max mem: 33301 +Epoch: [28] [ 690/4276] eta: 5:32:49 lr: 1.6713974432000117e-05 loss: 0.0854 (0.0929) time: 2.9269 data: 0.0093 max mem: 33301 +Epoch: [28] [ 700/4276] eta: 5:29:39 lr: 1.671100279462038e-05 loss: 0.0819 (0.0927) time: 2.9323 data: 0.0089 max mem: 33301 +Epoch: [28] [ 710/4276] eta: 5:26:35 lr: 1.6708031098524817e-05 loss: 0.0799 (0.0927) time: 2.9532 data: 0.0087 max mem: 33301 +Epoch: [28] [ 720/4276] eta: 5:23:36 lr: 1.670505934370066e-05 loss: 0.0807 (0.0926) time: 2.9703 data: 0.0083 max mem: 33301 +Epoch: [28] [ 730/4276] eta: 5:20:41 lr: 1.670208753013514e-05 loss: 0.0806 (0.0927) time: 2.9820 data: 0.0091 max mem: 33301 +Epoch: [28] [ 740/4276] eta: 5:17:48 lr: 1.6699115657815492e-05 loss: 0.0825 (0.0926) time: 2.9622 data: 0.0090 max mem: 33301 +Epoch: [28] [ 750/4276] eta: 5:14:59 lr: 1.669614372672892e-05 loss: 0.0860 (0.0925) time: 2.9393 data: 0.0082 max mem: 33301 +Epoch: [28] [ 760/4276] eta: 5:12:14 lr: 1.6693171736862647e-05 loss: 0.0860 (0.0925) time: 2.9382 data: 0.0081 max mem: 33301 +Epoch: [28] [ 770/4276] eta: 5:09:32 lr: 1.669019968820388e-05 loss: 0.0865 (0.0925) time: 2.9394 data: 0.0084 max mem: 33301 +Epoch: [28] [ 780/4276] eta: 5:06:53 lr: 1.6687227580739835e-05 loss: 0.0871 (0.0925) time: 2.9404 data: 0.0085 max mem: 33301 +Epoch: [28] [ 790/4276] eta: 5:04:18 lr: 1.668425541445769e-05 loss: 0.0894 (0.0925) time: 2.9394 data: 0.0082 max mem: 33301 +Epoch: [28] [ 800/4276] eta: 5:01:46 lr: 1.668128318934465e-05 loss: 0.0888 (0.0926) time: 2.9379 data: 0.0081 max mem: 33301 +Epoch: [28] [ 810/4276] eta: 4:59:17 lr: 1.66783109053879e-05 loss: 0.0935 (0.0928) time: 2.9385 data: 0.0086 max mem: 33301 +Epoch: [28] [ 820/4276] eta: 4:56:51 lr: 1.667533856257463e-05 loss: 0.0905 (0.0926) time: 2.9382 data: 0.0089 max mem: 33301 +Epoch: [28] [ 830/4276] eta: 4:54:27 lr: 1.6672366160892008e-05 loss: 0.0811 (0.0926) time: 2.9319 data: 0.0089 max mem: 33301 +Epoch: [28] [ 840/4276] eta: 4:52:06 lr: 1.666939370032721e-05 loss: 0.1015 (0.0927) time: 2.9331 data: 0.0084 max mem: 33301 +Epoch: [28] [ 850/4276] eta: 4:49:48 lr: 1.66664211808674e-05 loss: 0.0756 (0.0925) time: 2.9386 data: 0.0079 max mem: 33301 +Epoch: [28] [ 860/4276] eta: 4:47:32 lr: 1.6663448602499748e-05 loss: 0.0865 (0.0926) time: 2.9383 data: 0.0078 max mem: 33301 +Epoch: [28] [ 870/4276] eta: 4:45:19 lr: 1.66604759652114e-05 loss: 0.0878 (0.0925) time: 2.9396 data: 0.0077 max mem: 33301 +Epoch: [28] [ 880/4276] eta: 4:43:09 lr: 1.6657503268989508e-05 loss: 0.0848 (0.0927) time: 2.9388 data: 0.0077 max mem: 33301 +Epoch: [28] [ 890/4276] eta: 4:41:00 lr: 1.665453051382122e-05 loss: 0.0940 (0.0929) time: 2.9373 data: 0.0078 max mem: 33301 +Epoch: [28] [ 900/4276] eta: 4:38:54 lr: 1.6651557699693684e-05 loss: 0.0946 (0.0929) time: 2.9371 data: 0.0079 max mem: 33301 +Epoch: [28] [ 910/4276] eta: 4:36:50 lr: 1.664858482659402e-05 loss: 0.0946 (0.0929) time: 2.9379 data: 0.0077 max mem: 33301 +Epoch: [28] [ 920/4276] eta: 4:34:48 lr: 1.664561189450936e-05 loss: 0.0987 (0.0930) time: 2.9390 data: 0.0077 max mem: 33301 +Epoch: [28] [ 930/4276] eta: 4:32:48 lr: 1.664263890342683e-05 loss: 0.0926 (0.0930) time: 2.9454 data: 0.0084 max mem: 33301 +Epoch: [28] [ 940/4276] eta: 4:30:50 lr: 1.663966585333356e-05 loss: 0.0848 (0.0930) time: 2.9456 data: 0.0091 max mem: 33301 +Epoch: [28] [ 950/4276] eta: 4:28:54 lr: 1.6636692744216643e-05 loss: 0.0858 (0.0931) time: 2.9403 data: 0.0085 max mem: 33301 +Epoch: [28] [ 960/4276] eta: 4:26:59 lr: 1.6633719576063203e-05 loss: 0.0908 (0.0932) time: 2.9393 data: 0.0081 max mem: 33301 +Epoch: [28] [ 970/4276] eta: 4:25:06 lr: 1.6630746348860334e-05 loss: 0.0862 (0.0931) time: 2.9295 data: 0.0084 max mem: 33301 +Epoch: [28] [ 980/4276] eta: 4:23:13 lr: 1.6627773062595138e-05 loss: 0.0948 (0.0932) time: 2.9095 data: 0.0088 max mem: 33301 +Epoch: [28] [ 990/4276] eta: 4:21:23 lr: 1.6624799717254697e-05 loss: 0.0917 (0.0931) time: 2.9060 data: 0.0092 max mem: 33301 +Epoch: [28] [1000/4276] eta: 4:19:34 lr: 1.6621826312826105e-05 loss: 0.0836 (0.0931) time: 2.9119 data: 0.0087 max mem: 33301 +Epoch: [28] [1010/4276] eta: 4:17:47 lr: 1.661885284929645e-05 loss: 0.0923 (0.0931) time: 2.9022 data: 0.0086 max mem: 33301 +Epoch: [28] [1020/4276] eta: 4:16:00 lr: 1.6615879326652788e-05 loss: 0.0923 (0.0931) time: 2.8906 data: 0.0086 max mem: 33301 +Epoch: [28] [1030/4276] eta: 4:14:16 lr: 1.6612905744882205e-05 loss: 0.0947 (0.0931) time: 2.8846 data: 0.0080 max mem: 33301 +Epoch: [28] [1040/4276] eta: 4:12:33 lr: 1.660993210397176e-05 loss: 0.0947 (0.0931) time: 2.8942 data: 0.0085 max mem: 33301 +Epoch: [28] [1050/4276] eta: 4:10:52 lr: 1.660695840390852e-05 loss: 0.0906 (0.0932) time: 2.9111 data: 0.0089 max mem: 33301 +Epoch: [28] [1060/4276] eta: 4:09:13 lr: 1.6603984644679522e-05 loss: 0.0983 (0.0933) time: 2.9274 data: 0.0085 max mem: 33301 +Epoch: [28] [1070/4276] eta: 4:07:35 lr: 1.6601010826271827e-05 loss: 0.1042 (0.0934) time: 2.9384 data: 0.0086 max mem: 33301 +Epoch: [28] [1080/4276] eta: 4:05:57 lr: 1.6598036948672474e-05 loss: 0.1029 (0.0935) time: 2.9202 data: 0.0085 max mem: 33301 +Epoch: [28] [1090/4276] eta: 4:04:21 lr: 1.659506301186851e-05 loss: 0.1044 (0.0937) time: 2.8962 data: 0.0082 max mem: 33301 +Epoch: [28] [1100/4276] eta: 4:02:46 lr: 1.659208901584695e-05 loss: 0.1089 (0.0937) time: 2.8991 data: 0.0081 max mem: 33301 +Epoch: [28] [1110/4276] eta: 4:01:12 lr: 1.6589114960594832e-05 loss: 0.0984 (0.0938) time: 2.9025 data: 0.0083 max mem: 33301 +Epoch: [28] [1120/4276] eta: 3:59:39 lr: 1.6586140846099174e-05 loss: 0.0984 (0.0938) time: 2.8936 data: 0.0086 max mem: 33301 +Epoch: [28] [1130/4276] eta: 3:58:08 lr: 1.6583166672347e-05 loss: 0.0878 (0.0938) time: 2.9021 data: 0.0087 max mem: 33301 +Epoch: [28] [1140/4276] eta: 3:56:38 lr: 1.658019243932531e-05 loss: 0.0865 (0.0938) time: 2.9276 data: 0.0087 max mem: 33301 +Epoch: [28] [1150/4276] eta: 3:55:10 lr: 1.6577218147021108e-05 loss: 0.0913 (0.0937) time: 2.9408 data: 0.0082 max mem: 33301 +Epoch: [28] [1160/4276] eta: 3:53:43 lr: 1.65742437954214e-05 loss: 0.0901 (0.0937) time: 2.9445 data: 0.0078 max mem: 33301 +Epoch: [28] [1170/4276] eta: 3:52:16 lr: 1.657126938451318e-05 loss: 0.0871 (0.0937) time: 2.9433 data: 0.0074 max mem: 33301 +Epoch: [28] [1180/4276] eta: 3:50:51 lr: 1.6568294914283435e-05 loss: 0.0871 (0.0937) time: 2.9450 data: 0.0074 max mem: 33301 +Epoch: [28] [1190/4276] eta: 3:49:26 lr: 1.656532038471915e-05 loss: 0.0777 (0.0936) time: 2.9254 data: 0.0074 max mem: 33301 +Epoch: [28] [1200/4276] eta: 3:48:01 lr: 1.6562345795807297e-05 loss: 0.0755 (0.0935) time: 2.8972 data: 0.0071 max mem: 33301 +Epoch: [28] [1210/4276] eta: 3:46:37 lr: 1.6559371147534854e-05 loss: 0.0846 (0.0935) time: 2.8918 data: 0.0071 max mem: 33301 +Epoch: [28] [1220/4276] eta: 3:45:15 lr: 1.6556396439888786e-05 loss: 0.0896 (0.0935) time: 2.9091 data: 0.0072 max mem: 33301 +Epoch: [28] [1230/4276] eta: 3:43:53 lr: 1.6553421672856055e-05 loss: 0.0871 (0.0935) time: 2.9106 data: 0.0078 max mem: 33301 +Epoch: [28] [1240/4276] eta: 3:42:32 lr: 1.655044684642361e-05 loss: 0.0871 (0.0934) time: 2.8999 data: 0.0079 max mem: 33301 +Epoch: [28] [1250/4276] eta: 3:41:12 lr: 1.654747196057842e-05 loss: 0.0891 (0.0934) time: 2.9179 data: 0.0079 max mem: 33301 +Epoch: [28] [1260/4276] eta: 3:39:54 lr: 1.6544497015307412e-05 loss: 0.0857 (0.0934) time: 2.9275 data: 0.0078 max mem: 33301 +Epoch: [28] [1270/4276] eta: 3:38:36 lr: 1.654152201059753e-05 loss: 0.0857 (0.0933) time: 2.9327 data: 0.0077 max mem: 33301 +Epoch: [28] [1280/4276] eta: 3:37:19 lr: 1.653854694643571e-05 loss: 0.0950 (0.0933) time: 2.9371 data: 0.0077 max mem: 33301 +Epoch: [28] [1290/4276] eta: 3:36:03 lr: 1.6535571822808884e-05 loss: 0.1019 (0.0934) time: 2.9396 data: 0.0077 max mem: 33301 +Epoch: [28] [1300/4276] eta: 3:34:48 lr: 1.6532596639703965e-05 loss: 0.0873 (0.0934) time: 2.9532 data: 0.0076 max mem: 33301 +Epoch: [28] [1310/4276] eta: 3:33:32 lr: 1.652962139710788e-05 loss: 0.0753 (0.0933) time: 2.9361 data: 0.0079 max mem: 33301 +Epoch: [28] [1320/4276] eta: 3:32:18 lr: 1.652664609500754e-05 loss: 0.0901 (0.0935) time: 2.9222 data: 0.0080 max mem: 33301 +Epoch: [28] [1330/4276] eta: 3:31:05 lr: 1.6523670733389844e-05 loss: 0.0891 (0.0934) time: 2.9414 data: 0.0073 max mem: 33301 +Epoch: [28] [1340/4276] eta: 3:29:52 lr: 1.65206953122417e-05 loss: 0.0829 (0.0934) time: 2.9485 data: 0.0076 max mem: 33301 +Epoch: [28] [1350/4276] eta: 3:28:40 lr: 1.6517719831550003e-05 loss: 0.0860 (0.0934) time: 2.9286 data: 0.0075 max mem: 33301 +Epoch: [28] [1360/4276] eta: 3:27:27 lr: 1.6514744291301644e-05 loss: 0.0917 (0.0934) time: 2.9050 data: 0.0077 max mem: 33301 +Epoch: [28] [1370/4276] eta: 3:26:16 lr: 1.65117686914835e-05 loss: 0.0780 (0.0934) time: 2.9098 data: 0.0079 max mem: 33301 +Epoch: [28] [1380/4276] eta: 3:25:06 lr: 1.6508793032082458e-05 loss: 0.0932 (0.0935) time: 2.9249 data: 0.0077 max mem: 33301 +Epoch: [28] [1390/4276] eta: 3:23:55 lr: 1.650581731308539e-05 loss: 0.1014 (0.0935) time: 2.9201 data: 0.0078 max mem: 33301 +Epoch: [28] [1400/4276] eta: 3:22:45 lr: 1.6502841534479165e-05 loss: 0.0910 (0.0935) time: 2.9048 data: 0.0077 max mem: 33301 +Epoch: [28] [1410/4276] eta: 3:21:36 lr: 1.6499865696250642e-05 loss: 0.0855 (0.0935) time: 2.8967 data: 0.0075 max mem: 33301 +Epoch: [28] [1420/4276] eta: 3:20:27 lr: 1.6496889798386677e-05 loss: 0.0851 (0.0935) time: 2.8907 data: 0.0073 max mem: 33301 +Epoch: [28] [1430/4276] eta: 3:19:19 lr: 1.6493913840874124e-05 loss: 0.0929 (0.0936) time: 2.8893 data: 0.0072 max mem: 33301 +Epoch: [28] [1440/4276] eta: 3:18:11 lr: 1.6490937823699835e-05 loss: 0.0995 (0.0936) time: 2.8945 data: 0.0072 max mem: 33301 +Epoch: [28] [1450/4276] eta: 3:17:04 lr: 1.648796174685064e-05 loss: 0.0898 (0.0936) time: 2.9033 data: 0.0073 max mem: 33301 +Epoch: [28] [1460/4276] eta: 3:15:57 lr: 1.6484985610313376e-05 loss: 0.0841 (0.0935) time: 2.9040 data: 0.0074 max mem: 33301 +Epoch: [28] [1470/4276] eta: 3:14:51 lr: 1.6482009414074872e-05 loss: 0.0834 (0.0935) time: 2.8957 data: 0.0073 max mem: 33301 +Epoch: [28] [1480/4276] eta: 3:13:45 lr: 1.6479033158121962e-05 loss: 0.0867 (0.0935) time: 2.8865 data: 0.0072 max mem: 33301 +Epoch: [28] [1490/4276] eta: 3:12:40 lr: 1.6476056842441452e-05 loss: 0.0867 (0.0934) time: 2.8860 data: 0.0073 max mem: 33301 +Epoch: [28] [1500/4276] eta: 3:11:35 lr: 1.6473080467020155e-05 loss: 0.0791 (0.0934) time: 2.8888 data: 0.0073 max mem: 33301 +Epoch: [28] [1510/4276] eta: 3:10:31 lr: 1.6470104031844882e-05 loss: 0.0791 (0.0933) time: 2.8899 data: 0.0073 max mem: 33301 +Epoch: [28] [1520/4276] eta: 3:09:28 lr: 1.646712753690244e-05 loss: 0.0754 (0.0933) time: 2.9102 data: 0.0072 max mem: 33301 +Epoch: [28] [1530/4276] eta: 3:08:25 lr: 1.6464150982179616e-05 loss: 0.0769 (0.0932) time: 2.9323 data: 0.0071 max mem: 33301 +Epoch: [28] [1540/4276] eta: 3:07:22 lr: 1.6461174367663202e-05 loss: 0.0806 (0.0931) time: 2.9205 data: 0.0071 max mem: 33301 +Epoch: [28] [1550/4276] eta: 3:06:21 lr: 1.6458197693339984e-05 loss: 0.0823 (0.0931) time: 2.9244 data: 0.0074 max mem: 33301 +Epoch: [28] [1560/4276] eta: 3:05:19 lr: 1.6455220959196744e-05 loss: 0.0821 (0.0931) time: 2.9355 data: 0.0083 max mem: 33301 +Epoch: [28] [1570/4276] eta: 3:04:18 lr: 1.6452244165220253e-05 loss: 0.0818 (0.0930) time: 2.9266 data: 0.0082 max mem: 33301 +Epoch: [28] [1580/4276] eta: 3:03:18 lr: 1.6449267311397272e-05 loss: 0.0783 (0.0930) time: 2.9353 data: 0.0073 max mem: 33301 +Epoch: [28] [1590/4276] eta: 3:02:18 lr: 1.6446290397714574e-05 loss: 0.0828 (0.0931) time: 2.9384 data: 0.0073 max mem: 33301 +Epoch: [28] [1600/4276] eta: 3:01:18 lr: 1.644331342415892e-05 loss: 0.0881 (0.0931) time: 2.9306 data: 0.0075 max mem: 33301 +Epoch: [28] [1610/4276] eta: 3:00:18 lr: 1.644033639071704e-05 loss: 0.0942 (0.0931) time: 2.9247 data: 0.0079 max mem: 33301 +Epoch: [28] [1620/4276] eta: 2:59:19 lr: 1.64373592973757e-05 loss: 0.0911 (0.0930) time: 2.9247 data: 0.0078 max mem: 33301 +Epoch: [28] [1630/4276] eta: 2:58:21 lr: 1.6434382144121637e-05 loss: 0.0917 (0.0931) time: 2.9349 data: 0.0074 max mem: 33301 +Epoch: [28] [1640/4276] eta: 2:57:22 lr: 1.6431404930941577e-05 loss: 0.0929 (0.0931) time: 2.9180 data: 0.0075 max mem: 33301 +Epoch: [28] [1650/4276] eta: 2:56:24 lr: 1.642842765782225e-05 loss: 0.0799 (0.0930) time: 2.9155 data: 0.0076 max mem: 33301 +Epoch: [28] [1660/4276] eta: 2:55:26 lr: 1.6425450324750383e-05 loss: 0.0799 (0.0929) time: 2.9355 data: 0.0074 max mem: 33301 +Epoch: [28] [1670/4276] eta: 2:54:29 lr: 1.6422472931712702e-05 loss: 0.0800 (0.0929) time: 2.9232 data: 0.0072 max mem: 33301 +Epoch: [28] [1680/4276] eta: 2:53:31 lr: 1.64194954786959e-05 loss: 0.0871 (0.0929) time: 2.9086 data: 0.0073 max mem: 33301 +Epoch: [28] [1690/4276] eta: 2:52:34 lr: 1.6416517965686696e-05 loss: 0.0807 (0.0928) time: 2.8978 data: 0.0073 max mem: 33301 +Epoch: [28] [1700/4276] eta: 2:51:38 lr: 1.6413540392671787e-05 loss: 0.0822 (0.0928) time: 2.9210 data: 0.0072 max mem: 33301 +Epoch: [28] [1710/4276] eta: 2:50:42 lr: 1.6410562759637878e-05 loss: 0.0944 (0.0928) time: 2.9319 data: 0.0073 max mem: 33301 +Epoch: [28] [1720/4276] eta: 2:49:46 lr: 1.6407585066571637e-05 loss: 0.0797 (0.0928) time: 2.9169 data: 0.0074 max mem: 33301 +Epoch: [28] [1730/4276] eta: 2:48:51 lr: 1.6404607313459766e-05 loss: 0.0797 (0.0927) time: 2.9195 data: 0.0075 max mem: 33301 +Epoch: [28] [1740/4276] eta: 2:47:56 lr: 1.6401629500288936e-05 loss: 0.0825 (0.0927) time: 2.9281 data: 0.0079 max mem: 33301 +Epoch: [28] [1750/4276] eta: 2:47:01 lr: 1.6398651627045828e-05 loss: 0.0788 (0.0926) time: 2.9419 data: 0.0080 max mem: 33301 +Epoch: [28] [1760/4276] eta: 2:46:07 lr: 1.6395673693717096e-05 loss: 0.0789 (0.0925) time: 2.9406 data: 0.0080 max mem: 33301 +Epoch: [28] [1770/4276] eta: 2:45:12 lr: 1.6392695700289408e-05 loss: 0.0848 (0.0925) time: 2.9264 data: 0.0079 max mem: 33301 +Epoch: [28] [1780/4276] eta: 2:44:18 lr: 1.6389717646749418e-05 loss: 0.0906 (0.0925) time: 2.9269 data: 0.0074 max mem: 33301 +Epoch: [28] [1790/4276] eta: 2:43:24 lr: 1.638673953308378e-05 loss: 0.0845 (0.0925) time: 2.9195 data: 0.0074 max mem: 33301 +Epoch: [28] [1800/4276] eta: 2:42:31 lr: 1.6383761359279135e-05 loss: 0.0774 (0.0924) time: 2.9009 data: 0.0078 max mem: 33301 +Epoch: [28] [1810/4276] eta: 2:41:37 lr: 1.638078312532212e-05 loss: 0.0790 (0.0924) time: 2.9057 data: 0.0076 max mem: 33301 +Epoch: [28] [1820/4276] eta: 2:40:44 lr: 1.6377804831199366e-05 loss: 0.0836 (0.0924) time: 2.9056 data: 0.0073 max mem: 33301 +Epoch: [28] [1830/4276] eta: 2:39:51 lr: 1.6374826476897515e-05 loss: 0.0836 (0.0924) time: 2.9021 data: 0.0074 max mem: 33301 +Epoch: [28] [1840/4276] eta: 2:38:58 lr: 1.637184806240317e-05 loss: 0.0766 (0.0923) time: 2.9051 data: 0.0077 max mem: 33301 +Epoch: [28] [1850/4276] eta: 2:38:06 lr: 1.6368869587702955e-05 loss: 0.0830 (0.0923) time: 2.9134 data: 0.0082 max mem: 33301 +Epoch: [28] [1860/4276] eta: 2:37:15 lr: 1.6365891052783475e-05 loss: 0.0888 (0.0923) time: 2.9359 data: 0.0080 max mem: 33301 +Epoch: [28] [1870/4276] eta: 2:36:23 lr: 1.636291245763135e-05 loss: 0.0911 (0.0924) time: 2.9308 data: 0.0075 max mem: 33301 +Epoch: [28] [1880/4276] eta: 2:35:31 lr: 1.635993380223316e-05 loss: 0.0911 (0.0924) time: 2.9076 data: 0.0075 max mem: 33302 +Epoch: [28] [1890/4276] eta: 2:34:40 lr: 1.6356955086575508e-05 loss: 0.0853 (0.0923) time: 2.9142 data: 0.0073 max mem: 33302 +Epoch: [28] [1900/4276] eta: 2:33:49 lr: 1.635397631064498e-05 loss: 0.0820 (0.0923) time: 2.9086 data: 0.0074 max mem: 33302 +Epoch: [28] [1910/4276] eta: 2:32:58 lr: 1.6350997474428163e-05 loss: 0.0835 (0.0923) time: 2.9014 data: 0.0077 max mem: 33302 +Epoch: [28] [1920/4276] eta: 2:32:07 lr: 1.634801857791162e-05 loss: 0.0823 (0.0922) time: 2.9051 data: 0.0076 max mem: 33302 +Epoch: [28] [1930/4276] eta: 2:31:16 lr: 1.634503962108193e-05 loss: 0.0823 (0.0922) time: 2.8964 data: 0.0076 max mem: 33302 +Epoch: [28] [1940/4276] eta: 2:30:26 lr: 1.6342060603925663e-05 loss: 0.0879 (0.0922) time: 2.9081 data: 0.0075 max mem: 33302 +Epoch: [28] [1950/4276] eta: 2:29:36 lr: 1.6339081526429366e-05 loss: 0.0879 (0.0922) time: 2.9114 data: 0.0077 max mem: 33302 +Epoch: [28] [1960/4276] eta: 2:28:46 lr: 1.6336102388579597e-05 loss: 0.0801 (0.0921) time: 2.9000 data: 0.0083 max mem: 33302 +Epoch: [28] [1970/4276] eta: 2:27:56 lr: 1.6333123190362907e-05 loss: 0.0801 (0.0921) time: 2.9032 data: 0.0087 max mem: 33302 +Epoch: [28] [1980/4276] eta: 2:27:07 lr: 1.6330143931765836e-05 loss: 0.0763 (0.0920) time: 2.9004 data: 0.0079 max mem: 33302 +Epoch: [28] [1990/4276] eta: 2:26:18 lr: 1.6327164612774917e-05 loss: 0.0798 (0.0921) time: 2.9153 data: 0.0077 max mem: 33302 +Epoch: [28] [2000/4276] eta: 2:25:29 lr: 1.632418523337668e-05 loss: 0.1021 (0.0921) time: 2.9185 data: 0.0081 max mem: 33302 +Epoch: [28] [2010/4276] eta: 2:24:40 lr: 1.6321205793557652e-05 loss: 0.0899 (0.0921) time: 2.9059 data: 0.0078 max mem: 33302 +Epoch: [28] [2020/4276] eta: 2:23:51 lr: 1.631822629330436e-05 loss: 0.0911 (0.0921) time: 2.8987 data: 0.0076 max mem: 33302 +Epoch: [28] [2030/4276] eta: 2:23:03 lr: 1.63152467326033e-05 loss: 0.0815 (0.0920) time: 2.9188 data: 0.0075 max mem: 33302 +Epoch: [28] [2040/4276] eta: 2:22:16 lr: 1.631226711144099e-05 loss: 0.0774 (0.0920) time: 2.9572 data: 0.0073 max mem: 33302 +Epoch: [28] [2050/4276] eta: 2:21:28 lr: 1.630928742980393e-05 loss: 0.0886 (0.0920) time: 2.9321 data: 0.0079 max mem: 33302 +Epoch: [28] [2060/4276] eta: 2:20:40 lr: 1.630630768767862e-05 loss: 0.0922 (0.0920) time: 2.9055 data: 0.0080 max mem: 33302 +Epoch: [28] [2070/4276] eta: 2:19:52 lr: 1.630332788505154e-05 loss: 0.0862 (0.0920) time: 2.9055 data: 0.0072 max mem: 33302 +Epoch: [28] [2080/4276] eta: 2:19:05 lr: 1.630034802190918e-05 loss: 0.0862 (0.0921) time: 2.9162 data: 0.0072 max mem: 33302 +Epoch: [28] [2090/4276] eta: 2:18:17 lr: 1.629736809823802e-05 loss: 0.0835 (0.0920) time: 2.9149 data: 0.0076 max mem: 33302 +Epoch: [28] [2100/4276] eta: 2:17:30 lr: 1.6294388114024534e-05 loss: 0.0883 (0.0920) time: 2.9088 data: 0.0078 max mem: 33302 +Epoch: [28] [2110/4276] eta: 2:16:43 lr: 1.6291408069255182e-05 loss: 0.0883 (0.0920) time: 2.9067 data: 0.0078 max mem: 33302 +Epoch: [28] [2120/4276] eta: 2:15:56 lr: 1.6288427963916432e-05 loss: 0.0679 (0.0919) time: 2.8933 data: 0.0078 max mem: 33302 +Epoch: [28] [2130/4276] eta: 2:15:09 lr: 1.6285447797994734e-05 loss: 0.0696 (0.0919) time: 2.8958 data: 0.0080 max mem: 33302 +Epoch: [28] [2140/4276] eta: 2:14:23 lr: 1.6282467571476546e-05 loss: 0.0812 (0.0918) time: 2.8952 data: 0.0079 max mem: 33302 +Epoch: [28] [2150/4276] eta: 2:13:36 lr: 1.6279487284348303e-05 loss: 0.0896 (0.0918) time: 2.8932 data: 0.0076 max mem: 33302 +Epoch: [28] [2160/4276] eta: 2:12:50 lr: 1.6276506936596445e-05 loss: 0.0859 (0.0918) time: 2.8937 data: 0.0082 max mem: 33302 +Epoch: [28] [2170/4276] eta: 2:12:04 lr: 1.6273526528207405e-05 loss: 0.0879 (0.0919) time: 2.8935 data: 0.0083 max mem: 33302 +Epoch: [28] [2180/4276] eta: 2:11:18 lr: 1.6270546059167618e-05 loss: 0.0906 (0.0919) time: 2.8915 data: 0.0079 max mem: 33302 +Epoch: [28] [2190/4276] eta: 2:10:32 lr: 1.6267565529463488e-05 loss: 0.0831 (0.0918) time: 2.8927 data: 0.0080 max mem: 33302 +Epoch: [28] [2200/4276] eta: 2:09:47 lr: 1.6264584939081444e-05 loss: 0.0861 (0.0919) time: 2.9063 data: 0.0078 max mem: 33302 +Epoch: [28] [2210/4276] eta: 2:09:02 lr: 1.6261604288007886e-05 loss: 0.0920 (0.0919) time: 2.9308 data: 0.0078 max mem: 33302 +Epoch: [28] [2220/4276] eta: 2:08:16 lr: 1.625862357622923e-05 loss: 0.0862 (0.0919) time: 2.9166 data: 0.0078 max mem: 33302 +Epoch: [28] [2230/4276] eta: 2:07:31 lr: 1.6255642803731856e-05 loss: 0.0862 (0.0919) time: 2.9086 data: 0.0075 max mem: 33302 +Epoch: [28] [2240/4276] eta: 2:06:46 lr: 1.6252661970502163e-05 loss: 0.0766 (0.0918) time: 2.9146 data: 0.0075 max mem: 33302 +Epoch: [28] [2250/4276] eta: 2:06:01 lr: 1.624968107652655e-05 loss: 0.0776 (0.0918) time: 2.9016 data: 0.0076 max mem: 33302 +Epoch: [28] [2260/4276] eta: 2:05:17 lr: 1.6246700121791372e-05 loss: 0.0821 (0.0918) time: 2.9026 data: 0.0077 max mem: 33302 +Epoch: [28] [2270/4276] eta: 2:04:32 lr: 1.624371910628302e-05 loss: 0.0866 (0.0917) time: 2.9033 data: 0.0078 max mem: 33302 +Epoch: [28] [2280/4276] eta: 2:03:48 lr: 1.624073802998786e-05 loss: 0.0835 (0.0917) time: 2.9119 data: 0.0075 max mem: 33302 +Epoch: [28] [2290/4276] eta: 2:03:04 lr: 1.6237756892892255e-05 loss: 0.0848 (0.0917) time: 2.9298 data: 0.0072 max mem: 33302 +Epoch: [28] [2300/4276] eta: 2:02:20 lr: 1.623477569498256e-05 loss: 0.0891 (0.0917) time: 2.9538 data: 0.0074 max mem: 33302 +Epoch: [28] [2310/4276] eta: 2:01:36 lr: 1.623179443624512e-05 loss: 0.0956 (0.0917) time: 2.9474 data: 0.0075 max mem: 33302 +Epoch: [28] [2320/4276] eta: 2:00:53 lr: 1.6228813116666285e-05 loss: 0.0971 (0.0918) time: 2.9271 data: 0.0073 max mem: 33302 +Epoch: [28] [2330/4276] eta: 2:00:09 lr: 1.6225831736232403e-05 loss: 0.0923 (0.0918) time: 2.9269 data: 0.0077 max mem: 33302 +Epoch: [28] [2340/4276] eta: 1:59:26 lr: 1.622285029492979e-05 loss: 0.0920 (0.0918) time: 2.9317 data: 0.0077 max mem: 33302 +Epoch: [28] [2350/4276] eta: 1:58:42 lr: 1.6219868792744786e-05 loss: 0.0835 (0.0918) time: 2.9245 data: 0.0074 max mem: 33302 +Epoch: [28] [2360/4276] eta: 1:57:59 lr: 1.6216887229663705e-05 loss: 0.0847 (0.0918) time: 2.9067 data: 0.0079 max mem: 33302 +Epoch: [28] [2370/4276] eta: 1:57:15 lr: 1.6213905605672875e-05 loss: 0.0894 (0.0918) time: 2.9008 data: 0.0083 max mem: 33302 +Epoch: [28] [2380/4276] eta: 1:56:32 lr: 1.6210923920758587e-05 loss: 0.0894 (0.0918) time: 2.8980 data: 0.0082 max mem: 33302 +Epoch: [28] [2390/4276] eta: 1:55:49 lr: 1.6207942174907156e-05 loss: 0.0939 (0.0919) time: 2.8932 data: 0.0079 max mem: 33302 +Epoch: [28] [2400/4276] eta: 1:55:06 lr: 1.620496036810488e-05 loss: 0.0939 (0.0919) time: 2.8909 data: 0.0078 max mem: 33302 +Epoch: [28] [2410/4276] eta: 1:54:23 lr: 1.6201978500338054e-05 loss: 0.0894 (0.0919) time: 2.8919 data: 0.0083 max mem: 33302 +Epoch: [28] [2420/4276] eta: 1:53:40 lr: 1.619899657159296e-05 loss: 0.0836 (0.0918) time: 2.8895 data: 0.0080 max mem: 33302 +Epoch: [28] [2430/4276] eta: 1:52:58 lr: 1.6196014581855873e-05 loss: 0.0836 (0.0919) time: 2.9102 data: 0.0077 max mem: 33302 +Epoch: [28] [2440/4276] eta: 1:52:15 lr: 1.6193032531113073e-05 loss: 0.0896 (0.0919) time: 2.9136 data: 0.0079 max mem: 33302 +Epoch: [28] [2450/4276] eta: 1:51:33 lr: 1.6190050419350836e-05 loss: 0.0884 (0.0919) time: 2.9060 data: 0.0084 max mem: 33302 +Epoch: [28] [2460/4276] eta: 1:50:51 lr: 1.6187068246555413e-05 loss: 0.0903 (0.0919) time: 2.9064 data: 0.0084 max mem: 33302 +Epoch: [28] [2470/4276] eta: 1:50:09 lr: 1.6184086012713058e-05 loss: 0.0899 (0.0919) time: 2.9165 data: 0.0085 max mem: 33302 +Epoch: [28] [2480/4276] eta: 1:49:27 lr: 1.6181103717810036e-05 loss: 0.0939 (0.0919) time: 2.9397 data: 0.0082 max mem: 33302 +Epoch: [28] [2490/4276] eta: 1:48:45 lr: 1.6178121361832588e-05 loss: 0.0939 (0.0919) time: 2.9425 data: 0.0077 max mem: 33302 +Epoch: [28] [2500/4276] eta: 1:48:04 lr: 1.6175138944766944e-05 loss: 0.0893 (0.0919) time: 2.9438 data: 0.0078 max mem: 33302 +Epoch: [28] [2510/4276] eta: 1:47:22 lr: 1.617215646659934e-05 loss: 0.0908 (0.0919) time: 2.9286 data: 0.0078 max mem: 33302 +Epoch: [28] [2520/4276] eta: 1:46:40 lr: 1.6169173927316008e-05 loss: 0.0832 (0.0919) time: 2.9246 data: 0.0080 max mem: 33302 +Epoch: [28] [2530/4276] eta: 1:45:59 lr: 1.6166191326903174e-05 loss: 0.0782 (0.0918) time: 2.9406 data: 0.0079 max mem: 33302 +Epoch: [28] [2540/4276] eta: 1:45:18 lr: 1.616320866534704e-05 loss: 0.0920 (0.0918) time: 2.9440 data: 0.0083 max mem: 33302 +Epoch: [28] [2550/4276] eta: 1:44:37 lr: 1.616022594263382e-05 loss: 0.0841 (0.0917) time: 2.9429 data: 0.0085 max mem: 33302 +Epoch: [28] [2560/4276] eta: 1:43:56 lr: 1.615724315874973e-05 loss: 0.0716 (0.0917) time: 2.9423 data: 0.0081 max mem: 33302 +Epoch: [28] [2570/4276] eta: 1:43:15 lr: 1.6154260313680945e-05 loss: 0.0736 (0.0917) time: 2.9434 data: 0.0079 max mem: 33302 +Epoch: [28] [2580/4276] eta: 1:42:34 lr: 1.615127740741367e-05 loss: 0.0781 (0.0916) time: 2.9441 data: 0.0081 max mem: 33302 +Epoch: [28] [2590/4276] eta: 1:41:53 lr: 1.6148294439934086e-05 loss: 0.0781 (0.0916) time: 2.9445 data: 0.0083 max mem: 33302 +Epoch: [28] [2600/4276] eta: 1:41:12 lr: 1.6145311411228387e-05 loss: 0.0785 (0.0916) time: 2.9321 data: 0.0078 max mem: 33302 +Epoch: [28] [2610/4276] eta: 1:40:32 lr: 1.6142328321282724e-05 loss: 0.0865 (0.0916) time: 2.9277 data: 0.0073 max mem: 33302 +Epoch: [28] [2620/4276] eta: 1:39:51 lr: 1.6139345170083277e-05 loss: 0.0937 (0.0916) time: 2.9407 data: 0.0079 max mem: 33302 +Epoch: [28] [2630/4276] eta: 1:39:11 lr: 1.613636195761621e-05 loss: 0.0803 (0.0915) time: 2.9440 data: 0.0082 max mem: 33302 +Epoch: [28] [2640/4276] eta: 1:38:31 lr: 1.613337868386768e-05 loss: 0.0764 (0.0915) time: 2.9430 data: 0.0080 max mem: 33302 +Epoch: [28] [2650/4276] eta: 1:37:50 lr: 1.6130395348823824e-05 loss: 0.0764 (0.0914) time: 2.9444 data: 0.0082 max mem: 33302 +Epoch: [28] [2660/4276] eta: 1:37:10 lr: 1.6127411952470793e-05 loss: 0.0806 (0.0914) time: 2.9445 data: 0.0084 max mem: 33302 +Epoch: [28] [2670/4276] eta: 1:36:30 lr: 1.612442849479473e-05 loss: 0.0899 (0.0915) time: 2.9443 data: 0.0084 max mem: 33302 +Epoch: [28] [2680/4276] eta: 1:35:50 lr: 1.6121444975781767e-05 loss: 0.0936 (0.0915) time: 2.9441 data: 0.0079 max mem: 33302 +Epoch: [28] [2690/4276] eta: 1:35:10 lr: 1.6118461395418017e-05 loss: 0.0838 (0.0915) time: 2.9329 data: 0.0082 max mem: 33302 +Epoch: [28] [2700/4276] eta: 1:34:30 lr: 1.611547775368961e-05 loss: 0.0770 (0.0914) time: 2.9067 data: 0.0086 max mem: 33302 +Epoch: [28] [2710/4276] eta: 1:33:50 lr: 1.611249405058266e-05 loss: 0.0782 (0.0914) time: 2.8897 data: 0.0084 max mem: 33302 +Epoch: [28] [2720/4276] eta: 1:33:10 lr: 1.6109510286083277e-05 loss: 0.0649 (0.0913) time: 2.8915 data: 0.0088 max mem: 33302 +Epoch: [28] [2730/4276] eta: 1:32:30 lr: 1.610652646017755e-05 loss: 0.0745 (0.0913) time: 2.8934 data: 0.0088 max mem: 33302 +Epoch: [28] [2740/4276] eta: 1:31:50 lr: 1.610354257285159e-05 loss: 0.0872 (0.0913) time: 2.9010 data: 0.0082 max mem: 33302 +Epoch: [28] [2750/4276] eta: 1:31:11 lr: 1.6100558624091478e-05 loss: 0.0914 (0.0914) time: 2.9079 data: 0.0085 max mem: 33302 +Epoch: [28] [2760/4276] eta: 1:30:31 lr: 1.6097574613883305e-05 loss: 0.0882 (0.0913) time: 2.9005 data: 0.0091 max mem: 33302 +Epoch: [28] [2770/4276] eta: 1:29:51 lr: 1.609459054221314e-05 loss: 0.0848 (0.0913) time: 2.8914 data: 0.0085 max mem: 33302 +Epoch: [28] [2780/4276] eta: 1:29:12 lr: 1.6091606409067057e-05 loss: 0.0888 (0.0913) time: 2.9021 data: 0.0085 max mem: 33302 +Epoch: [28] [2790/4276] eta: 1:28:33 lr: 1.6088622214431128e-05 loss: 0.0941 (0.0914) time: 2.9067 data: 0.0088 max mem: 33302 +Epoch: [28] [2800/4276] eta: 1:27:53 lr: 1.6085637958291415e-05 loss: 0.0839 (0.0913) time: 2.9021 data: 0.0084 max mem: 33302 +Epoch: [28] [2810/4276] eta: 1:27:14 lr: 1.6082653640633955e-05 loss: 0.0722 (0.0913) time: 2.9177 data: 0.0087 max mem: 33302 +Epoch: [28] [2820/4276] eta: 1:26:35 lr: 1.607966926144481e-05 loss: 0.0775 (0.0912) time: 2.9216 data: 0.0088 max mem: 33302 +Epoch: [28] [2830/4276] eta: 1:25:56 lr: 1.6076684820710014e-05 loss: 0.0846 (0.0913) time: 2.9085 data: 0.0090 max mem: 33302 +Epoch: [28] [2840/4276] eta: 1:25:17 lr: 1.6073700318415618e-05 loss: 0.0909 (0.0913) time: 2.9039 data: 0.0096 max mem: 33302 +Epoch: [28] [2850/4276] eta: 1:24:38 lr: 1.6070715754547628e-05 loss: 0.0909 (0.0913) time: 2.9185 data: 0.0090 max mem: 33302 +Epoch: [28] [2860/4276] eta: 1:24:00 lr: 1.606773112909208e-05 loss: 0.0738 (0.0913) time: 2.9412 data: 0.0078 max mem: 33302 +Epoch: [28] [2870/4276] eta: 1:23:21 lr: 1.6064746442034997e-05 loss: 0.0738 (0.0913) time: 2.9459 data: 0.0075 max mem: 33302 +Epoch: [28] [2880/4276] eta: 1:22:43 lr: 1.606176169336238e-05 loss: 0.0864 (0.0913) time: 2.9442 data: 0.0079 max mem: 33302 +Epoch: [28] [2890/4276] eta: 1:22:04 lr: 1.6058776883060237e-05 loss: 0.0963 (0.0913) time: 2.9446 data: 0.0077 max mem: 33302 +Epoch: [28] [2900/4276] eta: 1:21:26 lr: 1.6055792011114568e-05 loss: 0.0863 (0.0913) time: 2.9427 data: 0.0073 max mem: 33302 +Epoch: [28] [2910/4276] eta: 1:20:47 lr: 1.6052807077511374e-05 loss: 0.0870 (0.0913) time: 2.9448 data: 0.0073 max mem: 33302 +Epoch: [28] [2920/4276] eta: 1:20:09 lr: 1.604982208223663e-05 loss: 0.0910 (0.0913) time: 2.9423 data: 0.0074 max mem: 33302 +Epoch: [28] [2930/4276] eta: 1:19:30 lr: 1.604683702527632e-05 loss: 0.0851 (0.0913) time: 2.9177 data: 0.0077 max mem: 33302 +Epoch: [28] [2940/4276] eta: 1:18:52 lr: 1.604385190661642e-05 loss: 0.0870 (0.0913) time: 2.8979 data: 0.0081 max mem: 33302 +Epoch: [28] [2950/4276] eta: 1:18:14 lr: 1.6040866726242903e-05 loss: 0.0870 (0.0913) time: 2.9036 data: 0.0083 max mem: 33302 +Epoch: [28] [2960/4276] eta: 1:17:36 lr: 1.6037881484141724e-05 loss: 0.0869 (0.0913) time: 2.9181 data: 0.0087 max mem: 33302 +Epoch: [28] [2970/4276] eta: 1:16:57 lr: 1.6034896180298847e-05 loss: 0.0871 (0.0913) time: 2.9109 data: 0.0087 max mem: 33302 +Epoch: [28] [2980/4276] eta: 1:16:19 lr: 1.6031910814700218e-05 loss: 0.0938 (0.0913) time: 2.8993 data: 0.0082 max mem: 33302 +Epoch: [28] [2990/4276] eta: 1:15:41 lr: 1.602892538733179e-05 loss: 0.0868 (0.0913) time: 2.9188 data: 0.0084 max mem: 33302 +Epoch: [28] [3000/4276] eta: 1:15:04 lr: 1.6025939898179485e-05 loss: 0.0772 (0.0913) time: 2.9373 data: 0.0081 max mem: 33302 +Epoch: [28] [3010/4276] eta: 1:14:26 lr: 1.6022954347229244e-05 loss: 0.0772 (0.0913) time: 2.9415 data: 0.0078 max mem: 33302 +Epoch: [28] [3020/4276] eta: 1:13:48 lr: 1.6019968734466993e-05 loss: 0.0915 (0.0913) time: 2.9322 data: 0.0085 max mem: 33302 +Epoch: [28] [3030/4276] eta: 1:13:10 lr: 1.6016983059878663e-05 loss: 0.0913 (0.0913) time: 2.9067 data: 0.0083 max mem: 33302 +Epoch: [28] [3040/4276] eta: 1:12:32 lr: 1.6013997323450147e-05 loss: 0.1089 (0.0914) time: 2.8903 data: 0.0074 max mem: 33302 +Epoch: [28] [3050/4276] eta: 1:11:55 lr: 1.6011011525167366e-05 loss: 0.0983 (0.0914) time: 2.8884 data: 0.0072 max mem: 33302 +Epoch: [28] [3060/4276] eta: 1:11:17 lr: 1.6008025665016217e-05 loss: 0.0821 (0.0913) time: 2.8996 data: 0.0072 max mem: 33302 +Epoch: [28] [3070/4276] eta: 1:10:39 lr: 1.60050397429826e-05 loss: 0.0777 (0.0913) time: 2.9018 data: 0.0074 max mem: 33302 +Epoch: [28] [3080/4276] eta: 1:10:02 lr: 1.60020537590524e-05 loss: 0.0777 (0.0913) time: 2.8897 data: 0.0074 max mem: 33302 +Epoch: [28] [3090/4276] eta: 1:09:24 lr: 1.5999067713211496e-05 loss: 0.0773 (0.0912) time: 2.8903 data: 0.0074 max mem: 33302 +Epoch: [28] [3100/4276] eta: 1:08:47 lr: 1.5996081605445777e-05 loss: 0.0839 (0.0912) time: 2.9061 data: 0.0082 max mem: 33302 +Epoch: [28] [3110/4276] eta: 1:08:10 lr: 1.5993095435741108e-05 loss: 0.0790 (0.0912) time: 2.9163 data: 0.0086 max mem: 33302 +Epoch: [28] [3120/4276] eta: 1:07:32 lr: 1.599010920408335e-05 loss: 0.0790 (0.0912) time: 2.9260 data: 0.0086 max mem: 33302 +Epoch: [28] [3130/4276] eta: 1:06:55 lr: 1.598712291045836e-05 loss: 0.0874 (0.0911) time: 2.9347 data: 0.0091 max mem: 33302 +Epoch: [28] [3140/4276] eta: 1:06:18 lr: 1.5984136554852e-05 loss: 0.0812 (0.0911) time: 2.9111 data: 0.0088 max mem: 33302 +Epoch: [28] [3150/4276] eta: 1:05:41 lr: 1.598115013725011e-05 loss: 0.0828 (0.0911) time: 2.8901 data: 0.0081 max mem: 33302 +Epoch: [28] [3160/4276] eta: 1:05:04 lr: 1.5978163657638533e-05 loss: 0.0835 (0.0911) time: 2.8906 data: 0.0081 max mem: 33302 +Epoch: [28] [3170/4276] eta: 1:04:26 lr: 1.5975177116003096e-05 loss: 0.0845 (0.0912) time: 2.8914 data: 0.0081 max mem: 33302 +Epoch: [28] [3180/4276] eta: 1:03:49 lr: 1.597219051232964e-05 loss: 0.0815 (0.0911) time: 2.8897 data: 0.0079 max mem: 33302 +Epoch: [28] [3190/4276] eta: 1:03:12 lr: 1.596920384660397e-05 loss: 0.0808 (0.0912) time: 2.8887 data: 0.0078 max mem: 33302 +Epoch: [28] [3200/4276] eta: 1:02:35 lr: 1.5966217118811912e-05 loss: 0.0884 (0.0911) time: 2.8902 data: 0.0082 max mem: 33302 +Epoch: [28] [3210/4276] eta: 1:01:59 lr: 1.596323032893927e-05 loss: 0.0882 (0.0911) time: 2.9077 data: 0.0091 max mem: 33302 +Epoch: [28] [3220/4276] eta: 1:01:22 lr: 1.5960243476971857e-05 loss: 0.0882 (0.0912) time: 2.9151 data: 0.0093 max mem: 33302 +Epoch: [28] [3230/4276] eta: 1:00:45 lr: 1.5957256562895457e-05 loss: 0.0818 (0.0911) time: 2.9266 data: 0.0085 max mem: 33302 +Epoch: [28] [3240/4276] eta: 1:00:09 lr: 1.5954269586695862e-05 loss: 0.0896 (0.0912) time: 2.9432 data: 0.0076 max mem: 33302 +Epoch: [28] [3250/4276] eta: 0:59:32 lr: 1.5951282548358866e-05 loss: 0.1028 (0.0912) time: 2.9189 data: 0.0077 max mem: 33302 +Epoch: [28] [3260/4276] eta: 0:58:55 lr: 1.594829544787024e-05 loss: 0.0913 (0.0912) time: 2.8940 data: 0.0084 max mem: 33302 +Epoch: [28] [3270/4276] eta: 0:58:19 lr: 1.5945308285215756e-05 loss: 0.0914 (0.0912) time: 2.8926 data: 0.0084 max mem: 33302 +Epoch: [28] [3280/4276] eta: 0:57:42 lr: 1.594232106038118e-05 loss: 0.0921 (0.0912) time: 2.8926 data: 0.0083 max mem: 33302 +Epoch: [28] [3290/4276] eta: 0:57:06 lr: 1.593933377335227e-05 loss: 0.0890 (0.0912) time: 2.9006 data: 0.0082 max mem: 33302 +Epoch: [28] [3300/4276] eta: 0:56:29 lr: 1.5936346424114788e-05 loss: 0.0973 (0.0913) time: 2.9269 data: 0.0080 max mem: 33302 +Epoch: [28] [3310/4276] eta: 0:55:53 lr: 1.593335901265447e-05 loss: 0.1038 (0.0913) time: 2.9425 data: 0.0077 max mem: 33302 +Epoch: [28] [3320/4276] eta: 0:55:17 lr: 1.5930371538957062e-05 loss: 0.1064 (0.0913) time: 2.9411 data: 0.0076 max mem: 33302 +Epoch: [28] [3330/4276] eta: 0:54:41 lr: 1.5927384003008294e-05 loss: 0.0914 (0.0913) time: 2.9218 data: 0.0082 max mem: 33302 +Epoch: [28] [3340/4276] eta: 0:54:04 lr: 1.5924396404793907e-05 loss: 0.0843 (0.0913) time: 2.9223 data: 0.0083 max mem: 33302 +Epoch: [28] [3350/4276] eta: 0:53:28 lr: 1.5921408744299606e-05 loss: 0.0814 (0.0913) time: 2.9428 data: 0.0076 max mem: 33302 +Epoch: [28] [3360/4276] eta: 0:52:52 lr: 1.5918421021511114e-05 loss: 0.0817 (0.0913) time: 2.9424 data: 0.0074 max mem: 33302 +Epoch: [28] [3370/4276] eta: 0:52:16 lr: 1.5915433236414143e-05 loss: 0.0868 (0.0913) time: 2.9409 data: 0.0076 max mem: 33302 +Epoch: [28] [3380/4276] eta: 0:51:40 lr: 1.59124453889944e-05 loss: 0.0868 (0.0913) time: 2.9410 data: 0.0078 max mem: 33302 +Epoch: [28] [3390/4276] eta: 0:51:04 lr: 1.590945747923757e-05 loss: 0.0865 (0.0913) time: 2.9416 data: 0.0079 max mem: 33302 +Epoch: [28] [3400/4276] eta: 0:50:28 lr: 1.5906469507129352e-05 loss: 0.0910 (0.0913) time: 2.9432 data: 0.0074 max mem: 33302 +Epoch: [28] [3410/4276] eta: 0:49:52 lr: 1.5903481472655426e-05 loss: 0.0885 (0.0913) time: 2.9438 data: 0.0075 max mem: 33302 +Epoch: [28] [3420/4276] eta: 0:49:17 lr: 1.5900493375801477e-05 loss: 0.1016 (0.0914) time: 2.9434 data: 0.0077 max mem: 33302 +Epoch: [28] [3430/4276] eta: 0:48:41 lr: 1.589750521655317e-05 loss: 0.0965 (0.0914) time: 2.9449 data: 0.0077 max mem: 33302 +Epoch: [28] [3440/4276] eta: 0:48:05 lr: 1.589451699489617e-05 loss: 0.0798 (0.0914) time: 2.9441 data: 0.0076 max mem: 33302 +Epoch: [28] [3450/4276] eta: 0:47:29 lr: 1.5891528710816146e-05 loss: 0.1028 (0.0915) time: 2.9414 data: 0.0076 max mem: 33302 +Epoch: [28] [3460/4276] eta: 0:46:53 lr: 1.5888540364298745e-05 loss: 0.1057 (0.0915) time: 2.9304 data: 0.0077 max mem: 33302 +Epoch: [28] [3470/4276] eta: 0:46:18 lr: 1.5885551955329608e-05 loss: 0.0835 (0.0914) time: 2.9071 data: 0.0086 max mem: 33302 +Epoch: [28] [3480/4276] eta: 0:45:42 lr: 1.5882563483894383e-05 loss: 0.0804 (0.0914) time: 2.8948 data: 0.0094 max mem: 33302 +Epoch: [28] [3490/4276] eta: 0:45:06 lr: 1.5879574949978708e-05 loss: 0.0881 (0.0914) time: 2.8949 data: 0.0092 max mem: 33302 +Epoch: [28] [3500/4276] eta: 0:44:31 lr: 1.5876586353568196e-05 loss: 0.0767 (0.0914) time: 2.8934 data: 0.0089 max mem: 33302 +Epoch: [28] [3510/4276] eta: 0:43:55 lr: 1.5873597694648476e-05 loss: 0.0802 (0.0914) time: 2.8932 data: 0.0088 max mem: 33302 +Epoch: [28] [3520/4276] eta: 0:43:19 lr: 1.5870608973205168e-05 loss: 0.0795 (0.0914) time: 2.8936 data: 0.0089 max mem: 33302 +Epoch: [28] [3530/4276] eta: 0:42:44 lr: 1.586762018922388e-05 loss: 0.0810 (0.0914) time: 2.8923 data: 0.0090 max mem: 33302 +Epoch: [28] [3540/4276] eta: 0:42:08 lr: 1.586463134269021e-05 loss: 0.0898 (0.0914) time: 2.8945 data: 0.0091 max mem: 33302 +Epoch: [28] [3550/4276] eta: 0:41:33 lr: 1.586164243358975e-05 loss: 0.0845 (0.0914) time: 2.8975 data: 0.0092 max mem: 33302 +Epoch: [28] [3560/4276] eta: 0:40:58 lr: 1.5858653461908102e-05 loss: 0.0954 (0.0914) time: 2.9168 data: 0.0084 max mem: 33302 +Epoch: [28] [3570/4276] eta: 0:40:22 lr: 1.5855664427630844e-05 loss: 0.0984 (0.0914) time: 2.9383 data: 0.0074 max mem: 33302 +Epoch: [28] [3580/4276] eta: 0:39:47 lr: 1.5852675330743553e-05 loss: 0.0857 (0.0914) time: 2.9414 data: 0.0072 max mem: 33302 +Epoch: [28] [3590/4276] eta: 0:39:12 lr: 1.5849686171231793e-05 loss: 0.0814 (0.0914) time: 2.9414 data: 0.0072 max mem: 33302 +Epoch: [28] [3600/4276] eta: 0:38:37 lr: 1.584669694908114e-05 loss: 0.0848 (0.0914) time: 2.9392 data: 0.0073 max mem: 33302 +Epoch: [28] [3610/4276] eta: 0:38:01 lr: 1.584370766427715e-05 loss: 0.0862 (0.0914) time: 2.9407 data: 0.0073 max mem: 33302 +Epoch: [28] [3620/4276] eta: 0:37:26 lr: 1.5840718316805367e-05 loss: 0.0825 (0.0914) time: 2.9390 data: 0.0075 max mem: 33302 +Epoch: [28] [3630/4276] eta: 0:36:51 lr: 1.583772890665134e-05 loss: 0.0849 (0.0914) time: 2.9381 data: 0.0074 max mem: 33302 +Epoch: [28] [3640/4276] eta: 0:36:16 lr: 1.5834739433800612e-05 loss: 0.0831 (0.0914) time: 2.9425 data: 0.0072 max mem: 33302 +Epoch: [28] [3650/4276] eta: 0:35:41 lr: 1.5831749898238715e-05 loss: 0.0739 (0.0913) time: 2.9428 data: 0.0073 max mem: 33302 +Epoch: [28] [3660/4276] eta: 0:35:06 lr: 1.582876029995117e-05 loss: 0.0739 (0.0913) time: 2.9422 data: 0.0072 max mem: 33302 +Epoch: [28] [3670/4276] eta: 0:34:31 lr: 1.58257706389235e-05 loss: 0.0805 (0.0913) time: 2.9431 data: 0.0072 max mem: 33302 +Epoch: [28] [3680/4276] eta: 0:33:56 lr: 1.582278091514122e-05 loss: 0.0841 (0.0913) time: 2.9422 data: 0.0072 max mem: 33302 +Epoch: [28] [3690/4276] eta: 0:33:21 lr: 1.581979112858984e-05 loss: 0.0878 (0.0913) time: 2.9421 data: 0.0072 max mem: 33302 +Epoch: [28] [3700/4276] eta: 0:32:46 lr: 1.5816801279254854e-05 loss: 0.0878 (0.0913) time: 2.9430 data: 0.0072 max mem: 33302 +Epoch: [28] [3710/4276] eta: 0:32:11 lr: 1.5813811367121756e-05 loss: 0.0842 (0.0913) time: 2.9421 data: 0.0073 max mem: 33302 +Epoch: [28] [3720/4276] eta: 0:31:37 lr: 1.5810821392176036e-05 loss: 0.0924 (0.0913) time: 2.9467 data: 0.0072 max mem: 33302 +Epoch: [28] [3730/4276] eta: 0:31:02 lr: 1.5807831354403186e-05 loss: 0.0923 (0.0913) time: 2.9482 data: 0.0072 max mem: 33302 +Epoch: [28] [3740/4276] eta: 0:30:27 lr: 1.5804841253788666e-05 loss: 0.0843 (0.0913) time: 2.9431 data: 0.0073 max mem: 33302 +Epoch: [28] [3750/4276] eta: 0:29:52 lr: 1.580185109031795e-05 loss: 0.0958 (0.0913) time: 2.9415 data: 0.0073 max mem: 33302 +Epoch: [28] [3760/4276] eta: 0:29:17 lr: 1.5798860863976506e-05 loss: 0.0800 (0.0912) time: 2.9408 data: 0.0072 max mem: 33302 +Epoch: [28] [3770/4276] eta: 0:28:43 lr: 1.579587057474978e-05 loss: 0.0707 (0.0913) time: 2.9412 data: 0.0072 max mem: 33302 +Epoch: [28] [3780/4276] eta: 0:28:08 lr: 1.5792880222623228e-05 loss: 0.0858 (0.0912) time: 2.9414 data: 0.0072 max mem: 33302 +Epoch: [28] [3790/4276] eta: 0:27:33 lr: 1.578988980758229e-05 loss: 0.0739 (0.0912) time: 2.9406 data: 0.0072 max mem: 33302 +Epoch: [28] [3800/4276] eta: 0:26:59 lr: 1.578689932961241e-05 loss: 0.0782 (0.0912) time: 2.9406 data: 0.0072 max mem: 33302 +Epoch: [28] [3810/4276] eta: 0:26:24 lr: 1.5783908788699006e-05 loss: 0.0890 (0.0912) time: 2.9316 data: 0.0079 max mem: 33302 +Epoch: [28] [3820/4276] eta: 0:25:50 lr: 1.5780918184827508e-05 loss: 0.0821 (0.0912) time: 2.9073 data: 0.0092 max mem: 33302 +Epoch: [28] [3830/4276] eta: 0:25:15 lr: 1.5777927517983335e-05 loss: 0.0821 (0.0912) time: 2.9145 data: 0.0089 max mem: 33302 +Epoch: [28] [3840/4276] eta: 0:24:41 lr: 1.57749367881519e-05 loss: 0.0886 (0.0912) time: 2.9377 data: 0.0079 max mem: 33302 +Epoch: [28] [3850/4276] eta: 0:24:06 lr: 1.5771945995318598e-05 loss: 0.0787 (0.0912) time: 2.9422 data: 0.0079 max mem: 33302 +Epoch: [28] [3860/4276] eta: 0:23:32 lr: 1.5768955139468835e-05 loss: 0.0831 (0.0912) time: 2.9449 data: 0.0081 max mem: 33302 +Epoch: [28] [3870/4276] eta: 0:22:57 lr: 1.5765964220588e-05 loss: 0.0905 (0.0912) time: 2.9434 data: 0.0078 max mem: 33302 +Epoch: [28] [3880/4276] eta: 0:22:23 lr: 1.576297323866148e-05 loss: 0.0778 (0.0911) time: 2.9423 data: 0.0075 max mem: 33302 +Epoch: [28] [3890/4276] eta: 0:21:49 lr: 1.575998219367465e-05 loss: 0.0747 (0.0911) time: 2.9417 data: 0.0075 max mem: 33302 +Epoch: [28] [3900/4276] eta: 0:21:14 lr: 1.5756991085612887e-05 loss: 0.0802 (0.0911) time: 2.9425 data: 0.0077 max mem: 33302 +Epoch: [28] [3910/4276] eta: 0:20:40 lr: 1.5753999914461546e-05 loss: 0.0845 (0.0911) time: 2.9442 data: 0.0077 max mem: 33302 +Epoch: [28] [3920/4276] eta: 0:20:06 lr: 1.5751008680206004e-05 loss: 0.0786 (0.0911) time: 2.9451 data: 0.0077 max mem: 33302 +Epoch: [28] [3930/4276] eta: 0:19:31 lr: 1.5748017382831596e-05 loss: 0.0789 (0.0911) time: 2.9438 data: 0.0079 max mem: 33302 +Epoch: [28] [3940/4276] eta: 0:18:57 lr: 1.5745026022323676e-05 loss: 0.0875 (0.0911) time: 2.9432 data: 0.0079 max mem: 33302 +Epoch: [28] [3950/4276] eta: 0:18:23 lr: 1.5742034598667582e-05 loss: 0.0804 (0.0910) time: 2.9426 data: 0.0076 max mem: 33302 +Epoch: [28] [3960/4276] eta: 0:17:49 lr: 1.573904311184865e-05 loss: 0.0824 (0.0911) time: 2.9424 data: 0.0076 max mem: 33302 +Epoch: [28] [3970/4276] eta: 0:17:14 lr: 1.5736051561852207e-05 loss: 0.0985 (0.0911) time: 2.9432 data: 0.0076 max mem: 33302 +Epoch: [28] [3980/4276] eta: 0:16:40 lr: 1.5733059948663567e-05 loss: 0.1028 (0.0911) time: 2.9462 data: 0.0078 max mem: 33302 +Epoch: [28] [3990/4276] eta: 0:16:06 lr: 1.5730068272268047e-05 loss: 0.0896 (0.0911) time: 2.9408 data: 0.0079 max mem: 33302 +Epoch: [28] [4000/4276] eta: 0:15:32 lr: 1.572707653265096e-05 loss: 0.0770 (0.0911) time: 2.9159 data: 0.0082 max mem: 33302 +Epoch: [28] [4010/4276] eta: 0:14:58 lr: 1.5724084729797597e-05 loss: 0.0770 (0.0911) time: 2.9010 data: 0.0086 max mem: 33302 +Epoch: [28] [4020/4276] eta: 0:14:24 lr: 1.5721092863693258e-05 loss: 0.0843 (0.0911) time: 2.8989 data: 0.0083 max mem: 33302 +Epoch: [28] [4030/4276] eta: 0:13:50 lr: 1.5718100934323224e-05 loss: 0.0835 (0.0911) time: 2.8938 data: 0.0080 max mem: 33302 +Epoch: [28] [4040/4276] eta: 0:13:16 lr: 1.571510894167279e-05 loss: 0.0899 (0.0911) time: 2.8926 data: 0.0079 max mem: 33302 +Epoch: [28] [4050/4276] eta: 0:12:42 lr: 1.5712116885727213e-05 loss: 0.0887 (0.0911) time: 2.8920 data: 0.0075 max mem: 33302 +Epoch: [28] [4060/4276] eta: 0:12:08 lr: 1.570912476647177e-05 loss: 0.0723 (0.0911) time: 2.8936 data: 0.0074 max mem: 33302 +Epoch: [28] [4070/4276] eta: 0:11:34 lr: 1.5706132583891726e-05 loss: 0.0865 (0.0911) time: 2.8947 data: 0.0081 max mem: 33302 +Epoch: [28] [4080/4276] eta: 0:11:00 lr: 1.5703140337972327e-05 loss: 0.0938 (0.0911) time: 2.8963 data: 0.0087 max mem: 33302 +Epoch: [28] [4090/4276] eta: 0:10:26 lr: 1.5700148028698825e-05 loss: 0.0980 (0.0912) time: 2.9007 data: 0.0090 max mem: 33302 +Epoch: [28] [4100/4276] eta: 0:09:52 lr: 1.569715565605646e-05 loss: 0.1025 (0.0912) time: 2.8997 data: 0.0088 max mem: 33302 +Epoch: [28] [4110/4276] eta: 0:09:18 lr: 1.569416322003048e-05 loss: 0.0998 (0.0912) time: 2.8934 data: 0.0084 max mem: 33302 +Epoch: [28] [4120/4276] eta: 0:08:44 lr: 1.5691170720606095e-05 loss: 0.0986 (0.0912) time: 2.8923 data: 0.0087 max mem: 33302 +Epoch: [28] [4130/4276] eta: 0:08:11 lr: 1.5688178157768533e-05 loss: 0.0832 (0.0912) time: 2.8958 data: 0.0087 max mem: 33302 +Epoch: [28] [4140/4276] eta: 0:07:37 lr: 1.568518553150301e-05 loss: 0.0797 (0.0912) time: 2.8946 data: 0.0083 max mem: 33302 +Epoch: [28] [4150/4276] eta: 0:07:03 lr: 1.5682192841794745e-05 loss: 0.0853 (0.0912) time: 2.8918 data: 0.0085 max mem: 33302 +Epoch: [28] [4160/4276] eta: 0:06:29 lr: 1.5679200088628924e-05 loss: 0.0815 (0.0912) time: 2.8929 data: 0.0083 max mem: 33302 +Epoch: [28] [4170/4276] eta: 0:05:56 lr: 1.5676207271990746e-05 loss: 0.0908 (0.0913) time: 2.8943 data: 0.0082 max mem: 33302 +Epoch: [28] [4180/4276] eta: 0:05:22 lr: 1.567321439186541e-05 loss: 0.0983 (0.0913) time: 2.8927 data: 0.0084 max mem: 33302 +Epoch: [28] [4190/4276] eta: 0:04:48 lr: 1.5670221448238094e-05 loss: 0.0838 (0.0913) time: 2.8936 data: 0.0082 max mem: 33302 +Epoch: [28] [4200/4276] eta: 0:04:15 lr: 1.566722844109397e-05 loss: 0.1042 (0.0913) time: 2.8955 data: 0.0087 max mem: 33302 +Epoch: [28] [4210/4276] eta: 0:03:41 lr: 1.5664235370418208e-05 loss: 0.1030 (0.0913) time: 2.8955 data: 0.0089 max mem: 33302 +Epoch: [28] [4220/4276] eta: 0:03:07 lr: 1.566124223619597e-05 loss: 0.1044 (0.0914) time: 2.8941 data: 0.0088 max mem: 33302 +Epoch: [28] [4230/4276] eta: 0:02:34 lr: 1.565824903841242e-05 loss: 0.1066 (0.0914) time: 2.8918 data: 0.0087 max mem: 33302 +Epoch: [28] [4240/4276] eta: 0:02:00 lr: 1.56552557770527e-05 loss: 0.0975 (0.0914) time: 2.8907 data: 0.0083 max mem: 33302 +Epoch: [28] [4250/4276] eta: 0:01:27 lr: 1.5652262452101947e-05 loss: 0.0993 (0.0915) time: 2.8915 data: 0.0089 max mem: 33302 +Epoch: [28] [4260/4276] eta: 0:00:53 lr: 1.564926906354531e-05 loss: 0.0993 (0.0915) time: 2.8931 data: 0.0089 max mem: 33302 +Epoch: [28] [4270/4276] eta: 0:00:20 lr: 1.5646275611367915e-05 loss: 0.0926 (0.0915) time: 2.8878 data: 0.0080 max mem: 33302 +Epoch: [28] Total time: 3:58:34 +Test: [ 0/21770] eta: 13:22:19 time: 2.2113 data: 2.1720 max mem: 33302 +Test: [ 100/21770] eta: 0:21:40 time: 0.0387 data: 0.0008 max mem: 33302 +Test: [ 200/21770] eta: 0:17:40 time: 0.0384 data: 0.0008 max mem: 33302 +Test: [ 300/21770] eta: 0:16:17 time: 0.0384 data: 0.0008 max mem: 33302 +Test: [ 400/21770] eta: 0:15:33 time: 0.0380 data: 0.0008 max mem: 33302 +Test: [ 500/21770] eta: 0:15:05 time: 0.0382 data: 0.0008 max mem: 33302 +Test: [ 600/21770] eta: 0:14:46 time: 0.0387 data: 0.0008 max mem: 33302 +Test: [ 700/21770] eta: 0:14:32 time: 0.0385 data: 0.0008 max mem: 33302 +Test: [ 800/21770] eta: 0:14:19 time: 0.0383 data: 0.0008 max mem: 33302 +Test: [ 900/21770] eta: 0:14:09 time: 0.0381 data: 0.0008 max mem: 33302 +Test: [ 1000/21770] eta: 0:14:00 time: 0.0386 data: 0.0008 max mem: 33302 +Test: [ 1100/21770] eta: 0:13:51 time: 0.0380 data: 0.0009 max mem: 33302 +Test: [ 1200/21770] eta: 0:13:43 time: 0.0380 data: 0.0009 max mem: 33302 +Test: [ 1300/21770] eta: 0:13:36 time: 0.0383 data: 0.0009 max mem: 33302 +Test: [ 1400/21770] eta: 0:13:30 time: 0.0381 data: 0.0009 max mem: 33302 +Test: [ 1500/21770] eta: 0:13:23 time: 0.0382 data: 0.0009 max mem: 33302 +Test: [ 1600/21770] eta: 0:13:18 time: 0.0380 data: 0.0009 max mem: 33302 +Test: [ 1700/21770] eta: 0:13:12 time: 0.0383 data: 0.0009 max mem: 33302 +Test: [ 1800/21770] eta: 0:13:07 time: 0.0382 data: 0.0009 max mem: 33302 +Test: [ 1900/21770] eta: 0:13:02 time: 0.0383 data: 0.0009 max mem: 33302 +Test: [ 2000/21770] eta: 0:12:57 time: 0.0383 data: 0.0009 max mem: 33302 +Test: [ 2100/21770] eta: 0:12:52 time: 0.0382 data: 0.0008 max mem: 33302 +Test: [ 2200/21770] eta: 0:12:47 time: 0.0383 data: 0.0008 max mem: 33302 +Test: [ 2300/21770] eta: 0:12:42 time: 0.0380 data: 0.0008 max mem: 33302 +Test: [ 2400/21770] eta: 0:12:38 time: 0.0388 data: 0.0009 max mem: 33302 +Test: [ 2500/21770] eta: 0:12:34 time: 0.0387 data: 0.0009 max mem: 33302 +Test: [ 2600/21770] eta: 0:12:30 time: 0.0387 data: 0.0009 max mem: 33302 +Test: [ 2700/21770] eta: 0:12:25 time: 0.0385 data: 0.0009 max mem: 33302 +Test: [ 2800/21770] eta: 0:12:21 time: 0.0388 data: 0.0009 max mem: 33302 +Test: [ 2900/21770] eta: 0:12:17 time: 0.0388 data: 0.0009 max mem: 33302 +Test: [ 3000/21770] eta: 0:12:13 time: 0.0388 data: 0.0009 max mem: 33302 +Test: [ 3100/21770] eta: 0:12:09 time: 0.0386 data: 0.0009 max mem: 33302 +Test: [ 3200/21770] eta: 0:12:05 time: 0.0388 data: 0.0009 max mem: 33302 +Test: [ 3300/21770] eta: 0:12:01 time: 0.0388 data: 0.0009 max mem: 33302 +Test: [ 3400/21770] eta: 0:11:57 time: 0.0388 data: 0.0009 max mem: 33302 +Test: [ 3500/21770] eta: 0:11:53 time: 0.0387 data: 0.0009 max mem: 33302 +Test: [ 3600/21770] eta: 0:11:48 time: 0.0389 data: 0.0009 max mem: 33302 +Test: [ 3700/21770] eta: 0:11:44 time: 0.0386 data: 0.0009 max mem: 33302 +Test: [ 3800/21770] eta: 0:11:40 time: 0.0388 data: 0.0009 max mem: 33302 +Test: [ 3900/21770] eta: 0:11:36 time: 0.0388 data: 0.0009 max mem: 33302 +Test: [ 4000/21770] eta: 0:11:32 time: 0.0388 data: 0.0009 max mem: 33302 +Test: [ 4100/21770] eta: 0:11:28 time: 0.0386 data: 0.0009 max mem: 33302 +Test: [ 4200/21770] eta: 0:11:24 time: 0.0386 data: 0.0009 max mem: 33302 +Test: [ 4300/21770] eta: 0:11:20 time: 0.0384 data: 0.0009 max mem: 33302 +Test: [ 4400/21770] eta: 0:11:16 time: 0.0385 data: 0.0009 max mem: 33302 +Test: [ 4500/21770] eta: 0:11:12 time: 0.0382 data: 0.0009 max mem: 33302 +Test: [ 4600/21770] eta: 0:11:08 time: 0.0386 data: 0.0009 max mem: 33302 +Test: [ 4700/21770] eta: 0:11:04 time: 0.0381 data: 0.0009 max mem: 33302 +Test: [ 4800/21770] eta: 0:11:00 time: 0.0386 data: 0.0009 max mem: 33302 +Test: [ 4900/21770] eta: 0:10:56 time: 0.0383 data: 0.0009 max mem: 33302 +Test: [ 5000/21770] eta: 0:10:52 time: 0.0387 data: 0.0009 max mem: 33302 +Test: [ 5100/21770] eta: 0:10:48 time: 0.0386 data: 0.0009 max mem: 33302 +Test: [ 5200/21770] eta: 0:10:44 time: 0.0389 data: 0.0009 max mem: 33302 +Test: [ 5300/21770] eta: 0:10:40 time: 0.0383 data: 0.0009 max mem: 33302 +Test: [ 5400/21770] eta: 0:10:36 time: 0.0386 data: 0.0009 max mem: 33302 +Test: [ 5500/21770] eta: 0:10:32 time: 0.0383 data: 0.0009 max mem: 33302 +Test: [ 5600/21770] eta: 0:10:28 time: 0.0387 data: 0.0009 max mem: 33302 +Test: [ 5700/21770] eta: 0:10:24 time: 0.0383 data: 0.0009 max mem: 33302 +Test: [ 5800/21770] eta: 0:10:20 time: 0.0386 data: 0.0009 max mem: 33302 +Test: [ 5900/21770] eta: 0:10:16 time: 0.0382 data: 0.0009 max mem: 33302 +Test: [ 6000/21770] eta: 0:10:12 time: 0.0387 data: 0.0009 max mem: 33302 +Test: [ 6100/21770] eta: 0:10:08 time: 0.0383 data: 0.0009 max mem: 33302 +Test: [ 6200/21770] eta: 0:10:04 time: 0.0387 data: 0.0009 max mem: 33302 +Test: [ 6300/21770] eta: 0:10:00 time: 0.0382 data: 0.0009 max mem: 33302 +Test: [ 6400/21770] eta: 0:09:56 time: 0.0388 data: 0.0009 max mem: 33302 +Test: [ 6500/21770] eta: 0:09:52 time: 0.0383 data: 0.0009 max mem: 33302 +Test: [ 6600/21770] eta: 0:09:48 time: 0.0381 data: 0.0009 max mem: 33302 +Test: [ 6700/21770] eta: 0:09:44 time: 0.0380 data: 0.0009 max mem: 33302 +Test: [ 6800/21770] eta: 0:09:40 time: 0.0382 data: 0.0009 max mem: 33302 +Test: [ 6900/21770] eta: 0:09:36 time: 0.0381 data: 0.0009 max mem: 33302 +Test: [ 7000/21770] eta: 0:09:32 time: 0.0382 data: 0.0009 max mem: 33302 +Test: [ 7100/21770] eta: 0:09:28 time: 0.0380 data: 0.0009 max mem: 33302 +Test: [ 7200/21770] eta: 0:09:24 time: 0.0383 data: 0.0009 max mem: 33302 +Test: [ 7300/21770] eta: 0:09:20 time: 0.0382 data: 0.0009 max mem: 33302 +Test: [ 7400/21770] eta: 0:09:16 time: 0.0383 data: 0.0009 max mem: 33302 +Test: [ 7500/21770] eta: 0:09:12 time: 0.0381 data: 0.0009 max mem: 33302 +Test: [ 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time: 0.0378 data: 0.0009 max mem: 33302 +Test: [ 9000/21770] eta: 0:08:12 time: 0.0381 data: 0.0009 max mem: 33302 +Test: [ 9100/21770] eta: 0:08:09 time: 0.0381 data: 0.0009 max mem: 33302 +Test: [ 9200/21770] eta: 0:08:05 time: 0.0382 data: 0.0009 max mem: 33302 +Test: [ 9300/21770] eta: 0:08:01 time: 0.0379 data: 0.0009 max mem: 33302 +Test: [ 9400/21770] eta: 0:07:57 time: 0.0381 data: 0.0009 max mem: 33302 +Test: [ 9500/21770] eta: 0:07:53 time: 0.0384 data: 0.0009 max mem: 33302 +Test: [ 9600/21770] eta: 0:07:49 time: 0.0385 data: 0.0009 max mem: 33302 +Test: [ 9700/21770] eta: 0:07:45 time: 0.0384 data: 0.0009 max mem: 33302 +Test: [ 9800/21770] eta: 0:07:41 time: 0.0384 data: 0.0009 max mem: 33302 +Test: [ 9900/21770] eta: 0:07:37 time: 0.0383 data: 0.0009 max mem: 33302 +Test: [10000/21770] eta: 0:07:33 time: 0.0384 data: 0.0009 max mem: 33302 +Test: [10100/21770] eta: 0:07:30 time: 0.0387 data: 0.0009 max mem: 33302 +Test: [10200/21770] eta: 0:07:26 time: 0.0385 data: 0.0009 max mem: 33302 +Test: [10300/21770] eta: 0:07:22 time: 0.0385 data: 0.0009 max mem: 33302 +Test: [10400/21770] eta: 0:07:18 time: 0.0384 data: 0.0009 max mem: 33302 +Test: [10500/21770] eta: 0:07:14 time: 0.0383 data: 0.0009 max mem: 33302 +Test: [10600/21770] eta: 0:07:10 time: 0.0385 data: 0.0009 max mem: 33302 +Test: [10700/21770] eta: 0:07:06 time: 0.0383 data: 0.0009 max mem: 33302 +Test: [10800/21770] eta: 0:07:03 time: 0.0384 data: 0.0009 max mem: 33302 +Test: [10900/21770] eta: 0:06:59 time: 0.0382 data: 0.0009 max mem: 33302 +Test: [11000/21770] eta: 0:06:55 time: 0.0383 data: 0.0008 max mem: 33302 +Test: [11100/21770] eta: 0:06:51 time: 0.0385 data: 0.0009 max mem: 33302 +Test: [11200/21770] eta: 0:06:47 time: 0.0387 data: 0.0009 max mem: 33302 +Test: [11300/21770] eta: 0:06:43 time: 0.0385 data: 0.0009 max mem: 33302 +Test: [11400/21770] eta: 0:06:39 time: 0.0383 data: 0.0009 max mem: 33302 +Test: [11500/21770] eta: 0:06:35 time: 0.0385 data: 0.0009 max mem: 33302 +Test: 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0:05:41 time: 0.0383 data: 0.0009 max mem: 33302 +Test: [13000/21770] eta: 0:05:38 time: 0.0384 data: 0.0009 max mem: 33302 +Test: [13100/21770] eta: 0:05:34 time: 0.0386 data: 0.0009 max mem: 33302 +Test: [13200/21770] eta: 0:05:30 time: 0.0386 data: 0.0009 max mem: 33302 +Test: [13300/21770] eta: 0:05:26 time: 0.0386 data: 0.0009 max mem: 33302 +Test: [13400/21770] eta: 0:05:22 time: 0.0386 data: 0.0008 max mem: 33302 +Test: [13500/21770] eta: 0:05:18 time: 0.0390 data: 0.0009 max mem: 33302 +Test: [13600/21770] eta: 0:05:14 time: 0.0386 data: 0.0009 max mem: 33302 +Test: [13700/21770] eta: 0:05:11 time: 0.0390 data: 0.0009 max mem: 33302 +Test: [13800/21770] eta: 0:05:07 time: 0.0387 data: 0.0009 max mem: 33302 +Test: [13900/21770] eta: 0:05:03 time: 0.0388 data: 0.0009 max mem: 33302 +Test: [14000/21770] eta: 0:04:59 time: 0.0386 data: 0.0009 max mem: 33302 +Test: [14100/21770] eta: 0:04:55 time: 0.0388 data: 0.0009 max mem: 33302 +Test: [14200/21770] eta: 0:04:51 time: 0.0389 data: 0.0009 max mem: 33302 +Test: [14300/21770] eta: 0:04:48 time: 0.0390 data: 0.0009 max mem: 33302 +Test: [14400/21770] eta: 0:04:44 time: 0.0388 data: 0.0009 max mem: 33302 +Test: [14500/21770] eta: 0:04:40 time: 0.0389 data: 0.0009 max mem: 33302 +Test: [14600/21770] eta: 0:04:36 time: 0.0388 data: 0.0009 max mem: 33302 +Test: [14700/21770] eta: 0:04:32 time: 0.0389 data: 0.0009 max mem: 33302 +Test: [14800/21770] eta: 0:04:28 time: 0.0387 data: 0.0009 max mem: 33302 +Test: [14900/21770] eta: 0:04:24 time: 0.0390 data: 0.0009 max mem: 33302 +Test: [15000/21770] eta: 0:04:21 time: 0.0388 data: 0.0009 max mem: 33302 +Test: [15100/21770] eta: 0:04:17 time: 0.0390 data: 0.0009 max mem: 33302 +Test: [15200/21770] eta: 0:04:13 time: 0.0387 data: 0.0009 max mem: 33302 +Test: [15300/21770] eta: 0:04:09 time: 0.0389 data: 0.0009 max mem: 33302 +Test: [15400/21770] eta: 0:04:05 time: 0.0388 data: 0.0009 max mem: 33302 +Test: [15500/21770] eta: 0:04:01 time: 0.0390 data: 0.0009 max mem: 33302 +Test: [15600/21770] eta: 0:03:58 time: 0.0388 data: 0.0009 max mem: 33302 +Test: [15700/21770] eta: 0:03:54 time: 0.0396 data: 0.0009 max mem: 33302 +Test: [15800/21770] eta: 0:03:50 time: 0.0391 data: 0.0009 max mem: 33302 +Test: [15900/21770] eta: 0:03:46 time: 0.0394 data: 0.0008 max mem: 33302 +Test: [16000/21770] eta: 0:03:42 time: 0.0393 data: 0.0008 max mem: 33302 +Test: [16100/21770] eta: 0:03:38 time: 0.0392 data: 0.0009 max mem: 33302 +Test: [16200/21770] eta: 0:03:35 time: 0.0391 data: 0.0008 max mem: 33302 +Test: [16300/21770] eta: 0:03:31 time: 0.0390 data: 0.0008 max mem: 33302 +Test: [16400/21770] eta: 0:03:27 time: 0.0392 data: 0.0008 max mem: 33302 +Test: [16500/21770] eta: 0:03:23 time: 0.0388 data: 0.0008 max mem: 33302 +Test: [16600/21770] eta: 0:03:19 time: 0.0392 data: 0.0008 max mem: 33302 +Test: [16700/21770] eta: 0:03:15 time: 0.0389 data: 0.0008 max mem: 33302 +Test: [16800/21770] eta: 0:03:11 time: 0.0381 data: 0.0009 max mem: 33302 +Test: [16900/21770] eta: 0:03:08 time: 0.0381 data: 0.0009 max mem: 33302 +Test: [17000/21770] eta: 0:03:04 time: 0.0381 data: 0.0009 max mem: 33302 +Test: [17100/21770] eta: 0:03:00 time: 0.0381 data: 0.0009 max mem: 33302 +Test: [17200/21770] eta: 0:02:56 time: 0.0378 data: 0.0009 max mem: 33302 +Test: [17300/21770] eta: 0:02:52 time: 0.0379 data: 0.0009 max mem: 33302 +Test: [17400/21770] eta: 0:02:48 time: 0.0379 data: 0.0009 max mem: 33302 +Test: [17500/21770] eta: 0:02:44 time: 0.0378 data: 0.0009 max mem: 33302 +Test: [17600/21770] eta: 0:02:40 time: 0.0378 data: 0.0009 max mem: 33302 +Test: [17700/21770] eta: 0:02:37 time: 0.0379 data: 0.0009 max mem: 33302 +Test: [17800/21770] eta: 0:02:33 time: 0.0387 data: 0.0009 max mem: 33302 +Test: [17900/21770] eta: 0:02:29 time: 0.0387 data: 0.0009 max mem: 33302 +Test: [18000/21770] eta: 0:02:25 time: 0.0387 data: 0.0008 max mem: 33302 +Test: [18100/21770] eta: 0:02:21 time: 0.0388 data: 0.0009 max mem: 33302 +Test: [18200/21770] eta: 0:02:17 time: 0.0387 data: 0.0008 max mem: 33302 +Test: [18300/21770] eta: 0:02:13 time: 0.0388 data: 0.0009 max mem: 33302 +Test: [18400/21770] eta: 0:02:10 time: 0.0386 data: 0.0009 max mem: 33302 +Test: [18500/21770] eta: 0:02:06 time: 0.0387 data: 0.0009 max mem: 33302 +Test: [18600/21770] eta: 0:02:02 time: 0.0387 data: 0.0008 max mem: 33302 +Test: [18700/21770] eta: 0:01:58 time: 0.0388 data: 0.0008 max mem: 33302 +Test: [18800/21770] eta: 0:01:54 time: 0.0388 data: 0.0009 max mem: 33302 +Test: [18900/21770] eta: 0:01:50 time: 0.0391 data: 0.0008 max mem: 33302 +Test: [19000/21770] eta: 0:01:46 time: 0.0391 data: 0.0008 max mem: 33302 +Test: [19100/21770] eta: 0:01:43 time: 0.0389 data: 0.0008 max mem: 33302 +Test: [19200/21770] eta: 0:01:39 time: 0.0390 data: 0.0008 max mem: 33302 +Test: [19300/21770] eta: 0:01:35 time: 0.0391 data: 0.0008 max mem: 33302 +Test: [19400/21770] eta: 0:01:31 time: 0.0391 data: 0.0008 max mem: 33302 +Test: [19500/21770] eta: 0:01:27 time: 0.0390 data: 0.0008 max mem: 33302 +Test: [19600/21770] eta: 0:01:23 time: 0.0389 data: 0.0009 max mem: 33302 +Test: [19700/21770] eta: 0:01:19 time: 0.0387 data: 0.0009 max mem: 33302 +Test: [19800/21770] eta: 0:01:16 time: 0.0387 data: 0.0009 max mem: 33302 +Test: [19900/21770] eta: 0:01:12 time: 0.0388 data: 0.0009 max mem: 33302 +Test: [20000/21770] eta: 0:01:08 time: 0.0386 data: 0.0008 max mem: 33302 +Test: [20100/21770] eta: 0:01:04 time: 0.0389 data: 0.0008 max mem: 33302 +Test: [20200/21770] eta: 0:01:00 time: 0.0384 data: 0.0009 max mem: 33302 +Test: [20300/21770] eta: 0:00:56 time: 0.0385 data: 0.0009 max mem: 33302 +Test: [20400/21770] eta: 0:00:52 time: 0.0381 data: 0.0008 max mem: 33302 +Test: [20500/21770] eta: 0:00:49 time: 0.0385 data: 0.0009 max mem: 33302 +Test: [20600/21770] eta: 0:00:45 time: 0.0383 data: 0.0009 max mem: 33302 +Test: [20700/21770] eta: 0:00:41 time: 0.0381 data: 0.0009 max mem: 33302 +Test: [20800/21770] eta: 0:00:37 time: 0.0384 data: 0.0008 max mem: 33302 +Test: [20900/21770] eta: 0:00:33 time: 0.0382 data: 0.0009 max mem: 33302 +Test: [21000/21770] eta: 0:00:29 time: 0.0380 data: 0.0009 max mem: 33302 +Test: [21100/21770] eta: 0:00:25 time: 0.0382 data: 0.0009 max mem: 33302 +Test: [21200/21770] eta: 0:00:21 time: 0.0385 data: 0.0009 max mem: 33302 +Test: [21300/21770] eta: 0:00:18 time: 0.0384 data: 0.0009 max mem: 33302 +Test: [21400/21770] eta: 0:00:14 time: 0.0386 data: 0.0009 max mem: 33302 +Test: [21500/21770] eta: 0:00:10 time: 0.0385 data: 0.0009 max mem: 33302 +Test: [21600/21770] eta: 0:00:06 time: 0.0384 data: 0.0009 max mem: 33302 +Test: [21700/21770] eta: 0:00:02 time: 0.0385 data: 0.0009 max mem: 33302 +Test: Total time: 0:14:00 +Final results: +Mean IoU is 2.27 + + precision@0.5 = 0.05 + precision@0.6 = 0.00 + precision@0.7 = 0.00 + precision@0.8 = 0.00 + precision@0.9 = 0.00 + overall IoU = 2.26 + mean IoU = 2.27 + +Mean accuracy for one-to-zero sample is 0.00 + +Average object IoU 0.02268696492369037 +Overall IoU 2.263010025024414 +Epoch: [29] [ 0/4276] eta: 6:37:50 lr: 1.5644479509517323e-05 loss: 0.0641 (0.0641) time: 5.5825 data: 2.5154 max mem: 33302 +Epoch: [29] [ 10/4276] eta: 3:47:12 lr: 1.5641485955515762e-05 loss: 0.0805 (0.0842) time: 3.1956 data: 0.2364 max mem: 33302 +Epoch: [29] [ 20/4276] eta: 3:38:40 lr: 1.5638492337854742e-05 loss: 0.0835 (0.0917) time: 2.9579 data: 0.0080 max mem: 33302 +Epoch: [29] [ 30/4276] eta: 3:34:09 lr: 1.5635498656519375e-05 loss: 0.0850 (0.0916) time: 2.9331 data: 0.0074 max mem: 33302 +Epoch: [29] [ 40/4276] eta: 3:31:41 lr: 1.5632504911494768e-05 loss: 0.0868 (0.0908) time: 2.9096 data: 0.0081 max mem: 33302 +Epoch: [29] [ 50/4276] eta: 3:29:39 lr: 1.562951110276599e-05 loss: 0.0863 (0.0888) time: 2.8997 data: 0.0085 max mem: 33302 +Epoch: [29] [ 60/4276] eta: 3:28:13 lr: 1.5626517230318145e-05 loss: 0.0768 (0.0882) time: 2.8913 data: 0.0086 max mem: 33302 +Epoch: [29] [ 70/4276] eta: 3:27:07 lr: 1.5623523294136304e-05 loss: 0.0731 (0.0864) time: 2.8988 data: 0.0087 max mem: 33302 +Epoch: [29] [ 80/4276] eta: 3:26:05 lr: 1.562052929420555e-05 loss: 0.0803 (0.0869) time: 2.8976 data: 0.0089 max mem: 33302 +Epoch: [29] [ 90/4276] eta: 3:25:10 lr: 1.5617535230510933e-05 loss: 0.0837 (0.0871) time: 2.8916 data: 0.0089 max mem: 33302 +Epoch: [29] [ 100/4276] eta: 3:24:21 lr: 1.561454110303752e-05 loss: 0.0929 (0.0882) time: 2.8921 data: 0.0087 max mem: 33302 +Epoch: [29] [ 110/4276] eta: 3:23:35 lr: 1.561154691177036e-05 loss: 0.0996 (0.0898) time: 2.8929 data: 0.0087 max mem: 33302 +Epoch: [29] [ 120/4276] eta: 3:22:50 lr: 1.5608552656694507e-05 loss: 0.0955 (0.0903) time: 2.8893 data: 0.0086 max mem: 33302 +Epoch: [29] [ 130/4276] eta: 3:22:06 lr: 1.560555833779499e-05 loss: 0.0851 (0.0910) time: 2.8845 data: 0.0082 max mem: 33302 +Epoch: [29] [ 140/4276] eta: 3:21:29 lr: 1.560256395505685e-05 loss: 0.0806 (0.0910) time: 2.8899 data: 0.0084 max mem: 33302 +Epoch: [29] [ 150/4276] eta: 3:20:55 lr: 1.55995695084651e-05 loss: 0.0759 (0.0910) time: 2.9023 data: 0.0086 max mem: 33302 +Epoch: [29] [ 160/4276] eta: 3:20:19 lr: 1.5596574998004777e-05 loss: 0.0862 (0.0911) time: 2.8999 data: 0.0085 max mem: 33302 +Epoch: [29] [ 170/4276] eta: 3:19:43 lr: 1.5593580423660874e-05 loss: 0.0862 (0.0907) time: 2.8941 data: 0.0086 max mem: 33302 +Epoch: [29] [ 180/4276] eta: 3:19:10 lr: 1.55905857854184e-05 loss: 0.0769 (0.0904) time: 2.8965 data: 0.0089 max mem: 33302 +Epoch: [29] [ 190/4276] eta: 3:18:35 lr: 1.558759108326237e-05 loss: 0.0772 (0.0900) time: 2.8948 data: 0.0087 max mem: 33302 +Epoch: [29] [ 200/4276] eta: 3:18:00 lr: 1.5584596317177757e-05 loss: 0.0777 (0.0900) time: 2.8900 data: 0.0078 max mem: 33302 +Epoch: [29] [ 210/4276] eta: 3:17:26 lr: 1.5581601487149556e-05 loss: 0.0856 (0.0903) time: 2.8900 data: 0.0073 max mem: 33302 +Epoch: [29] [ 220/4276] eta: 3:16:54 lr: 1.5578606593162736e-05 loss: 0.0844 (0.0901) time: 2.8928 data: 0.0073 max mem: 33302 +Epoch: [29] [ 230/4276] eta: 3:16:23 lr: 1.5575611635202286e-05 loss: 0.0698 (0.0896) time: 2.8981 data: 0.0076 max mem: 33302 +Epoch: [29] [ 240/4276] eta: 3:15:52 lr: 1.5572616613253153e-05 loss: 0.0806 (0.0895) time: 2.9022 data: 0.0075 max mem: 33302 +Epoch: [29] [ 250/4276] eta: 3:15:20 lr: 1.5569621527300302e-05 loss: 0.0895 (0.0900) time: 2.8981 data: 0.0072 max mem: 33302 +Epoch: [29] [ 260/4276] eta: 3:14:51 lr: 1.5566626377328684e-05 loss: 0.0826 (0.0897) time: 2.9038 data: 0.0077 max mem: 33302 +Epoch: [29] [ 270/4276] eta: 3:14:19 lr: 1.556363116332325e-05 loss: 0.0733 (0.0895) time: 2.9017 data: 0.0082 max mem: 33302 +Epoch: [29] [ 280/4276] eta: 3:13:50 lr: 1.5560635885268926e-05 loss: 0.0733 (0.0892) time: 2.9001 data: 0.0085 max mem: 33302 +Epoch: [29] [ 290/4276] eta: 3:13:22 lr: 1.555764054315065e-05 loss: 0.0780 (0.0892) time: 2.9146 data: 0.0090 max mem: 33302 +Epoch: [29] [ 300/4276] eta: 3:12:56 lr: 1.5554645136953347e-05 loss: 0.0833 (0.0891) time: 2.9271 data: 0.0090 max mem: 33302 +Epoch: [29] [ 310/4276] eta: 3:12:31 lr: 1.5551649666661936e-05 loss: 0.0803 (0.0887) time: 2.9413 data: 0.0091 max mem: 33302 +Epoch: [29] [ 320/4276] eta: 3:12:07 lr: 1.554865413226132e-05 loss: 0.0805 (0.0888) time: 2.9474 data: 0.0090 max mem: 33302 +Epoch: [29] [ 330/4276] eta: 3:11:41 lr: 1.554565853373641e-05 loss: 0.0965 (0.0892) time: 2.9444 data: 0.0085 max mem: 33302 +Epoch: [29] [ 340/4276] eta: 3:11:15 lr: 1.55426628710721e-05 loss: 0.0915 (0.0891) time: 2.9419 data: 0.0081 max mem: 33302 +Epoch: [29] [ 350/4276] eta: 3:10:46 lr: 1.5539667144253288e-05 loss: 0.0799 (0.0893) time: 2.9289 data: 0.0082 max mem: 33302 +Epoch: [29] [ 360/4276] eta: 3:10:16 lr: 1.5536671353264846e-05 loss: 0.0934 (0.0899) time: 2.9146 data: 0.0087 max mem: 33302 +Epoch: [29] [ 370/4276] eta: 3:09:46 lr: 1.5533675498091655e-05 loss: 0.0938 (0.0898) time: 2.9082 data: 0.0092 max mem: 33302 +Epoch: [29] [ 380/4276] eta: 3:09:17 lr: 1.5530679578718584e-05 loss: 0.0824 (0.0900) time: 2.9088 data: 0.0095 max mem: 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data: 0.0072 max mem: 33302 +Epoch: [29] [ 470/4276] eta: 3:05:09 lr: 1.5503713412866665e-05 loss: 0.0671 (0.0905) time: 2.9395 data: 0.0072 max mem: 33302 +Epoch: [29] [ 480/4276] eta: 3:04:39 lr: 1.550071685066117e-05 loss: 0.0740 (0.0903) time: 2.9216 data: 0.0075 max mem: 33302 +Epoch: [29] [ 490/4276] eta: 3:04:10 lr: 1.549772022408892e-05 loss: 0.0740 (0.0900) time: 2.9111 data: 0.0082 max mem: 33302 +Epoch: [29] [ 500/4276] eta: 3:03:42 lr: 1.5494723533134703e-05 loss: 0.0797 (0.0899) time: 2.9284 data: 0.0082 max mem: 33302 +Epoch: [29] [ 510/4276] eta: 3:03:14 lr: 1.549172677778329e-05 loss: 0.0830 (0.0899) time: 2.9378 data: 0.0084 max mem: 33302 +Epoch: [29] [ 520/4276] eta: 3:02:43 lr: 1.5488729958019467e-05 loss: 0.0942 (0.0899) time: 2.9149 data: 0.0084 max mem: 33302 +Epoch: [29] [ 530/4276] eta: 3:02:16 lr: 1.548573307382799e-05 loss: 0.0887 (0.0900) time: 2.9210 data: 0.0085 max mem: 33302 +Epoch: [29] [ 540/4276] eta: 3:01:49 lr: 1.5482736125193636e-05 loss: 0.0880 (0.0900) time: 2.9463 data: 0.0087 max mem: 33302 +Epoch: [29] [ 550/4276] eta: 3:01:21 lr: 1.5479739112101145e-05 loss: 0.0899 (0.0901) time: 2.9450 data: 0.0085 max mem: 33302 +Epoch: [29] [ 560/4276] eta: 3:00:52 lr: 1.5476742034535267e-05 loss: 0.0899 (0.0902) time: 2.9336 data: 0.0088 max mem: 33302 +Epoch: [29] [ 570/4276] eta: 3:00:21 lr: 1.547374489248074e-05 loss: 0.0897 (0.0902) time: 2.9087 data: 0.0083 max mem: 33302 +Epoch: [29] [ 580/4276] eta: 2:59:50 lr: 1.547074768592231e-05 loss: 0.0899 (0.0902) time: 2.8943 data: 0.0079 max mem: 33302 +Epoch: [29] [ 590/4276] eta: 2:59:19 lr: 1.5467750414844684e-05 loss: 0.0779 (0.0900) time: 2.8925 data: 0.0081 max mem: 33302 +Epoch: [29] [ 600/4276] eta: 2:58:48 lr: 1.546475307923259e-05 loss: 0.0779 (0.0899) time: 2.8911 data: 0.0079 max mem: 33302 +Epoch: [29] [ 610/4276] eta: 2:58:20 lr: 1.5461755679070744e-05 loss: 0.0827 (0.0899) time: 2.9112 data: 0.0083 max mem: 33302 +Epoch: [29] [ 620/4276] eta: 2:57:53 lr: 1.545875821434385e-05 loss: 0.0829 (0.0898) time: 2.9412 data: 0.0091 max mem: 33302 +Epoch: [29] [ 630/4276] eta: 2:57:25 lr: 1.5455760685036598e-05 loss: 0.0892 (0.0900) time: 2.9496 data: 0.0092 max mem: 33302 +Epoch: [29] [ 640/4276] eta: 2:56:58 lr: 1.5452763091133685e-05 loss: 0.0892 (0.0902) time: 2.9533 data: 0.0093 max mem: 33302 +Epoch: [29] [ 650/4276] eta: 2:56:30 lr: 1.5449765432619798e-05 loss: 0.0802 (0.0901) time: 2.9494 data: 0.0095 max mem: 33302 +Epoch: [29] [ 660/4276] eta: 2:56:02 lr: 1.5446767709479617e-05 loss: 0.0986 (0.0904) time: 2.9380 data: 0.0094 max mem: 33302 +Epoch: [29] [ 670/4276] eta: 2:55:34 lr: 1.5443769921697802e-05 loss: 0.0913 (0.0903) time: 2.9407 data: 0.0090 max mem: 33302 +Epoch: [29] [ 680/4276] eta: 2:55:06 lr: 1.5440772069259024e-05 loss: 0.0844 (0.0902) time: 2.9481 data: 0.0085 max mem: 33302 +Epoch: [29] [ 690/4276] eta: 2:54:38 lr: 1.543777415214794e-05 loss: 0.0864 (0.0901) time: 2.9461 data: 0.0082 max mem: 33302 +Epoch: [29] [ 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33302 +Epoch: [29] [ 780/4276] eta: 2:50:12 lr: 1.541078998535929e-05 loss: 0.0822 (0.0898) time: 2.9061 data: 0.0086 max mem: 33302 +Epoch: [29] [ 790/4276] eta: 2:49:42 lr: 1.5407791420679724e-05 loss: 0.0793 (0.0899) time: 2.9114 data: 0.0087 max mem: 33302 +Epoch: [29] [ 800/4276] eta: 2:49:12 lr: 1.540479279115862e-05 loss: 0.0872 (0.0900) time: 2.9041 data: 0.0082 max mem: 33302 +Epoch: [29] [ 810/4276] eta: 2:48:41 lr: 1.5401794096780544e-05 loss: 0.0879 (0.0900) time: 2.8952 data: 0.0077 max mem: 33302 +Epoch: [29] [ 820/4276] eta: 2:48:11 lr: 1.5398795337530065e-05 loss: 0.0842 (0.0899) time: 2.8927 data: 0.0080 max mem: 33302 +Epoch: [29] [ 830/4276] eta: 2:47:41 lr: 1.5395796513391743e-05 loss: 0.0851 (0.0899) time: 2.8922 data: 0.0081 max mem: 33302 +Epoch: [29] [ 840/4276] eta: 2:47:10 lr: 1.5392797624350125e-05 loss: 0.0891 (0.0899) time: 2.8928 data: 0.0080 max mem: 33302 +Epoch: [29] [ 850/4276] eta: 2:46:40 lr: 1.5389798670389767e-05 loss: 0.0823 (0.0899) time: 2.8945 data: 0.0077 max mem: 33302 +Epoch: [29] [ 860/4276] eta: 2:46:10 lr: 1.5386799651495192e-05 loss: 0.0840 (0.0902) time: 2.8971 data: 0.0081 max mem: 33302 +Epoch: [29] [ 870/4276] eta: 2:45:42 lr: 1.5383800567650944e-05 loss: 0.0870 (0.0902) time: 2.9279 data: 0.0089 max mem: 33302 +Epoch: [29] [ 880/4276] eta: 2:45:14 lr: 1.5380801418841536e-05 loss: 0.0844 (0.0905) time: 2.9523 data: 0.0094 max mem: 33302 +Epoch: [29] [ 890/4276] eta: 2:44:46 lr: 1.53778022050515e-05 loss: 0.0917 (0.0905) time: 2.9470 data: 0.0094 max mem: 33302 +Epoch: [29] [ 900/4276] eta: 2:44:18 lr: 1.537480292626533e-05 loss: 0.0917 (0.0905) time: 2.9457 data: 0.0089 max mem: 33302 +Epoch: [29] [ 910/4276] eta: 2:43:50 lr: 1.5371803582467535e-05 loss: 0.0905 (0.0905) time: 2.9429 data: 0.0087 max mem: 33302 +Epoch: [29] [ 920/4276] eta: 2:43:21 lr: 1.536880417364261e-05 loss: 0.0893 (0.0905) time: 2.9424 data: 0.0089 max mem: 33302 +Epoch: [29] [ 930/4276] eta: 2:42:53 lr: 1.536580469977505e-05 loss: 0.0835 (0.0906) time: 2.9432 data: 0.0088 max mem: 33302 +Epoch: [29] [ 940/4276] eta: 2:42:24 lr: 1.5362805160849326e-05 loss: 0.0908 (0.0905) time: 2.9428 data: 0.0085 max mem: 33302 +Epoch: [29] [ 950/4276] eta: 2:41:56 lr: 1.5359805556849914e-05 loss: 0.0915 (0.0906) time: 2.9430 data: 0.0085 max mem: 33302 +Epoch: [29] [ 960/4276] eta: 2:41:27 lr: 1.535680588776129e-05 loss: 0.0919 (0.0906) time: 2.9417 data: 0.0087 max mem: 33302 +Epoch: [29] [ 970/4276] eta: 2:40:59 lr: 1.5353806153567912e-05 loss: 0.0919 (0.0907) time: 2.9414 data: 0.0087 max mem: 33302 +Epoch: [29] [ 980/4276] eta: 2:40:30 lr: 1.5350806354254226e-05 loss: 0.0923 (0.0906) time: 2.9415 data: 0.0085 max mem: 33302 +Epoch: [29] [ 990/4276] eta: 2:40:00 lr: 1.5347806489804685e-05 loss: 0.0784 (0.0905) time: 2.9212 data: 0.0082 max mem: 33302 +Epoch: [29] [1000/4276] eta: 2:39:32 lr: 1.534480656020372e-05 loss: 0.0775 (0.0904) time: 2.9222 data: 0.0085 max mem: 33302 +Epoch: [29] [1010/4276] eta: 2:39:03 lr: 1.534180656543578e-05 loss: 0.0812 (0.0904) time: 2.9428 data: 0.0085 max mem: 33302 +Epoch: [29] [1020/4276] eta: 2:38:35 lr: 1.533880650548527e-05 loss: 0.0878 (0.0904) time: 2.9447 data: 0.0082 max mem: 33302 +Epoch: [29] [1030/4276] eta: 2:38:06 lr: 1.5335806380336617e-05 loss: 0.0909 (0.0906) time: 2.9466 data: 0.0079 max mem: 33302 +Epoch: [29] [1040/4276] eta: 2:37:37 lr: 1.533280618997423e-05 loss: 0.0848 (0.0905) time: 2.9396 data: 0.0076 max mem: 33302 +Epoch: [29] [1050/4276] eta: 2:37:09 lr: 1.5329805934382523e-05 loss: 0.0834 (0.0906) time: 2.9390 data: 0.0074 max mem: 33302 +Epoch: [29] [1060/4276] eta: 2:36:40 lr: 1.5326805613545873e-05 loss: 0.1020 (0.0908) time: 2.9326 data: 0.0077 max mem: 33302 +Epoch: [29] [1070/4276] eta: 2:36:10 lr: 1.5323805227448683e-05 loss: 0.1020 (0.0909) time: 2.9184 data: 0.0082 max mem: 33302 +Epoch: [29] [1080/4276] eta: 2:35:41 lr: 1.5320804776075335e-05 loss: 0.0968 (0.0909) time: 2.9294 data: 0.0079 max mem: 33302 +Epoch: [29] [1090/4276] eta: 2:35:13 lr: 1.5317804259410198e-05 loss: 0.0968 (0.0910) time: 2.9405 data: 0.0072 max mem: 33302 +Epoch: [29] [1100/4276] eta: 2:34:44 lr: 1.5314803677437638e-05 loss: 0.0988 (0.0911) time: 2.9409 data: 0.0071 max mem: 33302 +Epoch: [29] [1110/4276] eta: 2:34:15 lr: 1.5311803030142026e-05 loss: 0.1041 (0.0912) time: 2.9408 data: 0.0071 max mem: 33302 +Epoch: [29] [1120/4276] eta: 2:33:47 lr: 1.530880231750771e-05 loss: 0.1012 (0.0912) time: 2.9401 data: 0.0073 max mem: 33302 +Epoch: [29] [1130/4276] eta: 2:33:18 lr: 1.5305801539519033e-05 loss: 0.0796 (0.0911) time: 2.9405 data: 0.0078 max mem: 33302 +Epoch: [29] [1140/4276] eta: 2:32:49 lr: 1.530280069616034e-05 loss: 0.0817 (0.0912) time: 2.9402 data: 0.0077 max mem: 33302 +Epoch: [29] [1150/4276] eta: 2:32:20 lr: 1.5299799787415956e-05 loss: 0.0882 (0.0912) time: 2.9407 data: 0.0079 max mem: 33302 +Epoch: [29] [1160/4276] eta: 2:31:51 lr: 1.5296798813270218e-05 loss: 0.0874 (0.0912) time: 2.9407 data: 0.0082 max mem: 33302 +Epoch: [29] [1170/4276] eta: 2:31:23 lr: 1.529379777370743e-05 loss: 0.0874 (0.0912) time: 2.9435 data: 0.0079 max mem: 33302 +Epoch: [29] [1180/4276] eta: 2:30:54 lr: 1.529079666871191e-05 loss: 0.0857 (0.0912) time: 2.9422 data: 0.0078 max mem: 33302 +Epoch: [29] [1190/4276] eta: 2:30:25 lr: 1.528779549826796e-05 loss: 0.0801 (0.0911) time: 2.9372 data: 0.0080 max mem: 33302 +Epoch: [29] [1200/4276] eta: 2:29:56 lr: 1.528479426235988e-05 loss: 0.0775 (0.0911) time: 2.9398 data: 0.0083 max mem: 33302 +Epoch: [29] [1210/4276] eta: 2:29:27 lr: 1.528179296097195e-05 loss: 0.0782 (0.0910) time: 2.9403 data: 0.0081 max mem: 33302 +Epoch: [29] [1220/4276] eta: 2:28:58 lr: 1.5278791594088464e-05 loss: 0.0801 (0.0910) time: 2.9393 data: 0.0079 max mem: 33302 +Epoch: [29] [1230/4276] eta: 2:28:29 lr: 1.5275790161693683e-05 loss: 0.0938 (0.0910) time: 2.9396 data: 0.0080 max mem: 33302 +Epoch: [29] [1240/4276] eta: 2:28:01 lr: 1.5272788663771888e-05 loss: 0.0863 (0.0911) time: 2.9397 data: 0.0083 max mem: 33302 +Epoch: [29] [1250/4276] eta: 2:27:32 lr: 1.5269787100307327e-05 loss: 0.0853 (0.0911) time: 2.9374 data: 0.0083 max mem: 33302 +Epoch: [29] [1260/4276] eta: 2:27:03 lr: 1.5266785471284263e-05 loss: 0.0790 (0.0910) time: 2.9386 data: 0.0079 max mem: 33302 +Epoch: [29] [1270/4276] eta: 2:26:34 lr: 1.526378377668693e-05 loss: 0.0783 (0.0909) time: 2.9415 data: 0.0079 max mem: 33302 +Epoch: [29] [1280/4276] eta: 2:26:04 lr: 1.5260782016499584e-05 loss: 0.0867 (0.0909) time: 2.9312 data: 0.0079 max mem: 33302 +Epoch: [29] [1290/4276] eta: 2:25:35 lr: 1.525778019070644e-05 loss: 0.0920 (0.0909) time: 2.9155 data: 0.0080 max mem: 33302 +Epoch: [29] [1300/4276] eta: 2:25:06 lr: 1.5254778299291724e-05 loss: 0.0728 (0.0908) time: 2.9283 data: 0.0088 max mem: 33302 +Epoch: [29] [1310/4276] eta: 2:24:37 lr: 1.5251776342239662e-05 loss: 0.0732 (0.0908) time: 2.9397 data: 0.0092 max mem: 33302 +Epoch: [29] [1320/4276] eta: 2:24:08 lr: 1.5248774319534461e-05 loss: 0.0845 (0.0909) time: 2.9344 data: 0.0081 max mem: 33302 +Epoch: [29] [1330/4276] eta: 2:23:39 lr: 1.5245772231160315e-05 loss: 0.0903 (0.0908) time: 2.9372 data: 0.0073 max mem: 33302 +Epoch: [29] [1340/4276] eta: 2:23:10 lr: 1.5242770077101425e-05 loss: 0.0843 (0.0908) time: 2.9375 data: 0.0073 max mem: 33302 +Epoch: [29] [1350/4276] eta: 2:22:41 lr: 1.523976785734198e-05 loss: 0.0903 (0.0909) time: 2.9355 data: 0.0072 max mem: 33302 +Epoch: [29] [1360/4276] eta: 2:22:12 lr: 1.5236765571866163e-05 loss: 0.0944 (0.0909) time: 2.9351 data: 0.0072 max mem: 33302 +Epoch: [29] [1370/4276] eta: 2:21:43 lr: 1.5233763220658138e-05 loss: 0.0799 (0.0909) time: 2.9391 data: 0.0072 max mem: 33302 +Epoch: [29] [1380/4276] eta: 2:21:14 lr: 1.5230760803702076e-05 loss: 0.0868 (0.0909) time: 2.9387 data: 0.0072 max mem: 33302 +Epoch: [29] [1390/4276] eta: 2:20:45 lr: 1.5227758320982141e-05 loss: 0.0997 (0.0910) time: 2.9360 data: 0.0074 max mem: 33302 +Epoch: [29] [1400/4276] eta: 2:20:16 lr: 1.5224755772482475e-05 loss: 0.0984 (0.0910) time: 2.9434 data: 0.0076 max mem: 33302 +Epoch: [29] [1410/4276] eta: 2:19:47 lr: 1.5221753158187223e-05 loss: 0.0930 (0.0910) time: 2.9450 data: 0.0080 max mem: 33302 +Epoch: [29] [1420/4276] eta: 2:19:18 lr: 1.5218750478080526e-05 loss: 0.0807 (0.0910) time: 2.9385 data: 0.0082 max mem: 33302 +Epoch: [29] [1430/4276] eta: 2:18:49 lr: 1.521574773214652e-05 loss: 0.0792 (0.0910) time: 2.9359 data: 0.0076 max mem: 33302 +Epoch: [29] [1440/4276] eta: 2:18:20 lr: 1.5212744920369312e-05 loss: 0.0813 (0.0909) time: 2.9351 data: 0.0074 max mem: 33302 +Epoch: [29] [1450/4276] eta: 2:17:51 lr: 1.5209742042733025e-05 loss: 0.0867 (0.0909) time: 2.9383 data: 0.0078 max mem: 33302 +Epoch: [29] [1460/4276] eta: 2:17:22 lr: 1.5206739099221768e-05 loss: 0.0854 (0.0909) time: 2.9402 data: 0.0078 max mem: 33302 +Epoch: [29] [1470/4276] eta: 2:16:52 lr: 1.5203736089819643e-05 loss: 0.0854 (0.0909) time: 2.9221 data: 0.0081 max mem: 33302 +Epoch: [29] [1480/4276] eta: 2:16:23 lr: 1.5200733014510732e-05 loss: 0.0923 (0.0909) time: 2.9144 data: 0.0088 max mem: 33302 +Epoch: [29] [1490/4276] eta: 2:15:53 lr: 1.5197729873279128e-05 loss: 0.0833 (0.0908) time: 2.9222 data: 0.0088 max mem: 33302 +Epoch: [29] [1500/4276] eta: 2:15:24 lr: 1.519472666610891e-05 loss: 0.0784 (0.0908) time: 2.9310 data: 0.0085 max mem: 33302 +Epoch: [29] [1510/4276] eta: 2:14:55 lr: 1.5191723392984156e-05 loss: 0.0812 (0.0908) time: 2.9396 data: 0.0078 max mem: 33302 +Epoch: [29] [1520/4276] eta: 2:14:26 lr: 1.518872005388891e-05 loss: 0.0812 (0.0908) time: 2.9363 data: 0.0071 max mem: 33302 +Epoch: [29] [1530/4276] eta: 2:13:57 lr: 1.5185716648807244e-05 loss: 0.0797 (0.0907) time: 2.9343 data: 0.0071 max mem: 33302 +Epoch: [29] [1540/4276] eta: 2:13:28 lr: 1.5182713177723201e-05 loss: 0.0799 (0.0907) time: 2.9355 data: 0.0071 max mem: 33302 +Epoch: [29] [1550/4276] eta: 2:12:59 lr: 1.517970964062083e-05 loss: 0.0806 (0.0907) time: 2.9407 data: 0.0071 max mem: 33302 +Epoch: [29] [1560/4276] eta: 2:12:30 lr: 1.517670603748415e-05 loss: 0.0781 (0.0907) time: 2.9411 data: 0.0071 max mem: 33302 +Epoch: [29] [1570/4276] eta: 2:12:01 lr: 1.5173702368297199e-05 loss: 0.0851 (0.0907) time: 2.9392 data: 0.0072 max mem: 33302 +Epoch: [29] [1580/4276] eta: 2:11:32 lr: 1.5170698633043995e-05 loss: 0.0796 (0.0906) time: 2.9412 data: 0.0071 max mem: 33302 +Epoch: [29] [1590/4276] eta: 2:11:03 lr: 1.5167694831708553e-05 loss: 0.0796 (0.0906) time: 2.9403 data: 0.0071 max mem: 33302 +Epoch: [29] [1600/4276] eta: 2:10:34 lr: 1.5164690964274867e-05 loss: 0.0823 (0.0906) time: 2.9391 data: 0.0071 max mem: 33302 +Epoch: [29] [1610/4276] eta: 2:10:05 lr: 1.5161687030726942e-05 loss: 0.0892 (0.0906) time: 2.9401 data: 0.0072 max mem: 33302 +Epoch: [29] [1620/4276] eta: 2:09:36 lr: 1.5158683031048765e-05 loss: 0.0876 (0.0906) time: 2.9404 data: 0.0071 max mem: 33302 +Epoch: [29] [1630/4276] eta: 2:09:06 lr: 1.5155678965224326e-05 loss: 0.0876 (0.0906) time: 2.9400 data: 0.0071 max mem: 33302 +Epoch: [29] [1640/4276] eta: 2:08:37 lr: 1.5152674833237588e-05 loss: 0.0880 (0.0906) time: 2.9383 data: 0.0072 max mem: 33302 +Epoch: [29] [1650/4276] eta: 2:08:08 lr: 1.5149670635072525e-05 loss: 0.0735 (0.0905) time: 2.9372 data: 0.0072 max mem: 33302 +Epoch: [29] [1660/4276] eta: 2:07:39 lr: 1.5146666370713094e-05 loss: 0.0798 (0.0905) time: 2.9464 data: 0.0072 max mem: 33302 +Epoch: [29] [1670/4276] eta: 2:07:10 lr: 1.5143662040143256e-05 loss: 0.0826 (0.0905) time: 2.9500 data: 0.0072 max mem: 33302 +Epoch: [29] [1680/4276] eta: 2:06:41 lr: 1.5140657643346944e-05 loss: 0.0801 (0.0905) time: 2.9396 data: 0.0077 max mem: 33302 +Epoch: [29] [1690/4276] eta: 2:06:12 lr: 1.5137653180308106e-05 loss: 0.0798 (0.0905) time: 2.9295 data: 0.0080 max mem: 33302 +Epoch: [29] [1700/4276] eta: 2:05:42 lr: 1.5134648651010672e-05 loss: 0.0881 (0.0905) time: 2.9203 data: 0.0083 max mem: 33302 +Epoch: [29] [1710/4276] eta: 2:05:13 lr: 1.5131644055438553e-05 loss: 0.0881 (0.0905) time: 2.9362 data: 0.0081 max mem: 33302 +Epoch: [29] [1720/4276] eta: 2:04:45 lr: 1.5128639393575678e-05 loss: 0.0873 (0.0905) time: 2.9525 data: 0.0073 max mem: 33302 +Epoch: [29] [1730/4276] eta: 2:04:16 lr: 1.5125634665405947e-05 loss: 0.0847 (0.0905) time: 2.9488 data: 0.0075 max mem: 33302 +Epoch: [29] [1740/4276] eta: 2:03:47 lr: 1.5122629870913272e-05 loss: 0.0836 (0.0905) time: 2.9480 data: 0.0075 max mem: 33302 +Epoch: [29] [1750/4276] eta: 2:03:17 lr: 1.5119625010081529e-05 loss: 0.0817 (0.0904) time: 2.9370 data: 0.0075 max mem: 33302 +Epoch: [29] [1760/4276] eta: 2:02:47 lr: 1.5116620082894613e-05 loss: 0.0730 (0.0903) time: 2.9092 data: 0.0078 max mem: 33302 +Epoch: [29] [1770/4276] eta: 2:02:18 lr: 1.5113615089336402e-05 loss: 0.0749 (0.0903) time: 2.8947 data: 0.0077 max mem: 33302 +Epoch: [29] [1780/4276] eta: 2:01:49 lr: 1.5110610029390772e-05 loss: 0.0791 (0.0903) time: 2.9201 data: 0.0080 max mem: 33302 +Epoch: [29] [1790/4276] eta: 2:01:20 lr: 1.5107604903041575e-05 loss: 0.0760 (0.0902) time: 2.9466 data: 0.0079 max mem: 33302 +Epoch: [29] [1800/4276] eta: 2:00:51 lr: 1.5104599710272675e-05 loss: 0.0780 (0.0902) time: 2.9474 data: 0.0075 max mem: 33302 +Epoch: [29] [1810/4276] eta: 2:00:22 lr: 1.5101594451067912e-05 loss: 0.0905 (0.0903) time: 2.9460 data: 0.0079 max mem: 33302 +Epoch: [29] [1820/4276] eta: 1:59:52 lr: 1.5098589125411142e-05 loss: 0.0903 (0.0902) time: 2.9453 data: 0.0080 max mem: 33302 +Epoch: [29] [1830/4276] eta: 1:59:23 lr: 1.509558373328618e-05 loss: 0.0848 (0.0903) time: 2.9462 data: 0.0076 max mem: 33302 +Epoch: [29] [1840/4276] eta: 1:58:54 lr: 1.5092578274676864e-05 loss: 0.0758 (0.0902) time: 2.9372 data: 0.0078 max mem: 33302 +Epoch: [29] [1850/4276] eta: 1:58:24 lr: 1.5089572749567004e-05 loss: 0.0758 (0.0902) time: 2.9100 data: 0.0077 max mem: 33302 +Epoch: [29] [1860/4276] eta: 1:57:55 lr: 1.5086567157940423e-05 loss: 0.0842 (0.0901) time: 2.8967 data: 0.0073 max mem: 33302 +Epoch: [29] [1870/4276] eta: 1:57:25 lr: 1.5083561499780912e-05 loss: 0.0829 (0.0901) time: 2.8989 data: 0.0076 max mem: 33302 +Epoch: [29] [1880/4276] eta: 1:56:55 lr: 1.508055577507227e-05 loss: 0.0772 (0.0901) time: 2.8993 data: 0.0078 max mem: 33302 +Epoch: [29] [1890/4276] eta: 1:56:26 lr: 1.5077549983798287e-05 loss: 0.0772 (0.0900) time: 2.8973 data: 0.0077 max mem: 33302 +Epoch: [29] [1900/4276] eta: 1:55:56 lr: 1.5074544125942744e-05 loss: 0.0803 (0.0900) time: 2.8969 data: 0.0079 max mem: 33302 +Epoch: [29] [1910/4276] eta: 1:55:27 lr: 1.5071538201489411e-05 loss: 0.0854 (0.0901) time: 2.9172 data: 0.0085 max mem: 33302 +Epoch: [29] [1920/4276] eta: 1:54:57 lr: 1.5068532210422053e-05 loss: 0.0855 (0.0900) time: 2.9185 data: 0.0084 max mem: 33302 +Epoch: [29] [1930/4276] eta: 1:54:28 lr: 1.5065526152724433e-05 loss: 0.0804 (0.0900) time: 2.9082 data: 0.0081 max mem: 33302 +Epoch: [29] [1940/4276] eta: 1:53:59 lr: 1.50625200283803e-05 loss: 0.0837 (0.0900) time: 2.9386 data: 0.0088 max mem: 33302 +Epoch: [29] [1950/4276] eta: 1:53:30 lr: 1.5059513837373393e-05 loss: 0.0922 (0.0901) time: 2.9604 data: 0.0090 max mem: 33302 +Epoch: [29] [1960/4276] eta: 1:53:01 lr: 1.5056507579687446e-05 loss: 0.0793 (0.0900) time: 2.9549 data: 0.0087 max mem: 33302 +Epoch: [29] [1970/4276] eta: 1:52:32 lr: 1.505350125530619e-05 loss: 0.0675 (0.0899) time: 2.9511 data: 0.0089 max mem: 33302 +Epoch: [29] [1980/4276] eta: 1:52:03 lr: 1.5050494864213352e-05 loss: 0.0680 (0.0898) time: 2.9575 data: 0.0090 max mem: 33302 +Epoch: [29] [1990/4276] eta: 1:51:34 lr: 1.5047488406392632e-05 loss: 0.0793 (0.0898) time: 2.9581 data: 0.0090 max mem: 33302 +Epoch: [29] [2000/4276] eta: 1:51:05 lr: 1.504448188182774e-05 loss: 0.0816 (0.0898) time: 2.9538 data: 0.0084 max mem: 33302 +Epoch: [29] [2010/4276] eta: 1:50:36 lr: 1.504147529050238e-05 loss: 0.0816 (0.0898) time: 2.9555 data: 0.0087 max mem: 33302 +Epoch: [29] [2020/4276] eta: 1:50:07 lr: 1.5038468632400227e-05 loss: 0.0932 (0.0899) time: 2.9473 data: 0.0090 max mem: 33302 +Epoch: [29] [2030/4276] eta: 1:49:38 lr: 1.5035461907504973e-05 loss: 0.0836 (0.0898) time: 2.9271 data: 0.0089 max mem: 33302 +Epoch: [29] [2040/4276] eta: 1:49:08 lr: 1.5032455115800289e-05 loss: 0.0786 (0.0898) time: 2.9304 data: 0.0092 max mem: 33302 +Epoch: [29] [2050/4276] eta: 1:48:39 lr: 1.502944825726985e-05 loss: 0.0886 (0.0898) time: 2.9508 data: 0.0085 max mem: 33302 +Epoch: [29] [2060/4276] eta: 1:48:10 lr: 1.5026441331897303e-05 loss: 0.0888 (0.0898) time: 2.9570 data: 0.0076 max mem: 33302 +Epoch: [29] [2070/4276] eta: 1:47:41 lr: 1.5023434339666306e-05 loss: 0.0804 (0.0898) time: 2.9562 data: 0.0077 max mem: 33302 +Epoch: [29] [2080/4276] eta: 1:47:12 lr: 1.50204272805605e-05 loss: 0.0864 (0.0899) time: 2.9528 data: 0.0079 max mem: 33302 +Epoch: [29] [2090/4276] eta: 1:46:43 lr: 1.5017420154563532e-05 loss: 0.0925 (0.0899) time: 2.9463 data: 0.0074 max mem: 33302 +Epoch: [29] [2100/4276] eta: 1:46:14 lr: 1.5014412961659013e-05 loss: 0.0842 (0.0899) time: 2.9426 data: 0.0071 max mem: 33302 +Epoch: [29] [2110/4276] eta: 1:45:45 lr: 1.5011405701830575e-05 loss: 0.0806 (0.0898) time: 2.9472 data: 0.0073 max mem: 33302 +Epoch: [29] [2120/4276] eta: 1:45:16 lr: 1.500839837506183e-05 loss: 0.0778 (0.0898) time: 2.9495 data: 0.0073 max mem: 33302 +Epoch: [29] [2130/4276] eta: 1:44:47 lr: 1.5005390981336387e-05 loss: 0.0715 (0.0897) time: 2.9474 data: 0.0074 max mem: 33302 +Epoch: [29] [2140/4276] eta: 1:44:18 lr: 1.5002383520637833e-05 loss: 0.0826 (0.0898) time: 2.9442 data: 0.0074 max mem: 33302 +Epoch: [29] [2150/4276] eta: 1:43:48 lr: 1.4999375992949769e-05 loss: 0.0821 (0.0897) time: 2.9436 data: 0.0073 max mem: 33302 +Epoch: [29] [2160/4276] eta: 1:43:19 lr: 1.499636839825577e-05 loss: 0.0743 (0.0897) time: 2.9443 data: 0.0077 max mem: 33302 +Epoch: [29] [2170/4276] eta: 1:42:50 lr: 1.4993360736539422e-05 loss: 0.0793 (0.0897) time: 2.9436 data: 0.0076 max mem: 33302 +Epoch: [29] [2180/4276] eta: 1:42:20 lr: 1.499035300778428e-05 loss: 0.0793 (0.0896) time: 2.9205 data: 0.0080 max mem: 33302 +Epoch: [29] [2190/4276] eta: 1:41:51 lr: 1.4987345211973911e-05 loss: 0.0815 (0.0896) time: 2.8931 data: 0.0084 max mem: 33302 +Epoch: [29] [2200/4276] eta: 1:41:22 lr: 1.4984337349091859e-05 loss: 0.0936 (0.0897) time: 2.9182 data: 0.0084 max mem: 33302 +Epoch: [29] [2210/4276] eta: 1:40:52 lr: 1.4981329419121685e-05 loss: 0.0953 (0.0897) time: 2.9276 data: 0.0084 max mem: 33302 +Epoch: [29] [2220/4276] eta: 1:40:23 lr: 1.4978321422046906e-05 loss: 0.0795 (0.0896) time: 2.9230 data: 0.0079 max mem: 33302 +Epoch: [29] [2230/4276] eta: 1:39:54 lr: 1.4975313357851059e-05 loss: 0.0799 (0.0896) time: 2.9406 data: 0.0074 max mem: 33302 +Epoch: [29] [2240/4276] eta: 1:39:25 lr: 1.4972305226517663e-05 loss: 0.0743 (0.0896) time: 2.9423 data: 0.0071 max mem: 33302 +Epoch: [29] [2250/4276] eta: 1:38:55 lr: 1.4969297028030244e-05 loss: 0.0756 (0.0895) time: 2.9425 data: 0.0072 max mem: 33302 +Epoch: [29] [2260/4276] eta: 1:38:26 lr: 1.4966288762372289e-05 loss: 0.0813 (0.0896) time: 2.9409 data: 0.0077 max mem: 33302 +Epoch: [29] [2270/4276] eta: 1:37:57 lr: 1.4963280429527302e-05 loss: 0.0869 (0.0896) time: 2.9400 data: 0.0077 max mem: 33302 +Epoch: [29] [2280/4276] eta: 1:37:28 lr: 1.4960272029478776e-05 loss: 0.0857 (0.0896) time: 2.9408 data: 0.0071 max mem: 33302 +Epoch: [29] [2290/4276] eta: 1:36:59 lr: 1.49572635622102e-05 loss: 0.0857 (0.0896) time: 2.9388 data: 0.0072 max mem: 33302 +Epoch: [29] [2300/4276] eta: 1:36:29 lr: 1.4954255027705034e-05 loss: 0.0841 (0.0896) time: 2.9389 data: 0.0072 max mem: 33302 +Epoch: [29] [2310/4276] eta: 1:36:00 lr: 1.495124642594675e-05 loss: 0.0879 (0.0896) time: 2.9413 data: 0.0072 max mem: 33302 +Epoch: [29] [2320/4276] eta: 1:35:31 lr: 1.4948237756918814e-05 loss: 0.0990 (0.0897) time: 2.9419 data: 0.0072 max mem: 33302 +Epoch: [29] [2330/4276] eta: 1:35:02 lr: 1.4945229020604667e-05 loss: 0.0877 (0.0897) time: 2.9434 data: 0.0072 max mem: 33302 +Epoch: [29] [2340/4276] eta: 1:34:33 lr: 1.494222021698776e-05 loss: 0.0863 (0.0896) time: 2.9436 data: 0.0074 max mem: 33302 +Epoch: [29] [2350/4276] eta: 1:34:03 lr: 1.4939211346051524e-05 loss: 0.0787 (0.0896) time: 2.9415 data: 0.0083 max mem: 33302 +Epoch: [29] [2360/4276] eta: 1:33:34 lr: 1.4936202407779396e-05 loss: 0.0824 (0.0896) time: 2.9428 data: 0.0084 max mem: 33302 +Epoch: [29] [2370/4276] eta: 1:33:05 lr: 1.4933193402154786e-05 loss: 0.0852 (0.0896) time: 2.9441 data: 0.0078 max mem: 33302 +Epoch: [29] [2380/4276] eta: 1:32:36 lr: 1.4930184329161107e-05 loss: 0.0891 (0.0897) time: 2.9427 data: 0.0076 max mem: 33302 +Epoch: [29] [2390/4276] eta: 1:32:07 lr: 1.4927175188781767e-05 loss: 0.0891 (0.0897) time: 2.9430 data: 0.0078 max mem: 33302 +Epoch: [29] [2400/4276] eta: 1:31:37 lr: 1.4924165981000169e-05 loss: 0.0837 (0.0897) time: 2.9436 data: 0.0078 max mem: 33302 +Epoch: [29] [2410/4276] eta: 1:31:08 lr: 1.4921156705799688e-05 loss: 0.0858 (0.0897) time: 2.9606 data: 0.0079 max mem: 33302 +Epoch: [29] [2420/4276] eta: 1:30:39 lr: 1.4918147363163715e-05 loss: 0.0798 (0.0897) time: 2.9451 data: 0.0080 max mem: 33302 +Epoch: [29] [2430/4276] eta: 1:30:10 lr: 1.4915137953075618e-05 loss: 0.0865 (0.0897) time: 2.9244 data: 0.0082 max mem: 33302 +Epoch: [29] [2440/4276] eta: 1:29:41 lr: 1.4912128475518771e-05 loss: 0.0838 (0.0897) time: 2.9444 data: 0.0086 max mem: 33302 +Epoch: [29] [2450/4276] eta: 1:29:11 lr: 1.4909118930476523e-05 loss: 0.0812 (0.0897) time: 2.9486 data: 0.0083 max mem: 33302 +Epoch: [29] [2460/4276] eta: 1:28:42 lr: 1.4906109317932223e-05 loss: 0.0861 (0.0897) time: 2.9448 data: 0.0079 max mem: 33302 +Epoch: [29] [2470/4276] eta: 1:28:13 lr: 1.490309963786922e-05 loss: 0.0855 (0.0897) time: 2.9401 data: 0.0078 max mem: 33302 +Epoch: [29] [2480/4276] eta: 1:27:43 lr: 1.4900089890270848e-05 loss: 0.0903 (0.0898) time: 2.9278 data: 0.0082 max mem: 33302 +Epoch: [29] [2490/4276] eta: 1:27:14 lr: 1.4897080075120428e-05 loss: 0.0895 (0.0898) time: 2.9305 data: 0.0080 max mem: 33302 +Epoch: [29] [2500/4276] eta: 1:26:45 lr: 1.489407019240128e-05 loss: 0.0869 (0.0898) time: 2.9421 data: 0.0072 max mem: 33302 +Epoch: [29] [2510/4276] eta: 1:26:16 lr: 1.4891060242096713e-05 loss: 0.0863 (0.0898) time: 2.9412 data: 0.0072 max mem: 33302 +Epoch: [29] [2520/4276] eta: 1:25:46 lr: 1.488805022419004e-05 loss: 0.0855 (0.0898) time: 2.9399 data: 0.0072 max mem: 33302 +Epoch: [29] [2530/4276] eta: 1:25:17 lr: 1.4885040138664538e-05 loss: 0.0838 (0.0897) time: 2.9396 data: 0.0072 max mem: 33302 +Epoch: [29] [2540/4276] eta: 1:24:48 lr: 1.4882029985503507e-05 loss: 0.0831 (0.0898) time: 2.9426 data: 0.0071 max mem: 33302 +Epoch: [29] [2550/4276] eta: 1:24:19 lr: 1.4879019764690221e-05 loss: 0.0802 (0.0897) time: 2.9441 data: 0.0075 max mem: 33302 +Epoch: [29] [2560/4276] eta: 1:23:50 lr: 1.4876009476207958e-05 loss: 0.0668 (0.0896) time: 2.9428 data: 0.0077 max mem: 33302 +Epoch: [29] [2570/4276] eta: 1:23:20 lr: 1.4872999120039973e-05 loss: 0.0755 (0.0896) time: 2.9444 data: 0.0077 max mem: 33302 +Epoch: [29] [2580/4276] eta: 1:22:51 lr: 1.4869988696169524e-05 loss: 0.0766 (0.0896) time: 2.9449 data: 0.0078 max mem: 33302 +Epoch: [29] [2590/4276] eta: 1:22:22 lr: 1.4866978204579856e-05 loss: 0.0747 (0.0895) time: 2.9444 data: 0.0076 max mem: 33302 +Epoch: [29] [2600/4276] eta: 1:21:53 lr: 1.4863967645254217e-05 loss: 0.0713 (0.0895) time: 2.9447 data: 0.0075 max mem: 33302 +Epoch: [29] [2610/4276] eta: 1:21:23 lr: 1.486095701817583e-05 loss: 0.0721 (0.0894) time: 2.9468 data: 0.0076 max mem: 33302 +Epoch: [29] [2620/4276] eta: 1:20:54 lr: 1.485794632332792e-05 loss: 0.0795 (0.0895) time: 2.9491 data: 0.0078 max mem: 33302 +Epoch: [29] [2630/4276] eta: 1:20:25 lr: 1.4854935560693712e-05 loss: 0.0753 (0.0894) time: 2.9491 data: 0.0079 max mem: 33302 +Epoch: [29] [2640/4276] eta: 1:19:56 lr: 1.4851924730256397e-05 loss: 0.0705 (0.0894) time: 2.9479 data: 0.0078 max mem: 33302 +Epoch: [29] [2650/4276] eta: 1:19:27 lr: 1.4848913831999186e-05 loss: 0.0724 (0.0893) time: 2.9471 data: 0.0076 max mem: 33302 +Epoch: [29] [2660/4276] eta: 1:18:57 lr: 1.484590286590527e-05 loss: 0.0807 (0.0893) time: 2.9324 data: 0.0082 max mem: 33302 +Epoch: [29] [2670/4276] eta: 1:18:28 lr: 1.4842891831957833e-05 loss: 0.0835 (0.0893) time: 2.9115 data: 0.0087 max mem: 33302 +Epoch: [29] [2680/4276] eta: 1:17:58 lr: 1.483988073014005e-05 loss: 0.0865 (0.0893) time: 2.9161 data: 0.0086 max mem: 33302 +Epoch: [29] [2690/4276] eta: 1:17:29 lr: 1.4836869560435084e-05 loss: 0.0799 (0.0892) time: 2.9379 data: 0.0086 max mem: 33302 +Epoch: [29] [2700/4276] eta: 1:17:00 lr: 1.4833858322826102e-05 loss: 0.0695 (0.0892) time: 2.9490 data: 0.0086 max mem: 33302 +Epoch: [29] [2710/4276] eta: 1:16:31 lr: 1.483084701729626e-05 loss: 0.0785 (0.0892) time: 2.9509 data: 0.0087 max mem: 33302 +Epoch: [29] [2720/4276] eta: 1:16:02 lr: 1.482783564382869e-05 loss: 0.0785 (0.0891) time: 2.9507 data: 0.0085 max mem: 33302 +Epoch: [29] [2730/4276] eta: 1:15:32 lr: 1.4824824202406534e-05 loss: 0.0844 (0.0891) time: 2.9484 data: 0.0081 max mem: 33302 +Epoch: [29] [2740/4276] eta: 1:15:03 lr: 1.482181269301292e-05 loss: 0.0844 (0.0891) time: 2.9477 data: 0.0079 max mem: 33302 +Epoch: [29] [2750/4276] eta: 1:14:34 lr: 1.4818801115630975e-05 loss: 0.0802 (0.0891) time: 2.9484 data: 0.0081 max mem: 33302 +Epoch: [29] [2760/4276] eta: 1:14:05 lr: 1.48157894702438e-05 loss: 0.0766 (0.0891) time: 2.9502 data: 0.0081 max mem: 33302 +Epoch: [29] [2770/4276] eta: 1:13:35 lr: 1.4812777756834501e-05 loss: 0.0766 (0.0891) time: 2.9488 data: 0.0078 max mem: 33302 +Epoch: [29] [2780/4276] eta: 1:13:06 lr: 1.4809765975386175e-05 loss: 0.0754 (0.0891) time: 2.9470 data: 0.0076 max mem: 33302 +Epoch: [29] [2790/4276] eta: 1:12:37 lr: 1.4806754125881923e-05 loss: 0.0753 (0.0890) time: 2.9316 data: 0.0082 max mem: 33302 +Epoch: [29] [2800/4276] eta: 1:12:07 lr: 1.4803742208304802e-05 loss: 0.0753 (0.0890) time: 2.9089 data: 0.0084 max mem: 33302 +Epoch: [29] [2810/4276] eta: 1:11:38 lr: 1.4800730222637902e-05 loss: 0.0684 (0.0889) time: 2.9041 data: 0.0082 max mem: 33302 +Epoch: [29] [2820/4276] eta: 1:11:08 lr: 1.4797718168864275e-05 loss: 0.0684 (0.0889) time: 2.9053 data: 0.0083 max mem: 33302 +Epoch: [29] [2830/4276] eta: 1:10:39 lr: 1.4794706046966992e-05 loss: 0.0824 (0.0889) time: 2.9173 data: 0.0092 max mem: 33302 +Epoch: [29] [2840/4276] eta: 1:10:10 lr: 1.4791693856929084e-05 loss: 0.0951 (0.0889) time: 2.9387 data: 0.0095 max mem: 33302 +Epoch: [29] [2850/4276] eta: 1:09:41 lr: 1.47886815987336e-05 loss: 0.0945 (0.0889) time: 2.9471 data: 0.0085 max mem: 33302 +Epoch: [29] [2860/4276] eta: 1:09:11 lr: 1.478566927236357e-05 loss: 0.0695 (0.0889) time: 2.9307 data: 0.0087 max mem: 33302 +Epoch: [29] [2870/4276] eta: 1:08:42 lr: 1.478265687780202e-05 loss: 0.0759 (0.0889) time: 2.9077 data: 0.0095 max mem: 33302 +Epoch: [29] [2880/4276] eta: 1:08:12 lr: 1.4779644415031962e-05 loss: 0.0766 (0.0889) time: 2.9220 data: 0.0101 max mem: 33302 +Epoch: [29] [2890/4276] eta: 1:07:43 lr: 1.4776631884036405e-05 loss: 0.0768 (0.0889) time: 2.9379 data: 0.0097 max mem: 33302 +Epoch: [29] [2900/4276] eta: 1:07:14 lr: 1.4773619284798346e-05 loss: 0.0840 (0.0889) time: 2.9211 data: 0.0090 max mem: 33302 +Epoch: [29] [2910/4276] eta: 1:06:44 lr: 1.4770606617300783e-05 loss: 0.0840 (0.0889) time: 2.9233 data: 0.0087 max mem: 33302 +Epoch: [29] [2920/4276] eta: 1:06:15 lr: 1.4767593881526692e-05 loss: 0.0829 (0.0889) time: 2.9414 data: 0.0080 max mem: 33302 +Epoch: [29] [2930/4276] eta: 1:05:46 lr: 1.4764581077459053e-05 loss: 0.0825 (0.0889) time: 2.9441 data: 0.0073 max mem: 33302 +Epoch: [29] [2940/4276] eta: 1:05:17 lr: 1.4761568205080834e-05 loss: 0.0823 (0.0889) time: 2.9456 data: 0.0072 max mem: 33302 +Epoch: [29] [2950/4276] eta: 1:04:47 lr: 1.4758555264374988e-05 loss: 0.0841 (0.0889) time: 2.9467 data: 0.0073 max mem: 33302 +Epoch: [29] [2960/4276] eta: 1:04:18 lr: 1.4755542255324468e-05 loss: 0.0834 (0.0889) time: 2.9465 data: 0.0075 max mem: 33302 +Epoch: [29] [2970/4276] eta: 1:03:49 lr: 1.4752529177912217e-05 loss: 0.0844 (0.0889) time: 2.9486 data: 0.0076 max mem: 33302 +Epoch: [29] [2980/4276] eta: 1:03:20 lr: 1.4749516032121174e-05 loss: 0.0876 (0.0889) time: 2.9510 data: 0.0078 max mem: 33302 +Epoch: [29] [2990/4276] eta: 1:02:50 lr: 1.4746502817934261e-05 loss: 0.0824 (0.0889) time: 2.9506 data: 0.0077 max mem: 33302 +Epoch: [29] [3000/4276] eta: 1:02:21 lr: 1.4743489535334393e-05 loss: 0.0747 (0.0888) time: 2.9492 data: 0.0077 max mem: 33302 +Epoch: [29] [3010/4276] eta: 1:01:52 lr: 1.4740476184304486e-05 loss: 0.0798 (0.0888) time: 2.9480 data: 0.0077 max mem: 33302 +Epoch: [29] [3020/4276] eta: 1:01:23 lr: 1.4737462764827448e-05 loss: 0.0808 (0.0888) time: 2.9470 data: 0.0075 max mem: 33302 +Epoch: [29] [3030/4276] eta: 1:00:53 lr: 1.4734449276886156e-05 loss: 0.0739 (0.0888) time: 2.9481 data: 0.0074 max mem: 33302 +Epoch: [29] [3040/4276] eta: 1:00:24 lr: 1.4731435720463508e-05 loss: 0.0919 (0.0888) time: 2.9512 data: 0.0080 max mem: 33302 +Epoch: [29] [3050/4276] eta: 0:59:55 lr: 1.4728422095542377e-05 loss: 0.0970 (0.0888) time: 2.9561 data: 0.0080 max mem: 33302 +Epoch: [29] [3060/4276] eta: 0:59:26 lr: 1.4725408402105639e-05 loss: 0.0730 (0.0888) time: 2.9528 data: 0.0075 max mem: 33302 +Epoch: [29] [3070/4276] eta: 0:58:56 lr: 1.4722394640136144e-05 loss: 0.0755 (0.0888) time: 2.9467 data: 0.0076 max mem: 33302 +Epoch: [29] [3080/4276] eta: 0:58:27 lr: 1.4719380809616751e-05 loss: 0.0755 (0.0887) time: 2.9467 data: 0.0082 max mem: 33302 +Epoch: [29] [3090/4276] eta: 0:57:58 lr: 1.4716366910530305e-05 loss: 0.0686 (0.0887) time: 2.9477 data: 0.0084 max mem: 33302 +Epoch: [29] [3100/4276] eta: 0:57:29 lr: 1.4713352942859649e-05 loss: 0.0784 (0.0887) time: 2.9487 data: 0.0080 max mem: 33302 +Epoch: [29] [3110/4276] eta: 0:56:59 lr: 1.4710338906587596e-05 loss: 0.0752 (0.0886) time: 2.9487 data: 0.0075 max mem: 33302 +Epoch: [29] [3120/4276] eta: 0:56:30 lr: 1.4707324801696975e-05 loss: 0.0768 (0.0886) time: 2.9473 data: 0.0071 max mem: 33302 +Epoch: [29] [3130/4276] eta: 0:56:01 lr: 1.4704310628170601e-05 loss: 0.0832 (0.0886) time: 2.9460 data: 0.0071 max mem: 33302 +Epoch: [29] [3140/4276] eta: 0:55:31 lr: 1.4701296385991278e-05 loss: 0.0832 (0.0886) time: 2.9499 data: 0.0072 max mem: 33302 +Epoch: [29] [3150/4276] eta: 0:55:02 lr: 1.4698282075141796e-05 loss: 0.0889 (0.0886) time: 2.9516 data: 0.0073 max mem: 33302 +Epoch: [29] [3160/4276] eta: 0:54:33 lr: 1.4695267695604938e-05 loss: 0.0855 (0.0886) time: 2.9474 data: 0.0073 max mem: 33302 +Epoch: [29] [3170/4276] eta: 0:54:04 lr: 1.4692253247363493e-05 loss: 0.0855 (0.0887) time: 2.9466 data: 0.0072 max mem: 33302 +Epoch: [29] [3180/4276] eta: 0:53:34 lr: 1.4689238730400234e-05 loss: 0.0835 (0.0886) time: 2.9473 data: 0.0072 max mem: 33302 +Epoch: [29] [3190/4276] eta: 0:53:05 lr: 1.468622414469791e-05 loss: 0.0747 (0.0886) time: 2.9481 data: 0.0072 max mem: 33302 +Epoch: [29] [3200/4276] eta: 0:52:36 lr: 1.4683209490239287e-05 loss: 0.0806 (0.0886) time: 2.9502 data: 0.0072 max mem: 33302 +Epoch: [29] [3210/4276] eta: 0:52:06 lr: 1.4680194767007108e-05 loss: 0.0761 (0.0886) time: 2.9389 data: 0.0077 max mem: 33302 +Epoch: [29] [3220/4276] eta: 0:51:37 lr: 1.4677179974984104e-05 loss: 0.0898 (0.0886) time: 2.9135 data: 0.0087 max mem: 33302 +Epoch: [29] [3230/4276] eta: 0:51:08 lr: 1.4674165114153013e-05 loss: 0.0898 (0.0886) time: 2.9095 data: 0.0094 max mem: 33302 +Epoch: [29] [3240/4276] eta: 0:50:38 lr: 1.4671150184496552e-05 loss: 0.0838 (0.0886) time: 2.9276 data: 0.0086 max mem: 33302 +Epoch: [29] [3250/4276] eta: 0:50:09 lr: 1.4668135185997443e-05 loss: 0.0868 (0.0887) time: 2.9376 data: 0.0074 max mem: 33302 +Epoch: [29] [3260/4276] eta: 0:49:40 lr: 1.4665120118638376e-05 loss: 0.0856 (0.0887) time: 2.9322 data: 0.0075 max mem: 33302 +Epoch: [29] [3270/4276] eta: 0:49:10 lr: 1.4662104982402052e-05 loss: 0.0848 (0.0887) time: 2.9216 data: 0.0081 max mem: 33302 +Epoch: [29] [3280/4276] eta: 0:48:41 lr: 1.4659089777271165e-05 loss: 0.0815 (0.0887) time: 2.9324 data: 0.0077 max mem: 33302 +Epoch: [29] [3290/4276] eta: 0:48:12 lr: 1.4656074503228392e-05 loss: 0.0939 (0.0887) time: 2.9386 data: 0.0077 max mem: 33302 +Epoch: [29] [3300/4276] eta: 0:47:42 lr: 1.4653059160256402e-05 loss: 0.0967 (0.0888) time: 2.9338 data: 0.0078 max mem: 33302 +Epoch: [29] [3310/4276] eta: 0:47:13 lr: 1.4650043748337857e-05 loss: 0.1014 (0.0888) time: 2.9369 data: 0.0073 max mem: 33302 +Epoch: [29] [3320/4276] eta: 0:46:44 lr: 1.4647028267455417e-05 loss: 0.1030 (0.0889) time: 2.9360 data: 0.0072 max mem: 33302 +Epoch: [29] [3330/4276] eta: 0:46:14 lr: 1.4644012717591729e-05 loss: 0.0974 (0.0888) time: 2.9377 data: 0.0072 max mem: 33302 +Epoch: [29] [3340/4276] eta: 0:45:45 lr: 1.4640997098729426e-05 loss: 0.0824 (0.0888) time: 2.9390 data: 0.0071 max mem: 33302 +Epoch: [29] [3350/4276] eta: 0:45:16 lr: 1.4637981410851135e-05 loss: 0.0831 (0.0888) time: 2.9450 data: 0.0073 max mem: 33302 +Epoch: [29] [3360/4276] eta: 0:44:46 lr: 1.4634965653939484e-05 loss: 0.0783 (0.0888) time: 2.9446 data: 0.0075 max mem: 33302 +Epoch: [29] [3370/4276] eta: 0:44:17 lr: 1.4631949827977086e-05 loss: 0.0795 (0.0888) time: 2.9395 data: 0.0073 max mem: 33302 +Epoch: [29] [3380/4276] eta: 0:43:48 lr: 1.4628933932946542e-05 loss: 0.0926 (0.0888) time: 2.9463 data: 0.0071 max mem: 33302 +Epoch: [29] [3390/4276] eta: 0:43:18 lr: 1.4625917968830449e-05 loss: 0.0845 (0.0888) time: 2.9472 data: 0.0071 max mem: 33302 +Epoch: [29] [3400/4276] eta: 0:42:49 lr: 1.4622901935611397e-05 loss: 0.0930 (0.0888) time: 2.9427 data: 0.0073 max mem: 33302 +Epoch: [29] [3410/4276] eta: 0:42:20 lr: 1.4619885833271968e-05 loss: 0.0803 (0.0888) time: 2.9329 data: 0.0082 max mem: 33302 +Epoch: [29] [3420/4276] eta: 0:41:50 lr: 1.4616869661794727e-05 loss: 0.0851 (0.0888) time: 2.9234 data: 0.0083 max mem: 33302 +Epoch: [29] [3430/4276] eta: 0:41:21 lr: 1.4613853421162236e-05 loss: 0.0906 (0.0889) time: 2.9127 data: 0.0082 max mem: 33302 +Epoch: [29] [3440/4276] eta: 0:40:52 lr: 1.4610837111357054e-05 loss: 0.0840 (0.0888) time: 2.9247 data: 0.0082 max mem: 33302 +Epoch: [29] [3450/4276] eta: 0:40:22 lr: 1.4607820732361733e-05 loss: 0.0863 (0.0889) time: 2.9490 data: 0.0077 max mem: 33302 +Epoch: [29] [3460/4276] eta: 0:39:53 lr: 1.4604804284158793e-05 loss: 0.1128 (0.0890) time: 2.9495 data: 0.0073 max mem: 33302 +Epoch: [29] [3470/4276] eta: 0:39:24 lr: 1.4601787766730779e-05 loss: 0.0871 (0.0889) time: 2.9489 data: 0.0073 max mem: 33302 +Epoch: [29] [3480/4276] eta: 0:38:55 lr: 1.4598771180060203e-05 loss: 0.0851 (0.0890) time: 2.9507 data: 0.0075 max mem: 33302 +Epoch: [29] [3490/4276] eta: 0:38:25 lr: 1.4595754524129584e-05 loss: 0.0855 (0.0890) time: 2.9537 data: 0.0075 max mem: 33302 +Epoch: [29] [3500/4276] eta: 0:37:56 lr: 1.4592737798921421e-05 loss: 0.0801 (0.0889) time: 2.9534 data: 0.0073 max mem: 33302 +Epoch: [29] [3510/4276] eta: 0:37:27 lr: 1.4589721004418208e-05 loss: 0.0816 (0.0889) time: 2.9503 data: 0.0074 max mem: 33302 +Epoch: [29] [3520/4276] eta: 0:36:57 lr: 1.4586704140602443e-05 loss: 0.0839 (0.0889) time: 2.9530 data: 0.0078 max mem: 33302 +Epoch: [29] [3530/4276] eta: 0:36:28 lr: 1.4583687207456587e-05 loss: 0.0839 (0.0889) time: 2.9561 data: 0.0077 max mem: 33302 +Epoch: [29] [3540/4276] eta: 0:35:59 lr: 1.4580670204963124e-05 loss: 0.0852 (0.0889) time: 2.9537 data: 0.0075 max mem: 33302 +Epoch: [29] [3550/4276] eta: 0:35:29 lr: 1.4577653133104505e-05 loss: 0.0819 (0.0889) time: 2.9521 data: 0.0075 max mem: 33302 +Epoch: [29] [3560/4276] eta: 0:35:00 lr: 1.4574635991863198e-05 loss: 0.0903 (0.0890) time: 2.9525 data: 0.0076 max mem: 33302 +Epoch: [29] [3570/4276] eta: 0:34:31 lr: 1.4571618781221632e-05 loss: 0.0962 (0.0890) time: 2.9548 data: 0.0080 max mem: 33302 +Epoch: [29] [3580/4276] eta: 0:34:02 lr: 1.4568601501162252e-05 loss: 0.0762 (0.0889) time: 2.9335 data: 0.0084 max mem: 33302 +Epoch: [29] [3590/4276] eta: 0:33:32 lr: 1.4565584151667483e-05 loss: 0.0801 (0.0890) time: 2.9044 data: 0.0081 max mem: 33302 +Epoch: [29] [3600/4276] eta: 0:33:03 lr: 1.4562566732719748e-05 loss: 0.0890 (0.0890) time: 2.9012 data: 0.0077 max mem: 33302 +Epoch: [29] [3610/4276] eta: 0:32:33 lr: 1.4559549244301452e-05 loss: 0.0897 (0.0890) time: 2.9282 data: 0.0078 max mem: 33302 +Epoch: [29] [3620/4276] eta: 0:32:04 lr: 1.4556531686394997e-05 loss: 0.0812 (0.0889) time: 2.9509 data: 0.0077 max mem: 33302 +Epoch: [29] [3630/4276] eta: 0:31:35 lr: 1.455351405898278e-05 loss: 0.0805 (0.0890) time: 2.9496 data: 0.0075 max mem: 33302 +Epoch: [29] [3640/4276] eta: 0:31:05 lr: 1.4550496362047192e-05 loss: 0.0913 (0.0890) time: 2.9510 data: 0.0075 max mem: 33302 +Epoch: [29] [3650/4276] eta: 0:30:36 lr: 1.4547478595570596e-05 loss: 0.0866 (0.0890) time: 2.9664 data: 0.0081 max mem: 33302 +Epoch: [29] [3660/4276] eta: 0:30:07 lr: 1.4544460759535369e-05 loss: 0.0844 (0.0889) time: 2.9470 data: 0.0086 max mem: 33302 +Epoch: [29] [3670/4276] eta: 0:29:37 lr: 1.4541442853923868e-05 loss: 0.0856 (0.0889) time: 2.9144 data: 0.0085 max mem: 33302 +Epoch: [29] [3680/4276] eta: 0:29:08 lr: 1.4538424878718448e-05 loss: 0.0828 (0.0889) time: 2.9280 data: 0.0089 max mem: 33302 +Epoch: [29] [3690/4276] eta: 0:28:39 lr: 1.4535406833901446e-05 loss: 0.0836 (0.0890) time: 2.9471 data: 0.0090 max mem: 33302 +Epoch: [29] [3700/4276] eta: 0:28:10 lr: 1.4532388719455198e-05 loss: 0.0839 (0.0890) time: 2.9514 data: 0.0085 max mem: 33302 +Epoch: [29] [3710/4276] eta: 0:27:40 lr: 1.4529370535362028e-05 loss: 0.0739 (0.0889) time: 2.9490 data: 0.0081 max mem: 33302 +Epoch: [29] [3720/4276] eta: 0:27:11 lr: 1.4526352281604261e-05 loss: 0.0725 (0.0889) time: 2.9487 data: 0.0081 max mem: 33302 +Epoch: [29] [3730/4276] eta: 0:26:42 lr: 1.4523333958164192e-05 loss: 0.0860 (0.0889) time: 2.9522 data: 0.0080 max mem: 33302 +Epoch: [29] [3740/4276] eta: 0:26:12 lr: 1.4520315565024129e-05 loss: 0.0864 (0.0889) time: 2.9549 data: 0.0078 max mem: 33302 +Epoch: [29] [3750/4276] eta: 0:25:43 lr: 1.4517297102166357e-05 loss: 0.0919 (0.0889) time: 2.9402 data: 0.0082 max mem: 33302 +Epoch: [29] [3760/4276] eta: 0:25:14 lr: 1.4514278569573173e-05 loss: 0.0733 (0.0889) time: 2.9395 data: 0.0083 max mem: 33302 +Epoch: [29] [3770/4276] eta: 0:24:44 lr: 1.4511259967226833e-05 loss: 0.0714 (0.0889) time: 2.9524 data: 0.0079 max mem: 33302 +Epoch: [29] [3780/4276] eta: 0:24:15 lr: 1.4508241295109613e-05 loss: 0.0736 (0.0889) time: 2.9521 data: 0.0076 max mem: 33302 +Epoch: [29] [3790/4276] eta: 0:23:46 lr: 1.4505222553203762e-05 loss: 0.0769 (0.0889) time: 2.9501 data: 0.0075 max mem: 33302 +Epoch: [29] [3800/4276] eta: 0:23:16 lr: 1.4502203741491537e-05 loss: 0.0855 (0.0889) time: 2.9479 data: 0.0075 max mem: 33302 +Epoch: [29] [3810/4276] eta: 0:22:47 lr: 1.4499184859955173e-05 loss: 0.0857 (0.0889) time: 2.9474 data: 0.0077 max mem: 33302 +Epoch: [29] 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mem: 33302 +Epoch: [29] [3900/4276] eta: 0:18:23 lr: 1.4472011781106851e-05 loss: 0.0765 (0.0888) time: 2.9540 data: 0.0076 max mem: 33302 +Epoch: [29] [3910/4276] eta: 0:17:54 lr: 1.4468992200350365e-05 loss: 0.0725 (0.0888) time: 2.9523 data: 0.0080 max mem: 33302 +Epoch: [29] [3920/4276] eta: 0:17:24 lr: 1.4465972549573797e-05 loss: 0.0759 (0.0888) time: 2.9368 data: 0.0087 max mem: 33302 +Epoch: [29] [3930/4276] eta: 0:16:55 lr: 1.4462952828759288e-05 loss: 0.0821 (0.0888) time: 2.9146 data: 0.0093 max mem: 33302 +Epoch: [29] [3940/4276] eta: 0:16:26 lr: 1.4459933037888965e-05 loss: 0.0729 (0.0888) time: 2.9032 data: 0.0083 max mem: 33302 +Epoch: [29] [3950/4276] eta: 0:15:56 lr: 1.4456913176944953e-05 loss: 0.0729 (0.0888) time: 2.9023 data: 0.0081 max mem: 33302 +Epoch: [29] [3960/4276] eta: 0:15:27 lr: 1.4453893245909345e-05 loss: 0.0817 (0.0888) time: 2.9034 data: 0.0083 max mem: 33302 +Epoch: [29] [3970/4276] eta: 0:14:57 lr: 1.4450873244764255e-05 loss: 0.0852 (0.0888) time: 2.9059 data: 0.0083 max mem: 33302 +Epoch: [29] [3980/4276] eta: 0:14:28 lr: 1.4447853173491767e-05 loss: 0.0796 (0.0888) time: 2.9085 data: 0.0082 max mem: 33302 +Epoch: [29] [3990/4276] eta: 0:13:59 lr: 1.4444833032073976e-05 loss: 0.0789 (0.0888) time: 2.9076 data: 0.0080 max mem: 33302 +Epoch: [29] [4000/4276] eta: 0:13:29 lr: 1.4441812820492943e-05 loss: 0.0755 (0.0888) time: 2.9203 data: 0.0081 max mem: 33302 +Epoch: [29] [4010/4276] eta: 0:13:00 lr: 1.4438792538730737e-05 loss: 0.0775 (0.0888) time: 2.9487 data: 0.0085 max mem: 33302 +Epoch: [29] [4020/4276] eta: 0:12:31 lr: 1.4435772186769416e-05 loss: 0.0775 (0.0887) time: 2.9620 data: 0.0086 max mem: 33302 +Epoch: [29] [4030/4276] eta: 0:12:01 lr: 1.4432751764591035e-05 loss: 0.0745 (0.0887) time: 2.9600 data: 0.0080 max mem: 33302 +Epoch: [29] [4040/4276] eta: 0:11:32 lr: 1.4429731272177624e-05 loss: 0.0871 (0.0888) time: 2.9638 data: 0.0079 max mem: 33302 +Epoch: [29] [4050/4276] eta: 0:11:03 lr: 1.4426710709511215e-05 loss: 0.0873 (0.0888) time: 2.9664 data: 0.0080 max mem: 33302 +Epoch: [29] [4060/4276] eta: 0:10:33 lr: 1.4423690076573831e-05 loss: 0.0882 (0.0888) time: 2.9663 data: 0.0082 max mem: 33302 +Epoch: [29] [4070/4276] eta: 0:10:04 lr: 1.4420669373347492e-05 loss: 0.0858 (0.0888) time: 2.9630 data: 0.0081 max mem: 33302 +Epoch: [29] [4080/4276] eta: 0:09:35 lr: 1.441764859981419e-05 loss: 0.0890 (0.0888) time: 2.9588 data: 0.0080 max mem: 33302 +Epoch: [29] [4090/4276] eta: 0:09:05 lr: 1.441462775595593e-05 loss: 0.0895 (0.0888) time: 2.9576 data: 0.0081 max mem: 33302 +Epoch: [29] [4100/4276] eta: 0:08:36 lr: 1.4411606841754691e-05 loss: 0.0882 (0.0888) time: 2.9536 data: 0.0082 max mem: 33302 +Epoch: [29] [4110/4276] eta: 0:08:07 lr: 1.440858585719246e-05 loss: 0.0919 (0.0888) time: 2.9503 data: 0.0084 max mem: 33302 +Epoch: [29] [4120/4276] eta: 0:07:37 lr: 1.4405564802251198e-05 loss: 0.0910 (0.0889) time: 2.9487 data: 0.0083 max mem: 33302 +Epoch: [29] [4130/4276] eta: 0:07:08 lr: 1.4402543676912867e-05 loss: 0.0806 (0.0888) time: 2.9482 data: 0.0081 max mem: 33302 +Epoch: [29] [4140/4276] eta: 0:06:39 lr: 1.4399522481159426e-05 loss: 0.0810 (0.0888) time: 2.9589 data: 0.0085 max mem: 33302 +Epoch: [29] [4150/4276] eta: 0:06:09 lr: 1.4396501214972804e-05 loss: 0.0828 (0.0888) time: 2.9764 data: 0.0085 max mem: 33302 +Epoch: [29] [4160/4276] eta: 0:05:40 lr: 1.4393479878334943e-05 loss: 0.0791 (0.0888) time: 2.9710 data: 0.0081 max mem: 33302 +Epoch: [29] [4170/4276] eta: 0:05:11 lr: 1.4390458471227767e-05 loss: 0.0932 (0.0889) time: 2.9572 data: 0.0079 max mem: 33302 +Epoch: [29] [4180/4276] eta: 0:04:41 lr: 1.4387436993633194e-05 loss: 0.0821 (0.0888) time: 2.9556 data: 0.0082 max mem: 33302 +Epoch: [29] [4190/4276] eta: 0:04:12 lr: 1.4384415445533125e-05 loss: 0.0805 (0.0888) time: 2.9564 data: 0.0082 max mem: 33302 +Epoch: [29] [4200/4276] eta: 0:03:43 lr: 1.4381393826909462e-05 loss: 0.0886 (0.0889) time: 2.9570 data: 0.0084 max mem: 33302 +Epoch: [29] 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0.0379 data: 0.0009 max mem: 33302 +Test: [ 1500/21770] eta: 0:13:08 time: 0.0377 data: 0.0009 max mem: 33302 +Test: [ 1600/21770] eta: 0:13:03 time: 0.0377 data: 0.0009 max mem: 33302 +Test: [ 1700/21770] eta: 0:12:58 time: 0.0377 data: 0.0009 max mem: 33302 +Test: [ 1800/21770] eta: 0:12:52 time: 0.0377 data: 0.0009 max mem: 33302 +Test: [ 1900/21770] eta: 0:12:48 time: 0.0377 data: 0.0009 max mem: 33302 +Test: [ 2000/21770] eta: 0:12:43 time: 0.0377 data: 0.0009 max mem: 33302 +Test: [ 2100/21770] eta: 0:12:38 time: 0.0377 data: 0.0009 max mem: 33302 +Test: [ 2200/21770] eta: 0:12:33 time: 0.0377 data: 0.0008 max mem: 33302 +Test: [ 2300/21770] eta: 0:12:29 time: 0.0377 data: 0.0009 max mem: 33302 +Test: [ 2400/21770] eta: 0:12:25 time: 0.0378 data: 0.0009 max mem: 33302 +Test: [ 2500/21770] eta: 0:12:20 time: 0.0378 data: 0.0009 max mem: 33302 +Test: [ 2600/21770] eta: 0:12:16 time: 0.0379 data: 0.0009 max mem: 33302 +Test: [ 2700/21770] eta: 0:12:12 time: 0.0379 data: 0.0009 max 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time: 0.0394 data: 0.0009 max mem: 33302 +Test: [ 5500/21770] eta: 0:10:26 time: 0.0391 data: 0.0009 max mem: 33302 +Test: [ 5600/21770] eta: 0:10:23 time: 0.0389 data: 0.0009 max mem: 33302 +Test: [ 5700/21770] eta: 0:10:19 time: 0.0389 data: 0.0009 max mem: 33302 +Test: [ 5800/21770] eta: 0:10:15 time: 0.0389 data: 0.0009 max mem: 33302 +Test: [ 5900/21770] eta: 0:10:11 time: 0.0387 data: 0.0008 max mem: 33302 +Test: [ 6000/21770] eta: 0:10:07 time: 0.0387 data: 0.0009 max mem: 33302 +Test: [ 6100/21770] eta: 0:10:04 time: 0.0385 data: 0.0008 max mem: 33302 +Test: [ 6200/21770] eta: 0:10:00 time: 0.0381 data: 0.0009 max mem: 33302 +Test: [ 6300/21770] eta: 0:09:56 time: 0.0382 data: 0.0009 max mem: 33302 +Test: [ 6400/21770] eta: 0:09:52 time: 0.0381 data: 0.0009 max mem: 33302 +Test: [ 6500/21770] eta: 0:09:48 time: 0.0382 data: 0.0009 max mem: 33302 +Test: [ 6600/21770] eta: 0:09:44 time: 0.0382 data: 0.0009 max mem: 33302 +Test: [ 6700/21770] eta: 0:09:40 time: 0.0383 data: 0.0009 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time: 0.0381 data: 0.0008 max mem: 33302 +Test: [ 9500/21770] eta: 0:07:51 time: 0.0379 data: 0.0009 max mem: 33302 +Test: [ 9600/21770] eta: 0:07:47 time: 0.0379 data: 0.0009 max mem: 33302 +Test: [ 9700/21770] eta: 0:07:43 time: 0.0379 data: 0.0009 max mem: 33302 +Test: [ 9800/21770] eta: 0:07:39 time: 0.0379 data: 0.0009 max mem: 33302 +Test: [ 9900/21770] eta: 0:07:35 time: 0.0378 data: 0.0009 max mem: 33302 +Test: [10000/21770] eta: 0:07:31 time: 0.0379 data: 0.0009 max mem: 33302 +Test: [10100/21770] eta: 0:07:27 time: 0.0383 data: 0.0009 max mem: 33302 +Test: [10200/21770] eta: 0:07:24 time: 0.0387 data: 0.0009 max mem: 33302 +Test: [10300/21770] eta: 0:07:20 time: 0.0390 data: 0.0009 max mem: 33302 +Test: [10400/21770] eta: 0:07:16 time: 0.0388 data: 0.0009 max mem: 33302 +Test: [10500/21770] eta: 0:07:12 time: 0.0388 data: 0.0009 max mem: 33302 +Test: [10600/21770] eta: 0:07:08 time: 0.0388 data: 0.0009 max mem: 33302 +Test: [10700/21770] eta: 0:07:05 time: 0.0388 data: 0.0009 max mem: 33302 +Test: [10800/21770] eta: 0:07:01 time: 0.0388 data: 0.0009 max mem: 33302 +Test: [10900/21770] eta: 0:06:57 time: 0.0389 data: 0.0009 max mem: 33302 +Test: [11000/21770] eta: 0:06:53 time: 0.0388 data: 0.0009 max mem: 33302 +Test: [11100/21770] eta: 0:06:49 time: 0.0389 data: 0.0009 max mem: 33302 +Test: [11200/21770] eta: 0:06:46 time: 0.0387 data: 0.0009 max mem: 33302 +Test: [11300/21770] eta: 0:06:42 time: 0.0390 data: 0.0009 max mem: 33302 +Test: [11400/21770] eta: 0:06:38 time: 0.0388 data: 0.0009 max mem: 33302 +Test: [11500/21770] eta: 0:06:34 time: 0.0388 data: 0.0009 max mem: 33302 +Test: [11600/21770] eta: 0:06:30 time: 0.0389 data: 0.0009 max mem: 33302 +Test: [11700/21770] eta: 0:06:27 time: 0.0389 data: 0.0009 max mem: 33302 +Test: [11800/21770] eta: 0:06:23 time: 0.0384 data: 0.0009 max mem: 33302 +Test: [11900/21770] eta: 0:06:19 time: 0.0385 data: 0.0009 max mem: 33302 +Test: [12000/21770] eta: 0:06:15 time: 0.0389 data: 0.0009 max mem: 33302 +Test: 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0:05:22 time: 0.0384 data: 0.0009 max mem: 33302 +Test: [13500/21770] eta: 0:05:18 time: 0.0386 data: 0.0009 max mem: 33302 +Test: [13600/21770] eta: 0:05:14 time: 0.0385 data: 0.0009 max mem: 33302 +Test: [13700/21770] eta: 0:05:10 time: 0.0385 data: 0.0009 max mem: 33302 +Test: [13800/21770] eta: 0:05:06 time: 0.0385 data: 0.0009 max mem: 33302 +Test: [13900/21770] eta: 0:05:02 time: 0.0386 data: 0.0009 max mem: 33302 +Test: [14000/21770] eta: 0:04:59 time: 0.0384 data: 0.0009 max mem: 33302 +Test: [14100/21770] eta: 0:04:55 time: 0.0385 data: 0.0009 max mem: 33302 +Test: [14200/21770] eta: 0:04:51 time: 0.0386 data: 0.0009 max mem: 33302 +Test: [14300/21770] eta: 0:04:47 time: 0.0387 data: 0.0009 max mem: 33302 +Test: [14400/21770] eta: 0:04:43 time: 0.0386 data: 0.0009 max mem: 33302 +Test: [14500/21770] eta: 0:04:39 time: 0.0385 data: 0.0009 max mem: 33302 +Test: [14600/21770] eta: 0:04:35 time: 0.0385 data: 0.0009 max mem: 33302 +Test: [14700/21770] eta: 0:04:32 time: 0.0385 data: 0.0009 max mem: 33302 +Test: [14800/21770] eta: 0:04:28 time: 0.0385 data: 0.0009 max mem: 33302 +Test: [14900/21770] eta: 0:04:24 time: 0.0387 data: 0.0009 max mem: 33302 +Test: [15000/21770] eta: 0:04:20 time: 0.0385 data: 0.0009 max mem: 33302 +Test: [15100/21770] eta: 0:04:16 time: 0.0386 data: 0.0009 max mem: 33302 +Test: [15200/21770] eta: 0:04:12 time: 0.0389 data: 0.0009 max mem: 33302 +Test: [15300/21770] eta: 0:04:09 time: 0.0385 data: 0.0009 max mem: 33302 +Test: [15400/21770] eta: 0:04:05 time: 0.0387 data: 0.0009 max mem: 33302 +Test: [15500/21770] eta: 0:04:01 time: 0.0386 data: 0.0009 max mem: 33302 +Test: [15600/21770] eta: 0:03:57 time: 0.0386 data: 0.0009 max mem: 33302 +Test: [15700/21770] eta: 0:03:53 time: 0.0385 data: 0.0009 max mem: 33302 +Test: [15800/21770] eta: 0:03:49 time: 0.0385 data: 0.0009 max mem: 33302 +Test: [15900/21770] eta: 0:03:45 time: 0.0385 data: 0.0009 max mem: 33302 +Test: [16000/21770] eta: 0:03:42 time: 0.0385 data: 0.0009 max mem: 33302 +Test: [16100/21770] eta: 0:03:38 time: 0.0385 data: 0.0009 max mem: 33302 +Test: [16200/21770] eta: 0:03:34 time: 0.0386 data: 0.0009 max mem: 33302 +Test: [16300/21770] eta: 0:03:30 time: 0.0385 data: 0.0009 max mem: 33302 +Test: [16400/21770] eta: 0:03:26 time: 0.0386 data: 0.0009 max mem: 33302 +Test: [16500/21770] eta: 0:03:22 time: 0.0385 data: 0.0009 max mem: 33302 +Test: [16600/21770] eta: 0:03:19 time: 0.0385 data: 0.0009 max mem: 33302 +Test: [16700/21770] eta: 0:03:15 time: 0.0384 data: 0.0009 max mem: 33302 +Test: [16800/21770] eta: 0:03:11 time: 0.0385 data: 0.0009 max mem: 33302 +Test: [16900/21770] eta: 0:03:07 time: 0.0385 data: 0.0009 max mem: 33302 +Test: [17000/21770] eta: 0:03:03 time: 0.0384 data: 0.0009 max mem: 33302 +Test: [17100/21770] eta: 0:02:59 time: 0.0384 data: 0.0009 max mem: 33302 +Test: [17200/21770] eta: 0:02:55 time: 0.0383 data: 0.0009 max mem: 33302 +Test: [17300/21770] eta: 0:02:52 time: 0.0386 data: 0.0009 max mem: 33302 +Test: 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0:01:58 time: 0.0383 data: 0.0009 max mem: 33302 +Test: [18800/21770] eta: 0:01:54 time: 0.0381 data: 0.0009 max mem: 33302 +Test: [18900/21770] eta: 0:01:50 time: 0.0382 data: 0.0008 max mem: 33302 +Test: [19000/21770] eta: 0:01:46 time: 0.0381 data: 0.0009 max mem: 33302 +Test: [19100/21770] eta: 0:01:42 time: 0.0382 data: 0.0009 max mem: 33302 +Test: [19200/21770] eta: 0:01:38 time: 0.0380 data: 0.0009 max mem: 33302 +Test: [19300/21770] eta: 0:01:35 time: 0.0381 data: 0.0009 max mem: 33302 +Test: [19400/21770] eta: 0:01:31 time: 0.0381 data: 0.0009 max mem: 33302 +Test: [19500/21770] eta: 0:01:27 time: 0.0382 data: 0.0008 max mem: 33302 +Test: [19600/21770] eta: 0:01:23 time: 0.0381 data: 0.0009 max mem: 33302 +Test: [19700/21770] eta: 0:01:19 time: 0.0382 data: 0.0009 max mem: 33302 +Test: [19800/21770] eta: 0:01:15 time: 0.0383 data: 0.0008 max mem: 33302 +Test: [19900/21770] eta: 0:01:11 time: 0.0387 data: 0.0008 max mem: 33302 +Test: [20000/21770] eta: 0:01:08 time: 0.0385 data: 0.0008 max mem: 33302 +Test: [20100/21770] eta: 0:01:04 time: 0.0381 data: 0.0009 max mem: 33302 +Test: [20200/21770] eta: 0:01:00 time: 0.0380 data: 0.0009 max mem: 33302 +Test: [20300/21770] eta: 0:00:56 time: 0.0379 data: 0.0009 max mem: 33302 +Test: [20400/21770] eta: 0:00:52 time: 0.0378 data: 0.0009 max mem: 33302 +Test: [20500/21770] eta: 0:00:48 time: 0.0379 data: 0.0009 max mem: 33302 +Test: [20600/21770] eta: 0:00:44 time: 0.0379 data: 0.0009 max mem: 33302 +Test: [20700/21770] eta: 0:00:41 time: 0.0378 data: 0.0009 max mem: 33302 +Test: [20800/21770] eta: 0:00:37 time: 0.0379 data: 0.0009 max mem: 33302 +Test: [20900/21770] eta: 0:00:33 time: 0.0379 data: 0.0009 max mem: 33302 +Test: [21000/21770] eta: 0:00:29 time: 0.0379 data: 0.0009 max mem: 33302 +Test: [21100/21770] eta: 0:00:25 time: 0.0379 data: 0.0009 max mem: 33302 +Test: [21200/21770] eta: 0:00:21 time: 0.0379 data: 0.0009 max mem: 33302 +Test: [21300/21770] eta: 0:00:18 time: 0.0379 data: 0.0009 max mem: 33302 +Test: [21400/21770] eta: 0:00:14 time: 0.0379 data: 0.0009 max mem: 33302 +Test: [21500/21770] eta: 0:00:10 time: 0.0379 data: 0.0009 max mem: 33302 +Test: [21600/21770] eta: 0:00:06 time: 0.0379 data: 0.0009 max mem: 33302 +Test: [21700/21770] eta: 0:00:02 time: 0.0379 data: 0.0009 max mem: 33302 +Test: Total time: 0:13:56 +Final results: +Mean IoU is 16.39 + + precision@0.5 = 3.00 + precision@0.6 = 1.32 + precision@0.7 = 0.40 + precision@0.8 = 0.03 + precision@0.9 = 0.00 + overall IoU = 16.52 + mean IoU = 16.39 + +Mean accuracy for one-to-zero sample is 0.00 + +Average object IoU 0.1638517244923191 +Overall IoU 16.523422241210938 +Better epoch: 29 + +Epoch: [30] [ 0/4276] eta: 6:46:31 lr: 1.4358427218763106e-05 loss: 0.0741 (0.0741) time: 5.7044 data: 2.6220 max mem: 33302 +Epoch: [30] [ 10/4276] eta: 3:47:59 lr: 1.4355404992888e-05 loss: 0.0741 (0.0820) time: 3.2066 data: 0.2457 max mem: 33302 +Epoch: [30] [ 20/4276] eta: 3:38:50 lr: 1.4352382696315067e-05 loss: 0.0895 (0.0888) time: 2.9542 data: 0.0077 max mem: 33302 +Epoch: [30] [ 30/4276] eta: 3:35:20 lr: 1.434936032902612e-05 loss: 0.0895 (0.0879) time: 2.9528 data: 0.0076 max mem: 33302 +Epoch: [30] [ 40/4276] eta: 3:33:25 lr: 1.4346337891002942e-05 loss: 0.0839 (0.0874) time: 2.9578 data: 0.0080 max mem: 33302 +Epoch: [30] [ 50/4276] eta: 3:31:55 lr: 1.4343315382227327e-05 loss: 0.0812 (0.0858) time: 2.9564 data: 0.0079 max mem: 33302 +Epoch: [30] [ 60/4276] eta: 3:30:47 lr: 1.4340292802681052e-05 loss: 0.0817 (0.0863) time: 2.9526 data: 0.0076 max mem: 33302 +Epoch: [30] [ 70/4276] eta: 3:29:50 lr: 1.4337270152345886e-05 loss: 0.0851 (0.0858) time: 2.9540 data: 0.0076 max mem: 33302 +Epoch: [30] [ 80/4276] eta: 3:29:00 lr: 1.433424743120358e-05 loss: 0.0785 (0.0858) time: 2.9548 data: 0.0078 max mem: 33302 +Epoch: [30] [ 90/4276] eta: 3:28:12 lr: 1.433122463923589e-05 loss: 0.0785 (0.0866) time: 2.9519 data: 0.0078 max mem: 33302 +Epoch: [30] [ 100/4276] eta: 3:27:28 lr: 1.4328201776424557e-05 loss: 0.0818 (0.0867) time: 2.9492 data: 0.0077 max mem: 33302 +Epoch: [30] [ 110/4276] eta: 3:26:49 lr: 1.4325178842751319e-05 loss: 0.0831 (0.0870) time: 2.9529 data: 0.0077 max mem: 33302 +Epoch: [30] [ 120/4276] eta: 3:26:10 lr: 1.4322155838197887e-05 loss: 0.0828 (0.0872) time: 2.9539 data: 0.0077 max mem: 33302 +Epoch: [30] [ 130/4276] eta: 3:25:33 lr: 1.4319132762745978e-05 loss: 0.0810 (0.0882) time: 2.9532 data: 0.0077 max mem: 33302 +Epoch: [30] [ 140/4276] eta: 3:24:57 lr: 1.4316109616377305e-05 loss: 0.0801 (0.0872) time: 2.9539 data: 0.0075 max mem: 33302 +Epoch: [30] [ 150/4276] eta: 3:24:23 lr: 1.4313086399073561e-05 loss: 0.0759 (0.0870) time: 2.9549 data: 0.0075 max mem: 33302 +Epoch: [30] [ 160/4276] eta: 3:23:43 lr: 1.4310063110816427e-05 loss: 0.0865 (0.0871) time: 2.9461 data: 0.0078 max mem: 33302 +Epoch: [30] [ 170/4276] eta: 3:22:57 lr: 1.4307039751587586e-05 loss: 0.0871 (0.0871) time: 2.9183 data: 0.0078 max mem: 33302 +Epoch: [30] [ 180/4276] eta: 3:22:14 lr: 1.4304016321368708e-05 loss: 0.0884 (0.0872) time: 2.9034 data: 0.0077 max mem: 33302 +Epoch: [30] [ 190/4276] eta: 3:21:33 lr: 1.4300992820141454e-05 loss: 0.0863 (0.0869) time: 2.9085 data: 0.0076 max mem: 33302 +Epoch: [30] [ 200/4276] eta: 3:20:53 lr: 1.429796924788747e-05 loss: 0.0715 (0.0865) time: 2.9094 data: 0.0078 max mem: 33302 +Epoch: [30] [ 210/4276] eta: 3:20:12 lr: 1.4294945604588396e-05 loss: 0.0755 (0.0866) time: 2.9031 data: 0.0076 max mem: 33302 +Epoch: [30] [ 220/4276] eta: 3:19:36 lr: 1.4291921890225876e-05 loss: 0.0801 (0.0861) time: 2.9092 data: 0.0078 max mem: 33302 +Epoch: [30] [ 230/4276] eta: 3:19:00 lr: 1.4288898104781522e-05 loss: 0.0760 (0.0858) time: 2.9165 data: 0.0080 max mem: 33302 +Epoch: [30] [ 240/4276] eta: 3:18:25 lr: 1.4285874248236955e-05 loss: 0.0744 (0.0860) time: 2.9146 data: 0.0079 max mem: 33302 +Epoch: [30] [ 250/4276] eta: 3:17:48 lr: 1.4282850320573776e-05 loss: 0.0934 (0.0872) time: 2.9118 data: 0.0080 max mem: 33302 +Epoch: [30] [ 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mem: 33302 +Epoch: [30] [ 340/4276] eta: 3:12:42 lr: 1.4255631768228215e-05 loss: 0.0920 (0.0867) time: 2.9026 data: 0.0070 max mem: 33302 +Epoch: [30] [ 350/4276] eta: 3:12:15 lr: 1.4252607128365253e-05 loss: 0.0845 (0.0866) time: 2.9321 data: 0.0075 max mem: 33302 +Epoch: [30] [ 360/4276] eta: 3:11:49 lr: 1.4249582417180742e-05 loss: 0.0864 (0.0870) time: 2.9620 data: 0.0087 max mem: 33302 +Epoch: [30] [ 370/4276] eta: 3:11:21 lr: 1.4246557634656179e-05 loss: 0.0792 (0.0870) time: 2.9607 data: 0.0091 max mem: 33302 +Epoch: [30] [ 380/4276] eta: 3:10:54 lr: 1.4243532780773059e-05 loss: 0.0792 (0.0870) time: 2.9619 data: 0.0085 max mem: 33302 +Epoch: [30] [ 390/4276] eta: 3:10:27 lr: 1.4240507855512844e-05 loss: 0.0900 (0.0871) time: 2.9618 data: 0.0078 max mem: 33302 +Epoch: [30] [ 400/4276] eta: 3:10:00 lr: 1.4237482858857007e-05 loss: 0.0972 (0.0874) time: 2.9612 data: 0.0074 max mem: 33302 +Epoch: [30] [ 410/4276] eta: 3:09:32 lr: 1.4234457790787015e-05 loss: 0.1008 (0.0876) time: 2.9598 data: 0.0074 max mem: 33302 +Epoch: [30] [ 420/4276] eta: 3:09:05 lr: 1.4231432651284316e-05 loss: 0.0979 (0.0876) time: 2.9651 data: 0.0077 max mem: 33302 +Epoch: [30] [ 430/4276] eta: 3:08:37 lr: 1.4228407440330344e-05 loss: 0.0977 (0.0880) time: 2.9630 data: 0.0077 max mem: 33302 +Epoch: [30] [ 440/4276] eta: 3:08:08 lr: 1.4225382157906533e-05 loss: 0.0938 (0.0881) time: 2.9541 data: 0.0074 max mem: 33302 +Epoch: [30] [ 450/4276] eta: 3:07:40 lr: 1.4222356803994311e-05 loss: 0.0854 (0.0882) time: 2.9519 data: 0.0073 max mem: 33302 +Epoch: [30] [ 460/4276] eta: 3:07:12 lr: 1.421933137857509e-05 loss: 0.0854 (0.0880) time: 2.9587 data: 0.0075 max mem: 33302 +Epoch: [30] [ 470/4276] eta: 3:06:40 lr: 1.421630588163027e-05 loss: 0.0801 (0.0880) time: 2.9380 data: 0.0080 max mem: 33302 +Epoch: [30] [ 480/4276] eta: 3:06:12 lr: 1.4213280313141247e-05 loss: 0.0799 (0.0878) time: 2.9327 data: 0.0087 max mem: 33302 +Epoch: [30] [ 490/4276] eta: 3:05:43 lr: 1.421025467308941e-05 loss: 0.0789 (0.0878) time: 2.9567 data: 0.0085 max mem: 33302 +Epoch: [30] [ 500/4276] eta: 3:05:15 lr: 1.4207228961456138e-05 loss: 0.0762 (0.0876) time: 2.9563 data: 0.0079 max mem: 33302 +Epoch: [30] [ 510/4276] eta: 3:04:46 lr: 1.4204203178222786e-05 loss: 0.0761 (0.0877) time: 2.9577 data: 0.0082 max mem: 33302 +Epoch: [30] [ 520/4276] eta: 3:04:18 lr: 1.420117732337072e-05 loss: 0.0850 (0.0878) time: 2.9567 data: 0.0082 max mem: 33302 +Epoch: [30] [ 530/4276] eta: 3:03:49 lr: 1.4198151396881296e-05 loss: 0.1006 (0.0881) time: 2.9552 data: 0.0079 max mem: 33302 +Epoch: [30] [ 540/4276] eta: 3:03:20 lr: 1.4195125398735836e-05 loss: 0.0857 (0.0879) time: 2.9556 data: 0.0082 max mem: 33302 +Epoch: [30] [ 550/4276] eta: 3:02:52 lr: 1.4192099328915683e-05 loss: 0.0834 (0.0880) time: 2.9558 data: 0.0085 max mem: 33302 +Epoch: [30] [ 560/4276] eta: 3:02:23 lr: 1.4189073187402156e-05 loss: 0.0863 (0.0880) time: 2.9556 data: 0.0081 max mem: 33302 +Epoch: [30] [ 570/4276] eta: 3:01:54 lr: 1.4186046974176564e-05 loss: 0.0776 (0.0879) time: 2.9565 data: 0.0079 max mem: 33302 +Epoch: [30] [ 580/4276] eta: 3:01:25 lr: 1.4183020689220209e-05 loss: 0.0776 (0.0880) time: 2.9558 data: 0.0083 max mem: 33302 +Epoch: [30] [ 590/4276] eta: 3:00:54 lr: 1.4179994332514383e-05 loss: 0.0881 (0.0882) time: 2.9304 data: 0.0078 max mem: 33302 +Epoch: [30] [ 600/4276] eta: 3:00:23 lr: 1.4176967904040372e-05 loss: 0.0779 (0.0882) time: 2.9127 data: 0.0075 max mem: 33302 +Epoch: [30] [ 610/4276] eta: 2:59:51 lr: 1.4173941403779456e-05 loss: 0.0850 (0.0882) time: 2.9139 data: 0.0076 max mem: 33302 +Epoch: [30] [ 620/4276] eta: 2:59:19 lr: 1.4170914831712886e-05 loss: 0.0850 (0.0881) time: 2.9068 data: 0.0075 max mem: 33302 +Epoch: [30] [ 630/4276] eta: 2:58:48 lr: 1.4167888187821927e-05 loss: 0.0804 (0.0882) time: 2.9040 data: 0.0074 max mem: 33302 +Epoch: [30] [ 640/4276] eta: 2:58:16 lr: 1.4164861472087823e-05 loss: 0.0808 (0.0881) time: 2.9082 data: 0.0074 max mem: 33302 +Epoch: [30] [ 650/4276] eta: 2:57:47 lr: 1.4161834684491814e-05 loss: 0.0808 (0.0882) time: 2.9254 data: 0.0082 max mem: 33302 +Epoch: [30] [ 660/4276] eta: 2:57:16 lr: 1.4158807825015122e-05 loss: 0.0827 (0.0884) time: 2.9255 data: 0.0084 max mem: 33302 +Epoch: [30] [ 670/4276] eta: 2:56:47 lr: 1.4155780893638968e-05 loss: 0.0860 (0.0883) time: 2.9346 data: 0.0087 max mem: 33302 +Epoch: [30] [ 680/4276] eta: 2:56:18 lr: 1.4152753890344558e-05 loss: 0.0860 (0.0883) time: 2.9546 data: 0.0091 max mem: 33302 +Epoch: [30] [ 690/4276] eta: 2:55:50 lr: 1.4149726815113104e-05 loss: 0.0867 (0.0882) time: 2.9534 data: 0.0082 max mem: 33302 +Epoch: [30] [ 700/4276] eta: 2:55:21 lr: 1.4146699667925778e-05 loss: 0.0758 (0.0882) time: 2.9559 data: 0.0078 max mem: 33302 +Epoch: [30] [ 710/4276] eta: 2:54:52 lr: 1.4143672448763768e-05 loss: 0.0791 (0.0882) time: 2.9574 data: 0.0078 max mem: 33302 +Epoch: [30] [ 720/4276] eta: 2:54:23 lr: 1.4140645157608245e-05 loss: 0.0822 (0.0880) time: 2.9560 data: 0.0078 max mem: 33302 +Epoch: [30] [ 730/4276] eta: 2:53:55 lr: 1.413761779444038e-05 loss: 0.0741 (0.0879) time: 2.9555 data: 0.0078 max mem: 33302 +Epoch: [30] [ 740/4276] eta: 2:53:26 lr: 1.4134590359241313e-05 loss: 0.0750 (0.0878) time: 2.9578 data: 0.0078 max mem: 33302 +Epoch: [30] [ 750/4276] eta: 2:52:57 lr: 1.4131562851992186e-05 loss: 0.0757 (0.0877) time: 2.9581 data: 0.0078 max mem: 33302 +Epoch: [30] [ 760/4276] eta: 2:52:28 lr: 1.412853527267414e-05 loss: 0.0757 (0.0879) time: 2.9552 data: 0.0080 max mem: 33302 +Epoch: [30] [ 770/4276] eta: 2:51:59 lr: 1.4125507621268305e-05 loss: 0.0858 (0.0879) time: 2.9550 data: 0.0082 max mem: 33302 +Epoch: [30] [ 780/4276] eta: 2:51:31 lr: 1.412247989775578e-05 loss: 0.0734 (0.0877) time: 2.9586 data: 0.0083 max mem: 33302 +Epoch: [30] [ 790/4276] eta: 2:51:01 lr: 1.4119452102117678e-05 loss: 0.0807 (0.0878) time: 2.9512 data: 0.0085 max mem: 33302 +Epoch: [30] [ 800/4276] eta: 2:50:33 lr: 1.4116424234335094e-05 loss: 0.0899 (0.0878) time: 2.9515 data: 0.0083 max mem: 33302 +Epoch: [30] [ 810/4276] eta: 2:50:04 lr: 1.411339629438912e-05 loss: 0.0899 (0.0878) time: 2.9578 data: 0.0079 max mem: 33302 +Epoch: [30] [ 820/4276] eta: 2:49:35 lr: 1.4110368282260821e-05 loss: 0.0851 (0.0878) time: 2.9549 data: 0.0081 max mem: 33302 +Epoch: [30] [ 830/4276] eta: 2:49:06 lr: 1.4107340197931277e-05 loss: 0.0858 (0.0879) time: 2.9548 data: 0.0080 max mem: 33302 +Epoch: [30] [ 840/4276] eta: 2:48:37 lr: 1.410431204138154e-05 loss: 0.0865 (0.0879) time: 2.9534 data: 0.0076 max mem: 33302 +Epoch: [30] [ 850/4276] eta: 2:48:07 lr: 1.4101283812592656e-05 loss: 0.0801 (0.0879) time: 2.9532 data: 0.0076 max mem: 33302 +Epoch: [30] [ 860/4276] eta: 2:47:38 lr: 1.4098255511545664e-05 loss: 0.0825 (0.0879) time: 2.9547 data: 0.0080 max mem: 33302 +Epoch: [30] [ 870/4276] eta: 2:47:10 lr: 1.4095227138221598e-05 loss: 0.0868 (0.0879) time: 2.9573 data: 0.0080 max mem: 33302 +Epoch: [30] [ 880/4276] eta: 2:46:41 lr: 1.409219869260148e-05 loss: 0.0877 (0.0881) time: 2.9575 data: 0.0076 max mem: 33302 +Epoch: [30] [ 890/4276] eta: 2:46:11 lr: 1.408917017466631e-05 loss: 0.1017 (0.0882) time: 2.9548 data: 0.0078 max mem: 33302 +Epoch: [30] [ 900/4276] eta: 2:45:42 lr: 1.4086141584397095e-05 loss: 0.0970 (0.0882) time: 2.9501 data: 0.0082 max mem: 33302 +Epoch: [30] [ 910/4276] eta: 2:45:13 lr: 1.4083112921774826e-05 loss: 0.0878 (0.0882) time: 2.9511 data: 0.0082 max mem: 33302 +Epoch: [30] [ 920/4276] eta: 2:44:44 lr: 1.4080084186780493e-05 loss: 0.0865 (0.0882) time: 2.9557 data: 0.0077 max mem: 33302 +Epoch: [30] [ 930/4276] eta: 2:44:15 lr: 1.4077055379395054e-05 loss: 0.0835 (0.0883) time: 2.9554 data: 0.0076 max mem: 33302 +Epoch: [30] [ 940/4276] eta: 2:43:46 lr: 1.4074026499599477e-05 loss: 0.0835 (0.0883) time: 2.9539 data: 0.0079 max mem: 33302 +Epoch: [30] [ 950/4276] eta: 2:43:16 lr: 1.4070997547374715e-05 loss: 0.0888 (0.0884) time: 2.9530 data: 0.0079 max mem: 33302 +Epoch: [30] [ 960/4276] eta: 2:42:47 lr: 1.4067968522701722e-05 loss: 0.0877 (0.0884) time: 2.9531 data: 0.0074 max mem: 33303 +Epoch: [30] [ 970/4276] eta: 2:42:19 lr: 1.4064939425561413e-05 loss: 0.0865 (0.0885) time: 2.9600 data: 0.0073 max mem: 33303 +Epoch: [30] [ 980/4276] eta: 2:41:49 lr: 1.4061910255934724e-05 loss: 0.0865 (0.0885) time: 2.9615 data: 0.0076 max mem: 33303 +Epoch: [30] [ 990/4276] eta: 2:41:20 lr: 1.405888101380257e-05 loss: 0.0833 (0.0884) time: 2.9529 data: 0.0075 max mem: 33303 +Epoch: [30] [1000/4276] eta: 2:40:51 lr: 1.4055851699145856e-05 loss: 0.0834 (0.0885) time: 2.9499 data: 0.0072 max mem: 33303 +Epoch: [30] [1010/4276] eta: 2:40:22 lr: 1.405282231194547e-05 loss: 0.0893 (0.0885) time: 2.9531 data: 0.0074 max mem: 33303 +Epoch: [30] [1020/4276] eta: 2:39:52 lr: 1.4049792852182307e-05 loss: 0.0868 (0.0885) time: 2.9560 data: 0.0075 max mem: 33303 +Epoch: [30] [1030/4276] eta: 2:39:23 lr: 1.4046763319837238e-05 loss: 0.0893 (0.0885) time: 2.9564 data: 0.0074 max mem: 33303 +Epoch: [30] [1040/4276] eta: 2:38:54 lr: 1.4043733714891138e-05 loss: 0.0861 (0.0884) time: 2.9588 data: 0.0072 max mem: 33303 +Epoch: [30] [1050/4276] eta: 2:38:25 lr: 1.4040704037324853e-05 loss: 0.0835 (0.0885) time: 2.9569 data: 0.0073 max mem: 33303 +Epoch: [30] [1060/4276] eta: 2:37:56 lr: 1.4037674287119234e-05 loss: 0.0878 (0.0885) time: 2.9545 data: 0.0075 max mem: 33303 +Epoch: [30] [1070/4276] eta: 2:37:27 lr: 1.4034644464255123e-05 loss: 0.0888 (0.0886) time: 2.9563 data: 0.0074 max mem: 33303 +Epoch: [30] [1080/4276] eta: 2:36:57 lr: 1.403161456871335e-05 loss: 0.0842 (0.0886) time: 2.9553 data: 0.0072 max mem: 33303 +Epoch: [30] [1090/4276] eta: 2:36:28 lr: 1.4028584600474724e-05 loss: 0.0950 (0.0887) time: 2.9557 data: 0.0074 max mem: 33303 +Epoch: [30] [1100/4276] eta: 2:35:59 lr: 1.4025554559520057e-05 loss: 0.0950 (0.0888) time: 2.9554 data: 0.0077 max mem: 33303 +Epoch: [30] [1110/4276] eta: 2:35:29 lr: 1.4022524445830151e-05 loss: 0.0908 (0.0890) time: 2.9485 data: 0.0083 max mem: 33303 +Epoch: [30] [1120/4276] eta: 2:35:00 lr: 1.4019494259385802e-05 loss: 0.0875 (0.0890) time: 2.9495 data: 0.0078 max mem: 33303 +Epoch: [30] [1130/4276] eta: 2:34:31 lr: 1.4016464000167775e-05 loss: 0.0826 (0.0889) time: 2.9541 data: 0.0068 max mem: 33303 +Epoch: [30] [1140/4276] eta: 2:34:02 lr: 1.401343366815685e-05 loss: 0.0858 (0.0889) time: 2.9530 data: 0.0068 max mem: 33303 +Epoch: [30] [1150/4276] eta: 2:33:32 lr: 1.401040326333379e-05 loss: 0.0877 (0.0889) time: 2.9530 data: 0.0069 max mem: 33303 +Epoch: [30] [1160/4276] eta: 2:33:03 lr: 1.4007372785679335e-05 loss: 0.0883 (0.0890) time: 2.9512 data: 0.0068 max mem: 33303 +Epoch: [30] [1170/4276] eta: 2:32:33 lr: 1.4004342235174231e-05 loss: 0.0912 (0.0890) time: 2.9488 data: 0.0070 max mem: 33303 +Epoch: [30] [1180/4276] eta: 2:32:04 lr: 1.4001311611799212e-05 loss: 0.0875 (0.0890) time: 2.9499 data: 0.0070 max mem: 33303 +Epoch: [30] [1190/4276] eta: 2:31:35 lr: 1.3998280915535e-05 loss: 0.0849 (0.0890) time: 2.9482 data: 0.0074 max mem: 33303 +Epoch: [30] [1200/4276] eta: 2:31:05 lr: 1.3995250146362302e-05 loss: 0.0805 (0.0890) time: 2.9487 data: 0.0076 max mem: 33303 +Epoch: [30] [1210/4276] eta: 2:30:36 lr: 1.3992219304261822e-05 loss: 0.0710 (0.0888) time: 2.9535 data: 0.0075 max mem: 33303 +Epoch: [30] [1220/4276] eta: 2:30:06 lr: 1.3989188389214254e-05 loss: 0.0779 (0.0889) time: 2.9472 data: 0.0076 max mem: 33303 +Epoch: [30] [1230/4276] eta: 2:29:37 lr: 1.3986157401200283e-05 loss: 0.0871 (0.0889) time: 2.9482 data: 0.0071 max mem: 33303 +Epoch: [30] [1240/4276] eta: 2:29:08 lr: 1.3983126340200573e-05 loss: 0.0871 (0.0889) time: 2.9566 data: 0.0071 max mem: 33303 +Epoch: [30] [1250/4276] eta: 2:28:39 lr: 1.3980095206195792e-05 loss: 0.0854 (0.0889) time: 2.9571 data: 0.0073 max mem: 33303 +Epoch: [30] [1260/4276] eta: 2:28:09 lr: 1.3977063999166596e-05 loss: 0.0779 (0.0888) time: 2.9548 data: 0.0076 max mem: 33303 +Epoch: [30] [1270/4276] eta: 2:27:40 lr: 1.397403271909363e-05 loss: 0.0776 (0.0887) time: 2.9521 data: 0.0077 max mem: 33303 +Epoch: [30] [1280/4276] eta: 2:27:11 lr: 1.3971001365957517e-05 loss: 0.0839 (0.0888) time: 2.9542 data: 0.0073 max mem: 33303 +Epoch: [30] [1290/4276] eta: 2:26:41 lr: 1.3967969939738887e-05 loss: 0.0839 (0.0888) time: 2.9429 data: 0.0076 max mem: 33303 +Epoch: [30] [1300/4276] eta: 2:26:10 lr: 1.3964938440418353e-05 loss: 0.0802 (0.0888) time: 2.9170 data: 0.0077 max mem: 33303 +Epoch: [30] [1310/4276] eta: 2:25:40 lr: 1.3961906867976532e-05 loss: 0.0780 (0.0887) time: 2.9135 data: 0.0081 max mem: 33303 +Epoch: [30] [1320/4276] eta: 2:25:10 lr: 1.3958875222393997e-05 loss: 0.0795 (0.0888) time: 2.9252 data: 0.0083 max mem: 33303 +Epoch: [30] [1330/4276] eta: 2:24:40 lr: 1.3955843503651342e-05 loss: 0.0823 (0.0887) time: 2.9226 data: 0.0084 max mem: 33303 +Epoch: [30] [1340/4276] eta: 2:24:10 lr: 1.3952811711729144e-05 loss: 0.0735 (0.0887) time: 2.9105 data: 0.0079 max mem: 33303 +Epoch: [30] [1350/4276] eta: 2:23:40 lr: 1.3949779846607971e-05 loss: 0.0823 (0.0887) time: 2.9226 data: 0.0071 max mem: 33303 +Epoch: [30] [1360/4276] eta: 2:23:11 lr: 1.3946747908268368e-05 loss: 0.0824 (0.0887) time: 2.9416 data: 0.0082 max mem: 33303 +Epoch: [30] [1370/4276] eta: 2:22:41 lr: 1.3943715896690885e-05 loss: 0.0872 (0.0887) time: 2.9500 data: 0.0087 max mem: 33303 +Epoch: [30] [1380/4276] eta: 2:22:12 lr: 1.3940683811856056e-05 loss: 0.0872 (0.0887) time: 2.9594 data: 0.0079 max mem: 33303 +Epoch: [30] [1390/4276] eta: 2:21:42 lr: 1.3937651653744416e-05 loss: 0.0942 (0.0888) time: 2.9446 data: 0.0079 max mem: 33303 +Epoch: [30] [1400/4276] eta: 2:21:13 lr: 1.3934619422336464e-05 loss: 0.0942 (0.0889) time: 2.9365 data: 0.0082 max mem: 33303 +Epoch: [30] [1410/4276] eta: 2:20:44 lr: 1.3931587117612713e-05 loss: 0.0838 (0.0889) time: 2.9496 data: 0.0074 max mem: 33303 +Epoch: [30] [1420/4276] eta: 2:20:13 lr: 1.3928554739553662e-05 loss: 0.0783 (0.0888) time: 2.9302 data: 0.0080 max mem: 33303 +Epoch: [30] [1430/4276] eta: 2:19:43 lr: 1.39255222881398e-05 loss: 0.0733 (0.0888) time: 2.9144 data: 0.0085 max mem: 33303 +Epoch: [30] [1440/4276] eta: 2:19:14 lr: 1.392248976335159e-05 loss: 0.0886 (0.0887) time: 2.9388 data: 0.0080 max mem: 33303 +Epoch: [30] [1450/4276] eta: 2:18:45 lr: 1.3919457165169506e-05 loss: 0.0822 (0.0887) time: 2.9542 data: 0.0077 max mem: 33303 +Epoch: [30] [1460/4276] eta: 2:18:16 lr: 1.391642449357401e-05 loss: 0.0822 (0.0887) time: 2.9556 data: 0.0072 max mem: 33303 +Epoch: [30] [1470/4276] eta: 2:17:47 lr: 1.3913391748545531e-05 loss: 0.0829 (0.0887) time: 2.9661 data: 0.0074 max mem: 33303 +Epoch: [30] [1480/4276] eta: 2:17:18 lr: 1.391035893006452e-05 loss: 0.0865 (0.0887) time: 2.9691 data: 0.0080 max mem: 33303 +Epoch: [30] [1490/4276] eta: 2:16:48 lr: 1.3907326038111396e-05 loss: 0.0852 (0.0886) time: 2.9520 data: 0.0082 max mem: 33303 +Epoch: [30] [1500/4276] eta: 2:16:18 lr: 1.3904293072666585e-05 loss: 0.0747 (0.0886) time: 2.9197 data: 0.0082 max mem: 33303 +Epoch: [30] [1510/4276] eta: 2:15:47 lr: 1.390126003371048e-05 loss: 0.0758 (0.0885) time: 2.9005 data: 0.0083 max mem: 33303 +Epoch: [30] [1520/4276] eta: 2:15:17 lr: 1.3898226921223484e-05 loss: 0.0776 (0.0885) time: 2.9007 data: 0.0078 max mem: 33303 +Epoch: [30] [1530/4276] eta: 2:14:47 lr: 1.389519373518598e-05 loss: 0.0800 (0.0884) time: 2.8983 data: 0.0074 max mem: 33303 +Epoch: [30] [1540/4276] eta: 2:14:16 lr: 1.3892160475578355e-05 loss: 0.0853 (0.0884) time: 2.8972 data: 0.0075 max mem: 33303 +Epoch: [30] [1550/4276] eta: 2:13:46 lr: 1.388912714238096e-05 loss: 0.0752 (0.0884) time: 2.8985 data: 0.0073 max mem: 33303 +Epoch: [30] [1560/4276] eta: 2:13:17 lr: 1.388609373557416e-05 loss: 0.0790 (0.0884) time: 2.9148 data: 0.0079 max mem: 33303 +Epoch: [30] [1570/4276] eta: 2:12:47 lr: 1.3883060255138297e-05 loss: 0.0790 (0.0884) time: 2.9408 data: 0.0085 max mem: 33303 +Epoch: [30] [1580/4276] eta: 2:12:18 lr: 1.3880026701053719e-05 loss: 0.0695 (0.0883) time: 2.9536 data: 0.0084 max mem: 33303 +Epoch: [30] [1590/4276] eta: 2:11:49 lr: 1.3876993073300737e-05 loss: 0.0782 (0.0884) time: 2.9515 data: 0.0083 max mem: 33303 +Epoch: [30] [1600/4276] eta: 2:11:19 lr: 1.387395937185967e-05 loss: 0.0885 (0.0883) time: 2.9448 data: 0.0084 max mem: 33303 +Epoch: [30] [1610/4276] eta: 2:10:50 lr: 1.3870925596710831e-05 loss: 0.0812 (0.0883) time: 2.9467 data: 0.0084 max mem: 33303 +Epoch: [30] [1620/4276] eta: 2:10:20 lr: 1.3867891747834519e-05 loss: 0.0806 (0.0883) time: 2.9532 data: 0.0083 max mem: 33303 +Epoch: [30] [1630/4276] eta: 2:09:51 lr: 1.3864857825211008e-05 loss: 0.0806 (0.0883) time: 2.9552 data: 0.0083 max mem: 33303 +Epoch: [30] [1640/4276] eta: 2:09:22 lr: 1.3861823828820578e-05 loss: 0.0794 (0.0883) time: 2.9547 data: 0.0085 max mem: 33303 +Epoch: [30] [1650/4276] eta: 2:08:53 lr: 1.3858789758643497e-05 loss: 0.0792 (0.0883) time: 2.9537 data: 0.0089 max mem: 33303 +Epoch: [30] [1660/4276] eta: 2:08:23 lr: 1.3855755614660026e-05 loss: 0.0796 (0.0882) time: 2.9552 data: 0.0089 max mem: 33303 +Epoch: [30] [1670/4276] eta: 2:07:54 lr: 1.3852721396850402e-05 loss: 0.0820 (0.0882) time: 2.9560 data: 0.0088 max mem: 33303 +Epoch: [30] [1680/4276] eta: 2:07:25 lr: 1.3849687105194861e-05 loss: 0.0820 (0.0882) time: 2.9547 data: 0.0090 max mem: 33303 +Epoch: [30] [1690/4276] eta: 2:06:55 lr: 1.3846652739673633e-05 loss: 0.0758 (0.0881) time: 2.9533 data: 0.0088 max mem: 33303 +Epoch: [30] [1700/4276] eta: 2:06:26 lr: 1.3843618300266935e-05 loss: 0.0775 (0.0881) time: 2.9500 data: 0.0086 max mem: 33303 +Epoch: [30] [1710/4276] eta: 2:05:57 lr: 1.3840583786954966e-05 loss: 0.0794 (0.0880) time: 2.9489 data: 0.0090 max mem: 33303 +Epoch: [30] [1720/4276] eta: 2:05:27 lr: 1.3837549199717926e-05 loss: 0.0782 (0.0880) time: 2.9502 data: 0.0092 max mem: 33303 +Epoch: [30] [1730/4276] eta: 2:04:58 lr: 1.3834514538535995e-05 loss: 0.0763 (0.0880) time: 2.9505 data: 0.0088 max mem: 33303 +Epoch: [30] [1740/4276] eta: 2:04:29 lr: 1.3831479803389358e-05 loss: 0.0765 (0.0879) time: 2.9518 data: 0.0086 max mem: 33303 +Epoch: [30] [1750/4276] eta: 2:03:59 lr: 1.382844499425817e-05 loss: 0.0748 (0.0878) time: 2.9536 data: 0.0087 max mem: 33303 +Epoch: [30] [1760/4276] eta: 2:03:30 lr: 1.3825410111122587e-05 loss: 0.0747 (0.0878) time: 2.9545 data: 0.0090 max mem: 33303 +Epoch: [30] [1770/4276] eta: 2:03:00 lr: 1.3822375153962758e-05 loss: 0.0753 (0.0878) time: 2.9528 data: 0.0088 max mem: 33303 +Epoch: [30] [1780/4276] eta: 2:02:31 lr: 1.381934012275881e-05 loss: 0.0839 (0.0878) time: 2.9541 data: 0.0089 max mem: 33303 +Epoch: [30] [1790/4276] eta: 2:02:02 lr: 1.3816305017490873e-05 loss: 0.0885 (0.0878) time: 2.9565 data: 0.0093 max mem: 33303 +Epoch: [30] [1800/4276] eta: 2:01:33 lr: 1.3813269838139061e-05 loss: 0.0867 (0.0878) time: 2.9554 data: 0.0092 max mem: 33303 +Epoch: [30] [1810/4276] eta: 2:01:03 lr: 1.3810234584683479e-05 loss: 0.0827 (0.0878) time: 2.9548 data: 0.0091 max mem: 33303 +Epoch: [30] [1820/4276] eta: 2:00:34 lr: 1.3807199257104215e-05 loss: 0.0874 (0.0879) time: 2.9537 data: 0.0090 max mem: 33303 +Epoch: [30] [1830/4276] eta: 2:00:05 lr: 1.380416385538135e-05 loss: 0.0874 (0.0878) time: 2.9529 data: 0.0092 max mem: 33303 +Epoch: [30] [1840/4276] eta: 1:59:35 lr: 1.3801128379494966e-05 loss: 0.0701 (0.0877) time: 2.9535 data: 0.0093 max mem: 33303 +Epoch: [30] [1850/4276] eta: 1:59:06 lr: 1.3798092829425125e-05 loss: 0.0750 (0.0878) time: 2.9555 data: 0.0091 max mem: 33303 +Epoch: [30] [1860/4276] eta: 1:58:37 lr: 1.3795057205151871e-05 loss: 0.0861 (0.0877) time: 2.9570 data: 0.0090 max mem: 33303 +Epoch: [30] [1870/4276] eta: 1:58:07 lr: 1.3792021506655253e-05 loss: 0.0887 (0.0878) time: 2.9562 data: 0.0092 max mem: 33303 +Epoch: [30] [1880/4276] eta: 1:57:38 lr: 1.3788985733915299e-05 loss: 0.0856 (0.0877) time: 2.9565 data: 0.0088 max mem: 33303 +Epoch: [30] [1890/4276] eta: 1:57:09 lr: 1.3785949886912041e-05 loss: 0.0826 (0.0877) time: 2.9551 data: 0.0085 max mem: 33303 +Epoch: [30] [1900/4276] eta: 1:56:39 lr: 1.378291396562548e-05 loss: 0.0877 (0.0877) time: 2.9562 data: 0.0087 max mem: 33303 +Epoch: [30] [1910/4276] eta: 1:56:10 lr: 1.3779877970035618e-05 loss: 0.0745 (0.0877) time: 2.9571 data: 0.0089 max mem: 33303 +Epoch: [30] [1920/4276] eta: 1:55:41 lr: 1.377684190012245e-05 loss: 0.0705 (0.0876) time: 2.9551 data: 0.0087 max mem: 33303 +Epoch: [30] [1930/4276] eta: 1:55:11 lr: 1.377380575586596e-05 loss: 0.0670 (0.0876) time: 2.9551 data: 0.0085 max mem: 33303 +Epoch: [30] [1940/4276] eta: 1:54:42 lr: 1.3770769537246109e-05 loss: 0.0679 (0.0875) time: 2.9489 data: 0.0084 max mem: 33303 +Epoch: [30] [1950/4276] eta: 1:54:12 lr: 1.376773324424286e-05 loss: 0.0839 (0.0876) time: 2.9328 data: 0.0086 max mem: 33303 +Epoch: [30] [1960/4276] eta: 1:53:42 lr: 1.3764696876836167e-05 loss: 0.0821 (0.0875) time: 2.9128 data: 0.0085 max mem: 33303 +Epoch: [30] [1970/4276] eta: 1:53:12 lr: 1.3761660435005972e-05 loss: 0.0748 (0.0875) time: 2.9071 data: 0.0081 max mem: 33303 +Epoch: [30] [1980/4276] eta: 1:52:42 lr: 1.3758623918732194e-05 loss: 0.0827 (0.0875) time: 2.9076 data: 0.0077 max mem: 33303 +Epoch: [30] [1990/4276] eta: 1:52:12 lr: 1.3755587327994756e-05 loss: 0.0799 (0.0875) time: 2.9021 data: 0.0073 max mem: 33303 +Epoch: [30] [2000/4276] eta: 1:51:42 lr: 1.375255066277357e-05 loss: 0.0827 (0.0875) time: 2.9088 data: 0.0075 max mem: 33303 +Epoch: [30] [2010/4276] eta: 1:51:13 lr: 1.3749513923048538e-05 loss: 0.0901 (0.0876) time: 2.9091 data: 0.0079 max mem: 33303 +Epoch: [30] [2020/4276] eta: 1:50:43 lr: 1.3746477108799532e-05 loss: 0.0982 (0.0876) time: 2.9018 data: 0.0075 max mem: 33303 +Epoch: [30] [2030/4276] eta: 1:50:13 lr: 1.3743440220006443e-05 loss: 0.0846 (0.0876) time: 2.9071 data: 0.0073 max mem: 33303 +Epoch: [30] [2040/4276] eta: 1:49:43 lr: 1.3740403256649134e-05 loss: 0.0789 (0.0875) time: 2.9162 data: 0.0079 max mem: 33303 +Epoch: [30] [2050/4276] eta: 1:49:13 lr: 1.3737366218707468e-05 loss: 0.0815 (0.0875) time: 2.9254 data: 0.0084 max mem: 33303 +Epoch: [30] [2060/4276] eta: 1:48:44 lr: 1.3734329106161276e-05 loss: 0.0863 (0.0875) time: 2.9293 data: 0.0085 max mem: 33303 +Epoch: [30] [2070/4276] eta: 1:48:14 lr: 1.3731291918990404e-05 loss: 0.0827 (0.0875) time: 2.9375 data: 0.0088 max mem: 33303 +Epoch: [30] [2080/4276] eta: 1:47:45 lr: 1.3728254657174686e-05 loss: 0.0847 (0.0876) time: 2.9403 data: 0.0089 max mem: 33303 +Epoch: [30] [2090/4276] eta: 1:47:16 lr: 1.3725217320693918e-05 loss: 0.0864 (0.0876) time: 2.9440 data: 0.0083 max mem: 33303 +Epoch: [30] [2100/4276] eta: 1:46:46 lr: 1.3722179909527915e-05 loss: 0.0824 (0.0876) time: 2.9541 data: 0.0075 max mem: 33303 +Epoch: [30] [2110/4276] eta: 1:46:17 lr: 1.3719142423656473e-05 loss: 0.0780 (0.0875) time: 2.9534 data: 0.0072 max mem: 33303 +Epoch: [30] [2120/4276] eta: 1:45:47 lr: 1.3716104863059376e-05 loss: 0.0689 (0.0874) time: 2.9509 data: 0.0072 max mem: 33303 +Epoch: [30] [2130/4276] eta: 1:45:18 lr: 1.3713067227716389e-05 loss: 0.0687 (0.0874) time: 2.9502 data: 0.0070 max mem: 33303 +Epoch: [30] [2140/4276] eta: 1:44:49 lr: 1.371002951760728e-05 loss: 0.0749 (0.0873) time: 2.9499 data: 0.0070 max mem: 33303 +Epoch: [30] [2150/4276] eta: 1:44:19 lr: 1.3706991732711802e-05 loss: 0.0794 (0.0873) time: 2.9502 data: 0.0072 max mem: 33303 +Epoch: [30] [2160/4276] eta: 1:43:50 lr: 1.3703953873009704e-05 loss: 0.0797 (0.0873) time: 2.9508 data: 0.0077 max mem: 33303 +Epoch: [30] [2170/4276] eta: 1:43:21 lr: 1.3700915938480705e-05 loss: 0.0820 (0.0873) time: 2.9539 data: 0.0079 max mem: 33303 +Epoch: [30] [2180/4276] eta: 1:42:51 lr: 1.3697877929104528e-05 loss: 0.0906 (0.0873) time: 2.9554 data: 0.0077 max mem: 33303 +Epoch: [30] [2190/4276] eta: 1:42:22 lr: 1.3694839844860889e-05 loss: 0.0881 (0.0873) time: 2.9533 data: 0.0075 max mem: 33303 +Epoch: [30] [2200/4276] eta: 1:41:53 lr: 1.3691801685729488e-05 loss: 0.0866 (0.0874) time: 2.9524 data: 0.0073 max mem: 33303 +Epoch: [30] [2210/4276] eta: 1:41:23 lr: 1.368876345169001e-05 loss: 0.0866 (0.0874) time: 2.9520 data: 0.0074 max mem: 33303 +Epoch: [30] [2220/4276] eta: 1:40:53 lr: 1.3685725142722133e-05 loss: 0.0830 (0.0874) time: 2.9315 data: 0.0080 max mem: 33303 +Epoch: [30] [2230/4276] eta: 1:40:24 lr: 1.368268675880553e-05 loss: 0.0830 (0.0874) time: 2.9213 data: 0.0083 max mem: 33303 +Epoch: [30] [2240/4276] eta: 1:39:54 lr: 1.3679648299919862e-05 loss: 0.0765 (0.0873) time: 2.9440 data: 0.0079 max mem: 33303 +Epoch: [30] [2250/4276] eta: 1:39:25 lr: 1.3676609766044765e-05 loss: 0.0696 (0.0872) time: 2.9558 data: 0.0077 max mem: 33303 +Epoch: [30] [2260/4276] eta: 1:38:56 lr: 1.3673571157159882e-05 loss: 0.0724 (0.0872) time: 2.9549 data: 0.0075 max mem: 33303 +Epoch: [30] [2270/4276] eta: 1:38:26 lr: 1.3670532473244841e-05 loss: 0.0778 (0.0872) time: 2.9491 data: 0.0074 max mem: 33303 +Epoch: [30] [2280/4276] eta: 1:37:57 lr: 1.366749371427926e-05 loss: 0.0765 (0.0872) time: 2.9499 data: 0.0073 max mem: 33303 +Epoch: [30] [2290/4276] eta: 1:37:27 lr: 1.3664454880242736e-05 loss: 0.0765 (0.0872) time: 2.9330 data: 0.0079 max mem: 33303 +Epoch: [30] [2300/4276] eta: 1:36:57 lr: 1.3661415971114868e-05 loss: 0.0826 (0.0872) time: 2.9059 data: 0.0085 max mem: 33303 +Epoch: [30] [2310/4276] eta: 1:36:28 lr: 1.3658376986875238e-05 loss: 0.0934 (0.0872) time: 2.9017 data: 0.0080 max mem: 33303 +Epoch: [30] [2320/4276] eta: 1:35:58 lr: 1.3655337927503428e-05 loss: 0.0851 (0.0873) time: 2.9000 data: 0.0077 max mem: 33303 +Epoch: [30] [2330/4276] eta: 1:35:28 lr: 1.3652298792978987e-05 loss: 0.0845 (0.0873) time: 2.9088 data: 0.0085 max mem: 33303 +Epoch: [30] [2340/4276] eta: 1:34:59 lr: 1.3649259583281473e-05 loss: 0.0823 (0.0872) time: 2.9363 data: 0.0091 max mem: 33303 +Epoch: [30] [2350/4276] eta: 1:34:29 lr: 1.364622029839043e-05 loss: 0.0787 (0.0872) time: 2.9542 data: 0.0081 max mem: 33303 +Epoch: [30] [2360/4276] eta: 1:34:00 lr: 1.3643180938285391e-05 loss: 0.0784 (0.0872) time: 2.9551 data: 0.0074 max mem: 33303 +Epoch: [30] [2370/4276] eta: 1:33:31 lr: 1.3640141502945866e-05 loss: 0.0847 (0.0872) time: 2.9541 data: 0.0073 max mem: 33303 +Epoch: [30] [2380/4276] eta: 1:33:01 lr: 1.3637101992351373e-05 loss: 0.0899 (0.0873) time: 2.9531 data: 0.0076 max mem: 33303 +Epoch: [30] [2390/4276] eta: 1:32:32 lr: 1.3634062406481413e-05 loss: 0.0984 (0.0873) time: 2.9532 data: 0.0076 max mem: 33303 +Epoch: [30] [2400/4276] eta: 1:32:03 lr: 1.3631022745315463e-05 loss: 0.0881 (0.0873) time: 2.9484 data: 0.0075 max mem: 33303 +Epoch: [30] [2410/4276] eta: 1:31:33 lr: 1.362798300883301e-05 loss: 0.0828 (0.0873) time: 2.9454 data: 0.0079 max mem: 33303 +Epoch: [30] [2420/4276] eta: 1:31:04 lr: 1.3624943197013516e-05 loss: 0.0801 (0.0873) time: 2.9507 data: 0.0078 max mem: 33303 +Epoch: [30] [2430/4276] eta: 1:30:34 lr: 1.3621903309836442e-05 loss: 0.0868 (0.0873) time: 2.9569 data: 0.0076 max mem: 33303 +Epoch: [30] [2440/4276] eta: 1:30:05 lr: 1.3618863347281228e-05 loss: 0.0815 (0.0873) time: 2.9568 data: 0.0075 max mem: 33303 +Epoch: [30] [2450/4276] eta: 1:29:36 lr: 1.361582330932731e-05 loss: 0.0815 (0.0873) time: 2.9526 data: 0.0074 max mem: 33303 +Epoch: [30] [2460/4276] eta: 1:29:06 lr: 1.3612783195954118e-05 loss: 0.0837 (0.0873) time: 2.9533 data: 0.0079 max mem: 33303 +Epoch: [30] [2470/4276] eta: 1:28:37 lr: 1.3609743007141062e-05 loss: 0.0848 (0.0873) time: 2.9549 data: 0.0078 max mem: 33303 +Epoch: [30] [2480/4276] eta: 1:28:08 lr: 1.360670274286754e-05 loss: 0.0848 (0.0873) time: 2.9523 data: 0.0074 max mem: 33303 +Epoch: [30] [2490/4276] eta: 1:27:38 lr: 1.3603662403112947e-05 loss: 0.0825 (0.0873) time: 2.9467 data: 0.0075 max mem: 33303 +Epoch: [30] [2500/4276] eta: 1:27:08 lr: 1.3600621987856663e-05 loss: 0.0846 (0.0873) time: 2.9328 data: 0.0079 max mem: 33303 +Epoch: [30] [2510/4276] eta: 1:26:39 lr: 1.3597581497078066e-05 loss: 0.0873 (0.0873) time: 2.9384 data: 0.0076 max mem: 33303 +Epoch: [30] [2520/4276] eta: 1:26:10 lr: 1.3594540930756506e-05 loss: 0.0873 (0.0873) time: 2.9529 data: 0.0071 max mem: 33303 +Epoch: [30] [2530/4276] eta: 1:25:40 lr: 1.359150028887133e-05 loss: 0.0727 (0.0873) time: 2.9524 data: 0.0072 max mem: 33303 +Epoch: [30] [2540/4276] eta: 1:25:11 lr: 1.3588459571401885e-05 loss: 0.0779 (0.0873) time: 2.9528 data: 0.0070 max mem: 33303 +Epoch: [30] [2550/4276] eta: 1:24:42 lr: 1.3585418778327499e-05 loss: 0.0767 (0.0872) time: 2.9519 data: 0.0070 max mem: 33303 +Epoch: [30] [2560/4276] eta: 1:24:12 lr: 1.358237790962748e-05 loss: 0.0716 (0.0872) time: 2.9514 data: 0.0071 max mem: 33303 +Epoch: [30] [2570/4276] eta: 1:23:43 lr: 1.3579336965281136e-05 loss: 0.0798 (0.0872) time: 2.9519 data: 0.0072 max mem: 33303 +Epoch: [30] [2580/4276] eta: 1:23:13 lr: 1.3576295945267765e-05 loss: 0.0848 (0.0872) time: 2.9525 data: 0.0072 max mem: 33303 +Epoch: [30] [2590/4276] eta: 1:22:44 lr: 1.3573254849566652e-05 loss: 0.0795 (0.0872) time: 2.9519 data: 0.0070 max mem: 33303 +Epoch: [30] [2600/4276] eta: 1:22:15 lr: 1.3570213678157064e-05 loss: 0.0775 (0.0872) time: 2.9528 data: 0.0071 max mem: 33303 +Epoch: [30] [2610/4276] eta: 1:21:45 lr: 1.3567172431018268e-05 loss: 0.0810 (0.0872) time: 2.9530 data: 0.0070 max mem: 33303 +Epoch: [30] [2620/4276] eta: 1:21:16 lr: 1.3564131108129513e-05 loss: 0.0869 (0.0872) time: 2.9521 data: 0.0070 max mem: 33303 +Epoch: [30] [2630/4276] eta: 1:20:46 lr: 1.3561089709470046e-05 loss: 0.0797 (0.0871) time: 2.9511 data: 0.0071 max mem: 33303 +Epoch: [30] [2640/4276] eta: 1:20:17 lr: 1.3558048235019089e-05 loss: 0.0782 (0.0871) time: 2.9514 data: 0.0072 max mem: 33303 +Epoch: [30] [2650/4276] eta: 1:19:48 lr: 1.355500668475586e-05 loss: 0.0821 (0.0871) time: 2.9537 data: 0.0074 max mem: 33303 +Epoch: [30] [2660/4276] eta: 1:19:18 lr: 1.3551965058659577e-05 loss: 0.0782 (0.0871) time: 2.9533 data: 0.0075 max mem: 33303 +Epoch: [30] [2670/4276] eta: 1:18:49 lr: 1.3548923356709428e-05 loss: 0.0845 (0.0871) time: 2.9525 data: 0.0075 max mem: 33303 +Epoch: [30] [2680/4276] eta: 1:18:19 lr: 1.35458815788846e-05 loss: 0.0847 (0.0871) time: 2.9576 data: 0.0078 max mem: 33303 +Epoch: [30] [2690/4276] eta: 1:17:50 lr: 1.3542839725164271e-05 loss: 0.0808 (0.0871) time: 2.9596 data: 0.0080 max mem: 33303 +Epoch: [30] [2700/4276] eta: 1:17:21 lr: 1.3539797795527612e-05 loss: 0.0730 (0.0870) time: 2.9544 data: 0.0080 max mem: 33303 +Epoch: [30] [2710/4276] eta: 1:16:51 lr: 1.3536755789953761e-05 loss: 0.0792 (0.0870) time: 2.9535 data: 0.0079 max mem: 33303 +Epoch: [30] [2720/4276] eta: 1:16:22 lr: 1.353371370842187e-05 loss: 0.0783 (0.0869) time: 2.9549 data: 0.0080 max mem: 33303 +Epoch: [30] [2730/4276] eta: 1:15:52 lr: 1.353067155091107e-05 loss: 0.0804 (0.0869) time: 2.9542 data: 0.0079 max mem: 33303 +Epoch: [30] [2740/4276] eta: 1:15:23 lr: 1.3527629317400486e-05 loss: 0.0844 (0.0869) time: 2.9535 data: 0.0079 max mem: 33303 +Epoch: [30] [2750/4276] eta: 1:14:54 lr: 1.352458700786922e-05 loss: 0.0798 (0.0869) time: 2.9533 data: 0.0080 max mem: 33303 +Epoch: [30] [2760/4276] eta: 1:14:24 lr: 1.352154462229637e-05 loss: 0.0733 (0.0869) time: 2.9450 data: 0.0081 max mem: 33303 +Epoch: [30] [2770/4276] eta: 1:13:55 lr: 1.3518502160661032e-05 loss: 0.0835 (0.0869) time: 2.9457 data: 0.0082 max mem: 33303 +Epoch: [30] [2780/4276] eta: 1:13:25 lr: 1.3515459622942277e-05 loss: 0.0866 (0.0869) time: 2.9546 data: 0.0077 max mem: 33303 +Epoch: [30] [2790/4276] eta: 1:12:56 lr: 1.3512417009119175e-05 loss: 0.0854 (0.0869) time: 2.9531 data: 0.0074 max mem: 33303 +Epoch: [30] [2800/4276] eta: 1:12:27 lr: 1.3509374319170773e-05 loss: 0.0818 (0.0869) time: 2.9547 data: 0.0078 max mem: 33303 +Epoch: [30] [2810/4276] eta: 1:11:57 lr: 1.3506331553076119e-05 loss: 0.0690 (0.0868) time: 2.9549 data: 0.0081 max mem: 33303 +Epoch: [30] [2820/4276] eta: 1:11:28 lr: 1.3503288710814254e-05 loss: 0.0714 (0.0868) time: 2.9529 data: 0.0079 max mem: 33303 +Epoch: [30] [2830/4276] eta: 1:10:58 lr: 1.3500245792364185e-05 loss: 0.0863 (0.0868) time: 2.9538 data: 0.0077 max mem: 33303 +Epoch: [30] [2840/4276] eta: 1:10:29 lr: 1.3497202797704934e-05 loss: 0.0863 (0.0868) time: 2.9581 data: 0.0081 max mem: 33303 +Epoch: [30] [2850/4276] eta: 1:10:00 lr: 1.3494159726815492e-05 loss: 0.0917 (0.0869) time: 2.9508 data: 0.0087 max mem: 33303 +Epoch: [30] [2860/4276] eta: 1:09:30 lr: 1.3491116579674859e-05 loss: 0.0793 (0.0869) time: 2.9488 data: 0.0082 max mem: 33303 +Epoch: [30] [2870/4276] eta: 1:09:01 lr: 1.3488073356262002e-05 loss: 0.0738 (0.0868) time: 2.9606 data: 0.0074 max mem: 33303 +Epoch: [30] [2880/4276] eta: 1:08:31 lr: 1.348503005655589e-05 loss: 0.0811 (0.0868) time: 2.9569 data: 0.0074 max mem: 33303 +Epoch: [30] [2890/4276] eta: 1:08:02 lr: 1.348198668053548e-05 loss: 0.0805 (0.0869) time: 2.9536 data: 0.0078 max mem: 33303 +Epoch: [30] [2900/4276] eta: 1:07:33 lr: 1.3478943228179722e-05 loss: 0.0784 (0.0868) time: 2.9558 data: 0.0076 max mem: 33303 +Epoch: [30] [2910/4276] eta: 1:07:03 lr: 1.347589969946754e-05 loss: 0.0808 (0.0868) time: 2.9532 data: 0.0070 max mem: 33303 +Epoch: [30] [2920/4276] eta: 1:06:34 lr: 1.3472856094377857e-05 loss: 0.0872 (0.0869) time: 2.9528 data: 0.0069 max mem: 33303 +Epoch: [30] [2930/4276] eta: 1:06:04 lr: 1.3469812412889585e-05 loss: 0.0918 (0.0869) time: 2.9532 data: 0.0070 max mem: 33303 +Epoch: [30] [2940/4276] eta: 1:05:35 lr: 1.3466768654981635e-05 loss: 0.0844 (0.0869) time: 2.9526 data: 0.0070 max mem: 33303 +Epoch: [30] [2950/4276] eta: 1:05:05 lr: 1.3463724820632879e-05 loss: 0.0879 (0.0869) time: 2.9521 data: 0.0070 max mem: 33303 +Epoch: [30] [2960/4276] eta: 1:04:36 lr: 1.3460680909822202e-05 loss: 0.0889 (0.0869) time: 2.9542 data: 0.0070 max mem: 33303 +Epoch: [30] [2970/4276] eta: 1:04:07 lr: 1.3457636922528474e-05 loss: 0.0889 (0.0869) time: 2.9541 data: 0.0069 max mem: 33303 +Epoch: [30] [2980/4276] eta: 1:03:37 lr: 1.3454592858730545e-05 loss: 0.0810 (0.0869) time: 2.9509 data: 0.0070 max mem: 33303 +Epoch: [30] [2990/4276] eta: 1:03:08 lr: 1.3451548718407258e-05 loss: 0.0810 (0.0869) time: 2.9508 data: 0.0070 max mem: 33303 +Epoch: [30] [3000/4276] eta: 1:02:38 lr: 1.3448504501537452e-05 loss: 0.0803 (0.0869) time: 2.9458 data: 0.0069 max mem: 33303 +Epoch: [30] [3010/4276] eta: 1:02:09 lr: 1.344546020809995e-05 loss: 0.0818 (0.0868) time: 2.9222 data: 0.0078 max mem: 33303 +Epoch: [30] [3020/4276] eta: 1:01:39 lr: 1.3442415838073552e-05 loss: 0.0818 (0.0868) time: 2.9286 data: 0.0085 max mem: 33303 +Epoch: [30] [3030/4276] eta: 1:01:10 lr: 1.3439371391437067e-05 loss: 0.0757 (0.0868) time: 2.9561 data: 0.0083 max mem: 33303 +Epoch: [30] [3040/4276] eta: 1:00:40 lr: 1.3436326868169277e-05 loss: 0.0962 (0.0869) time: 2.9555 data: 0.0084 max mem: 33303 +Epoch: [30] [3050/4276] eta: 1:00:11 lr: 1.343328226824897e-05 loss: 0.0962 (0.0869) time: 2.9551 data: 0.0084 max mem: 33303 +Epoch: [30] [3060/4276] eta: 0:59:41 lr: 1.3430237591654899e-05 loss: 0.0729 (0.0868) time: 2.9554 data: 0.0089 max mem: 33303 +Epoch: [30] [3070/4276] eta: 0:59:12 lr: 1.342719283836582e-05 loss: 0.0722 (0.0868) time: 2.9552 data: 0.0089 max mem: 33303 +Epoch: [30] [3080/4276] eta: 0:58:43 lr: 1.3424148008360485e-05 loss: 0.0766 (0.0867) time: 2.9557 data: 0.0087 max mem: 33303 +Epoch: [30] [3090/4276] eta: 0:58:13 lr: 1.3421103101617624e-05 loss: 0.0766 (0.0868) time: 2.9551 data: 0.0087 max mem: 33303 +Epoch: [30] [3100/4276] eta: 0:57:44 lr: 1.3418058118115947e-05 loss: 0.0735 (0.0867) time: 2.9546 data: 0.0088 max mem: 33303 +Epoch: [30] [3110/4276] eta: 0:57:14 lr: 1.3415013057834175e-05 loss: 0.0712 (0.0867) time: 2.9544 data: 0.0087 max mem: 33303 +Epoch: [30] [3120/4276] eta: 0:56:45 lr: 1.3411967920751003e-05 loss: 0.0730 (0.0867) time: 2.9559 data: 0.0088 max mem: 33303 +Epoch: [30] [3130/4276] eta: 0:56:16 lr: 1.3408922706845123e-05 loss: 0.0834 (0.0867) time: 2.9568 data: 0.0088 max mem: 33303 +Epoch: [30] [3140/4276] eta: 0:55:46 lr: 1.3405877416095196e-05 loss: 0.0842 (0.0866) time: 2.9564 data: 0.0086 max mem: 33303 +Epoch: [30] [3150/4276] eta: 0:55:17 lr: 1.3402832048479903e-05 loss: 0.0772 (0.0866) time: 2.9551 data: 0.0083 max mem: 33303 +Epoch: [30] [3160/4276] eta: 0:54:47 lr: 1.3399786603977885e-05 loss: 0.0787 (0.0866) time: 2.9544 data: 0.0082 max mem: 33303 +Epoch: [30] [3170/4276] eta: 0:54:18 lr: 1.3396741082567796e-05 loss: 0.0793 (0.0866) time: 2.9533 data: 0.0082 max mem: 33303 +Epoch: [30] [3180/4276] eta: 0:53:48 lr: 1.3393695484228253e-05 loss: 0.0835 (0.0866) time: 2.9538 data: 0.0084 max mem: 33303 +Epoch: [30] [3190/4276] eta: 0:53:19 lr: 1.339064980893788e-05 loss: 0.0840 (0.0867) time: 2.9557 data: 0.0085 max mem: 33303 +Epoch: [30] [3200/4276] eta: 0:52:50 lr: 1.3387604056675288e-05 loss: 0.0791 (0.0866) time: 2.9521 data: 0.0084 max mem: 33303 +Epoch: [30] [3210/4276] eta: 0:52:20 lr: 1.3384558227419077e-05 loss: 0.0736 (0.0866) time: 2.9524 data: 0.0086 max mem: 33303 +Epoch: [30] [3220/4276] eta: 0:51:51 lr: 1.338151232114782e-05 loss: 0.0775 (0.0866) time: 2.9548 data: 0.0085 max mem: 33303 +Epoch: [30] [3230/4276] eta: 0:51:21 lr: 1.3378466337840098e-05 loss: 0.0820 (0.0866) time: 2.9543 data: 0.0081 max mem: 33303 +Epoch: [30] [3240/4276] eta: 0:50:52 lr: 1.3375420277474474e-05 loss: 0.0854 (0.0866) time: 2.9548 data: 0.0080 max mem: 33303 +Epoch: [30] [3250/4276] eta: 0:50:22 lr: 1.3372374140029501e-05 loss: 0.0854 (0.0866) time: 2.9554 data: 0.0081 max mem: 33303 +Epoch: [30] [3260/4276] eta: 0:49:53 lr: 1.3369327925483707e-05 loss: 0.0863 (0.0866) time: 2.9552 data: 0.0081 max mem: 33303 +Epoch: [30] [3270/4276] eta: 0:49:23 lr: 1.3366281633815631e-05 loss: 0.0849 (0.0866) time: 2.9535 data: 0.0080 max mem: 33303 +Epoch: [30] [3280/4276] eta: 0:48:54 lr: 1.336323526500379e-05 loss: 0.0841 (0.0866) time: 2.9532 data: 0.0080 max mem: 33303 +Epoch: [30] [3290/4276] eta: 0:48:25 lr: 1.3360188819026684e-05 loss: 0.0919 (0.0867) time: 2.9533 data: 0.0080 max mem: 33303 +Epoch: [30] [3300/4276] eta: 0:47:55 lr: 1.3357142295862804e-05 loss: 0.0999 (0.0867) time: 2.9542 data: 0.0080 max mem: 33303 +Epoch: [30] [3310/4276] eta: 0:47:26 lr: 1.335409569549064e-05 loss: 0.0956 (0.0867) time: 2.9393 data: 0.0088 max mem: 33303 +Epoch: [30] [3320/4276] eta: 0:46:56 lr: 1.3351049017888664e-05 loss: 0.1004 (0.0868) time: 2.9154 data: 0.0090 max mem: 33303 +Epoch: [30] [3330/4276] eta: 0:46:27 lr: 1.3348002263035325e-05 loss: 0.0862 (0.0868) time: 2.9265 data: 0.0089 max mem: 33303 +Epoch: [30] [3340/4276] eta: 0:45:57 lr: 1.3344955430909078e-05 loss: 0.0862 (0.0868) time: 2.9500 data: 0.0089 max mem: 33303 +Epoch: [30] [3350/4276] eta: 0:45:28 lr: 1.3341908521488359e-05 loss: 0.0876 (0.0868) time: 2.9546 data: 0.0084 max mem: 33303 +Epoch: [30] [3360/4276] eta: 0:44:58 lr: 1.3338861534751595e-05 loss: 0.0776 (0.0868) time: 2.9565 data: 0.0086 max mem: 33303 +Epoch: [30] [3370/4276] eta: 0:44:29 lr: 1.3335814470677197e-05 loss: 0.0820 (0.0868) time: 2.9568 data: 0.0086 max mem: 33303 +Epoch: [30] [3380/4276] eta: 0:43:59 lr: 1.3332767329243562e-05 loss: 0.0838 (0.0868) time: 2.9546 data: 0.0084 max mem: 33303 +Epoch: [30] [3390/4276] eta: 0:43:30 lr: 1.3329720110429086e-05 loss: 0.0770 (0.0868) time: 2.9542 data: 0.0084 max mem: 33303 +Epoch: [30] [3400/4276] eta: 0:43:01 lr: 1.3326672814212158e-05 loss: 0.0825 (0.0868) time: 2.9545 data: 0.0086 max mem: 33303 +Epoch: [30] [3410/4276] eta: 0:42:31 lr: 1.3323625440571125e-05 loss: 0.0862 (0.0869) time: 2.9552 data: 0.0086 max mem: 33303 +Epoch: [30] [3420/4276] eta: 0:42:02 lr: 1.3320577989484351e-05 loss: 0.0872 (0.0869) time: 2.9520 data: 0.0088 max mem: 33303 +Epoch: [30] [3430/4276] eta: 0:41:32 lr: 1.3317530460930186e-05 loss: 0.0966 (0.0869) time: 2.9515 data: 0.0088 max mem: 33303 +Epoch: [30] [3440/4276] eta: 0:41:03 lr: 1.3314482854886962e-05 loss: 0.0815 (0.0869) time: 2.9571 data: 0.0086 max mem: 33303 +Epoch: [30] [3450/4276] eta: 0:40:33 lr: 1.3311435171332991e-05 loss: 0.0848 (0.0870) time: 2.9569 data: 0.0086 max mem: 33303 +Epoch: [30] [3460/4276] eta: 0:40:04 lr: 1.330838741024659e-05 loss: 0.1021 (0.0870) time: 2.9543 data: 0.0085 max mem: 33303 +Epoch: [30] [3470/4276] eta: 0:39:34 lr: 1.3305339571606054e-05 loss: 0.0859 (0.0870) time: 2.9537 data: 0.0084 max mem: 33303 +Epoch: [30] [3480/4276] eta: 0:39:05 lr: 1.3302291655389676e-05 loss: 0.0845 (0.0870) time: 2.9535 data: 0.0086 max mem: 33303 +Epoch: [30] [3490/4276] eta: 0:38:36 lr: 1.3299243661575723e-05 loss: 0.0825 (0.0870) time: 2.9553 data: 0.0083 max mem: 33303 +Epoch: [30] [3500/4276] eta: 0:38:06 lr: 1.3296195590142457e-05 loss: 0.0825 (0.0870) time: 2.9613 data: 0.0079 max mem: 33303 +Epoch: [30] [3510/4276] eta: 0:37:37 lr: 1.3293147441068135e-05 loss: 0.0780 (0.0870) time: 2.9601 data: 0.0083 max mem: 33303 +Epoch: [30] [3520/4276] eta: 0:37:07 lr: 1.3290099214331e-05 loss: 0.0780 (0.0870) time: 2.9547 data: 0.0087 max mem: 33303 +Epoch: [30] [3530/4276] eta: 0:36:38 lr: 1.3287050909909269e-05 loss: 0.0838 (0.0870) time: 2.9533 data: 0.0083 max mem: 33303 +Epoch: [30] [3540/4276] eta: 0:36:08 lr: 1.3284002527781167e-05 loss: 0.0859 (0.0870) time: 2.9530 data: 0.0080 max mem: 33303 +Epoch: [30] [3550/4276] eta: 0:35:39 lr: 1.3280954067924895e-05 loss: 0.0859 (0.0870) time: 2.9548 data: 0.0081 max mem: 33303 +Epoch: [30] [3560/4276] eta: 0:35:09 lr: 1.3277905530318654e-05 loss: 0.0868 (0.0870) time: 2.9534 data: 0.0081 max mem: 33303 +Epoch: [30] [3570/4276] eta: 0:34:40 lr: 1.3274856914940614e-05 loss: 0.0868 (0.0870) time: 2.9511 data: 0.0082 max mem: 33303 +Epoch: [30] [3580/4276] eta: 0:34:10 lr: 1.3271808221768952e-05 loss: 0.0786 (0.0870) time: 2.9513 data: 0.0081 max mem: 33303 +Epoch: [30] [3590/4276] eta: 0:33:41 lr: 1.326875945078183e-05 loss: 0.0782 (0.0870) time: 2.9540 data: 0.0080 max mem: 33303 +Epoch: [30] [3600/4276] eta: 0:33:12 lr: 1.3265710601957382e-05 loss: 0.0751 (0.0870) time: 2.9543 data: 0.0082 max mem: 33303 +Epoch: [30] [3610/4276] eta: 0:32:42 lr: 1.3262661675273752e-05 loss: 0.0796 (0.0870) time: 2.9543 data: 0.0083 max mem: 33303 +Epoch: [30] [3620/4276] eta: 0:32:13 lr: 1.325961267070906e-05 loss: 0.0778 (0.0869) time: 2.9560 data: 0.0080 max mem: 33303 +Epoch: [30] [3630/4276] eta: 0:31:43 lr: 1.3256563588241422e-05 loss: 0.0820 (0.0870) time: 2.9547 data: 0.0080 max mem: 33303 +Epoch: [30] [3640/4276] eta: 0:31:14 lr: 1.3253514427848931e-05 loss: 0.0852 (0.0869) time: 2.9528 data: 0.0080 max mem: 33303 +Epoch: [30] [3650/4276] eta: 0:30:44 lr: 1.3250465189509675e-05 loss: 0.0810 (0.0869) time: 2.9527 data: 0.0080 max mem: 33303 +Epoch: [30] [3660/4276] eta: 0:30:15 lr: 1.3247415873201734e-05 loss: 0.0808 (0.0869) time: 2.9543 data: 0.0081 max mem: 33303 +Epoch: [30] [3670/4276] eta: 0:29:45 lr: 1.3244366478903177e-05 loss: 0.0774 (0.0869) time: 2.9546 data: 0.0081 max mem: 33303 +Epoch: [30] [3680/4276] eta: 0:29:16 lr: 1.3241317006592044e-05 loss: 0.0774 (0.0869) time: 2.9538 data: 0.0080 max mem: 33303 +Epoch: [30] [3690/4276] eta: 0:28:46 lr: 1.3238267456246384e-05 loss: 0.0839 (0.0869) time: 2.9543 data: 0.0080 max mem: 33303 +Epoch: [30] [3700/4276] eta: 0:28:17 lr: 1.323521782784422e-05 loss: 0.0889 (0.0869) time: 2.9540 data: 0.0079 max mem: 33303 +Epoch: [30] [3710/4276] eta: 0:27:48 lr: 1.3232168121363581e-05 loss: 0.0781 (0.0869) time: 2.9528 data: 0.0079 max mem: 33303 +Epoch: [30] [3720/4276] eta: 0:27:18 lr: 1.3229118336782456e-05 loss: 0.0727 (0.0869) time: 2.9534 data: 0.0080 max mem: 33303 +Epoch: [30] [3730/4276] eta: 0:26:49 lr: 1.3226068474078848e-05 loss: 0.0919 (0.0869) time: 2.9539 data: 0.0080 max mem: 33303 +Epoch: [30] [3740/4276] eta: 0:26:19 lr: 1.3223018533230738e-05 loss: 0.0806 (0.0869) time: 2.9523 data: 0.0080 max mem: 33303 +Epoch: [30] [3750/4276] eta: 0:25:50 lr: 1.3219968514216097e-05 loss: 0.0785 (0.0869) time: 2.9527 data: 0.0080 max mem: 33303 +Epoch: [30] [3760/4276] eta: 0:25:20 lr: 1.3216918417012878e-05 loss: 0.0765 (0.0868) time: 2.9582 data: 0.0081 max mem: 33303 +Epoch: [30] [3770/4276] eta: 0:24:51 lr: 1.3213868241599028e-05 loss: 0.0728 (0.0868) time: 2.9605 data: 0.0083 max mem: 33303 +Epoch: [30] [3780/4276] eta: 0:24:21 lr: 1.3210817987952481e-05 loss: 0.0777 (0.0868) time: 2.9565 data: 0.0085 max mem: 33303 +Epoch: [30] [3790/4276] eta: 0:23:52 lr: 1.320776765605117e-05 loss: 0.0806 (0.0868) time: 2.9546 data: 0.0082 max mem: 33303 +Epoch: [30] [3800/4276] eta: 0:23:22 lr: 1.320471724587299e-05 loss: 0.0806 (0.0868) time: 2.9546 data: 0.0080 max mem: 33303 +Epoch: [30] [3810/4276] eta: 0:22:53 lr: 1.3201666757395841e-05 loss: 0.0774 (0.0868) time: 2.9541 data: 0.0080 max mem: 33303 +Epoch: [30] [3820/4276] eta: 0:22:23 lr: 1.3198616190597619e-05 loss: 0.0750 (0.0867) time: 2.9550 data: 0.0080 max mem: 33303 +Epoch: [30] [3830/4276] eta: 0:21:54 lr: 1.3195565545456196e-05 loss: 0.0733 (0.0867) time: 2.9557 data: 0.0080 max mem: 33303 +Epoch: [30] [3840/4276] eta: 0:21:25 lr: 1.3192514821949426e-05 loss: 0.0744 (0.0867) time: 2.9584 data: 0.0080 max mem: 33303 +Epoch: [30] [3850/4276] eta: 0:20:55 lr: 1.3189464020055166e-05 loss: 0.0647 (0.0867) time: 2.9478 data: 0.0081 max mem: 33303 +Epoch: [30] [3860/4276] eta: 0:20:26 lr: 1.3186413139751255e-05 loss: 0.0896 (0.0867) time: 2.9448 data: 0.0085 max mem: 33303 +Epoch: [30] [3870/4276] eta: 0:19:56 lr: 1.3183362181015524e-05 loss: 0.0896 (0.0867) time: 2.9549 data: 0.0086 max mem: 33303 +Epoch: [30] [3880/4276] eta: 0:19:27 lr: 1.318031114382578e-05 loss: 0.0801 (0.0867) time: 2.9550 data: 0.0082 max mem: 33303 +Epoch: [30] [3890/4276] eta: 0:18:57 lr: 1.3177260028159826e-05 loss: 0.0817 (0.0867) time: 2.9539 data: 0.0080 max mem: 33303 +Epoch: [30] [3900/4276] eta: 0:18:28 lr: 1.3174208833995464e-05 loss: 0.0834 (0.0867) time: 2.9534 data: 0.0080 max mem: 33303 +Epoch: [30] [3910/4276] eta: 0:17:58 lr: 1.3171157561310454e-05 loss: 0.0822 (0.0866) time: 2.9546 data: 0.0080 max mem: 33303 +Epoch: [30] [3920/4276] eta: 0:17:29 lr: 1.3168106210082575e-05 loss: 0.0713 (0.0867) time: 2.9540 data: 0.0082 max mem: 33303 +Epoch: [30] [3930/4276] eta: 0:16:59 lr: 1.3165054780289581e-05 loss: 0.0771 (0.0867) time: 2.9544 data: 0.0082 max mem: 33303 +Epoch: [30] [3940/4276] eta: 0:16:30 lr: 1.3162003271909221e-05 loss: 0.0771 (0.0866) time: 2.9530 data: 0.0080 max mem: 33303 +Epoch: [30] [3950/4276] eta: 0:16:00 lr: 1.315895168491921e-05 loss: 0.0763 (0.0866) time: 2.9538 data: 0.0080 max mem: 33303 +Epoch: [30] [3960/4276] eta: 0:15:31 lr: 1.3155900019297273e-05 loss: 0.0855 (0.0866) time: 2.9540 data: 0.0082 max mem: 33303 +Epoch: [30] [3970/4276] eta: 0:15:01 lr: 1.3152848275021124e-05 loss: 0.0880 (0.0866) time: 2.9508 data: 0.0084 max mem: 33303 +Epoch: [30] [3980/4276] eta: 0:14:32 lr: 1.3149796452068453e-05 loss: 0.0766 (0.0866) time: 2.9578 data: 0.0082 max mem: 33303 +Epoch: [30] [3990/4276] eta: 0:14:02 lr: 1.3146744550416937e-05 loss: 0.0879 (0.0866) time: 2.9512 data: 0.0080 max mem: 33303 +Epoch: [30] [4000/4276] eta: 0:13:33 lr: 1.3143692570044253e-05 loss: 0.0871 (0.0866) time: 2.9328 data: 0.0090 max mem: 33303 +Epoch: [30] [4010/4276] eta: 0:13:04 lr: 1.3140640510928053e-05 loss: 0.0833 (0.0866) time: 2.9313 data: 0.0093 max mem: 33303 +Epoch: [30] [4020/4276] eta: 0:12:34 lr: 1.3137588373045997e-05 loss: 0.0834 (0.0866) time: 2.9447 data: 0.0079 max mem: 33303 +Epoch: [30] [4030/4276] eta: 0:12:05 lr: 1.3134536156375702e-05 loss: 0.0790 (0.0866) time: 2.9534 data: 0.0072 max mem: 33303 +Epoch: [30] [4040/4276] eta: 0:11:35 lr: 1.3131483860894797e-05 loss: 0.0772 (0.0866) time: 2.9530 data: 0.0070 max mem: 33303 +Epoch: [30] [4050/4276] eta: 0:11:06 lr: 1.3128431486580891e-05 loss: 0.0775 (0.0866) time: 2.9465 data: 0.0070 max mem: 33303 +Epoch: [30] [4060/4276] eta: 0:10:36 lr: 1.312537903341159e-05 loss: 0.0775 (0.0866) time: 2.9456 data: 0.0071 max mem: 33303 +Epoch: [30] [4070/4276] eta: 0:10:07 lr: 1.3122326501364462e-05 loss: 0.0864 (0.0866) time: 2.9516 data: 0.0072 max mem: 33303 +Epoch: [30] [4080/4276] eta: 0:09:37 lr: 1.3119273890417095e-05 loss: 0.0829 (0.0866) time: 2.9517 data: 0.0070 max mem: 33303 +Epoch: [30] [4090/4276] eta: 0:09:08 lr: 1.3116221200547043e-05 loss: 0.0829 (0.0866) time: 2.9534 data: 0.0072 max mem: 33303 +Epoch: [30] [4100/4276] eta: 0:08:38 lr: 1.3113168431731862e-05 loss: 0.0895 (0.0867) time: 2.9517 data: 0.0072 max mem: 33303 +Epoch: [30] [4110/4276] eta: 0:08:09 lr: 1.3110115583949082e-05 loss: 0.0869 (0.0867) time: 2.9525 data: 0.0070 max mem: 33303 +Epoch: [30] [4120/4276] eta: 0:07:39 lr: 1.3107062657176226e-05 loss: 0.0914 (0.0867) time: 2.9529 data: 0.0071 max mem: 33303 +Epoch: [30] [4130/4276] eta: 0:07:10 lr: 1.3104009651390811e-05 loss: 0.0784 (0.0867) time: 2.9536 data: 0.0075 max mem: 33303 +Epoch: [30] [4140/4276] eta: 0:06:40 lr: 1.3100956566570342e-05 loss: 0.0765 (0.0867) time: 2.9531 data: 0.0076 max mem: 33303 +Epoch: [30] [4150/4276] eta: 0:06:11 lr: 1.3097903402692294e-05 loss: 0.0747 (0.0867) time: 2.9522 data: 0.0072 max mem: 33303 +Epoch: [30] [4160/4276] eta: 0:05:41 lr: 1.3094850159734148e-05 loss: 0.0769 (0.0867) time: 2.9529 data: 0.0071 max mem: 33303 +Epoch: [30] [4170/4276] eta: 0:05:12 lr: 1.309179683767337e-05 loss: 0.0902 (0.0867) time: 2.9514 data: 0.0070 max mem: 33303 +Epoch: [30] [4180/4276] eta: 0:04:42 lr: 1.3088743436487416e-05 loss: 0.0889 (0.0867) time: 2.9504 data: 0.0071 max mem: 33303 +Epoch: [30] [4190/4276] eta: 0:04:13 lr: 1.3085689956153712e-05 loss: 0.0851 (0.0867) time: 2.9501 data: 0.0071 max mem: 33303 +Epoch: [30] [4200/4276] eta: 0:03:44 lr: 1.3082636396649692e-05 loss: 0.0905 (0.0867) time: 2.9526 data: 0.0073 max mem: 33303 +Epoch: [30] [4210/4276] eta: 0:03:14 lr: 1.3079582757952778e-05 loss: 0.0908 (0.0867) time: 2.9605 data: 0.0075 max mem: 33303 +Epoch: [30] [4220/4276] eta: 0:02:45 lr: 1.3076529040040352e-05 loss: 0.0931 (0.0868) time: 2.9595 data: 0.0073 max mem: 33303 +Epoch: [30] [4230/4276] eta: 0:02:15 lr: 1.3073475242889816e-05 loss: 0.0864 (0.0868) time: 2.9525 data: 0.0071 max mem: 33303 +Epoch: [30] [4240/4276] eta: 0:01:46 lr: 1.3070421366478547e-05 loss: 0.0959 (0.0868) time: 2.9530 data: 0.0074 max mem: 33303 +Epoch: [30] [4250/4276] eta: 0:01:16 lr: 1.3067367410783914e-05 loss: 0.0959 (0.0868) time: 2.9503 data: 0.0075 max mem: 33303 +Epoch: [30] [4260/4276] eta: 0:00:47 lr: 1.306431337578326e-05 loss: 0.0803 (0.0868) time: 2.9307 data: 0.0080 max mem: 33303 +Epoch: [30] [4270/4276] eta: 0:00:17 lr: 1.3061259261453932e-05 loss: 0.0895 (0.0868) time: 2.9092 data: 0.0078 max mem: 33303 +Epoch: [30] Total time: 3:30:04 +Test: [ 0/21770] eta: 11:18:45 time: 1.8707 data: 1.8323 max mem: 33303 +Test: [ 100/21770] eta: 0:21:01 time: 0.0380 data: 0.0008 max mem: 33303 +Test: [ 200/21770] eta: 0:17:23 time: 0.0386 data: 0.0008 max mem: 33303 +Test: [ 300/21770] eta: 0:16:07 time: 0.0384 data: 0.0008 max mem: 33303 +Test: [ 400/21770] eta: 0:15:28 time: 0.0386 data: 0.0008 max mem: 33303 +Test: [ 500/21770] eta: 0:15:02 time: 0.0383 data: 0.0008 max mem: 33303 +Test: [ 600/21770] eta: 0:14:44 time: 0.0387 data: 0.0008 max mem: 33303 +Test: [ 700/21770] eta: 0:14:30 time: 0.0382 data: 0.0008 max mem: 33303 +Test: [ 800/21770] eta: 0:14:19 time: 0.0390 data: 0.0008 max mem: 33303 +Test: [ 900/21770] eta: 0:14:09 time: 0.0383 data: 0.0009 max mem: 33303 +Test: [ 1000/21770] eta: 0:14:00 time: 0.0379 data: 0.0009 max mem: 33303 +Test: [ 1100/21770] eta: 0:13:51 time: 0.0381 data: 0.0009 max mem: 33303 +Test: [ 1200/21770] eta: 0:13:43 time: 0.0379 data: 0.0009 max mem: 33303 +Test: [ 1300/21770] eta: 0:13:36 time: 0.0382 data: 0.0009 max mem: 33303 +Test: [ 1400/21770] eta: 0:13:29 time: 0.0380 data: 0.0009 max mem: 33303 +Test: [ 1500/21770] eta: 0:13:23 time: 0.0384 data: 0.0009 max mem: 33303 +Test: [ 1600/21770] eta: 0:13:18 time: 0.0384 data: 0.0009 max mem: 33303 +Test: [ 1700/21770] eta: 0:13:13 time: 0.0384 data: 0.0009 max mem: 33303 +Test: [ 1800/21770] eta: 0:13:07 time: 0.0383 data: 0.0009 max mem: 33303 +Test: [ 1900/21770] eta: 0:13:02 time: 0.0382 data: 0.0009 max mem: 33303 +Test: [ 2000/21770] eta: 0:12:57 time: 0.0384 data: 0.0009 max mem: 33303 +Test: [ 2100/21770] eta: 0:12:53 time: 0.0384 data: 0.0008 max mem: 33303 +Test: [ 2200/21770] eta: 0:12:48 time: 0.0384 data: 0.0009 max mem: 33303 +Test: [ 2300/21770] eta: 0:12:44 time: 0.0388 data: 0.0008 max mem: 33303 +Test: [ 2400/21770] eta: 0:12:40 time: 0.0395 data: 0.0008 max mem: 33303 +Test: [ 2500/21770] eta: 0:12:36 time: 0.0392 data: 0.0008 max mem: 33303 +Test: [ 2600/21770] eta: 0:12:32 time: 0.0399 data: 0.0008 max mem: 33303 +Test: [ 2700/21770] eta: 0:12:28 time: 0.0378 data: 0.0009 max mem: 33303 +Test: [ 2800/21770] eta: 0:12:24 time: 0.0382 data: 0.0009 max mem: 33303 +Test: [ 2900/21770] eta: 0:12:19 time: 0.0381 data: 0.0009 max mem: 33303 +Test: [ 3000/21770] eta: 0:12:14 time: 0.0382 data: 0.0009 max mem: 33303 +Test: [ 3100/21770] eta: 0:12:10 time: 0.0380 data: 0.0009 max mem: 33303 +Test: [ 3200/21770] eta: 0:12:05 time: 0.0382 data: 0.0009 max mem: 33303 +Test: [ 3300/21770] eta: 0:12:01 time: 0.0381 data: 0.0009 max mem: 33303 +Test: [ 3400/21770] eta: 0:11:56 time: 0.0381 data: 0.0009 max mem: 33303 +Test: [ 3500/21770] eta: 0:11:52 time: 0.0380 data: 0.0009 max mem: 33303 +Test: [ 3600/21770] eta: 0:11:48 time: 0.0382 data: 0.0009 max mem: 33303 +Test: [ 3700/21770] eta: 0:11:43 time: 0.0380 data: 0.0009 max mem: 33303 +Test: [ 3800/21770] eta: 0:11:39 time: 0.0381 data: 0.0009 max mem: 33303 +Test: [ 3900/21770] eta: 0:11:35 time: 0.0381 data: 0.0009 max mem: 33303 +Test: [ 4000/21770] eta: 0:11:31 time: 0.0382 data: 0.0009 max mem: 33303 +Test: [ 4100/21770] eta: 0:11:26 time: 0.0380 data: 0.0009 max mem: 33303 +Test: [ 4200/21770] eta: 0:11:22 time: 0.0381 data: 0.0009 max mem: 33303 +Test: [ 4300/21770] eta: 0:11:18 time: 0.0380 data: 0.0009 max mem: 33303 +Test: [ 4400/21770] eta: 0:11:14 time: 0.0386 data: 0.0009 max mem: 33303 +Test: [ 4500/21770] eta: 0:11:10 time: 0.0384 data: 0.0009 max mem: 33303 +Test: [ 4600/21770] eta: 0:11:06 time: 0.0384 data: 0.0009 max mem: 33303 +Test: [ 4700/21770] eta: 0:11:02 time: 0.0383 data: 0.0009 max mem: 33303 +Test: [ 4800/21770] eta: 0:10:58 time: 0.0384 data: 0.0009 max mem: 33303 +Test: [ 4900/21770] eta: 0:10:54 time: 0.0382 data: 0.0009 max mem: 33303 +Test: [ 5000/21770] eta: 0:10:50 time: 0.0385 data: 0.0009 max mem: 33303 +Test: [ 5100/21770] eta: 0:10:46 time: 0.0384 data: 0.0009 max mem: 33303 +Test: [ 5200/21770] eta: 0:10:42 time: 0.0386 data: 0.0009 max mem: 33303 +Test: [ 5300/21770] eta: 0:10:38 time: 0.0382 data: 0.0009 max mem: 33303 +Test: [ 5400/21770] eta: 0:10:34 time: 0.0387 data: 0.0009 max mem: 33303 +Test: [ 5500/21770] eta: 0:10:30 time: 0.0391 data: 0.0008 max mem: 33303 +Test: [ 5600/21770] eta: 0:10:26 time: 0.0390 data: 0.0008 max mem: 33303 +Test: [ 5700/21770] eta: 0:10:22 time: 0.0394 data: 0.0008 max mem: 33303 +Test: [ 5800/21770] eta: 0:10:19 time: 0.0390 data: 0.0008 max mem: 33303 +Test: [ 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time: 0.0392 data: 0.0008 max mem: 33303 +Test: [ 7300/21770] eta: 0:09:21 time: 0.0391 data: 0.0008 max mem: 33303 +Test: [ 7400/21770] eta: 0:09:17 time: 0.0391 data: 0.0008 max mem: 33303 +Test: [ 7500/21770] eta: 0:09:13 time: 0.0391 data: 0.0008 max mem: 33303 +Test: [ 7600/21770] eta: 0:09:10 time: 0.0391 data: 0.0008 max mem: 33303 +Test: [ 7700/21770] eta: 0:09:06 time: 0.0392 data: 0.0008 max mem: 33303 +Test: [ 7800/21770] eta: 0:09:02 time: 0.0388 data: 0.0008 max mem: 33303 +Test: [ 7900/21770] eta: 0:08:58 time: 0.0387 data: 0.0008 max mem: 33303 +Test: [ 8000/21770] eta: 0:08:54 time: 0.0388 data: 0.0008 max mem: 33303 +Test: [ 8100/21770] eta: 0:08:50 time: 0.0387 data: 0.0008 max mem: 33303 +Test: [ 8200/21770] eta: 0:08:46 time: 0.0386 data: 0.0008 max mem: 33303 +Test: [ 8300/21770] eta: 0:08:42 time: 0.0387 data: 0.0008 max mem: 33303 +Test: [ 8400/21770] eta: 0:08:39 time: 0.0390 data: 0.0008 max mem: 33303 +Test: [ 8500/21770] eta: 0:08:35 time: 0.0391 data: 0.0008 max mem: 33303 +Test: [ 8600/21770] eta: 0:08:31 time: 0.0391 data: 0.0008 max mem: 33303 +Test: [ 8700/21770] eta: 0:08:27 time: 0.0390 data: 0.0008 max mem: 33303 +Test: [ 8800/21770] eta: 0:08:23 time: 0.0391 data: 0.0008 max mem: 33303 +Test: [ 8900/21770] eta: 0:08:19 time: 0.0392 data: 0.0008 max mem: 33303 +Test: [ 9000/21770] eta: 0:08:15 time: 0.0389 data: 0.0008 max mem: 33303 +Test: [ 9100/21770] eta: 0:08:12 time: 0.0389 data: 0.0008 max mem: 33303 +Test: [ 9200/21770] eta: 0:08:08 time: 0.0386 data: 0.0008 max mem: 33303 +Test: [ 9300/21770] eta: 0:08:04 time: 0.0387 data: 0.0008 max mem: 33303 +Test: [ 9400/21770] eta: 0:08:00 time: 0.0385 data: 0.0008 max mem: 33303 +Test: [ 9500/21770] eta: 0:07:56 time: 0.0389 data: 0.0008 max mem: 33303 +Test: [ 9600/21770] eta: 0:07:52 time: 0.0387 data: 0.0008 max mem: 33303 +Test: [ 9700/21770] eta: 0:07:48 time: 0.0388 data: 0.0008 max mem: 33303 +Test: [ 9800/21770] eta: 0:07:44 time: 0.0387 data: 0.0008 max mem: 33303 +Test: [ 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time: 0.0387 data: 0.0009 max mem: 33303 +Test: [11300/21770] eta: 0:06:46 time: 0.0389 data: 0.0008 max mem: 33303 +Test: [11400/21770] eta: 0:06:42 time: 0.0391 data: 0.0008 max mem: 33303 +Test: [11500/21770] eta: 0:06:38 time: 0.0388 data: 0.0008 max mem: 33303 +Test: [11600/21770] eta: 0:06:34 time: 0.0386 data: 0.0008 max mem: 33303 +Test: [11700/21770] eta: 0:06:30 time: 0.0384 data: 0.0008 max mem: 33303 +Test: [11800/21770] eta: 0:06:27 time: 0.0384 data: 0.0008 max mem: 33303 +Test: [11900/21770] eta: 0:06:23 time: 0.0385 data: 0.0008 max mem: 33303 +Test: [12000/21770] eta: 0:06:19 time: 0.0385 data: 0.0009 max mem: 33303 +Test: [12100/21770] eta: 0:06:15 time: 0.0385 data: 0.0008 max mem: 33303 +Test: [12200/21770] eta: 0:06:11 time: 0.0384 data: 0.0009 max mem: 33303 +Test: [12300/21770] eta: 0:06:07 time: 0.0385 data: 0.0008 max mem: 33303 +Test: [12400/21770] eta: 0:06:03 time: 0.0385 data: 0.0009 max mem: 33303 +Test: [12500/21770] eta: 0:05:59 time: 0.0384 data: 0.0008 max mem: 33303 +Test: [12600/21770] eta: 0:05:55 time: 0.0386 data: 0.0009 max mem: 33303 +Test: [12700/21770] eta: 0:05:51 time: 0.0384 data: 0.0008 max mem: 33303 +Test: [12800/21770] eta: 0:05:47 time: 0.0385 data: 0.0009 max mem: 33303 +Test: [12900/21770] eta: 0:05:44 time: 0.0384 data: 0.0009 max mem: 33303 +Test: [13000/21770] eta: 0:05:40 time: 0.0386 data: 0.0009 max mem: 33303 +Test: [13100/21770] eta: 0:05:36 time: 0.0384 data: 0.0008 max mem: 33303 +Test: [13200/21770] eta: 0:05:32 time: 0.0385 data: 0.0008 max mem: 33303 +Test: [13300/21770] eta: 0:05:28 time: 0.0385 data: 0.0008 max mem: 33303 +Test: [13400/21770] eta: 0:05:24 time: 0.0384 data: 0.0008 max mem: 33303 +Test: [13500/21770] eta: 0:05:20 time: 0.0388 data: 0.0008 max mem: 33303 +Test: [13600/21770] eta: 0:05:16 time: 0.0389 data: 0.0008 max mem: 33303 +Test: [13700/21770] eta: 0:05:12 time: 0.0388 data: 0.0008 max mem: 33303 +Test: [13800/21770] eta: 0:05:09 time: 0.0389 data: 0.0008 max mem: 33303 +Test: [13900/21770] eta: 0:05:05 time: 0.0387 data: 0.0008 max mem: 33303 +Test: [14000/21770] eta: 0:05:01 time: 0.0390 data: 0.0008 max mem: 33303 +Test: [14100/21770] eta: 0:04:57 time: 0.0388 data: 0.0009 max mem: 33303 +Test: [14200/21770] eta: 0:04:53 time: 0.0389 data: 0.0009 max mem: 33303 +Test: [14300/21770] eta: 0:04:49 time: 0.0385 data: 0.0009 max mem: 33303 +Test: [14400/21770] eta: 0:04:45 time: 0.0385 data: 0.0009 max mem: 33303 +Test: [14500/21770] eta: 0:04:41 time: 0.0385 data: 0.0008 max mem: 33303 +Test: [14600/21770] eta: 0:04:38 time: 0.0386 data: 0.0009 max mem: 33303 +Test: [14700/21770] eta: 0:04:34 time: 0.0385 data: 0.0008 max mem: 33303 +Test: [14800/21770] eta: 0:04:30 time: 0.0384 data: 0.0009 max mem: 33303 +Test: [14900/21770] eta: 0:04:26 time: 0.0386 data: 0.0008 max mem: 33303 +Test: [15000/21770] eta: 0:04:22 time: 0.0386 data: 0.0009 max mem: 33303 +Test: [15100/21770] eta: 0:04:18 time: 0.0384 data: 0.0008 max mem: 33303 +Test: [15200/21770] eta: 0:04:14 time: 0.0385 data: 0.0008 max mem: 33303 +Test: [15300/21770] eta: 0:04:10 time: 0.0385 data: 0.0008 max mem: 33303 +Test: [15400/21770] eta: 0:04:06 time: 0.0385 data: 0.0008 max mem: 33303 +Test: [15500/21770] eta: 0:04:03 time: 0.0385 data: 0.0009 max mem: 33303 +Test: [15600/21770] eta: 0:03:59 time: 0.0387 data: 0.0009 max mem: 33303 +Test: [15700/21770] eta: 0:03:55 time: 0.0389 data: 0.0009 max mem: 33303 +Test: [15800/21770] eta: 0:03:51 time: 0.0392 data: 0.0009 max mem: 33303 +Test: [15900/21770] eta: 0:03:47 time: 0.0390 data: 0.0009 max mem: 33303 +Test: [16000/21770] eta: 0:03:43 time: 0.0391 data: 0.0009 max mem: 33303 +Test: [16100/21770] eta: 0:03:39 time: 0.0392 data: 0.0009 max mem: 33303 +Test: [16200/21770] eta: 0:03:35 time: 0.0390 data: 0.0009 max mem: 33303 +Test: [16300/21770] eta: 0:03:32 time: 0.0390 data: 0.0009 max mem: 33303 +Test: [16400/21770] eta: 0:03:28 time: 0.0390 data: 0.0009 max mem: 33303 +Test: [16500/21770] eta: 0:03:24 time: 0.0389 data: 0.0009 max mem: 33303 +Test: [16600/21770] eta: 0:03:20 time: 0.0391 data: 0.0009 max mem: 33303 +Test: [16700/21770] eta: 0:03:16 time: 0.0389 data: 0.0008 max mem: 33303 +Test: [16800/21770] eta: 0:03:12 time: 0.0392 data: 0.0008 max mem: 33303 +Test: [16900/21770] eta: 0:03:08 time: 0.0391 data: 0.0008 max mem: 33303 +Test: [17000/21770] eta: 0:03:04 time: 0.0390 data: 0.0008 max mem: 33303 +Test: [17100/21770] eta: 0:03:01 time: 0.0390 data: 0.0008 max mem: 33303 +Test: [17200/21770] eta: 0:02:57 time: 0.0387 data: 0.0008 max mem: 33303 +Test: [17300/21770] eta: 0:02:53 time: 0.0391 data: 0.0008 max mem: 33303 +Test: [17400/21770] eta: 0:02:49 time: 0.0391 data: 0.0008 max mem: 33303 +Test: [17500/21770] eta: 0:02:45 time: 0.0389 data: 0.0008 max mem: 33303 +Test: [17600/21770] eta: 0:02:41 time: 0.0391 data: 0.0008 max mem: 33303 +Test: [17700/21770] eta: 0:02:37 time: 0.0389 data: 0.0008 max mem: 33303 +Test: [17800/21770] eta: 0:02:33 time: 0.0388 data: 0.0008 max mem: 33303 +Test: [17900/21770] eta: 0:02:30 time: 0.0386 data: 0.0008 max mem: 33303 +Test: [18000/21770] eta: 0:02:26 time: 0.0388 data: 0.0008 max mem: 33303 +Test: [18100/21770] eta: 0:02:22 time: 0.0384 data: 0.0008 max mem: 33303 +Test: [18200/21770] eta: 0:02:18 time: 0.0387 data: 0.0008 max mem: 33303 +Test: [18300/21770] eta: 0:02:14 time: 0.0386 data: 0.0008 max mem: 33303 +Test: [18400/21770] eta: 0:02:10 time: 0.0390 data: 0.0008 max mem: 33303 +Test: [18500/21770] eta: 0:02:06 time: 0.0386 data: 0.0009 max mem: 33303 +Test: [18600/21770] eta: 0:02:02 time: 0.0387 data: 0.0009 max mem: 33303 +Test: [18700/21770] eta: 0:01:59 time: 0.0388 data: 0.0009 max mem: 33303 +Test: [18800/21770] eta: 0:01:55 time: 0.0387 data: 0.0009 max mem: 33303 +Test: [18900/21770] eta: 0:01:51 time: 0.0388 data: 0.0009 max mem: 33303 +Test: [19000/21770] eta: 0:01:47 time: 0.0387 data: 0.0009 max mem: 33303 +Test: [19100/21770] eta: 0:01:43 time: 0.0390 data: 0.0009 max mem: 33303 +Test: [19200/21770] eta: 0:01:39 time: 0.0388 data: 0.0009 max mem: 33303 +Test: [19300/21770] eta: 0:01:35 time: 0.0391 data: 0.0009 max mem: 33303 +Test: [19400/21770] eta: 0:01:31 time: 0.0392 data: 0.0009 max mem: 33303 +Test: [19500/21770] eta: 0:01:28 time: 0.0392 data: 0.0009 max mem: 33303 +Test: [19600/21770] eta: 0:01:24 time: 0.0395 data: 0.0009 max mem: 33303 +Test: [19700/21770] eta: 0:01:20 time: 0.0394 data: 0.0009 max mem: 33303 +Test: [19800/21770] eta: 0:01:16 time: 0.0390 data: 0.0009 max mem: 33303 +Test: [19900/21770] eta: 0:01:12 time: 0.0394 data: 0.0009 max mem: 33303 +Test: [20000/21770] eta: 0:01:08 time: 0.0392 data: 0.0009 max mem: 33303 +Test: [20100/21770] eta: 0:01:04 time: 0.0394 data: 0.0009 max mem: 33303 +Test: [20200/21770] eta: 0:01:00 time: 0.0393 data: 0.0009 max mem: 33303 +Test: [20300/21770] eta: 0:00:57 time: 0.0394 data: 0.0009 max mem: 33303 +Test: [20400/21770] eta: 0:00:53 time: 0.0391 data: 0.0009 max mem: 33303 +Test: [20500/21770] eta: 0:00:49 time: 0.0394 data: 0.0009 max mem: 33303 +Test: [20600/21770] eta: 0:00:45 time: 0.0390 data: 0.0009 max mem: 33303 +Test: [20700/21770] eta: 0:00:41 time: 0.0390 data: 0.0009 max mem: 33303 +Test: [20800/21770] eta: 0:00:37 time: 0.0385 data: 0.0008 max mem: 33303 +Test: [20900/21770] eta: 0:00:33 time: 0.0387 data: 0.0009 max mem: 33303 +Test: [21000/21770] eta: 0:00:29 time: 0.0387 data: 0.0009 max mem: 33303 +Test: [21100/21770] eta: 0:00:26 time: 0.0398 data: 0.0009 max mem: 33303 +Test: [21200/21770] eta: 0:00:22 time: 0.0389 data: 0.0009 max mem: 33303 +Test: [21300/21770] eta: 0:00:18 time: 0.0388 data: 0.0009 max mem: 33303 +Test: [21400/21770] eta: 0:00:14 time: 0.0386 data: 0.0009 max mem: 33303 +Test: [21500/21770] eta: 0:00:10 time: 0.0384 data: 0.0009 max mem: 33303 +Test: [21600/21770] eta: 0:00:06 time: 0.0386 data: 0.0009 max mem: 33303 +Test: [21700/21770] eta: 0:00:02 time: 0.0384 data: 0.0008 max mem: 33303 +Test: Total time: 0:14:05 +Final results: +Mean IoU is 0.00 + + precision@0.5 = 0.00 + precision@0.6 = 0.00 + precision@0.7 = 0.00 + precision@0.8 = 0.00 + precision@0.9 = 0.00 + overall IoU = 0.00 + mean IoU = 0.00 + +Mean accuracy for one-to-zero sample is 99.96 + +Average object IoU 0.0 +Overall IoU 0.0 +Epoch: [31] [ 0/4276] eta: 6:30:52 lr: 1.3059426754769138e-05 loss: 0.0745 (0.0745) time: 5.4847 data: 2.3910 max mem: 33303 +Epoch: [31] [ 10/4276] eta: 3:45:45 lr: 1.3056372513466764e-05 loss: 0.0745 (0.0817) time: 3.1752 data: 0.2252 max mem: 33303 +Epoch: [31] [ 20/4276] eta: 3:37:41 lr: 1.3053318192776742e-05 loss: 0.0699 (0.0878) time: 2.9483 data: 0.0087 max mem: 33303 +Epoch: [31] [ 30/4276] eta: 3:34:39 lr: 1.3050263792676364e-05 loss: 0.0804 (0.0878) time: 2.9554 data: 0.0082 max mem: 33303 +Epoch: [31] [ 40/4276] eta: 3:32:50 lr: 1.3047209313142916e-05 loss: 0.0817 (0.0874) time: 2.9575 data: 0.0074 max mem: 33303 +Epoch: [31] [ 50/4276] eta: 3:31:29 lr: 1.3044154754153667e-05 loss: 0.0731 (0.0848) time: 2.9551 data: 0.0072 max mem: 33303 +Epoch: [31] [ 60/4276] eta: 3:30:29 lr: 1.3041100115685886e-05 loss: 0.0664 (0.0828) time: 2.9562 data: 0.0071 max mem: 33303 +Epoch: [31] [ 70/4276] eta: 3:29:23 lr: 1.3038045397716803e-05 loss: 0.0619 (0.0802) time: 2.9472 data: 0.0073 max mem: 33303 +Epoch: [31] [ 80/4276] eta: 3:28:15 lr: 1.3034990600223656e-05 loss: 0.0756 (0.0810) time: 2.9241 data: 0.0079 max mem: 33303 +Epoch: [31] [ 90/4276] eta: 3:27:13 lr: 1.3031935723183671e-05 loss: 0.0856 (0.0827) time: 2.9109 data: 0.0085 max mem: 33303 +Epoch: [31] [ 100/4276] eta: 3:26:17 lr: 1.3028880766574062e-05 loss: 0.0856 (0.0846) time: 2.9077 data: 0.0083 max mem: 33303 +Epoch: [31] [ 110/4276] eta: 3:25:31 lr: 1.3025825730372007e-05 loss: 0.0928 (0.0857) time: 2.9135 data: 0.0085 max mem: 33303 +Epoch: [31] [ 120/4276] eta: 3:24:46 lr: 1.3022770614554705e-05 loss: 0.0928 (0.0859) time: 2.9180 data: 0.0088 max mem: 33303 +Epoch: [31] [ 130/4276] eta: 3:24:02 lr: 1.3019715419099322e-05 loss: 0.0903 (0.0862) time: 2.9129 data: 0.0088 max mem: 33303 +Epoch: [31] [ 140/4276] eta: 3:23:21 lr: 1.301666014398302e-05 loss: 0.0795 (0.0855) time: 2.9120 data: 0.0084 max mem: 33303 +Epoch: [31] [ 150/4276] eta: 3:22:53 lr: 1.301360478918294e-05 loss: 0.0736 (0.0849) time: 2.9342 data: 0.0086 max mem: 33303 +Epoch: [31] [ 160/4276] eta: 3:22:24 lr: 1.3010549354676218e-05 loss: 0.0798 (0.0851) time: 2.9549 data: 0.0081 max mem: 33303 +Epoch: [31] [ 170/4276] eta: 3:21:56 lr: 1.3007493840439978e-05 loss: 0.0850 (0.0853) time: 2.9545 data: 0.0071 max mem: 33303 +Epoch: [31] [ 180/4276] eta: 3:21:27 lr: 1.3004438246451328e-05 loss: 0.0954 (0.0856) time: 2.9530 data: 0.0071 max mem: 33303 +Epoch: [31] [ 190/4276] eta: 3:20:58 lr: 1.300138257268736e-05 loss: 0.0789 (0.0851) time: 2.9532 data: 0.0071 max mem: 33303 +Epoch: [31] [ 200/4276] eta: 3:20:28 lr: 1.2998326819125156e-05 loss: 0.0771 (0.0851) time: 2.9531 data: 0.0071 max mem: 33303 +Epoch: [31] [ 210/4276] eta: 3:19:57 lr: 1.2995270985741794e-05 loss: 0.0884 (0.0853) time: 2.9451 data: 0.0073 max mem: 33303 +Epoch: [31] [ 220/4276] eta: 3:19:24 lr: 1.2992215072514333e-05 loss: 0.0842 (0.0849) time: 2.9377 data: 0.0078 max mem: 33303 +Epoch: [31] [ 230/4276] eta: 3:18:55 lr: 1.298915907941981e-05 loss: 0.0698 (0.0843) time: 2.9425 data: 0.0077 max mem: 33303 +Epoch: [31] [ 240/4276] eta: 3:18:26 lr: 1.2986103006435266e-05 loss: 0.0704 (0.0840) time: 2.9503 data: 0.0073 max mem: 33303 +Epoch: [31] [ 250/4276] eta: 3:17:56 lr: 1.2983046853537716e-05 loss: 0.0808 (0.0844) time: 2.9522 data: 0.0071 max mem: 33303 +Epoch: [31] [ 260/4276] eta: 3:17:27 lr: 1.2979990620704177e-05 loss: 0.0844 (0.0845) time: 2.9522 data: 0.0072 max mem: 33303 +Epoch: [31] [ 270/4276] eta: 3:16:58 lr: 1.2976934307911634e-05 loss: 0.0724 (0.0848) time: 2.9515 data: 0.0073 max mem: 33303 +Epoch: [31] [ 280/4276] eta: 3:16:29 lr: 1.2973877915137073e-05 loss: 0.0806 (0.0847) time: 2.9519 data: 0.0071 max mem: 33303 +Epoch: [31] [ 290/4276] eta: 3:15:59 lr: 1.297082144235747e-05 loss: 0.0808 (0.0844) time: 2.9523 data: 0.0073 max mem: 33303 +Epoch: [31] [ 300/4276] eta: 3:15:30 lr: 1.2967764889549772e-05 loss: 0.0777 (0.0844) time: 2.9501 data: 0.0073 max mem: 33303 +Epoch: [31] [ 310/4276] eta: 3:15:00 lr: 1.296470825669093e-05 loss: 0.0766 (0.0839) time: 2.9504 data: 0.0070 max mem: 33303 +Epoch: [31] [ 320/4276] eta: 3:14:32 lr: 1.2961651543757875e-05 loss: 0.0879 (0.0845) time: 2.9564 data: 0.0072 max mem: 33303 +Epoch: [31] [ 330/4276] eta: 3:14:03 lr: 1.2958594750727529e-05 loss: 0.1031 (0.0850) time: 2.9568 data: 0.0076 max mem: 33303 +Epoch: [31] [ 340/4276] eta: 3:13:33 lr: 1.2955537877576792e-05 loss: 0.0873 (0.0850) time: 2.9520 data: 0.0080 max mem: 33303 +Epoch: [31] [ 350/4276] eta: 3:13:01 lr: 1.2952480924282564e-05 loss: 0.0859 (0.0852) time: 2.9360 data: 0.0087 max mem: 33303 +Epoch: [31] [ 360/4276] eta: 3:12:27 lr: 1.2949423890821721e-05 loss: 0.0935 (0.0858) time: 2.9143 data: 0.0088 max mem: 33303 +Epoch: [31] [ 370/4276] eta: 3:11:53 lr: 1.2946366777171142e-05 loss: 0.0874 (0.0858) time: 2.9094 data: 0.0084 max mem: 33303 +Epoch: [31] [ 380/4276] eta: 3:11:23 lr: 1.294330958330767e-05 loss: 0.0816 (0.0862) time: 2.9263 data: 0.0086 max mem: 33303 +Epoch: [31] [ 390/4276] eta: 3:10:54 lr: 1.294025230920815e-05 loss: 0.0816 (0.0862) time: 2.9480 data: 0.0084 max mem: 33303 +Epoch: [31] [ 400/4276] eta: 3:10:25 lr: 1.2937194954849419e-05 loss: 0.0890 (0.0865) time: 2.9550 data: 0.0079 max mem: 33303 +Epoch: [31] [ 410/4276] eta: 3:09:58 lr: 1.2934137520208295e-05 loss: 0.0950 (0.0867) time: 2.9618 data: 0.0077 max mem: 33303 +Epoch: [31] [ 420/4276] eta: 3:09:29 lr: 1.293108000526157e-05 loss: 0.0885 (0.0870) time: 2.9612 data: 0.0077 max mem: 33303 +Epoch: [31] [ 430/4276] eta: 3:09:01 lr: 1.2928022409986048e-05 loss: 0.0841 (0.0872) time: 2.9571 data: 0.0078 max mem: 33303 +Epoch: [31] [ 440/4276] eta: 3:08:32 lr: 1.2924964734358503e-05 loss: 0.0889 (0.0872) time: 2.9595 data: 0.0078 max mem: 33303 +Epoch: [31] [ 450/4276] eta: 3:08:03 lr: 1.2921906978355708e-05 loss: 0.0777 (0.0871) time: 2.9583 data: 0.0078 max mem: 33303 +Epoch: [31] [ 460/4276] eta: 3:07:34 lr: 1.2918849141954404e-05 loss: 0.0743 (0.0867) time: 2.9557 data: 0.0079 max mem: 33303 +Epoch: [31] [ 470/4276] eta: 3:07:05 lr: 1.2915791225131338e-05 loss: 0.0660 (0.0865) time: 2.9543 data: 0.0080 max mem: 33303 +Epoch: [31] [ 480/4276] eta: 3:06:37 lr: 1.2912733227863238e-05 loss: 0.0824 (0.0864) time: 2.9603 data: 0.0079 max mem: 33303 +Epoch: [31] [ 490/4276] eta: 3:06:06 lr: 1.2909675150126826e-05 loss: 0.0785 (0.0862) time: 2.9492 data: 0.0084 max mem: 33303 +Epoch: [31] [ 500/4276] eta: 3:05:37 lr: 1.290661699189879e-05 loss: 0.0755 (0.0861) time: 2.9424 data: 0.0084 max mem: 33303 +Epoch: [31] [ 510/4276] eta: 3:05:08 lr: 1.2903558753155826e-05 loss: 0.0755 (0.0859) time: 2.9531 data: 0.0075 max mem: 33303 +Epoch: [31] [ 520/4276] eta: 3:04:37 lr: 1.290050043387461e-05 loss: 0.0778 (0.0860) time: 2.9462 data: 0.0077 max mem: 33303 +Epoch: [31] [ 530/4276] eta: 3:04:08 lr: 1.289744203403181e-05 loss: 0.0813 (0.0860) time: 2.9459 data: 0.0077 max mem: 33303 +Epoch: [31] [ 540/4276] eta: 3:03:39 lr: 1.2894383553604065e-05 loss: 0.0774 (0.0859) time: 2.9536 data: 0.0074 max mem: 33303 +Epoch: [31] [ 550/4276] eta: 3:03:10 lr: 1.289132499256802e-05 loss: 0.0778 (0.0859) time: 2.9578 data: 0.0074 max mem: 33303 +Epoch: [31] [ 560/4276] eta: 3:02:41 lr: 1.2888266350900299e-05 loss: 0.0828 (0.0859) time: 2.9581 data: 0.0075 max mem: 33303 +Epoch: [31] [ 570/4276] eta: 3:02:12 lr: 1.2885207628577516e-05 loss: 0.0907 (0.0861) time: 2.9566 data: 0.0075 max mem: 33303 +Epoch: [31] [ 580/4276] eta: 3:01:43 lr: 1.2882148825576266e-05 loss: 0.0907 (0.0861) time: 2.9569 data: 0.0073 max mem: 33303 +Epoch: [31] [ 590/4276] eta: 3:01:14 lr: 1.2879089941873129e-05 loss: 0.0744 (0.0858) time: 2.9572 data: 0.0074 max mem: 33303 +Epoch: [31] [ 600/4276] eta: 3:00:45 lr: 1.2876030977444695e-05 loss: 0.0724 (0.0858) time: 2.9589 data: 0.0078 max mem: 33303 +Epoch: [31] [ 610/4276] eta: 3:00:16 lr: 1.2872971932267502e-05 loss: 0.0782 (0.0857) time: 2.9595 data: 0.0078 max mem: 33303 +Epoch: [31] [ 620/4276] eta: 2:59:47 lr: 1.286991280631811e-05 loss: 0.0815 (0.0858) time: 2.9609 data: 0.0080 max mem: 33303 +Epoch: [31] [ 630/4276] eta: 2:59:18 lr: 1.2866853599573051e-05 loss: 0.0893 (0.0860) time: 2.9582 data: 0.0081 max mem: 33303 +Epoch: [31] [ 640/4276] eta: 2:58:49 lr: 1.2863794312008847e-05 loss: 0.0814 (0.0859) time: 2.9563 data: 0.0080 max mem: 33303 +Epoch: [31] [ 650/4276] eta: 2:58:20 lr: 1.2860734943601998e-05 loss: 0.0813 (0.0864) time: 2.9568 data: 0.0078 max mem: 33303 +Epoch: [31] [ 660/4276] eta: 2:57:50 lr: 1.2857675494329005e-05 loss: 0.0985 (0.0867) time: 2.9523 data: 0.0075 max mem: 33303 +Epoch: [31] [ 670/4276] eta: 2:57:18 lr: 1.2854615964166347e-05 loss: 0.0965 (0.0867) time: 2.9254 data: 0.0073 max mem: 33303 +Epoch: [31] [ 680/4276] eta: 2:56:46 lr: 1.2851556353090499e-05 loss: 0.0817 (0.0867) time: 2.9008 data: 0.0071 max mem: 33303 +Epoch: [31] [ 690/4276] eta: 2:56:14 lr: 1.2848496661077907e-05 loss: 0.0837 (0.0867) time: 2.9003 data: 0.0070 max mem: 33303 +Epoch: [31] [ 700/4276] eta: 2:55:42 lr: 1.2845436888105017e-05 loss: 0.0870 (0.0867) time: 2.9080 data: 0.0074 max mem: 33303 +Epoch: [31] [ 710/4276] eta: 2:55:12 lr: 1.2842377034148258e-05 loss: 0.0777 (0.0866) time: 2.9232 data: 0.0080 max mem: 33303 +Epoch: [31] [ 720/4276] eta: 2:54:41 lr: 1.2839317099184054e-05 loss: 0.0738 (0.0865) time: 2.9238 data: 0.0082 max mem: 33303 +Epoch: [31] [ 730/4276] eta: 2:54:09 lr: 1.2836257083188791e-05 loss: 0.0751 (0.0866) time: 2.9089 data: 0.0079 max mem: 33303 +Epoch: [31] [ 740/4276] eta: 2:53:38 lr: 1.2833196986138871e-05 loss: 0.0753 (0.0865) time: 2.9030 data: 0.0074 max mem: 33303 +Epoch: [31] [ 750/4276] eta: 2:53:07 lr: 1.2830136808010667e-05 loss: 0.0710 (0.0863) time: 2.9143 data: 0.0073 max mem: 33303 +Epoch: [31] [ 760/4276] eta: 2:52:36 lr: 1.2827076548780553e-05 loss: 0.0736 (0.0863) time: 2.9136 data: 0.0075 max mem: 33303 +Epoch: [31] [ 770/4276] eta: 2:52:05 lr: 1.282401620842486e-05 loss: 0.0860 (0.0864) time: 2.9037 data: 0.0076 max mem: 33303 +Epoch: [31] [ 780/4276] eta: 2:51:33 lr: 1.2820955786919939e-05 loss: 0.0783 (0.0863) time: 2.9039 data: 0.0074 max mem: 33303 +Epoch: [31] [ 790/4276] eta: 2:51:04 lr: 1.281789528424211e-05 loss: 0.0839 (0.0864) time: 2.9295 data: 0.0080 max mem: 33303 +Epoch: [31] [ 800/4276] eta: 2:50:35 lr: 1.281483470036769e-05 loss: 0.0846 (0.0863) time: 2.9568 data: 0.0089 max mem: 33303 +Epoch: [31] [ 810/4276] eta: 2:50:06 lr: 1.2811774035272963e-05 loss: 0.0810 (0.0865) time: 2.9568 data: 0.0088 max mem: 33303 +Epoch: [31] [ 820/4276] eta: 2:49:37 lr: 1.2808713288934223e-05 loss: 0.0810 (0.0864) time: 2.9548 data: 0.0079 max mem: 33303 +Epoch: [31] [ 830/4276] eta: 2:49:08 lr: 1.2805652461327742e-05 loss: 0.0778 (0.0864) time: 2.9544 data: 0.0073 max mem: 33303 +Epoch: [31] [ 840/4276] eta: 2:48:39 lr: 1.280259155242978e-05 loss: 0.0778 (0.0864) time: 2.9551 data: 0.0075 max mem: 33303 +Epoch: [31] [ 850/4276] eta: 2:48:10 lr: 1.2799530562216572e-05 loss: 0.0741 (0.0864) time: 2.9559 data: 0.0075 max mem: 33303 +Epoch: [31] [ 860/4276] eta: 2:47:41 lr: 1.2796469490664354e-05 loss: 0.0782 (0.0865) time: 2.9577 data: 0.0073 max mem: 33303 +Epoch: [31] [ 870/4276] eta: 2:47:12 lr: 1.2793408337749347e-05 loss: 0.0814 (0.0866) time: 2.9571 data: 0.0073 max mem: 33303 +Epoch: [31] [ 880/4276] eta: 2:46:43 lr: 1.2790347103447758e-05 loss: 0.0945 (0.0868) time: 2.9572 data: 0.0075 max mem: 33303 +Epoch: [31] [ 890/4276] eta: 2:46:14 lr: 1.278728578773577e-05 loss: 0.0983 (0.0869) time: 2.9588 data: 0.0075 max mem: 33303 +Epoch: [31] [ 900/4276] eta: 2:45:45 lr: 1.278422439058957e-05 loss: 0.0932 (0.0871) time: 2.9565 data: 0.0073 max mem: 33303 +Epoch: [31] [ 910/4276] eta: 2:45:16 lr: 1.2781162911985319e-05 loss: 0.0841 (0.0870) time: 2.9541 data: 0.0073 max mem: 33303 +Epoch: [31] [ 920/4276] eta: 2:44:47 lr: 1.2778101351899169e-05 loss: 0.0814 (0.0871) time: 2.9551 data: 0.0074 max mem: 33303 +Epoch: [31] [ 930/4276] eta: 2:44:18 lr: 1.2775039710307254e-05 loss: 0.0844 (0.0871) time: 2.9543 data: 0.0075 max mem: 33303 +Epoch: [31] [ 940/4276] eta: 2:43:49 lr: 1.2771977987185707e-05 loss: 0.0806 (0.0871) time: 2.9542 data: 0.0075 max mem: 33303 +Epoch: [31] [ 950/4276] eta: 2:43:19 lr: 1.2768916182510643e-05 loss: 0.0806 (0.0871) time: 2.9539 data: 0.0076 max mem: 33303 +Epoch: [31] [ 960/4276] eta: 2:42:49 lr: 1.2765854296258145e-05 loss: 0.0830 (0.0872) time: 2.9413 data: 0.0076 max mem: 33303 +Epoch: [31] [ 970/4276] eta: 2:42:19 lr: 1.2762792328404308e-05 loss: 0.0841 (0.0873) time: 2.9269 data: 0.0079 max mem: 33303 +Epoch: [31] [ 980/4276] eta: 2:41:49 lr: 1.2759730278925203e-05 loss: 0.0893 (0.0873) time: 2.9218 data: 0.0080 max mem: 33303 +Epoch: [31] [ 990/4276] eta: 2:41:18 lr: 1.275666814779689e-05 loss: 0.0809 (0.0873) time: 2.9124 data: 0.0080 max mem: 33303 +Epoch: [31] [1000/4276] eta: 2:40:47 lr: 1.2753605934995411e-05 loss: 0.0777 (0.0872) time: 2.9059 data: 0.0083 max mem: 33303 +Epoch: [31] [1010/4276] eta: 2:40:17 lr: 1.2750543640496793e-05 loss: 0.0854 (0.0872) time: 2.9072 data: 0.0088 max mem: 33303 +Epoch: [31] [1020/4276] eta: 2:39:46 lr: 1.2747481264277062e-05 loss: 0.0808 (0.0872) time: 2.9039 data: 0.0085 max mem: 33303 +Epoch: [31] [1030/4276] eta: 2:39:16 lr: 1.2744418806312222e-05 loss: 0.0727 (0.0872) time: 2.9244 data: 0.0088 max mem: 33303 +Epoch: [31] [1040/4276] eta: 2:38:47 lr: 1.2741356266578256e-05 loss: 0.0761 (0.0872) time: 2.9534 data: 0.0094 max mem: 33303 +Epoch: [31] [1050/4276] eta: 2:38:18 lr: 1.2738293645051147e-05 loss: 0.0820 (0.0873) time: 2.9555 data: 0.0090 max mem: 33303 +Epoch: [31] [1060/4276] eta: 2:37:49 lr: 1.2735230941706858e-05 loss: 0.0820 (0.0872) time: 2.9535 data: 0.0089 max mem: 33303 +Epoch: [31] [1070/4276] eta: 2:37:20 lr: 1.2732168156521345e-05 loss: 0.0768 (0.0873) time: 2.9555 data: 0.0084 max mem: 33303 +Epoch: [31] [1080/4276] eta: 2:36:51 lr: 1.2729105289470538e-05 loss: 0.0790 (0.0873) time: 2.9546 data: 0.0081 max mem: 33303 +Epoch: [31] [1090/4276] eta: 2:36:22 lr: 1.2726042340530362e-05 loss: 0.0960 (0.0874) time: 2.9545 data: 0.0081 max mem: 33303 +Epoch: [31] [1100/4276] eta: 2:35:52 lr: 1.2722979309676725e-05 loss: 0.0960 (0.0875) time: 2.9524 data: 0.0085 max mem: 33303 +Epoch: [31] [1110/4276] eta: 2:35:22 lr: 1.2719916196885535e-05 loss: 0.0877 (0.0875) time: 2.9362 data: 0.0086 max mem: 33303 +Epoch: [31] [1120/4276] eta: 2:34:52 lr: 1.2716853002132661e-05 loss: 0.0922 (0.0876) time: 2.9203 data: 0.0075 max mem: 33303 +Epoch: [31] [1130/4276] eta: 2:34:24 lr: 1.2713789725393976e-05 loss: 0.0888 (0.0875) time: 2.9504 data: 0.0075 max mem: 33303 +Epoch: [31] [1140/4276] eta: 2:33:53 lr: 1.271072636664534e-05 loss: 0.0836 (0.0875) time: 2.9479 data: 0.0083 max mem: 33303 +Epoch: [31] [1150/4276] eta: 2:33:23 lr: 1.2707662925862598e-05 loss: 0.0885 (0.0875) time: 2.9073 data: 0.0088 max mem: 33303 +Epoch: [31] [1160/4276] eta: 2:32:52 lr: 1.2704599403021567e-05 loss: 0.0885 (0.0875) time: 2.9010 data: 0.0084 max mem: 33303 +Epoch: [31] [1170/4276] eta: 2:32:22 lr: 1.270153579809807e-05 loss: 0.0826 (0.0875) time: 2.9060 data: 0.0079 max mem: 33303 +Epoch: [31] [1180/4276] eta: 2:31:52 lr: 1.2698472111067906e-05 loss: 0.0849 (0.0875) time: 2.9137 data: 0.0083 max mem: 33303 +Epoch: [31] [1190/4276] eta: 2:31:21 lr: 1.269540834190687e-05 loss: 0.0876 (0.0875) time: 2.9099 data: 0.0085 max mem: 33303 +Epoch: [31] [1200/4276] eta: 2:30:51 lr: 1.2692344490590727e-05 loss: 0.0730 (0.0874) time: 2.9052 data: 0.0085 max mem: 33303 +Epoch: [31] [1210/4276] eta: 2:30:21 lr: 1.268928055709524e-05 loss: 0.0740 (0.0873) time: 2.9057 data: 0.0086 max mem: 33303 +Epoch: [31] [1220/4276] eta: 2:29:50 lr: 1.2686216541396163e-05 loss: 0.0805 (0.0873) time: 2.9108 data: 0.0086 max mem: 33303 +Epoch: [31] [1230/4276] eta: 2:29:21 lr: 1.2683152443469215e-05 loss: 0.0867 (0.0873) time: 2.9307 data: 0.0087 max mem: 33303 +Epoch: [31] [1240/4276] eta: 2:28:51 lr: 1.2680088263290127e-05 loss: 0.0788 (0.0873) time: 2.9319 data: 0.0088 max mem: 33303 +Epoch: [31] [1250/4276] eta: 2:28:21 lr: 1.26770240008346e-05 loss: 0.0861 (0.0873) time: 2.9121 data: 0.0088 max mem: 33303 +Epoch: [31] [1260/4276] eta: 2:27:51 lr: 1.2673959656078333e-05 loss: 0.0851 (0.0872) time: 2.9071 data: 0.0086 max mem: 33303 +Epoch: [31] [1270/4276] eta: 2:27:20 lr: 1.2670895228996996e-05 loss: 0.0841 (0.0871) time: 2.9061 data: 0.0084 max mem: 33303 +Epoch: [31] [1280/4276] eta: 2:26:50 lr: 1.2667830719566254e-05 loss: 0.0878 (0.0872) time: 2.9082 data: 0.0086 max mem: 33303 +Epoch: [31] [1290/4276] eta: 2:26:20 lr: 1.2664766127761762e-05 loss: 0.0939 (0.0872) time: 2.9111 data: 0.0087 max mem: 33303 +Epoch: [31] [1300/4276] eta: 2:25:50 lr: 1.2661701453559164e-05 loss: 0.0811 (0.0872) time: 2.9124 data: 0.0083 max mem: 33303 +Epoch: [31] [1310/4276] eta: 2:25:20 lr: 1.2658636696934067e-05 loss: 0.0741 (0.0872) time: 2.9128 data: 0.0082 max mem: 33303 +Epoch: [31] [1320/4276] eta: 2:24:51 lr: 1.2655571857862093e-05 loss: 0.0850 (0.0873) time: 2.9294 data: 0.0088 max mem: 33303 +Epoch: [31] [1330/4276] eta: 2:24:21 lr: 1.265250693631883e-05 loss: 0.0760 (0.0872) time: 2.9327 data: 0.0090 max mem: 33303 +Epoch: [31] [1340/4276] eta: 2:23:52 lr: 1.2649441932279873e-05 loss: 0.0760 (0.0872) time: 2.9392 data: 0.0089 max mem: 33303 +Epoch: [31] [1350/4276] eta: 2:23:23 lr: 1.2646376845720779e-05 loss: 0.0864 (0.0872) time: 2.9615 data: 0.0085 max mem: 33303 +Epoch: [31] [1360/4276] eta: 2:22:54 lr: 1.2643311676617101e-05 loss: 0.0853 (0.0872) time: 2.9604 data: 0.0077 max mem: 33303 +Epoch: [31] [1370/4276] eta: 2:22:25 lr: 1.2640246424944385e-05 loss: 0.0805 (0.0872) time: 2.9580 data: 0.0074 max mem: 33303 +Epoch: [31] [1380/4276] eta: 2:21:56 lr: 1.2637181090678166e-05 loss: 0.0862 (0.0872) time: 2.9569 data: 0.0074 max mem: 33303 +Epoch: [31] [1390/4276] eta: 2:21:27 lr: 1.263411567379394e-05 loss: 0.0904 (0.0872) time: 2.9572 data: 0.0076 max mem: 33303 +Epoch: [31] [1400/4276] eta: 2:20:58 lr: 1.2631050174267215e-05 loss: 0.0904 (0.0872) time: 2.9527 data: 0.0076 max mem: 33303 +Epoch: [31] [1410/4276] eta: 2:20:28 lr: 1.2627984592073475e-05 loss: 0.0806 (0.0872) time: 2.9275 data: 0.0083 max mem: 33303 +Epoch: [31] [1420/4276] eta: 2:19:57 lr: 1.2624918927188194e-05 loss: 0.0734 (0.0871) time: 2.9065 data: 0.0086 max mem: 33303 +Epoch: [31] [1430/4276] eta: 2:19:27 lr: 1.2621853179586826e-05 loss: 0.0837 (0.0872) time: 2.9060 data: 0.0080 max mem: 33303 +Epoch: [31] [1440/4276] eta: 2:18:57 lr: 1.2618787349244814e-05 loss: 0.0849 (0.0872) time: 2.9062 data: 0.0081 max mem: 33303 +Epoch: [31] [1450/4276] eta: 2:18:27 lr: 1.2615721436137592e-05 loss: 0.0787 (0.0871) time: 2.9070 data: 0.0085 max mem: 33303 +Epoch: [31] [1460/4276] eta: 2:17:57 lr: 1.2612655440240579e-05 loss: 0.0800 (0.0871) time: 2.9087 data: 0.0085 max mem: 33303 +Epoch: [31] [1470/4276] eta: 2:17:28 lr: 1.2609589361529165e-05 loss: 0.0823 (0.0871) time: 2.9393 data: 0.0088 max mem: 33303 +Epoch: [31] [1480/4276] eta: 2:16:59 lr: 1.2606523199978743e-05 loss: 0.0851 (0.0871) time: 2.9467 data: 0.0090 max mem: 33303 +Epoch: [31] [1490/4276] eta: 2:16:29 lr: 1.2603456955564685e-05 loss: 0.0851 (0.0871) time: 2.9253 data: 0.0086 max mem: 33303 +Epoch: [31] [1500/4276] eta: 2:16:00 lr: 1.2600390628262362e-05 loss: 0.0834 (0.0871) time: 2.9370 data: 0.0086 max mem: 33303 +Epoch: [31] [1510/4276] eta: 2:15:30 lr: 1.2597324218047107e-05 loss: 0.0812 (0.0870) time: 2.9354 data: 0.0089 max mem: 33303 +Epoch: [31] [1520/4276] eta: 2:15:01 lr: 1.2594257724894254e-05 loss: 0.0789 (0.0870) time: 2.9390 data: 0.0090 max mem: 33303 +Epoch: [31] [1530/4276] eta: 2:14:32 lr: 1.2591191148779131e-05 loss: 0.0789 (0.0870) time: 2.9569 data: 0.0083 max mem: 33303 +Epoch: [31] [1540/4276] eta: 2:14:03 lr: 1.2588124489677028e-05 loss: 0.0834 (0.0870) time: 2.9602 data: 0.0076 max mem: 33303 +Epoch: [31] [1550/4276] eta: 2:13:34 lr: 1.2585057747563239e-05 loss: 0.0846 (0.0869) time: 2.9578 data: 0.0076 max mem: 33303 +Epoch: [31] [1560/4276] eta: 2:13:05 lr: 1.2581990922413042e-05 loss: 0.0764 (0.0869) time: 2.9557 data: 0.0076 max mem: 33303 +Epoch: [31] [1570/4276] eta: 2:12:36 lr: 1.2578924014201707e-05 loss: 0.0764 (0.0869) time: 2.9568 data: 0.0074 max mem: 33303 +Epoch: [31] [1580/4276] eta: 2:12:06 lr: 1.2575857022904464e-05 loss: 0.0752 (0.0868) time: 2.9549 data: 0.0074 max mem: 33303 +Epoch: [31] [1590/4276] eta: 2:11:37 lr: 1.2572789948496558e-05 loss: 0.0752 (0.0867) time: 2.9549 data: 0.0076 max mem: 33303 +Epoch: [31] [1600/4276] eta: 2:11:08 lr: 1.2569722790953203e-05 loss: 0.0798 (0.0867) time: 2.9526 data: 0.0075 max mem: 33303 +Epoch: [31] [1610/4276] eta: 2:10:38 lr: 1.2566655550249614e-05 loss: 0.0798 (0.0867) time: 2.9275 data: 0.0074 max mem: 33303 +Epoch: [31] [1620/4276] eta: 2:10:08 lr: 1.256358822636097e-05 loss: 0.0762 (0.0866) time: 2.8978 data: 0.0075 max mem: 33303 +Epoch: [31] [1630/4276] eta: 2:09:38 lr: 1.2560520819262453e-05 loss: 0.0767 (0.0866) time: 2.8892 data: 0.0076 max mem: 33303 +Epoch: [31] [1640/4276] eta: 2:09:07 lr: 1.2557453328929227e-05 loss: 0.0807 (0.0866) time: 2.8920 data: 0.0079 max mem: 33303 +Epoch: [31] [1650/4276] eta: 2:08:38 lr: 1.2554385755336445e-05 loss: 0.0743 (0.0865) time: 2.9142 data: 0.0082 max mem: 33303 +Epoch: [31] [1660/4276] eta: 2:08:09 lr: 1.2551318098459234e-05 loss: 0.0717 (0.0865) time: 2.9391 data: 0.0085 max mem: 33303 +Epoch: [31] [1670/4276] eta: 2:07:40 lr: 1.2548250358272712e-05 loss: 0.0812 (0.0864) time: 2.9489 data: 0.0086 max mem: 33303 +Epoch: [31] [1680/4276] eta: 2:07:10 lr: 1.2545182534751992e-05 loss: 0.0767 (0.0865) time: 2.9506 data: 0.0082 max mem: 33303 +Epoch: [31] [1690/4276] eta: 2:06:41 lr: 1.2542114627872172e-05 loss: 0.0736 (0.0864) time: 2.9469 data: 0.0081 max mem: 33303 +Epoch: [31] [1700/4276] eta: 2:06:12 lr: 1.2539046637608316e-05 loss: 0.0823 (0.0864) time: 2.9467 data: 0.0082 max mem: 33303 +Epoch: [31] [1710/4276] eta: 2:05:42 lr: 1.2535978563935493e-05 loss: 0.0833 (0.0864) time: 2.9503 data: 0.0082 max mem: 33303 +Epoch: [31] [1720/4276] eta: 2:05:13 lr: 1.2532910406828751e-05 loss: 0.0705 (0.0863) time: 2.9375 data: 0.0083 max mem: 33303 +Epoch: [31] [1730/4276] eta: 2:04:43 lr: 1.2529842166263136e-05 loss: 0.0645 (0.0862) time: 2.9109 data: 0.0081 max mem: 33303 +Epoch: [31] [1740/4276] eta: 2:04:14 lr: 1.2526773842213655e-05 loss: 0.0696 (0.0862) time: 2.9229 data: 0.0077 max mem: 33303 +Epoch: [31] [1750/4276] eta: 2:03:44 lr: 1.2523705434655316e-05 loss: 0.0764 (0.0862) time: 2.9462 data: 0.0076 max mem: 33303 +Epoch: [31] [1760/4276] eta: 2:03:15 lr: 1.2520636943563116e-05 loss: 0.0762 (0.0861) time: 2.9470 data: 0.0075 max mem: 33303 +Epoch: [31] [1770/4276] eta: 2:02:46 lr: 1.2517568368912037e-05 loss: 0.0798 (0.0861) time: 2.9494 data: 0.0074 max mem: 33303 +Epoch: [31] [1780/4276] eta: 2:02:17 lr: 1.2514499710677034e-05 loss: 0.0745 (0.0861) time: 2.9501 data: 0.0073 max mem: 33303 +Epoch: [31] [1790/4276] eta: 2:01:47 lr: 1.2511430968833055e-05 loss: 0.0740 (0.0860) time: 2.9488 data: 0.0075 max mem: 33303 +Epoch: [31] [1800/4276] eta: 2:01:18 lr: 1.2508362143355042e-05 loss: 0.0801 (0.0860) time: 2.9424 data: 0.0077 max mem: 33303 +Epoch: [31] [1810/4276] eta: 2:00:48 lr: 1.2505293234217918e-05 loss: 0.0801 (0.0861) time: 2.9347 data: 0.0080 max mem: 33303 +Epoch: [31] [1820/4276] eta: 2:00:19 lr: 1.2502224241396581e-05 loss: 0.0925 (0.0861) time: 2.9404 data: 0.0084 max mem: 33303 +Epoch: [31] [1830/4276] eta: 1:59:50 lr: 1.2499155164865924e-05 loss: 0.0786 (0.0861) time: 2.9472 data: 0.0083 max mem: 33303 +Epoch: [31] [1840/4276] eta: 1:59:20 lr: 1.2496086004600833e-05 loss: 0.0716 (0.0860) time: 2.9465 data: 0.0080 max mem: 33303 +Epoch: [31] [1850/4276] eta: 1:58:51 lr: 1.2493016760576161e-05 loss: 0.0746 (0.0860) time: 2.9502 data: 0.0078 max mem: 33303 +Epoch: [31] [1860/4276] eta: 1:58:22 lr: 1.2489947432766759e-05 loss: 0.0862 (0.0861) time: 2.9527 data: 0.0078 max mem: 33303 +Epoch: [31] [1870/4276] eta: 1:57:53 lr: 1.2486878021147462e-05 loss: 0.0863 (0.0861) time: 2.9491 data: 0.0081 max mem: 33303 +Epoch: [31] [1880/4276] eta: 1:57:23 lr: 1.2483808525693097e-05 loss: 0.0693 (0.0860) time: 2.9457 data: 0.0079 max mem: 33303 +Epoch: [31] [1890/4276] eta: 1:56:54 lr: 1.2480738946378458e-05 loss: 0.0676 (0.0859) time: 2.9436 data: 0.0078 max mem: 33303 +Epoch: [31] [1900/4276] eta: 1:56:25 lr: 1.247766928317834e-05 loss: 0.0687 (0.0859) time: 2.9419 data: 0.0078 max mem: 33303 +Epoch: [31] [1910/4276] eta: 1:55:55 lr: 1.2474599536067521e-05 loss: 0.0770 (0.0859) time: 2.9419 data: 0.0078 max mem: 33303 +Epoch: [31] [1920/4276] eta: 1:55:26 lr: 1.2471529705020769e-05 loss: 0.0860 (0.0859) time: 2.9426 data: 0.0078 max mem: 33303 +Epoch: [31] [1930/4276] eta: 1:54:56 lr: 1.2468459790012817e-05 loss: 0.0824 (0.0859) time: 2.9391 data: 0.0080 max mem: 33303 +Epoch: [31] [1940/4276] eta: 1:54:27 lr: 1.2465389791018409e-05 loss: 0.0800 (0.0859) time: 2.9310 data: 0.0081 max mem: 33303 +Epoch: [31] [1950/4276] eta: 1:53:57 lr: 1.2462319708012257e-05 loss: 0.0905 (0.0859) time: 2.9289 data: 0.0081 max mem: 33303 +Epoch: [31] [1960/4276] eta: 1:53:28 lr: 1.2459249540969076e-05 loss: 0.0740 (0.0858) time: 2.9339 data: 0.0084 max mem: 33303 +Epoch: [31] [1970/4276] eta: 1:52:58 lr: 1.2456179289863542e-05 loss: 0.0794 (0.0858) time: 2.9370 data: 0.0085 max mem: 33303 +Epoch: [31] [1980/4276] eta: 1:52:29 lr: 1.2453108954670335e-05 loss: 0.0802 (0.0858) time: 2.9362 data: 0.0083 max mem: 33303 +Epoch: [31] [1990/4276] eta: 1:52:00 lr: 1.2450038535364115e-05 loss: 0.0790 (0.0858) time: 2.9347 data: 0.0083 max mem: 33303 +Epoch: [31] [2000/4276] eta: 1:51:30 lr: 1.2446968031919532e-05 loss: 0.0851 (0.0858) time: 2.9362 data: 0.0084 max mem: 33303 +Epoch: [31] [2010/4276] eta: 1:51:01 lr: 1.2443897444311212e-05 loss: 0.0848 (0.0858) time: 2.9412 data: 0.0084 max mem: 33303 +Epoch: [31] [2020/4276] eta: 1:50:31 lr: 1.244082677251377e-05 loss: 0.0790 (0.0858) time: 2.9338 data: 0.0084 max mem: 33303 +Epoch: [31] [2030/4276] eta: 1:50:02 lr: 1.2437756016501812e-05 loss: 0.0714 (0.0857) time: 2.9277 data: 0.0084 max mem: 33303 +Epoch: [31] [2040/4276] eta: 1:49:32 lr: 1.2434685176249928e-05 loss: 0.0664 (0.0857) time: 2.9187 data: 0.0083 max mem: 33303 +Epoch: [31] [2050/4276] eta: 1:49:02 lr: 1.2431614251732682e-05 loss: 0.0796 (0.0857) time: 2.9108 data: 0.0084 max mem: 33303 +Epoch: [31] [2060/4276] eta: 1:48:33 lr: 1.2428543242924637e-05 loss: 0.0846 (0.0857) time: 2.9151 data: 0.0085 max mem: 33303 +Epoch: [31] [2070/4276] eta: 1:48:03 lr: 1.2425472149800333e-05 loss: 0.0787 (0.0857) time: 2.9139 data: 0.0082 max mem: 33303 +Epoch: [31] [2080/4276] eta: 1:47:33 lr: 1.2422400972334309e-05 loss: 0.0770 (0.0857) time: 2.9107 data: 0.0078 max mem: 33303 +Epoch: [31] [2090/4276] eta: 1:47:03 lr: 1.2419329710501066e-05 loss: 0.0770 (0.0857) time: 2.9031 data: 0.0078 max mem: 33303 +Epoch: [31] [2100/4276] eta: 1:46:34 lr: 1.2416258364275108e-05 loss: 0.0900 (0.0857) time: 2.8924 data: 0.0082 max mem: 33303 +Epoch: [31] [2110/4276] eta: 1:46:04 lr: 1.2413186933630924e-05 loss: 0.0886 (0.0857) time: 2.8995 data: 0.0079 max mem: 33303 +Epoch: [31] [2120/4276] eta: 1:45:34 lr: 1.2410115418542973e-05 loss: 0.0666 (0.0856) time: 2.9238 data: 0.0077 max mem: 33303 +Epoch: [31] [2130/4276] eta: 1:45:05 lr: 1.2407043818985719e-05 loss: 0.0641 (0.0856) time: 2.9340 data: 0.0077 max mem: 33303 +Epoch: [31] [2140/4276] eta: 1:44:36 lr: 1.2403972134933597e-05 loss: 0.0758 (0.0855) time: 2.9320 data: 0.0076 max mem: 33303 +Epoch: [31] [2150/4276] eta: 1:44:06 lr: 1.2400900366361044e-05 loss: 0.0739 (0.0855) time: 2.9317 data: 0.0078 max mem: 33303 +Epoch: [31] [2160/4276] eta: 1:43:37 lr: 1.2397828513242452e-05 loss: 0.0697 (0.0854) time: 2.9359 data: 0.0080 max mem: 33303 +Epoch: [31] [2170/4276] eta: 1:43:07 lr: 1.2394756575552227e-05 loss: 0.0817 (0.0855) time: 2.9197 data: 0.0078 max mem: 33303 +Epoch: [31] [2180/4276] eta: 1:42:37 lr: 1.2391684553264752e-05 loss: 0.0817 (0.0854) time: 2.8930 data: 0.0080 max mem: 33303 +Epoch: [31] [2190/4276] eta: 1:42:08 lr: 1.2388612446354394e-05 loss: 0.0847 (0.0855) time: 2.8998 data: 0.0085 max mem: 33303 +Epoch: [31] [2200/4276] eta: 1:41:38 lr: 1.2385540254795496e-05 loss: 0.0847 (0.0855) time: 2.9258 data: 0.0086 max mem: 33303 +Epoch: [31] [2210/4276] eta: 1:41:09 lr: 1.23824679785624e-05 loss: 0.0861 (0.0855) time: 2.9379 data: 0.0083 max mem: 33303 +Epoch: [31] [2220/4276] eta: 1:40:39 lr: 1.2379395617629429e-05 loss: 0.0861 (0.0855) time: 2.9367 data: 0.0080 max mem: 33303 +Epoch: [31] [2230/4276] eta: 1:40:10 lr: 1.2376323171970892e-05 loss: 0.0766 (0.0855) time: 2.9344 data: 0.0079 max mem: 33303 +Epoch: [31] [2240/4276] eta: 1:39:41 lr: 1.2373250641561073e-05 loss: 0.0693 (0.0854) time: 2.9351 data: 0.0081 max mem: 33303 +Epoch: [31] [2250/4276] eta: 1:39:11 lr: 1.237017802637425e-05 loss: 0.0672 (0.0853) time: 2.9352 data: 0.0080 max mem: 33303 +Epoch: [31] [2260/4276] eta: 1:38:42 lr: 1.236710532638469e-05 loss: 0.0762 (0.0854) time: 2.9342 data: 0.0078 max mem: 33303 +Epoch: [31] [2270/4276] eta: 1:38:12 lr: 1.2364032541566645e-05 loss: 0.0881 (0.0854) time: 2.9254 data: 0.0079 max mem: 33303 +Epoch: [31] [2280/4276] eta: 1:37:43 lr: 1.2360959671894335e-05 loss: 0.0797 (0.0854) time: 2.9177 data: 0.0081 max mem: 33303 +Epoch: [31] [2290/4276] eta: 1:37:13 lr: 1.2357886717341985e-05 loss: 0.0773 (0.0853) time: 2.8964 data: 0.0086 max mem: 33303 +Epoch: [31] [2300/4276] eta: 1:36:43 lr: 1.2354813677883793e-05 loss: 0.0773 (0.0853) time: 2.8685 data: 0.0088 max mem: 33303 +Epoch: [31] [2310/4276] eta: 1:36:13 lr: 1.2351740553493956e-05 loss: 0.0860 (0.0854) time: 2.8629 data: 0.0086 max mem: 33303 +Epoch: [31] [2320/4276] eta: 1:35:43 lr: 1.2348667344146633e-05 loss: 0.0836 (0.0854) time: 2.8662 data: 0.0085 max mem: 33303 +Epoch: [31] [2330/4276] eta: 1:35:13 lr: 1.2345594049815987e-05 loss: 0.0787 (0.0853) time: 2.8789 data: 0.0081 max mem: 33303 +Epoch: [31] [2340/4276] eta: 1:34:44 lr: 1.2342520670476162e-05 loss: 0.0815 (0.0853) time: 2.9045 data: 0.0084 max mem: 33303 +Epoch: [31] [2350/4276] eta: 1:34:14 lr: 1.2339447206101291e-05 loss: 0.0770 (0.0853) time: 2.9085 data: 0.0091 max mem: 33303 +Epoch: [31] [2360/4276] eta: 1:33:44 lr: 1.2336373656665474e-05 loss: 0.0739 (0.0853) time: 2.8951 data: 0.0090 max mem: 33303 +Epoch: [31] [2370/4276] eta: 1:33:14 lr: 1.2333300022142814e-05 loss: 0.0748 (0.0853) time: 2.8886 data: 0.0082 max mem: 33303 +Epoch: [31] [2380/4276] eta: 1:32:45 lr: 1.2330226302507394e-05 loss: 0.0698 (0.0853) time: 2.8882 data: 0.0078 max mem: 33303 +Epoch: [31] [2390/4276] eta: 1:32:15 lr: 1.2327152497733287e-05 loss: 0.0751 (0.0852) time: 2.8888 data: 0.0081 max mem: 33303 +Epoch: [31] [2400/4276] eta: 1:31:45 lr: 1.2324078607794532e-05 loss: 0.0869 (0.0853) time: 2.8838 data: 0.0080 max mem: 33303 +Epoch: [31] [2410/4276] eta: 1:31:15 lr: 1.2321004632665172e-05 loss: 0.0808 (0.0852) time: 2.8819 data: 0.0078 max mem: 33303 +Epoch: [31] [2420/4276] eta: 1:30:46 lr: 1.2317930572319235e-05 loss: 0.0734 (0.0852) time: 2.8817 data: 0.0080 max mem: 33303 +Epoch: [31] [2430/4276] eta: 1:30:16 lr: 1.2314856426730719e-05 loss: 0.0818 (0.0853) time: 2.8829 data: 0.0082 max mem: 33303 +Epoch: [31] [2440/4276] eta: 1:29:46 lr: 1.2311782195873617e-05 loss: 0.0876 (0.0852) time: 2.8820 data: 0.0084 max mem: 33303 +Epoch: [31] [2450/4276] eta: 1:29:16 lr: 1.2308707879721906e-05 loss: 0.0791 (0.0852) time: 2.8822 data: 0.0086 max mem: 33303 +Epoch: [31] [2460/4276] eta: 1:28:47 lr: 1.2305633478249557e-05 loss: 0.0783 (0.0852) time: 2.8833 data: 0.0088 max mem: 33303 +Epoch: [31] [2470/4276] eta: 1:28:17 lr: 1.2302558991430501e-05 loss: 0.0687 (0.0852) time: 2.8840 data: 0.0088 max mem: 33303 +Epoch: [31] [2480/4276] eta: 1:27:47 lr: 1.2299484419238674e-05 loss: 0.0778 (0.0852) time: 2.8834 data: 0.0088 max mem: 33303 +Epoch: [31] [2490/4276] eta: 1:27:18 lr: 1.2296409761647995e-05 loss: 0.0886 (0.0852) time: 2.8824 data: 0.0088 max mem: 33303 +Epoch: [31] [2500/4276] eta: 1:26:48 lr: 1.2293335018632369e-05 loss: 0.0883 (0.0852) time: 2.8836 data: 0.0088 max mem: 33303 +Epoch: [31] [2510/4276] eta: 1:26:18 lr: 1.2290260190165667e-05 loss: 0.0883 (0.0852) time: 2.8823 data: 0.0088 max mem: 33303 +Epoch: [31] [2520/4276] eta: 1:25:49 lr: 1.228718527622177e-05 loss: 0.0861 (0.0852) time: 2.8818 data: 0.0088 max mem: 33303 +Epoch: [31] [2530/4276] eta: 1:25:19 lr: 1.2284110276774526e-05 loss: 0.0697 (0.0852) time: 2.8838 data: 0.0088 max mem: 33303 +Epoch: [31] [2540/4276] eta: 1:24:49 lr: 1.2281035191797786e-05 loss: 0.0697 (0.0852) time: 2.8838 data: 0.0088 max mem: 33303 +Epoch: [31] [2550/4276] eta: 1:24:20 lr: 1.2277960021265359e-05 loss: 0.0760 (0.0851) time: 2.8835 data: 0.0088 max mem: 33303 +Epoch: [31] [2560/4276] eta: 1:23:50 lr: 1.2274884765151063e-05 loss: 0.0677 (0.0851) time: 2.8827 data: 0.0088 max mem: 33303 +Epoch: [31] [2570/4276] eta: 1:23:20 lr: 1.2271809423428688e-05 loss: 0.0674 (0.0851) time: 2.8820 data: 0.0088 max mem: 33303 +Epoch: [31] [2580/4276] eta: 1:22:51 lr: 1.2268733996072023e-05 loss: 0.0716 (0.0850) time: 2.8823 data: 0.0088 max mem: 33303 +Epoch: [31] [2590/4276] eta: 1:22:21 lr: 1.2265658483054813e-05 loss: 0.0673 (0.0850) time: 2.8803 data: 0.0088 max mem: 33303 +Epoch: [31] [2600/4276] eta: 1:21:52 lr: 1.2262582884350814e-05 loss: 0.0658 (0.0849) time: 2.8827 data: 0.0085 max mem: 33303 +Epoch: [31] [2610/4276] eta: 1:21:22 lr: 1.2259507199933761e-05 loss: 0.0767 (0.0849) time: 2.8944 data: 0.0087 max mem: 33303 +Epoch: [31] [2620/4276] eta: 1:20:52 lr: 1.2256431429777373e-05 loss: 0.0828 (0.0849) time: 2.8937 data: 0.0087 max mem: 33303 +Epoch: [31] [2630/4276] eta: 1:20:23 lr: 1.225335557385534e-05 loss: 0.0849 (0.0849) time: 2.8894 data: 0.0079 max mem: 33303 +Epoch: [31] [2640/4276] eta: 1:19:53 lr: 1.2250279632141357e-05 loss: 0.0635 (0.0849) time: 2.8973 data: 0.0079 max mem: 33303 +Epoch: [31] [2650/4276] eta: 1:19:24 lr: 1.2247203604609092e-05 loss: 0.0727 (0.0849) time: 2.9032 data: 0.0085 max mem: 33303 +Epoch: [31] [2660/4276] eta: 1:18:55 lr: 1.2244127491232207e-05 loss: 0.0769 (0.0849) time: 2.9127 data: 0.0086 max mem: 33303 +Epoch: [31] [2670/4276] eta: 1:18:25 lr: 1.2241051291984327e-05 loss: 0.0822 (0.0849) time: 2.9075 data: 0.0084 max mem: 33303 +Epoch: [31] [2680/4276] eta: 1:17:55 lr: 1.2237975006839087e-05 loss: 0.0843 (0.0849) time: 2.8883 data: 0.0080 max mem: 33303 +Epoch: [31] [2690/4276] eta: 1:17:26 lr: 1.2234898635770092e-05 loss: 0.0799 (0.0849) time: 2.8812 data: 0.0078 max mem: 33303 +Epoch: [31] [2700/4276] eta: 1:16:56 lr: 1.2231822178750942e-05 loss: 0.0750 (0.0849) time: 2.8771 data: 0.0078 max mem: 33303 +Epoch: [31] [2710/4276] eta: 1:16:27 lr: 1.2228745635755207e-05 loss: 0.0750 (0.0849) time: 2.8746 data: 0.0077 max mem: 33303 +Epoch: [31] [2720/4276] eta: 1:15:57 lr: 1.2225669006756449e-05 loss: 0.0663 (0.0848) time: 2.8761 data: 0.0076 max mem: 33303 +Epoch: [31] [2730/4276] eta: 1:15:28 lr: 1.2222592291728224e-05 loss: 0.0674 (0.0848) time: 2.8874 data: 0.0079 max mem: 33303 +Epoch: [31] [2740/4276] eta: 1:14:58 lr: 1.2219515490644051e-05 loss: 0.0758 (0.0848) time: 2.8992 data: 0.0087 max mem: 33303 +Epoch: [31] [2750/4276] eta: 1:14:29 lr: 1.2216438603477452e-05 loss: 0.0753 (0.0848) time: 2.8973 data: 0.0085 max mem: 33303 +Epoch: [31] [2760/4276] eta: 1:13:59 lr: 1.2213361630201926e-05 loss: 0.0652 (0.0847) time: 2.9005 data: 0.0087 max mem: 33303 +Epoch: [31] [2770/4276] eta: 1:13:30 lr: 1.2210284570790965e-05 loss: 0.0652 (0.0847) time: 2.9047 data: 0.0093 max mem: 33303 +Epoch: [31] [2780/4276] eta: 1:13:00 lr: 1.2207207425218025e-05 loss: 0.0816 (0.0847) time: 2.8905 data: 0.0086 max mem: 33303 +Epoch: [31] [2790/4276] eta: 1:12:31 lr: 1.2204130193456566e-05 loss: 0.0858 (0.0847) time: 2.8835 data: 0.0083 max mem: 33303 +Epoch: [31] [2800/4276] eta: 1:12:01 lr: 1.2201052875480025e-05 loss: 0.0785 (0.0847) time: 2.8965 data: 0.0082 max mem: 33303 +Epoch: [31] [2810/4276] eta: 1:11:32 lr: 1.219797547126183e-05 loss: 0.0648 (0.0846) time: 2.9120 data: 0.0086 max mem: 33303 +Epoch: [31] [2820/4276] eta: 1:11:03 lr: 1.2194897980775378e-05 loss: 0.0650 (0.0846) time: 2.9264 data: 0.0089 max mem: 33303 +Epoch: [31] [2830/4276] eta: 1:10:34 lr: 1.219182040399406e-05 loss: 0.0740 (0.0846) time: 2.9319 data: 0.0086 max mem: 33303 +Epoch: [31] [2840/4276] eta: 1:10:04 lr: 1.2188742740891258e-05 loss: 0.0894 (0.0846) time: 2.9315 data: 0.0087 max mem: 33303 +Epoch: [31] [2850/4276] eta: 1:09:35 lr: 1.2185664991440332e-05 loss: 0.0909 (0.0846) time: 2.9327 data: 0.0087 max mem: 33303 +Epoch: [31] [2860/4276] eta: 1:09:06 lr: 1.2182587155614617e-05 loss: 0.0772 (0.0846) time: 2.9309 data: 0.0083 max mem: 33303 +Epoch: [31] [2870/4276] eta: 1:08:36 lr: 1.2179509233387446e-05 loss: 0.0794 (0.0846) time: 2.9159 data: 0.0080 max mem: 33303 +Epoch: [31] [2880/4276] eta: 1:08:07 lr: 1.2176431224732131e-05 loss: 0.0794 (0.0846) time: 2.9156 data: 0.0079 max mem: 33303 +Epoch: [31] [2890/4276] eta: 1:07:38 lr: 1.2173353129621975e-05 loss: 0.0786 (0.0846) time: 2.9275 data: 0.0076 max mem: 33303 +Epoch: [31] [2900/4276] eta: 1:07:08 lr: 1.2170274948030245e-05 loss: 0.0742 (0.0846) time: 2.9261 data: 0.0072 max mem: 33303 +Epoch: [31] [2910/4276] eta: 1:06:39 lr: 1.2167196679930215e-05 loss: 0.0869 (0.0846) time: 2.9268 data: 0.0073 max mem: 33303 +Epoch: [31] [2920/4276] eta: 1:06:10 lr: 1.2164118325295133e-05 loss: 0.0919 (0.0846) time: 2.9285 data: 0.0075 max mem: 33303 +Epoch: [31] [2930/4276] eta: 1:05:41 lr: 1.2161039884098238e-05 loss: 0.0863 (0.0846) time: 2.9274 data: 0.0075 max mem: 33303 +Epoch: [31] [2940/4276] eta: 1:05:11 lr: 1.2157961356312737e-05 loss: 0.0785 (0.0846) time: 2.9272 data: 0.0073 max mem: 33303 +Epoch: [31] [2950/4276] eta: 1:04:42 lr: 1.2154882741911835e-05 loss: 0.0804 (0.0846) time: 2.9277 data: 0.0073 max mem: 33303 +Epoch: [31] [2960/4276] eta: 1:04:13 lr: 1.215180404086872e-05 loss: 0.0816 (0.0846) time: 2.9224 data: 0.0078 max mem: 33303 +Epoch: [31] [2970/4276] eta: 1:03:43 lr: 1.2148725253156568e-05 loss: 0.0785 (0.0846) time: 2.9226 data: 0.0083 max mem: 33303 +Epoch: [31] [2980/4276] eta: 1:03:14 lr: 1.2145646378748523e-05 loss: 0.0756 (0.0846) time: 2.9261 data: 0.0080 max mem: 33303 +Epoch: [31] [2990/4276] eta: 1:02:45 lr: 1.2142567417617725e-05 loss: 0.0755 (0.0846) time: 2.9251 data: 0.0076 max mem: 33303 +Epoch: [31] [3000/4276] eta: 1:02:16 lr: 1.2139488369737302e-05 loss: 0.0764 (0.0846) time: 2.9274 data: 0.0081 max mem: 33303 +Epoch: [31] [3010/4276] eta: 1:01:46 lr: 1.213640923508036e-05 loss: 0.0764 (0.0846) time: 2.9311 data: 0.0084 max mem: 33303 +Epoch: [31] [3020/4276] eta: 1:01:17 lr: 1.2133330013619983e-05 loss: 0.0766 (0.0846) time: 2.9327 data: 0.0079 max mem: 33303 +Epoch: [31] [3030/4276] eta: 1:00:48 lr: 1.213025070532925e-05 loss: 0.0803 (0.0846) time: 2.9298 data: 0.0077 max mem: 33303 +Epoch: [31] [3040/4276] eta: 1:00:19 lr: 1.2127171310181223e-05 loss: 0.0899 (0.0846) time: 2.9258 data: 0.0076 max mem: 33303 +Epoch: [31] [3050/4276] eta: 0:59:49 lr: 1.2124091828148939e-05 loss: 0.0912 (0.0846) time: 2.9256 data: 0.0079 max mem: 33303 +Epoch: [31] [3060/4276] eta: 0:59:20 lr: 1.2121012259205425e-05 loss: 0.0682 (0.0845) time: 2.9260 data: 0.0081 max mem: 33303 +Epoch: [31] [3070/4276] eta: 0:58:51 lr: 1.2117932603323695e-05 loss: 0.0702 (0.0845) time: 2.9263 data: 0.0079 max mem: 33303 +Epoch: [31] [3080/4276] eta: 0:58:21 lr: 1.211485286047675e-05 loss: 0.0719 (0.0845) time: 2.9259 data: 0.0079 max mem: 33303 +Epoch: [31] [3090/4276] eta: 0:57:52 lr: 1.2111773030637555e-05 loss: 0.0736 (0.0845) time: 2.9258 data: 0.0079 max mem: 33303 +Epoch: [31] [3100/4276] eta: 0:57:23 lr: 1.2108693113779079e-05 loss: 0.0736 (0.0845) time: 2.9293 data: 0.0077 max mem: 33303 +Epoch: [31] [3110/4276] eta: 0:56:54 lr: 1.210561310987427e-05 loss: 0.0729 (0.0845) time: 2.9261 data: 0.0080 max mem: 33303 +Epoch: [31] [3120/4276] eta: 0:56:24 lr: 1.2102533018896063e-05 loss: 0.0729 (0.0844) time: 2.9282 data: 0.0083 max mem: 33303 +Epoch: [31] [3130/4276] eta: 0:55:55 lr: 1.2099452840817362e-05 loss: 0.0766 (0.0844) time: 2.9193 data: 0.0088 max mem: 33303 +Epoch: [31] [3140/4276] eta: 0:55:25 lr: 1.2096372575611073e-05 loss: 0.0766 (0.0844) time: 2.8939 data: 0.0089 max mem: 33303 +Epoch: [31] [3150/4276] eta: 0:54:56 lr: 1.2093292223250075e-05 loss: 0.0732 (0.0844) time: 2.9068 data: 0.0081 max mem: 33303 +Epoch: [31] [3160/4276] eta: 0:54:27 lr: 1.2090211783707241e-05 loss: 0.0798 (0.0844) time: 2.9280 data: 0.0077 max mem: 33303 +Epoch: [31] [3170/4276] eta: 0:53:58 lr: 1.2087131256955411e-05 loss: 0.0805 (0.0844) time: 2.9332 data: 0.0078 max mem: 33303 +Epoch: [31] [3180/4276] eta: 0:53:28 lr: 1.2084050642967423e-05 loss: 0.0805 (0.0844) time: 2.9391 data: 0.0079 max mem: 33303 +Epoch: [31] [3190/4276] eta: 0:52:59 lr: 1.2080969941716098e-05 loss: 0.0821 (0.0844) time: 2.9393 data: 0.0078 max mem: 33303 +Epoch: [31] [3200/4276] eta: 0:52:30 lr: 1.207788915317424e-05 loss: 0.0813 (0.0844) time: 2.9399 data: 0.0079 max mem: 33303 +Epoch: [31] [3210/4276] eta: 0:52:01 lr: 1.2074808277314625e-05 loss: 0.0739 (0.0844) time: 2.9359 data: 0.0080 max mem: 33303 +Epoch: [31] [3220/4276] eta: 0:51:31 lr: 1.2071727314110024e-05 loss: 0.0754 (0.0844) time: 2.9100 data: 0.0082 max mem: 33303 +Epoch: [31] [3230/4276] eta: 0:51:02 lr: 1.2068646263533196e-05 loss: 0.0772 (0.0844) time: 2.8879 data: 0.0081 max mem: 33303 +Epoch: [31] [3240/4276] eta: 0:50:32 lr: 1.206556512555688e-05 loss: 0.0795 (0.0844) time: 2.8881 data: 0.0082 max mem: 33303 +Epoch: [31] [3250/4276] eta: 0:50:03 lr: 1.2062483900153789e-05 loss: 0.0922 (0.0845) time: 2.8874 data: 0.0085 max mem: 33303 +Epoch: [31] [3260/4276] eta: 0:49:34 lr: 1.2059402587296627e-05 loss: 0.0843 (0.0845) time: 2.9033 data: 0.0090 max mem: 33303 +Epoch: [31] [3270/4276] eta: 0:49:04 lr: 1.2056321186958085e-05 loss: 0.0843 (0.0845) time: 2.9177 data: 0.0095 max mem: 33303 +Epoch: [31] [3280/4276] eta: 0:48:35 lr: 1.2053239699110844e-05 loss: 0.0881 (0.0845) time: 2.9114 data: 0.0093 max mem: 33303 +Epoch: [31] [3290/4276] eta: 0:48:06 lr: 1.2050158123727543e-05 loss: 0.0909 (0.0845) time: 2.9153 data: 0.0088 max mem: 33303 +Epoch: [31] [3300/4276] eta: 0:47:37 lr: 1.2047076460780827e-05 loss: 0.0874 (0.0846) time: 2.9333 data: 0.0082 max mem: 33303 +Epoch: [31] [3310/4276] eta: 0:47:07 lr: 1.2043994710243322e-05 loss: 0.0869 (0.0846) time: 2.9409 data: 0.0082 max mem: 33303 +Epoch: [31] [3320/4276] eta: 0:46:38 lr: 1.2040912872087638e-05 loss: 0.0869 (0.0846) time: 2.9396 data: 0.0080 max mem: 33303 +Epoch: [31] [3330/4276] eta: 0:46:09 lr: 1.2037830946286353e-05 loss: 0.0815 (0.0846) time: 2.9407 data: 0.0079 max mem: 33303 +Epoch: [31] [3340/4276] eta: 0:45:40 lr: 1.203474893281205e-05 loss: 0.0797 (0.0846) time: 2.9404 data: 0.0081 max mem: 33303 +Epoch: [31] [3350/4276] eta: 0:45:10 lr: 1.2031666831637289e-05 loss: 0.0812 (0.0846) time: 2.9331 data: 0.0084 max mem: 33303 +Epoch: [31] [3360/4276] eta: 0:44:41 lr: 1.20285846427346e-05 loss: 0.0776 (0.0845) time: 2.9153 data: 0.0087 max mem: 33303 +Epoch: [31] [3370/4276] eta: 0:44:12 lr: 1.2025502366076514e-05 loss: 0.0815 (0.0846) time: 2.8996 data: 0.0083 max mem: 33303 +Epoch: [31] [3380/4276] eta: 0:43:42 lr: 1.2022420001635538e-05 loss: 0.0833 (0.0846) time: 2.9001 data: 0.0083 max mem: 33303 +Epoch: [31] [3390/4276] eta: 0:43:13 lr: 1.2019337549384172e-05 loss: 0.0751 (0.0846) time: 2.8989 data: 0.0089 max mem: 33303 +Epoch: [31] [3400/4276] eta: 0:42:44 lr: 1.2016255009294876e-05 loss: 0.0781 (0.0845) time: 2.8931 data: 0.0085 max mem: 33303 +Epoch: [31] [3410/4276] eta: 0:42:14 lr: 1.2013172381340117e-05 loss: 0.0861 (0.0846) time: 2.9029 data: 0.0081 max mem: 33303 +Epoch: [31] [3420/4276] eta: 0:41:45 lr: 1.2010089665492335e-05 loss: 0.0801 (0.0846) time: 2.9108 data: 0.0084 max mem: 33303 +Epoch: [31] [3430/4276] eta: 0:41:16 lr: 1.2007006861723965e-05 loss: 0.0820 (0.0846) time: 2.9045 data: 0.0089 max mem: 33303 +Epoch: [31] [3440/4276] eta: 0:40:46 lr: 1.2003923970007401e-05 loss: 0.0839 (0.0846) time: 2.9083 data: 0.0088 max mem: 33303 +Epoch: [31] [3450/4276] eta: 0:40:17 lr: 1.2000840990315043e-05 loss: 0.0859 (0.0846) time: 2.9110 data: 0.0087 max mem: 33303 +Epoch: [31] [3460/4276] eta: 0:39:48 lr: 1.1997757922619269e-05 loss: 0.0928 (0.0847) time: 2.9000 data: 0.0084 max mem: 33303 +Epoch: [31] [3470/4276] eta: 0:39:18 lr: 1.199467476689244e-05 loss: 0.0821 (0.0846) time: 2.9150 data: 0.0083 max mem: 33303 +Epoch: [31] [3480/4276] eta: 0:38:49 lr: 1.1991591523106892e-05 loss: 0.0845 (0.0847) time: 2.9357 data: 0.0079 max mem: 33303 +Epoch: [31] [3490/4276] eta: 0:38:20 lr: 1.1988508191234953e-05 loss: 0.0817 (0.0847) time: 2.9360 data: 0.0074 max mem: 33303 +Epoch: [31] [3500/4276] eta: 0:37:51 lr: 1.1985424771248936e-05 loss: 0.0725 (0.0846) time: 2.9343 data: 0.0076 max mem: 33303 +Epoch: [31] [3510/4276] eta: 0:37:21 lr: 1.1982341263121138e-05 loss: 0.0842 (0.0846) time: 2.9323 data: 0.0076 max mem: 33303 +Epoch: [31] [3520/4276] eta: 0:36:52 lr: 1.1979257666823826e-05 loss: 0.0774 (0.0846) time: 2.9298 data: 0.0079 max mem: 33303 +Epoch: [31] [3530/4276] eta: 0:36:23 lr: 1.1976173982329264e-05 loss: 0.0774 (0.0847) time: 2.9337 data: 0.0082 max mem: 33303 +Epoch: [31] [3540/4276] eta: 0:35:54 lr: 1.1973090209609695e-05 loss: 0.0841 (0.0847) time: 2.9372 data: 0.0082 max mem: 33303 +Epoch: [31] [3550/4276] eta: 0:35:24 lr: 1.1970006348637352e-05 loss: 0.0789 (0.0846) time: 2.9300 data: 0.0086 max mem: 33303 +Epoch: [31] [3560/4276] eta: 0:34:55 lr: 1.1966922399384433e-05 loss: 0.0751 (0.0846) time: 2.9078 data: 0.0088 max mem: 33303 +Epoch: [31] [3570/4276] eta: 0:34:26 lr: 1.1963838361823137e-05 loss: 0.0828 (0.0847) time: 2.8988 data: 0.0087 max mem: 33303 +Epoch: [31] [3580/4276] eta: 0:33:56 lr: 1.196075423592564e-05 loss: 0.0774 (0.0846) time: 2.8950 data: 0.0086 max mem: 33303 +Epoch: [31] [3590/4276] eta: 0:33:27 lr: 1.195767002166411e-05 loss: 0.0744 (0.0846) time: 2.8934 data: 0.0086 max mem: 33303 +Epoch: [31] [3600/4276] eta: 0:32:58 lr: 1.1954585719010673e-05 loss: 0.0814 (0.0846) time: 2.9067 data: 0.0081 max mem: 33303 +Epoch: [31] [3610/4276] eta: 0:32:29 lr: 1.1951501327937466e-05 loss: 0.0813 (0.0846) time: 2.9246 data: 0.0076 max mem: 33303 +Epoch: [31] [3620/4276] eta: 0:31:59 lr: 1.1948416848416595e-05 loss: 0.0728 (0.0846) time: 2.9400 data: 0.0072 max mem: 33303 +Epoch: [31] [3630/4276] eta: 0:31:30 lr: 1.194533228042016e-05 loss: 0.0815 (0.0846) time: 2.9380 data: 0.0071 max mem: 33303 +Epoch: [31] [3640/4276] eta: 0:31:01 lr: 1.1942247623920226e-05 loss: 0.0918 (0.0846) time: 2.9377 data: 0.0070 max mem: 33303 +Epoch: [31] [3650/4276] eta: 0:30:32 lr: 1.1939162878888854e-05 loss: 0.0816 (0.0846) time: 2.9487 data: 0.0070 max mem: 33303 +Epoch: [31] [3660/4276] eta: 0:30:02 lr: 1.1936078045298096e-05 loss: 0.0832 (0.0846) time: 2.9647 data: 0.0074 max mem: 33303 +Epoch: [31] [3670/4276] eta: 0:29:33 lr: 1.1932993123119964e-05 loss: 0.0853 (0.0846) time: 2.9566 data: 0.0079 max mem: 33303 +Epoch: [31] [3680/4276] eta: 0:29:04 lr: 1.1929908112326472e-05 loss: 0.0853 (0.0846) time: 2.9401 data: 0.0079 max mem: 33303 +Epoch: [31] [3690/4276] eta: 0:28:35 lr: 1.1926823012889609e-05 loss: 0.0909 (0.0847) time: 2.9403 data: 0.0075 max mem: 33303 +Epoch: [31] [3700/4276] eta: 0:28:05 lr: 1.192373782478136e-05 loss: 0.0866 (0.0847) time: 2.9429 data: 0.0076 max mem: 33303 +Epoch: [31] [3710/4276] eta: 0:27:36 lr: 1.1920652547973669e-05 loss: 0.0719 (0.0846) time: 2.9549 data: 0.0077 max mem: 33303 +Epoch: [31] [3720/4276] eta: 0:27:07 lr: 1.191756718243848e-05 loss: 0.0734 (0.0847) time: 2.9596 data: 0.0077 max mem: 33303 +Epoch: [31] [3730/4276] eta: 0:26:38 lr: 1.1914481728147722e-05 loss: 0.0890 (0.0847) time: 2.9283 data: 0.0071 max mem: 33303 +Epoch: [31] [3740/4276] eta: 0:26:08 lr: 1.19113961850733e-05 loss: 0.0794 (0.0846) time: 2.9006 data: 0.0065 max mem: 33303 +Epoch: [31] [3750/4276] eta: 0:25:39 lr: 1.1908310553187099e-05 loss: 0.0864 (0.0847) time: 2.8938 data: 0.0067 max mem: 33303 +Epoch: [31] [3760/4276] eta: 0:25:10 lr: 1.1905224832460994e-05 loss: 0.0832 (0.0846) time: 2.8985 data: 0.0066 max mem: 33303 +Epoch: [31] [3770/4276] eta: 0:24:40 lr: 1.1902139022866843e-05 loss: 0.0689 (0.0846) time: 2.9029 data: 0.0067 max mem: 33303 +Epoch: [31] [3780/4276] eta: 0:24:11 lr: 1.1899053124376489e-05 loss: 0.0706 (0.0846) time: 2.9006 data: 0.0068 max mem: 33303 +Epoch: [31] [3790/4276] eta: 0:23:42 lr: 1.1895967136961742e-05 loss: 0.0706 (0.0846) time: 2.9296 data: 0.0074 max mem: 33303 +Epoch: [31] [3800/4276] eta: 0:23:13 lr: 1.1892881060594412e-05 loss: 0.0788 (0.0846) time: 2.9306 data: 0.0074 max mem: 33303 +Epoch: [31] [3810/4276] eta: 0:22:43 lr: 1.1889794895246287e-05 loss: 0.0831 (0.0845) time: 2.9131 data: 0.0078 max mem: 33303 +Epoch: [31] [3820/4276] eta: 0:22:14 lr: 1.1886708640889146e-05 loss: 0.0693 (0.0845) time: 2.9203 data: 0.0086 max mem: 33303 +Epoch: [31] [3830/4276] eta: 0:21:45 lr: 1.1883622297494726e-05 loss: 0.0693 (0.0845) time: 2.9161 data: 0.0086 max mem: 33303 +Epoch: [31] [3840/4276] eta: 0:21:16 lr: 1.1880535865034772e-05 loss: 0.0733 (0.0845) time: 2.9355 data: 0.0079 max mem: 33303 +Epoch: [31] [3850/4276] eta: 0:20:46 lr: 1.1877449343481003e-05 loss: 0.0733 (0.0844) time: 2.9571 data: 0.0071 max mem: 33303 +Epoch: [31] [3860/4276] eta: 0:20:17 lr: 1.1874362732805127e-05 loss: 0.0818 (0.0845) time: 2.9553 data: 0.0075 max mem: 33303 +Epoch: [31] [3870/4276] eta: 0:19:48 lr: 1.1871276032978815e-05 loss: 0.0787 (0.0844) time: 2.9337 data: 0.0078 max mem: 33303 +Epoch: [31] [3880/4276] eta: 0:19:19 lr: 1.1868189243973742e-05 loss: 0.0770 (0.0844) time: 2.9111 data: 0.0075 max mem: 33303 +Epoch: [31] [3890/4276] eta: 0:18:49 lr: 1.1865102365761559e-05 loss: 0.0807 (0.0844) time: 2.9054 data: 0.0074 max mem: 33303 +Epoch: [31] [3900/4276] eta: 0:18:20 lr: 1.1862015398313903e-05 loss: 0.0726 (0.0844) time: 2.9029 data: 0.0075 max mem: 33303 +Epoch: [31] [3910/4276] eta: 0:17:51 lr: 1.1858928341602381e-05 loss: 0.0709 (0.0844) time: 2.9004 data: 0.0075 max mem: 33303 +Epoch: [31] [3920/4276] eta: 0:17:21 lr: 1.1855841195598594e-05 loss: 0.0719 (0.0844) time: 2.9071 data: 0.0078 max mem: 33303 +Epoch: [31] [3930/4276] eta: 0:16:52 lr: 1.1852753960274128e-05 loss: 0.0764 (0.0844) time: 2.9267 data: 0.0082 max mem: 33303 +Epoch: [31] [3940/4276] eta: 0:16:23 lr: 1.184966663560055e-05 loss: 0.0764 (0.0844) time: 2.9469 data: 0.0085 max mem: 33303 +Epoch: [31] [3950/4276] eta: 0:15:54 lr: 1.1846579221549396e-05 loss: 0.0763 (0.0843) time: 2.9567 data: 0.0083 max mem: 33303 +Epoch: [31] [3960/4276] eta: 0:15:24 lr: 1.1843491718092201e-05 loss: 0.0851 (0.0843) time: 2.9508 data: 0.0079 max mem: 33303 +Epoch: [31] [3970/4276] eta: 0:14:55 lr: 1.1840404125200484e-05 loss: 0.0821 (0.0843) time: 2.9490 data: 0.0079 max mem: 33303 +Epoch: [31] [3980/4276] eta: 0:14:26 lr: 1.1837316442845728e-05 loss: 0.0830 (0.0844) time: 2.9490 data: 0.0079 max mem: 33303 +Epoch: [31] [3990/4276] eta: 0:13:57 lr: 1.1834228670999415e-05 loss: 0.0844 (0.0844) time: 2.9461 data: 0.0081 max mem: 33303 +Epoch: [31] [4000/4276] eta: 0:13:27 lr: 1.1831140809633007e-05 loss: 0.0728 (0.0844) time: 2.9433 data: 0.0086 max mem: 33303 +Epoch: [31] [4010/4276] eta: 0:12:58 lr: 1.1828052858717955e-05 loss: 0.0752 (0.0844) time: 2.9439 data: 0.0088 max mem: 33303 +Epoch: [31] [4020/4276] eta: 0:12:29 lr: 1.1824964818225666e-05 loss: 0.0890 (0.0844) time: 2.9537 data: 0.0085 max mem: 33303 +Epoch: [31] [4030/4276] eta: 0:12:00 lr: 1.1821876688127561e-05 loss: 0.0780 (0.0844) time: 2.9753 data: 0.0085 max mem: 33303 +Epoch: [31] [4040/4276] eta: 0:11:30 lr: 1.1818788468395025e-05 loss: 0.0768 (0.0844) time: 2.9642 data: 0.0087 max mem: 33303 +Epoch: [31] [4050/4276] eta: 0:11:01 lr: 1.1815700158999442e-05 loss: 0.0891 (0.0844) time: 2.9458 data: 0.0085 max mem: 33303 +Epoch: [31] [4060/4276] eta: 0:10:32 lr: 1.1812611759912152e-05 loss: 0.0771 (0.0844) time: 2.9524 data: 0.0082 max mem: 33303 +Epoch: [31] [4070/4276] eta: 0:10:03 lr: 1.1809523271104503e-05 loss: 0.0771 (0.0844) time: 2.9342 data: 0.0080 max mem: 33303 +Epoch: [31] [4080/4276] eta: 0:09:33 lr: 1.1806434692547811e-05 loss: 0.0793 (0.0844) time: 2.9084 data: 0.0083 max mem: 33303 +Epoch: [31] [4090/4276] eta: 0:09:04 lr: 1.180334602421339e-05 loss: 0.0990 (0.0844) time: 2.9057 data: 0.0085 max mem: 33303 +Epoch: [31] [4100/4276] eta: 0:08:35 lr: 1.180025726607251e-05 loss: 0.0889 (0.0844) time: 2.9432 data: 0.0094 max mem: 33303 +Epoch: [31] [4110/4276] eta: 0:08:05 lr: 1.1797168418096447e-05 loss: 0.0834 (0.0844) time: 2.9691 data: 0.0094 max mem: 33303 +Epoch: [31] [4120/4276] eta: 0:07:36 lr: 1.1794079480256453e-05 loss: 0.0797 (0.0844) time: 2.9564 data: 0.0082 max mem: 33303 +Epoch: [31] [4130/4276] eta: 0:07:07 lr: 1.1790990452523764e-05 loss: 0.0725 (0.0844) time: 2.9513 data: 0.0083 max mem: 33303 +Epoch: [31] [4140/4276] eta: 0:06:38 lr: 1.1787901334869585e-05 loss: 0.0725 (0.0844) time: 2.9540 data: 0.0087 max mem: 33303 +Epoch: [31] [4150/4276] eta: 0:06:08 lr: 1.1784812127265122e-05 loss: 0.0817 (0.0844) time: 2.9526 data: 0.0087 max mem: 33303 +Epoch: [31] [4160/4276] eta: 0:05:39 lr: 1.1781722829681551e-05 loss: 0.0890 (0.0844) time: 2.9509 data: 0.0085 max mem: 33303 +Epoch: [31] [4170/4276] eta: 0:05:10 lr: 1.1778633442090044e-05 loss: 0.0816 (0.0845) time: 2.9480 data: 0.0085 max mem: 33303 +Epoch: [31] [4180/4276] eta: 0:04:41 lr: 1.1775543964461733e-05 loss: 0.0735 (0.0844) time: 2.9435 data: 0.0087 max mem: 33303 +Epoch: [31] [4190/4276] eta: 0:04:11 lr: 1.177245439676775e-05 loss: 0.0701 (0.0844) time: 2.9473 data: 0.0086 max mem: 33303 +Epoch: [31] [4200/4276] eta: 0:03:42 lr: 1.1769364738979207e-05 loss: 0.0832 (0.0844) time: 2.9514 data: 0.0087 max mem: 33303 +Epoch: [31] [4210/4276] eta: 0:03:13 lr: 1.17662749910672e-05 loss: 0.0861 (0.0844) time: 2.9516 data: 0.0090 max mem: 33303 +Epoch: [31] [4220/4276] eta: 0:02:43 lr: 1.1763185153002792e-05 loss: 0.0874 (0.0845) time: 2.9524 data: 0.0089 max mem: 33303 +Epoch: [31] [4230/4276] eta: 0:02:14 lr: 1.1760095224757046e-05 loss: 0.0888 (0.0845) time: 2.9545 data: 0.0087 max mem: 33303 +Epoch: [31] [4240/4276] eta: 0:01:45 lr: 1.1757005206300998e-05 loss: 0.0888 (0.0845) time: 2.9544 data: 0.0086 max mem: 33303 +Epoch: [31] [4250/4276] eta: 0:01:16 lr: 1.1753915097605679e-05 loss: 0.0968 (0.0846) time: 2.9522 data: 0.0085 max mem: 33303 +Epoch: [31] [4260/4276] eta: 0:00:46 lr: 1.1750824898642079e-05 loss: 0.0973 (0.0846) time: 2.9506 data: 0.0087 max mem: 33303 +Epoch: [31] [4270/4276] eta: 0:00:17 lr: 1.1747734609381188e-05 loss: 0.0892 (0.0846) time: 2.9453 data: 0.0079 max mem: 33303 +Epoch: [31] Total time: 3:28:42 +Test: [ 0/21770] eta: 11:30:34 time: 1.9033 data: 1.8645 max mem: 33303 +Test: [ 100/21770] eta: 0:20:17 time: 0.0383 data: 0.0008 max mem: 33303 +Test: [ 200/21770] eta: 0:16:58 time: 0.0381 data: 0.0008 max mem: 33303 +Test: [ 300/21770] eta: 0:15:50 time: 0.0386 data: 0.0008 max mem: 33303 +Test: [ 400/21770] eta: 0:15:15 time: 0.0383 data: 0.0008 max mem: 33303 +Test: [ 500/21770] eta: 0:14:53 time: 0.0386 data: 0.0008 max mem: 33303 +Test: [ 600/21770] eta: 0:14:36 time: 0.0386 data: 0.0008 max mem: 33303 +Test: [ 700/21770] eta: 0:14:24 time: 0.0385 data: 0.0009 max mem: 33303 +Test: [ 800/21770] eta: 0:14:13 time: 0.0388 data: 0.0009 max mem: 33303 +Test: [ 900/21770] eta: 0:14:05 time: 0.0386 data: 0.0009 max mem: 33303 +Test: [ 1000/21770] eta: 0:13:57 time: 0.0388 data: 0.0009 max mem: 33303 +Test: [ 1100/21770] eta: 0:13:50 time: 0.0386 data: 0.0009 max mem: 33303 +Test: [ 1200/21770] eta: 0:13:43 time: 0.0389 data: 0.0009 max mem: 33303 +Test: [ 1300/21770] eta: 0:13:37 time: 0.0384 data: 0.0009 max mem: 33303 +Test: [ 1400/21770] eta: 0:13:31 time: 0.0389 data: 0.0009 max mem: 33303 +Test: [ 1500/21770] eta: 0:13:25 time: 0.0382 data: 0.0009 max mem: 33303 +Test: [ 1600/21770] eta: 0:13:20 time: 0.0384 data: 0.0008 max mem: 33303 +Test: [ 1700/21770] eta: 0:13:14 time: 0.0385 data: 0.0009 max mem: 33303 +Test: [ 1800/21770] eta: 0:13:09 time: 0.0385 data: 0.0009 max mem: 33303 +Test: [ 1900/21770] eta: 0:13:04 time: 0.0384 data: 0.0009 max mem: 33303 +Test: [ 2000/21770] eta: 0:12:59 time: 0.0385 data: 0.0009 max mem: 33303 +Test: [ 2100/21770] eta: 0:12:54 time: 0.0386 data: 0.0009 max mem: 33303 +Test: [ 2200/21770] eta: 0:12:50 time: 0.0387 data: 0.0009 max mem: 33303 +Test: [ 2300/21770] eta: 0:12:45 time: 0.0384 data: 0.0009 max mem: 33303 +Test: [ 2400/21770] eta: 0:12:41 time: 0.0387 data: 0.0009 max mem: 33303 +Test: [ 2500/21770] eta: 0:12:36 time: 0.0384 data: 0.0009 max mem: 33303 +Test: [ 2600/21770] eta: 0:12:32 time: 0.0387 data: 0.0009 max mem: 33303 +Test: [ 2700/21770] eta: 0:12:27 time: 0.0383 data: 0.0009 max mem: 33303 +Test: [ 2800/21770] eta: 0:12:23 time: 0.0387 data: 0.0009 max mem: 33303 +Test: [ 2900/21770] eta: 0:12:18 time: 0.0387 data: 0.0009 max mem: 33303 +Test: [ 3000/21770] eta: 0:12:14 time: 0.0388 data: 0.0009 max mem: 33303 +Test: [ 3100/21770] eta: 0:12:10 time: 0.0387 data: 0.0009 max mem: 33303 +Test: [ 3200/21770] eta: 0:12:06 time: 0.0389 data: 0.0009 max mem: 33303 +Test: [ 3300/21770] eta: 0:12:02 time: 0.0394 data: 0.0009 max mem: 33303 +Test: [ 3400/21770] eta: 0:11:58 time: 0.0391 data: 0.0009 max mem: 33303 +Test: [ 3500/21770] eta: 0:11:54 time: 0.0394 data: 0.0009 max mem: 33303 +Test: [ 3600/21770] eta: 0:11:50 time: 0.0391 data: 0.0009 max mem: 33303 +Test: [ 3700/21770] eta: 0:11:46 time: 0.0392 data: 0.0009 max mem: 33303 +Test: [ 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time: 0.0389 data: 0.0009 max mem: 33303 +Test: [ 5200/21770] eta: 0:10:47 time: 0.0388 data: 0.0009 max mem: 33303 +Test: [ 5300/21770] eta: 0:10:43 time: 0.0392 data: 0.0009 max mem: 33303 +Test: [ 5400/21770] eta: 0:10:39 time: 0.0392 data: 0.0009 max mem: 33303 +Test: [ 5500/21770] eta: 0:10:35 time: 0.0392 data: 0.0009 max mem: 33303 +Test: [ 5600/21770] eta: 0:10:32 time: 0.0391 data: 0.0009 max mem: 33303 +Test: [ 5700/21770] eta: 0:10:28 time: 0.0391 data: 0.0009 max mem: 33303 +Test: [ 5800/21770] eta: 0:10:24 time: 0.0391 data: 0.0009 max mem: 33303 +Test: [ 5900/21770] eta: 0:10:20 time: 0.0391 data: 0.0009 max mem: 33303 +Test: [ 6000/21770] eta: 0:10:16 time: 0.0392 data: 0.0009 max mem: 33303 +Test: [ 6100/21770] eta: 0:10:12 time: 0.0390 data: 0.0009 max mem: 33303 +Test: [ 6200/21770] eta: 0:10:08 time: 0.0393 data: 0.0009 max mem: 33303 +Test: [ 6300/21770] eta: 0:10:04 time: 0.0390 data: 0.0009 max mem: 33303 +Test: [ 6400/21770] eta: 0:10:00 time: 0.0382 data: 0.0008 max mem: 33303 +Test: [ 6500/21770] eta: 0:09:56 time: 0.0382 data: 0.0009 max mem: 33303 +Test: [ 6600/21770] eta: 0:09:52 time: 0.0383 data: 0.0008 max mem: 33303 +Test: [ 6700/21770] eta: 0:09:48 time: 0.0382 data: 0.0009 max mem: 33303 +Test: [ 6800/21770] eta: 0:09:44 time: 0.0398 data: 0.0009 max mem: 33303 +Test: [ 6900/21770] eta: 0:09:40 time: 0.0402 data: 0.0009 max mem: 33303 +Test: [ 7000/21770] eta: 0:09:37 time: 0.0393 data: 0.0009 max mem: 33303 +Test: [ 7100/21770] eta: 0:09:33 time: 0.0392 data: 0.0009 max mem: 33303 +Test: [ 7200/21770] eta: 0:09:29 time: 0.0392 data: 0.0009 max mem: 33303 +Test: [ 7300/21770] eta: 0:09:25 time: 0.0391 data: 0.0009 max mem: 33303 +Test: [ 7400/21770] eta: 0:09:21 time: 0.0391 data: 0.0009 max mem: 33303 +Test: [ 7500/21770] eta: 0:09:17 time: 0.0394 data: 0.0009 max mem: 33303 +Test: [ 7600/21770] eta: 0:09:13 time: 0.0382 data: 0.0009 max mem: 33303 +Test: [ 7700/21770] eta: 0:09:09 time: 0.0382 data: 0.0009 max mem: 33303 +Test: [ 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time: 0.0389 data: 0.0009 max mem: 33303 +Test: [ 9200/21770] eta: 0:08:10 time: 0.0387 data: 0.0009 max mem: 33303 +Test: [ 9300/21770] eta: 0:08:06 time: 0.0389 data: 0.0009 max mem: 33303 +Test: [ 9400/21770] eta: 0:08:02 time: 0.0388 data: 0.0009 max mem: 33303 +Test: [ 9500/21770] eta: 0:07:58 time: 0.0389 data: 0.0009 max mem: 33303 +Test: [ 9600/21770] eta: 0:07:54 time: 0.0388 data: 0.0009 max mem: 33303 +Test: [ 9700/21770] eta: 0:07:50 time: 0.0391 data: 0.0009 max mem: 33303 +Test: [ 9800/21770] eta: 0:07:46 time: 0.0388 data: 0.0009 max mem: 33303 +Test: [ 9900/21770] eta: 0:07:42 time: 0.0388 data: 0.0009 max mem: 33303 +Test: [10000/21770] eta: 0:07:38 time: 0.0389 data: 0.0009 max mem: 33303 +Test: [10100/21770] eta: 0:07:35 time: 0.0390 data: 0.0009 max mem: 33303 +Test: [10200/21770] eta: 0:07:31 time: 0.0387 data: 0.0009 max mem: 33303 +Test: [10300/21770] eta: 0:07:27 time: 0.0390 data: 0.0009 max mem: 33303 +Test: [10400/21770] eta: 0:07:23 time: 0.0388 data: 0.0009 max mem: 33303 +Test: [10500/21770] eta: 0:07:19 time: 0.0390 data: 0.0009 max mem: 33303 +Test: [10600/21770] eta: 0:07:15 time: 0.0389 data: 0.0009 max mem: 33303 +Test: [10700/21770] eta: 0:07:11 time: 0.0388 data: 0.0009 max mem: 33303 +Test: [10800/21770] eta: 0:07:07 time: 0.0388 data: 0.0009 max mem: 33303 +Test: [10900/21770] eta: 0:07:03 time: 0.0389 data: 0.0009 max mem: 33303 +Test: [11000/21770] eta: 0:06:59 time: 0.0388 data: 0.0009 max mem: 33303 +Test: [11100/21770] eta: 0:06:55 time: 0.0388 data: 0.0009 max mem: 33303 +Test: [11200/21770] eta: 0:06:51 time: 0.0387 data: 0.0009 max mem: 33303 +Test: [11300/21770] eta: 0:06:48 time: 0.0390 data: 0.0009 max mem: 33303 +Test: [11400/21770] eta: 0:06:44 time: 0.0388 data: 0.0009 max mem: 33303 +Test: [11500/21770] eta: 0:06:40 time: 0.0392 data: 0.0009 max mem: 33303 +Test: [11600/21770] eta: 0:06:36 time: 0.0392 data: 0.0009 max mem: 33303 +Test: [11700/21770] eta: 0:06:32 time: 0.0389 data: 0.0009 max mem: 33303 +Test: [11800/21770] eta: 0:06:28 time: 0.0388 data: 0.0009 max mem: 33303 +Test: [11900/21770] eta: 0:06:24 time: 0.0388 data: 0.0009 max mem: 33303 +Test: [12000/21770] eta: 0:06:20 time: 0.0389 data: 0.0009 max mem: 33303 +Test: [12100/21770] eta: 0:06:16 time: 0.0389 data: 0.0009 max mem: 33303 +Test: [12200/21770] eta: 0:06:12 time: 0.0386 data: 0.0009 max mem: 33303 +Test: [12300/21770] eta: 0:06:09 time: 0.0389 data: 0.0009 max mem: 33303 +Test: [12400/21770] eta: 0:06:05 time: 0.0389 data: 0.0009 max mem: 33303 +Test: [12500/21770] eta: 0:06:01 time: 0.0390 data: 0.0009 max mem: 33303 +Test: [12600/21770] eta: 0:05:57 time: 0.0388 data: 0.0009 max mem: 33303 +Test: [12700/21770] eta: 0:05:53 time: 0.0390 data: 0.0009 max mem: 33303 +Test: [12800/21770] eta: 0:05:49 time: 0.0387 data: 0.0009 max mem: 33303 +Test: [12900/21770] eta: 0:05:45 time: 0.0391 data: 0.0009 max mem: 33303 +Test: [13000/21770] eta: 0:05:41 time: 0.0388 data: 0.0009 max mem: 33303 +Test: [13100/21770] eta: 0:05:37 time: 0.0393 data: 0.0009 max mem: 33303 +Test: [13200/21770] eta: 0:05:33 time: 0.0391 data: 0.0008 max mem: 33303 +Test: [13300/21770] eta: 0:05:30 time: 0.0393 data: 0.0009 max mem: 33303 +Test: [13400/21770] eta: 0:05:26 time: 0.0392 data: 0.0009 max mem: 33303 +Test: [13500/21770] eta: 0:05:22 time: 0.0394 data: 0.0009 max mem: 33303 +Test: [13600/21770] eta: 0:05:18 time: 0.0391 data: 0.0008 max mem: 33303 +Test: [13700/21770] eta: 0:05:14 time: 0.0394 data: 0.0009 max mem: 33303 +Test: [13800/21770] eta: 0:05:10 time: 0.0391 data: 0.0008 max mem: 33303 +Test: [13900/21770] eta: 0:05:06 time: 0.0394 data: 0.0009 max mem: 33303 +Test: [14000/21770] eta: 0:05:02 time: 0.0391 data: 0.0009 max mem: 33303 +Test: [14100/21770] eta: 0:04:59 time: 0.0393 data: 0.0009 max mem: 33303 +Test: [14200/21770] eta: 0:04:55 time: 0.0391 data: 0.0009 max mem: 33303 +Test: [14300/21770] eta: 0:04:51 time: 0.0394 data: 0.0009 max mem: 33303 +Test: [14400/21770] eta: 0:04:47 time: 0.0391 data: 0.0009 max mem: 33303 +Test: [14500/21770] eta: 0:04:43 time: 0.0401 data: 0.0009 max mem: 33303 +Test: [14600/21770] eta: 0:04:39 time: 0.0395 data: 0.0009 max mem: 33303 +Test: [14700/21770] eta: 0:04:35 time: 0.0396 data: 0.0009 max mem: 33303 +Test: [14800/21770] eta: 0:04:31 time: 0.0393 data: 0.0009 max mem: 33303 +Test: [14900/21770] eta: 0:04:27 time: 0.0398 data: 0.0009 max mem: 33303 +Test: [15000/21770] eta: 0:04:24 time: 0.0390 data: 0.0009 max mem: 33303 +Test: [15100/21770] eta: 0:04:20 time: 0.0395 data: 0.0010 max mem: 33303 +Test: [15200/21770] eta: 0:04:16 time: 0.0392 data: 0.0009 max mem: 33303 +Test: [15300/21770] eta: 0:04:12 time: 0.0392 data: 0.0009 max mem: 33303 +Test: [15400/21770] eta: 0:04:08 time: 0.0394 data: 0.0009 max mem: 33303 +Test: [15500/21770] eta: 0:04:04 time: 0.0394 data: 0.0009 max mem: 33303 +Test: [15600/21770] eta: 0:04:00 time: 0.0398 data: 0.0008 max mem: 33303 +Test: [15700/21770] eta: 0:03:56 time: 0.0393 data: 0.0009 max mem: 33303 +Test: [15800/21770] eta: 0:03:52 time: 0.0391 data: 0.0009 max mem: 33303 +Test: [15900/21770] eta: 0:03:49 time: 0.0395 data: 0.0009 max mem: 33303 +Test: [16000/21770] eta: 0:03:45 time: 0.0391 data: 0.0009 max mem: 33303 +Test: [16100/21770] eta: 0:03:41 time: 0.0393 data: 0.0009 max mem: 33303 +Test: [16200/21770] eta: 0:03:37 time: 0.0389 data: 0.0009 max mem: 33303 +Test: [16300/21770] eta: 0:03:33 time: 0.0396 data: 0.0008 max mem: 33303 +Test: [16400/21770] eta: 0:03:29 time: 0.0393 data: 0.0008 max mem: 33303 +Test: [16500/21770] eta: 0:03:25 time: 0.0393 data: 0.0009 max mem: 33303 +Test: [16600/21770] eta: 0:03:21 time: 0.0393 data: 0.0009 max mem: 33303 +Test: [16700/21770] eta: 0:03:17 time: 0.0395 data: 0.0008 max mem: 33303 +Test: [16800/21770] eta: 0:03:14 time: 0.0395 data: 0.0008 max mem: 33303 +Test: [16900/21770] eta: 0:03:10 time: 0.0397 data: 0.0008 max mem: 33303 +Test: [17000/21770] eta: 0:03:06 time: 0.0392 data: 0.0008 max mem: 33303 +Test: [17100/21770] eta: 0:03:02 time: 0.0389 data: 0.0008 max mem: 33303 +Test: [17200/21770] eta: 0:02:58 time: 0.0388 data: 0.0008 max mem: 33303 +Test: [17300/21770] eta: 0:02:54 time: 0.0471 data: 0.0099 max mem: 33303 +Test: [17400/21770] eta: 0:02:50 time: 0.0384 data: 0.0009 max mem: 33303 +Test: [17500/21770] eta: 0:02:46 time: 0.0386 data: 0.0008 max mem: 33303 +Test: [17600/21770] eta: 0:02:42 time: 0.0387 data: 0.0008 max mem: 33303 +Test: [17700/21770] eta: 0:02:38 time: 0.0386 data: 0.0009 max mem: 33303 +Test: [17800/21770] eta: 0:02:34 time: 0.0386 data: 0.0009 max mem: 33303 +Test: [17900/21770] eta: 0:02:31 time: 0.0472 data: 0.0091 max mem: 33303 +Test: [18000/21770] eta: 0:02:27 time: 0.0385 data: 0.0009 max mem: 33303 +Test: [18100/21770] eta: 0:02:23 time: 0.0388 data: 0.0009 max mem: 33303 +Test: [18200/21770] eta: 0:02:19 time: 0.0383 data: 0.0009 max mem: 33303 +Test: [18300/21770] eta: 0:02:15 time: 0.0392 data: 0.0009 max mem: 33303 +Test: [18400/21770] eta: 0:02:11 time: 0.0387 data: 0.0009 max mem: 33303 +Test: [18500/21770] eta: 0:02:07 time: 0.0390 data: 0.0009 max mem: 33303 +Test: [18600/21770] eta: 0:02:03 time: 0.0388 data: 0.0009 max mem: 33303 +Test: [18700/21770] eta: 0:01:59 time: 0.0390 data: 0.0009 max mem: 33303 +Test: [18800/21770] eta: 0:01:55 time: 0.0387 data: 0.0009 max mem: 33303 +Test: [18900/21770] eta: 0:01:52 time: 0.0390 data: 0.0009 max mem: 33303 +Test: [19000/21770] eta: 0:01:48 time: 0.0389 data: 0.0009 max mem: 33303 +Test: [19100/21770] eta: 0:01:44 time: 0.0388 data: 0.0009 max mem: 33303 +Test: [19200/21770] eta: 0:01:40 time: 0.0388 data: 0.0008 max mem: 33303 +Test: [19300/21770] eta: 0:01:36 time: 0.0390 data: 0.0009 max mem: 33303 +Test: [19400/21770] eta: 0:01:32 time: 0.0388 data: 0.0009 max mem: 33303 +Test: [19500/21770] eta: 0:01:28 time: 0.0388 data: 0.0008 max mem: 33303 +Test: [19600/21770] eta: 0:01:24 time: 0.0387 data: 0.0009 max mem: 33303 +Test: [19700/21770] eta: 0:01:20 time: 0.0389 data: 0.0009 max mem: 33303 +Test: [19800/21770] eta: 0:01:16 time: 0.0388 data: 0.0008 max mem: 33303 +Test: [19900/21770] eta: 0:01:12 time: 0.0386 data: 0.0009 max mem: 33303 +Test: [20000/21770] eta: 0:01:09 time: 0.0386 data: 0.0009 max mem: 33303 +Test: [20100/21770] eta: 0:01:05 time: 0.0385 data: 0.0009 max mem: 33303 +Test: [20200/21770] eta: 0:01:01 time: 0.0386 data: 0.0009 max mem: 33303 +Test: [20300/21770] eta: 0:00:57 time: 0.0386 data: 0.0009 max mem: 33303 +Test: [20400/21770] eta: 0:00:53 time: 0.0386 data: 0.0009 max mem: 33303 +Test: [20500/21770] eta: 0:00:49 time: 0.0384 data: 0.0008 max mem: 33303 +Test: [20600/21770] eta: 0:00:45 time: 0.0388 data: 0.0009 max mem: 33303 +Test: [20700/21770] eta: 0:00:41 time: 0.0389 data: 0.0008 max mem: 33303 +Test: [20800/21770] eta: 0:00:37 time: 0.0388 data: 0.0008 max mem: 33303 +Test: [20900/21770] eta: 0:00:33 time: 0.0391 data: 0.0009 max mem: 33303 +Test: [21000/21770] eta: 0:00:30 time: 0.0389 data: 0.0009 max mem: 33303 +Test: [21100/21770] eta: 0:00:26 time: 0.0391 data: 0.0008 max mem: 33303 +Test: [21200/21770] eta: 0:00:22 time: 0.0389 data: 0.0009 max mem: 33303 +Test: [21300/21770] eta: 0:00:18 time: 0.0390 data: 0.0008 max mem: 33303 +Test: [21400/21770] eta: 0:00:14 time: 0.0390 data: 0.0009 max mem: 33303 +Test: [21500/21770] eta: 0:00:10 time: 0.0391 data: 0.0009 max mem: 33303 +Test: [21600/21770] eta: 0:00:06 time: 0.0395 data: 0.0009 max mem: 33303 +Test: [21700/21770] eta: 0:00:02 time: 0.0396 data: 0.0009 max mem: 33303 +Test: Total time: 0:14:09 +Final results: +Mean IoU is 0.00 + + precision@0.5 = 0.00 + precision@0.6 = 0.00 + precision@0.7 = 0.00 + precision@0.8 = 0.00 + precision@0.9 = 0.00 + overall IoU = 0.00 + mean IoU = 0.00 + +Mean accuracy for one-to-zero sample is 100.00 + +Average object IoU 0.0 +Overall IoU 0.0 +Epoch: [32] [ 0/4276] eta: 6:24:59 lr: 1.174588039246988e-05 loss: 0.0738 (0.0738) time: 5.4022 data: 2.3652 max mem: 33303 +Epoch: [32] [ 10/4276] eta: 3:44:21 lr: 1.174278995867293e-05 loss: 0.0738 (0.0819) time: 3.1556 data: 0.2229 max mem: 33303 +Epoch: [32] [ 20/4276] eta: 3:36:54 lr: 1.1739699434503175e-05 loss: 0.0769 (0.0839) time: 2.9407 data: 0.0084 max mem: 33303 +Epoch: [32] [ 30/4276] eta: 3:33:55 lr: 1.1736608819931524e-05 loss: 0.0814 (0.0836) time: 2.9499 data: 0.0077 max mem: 33303 +Epoch: [32] [ 40/4276] eta: 3:32:09 lr: 1.1733518114928887e-05 loss: 0.0777 (0.0823) time: 2.9494 data: 0.0072 max mem: 33303 +Epoch: [32] [ 50/4276] eta: 3:30:53 lr: 1.1730427319466154e-05 loss: 0.0766 (0.0833) time: 2.9500 data: 0.0072 max mem: 33303 +Epoch: [32] [ 60/4276] eta: 3:29:41 lr: 1.1727336433514182e-05 loss: 0.0752 (0.0814) time: 2.9415 data: 0.0072 max mem: 33303 +Epoch: [32] [ 70/4276] eta: 3:28:42 lr: 1.1724245457043825e-05 loss: 0.0702 (0.0799) time: 2.9338 data: 0.0072 max mem: 33303 +Epoch: [32] [ 80/4276] eta: 3:27:49 lr: 1.1721154390025917e-05 loss: 0.0762 (0.0807) time: 2.9340 data: 0.0071 max mem: 33303 +Epoch: [32] [ 90/4276] eta: 3:27:04 lr: 1.1718063232431276e-05 loss: 0.0801 (0.0804) time: 2.9353 data: 0.0071 max mem: 33303 +Epoch: [32] [ 100/4276] eta: 3:26:24 lr: 1.1714971984230687e-05 loss: 0.0816 (0.0814) time: 2.9410 data: 0.0072 max mem: 33303 +Epoch: [32] [ 110/4276] eta: 3:25:49 lr: 1.1711880645394932e-05 loss: 0.0833 (0.0821) time: 2.9470 data: 0.0072 max mem: 33303 +Epoch: [32] [ 120/4276] eta: 3:25:16 lr: 1.1708789215894772e-05 loss: 0.0833 (0.0821) time: 2.9523 data: 0.0071 max mem: 33303 +Epoch: [32] [ 130/4276] eta: 3:24:40 lr: 1.1705697695700957e-05 loss: 0.0877 (0.0827) time: 2.9494 data: 0.0073 max mem: 33303 +Epoch: [32] [ 140/4276] eta: 3:24:06 lr: 1.1702606084784195e-05 loss: 0.0754 (0.0818) time: 2.9452 data: 0.0073 max mem: 33303 +Epoch: [32] [ 150/4276] eta: 3:23:33 lr: 1.16995143831152e-05 loss: 0.0720 (0.0815) time: 2.9479 data: 0.0071 max mem: 33303 +Epoch: [32] [ 160/4276] eta: 3:22:57 lr: 1.1696422590664659e-05 loss: 0.0754 (0.0815) time: 2.9420 data: 0.0072 max mem: 33303 +Epoch: [32] [ 170/4276] eta: 3:22:12 lr: 1.1693330707403246e-05 loss: 0.0806 (0.0815) time: 2.9146 data: 0.0080 max mem: 33303 +Epoch: [32] [ 180/4276] eta: 3:21:29 lr: 1.1690238733301604e-05 loss: 0.0810 (0.0824) time: 2.8953 data: 0.0088 max mem: 33303 +Epoch: [32] [ 190/4276] eta: 3:21:00 lr: 1.1687146668330372e-05 loss: 0.0807 (0.0821) time: 2.9256 data: 0.0084 max mem: 33303 +Epoch: [32] [ 200/4276] eta: 3:20:30 lr: 1.1684054512460162e-05 loss: 0.0711 (0.0817) time: 2.9506 data: 0.0077 max mem: 33303 +Epoch: [32] [ 210/4276] eta: 3:19:58 lr: 1.168096226566158e-05 loss: 0.0755 (0.0822) time: 2.9435 data: 0.0074 max mem: 33303 +Epoch: [32] [ 220/4276] eta: 3:19:25 lr: 1.1677869927905192e-05 loss: 0.0755 (0.0823) time: 2.9364 data: 0.0074 max mem: 33303 +Epoch: [32] [ 230/4276] eta: 3:18:55 lr: 1.1674777499161565e-05 loss: 0.0780 (0.0824) time: 2.9381 data: 0.0083 max mem: 33303 +Epoch: [32] [ 240/4276] eta: 3:18:28 lr: 1.1671684979401242e-05 loss: 0.0832 (0.0827) time: 2.9555 data: 0.0086 max mem: 33303 +Epoch: [32] [ 250/4276] eta: 3:17:59 lr: 1.166859236859475e-05 loss: 0.0864 (0.0829) time: 2.9592 data: 0.0075 max mem: 33303 +Epoch: [32] [ 260/4276] eta: 3:17:29 lr: 1.166549966671259e-05 loss: 0.0891 (0.0834) time: 2.9522 data: 0.0071 max mem: 33303 +Epoch: [32] [ 270/4276] eta: 3:17:00 lr: 1.166240687372525e-05 loss: 0.0852 (0.0834) time: 2.9513 data: 0.0072 max mem: 33303 +Epoch: [32] [ 280/4276] eta: 3:16:31 lr: 1.1659313989603201e-05 loss: 0.0648 (0.0832) time: 2.9521 data: 0.0070 max mem: 33303 +Epoch: [32] [ 290/4276] eta: 3:16:02 lr: 1.1656221014316901e-05 loss: 0.0710 (0.0830) time: 2.9551 data: 0.0070 max mem: 33303 +Epoch: [32] [ 300/4276] eta: 3:15:33 lr: 1.1653127947836772e-05 loss: 0.0716 (0.0829) time: 2.9573 data: 0.0073 max mem: 33303 +Epoch: [32] [ 310/4276] eta: 3:15:04 lr: 1.1650034790133233e-05 loss: 0.0662 (0.0824) time: 2.9559 data: 0.0073 max mem: 33303 +Epoch: [32] [ 320/4276] eta: 3:14:35 lr: 1.1646941541176681e-05 loss: 0.0720 (0.0825) time: 2.9519 data: 0.0071 max mem: 33303 +Epoch: [32] [ 330/4276] eta: 3:14:03 lr: 1.1643848200937501e-05 loss: 0.0794 (0.0826) time: 2.9426 data: 0.0072 max mem: 33303 +Epoch: [32] [ 340/4276] eta: 3:13:33 lr: 1.164075476938604e-05 loss: 0.0789 (0.0825) time: 2.9399 data: 0.0073 max mem: 33303 +Epoch: [32] [ 350/4276] eta: 3:13:03 lr: 1.1637661246492643e-05 loss: 0.0805 (0.0828) time: 2.9450 data: 0.0073 max mem: 33303 +Epoch: [32] [ 360/4276] eta: 3:12:33 lr: 1.1634567632227643e-05 loss: 0.0935 (0.0833) time: 2.9443 data: 0.0071 max mem: 33303 +Epoch: [32] [ 370/4276] eta: 3:12:02 lr: 1.163147392656133e-05 loss: 0.0859 (0.0835) time: 2.9440 data: 0.0069 max mem: 33303 +Epoch: [32] [ 380/4276] eta: 3:11:32 lr: 1.1628380129463998e-05 loss: 0.0846 (0.0835) time: 2.9439 data: 0.0069 max mem: 33303 +Epoch: [32] [ 390/4276] eta: 3:11:03 lr: 1.1625286240905913e-05 loss: 0.0753 (0.0834) time: 2.9457 data: 0.0069 max mem: 33303 +Epoch: [32] [ 400/4276] eta: 3:10:32 lr: 1.162219226085733e-05 loss: 0.0875 (0.0837) time: 2.9454 data: 0.0069 max mem: 33303 +Epoch: [32] [ 410/4276] eta: 3:10:02 lr: 1.161909818928847e-05 loss: 0.0903 (0.0838) time: 2.9439 data: 0.0069 max mem: 33303 +Epoch: [32] [ 420/4276] eta: 3:09:33 lr: 1.1616004026169548e-05 loss: 0.0834 (0.0839) time: 2.9453 data: 0.0070 max mem: 33303 +Epoch: [32] [ 430/4276] eta: 3:09:03 lr: 1.161290977147076e-05 loss: 0.0887 (0.0840) time: 2.9458 data: 0.0070 max mem: 33303 +Epoch: [32] [ 440/4276] eta: 3:08:33 lr: 1.1609815425162287e-05 loss: 0.0802 (0.0839) time: 2.9447 data: 0.0070 max mem: 33303 +Epoch: [32] [ 450/4276] eta: 3:08:03 lr: 1.160672098721427e-05 loss: 0.0795 (0.0840) time: 2.9444 data: 0.0069 max mem: 33303 +Epoch: [32] [ 460/4276] eta: 3:07:33 lr: 1.160362645759686e-05 loss: 0.0806 (0.0838) time: 2.9435 data: 0.0071 max mem: 33303 +Epoch: [32] [ 470/4276] eta: 3:07:03 lr: 1.1600531836280172e-05 loss: 0.0798 (0.0837) time: 2.9412 data: 0.0072 max mem: 33303 +Epoch: [32] [ 480/4276] eta: 3:06:32 lr: 1.1597437123234313e-05 loss: 0.0817 (0.0836) time: 2.9371 data: 0.0073 max mem: 33303 +Epoch: [32] [ 490/4276] eta: 3:06:02 lr: 1.1594342318429353e-05 loss: 0.0795 (0.0834) time: 2.9365 data: 0.0074 max mem: 33303 +Epoch: [32] [ 500/4276] eta: 3:05:31 lr: 1.1591247421835363e-05 loss: 0.0691 (0.0833) time: 2.9360 data: 0.0071 max mem: 33303 +Epoch: [32] [ 510/4276] eta: 3:05:01 lr: 1.1588152433422386e-05 loss: 0.0726 (0.0833) time: 2.9327 data: 0.0070 max mem: 33303 +Epoch: [32] [ 520/4276] eta: 3:04:31 lr: 1.1585057353160458e-05 loss: 0.0792 (0.0833) time: 2.9380 data: 0.0069 max mem: 33303 +Epoch: [32] [ 530/4276] eta: 3:03:59 lr: 1.158196218101957e-05 loss: 0.0792 (0.0834) time: 2.9305 data: 0.0073 max mem: 33303 +Epoch: [32] [ 540/4276] eta: 3:03:26 lr: 1.157886691696972e-05 loss: 0.0804 (0.0834) time: 2.9042 data: 0.0077 max mem: 33303 +Epoch: [32] [ 550/4276] eta: 3:02:53 lr: 1.1575771560980877e-05 loss: 0.0809 (0.0834) time: 2.8902 data: 0.0079 max mem: 33303 +Epoch: [32] [ 560/4276] eta: 3:02:20 lr: 1.1572676113022999e-05 loss: 0.0849 (0.0836) time: 2.8907 data: 0.0082 max mem: 33303 +Epoch: [32] [ 570/4276] eta: 3:01:47 lr: 1.1569580573066006e-05 loss: 0.0795 (0.0836) time: 2.8904 data: 0.0083 max mem: 33303 +Epoch: [32] [ 580/4276] eta: 3:01:14 lr: 1.156648494107982e-05 loss: 0.0774 (0.0837) time: 2.8894 data: 0.0081 max mem: 33303 +Epoch: [32] [ 590/4276] eta: 3:00:41 lr: 1.1563389217034332e-05 loss: 0.0805 (0.0836) time: 2.8886 data: 0.0081 max mem: 33303 +Epoch: [32] [ 600/4276] eta: 3:00:09 lr: 1.156029340089943e-05 loss: 0.0805 (0.0836) time: 2.8939 data: 0.0083 max mem: 33303 +Epoch: [32] [ 610/4276] eta: 2:59:38 lr: 1.1557197492644954e-05 loss: 0.0759 (0.0836) time: 2.9062 data: 0.0084 max mem: 33303 +Epoch: [32] [ 620/4276] eta: 2:59:06 lr: 1.1554101492240752e-05 loss: 0.0730 (0.0836) time: 2.9033 data: 0.0082 max mem: 33303 +Epoch: [32] [ 630/4276] eta: 2:58:34 lr: 1.1551005399656642e-05 loss: 0.0797 (0.0837) time: 2.8938 data: 0.0082 max mem: 33303 +Epoch: [32] [ 640/4276] eta: 2:58:02 lr: 1.1547909214862433e-05 loss: 0.0803 (0.0837) time: 2.8924 data: 0.0084 max mem: 33303 +Epoch: [32] [ 650/4276] eta: 2:57:30 lr: 1.1544812937827892e-05 loss: 0.0761 (0.0836) time: 2.8933 data: 0.0083 max mem: 33303 +Epoch: [32] [ 660/4276] eta: 2:56:58 lr: 1.154171656852279e-05 loss: 0.0820 (0.0838) time: 2.8885 data: 0.0080 max mem: 33303 +Epoch: [32] [ 670/4276] eta: 2:56:25 lr: 1.1538620106916879e-05 loss: 0.0833 (0.0840) time: 2.8754 data: 0.0081 max mem: 33303 +Epoch: [32] [ 680/4276] eta: 2:55:52 lr: 1.153552355297987e-05 loss: 0.0854 (0.0840) time: 2.8718 data: 0.0084 max mem: 33303 +Epoch: [32] [ 690/4276] eta: 2:55:18 lr: 1.1532426906681476e-05 loss: 0.0831 (0.0840) time: 2.8643 data: 0.0086 max mem: 33303 +Epoch: [32] [ 700/4276] eta: 2:54:45 lr: 1.1529330167991382e-05 loss: 0.0766 (0.0839) time: 2.8563 data: 0.0084 max mem: 33303 +Epoch: [32] [ 710/4276] eta: 2:54:15 lr: 1.1526233336879266e-05 loss: 0.0775 (0.0839) time: 2.8823 data: 0.0084 max mem: 33303 +Epoch: [32] [ 720/4276] eta: 2:53:45 lr: 1.1523136413314763e-05 loss: 0.0778 (0.0838) time: 2.9169 data: 0.0085 max mem: 33303 +Epoch: [32] [ 730/4276] eta: 2:53:16 lr: 1.152003939726751e-05 loss: 0.0748 (0.0838) time: 2.9337 data: 0.0081 max mem: 33303 +Epoch: [32] [ 740/4276] eta: 2:52:47 lr: 1.1516942288707117e-05 loss: 0.0731 (0.0836) time: 2.9386 data: 0.0078 max mem: 33303 +Epoch: [32] [ 750/4276] eta: 2:52:18 lr: 1.1513845087603186e-05 loss: 0.0721 (0.0837) time: 2.9334 data: 0.0080 max mem: 33303 +Epoch: [32] [ 760/4276] eta: 2:51:49 lr: 1.1510747793925272e-05 loss: 0.0721 (0.0837) time: 2.9343 data: 0.0078 max mem: 33303 +Epoch: [32] [ 770/4276] eta: 2:51:20 lr: 1.150765040764294e-05 loss: 0.0801 (0.0838) time: 2.9374 data: 0.0075 max mem: 33303 +Epoch: [32] [ 780/4276] eta: 2:50:50 lr: 1.1504552928725723e-05 loss: 0.0797 (0.0836) time: 2.9343 data: 0.0075 max mem: 33303 +Epoch: [32] [ 790/4276] eta: 2:50:21 lr: 1.1501455357143143e-05 loss: 0.0797 (0.0837) time: 2.9382 data: 0.0073 max mem: 33303 +Epoch: [32] [ 800/4276] eta: 2:49:50 lr: 1.1498357692864683e-05 loss: 0.0792 (0.0836) time: 2.9126 data: 0.0074 max mem: 33303 +Epoch: [32] [ 810/4276] eta: 2:49:18 lr: 1.1495259935859828e-05 loss: 0.0795 (0.0837) time: 2.8821 data: 0.0077 max mem: 33303 +Epoch: [32] [ 820/4276] eta: 2:48:47 lr: 1.1492162086098037e-05 loss: 0.0780 (0.0837) time: 2.8836 data: 0.0076 max mem: 33303 +Epoch: [32] [ 830/4276] eta: 2:48:16 lr: 1.1489064143548754e-05 loss: 0.0756 (0.0837) time: 2.8870 data: 0.0074 max mem: 33303 +Epoch: [32] [ 840/4276] eta: 2:47:46 lr: 1.1485966108181385e-05 loss: 0.0756 (0.0839) time: 2.8997 data: 0.0076 max mem: 33303 +Epoch: [32] [ 850/4276] eta: 2:47:15 lr: 1.1482867979965339e-05 loss: 0.0761 (0.0837) time: 2.8995 data: 0.0076 max mem: 33303 +Epoch: [32] [ 860/4276] eta: 2:46:44 lr: 1.1479769758869994e-05 loss: 0.0774 (0.0839) time: 2.8878 data: 0.0077 max mem: 33303 +Epoch: [32] [ 870/4276] eta: 2:46:13 lr: 1.1476671444864723e-05 loss: 0.0889 (0.0839) time: 2.8837 data: 0.0078 max mem: 33303 +Epoch: [32] [ 880/4276] eta: 2:45:42 lr: 1.1473573037918852e-05 loss: 0.0866 (0.0840) time: 2.8848 data: 0.0078 max mem: 33303 +Epoch: [32] [ 890/4276] eta: 2:45:12 lr: 1.1470474538001711e-05 loss: 0.0866 (0.0841) time: 2.8925 data: 0.0078 max mem: 33303 +Epoch: [32] [ 900/4276] eta: 2:44:42 lr: 1.1467375945082608e-05 loss: 0.0862 (0.0842) time: 2.9109 data: 0.0076 max mem: 33303 +Epoch: [32] [ 910/4276] eta: 2:44:14 lr: 1.146427725913083e-05 loss: 0.0899 (0.0843) time: 2.9354 data: 0.0078 max mem: 33303 +Epoch: [32] [ 920/4276] eta: 2:43:45 lr: 1.146117848011563e-05 loss: 0.0940 (0.0844) time: 2.9431 data: 0.0083 max mem: 33303 +Epoch: [32] [ 930/4276] eta: 2:43:16 lr: 1.145807960800626e-05 loss: 0.0905 (0.0844) time: 2.9426 data: 0.0083 max mem: 33303 +Epoch: [32] [ 940/4276] eta: 2:42:47 lr: 1.1454980642771948e-05 loss: 0.0799 (0.0845) time: 2.9415 data: 0.0081 max mem: 33303 +Epoch: [32] [ 950/4276] eta: 2:42:19 lr: 1.1451881584381906e-05 loss: 0.0874 (0.0846) time: 2.9392 data: 0.0082 max mem: 33303 +Epoch: [32] [ 960/4276] eta: 2:41:50 lr: 1.144878243280531e-05 loss: 0.0874 (0.0845) time: 2.9394 data: 0.0085 max mem: 33303 +Epoch: [32] [ 970/4276] eta: 2:41:21 lr: 1.1445683188011334e-05 loss: 0.0775 (0.0845) time: 2.9400 data: 0.0085 max mem: 33303 +Epoch: [32] [ 980/4276] eta: 2:40:52 lr: 1.1442583849969134e-05 loss: 0.0802 (0.0845) time: 2.9372 data: 0.0082 max mem: 33303 +Epoch: [32] [ 990/4276] eta: 2:40:23 lr: 1.1439484418647824e-05 loss: 0.0826 (0.0844) time: 2.9367 data: 0.0082 max mem: 33303 +Epoch: [32] [1000/4276] eta: 2:39:54 lr: 1.1436384894016522e-05 loss: 0.0732 (0.0843) time: 2.9480 data: 0.0087 max mem: 33303 +Epoch: [32] [1010/4276] eta: 2:39:25 lr: 1.1433285276044317e-05 loss: 0.0733 (0.0843) time: 2.9334 data: 0.0092 max mem: 33303 +Epoch: [32] [1020/4276] eta: 2:38:54 lr: 1.1430185564700286e-05 loss: 0.0782 (0.0843) time: 2.9054 data: 0.0090 max mem: 33303 +Epoch: [32] [1030/4276] eta: 2:38:24 lr: 1.1427085759953468e-05 loss: 0.0813 (0.0844) time: 2.9023 data: 0.0088 max mem: 33303 +Epoch: [32] [1040/4276] eta: 2:37:54 lr: 1.1423985861772901e-05 loss: 0.0797 (0.0843) time: 2.9032 data: 0.0091 max mem: 33303 +Epoch: [32] [1050/4276] eta: 2:37:24 lr: 1.1420885870127595e-05 loss: 0.0797 (0.0844) time: 2.8996 data: 0.0089 max mem: 33303 +Epoch: [32] [1060/4276] eta: 2:36:54 lr: 1.141778578498655e-05 loss: 0.0878 (0.0846) time: 2.8977 data: 0.0087 max mem: 33303 +Epoch: [32] [1070/4276] eta: 2:36:23 lr: 1.1414685606318726e-05 loss: 0.0926 (0.0847) time: 2.8945 data: 0.0082 max mem: 33303 +Epoch: [32] [1080/4276] eta: 2:35:54 lr: 1.1411585334093083e-05 loss: 0.0913 (0.0848) time: 2.8996 data: 0.0081 max mem: 33303 +Epoch: [32] [1090/4276] eta: 2:35:24 lr: 1.140848496827855e-05 loss: 0.0876 (0.0849) time: 2.9180 data: 0.0087 max mem: 33303 +Epoch: [32] [1100/4276] eta: 2:34:55 lr: 1.1405384508844049e-05 loss: 0.0949 (0.0850) time: 2.9235 data: 0.0089 max mem: 33303 +Epoch: [32] [1110/4276] eta: 2:34:26 lr: 1.1402283955758463e-05 loss: 0.0949 (0.0851) time: 2.9340 data: 0.0085 max mem: 33303 +Epoch: [32] [1120/4276] eta: 2:33:58 lr: 1.1399183308990671e-05 loss: 0.0870 (0.0851) time: 2.9500 data: 0.0080 max mem: 33303 +Epoch: [32] [1130/4276] eta: 2:33:29 lr: 1.1396082568509529e-05 loss: 0.0814 (0.0851) time: 2.9501 data: 0.0077 max mem: 33303 +Epoch: [32] [1140/4276] eta: 2:33:00 lr: 1.1392981734283872e-05 loss: 0.0814 (0.0851) time: 2.9500 data: 0.0077 max mem: 33303 +Epoch: [32] [1150/4276] eta: 2:32:32 lr: 1.1389880806282508e-05 loss: 0.0785 (0.0851) time: 2.9512 data: 0.0077 max mem: 33303 +Epoch: [32] [1160/4276] eta: 2:32:03 lr: 1.1386779784474236e-05 loss: 0.0813 (0.0851) time: 2.9519 data: 0.0078 max mem: 33303 +Epoch: [32] [1170/4276] eta: 2:31:33 lr: 1.138367866882783e-05 loss: 0.0821 (0.0852) time: 2.9334 data: 0.0080 max mem: 33303 +Epoch: [32] [1180/4276] eta: 2:31:04 lr: 1.1380577459312055e-05 loss: 0.0796 (0.0852) time: 2.9102 data: 0.0084 max mem: 33303 +Epoch: [32] [1190/4276] eta: 2:30:35 lr: 1.137747615589563e-05 loss: 0.0795 (0.0851) time: 2.9305 data: 0.0085 max mem: 33303 +Epoch: [32] [1200/4276] eta: 2:30:06 lr: 1.1374374758547277e-05 loss: 0.0795 (0.0851) time: 2.9541 data: 0.0084 max mem: 33303 +Epoch: [32] [1210/4276] eta: 2:29:38 lr: 1.1371273267235693e-05 loss: 0.0708 (0.0850) time: 2.9529 data: 0.0082 max mem: 33303 +Epoch: [32] [1220/4276] eta: 2:29:09 lr: 1.1368171681929561e-05 loss: 0.0819 (0.0851) time: 2.9530 data: 0.0082 max mem: 33303 +Epoch: [32] [1230/4276] eta: 2:28:40 lr: 1.1365070002597522e-05 loss: 0.0928 (0.0851) time: 2.9512 data: 0.0085 max mem: 33303 +Epoch: [32] [1240/4276] eta: 2:28:11 lr: 1.1361968229208218e-05 loss: 0.0929 (0.0852) time: 2.9448 data: 0.0084 max mem: 33303 +Epoch: [32] [1250/4276] eta: 2:27:43 lr: 1.1358866361730264e-05 loss: 0.0880 (0.0852) time: 2.9464 data: 0.0091 max mem: 33303 +Epoch: [32] [1260/4276] eta: 2:27:14 lr: 1.1355764400132266e-05 loss: 0.0712 (0.0851) time: 2.9506 data: 0.0089 max mem: 33303 +Epoch: [32] [1270/4276] eta: 2:26:45 lr: 1.1352662344382781e-05 loss: 0.0699 (0.0850) time: 2.9494 data: 0.0079 max mem: 33303 +Epoch: [32] [1280/4276] eta: 2:26:16 lr: 1.1349560194450378e-05 loss: 0.0806 (0.0850) time: 2.9525 data: 0.0081 max mem: 33303 +Epoch: [32] [1290/4276] eta: 2:25:48 lr: 1.1346457950303593e-05 loss: 0.0855 (0.0851) time: 2.9541 data: 0.0080 max mem: 33303 +Epoch: [32] [1300/4276] eta: 2:25:19 lr: 1.1343355611910932e-05 loss: 0.0835 (0.0851) time: 2.9516 data: 0.0076 max mem: 33303 +Epoch: [32] [1310/4276] eta: 2:24:50 lr: 1.1340253179240896e-05 loss: 0.0751 (0.0850) time: 2.9527 data: 0.0074 max mem: 33303 +Epoch: [32] [1320/4276] eta: 2:24:21 lr: 1.133715065226196e-05 loss: 0.0751 (0.0851) time: 2.9475 data: 0.0074 max mem: 33303 +Epoch: [32] [1330/4276] eta: 2:23:52 lr: 1.1334048030942586e-05 loss: 0.0837 (0.0850) time: 2.9411 data: 0.0078 max mem: 33303 +Epoch: [32] [1340/4276] eta: 2:23:23 lr: 1.1330945315251196e-05 loss: 0.0713 (0.0850) time: 2.9412 data: 0.0080 max mem: 33303 +Epoch: [32] [1350/4276] eta: 2:22:54 lr: 1.1327842505156211e-05 loss: 0.0721 (0.0849) time: 2.9484 data: 0.0076 max mem: 33303 +Epoch: [32] [1360/4276] eta: 2:22:25 lr: 1.1324739600626027e-05 loss: 0.0821 (0.0849) time: 2.9540 data: 0.0074 max mem: 33303 +Epoch: [32] [1370/4276] eta: 2:21:56 lr: 1.1321636601629022e-05 loss: 0.0865 (0.0849) time: 2.9519 data: 0.0077 max mem: 33303 +Epoch: [32] [1380/4276] eta: 2:21:28 lr: 1.131853350813354e-05 loss: 0.0817 (0.0849) time: 2.9532 data: 0.0081 max mem: 33303 +Epoch: [32] [1390/4276] eta: 2:20:58 lr: 1.1315430320107924e-05 loss: 0.0834 (0.0849) time: 2.9422 data: 0.0084 max mem: 33303 +Epoch: [32] [1400/4276] eta: 2:20:29 lr: 1.1312327037520482e-05 loss: 0.0829 (0.0849) time: 2.9333 data: 0.0082 max mem: 33303 +Epoch: [32] [1410/4276] eta: 2:20:00 lr: 1.1309223660339518e-05 loss: 0.0780 (0.0848) time: 2.9438 data: 0.0075 max mem: 33303 +Epoch: [32] [1420/4276] eta: 2:19:31 lr: 1.130612018853329e-05 loss: 0.0723 (0.0848) time: 2.9520 data: 0.0072 max mem: 33303 +Epoch: [32] [1430/4276] eta: 2:19:02 lr: 1.1303016622070057e-05 loss: 0.0765 (0.0849) time: 2.9458 data: 0.0070 max mem: 33303 +Epoch: [32] [1440/4276] eta: 2:18:33 lr: 1.1299912960918055e-05 loss: 0.0845 (0.0849) time: 2.9342 data: 0.0074 max mem: 33303 +Epoch: [32] [1450/4276] eta: 2:18:03 lr: 1.1296809205045499e-05 loss: 0.0737 (0.0848) time: 2.9222 data: 0.0075 max mem: 33303 +Epoch: [32] [1460/4276] eta: 2:17:33 lr: 1.1293705354420568e-05 loss: 0.0737 (0.0848) time: 2.9064 data: 0.0078 max mem: 33303 +Epoch: [32] [1470/4276] eta: 2:17:03 lr: 1.1290601409011444e-05 loss: 0.0864 (0.0849) time: 2.8962 data: 0.0079 max mem: 33303 +Epoch: [32] [1480/4276] eta: 2:16:33 lr: 1.1287497368786272e-05 loss: 0.0864 (0.0849) time: 2.8984 data: 0.0075 max mem: 33303 +Epoch: [32] [1490/4276] eta: 2:16:03 lr: 1.1284393233713193e-05 loss: 0.0845 (0.0848) time: 2.9017 data: 0.0075 max mem: 33303 +Epoch: [32] [1500/4276] eta: 2:15:34 lr: 1.1281289003760303e-05 loss: 0.0796 (0.0848) time: 2.9013 data: 0.0078 max mem: 33303 +Epoch: [32] [1510/4276] eta: 2:15:04 lr: 1.1278184678895699e-05 loss: 0.0752 (0.0847) time: 2.9072 data: 0.0076 max mem: 33303 +Epoch: [32] [1520/4276] eta: 2:14:35 lr: 1.1275080259087448e-05 loss: 0.0692 (0.0847) time: 2.9263 data: 0.0073 max mem: 33303 +Epoch: [32] [1530/4276] eta: 2:14:06 lr: 1.1271975744303605e-05 loss: 0.0669 (0.0846) time: 2.9328 data: 0.0079 max mem: 33303 +Epoch: [32] [1540/4276] eta: 2:13:36 lr: 1.1268871134512188e-05 loss: 0.0769 (0.0846) time: 2.9303 data: 0.0083 max mem: 33303 +Epoch: [32] [1550/4276] eta: 2:13:07 lr: 1.126576642968121e-05 loss: 0.0782 (0.0846) time: 2.9415 data: 0.0078 max mem: 33303 +Epoch: [32] [1560/4276] eta: 2:12:38 lr: 1.1262661629778662e-05 loss: 0.0725 (0.0845) time: 2.9497 data: 0.0073 max mem: 33303 +Epoch: [32] [1570/4276] eta: 2:12:09 lr: 1.12595567347725e-05 loss: 0.0725 (0.0845) time: 2.9496 data: 0.0074 max mem: 33303 +Epoch: [32] [1580/4276] eta: 2:11:40 lr: 1.1256451744630676e-05 loss: 0.0684 (0.0844) time: 2.9484 data: 0.0072 max mem: 33303 +Epoch: [32] [1590/4276] eta: 2:11:11 lr: 1.1253346659321114e-05 loss: 0.0699 (0.0844) time: 2.9488 data: 0.0070 max mem: 33303 +Epoch: [32] [1600/4276] eta: 2:10:42 lr: 1.1250241478811725e-05 loss: 0.0879 (0.0844) time: 2.9482 data: 0.0070 max mem: 33303 +Epoch: [32] [1610/4276] eta: 2:10:13 lr: 1.124713620307038e-05 loss: 0.0873 (0.0844) time: 2.9310 data: 0.0074 max mem: 33303 +Epoch: [32] [1620/4276] eta: 2:09:44 lr: 1.1244030832064947e-05 loss: 0.0787 (0.0844) time: 2.9307 data: 0.0077 max mem: 33303 +Epoch: [32] [1630/4276] eta: 2:09:15 lr: 1.1240925365763271e-05 loss: 0.0917 (0.0845) time: 2.9510 data: 0.0075 max mem: 33303 +Epoch: [32] [1640/4276] eta: 2:08:46 lr: 1.123781980413318e-05 loss: 0.0876 (0.0844) time: 2.9532 data: 0.0072 max mem: 33303 +Epoch: [32] [1650/4276] eta: 2:08:17 lr: 1.1234714147142462e-05 loss: 0.0676 (0.0844) time: 2.9522 data: 0.0070 max mem: 33303 +Epoch: [32] [1660/4276] eta: 2:07:48 lr: 1.1231608394758902e-05 loss: 0.0802 (0.0844) time: 2.9513 data: 0.0070 max mem: 33303 +Epoch: [32] [1670/4276] eta: 2:07:19 lr: 1.1228502546950258e-05 loss: 0.0831 (0.0845) time: 2.9483 data: 0.0070 max mem: 33303 +Epoch: [32] [1680/4276] eta: 2:06:49 lr: 1.1225396603684276e-05 loss: 0.0738 (0.0844) time: 2.9338 data: 0.0073 max mem: 33303 +Epoch: [32] [1690/4276] eta: 2:06:19 lr: 1.1222290564928663e-05 loss: 0.0734 (0.0844) time: 2.9086 data: 0.0078 max mem: 33303 +Epoch: [32] [1700/4276] eta: 2:05:50 lr: 1.1219184430651124e-05 loss: 0.0801 (0.0844) time: 2.9041 data: 0.0081 max mem: 33303 +Epoch: [32] [1710/4276] eta: 2:05:21 lr: 1.1216078200819329e-05 loss: 0.0785 (0.0843) time: 2.9340 data: 0.0086 max mem: 33303 +Epoch: [32] [1720/4276] eta: 2:04:52 lr: 1.1212971875400941e-05 loss: 0.0730 (0.0843) time: 2.9466 data: 0.0087 max mem: 33303 +Epoch: [32] [1730/4276] eta: 2:04:23 lr: 1.1209865454363586e-05 loss: 0.0730 (0.0843) time: 2.9430 data: 0.0081 max mem: 33303 +Epoch: [32] [1740/4276] eta: 2:03:54 lr: 1.1206758937674879e-05 loss: 0.0698 (0.0842) time: 2.9477 data: 0.0075 max mem: 33303 +Epoch: [32] [1750/4276] eta: 2:03:24 lr: 1.1203652325302413e-05 loss: 0.0698 (0.0842) time: 2.9464 data: 0.0073 max mem: 33303 +Epoch: [32] [1760/4276] eta: 2:02:55 lr: 1.1200545617213766e-05 loss: 0.0695 (0.0841) time: 2.9477 data: 0.0073 max mem: 33303 +Epoch: [32] [1770/4276] eta: 2:02:26 lr: 1.1197438813376477e-05 loss: 0.0744 (0.0841) time: 2.9366 data: 0.0082 max mem: 33303 +Epoch: [32] [1780/4276] eta: 2:01:57 lr: 1.1194331913758082e-05 loss: 0.0775 (0.0841) time: 2.9392 data: 0.0085 max mem: 33303 +Epoch: [32] [1790/4276] eta: 2:01:28 lr: 1.1191224918326085e-05 loss: 0.0775 (0.0841) time: 2.9516 data: 0.0078 max mem: 33303 +Epoch: [32] [1800/4276] eta: 2:00:59 lr: 1.1188117827047983e-05 loss: 0.0752 (0.0840) time: 2.9493 data: 0.0077 max mem: 33303 +Epoch: [32] [1810/4276] eta: 2:00:30 lr: 1.1185010639891231e-05 loss: 0.0842 (0.0841) time: 2.9480 data: 0.0079 max mem: 33303 +Epoch: [32] [1820/4276] eta: 2:00:01 lr: 1.1181903356823277e-05 loss: 0.0851 (0.0840) time: 2.9489 data: 0.0080 max mem: 33303 +Epoch: [32] [1830/4276] eta: 1:59:31 lr: 1.1178795977811548e-05 loss: 0.0772 (0.0840) time: 2.9483 data: 0.0079 max mem: 33303 +Epoch: [32] [1840/4276] eta: 1:59:02 lr: 1.117568850282345e-05 loss: 0.0722 (0.0840) time: 2.9495 data: 0.0079 max mem: 33303 +Epoch: [32] [1850/4276] eta: 1:58:34 lr: 1.1172580931826353e-05 loss: 0.0693 (0.0840) time: 2.9746 data: 0.0076 max mem: 33303 +Epoch: [32] [1860/4276] eta: 1:58:06 lr: 1.1169473264787627e-05 loss: 0.0711 (0.0840) time: 2.9998 data: 0.0076 max mem: 33303 +Epoch: [32] [1870/4276] eta: 1:57:37 lr: 1.1166365501674612e-05 loss: 0.0719 (0.0839) time: 2.9817 data: 0.0080 max mem: 33303 +Epoch: [32] [1880/4276] eta: 1:57:07 lr: 1.1163257642454618e-05 loss: 0.0725 (0.0839) time: 2.9511 data: 0.0074 max mem: 33303 +Epoch: [32] [1890/4276] eta: 1:56:38 lr: 1.1160149687094949e-05 loss: 0.0754 (0.0839) time: 2.9313 data: 0.0074 max mem: 33303 +Epoch: [32] [1900/4276] eta: 1:56:09 lr: 1.1157041635562877e-05 loss: 0.0738 (0.0838) time: 2.9421 data: 0.0077 max mem: 33303 +Epoch: [32] [1910/4276] eta: 1:55:40 lr: 1.1153933487825665e-05 loss: 0.0738 (0.0838) time: 2.9618 data: 0.0074 max mem: 33303 +Epoch: [32] [1920/4276] eta: 1:55:11 lr: 1.1150825243850531e-05 loss: 0.0731 (0.0838) time: 2.9611 data: 0.0072 max mem: 33303 +Epoch: [32] [1930/4276] eta: 1:54:42 lr: 1.1147716903604696e-05 loss: 0.0754 (0.0838) time: 2.9595 data: 0.0071 max mem: 33303 +Epoch: [32] [1940/4276] eta: 1:54:13 lr: 1.114460846705535e-05 loss: 0.0754 (0.0838) time: 2.9646 data: 0.0074 max mem: 33303 +Epoch: [32] [1950/4276] eta: 1:53:44 lr: 1.1141499934169665e-05 loss: 0.0743 (0.0838) time: 2.9599 data: 0.0075 max mem: 33303 +Epoch: [32] [1960/4276] eta: 1:53:15 lr: 1.113839130491478e-05 loss: 0.0702 (0.0837) time: 2.9468 data: 0.0074 max mem: 33303 +Epoch: [32] [1970/4276] eta: 1:52:45 lr: 1.1135282579257827e-05 loss: 0.0667 (0.0837) time: 2.9479 data: 0.0077 max mem: 33303 +Epoch: [32] [1980/4276] eta: 1:52:17 lr: 1.113217375716591e-05 loss: 0.0667 (0.0836) time: 2.9596 data: 0.0082 max mem: 33303 +Epoch: [32] [1990/4276] eta: 1:51:47 lr: 1.1129064838606118e-05 loss: 0.0697 (0.0836) time: 2.9584 data: 0.0084 max mem: 33303 +Epoch: [32] [2000/4276] eta: 1:51:18 lr: 1.1125955823545503e-05 loss: 0.0755 (0.0836) time: 2.9478 data: 0.0080 max mem: 33303 +Epoch: [32] [2010/4276] eta: 1:50:49 lr: 1.112284671195111e-05 loss: 0.0786 (0.0836) time: 2.9595 data: 0.0083 max mem: 33303 +Epoch: [32] [2020/4276] eta: 1:50:20 lr: 1.1119737503789958e-05 loss: 0.0820 (0.0836) time: 2.9622 data: 0.0089 max mem: 33303 +Epoch: [32] [2030/4276] eta: 1:49:51 lr: 1.111662819902905e-05 loss: 0.0708 (0.0835) time: 2.9598 data: 0.0088 max mem: 33303 +Epoch: [32] [2040/4276] eta: 1:49:22 lr: 1.1113518797635352e-05 loss: 0.0691 (0.0835) time: 2.9624 data: 0.0084 max mem: 33303 +Epoch: [32] [2050/4276] eta: 1:48:53 lr: 1.1110409299575822e-05 loss: 0.0771 (0.0836) time: 2.9610 data: 0.0088 max mem: 33303 +Epoch: [32] [2060/4276] eta: 1:48:24 lr: 1.1107299704817395e-05 loss: 0.0810 (0.0835) time: 2.9590 data: 0.0095 max mem: 33303 +Epoch: [32] [2070/4276] eta: 1:47:55 lr: 1.1104190013326986e-05 loss: 0.0781 (0.0835) time: 2.9519 data: 0.0095 max mem: 33303 +Epoch: [32] [2080/4276] eta: 1:47:25 lr: 1.1101080225071477e-05 loss: 0.0815 (0.0835) time: 2.9487 data: 0.0089 max mem: 33303 +Epoch: [32] [2090/4276] eta: 1:46:56 lr: 1.1097970340017737e-05 loss: 0.0796 (0.0835) time: 2.9483 data: 0.0087 max mem: 33303 +Epoch: [32] [2100/4276] eta: 1:46:27 lr: 1.1094860358132613e-05 loss: 0.0693 (0.0835) time: 2.9479 data: 0.0092 max mem: 33303 +Epoch: [32] [2110/4276] eta: 1:45:58 lr: 1.1091750279382938e-05 loss: 0.0781 (0.0834) time: 2.9472 data: 0.0091 max mem: 33303 +Epoch: [32] [2120/4276] eta: 1:45:29 lr: 1.1088640103735502e-05 loss: 0.0640 (0.0833) time: 2.9471 data: 0.0088 max mem: 33303 +Epoch: [32] [2130/4276] eta: 1:44:59 lr: 1.108552983115709e-05 loss: 0.0624 (0.0833) time: 2.9395 data: 0.0087 max mem: 33303 +Epoch: [32] [2140/4276] eta: 1:44:30 lr: 1.1082419461614465e-05 loss: 0.0794 (0.0833) time: 2.9419 data: 0.0091 max mem: 33303 +Epoch: [32] [2150/4276] eta: 1:44:01 lr: 1.107930899507437e-05 loss: 0.0794 (0.0832) time: 2.9518 data: 0.0091 max mem: 33303 +Epoch: [32] [2160/4276] eta: 1:43:32 lr: 1.1076198431503507e-05 loss: 0.0716 (0.0832) time: 2.9509 data: 0.0087 max mem: 33303 +Epoch: [32] [2170/4276] eta: 1:43:03 lr: 1.1073087770868577e-05 loss: 0.0772 (0.0832) time: 2.9643 data: 0.0088 max mem: 33303 +Epoch: [32] [2180/4276] eta: 1:42:33 lr: 1.1069977013136257e-05 loss: 0.0792 (0.0832) time: 2.9678 data: 0.0087 max mem: 33303 +Epoch: [32] [2190/4276] eta: 1:42:04 lr: 1.1066866158273188e-05 loss: 0.0697 (0.0831) time: 2.9582 data: 0.0088 max mem: 33303 +Epoch: [32] [2200/4276] eta: 1:41:35 lr: 1.1063755206246003e-05 loss: 0.0820 (0.0832) time: 2.9579 data: 0.0087 max mem: 33303 +Epoch: [32] [2210/4276] eta: 1:41:06 lr: 1.1060644157021308e-05 loss: 0.0826 (0.0832) time: 2.9584 data: 0.0087 max mem: 33303 +Epoch: [32] [2220/4276] eta: 1:40:37 lr: 1.1057533010565695e-05 loss: 0.0811 (0.0832) time: 2.9541 data: 0.0091 max mem: 33303 +Epoch: [32] [2230/4276] eta: 1:40:07 lr: 1.1054421766845715e-05 loss: 0.0830 (0.0832) time: 2.9321 data: 0.0089 max mem: 33303 +Epoch: [32] [2240/4276] eta: 1:39:38 lr: 1.1051310425827912e-05 loss: 0.0645 (0.0831) time: 2.9152 data: 0.0091 max mem: 33303 +Epoch: [32] [2250/4276] eta: 1:39:08 lr: 1.1048198987478808e-05 loss: 0.0676 (0.0831) time: 2.9182 data: 0.0093 max mem: 33303 +Epoch: [32] [2260/4276] eta: 1:38:39 lr: 1.1045087451764904e-05 loss: 0.0829 (0.0831) time: 2.9435 data: 0.0084 max mem: 33303 +Epoch: [32] [2270/4276] eta: 1:38:10 lr: 1.1041975818652665e-05 loss: 0.0839 (0.0831) time: 2.9623 data: 0.0079 max mem: 33303 +Epoch: [32] [2280/4276] eta: 1:37:41 lr: 1.1038864088108547e-05 loss: 0.0749 (0.0831) time: 2.9582 data: 0.0080 max mem: 33303 +Epoch: [32] [2290/4276] eta: 1:37:11 lr: 1.1035752260098982e-05 loss: 0.0778 (0.0831) time: 2.9579 data: 0.0080 max mem: 33303 +Epoch: [32] [2300/4276] eta: 1:36:42 lr: 1.1032640334590384e-05 loss: 0.0816 (0.0831) time: 2.9594 data: 0.0080 max mem: 33303 +Epoch: [32] [2310/4276] eta: 1:36:13 lr: 1.102952831154913e-05 loss: 0.0906 (0.0832) time: 2.9424 data: 0.0085 max mem: 33303 +Epoch: [32] [2320/4276] eta: 1:35:44 lr: 1.1026416190941586e-05 loss: 0.0837 (0.0831) time: 2.9400 data: 0.0087 max mem: 33303 +Epoch: [32] [2330/4276] eta: 1:35:14 lr: 1.1023303972734097e-05 loss: 0.0829 (0.0832) time: 2.9565 data: 0.0079 max mem: 33303 +Epoch: [32] [2340/4276] eta: 1:34:45 lr: 1.1020191656892989e-05 loss: 0.0829 (0.0832) time: 2.9592 data: 0.0077 max mem: 33303 +Epoch: [32] [2350/4276] eta: 1:34:16 lr: 1.1017079243384549e-05 loss: 0.0818 (0.0832) time: 2.9602 data: 0.0079 max mem: 33303 +Epoch: [32] [2360/4276] eta: 1:33:47 lr: 1.1013966732175055e-05 loss: 0.0818 (0.0832) time: 2.9629 data: 0.0080 max mem: 33303 +Epoch: [32] [2370/4276] eta: 1:33:18 lr: 1.1010854123230762e-05 loss: 0.0781 (0.0833) time: 2.9605 data: 0.0080 max mem: 33303 +Epoch: [32] [2380/4276] eta: 1:32:48 lr: 1.1007741416517908e-05 loss: 0.0857 (0.0833) time: 2.9410 data: 0.0082 max mem: 33303 +Epoch: [32] [2390/4276] eta: 1:32:19 lr: 1.100462861200269e-05 loss: 0.0826 (0.0833) time: 2.9354 data: 0.0084 max mem: 33303 +Epoch: [32] [2400/4276] eta: 1:31:50 lr: 1.10015157096513e-05 loss: 0.0838 (0.0833) time: 2.9478 data: 0.0084 max mem: 33303 +Epoch: [32] [2410/4276] eta: 1:31:20 lr: 1.0998402709429902e-05 loss: 0.0870 (0.0833) time: 2.9471 data: 0.0080 max mem: 33303 +Epoch: [32] [2420/4276] eta: 1:30:51 lr: 1.0995289611304645e-05 loss: 0.0769 (0.0833) time: 2.9429 data: 0.0075 max mem: 33303 +Epoch: [32] [2430/4276] eta: 1:30:22 lr: 1.0992176415241633e-05 loss: 0.0855 (0.0833) time: 2.9430 data: 0.0077 max mem: 33303 +Epoch: [32] [2440/4276] eta: 1:29:52 lr: 1.0989063121206972e-05 loss: 0.0855 (0.0833) time: 2.9450 data: 0.0077 max mem: 33303 +Epoch: [32] [2450/4276] eta: 1:29:23 lr: 1.0985949729166739e-05 loss: 0.0746 (0.0833) time: 2.9468 data: 0.0075 max mem: 33303 +Epoch: [32] [2460/4276] eta: 1:28:54 lr: 1.0982836239086989e-05 loss: 0.0783 (0.0833) time: 2.9468 data: 0.0084 max mem: 33303 +Epoch: [32] [2470/4276] eta: 1:28:25 lr: 1.0979722650933739e-05 loss: 0.0772 (0.0833) time: 2.9558 data: 0.0088 max mem: 33303 +Epoch: [32] [2480/4276] eta: 1:27:55 lr: 1.0976608964673004e-05 loss: 0.0772 (0.0833) time: 2.9605 data: 0.0080 max mem: 33303 +Epoch: [32] [2490/4276] eta: 1:27:26 lr: 1.0973495180270773e-05 loss: 0.0833 (0.0833) time: 2.9563 data: 0.0078 max mem: 33303 +Epoch: [32] [2500/4276] eta: 1:26:57 lr: 1.0970381297693e-05 loss: 0.0842 (0.0833) time: 2.9571 data: 0.0080 max mem: 33303 +Epoch: [32] [2510/4276] eta: 1:26:28 lr: 1.096726731690563e-05 loss: 0.0842 (0.0833) time: 2.9579 data: 0.0082 max mem: 33303 +Epoch: [32] [2520/4276] eta: 1:25:58 lr: 1.0964153237874576e-05 loss: 0.0814 (0.0833) time: 2.9572 data: 0.0080 max mem: 33303 +Epoch: [32] [2530/4276] eta: 1:25:29 lr: 1.0961039060565741e-05 loss: 0.0694 (0.0832) time: 2.9607 data: 0.0077 max mem: 33303 +Epoch: [32] [2540/4276] eta: 1:25:00 lr: 1.0957924784944986e-05 loss: 0.0668 (0.0832) time: 2.9593 data: 0.0074 max mem: 33303 +Epoch: [32] [2550/4276] eta: 1:35:16 lr: 1.0954810410978166e-05 loss: 0.0693 (0.0832) time: 50.6122 data: 47.6538 max mem: 33303 +Epoch: [32] [2560/4276] eta: 1:34:40 lr: 1.0951695938631109e-05 loss: 0.0693 (0.0831) time: 50.6048 data: 47.6539 max mem: 33303 +Epoch: [32] [2570/4276] eta: 1:34:05 lr: 1.0948581367869621e-05 loss: 0.0698 (0.0831) time: 2.9446 data: 0.0074 max mem: 33303 +Epoch: [32] [2580/4276] eta: 1:33:29 lr: 1.0945466698659476e-05 loss: 0.0717 (0.0831) time: 2.9578 data: 0.0076 max mem: 33303 +Epoch: [32] [2590/4276] eta: 1:32:54 lr: 1.0942351930966434e-05 loss: 0.0691 (0.0831) time: 2.9436 data: 0.0076 max mem: 33303 +Epoch: [32] [2600/4276] eta: 1:32:18 lr: 1.0939237064756236e-05 loss: 0.0663 (0.0831) time: 2.9291 data: 0.0077 max mem: 33303 +Epoch: [32] [2610/4276] eta: 1:31:43 lr: 1.0936122099994598e-05 loss: 0.0753 (0.0831) time: 2.9313 data: 0.0079 max mem: 33303 +Epoch: [32] [2620/4276] eta: 1:31:07 lr: 1.0933007036647198e-05 loss: 0.0797 (0.0831) time: 2.9333 data: 0.0078 max mem: 33303 +Epoch: [32] [2630/4276] eta: 1:30:32 lr: 1.092989187467971e-05 loss: 0.0720 (0.0831) time: 2.9390 data: 0.0080 max mem: 33303 +Epoch: [32] [2640/4276] eta: 1:29:57 lr: 1.092677661405778e-05 loss: 0.0720 (0.0831) time: 2.9424 data: 0.0076 max mem: 33303 +Epoch: [32] [2650/4276] eta: 1:29:22 lr: 1.0923661254747034e-05 loss: 0.0789 (0.0831) time: 2.9484 data: 0.0071 max mem: 33303 +Epoch: [32] [2660/4276] eta: 1:28:47 lr: 1.0920545796713059e-05 loss: 0.0891 (0.0831) time: 2.9496 data: 0.0071 max mem: 33303 +Epoch: [32] [2670/4276] eta: 1:28:12 lr: 1.0917430239921439e-05 loss: 0.0829 (0.0832) time: 2.9478 data: 0.0077 max mem: 33303 +Epoch: [32] [2680/4276] eta: 1:27:37 lr: 1.0914314584337725e-05 loss: 0.0831 (0.0832) time: 2.9535 data: 0.0078 max mem: 33303 +Epoch: [32] [2690/4276] eta: 1:27:02 lr: 1.0911198829927453e-05 loss: 0.0722 (0.0831) time: 2.9547 data: 0.0078 max mem: 33303 +Epoch: [32] [2700/4276] eta: 1:26:27 lr: 1.0908082976656121e-05 loss: 0.0722 (0.0831) time: 2.9412 data: 0.0081 max mem: 33303 +Epoch: [32] [2710/4276] eta: 1:25:51 lr: 1.0904967024489216e-05 loss: 0.0695 (0.0831) time: 2.9123 data: 0.0084 max mem: 33303 +Epoch: [32] [2720/4276] eta: 1:25:16 lr: 1.0901850973392202e-05 loss: 0.0675 (0.0830) time: 2.9142 data: 0.0086 max mem: 33303 +Epoch: [32] [2730/4276] eta: 1:24:42 lr: 1.0898734823330522e-05 loss: 0.0711 (0.0830) time: 2.9404 data: 0.0086 max mem: 33303 +Epoch: [32] [2740/4276] eta: 1:24:07 lr: 1.0895618574269579e-05 loss: 0.0773 (0.0830) time: 2.9517 data: 0.0083 max mem: 33303 +Epoch: [32] [2750/4276] eta: 1:23:32 lr: 1.089250222617477e-05 loss: 0.0773 (0.0830) time: 2.9804 data: 0.0078 max mem: 33303 +Epoch: [32] [2760/4276] eta: 1:22:58 lr: 1.0889385779011463e-05 loss: 0.0786 (0.0830) time: 2.9919 data: 0.0076 max mem: 33303 +Epoch: [32] [2770/4276] eta: 1:22:23 lr: 1.0886269232745014e-05 loss: 0.0787 (0.0830) time: 2.9631 data: 0.0077 max mem: 33303 +Epoch: [32] [2780/4276] eta: 1:21:49 lr: 1.0883152587340731e-05 loss: 0.0799 (0.0830) time: 2.9498 data: 0.0079 max mem: 33303 +Epoch: [32] [2790/4276] eta: 1:21:14 lr: 1.088003584276392e-05 loss: 0.0839 (0.0830) time: 2.9537 data: 0.0074 max mem: 33303 +Epoch: [32] [2800/4276] eta: 1:20:40 lr: 1.0876918998979862e-05 loss: 0.0775 (0.0830) time: 2.9468 data: 0.0074 max mem: 33303 +Epoch: [32] [2810/4276] eta: 1:20:05 lr: 1.08738020559538e-05 loss: 0.0637 (0.0829) time: 2.9407 data: 0.0080 max mem: 33303 +Epoch: [32] [2820/4276] eta: 1:19:31 lr: 1.0870685013650967e-05 loss: 0.0606 (0.0829) time: 2.9439 data: 0.0080 max mem: 33303 +Epoch: [32] [2830/4276] eta: 1:18:56 lr: 1.0867567872036574e-05 loss: 0.0812 (0.0829) time: 2.9676 data: 0.0076 max mem: 33303 +Epoch: [32] [2840/4276] eta: 1:18:22 lr: 1.0864450631075806e-05 loss: 0.0859 (0.0829) time: 2.9638 data: 0.0073 max mem: 33303 +Epoch: [32] [2850/4276] eta: 1:17:48 lr: 1.0861333290733814e-05 loss: 0.0902 (0.0829) time: 2.9619 data: 0.0073 max mem: 33303 +Epoch: [32] [2860/4276] eta: 1:17:13 lr: 1.085821585097574e-05 loss: 0.0761 (0.0829) time: 2.9625 data: 0.0073 max mem: 33303 +Epoch: [32] [2870/4276] eta: 1:16:39 lr: 1.0855098311766694e-05 loss: 0.0761 (0.0829) time: 2.9686 data: 0.0077 max mem: 33303 +Epoch: [32] [2880/4276] eta: 1:16:05 lr: 1.0851980673071776e-05 loss: 0.0730 (0.0828) time: 2.9921 data: 0.0077 max mem: 33303 +Epoch: [32] [2890/4276] eta: 1:15:31 lr: 1.0848862934856039e-05 loss: 0.0730 (0.0829) time: 2.9726 data: 0.0076 max mem: 33303 +Epoch: [32] [2900/4276] eta: 1:14:57 lr: 1.0845745097084531e-05 loss: 0.0727 (0.0828) time: 2.9435 data: 0.0078 max mem: 33303 +Epoch: [32] [2910/4276] eta: 1:14:22 lr: 1.0842627159722274e-05 loss: 0.0806 (0.0829) time: 2.9407 data: 0.0080 max mem: 33303 +Epoch: [32] [2920/4276] eta: 1:13:48 lr: 1.0839509122734267e-05 loss: 0.0860 (0.0829) time: 2.9454 data: 0.0080 max mem: 33303 +Epoch: [32] [2930/4276] eta: 1:13:14 lr: 1.0836390986085474e-05 loss: 0.0789 (0.0828) time: 2.9554 data: 0.0079 max mem: 33303 +Epoch: [32] [2940/4276] eta: 1:12:40 lr: 1.0833272749740849e-05 loss: 0.0751 (0.0829) time: 2.9572 data: 0.0083 max mem: 33303 +Epoch: [32] [2950/4276] eta: 1:12:06 lr: 1.0830154413665315e-05 loss: 0.0798 (0.0829) time: 2.9468 data: 0.0085 max mem: 33303 +Epoch: [32] [2960/4276] eta: 1:11:32 lr: 1.0827035977823783e-05 loss: 0.0769 (0.0828) time: 2.9397 data: 0.0085 max mem: 33303 +Epoch: [32] [2970/4276] eta: 1:10:58 lr: 1.0823917442181119e-05 loss: 0.0757 (0.0828) time: 2.9394 data: 0.0086 max mem: 33303 +Epoch: [32] [2980/4276] eta: 1:10:24 lr: 1.0820798806702183e-05 loss: 0.0757 (0.0828) time: 2.9265 data: 0.0084 max mem: 33303 +Epoch: [32] [2990/4276] eta: 1:09:50 lr: 1.0817680071351808e-05 loss: 0.0739 (0.0828) time: 2.9000 data: 0.0084 max mem: 33303 +Epoch: [32] [3000/4276] eta: 1:09:16 lr: 1.0814561236094803e-05 loss: 0.0740 (0.0828) time: 2.9027 data: 0.0091 max mem: 33303 +Epoch: [32] [3010/4276] eta: 1:08:42 lr: 1.0811442300895945e-05 loss: 0.0766 (0.0828) time: 2.9359 data: 0.0089 max mem: 33303 +Epoch: [32] [3020/4276] eta: 1:08:08 lr: 1.0808323265719998e-05 loss: 0.0746 (0.0828) time: 2.9808 data: 0.0082 max mem: 33303 +Epoch: [32] [3030/4276] eta: 1:07:34 lr: 1.08052041305317e-05 loss: 0.0775 (0.0828) time: 2.9968 data: 0.0083 max mem: 33303 +Epoch: [32] [3040/4276] eta: 1:07:01 lr: 1.0802084895295766e-05 loss: 0.0837 (0.0828) time: 2.9682 data: 0.0083 max mem: 33303 +Epoch: [32] [3050/4276] eta: 1:06:27 lr: 1.0798965559976875e-05 loss: 0.0820 (0.0828) time: 2.9441 data: 0.0080 max mem: 33303 +Epoch: [32] [3060/4276] eta: 1:05:53 lr: 1.0795846124539698e-05 loss: 0.0664 (0.0827) time: 2.9452 data: 0.0080 max mem: 33303 +Epoch: [32] [3070/4276] eta: 1:05:19 lr: 1.0792726588948876e-05 loss: 0.0696 (0.0827) time: 2.9468 data: 0.0083 max mem: 33303 +Epoch: [32] [3080/4276] eta: 1:04:46 lr: 1.0789606953169034e-05 loss: 0.0717 (0.0827) time: 2.9606 data: 0.0081 max mem: 33303 +Epoch: [32] [3090/4276] eta: 1:04:12 lr: 1.0786487217164752e-05 loss: 0.0706 (0.0827) time: 2.9801 data: 0.0080 max mem: 33303 +Epoch: [32] [3100/4276] eta: 1:03:39 lr: 1.0783367380900605e-05 loss: 0.0705 (0.0826) time: 2.9680 data: 0.0081 max mem: 33303 +Epoch: [32] [3110/4276] eta: 1:03:05 lr: 1.0780247444341147e-05 loss: 0.0723 (0.0826) time: 2.9327 data: 0.0081 max mem: 33303 +Epoch: [32] [3120/4276] eta: 1:02:31 lr: 1.0777127407450885e-05 loss: 0.0743 (0.0826) time: 2.9340 data: 0.0084 max mem: 33303 +Epoch: [32] [3130/4276] eta: 1:01:58 lr: 1.0774007270194326e-05 loss: 0.0773 (0.0826) time: 2.9345 data: 0.0094 max mem: 33303 +Epoch: [32] [3140/4276] eta: 1:01:24 lr: 1.0770887032535942e-05 loss: 0.0773 (0.0826) time: 2.9536 data: 0.0095 max mem: 33303 +Epoch: [32] [3150/4276] eta: 1:00:51 lr: 1.0767766694440188e-05 loss: 0.0843 (0.0826) time: 2.9810 data: 0.0083 max mem: 33303 +Epoch: [32] [3160/4276] eta: 1:00:18 lr: 1.0764646255871478e-05 loss: 0.0850 (0.0826) time: 2.9843 data: 0.0079 max mem: 33303 +Epoch: [32] [3170/4276] eta: 0:59:44 lr: 1.0761525716794222e-05 loss: 0.0800 (0.0826) time: 2.9915 data: 0.0075 max mem: 33303 +Epoch: [32] [3180/4276] eta: 0:59:11 lr: 1.0758405077172795e-05 loss: 0.0765 (0.0826) time: 2.9785 data: 0.0071 max mem: 33303 +Epoch: [32] [3190/4276] eta: 0:58:38 lr: 1.0755284336971556e-05 loss: 0.0765 (0.0826) time: 2.9540 data: 0.0073 max mem: 33303 +Epoch: [32] [3200/4276] eta: 0:58:04 lr: 1.0752163496154826e-05 loss: 0.0834 (0.0826) time: 2.9637 data: 0.0073 max mem: 33303 +Epoch: [32] [3210/4276] eta: 0:57:31 lr: 1.0749042554686913e-05 loss: 0.0775 (0.0826) time: 2.9742 data: 0.0071 max mem: 33303 +Epoch: [32] [3220/4276] eta: 0:56:58 lr: 1.07459215125321e-05 loss: 0.0715 (0.0826) time: 2.9650 data: 0.0070 max mem: 33303 +Epoch: [32] [3230/4276] eta: 0:56:25 lr: 1.0742800369654648e-05 loss: 0.0780 (0.0826) time: 2.9658 data: 0.0071 max mem: 33303 +Epoch: [32] [3240/4276] eta: 0:55:51 lr: 1.073967912601878e-05 loss: 0.0858 (0.0826) time: 2.9547 data: 0.0073 max mem: 33303 +Epoch: [32] [3250/4276] eta: 0:55:18 lr: 1.0736557781588706e-05 loss: 0.0906 (0.0826) time: 2.9432 data: 0.0073 max mem: 33303 +Epoch: [32] [3260/4276] eta: 0:54:45 lr: 1.0733436336328616e-05 loss: 0.0886 (0.0827) time: 2.9534 data: 0.0074 max mem: 33303 +Epoch: [32] [3270/4276] eta: 0:54:12 lr: 1.073031479020267e-05 loss: 0.0842 (0.0827) time: 2.9602 data: 0.0074 max mem: 33303 +Epoch: [32] [3280/4276] eta: 0:53:38 lr: 1.0727193143174996e-05 loss: 0.0843 (0.0827) time: 2.9581 data: 0.0073 max mem: 33303 +Epoch: [32] [3290/4276] eta: 0:53:05 lr: 1.0724071395209707e-05 loss: 0.0863 (0.0827) time: 2.9503 data: 0.0073 max mem: 33303 +Epoch: [32] [3300/4276] eta: 0:52:32 lr: 1.0720949546270894e-05 loss: 0.0867 (0.0828) time: 2.9387 data: 0.0074 max mem: 33303 +Epoch: [32] [3310/4276] eta: 0:51:59 lr: 1.0717827596322623e-05 loss: 0.0938 (0.0828) time: 2.9555 data: 0.0073 max mem: 33303 +Epoch: [32] [3320/4276] eta: 0:51:26 lr: 1.0714705545328918e-05 loss: 0.0905 (0.0828) time: 2.9631 data: 0.0072 max mem: 33303 +Epoch: [32] [3330/4276] eta: 0:50:53 lr: 1.0711583393253802e-05 loss: 0.0816 (0.0828) time: 2.9668 data: 0.0072 max mem: 33303 +Epoch: [32] [3340/4276] eta: 0:50:20 lr: 1.0708461140061263e-05 loss: 0.0736 (0.0828) time: 2.9639 data: 0.0072 max mem: 33303 +Epoch: [32] [3350/4276] eta: 0:49:47 lr: 1.070533878571527e-05 loss: 0.0794 (0.0828) time: 2.9731 data: 0.0075 max mem: 33303 +Epoch: [32] [3360/4276] eta: 0:49:14 lr: 1.070221633017975e-05 loss: 0.0794 (0.0828) time: 2.9612 data: 0.0077 max mem: 33303 +Epoch: [32] [3370/4276] eta: 0:48:41 lr: 1.0699093773418628e-05 loss: 0.0818 (0.0828) time: 2.9306 data: 0.0076 max mem: 33303 +Epoch: [32] [3380/4276] eta: 0:48:08 lr: 1.0695971115395792e-05 loss: 0.0766 (0.0828) time: 2.9367 data: 0.0075 max mem: 33303 +Epoch: [32] [3390/4276] eta: 0:47:35 lr: 1.0692848356075116e-05 loss: 0.0707 (0.0828) time: 2.9383 data: 0.0074 max mem: 33303 +Epoch: [32] [3400/4276] eta: 0:47:02 lr: 1.0689725495420427e-05 loss: 0.0772 (0.0828) time: 2.9388 data: 0.0073 max mem: 33303 +Epoch: [32] [3410/4276] eta: 0:46:29 lr: 1.068660253339555e-05 loss: 0.0753 (0.0828) time: 2.9685 data: 0.0072 max mem: 33303 +Epoch: [32] [3420/4276] eta: 0:45:56 lr: 1.0683479469964284e-05 loss: 0.0875 (0.0828) time: 2.9782 data: 0.0074 max mem: 33303 +Epoch: [32] [3430/4276] eta: 0:45:23 lr: 1.0680356305090381e-05 loss: 0.0908 (0.0828) time: 2.9531 data: 0.0076 max mem: 33303 +Epoch: [32] [3440/4276] eta: 0:44:51 lr: 1.0677233038737594e-05 loss: 0.0784 (0.0828) time: 2.9440 data: 0.0080 max mem: 33303 +Epoch: [32] [3450/4276] eta: 0:44:18 lr: 1.067410967086964e-05 loss: 0.0909 (0.0829) time: 2.9616 data: 0.0078 max mem: 33303 +Epoch: [32] [3460/4276] eta: 0:43:45 lr: 1.0670986201450215e-05 loss: 0.0932 (0.0829) time: 2.9851 data: 0.0073 max mem: 33303 +Epoch: [32] [3470/4276] eta: 0:43:12 lr: 1.066786263044298e-05 loss: 0.0803 (0.0829) time: 2.9974 data: 0.0072 max mem: 33303 +Epoch: [32] [3480/4276] eta: 0:42:40 lr: 1.066473895781158e-05 loss: 0.0804 (0.0829) time: 2.9724 data: 0.0073 max mem: 33303 +Epoch: [32] [3490/4276] eta: 0:42:07 lr: 1.066161518351964e-05 loss: 0.0850 (0.0829) time: 2.9413 data: 0.0072 max mem: 33303 +Epoch: [32] [3500/4276] eta: 0:41:34 lr: 1.0658491307530755e-05 loss: 0.0756 (0.0829) time: 2.9444 data: 0.0073 max mem: 33303 +Epoch: [32] [3510/4276] eta: 0:41:01 lr: 1.0655367329808483e-05 loss: 0.0768 (0.0829) time: 2.9457 data: 0.0077 max mem: 33303 +Epoch: [32] [3520/4276] eta: 0:40:29 lr: 1.0652243250316375e-05 loss: 0.0789 (0.0829) time: 2.9465 data: 0.0077 max mem: 33303 +Epoch: [32] [3530/4276] eta: 0:39:56 lr: 1.064911906901795e-05 loss: 0.0881 (0.0829) time: 2.9457 data: 0.0075 max mem: 33303 +Epoch: [32] [3540/4276] eta: 0:39:23 lr: 1.0645994785876709e-05 loss: 0.0881 (0.0829) time: 2.9469 data: 0.0077 max mem: 33303 +Epoch: [32] [3550/4276] eta: 0:38:51 lr: 1.0642870400856107e-05 loss: 0.0759 (0.0829) time: 2.9483 data: 0.0080 max mem: 33303 +Epoch: [32] [3560/4276] eta: 0:38:18 lr: 1.0639745913919596e-05 loss: 0.0759 (0.0829) time: 2.9472 data: 0.0080 max mem: 33303 +Epoch: [32] [3570/4276] eta: 0:37:45 lr: 1.0636621325030594e-05 loss: 0.0826 (0.0829) time: 2.9591 data: 0.0080 max mem: 33303 +Epoch: [32] [3580/4276] eta: 0:37:13 lr: 1.0633496634152502e-05 loss: 0.0826 (0.0830) time: 2.9741 data: 0.0080 max mem: 33303 +Epoch: [32] [3590/4276] eta: 0:36:40 lr: 1.0630371841248678e-05 loss: 0.0767 (0.0830) time: 2.9640 data: 0.0079 max mem: 33303 +Epoch: [32] [3600/4276] eta: 0:36:08 lr: 1.0627246946282469e-05 loss: 0.0859 (0.0830) time: 2.9326 data: 0.0078 max mem: 33303 +Epoch: [32] [3610/4276] eta: 0:35:35 lr: 1.0624121949217197e-05 loss: 0.0856 (0.0830) time: 2.9124 data: 0.0080 max mem: 33303 +Epoch: [32] [3620/4276] eta: 0:35:02 lr: 1.0620996850016158e-05 loss: 0.0731 (0.0829) time: 2.9007 data: 0.0082 max mem: 33303 +Epoch: [32] [3630/4276] eta: 0:34:30 lr: 1.0617871648642613e-05 loss: 0.0832 (0.0829) time: 2.8864 data: 0.0075 max mem: 33303 +Epoch: [32] [3640/4276] eta: 0:33:57 lr: 1.0614746345059804e-05 loss: 0.0832 (0.0829) time: 2.8835 data: 0.0072 max mem: 33303 +Epoch: [32] [3650/4276] eta: 0:33:25 lr: 1.0611620939230957e-05 loss: 0.0810 (0.0829) time: 2.8834 data: 0.0079 max mem: 33303 +Epoch: [32] [3660/4276] eta: 0:32:52 lr: 1.0608495431119263e-05 loss: 0.0827 (0.0829) time: 2.9114 data: 0.0085 max mem: 33303 +Epoch: [32] [3670/4276] eta: 0:32:20 lr: 1.0605369820687883e-05 loss: 0.0827 (0.0829) time: 2.9441 data: 0.0088 max mem: 33303 +Epoch: [32] [3680/4276] eta: 0:31:47 lr: 1.0602244107899965e-05 loss: 0.0764 (0.0829) time: 2.9479 data: 0.0089 max mem: 33303 +Epoch: [32] [3690/4276] eta: 0:31:15 lr: 1.0599118292718619e-05 loss: 0.0827 (0.0830) time: 2.9474 data: 0.0088 max mem: 33303 +Epoch: [32] [3700/4276] eta: 0:30:42 lr: 1.0595992375106948e-05 loss: 0.0827 (0.0829) time: 2.9484 data: 0.0086 max mem: 33303 +Epoch: [32] [3710/4276] eta: 0:30:10 lr: 1.0592866355028005e-05 loss: 0.0813 (0.0829) time: 2.9485 data: 0.0086 max mem: 33303 +Epoch: [32] [3720/4276] eta: 0:29:38 lr: 1.0589740232444837e-05 loss: 0.0777 (0.0829) time: 2.9474 data: 0.0088 max mem: 33303 +Epoch: [32] [3730/4276] eta: 0:29:05 lr: 1.0586614007320461e-05 loss: 0.0777 (0.0830) time: 2.9331 data: 0.0091 max mem: 33303 +Epoch: [32] [3740/4276] eta: 0:28:33 lr: 1.058348767961786e-05 loss: 0.0769 (0.0829) time: 2.9297 data: 0.0086 max mem: 33303 +Epoch: [32] [3750/4276] eta: 0:28:01 lr: 1.0580361249299999e-05 loss: 0.0791 (0.0829) time: 2.9436 data: 0.0080 max mem: 33303 +Epoch: [32] [3760/4276] eta: 0:27:28 lr: 1.0577234716329818e-05 loss: 0.0762 (0.0829) time: 3.0116 data: 0.0075 max mem: 33303 +Epoch: [32] [3770/4276] eta: 0:33:44 lr: 1.0574108080670235e-05 loss: 0.0701 (0.0830) time: 154.9523 data: 151.3996 max mem: 33303 +Epoch: [32] [3780/4276] eta: 0:33:36 lr: 1.0570981342284127e-05 loss: 0.0701 (0.0829) time: 167.7421 data: 163.9925 max mem: 33303 +Epoch: [32] [3790/4276] eta: 0:33:27 lr: 1.0567854501134363e-05 loss: 0.0668 (0.0829) time: 28.4175 data: 24.8906 max mem: 33303 +Epoch: [32] [3800/4276] eta: 0:33:14 lr: 1.0564727557183775e-05 loss: 0.0809 (0.0829) time: 27.7598 data: 24.1809 max mem: 33303 +Epoch: [32] [3810/4276] eta: 0:33:33 lr: 1.0561600510395182e-05 loss: 0.0808 (0.0829) time: 40.6605 data: 36.8461 max mem: 33303 +Epoch: [32] [3820/4276] eta: 0:33:18 lr: 1.0558473360731354e-05 loss: 0.0788 (0.0829) time: 41.0438 data: 37.2699 max mem: 33303 +Epoch: [32] [3830/4276] eta: 0:33:05 lr: 1.0555346108155058e-05 loss: 0.0728 (0.0829) time: 29.2520 data: 25.6704 max mem: 33303 +Epoch: [32] [3840/4276] eta: 0:32:48 lr: 1.0552218752629028e-05 loss: 0.0686 (0.0829) time: 29.5477 data: 25.9210 max mem: 33303 +Epoch: [32] [3850/4276] eta: 0:32:57 lr: 1.0549091294115974e-05 loss: 0.0685 (0.0828) time: 41.0501 data: 37.2423 max mem: 33303 +Epoch: [32] [3860/4276] eta: 0:32:36 lr: 1.054596373257857e-05 loss: 0.0880 (0.0829) time: 40.9166 data: 37.1445 max mem: 33303 +Epoch: [32] [3870/4276] eta: 0:32:15 lr: 1.0542836067979473e-05 loss: 0.0751 (0.0829) time: 28.7478 data: 25.2886 max mem: 33303 +Epoch: [32] [3880/4276] eta: 0:31:50 lr: 1.0539708300281317e-05 loss: 0.0729 (0.0829) time: 28.4353 data: 25.0021 max mem: 33303 +Epoch: [32] [3890/4276] eta: 0:31:50 lr: 1.053658042944671e-05 loss: 0.0794 (0.0829) time: 40.3014 data: 36.5665 max mem: 33303 +Epoch: [32] [3900/4276] eta: 0:31:24 lr: 1.0533452455438217e-05 loss: 0.0876 (0.0829) time: 41.1279 data: 37.4009 max mem: 33303 +Epoch: [32] [3910/4276] eta: 0:30:54 lr: 1.0530324378218397e-05 loss: 0.0773 (0.0829) time: 28.2113 data: 24.7791 max mem: 33303 +Epoch: [32] [3920/4276] eta: 0:30:27 lr: 1.052719619774978e-05 loss: 0.0681 (0.0828) time: 28.7242 data: 25.1891 max mem: 33303 +Epoch: [32] [3930/4276] eta: 0:30:18 lr: 1.0524067913994865e-05 loss: 0.0727 (0.0828) time: 41.9998 data: 38.1094 max mem: 33303 +Epoch: [32] [3940/4276] eta: 0:29:45 lr: 1.0520939526916121e-05 loss: 0.0780 (0.0828) time: 40.6515 data: 36.8656 max mem: 33303 +Epoch: [32] [3950/4276] eta: 0:29:12 lr: 1.0517811036475998e-05 loss: 0.0697 (0.0828) time: 28.8474 data: 25.3436 max mem: 33303 +Epoch: [32] [3960/4276] eta: 0:28:36 lr: 1.051468244263692e-05 loss: 0.0702 (0.0828) time: 28.6106 data: 24.9910 max mem: 33303 +Epoch: [32] [3970/4276] eta: 0:28:18 lr: 1.0511553745361286e-05 loss: 0.0749 (0.0828) time: 40.4271 data: 36.5256 max mem: 33303 +Epoch: [32] [3980/4276] eta: 0:27:40 lr: 1.050842494461146e-05 loss: 0.0737 (0.0828) time: 41.0342 data: 37.2264 max mem: 33303 +Epoch: [32] [3990/4276] eta: 0:27:01 lr: 1.0505296040349787e-05 loss: 0.0697 (0.0828) time: 28.9490 data: 25.4384 max mem: 33303 +Epoch: [32] [4000/4276] eta: 0:26:19 lr: 1.0502167032538585e-05 loss: 0.0697 (0.0827) time: 28.5461 data: 24.9885 max mem: 33303 +Epoch: [32] [4010/4276] eta: 0:25:53 lr: 1.0499037921140151e-05 loss: 0.0772 (0.0828) time: 39.6831 data: 35.8415 max mem: 33303 +Epoch: [32] [4020/4276] eta: 0:25:09 lr: 1.0495908706116742e-05 loss: 0.0849 (0.0828) time: 40.1610 data: 36.3922 max mem: 33303 +Epoch: [32] [4030/4276] eta: 0:24:24 lr: 1.0492779387430598e-05 loss: 0.0809 (0.0827) time: 28.9585 data: 25.4129 max mem: 33303 +Epoch: [32] [4040/4276] eta: 0:23:38 lr: 1.0489649965043942e-05 loss: 0.0792 (0.0828) time: 29.2380 data: 25.6673 max mem: 33303 +Epoch: [32] [4050/4276] eta: 0:23:05 lr: 1.0486520438918944e-05 loss: 0.0787 (0.0828) time: 42.0404 data: 38.2103 max mem: 33303 +Epoch: [32] [4060/4276] eta: 0:22:15 lr: 1.0483390809017773e-05 loss: 0.0778 (0.0828) time: 40.9861 data: 37.1628 max mem: 33303 +Epoch: [32] [4070/4276] eta: 0:21:25 lr: 1.0480261075302562e-05 loss: 0.0872 (0.0828) time: 28.1877 data: 24.7401 max mem: 33303 +Epoch: [32] [4080/4276] eta: 0:20:34 lr: 1.0477131237735424e-05 loss: 0.0865 (0.0828) time: 29.4350 data: 25.9820 max mem: 33303 +Epoch: [32] [4090/4276] eta: 0:19:52 lr: 1.0474001296278428e-05 loss: 0.0765 (0.0828) time: 41.5018 data: 37.7305 max mem: 33303 +Epoch: [32] [4100/4276] eta: 0:18:57 lr: 1.0470871250893635e-05 loss: 0.0816 (0.0829) time: 40.5349 data: 36.7747 max mem: 33303 +Epoch: [32] [4110/4276] eta: 0:18:01 lr: 1.0467741101543072e-05 loss: 0.0805 (0.0828) time: 27.9231 data: 24.4707 max mem: 33303 +Epoch: [32] [4120/4276] eta: 0:17:04 lr: 1.0464610848188746e-05 loss: 0.0811 (0.0829) time: 27.8533 data: 24.4135 max mem: 33303 +Epoch: [32] [4130/4276] eta: 0:16:15 lr: 1.0461480490792621e-05 loss: 0.0753 (0.0828) time: 40.3034 data: 36.5728 max mem: 33303 +Epoch: [32] [4140/4276] eta: 0:15:15 lr: 1.0458350029316652e-05 loss: 0.0706 (0.0828) time: 40.9835 data: 37.2438 max mem: 33303 +Epoch: [32] [4150/4276] eta: 0:14:14 lr: 1.0455219463722759e-05 loss: 0.0732 (0.0828) time: 28.3766 data: 24.8062 max mem: 33303 +Epoch: [32] [4160/4276] eta: 0:13:13 lr: 1.0452088793972845e-05 loss: 0.0812 (0.0828) time: 28.2818 data: 24.7149 max mem: 33303 +Epoch: [32] [4170/4276] eta: 0:12:16 lr: 1.0448958020028764e-05 loss: 0.0873 (0.0828) time: 40.8825 data: 37.1729 max mem: 33303 +Epoch: [32] [4180/4276] eta: 0:11:12 lr: 1.0445827141852365e-05 loss: 0.0729 (0.0828) time: 40.8810 data: 37.0865 max mem: 33303 +Epoch: [32] [4190/4276] eta: 0:10:06 lr: 1.0442696159405466e-05 loss: 0.0744 (0.0828) time: 28.6628 data: 25.1524 max mem: 33303 +Epoch: [32] [4200/4276] eta: 0:08:59 lr: 1.0439565072649858e-05 loss: 0.0892 (0.0828) time: 28.2972 data: 24.8513 max mem: 33303 +Epoch: [32] [4210/4276] eta: 0:07:55 lr: 1.0436433881547293e-05 loss: 0.0856 (0.0829) time: 40.7430 data: 37.0055 max mem: 33303 +Epoch: [32] [4220/4276] eta: 0:06:46 lr: 1.043330258605951e-05 loss: 0.0891 (0.0829) time: 41.0736 data: 37.3511 max mem: 33303 +Epoch: [32] [4230/4276] eta: 0:05:36 lr: 1.0430171186148217e-05 loss: 0.0900 (0.0829) time: 28.1218 data: 24.6755 max mem: 33303 +Epoch: [32] [4240/4276] eta: 0:04:24 lr: 1.0427039681775105e-05 loss: 0.0873 (0.0829) time: 28.0412 data: 24.5811 max mem: 33303 +Epoch: [32] [4250/4276] eta: 0:03:14 lr: 1.0423908072901812e-05 loss: 0.0865 (0.0830) time: 40.6843 data: 36.9223 max mem: 33303 +Epoch: [32] [4260/4276] eta: 0:02:00 lr: 1.0420776359489976e-05 loss: 0.0865 (0.0830) time: 41.2194 data: 37.4587 max mem: 33303 +Epoch: [32] [4270/4276] eta: 0:00:45 lr: 1.0417644541501192e-05 loss: 0.0818 (0.0830) time: 28.8658 data: 25.4146 max mem: 33303 +Epoch: [32] Total time: 9:02:05 +Test: [ 0/21770] eta: 21 days, 12:15:10 time: 85.3702 data: 85.2991 max mem: 33303 +Test: [ 100/21770] eta: 16:19:01 time: 1.6439 data: 1.6074 max mem: 33303 +Test: [ 200/21770] eta: 14:41:46 time: 2.6530 data: 2.5411 max mem: 33303 +Test: [ 300/21770] eta: 13:56:57 time: 1.7601 data: 1.6778 max mem: 33303 +Test: [ 400/21770] eta: 13:32:25 time: 2.3405 data: 2.3023 max mem: 33303 +Test: [ 500/21770] eta: 13:18:32 time: 1.3401 data: 1.2999 max mem: 33303 +Test: [ 600/21770] eta: 13:08:21 time: 2.3098 data: 2.2725 max mem: 33303 +Test: [ 700/21770] eta: 12:51:08 time: 1.3578 data: 1.3216 max mem: 33303 +Test: [ 800/21770] eta: 12:50:31 time: 2.7036 data: 2.6639 max mem: 33303 +Test: [ 900/21770] eta: 12:39:01 time: 1.7043 data: 1.6316 max mem: 33303 +Test: [ 1000/21770] eta: 12:38:21 time: 2.5611 data: 2.4512 max mem: 33303 +Test: [ 1100/21770] eta: 12:28:34 time: 1.5621 data: 1.5063 max mem: 33303 +Test: [ 1200/21770] eta: 12:24:45 time: 2.4986 data: 2.4252 max mem: 33303 +Test: [ 1300/21770] eta: 12:16:53 time: 1.7037 data: 1.6335 max mem: 33303 +Test: [ 1400/21770] eta: 12:15:36 time: 1.8536 data: 1.8171 max mem: 33303 +Test: [ 1500/21770] eta: 12:07:05 time: 1.6502 data: 1.5976 max mem: 33303 +Test: [ 1600/21770] eta: 12:03:38 time: 2.1231 data: 2.0859 max mem: 33303 +Test: [ 1700/21770] eta: 11:59:18 time: 1.8699 data: 1.8278 max mem: 33303 +Test: [ 1800/21770] eta: 11:58:08 time: 3.0532 data: 3.0091 max mem: 33303 +Test: [ 1900/21770] eta: 11:51:48 time: 1.8725 data: 1.8326 max mem: 33303 +Test: [ 2000/21770] eta: 11:50:18 time: 2.6809 data: 2.5873 max mem: 33303 +Test: [ 2100/21770] eta: 11:44:40 time: 1.8137 data: 1.7043 max mem: 33303 +Test: [ 2200/21770] eta: 11:40:45 time: 2.5805 data: 2.4707 max mem: 33303 +Test: [ 2300/21770] eta: 11:36:07 time: 1.7695 data: 1.6590 max mem: 33303 +Test: [ 2400/21770] eta: 11:21:53 time: 1.3729 data: 1.3364 max mem: 33303 +Test: [ 2500/21770] eta: 10:57:31 time: 0.8081 data: 0.6804 max mem: 33303 +Test: [ 2600/21770] eta: 10:37:22 time: 0.8899 data: 0.7986 max mem: 33303 +Test: [ 2700/21770] eta: 10:18:01 time: 0.7917 data: 0.6828 max mem: 33303 +Test: [ 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time: 0.4692 data: 0.4325 max mem: 33303 +Test: [ 4200/21770] eta: 7:22:55 time: 0.3734 data: 0.3370 max mem: 33303 +Test: [ 4300/21770] eta: 7:15:12 time: 0.6483 data: 0.6119 max mem: 33303 +Test: [ 4400/21770] eta: 7:08:13 time: 0.7961 data: 0.7589 max mem: 33303 +Test: [ 4500/21770] eta: 7:01:20 time: 0.7449 data: 0.7082 max mem: 33303 +Test: [ 4600/21770] eta: 6:53:52 time: 0.4828 data: 0.4461 max mem: 33303 +Test: [ 4700/21770] eta: 6:46:46 time: 0.7492 data: 0.7125 max mem: 33303 +Test: [ 4800/21770] eta: 6:39:28 time: 0.3132 data: 0.2768 max mem: 33303 +Test: [ 4900/21770] eta: 6:33:02 time: 0.6623 data: 0.6260 max mem: 33303 +Test: [ 5000/21770] eta: 6:26:29 time: 0.0604 data: 0.0239 max mem: 33303 +Test: [ 5100/21770] eta: 6:20:32 time: 0.7039 data: 0.6676 max mem: 33303 +Test: [ 5200/21770] eta: 6:15:16 time: 0.7911 data: 0.7545 max mem: 33303 +Test: [ 5300/21770] eta: 6:10:22 time: 0.3493 data: 0.3129 max mem: 33303 +Test: [ 5400/21770] eta: 6:04:48 time: 0.3628 data: 0.3256 max mem: 33303 +Test: [ 5500/21770] eta: 6:00:09 time: 0.9205 data: 0.8843 max mem: 33303 +Test: [ 5600/21770] eta: 5:55:21 time: 0.7688 data: 0.6763 max mem: 33303 +Test: [ 5700/21770] eta: 5:50:16 time: 0.9072 data: 0.8533 max mem: 33303 +Test: [ 5800/21770] eta: 5:44:55 time: 0.8218 data: 0.7845 max mem: 33303 +Test: [ 5900/21770] eta: 5:40:18 time: 1.1742 data: 1.1371 max mem: 33303 +Test: [ 6000/21770] eta: 5:35:33 time: 0.6246 data: 0.5876 max mem: 33303 +Test: [ 6100/21770] eta: 5:31:13 time: 0.3879 data: 0.3509 max mem: 33303 +Test: [ 6200/21770] eta: 5:26:20 time: 0.6639 data: 0.6270 max mem: 33303 +Test: [ 6300/21770] eta: 5:22:01 time: 0.7345 data: 0.6983 max mem: 33303 +Test: [ 6400/21770] eta: 5:17:49 time: 0.7233 data: 0.6870 max mem: 33303 +Test: [ 6500/21770] eta: 5:13:25 time: 0.7645 data: 0.7280 max mem: 33303 +Test: [ 6600/21770] eta: 5:09:05 time: 0.7502 data: 0.7138 max mem: 33303 +Test: [ 6700/21770] eta: 5:05:02 time: 0.6553 data: 0.6191 max mem: 33303 +Test: [ 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time: 0.8539 data: 0.8174 max mem: 33303 +Test: [ 8200/21770] eta: 4:14:12 time: 0.7662 data: 0.7296 max mem: 33303 +Test: [ 8300/21770] eta: 4:11:57 time: 1.3704 data: 1.2609 max mem: 33303 +Test: [ 8400/21770] eta: 4:11:23 time: 2.0193 data: 1.9827 max mem: 33303 +Test: [ 8500/21770] eta: 4:10:14 time: 1.1573 data: 1.1204 max mem: 33303 +Test: [ 8600/21770] eta: 4:10:01 time: 1.7428 data: 1.7066 max mem: 33303 +Test: [ 8700/21770] eta: 4:09:06 time: 1.8650 data: 1.7946 max mem: 33303 +Test: [ 8800/21770] eta: 4:07:59 time: 1.7988 data: 1.7621 max mem: 33303 +Test: [ 8900/21770] eta: 4:07:04 time: 1.3195 data: 1.2831 max mem: 33303 +Test: [ 9000/21770] eta: 4:05:51 time: 1.2977 data: 1.2117 max mem: 33303 +Test: [ 9100/21770] eta: 4:04:50 time: 1.2311 data: 1.1948 max mem: 33303 +Test: [ 9200/21770] eta: 4:04:08 time: 1.3052 data: 1.2323 max mem: 33303 +Test: [ 9300/21770] eta: 4:03:03 time: 1.4293 data: 1.3926 max mem: 33303 +Test: [ 9400/21770] eta: 4:02:07 time: 1.3666 data: 1.3300 max mem: 33303 +Test: [ 9500/21770] eta: 4:01:16 time: 1.3119 data: 1.2756 max mem: 33303 +Test: [ 9600/21770] eta: 4:00:34 time: 1.6153 data: 1.5594 max mem: 33303 +Test: [ 9700/21770] eta: 4:00:30 time: 2.3909 data: 2.3528 max mem: 33303 +Test: [ 9800/21770] eta: 4:00:20 time: 1.5649 data: 1.5235 max mem: 33303 +Test: [ 9900/21770] eta: 3:59:32 time: 1.7203 data: 1.6831 max mem: 33303 +Test: [10000/21770] eta: 3:59:07 time: 2.3751 data: 2.2839 max mem: 33303 +Test: [10100/21770] eta: 3:58:13 time: 1.5343 data: 1.4977 max mem: 33303 +Test: [10200/21770] eta: 3:57:40 time: 1.4240 data: 1.3872 max mem: 33303 +Test: [10300/21770] eta: 3:57:00 time: 1.3754 data: 1.3387 max mem: 33303 +Test: [10400/21770] eta: 3:55:31 time: 1.3491 data: 1.2936 max mem: 33303 +Test: [10500/21770] eta: 3:53:54 time: 2.3991 data: 2.3417 max mem: 33303 +Test: [10600/21770] eta: 3:53:17 time: 1.7986 data: 1.6716 max mem: 33303 +Test: [10700/21770] eta: 3:53:00 time: 2.7143 data: 2.6154 max mem: 33303 +Test: 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3:39:53 time: 2.3714 data: 2.2843 max mem: 33303 +Test: [12200/21770] eta: 3:38:31 time: 1.5436 data: 1.4618 max mem: 33303 +Test: [12300/21770] eta: 3:37:13 time: 2.4665 data: 2.3628 max mem: 33303 +Test: [12400/21770] eta: 3:35:48 time: 1.8642 data: 1.7649 max mem: 33303 +Test: [12500/21770] eta: 3:34:41 time: 3.6349 data: 3.5928 max mem: 33303 +Test: [12600/21770] eta: 3:32:57 time: 1.5701 data: 1.5336 max mem: 33303 +Test: [12700/21770] eta: 3:31:31 time: 2.4395 data: 2.3889 max mem: 33303 +Test: [12800/21770] eta: 3:30:06 time: 1.9181 data: 1.8261 max mem: 33303 +Test: [12900/21770] eta: 3:28:35 time: 2.5816 data: 2.5160 max mem: 33303 +Test: [13000/21770] eta: 3:27:04 time: 1.7956 data: 1.6872 max mem: 33303 +Test: [13100/21770] eta: 3:25:04 time: 1.2308 data: 1.1401 max mem: 33303 +Test: [13200/21770] eta: 3:22:55 time: 2.0750 data: 1.9875 max mem: 33303 +Test: [13300/21770] eta: 3:20:36 time: 1.7524 data: 1.7161 max mem: 33303 +Test: [13400/21770] eta: 3:18:20 time: 1.1003 data: 1.0280 max mem: 33303 +Test: [13500/21770] eta: 3:15:58 time: 1.0714 data: 1.0344 max mem: 33303 +Test: [13600/21770] eta: 3:13:25 time: 1.2095 data: 1.1730 max mem: 33303 +Test: [13700/21770] eta: 3:10:53 time: 0.6528 data: 0.6162 max mem: 33303 +Test: [13800/21770] eta: 3:08:43 time: 1.4102 data: 1.3370 max mem: 33303 +Test: [13900/21770] eta: 3:06:45 time: 1.4361 data: 1.3995 max mem: 33303 +Test: [14000/21770] eta: 3:04:20 time: 1.1511 data: 1.1149 max mem: 33303 +Test: [14100/21770] eta: 3:01:52 time: 1.8890 data: 1.8348 max mem: 33303 +Test: [14200/21770] eta: 2:59:29 time: 1.2949 data: 1.2584 max mem: 33303 +Test: [14300/21770] eta: 2:57:05 time: 1.1400 data: 1.1035 max mem: 33303 +Test: [14400/21770] eta: 2:54:41 time: 1.4047 data: 1.3683 max mem: 33303 +Test: [14500/21770] eta: 2:52:14 time: 2.1118 data: 2.0726 max mem: 33303 +Test: [14600/21770] eta: 2:49:27 time: 0.9492 data: 0.8604 max mem: 33303 +Test: [14700/21770] eta: 2:46:39 time: 0.8767 data: 0.8405 max mem: 33303 +Test: [14800/21770] eta: 2:44:06 time: 1.3647 data: 1.3104 max mem: 33303 +Test: [14900/21770] eta: 2:41:30 time: 0.9806 data: 0.9441 max mem: 33303 +Test: [15000/21770] eta: 2:38:55 time: 1.0676 data: 1.0308 max mem: 33303 +Test: [15100/21770] eta: 2:36:23 time: 1.2044 data: 1.1680 max mem: 33303 +Test: [15200/21770] eta: 2:33:55 time: 1.2117 data: 1.1753 max mem: 33303 +Test: [15300/21770] eta: 2:31:30 time: 0.9867 data: 0.9505 max mem: 33303 +Test: [15400/21770] eta: 2:29:04 time: 1.5350 data: 1.4985 max mem: 33303 +Test: [15500/21770] eta: 2:26:34 time: 1.1191 data: 1.0468 max mem: 33303 +Test: [15600/21770] eta: 2:24:07 time: 1.6153 data: 1.5783 max mem: 33303 +Test: [15700/21770] eta: 2:21:36 time: 1.1371 data: 1.1008 max mem: 33303 +Test: [15800/21770] eta: 2:19:13 time: 1.2595 data: 1.2231 max mem: 33303 +Test: [15900/21770] eta: 2:16:51 time: 0.9571 data: 0.9209 max mem: 33303 +Test: [16000/21770] eta: 2:14:33 time: 1.5876 data: 1.5512 max mem: 33303 +Test: [16100/21770] eta: 2:12:12 time: 1.2896 data: 1.1999 max mem: 33303 +Test: [16200/21770] eta: 2:09:51 time: 1.5374 data: 1.4468 max mem: 33303 +Test: [16300/21770] eta: 2:07:48 time: 2.3510 data: 2.2964 max mem: 33303 +Test: [16400/21770] eta: 2:05:44 time: 1.5959 data: 1.5586 max mem: 33303 +Test: [16500/21770] eta: 2:03:42 time: 2.2195 data: 2.1461 max mem: 33303 +Test: [16600/21770] eta: 2:01:37 time: 1.3952 data: 1.3589 max mem: 33303 +Test: [16700/21770] eta: 1:59:39 time: 2.6105 data: 2.5708 max mem: 33303 +Test: [16800/21770] eta: 1:57:37 time: 2.8817 data: 2.8424 max mem: 33303 +Test: [16900/21770] eta: 1:55:30 time: 1.5693 data: 1.5321 max mem: 33303 +Test: [17000/21770] eta: 1:53:28 time: 2.4144 data: 2.3769 max mem: 33303 +Test: [17100/21770] eta: 1:51:17 time: 1.5134 data: 1.4624 max mem: 33303 +Test: [17200/21770] eta: 1:49:13 time: 2.3087 data: 2.2712 max mem: 33303 +Test: [17300/21770] eta: 1:47:01 time: 1.4816 data: 1.4453 max mem: 33303 +Test: [17400/21770] eta: 1:44:55 time: 2.8198 data: 2.7441 max mem: 33303 +Test: [17500/21770] eta: 1:42:42 time: 1.4000 data: 1.3632 max mem: 33303 +Test: [17600/21770] eta: 1:40:34 time: 1.7068 data: 1.6693 max mem: 33303 +Test: [17700/21770] eta: 1:38:24 time: 2.8321 data: 2.7382 max mem: 33303 +Test: [17800/21770] eta: 1:36:09 time: 2.2525 data: 2.2150 max mem: 33303 +Test: [17900/21770] eta: 1:33:58 time: 1.6429 data: 1.5304 max mem: 33303 +Test: [18000/21770] eta: 1:31:49 time: 3.5906 data: 3.5313 max mem: 33303 +Test: [18100/21770] eta: 1:29:30 time: 1.6074 data: 1.5702 max mem: 33303 +Test: [18200/21770] eta: 1:27:16 time: 2.2963 data: 2.2539 max mem: 33303 +Test: [18300/21770] eta: 1:24:59 time: 1.6512 data: 1.6139 max mem: 33303 +Test: [18400/21770] eta: 1:22:43 time: 2.2448 data: 2.2082 max mem: 33303 +Test: [18500/21770] eta: 1:20:25 time: 2.1964 data: 2.1595 max mem: 33303 +Test: [18600/21770] eta: 1:18:06 time: 1.8197 data: 1.7826 max mem: 33303 +Test: [18700/21770] eta: 1:15:49 time: 2.6936 data: 2.6537 max mem: 33303 +Test: [18800/21770] eta: 1:13:29 time: 1.5673 data: 1.5301 max mem: 33303 +Test: [18900/21770] eta: 1:11:10 time: 2.1619 data: 2.1253 max mem: 33303 +Test: [19000/21770] eta: 1:08:48 time: 2.3811 data: 2.3441 max mem: 33303 +Test: [19100/21770] eta: 1:06:24 time: 2.4113 data: 2.3730 max mem: 33303 +Test: [19200/21770] eta: 1:04:03 time: 1.5340 data: 1.4967 max mem: 33303 +Test: [19300/21770] eta: 1:01:41 time: 2.3534 data: 2.3167 max mem: 33303 +Test: [19400/21770] eta: 0:59:17 time: 1.6554 data: 1.6185 max mem: 33303 +Test: [19500/21770] eta: 0:56:55 time: 2.4024 data: 2.3483 max mem: 33303 +Test: [19600/21770] eta: 0:54:30 time: 2.4010 data: 2.3261 max mem: 33303 +Test: [19700/21770] eta: 0:52:03 time: 1.6258 data: 1.5516 max mem: 33303 +Test: [19800/21770] eta: 0:49:40 time: 2.3147 data: 2.2594 max mem: 33303 +Test: [19900/21770] eta: 0:47:13 time: 1.7295 data: 1.6359 max mem: 33303 +Test: [20000/21770] eta: 0:44:46 time: 2.4153 data: 2.3416 max mem: 33303 +Test: [20100/21770] eta: 0:42:19 time: 1.6770 data: 1.6397 max mem: 33303 +Test: [20200/21770] eta: 0:39:52 time: 2.4333 data: 2.3054 max mem: 33303 +Test: [20300/21770] eta: 0:37:23 time: 1.6281 data: 1.5605 max mem: 33303 +Test: [20400/21770] eta: 0:34:54 time: 2.1323 data: 2.0956 max mem: 33303 +Test: [20500/21770] eta: 0:32:25 time: 1.5226 data: 1.4860 max mem: 33303 +Test: [20600/21770] eta: 0:29:55 time: 2.6251 data: 2.5127 max mem: 33303 +Test: [20700/21770] eta: 0:27:25 time: 1.5586 data: 1.5215 max mem: 33303 +Test: [20800/21770] eta: 0:24:53 time: 2.2196 data: 2.1671 max mem: 33303 +Test: [20900/21770] eta: 0:22:21 time: 2.9420 data: 2.8507 max mem: 33303 +Test: [21000/21770] eta: 0:19:46 time: 1.1398 data: 1.0856 max mem: 33303 +Test: [21100/21770] eta: 0:17:12 time: 1.6279 data: 1.5904 max mem: 33303 +Test: [21200/21770] eta: 0:14:38 time: 1.8079 data: 1.7716 max mem: 33303 +Test: [21300/21770] eta: 0:12:04 time: 2.3175 data: 2.2807 max mem: 33303 +Test: [21400/21770] eta: 0:09:30 time: 1.1380 data: 1.0722 max mem: 33303 +Test: [21500/21770] eta: 0:06:56 time: 1.4121 data: 1.3758 max mem: 33303 +Test: [21600/21770] eta: 0:04:21 time: 1.7925 data: 1.7557 max mem: 33303 +Test: [21700/21770] eta: 0:01:47 time: 1.4611 data: 1.4071 max mem: 33303 +Test: Total time: 9:19:37 +Final results: +Mean IoU is 0.00 + + precision@0.5 = 0.00 + precision@0.6 = 0.00 + precision@0.7 = 0.00 + precision@0.8 = 0.00 + precision@0.9 = 0.00 + overall IoU = 0.00 + mean IoU = 0.00 + +Mean accuracy for one-to-zero sample is 37.60 + +Average object IoU 4.5207339821769405e-06 +Overall IoU 0.0004990559536963701 +Epoch: [33] [ 0/4276] eta: 16 days, 2:38:51 lr: 1.0415765400495008e-05 loss: 0.0901 (0.0901) time: 325.5219 data: 316.8533 max mem: 33303 +Epoch: [33] [ 10/4276] eta: 2 days, 17:57:30 lr: 1.0412633415103181e-05 loss: 0.0823 (0.0804) time: 55.6612 data: 51.7041 max mem: 33303 +Epoch: [33] [ 20/4276] eta: 2 days, 2:20:40 lr: 1.0409501325034442e-05 loss: 0.0805 (0.0789) time: 28.4378 data: 24.9456 max mem: 33303 +Epoch: [33] [ 30/4276] eta: 1 day, 21:11:04 lr: 1.0406369130250295e-05 loss: 0.0832 (0.0808) time: 28.7670 data: 25.2706 max mem: 33303 +Epoch: [33] [ 40/4276] eta: 2 days, 1:18:08 lr: 1.040323683071222e-05 loss: 0.0822 (0.0804) time: 41.1813 data: 37.4012 max mem: 33303 +Epoch: [33] [ 50/4276] eta: 1 day, 22:15:25 lr: 1.0400104426381674e-05 loss: 0.0757 (0.0798) time: 41.1021 data: 37.3331 max mem: 33303 +Epoch: [33] [ 60/4276] eta: 1 day, 19:52:24 lr: 1.0396971917220064e-05 loss: 0.0694 (0.0793) time: 28.3675 data: 24.9104 max mem: 33303 +Epoch: [33] [ 70/4276] eta: 1 day, 18:22:56 lr: 1.0393839303188791e-05 loss: 0.0667 (0.0778) time: 28.2968 data: 24.8457 max mem: 33303 +Epoch: [33] [ 80/4276] eta: 1 day, 20:49:28 lr: 1.0390706584249227e-05 loss: 0.0696 (0.0784) time: 41.4910 data: 37.7564 max mem: 33303 +Epoch: [33] [ 90/4276] eta: 1 day, 19:20:25 lr: 1.0387573760362716e-05 loss: 0.0818 (0.0795) time: 40.8133 data: 37.0782 max mem: 33303 +Epoch: [33] [ 100/4276] eta: 1 day, 18:19:27 lr: 1.038444083149056e-05 loss: 0.0771 (0.0800) time: 28.5028 data: 25.0416 max mem: 33303 +Epoch: [33] [ 110/4276] eta: 1 day, 17:21:23 lr: 1.0381307797594052e-05 loss: 0.0851 (0.0813) time: 28.7514 data: 25.3003 max mem: 33303 +Epoch: [33] [ 120/4276] eta: 1 day, 18:50:17 lr: 1.0378174658634457e-05 loss: 0.0851 (0.0811) time: 40.2414 data: 36.4406 max mem: 33303 +Epoch: [33] [ 130/4276] eta: 1 day, 17:56:12 lr: 1.0375041414572995e-05 loss: 0.0803 (0.0823) time: 40.1671 data: 36.2988 max mem: 33303 +Epoch: [33] [ 140/4276] eta: 1 day, 17:12:31 lr: 1.0371908065370877e-05 loss: 0.0757 (0.0817) time: 28.3745 data: 24.8615 max mem: 33303 +Epoch: [33] [ 150/4276] eta: 1 day, 16:27:29 lr: 1.0368774610989282e-05 loss: 0.0715 (0.0816) time: 28.0067 data: 24.5493 max mem: 33303 +Epoch: [33] [ 160/4276] eta: 1 day, 17:40:50 lr: 1.0365641051389362e-05 loss: 0.0793 (0.0817) time: 40.5944 data: 36.7703 max mem: 33303 +Epoch: [33] [ 170/4276] eta: 1 day, 17:05:25 lr: 1.036250738653223e-05 loss: 0.0765 (0.0815) time: 41.5110 data: 37.6764 max mem: 33303 +Epoch: [33] [ 180/4276] eta: 1 day, 16:28:23 lr: 1.0359373616378988e-05 loss: 0.0768 (0.0816) time: 28.4612 data: 24.9865 max mem: 33303 +Epoch: [33] [ 190/4276] eta: 1 day, 16:04:23 lr: 1.03562397408907e-05 loss: 0.0761 (0.0815) time: 29.1503 data: 25.6582 max mem: 33303 +Epoch: [33] [ 200/4276] eta: 1 day, 17:02:55 lr: 1.0353105760028418e-05 loss: 0.0704 (0.0815) time: 42.4340 data: 38.5715 max mem: 33303 +Epoch: [33] [ 210/4276] eta: 1 day, 16:27:22 lr: 1.0349971673753137e-05 loss: 0.0724 (0.0812) time: 40.7166 data: 36.8822 max mem: 33303 +Epoch: [33] [ 220/4276] eta: 1 day, 16:00:39 lr: 1.0346837482025849e-05 loss: 0.0713 (0.0811) time: 28.0541 data: 24.5927 max mem: 33303 +Epoch: [33] [ 230/4276] eta: 1 day, 15:37:39 lr: 1.0343703184807516e-05 loss: 0.0674 (0.0806) time: 29.3490 data: 25.8152 max mem: 33303 +Epoch: [33] [ 240/4276] eta: 1 day, 16:20:44 lr: 1.0340568782059067e-05 loss: 0.0712 (0.0804) time: 41.2311 data: 37.3136 max mem: 33303 +Epoch: [33] [ 250/4276] eta: 1 day, 15:53:36 lr: 1.0337434273741399e-05 loss: 0.0811 (0.0812) time: 40.4429 data: 36.5593 max mem: 33303 +Epoch: [33] [ 260/4276] eta: 1 day, 15:33:34 lr: 1.0334299659815387e-05 loss: 0.0833 (0.0815) time: 29.1296 data: 25.5182 max mem: 33303 +Epoch: [33] [ 270/4276] eta: 1 day, 15:06:27 lr: 1.0331164940241881e-05 loss: 0.0752 (0.0813) time: 28.5169 data: 24.9487 max mem: 33303 +Epoch: [33] [ 280/4276] eta: 1 day, 15:43:37 lr: 1.0328030114981708e-05 loss: 0.0677 (0.0813) time: 40.0763 data: 36.3448 max mem: 33303 +Epoch: [33] [ 290/4276] eta: 1 day, 15:22:47 lr: 1.0324895183995644e-05 loss: 0.0771 (0.0810) time: 41.2850 data: 37.5626 max mem: 33303 +Epoch: [33] [ 300/4276] eta: 1 day, 15:01:34 lr: 1.0321760147244457e-05 loss: 0.0791 (0.0812) time: 28.9478 data: 25.5000 max mem: 33303 +Epoch: [33] [ 310/4276] eta: 1 day, 14:42:44 lr: 1.0318625004688888e-05 loss: 0.0744 (0.0807) time: 28.9356 data: 25.3789 max mem: 33303 +Epoch: [33] [ 320/4276] eta: 1 day, 15:11:02 lr: 1.0315489756289648e-05 loss: 0.0735 (0.0810) time: 40.5057 data: 36.6092 max mem: 33303 +Epoch: [33] [ 330/4276] eta: 1 day, 14:49:45 lr: 1.0312354402007406e-05 loss: 0.0772 (0.0809) time: 39.8504 data: 36.0639 max mem: 33303 +Epoch: [33] [ 340/4276] eta: 1 day, 14:30:54 lr: 1.030921894180282e-05 loss: 0.0762 (0.0809) time: 28.3168 data: 24.8765 max mem: 33303 +Epoch: [33] [ 350/4276] eta: 1 day, 14:10:19 lr: 1.0306083375636515e-05 loss: 0.0741 (0.0809) time: 28.0165 data: 24.5738 max mem: 33303 +Epoch: [33] [ 360/4276] eta: 1 day, 14:36:33 lr: 1.030294770346909e-05 loss: 0.0810 (0.0812) time: 40.0385 data: 36.2948 max mem: 33303 +Epoch: [33] [ 370/4276] eta: 1 day, 14:17:33 lr: 1.0299811925261106e-05 loss: 0.0858 (0.0813) time: 40.3859 data: 36.6402 max mem: 33303 +Epoch: [33] [ 380/4276] eta: 1 day, 13:59:47 lr: 1.0296676040973108e-05 loss: 0.0809 (0.0815) time: 28.1758 data: 24.7061 max mem: 33303 +Epoch: [33] [ 390/4276] eta: 1 day, 13:45:54 lr: 1.0293540050565607e-05 loss: 0.0896 (0.0818) time: 29.2933 data: 25.8171 max mem: 33303 +Epoch: [33] [ 400/4276] eta: 1 day, 14:10:00 lr: 1.0290403953999094e-05 loss: 0.0907 (0.0819) time: 41.9156 data: 38.1766 max mem: 33303 +Epoch: [33] [ 410/4276] eta: 1 day, 13:53:49 lr: 1.0287267751234013e-05 loss: 0.0883 (0.0821) time: 41.2294 data: 37.4996 max mem: 33303 +Epoch: [33] [ 420/4276] eta: 1 day, 13:35:28 lr: 1.02841314422308e-05 loss: 0.0791 (0.0821) time: 28.0059 data: 24.5602 max mem: 33303 +Epoch: [33] [ 430/4276] eta: 1 day, 13:22:04 lr: 1.0280995026949856e-05 loss: 0.0773 (0.0821) time: 28.5676 data: 25.1160 max mem: 33303 +Epoch: [33] [ 440/4276] eta: 1 day, 13:44:06 lr: 1.0277858505351546e-05 loss: 0.0765 (0.0820) time: 42.1097 data: 38.2708 max mem: 33303 +Epoch: [33] [ 450/4276] eta: 1 day, 13:28:09 lr: 1.0274721877396216e-05 loss: 0.0765 (0.0819) time: 41.2535 data: 37.2921 max mem: 33303 +Epoch: [33] [ 460/4276] eta: 1 day, 13:13:30 lr: 1.0271585143044184e-05 loss: 0.0723 (0.0817) time: 28.6000 data: 24.9898 max mem: 33303 +Epoch: [33] [ 470/4276] eta: 1 day, 13:00:20 lr: 1.026844830225574e-05 loss: 0.0719 (0.0817) time: 29.2948 data: 25.7569 max mem: 33303 +Epoch: [33] [ 480/4276] eta: 1 day, 13:17:29 lr: 1.0265311354991134e-05 loss: 0.0778 (0.0817) time: 41.0862 data: 37.2268 max mem: 33303 +Epoch: [33] [ 490/4276] eta: 1 day, 13:01:56 lr: 1.0262174301210598e-05 loss: 0.0741 (0.0815) time: 40.1633 data: 36.2710 max mem: 33303 +Epoch: [33] [ 500/4276] eta: 1 day, 12:48:45 lr: 1.0259037140874336e-05 loss: 0.0728 (0.0813) time: 28.6209 data: 24.9677 max mem: 33303 +Epoch: [33] [ 510/4276] eta: 1 day, 12:33:02 lr: 1.025589987394253e-05 loss: 0.0733 (0.0813) time: 28.2243 data: 24.5427 max mem: 33303 +Epoch: [33] [ 520/4276] eta: 1 day, 12:48:22 lr: 1.025276250037531e-05 loss: 0.0778 (0.0814) time: 39.8043 data: 35.8959 max mem: 33303 +Epoch: [33] [ 530/4276] eta: 1 day, 12:35:12 lr: 1.02496250201328e-05 loss: 0.0773 (0.0814) time: 40.8143 data: 37.0232 max mem: 33303 +Epoch: [33] [ 540/4276] eta: 1 day, 12:22:14 lr: 1.0246487433175087e-05 loss: 0.0822 (0.0815) time: 29.0363 data: 25.5970 max mem: 33303 +Epoch: [33] [ 550/4276] eta: 1 day, 12:09:21 lr: 1.0243349739462236e-05 loss: 0.0827 (0.0818) time: 28.8934 data: 25.2892 max mem: 33303 +Epoch: [33] [ 560/4276] eta: 1 day, 12:23:57 lr: 1.024021193895427e-05 loss: 0.0841 (0.0818) time: 41.1117 data: 37.1252 max mem: 33303 +Epoch: [33] [ 570/4276] eta: 1 day, 12:10:23 lr: 1.0237074031611193e-05 loss: 0.0783 (0.0817) time: 40.7913 data: 36.9627 max mem: 33303 +Epoch: [33] [ 580/4276] eta: 1 day, 11:58:28 lr: 1.0233936017392982e-05 loss: 0.0763 (0.0819) time: 28.7882 data: 25.3336 max mem: 33303 +Epoch: [33] [ 590/4276] eta: 1 day, 11:46:38 lr: 1.0230797896259585e-05 loss: 0.0771 (0.0818) time: 29.3537 data: 25.8794 max mem: 33303 +Epoch: [33] [ 600/4276] eta: 1 day, 11:59:31 lr: 1.0227659668170912e-05 loss: 0.0734 (0.0817) time: 41.2840 data: 37.4753 max mem: 33303 +Epoch: [33] [ 610/4276] eta: 1 day, 11:48:13 lr: 1.0224521333086853e-05 loss: 0.0781 (0.0818) time: 41.5573 data: 37.7250 max mem: 33303 +Epoch: [33] [ 620/4276] eta: 1 day, 11:35:45 lr: 1.0221382890967265e-05 loss: 0.0772 (0.0819) time: 29.1207 data: 25.6060 max mem: 33303 +Epoch: [33] [ 630/4276] eta: 1 day, 11:23:48 lr: 1.0218244341771989e-05 loss: 0.0830 (0.0822) time: 28.5657 data: 25.0847 max mem: 33303 +Epoch: [33] [ 640/4276] eta: 1 day, 11:33:49 lr: 1.0215105685460813e-05 loss: 0.0853 (0.0822) time: 40.2143 data: 36.4722 max mem: 33303 +Epoch: [33] [ 650/4276] eta: 1 day, 11:22:47 lr: 1.0211966921993515e-05 loss: 0.0700 (0.0822) time: 40.6727 data: 36.8611 max mem: 33303 +Epoch: [33] [ 660/4276] eta: 1 day, 11:10:34 lr: 1.020882805132984e-05 loss: 0.0821 (0.0824) time: 28.8944 data: 25.3424 max mem: 33303 +Epoch: [33] [ 670/4276] eta: 1 day, 10:59:38 lr: 1.0205689073429508e-05 loss: 0.0828 (0.0824) time: 28.7460 data: 25.2700 max mem: 33303 +Epoch: [33] [ 680/4276] eta: 1 day, 11:09:39 lr: 1.0202549988252195e-05 loss: 0.0726 (0.0823) time: 41.1294 data: 37.3844 max mem: 33303 +Epoch: [33] [ 690/4276] eta: 1 day, 11:00:07 lr: 1.019941079575756e-05 loss: 0.0751 (0.0822) time: 41.9453 data: 38.0634 max mem: 33303 +Epoch: [33] [ 700/4276] eta: 1 day, 10:50:18 lr: 1.0196271495905237e-05 loss: 0.0739 (0.0822) time: 30.7208 data: 27.1337 max mem: 33303 +Epoch: [33] [ 710/4276] eta: 1 day, 10:39:43 lr: 1.0193132088654827e-05 loss: 0.0739 (0.0822) time: 29.9464 data: 26.5041 max mem: 33303 +Epoch: [33] [ 720/4276] eta: 1 day, 10:51:45 lr: 1.018999257396589e-05 loss: 0.0744 (0.0821) time: 43.0641 data: 39.3248 max mem: 33303 +Epoch: [33] [ 730/4276] eta: 1 day, 10:41:36 lr: 1.0186852951797973e-05 loss: 0.0689 (0.0820) time: 43.3640 data: 39.5395 max mem: 33303 +Epoch: [33] [ 740/4276] eta: 1 day, 10:31:27 lr: 1.0183713222110595e-05 loss: 0.0742 (0.0819) time: 29.9332 data: 26.3888 max mem: 33303 +Epoch: [33] [ 750/4276] eta: 1 day, 10:22:45 lr: 1.0180573384863223e-05 loss: 0.0707 (0.0818) time: 30.6777 data: 27.1576 max mem: 33303 +Epoch: [33] [ 760/4276] eta: 1 day, 10:32:56 lr: 1.017743344001532e-05 loss: 0.0705 (0.0817) time: 43.7155 data: 39.9157 max mem: 33303 +Epoch: [33] [ 770/4276] eta: 1 day, 10:24:09 lr: 1.017429338752631e-05 loss: 0.0740 (0.0818) time: 43.7464 data: 39.9170 max mem: 33303 +Epoch: [33] [ 780/4276] eta: 1 day, 10:13:09 lr: 1.0171153227355596e-05 loss: 0.0831 (0.0818) time: 30.0180 data: 26.4633 max mem: 33303 +Epoch: [33] [ 790/4276] eta: 1 day, 10:02:24 lr: 1.016801295946253e-05 loss: 0.0886 (0.0819) time: 28.5410 data: 25.0645 max mem: 33303 +Epoch: [33] [ 800/4276] eta: 1 day, 10:07:56 lr: 1.0164872583806454e-05 loss: 0.0879 (0.0819) time: 39.7564 data: 35.9311 max mem: 33303 +Epoch: [33] [ 810/4276] eta: 1 day, 9:58:08 lr: 1.0161732100346677e-05 loss: 0.0879 (0.0821) time: 40.3739 data: 36.5400 max mem: 33303 +Epoch: [33] [ 820/4276] eta: 1 day, 9:47:42 lr: 1.0158591509042483e-05 loss: 0.0745 (0.0820) time: 29.3230 data: 25.8372 max mem: 33303 +Epoch: [33] [ 830/4276] eta: 1 day, 9:36:57 lr: 1.015545080985311e-05 loss: 0.0686 (0.0820) time: 28.4672 data: 24.9124 max mem: 33303 +Epoch: [33] [ 840/4276] eta: 1 day, 9:42:38 lr: 1.015231000273778e-05 loss: 0.0756 (0.0820) time: 40.1085 data: 36.2601 max mem: 33303 +Epoch: [33] [ 850/4276] eta: 1 day, 9:31:57 lr: 1.0149169087655685e-05 loss: 0.0775 (0.0819) time: 40.1141 data: 36.3303 max mem: 33303 +Epoch: [33] [ 860/4276] eta: 1 day, 9:22:18 lr: 1.0146028064565993e-05 loss: 0.0799 (0.0821) time: 28.8402 data: 25.2901 max mem: 33303 +Epoch: [33] [ 870/4276] eta: 1 day, 9:11:49 lr: 1.014288693342782e-05 loss: 0.0758 (0.0820) time: 28.8094 data: 25.2761 max mem: 33303 +Epoch: [33] [ 880/4276] eta: 1 day, 9:16:48 lr: 1.0139745694200275e-05 loss: 0.0809 (0.0822) time: 40.0160 data: 36.2320 max mem: 33303 +Epoch: [33] [ 890/4276] eta: 1 day, 9:06:46 lr: 1.013660434684243e-05 loss: 0.0934 (0.0823) time: 40.3245 data: 36.5367 max mem: 33303 +Epoch: [33] [ 900/4276] eta: 1 day, 8:58:03 lr: 1.0133462891313333e-05 loss: 0.0851 (0.0824) time: 29.6837 data: 26.1112 max mem: 33303 +Epoch: [33] [ 910/4276] eta: 1 day, 8:48:01 lr: 1.0130321327571984e-05 loss: 0.0797 (0.0824) time: 29.5204 data: 25.9603 max mem: 33303 +Epoch: [33] [ 920/4276] eta: 1 day, 8:53:56 lr: 1.0127179655577371e-05 loss: 0.0805 (0.0826) time: 41.4071 data: 37.5818 max mem: 33303 +Epoch: [33] [ 930/4276] eta: 1 day, 8:43:49 lr: 1.0124037875288451e-05 loss: 0.0817 (0.0826) time: 41.3283 data: 37.4361 max mem: 33303 +Epoch: [33] [ 940/4276] eta: 1 day, 8:34:39 lr: 1.012089598666415e-05 loss: 0.0793 (0.0826) time: 28.9288 data: 25.3483 max mem: 33303 +Epoch: [33] [ 950/4276] eta: 1 day, 8:24:39 lr: 1.0117753989663351e-05 loss: 0.0840 (0.0827) time: 28.8523 data: 25.2819 max mem: 33303 +Epoch: [33] [ 960/4276] eta: 1 day, 8:29:55 lr: 1.0114611884244926e-05 loss: 0.0840 (0.0826) time: 41.2345 data: 37.3421 max mem: 33303 +Epoch: [33] [ 970/4276] eta: 1 day, 8:19:41 lr: 1.0111469670367705e-05 loss: 0.0779 (0.0826) time: 40.9944 data: 37.1473 max mem: 33303 +Epoch: [33] [ 980/4276] eta: 1 day, 8:10:22 lr: 1.0108327347990501e-05 loss: 0.0792 (0.0827) time: 28.3198 data: 24.8656 max mem: 33303 +Epoch: [33] [ 990/4276] eta: 1 day, 8:00:47 lr: 1.0105184917072078e-05 loss: 0.0829 (0.0826) time: 28.7245 data: 25.2769 max mem: 33303 +Epoch: [33] [1000/4276] eta: 1 day, 8:04:28 lr: 1.0102042377571181e-05 loss: 0.0791 (0.0826) time: 40.4726 data: 36.7427 max mem: 33303 +Epoch: [33] [1010/4276] eta: 1 day, 7:55:10 lr: 1.0098899729446537e-05 loss: 0.0791 (0.0826) time: 40.7089 data: 36.9707 max mem: 33303 +Epoch: [33] [1020/4276] eta: 1 day, 7:46:01 lr: 1.0095756972656816e-05 loss: 0.0769 (0.0826) time: 28.9400 data: 25.4463 max mem: 33303 +Epoch: [33] [1030/4276] eta: 1 day, 7:36:57 lr: 1.0092614107160678e-05 loss: 0.0883 (0.0827) time: 29.0023 data: 25.4985 max mem: 33303 +Epoch: [33] [1040/4276] eta: 1 day, 7:39:50 lr: 1.0089471132916747e-05 loss: 0.0839 (0.0827) time: 40.4556 data: 36.6602 max mem: 33303 +Epoch: [33] [1050/4276] eta: 1 day, 7:30:21 lr: 1.0086328049883626e-05 loss: 0.0807 (0.0827) time: 40.0409 data: 36.2469 max mem: 33303 +Epoch: [33] [1060/4276] eta: 1 day, 7:22:04 lr: 1.0083184858019864e-05 loss: 0.0862 (0.0829) time: 29.2661 data: 25.6973 max mem: 33303 +Epoch: [33] [1070/4276] eta: 1 day, 7:12:46 lr: 1.0080041557284005e-05 loss: 0.0871 (0.0829) time: 29.2823 data: 25.6736 max mem: 33303 +Epoch: [33] [1080/4276] eta: 1 day, 7:16:16 lr: 1.007689814763455e-05 loss: 0.0871 (0.0829) time: 41.1108 data: 37.3127 max mem: 33303 +Epoch: [33] [1090/4276] eta: 1 day, 7:07:07 lr: 1.0073754629029981e-05 loss: 0.0989 (0.0831) time: 41.2396 data: 37.4775 max mem: 33303 +Epoch: [33] [1100/4276] eta: 1 day, 6:58:36 lr: 1.007061100142873e-05 loss: 0.0833 (0.0832) time: 29.0572 data: 25.4944 max mem: 33303 +Epoch: [33] [1110/4276] eta: 1 day, 6:49:50 lr: 1.006746726478921e-05 loss: 0.0814 (0.0834) time: 29.3207 data: 25.7450 max mem: 33303 +Epoch: [33] [1120/4276] eta: 1 day, 6:52:19 lr: 1.0064323419069814e-05 loss: 0.0908 (0.0835) time: 40.8890 data: 37.0445 max mem: 33303 +Epoch: [33] [1130/4276] eta: 1 day, 6:43:28 lr: 1.0061179464228896e-05 loss: 0.0826 (0.0834) time: 40.7910 data: 36.9788 max mem: 33303 +Epoch: [33] [1140/4276] eta: 1 day, 6:34:28 lr: 1.0058035400224763e-05 loss: 0.0812 (0.0835) time: 28.5466 data: 25.0362 max mem: 33303 +Epoch: [33] [1150/4276] eta: 1 day, 6:25:47 lr: 1.0054891227015719e-05 loss: 0.0769 (0.0834) time: 28.5682 data: 25.0645 max mem: 33303 +Epoch: [33] [1160/4276] eta: 1 day, 6:28:02 lr: 1.005174694456002e-05 loss: 0.0753 (0.0835) time: 40.9714 data: 37.2398 max mem: 33303 +Epoch: [33] [1170/4276] eta: 1 day, 6:19:12 lr: 1.004860255281591e-05 loss: 0.0941 (0.0836) time: 40.8113 data: 37.0034 max mem: 33303 +Epoch: [33] [1180/4276] eta: 1 day, 6:11:17 lr: 1.004545805174157e-05 loss: 0.0941 (0.0837) time: 29.4580 data: 25.8308 max mem: 33303 +Epoch: [33] [1190/4276] eta: 1 day, 6:02:10 lr: 1.0042313441295181e-05 loss: 0.0746 (0.0836) time: 28.9880 data: 25.3665 max mem: 33303 +Epoch: [33] [1200/4276] eta: 1 day, 6:03:31 lr: 1.003916872143488e-05 loss: 0.0711 (0.0837) time: 39.7171 data: 35.8822 max mem: 33303 +Epoch: [33] [1210/4276] eta: 1 day, 5:55:14 lr: 1.0036023892118783e-05 loss: 0.0779 (0.0836) time: 40.6537 data: 36.8436 max mem: 33303 +Epoch: [33] [1220/4276] eta: 1 day, 5:46:50 lr: 1.0032878953304955e-05 loss: 0.0779 (0.0836) time: 29.2349 data: 25.6408 max mem: 33303 +Epoch: [33] [1230/4276] eta: 1 day, 5:37:50 lr: 1.0029733904951453e-05 loss: 0.0838 (0.0838) time: 28.2358 data: 24.6583 max mem: 33303 +Epoch: [33] [1240/4276] eta: 1 day, 5:39:17 lr: 1.002658874701629e-05 loss: 0.0786 (0.0837) time: 40.1785 data: 36.3916 max mem: 33303 +Epoch: [33] [1250/4276] eta: 1 day, 5:30:44 lr: 1.0023443479457459e-05 loss: 0.0778 (0.0838) time: 40.6840 data: 36.9161 max mem: 33303 +Epoch: [33] [1260/4276] eta: 1 day, 5:22:53 lr: 1.0020298102232905e-05 loss: 0.0799 (0.0837) time: 29.2845 data: 25.8184 max mem: 33303 +Epoch: [33] [1270/4276] eta: 1 day, 5:14:24 lr: 1.0017152615300557e-05 loss: 0.0722 (0.0836) time: 29.2381 data: 25.7783 max mem: 33303 +Epoch: [33] [1280/4276] eta: 1 day, 5:16:10 lr: 1.001400701861831e-05 loss: 0.0779 (0.0836) time: 41.4626 data: 37.7234 max mem: 33303 +Epoch: [33] [1290/4276] eta: 1 day, 5:07:24 lr: 1.0010861312144032e-05 loss: 0.0851 (0.0837) time: 41.0938 data: 37.2968 max mem: 33303 +Epoch: [33] [1300/4276] eta: 1 day, 4:59:32 lr: 1.0007715495835544e-05 loss: 0.0792 (0.0838) time: 28.7287 data: 25.1850 max mem: 33303 +Epoch: [33] [1310/4276] eta: 1 day, 4:51:14 lr: 1.000456956965065e-05 loss: 0.0747 (0.0837) time: 29.1814 data: 25.6739 max mem: 33303 +Epoch: [33] [1320/4276] eta: 1 day, 4:52:12 lr: 1.0001423533547131e-05 loss: 0.0755 (0.0837) time: 40.9114 data: 37.1840 max mem: 33303 +Epoch: [33] [1330/4276] eta: 1 day, 4:43:57 lr: 9.998277387482709e-06 loss: 0.0893 (0.0837) time: 40.9817 data: 37.2793 max mem: 33303 +Epoch: [33] [1340/4276] eta: 1 day, 4:36:13 lr: 9.995131131415102e-06 loss: 0.0820 (0.0837) time: 29.3140 data: 25.7872 max mem: 33303 +Epoch: [33] [1350/4276] eta: 1 day, 4:27:55 lr: 9.991984765301986e-06 loss: 0.0806 (0.0837) time: 29.1195 data: 25.5754 max mem: 33303 +Epoch: [33] [1360/4276] eta: 1 day, 4:28:38 lr: 9.988838289101012e-06 loss: 0.0823 (0.0837) time: 40.8233 data: 37.0456 max mem: 33303 +Epoch: [33] [1370/4276] eta: 1 day, 4:20:41 lr: 9.985691702769784e-06 loss: 0.0812 (0.0836) time: 41.2973 data: 37.4752 max mem: 33303 +Epoch: [33] [1380/4276] eta: 1 day, 4:12:44 lr: 9.98254500626589e-06 loss: 0.0789 (0.0836) time: 29.1829 data: 25.6203 max mem: 33303 +Epoch: [33] [1390/4276] eta: 1 day, 4:04:19 lr: 9.979398199546884e-06 loss: 0.0787 (0.0837) time: 28.3747 data: 24.8769 max mem: 33303 +Epoch: [33] [1400/4276] eta: 1 day, 4:04:49 lr: 9.976251282570292e-06 loss: 0.0775 (0.0837) time: 40.5888 data: 36.8734 max mem: 33303 +Epoch: [33] [1410/4276] eta: 1 day, 3:56:43 lr: 9.973104255293594e-06 loss: 0.0800 (0.0836) time: 41.0368 data: 37.3161 max mem: 33303 +Epoch: [33] [1420/4276] eta: 1 day, 3:48:59 lr: 9.969957117674252e-06 loss: 0.0738 (0.0836) time: 29.0033 data: 25.5452 max mem: 33303 +Epoch: [33] [1430/4276] eta: 1 day, 3:40:59 lr: 9.966809869669695e-06 loss: 0.0711 (0.0836) time: 29.0069 data: 25.4997 max mem: 33303 +Epoch: [33] [1440/4276] eta: 1 day, 3:40:56 lr: 9.963662511237325e-06 loss: 0.0718 (0.0836) time: 40.6057 data: 36.8158 max mem: 33303 +Epoch: [33] [1450/4276] eta: 1 day, 3:33:04 lr: 9.960515042334493e-06 loss: 0.0733 (0.0835) time: 40.8175 data: 37.0769 max mem: 33303 +Epoch: [33] [1460/4276] eta: 1 day, 3:25:27 lr: 9.95736746291854e-06 loss: 0.0777 (0.0835) time: 29.2721 data: 25.7493 max mem: 33303 +Epoch: [33] [1470/4276] eta: 1 day, 3:17:19 lr: 9.954219772946766e-06 loss: 0.0777 (0.0835) time: 28.7270 data: 25.1636 max mem: 33303 +Epoch: [33] [1480/4276] eta: 1 day, 3:17:22 lr: 9.951071972376448e-06 loss: 0.0879 (0.0836) time: 40.7648 data: 37.0078 max mem: 33303 +Epoch: [33] [1490/4276] eta: 1 day, 3:09:38 lr: 9.947924061164812e-06 loss: 0.0773 (0.0835) time: 41.3954 data: 37.6806 max mem: 33303 +Epoch: [33] [1500/4276] eta: 1 day, 3:01:40 lr: 9.944776039269072e-06 loss: 0.0674 (0.0834) time: 28.6891 data: 25.1543 max mem: 33303 +Epoch: [33] [1510/4276] eta: 1 day, 2:53:45 lr: 9.941627906646401e-06 loss: 0.0694 (0.0834) time: 28.2559 data: 24.7070 max mem: 33303 +Epoch: [33] [1520/4276] eta: 1 day, 2:53:31 lr: 9.938479663253953e-06 loss: 0.0737 (0.0833) time: 40.8807 data: 37.0960 max mem: 33303 +Epoch: [33] [1530/4276] eta: 1 day, 2:45:48 lr: 9.935331309048823e-06 loss: 0.0736 (0.0833) time: 41.2308 data: 37.3762 max mem: 33303 +Epoch: [33] [1540/4276] eta: 1 day, 2:38:20 lr: 9.932182843988101e-06 loss: 0.0760 (0.0832) time: 29.2675 data: 25.7331 max mem: 33303 +Epoch: [33] [1550/4276] eta: 1 day, 2:29:52 lr: 9.929034268028833e-06 loss: 0.0818 (0.0832) time: 27.8531 data: 24.3277 max mem: 33303 +Epoch: [33] [1560/4276] eta: 1 day, 2:29:09 lr: 9.925885581128046e-06 loss: 0.0739 (0.0832) time: 39.3502 data: 35.5437 max mem: 33303 +Epoch: [33] [1570/4276] eta: 1 day, 2:21:37 lr: 9.922736783242709e-06 loss: 0.0698 (0.0831) time: 40.9182 data: 37.1902 max mem: 33303 +Epoch: [33] [1580/4276] eta: 1 day, 2:14:10 lr: 9.919587874329782e-06 loss: 0.0677 (0.0831) time: 29.3324 data: 25.7279 max mem: 33303 +Epoch: [33] [1590/4276] eta: 1 day, 2:06:21 lr: 9.916438854346187e-06 loss: 0.0774 (0.0831) time: 28.7246 data: 25.0346 max mem: 33303 +Epoch: [33] [1600/4276] eta: 1 day, 2:05:21 lr: 9.913289723248818e-06 loss: 0.0865 (0.0831) time: 40.1855 data: 36.3050 max mem: 33303 +Epoch: [33] [1610/4276] eta: 1 day, 1:57:38 lr: 9.910140480994523e-06 loss: 0.0863 (0.0831) time: 40.3340 data: 36.4384 max mem: 33303 +Epoch: [33] [1620/4276] eta: 1 day, 1:49:58 lr: 9.906991127540132e-06 loss: 0.0757 (0.0831) time: 28.3354 data: 24.7688 max mem: 33303 +Epoch: [33] [1630/4276] eta: 1 day, 1:42:36 lr: 9.903841662842443e-06 loss: 0.0839 (0.0832) time: 28.8630 data: 25.2967 max mem: 33303 +Epoch: [33] [1640/4276] eta: 1 day, 1:41:52 lr: 9.900692086858209e-06 loss: 0.0814 (0.0832) time: 41.6892 data: 37.7055 max mem: 33303 +Epoch: [33] [1650/4276] eta: 1 day, 1:33:47 lr: 9.89754239954416e-06 loss: 0.0803 (0.0831) time: 40.3447 data: 36.4175 max mem: 33303 +Epoch: [33] [1660/4276] eta: 1 day, 1:26:12 lr: 9.894392600856997e-06 loss: 0.0780 (0.0831) time: 27.5450 data: 24.0360 max mem: 33303 +Epoch: [33] [1670/4276] eta: 1 day, 1:18:30 lr: 9.891242690753389e-06 loss: 0.0795 (0.0832) time: 28.1250 data: 24.6385 max mem: 33303 +Epoch: [33] [1680/4276] eta: 1 day, 1:17:19 lr: 9.88809266918996e-06 loss: 0.0795 (0.0832) time: 40.4056 data: 36.6610 max mem: 33303 +Epoch: [33] [1690/4276] eta: 1 day, 1:09:46 lr: 9.884942536123311e-06 loss: 0.0749 (0.0832) time: 40.6657 data: 36.9336 max mem: 33303 +Epoch: [33] [1700/4276] eta: 1 day, 1:02:29 lr: 9.881792291510015e-06 loss: 0.0810 (0.0832) time: 28.8510 data: 25.3447 max mem: 33303 +Epoch: [33] [1710/4276] eta: 1 day, 0:55:04 lr: 9.87864193530661e-06 loss: 0.0818 (0.0832) time: 28.9804 data: 25.3416 max mem: 33303 +Epoch: [33] [1720/4276] eta: 1 day, 0:53:58 lr: 9.875491467469592e-06 loss: 0.0738 (0.0831) time: 41.3442 data: 37.4781 max mem: 33303 +Epoch: [33] [1730/4276] eta: 1 day, 0:46:45 lr: 9.872340887955435e-06 loss: 0.0735 (0.0831) time: 41.7867 data: 38.0621 max mem: 33303 +Epoch: [33] [1740/4276] eta: 1 day, 0:39:10 lr: 9.86919019672058e-06 loss: 0.0788 (0.0831) time: 28.6931 data: 25.2300 max mem: 33303 +Epoch: [33] [1750/4276] eta: 1 day, 0:32:18 lr: 9.866039393721436e-06 loss: 0.0748 (0.0830) time: 29.2675 data: 25.7168 max mem: 33303 +Epoch: [33] [1760/4276] eta: 1 day, 0:30:50 lr: 9.862888478914365e-06 loss: 0.0692 (0.0830) time: 41.9636 data: 38.1608 max mem: 33303 +Epoch: [33] [1770/4276] eta: 1 day, 0:23:18 lr: 9.85973745225572e-06 loss: 0.0669 (0.0829) time: 40.5917 data: 36.8644 max mem: 33303 +Epoch: [33] [1780/4276] eta: 1 day, 0:16:13 lr: 9.856586313701804e-06 loss: 0.0669 (0.0829) time: 28.8474 data: 25.3709 max mem: 33303 +Epoch: [33] [1790/4276] eta: 1 day, 0:08:51 lr: 9.8534350632089e-06 loss: 0.0732 (0.0828) time: 29.0665 data: 25.4910 max mem: 33303 +Epoch: [33] [1800/4276] eta: 1 day, 0:07:20 lr: 9.850283700733243e-06 loss: 0.0784 (0.0829) time: 41.0480 data: 37.1492 max mem: 33303 +Epoch: [33] [1810/4276] eta: 23:59:39 lr: 9.847132226231045e-06 loss: 0.0761 (0.0829) time: 40.3809 data: 36.5830 max mem: 33303 +Epoch: [33] [1820/4276] eta: 23:52:29 lr: 9.843980639658488e-06 loss: 0.0761 (0.0828) time: 28.0626 data: 24.5742 max mem: 33303 +Epoch: [33] [1830/4276] eta: 23:45:00 lr: 9.840828940971722e-06 loss: 0.0740 (0.0828) time: 28.3424 data: 24.8668 max mem: 33303 +Epoch: [33] [1840/4276] eta: 23:43:24 lr: 9.837677130126845e-06 loss: 0.0665 (0.0827) time: 40.8687 data: 37.1587 max mem: 33303 +Epoch: [33] [1850/4276] eta: 23:36:14 lr: 9.834525207079949e-06 loss: 0.0688 (0.0828) time: 41.5528 data: 37.8424 max mem: 33303 +Epoch: [33] [1860/4276] eta: 23:28:49 lr: 9.831373171787075e-06 loss: 0.0875 (0.0828) time: 28.3633 data: 24.9198 max mem: 33303 +Epoch: [33] [1870/4276] eta: 23:21:47 lr: 9.828221024204249e-06 loss: 0.0850 (0.0827) time: 28.5747 data: 25.0379 max mem: 33303 +Epoch: [33] [1880/4276] eta: 23:20:05 lr: 9.825068764287433e-06 loss: 0.0689 (0.0827) time: 41.8545 data: 37.9851 max mem: 33303 +Epoch: [33] [1890/4276] eta: 23:12:51 lr: 9.821916391992586e-06 loss: 0.0685 (0.0826) time: 41.4144 data: 37.6133 max mem: 33303 +Epoch: [33] [1900/4276] eta: 23:05:35 lr: 9.818763907275623e-06 loss: 0.0775 (0.0826) time: 28.3194 data: 24.8574 max mem: 33303 +Epoch: [33] [1910/4276] eta: 22:58:53 lr: 9.815611310092431e-06 loss: 0.0741 (0.0826) time: 29.4629 data: 25.9382 max mem: 33303 +Epoch: [33] [1920/4276] eta: 22:56:45 lr: 9.812458600398849e-06 loss: 0.0621 (0.0826) time: 41.9356 data: 38.1313 max mem: 33303 +Epoch: [33] [1930/4276] eta: 22:49:30 lr: 9.809305778150695e-06 loss: 0.0715 (0.0825) time: 40.5839 data: 36.8554 max mem: 33303 +Epoch: [33] [1940/4276] eta: 22:42:27 lr: 9.806152843303762e-06 loss: 0.0715 (0.0825) time: 28.5487 data: 25.1072 max mem: 33303 +Epoch: [33] [1950/4276] eta: 22:35:19 lr: 9.802999795813786e-06 loss: 0.0841 (0.0826) time: 28.6973 data: 25.1727 max mem: 33303 +Epoch: [33] [1960/4276] eta: 22:33:11 lr: 9.799846635636492e-06 loss: 0.0752 (0.0826) time: 41.0572 data: 37.2420 max mem: 33303 +Epoch: [33] [1970/4276] eta: 22:25:56 lr: 9.796693362727558e-06 loss: 0.0751 (0.0826) time: 40.7935 data: 37.0313 max mem: 33303 +Epoch: [33] [1980/4276] eta: 22:18:56 lr: 9.793539977042644e-06 loss: 0.0712 (0.0825) time: 28.4143 data: 24.8585 max mem: 33303 +Epoch: [33] [1990/4276] eta: 22:11:54 lr: 9.790386478537356e-06 loss: 0.0714 (0.0825) time: 28.8709 data: 25.2816 max mem: 33303 +Epoch: [33] [2000/4276] eta: 22:09:31 lr: 9.787232867167279e-06 loss: 0.0826 (0.0825) time: 40.9489 data: 37.1502 max mem: 33303 +Epoch: [33] [2010/4276] eta: 22:02:26 lr: 9.784079142887966e-06 loss: 0.0835 (0.0826) time: 40.7738 data: 37.0474 max mem: 33303 +Epoch: [33] [2020/4276] eta: 21:55:09 lr: 9.780925305654937e-06 loss: 0.0837 (0.0826) time: 27.8306 data: 24.3822 max mem: 33303 +Epoch: [33] [2030/4276] eta: 21:47:57 lr: 9.777771355423667e-06 loss: 0.0692 (0.0825) time: 27.3966 data: 23.9473 max mem: 33303 +Epoch: [33] [2040/4276] eta: 21:45:44 lr: 9.774617292149608e-06 loss: 0.0656 (0.0825) time: 41.0907 data: 37.3698 max mem: 33303 +Epoch: [33] [2050/4276] eta: 21:38:38 lr: 9.771463115788177e-06 loss: 0.0798 (0.0825) time: 41.3644 data: 37.6350 max mem: 33303 +Epoch: [33] [2060/4276] eta: 21:31:50 lr: 9.768308826294765e-06 loss: 0.0771 (0.0825) time: 28.8793 data: 25.4375 max mem: 33303 +Epoch: [33] [2070/4276] eta: 21:24:37 lr: 9.765154423624703e-06 loss: 0.0722 (0.0825) time: 28.3985 data: 24.8720 max mem: 33303 +Epoch: [33] [2080/4276] eta: 21:22:07 lr: 9.761999907733317e-06 loss: 0.0783 (0.0825) time: 40.4685 data: 36.5827 max mem: 33303 +Epoch: [33] [2090/4276] eta: 21:15:21 lr: 9.758845278575886e-06 loss: 0.0858 (0.0825) time: 41.7387 data: 37.9048 max mem: 33303 +Epoch: [33] [2100/4276] eta: 21:08:38 lr: 9.755690536107666e-06 loss: 0.0765 (0.0825) time: 29.8007 data: 26.2286 max mem: 33303 +Epoch: [33] [2110/4276] eta: 21:01:59 lr: 9.752535680283855e-06 loss: 0.0752 (0.0824) time: 30.0774 data: 26.5343 max mem: 33303 +Epoch: [33] [2120/4276] eta: 20:59:15 lr: 9.749380711059645e-06 loss: 0.0651 (0.0823) time: 41.6839 data: 37.8953 max mem: 33303 +Epoch: [33] [2130/4276] eta: 20:52:12 lr: 9.746225628390176e-06 loss: 0.0651 (0.0823) time: 40.5131 data: 36.6446 max mem: 33303 +Epoch: [33] [2140/4276] eta: 20:45:25 lr: 9.74307043223057e-06 loss: 0.0752 (0.0823) time: 28.5908 data: 24.9932 max mem: 33303 +Epoch: [33] [2150/4276] eta: 20:38:59 lr: 9.739915122535893e-06 loss: 0.0716 (0.0822) time: 30.3307 data: 26.8131 max mem: 33303 +Epoch: [33] [2160/4276] eta: 20:36:24 lr: 9.736759699261196e-06 loss: 0.0716 (0.0822) time: 43.1076 data: 39.3701 max mem: 33303 +Epoch: [33] [2170/4276] eta: 20:29:15 lr: 9.733604162361488e-06 loss: 0.0765 (0.0823) time: 40.8965 data: 37.1594 max mem: 33303 +Epoch: [33] [2180/4276] eta: 20:22:25 lr: 9.730448511791753e-06 loss: 0.0804 (0.0823) time: 27.8934 data: 24.4458 max mem: 33303 +Epoch: [33] [2190/4276] eta: 20:15:30 lr: 9.72729274750692e-06 loss: 0.0827 (0.0823) time: 28.4988 data: 25.0626 max mem: 33303 +Epoch: [33] [2200/4276] eta: 20:12:35 lr: 9.724136869461904e-06 loss: 0.0840 (0.0823) time: 40.8213 data: 37.0894 max mem: 33303 +Epoch: [33] [2210/4276] eta: 20:05:52 lr: 9.72098087761158e-06 loss: 0.0782 (0.0823) time: 41.4262 data: 37.6731 max mem: 33303 +Epoch: [33] [2220/4276] eta: 19:58:59 lr: 9.717824771910792e-06 loss: 0.0771 (0.0823) time: 28.8212 data: 25.3613 max mem: 33303 +Epoch: [33] [2230/4276] eta: 19:52:01 lr: 9.714668552314335e-06 loss: 0.0771 (0.0823) time: 27.8778 data: 24.4367 max mem: 33303 +Epoch: [33] [2240/4276] eta: 19:49:04 lr: 9.711512218776987e-06 loss: 0.0717 (0.0823) time: 40.7674 data: 37.0409 max mem: 33303 +Epoch: [33] [2250/4276] eta: 19:42:17 lr: 9.70835577125349e-06 loss: 0.0717 (0.0823) time: 41.4015 data: 37.6763 max mem: 33303 +Epoch: [33] [2260/4276] eta: 19:35:23 lr: 9.705199209698536e-06 loss: 0.0794 (0.0823) time: 28.2533 data: 24.8123 max mem: 33303 +Epoch: [33] [2270/4276] eta: 19:28:35 lr: 9.702042534066799e-06 loss: 0.0739 (0.0822) time: 28.1086 data: 24.5591 max mem: 33303 +Epoch: [33] [2280/4276] eta: 19:25:22 lr: 9.698885744312913e-06 loss: 0.0749 (0.0822) time: 40.6598 data: 36.7104 max mem: 33303 +Epoch: [33] [2290/4276] eta: 19:18:36 lr: 9.695728840391483e-06 loss: 0.0793 (0.0822) time: 40.6937 data: 36.8588 max mem: 33303 +Epoch: [33] [2300/4276] eta: 19:12:00 lr: 9.692571822257062e-06 loss: 0.0746 (0.0822) time: 29.0922 data: 25.5883 max mem: 33303 +Epoch: [33] [2310/4276] eta: 19:05:12 lr: 9.689414689864189e-06 loss: 0.0840 (0.0822) time: 28.9232 data: 25.3219 max mem: 33303 +Epoch: [33] [2320/4276] eta: 19:01:45 lr: 9.686257443167357e-06 loss: 0.0895 (0.0822) time: 40.0271 data: 36.1600 max mem: 33303 +Epoch: [33] [2330/4276] eta: 18:55:02 lr: 9.683100082121036e-06 loss: 0.0832 (0.0823) time: 40.2770 data: 36.4997 max mem: 33303 +Epoch: [33] [2340/4276] eta: 18:48:18 lr: 9.679942606679637e-06 loss: 0.0809 (0.0823) time: 28.5508 data: 25.1096 max mem: 33303 +Epoch: [33] [2350/4276] eta: 18:41:48 lr: 9.676785016797562e-06 loss: 0.0755 (0.0822) time: 29.2282 data: 25.6826 max mem: 33303 +Epoch: [33] [2360/4276] eta: 18:38:26 lr: 9.673627312429167e-06 loss: 0.0727 (0.0822) time: 41.6084 data: 37.6953 max mem: 33303 +Epoch: [33] [2370/4276] eta: 18:31:43 lr: 9.67046949352878e-06 loss: 0.0822 (0.0822) time: 40.8028 data: 36.9813 max mem: 33303 +Epoch: [33] [2380/4276] eta: 18:25:01 lr: 9.667311560050678e-06 loss: 0.0757 (0.0822) time: 28.4602 data: 25.0059 max mem: 33303 +Epoch: [33] [2390/4276] eta: 18:18:16 lr: 9.664153511949117e-06 loss: 0.0749 (0.0822) time: 28.2445 data: 24.6300 max mem: 33303 +Epoch: [33] [2400/4276] eta: 18:14:53 lr: 9.660995349178319e-06 loss: 0.0809 (0.0822) time: 40.7858 data: 36.7961 max mem: 33303 +Epoch: [33] [2410/4276] eta: 18:08:12 lr: 9.65783707169247e-06 loss: 0.0853 (0.0823) time: 41.0197 data: 37.2080 max mem: 33303 +Epoch: [33] [2420/4276] eta: 18:01:29 lr: 9.654678679445709e-06 loss: 0.0814 (0.0823) time: 28.2956 data: 24.8603 max mem: 33303 +Epoch: [33] [2430/4276] eta: 17:54:48 lr: 9.651520172392152e-06 loss: 0.0788 (0.0823) time: 28.1817 data: 24.7231 max mem: 33303 +Epoch: [33] [2440/4276] eta: 17:51:17 lr: 9.64836155048588e-06 loss: 0.0760 (0.0822) time: 40.7351 data: 36.9724 max mem: 33303 +Epoch: [33] [2450/4276] eta: 17:44:38 lr: 9.645202813680938e-06 loss: 0.0735 (0.0822) time: 40.8539 data: 37.1100 max mem: 33303 +Epoch: [33] [2460/4276] eta: 17:38:01 lr: 9.642043961931326e-06 loss: 0.0756 (0.0822) time: 28.5436 data: 25.1057 max mem: 33303 +Epoch: [33] [2470/4276] eta: 17:31:10 lr: 9.638884995191024e-06 loss: 0.0776 (0.0822) time: 27.5942 data: 24.1461 max mem: 33303 +Epoch: [33] [2480/4276] eta: 17:27:25 lr: 9.635725913413964e-06 loss: 0.0878 (0.0823) time: 39.3304 data: 35.5965 max mem: 33303 +Epoch: [33] [2490/4276] eta: 17:20:54 lr: 9.632566716554058e-06 loss: 0.0795 (0.0823) time: 40.6583 data: 36.9293 max mem: 33303 +Epoch: [33] [2500/4276] eta: 17:14:20 lr: 9.629407404565159e-06 loss: 0.0795 (0.0822) time: 28.9744 data: 25.5183 max mem: 33303 +Epoch: [33] [2510/4276] eta: 17:07:53 lr: 9.626247977401107e-06 loss: 0.0880 (0.0823) time: 29.1814 data: 25.6705 max mem: 33303 +Epoch: [33] [2520/4276] eta: 17:04:19 lr: 9.623088435015698e-06 loss: 0.0751 (0.0822) time: 41.9550 data: 38.1494 max mem: 33303 +Epoch: [33] [2530/4276] eta: 16:57:39 lr: 9.619928777362697e-06 loss: 0.0696 (0.0822) time: 41.0160 data: 37.2651 max mem: 33303 +Epoch: [33] [2540/4276] eta: 16:51:01 lr: 9.61676900439582e-06 loss: 0.0716 (0.0822) time: 27.8520 data: 24.3304 max mem: 33303 +Epoch: [33] [2550/4276] eta: 16:44:30 lr: 9.61360911606876e-06 loss: 0.0698 (0.0821) time: 28.3548 data: 24.8242 max mem: 33303 +Epoch: [33] [2560/4276] eta: 16:40:48 lr: 9.610449112335183e-06 loss: 0.0635 (0.0821) time: 41.3416 data: 37.5753 max mem: 33303 +Epoch: [33] [2570/4276] eta: 16:34:09 lr: 9.60728899314869e-06 loss: 0.0716 (0.0821) time: 40.7780 data: 36.9567 max mem: 33303 +Epoch: [33] [2580/4276] eta: 16:27:44 lr: 9.604128758462873e-06 loss: 0.0758 (0.0821) time: 28.6233 data: 25.0122 max mem: 33303 +Epoch: [33] [2590/4276] eta: 16:21:05 lr: 9.60096840823128e-06 loss: 0.0701 (0.0820) time: 28.4131 data: 24.7985 max mem: 33303 +Epoch: [33] [2600/4276] eta: 16:17:13 lr: 9.597807942407428e-06 loss: 0.0669 (0.0820) time: 40.1962 data: 36.3283 max mem: 33303 +Epoch: [33] [2610/4276] eta: 16:10:46 lr: 9.594647360944783e-06 loss: 0.0703 (0.0820) time: 41.1617 data: 37.2952 max mem: 33303 +Epoch: [33] [2620/4276] eta: 16:04:16 lr: 9.59148666379679e-06 loss: 0.0785 (0.0820) time: 28.8212 data: 25.2916 max mem: 33303 +Epoch: [33] [2630/4276] eta: 15:57:52 lr: 9.588325850916854e-06 loss: 0.0752 (0.0819) time: 28.9930 data: 25.5386 max mem: 33303 +Epoch: [33] [2640/4276] eta: 15:53:55 lr: 9.585164922258349e-06 loss: 0.0703 (0.0819) time: 41.2468 data: 37.5132 max mem: 33303 +Epoch: [33] [2650/4276] eta: 15:47:24 lr: 9.5820038777746e-06 loss: 0.0736 (0.0819) time: 40.5933 data: 36.7682 max mem: 33303 +Epoch: [33] [2660/4276] eta: 15:41:01 lr: 9.578842717418906e-06 loss: 0.0764 (0.0819) time: 28.8330 data: 25.2159 max mem: 33303 +Epoch: [33] [2670/4276] eta: 15:34:25 lr: 9.575681441144529e-06 loss: 0.0771 (0.0819) time: 28.3622 data: 24.7500 max mem: 33303 +Epoch: [33] [2680/4276] eta: 15:30:28 lr: 9.572520048904699e-06 loss: 0.0792 (0.0819) time: 40.4622 data: 36.6453 max mem: 33303 +Epoch: [33] [2690/4276] eta: 15:23:59 lr: 9.569358540652598e-06 loss: 0.0742 (0.0818) time: 41.0045 data: 37.2765 max mem: 33303 +Epoch: [33] [2700/4276] eta: 15:17:31 lr: 9.566196916341382e-06 loss: 0.0677 (0.0818) time: 28.4059 data: 24.9516 max mem: 33303 +Epoch: [33] [2710/4276] eta: 15:11:04 lr: 9.563035175924165e-06 loss: 0.0698 (0.0818) time: 28.4043 data: 24.9468 max mem: 33303 +Epoch: [33] [2720/4276] eta: 15:07:01 lr: 9.55987331935404e-06 loss: 0.0713 (0.0817) time: 40.9243 data: 37.2053 max mem: 33303 +Epoch: [33] [2730/4276] eta: 15:00:37 lr: 9.556711346584033e-06 loss: 0.0713 (0.0817) time: 41.1620 data: 37.4361 max mem: 33303 +Epoch: [33] [2740/4276] eta: 14:54:12 lr: 9.553549257567161e-06 loss: 0.0752 (0.0817) time: 28.7515 data: 25.2960 max mem: 33303 +Epoch: [33] [2750/4276] eta: 14:47:53 lr: 9.550387052256399e-06 loss: 0.0791 (0.0817) time: 29.1798 data: 25.7063 max mem: 33303 +Epoch: [33] [2760/4276] eta: 14:43:49 lr: 9.547224730604682e-06 loss: 0.0793 (0.0817) time: 41.7875 data: 38.0465 max mem: 33303 +Epoch: [33] [2770/4276] eta: 14:37:23 lr: 9.544062292564906e-06 loss: 0.0682 (0.0816) time: 41.1094 data: 37.3906 max mem: 33303 +Epoch: [33] [2780/4276] eta: 14:31:04 lr: 9.54089973808993e-06 loss: 0.0692 (0.0816) time: 28.8922 data: 25.4027 max mem: 33303 +Epoch: [33] [2790/4276] eta: 14:24:36 lr: 9.537737067132589e-06 loss: 0.0873 (0.0817) time: 28.5961 data: 25.1078 max mem: 33303 +Epoch: [33] [2800/4276] eta: 14:20:26 lr: 9.534574279645673e-06 loss: 0.0692 (0.0816) time: 40.7078 data: 36.9052 max mem: 33303 +Epoch: [33] [2810/4276] eta: 14:14:09 lr: 9.531411375581927e-06 loss: 0.0602 (0.0815) time: 41.7634 data: 37.8792 max mem: 33303 +Epoch: [33] [2820/4276] eta: 14:07:44 lr: 9.528248354894073e-06 loss: 0.0602 (0.0815) time: 29.0015 data: 25.4518 max mem: 33303 +Epoch: [33] [2830/4276] eta: 14:01:23 lr: 9.525085217534788e-06 loss: 0.0737 (0.0815) time: 28.3706 data: 24.8785 max mem: 33303 +Epoch: [33] [2840/4276] eta: 13:57:03 lr: 9.521921963456727e-06 loss: 0.0894 (0.0816) time: 40.6381 data: 36.8785 max mem: 33303 +Epoch: [33] [2850/4276] eta: 13:50:41 lr: 9.51875859261248e-06 loss: 0.0767 (0.0816) time: 40.5902 data: 36.8324 max mem: 33303 +Epoch: [33] [2860/4276] eta: 13:44:23 lr: 9.515595104954625e-06 loss: 0.0730 (0.0816) time: 28.8589 data: 25.3695 max mem: 33303 +Epoch: [33] [2870/4276] eta: 13:37:58 lr: 9.5124315004357e-06 loss: 0.0713 (0.0816) time: 28.4452 data: 24.9712 max mem: 33303 +Epoch: [33] [2880/4276] eta: 13:33:38 lr: 9.509267779008192e-06 loss: 0.0731 (0.0816) time: 40.3870 data: 36.6462 max mem: 33303 +Epoch: [33] [2890/4276] eta: 13:27:10 lr: 9.506103940624564e-06 loss: 0.0731 (0.0815) time: 40.0962 data: 36.2480 max mem: 33303 +Epoch: [33] [2900/4276] eta: 13:20:49 lr: 9.502939985237238e-06 loss: 0.0649 (0.0815) time: 27.7224 data: 24.1579 max mem: 33303 +Epoch: [33] [2910/4276] eta: 13:14:26 lr: 9.499775912798608e-06 loss: 0.0778 (0.0815) time: 27.9605 data: 24.5116 max mem: 33303 +Epoch: [33] [2920/4276] eta: 13:09:58 lr: 9.49661172326101e-06 loss: 0.0778 (0.0815) time: 39.9430 data: 36.2191 max mem: 33303 +Epoch: [33] [2930/4276] eta: 13:03:35 lr: 9.493447416576761e-06 loss: 0.0755 (0.0816) time: 40.0664 data: 36.3234 max mem: 33303 +Epoch: [33] [2940/4276] eta: 12:57:21 lr: 9.490282992698135e-06 loss: 0.0853 (0.0815) time: 28.6449 data: 25.1841 max mem: 33303 +Epoch: [33] [2950/4276] eta: 12:51:02 lr: 9.487118451577378e-06 loss: 0.0845 (0.0816) time: 28.9038 data: 25.3952 max mem: 33303 +Epoch: [33] [2960/4276] eta: 12:46:35 lr: 9.483953793166674e-06 loss: 0.0757 (0.0816) time: 40.8029 data: 37.0175 max mem: 33303 +Epoch: [33] [2970/4276] eta: 12:40:20 lr: 9.480789017418195e-06 loss: 0.0757 (0.0816) time: 41.2152 data: 37.4814 max mem: 33303 +Epoch: [33] [2980/4276] eta: 12:34:02 lr: 9.477624124284065e-06 loss: 0.0783 (0.0815) time: 28.7381 data: 25.2775 max mem: 33303 +Epoch: [33] [2990/4276] eta: 12:27:52 lr: 9.474459113716379e-06 loss: 0.0700 (0.0815) time: 29.1475 data: 25.7006 max mem: 33303 +Epoch: [33] [3000/4276] eta: 12:23:13 lr: 9.471293985667176e-06 loss: 0.0700 (0.0815) time: 40.5944 data: 36.7738 max mem: 33303 +Epoch: [33] [3010/4276] eta: 12:16:54 lr: 9.468128740088477e-06 loss: 0.0764 (0.0815) time: 39.6322 data: 35.8204 max mem: 33303 +Epoch: [33] [3020/4276] eta: 12:10:40 lr: 9.464963376932257e-06 loss: 0.0684 (0.0814) time: 28.4735 data: 25.0499 max mem: 33303 +Epoch: [33] [3030/4276] eta: 12:04:27 lr: 9.46179789615046e-06 loss: 0.0680 (0.0814) time: 29.0274 data: 25.5004 max mem: 33303 +Epoch: [33] [3040/4276] eta: 11:59:57 lr: 9.458632297694975e-06 loss: 0.0768 (0.0814) time: 41.6992 data: 37.8094 max mem: 33303 +Epoch: [33] [3050/4276] eta: 11:53:40 lr: 9.455466581517673e-06 loss: 0.0777 (0.0814) time: 41.1735 data: 37.3022 max mem: 33303 +Epoch: [33] [3060/4276] eta: 11:47:26 lr: 9.45230074757038e-06 loss: 0.0664 (0.0814) time: 28.3634 data: 24.8528 max mem: 33303 +Epoch: [33] [3070/4276] eta: 11:41:11 lr: 9.44913479580489e-06 loss: 0.0748 (0.0814) time: 28.5017 data: 25.0628 max mem: 33303 +Epoch: [33] [3080/4276] eta: 11:36:33 lr: 9.445968726172941e-06 loss: 0.0817 (0.0814) time: 40.7742 data: 37.0188 max mem: 33303 +Epoch: [33] [3090/4276] eta: 11:30:19 lr: 9.442802538626255e-06 loss: 0.0663 (0.0813) time: 40.8680 data: 37.1099 max mem: 33303 +Epoch: [33] [3100/4276] eta: 11:24:04 lr: 9.439636233116503e-06 loss: 0.0663 (0.0813) time: 28.3990 data: 24.8374 max mem: 33303 +Epoch: [33] [3110/4276] eta: 11:17:51 lr: 9.43646980959533e-06 loss: 0.0657 (0.0812) time: 28.3521 data: 24.7652 max mem: 33303 +Epoch: [33] [3120/4276] eta: 11:13:13 lr: 9.433303268014325e-06 loss: 0.0671 (0.0812) time: 41.1857 data: 37.3333 max mem: 33303 +Epoch: [33] [3130/4276] eta: 11:07:01 lr: 9.430136608325053e-06 loss: 0.0779 (0.0812) time: 41.4112 data: 37.5736 max mem: 33303 +Epoch: [33] [3140/4276] eta: 11:00:49 lr: 9.426969830479038e-06 loss: 0.0728 (0.0812) time: 28.6443 data: 25.1097 max mem: 33303 +Epoch: [33] [3150/4276] eta: 10:54:35 lr: 9.423802934427776e-06 loss: 0.0676 (0.0812) time: 28.1585 data: 24.6427 max mem: 33303 +Epoch: [33] [3160/4276] eta: 10:49:49 lr: 9.420635920122695e-06 loss: 0.0704 (0.0812) time: 40.4126 data: 36.6899 max mem: 33303 +Epoch: [33] [3170/4276] eta: 10:43:37 lr: 9.417468787515218e-06 loss: 0.0771 (0.0812) time: 40.6743 data: 36.8926 max mem: 33303 +Epoch: [33] [3180/4276] eta: 10:37:30 lr: 9.414301536556719e-06 loss: 0.0771 (0.0812) time: 28.9804 data: 25.3948 max mem: 33303 +Epoch: [33] [3190/4276] eta: 10:31:20 lr: 9.411134167198517e-06 loss: 0.0779 (0.0812) time: 29.2068 data: 25.5924 max mem: 33303 +Epoch: [33] [3200/4276] eta: 10:26:31 lr: 9.407966679391916e-06 loss: 0.0771 (0.0812) time: 40.7527 data: 36.9105 max mem: 33303 +Epoch: [33] [3210/4276] eta: 10:20:19 lr: 9.404799073088172e-06 loss: 0.0734 (0.0812) time: 40.3589 data: 36.5604 max mem: 33303 +Epoch: [33] [3220/4276] eta: 10:14:09 lr: 9.40163134823851e-06 loss: 0.0734 (0.0812) time: 28.3530 data: 24.7810 max mem: 33303 +Epoch: [33] [3230/4276] eta: 10:07:58 lr: 9.398463504794096e-06 loss: 0.0766 (0.0812) time: 28.3813 data: 24.7902 max mem: 33303 +Epoch: [33] [3240/4276] eta: 10:03:07 lr: 9.39529554270608e-06 loss: 0.0766 (0.0812) time: 40.4587 data: 36.5914 max mem: 33303 +Epoch: [33] [3250/4276] eta: 9:57:01 lr: 9.392127461925564e-06 loss: 0.0769 (0.0812) time: 41.1694 data: 37.2989 max mem: 33303 +Epoch: [33] [3260/4276] eta: 9:50:49 lr: 9.388959262403618e-06 loss: 0.0774 (0.0813) time: 28.6390 data: 25.0821 max mem: 33303 +Epoch: [33] [3270/4276] eta: 9:44:45 lr: 9.38579094409126e-06 loss: 0.0774 (0.0812) time: 28.8106 data: 25.3007 max mem: 33303 +Epoch: [33] [3280/4276] eta: 9:39:54 lr: 9.382622506939477e-06 loss: 0.0813 (0.0813) time: 41.9037 data: 38.1548 max mem: 33303 +Epoch: [33] [3290/4276] eta: 9:33:45 lr: 9.379453950899224e-06 loss: 0.0907 (0.0813) time: 41.1449 data: 37.3787 max mem: 33303 +Epoch: [33] [3300/4276] eta: 9:27:40 lr: 9.376285275921416e-06 loss: 0.0917 (0.0813) time: 29.0097 data: 25.4205 max mem: 33303 +Epoch: [33] [3310/4276] eta: 9:21:28 lr: 9.37311648195691e-06 loss: 0.0851 (0.0813) time: 28.2546 data: 24.6524 max mem: 33303 +Epoch: [33] [3320/4276] eta: 9:16:39 lr: 9.369947568956545e-06 loss: 0.0851 (0.0814) time: 41.3710 data: 37.5700 max mem: 33303 +Epoch: [33] [3330/4276] eta: 9:10:30 lr: 9.36677853687112e-06 loss: 0.0905 (0.0814) time: 41.9032 data: 38.1164 max mem: 33303 +Epoch: [33] [3340/4276] eta: 9:04:23 lr: 9.363609385651391e-06 loss: 0.0858 (0.0814) time: 28.2413 data: 24.6321 max mem: 33303 +Epoch: [33] [3350/4276] eta: 8:58:16 lr: 9.360440115248066e-06 loss: 0.0833 (0.0814) time: 28.3923 data: 24.7897 max mem: 33303 +Epoch: [33] [3360/4276] eta: 8:53:23 lr: 9.357270725611824e-06 loss: 0.0729 (0.0814) time: 41.9148 data: 38.1794 max mem: 33303 +Epoch: [33] [3370/4276] eta: 8:47:15 lr: 9.354101216693307e-06 loss: 0.0752 (0.0814) time: 41.7178 data: 37.9687 max mem: 33303 +Epoch: [33] [3380/4276] eta: 8:41:09 lr: 9.35093158844312e-06 loss: 0.0758 (0.0814) time: 28.2699 data: 24.7285 max mem: 33303 +Epoch: [33] [3390/4276] eta: 8:35:03 lr: 9.34776184081181e-06 loss: 0.0808 (0.0814) time: 28.4080 data: 24.8082 max mem: 33303 +Epoch: [33] [3400/4276] eta: 8:30:02 lr: 9.344591973749905e-06 loss: 0.0808 (0.0814) time: 40.8313 data: 36.9107 max mem: 33303 +Epoch: [33] [3410/4276] eta: 8:23:54 lr: 9.341421987207887e-06 loss: 0.0789 (0.0814) time: 40.5766 data: 36.6683 max mem: 33303 +Epoch: [33] [3420/4276] eta: 8:17:49 lr: 9.338251881136206e-06 loss: 0.0747 (0.0814) time: 28.1413 data: 24.5744 max mem: 33303 +Epoch: [33] [3430/4276] eta: 8:11:48 lr: 9.33508165548525e-06 loss: 0.0822 (0.0814) time: 29.3874 data: 25.7889 max mem: 33303 +Epoch: [33] [3440/4276] eta: 8:06:46 lr: 9.331911310205391e-06 loss: 0.0774 (0.0814) time: 42.0589 data: 38.1173 max mem: 33303 +Epoch: [33] [3450/4276] eta: 8:00:41 lr: 9.328740845246958e-06 loss: 0.0752 (0.0815) time: 41.2077 data: 37.3486 max mem: 33303 +Epoch: [33] [3460/4276] eta: 7:54:36 lr: 9.325570260560237e-06 loss: 0.1053 (0.0815) time: 28.2422 data: 24.7392 max mem: 33303 +Epoch: [33] [3470/4276] eta: 7:48:35 lr: 9.322399556095464e-06 loss: 0.0745 (0.0815) time: 28.8353 data: 25.2572 max mem: 33303 +Epoch: [33] [3480/4276] eta: 7:43:26 lr: 9.319228731802851e-06 loss: 0.0706 (0.0815) time: 40.9569 data: 37.1204 max mem: 33303 +Epoch: [33] [3490/4276] eta: 7:37:20 lr: 9.316057787632573e-06 loss: 0.0754 (0.0815) time: 40.0529 data: 36.2792 max mem: 33303 +Epoch: [33] [3500/4276] eta: 7:31:18 lr: 9.312886723534743e-06 loss: 0.0724 (0.0815) time: 28.3202 data: 24.7276 max mem: 33303 +Epoch: [33] [3510/4276] eta: 7:25:15 lr: 9.309715539459457e-06 loss: 0.0724 (0.0815) time: 28.7447 data: 25.1787 max mem: 33303 +Epoch: [33] [3520/4276] eta: 7:20:04 lr: 9.306544235356763e-06 loss: 0.0753 (0.0815) time: 40.5045 data: 36.6540 max mem: 33303 +Epoch: [33] [3530/4276] eta: 7:14:04 lr: 9.303372811176672e-06 loss: 0.0753 (0.0815) time: 41.2198 data: 37.2778 max mem: 33303 +Epoch: [33] [3540/4276] eta: 7:08:04 lr: 9.300201266869145e-06 loss: 0.0771 (0.0815) time: 29.7309 data: 26.1139 max mem: 33303 +Epoch: [33] [3550/4276] eta: 7:02:02 lr: 9.297029602384115e-06 loss: 0.0800 (0.0815) time: 28.9795 data: 25.4675 max mem: 33303 +Epoch: [33] [3560/4276] eta: 6:56:50 lr: 9.293857817671472e-06 loss: 0.0858 (0.0815) time: 40.9942 data: 37.2726 max mem: 33303 +Epoch: [33] [3570/4276] eta: 6:50:50 lr: 9.290685912681068e-06 loss: 0.0858 (0.0815) time: 41.3522 data: 37.6269 max mem: 33303 +Epoch: [33] [3580/4276] eta: 6:44:48 lr: 9.287513887362706e-06 loss: 0.0755 (0.0815) time: 28.7342 data: 25.2606 max mem: 33303 +Epoch: [33] [3590/4276] eta: 6:38:51 lr: 9.284341741666156e-06 loss: 0.0720 (0.0815) time: 29.4663 data: 25.8927 max mem: 33303 +Epoch: [33] [3600/4276] eta: 6:33:36 lr: 9.281169475541148e-06 loss: 0.0792 (0.0815) time: 41.8468 data: 37.7974 max mem: 33303 +Epoch: [33] [3610/4276] eta: 6:27:37 lr: 9.277997088937379e-06 loss: 0.0792 (0.0815) time: 41.2808 data: 37.1079 max mem: 33303 +Epoch: [33] [3620/4276] eta: 6:21:35 lr: 9.274824581804484e-06 loss: 0.0727 (0.0815) time: 28.8561 data: 25.1748 max mem: 33303 +Epoch: [33] [3630/4276] eta: 6:15:33 lr: 9.271651954092078e-06 loss: 0.0741 (0.0815) time: 27.9469 data: 24.4830 max mem: 33303 +Epoch: [33] [3640/4276] eta: 6:10:22 lr: 9.268479205749731e-06 loss: 0.0775 (0.0814) time: 42.1813 data: 38.4340 max mem: 33303 +Epoch: [33] [3650/4276] eta: 6:04:22 lr: 9.265306336726975e-06 loss: 0.0692 (0.0814) time: 42.5731 data: 38.8451 max mem: 33303 +Epoch: [33] [3660/4276] eta: 5:58:25 lr: 9.262133346973289e-06 loss: 0.0701 (0.0814) time: 29.4576 data: 25.9420 max mem: 33303 +Epoch: [33] [3670/4276] eta: 5:52:25 lr: 9.258960236438124e-06 loss: 0.0777 (0.0814) time: 29.1807 data: 25.6260 max mem: 33303 +Epoch: [33] [3680/4276] eta: 5:47:05 lr: 9.255787005070885e-06 loss: 0.0728 (0.0814) time: 40.4411 data: 36.6139 max mem: 33303 +Epoch: [33] [3690/4276] eta: 5:41:06 lr: 9.25261365282095e-06 loss: 0.0716 (0.0814) time: 40.8040 data: 36.9616 max mem: 33303 +Epoch: [33] [3700/4276] eta: 5:35:06 lr: 9.249440179637627e-06 loss: 0.0878 (0.0814) time: 28.6378 data: 25.0902 max mem: 33303 +Epoch: [33] [3710/4276] eta: 5:29:12 lr: 9.246266585470212e-06 loss: 0.0685 (0.0814) time: 29.9363 data: 26.3414 max mem: 33303 +Epoch: [33] [3720/4276] eta: 5:23:47 lr: 9.243092870267948e-06 loss: 0.0657 (0.0814) time: 41.2448 data: 37.4262 max mem: 33303 +Epoch: [33] [3730/4276] eta: 5:17:48 lr: 9.239919033980046e-06 loss: 0.0799 (0.0814) time: 39.8085 data: 35.9995 max mem: 33303 +Epoch: [33] [3740/4276] eta: 5:11:49 lr: 9.236745076555657e-06 loss: 0.0782 (0.0813) time: 28.3190 data: 24.7876 max mem: 33303 +Epoch: [33] [3750/4276] eta: 5:05:51 lr: 9.23357099794391e-06 loss: 0.0691 (0.0814) time: 28.2920 data: 24.8465 max mem: 33303 +Epoch: [33] [3760/4276] eta: 5:00:28 lr: 9.230396798093894e-06 loss: 0.0684 (0.0813) time: 41.2179 data: 37.4802 max mem: 33303 +Epoch: [33] [3770/4276] eta: 4:54:29 lr: 9.227222476954634e-06 loss: 0.0811 (0.0814) time: 40.5631 data: 36.8061 max mem: 33303 +Epoch: [33] [3780/4276] eta: 4:48:30 lr: 9.224048034475142e-06 loss: 0.0772 (0.0814) time: 27.6168 data: 24.1356 max mem: 33303 +Epoch: [33] [3790/4276] eta: 4:42:35 lr: 9.220873470604371e-06 loss: 0.0749 (0.0814) time: 28.9910 data: 25.4945 max mem: 33303 +slurmstepd-node07: error: *** JOB 5753 ON node07 CANCELLED AT 2025-02-02T19:09:53 *** +slurmstepd-node07: error: *** JOB 5753 STEPD TERMINATED ON node07 AT 2025-02-02T19:10:54 DUE TO JOB NOT ENDING WITH SIGNALS *** +slurmstepd-node07: error: Container 3801075 in cgroup plugin has 2 processes, giving up after 63 sec diff --git a/LAVT-RIS/logs/lavt_refzom_repro_bs32.log b/LAVT-RIS/logs/lavt_refzom_repro_bs32.log new file mode 100644 index 0000000000000000000000000000000000000000..f39474afac27fabc3f9a2b5a29ab5becdb20e6d8 --- /dev/null +++ b/LAVT-RIS/logs/lavt_refzom_repro_bs32.log @@ -0,0 +1,37 @@ +[2025-01-26 08:58:45,699] torch.distributed.run: [WARNING] +[2025-01-26 08:58:45,699] torch.distributed.run: [WARNING] ***************************************** +[2025-01-26 08:58:45,699] torch.distributed.run: [WARNING] Setting OMP_NUM_THREADS environment variable for each process to be 1 in default, to avoid your system being overloaded, please further tune the variable for optimal performance in your application as needed. +[2025-01-26 08:58:45,699] torch.distributed.run: [WARNING] ***************************************** +[W socket.cpp:436] [c10d] The server socket has failed to bind to [::]:7852 (errno: 98 - Address already in use). +[W socket.cpp:436] [c10d] The server socket has failed to bind to 0.0.0.0:7852 (errno: 98 - Address already in use). +[E socket.cpp:472] [c10d] The server socket has failed to listen on any local network address. +Traceback (most recent call last): + File "/home/chaeyun/.conda/envs/risall/bin/torchrun", line 8, in + sys.exit(main()) + File "/home/chaeyun/.conda/envs/risall/lib/python3.9/site-packages/torch/distributed/elastic/multiprocessing/errors/__init__.py", line 346, in wrapper + return f(*args, **kwargs) + File "/home/chaeyun/.conda/envs/risall/lib/python3.9/site-packages/torch/distributed/run.py", line 806, in main + run(args) + File "/home/chaeyun/.conda/envs/risall/lib/python3.9/site-packages/torch/distributed/run.py", line 797, in run + elastic_launch( + File "/home/chaeyun/.conda/envs/risall/lib/python3.9/site-packages/torch/distributed/launcher/api.py", line 134, in __call__ + return launch_agent(self._config, self._entrypoint, list(args)) + File "/home/chaeyun/.conda/envs/risall/lib/python3.9/site-packages/torch/distributed/launcher/api.py", line 255, in launch_agent + result = agent.run() + File "/home/chaeyun/.conda/envs/risall/lib/python3.9/site-packages/torch/distributed/elastic/metrics/api.py", line 124, in wrapper + result = f(*args, **kwargs) + File "/home/chaeyun/.conda/envs/risall/lib/python3.9/site-packages/torch/distributed/elastic/agent/server/api.py", line 736, in run + result = self._invoke_run(role) + File "/home/chaeyun/.conda/envs/risall/lib/python3.9/site-packages/torch/distributed/elastic/agent/server/api.py", line 871, in _invoke_run + self._initialize_workers(self._worker_group) + File "/home/chaeyun/.conda/envs/risall/lib/python3.9/site-packages/torch/distributed/elastic/metrics/api.py", line 124, in wrapper + result = f(*args, **kwargs) + File "/home/chaeyun/.conda/envs/risall/lib/python3.9/site-packages/torch/distributed/elastic/agent/server/api.py", line 705, in _initialize_workers + self._rendezvous(worker_group) + File "/home/chaeyun/.conda/envs/risall/lib/python3.9/site-packages/torch/distributed/elastic/metrics/api.py", line 124, in wrapper + result = f(*args, **kwargs) + File "/home/chaeyun/.conda/envs/risall/lib/python3.9/site-packages/torch/distributed/elastic/agent/server/api.py", line 546, in _rendezvous + store, group_rank, group_world_size = spec.rdzv_handler.next_rendezvous() + File "/home/chaeyun/.conda/envs/risall/lib/python3.9/site-packages/torch/distributed/elastic/rendezvous/static_tcp_rendezvous.py", line 54, in next_rendezvous + self._store = TCPStore( # type: ignore[call-arg] +RuntimeError: The server socket has failed to listen on any local network address. The server socket has failed to bind to [::]:7852 (errno: 98 - Address already in use). The server socket has failed to bind to 0.0.0.0:7852 (errno: 98 - Address already in use). diff --git a/LAVT-RIS/logs/lavt_shbest_mostat.txt b/LAVT-RIS/logs/lavt_shbest_mostat.txt new file mode 100644 index 0000000000000000000000000000000000000000..b5e8c26f84049162c0ee276edcdcb846095f176c --- /dev/null +++ b/LAVT-RIS/logs/lavt_shbest_mostat.txt @@ -0,0 +1,68 @@ +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/timm/models/layers/__init__.py:48: FutureWarning: Importing from timm.models.layers is deprecated, please import via timm.layers + warnings.warn(f"Importing from {__name__} is deprecated, please import via timm.layers", FutureWarning) +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torch/functional.py:478: UserWarning: torch.meshgrid: in an upcoming release, it will be required to pass the indexing argument. (Triggered internally at ../aten/src/ATen/native/TensorShape.cpp:2894.) + return _VF.meshgrid(tensors, **kwargs) # type: ignore[attr-defined] +Image size: 480 +Easy & Hard Example Experiments - dataset : refcocog, split : motion +loading dataset refcocog into memory... +creating index... +index created. +DONE (t=6.33s) +lavt_one +Window size 12! +Randomly initialize Multi-modal Swin Transformer weights. +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/151] eta: 0:08:05 time: 3.2140 data: 0.9841 max mem: 1021 +Test: [100/151] eta: 0:00:05 time: 0.0848 data: 0.0016 max mem: 1021 +Test: Total time: 0:00:16 +Final results: +Mean IoU is 54.43 + + precision@0.5 = 60.93 + precision@0.6 = 58.94 + precision@0.7 = 53.64 + precision@0.8 = 49.01 + precision@0.9 = 29.14 + overall IoU = 48.27 + +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/timm/models/layers/__init__.py:48: FutureWarning: Importing from timm.models.layers is deprecated, please import via timm.layers + warnings.warn(f"Importing from {__name__} is deprecated, please import via timm.layers", FutureWarning) +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torch/functional.py:478: UserWarning: torch.meshgrid: in an upcoming release, it will be required to pass the indexing argument. (Triggered internally at ../aten/src/ATen/native/TensorShape.cpp:2894.) + return _VF.meshgrid(tensors, **kwargs) # type: ignore[attr-defined] +Image size: 480 +Easy & Hard Example Experiments - dataset : refcocog, split : static +loading dataset refcocog into memory... +creating index... +index created. +DONE (t=6.38s) +lavt_one +Window size 12! +Randomly initialize Multi-modal Swin Transformer weights. +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/151] eta: 0:07:47 time: 3.0938 data: 0.8532 max mem: 1021 +Test: [100/151] eta: 0:00:05 time: 0.0853 data: 0.0016 max mem: 1021 +Test: Total time: 0:00:15 +Final results: +Mean IoU is 73.06 + + precision@0.5 = 82.12 + precision@0.6 = 80.79 + precision@0.7 = 75.50 + precision@0.8 = 70.20 + precision@0.9 = 39.07 + overall IoU = 67.73 + diff --git a/LAVT-RIS/logs/lavt_static.txt b/LAVT-RIS/logs/lavt_static.txt new file mode 100644 index 0000000000000000000000000000000000000000..7949e142a6fad53dc566cd13762246271c391781 --- /dev/null +++ b/LAVT-RIS/logs/lavt_static.txt @@ -0,0 +1,34 @@ +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/timm/models/layers/__init__.py:48: FutureWarning: Importing from timm.models.layers is deprecated, please import via timm.layers + warnings.warn(f"Importing from {__name__} is deprecated, please import via timm.layers", FutureWarning) +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torch/functional.py:478: UserWarning: torch.meshgrid: in an upcoming release, it will be required to pass the indexing argument. (Triggered internally at ../aten/src/ATen/native/TensorShape.cpp:2894.) + return _VF.meshgrid(tensors, **kwargs) # type: ignore[attr-defined] +Image size: 480 +Easy & Hard Example Experiments - dataset : refcocog, split : static +loading dataset refcocog into memory... +creating index... +index created. +DONE (t=6.52s) +lavt_one +Window size 12! +Randomly initialize Multi-modal Swin Transformer weights. +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/151] eta: 0:07:58 time: 3.1700 data: 0.9497 max mem: 1021 +Test: [100/151] eta: 0:00:05 time: 0.0856 data: 0.0016 max mem: 1021 +Test: Total time: 0:00:16 +Final results: +Mean IoU is 73.91 + + precision@0.5 = 84.77 + precision@0.6 = 81.46 + precision@0.7 = 75.50 + precision@0.8 = 70.20 + precision@0.9 = 37.09 + overall IoU = 71.75 + diff --git a/LAVT-RIS/logs/lavt_test.txt b/LAVT-RIS/logs/lavt_test.txt new file mode 100644 index 0000000000000000000000000000000000000000..c0115fc3224782126bd70454039373c6ae87d541 --- /dev/null +++ b/LAVT-RIS/logs/lavt_test.txt @@ -0,0 +1,82 @@ +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/timm/models/layers/__init__.py:48: FutureWarning: Importing from timm.models.layers is deprecated, please import via timm.layers + warnings.warn(f"Importing from {__name__} is deprecated, please import via timm.layers", FutureWarning) +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torch/functional.py:478: UserWarning: torch.meshgrid: in an upcoming release, it will be required to pass the indexing argument. (Triggered internally at ../aten/src/ATen/native/TensorShape.cpp:2894.) + return _VF.meshgrid(tensors, **kwargs) # type: ignore[attr-defined] +Image size: 480 +loading dataset refcocog into memory... +creating index... +index created. +DONE (t=6.91s) +lavt_one +Window size 12! +Randomly initialize Multi-modal Swin Transformer weights. +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/5023] eta: 1 day, 11:23:15 time: 25.3624 data: 1.4797 max mem: 1021 +Test: [ 100/5023] eta: 0:33:48 time: 0.1684 data: 0.0016 max mem: 1021 +Test: [ 200/5023] eta: 0:23:03 time: 0.1592 data: 0.0017 max mem: 1021 +Test: [ 300/5023] eta: 0:19:25 time: 0.1644 data: 0.0016 max mem: 1021 +Test: [ 400/5023] eta: 0:17:22 time: 0.1612 data: 0.0017 max mem: 1021 +Test: [ 500/5023] eta: 0:16:03 time: 0.1652 data: 0.0018 max mem: 1021 +Test: [ 600/5023] eta: 0:15:05 time: 0.1696 data: 0.0017 max mem: 1021 +Test: [ 700/5023] eta: 0:14:20 time: 0.1571 data: 0.0017 max mem: 1021 +Test: [ 800/5023] eta: 0:13:43 time: 0.1656 data: 0.0016 max mem: 1021 +Test: [ 900/5023] eta: 0:13:10 time: 0.1706 data: 0.0065 max mem: 1021 +Test: [1000/5023] eta: 0:12:43 time: 0.1676 data: 0.0018 max mem: 1021 +Test: [1100/5023] eta: 0:12:15 time: 0.1624 data: 0.0018 max mem: 1021 +Test: [1200/5023] eta: 0:11:49 time: 0.1668 data: 0.0016 max mem: 1021 +Test: [1300/5023] eta: 0:11:25 time: 0.1618 data: 0.0016 max mem: 1021 +Test: [1400/5023] eta: 0:11:01 time: 0.1540 data: 0.0017 max mem: 1021 +Test: [1500/5023] eta: 0:10:38 time: 0.1667 data: 0.0017 max mem: 1021 +Test: [1600/5023] eta: 0:10:16 time: 0.1638 data: 0.0017 max mem: 1021 +Test: [1700/5023] eta: 0:09:55 time: 0.1625 data: 0.0017 max mem: 1021 +Test: [1800/5023] eta: 0:09:35 time: 0.1670 data: 0.0017 max mem: 1021 +Test: [1900/5023] eta: 0:09:15 time: 0.1800 data: 0.0148 max mem: 1021 +Test: [2000/5023] eta: 0:08:55 time: 0.1717 data: 0.0017 max mem: 1021 +Test: [2100/5023] eta: 0:08:35 time: 0.1545 data: 0.0017 max mem: 1021 +Test: [2200/5023] eta: 0:08:16 time: 0.1496 data: 0.0017 max mem: 1021 +Test: [2300/5023] eta: 0:07:57 time: 0.1710 data: 0.0018 max mem: 1021 +Test: [2400/5023] eta: 0:07:38 time: 0.1629 data: 0.0017 max mem: 1021 +Test: [2500/5023] eta: 0:07:20 time: 0.1680 data: 0.0017 max mem: 1021 +Test: [2600/5023] eta: 0:07:02 time: 0.1635 data: 0.0017 max mem: 1021 +Test: [2700/5023] eta: 0:06:43 time: 0.1665 data: 0.0018 max mem: 1021 +Test: [2800/5023] eta: 0:06:25 time: 0.1665 data: 0.0017 max mem: 1021 +Test: [2900/5023] eta: 0:06:07 time: 0.1705 data: 0.0017 max mem: 1021 +Test: [3000/5023] eta: 0:05:49 time: 0.1665 data: 0.0016 max mem: 1021 +Test: [3100/5023] eta: 0:05:32 time: 0.1715 data: 0.0016 max mem: 1021 +Test: [3200/5023] eta: 0:05:15 time: 0.1609 data: 0.0017 max mem: 1021 +Test: [3300/5023] eta: 0:04:57 time: 0.1610 data: 0.0017 max mem: 1021 +Test: [3400/5023] eta: 0:04:39 time: 0.1459 data: 0.0017 max mem: 1021 +Test: [3500/5023] eta: 0:04:21 time: 0.1573 data: 0.0016 max mem: 1021 +Test: [3600/5023] eta: 0:04:04 time: 0.1657 data: 0.0018 max mem: 1021 +Test: [3700/5023] eta: 0:03:46 time: 0.1691 data: 0.0045 max mem: 1021 +Test: [3800/5023] eta: 0:03:29 time: 0.1700 data: 0.0017 max mem: 1021 +Test: [3900/5023] eta: 0:03:12 time: 0.1571 data: 0.0016 max mem: 1021 +Test: [4000/5023] eta: 0:02:54 time: 0.1535 data: 0.0017 max mem: 1021 +Test: [4100/5023] eta: 0:02:37 time: 0.1576 data: 0.0018 max mem: 1021 +Test: [4200/5023] eta: 0:02:19 time: 0.1623 data: 0.0017 max mem: 1021 +Test: [4300/5023] eta: 0:02:02 time: 0.1656 data: 0.0017 max mem: 1021 +Test: [4400/5023] eta: 0:01:45 time: 0.1578 data: 0.0017 max mem: 1021 +Test: [4500/5023] eta: 0:01:28 time: 0.1532 data: 0.0016 max mem: 1021 +Test: [4600/5023] eta: 0:01:11 time: 0.1494 data: 0.0017 max mem: 1021 +Test: [4700/5023] eta: 0:00:54 time: 0.1659 data: 0.0017 max mem: 1021 +Test: [4800/5023] eta: 0:00:37 time: 0.1613 data: 0.0016 max mem: 1021 +Test: [4900/5023] eta: 0:00:20 time: 0.1614 data: 0.0017 max mem: 1021 +Test: [5000/5023] eta: 0:00:03 time: 0.1661 data: 0.0016 max mem: 1021 +Test: Total time: 0:14:08 +Final results: +Mean IoU is 65.28 + + precision@0.5 = 73.84 + precision@0.6 = 69.06 + precision@0.7 = 62.71 + precision@0.8 = 51.72 + precision@0.9 = 26.82 + overall IoU = 63.68 + diff --git a/LAVT-RIS/logs/lavt_val.txt b/LAVT-RIS/logs/lavt_val.txt new file mode 100644 index 0000000000000000000000000000000000000000..6f16b0f72adaacafca343838855cd7753c39f4c3 --- /dev/null +++ b/LAVT-RIS/logs/lavt_val.txt @@ -0,0 +1,57 @@ +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/timm/models/layers/__init__.py:48: FutureWarning: Importing from timm.models.layers is deprecated, please import via timm.layers + warnings.warn(f"Importing from {__name__} is deprecated, please import via timm.layers", FutureWarning) +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torch/functional.py:478: UserWarning: torch.meshgrid: in an upcoming release, it will be required to pass the indexing argument. (Triggered internally at ../aten/src/ATen/native/TensorShape.cpp:2894.) + return _VF.meshgrid(tensors, **kwargs) # type: ignore[attr-defined] +Image size: 480 +loading dataset refcocog into memory... +creating index... +index created. +DONE (t=6.20s) +lavt_one +Window size 12! +Randomly initialize Multi-modal Swin Transformer weights. +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 2:26:06 time: 3.4071 data: 1.0594 max mem: 1021 +Test: [ 100/2573] eta: 0:07:37 time: 0.1520 data: 0.0016 max mem: 1021 +Test: [ 200/2573] eta: 0:06:48 time: 0.1564 data: 0.0017 max mem: 1021 +Test: [ 300/2573] eta: 0:06:17 time: 0.1611 data: 0.0016 max mem: 1021 +Test: [ 400/2573] eta: 0:06:00 time: 0.2034 data: 0.0425 max mem: 1021 +Test: [ 500/2573] eta: 0:05:41 time: 0.1593 data: 0.0018 max mem: 1021 +Test: [ 600/2573] eta: 0:05:23 time: 0.1594 data: 0.0017 max mem: 1021 +Test: [ 700/2573] eta: 0:05:07 time: 0.1600 data: 0.0018 max mem: 1021 +Test: [ 800/2573] eta: 0:04:50 time: 0.1678 data: 0.0017 max mem: 1021 +Test: [ 900/2573] eta: 0:04:34 time: 0.1776 data: 0.0185 max mem: 1021 +Test: [1000/2573] eta: 0:04:17 time: 0.1601 data: 0.0016 max mem: 1021 +Test: [1100/2573] eta: 0:04:01 time: 0.1609 data: 0.0017 max mem: 1021 +Test: [1200/2573] eta: 0:03:44 time: 0.1612 data: 0.0018 max mem: 1021 +Test: [1300/2573] eta: 0:03:28 time: 0.1606 data: 0.0016 max mem: 1021 +Test: [1400/2573] eta: 0:03:11 time: 0.1571 data: 0.0016 max mem: 1021 +Test: [1500/2573] eta: 0:02:54 time: 0.1613 data: 0.0016 max mem: 1021 +Test: [1600/2573] eta: 0:02:38 time: 0.1695 data: 0.0016 max mem: 1021 +Test: [1700/2573] eta: 0:02:22 time: 0.1571 data: 0.0016 max mem: 1021 +Test: [1800/2573] eta: 0:02:05 time: 0.1648 data: 0.0016 max mem: 1021 +Test: [1900/2573] eta: 0:01:49 time: 0.1569 data: 0.0016 max mem: 1021 +Test: [2000/2573] eta: 0:01:32 time: 0.1615 data: 0.0016 max mem: 1021 +Test: [2100/2573] eta: 0:01:16 time: 0.1647 data: 0.0016 max mem: 1021 +Test: [2200/2573] eta: 0:01:00 time: 0.1645 data: 0.0016 max mem: 1021 +Test: [2300/2573] eta: 0:00:44 time: 0.1654 data: 0.0016 max mem: 1021 +Test: [2400/2573] eta: 0:00:28 time: 0.1522 data: 0.0016 max mem: 1021 +Test: [2500/2573] eta: 0:00:11 time: 0.1620 data: 0.0016 max mem: 1021 +Test: Total time: 0:06:57 +Final results: +Mean IoU is 65.17 + + precision@0.5 = 73.08 + precision@0.6 = 68.28 + precision@0.7 = 61.87 + precision@0.8 = 50.65 + precision@0.9 = 26.04 + overall IoU = 62.64 + diff --git a/LAVT-RIS/logs/old/gref_m10_mg10_tmp007_4gpu_bs32_ang.log b/LAVT-RIS/logs/old/gref_m10_mg10_tmp007_4gpu_bs32_ang.log new file mode 100644 index 0000000000000000000000000000000000000000..1f564fd080a4247ea4005b3c944c761f2668a03e --- /dev/null +++ b/LAVT-RIS/logs/old/gref_m10_mg10_tmp007_4gpu_bs32_ang.log @@ -0,0 +1,12093 @@ +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torch/distributed/launch.py:178: FutureWarning: The module torch.distributed.launch is deprecated +and will be removed in future. Use torchrun. +Note that --use_env is set by default in torchrun. +If your script expects `--local_rank` argument to be set, please +change it to read from `os.environ['LOCAL_RANK']` instead. See +https://pytorch.org/docs/stable/distributed.html#launch-utility for +further instructions + + warnings.warn( +WARNING:torch.distributed.run: +***************************************** +Setting OMP_NUM_THREADS environment variable for each process to be 1 in default, to avoid your system being overloaded, please further tune the variable for optimal performance in your application as needed. +***************************************** +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/timm/models/layers/__init__.py:48: FutureWarning: Importing from timm.models.layers is deprecated, please import via timm.layers + warnings.warn(f"Importing from {__name__} is deprecated, please import via timm.layers", FutureWarning) +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/timm/models/layers/__init__.py:48: FutureWarning: Importing from timm.models.layers is deprecated, please import via timm.layers + warnings.warn(f"Importing from {__name__} is deprecated, please import via timm.layers", FutureWarning) +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/timm/models/layers/__init__.py:48: FutureWarning: Importing from timm.models.layers is deprecated, please import via timm.layers + warnings.warn(f"Importing from {__name__} is deprecated, please import via timm.layers", FutureWarning) +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/timm/models/layers/__init__.py:48: FutureWarning: Importing from timm.models.layers is deprecated, please import via timm.layers + warnings.warn(f"Importing from {__name__} is deprecated, please import via timm.layers", FutureWarning) +RANK and WORLD_SIZE in environment: 0/4 +RANK and WORLD_SIZE in environment: 3/4 +RANK and WORLD_SIZE in environment: 1/4RANK and WORLD_SIZE in environment: 2/4 + +Image size: 480 +loading dataset refcocog into memory... +creating index... +index created. +DONE (t=7.72s) +loading dataset refcocog into memory... +creating index... +index created. +DONE (t=6.87s) +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torch/functional.py:478: UserWarning: torch.meshgrid: in an upcoming release, it will be required to pass the indexing argument. (Triggered internally at ../aten/src/ATen/native/TensorShape.cpp:2894.) + return _VF.meshgrid(tensors, **kwargs) # type: ignore[attr-defined] +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torch/functional.py:478: UserWarning: torch.meshgrid: in an upcoming release, it will be required to pass the indexing argument. (Triggered internally at ../aten/src/ATen/native/TensorShape.cpp:2894.) + return _VF.meshgrid(tensors, **kwargs) # type: ignore[attr-defined] +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torch/functional.py:478: UserWarning: torch.meshgrid: in an upcoming release, it will be required to pass the indexing argument. (Triggered internally at ../aten/src/ATen/native/TensorShape.cpp:2894.) + return _VF.meshgrid(tensors, **kwargs) # type: ignore[attr-defined] +local rank 0 / global rank 0 successfully built train dataset. +lavt_one +Window size 12! +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torch/functional.py:478: UserWarning: torch.meshgrid: in an upcoming release, it will be required to pass the indexing argument. (Triggered internally at ../aten/src/ATen/native/TensorShape.cpp:2894.) + return _VF.meshgrid(tensors, **kwargs) # type: ignore[attr-defined] +Initializing Multi-modal Swin Transformer weights from ./pretrained_weights/swin_base_patch4_window12_384_22k.pth +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [0] [ 0/1319] eta: 6:23:26 lr: 4.9999147080313756e-05 loss: 0.6746 (0.6746) time: 17.4423 data: 3.9795 max mem: 20156 +Epoch: [0] [ 10/1319] eta: 1:38:09 lr: 4.999061779453083e-05 loss: 0.3692 (0.4188) time: 4.4991 data: 0.3724 max mem: 28287 +Epoch: [0] [ 20/1319] eta: 1:24:29 lr: 4.9982088347050674e-05 loss: 0.3382 (0.3696) time: 3.2254 data: 0.0098 max mem: 28288 +Epoch: [0] [ 30/1319] eta: 1:19:49 lr: 4.9973558737839576e-05 loss: 0.2901 (0.3424) time: 3.2851 data: 0.0091 max mem: 31676 +Epoch: [0] [ 40/1319] eta: 1:16:45 lr: 4.9965028966863786e-05 loss: 0.2611 (0.3246) time: 3.2843 data: 0.0103 max mem: 31676 +Epoch: [0] [ 50/1319] eta: 1:14:37 lr: 4.995649903408956e-05 loss: 0.2648 (0.3184) time: 3.2386 data: 0.0100 max mem: 31676 +Epoch: [0] [ 60/1319] eta: 1:13:07 lr: 4.9947968939483133e-05 loss: 0.2978 (0.3229) time: 3.2465 data: 0.0102 max mem: 31676 +Epoch: [0] [ 70/1319] eta: 1:11:55 lr: 4.993943868301072e-05 loss: 0.2978 (0.3153) time: 3.2679 data: 0.0104 max mem: 31676 +Epoch: [0] [ 80/1319] eta: 1:10:48 lr: 4.993090826463852e-05 loss: 0.2609 (0.3081) time: 3.2582 data: 0.0103 max mem: 31676 +Epoch: [0] [ 90/1319] eta: 1:09:57 lr: 4.9922377684332736e-05 loss: 0.2467 (0.3030) time: 3.2724 data: 0.0095 max mem: 31677 +Epoch: [0] [ 100/1319] eta: 1:09:07 lr: 4.991384694205954e-05 loss: 0.2395 (0.2974) time: 3.2938 data: 0.0093 max mem: 31677 +Epoch: [0] [ 110/1319] eta: 1:08:17 lr: 4.990531603778512e-05 loss: 0.2962 (0.3019) time: 3.2709 data: 0.0094 max mem: 31677 +Epoch: [0] [ 120/1319] eta: 1:07:31 lr: 4.98967849714756e-05 loss: 0.2978 (0.2988) time: 3.2615 data: 0.0095 max mem: 31677 +Epoch: [0] [ 130/1319] eta: 1:06:47 lr: 4.988825374309713e-05 loss: 0.2381 (0.2959) time: 3.2688 data: 0.0096 max mem: 31677 +Epoch: [0] [ 140/1319] eta: 1:06:06 lr: 4.987972235261584e-05 loss: 0.2339 (0.2924) time: 3.2735 data: 0.0093 max mem: 31677 +Epoch: [0] [ 150/1319] eta: 1:05:23 lr: 4.987119079999784e-05 loss: 0.2421 (0.2914) time: 3.2648 data: 0.0091 max mem: 31677 +Epoch: [0] [ 160/1319] eta: 1:04:40 lr: 4.986265908520923e-05 loss: 0.2417 (0.2877) time: 3.2344 data: 0.0091 max mem: 31677 +Epoch: [0] [ 170/1319] eta: 1:03:59 lr: 4.985412720821609e-05 loss: 0.2358 (0.2869) time: 3.2269 data: 0.0092 max mem: 31677 +Epoch: [0] [ 180/1319] eta: 1:03:21 lr: 4.984559516898449e-05 loss: 0.2358 (0.2836) time: 3.2530 data: 0.0089 max mem: 31677 +Epoch: [0] [ 190/1319] eta: 1:02:44 lr: 4.98370629674805e-05 loss: 0.2433 (0.2826) time: 3.2713 data: 0.0087 max mem: 31677 +Epoch: [0] [ 200/1319] eta: 1:02:15 lr: 4.982853060367015e-05 loss: 0.2531 (0.2807) time: 3.3456 data: 0.0098 max mem: 31677 +Epoch: [0] [ 210/1319] eta: 1:01:43 lr: 4.9819998077519475e-05 loss: 0.2235 (0.2795) time: 3.3951 data: 0.0108 max mem: 31677 +Epoch: [0] [ 220/1319] eta: 1:01:12 lr: 4.98114653889945e-05 loss: 0.2092 (0.2767) time: 3.3762 data: 0.0111 max mem: 31677 +Epoch: [0] [ 230/1319] eta: 1:00:47 lr: 4.980293253806122e-05 loss: 0.2241 (0.2756) time: 3.4512 data: 0.0107 max mem: 31677 +Epoch: [0] [ 240/1319] eta: 1:00:11 lr: 4.9794399524685624e-05 loss: 0.2362 (0.2743) time: 3.4120 data: 0.0099 max mem: 31677 +Epoch: [0] [ 250/1319] eta: 0:59:35 lr: 4.97858663488337e-05 loss: 0.2228 (0.2722) time: 3.2934 data: 0.0099 max mem: 31677 +Epoch: [0] [ 260/1319] eta: 0:59:00 lr: 4.977733301047139e-05 loss: 0.2203 (0.2699) time: 3.2970 data: 0.0096 max mem: 33369 +Epoch: [0] [ 270/1319] eta: 0:58:25 lr: 4.9768799509564675e-05 loss: 0.2232 (0.2695) time: 3.3028 data: 0.0089 max mem: 33369 +Epoch: [0] [ 280/1319] eta: 0:57:50 lr: 4.976026584607946e-05 loss: 0.2346 (0.2678) time: 3.2961 data: 0.0093 max mem: 33369 +Epoch: [0] [ 290/1319] eta: 0:57:15 lr: 4.9751732019981684e-05 loss: 0.2363 (0.2679) time: 3.2956 data: 0.0095 max mem: 33369 +Epoch: [0] [ 300/1319] eta: 0:56:40 lr: 4.974319803123725e-05 loss: 0.2472 (0.2678) time: 3.2887 data: 0.0087 max mem: 33369 +Epoch: [0] [ 310/1319] eta: 0:56:05 lr: 4.973466387981205e-05 loss: 0.2595 (0.2684) time: 3.2935 data: 0.0090 max mem: 33369 +Epoch: [0] [ 320/1319] eta: 0:55:31 lr: 4.972612956567197e-05 loss: 0.2595 (0.2674) time: 3.3014 data: 0.0092 max mem: 33369 +Epoch: [0] [ 330/1319] eta: 0:54:51 lr: 4.971759508878288e-05 loss: 0.2182 (0.2664) time: 3.2137 data: 0.0087 max mem: 33369 +Epoch: [0] [ 340/1319] eta: 0:54:16 lr: 4.970906044911062e-05 loss: 0.2191 (0.2663) time: 3.2005 data: 0.0090 max mem: 33369 +Epoch: [0] [ 350/1319] eta: 0:53:42 lr: 4.970052564662105e-05 loss: 0.2355 (0.2654) time: 3.2688 data: 0.0095 max mem: 33369 +Epoch: [0] [ 360/1319] eta: 0:53:08 lr: 4.9691990681279974e-05 loss: 0.2033 (0.2641) time: 3.2904 data: 0.0093 max mem: 33369 +Epoch: [0] [ 370/1319] eta: 0:52:35 lr: 4.9683455553053225e-05 loss: 0.2195 (0.2635) time: 3.3154 data: 0.0089 max mem: 33369 +Epoch: [0] [ 380/1319] eta: 0:52:00 lr: 4.9674920261906595e-05 loss: 0.2068 (0.2622) time: 3.2973 data: 0.0090 max mem: 33369 +Epoch: [0] [ 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3.2788 data: 0.0100 max mem: 33369 +Epoch: [0] [ 710/1319] eta: 0:33:35 lr: 4.939316403135663e-05 loss: 0.2195 (0.2462) time: 3.3439 data: 0.0103 max mem: 33369 +Epoch: [0] [ 720/1319] eta: 0:33:02 lr: 4.938462318048596e-05 loss: 0.2195 (0.2456) time: 3.3357 data: 0.0094 max mem: 33369 +Epoch: [0] [ 730/1319] eta: 0:32:28 lr: 4.937608216548967e-05 loss: 0.1947 (0.2448) time: 3.2774 data: 0.0090 max mem: 33369 +Epoch: [0] [ 740/1319] eta: 0:31:55 lr: 4.936754098633307e-05 loss: 0.1942 (0.2448) time: 3.2636 data: 0.0095 max mem: 33369 +Epoch: [0] [ 750/1319] eta: 0:31:21 lr: 4.935899964298143e-05 loss: 0.1929 (0.2441) time: 3.2852 data: 0.0099 max mem: 33369 +Epoch: [0] [ 760/1319] eta: 0:30:48 lr: 4.9350458135400046e-05 loss: 0.1768 (0.2436) time: 3.2731 data: 0.0103 max mem: 33369 +Epoch: [0] [ 770/1319] eta: 0:30:15 lr: 4.934191646355415e-05 loss: 0.2072 (0.2435) time: 3.2616 data: 0.0100 max mem: 33369 +Epoch: [0] [ 780/1319] eta: 0:29:41 lr: 4.9333374627409e-05 loss: 0.2159 (0.2432) time: 3.2738 data: 0.0102 max mem: 33369 +Epoch: [0] [ 790/1319] eta: 0:29:08 lr: 4.932483262692982e-05 loss: 0.2081 (0.2428) time: 3.2875 data: 0.0100 max mem: 33369 +Epoch: [0] [ 800/1319] eta: 0:28:36 lr: 4.931629046208183e-05 loss: 0.1985 (0.2423) time: 3.3649 data: 0.0093 max mem: 33369 +Epoch: [0] [ 810/1319] eta: 0:28:03 lr: 4.9307748132830237e-05 loss: 0.2124 (0.2421) time: 3.3727 data: 0.0095 max mem: 33369 +Epoch: [0] [ 820/1319] eta: 0:27:30 lr: 4.929920563914022e-05 loss: 0.2207 (0.2419) time: 3.3274 data: 0.0095 max mem: 33369 +Epoch: [0] [ 830/1319] eta: 0:26:57 lr: 4.929066298097696e-05 loss: 0.2100 (0.2416) time: 3.2936 data: 0.0089 max mem: 33369 +Epoch: [0] [ 840/1319] eta: 0:26:24 lr: 4.928212015830561e-05 loss: 0.1919 (0.2410) time: 3.2805 data: 0.0089 max mem: 33369 +Epoch: [0] [ 850/1319] eta: 0:25:51 lr: 4.927357717109131e-05 loss: 0.1891 (0.2406) time: 3.3138 data: 0.0084 max mem: 33369 +Epoch: [0] [ 860/1319] eta: 0:25:17 lr: 4.926503401929921e-05 loss: 0.1955 (0.2404) time: 3.2880 data: 0.0088 max mem: 33369 +Epoch: [0] [ 870/1319] eta: 0:24:44 lr: 4.925649070289441e-05 loss: 0.2211 (0.2402) time: 3.2752 data: 0.0096 max mem: 33369 +Epoch: [0] [ 880/1319] eta: 0:24:11 lr: 4.9247947221842024e-05 loss: 0.2215 (0.2400) time: 3.2664 data: 0.0096 max mem: 33369 +Epoch: [0] [ 890/1319] eta: 0:23:38 lr: 4.923940357610714e-05 loss: 0.1966 (0.2395) time: 3.2614 data: 0.0101 max mem: 33369 +Epoch: [0] [ 900/1319] eta: 0:23:05 lr: 4.9230859765654824e-05 loss: 0.1798 (0.2390) time: 3.3014 data: 0.0099 max mem: 33369 +Epoch: [0] [ 910/1319] eta: 0:22:31 lr: 4.922231579045014e-05 loss: 0.1787 (0.2383) time: 3.2852 data: 0.0099 max mem: 33369 +Epoch: [0] [ 920/1319] eta: 0:21:58 lr: 4.921377165045815e-05 loss: 0.1818 (0.2381) time: 3.2782 data: 0.0103 max mem: 33369 +Epoch: [0] [ 930/1319] eta: 0:21:25 lr: 4.9205227345643864e-05 loss: 0.2073 (0.2378) time: 3.3317 data: 0.0097 max mem: 33369 +Epoch: [0] [ 940/1319] eta: 0:20:52 lr: 4.919668287597232e-05 loss: 0.1887 (0.2378) time: 3.3232 data: 0.0097 max mem: 33369 +Epoch: [0] [ 950/1319] eta: 0:20:19 lr: 4.918813824140851e-05 loss: 0.1952 (0.2375) time: 3.2750 data: 0.0093 max mem: 33369 +Epoch: [0] [ 960/1319] eta: 0:19:46 lr: 4.9179593441917424e-05 loss: 0.1907 (0.2369) time: 3.2577 data: 0.0091 max mem: 33369 +Epoch: [0] [ 970/1319] eta: 0:19:13 lr: 4.917104847746404e-05 loss: 0.1763 (0.2363) time: 3.2609 data: 0.0092 max mem: 33369 +Epoch: [0] [ 980/1319] eta: 0:18:39 lr: 4.916250334801333e-05 loss: 0.1899 (0.2361) time: 3.2595 data: 0.0086 max mem: 33369 +Epoch: [0] [ 990/1319] eta: 0:18:06 lr: 4.915395805353022e-05 loss: 0.1917 (0.2356) time: 3.2744 data: 0.0090 max mem: 33369 +Epoch: [0] [1000/1319] eta: 0:17:33 lr: 4.9145412593979664e-05 loss: 0.1865 (0.2353) time: 3.3031 data: 0.0092 max mem: 33369 +Epoch: [0] [1010/1319] eta: 0:17:01 lr: 4.913686696932656e-05 loss: 0.1957 (0.2350) time: 3.3456 data: 0.0098 max mem: 33369 +Epoch: [0] [1020/1319] eta: 0:16:28 lr: 4.9128321179535836e-05 loss: 0.1857 (0.2345) time: 3.3825 data: 0.0105 max mem: 33369 +Epoch: [0] [1030/1319] eta: 0:15:55 lr: 4.911977522457237e-05 loss: 0.1852 (0.2342) time: 3.3886 data: 0.0108 max mem: 33369 +Epoch: [0] [1040/1319] eta: 0:15:22 lr: 4.9111229104401044e-05 loss: 0.1931 (0.2340) time: 3.3616 data: 0.0104 max mem: 33369 +Epoch: [0] [1050/1319] eta: 0:14:49 lr: 4.910268281898671e-05 loss: 0.1852 (0.2339) time: 3.2938 data: 0.0100 max mem: 33369 +Epoch: [0] [1060/1319] eta: 0:14:16 lr: 4.9094136368294215e-05 loss: 0.2047 (0.2337) time: 3.2456 data: 0.0096 max mem: 33369 +Epoch: [0] [1070/1319] eta: 0:13:42 lr: 4.90855897522884e-05 loss: 0.1928 (0.2334) time: 3.2616 data: 0.0092 max mem: 33369 +Epoch: [0] [1080/1319] eta: 0:13:09 lr: 4.907704297093409e-05 loss: 0.1803 (0.2329) time: 3.2798 data: 0.0091 max mem: 33369 +Epoch: [0] [1090/1319] eta: 0:12:36 lr: 4.906849602419608e-05 loss: 0.1852 (0.2327) time: 3.2650 data: 0.0091 max mem: 33369 +Epoch: [0] [1100/1319] eta: 0:12:03 lr: 4.905994891203916e-05 loss: 0.1946 (0.2327) time: 3.2645 data: 0.0103 max mem: 33369 +Epoch: [0] [1110/1319] eta: 0:11:30 lr: 4.905140163442811e-05 loss: 0.2049 (0.2324) time: 3.3049 data: 0.0113 max mem: 33369 +Epoch: [0] [1120/1319] eta: 0:10:57 lr: 4.904285419132769e-05 loss: 0.1923 (0.2323) time: 3.2943 data: 0.0108 max mem: 33369 +Epoch: [0] [1130/1319] eta: 0:10:24 lr: 4.903430658270266e-05 loss: 0.1885 (0.2320) time: 3.2887 data: 0.0103 max mem: 33369 +Epoch: [0] [1140/1319] eta: 0:09:51 lr: 4.902575880851773e-05 loss: 0.1820 (0.2317) time: 3.3422 data: 0.0103 max mem: 33369 +Epoch: [0] [1150/1319] eta: 0:09:18 lr: 4.9017210868737634e-05 loss: 0.1728 (0.2313) time: 3.3457 data: 0.0104 max mem: 33369 +Epoch: [0] [1160/1319] eta: 0:08:45 lr: 4.900866276332707e-05 loss: 0.1725 (0.2309) time: 3.3255 data: 0.0107 max mem: 33369 +Epoch: [0] [1170/1319] eta: 0:08:12 lr: 4.9000114492250734e-05 loss: 0.1710 (0.2306) time: 3.3468 data: 0.0106 max mem: 33369 +Epoch: [0] [1180/1319] eta: 0:07:39 lr: 4.8991566055473306e-05 loss: 0.1701 (0.2301) time: 3.3359 data: 0.0105 max mem: 33369 +Epoch: [0] [1190/1319] eta: 0:07:06 lr: 4.8983017452959435e-05 loss: 0.1701 (0.2299) time: 3.2910 data: 0.0103 max mem: 33369 +Epoch: [0] [1200/1319] eta: 0:06:33 lr: 4.8974468684673776e-05 loss: 0.2122 (0.2299) time: 3.3156 data: 0.0100 max mem: 33369 +Epoch: [0] [1210/1319] eta: 0:06:00 lr: 4.896591975058095e-05 loss: 0.1948 (0.2294) time: 3.3527 data: 0.0110 max mem: 33369 +Epoch: [0] [1220/1319] eta: 0:05:27 lr: 4.89573706506456e-05 loss: 0.1662 (0.2292) time: 3.3461 data: 0.0116 max mem: 33369 +Epoch: [0] [1230/1319] eta: 0:04:54 lr: 4.89488213848323e-05 loss: 0.1816 (0.2290) time: 3.3621 data: 0.0101 max mem: 33369 +Epoch: [0] [1240/1319] eta: 0:04:21 lr: 4.894027195310566e-05 loss: 0.1786 (0.2287) time: 3.3744 data: 0.0097 max mem: 33369 +Epoch: [0] [1250/1319] eta: 0:03:48 lr: 4.893172235543025e-05 loss: 0.1809 (0.2285) time: 3.3657 data: 0.0100 max mem: 33369 +Epoch: [0] [1260/1319] eta: 0:03:15 lr: 4.892317259177062e-05 loss: 0.1964 (0.2286) time: 3.3544 data: 0.0095 max mem: 33369 +Epoch: [0] [1270/1319] eta: 0:02:42 lr: 4.8914622662091334e-05 loss: 0.1964 (0.2283) time: 3.3477 data: 0.0103 max mem: 33369 +Epoch: [0] [1280/1319] eta: 0:02:09 lr: 4.890607256635692e-05 loss: 0.1891 (0.2282) time: 3.3471 data: 0.0113 max mem: 33369 +Epoch: [0] [1290/1319] eta: 0:01:35 lr: 4.8897522304531876e-05 loss: 0.2017 (0.2279) time: 3.3360 data: 0.0115 max mem: 33369 +Epoch: [0] [1300/1319] eta: 0:01:02 lr: 4.888897187658072e-05 loss: 0.1780 (0.2275) time: 3.3214 data: 0.0114 max mem: 33369 +Epoch: [0] [1310/1319] eta: 0:00:29 lr: 4.888042128246795e-05 loss: 0.1789 (0.2273) time: 3.3267 data: 0.0103 max mem: 33369 +Epoch: [0] Total time: 1:12:46 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 2:46:17 time: 3.8778 data: 3.6704 max mem: 33369 +Test: [ 100/2573] eta: 0:04:58 time: 0.0826 data: 0.0017 max mem: 33369 +Test: [ 200/2573] eta: 0:04:01 time: 0.0827 data: 0.0016 max mem: 33369 +Test: [ 300/2573] eta: 0:03:36 time: 0.0850 data: 0.0016 max mem: 33369 +Test: [ 400/2573] eta: 0:03:19 time: 0.0837 data: 0.0017 max mem: 33369 +Test: [ 500/2573] eta: 0:03:07 time: 0.0857 data: 0.0020 max mem: 33369 +Test: [ 600/2573] eta: 0:02:55 time: 0.0826 data: 0.0018 max mem: 33369 +Test: [ 700/2573] eta: 0:02:45 time: 0.0828 data: 0.0019 max mem: 33369 +Test: [ 800/2573] eta: 0:02:36 time: 0.0870 data: 0.0019 max mem: 33369 +Test: [ 900/2573] eta: 0:02:26 time: 0.0828 data: 0.0019 max mem: 33369 +Test: [1000/2573] eta: 0:02:17 time: 0.0826 data: 0.0017 max mem: 33369 +Test: [1100/2573] eta: 0:02:08 time: 0.0835 data: 0.0017 max mem: 33369 +Test: [1200/2573] eta: 0:01:59 time: 0.0839 data: 0.0015 max mem: 33369 +Test: [1300/2573] eta: 0:01:50 time: 0.0822 data: 0.0016 max mem: 33369 +Test: [1400/2573] eta: 0:01:41 time: 0.0804 data: 0.0017 max mem: 33369 +Test: [1500/2573] eta: 0:01:32 time: 0.0834 data: 0.0016 max mem: 33369 +Test: [1600/2573] eta: 0:01:23 time: 0.0866 data: 0.0017 max mem: 33369 +Test: [1700/2573] eta: 0:01:14 time: 0.0821 data: 0.0016 max mem: 33369 +Test: [1800/2573] eta: 0:01:06 time: 0.0856 data: 0.0017 max mem: 33369 +Test: [1900/2573] eta: 0:00:57 time: 0.0822 data: 0.0016 max mem: 33369 +Test: [2000/2573] eta: 0:00:48 time: 0.0839 data: 0.0019 max mem: 33369 +Test: [2100/2573] eta: 0:00:40 time: 0.0900 data: 0.0022 max mem: 33369 +Test: [2200/2573] eta: 0:00:31 time: 0.0893 data: 0.0021 max mem: 33369 +Test: [2300/2573] eta: 0:00:23 time: 0.0829 data: 0.0017 max mem: 33369 +Test: [2400/2573] eta: 0:00:14 time: 0.0838 data: 0.0020 max mem: 33369 +Test: [2500/2573] eta: 0:00:06 time: 0.0840 data: 0.0018 max mem: 33369 +Test: Total time: 0:03:40 +Final results: +Mean IoU is 25.75 + + precision@0.5 = 24.37 + precision@0.6 = 17.75 + precision@0.7 = 11.38 + precision@0.8 = 6.11 + precision@0.9 = 1.21 + overall IoU = 31.96 + +Average object IoU 25.746404771785304 +Overall IoU 31.959535598754883 +Better epoch: 0 + +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [1] [ 0/1319] eta: 3:04:24 lr: 4.8872725605668895e-05 loss: 0.1856 (0.1856) time: 8.3885 data: 2.0262 max mem: 33369 +Epoch: [1] [ 10/1319] eta: 1:23:25 lr: 4.886417469575114e-05 loss: 0.1957 (0.1974) time: 3.8242 data: 0.1924 max mem: 33369 +Epoch: [1] [ 20/1319] eta: 1:18:08 lr: 4.88556236195687e-05 loss: 0.1847 (0.1848) time: 3.3703 data: 0.0100 max mem: 33369 +Epoch: [1] [ 30/1319] eta: 1:15:34 lr: 4.884707237708599e-05 loss: 0.1805 (0.1887) time: 3.3500 data: 0.0109 max mem: 33369 +Epoch: [1] [ 40/1319] eta: 1:13:41 lr: 4.883852096826744e-05 loss: 0.1879 (0.1922) time: 3.2978 data: 0.0102 max mem: 33369 +Epoch: [1] [ 50/1319] eta: 1:12:37 lr: 4.882996939307746e-05 loss: 0.1997 (0.1950) time: 3.3038 data: 0.0107 max mem: 33369 +Epoch: [1] [ 60/1319] eta: 1:11:55 lr: 4.882141765148041e-05 loss: 0.1951 (0.1940) time: 3.3666 data: 0.0114 max mem: 33369 +Epoch: [1] [ 70/1319] eta: 1:10:58 lr: 4.881286574344069e-05 loss: 0.1684 (0.1884) time: 3.3456 data: 0.0111 max mem: 33369 +Epoch: [1] [ 80/1319] eta: 1:10:16 lr: 4.8804313668922646e-05 loss: 0.1622 (0.1901) time: 3.3292 data: 0.0114 max mem: 33369 +Epoch: [1] [ 90/1319] eta: 1:09:43 lr: 4.879576142789063e-05 loss: 0.1667 (0.1885) time: 3.3859 data: 0.0113 max mem: 33369 +Epoch: [1] [ 100/1319] eta: 1:09:07 lr: 4.878720902030896e-05 loss: 0.1667 (0.1885) time: 3.3983 data: 0.0111 max mem: 33369 +Epoch: [1] [ 110/1319] eta: 1:08:26 lr: 4.877865644614197e-05 loss: 0.1719 (0.1871) time: 3.3617 data: 0.0105 max mem: 33369 +Epoch: [1] [ 120/1319] eta: 1:07:45 lr: 4.877010370535394e-05 loss: 0.1744 (0.1887) time: 3.3331 data: 0.0105 max mem: 33369 +Epoch: [1] [ 130/1319] eta: 1:07:09 lr: 4.8761550797909164e-05 loss: 0.1817 (0.1880) time: 3.3466 data: 0.0112 max mem: 33369 +Epoch: [1] [ 140/1319] eta: 1:06:29 lr: 4.875299772377192e-05 loss: 0.1810 (0.1875) time: 3.3430 data: 0.0112 max mem: 33369 +Epoch: [1] [ 150/1319] eta: 1:05:54 lr: 4.874444448290645e-05 loss: 0.1810 (0.1874) time: 3.3424 data: 0.0115 max mem: 33369 +Epoch: [1] [ 160/1319] eta: 1:05:18 lr: 4.873589107527701e-05 loss: 0.1749 (0.1866) time: 3.3556 data: 0.0111 max mem: 33369 +Epoch: [1] [ 170/1319] eta: 1:04:43 lr: 4.872733750084782e-05 loss: 0.1766 (0.1863) time: 3.3573 data: 0.0102 max mem: 33369 +Epoch: [1] [ 180/1319] eta: 1:04:07 lr: 4.871878375958309e-05 loss: 0.1819 (0.1866) time: 3.3599 data: 0.0104 max mem: 33369 +Epoch: [1] [ 190/1319] eta: 1:03:32 lr: 4.871022985144703e-05 loss: 0.1772 (0.1865) time: 3.3538 data: 0.0109 max mem: 33369 +Epoch: [1] [ 200/1319] eta: 1:02:57 lr: 4.870167577640381e-05 loss: 0.1845 (0.1880) time: 3.3536 data: 0.0102 max mem: 33369 +Epoch: [1] [ 210/1319] eta: 1:02:21 lr: 4.869312153441761e-05 loss: 0.1828 (0.1882) time: 3.3428 data: 0.0101 max mem: 33369 +Epoch: [1] [ 220/1319] eta: 1:01:46 lr: 4.868456712545258e-05 loss: 0.1633 (0.1890) time: 3.3391 data: 0.0108 max mem: 33369 +Epoch: [1] [ 230/1319] eta: 1:01:10 lr: 4.8676012549472854e-05 loss: 0.1769 (0.1883) time: 3.3408 data: 0.0105 max mem: 33369 +Epoch: [1] [ 240/1319] eta: 1:00:34 lr: 4.866745780644256e-05 loss: 0.1664 (0.1874) time: 3.3260 data: 0.0107 max mem: 33369 +Epoch: [1] [ 250/1319] eta: 0:59:59 lr: 4.865890289632581e-05 loss: 0.1676 (0.1874) time: 3.3258 data: 0.0112 max mem: 33369 +Epoch: [1] [ 260/1319] eta: 0:59:27 lr: 4.8650347819086694e-05 loss: 0.1809 (0.1870) time: 3.3643 data: 0.0106 max mem: 33369 +Epoch: [1] [ 270/1319] eta: 0:58:51 lr: 4.864179257468931e-05 loss: 0.1685 (0.1869) time: 3.3608 data: 0.0103 max mem: 33369 +Epoch: [1] [ 280/1319] eta: 0:58:20 lr: 4.8633237163097687e-05 loss: 0.1772 (0.1871) time: 3.3811 data: 0.0110 max mem: 33369 +Epoch: [1] [ 290/1319] eta: 0:57:44 lr: 4.862468158427592e-05 loss: 0.1708 (0.1872) time: 3.3664 data: 0.0117 max mem: 33369 +Epoch: [1] [ 300/1319] eta: 0:57:10 lr: 4.861612583818801e-05 loss: 0.1663 (0.1878) time: 3.3243 data: 0.0114 max mem: 33369 +Epoch: [1] [ 310/1319] eta: 0:56:34 lr: 4.860756992479799e-05 loss: 0.1694 (0.1881) time: 3.3273 data: 0.0103 max mem: 33369 +Epoch: [1] [ 320/1319] eta: 0:56:01 lr: 4.859901384406988e-05 loss: 0.1862 (0.1880) time: 3.3481 data: 0.0100 max mem: 33369 +Epoch: [1] [ 330/1319] eta: 0:55:28 lr: 4.8590457595967656e-05 loss: 0.1862 (0.1884) time: 3.3822 data: 0.0100 max mem: 33369 +Epoch: [1] [ 340/1319] eta: 0:54:51 lr: 4.85819011804553e-05 loss: 0.1711 (0.1877) time: 3.3105 data: 0.0106 max mem: 33369 +Epoch: [1] [ 350/1319] eta: 0:54:16 lr: 4.8573344597496775e-05 loss: 0.1632 (0.1875) time: 3.2854 data: 0.0117 max mem: 33369 +Epoch: [1] [ 360/1319] eta: 0:53:42 lr: 4.856478784705602e-05 loss: 0.1578 (0.1875) time: 3.3276 data: 0.0121 max mem: 33369 +Epoch: [1] [ 370/1319] eta: 0:53:09 lr: 4.8556230929096985e-05 loss: 0.1953 (0.1883) time: 3.3544 data: 0.0123 max mem: 33369 +Epoch: [1] [ 380/1319] eta: 0:52:35 lr: 4.854767384358357e-05 loss: 0.1861 (0.1881) time: 3.3688 data: 0.0111 max mem: 33369 +Epoch: [1] [ 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3.3610 data: 0.0109 max mem: 33369 +Epoch: [1] [ 710/1319] eta: 0:34:08 lr: 4.826519578660238e-05 loss: 0.1625 (0.1846) time: 3.4021 data: 0.0116 max mem: 33369 +Epoch: [1] [ 720/1319] eta: 0:33:34 lr: 4.825663298266489e-05 loss: 0.1783 (0.1846) time: 3.3351 data: 0.0127 max mem: 33369 +Epoch: [1] [ 730/1319] eta: 0:33:00 lr: 4.824807000990074e-05 loss: 0.1658 (0.1843) time: 3.3208 data: 0.0124 max mem: 33369 +Epoch: [1] [ 740/1319] eta: 0:32:27 lr: 4.82395068682733e-05 loss: 0.1548 (0.1842) time: 3.3701 data: 0.0117 max mem: 33369 +Epoch: [1] [ 750/1319] eta: 0:31:53 lr: 4.823094355774595e-05 loss: 0.1596 (0.1844) time: 3.3685 data: 0.0114 max mem: 33369 +Epoch: [1] [ 760/1319] eta: 0:31:19 lr: 4.822238007828201e-05 loss: 0.1670 (0.1844) time: 3.3583 data: 0.0117 max mem: 33369 +Epoch: [1] [ 770/1319] eta: 0:30:46 lr: 4.8213816429844826e-05 loss: 0.1670 (0.1841) time: 3.3881 data: 0.0112 max mem: 33369 +Epoch: [1] [ 780/1319] eta: 0:30:13 lr: 4.8205252612397726e-05 loss: 0.1605 (0.1837) time: 3.4184 data: 0.0118 max mem: 33369 +Epoch: [1] [ 790/1319] eta: 0:29:39 lr: 4.8196688625903984e-05 loss: 0.1452 (0.1837) time: 3.3866 data: 0.0116 max mem: 33369 +Epoch: [1] [ 800/1319] eta: 0:29:05 lr: 4.8188124470326915e-05 loss: 0.1434 (0.1834) time: 3.3656 data: 0.0114 max mem: 33369 +Epoch: [1] [ 810/1319] eta: 0:28:32 lr: 4.8179560145629784e-05 loss: 0.1605 (0.1834) time: 3.3584 data: 0.0116 max mem: 33369 +Epoch: [1] [ 820/1319] eta: 0:27:58 lr: 4.817099565177583e-05 loss: 0.1744 (0.1834) time: 3.3393 data: 0.0109 max mem: 33369 +Epoch: [1] [ 830/1319] eta: 0:27:24 lr: 4.8162430988728305e-05 loss: 0.1772 (0.1836) time: 3.3571 data: 0.0117 max mem: 33369 +Epoch: [1] [ 840/1319] eta: 0:26:51 lr: 4.815386615645044e-05 loss: 0.1605 (0.1832) time: 3.3723 data: 0.0118 max mem: 33369 +Epoch: [1] [ 850/1319] eta: 0:26:17 lr: 4.814530115490545e-05 loss: 0.1525 (0.1832) time: 3.3800 data: 0.0107 max mem: 33369 +Epoch: [1] [ 860/1319] eta: 0:25:43 lr: 4.813673598405651e-05 loss: 0.1649 (0.1829) time: 3.3509 data: 0.0099 max mem: 33369 +Epoch: [1] [ 870/1319] eta: 0:25:09 lr: 4.812817064386682e-05 loss: 0.1649 (0.1829) time: 3.3132 data: 0.0103 max mem: 33369 +Epoch: [1] [ 880/1319] eta: 0:24:36 lr: 4.8119605134299526e-05 loss: 0.1685 (0.1828) time: 3.3341 data: 0.0105 max mem: 33369 +Epoch: [1] [ 890/1319] eta: 0:24:02 lr: 4.81110394553178e-05 loss: 0.1670 (0.1825) time: 3.3201 data: 0.0101 max mem: 33369 +Epoch: [1] [ 900/1319] eta: 0:23:28 lr: 4.810247360688475e-05 loss: 0.1556 (0.1823) time: 3.3004 data: 0.0105 max mem: 33369 +Epoch: [1] [ 910/1319] eta: 0:22:54 lr: 4.809390758896352e-05 loss: 0.1454 (0.1819) time: 3.3428 data: 0.0104 max mem: 33369 +Epoch: [1] [ 920/1319] eta: 0:22:21 lr: 4.808534140151719e-05 loss: 0.1568 (0.1820) time: 3.3778 data: 0.0108 max mem: 33369 +Epoch: [1] [ 930/1319] eta: 0:21:47 lr: 4.807677504450886e-05 loss: 0.1655 (0.1820) time: 3.3885 data: 0.0114 max mem: 33369 +Epoch: [1] [ 940/1319] eta: 0:21:14 lr: 4.806820851790161e-05 loss: 0.1655 (0.1820) time: 3.3758 data: 0.0115 max mem: 33369 +Epoch: [1] [ 950/1319] eta: 0:20:40 lr: 4.805964182165848e-05 loss: 0.1666 (0.1819) time: 3.3758 data: 0.0117 max mem: 33369 +Epoch: [1] [ 960/1319] eta: 0:20:06 lr: 4.8051074955742525e-05 loss: 0.1543 (0.1816) time: 3.3640 data: 0.0119 max mem: 33369 +Epoch: [1] [ 970/1319] eta: 0:19:33 lr: 4.804250792011677e-05 loss: 0.1686 (0.1818) time: 3.3672 data: 0.0113 max mem: 33369 +Epoch: [1] [ 980/1319] eta: 0:18:59 lr: 4.803394071474422e-05 loss: 0.1778 (0.1820) time: 3.3939 data: 0.0109 max mem: 33369 +Epoch: [1] [ 990/1319] eta: 0:18:26 lr: 4.802537333958788e-05 loss: 0.1664 (0.1819) time: 3.4070 data: 0.0114 max mem: 33369 +Epoch: [1] [1000/1319] eta: 0:17:53 lr: 4.801680579461071e-05 loss: 0.1836 (0.1821) time: 3.4148 data: 0.0112 max mem: 33369 +Epoch: [1] [1010/1319] eta: 0:17:19 lr: 4.80082380797757e-05 loss: 0.1880 (0.1821) time: 3.3894 data: 0.0109 max mem: 33369 +Epoch: [1] [1020/1319] eta: 0:16:45 lr: 4.79996701950458e-05 loss: 0.1896 (0.1824) time: 3.3562 data: 0.0109 max mem: 33369 +Epoch: [1] [1030/1319] eta: 0:16:12 lr: 4.799110214038392e-05 loss: 0.1923 (0.1824) time: 3.3428 data: 0.0107 max mem: 33369 +Epoch: [1] [1040/1319] eta: 0:15:38 lr: 4.7982533915752995e-05 loss: 0.1945 (0.1825) time: 3.3521 data: 0.0103 max mem: 33369 +Epoch: [1] [1050/1319] eta: 0:15:04 lr: 4.797396552111593e-05 loss: 0.1970 (0.1823) time: 3.3599 data: 0.0107 max mem: 33369 +Epoch: [1] [1060/1319] eta: 0:14:31 lr: 4.7965396956435596e-05 loss: 0.1450 (0.1820) time: 3.3406 data: 0.0106 max mem: 33369 +Epoch: [1] [1070/1319] eta: 0:13:57 lr: 4.795682822167489e-05 loss: 0.1525 (0.1821) time: 3.3196 data: 0.0102 max mem: 33369 +Epoch: [1] [1080/1319] eta: 0:13:23 lr: 4.794825931679665e-05 loss: 0.1804 (0.1821) time: 3.3420 data: 0.0102 max mem: 33369 +Epoch: [1] [1090/1319] eta: 0:12:50 lr: 4.7939690241763725e-05 loss: 0.1677 (0.1818) time: 3.3591 data: 0.0110 max mem: 33369 +Epoch: [1] 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+Epoch: [1] [1180/1319] eta: 0:07:47 lr: 4.786256090336764e-05 loss: 0.1594 (0.1818) time: 3.3468 data: 0.0103 max mem: 33369 +Epoch: [1] [1190/1319] eta: 0:07:13 lr: 4.7853990124740705e-05 loss: 0.1561 (0.1815) time: 3.3759 data: 0.0108 max mem: 33369 +Epoch: [1] [1200/1319] eta: 0:06:39 lr: 4.784541917554932e-05 loss: 0.1545 (0.1814) time: 3.3692 data: 0.0121 max mem: 33369 +Epoch: [1] [1210/1319] eta: 0:06:06 lr: 4.783684805575612e-05 loss: 0.1556 (0.1814) time: 3.3535 data: 0.0118 max mem: 33369 +Epoch: [1] [1220/1319] eta: 0:05:32 lr: 4.782827676532376e-05 loss: 0.1559 (0.1813) time: 3.3577 data: 0.0127 max mem: 33369 +Epoch: [1] [1230/1319] eta: 0:04:59 lr: 4.781970530421487e-05 loss: 0.1609 (0.1811) time: 3.3838 data: 0.0131 max mem: 33369 +Epoch: [1] [1240/1319] eta: 0:04:25 lr: 4.7811133672392044e-05 loss: 0.1406 (0.1807) time: 3.3621 data: 0.0116 max mem: 33369 +Epoch: [1] [1250/1319] eta: 0:03:51 lr: 4.780256186981787e-05 loss: 0.1406 (0.1806) time: 3.3152 data: 0.0105 max mem: 33369 +Epoch: [1] [1260/1319] eta: 0:03:18 lr: 4.779398989645494e-05 loss: 0.1624 (0.1805) time: 3.3313 data: 0.0104 max mem: 33369 +Epoch: [1] [1270/1319] eta: 0:02:44 lr: 4.778541775226581e-05 loss: 0.1607 (0.1805) time: 3.3461 data: 0.0108 max mem: 33369 +Epoch: [1] [1280/1319] eta: 0:02:11 lr: 4.777684543721302e-05 loss: 0.1607 (0.1803) time: 3.3200 data: 0.0105 max mem: 33369 +Epoch: [1] [1290/1319] eta: 0:01:37 lr: 4.776827295125911e-05 loss: 0.1530 (0.1801) time: 3.3439 data: 0.0105 max mem: 33369 +Epoch: [1] [1300/1319] eta: 0:01:03 lr: 4.775970029436657e-05 loss: 0.1481 (0.1798) time: 3.3844 data: 0.0096 max mem: 33369 +Epoch: [1] [1310/1319] eta: 0:00:30 lr: 4.7751127466497925e-05 loss: 0.1693 (0.1799) time: 3.3642 data: 0.0089 max mem: 33369 +Epoch: [1] Total time: 1:13:52 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 2:41:55 time: 3.7758 data: 3.6842 max mem: 33369 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 100/2573] eta: 0:05:04 time: 0.0819 data: 0.0016 max mem: 33369 +Test: [ 200/2573] eta: 0:04:05 time: 0.0828 data: 0.0016 max mem: 33369 +Test: [ 300/2573] eta: 0:03:38 time: 0.0845 data: 0.0018 max mem: 33369 +Test: [ 400/2573] eta: 0:03:21 time: 0.0852 data: 0.0016 max mem: 33369 +Test: [ 500/2573] eta: 0:03:09 time: 0.0893 data: 0.0023 max mem: 33369 +Test: [ 600/2573] eta: 0:02:58 time: 0.0830 data: 0.0017 max mem: 33369 +Test: [ 700/2573] eta: 0:02:48 time: 0.0832 data: 0.0015 max mem: 33369 +Test: [ 800/2573] eta: 0:02:37 time: 0.0855 data: 0.0017 max mem: 33369 +Test: [ 900/2573] eta: 0:02:28 time: 0.0825 data: 0.0016 max mem: 33369 +Test: [1000/2573] eta: 0:02:18 time: 0.0827 data: 0.0016 max mem: 33369 +Test: [1100/2573] eta: 0:02:09 time: 0.0906 data: 0.0023 max mem: 33369 +Test: [1200/2573] eta: 0:02:00 time: 0.0838 data: 0.0015 max mem: 33369 +Test: [1300/2573] eta: 0:01:51 time: 0.0837 data: 0.0017 max mem: 33369 +Test: [1400/2573] eta: 0:01:42 time: 0.0854 data: 0.0020 max mem: 33369 +Test: [1500/2573] eta: 0:01:33 time: 0.0901 data: 0.0023 max mem: 33369 +Test: [1600/2573] eta: 0:01:24 time: 0.0900 data: 0.0020 max mem: 33369 +Test: [1700/2573] eta: 0:01:16 time: 0.0821 data: 0.0016 max mem: 33369 +Test: [1800/2573] eta: 0:01:07 time: 0.0894 data: 0.0022 max mem: 33369 +Test: [1900/2573] eta: 0:00:58 time: 0.0884 data: 0.0022 max mem: 33369 +Test: [2000/2573] eta: 0:00:49 time: 0.0894 data: 0.0021 max mem: 33369 +Test: [2100/2573] eta: 0:00:41 time: 0.0846 data: 0.0016 max mem: 33369 +Test: [2200/2573] eta: 0:00:32 time: 0.0873 data: 0.0019 max mem: 33369 +Test: [2300/2573] eta: 0:00:23 time: 0.0863 data: 0.0017 max mem: 33369 +Test: [2400/2573] eta: 0:00:15 time: 0.0819 data: 0.0018 max mem: 33369 +Test: [2500/2573] eta: 0:00:06 time: 0.0827 data: 0.0016 max mem: 33369 +Test: Total time: 0:03:43 +Final results: +Mean IoU is 47.78 + + precision@0.5 = 48.86 + precision@0.6 = 38.30 + precision@0.7 = 27.61 + precision@0.8 = 17.24 + precision@0.9 = 4.94 + overall IoU = 48.47 + +Average object IoU 47.7757666810126 +Overall IoU 48.46860122680664 +Better epoch: 1 + +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [2] [ 0/1319] eta: 2:26:56 lr: 4.774341177520056e-05 loss: 0.1066 (0.1066) time: 6.6839 data: 3.1199 max mem: 33369 +Epoch: [2] [ 10/1319] eta: 1:19:26 lr: 4.773483862237391e-05 loss: 0.1577 (0.2007) time: 3.6411 data: 0.2932 max mem: 33369 +Epoch: [2] [ 20/1319] eta: 1:15:47 lr: 4.772626529846231e-05 loss: 0.1546 (0.1781) time: 3.3419 data: 0.0091 max mem: 33369 +Epoch: [2] [ 30/1319] eta: 1:14:10 lr: 4.771769180342819e-05 loss: 0.1440 (0.1723) time: 3.3486 data: 0.0097 max mem: 33369 +Epoch: [2] [ 40/1319] eta: 1:13:11 lr: 4.7709118137233964e-05 loss: 0.1269 (0.1678) time: 3.3631 data: 0.0113 max mem: 33369 +Epoch: [2] [ 50/1319] eta: 1:12:23 lr: 4.770054429984204e-05 loss: 0.1482 (0.1668) time: 3.3764 data: 0.0120 max mem: 33369 +Epoch: [2] [ 60/1319] eta: 1:11:36 lr: 4.769197029121481e-05 loss: 0.1467 (0.1663) time: 3.3688 data: 0.0128 max mem: 33369 +Epoch: [2] [ 70/1319] eta: 1:10:58 lr: 4.7683396111314645e-05 loss: 0.1550 (0.1701) time: 3.3768 data: 0.0118 max mem: 33369 +Epoch: [2] [ 80/1319] eta: 1:10:16 lr: 4.7674821760103904e-05 loss: 0.1648 (0.1672) time: 3.3763 data: 0.0112 max mem: 33369 +Epoch: [2] [ 90/1319] eta: 1:09:42 lr: 4.766624723754494e-05 loss: 0.1503 (0.1653) time: 3.3787 data: 0.0113 max mem: 33369 +Epoch: [2] [ 100/1319] eta: 1:09:00 lr: 4.7657672543600056e-05 loss: 0.1503 (0.1643) time: 3.3680 data: 0.0120 max mem: 33369 +Epoch: [2] [ 110/1319] eta: 1:08:27 lr: 4.764909767823158e-05 loss: 0.1501 (0.1623) time: 3.3720 data: 0.0126 max mem: 33369 +Epoch: [2] [ 120/1319] eta: 1:07:50 lr: 4.76405226414018e-05 loss: 0.1501 (0.1620) time: 3.3860 data: 0.0131 max mem: 33369 +Epoch: [2] [ 130/1319] eta: 1:07:13 lr: 4.7631947433073e-05 loss: 0.1430 (0.1604) time: 3.3641 data: 0.0127 max mem: 33369 +Epoch: [2] [ 140/1319] eta: 1:06:37 lr: 4.762337205320744e-05 loss: 0.1433 (0.1602) time: 3.3676 data: 0.0123 max mem: 33369 +Epoch: [2] [ 150/1319] eta: 1:06:04 lr: 4.7614796501767376e-05 loss: 0.1558 (0.1603) time: 3.3826 data: 0.0117 max mem: 33369 +Epoch: [2] [ 160/1319] eta: 1:05:29 lr: 4.760622077871502e-05 loss: 0.1686 (0.1613) time: 3.3871 data: 0.0101 max mem: 33369 +Epoch: [2] [ 170/1319] eta: 1:04:52 lr: 4.75976448840126e-05 loss: 0.1642 (0.1605) time: 3.3610 data: 0.0100 max mem: 33369 +Epoch: [2] [ 180/1319] eta: 1:04:15 lr: 4.7589068817622304e-05 loss: 0.1304 (0.1588) time: 3.3429 data: 0.0108 max mem: 33369 +Epoch: [2] [ 190/1319] eta: 1:03:40 lr: 4.758049257950633e-05 loss: 0.1306 (0.1582) time: 3.3582 data: 0.0104 max mem: 33369 +Epoch: [2] [ 200/1319] eta: 1:03:03 lr: 4.757191616962685e-05 loss: 0.1475 (0.1589) time: 3.3422 data: 0.0104 max mem: 33369 +Epoch: [2] [ 210/1319] eta: 1:02:29 lr: 4.756333958794601e-05 loss: 0.1475 (0.1579) time: 3.3475 data: 0.0116 max mem: 33369 +Epoch: [2] [ 220/1319] eta: 1:01:53 lr: 4.7554762834425936e-05 loss: 0.1399 (0.1573) time: 3.3605 data: 0.0120 max mem: 33369 +Epoch: [2] [ 230/1319] eta: 1:01:19 lr: 4.7546185909028754e-05 loss: 0.1606 (0.1587) time: 3.3538 data: 0.0109 max mem: 33369 +Epoch: [2] [ 240/1319] eta: 1:00:44 lr: 4.753760881171657e-05 loss: 0.1821 (0.1585) time: 3.3612 data: 0.0106 max mem: 33369 +Epoch: [2] [ 250/1319] eta: 1:00:09 lr: 4.7529031542451477e-05 loss: 0.1543 (0.1589) time: 3.3504 data: 0.0108 max mem: 33369 +Epoch: [2] [ 260/1319] eta: 0:59:37 lr: 4.7520454101195535e-05 loss: 0.1505 (0.1591) time: 3.3892 data: 0.0107 max mem: 33369 +Epoch: [2] [ 270/1319] eta: 0:59:04 lr: 4.751187648791081e-05 loss: 0.1505 (0.1589) time: 3.4082 data: 0.0114 max mem: 33369 +Epoch: [2] [ 280/1319] eta: 0:58:29 lr: 4.7503298702559326e-05 loss: 0.1584 (0.1589) time: 3.3628 data: 0.0120 max mem: 33369 +Epoch: [2] [ 290/1319] eta: 0:57:54 lr: 4.7494720745103136e-05 loss: 0.1582 (0.1595) time: 3.3537 data: 0.0111 max mem: 33369 +Epoch: [2] [ 300/1319] eta: 0:57:20 lr: 4.748614261550422e-05 loss: 0.1355 (0.1586) time: 3.3556 data: 0.0106 max mem: 33369 +Epoch: [2] [ 310/1319] eta: 0:56:43 lr: 4.7477564313724594e-05 loss: 0.1272 (0.1584) time: 3.3136 data: 0.0115 max mem: 33369 +Epoch: [2] [ 320/1319] eta: 0:56:10 lr: 4.746898583972622e-05 loss: 0.1646 (0.1597) time: 3.3449 data: 0.0111 max mem: 33369 +Epoch: [2] [ 330/1319] eta: 0:55:37 lr: 4.746040719347105e-05 loss: 0.1435 (0.1591) time: 3.4072 data: 0.0119 max mem: 33369 +Epoch: [2] [ 340/1319] eta: 0:55:02 lr: 4.745182837492104e-05 loss: 0.1322 (0.1594) time: 3.3713 data: 0.0130 max mem: 33369 +Epoch: [2] [ 350/1319] eta: 0:54:29 lr: 4.744324938403812e-05 loss: 0.1380 (0.1599) time: 3.3558 data: 0.0124 max mem: 33369 +Epoch: [2] [ 360/1319] eta: 0:53:55 lr: 4.7434670220784206e-05 loss: 0.1369 (0.1593) time: 3.3705 data: 0.0113 max mem: 33369 +Epoch: [2] [ 370/1319] eta: 0:53:19 lr: 4.7426090885121175e-05 loss: 0.1366 (0.1591) time: 3.3304 data: 0.0101 max mem: 33369 +Epoch: [2] [ 380/1319] eta: 0:52:45 lr: 4.741751137701092e-05 loss: 0.1405 (0.1593) time: 3.3320 data: 0.0107 max mem: 33369 +Epoch: [2] [ 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0:12:15 lr: 4.679933111092072e-05 loss: 0.1359 (0.1571) time: 3.3161 data: 0.0127 max mem: 33369 +Epoch: [2] [1110/1319] eta: 0:11:41 lr: 4.6790738910101147e-05 loss: 0.1630 (0.1575) time: 3.3523 data: 0.0120 max mem: 33369 +Epoch: [2] [1120/1319] eta: 0:11:08 lr: 4.67821465339681e-05 loss: 0.1677 (0.1576) time: 3.3489 data: 0.0117 max mem: 33369 +Epoch: [2] [1130/1319] eta: 0:10:34 lr: 4.677355398248223e-05 loss: 0.1616 (0.1577) time: 3.3384 data: 0.0115 max mem: 33369 +Epoch: [2] [1140/1319] eta: 0:10:01 lr: 4.676496125560416e-05 loss: 0.1583 (0.1578) time: 3.3338 data: 0.0119 max mem: 33369 +Epoch: [2] [1150/1319] eta: 0:09:27 lr: 4.6756368353294506e-05 loss: 0.1209 (0.1576) time: 3.3167 data: 0.0129 max mem: 33369 +Epoch: [2] [1160/1319] eta: 0:08:53 lr: 4.6747775275513856e-05 loss: 0.1153 (0.1573) time: 3.3414 data: 0.0128 max mem: 33369 +Epoch: [2] [1170/1319] eta: 0:08:20 lr: 4.6739182022222775e-05 loss: 0.1234 (0.1572) time: 3.3756 data: 0.0129 max mem: 33369 +Epoch: [2] 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+Epoch: [2] [1260/1319] eta: 0:03:18 lr: 4.6661834838121084e-05 loss: 0.1363 (0.1574) time: 3.3251 data: 0.0095 max mem: 33369 +Epoch: [2] [1270/1319] eta: 0:02:44 lr: 4.665323982755382e-05 loss: 0.1363 (0.1574) time: 3.3218 data: 0.0094 max mem: 33369 +Epoch: [2] [1280/1319] eta: 0:02:10 lr: 4.664464464104137e-05 loss: 0.1514 (0.1575) time: 3.3544 data: 0.0099 max mem: 33369 +Epoch: [2] [1290/1319] eta: 0:01:37 lr: 4.6636049278544094e-05 loss: 0.1645 (0.1575) time: 3.3576 data: 0.0098 max mem: 33369 +Epoch: [2] [1300/1319] eta: 0:01:03 lr: 4.662745374002236e-05 loss: 0.1437 (0.1574) time: 3.3522 data: 0.0109 max mem: 33369 +Epoch: [2] [1310/1319] eta: 0:00:30 lr: 4.6618858025436495e-05 loss: 0.1421 (0.1574) time: 3.3941 data: 0.0107 max mem: 33369 +Epoch: [2] Total time: 1:13:48 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 2:54:53 time: 4.0782 data: 3.8669 max mem: 33369 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 100/2573] eta: 0:05:00 time: 0.0831 data: 0.0022 max mem: 33369 +Test: [ 200/2573] eta: 0:04:02 time: 0.0819 data: 0.0017 max mem: 33369 +Test: [ 300/2573] eta: 0:03:38 time: 0.0853 data: 0.0017 max mem: 33369 +Test: [ 400/2573] eta: 0:03:22 time: 0.0879 data: 0.0020 max mem: 33369 +Test: [ 500/2573] eta: 0:03:10 time: 0.0844 data: 0.0018 max mem: 33369 +Test: [ 600/2573] eta: 0:02:59 time: 0.0890 data: 0.0022 max mem: 33369 +Test: [ 700/2573] eta: 0:02:49 time: 0.0832 data: 0.0017 max mem: 33369 +Test: [ 800/2573] eta: 0:02:39 time: 0.0868 data: 0.0016 max mem: 33369 +Test: [ 900/2573] eta: 0:02:30 time: 0.0893 data: 0.0022 max mem: 33369 +Test: [1000/2573] eta: 0:02:21 time: 0.0902 data: 0.0024 max mem: 33369 +Test: [1100/2573] eta: 0:02:12 time: 0.0895 data: 0.0023 max mem: 33369 +Test: [1200/2573] eta: 0:02:02 time: 0.0897 data: 0.0022 max mem: 33369 +Test: [1300/2573] eta: 0:01:53 time: 0.0888 data: 0.0022 max mem: 33369 +Test: [1400/2573] eta: 0:01:44 time: 0.0808 data: 0.0017 max mem: 33369 +Test: [1500/2573] eta: 0:01:35 time: 0.0889 data: 0.0024 max mem: 33369 +Test: [1600/2573] eta: 0:01:26 time: 0.0910 data: 0.0022 max mem: 33369 +Test: [1700/2573] eta: 0:01:17 time: 0.0880 data: 0.0020 max mem: 33369 +Test: [1800/2573] eta: 0:01:08 time: 0.0901 data: 0.0023 max mem: 33369 +Test: [1900/2573] eta: 0:00:59 time: 0.0832 data: 0.0019 max mem: 33369 +Test: [2000/2573] eta: 0:00:50 time: 0.0831 data: 0.0016 max mem: 33369 +Test: [2100/2573] eta: 0:00:41 time: 0.0894 data: 0.0021 max mem: 33369 +Test: [2200/2573] eta: 0:00:32 time: 0.0881 data: 0.0021 max mem: 33369 +Test: [2300/2573] eta: 0:00:24 time: 0.0891 data: 0.0022 max mem: 33369 +Test: [2400/2573] eta: 0:00:15 time: 0.0818 data: 0.0018 max mem: 33369 +Test: [2500/2573] eta: 0:00:06 time: 0.0839 data: 0.0018 max mem: 33369 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: Total time: 0:03:47 +Final results: +Mean IoU is 46.75 + + precision@0.5 = 51.27 + precision@0.6 = 43.50 + precision@0.7 = 34.97 + precision@0.8 = 22.69 + precision@0.9 = 7.92 + overall IoU = 49.45 + +Average object IoU 46.747645392205264 +Overall IoU 49.453548431396484 +Better epoch: 2 + +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [3] [ 0/1319] eta: 2:15:12 lr: 4.661112173174161e-05 loss: 0.1091 (0.1091) time: 6.1504 data: 2.7127 max mem: 33369 +Epoch: [3] [ 10/1319] eta: 1:18:18 lr: 4.660252568252458e-05 loss: 0.1093 (0.1235) time: 3.5895 data: 0.2551 max mem: 33369 +Epoch: [3] [ 20/1319] eta: 1:14:53 lr: 4.6593929457128314e-05 loss: 0.1155 (0.1206) time: 3.3244 data: 0.0088 max mem: 33369 +Epoch: [3] [ 30/1319] eta: 1:13:12 lr: 4.6585333055513096e-05 loss: 0.1160 (0.1222) time: 3.3073 data: 0.0099 max mem: 33369 +Epoch: [3] [ 40/1319] eta: 1:12:32 lr: 4.657673647763916e-05 loss: 0.1409 (0.1370) time: 3.3441 data: 0.0110 max mem: 33369 +Epoch: [3] [ 50/1319] eta: 1:11:54 lr: 4.656813972346675e-05 loss: 0.1365 (0.1357) time: 3.3890 data: 0.0113 max mem: 33369 +Epoch: [3] [ 60/1319] eta: 1:11:07 lr: 4.655954279295608e-05 loss: 0.1151 (0.1343) time: 3.3633 data: 0.0125 max mem: 33369 +Epoch: [3] [ 70/1319] eta: 1:10:26 lr: 4.655094568606738e-05 loss: 0.1190 (0.1355) time: 3.3426 data: 0.0117 max mem: 33369 +Epoch: [3] [ 80/1319] eta: 1:09:51 lr: 4.6542348402760813e-05 loss: 0.1365 (0.1378) time: 3.3603 data: 0.0121 max mem: 33369 +Epoch: [3] [ 90/1319] eta: 1:09:17 lr: 4.653375094299656e-05 loss: 0.1375 (0.1416) time: 3.3801 data: 0.0129 max mem: 33369 +Epoch: [3] [ 100/1319] eta: 1:08:42 lr: 4.652515330673476e-05 loss: 0.1188 (0.1420) time: 3.3775 data: 0.0125 max mem: 33369 +Epoch: [3] [ 110/1319] eta: 1:08:04 lr: 4.651655549393556e-05 loss: 0.1069 (0.1418) time: 3.3547 data: 0.0120 max mem: 33369 +Epoch: [3] [ 120/1319] eta: 1:07:25 lr: 4.650795750455908e-05 loss: 0.1329 (0.1413) time: 3.3349 data: 0.0107 max mem: 33369 +Epoch: [3] [ 130/1319] eta: 1:06:50 lr: 4.649935933856541e-05 loss: 0.1334 (0.1411) time: 3.3453 data: 0.0102 max mem: 33369 +Epoch: [3] [ 140/1319] eta: 1:06:15 lr: 4.6490760995914644e-05 loss: 0.1251 (0.1392) time: 3.3595 data: 0.0099 max mem: 33369 +Epoch: [3] [ 150/1319] eta: 1:05:44 lr: 4.648216247656684e-05 loss: 0.1188 (0.1388) time: 3.3808 data: 0.0104 max mem: 33369 +Epoch: [3] [ 160/1319] eta: 1:05:10 lr: 4.647356378048206e-05 loss: 0.1199 (0.1375) time: 3.3927 data: 0.0117 max mem: 33369 +Epoch: [3] [ 170/1319] eta: 1:04:37 lr: 4.646496490762032e-05 loss: 0.1381 (0.1391) time: 3.3818 data: 0.0122 max mem: 33369 +Epoch: [3] [ 180/1319] eta: 1:04:02 lr: 4.645636585794164e-05 loss: 0.1308 (0.1388) time: 3.3649 data: 0.0123 max mem: 33369 +Epoch: [3] [ 190/1319] eta: 1:03:25 lr: 4.644776663140602e-05 loss: 0.1226 (0.1393) time: 3.3344 data: 0.0135 max mem: 33369 +Epoch: [3] [ 200/1319] eta: 1:02:50 lr: 4.6439167227973446e-05 loss: 0.1381 (0.1400) time: 3.3330 data: 0.0136 max mem: 33369 +Epoch: [3] [ 210/1319] eta: 1:02:12 lr: 4.643056764760387e-05 loss: 0.1440 (0.1410) time: 3.3208 data: 0.0121 max mem: 33369 +Epoch: [3] [ 220/1319] eta: 1:01:37 lr: 4.642196789025724e-05 loss: 0.1440 (0.1407) time: 3.3170 data: 0.0115 max mem: 33369 +Epoch: [3] [ 230/1319] eta: 1:01:06 lr: 4.641336795589349e-05 loss: 0.1280 (0.1405) time: 3.3726 data: 0.0109 max mem: 33369 +Epoch: [3] [ 240/1319] eta: 1:00:31 lr: 4.6404767844472526e-05 loss: 0.1280 (0.1402) time: 3.3753 data: 0.0104 max mem: 33369 +Epoch: [3] [ 250/1319] eta: 0:59:58 lr: 4.639616755595424e-05 loss: 0.1168 (0.1401) time: 3.3605 data: 0.0102 max mem: 33369 +Epoch: [3] [ 260/1319] eta: 0:59:21 lr: 4.638756709029851e-05 loss: 0.1294 (0.1404) time: 3.3322 data: 0.0108 max mem: 33369 +Epoch: [3] [ 270/1319] eta: 0:58:48 lr: 4.6378966447465196e-05 loss: 0.1517 (0.1416) time: 3.3284 data: 0.0106 max mem: 33369 +Epoch: [3] [ 280/1319] eta: 0:58:14 lr: 4.637036562741414e-05 loss: 0.1539 (0.1416) time: 3.3651 data: 0.0103 max mem: 33369 +Epoch: [3] [ 290/1319] eta: 0:57:40 lr: 4.636176463010516e-05 loss: 0.1347 (0.1421) time: 3.3589 data: 0.0128 max mem: 33369 +Epoch: [3] [ 300/1319] eta: 0:57:04 lr: 4.635316345549808e-05 loss: 0.1140 (0.1413) time: 3.3217 data: 0.0124 max mem: 33369 +Epoch: [3] [ 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3.2891 data: 0.0110 max mem: 33369 +Epoch: [3] [ 630/1319] eta: 0:38:16 lr: 4.606922496512879e-05 loss: 0.1446 (0.1397) time: 3.2739 data: 0.0117 max mem: 33369 +Epoch: [3] [ 640/1319] eta: 0:37:42 lr: 4.606061773834596e-05 loss: 0.1354 (0.1398) time: 3.2700 data: 0.0113 max mem: 33369 +Epoch: [3] [ 650/1319] eta: 0:37:08 lr: 4.60520103328472e-05 loss: 0.1271 (0.1398) time: 3.2680 data: 0.0108 max mem: 33369 +Epoch: [3] [ 660/1319] eta: 0:36:33 lr: 4.60434027485917e-05 loss: 0.1323 (0.1399) time: 3.2549 data: 0.0101 max mem: 33369 +Epoch: [3] [ 670/1319] eta: 0:35:59 lr: 4.6034794985538615e-05 loss: 0.1360 (0.1397) time: 3.2435 data: 0.0103 max mem: 33369 +Epoch: [3] [ 680/1319] eta: 0:35:25 lr: 4.602618704364706e-05 loss: 0.1300 (0.1397) time: 3.2498 data: 0.0111 max mem: 33369 +Epoch: [3] [ 690/1319] eta: 0:34:52 lr: 4.601757892287618e-05 loss: 0.1286 (0.1399) time: 3.2764 data: 0.0111 max mem: 33369 +Epoch: [3] [ 700/1319] eta: 0:34:18 lr: 4.600897062318506e-05 loss: 0.1350 (0.1403) time: 3.3034 data: 0.0109 max mem: 33369 +Epoch: [3] [ 710/1319] eta: 0:33:44 lr: 4.600036214453279e-05 loss: 0.1350 (0.1403) time: 3.2751 data: 0.0106 max mem: 33369 +Epoch: [3] [ 720/1319] eta: 0:33:11 lr: 4.599175348687844e-05 loss: 0.1060 (0.1398) time: 3.2616 data: 0.0110 max mem: 33369 +Epoch: [3] [ 730/1319] eta: 0:32:37 lr: 4.598314465018106e-05 loss: 0.1096 (0.1398) time: 3.2901 data: 0.0121 max mem: 33369 +Epoch: [3] [ 740/1319] eta: 0:32:04 lr: 4.5974535634399665e-05 loss: 0.1325 (0.1400) time: 3.2809 data: 0.0114 max mem: 33369 +Epoch: [3] [ 750/1319] eta: 0:31:30 lr: 4.596592643949328e-05 loss: 0.1369 (0.1399) time: 3.2765 data: 0.0105 max mem: 33369 +Epoch: [3] [ 760/1319] eta: 0:30:57 lr: 4.595731706542089e-05 loss: 0.1188 (0.1400) time: 3.2793 data: 0.0102 max mem: 33369 +Epoch: [3] [ 770/1319] eta: 0:30:23 lr: 4.5948707512141485e-05 loss: 0.1357 (0.1399) time: 3.2831 data: 0.0094 max mem: 33369 +Epoch: [3] [ 780/1319] eta: 0:29:50 lr: 4.594009777961402e-05 loss: 0.1229 (0.1396) time: 3.2828 data: 0.0099 max mem: 33369 +Epoch: [3] [ 790/1319] eta: 0:29:16 lr: 4.593148786779743e-05 loss: 0.1311 (0.1401) time: 3.2654 data: 0.0113 max mem: 33369 +Epoch: [3] [ 800/1319] eta: 0:28:42 lr: 4.592287777665063e-05 loss: 0.1162 (0.1399) time: 3.2582 data: 0.0115 max mem: 33369 +Epoch: [3] [ 810/1319] eta: 0:28:09 lr: 4.5914267506132555e-05 loss: 0.1162 (0.1401) time: 3.2531 data: 0.0104 max mem: 33369 +Epoch: [3] [ 820/1319] eta: 0:27:35 lr: 4.590565705620206e-05 loss: 0.1255 (0.1399) time: 3.2518 data: 0.0102 max mem: 33369 +Epoch: [3] [ 830/1319] eta: 0:27:02 lr: 4.589704642681802e-05 loss: 0.1211 (0.1398) time: 3.2613 data: 0.0108 max mem: 33369 +Epoch: [3] [ 840/1319] eta: 0:26:28 lr: 4.58884356179393e-05 loss: 0.1443 (0.1400) time: 3.2503 data: 0.0102 max mem: 33369 +Epoch: [3] [ 850/1319] eta: 0:25:54 lr: 4.5879824629524725e-05 loss: 0.1480 (0.1398) time: 3.2398 data: 0.0100 max mem: 33369 +Epoch: [3] [ 860/1319] eta: 0:25:21 lr: 4.5871213461533106e-05 loss: 0.1437 (0.1401) time: 3.2655 data: 0.0105 max mem: 33369 +Epoch: [3] [ 870/1319] eta: 0:24:48 lr: 4.5862602113923244e-05 loss: 0.1278 (0.1399) time: 3.2650 data: 0.0102 max mem: 33369 +Epoch: [3] [ 880/1319] eta: 0:24:14 lr: 4.585399058665391e-05 loss: 0.1099 (0.1397) time: 3.2756 data: 0.0099 max mem: 33369 +Epoch: [3] [ 890/1319] eta: 0:23:41 lr: 4.5845378879683885e-05 loss: 0.1346 (0.1398) time: 3.2653 data: 0.0098 max mem: 33369 +Epoch: [3] [ 900/1319] eta: 0:23:07 lr: 4.583676699297189e-05 loss: 0.1387 (0.1399) time: 3.2451 data: 0.0100 max mem: 33369 +Epoch: [3] [ 910/1319] eta: 0:22:34 lr: 4.582815492647665e-05 loss: 0.1337 (0.1398) time: 3.2686 data: 0.0108 max mem: 33369 +Epoch: [3] [ 920/1319] eta: 0:22:01 lr: 4.5819542680156885e-05 loss: 0.1427 (0.1404) time: 3.2802 data: 0.0101 max mem: 33369 +Epoch: [3] [ 930/1319] eta: 0:21:28 lr: 4.5810930253971277e-05 loss: 0.1348 (0.1404) time: 3.2662 data: 0.0093 max mem: 33369 +Epoch: [3] [ 940/1319] eta: 0:20:54 lr: 4.580231764787849e-05 loss: 0.1436 (0.1406) time: 3.2776 data: 0.0095 max mem: 33369 +Epoch: [3] [ 950/1319] eta: 0:20:21 lr: 4.579370486183719e-05 loss: 0.1441 (0.1408) time: 3.3089 data: 0.0094 max mem: 33369 +Epoch: [3] [ 960/1319] eta: 0:19:48 lr: 4.5785091895806004e-05 loss: 0.1228 (0.1407) time: 3.2798 data: 0.0097 max mem: 33369 +Epoch: [3] [ 970/1319] eta: 0:19:15 lr: 4.577647874974354e-05 loss: 0.1383 (0.1408) time: 3.2579 data: 0.0103 max mem: 33369 +Epoch: [3] [ 980/1319] eta: 0:18:42 lr: 4.57678654236084e-05 loss: 0.1362 (0.1405) time: 3.2781 data: 0.0112 max mem: 33369 +Epoch: [3] [ 990/1319] eta: 0:18:08 lr: 4.575925191735917e-05 loss: 0.1173 (0.1405) time: 3.2675 data: 0.0114 max mem: 33369 +Epoch: [3] [1000/1319] eta: 0:17:35 lr: 4.57506382309544e-05 loss: 0.1359 (0.1405) time: 3.2668 data: 0.0099 max mem: 33369 +Epoch: [3] [1010/1319] eta: 0:17:02 lr: 4.574202436435264e-05 loss: 0.1359 (0.1405) time: 3.2844 data: 0.0091 max mem: 33369 +Epoch: [3] [1020/1319] eta: 0:16:29 lr: 4.573341031751242e-05 loss: 0.1256 (0.1404) time: 3.3110 data: 0.0097 max mem: 33369 +Epoch: [3] [1030/1319] eta: 0:15:56 lr: 4.5724796090392234e-05 loss: 0.1321 (0.1405) time: 3.3166 data: 0.0094 max mem: 33369 +Epoch: [3] [1040/1319] eta: 0:15:23 lr: 4.571618168295058e-05 loss: 0.1196 (0.1403) time: 3.2862 data: 0.0095 max mem: 33369 +Epoch: [3] [1050/1319] eta: 0:14:49 lr: 4.570756709514592e-05 loss: 0.1124 (0.1401) time: 3.2728 data: 0.0108 max mem: 33369 +Epoch: [3] [1060/1319] eta: 0:14:16 lr: 4.569895232693671e-05 loss: 0.1241 (0.1404) time: 3.2659 data: 0.0111 max mem: 33369 +Epoch: [3] [1070/1319] eta: 0:13:43 lr: 4.569033737828139e-05 loss: 0.1290 (0.1403) time: 3.2707 data: 0.0110 max mem: 33369 +Epoch: [3] [1080/1319] eta: 0:13:10 lr: 4.568172224913836e-05 loss: 0.1209 (0.1401) time: 3.2821 data: 0.0113 max mem: 33369 +Epoch: [3] [1090/1319] eta: 0:12:37 lr: 4.567310693946603e-05 loss: 0.1234 (0.1402) time: 3.2920 data: 0.0107 max mem: 33369 +Epoch: [3] [1100/1319] eta: 0:12:04 lr: 4.566449144922278e-05 loss: 0.1250 (0.1399) time: 3.3061 data: 0.0106 max mem: 33369 +Epoch: [3] [1110/1319] eta: 0:11:31 lr: 4.565587577836695e-05 loss: 0.1143 (0.1399) time: 3.2793 data: 0.0109 max mem: 33369 +Epoch: [3] [1120/1319] eta: 0:10:58 lr: 4.5647259926856906e-05 loss: 0.1377 (0.1401) time: 3.2637 data: 0.0106 max mem: 33369 +Epoch: [3] [1130/1319] eta: 0:10:24 lr: 4.563864389465096e-05 loss: 0.1218 (0.1399) time: 3.2809 data: 0.0106 max mem: 33369 +Epoch: [3] [1140/1319] eta: 0:09:51 lr: 4.563002768170741e-05 loss: 0.1298 (0.1400) time: 3.2882 data: 0.0104 max mem: 33369 +Epoch: [3] [1150/1319] eta: 0:09:18 lr: 4.562141128798457e-05 loss: 0.1338 (0.1400) time: 3.2917 data: 0.0100 max mem: 33369 +Epoch: [3] [1160/1319] eta: 0:08:45 lr: 4.561279471344068e-05 loss: 0.1309 (0.1401) time: 3.2959 data: 0.0102 max mem: 33369 +Epoch: [3] [1170/1319] eta: 0:08:12 lr: 4.5604177958034e-05 loss: 0.1319 (0.1402) time: 3.2896 data: 0.0095 max mem: 33369 +Epoch: [3] [1180/1319] eta: 0:07:39 lr: 4.559556102172276e-05 loss: 0.1310 (0.1401) time: 3.2868 data: 0.0101 max mem: 33369 +Epoch: [3] [1190/1319] eta: 0:07:06 lr: 4.5586943904465176e-05 loss: 0.1271 (0.1402) time: 3.3353 data: 0.0114 max mem: 33369 +Epoch: [3] [1200/1319] eta: 0:06:33 lr: 4.557832660621944e-05 loss: 0.1098 (0.1400) time: 3.3754 data: 0.0119 max mem: 33369 +Epoch: [3] [1210/1319] eta: 0:06:00 lr: 4.556970912694373e-05 loss: 0.1147 (0.1400) time: 3.3448 data: 0.0117 max mem: 33369 +Epoch: [3] [1220/1319] eta: 0:05:27 lr: 4.5561091466596205e-05 loss: 0.1384 (0.1401) time: 3.2868 data: 0.0106 max mem: 33369 +Epoch: [3] [1230/1319] eta: 0:04:54 lr: 4.555247362513501e-05 loss: 0.1384 (0.1400) time: 3.2646 data: 0.0103 max mem: 33369 +Epoch: [3] [1240/1319] eta: 0:04:21 lr: 4.5543855602518245e-05 loss: 0.1280 (0.1401) time: 3.2949 data: 0.0105 max mem: 33369 +Epoch: [3] [1250/1319] eta: 0:03:48 lr: 4.553523739870403e-05 loss: 0.1261 (0.1399) time: 3.3184 data: 0.0112 max mem: 33369 +Epoch: [3] [1260/1319] eta: 0:03:15 lr: 4.552661901365045e-05 loss: 0.1228 (0.1400) time: 3.2941 data: 0.0120 max mem: 33369 +Epoch: [3] [1270/1319] eta: 0:02:41 lr: 4.551800044731557e-05 loss: 0.1330 (0.1399) time: 3.2845 data: 0.0107 max mem: 33369 +Epoch: [3] [1280/1319] eta: 0:02:08 lr: 4.550938169965743e-05 loss: 0.1284 (0.1400) time: 3.3026 data: 0.0093 max mem: 33369 +Epoch: [3] [1290/1319] eta: 0:01:35 lr: 4.550076277063406e-05 loss: 0.1284 (0.1400) time: 3.2719 data: 0.0095 max mem: 33369 +Epoch: [3] [1300/1319] eta: 0:01:02 lr: 4.549214366020347e-05 loss: 0.1290 (0.1402) time: 3.2494 data: 0.0100 max mem: 33369 +Epoch: [3] [1310/1319] eta: 0:00:29 lr: 4.5483524368323656e-05 loss: 0.1457 (0.1405) time: 3.3066 data: 0.0089 max mem: 33369 +Epoch: [3] Total time: 1:12:40 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 3:02:10 time: 4.2482 data: 3.9942 max mem: 33369 +Test: [ 100/2573] eta: 0:05:00 time: 0.0803 data: 0.0016 max mem: 33369 +Test: [ 200/2573] eta: 0:04:02 time: 0.0837 data: 0.0018 max mem: 33369 +Test: [ 300/2573] eta: 0:03:38 time: 0.0841 data: 0.0017 max mem: 33369 +Test: [ 400/2573] eta: 0:03:21 time: 0.0848 data: 0.0015 max mem: 33369 +Test: [ 500/2573] eta: 0:03:07 time: 0.0815 data: 0.0017 max mem: 33369 +Test: [ 600/2573] eta: 0:02:56 time: 0.0817 data: 0.0016 max mem: 33369 +Test: [ 700/2573] eta: 0:02:46 time: 0.0834 data: 0.0016 max mem: 33369 +Test: [ 800/2573] eta: 0:02:36 time: 0.0869 data: 0.0015 max mem: 33369 +Test: [ 900/2573] eta: 0:02:27 time: 0.0834 data: 0.0017 max mem: 33369 +Test: [1000/2573] eta: 0:02:17 time: 0.0828 data: 0.0015 max mem: 33369 +Test: [1100/2573] eta: 0:02:08 time: 0.0845 data: 0.0020 max mem: 33369 +Test: [1200/2573] eta: 0:01:59 time: 0.0874 data: 0.0020 max mem: 33369 +Test: [1300/2573] eta: 0:01:50 time: 0.0825 data: 0.0016 max mem: 33369 +Test: [1400/2573] eta: 0:01:41 time: 0.0825 data: 0.0017 max mem: 33369 +Test: [1500/2573] eta: 0:01:32 time: 0.0839 data: 0.0017 max mem: 33369 +Test: [1600/2573] eta: 0:01:24 time: 0.0859 data: 0.0019 max mem: 33369 +Test: [1700/2573] eta: 0:01:15 time: 0.0804 data: 0.0014 max mem: 33369 +Test: [1800/2573] eta: 0:01:06 time: 0.0880 data: 0.0021 max mem: 33369 +Test: [1900/2573] eta: 0:00:57 time: 0.0852 data: 0.0018 max mem: 33369 +Test: [2000/2573] eta: 0:00:49 time: 0.0812 data: 0.0015 max mem: 33369 +Test: [2100/2573] eta: 0:00:40 time: 0.0839 data: 0.0016 max mem: 33369 +Test: [2200/2573] eta: 0:00:31 time: 0.0868 data: 0.0017 max mem: 33369 +Test: [2300/2573] eta: 0:00:23 time: 0.0822 data: 0.0016 max mem: 33369 +Test: [2400/2573] eta: 0:00:14 time: 0.0836 data: 0.0019 max mem: 33369 +Test: [2500/2573] eta: 0:00:06 time: 0.0847 data: 0.0015 max mem: 33369 +Test: Total time: 0:03:39 +Final results: +Mean IoU is 54.06 + + precision@0.5 = 59.56 + precision@0.6 = 50.47 + precision@0.7 = 40.81 + precision@0.8 = 28.19 + precision@0.9 = 10.25 + overall IoU = 54.22 + +Average object IoU 54.05895729233483 +Overall IoU 54.2227783203125 +Better epoch: 3 + +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [4] [ 0/1319] eta: 2:08:59 lr: 4.547576685045799e-05 loss: 0.1032 (0.1032) time: 5.8673 data: 2.3179 max mem: 33369 +Epoch: [4] [ 10/1319] eta: 1:19:28 lr: 4.546714721370884e-05 loss: 0.1234 (0.1336) time: 3.6426 data: 0.2207 max mem: 33369 +Epoch: [4] [ 20/1319] eta: 1:16:15 lr: 4.5458527395388535e-05 loss: 0.1091 (0.1247) time: 3.4049 data: 0.0115 max mem: 33369 +Epoch: [4] [ 30/1319] eta: 1:14:39 lr: 4.544990739545498e-05 loss: 0.1046 (0.1241) time: 3.3837 data: 0.0112 max mem: 33369 +Epoch: [4] [ 40/1319] eta: 1:13:40 lr: 4.544128721386609e-05 loss: 0.1160 (0.1282) time: 3.3863 data: 0.0116 max mem: 33369 +Epoch: [4] [ 50/1319] eta: 1:12:58 lr: 4.543266685057974e-05 loss: 0.1039 (0.1209) time: 3.4109 data: 0.0123 max mem: 33369 +Epoch: [4] [ 60/1319] eta: 1:12:10 lr: 4.54240463055538e-05 loss: 0.0994 (0.1191) time: 3.4067 data: 0.0116 max mem: 33369 +Epoch: [4] [ 70/1319] eta: 1:11:14 lr: 4.541542557874611e-05 loss: 0.1071 (0.1192) time: 3.3503 data: 0.0104 max mem: 33369 +Epoch: [4] [ 80/1319] eta: 1:10:37 lr: 4.540680467011449e-05 loss: 0.1224 (0.1259) time: 3.3588 data: 0.0095 max mem: 33369 +Epoch: [4] [ 90/1319] eta: 1:09:57 lr: 4.5398183579616753e-05 loss: 0.1460 (0.1285) time: 3.3922 data: 0.0100 max mem: 33369 +Epoch: [4] [ 100/1319] eta: 1:09:16 lr: 4.5389562307210684e-05 loss: 0.1200 (0.1273) time: 3.3683 data: 0.0102 max mem: 33369 +Epoch: [4] [ 110/1319] eta: 1:08:40 lr: 4.5380940852854056e-05 loss: 0.1100 (0.1272) time: 3.3740 data: 0.0104 max mem: 33369 +Epoch: [4] [ 120/1319] eta: 1:08:10 lr: 4.537231921650461e-05 loss: 0.1015 (0.1264) time: 3.4214 data: 0.0112 max mem: 33369 +Epoch: [4] [ 130/1319] eta: 1:07:32 lr: 4.53636973981201e-05 loss: 0.1015 (0.1254) time: 3.4097 data: 0.0115 max mem: 33369 +Epoch: [4] [ 140/1319] eta: 1:06:58 lr: 4.535507539765821e-05 loss: 0.1072 (0.1259) time: 3.3879 data: 0.0108 max mem: 33369 +Epoch: [4] [ 150/1319] eta: 1:06:24 lr: 4.534645321507665e-05 loss: 0.1248 (0.1264) time: 3.4091 data: 0.0105 max mem: 33369 +Epoch: [4] [ 160/1319] eta: 1:05:51 lr: 4.53378308503331e-05 loss: 0.1264 (0.1270) time: 3.4192 data: 0.0112 max mem: 33369 +Epoch: [4] [ 170/1319] eta: 1:05:13 lr: 4.532920830338521e-05 loss: 0.1255 (0.1279) time: 3.3881 data: 0.0123 max mem: 33369 +Epoch: [4] [ 180/1319] eta: 1:04:39 lr: 4.5320585574190625e-05 loss: 0.1219 (0.1277) time: 3.3806 data: 0.0119 max mem: 33369 +Epoch: [4] [ 190/1319] eta: 1:04:16 lr: 4.5311962662706955e-05 loss: 0.1219 (0.1276) time: 3.4979 data: 0.0110 max mem: 33369 +Epoch: [4] [ 200/1319] eta: 1:03:39 lr: 4.5303339568891794e-05 loss: 0.0943 (0.1260) time: 3.4721 data: 0.0114 max mem: 33369 +Epoch: [4] [ 210/1319] eta: 1:03:00 lr: 4.529471629270274e-05 loss: 0.0951 (0.1252) time: 3.3465 data: 0.0116 max mem: 33369 +Epoch: [4] [ 220/1319] eta: 1:02:25 lr: 4.5286092834097356e-05 loss: 0.0964 (0.1242) time: 3.3629 data: 0.0122 max mem: 33369 +Epoch: [4] [ 230/1319] eta: 1:01:52 lr: 4.527746919303318e-05 loss: 0.1033 (0.1242) time: 3.4112 data: 0.0121 max mem: 33369 +Epoch: [4] [ 240/1319] eta: 1:01:16 lr: 4.5268845369467734e-05 loss: 0.1156 (0.1242) time: 3.4003 data: 0.0108 max mem: 33369 +Epoch: [4] [ 250/1319] eta: 1:00:39 lr: 4.526022136335852e-05 loss: 0.1152 (0.1247) time: 3.3513 data: 0.0100 max mem: 33369 +Epoch: [4] [ 260/1319] eta: 1:00:01 lr: 4.525159717466304e-05 loss: 0.1164 (0.1253) time: 3.3201 data: 0.0105 max mem: 33369 +Epoch: [4] [ 270/1319] eta: 0:59:27 lr: 4.524297280333875e-05 loss: 0.1164 (0.1253) time: 3.3537 data: 0.0109 max mem: 33369 +Epoch: [4] [ 280/1319] eta: 0:58:54 lr: 4.5234348249343114e-05 loss: 0.1070 (0.1252) time: 3.4171 data: 0.0108 max mem: 33369 +Epoch: [4] [ 290/1319] eta: 0:58:20 lr: 4.522572351263354e-05 loss: 0.1052 (0.1255) time: 3.4161 data: 0.0098 max mem: 33369 +Epoch: [4] [ 300/1319] eta: 0:57:48 lr: 4.521709859316746e-05 loss: 0.1193 (0.1260) time: 3.4245 data: 0.0095 max mem: 33369 +Epoch: [4] [ 310/1319] eta: 0:57:14 lr: 4.520847349090225e-05 loss: 0.1176 (0.1258) time: 3.4377 data: 0.0115 max mem: 33369 +Epoch: [4] [ 320/1319] eta: 0:56:40 lr: 4.5199848205795306e-05 loss: 0.1060 (0.1251) time: 3.4036 data: 0.0120 max mem: 33369 +Epoch: [4] [ 330/1319] eta: 0:56:04 lr: 4.519122273780396e-05 loss: 0.0955 (0.1246) time: 3.3670 data: 0.0119 max mem: 33369 +Epoch: [4] [ 340/1319] eta: 0:55:29 lr: 4.518259708688556e-05 loss: 0.1047 (0.1248) time: 3.3593 data: 0.0114 max mem: 33369 +Epoch: [4] [ 350/1319] eta: 0:54:57 lr: 4.5173971252997424e-05 loss: 0.1260 (0.1253) time: 3.4211 data: 0.0111 max mem: 33369 +Epoch: [4] [ 360/1319] eta: 0:54:24 lr: 4.5165345236096837e-05 loss: 0.1260 (0.1256) time: 3.4471 data: 0.0118 max mem: 33369 +Epoch: [4] [ 370/1319] eta: 0:53:48 lr: 4.5156719036141086e-05 loss: 0.1341 (0.1260) time: 3.3809 data: 0.0113 max mem: 33369 +Epoch: [4] [ 380/1319] eta: 0:53:12 lr: 4.5148092653087434e-05 loss: 0.1341 (0.1260) time: 3.3436 data: 0.0108 max mem: 33369 +Epoch: [4] [ 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(0.1271) time: 3.4304 data: 0.0108 max mem: 33369 +Epoch: [4] [ 790/1319] eta: 0:30:02 lr: 4.4794252770532266e-05 loss: 0.1141 (0.1269) time: 3.4635 data: 0.0116 max mem: 33369 +Epoch: [4] [ 800/1319] eta: 0:29:27 lr: 4.4785618658517975e-05 loss: 0.1108 (0.1269) time: 3.3763 data: 0.0117 max mem: 33369 +Epoch: [4] [ 810/1319] eta: 0:28:53 lr: 4.477698436154974e-05 loss: 0.1108 (0.1268) time: 3.3437 data: 0.0104 max mem: 33369 +Epoch: [4] [ 820/1319] eta: 0:28:19 lr: 4.476834987958398e-05 loss: 0.1089 (0.1268) time: 3.3983 data: 0.0102 max mem: 33369 +Epoch: [4] [ 830/1319] eta: 0:27:45 lr: 4.4759715212577086e-05 loss: 0.1356 (0.1271) time: 3.4188 data: 0.0105 max mem: 33369 +Epoch: [4] [ 840/1319] eta: 0:27:11 lr: 4.475108036048542e-05 loss: 0.1072 (0.1270) time: 3.3731 data: 0.0108 max mem: 33369 +Epoch: [4] [ 850/1319] eta: 0:26:36 lr: 4.4742445323265344e-05 loss: 0.1135 (0.1271) time: 3.3710 data: 0.0111 max mem: 33369 +Epoch: [4] [ 860/1319] eta: 0:26:03 lr: 4.473381010087318e-05 loss: 0.1135 (0.1269) time: 3.4453 data: 0.0107 max mem: 33369 +Epoch: [4] [ 870/1319] eta: 0:25:29 lr: 4.4725174693265234e-05 loss: 0.1023 (0.1268) time: 3.4571 data: 0.0120 max mem: 33369 +Epoch: [4] [ 880/1319] eta: 0:24:55 lr: 4.471653910039782e-05 loss: 0.1222 (0.1269) time: 3.4047 data: 0.0121 max mem: 33369 +Epoch: [4] [ 890/1319] eta: 0:24:21 lr: 4.4707903322227184e-05 loss: 0.1214 (0.1269) time: 3.3825 data: 0.0106 max mem: 33369 +Epoch: [4] [ 900/1319] eta: 0:23:47 lr: 4.469926735870959e-05 loss: 0.1046 (0.1266) time: 3.4376 data: 0.0104 max mem: 33369 +Epoch: [4] [ 910/1319] eta: 0:23:13 lr: 4.4690631209801266e-05 loss: 0.1046 (0.1264) time: 3.5126 data: 0.0101 max mem: 33369 +Epoch: [4] [ 920/1319] eta: 0:22:39 lr: 4.4681994875458425e-05 loss: 0.1110 (0.1264) time: 3.4594 data: 0.0098 max mem: 33369 +Epoch: [4] [ 930/1319] eta: 0:22:05 lr: 4.467335835563727e-05 loss: 0.1155 (0.1262) time: 3.3903 data: 0.0105 max mem: 33369 +Epoch: [4] [ 940/1319] eta: 0:21:31 lr: 4.466472165029396e-05 loss: 0.1376 (0.1266) time: 3.4017 data: 0.0120 max mem: 33369 +Epoch: [4] [ 950/1319] eta: 0:20:57 lr: 4.4656084759384645e-05 loss: 0.1397 (0.1266) time: 3.4058 data: 0.0121 max mem: 33369 +Epoch: [4] [ 960/1319] eta: 0:20:23 lr: 4.464744768286547e-05 loss: 0.1130 (0.1266) time: 3.3921 data: 0.0109 max mem: 33369 +Epoch: [4] [ 970/1319] eta: 0:19:49 lr: 4.463881042069255e-05 loss: 0.1267 (0.1267) time: 3.3931 data: 0.0105 max mem: 33369 +Epoch: [4] [ 980/1319] eta: 0:19:15 lr: 4.463017297282197e-05 loss: 0.1215 (0.1266) time: 3.4006 data: 0.0107 max mem: 33369 +Epoch: [4] [ 990/1319] eta: 0:18:41 lr: 4.4621535339209816e-05 loss: 0.1167 (0.1266) time: 3.4447 data: 0.0108 max mem: 33369 +Epoch: [4] [1000/1319] eta: 0:18:06 lr: 4.461289751981212e-05 loss: 0.1072 (0.1265) time: 3.4077 data: 0.0115 max mem: 33369 +Epoch: [4] [1010/1319] eta: 0:17:32 lr: 4.460425951458493e-05 loss: 0.1074 (0.1266) time: 3.3440 data: 0.0114 max mem: 33369 +Epoch: [4] [1020/1319] eta: 0:16:58 lr: 4.459562132348427e-05 loss: 0.1191 (0.1267) time: 3.4073 data: 0.0105 max mem: 33369 +Epoch: [4] [1030/1319] eta: 0:16:24 lr: 4.458698294646612e-05 loss: 0.1226 (0.1266) time: 3.4133 data: 0.0099 max mem: 33369 +Epoch: [4] [1040/1319] eta: 0:15:50 lr: 4.457834438348646e-05 loss: 0.0994 (0.1264) time: 3.3454 data: 0.0094 max mem: 33369 +Epoch: [4] [1050/1319] eta: 0:15:16 lr: 4.456970563450125e-05 loss: 0.1155 (0.1263) time: 3.3555 data: 0.0104 max mem: 33369 +Epoch: [4] [1060/1319] eta: 0:14:42 lr: 4.456106669946641e-05 loss: 0.1155 (0.1263) time: 3.4143 data: 0.0118 max mem: 33369 +Epoch: [4] [1070/1319] eta: 0:14:08 lr: 4.4552427578337865e-05 loss: 0.1017 (0.1263) time: 3.4577 data: 0.0113 max mem: 33369 +Epoch: [4] [1080/1319] eta: 0:13:33 lr: 4.45437882710715e-05 loss: 0.1204 (0.1265) time: 3.3707 data: 0.0115 max mem: 33369 +Epoch: [4] [1090/1319] eta: 0:12:59 lr: 4.453514877762321e-05 loss: 0.1116 (0.1263) time: 3.2874 data: 0.0113 max mem: 33369 +Epoch: [4] 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+Epoch: [4] [1180/1319] eta: 0:07:53 lr: 4.4457384951110855e-05 loss: 0.1144 (0.1265) time: 3.4270 data: 0.0127 max mem: 33369 +Epoch: [4] [1190/1319] eta: 0:07:19 lr: 4.44487435934119e-05 loss: 0.1192 (0.1265) time: 3.3978 data: 0.0117 max mem: 33369 +Epoch: [4] [1200/1319] eta: 0:06:45 lr: 4.4440102049044326e-05 loss: 0.1264 (0.1266) time: 3.4000 data: 0.0115 max mem: 33369 +Epoch: [4] [1210/1319] eta: 0:06:11 lr: 4.443146031796374e-05 loss: 0.1114 (0.1264) time: 3.4359 data: 0.0120 max mem: 33369 +Epoch: [4] [1220/1319] eta: 0:05:37 lr: 4.442281840012577e-05 loss: 0.1139 (0.1267) time: 3.4513 data: 0.0125 max mem: 33369 +Epoch: [4] [1230/1319] eta: 0:05:03 lr: 4.441417629548601e-05 loss: 0.1391 (0.1267) time: 3.4181 data: 0.0127 max mem: 33369 +Epoch: [4] [1240/1319] eta: 0:04:29 lr: 4.4405534004000035e-05 loss: 0.1279 (0.1267) time: 3.3750 data: 0.0111 max mem: 33369 +Epoch: [4] [1250/1319] eta: 0:03:54 lr: 4.439689152562339e-05 loss: 0.1284 (0.1269) time: 3.3733 data: 0.0092 max mem: 33369 +Epoch: [4] [1260/1319] eta: 0:03:20 lr: 4.438824886031161e-05 loss: 0.1491 (0.1270) time: 3.3964 data: 0.0103 max mem: 33369 +Epoch: [4] [1270/1319] eta: 0:02:46 lr: 4.437960600802022e-05 loss: 0.1101 (0.1269) time: 3.4101 data: 0.0116 max mem: 33369 +Epoch: [4] [1280/1319] eta: 0:02:12 lr: 4.4370962968704706e-05 loss: 0.1101 (0.1269) time: 3.3925 data: 0.0112 max mem: 33369 +Epoch: [4] [1290/1319] eta: 0:01:38 lr: 4.436231974232054e-05 loss: 0.1056 (0.1268) time: 3.3992 data: 0.0118 max mem: 33369 +Epoch: [4] [1300/1319] eta: 0:01:04 lr: 4.435367632882316e-05 loss: 0.0989 (0.1267) time: 3.4189 data: 0.0122 max mem: 33369 +Epoch: [4] [1310/1319] eta: 0:00:30 lr: 4.434503272816803e-05 loss: 0.1023 (0.1266) time: 3.3967 data: 0.0104 max mem: 33369 +Epoch: [4] Total time: 1:14:52 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 2:57:18 time: 4.1347 data: 3.7911 max mem: 33369 +Test: [ 100/2573] eta: 0:05:01 time: 0.0797 data: 0.0016 max mem: 33369 +Test: [ 200/2573] eta: 0:04:06 time: 0.0840 data: 0.0018 max mem: 33369 +Test: [ 300/2573] eta: 0:03:41 time: 0.0901 data: 0.0022 max mem: 33369 +Test: [ 400/2573] eta: 0:03:23 time: 0.0845 data: 0.0017 max mem: 33369 +Test: [ 500/2573] eta: 0:03:10 time: 0.0832 data: 0.0016 max mem: 33369 +Test: [ 600/2573] eta: 0:02:59 time: 0.0832 data: 0.0016 max mem: 33369 +Test: [ 700/2573] eta: 0:02:49 time: 0.0898 data: 0.0022 max mem: 33369 +Test: [ 800/2573] eta: 0:02:39 time: 0.0857 data: 0.0014 max mem: 33369 +Test: [ 900/2573] eta: 0:02:29 time: 0.0838 data: 0.0017 max mem: 33369 +Test: [1000/2573] eta: 0:02:19 time: 0.0862 data: 0.0018 max mem: 33369 +Test: [1100/2573] eta: 0:02:11 time: 0.0855 data: 0.0019 max mem: 33369 +Test: [1200/2573] eta: 0:02:01 time: 0.0822 data: 0.0016 max mem: 33369 +Test: [1300/2573] eta: 0:01:52 time: 0.0821 data: 0.0017 max mem: 33369 +Test: [1400/2573] eta: 0:01:43 time: 0.0822 data: 0.0015 max mem: 33369 +Test: [1500/2573] eta: 0:01:34 time: 0.0817 data: 0.0016 max mem: 33369 +Test: [1600/2573] eta: 0:01:25 time: 0.0871 data: 0.0019 max mem: 33369 +Test: [1700/2573] eta: 0:01:16 time: 0.0809 data: 0.0016 max mem: 33369 +Test: [1800/2573] eta: 0:01:07 time: 0.0892 data: 0.0020 max mem: 33369 +Test: [1900/2573] eta: 0:00:58 time: 0.0870 data: 0.0020 max mem: 33369 +Test: [2000/2573] eta: 0:00:49 time: 0.0838 data: 0.0016 max mem: 33369 +Test: [2100/2573] eta: 0:00:41 time: 0.0901 data: 0.0023 max mem: 33369 +Test: [2200/2573] eta: 0:00:32 time: 0.0849 data: 0.0016 max mem: 33369 +Test: [2300/2573] eta: 0:00:23 time: 0.0834 data: 0.0017 max mem: 33369 +Test: [2400/2573] eta: 0:00:14 time: 0.0886 data: 0.0023 max mem: 33369 +Test: [2500/2573] eta: 0:00:06 time: 0.0833 data: 0.0018 max mem: 33369 +Test: Total time: 0:03:43 +Final results: +Mean IoU is 54.43 + + precision@0.5 = 60.87 + precision@0.6 = 52.76 + precision@0.7 = 42.91 + precision@0.8 = 30.11 + precision@0.9 = 11.68 + overall IoU = 55.37 + +Average object IoU 54.43197049574253 +Overall IoU 55.372867584228516 +Better epoch: 4 + +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [5] [ 0/1319] eta: 2:26:08 lr: 4.433725332752167e-05 loss: 0.2499 (0.2499) time: 6.6480 data: 2.9327 max mem: 33369 +Epoch: [5] [ 10/1319] eta: 1:20:50 lr: 4.432860937114392e-05 loss: 0.0913 (0.1190) time: 3.7055 data: 0.2751 max mem: 33369 +Epoch: [5] [ 20/1319] eta: 1:18:17 lr: 4.4319965227479046e-05 loss: 0.1041 (0.1219) time: 3.4648 data: 0.0099 max mem: 33369 +Epoch: [5] [ 30/1319] eta: 1:16:37 lr: 4.43113208964824e-05 loss: 0.1099 (0.1194) time: 3.4906 data: 0.0115 max mem: 33369 +Epoch: [5] [ 40/1319] eta: 1:15:00 lr: 4.43026763781093e-05 loss: 0.1008 (0.1153) time: 3.4161 data: 0.0121 max mem: 33369 +Epoch: [5] [ 50/1319] eta: 1:13:53 lr: 4.429403167231508e-05 loss: 0.1083 (0.1210) time: 3.3797 data: 0.0108 max mem: 33369 +Epoch: [5] [ 60/1319] eta: 1:13:28 lr: 4.428538677905502e-05 loss: 0.1086 (0.1187) time: 3.4656 data: 0.0110 max mem: 33369 +Epoch: [5] [ 70/1319] eta: 1:12:41 lr: 4.4276741698284395e-05 loss: 0.1045 (0.1180) time: 3.4891 data: 0.0116 max mem: 33369 +Epoch: [5] [ 80/1319] eta: 1:11:51 lr: 4.4268096429958464e-05 loss: 0.1045 (0.1182) time: 3.4150 data: 0.0114 max mem: 33369 +Epoch: [5] [ 90/1319] eta: 1:11:03 lr: 4.425945097403244e-05 loss: 0.0921 (0.1169) time: 3.3879 data: 0.0121 max mem: 33369 +Epoch: [5] [ 100/1319] eta: 1:10:13 lr: 4.425080533046155e-05 loss: 0.0919 (0.1150) time: 3.3617 data: 0.0108 max mem: 33369 +Epoch: [5] [ 110/1319] eta: 1:09:26 lr: 4.424215949920098e-05 loss: 0.1105 (0.1161) time: 3.3391 data: 0.0092 max mem: 33369 +Epoch: [5] [ 120/1319] eta: 1:08:33 lr: 4.423351348020589e-05 loss: 0.1397 (0.1186) time: 3.3000 data: 0.0089 max mem: 33369 +Epoch: [5] [ 130/1319] eta: 1:07:48 lr: 4.4224867273431445e-05 loss: 0.1107 (0.1167) time: 3.2875 data: 0.0083 max mem: 33369 +Epoch: [5] [ 140/1319] eta: 1:07:04 lr: 4.421622087883277e-05 loss: 0.0934 (0.1168) time: 3.3119 data: 0.0089 max mem: 33369 +Epoch: [5] [ 150/1319] eta: 1:06:26 lr: 4.4207574296364965e-05 loss: 0.0997 (0.1157) time: 3.3330 data: 0.0106 max mem: 33369 +Epoch: [5] [ 160/1319] eta: 1:05:54 lr: 4.419892752598312e-05 loss: 0.0959 (0.1161) time: 3.4019 data: 0.0109 max mem: 33369 +Epoch: [5] [ 170/1319] eta: 1:05:20 lr: 4.419028056764231e-05 loss: 0.1058 (0.1167) time: 3.4266 data: 0.0103 max mem: 33369 +Epoch: [5] [ 180/1319] eta: 1:04:44 lr: 4.418163342129758e-05 loss: 0.1020 (0.1163) time: 3.3916 data: 0.0105 max mem: 33369 +Epoch: [5] [ 190/1319] eta: 1:04:05 lr: 4.417298608690395e-05 loss: 0.1056 (0.1169) time: 3.3600 data: 0.0103 max mem: 33369 +Epoch: [5] [ 200/1319] eta: 1:03:37 lr: 4.416433856441643e-05 loss: 0.1103 (0.1169) time: 3.4222 data: 0.0096 max mem: 33369 +Epoch: [5] [ 210/1319] eta: 1:03:02 lr: 4.415569085379001e-05 loss: 0.1198 (0.1177) time: 3.4487 data: 0.0102 max mem: 33369 +Epoch: [5] [ 220/1319] eta: 1:02:24 lr: 4.4147042954979643e-05 loss: 0.1107 (0.1179) time: 3.3658 data: 0.0101 max mem: 33369 +Epoch: [5] [ 230/1319] eta: 1:01:48 lr: 4.413839486794028e-05 loss: 0.1101 (0.1175) time: 3.3488 data: 0.0093 max mem: 33369 +Epoch: [5] [ 240/1319] eta: 1:01:13 lr: 4.412974659262685e-05 loss: 0.1140 (0.1180) time: 3.3702 data: 0.0107 max mem: 33369 +Epoch: [5] [ 250/1319] eta: 1:00:35 lr: 4.412109812899424e-05 loss: 0.1173 (0.1183) time: 3.3473 data: 0.0115 max mem: 33369 +Epoch: [5] [ 260/1319] eta: 1:00:00 lr: 4.411244947699735e-05 loss: 0.1050 (0.1179) time: 3.3497 data: 0.0109 max mem: 33369 +Epoch: [5] [ 270/1319] eta: 0:59:28 lr: 4.4103800636591036e-05 loss: 0.1081 (0.1179) time: 3.4213 data: 0.0114 max mem: 33369 +Epoch: [5] [ 280/1319] eta: 0:58:57 lr: 4.409515160773014e-05 loss: 0.1181 (0.1184) time: 3.4688 data: 0.0114 max mem: 33369 +Epoch: [5] [ 290/1319] eta: 0:58:23 lr: 4.408650239036947e-05 loss: 0.1104 (0.1186) time: 3.4367 data: 0.0115 max mem: 33369 +Epoch: [5] [ 300/1319] eta: 0:57:48 lr: 4.407785298446384e-05 loss: 0.0999 (0.1182) time: 3.3827 data: 0.0112 max mem: 33369 +Epoch: [5] [ 310/1319] eta: 0:57:15 lr: 4.406920338996803e-05 loss: 0.1003 (0.1181) time: 3.4170 data: 0.0104 max mem: 33369 +Epoch: [5] [ 320/1319] eta: 0:56:45 lr: 4.406055360683679e-05 loss: 0.1028 (0.1185) time: 3.4893 data: 0.0110 max mem: 33369 +Epoch: [5] [ 330/1319] eta: 0:56:10 lr: 4.4051903635024855e-05 loss: 0.1053 (0.1187) time: 3.4576 data: 0.0106 max mem: 33369 +Epoch: [5] [ 340/1319] eta: 0:55:35 lr: 4.404325347448695e-05 loss: 0.0894 (0.1182) time: 3.3741 data: 0.0110 max mem: 33369 +Epoch: [5] [ 350/1319] eta: 0:55:01 lr: 4.403460312517776e-05 loss: 0.0969 (0.1181) time: 3.3829 data: 0.0127 max mem: 33369 +Epoch: [5] [ 360/1319] eta: 0:54:27 lr: 4.402595258705198e-05 loss: 0.1107 (0.1181) time: 3.4199 data: 0.0128 max mem: 33369 +Epoch: [5] [ 370/1319] eta: 0:53:56 lr: 4.401730186006425e-05 loss: 0.1173 (0.1185) time: 3.4703 data: 0.0118 max mem: 33369 +Epoch: [5] [ 380/1319] eta: 0:53:22 lr: 4.40086509441692e-05 loss: 0.1076 (0.1183) time: 3.4631 data: 0.0109 max mem: 33369 +Epoch: [5] [ 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(0.1187) time: 3.3984 data: 0.0114 max mem: 33369 +Epoch: [5] [ 790/1319] eta: 0:30:01 lr: 4.3653800180569845e-05 loss: 0.1051 (0.1188) time: 3.4473 data: 0.0109 max mem: 33369 +Epoch: [5] [ 800/1319] eta: 0:29:26 lr: 4.364514128932435e-05 loss: 0.1023 (0.1188) time: 3.3943 data: 0.0103 max mem: 33369 +Epoch: [5] [ 810/1319] eta: 0:28:52 lr: 4.363648220720092e-05 loss: 0.0993 (0.1186) time: 3.3485 data: 0.0121 max mem: 33369 +Epoch: [5] [ 820/1319] eta: 0:28:18 lr: 4.3627822934153263e-05 loss: 0.1033 (0.1184) time: 3.4201 data: 0.0124 max mem: 33369 +Epoch: [5] [ 830/1319] eta: 0:27:44 lr: 4.361916347013505e-05 loss: 0.0891 (0.1182) time: 3.4315 data: 0.0113 max mem: 33369 +Epoch: [5] [ 840/1319] eta: 0:27:10 lr: 4.361050381509995e-05 loss: 0.0885 (0.1181) time: 3.4045 data: 0.0106 max mem: 33369 +Epoch: [5] [ 850/1319] eta: 0:26:36 lr: 4.3601843969001596e-05 loss: 0.0996 (0.1181) time: 3.3828 data: 0.0109 max mem: 33369 +Epoch: [5] [ 860/1319] eta: 0:26:02 lr: 4.359318393179363e-05 loss: 0.1044 (0.1181) time: 3.3824 data: 0.0126 max mem: 33369 +Epoch: [5] [ 870/1319] eta: 0:25:28 lr: 4.3584523703429616e-05 loss: 0.1256 (0.1185) time: 3.3915 data: 0.0116 max mem: 33369 +Epoch: [5] [ 880/1319] eta: 0:24:54 lr: 4.357586328386315e-05 loss: 0.1248 (0.1184) time: 3.3799 data: 0.0113 max mem: 33369 +Epoch: [5] [ 890/1319] eta: 0:24:19 lr: 4.356720267304778e-05 loss: 0.1052 (0.1182) time: 3.3806 data: 0.0115 max mem: 33369 +Epoch: [5] [ 900/1319] eta: 0:23:46 lr: 4.3558541870937056e-05 loss: 0.1052 (0.1181) time: 3.4189 data: 0.0113 max mem: 33369 +Epoch: [5] [ 910/1319] eta: 0:23:12 lr: 4.354988087748445e-05 loss: 0.0958 (0.1178) time: 3.4294 data: 0.0124 max mem: 33369 +Epoch: [5] [ 920/1319] eta: 0:22:37 lr: 4.35412196926435e-05 loss: 0.0887 (0.1176) time: 3.3834 data: 0.0119 max mem: 33369 +Epoch: [5] [ 930/1319] eta: 0:22:03 lr: 4.353255831636764e-05 loss: 0.1122 (0.1178) time: 3.3782 data: 0.0108 max mem: 33369 +Epoch: [5] [ 940/1319] eta: 0:21:30 lr: 4.352389674861032e-05 loss: 0.1336 (0.1180) time: 3.4257 data: 0.0103 max mem: 33369 +Epoch: [5] [ 950/1319] eta: 0:20:55 lr: 4.3515234989324975e-05 loss: 0.1336 (0.1181) time: 3.4299 data: 0.0106 max mem: 33369 +Epoch: [5] [ 960/1319] eta: 0:20:21 lr: 4.350657303846501e-05 loss: 0.1102 (0.1182) time: 3.3546 data: 0.0102 max mem: 33369 +Epoch: [5] [ 970/1319] eta: 0:19:47 lr: 4.34979108959838e-05 loss: 0.1029 (0.1181) time: 3.3401 data: 0.0099 max mem: 33369 +Epoch: [5] [ 980/1319] eta: 0:19:13 lr: 4.348924856183469e-05 loss: 0.1096 (0.1187) time: 3.3929 data: 0.0100 max mem: 33369 +Epoch: [5] [ 990/1319] eta: 0:18:39 lr: 4.348058603597104e-05 loss: 0.1249 (0.1186) time: 3.4127 data: 0.0108 max mem: 33369 +Epoch: [5] [1000/1319] eta: 0:18:05 lr: 4.347192331834616e-05 loss: 0.1113 (0.1188) time: 3.3869 data: 0.0114 max mem: 33369 +Epoch: [5] [1010/1319] eta: 0:17:31 lr: 4.346326040891335e-05 loss: 0.1268 (0.1188) time: 3.3898 data: 0.0119 max mem: 33369 +Epoch: [5] [1020/1319] eta: 0:16:57 lr: 4.345459730762588e-05 loss: 0.1130 (0.1188) time: 3.4263 data: 0.0117 max mem: 33369 +Epoch: [5] [1030/1319] eta: 0:16:23 lr: 4.344593401443699e-05 loss: 0.1242 (0.1190) time: 3.4257 data: 0.0107 max mem: 33369 +Epoch: [5] [1040/1319] eta: 0:15:49 lr: 4.343727052929992e-05 loss: 0.1255 (0.1193) time: 3.3703 data: 0.0107 max mem: 33369 +Epoch: [5] [1050/1319] eta: 0:15:14 lr: 4.342860685216788e-05 loss: 0.1082 (0.1191) time: 3.3298 data: 0.0107 max mem: 33369 +Epoch: [5] [1060/1319] eta: 0:14:40 lr: 4.341994298299405e-05 loss: 0.1102 (0.1191) time: 3.3676 data: 0.0107 max mem: 33369 +Epoch: [5] [1070/1319] eta: 0:14:06 lr: 4.341127892173159e-05 loss: 0.1189 (0.1193) time: 3.3778 data: 0.0107 max mem: 33369 +Epoch: [5] [1080/1319] eta: 0:13:32 lr: 4.3402614668333656e-05 loss: 0.1274 (0.1193) time: 3.3776 data: 0.0107 max mem: 33369 +Epoch: [5] [1090/1319] eta: 0:12:58 lr: 4.339395022275336e-05 loss: 0.1092 (0.1193) time: 3.4010 data: 0.0110 max mem: 33369 +Epoch: [5] 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+Epoch: [5] [1180/1319] eta: 0:07:52 lr: 4.331596155657851e-05 loss: 0.1097 (0.1192) time: 3.4892 data: 0.0105 max mem: 33369 +Epoch: [5] [1190/1319] eta: 0:07:18 lr: 4.3307295186591415e-05 loss: 0.1097 (0.1191) time: 3.5013 data: 0.0101 max mem: 33369 +Epoch: [5] [1200/1319] eta: 0:06:44 lr: 4.329862862390485e-05 loss: 0.1093 (0.1193) time: 3.3777 data: 0.0101 max mem: 33369 +Epoch: [5] [1210/1319] eta: 0:06:10 lr: 4.328996186847165e-05 loss: 0.1243 (0.1193) time: 3.3478 data: 0.0092 max mem: 33369 +Epoch: [5] [1220/1319] eta: 0:05:36 lr: 4.328129492024467e-05 loss: 0.1031 (0.1192) time: 3.3422 data: 0.0090 max mem: 33369 +Epoch: [5] [1230/1319] eta: 0:05:02 lr: 4.3272627779176715e-05 loss: 0.1031 (0.1191) time: 3.4000 data: 0.0096 max mem: 33369 +Epoch: [5] [1240/1319] eta: 0:04:28 lr: 4.326396044522058e-05 loss: 0.1164 (0.1193) time: 3.3784 data: 0.0098 max mem: 33369 +Epoch: [5] [1250/1319] eta: 0:03:54 lr: 4.3255292918329036e-05 loss: 0.1308 (0.1193) time: 3.3213 data: 0.0105 max mem: 33369 +Epoch: [5] [1260/1319] eta: 0:03:20 lr: 4.324662519845482e-05 loss: 0.1199 (0.1194) time: 3.3369 data: 0.0099 max mem: 33369 +Epoch: [5] [1270/1319] eta: 0:02:46 lr: 4.323795728555066e-05 loss: 0.1192 (0.1194) time: 3.3543 data: 0.0099 max mem: 33369 +Epoch: [5] [1280/1319] eta: 0:02:12 lr: 4.322928917956926e-05 loss: 0.1177 (0.1194) time: 3.3815 data: 0.0110 max mem: 33369 +Epoch: [5] [1290/1319] eta: 0:01:38 lr: 4.322062088046332e-05 loss: 0.1173 (0.1193) time: 3.3866 data: 0.0097 max mem: 33369 +Epoch: [5] [1300/1319] eta: 0:01:04 lr: 4.321195238818547e-05 loss: 0.1111 (0.1193) time: 3.3751 data: 0.0097 max mem: 33369 +Epoch: [5] [1310/1319] eta: 0:00:30 lr: 4.3203283702688355e-05 loss: 0.0966 (0.1191) time: 3.3766 data: 0.0100 max mem: 33369 +Epoch: [5] Total time: 1:14:44 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 2:59:11 time: 4.1788 data: 3.9018 max mem: 33369 +Test: [ 100/2573] eta: 0:05:01 time: 0.0815 data: 0.0017 max mem: 33369 +Test: [ 200/2573] eta: 0:04:08 time: 0.0830 data: 0.0020 max mem: 33369 +Test: [ 300/2573] eta: 0:03:40 time: 0.0831 data: 0.0016 max mem: 33369 +Test: [ 400/2573] eta: 0:03:23 time: 0.0849 data: 0.0018 max mem: 33369 +Test: [ 500/2573] eta: 0:03:10 time: 0.0832 data: 0.0016 max mem: 33369 +Test: [ 600/2573] eta: 0:02:58 time: 0.0821 data: 0.0016 max mem: 33369 +Test: [ 700/2573] eta: 0:02:47 time: 0.0832 data: 0.0017 max mem: 33369 +Test: [ 800/2573] eta: 0:02:37 time: 0.0851 data: 0.0016 max mem: 33369 +Test: [ 900/2573] eta: 0:02:27 time: 0.0814 data: 0.0017 max mem: 33369 +Test: [1000/2573] eta: 0:02:18 time: 0.0844 data: 0.0018 max mem: 33369 +Test: [1100/2573] eta: 0:02:09 time: 0.0869 data: 0.0008 max mem: 33369 +Test: [1200/2573] eta: 0:02:01 time: 0.0882 data: 0.0015 max mem: 33369 +Test: [1300/2573] eta: 0:01:52 time: 0.0855 data: 0.0019 max mem: 33369 +Test: [1400/2573] eta: 0:01:42 time: 0.0859 data: 0.0016 max mem: 33369 +Test: [1500/2573] eta: 0:01:33 time: 0.0832 data: 0.0017 max mem: 33369 +Test: [1600/2573] eta: 0:01:24 time: 0.0863 data: 0.0016 max mem: 33369 +Test: [1700/2573] eta: 0:01:16 time: 0.0823 data: 0.0018 max mem: 33369 +Test: [1800/2573] eta: 0:01:07 time: 0.0850 data: 0.0017 max mem: 33369 +Test: [1900/2573] eta: 0:00:58 time: 0.0830 data: 0.0017 max mem: 33369 +Test: [2000/2573] eta: 0:00:49 time: 0.0879 data: 0.0019 max mem: 33369 +Test: [2100/2573] eta: 0:00:40 time: 0.0854 data: 0.0019 max mem: 33369 +Test: [2200/2573] eta: 0:00:32 time: 0.0866 data: 0.0021 max mem: 33369 +Test: [2300/2573] eta: 0:00:23 time: 0.0843 data: 0.0017 max mem: 33369 +Test: [2400/2573] eta: 0:00:14 time: 0.0807 data: 0.0017 max mem: 33369 +Test: [2500/2573] eta: 0:00:06 time: 0.0838 data: 0.0018 max mem: 33369 +Test: Total time: 0:03:43 +Final results: +Mean IoU is 55.69 + + precision@0.5 = 62.38 + precision@0.6 = 55.27 + precision@0.7 = 46.22 + precision@0.8 = 34.19 + precision@0.9 = 14.34 + overall IoU = 56.70 + +Average object IoU 55.69124471972721 +Overall IoU 56.69709396362305 +Better epoch: 5 + +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [6] [ 0/1319] eta: 2:17:48 lr: 4.319548172049932e-05 loss: 0.0517 (0.0517) time: 6.2686 data: 2.4316 max mem: 33369 +Epoch: [6] [ 10/1319] eta: 1:20:22 lr: 4.318681266775505e-05 loss: 0.0855 (0.1033) time: 3.6843 data: 0.2318 max mem: 33369 +Epoch: [6] [ 20/1319] eta: 1:16:16 lr: 4.317814342165404e-05 loss: 0.0882 (0.1076) time: 3.3857 data: 0.0106 max mem: 33369 +Epoch: [6] [ 30/1319] eta: 1:14:41 lr: 4.316947398214883e-05 loss: 0.0831 (0.1001) time: 3.3629 data: 0.0099 max mem: 33369 +Epoch: [6] [ 40/1319] eta: 1:13:35 lr: 4.316080434919196e-05 loss: 0.0831 (0.1018) time: 3.3777 data: 0.0104 max mem: 33369 +Epoch: [6] [ 50/1319] eta: 1:13:43 lr: 4.315213452273593e-05 loss: 0.0863 (0.0995) time: 3.5002 data: 0.0102 max mem: 33369 +Epoch: [6] [ 60/1319] eta: 1:12:48 lr: 4.314346450273323e-05 loss: 0.0915 (0.1037) time: 3.5066 data: 0.0101 max mem: 33369 +Epoch: [6] [ 70/1319] eta: 1:11:59 lr: 4.313479428913631e-05 loss: 0.1033 (0.1054) time: 3.3890 data: 0.0100 max mem: 33369 +Epoch: [6] [ 80/1319] eta: 1:11:15 lr: 4.312612388189762e-05 loss: 0.0968 (0.1048) time: 3.3912 data: 0.0111 max mem: 33369 +Epoch: [6] [ 90/1319] eta: 1:10:39 lr: 4.311745328096956e-05 loss: 0.0940 (0.1053) time: 3.4172 data: 0.0121 max mem: 33369 +Epoch: [6] [ 100/1319] eta: 1:10:00 lr: 4.3108782486304546e-05 loss: 0.0963 (0.1057) time: 3.4250 data: 0.0120 max mem: 33369 +Epoch: [6] [ 110/1319] eta: 1:09:17 lr: 4.310011149785494e-05 loss: 0.1011 (0.1066) time: 3.3881 data: 0.0111 max mem: 33369 +Epoch: [6] [ 120/1319] eta: 1:08:39 lr: 4.309144031557308e-05 loss: 0.0990 (0.1054) time: 3.3857 data: 0.0106 max mem: 33369 +Epoch: [6] [ 130/1319] eta: 1:08:01 lr: 4.308276893941131e-05 loss: 0.0981 (0.1053) time: 3.4016 data: 0.0108 max mem: 33369 +Epoch: [6] [ 140/1319] eta: 1:07:22 lr: 4.307409736932192e-05 loss: 0.0920 (0.1038) time: 3.3880 data: 0.0108 max mem: 33369 +Epoch: [6] [ 150/1319] eta: 1:06:45 lr: 4.306542560525721e-05 loss: 0.0927 (0.1047) time: 3.3841 data: 0.0116 max mem: 33369 +Epoch: [6] [ 160/1319] eta: 1:06:12 lr: 4.305675364716942e-05 loss: 0.1121 (0.1050) time: 3.4187 data: 0.0119 max mem: 33369 +Epoch: [6] [ 170/1319] eta: 1:05:36 lr: 4.3048081495010805e-05 loss: 0.1054 (0.1051) time: 3.4250 data: 0.0123 max mem: 33369 +Epoch: [6] [ 180/1319] eta: 1:04:59 lr: 4.303940914873357e-05 loss: 0.1017 (0.1050) time: 3.3930 data: 0.0131 max mem: 33369 +Epoch: [6] [ 190/1319] eta: 1:04:21 lr: 4.30307366082899e-05 loss: 0.0973 (0.1052) time: 3.3697 data: 0.0127 max mem: 33369 +Epoch: [6] [ 200/1319] eta: 1:03:47 lr: 4.302206387363197e-05 loss: 0.1072 (0.1062) time: 3.3916 data: 0.0119 max mem: 33369 +Epoch: [6] [ 210/1319] eta: 1:03:13 lr: 4.301339094471194e-05 loss: 0.1158 (0.1068) time: 3.4223 data: 0.0110 max mem: 33369 +Epoch: [6] [ 220/1319] eta: 1:02:35 lr: 4.300471782148193e-05 loss: 0.0956 (0.1070) time: 3.3804 data: 0.0106 max mem: 33369 +Epoch: [6] [ 230/1319] eta: 1:01:56 lr: 4.299604450389403e-05 loss: 0.0968 (0.1076) time: 3.3269 data: 0.0111 max mem: 33369 +Epoch: [6] [ 240/1319] eta: 1:01:24 lr: 4.298737099190034e-05 loss: 0.0968 (0.1073) time: 3.3908 data: 0.0120 max mem: 33369 +Epoch: [6] [ 250/1319] eta: 1:00:51 lr: 4.297869728545289e-05 loss: 0.0823 (0.1074) time: 3.4568 data: 0.0116 max mem: 33369 +Epoch: [6] [ 260/1319] eta: 1:00:15 lr: 4.2970023384503735e-05 loss: 0.0867 (0.1070) time: 3.4099 data: 0.0113 max mem: 33369 +Epoch: [6] [ 270/1319] eta: 0:59:40 lr: 4.296134928900489e-05 loss: 0.0871 (0.1071) time: 3.3789 data: 0.0111 max mem: 33369 +Epoch: [6] [ 280/1319] eta: 0:59:16 lr: 4.295267499890832e-05 loss: 0.0924 (0.1068) time: 3.5390 data: 0.0113 max mem: 33369 +Epoch: [6] [ 290/1319] eta: 0:58:43 lr: 4.2944000514166015e-05 loss: 0.0924 (0.1068) time: 3.5695 data: 0.0113 max mem: 33369 +Epoch: [6] [ 300/1319] eta: 0:58:08 lr: 4.293532583472992e-05 loss: 0.0750 (0.1065) time: 3.4200 data: 0.0107 max mem: 33369 +Epoch: [6] [ 310/1319] eta: 0:57:33 lr: 4.292665096055194e-05 loss: 0.0847 (0.1062) time: 3.4081 data: 0.0111 max mem: 33369 +Epoch: [6] [ 320/1319] eta: 0:56:59 lr: 4.2917975891583976e-05 loss: 0.0847 (0.1056) time: 3.4189 data: 0.0106 max mem: 33369 +Epoch: [6] [ 330/1319] eta: 0:56:24 lr: 4.2909300627777926e-05 loss: 0.0926 (0.1055) time: 3.4101 data: 0.0110 max mem: 33369 +Epoch: [6] [ 340/1319] eta: 0:55:49 lr: 4.290062516908562e-05 loss: 0.1080 (0.1058) time: 3.4013 data: 0.0120 max mem: 33369 +Epoch: [6] [ 350/1319] eta: 0:55:14 lr: 4.2891949515458894e-05 loss: 0.1160 (0.1059) time: 3.3940 data: 0.0119 max mem: 33369 +Epoch: [6] [ 360/1319] eta: 0:54:41 lr: 4.288327366684957e-05 loss: 0.1075 (0.1066) time: 3.4323 data: 0.0123 max mem: 33369 +Epoch: [6] [ 370/1319] eta: 0:54:06 lr: 4.287459762320942e-05 loss: 0.0897 (0.1057) time: 3.4222 data: 0.0125 max mem: 33369 +Epoch: [6] [ 380/1319] eta: 0:53:31 lr: 4.28659213844902e-05 loss: 0.0735 (0.1053) time: 3.3804 data: 0.0128 max mem: 33369 +Epoch: [6] [ 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3.3999 data: 0.0109 max mem: 33369 +Epoch: [6] [ 710/1319] eta: 0:34:38 lr: 4.257949575034011e-05 loss: 0.1023 (0.1076) time: 3.3987 data: 0.0112 max mem: 33369 +Epoch: [6] [ 720/1319] eta: 0:34:04 lr: 4.257081285006789e-05 loss: 0.1075 (0.1078) time: 3.3658 data: 0.0126 max mem: 33369 +Epoch: [6] [ 730/1319] eta: 0:33:31 lr: 4.256212975301382e-05 loss: 0.1092 (0.1078) time: 3.4379 data: 0.0129 max mem: 33369 +Epoch: [6] [ 740/1319] eta: 0:32:57 lr: 4.255344645912884e-05 loss: 0.0994 (0.1078) time: 3.4797 data: 0.0118 max mem: 33369 +Epoch: [6] [ 750/1319] eta: 0:32:22 lr: 4.254476296836386e-05 loss: 0.0826 (0.1076) time: 3.4162 data: 0.0117 max mem: 33369 +Epoch: [6] [ 760/1319] eta: 0:31:48 lr: 4.253607928066978e-05 loss: 0.0857 (0.1077) time: 3.3886 data: 0.0122 max mem: 33369 +Epoch: [6] [ 770/1319] eta: 0:31:13 lr: 4.252739539599743e-05 loss: 0.1144 (0.1081) time: 3.3701 data: 0.0122 max mem: 33369 +Epoch: [6] [ 780/1319] eta: 0:30:39 lr: 4.2518711314297674e-05 loss: 0.1174 (0.1082) time: 3.3915 data: 0.0129 max mem: 33369 +Epoch: [6] [ 790/1319] eta: 0:30:05 lr: 4.2510027035521314e-05 loss: 0.1092 (0.1083) time: 3.4088 data: 0.0128 max mem: 33369 +Epoch: [6] [ 800/1319] eta: 0:29:31 lr: 4.250134255961916e-05 loss: 0.1140 (0.1083) time: 3.4047 data: 0.0115 max mem: 33369 +Epoch: [6] [ 810/1319] eta: 0:28:57 lr: 4.2492657886541955e-05 loss: 0.0920 (0.1083) time: 3.4209 data: 0.0124 max mem: 33369 +Epoch: [6] [ 820/1319] eta: 0:28:23 lr: 4.2483973016240455e-05 loss: 0.0886 (0.1081) time: 3.4411 data: 0.0116 max mem: 33369 +Epoch: [6] [ 830/1319] eta: 0:27:49 lr: 4.247528794866539e-05 loss: 0.0886 (0.1084) time: 3.4387 data: 0.0104 max mem: 33369 +Epoch: [6] [ 840/1319] eta: 0:27:14 lr: 4.2466602683767445e-05 loss: 0.0933 (0.1083) time: 3.3956 data: 0.0114 max mem: 33369 +Epoch: [6] [ 850/1319] eta: 0:26:41 lr: 4.24579172214973e-05 loss: 0.1000 (0.1086) time: 3.4353 data: 0.0112 max mem: 33369 +Epoch: [6] [ 860/1319] eta: 0:26:07 lr: 4.244923156180561e-05 loss: 0.1000 (0.1085) time: 3.4789 data: 0.0109 max mem: 33369 +Epoch: [6] [ 870/1319] eta: 0:25:33 lr: 4.2440545704643e-05 loss: 0.0927 (0.1085) time: 3.4156 data: 0.0108 max mem: 33369 +Epoch: [6] [ 880/1319] eta: 0:24:59 lr: 4.243185964996007e-05 loss: 0.1067 (0.1086) time: 3.4147 data: 0.0111 max mem: 33369 +Epoch: [6] [ 890/1319] eta: 0:24:25 lr: 4.24231733977074e-05 loss: 0.1067 (0.1086) time: 3.4362 data: 0.0126 max mem: 33369 +Epoch: [6] [ 900/1319] eta: 0:23:50 lr: 4.2414486947835554e-05 loss: 0.0977 (0.1087) time: 3.3833 data: 0.0135 max mem: 33369 +Epoch: [6] [ 910/1319] eta: 0:23:16 lr: 4.240580030029505e-05 loss: 0.0986 (0.1086) time: 3.3675 data: 0.0126 max mem: 33369 +Epoch: [6] [ 920/1319] eta: 0:22:42 lr: 4.239711345503641e-05 loss: 0.0986 (0.1088) time: 3.4069 data: 0.0123 max mem: 33369 +Epoch: [6] [ 930/1319] eta: 0:22:07 lr: 4.2388426412010114e-05 loss: 0.1089 (0.1089) time: 3.4109 data: 0.0126 max mem: 33369 +Epoch: [6] [ 940/1319] eta: 0:21:33 lr: 4.237973917116662e-05 loss: 0.1061 (0.1088) time: 3.3729 data: 0.0115 max mem: 33369 +Epoch: [6] [ 950/1319] eta: 0:20:59 lr: 4.237105173245638e-05 loss: 0.0983 (0.1087) time: 3.3583 data: 0.0106 max mem: 33369 +Epoch: [6] [ 960/1319] eta: 0:20:25 lr: 4.23623640958298e-05 loss: 0.0900 (0.1089) time: 3.4040 data: 0.0107 max mem: 33369 +Epoch: [6] [ 970/1319] eta: 0:19:51 lr: 4.235367626123727e-05 loss: 0.0915 (0.1089) time: 3.4302 data: 0.0115 max mem: 33369 +Epoch: [6] [ 980/1319] eta: 0:19:16 lr: 4.234498822862916e-05 loss: 0.1044 (0.1090) time: 3.3965 data: 0.0114 max mem: 33369 +Epoch: [6] [ 990/1319] eta: 0:18:43 lr: 4.23362999979558e-05 loss: 0.0996 (0.1089) time: 3.4309 data: 0.0108 max mem: 33369 +Epoch: [6] [1000/1319] eta: 0:18:08 lr: 4.2327611569167524e-05 loss: 0.0983 (0.1089) time: 3.4551 data: 0.0113 max mem: 33369 +Epoch: [6] [1010/1319] eta: 0:17:34 lr: 4.2318922942214635e-05 loss: 0.0983 (0.1090) time: 3.4077 data: 0.0119 max mem: 33369 +Epoch: [6] [1020/1319] eta: 0:17:00 lr: 4.231023411704738e-05 loss: 0.1039 (0.1089) time: 3.3892 data: 0.0125 max mem: 33369 +Epoch: [6] [1030/1319] eta: 0:16:26 lr: 4.230154509361603e-05 loss: 0.1117 (0.1092) time: 3.3502 data: 0.0118 max mem: 33369 +Epoch: [6] [1040/1319] eta: 0:15:52 lr: 4.229285587187079e-05 loss: 0.1193 (0.1091) time: 3.3750 data: 0.0109 max mem: 33369 +Epoch: [6] [1050/1319] eta: 0:15:17 lr: 4.2284166451761876e-05 loss: 0.1105 (0.1092) time: 3.4163 data: 0.0112 max mem: 33369 +Epoch: [6] [1060/1319] eta: 0:14:43 lr: 4.2275476833239456e-05 loss: 0.0984 (0.1092) time: 3.4085 data: 0.0108 max mem: 33369 +Epoch: [6] [1070/1319] eta: 0:14:09 lr: 4.2266787016253686e-05 loss: 0.0927 (0.1091) time: 3.4708 data: 0.0107 max mem: 33369 +Epoch: [6] [1080/1319] eta: 0:13:35 lr: 4.22580970007547e-05 loss: 0.0961 (0.1091) time: 3.4683 data: 0.0116 max mem: 33369 +Epoch: [6] [1090/1319] eta: 0:13:01 lr: 4.224940678669259e-05 loss: 0.0861 (0.1090) time: 3.3811 data: 0.0118 max mem: 33369 +Epoch: [6] 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+Epoch: [6] [1180/1319] eta: 0:07:54 lr: 4.217118591654868e-05 loss: 0.1149 (0.1088) time: 3.3596 data: 0.0127 max mem: 33369 +Epoch: [6] [1190/1319] eta: 0:07:20 lr: 4.2162493714105874e-05 loss: 0.0933 (0.1087) time: 3.4564 data: 0.0123 max mem: 33369 +Epoch: [6] [1200/1319] eta: 0:06:46 lr: 4.2153801312549505e-05 loss: 0.0859 (0.1086) time: 3.4302 data: 0.0112 max mem: 33369 +Epoch: [6] [1210/1319] eta: 0:06:12 lr: 4.2145108711829405e-05 loss: 0.0771 (0.1084) time: 3.3690 data: 0.0105 max mem: 33369 +Epoch: [6] [1220/1319] eta: 0:05:37 lr: 4.213641591189537e-05 loss: 0.0822 (0.1083) time: 3.3712 data: 0.0109 max mem: 33369 +Epoch: [6] [1230/1319] eta: 0:05:03 lr: 4.212772291269716e-05 loss: 0.0926 (0.1083) time: 3.3782 data: 0.0115 max mem: 33369 +Epoch: [6] [1240/1319] eta: 0:04:29 lr: 4.2119029714184504e-05 loss: 0.1076 (0.1084) time: 3.3716 data: 0.0117 max mem: 33369 +Epoch: [6] [1250/1319] eta: 0:03:55 lr: 4.211033631630714e-05 loss: 0.1158 (0.1086) time: 3.3172 data: 0.0116 max mem: 33369 +Epoch: [6] [1260/1319] eta: 0:03:21 lr: 4.2101642719014764e-05 loss: 0.1141 (0.1085) time: 3.3412 data: 0.0110 max mem: 33369 +Epoch: [6] [1270/1319] eta: 0:02:47 lr: 4.2092948922257045e-05 loss: 0.1106 (0.1086) time: 3.3657 data: 0.0112 max mem: 33369 +Epoch: [6] [1280/1319] eta: 0:02:12 lr: 4.208425492598362e-05 loss: 0.1136 (0.1089) time: 3.3724 data: 0.0123 max mem: 33369 +Epoch: [6] [1290/1319] eta: 0:01:38 lr: 4.207556073014412e-05 loss: 0.1254 (0.1090) time: 3.3929 data: 0.0127 max mem: 33369 +Epoch: [6] [1300/1319] eta: 0:01:04 lr: 4.2066866334688144e-05 loss: 0.0933 (0.1089) time: 3.3327 data: 0.0125 max mem: 33369 +Epoch: [6] [1310/1319] eta: 0:00:30 lr: 4.205817173956526e-05 loss: 0.1005 (0.1091) time: 3.3052 data: 0.0112 max mem: 33369 +Epoch: [6] Total time: 1:14:56 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 2:44:42 time: 3.8408 data: 3.7251 max mem: 33369 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 100/2573] eta: 0:04:58 time: 0.0815 data: 0.0019 max mem: 33369 +Test: [ 200/2573] eta: 0:04:07 time: 0.0888 data: 0.0023 max mem: 33369 +Test: [ 300/2573] eta: 0:03:39 time: 0.0833 data: 0.0016 max mem: 33369 +Test: [ 400/2573] eta: 0:03:24 time: 0.0897 data: 0.0021 max mem: 33369 +Test: [ 500/2573] eta: 0:03:10 time: 0.0841 data: 0.0019 max mem: 33369 +Test: [ 600/2573] eta: 0:02:58 time: 0.0833 data: 0.0016 max mem: 33369 +Test: [ 700/2573] eta: 0:02:48 time: 0.0839 data: 0.0017 max mem: 33369 +Test: [ 800/2573] eta: 0:02:38 time: 0.0909 data: 0.0023 max mem: 33369 +Test: [ 900/2573] eta: 0:02:29 time: 0.0876 data: 0.0021 max mem: 33369 +Test: [1000/2573] eta: 0:02:20 time: 0.0896 data: 0.0023 max mem: 33369 +Test: [1100/2573] eta: 0:02:11 time: 0.0821 data: 0.0018 max mem: 33369 +Test: [1200/2573] eta: 0:02:01 time: 0.0862 data: 0.0017 max mem: 33369 +Test: [1300/2573] eta: 0:01:52 time: 0.0889 data: 0.0022 max mem: 33369 +Test: [1400/2573] eta: 0:01:43 time: 0.0841 data: 0.0017 max mem: 33369 +Test: [1500/2573] eta: 0:01:34 time: 0.0860 data: 0.0019 max mem: 33369 +Test: [1600/2573] eta: 0:01:25 time: 0.0853 data: 0.0016 max mem: 33369 +Test: [1700/2573] eta: 0:01:16 time: 0.0851 data: 0.0019 max mem: 33369 +Test: [1800/2573] eta: 0:01:07 time: 0.0859 data: 0.0019 max mem: 33369 +Test: [1900/2573] eta: 0:00:58 time: 0.0837 data: 0.0021 max mem: 33369 +Test: [2000/2573] eta: 0:00:49 time: 0.0835 data: 0.0017 max mem: 33369 +Test: [2100/2573] eta: 0:00:41 time: 0.0905 data: 0.0023 max mem: 33369 +Test: [2200/2573] eta: 0:00:32 time: 0.0844 data: 0.0015 max mem: 33369 +Test: [2300/2573] eta: 0:00:23 time: 0.0853 data: 0.0016 max mem: 33369 +Test: [2400/2573] eta: 0:00:15 time: 0.0806 data: 0.0016 max mem: 33369 +Test: [2500/2573] eta: 0:00:06 time: 0.0835 data: 0.0017 max mem: 33369 +Test: Total time: 0:03:43 +Final results: +Mean IoU is 58.50 + + precision@0.5 = 65.16 + precision@0.6 = 57.25 + precision@0.7 = 47.04 + precision@0.8 = 34.13 + precision@0.9 = 14.58 + overall IoU = 57.93 + +Average object IoU 58.49811998544213 +Overall IoU 57.933013916015625 +Better epoch: 6 + +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [7] [ 0/1319] eta: 2:26:43 lr: 4.205034643319776e-05 loss: 0.0872 (0.0872) time: 6.6746 data: 2.9740 max mem: 33369 +Epoch: [7] [ 10/1319] eta: 1:24:44 lr: 4.204165145856875e-05 loss: 0.0721 (0.0849) time: 3.8841 data: 0.2792 max mem: 33369 +Epoch: [7] [ 20/1319] eta: 1:18:37 lr: 4.203295628412646e-05 loss: 0.0785 (0.0843) time: 3.4798 data: 0.0102 max mem: 33369 +Epoch: [7] [ 30/1319] eta: 1:16:20 lr: 4.202426090982037e-05 loss: 0.0821 (0.0896) time: 3.3715 data: 0.0121 max mem: 33369 +Epoch: [7] [ 40/1319] eta: 1:15:34 lr: 4.201556533559993e-05 loss: 0.0908 (0.0923) time: 3.4547 data: 0.0123 max mem: 33369 +Epoch: [7] [ 50/1319] eta: 1:14:40 lr: 4.2006869561414584e-05 loss: 0.0943 (0.0952) time: 3.4959 data: 0.0119 max mem: 33369 +Epoch: [7] [ 60/1319] eta: 1:13:23 lr: 4.199817358721372e-05 loss: 0.0943 (0.0953) time: 3.4001 data: 0.0113 max mem: 33369 +Epoch: [7] [ 70/1319] eta: 1:12:33 lr: 4.1989477412946735e-05 loss: 0.1074 (0.1003) time: 3.3701 data: 0.0102 max mem: 33369 +Epoch: [7] [ 80/1319] eta: 1:11:44 lr: 4.1980781038562975e-05 loss: 0.1074 (0.1010) time: 3.4024 data: 0.0108 max mem: 33369 +Epoch: [7] [ 90/1319] eta: 1:10:54 lr: 4.1972084464011784e-05 loss: 0.0940 (0.1018) time: 3.3776 data: 0.0119 max mem: 33369 +Epoch: [7] [ 100/1319] eta: 1:10:06 lr: 4.1963387689242456e-05 loss: 0.1005 (0.1018) time: 3.3573 data: 0.0114 max mem: 33369 +Epoch: [7] [ 110/1319] eta: 1:09:30 lr: 4.1954690714204276e-05 loss: 0.0878 (0.1012) time: 3.3919 data: 0.0109 max mem: 33369 +Epoch: [7] [ 120/1319] eta: 1:08:58 lr: 4.194599353884651e-05 loss: 0.0976 (0.1043) time: 3.4562 data: 0.0128 max mem: 33369 +Epoch: [7] [ 130/1319] eta: 1:08:11 lr: 4.193729616311839e-05 loss: 0.1100 (0.1038) time: 3.3949 data: 0.0129 max mem: 33369 +Epoch: [7] [ 140/1319] eta: 1:07:24 lr: 4.1928598586969124e-05 loss: 0.1018 (0.1045) time: 3.3003 data: 0.0111 max mem: 33369 +Epoch: [7] [ 150/1319] eta: 1:06:52 lr: 4.1919900810347894e-05 loss: 0.1018 (0.1061) time: 3.3777 data: 0.0106 max mem: 33369 +Epoch: [7] [ 160/1319] eta: 1:06:17 lr: 4.191120283320388e-05 loss: 0.0951 (0.1062) time: 3.4414 data: 0.0103 max mem: 33369 +Epoch: [7] [ 170/1319] eta: 1:05:37 lr: 4.190250465548619e-05 loss: 0.0804 (0.1048) time: 3.3833 data: 0.0105 max mem: 33369 +Epoch: [7] [ 180/1319] eta: 1:04:58 lr: 4.189380627714394e-05 loss: 0.0694 (0.1040) time: 3.3502 data: 0.0111 max mem: 33369 +Epoch: [7] [ 190/1319] eta: 1:04:23 lr: 4.188510769812624e-05 loss: 0.0714 (0.1032) time: 3.3821 data: 0.0110 max mem: 33369 +Epoch: [7] [ 200/1319] eta: 1:03:56 lr: 4.1876408918382123e-05 loss: 0.0780 (0.1023) time: 3.4770 data: 0.0111 max mem: 33369 +Epoch: [7] [ 210/1319] eta: 1:03:16 lr: 4.1867709937860646e-05 loss: 0.0780 (0.1017) time: 3.4384 data: 0.0109 max mem: 33369 +Epoch: [7] [ 220/1319] eta: 1:02:40 lr: 4.185901075651081e-05 loss: 0.0790 (0.1009) time: 3.3560 data: 0.0104 max mem: 33369 +Epoch: [7] [ 230/1319] eta: 1:02:08 lr: 4.185031137428161e-05 loss: 0.0790 (0.1005) time: 3.4272 data: 0.0113 max mem: 33369 +Epoch: [7] [ 240/1319] eta: 1:01:35 lr: 4.1841611791121996e-05 loss: 0.0822 (0.0999) time: 3.4582 data: 0.0128 max mem: 33369 +Epoch: [7] [ 250/1319] eta: 1:00:59 lr: 4.183291200698093e-05 loss: 0.0812 (0.0995) time: 3.4160 data: 0.0119 max mem: 33369 +Epoch: [7] [ 260/1319] eta: 1:00:23 lr: 4.182421202180731e-05 loss: 0.0883 (0.1000) time: 3.3902 data: 0.0111 max mem: 33369 +Epoch: [7] [ 270/1319] eta: 0:59:50 lr: 4.181551183555002e-05 loss: 0.1110 (0.1005) time: 3.4117 data: 0.0108 max mem: 33369 +Epoch: [7] [ 280/1319] eta: 0:59:17 lr: 4.180681144815793e-05 loss: 0.1026 (0.1008) time: 3.4485 data: 0.0107 max mem: 33369 +Epoch: [7] [ 290/1319] eta: 0:58:41 lr: 4.179811085957988e-05 loss: 0.0849 (0.1000) time: 3.4198 data: 0.0116 max mem: 33369 +Epoch: [7] [ 300/1319] eta: 0:58:05 lr: 4.178941006976469e-05 loss: 0.0811 (0.0995) time: 3.3762 data: 0.0112 max mem: 33369 +Epoch: [7] [ 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4.130184307482921e-05 loss: 0.1094 (0.1009) time: 3.4845 data: 0.0100 max mem: 33369 +Epoch: [7] [ 870/1319] eta: 0:25:32 lr: 4.1293130729069835e-05 loss: 0.0935 (0.1009) time: 3.4673 data: 0.0107 max mem: 33369 +Epoch: [7] [ 880/1319] eta: 0:24:58 lr: 4.128441817906139e-05 loss: 0.0857 (0.1008) time: 3.4084 data: 0.0122 max mem: 33369 +Epoch: [7] [ 890/1319] eta: 0:24:24 lr: 4.1275705424751206e-05 loss: 0.0873 (0.1010) time: 3.4480 data: 0.0116 max mem: 33369 +Epoch: [7] [ 900/1319] eta: 0:23:50 lr: 4.1266992466086555e-05 loss: 0.0873 (0.1008) time: 3.4193 data: 0.0114 max mem: 33369 +Epoch: [7] [ 910/1319] eta: 0:23:15 lr: 4.125827930301473e-05 loss: 0.0878 (0.1007) time: 3.3781 data: 0.0125 max mem: 33369 +Epoch: [7] [ 920/1319] eta: 0:22:42 lr: 4.124956593548294e-05 loss: 0.0923 (0.1008) time: 3.4316 data: 0.0115 max mem: 33369 +Epoch: [7] [ 930/1319] eta: 0:22:07 lr: 4.124085236343841e-05 loss: 0.0914 (0.1008) time: 3.4254 data: 0.0108 max mem: 33369 +Epoch: [7] [ 940/1319] eta: 0:21:33 lr: 4.123213858682832e-05 loss: 0.0834 (0.1006) time: 3.3765 data: 0.0108 max mem: 33369 +Epoch: [7] [ 950/1319] eta: 0:20:59 lr: 4.122342460559985e-05 loss: 0.0834 (0.1005) time: 3.3808 data: 0.0105 max mem: 33369 +Epoch: [7] [ 960/1319] eta: 0:20:25 lr: 4.12147104197001e-05 loss: 0.0899 (0.1005) time: 3.4515 data: 0.0106 max mem: 33369 +Epoch: [7] [ 970/1319] eta: 0:19:51 lr: 4.12059960290762e-05 loss: 0.0898 (0.1005) time: 3.4896 data: 0.0102 max mem: 33369 +Epoch: [7] [ 980/1319] eta: 0:19:17 lr: 4.119728143367523e-05 loss: 0.0898 (0.1006) time: 3.4497 data: 0.0103 max mem: 33369 +Epoch: [7] [ 990/1319] eta: 0:18:43 lr: 4.1188566633444246e-05 loss: 0.1068 (0.1007) time: 3.3736 data: 0.0100 max mem: 33369 +Epoch: [7] [1000/1319] eta: 0:18:08 lr: 4.1179851628330275e-05 loss: 0.1103 (0.1009) time: 3.3310 data: 0.0104 max mem: 33369 +Epoch: [7] [1010/1319] eta: 0:17:34 lr: 4.117113641828032e-05 loss: 0.1149 (0.1010) time: 3.3830 data: 0.0114 max mem: 33369 +Epoch: [7] 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+Epoch: [7] [1100/1319] eta: 0:12:27 lr: 4.109269029695397e-05 loss: 0.0921 (0.1008) time: 3.4129 data: 0.0112 max mem: 33369 +Epoch: [7] [1110/1319] eta: 0:11:53 lr: 4.108397303462358e-05 loss: 0.0847 (0.1009) time: 3.3792 data: 0.0118 max mem: 33369 +Epoch: [7] [1120/1319] eta: 0:11:19 lr: 4.1075255566772506e-05 loss: 0.1086 (0.1011) time: 3.4417 data: 0.0120 max mem: 33369 +Epoch: [7] [1130/1319] eta: 0:10:45 lr: 4.106653789334745e-05 loss: 0.1130 (0.1012) time: 3.5304 data: 0.0111 max mem: 33369 +Epoch: [7] [1140/1319] eta: 0:10:10 lr: 4.105782001429505e-05 loss: 0.1175 (0.1015) time: 3.4607 data: 0.0098 max mem: 33369 +Epoch: [7] [1150/1319] eta: 0:09:36 lr: 4.104910192956196e-05 loss: 0.0970 (0.1014) time: 3.3479 data: 0.0096 max mem: 33369 +Epoch: [7] [1160/1319] eta: 0:09:02 lr: 4.104038363909479e-05 loss: 0.0819 (0.1012) time: 3.3869 data: 0.0108 max mem: 33369 +Epoch: [7] [1170/1319] eta: 0:08:28 lr: 4.1031665142840106e-05 loss: 0.0819 (0.1011) time: 3.4183 data: 0.0105 max mem: 33369 +Epoch: [7] [1180/1319] eta: 0:07:54 lr: 4.1022946440744476e-05 loss: 0.0889 (0.1013) time: 3.4030 data: 0.0098 max mem: 33369 +Epoch: [7] [1190/1319] eta: 0:07:20 lr: 4.1014227532754415e-05 loss: 0.0906 (0.1013) time: 3.3734 data: 0.0112 max mem: 33369 +Epoch: [7] [1200/1319] eta: 0:06:46 lr: 4.100550841881645e-05 loss: 0.0842 (0.1013) time: 3.3775 data: 0.0126 max mem: 33369 +Epoch: [7] [1210/1319] eta: 0:06:11 lr: 4.099678909887704e-05 loss: 0.0800 (0.1012) time: 3.4043 data: 0.0130 max mem: 33369 +Epoch: [7] [1220/1319] eta: 0:05:37 lr: 4.098806957288263e-05 loss: 0.0901 (0.1013) time: 3.3737 data: 0.0113 max mem: 33369 +Epoch: [7] [1230/1319] eta: 0:05:03 lr: 4.0979349840779665e-05 loss: 0.0901 (0.1012) time: 3.3557 data: 0.0098 max mem: 33369 +Epoch: [7] [1240/1319] eta: 0:04:29 lr: 4.0970629902514516e-05 loss: 0.0853 (0.1011) time: 3.3903 data: 0.0104 max mem: 33369 +Epoch: [7] [1250/1319] eta: 0:03:55 lr: 4.0961909758033565e-05 loss: 0.0969 (0.1012) time: 3.4031 data: 0.0109 max mem: 33369 +Epoch: [7] [1260/1319] eta: 0:03:21 lr: 4.095318940728316e-05 loss: 0.1015 (0.1011) time: 3.3484 data: 0.0101 max mem: 33369 +Epoch: [7] [1270/1319] eta: 0:02:47 lr: 4.0944468850209605e-05 loss: 0.0907 (0.1010) time: 3.3018 data: 0.0096 max mem: 33369 +Epoch: [7] [1280/1319] eta: 0:02:12 lr: 4.093574808675919e-05 loss: 0.0882 (0.1010) time: 3.3457 data: 0.0108 max mem: 33369 +Epoch: [7] [1290/1319] eta: 0:01:38 lr: 4.09270271168782e-05 loss: 0.1144 (0.1012) time: 3.3995 data: 0.0108 max mem: 33369 +Epoch: [7] [1300/1319] eta: 0:01:04 lr: 4.091830594051285e-05 loss: 0.1034 (0.1012) time: 3.3701 data: 0.0094 max mem: 33369 +Epoch: [7] [1310/1319] eta: 0:00:30 lr: 4.090958455760934e-05 loss: 0.0882 (0.1014) time: 3.3842 data: 0.0089 max mem: 33369 +Epoch: [7] Total time: 1:14:56 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 2:49:08 time: 3.9443 data: 3.8516 max mem: 33369 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 100/2573] eta: 0:05:12 time: 0.0879 data: 0.0021 max mem: 33369 +Test: [ 200/2573] eta: 0:04:09 time: 0.0829 data: 0.0017 max mem: 33369 +Test: [ 300/2573] eta: 0:03:43 time: 0.0858 data: 0.0017 max mem: 33369 +Test: [ 400/2573] eta: 0:03:25 time: 0.0834 data: 0.0016 max mem: 33369 +Test: [ 500/2573] eta: 0:03:11 time: 0.0832 data: 0.0017 max mem: 33369 +Test: [ 600/2573] eta: 0:03:00 time: 0.0885 data: 0.0022 max mem: 33369 +Test: [ 700/2573] eta: 0:02:50 time: 0.0838 data: 0.0017 max mem: 33369 +Test: [ 800/2573] eta: 0:02:40 time: 0.0875 data: 0.0018 max mem: 33369 +Test: [ 900/2573] eta: 0:02:30 time: 0.0906 data: 0.0021 max mem: 33369 +Test: [1000/2573] eta: 0:02:21 time: 0.0902 data: 0.0023 max mem: 33369 +Test: [1100/2573] eta: 0:02:11 time: 0.0837 data: 0.0017 max mem: 33369 +Test: [1200/2573] eta: 0:02:02 time: 0.0892 data: 0.0021 max mem: 33369 +Test: [1300/2573] eta: 0:01:52 time: 0.0834 data: 0.0015 max mem: 33369 +Test: [1400/2573] eta: 0:01:43 time: 0.0826 data: 0.0017 max mem: 33369 +Test: [1500/2573] eta: 0:01:34 time: 0.0865 data: 0.0019 max mem: 33369 +Test: [1600/2573] eta: 0:01:25 time: 0.0927 data: 0.0023 max mem: 33369 +Test: [1700/2573] eta: 0:01:17 time: 0.0817 data: 0.0018 max mem: 33369 +Test: [1800/2573] eta: 0:01:08 time: 0.0856 data: 0.0018 max mem: 33369 +Test: [1900/2573] eta: 0:00:59 time: 0.0825 data: 0.0016 max mem: 33369 +Test: [2000/2573] eta: 0:00:50 time: 0.0839 data: 0.0016 max mem: 33369 +Test: [2100/2573] eta: 0:00:41 time: 0.0898 data: 0.0021 max mem: 33369 +Test: [2200/2573] eta: 0:00:32 time: 0.0851 data: 0.0015 max mem: 33369 +Test: [2300/2573] eta: 0:00:23 time: 0.0849 data: 0.0019 max mem: 33369 +Test: [2400/2573] eta: 0:00:15 time: 0.0863 data: 0.0020 max mem: 33369 +Test: [2500/2573] eta: 0:00:06 time: 0.0848 data: 0.0016 max mem: 33369 +Test: Total time: 0:03:45 +Final results: +Mean IoU is 59.24 + + precision@0.5 = 65.65 + precision@0.6 = 58.42 + precision@0.7 = 49.65 + precision@0.8 = 37.66 + precision@0.9 = 15.95 + overall IoU = 58.45 + +Average object IoU 59.240697178490386 +Overall IoU 58.450340270996094 +Better epoch: 7 + +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [8] [ 0/1319] eta: 2:10:42 lr: 4.09017351363616e-05 loss: 0.1173 (0.1173) time: 5.9456 data: 2.3236 max mem: 33369 +Epoch: [8] [ 10/1319] eta: 1:19:45 lr: 4.089301336088734e-05 loss: 0.1027 (0.0967) time: 3.6556 data: 0.2223 max mem: 33369 +Epoch: [8] [ 20/1319] eta: 1:16:27 lr: 4.088429137871879e-05 loss: 0.0835 (0.0944) time: 3.4112 data: 0.0108 max mem: 33369 +Epoch: [8] [ 30/1319] eta: 1:14:43 lr: 4.087556918980205e-05 loss: 0.0887 (0.0966) time: 3.3809 data: 0.0100 max mem: 33369 +Epoch: [8] [ 40/1319] eta: 1:13:20 lr: 4.0866846794083216e-05 loss: 0.0826 (0.0923) time: 3.3441 data: 0.0110 max mem: 33369 +Epoch: [8] [ 50/1319] eta: 1:12:24 lr: 4.0858124191508315e-05 loss: 0.0716 (0.0890) time: 3.3387 data: 0.0106 max mem: 33369 +Epoch: [8] [ 60/1319] eta: 1:11:35 lr: 4.08494013820234e-05 loss: 0.0822 (0.0948) time: 3.3547 data: 0.0100 max mem: 33369 +Epoch: [8] [ 70/1319] eta: 1:10:51 lr: 4.0840678365574436e-05 loss: 0.0978 (0.0990) time: 3.3532 data: 0.0117 max mem: 33369 +Epoch: [8] [ 80/1319] eta: 1:10:14 lr: 4.083195514210742e-05 loss: 0.0918 (0.0968) time: 3.3694 data: 0.0125 max mem: 33369 +Epoch: [8] [ 90/1319] eta: 1:09:46 lr: 4.0823231711568287e-05 loss: 0.0703 (0.0935) time: 3.4147 data: 0.0118 max mem: 33369 +Epoch: [8] [ 100/1319] eta: 1:09:07 lr: 4.081450807390295e-05 loss: 0.0722 (0.0927) time: 3.4056 data: 0.0122 max mem: 33369 +Epoch: [8] [ 110/1319] eta: 1:08:30 lr: 4.0805784229057304e-05 loss: 0.0787 (0.0916) time: 3.3716 data: 0.0116 max mem: 33369 +Epoch: [8] [ 120/1319] eta: 1:08:05 lr: 4.079706017697721e-05 loss: 0.0813 (0.0918) time: 3.4347 data: 0.0114 max mem: 33369 +Epoch: [8] [ 130/1319] eta: 1:07:42 lr: 4.0788335917608504e-05 loss: 0.0902 (0.0923) time: 3.5118 data: 0.0116 max mem: 33369 +Epoch: [8] [ 140/1319] eta: 1:07:03 lr: 4.077961145089699e-05 loss: 0.0873 (0.0920) time: 3.4403 data: 0.0120 max mem: 33369 +Epoch: [8] [ 150/1319] eta: 1:06:21 lr: 4.0770886776788466e-05 loss: 0.0873 (0.0920) time: 3.3341 data: 0.0119 max mem: 33369 +Epoch: [8] [ 160/1319] eta: 1:05:45 lr: 4.076216189522867e-05 loss: 0.0978 (0.0930) time: 3.3463 data: 0.0117 max mem: 33369 +Epoch: [8] [ 170/1319] eta: 1:05:10 lr: 4.075343680616333e-05 loss: 0.0724 (0.0916) time: 3.3869 data: 0.0126 max mem: 33369 +Epoch: [8] [ 180/1319] eta: 1:04:34 lr: 4.074471150953815e-05 loss: 0.0686 (0.0918) time: 3.3844 data: 0.0118 max mem: 33369 +Epoch: [8] [ 190/1319] eta: 1:03:57 lr: 4.0735986005298814e-05 loss: 0.0850 (0.0917) time: 3.3595 data: 0.0110 max mem: 33369 +Epoch: [8] [ 200/1319] eta: 1:03:23 lr: 4.072726029339096e-05 loss: 0.0828 (0.0919) time: 3.3720 data: 0.0110 max mem: 33369 +Epoch: [8] [ 210/1319] eta: 1:02:51 lr: 4.07185343737602e-05 loss: 0.0697 (0.0915) time: 3.4165 data: 0.0104 max mem: 33369 +Epoch: [8] [ 220/1319] eta: 1:02:16 lr: 4.070980824635213e-05 loss: 0.0687 (0.0907) time: 3.4118 data: 0.0110 max mem: 33369 +Epoch: [8] [ 230/1319] eta: 1:01:41 lr: 4.070108191111232e-05 loss: 0.0639 (0.0902) time: 3.3817 data: 0.0121 max mem: 33369 +Epoch: [8] [ 240/1319] eta: 1:01:06 lr: 4.069235536798631e-05 loss: 0.0697 (0.0899) time: 3.3756 data: 0.0115 max mem: 33369 +Epoch: [8] [ 250/1319] eta: 1:00:34 lr: 4.0683628616919596e-05 loss: 0.0697 (0.0894) time: 3.4072 data: 0.0117 max mem: 33369 +Epoch: [8] [ 260/1319] eta: 0:59:59 lr: 4.0674901657857675e-05 loss: 0.0740 (0.0896) time: 3.4141 data: 0.0120 max mem: 33369 +Epoch: [8] [ 270/1319] eta: 0:59:26 lr: 4.066617449074599e-05 loss: 0.0830 (0.0896) time: 3.3959 data: 0.0110 max mem: 33369 +Epoch: [8] [ 280/1319] eta: 0:58:52 lr: 4.065744711552997e-05 loss: 0.0871 (0.0895) time: 3.4009 data: 0.0110 max mem: 33369 +Epoch: [8] [ 290/1319] eta: 0:58:18 lr: 4.064871953215503e-05 loss: 0.0984 (0.0903) time: 3.4003 data: 0.0112 max mem: 33369 +Epoch: [8] [ 300/1319] eta: 0:57:42 lr: 4.063999174056654e-05 loss: 0.0964 (0.0902) time: 3.3760 data: 0.0114 max mem: 33369 +Epoch: [8] [ 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loss: 0.0943 (0.0917) time: 3.2724 data: 0.0090 max mem: 33369 +Epoch: [8] [ 790/1319] eta: 0:29:49 lr: 4.021207374606688e-05 loss: 0.0929 (0.0917) time: 3.2983 data: 0.0089 max mem: 33369 +Epoch: [8] [ 800/1319] eta: 0:29:14 lr: 4.0203335473541464e-05 loss: 0.0981 (0.0918) time: 3.2862 data: 0.0087 max mem: 33369 +Epoch: [8] [ 810/1319] eta: 0:28:39 lr: 4.01945969899798e-05 loss: 0.0939 (0.0918) time: 3.2428 data: 0.0097 max mem: 33369 +Epoch: [8] [ 820/1319] eta: 0:28:05 lr: 4.0185858295325805e-05 loss: 0.0817 (0.0917) time: 3.2738 data: 0.0096 max mem: 33369 +Epoch: [8] [ 830/1319] eta: 0:27:31 lr: 4.017711938952337e-05 loss: 0.0872 (0.0918) time: 3.3072 data: 0.0094 max mem: 33369 +Epoch: [8] [ 840/1319] eta: 0:26:56 lr: 4.0168380272516376e-05 loss: 0.1016 (0.0920) time: 3.2402 data: 0.0093 max mem: 33369 +Epoch: [8] [ 850/1319] eta: 0:26:21 lr: 4.0159640944248643e-05 loss: 0.0945 (0.0920) time: 3.2191 data: 0.0088 max mem: 33369 +Epoch: [8] [ 860/1319] eta: 0:25:48 lr: 4.0150901404663985e-05 loss: 0.0951 (0.0922) time: 3.2861 data: 0.0093 max mem: 33369 +Epoch: [8] [ 870/1319] eta: 0:25:13 lr: 4.0142161653706185e-05 loss: 0.0969 (0.0923) time: 3.3056 data: 0.0094 max mem: 33369 +Epoch: [8] [ 880/1319] eta: 0:24:39 lr: 4.013342169131899e-05 loss: 0.0917 (0.0924) time: 3.2720 data: 0.0093 max mem: 33369 +Epoch: [8] [ 890/1319] eta: 0:24:05 lr: 4.012468151744613e-05 loss: 0.0851 (0.0924) time: 3.2898 data: 0.0090 max mem: 33369 +Epoch: [8] [ 900/1319] eta: 0:23:31 lr: 4.01159411320313e-05 loss: 0.0801 (0.0924) time: 3.3075 data: 0.0090 max mem: 33369 +Epoch: [8] [ 910/1319] eta: 0:22:57 lr: 4.010720053501816e-05 loss: 0.0829 (0.0924) time: 3.2544 data: 0.0096 max mem: 33369 +Epoch: [8] [ 920/1319] eta: 0:22:23 lr: 4.009845972635034e-05 loss: 0.0796 (0.0922) time: 3.2231 data: 0.0094 max mem: 33369 +Epoch: [8] [ 930/1319] eta: 0:21:49 lr: 4.008971870597147e-05 loss: 0.0781 (0.0920) time: 3.2696 data: 0.0092 max mem: 33369 +Epoch: [8] [ 940/1319] eta: 0:21:15 lr: 4.008097747382511e-05 loss: 0.0772 (0.0919) time: 3.3073 data: 0.0099 max mem: 33369 +Epoch: [8] [ 950/1319] eta: 0:20:41 lr: 4.0072236029854826e-05 loss: 0.0866 (0.0921) time: 3.2852 data: 0.0096 max mem: 33369 +Epoch: [8] [ 960/1319] eta: 0:20:07 lr: 4.006349437400413e-05 loss: 0.0996 (0.0923) time: 3.2524 data: 0.0095 max mem: 33369 +Epoch: [8] [ 970/1319] eta: 0:19:33 lr: 4.005475250621652e-05 loss: 0.0840 (0.0922) time: 3.2565 data: 0.0098 max mem: 33369 +Epoch: [8] [ 980/1319] eta: 0:18:59 lr: 4.004601042643546e-05 loss: 0.0840 (0.0922) time: 3.2412 data: 0.0104 max mem: 33369 +Epoch: [8] [ 990/1319] eta: 0:18:24 lr: 4.003726813460439e-05 loss: 0.0894 (0.0923) time: 3.2305 data: 0.0107 max mem: 33369 +Epoch: [8] [1000/1319] eta: 0:17:51 lr: 4.0028525630666715e-05 loss: 0.0894 (0.0923) time: 3.2390 data: 0.0096 max mem: 33369 +Epoch: [8] [1010/1319] eta: 0:17:17 lr: 4.00197829145658e-05 loss: 0.0901 (0.0924) time: 3.2619 data: 0.0100 max mem: 33369 +Epoch: [8] 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+Epoch: [8] [1100/1319] eta: 0:12:13 lr: 3.994108891295557e-05 loss: 0.0821 (0.0927) time: 3.2394 data: 0.0103 max mem: 33369 +Epoch: [8] [1110/1319] eta: 0:11:39 lr: 3.9932344072101854e-05 loss: 0.0821 (0.0928) time: 3.2651 data: 0.0102 max mem: 33369 +Epoch: [8] [1120/1319] eta: 0:11:06 lr: 3.9923599018460164e-05 loss: 0.0915 (0.0928) time: 3.2742 data: 0.0108 max mem: 33369 +Epoch: [8] [1130/1319] eta: 0:10:32 lr: 3.991485375197353e-05 loss: 0.0910 (0.0928) time: 3.2617 data: 0.0100 max mem: 33369 +Epoch: [8] [1140/1319] eta: 0:09:58 lr: 3.990610827258495e-05 loss: 0.0942 (0.0929) time: 3.2234 data: 0.0098 max mem: 33369 +Epoch: [8] [1150/1319] eta: 0:09:25 lr: 3.9897362580237394e-05 loss: 0.0875 (0.0928) time: 3.2460 data: 0.0098 max mem: 33369 +Epoch: [8] [1160/1319] eta: 0:08:51 lr: 3.988861667487383e-05 loss: 0.0808 (0.0928) time: 3.2836 data: 0.0101 max mem: 33369 +Epoch: [8] [1170/1319] eta: 0:08:18 lr: 3.987987055643715e-05 loss: 0.0808 (0.0928) time: 3.2745 data: 0.0103 max mem: 33369 +Epoch: [8] [1180/1319] eta: 0:07:44 lr: 3.9871124224870237e-05 loss: 0.0844 (0.0928) time: 3.2619 data: 0.0101 max mem: 33369 +Epoch: [8] [1190/1319] eta: 0:07:11 lr: 3.986237768011596e-05 loss: 0.0993 (0.0930) time: 3.2431 data: 0.0099 max mem: 33369 +Epoch: [8] [1200/1319] eta: 0:06:37 lr: 3.985363092211714e-05 loss: 0.0817 (0.0930) time: 3.2236 data: 0.0097 max mem: 33369 +Epoch: [8] [1210/1319] eta: 0:06:04 lr: 3.984488395081657e-05 loss: 0.0872 (0.0930) time: 3.2007 data: 0.0108 max mem: 33369 +Epoch: [8] [1220/1319] eta: 0:05:30 lr: 3.9836136766157016e-05 loss: 0.0889 (0.0930) time: 3.1834 data: 0.0114 max mem: 33369 +Epoch: [8] [1230/1319] eta: 0:04:57 lr: 3.9827389368081224e-05 loss: 0.0853 (0.0930) time: 3.2455 data: 0.0108 max mem: 33369 +Epoch: [8] [1240/1319] eta: 0:04:23 lr: 3.9818641756531906e-05 loss: 0.0834 (0.0930) time: 3.2702 data: 0.0105 max mem: 33369 +Epoch: [8] [1250/1319] eta: 0:03:50 lr: 3.980989393145173e-05 loss: 0.0829 (0.0929) time: 3.2214 data: 0.0103 max mem: 33369 +Epoch: [8] [1260/1319] eta: 0:03:16 lr: 3.9801145892783356e-05 loss: 0.0836 (0.0929) time: 3.2573 data: 0.0105 max mem: 33369 +Epoch: [8] [1270/1319] eta: 0:02:43 lr: 3.97923976404694e-05 loss: 0.0960 (0.0930) time: 3.2620 data: 0.0099 max mem: 33369 +Epoch: [8] [1280/1319] eta: 0:02:10 lr: 3.978364917445246e-05 loss: 0.0922 (0.0930) time: 3.2146 data: 0.0097 max mem: 33369 +Epoch: [8] [1290/1319] eta: 0:01:36 lr: 3.9774900494675086e-05 loss: 0.0787 (0.0930) time: 3.2139 data: 0.0101 max mem: 33369 +Epoch: [8] [1300/1319] eta: 0:01:03 lr: 3.976615160107982e-05 loss: 0.0973 (0.0932) time: 3.2332 data: 0.0106 max mem: 33369 +Epoch: [8] [1310/1319] eta: 0:00:29 lr: 3.975740249360917e-05 loss: 0.0862 (0.0930) time: 3.2542 data: 0.0093 max mem: 33369 +Epoch: [8] Total time: 1:13:14 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 2:48:51 time: 3.9377 data: 3.7273 max mem: 33369 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 100/2573] eta: 0:04:54 time: 0.0790 data: 0.0016 max mem: 33369 +Test: [ 200/2573] eta: 0:03:57 time: 0.0798 data: 0.0016 max mem: 33369 +Test: [ 300/2573] eta: 0:03:32 time: 0.0819 data: 0.0016 max mem: 33369 +Test: [ 400/2573] eta: 0:03:16 time: 0.0822 data: 0.0014 max mem: 33369 +Test: [ 500/2573] eta: 0:03:02 time: 0.0808 data: 0.0015 max mem: 33369 +Test: [ 600/2573] eta: 0:02:51 time: 0.0805 data: 0.0017 max mem: 33369 +Test: [ 700/2573] eta: 0:02:41 time: 0.0817 data: 0.0016 max mem: 33369 +Test: [ 800/2573] eta: 0:02:32 time: 0.0845 data: 0.0015 max mem: 33369 +Test: [ 900/2573] eta: 0:02:23 time: 0.0863 data: 0.0021 max mem: 33369 +Test: [1000/2573] eta: 0:02:14 time: 0.0842 data: 0.0019 max mem: 33369 +Test: [1100/2573] eta: 0:02:05 time: 0.0849 data: 0.0019 max mem: 33369 +Test: [1200/2573] eta: 0:01:56 time: 0.0814 data: 0.0016 max mem: 33369 +Test: [1300/2573] eta: 0:01:47 time: 0.0803 data: 0.0015 max mem: 33369 +Test: [1400/2573] eta: 0:01:38 time: 0.0812 data: 0.0015 max mem: 33369 +Test: [1500/2573] eta: 0:01:30 time: 0.0825 data: 0.0017 max mem: 33369 +Test: [1600/2573] eta: 0:01:21 time: 0.0848 data: 0.0016 max mem: 33369 +Test: [1700/2573] eta: 0:01:13 time: 0.0801 data: 0.0015 max mem: 33369 +Test: [1800/2573] eta: 0:01:04 time: 0.0826 data: 0.0018 max mem: 33369 +Test: [1900/2573] eta: 0:00:56 time: 0.0796 data: 0.0016 max mem: 33369 +Test: [2000/2573] eta: 0:00:47 time: 0.0820 data: 0.0016 max mem: 33369 +Test: [2100/2573] eta: 0:00:39 time: 0.0847 data: 0.0016 max mem: 33369 +Test: [2200/2573] eta: 0:00:31 time: 0.0836 data: 0.0017 max mem: 33369 +Test: [2300/2573] eta: 0:00:22 time: 0.0834 data: 0.0016 max mem: 33369 +Test: [2400/2573] eta: 0:00:14 time: 0.0783 data: 0.0016 max mem: 33369 +Test: [2500/2573] eta: 0:00:06 time: 0.0822 data: 0.0017 max mem: 33369 +Test: Total time: 0:03:34 +Final results: +Mean IoU is 59.89 + + precision@0.5 = 66.97 + precision@0.6 = 60.21 + precision@0.7 = 51.72 + precision@0.8 = 39.44 + precision@0.9 = 17.83 + overall IoU = 59.09 + +Average object IoU 59.89326593237896 +Overall IoU 59.092411041259766 +Better epoch: 8 + +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [9] [ 0/1319] eta: 1:59:07 lr: 3.974952811397457e-05 loss: 0.0701 (0.0701) time: 5.4191 data: 1.8818 max mem: 33369 +Epoch: [9] [ 10/1319] eta: 1:15:57 lr: 3.974077859998216e-05 loss: 0.0937 (0.0890) time: 3.4816 data: 0.1806 max mem: 33369 +Epoch: [9] [ 20/1319] eta: 1:12:49 lr: 3.9732028871947454e-05 loss: 0.0741 (0.0903) time: 3.2611 data: 0.0092 max mem: 33369 +Epoch: [9] [ 30/1319] eta: 1:11:37 lr: 3.972327892981283e-05 loss: 0.0692 (0.0866) time: 3.2528 data: 0.0083 max mem: 33369 +Epoch: [9] [ 40/1319] eta: 1:10:37 lr: 3.971452877352066e-05 loss: 0.0702 (0.0933) time: 3.2593 data: 0.0092 max mem: 33369 +Epoch: [9] [ 50/1319] eta: 1:09:41 lr: 3.9705778403013264e-05 loss: 0.0805 (0.0938) time: 3.2342 data: 0.0093 max mem: 33369 +Epoch: [9] [ 60/1319] eta: 1:09:03 lr: 3.969702781823294e-05 loss: 0.0850 (0.0930) time: 3.2460 data: 0.0097 max mem: 33369 +Epoch: [9] [ 70/1319] eta: 1:08:30 lr: 3.9688277019121967e-05 loss: 0.0902 (0.0928) time: 3.2825 data: 0.0097 max mem: 33369 +Epoch: [9] [ 80/1319] eta: 1:07:49 lr: 3.967952600562257e-05 loss: 0.0902 (0.0929) time: 3.2665 data: 0.0097 max mem: 33369 +Epoch: [9] [ 90/1319] eta: 1:07:18 lr: 3.967077477767697e-05 loss: 0.0888 (0.0926) time: 3.2654 data: 0.0102 max mem: 33369 +Epoch: [9] [ 100/1319] eta: 1:07:00 lr: 3.966202333522733e-05 loss: 0.0868 (0.0929) time: 3.3533 data: 0.0100 max mem: 33369 +Epoch: [9] [ 110/1319] eta: 1:06:31 lr: 3.965327167821583e-05 loss: 0.0738 (0.0915) time: 3.3726 data: 0.0101 max mem: 33369 +Epoch: [9] [ 120/1319] eta: 1:05:58 lr: 3.9644519806584564e-05 loss: 0.0718 (0.0912) time: 3.3158 data: 0.0110 max mem: 33369 +Epoch: [9] [ 130/1319] eta: 1:05:22 lr: 3.963576772027564e-05 loss: 0.0725 (0.0905) time: 3.2838 data: 0.0108 max mem: 33369 +Epoch: [9] [ 140/1319] eta: 1:04:48 lr: 3.96270154192311e-05 loss: 0.0829 (0.0900) time: 3.2774 data: 0.0104 max mem: 33369 +Epoch: [9] [ 150/1319] eta: 1:04:12 lr: 3.9618262903393e-05 loss: 0.0739 (0.0893) time: 3.2739 data: 0.0110 max mem: 33369 +Epoch: [9] [ 160/1319] eta: 1:03:39 lr: 3.960951017270332e-05 loss: 0.0660 (0.0878) time: 3.2805 data: 0.0110 max mem: 33369 +Epoch: [9] [ 170/1319] eta: 1:03:12 lr: 3.9600757227104046e-05 loss: 0.0748 (0.0888) time: 3.3381 data: 0.0107 max mem: 33369 +Epoch: [9] [ 180/1319] eta: 1:02:38 lr: 3.95920040665371e-05 loss: 0.0800 (0.0888) time: 3.3294 data: 0.0110 max mem: 33369 +Epoch: [9] [ 190/1319] eta: 1:02:00 lr: 3.958325069094442e-05 loss: 0.0716 (0.0891) time: 3.2512 data: 0.0102 max mem: 33369 +Epoch: [9] [ 200/1319] eta: 1:01:26 lr: 3.957449710026786e-05 loss: 0.0855 (0.0893) time: 3.2453 data: 0.0088 max mem: 33369 +Epoch: [9] [ 210/1319] eta: 1:00:54 lr: 3.9565743294449283e-05 loss: 0.0762 (0.0884) time: 3.3009 data: 0.0091 max mem: 33369 +Epoch: [9] [ 220/1319] eta: 1:00:18 lr: 3.955698927343052e-05 loss: 0.0584 (0.0877) time: 3.2822 data: 0.0096 max mem: 33369 +Epoch: [9] [ 230/1319] eta: 0:59:44 lr: 3.954823503715335e-05 loss: 0.0590 (0.0871) time: 3.2440 data: 0.0093 max mem: 33369 +Epoch: [9] [ 240/1319] eta: 0:59:09 lr: 3.953948058555954e-05 loss: 0.0683 (0.0870) time: 3.2559 data: 0.0091 max mem: 33369 +Epoch: [9] [ 250/1319] eta: 0:58:37 lr: 3.9530725918590825e-05 loss: 0.0775 (0.0868) time: 3.2779 data: 0.0092 max mem: 33369 +Epoch: [9] [ 260/1319] eta: 0:58:01 lr: 3.952197103618889e-05 loss: 0.0673 (0.0861) time: 3.2616 data: 0.0094 max mem: 33369 +Epoch: [9] [ 270/1319] eta: 0:57:26 lr: 3.951321593829542e-05 loss: 0.0733 (0.0860) time: 3.2222 data: 0.0099 max mem: 33369 +Epoch: [9] [ 280/1319] eta: 0:56:53 lr: 3.9504460624852056e-05 loss: 0.0815 (0.0858) time: 3.2564 data: 0.0099 max mem: 33369 +Epoch: [9] [ 290/1319] eta: 0:56:18 lr: 3.94957050958004e-05 loss: 0.0821 (0.0856) time: 3.2607 data: 0.0097 max mem: 33369 +Epoch: [9] [ 300/1319] eta: 0:55:43 lr: 3.9486949351082035e-05 loss: 0.0780 (0.0854) time: 3.2223 data: 0.0093 max mem: 33369 +Epoch: [9] [ 310/1319] eta: 0:55:09 lr: 3.9478193390638515e-05 loss: 0.0760 (0.0852) time: 3.2258 data: 0.0095 max mem: 33369 +Epoch: [9] [ 320/1319] eta: 0:54:38 lr: 3.946943721441136e-05 loss: 0.0771 (0.0850) time: 3.2928 data: 0.0103 max mem: 33369 +Epoch: [9] [ 330/1319] eta: 0:54:05 lr: 3.946068082234206e-05 loss: 0.0752 (0.0848) time: 3.3155 data: 0.0096 max mem: 33369 +Epoch: [9] [ 340/1319] eta: 0:53:32 lr: 3.945192421437206e-05 loss: 0.0755 (0.0847) time: 3.2713 data: 0.0091 max mem: 33369 +Epoch: [9] [ 350/1319] eta: 0:52:59 lr: 3.944316739044282e-05 loss: 0.0773 (0.0847) time: 3.2749 data: 0.0092 max mem: 33369 +Epoch: [9] [ 360/1319] eta: 0:52:28 lr: 3.94344103504957e-05 loss: 0.0763 (0.0844) time: 3.3049 data: 0.0097 max mem: 33369 +Epoch: [9] [ 370/1319] eta: 0:51:55 lr: 3.94256530944721e-05 loss: 0.0783 (0.0847) time: 3.3000 data: 0.0104 max mem: 33369 +Epoch: [9] [ 380/1319] eta: 0:51:20 lr: 3.9416895622313336e-05 loss: 0.0783 (0.0845) time: 3.2492 data: 0.0094 max mem: 33369 +Epoch: [9] [ 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(0.0866) time: 3.2397 data: 0.0099 max mem: 33369 +Epoch: [9] [ 790/1319] eta: 0:28:57 lr: 3.9057652443333534e-05 loss: 0.0812 (0.0869) time: 3.2410 data: 0.0094 max mem: 33369 +Epoch: [9] [ 800/1319] eta: 0:28:25 lr: 3.904888584012046e-05 loss: 0.0777 (0.0869) time: 3.3473 data: 0.0096 max mem: 33369 +Epoch: [9] [ 810/1319] eta: 0:27:52 lr: 3.904011901822068e-05 loss: 0.0735 (0.0868) time: 3.3553 data: 0.0094 max mem: 33369 +Epoch: [9] [ 820/1319] eta: 0:27:19 lr: 3.9031351977574175e-05 loss: 0.0751 (0.0866) time: 3.2425 data: 0.0089 max mem: 33369 +Epoch: [9] [ 830/1319] eta: 0:26:46 lr: 3.9022584718120886e-05 loss: 0.0805 (0.0868) time: 3.3034 data: 0.0103 max mem: 33369 +Epoch: [9] [ 840/1319] eta: 0:26:13 lr: 3.901381723980073e-05 loss: 0.0930 (0.0869) time: 3.3128 data: 0.0106 max mem: 33369 +Epoch: [9] [ 850/1319] eta: 0:25:40 lr: 3.900504954255358e-05 loss: 0.0874 (0.0869) time: 3.2452 data: 0.0104 max mem: 33369 +Epoch: [9] [ 860/1319] eta: 0:25:07 lr: 3.899628162631931e-05 loss: 0.0889 (0.0870) time: 3.2663 data: 0.0110 max mem: 33369 +Epoch: [9] [ 870/1319] eta: 0:24:34 lr: 3.898751349103772e-05 loss: 0.0889 (0.0874) time: 3.2691 data: 0.0101 max mem: 33369 +Epoch: [9] [ 880/1319] eta: 0:24:01 lr: 3.8978745136648617e-05 loss: 0.0749 (0.0873) time: 3.2238 data: 0.0092 max mem: 33369 +Epoch: [9] [ 890/1319] eta: 0:23:28 lr: 3.896997656309173e-05 loss: 0.0795 (0.0873) time: 3.1922 data: 0.0095 max mem: 33369 +Epoch: [9] [ 900/1319] eta: 0:22:55 lr: 3.896120777030681e-05 loss: 0.0799 (0.0872) time: 3.2040 data: 0.0095 max mem: 33369 +Epoch: [9] [ 910/1319] eta: 0:22:22 lr: 3.895243875823353e-05 loss: 0.0827 (0.0875) time: 3.2145 data: 0.0093 max mem: 33369 +Epoch: [9] [ 920/1319] eta: 0:21:48 lr: 3.894366952681158e-05 loss: 0.0893 (0.0876) time: 3.2043 data: 0.0097 max mem: 33369 +Epoch: [9] [ 930/1319] eta: 0:21:15 lr: 3.8934900075980555e-05 loss: 0.0912 (0.0877) time: 3.1960 data: 0.0104 max mem: 33369 +Epoch: [9] [ 940/1319] eta: 0:20:42 lr: 3.8926130405680076e-05 loss: 0.0897 (0.0876) time: 3.2118 data: 0.0102 max mem: 33369 +Epoch: [9] [ 950/1319] eta: 0:20:09 lr: 3.8917360515849704e-05 loss: 0.0691 (0.0874) time: 3.1896 data: 0.0090 max mem: 33369 +Epoch: [9] [ 960/1319] eta: 0:19:36 lr: 3.8908590406428975e-05 loss: 0.0653 (0.0873) time: 3.1644 data: 0.0087 max mem: 33369 +Epoch: [9] [ 970/1319] eta: 0:19:03 lr: 3.889982007735738e-05 loss: 0.0653 (0.0872) time: 3.1921 data: 0.0096 max mem: 33369 +Epoch: [9] [ 980/1319] eta: 0:18:30 lr: 3.889104952857442e-05 loss: 0.0739 (0.0872) time: 3.1804 data: 0.0100 max mem: 33369 +Epoch: [9] [ 990/1319] eta: 0:17:57 lr: 3.888227876001951e-05 loss: 0.0779 (0.0871) time: 3.1911 data: 0.0106 max mem: 33369 +Epoch: [9] [1000/1319] eta: 0:17:24 lr: 3.887350777163206e-05 loss: 0.0875 (0.0875) time: 3.2283 data: 0.0105 max mem: 33369 +Epoch: [9] [1010/1319] eta: 0:16:51 lr: 3.886473656335145e-05 loss: 0.0767 (0.0874) time: 3.2579 data: 0.0103 max mem: 33369 +Epoch: [9] [1020/1319] eta: 0:16:18 lr: 3.8855965135117015e-05 loss: 0.0703 (0.0874) time: 3.2477 data: 0.0111 max mem: 33369 +Epoch: [9] [1030/1319] eta: 0:15:45 lr: 3.8847193486868084e-05 loss: 0.0771 (0.0875) time: 3.1986 data: 0.0107 max mem: 33369 +Epoch: [9] [1040/1319] eta: 0:15:12 lr: 3.883842161854392e-05 loss: 0.0718 (0.0874) time: 3.1845 data: 0.0099 max mem: 33369 +Epoch: [9] [1050/1319] eta: 0:14:39 lr: 3.8829649530083775e-05 loss: 0.0927 (0.0875) time: 3.1864 data: 0.0099 max mem: 33369 +Epoch: [9] [1060/1319] eta: 0:14:06 lr: 3.882087722142687e-05 loss: 0.0962 (0.0875) time: 3.1905 data: 0.0106 max mem: 33369 +Epoch: [9] [1070/1319] eta: 0:13:34 lr: 3.8812104692512384e-05 loss: 0.0827 (0.0875) time: 3.1946 data: 0.0104 max mem: 33369 +Epoch: [9] [1080/1319] eta: 0:13:01 lr: 3.880333194327947e-05 loss: 0.0825 (0.0875) time: 3.1970 data: 0.0094 max mem: 33369 +Epoch: [9] [1090/1319] eta: 0:12:28 lr: 3.879455897366725e-05 loss: 0.0825 (0.0875) time: 3.2001 data: 0.0095 max mem: 33369 +Epoch: [9] 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+Epoch: [9] [1180/1319] eta: 0:07:33 lr: 3.871559232002716e-05 loss: 0.0711 (0.0873) time: 3.2629 data: 0.0096 max mem: 33369 +Epoch: [9] [1190/1319] eta: 0:07:01 lr: 3.870681714326634e-05 loss: 0.0716 (0.0873) time: 3.2410 data: 0.0097 max mem: 33369 +Epoch: [9] [1200/1319] eta: 0:06:28 lr: 3.86980417454544e-05 loss: 0.0716 (0.0872) time: 3.2252 data: 0.0096 max mem: 33369 +Epoch: [9] [1210/1319] eta: 0:05:55 lr: 3.8689266126530076e-05 loss: 0.0843 (0.0874) time: 3.2573 data: 0.0105 max mem: 33369 +Epoch: [9] [1220/1319] eta: 0:05:23 lr: 3.868049028643206e-05 loss: 0.0930 (0.0874) time: 3.2638 data: 0.0114 max mem: 33369 +Epoch: [9] [1230/1319] eta: 0:04:50 lr: 3.867171422509902e-05 loss: 0.0787 (0.0874) time: 3.2488 data: 0.0105 max mem: 33369 +Epoch: [9] [1240/1319] eta: 0:04:18 lr: 3.866293794246959e-05 loss: 0.0894 (0.0877) time: 3.2952 data: 0.0099 max mem: 33369 +Epoch: [9] [1250/1319] eta: 0:03:45 lr: 3.8654161438482394e-05 loss: 0.0930 (0.0877) time: 3.2887 data: 0.0107 max mem: 33369 +Epoch: [9] [1260/1319] eta: 0:03:12 lr: 3.864538471307598e-05 loss: 0.0744 (0.0876) time: 3.2877 data: 0.0114 max mem: 33369 +Epoch: [9] [1270/1319] eta: 0:02:40 lr: 3.863660776618888e-05 loss: 0.0745 (0.0877) time: 3.3386 data: 0.0110 max mem: 33369 +Epoch: [9] [1280/1319] eta: 0:02:07 lr: 3.8627830597759606e-05 loss: 0.0812 (0.0877) time: 3.3480 data: 0.0106 max mem: 33369 +Epoch: [9] [1290/1319] eta: 0:01:34 lr: 3.861905320772664e-05 loss: 0.0819 (0.0878) time: 3.3084 data: 0.0099 max mem: 33369 +Epoch: [9] [1300/1319] eta: 0:01:02 lr: 3.861027559602841e-05 loss: 0.0874 (0.0878) time: 3.3357 data: 0.0092 max mem: 33369 +Epoch: [9] [1310/1319] eta: 0:00:29 lr: 3.860149776260333e-05 loss: 0.0854 (0.0878) time: 3.4206 data: 0.0086 max mem: 33369 +Epoch: [9] Total time: 1:11:54 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 3:00:24 time: 4.2069 data: 3.9999 max mem: 33369 +Test: [ 100/2573] eta: 0:05:02 time: 0.0821 data: 0.0016 max mem: 33369 +Test: [ 200/2573] eta: 0:04:04 time: 0.0839 data: 0.0019 max mem: 33369 +Test: [ 300/2573] eta: 0:03:39 time: 0.0884 data: 0.0021 max mem: 33369 +Test: [ 400/2573] eta: 0:03:24 time: 0.0889 data: 0.0021 max mem: 33369 +Test: [ 500/2573] eta: 0:03:12 time: 0.0886 data: 0.0022 max mem: 33369 +Test: [ 600/2573] eta: 0:03:01 time: 0.0811 data: 0.0015 max mem: 33369 +Test: [ 700/2573] eta: 0:02:50 time: 0.0817 data: 0.0015 max mem: 33369 +Test: [ 800/2573] eta: 0:02:39 time: 0.0860 data: 0.0015 max mem: 33369 +Test: [ 900/2573] eta: 0:02:29 time: 0.0884 data: 0.0022 max mem: 33369 +Test: [1000/2573] eta: 0:02:19 time: 0.0831 data: 0.0018 max mem: 33369 +Test: [1100/2573] eta: 0:02:10 time: 0.0840 data: 0.0016 max mem: 33369 +Test: [1200/2573] eta: 0:02:00 time: 0.0812 data: 0.0015 max mem: 33369 +Test: [1300/2573] eta: 0:01:51 time: 0.0881 data: 0.0020 max mem: 33369 +Test: [1400/2573] eta: 0:01:43 time: 0.0874 data: 0.0021 max mem: 33369 +Test: [1500/2573] eta: 0:01:34 time: 0.0886 data: 0.0022 max mem: 33369 +Test: [1600/2573] eta: 0:01:25 time: 0.0907 data: 0.0023 max mem: 33369 +Test: [1700/2573] eta: 0:01:16 time: 0.0874 data: 0.0021 max mem: 33369 +Test: [1800/2573] eta: 0:01:08 time: 0.0886 data: 0.0021 max mem: 33369 +Test: [1900/2573] eta: 0:00:59 time: 0.0875 data: 0.0021 max mem: 33369 +Test: [2000/2573] eta: 0:00:50 time: 0.0834 data: 0.0016 max mem: 33369 +Test: [2100/2573] eta: 0:00:41 time: 0.0840 data: 0.0016 max mem: 33369 +Test: [2200/2573] eta: 0:00:32 time: 0.0827 data: 0.0017 max mem: 33369 +Test: [2300/2573] eta: 0:00:23 time: 0.0837 data: 0.0016 max mem: 33369 +Test: [2400/2573] eta: 0:00:15 time: 0.0796 data: 0.0016 max mem: 33369 +Test: [2500/2573] eta: 0:00:06 time: 0.0831 data: 0.0017 max mem: 33369 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: Total time: 0:03:44 +Final results: +Mean IoU is 58.82 + + precision@0.5 = 66.24 + precision@0.6 = 59.95 + precision@0.7 = 51.39 + precision@0.8 = 38.75 + precision@0.9 = 17.36 + overall IoU = 57.91 + +Average object IoU 58.823382123296874 +Overall IoU 57.91440200805664 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [10] [ 0/1319] eta: 2:49:25 lr: 3.859359752289337e-05 loss: 0.1051 (0.1051) time: 7.7072 data: 4.0072 max mem: 33369 +Epoch: [10] [ 10/1319] eta: 1:22:28 lr: 3.858481926801746e-05 loss: 0.0698 (0.0820) time: 3.7800 data: 0.3723 max mem: 33369 +Epoch: [10] [ 20/1319] eta: 1:16:54 lr: 3.857604079123589e-05 loss: 0.0678 (0.0822) time: 3.3444 data: 0.0094 max mem: 33369 +Epoch: [10] [ 30/1319] eta: 1:14:26 lr: 3.856726209248695e-05 loss: 0.0720 (0.0814) time: 3.2916 data: 0.0093 max mem: 33369 +Epoch: [10] [ 40/1319] eta: 1:13:11 lr: 3.855848317170887e-05 loss: 0.0720 (0.0814) time: 3.3095 data: 0.0090 max mem: 33369 +Epoch: [10] [ 50/1319] eta: 1:11:55 lr: 3.854970402883988e-05 loss: 0.0694 (0.0788) time: 3.3006 data: 0.0097 max mem: 33369 +Epoch: [10] [ 60/1319] eta: 1:11:18 lr: 3.854092466381814e-05 loss: 0.0744 (0.0787) time: 3.3267 data: 0.0103 max mem: 33369 +Epoch: [10] [ 70/1319] eta: 1:10:36 lr: 3.853214507658182e-05 loss: 0.0705 (0.0792) time: 3.3709 data: 0.0110 max mem: 33369 +Epoch: [10] [ 80/1319] eta: 1:09:43 lr: 3.852336526706903e-05 loss: 0.0743 (0.0802) time: 3.3081 data: 0.0113 max mem: 33369 +Epoch: [10] [ 90/1319] eta: 1:08:59 lr: 3.8514585235217835e-05 loss: 0.0907 (0.0825) time: 3.2844 data: 0.0113 max mem: 33369 +Epoch: [10] [ 100/1319] eta: 1:08:23 lr: 3.850580498096631e-05 loss: 0.0907 (0.0842) time: 3.3266 data: 0.0108 max mem: 33369 +Epoch: [10] [ 110/1319] eta: 1:07:48 lr: 3.849702450425245e-05 loss: 0.0738 (0.0825) time: 3.3498 data: 0.0103 max mem: 33369 +Epoch: [10] [ 120/1319] eta: 1:07:16 lr: 3.8488243805014244e-05 loss: 0.0588 (0.0807) time: 3.3653 data: 0.0101 max mem: 33369 +Epoch: [10] [ 130/1319] eta: 1:06:51 lr: 3.8479462883189646e-05 loss: 0.0606 (0.0803) time: 3.4214 data: 0.0093 max mem: 33369 +Epoch: [10] [ 140/1319] eta: 1:06:19 lr: 3.8470681738716575e-05 loss: 0.0724 (0.0798) time: 3.4273 data: 0.0088 max mem: 33369 +Epoch: [10] [ 150/1319] eta: 1:05:42 lr: 3.846190037153291e-05 loss: 0.0708 (0.0799) time: 3.3631 data: 0.0097 max mem: 33369 +Epoch: [10] [ 160/1319] eta: 1:05:14 lr: 3.84531187815765e-05 loss: 0.0708 (0.0795) time: 3.3936 data: 0.0104 max mem: 33369 +Epoch: [10] [ 170/1319] eta: 1:04:38 lr: 3.844433696878517e-05 loss: 0.0735 (0.0796) time: 3.4025 data: 0.0107 max mem: 33369 +Epoch: [10] [ 180/1319] eta: 1:03:59 lr: 3.843555493309671e-05 loss: 0.0731 (0.0797) time: 3.3198 data: 0.0116 max mem: 33369 +Epoch: [10] [ 190/1319] eta: 1:03:28 lr: 3.842677267444885e-05 loss: 0.0769 (0.0799) time: 3.3536 data: 0.0115 max mem: 33369 +Epoch: [10] [ 200/1319] eta: 1:02:51 lr: 3.8417990192779335e-05 loss: 0.0808 (0.0810) time: 3.3646 data: 0.0102 max mem: 33369 +Epoch: [10] [ 210/1319] eta: 1:02:13 lr: 3.8409207488025836e-05 loss: 0.0718 (0.0816) time: 3.2963 data: 0.0097 max mem: 33369 +Epoch: [10] [ 220/1319] eta: 1:01:40 lr: 3.8400424560126e-05 loss: 0.0721 (0.0821) time: 3.3370 data: 0.0107 max mem: 33369 +Epoch: [10] [ 230/1319] eta: 1:01:02 lr: 3.839164140901745e-05 loss: 0.0742 (0.0818) time: 3.3334 data: 0.0117 max mem: 33369 +Epoch: [10] [ 240/1319] eta: 1:00:26 lr: 3.838285803463778e-05 loss: 0.0742 (0.0817) time: 3.2891 data: 0.0118 max mem: 33369 +Epoch: [10] [ 250/1319] eta: 0:59:57 lr: 3.8374074436924536e-05 loss: 0.0744 (0.0815) time: 3.3860 data: 0.0111 max mem: 33369 +Epoch: [10] [ 260/1319] eta: 0:59:20 lr: 3.836529061581523e-05 loss: 0.0744 (0.0814) time: 3.3843 data: 0.0103 max mem: 33369 +Epoch: [10] [ 270/1319] eta: 0:58:46 lr: 3.8356506571247355e-05 loss: 0.0743 (0.0815) time: 3.3163 data: 0.0116 max mem: 33369 +Epoch: [10] [ 280/1319] eta: 0:58:11 lr: 3.834772230315837e-05 loss: 0.0708 (0.0813) time: 3.3374 data: 0.0123 max mem: 33369 +Epoch: [10] [ 290/1319] eta: 0:57:36 lr: 3.833893781148568e-05 loss: 0.0653 (0.0813) time: 3.3253 data: 0.0113 max mem: 33369 +Epoch: [10] [ 300/1319] eta: 0:57:00 lr: 3.833015309616668e-05 loss: 0.0708 (0.0818) time: 3.3034 data: 0.0101 max mem: 33369 +Epoch: [10] [ 310/1319] eta: 0:56:27 lr: 3.832136815713871e-05 loss: 0.0718 (0.0816) time: 3.3328 data: 0.0103 max mem: 33369 +Epoch: [10] [ 320/1319] eta: 0:55:51 lr: 3.83125829943391e-05 loss: 0.0684 (0.0815) time: 3.3278 data: 0.0114 max mem: 33369 +Epoch: [10] [ 330/1319] eta: 0:55:18 lr: 3.830379760770512e-05 loss: 0.0675 (0.0809) time: 3.3247 data: 0.0115 max mem: 33369 +Epoch: [10] [ 340/1319] eta: 0:54:45 lr: 3.829501199717404e-05 loss: 0.0620 (0.0804) time: 3.3664 data: 0.0119 max mem: 33369 +Epoch: [10] [ 350/1319] eta: 0:54:10 lr: 3.828622616268306e-05 loss: 0.0659 (0.0802) time: 3.3481 data: 0.0125 max mem: 33369 +Epoch: [10] [ 360/1319] eta: 0:53:35 lr: 3.8277440104169376e-05 loss: 0.0722 (0.0801) time: 3.3037 data: 0.0112 max mem: 33369 +Epoch: [10] [ 370/1319] eta: 0:52:59 lr: 3.826865382157014e-05 loss: 0.0743 (0.0806) time: 3.2757 data: 0.0098 max mem: 33369 +Epoch: [10] [ 380/1319] eta: 0:52:26 lr: 3.8259867314822454e-05 loss: 0.0720 (0.0805) time: 3.3185 data: 0.0099 max 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33369 +Epoch: [10] [1250/1319] eta: 0:03:45 lr: 3.749457595893693e-05 loss: 0.0707 (0.0818) time: 3.2557 data: 0.0098 max mem: 33369 +Epoch: [10] [1260/1319] eta: 0:03:12 lr: 3.748576947684619e-05 loss: 0.0681 (0.0820) time: 3.2564 data: 0.0111 max mem: 33369 +Epoch: [10] [1270/1319] eta: 0:02:40 lr: 3.74769627648722e-05 loss: 0.0746 (0.0820) time: 3.2634 data: 0.0117 max mem: 33369 +Epoch: [10] [1280/1319] eta: 0:02:07 lr: 3.746815582294894e-05 loss: 0.0705 (0.0819) time: 3.2543 data: 0.0119 max mem: 33369 +Epoch: [10] [1290/1319] eta: 0:01:34 lr: 3.745934865101035e-05 loss: 0.0670 (0.0819) time: 3.3123 data: 0.0109 max mem: 33369 +Epoch: [10] [1300/1319] eta: 0:01:02 lr: 3.7450541248990324e-05 loss: 0.0709 (0.0820) time: 3.3746 data: 0.0102 max mem: 33369 +Epoch: [10] [1310/1319] eta: 0:00:29 lr: 3.7441733616822736e-05 loss: 0.0643 (0.0821) time: 3.3229 data: 0.0097 max mem: 33369 +Epoch: [10] Total time: 1:11:51 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 2:47:10 time: 3.8983 data: 3.8012 max mem: 33369 +Test: [ 100/2573] eta: 0:04:57 time: 0.0808 data: 0.0017 max mem: 33369 +Test: [ 200/2573] eta: 0:04:00 time: 0.0812 data: 0.0015 max mem: 33369 +Test: [ 300/2573] eta: 0:03:33 time: 0.0815 data: 0.0015 max mem: 33369 +Test: [ 400/2573] eta: 0:03:18 time: 0.0820 data: 0.0015 max mem: 33369 +Test: [ 500/2573] eta: 0:03:06 time: 0.0828 data: 0.0015 max mem: 33369 +Test: [ 600/2573] eta: 0:02:55 time: 0.0852 data: 0.0019 max mem: 33369 +Test: [ 700/2573] eta: 0:02:45 time: 0.0857 data: 0.0021 max mem: 33369 +Test: [ 800/2573] eta: 0:02:36 time: 0.0877 data: 0.0019 max mem: 33369 +Test: [ 900/2573] eta: 0:02:27 time: 0.0818 data: 0.0016 max mem: 33369 +Test: [1000/2573] eta: 0:02:17 time: 0.0885 data: 0.0023 max mem: 33369 +Test: [1100/2573] eta: 0:02:09 time: 0.0860 data: 0.0020 max mem: 33369 +Test: [1200/2573] eta: 0:02:00 time: 0.0825 data: 0.0016 max mem: 33369 +Test: [1300/2573] eta: 0:01:50 time: 0.0849 data: 0.0017 max mem: 33369 +Test: [1400/2573] eta: 0:01:41 time: 0.0805 data: 0.0016 max mem: 33369 +Test: [1500/2573] eta: 0:01:33 time: 0.0889 data: 0.0023 max mem: 33369 +Test: [1600/2573] eta: 0:01:24 time: 0.0859 data: 0.0015 max mem: 33369 +Test: [1700/2573] eta: 0:01:15 time: 0.0823 data: 0.0018 max mem: 33369 +Test: [1800/2573] eta: 0:01:06 time: 0.0887 data: 0.0023 max mem: 33369 +Test: [1900/2573] eta: 0:00:58 time: 0.0798 data: 0.0017 max mem: 33369 +Test: [2000/2573] eta: 0:00:49 time: 0.0853 data: 0.0018 max mem: 33369 +Test: [2100/2573] eta: 0:00:40 time: 0.0834 data: 0.0018 max mem: 33369 +Test: [2200/2573] eta: 0:00:32 time: 0.0870 data: 0.0019 max mem: 33369 +Test: [2300/2573] eta: 0:00:23 time: 0.0848 data: 0.0019 max mem: 33369 +Test: [2400/2573] eta: 0:00:14 time: 0.0866 data: 0.0023 max mem: 33369 +Test: [2500/2573] eta: 0:00:06 time: 0.0838 data: 0.0017 max mem: 33369 +Test: Total time: 0:03:41 +Final results: +Mean IoU is 61.30 + + precision@0.5 = 69.28 + precision@0.6 = 62.40 + precision@0.7 = 53.19 + precision@0.8 = 40.62 + precision@0.9 = 18.89 + overall IoU = 59.43 + +Average object IoU 61.298733178090316 +Overall IoU 59.42734909057617 +Better epoch: 10 + +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [11] [ 0/1319] eta: 2:10:52 lr: 3.743380655104104e-05 loss: 0.0373 (0.0373) time: 5.9533 data: 2.3798 max mem: 33369 +Epoch: [11] [ 10/1319] eta: 1:18:11 lr: 3.742499848141075e-05 loss: 0.0639 (0.0725) time: 3.5838 data: 0.2254 max mem: 33369 +Epoch: [11] [ 20/1319] eta: 1:14:51 lr: 3.741619018144089e-05 loss: 0.0597 (0.0658) time: 3.3327 data: 0.0094 max mem: 33369 +Epoch: [11] [ 30/1319] eta: 1:14:22 lr: 3.7407381651065185e-05 loss: 0.0620 (0.0684) time: 3.3946 data: 0.0095 max mem: 33369 +Epoch: [11] [ 40/1319] eta: 1:13:26 lr: 3.739857289021734e-05 loss: 0.0712 (0.0755) time: 3.4330 data: 0.0103 max mem: 33369 +Epoch: [11] [ 50/1319] eta: 1:12:21 lr: 3.738976389883098e-05 loss: 0.0712 (0.0814) time: 3.3581 data: 0.0104 max mem: 33369 +Epoch: [11] [ 60/1319] eta: 1:11:38 lr: 3.738095467683973e-05 loss: 0.0693 (0.0782) time: 3.3507 data: 0.0103 max mem: 33369 +Epoch: [11] [ 70/1319] eta: 1:10:47 lr: 3.737214522417717e-05 loss: 0.0673 (0.0785) time: 3.3489 data: 0.0107 max mem: 33369 +Epoch: [11] [ 80/1319] eta: 1:09:54 lr: 3.736333554077684e-05 loss: 0.0673 (0.0770) time: 3.2963 data: 0.0112 max mem: 33369 +Epoch: [11] [ 90/1319] eta: 1:09:24 lr: 3.735452562657224e-05 loss: 0.0755 (0.0796) time: 3.3469 data: 0.0112 max mem: 33369 +Epoch: [11] [ 100/1319] eta: 1:08:44 lr: 3.734571548149683e-05 loss: 0.0772 (0.0792) time: 3.3754 data: 0.0108 max mem: 33369 +Epoch: [11] [ 110/1319] eta: 1:08:04 lr: 3.733690510548406e-05 loss: 0.0674 (0.0788) time: 3.3304 data: 0.0103 max mem: 33369 +Epoch: [11] [ 120/1319] eta: 1:07:27 lr: 3.732809449846732e-05 loss: 0.0693 (0.0802) time: 3.3370 data: 0.0105 max mem: 33369 +Epoch: [11] [ 130/1319] eta: 1:06:49 lr: 3.7319283660379954e-05 loss: 0.0656 (0.0784) time: 3.3393 data: 0.0109 max mem: 33369 +Epoch: [11] [ 140/1319] eta: 1:06:09 lr: 3.7310472591155297e-05 loss: 0.0628 (0.0778) time: 3.3135 data: 0.0108 max mem: 33369 +Epoch: [11] [ 150/1319] eta: 1:05:29 lr: 3.7301661290726626e-05 loss: 0.0654 (0.0774) time: 3.2918 data: 0.0113 max mem: 33369 +Epoch: [11] [ 160/1319] eta: 1:04:58 lr: 3.729284975902719e-05 loss: 0.0746 (0.0779) time: 3.3381 data: 0.0111 max mem: 33369 +Epoch: [11] [ 170/1319] eta: 1:04:26 lr: 3.728403799599019e-05 loss: 0.0777 (0.0790) time: 3.3939 data: 0.0102 max mem: 33369 +Epoch: [11] [ 180/1319] eta: 1:03:50 lr: 3.727522600154881e-05 loss: 0.0757 (0.0789) time: 3.3573 data: 0.0102 max mem: 33369 +Epoch: [11] [ 190/1319] eta: 1:03:16 lr: 3.7266413775636196e-05 loss: 0.0757 (0.0794) time: 3.3396 data: 0.0120 max mem: 33369 +Epoch: [11] [ 200/1319] eta: 1:02:40 lr: 3.725760131818543e-05 loss: 0.0658 (0.0784) time: 3.3460 data: 0.0119 max mem: 33369 +Epoch: [11] [ 210/1319] eta: 1:02:04 lr: 3.724878862912958e-05 loss: 0.0587 (0.0775) time: 3.3165 data: 0.0103 max mem: 33369 +Epoch: [11] [ 220/1319] eta: 1:01:26 lr: 3.723997570840168e-05 loss: 0.0670 (0.0778) time: 3.2849 data: 0.0103 max mem: 33369 +Epoch: [11] [ 230/1319] eta: 1:00:51 lr: 3.723116255593471e-05 loss: 0.0670 (0.0773) time: 3.2967 data: 0.0114 max mem: 33369 +Epoch: [11] [ 240/1319] eta: 1:00:19 lr: 3.7222349171661633e-05 loss: 0.0648 (0.0771) time: 3.3592 data: 0.0119 max mem: 33369 +Epoch: [11] [ 250/1319] eta: 0:59:42 lr: 3.721353555551535e-05 loss: 0.0686 (0.0768) time: 3.3286 data: 0.0109 max mem: 33369 +Epoch: [11] [ 260/1319] eta: 0:59:06 lr: 3.720472170742875e-05 loss: 0.0806 (0.0773) time: 3.2758 data: 0.0099 max mem: 33369 +Epoch: [11] [ 270/1319] eta: 0:58:31 lr: 3.719590762733466e-05 loss: 0.0839 (0.0778) time: 3.3063 data: 0.0098 max mem: 33369 +Epoch: [11] [ 280/1319] eta: 0:57:59 lr: 3.718709331516589e-05 loss: 0.0745 (0.0778) time: 3.3556 data: 0.0102 max mem: 33369 +Epoch: [11] [ 290/1319] eta: 0:57:24 lr: 3.7178278770855225e-05 loss: 0.0773 (0.0778) time: 3.3387 data: 0.0109 max mem: 33369 +Epoch: [11] [ 300/1319] eta: 0:56:50 lr: 3.716946399433537e-05 loss: 0.0640 (0.0773) time: 3.3166 data: 0.0106 max mem: 33369 +Epoch: [11] [ 310/1319] eta: 0:56:14 lr: 3.716064898553902e-05 loss: 0.0616 (0.0769) time: 3.3014 data: 0.0102 max mem: 33369 +Epoch: [11] [ 320/1319] eta: 0:55:39 lr: 3.715183374439884e-05 loss: 0.0597 (0.0771) time: 3.2837 data: 0.0094 max mem: 33369 +Epoch: [11] [ 330/1319] eta: 0:55:06 lr: 3.7143018270847454e-05 loss: 0.0662 (0.0770) time: 3.3310 data: 0.0089 max mem: 33369 +Epoch: [11] [ 340/1319] eta: 0:54:31 lr: 3.713420256481742e-05 loss: 0.0608 (0.0767) time: 3.3215 data: 0.0094 max mem: 33369 +Epoch: [11] [ 350/1319] eta: 0:53:56 lr: 3.712538662624129e-05 loss: 0.0608 (0.0766) time: 3.2901 data: 0.0093 max mem: 33369 +Epoch: [11] [ 360/1319] eta: 0:53:24 lr: 3.7116570455051586e-05 loss: 0.0599 (0.0765) time: 3.3385 data: 0.0103 max mem: 33369 +Epoch: [11] [ 370/1319] eta: 0:52:48 lr: 3.710775405118075e-05 loss: 0.0658 (0.0765) time: 3.3193 data: 0.0107 max mem: 33369 +Epoch: [11] [ 380/1319] eta: 0:52:14 lr: 3.709893741456123e-05 loss: 0.0680 (0.0765) time: 3.2787 data: 0.0100 max 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+/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 2:52:12 time: 4.0157 data: 3.8382 max mem: 33369 +Test: [ 100/2573] eta: 0:04:49 time: 0.0779 data: 0.0016 max mem: 33369 +Test: [ 200/2573] eta: 0:03:55 time: 0.0800 data: 0.0016 max mem: 33369 +Test: [ 300/2573] eta: 0:03:30 time: 0.0819 data: 0.0016 max mem: 33369 +Test: [ 400/2573] eta: 0:03:13 time: 0.0815 data: 0.0015 max mem: 33369 +Test: [ 500/2573] eta: 0:03:01 time: 0.0814 data: 0.0015 max mem: 33369 +Test: [ 600/2573] eta: 0:02:50 time: 0.0809 data: 0.0017 max mem: 33369 +Test: [ 700/2573] eta: 0:02:40 time: 0.0809 data: 0.0017 max mem: 33369 +Test: [ 800/2573] eta: 0:02:31 time: 0.0846 data: 0.0017 max mem: 33369 +Test: [ 900/2573] eta: 0:02:22 time: 0.0800 data: 0.0014 max mem: 33369 +Test: [1000/2573] eta: 0:02:13 time: 0.0812 data: 0.0014 max mem: 33369 +Test: [1100/2573] eta: 0:02:04 time: 0.0802 data: 0.0013 max mem: 33369 +Test: [1200/2573] eta: 0:01:55 time: 0.0793 data: 0.0016 max mem: 33369 +Test: [1300/2573] eta: 0:01:46 time: 0.0811 data: 0.0014 max mem: 33369 +Test: [1400/2573] eta: 0:01:37 time: 0.0793 data: 0.0014 max mem: 33369 +Test: [1500/2573] eta: 0:01:29 time: 0.0818 data: 0.0016 max mem: 33369 +Test: [1600/2573] eta: 0:01:20 time: 0.0836 data: 0.0015 max mem: 33369 +Test: [1700/2573] eta: 0:01:12 time: 0.0796 data: 0.0014 max mem: 33369 +Test: [1800/2573] eta: 0:01:04 time: 0.0826 data: 0.0016 max mem: 33369 +Test: [1900/2573] eta: 0:00:55 time: 0.0803 data: 0.0016 max mem: 33369 +Test: [2000/2573] eta: 0:00:47 time: 0.0798 data: 0.0015 max mem: 33369 +Test: [2100/2573] eta: 0:00:39 time: 0.0835 data: 0.0015 max mem: 33369 +Test: [2200/2573] eta: 0:00:30 time: 0.0818 data: 0.0014 max mem: 33369 +Test: [2300/2573] eta: 0:00:22 time: 0.0821 data: 0.0015 max mem: 33369 +Test: [2400/2573] eta: 0:00:14 time: 0.0788 data: 0.0015 max mem: 33369 +Test: [2500/2573] eta: 0:00:06 time: 0.0813 data: 0.0015 max mem: 33369 +Test: Total time: 0:03:31 +Final results: +Mean IoU is 61.47 + + precision@0.5 = 68.89 + precision@0.6 = 61.54 + precision@0.7 = 53.23 + precision@0.8 = 41.07 + precision@0.9 = 18.81 + overall IoU = 59.75 + +Average object IoU 61.47106662235925 +Overall IoU 59.753456115722656 +Better epoch: 11 + +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [12] [ 0/1319] eta: 1:55:43 lr: 3.6270008456269996e-05 loss: 0.1198 (0.1198) time: 5.2640 data: 1.8716 max mem: 33369 +Epoch: [12] [ 10/1319] eta: 1:14:34 lr: 3.6261169418713356e-05 loss: 0.0642 (0.0660) time: 3.4179 data: 0.1786 max mem: 33369 +Epoch: [12] [ 20/1319] eta: 1:11:40 lr: 3.62523301417494e-05 loss: 0.0588 (0.0707) time: 3.2131 data: 0.0085 max mem: 33369 +Epoch: [12] [ 30/1319] eta: 1:10:11 lr: 3.624349062530679e-05 loss: 0.0706 (0.0733) time: 3.1843 data: 0.0081 max mem: 33369 +Epoch: [12] [ 40/1319] eta: 1:09:14 lr: 3.623465086931413e-05 loss: 0.0651 (0.0696) time: 3.1823 data: 0.0084 max mem: 33369 +Epoch: [12] [ 50/1319] eta: 1:08:15 lr: 3.62258108737e-05 loss: 0.0617 (0.0691) time: 3.1665 data: 0.0083 max mem: 33369 +Epoch: [12] [ 60/1319] eta: 1:07:40 lr: 3.621697063839292e-05 loss: 0.0644 (0.0704) time: 3.1788 data: 0.0085 max mem: 33369 +Epoch: [12] [ 70/1319] eta: 1:07:00 lr: 3.6208130163321375e-05 loss: 0.0604 (0.0691) time: 3.1953 data: 0.0089 max mem: 33369 +Epoch: [12] [ 80/1319] eta: 1:06:21 lr: 3.619928944841383e-05 loss: 0.0592 (0.0688) time: 3.1760 data: 0.0104 max mem: 33369 +Epoch: [12] [ 90/1319] eta: 1:05:41 lr: 3.6190448493598675e-05 loss: 0.0637 (0.0689) time: 3.1676 data: 0.0103 max mem: 33369 +Epoch: [12] [ 100/1319] eta: 1:05:09 lr: 3.61816072988043e-05 loss: 0.0640 (0.0692) time: 3.1841 data: 0.0090 max mem: 33369 +Epoch: [12] [ 110/1319] eta: 1:04:34 lr: 3.617276586395901e-05 loss: 0.0587 (0.0692) time: 3.1935 data: 0.0095 max mem: 33369 +Epoch: [12] [ 120/1319] eta: 1:03:57 lr: 3.61639241889911e-05 loss: 0.0537 (0.0690) time: 3.1665 data: 0.0095 max mem: 33369 +Epoch: [12] [ 130/1319] eta: 1:03:22 lr: 3.615508227382881e-05 loss: 0.0537 (0.0691) time: 3.1600 data: 0.0093 max mem: 33369 +Epoch: [12] [ 140/1319] eta: 1:02:48 lr: 3.614624011840035e-05 loss: 0.0665 (0.0688) time: 3.1725 data: 0.0097 max mem: 33369 +Epoch: [12] [ 150/1319] eta: 1:02:14 lr: 3.613739772263389e-05 loss: 0.0613 (0.0683) time: 3.1701 data: 0.0091 max mem: 33369 +Epoch: [12] [ 160/1319] eta: 1:01:43 lr: 3.6128555086457536e-05 loss: 0.0586 (0.0679) time: 3.1863 data: 0.0088 max mem: 33369 +Epoch: [12] [ 170/1319] eta: 1:01:10 lr: 3.6119712209799373e-05 loss: 0.0597 (0.0680) time: 3.1963 data: 0.0098 max mem: 33369 +Epoch: [12] [ 180/1319] eta: 1:00:38 lr: 3.6110869092587446e-05 loss: 0.0615 (0.0695) time: 3.1843 data: 0.0102 max mem: 33369 +Epoch: [12] [ 190/1319] eta: 1:00:06 lr: 3.610202573474975e-05 loss: 0.0615 (0.0691) time: 3.1956 data: 0.0104 max mem: 33369 +Epoch: [12] [ 200/1319] eta: 0:59:33 lr: 3.609318213621424e-05 loss: 0.0588 (0.0688) time: 3.1873 data: 0.0106 max mem: 33369 +Epoch: [12] [ 210/1319] eta: 0:59:01 lr: 3.608433829690883e-05 loss: 0.0633 (0.0688) time: 3.1790 data: 0.0097 max mem: 33369 +Epoch: [12] [ 220/1319] eta: 0:58:28 lr: 3.607549421676141e-05 loss: 0.0665 (0.0696) time: 3.1864 data: 0.0092 max mem: 33369 +Epoch: [12] [ 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eta: 0:12:08 lr: 3.5305129002887835e-05 loss: 0.0626 (0.0722) time: 3.1592 data: 0.0108 max mem: 33369 +Epoch: [12] [1100/1319] eta: 0:11:37 lr: 3.529626344126292e-05 loss: 0.0610 (0.0721) time: 3.1694 data: 0.0102 max mem: 33369 +Epoch: [12] [1110/1319] eta: 0:11:05 lr: 3.5287397632207417e-05 loss: 0.0610 (0.0721) time: 3.1722 data: 0.0098 max mem: 33369 +Epoch: [12] [1120/1319] eta: 0:10:33 lr: 3.527853157564535e-05 loss: 0.0606 (0.0721) time: 3.1643 data: 0.0098 max mem: 33369 +Epoch: [12] [1130/1319] eta: 0:10:01 lr: 3.526966527150067e-05 loss: 0.0712 (0.0721) time: 3.1794 data: 0.0100 max mem: 33369 +Epoch: [12] [1140/1319] eta: 0:09:29 lr: 3.5260798719697326e-05 loss: 0.0832 (0.0724) time: 3.1695 data: 0.0101 max mem: 33369 +Epoch: [12] [1150/1319] eta: 0:08:57 lr: 3.52519319201592e-05 loss: 0.0823 (0.0724) time: 3.1829 data: 0.0101 max mem: 33369 +Epoch: [12] [1160/1319] eta: 0:08:26 lr: 3.524306487281011e-05 loss: 0.0650 (0.0724) time: 3.1788 data: 0.0101 max mem: 33369 +Epoch: [12] [1170/1319] eta: 0:07:54 lr: 3.523419757757387e-05 loss: 0.0564 (0.0723) time: 3.1514 data: 0.0099 max mem: 33369 +Epoch: [12] [1180/1319] eta: 0:07:22 lr: 3.5225330034374235e-05 loss: 0.0659 (0.0723) time: 3.1733 data: 0.0099 max mem: 33369 +Epoch: [12] [1190/1319] eta: 0:06:50 lr: 3.5216462243134885e-05 loss: 0.0692 (0.0723) time: 3.1682 data: 0.0094 max mem: 33369 +Epoch: [12] [1200/1319] eta: 0:06:18 lr: 3.52075942037795e-05 loss: 0.0568 (0.0722) time: 3.1714 data: 0.0098 max mem: 33369 +Epoch: [12] [1210/1319] eta: 0:05:46 lr: 3.519872591623169e-05 loss: 0.0519 (0.0721) time: 3.1933 data: 0.0103 max mem: 33369 +Epoch: [12] [1220/1319] eta: 0:05:15 lr: 3.518985738041502e-05 loss: 0.0683 (0.0722) time: 3.1882 data: 0.0102 max mem: 33369 +Epoch: [12] [1230/1319] eta: 0:04:43 lr: 3.518098859625303e-05 loss: 0.0699 (0.0721) time: 3.1988 data: 0.0102 max mem: 33369 +Epoch: [12] [1240/1319] eta: 0:04:11 lr: 3.517211956366918e-05 loss: 0.0592 (0.0721) time: 3.2088 data: 0.0099 max mem: 33369 +Epoch: [12] [1250/1319] eta: 0:03:39 lr: 3.5163250282586914e-05 loss: 0.0634 (0.0722) time: 3.1977 data: 0.0098 max mem: 33369 +Epoch: [12] [1260/1319] eta: 0:03:07 lr: 3.515438075292963e-05 loss: 0.0758 (0.0723) time: 3.1996 data: 0.0106 max mem: 33369 +Epoch: [12] [1270/1319] eta: 0:02:35 lr: 3.514551097462066e-05 loss: 0.0656 (0.0722) time: 3.1969 data: 0.0108 max mem: 33369 +Epoch: [12] [1280/1319] eta: 0:02:04 lr: 3.513664094758331e-05 loss: 0.0759 (0.0724) time: 3.1754 data: 0.0103 max mem: 33369 +Epoch: [12] [1290/1319] eta: 0:01:32 lr: 3.512777067174083e-05 loss: 0.0776 (0.0724) time: 3.1624 data: 0.0099 max mem: 33369 +Epoch: [12] [1300/1319] eta: 0:01:00 lr: 3.511890014701643e-05 loss: 0.0608 (0.0724) time: 3.1582 data: 0.0096 max mem: 33369 +Epoch: [12] [1310/1319] eta: 0:00:28 lr: 3.511002937333328e-05 loss: 0.0762 (0.0725) time: 3.1535 data: 0.0084 max mem: 33369 +Epoch: [12] Total time: 1:09:58 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 2:52:46 time: 4.0291 data: 3.7033 max mem: 33369 +Test: [ 100/2573] eta: 0:04:49 time: 0.0775 data: 0.0015 max mem: 33369 +Test: [ 200/2573] eta: 0:03:54 time: 0.0792 data: 0.0016 max mem: 33369 +Test: [ 300/2573] eta: 0:03:29 time: 0.0814 data: 0.0015 max mem: 33369 +Test: [ 400/2573] eta: 0:03:13 time: 0.0812 data: 0.0013 max mem: 33369 +Test: [ 500/2573] eta: 0:03:00 time: 0.0790 data: 0.0015 max mem: 33369 +Test: [ 600/2573] eta: 0:02:50 time: 0.0796 data: 0.0014 max mem: 33369 +Test: [ 700/2573] eta: 0:02:40 time: 0.0794 data: 0.0015 max mem: 33369 +Test: [ 800/2573] eta: 0:02:30 time: 0.0833 data: 0.0015 max mem: 33369 +Test: [ 900/2573] eta: 0:02:21 time: 0.0807 data: 0.0014 max mem: 33369 +Test: [1000/2573] eta: 0:02:12 time: 0.0806 data: 0.0016 max mem: 33369 +Test: [1100/2573] eta: 0:02:03 time: 0.0799 data: 0.0015 max mem: 33369 +Test: [1200/2573] eta: 0:01:55 time: 0.0827 data: 0.0015 max mem: 33369 +Test: [1300/2573] eta: 0:01:46 time: 0.0800 data: 0.0014 max mem: 33369 +Test: [1400/2573] eta: 0:01:37 time: 0.0801 data: 0.0016 max mem: 33369 +Test: [1500/2573] eta: 0:01:29 time: 0.0811 data: 0.0016 max mem: 33369 +Test: [1600/2573] eta: 0:01:20 time: 0.0850 data: 0.0019 max mem: 33369 +Test: [1700/2573] eta: 0:01:12 time: 0.0789 data: 0.0014 max mem: 33369 +Test: [1800/2573] eta: 0:01:04 time: 0.0829 data: 0.0015 max mem: 33369 +Test: [1900/2573] eta: 0:00:55 time: 0.0791 data: 0.0015 max mem: 33369 +Test: [2000/2573] eta: 0:00:47 time: 0.0799 data: 0.0016 max mem: 33369 +Test: [2100/2573] eta: 0:00:39 time: 0.0815 data: 0.0015 max mem: 33369 +Test: [2200/2573] eta: 0:00:30 time: 0.0823 data: 0.0014 max mem: 33369 +Test: [2300/2573] eta: 0:00:22 time: 0.0825 data: 0.0014 max mem: 33369 +Test: [2400/2573] eta: 0:00:14 time: 0.0775 data: 0.0015 max mem: 33369 +Test: [2500/2573] eta: 0:00:06 time: 0.0806 data: 0.0015 max mem: 33369 +Test: Total time: 0:03:32 +Final results: +Mean IoU is 61.25 + + precision@0.5 = 68.75 + precision@0.6 = 61.68 + precision@0.7 = 53.51 + precision@0.8 = 40.87 + precision@0.9 = 18.63 + overall IoU = 59.90 + +Average object IoU 61.250101635384524 +Overall IoU 59.90025329589844 +Better epoch: 12 + +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [13] [ 0/1319] eta: 2:04:38 lr: 3.510204546409517e-05 loss: 0.0504 (0.0504) time: 5.6699 data: 2.2501 max mem: 33369 +Epoch: [13] [ 10/1319] eta: 1:14:58 lr: 3.509317421717855e-05 loss: 0.0672 (0.0674) time: 3.4364 data: 0.2130 max mem: 33369 +Epoch: [13] [ 20/1319] eta: 1:12:03 lr: 3.50843027210801e-05 loss: 0.0693 (0.0711) time: 3.2115 data: 0.0097 max mem: 33369 +Epoch: [13] [ 30/1319] eta: 1:10:34 lr: 3.5075430975722793e-05 loss: 0.0707 (0.0719) time: 3.2018 data: 0.0102 max mem: 33369 +Epoch: [13] [ 40/1319] eta: 1:09:23 lr: 3.506655898102959e-05 loss: 0.0621 (0.0711) time: 3.1790 data: 0.0105 max mem: 33369 +Epoch: [13] [ 50/1319] eta: 1:08:30 lr: 3.505768673692337e-05 loss: 0.0476 (0.0674) time: 3.1688 data: 0.0098 max mem: 33369 +Epoch: [13] [ 60/1319] eta: 1:07:46 lr: 3.5048814243327e-05 loss: 0.0469 (0.0681) time: 3.1776 data: 0.0091 max mem: 33369 +Epoch: [13] [ 70/1319] eta: 1:07:01 lr: 3.503994150016327e-05 loss: 0.0589 (0.0682) time: 3.1693 data: 0.0096 max mem: 33369 +Epoch: [13] [ 80/1319] eta: 1:06:28 lr: 3.503106850735495e-05 loss: 0.0511 (0.0660) time: 3.1863 data: 0.0098 max mem: 33369 +Epoch: [13] [ 90/1319] eta: 1:05:56 lr: 3.502219526482476e-05 loss: 0.0511 (0.0652) time: 3.2163 data: 0.0099 max mem: 33369 +Epoch: [13] [ 100/1319] eta: 1:05:20 lr: 3.501332177249536e-05 loss: 0.0510 (0.0642) time: 3.2042 data: 0.0106 max mem: 33369 +Epoch: [13] [ 110/1319] eta: 1:04:37 lr: 3.500444803028936e-05 loss: 0.0501 (0.0636) time: 3.1553 data: 0.0106 max mem: 33369 +Epoch: [13] [ 120/1319] eta: 1:04:04 lr: 3.499557403812936e-05 loss: 0.0513 (0.0628) time: 3.1555 data: 0.0100 max mem: 33369 +Epoch: [13] [ 130/1319] eta: 1:03:31 lr: 3.498669979593787e-05 loss: 0.0527 (0.0633) time: 3.1969 data: 0.0099 max mem: 33369 +Epoch: [13] [ 140/1319] eta: 1:02:57 lr: 3.497782530363739e-05 loss: 0.0533 (0.0634) time: 3.1900 data: 0.0100 max mem: 33369 +Epoch: [13] [ 150/1319] eta: 1:02:23 lr: 3.4968950561150356e-05 loss: 0.0522 (0.0642) time: 3.1768 data: 0.0095 max mem: 33369 +Epoch: [13] [ 160/1319] eta: 1:01:48 lr: 3.496007556839915e-05 loss: 0.0742 (0.0653) time: 3.1726 data: 0.0099 max mem: 33369 +Epoch: [13] [ 170/1319] eta: 1:01:14 lr: 3.495120032530614e-05 loss: 0.0597 (0.0645) time: 3.1648 data: 0.0101 max mem: 33369 +Epoch: [13] [ 180/1319] eta: 1:00:40 lr: 3.49423248317936e-05 loss: 0.0518 (0.0647) time: 3.1647 data: 0.0092 max mem: 33369 +Epoch: [13] [ 190/1319] eta: 1:00:06 lr: 3.493344908778381e-05 loss: 0.0592 (0.0649) time: 3.1687 data: 0.0095 max mem: 33369 +Epoch: [13] [ 200/1319] eta: 0:59:32 lr: 3.4924573093198975e-05 loss: 0.0583 (0.0645) time: 3.1615 data: 0.0095 max mem: 33369 +Epoch: [13] [ 210/1319] eta: 0:59:00 lr: 3.491569684796125e-05 loss: 0.0514 (0.0640) time: 3.1684 data: 0.0092 max mem: 33369 +Epoch: [13] [ 220/1319] eta: 0:58:29 lr: 3.490682035199276e-05 loss: 0.0519 (0.0645) time: 3.1971 data: 0.0095 max mem: 33369 +Epoch: [13] [ 230/1319] eta: 0:57:56 lr: 3.4897943605215565e-05 loss: 0.0560 (0.0648) time: 3.1953 data: 0.0097 max mem: 33369 +Epoch: [13] [ 240/1319] eta: 0:57:23 lr: 3.488906660755169e-05 loss: 0.0520 (0.0643) time: 3.1774 data: 0.0100 max mem: 33369 +Epoch: [13] [ 250/1319] eta: 0:56:51 lr: 3.4880189358923125e-05 loss: 0.0520 (0.0643) time: 3.1763 data: 0.0100 max mem: 33369 +Epoch: [13] [ 260/1319] eta: 0:56:19 lr: 3.487131185925179e-05 loss: 0.0561 (0.0643) time: 3.1807 data: 0.0098 max mem: 33369 +Epoch: [13] [ 270/1319] eta: 0:55:48 lr: 3.486243410845958e-05 loss: 0.0513 (0.0640) time: 3.2073 data: 0.0099 max mem: 33369 +Epoch: [13] [ 280/1319] eta: 0:55:17 lr: 3.485355610646832e-05 loss: 0.0546 (0.0643) time: 3.2156 data: 0.0102 max mem: 33369 +Epoch: [13] [ 290/1319] eta: 0:54:45 lr: 3.484467785319982e-05 loss: 0.0575 (0.0650) time: 3.2017 data: 0.0097 max mem: 33369 +Epoch: [13] [ 300/1319] eta: 0:54:12 lr: 3.483579934857581e-05 loss: 0.0666 (0.0652) time: 3.1854 data: 0.0089 max mem: 33369 +Epoch: [13] [ 310/1319] eta: 0:53:40 lr: 3.4826920592518003e-05 loss: 0.0678 (0.0654) time: 3.1760 data: 0.0085 max mem: 33369 +Epoch: [13] [ 320/1319] eta: 0:53:07 lr: 3.481804158494804e-05 loss: 0.0678 (0.0657) time: 3.1645 data: 0.0088 max mem: 33369 +Epoch: [13] [ 330/1319] eta: 0:52:34 lr: 3.4809162325787535e-05 loss: 0.0618 (0.0657) time: 3.1547 data: 0.0091 max mem: 33369 +Epoch: [13] [ 340/1319] eta: 0:52:03 lr: 3.480028281495805e-05 loss: 0.0550 (0.0655) time: 3.1849 data: 0.0089 max mem: 33369 +Epoch: [13] [ 350/1319] eta: 0:51:30 lr: 3.479140305238109e-05 loss: 0.0584 (0.0657) time: 3.1825 data: 0.0102 max mem: 33369 +Epoch: [13] [ 360/1319] eta: 0:50:57 lr: 3.478252303797812e-05 loss: 0.0586 (0.0656) time: 3.1586 data: 0.0103 max mem: 33369 +Epoch: [13] [ 370/1319] eta: 0:50:25 lr: 3.4773642771670566e-05 loss: 0.0687 (0.0658) time: 3.1726 data: 0.0089 max mem: 33369 +Epoch: [13] [ 380/1319] eta: 0:49:52 lr: 3.47647622533798e-05 loss: 0.0571 (0.0659) time: 3.1697 data: 0.0085 max 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3.413359644072625e-05 loss: 0.0740 (0.0690) time: 3.1983 data: 0.0100 max mem: 33369 +Epoch: [13] [1100/1319] eta: 0:11:37 lr: 3.412469756992473e-05 loss: 0.0686 (0.0691) time: 3.2051 data: 0.0092 max mem: 33369 +Epoch: [13] [1110/1319] eta: 0:11:05 lr: 3.411579844127087e-05 loss: 0.0701 (0.0693) time: 3.1649 data: 0.0101 max mem: 33369 +Epoch: [13] [1120/1319] eta: 0:10:33 lr: 3.410689905468246e-05 loss: 0.0538 (0.0693) time: 3.1670 data: 0.0110 max mem: 33369 +Epoch: [13] [1130/1319] eta: 0:10:01 lr: 3.409799941007725e-05 loss: 0.0529 (0.0692) time: 3.2183 data: 0.0108 max mem: 33369 +Epoch: [13] [1140/1319] eta: 0:09:29 lr: 3.408909950737292e-05 loss: 0.0562 (0.0691) time: 3.2028 data: 0.0110 max mem: 33369 +Epoch: [13] [1150/1319] eta: 0:08:58 lr: 3.4080199346487104e-05 loss: 0.0587 (0.0691) time: 3.1938 data: 0.0096 max mem: 33369 +Epoch: [13] [1160/1319] eta: 0:08:26 lr: 3.4071298927337405e-05 loss: 0.0660 (0.0692) time: 3.2218 data: 0.0093 max mem: 33369 +Epoch: [13] [1170/1319] eta: 0:07:54 lr: 3.406239824984136e-05 loss: 0.0691 (0.0693) time: 3.2035 data: 0.0096 max mem: 33369 +Epoch: [13] [1180/1319] eta: 0:07:22 lr: 3.405349731391645e-05 loss: 0.0685 (0.0694) time: 3.1689 data: 0.0096 max mem: 33369 +Epoch: [13] [1190/1319] eta: 0:06:50 lr: 3.404459611948011e-05 loss: 0.0643 (0.0695) time: 3.1568 data: 0.0093 max mem: 33369 +Epoch: [13] [1200/1319] eta: 0:06:18 lr: 3.4035694666449745e-05 loss: 0.0568 (0.0695) time: 3.1630 data: 0.0093 max mem: 33369 +Epoch: [13] [1210/1319] eta: 0:05:47 lr: 3.402679295474268e-05 loss: 0.0676 (0.0695) time: 3.1719 data: 0.0101 max mem: 33369 +Epoch: [13] [1220/1319] eta: 0:05:15 lr: 3.401789098427621e-05 loss: 0.0676 (0.0695) time: 3.1620 data: 0.0100 max mem: 33369 +Epoch: [13] [1230/1319] eta: 0:04:43 lr: 3.400898875496756e-05 loss: 0.0627 (0.0695) time: 3.1937 data: 0.0103 max mem: 33369 +Epoch: [13] [1240/1319] eta: 0:04:11 lr: 3.400008626673392e-05 loss: 0.0563 (0.0693) time: 3.2035 data: 0.0103 max mem: 33369 +Epoch: [13] [1250/1319] eta: 0:03:39 lr: 3.399118351949243e-05 loss: 0.0547 (0.0692) time: 3.1766 data: 0.0102 max mem: 33369 +Epoch: [13] [1260/1319] eta: 0:03:07 lr: 3.398228051316017e-05 loss: 0.0595 (0.0693) time: 3.1975 data: 0.0102 max mem: 33369 +Epoch: [13] [1270/1319] eta: 0:02:36 lr: 3.397337724765419e-05 loss: 0.0766 (0.0694) time: 3.1805 data: 0.0101 max mem: 33369 +Epoch: [13] [1280/1319] eta: 0:02:04 lr: 3.396447372289146e-05 loss: 0.0733 (0.0694) time: 3.1698 data: 0.0098 max mem: 33369 +Epoch: [13] [1290/1319] eta: 0:01:32 lr: 3.395556993878891e-05 loss: 0.0695 (0.0693) time: 3.1976 data: 0.0092 max mem: 33369 +Epoch: [13] [1300/1319] eta: 0:01:00 lr: 3.394666589526343e-05 loss: 0.0627 (0.0693) time: 3.1874 data: 0.0092 max mem: 33369 +Epoch: [13] [1310/1319] eta: 0:00:28 lr: 3.393776159223184e-05 loss: 0.0602 (0.0693) time: 3.1838 data: 0.0086 max mem: 33369 +Epoch: [13] Total time: 1:09:59 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 2:55:12 time: 4.0856 data: 3.9009 max mem: 33369 +Test: [ 100/2573] eta: 0:04:52 time: 0.0780 data: 0.0016 max mem: 33369 +Test: [ 200/2573] eta: 0:03:55 time: 0.0801 data: 0.0016 max mem: 33369 +Test: [ 300/2573] eta: 0:03:30 time: 0.0820 data: 0.0016 max mem: 33369 +Test: [ 400/2573] eta: 0:03:14 time: 0.0849 data: 0.0018 max mem: 33369 +Test: [ 500/2573] eta: 0:03:02 time: 0.0803 data: 0.0015 max mem: 33369 +Test: [ 600/2573] eta: 0:02:51 time: 0.0814 data: 0.0017 max mem: 33369 +Test: [ 700/2573] eta: 0:02:41 time: 0.0802 data: 0.0014 max mem: 33369 +Test: [ 800/2573] eta: 0:02:31 time: 0.0829 data: 0.0016 max mem: 33369 +Test: [ 900/2573] eta: 0:02:22 time: 0.0815 data: 0.0016 max mem: 33369 +Test: [1000/2573] eta: 0:02:13 time: 0.0809 data: 0.0016 max mem: 33369 +Test: [1100/2573] eta: 0:02:04 time: 0.0809 data: 0.0016 max mem: 33369 +Test: [1200/2573] eta: 0:01:55 time: 0.0802 data: 0.0015 max mem: 33369 +Test: [1300/2573] eta: 0:01:46 time: 0.0819 data: 0.0016 max mem: 33369 +Test: [1400/2573] eta: 0:01:38 time: 0.0809 data: 0.0015 max mem: 33369 +Test: [1500/2573] eta: 0:01:29 time: 0.0812 data: 0.0016 max mem: 33369 +Test: [1600/2573] eta: 0:01:21 time: 0.0846 data: 0.0015 max mem: 33369 +Test: [1700/2573] eta: 0:01:12 time: 0.0802 data: 0.0016 max mem: 33369 +Test: [1800/2573] eta: 0:01:04 time: 0.0830 data: 0.0015 max mem: 33369 +Test: [1900/2573] eta: 0:00:55 time: 0.0797 data: 0.0016 max mem: 33369 +Test: [2000/2573] eta: 0:00:47 time: 0.0819 data: 0.0016 max mem: 33369 +Test: [2100/2573] eta: 0:00:39 time: 0.0828 data: 0.0013 max mem: 33369 +Test: [2200/2573] eta: 0:00:30 time: 0.0831 data: 0.0014 max mem: 33369 +Test: [2300/2573] eta: 0:00:22 time: 0.0822 data: 0.0015 max mem: 33369 +Test: [2400/2573] eta: 0:00:14 time: 0.0788 data: 0.0015 max mem: 33369 +Test: [2500/2573] eta: 0:00:06 time: 0.0803 data: 0.0015 max mem: 33369 +Test: Total time: 0:03:33 +Final results: +Mean IoU is 61.30 + + precision@0.5 = 69.08 + precision@0.6 = 62.85 + precision@0.7 = 54.53 + precision@0.8 = 42.99 + precision@0.9 = 20.38 + overall IoU = 60.24 + +Average object IoU 61.30343438365997 +Overall IoU 60.23670196533203 +Better epoch: 13 + +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [14] [ 0/1319] eta: 1:57:33 lr: 3.392974749755691e-05 loss: 0.0493 (0.0493) time: 5.3473 data: 2.0708 max mem: 33369 +Epoch: [14] [ 10/1319] eta: 1:14:26 lr: 3.392084270123441e-05 loss: 0.0493 (0.0596) time: 3.4122 data: 0.1974 max mem: 33369 +Epoch: [14] [ 20/1319] eta: 1:11:29 lr: 3.391193764516433e-05 loss: 0.0515 (0.0676) time: 3.1997 data: 0.0090 max mem: 33369 +Epoch: [14] [ 30/1319] eta: 1:10:19 lr: 3.3903032329263314e-05 loss: 0.0660 (0.0693) time: 3.1977 data: 0.0089 max mem: 33369 +Epoch: [14] [ 40/1319] eta: 1:09:25 lr: 3.389412675344791e-05 loss: 0.0647 (0.0697) time: 3.2102 data: 0.0103 max mem: 33369 +Epoch: [14] [ 50/1319] eta: 1:08:35 lr: 3.388522091763468e-05 loss: 0.0638 (0.0706) time: 3.1949 data: 0.0105 max mem: 33369 +Epoch: [14] [ 60/1319] eta: 1:07:51 lr: 3.387631482174009e-05 loss: 0.0638 (0.0727) time: 3.1870 data: 0.0099 max mem: 33369 +Epoch: [14] [ 70/1319] eta: 1:07:09 lr: 3.386740846568057e-05 loss: 0.0501 (0.0697) time: 3.1826 data: 0.0095 max mem: 33369 +Epoch: [14] [ 80/1319] eta: 1:06:34 lr: 3.385850184937249e-05 loss: 0.0464 (0.0689) time: 3.1918 data: 0.0091 max mem: 33369 +Epoch: [14] [ 90/1319] eta: 1:05:57 lr: 3.3849594972732175e-05 loss: 0.0544 (0.0686) time: 3.2000 data: 0.0095 max mem: 33369 +Epoch: [14] [ 100/1319] eta: 1:05:20 lr: 3.38406878356759e-05 loss: 0.0522 (0.0673) time: 3.1836 data: 0.0100 max mem: 33369 +Epoch: [14] [ 110/1319] eta: 1:04:40 lr: 3.3831780438119907e-05 loss: 0.0522 (0.0673) time: 3.1623 data: 0.0100 max mem: 33369 +Epoch: [14] [ 120/1319] eta: 1:04:05 lr: 3.3822872779980336e-05 loss: 0.0643 (0.0676) time: 3.1638 data: 0.0102 max mem: 33369 +Epoch: [14] [ 130/1319] eta: 1:03:31 lr: 3.381396486117332e-05 loss: 0.0620 (0.0673) time: 3.1819 data: 0.0099 max mem: 33369 +Epoch: [14] [ 140/1319] eta: 1:02:58 lr: 3.380505668161494e-05 loss: 0.0577 (0.0674) time: 3.1904 data: 0.0099 max mem: 33369 +Epoch: [14] [ 150/1319] eta: 1:02:21 lr: 3.3796148241221185e-05 loss: 0.0580 (0.0668) time: 3.1696 data: 0.0101 max mem: 33369 +Epoch: [14] [ 160/1319] eta: 1:01:48 lr: 3.378723953990804e-05 loss: 0.0576 (0.0673) time: 3.1655 data: 0.0095 max mem: 33369 +Epoch: [14] [ 170/1319] eta: 1:01:15 lr: 3.3778330577591404e-05 loss: 0.0621 (0.0673) time: 3.1873 data: 0.0092 max mem: 33369 +Epoch: [14] [ 180/1319] eta: 1:00:41 lr: 3.3769421354187145e-05 loss: 0.0697 (0.0676) time: 3.1752 data: 0.0096 max mem: 33369 +Epoch: [14] [ 190/1319] eta: 1:00:07 lr: 3.376051186961107e-05 loss: 0.0571 (0.0673) time: 3.1597 data: 0.0095 max mem: 33369 +Epoch: [14] [ 200/1319] eta: 0:59:33 lr: 3.375160212377894e-05 loss: 0.0586 (0.0674) time: 3.1584 data: 0.0094 max mem: 33369 +Epoch: [14] [ 210/1319] eta: 0:59:00 lr: 3.374269211660646e-05 loss: 0.0545 (0.0669) time: 3.1676 data: 0.0098 max mem: 33369 +Epoch: [14] [ 220/1319] eta: 0:58:29 lr: 3.373378184800928e-05 loss: 0.0536 (0.0671) time: 3.1899 data: 0.0098 max mem: 33369 +Epoch: [14] [ 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33369 +Epoch: [14] [ 310/1319] eta: 0:53:34 lr: 3.365357765258022e-05 loss: 0.0500 (0.0646) time: 3.1859 data: 0.0108 max mem: 33369 +Epoch: [14] [ 320/1319] eta: 0:53:05 lr: 3.364466476508552e-05 loss: 0.0497 (0.0642) time: 3.2176 data: 0.0105 max mem: 33369 +Epoch: [14] [ 330/1319] eta: 0:52:33 lr: 3.363575161523487e-05 loss: 0.0472 (0.0637) time: 3.2334 data: 0.0105 max mem: 33369 +Epoch: [14] [ 340/1319] eta: 0:52:00 lr: 3.362683820294329e-05 loss: 0.0485 (0.0638) time: 3.1679 data: 0.0102 max mem: 33369 +Epoch: [14] [ 350/1319] eta: 0:51:28 lr: 3.361792452812576e-05 loss: 0.0525 (0.0639) time: 3.1579 data: 0.0095 max mem: 33369 +Epoch: [14] [ 360/1319] eta: 0:50:56 lr: 3.36090105906972e-05 loss: 0.0698 (0.0643) time: 3.1870 data: 0.0093 max mem: 33369 +Epoch: [14] [ 370/1319] eta: 0:50:25 lr: 3.3600096390572475e-05 loss: 0.0663 (0.0642) time: 3.2037 data: 0.0098 max mem: 33369 +Epoch: [14] [ 380/1319] eta: 0:49:53 lr: 3.3591181927666404e-05 loss: 0.0624 (0.0641) time: 3.1900 data: 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eta: 0:32:50 lr: 3.330577985360116e-05 loss: 0.0682 (0.0656) time: 3.2277 data: 0.0101 max mem: 33369 +Epoch: [14] [ 710/1319] eta: 0:32:19 lr: 3.329685667077455e-05 loss: 0.0536 (0.0655) time: 3.2369 data: 0.0101 max mem: 33369 +Epoch: [14] [ 720/1319] eta: 0:31:47 lr: 3.3287933222238623e-05 loss: 0.0516 (0.0656) time: 3.1869 data: 0.0110 max mem: 33369 +Epoch: [14] [ 730/1319] eta: 0:31:15 lr: 3.327900950790632e-05 loss: 0.0603 (0.0655) time: 3.1733 data: 0.0104 max mem: 33369 +Epoch: [14] [ 740/1319] eta: 0:30:43 lr: 3.327008552769054e-05 loss: 0.0537 (0.0654) time: 3.1954 data: 0.0090 max mem: 33369 +Epoch: [14] [ 750/1319] eta: 0:30:11 lr: 3.32611612815041e-05 loss: 0.0513 (0.0653) time: 3.1850 data: 0.0096 max mem: 33369 +Epoch: [14] [ 760/1319] eta: 0:29:40 lr: 3.325223676925979e-05 loss: 0.0536 (0.0652) time: 3.1925 data: 0.0096 max mem: 33369 +Epoch: [14] [ 770/1319] eta: 0:29:08 lr: 3.324331199087032e-05 loss: 0.0622 (0.0654) time: 3.1907 data: 0.0092 max mem: 33369 +Epoch: 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mem: 33369 +Epoch: [14] [ 860/1319] eta: 0:24:21 lr: 3.3162976994405264e-05 loss: 0.0562 (0.0654) time: 3.1685 data: 0.0097 max mem: 33369 +Epoch: [14] [ 870/1319] eta: 0:23:49 lr: 3.315404954975194e-05 loss: 0.0612 (0.0653) time: 3.1760 data: 0.0098 max mem: 33369 +Epoch: [14] [ 880/1319] eta: 0:23:17 lr: 3.314512183798977e-05 loss: 0.0575 (0.0653) time: 3.1656 data: 0.0092 max mem: 33369 +Epoch: [14] [ 890/1319] eta: 0:22:45 lr: 3.3136193859030854e-05 loss: 0.0549 (0.0653) time: 3.1623 data: 0.0086 max mem: 33369 +Epoch: [14] [ 900/1319] eta: 0:22:13 lr: 3.312726561278717e-05 loss: 0.0492 (0.0651) time: 3.1846 data: 0.0081 max mem: 33369 +Epoch: [14] [ 910/1319] eta: 0:21:41 lr: 3.311833709917069e-05 loss: 0.0493 (0.0651) time: 3.2073 data: 0.0089 max mem: 33369 +Epoch: [14] [ 920/1319] eta: 0:21:10 lr: 3.3109408318093296e-05 loss: 0.0588 (0.0650) time: 3.1943 data: 0.0101 max mem: 33369 +Epoch: [14] [ 930/1319] eta: 0:20:38 lr: 3.310047926946684e-05 loss: 0.0560 (0.0650) time: 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(0.0654) time: 3.1923 data: 0.0089 max mem: 33369 +Epoch: [14] [1020/1319] eta: 0:15:51 lr: 3.3020105777547046e-05 loss: 0.0635 (0.0654) time: 3.1897 data: 0.0094 max mem: 33369 +Epoch: [14] [1030/1319] eta: 0:15:20 lr: 3.301117404856897e-05 loss: 0.0635 (0.0654) time: 3.1934 data: 0.0094 max mem: 33369 +Epoch: [14] [1040/1319] eta: 0:14:48 lr: 3.300224205106842e-05 loss: 0.0571 (0.0653) time: 3.1990 data: 0.0090 max mem: 33369 +Epoch: [14] [1050/1319] eta: 0:14:16 lr: 3.2993309784956545e-05 loss: 0.0591 (0.0654) time: 3.2200 data: 0.0093 max mem: 33369 +Epoch: [14] [1060/1319] eta: 0:13:44 lr: 3.298437725014447e-05 loss: 0.0615 (0.0653) time: 3.2114 data: 0.0103 max mem: 33369 +Epoch: [14] [1070/1319] eta: 0:13:12 lr: 3.297544444654327e-05 loss: 0.0538 (0.0653) time: 3.2041 data: 0.0102 max mem: 33369 +Epoch: [14] [1080/1319] eta: 0:12:40 lr: 3.296651137406393e-05 loss: 0.0550 (0.0653) time: 3.1713 data: 0.0096 max mem: 33369 +Epoch: [14] [1090/1319] eta: 0:12:09 lr: 3.2957578032617413e-05 loss: 0.0566 (0.0654) time: 3.1751 data: 0.0090 max mem: 33369 +Epoch: [14] [1100/1319] eta: 0:11:37 lr: 3.29486444221146e-05 loss: 0.0598 (0.0655) time: 3.2069 data: 0.0090 max mem: 33369 +Epoch: [14] [1110/1319] eta: 0:11:05 lr: 3.293971054246633e-05 loss: 0.0665 (0.0656) time: 3.1991 data: 0.0092 max mem: 33369 +Epoch: [14] [1120/1319] eta: 0:10:33 lr: 3.293077639358339e-05 loss: 0.0596 (0.0655) time: 3.1809 data: 0.0098 max mem: 33369 +Epoch: [14] [1130/1319] eta: 0:10:01 lr: 3.2921841975376476e-05 loss: 0.0545 (0.0656) time: 3.1762 data: 0.0099 max mem: 33369 +Epoch: [14] [1140/1319] eta: 0:09:30 lr: 3.291290728775627e-05 loss: 0.0612 (0.0655) time: 3.1808 data: 0.0093 max mem: 33369 +Epoch: [14] [1150/1319] eta: 0:08:58 lr: 3.290397233063338e-05 loss: 0.0664 (0.0656) time: 3.1768 data: 0.0099 max mem: 33369 +Epoch: [14] [1160/1319] eta: 0:08:26 lr: 3.2895037103918356e-05 loss: 0.0688 (0.0657) time: 3.1820 data: 0.0103 max mem: 33369 +Epoch: [14] [1170/1319] eta: 0:07:54 lr: 3.2886101607521696e-05 loss: 0.0578 (0.0656) time: 3.2041 data: 0.0100 max mem: 33369 +Epoch: [14] [1180/1319] eta: 0:07:22 lr: 3.287716584135384e-05 loss: 0.0547 (0.0656) time: 3.2101 data: 0.0101 max mem: 33369 +Epoch: [14] [1190/1319] eta: 0:06:50 lr: 3.286822980532516e-05 loss: 0.0598 (0.0656) time: 3.1931 data: 0.0106 max mem: 33369 +Epoch: [14] [1200/1319] eta: 0:06:18 lr: 3.285929349934599e-05 loss: 0.0625 (0.0656) time: 3.1768 data: 0.0110 max mem: 33369 +Epoch: [14] [1210/1319] eta: 0:05:47 lr: 3.28503569233266e-05 loss: 0.0561 (0.0656) time: 3.1750 data: 0.0103 max mem: 33369 +Epoch: [14] [1220/1319] eta: 0:05:15 lr: 3.284142007717719e-05 loss: 0.0647 (0.0656) time: 3.1735 data: 0.0091 max mem: 33369 +Epoch: [14] [1230/1319] eta: 0:04:43 lr: 3.283248296080793e-05 loss: 0.0647 (0.0656) time: 3.1953 data: 0.0089 max mem: 33369 +Epoch: [14] [1240/1319] eta: 0:04:11 lr: 3.2823545574128904e-05 loss: 0.0606 (0.0656) time: 3.1966 data: 0.0091 max mem: 33369 +Epoch: [14] [1250/1319] eta: 0:03:39 lr: 3.2814607917050156e-05 loss: 0.0586 (0.0655) time: 3.1702 data: 0.0091 max mem: 33369 +Epoch: [14] [1260/1319] eta: 0:03:07 lr: 3.280566998948166e-05 loss: 0.0505 (0.0654) time: 3.1885 data: 0.0095 max mem: 33369 +Epoch: [14] [1270/1319] eta: 0:02:36 lr: 3.2796731791333364e-05 loss: 0.0664 (0.0655) time: 3.1937 data: 0.0099 max mem: 33369 +Epoch: [14] [1280/1319] eta: 0:02:04 lr: 3.278779332251511e-05 loss: 0.0575 (0.0654) time: 3.1811 data: 0.0103 max mem: 33369 +Epoch: [14] [1290/1319] eta: 0:01:32 lr: 3.277885458293673e-05 loss: 0.0560 (0.0654) time: 3.1816 data: 0.0105 max mem: 33369 +Epoch: [14] [1300/1319] eta: 0:01:00 lr: 3.276991557250796e-05 loss: 0.0581 (0.0654) time: 3.1984 data: 0.0106 max mem: 33369 +Epoch: [14] [1310/1319] eta: 0:00:28 lr: 3.276097629113851e-05 loss: 0.0581 (0.0654) time: 3.1843 data: 0.0095 max mem: 33369 +Epoch: [14] Total time: 1:10:01 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 2:55:45 time: 4.0984 data: 4.0141 max mem: 33369 +Test: [ 100/2573] eta: 0:04:52 time: 0.0764 data: 0.0014 max mem: 33369 +Test: [ 200/2573] eta: 0:03:56 time: 0.0797 data: 0.0016 max mem: 33369 +Test: [ 300/2573] eta: 0:03:31 time: 0.0799 data: 0.0014 max mem: 33369 +Test: [ 400/2573] eta: 0:03:14 time: 0.0806 data: 0.0014 max mem: 33369 +Test: [ 500/2573] eta: 0:03:01 time: 0.0829 data: 0.0017 max mem: 33369 +Test: [ 600/2573] eta: 0:02:50 time: 0.0793 data: 0.0015 max mem: 33369 +Test: [ 700/2573] eta: 0:02:40 time: 0.0814 data: 0.0017 max mem: 33369 +Test: [ 800/2573] eta: 0:02:31 time: 0.0831 data: 0.0016 max mem: 33369 +Test: [ 900/2573] eta: 0:02:22 time: 0.0806 data: 0.0015 max mem: 33369 +Test: [1000/2573] eta: 0:02:12 time: 0.0806 data: 0.0014 max mem: 33369 +Test: [1100/2573] eta: 0:02:03 time: 0.0816 data: 0.0017 max mem: 33369 +Test: [1200/2573] eta: 0:01:55 time: 0.0795 data: 0.0015 max mem: 33369 +Test: [1300/2573] eta: 0:01:46 time: 0.0797 data: 0.0016 max mem: 33369 +Test: [1400/2573] eta: 0:01:37 time: 0.0814 data: 0.0015 max mem: 33369 +Test: [1500/2573] eta: 0:01:29 time: 0.0809 data: 0.0016 max mem: 33369 +Test: [1600/2573] eta: 0:01:20 time: 0.0833 data: 0.0015 max mem: 33369 +Test: [1700/2573] eta: 0:01:12 time: 0.0812 data: 0.0016 max mem: 33369 +Test: [1800/2573] eta: 0:01:04 time: 0.0828 data: 0.0015 max mem: 33369 +Test: [1900/2573] eta: 0:00:55 time: 0.0797 data: 0.0016 max mem: 33369 +Test: [2000/2573] eta: 0:00:47 time: 0.0813 data: 0.0017 max mem: 33369 +Test: [2100/2573] eta: 0:00:39 time: 0.0843 data: 0.0016 max mem: 33369 +Test: [2200/2573] eta: 0:00:30 time: 0.0823 data: 0.0015 max mem: 33369 +Test: [2300/2573] eta: 0:00:22 time: 0.0832 data: 0.0017 max mem: 33369 +Test: [2400/2573] eta: 0:00:14 time: 0.0782 data: 0.0016 max mem: 33369 +Test: [2500/2573] eta: 0:00:06 time: 0.0800 data: 0.0015 max mem: 33369 +Test: Total time: 0:03:32 +Final results: +Mean IoU is 61.30 + + precision@0.5 = 68.75 + precision@0.6 = 63.05 + precision@0.7 = 54.82 + precision@0.8 = 43.46 + precision@0.9 = 20.14 + overall IoU = 60.16 + +Average object IoU 61.296680521665714 +Overall IoU 60.161170959472656 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [15] [ 0/1319] eta: 3:30:36 lr: 3.275293070617704e-05 loss: 0.1086 (0.1086) time: 9.5804 data: 2.9424 max mem: 33369 +Epoch: [15] [ 10/1319] eta: 1:22:45 lr: 3.274399090977129e-05 loss: 0.0731 (0.0878) time: 3.7930 data: 0.2765 max mem: 33369 +Epoch: [15] [ 20/1319] eta: 1:16:01 lr: 3.2735050842162644e-05 loss: 0.0545 (0.0764) time: 3.2082 data: 0.0096 max mem: 33369 +Epoch: [15] [ 30/1319] eta: 1:13:00 lr: 3.2726110503260586e-05 loss: 0.0534 (0.0714) time: 3.1810 data: 0.0091 max mem: 33369 +Epoch: [15] [ 40/1319] eta: 1:11:16 lr: 3.271716989297451e-05 loss: 0.0505 (0.0657) time: 3.1676 data: 0.0088 max mem: 33369 +Epoch: [15] [ 50/1319] eta: 1:10:00 lr: 3.2708229011213794e-05 loss: 0.0430 (0.0691) time: 3.1727 data: 0.0085 max mem: 33369 +Epoch: [15] [ 60/1319] eta: 1:08:56 lr: 3.269928785788772e-05 loss: 0.0632 (0.0694) time: 3.1660 data: 0.0084 max mem: 33369 +Epoch: [15] [ 70/1319] eta: 1:08:13 lr: 3.2690346432905536e-05 loss: 0.0578 (0.0683) time: 3.1948 data: 0.0088 max mem: 33369 +Epoch: [15] [ 80/1319] eta: 1:07:27 lr: 3.268140473617642e-05 loss: 0.0572 (0.0682) time: 3.2095 data: 0.0099 max mem: 33369 +Epoch: [15] [ 90/1319] eta: 1:06:39 lr: 3.26724627676095e-05 loss: 0.0522 (0.0663) time: 3.1721 data: 0.0104 max mem: 33369 +Epoch: [15] [ 100/1319] eta: 1:05:59 lr: 3.266352052711384e-05 loss: 0.0503 (0.0652) time: 3.1726 data: 0.0100 max mem: 33369 +Epoch: [15] [ 110/1319] eta: 1:05:22 lr: 3.265457801459844e-05 loss: 0.0555 (0.0644) time: 3.2019 data: 0.0097 max mem: 33369 +Epoch: [15] [ 120/1319] eta: 1:04:46 lr: 3.2645635229972264e-05 loss: 0.0560 (0.0635) time: 3.2081 data: 0.0099 max mem: 33369 +Epoch: [15] [ 130/1319] eta: 1:04:10 lr: 3.2636692173144204e-05 loss: 0.0547 (0.0639) time: 3.2027 data: 0.0096 max mem: 33369 +Epoch: [15] [ 140/1319] eta: 1:03:31 lr: 3.2627748844023084e-05 loss: 0.0541 (0.0636) time: 3.1813 data: 0.0088 max mem: 33369 +Epoch: [15] [ 150/1319] eta: 1:02:54 lr: 3.261880524251768e-05 loss: 0.0541 (0.0634) time: 3.1679 data: 0.0095 max mem: 33369 +Epoch: [15] [ 160/1319] eta: 1:02:20 lr: 3.260986136853672e-05 loss: 0.0608 (0.0634) time: 3.1847 data: 0.0098 max mem: 33369 +Epoch: [15] [ 170/1319] eta: 1:01:46 lr: 3.2600917221988844e-05 loss: 0.0643 (0.0644) time: 3.2004 data: 0.0102 max mem: 33369 +Epoch: [15] [ 180/1319] eta: 1:01:13 lr: 3.259197280278268e-05 loss: 0.0592 (0.0640) time: 3.2126 data: 0.0104 max mem: 33369 +Epoch: [15] [ 190/1319] eta: 1:00:39 lr: 3.258302811082674e-05 loss: 0.0489 (0.0633) time: 3.2042 data: 0.0100 max mem: 33369 +Epoch: [15] [ 200/1319] eta: 1:00:04 lr: 3.257408314602953e-05 loss: 0.0485 (0.0629) time: 3.1846 data: 0.0102 max mem: 33369 +Epoch: [15] [ 210/1319] eta: 0:59:29 lr: 3.2565137908299456e-05 loss: 0.0586 (0.0645) time: 3.1735 data: 0.0105 max mem: 33369 +Epoch: [15] [ 220/1319] eta: 0:58:53 lr: 3.25561923975449e-05 loss: 0.0589 (0.0642) time: 3.1578 data: 0.0102 max mem: 33369 +Epoch: [15] [ 230/1319] eta: 0:58:22 lr: 3.2547246613674155e-05 loss: 0.0503 (0.0636) time: 3.1896 data: 0.0094 max mem: 33369 +Epoch: [15] [ 240/1319] eta: 0:57:48 lr: 3.253830055659547e-05 loss: 0.0536 (0.0634) time: 3.2036 data: 0.0090 max mem: 33369 +Epoch: [15] [ 250/1319] eta: 0:57:15 lr: 3.252935422621704e-05 loss: 0.0543 (0.0630) time: 3.1876 data: 0.0089 max mem: 33369 +Epoch: [15] [ 260/1319] eta: 0:56:42 lr: 3.252040762244701e-05 loss: 0.0470 (0.0627) time: 3.1880 data: 0.0092 max mem: 33369 +Epoch: [15] [ 270/1319] eta: 0:56:07 lr: 3.251146074519342e-05 loss: 0.0483 (0.0630) time: 3.1614 data: 0.0106 max mem: 33369 +Epoch: [15] [ 280/1319] eta: 0:55:32 lr: 3.2502513594364305e-05 loss: 0.0557 (0.0629) time: 3.1395 data: 0.0102 max mem: 33369 +Epoch: [15] [ 290/1319] eta: 0:55:01 lr: 3.2493566169867616e-05 loss: 0.0557 (0.0627) time: 3.1847 data: 0.0098 max mem: 33369 +Epoch: [15] [ 300/1319] eta: 0:54:29 lr: 3.248461847161124e-05 loss: 0.0523 (0.0624) time: 3.2200 data: 0.0098 max mem: 33369 +Epoch: [15] [ 310/1319] eta: 0:53:56 lr: 3.247567049950301e-05 loss: 0.0540 (0.0625) time: 3.2046 data: 0.0096 max mem: 33369 +Epoch: [15] [ 320/1319] eta: 0:53:25 lr: 3.246672225345071e-05 loss: 0.0595 (0.0622) time: 3.2097 data: 0.0101 max mem: 33369 +Epoch: [15] [ 330/1319] eta: 0:52:52 lr: 3.245777373336205e-05 loss: 0.0527 (0.0620) time: 3.2006 data: 0.0092 max mem: 33369 +Epoch: [15] [ 340/1319] eta: 0:52:19 lr: 3.244882493914469e-05 loss: 0.0485 (0.0617) time: 3.1835 data: 0.0095 max mem: 33369 +Epoch: [15] [ 350/1319] eta: 0:51:46 lr: 3.243987587070623e-05 loss: 0.0487 (0.0617) time: 3.1801 data: 0.0099 max mem: 33369 +Epoch: [15] [ 360/1319] eta: 0:51:13 lr: 3.24309265279542e-05 loss: 0.0576 (0.0616) time: 3.1665 data: 0.0095 max mem: 33369 +Epoch: [15] [ 370/1319] eta: 0:50:40 lr: 3.2421976910796087e-05 loss: 0.0544 (0.0612) time: 3.1726 data: 0.0090 max mem: 33369 +Epoch: [15] [ 380/1319] eta: 0:50:08 lr: 3.24130270191393e-05 loss: 0.0544 (0.0613) time: 3.1969 data: 0.0090 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eta: 0:07:55 lr: 3.170511015754181e-05 loss: 0.0666 (0.0623) time: 3.1548 data: 0.0101 max mem: 33369 +Epoch: [15] [1180/1319] eta: 0:07:23 lr: 3.16961380006451e-05 loss: 0.0539 (0.0622) time: 3.1486 data: 0.0096 max mem: 33369 +Epoch: [15] [1190/1319] eta: 0:06:51 lr: 3.16871655615474e-05 loss: 0.0613 (0.0624) time: 3.1746 data: 0.0093 max mem: 33369 +Epoch: [15] [1200/1319] eta: 0:06:19 lr: 3.1678192840151044e-05 loss: 0.0613 (0.0624) time: 3.2079 data: 0.0088 max mem: 33369 +Epoch: [15] [1210/1319] eta: 0:05:47 lr: 3.16692198363583e-05 loss: 0.0551 (0.0624) time: 3.2008 data: 0.0088 max mem: 33369 +Epoch: [15] [1220/1319] eta: 0:05:15 lr: 3.1660246550071386e-05 loss: 0.0573 (0.0623) time: 3.1743 data: 0.0094 max mem: 33369 +Epoch: [15] [1230/1319] eta: 0:04:43 lr: 3.165127298119242e-05 loss: 0.0627 (0.0624) time: 3.1654 data: 0.0094 max mem: 33369 +Epoch: [15] [1240/1319] eta: 0:04:11 lr: 3.164229912962349e-05 loss: 0.0622 (0.0625) time: 3.1662 data: 0.0094 max mem: 33369 +Epoch: 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+/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 2:41:31 time: 3.7665 data: 3.4045 max mem: 33369 +Test: [ 100/2573] eta: 0:04:46 time: 0.0782 data: 0.0014 max mem: 33369 +Test: [ 200/2573] eta: 0:03:53 time: 0.0802 data: 0.0014 max mem: 33369 +Test: [ 300/2573] eta: 0:03:28 time: 0.0825 data: 0.0016 max mem: 33369 +Test: [ 400/2573] eta: 0:03:13 time: 0.0835 data: 0.0017 max mem: 33369 +Test: [ 500/2573] eta: 0:03:01 time: 0.0799 data: 0.0016 max mem: 33369 +Test: [ 600/2573] eta: 0:02:50 time: 0.0808 data: 0.0015 max mem: 33369 +Test: [ 700/2573] eta: 0:02:40 time: 0.0803 data: 0.0014 max mem: 33369 +Test: [ 800/2573] eta: 0:02:31 time: 0.0845 data: 0.0015 max mem: 33369 +Test: [ 900/2573] eta: 0:02:22 time: 0.0816 data: 0.0016 max mem: 33369 +Test: [1000/2573] eta: 0:02:13 time: 0.0819 data: 0.0019 max mem: 33369 +Test: [1100/2573] eta: 0:02:04 time: 0.0804 data: 0.0015 max mem: 33369 +Test: [1200/2573] eta: 0:01:55 time: 0.0806 data: 0.0016 max mem: 33369 +Test: [1300/2573] eta: 0:01:46 time: 0.0799 data: 0.0014 max mem: 33369 +Test: [1400/2573] eta: 0:01:38 time: 0.0789 data: 0.0016 max mem: 33369 +Test: [1500/2573] eta: 0:01:29 time: 0.0814 data: 0.0014 max mem: 33369 +Test: [1600/2573] eta: 0:01:21 time: 0.0836 data: 0.0014 max mem: 33369 +Test: [1700/2573] eta: 0:01:12 time: 0.0794 data: 0.0016 max mem: 33369 +Test: [1800/2573] eta: 0:01:04 time: 0.0817 data: 0.0015 max mem: 33369 +Test: [1900/2573] eta: 0:00:55 time: 0.0809 data: 0.0016 max mem: 33369 +Test: [2000/2573] eta: 0:00:47 time: 0.0803 data: 0.0016 max mem: 33369 +Test: [2100/2573] eta: 0:00:39 time: 0.0838 data: 0.0018 max mem: 33369 +Test: [2200/2573] eta: 0:00:30 time: 0.0830 data: 0.0015 max mem: 33369 +Test: [2300/2573] eta: 0:00:22 time: 0.0842 data: 0.0016 max mem: 33369 +Test: [2400/2573] eta: 0:00:14 time: 0.0764 data: 0.0015 max mem: 33369 +Test: [2500/2573] eta: 0:00:06 time: 0.0804 data: 0.0014 max mem: 33369 +Test: Total time: 0:03:32 +Final results: +Mean IoU is 62.09 + + precision@0.5 = 69.98 + precision@0.6 = 64.07 + precision@0.7 = 55.88 + precision@0.8 = 43.79 + precision@0.9 = 21.20 + overall IoU = 60.45 + +Average object IoU 62.09440768394141 +Overall IoU 60.4500732421875 +Better epoch: 15 + +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [16] [ 0/1319] eta: 1:59:24 lr: 3.157139575288201e-05 loss: 0.0531 (0.0531) time: 5.4319 data: 2.0670 max mem: 33369 +Epoch: [16] [ 10/1319] eta: 1:14:17 lr: 3.1562419381047834e-05 loss: 0.0505 (0.0481) time: 3.4055 data: 0.1968 max mem: 33369 +Epoch: [16] [ 20/1319] eta: 1:11:18 lr: 3.155344272555071e-05 loss: 0.0510 (0.0501) time: 3.1868 data: 0.0093 max mem: 33369 +Epoch: [16] [ 30/1319] eta: 1:10:03 lr: 3.154446578629201e-05 loss: 0.0541 (0.0513) time: 3.1814 data: 0.0098 max mem: 33369 +Epoch: [16] [ 40/1319] eta: 1:09:01 lr: 3.153548856317304e-05 loss: 0.0504 (0.0514) time: 3.1798 data: 0.0103 max mem: 33369 +Epoch: [16] [ 50/1319] eta: 1:08:19 lr: 3.152651105609501e-05 loss: 0.0430 (0.0494) time: 3.1828 data: 0.0095 max mem: 33369 +Epoch: [16] [ 60/1319] eta: 1:07:38 lr: 3.1517533264959104e-05 loss: 0.0425 (0.0493) time: 3.1936 data: 0.0088 max mem: 33369 +Epoch: [16] [ 70/1319] eta: 1:06:57 lr: 3.150855518966642e-05 loss: 0.0508 (0.0511) time: 3.1808 data: 0.0089 max mem: 33369 +Epoch: [16] [ 80/1319] eta: 1:06:21 lr: 3.1499576830118e-05 loss: 0.0508 (0.0505) time: 3.1817 data: 0.0093 max mem: 33369 +Epoch: [16] [ 90/1319] eta: 1:05:46 lr: 3.14905981862148e-05 loss: 0.0438 (0.0506) time: 3.1927 data: 0.0089 max mem: 33369 +Epoch: [16] [ 100/1319] eta: 1:05:13 lr: 3.1481619257857746e-05 loss: 0.0532 (0.0524) time: 3.1984 data: 0.0090 max mem: 33369 +Epoch: [16] [ 110/1319] eta: 1:04:39 lr: 3.147264004494766e-05 loss: 0.0565 (0.0525) time: 3.1970 data: 0.0092 max mem: 33369 +Epoch: [16] [ 120/1319] eta: 1:04:02 lr: 3.1463660547385324e-05 loss: 0.0530 (0.0528) time: 3.1785 data: 0.0096 max mem: 33369 +Epoch: [16] [ 130/1319] eta: 1:03:25 lr: 3.1454680765071425e-05 loss: 0.0491 (0.0528) time: 3.1565 data: 0.0099 max mem: 33369 +Epoch: [16] [ 140/1319] eta: 1:02:52 lr: 3.1445700697906627e-05 loss: 0.0459 (0.0523) time: 3.1689 data: 0.0097 max mem: 33369 +Epoch: [16] [ 150/1319] eta: 1:02:18 lr: 3.1436720345791495e-05 loss: 0.0518 (0.0536) time: 3.1829 data: 0.0096 max mem: 33369 +Epoch: [16] [ 160/1319] eta: 1:01:44 lr: 3.1427739708626534e-05 loss: 0.0560 (0.0538) time: 3.1712 data: 0.0095 max mem: 33369 +Epoch: [16] [ 170/1319] eta: 1:01:11 lr: 3.141875878631219e-05 loss: 0.0444 (0.0534) time: 3.1759 data: 0.0094 max mem: 33369 +Epoch: [16] [ 180/1319] eta: 1:00:38 lr: 3.140977757874883e-05 loss: 0.0430 (0.0537) time: 3.1813 data: 0.0094 max mem: 33369 +Epoch: [16] [ 190/1319] eta: 1:00:06 lr: 3.140079608583676e-05 loss: 0.0573 (0.0542) time: 3.1833 data: 0.0098 max mem: 33369 +Epoch: [16] [ 200/1319] eta: 0:59:32 lr: 3.1391814307476244e-05 loss: 0.0508 (0.0541) time: 3.1760 data: 0.0099 max mem: 33369 +Epoch: [16] [ 210/1319] eta: 0:59:00 lr: 3.138283224356744e-05 loss: 0.0497 (0.0544) time: 3.1758 data: 0.0094 max mem: 33369 +Epoch: [16] [ 220/1319] eta: 0:58:26 lr: 3.137384989401046e-05 loss: 0.0523 (0.0545) time: 3.1637 data: 0.0088 max mem: 33369 +Epoch: [16] [ 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33369 +Epoch: [16] [ 310/1319] eta: 0:53:38 lr: 3.129299587731458e-05 loss: 0.0553 (0.0551) time: 3.2209 data: 0.0096 max mem: 33369 +Epoch: [16] [ 320/1319] eta: 0:53:06 lr: 3.1284010665767105e-05 loss: 0.0553 (0.0555) time: 3.2223 data: 0.0093 max mem: 33369 +Epoch: [16] [ 330/1319] eta: 0:52:35 lr: 3.1275025167468235e-05 loss: 0.0599 (0.0563) time: 3.2050 data: 0.0084 max mem: 33369 +Epoch: [16] [ 340/1319] eta: 0:52:03 lr: 3.126603938231727e-05 loss: 0.0599 (0.0565) time: 3.1947 data: 0.0082 max mem: 33369 +Epoch: [16] [ 350/1319] eta: 0:51:30 lr: 3.1257053310213444e-05 loss: 0.0557 (0.0564) time: 3.1740 data: 0.0092 max mem: 33369 +Epoch: [16] [ 360/1319] eta: 0:50:58 lr: 3.124806695105593e-05 loss: 0.0457 (0.0561) time: 3.1648 data: 0.0101 max mem: 33369 +Epoch: [16] [ 370/1319] eta: 0:50:27 lr: 3.1239080304743815e-05 loss: 0.0501 (0.0563) time: 3.1938 data: 0.0096 max mem: 33369 +Epoch: [16] [ 380/1319] eta: 0:49:54 lr: 3.123009337117616e-05 loss: 0.0515 (0.0564) time: 3.1941 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eta: 0:12:08 lr: 3.059128050381978e-05 loss: 0.0464 (0.0583) time: 3.1705 data: 0.0087 max mem: 33369 +Epoch: [16] [1100/1319] eta: 0:11:36 lr: 3.058227261803723e-05 loss: 0.0467 (0.0584) time: 3.1619 data: 0.0093 max mem: 33369 +Epoch: [16] [1110/1319] eta: 0:11:04 lr: 3.0573264437440946e-05 loss: 0.0639 (0.0585) time: 3.1826 data: 0.0102 max mem: 33369 +Epoch: [16] [1120/1319] eta: 0:10:33 lr: 3.056425596192476e-05 loss: 0.0639 (0.0587) time: 3.2034 data: 0.0101 max mem: 33369 +Epoch: [16] [1130/1319] eta: 0:10:01 lr: 3.0555247191382436e-05 loss: 0.0521 (0.0586) time: 3.1802 data: 0.0108 max mem: 33369 +Epoch: [16] [1140/1319] eta: 0:09:29 lr: 3.054623812570766e-05 loss: 0.0519 (0.0585) time: 3.1696 data: 0.0112 max mem: 33369 +Epoch: [16] [1150/1319] eta: 0:08:57 lr: 3.053722876479403e-05 loss: 0.0511 (0.0585) time: 3.1898 data: 0.0098 max mem: 33369 +Epoch: [16] [1160/1319] eta: 0:08:25 lr: 3.0528219108535084e-05 loss: 0.0483 (0.0585) time: 3.2074 data: 0.0092 max mem: 33369 +Epoch: [16] [1170/1319] eta: 0:07:54 lr: 3.0519209156824297e-05 loss: 0.0616 (0.0586) time: 3.1986 data: 0.0094 max mem: 33369 +Epoch: [16] [1180/1319] eta: 0:07:22 lr: 3.0510198909555044e-05 loss: 0.0675 (0.0587) time: 3.1759 data: 0.0091 max mem: 33369 +Epoch: [16] [1190/1319] eta: 0:06:50 lr: 3.0501188366620653e-05 loss: 0.0590 (0.0586) time: 3.1952 data: 0.0093 max mem: 33369 +Epoch: [16] [1200/1319] eta: 0:06:18 lr: 3.0492177527914355e-05 loss: 0.0513 (0.0586) time: 3.1876 data: 0.0098 max mem: 33369 +Epoch: [16] [1210/1319] eta: 0:05:46 lr: 3.0483166393329327e-05 loss: 0.0546 (0.0586) time: 3.1609 data: 0.0098 max mem: 33369 +Epoch: [16] [1220/1319] eta: 0:05:14 lr: 3.0474154962758662e-05 loss: 0.0603 (0.0587) time: 3.1541 data: 0.0094 max mem: 33369 +Epoch: [16] [1230/1319] eta: 0:04:43 lr: 3.0465143236095372e-05 loss: 0.0650 (0.0588) time: 3.1630 data: 0.0095 max mem: 33369 +Epoch: [16] [1240/1319] eta: 0:04:11 lr: 3.045613121323242e-05 loss: 0.0584 (0.0588) time: 3.1887 data: 0.0097 max mem: 33369 +Epoch: [16] [1250/1319] eta: 0:03:39 lr: 3.044711889406267e-05 loss: 0.0496 (0.0587) time: 3.1963 data: 0.0092 max mem: 33369 +Epoch: [16] [1260/1319] eta: 0:03:07 lr: 3.0438106278478923e-05 loss: 0.0522 (0.0588) time: 3.1524 data: 0.0091 max mem: 33369 +Epoch: [16] [1270/1319] eta: 0:02:35 lr: 3.0429093366373907e-05 loss: 0.0604 (0.0589) time: 3.1636 data: 0.0096 max mem: 33369 +Epoch: [16] [1280/1319] eta: 0:02:04 lr: 3.0420080157640274e-05 loss: 0.0508 (0.0589) time: 3.2007 data: 0.0103 max mem: 33369 +Epoch: [16] [1290/1319] eta: 0:01:32 lr: 3.0411066652170593e-05 loss: 0.0498 (0.0588) time: 3.1922 data: 0.0095 max mem: 33369 +Epoch: [16] [1300/1319] eta: 0:01:00 lr: 3.040205284985739e-05 loss: 0.0541 (0.0588) time: 3.2087 data: 0.0089 max mem: 33369 +Epoch: [16] [1310/1319] eta: 0:00:28 lr: 3.039303875059306e-05 loss: 0.0592 (0.0589) time: 3.1985 data: 0.0085 max mem: 33369 +Epoch: [16] Total time: 1:09:57 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 2:49:54 time: 3.9623 data: 3.8257 max mem: 33369 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 100/2573] eta: 0:04:50 time: 0.0784 data: 0.0015 max mem: 33369 +Test: [ 200/2573] eta: 0:03:54 time: 0.0798 data: 0.0015 max mem: 33369 +Test: [ 300/2573] eta: 0:03:28 time: 0.0804 data: 0.0015 max mem: 33369 +Test: [ 400/2573] eta: 0:03:12 time: 0.0821 data: 0.0016 max mem: 33369 +Test: [ 500/2573] eta: 0:03:00 time: 0.0809 data: 0.0017 max mem: 33369 +Test: [ 600/2573] eta: 0:02:49 time: 0.0805 data: 0.0015 max mem: 33369 +Test: [ 700/2573] eta: 0:02:40 time: 0.0795 data: 0.0015 max mem: 33369 +Test: [ 800/2573] eta: 0:02:30 time: 0.0847 data: 0.0020 max mem: 33369 +Test: [ 900/2573] eta: 0:02:21 time: 0.0800 data: 0.0015 max mem: 33369 +Test: [1000/2573] eta: 0:02:12 time: 0.0796 data: 0.0015 max mem: 33369 +Test: [1100/2573] eta: 0:02:03 time: 0.0811 data: 0.0017 max mem: 33369 +Test: [1200/2573] eta: 0:01:54 time: 0.0813 data: 0.0014 max mem: 33369 +Test: [1300/2573] eta: 0:01:46 time: 0.0823 data: 0.0016 max mem: 33369 +Test: [1400/2573] eta: 0:01:37 time: 0.0810 data: 0.0015 max mem: 33369 +Test: [1500/2573] eta: 0:01:29 time: 0.0844 data: 0.0018 max mem: 33369 +Test: [1600/2573] eta: 0:01:21 time: 0.0886 data: 0.0019 max mem: 33369 +Test: [1700/2573] eta: 0:01:12 time: 0.0790 data: 0.0018 max mem: 33369 +Test: [1800/2573] eta: 0:01:04 time: 0.0833 data: 0.0015 max mem: 33369 +Test: [1900/2573] eta: 0:00:55 time: 0.0828 data: 0.0017 max mem: 33369 +Test: [2000/2573] eta: 0:00:47 time: 0.0809 data: 0.0015 max mem: 33369 +Test: [2100/2573] eta: 0:00:39 time: 0.0839 data: 0.0016 max mem: 33369 +Test: [2200/2573] eta: 0:00:30 time: 0.0841 data: 0.0015 max mem: 33369 +Test: [2300/2573] eta: 0:00:22 time: 0.0813 data: 0.0017 max mem: 33369 +Test: [2400/2573] eta: 0:00:14 time: 0.0792 data: 0.0017 max mem: 33369 +Test: [2500/2573] eta: 0:00:06 time: 0.0819 data: 0.0016 max mem: 33369 +Test: Total time: 0:03:33 +Final results: +Mean IoU is 62.39 + + precision@0.5 = 70.06 + precision@0.6 = 64.38 + precision@0.7 = 56.60 + precision@0.8 = 45.02 + precision@0.9 = 21.30 + overall IoU = 61.32 + +Average object IoU 62.39378555349716 +Overall IoU 61.32426452636719 +Better epoch: 16 + +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [17] [ 0/1319] eta: 2:07:48 lr: 3.0384925807273e-05 loss: 0.0411 (0.0411) time: 5.8140 data: 2.1366 max mem: 33369 +Epoch: [17] [ 10/1319] eta: 1:16:42 lr: 3.0375911143504937e-05 loss: 0.0523 (0.0702) time: 3.5158 data: 0.2049 max mem: 33369 +Epoch: [17] [ 20/1319] eta: 1:13:32 lr: 3.0366896182473385e-05 loss: 0.0534 (0.0614) time: 3.2760 data: 0.0107 max mem: 33369 +Epoch: [17] [ 30/1319] eta: 1:11:20 lr: 3.035788092407048e-05 loss: 0.0534 (0.0574) time: 3.2139 data: 0.0102 max mem: 33369 +Epoch: [17] [ 40/1319] eta: 1:10:13 lr: 3.034886536818829e-05 loss: 0.0462 (0.0576) time: 3.1866 data: 0.0096 max mem: 33369 +Epoch: [17] [ 50/1319] eta: 1:09:29 lr: 3.0339849514718806e-05 loss: 0.0465 (0.0571) time: 3.2308 data: 0.0082 max mem: 33369 +Epoch: [17] [ 60/1319] eta: 1:08:42 lr: 3.033083336355392e-05 loss: 0.0457 (0.0557) time: 3.2338 data: 0.0086 max mem: 33369 +Epoch: [17] [ 70/1319] eta: 1:08:17 lr: 3.03218169145855e-05 loss: 0.0434 (0.0543) time: 3.2674 data: 0.0097 max mem: 33369 +Epoch: [17] [ 80/1319] eta: 1:07:34 lr: 3.0312800167705292e-05 loss: 0.0431 (0.0545) time: 3.2673 data: 0.0108 max mem: 33369 +Epoch: [17] [ 90/1319] eta: 1:07:17 lr: 3.030378312280498e-05 loss: 0.0441 (0.0537) time: 3.3004 data: 0.0110 max mem: 33369 +Epoch: [17] [ 100/1319] eta: 1:06:44 lr: 3.0294765779776184e-05 loss: 0.0514 (0.0540) time: 3.3352 data: 0.0106 max mem: 33369 +Epoch: [17] [ 110/1319] eta: 1:06:05 lr: 3.0285748138510444e-05 loss: 0.0514 (0.0543) time: 3.2564 data: 0.0101 max mem: 33369 +Epoch: [17] [ 120/1319] eta: 1:05:26 lr: 3.0276730198899216e-05 loss: 0.0441 (0.0533) time: 3.2254 data: 0.0094 max mem: 33369 +Epoch: [17] [ 130/1319] eta: 1:04:53 lr: 3.0267711960833896e-05 loss: 0.0438 (0.0545) time: 3.2486 data: 0.0106 max mem: 33369 +Epoch: [17] [ 140/1319] eta: 1:04:17 lr: 3.0258693424205785e-05 loss: 0.0535 (0.0548) time: 3.2529 data: 0.0113 max mem: 33369 +Epoch: [17] [ 150/1319] eta: 1:03:42 lr: 3.024967458890613e-05 loss: 0.0485 (0.0544) time: 3.2343 data: 0.0098 max mem: 33369 +Epoch: [17] [ 160/1319] eta: 1:03:04 lr: 3.0240655454826085e-05 loss: 0.0484 (0.0547) time: 3.2201 data: 0.0099 max mem: 33369 +Epoch: [17] [ 170/1319] eta: 1:02:27 lr: 3.023163602185673e-05 loss: 0.0524 (0.0548) time: 3.2019 data: 0.0098 max mem: 33369 +Epoch: [17] [ 180/1319] eta: 1:01:49 lr: 3.022261628988908e-05 loss: 0.0542 (0.0552) time: 3.1885 data: 0.0093 max mem: 33369 +Epoch: [17] [ 190/1319] eta: 1:01:15 lr: 3.0213596258814065e-05 loss: 0.0528 (0.0555) time: 3.2010 data: 0.0098 max mem: 33369 +Epoch: [17] [ 200/1319] eta: 1:00:38 lr: 3.020457592852254e-05 loss: 0.0498 (0.0554) time: 3.2017 data: 0.0099 max mem: 33369 +Epoch: [17] [ 210/1319] eta: 1:00:02 lr: 3.0195555298905282e-05 loss: 0.0440 (0.0551) time: 3.1787 data: 0.0099 max mem: 33369 +Epoch: [17] [ 220/1319] eta: 0:59:24 lr: 3.0186534369853002e-05 loss: 0.0442 (0.0549) time: 3.1664 data: 0.0099 max mem: 33369 +Epoch: [17] [ 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33369 +Epoch: [17] [ 310/1319] eta: 0:54:09 lr: 3.010533251573493e-05 loss: 0.0516 (0.0554) time: 3.1451 data: 0.0105 max mem: 33369 +Epoch: [17] [ 320/1319] eta: 0:53:36 lr: 3.0096308586304355e-05 loss: 0.0556 (0.0556) time: 3.1699 data: 0.0102 max mem: 33369 +Epoch: [17] [ 330/1319] eta: 0:53:03 lr: 3.0087284356231465e-05 loss: 0.0478 (0.0555) time: 3.1922 data: 0.0099 max mem: 33369 +Epoch: [17] [ 340/1319] eta: 0:52:30 lr: 3.0078259825406035e-05 loss: 0.0441 (0.0551) time: 3.2013 data: 0.0094 max mem: 33369 +Epoch: [17] [ 350/1319] eta: 0:51:58 lr: 3.0069234993717783e-05 loss: 0.0446 (0.0551) time: 3.2122 data: 0.0093 max mem: 33369 +Epoch: [17] [ 360/1319] eta: 0:51:25 lr: 3.006020986105632e-05 loss: 0.0459 (0.0549) time: 3.1982 data: 0.0099 max mem: 33369 +Epoch: [17] [ 370/1319] eta: 0:50:52 lr: 3.005118442731122e-05 loss: 0.0468 (0.0551) time: 3.1782 data: 0.0095 max mem: 33369 +Epoch: [17] [ 380/1319] eta: 0:50:19 lr: 3.004215869237195e-05 loss: 0.0492 (0.0550) time: 3.1870 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eta: 0:37:15 lr: 2.9825450406848343e-05 loss: 0.0510 (0.0561) time: 3.1779 data: 0.0093 max mem: 33369 +Epoch: [17] [ 630/1319] eta: 0:36:43 lr: 2.981641710590631e-05 loss: 0.0632 (0.0562) time: 3.1542 data: 0.0097 max mem: 33369 +Epoch: [17] [ 640/1319] eta: 0:36:10 lr: 2.9807383500869036e-05 loss: 0.0643 (0.0564) time: 3.1503 data: 0.0103 max mem: 33369 +Epoch: [17] [ 650/1319] eta: 0:35:38 lr: 2.9798349591623877e-05 loss: 0.0610 (0.0564) time: 3.1487 data: 0.0112 max mem: 33369 +Epoch: [17] [ 660/1319] eta: 0:35:06 lr: 2.9789315378058107e-05 loss: 0.0564 (0.0567) time: 3.1768 data: 0.0109 max mem: 33369 +Epoch: [17] [ 670/1319] eta: 0:34:33 lr: 2.978028086005893e-05 loss: 0.0564 (0.0569) time: 3.1796 data: 0.0100 max mem: 33369 +Epoch: [17] [ 680/1319] eta: 0:34:02 lr: 2.977124603751345e-05 loss: 0.0516 (0.0568) time: 3.1920 data: 0.0099 max mem: 33369 +Epoch: [17] [ 690/1319] eta: 0:33:30 lr: 2.9762210910308712e-05 loss: 0.0516 (0.0569) time: 3.2067 data: 0.0102 max mem: 33369 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time: 3.1687 data: 0.0102 max mem: 33369 +Epoch: [17] [ 860/1319] eta: 0:24:24 lr: 2.96085670251099e-05 loss: 0.0512 (0.0568) time: 3.1575 data: 0.0101 max mem: 33369 +Epoch: [17] [ 870/1319] eta: 0:23:52 lr: 2.959952639462995e-05 loss: 0.0586 (0.0569) time: 3.1750 data: 0.0099 max mem: 33369 +Epoch: [17] [ 880/1319] eta: 0:23:20 lr: 2.9590485457329127e-05 loss: 0.0586 (0.0570) time: 3.1925 data: 0.0098 max mem: 33369 +Epoch: [17] [ 890/1319] eta: 0:22:48 lr: 2.9581444213092834e-05 loss: 0.0438 (0.0568) time: 3.1743 data: 0.0096 max mem: 33369 +Epoch: [17] [ 900/1319] eta: 0:22:16 lr: 2.957240266180642e-05 loss: 0.0556 (0.0571) time: 3.1472 data: 0.0097 max mem: 33369 +Epoch: [17] [ 910/1319] eta: 0:21:44 lr: 2.956336080335514e-05 loss: 0.0595 (0.0570) time: 3.1780 data: 0.0091 max mem: 33369 +Epoch: [17] [ 920/1319] eta: 0:21:12 lr: 2.955431863762416e-05 loss: 0.0578 (0.0571) time: 3.1709 data: 0.0089 max mem: 33369 +Epoch: [17] [ 930/1319] eta: 0:20:40 lr: 2.9545276164498587e-05 loss: 0.0494 (0.0571) time: 3.1652 data: 0.0092 max mem: 33369 +Epoch: [17] [ 940/1319] eta: 0:20:08 lr: 2.953623338386342e-05 loss: 0.0494 (0.0571) time: 3.1742 data: 0.0094 max mem: 33369 +Epoch: [17] [ 950/1319] eta: 0:19:36 lr: 2.9527190295603586e-05 loss: 0.0500 (0.0570) time: 3.1567 data: 0.0093 max mem: 33369 +Epoch: [17] [ 960/1319] eta: 0:19:04 lr: 2.9518146899603932e-05 loss: 0.0459 (0.0570) time: 3.1737 data: 0.0090 max mem: 33369 +Epoch: [17] [ 970/1319] eta: 0:18:32 lr: 2.9509103195749226e-05 loss: 0.0463 (0.0569) time: 3.1688 data: 0.0092 max mem: 33369 +Epoch: [17] [ 980/1319] eta: 0:18:00 lr: 2.9500059183924145e-05 loss: 0.0485 (0.0569) time: 3.1560 data: 0.0094 max mem: 33369 +Epoch: [17] [ 990/1319] eta: 0:17:28 lr: 2.9491014864013282e-05 loss: 0.0467 (0.0569) time: 3.1680 data: 0.0094 max mem: 33369 +Epoch: [17] [1000/1319] eta: 0:16:56 lr: 2.9481970235901164e-05 loss: 0.0475 (0.0568) time: 3.2087 data: 0.0095 max mem: 33369 +Epoch: [17] [1010/1319] eta: 0:16:24 lr: 2.9472925299472214e-05 loss: 0.0500 (0.0568) time: 3.1903 data: 0.0096 max mem: 33369 +Epoch: [17] [1020/1319] eta: 0:15:52 lr: 2.9463880054610792e-05 loss: 0.0487 (0.0568) time: 3.1602 data: 0.0094 max mem: 33369 +Epoch: [17] [1030/1319] eta: 0:15:21 lr: 2.9454834501201163e-05 loss: 0.0534 (0.0568) time: 3.2057 data: 0.0097 max mem: 33369 +Epoch: [17] [1040/1319] eta: 0:14:49 lr: 2.9445788639127496e-05 loss: 0.0553 (0.0568) time: 3.2261 data: 0.0097 max mem: 33369 +Epoch: [17] [1050/1319] eta: 0:14:17 lr: 2.943674246827392e-05 loss: 0.0553 (0.0568) time: 3.2235 data: 0.0098 max mem: 33369 +Epoch: [17] [1060/1319] eta: 0:13:45 lr: 2.9427695988524433e-05 loss: 0.0501 (0.0567) time: 3.1738 data: 0.0099 max mem: 33369 +Epoch: [17] [1070/1319] eta: 0:13:13 lr: 2.941864919976297e-05 loss: 0.0438 (0.0567) time: 3.1501 data: 0.0091 max mem: 33369 +Epoch: [17] [1080/1319] eta: 0:12:41 lr: 2.9409602101873397e-05 loss: 0.0604 (0.0569) time: 3.1761 data: 0.0088 max mem: 33369 +Epoch: [17] 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33369 +Epoch: [17] [1170/1319] eta: 0:07:54 lr: 2.9328164290896108e-05 loss: 0.0453 (0.0570) time: 3.1606 data: 0.0094 max mem: 33369 +Epoch: [17] [1180/1319] eta: 0:07:22 lr: 2.9319114095318817e-05 loss: 0.0465 (0.0569) time: 3.1551 data: 0.0102 max mem: 33369 +Epoch: [17] [1190/1319] eta: 0:06:50 lr: 2.9310063589330256e-05 loss: 0.0499 (0.0569) time: 3.1551 data: 0.0097 max mem: 33369 +Epoch: [17] [1200/1319] eta: 0:06:18 lr: 2.9301012772813273e-05 loss: 0.0527 (0.0569) time: 3.1627 data: 0.0095 max mem: 33369 +Epoch: [17] [1210/1319] eta: 0:05:47 lr: 2.9291961645650624e-05 loss: 0.0566 (0.0570) time: 3.1818 data: 0.0100 max mem: 33369 +Epoch: [17] [1220/1319] eta: 0:05:15 lr: 2.9282910207724996e-05 loss: 0.0566 (0.0570) time: 3.1722 data: 0.0098 max mem: 33369 +Epoch: [17] [1230/1319] eta: 0:04:43 lr: 2.9273858458918974e-05 loss: 0.0544 (0.0570) time: 3.1694 data: 0.0096 max mem: 33369 +Epoch: [17] [1240/1319] eta: 0:04:11 lr: 2.9264806399115058e-05 loss: 0.0484 (0.0569) time: 3.1803 data: 0.0094 max mem: 33369 +Epoch: [17] [1250/1319] eta: 0:03:39 lr: 2.925575402819568e-05 loss: 0.0451 (0.0568) time: 3.1905 data: 0.0094 max mem: 33369 +Epoch: [17] [1260/1319] eta: 0:03:07 lr: 2.9246701346043183e-05 loss: 0.0452 (0.0568) time: 3.1817 data: 0.0092 max mem: 33369 +Epoch: [17] [1270/1319] eta: 0:02:36 lr: 2.9237648352539803e-05 loss: 0.0493 (0.0568) time: 3.1873 data: 0.0088 max mem: 33369 +Epoch: [17] [1280/1319] eta: 0:02:04 lr: 2.9228595047567713e-05 loss: 0.0650 (0.0569) time: 3.2107 data: 0.0092 max mem: 33369 +Epoch: [17] [1290/1319] eta: 0:01:32 lr: 2.9219541431009008e-05 loss: 0.0566 (0.0569) time: 3.1986 data: 0.0100 max mem: 33369 +Epoch: [17] [1300/1319] eta: 0:01:00 lr: 2.921048750274567e-05 loss: 0.0533 (0.0569) time: 3.1913 data: 0.0092 max mem: 33369 +Epoch: [17] [1310/1319] eta: 0:00:28 lr: 2.9201433262659623e-05 loss: 0.0565 (0.0569) time: 3.1715 data: 0.0085 max mem: 33369 +Epoch: [17] Total time: 1:10:00 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 2:58:42 time: 4.1674 data: 4.0634 max mem: 33369 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 100/2573] eta: 0:04:52 time: 0.0774 data: 0.0015 max mem: 33369 +Test: [ 200/2573] eta: 0:03:54 time: 0.0790 data: 0.0016 max mem: 33369 +Test: [ 300/2573] eta: 0:03:29 time: 0.0816 data: 0.0014 max mem: 33369 +Test: [ 400/2573] eta: 0:03:13 time: 0.0817 data: 0.0016 max mem: 33369 +Test: [ 500/2573] eta: 0:03:00 time: 0.0792 data: 0.0015 max mem: 33369 +Test: [ 600/2573] eta: 0:02:49 time: 0.0811 data: 0.0017 max mem: 33369 +Test: [ 700/2573] eta: 0:02:39 time: 0.0793 data: 0.0015 max mem: 33369 +Test: [ 800/2573] eta: 0:02:30 time: 0.0830 data: 0.0016 max mem: 33369 +Test: [ 900/2573] eta: 0:02:21 time: 0.0794 data: 0.0015 max mem: 33369 +Test: [1000/2573] eta: 0:02:12 time: 0.0807 data: 0.0016 max mem: 33369 +Test: [1100/2573] eta: 0:02:03 time: 0.0792 data: 0.0014 max mem: 33369 +Test: [1200/2573] eta: 0:01:54 time: 0.0804 data: 0.0016 max mem: 33369 +Test: [1300/2573] eta: 0:01:46 time: 0.0804 data: 0.0014 max mem: 33369 +Test: [1400/2573] eta: 0:01:37 time: 0.0788 data: 0.0015 max mem: 33369 +Test: [1500/2573] eta: 0:01:29 time: 0.0811 data: 0.0014 max mem: 33369 +Test: [1600/2573] eta: 0:01:20 time: 0.0840 data: 0.0016 max mem: 33369 +Test: [1700/2573] eta: 0:01:12 time: 0.0789 data: 0.0015 max mem: 33369 +Test: [1800/2573] eta: 0:01:03 time: 0.0821 data: 0.0014 max mem: 33369 +Test: [1900/2573] eta: 0:00:55 time: 0.0792 data: 0.0015 max mem: 33369 +Test: [2000/2573] eta: 0:00:47 time: 0.0800 data: 0.0014 max mem: 33369 +Test: [2100/2573] eta: 0:00:38 time: 0.0825 data: 0.0019 max mem: 33369 +Test: [2200/2573] eta: 0:00:30 time: 0.0825 data: 0.0014 max mem: 33369 +Test: [2300/2573] eta: 0:00:22 time: 0.0825 data: 0.0016 max mem: 33369 +Test: [2400/2573] eta: 0:00:14 time: 0.0784 data: 0.0015 max mem: 33369 +Test: [2500/2573] eta: 0:00:05 time: 0.0808 data: 0.0014 max mem: 33369 +Test: Total time: 0:03:31 +Final results: +Mean IoU is 62.15 + + precision@0.5 = 70.20 + precision@0.6 = 64.69 + precision@0.7 = 56.33 + precision@0.8 = 43.85 + precision@0.9 = 21.06 + overall IoU = 60.89 + +Average object IoU 62.154193151298585 +Overall IoU 60.88709259033203 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [18] [ 0/1319] eta: 4:09:43 lr: 2.9193284179876086e-05 loss: 0.0400 (0.0400) time: 11.3596 data: 2.9783 max mem: 33369 +Epoch: [18] [ 10/1319] eta: 1:26:30 lr: 2.9184229347001237e-05 loss: 0.0419 (0.0461) time: 3.9656 data: 0.2786 max mem: 33369 +Epoch: [18] [ 20/1319] eta: 1:17:56 lr: 2.9175174201960736e-05 loss: 0.0480 (0.0491) time: 3.2123 data: 0.0085 max mem: 33369 +Epoch: [18] [ 30/1319] eta: 1:14:30 lr: 2.9166118744636155e-05 loss: 0.0495 (0.0565) time: 3.1946 data: 0.0089 max mem: 33369 +Epoch: [18] [ 40/1319] eta: 1:12:27 lr: 2.9157062974908988e-05 loss: 0.0439 (0.0529) time: 3.1887 data: 0.0102 max mem: 33369 +Epoch: [18] [ 50/1319] eta: 1:11:01 lr: 2.9148006892660646e-05 loss: 0.0427 (0.0533) time: 3.1866 data: 0.0109 max mem: 33369 +Epoch: [18] [ 60/1319] eta: 1:09:54 lr: 2.9138950497772444e-05 loss: 0.0427 (0.0519) time: 3.1918 data: 0.0101 max mem: 33369 +Epoch: [18] [ 70/1319] eta: 1:08:58 lr: 2.9129893790125616e-05 loss: 0.0421 (0.0511) time: 3.1997 data: 0.0093 max mem: 33369 +Epoch: [18] [ 80/1319] eta: 1:08:06 lr: 2.9120836769601318e-05 loss: 0.0460 (0.0508) time: 3.1959 data: 0.0100 max mem: 33369 +Epoch: [18] [ 90/1319] eta: 1:07:25 lr: 2.9111779436080605e-05 loss: 0.0524 (0.0523) time: 3.2170 data: 0.0104 max mem: 33369 +Epoch: [18] [ 100/1319] eta: 1:06:39 lr: 2.910272178944446e-05 loss: 0.0524 (0.0518) time: 3.2106 data: 0.0101 max mem: 33369 +Epoch: [18] [ 110/1319] eta: 1:05:53 lr: 2.9093663829573763e-05 loss: 0.0444 (0.0520) time: 3.1699 data: 0.0101 max mem: 33369 +Epoch: [18] [ 120/1319] eta: 1:05:10 lr: 2.9084605556349322e-05 loss: 0.0451 (0.0518) time: 3.1661 data: 0.0103 max mem: 33369 +Epoch: [18] [ 130/1319] eta: 1:04:35 lr: 2.9075546969651845e-05 loss: 0.0467 (0.0518) time: 3.2001 data: 0.0103 max mem: 33369 +Epoch: [18] [ 140/1319] eta: 1:03:58 lr: 2.906648806936197e-05 loss: 0.0489 (0.0525) time: 3.2175 data: 0.0093 max mem: 33369 +Epoch: [18] [ 150/1319] eta: 1:03:22 lr: 2.9057428855360237e-05 loss: 0.0546 (0.0526) time: 3.2065 data: 0.0089 max mem: 33369 +Epoch: [18] [ 160/1319] eta: 1:02:42 lr: 2.9048369327527098e-05 loss: 0.0482 (0.0522) time: 3.1830 data: 0.0102 max mem: 33369 +Epoch: [18] [ 170/1319] eta: 1:02:06 lr: 2.903930948574293e-05 loss: 0.0409 (0.0519) time: 3.1740 data: 0.0106 max mem: 33369 +Epoch: [18] [ 180/1319] eta: 1:01:28 lr: 2.9030249329888e-05 loss: 0.0487 (0.0522) time: 3.1711 data: 0.0103 max mem: 33369 +Epoch: [18] [ 190/1319] eta: 1:00:53 lr: 2.9021188859842518e-05 loss: 0.0472 (0.0521) time: 3.1746 data: 0.0096 max mem: 33369 +Epoch: [18] [ 200/1319] eta: 1:00:17 lr: 2.9012128075486583e-05 loss: 0.0462 (0.0519) time: 3.1861 data: 0.0089 max mem: 33369 +Epoch: [18] [ 210/1319] eta: 0:59:41 lr: 2.900306697670022e-05 loss: 0.0477 (0.0518) time: 3.1644 data: 0.0096 max mem: 33369 +Epoch: [18] [ 220/1319] eta: 0:59:05 lr: 2.8994005563363352e-05 loss: 0.0493 (0.0523) time: 3.1605 data: 0.0096 max mem: 33369 +Epoch: [18] [ 230/1319] eta: 0:58:31 lr: 2.8984943835355838e-05 loss: 0.0508 (0.0525) time: 3.1706 data: 0.0093 max mem: 33369 +Epoch: [18] [ 240/1319] eta: 0:57:55 lr: 2.8975881792557412e-05 loss: 0.0505 (0.0525) time: 3.1639 data: 0.0094 max mem: 33369 +Epoch: [18] [ 250/1319] eta: 0:57:20 lr: 2.8966819434847762e-05 loss: 0.0477 (0.0526) time: 3.1481 data: 0.0099 max mem: 33369 +Epoch: [18] [ 260/1319] eta: 0:56:46 lr: 2.8957756762106468e-05 loss: 0.0478 (0.0527) time: 3.1654 data: 0.0099 max mem: 33369 +Epoch: [18] [ 270/1319] eta: 0:56:14 lr: 2.8948693774213014e-05 loss: 0.0472 (0.0529) time: 3.1974 data: 0.0097 max mem: 33369 +Epoch: [18] [ 280/1319] eta: 0:55:40 lr: 2.8939630471046815e-05 loss: 0.0472 (0.0533) time: 3.1854 data: 0.0096 max mem: 33369 +Epoch: [18] [ 290/1319] eta: 0:55:04 lr: 2.893056685248718e-05 loss: 0.0572 (0.0538) time: 3.1418 data: 0.0095 max mem: 33369 +Epoch: [18] [ 300/1319] eta: 0:54:32 lr: 2.892150291841334e-05 loss: 0.0475 (0.0537) time: 3.1652 data: 0.0098 max mem: 33369 +Epoch: [18] [ 310/1319] eta: 0:53:59 lr: 2.891243866870445e-05 loss: 0.0475 (0.0538) time: 3.2062 data: 0.0101 max mem: 33369 +Epoch: [18] [ 320/1319] eta: 0:53:26 lr: 2.8903374103239537e-05 loss: 0.0543 (0.0539) time: 3.1832 data: 0.0099 max mem: 33369 +Epoch: [18] [ 330/1319] eta: 0:52:53 lr: 2.889430922189758e-05 loss: 0.0502 (0.0539) time: 3.1683 data: 0.0096 max mem: 33369 +Epoch: [18] [ 340/1319] eta: 0:52:21 lr: 2.8885244024557463e-05 loss: 0.0459 (0.0538) time: 3.2004 data: 0.0092 max mem: 33369 +Epoch: [18] [ 350/1319] eta: 0:51:47 lr: 2.8876178511097952e-05 loss: 0.0473 (0.0540) time: 3.1862 data: 0.0095 max mem: 33369 +Epoch: [18] [ 360/1319] eta: 0:51:15 lr: 2.886711268139775e-05 loss: 0.0483 (0.0539) time: 3.1660 data: 0.0097 max mem: 33369 +Epoch: [18] [ 370/1319] eta: 0:50:43 lr: 2.8858046535335475e-05 loss: 0.0483 (0.0539) time: 3.1971 data: 0.0091 max mem: 33369 +Epoch: [18] [ 380/1319] eta: 0:50:10 lr: 2.8848980072789644e-05 loss: 0.0522 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data: 0.0096 max mem: 33369 +Epoch: [18] [ 700/1319] eta: 0:32:56 lr: 2.8558685436370514e-05 loss: 0.0386 (0.0532) time: 3.1597 data: 0.0095 max mem: 33369 +Epoch: [18] [ 710/1319] eta: 0:32:24 lr: 2.854960846112869e-05 loss: 0.0429 (0.0531) time: 3.1919 data: 0.0098 max mem: 33369 +Epoch: [18] [ 720/1319] eta: 0:31:52 lr: 2.8540531165219343e-05 loss: 0.0440 (0.0531) time: 3.2102 data: 0.0095 max mem: 33369 +Epoch: [18] [ 730/1319] eta: 0:31:20 lr: 2.8531453548517806e-05 loss: 0.0459 (0.0530) time: 3.2082 data: 0.0101 max mem: 33369 +Epoch: [18] [ 740/1319] eta: 0:30:48 lr: 2.8522375610899337e-05 loss: 0.0520 (0.0531) time: 3.1887 data: 0.0105 max mem: 33369 +Epoch: [18] [ 750/1319] eta: 0:30:16 lr: 2.8513297352239087e-05 loss: 0.0523 (0.0531) time: 3.1660 data: 0.0104 max mem: 33369 +Epoch: [18] [ 760/1319] eta: 0:29:44 lr: 2.850421877241213e-05 loss: 0.0483 (0.0531) time: 3.1568 data: 0.0110 max mem: 33369 +Epoch: [18] [ 770/1319] eta: 0:29:12 lr: 2.8495139871293436e-05 loss: 0.0499 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2.8422497080807237e-05 loss: 0.0471 (0.0533) time: 3.1962 data: 0.0097 max mem: 33369 +Epoch: [18] [ 860/1319] eta: 0:24:24 lr: 2.8413415282421285e-05 loss: 0.0484 (0.0533) time: 3.1895 data: 0.0090 max mem: 33369 +Epoch: [18] [ 870/1319] eta: 0:23:53 lr: 2.840433316148819e-05 loss: 0.0480 (0.0534) time: 3.2004 data: 0.0087 max mem: 33369 +Epoch: [18] [ 880/1319] eta: 0:23:21 lr: 2.8395250717881906e-05 loss: 0.0443 (0.0534) time: 3.2268 data: 0.0092 max mem: 33369 +Epoch: [18] [ 890/1319] eta: 0:22:49 lr: 2.8386167951476273e-05 loss: 0.0446 (0.0534) time: 3.2034 data: 0.0099 max mem: 33369 +Epoch: [18] [ 900/1319] eta: 0:22:17 lr: 2.8377084862145048e-05 loss: 0.0482 (0.0534) time: 3.1795 data: 0.0095 max mem: 33369 +Epoch: [18] [ 910/1319] eta: 0:21:45 lr: 2.8368001449761894e-05 loss: 0.0535 (0.0535) time: 3.1726 data: 0.0088 max mem: 33369 +Epoch: [18] [ 920/1319] eta: 0:21:13 lr: 2.8358917714200377e-05 loss: 0.0530 (0.0535) time: 3.1717 data: 0.0084 max mem: 33369 +Epoch: [18] [ 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data: 0.0090 max mem: 33369 +Epoch: [18] [1090/1319] eta: 0:12:10 lr: 2.820444464039311e-05 loss: 0.0480 (0.0536) time: 3.1841 data: 0.0091 max mem: 33369 +Epoch: [18] [1100/1319] eta: 0:11:38 lr: 2.819535506589294e-05 loss: 0.0480 (0.0536) time: 3.1656 data: 0.0095 max mem: 33369 +Epoch: [18] [1110/1319] eta: 0:11:06 lr: 2.8186265165794125e-05 loss: 0.0509 (0.0536) time: 3.1825 data: 0.0089 max mem: 33369 +Epoch: [18] [1120/1319] eta: 0:10:34 lr: 2.817717493996831e-05 loss: 0.0582 (0.0537) time: 3.2255 data: 0.0090 max mem: 33369 +Epoch: [18] [1130/1319] eta: 0:10:02 lr: 2.816808438828707e-05 loss: 0.0539 (0.0537) time: 3.2149 data: 0.0096 max mem: 33369 +Epoch: [18] [1140/1319] eta: 0:09:30 lr: 2.8158993510621856e-05 loss: 0.0445 (0.0536) time: 3.1825 data: 0.0101 max mem: 33369 +Epoch: [18] [1150/1319] eta: 0:08:59 lr: 2.814990230684405e-05 loss: 0.0445 (0.0536) time: 3.1874 data: 0.0103 max mem: 33369 +Epoch: [18] [1160/1319] eta: 0:08:27 lr: 2.814081077682491e-05 loss: 0.0496 (0.0537) time: 3.1973 data: 0.0100 max mem: 33369 +Epoch: [18] [1170/1319] eta: 0:07:55 lr: 2.8131718920435623e-05 loss: 0.0473 (0.0538) time: 3.1528 data: 0.0096 max mem: 33369 +Epoch: [18] [1180/1319] eta: 0:07:23 lr: 2.812262673754726e-05 loss: 0.0551 (0.0539) time: 3.1385 data: 0.0099 max mem: 33369 +Epoch: [18] [1190/1319] eta: 0:06:51 lr: 2.8113534228030784e-05 loss: 0.0538 (0.0539) time: 3.1369 data: 0.0098 max mem: 33369 +Epoch: [18] [1200/1319] eta: 0:06:19 lr: 2.8104441391757102e-05 loss: 0.0460 (0.0539) time: 3.1677 data: 0.0098 max mem: 33369 +Epoch: [18] [1210/1319] eta: 0:05:47 lr: 2.809534822859698e-05 loss: 0.0449 (0.0538) time: 3.2114 data: 0.0100 max mem: 33369 +Epoch: [18] [1220/1319] eta: 0:05:15 lr: 2.8086254738421114e-05 loss: 0.0457 (0.0539) time: 3.2156 data: 0.0093 max mem: 33369 +Epoch: [18] [1230/1319] eta: 0:04:43 lr: 2.8077160921100087e-05 loss: 0.0512 (0.0539) time: 3.1810 data: 0.0088 max mem: 33369 +Epoch: [18] [1240/1319] eta: 0:04:11 lr: 2.8068066776504393e-05 loss: 0.0471 (0.0540) time: 3.1719 data: 0.0093 max mem: 33369 +Epoch: [18] [1250/1319] eta: 0:03:39 lr: 2.8058972304504428e-05 loss: 0.0540 (0.0541) time: 3.1843 data: 0.0096 max mem: 33369 +Epoch: [18] [1260/1319] eta: 0:03:08 lr: 2.8049877504970483e-05 loss: 0.0511 (0.0540) time: 3.1699 data: 0.0099 max mem: 33369 +Epoch: [18] [1270/1319] eta: 0:02:36 lr: 2.8040782377772763e-05 loss: 0.0417 (0.0539) time: 3.1795 data: 0.0095 max mem: 33369 +Epoch: [18] [1280/1319] eta: 0:02:04 lr: 2.803168692278136e-05 loss: 0.0422 (0.0539) time: 3.1845 data: 0.0085 max mem: 33369 +Epoch: [18] [1290/1319] eta: 0:01:32 lr: 2.8022591139866265e-05 loss: 0.0487 (0.0539) time: 3.1748 data: 0.0094 max mem: 33369 +Epoch: [18] [1300/1319] eta: 0:01:00 lr: 2.80134950288974e-05 loss: 0.0425 (0.0538) time: 3.1720 data: 0.0106 max mem: 33369 +Epoch: [18] [1310/1319] eta: 0:00:28 lr: 2.800439858974456e-05 loss: 0.0469 (0.0539) time: 3.1963 data: 0.0092 max mem: 33369 +Epoch: [18] Total time: 1:10:06 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 2:45:22 time: 3.8563 data: 3.5955 max mem: 33369 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 100/2573] eta: 0:04:54 time: 0.0798 data: 0.0017 max mem: 33369 +Test: [ 200/2573] eta: 0:03:58 time: 0.0801 data: 0.0016 max mem: 33369 +Test: [ 300/2573] eta: 0:03:32 time: 0.0842 data: 0.0018 max mem: 33369 +Test: [ 400/2573] eta: 0:03:16 time: 0.0817 data: 0.0015 max mem: 33369 +Test: [ 500/2573] eta: 0:03:03 time: 0.0824 data: 0.0019 max mem: 33369 +Test: [ 600/2573] eta: 0:02:52 time: 0.0820 data: 0.0018 max mem: 33369 +Test: [ 700/2573] eta: 0:02:43 time: 0.0810 data: 0.0017 max mem: 33369 +Test: [ 800/2573] eta: 0:02:33 time: 0.0881 data: 0.0017 max mem: 33369 +Test: [ 900/2573] eta: 0:02:24 time: 0.0814 data: 0.0015 max mem: 33369 +Test: [1000/2573] eta: 0:02:15 time: 0.0847 data: 0.0019 max mem: 33369 +Test: [1100/2573] eta: 0:02:06 time: 0.0809 data: 0.0016 max mem: 33369 +Test: [1200/2573] eta: 0:01:57 time: 0.0813 data: 0.0016 max mem: 33369 +Test: [1300/2573] eta: 0:01:48 time: 0.0807 data: 0.0016 max mem: 33369 +Test: [1400/2573] eta: 0:01:39 time: 0.0819 data: 0.0017 max mem: 33369 +Test: [1500/2573] eta: 0:01:31 time: 0.0858 data: 0.0020 max mem: 33369 +Test: [1600/2573] eta: 0:01:22 time: 0.0859 data: 0.0019 max mem: 33369 +Test: [1700/2573] eta: 0:01:13 time: 0.0844 data: 0.0019 max mem: 33369 +Test: [1800/2573] eta: 0:01:05 time: 0.0855 data: 0.0020 max mem: 33369 +Test: [1900/2573] eta: 0:00:56 time: 0.0805 data: 0.0016 max mem: 33369 +Test: [2000/2573] eta: 0:00:48 time: 0.0818 data: 0.0015 max mem: 33369 +Test: [2100/2573] eta: 0:00:39 time: 0.0831 data: 0.0016 max mem: 33369 +Test: [2200/2573] eta: 0:00:31 time: 0.0820 data: 0.0015 max mem: 33369 +Test: [2300/2573] eta: 0:00:22 time: 0.0832 data: 0.0016 max mem: 33369 +Test: [2400/2573] eta: 0:00:14 time: 0.0792 data: 0.0015 max mem: 33369 +Test: [2500/2573] eta: 0:00:06 time: 0.0814 data: 0.0016 max mem: 33369 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: Total time: 0:03:36 +Final results: +Mean IoU is 63.26 + + precision@0.5 = 71.49 + precision@0.6 = 65.85 + precision@0.7 = 57.70 + precision@0.8 = 45.61 + precision@0.9 = 22.12 + overall IoU = 61.85 + +Average object IoU 63.255273524818875 +Overall IoU 61.84575653076172 +Better epoch: 18 + +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [19] [ 0/1319] eta: 2:04:01 lr: 2.7996211513802005e-05 loss: 0.0383 (0.0383) time: 5.6421 data: 2.1695 max mem: 33369 +Epoch: [19] [ 10/1319] eta: 1:15:30 lr: 2.7987114450740563e-05 loss: 0.0563 (0.0550) time: 3.4614 data: 0.2061 max mem: 33369 +Epoch: [19] [ 20/1319] eta: 1:13:20 lr: 2.7978017059117013e-05 loss: 0.0494 (0.0493) time: 3.2745 data: 0.0101 max mem: 33369 +Epoch: [19] [ 30/1319] eta: 1:11:44 lr: 2.7968919338800786e-05 loss: 0.0470 (0.0504) time: 3.2725 data: 0.0106 max mem: 33369 +Epoch: [19] [ 40/1319] eta: 1:10:37 lr: 2.7959821289661182e-05 loss: 0.0470 (0.0492) time: 3.2354 data: 0.0099 max mem: 33369 +Epoch: [19] [ 50/1319] eta: 1:09:58 lr: 2.795072291156743e-05 loss: 0.0459 (0.0517) time: 3.2602 data: 0.0096 max mem: 33369 +Epoch: [19] [ 60/1319] eta: 1:09:07 lr: 2.7941624204388656e-05 loss: 0.0617 (0.0534) time: 3.2553 data: 0.0100 max mem: 33369 +Epoch: [19] [ 70/1319] eta: 1:08:22 lr: 2.7932525167993873e-05 loss: 0.0520 (0.0519) time: 3.2230 data: 0.0104 max mem: 33369 +Epoch: [19] [ 80/1319] eta: 1:07:36 lr: 2.7923425802252002e-05 loss: 0.0421 (0.0506) time: 3.2125 data: 0.0105 max mem: 33369 +Epoch: [19] [ 90/1319] eta: 1:06:58 lr: 2.791432610703186e-05 loss: 0.0441 (0.0513) time: 3.2177 data: 0.0098 max mem: 33369 +Epoch: [19] [ 100/1319] eta: 1:06:22 lr: 2.790522608220219e-05 loss: 0.0453 (0.0515) time: 3.2382 data: 0.0106 max mem: 33369 +Epoch: [19] [ 110/1319] eta: 1:05:50 lr: 2.789612572763159e-05 loss: 0.0466 (0.0514) time: 3.2582 data: 0.0121 max mem: 33369 +Epoch: [19] [ 120/1319] eta: 1:05:22 lr: 2.7887025043188598e-05 loss: 0.0433 (0.0509) time: 3.2939 data: 0.0116 max mem: 33369 +Epoch: [19] [ 130/1319] eta: 1:04:47 lr: 2.7877924028741625e-05 loss: 0.0464 (0.0514) time: 3.2788 data: 0.0107 max mem: 33369 +Epoch: [19] [ 140/1319] eta: 1:04:10 lr: 2.7868822684159008e-05 loss: 0.0506 (0.0512) time: 3.2335 data: 0.0110 max mem: 33369 +Epoch: [19] [ 150/1319] eta: 1:03:36 lr: 2.7859721009308947e-05 loss: 0.0419 (0.0509) time: 3.2369 data: 0.0117 max mem: 33369 +Epoch: [19] [ 160/1319] eta: 1:03:00 lr: 2.7850619004059574e-05 loss: 0.0404 (0.0511) time: 3.2342 data: 0.0115 max mem: 33369 +Epoch: [19] [ 170/1319] eta: 1:02:26 lr: 2.7841516668278917e-05 loss: 0.0508 (0.0513) time: 3.2276 data: 0.0102 max mem: 33369 +Epoch: [19] [ 180/1319] eta: 1:01:52 lr: 2.7832414001834883e-05 loss: 0.0476 (0.0512) time: 3.2365 data: 0.0089 max mem: 33369 +Epoch: [19] [ 190/1319] eta: 1:01:23 lr: 2.782331100459529e-05 loss: 0.0450 (0.0511) time: 3.2832 data: 0.0097 max mem: 33369 +Epoch: [19] [ 200/1319] eta: 1:00:52 lr: 2.781420767642787e-05 loss: 0.0419 (0.0508) time: 3.3078 data: 0.0100 max mem: 33369 +Epoch: [19] [ 210/1319] eta: 1:00:19 lr: 2.7805104017200224e-05 loss: 0.0419 (0.0511) time: 3.2725 data: 0.0099 max mem: 33369 +Epoch: [19] [ 220/1319] eta: 0:59:44 lr: 2.779600002677987e-05 loss: 0.0475 (0.0511) time: 3.2333 data: 0.0106 max mem: 33369 +Epoch: [19] [ 230/1319] eta: 0:59:12 lr: 2.778689570503424e-05 loss: 0.0472 (0.0511) time: 3.2428 data: 0.0105 max mem: 33369 +Epoch: [19] [ 240/1319] eta: 0:58:40 lr: 2.7777791051830626e-05 loss: 0.0472 (0.0509) time: 3.2811 data: 0.0103 max mem: 33369 +Epoch: [19] [ 250/1319] eta: 0:58:07 lr: 2.7768686067036253e-05 loss: 0.0490 (0.0508) time: 3.2652 data: 0.0099 max mem: 33369 +Epoch: [19] [ 260/1319] eta: 0:57:37 lr: 2.775958075051822e-05 loss: 0.0490 (0.0508) time: 3.2875 data: 0.0101 max mem: 33369 +Epoch: [19] [ 270/1319] eta: 0:57:05 lr: 2.7750475102143547e-05 loss: 0.0488 (0.0509) time: 3.3042 data: 0.0113 max mem: 33369 +Epoch: [19] [ 280/1319] eta: 0:56:31 lr: 2.7741369121779126e-05 loss: 0.0459 (0.0510) time: 3.2533 data: 0.0110 max mem: 33369 +Epoch: [19] [ 290/1319] eta: 0:55:58 lr: 2.7732262809291776e-05 loss: 0.0472 (0.0513) time: 3.2465 data: 0.0101 max mem: 33369 +Epoch: [19] [ 300/1319] eta: 0:55:27 lr: 2.7723156164548194e-05 loss: 0.0554 (0.0513) time: 3.2816 data: 0.0106 max mem: 33369 +Epoch: [19] [ 310/1319] eta: 0:54:53 lr: 2.771404918741497e-05 loss: 0.0499 (0.0513) time: 3.2601 data: 0.0102 max mem: 33369 +Epoch: [19] [ 320/1319] eta: 0:54:20 lr: 2.7704941877758615e-05 loss: 0.0469 (0.0515) time: 3.2441 data: 0.0102 max mem: 33369 +Epoch: [19] [ 330/1319] eta: 0:53:47 lr: 2.7695834235445526e-05 loss: 0.0529 (0.0514) time: 3.2593 data: 0.0101 max mem: 33369 +Epoch: [19] [ 340/1319] eta: 0:53:14 lr: 2.7686726260341988e-05 loss: 0.0464 (0.0513) time: 3.2565 data: 0.0103 max mem: 33369 +Epoch: [19] [ 350/1319] eta: 0:52:43 lr: 2.7677617952314193e-05 loss: 0.0464 (0.0511) time: 3.2753 data: 0.0115 max mem: 33369 +Epoch: [19] [ 360/1319] eta: 0:52:10 lr: 2.7668509311228242e-05 loss: 0.0530 (0.0514) time: 3.2707 data: 0.0114 max mem: 33369 +Epoch: [19] [ 370/1319] eta: 0:51:36 lr: 2.7659400336950098e-05 loss: 0.0563 (0.0514) time: 3.2407 data: 0.0110 max mem: 33369 +Epoch: [19] [ 380/1319] eta: 0:51:04 lr: 2.765029102934566e-05 loss: 0.0492 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data: 0.0096 max mem: 33369 +Epoch: [19] [1090/1319] eta: 0:12:25 lr: 2.700266974524126e-05 loss: 0.0503 (0.0523) time: 3.2436 data: 0.0099 max mem: 33369 +Epoch: [19] [1100/1319] eta: 0:11:52 lr: 2.699353607885957e-05 loss: 0.0419 (0.0522) time: 3.2335 data: 0.0117 max mem: 33369 +Epoch: [19] [1110/1319] eta: 0:11:20 lr: 2.6984402069074687e-05 loss: 0.0482 (0.0524) time: 3.2845 data: 0.0113 max mem: 33369 +Epoch: [19] [1120/1319] eta: 0:10:47 lr: 2.6975267715744523e-05 loss: 0.0487 (0.0523) time: 3.2895 data: 0.0092 max mem: 33369 +Epoch: [19] [1130/1319] eta: 0:10:15 lr: 2.6966133018726902e-05 loss: 0.0469 (0.0523) time: 3.2545 data: 0.0088 max mem: 33369 +Epoch: [19] [1140/1319] eta: 0:09:42 lr: 2.6956997977879505e-05 loss: 0.0592 (0.0525) time: 3.2660 data: 0.0095 max mem: 33369 +Epoch: [19] [1150/1319] eta: 0:09:10 lr: 2.6947862593059943e-05 loss: 0.0568 (0.0524) time: 3.2421 data: 0.0095 max mem: 33369 +Epoch: [19] [1160/1319] eta: 0:08:37 lr: 2.6938726864125667e-05 loss: 0.0485 (0.0524) time: 3.2486 data: 0.0093 max mem: 33369 +Epoch: [19] [1170/1319] eta: 0:08:04 lr: 2.6929590790934063e-05 loss: 0.0479 (0.0524) time: 3.2561 data: 0.0099 max mem: 33369 +Epoch: [19] [1180/1319] eta: 0:07:32 lr: 2.6920454373342357e-05 loss: 0.0464 (0.0524) time: 3.2320 data: 0.0112 max mem: 33369 +Epoch: [19] [1190/1319] eta: 0:06:59 lr: 2.6911317611207703e-05 loss: 0.0436 (0.0524) time: 3.2812 data: 0.0113 max mem: 33369 +Epoch: [19] [1200/1319] eta: 0:06:27 lr: 2.6902180504387114e-05 loss: 0.0566 (0.0525) time: 3.2894 data: 0.0104 max mem: 33369 +Epoch: [19] [1210/1319] eta: 0:05:54 lr: 2.689304305273751e-05 loss: 0.0524 (0.0525) time: 3.2620 data: 0.0099 max mem: 33369 +Epoch: [19] [1220/1319] eta: 0:05:22 lr: 2.6883905256115667e-05 loss: 0.0482 (0.0525) time: 3.2812 data: 0.0102 max mem: 33369 +Epoch: [19] [1230/1319] eta: 0:04:49 lr: 2.687476711437828e-05 loss: 0.0518 (0.0527) time: 3.2658 data: 0.0103 max mem: 33369 +Epoch: [19] [1240/1319] eta: 0:04:17 lr: 2.6865628627381928e-05 loss: 0.0478 (0.0527) time: 3.2339 data: 0.0097 max mem: 33369 +Epoch: [19] [1250/1319] eta: 0:03:44 lr: 2.6856489794983043e-05 loss: 0.0444 (0.0527) time: 3.2409 data: 0.0095 max mem: 33369 +Epoch: [19] [1260/1319] eta: 0:03:12 lr: 2.6847350617037976e-05 loss: 0.0444 (0.0526) time: 3.2382 data: 0.0097 max mem: 33369 +Epoch: [19] [1270/1319] eta: 0:02:39 lr: 2.683821109340296e-05 loss: 0.0435 (0.0525) time: 3.2725 data: 0.0100 max mem: 33369 +Epoch: [19] [1280/1319] eta: 0:02:06 lr: 2.68290712239341e-05 loss: 0.0417 (0.0525) time: 3.3539 data: 0.0107 max mem: 33369 +Epoch: [19] [1290/1319] eta: 0:01:34 lr: 2.681993100848739e-05 loss: 0.0566 (0.0526) time: 3.3838 data: 0.0105 max mem: 33369 +Epoch: [19] [1300/1319] eta: 0:01:01 lr: 2.6810790446918727e-05 loss: 0.0480 (0.0526) time: 3.3619 data: 0.0111 max mem: 33369 +Epoch: [19] [1310/1319] eta: 0:00:29 lr: 2.680164953908387e-05 loss: 0.0485 (0.0527) time: 3.3336 data: 0.0100 max mem: 33369 +Epoch: [19] Total time: 1:11:39 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 2:40:12 time: 3.7359 data: 3.5401 max mem: 33369 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 100/2573] eta: 0:04:55 time: 0.0812 data: 0.0015 max mem: 33369 +Test: [ 200/2573] eta: 0:03:59 time: 0.0817 data: 0.0016 max mem: 33369 +Test: [ 300/2573] eta: 0:03:33 time: 0.0829 data: 0.0015 max mem: 33369 +Test: [ 400/2573] eta: 0:03:18 time: 0.0854 data: 0.0016 max mem: 33369 +Test: [ 500/2573] eta: 0:03:07 time: 0.0893 data: 0.0018 max mem: 33369 +Test: [ 600/2573] eta: 0:02:56 time: 0.0833 data: 0.0016 max mem: 33369 +Test: [ 700/2573] eta: 0:02:46 time: 0.0834 data: 0.0020 max mem: 33369 +Test: [ 800/2573] eta: 0:02:36 time: 0.0891 data: 0.0019 max mem: 33369 +Test: [ 900/2573] eta: 0:02:27 time: 0.0820 data: 0.0016 max mem: 33369 +Test: [1000/2573] eta: 0:02:18 time: 0.0877 data: 0.0020 max mem: 33369 +Test: [1100/2573] eta: 0:02:08 time: 0.0839 data: 0.0019 max mem: 33369 +Test: [1200/2573] eta: 0:01:59 time: 0.0820 data: 0.0016 max mem: 33369 +Test: [1300/2573] eta: 0:01:50 time: 0.0817 data: 0.0014 max mem: 33369 +Test: [1400/2573] eta: 0:01:41 time: 0.0821 data: 0.0016 max mem: 33369 +Test: [1500/2573] eta: 0:01:32 time: 0.0824 data: 0.0017 max mem: 33369 +Test: [1600/2573] eta: 0:01:24 time: 0.0893 data: 0.0019 max mem: 33369 +Test: [1700/2573] eta: 0:01:15 time: 0.0814 data: 0.0015 max mem: 33369 +Test: [1800/2573] eta: 0:01:06 time: 0.0839 data: 0.0015 max mem: 33369 +Test: [1900/2573] eta: 0:00:57 time: 0.0821 data: 0.0016 max mem: 33369 +Test: [2000/2573] eta: 0:00:49 time: 0.0828 data: 0.0016 max mem: 33369 +Test: [2100/2573] eta: 0:00:40 time: 0.0872 data: 0.0020 max mem: 33369 +Test: [2200/2573] eta: 0:00:32 time: 0.0863 data: 0.0019 max mem: 33369 +Test: [2300/2573] eta: 0:00:23 time: 0.0852 data: 0.0016 max mem: 33369 +Test: [2400/2573] eta: 0:00:14 time: 0.0802 data: 0.0016 max mem: 33369 +Test: [2500/2573] eta: 0:00:06 time: 0.0832 data: 0.0017 max mem: 33369 +Test: Total time: 0:03:40 +Final results: +Mean IoU is 63.14 + + precision@0.5 = 71.26 + precision@0.6 = 65.42 + precision@0.7 = 57.86 + precision@0.8 = 46.14 + precision@0.9 = 21.63 + overall IoU = 60.88 + +Average object IoU 63.137503049708364 +Overall IoU 60.883941650390625 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [20] [ 0/1319] eta: 4:29:46 lr: 2.6793422425855603e-05 loss: 0.0463 (0.0463) time: 12.2716 data: 2.1750 max mem: 33369 +Epoch: [20] [ 10/1319] eta: 1:31:55 lr: 2.678428085971722e-05 loss: 0.0454 (0.0438) time: 4.2137 data: 0.2061 max mem: 33369 +Epoch: [20] [ 20/1319] eta: 1:22:37 lr: 2.6775138946893718e-05 loss: 0.0424 (0.0444) time: 3.3938 data: 0.0087 max mem: 33369 +Epoch: [20] [ 30/1319] eta: 1:18:22 lr: 2.6765996687240426e-05 loss: 0.0407 (0.0432) time: 3.3366 data: 0.0089 max mem: 33369 +Epoch: [20] [ 40/1319] eta: 1:16:12 lr: 2.675685408061254e-05 loss: 0.0417 (0.0447) time: 3.3223 data: 0.0099 max mem: 33369 +Epoch: [20] [ 50/1319] eta: 1:14:55 lr: 2.6747711126865168e-05 loss: 0.0417 (0.0447) time: 3.3796 data: 0.0106 max mem: 33369 +Epoch: [20] [ 60/1319] eta: 1:13:45 lr: 2.6738567825853273e-05 loss: 0.0497 (0.0497) time: 3.3908 data: 0.0103 max mem: 33369 +Epoch: [20] [ 70/1319] eta: 1:12:32 lr: 2.6729424177431713e-05 loss: 0.0516 (0.0491) time: 3.3381 data: 0.0094 max mem: 33369 +Epoch: [20] [ 80/1319] eta: 1:11:33 lr: 2.6720280181455227e-05 loss: 0.0451 (0.0486) time: 3.3137 data: 0.0094 max mem: 33369 +Epoch: [20] [ 90/1319] eta: 1:10:39 lr: 2.671113583777845e-05 loss: 0.0437 (0.0481) time: 3.3233 data: 0.0089 max mem: 33369 +Epoch: [20] [ 100/1319] eta: 1:09:52 lr: 2.670199114625589e-05 loss: 0.0436 (0.0481) time: 3.3336 data: 0.0089 max mem: 33369 +Epoch: [20] [ 110/1319] eta: 1:09:01 lr: 2.6692846106741932e-05 loss: 0.0371 (0.0472) time: 3.3179 data: 0.0087 max mem: 33369 +Epoch: [20] [ 120/1319] eta: 1:08:16 lr: 2.668370071909087e-05 loss: 0.0387 (0.0475) time: 3.3002 data: 0.0087 max mem: 33369 +Epoch: [20] [ 130/1319] eta: 1:07:35 lr: 2.6674554983156852e-05 loss: 0.0414 (0.0473) time: 3.3271 data: 0.0095 max mem: 33369 +Epoch: [20] [ 140/1319] eta: 1:06:55 lr: 2.666540889879393e-05 loss: 0.0448 (0.0476) time: 3.3416 data: 0.0100 max mem: 33369 +Epoch: [20] [ 150/1319] eta: 1:06:13 lr: 2.6656262465856026e-05 loss: 0.0474 (0.0479) time: 3.3204 data: 0.0115 max mem: 33369 +Epoch: [20] [ 160/1319] eta: 1:05:34 lr: 2.6647115684196954e-05 loss: 0.0487 (0.0480) time: 3.3215 data: 0.0112 max mem: 33369 +Epoch: [20] [ 170/1319] eta: 1:04:59 lr: 2.663796855367041e-05 loss: 0.0440 (0.0480) time: 3.3561 data: 0.0102 max mem: 33369 +Epoch: [20] [ 180/1319] eta: 1:04:21 lr: 2.662882107412996e-05 loss: 0.0404 (0.0479) time: 3.3492 data: 0.0105 max mem: 33369 +Epoch: [20] [ 190/1319] eta: 1:03:44 lr: 2.661967324542908e-05 loss: 0.0404 (0.0487) time: 3.3377 data: 0.0101 max mem: 33369 +Epoch: [20] [ 200/1319] eta: 1:03:11 lr: 2.6610525067421092e-05 loss: 0.0481 (0.0489) time: 3.3703 data: 0.0099 max mem: 33369 +Epoch: [20] [ 210/1319] eta: 1:02:35 lr: 2.6601376539959238e-05 loss: 0.0491 (0.0494) time: 3.3705 data: 0.0101 max mem: 33369 +Epoch: [20] [ 220/1319] eta: 1:02:00 lr: 2.6592227662896617e-05 loss: 0.0491 (0.0498) time: 3.3555 data: 0.0097 max mem: 33369 +Epoch: [20] [ 230/1319] eta: 1:01:23 lr: 2.658307843608621e-05 loss: 0.0447 (0.0495) time: 3.3406 data: 0.0102 max mem: 33369 +Epoch: [20] [ 240/1319] eta: 1:00:46 lr: 2.65739288593809e-05 loss: 0.0477 (0.0505) time: 3.3135 data: 0.0100 max mem: 33369 +Epoch: [20] [ 250/1319] eta: 1:00:11 lr: 2.6564778932633426e-05 loss: 0.0484 (0.0502) time: 3.3287 data: 0.0090 max mem: 33369 +Epoch: [20] [ 260/1319] eta: 0:59:36 lr: 2.655562865569643e-05 loss: 0.0427 (0.0500) time: 3.3575 data: 0.0100 max mem: 33369 +Epoch: [20] [ 270/1319] eta: 0:59:00 lr: 2.654647802842242e-05 loss: 0.0451 (0.0502) time: 3.3444 data: 0.0100 max mem: 33369 +Epoch: [20] [ 280/1319] eta: 0:58:27 lr: 2.6537327050663813e-05 loss: 0.0447 (0.0500) time: 3.3583 data: 0.0089 max mem: 33369 +Epoch: [20] [ 290/1319] eta: 0:57:54 lr: 2.6528175722272857e-05 loss: 0.0474 (0.0503) time: 3.3885 data: 0.0093 max mem: 33369 +Epoch: [20] [ 300/1319] eta: 0:57:18 lr: 2.6519024043101733e-05 loss: 0.0523 (0.0503) time: 3.3451 data: 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2.637254934915819e-05 loss: 0.0402 (0.0488) time: 3.3488 data: 0.0106 max mem: 33369 +Epoch: [20] [ 470/1319] eta: 0:47:32 lr: 2.6363391683988447e-05 loss: 0.0401 (0.0487) time: 3.3273 data: 0.0100 max mem: 33369 +Epoch: [20] [ 480/1319] eta: 0:46:58 lr: 2.6354233665356892e-05 loss: 0.0427 (0.0488) time: 3.3530 data: 0.0099 max mem: 33369 +Epoch: [20] [ 490/1319] eta: 0:46:26 lr: 2.6345075293113398e-05 loss: 0.0425 (0.0487) time: 3.3962 data: 0.0090 max mem: 33369 +Epoch: [20] [ 500/1319] eta: 0:45:51 lr: 2.633591656710771e-05 loss: 0.0359 (0.0486) time: 3.3579 data: 0.0085 max mem: 33369 +Epoch: [20] [ 510/1319] eta: 0:45:17 lr: 2.6326757487189457e-05 loss: 0.0453 (0.0487) time: 3.3228 data: 0.0091 max mem: 33369 +Epoch: [20] [ 520/1319] eta: 0:44:44 lr: 2.6317598053208148e-05 loss: 0.0472 (0.0489) time: 3.3540 data: 0.0099 max mem: 33369 +Epoch: [20] [ 530/1319] eta: 0:44:12 lr: 2.6308438265013168e-05 loss: 0.0453 (0.0488) time: 3.4072 data: 0.0099 max mem: 33369 +Epoch: [20] [ 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data: 0.0102 max mem: 33369 +Epoch: [20] [ 700/1319] eta: 0:34:37 lr: 2.615266752446517e-05 loss: 0.0440 (0.0489) time: 3.3415 data: 0.0102 max mem: 33369 +Epoch: [20] [ 710/1319] eta: 0:34:03 lr: 2.614350133452863e-05 loss: 0.0420 (0.0490) time: 3.3398 data: 0.0103 max mem: 33369 +Epoch: [20] [ 720/1319] eta: 0:33:29 lr: 2.6134334787493302e-05 loss: 0.0394 (0.0490) time: 3.3171 data: 0.0103 max mem: 33369 +Epoch: [20] [ 730/1319] eta: 0:32:55 lr: 2.6125167883206104e-05 loss: 0.0454 (0.0489) time: 3.3023 data: 0.0112 max mem: 33369 +Epoch: [20] [ 740/1319] eta: 0:32:21 lr: 2.61160006215138e-05 loss: 0.0448 (0.0489) time: 3.3359 data: 0.0110 max mem: 33369 +Epoch: [20] [ 750/1319] eta: 0:31:48 lr: 2.610683300226307e-05 loss: 0.0414 (0.0488) time: 3.3577 data: 0.0097 max mem: 33369 +Epoch: [20] [ 760/1319] eta: 0:31:14 lr: 2.6097665025300437e-05 loss: 0.0404 (0.0487) time: 3.3378 data: 0.0099 max mem: 33369 +Epoch: [20] [ 770/1319] eta: 0:30:41 lr: 2.608849669047231e-05 loss: 0.0470 (0.0487) time: 3.3498 data: 0.0104 max mem: 33369 +Epoch: [20] [ 780/1319] eta: 0:30:07 lr: 2.6079327997624963e-05 loss: 0.0475 (0.0488) time: 3.3319 data: 0.0108 max mem: 33369 +Epoch: [20] [ 790/1319] eta: 0:29:33 lr: 2.6070158946604555e-05 loss: 0.0454 (0.0490) time: 3.3265 data: 0.0114 max mem: 33369 +Epoch: [20] [ 800/1319] eta: 0:29:00 lr: 2.6060989537257118e-05 loss: 0.0456 (0.0490) time: 3.3608 data: 0.0107 max mem: 33369 +Epoch: [20] [ 810/1319] eta: 0:28:26 lr: 2.6051819769428553e-05 loss: 0.0456 (0.0490) time: 3.3310 data: 0.0104 max mem: 33369 +Epoch: [20] [ 820/1319] eta: 0:27:53 lr: 2.604264964296463e-05 loss: 0.0445 (0.0495) time: 3.3946 data: 0.0101 max mem: 33369 +Epoch: [20] [ 830/1319] eta: 0:27:19 lr: 2.6033479157711e-05 loss: 0.0473 (0.0496) time: 3.3993 data: 0.0091 max mem: 33369 +Epoch: [20] [ 840/1319] eta: 0:26:46 lr: 2.6024308313513185e-05 loss: 0.0473 (0.0495) time: 3.3327 data: 0.0092 max mem: 33369 +Epoch: [20] [ 850/1319] eta: 0:26:13 lr: 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33369 +Epoch: [20] [1010/1319] eta: 0:17:16 lr: 2.586834889338287e-05 loss: 0.0409 (0.0494) time: 3.3716 data: 0.0105 max mem: 33369 +Epoch: [20] [1020/1319] eta: 0:16:42 lr: 2.58591715616284e-05 loss: 0.0414 (0.0495) time: 3.3401 data: 0.0119 max mem: 33369 +Epoch: [20] [1030/1319] eta: 0:16:09 lr: 2.584999386797035e-05 loss: 0.0443 (0.0495) time: 3.3437 data: 0.0119 max mem: 33369 +Epoch: [20] [1040/1319] eta: 0:15:35 lr: 2.5840815812251663e-05 loss: 0.0443 (0.0494) time: 3.3457 data: 0.0106 max mem: 33369 +Epoch: [20] [1050/1319] eta: 0:15:01 lr: 2.583163739431517e-05 loss: 0.0491 (0.0494) time: 3.3226 data: 0.0103 max mem: 33369 +Epoch: [20] [1060/1319] eta: 0:14:28 lr: 2.582245861400355e-05 loss: 0.0505 (0.0495) time: 3.3503 data: 0.0112 max mem: 33369 +Epoch: [20] [1070/1319] eta: 0:13:55 lr: 2.5813279471159375e-05 loss: 0.0485 (0.0495) time: 3.3865 data: 0.0106 max mem: 33369 +Epoch: [20] [1080/1319] eta: 0:13:21 lr: 2.5804099965625085e-05 loss: 0.0472 (0.0496) time: 3.3446 data: 0.0105 max mem: 33369 +Epoch: [20] [1090/1319] eta: 0:12:47 lr: 2.5794920097242954e-05 loss: 0.0418 (0.0496) time: 3.3360 data: 0.0101 max mem: 33369 +Epoch: [20] [1100/1319] eta: 0:12:14 lr: 2.5785739865855164e-05 loss: 0.0394 (0.0495) time: 3.3386 data: 0.0105 max mem: 33369 +Epoch: [20] [1110/1319] eta: 0:11:40 lr: 2.5776559271303753e-05 loss: 0.0445 (0.0495) time: 3.3048 data: 0.0129 max mem: 33369 +Epoch: [20] [1120/1319] eta: 0:11:07 lr: 2.5767378313430623e-05 loss: 0.0415 (0.0495) time: 3.3189 data: 0.0123 max mem: 33369 +Epoch: [20] [1130/1319] eta: 0:10:33 lr: 2.5758196992077554e-05 loss: 0.0392 (0.0496) time: 3.3152 data: 0.0116 max mem: 33369 +Epoch: [20] [1140/1319] eta: 0:09:59 lr: 2.574901530708619e-05 loss: 0.0498 (0.0496) time: 3.3115 data: 0.0117 max mem: 33369 +Epoch: [20] [1150/1319] eta: 0:09:26 lr: 2.573983325829803e-05 loss: 0.0490 (0.0496) time: 3.3354 data: 0.0112 max mem: 33369 +Epoch: [20] [1160/1319] eta: 0:08:52 lr: 2.573065084555446e-05 loss: 0.0428 (0.0495) time: 3.3182 data: 0.0116 max mem: 33369 +Epoch: [20] [1170/1319] eta: 0:08:19 lr: 2.572146806869673e-05 loss: 0.0428 (0.0495) time: 3.3126 data: 0.0115 max mem: 33369 +Epoch: [20] [1180/1319] eta: 0:07:45 lr: 2.5712284927565954e-05 loss: 0.0488 (0.0496) time: 3.3309 data: 0.0120 max mem: 33369 +Epoch: [20] [1190/1319] eta: 0:07:12 lr: 2.5703101422003118e-05 loss: 0.0473 (0.0495) time: 3.3136 data: 0.0123 max mem: 33369 +Epoch: [20] [1200/1319] eta: 0:06:38 lr: 2.569391755184906e-05 loss: 0.0381 (0.0494) time: 3.3278 data: 0.0104 max mem: 33369 +Epoch: [20] [1210/1319] eta: 0:06:05 lr: 2.5684733316944508e-05 loss: 0.0409 (0.0494) time: 3.3724 data: 0.0094 max mem: 33369 +Epoch: [20] [1220/1319] eta: 0:05:31 lr: 2.5675548717130043e-05 loss: 0.0494 (0.0495) time: 3.3758 data: 0.0107 max mem: 33369 +Epoch: [20] [1230/1319] eta: 0:04:58 lr: 2.5666363752246116e-05 loss: 0.0486 (0.0495) time: 3.3443 data: 0.0111 max mem: 33369 +Epoch: [20] [1240/1319] eta: 0:04:24 lr: 2.5657178422133044e-05 loss: 0.0507 (0.0496) time: 3.3052 data: 0.0100 max mem: 33369 +Epoch: [20] [1250/1319] eta: 0:03:51 lr: 2.564799272663101e-05 loss: 0.0590 (0.0497) time: 3.2897 data: 0.0103 max mem: 33369 +Epoch: [20] [1260/1319] eta: 0:03:17 lr: 2.5638806665580068e-05 loss: 0.0486 (0.0497) time: 3.3049 data: 0.0113 max mem: 33369 +Epoch: [20] [1270/1319] eta: 0:02:44 lr: 2.5629620238820134e-05 loss: 0.0486 (0.0498) time: 3.3425 data: 0.0117 max mem: 33369 +Epoch: [20] [1280/1319] eta: 0:02:10 lr: 2.562043344619099e-05 loss: 0.0448 (0.0498) time: 3.3356 data: 0.0117 max mem: 33369 +Epoch: [20] [1290/1319] eta: 0:01:37 lr: 2.5611246287532285e-05 loss: 0.0459 (0.0497) time: 3.3038 data: 0.0117 max mem: 33369 +Epoch: [20] [1300/1319] eta: 0:01:03 lr: 2.560205876268355e-05 loss: 0.0461 (0.0497) time: 3.3461 data: 0.0111 max mem: 33369 +Epoch: [20] [1310/1319] eta: 0:00:30 lr: 2.5592870871484144e-05 loss: 0.0458 (0.0497) time: 3.3486 data: 0.0096 max mem: 33369 +Epoch: [20] Total time: 1:13:37 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 2:34:09 time: 3.5949 data: 3.4717 max mem: 33369 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 100/2573] eta: 0:05:06 time: 0.0869 data: 0.0021 max mem: 33369 +Test: [ 200/2573] eta: 0:04:09 time: 0.0838 data: 0.0018 max mem: 33369 +Test: [ 300/2573] eta: 0:03:45 time: 0.0877 data: 0.0020 max mem: 33369 +Test: [ 400/2573] eta: 0:03:29 time: 0.0885 data: 0.0020 max mem: 33369 +Test: [ 500/2573] eta: 0:03:15 time: 0.0873 data: 0.0021 max mem: 33369 +Test: [ 600/2573] eta: 0:03:04 time: 0.0874 data: 0.0021 max mem: 33369 +Test: [ 700/2573] eta: 0:02:52 time: 0.0817 data: 0.0016 max mem: 33369 +Test: [ 800/2573] eta: 0:02:41 time: 0.0855 data: 0.0016 max mem: 33369 +Test: [ 900/2573] eta: 0:02:31 time: 0.0818 data: 0.0015 max mem: 33369 +Test: [1000/2573] eta: 0:02:20 time: 0.0823 data: 0.0015 max mem: 33369 +Test: [1100/2573] eta: 0:02:10 time: 0.0830 data: 0.0017 max mem: 33369 +Test: [1200/2573] eta: 0:02:01 time: 0.0856 data: 0.0018 max mem: 33369 +Test: [1300/2573] eta: 0:01:52 time: 0.0824 data: 0.0015 max mem: 33369 +Test: [1400/2573] eta: 0:01:42 time: 0.0803 data: 0.0015 max mem: 33369 +Test: [1500/2573] eta: 0:01:34 time: 0.0886 data: 0.0021 max mem: 33369 +Test: [1600/2573] eta: 0:01:25 time: 0.0903 data: 0.0021 max mem: 33369 +Test: [1700/2573] eta: 0:01:16 time: 0.0822 data: 0.0017 max mem: 33369 +Test: [1800/2573] eta: 0:01:07 time: 0.0854 data: 0.0018 max mem: 33369 +Test: [1900/2573] eta: 0:00:58 time: 0.0789 data: 0.0015 max mem: 33369 +Test: [2000/2573] eta: 0:00:49 time: 0.0866 data: 0.0020 max mem: 33369 +Test: [2100/2573] eta: 0:00:41 time: 0.0883 data: 0.0020 max mem: 33369 +Test: [2200/2573] eta: 0:00:32 time: 0.0879 data: 0.0020 max mem: 33369 +Test: [2300/2573] eta: 0:00:23 time: 0.0882 data: 0.0022 max mem: 33369 +Test: [2400/2573] eta: 0:00:15 time: 0.0805 data: 0.0015 max mem: 33369 +Test: [2500/2573] eta: 0:00:06 time: 0.0828 data: 0.0015 max mem: 33369 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: Total time: 0:03:44 +Final results: +Mean IoU is 63.29 + + precision@0.5 = 71.26 + precision@0.6 = 65.65 + precision@0.7 = 58.21 + precision@0.8 = 46.24 + precision@0.9 = 22.67 + overall IoU = 61.10 + +Average object IoU 63.294037590855645 +Overall IoU 61.095787048339844 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [21] [ 0/1319] eta: 3:55:31 lr: 2.5584601456041995e-05 loss: 0.0627 (0.0627) time: 10.7137 data: 2.7711 max mem: 33369 +Epoch: [21] [ 10/1319] eta: 1:27:22 lr: 2.5575412868333344e-05 loss: 0.0470 (0.0573) time: 4.0051 data: 0.2607 max mem: 33369 +Epoch: [21] [ 20/1319] eta: 1:19:33 lr: 2.5566223913807464e-05 loss: 0.0415 (0.0502) time: 3.3226 data: 0.0089 max mem: 33369 +Epoch: [21] [ 30/1319] eta: 1:16:24 lr: 2.5557034592303224e-05 loss: 0.0413 (0.0522) time: 3.3097 data: 0.0096 max mem: 33369 +Epoch: [21] [ 40/1319] eta: 1:14:44 lr: 2.5547844903659336e-05 loss: 0.0459 (0.0513) time: 3.3300 data: 0.0114 max mem: 33369 +Epoch: [21] [ 50/1319] eta: 1:13:33 lr: 2.5538654847714393e-05 loss: 0.0422 (0.0499) time: 3.3567 data: 0.0114 max mem: 33369 +Epoch: [21] [ 60/1319] eta: 1:12:23 lr: 2.552946442430683e-05 loss: 0.0404 (0.0483) time: 3.3335 data: 0.0105 max mem: 33369 +Epoch: [21] [ 70/1319] eta: 1:11:29 lr: 2.552027363327497e-05 loss: 0.0426 (0.0501) time: 3.3233 data: 0.0097 max mem: 33369 +Epoch: [21] [ 80/1319] eta: 1:10:43 lr: 2.551108247445699e-05 loss: 0.0438 (0.0491) time: 3.3480 data: 0.0100 max mem: 33369 +Epoch: [21] [ 90/1319] eta: 1:09:48 lr: 2.5501890947690927e-05 loss: 0.0407 (0.0482) time: 3.3125 data: 0.0113 max mem: 33369 +Epoch: [21] [ 100/1319] eta: 1:08:58 lr: 2.5492699052814688e-05 loss: 0.0474 (0.0484) time: 3.2749 data: 0.0117 max mem: 33369 +Epoch: [21] [ 110/1319] eta: 1:08:19 lr: 2.548350678966605e-05 loss: 0.0419 (0.0475) time: 3.3134 data: 0.0113 max mem: 33369 +Epoch: [21] [ 120/1319] eta: 1:07:49 lr: 2.547431415808263e-05 loss: 0.0397 (0.0472) time: 3.3871 data: 0.0113 max mem: 33369 +Epoch: [21] [ 130/1319] eta: 1:07:09 lr: 2.5465121157901932e-05 loss: 0.0393 (0.0467) time: 3.3819 data: 0.0121 max mem: 33369 +Epoch: [21] [ 140/1319] eta: 1:06:31 lr: 2.5455927788961316e-05 loss: 0.0375 (0.0462) time: 3.3357 data: 0.0120 max mem: 33369 +Epoch: [21] [ 150/1319] eta: 1:05:50 lr: 2.5446734051098e-05 loss: 0.0401 (0.0460) time: 3.3136 data: 0.0112 max mem: 33369 +Epoch: [21] [ 160/1319] eta: 1:05:06 lr: 2.5437539944149068e-05 loss: 0.0493 (0.0464) time: 3.2657 data: 0.0109 max mem: 33369 +Epoch: [21] [ 170/1319] eta: 1:04:23 lr: 2.542834546795147e-05 loss: 0.0498 (0.0464) time: 3.2379 data: 0.0109 max mem: 33369 +Epoch: [21] [ 180/1319] eta: 1:03:37 lr: 2.5419150622342014e-05 loss: 0.0490 (0.0476) time: 3.2027 data: 0.0108 max mem: 33369 +Epoch: [21] [ 190/1319] eta: 1:02:55 lr: 2.5409955407157366e-05 loss: 0.0420 (0.0472) time: 3.1810 data: 0.0107 max mem: 33369 +Epoch: [21] [ 200/1319] eta: 1:02:17 lr: 2.5400759822234066e-05 loss: 0.0362 (0.0469) time: 3.2353 data: 0.0106 max mem: 33369 +Epoch: [21] [ 210/1319] eta: 1:01:37 lr: 2.539156386740852e-05 loss: 0.0369 (0.0467) time: 3.2421 data: 0.0109 max mem: 33369 +Epoch: [21] [ 220/1319] eta: 1:01:00 lr: 2.538236754251696e-05 loss: 0.0403 (0.0465) time: 3.2336 data: 0.0108 max mem: 33369 +Epoch: 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+/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 2:37:36 time: 3.6752 data: 3.4797 max mem: 33369 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 100/2573] eta: 0:04:46 time: 0.0796 data: 0.0016 max mem: 33369 +Test: [ 200/2573] eta: 0:03:55 time: 0.0802 data: 0.0016 max mem: 33369 +Test: [ 300/2573] eta: 0:03:30 time: 0.0818 data: 0.0015 max mem: 33369 +Test: [ 400/2573] eta: 0:03:15 time: 0.0822 data: 0.0016 max mem: 33369 +Test: [ 500/2573] eta: 0:03:03 time: 0.0822 data: 0.0016 max mem: 33369 +Test: [ 600/2573] eta: 0:02:52 time: 0.0821 data: 0.0016 max mem: 33369 +Test: [ 700/2573] eta: 0:02:42 time: 0.0806 data: 0.0014 max mem: 33369 +Test: [ 800/2573] eta: 0:02:32 time: 0.0856 data: 0.0016 max mem: 33369 +Test: [ 900/2573] eta: 0:02:23 time: 0.0809 data: 0.0015 max mem: 33369 +Test: [1000/2573] eta: 0:02:14 time: 0.0817 data: 0.0015 max mem: 33369 +Test: [1100/2573] eta: 0:02:05 time: 0.0817 data: 0.0017 max mem: 33369 +Test: [1200/2573] eta: 0:01:56 time: 0.0820 data: 0.0016 max mem: 33369 +Test: [1300/2573] eta: 0:01:47 time: 0.0812 data: 0.0014 max mem: 33369 +Test: [1400/2573] eta: 0:01:38 time: 0.0797 data: 0.0015 max mem: 33369 +Test: [1500/2573] eta: 0:01:30 time: 0.0855 data: 0.0019 max mem: 33369 +Test: [1600/2573] eta: 0:01:22 time: 0.0867 data: 0.0019 max mem: 33369 +Test: [1700/2573] eta: 0:01:13 time: 0.0815 data: 0.0016 max mem: 33369 +Test: [1800/2573] eta: 0:01:05 time: 0.0831 data: 0.0017 max mem: 33369 +Test: [1900/2573] eta: 0:00:56 time: 0.0801 data: 0.0017 max mem: 33369 +Test: [2000/2573] eta: 0:00:47 time: 0.0830 data: 0.0017 max mem: 33369 +Test: [2100/2573] eta: 0:00:39 time: 0.0824 data: 0.0015 max mem: 33369 +Test: [2200/2573] eta: 0:00:31 time: 0.0843 data: 0.0017 max mem: 33369 +Test: [2300/2573] eta: 0:00:22 time: 0.0841 data: 0.0016 max mem: 33369 +Test: [2400/2573] eta: 0:00:14 time: 0.0833 data: 0.0018 max mem: 33369 +Test: [2500/2573] eta: 0:00:06 time: 0.0850 data: 0.0018 max mem: 33369 +Test: Total time: 0:03:35 +Final results: +Mean IoU is 63.45 + + precision@0.5 = 71.43 + precision@0.6 = 65.60 + precision@0.7 = 57.41 + precision@0.8 = 45.75 + precision@0.9 = 22.34 + overall IoU = 61.27 + +Average object IoU 63.446277540023786 +Overall IoU 61.2745361328125 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [22] [ 0/1319] eta: 4:01:43 lr: 2.4369398138885975e-05 loss: 0.0438 (0.0438) time: 10.9961 data: 2.8580 max mem: 33369 +Epoch: [22] [ 10/1319] eta: 1:27:12 lr: 2.436015972419942e-05 loss: 0.0466 (0.0484) time: 3.9976 data: 0.2680 max mem: 33369 +Epoch: [22] [ 20/1319] eta: 1:19:19 lr: 2.4350920920207323e-05 loss: 0.0466 (0.0487) time: 3.2970 data: 0.0088 max mem: 33369 +Epoch: [22] [ 30/1319] eta: 1:15:43 lr: 2.4341681726729162e-05 loss: 0.0462 (0.0488) time: 3.2643 data: 0.0099 max mem: 33369 +Epoch: [22] [ 40/1319] eta: 1:13:40 lr: 2.4332442143584247e-05 loss: 0.0429 (0.0480) time: 3.2384 data: 0.0109 max mem: 33369 +Epoch: [22] [ 50/1319] eta: 1:12:01 lr: 2.4323202170591704e-05 loss: 0.0507 (0.0497) time: 3.2205 data: 0.0104 max mem: 33369 +Epoch: [22] [ 60/1319] eta: 1:10:59 lr: 2.4313961807570534e-05 loss: 0.0507 (0.0501) time: 3.2326 data: 0.0099 max mem: 33369 +Epoch: [22] [ 70/1319] eta: 1:10:02 lr: 2.430472105433956e-05 loss: 0.0460 (0.0492) time: 3.2624 data: 0.0105 max mem: 33369 +Epoch: [22] [ 80/1319] eta: 1:09:12 lr: 2.4295479910717442e-05 loss: 0.0386 (0.0479) time: 3.2560 data: 0.0106 max mem: 33369 +Epoch: [22] [ 90/1319] eta: 1:08:26 lr: 2.4286238376522685e-05 loss: 0.0353 (0.0487) time: 3.2574 data: 0.0091 max mem: 33369 +Epoch: [22] [ 100/1319] eta: 1:07:41 lr: 2.4276996451573638e-05 loss: 0.0376 (0.0481) time: 3.2538 data: 0.0081 max mem: 33369 +Epoch: [22] [ 110/1319] eta: 1:07:02 lr: 2.426775413568847e-05 loss: 0.0392 (0.0477) time: 3.2614 data: 0.0079 max mem: 33369 +Epoch: [22] [ 120/1319] eta: 1:06:15 lr: 2.4258511428685206e-05 loss: 0.0402 (0.0479) time: 3.2309 data: 0.0085 max mem: 33369 +Epoch: [22] [ 130/1319] eta: 1:05:29 lr: 2.4249268330381702e-05 loss: 0.0390 (0.0471) time: 3.1837 data: 0.0088 max mem: 33369 +Epoch: [22] [ 140/1319] eta: 1:04:46 lr: 2.4240024840595657e-05 loss: 0.0390 (0.0470) time: 3.1815 data: 0.0081 max mem: 33369 +Epoch: [22] [ 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time: 1:10:09 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 2:53:14 time: 4.0398 data: 3.9069 max mem: 33369 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 100/2573] eta: 0:04:51 time: 0.0785 data: 0.0015 max mem: 33369 +Test: [ 200/2573] eta: 0:03:56 time: 0.0799 data: 0.0015 max mem: 33369 +Test: [ 300/2573] eta: 0:03:31 time: 0.0820 data: 0.0015 max mem: 33369 +Test: [ 400/2573] eta: 0:03:14 time: 0.0813 data: 0.0016 max mem: 33369 +Test: [ 500/2573] eta: 0:03:02 time: 0.0808 data: 0.0016 max mem: 33369 +Test: [ 600/2573] eta: 0:02:51 time: 0.0817 data: 0.0014 max mem: 33369 +Test: [ 700/2573] eta: 0:02:42 time: 0.0808 data: 0.0014 max mem: 33369 +Test: [ 800/2573] eta: 0:02:32 time: 0.0836 data: 0.0014 max mem: 33369 +Test: [ 900/2573] eta: 0:02:22 time: 0.0815 data: 0.0015 max mem: 33369 +Test: [1000/2573] eta: 0:02:13 time: 0.0817 data: 0.0015 max mem: 33369 +Test: [1100/2573] eta: 0:02:04 time: 0.0810 data: 0.0015 max mem: 33369 +Test: [1200/2573] eta: 0:01:56 time: 0.0808 data: 0.0015 max mem: 33369 +Test: [1300/2573] eta: 0:01:47 time: 0.0809 data: 0.0016 max mem: 33369 +Test: [1400/2573] eta: 0:01:38 time: 0.0786 data: 0.0014 max mem: 33369 +Test: [1500/2573] eta: 0:01:30 time: 0.0806 data: 0.0015 max mem: 33369 +Test: [1600/2573] eta: 0:01:21 time: 0.0838 data: 0.0016 max mem: 33369 +Test: [1700/2573] eta: 0:01:12 time: 0.0793 data: 0.0014 max mem: 33369 +Test: [1800/2573] eta: 0:01:04 time: 0.0826 data: 0.0015 max mem: 33369 +Test: [1900/2573] eta: 0:00:56 time: 0.0798 data: 0.0015 max mem: 33369 +Test: [2000/2573] eta: 0:00:47 time: 0.0825 data: 0.0016 max mem: 33369 +Test: [2100/2573] eta: 0:00:39 time: 0.0820 data: 0.0014 max mem: 33369 +Test: [2200/2573] eta: 0:00:30 time: 0.0825 data: 0.0016 max mem: 33369 +Test: [2300/2573] eta: 0:00:22 time: 0.0823 data: 0.0015 max mem: 33369 +Test: [2400/2573] eta: 0:00:14 time: 0.0776 data: 0.0016 max mem: 33369 +Test: [2500/2573] eta: 0:00:06 time: 0.0800 data: 0.0015 max mem: 33369 +Test: Total time: 0:03:32 +Final results: +Mean IoU is 64.00 + + precision@0.5 = 72.18 + precision@0.6 = 65.99 + precision@0.7 = 57.95 + precision@0.8 = 46.79 + precision@0.9 = 23.55 + overall IoU = 61.95 + +Average object IoU 64.0043633965855 +Overall IoU 61.95465850830078 +Better epoch: 22 + +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [23] [ 0/1319] eta: 2:15:03 lr: 2.3147420946379584e-05 loss: 0.0745 (0.0745) time: 6.1437 data: 2.9120 max mem: 33369 +Epoch: [23] [ 10/1319] eta: 1:15:01 lr: 2.313812956136191e-05 loss: 0.0432 (0.0444) time: 3.4386 data: 0.2716 max mem: 33369 +Epoch: [23] [ 20/1319] eta: 1:12:02 lr: 2.3128837761763095e-05 loss: 0.0439 (0.0461) time: 3.1867 data: 0.0075 max mem: 33369 +Epoch: [23] [ 30/1319] eta: 1:10:51 lr: 2.3119545547379566e-05 loss: 0.0430 (0.0434) time: 3.2210 data: 0.0074 max mem: 33369 +Epoch: [23] [ 40/1319] eta: 1:09:42 lr: 2.3110252918007542e-05 loss: 0.0363 (0.0425) time: 3.2097 data: 0.0074 max mem: 33369 +Epoch: [23] [ 50/1319] eta: 1:08:50 lr: 2.3100959873443074e-05 loss: 0.0375 (0.0444) time: 3.1879 data: 0.0078 max mem: 33369 +Epoch: [23] [ 60/1319] eta: 1:08:02 lr: 2.3091666413482015e-05 loss: 0.0387 (0.0442) time: 3.1857 data: 0.0089 max mem: 33369 +Epoch: [23] [ 70/1319] eta: 1:07:37 lr: 2.3082372537920018e-05 loss: 0.0383 (0.0437) time: 3.2326 data: 0.0086 max mem: 33369 +Epoch: [23] [ 80/1319] eta: 1:07:09 lr: 2.307307824655256e-05 loss: 0.0384 (0.0445) time: 3.2805 data: 0.0080 max mem: 33369 +Epoch: [23] [ 90/1319] eta: 1:06:24 lr: 2.3063783539174907e-05 loss: 0.0384 (0.0448) time: 3.2176 data: 0.0090 max mem: 33369 +Epoch: [23] [ 100/1319] eta: 1:05:40 lr: 2.3054488415582145e-05 loss: 0.0354 (0.0440) time: 3.1561 data: 0.0090 max mem: 33369 +Epoch: [23] [ 110/1319] eta: 1:05:07 lr: 2.3045192875569164e-05 loss: 0.0381 (0.0439) time: 3.1867 data: 0.0093 max mem: 33369 +Epoch: [23] [ 120/1319] eta: 1:04:30 lr: 2.3035896918930662e-05 loss: 0.0401 (0.0437) time: 3.2062 data: 0.0094 max mem: 33369 +Epoch: [23] [ 130/1319] eta: 1:03:55 lr: 2.3026600545461138e-05 loss: 0.0365 (0.0435) time: 3.1907 data: 0.0086 max mem: 33369 +Epoch: [23] [ 140/1319] eta: 1:03:21 lr: 2.3017303754954915e-05 loss: 0.0360 (0.0430) time: 3.2016 data: 0.0093 max mem: 33369 +Epoch: [23] [ 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time: 1:10:02 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 2:49:53 time: 3.9619 data: 3.8292 max mem: 33369 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 100/2573] eta: 0:04:53 time: 0.0810 data: 0.0017 max mem: 33369 +Test: [ 200/2573] eta: 0:03:56 time: 0.0788 data: 0.0016 max mem: 33369 +Test: [ 300/2573] eta: 0:03:30 time: 0.0822 data: 0.0013 max mem: 33369 +Test: [ 400/2573] eta: 0:03:14 time: 0.0816 data: 0.0016 max mem: 33369 +Test: [ 500/2573] eta: 0:03:01 time: 0.0792 data: 0.0014 max mem: 33369 +Test: [ 600/2573] eta: 0:02:50 time: 0.0801 data: 0.0014 max mem: 33369 +Test: [ 700/2573] eta: 0:02:41 time: 0.0796 data: 0.0014 max mem: 33369 +Test: [ 800/2573] eta: 0:02:31 time: 0.0823 data: 0.0014 max mem: 33369 +Test: [ 900/2573] eta: 0:02:22 time: 0.0812 data: 0.0015 max mem: 33369 +Test: [1000/2573] eta: 0:02:13 time: 0.0801 data: 0.0014 max mem: 33369 +Test: [1100/2573] eta: 0:02:03 time: 0.0797 data: 0.0016 max mem: 33369 +Test: [1200/2573] eta: 0:01:55 time: 0.0808 data: 0.0015 max mem: 33369 +Test: [1300/2573] eta: 0:01:46 time: 0.0803 data: 0.0014 max mem: 33369 +Test: [1400/2573] eta: 0:01:37 time: 0.0814 data: 0.0016 max mem: 33369 +Test: [1500/2573] eta: 0:01:29 time: 0.0811 data: 0.0015 max mem: 33369 +Test: [1600/2573] eta: 0:01:21 time: 0.0842 data: 0.0015 max mem: 33369 +Test: [1700/2573] eta: 0:01:12 time: 0.0811 data: 0.0016 max mem: 33369 +Test: [1800/2573] eta: 0:01:04 time: 0.0828 data: 0.0014 max mem: 33369 +Test: [1900/2573] eta: 0:00:55 time: 0.0801 data: 0.0016 max mem: 33369 +Test: [2000/2573] eta: 0:00:47 time: 0.0805 data: 0.0015 max mem: 33369 +Test: [2100/2573] eta: 0:00:39 time: 0.0817 data: 0.0011 max mem: 33369 +Test: [2200/2573] eta: 0:00:30 time: 0.0822 data: 0.0014 max mem: 33369 +Test: [2300/2573] eta: 0:00:22 time: 0.0844 data: 0.0016 max mem: 33369 +Test: [2400/2573] eta: 0:00:14 time: 0.0791 data: 0.0015 max mem: 33369 +Test: [2500/2573] eta: 0:00:06 time: 0.0809 data: 0.0015 max mem: 33369 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: Total time: 0:03:33 +Final results: +Mean IoU is 63.19 + + precision@0.5 = 71.28 + precision@0.6 = 65.83 + precision@0.7 = 58.64 + precision@0.8 = 46.65 + precision@0.9 = 23.22 + overall IoU = 61.40 + +Average object IoU 63.188976699185694 +Overall IoU 61.40068054199219 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [24] [ 0/1319] eta: 3:38:35 lr: 2.1918229762028934e-05 loss: 0.0729 (0.0729) time: 9.9433 data: 2.3834 max mem: 33369 +Epoch: [24] [ 10/1319] eta: 1:22:06 lr: 2.1908881861611456e-05 loss: 0.0396 (0.0408) time: 3.7636 data: 0.2257 max mem: 33369 +Epoch: [24] [ 20/1319] eta: 1:15:28 lr: 2.1899533518007982e-05 loss: 0.0390 (0.0414) time: 3.1630 data: 0.0098 max mem: 33369 +Epoch: [24] [ 30/1319] eta: 1:12:29 lr: 2.189018473098726e-05 loss: 0.0370 (0.0422) time: 3.1605 data: 0.0100 max mem: 33369 +Epoch: [24] [ 40/1319] eta: 1:10:53 lr: 2.188083550031783e-05 loss: 0.0353 (0.0411) time: 3.1576 data: 0.0089 max mem: 33369 +Epoch: [24] [ 50/1319] eta: 1:09:32 lr: 2.1871485825767997e-05 loss: 0.0367 (0.0418) time: 3.1549 data: 0.0081 max mem: 33369 +Epoch: [24] [ 60/1319] eta: 1:08:27 lr: 2.1862135707105826e-05 loss: 0.0398 (0.0408) time: 3.1324 data: 0.0091 max mem: 33369 +Epoch: [24] [ 70/1319] eta: 1:07:35 lr: 2.1852785144099174e-05 loss: 0.0319 (0.0402) time: 3.1401 data: 0.0088 max mem: 33369 +Epoch: [24] [ 80/1319] eta: 1:06:47 lr: 2.184343413651562e-05 loss: 0.0319 (0.0397) time: 3.1489 data: 0.0083 max mem: 33369 +Epoch: [24] [ 90/1319] eta: 1:06:02 lr: 2.1834082684122557e-05 loss: 0.0351 (0.0413) time: 3.1437 data: 0.0090 max mem: 33369 +Epoch: [24] [ 100/1319] eta: 1:05:28 lr: 2.1824730786687132e-05 loss: 0.0385 (0.0411) time: 3.1757 data: 0.0090 max mem: 33369 +Epoch: [24] [ 110/1319] eta: 1:04:50 lr: 2.181537844397624e-05 loss: 0.0372 (0.0410) time: 3.1899 data: 0.0087 max mem: 33369 +Epoch: [24] [ 120/1319] eta: 1:04:13 lr: 2.1806025655756576e-05 loss: 0.0383 (0.0410) time: 3.1702 data: 0.0091 max mem: 33369 +Epoch: [24] [ 130/1319] eta: 1:03:35 lr: 2.1796672421794575e-05 loss: 0.0383 (0.0407) time: 3.1601 data: 0.0091 max mem: 33369 +Epoch: [24] [ 140/1319] eta: 1:02:58 lr: 2.1787318741856443e-05 loss: 0.0350 (0.0407) time: 3.1517 data: 0.0094 max mem: 33369 +Epoch: [24] [ 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33369 +Epoch: [24] [ 230/1319] eta: 0:58:06 lr: 2.1703115514795925e-05 loss: 0.0409 (0.0425) time: 3.1756 data: 0.0084 max mem: 33369 +Epoch: [24] [ 240/1319] eta: 0:57:35 lr: 2.1693757362186356e-05 loss: 0.0462 (0.0430) time: 3.1970 data: 0.0092 max mem: 33369 +Epoch: [24] [ 250/1319] eta: 0:57:02 lr: 2.1684398761013434e-05 loss: 0.0434 (0.0430) time: 3.1963 data: 0.0095 max mem: 33369 +Epoch: [24] [ 260/1319] eta: 0:56:28 lr: 2.1675039711040532e-05 loss: 0.0388 (0.0430) time: 3.1754 data: 0.0093 max mem: 33369 +Epoch: [24] [ 270/1319] eta: 0:55:56 lr: 2.166568021203079e-05 loss: 0.0388 (0.0431) time: 3.1825 data: 0.0096 max mem: 33369 +Epoch: [24] [ 280/1319] eta: 0:55:24 lr: 2.1656320263747106e-05 loss: 0.0366 (0.0428) time: 3.1902 data: 0.0090 max mem: 33369 +Epoch: [24] [ 290/1319] eta: 0:54:52 lr: 2.164695986595215e-05 loss: 0.0366 (0.0435) time: 3.1981 data: 0.0091 max mem: 33369 +Epoch: [24] [ 300/1319] eta: 0:54:19 lr: 2.163759901840832e-05 loss: 0.0397 (0.0435) time: 3.1861 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eta: 0:20:38 lr: 2.104694837585335e-05 loss: 0.0339 (0.0434) time: 3.1601 data: 0.0102 max mem: 33369 +Epoch: [24] [ 940/1319] eta: 0:20:06 lr: 2.1037558238977907e-05 loss: 0.0383 (0.0434) time: 3.1684 data: 0.0092 max mem: 33369 +Epoch: [24] [ 950/1319] eta: 0:19:35 lr: 2.1028167636379597e-05 loss: 0.0383 (0.0434) time: 3.1898 data: 0.0089 max mem: 33369 +Epoch: [24] [ 960/1319] eta: 0:19:03 lr: 2.1018776567804213e-05 loss: 0.0380 (0.0434) time: 3.1910 data: 0.0098 max mem: 33369 +Epoch: [24] [ 970/1319] eta: 0:18:31 lr: 2.1009385032997278e-05 loss: 0.0356 (0.0434) time: 3.1740 data: 0.0113 max mem: 33369 +Epoch: [24] [ 980/1319] eta: 0:17:59 lr: 2.0999993031704057e-05 loss: 0.0361 (0.0433) time: 3.1506 data: 0.0107 max mem: 33369 +Epoch: [24] [ 990/1319] eta: 0:17:27 lr: 2.0990600563669546e-05 loss: 0.0369 (0.0433) time: 3.1519 data: 0.0100 max mem: 33369 +Epoch: [24] [1000/1319] eta: 0:16:55 lr: 2.0981207628638462e-05 loss: 0.0399 (0.0433) time: 3.1823 data: 0.0097 max mem: 33369 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data: 0.0086 max mem: 33369 +Epoch: [24] [1090/1319] eta: 0:12:09 lr: 2.0896650156261064e-05 loss: 0.0353 (0.0432) time: 3.2086 data: 0.0091 max mem: 33369 +Epoch: [24] [1100/1319] eta: 0:11:37 lr: 2.0887252537165494e-05 loss: 0.0375 (0.0432) time: 3.2080 data: 0.0086 max mem: 33369 +Epoch: [24] [1110/1319] eta: 0:11:05 lr: 2.087785444824768e-05 loss: 0.0399 (0.0434) time: 3.1966 data: 0.0087 max mem: 33369 +Epoch: [24] [1120/1319] eta: 0:10:33 lr: 2.086845588924912e-05 loss: 0.0413 (0.0434) time: 3.1709 data: 0.0093 max mem: 33369 +Epoch: [24] [1130/1319] eta: 0:10:01 lr: 2.0859056859911038e-05 loss: 0.0419 (0.0434) time: 3.1744 data: 0.0095 max mem: 33369 +Epoch: [24] [1140/1319] eta: 0:09:29 lr: 2.0849657359974397e-05 loss: 0.0458 (0.0435) time: 3.1877 data: 0.0091 max mem: 33369 +Epoch: [24] [1150/1319] eta: 0:08:58 lr: 2.084025738917989e-05 loss: 0.0409 (0.0434) time: 3.1825 data: 0.0092 max mem: 33369 +Epoch: [24] [1160/1319] eta: 0:08:26 lr: 2.083085694726791e-05 loss: 0.0380 (0.0434) time: 3.1858 data: 0.0098 max mem: 33369 +Epoch: [24] [1170/1319] eta: 0:07:54 lr: 2.0821456033978605e-05 loss: 0.0407 (0.0434) time: 3.1981 data: 0.0094 max mem: 33369 +Epoch: [24] [1180/1319] eta: 0:07:22 lr: 2.0812054649051834e-05 loss: 0.0407 (0.0434) time: 3.1888 data: 0.0094 max mem: 33369 +Epoch: [24] [1190/1319] eta: 0:06:50 lr: 2.0802652792227197e-05 loss: 0.0390 (0.0434) time: 3.1685 data: 0.0097 max mem: 33369 +Epoch: [24] [1200/1319] eta: 0:06:18 lr: 2.0793250463244006e-05 loss: 0.0425 (0.0435) time: 3.1694 data: 0.0091 max mem: 33369 +Epoch: [24] [1210/1319] eta: 0:05:47 lr: 2.07838476618413e-05 loss: 0.0453 (0.0435) time: 3.1913 data: 0.0084 max mem: 33369 +Epoch: [24] [1220/1319] eta: 0:05:15 lr: 2.077444438775784e-05 loss: 0.0444 (0.0437) time: 3.1997 data: 0.0090 max mem: 33369 +Epoch: [24] [1230/1319] eta: 0:04:43 lr: 2.0765040640732118e-05 loss: 0.0486 (0.0437) time: 3.1644 data: 0.0093 max mem: 33369 +Epoch: [24] [1240/1319] eta: 0:04:11 lr: 2.0755636420502354e-05 loss: 0.0471 (0.0437) time: 3.1459 data: 0.0091 max mem: 33369 +Epoch: [24] [1250/1319] eta: 0:03:39 lr: 2.074623172680648e-05 loss: 0.0426 (0.0437) time: 3.1497 data: 0.0092 max mem: 33369 +Epoch: [24] [1260/1319] eta: 0:03:07 lr: 2.0736826559382146e-05 loss: 0.0418 (0.0437) time: 3.1717 data: 0.0092 max mem: 33369 +Epoch: [24] [1270/1319] eta: 0:02:35 lr: 2.072742091796674e-05 loss: 0.0463 (0.0438) time: 3.1857 data: 0.0093 max mem: 33369 +Epoch: [24] [1280/1319] eta: 0:02:04 lr: 2.071801480229737e-05 loss: 0.0438 (0.0438) time: 3.1741 data: 0.0099 max mem: 33369 +Epoch: [24] [1290/1319] eta: 0:01:32 lr: 2.0708608212110852e-05 loss: 0.0451 (0.0438) time: 3.1857 data: 0.0091 max mem: 33369 +Epoch: [24] [1300/1319] eta: 0:01:00 lr: 2.0699201147143737e-05 loss: 0.0464 (0.0440) time: 3.1976 data: 0.0087 max mem: 33369 +Epoch: [24] [1310/1319] eta: 0:00:28 lr: 2.0689793607132295e-05 loss: 0.0401 (0.0439) time: 3.1822 data: 0.0082 max mem: 33369 +Epoch: [24] Total time: 1:09:59 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 2:42:45 time: 3.7953 data: 3.4451 max mem: 33369 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 100/2573] eta: 0:04:46 time: 0.0783 data: 0.0015 max mem: 33369 +Test: [ 200/2573] eta: 0:03:52 time: 0.0790 data: 0.0015 max mem: 33369 +Test: [ 300/2573] eta: 0:03:28 time: 0.0814 data: 0.0015 max mem: 33369 +Test: [ 400/2573] eta: 0:03:13 time: 0.0819 data: 0.0014 max mem: 33369 +Test: [ 500/2573] eta: 0:03:01 time: 0.0796 data: 0.0015 max mem: 33369 +Test: [ 600/2573] eta: 0:02:50 time: 0.0804 data: 0.0017 max mem: 33369 +Test: [ 700/2573] eta: 0:02:40 time: 0.0801 data: 0.0015 max mem: 33369 +Test: [ 800/2573] eta: 0:02:30 time: 0.0841 data: 0.0018 max mem: 33369 +Test: [ 900/2573] eta: 0:02:21 time: 0.0808 data: 0.0014 max mem: 33369 +Test: [1000/2573] eta: 0:02:12 time: 0.0800 data: 0.0015 max mem: 33369 +Test: [1100/2573] eta: 0:02:03 time: 0.0824 data: 0.0017 max mem: 33369 +Test: [1200/2573] eta: 0:01:55 time: 0.0813 data: 0.0014 max mem: 33369 +Test: [1300/2573] eta: 0:01:46 time: 0.0836 data: 0.0019 max mem: 33369 +Test: [1400/2573] eta: 0:01:38 time: 0.0796 data: 0.0016 max mem: 33369 +Test: [1500/2573] eta: 0:01:29 time: 0.0823 data: 0.0015 max mem: 33369 +Test: [1600/2573] eta: 0:01:21 time: 0.0842 data: 0.0014 max mem: 33369 +Test: [1700/2573] eta: 0:01:12 time: 0.0814 data: 0.0017 max mem: 33369 +Test: [1800/2573] eta: 0:01:04 time: 0.0833 data: 0.0015 max mem: 33369 +Test: [1900/2573] eta: 0:00:55 time: 0.0817 data: 0.0017 max mem: 33369 +Test: [2000/2573] eta: 0:00:47 time: 0.0814 data: 0.0015 max mem: 33369 +Test: [2100/2573] eta: 0:00:39 time: 0.0829 data: 0.0014 max mem: 33369 +Test: [2200/2573] eta: 0:00:30 time: 0.0820 data: 0.0014 max mem: 33369 +Test: [2300/2573] eta: 0:00:22 time: 0.0830 data: 0.0015 max mem: 33369 +Test: [2400/2573] eta: 0:00:14 time: 0.0780 data: 0.0014 max mem: 33369 +Test: [2500/2573] eta: 0:00:06 time: 0.0822 data: 0.0015 max mem: 33369 +Test: Total time: 0:03:32 +Final results: +Mean IoU is 64.20 + + precision@0.5 = 72.08 + precision@0.6 = 65.97 + precision@0.7 = 58.03 + precision@0.8 = 46.55 + precision@0.9 = 23.24 + overall IoU = 61.94 + +Average object IoU 64.2043389722264 +Overall IoU 61.94330596923828 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [25] [ 0/1319] eta: 3:42:42 lr: 2.0681326414740886e-05 loss: 0.0378 (0.0378) time: 10.1304 data: 2.8803 max mem: 33369 +Epoch: [25] [ 10/1319] eta: 1:23:14 lr: 2.0671917971417626e-05 loss: 0.0316 (0.0374) time: 3.8153 data: 0.2696 max mem: 33369 +Epoch: [25] [ 20/1319] eta: 1:16:18 lr: 2.0662509052283616e-05 loss: 0.0320 (0.0377) time: 3.1945 data: 0.0092 max mem: 33369 +Epoch: [25] [ 30/1319] eta: 1:13:29 lr: 2.0653099657074033e-05 loss: 0.0321 (0.0373) time: 3.2041 data: 0.0103 max mem: 33369 +Epoch: [25] [ 40/1319] eta: 1:11:33 lr: 2.064368978552377e-05 loss: 0.0313 (0.0381) time: 3.1801 data: 0.0102 max mem: 33369 +Epoch: [25] [ 50/1319] eta: 1:10:21 lr: 2.0634279437367437e-05 loss: 0.0359 (0.0390) time: 3.1809 data: 0.0098 max mem: 33369 +Epoch: [25] [ 60/1319] eta: 1:09:20 lr: 2.0624868612339364e-05 loss: 0.0359 (0.0382) time: 3.1971 data: 0.0095 max mem: 33369 +Epoch: [25] [ 70/1319] eta: 1:08:27 lr: 2.0615457310173584e-05 loss: 0.0324 (0.0388) time: 3.1901 data: 0.0093 max mem: 33369 +Epoch: [25] [ 80/1319] eta: 1:07:37 lr: 2.0606045530603866e-05 loss: 0.0416 (0.0396) time: 3.1844 data: 0.0097 max mem: 33369 +Epoch: [25] [ 90/1319] eta: 1:06:53 lr: 2.059663327336368e-05 loss: 0.0424 (0.0399) time: 3.1856 data: 0.0100 max mem: 33369 +Epoch: [25] [ 100/1319] eta: 1:06:10 lr: 2.058722053818622e-05 loss: 0.0398 (0.0406) time: 3.1852 data: 0.0109 max mem: 33369 +Epoch: [25] [ 110/1319] eta: 1:05:31 lr: 2.0577807324804403e-05 loss: 0.0414 (0.0406) time: 3.1882 data: 0.0109 max mem: 33369 +Epoch: [25] [ 120/1319] eta: 1:04:51 lr: 2.0568393632950847e-05 loss: 0.0414 (0.0407) time: 3.1887 data: 0.0101 max mem: 33369 +Epoch: [25] [ 130/1319] eta: 1:04:13 lr: 2.055897946235788e-05 loss: 0.0415 (0.0410) time: 3.1793 data: 0.0093 max mem: 33369 +Epoch: [25] [ 140/1319] eta: 1:03:36 lr: 2.054956481275756e-05 loss: 0.0372 (0.0407) time: 3.1878 data: 0.0084 max mem: 33369 +Epoch: [25] [ 150/1319] eta: 1:02:59 lr: 2.0540149683881653e-05 loss: 0.0372 (0.0409) time: 3.1840 data: 0.0088 max mem: 33369 +Epoch: [25] [ 160/1319] eta: 1:02:26 lr: 2.0530734075461633e-05 loss: 0.0382 (0.0406) time: 3.1974 data: 0.0087 max mem: 33369 +Epoch: [25] [ 170/1319] eta: 1:01:52 lr: 2.05213179872287e-05 loss: 0.0357 (0.0418) time: 3.2152 data: 0.0086 max mem: 33369 +Epoch: [25] [ 180/1319] eta: 1:01:21 lr: 2.051190141891374e-05 loss: 0.0326 (0.0414) time: 3.2321 data: 0.0088 max mem: 33369 +Epoch: [25] [ 190/1319] eta: 1:00:46 lr: 2.050248437024738e-05 loss: 0.0326 (0.0414) time: 3.2233 data: 0.0090 max mem: 33369 +Epoch: [25] [ 200/1319] eta: 1:00:10 lr: 2.049306684095994e-05 loss: 0.0372 (0.0412) time: 3.1762 data: 0.0095 max mem: 33369 +Epoch: [25] [ 210/1319] eta: 0:59:35 lr: 2.048364883078146e-05 loss: 0.0338 (0.0411) time: 3.1680 data: 0.0091 max mem: 33369 +Epoch: [25] [ 220/1319] eta: 0:59:01 lr: 2.0474230339441687e-05 loss: 0.0373 (0.0412) time: 3.1793 data: 0.0090 max mem: 33369 +Epoch: [25] [ 230/1319] eta: 0:58:27 lr: 2.0464811366670074e-05 loss: 0.0373 (0.0410) time: 3.1803 data: 0.0095 max mem: 33369 +Epoch: [25] [ 240/1319] eta: 0:57:54 lr: 2.0455391912195788e-05 loss: 0.0329 (0.0407) time: 3.1978 data: 0.0099 max mem: 33369 +Epoch: [25] [ 250/1319] eta: 0:57:19 lr: 2.0445971975747706e-05 loss: 0.0315 (0.0409) time: 3.1849 data: 0.0105 max mem: 33369 +Epoch: [25] [ 260/1319] eta: 0:56:44 lr: 2.0436551557054405e-05 loss: 0.0405 (0.0408) time: 3.1464 data: 0.0099 max mem: 33369 +Epoch: [25] [ 270/1319] eta: 0:56:10 lr: 2.0427130655844186e-05 loss: 0.0369 (0.0407) time: 3.1489 data: 0.0097 max mem: 33369 +Epoch: [25] [ 280/1319] eta: 0:55:38 lr: 2.041770927184505e-05 loss: 0.0369 (0.0406) time: 3.1919 data: 0.0102 max mem: 33369 +Epoch: [25] [ 290/1319] eta: 0:55:04 lr: 2.0408287404784693e-05 loss: 0.0361 (0.0406) time: 3.1934 data: 0.0095 max mem: 33369 +Epoch: [25] [ 300/1319] eta: 0:54:31 lr: 2.0398865054390533e-05 loss: 0.0368 (0.0408) time: 3.1717 data: 0.0094 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33369 +Epoch: [25] [1090/1319] eta: 0:12:33 lr: 1.9652948254317503e-05 loss: 0.0415 (0.0420) time: 3.6004 data: 0.0129 max mem: 33369 +Epoch: [25] [1100/1319] eta: 0:12:01 lr: 1.9643486327172213e-05 loss: 0.0431 (0.0420) time: 3.7527 data: 0.0136 max mem: 33369 +Epoch: [25] [1110/1319] eta: 0:11:29 lr: 1.9634023893594635e-05 loss: 0.0396 (0.0419) time: 3.7753 data: 0.0141 max mem: 33369 +Epoch: [25] [1120/1319] eta: 0:10:57 lr: 1.9624560953286446e-05 loss: 0.0307 (0.0419) time: 3.5905 data: 0.0128 max mem: 33369 +Epoch: [25] [1130/1319] eta: 0:10:24 lr: 1.961509750594899e-05 loss: 0.0379 (0.0419) time: 3.4576 data: 0.0111 max mem: 33369 +Epoch: [25] [1140/1319] eta: 0:09:51 lr: 1.9605633551283273e-05 loss: 0.0447 (0.0419) time: 3.5357 data: 0.0098 max mem: 33369 +Epoch: [25] [1150/1319] eta: 0:09:19 lr: 1.9596169088989948e-05 loss: 0.0435 (0.0419) time: 3.7790 data: 0.0115 max mem: 33369 +Epoch: [25] [1160/1319] eta: 0:08:47 lr: 1.9586704118769358e-05 loss: 0.0340 (0.0418) time: 3.8201 data: 0.0122 max mem: 33369 +Epoch: [25] [1170/1319] eta: 0:08:14 lr: 1.9577238640321492e-05 loss: 0.0341 (0.0418) time: 3.7285 data: 0.0118 max mem: 33369 +Epoch: [25] [1180/1319] eta: 0:07:41 lr: 1.9567772653346e-05 loss: 0.0411 (0.0419) time: 3.7261 data: 0.0124 max mem: 33369 +Epoch: [25] [1190/1319] eta: 0:07:08 lr: 1.9558306157542204e-05 loss: 0.0422 (0.0420) time: 3.7297 data: 0.0123 max mem: 33369 +Epoch: [25] [1200/1319] eta: 0:06:35 lr: 1.9548839152609067e-05 loss: 0.0477 (0.0421) time: 3.6741 data: 0.0134 max mem: 33369 +Epoch: [25] [1210/1319] eta: 0:06:02 lr: 1.9539371638245233e-05 loss: 0.0393 (0.0421) time: 3.6424 data: 0.0141 max mem: 33369 +Epoch: [25] [1220/1319] eta: 0:05:29 lr: 1.952990361414899e-05 loss: 0.0393 (0.0421) time: 3.6770 data: 0.0139 max mem: 33369 +Epoch: [25] [1230/1319] eta: 0:04:56 lr: 1.9520435080018294e-05 loss: 0.0383 (0.0421) time: 3.7196 data: 0.0134 max mem: 33369 +Epoch: [25] [1240/1319] eta: 0:04:23 lr: 1.9510966035550763e-05 loss: 0.0373 (0.0421) time: 3.6563 data: 0.0129 max mem: 33369 +Epoch: [25] [1250/1319] eta: 0:03:50 lr: 1.9501496480443652e-05 loss: 0.0394 (0.0421) time: 3.5865 data: 0.0143 max mem: 33369 +Epoch: [25] [1260/1319] eta: 0:03:17 lr: 1.9492026414393892e-05 loss: 0.0394 (0.0421) time: 3.6187 data: 0.0149 max mem: 33369 +Epoch: [25] [1270/1319] eta: 0:02:43 lr: 1.9482555837098063e-05 loss: 0.0394 (0.0421) time: 3.7060 data: 0.0143 max mem: 33369 +Epoch: [25] [1280/1319] eta: 0:02:10 lr: 1.9473084748252403e-05 loss: 0.0405 (0.0421) time: 3.6978 data: 0.0132 max mem: 33369 +Epoch: [25] [1290/1319] eta: 0:01:37 lr: 1.9463613147552807e-05 loss: 0.0410 (0.0422) time: 3.6432 data: 0.0128 max mem: 33369 +Epoch: [25] [1300/1319] eta: 0:01:03 lr: 1.9454141034694828e-05 loss: 0.0388 (0.0421) time: 3.6827 data: 0.0123 max mem: 33369 +Epoch: [25] [1310/1319] eta: 0:00:30 lr: 1.9444668409373652e-05 loss: 0.0317 (0.0421) time: 3.5990 data: 0.0103 max mem: 33369 +Epoch: [25] Total time: 1:13:45 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 2:44:35 time: 3.8381 data: 3.4483 max mem: 33369 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 100/2573] eta: 0:05:12 time: 0.0884 data: 0.0023 max mem: 33369 +Test: [ 200/2573] eta: 0:04:14 time: 0.0874 data: 0.0023 max mem: 33369 +Test: [ 300/2573] eta: 0:03:44 time: 0.0842 data: 0.0015 max mem: 33369 +Test: [ 400/2573] eta: 0:03:25 time: 0.0859 data: 0.0017 max mem: 33369 +Test: [ 500/2573] eta: 0:03:11 time: 0.0828 data: 0.0017 max mem: 33369 +Test: [ 600/2573] eta: 0:02:59 time: 0.0810 data: 0.0016 max mem: 33369 +Test: [ 700/2573] eta: 0:02:48 time: 0.0871 data: 0.0019 max mem: 33369 +Test: [ 800/2573] eta: 0:02:39 time: 0.0864 data: 0.0019 max mem: 33369 +Test: [ 900/2573] eta: 0:02:29 time: 0.0826 data: 0.0016 max mem: 33369 +Test: [1000/2573] eta: 0:02:19 time: 0.0819 data: 0.0016 max mem: 33369 +Test: [1100/2573] eta: 0:02:09 time: 0.0846 data: 0.0019 max mem: 33369 +Test: [1200/2573] eta: 0:02:00 time: 0.0831 data: 0.0016 max mem: 33369 +Test: [1300/2573] eta: 0:01:51 time: 0.0835 data: 0.0017 max mem: 33369 +Test: [1400/2573] eta: 0:01:42 time: 0.0846 data: 0.0019 max mem: 33369 +Test: [1500/2573] eta: 0:01:33 time: 0.0898 data: 0.0022 max mem: 33369 +Test: [1600/2573] eta: 0:01:24 time: 0.0862 data: 0.0017 max mem: 33369 +Test: [1700/2573] eta: 0:01:15 time: 0.0834 data: 0.0016 max mem: 33369 +Test: [1800/2573] eta: 0:01:07 time: 0.0876 data: 0.0021 max mem: 33369 +Test: [1900/2573] eta: 0:00:58 time: 0.0807 data: 0.0015 max mem: 33369 +Test: [2000/2573] eta: 0:00:49 time: 0.0818 data: 0.0015 max mem: 33369 +Test: [2100/2573] eta: 0:00:40 time: 0.0846 data: 0.0016 max mem: 33369 +Test: [2200/2573] eta: 0:00:32 time: 0.0886 data: 0.0018 max mem: 33369 +Test: [2300/2573] eta: 0:00:23 time: 0.0894 data: 0.0022 max mem: 33369 +Test: [2400/2573] eta: 0:00:14 time: 0.0882 data: 0.0022 max mem: 33369 +Test: [2500/2573] eta: 0:00:06 time: 0.0888 data: 0.0021 max mem: 33369 +Test: Total time: 0:03:42 +Final results: +Mean IoU is 63.93 + + precision@0.5 = 71.53 + precision@0.6 = 66.01 + precision@0.7 = 59.33 + precision@0.8 = 47.88 + precision@0.9 = 23.47 + overall IoU = 62.08 + +Average object IoU 63.93399950071736 +Overall IoU 62.078678131103516 +Better epoch: 25 + +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [26] [ 0/1319] eta: 2:17:26 lr: 1.943614260817638e-05 loss: 0.0338 (0.0338) time: 6.2524 data: 2.5325 max mem: 33369 +Epoch: [26] [ 10/1319] eta: 1:21:13 lr: 1.9426669008334188e-05 loss: 0.0337 (0.0377) time: 3.7229 data: 0.2390 max mem: 33369 +Epoch: [26] [ 20/1319] eta: 1:17:12 lr: 1.941719489514293e-05 loss: 0.0334 (0.0417) time: 3.4318 data: 0.0103 max mem: 33369 +Epoch: [26] [ 30/1319] eta: 1:16:03 lr: 1.9407720268296455e-05 loss: 0.0380 (0.0408) time: 3.4406 data: 0.0108 max mem: 33369 +Epoch: [26] [ 40/1319] eta: 1:14:56 lr: 1.9398245127488253e-05 loss: 0.0377 (0.0401) time: 3.4631 data: 0.0106 max mem: 33369 +Epoch: [26] [ 50/1319] eta: 1:13:46 lr: 1.9388769472411493e-05 loss: 0.0334 (0.0404) time: 3.4060 data: 0.0107 max mem: 33369 +Epoch: [26] [ 60/1319] eta: 1:13:01 lr: 1.9379293302758954e-05 loss: 0.0344 (0.0401) time: 3.4068 data: 0.0112 max mem: 33369 +Epoch: [26] [ 70/1319] eta: 1:12:30 lr: 1.936981661822309e-05 loss: 0.0345 (0.0397) time: 3.4720 data: 0.0111 max mem: 33369 +Epoch: [26] [ 80/1319] eta: 1:12:03 lr: 1.9360339418495996e-05 loss: 0.0377 (0.0393) time: 3.5183 data: 0.0105 max mem: 33369 +Epoch: [26] [ 90/1319] eta: 1:11:30 lr: 1.935086170326942e-05 loss: 0.0352 (0.0387) time: 3.5180 data: 0.0120 max mem: 33369 +Epoch: [26] [ 100/1319] eta: 1:10:47 lr: 1.934138347223476e-05 loss: 0.0343 (0.0388) time: 3.4654 data: 0.0132 max mem: 33369 +Epoch: [26] [ 110/1319] eta: 1:10:17 lr: 1.9331904725083057e-05 loss: 0.0342 (0.0387) time: 3.4783 data: 0.0128 max mem: 33369 +Epoch: [26] [ 120/1319] eta: 1:09:57 lr: 1.9322425461504988e-05 loss: 0.0386 (0.0390) time: 3.5835 data: 0.0118 max mem: 33369 +Epoch: [26] [ 130/1319] eta: 1:09:15 lr: 1.931294568119089e-05 loss: 0.0410 (0.0399) time: 3.5304 data: 0.0106 max mem: 33369 +Epoch: [26] [ 140/1319] eta: 1:08:34 lr: 1.930346538383074e-05 loss: 0.0410 (0.0402) time: 3.4231 data: 0.0105 max mem: 33369 +Epoch: [26] [ 150/1319] eta: 1:08:01 lr: 1.9293984569114164e-05 loss: 0.0379 (0.0402) time: 3.4674 data: 0.0110 max mem: 33369 +Epoch: [26] [ 160/1319] eta: 1:07:19 lr: 1.9284503236730435e-05 loss: 0.0376 (0.0403) time: 3.4536 data: 0.0113 max mem: 33369 +Epoch: [26] [ 170/1319] eta: 1:06:42 lr: 1.927502138636845e-05 loss: 0.0401 (0.0412) time: 3.4199 data: 0.0115 max mem: 33369 +Epoch: [26] [ 180/1319] eta: 1:06:06 lr: 1.9265539017716765e-05 loss: 0.0449 (0.0410) time: 3.4608 data: 0.0110 max mem: 33369 +Epoch: [26] [ 190/1319] eta: 1:05:31 lr: 1.9256056130463582e-05 loss: 0.0449 (0.0415) time: 3.4778 data: 0.0101 max mem: 33369 +Epoch: [26] [ 200/1319] eta: 1:04:51 lr: 1.9246572724296735e-05 loss: 0.0356 (0.0411) time: 3.4292 data: 0.0109 max mem: 33369 +Epoch: [26] [ 210/1319] eta: 1:04:19 lr: 1.9237088798903708e-05 loss: 0.0342 (0.0409) time: 3.4565 data: 0.0120 max mem: 33369 +Epoch: [26] [ 220/1319] eta: 1:03:42 lr: 1.922760435397161e-05 loss: 0.0377 (0.0411) time: 3.4879 data: 0.0114 max mem: 33369 +Epoch: [26] [ 230/1319] eta: 1:03:16 lr: 1.9218119389187204e-05 loss: 0.0325 (0.0410) time: 3.5539 data: 0.0108 max mem: 33369 +Epoch: [26] [ 240/1319] eta: 1:02:40 lr: 1.9208633904236885e-05 loss: 0.0393 (0.0414) time: 3.5639 data: 0.0116 max mem: 33369 +Epoch: [26] [ 250/1319] eta: 1:02:02 lr: 1.9199147898806697e-05 loss: 0.0395 (0.0414) time: 3.4355 data: 0.0115 max mem: 33369 +Epoch: [26] [ 260/1319] eta: 1:01:24 lr: 1.9189661372582306e-05 loss: 0.0389 (0.0414) time: 3.4065 data: 0.0117 max mem: 33369 +Epoch: [26] [ 270/1319] eta: 1:00:53 lr: 1.918017432524904e-05 loss: 0.0368 (0.0413) time: 3.4934 data: 0.0113 max mem: 33369 +Epoch: [26] [ 280/1319] eta: 1:00:17 lr: 1.9170686756491828e-05 loss: 0.0350 (0.0412) time: 3.5063 data: 0.0100 max mem: 33369 +Epoch: [26] [ 290/1319] eta: 0:59:43 lr: 1.916119866599526e-05 loss: 0.0388 (0.0412) time: 3.4752 data: 0.0107 max mem: 33369 +Epoch: [26] [ 300/1319] eta: 0:59:08 lr: 1.9151710053443563e-05 loss: 0.0380 (0.0410) time: 3.4906 data: 0.0118 max mem: 33369 +Epoch: [26] [ 310/1319] eta: 0:58:34 lr: 1.9142220918520593e-05 loss: 0.0299 (0.0411) time: 3.4966 data: 0.0116 max mem: 33369 +Epoch: [26] [ 320/1319] eta: 0:57:59 lr: 1.9132731260909836e-05 loss: 0.0307 (0.0410) time: 3.5021 data: 0.0108 max mem: 33369 +Epoch: [26] [ 330/1319] eta: 0:57:22 lr: 1.9123241080294413e-05 loss: 0.0350 (0.0409) time: 3.4376 data: 0.0121 max mem: 33369 +Epoch: [26] [ 340/1319] eta: 0:56:48 lr: 1.9113750376357084e-05 loss: 0.0437 (0.0411) time: 3.4498 data: 0.0122 max mem: 33369 +Epoch: [26] [ 350/1319] eta: 0:56:11 lr: 1.9104259148780233e-05 loss: 0.0397 (0.0409) time: 3.4519 data: 0.0100 max mem: 33369 +Epoch: [26] [ 360/1319] eta: 0:55:36 lr: 1.909476739724589e-05 loss: 0.0327 (0.0408) time: 3.4359 data: 0.0105 max mem: 33369 +Epoch: [26] [ 370/1319] eta: 0:54:59 lr: 1.9085275121435705e-05 loss: 0.0377 (0.0407) time: 3.4320 data: 0.0116 max mem: 33369 +Epoch: [26] [ 380/1319] eta: 0:54:24 lr: 1.907578232103095e-05 loss: 0.0376 (0.0407) time: 3.4402 data: 0.0113 max mem: 33369 +Epoch: [26] [ 390/1319] eta: 0:53:48 lr: 1.906628899571255e-05 loss: 0.0356 (0.0408) time: 3.4480 data: 0.0117 max mem: 33369 +Epoch: [26] [ 400/1319] eta: 0:53:14 lr: 1.9056795145161037e-05 loss: 0.0356 (0.0408) time: 3.4575 data: 0.0122 max mem: 33369 +Epoch: [26] [ 410/1319] eta: 0:52:37 lr: 1.9047300769056588e-05 loss: 0.0348 (0.0408) time: 3.4326 data: 0.0122 max mem: 33369 +Epoch: [26] [ 420/1319] eta: 0:52:03 lr: 1.9037805867078998e-05 loss: 0.0377 (0.0408) time: 3.4468 data: 0.0123 max mem: 33369 +Epoch: [26] [ 430/1319] eta: 0:51:27 lr: 1.9028310438907695e-05 loss: 0.0315 (0.0406) time: 3.4684 data: 0.0121 max mem: 33369 +Epoch: [26] [ 440/1319] eta: 0:50:51 lr: 1.901881448422173e-05 loss: 0.0283 (0.0405) time: 3.4173 data: 0.0108 max mem: 33369 +Epoch: [26] [ 450/1319] eta: 0:50:18 lr: 1.900931800269978e-05 loss: 0.0303 (0.0404) time: 3.4787 data: 0.0101 max mem: 33369 +Epoch: [26] [ 460/1319] eta: 0:49:43 lr: 1.8999820994020145e-05 loss: 0.0336 (0.0403) time: 3.5021 data: 0.0112 max mem: 33369 +Epoch: [26] [ 470/1319] eta: 0:49:07 lr: 1.899032345786076e-05 loss: 0.0336 (0.0402) time: 3.4331 data: 0.0115 max mem: 33369 +Epoch: [26] [ 480/1319] eta: 0:48:32 lr: 1.8980825393899182e-05 loss: 0.0341 (0.0402) time: 3.4460 data: 0.0113 max mem: 33369 +Epoch: [26] [ 490/1319] eta: 0:47:59 lr: 1.897132680181258e-05 loss: 0.0356 (0.0402) time: 3.5170 data: 0.0114 max mem: 33369 +Epoch: [26] [ 500/1319] eta: 0:47:27 lr: 1.8961827681277747e-05 loss: 0.0339 (0.0401) time: 3.5880 data: 0.0114 max mem: 33369 +Epoch: [26] [ 510/1319] eta: 0:46:52 lr: 1.8952328031971114e-05 loss: 0.0361 (0.0400) time: 3.5659 data: 0.0112 max mem: 33369 +Epoch: [26] [ 520/1319] eta: 0:46:16 lr: 1.8942827853568723e-05 loss: 0.0388 (0.0401) time: 3.4368 data: 0.0107 max mem: 33369 +Epoch: [26] [ 530/1319] eta: 0:45:42 lr: 1.893332714574624e-05 loss: 0.0371 (0.0400) time: 3.4485 data: 0.0110 max mem: 33369 +Epoch: [26] [ 540/1319] eta: 0:45:09 lr: 1.892382590817894e-05 loss: 0.0317 (0.0399) time: 3.5463 data: 0.0113 max mem: 33369 +Epoch: [26] [ 550/1319] eta: 0:44:33 lr: 1.8914324140541728e-05 loss: 0.0311 (0.0400) time: 3.4960 data: 0.0104 max mem: 33369 +Epoch: [26] [ 560/1319] eta: 0:43:58 lr: 1.8904821842509134e-05 loss: 0.0361 (0.0400) time: 3.4200 data: 0.0107 max mem: 33369 +Epoch: [26] [ 570/1319] eta: 0:43:24 lr: 1.889531901375529e-05 loss: 0.0411 (0.0402) time: 3.4961 data: 0.0112 max mem: 33369 +Epoch: [26] [ 580/1319] eta: 0:42:49 lr: 1.888581565395396e-05 loss: 0.0399 (0.0402) time: 3.5045 data: 0.0117 max mem: 33369 +Epoch: [26] [ 590/1319] eta: 0:42:14 lr: 1.8876311762778523e-05 loss: 0.0333 (0.0402) time: 3.4576 data: 0.0122 max mem: 33369 +Epoch: [26] [ 600/1319] eta: 0:41:39 lr: 1.8866807339901958e-05 loss: 0.0394 (0.0402) time: 3.4524 data: 0.0120 max mem: 33369 +Epoch: [26] [ 610/1319] eta: 0:41:07 lr: 1.885730238499688e-05 loss: 0.0416 (0.0402) time: 3.5986 data: 0.0106 max mem: 33369 +Epoch: [26] [ 620/1319] eta: 0:40:34 lr: 1.8847796897735508e-05 loss: 0.0383 (0.0402) time: 3.6833 data: 0.0099 max mem: 33369 +Epoch: [26] [ 630/1319] eta: 0:39:59 lr: 1.8838290877789684e-05 loss: 0.0342 (0.0402) time: 3.5625 data: 0.0110 max mem: 33369 +Epoch: [26] [ 640/1319] eta: 0:39:24 lr: 1.882878432483085e-05 loss: 0.0338 (0.0401) time: 3.4790 data: 0.0110 max mem: 33369 +Epoch: [26] [ 650/1319] eta: 0:38:49 lr: 1.8819277238530077e-05 loss: 0.0367 (0.0402) time: 3.4245 data: 0.0114 max mem: 33369 +Epoch: [26] [ 660/1319] eta: 0:38:13 lr: 1.880976961855803e-05 loss: 0.0406 (0.0402) time: 3.3987 data: 0.0114 max mem: 33369 +Epoch: [26] [ 670/1319] eta: 0:37:38 lr: 1.8800261464585002e-05 loss: 0.0376 (0.0402) time: 3.4235 data: 0.0109 max mem: 33369 +Epoch: [26] [ 680/1319] eta: 0:37:02 lr: 1.8790752776280883e-05 loss: 0.0403 (0.0402) time: 3.4256 data: 0.0115 max mem: 33369 +Epoch: [26] [ 690/1319] eta: 0:36:27 lr: 1.8781243553315193e-05 loss: 0.0378 (0.0402) time: 3.4036 data: 0.0116 max mem: 33369 +Epoch: [26] [ 700/1319] eta: 0:35:51 lr: 1.8771733795357048e-05 loss: 0.0365 (0.0401) time: 3.4181 data: 0.0112 max mem: 33369 +Epoch: [26] [ 710/1319] eta: 0:35:16 lr: 1.876222350207516e-05 loss: 0.0375 (0.0402) time: 3.4034 data: 0.0116 max mem: 33369 +Epoch: [26] [ 720/1319] eta: 0:34:41 lr: 1.875271267313787e-05 loss: 0.0394 (0.0402) time: 3.4141 data: 0.0118 max mem: 33369 +Epoch: [26] [ 730/1319] eta: 0:34:06 lr: 1.8743201308213124e-05 loss: 0.0340 (0.0402) time: 3.4458 data: 0.0110 max mem: 33369 +Epoch: [26] [ 740/1319] eta: 0:33:32 lr: 1.8733689406968465e-05 loss: 0.0362 (0.0402) time: 3.4903 data: 0.0107 max mem: 33369 +Epoch: [26] [ 750/1319] eta: 0:32:57 lr: 1.872417696907106e-05 loss: 0.0362 (0.0401) time: 3.4912 data: 0.0105 max mem: 33369 +Epoch: [26] [ 760/1319] eta: 0:32:22 lr: 1.871466399418765e-05 loss: 0.0387 (0.0402) time: 3.4548 data: 0.0117 max mem: 33369 +Epoch: [26] [ 770/1319] eta: 0:31:48 lr: 1.870515048198461e-05 loss: 0.0452 (0.0403) time: 3.4951 data: 0.0119 max mem: 33369 +Epoch: [26] [ 780/1319] eta: 0:31:12 lr: 1.8695636432127905e-05 loss: 0.0385 (0.0403) time: 3.4551 data: 0.0111 max mem: 33369 +Epoch: [26] [ 790/1319] eta: 0:30:37 lr: 1.8686121844283114e-05 loss: 0.0332 (0.0403) time: 3.4256 data: 0.0114 max mem: 33369 +Epoch: [26] [ 800/1319] eta: 0:30:03 lr: 1.8676606718115407e-05 loss: 0.0332 (0.0403) time: 3.5205 data: 0.0112 max mem: 33369 +Epoch: [26] [ 810/1319] eta: 0:29:29 lr: 1.866709105328956e-05 loss: 0.0351 (0.0402) time: 3.5864 data: 0.0111 max mem: 33369 +Epoch: [26] [ 820/1319] eta: 0:28:54 lr: 1.8657574849469954e-05 loss: 0.0312 (0.0402) time: 3.5285 data: 0.0113 max mem: 33369 +Epoch: [26] [ 830/1319] eta: 0:28:19 lr: 1.864805810632056e-05 loss: 0.0363 (0.0401) time: 3.4354 data: 0.0111 max mem: 33369 +Epoch: [26] [ 840/1319] eta: 0:27:44 lr: 1.8638540823504965e-05 loss: 0.0337 (0.0401) time: 3.4230 data: 0.0108 max mem: 33369 +Epoch: [26] [ 850/1319] eta: 0:27:09 lr: 1.8629023000686338e-05 loss: 0.0316 (0.0400) time: 3.4330 data: 0.0115 max mem: 33369 +Epoch: [26] [ 860/1319] eta: 0:26:34 lr: 1.8619504637527467e-05 loss: 0.0367 (0.0399) time: 3.4282 data: 0.0124 max mem: 33369 +Epoch: [26] [ 870/1319] eta: 0:25:59 lr: 1.8609985733690715e-05 loss: 0.0377 (0.0399) time: 3.4438 data: 0.0112 max mem: 33369 +Epoch: [26] [ 880/1319] eta: 0:25:25 lr: 1.860046628883806e-05 loss: 0.0330 (0.0399) time: 3.4660 data: 0.0113 max mem: 33369 +Epoch: [26] [ 890/1319] eta: 0:24:50 lr: 1.859094630263106e-05 loss: 0.0375 (0.0399) time: 3.4617 data: 0.0122 max mem: 33369 +Epoch: [26] [ 900/1319] eta: 0:24:15 lr: 1.8581425774730882e-05 loss: 0.0338 (0.0398) time: 3.4840 data: 0.0122 max mem: 33369 +Epoch: [26] [ 910/1319] eta: 0:23:40 lr: 1.8571904704798292e-05 loss: 0.0338 (0.0399) time: 3.4616 data: 0.0133 max mem: 33369 +Epoch: [26] [ 920/1319] eta: 0:23:05 lr: 1.856238309249363e-05 loss: 0.0356 (0.0398) time: 3.4289 data: 0.0135 max mem: 33369 +Epoch: [26] [ 930/1319] eta: 0:22:31 lr: 1.855286093747684e-05 loss: 0.0356 (0.0399) time: 3.4592 data: 0.0124 max mem: 33369 +Epoch: [26] [ 940/1319] eta: 0:21:56 lr: 1.854333823940747e-05 loss: 0.0373 (0.0398) time: 3.5110 data: 0.0121 max mem: 33369 +Epoch: [26] [ 950/1319] eta: 0:21:21 lr: 1.853381499794464e-05 loss: 0.0335 (0.0398) time: 3.5089 data: 0.0116 max mem: 33369 +Epoch: [26] [ 960/1319] eta: 0:20:47 lr: 1.8524291212747084e-05 loss: 0.0356 (0.0398) time: 3.4748 data: 0.0114 max mem: 33369 +Epoch: [26] [ 970/1319] eta: 0:20:12 lr: 1.85147668834731e-05 loss: 0.0329 (0.0397) time: 3.4401 data: 0.0118 max mem: 33369 +Epoch: [26] [ 980/1319] eta: 0:19:37 lr: 1.8505242009780593e-05 loss: 0.0303 (0.0397) time: 3.4346 data: 0.0106 max mem: 33369 +Epoch: [26] [ 990/1319] eta: 0:19:02 lr: 1.8495716591327057e-05 loss: 0.0406 (0.0398) time: 3.4771 data: 0.0113 max mem: 33369 +Epoch: [26] [1000/1319] eta: 0:18:27 lr: 1.848619062776957e-05 loss: 0.0371 (0.0397) time: 3.4740 data: 0.0115 max mem: 33369 +Epoch: [26] [1010/1319] eta: 0:17:53 lr: 1.8476664118764797e-05 loss: 0.0328 (0.0397) time: 3.5193 data: 0.0102 max mem: 33369 +Epoch: [26] [1020/1319] eta: 0:17:18 lr: 1.8467137063969e-05 loss: 0.0320 (0.0397) time: 3.5136 data: 0.0110 max mem: 33369 +Epoch: [26] [1030/1319] eta: 0:16:43 lr: 1.8457609463038007e-05 loss: 0.0368 (0.0397) time: 3.4466 data: 0.0109 max mem: 33369 +Epoch: [26] [1040/1319] eta: 0:16:09 lr: 1.8448081315627246e-05 loss: 0.0342 (0.0397) time: 3.4885 data: 0.0114 max mem: 33369 +Epoch: [26] [1050/1319] eta: 0:15:34 lr: 1.843855262139173e-05 loss: 0.0307 (0.0396) time: 3.4891 data: 0.0121 max mem: 33369 +Epoch: [26] [1060/1319] eta: 0:14:59 lr: 1.8429023379986053e-05 loss: 0.0293 (0.0396) time: 3.4434 data: 0.0113 max mem: 33369 +Epoch: [26] [1070/1319] eta: 0:14:24 lr: 1.8419493591064395e-05 loss: 0.0338 (0.0396) time: 3.4249 data: 0.0122 max mem: 33369 +Epoch: [26] [1080/1319] eta: 0:13:50 lr: 1.840996325428051e-05 loss: 0.0356 (0.0396) time: 3.4724 data: 0.0124 max mem: 33369 +Epoch: [26] [1090/1319] eta: 0:13:15 lr: 1.840043236928774e-05 loss: 0.0388 (0.0396) time: 3.5071 data: 0.0115 max mem: 33369 +Epoch: [26] [1100/1319] eta: 0:12:40 lr: 1.839090093573901e-05 loss: 0.0424 (0.0398) time: 3.4489 data: 0.0104 max mem: 33369 +Epoch: [26] [1110/1319] eta: 0:12:05 lr: 1.838136895328682e-05 loss: 0.0403 (0.0398) time: 3.4455 data: 0.0101 max mem: 33369 +Epoch: [26] [1120/1319] eta: 0:11:31 lr: 1.8371836421583257e-05 loss: 0.0377 (0.0398) time: 3.5355 data: 0.0107 max mem: 33369 +Epoch: [26] [1130/1319] eta: 0:10:56 lr: 1.836230334027998e-05 loss: 0.0360 (0.0398) time: 3.5360 data: 0.0104 max mem: 33369 +Epoch: [26] [1140/1319] eta: 0:10:21 lr: 1.8352769709028224e-05 loss: 0.0360 (0.0399) time: 3.4489 data: 0.0103 max mem: 33369 +Epoch: [26] [1150/1319] eta: 0:09:47 lr: 1.8343235527478807e-05 loss: 0.0360 (0.0399) time: 3.4388 data: 0.0105 max mem: 33369 +Epoch: [26] [1160/1319] eta: 0:09:12 lr: 1.8333700795282125e-05 loss: 0.0369 (0.0399) time: 3.4675 data: 0.0102 max mem: 33369 +Epoch: [26] [1170/1319] eta: 0:08:37 lr: 1.832416551208814e-05 loss: 0.0361 (0.0399) time: 3.4791 data: 0.0110 max mem: 33369 +Epoch: [26] [1180/1319] eta: 0:08:02 lr: 1.8314629677546413e-05 loss: 0.0359 (0.0400) time: 3.4602 data: 0.0122 max mem: 33369 +Epoch: [26] [1190/1319] eta: 0:07:28 lr: 1.8305093291306038e-05 loss: 0.0379 (0.0400) time: 3.5398 data: 0.0121 max mem: 33369 +Epoch: [26] [1200/1319] eta: 0:06:53 lr: 1.829555635301572e-05 loss: 0.0363 (0.0401) time: 3.5275 data: 0.0117 max mem: 33369 +Epoch: [26] [1210/1319] eta: 0:06:18 lr: 1.8286018862323718e-05 loss: 0.0352 (0.0400) time: 3.4566 data: 0.0114 max mem: 33369 +Epoch: [26] [1220/1319] eta: 0:05:44 lr: 1.8276480818877866e-05 loss: 0.0359 (0.0400) time: 3.5358 data: 0.0110 max mem: 33369 +Epoch: [26] [1230/1319] eta: 0:05:09 lr: 1.8266942222325584e-05 loss: 0.0351 (0.0400) time: 3.5097 data: 0.0106 max mem: 33369 +Epoch: [26] [1240/1319] eta: 0:04:34 lr: 1.8257403072313833e-05 loss: 0.0351 (0.0400) time: 3.4159 data: 0.0108 max mem: 33369 +Epoch: [26] [1250/1319] eta: 0:03:59 lr: 1.8247863368489165e-05 loss: 0.0362 (0.0400) time: 3.4210 data: 0.0108 max mem: 33369 +Epoch: [26] [1260/1319] eta: 0:03:24 lr: 1.8238323110497695e-05 loss: 0.0342 (0.0400) time: 3.4404 data: 0.0110 max mem: 33369 +Epoch: [26] [1270/1319] eta: 0:02:50 lr: 1.822878229798511e-05 loss: 0.0350 (0.0400) time: 3.4438 data: 0.0118 max mem: 33369 +Epoch: [26] [1280/1319] eta: 0:02:15 lr: 1.821924093059666e-05 loss: 0.0350 (0.0400) time: 3.4435 data: 0.0109 max mem: 33369 +Epoch: [26] [1290/1319] eta: 0:01:40 lr: 1.8209699007977167e-05 loss: 0.0350 (0.0400) time: 3.4224 data: 0.0104 max mem: 33369 +Epoch: [26] [1300/1319] eta: 0:01:05 lr: 1.8200156529771002e-05 loss: 0.0357 (0.0400) time: 3.4387 data: 0.0123 max mem: 33369 +Epoch: [26] [1310/1319] eta: 0:00:31 lr: 1.819061349562212e-05 loss: 0.0424 (0.0400) time: 3.4666 data: 0.0111 max mem: 33369 +Epoch: [26] Total time: 1:16:22 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 3:12:55 time: 4.4988 data: 4.4041 max mem: 33369 +Test: [ 100/2573] eta: 0:05:17 time: 0.0876 data: 0.0022 max mem: 33369 +Test: [ 200/2573] eta: 0:04:12 time: 0.0810 data: 0.0017 max mem: 33369 +Test: [ 300/2573] eta: 0:03:42 time: 0.0844 data: 0.0016 max mem: 33369 +Test: [ 400/2573] eta: 0:03:25 time: 0.0857 data: 0.0017 max mem: 33369 +Test: [ 500/2573] eta: 0:03:11 time: 0.0861 data: 0.0018 max mem: 33369 +Test: [ 600/2573] eta: 0:02:59 time: 0.0847 data: 0.0017 max mem: 33369 +Test: [ 700/2573] eta: 0:02:49 time: 0.0834 data: 0.0016 max mem: 33369 +Test: [ 800/2573] eta: 0:02:39 time: 0.0837 data: 0.0016 max mem: 33369 +Test: [ 900/2573] eta: 0:02:29 time: 0.0855 data: 0.0019 max mem: 33369 +Test: [1000/2573] eta: 0:02:20 time: 0.0883 data: 0.0023 max mem: 33369 +Test: [1100/2573] eta: 0:02:11 time: 0.0830 data: 0.0017 max mem: 33369 +Test: [1200/2573] eta: 0:02:01 time: 0.0879 data: 0.0021 max mem: 33369 +Test: [1300/2573] eta: 0:01:52 time: 0.0890 data: 0.0022 max mem: 33369 +Test: [1400/2573] eta: 0:01:43 time: 0.0823 data: 0.0017 max mem: 33369 +Test: [1500/2573] eta: 0:01:34 time: 0.0887 data: 0.0021 max mem: 33369 +Test: [1600/2573] eta: 0:01:25 time: 0.0859 data: 0.0017 max mem: 33369 +Test: [1700/2573] eta: 0:01:16 time: 0.0884 data: 0.0020 max mem: 33369 +Test: [1800/2573] eta: 0:01:07 time: 0.0898 data: 0.0022 max mem: 33369 +Test: [1900/2573] eta: 0:00:59 time: 0.0816 data: 0.0017 max mem: 33369 +Test: [2000/2573] eta: 0:00:50 time: 0.0831 data: 0.0016 max mem: 33369 +Test: [2100/2573] eta: 0:00:41 time: 0.0894 data: 0.0022 max mem: 33369 +Test: [2200/2573] eta: 0:00:32 time: 0.0881 data: 0.0021 max mem: 33369 +Test: [2300/2573] eta: 0:00:23 time: 0.0890 data: 0.0022 max mem: 33369 +Test: [2400/2573] eta: 0:00:15 time: 0.0873 data: 0.0022 max mem: 33369 +Test: [2500/2573] eta: 0:00:06 time: 0.0865 data: 0.0019 max mem: 33369 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: Total time: 0:03:46 +Final results: +Mean IoU is 64.49 + + precision@0.5 = 72.61 + precision@0.6 = 66.99 + precision@0.7 = 60.36 + precision@0.8 = 48.00 + precision@0.9 = 23.79 + overall IoU = 62.54 + +Average object IoU 64.48845480748159 +Overall IoU 62.5352897644043 +Better epoch: 26 + +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [27] [ 0/1319] eta: 2:09:04 lr: 1.818202428926248e-05 loss: 0.0265 (0.0265) time: 5.8717 data: 2.2881 max mem: 33369 +Epoch: [27] [ 10/1319] eta: 1:21:39 lr: 1.817248019783995e-05 loss: 0.0310 (0.0339) time: 3.7430 data: 0.2178 max mem: 33369 +Epoch: [27] [ 20/1319] eta: 1:18:44 lr: 1.8162935549439682e-05 loss: 0.0319 (0.0363) time: 3.5253 data: 0.0108 max mem: 33369 +Epoch: [27] [ 30/1319] eta: 1:16:54 lr: 1.8153390343703928e-05 loss: 0.0404 (0.0385) time: 3.4896 data: 0.0116 max mem: 33369 +Epoch: [27] [ 40/1319] eta: 1:15:23 lr: 1.8143844580274487e-05 loss: 0.0385 (0.0376) time: 3.4313 data: 0.0118 max mem: 33369 +Epoch: [27] [ 50/1319] eta: 1:14:25 lr: 1.813429825879272e-05 loss: 0.0359 (0.0374) time: 3.4242 data: 0.0108 max mem: 33369 +Epoch: [27] [ 60/1319] eta: 1:13:44 lr: 1.8124751378899558e-05 loss: 0.0398 (0.0378) time: 3.4681 data: 0.0104 max mem: 33369 +Epoch: [27] [ 70/1319] eta: 1:13:09 lr: 1.811520394023548e-05 loss: 0.0384 (0.0381) time: 3.5047 data: 0.0107 max mem: 33369 +Epoch: [27] [ 80/1319] eta: 1:12:45 lr: 1.8105655942440525e-05 loss: 0.0377 (0.0386) time: 3.5530 data: 0.0110 max mem: 33369 +Epoch: [27] [ 90/1319] eta: 1:12:07 lr: 1.8096107385154294e-05 loss: 0.0349 (0.0385) time: 3.5457 data: 0.0114 max mem: 33369 +Epoch: [27] [ 100/1319] eta: 1:11:23 lr: 1.8086558268015952e-05 loss: 0.0353 (0.0389) time: 3.4730 data: 0.0117 max mem: 33369 +Epoch: [27] [ 110/1319] eta: 1:10:42 lr: 1.807700859066419e-05 loss: 0.0381 (0.0394) time: 3.4523 data: 0.0114 max mem: 33369 +Epoch: [27] [ 120/1319] eta: 1:09:55 lr: 1.8067458352737284e-05 loss: 0.0356 (0.0396) time: 3.4269 data: 0.0111 max mem: 33369 +Epoch: [27] [ 130/1319] eta: 1:09:14 lr: 1.8057907553873043e-05 loss: 0.0359 (0.0395) time: 3.4110 data: 0.0119 max mem: 33369 +Epoch: [27] [ 140/1319] eta: 1:09:07 lr: 1.8048356193708847e-05 loss: 0.0359 (0.0392) time: 3.6316 data: 0.0117 max mem: 33369 +Epoch: [27] [ 150/1319] eta: 1:08:26 lr: 1.803880427188162e-05 loss: 0.0289 (0.0388) time: 3.6372 data: 0.0100 max mem: 33369 +Epoch: [27] [ 160/1319] eta: 1:07:47 lr: 1.802925178802783e-05 loss: 0.0317 (0.0386) time: 3.4480 data: 0.0101 max mem: 33369 +Epoch: [27] [ 170/1319] eta: 1:07:06 lr: 1.8019698741783504e-05 loss: 0.0324 (0.0381) time: 3.4364 data: 0.0108 max mem: 33369 +Epoch: [27] [ 180/1319] eta: 1:06:35 lr: 1.8010145132784217e-05 loss: 0.0309 (0.0380) time: 3.4945 data: 0.0109 max mem: 33369 +Epoch: [27] [ 190/1319] eta: 1:05:58 lr: 1.8000590960665095e-05 loss: 0.0322 (0.0377) time: 3.5213 data: 0.0111 max mem: 33369 +Epoch: [27] [ 200/1319] eta: 1:05:18 lr: 1.7991036225060814e-05 loss: 0.0368 (0.0377) time: 3.4494 data: 0.0116 max mem: 33369 +Epoch: [27] [ 210/1319] eta: 1:04:41 lr: 1.7981480925605583e-05 loss: 0.0375 (0.0379) time: 3.4465 data: 0.0117 max mem: 33369 +Epoch: [27] [ 220/1319] eta: 1:04:08 lr: 1.7971925061933174e-05 loss: 0.0342 (0.0378) time: 3.4957 data: 0.0112 max mem: 33369 +Epoch: [27] [ 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mem: 33369 +Epoch: [27] [ 310/1319] eta: 0:58:56 lr: 1.7885896838454187e-05 loss: 0.0339 (0.0387) time: 3.5432 data: 0.0120 max mem: 33369 +Epoch: [27] [ 320/1319] eta: 0:58:17 lr: 1.787633531236672e-05 loss: 0.0339 (0.0385) time: 3.4175 data: 0.0120 max mem: 33369 +Epoch: [27] [ 330/1319] eta: 0:57:42 lr: 1.786677321800332e-05 loss: 0.0344 (0.0385) time: 3.4469 data: 0.0126 max mem: 33369 +Epoch: [27] [ 340/1319] eta: 0:57:07 lr: 1.7857210554992246e-05 loss: 0.0357 (0.0387) time: 3.4970 data: 0.0127 max mem: 33369 +Epoch: [27] [ 350/1319] eta: 0:56:32 lr: 1.7847647322961293e-05 loss: 0.0346 (0.0386) time: 3.4990 data: 0.0114 max mem: 33369 +Epoch: [27] [ 360/1319] eta: 0:55:56 lr: 1.783808352153779e-05 loss: 0.0360 (0.0389) time: 3.4772 data: 0.0106 max mem: 33369 +Epoch: [27] [ 370/1319] eta: 0:55:19 lr: 1.782851915034859e-05 loss: 0.0488 (0.0392) time: 3.4432 data: 0.0111 max mem: 33369 +Epoch: [27] [ 380/1319] eta: 0:54:43 lr: 1.78189542090201e-05 loss: 0.0371 (0.0391) time: 3.4496 data: 0.0109 max mem: 33369 +Epoch: [27] [ 390/1319] eta: 0:54:07 lr: 1.780938869717823e-05 loss: 0.0372 (0.0392) time: 3.4599 data: 0.0101 max mem: 33369 +Epoch: [27] [ 400/1319] eta: 0:53:30 lr: 1.779982261444845e-05 loss: 0.0372 (0.0391) time: 3.4350 data: 0.0105 max mem: 33369 +Epoch: [27] [ 410/1319] eta: 0:52:56 lr: 1.7790255960455746e-05 loss: 0.0340 (0.0392) time: 3.4588 data: 0.0112 max mem: 33369 +Epoch: [27] [ 420/1319] eta: 0:52:27 lr: 1.7780688734824637e-05 loss: 0.0374 (0.0393) time: 3.6491 data: 0.0110 max mem: 33369 +Epoch: [27] [ 430/1319] eta: 0:51:50 lr: 1.777112093717916e-05 loss: 0.0337 (0.0391) time: 3.6014 data: 0.0106 max mem: 33369 +Epoch: [27] [ 440/1319] eta: 0:51:14 lr: 1.7761552567142895e-05 loss: 0.0327 (0.0392) time: 3.4306 data: 0.0108 max mem: 33369 +Epoch: [27] [ 450/1319] eta: 0:50:41 lr: 1.7751983624338938e-05 loss: 0.0317 (0.0390) time: 3.5160 data: 0.0109 max mem: 33369 +Epoch: [27] [ 460/1319] eta: 0:50:03 lr: 1.7742414108389917e-05 loss: 0.0347 (0.0392) time: 3.4627 data: 0.0108 max mem: 33369 +Epoch: [27] [ 470/1319] eta: 0:49:27 lr: 1.7732844018917994e-05 loss: 0.0387 (0.0392) time: 3.3865 data: 0.0103 max mem: 33369 +Epoch: [27] [ 480/1319] eta: 0:48:50 lr: 1.7723273355544827e-05 loss: 0.0387 (0.0392) time: 3.4192 data: 0.0097 max mem: 33369 +Epoch: [27] [ 490/1319] eta: 0:48:15 lr: 1.771370211789162e-05 loss: 0.0382 (0.0392) time: 3.4476 data: 0.0108 max mem: 33369 +Epoch: [27] [ 500/1319] eta: 0:47:39 lr: 1.7704130305579097e-05 loss: 0.0382 (0.0392) time: 3.4339 data: 0.0110 max mem: 33369 +Epoch: [27] [ 510/1319] eta: 0:47:04 lr: 1.76945579182275e-05 loss: 0.0395 (0.0393) time: 3.4584 data: 0.0110 max mem: 33369 +Epoch: [27] [ 520/1319] eta: 0:46:29 lr: 1.7684984955456597e-05 loss: 0.0374 (0.0393) time: 3.5098 data: 0.0122 max mem: 33369 +Epoch: [27] [ 530/1319] eta: 0:45:55 lr: 1.767541141688566e-05 loss: 0.0355 (0.0392) time: 3.5056 data: 0.0119 max mem: 33369 +Epoch: [27] [ 540/1319] eta: 0:45:19 lr: 1.76658373021335e-05 loss: 0.0362 (0.0393) time: 3.4680 data: 0.0104 max mem: 33369 +Epoch: [27] [ 550/1319] eta: 0:44:43 lr: 1.7656262610818425e-05 loss: 0.0331 (0.0392) time: 3.4345 data: 0.0108 max mem: 33369 +Epoch: [27] [ 560/1319] eta: 0:44:08 lr: 1.7646687342558284e-05 loss: 0.0338 (0.0394) time: 3.4512 data: 0.0122 max mem: 33369 +Epoch: [27] [ 570/1319] eta: 0:43:32 lr: 1.7637111496970423e-05 loss: 0.0346 (0.0393) time: 3.4420 data: 0.0126 max mem: 33369 +Epoch: [27] [ 580/1319] eta: 0:42:57 lr: 1.762753507367172e-05 loss: 0.0321 (0.0392) time: 3.4379 data: 0.0125 max mem: 33369 +Epoch: [27] [ 590/1319] eta: 0:42:21 lr: 1.7617958072278543e-05 loss: 0.0331 (0.0392) time: 3.4079 data: 0.0129 max mem: 33369 +Epoch: [27] [ 600/1319] eta: 0:41:46 lr: 1.7608380492406792e-05 loss: 0.0333 (0.0392) time: 3.4399 data: 0.0124 max mem: 33369 +Epoch: [27] [ 610/1319] eta: 0:41:11 lr: 1.759880233367188e-05 loss: 0.0359 (0.0393) time: 3.5088 data: 0.0125 max mem: 33369 +Epoch: [27] [ 620/1319] eta: 0:40:36 lr: 1.758922359568872e-05 loss: 0.0380 (0.0393) time: 3.4660 data: 0.0130 max mem: 33369 +Epoch: [27] [ 630/1319] eta: 0:40:00 lr: 1.7579644278071756e-05 loss: 0.0407 (0.0393) time: 3.4156 data: 0.0122 max mem: 33369 +Epoch: [27] [ 640/1319] eta: 0:39:28 lr: 1.757006438043491e-05 loss: 0.0404 (0.0394) time: 3.5844 data: 0.0120 max mem: 33369 +Epoch: [27] [ 650/1319] eta: 0:38:53 lr: 1.7560483902391635e-05 loss: 0.0342 (0.0393) time: 3.6014 data: 0.0114 max mem: 33369 +Epoch: [27] [ 660/1319] eta: 0:38:18 lr: 1.7550902843554898e-05 loss: 0.0357 (0.0394) time: 3.4508 data: 0.0111 max mem: 33369 +Epoch: [27] [ 670/1319] eta: 0:37:43 lr: 1.7541321203537154e-05 loss: 0.0364 (0.0394) time: 3.4712 data: 0.0112 max mem: 33369 +Epoch: [27] [ 680/1319] eta: 0:37:08 lr: 1.753173898195038e-05 loss: 0.0353 (0.0394) time: 3.4915 data: 0.0115 max mem: 33369 +Epoch: [27] [ 690/1319] eta: 0:36:33 lr: 1.752215617840604e-05 loss: 0.0361 (0.0393) time: 3.4624 data: 0.0105 max mem: 33369 +Epoch: [27] [ 700/1319] eta: 0:35:58 lr: 1.751257279251512e-05 loss: 0.0361 (0.0393) time: 3.4572 data: 0.0098 max mem: 33369 +Epoch: [27] [ 710/1319] eta: 0:35:22 lr: 1.7502988823888103e-05 loss: 0.0336 (0.0393) time: 3.4539 data: 0.0102 max mem: 33369 +Epoch: [27] [ 720/1319] eta: 0:34:48 lr: 1.749340427213497e-05 loss: 0.0391 (0.0394) time: 3.4866 data: 0.0105 max mem: 33369 +Epoch: [27] [ 730/1319] eta: 0:34:13 lr: 1.7483819136865212e-05 loss: 0.0391 (0.0393) time: 3.5359 data: 0.0110 max mem: 33369 +Epoch: [27] [ 740/1319] eta: 0:33:38 lr: 1.7474233417687816e-05 loss: 0.0341 (0.0393) time: 3.4686 data: 0.0109 max mem: 33369 +Epoch: [27] [ 750/1319] eta: 0:33:03 lr: 1.7464647114211257e-05 loss: 0.0307 (0.0393) time: 3.4617 data: 0.0103 max mem: 33369 +Epoch: [27] [ 760/1319] eta: 0:32:30 lr: 1.7455060226043528e-05 loss: 0.0356 (0.0394) time: 3.5741 data: 0.0107 max mem: 33369 +Epoch: [27] [ 770/1319] eta: 0:31:54 lr: 1.744547275279211e-05 loss: 0.0336 (0.0393) time: 3.5291 data: 0.0104 max mem: 33369 +Epoch: [27] [ 780/1319] eta: 0:31:19 lr: 1.7435884694063984e-05 loss: 0.0344 (0.0394) time: 3.4130 data: 0.0097 max mem: 33369 +Epoch: [27] [ 790/1319] eta: 0:30:44 lr: 1.7426296049465625e-05 loss: 0.0403 (0.0395) time: 3.4230 data: 0.0107 max mem: 33369 +Epoch: [27] [ 800/1319] eta: 0:30:08 lr: 1.7416706818602993e-05 loss: 0.0370 (0.0395) time: 3.4417 data: 0.0109 max mem: 33369 +Epoch: [27] [ 810/1319] eta: 0:29:33 lr: 1.7407117001081557e-05 loss: 0.0354 (0.0395) time: 3.4023 data: 0.0120 max mem: 33369 +Epoch: [27] [ 820/1319] eta: 0:28:58 lr: 1.7397526596506272e-05 loss: 0.0366 (0.0395) time: 3.4237 data: 0.0132 max mem: 33369 +Epoch: [27] [ 830/1319] eta: 0:28:23 lr: 1.7387935604481586e-05 loss: 0.0372 (0.0397) time: 3.5031 data: 0.0127 max mem: 33369 +Epoch: [27] [ 840/1319] eta: 0:27:49 lr: 1.7378344024611436e-05 loss: 0.0423 (0.0397) time: 3.5886 data: 0.0116 max mem: 33369 +Epoch: [27] [ 850/1319] eta: 0:27:14 lr: 1.7368751856499257e-05 loss: 0.0366 (0.0397) time: 3.5045 data: 0.0107 max mem: 33369 +Epoch: [27] [ 860/1319] eta: 0:26:39 lr: 1.7359159099747958e-05 loss: 0.0318 (0.0397) time: 3.4140 data: 0.0098 max mem: 33369 +Epoch: [27] [ 870/1319] eta: 0:26:04 lr: 1.7349565753959942e-05 loss: 0.0327 (0.0396) time: 3.4771 data: 0.0103 max mem: 33369 +Epoch: [27] [ 880/1319] eta: 0:25:30 lr: 1.7339971818737108e-05 loss: 0.0362 (0.0396) time: 3.5245 data: 0.0106 max mem: 33369 +Epoch: [27] [ 890/1319] eta: 0:24:55 lr: 1.733037729368083e-05 loss: 0.0396 (0.0397) time: 3.4948 data: 0.0105 max mem: 33369 +Epoch: [27] [ 900/1319] eta: 0:24:19 lr: 1.7320782178391982e-05 loss: 0.0384 (0.0396) time: 3.4153 data: 0.0108 max mem: 33369 +Epoch: [27] [ 910/1319] eta: 0:23:44 lr: 1.7311186472470895e-05 loss: 0.0308 (0.0396) time: 3.4417 data: 0.0113 max mem: 33369 +Epoch: [27] [ 920/1319] eta: 0:23:09 lr: 1.7301590175517403e-05 loss: 0.0307 (0.0395) time: 3.4344 data: 0.0114 max mem: 33369 +Epoch: [27] [ 930/1319] eta: 0:22:34 lr: 1.7291993287130824e-05 loss: 0.0314 (0.0395) time: 3.4132 data: 0.0103 max mem: 33369 +Epoch: [27] [ 940/1319] eta: 0:21:59 lr: 1.728239580690995e-05 loss: 0.0337 (0.0394) time: 3.4730 data: 0.0113 max mem: 33369 +Epoch: [27] [ 950/1319] eta: 0:21:25 lr: 1.727279773445306e-05 loss: 0.0343 (0.0394) time: 3.5624 data: 0.0118 max mem: 33369 +Epoch: [27] [ 960/1319] eta: 0:20:50 lr: 1.7263199069357895e-05 loss: 0.0318 (0.0393) time: 3.5079 data: 0.0114 max mem: 33369 +Epoch: [27] [ 970/1319] eta: 0:20:15 lr: 1.725359981122169e-05 loss: 0.0318 (0.0392) time: 3.4160 data: 0.0122 max mem: 33369 +Epoch: [27] [ 980/1319] eta: 0:19:40 lr: 1.7243999959641156e-05 loss: 0.0306 (0.0392) time: 3.4327 data: 0.0115 max mem: 33369 +Epoch: [27] [ 990/1319] eta: 0:19:05 lr: 1.7234399514212475e-05 loss: 0.0314 (0.0391) time: 3.4689 data: 0.0107 max mem: 33369 +Epoch: [27] [1000/1319] eta: 0:18:30 lr: 1.7224798474531302e-05 loss: 0.0332 (0.0391) time: 3.4127 data: 0.0109 max mem: 33369 +Epoch: [27] [1010/1319] eta: 0:17:55 lr: 1.7215196840192783e-05 loss: 0.0348 (0.0392) time: 3.3157 data: 0.0101 max mem: 33369 +Epoch: [27] [1020/1319] eta: 0:17:19 lr: 1.7205594610791508e-05 loss: 0.0341 (0.0391) time: 3.3287 data: 0.0095 max mem: 33369 +Epoch: [27] [1030/1319] eta: 0:16:44 lr: 1.7195991785921565e-05 loss: 0.0348 (0.0391) time: 3.3568 data: 0.0101 max mem: 33369 +Epoch: [27] [1040/1319] eta: 0:16:09 lr: 1.71863883651765e-05 loss: 0.0357 (0.0391) time: 3.3604 data: 0.0105 max mem: 33369 +Epoch: [27] [1050/1319] eta: 0:15:34 lr: 1.7176784348149333e-05 loss: 0.0347 (0.0390) time: 3.3453 data: 0.0097 max mem: 33369 +Epoch: [27] [1060/1319] eta: 0:14:59 lr: 1.7167179734432558e-05 loss: 0.0346 (0.0391) time: 3.3607 data: 0.0091 max mem: 33369 +Epoch: [27] [1070/1319] eta: 0:14:24 lr: 1.7157574523618118e-05 loss: 0.0391 (0.0391) time: 3.3785 data: 0.0104 max mem: 33369 +Epoch: [27] [1080/1319] eta: 0:13:49 lr: 1.7147968715297445e-05 loss: 0.0383 (0.0391) time: 3.3115 data: 0.0111 max mem: 33369 +Epoch: [27] [1090/1319] eta: 0:13:14 lr: 1.7138362309061432e-05 loss: 0.0359 (0.0392) time: 3.2676 data: 0.0106 max mem: 33369 +Epoch: [27] [1100/1319] eta: 0:12:39 lr: 1.7128755304500424e-05 loss: 0.0351 (0.0393) time: 3.3244 data: 0.0102 max mem: 33369 +Epoch: [27] [1110/1319] eta: 0:12:04 lr: 1.7119147701204254e-05 loss: 0.0351 (0.0392) time: 3.3515 data: 0.0095 max mem: 33369 +Epoch: [27] [1120/1319] eta: 0:11:29 lr: 1.710953949876218e-05 loss: 0.0346 (0.0393) time: 3.3357 data: 0.0099 max mem: 33369 +Epoch: [27] [1130/1319] eta: 0:10:54 lr: 1.709993069676296e-05 loss: 0.0373 (0.0393) time: 3.3011 data: 0.0099 max mem: 33369 +Epoch: [27] [1140/1319] eta: 0:10:19 lr: 1.7090321294794796e-05 loss: 0.0407 (0.0394) time: 3.2945 data: 0.0088 max mem: 33369 +Epoch: [27] [1150/1319] eta: 0:09:44 lr: 1.7080711292445346e-05 loss: 0.0407 (0.0394) time: 3.2916 data: 0.0086 max mem: 33369 +Epoch: [27] [1160/1319] eta: 0:09:09 lr: 1.7071100689301735e-05 loss: 0.0399 (0.0394) time: 3.2492 data: 0.0102 max mem: 33369 +Epoch: [27] [1170/1319] eta: 0:08:35 lr: 1.706148948495055e-05 loss: 0.0410 (0.0394) time: 3.2354 data: 0.0107 max mem: 33369 +Epoch: [27] [1180/1319] eta: 0:08:00 lr: 1.705187767897781e-05 loss: 0.0385 (0.0394) time: 3.2405 data: 0.0110 max mem: 33369 +Epoch: [27] [1190/1319] eta: 0:07:25 lr: 1.704226527096902e-05 loss: 0.0385 (0.0395) time: 3.2369 data: 0.0110 max mem: 33369 +Epoch: [27] [1200/1319] eta: 0:06:50 lr: 1.703265226050912e-05 loss: 0.0372 (0.0394) time: 3.2378 data: 0.0107 max mem: 33369 +Epoch: [27] [1210/1319] eta: 0:06:16 lr: 1.702303864718251e-05 loss: 0.0333 (0.0394) time: 3.2481 data: 0.0110 max mem: 33369 +Epoch: [27] [1220/1319] eta: 0:05:41 lr: 1.7013424430573045e-05 loss: 0.0333 (0.0394) time: 3.3118 data: 0.0113 max mem: 33369 +Epoch: [27] [1230/1319] eta: 0:05:06 lr: 1.7003809610264022e-05 loss: 0.0320 (0.0394) time: 3.3090 data: 0.0108 max mem: 33369 +Epoch: [27] [1240/1319] eta: 0:04:32 lr: 1.6994194185838196e-05 loss: 0.0329 (0.0394) time: 3.2427 data: 0.0093 max mem: 33369 +Epoch: [27] [1250/1319] eta: 0:03:57 lr: 1.698457815687777e-05 loss: 0.0356 (0.0394) time: 3.2895 data: 0.0094 max mem: 33369 +Epoch: [27] [1260/1319] eta: 0:03:23 lr: 1.6974961522964392e-05 loss: 0.0356 (0.0394) time: 3.2773 data: 0.0096 max mem: 33369 +Epoch: [27] [1270/1319] eta: 0:02:48 lr: 1.6965344283679166e-05 loss: 0.0316 (0.0394) time: 3.2353 data: 0.0098 max mem: 33369 +Epoch: [27] [1280/1319] eta: 0:02:14 lr: 1.6955726438602627e-05 loss: 0.0289 (0.0393) time: 3.2461 data: 0.0099 max mem: 33369 +Epoch: [27] [1290/1319] eta: 0:01:39 lr: 1.694610798731476e-05 loss: 0.0354 (0.0394) time: 3.2382 data: 0.0098 max mem: 33369 +Epoch: [27] [1300/1319] eta: 0:01:05 lr: 1.6936488929395006e-05 loss: 0.0337 (0.0393) time: 3.2631 data: 0.0096 max mem: 33369 +Epoch: [27] [1310/1319] eta: 0:00:30 lr: 1.6926869264422233e-05 loss: 0.0341 (0.0394) time: 3.2602 data: 0.0084 max mem: 33369 +Epoch: [27] Total time: 1:15:30 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 2:42:03 time: 3.7792 data: 3.4484 max mem: 33369 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 100/2573] eta: 0:04:53 time: 0.0788 data: 0.0014 max mem: 33369 +Test: [ 200/2573] eta: 0:03:57 time: 0.0814 data: 0.0017 max mem: 33369 +Test: [ 300/2573] eta: 0:03:32 time: 0.0810 data: 0.0015 max mem: 33369 +Test: [ 400/2573] eta: 0:03:16 time: 0.0831 data: 0.0015 max mem: 33369 +Test: [ 500/2573] eta: 0:03:03 time: 0.0813 data: 0.0016 max mem: 33369 +Test: [ 600/2573] eta: 0:02:52 time: 0.0800 data: 0.0015 max mem: 33369 +Test: [ 700/2573] eta: 0:02:42 time: 0.0829 data: 0.0017 max mem: 33369 +Test: [ 800/2573] eta: 0:02:32 time: 0.0845 data: 0.0016 max mem: 33369 +Test: [ 900/2573] eta: 0:02:23 time: 0.0818 data: 0.0017 max mem: 33369 +Test: [1000/2573] eta: 0:02:14 time: 0.0810 data: 0.0016 max mem: 33369 +Test: [1100/2573] eta: 0:02:05 time: 0.0832 data: 0.0016 max mem: 33369 +Test: [1200/2573] eta: 0:01:56 time: 0.0834 data: 0.0018 max mem: 33369 +Test: [1300/2573] eta: 0:01:47 time: 0.0801 data: 0.0015 max mem: 33369 +Test: [1400/2573] eta: 0:01:39 time: 0.0816 data: 0.0016 max mem: 33369 +Test: [1500/2573] eta: 0:01:30 time: 0.0835 data: 0.0017 max mem: 33369 +Test: [1600/2573] eta: 0:01:21 time: 0.0843 data: 0.0017 max mem: 33369 +Test: [1700/2573] eta: 0:01:13 time: 0.0814 data: 0.0016 max mem: 33369 +Test: [1800/2573] eta: 0:01:04 time: 0.0849 data: 0.0018 max mem: 33369 +Test: [1900/2573] eta: 0:00:56 time: 0.0816 data: 0.0017 max mem: 33369 +Test: [2000/2573] eta: 0:00:47 time: 0.0819 data: 0.0016 max mem: 33369 +Test: [2100/2573] eta: 0:00:39 time: 0.0828 data: 0.0015 max mem: 33369 +Test: [2200/2573] eta: 0:00:31 time: 0.0819 data: 0.0015 max mem: 33369 +Test: [2300/2573] eta: 0:00:22 time: 0.0844 data: 0.0017 max mem: 33369 +Test: [2400/2573] eta: 0:00:14 time: 0.0787 data: 0.0017 max mem: 33369 +Test: [2500/2573] eta: 0:00:06 time: 0.0811 data: 0.0016 max mem: 33369 +Test: Total time: 0:03:35 +Final results: +Mean IoU is 64.24 + + precision@0.5 = 72.22 + precision@0.6 = 66.95 + precision@0.7 = 59.76 + precision@0.8 = 47.57 + precision@0.9 = 24.18 + overall IoU = 62.26 + +Average object IoU 64.2431230787338 +Overall IoU 62.2641487121582 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [28] [ 0/1319] eta: 3:42:32 lr: 1.69182110465679e-05 loss: 0.0336 (0.0336) time: 10.1233 data: 2.8190 max mem: 33369 +Epoch: [28] [ 10/1319] eta: 1:24:31 lr: 1.690859022703219e-05 loss: 0.0336 (0.0394) time: 3.8744 data: 0.2657 max mem: 33369 +Epoch: [28] [ 20/1319] eta: 1:17:27 lr: 1.6898968799219036e-05 loss: 0.0330 (0.0402) time: 3.2509 data: 0.0105 max mem: 33369 +Epoch: [28] [ 30/1319] eta: 1:14:26 lr: 1.6889346762705132e-05 loss: 0.0379 (0.0410) time: 3.2399 data: 0.0107 max mem: 33369 +Epoch: [28] [ 40/1319] eta: 1:13:03 lr: 1.6879724117066593e-05 loss: 0.0377 (0.0397) time: 3.2696 data: 0.0105 max mem: 33369 +Epoch: [28] [ 50/1319] eta: 1:11:51 lr: 1.6870100861878995e-05 loss: 0.0377 (0.0401) time: 3.2933 data: 0.0099 max mem: 33369 +Epoch: [28] [ 60/1319] eta: 1:10:51 lr: 1.6860476996717327e-05 loss: 0.0368 (0.0398) time: 3.2732 data: 0.0089 max mem: 33369 +Epoch: [28] [ 70/1319] eta: 1:10:00 lr: 1.6850852521156025e-05 loss: 0.0387 (0.0402) time: 3.2749 data: 0.0087 max mem: 33369 +Epoch: [28] [ 80/1319] eta: 1:09:28 lr: 1.684122743476896e-05 loss: 0.0385 (0.0394) time: 3.3251 data: 0.0089 max mem: 33369 +Epoch: [28] [ 90/1319] eta: 1:09:02 lr: 1.6831601737129412e-05 loss: 0.0321 (0.0388) time: 3.3956 data: 0.0090 max mem: 33369 +Epoch: [28] [ 100/1319] eta: 1:08:18 lr: 1.6821975427810122e-05 loss: 0.0321 (0.0381) time: 3.3553 data: 0.0090 max mem: 33369 +Epoch: [28] [ 110/1319] eta: 1:07:30 lr: 1.6812348506383245e-05 loss: 0.0303 (0.0377) time: 3.2610 data: 0.0090 max mem: 33369 +Epoch: [28] [ 120/1319] eta: 1:06:47 lr: 1.680272097242036e-05 loss: 0.0337 (0.0375) time: 3.2425 data: 0.0101 max mem: 33369 +Epoch: [28] [ 130/1319] eta: 1:06:11 lr: 1.6793092825492484e-05 loss: 0.0354 (0.0377) time: 3.2824 data: 0.0104 max mem: 33369 +Epoch: [28] [ 140/1319] eta: 1:05:31 lr: 1.6783464065170062e-05 loss: 0.0336 (0.0375) time: 3.2881 data: 0.0105 max mem: 33369 +Epoch: [28] [ 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mem: 33369 +Epoch: [28] [ 230/1319] eta: 0:59:58 lr: 1.6696777548350058e-05 loss: 0.0399 (0.0378) time: 3.2334 data: 0.0105 max mem: 33369 +Epoch: [28] [ 240/1319] eta: 0:59:22 lr: 1.668714263032912e-05 loss: 0.0375 (0.0378) time: 3.2317 data: 0.0109 max mem: 33369 +Epoch: [28] [ 250/1319] eta: 0:58:51 lr: 1.6677507094150246e-05 loss: 0.0375 (0.0379) time: 3.2980 data: 0.0096 max mem: 33369 +Epoch: [28] [ 260/1319] eta: 0:58:20 lr: 1.6667870939376894e-05 loss: 0.0402 (0.0380) time: 3.3540 data: 0.0101 max mem: 33369 +Epoch: [28] [ 270/1319] eta: 0:57:45 lr: 1.6658234165571935e-05 loss: 0.0409 (0.0388) time: 3.2992 data: 0.0108 max mem: 33369 +Epoch: [28] [ 280/1319] eta: 0:57:10 lr: 1.6648596772297652e-05 loss: 0.0382 (0.0387) time: 3.2443 data: 0.0097 max mem: 33369 +Epoch: [28] [ 290/1319] eta: 0:56:34 lr: 1.6638958759115745e-05 loss: 0.0377 (0.0388) time: 3.2433 data: 0.0095 max mem: 33369 +Epoch: [28] [ 300/1319] eta: 0:55:59 lr: 1.6629320125587307e-05 loss: 0.0377 (0.0388) time: 3.2371 data: 0.0093 max mem: 33369 +Epoch: [28] [ 310/1319] eta: 0:55:27 lr: 1.6619680871272843e-05 loss: 0.0351 (0.0386) time: 3.2706 data: 0.0101 max mem: 33369 +Epoch: [28] [ 320/1319] eta: 0:54:54 lr: 1.6610040995732262e-05 loss: 0.0351 (0.0387) time: 3.3009 data: 0.0110 max mem: 33369 +Epoch: [28] [ 330/1319] eta: 0:54:18 lr: 1.6600400498524878e-05 loss: 0.0345 (0.0386) time: 3.2567 data: 0.0100 max mem: 33369 +Epoch: [28] [ 340/1319] eta: 0:53:42 lr: 1.659075937920942e-05 loss: 0.0366 (0.0386) time: 3.1937 data: 0.0103 max mem: 33369 +Epoch: [28] [ 350/1319] eta: 0:53:08 lr: 1.6581117637343994e-05 loss: 0.0360 (0.0385) time: 3.2188 data: 0.0103 max mem: 33369 +Epoch: [28] [ 360/1319] eta: 0:52:35 lr: 1.657147527248612e-05 loss: 0.0278 (0.0385) time: 3.2688 data: 0.0096 max mem: 33369 +Epoch: [28] [ 370/1319] eta: 0:52:01 lr: 1.6561832284192722e-05 loss: 0.0338 (0.0387) time: 3.2631 data: 0.0102 max mem: 33369 +Epoch: [28] [ 380/1319] eta: 0:51:28 lr: 1.6552188672020112e-05 loss: 0.0346 (0.0385) time: 3.2736 data: 0.0098 max mem: 33369 +Epoch: [28] [ 390/1319] eta: 0:50:56 lr: 1.654254443552401e-05 loss: 0.0298 (0.0384) time: 3.3024 data: 0.0100 max mem: 33369 +Epoch: [28] [ 400/1319] eta: 0:50:26 lr: 1.6532899574259518e-05 loss: 0.0330 (0.0384) time: 3.3803 data: 0.0101 max mem: 33369 +Epoch: [28] [ 410/1319] eta: 0:49:51 lr: 1.6523254087781154e-05 loss: 0.0340 (0.0385) time: 3.3178 data: 0.0092 max mem: 33369 +Epoch: [28] [ 420/1319] eta: 0:49:17 lr: 1.651360797564279e-05 loss: 0.0419 (0.0386) time: 3.2138 data: 0.0105 max mem: 33369 +Epoch: [28] [ 430/1319] eta: 0:48:45 lr: 1.6503961237397734e-05 loss: 0.0362 (0.0385) time: 3.2864 data: 0.0114 max mem: 33369 +Epoch: [28] [ 440/1319] eta: 0:48:12 lr: 1.6494313872598656e-05 loss: 0.0299 (0.0384) time: 3.3012 data: 0.0100 max mem: 33369 +Epoch: [28] [ 450/1319] eta: 0:47:38 lr: 1.6484665880797628e-05 loss: 0.0324 (0.0387) time: 3.2514 data: 0.0101 max mem: 33369 +Epoch: [28] [ 460/1319] eta: 0:47:04 lr: 1.6475017261546112e-05 loss: 0.0364 (0.0388) time: 3.2469 data: 0.0099 max mem: 33369 +Epoch: [28] [ 470/1319] eta: 0:46:32 lr: 1.6465368014394945e-05 loss: 0.0405 (0.0389) time: 3.2770 data: 0.0095 max mem: 33369 +Epoch: [28] [ 480/1319] eta: 0:45:57 lr: 1.6455718138894353e-05 loss: 0.0390 (0.0389) time: 3.2405 data: 0.0103 max mem: 33369 +Epoch: [28] [ 490/1319] eta: 0:45:22 lr: 1.6446067634593955e-05 loss: 0.0347 (0.0388) time: 3.1808 data: 0.0103 max mem: 33369 +Epoch: [28] [ 500/1319] eta: 0:44:48 lr: 1.6436416501042754e-05 loss: 0.0328 (0.0387) time: 3.1797 data: 0.0100 max mem: 33369 +Epoch: [28] [ 510/1319] eta: 0:44:13 lr: 1.6426764737789128e-05 loss: 0.0289 (0.0385) time: 3.1770 data: 0.0100 max mem: 33369 +Epoch: [28] [ 520/1319] eta: 0:43:39 lr: 1.6417112344380827e-05 loss: 0.0289 (0.0386) time: 3.1798 data: 0.0097 max mem: 33369 +Epoch: [28] [ 530/1319] eta: 0:43:04 lr: 1.6407459320365e-05 loss: 0.0372 (0.0386) time: 3.1799 data: 0.0091 max mem: 33369 +Epoch: [28] [ 540/1319] eta: 0:42:30 lr: 1.6397805665288162e-05 loss: 0.0361 (0.0385) time: 3.1624 data: 0.0087 max mem: 33369 +Epoch: [28] [ 550/1319] eta: 0:41:56 lr: 1.6388151378696212e-05 loss: 0.0330 (0.0385) time: 3.1649 data: 0.0086 max mem: 33369 +Epoch: [28] [ 560/1319] eta: 0:41:22 lr: 1.6378496460134414e-05 loss: 0.0317 (0.0384) time: 3.1738 data: 0.0084 max mem: 33369 +Epoch: [28] [ 570/1319] eta: 0:40:48 lr: 1.636884090914743e-05 loss: 0.0317 (0.0383) time: 3.1692 data: 0.0085 max mem: 33369 +Epoch: [28] [ 580/1319] eta: 0:40:14 lr: 1.635918472527926e-05 loss: 0.0311 (0.0382) time: 3.1666 data: 0.0086 max mem: 33369 +Epoch: [28] [ 590/1319] eta: 0:39:40 lr: 1.6349527908073296e-05 loss: 0.0310 (0.0382) time: 3.1716 data: 0.0090 max mem: 33369 +Epoch: [28] [ 600/1319] eta: 0:39:07 lr: 1.6339870457072308e-05 loss: 0.0337 (0.0382) time: 3.1884 data: 0.0098 max mem: 33369 +Epoch: [28] [ 610/1319] eta: 0:38:33 lr: 1.6330212371818425e-05 loss: 0.0337 (0.0382) time: 3.1865 data: 0.0100 max mem: 33369 +Epoch: [28] [ 620/1319] eta: 0:37:59 lr: 1.632055365185315e-05 loss: 0.0338 (0.0382) time: 3.1814 data: 0.0092 max mem: 33369 +Epoch: [28] [ 630/1319] eta: 0:37:26 lr: 1.6310894296717336e-05 loss: 0.0341 (0.0383) time: 3.1962 data: 0.0094 max mem: 33369 +Epoch: [28] [ 640/1319] eta: 0:36:52 lr: 1.630123430595122e-05 loss: 0.0363 (0.0383) time: 3.1825 data: 0.0098 max mem: 33369 +Epoch: [28] [ 650/1319] eta: 0:36:19 lr: 1.6291573679094406e-05 loss: 0.0380 (0.0383) time: 3.1733 data: 0.0092 max mem: 33369 +Epoch: [28] [ 660/1319] eta: 0:35:46 lr: 1.6281912415685837e-05 loss: 0.0334 (0.0383) time: 3.1859 data: 0.0095 max mem: 33369 +Epoch: [28] [ 670/1319] eta: 0:35:13 lr: 1.6272250515263847e-05 loss: 0.0338 (0.0383) time: 3.1998 data: 0.0099 max mem: 33369 +Epoch: [28] [ 680/1319] eta: 0:34:40 lr: 1.626258797736611e-05 loss: 0.0349 (0.0383) time: 3.2000 data: 0.0090 max mem: 33369 +Epoch: [28] [ 690/1319] eta: 0:34:07 lr: 1.6252924801529664e-05 loss: 0.0312 (0.0383) time: 3.1994 data: 0.0088 max mem: 33369 +Epoch: [28] [ 700/1319] eta: 0:33:33 lr: 1.6243260987290905e-05 loss: 0.0333 (0.0382) time: 3.1795 data: 0.0095 max mem: 33369 +Epoch: [28] [ 710/1319] eta: 0:33:00 lr: 1.6233596534185593e-05 loss: 0.0347 (0.0382) time: 3.1608 data: 0.0091 max mem: 33369 +Epoch: [28] [ 720/1319] eta: 0:32:27 lr: 1.6223931441748828e-05 loss: 0.0374 (0.0383) time: 3.1702 data: 0.0090 max mem: 33369 +Epoch: [28] [ 730/1319] eta: 0:31:54 lr: 1.6214265709515084e-05 loss: 0.0402 (0.0383) time: 3.1669 data: 0.0088 max mem: 33369 +Epoch: [28] [ 740/1319] eta: 0:31:20 lr: 1.620459933701816e-05 loss: 0.0353 (0.0384) time: 3.1642 data: 0.0089 max mem: 33369 +Epoch: [28] [ 750/1319] eta: 0:30:48 lr: 1.6194932323791233e-05 loss: 0.0348 (0.0384) time: 3.1859 data: 0.0090 max mem: 33369 +Epoch: [28] [ 760/1319] eta: 0:30:15 lr: 1.6185264669366818e-05 loss: 0.0352 (0.0384) time: 3.1927 data: 0.0084 max mem: 33369 +Epoch: [28] [ 770/1319] eta: 0:29:42 lr: 1.617559637327677e-05 loss: 0.0336 (0.0383) time: 3.1826 data: 0.0083 max mem: 33369 +Epoch: [28] [ 780/1319] eta: 0:29:09 lr: 1.6165927435052318e-05 loss: 0.0310 (0.0382) time: 3.2012 data: 0.0087 max mem: 33369 +Epoch: [28] [ 790/1319] eta: 0:28:36 lr: 1.6156257854223998e-05 loss: 0.0341 (0.0382) time: 3.1786 data: 0.0091 max mem: 33369 +Epoch: [28] [ 800/1319] eta: 0:28:03 lr: 1.614658763032172e-05 loss: 0.0374 (0.0383) time: 3.1557 data: 0.0089 max mem: 33369 +Epoch: [28] [ 810/1319] eta: 0:27:30 lr: 1.6136916762874727e-05 loss: 0.0386 (0.0385) time: 3.1743 data: 0.0090 max mem: 33369 +Epoch: [28] [ 820/1319] eta: 0:26:57 lr: 1.6127245251411607e-05 loss: 0.0383 (0.0385) time: 3.1863 data: 0.0093 max mem: 33369 +Epoch: [28] [ 830/1319] eta: 0:26:25 lr: 1.6117573095460284e-05 loss: 0.0370 (0.0385) time: 3.1905 data: 0.0100 max mem: 33369 +Epoch: [28] [ 840/1319] eta: 0:25:52 lr: 1.610790029454803e-05 loss: 0.0374 (0.0385) time: 3.1681 data: 0.0100 max mem: 33369 +Epoch: [28] [ 850/1319] eta: 0:25:19 lr: 1.609822684820143e-05 loss: 0.0413 (0.0386) time: 3.1456 data: 0.0095 max mem: 33369 +Epoch: [28] [ 860/1319] eta: 0:24:46 lr: 1.608855275594644e-05 loss: 0.0386 (0.0386) time: 3.1698 data: 0.0098 max mem: 33369 +Epoch: [28] [ 870/1319] eta: 0:24:13 lr: 1.6078878017308325e-05 loss: 0.0340 (0.0386) time: 3.1771 data: 0.0100 max mem: 33369 +Epoch: [28] [ 880/1319] eta: 0:23:40 lr: 1.6069202631811695e-05 loss: 0.0346 (0.0385) time: 3.1495 data: 0.0103 max mem: 33369 +Epoch: [28] [ 890/1319] eta: 0:23:08 lr: 1.6059526598980493e-05 loss: 0.0367 (0.0386) time: 3.1539 data: 0.0104 max mem: 33369 +Epoch: [28] [ 900/1319] eta: 0:22:35 lr: 1.6049849918337977e-05 loss: 0.0407 (0.0387) time: 3.1538 data: 0.0101 max mem: 33369 +Epoch: [28] [ 910/1319] eta: 0:22:02 lr: 1.6040172589406754e-05 loss: 0.0360 (0.0387) time: 3.1389 data: 0.0096 max mem: 33369 +Epoch: [28] [ 920/1319] eta: 0:21:30 lr: 1.603049461170875e-05 loss: 0.0360 (0.0386) time: 3.1668 data: 0.0095 max mem: 33369 +Epoch: [28] [ 930/1319] eta: 0:20:57 lr: 1.602081598476522e-05 loss: 0.0342 (0.0386) time: 3.1974 data: 0.0092 max mem: 33369 +Epoch: [28] [ 940/1319] eta: 0:20:24 lr: 1.6011136708096744e-05 loss: 0.0342 (0.0386) time: 3.1738 data: 0.0097 max mem: 33369 +Epoch: [28] [ 950/1319] eta: 0:19:52 lr: 1.6001456781223216e-05 loss: 0.0330 (0.0386) time: 3.1738 data: 0.0104 max mem: 33369 +Epoch: [28] [ 960/1319] eta: 0:19:20 lr: 1.599177620366387e-05 loss: 0.0330 (0.0386) time: 3.1869 data: 0.0098 max mem: 33369 +Epoch: [28] [ 970/1319] eta: 0:18:47 lr: 1.598209497493724e-05 loss: 0.0361 (0.0386) time: 3.1695 data: 0.0092 max mem: 33369 +Epoch: [28] [ 980/1319] eta: 0:18:14 lr: 1.5972413094561205e-05 loss: 0.0370 (0.0386) time: 3.1695 data: 0.0091 max mem: 33369 +Epoch: [28] [ 990/1319] eta: 0:17:42 lr: 1.5962730562052938e-05 loss: 0.0396 (0.0387) time: 3.1801 data: 0.0091 max mem: 33369 +Epoch: [28] [1000/1319] eta: 0:17:10 lr: 1.5953047376928946e-05 loss: 0.0396 (0.0387) time: 3.1952 data: 0.0089 max mem: 33369 +Epoch: [28] [1010/1319] eta: 0:16:37 lr: 1.5943363538705032e-05 loss: 0.0372 (0.0386) time: 3.2036 data: 0.0087 max mem: 33369 +Epoch: [28] [1020/1319] eta: 0:16:05 lr: 1.5933679046896337e-05 loss: 0.0367 (0.0386) time: 3.1978 data: 0.0089 max mem: 33369 +Epoch: [28] [1030/1319] eta: 0:15:32 lr: 1.592399390101729e-05 loss: 0.0378 (0.0386) time: 3.1854 data: 0.0090 max mem: 33369 +Epoch: [28] [1040/1319] eta: 0:15:00 lr: 1.5914308100581652e-05 loss: 0.0355 (0.0386) time: 3.1686 data: 0.0088 max mem: 33369 +Epoch: [28] [1050/1319] eta: 0:14:28 lr: 1.5904621645102482e-05 loss: 0.0349 (0.0386) time: 3.1695 data: 0.0091 max mem: 33369 +Epoch: [28] [1060/1319] eta: 0:13:55 lr: 1.5894934534092145e-05 loss: 0.0413 (0.0387) time: 3.1625 data: 0.0097 max mem: 33369 +Epoch: [28] [1070/1319] eta: 0:13:23 lr: 1.588524676706232e-05 loss: 0.0394 (0.0387) time: 3.1473 data: 0.0097 max mem: 33369 +Epoch: [28] [1080/1319] eta: 0:12:50 lr: 1.5875558343523986e-05 loss: 0.0376 (0.0387) time: 3.1596 data: 0.0100 max mem: 33369 +Epoch: [28] [1090/1319] eta: 0:12:18 lr: 1.5865869262987425e-05 loss: 0.0373 (0.0387) time: 3.1640 data: 0.0097 max mem: 33369 +Epoch: [28] [1100/1319] eta: 0:11:46 lr: 1.5856179524962237e-05 loss: 0.0374 (0.0387) time: 3.1625 data: 0.0089 max mem: 33369 +Epoch: [28] [1110/1319] eta: 0:11:13 lr: 1.5846489128957288e-05 loss: 0.0379 (0.0387) time: 3.1791 data: 0.0090 max mem: 33369 +Epoch: [28] [1120/1319] eta: 0:10:41 lr: 1.5836798074480774e-05 loss: 0.0379 (0.0388) time: 3.1782 data: 0.0098 max mem: 33369 +Epoch: [28] [1130/1319] eta: 0:10:09 lr: 1.582710636104018e-05 loss: 0.0347 (0.0387) time: 3.1871 data: 0.0107 max mem: 33369 +Epoch: [28] [1140/1319] eta: 0:09:36 lr: 1.5817413988142284e-05 loss: 0.0353 (0.0387) time: 3.1777 data: 0.0106 max mem: 33369 +Epoch: [28] [1150/1319] eta: 0:09:04 lr: 1.5807720955293166e-05 loss: 0.0390 (0.0387) time: 3.1676 data: 0.0103 max mem: 33369 +Epoch: [28] [1160/1319] eta: 0:08:32 lr: 1.579802726199819e-05 loss: 0.0377 (0.0387) time: 3.1931 data: 0.0106 max mem: 33369 +Epoch: [28] [1170/1319] eta: 0:08:00 lr: 1.5788332907762015e-05 loss: 0.0340 (0.0387) time: 3.2031 data: 0.0105 max mem: 33369 +Epoch: [28] [1180/1319] eta: 0:07:27 lr: 1.577863789208859e-05 loss: 0.0380 (0.0388) time: 3.1801 data: 0.0106 max mem: 33369 +Epoch: [28] [1190/1319] eta: 0:06:55 lr: 1.576894221448116e-05 loss: 0.0319 (0.0387) time: 3.1482 data: 0.0102 max mem: 33369 +Epoch: [28] [1200/1319] eta: 0:06:23 lr: 1.5759245874442245e-05 loss: 0.0300 (0.0386) time: 3.1594 data: 0.0092 max mem: 33369 +Epoch: [28] [1210/1319] eta: 0:05:50 lr: 1.5749548871473663e-05 loss: 0.0318 (0.0387) time: 3.1566 data: 0.0096 max mem: 33369 +Epoch: [28] [1220/1319] eta: 0:05:18 lr: 1.57398512050765e-05 loss: 0.0325 (0.0386) time: 3.1586 data: 0.0100 max mem: 33369 +Epoch: [28] [1230/1319] eta: 0:04:46 lr: 1.5730152874751144e-05 loss: 0.0343 (0.0386) time: 3.1984 data: 0.0098 max mem: 33369 +Epoch: [28] [1240/1319] eta: 0:04:14 lr: 1.572045387999725e-05 loss: 0.0347 (0.0386) time: 3.1952 data: 0.0103 max mem: 33369 +Epoch: [28] [1250/1319] eta: 0:03:42 lr: 1.5710754220313764e-05 loss: 0.0365 (0.0386) time: 3.1799 data: 0.0102 max mem: 33369 +Epoch: [28] [1260/1319] eta: 0:03:09 lr: 1.5701053895198906e-05 loss: 0.0365 (0.0386) time: 3.1832 data: 0.0097 max mem: 33369 +Epoch: [28] [1270/1319] eta: 0:02:37 lr: 1.5691352904150157e-05 loss: 0.0333 (0.0386) time: 3.1888 data: 0.0092 max mem: 33369 +Epoch: [28] [1280/1319] eta: 0:02:05 lr: 1.5681651246664294e-05 loss: 0.0364 (0.0386) time: 3.1887 data: 0.0097 max mem: 33369 +Epoch: [28] [1290/1319] eta: 0:01:33 lr: 1.5671948922237363e-05 loss: 0.0335 (0.0386) time: 3.2025 data: 0.0107 max mem: 33369 +Epoch: [28] [1300/1319] eta: 0:01:01 lr: 1.5662245930364672e-05 loss: 0.0328 (0.0385) time: 3.2064 data: 0.0096 max mem: 33369 +Epoch: [28] [1310/1319] eta: 0:00:28 lr: 1.5652542270540813e-05 loss: 0.0336 (0.0385) time: 3.1886 data: 0.0086 max mem: 33369 +Epoch: [28] Total time: 1:10:44 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 2:37:08 time: 3.6642 data: 3.3219 max mem: 33369 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 100/2573] eta: 0:04:42 time: 0.0791 data: 0.0018 max mem: 33369 +Test: [ 200/2573] eta: 0:03:52 time: 0.0797 data: 0.0017 max mem: 33369 +Test: [ 300/2573] eta: 0:03:29 time: 0.0825 data: 0.0015 max mem: 33369 +Test: [ 400/2573] eta: 0:03:13 time: 0.0815 data: 0.0013 max mem: 33369 +Test: [ 500/2573] eta: 0:03:01 time: 0.0796 data: 0.0014 max mem: 33369 +Test: [ 600/2573] eta: 0:02:50 time: 0.0808 data: 0.0016 max mem: 33369 +Test: [ 700/2573] eta: 0:02:41 time: 0.0822 data: 0.0016 max mem: 33369 +Test: [ 800/2573] eta: 0:02:31 time: 0.0836 data: 0.0013 max mem: 33369 +Test: [ 900/2573] eta: 0:02:22 time: 0.0807 data: 0.0015 max mem: 33369 +Test: [1000/2573] eta: 0:02:13 time: 0.0799 data: 0.0015 max mem: 33369 +Test: [1100/2573] eta: 0:02:04 time: 0.0810 data: 0.0015 max mem: 33369 +Test: [1200/2573] eta: 0:01:55 time: 0.0819 data: 0.0016 max mem: 33369 +Test: [1300/2573] eta: 0:01:46 time: 0.0825 data: 0.0014 max mem: 33369 +Test: [1400/2573] eta: 0:01:38 time: 0.0795 data: 0.0015 max mem: 33369 +Test: [1500/2573] eta: 0:01:29 time: 0.0824 data: 0.0016 max mem: 33369 +Test: [1600/2573] eta: 0:01:21 time: 0.0843 data: 0.0017 max mem: 33369 +Test: [1700/2573] eta: 0:01:12 time: 0.0797 data: 0.0014 max mem: 33369 +Test: [1800/2573] eta: 0:01:04 time: 0.0818 data: 0.0015 max mem: 33369 +Test: [1900/2573] eta: 0:00:55 time: 0.0805 data: 0.0016 max mem: 33369 +Test: [2000/2573] eta: 0:00:47 time: 0.0806 data: 0.0014 max mem: 33369 +Test: [2100/2573] eta: 0:00:39 time: 0.0830 data: 0.0014 max mem: 33369 +Test: [2200/2573] eta: 0:00:30 time: 0.0831 data: 0.0016 max mem: 33369 +Test: [2300/2573] eta: 0:00:22 time: 0.0833 data: 0.0016 max mem: 33369 +Test: [2400/2573] eta: 0:00:14 time: 0.0783 data: 0.0014 max mem: 33369 +Test: [2500/2573] eta: 0:00:06 time: 0.0812 data: 0.0014 max mem: 33369 +Test: Total time: 0:03:32 +Final results: +Mean IoU is 64.45 + + precision@0.5 = 72.55 + precision@0.6 = 67.05 + precision@0.7 = 59.48 + precision@0.8 = 48.55 + precision@0.9 = 23.94 + overall IoU = 62.23 + +Average object IoU 64.45436333094167 +Overall IoU 62.22784423828125 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [29] [ 0/1319] eta: 3:42:57 lr: 1.5643808405182777e-05 loss: 0.0190 (0.0190) time: 10.1419 data: 2.5781 max mem: 33369 +Epoch: [29] [ 10/1319] eta: 1:22:41 lr: 1.563410347485666e-05 loss: 0.0368 (0.0412) time: 3.7901 data: 0.2432 max mem: 33369 +Epoch: [29] [ 20/1319] eta: 1:15:39 lr: 1.5624397875109532e-05 loss: 0.0398 (0.0404) time: 3.1625 data: 0.0096 max mem: 33369 +Epoch: [29] [ 30/1319] eta: 1:13:16 lr: 1.5614691605433113e-05 loss: 0.0351 (0.0389) time: 3.2019 data: 0.0100 max mem: 33369 +Epoch: [29] [ 40/1319] eta: 1:11:33 lr: 1.5604984665318397e-05 loss: 0.0320 (0.0374) time: 3.2118 data: 0.0103 max mem: 33369 +Epoch: [29] [ 50/1319] eta: 1:10:13 lr: 1.5595277054255625e-05 loss: 0.0348 (0.0379) time: 3.1806 data: 0.0100 max mem: 33369 +Epoch: [29] [ 60/1319] eta: 1:09:02 lr: 1.558556877173431e-05 loss: 0.0322 (0.0376) time: 3.1549 data: 0.0098 max mem: 33369 +Epoch: [29] [ 70/1319] eta: 1:08:14 lr: 1.557585981724323e-05 loss: 0.0322 (0.0373) time: 3.1702 data: 0.0094 max mem: 33369 +Epoch: [29] [ 80/1319] eta: 1:07:28 lr: 1.5566150190270393e-05 loss: 0.0311 (0.0368) time: 3.1984 data: 0.0087 max mem: 33369 +Epoch: [29] [ 90/1319] eta: 1:06:43 lr: 1.5556439890303075e-05 loss: 0.0330 (0.0365) time: 3.1858 data: 0.0091 max mem: 33369 +Epoch: [29] [ 100/1319] eta: 1:06:02 lr: 1.554672891682782e-05 loss: 0.0323 (0.0361) time: 3.1796 data: 0.0095 max mem: 33369 +Epoch: [29] [ 110/1319] eta: 1:05:24 lr: 1.55370172693304e-05 loss: 0.0320 (0.0361) time: 3.1927 data: 0.0091 max mem: 33369 +Epoch: [29] [ 120/1319] eta: 1:04:44 lr: 1.552730494729585e-05 loss: 0.0330 (0.0359) time: 3.1885 data: 0.0086 max mem: 33369 +Epoch: [29] [ 130/1319] eta: 1:04:09 lr: 1.551759195020846e-05 loss: 0.0323 (0.0358) time: 3.1897 data: 0.0091 max mem: 33369 +Epoch: [29] [ 140/1319] eta: 1:03:34 lr: 1.5507878277551742e-05 loss: 0.0315 (0.0355) time: 3.2036 data: 0.0094 max mem: 33369 +Epoch: [29] [ 150/1319] eta: 1:02:57 lr: 1.5498163928808475e-05 loss: 0.0294 (0.0355) time: 3.1947 data: 0.0089 max mem: 33369 +Epoch: [29] [ 160/1319] eta: 1:02:23 lr: 1.548844890346068e-05 loss: 0.0317 (0.0357) time: 3.1948 data: 0.0089 max mem: 33369 +Epoch: [29] [ 170/1319] eta: 1:01:47 lr: 1.547873320098961e-05 loss: 0.0366 (0.0358) time: 3.1852 data: 0.0096 max mem: 33369 +Epoch: [29] [ 180/1319] eta: 1:01:13 lr: 1.546901682087577e-05 loss: 0.0347 (0.0360) time: 3.1836 data: 0.0109 max mem: 33369 +Epoch: [29] [ 190/1319] eta: 1:00:37 lr: 1.5459299762598884e-05 loss: 0.0319 (0.0358) time: 3.1866 data: 0.0111 max mem: 33369 +Epoch: [29] [ 200/1319] eta: 1:00:01 lr: 1.5449582025637935e-05 loss: 0.0290 (0.0356) time: 3.1604 data: 0.0102 max mem: 33369 +Epoch: [29] [ 210/1319] eta: 0:59:25 lr: 1.543986360947113e-05 loss: 0.0287 (0.0355) time: 3.1452 data: 0.0097 max mem: 33369 +Epoch: [29] [ 220/1319] eta: 0:58:53 lr: 1.543014451357591e-05 loss: 0.0311 (0.0357) time: 3.1829 data: 0.0099 max mem: 33369 +Epoch: [29] [ 230/1319] eta: 0:58:18 lr: 1.5420424737428955e-05 loss: 0.0346 (0.0357) time: 3.1894 data: 0.0098 max mem: 33369 +Epoch: [29] [ 240/1319] eta: 0:57:45 lr: 1.541070428050616e-05 loss: 0.0346 (0.0359) time: 3.1724 data: 0.0095 max mem: 33369 +Epoch: [29] [ 250/1319] eta: 0:57:13 lr: 1.5400983142282667e-05 loss: 0.0356 (0.0358) time: 3.2045 data: 0.0090 max mem: 33369 +Epoch: [29] [ 260/1319] eta: 0:56:39 lr: 1.539126132223283e-05 loss: 0.0371 (0.0361) time: 3.1962 data: 0.0092 max mem: 33369 +Epoch: [29] [ 270/1319] eta: 0:56:06 lr: 1.538153881983024e-05 loss: 0.0402 (0.0366) time: 3.1748 data: 0.0094 max mem: 33369 +Epoch: [29] [ 280/1319] eta: 0:55:33 lr: 1.53718156345477e-05 loss: 0.0381 (0.0366) time: 3.1826 data: 0.0091 max mem: 33369 +Epoch: [29] [ 290/1319] eta: 0:54:59 lr: 1.5362091765857252e-05 loss: 0.0314 (0.0365) time: 3.1717 data: 0.0092 max mem: 33369 +Epoch: [29] [ 300/1319] eta: 0:54:26 lr: 1.5352367213230138e-05 loss: 0.0351 (0.0364) time: 3.1658 data: 0.0091 max mem: 33369 +Epoch: [29] [ 310/1319] eta: 0:53:55 lr: 1.5342641976136825e-05 loss: 0.0294 (0.0362) time: 3.2036 data: 0.0091 max mem: 33369 +Epoch: [29] [ 320/1319] eta: 0:53:22 lr: 1.5332916054047e-05 loss: 0.0309 (0.0363) time: 3.1988 data: 0.0092 max mem: 33369 +Epoch: [29] [ 330/1319] eta: 0:52:49 lr: 1.532318944642957e-05 loss: 0.0340 (0.0361) time: 3.1829 data: 0.0094 max mem: 33369 +Epoch: [29] [ 340/1319] eta: 0:52:16 lr: 1.5313462152752656e-05 loss: 0.0306 (0.0361) time: 3.1789 data: 0.0093 max mem: 33369 +Epoch: [29] [ 350/1319] eta: 0:51:44 lr: 1.5303734172483566e-05 loss: 0.0333 (0.0361) time: 3.1857 data: 0.0092 max mem: 33369 +Epoch: [29] [ 360/1319] eta: 0:51:12 lr: 1.529400550508885e-05 loss: 0.0339 (0.0360) time: 3.2073 data: 0.0094 max mem: 33369 +Epoch: [29] [ 370/1319] eta: 0:50:38 lr: 1.528427615003424e-05 loss: 0.0318 (0.0360) time: 3.1683 data: 0.0096 max mem: 33369 +Epoch: [29] [ 380/1319] eta: 0:50:05 lr: 1.5274546106784702e-05 loss: 0.0318 (0.0360) time: 3.1491 data: 0.0095 max mem: 33369 +Epoch: [29] [ 390/1319] eta: 0:49:33 lr: 1.526481537480438e-05 loss: 0.0282 (0.0359) time: 3.1761 data: 0.0094 max mem: 33369 +Epoch: [29] [ 400/1319] eta: 0:48:59 lr: 1.525508395355664e-05 loss: 0.0282 (0.0361) time: 3.1545 data: 0.0104 max mem: 33369 +Epoch: [29] [ 410/1319] eta: 0:48:26 lr: 1.5245351842504036e-05 loss: 0.0326 (0.0361) time: 3.1336 data: 0.0111 max mem: 33369 +Epoch: [29] [ 420/1319] eta: 0:47:54 lr: 1.5235619041108326e-05 loss: 0.0329 (0.0362) time: 3.1750 data: 0.0108 max mem: 33369 +Epoch: [29] [ 430/1319] eta: 0:47:21 lr: 1.5225885548830468e-05 loss: 0.0320 (0.0361) time: 3.1708 data: 0.0100 max mem: 33369 +Epoch: [29] [ 440/1319] eta: 0:46:49 lr: 1.5216151365130616e-05 loss: 0.0317 (0.0360) time: 3.1564 data: 0.0100 max mem: 33369 +Epoch: [29] [ 450/1319] eta: 0:46:16 lr: 1.520641648946812e-05 loss: 0.0304 (0.0361) time: 3.1808 data: 0.0098 max mem: 33369 +Epoch: [29] [ 460/1319] eta: 0:45:44 lr: 1.519668092130151e-05 loss: 0.0341 (0.0360) time: 3.1884 data: 0.0094 max mem: 33369 +Epoch: [29] [ 470/1319] eta: 0:45:12 lr: 1.5186944660088521e-05 loss: 0.0356 (0.0361) time: 3.1681 data: 0.0095 max mem: 33369 +Epoch: [29] [ 480/1319] eta: 0:44:39 lr: 1.5177207705286068e-05 loss: 0.0353 (0.0361) time: 3.1607 data: 0.0094 max mem: 33369 +Epoch: [29] [ 490/1319] eta: 0:44:07 lr: 1.5167470056350257e-05 loss: 0.0336 (0.0362) time: 3.1724 data: 0.0099 max mem: 33369 +Epoch: [29] [ 500/1319] eta: 0:43:36 lr: 1.5157731712736389e-05 loss: 0.0344 (0.0364) time: 3.2150 data: 0.0095 max mem: 33369 +Epoch: [29] [ 510/1319] eta: 0:43:04 lr: 1.514799267389892e-05 loss: 0.0407 (0.0366) time: 3.2278 data: 0.0093 max mem: 33369 +Epoch: [29] [ 520/1319] eta: 0:42:32 lr: 1.5138252939291514e-05 loss: 0.0278 (0.0364) time: 3.1932 data: 0.0100 max mem: 33369 +Epoch: [29] [ 530/1319] eta: 0:42:00 lr: 1.5128512508367005e-05 loss: 0.0278 (0.0364) time: 3.1967 data: 0.0104 max mem: 33369 +Epoch: [29] [ 540/1319] eta: 0:41:28 lr: 1.5118771380577405e-05 loss: 0.0300 (0.0364) time: 3.2029 data: 0.0097 max mem: 33369 +Epoch: [29] [ 550/1319] eta: 0:40:56 lr: 1.5109029555373904e-05 loss: 0.0334 (0.0365) time: 3.1726 data: 0.0089 max mem: 33369 +Epoch: [29] [ 560/1319] eta: 0:40:24 lr: 1.5099287032206873e-05 loss: 0.0355 (0.0364) time: 3.1625 data: 0.0087 max mem: 33369 +Epoch: [29] [ 570/1319] eta: 0:39:51 lr: 1.5089543810525833e-05 loss: 0.0342 (0.0364) time: 3.1746 data: 0.0084 max mem: 33369 +Epoch: [29] [ 580/1319] eta: 0:39:19 lr: 1.50797998897795e-05 loss: 0.0343 (0.0364) time: 3.1672 data: 0.0089 max mem: 33369 +Epoch: [29] [ 590/1319] eta: 0:38:47 lr: 1.5070055269415744e-05 loss: 0.0343 (0.0364) time: 3.1817 data: 0.0092 max mem: 33369 +Epoch: [29] [ 600/1319] eta: 0:38:15 lr: 1.5060309948881612e-05 loss: 0.0348 (0.0367) time: 3.1739 data: 0.0093 max mem: 33369 +Epoch: [29] [ 610/1319] eta: 0:37:42 lr: 1.5050563927623313e-05 loss: 0.0356 (0.0367) time: 3.1532 data: 0.0089 max mem: 33369 +Epoch: [29] [ 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33369 +Epoch: [29] [ 700/1319] eta: 0:32:56 lr: 1.4962818111919327e-05 loss: 0.0350 (0.0368) time: 3.1702 data: 0.0094 max mem: 33369 +Epoch: [29] [ 710/1319] eta: 0:32:23 lr: 1.4953065052775669e-05 loss: 0.0361 (0.0368) time: 3.1528 data: 0.0103 max mem: 33369 +Epoch: [29] [ 720/1319] eta: 0:31:51 lr: 1.494331128676048e-05 loss: 0.0415 (0.0370) time: 3.1515 data: 0.0107 max mem: 33369 +Epoch: [29] [ 730/1319] eta: 0:31:19 lr: 1.4933556813309787e-05 loss: 0.0390 (0.0369) time: 3.1696 data: 0.0092 max mem: 33369 +Epoch: [29] [ 740/1319] eta: 0:30:47 lr: 1.4923801631858781e-05 loss: 0.0353 (0.0369) time: 3.1985 data: 0.0098 max mem: 33369 +Epoch: [29] [ 750/1319] eta: 0:30:15 lr: 1.4914045741841778e-05 loss: 0.0381 (0.0370) time: 3.1904 data: 0.0110 max mem: 33369 +Epoch: [29] [ 760/1319] eta: 0:29:43 lr: 1.4904289142692235e-05 loss: 0.0390 (0.0370) time: 3.1648 data: 0.0108 max mem: 33369 +Epoch: [29] [ 770/1319] eta: 0:29:11 lr: 1.4894531833842748e-05 loss: 0.0372 (0.0370) time: 3.1802 data: 0.0107 max mem: 33369 +Epoch: [29] [ 780/1319] eta: 0:28:39 lr: 1.4884773814725032e-05 loss: 0.0332 (0.0369) time: 3.1804 data: 0.0107 max mem: 33369 +Epoch: [29] [ 790/1319] eta: 0:28:07 lr: 1.4875015084769944e-05 loss: 0.0325 (0.0370) time: 3.1950 data: 0.0104 max mem: 33369 +Epoch: [29] [ 800/1319] eta: 0:27:36 lr: 1.4865255643407467e-05 loss: 0.0335 (0.0370) time: 3.2117 data: 0.0103 max mem: 33369 +Epoch: [29] [ 810/1319] eta: 0:27:04 lr: 1.4855495490066707e-05 loss: 0.0335 (0.0370) time: 3.2203 data: 0.0104 max mem: 33369 +Epoch: [29] [ 820/1319] eta: 0:26:32 lr: 1.4845734624175911e-05 loss: 0.0327 (0.0369) time: 3.2073 data: 0.0102 max mem: 33369 +Epoch: [29] [ 830/1319] eta: 0:26:00 lr: 1.4835973045162419e-05 loss: 0.0351 (0.0370) time: 3.1838 data: 0.0104 max mem: 33369 +Epoch: [29] [ 840/1319] eta: 0:25:28 lr: 1.4826210752452718e-05 loss: 0.0387 (0.0370) time: 3.1862 data: 0.0093 max mem: 33369 +Epoch: [29] [ 850/1319] eta: 0:24:56 lr: 1.48164477454724e-05 loss: 0.0381 (0.0370) time: 3.1927 data: 0.0089 max mem: 33369 +Epoch: [29] [ 860/1319] eta: 0:24:25 lr: 1.4806684023646183e-05 loss: 0.0360 (0.0370) time: 3.2226 data: 0.0087 max mem: 33369 +Epoch: [29] [ 870/1319] eta: 0:23:52 lr: 1.4796919586397895e-05 loss: 0.0373 (0.0371) time: 3.2015 data: 0.0085 max mem: 33369 +Epoch: [29] [ 880/1319] eta: 0:23:21 lr: 1.4787154433150476e-05 loss: 0.0368 (0.0371) time: 3.1827 data: 0.0095 max mem: 33369 +Epoch: [29] [ 890/1319] eta: 0:22:49 lr: 1.4777388563325976e-05 loss: 0.0322 (0.0370) time: 3.2108 data: 0.0098 max mem: 33369 +Epoch: [29] [ 900/1319] eta: 0:22:17 lr: 1.4767621976345552e-05 loss: 0.0322 (0.0370) time: 3.2026 data: 0.0102 max mem: 33369 +Epoch: [29] [ 910/1319] eta: 0:21:45 lr: 1.4757854671629475e-05 loss: 0.0352 (0.0370) time: 3.1872 data: 0.0109 max mem: 33369 +Epoch: [29] [ 920/1319] eta: 0:21:13 lr: 1.4748086648597121e-05 loss: 0.0383 (0.0370) time: 3.1643 data: 0.0111 max mem: 33369 +Epoch: [29] [ 930/1319] eta: 0:20:41 lr: 1.4738317906666963e-05 loss: 0.0330 (0.0370) time: 3.1544 data: 0.0110 max mem: 33369 +Epoch: [29] [ 940/1319] eta: 0:20:09 lr: 1.4728548445256565e-05 loss: 0.0338 (0.0370) time: 3.1470 data: 0.0111 max mem: 33369 +Epoch: [29] [ 950/1319] eta: 0:19:37 lr: 1.471877826378261e-05 loss: 0.0338 (0.0370) time: 3.1685 data: 0.0112 max mem: 33369 +Epoch: [29] [ 960/1319] eta: 0:19:05 lr: 1.4709007361660864e-05 loss: 0.0368 (0.0371) time: 3.1904 data: 0.0107 max mem: 33369 +Epoch: [29] [ 970/1319] eta: 0:18:33 lr: 1.4699235738306196e-05 loss: 0.0401 (0.0371) time: 3.1695 data: 0.0103 max mem: 33369 +Epoch: [29] [ 980/1319] eta: 0:18:01 lr: 1.4689463393132561e-05 loss: 0.0379 (0.0371) time: 3.1811 data: 0.0093 max mem: 33369 +Epoch: [29] [ 990/1319] eta: 0:17:29 lr: 1.4679690325553006e-05 loss: 0.0291 (0.0370) time: 3.1893 data: 0.0086 max mem: 33369 +Epoch: [29] [1000/1319] eta: 0:16:57 lr: 1.466991653497966e-05 loss: 0.0309 (0.0370) time: 3.1469 data: 0.0090 max mem: 33369 +Epoch: [29] [1010/1319] eta: 0:16:25 lr: 1.466014202082375e-05 loss: 0.0343 (0.0370) time: 3.1662 data: 0.0090 max mem: 33369 +Epoch: [29] [1020/1319] eta: 0:15:53 lr: 1.4650366782495577e-05 loss: 0.0303 (0.0369) time: 3.2331 data: 0.0100 max mem: 33369 +Epoch: [29] [1030/1319] eta: 0:15:21 lr: 1.4640590819404531e-05 loss: 0.0327 (0.0369) time: 3.2230 data: 0.0103 max mem: 33369 +Epoch: [29] [1040/1319] eta: 0:14:49 lr: 1.4630814130959084e-05 loss: 0.0385 (0.0370) time: 3.1639 data: 0.0105 max mem: 33369 +Epoch: [29] [1050/1319] eta: 0:14:18 lr: 1.4621036716566766e-05 loss: 0.0329 (0.0369) time: 3.1529 data: 0.0107 max mem: 33369 +Epoch: [29] [1060/1319] eta: 0:13:46 lr: 1.4611258575634206e-05 loss: 0.0327 (0.0370) time: 3.1859 data: 0.0096 max mem: 33369 +Epoch: [29] [1070/1319] eta: 0:13:14 lr: 1.4601479707567092e-05 loss: 0.0375 (0.0370) time: 3.1994 data: 0.0090 max mem: 33369 +Epoch: [29] [1080/1319] eta: 0:12:42 lr: 1.4591700111770195e-05 loss: 0.0334 (0.0370) time: 3.2044 data: 0.0093 max mem: 33369 +Epoch: [29] [1090/1319] eta: 0:12:10 lr: 1.4581919787647347e-05 loss: 0.0345 (0.0370) time: 3.1974 data: 0.0095 max mem: 33369 +Epoch: [29] [1100/1319] eta: 0:11:38 lr: 1.4572138734601442e-05 loss: 0.0347 (0.0370) time: 3.1896 data: 0.0099 max mem: 33369 +Epoch: [29] [1110/1319] eta: 0:11:06 lr: 1.4562356952034447e-05 loss: 0.0337 (0.0370) time: 3.1980 data: 0.0102 max mem: 33369 +Epoch: [29] [1120/1319] eta: 0:10:34 lr: 1.4552574439347391e-05 loss: 0.0344 (0.0370) time: 3.1950 data: 0.0094 max mem: 33369 +Epoch: [29] [1130/1319] eta: 0:10:02 lr: 1.4542791195940364e-05 loss: 0.0338 (0.0370) time: 3.1843 data: 0.0096 max mem: 33369 +Epoch: [29] [1140/1319] eta: 0:09:30 lr: 1.453300722121251e-05 loss: 0.0339 (0.0370) time: 3.1610 data: 0.0103 max mem: 33369 +Epoch: [29] [1150/1319] eta: 0:08:59 lr: 1.4523222514562035e-05 loss: 0.0289 (0.0370) time: 3.1735 data: 0.0104 max mem: 33369 +Epoch: [29] [1160/1319] eta: 0:08:27 lr: 1.4513437075386188e-05 loss: 0.0298 (0.0370) time: 3.1780 data: 0.0099 max mem: 33369 +Epoch: [29] [1170/1319] eta: 0:07:55 lr: 1.4503650903081281e-05 loss: 0.0334 (0.0369) time: 3.1461 data: 0.0086 max mem: 33369 +Epoch: [29] [1180/1319] eta: 0:07:23 lr: 1.449386399704267e-05 loss: 0.0352 (0.0369) time: 3.1720 data: 0.0080 max mem: 33369 +Epoch: [29] [1190/1319] eta: 0:06:51 lr: 1.4484076356664761e-05 loss: 0.0360 (0.0369) time: 3.1805 data: 0.0093 max mem: 33369 +Epoch: [29] [1200/1319] eta: 0:06:19 lr: 1.447428798134101e-05 loss: 0.0355 (0.0369) time: 3.1690 data: 0.0102 max mem: 33369 +Epoch: [29] [1210/1319] eta: 0:05:47 lr: 1.4464498870463896e-05 loss: 0.0339 (0.0369) time: 3.1729 data: 0.0099 max mem: 33369 +Epoch: [29] [1220/1319] eta: 0:05:15 lr: 1.4454709023424959e-05 loss: 0.0308 (0.0369) time: 3.1776 data: 0.0103 max mem: 33369 +Epoch: [29] [1230/1319] eta: 0:04:43 lr: 1.444491843961477e-05 loss: 0.0315 (0.0368) time: 3.1913 data: 0.0098 max mem: 33369 +Epoch: [29] [1240/1319] eta: 0:04:11 lr: 1.4435127118422938e-05 loss: 0.0367 (0.0369) time: 3.1650 data: 0.0088 max mem: 33369 +Epoch: [29] [1250/1319] eta: 0:03:39 lr: 1.442533505923811e-05 loss: 0.0361 (0.0368) time: 3.1567 data: 0.0090 max mem: 33369 +Epoch: [29] [1260/1319] eta: 0:03:08 lr: 1.4415542261447945e-05 loss: 0.0336 (0.0368) time: 3.1809 data: 0.0097 max mem: 33369 +Epoch: [29] [1270/1319] eta: 0:02:36 lr: 1.4405748724439155e-05 loss: 0.0343 (0.0368) time: 3.1958 data: 0.0107 max mem: 33369 +Epoch: [29] [1280/1319] eta: 0:02:04 lr: 1.4395954447597464e-05 loss: 0.0312 (0.0368) time: 3.1909 data: 0.0097 max mem: 33369 +Epoch: [29] [1290/1319] eta: 0:01:32 lr: 1.4386159430307632e-05 loss: 0.0336 (0.0368) time: 3.1641 data: 0.0085 max mem: 33369 +Epoch: [29] [1300/1319] eta: 0:01:00 lr: 1.4376363671953435e-05 loss: 0.0358 (0.0368) time: 3.1482 data: 0.0088 max mem: 33369 +Epoch: [29] [1310/1319] eta: 0:00:28 lr: 1.4366567171917672e-05 loss: 0.0345 (0.0368) time: 3.1739 data: 0.0086 max mem: 33369 +Epoch: [29] Total time: 1:10:05 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 2:45:10 time: 3.8518 data: 3.7039 max mem: 33369 +Test: [ 100/2573] eta: 0:04:48 time: 0.0789 data: 0.0015 max mem: 33369 +Test: [ 200/2573] eta: 0:03:55 time: 0.0807 data: 0.0015 max mem: 33369 +Test: [ 300/2573] eta: 0:03:29 time: 0.0824 data: 0.0014 max mem: 33369 +Test: [ 400/2573] eta: 0:03:13 time: 0.0805 data: 0.0014 max mem: 33369 +Test: [ 500/2573] eta: 0:03:01 time: 0.0820 data: 0.0017 max mem: 33369 +Test: [ 600/2573] eta: 0:02:50 time: 0.0794 data: 0.0015 max mem: 33369 +Test: [ 700/2573] eta: 0:02:40 time: 0.0815 data: 0.0015 max mem: 33369 +Test: [ 800/2573] eta: 0:02:31 time: 0.0837 data: 0.0015 max mem: 33369 +Test: [ 900/2573] eta: 0:02:22 time: 0.0814 data: 0.0015 max mem: 33369 +Test: [1000/2573] eta: 0:02:12 time: 0.0805 data: 0.0015 max mem: 33369 +Test: [1100/2573] eta: 0:02:04 time: 0.0817 data: 0.0016 max mem: 33369 +Test: [1200/2573] eta: 0:01:55 time: 0.0822 data: 0.0015 max mem: 33369 +Test: [1300/2573] eta: 0:01:46 time: 0.0812 data: 0.0015 max mem: 33369 +Test: [1400/2573] eta: 0:01:38 time: 0.0793 data: 0.0015 max mem: 33369 +Test: [1500/2573] eta: 0:01:29 time: 0.0807 data: 0.0014 max mem: 33369 +Test: [1600/2573] eta: 0:01:21 time: 0.0856 data: 0.0017 max mem: 33369 +Test: [1700/2573] eta: 0:01:12 time: 0.0790 data: 0.0014 max mem: 33369 +Test: [1800/2573] eta: 0:01:04 time: 0.0840 data: 0.0016 max mem: 33369 +Test: [1900/2573] eta: 0:00:55 time: 0.0790 data: 0.0016 max mem: 33369 +Test: [2000/2573] eta: 0:00:47 time: 0.0807 data: 0.0015 max mem: 33369 +Test: [2100/2573] eta: 0:00:39 time: 0.0814 data: 0.0015 max mem: 33369 +Test: [2200/2573] eta: 0:00:30 time: 0.0828 data: 0.0015 max mem: 33369 +Test: [2300/2573] eta: 0:00:22 time: 0.0832 data: 0.0015 max mem: 33369 +Test: [2400/2573] eta: 0:00:14 time: 0.0808 data: 0.0016 max mem: 33369 +Test: [2500/2573] eta: 0:00:06 time: 0.0809 data: 0.0015 max mem: 33369 +Test: Total time: 0:03:32 +Final results: +Mean IoU is 64.35 + + precision@0.5 = 72.24 + precision@0.6 = 66.89 + precision@0.7 = 60.09 + precision@0.8 = 48.53 + precision@0.9 = 24.63 + overall IoU = 61.99 + +Average object IoU 64.34817430119543 +Overall IoU 61.98772048950195 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [30] [ 0/1319] eta: 3:47:43 lr: 1.4357749687236825e-05 loss: 0.0347 (0.0347) time: 10.3588 data: 2.1393 max mem: 33369 +Epoch: [30] [ 10/1319] eta: 1:23:29 lr: 1.4347951776302166e-05 loss: 0.0349 (0.0362) time: 3.8273 data: 0.2037 max mem: 33369 +Epoch: [30] [ 20/1319] eta: 1:15:57 lr: 1.433815312189048e-05 loss: 0.0349 (0.0363) time: 3.1662 data: 0.0100 max mem: 33369 +Epoch: [30] [ 30/1319] eta: 1:12:59 lr: 1.4328353723380728e-05 loss: 0.0307 (0.0355) time: 3.1608 data: 0.0098 max mem: 33369 +Epoch: [30] [ 40/1319] eta: 1:11:22 lr: 1.431855358015087e-05 loss: 0.0293 (0.0338) time: 3.1801 data: 0.0096 max mem: 33369 +Epoch: [30] [ 50/1319] eta: 1:10:05 lr: 1.4308752691577878e-05 loss: 0.0268 (0.0333) time: 3.1852 data: 0.0095 max mem: 33369 +Epoch: [30] [ 60/1319] eta: 1:08:59 lr: 1.4298951057037729e-05 loss: 0.0272 (0.0329) time: 3.1648 data: 0.0096 max mem: 33369 +Epoch: [30] [ 70/1319] eta: 1:08:09 lr: 1.4289148675905387e-05 loss: 0.0314 (0.0335) time: 3.1734 data: 0.0098 max mem: 33369 +Epoch: [30] [ 80/1319] eta: 1:07:18 lr: 1.4279345547554832e-05 loss: 0.0328 (0.0335) time: 3.1724 data: 0.0100 max mem: 33369 +Epoch: [30] [ 90/1319] eta: 1:06:35 lr: 1.4269541671359036e-05 loss: 0.0321 (0.0332) time: 3.1670 data: 0.0097 max mem: 33369 +Epoch: [30] [ 100/1319] eta: 1:05:58 lr: 1.4259737046689963e-05 loss: 0.0331 (0.0339) time: 3.1993 data: 0.0088 max mem: 33369 +Epoch: [30] [ 110/1319] eta: 1:05:22 lr: 1.424993167291858e-05 loss: 0.0343 (0.0335) time: 3.2141 data: 0.0095 max mem: 33369 +Epoch: [30] [ 120/1319] eta: 1:04:43 lr: 1.4240125549414829e-05 loss: 0.0344 (0.0338) time: 3.1935 data: 0.0102 max mem: 33369 +Epoch: [30] [ 130/1319] eta: 1:04:05 lr: 1.4230318675547643e-05 loss: 0.0349 (0.0341) time: 3.1794 data: 0.0107 max mem: 33369 +Epoch: [30] [ 140/1319] eta: 1:03:32 lr: 1.4220511050684946e-05 loss: 0.0342 (0.0342) time: 3.2003 data: 0.0109 max mem: 33369 +Epoch: [30] [ 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data: 0.0097 max mem: 33369 +Epoch: [30] [ 310/1319] eta: 0:53:54 lr: 1.4053665908255448e-05 loss: 0.0323 (0.0342) time: 3.1896 data: 0.0097 max mem: 33369 +Epoch: [30] [ 320/1319] eta: 0:53:20 lr: 1.4043844656216607e-05 loss: 0.0340 (0.0342) time: 3.1564 data: 0.0093 max mem: 33369 +Epoch: [30] [ 330/1319] eta: 0:52:48 lr: 1.4034022640976696e-05 loss: 0.0323 (0.0341) time: 3.1695 data: 0.0092 max mem: 33369 +Epoch: [30] [ 340/1319] eta: 0:52:15 lr: 1.4024199861882808e-05 loss: 0.0316 (0.0342) time: 3.1909 data: 0.0091 max mem: 33369 +Epoch: [30] [ 350/1319] eta: 0:51:44 lr: 1.4014376318280992e-05 loss: 0.0296 (0.0341) time: 3.2111 data: 0.0086 max mem: 33369 +Epoch: [30] [ 360/1319] eta: 0:51:12 lr: 1.4004552009516214e-05 loss: 0.0267 (0.0339) time: 3.2074 data: 0.0090 max mem: 33369 +Epoch: [30] [ 370/1319] eta: 0:50:39 lr: 1.3994726934932381e-05 loss: 0.0284 (0.0341) time: 3.1918 data: 0.0091 max mem: 33369 +Epoch: [30] [ 380/1319] eta: 0:50:07 lr: 1.3984901093872316e-05 loss: 0.0305 (0.0342) time: 3.1951 data: 0.0091 max mem: 33369 +Epoch: [30] [ 390/1319] eta: 0:49:34 lr: 1.3975074485677755e-05 loss: 0.0323 (0.0342) time: 3.1806 data: 0.0095 max mem: 33369 +Epoch: [30] [ 400/1319] eta: 0:49:03 lr: 1.3965247109689372e-05 loss: 0.0323 (0.0342) time: 3.1956 data: 0.0091 max mem: 33369 +Epoch: [30] [ 410/1319] eta: 0:48:31 lr: 1.3955418965246752e-05 loss: 0.0312 (0.0341) time: 3.2101 data: 0.0090 max mem: 33369 +Epoch: [30] [ 420/1319] eta: 0:48:00 lr: 1.394559005168839e-05 loss: 0.0322 (0.0342) time: 3.2302 data: 0.0103 max mem: 33369 +Epoch: [30] [ 430/1319] eta: 0:47:28 lr: 1.39357603683517e-05 loss: 0.0348 (0.0342) time: 3.2382 data: 0.0108 max mem: 33369 +Epoch: [30] [ 440/1319] eta: 0:46:57 lr: 1.3925929914573002e-05 loss: 0.0385 (0.0345) time: 3.2248 data: 0.0098 max mem: 33369 +Epoch: [30] [ 450/1319] eta: 0:46:25 lr: 1.3916098689687517e-05 loss: 0.0347 (0.0346) time: 3.2232 data: 0.0098 max mem: 33369 +Epoch: [30] [ 460/1319] eta: 0:45:52 lr: 1.3906266693029377e-05 loss: 0.0329 (0.0346) time: 3.1971 data: 0.0105 max mem: 33369 +Epoch: [30] [ 470/1319] eta: 0:45:20 lr: 1.3896433923931618e-05 loss: 0.0329 (0.0346) time: 3.1786 data: 0.0104 max mem: 33369 +Epoch: [30] [ 480/1319] eta: 0:44:48 lr: 1.3886600381726167e-05 loss: 0.0356 (0.0346) time: 3.1918 data: 0.0102 max mem: 33369 +Epoch: [30] [ 490/1319] eta: 0:44:15 lr: 1.3876766065743859e-05 loss: 0.0331 (0.0346) time: 3.1856 data: 0.0098 max mem: 33369 +Epoch: [30] [ 500/1319] eta: 0:43:43 lr: 1.3866930975314405e-05 loss: 0.0331 (0.0346) time: 3.1845 data: 0.0093 max mem: 33369 +Epoch: [30] [ 510/1319] eta: 0:43:10 lr: 1.3857095109766416e-05 loss: 0.0334 (0.0346) time: 3.1916 data: 0.0090 max mem: 33369 +Epoch: [30] [ 520/1319] eta: 0:42:39 lr: 1.3847258468427396e-05 loss: 0.0334 (0.0346) time: 3.2208 data: 0.0090 max mem: 33369 +Epoch: [30] [ 530/1319] eta: 0:42:07 lr: 1.3837421050623725e-05 loss: 0.0340 (0.0347) time: 3.2099 data: 0.0094 max mem: 33369 +Epoch: [30] [ 540/1319] eta: 0:41:33 lr: 1.3827582855680673e-05 loss: 0.0324 (0.0346) time: 3.1366 data: 0.0090 max mem: 33369 +Epoch: [30] [ 550/1319] eta: 0:41:01 lr: 1.381774388292239e-05 loss: 0.0308 (0.0345) time: 3.1493 data: 0.0082 max mem: 33369 +Epoch: [30] [ 560/1319] eta: 0:40:29 lr: 1.3807904131671886e-05 loss: 0.0325 (0.0345) time: 3.2040 data: 0.0082 max mem: 33369 +Epoch: [30] [ 570/1319] eta: 0:39:56 lr: 1.379806360125107e-05 loss: 0.0333 (0.0345) time: 3.1735 data: 0.0083 max mem: 33369 +Epoch: [30] [ 580/1319] eta: 0:39:24 lr: 1.3788222290980706e-05 loss: 0.0330 (0.0345) time: 3.1478 data: 0.0092 max mem: 33369 +Epoch: [30] [ 590/1319] eta: 0:38:52 lr: 1.3778380200180439e-05 loss: 0.0358 (0.0348) time: 3.1736 data: 0.0097 max mem: 33369 +Epoch: [30] [ 600/1319] eta: 0:38:20 lr: 1.3768537328168768e-05 loss: 0.0364 (0.0348) time: 3.1770 data: 0.0097 max mem: 33369 +Epoch: [30] [ 610/1319] eta: 0:37:47 lr: 1.3758693674263054e-05 loss: 0.0328 (0.0347) time: 3.1774 data: 0.0104 max mem: 33369 +Epoch: [30] [ 620/1319] eta: 0:37:16 lr: 1.374884923777953e-05 loss: 0.0326 (0.0348) time: 3.2032 data: 0.0106 max mem: 33369 +Epoch: [30] [ 630/1319] eta: 0:36:44 lr: 1.373900401803328e-05 loss: 0.0307 (0.0348) time: 3.2123 data: 0.0096 max mem: 33369 +Epoch: [30] [ 640/1319] eta: 0:36:11 lr: 1.3729158014338244e-05 loss: 0.0295 (0.0348) time: 3.1788 data: 0.0087 max mem: 33369 +Epoch: [30] [ 650/1319] eta: 0:35:39 lr: 1.371931122600722e-05 loss: 0.0272 (0.0347) time: 3.1801 data: 0.0090 max mem: 33369 +Epoch: [30] [ 660/1319] eta: 0:35:07 lr: 1.3709463652351833e-05 loss: 0.0297 (0.0347) time: 3.1837 data: 0.0089 max mem: 33369 +Epoch: [30] [ 670/1319] eta: 0:34:35 lr: 1.369961529268258e-05 loss: 0.0322 (0.0347) time: 3.1781 data: 0.0089 max mem: 33369 +Epoch: [30] [ 680/1319] eta: 0:34:03 lr: 1.3689766146308788e-05 loss: 0.0331 (0.0348) time: 3.1735 data: 0.0092 max mem: 33369 +Epoch: [30] [ 690/1319] eta: 0:33:30 lr: 1.3679916212538627e-05 loss: 0.0355 (0.0348) time: 3.1666 data: 0.0097 max mem: 33369 +Epoch: [30] [ 700/1319] eta: 0:32:58 lr: 1.3670065490679108e-05 loss: 0.0301 (0.0347) time: 3.1501 data: 0.0104 max mem: 33369 +Epoch: [30] [ 710/1319] eta: 0:32:26 lr: 1.3660213980036074e-05 loss: 0.0306 (0.0347) time: 3.1848 data: 0.0093 max mem: 33369 +Epoch: [30] [ 720/1319] eta: 0:31:54 lr: 1.3650361679914193e-05 loss: 0.0351 (0.0348) time: 3.2036 data: 0.0084 max mem: 33369 +Epoch: [30] [ 730/1319] eta: 0:31:22 lr: 1.3640508589616971e-05 loss: 0.0357 (0.0348) time: 3.1830 data: 0.0095 max mem: 33369 +Epoch: [30] [ 740/1319] eta: 0:30:50 lr: 1.3630654708446738e-05 loss: 0.0348 (0.0349) time: 3.1697 data: 0.0101 max mem: 33369 +Epoch: [30] [ 750/1319] eta: 0:30:17 lr: 1.3620800035704648e-05 loss: 0.0409 (0.0350) time: 3.1547 data: 0.0097 max mem: 33369 +Epoch: [30] [ 760/1319] eta: 0:29:45 lr: 1.3610944570690678e-05 loss: 0.0367 (0.0350) time: 3.1743 data: 0.0096 max mem: 33369 +Epoch: [30] [ 770/1319] eta: 0:29:13 lr: 1.3601088312703605e-05 loss: 0.0326 (0.0350) time: 3.1806 data: 0.0095 max mem: 33369 +Epoch: [30] [ 780/1319] eta: 0:28:42 lr: 1.3591231261041042e-05 loss: 0.0318 (0.0351) time: 3.1968 data: 0.0095 max mem: 33369 +Epoch: [30] [ 790/1319] eta: 0:28:09 lr: 1.3581373414999401e-05 loss: 0.0358 (0.0351) time: 3.1862 data: 0.0090 max mem: 33369 +Epoch: [30] [ 800/1319] eta: 0:27:37 lr: 1.3571514773873906e-05 loss: 0.0358 (0.0351) time: 3.1738 data: 0.0081 max mem: 33369 +Epoch: [30] [ 810/1319] eta: 0:27:05 lr: 1.3561655336958593e-05 loss: 0.0298 (0.0351) time: 3.1934 data: 0.0083 max mem: 33369 +Epoch: [30] [ 820/1319] eta: 0:26:34 lr: 1.3551795103546277e-05 loss: 0.0309 (0.0351) time: 3.2056 data: 0.0084 max mem: 33369 +Epoch: [30] [ 830/1319] eta: 0:26:01 lr: 1.3541934072928603e-05 loss: 0.0339 (0.0351) time: 3.1733 data: 0.0083 max mem: 33369 +Epoch: [30] [ 840/1319] eta: 0:25:29 lr: 1.3532072244395987e-05 loss: 0.0335 (0.0351) time: 3.1424 data: 0.0082 max mem: 33369 +Epoch: [30] [ 850/1319] eta: 0:24:57 lr: 1.3522209617237661e-05 loss: 0.0335 (0.0351) time: 3.1359 data: 0.0083 max mem: 33369 +Epoch: [30] [ 860/1319] eta: 0:24:25 lr: 1.3512346190741623e-05 loss: 0.0388 (0.0352) time: 3.1730 data: 0.0084 max mem: 33369 +Epoch: [30] [ 870/1319] eta: 0:23:53 lr: 1.3502481964194685e-05 loss: 0.0388 (0.0352) time: 3.1771 data: 0.0085 max mem: 33369 +Epoch: [30] [ 880/1319] eta: 0:23:21 lr: 1.3492616936882415e-05 loss: 0.0353 (0.0352) time: 3.1597 data: 0.0084 max mem: 33369 +Epoch: [30] [ 890/1319] eta: 0:22:49 lr: 1.3482751108089178e-05 loss: 0.0352 (0.0353) time: 3.1737 data: 0.0087 max mem: 33369 +Epoch: [30] [ 900/1319] eta: 0:22:17 lr: 1.3472884477098122e-05 loss: 0.0361 (0.0352) time: 3.1858 data: 0.0089 max mem: 33369 +Epoch: [30] [ 910/1319] eta: 0:21:45 lr: 1.3463017043191156e-05 loss: 0.0334 (0.0352) time: 3.1936 data: 0.0085 max mem: 33369 +Epoch: [30] [ 920/1319] eta: 0:21:13 lr: 1.3453148805648974e-05 loss: 0.0320 (0.0352) time: 3.1587 data: 0.0086 max mem: 33369 +Epoch: [30] [ 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33369 +Epoch: [30] [1010/1319] eta: 0:16:25 lr: 1.3364298384885935e-05 loss: 0.0299 (0.0352) time: 3.1924 data: 0.0101 max mem: 33369 +Epoch: [30] [1020/1319] eta: 0:15:53 lr: 1.3354422071156945e-05 loss: 0.0293 (0.0352) time: 3.1452 data: 0.0104 max mem: 33369 +Epoch: [30] [1030/1319] eta: 0:15:21 lr: 1.3344544945798354e-05 loss: 0.0367 (0.0353) time: 3.1754 data: 0.0101 max mem: 33369 +Epoch: [30] [1040/1319] eta: 0:14:49 lr: 1.3334667008075852e-05 loss: 0.0343 (0.0353) time: 3.2052 data: 0.0103 max mem: 33369 +Epoch: [30] [1050/1319] eta: 0:14:17 lr: 1.3324788257253885e-05 loss: 0.0297 (0.0353) time: 3.1880 data: 0.0094 max mem: 33369 +Epoch: [30] [1060/1319] eta: 0:13:45 lr: 1.3314908692595609e-05 loss: 0.0293 (0.0353) time: 3.1826 data: 0.0087 max mem: 33369 +Epoch: [30] [1070/1319] eta: 0:13:14 lr: 1.3305028313362919e-05 loss: 0.0332 (0.0353) time: 3.1904 data: 0.0090 max mem: 33369 +Epoch: [30] [1080/1319] eta: 0:12:42 lr: 1.3295147118816423e-05 loss: 0.0338 (0.0353) time: 3.1688 data: 0.0095 max mem: 33369 +Epoch: [30] [1090/1319] eta: 0:12:10 lr: 1.328526510821544e-05 loss: 0.0305 (0.0353) time: 3.1587 data: 0.0097 max mem: 33369 +Epoch: [30] [1100/1319] eta: 0:11:38 lr: 1.3275382280818008e-05 loss: 0.0305 (0.0353) time: 3.1885 data: 0.0092 max mem: 33369 +Epoch: [30] [1110/1319] eta: 0:11:06 lr: 1.3265498635880886e-05 loss: 0.0328 (0.0353) time: 3.1830 data: 0.0090 max mem: 33369 +Epoch: [30] [1120/1319] eta: 0:10:34 lr: 1.325561417265953e-05 loss: 0.0328 (0.0353) time: 3.1920 data: 0.0090 max mem: 33369 +Epoch: [30] [1130/1319] eta: 0:10:02 lr: 1.3245728890408104e-05 loss: 0.0377 (0.0354) time: 3.1817 data: 0.0091 max mem: 33369 +Epoch: [30] [1140/1319] eta: 0:09:30 lr: 1.3235842788379476e-05 loss: 0.0357 (0.0354) time: 3.1800 data: 0.0094 max mem: 33369 +Epoch: [30] [1150/1319] eta: 0:08:58 lr: 1.3225955865825202e-05 loss: 0.0306 (0.0354) time: 3.1784 data: 0.0096 max mem: 33369 +Epoch: [30] [1160/1319] eta: 0:08:26 lr: 1.321606812199554e-05 loss: 0.0329 (0.0354) time: 3.1399 data: 0.0090 max mem: 33369 +Epoch: [30] [1170/1319] eta: 0:07:54 lr: 1.320617955613944e-05 loss: 0.0331 (0.0354) time: 3.1575 data: 0.0093 max mem: 33369 +Epoch: [30] [1180/1319] eta: 0:07:23 lr: 1.3196290167504535e-05 loss: 0.0343 (0.0354) time: 3.1925 data: 0.0097 max mem: 33369 +Epoch: [30] [1190/1319] eta: 0:06:51 lr: 1.3186399955337153e-05 loss: 0.0374 (0.0354) time: 3.1719 data: 0.0094 max mem: 33369 +Epoch: [30] [1200/1319] eta: 0:06:19 lr: 1.3176508918882283e-05 loss: 0.0345 (0.0354) time: 3.1579 data: 0.0102 max mem: 33369 +Epoch: [30] [1210/1319] eta: 0:05:47 lr: 1.3166617057383607e-05 loss: 0.0305 (0.0353) time: 3.1731 data: 0.0101 max mem: 33369 +Epoch: [30] [1220/1319] eta: 0:05:15 lr: 1.3156724370083478e-05 loss: 0.0292 (0.0353) time: 3.1634 data: 0.0096 max mem: 33369 +Epoch: [30] [1230/1319] eta: 0:04:43 lr: 1.3146830856222919e-05 loss: 0.0314 (0.0353) time: 3.1843 data: 0.0102 max mem: 33369 +Epoch: [30] [1240/1319] eta: 0:04:11 lr: 1.3136936515041629e-05 loss: 0.0313 (0.0353) time: 3.1994 data: 0.0100 max mem: 33369 +Epoch: [30] [1250/1319] eta: 0:03:39 lr: 1.3127041345777947e-05 loss: 0.0317 (0.0353) time: 3.1860 data: 0.0091 max mem: 33369 +Epoch: [30] [1260/1319] eta: 0:03:08 lr: 1.3117145347668891e-05 loss: 0.0307 (0.0353) time: 3.1849 data: 0.0085 max mem: 33369 +Epoch: [30] [1270/1319] eta: 0:02:36 lr: 1.3107248519950133e-05 loss: 0.0314 (0.0353) time: 3.1708 data: 0.0080 max mem: 33369 +Epoch: [30] [1280/1319] eta: 0:02:04 lr: 1.3097350861856001e-05 loss: 0.0374 (0.0353) time: 3.1706 data: 0.0088 max mem: 33369 +Epoch: [30] [1290/1319] eta: 0:01:32 lr: 1.3087452372619463e-05 loss: 0.0319 (0.0353) time: 3.1807 data: 0.0095 max mem: 33369 +Epoch: [30] [1300/1319] eta: 0:01:00 lr: 1.3077553051472149e-05 loss: 0.0355 (0.0353) time: 3.1681 data: 0.0094 max mem: 33369 +Epoch: [30] [1310/1319] eta: 0:00:28 lr: 1.3067652897644308e-05 loss: 0.0355 (0.0354) time: 3.1458 data: 0.0085 max mem: 33369 +Epoch: [30] Total time: 1:10:02 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 2:50:19 time: 3.9717 data: 3.7566 max mem: 33369 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 100/2573] eta: 0:04:47 time: 0.0779 data: 0.0015 max mem: 33369 +Test: [ 200/2573] eta: 0:03:54 time: 0.0815 data: 0.0016 max mem: 33369 +Test: [ 300/2573] eta: 0:03:29 time: 0.0808 data: 0.0014 max mem: 33369 +Test: [ 400/2573] eta: 0:03:13 time: 0.0807 data: 0.0016 max mem: 33369 +Test: [ 500/2573] eta: 0:03:01 time: 0.0785 data: 0.0015 max mem: 33369 +Test: [ 600/2573] eta: 0:02:50 time: 0.0796 data: 0.0014 max mem: 33369 +Test: [ 700/2573] eta: 0:02:40 time: 0.0813 data: 0.0015 max mem: 33369 +Test: [ 800/2573] eta: 0:02:31 time: 0.0833 data: 0.0014 max mem: 33369 +Test: [ 900/2573] eta: 0:02:22 time: 0.0835 data: 0.0017 max mem: 33369 +Test: [1000/2573] eta: 0:02:13 time: 0.0814 data: 0.0015 max mem: 33369 +Test: [1100/2573] eta: 0:02:04 time: 0.0810 data: 0.0014 max mem: 33369 +Test: [1200/2573] eta: 0:01:55 time: 0.0807 data: 0.0014 max mem: 33369 +Test: [1300/2573] eta: 0:01:46 time: 0.0816 data: 0.0014 max mem: 33369 +Test: [1400/2573] eta: 0:01:38 time: 0.0803 data: 0.0015 max mem: 33369 +Test: [1500/2573] eta: 0:01:29 time: 0.0817 data: 0.0015 max mem: 33369 +Test: [1600/2573] eta: 0:01:21 time: 0.0839 data: 0.0014 max mem: 33369 +Test: [1700/2573] eta: 0:01:12 time: 0.0787 data: 0.0015 max mem: 33369 +Test: [1800/2573] eta: 0:01:04 time: 0.0856 data: 0.0019 max mem: 33369 +Test: [1900/2573] eta: 0:00:55 time: 0.0799 data: 0.0016 max mem: 33369 +Test: [2000/2573] eta: 0:00:47 time: 0.0800 data: 0.0016 max mem: 33369 +Test: [2100/2573] eta: 0:00:39 time: 0.0818 data: 0.0015 max mem: 33369 +Test: [2200/2573] eta: 0:00:30 time: 0.0823 data: 0.0013 max mem: 33369 +Test: [2300/2573] eta: 0:00:22 time: 0.0828 data: 0.0014 max mem: 33369 +Test: [2400/2573] eta: 0:00:14 time: 0.0775 data: 0.0015 max mem: 33369 +Test: [2500/2573] eta: 0:00:06 time: 0.0804 data: 0.0015 max mem: 33369 +Test: Total time: 0:03:32 +Final results: +Mean IoU is 64.89 + + precision@0.5 = 73.06 + precision@0.6 = 67.34 + precision@0.7 = 59.93 + precision@0.8 = 48.86 + precision@0.9 = 24.16 + overall IoU = 62.01 + +Average object IoU 64.88908905465128 +Overall IoU 62.00644302368164 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [31] [ 0/1319] eta: 4:02:20 lr: 1.3058742046620123e-05 loss: 0.0384 (0.0384) time: 11.0239 data: 2.5511 max mem: 33369 +Epoch: [31] [ 10/1319] eta: 1:25:42 lr: 1.3048840308573793e-05 loss: 0.0360 (0.0346) time: 3.9282 data: 0.2402 max mem: 33369 +Epoch: [31] [ 20/1319] eta: 1:17:36 lr: 1.3038937735606992e-05 loss: 0.0326 (0.0346) time: 3.2124 data: 0.0084 max mem: 33369 +Epoch: [31] [ 30/1319] eta: 1:14:07 lr: 1.3029034326944665e-05 loss: 0.0340 (0.0366) time: 3.1879 data: 0.0083 max mem: 33369 +Epoch: [31] [ 40/1319] eta: 1:12:15 lr: 1.3019130081810363e-05 loss: 0.0283 (0.0356) time: 3.1859 data: 0.0096 max mem: 33369 +Epoch: [31] [ 50/1319] eta: 1:10:57 lr: 1.3009224999426282e-05 loss: 0.0308 (0.0366) time: 3.2059 data: 0.0097 max mem: 33369 +Epoch: [31] [ 60/1319] eta: 1:09:48 lr: 1.2999319079013207e-05 loss: 0.0354 (0.0365) time: 3.1976 data: 0.0090 max mem: 33369 +Epoch: [31] [ 70/1319] eta: 1:08:43 lr: 1.298941231979056e-05 loss: 0.0328 (0.0363) time: 3.1648 data: 0.0094 max mem: 33369 +Epoch: [31] [ 80/1319] eta: 1:07:51 lr: 1.2979504720976363e-05 loss: 0.0303 (0.0367) time: 3.1633 data: 0.0093 max mem: 33369 +Epoch: [31] [ 90/1319] eta: 1:07:08 lr: 1.2969596281787253e-05 loss: 0.0319 (0.0366) time: 3.1964 data: 0.0091 max mem: 33369 +Epoch: [31] [ 100/1319] eta: 1:06:27 lr: 1.2959687001438464e-05 loss: 0.0303 (0.0363) time: 3.2068 data: 0.0093 max mem: 33369 +Epoch: [31] [ 110/1319] eta: 1:05:44 lr: 1.2949776879143838e-05 loss: 0.0301 (0.0359) time: 3.1906 data: 0.0094 max mem: 33369 +Epoch: [31] [ 120/1319] eta: 1:04:58 lr: 1.2939865914115796e-05 loss: 0.0301 (0.0359) time: 3.1565 data: 0.0102 max mem: 33369 +Epoch: [31] [ 130/1319] eta: 1:04:22 lr: 1.2929954105565368e-05 loss: 0.0296 (0.0359) time: 3.1728 data: 0.0095 max mem: 33369 +Epoch: [31] [ 140/1319] eta: 1:03:47 lr: 1.2920041452702167e-05 loss: 0.0292 (0.0360) time: 3.2133 data: 0.0087 max mem: 33369 +Epoch: [31] [ 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mem: 33369 +Epoch: [31] [ 230/1319] eta: 0:58:25 lr: 1.2830789451741262e-05 loss: 0.0296 (0.0347) time: 3.1648 data: 0.0089 max mem: 33369 +Epoch: [31] [ 240/1319] eta: 0:57:50 lr: 1.2820868311965862e-05 loss: 0.0296 (0.0345) time: 3.1606 data: 0.0093 max mem: 33369 +Epoch: [31] [ 250/1319] eta: 0:57:14 lr: 1.2810946319089204e-05 loss: 0.0292 (0.0344) time: 3.1483 data: 0.0101 max mem: 33369 +Epoch: [31] [ 260/1319] eta: 0:56:41 lr: 1.2801023472303672e-05 loss: 0.0311 (0.0344) time: 3.1620 data: 0.0102 max mem: 33369 +Epoch: [31] [ 270/1319] eta: 0:56:07 lr: 1.2791099770800195e-05 loss: 0.0322 (0.0343) time: 3.1676 data: 0.0100 max mem: 33369 +Epoch: [31] [ 280/1319] eta: 0:55:34 lr: 1.2781175213768214e-05 loss: 0.0322 (0.0343) time: 3.1726 data: 0.0094 max mem: 33369 +Epoch: [31] [ 290/1319] eta: 0:55:01 lr: 1.277124980039573e-05 loss: 0.0314 (0.0343) time: 3.1956 data: 0.0093 max mem: 33369 +Epoch: [31] [ 300/1319] eta: 0:54:27 lr: 1.2761323529869248e-05 loss: 0.0321 (0.0345) time: 3.1723 data: 0.0098 max mem: 33369 +Epoch: [31] [ 310/1319] eta: 0:53:54 lr: 1.2751396401373813e-05 loss: 0.0416 (0.0347) time: 3.1578 data: 0.0093 max mem: 33369 +Epoch: [31] [ 320/1319] eta: 0:53:22 lr: 1.2741468414092989e-05 loss: 0.0340 (0.0347) time: 3.1877 data: 0.0098 max mem: 33369 +Epoch: [31] [ 330/1319] eta: 0:52:49 lr: 1.2731539567208833e-05 loss: 0.0329 (0.0346) time: 3.1999 data: 0.0097 max mem: 33369 +Epoch: [31] [ 340/1319] eta: 0:52:17 lr: 1.2721609859901942e-05 loss: 0.0316 (0.0346) time: 3.1866 data: 0.0087 max mem: 33369 +Epoch: [31] [ 350/1319] eta: 0:51:43 lr: 1.2711679291351405e-05 loss: 0.0322 (0.0348) time: 3.1681 data: 0.0090 max mem: 33369 +Epoch: [31] [ 360/1319] eta: 0:51:11 lr: 1.2701747860734819e-05 loss: 0.0356 (0.0348) time: 3.1854 data: 0.0093 max mem: 33369 +Epoch: [31] [ 370/1319] eta: 0:50:38 lr: 1.2691815567228285e-05 loss: 0.0379 (0.0349) time: 3.1813 data: 0.0095 max mem: 33369 +Epoch: [31] [ 380/1319] eta: 0:50:06 lr: 1.2681882410006382e-05 loss: 0.0347 (0.0349) time: 3.1686 data: 0.0096 max mem: 33369 +Epoch: [31] [ 390/1319] eta: 0:49:32 lr: 1.26719483882422e-05 loss: 0.0330 (0.0349) time: 3.1575 data: 0.0093 max mem: 33369 +Epoch: [31] [ 400/1319] eta: 0:49:00 lr: 1.2662013501107303e-05 loss: 0.0325 (0.0349) time: 3.1719 data: 0.0093 max mem: 33369 +Epoch: [31] [ 410/1319] eta: 0:48:28 lr: 1.265207774777175e-05 loss: 0.0319 (0.0349) time: 3.2045 data: 0.0103 max mem: 33369 +Epoch: [31] [ 420/1319] eta: 0:47:56 lr: 1.2642141127404073e-05 loss: 0.0305 (0.0348) time: 3.1837 data: 0.0107 max mem: 33369 +Epoch: [31] [ 430/1319] eta: 0:47:24 lr: 1.2632203639171281e-05 loss: 0.0291 (0.0348) time: 3.1869 data: 0.0104 max mem: 33369 +Epoch: [31] [ 440/1319] eta: 0:46:52 lr: 1.2622265282238837e-05 loss: 0.0346 (0.0348) time: 3.2039 data: 0.0102 max mem: 33369 +Epoch: [31] [ 450/1319] eta: 0:46:20 lr: 1.2612326055770701e-05 loss: 0.0335 (0.0347) time: 3.2126 data: 0.0102 max mem: 33369 +Epoch: [31] [ 460/1319] eta: 0:45:48 lr: 1.2602385958929271e-05 loss: 0.0310 (0.0347) time: 3.2027 data: 0.0101 max mem: 33369 +Epoch: [31] [ 470/1319] eta: 0:45:15 lr: 1.2592444990875415e-05 loss: 0.0327 (0.0347) time: 3.1711 data: 0.0090 max mem: 33369 +Epoch: [31] [ 480/1319] eta: 0:44:42 lr: 1.258250315076846e-05 loss: 0.0344 (0.0347) time: 3.1521 data: 0.0095 max mem: 33369 +Epoch: [31] [ 490/1319] eta: 0:44:10 lr: 1.2572560437766163e-05 loss: 0.0353 (0.0347) time: 3.1604 data: 0.0097 max mem: 33369 +Epoch: [31] [ 500/1319] eta: 0:43:37 lr: 1.2562616851024742e-05 loss: 0.0310 (0.0347) time: 3.1711 data: 0.0084 max mem: 33369 +Epoch: [31] [ 510/1319] eta: 0:43:05 lr: 1.2552672389698855e-05 loss: 0.0299 (0.0346) time: 3.1813 data: 0.0086 max mem: 33369 +Epoch: [31] [ 520/1319] eta: 0:42:33 lr: 1.2542727052941597e-05 loss: 0.0312 (0.0346) time: 3.1878 data: 0.0091 max mem: 33369 +Epoch: [31] [ 530/1319] eta: 0:42:00 lr: 1.2532780839904498e-05 loss: 0.0346 (0.0346) time: 3.1525 data: 0.0095 max mem: 33369 +Epoch: [31] [ 540/1319] eta: 0:41:29 lr: 1.2522833749737507e-05 loss: 0.0307 (0.0346) time: 3.1675 data: 0.0094 max mem: 33369 +Epoch: [31] [ 550/1319] eta: 0:40:56 lr: 1.2512885781589004e-05 loss: 0.0286 (0.0345) time: 3.1807 data: 0.0087 max mem: 33369 +Epoch: [31] [ 560/1319] eta: 0:40:23 lr: 1.2502936934605792e-05 loss: 0.0310 (0.0345) time: 3.1387 data: 0.0089 max mem: 33369 +Epoch: [31] [ 570/1319] eta: 0:39:52 lr: 1.2492987207933083e-05 loss: 0.0318 (0.0344) time: 3.1814 data: 0.0096 max mem: 33369 +Epoch: [31] [ 580/1319] eta: 0:39:20 lr: 1.2483036600714508e-05 loss: 0.0282 (0.0343) time: 3.2062 data: 0.0091 max mem: 33369 +Epoch: [31] [ 590/1319] eta: 0:38:47 lr: 1.2473085112092107e-05 loss: 0.0292 (0.0343) time: 3.1793 data: 0.0092 max mem: 33369 +Epoch: [31] [ 600/1319] eta: 0:38:15 lr: 1.24631327412063e-05 loss: 0.0316 (0.0343) time: 3.1739 data: 0.0102 max mem: 33369 +Epoch: [31] [ 610/1319] eta: 0:37:43 lr: 1.2453179487195933e-05 loss: 0.0311 (0.0343) time: 3.1732 data: 0.0107 max mem: 33369 +Epoch: [31] [ 620/1319] eta: 0:37:11 lr: 1.2443225349198233e-05 loss: 0.0329 (0.0344) time: 3.1558 data: 0.0103 max mem: 33369 +Epoch: [31] [ 630/1319] eta: 0:36:38 lr: 1.2433270326348818e-05 loss: 0.0321 (0.0343) time: 3.1503 data: 0.0099 max mem: 33369 +Epoch: [31] [ 640/1319] eta: 0:36:06 lr: 1.2423314417781696e-05 loss: 0.0315 (0.0343) time: 3.1521 data: 0.0101 max mem: 33369 +Epoch: [31] [ 650/1319] eta: 0:35:34 lr: 1.2413357622629242e-05 loss: 0.0327 (0.0344) time: 3.1662 data: 0.0101 max mem: 33369 +Epoch: [31] [ 660/1319] eta: 0:35:02 lr: 1.240339994002222e-05 loss: 0.0328 (0.0345) time: 3.1915 data: 0.0099 max mem: 33369 +Epoch: [31] [ 670/1319] eta: 0:34:30 lr: 1.2393441369089758e-05 loss: 0.0317 (0.0344) time: 3.1624 data: 0.0095 max mem: 33369 +Epoch: [31] [ 680/1319] eta: 0:33:58 lr: 1.2383481908959357e-05 loss: 0.0321 (0.0345) time: 3.1544 data: 0.0100 max mem: 33369 +Epoch: [31] [ 690/1319] eta: 0:33:26 lr: 1.237352155875688e-05 loss: 0.0321 (0.0345) time: 3.1716 data: 0.0103 max mem: 33369 +Epoch: [31] [ 700/1319] eta: 0:32:54 lr: 1.236356031760655e-05 loss: 0.0309 (0.0345) time: 3.1858 data: 0.0100 max mem: 33369 +Epoch: [31] [ 710/1319] eta: 0:32:22 lr: 1.2353598184630927e-05 loss: 0.0328 (0.0345) time: 3.1977 data: 0.0103 max mem: 33369 +Epoch: [31] [ 720/1319] eta: 0:31:50 lr: 1.2343635158950937e-05 loss: 0.0344 (0.0346) time: 3.1827 data: 0.0108 max mem: 33369 +Epoch: [31] [ 730/1319] eta: 0:31:18 lr: 1.2333671239685849e-05 loss: 0.0326 (0.0346) time: 3.1895 data: 0.0107 max mem: 33369 +Epoch: [31] [ 740/1319] eta: 0:30:47 lr: 1.2323706425953264e-05 loss: 0.0297 (0.0345) time: 3.2197 data: 0.0095 max mem: 33369 +Epoch: [31] [ 750/1319] eta: 0:30:14 lr: 1.2313740716869131e-05 loss: 0.0281 (0.0344) time: 3.2009 data: 0.0083 max mem: 33369 +Epoch: [31] [ 760/1319] eta: 0:29:43 lr: 1.2303774111547706e-05 loss: 0.0266 (0.0344) time: 3.1809 data: 0.0084 max mem: 33369 +Epoch: [31] [ 770/1319] eta: 0:29:11 lr: 1.2293806609101593e-05 loss: 0.0290 (0.0344) time: 3.1822 data: 0.0087 max mem: 33369 +Epoch: [31] [ 780/1319] eta: 0:28:39 lr: 1.2283838208641708e-05 loss: 0.0385 (0.0344) time: 3.1758 data: 0.0084 max mem: 33369 +Epoch: [31] [ 790/1319] eta: 0:28:07 lr: 1.2273868909277286e-05 loss: 0.0354 (0.0347) time: 3.1929 data: 0.0084 max mem: 33369 +Epoch: [31] [ 800/1319] eta: 0:27:35 lr: 1.2263898710115878e-05 loss: 0.0304 (0.0346) time: 3.1681 data: 0.0088 max mem: 33369 +Epoch: [31] [ 810/1319] eta: 0:27:03 lr: 1.2253927610263324e-05 loss: 0.0301 (0.0346) time: 3.1500 data: 0.0091 max mem: 33369 +Epoch: [31] [ 820/1319] eta: 0:26:31 lr: 1.2243955608823781e-05 loss: 0.0344 (0.0346) time: 3.1887 data: 0.0086 max mem: 33369 +Epoch: [31] [ 830/1319] eta: 0:25:59 lr: 1.2233982704899707e-05 loss: 0.0329 (0.0347) time: 3.1805 data: 0.0085 max mem: 33369 +Epoch: [31] [ 840/1319] eta: 0:25:27 lr: 1.2224008897591841e-05 loss: 0.0320 (0.0347) time: 3.1813 data: 0.0087 max mem: 33369 +Epoch: [31] [ 850/1319] eta: 0:24:55 lr: 1.2214034185999218e-05 loss: 0.0300 (0.0346) time: 3.2035 data: 0.0083 max mem: 33369 +Epoch: [31] [ 860/1319] eta: 0:24:23 lr: 1.2204058569219158e-05 loss: 0.0300 (0.0346) time: 3.1808 data: 0.0087 max mem: 33369 +Epoch: [31] [ 870/1319] eta: 0:23:51 lr: 1.2194082046347242e-05 loss: 0.0327 (0.0345) time: 3.1767 data: 0.0093 max mem: 33369 +Epoch: [31] [ 880/1319] eta: 0:23:19 lr: 1.2184104616477345e-05 loss: 0.0337 (0.0346) time: 3.1898 data: 0.0093 max mem: 33369 +Epoch: [31] [ 890/1319] eta: 0:22:47 lr: 1.2174126278701602e-05 loss: 0.0348 (0.0346) time: 3.1674 data: 0.0094 max mem: 33369 +Epoch: [31] [ 900/1319] eta: 0:22:15 lr: 1.2164147032110409e-05 loss: 0.0306 (0.0347) time: 3.1654 data: 0.0098 max mem: 33369 +Epoch: [31] [ 910/1319] eta: 0:21:43 lr: 1.215416687579243e-05 loss: 0.0329 (0.0347) time: 3.1724 data: 0.0101 max mem: 33369 +Epoch: [31] [ 920/1319] eta: 0:21:11 lr: 1.2144185808834565e-05 loss: 0.0335 (0.0348) time: 3.1398 data: 0.0099 max mem: 33369 +Epoch: [31] [ 930/1319] eta: 0:20:39 lr: 1.213420383032198e-05 loss: 0.0317 (0.0348) time: 3.1299 data: 0.0093 max mem: 33369 +Epoch: [31] [ 940/1319] eta: 0:20:07 lr: 1.212422093933808e-05 loss: 0.0346 (0.0348) time: 3.1638 data: 0.0090 max mem: 33369 +Epoch: [31] [ 950/1319] eta: 0:19:35 lr: 1.2114237134964505e-05 loss: 0.0355 (0.0348) time: 3.1728 data: 0.0093 max mem: 33369 +Epoch: [31] [ 960/1319] eta: 0:19:03 lr: 1.210425241628114e-05 loss: 0.0329 (0.0348) time: 3.1344 data: 0.0094 max mem: 33369 +Epoch: [31] [ 970/1319] eta: 0:18:31 lr: 1.2094266782366075e-05 loss: 0.0342 (0.0348) time: 3.1296 data: 0.0089 max mem: 33369 +Epoch: [31] [ 980/1319] eta: 0:17:59 lr: 1.208428023229565e-05 loss: 0.0305 (0.0348) time: 3.1543 data: 0.0083 max mem: 33369 +Epoch: [31] [ 990/1319] eta: 0:17:27 lr: 1.2074292765144408e-05 loss: 0.0286 (0.0348) time: 3.1956 data: 0.0092 max mem: 33369 +Epoch: [31] [1000/1319] eta: 0:16:56 lr: 1.2064304379985111e-05 loss: 0.0285 (0.0348) time: 3.1991 data: 0.0098 max mem: 33369 +Epoch: [31] [1010/1319] eta: 0:16:24 lr: 1.2054315075888731e-05 loss: 0.0338 (0.0348) time: 3.1805 data: 0.0096 max mem: 33369 +Epoch: [31] [1020/1319] eta: 0:15:52 lr: 1.2044324851924447e-05 loss: 0.0344 (0.0348) time: 3.2054 data: 0.0093 max mem: 33369 +Epoch: [31] [1030/1319] eta: 0:15:20 lr: 1.2034333707159618e-05 loss: 0.0347 (0.0349) time: 3.2076 data: 0.0089 max mem: 33369 +Epoch: [31] [1040/1319] eta: 0:14:48 lr: 1.2024341640659817e-05 loss: 0.0385 (0.0349) time: 3.1685 data: 0.0095 max mem: 33369 +Epoch: [31] [1050/1319] eta: 0:14:16 lr: 1.2014348651488794e-05 loss: 0.0327 (0.0349) time: 3.1654 data: 0.0094 max mem: 33369 +Epoch: [31] [1060/1319] eta: 0:13:45 lr: 1.2004354738708488e-05 loss: 0.0323 (0.0349) time: 3.1961 data: 0.0091 max mem: 33369 +Epoch: [31] [1070/1319] eta: 0:13:13 lr: 1.1994359901379014e-05 loss: 0.0346 (0.0349) time: 3.1865 data: 0.0090 max mem: 33369 +Epoch: [31] [1080/1319] eta: 0:12:41 lr: 1.1984364138558649e-05 loss: 0.0353 (0.0350) time: 3.1856 data: 0.0089 max mem: 33369 +Epoch: [31] [1090/1319] eta: 0:12:09 lr: 1.1974367449303851e-05 loss: 0.0324 (0.0350) time: 3.1974 data: 0.0096 max mem: 33369 +Epoch: [31] [1100/1319] eta: 0:11:37 lr: 1.1964369832669236e-05 loss: 0.0315 (0.0350) time: 3.1809 data: 0.0103 max mem: 33369 +Epoch: [31] [1110/1319] eta: 0:11:05 lr: 1.195437128770757e-05 loss: 0.0319 (0.0350) time: 3.1869 data: 0.0104 max mem: 33369 +Epoch: [31] [1120/1319] eta: 0:10:33 lr: 1.194437181346979e-05 loss: 0.0319 (0.0350) time: 3.1947 data: 0.0103 max mem: 33369 +Epoch: [31] [1130/1319] eta: 0:10:02 lr: 1.1934371409004944e-05 loss: 0.0332 (0.0350) time: 3.1913 data: 0.0108 max mem: 33369 +Epoch: [31] [1140/1319] eta: 0:09:30 lr: 1.192437007336025e-05 loss: 0.0312 (0.0350) time: 3.1830 data: 0.0100 max mem: 33369 +Epoch: [31] [1150/1319] eta: 0:08:58 lr: 1.1914367805581053e-05 loss: 0.0323 (0.0350) time: 3.1777 data: 0.0082 max mem: 33369 +Epoch: [31] [1160/1319] eta: 0:08:26 lr: 1.1904364604710826e-05 loss: 0.0354 (0.0350) time: 3.1800 data: 0.0088 max mem: 33369 +Epoch: [31] [1170/1319] eta: 0:07:54 lr: 1.1894360469791169e-05 loss: 0.0312 (0.0350) time: 3.1649 data: 0.0092 max mem: 33369 +Epoch: [31] [1180/1319] eta: 0:07:22 lr: 1.1884355399861802e-05 loss: 0.0314 (0.0350) time: 3.1768 data: 0.0088 max mem: 33369 +Epoch: [31] [1190/1319] eta: 0:06:50 lr: 1.1874349393960545e-05 loss: 0.0408 (0.0351) time: 3.1809 data: 0.0086 max mem: 33369 +Epoch: [31] [1200/1319] eta: 0:06:19 lr: 1.1864342451123342e-05 loss: 0.0390 (0.0351) time: 3.1907 data: 0.0088 max mem: 33369 +Epoch: [31] [1210/1319] eta: 0:05:47 lr: 1.1854334570384235e-05 loss: 0.0286 (0.0350) time: 3.2022 data: 0.0093 max mem: 33369 +Epoch: [31] [1220/1319] eta: 0:05:15 lr: 1.1844325750775364e-05 loss: 0.0286 (0.0350) time: 3.1935 data: 0.0092 max mem: 33369 +Epoch: [31] [1230/1319] eta: 0:04:43 lr: 1.183431599132696e-05 loss: 0.0339 (0.0350) time: 3.1778 data: 0.0092 max mem: 33369 +Epoch: [31] [1240/1319] eta: 0:04:11 lr: 1.1824305291067328e-05 loss: 0.0333 (0.0350) time: 3.1891 data: 0.0090 max mem: 33369 +Epoch: [31] [1250/1319] eta: 0:03:39 lr: 1.1814293649022872e-05 loss: 0.0298 (0.0349) time: 3.1982 data: 0.0088 max mem: 33369 +Epoch: [31] [1260/1319] eta: 0:03:07 lr: 1.180428106421806e-05 loss: 0.0298 (0.0350) time: 3.2036 data: 0.0087 max mem: 33369 +Epoch: [31] [1270/1319] eta: 0:02:36 lr: 1.1794267535675433e-05 loss: 0.0287 (0.0349) time: 3.2099 data: 0.0087 max mem: 33369 +Epoch: [31] [1280/1319] eta: 0:02:04 lr: 1.1784253062415594e-05 loss: 0.0300 (0.0349) time: 3.1738 data: 0.0090 max mem: 33369 +Epoch: [31] [1290/1319] eta: 0:01:32 lr: 1.1774237643457209e-05 loss: 0.0329 (0.0349) time: 3.1621 data: 0.0087 max mem: 33369 +Epoch: [31] [1300/1319] eta: 0:01:00 lr: 1.1764221277816978e-05 loss: 0.0308 (0.0349) time: 3.1841 data: 0.0090 max mem: 33369 +Epoch: [31] [1310/1319] eta: 0:00:28 lr: 1.1754203964509668e-05 loss: 0.0297 (0.0349) time: 3.2105 data: 0.0082 max mem: 33369 +Epoch: [31] Total time: 1:10:02 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 2:45:51 time: 3.8676 data: 3.7647 max mem: 33369 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 100/2573] eta: 0:04:48 time: 0.0793 data: 0.0015 max mem: 33369 +Test: [ 200/2573] eta: 0:03:54 time: 0.0791 data: 0.0013 max mem: 33369 +Test: [ 300/2573] eta: 0:03:29 time: 0.0823 data: 0.0016 max mem: 33369 +Test: [ 400/2573] eta: 0:03:13 time: 0.0812 data: 0.0014 max mem: 33369 +Test: [ 500/2573] eta: 0:03:01 time: 0.0801 data: 0.0015 max mem: 33369 +Test: [ 600/2573] eta: 0:02:50 time: 0.0814 data: 0.0015 max mem: 33369 +Test: [ 700/2573] eta: 0:02:40 time: 0.0817 data: 0.0015 max mem: 33369 +Test: [ 800/2573] eta: 0:02:31 time: 0.0849 data: 0.0016 max mem: 33369 +Test: [ 900/2573] eta: 0:02:22 time: 0.0812 data: 0.0015 max mem: 33369 +Test: [1000/2573] eta: 0:02:13 time: 0.0823 data: 0.0017 max mem: 33369 +Test: [1100/2573] eta: 0:02:04 time: 0.0809 data: 0.0014 max mem: 33369 +Test: [1200/2573] eta: 0:01:55 time: 0.0810 data: 0.0015 max mem: 33369 +Test: [1300/2573] eta: 0:01:46 time: 0.0803 data: 0.0015 max mem: 33369 +Test: [1400/2573] eta: 0:01:38 time: 0.0800 data: 0.0017 max mem: 33369 +Test: [1500/2573] eta: 0:01:29 time: 0.0812 data: 0.0015 max mem: 33369 +Test: [1600/2573] eta: 0:01:21 time: 0.0861 data: 0.0016 max mem: 33369 +Test: [1700/2573] eta: 0:01:12 time: 0.0788 data: 0.0015 max mem: 33369 +Test: [1800/2573] eta: 0:01:04 time: 0.0824 data: 0.0016 max mem: 33369 +Test: [1900/2573] eta: 0:00:55 time: 0.0797 data: 0.0017 max mem: 33369 +Test: [2000/2573] eta: 0:00:47 time: 0.0811 data: 0.0015 max mem: 33369 +Test: [2100/2573] eta: 0:00:39 time: 0.0829 data: 0.0014 max mem: 33369 +Test: [2200/2573] eta: 0:00:30 time: 0.0810 data: 0.0014 max mem: 33369 +Test: [2300/2573] eta: 0:00:22 time: 0.0823 data: 0.0013 max mem: 33369 +Test: [2400/2573] eta: 0:00:14 time: 0.0779 data: 0.0015 max mem: 33369 +Test: [2500/2573] eta: 0:00:06 time: 0.0817 data: 0.0015 max mem: 33369 +Test: Total time: 0:03:32 +Final results: +Mean IoU is 64.80 + + precision@0.5 = 72.77 + precision@0.6 = 67.40 + precision@0.7 = 60.38 + precision@0.8 = 48.79 + precision@0.9 = 25.02 + overall IoU = 62.64 + +Average object IoU 64.79699523564514 +Overall IoU 62.6449089050293 +Better epoch: 31 + +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [32] [ 0/1319] eta: 1:59:13 lr: 1.1745187571461855e-05 loss: 0.0251 (0.0251) time: 5.4234 data: 2.1328 max mem: 33369 +Epoch: [32] [ 10/1319] eta: 1:14:16 lr: 1.1735168454865734e-05 loss: 0.0251 (0.0292) time: 3.4046 data: 0.2036 max mem: 33369 +Epoch: [32] [ 20/1319] eta: 1:11:13 lr: 1.1725148387734231e-05 loss: 0.0311 (0.0331) time: 3.1835 data: 0.0094 max mem: 33369 +Epoch: [32] [ 30/1319] eta: 1:09:56 lr: 1.1715127369074435e-05 loss: 0.0295 (0.0317) time: 3.1742 data: 0.0086 max mem: 33369 +Epoch: [32] [ 40/1319] eta: 1:08:59 lr: 1.1705105397891451e-05 loss: 0.0285 (0.0315) time: 3.1798 data: 0.0088 max mem: 33369 +Epoch: [32] [ 50/1319] eta: 1:08:13 lr: 1.1695082473188386e-05 loss: 0.0312 (0.0320) time: 3.1790 data: 0.0087 max mem: 33369 +Epoch: [32] [ 60/1319] eta: 1:07:30 lr: 1.1685058593966367e-05 loss: 0.0305 (0.0333) time: 3.1787 data: 0.0096 max mem: 33369 +Epoch: [32] [ 70/1319] eta: 1:06:56 lr: 1.1675033759224512e-05 loss: 0.0270 (0.0327) time: 3.1901 data: 0.0104 max mem: 33369 +Epoch: [32] [ 80/1319] eta: 1:06:15 lr: 1.1665007967959945e-05 loss: 0.0298 (0.0336) time: 3.1819 data: 0.0105 max mem: 33369 +Epoch: [32] [ 90/1319] eta: 1:05:48 lr: 1.1654981219167763e-05 loss: 0.0323 (0.0335) time: 3.2017 data: 0.0097 max mem: 33369 +Epoch: [32] [ 100/1319] eta: 1:05:11 lr: 1.1644953511841062e-05 loss: 0.0326 (0.0338) time: 3.2108 data: 0.0091 max mem: 33369 +Epoch: [32] [ 110/1319] eta: 1:04:35 lr: 1.1634924844970898e-05 loss: 0.0322 (0.0333) time: 3.1723 data: 0.0090 max mem: 33369 +Epoch: [32] [ 120/1319] eta: 1:04:01 lr: 1.1624895217546308e-05 loss: 0.0337 (0.0333) time: 3.1799 data: 0.0087 max mem: 33369 +Epoch: [32] [ 130/1319] eta: 1:03:24 lr: 1.1614864628554293e-05 loss: 0.0337 (0.0333) time: 3.1712 data: 0.0082 max mem: 33369 +Epoch: [32] [ 140/1319] eta: 1:02:51 lr: 1.160483307697981e-05 loss: 0.0292 (0.0331) time: 3.1678 data: 0.0081 max mem: 33369 +Epoch: [32] [ 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33369 +Epoch: [32] [ 230/1319] eta: 0:57:51 lr: 1.1514505628098139e-05 loss: 0.0292 (0.0332) time: 3.1927 data: 0.0102 max mem: 33369 +Epoch: [32] [ 240/1319] eta: 0:57:19 lr: 1.1504464394418176e-05 loss: 0.0306 (0.0334) time: 3.1789 data: 0.0098 max mem: 33369 +Epoch: [32] [ 250/1319] eta: 0:56:48 lr: 1.149442218685379e-05 loss: 0.0302 (0.0333) time: 3.1922 data: 0.0096 max mem: 33369 +Epoch: [32] [ 260/1319] eta: 0:56:17 lr: 1.1484379004364971e-05 loss: 0.0269 (0.0330) time: 3.2035 data: 0.0095 max mem: 33369 +Epoch: [32] [ 270/1319] eta: 0:55:43 lr: 1.147433484590956e-05 loss: 0.0278 (0.0331) time: 3.1781 data: 0.0099 max mem: 33369 +Epoch: [32] [ 280/1319] eta: 0:55:13 lr: 1.1464289710443295e-05 loss: 0.0282 (0.0329) time: 3.1900 data: 0.0100 max mem: 33369 +Epoch: [32] [ 290/1319] eta: 0:54:42 lr: 1.1454243596919765e-05 loss: 0.0303 (0.0333) time: 3.2168 data: 0.0097 max mem: 33369 +Epoch: [32] [ 300/1319] eta: 0:54:09 lr: 1.144419650429042e-05 loss: 0.0331 (0.0333) time: 3.1807 data: 0.0102 max mem: 33369 +Epoch: [32] [ 310/1319] eta: 0:53:36 lr: 1.1434148431504575e-05 loss: 0.0279 (0.0332) time: 3.1697 data: 0.0102 max mem: 33369 +Epoch: [32] [ 320/1319] eta: 0:53:04 lr: 1.1424099377509363e-05 loss: 0.0273 (0.0331) time: 3.1741 data: 0.0095 max mem: 33369 +Epoch: [32] [ 330/1319] eta: 0:52:32 lr: 1.141404934124978e-05 loss: 0.0298 (0.0330) time: 3.1733 data: 0.0098 max mem: 33369 +Epoch: [32] [ 340/1319] eta: 0:51:59 lr: 1.140399832166864e-05 loss: 0.0294 (0.0330) time: 3.1604 data: 0.0107 max mem: 33369 +Epoch: [32] [ 350/1319] eta: 0:51:28 lr: 1.1393946317706594e-05 loss: 0.0294 (0.0330) time: 3.1835 data: 0.0105 max mem: 33369 +Epoch: [32] [ 360/1319] eta: 0:50:56 lr: 1.138389332830211e-05 loss: 0.0319 (0.0331) time: 3.2029 data: 0.0096 max mem: 33369 +Epoch: [32] [ 370/1319] eta: 0:50:23 lr: 1.1373839352391454e-05 loss: 0.0338 (0.0332) time: 3.1684 data: 0.0092 max mem: 33369 +Epoch: [32] [ 380/1319] eta: 0:49:52 lr: 1.1363784388908714e-05 loss: 0.0350 (0.0333) time: 3.1897 data: 0.0091 max mem: 33369 +Epoch: [32] [ 390/1319] eta: 0:49:21 lr: 1.1353728436785773e-05 loss: 0.0319 (0.0333) time: 3.2123 data: 0.0090 max mem: 33369 +Epoch: [32] [ 400/1319] eta: 0:48:49 lr: 1.1343671494952302e-05 loss: 0.0339 (0.0335) time: 3.2007 data: 0.0094 max mem: 33369 +Epoch: [32] [ 410/1319] eta: 0:48:17 lr: 1.1333613562335765e-05 loss: 0.0374 (0.0336) time: 3.1797 data: 0.0093 max mem: 33369 +Epoch: [32] [ 420/1319] eta: 0:47:43 lr: 1.1323554637861402e-05 loss: 0.0339 (0.0336) time: 3.1438 data: 0.0099 max mem: 33369 +Epoch: [32] [ 430/1319] eta: 0:47:11 lr: 1.1313494720452216e-05 loss: 0.0308 (0.0336) time: 3.1525 data: 0.0098 max mem: 33369 +Epoch: [32] [ 440/1319] eta: 0:46:39 lr: 1.1303433809028986e-05 loss: 0.0279 (0.0335) time: 3.1774 data: 0.0092 max mem: 33369 +Epoch: [32] [ 450/1319] eta: 0:46:06 lr: 1.1293371902510248e-05 loss: 0.0350 (0.0336) time: 3.1540 data: 0.0093 max mem: 33369 +Epoch: [32] [ 460/1319] eta: 0:45:35 lr: 1.1283308999812288e-05 loss: 0.0368 (0.0336) time: 3.1593 data: 0.0092 max mem: 33369 +Epoch: [32] [ 470/1319] eta: 0:45:03 lr: 1.1273245099849142e-05 loss: 0.0283 (0.0336) time: 3.1901 data: 0.0095 max mem: 33369 +Epoch: [32] [ 480/1319] eta: 0:44:30 lr: 1.1263180201532567e-05 loss: 0.0309 (0.0335) time: 3.1670 data: 0.0096 max mem: 33369 +Epoch: [32] [ 490/1319] eta: 0:43:59 lr: 1.1253114303772065e-05 loss: 0.0309 (0.0335) time: 3.1727 data: 0.0093 max mem: 33369 +Epoch: [32] [ 500/1319] eta: 0:43:27 lr: 1.1243047405474862e-05 loss: 0.0264 (0.0334) time: 3.1907 data: 0.0092 max mem: 33369 +Epoch: [32] [ 510/1319] eta: 0:42:56 lr: 1.1232979505545897e-05 loss: 0.0282 (0.0335) time: 3.2032 data: 0.0092 max mem: 33369 +Epoch: [32] [ 520/1319] eta: 0:42:24 lr: 1.1222910602887823e-05 loss: 0.0320 (0.0335) time: 3.2097 data: 0.0090 max mem: 33369 +Epoch: [32] [ 530/1319] eta: 0:41:53 lr: 1.121284069640098e-05 loss: 0.0330 (0.0335) time: 3.2036 data: 0.0088 max mem: 33369 +Epoch: [32] [ 540/1319] eta: 0:41:21 lr: 1.1202769784983422e-05 loss: 0.0340 (0.0335) time: 3.1899 data: 0.0088 max mem: 33369 +Epoch: [32] [ 550/1319] eta: 0:40:49 lr: 1.1192697867530886e-05 loss: 0.0301 (0.0335) time: 3.1801 data: 0.0092 max mem: 33369 +Epoch: [32] [ 560/1319] eta: 0:40:17 lr: 1.1182624942936785e-05 loss: 0.0305 (0.0335) time: 3.1996 data: 0.0088 max mem: 33369 +Epoch: [32] [ 570/1319] eta: 0:39:45 lr: 1.1172551010092211e-05 loss: 0.0305 (0.0335) time: 3.1709 data: 0.0084 max mem: 33369 +Epoch: [32] [ 580/1319] eta: 0:39:13 lr: 1.1162476067885926e-05 loss: 0.0324 (0.0337) time: 3.1534 data: 0.0091 max mem: 33369 +Epoch: [32] [ 590/1319] eta: 0:38:41 lr: 1.1152400115204338e-05 loss: 0.0320 (0.0338) time: 3.1677 data: 0.0099 max mem: 33369 +Epoch: [32] [ 600/1319] eta: 0:38:09 lr: 1.1142323150931518e-05 loss: 0.0325 (0.0339) time: 3.1781 data: 0.0096 max mem: 33369 +Epoch: [32] [ 610/1319] eta: 0:37:37 lr: 1.1132245173949183e-05 loss: 0.0359 (0.0341) time: 3.1906 data: 0.0091 max mem: 33369 +Epoch: [32] [ 620/1319] eta: 0:37:05 lr: 1.112216618313668e-05 loss: 0.0321 (0.0340) time: 3.1946 data: 0.0094 max mem: 33369 +Epoch: [32] [ 630/1319] eta: 0:36:33 lr: 1.1112086177371001e-05 loss: 0.0279 (0.0340) time: 3.1751 data: 0.0092 max mem: 33369 +Epoch: [32] [ 640/1319] eta: 0:36:01 lr: 1.1102005155526735e-05 loss: 0.0279 (0.0339) time: 3.1706 data: 0.0090 max mem: 33369 +Epoch: [32] [ 650/1319] eta: 0:35:30 lr: 1.109192311647611e-05 loss: 0.0317 (0.0339) time: 3.2024 data: 0.0092 max mem: 33369 +Epoch: [32] [ 660/1319] eta: 0:34:58 lr: 1.1081840059088951e-05 loss: 0.0304 (0.0339) time: 3.2118 data: 0.0088 max mem: 33369 +Epoch: [32] [ 670/1319] eta: 0:34:27 lr: 1.1071755982232689e-05 loss: 0.0293 (0.0339) time: 3.2170 data: 0.0085 max mem: 33369 +Epoch: [32] [ 680/1319] eta: 0:33:55 lr: 1.1061670884772347e-05 loss: 0.0295 (0.0339) time: 3.1991 data: 0.0088 max mem: 33369 +Epoch: [32] [ 690/1319] eta: 0:33:23 lr: 1.1051584765570521e-05 loss: 0.0286 (0.0339) time: 3.1947 data: 0.0090 max mem: 33369 +Epoch: [32] [ 700/1319] eta: 0:32:52 lr: 1.1041497623487401e-05 loss: 0.0289 (0.0338) time: 3.2112 data: 0.0095 max mem: 33369 +Epoch: [32] [ 710/1319] eta: 0:32:20 lr: 1.103140945738074e-05 loss: 0.0345 (0.0339) time: 3.1905 data: 0.0093 max mem: 33369 +Epoch: [32] [ 720/1319] eta: 0:31:48 lr: 1.1021320266105851e-05 loss: 0.0378 (0.0339) time: 3.1821 data: 0.0098 max mem: 33369 +Epoch: [32] [ 730/1319] eta: 0:31:16 lr: 1.101123004851561e-05 loss: 0.0305 (0.0339) time: 3.1864 data: 0.0106 max mem: 33369 +Epoch: [32] [ 740/1319] eta: 0:30:44 lr: 1.1001138803460437e-05 loss: 0.0251 (0.0338) time: 3.1530 data: 0.0099 max mem: 33369 +Epoch: [32] [ 750/1319] eta: 0:30:12 lr: 1.099104652978828e-05 loss: 0.0256 (0.0338) time: 3.1846 data: 0.0088 max mem: 33369 +Epoch: [32] [ 760/1319] eta: 0:29:42 lr: 1.0980953226344629e-05 loss: 0.0284 (0.0337) time: 3.2955 data: 0.0091 max mem: 33369 +Epoch: [32] [ 770/1319] eta: 0:29:11 lr: 1.09708588919725e-05 loss: 0.0327 (0.0337) time: 3.3899 data: 0.0105 max mem: 33369 +Epoch: [32] [ 780/1319] eta: 0:28:41 lr: 1.096076352551242e-05 loss: 0.0340 (0.0338) time: 3.3829 data: 0.0111 max mem: 33369 +Epoch: [32] [ 790/1319] eta: 0:28:09 lr: 1.0950667125802427e-05 loss: 0.0343 (0.0338) time: 3.3282 data: 0.0105 max mem: 33369 +Epoch: [32] [ 800/1319] eta: 0:27:38 lr: 1.0940569691678052e-05 loss: 0.0333 (0.0338) time: 3.3358 data: 0.0096 max mem: 33369 +Epoch: [32] [ 810/1319] eta: 0:27:07 lr: 1.0930471221972321e-05 loss: 0.0299 (0.0337) time: 3.3227 data: 0.0105 max mem: 33369 +Epoch: [32] [ 820/1319] eta: 0:26:36 lr: 1.0920371715515753e-05 loss: 0.0285 (0.0337) time: 3.3322 data: 0.0113 max mem: 33369 +Epoch: [32] [ 830/1319] eta: 0:26:05 lr: 1.0910271171136331e-05 loss: 0.0325 (0.0338) time: 3.3649 data: 0.0109 max mem: 33369 +Epoch: [32] [ 840/1319] eta: 0:25:34 lr: 1.0900169587659515e-05 loss: 0.0331 (0.0338) time: 3.3442 data: 0.0113 max mem: 33369 +Epoch: [32] [ 850/1319] eta: 0:25:03 lr: 1.0890066963908222e-05 loss: 0.0280 (0.0337) time: 3.3311 data: 0.0117 max mem: 33369 +Epoch: [32] [ 860/1319] eta: 0:24:32 lr: 1.087996329870281e-05 loss: 0.0288 (0.0337) time: 3.3927 data: 0.0110 max mem: 33369 +Epoch: [32] [ 870/1319] eta: 0:24:01 lr: 1.0869858590861098e-05 loss: 0.0316 (0.0337) time: 3.4088 data: 0.0109 max mem: 33369 +Epoch: [32] [ 880/1319] eta: 0:23:30 lr: 1.085975283919833e-05 loss: 0.0290 (0.0337) time: 3.4127 data: 0.0113 max mem: 33369 +Epoch: [32] [ 890/1319] eta: 0:22:58 lr: 1.0849646042527184e-05 loss: 0.0296 (0.0337) time: 3.4135 data: 0.0113 max mem: 33369 +Epoch: [32] [ 900/1319] eta: 0:22:27 lr: 1.0839538199657755e-05 loss: 0.0297 (0.0337) time: 3.3502 data: 0.0110 max mem: 33369 +Epoch: [32] [ 910/1319] eta: 0:21:56 lr: 1.0829429309397535e-05 loss: 0.0306 (0.0337) time: 3.3773 data: 0.0110 max mem: 33369 +Epoch: [32] [ 920/1319] eta: 0:21:24 lr: 1.0819319370551438e-05 loss: 0.0315 (0.0337) time: 3.4407 data: 0.0107 max mem: 33369 +Epoch: [32] [ 930/1319] eta: 0:20:53 lr: 1.0809208381921764e-05 loss: 0.0312 (0.0337) time: 3.3929 data: 0.0105 max mem: 33369 +Epoch: [32] [ 940/1319] eta: 0:20:21 lr: 1.0799096342308196e-05 loss: 0.0321 (0.0337) time: 3.3429 data: 0.0106 max mem: 33369 +Epoch: [32] [ 950/1319] eta: 0:19:49 lr: 1.0788983250507807e-05 loss: 0.0320 (0.0337) time: 3.3419 data: 0.0101 max mem: 33369 +Epoch: [32] [ 960/1319] eta: 0:19:17 lr: 1.0778869105315014e-05 loss: 0.0320 (0.0337) time: 3.3220 data: 0.0111 max mem: 33369 +Epoch: [32] [ 970/1319] eta: 0:18:45 lr: 1.0768753905521617e-05 loss: 0.0331 (0.0337) time: 3.3193 data: 0.0111 max mem: 33369 +Epoch: [32] [ 980/1319] eta: 0:18:14 lr: 1.0758637649916756e-05 loss: 0.0331 (0.0338) time: 3.3540 data: 0.0098 max mem: 33369 +Epoch: [32] [ 990/1319] eta: 0:17:42 lr: 1.074852033728692e-05 loss: 0.0331 (0.0339) time: 3.3962 data: 0.0101 max mem: 33369 +Epoch: [32] [1000/1319] eta: 0:17:10 lr: 1.073840196641593e-05 loss: 0.0311 (0.0338) time: 3.4004 data: 0.0101 max mem: 33369 +Epoch: [32] [1010/1319] eta: 0:16:38 lr: 1.0728282536084938e-05 loss: 0.0311 (0.0339) time: 3.3858 data: 0.0096 max mem: 33369 +Epoch: [32] [1020/1319] eta: 0:16:07 lr: 1.0718162045072395e-05 loss: 0.0283 (0.0338) time: 3.4017 data: 0.0103 max mem: 33369 +Epoch: [32] [1030/1319] eta: 0:15:35 lr: 1.0708040492154082e-05 loss: 0.0271 (0.0339) time: 3.3962 data: 0.0110 max mem: 33369 +Epoch: [32] [1040/1319] eta: 0:15:02 lr: 1.069791787610307e-05 loss: 0.0304 (0.0339) time: 3.3165 data: 0.0110 max mem: 33369 +Epoch: [32] [1050/1319] eta: 0:14:30 lr: 1.0687794195689722e-05 loss: 0.0282 (0.0339) time: 3.3112 data: 0.0113 max mem: 33369 +Epoch: [32] [1060/1319] eta: 0:13:58 lr: 1.0677669449681687e-05 loss: 0.0296 (0.0339) time: 3.3389 data: 0.0114 max mem: 33369 +Epoch: [32] [1070/1319] eta: 0:13:26 lr: 1.0667543636843873e-05 loss: 0.0328 (0.0339) time: 3.3274 data: 0.0110 max mem: 33369 +Epoch: [32] [1080/1319] eta: 0:12:54 lr: 1.0657416755938468e-05 loss: 0.0356 (0.0340) time: 3.3466 data: 0.0107 max mem: 33369 +Epoch: [32] [1090/1319] eta: 0:12:22 lr: 1.0647288805724908e-05 loss: 0.0332 (0.0340) time: 3.3498 data: 0.0109 max mem: 33369 +Epoch: [32] [1100/1319] eta: 0:11:49 lr: 1.0637159784959879e-05 loss: 0.0332 (0.0341) time: 3.3481 data: 0.0116 max mem: 33369 +Epoch: [32] [1110/1319] eta: 0:11:17 lr: 1.0627029692397306e-05 loss: 0.0399 (0.0341) time: 3.3764 data: 0.0117 max mem: 33369 +Epoch: [32] [1120/1319] eta: 0:10:45 lr: 1.0616898526788328e-05 loss: 0.0307 (0.0341) time: 3.4058 data: 0.0114 max mem: 33369 +Epoch: [32] [1130/1319] eta: 0:10:13 lr: 1.0606766286881316e-05 loss: 0.0307 (0.0341) time: 3.3645 data: 0.0116 max mem: 33369 +Epoch: [32] [1140/1319] eta: 0:09:40 lr: 1.059663297142185e-05 loss: 0.0300 (0.0341) time: 3.2967 data: 0.0113 max mem: 33369 +Epoch: [32] [1150/1319] eta: 0:09:08 lr: 1.058649857915271e-05 loss: 0.0331 (0.0341) time: 3.3237 data: 0.0108 max mem: 33369 +Epoch: [32] [1160/1319] eta: 0:08:36 lr: 1.0576363108813862e-05 loss: 0.0364 (0.0341) time: 3.3634 data: 0.0103 max mem: 33369 +Epoch: [32] [1170/1319] eta: 0:08:03 lr: 1.0566226559142468e-05 loss: 0.0384 (0.0342) time: 3.3306 data: 0.0093 max mem: 33369 +Epoch: [32] [1180/1319] eta: 0:07:31 lr: 1.0556088928872841e-05 loss: 0.0321 (0.0342) time: 3.3266 data: 0.0090 max mem: 33369 +Epoch: [32] [1190/1319] eta: 0:06:59 lr: 1.0545950216736473e-05 loss: 0.0309 (0.0342) time: 3.3496 data: 0.0091 max mem: 33369 +Epoch: [32] [1200/1319] eta: 0:06:26 lr: 1.0535810421462011e-05 loss: 0.0329 (0.0343) time: 3.3489 data: 0.0091 max mem: 33369 +Epoch: [32] [1210/1319] eta: 0:05:54 lr: 1.0525669541775238e-05 loss: 0.0329 (0.0342) time: 3.3367 data: 0.0095 max mem: 33369 +Epoch: [32] [1220/1319] eta: 0:05:21 lr: 1.0515527576399085e-05 loss: 0.0300 (0.0342) time: 3.3175 data: 0.0093 max mem: 33369 +Epoch: [32] [1230/1319] eta: 0:04:49 lr: 1.050538452405359e-05 loss: 0.0335 (0.0342) time: 3.3394 data: 0.0100 max mem: 33369 +Epoch: [32] [1240/1319] eta: 0:04:17 lr: 1.049524038345592e-05 loss: 0.0329 (0.0342) time: 3.3621 data: 0.0108 max mem: 33369 +Epoch: [32] [1250/1319] eta: 0:03:44 lr: 1.048509515332035e-05 loss: 0.0277 (0.0342) time: 3.3623 data: 0.0103 max mem: 33369 +Epoch: [32] [1260/1319] eta: 0:03:12 lr: 1.0474948832358245e-05 loss: 0.0277 (0.0342) time: 3.4702 data: 0.0103 max mem: 33369 +Epoch: [32] [1270/1319] eta: 0:02:39 lr: 1.0464801419278068e-05 loss: 0.0326 (0.0342) time: 3.4528 data: 0.0105 max mem: 33369 +Epoch: [32] [1280/1319] eta: 0:02:07 lr: 1.0454652912785337e-05 loss: 0.0328 (0.0342) time: 3.3393 data: 0.0101 max mem: 33369 +Epoch: [32] [1290/1319] eta: 0:01:34 lr: 1.0444503311582662e-05 loss: 0.0328 (0.0343) time: 3.4338 data: 0.0099 max mem: 33369 +Epoch: [32] [1300/1319] eta: 0:01:01 lr: 1.0434352614369702e-05 loss: 0.0312 (0.0343) time: 3.4218 data: 0.0111 max mem: 33369 +Epoch: [32] [1310/1319] eta: 0:00:29 lr: 1.0424200819843158e-05 loss: 0.0290 (0.0342) time: 3.3281 data: 0.0104 max mem: 33369 +Epoch: [32] Total time: 1:11:43 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 2:47:34 time: 3.9077 data: 3.5069 max mem: 33369 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 100/2573] eta: 0:04:54 time: 0.0798 data: 0.0016 max mem: 33369 +Test: [ 200/2573] eta: 0:03:59 time: 0.0820 data: 0.0018 max mem: 33369 +Test: [ 300/2573] eta: 0:03:33 time: 0.0828 data: 0.0014 max mem: 33369 +Test: [ 400/2573] eta: 0:03:17 time: 0.0860 data: 0.0018 max mem: 33369 +Test: [ 500/2573] eta: 0:03:04 time: 0.0822 data: 0.0016 max mem: 33369 +Test: [ 600/2573] eta: 0:02:53 time: 0.0817 data: 0.0015 max mem: 33369 +Test: [ 700/2573] eta: 0:02:43 time: 0.0800 data: 0.0016 max mem: 33369 +Test: [ 800/2573] eta: 0:02:34 time: 0.0833 data: 0.0015 max mem: 33369 +Test: [ 900/2573] eta: 0:02:24 time: 0.0807 data: 0.0017 max mem: 33369 +Test: [1000/2573] eta: 0:02:15 time: 0.0802 data: 0.0015 max mem: 33369 +Test: [1100/2573] eta: 0:02:06 time: 0.0821 data: 0.0015 max mem: 33369 +Test: [1200/2573] eta: 0:01:57 time: 0.0814 data: 0.0015 max mem: 33369 +Test: [1300/2573] eta: 0:01:48 time: 0.0815 data: 0.0016 max mem: 33369 +Test: [1400/2573] eta: 0:01:39 time: 0.0856 data: 0.0020 max mem: 33369 +Test: [1500/2573] eta: 0:01:31 time: 0.0818 data: 0.0018 max mem: 33369 +Test: [1600/2573] eta: 0:01:22 time: 0.0884 data: 0.0020 max mem: 33369 +Test: [1700/2573] eta: 0:01:13 time: 0.0804 data: 0.0016 max mem: 33369 +Test: [1800/2573] eta: 0:01:05 time: 0.0827 data: 0.0016 max mem: 33369 +Test: [1900/2573] eta: 0:00:56 time: 0.0804 data: 0.0016 max mem: 33369 +Test: [2000/2573] eta: 0:00:48 time: 0.0871 data: 0.0021 max mem: 33369 +Test: [2100/2573] eta: 0:00:39 time: 0.0830 data: 0.0015 max mem: 33369 +Test: [2200/2573] eta: 0:00:31 time: 0.0877 data: 0.0018 max mem: 33369 +Test: [2300/2573] eta: 0:00:23 time: 0.0869 data: 0.0020 max mem: 33369 +Test: [2400/2573] eta: 0:00:14 time: 0.0818 data: 0.0018 max mem: 33369 +Test: [2500/2573] eta: 0:00:06 time: 0.0855 data: 0.0019 max mem: 33369 +Test: Total time: 0:03:37 +Final results: +Mean IoU is 64.86 + + precision@0.5 = 73.12 + precision@0.6 = 67.34 + precision@0.7 = 60.31 + precision@0.8 = 49.12 + precision@0.9 = 24.51 + overall IoU = 62.69 + +Average object IoU 64.86365866028969 +Overall IoU 62.69374465942383 +Better epoch: 32 + +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [33] [ 0/1319] eta: 2:02:46 lr: 1.04150632654866e-05 loss: 0.0256 (0.0256) time: 5.5847 data: 2.1830 max mem: 33369 +Epoch: [33] [ 10/1319] eta: 1:19:05 lr: 1.0404909382463066e-05 loss: 0.0256 (0.0262) time: 3.6252 data: 0.2074 max mem: 33369 +Epoch: [33] [ 20/1319] eta: 1:15:32 lr: 1.0394754398329612e-05 loss: 0.0281 (0.0303) time: 3.3848 data: 0.0103 max mem: 33369 +Epoch: [33] [ 30/1319] eta: 1:13:54 lr: 1.0384598311771345e-05 loss: 0.0301 (0.0298) time: 3.3383 data: 0.0112 max mem: 33369 +Epoch: [33] [ 40/1319] eta: 1:13:41 lr: 1.0374441121470351e-05 loss: 0.0331 (0.0310) time: 3.4229 data: 0.0107 max mem: 33369 +Epoch: [33] [ 50/1319] eta: 1:12:36 lr: 1.0364282826105723e-05 loss: 0.0359 (0.0316) time: 3.4223 data: 0.0099 max mem: 33369 +Epoch: [33] [ 60/1319] eta: 1:11:45 lr: 1.0354123424353528e-05 loss: 0.0302 (0.0319) time: 3.3425 data: 0.0100 max mem: 33369 +Epoch: [33] [ 70/1319] eta: 1:10:59 lr: 1.0343962914886797e-05 loss: 0.0302 (0.0317) time: 3.3512 data: 0.0098 max mem: 33369 +Epoch: [33] [ 80/1319] eta: 1:10:08 lr: 1.033380129637553e-05 loss: 0.0280 (0.0316) time: 3.3265 data: 0.0103 max mem: 33369 +Epoch: [33] [ 90/1319] eta: 1:09:23 lr: 1.0323638567486653e-05 loss: 0.0273 (0.0317) time: 3.3091 data: 0.0108 max mem: 33369 +Epoch: [33] [ 100/1319] eta: 1:08:52 lr: 1.0313474726884054e-05 loss: 0.0328 (0.0322) time: 3.3640 data: 0.0106 max mem: 33369 +Epoch: [33] [ 110/1319] eta: 1:08:11 lr: 1.0303309773228537e-05 loss: 0.0314 (0.0320) time: 3.3675 data: 0.0103 max mem: 33369 +Epoch: [33] [ 120/1319] eta: 1:07:33 lr: 1.0293143705177821e-05 loss: 0.0309 (0.0319) time: 3.3329 data: 0.0095 max mem: 33369 +Epoch: [33] [ 130/1319] eta: 1:06:54 lr: 1.0282976521386539e-05 loss: 0.0323 (0.0321) time: 3.3351 data: 0.0092 max mem: 33369 +Epoch: [33] [ 140/1319] eta: 1:06:29 lr: 1.0272808220506222e-05 loss: 0.0297 (0.0322) time: 3.4017 data: 0.0100 max mem: 33369 +Epoch: [33] [ 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data: 0.0092 max mem: 33369 +Epoch: [33] [ 310/1319] eta: 0:56:51 lr: 1.0099774868986322e-05 loss: 0.0314 (0.0327) time: 3.3765 data: 0.0088 max mem: 33369 +Epoch: [33] [ 320/1319] eta: 0:56:16 lr: 1.008958622631076e-05 loss: 0.0282 (0.0327) time: 3.3630 data: 0.0097 max mem: 33369 +Epoch: [33] [ 330/1319] eta: 0:55:39 lr: 1.0079396440320953e-05 loss: 0.0354 (0.0328) time: 3.3069 data: 0.0094 max mem: 33369 +Epoch: [33] [ 340/1319] eta: 0:55:03 lr: 1.0069205509604051e-05 loss: 0.0323 (0.0327) time: 3.2977 data: 0.0094 max mem: 33369 +Epoch: [33] [ 350/1319] eta: 0:54:28 lr: 1.0059013432743876e-05 loss: 0.0278 (0.0327) time: 3.3199 data: 0.0105 max mem: 33369 +Epoch: [33] [ 360/1319] eta: 0:53:54 lr: 1.0048820208320883e-05 loss: 0.0301 (0.0327) time: 3.3342 data: 0.0102 max mem: 33369 +Epoch: [33] [ 370/1319] eta: 0:53:20 lr: 1.0038625834912186e-05 loss: 0.0296 (0.0327) time: 3.3549 data: 0.0093 max mem: 33369 +Epoch: [33] [ 380/1319] eta: 0:52:46 lr: 1.0028430311091521e-05 loss: 0.0306 (0.0327) time: 3.3600 data: 0.0095 max mem: 33369 +Epoch: [33] [ 390/1319] eta: 0:52:11 lr: 1.0018233635429235e-05 loss: 0.0306 (0.0326) time: 3.3455 data: 0.0101 max mem: 33369 +Epoch: [33] [ 400/1319] eta: 0:51:37 lr: 1.0008035806492287e-05 loss: 0.0281 (0.0327) time: 3.3409 data: 0.0106 max mem: 33369 +Epoch: [33] [ 410/1319] eta: 0:51:04 lr: 9.99783682284423e-06 loss: 0.0306 (0.0328) time: 3.3729 data: 0.0110 max mem: 33369 +Epoch: [33] [ 420/1319] eta: 0:50:29 lr: 9.987636683045179e-06 loss: 0.0306 (0.0327) time: 3.3642 data: 0.0112 max mem: 33369 +Epoch: [33] [ 430/1319] eta: 0:49:54 lr: 9.977435385651839e-06 loss: 0.0269 (0.0327) time: 3.3306 data: 0.0108 max mem: 33369 +Epoch: [33] [ 440/1319] eta: 0:49:20 lr: 9.967232929217462e-06 loss: 0.0269 (0.0326) time: 3.3229 data: 0.0099 max mem: 33369 +Epoch: [33] [ 450/1319] eta: 0:48:46 lr: 9.957029312291845e-06 loss: 0.0277 (0.0326) time: 3.3350 data: 0.0103 max mem: 33369 +Epoch: [33] [ 460/1319] eta: 0:48:15 lr: 9.946824533421325e-06 loss: 0.0326 (0.0327) time: 3.4239 data: 0.0106 max mem: 33369 +Epoch: [33] [ 470/1319] eta: 0:47:40 lr: 9.936618591148734e-06 loss: 0.0318 (0.0327) time: 3.4182 data: 0.0096 max mem: 33369 +Epoch: [33] [ 480/1319] eta: 0:47:06 lr: 9.92641148401344e-06 loss: 0.0332 (0.0329) time: 3.3368 data: 0.0090 max mem: 33369 +Epoch: [33] [ 490/1319] eta: 0:46:31 lr: 9.916203210551294e-06 loss: 0.0339 (0.0329) time: 3.3067 data: 0.0090 max mem: 33369 +Epoch: [33] [ 500/1319] eta: 0:45:57 lr: 9.905993769294629e-06 loss: 0.0310 (0.0329) time: 3.3212 data: 0.0104 max mem: 33369 +Epoch: [33] [ 510/1319] eta: 0:45:24 lr: 9.895783158772255e-06 loss: 0.0339 (0.0330) time: 3.3839 data: 0.0105 max mem: 33369 +Epoch: [33] [ 520/1319] eta: 0:44:50 lr: 9.885571377509421e-06 loss: 0.0359 (0.0330) time: 3.3611 data: 0.0098 max mem: 33369 +Epoch: [33] [ 530/1319] eta: 0:44:15 lr: 9.875358424027841e-06 loss: 0.0305 (0.0330) time: 3.3053 data: 0.0096 max mem: 33369 +Epoch: [33] [ 540/1319] eta: 0:43:41 lr: 9.865144296845656e-06 loss: 0.0296 (0.0331) time: 3.3244 data: 0.0095 max mem: 33369 +Epoch: [33] [ 550/1319] eta: 0:43:07 lr: 9.85492899447742e-06 loss: 0.0287 (0.0330) time: 3.3410 data: 0.0096 max mem: 33369 +Epoch: [33] [ 560/1319] eta: 0:42:33 lr: 9.844712515434104e-06 loss: 0.0283 (0.0330) time: 3.3535 data: 0.0106 max mem: 33369 +Epoch: [33] [ 570/1319] eta: 0:41:59 lr: 9.83449485822307e-06 loss: 0.0316 (0.0330) time: 3.3614 data: 0.0126 max mem: 33369 +Epoch: [33] [ 580/1319] eta: 0:41:26 lr: 9.824276021348049e-06 loss: 0.0297 (0.0329) time: 3.3526 data: 0.0123 max mem: 33369 +Epoch: [33] [ 590/1319] eta: 0:40:52 lr: 9.814056003309152e-06 loss: 0.0297 (0.0329) time: 3.3424 data: 0.0107 max mem: 33369 +Epoch: [33] [ 600/1319] eta: 0:40:18 lr: 9.803834802602848e-06 loss: 0.0337 (0.0329) time: 3.3308 data: 0.0103 max mem: 33369 +Epoch: [33] [ 610/1319] eta: 0:39:44 lr: 9.793612417721937e-06 loss: 0.0313 (0.0330) time: 3.3515 data: 0.0110 max mem: 33369 +Epoch: [33] [ 620/1319] eta: 0:39:10 lr: 9.783388847155563e-06 loss: 0.0304 (0.0329) time: 3.3531 data: 0.0107 max mem: 33369 +Epoch: [33] [ 630/1319] eta: 0:38:37 lr: 9.773164089389164e-06 loss: 0.0296 (0.0329) time: 3.3604 data: 0.0107 max mem: 33369 +Epoch: [33] [ 640/1319] eta: 0:38:04 lr: 9.762938142904499e-06 loss: 0.0297 (0.0329) time: 3.4113 data: 0.0107 max mem: 33369 +Epoch: [33] [ 650/1319] eta: 0:37:30 lr: 9.752711006179608e-06 loss: 0.0292 (0.0329) time: 3.3760 data: 0.0098 max mem: 33369 +Epoch: [33] [ 660/1319] eta: 0:36:56 lr: 9.742482677688807e-06 loss: 0.0292 (0.0329) time: 3.3555 data: 0.0097 max mem: 33369 +Epoch: [33] [ 670/1319] eta: 0:36:22 lr: 9.732253155902685e-06 loss: 0.0290 (0.0329) time: 3.3582 data: 0.0106 max mem: 33369 +Epoch: [33] [ 680/1319] eta: 0:35:49 lr: 9.722022439288054e-06 loss: 0.0290 (0.0329) time: 3.3428 data: 0.0110 max mem: 33369 +Epoch: [33] [ 690/1319] eta: 0:35:15 lr: 9.711790526307984e-06 loss: 0.0306 (0.0328) time: 3.3732 data: 0.0104 max mem: 33369 +Epoch: [33] [ 700/1319] eta: 0:34:42 lr: 9.701557415421759e-06 loss: 0.0327 (0.0329) time: 3.3961 data: 0.0093 max mem: 33369 +Epoch: [33] [ 710/1319] eta: 0:34:09 lr: 9.69132310508487e-06 loss: 0.0318 (0.0329) time: 3.4143 data: 0.0094 max mem: 33369 +Epoch: [33] [ 720/1319] eta: 0:33:35 lr: 9.681087593749006e-06 loss: 0.0319 (0.0328) time: 3.3963 data: 0.0109 max mem: 33369 +Epoch: [33] [ 730/1319] eta: 0:33:02 lr: 9.670850879862032e-06 loss: 0.0326 (0.0328) time: 3.3878 data: 0.0113 max mem: 33369 +Epoch: [33] [ 740/1319] eta: 0:32:28 lr: 9.660612961867972e-06 loss: 0.0306 (0.0328) time: 3.3604 data: 0.0109 max mem: 33369 +Epoch: [33] [ 750/1319] eta: 0:31:54 lr: 9.650373838207014e-06 loss: 0.0275 (0.0328) time: 3.3266 data: 0.0113 max mem: 33369 +Epoch: [33] [ 760/1319] eta: 0:31:20 lr: 9.640133507315477e-06 loss: 0.0288 (0.0328) time: 3.3082 data: 0.0112 max mem: 33369 +Epoch: [33] [ 770/1319] eta: 0:30:46 lr: 9.62989196762581e-06 loss: 0.0326 (0.0329) time: 3.3342 data: 0.0110 max mem: 33369 +Epoch: [33] [ 780/1319] eta: 0:30:13 lr: 9.61964921756657e-06 loss: 0.0312 (0.0328) time: 3.3723 data: 0.0104 max mem: 33369 +Epoch: [33] [ 790/1319] eta: 0:29:40 lr: 9.609405255562397e-06 loss: 0.0271 (0.0328) time: 3.4080 data: 0.0104 max mem: 33369 +Epoch: [33] [ 800/1319] eta: 0:29:06 lr: 9.599160080034027e-06 loss: 0.0317 (0.0329) time: 3.3830 data: 0.0114 max mem: 33369 +Epoch: [33] [ 810/1319] eta: 0:28:32 lr: 9.588913689398257e-06 loss: 0.0314 (0.0329) time: 3.3141 data: 0.0119 max mem: 33369 +Epoch: [33] [ 820/1319] eta: 0:27:58 lr: 9.578666082067937e-06 loss: 0.0286 (0.0328) time: 3.3178 data: 0.0118 max mem: 33369 +Epoch: [33] [ 830/1319] eta: 0:27:24 lr: 9.568417256451955e-06 loss: 0.0341 (0.0330) time: 3.3720 data: 0.0114 max mem: 33369 +Epoch: [33] [ 840/1319] eta: 0:26:51 lr: 9.558167210955227e-06 loss: 0.0345 (0.0330) time: 3.3869 data: 0.0104 max mem: 33369 +Epoch: [33] [ 850/1319] eta: 0:26:17 lr: 9.547915943978656e-06 loss: 0.0304 (0.0330) time: 3.3702 data: 0.0088 max mem: 33369 +Epoch: [33] [ 860/1319] eta: 0:25:44 lr: 9.537663453919165e-06 loss: 0.0306 (0.0330) time: 3.4007 data: 0.0104 max mem: 33369 +Epoch: [33] [ 870/1319] eta: 0:25:10 lr: 9.52740973916964e-06 loss: 0.0316 (0.0330) time: 3.3888 data: 0.0122 max mem: 33369 +Epoch: [33] [ 880/1319] eta: 0:24:37 lr: 9.517154798118936e-06 loss: 0.0304 (0.0330) time: 3.3601 data: 0.0115 max mem: 33369 +Epoch: [33] [ 890/1319] eta: 0:24:03 lr: 9.506898629151863e-06 loss: 0.0329 (0.0331) time: 3.3918 data: 0.0108 max mem: 33369 +Epoch: [33] [ 900/1319] eta: 0:23:30 lr: 9.496641230649144e-06 loss: 0.0327 (0.0331) time: 3.3919 data: 0.0098 max mem: 33369 +Epoch: [33] [ 910/1319] eta: 0:22:55 lr: 9.48638260098744e-06 loss: 0.0261 (0.0330) time: 3.3125 data: 0.0098 max mem: 33369 +Epoch: [33] [ 920/1319] eta: 0:22:22 lr: 9.476122738539313e-06 loss: 0.0262 (0.0330) time: 3.2928 data: 0.0107 max mem: 33369 +Epoch: [33] [ 930/1319] eta: 0:21:48 lr: 9.465861641673206e-06 loss: 0.0281 (0.0329) time: 3.3416 data: 0.0109 max mem: 33369 +Epoch: [33] [ 940/1319] eta: 0:21:14 lr: 9.455599308753445e-06 loss: 0.0287 (0.0329) time: 3.3354 data: 0.0108 max mem: 33369 +Epoch: [33] [ 950/1319] eta: 0:20:40 lr: 9.445335738140192e-06 loss: 0.0326 (0.0329) time: 3.3190 data: 0.0100 max mem: 33369 +Epoch: [33] [ 960/1319] eta: 0:20:07 lr: 9.435070928189476e-06 loss: 0.0287 (0.0329) time: 3.3481 data: 0.0099 max mem: 33369 +Epoch: [33] [ 970/1319] eta: 0:19:33 lr: 9.424804877253139e-06 loss: 0.0280 (0.0328) time: 3.3529 data: 0.0102 max mem: 33369 +Epoch: [33] [ 980/1319] eta: 0:18:59 lr: 9.414537583678836e-06 loss: 0.0303 (0.0329) time: 3.3245 data: 0.0099 max mem: 33369 +Epoch: [33] [ 990/1319] eta: 0:18:25 lr: 9.404269045810016e-06 loss: 0.0323 (0.0329) time: 3.3225 data: 0.0102 max mem: 33369 +Epoch: [33] [1000/1319] eta: 0:17:52 lr: 9.393999261985916e-06 loss: 0.0331 (0.0329) time: 3.3366 data: 0.0123 max mem: 33369 +Epoch: [33] [1010/1319] eta: 0:17:18 lr: 9.383728230541512e-06 loss: 0.0327 (0.0329) time: 3.3351 data: 0.0126 max mem: 33369 +Epoch: [33] [1020/1319] eta: 0:16:45 lr: 9.373455949807552e-06 loss: 0.0327 (0.0329) time: 3.3591 data: 0.0108 max mem: 33369 +Epoch: [33] [1030/1319] eta: 0:16:11 lr: 9.363182418110507e-06 loss: 0.0325 (0.0328) time: 3.3438 data: 0.0103 max mem: 33369 +Epoch: [33] [1040/1319] eta: 0:15:37 lr: 9.352907633772557e-06 loss: 0.0294 (0.0328) time: 3.3091 data: 0.0107 max mem: 33369 +Epoch: [33] [1050/1319] eta: 0:15:03 lr: 9.342631595111597e-06 loss: 0.0286 (0.0328) time: 3.3018 data: 0.0112 max mem: 33369 +Epoch: [33] [1060/1319] eta: 0:14:29 lr: 9.332354300441178e-06 loss: 0.0280 (0.0329) time: 3.2824 data: 0.0113 max mem: 33369 +Epoch: [33] [1070/1319] eta: 0:13:56 lr: 9.322075748070539e-06 loss: 0.0314 (0.0329) time: 3.2918 data: 0.0105 max mem: 33369 +Epoch: [33] [1080/1319] eta: 0:13:22 lr: 9.311795936304561e-06 loss: 0.0285 (0.0329) time: 3.3173 data: 0.0107 max mem: 33369 +Epoch: [33] [1090/1319] eta: 0:12:49 lr: 9.301514863443759e-06 loss: 0.0298 (0.0328) time: 3.3541 data: 0.0120 max mem: 33369 +Epoch: [33] [1100/1319] eta: 0:12:15 lr: 9.291232527784269e-06 loss: 0.0316 (0.0329) time: 3.3790 data: 0.0122 max mem: 33369 +Epoch: [33] [1110/1319] eta: 0:11:41 lr: 9.280948927617811e-06 loss: 0.0327 (0.0329) time: 3.3604 data: 0.0119 max mem: 33369 +Epoch: [33] [1120/1319] eta: 0:11:08 lr: 9.270664061231702e-06 loss: 0.0305 (0.0329) time: 3.3360 data: 0.0117 max mem: 33369 +Epoch: [33] [1130/1319] eta: 0:10:34 lr: 9.260377926908826e-06 loss: 0.0298 (0.0329) time: 3.3650 data: 0.0120 max mem: 33369 +Epoch: [33] [1140/1319] eta: 0:10:01 lr: 9.250090522927605e-06 loss: 0.0295 (0.0329) time: 3.4006 data: 0.0117 max mem: 33369 +Epoch: [33] [1150/1319] eta: 0:09:27 lr: 9.239801847562006e-06 loss: 0.0295 (0.0329) time: 3.3558 data: 0.0120 max mem: 33369 +Epoch: [33] [1160/1319] eta: 0:08:53 lr: 9.229511899081506e-06 loss: 0.0288 (0.0329) time: 3.2967 data: 0.0126 max mem: 33369 +Epoch: [33] [1170/1319] eta: 0:08:20 lr: 9.219220675751069e-06 loss: 0.0281 (0.0328) time: 3.3324 data: 0.0122 max mem: 33369 +Epoch: [33] [1180/1319] eta: 0:07:46 lr: 9.20892817583115e-06 loss: 0.0284 (0.0328) time: 3.3535 data: 0.0120 max mem: 33369 +Epoch: [33] [1190/1319] eta: 0:07:13 lr: 9.19863439757767e-06 loss: 0.0296 (0.0329) time: 3.3319 data: 0.0119 max mem: 33369 +Epoch: [33] [1200/1319] eta: 0:06:39 lr: 9.188339339241987e-06 loss: 0.0317 (0.0329) time: 3.3650 data: 0.0115 max mem: 33369 +Epoch: [33] [1210/1319] eta: 0:06:05 lr: 9.178042999070898e-06 loss: 0.0313 (0.0329) time: 3.3480 data: 0.0112 max mem: 33369 +Epoch: [33] [1220/1319] eta: 0:05:32 lr: 9.16774537530659e-06 loss: 0.0318 (0.0330) time: 3.2886 data: 0.0105 max mem: 33369 +Epoch: [33] [1230/1319] eta: 0:04:58 lr: 9.157446466186662e-06 loss: 0.0323 (0.0330) time: 3.2970 data: 0.0095 max mem: 33369 +Epoch: [33] [1240/1319] eta: 0:04:25 lr: 9.147146269944078e-06 loss: 0.0300 (0.0329) time: 3.3499 data: 0.0095 max mem: 33369 +Epoch: [33] [1250/1319] eta: 0:03:51 lr: 9.136844784807162e-06 loss: 0.0279 (0.0329) time: 3.3358 data: 0.0099 max mem: 33369 +Epoch: [33] [1260/1319] eta: 0:03:18 lr: 9.126542008999582e-06 loss: 0.0307 (0.0329) time: 3.3328 data: 0.0108 max mem: 33369 +Epoch: [33] [1270/1319] eta: 0:02:44 lr: 9.11623794074031e-06 loss: 0.0314 (0.0330) time: 3.3696 data: 0.0109 max mem: 33369 +Epoch: [33] [1280/1319] eta: 0:02:10 lr: 9.105932578243631e-06 loss: 0.0307 (0.0330) time: 3.3444 data: 0.0100 max mem: 33369 +Epoch: [33] [1290/1319] eta: 0:01:37 lr: 9.095625919719118e-06 loss: 0.0332 (0.0330) time: 3.3475 data: 0.0097 max mem: 33369 +Epoch: [33] [1300/1319] eta: 0:01:03 lr: 9.085317963371604e-06 loss: 0.0333 (0.0330) time: 3.3648 data: 0.0089 max mem: 33369 +Epoch: [33] [1310/1319] eta: 0:00:30 lr: 9.075008707401167e-06 loss: 0.0299 (0.0330) time: 3.3917 data: 0.0084 max mem: 33369 +Epoch: [33] Total time: 1:13:47 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 2:50:41 time: 3.9802 data: 3.7260 max mem: 33369 +Test: [ 100/2573] eta: 0:04:51 time: 0.0787 data: 0.0017 max mem: 33369 +Test: [ 200/2573] eta: 0:03:56 time: 0.0808 data: 0.0017 max mem: 33369 +Test: [ 300/2573] eta: 0:03:31 time: 0.0826 data: 0.0018 max mem: 33369 +Test: [ 400/2573] eta: 0:03:15 time: 0.0837 data: 0.0018 max mem: 33369 +Test: [ 500/2573] eta: 0:03:04 time: 0.0853 data: 0.0019 max mem: 33369 +Test: [ 600/2573] eta: 0:02:53 time: 0.0821 data: 0.0015 max mem: 33369 +Test: [ 700/2573] eta: 0:02:43 time: 0.0822 data: 0.0015 max mem: 33369 +Test: [ 800/2573] eta: 0:02:34 time: 0.0858 data: 0.0019 max mem: 33369 +Test: [ 900/2573] eta: 0:02:24 time: 0.0823 data: 0.0015 max mem: 33369 +Test: [1000/2573] eta: 0:02:15 time: 0.0818 data: 0.0016 max mem: 33369 +Test: [1100/2573] eta: 0:02:06 time: 0.0831 data: 0.0019 max mem: 33369 +Test: [1200/2573] eta: 0:01:57 time: 0.0820 data: 0.0017 max mem: 33369 +Test: [1300/2573] eta: 0:01:48 time: 0.0813 data: 0.0016 max mem: 33369 +Test: [1400/2573] eta: 0:01:40 time: 0.0814 data: 0.0016 max mem: 33369 +Test: [1500/2573] eta: 0:01:31 time: 0.0806 data: 0.0016 max mem: 33369 +Test: [1600/2573] eta: 0:01:22 time: 0.0877 data: 0.0020 max mem: 33369 +Test: [1700/2573] eta: 0:01:14 time: 0.0860 data: 0.0020 max mem: 33369 +Test: [1800/2573] eta: 0:01:05 time: 0.0840 data: 0.0018 max mem: 33369 +Test: [1900/2573] eta: 0:00:57 time: 0.0806 data: 0.0016 max mem: 33369 +Test: [2000/2573] eta: 0:00:48 time: 0.0823 data: 0.0016 max mem: 33369 +Test: [2100/2573] eta: 0:00:40 time: 0.0845 data: 0.0016 max mem: 33369 +Test: [2200/2573] eta: 0:00:31 time: 0.0839 data: 0.0017 max mem: 33369 +Test: [2300/2573] eta: 0:00:23 time: 0.0844 data: 0.0017 max mem: 33369 +Test: [2400/2573] eta: 0:00:14 time: 0.0800 data: 0.0018 max mem: 33369 +Test: [2500/2573] eta: 0:00:06 time: 0.0831 data: 0.0019 max mem: 33369 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: Total time: 0:03:38 +Final results: +Mean IoU is 64.79 + + precision@0.5 = 73.06 + precision@0.6 = 67.40 + precision@0.7 = 60.29 + precision@0.8 = 48.55 + precision@0.9 = 25.12 + overall IoU = 62.48 + +Average object IoU 64.78675526011148 +Overall IoU 62.483680725097656 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [34] [ 0/1319] eta: 3:39:27 lr: 9.065729264358701e-06 loss: 0.0361 (0.0361) time: 9.9828 data: 3.2067 max mem: 33369 +Epoch: [34] [ 10/1319] eta: 1:28:35 lr: 9.05541753412883e-06 loss: 0.0253 (0.0281) time: 4.0608 data: 0.3015 max mem: 33369 +Epoch: [34] [ 20/1319] eta: 1:22:21 lr: 9.045104499029229e-06 loss: 0.0291 (0.0302) time: 3.4950 data: 0.0097 max mem: 33369 +Epoch: [34] [ 30/1319] eta: 1:18:31 lr: 9.03479015724125e-06 loss: 0.0311 (0.0312) time: 3.4324 data: 0.0091 max mem: 33369 +Epoch: [34] [ 40/1319] eta: 1:16:25 lr: 9.024474506941415e-06 loss: 0.0315 (0.0313) time: 3.3552 data: 0.0096 max mem: 33369 +Epoch: [34] [ 50/1319] eta: 1:14:30 lr: 9.014157546301385e-06 loss: 0.0289 (0.0312) time: 3.3179 data: 0.0105 max mem: 33369 +Epoch: [34] [ 60/1319] eta: 1:13:41 lr: 9.003839273487931e-06 loss: 0.0301 (0.0318) time: 3.3617 data: 0.0113 max mem: 33369 +Epoch: [34] [ 70/1319] eta: 1:12:34 lr: 8.99351968666293e-06 loss: 0.0304 (0.0311) time: 3.3939 data: 0.0111 max mem: 33369 +Epoch: [34] [ 80/1319] eta: 1:12:02 lr: 8.983198783983315e-06 loss: 0.0309 (0.0321) time: 3.4189 data: 0.0107 max mem: 33369 +Epoch: [34] [ 90/1319] eta: 1:11:04 lr: 8.972876563601101e-06 loss: 0.0343 (0.0318) time: 3.4086 data: 0.0105 max mem: 33369 +Epoch: [34] [ 100/1319] eta: 1:10:12 lr: 8.962553023663333e-06 loss: 0.0359 (0.0330) time: 3.3227 data: 0.0115 max mem: 33369 +Epoch: [34] [ 110/1319] eta: 1:09:26 lr: 8.952228162312077e-06 loss: 0.0370 (0.0325) time: 3.3426 data: 0.0121 max mem: 33369 +Epoch: [34] [ 120/1319] eta: 1:08:41 lr: 8.941901977684397e-06 loss: 0.0296 (0.0329) time: 3.3463 data: 0.0113 max mem: 33369 +Epoch: [34] [ 130/1319] eta: 1:08:03 lr: 8.93157446791234e-06 loss: 0.0337 (0.0328) time: 3.3679 data: 0.0109 max mem: 33369 +Epoch: [34] [ 140/1319] eta: 1:07:28 lr: 8.9212456311229e-06 loss: 0.0308 (0.0329) time: 3.4076 data: 0.0106 max mem: 33369 +Epoch: [34] [ 150/1319] eta: 1:06:50 lr: 8.910915465438025e-06 loss: 0.0321 (0.0333) time: 3.4039 data: 0.0107 max mem: 33369 +Epoch: [34] [ 160/1319] eta: 1:06:08 lr: 8.900583968974578e-06 loss: 0.0312 (0.0333) time: 3.3571 data: 0.0114 max mem: 33369 +Epoch: [34] [ 170/1319] eta: 1:05:28 lr: 8.89025113984432e-06 loss: 0.0303 (0.0332) time: 3.3328 data: 0.0117 max mem: 33369 +Epoch: [34] [ 180/1319] eta: 1:04:50 lr: 8.879916976153894e-06 loss: 0.0303 (0.0332) time: 3.3451 data: 0.0116 max mem: 33369 +Epoch: [34] [ 190/1319] eta: 1:04:13 lr: 8.869581476004788e-06 loss: 0.0317 (0.0331) time: 3.3589 data: 0.0115 max mem: 33369 +Epoch: [34] [ 200/1319] eta: 1:03:32 lr: 8.859244637493344e-06 loss: 0.0308 (0.0331) time: 3.3350 data: 0.0109 max mem: 33369 +Epoch: [34] [ 210/1319] eta: 1:02:59 lr: 8.84890645871071e-06 loss: 0.0301 (0.0330) time: 3.3625 data: 0.0107 max mem: 33369 +Epoch: [34] [ 220/1319] eta: 1:02:29 lr: 8.838566937742836e-06 loss: 0.0322 (0.0329) time: 3.4520 data: 0.0099 max mem: 33369 +Epoch: [34] [ 230/1319] eta: 1:01:51 lr: 8.828226072670449e-06 loss: 0.0322 (0.0330) time: 3.4091 data: 0.0098 max mem: 33369 +Epoch: [34] [ 240/1319] eta: 1:01:15 lr: 8.817883861569014e-06 loss: 0.0308 (0.0329) time: 3.3467 data: 0.0113 max mem: 33369 +Epoch: [34] [ 250/1319] eta: 1:00:39 lr: 8.807540302508743e-06 loss: 0.0307 (0.0331) time: 3.3604 data: 0.0113 max mem: 33369 +Epoch: [34] [ 260/1319] eta: 1:00:03 lr: 8.797195393554557e-06 loss: 0.0293 (0.0329) time: 3.3675 data: 0.0111 max mem: 33369 +Epoch: [34] [ 270/1319] eta: 0:59:30 lr: 8.786849132766063e-06 loss: 0.0265 (0.0328) time: 3.4025 data: 0.0114 max mem: 33369 +Epoch: [34] [ 280/1319] eta: 0:58:53 lr: 8.776501518197541e-06 loss: 0.0266 (0.0327) time: 3.3749 data: 0.0116 max mem: 33369 +Epoch: [34] [ 290/1319] eta: 0:58:17 lr: 8.76615254789792e-06 loss: 0.0310 (0.0328) time: 3.3323 data: 0.0117 max mem: 33369 +Epoch: [34] [ 300/1319] eta: 0:57:41 lr: 8.755802219910735e-06 loss: 0.0308 (0.0328) time: 3.3379 data: 0.0117 max mem: 33369 +Epoch: [34] [ 310/1319] eta: 0:57:07 lr: 8.745450532274145e-06 loss: 0.0302 (0.0327) time: 3.3697 data: 0.0112 max mem: 33369 +Epoch: [34] [ 320/1319] eta: 0:56:32 lr: 8.735097483020883e-06 loss: 0.0340 (0.0328) time: 3.3737 data: 0.0097 max mem: 33369 +Epoch: [34] [ 330/1319] eta: 0:55:57 lr: 8.724743070178239e-06 loss: 0.0371 (0.0329) time: 3.3497 data: 0.0094 max mem: 33369 +Epoch: [34] [ 340/1319] eta: 0:55:21 lr: 8.714387291768046e-06 loss: 0.0304 (0.0328) time: 3.3474 data: 0.0104 max mem: 33369 +Epoch: [34] [ 350/1319] eta: 0:54:44 lr: 8.704030145806636e-06 loss: 0.0270 (0.0327) time: 3.3129 data: 0.0103 max mem: 33369 +Epoch: [34] [ 360/1319] eta: 0:54:09 lr: 8.693671630304845e-06 loss: 0.0281 (0.0327) time: 3.3136 data: 0.0102 max mem: 33369 +Epoch: [34] [ 370/1319] eta: 0:53:33 lr: 8.683311743267978e-06 loss: 0.0309 (0.0326) time: 3.3323 data: 0.0104 max mem: 33369 +Epoch: [34] [ 380/1319] eta: 0:52:59 lr: 8.672950482695785e-06 loss: 0.0300 (0.0326) time: 3.3442 data: 0.0101 max mem: 33369 +Epoch: [34] [ 390/1319] eta: 0:52:24 lr: 8.662587846582436e-06 loss: 0.0299 (0.0327) time: 3.3472 data: 0.0096 max mem: 33369 +Epoch: [34] [ 400/1319] eta: 0:51:49 lr: 8.65222383291651e-06 loss: 0.0300 (0.0327) time: 3.3334 data: 0.0099 max mem: 33369 +Epoch: [34] [ 410/1319] eta: 0:51:14 lr: 8.641858439680947e-06 loss: 0.0300 (0.0327) time: 3.3259 data: 0.0109 max mem: 33369 +Epoch: [34] [ 420/1319] eta: 0:50:40 lr: 8.631491664853054e-06 loss: 0.0310 (0.0327) time: 3.3586 data: 0.0105 max mem: 33369 +Epoch: [34] [ 430/1319] eta: 0:50:08 lr: 8.621123506404469e-06 loss: 0.0334 (0.0329) time: 3.4430 data: 0.0106 max mem: 33369 +Epoch: [34] [ 440/1319] eta: 0:49:35 lr: 8.610753962301133e-06 loss: 0.0293 (0.0327) time: 3.4512 data: 0.0115 max mem: 33369 +Epoch: [34] [ 450/1319] eta: 0:49:00 lr: 8.600383030503278e-06 loss: 0.0293 (0.0328) time: 3.3741 data: 0.0115 max mem: 33369 +Epoch: [34] [ 460/1319] eta: 0:48:26 lr: 8.590010708965377e-06 loss: 0.0360 (0.0329) time: 3.3533 data: 0.0115 max mem: 33369 +Epoch: [34] [ 470/1319] eta: 0:47:55 lr: 8.579636995636159e-06 loss: 0.0360 (0.0330) time: 3.4480 data: 0.0103 max mem: 33369 +Epoch: [34] [ 480/1319] eta: 0:47:20 lr: 8.569261888458558e-06 loss: 0.0294 (0.0328) time: 3.4359 data: 0.0098 max mem: 33369 +Epoch: [34] [ 490/1319] eta: 0:46:46 lr: 8.558885385369697e-06 loss: 0.0249 (0.0328) time: 3.3600 data: 0.0116 max mem: 33369 +Epoch: [34] [ 500/1319] eta: 0:46:12 lr: 8.548507484300866e-06 loss: 0.0299 (0.0328) time: 3.3623 data: 0.0110 max mem: 33369 +Epoch: [34] [ 510/1319] eta: 0:45:37 lr: 8.538128183177479e-06 loss: 0.0344 (0.0329) time: 3.3420 data: 0.0098 max mem: 33369 +Epoch: [34] [ 520/1319] eta: 0:45:02 lr: 8.527747479919078e-06 loss: 0.0344 (0.0329) time: 3.3301 data: 0.0099 max mem: 33369 +Epoch: [34] [ 530/1319] eta: 0:44:29 lr: 8.517365372439296e-06 loss: 0.0316 (0.0329) time: 3.3519 data: 0.0105 max mem: 33369 +Epoch: [34] [ 540/1319] eta: 0:43:54 lr: 8.506981858645828e-06 loss: 0.0286 (0.0329) time: 3.3492 data: 0.0115 max mem: 33369 +Epoch: [34] [ 550/1319] eta: 0:43:19 lr: 8.496596936440405e-06 loss: 0.0288 (0.0328) time: 3.3150 data: 0.0119 max mem: 33369 +Epoch: [34] [ 560/1319] eta: 0:42:46 lr: 8.486210603718787e-06 loss: 0.0302 (0.0328) time: 3.3821 data: 0.0116 max mem: 33369 +Epoch: [34] [ 570/1319] eta: 0:42:12 lr: 8.475822858370701e-06 loss: 0.0301 (0.0328) time: 3.4059 data: 0.0115 max mem: 33369 +Epoch: [34] [ 580/1319] eta: 0:41:37 lr: 8.465433698279856e-06 loss: 0.0301 (0.0328) time: 3.3326 data: 0.0116 max mem: 33369 +Epoch: [34] [ 590/1319] eta: 0:41:06 lr: 8.455043121323896e-06 loss: 0.0292 (0.0328) time: 3.4448 data: 0.0104 max mem: 33369 +Epoch: [34] [ 600/1319] eta: 0:40:32 lr: 8.444651125374376e-06 loss: 0.0272 (0.0327) time: 3.4568 data: 0.0095 max mem: 33369 +Epoch: [34] [ 610/1319] eta: 0:39:57 lr: 8.43425770829675e-06 loss: 0.0272 (0.0326) time: 3.3292 data: 0.0093 max mem: 33369 +Epoch: [34] [ 620/1319] eta: 0:39:23 lr: 8.423862867950307e-06 loss: 0.0304 (0.0326) time: 3.3373 data: 0.0093 max mem: 33369 +Epoch: [34] [ 630/1319] eta: 0:38:50 lr: 8.413466602188201e-06 loss: 0.0301 (0.0326) time: 3.3929 data: 0.0099 max mem: 33369 +Epoch: [34] [ 640/1319] eta: 0:38:16 lr: 8.403068908857377e-06 loss: 0.0277 (0.0326) time: 3.4130 data: 0.0098 max mem: 33369 +Epoch: [34] [ 650/1319] eta: 0:37:42 lr: 8.39266978579857e-06 loss: 0.0266 (0.0326) time: 3.3957 data: 0.0098 max mem: 33369 +Epoch: [34] [ 660/1319] eta: 0:37:09 lr: 8.382269230846276e-06 loss: 0.0323 (0.0326) time: 3.3963 data: 0.0112 max mem: 33369 +Epoch: [34] [ 670/1319] eta: 0:36:34 lr: 8.371867241828703e-06 loss: 0.0344 (0.0326) time: 3.3687 data: 0.0120 max mem: 33369 +Epoch: [34] [ 680/1319] eta: 0:36:01 lr: 8.361463816567778e-06 loss: 0.0305 (0.0326) time: 3.3734 data: 0.0114 max mem: 33369 +Epoch: [34] [ 690/1319] eta: 0:35:26 lr: 8.3510589528791e-06 loss: 0.0290 (0.0326) time: 3.3451 data: 0.0113 max mem: 33369 +Epoch: [34] [ 700/1319] eta: 0:34:52 lr: 8.340652648571916e-06 loss: 0.0279 (0.0326) time: 3.3003 data: 0.0105 max mem: 33369 +Epoch: [34] [ 710/1319] eta: 0:34:17 lr: 8.330244901449094e-06 loss: 0.0279 (0.0326) time: 3.3179 data: 0.0099 max mem: 33369 +Epoch: [34] [ 720/1319] eta: 0:33:43 lr: 8.319835709307101e-06 loss: 0.0307 (0.0326) time: 3.3126 data: 0.0102 max mem: 33369 +Epoch: [34] [ 730/1319] eta: 0:33:09 lr: 8.309425069935955e-06 loss: 0.0307 (0.0326) time: 3.3152 data: 0.0109 max mem: 33369 +Epoch: [34] [ 740/1319] eta: 0:32:36 lr: 8.299012981119228e-06 loss: 0.0278 (0.0325) time: 3.3851 data: 0.0104 max mem: 33369 +Epoch: [34] [ 750/1319] eta: 0:32:01 lr: 8.288599440633996e-06 loss: 0.0288 (0.0325) time: 3.3822 data: 0.0112 max mem: 33369 +Epoch: [34] [ 760/1319] eta: 0:31:27 lr: 8.278184446250822e-06 loss: 0.0288 (0.0326) time: 3.3066 data: 0.0128 max mem: 33369 +Epoch: [34] [ 770/1319] eta: 0:30:53 lr: 8.267767995733725e-06 loss: 0.0288 (0.0326) time: 3.3025 data: 0.0115 max mem: 33369 +Epoch: [34] [ 780/1319] eta: 0:30:19 lr: 8.25735008684013e-06 loss: 0.0306 (0.0326) time: 3.3152 data: 0.0103 max mem: 33369 +Epoch: [34] [ 790/1319] eta: 0:29:44 lr: 8.246930717320888e-06 loss: 0.0268 (0.0325) time: 3.3173 data: 0.0108 max mem: 33369 +Epoch: [34] [ 800/1319] eta: 0:29:11 lr: 8.236509884920197e-06 loss: 0.0277 (0.0325) time: 3.3354 data: 0.0117 max mem: 33369 +Epoch: [34] [ 810/1319] eta: 0:28:37 lr: 8.226087587375607e-06 loss: 0.0283 (0.0324) time: 3.3536 data: 0.0112 max mem: 33369 +Epoch: [34] [ 820/1319] eta: 0:28:02 lr: 8.215663822417979e-06 loss: 0.0298 (0.0325) time: 3.3261 data: 0.0114 max mem: 33369 +Epoch: [34] [ 830/1319] eta: 0:27:29 lr: 8.20523858777144e-06 loss: 0.0298 (0.0325) time: 3.3227 data: 0.0117 max mem: 33369 +Epoch: [34] [ 840/1319] eta: 0:26:55 lr: 8.194811881153384e-06 loss: 0.0301 (0.0325) time: 3.3510 data: 0.0114 max mem: 33369 +Epoch: [34] [ 850/1319] eta: 0:26:21 lr: 8.184383700274422e-06 loss: 0.0277 (0.0324) time: 3.3497 data: 0.0113 max mem: 33369 +Epoch: [34] [ 860/1319] eta: 0:25:47 lr: 8.173954042838362e-06 loss: 0.0292 (0.0325) time: 3.3248 data: 0.0114 max mem: 33369 +Epoch: [34] [ 870/1319] eta: 0:25:13 lr: 8.163522906542168e-06 loss: 0.0324 (0.0325) time: 3.2861 data: 0.0099 max mem: 33369 +Epoch: [34] [ 880/1319] eta: 0:24:40 lr: 8.153090289075947e-06 loss: 0.0304 (0.0324) time: 3.4020 data: 0.0088 max mem: 33369 +Epoch: [34] [ 890/1319] eta: 0:24:06 lr: 8.142656188122887e-06 loss: 0.0286 (0.0324) time: 3.4342 data: 0.0091 max mem: 33369 +Epoch: [34] [ 900/1319] eta: 0:23:32 lr: 8.132220601359272e-06 loss: 0.0286 (0.0324) time: 3.3370 data: 0.0095 max mem: 33369 +Epoch: [34] [ 910/1319] eta: 0:22:58 lr: 8.121783526454415e-06 loss: 0.0289 (0.0324) time: 3.3245 data: 0.0095 max mem: 33369 +Epoch: [34] [ 920/1319] eta: 0:22:24 lr: 8.111344961070641e-06 loss: 0.0294 (0.0324) time: 3.3352 data: 0.0095 max mem: 33369 +Epoch: [34] [ 930/1319] eta: 0:21:51 lr: 8.100904902863262e-06 loss: 0.0296 (0.0323) time: 3.4035 data: 0.0099 max mem: 33369 +Epoch: [34] [ 940/1319] eta: 0:21:17 lr: 8.090463349480519e-06 loss: 0.0255 (0.0323) time: 3.3662 data: 0.0104 max mem: 33369 +Epoch: [34] [ 950/1319] eta: 0:20:43 lr: 8.080020298563588e-06 loss: 0.0340 (0.0324) time: 3.3133 data: 0.0114 max mem: 33369 +Epoch: [34] [ 960/1319] eta: 0:20:09 lr: 8.069575747746527e-06 loss: 0.0282 (0.0323) time: 3.3316 data: 0.0113 max mem: 33369 +Epoch: [34] [ 970/1319] eta: 0:19:35 lr: 8.059129694656241e-06 loss: 0.0274 (0.0323) time: 3.3361 data: 0.0110 max mem: 33369 +Epoch: [34] [ 980/1319] eta: 0:19:01 lr: 8.048682136912463e-06 loss: 0.0296 (0.0323) time: 3.3390 data: 0.0116 max mem: 33369 +Epoch: [34] [ 990/1319] eta: 0:18:28 lr: 8.038233072127722e-06 loss: 0.0318 (0.0324) time: 3.3199 data: 0.0123 max mem: 33369 +Epoch: [34] [1000/1319] eta: 0:17:54 lr: 8.027782497907283e-06 loss: 0.0318 (0.0324) time: 3.3555 data: 0.0124 max mem: 33369 +Epoch: [34] [1010/1319] eta: 0:17:20 lr: 8.017330411849153e-06 loss: 0.0287 (0.0323) time: 3.3995 data: 0.0116 max mem: 33369 +Epoch: [34] [1020/1319] eta: 0:16:47 lr: 8.006876811544029e-06 loss: 0.0286 (0.0323) time: 3.3822 data: 0.0112 max mem: 33369 +Epoch: [34] [1030/1319] eta: 0:16:13 lr: 7.996421694575264e-06 loss: 0.0275 (0.0323) time: 3.3849 data: 0.0109 max mem: 33369 +Epoch: [34] [1040/1319] eta: 0:15:39 lr: 7.985965058518847e-06 loss: 0.0308 (0.0324) time: 3.3687 data: 0.0105 max mem: 33369 +Epoch: [34] [1050/1319] eta: 0:15:06 lr: 7.97550690094334e-06 loss: 0.0309 (0.0323) time: 3.3236 data: 0.0110 max mem: 33369 +Epoch: [34] [1060/1319] eta: 0:14:32 lr: 7.965047219409881e-06 loss: 0.0309 (0.0324) time: 3.3515 data: 0.0105 max mem: 33369 +Epoch: [34] [1070/1319] eta: 0:13:58 lr: 7.95458601147213e-06 loss: 0.0316 (0.0324) time: 3.3740 data: 0.0096 max mem: 33369 +Epoch: [34] [1080/1319] eta: 0:13:25 lr: 7.944123274676236e-06 loss: 0.0321 (0.0324) time: 3.4173 data: 0.0105 max mem: 33369 +Epoch: [34] [1090/1319] eta: 0:12:51 lr: 7.933659006560817e-06 loss: 0.0325 (0.0324) time: 3.4255 data: 0.0104 max mem: 33369 +Epoch: [34] [1100/1319] eta: 0:12:18 lr: 7.923193204656895e-06 loss: 0.0307 (0.0324) time: 3.4066 data: 0.0102 max mem: 33369 +Epoch: [34] [1110/1319] eta: 0:11:44 lr: 7.912725866487896e-06 loss: 0.0283 (0.0324) time: 3.3780 data: 0.0100 max mem: 33369 +Epoch: [34] [1120/1319] eta: 0:11:10 lr: 7.902256989569599e-06 loss: 0.0265 (0.0323) time: 3.3419 data: 0.0090 max mem: 33369 +Epoch: [34] [1130/1319] eta: 0:10:36 lr: 7.891786571410098e-06 loss: 0.0307 (0.0323) time: 3.3964 data: 0.0096 max mem: 33369 +Epoch: [34] [1140/1319] eta: 0:10:03 lr: 7.881314609509776e-06 loss: 0.0310 (0.0323) time: 3.3674 data: 0.0102 max mem: 33369 +Epoch: [34] [1150/1319] eta: 0:09:29 lr: 7.870841101361268e-06 loss: 0.0259 (0.0323) time: 3.3134 data: 0.0101 max mem: 33369 +Epoch: [34] [1160/1319] eta: 0:08:55 lr: 7.860366044449406e-06 loss: 0.0266 (0.0322) time: 3.3135 data: 0.0102 max mem: 33369 +Epoch: [34] [1170/1319] eta: 0:08:21 lr: 7.849889436251218e-06 loss: 0.0277 (0.0323) time: 3.3187 data: 0.0095 max mem: 33369 +Epoch: [34] [1180/1319] eta: 0:07:48 lr: 7.839411274235871e-06 loss: 0.0289 (0.0323) time: 3.3325 data: 0.0098 max mem: 33369 +Epoch: [34] [1190/1319] eta: 0:07:14 lr: 7.82893155586463e-06 loss: 0.0311 (0.0323) time: 3.3386 data: 0.0106 max mem: 33369 +Epoch: [34] [1200/1319] eta: 0:06:40 lr: 7.818450278590844e-06 loss: 0.0310 (0.0323) time: 3.4233 data: 0.0101 max mem: 33369 +Epoch: [34] [1210/1319] eta: 0:06:07 lr: 7.80796743985987e-06 loss: 0.0274 (0.0323) time: 3.4402 data: 0.0099 max mem: 33369 +Epoch: [34] [1220/1319] eta: 0:05:33 lr: 7.797483037109084e-06 loss: 0.0306 (0.0323) time: 3.3403 data: 0.0097 max mem: 33369 +Epoch: [34] [1230/1319] eta: 0:04:59 lr: 7.786997067767811e-06 loss: 0.0272 (0.0323) time: 3.3225 data: 0.0101 max mem: 33369 +Epoch: [34] [1240/1319] eta: 0:04:26 lr: 7.776509529257303e-06 loss: 0.0295 (0.0323) time: 3.3680 data: 0.0105 max mem: 33369 +Epoch: [34] [1250/1319] eta: 0:03:52 lr: 7.766020418990693e-06 loss: 0.0309 (0.0323) time: 3.3779 data: 0.0095 max mem: 33369 +Epoch: [34] [1260/1319] eta: 0:03:18 lr: 7.755529734372952e-06 loss: 0.0288 (0.0323) time: 3.4340 data: 0.0092 max mem: 33369 +Epoch: [34] [1270/1319] eta: 0:02:45 lr: 7.74503747280087e-06 loss: 0.0270 (0.0323) time: 3.4407 data: 0.0092 max mem: 33369 +Epoch: [34] [1280/1319] eta: 0:02:11 lr: 7.734543631663006e-06 loss: 0.0294 (0.0322) time: 3.4213 data: 0.0101 max mem: 33369 +Epoch: [34] [1290/1319] eta: 0:01:37 lr: 7.724048208339646e-06 loss: 0.0298 (0.0323) time: 3.4351 data: 0.0100 max mem: 33369 +Epoch: [34] [1300/1319] eta: 0:01:04 lr: 7.713551200202774e-06 loss: 0.0305 (0.0322) time: 3.3534 data: 0.0102 max mem: 33369 +Epoch: [34] [1310/1319] eta: 0:00:30 lr: 7.703052604616029e-06 loss: 0.0312 (0.0323) time: 3.3792 data: 0.0105 max mem: 33369 +Epoch: [34] Total time: 1:14:06 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 3:01:56 time: 4.2427 data: 4.1544 max mem: 33369 +Test: [ 100/2573] eta: 0:04:57 time: 0.0790 data: 0.0017 max mem: 33369 +Test: [ 200/2573] eta: 0:04:00 time: 0.0803 data: 0.0016 max mem: 33369 +Test: [ 300/2573] eta: 0:03:34 time: 0.0815 data: 0.0015 max mem: 33369 +Test: [ 400/2573] eta: 0:03:18 time: 0.0841 data: 0.0018 max mem: 33369 +Test: [ 500/2573] eta: 0:03:05 time: 0.0814 data: 0.0015 max mem: 33369 +Test: [ 600/2573] eta: 0:02:54 time: 0.0857 data: 0.0019 max mem: 33369 +Test: [ 700/2573] eta: 0:02:44 time: 0.0832 data: 0.0016 max mem: 33369 +Test: [ 800/2573] eta: 0:02:34 time: 0.0858 data: 0.0017 max mem: 33369 +Test: [ 900/2573] eta: 0:02:24 time: 0.0814 data: 0.0016 max mem: 33369 +Test: [1000/2573] eta: 0:02:15 time: 0.0836 data: 0.0017 max mem: 33369 +Test: [1100/2573] eta: 0:02:06 time: 0.0817 data: 0.0016 max mem: 33369 +Test: [1200/2573] eta: 0:01:57 time: 0.0807 data: 0.0015 max mem: 33369 +Test: [1300/2573] eta: 0:01:48 time: 0.0819 data: 0.0015 max mem: 33369 +Test: [1400/2573] eta: 0:01:39 time: 0.0830 data: 0.0018 max mem: 33369 +Test: [1500/2573] eta: 0:01:31 time: 0.0820 data: 0.0016 max mem: 33369 +Test: [1600/2573] eta: 0:01:22 time: 0.0862 data: 0.0017 max mem: 33369 +Test: [1700/2573] eta: 0:01:14 time: 0.0827 data: 0.0017 max mem: 33369 +Test: [1800/2573] eta: 0:01:05 time: 0.0823 data: 0.0015 max mem: 33369 +Test: [1900/2573] eta: 0:00:56 time: 0.0807 data: 0.0017 max mem: 33369 +Test: [2000/2573] eta: 0:00:48 time: 0.0850 data: 0.0017 max mem: 33369 +Test: [2100/2573] eta: 0:00:39 time: 0.0832 data: 0.0016 max mem: 33369 +Test: [2200/2573] eta: 0:00:31 time: 0.0829 data: 0.0016 max mem: 33369 +Test: [2300/2573] eta: 0:00:23 time: 0.0865 data: 0.0019 max mem: 33369 +Test: [2400/2573] eta: 0:00:14 time: 0.0813 data: 0.0018 max mem: 33369 +Test: [2500/2573] eta: 0:00:06 time: 0.0826 data: 0.0016 max mem: 33369 +Test: Total time: 0:03:37 +Final results: +Mean IoU is 65.31 + + precision@0.5 = 73.28 + precision@0.6 = 67.81 + precision@0.7 = 60.50 + precision@0.8 = 48.75 + precision@0.9 = 24.94 + overall IoU = 63.00 + +Average object IoU 65.31466028981453 +Overall IoU 62.997623443603516 +Better epoch: 34 + +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [35] [ 0/1319] eta: 2:12:07 lr: 7.693602509132593e-06 loss: 0.0381 (0.0381) time: 6.0104 data: 2.3278 max mem: 33369 +Epoch: [35] [ 10/1319] eta: 1:18:36 lr: 7.683100890097833e-06 loss: 0.0330 (0.0337) time: 3.6033 data: 0.2198 max mem: 33369 +Epoch: [35] [ 20/1319] eta: 1:15:44 lr: 7.67259767592017e-06 loss: 0.0318 (0.0333) time: 3.3726 data: 0.0101 max mem: 33369 +Epoch: [35] [ 30/1319] eta: 1:13:51 lr: 7.66209286393032e-06 loss: 0.0318 (0.0344) time: 3.3475 data: 0.0117 max mem: 33369 +Epoch: [35] [ 40/1319] eta: 1:12:47 lr: 7.651586451450453e-06 loss: 0.0327 (0.0341) time: 3.3264 data: 0.0116 max mem: 33369 +Epoch: [35] [ 50/1319] eta: 1:12:03 lr: 7.641078435794154e-06 loss: 0.0276 (0.0329) time: 3.3579 data: 0.0103 max mem: 33369 +Epoch: [35] [ 60/1319] eta: 1:11:37 lr: 7.630568814266394e-06 loss: 0.0294 (0.0327) time: 3.4115 data: 0.0098 max mem: 33369 +Epoch: [35] [ 70/1319] eta: 1:11:06 lr: 7.62005758416347e-06 loss: 0.0324 (0.0328) time: 3.4387 data: 0.0104 max mem: 33369 +Epoch: [35] [ 80/1319] eta: 1:10:20 lr: 7.609544742772985e-06 loss: 0.0336 (0.0326) time: 3.3852 data: 0.0109 max mem: 33369 +Epoch: [35] [ 90/1319] eta: 1:09:34 lr: 7.599030287373793e-06 loss: 0.0340 (0.0327) time: 3.3270 data: 0.0115 max mem: 33369 +Epoch: [35] [ 100/1319] eta: 1:09:05 lr: 7.588514215235963e-06 loss: 0.0275 (0.0325) time: 3.3787 data: 0.0115 max mem: 33369 +Epoch: [35] [ 110/1319] eta: 1:08:22 lr: 7.5779965236207366e-06 loss: 0.0253 (0.0320) time: 3.3788 data: 0.0102 max mem: 33369 +Epoch: [35] [ 120/1319] eta: 1:07:38 lr: 7.5674772097804864e-06 loss: 0.0277 (0.0320) time: 3.3039 data: 0.0092 max mem: 33369 +Epoch: [35] [ 130/1319] eta: 1:07:02 lr: 7.556956270958658e-06 loss: 0.0253 (0.0313) time: 3.3260 data: 0.0094 max mem: 33369 +Epoch: [35] [ 140/1319] eta: 1:06:23 lr: 7.546433704389756e-06 loss: 0.0253 (0.0319) time: 3.3413 data: 0.0106 max mem: 33369 +Epoch: [35] [ 150/1319] eta: 1:05:43 lr: 7.535909507299282e-06 loss: 0.0271 (0.0314) time: 3.3089 data: 0.0114 max mem: 33369 +Epoch: [35] [ 160/1319] eta: 1:05:05 lr: 7.525383676903694e-06 loss: 0.0271 (0.0314) time: 3.3050 data: 0.0114 max mem: 33369 +Epoch: [35] [ 170/1319] eta: 1:04:31 lr: 7.514856210410369e-06 loss: 0.0310 (0.0315) time: 3.3394 data: 0.0109 max mem: 33369 +Epoch: [35] [ 180/1319] eta: 1:03:55 lr: 7.504327105017539e-06 loss: 0.0298 (0.0317) time: 3.3490 data: 0.0108 max mem: 33369 +Epoch: [35] [ 190/1319] eta: 1:03:17 lr: 7.493796357914276e-06 loss: 0.0286 (0.0314) time: 3.3185 data: 0.0124 max mem: 33369 +Epoch: [35] [ 200/1319] eta: 1:02:46 lr: 7.483263966280434e-06 loss: 0.0286 (0.0315) time: 3.3509 data: 0.0119 max mem: 33369 +Epoch: [35] [ 210/1319] eta: 1:02:08 lr: 7.4727299272865964e-06 loss: 0.0320 (0.0316) time: 3.3483 data: 0.0109 max mem: 33369 +Epoch: [35] [ 220/1319] eta: 1:01:32 lr: 7.462194238094052e-06 loss: 0.0301 (0.0316) time: 3.2995 data: 0.0103 max mem: 33369 +Epoch: [35] [ 230/1319] eta: 1:01:01 lr: 7.4516568958547115e-06 loss: 0.0301 (0.0317) time: 3.3574 data: 0.0097 max mem: 33369 +Epoch: [35] [ 240/1319] eta: 1:00:26 lr: 7.4411178977111085e-06 loss: 0.0277 (0.0315) time: 3.3787 data: 0.0107 max mem: 33369 +Epoch: [35] [ 250/1319] eta: 0:59:55 lr: 7.430577240796325e-06 loss: 0.0259 (0.0315) time: 3.3808 data: 0.0106 max mem: 33369 +Epoch: [35] [ 260/1319] eta: 0:59:20 lr: 7.420034922233955e-06 loss: 0.0281 (0.0314) time: 3.3740 data: 0.0101 max mem: 33369 +Epoch: [35] [ 270/1319] eta: 0:58:44 lr: 7.4094909391380505e-06 loss: 0.0294 (0.0314) time: 3.3212 data: 0.0104 max mem: 33369 +Epoch: [35] [ 280/1319] eta: 0:58:12 lr: 7.398945288613088e-06 loss: 0.0315 (0.0315) time: 3.3502 data: 0.0107 max mem: 33369 +Epoch: [35] [ 290/1319] eta: 0:57:37 lr: 7.388397967753893e-06 loss: 0.0321 (0.0317) time: 3.3603 data: 0.0114 max mem: 33369 +Epoch: [35] [ 300/1319] eta: 0:57:07 lr: 7.3778489736456335e-06 loss: 0.0316 (0.0317) time: 3.3970 data: 0.0111 max mem: 33369 +Epoch: [35] [ 310/1319] eta: 0:56:34 lr: 7.367298303363743e-06 loss: 0.0313 (0.0318) time: 3.4190 data: 0.0114 max mem: 33369 +Epoch: [35] [ 320/1319] eta: 0:55:59 lr: 7.35674595397388e-06 loss: 0.0262 (0.0316) time: 3.3517 data: 0.0123 max mem: 33369 +Epoch: [35] [ 330/1319] eta: 0:55:28 lr: 7.34619192253189e-06 loss: 0.0257 (0.0315) time: 3.3953 data: 0.0109 max mem: 33369 +Epoch: [35] [ 340/1319] eta: 0:54:55 lr: 7.335636206083729e-06 loss: 0.0316 (0.0316) time: 3.4157 data: 0.0112 max mem: 33369 +Epoch: [35] [ 350/1319] eta: 0:54:22 lr: 7.325078801665445e-06 loss: 0.0323 (0.0316) time: 3.3790 data: 0.0122 max mem: 33369 +Epoch: [35] [ 360/1319] eta: 0:53:49 lr: 7.31451970630312e-06 loss: 0.0289 (0.0316) time: 3.3904 data: 0.0110 max mem: 33369 +Epoch: [35] [ 370/1319] eta: 0:53:18 lr: 7.303958917012809e-06 loss: 0.0273 (0.0315) time: 3.4334 data: 0.0100 max mem: 33369 +Epoch: [35] [ 380/1319] eta: 0:52:43 lr: 7.293396430800509e-06 loss: 0.0288 (0.0316) time: 3.3937 data: 0.0093 max mem: 33369 +Epoch: [35] [ 390/1319] eta: 0:52:09 lr: 7.282832244662077e-06 loss: 0.0303 (0.0316) time: 3.3394 data: 0.0098 max mem: 33369 +Epoch: [35] [ 400/1319] eta: 0:51:35 lr: 7.272266355583221e-06 loss: 0.0328 (0.0319) time: 3.3517 data: 0.0104 max mem: 33369 +Epoch: [35] [ 410/1319] eta: 0:51:01 lr: 7.261698760539424e-06 loss: 0.0315 (0.0318) time: 3.3602 data: 0.0102 max mem: 33369 +Epoch: [35] [ 420/1319] eta: 0:50:28 lr: 7.2511294564958895e-06 loss: 0.0311 (0.0318) time: 3.3894 data: 0.0106 max mem: 33369 +Epoch: [35] [ 430/1319] eta: 0:49:55 lr: 7.240558440407508e-06 loss: 0.0301 (0.0318) time: 3.3843 data: 0.0111 max mem: 33369 +Epoch: [35] [ 440/1319] eta: 0:49:20 lr: 7.229985709218795e-06 loss: 0.0298 (0.0319) time: 3.3427 data: 0.0117 max mem: 33369 +Epoch: [35] [ 450/1319] eta: 0:48:46 lr: 7.219411259863819e-06 loss: 0.0323 (0.0319) time: 3.3293 data: 0.0121 max mem: 33369 +Epoch: [35] [ 460/1319] eta: 0:48:11 lr: 7.208835089266191e-06 loss: 0.0345 (0.0320) time: 3.3187 data: 0.0122 max mem: 33369 +Epoch: [35] [ 470/1319] eta: 0:47:37 lr: 7.198257194338982e-06 loss: 0.0345 (0.0323) time: 3.3346 data: 0.0130 max mem: 33369 +Epoch: [35] [ 480/1319] eta: 0:47:05 lr: 7.187677571984675e-06 loss: 0.0316 (0.0323) time: 3.4019 data: 0.0125 max mem: 33369 +Epoch: [35] [ 490/1319] eta: 0:46:31 lr: 7.177096219095117e-06 loss: 0.0291 (0.0323) time: 3.4021 data: 0.0101 max mem: 33369 +Epoch: [35] [ 500/1319] eta: 0:45:56 lr: 7.166513132551446e-06 loss: 0.0291 (0.0323) time: 3.3386 data: 0.0094 max mem: 33369 +Epoch: [35] [ 510/1319] eta: 0:45:22 lr: 7.15592830922407e-06 loss: 0.0310 (0.0323) time: 3.3128 data: 0.0100 max mem: 33369 +Epoch: [35] [ 520/1319] eta: 0:44:48 lr: 7.145341745972588e-06 loss: 0.0304 (0.0328) time: 3.3445 data: 0.0104 max mem: 33369 +Epoch: [35] [ 530/1319] eta: 0:44:14 lr: 7.134753439645737e-06 loss: 0.0298 (0.0328) time: 3.3388 data: 0.0111 max mem: 33369 +Epoch: [35] [ 540/1319] eta: 0:43:41 lr: 7.124163387081344e-06 loss: 0.0294 (0.0328) time: 3.3743 data: 0.0107 max mem: 33369 +Epoch: [35] [ 550/1319] eta: 0:43:08 lr: 7.1135715851062684e-06 loss: 0.0293 (0.0330) time: 3.4038 data: 0.0109 max mem: 33369 +Epoch: [35] [ 560/1319] eta: 0:42:34 lr: 7.102978030536328e-06 loss: 0.0358 (0.0330) time: 3.3735 data: 0.0117 max mem: 33369 +Epoch: [35] [ 570/1319] eta: 0:42:00 lr: 7.092382720176277e-06 loss: 0.0309 (0.0329) time: 3.3553 data: 0.0107 max mem: 33369 +Epoch: [35] [ 580/1319] eta: 0:41:26 lr: 7.081785650819721e-06 loss: 0.0302 (0.0329) time: 3.3306 data: 0.0100 max mem: 33369 +Epoch: [35] [ 590/1319] eta: 0:40:55 lr: 7.071186819249069e-06 loss: 0.0279 (0.0329) time: 3.4553 data: 0.0100 max mem: 33369 +Epoch: [35] [ 600/1319] eta: 0:40:23 lr: 7.060586222235484e-06 loss: 0.0294 (0.0329) time: 3.5271 data: 0.0096 max mem: 33369 +Epoch: [35] [ 610/1319] eta: 0:39:48 lr: 7.049983856538794e-06 loss: 0.0294 (0.0328) time: 3.3886 data: 0.0099 max mem: 33369 +Epoch: [35] [ 620/1319] eta: 0:39:14 lr: 7.039379718907476e-06 loss: 0.0267 (0.0328) time: 3.3264 data: 0.0101 max mem: 33369 +Epoch: [35] [ 630/1319] eta: 0:38:40 lr: 7.0287738060785644e-06 loss: 0.0294 (0.0328) time: 3.3454 data: 0.0109 max mem: 33369 +Epoch: [35] [ 640/1319] eta: 0:38:06 lr: 7.018166114777613e-06 loss: 0.0304 (0.0328) time: 3.3331 data: 0.0117 max mem: 33369 +Epoch: [35] [ 650/1319] eta: 0:37:32 lr: 7.007556641718624e-06 loss: 0.0304 (0.0328) time: 3.3221 data: 0.0111 max mem: 33369 +Epoch: [35] [ 660/1319] eta: 0:36:58 lr: 6.9969453836039725e-06 loss: 0.0319 (0.0327) time: 3.3469 data: 0.0103 max mem: 33369 +Epoch: [35] [ 670/1319] eta: 0:36:25 lr: 6.986332337124384e-06 loss: 0.0316 (0.0327) time: 3.3799 data: 0.0102 max mem: 33369 +Epoch: [35] [ 680/1319] eta: 0:35:51 lr: 6.975717498958839e-06 loss: 0.0299 (0.0327) time: 3.3595 data: 0.0110 max mem: 33369 +Epoch: [35] [ 690/1319] eta: 0:35:17 lr: 6.965100865774533e-06 loss: 0.0302 (0.0326) time: 3.3305 data: 0.0111 max mem: 33369 +Epoch: [35] [ 700/1319] eta: 0:34:43 lr: 6.954482434226801e-06 loss: 0.0302 (0.0326) time: 3.3503 data: 0.0106 max mem: 33369 +Epoch: [35] [ 710/1319] eta: 0:34:09 lr: 6.9438622009590656e-06 loss: 0.0324 (0.0327) time: 3.3508 data: 0.0105 max mem: 33369 +Epoch: [35] [ 720/1319] eta: 0:33:36 lr: 6.933240162602753e-06 loss: 0.0330 (0.0327) time: 3.3548 data: 0.0103 max mem: 33369 +Epoch: [35] [ 730/1319] eta: 0:33:02 lr: 6.922616315777261e-06 loss: 0.0290 (0.0327) time: 3.3633 data: 0.0093 max mem: 33369 +Epoch: [35] [ 740/1319] eta: 0:32:28 lr: 6.911990657089877e-06 loss: 0.0290 (0.0327) time: 3.3432 data: 0.0092 max mem: 33369 +Epoch: [35] [ 750/1319] eta: 0:31:54 lr: 6.901363183135715e-06 loss: 0.0291 (0.0327) time: 3.3416 data: 0.0098 max mem: 33369 +Epoch: [35] [ 760/1319] eta: 0:31:21 lr: 6.890733890497658e-06 loss: 0.0307 (0.0327) time: 3.3573 data: 0.0100 max mem: 33369 +Epoch: [35] [ 770/1319] eta: 0:30:47 lr: 6.880102775746271e-06 loss: 0.0331 (0.0327) time: 3.3936 data: 0.0101 max mem: 33369 +Epoch: [35] [ 780/1319] eta: 0:30:14 lr: 6.869469835439768e-06 loss: 0.0315 (0.0327) time: 3.3964 data: 0.0100 max mem: 33369 +Epoch: [35] [ 790/1319] eta: 0:29:40 lr: 6.858835066123928e-06 loss: 0.0294 (0.0326) time: 3.3824 data: 0.0107 max mem: 33369 +Epoch: [35] [ 800/1319] eta: 0:29:07 lr: 6.848198464332027e-06 loss: 0.0290 (0.0327) time: 3.4027 data: 0.0118 max mem: 33369 +Epoch: [35] [ 810/1319] eta: 0:28:33 lr: 6.837560026584784e-06 loss: 0.0290 (0.0326) time: 3.3745 data: 0.0122 max mem: 33369 +Epoch: [35] [ 820/1319] eta: 0:27:59 lr: 6.826919749390266e-06 loss: 0.0292 (0.0326) time: 3.3346 data: 0.0116 max mem: 33369 +Epoch: [35] [ 830/1319] eta: 0:27:25 lr: 6.816277629243854e-06 loss: 0.0324 (0.0326) time: 3.3400 data: 0.0105 max mem: 33369 +Epoch: [35] [ 840/1319] eta: 0:26:52 lr: 6.805633662628158e-06 loss: 0.0304 (0.0326) time: 3.3409 data: 0.0107 max mem: 33369 +Epoch: [35] [ 850/1319] eta: 0:26:18 lr: 6.794987846012945e-06 loss: 0.0294 (0.0326) time: 3.3853 data: 0.0106 max mem: 33369 +Epoch: [35] [ 860/1319] eta: 0:25:45 lr: 6.784340175855078e-06 loss: 0.0283 (0.0325) time: 3.4053 data: 0.0111 max mem: 33369 +Epoch: [35] [ 870/1319] eta: 0:25:11 lr: 6.7736906485984466e-06 loss: 0.0256 (0.0325) time: 3.3717 data: 0.0107 max mem: 33369 +Epoch: [35] [ 880/1319] eta: 0:24:38 lr: 6.763039260673876e-06 loss: 0.0276 (0.0325) time: 3.3877 data: 0.0092 max mem: 33369 +Epoch: [35] [ 890/1319] eta: 0:24:04 lr: 6.752386008499089e-06 loss: 0.0281 (0.0324) time: 3.3801 data: 0.0095 max mem: 33369 +Epoch: [35] [ 900/1319] eta: 0:23:30 lr: 6.741730888478615e-06 loss: 0.0283 (0.0324) time: 3.3438 data: 0.0096 max mem: 33369 +Epoch: [35] [ 910/1319] eta: 0:22:56 lr: 6.7310738970037205e-06 loss: 0.0285 (0.0325) time: 3.3165 data: 0.0093 max mem: 33369 +Epoch: [35] [ 920/1319] eta: 0:22:22 lr: 6.7204150304523424e-06 loss: 0.0263 (0.0324) time: 3.3089 data: 0.0093 max mem: 33369 +Epoch: [35] [ 930/1319] eta: 0:21:48 lr: 6.709754285188997e-06 loss: 0.0299 (0.0324) time: 3.3233 data: 0.0089 max mem: 33369 +Epoch: [35] [ 940/1319] eta: 0:21:15 lr: 6.699091657564736e-06 loss: 0.0343 (0.0324) time: 3.3275 data: 0.0096 max mem: 33369 +Epoch: [35] [ 950/1319] eta: 0:20:41 lr: 6.688427143917049e-06 loss: 0.0320 (0.0324) time: 3.3666 data: 0.0104 max mem: 33369 +Epoch: [35] [ 960/1319] eta: 0:20:07 lr: 6.677760740569799e-06 loss: 0.0262 (0.0324) time: 3.3755 data: 0.0098 max mem: 33369 +Epoch: [35] [ 970/1319] eta: 0:19:34 lr: 6.667092443833153e-06 loss: 0.0307 (0.0324) time: 3.3475 data: 0.0098 max mem: 33369 +Epoch: [35] [ 980/1319] eta: 0:19:00 lr: 6.656422250003478e-06 loss: 0.0327 (0.0324) time: 3.3461 data: 0.0099 max mem: 33369 +Epoch: [35] [ 990/1319] eta: 0:18:26 lr: 6.645750155363307e-06 loss: 0.0282 (0.0324) time: 3.3531 data: 0.0110 max mem: 33369 +Epoch: [35] [1000/1319] eta: 0:17:52 lr: 6.635076156181232e-06 loss: 0.0297 (0.0325) time: 3.2821 data: 0.0109 max mem: 33369 +Epoch: [35] [1010/1319] eta: 0:17:18 lr: 6.624400248711836e-06 loss: 0.0317 (0.0325) time: 3.2742 data: 0.0112 max mem: 33369 +Epoch: [35] [1020/1319] eta: 0:16:45 lr: 6.613722429195618e-06 loss: 0.0301 (0.0325) time: 3.3305 data: 0.0120 max mem: 33369 +Epoch: [35] [1030/1319] eta: 0:16:11 lr: 6.603042693858916e-06 loss: 0.0327 (0.0325) time: 3.3200 data: 0.0104 max mem: 33369 +Epoch: [35] [1040/1319] eta: 0:15:37 lr: 6.5923610389138055e-06 loss: 0.0327 (0.0325) time: 3.3260 data: 0.0100 max mem: 33369 +Epoch: [35] [1050/1319] eta: 0:15:04 lr: 6.581677460558057e-06 loss: 0.0269 (0.0324) time: 3.3381 data: 0.0110 max mem: 33369 +Epoch: [35] [1060/1319] eta: 0:14:30 lr: 6.570991954975031e-06 loss: 0.0277 (0.0324) time: 3.3603 data: 0.0102 max mem: 33369 +Epoch: [35] [1070/1319] eta: 0:13:56 lr: 6.560304518333606e-06 loss: 0.0289 (0.0324) time: 3.3770 data: 0.0102 max mem: 33369 +Epoch: [35] [1080/1319] eta: 0:13:23 lr: 6.549615146788095e-06 loss: 0.0316 (0.0324) time: 3.4193 data: 0.0107 max mem: 33369 +Epoch: [35] [1090/1319] eta: 0:12:49 lr: 6.538923836478152e-06 loss: 0.0293 (0.0324) time: 3.3730 data: 0.0094 max mem: 33369 +Epoch: [35] [1100/1319] eta: 0:12:16 lr: 6.528230583528713e-06 loss: 0.0270 (0.0323) time: 3.3362 data: 0.0097 max mem: 33369 +Epoch: [35] [1110/1319] eta: 0:11:42 lr: 6.5175353840499016e-06 loss: 0.0282 (0.0323) time: 3.3466 data: 0.0102 max mem: 33369 +Epoch: [35] [1120/1319] eta: 0:11:08 lr: 6.506838234136938e-06 loss: 0.0297 (0.0323) time: 3.3195 data: 0.0108 max mem: 33369 +Epoch: [35] [1130/1319] eta: 0:10:35 lr: 6.4961391298700616e-06 loss: 0.0297 (0.0323) time: 3.3536 data: 0.0118 max mem: 33369 +Epoch: [35] [1140/1319] eta: 0:10:01 lr: 6.485438067314456e-06 loss: 0.0303 (0.0324) time: 3.3525 data: 0.0109 max mem: 33369 +Epoch: [35] [1150/1319] eta: 0:09:28 lr: 6.4747350425201315e-06 loss: 0.0294 (0.0323) time: 3.3643 data: 0.0099 max mem: 33369 +Epoch: [35] [1160/1319] eta: 0:08:54 lr: 6.464030051521878e-06 loss: 0.0295 (0.0323) time: 3.3689 data: 0.0092 max mem: 33369 +Epoch: [35] [1170/1319] eta: 0:08:20 lr: 6.453323090339156e-06 loss: 0.0266 (0.0323) time: 3.3287 data: 0.0087 max mem: 33369 +Epoch: [35] [1180/1319] eta: 0:07:47 lr: 6.442614154976011e-06 loss: 0.0259 (0.0322) time: 3.3221 data: 0.0096 max mem: 33369 +Epoch: [35] [1190/1319] eta: 0:07:13 lr: 6.431903241420996e-06 loss: 0.0282 (0.0322) time: 3.3256 data: 0.0097 max mem: 33369 +Epoch: [35] [1200/1319] eta: 0:06:39 lr: 6.4211903456470515e-06 loss: 0.0278 (0.0322) time: 3.3676 data: 0.0088 max mem: 33369 +Epoch: [35] [1210/1319] eta: 0:06:06 lr: 6.410475463611462e-06 loss: 0.0269 (0.0322) time: 3.3754 data: 0.0102 max mem: 33369 +Epoch: [35] [1220/1319] eta: 0:05:32 lr: 6.399758591255733e-06 loss: 0.0269 (0.0322) time: 3.3358 data: 0.0112 max mem: 33369 +Epoch: [35] [1230/1319] eta: 0:04:59 lr: 6.389039724505507e-06 loss: 0.0360 (0.0322) time: 3.3149 data: 0.0099 max mem: 33369 +Epoch: [35] [1240/1319] eta: 0:04:25 lr: 6.378318859270487e-06 loss: 0.0314 (0.0322) time: 3.3397 data: 0.0099 max mem: 33369 +Epoch: [35] [1250/1319] eta: 0:03:51 lr: 6.3675959914443046e-06 loss: 0.0307 (0.0322) time: 3.3909 data: 0.0101 max mem: 33369 +Epoch: [35] [1260/1319] eta: 0:03:18 lr: 6.356871116904475e-06 loss: 0.0316 (0.0322) time: 3.3947 data: 0.0108 max mem: 33369 +Epoch: [35] [1270/1319] eta: 0:02:44 lr: 6.34614423151228e-06 loss: 0.0339 (0.0323) time: 3.3675 data: 0.0113 max mem: 33369 +Epoch: [35] [1280/1319] eta: 0:02:11 lr: 6.335415331112665e-06 loss: 0.0314 (0.0322) time: 3.3591 data: 0.0112 max mem: 33369 +Epoch: [35] [1290/1319] eta: 0:01:37 lr: 6.324684411534165e-06 loss: 0.0314 (0.0323) time: 3.3850 data: 0.0111 max mem: 33369 +Epoch: [35] [1300/1319] eta: 0:01:03 lr: 6.313951468588795e-06 loss: 0.0354 (0.0323) time: 3.3535 data: 0.0110 max mem: 33369 +Epoch: [35] [1310/1319] eta: 0:00:30 lr: 6.3032164980719415e-06 loss: 0.0289 (0.0322) time: 3.3162 data: 0.0098 max mem: 33369 +Epoch: [35] Total time: 1:13:52 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 2:36:57 time: 3.6603 data: 3.3571 max mem: 33369 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 100/2573] eta: 0:05:02 time: 0.0787 data: 0.0016 max mem: 33369 +Test: [ 200/2573] eta: 0:04:04 time: 0.0855 data: 0.0021 max mem: 33369 +Test: [ 300/2573] eta: 0:03:37 time: 0.0825 data: 0.0015 max mem: 33369 +Test: [ 400/2573] eta: 0:03:19 time: 0.0830 data: 0.0015 max mem: 33369 +Test: [ 500/2573] eta: 0:03:06 time: 0.0811 data: 0.0017 max mem: 33369 +Test: [ 600/2573] eta: 0:02:54 time: 0.0801 data: 0.0015 max mem: 33369 +Test: [ 700/2573] eta: 0:02:45 time: 0.0862 data: 0.0021 max mem: 33369 +Test: [ 800/2573] eta: 0:02:35 time: 0.0861 data: 0.0016 max mem: 33369 +Test: [ 900/2573] eta: 0:02:25 time: 0.0821 data: 0.0017 max mem: 33369 +Test: [1000/2573] eta: 0:02:16 time: 0.0821 data: 0.0017 max mem: 33369 +Test: [1100/2573] eta: 0:02:07 time: 0.0840 data: 0.0020 max mem: 33369 +Test: [1200/2573] eta: 0:01:58 time: 0.0837 data: 0.0018 max mem: 33369 +Test: [1300/2573] eta: 0:01:49 time: 0.0819 data: 0.0016 max mem: 33369 +Test: [1400/2573] eta: 0:01:40 time: 0.0797 data: 0.0016 max mem: 33369 +Test: [1500/2573] eta: 0:01:31 time: 0.0834 data: 0.0018 max mem: 33369 +Test: [1600/2573] eta: 0:01:23 time: 0.0873 data: 0.0021 max mem: 33369 +Test: [1700/2573] eta: 0:01:14 time: 0.0839 data: 0.0018 max mem: 33369 +Test: [1800/2573] eta: 0:01:05 time: 0.0834 data: 0.0016 max mem: 33369 +Test: [1900/2573] eta: 0:00:57 time: 0.0810 data: 0.0017 max mem: 33369 +Test: [2000/2573] eta: 0:00:48 time: 0.0807 data: 0.0016 max mem: 33369 +Test: [2100/2573] eta: 0:00:40 time: 0.0838 data: 0.0016 max mem: 33369 +Test: [2200/2573] eta: 0:00:31 time: 0.0874 data: 0.0019 max mem: 33369 +Test: [2300/2573] eta: 0:00:23 time: 0.0838 data: 0.0018 max mem: 33369 +Test: [2400/2573] eta: 0:00:14 time: 0.0822 data: 0.0019 max mem: 33369 +Test: [2500/2573] eta: 0:00:06 time: 0.0827 data: 0.0018 max mem: 33369 +Test: Total time: 0:03:37 +Final results: +Mean IoU is 65.49 + + precision@0.5 = 73.75 + precision@0.6 = 67.99 + precision@0.7 = 60.91 + precision@0.8 = 49.47 + precision@0.9 = 24.98 + overall IoU = 63.02 + +Average object IoU 65.49251810657762 +Overall IoU 63.02033996582031 +Better epoch: 35 + +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [36] [ 0/1319] eta: 2:11:38 lr: 6.293553287544593e-06 loss: 0.0437 (0.0437) time: 5.9879 data: 2.0368 max mem: 33369 +Epoch: [36] [ 10/1319] eta: 1:22:22 lr: 6.282814452998321e-06 loss: 0.0384 (0.0355) time: 3.7758 data: 0.1943 max mem: 33369 +Epoch: [36] [ 20/1319] eta: 1:17:03 lr: 6.2720735785923675e-06 loss: 0.0327 (0.0330) time: 3.4382 data: 0.0090 max mem: 33369 +Epoch: [36] [ 30/1319] eta: 1:15:18 lr: 6.261330660056396e-06 loss: 0.0319 (0.0320) time: 3.3569 data: 0.0087 max mem: 33369 +Epoch: [36] [ 40/1319] eta: 1:13:51 lr: 6.250585693102968e-06 loss: 0.0332 (0.0326) time: 3.3648 data: 0.0089 max mem: 33369 +Epoch: [36] [ 50/1319] eta: 1:12:31 lr: 6.2398386734274585e-06 loss: 0.0324 (0.0326) time: 3.3114 data: 0.0091 max mem: 33369 +Epoch: [36] [ 60/1319] eta: 1:11:47 lr: 6.229089596707912e-06 loss: 0.0299 (0.0320) time: 3.3320 data: 0.0095 max mem: 33369 +Epoch: [36] [ 70/1319] eta: 1:10:49 lr: 6.218338458604991e-06 loss: 0.0261 (0.0317) time: 3.3344 data: 0.0107 max mem: 33369 +Epoch: [36] [ 80/1319] eta: 1:10:06 lr: 6.207585254761843e-06 loss: 0.0307 (0.0316) time: 3.3155 data: 0.0115 max mem: 33369 +Epoch: [36] [ 90/1319] eta: 1:09:26 lr: 6.196829980804001e-06 loss: 0.0301 (0.0313) time: 3.3441 data: 0.0107 max mem: 33369 +Epoch: [36] [ 100/1319] eta: 1:08:51 lr: 6.1860726323392754e-06 loss: 0.0286 (0.0313) time: 3.3658 data: 0.0102 max mem: 33369 +Epoch: [36] [ 110/1319] eta: 1:08:11 lr: 6.175313204957665e-06 loss: 0.0311 (0.0313) time: 3.3570 data: 0.0099 max mem: 33369 +Epoch: [36] [ 120/1319] eta: 1:07:44 lr: 6.164551694231212e-06 loss: 0.0316 (0.0312) time: 3.3957 data: 0.0101 max mem: 33369 +Epoch: [36] [ 130/1319] eta: 1:07:10 lr: 6.153788095713938e-06 loss: 0.0316 (0.0313) time: 3.4240 data: 0.0104 max mem: 33369 +Epoch: [36] [ 140/1319] eta: 1:06:29 lr: 6.143022404941713e-06 loss: 0.0277 (0.0312) time: 3.3439 data: 0.0108 max mem: 33369 +Epoch: [36] [ 150/1319] eta: 1:05:49 lr: 6.132254617432146e-06 loss: 0.0264 (0.0311) time: 3.3029 data: 0.0117 max mem: 33369 +Epoch: [36] [ 160/1319] eta: 1:05:13 lr: 6.121484728684484e-06 loss: 0.0294 (0.0310) time: 3.3280 data: 0.0110 max mem: 33369 +Epoch: [36] [ 170/1319] eta: 1:04:37 lr: 6.110712734179475e-06 loss: 0.0255 (0.0308) time: 3.3440 data: 0.0100 max mem: 33369 +Epoch: [36] [ 180/1319] eta: 1:03:59 lr: 6.099938629379293e-06 loss: 0.0246 (0.0307) time: 3.3234 data: 0.0108 max mem: 33369 +Epoch: [36] [ 190/1319] eta: 1:03:21 lr: 6.0891624097274035e-06 loss: 0.0278 (0.0308) time: 3.3037 data: 0.0106 max mem: 33369 +Epoch: [36] [ 200/1319] eta: 1:02:49 lr: 6.07838407064845e-06 loss: 0.0304 (0.0308) time: 3.3523 data: 0.0098 max mem: 33369 +Epoch: [36] [ 210/1319] eta: 1:02:17 lr: 6.067603607548146e-06 loss: 0.0287 (0.0307) time: 3.3992 data: 0.0098 max mem: 33369 +Epoch: [36] [ 220/1319] eta: 1:01:38 lr: 6.05682101581314e-06 loss: 0.0291 (0.0307) time: 3.3257 data: 0.0101 max mem: 33369 +Epoch: [36] [ 230/1319] eta: 1:01:00 lr: 6.0460362908109285e-06 loss: 0.0303 (0.0308) time: 3.2719 data: 0.0104 max mem: 33369 +Epoch: [36] [ 240/1319] eta: 1:00:27 lr: 6.035249427889721e-06 loss: 0.0293 (0.0307) time: 3.3264 data: 0.0105 max mem: 33369 +Epoch: [36] [ 250/1319] eta: 0:59:55 lr: 6.024460422378318e-06 loss: 0.0281 (0.0306) time: 3.3823 data: 0.0099 max mem: 33369 +Epoch: [36] [ 260/1319] eta: 0:59:20 lr: 6.013669269586002e-06 loss: 0.0275 (0.0307) time: 3.3609 data: 0.0097 max mem: 33369 +Epoch: [36] [ 270/1319] eta: 0:58:46 lr: 6.002875964802412e-06 loss: 0.0294 (0.0307) time: 3.3416 data: 0.0102 max mem: 33369 +Epoch: [36] [ 280/1319] eta: 0:58:12 lr: 5.992080503297408e-06 loss: 0.0323 (0.0308) time: 3.3529 data: 0.0103 max mem: 33369 +Epoch: [36] [ 290/1319] eta: 0:57:35 lr: 5.981282880320978e-06 loss: 0.0291 (0.0308) time: 3.3116 data: 0.0101 max mem: 33369 +Epoch: [36] [ 300/1319] eta: 0:57:00 lr: 5.97048309110309e-06 loss: 0.0291 (0.0308) time: 3.2996 data: 0.0098 max mem: 33369 +Epoch: [36] [ 310/1319] eta: 0:56:25 lr: 5.959681130853577e-06 loss: 0.0255 (0.0307) time: 3.3207 data: 0.0096 max mem: 33369 +Epoch: [36] [ 320/1319] eta: 0:55:52 lr: 5.948876994762015e-06 loss: 0.0250 (0.0307) time: 3.3431 data: 0.0093 max mem: 33369 +Epoch: [36] [ 330/1319] eta: 0:55:20 lr: 5.938070677997572e-06 loss: 0.0261 (0.0307) time: 3.3816 data: 0.0099 max mem: 33369 +Epoch: [36] [ 340/1319] eta: 0:54:46 lr: 5.927262175708919e-06 loss: 0.0294 (0.0310) time: 3.3720 data: 0.0109 max mem: 33369 +Epoch: [36] [ 350/1319] eta: 0:54:11 lr: 5.916451483024071e-06 loss: 0.0312 (0.0310) time: 3.3209 data: 0.0116 max mem: 33369 +Epoch: [36] [ 360/1319] eta: 0:53:39 lr: 5.905638595050271e-06 loss: 0.0312 (0.0310) time: 3.3517 data: 0.0110 max mem: 33369 +Epoch: [36] [ 370/1319] eta: 0:53:06 lr: 5.894823506873858e-06 loss: 0.0301 (0.0311) time: 3.3973 data: 0.0099 max mem: 33369 +Epoch: [36] [ 380/1319] eta: 0:52:32 lr: 5.884006213560114e-06 loss: 0.0349 (0.0313) time: 3.3622 data: 0.0100 max mem: 33369 +Epoch: [36] [ 390/1319] eta: 0:51:57 lr: 5.873186710153169e-06 loss: 0.0324 (0.0313) time: 3.3146 data: 0.0106 max mem: 33369 +Epoch: [36] [ 400/1319] eta: 0:51:23 lr: 5.862364991675836e-06 loss: 0.0286 (0.0312) time: 3.3137 data: 0.0102 max mem: 33369 +Epoch: [36] [ 410/1319] eta: 0:50:50 lr: 5.85154105312949e-06 loss: 0.0260 (0.0311) time: 3.3694 data: 0.0104 max mem: 33369 +Epoch: [36] [ 420/1319] eta: 0:50:17 lr: 5.840714889493923e-06 loss: 0.0260 (0.0311) time: 3.3824 data: 0.0096 max mem: 33369 +Epoch: [36] [ 430/1319] eta: 0:49:42 lr: 5.829886495727219e-06 loss: 0.0273 (0.0312) time: 3.3396 data: 0.0089 max mem: 33369 +Epoch: [36] [ 440/1319] eta: 0:49:09 lr: 5.819055866765587e-06 loss: 0.0276 (0.0311) time: 3.3511 data: 0.0100 max mem: 33369 +Epoch: [36] [ 450/1319] eta: 0:48:37 lr: 5.808222997523256e-06 loss: 0.0276 (0.0311) time: 3.3916 data: 0.0094 max mem: 33369 +Epoch: [36] [ 460/1319] eta: 0:48:02 lr: 5.797387882892317e-06 loss: 0.0262 (0.0310) time: 3.3512 data: 0.0088 max mem: 33369 +Epoch: [36] [ 470/1319] eta: 0:47:29 lr: 5.786550517742576e-06 loss: 0.0262 (0.0310) time: 3.3330 data: 0.0093 max mem: 33369 +Epoch: [36] [ 480/1319] eta: 0:46:54 lr: 5.775710896921423e-06 loss: 0.0274 (0.0309) time: 3.3365 data: 0.0098 max mem: 33369 +Epoch: [36] [ 490/1319] eta: 0:46:21 lr: 5.764869015253661e-06 loss: 0.0278 (0.0309) time: 3.3535 data: 0.0104 max mem: 33369 +Epoch: [36] [ 500/1319] eta: 0:45:50 lr: 5.7540248675414e-06 loss: 0.0292 (0.0309) time: 3.4409 data: 0.0106 max mem: 33369 +Epoch: [36] [ 510/1319] eta: 0:45:15 lr: 5.743178448563874e-06 loss: 0.0292 (0.0309) time: 3.3819 data: 0.0109 max mem: 33369 +Epoch: [36] [ 520/1319] eta: 0:44:43 lr: 5.732329753077314e-06 loss: 0.0273 (0.0309) time: 3.3621 data: 0.0110 max mem: 33369 +Epoch: [36] [ 530/1319] eta: 0:44:10 lr: 5.7214787758147914e-06 loss: 0.0277 (0.0309) time: 3.4301 data: 0.0103 max mem: 33369 +Epoch: [36] [ 540/1319] eta: 0:43:37 lr: 5.710625511486047e-06 loss: 0.0306 (0.0309) time: 3.3815 data: 0.0101 max mem: 33369 +Epoch: [36] [ 550/1319] eta: 0:43:02 lr: 5.6997699547773765e-06 loss: 0.0300 (0.0310) time: 3.3280 data: 0.0102 max mem: 33369 +Epoch: [36] [ 560/1319] eta: 0:42:28 lr: 5.68891210035145e-06 loss: 0.0283 (0.0309) time: 3.3203 data: 0.0099 max mem: 33369 +Epoch: [36] [ 570/1319] eta: 0:41:55 lr: 5.678051942847162e-06 loss: 0.0278 (0.0309) time: 3.3516 data: 0.0106 max mem: 33369 +Epoch: [36] [ 580/1319] eta: 0:41:21 lr: 5.667189476879478e-06 loss: 0.0304 (0.0310) time: 3.3429 data: 0.0105 max mem: 33369 +Epoch: [36] [ 590/1319] eta: 0:40:47 lr: 5.656324697039277e-06 loss: 0.0304 (0.0310) time: 3.3215 data: 0.0100 max mem: 33369 +Epoch: [36] [ 600/1319] eta: 0:40:13 lr: 5.645457597893177e-06 loss: 0.0274 (0.0310) time: 3.3365 data: 0.0105 max mem: 33369 +Epoch: [36] [ 610/1319] eta: 0:39:39 lr: 5.634588173983401e-06 loss: 0.0273 (0.0310) time: 3.3393 data: 0.0102 max mem: 33369 +Epoch: [36] [ 620/1319] eta: 0:39:06 lr: 5.623716419827592e-06 loss: 0.0273 (0.0309) time: 3.3697 data: 0.0097 max mem: 33369 +Epoch: [36] [ 630/1319] eta: 0:38:33 lr: 5.612842329918665e-06 loss: 0.0261 (0.0308) time: 3.3911 data: 0.0100 max mem: 33369 +Epoch: [36] [ 640/1319] eta: 0:37:59 lr: 5.6019658987246355e-06 loss: 0.0270 (0.0308) time: 3.3689 data: 0.0100 max mem: 33369 +Epoch: [36] [ 650/1319] eta: 0:37:25 lr: 5.591087120688435e-06 loss: 0.0302 (0.0308) time: 3.3370 data: 0.0103 max mem: 33369 +Epoch: [36] [ 660/1319] eta: 0:36:51 lr: 5.5802059902277785e-06 loss: 0.0315 (0.0309) time: 3.3227 data: 0.0108 max mem: 33369 +Epoch: [36] [ 670/1319] eta: 0:36:18 lr: 5.569322501734972e-06 loss: 0.0305 (0.0309) time: 3.3492 data: 0.0105 max mem: 33369 +Epoch: [36] [ 680/1319] eta: 0:35:44 lr: 5.5584366495767425e-06 loss: 0.0289 (0.0309) time: 3.3642 data: 0.0106 max mem: 33369 +Epoch: [36] [ 690/1319] eta: 0:35:10 lr: 5.547548428094075e-06 loss: 0.0285 (0.0308) time: 3.3291 data: 0.0116 max mem: 33369 +Epoch: [36] [ 700/1319] eta: 0:34:36 lr: 5.536657831602032e-06 loss: 0.0293 (0.0309) time: 3.3060 data: 0.0121 max mem: 33369 +Epoch: [36] [ 710/1319] eta: 0:34:04 lr: 5.525764854389564e-06 loss: 0.0279 (0.0309) time: 3.3987 data: 0.0120 max mem: 33369 +Epoch: [36] [ 720/1319] eta: 0:33:30 lr: 5.514869490719365e-06 loss: 0.0275 (0.0308) time: 3.3987 data: 0.0109 max mem: 33369 +Epoch: [36] [ 730/1319] eta: 0:32:56 lr: 5.503971734827667e-06 loss: 0.0275 (0.0308) time: 3.3372 data: 0.0104 max mem: 33369 +Epoch: [36] [ 740/1319] eta: 0:32:23 lr: 5.493071580924068e-06 loss: 0.0261 (0.0308) time: 3.3752 data: 0.0098 max mem: 33369 +Epoch: [36] [ 750/1319] eta: 0:31:49 lr: 5.482169023191358e-06 loss: 0.0267 (0.0308) time: 3.3526 data: 0.0097 max mem: 33369 +Epoch: [36] [ 760/1319] eta: 0:31:17 lr: 5.471264055785306e-06 loss: 0.0284 (0.0308) time: 3.3857 data: 0.0105 max mem: 33369 +Epoch: [36] [ 770/1319] eta: 0:30:43 lr: 5.4603566728345144e-06 loss: 0.0289 (0.0309) time: 3.4423 data: 0.0093 max mem: 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0.0096 max mem: 33369 +Epoch: [36] [ 860/1319] eta: 0:25:40 lr: 5.362080544282056e-06 loss: 0.0313 (0.0310) time: 3.3352 data: 0.0099 max mem: 33369 +Epoch: [36] [ 870/1319] eta: 0:25:07 lr: 5.351148676839889e-06 loss: 0.0268 (0.0310) time: 3.3575 data: 0.0117 max mem: 33369 +Epoch: [36] [ 880/1319] eta: 0:24:34 lr: 5.340214327418554e-06 loss: 0.0269 (0.0309) time: 3.4198 data: 0.0112 max mem: 33369 +Epoch: [36] [ 890/1319] eta: 0:24:00 lr: 5.3292774898053224e-06 loss: 0.0269 (0.0309) time: 3.4345 data: 0.0109 max mem: 33369 +Epoch: [36] [ 900/1319] eta: 0:23:26 lr: 5.3183381577577165e-06 loss: 0.0280 (0.0310) time: 3.3588 data: 0.0114 max mem: 33369 +Epoch: [36] [ 910/1319] eta: 0:22:53 lr: 5.307396325003292e-06 loss: 0.0292 (0.0309) time: 3.3458 data: 0.0112 max mem: 33369 +Epoch: [36] [ 920/1319] eta: 0:22:20 lr: 5.296451985239408e-06 loss: 0.0256 (0.0309) time: 3.3798 data: 0.0104 max mem: 33369 +Epoch: [36] [ 930/1319] eta: 0:21:46 lr: 5.285505132133047e-06 loss: 0.0276 (0.0309) time: 3.3631 data: 0.0102 max mem: 33369 +Epoch: [36] [ 940/1319] eta: 0:21:13 lr: 5.274555759320574e-06 loss: 0.0268 (0.0309) time: 3.3847 data: 0.0099 max mem: 33369 +Epoch: [36] [ 950/1319] eta: 0:20:39 lr: 5.263603860407521e-06 loss: 0.0275 (0.0309) time: 3.4067 data: 0.0094 max mem: 33369 +Epoch: [36] [ 960/1319] eta: 0:20:05 lr: 5.252649428968377e-06 loss: 0.0329 (0.0309) time: 3.3737 data: 0.0103 max mem: 33369 +Epoch: [36] [ 970/1319] eta: 0:19:32 lr: 5.241692458546333e-06 loss: 0.0314 (0.0309) time: 3.3913 data: 0.0113 max mem: 33369 +Epoch: [36] [ 980/1319] eta: 0:18:59 lr: 5.230732942653104e-06 loss: 0.0299 (0.0309) time: 3.3877 data: 0.0101 max mem: 33369 +Epoch: [36] [ 990/1319] eta: 0:18:25 lr: 5.2197708747686676e-06 loss: 0.0302 (0.0310) time: 3.3406 data: 0.0101 max mem: 33369 +Epoch: [36] [1000/1319] eta: 0:17:51 lr: 5.208806248341044e-06 loss: 0.0274 (0.0310) time: 3.3338 data: 0.0106 max mem: 33369 +Epoch: [36] [1010/1319] eta: 0:17:17 lr: 5.197839056786066e-06 loss: 0.0262 (0.0310) time: 3.3324 data: 0.0103 max mem: 33369 +Epoch: [36] [1020/1319] eta: 0:16:44 lr: 5.186869293487148e-06 loss: 0.0295 (0.0310) time: 3.3287 data: 0.0103 max mem: 33369 +Epoch: [36] [1030/1319] eta: 0:16:10 lr: 5.175896951795028e-06 loss: 0.0304 (0.0310) time: 3.3416 data: 0.0111 max mem: 33369 +Epoch: [36] [1040/1319] eta: 0:15:36 lr: 5.164922025027563e-06 loss: 0.0301 (0.0310) time: 3.3393 data: 0.0123 max mem: 33369 +Epoch: [36] [1050/1319] eta: 0:15:03 lr: 5.153944506469468e-06 loss: 0.0311 (0.0311) time: 3.3359 data: 0.0120 max mem: 33369 +Epoch: [36] [1060/1319] eta: 0:14:29 lr: 5.142964389372074e-06 loss: 0.0335 (0.0311) time: 3.3482 data: 0.0117 max mem: 33369 +Epoch: [36] [1070/1319] eta: 0:13:56 lr: 5.13198166695309e-06 loss: 0.0279 (0.0311) time: 3.3256 data: 0.0117 max mem: 33369 +Epoch: [36] [1080/1319] eta: 0:13:22 lr: 5.120996332396334e-06 loss: 0.0263 (0.0311) time: 3.3255 data: 0.0123 max mem: 33369 +Epoch: [36] [1090/1319] eta: 0:12:48 lr: 5.1100083788515145e-06 loss: 0.0298 (0.0311) time: 3.3360 data: 0.0122 max mem: 33369 +Epoch: [36] [1100/1319] eta: 0:12:15 lr: 5.0990177994339575e-06 loss: 0.0294 (0.0311) time: 3.3184 data: 0.0118 max mem: 33369 +Epoch: [36] [1110/1319] eta: 0:11:41 lr: 5.088024587224353e-06 loss: 0.0334 (0.0311) time: 3.3151 data: 0.0119 max mem: 33369 +Epoch: [36] [1120/1319] eta: 0:11:07 lr: 5.077028735268508e-06 loss: 0.0334 (0.0311) time: 3.3028 data: 0.0113 max mem: 33369 +Epoch: [36] [1130/1319] eta: 0:10:34 lr: 5.066030236577056e-06 loss: 0.0326 (0.0312) time: 3.2930 data: 0.0116 max mem: 33369 +Epoch: [36] [1140/1319] eta: 0:10:00 lr: 5.055029084125236e-06 loss: 0.0282 (0.0311) time: 3.3325 data: 0.0127 max mem: 33369 +Epoch: [36] [1150/1319] eta: 0:09:27 lr: 5.044025270852602e-06 loss: 0.0266 (0.0311) time: 3.3973 data: 0.0121 max mem: 33369 +Epoch: [36] [1160/1319] eta: 0:08:53 lr: 5.033018789662757e-06 loss: 0.0266 (0.0311) time: 3.3642 data: 0.0107 max mem: 33369 +Epoch: [36] [1170/1319] eta: 0:08:20 lr: 5.022009633423085e-06 loss: 0.0276 (0.0311) time: 3.3437 data: 0.0107 max mem: 33369 +Epoch: [36] [1180/1319] eta: 0:07:46 lr: 5.0109977949644845e-06 loss: 0.0284 (0.0311) time: 3.3651 data: 0.0103 max mem: 33369 +Epoch: [36] [1190/1319] eta: 0:07:12 lr: 4.999983267081064e-06 loss: 0.0286 (0.0311) time: 3.3534 data: 0.0097 max mem: 33369 +Epoch: [36] [1200/1319] eta: 0:06:39 lr: 4.988966042529905e-06 loss: 0.0274 (0.0311) time: 3.3604 data: 0.0111 max mem: 33369 +Epoch: [36] [1210/1319] eta: 0:06:05 lr: 4.977946114030749e-06 loss: 0.0274 (0.0311) time: 3.3585 data: 0.0115 max mem: 33369 +Epoch: [36] [1220/1319] eta: 0:05:32 lr: 4.966923474265728e-06 loss: 0.0291 (0.0311) time: 3.3447 data: 0.0102 max mem: 33369 +Epoch: [36] [1230/1319] eta: 0:04:58 lr: 4.9558981158790714e-06 loss: 0.0295 (0.0311) time: 3.3442 data: 0.0098 max mem: 33369 +Epoch: [36] [1240/1319] eta: 0:04:25 lr: 4.944870031476802e-06 loss: 0.0291 (0.0311) time: 3.3722 data: 0.0105 max mem: 33369 +Epoch: [36] [1250/1319] eta: 0:03:51 lr: 4.9338392136264714e-06 loss: 0.0285 (0.0310) time: 3.3397 data: 0.0120 max mem: 33369 +Epoch: [36] [1260/1319] eta: 0:03:17 lr: 4.922805654856843e-06 loss: 0.0313 (0.0311) time: 3.3319 data: 0.0127 max mem: 33369 +Epoch: [36] [1270/1319] eta: 0:02:44 lr: 4.9117693476576e-06 loss: 0.0308 (0.0311) time: 3.3991 data: 0.0120 max mem: 33369 +Epoch: [36] [1280/1319] eta: 0:02:10 lr: 4.9007302844790375e-06 loss: 0.0291 (0.0311) time: 3.3760 data: 0.0115 max mem: 33369 +Epoch: [36] [1290/1319] eta: 0:01:37 lr: 4.889688457731768e-06 loss: 0.0289 (0.0311) time: 3.3685 data: 0.0112 max mem: 33369 +Epoch: [36] [1300/1319] eta: 0:01:03 lr: 4.878643859786385e-06 loss: 0.0274 (0.0311) time: 3.3919 data: 0.0112 max mem: 33369 +Epoch: [36] [1310/1319] eta: 0:00:30 lr: 4.867596482973188e-06 loss: 0.0274 (0.0311) time: 3.3667 data: 0.0103 max mem: 33369 +Epoch: [36] Total time: 1:13:47 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 2:45:55 time: 3.8691 data: 3.7312 max mem: 33369 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 100/2573] eta: 0:04:51 time: 0.0785 data: 0.0016 max mem: 33369 +Test: [ 200/2573] eta: 0:03:56 time: 0.0803 data: 0.0017 max mem: 33369 +Test: [ 300/2573] eta: 0:03:32 time: 0.0864 data: 0.0021 max mem: 33369 +Test: [ 400/2573] eta: 0:03:17 time: 0.0841 data: 0.0016 max mem: 33369 +Test: [ 500/2573] eta: 0:03:04 time: 0.0805 data: 0.0016 max mem: 33369 +Test: [ 600/2573] eta: 0:02:53 time: 0.0821 data: 0.0016 max mem: 33369 +Test: [ 700/2573] eta: 0:02:43 time: 0.0815 data: 0.0018 max mem: 33369 +Test: [ 800/2573] eta: 0:02:33 time: 0.0852 data: 0.0017 max mem: 33369 +Test: [ 900/2573] eta: 0:02:24 time: 0.0826 data: 0.0016 max mem: 33369 +Test: [1000/2573] eta: 0:02:15 time: 0.0819 data: 0.0017 max mem: 33369 +Test: [1100/2573] eta: 0:02:06 time: 0.0815 data: 0.0016 max mem: 33369 +Test: [1200/2573] eta: 0:01:57 time: 0.0819 data: 0.0016 max mem: 33369 +Test: [1300/2573] eta: 0:01:48 time: 0.0859 data: 0.0019 max mem: 33369 +Test: [1400/2573] eta: 0:01:39 time: 0.0786 data: 0.0016 max mem: 33369 +Test: [1500/2573] eta: 0:01:31 time: 0.0842 data: 0.0020 max mem: 33369 +Test: [1600/2573] eta: 0:01:22 time: 0.0846 data: 0.0015 max mem: 33369 +Test: [1700/2573] eta: 0:01:13 time: 0.0798 data: 0.0016 max mem: 33369 +Test: [1800/2573] eta: 0:01:05 time: 0.0840 data: 0.0015 max mem: 33369 +Test: [1900/2573] eta: 0:00:56 time: 0.0805 data: 0.0018 max mem: 33369 +Test: [2000/2573] eta: 0:00:48 time: 0.0866 data: 0.0020 max mem: 33369 +Test: [2100/2573] eta: 0:00:39 time: 0.0837 data: 0.0016 max mem: 33369 +Test: [2200/2573] eta: 0:00:31 time: 0.0849 data: 0.0017 max mem: 33369 +Test: [2300/2573] eta: 0:00:22 time: 0.0820 data: 0.0015 max mem: 33369 +Test: [2400/2573] eta: 0:00:14 time: 0.0794 data: 0.0016 max mem: 33369 +Test: [2500/2573] eta: 0:00:06 time: 0.0806 data: 0.0017 max mem: 33369 +Test: Total time: 0:03:36 +Final results: +Mean IoU is 65.44 + + precision@0.5 = 73.75 + precision@0.6 = 68.08 + precision@0.7 = 61.03 + precision@0.8 = 49.53 + precision@0.9 = 25.12 + overall IoU = 62.76 + +Average object IoU 65.4419934499904 +Overall IoU 62.75981521606445 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [37] [ 0/1319] eta: 4:33:25 lr: 4.85765146153759e-06 loss: 0.0198 (0.0198) time: 12.4379 data: 2.9595 max mem: 33369 +Epoch: [37] [ 10/1319] eta: 1:33:41 lr: 4.846598783599751e-06 loss: 0.0242 (0.0238) time: 4.2945 data: 0.2778 max mem: 33369 +Epoch: [37] [ 20/1319] eta: 1:22:58 lr: 4.835543304321068e-06 loss: 0.0243 (0.0265) time: 3.4022 data: 0.0097 max mem: 33369 +Epoch: [37] [ 30/1319] eta: 1:18:57 lr: 4.824485015871577e-06 loss: 0.0274 (0.0277) time: 3.3342 data: 0.0104 max mem: 33369 +Epoch: [37] [ 40/1319] eta: 1:16:26 lr: 4.813423910379438e-06 loss: 0.0309 (0.0290) time: 3.3276 data: 0.0114 max mem: 33369 +Epoch: [37] [ 50/1319] eta: 1:14:53 lr: 4.802359979930566e-06 loss: 0.0312 (0.0290) time: 3.3329 data: 0.0103 max mem: 33369 +Epoch: [37] [ 60/1319] eta: 1:13:41 lr: 4.791293216568347e-06 loss: 0.0227 (0.0284) time: 3.3593 data: 0.0095 max mem: 33369 +Epoch: [37] [ 70/1319] eta: 1:12:38 lr: 4.780223612293264e-06 loss: 0.0247 (0.0289) time: 3.3575 data: 0.0097 max mem: 33369 +Epoch: [37] [ 80/1319] eta: 1:11:41 lr: 4.7691511590625665e-06 loss: 0.0324 (0.0297) time: 3.3509 data: 0.0099 max mem: 33369 +Epoch: [37] [ 90/1319] eta: 1:10:55 lr: 4.75807584878992e-06 loss: 0.0324 (0.0303) time: 3.3690 data: 0.0098 max mem: 33369 +Epoch: [37] [ 100/1319] eta: 1:10:05 lr: 4.7469976733450685e-06 loss: 0.0295 (0.0300) time: 3.3598 data: 0.0094 max mem: 33369 +Epoch: [37] [ 110/1319] eta: 1:09:19 lr: 4.735916624553454e-06 loss: 0.0274 (0.0298) time: 3.3401 data: 0.0100 max mem: 33369 +Epoch: [37] [ 120/1319] eta: 1:08:36 lr: 4.724832694195895e-06 loss: 0.0278 (0.0300) time: 3.3483 data: 0.0112 max mem: 33369 +Epoch: [37] [ 130/1319] eta: 1:07:59 lr: 4.713745874008202e-06 loss: 0.0253 (0.0297) time: 3.3762 data: 0.0118 max mem: 33369 +Epoch: [37] [ 140/1319] eta: 1:07:17 lr: 4.702656155680819e-06 loss: 0.0239 (0.0296) time: 3.3734 data: 0.0111 max mem: 33369 +Epoch: [37] [ 150/1319] eta: 1:06:45 lr: 4.691563530858464e-06 loss: 0.0283 (0.0297) time: 3.3996 data: 0.0106 max mem: 33369 +Epoch: [37] [ 160/1319] eta: 1:06:07 lr: 4.6804679911397265e-06 loss: 0.0326 (0.0300) time: 3.4164 data: 0.0109 max mem: 33369 +Epoch: [37] [ 170/1319] eta: 1:05:35 lr: 4.66936952807673e-06 loss: 0.0300 (0.0299) time: 3.4109 data: 0.0111 max mem: 33369 +Epoch: [37] [ 180/1319] eta: 1:04:51 lr: 4.65826813317473e-06 loss: 0.0251 (0.0298) time: 3.3620 data: 0.0109 max mem: 33369 +Epoch: [37] [ 190/1319] eta: 1:04:10 lr: 4.64716379789173e-06 loss: 0.0264 (0.0297) time: 3.2902 data: 0.0107 max mem: 33369 +Epoch: [37] [ 200/1319] eta: 1:03:34 lr: 4.636056513638103e-06 loss: 0.0265 (0.0298) time: 3.3359 data: 0.0114 max mem: 33369 +Epoch: [37] [ 210/1319] eta: 1:02:54 lr: 4.6249462717761695e-06 loss: 0.0328 (0.0301) time: 3.3370 data: 0.0111 max mem: 33369 +Epoch: [37] [ 220/1319] eta: 1:02:14 lr: 4.6138330636198426e-06 loss: 0.0292 (0.0300) time: 3.2926 data: 0.0103 max mem: 33369 +Epoch: [37] [ 230/1319] eta: 1:01:36 lr: 4.602716880434195e-06 loss: 0.0236 (0.0298) time: 3.2944 data: 0.0101 max mem: 33369 +Epoch: [37] [ 240/1319] eta: 1:01:00 lr: 4.591597713435064e-06 loss: 0.0290 (0.0300) time: 3.3329 data: 0.0096 max mem: 33369 +Epoch: [37] [ 250/1319] eta: 1:00:24 lr: 4.580475553788638e-06 loss: 0.0301 (0.0299) time: 3.3444 data: 0.0098 max mem: 33369 +Epoch: [37] [ 260/1319] eta: 0:59:44 lr: 4.569350392611047e-06 loss: 0.0254 (0.0299) time: 3.2901 data: 0.0097 max mem: 33369 +Epoch: [37] [ 270/1319] eta: 0:59:05 lr: 4.558222220967921e-06 loss: 0.0296 (0.0300) time: 3.2466 data: 0.0094 max mem: 33369 +Epoch: [37] [ 280/1319] eta: 0:58:28 lr: 4.547091029873999e-06 loss: 0.0301 (0.0299) time: 3.2716 data: 0.0106 max mem: 33369 +Epoch: [37] [ 290/1319] eta: 0:57:50 lr: 4.5359568102926745e-06 loss: 0.0301 (0.0299) time: 3.2812 data: 0.0109 max mem: 33369 +Epoch: [37] [ 300/1319] eta: 0:57:16 lr: 4.524819553135574e-06 loss: 0.0267 (0.0298) time: 3.3110 data: 0.0094 max mem: 33369 +Epoch: [37] [ 310/1319] eta: 0:56:40 lr: 4.5136792492621144e-06 loss: 0.0270 (0.0299) time: 3.3296 data: 0.0100 max mem: 33369 +Epoch: [37] [ 320/1319] eta: 0:56:04 lr: 4.502535889479041e-06 loss: 0.0263 (0.0298) time: 3.2987 data: 0.0106 max mem: 33369 +Epoch: [37] [ 330/1319] eta: 0:55:29 lr: 4.491389464540016e-06 loss: 0.0260 (0.0298) time: 3.3089 data: 0.0103 max mem: 33369 +Epoch: [37] [ 340/1319] eta: 0:54:53 lr: 4.480239965145135e-06 loss: 0.0304 (0.0299) time: 3.3108 data: 0.0107 max mem: 33369 +Epoch: [37] [ 350/1319] eta: 0:54:19 lr: 4.469087381940477e-06 loss: 0.0273 (0.0299) time: 3.3260 data: 0.0109 max mem: 33369 +Epoch: [37] [ 360/1319] eta: 0:53:45 lr: 4.457931705517646e-06 loss: 0.0257 (0.0298) time: 3.3433 data: 0.0109 max mem: 33369 +Epoch: [37] [ 370/1319] eta: 0:53:10 lr: 4.446772926413276e-06 loss: 0.0289 (0.0298) time: 3.3332 data: 0.0110 max mem: 33369 +Epoch: [37] [ 380/1319] eta: 0:52:35 lr: 4.435611035108594e-06 loss: 0.0299 (0.0298) time: 3.3169 data: 0.0117 max mem: 33369 +Epoch: [37] [ 390/1319] eta: 0:52:00 lr: 4.424446022028913e-06 loss: 0.0297 (0.0299) time: 3.3014 data: 0.0121 max mem: 33369 +Epoch: [37] [ 400/1319] eta: 0:51:25 lr: 4.413277877543152e-06 loss: 0.0288 (0.0298) time: 3.2961 data: 0.0118 max mem: 33369 +Epoch: [37] [ 410/1319] eta: 0:50:53 lr: 4.40210659196335e-06 loss: 0.0308 (0.0299) time: 3.3498 data: 0.0108 max mem: 33369 +Epoch: [37] [ 420/1319] eta: 0:50:18 lr: 4.390932155544163e-06 loss: 0.0325 (0.0300) time: 3.3564 data: 0.0096 max mem: 33369 +Epoch: [37] [ 430/1319] eta: 0:49:46 lr: 4.379754558482349e-06 loss: 0.0299 (0.0300) time: 3.3583 data: 0.0090 max mem: 33369 +Epoch: [37] [ 440/1319] eta: 0:49:11 lr: 4.368573790916289e-06 loss: 0.0285 (0.0301) time: 3.3660 data: 0.0089 max mem: 33369 +Epoch: [37] [ 450/1319] eta: 0:48:37 lr: 4.357389842925446e-06 loss: 0.0275 (0.0301) time: 3.3198 data: 0.0096 max mem: 33369 +Epoch: [37] [ 460/1319] eta: 0:48:03 lr: 4.346202704529857e-06 loss: 0.0270 (0.0300) time: 3.3259 data: 0.0100 max mem: 33369 +Epoch: [37] [ 470/1319] eta: 0:47:28 lr: 4.335012365689605e-06 loss: 0.0297 (0.0302) time: 3.3048 data: 0.0101 max mem: 33369 +Epoch: [37] [ 480/1319] eta: 0:46:53 lr: 4.323818816304266e-06 loss: 0.0316 (0.0302) time: 3.2820 data: 0.0107 max mem: 33369 +Epoch: [37] [ 490/1319] eta: 0:46:20 lr: 4.3126220462124026e-06 loss: 0.0292 (0.0301) time: 3.3415 data: 0.0106 max mem: 33369 +Epoch: [37] [ 500/1319] eta: 0:45:47 lr: 4.3014220451909986e-06 loss: 0.0268 (0.0301) time: 3.3809 data: 0.0107 max mem: 33369 +Epoch: [37] [ 510/1319] eta: 0:45:13 lr: 4.2902188029549045e-06 loss: 0.0258 (0.0301) time: 3.3545 data: 0.0117 max mem: 33369 +Epoch: [37] [ 520/1319] eta: 0:44:39 lr: 4.279012309156296e-06 loss: 0.0258 (0.0301) time: 3.3287 data: 0.0114 max mem: 33369 +Epoch: [37] [ 530/1319] eta: 0:44:05 lr: 4.267802553384072e-06 loss: 0.0327 (0.0302) time: 3.3278 data: 0.0112 max mem: 33369 +Epoch: [37] [ 540/1319] eta: 0:43:32 lr: 4.256589525163327e-06 loss: 0.0346 (0.0303) time: 3.3591 data: 0.0116 max mem: 33369 +Epoch: [37] [ 550/1319] eta: 0:42:58 lr: 4.2453732139547435e-06 loss: 0.0318 (0.0302) time: 3.3399 data: 0.0112 max mem: 33369 +Epoch: [37] [ 560/1319] eta: 0:42:23 lr: 4.234153609154016e-06 loss: 0.0306 (0.0302) time: 3.2917 data: 0.0103 max mem: 33369 +Epoch: [37] [ 570/1319] eta: 0:41:50 lr: 4.222930700091251e-06 loss: 0.0307 (0.0303) time: 3.3167 data: 0.0105 max mem: 33369 +Epoch: [37] [ 580/1319] eta: 0:41:16 lr: 4.211704476030378e-06 loss: 0.0302 (0.0303) time: 3.3415 data: 0.0114 max mem: 33369 +Epoch: [37] [ 590/1319] eta: 0:40:42 lr: 4.200474926168517e-06 loss: 0.0269 (0.0303) time: 3.3138 data: 0.0106 max mem: 33369 +Epoch: [37] [ 600/1319] eta: 0:40:09 lr: 4.189242039635394e-06 loss: 0.0266 (0.0303) time: 3.3412 data: 0.0093 max mem: 33369 +Epoch: [37] [ 610/1319] eta: 0:39:35 lr: 4.178005805492704e-06 loss: 0.0262 (0.0303) time: 3.3590 data: 0.0090 max mem: 33369 +Epoch: [37] [ 620/1319] eta: 0:39:02 lr: 4.166766212733477e-06 loss: 0.0251 (0.0303) time: 3.3520 data: 0.0097 max mem: 33369 +Epoch: [37] [ 630/1319] eta: 0:38:28 lr: 4.15552325028145e-06 loss: 0.0258 (0.0302) time: 3.3568 data: 0.0096 max mem: 33369 +Epoch: [37] [ 640/1319] eta: 0:37:54 lr: 4.1442769069903985e-06 loss: 0.0275 (0.0302) time: 3.3123 data: 0.0092 max mem: 33369 +Epoch: [37] [ 650/1319] eta: 0:37:20 lr: 4.133027171643516e-06 loss: 0.0252 (0.0302) time: 3.2913 data: 0.0100 max mem: 33369 +Epoch: [37] [ 660/1319] eta: 0:36:47 lr: 4.121774032952729e-06 loss: 0.0276 (0.0302) time: 3.3415 data: 0.0108 max mem: 33369 +Epoch: [37] [ 670/1319] eta: 0:36:14 lr: 4.110517479558032e-06 loss: 0.0279 (0.0302) time: 3.3917 data: 0.0108 max mem: 33369 +Epoch: [37] [ 680/1319] eta: 0:35:40 lr: 4.099257500026817e-06 loss: 0.0279 (0.0302) time: 3.3732 data: 0.0103 max mem: 33369 +Epoch: [37] [ 690/1319] eta: 0:35:07 lr: 4.087994082853156e-06 loss: 0.0279 (0.0302) time: 3.3372 data: 0.0103 max mem: 33369 +Epoch: [37] [ 700/1319] eta: 0:34:33 lr: 4.076727216457151e-06 loss: 0.0272 (0.0301) time: 3.3110 data: 0.0106 max mem: 33369 +Epoch: [37] [ 710/1319] eta: 0:33:59 lr: 4.065456889184196e-06 loss: 0.0299 (0.0302) time: 3.2931 data: 0.0106 max mem: 33369 +Epoch: [37] [ 720/1319] eta: 0:33:25 lr: 4.054183089304276e-06 loss: 0.0307 (0.0302) time: 3.3049 data: 0.0097 max mem: 33369 +Epoch: [37] [ 730/1319] eta: 0:32:51 lr: 4.0429058050112415e-06 loss: 0.0317 (0.0303) time: 3.3267 data: 0.0093 max mem: 33369 +Epoch: [37] [ 740/1319] eta: 0:32:18 lr: 4.031625024422082e-06 loss: 0.0279 (0.0302) time: 3.3435 data: 0.0099 max mem: 33369 +Epoch: [37] [ 750/1319] eta: 0:31:44 lr: 4.020340735576163e-06 loss: 0.0279 (0.0303) time: 3.3388 data: 0.0111 max mem: 33369 +Epoch: [37] [ 760/1319] eta: 0:31:10 lr: 4.0090529264345135e-06 loss: 0.0273 (0.0302) time: 3.3183 data: 0.0116 max mem: 33369 +Epoch: [37] [ 770/1319] eta: 0:30:37 lr: 3.997761584879033e-06 loss: 0.0286 (0.0302) time: 3.3114 data: 0.0113 max mem: 33369 +Epoch: [37] [ 780/1319] eta: 0:30:03 lr: 3.986466698711739e-06 loss: 0.0301 (0.0302) time: 3.3195 data: 0.0110 max mem: 33369 +Epoch: [37] [ 790/1319] eta: 0:29:30 lr: 3.975168255653987e-06 loss: 0.0301 (0.0303) time: 3.3279 data: 0.0111 max mem: 33369 +Epoch: [37] [ 800/1319] eta: 0:28:56 lr: 3.963866243345654e-06 loss: 0.0313 (0.0303) time: 3.3395 data: 0.0109 max mem: 33369 +Epoch: [37] [ 810/1319] eta: 0:28:24 lr: 3.952560649344379e-06 loss: 0.0296 (0.0303) time: 3.4369 data: 0.0104 max mem: 33369 +Epoch: [37] [ 820/1319] eta: 0:27:50 lr: 3.94125146112473e-06 loss: 0.0288 (0.0304) time: 3.4153 data: 0.0105 max mem: 33369 +Epoch: [37] [ 830/1319] eta: 0:27:16 lr: 3.929938666077381e-06 loss: 0.0258 (0.0304) time: 3.3152 data: 0.0101 max mem: 33369 +Epoch: [37] [ 840/1319] eta: 0:26:43 lr: 3.918622251508287e-06 loss: 0.0258 (0.0304) time: 3.3409 data: 0.0097 max mem: 33369 +Epoch: [37] [ 850/1319] eta: 0:26:09 lr: 3.907302204637846e-06 loss: 0.0295 (0.0304) time: 3.3474 data: 0.0096 max mem: 33369 +Epoch: [37] [ 860/1319] eta: 0:25:36 lr: 3.895978512600013e-06 loss: 0.0338 (0.0304) time: 3.3549 data: 0.0094 max mem: 33369 +Epoch: [37] [ 870/1319] eta: 0:25:03 lr: 3.8846511624414845e-06 loss: 0.0284 (0.0304) time: 3.3603 data: 0.0094 max mem: 33369 +Epoch: [37] [ 880/1319] eta: 0:24:29 lr: 3.873320141120784e-06 loss: 0.0256 (0.0303) time: 3.3579 data: 0.0098 max mem: 33369 +Epoch: [37] [ 890/1319] eta: 0:23:56 lr: 3.86198543550739e-06 loss: 0.0249 (0.0303) time: 3.3518 data: 0.0099 max mem: 33369 +Epoch: [37] [ 900/1319] eta: 0:23:22 lr: 3.850647032380834e-06 loss: 0.0262 (0.0303) time: 3.3544 data: 0.0095 max mem: 33369 +Epoch: [37] [ 910/1319] eta: 0:22:49 lr: 3.839304918429766e-06 loss: 0.0264 (0.0303) time: 3.3595 data: 0.0096 max mem: 33369 +Epoch: [37] [ 920/1319] eta: 0:22:15 lr: 3.8279590802510684e-06 loss: 0.0269 (0.0303) time: 3.3311 data: 0.0096 max mem: 33369 +Epoch: [37] [ 930/1319] eta: 0:21:42 lr: 3.816609504348892e-06 loss: 0.0297 (0.0303) time: 3.3096 data: 0.0094 max mem: 33369 +Epoch: [37] [ 940/1319] eta: 0:21:08 lr: 3.805256177133712e-06 loss: 0.0297 (0.0303) time: 3.3218 data: 0.0090 max mem: 33369 +Epoch: [37] [ 950/1319] eta: 0:20:34 lr: 3.7938990849213705e-06 loss: 0.0292 (0.0303) time: 3.3173 data: 0.0086 max mem: 33369 +Epoch: [37] [ 960/1319] eta: 0:20:01 lr: 3.782538213932079e-06 loss: 0.0285 (0.0303) time: 3.3199 data: 0.0090 max mem: 33369 +Epoch: [37] [ 970/1319] eta: 0:19:28 lr: 3.771173550289461e-06 loss: 0.0279 (0.0303) time: 3.3528 data: 0.0089 max mem: 33369 +Epoch: [37] [ 980/1319] eta: 0:18:54 lr: 3.7598050800195294e-06 loss: 0.0279 (0.0303) time: 3.3485 data: 0.0093 max mem: 33369 +Epoch: [37] [ 990/1319] eta: 0:18:20 lr: 3.748432789049672e-06 loss: 0.0288 (0.0303) time: 3.3282 data: 0.0105 max mem: 33369 +Epoch: [37] [1000/1319] eta: 0:17:47 lr: 3.7370566632076215e-06 loss: 0.0278 (0.0303) time: 3.3471 data: 0.0111 max mem: 33369 +Epoch: [37] [1010/1319] eta: 0:17:14 lr: 3.725676688220417e-06 loss: 0.0267 (0.0303) time: 3.3529 data: 0.0113 max mem: 33369 +Epoch: [37] [1020/1319] eta: 0:16:40 lr: 3.714292849713318e-06 loss: 0.0267 (0.0302) time: 3.3339 data: 0.0113 max mem: 33369 +Epoch: [37] [1030/1319] eta: 0:16:07 lr: 3.7029051332087708e-06 loss: 0.0294 (0.0303) time: 3.3241 data: 0.0115 max mem: 33369 +Epoch: [37] [1040/1319] eta: 0:15:33 lr: 3.691513524125288e-06 loss: 0.0291 (0.0302) time: 3.3280 data: 0.0110 max mem: 33369 +Epoch: [37] [1050/1319] eta: 0:15:00 lr: 3.680118007776355e-06 loss: 0.0276 (0.0303) time: 3.3330 data: 0.0107 max mem: 33369 +Epoch: [37] [1060/1319] eta: 0:14:26 lr: 3.6687185693693123e-06 loss: 0.0285 (0.0302) time: 3.3246 data: 0.0110 max mem: 33369 +Epoch: [37] [1070/1319] eta: 0:13:52 lr: 3.657315194004196e-06 loss: 0.0304 (0.0302) time: 3.3133 data: 0.0110 max mem: 33369 +Epoch: [37] [1080/1319] eta: 0:13:19 lr: 3.6459078666726217e-06 loss: 0.0307 (0.0303) time: 3.3111 data: 0.0109 max mem: 33369 +Epoch: [37] [1090/1319] eta: 0:12:46 lr: 3.6344965722565904e-06 loss: 0.0279 (0.0302) time: 3.3390 data: 0.0106 max mem: 33369 +Epoch: [37] [1100/1319] eta: 0:12:12 lr: 3.6230812955273095e-06 loss: 0.0301 (0.0303) time: 3.3718 data: 0.0104 max mem: 33369 +Epoch: [37] [1110/1319] eta: 0:11:39 lr: 3.6116620211439967e-06 loss: 0.0311 (0.0304) time: 3.3745 data: 0.0097 max mem: 33369 +Epoch: [37] [1120/1319] eta: 0:11:05 lr: 3.6002387336526318e-06 loss: 0.0305 (0.0304) time: 3.3238 data: 0.0096 max mem: 33369 +Epoch: [37] [1130/1319] eta: 0:10:32 lr: 3.588811417484761e-06 loss: 0.0308 (0.0304) time: 3.3135 data: 0.0108 max mem: 33369 +Epoch: [37] [1140/1319] eta: 0:09:58 lr: 3.577380056956213e-06 loss: 0.0287 (0.0304) time: 3.3419 data: 0.0113 max mem: 33369 +Epoch: [37] [1150/1319] eta: 0:09:25 lr: 3.5659446362658317e-06 loss: 0.0261 (0.0304) time: 3.3430 data: 0.0105 max mem: 33369 +Epoch: [37] [1160/1319] eta: 0:08:51 lr: 3.5545051394941854e-06 loss: 0.0303 (0.0304) time: 3.3281 data: 0.0112 max mem: 33369 +Epoch: [37] [1170/1319] eta: 0:08:18 lr: 3.5430615506022587e-06 loss: 0.0310 (0.0304) time: 3.3163 data: 0.0121 max mem: 33369 +Epoch: [37] [1180/1319] eta: 0:07:44 lr: 3.531613853430098e-06 loss: 0.0287 (0.0304) time: 3.3589 data: 0.0117 max mem: 33369 +Epoch: [37] [1190/1319] eta: 0:07:11 lr: 3.5201620316954973e-06 loss: 0.0266 (0.0304) time: 3.3972 data: 0.0109 max mem: 33369 +Epoch: [37] [1200/1319] eta: 0:06:38 lr: 3.5087060689926057e-06 loss: 0.0266 (0.0304) time: 3.3616 data: 0.0114 max mem: 33369 +Epoch: [37] [1210/1319] eta: 0:06:04 lr: 3.4972459487905388e-06 loss: 0.0274 (0.0304) time: 3.3301 data: 0.0124 max mem: 33369 +Epoch: [37] [1220/1319] eta: 0:05:31 lr: 3.485781654431977e-06 loss: 0.0264 (0.0304) time: 3.3313 data: 0.0116 max mem: 33369 +Epoch: [37] [1230/1319] eta: 0:04:57 lr: 3.4743131691317023e-06 loss: 0.0285 (0.0305) time: 3.3088 data: 0.0102 max mem: 33369 +Epoch: [37] [1240/1319] eta: 0:04:24 lr: 3.462840475975186e-06 loss: 0.0324 (0.0305) time: 3.2972 data: 0.0106 max mem: 33369 +Epoch: [37] [1250/1319] eta: 0:03:50 lr: 3.451363557917087e-06 loss: 0.0302 (0.0305) time: 3.3099 data: 0.0113 max mem: 33369 +Epoch: [37] [1260/1319] eta: 0:03:17 lr: 3.439882397779757e-06 loss: 0.0312 (0.0305) time: 3.3352 data: 0.0107 max mem: 33369 +Epoch: [37] [1270/1319] eta: 0:02:43 lr: 3.4283969782517246e-06 loss: 0.0293 (0.0305) time: 3.3392 data: 0.0100 max mem: 33369 +Epoch: [37] [1280/1319] eta: 0:02:10 lr: 3.416907281886128e-06 loss: 0.0280 (0.0305) time: 3.3182 data: 0.0091 max mem: 33369 +Epoch: [37] [1290/1319] eta: 0:01:36 lr: 3.405413291099184e-06 loss: 0.0279 (0.0305) time: 3.3208 data: 0.0096 max mem: 33369 +Epoch: [37] [1300/1319] eta: 0:01:03 lr: 3.393914988168568e-06 loss: 0.0279 (0.0305) time: 3.3096 data: 0.0101 max mem: 33369 +Epoch: [37] [1310/1319] eta: 0:00:30 lr: 3.3824123552318046e-06 loss: 0.0315 (0.0305) time: 3.2925 data: 0.0090 max mem: 33369 +Epoch: [37] Total time: 1:13:30 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 2:40:29 time: 3.7427 data: 3.6509 max mem: 33369 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 100/2573] eta: 0:04:51 time: 0.0791 data: 0.0017 max mem: 33369 +Test: [ 200/2573] eta: 0:03:56 time: 0.0812 data: 0.0016 max mem: 33369 +Test: [ 300/2573] eta: 0:03:32 time: 0.0825 data: 0.0015 max mem: 33369 +Test: [ 400/2573] eta: 0:03:16 time: 0.0832 data: 0.0015 max mem: 33369 +Test: [ 500/2573] eta: 0:03:03 time: 0.0831 data: 0.0017 max mem: 33369 +Test: [ 600/2573] eta: 0:02:52 time: 0.0806 data: 0.0016 max mem: 33369 +Test: [ 700/2573] eta: 0:02:43 time: 0.0836 data: 0.0019 max mem: 33369 +Test: [ 800/2573] eta: 0:02:33 time: 0.0845 data: 0.0015 max mem: 33369 +Test: [ 900/2573] eta: 0:02:24 time: 0.0821 data: 0.0014 max mem: 33369 +Test: [1000/2573] eta: 0:02:15 time: 0.0821 data: 0.0017 max mem: 33369 +Test: [1100/2573] eta: 0:02:06 time: 0.0815 data: 0.0015 max mem: 33369 +Test: [1200/2573] eta: 0:01:57 time: 0.0828 data: 0.0015 max mem: 33369 +Test: [1300/2573] eta: 0:01:48 time: 0.0820 data: 0.0014 max mem: 33369 +Test: [1400/2573] eta: 0:01:39 time: 0.0859 data: 0.0022 max mem: 33369 +Test: [1500/2573] eta: 0:01:31 time: 0.0863 data: 0.0020 max mem: 33369 +Test: [1600/2573] eta: 0:01:22 time: 0.0835 data: 0.0015 max mem: 33369 +Test: [1700/2573] eta: 0:01:13 time: 0.0801 data: 0.0017 max mem: 33369 +Test: [1800/2573] eta: 0:01:05 time: 0.0828 data: 0.0016 max mem: 33369 +Test: [1900/2573] eta: 0:00:56 time: 0.0840 data: 0.0019 max mem: 33369 +Test: [2000/2573] eta: 0:00:48 time: 0.0817 data: 0.0015 max mem: 33369 +Test: [2100/2573] eta: 0:00:39 time: 0.0829 data: 0.0014 max mem: 33369 +Test: [2200/2573] eta: 0:00:31 time: 0.0826 data: 0.0015 max mem: 33369 +Test: [2300/2573] eta: 0:00:22 time: 0.0844 data: 0.0017 max mem: 33369 +Test: [2400/2573] eta: 0:00:14 time: 0.0782 data: 0.0016 max mem: 33369 +Test: [2500/2573] eta: 0:00:06 time: 0.0833 data: 0.0017 max mem: 33369 +Test: Total time: 0:03:36 +Final results: +Mean IoU is 65.13 + + precision@0.5 = 73.20 + precision@0.6 = 67.93 + precision@0.7 = 60.95 + precision@0.8 = 49.67 + precision@0.9 = 25.37 + overall IoU = 62.57 + +Average object IoU 65.12722612436097 +Overall IoU 62.570987701416016 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [38] [ 0/1319] eta: 4:26:15 lr: 3.3720562685558925e-06 loss: 0.0272 (0.0272) time: 12.1115 data: 2.6592 max mem: 33369 +Epoch: [38] [ 10/1319] eta: 1:31:38 lr: 3.3605453588871517e-06 loss: 0.0273 (0.0362) time: 4.2007 data: 0.2504 max mem: 33369 +Epoch: [38] [ 20/1319] eta: 1:21:35 lr: 3.349030066603249e-06 loss: 0.0325 (0.0344) time: 3.3517 data: 0.0094 max mem: 33369 +Epoch: [38] [ 30/1319] eta: 1:18:18 lr: 3.3375103732791936e-06 loss: 0.0320 (0.0389) time: 3.3391 data: 0.0091 max mem: 33369 +Epoch: [38] [ 40/1319] eta: 1:15:43 lr: 3.3259862603415314e-06 loss: 0.0285 (0.0367) time: 3.3250 data: 0.0094 max mem: 33369 +Epoch: [38] [ 50/1319] eta: 1:14:22 lr: 3.314457709066606e-06 loss: 0.0292 (0.0360) time: 3.3170 data: 0.0095 max mem: 33369 +Epoch: [38] [ 60/1319] eta: 1:13:18 lr: 3.302924700578736e-06 loss: 0.0307 (0.0353) time: 3.3733 data: 0.0089 max mem: 33369 +Epoch: [38] [ 70/1319] eta: 1:12:25 lr: 3.2913872158483893e-06 loss: 0.0271 (0.0347) time: 3.3832 data: 0.0092 max mem: 33369 +Epoch: [38] [ 80/1319] eta: 1:11:29 lr: 3.279845235690334e-06 loss: 0.0271 (0.0339) time: 3.3646 data: 0.0093 max mem: 33369 +Epoch: [38] [ 90/1319] eta: 1:10:45 lr: 3.268298740761722e-06 loss: 0.0277 (0.0334) time: 3.3665 data: 0.0090 max mem: 33369 +Epoch: [38] [ 100/1319] eta: 1:09:55 lr: 3.2567477115602124e-06 loss: 0.0304 (0.0332) time: 3.3608 data: 0.0102 max mem: 33369 +Epoch: [38] [ 110/1319] eta: 1:09:06 lr: 3.2451921284219928e-06 loss: 0.0311 (0.0332) time: 3.3206 data: 0.0115 max mem: 33369 +Epoch: [38] [ 120/1319] eta: 1:08:24 lr: 3.233631971519807e-06 loss: 0.0297 (0.0330) time: 3.3275 data: 0.0104 max mem: 33369 +Epoch: [38] [ 130/1319] eta: 1:07:42 lr: 3.2220672208609392e-06 loss: 0.0235 (0.0325) time: 3.3448 data: 0.0092 max mem: 33369 +Epoch: [38] [ 140/1319] eta: 1:07:02 lr: 3.2104978562851772e-06 loss: 0.0245 (0.0321) time: 3.3419 data: 0.0097 max mem: 33369 +Epoch: [38] [ 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data: 0.0108 max mem: 33369 +Epoch: [38] [ 310/1319] eta: 0:56:43 lr: 3.013092338126003e-06 loss: 0.0300 (0.0310) time: 3.3427 data: 0.0100 max mem: 33369 +Epoch: [38] [ 320/1319] eta: 0:56:09 lr: 3.0014362715060913e-06 loss: 0.0328 (0.0311) time: 3.3480 data: 0.0094 max mem: 33369 +Epoch: [38] [ 330/1319] eta: 0:55:35 lr: 2.9897751731121923e-06 loss: 0.0294 (0.0311) time: 3.3521 data: 0.0092 max mem: 33369 +Epoch: [38] [ 340/1319] eta: 0:55:02 lr: 2.978109018946967e-06 loss: 0.0270 (0.0309) time: 3.3794 data: 0.0097 max mem: 33369 +Epoch: [38] [ 350/1319] eta: 0:54:28 lr: 2.9664377847936435e-06 loss: 0.0260 (0.0308) time: 3.3813 data: 0.0097 max mem: 33369 +Epoch: [38] [ 360/1319] eta: 0:53:54 lr: 2.954761446213011e-06 loss: 0.0261 (0.0308) time: 3.3660 data: 0.0101 max mem: 33369 +Epoch: [38] [ 370/1319] eta: 0:53:19 lr: 2.943079978540434e-06 loss: 0.0281 (0.0308) time: 3.3509 data: 0.0104 max mem: 33369 +Epoch: [38] [ 380/1319] eta: 0:52:45 lr: 2.931393356882739e-06 loss: 0.0262 (0.0308) time: 3.3382 data: 0.0092 max mem: 33369 +Epoch: [38] [ 390/1319] eta: 0:52:10 lr: 2.919701556115084e-06 loss: 0.0288 (0.0308) time: 3.3339 data: 0.0098 max mem: 33369 +Epoch: [38] [ 400/1319] eta: 0:51:35 lr: 2.908004550877762e-06 loss: 0.0274 (0.0307) time: 3.3348 data: 0.0113 max mem: 33369 +Epoch: [38] [ 410/1319] eta: 0:51:00 lr: 2.8963023155729493e-06 loss: 0.0273 (0.0307) time: 3.3237 data: 0.0118 max mem: 33369 +Epoch: [38] [ 420/1319] eta: 0:50:29 lr: 2.884594824361366e-06 loss: 0.0283 (0.0306) time: 3.3963 data: 0.0115 max mem: 33369 +Epoch: [38] [ 430/1319] eta: 0:49:55 lr: 2.8728820511589384e-06 loss: 0.0283 (0.0307) time: 3.4217 data: 0.0109 max mem: 33369 +Epoch: [38] [ 440/1319] eta: 0:49:21 lr: 2.861163969633332e-06 loss: 0.0254 (0.0306) time: 3.3366 data: 0.0108 max mem: 33369 +Epoch: [38] [ 450/1319] eta: 0:48:46 lr: 2.849440553200456e-06 loss: 0.0240 (0.0305) time: 3.3266 data: 0.0105 max mem: 33369 +Epoch: [38] [ 460/1319] eta: 0:48:12 lr: 2.837711775020899e-06 loss: 0.0261 (0.0305) time: 3.3372 data: 0.0105 max mem: 33369 +Epoch: [38] [ 470/1319] eta: 0:47:38 lr: 2.8259776079962665e-06 loss: 0.0253 (0.0304) time: 3.3411 data: 0.0106 max mem: 33369 +Epoch: [38] [ 480/1319] eta: 0:47:04 lr: 2.814238024765515e-06 loss: 0.0261 (0.0305) time: 3.3444 data: 0.0108 max mem: 33369 +Epoch: [38] [ 490/1319] eta: 0:46:30 lr: 2.8024929977011503e-06 loss: 0.0300 (0.0305) time: 3.3449 data: 0.0112 max mem: 33369 +Epoch: [38] [ 500/1319] eta: 0:45:56 lr: 2.790742498905385e-06 loss: 0.0243 (0.0304) time: 3.3367 data: 0.0112 max mem: 33369 +Epoch: [38] [ 510/1319] eta: 0:45:22 lr: 2.7789865002062234e-06 loss: 0.0254 (0.0304) time: 3.3322 data: 0.0111 max mem: 33369 +Epoch: [38] [ 520/1319] eta: 0:44:48 lr: 2.7672249731534377e-06 loss: 0.0291 (0.0304) time: 3.3425 data: 0.0117 max mem: 33369 +Epoch: [38] [ 530/1319] eta: 0:44:14 lr: 2.7554578890145323e-06 loss: 0.0290 (0.0304) time: 3.3505 data: 0.0119 max mem: 33369 +Epoch: [38] [ 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mem: 33369 +Epoch: [38] [ 620/1319] eta: 0:39:12 lr: 2.6492991768045523e-06 loss: 0.0249 (0.0303) time: 3.3402 data: 0.0098 max mem: 33369 +Epoch: [38] [ 630/1319] eta: 0:38:40 lr: 2.637474876335259e-06 loss: 0.0251 (0.0303) time: 3.4310 data: 0.0101 max mem: 33369 +Epoch: [38] [ 640/1319] eta: 0:38:05 lr: 2.6256446828424878e-06 loss: 0.0297 (0.0304) time: 3.4170 data: 0.0098 max mem: 33369 +Epoch: [38] [ 650/1319] eta: 0:37:31 lr: 2.613808563857519e-06 loss: 0.0313 (0.0304) time: 3.3253 data: 0.0106 max mem: 33369 +Epoch: [38] [ 660/1319] eta: 0:36:57 lr: 2.6019664865683917e-06 loss: 0.0299 (0.0304) time: 3.3316 data: 0.0101 max mem: 33369 +Epoch: [38] [ 670/1319] eta: 0:36:25 lr: 2.590118417814524e-06 loss: 0.0252 (0.0304) time: 3.3951 data: 0.0103 max mem: 33369 +Epoch: [38] [ 680/1319] eta: 0:35:51 lr: 2.5782643240811925e-06 loss: 0.0269 (0.0304) time: 3.4395 data: 0.0105 max mem: 33369 +Epoch: [38] [ 690/1319] eta: 0:35:18 lr: 2.566404171493961e-06 loss: 0.0292 (0.0305) time: 3.3956 data: 0.0101 max mem: 33369 +Epoch: [38] [ 700/1319] eta: 0:34:45 lr: 2.5545379258129243e-06 loss: 0.0336 (0.0305) time: 3.4043 data: 0.0104 max mem: 33369 +Epoch: [38] [ 710/1319] eta: 0:34:12 lr: 2.5426655524268633e-06 loss: 0.0250 (0.0304) time: 3.4312 data: 0.0101 max mem: 33369 +Epoch: [38] [ 720/1319] eta: 0:33:37 lr: 2.5307870163472715e-06 loss: 0.0248 (0.0304) time: 3.3667 data: 0.0100 max mem: 33369 +Epoch: [38] [ 730/1319] eta: 0:33:04 lr: 2.5189022822022593e-06 loss: 0.0248 (0.0303) time: 3.3633 data: 0.0096 max mem: 33369 +Epoch: [38] [ 740/1319] eta: 0:32:31 lr: 2.5070113142302914e-06 loss: 0.0248 (0.0302) time: 3.4043 data: 0.0098 max mem: 33369 +Epoch: [38] [ 750/1319] eta: 0:31:56 lr: 2.495114076273858e-06 loss: 0.0271 (0.0302) time: 3.3477 data: 0.0105 max mem: 33369 +Epoch: [38] [ 760/1319] eta: 0:31:23 lr: 2.483210531772943e-06 loss: 0.0285 (0.0303) time: 3.3303 data: 0.0104 max mem: 33369 +Epoch: [38] [ 770/1319] eta: 0:30:49 lr: 2.4713006437583777e-06 loss: 0.0266 (0.0302) time: 3.3670 data: 0.0101 max mem: 33369 +Epoch: [38] [ 780/1319] eta: 0:30:15 lr: 2.4593843748450576e-06 loss: 0.0266 (0.0303) time: 3.3481 data: 0.0097 max mem: 33369 +Epoch: [38] [ 790/1319] eta: 0:29:41 lr: 2.447461687224963e-06 loss: 0.0271 (0.0302) time: 3.3184 data: 0.0091 max mem: 33369 +Epoch: [38] [ 800/1319] eta: 0:29:07 lr: 2.4355325426601037e-06 loss: 0.0288 (0.0303) time: 3.3300 data: 0.0093 max mem: 33369 +Epoch: [38] [ 810/1319] eta: 0:28:34 lr: 2.423596902475233e-06 loss: 0.0277 (0.0303) time: 3.3804 data: 0.0096 max mem: 33369 +Epoch: [38] [ 820/1319] eta: 0:28:00 lr: 2.4116547275504333e-06 loss: 0.0277 (0.0303) time: 3.3640 data: 0.0093 max mem: 33369 +Epoch: [38] [ 830/1319] eta: 0:27:26 lr: 2.3997059783135262e-06 loss: 0.0247 (0.0302) time: 3.3236 data: 0.0099 max mem: 33369 +Epoch: [38] [ 840/1319] eta: 0:26:52 lr: 2.38775061473232e-06 loss: 0.0277 (0.0302) time: 3.3473 data: 0.0110 max mem: 33369 +Epoch: [38] [ 850/1319] eta: 0:26:18 lr: 2.3757885963066428e-06 loss: 0.0327 (0.0303) time: 3.3520 data: 0.0104 max mem: 33369 +Epoch: [38] [ 860/1319] eta: 0:25:44 lr: 2.3638198820602614e-06 loss: 0.0270 (0.0302) time: 3.3291 data: 0.0096 max mem: 33369 +Epoch: [38] [ 870/1319] eta: 0:25:12 lr: 2.351844430532552e-06 loss: 0.0273 (0.0302) time: 3.4373 data: 0.0107 max mem: 33369 +Epoch: [38] [ 880/1319] eta: 0:24:39 lr: 2.339862199770001e-06 loss: 0.0292 (0.0302) time: 3.5273 data: 0.0104 max mem: 33369 +Epoch: [38] [ 890/1319] eta: 0:24:05 lr: 2.327873147317513e-06 loss: 0.0293 (0.0303) time: 3.4059 data: 0.0092 max mem: 33369 +Epoch: [38] [ 900/1319] eta: 0:23:31 lr: 2.315877230209485e-06 loss: 0.0320 (0.0303) time: 3.3189 data: 0.0099 max mem: 33369 +Epoch: [38] [ 910/1319] eta: 0:22:57 lr: 2.303874404960728e-06 loss: 0.0284 (0.0303) time: 3.3499 data: 0.0106 max mem: 33369 +Epoch: [38] [ 920/1319] eta: 0:22:23 lr: 2.291864627557113e-06 loss: 0.0288 (0.0303) time: 3.3480 data: 0.0097 max mem: 33369 +Epoch: [38] [ 930/1319] eta: 0:21:49 lr: 2.2798478534460264e-06 loss: 0.0288 (0.0303) time: 3.3242 data: 0.0102 max mem: 33369 +Epoch: [38] [ 940/1319] eta: 0:21:16 lr: 2.2678240375265906e-06 loss: 0.0286 (0.0303) time: 3.3740 data: 0.0109 max mem: 33369 +Epoch: [38] [ 950/1319] eta: 0:20:43 lr: 2.25579313413962e-06 loss: 0.0280 (0.0303) time: 3.4506 data: 0.0112 max mem: 33369 +Epoch: [38] [ 960/1319] eta: 0:20:09 lr: 2.243755097057401e-06 loss: 0.0275 (0.0303) time: 3.4462 data: 0.0117 max mem: 33369 +Epoch: [38] [ 970/1319] eta: 0:19:35 lr: 2.2317098794731506e-06 loss: 0.0264 (0.0303) time: 3.3593 data: 0.0115 max mem: 33369 +Epoch: [38] [ 980/1319] eta: 0:19:02 lr: 2.2196574339902486e-06 loss: 0.0300 (0.0303) time: 3.3475 data: 0.0115 max mem: 33369 +Epoch: [38] [ 990/1319] eta: 0:18:28 lr: 2.2075977126112046e-06 loss: 0.0328 (0.0303) time: 3.3560 data: 0.0113 max mem: 33369 +Epoch: [38] [1000/1319] eta: 0:17:54 lr: 2.195530666726346e-06 loss: 0.0289 (0.0303) time: 3.3168 data: 0.0107 max mem: 33369 +Epoch: [38] [1010/1319] eta: 0:17:21 lr: 2.183456247102197e-06 loss: 0.0276 (0.0303) time: 3.4151 data: 0.0107 max mem: 33369 +Epoch: [38] [1020/1319] eta: 0:16:48 lr: 2.1713744038696293e-06 loss: 0.0292 (0.0303) time: 3.5290 data: 0.0111 max mem: 33369 +Epoch: [38] [1030/1319] eta: 0:16:14 lr: 2.1592850865116445e-06 loss: 0.0292 (0.0303) time: 3.4926 data: 0.0102 max mem: 33369 +Epoch: [38] [1040/1319] eta: 0:15:40 lr: 2.1471882438508782e-06 loss: 0.0320 (0.0303) time: 3.3933 data: 0.0096 max mem: 33369 +Epoch: [38] [1050/1319] eta: 0:15:07 lr: 2.135083824036786e-06 loss: 0.0331 (0.0303) time: 3.3637 data: 0.0100 max mem: 33369 +Epoch: [38] [1060/1319] eta: 0:14:33 lr: 2.1229717745324578e-06 loss: 0.0307 (0.0303) time: 3.3772 data: 0.0105 max mem: 33369 +Epoch: [38] [1070/1319] eta: 0:13:59 lr: 2.110852042101167e-06 loss: 0.0300 (0.0303) time: 3.3188 data: 0.0099 max mem: 33369 +Epoch: [38] [1080/1319] eta: 0:13:25 lr: 2.0987245727924905e-06 loss: 0.0269 (0.0303) time: 3.3504 data: 0.0086 max mem: 33369 +Epoch: [38] [1090/1319] eta: 0:12:52 lr: 2.086589311928101e-06 loss: 0.0252 (0.0303) time: 3.4119 data: 0.0100 max mem: 33369 +Epoch: [38] [1100/1319] eta: 0:12:18 lr: 2.074446204087186e-06 loss: 0.0321 (0.0304) time: 3.3205 data: 0.0106 max mem: 33369 +Epoch: [38] [1110/1319] eta: 0:11:44 lr: 2.062295193091432e-06 loss: 0.0306 (0.0304) time: 3.2636 data: 0.0100 max mem: 33369 +Epoch: [38] [1120/1319] eta: 0:11:10 lr: 2.050136221989693e-06 loss: 0.0306 (0.0304) time: 3.3823 data: 0.0106 max mem: 33369 +Epoch: [38] [1130/1319] eta: 0:10:37 lr: 2.0379692330421533e-06 loss: 0.0310 (0.0304) time: 3.4636 data: 0.0101 max mem: 33369 +Epoch: [38] [1140/1319] eta: 0:10:03 lr: 2.0257941677041134e-06 loss: 0.0249 (0.0303) time: 3.3651 data: 0.0101 max mem: 33369 +Epoch: [38] [1150/1319] eta: 0:09:29 lr: 2.013610966609312e-06 loss: 0.0273 (0.0303) time: 3.3042 data: 0.0111 max mem: 33369 +Epoch: [38] [1160/1319] eta: 0:08:55 lr: 2.0014195695528014e-06 loss: 0.0281 (0.0303) time: 3.3667 data: 0.0104 max mem: 33369 +Epoch: [38] [1170/1319] eta: 0:08:22 lr: 1.9892199154733075e-06 loss: 0.0295 (0.0303) time: 3.4148 data: 0.0091 max mem: 33369 +Epoch: [38] [1180/1319] eta: 0:07:48 lr: 1.977011942435173e-06 loss: 0.0327 (0.0303) time: 3.3738 data: 0.0088 max mem: 33369 +Epoch: [38] [1190/1319] eta: 0:07:14 lr: 1.964795587609718e-06 loss: 0.0284 (0.0303) time: 3.3158 data: 0.0089 max mem: 33369 +Epoch: [38] [1200/1319] eta: 0:06:41 lr: 1.9525707872561044e-06 loss: 0.0273 (0.0303) time: 3.3460 data: 0.0090 max mem: 33369 +Epoch: [38] [1210/1319] eta: 0:06:07 lr: 1.9403374767016633e-06 loss: 0.0274 (0.0303) time: 3.3653 data: 0.0092 max mem: 33369 +Epoch: [38] [1220/1319] eta: 0:05:33 lr: 1.928095590321611e-06 loss: 0.0321 (0.0303) time: 3.3220 data: 0.0095 max mem: 33369 +Epoch: [38] [1230/1319] eta: 0:04:59 lr: 1.915845061518256e-06 loss: 0.0247 (0.0303) time: 3.3590 data: 0.0092 max mem: 33369 +Epoch: [38] [1240/1319] eta: 0:04:26 lr: 1.9035858226995284e-06 loss: 0.0245 (0.0303) time: 3.4024 data: 0.0092 max mem: 33369 +Epoch: [38] [1250/1319] eta: 0:03:52 lr: 1.8913178052569088e-06 loss: 0.0262 (0.0303) time: 3.3425 data: 0.0090 max mem: 33369 +Epoch: [38] [1260/1319] eta: 0:03:18 lr: 1.8790409395427117e-06 loss: 0.0272 (0.0303) time: 3.3263 data: 0.0090 max mem: 33369 +Epoch: [38] [1270/1319] eta: 0:02:45 lr: 1.8667551548466507e-06 loss: 0.0245 (0.0302) time: 3.3417 data: 0.0099 max mem: 33369 +Epoch: [38] [1280/1319] eta: 0:02:11 lr: 1.8544603793717773e-06 loss: 0.0306 (0.0303) time: 3.3664 data: 0.0107 max mem: 33369 +Epoch: [38] [1290/1319] eta: 0:01:37 lr: 1.8421565402096163e-06 loss: 0.0322 (0.0303) time: 3.4264 data: 0.0099 max mem: 33369 +Epoch: [38] [1300/1319] eta: 0:01:04 lr: 1.8298435633145817e-06 loss: 0.0274 (0.0303) time: 3.3911 data: 0.0093 max mem: 33369 +Epoch: [38] [1310/1319] eta: 0:00:30 lr: 1.8175213734776007e-06 loss: 0.0263 (0.0303) time: 3.3370 data: 0.0090 max mem: 33369 +Epoch: [38] Total time: 1:14:04 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 2:43:48 time: 3.8200 data: 3.6124 max mem: 33369 +Test: [ 100/2573] eta: 0:04:48 time: 0.0802 data: 0.0017 max mem: 33369 +Test: [ 200/2573] eta: 0:04:00 time: 0.0855 data: 0.0021 max mem: 33369 +Test: [ 300/2573] eta: 0:03:36 time: 0.0829 data: 0.0015 max mem: 33369 +Test: [ 400/2573] eta: 0:03:19 time: 0.0841 data: 0.0018 max mem: 33369 +Test: [ 500/2573] eta: 0:03:05 time: 0.0816 data: 0.0019 max mem: 33369 +Test: [ 600/2573] eta: 0:02:54 time: 0.0822 data: 0.0015 max mem: 33369 +Test: [ 700/2573] eta: 0:02:44 time: 0.0822 data: 0.0017 max mem: 33369 +Test: [ 800/2573] eta: 0:02:34 time: 0.0851 data: 0.0019 max mem: 33369 +Test: [ 900/2573] eta: 0:02:24 time: 0.0846 data: 0.0018 max mem: 33369 +Test: [1000/2573] eta: 0:02:15 time: 0.0815 data: 0.0017 max mem: 33369 +Test: [1100/2573] eta: 0:02:06 time: 0.0803 data: 0.0017 max mem: 33369 +Test: [1200/2573] eta: 0:01:57 time: 0.0817 data: 0.0017 max mem: 33369 +Test: [1300/2573] eta: 0:01:48 time: 0.0814 data: 0.0015 max mem: 33369 +Test: [1400/2573] eta: 0:01:39 time: 0.0791 data: 0.0016 max mem: 33369 +Test: [1500/2573] eta: 0:01:30 time: 0.0818 data: 0.0017 max mem: 33369 +Test: [1600/2573] eta: 0:01:22 time: 0.0879 data: 0.0018 max mem: 33369 +Test: [1700/2573] eta: 0:01:13 time: 0.0815 data: 0.0017 max mem: 33369 +Test: [1800/2573] eta: 0:01:05 time: 0.0838 data: 0.0015 max mem: 33369 +Test: [1900/2573] eta: 0:00:56 time: 0.0804 data: 0.0016 max mem: 33369 +Test: [2000/2573] eta: 0:00:48 time: 0.0825 data: 0.0016 max mem: 33369 +Test: [2100/2573] eta: 0:00:39 time: 0.0850 data: 0.0017 max mem: 33369 +Test: [2200/2573] eta: 0:00:31 time: 0.0811 data: 0.0015 max mem: 33369 +Test: [2300/2573] eta: 0:00:22 time: 0.0836 data: 0.0017 max mem: 33369 +Test: [2400/2573] eta: 0:00:14 time: 0.0786 data: 0.0017 max mem: 33369 +Test: [2500/2573] eta: 0:00:06 time: 0.0821 data: 0.0017 max mem: 33369 +Test: Total time: 0:03:35 +Final results: +Mean IoU is 65.35 + + precision@0.5 = 73.88 + precision@0.6 = 67.91 + precision@0.7 = 61.36 + precision@0.8 = 49.75 + precision@0.9 = 25.33 + overall IoU = 62.84 + +Average object IoU 65.35317479209588 +Overall IoU 62.84455871582031 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [39] [ 0/1319] eta: 3:47:34 lr: 1.8064234624396156e-06 loss: 0.0378 (0.0378) time: 10.3519 data: 2.6449 max mem: 33369 +Epoch: [39] [ 10/1319] eta: 1:25:58 lr: 1.7940835565249508e-06 loss: 0.0280 (0.0276) time: 3.9411 data: 0.2495 max mem: 33369 +Epoch: [39] [ 20/1319] eta: 1:19:44 lr: 1.7817342127276263e-06 loss: 0.0265 (0.0271) time: 3.3501 data: 0.0099 max mem: 33369 +Epoch: [39] [ 30/1319] eta: 1:17:25 lr: 1.7693753510331764e-06 loss: 0.0261 (0.0267) time: 3.4189 data: 0.0098 max mem: 33369 +Epoch: [39] [ 40/1319] eta: 1:15:43 lr: 1.757006890122028e-06 loss: 0.0276 (0.0276) time: 3.4154 data: 0.0097 max mem: 33369 +Epoch: [39] [ 50/1319] eta: 1:14:33 lr: 1.7446287473378005e-06 loss: 0.0294 (0.0278) time: 3.4024 data: 0.0093 max mem: 33369 +Epoch: [39] [ 60/1319] eta: 1:13:31 lr: 1.7322408386546176e-06 loss: 0.0287 (0.0282) time: 3.4050 data: 0.0095 max mem: 33369 +Epoch: [39] [ 70/1319] eta: 1:13:20 lr: 1.7198430786433514e-06 loss: 0.0295 (0.0286) time: 3.5182 data: 0.0097 max mem: 33369 +Epoch: [39] [ 80/1319] eta: 1:12:23 lr: 1.7074353804367206e-06 loss: 0.0333 (0.0290) time: 3.5086 data: 0.0094 max mem: 33369 +Epoch: [39] [ 90/1319] eta: 1:11:20 lr: 1.6950176556933094e-06 loss: 0.0271 (0.0290) time: 3.3418 data: 0.0099 max mem: 33369 +Epoch: [39] [ 100/1319] eta: 1:11:05 lr: 1.682589814560305e-06 loss: 0.0306 (0.0296) time: 3.4745 data: 0.0096 max mem: 33369 +Epoch: [39] [ 110/1319] eta: 1:10:09 lr: 1.6701517656350208e-06 loss: 0.0303 (0.0293) time: 3.4749 data: 0.0094 max mem: 33369 +Epoch: [39] [ 120/1319] eta: 1:09:13 lr: 1.6577034159251048e-06 loss: 0.0255 (0.0294) time: 3.2871 data: 0.0099 max mem: 33369 +Epoch: [39] [ 130/1319] eta: 1:08:41 lr: 1.6452446708073954e-06 loss: 0.0290 (0.0293) time: 3.3798 data: 0.0107 max mem: 33369 +Epoch: [39] [ 140/1319] eta: 1:07:59 lr: 1.632775433985313e-06 loss: 0.0279 (0.0291) time: 3.4382 data: 0.0116 max mem: 33369 +Epoch: [39] [ 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33369 +Epoch: [39] [ 230/1319] eta: 1:01:59 lr: 1.5200633991482792e-06 loss: 0.0275 (0.0297) time: 3.3179 data: 0.0096 max mem: 33369 +Epoch: [39] [ 240/1319] eta: 1:01:25 lr: 1.5074835472089545e-06 loss: 0.0253 (0.0296) time: 3.3738 data: 0.0096 max mem: 33369 +Epoch: [39] [ 250/1319] eta: 1:00:44 lr: 1.4948920200579605e-06 loss: 0.0250 (0.0296) time: 3.3407 data: 0.0107 max mem: 33369 +Epoch: [39] [ 260/1319] eta: 1:00:06 lr: 1.4822886973851744e-06 loss: 0.0276 (0.0295) time: 3.2862 data: 0.0106 max mem: 33369 +Epoch: [39] [ 270/1319] eta: 0:59:30 lr: 1.4696734564912314e-06 loss: 0.0278 (0.0296) time: 3.3237 data: 0.0106 max mem: 33369 +Epoch: [39] [ 280/1319] eta: 0:58:54 lr: 1.457046172216814e-06 loss: 0.0311 (0.0297) time: 3.3500 data: 0.0105 max mem: 33369 +Epoch: [39] [ 290/1319] eta: 0:58:15 lr: 1.444406716869153e-06 loss: 0.0325 (0.0299) time: 3.3105 data: 0.0095 max mem: 33369 +Epoch: [39] [ 300/1319] eta: 0:57:39 lr: 1.4317549601455566e-06 loss: 0.0302 (0.0299) time: 3.3045 data: 0.0101 max mem: 33369 +Epoch: [39] [ 310/1319] eta: 0:57:08 lr: 1.419090769053936e-06 loss: 0.0293 (0.0299) time: 3.4111 data: 0.0104 max mem: 33369 +Epoch: [39] [ 320/1319] eta: 0:56:33 lr: 1.4064140078300187e-06 loss: 0.0301 (0.0299) time: 3.4127 data: 0.0094 max mem: 33369 +Epoch: [39] [ 330/1319] eta: 0:55:55 lr: 1.3937245378511972e-06 loss: 0.0283 (0.0300) time: 3.3216 data: 0.0092 max mem: 33369 +Epoch: [39] [ 340/1319] eta: 0:55:20 lr: 1.3810222175468009e-06 loss: 0.0267 (0.0301) time: 3.3228 data: 0.0093 max mem: 33369 +Epoch: [39] [ 350/1319] eta: 0:54:46 lr: 1.3683069023045655e-06 loss: 0.0267 (0.0300) time: 3.3735 data: 0.0090 max mem: 33369 +Epoch: [39] [ 360/1319] eta: 0:54:13 lr: 1.355578444373217e-06 loss: 0.0267 (0.0300) time: 3.4030 data: 0.0090 max mem: 33369 +Epoch: [39] [ 370/1319] eta: 0:53:38 lr: 1.3428366927608033e-06 loss: 0.0267 (0.0300) time: 3.3722 data: 0.0097 max mem: 33369 +Epoch: [39] [ 380/1319] eta: 0:53:03 lr: 1.330081493128668e-06 loss: 0.0268 (0.0299) time: 3.3562 data: 0.0104 max mem: 33369 +Epoch: [39] [ 390/1319] eta: 0:52:34 lr: 1.3173126876807778e-06 loss: 0.0267 (0.0299) time: 3.4794 data: 0.0101 max mem: 33369 +Epoch: [39] [ 400/1319] eta: 0:51:58 lr: 1.304530115048165e-06 loss: 0.0260 (0.0299) time: 3.4384 data: 0.0112 max mem: 33369 +Epoch: [39] [ 410/1319] eta: 0:51:23 lr: 1.2917336101681678e-06 loss: 0.0269 (0.0299) time: 3.3266 data: 0.0113 max mem: 33369 +Epoch: [39] [ 420/1319] eta: 0:50:50 lr: 1.2789230041582899e-06 loss: 0.0269 (0.0298) time: 3.3874 data: 0.0108 max mem: 33369 +Epoch: [39] [ 430/1319] eta: 0:50:14 lr: 1.2660981241842216e-06 loss: 0.0264 (0.0298) time: 3.3675 data: 0.0108 max mem: 33369 +Epoch: [39] [ 440/1319] eta: 0:49:39 lr: 1.2532587933218004e-06 loss: 0.0246 (0.0297) time: 3.3198 data: 0.0106 max mem: 33369 +Epoch: [39] [ 450/1319] eta: 0:49:04 lr: 1.2404048304125217e-06 loss: 0.0275 (0.0297) time: 3.3176 data: 0.0109 max mem: 33369 +Epoch: [39] [ 460/1319] eta: 0:48:32 lr: 1.2275360499121832e-06 loss: 0.0313 (0.0298) time: 3.4076 data: 0.0104 max mem: 33369 +Epoch: [39] [ 470/1319] eta: 0:47:56 lr: 1.2146522617323656e-06 loss: 0.0296 (0.0298) time: 3.3935 data: 0.0107 max mem: 33369 +Epoch: [39] [ 480/1319] eta: 0:47:21 lr: 1.2017532710741682e-06 loss: 0.0274 (0.0298) time: 3.3053 data: 0.0118 max mem: 33369 +Epoch: [39] [ 490/1319] eta: 0:46:54 lr: 1.1888388782538434e-06 loss: 0.0264 (0.0297) time: 3.5536 data: 0.0110 max mem: 33369 +Epoch: [39] [ 500/1319] eta: 0:46:17 lr: 1.175908878519789e-06 loss: 0.0269 (0.0296) time: 3.5119 data: 0.0100 max mem: 33369 +Epoch: [39] [ 510/1319] eta: 0:45:43 lr: 1.1629630618603247e-06 loss: 0.0277 (0.0296) time: 3.3008 data: 0.0110 max mem: 33369 +Epoch: [39] [ 520/1319] eta: 0:45:08 lr: 1.150001212801783e-06 loss: 0.0276 (0.0296) time: 3.3412 data: 0.0121 max mem: 33369 +Epoch: [39] [ 530/1319] eta: 0:44:35 lr: 1.1370231101961411e-06 loss: 0.0271 (0.0296) time: 3.3972 data: 0.0114 max mem: 33369 +Epoch: [39] [ 540/1319] eta: 0:44:00 lr: 1.1240285269976361e-06 loss: 0.0280 (0.0297) time: 3.3761 data: 0.0105 max mem: 33369 +Epoch: [39] [ 550/1319] eta: 0:43:25 lr: 1.1110172300275867e-06 loss: 0.0290 (0.0297) time: 3.2876 data: 0.0097 max mem: 33369 +Epoch: [39] [ 560/1319] eta: 0:42:52 lr: 1.097988979726662e-06 loss: 0.0295 (0.0297) time: 3.3881 data: 0.0090 max mem: 33369 +Epoch: [39] [ 570/1319] eta: 0:42:17 lr: 1.084943529893699e-06 loss: 0.0284 (0.0297) time: 3.3956 data: 0.0085 max mem: 33369 +Epoch: [39] [ 580/1319] eta: 0:41:42 lr: 1.0718806274102695e-06 loss: 0.0258 (0.0296) time: 3.3196 data: 0.0086 max mem: 33369 +Epoch: [39] [ 590/1319] eta: 0:41:08 lr: 1.0588000119498569e-06 loss: 0.0258 (0.0296) time: 3.3560 data: 0.0093 max mem: 33369 +Epoch: [39] [ 600/1319] eta: 0:40:35 lr: 1.0457014156706775e-06 loss: 0.0260 (0.0296) time: 3.3814 data: 0.0103 max mem: 33369 +Epoch: [39] [ 610/1319] eta: 0:39:59 lr: 1.032584562890946e-06 loss: 0.0256 (0.0296) time: 3.3294 data: 0.0117 max mem: 33369 +Epoch: [39] [ 620/1319] eta: 0:39:25 lr: 1.0194491697452832e-06 loss: 0.0305 (0.0297) time: 3.2996 data: 0.0119 max mem: 33369 +Epoch: [39] [ 630/1319] eta: 0:38:52 lr: 1.0062949438209979e-06 loss: 0.0288 (0.0297) time: 3.3793 data: 0.0116 max mem: 33369 +Epoch: [39] [ 640/1319] eta: 0:38:18 lr: 9.931215837725994e-07 loss: 0.0271 (0.0297) time: 3.3994 data: 0.0114 max mem: 33369 +Epoch: [39] [ 650/1319] eta: 0:37:43 lr: 9.799287789130144e-07 loss: 0.0279 (0.0297) time: 3.3280 data: 0.0111 max mem: 33369 +Epoch: [39] [ 660/1319] eta: 0:37:09 lr: 9.667162087796925e-07 loss: 0.0282 (0.0297) time: 3.3533 data: 0.0097 max mem: 33369 +Epoch: [39] [ 670/1319] eta: 0:36:36 lr: 9.534835426736097e-07 loss: 0.0290 (0.0297) time: 3.4435 data: 0.0094 max mem: 33369 +Epoch: [39] [ 680/1319] eta: 0:36:02 lr: 9.402304391691554e-07 loss: 0.0290 (0.0297) time: 3.3992 data: 0.0095 max mem: 33369 +Epoch: [39] [ 690/1319] eta: 0:35:27 lr: 9.269565455924141e-07 loss: 0.0259 (0.0297) time: 3.3255 data: 0.0089 max mem: 33369 +Epoch: [39] [ 700/1319] eta: 0:34:55 lr: 9.136614974653884e-07 loss: 0.0301 (0.0298) time: 3.4446 data: 0.0094 max mem: 33369 +Epoch: [39] [ 710/1319] eta: 0:34:21 lr: 9.003449179133091e-07 loss: 0.0298 (0.0298) time: 3.4810 data: 0.0095 max mem: 33369 +Epoch: [39] [ 720/1319] eta: 0:33:47 lr: 8.870064170319405e-07 loss: 0.0274 (0.0297) time: 3.3646 data: 0.0098 max mem: 33369 +Epoch: [39] [ 730/1319] eta: 0:33:13 lr: 8.736455912114245e-07 loss: 0.0263 (0.0297) time: 3.3380 data: 0.0096 max mem: 33369 +Epoch: [39] [ 740/1319] eta: 0:32:39 lr: 8.602620224130043e-07 loss: 0.0290 (0.0298) time: 3.3614 data: 0.0091 max mem: 33369 +Epoch: [39] [ 750/1319] eta: 0:32:05 lr: 8.468552773943076e-07 loss: 0.0319 (0.0298) time: 3.3419 data: 0.0089 max mem: 33369 +Epoch: [39] [ 760/1319] eta: 0:31:30 lr: 8.334249068786857e-07 loss: 0.0262 (0.0297) time: 3.3177 data: 0.0093 max mem: 33369 +Epoch: [39] [ 770/1319] eta: 0:30:58 lr: 8.199704446634483e-07 loss: 0.0262 (0.0297) time: 3.4289 data: 0.0100 max mem: 33369 +Epoch: [39] [ 780/1319] eta: 0:30:23 lr: 8.064914066612595e-07 loss: 0.0281 (0.0297) time: 3.3970 data: 0.0106 max mem: 33369 +Epoch: [39] [ 790/1319] eta: 0:29:48 lr: 7.92987289868475e-07 loss: 0.0304 (0.0297) time: 3.2706 data: 0.0110 max mem: 33369 +Epoch: [39] [ 800/1319] eta: 0:29:14 lr: 7.79457571253187e-07 loss: 0.0311 (0.0298) time: 3.2848 data: 0.0102 max mem: 33369 +Epoch: [39] [ 810/1319] eta: 0:28:40 lr: 7.659017065551902e-07 loss: 0.0321 (0.0298) time: 3.3579 data: 0.0109 max mem: 33369 +Epoch: [39] [ 820/1319] eta: 0:28:06 lr: 7.523191289889679e-07 loss: 0.0312 (0.0298) time: 3.3670 data: 0.0112 max mem: 33369 +Epoch: [39] [ 830/1319] eta: 0:27:32 lr: 7.387092478397154e-07 loss: 0.0279 (0.0298) time: 3.3102 data: 0.0109 max mem: 33369 +Epoch: [39] [ 840/1319] eta: 0:27:00 lr: 7.250714469413284e-07 loss: 0.0281 (0.0298) time: 3.4560 data: 0.0110 max mem: 33369 +Epoch: [39] [ 850/1319] eta: 0:26:26 lr: 7.114050830235778e-07 loss: 0.0281 (0.0298) time: 3.5391 data: 0.0101 max mem: 33369 +Epoch: [39] [ 860/1319] eta: 0:25:52 lr: 6.977094839143229e-07 loss: 0.0274 (0.0298) time: 3.4000 data: 0.0097 max mem: 33369 +Epoch: [39] [ 870/1319] eta: 0:25:18 lr: 6.839839465805414e-07 loss: 0.0274 (0.0298) time: 3.3144 data: 0.0096 max mem: 33369 +Epoch: [39] [ 880/1319] eta: 0:24:45 lr: 6.702277349898191e-07 loss: 0.0271 (0.0298) time: 3.3918 data: 0.0095 max mem: 33369 +Epoch: [39] [ 890/1319] eta: 0:24:10 lr: 6.564400777713066e-07 loss: 0.0293 (0.0298) time: 3.3665 data: 0.0102 max mem: 33369 +Epoch: [39] [ 900/1319] eta: 0:23:36 lr: 6.426201656523381e-07 loss: 0.0312 (0.0299) time: 3.3035 data: 0.0111 max mem: 33369 +Epoch: [39] [ 910/1319] eta: 0:23:02 lr: 6.287671486431178e-07 loss: 0.0306 (0.0299) time: 3.3377 data: 0.0113 max mem: 33369 +Epoch: [39] [ 920/1319] eta: 0:22:28 lr: 6.148801329380617e-07 loss: 0.0293 (0.0299) time: 3.3351 data: 0.0101 max mem: 33369 +Epoch: [39] [ 930/1319] eta: 0:21:54 lr: 6.009581774973726e-07 loss: 0.0270 (0.0299) time: 3.3233 data: 0.0101 max mem: 33369 +Epoch: [39] [ 940/1319] eta: 0:21:20 lr: 5.870002902666957e-07 loss: 0.0277 (0.0299) time: 3.3240 data: 0.0113 max mem: 33369 +Epoch: [39] [ 950/1319] eta: 0:20:46 lr: 5.7300542398606e-07 loss: 0.0277 (0.0299) time: 3.3835 data: 0.0109 max mem: 33369 +Epoch: [39] [ 960/1319] eta: 0:20:12 lr: 5.589724715308914e-07 loss: 0.0273 (0.0299) time: 3.3603 data: 0.0094 max mem: 33369 +Epoch: [39] [ 970/1319] eta: 0:19:38 lr: 5.449002607184345e-07 loss: 0.0266 (0.0298) time: 3.3147 data: 0.0100 max mem: 33369 +Epoch: [39] [ 980/1319] eta: 0:19:04 lr: 5.307875485010082e-07 loss: 0.0266 (0.0298) time: 3.3394 data: 0.0106 max mem: 33369 +Epoch: [39] [ 990/1319] eta: 0:18:31 lr: 5.166330144533874e-07 loss: 0.0293 (0.0298) time: 3.3646 data: 0.0100 max mem: 33369 +Epoch: [39] [1000/1319] eta: 0:17:57 lr: 5.024352534442401e-07 loss: 0.0303 (0.0298) time: 3.3437 data: 0.0098 max mem: 33369 +Epoch: [39] [1010/1319] eta: 0:17:23 lr: 4.881927673605746e-07 loss: 0.0302 (0.0298) time: 3.3014 data: 0.0094 max mem: 33369 +Epoch: [39] [1020/1319] eta: 0:16:49 lr: 4.7390395572780197e-07 loss: 0.0268 (0.0298) time: 3.3313 data: 0.0089 max mem: 33369 +Epoch: [39] [1030/1319] eta: 0:16:15 lr: 4.595671050360423e-07 loss: 0.0268 (0.0298) time: 3.3784 data: 0.0087 max mem: 33369 +Epoch: [39] [1040/1319] eta: 0:15:41 lr: 4.4518037654287396e-07 loss: 0.0277 (0.0298) time: 3.3491 data: 0.0102 max mem: 33369 +Epoch: [39] [1050/1319] eta: 0:15:08 lr: 4.3074179227215756e-07 loss: 0.0269 (0.0298) time: 3.3491 data: 0.0114 max mem: 33369 +Epoch: [39] [1060/1319] eta: 0:14:34 lr: 4.162492188647174e-07 loss: 0.0273 (0.0298) time: 3.4303 data: 0.0114 max mem: 33369 +Epoch: [39] [1070/1319] eta: 0:14:00 lr: 4.01700348854669e-07 loss: 0.0269 (0.0298) time: 3.3967 data: 0.0107 max mem: 33369 +Epoch: [39] [1080/1319] eta: 0:13:26 lr: 3.8709267884030336e-07 loss: 0.0264 (0.0297) time: 3.3128 data: 0.0107 max mem: 33369 +Epoch: [39] [1090/1319] eta: 0:12:52 lr: 3.724234838815835e-07 loss: 0.0262 (0.0298) time: 3.3441 data: 0.0102 max mem: 33369 +Epoch: [39] [1100/1319] eta: 0:12:19 lr: 3.5768978727688177e-07 loss: 0.0291 (0.0298) time: 3.3311 data: 0.0089 max mem: 33369 +Epoch: [39] [1110/1319] eta: 0:11:45 lr: 3.428883246336122e-07 loss: 0.0266 (0.0297) time: 3.2796 data: 0.0093 max mem: 33369 +Epoch: [39] [1120/1319] eta: 0:11:11 lr: 3.280155008272766e-07 loss: 0.0256 (0.0297) time: 3.3742 data: 0.0098 max mem: 33369 +Epoch: [39] [1130/1319] eta: 0:10:37 lr: 3.1306733800860497e-07 loss: 0.0268 (0.0297) time: 3.4153 data: 0.0089 max mem: 33369 +Epoch: [39] [1140/1319] eta: 0:10:03 lr: 2.9803941221786203e-07 loss: 0.0264 (0.0297) time: 3.3324 data: 0.0100 max mem: 33369 +Epoch: [39] [1150/1319] eta: 0:09:30 lr: 2.829267753240405e-07 loss: 0.0263 (0.0298) time: 3.3198 data: 0.0134 max mem: 33369 +Epoch: [39] [1160/1319] eta: 0:08:56 lr: 2.677238578071334e-07 loss: 0.0287 (0.0298) time: 3.4081 data: 0.0128 max mem: 33369 +Epoch: [39] [1170/1319] eta: 0:08:22 lr: 2.524243461593822e-07 loss: 0.0282 (0.0297) time: 3.4130 data: 0.0100 max mem: 33369 +Epoch: [39] [1180/1319] eta: 0:07:48 lr: 2.370210260957732e-07 loss: 0.0271 (0.0297) time: 3.3120 data: 0.0106 max mem: 33369 +Epoch: [39] [1190/1319] eta: 0:07:15 lr: 2.2150557883672493e-07 loss: 0.0271 (0.0297) time: 3.3100 data: 0.0111 max mem: 33369 +Epoch: [39] [1200/1319] eta: 0:06:41 lr: 2.058683115970694e-07 loss: 0.0279 (0.0297) time: 3.3639 data: 0.0098 max mem: 33369 +Epoch: [39] [1210/1319] eta: 0:06:07 lr: 1.9009779355624344e-07 loss: 0.0268 (0.0297) time: 3.3389 data: 0.0097 max mem: 33369 +Epoch: [39] [1220/1319] eta: 0:05:33 lr: 1.7418035215766808e-07 loss: 0.0268 (0.0297) time: 3.3070 data: 0.0100 max mem: 33369 +Epoch: [39] [1230/1319] eta: 0:05:00 lr: 1.5809935607220197e-07 loss: 0.0270 (0.0296) time: 3.4212 data: 0.0100 max mem: 33369 +Epoch: [39] [1240/1319] eta: 0:04:26 lr: 1.4183415922236583e-07 loss: 0.0288 (0.0297) time: 3.4594 data: 0.0102 max mem: 33369 +Epoch: [39] [1250/1319] eta: 0:03:52 lr: 1.2535848000328487e-07 loss: 0.0298 (0.0296) time: 3.3670 data: 0.0096 max mem: 33369 +Epoch: [39] [1260/1319] eta: 0:03:18 lr: 1.0863778202227116e-07 loss: 0.0287 (0.0296) time: 3.3308 data: 0.0100 max mem: 33369 +Epoch: [39] [1270/1319] eta: 0:02:45 lr: 9.162475150165058e-08 loss: 0.0296 (0.0296) time: 3.4950 data: 0.0112 max mem: 33369 +Epoch: [39] [1280/1319] eta: 0:02:11 lr: 7.425076510067331e-08 loss: 0.0293 (0.0297) time: 3.4678 data: 0.0100 max mem: 33369 +Epoch: [39] [1290/1319] eta: 0:01:37 lr: 5.640763927216541e-08 loss: 0.0284 (0.0297) time: 3.3067 data: 0.0097 max mem: 33369 +Epoch: [39] [1300/1319] eta: 0:01:04 lr: 3.790015191412361e-08 loss: 0.0278 (0.0297) time: 3.4305 data: 0.0102 max mem: 33369 +Epoch: [39] [1310/1319] eta: 0:00:30 lr: 1.8267397722216235e-08 loss: 0.0263 (0.0297) time: 3.4189 data: 0.0088 max mem: 33369 +Epoch: [39] Total time: 1:14:12 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 2:26:12 time: 3.4094 data: 3.2995 max mem: 33369 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 100/2573] eta: 0:04:50 time: 0.0805 data: 0.0018 max mem: 33369 +Test: [ 200/2573] eta: 0:03:56 time: 0.0797 data: 0.0016 max mem: 33369 +Test: [ 300/2573] eta: 0:03:30 time: 0.0809 data: 0.0016 max mem: 33369 +Test: [ 400/2573] eta: 0:03:14 time: 0.0842 data: 0.0017 max mem: 33369 +Test: [ 500/2573] eta: 0:03:02 time: 0.0822 data: 0.0020 max mem: 33369 +Test: [ 600/2573] eta: 0:02:51 time: 0.0809 data: 0.0015 max mem: 33369 +Test: [ 700/2573] eta: 0:02:42 time: 0.0871 data: 0.0022 max mem: 33369 +Test: [ 800/2573] eta: 0:02:32 time: 0.0841 data: 0.0015 max mem: 33369 +Test: [ 900/2573] eta: 0:02:23 time: 0.0806 data: 0.0017 max mem: 33369 +Test: [1000/2573] eta: 0:02:14 time: 0.0841 data: 0.0017 max mem: 33369 +Test: [1100/2573] eta: 0:02:05 time: 0.0825 data: 0.0018 max mem: 33369 +Test: [1200/2573] eta: 0:01:56 time: 0.0833 data: 0.0016 max mem: 33369 +Test: [1300/2573] eta: 0:01:47 time: 0.0814 data: 0.0015 max mem: 33369 +Test: [1400/2573] eta: 0:01:39 time: 0.0814 data: 0.0017 max mem: 33369 +Test: [1500/2573] eta: 0:01:30 time: 0.0833 data: 0.0018 max mem: 33369 +Test: [1600/2573] eta: 0:01:22 time: 0.0858 data: 0.0017 max mem: 33369 +Test: [1700/2573] eta: 0:01:13 time: 0.0802 data: 0.0016 max mem: 33369 +Test: [1800/2573] eta: 0:01:04 time: 0.0855 data: 0.0019 max mem: 33369 +Test: [1900/2573] eta: 0:00:56 time: 0.0801 data: 0.0016 max mem: 33369 +Test: [2000/2573] eta: 0:00:48 time: 0.0810 data: 0.0016 max mem: 33369 +Test: [2100/2573] eta: 0:00:39 time: 0.0847 data: 0.0017 max mem: 33369 +Test: [2200/2573] eta: 0:00:31 time: 0.0837 data: 0.0017 max mem: 33369 +Test: [2300/2573] eta: 0:00:22 time: 0.0824 data: 0.0016 max mem: 33369 +Test: [2400/2573] eta: 0:00:14 time: 0.0791 data: 0.0015 max mem: 33369 +Test: [2500/2573] eta: 0:00:06 time: 0.0828 data: 0.0014 max mem: 33369 +Test: Total time: 0:03:35 +Final results: +Mean IoU is 65.38 + + precision@0.5 = 73.82 + precision@0.6 = 68.10 + precision@0.7 = 61.29 + precision@0.8 = 49.90 + precision@0.9 = 25.35 + overall IoU = 62.87 + +Average object IoU 65.37900547872243 +Overall IoU 62.871002197265625 +Training time 2 days, 2:42:32 diff --git a/LAVT-RIS/logs/old/gref_m10_mg10_tmp010_4gpu_bs16_ang.log b/LAVT-RIS/logs/old/gref_m10_mg10_tmp010_4gpu_bs16_ang.log new file mode 100644 index 0000000000000000000000000000000000000000..12ed9cf08eded4ff486b3f6fcb649e1d2bee0ed8 --- /dev/null +++ b/LAVT-RIS/logs/old/gref_m10_mg10_tmp010_4gpu_bs16_ang.log @@ -0,0 +1,14811 @@ +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torch/distributed/launch.py:178: FutureWarning: The module torch.distributed.launch is deprecated +and will be removed in future. Use torchrun. +Note that --use_env is set by default in torchrun. +If your script expects `--local_rank` argument to be set, please +change it to read from `os.environ['LOCAL_RANK']` instead. See +https://pytorch.org/docs/stable/distributed.html#launch-utility for +further instructions + + warnings.warn( +WARNING:torch.distributed.run: +***************************************** +Setting OMP_NUM_THREADS environment variable for each process to be 1 in default, to avoid your system being overloaded, please further tune the variable for optimal performance in your application as needed. +***************************************** +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/timm/models/layers/__init__.py:48: FutureWarning: Importing from timm.models.layers is deprecated, please import via timm.layers + warnings.warn(f"Importing from {__name__} is deprecated, please import via timm.layers", FutureWarning) +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/timm/models/layers/__init__.py:48: FutureWarning: Importing from timm.models.layers is deprecated, please import via timm.layers + warnings.warn(f"Importing from {__name__} is deprecated, please import via timm.layers", FutureWarning) +RANK and WORLD_SIZE in environment: 1/2RANK and WORLD_SIZE in environment: 0/2 + +Image size: 480 +loading dataset refcocog into memory... +creating index... +index created. +DONE (t=6.84s) +loading dataset refcocog into memory... +creating index... +index created. +DONE (t=6.67s) +local rank 0 / global rank 0 successfully built train dataset. +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torch/utils/data/dataloader.py:557: UserWarning: This DataLoader will create 8 worker processes in total. Our suggested max number of worker in current system is 6, which is smaller than what this DataLoader is going to create. Please be aware that excessive worker creation might get DataLoader running slow or even freeze, lower the worker number to avoid potential slowness/freeze if necessary. + warnings.warn(_create_warning_msg( +lavt_one +Window size 12! +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torch/functional.py:478: UserWarning: torch.meshgrid: in an upcoming release, it will be required to pass the indexing argument. (Triggered internally at ../aten/src/ATen/native/TensorShape.cpp:2894.) + return _VF.meshgrid(tensors, **kwargs) # type: ignore[attr-defined] +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torch/utils/data/dataloader.py:557: UserWarning: This DataLoader will create 8 worker processes in total. Our suggested max number of worker in current system is 6, which is smaller than what this DataLoader is going to create. Please be aware that excessive worker creation might get DataLoader running slow or even freeze, lower the worker number to avoid potential slowness/freeze if necessary. + warnings.warn(_create_warning_msg( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torch/functional.py:478: UserWarning: torch.meshgrid: in an upcoming release, it will be required to pass the indexing argument. (Triggered internally at ../aten/src/ATen/native/TensorShape.cpp:2894.) + return _VF.meshgrid(tensors, **kwargs) # type: ignore[attr-defined] +Initializing Multi-modal Swin Transformer weights from ./pretrained_weights/swin_base_patch4_window12_384_22k.pth +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [0] [ 0/2639] eta: 7:03:13 lr: 4.999957370195798e-05 loss: 0.7789 (0.7789) time: 9.6225 data: 3.3390 max mem: 22605 +Epoch: [0] [ 10/2639] eta: 2:39:31 lr: 4.99953106993255e-05 loss: 0.4791 (0.4919) time: 3.6409 data: 0.3101 max mem: 28325 +Epoch: [0] [ 20/2639] eta: 2:25:50 lr: 4.999104765630397e-05 loss: 0.3300 (0.4049) time: 3.0271 data: 0.0068 max mem: 28325 +Epoch: [0] [ 30/2639] eta: 2:20:34 lr: 4.998678457288919e-05 loss: 0.3025 (0.3753) time: 3.0083 data: 0.0075 max mem: 30031 +Epoch: [0] [ 40/2639] eta: 2:17:52 lr: 4.998252144907695e-05 loss: 0.2935 (0.3538) time: 3.0166 data: 0.0081 max mem: 30031 +Epoch: [0] [ 50/2639] eta: 2:15:54 lr: 4.9978258284863036e-05 loss: 0.2844 (0.3413) time: 3.0205 data: 0.0076 max mem: 30031 +Epoch: [0] [ 60/2639] eta: 2:15:00 lr: 4.997399508024324e-05 loss: 0.2832 (0.3324) time: 3.0548 data: 0.0076 max mem: 30032 +Epoch: [0] [ 70/2639] eta: 2:13:33 lr: 4.996973183521335e-05 loss: 0.2836 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3.0454 data: 0.0071 max mem: 31715 +Epoch: [0] [ 790/2639] eta: 1:33:43 lr: 4.966267172119903e-05 loss: 0.2177 (0.2574) time: 3.0443 data: 0.0076 max mem: 31715 +Epoch: [0] [ 800/2639] eta: 1:33:14 lr: 4.965840551479581e-05 loss: 0.2534 (0.2573) time: 3.0356 data: 0.0077 max mem: 31715 +Epoch: [0] [ 810/2639] eta: 1:32:42 lr: 4.965413926766839e-05 loss: 0.2327 (0.2571) time: 3.0459 data: 0.0075 max mem: 31715 +Epoch: [0] [ 820/2639] eta: 1:32:12 lr: 4.96498729798125e-05 loss: 0.2224 (0.2569) time: 3.0151 data: 0.0074 max mem: 31715 +Epoch: [0] [ 830/2639] eta: 1:31:40 lr: 4.964560665122384e-05 loss: 0.2485 (0.2567) time: 3.0003 data: 0.0072 max mem: 31715 +Epoch: [0] [ 840/2639] eta: 1:31:10 lr: 4.964134028189815e-05 loss: 0.2201 (0.2565) time: 3.0251 data: 0.0074 max mem: 31715 +Epoch: [0] [ 850/2639] eta: 1:30:39 lr: 4.9637073871831144e-05 loss: 0.2190 (0.2569) time: 3.0525 data: 0.0081 max mem: 31715 +Epoch: [0] [ 860/2639] eta: 1:30:09 lr: 4.963280742101855e-05 loss: 0.2190 (0.2566) time: 3.0283 data: 0.0084 max mem: 31715 +Epoch: [0] [ 870/2639] eta: 1:29:38 lr: 4.9628540929456074e-05 loss: 0.2172 (0.2564) time: 3.0182 data: 0.0085 max mem: 31715 +Epoch: [0] [ 880/2639] eta: 1:29:07 lr: 4.962427439713945e-05 loss: 0.2191 (0.2565) time: 3.0165 data: 0.0087 max mem: 31715 +Epoch: [0] [ 890/2639] eta: 1:28:38 lr: 4.962000782406438e-05 loss: 0.2266 (0.2564) time: 3.0628 data: 0.0083 max mem: 31715 +Epoch: [0] [ 900/2639] eta: 1:28:07 lr: 4.961574121022658e-05 loss: 0.2256 (0.2559) time: 3.0622 data: 0.0079 max mem: 31715 +Epoch: [0] [ 910/2639] eta: 1:27:36 lr: 4.961147455562178e-05 loss: 0.2114 (0.2555) time: 3.0130 data: 0.0077 max mem: 31715 +Epoch: [0] [ 920/2639] eta: 1:27:05 lr: 4.9607207860245686e-05 loss: 0.2114 (0.2551) time: 3.0073 data: 0.0075 max mem: 31716 +Epoch: [0] [ 930/2639] eta: 1:26:37 lr: 4.960294112409401e-05 loss: 0.2192 (0.2547) time: 3.0979 data: 0.0078 max mem: 31716 +Epoch: [0] [ 940/2639] eta: 1:26:06 lr: 4.9598674347162476e-05 loss: 0.2021 (0.2541) time: 3.0878 data: 0.0081 max mem: 31716 +Epoch: [0] [ 950/2639] eta: 1:25:35 lr: 4.9594407529446787e-05 loss: 0.2021 (0.2537) time: 3.0132 data: 0.0075 max mem: 31716 +Epoch: [0] [ 960/2639] eta: 1:25:05 lr: 4.959014067094265e-05 loss: 0.2111 (0.2536) time: 3.0269 data: 0.0078 max mem: 31716 +Epoch: [0] [ 970/2639] eta: 1:24:34 lr: 4.9585873771645784e-05 loss: 0.2111 (0.2531) time: 3.0193 data: 0.0078 max mem: 31716 +Epoch: [0] [ 980/2639] eta: 1:24:05 lr: 4.95816068315519e-05 loss: 0.2203 (0.2528) time: 3.0694 data: 0.0075 max mem: 31716 +Epoch: [0] [ 990/2639] eta: 1:23:33 lr: 4.95773398506567e-05 loss: 0.2299 (0.2526) time: 3.0439 data: 0.0080 max mem: 31716 +Epoch: [0] [1000/2639] eta: 1:23:03 lr: 4.9573072828955893e-05 loss: 0.2225 (0.2522) time: 3.0209 data: 0.0081 max mem: 31716 +Epoch: [0] [1010/2639] eta: 1:22:32 lr: 4.9568805766445195e-05 loss: 0.2082 (0.2518) time: 3.0223 data: 0.0079 max mem: 31716 +Epoch: [0] [1020/2639] eta: 1:22:03 lr: 4.95645386631203e-05 loss: 0.2021 (0.2517) time: 3.0561 data: 0.0078 max mem: 31716 +Epoch: [0] [1030/2639] eta: 1:21:31 lr: 4.9560271518976925e-05 loss: 0.1990 (0.2524) time: 3.0424 data: 0.0079 max mem: 31716 +Epoch: [0] [1040/2639] eta: 1:21:00 lr: 4.9556004334010755e-05 loss: 0.2326 (0.2525) time: 2.9828 data: 0.0077 max mem: 31716 +Epoch: [0] [1050/2639] eta: 1:20:29 lr: 4.955173710821752e-05 loss: 0.2410 (0.2523) time: 2.9939 data: 0.0076 max mem: 31716 +Epoch: [0] [1060/2639] eta: 1:19:58 lr: 4.95474698415929e-05 loss: 0.2128 (0.2518) time: 2.9934 data: 0.0076 max mem: 31716 +Epoch: [0] [1070/2639] eta: 1:19:28 lr: 4.9543202534132616e-05 loss: 0.2004 (0.2515) time: 3.0281 data: 0.0073 max mem: 31716 +Epoch: [0] [1080/2639] eta: 1:18:57 lr: 4.953893518583235e-05 loss: 0.2075 (0.2511) time: 3.0362 data: 0.0078 max mem: 31716 +Epoch: [0] [1090/2639] eta: 1:18:27 lr: 4.9534667796687825e-05 loss: 0.1922 (0.2511) time: 3.0417 data: 0.0077 max mem: 31716 +Epoch: [0] [1100/2639] eta: 1:17:57 lr: 4.9530400366694714e-05 loss: 0.1946 (0.2508) time: 3.0410 data: 0.0072 max mem: 31716 +Epoch: [0] [1110/2639] eta: 1:17:26 lr: 4.952613289584874e-05 loss: 0.1989 (0.2504) time: 3.0367 data: 0.0073 max mem: 31716 +Epoch: [0] [1120/2639] eta: 1:16:55 lr: 4.952186538414557e-05 loss: 0.1989 (0.2504) time: 3.0202 data: 0.0077 max mem: 31716 +Epoch: [0] [1130/2639] eta: 1:16:26 lr: 4.951759783158094e-05 loss: 0.2068 (0.2504) time: 3.0642 data: 0.0077 max mem: 31716 +Epoch: [0] [1140/2639] eta: 1:15:55 lr: 4.951333023815051e-05 loss: 0.2068 (0.2501) time: 3.0518 data: 0.0076 max mem: 31716 +Epoch: [0] [1150/2639] eta: 1:15:25 lr: 4.9509062603850004e-05 loss: 0.2029 (0.2497) time: 3.0401 data: 0.0076 max mem: 31716 +Epoch: [0] [1160/2639] eta: 1:14:55 lr: 4.950479492867509e-05 loss: 0.2029 (0.2496) time: 3.0587 data: 0.0080 max mem: 31716 +Epoch: [0] [1170/2639] eta: 1:14:25 lr: 4.9500527212621484e-05 loss: 0.2088 (0.2494) time: 3.0417 data: 0.0083 max mem: 31716 +Epoch: [0] [1180/2639] eta: 1:13:54 lr: 4.9496259455684864e-05 loss: 0.2182 (0.2492) time: 3.0336 data: 0.0080 max mem: 31716 +Epoch: [0] [1190/2639] eta: 1:13:23 lr: 4.949199165786093e-05 loss: 0.2163 (0.2489) time: 3.0106 data: 0.0078 max mem: 31716 +Epoch: [0] [1200/2639] eta: 1:12:53 lr: 4.9487723819145357e-05 loss: 0.2091 (0.2488) time: 3.0243 data: 0.0074 max mem: 31716 +Epoch: [0] [1210/2639] eta: 1:12:22 lr: 4.9483455939533856e-05 loss: 0.2259 (0.2486) time: 3.0326 data: 0.0072 max mem: 31716 +Epoch: [0] [1220/2639] eta: 1:11:51 lr: 4.94791880190221e-05 loss: 0.2267 (0.2486) time: 3.0018 data: 0.0078 max mem: 31716 +Epoch: [0] [1230/2639] eta: 1:11:21 lr: 4.947492005760579e-05 loss: 0.2282 (0.2485) time: 3.0256 data: 0.0080 max mem: 31716 +Epoch: [0] [1240/2639] eta: 1:10:50 lr: 4.9470652055280605e-05 loss: 0.2201 (0.2484) time: 3.0480 data: 0.0075 max mem: 31716 +Epoch: [0] [1250/2639] eta: 1:10:21 lr: 4.946638401204223e-05 loss: 0.2257 (0.2485) time: 3.0565 data: 0.0075 max mem: 31717 +Epoch: [0] [1260/2639] eta: 1:09:50 lr: 4.946211592788635e-05 loss: 0.2176 (0.2481) time: 3.0516 data: 0.0078 max mem: 31717 +Epoch: [0] [1270/2639] eta: 1:09:20 lr: 4.945784780280866e-05 loss: 0.1928 (0.2477) time: 3.0277 data: 0.0079 max mem: 31717 +Epoch: [0] [1280/2639] eta: 1:08:50 lr: 4.945357963680484e-05 loss: 0.2042 (0.2478) time: 3.0723 data: 0.0076 max mem: 31717 +Epoch: [0] [1290/2639] eta: 1:08:19 lr: 4.9449311429870553e-05 loss: 0.2113 (0.2475) time: 3.0640 data: 0.0075 max mem: 31717 +Epoch: [0] [1300/2639] eta: 1:07:49 lr: 4.944504318200151e-05 loss: 0.2100 (0.2472) time: 3.0609 data: 0.0075 max mem: 31717 +Epoch: [0] [1310/2639] eta: 1:07:19 lr: 4.9440774893193375e-05 loss: 0.2115 (0.2471) time: 3.0448 data: 0.0075 max mem: 31717 +Epoch: [0] [1320/2639] eta: 1:06:48 lr: 4.9436506563441834e-05 loss: 0.2033 (0.2469) time: 2.9844 data: 0.0077 max mem: 31717 +Epoch: [0] [1330/2639] eta: 1:06:17 lr: 4.9432238192742565e-05 loss: 0.2254 (0.2469) time: 2.9767 data: 0.0077 max mem: 31717 +Epoch: [0] [1340/2639] eta: 1:05:46 lr: 4.9427969781091246e-05 loss: 0.2254 (0.2467) time: 2.9853 data: 0.0076 max mem: 31717 +Epoch: [0] [1350/2639] eta: 1:05:15 lr: 4.942370132848356e-05 loss: 0.1997 (0.2463) time: 2.9740 data: 0.0077 max mem: 31717 +Epoch: [0] [1360/2639] eta: 1:04:43 lr: 4.941943283491517e-05 loss: 0.2060 (0.2461) time: 2.9532 data: 0.0081 max mem: 31717 +Epoch: [0] [1370/2639] eta: 1:04:12 lr: 4.941516430038176e-05 loss: 0.2135 (0.2459) time: 2.9369 data: 0.0082 max mem: 31717 +Epoch: [0] [1380/2639] eta: 1:03:41 lr: 4.941089572487902e-05 loss: 0.2252 (0.2458) time: 2.9331 data: 0.0081 max mem: 31717 +Epoch: [0] [1390/2639] eta: 1:03:10 lr: 4.9406627108402595e-05 loss: 0.2252 (0.2457) time: 2.9746 data: 0.0080 max mem: 31717 +Epoch: [0] [1400/2639] eta: 1:02:40 lr: 4.9402358450948176e-05 loss: 0.2090 (0.2454) time: 3.0240 data: 0.0079 max mem: 31717 +Epoch: [0] [1410/2639] eta: 1:02:10 lr: 4.939808975251144e-05 loss: 0.2061 (0.2454) time: 3.0450 data: 0.0078 max mem: 31717 +Epoch: [0] [1420/2639] eta: 1:01:39 lr: 4.939382101308804e-05 loss: 0.2241 (0.2454) time: 3.0023 data: 0.0079 max mem: 31717 +Epoch: [0] [1430/2639] eta: 1:01:09 lr: 4.9389552232673656e-05 loss: 0.2227 (0.2452) time: 3.0106 data: 0.0083 max mem: 31717 +Epoch: [0] [1440/2639] eta: 1:00:38 lr: 4.938528341126397e-05 loss: 0.2131 (0.2448) time: 3.0662 data: 0.0079 max mem: 31717 +Epoch: [0] [1450/2639] eta: 1:00:08 lr: 4.9381014548854634e-05 loss: 0.2052 (0.2446) time: 3.0362 data: 0.0079 max mem: 31717 +Epoch: [0] [1460/2639] eta: 0:59:38 lr: 4.9376745645441316e-05 loss: 0.1967 (0.2442) time: 3.0291 data: 0.0082 max mem: 31717 +Epoch: [0] [1470/2639] eta: 0:59:07 lr: 4.93724767010197e-05 loss: 0.1902 (0.2442) time: 3.0211 data: 0.0081 max mem: 31717 +Epoch: [0] [1480/2639] eta: 0:58:37 lr: 4.936820771558544e-05 loss: 0.1902 (0.2439) time: 3.0460 data: 0.0079 max mem: 31717 +Epoch: [0] [1490/2639] eta: 0:58:07 lr: 4.93639386891342e-05 loss: 0.1887 (0.2436) time: 3.0585 data: 0.0081 max mem: 31717 +Epoch: [0] [1500/2639] eta: 0:57:37 lr: 4.9359669621661654e-05 loss: 0.1870 (0.2433) time: 3.0558 data: 0.0081 max mem: 31717 +Epoch: [0] [1510/2639] eta: 0:57:06 lr: 4.935540051316345e-05 loss: 0.1974 (0.2433) time: 3.0501 data: 0.0080 max mem: 31717 +Epoch: [0] [1520/2639] eta: 0:56:36 lr: 4.935113136363527e-05 loss: 0.2132 (0.2431) time: 3.0160 data: 0.0079 max mem: 31717 +Epoch: [0] [1530/2639] eta: 0:56:06 lr: 4.934686217307276e-05 loss: 0.2064 (0.2429) time: 3.0342 data: 0.0079 max mem: 31717 +Epoch: [0] [1540/2639] eta: 0:55:35 lr: 4.934259294147158e-05 loss: 0.2195 (0.2429) time: 3.0114 data: 0.0080 max mem: 31717 +Epoch: [0] [1550/2639] eta: 0:55:05 lr: 4.9338323668827404e-05 loss: 0.2239 (0.2429) time: 3.0323 data: 0.0077 max mem: 31717 +Epoch: [0] [1560/2639] eta: 0:54:34 lr: 4.933405435513589e-05 loss: 0.2110 (0.2427) time: 3.0329 data: 0.0081 max mem: 31717 +Epoch: [0] [1570/2639] eta: 0:54:03 lr: 4.932978500039269e-05 loss: 0.2017 (0.2426) time: 2.9924 data: 0.0083 max mem: 31717 +Epoch: [0] [1580/2639] eta: 0:53:33 lr: 4.932551560459345e-05 loss: 0.2013 (0.2423) time: 3.0081 data: 0.0081 max mem: 31717 +Epoch: [0] [1590/2639] eta: 0:53:03 lr: 4.9321246167733846e-05 loss: 0.1911 (0.2421) time: 3.0489 data: 0.0079 max mem: 31717 +Epoch: [0] [1600/2639] eta: 0:52:32 lr: 4.931697668980953e-05 loss: 0.1892 (0.2419) time: 3.0369 data: 0.0078 max mem: 31717 +Epoch: [0] [1610/2639] eta: 0:52:02 lr: 4.9312707170816146e-05 loss: 0.2109 (0.2417) time: 3.0143 data: 0.0077 max mem: 31717 +Epoch: [0] [1620/2639] eta: 0:51:31 lr: 4.930843761074936e-05 loss: 0.2008 (0.2415) time: 3.0142 data: 0.0074 max mem: 31717 +Epoch: [0] [1630/2639] eta: 0:51:01 lr: 4.9304168009604826e-05 loss: 0.1954 (0.2413) time: 3.0117 data: 0.0074 max mem: 31717 +Epoch: [0] [1640/2639] eta: 0:50:31 lr: 4.929989836737818e-05 loss: 0.1954 (0.2411) time: 3.0346 data: 0.0078 max mem: 31717 +Epoch: [0] [1650/2639] eta: 0:50:00 lr: 4.929562868406509e-05 loss: 0.1841 (0.2409) time: 3.0352 data: 0.0081 max mem: 31717 +Epoch: [0] [1660/2639] eta: 0:49:30 lr: 4.9291358959661196e-05 loss: 0.2164 (0.2409) time: 3.0091 data: 0.0082 max mem: 31717 +Epoch: [0] [1670/2639] eta: 0:48:59 lr: 4.928708919416216e-05 loss: 0.2161 (0.2407) time: 3.0130 data: 0.0080 max mem: 31717 +Epoch: [0] [1680/2639] eta: 0:48:29 lr: 4.928281938756362e-05 loss: 0.1936 (0.2405) time: 3.0187 data: 0.0076 max mem: 31717 +Epoch: [0] [1690/2639] eta: 0:47:59 lr: 4.9278549539861226e-05 loss: 0.1933 (0.2402) time: 3.0383 data: 0.0076 max mem: 31717 +Epoch: [0] [1700/2639] eta: 0:47:28 lr: 4.927427965105062e-05 loss: 0.1841 (0.2400) time: 3.0573 data: 0.0081 max mem: 31717 +Epoch: [0] [1710/2639] eta: 0:46:58 lr: 4.9270009721127455e-05 loss: 0.1951 (0.2398) time: 3.0149 data: 0.0082 max mem: 31717 +Epoch: [0] [1720/2639] eta: 0:46:27 lr: 4.926573975008739e-05 loss: 0.1962 (0.2396) time: 3.0031 data: 0.0081 max mem: 31717 +Epoch: [0] [1730/2639] eta: 0:45:57 lr: 4.9261469737926035e-05 loss: 0.1913 (0.2395) time: 3.0015 data: 0.0083 max mem: 31717 +Epoch: [0] [1740/2639] eta: 0:45:27 lr: 4.925719968463906e-05 loss: 0.1913 (0.2394) time: 3.0276 data: 0.0080 max mem: 31717 +Epoch: [0] [1750/2639] eta: 0:44:56 lr: 4.925292959022211e-05 loss: 0.2173 (0.2393) time: 3.0383 data: 0.0078 max mem: 31717 +Epoch: [0] [1760/2639] eta: 0:44:26 lr: 4.924865945467081e-05 loss: 0.1974 (0.2390) time: 3.0160 data: 0.0079 max mem: 31717 +Epoch: [0] [1770/2639] eta: 0:43:56 lr: 4.9244389277980806e-05 loss: 0.1873 (0.2388) time: 3.0324 data: 0.0080 max mem: 31717 +Epoch: [0] [1780/2639] eta: 0:43:25 lr: 4.9240119060147744e-05 loss: 0.1836 (0.2385) time: 3.0501 data: 0.0086 max mem: 31717 +Epoch: [0] [1790/2639] eta: 0:42:55 lr: 4.923584880116726e-05 loss: 0.1836 (0.2382) time: 3.0471 data: 0.0089 max mem: 31717 +Epoch: [0] [1800/2639] eta: 0:42:25 lr: 4.923157850103499e-05 loss: 0.1850 (0.2381) time: 3.0815 data: 0.0081 max mem: 31717 +Epoch: [0] [1810/2639] eta: 0:41:55 lr: 4.922730815974657e-05 loss: 0.1902 (0.2379) time: 3.0603 data: 0.0082 max mem: 31717 +Epoch: [0] [1820/2639] eta: 0:41:24 lr: 4.922303777729764e-05 loss: 0.1819 (0.2376) time: 3.0377 data: 0.0081 max mem: 31717 +Epoch: [0] [1830/2639] eta: 0:40:54 lr: 4.9218767353683825e-05 loss: 0.1851 (0.2375) time: 3.0375 data: 0.0075 max mem: 31717 +Epoch: [0] [1840/2639] eta: 0:40:24 lr: 4.921449688890078e-05 loss: 0.2099 (0.2373) time: 3.0462 data: 0.0073 max mem: 31717 +Epoch: [0] [1850/2639] eta: 0:39:54 lr: 4.921022638294413e-05 loss: 0.2019 (0.2371) time: 3.1032 data: 0.0074 max mem: 31717 +Epoch: [0] [1860/2639] eta: 0:39:23 lr: 4.9205955835809496e-05 loss: 0.1977 (0.2370) time: 3.0377 data: 0.0074 max mem: 31717 +Epoch: [0] [1870/2639] eta: 0:38:53 lr: 4.920168524749252e-05 loss: 0.2207 (0.2371) time: 2.9886 data: 0.0076 max mem: 31717 +Epoch: [0] [1880/2639] eta: 0:38:22 lr: 4.919741461798884e-05 loss: 0.2207 (0.2370) time: 2.9856 data: 0.0079 max mem: 31717 +Epoch: [0] [1890/2639] eta: 0:37:52 lr: 4.9193143947294075e-05 loss: 0.2096 (0.2370) time: 2.9660 data: 0.0081 max mem: 31717 +Epoch: [0] [1900/2639] eta: 0:37:21 lr: 4.9188873235403865e-05 loss: 0.2096 (0.2368) time: 3.0101 data: 0.0080 max mem: 31717 +Epoch: [0] [1910/2639] eta: 0:36:51 lr: 4.918460248231382e-05 loss: 0.1930 (0.2366) time: 3.0358 data: 0.0078 max mem: 31717 +Epoch: [0] [1920/2639] eta: 0:36:21 lr: 4.9180331688019586e-05 loss: 0.1734 (0.2362) time: 3.0503 data: 0.0081 max mem: 31717 +Epoch: [0] [1930/2639] eta: 0:35:50 lr: 4.917606085251678e-05 loss: 0.1750 (0.2360) time: 3.0193 data: 0.0080 max mem: 31717 +Epoch: [0] [1940/2639] eta: 0:35:20 lr: 4.917178997580103e-05 loss: 0.1888 (0.2359) time: 3.0135 data: 0.0077 max mem: 31717 +Epoch: [0] [1950/2639] eta: 0:34:49 lr: 4.916751905786797e-05 loss: 0.1787 (0.2357) time: 3.0017 data: 0.0074 max mem: 31717 +Epoch: [0] [1960/2639] eta: 0:34:19 lr: 4.916324809871321e-05 loss: 0.1787 (0.2355) time: 2.9829 data: 0.0075 max mem: 31717 +Epoch: [0] [1970/2639] eta: 0:33:48 lr: 4.915897709833237e-05 loss: 0.1863 (0.2352) time: 3.0122 data: 0.0075 max mem: 31717 +Epoch: [0] [1980/2639] eta: 0:33:18 lr: 4.915470605672109e-05 loss: 0.1903 (0.2351) time: 3.0244 data: 0.0075 max mem: 31717 +Epoch: [0] [1990/2639] eta: 0:32:48 lr: 4.915043497387498e-05 loss: 0.2043 (0.2349) time: 2.9895 data: 0.0075 max mem: 31717 +Epoch: [0] [2000/2639] eta: 0:32:17 lr: 4.914616384978966e-05 loss: 0.2068 (0.2349) time: 2.9787 data: 0.0079 max mem: 31717 +Epoch: [0] [2010/2639] eta: 0:31:47 lr: 4.914189268446076e-05 loss: 0.1986 (0.2347) time: 3.0694 data: 0.0079 max mem: 31717 +Epoch: [0] [2020/2639] eta: 0:31:17 lr: 4.9137621477883886e-05 loss: 0.1986 (0.2346) time: 3.0536 data: 0.0078 max mem: 31717 +Epoch: [0] [2030/2639] eta: 0:30:46 lr: 4.913335023005466e-05 loss: 0.2001 (0.2344) time: 3.0153 data: 0.0077 max mem: 31717 +Epoch: [0] [2040/2639] eta: 0:30:16 lr: 4.91290789409687e-05 loss: 0.1950 (0.2343) time: 3.0442 data: 0.0074 max mem: 31717 +Epoch: [0] [2050/2639] eta: 0:29:46 lr: 4.912480761062162e-05 loss: 0.1910 (0.2343) time: 3.0656 data: 0.0078 max mem: 31717 +Epoch: [0] [2060/2639] eta: 0:29:16 lr: 4.912053623900903e-05 loss: 0.1903 (0.2341) time: 3.0591 data: 0.0080 max mem: 31717 +Epoch: [0] [2070/2639] eta: 0:28:45 lr: 4.9116264826126566e-05 loss: 0.1903 (0.2339) time: 3.0409 data: 0.0083 max mem: 31717 +Epoch: [0] [2080/2639] eta: 0:28:15 lr: 4.911199337196982e-05 loss: 0.1907 (0.2341) time: 3.0395 data: 0.0078 max mem: 31717 +Epoch: [0] [2090/2639] eta: 0:27:45 lr: 4.9107721876534415e-05 loss: 0.2225 (0.2341) time: 3.0142 data: 0.0078 max mem: 31717 +Epoch: [0] [2100/2639] eta: 0:27:14 lr: 4.910345033981595e-05 loss: 0.2020 (0.2341) time: 3.0173 data: 0.0084 max mem: 31717 +Epoch: [0] [2110/2639] eta: 0:26:44 lr: 4.909917876181004e-05 loss: 0.2020 (0.2341) time: 3.0329 data: 0.0081 max mem: 31717 +Epoch: [0] [2120/2639] eta: 0:26:13 lr: 4.9094907142512306e-05 loss: 0.2140 (0.2340) time: 2.9894 data: 0.0078 max mem: 31717 +Epoch: [0] [2130/2639] eta: 0:25:43 lr: 4.9090635481918355e-05 loss: 0.2157 (0.2339) time: 2.9759 data: 0.0080 max mem: 31717 +Epoch: [0] [2140/2639] eta: 0:25:13 lr: 4.908636378002378e-05 loss: 0.2009 (0.2338) time: 3.0346 data: 0.0077 max mem: 31717 +Epoch: [0] [2150/2639] eta: 0:24:43 lr: 4.908209203682421e-05 loss: 0.1932 (0.2336) time: 3.0904 data: 0.0073 max mem: 31717 +Epoch: [0] [2160/2639] eta: 0:24:12 lr: 4.907782025231522e-05 loss: 0.1777 (0.2334) time: 3.0535 data: 0.0076 max mem: 31717 +Epoch: [0] [2170/2639] eta: 0:23:42 lr: 4.907354842649245e-05 loss: 0.1816 (0.2334) time: 3.0280 data: 0.0076 max mem: 31717 +Epoch: [0] [2180/2639] eta: 0:23:11 lr: 4.906927655935148e-05 loss: 0.1928 (0.2331) time: 3.0290 data: 0.0076 max mem: 31717 +Epoch: [0] [2190/2639] eta: 0:22:41 lr: 4.906500465088792e-05 loss: 0.1871 (0.2331) time: 3.0123 data: 0.0081 max mem: 31717 +Epoch: [0] [2200/2639] eta: 0:22:11 lr: 4.906073270109739e-05 loss: 0.1900 (0.2329) time: 3.0201 data: 0.0081 max mem: 31717 +Epoch: [0] [2210/2639] eta: 0:21:40 lr: 4.905646070997546e-05 loss: 0.1968 (0.2329) time: 3.0263 data: 0.0076 max mem: 31717 +Epoch: [0] [2220/2639] eta: 0:21:10 lr: 4.905218867751776e-05 loss: 0.1901 (0.2327) time: 3.0220 data: 0.0079 max mem: 31717 +Epoch: [0] [2230/2639] eta: 0:20:40 lr: 4.9047916603719866e-05 loss: 0.1914 (0.2327) time: 3.0166 data: 0.0081 max mem: 31717 +Epoch: [0] [2240/2639] eta: 0:20:09 lr: 4.904364448857739e-05 loss: 0.2044 (0.2325) time: 3.0006 data: 0.0079 max mem: 31717 +Epoch: [0] [2250/2639] eta: 0:19:39 lr: 4.9039372332085935e-05 loss: 0.2007 (0.2324) time: 2.9940 data: 0.0077 max mem: 31717 +Epoch: [0] [2260/2639] eta: 0:19:09 lr: 4.903510013424109e-05 loss: 0.2095 (0.2323) time: 3.0182 data: 0.0077 max mem: 31717 +Epoch: [0] [2270/2639] eta: 0:18:38 lr: 4.903082789503846e-05 loss: 0.2144 (0.2321) time: 3.0106 data: 0.0075 max mem: 31717 +Epoch: [0] [2280/2639] eta: 0:18:08 lr: 4.902655561447363e-05 loss: 0.1922 (0.2320) time: 3.0146 data: 0.0074 max mem: 31717 +Epoch: [0] [2290/2639] eta: 0:17:38 lr: 4.902228329254219e-05 loss: 0.1931 (0.2319) time: 3.0400 data: 0.0077 max mem: 31717 +Epoch: [0] [2300/2639] eta: 0:17:07 lr: 4.901801092923974e-05 loss: 0.1991 (0.2318) time: 3.0481 data: 0.0076 max mem: 31717 +Epoch: [0] [2310/2639] eta: 0:16:37 lr: 4.901373852456188e-05 loss: 0.1758 (0.2316) time: 3.0564 data: 0.0074 max mem: 31717 +Epoch: [0] [2320/2639] eta: 0:16:07 lr: 4.90094660785042e-05 loss: 0.1818 (0.2316) time: 3.0287 data: 0.0078 max mem: 31717 +Epoch: [0] [2330/2639] eta: 0:15:36 lr: 4.9005193591062285e-05 loss: 0.1805 (0.2314) time: 3.0365 data: 0.0080 max mem: 31717 +Epoch: [0] [2340/2639] eta: 0:15:06 lr: 4.900092106223173e-05 loss: 0.2010 (0.2312) time: 3.0378 data: 0.0077 max mem: 31717 +Epoch: [0] [2350/2639] eta: 0:14:36 lr: 4.8996648492008116e-05 loss: 0.2164 (0.2312) time: 3.0097 data: 0.0075 max mem: 31717 +Epoch: [0] [2360/2639] eta: 0:14:05 lr: 4.8992375880387045e-05 loss: 0.2020 (0.2311) time: 3.0226 data: 0.0076 max mem: 31717 +Epoch: [0] [2370/2639] eta: 0:13:35 lr: 4.8988103227364095e-05 loss: 0.1895 (0.2309) time: 3.0054 data: 0.0076 max mem: 31717 +Epoch: [0] [2380/2639] eta: 0:13:05 lr: 4.8983830532934854e-05 loss: 0.1994 (0.2309) time: 2.9883 data: 0.0072 max mem: 31717 +Epoch: [0] [2390/2639] eta: 0:12:34 lr: 4.8979557797094904e-05 loss: 0.2076 (0.2309) time: 3.0070 data: 0.0078 max mem: 31717 +Epoch: [0] [2400/2639] eta: 0:12:04 lr: 4.897528501983984e-05 loss: 0.2037 (0.2308) time: 3.0095 data: 0.0087 max mem: 31717 +Epoch: [0] [2410/2639] eta: 0:11:34 lr: 4.897101220116523e-05 loss: 0.1749 (0.2306) time: 3.0039 data: 0.0084 max mem: 31717 +Epoch: [0] [2420/2639] eta: 0:11:03 lr: 4.896673934106668e-05 loss: 0.1786 (0.2307) time: 2.9912 data: 0.0078 max mem: 31717 +Epoch: [0] [2430/2639] eta: 0:10:33 lr: 4.896246643953975e-05 loss: 0.1897 (0.2305) time: 3.0237 data: 0.0077 max mem: 31717 +Epoch: [0] [2440/2639] eta: 0:10:03 lr: 4.895819349658003e-05 loss: 0.1953 (0.2304) time: 3.0454 data: 0.0077 max mem: 31717 +Epoch: [0] [2450/2639] eta: 0:09:32 lr: 4.89539205121831e-05 loss: 0.1977 (0.2303) time: 3.0354 data: 0.0077 max mem: 31717 +Epoch: [0] [2460/2639] eta: 0:09:02 lr: 4.894964748634454e-05 loss: 0.2033 (0.2303) time: 3.0077 data: 0.0080 max mem: 31717 +Epoch: [0] [2470/2639] eta: 0:08:32 lr: 4.8945374419059924e-05 loss: 0.2047 (0.2303) time: 3.0179 data: 0.0080 max mem: 31717 +Epoch: [0] [2480/2639] eta: 0:08:01 lr: 4.894110131032483e-05 loss: 0.1874 (0.2300) time: 3.0367 data: 0.0075 max mem: 31717 +Epoch: [0] [2490/2639] eta: 0:07:31 lr: 4.893682816013485e-05 loss: 0.1874 (0.2299) time: 3.0303 data: 0.0075 max mem: 31717 +Epoch: [0] [2500/2639] eta: 0:07:01 lr: 4.893255496848554e-05 loss: 0.2006 (0.2299) time: 3.0228 data: 0.0075 max mem: 31717 +Epoch: [0] [2510/2639] eta: 0:06:31 lr: 4.892828173537248e-05 loss: 0.1743 (0.2297) time: 3.0374 data: 0.0078 max mem: 31717 +Epoch: [0] [2520/2639] eta: 0:06:00 lr: 4.8924008460791246e-05 loss: 0.1914 (0.2298) time: 3.0341 data: 0.0080 max mem: 31717 +Epoch: [0] [2530/2639] eta: 0:05:30 lr: 4.891973514473742e-05 loss: 0.2053 (0.2297) time: 3.0277 data: 0.0078 max mem: 31717 +Epoch: [0] [2540/2639] eta: 0:05:00 lr: 4.891546178720656e-05 loss: 0.1951 (0.2296) time: 3.0654 data: 0.0079 max mem: 31717 +Epoch: [0] [2550/2639] eta: 0:04:29 lr: 4.891118838819424e-05 loss: 0.1864 (0.2295) time: 3.0073 data: 0.0077 max mem: 31717 +Epoch: [0] [2560/2639] eta: 0:03:59 lr: 4.890691494769603e-05 loss: 0.1856 (0.2294) time: 3.0371 data: 0.0076 max mem: 31717 +Epoch: [0] [2570/2639] eta: 0:03:29 lr: 4.890264146570751e-05 loss: 0.1799 (0.2293) time: 3.0280 data: 0.0079 max mem: 31717 +Epoch: [0] [2580/2639] eta: 0:02:58 lr: 4.8898367942224233e-05 loss: 0.1799 (0.2291) time: 2.9892 data: 0.0079 max mem: 31717 +Epoch: [0] [2590/2639] eta: 0:02:28 lr: 4.889409437724178e-05 loss: 0.1931 (0.2290) time: 2.9905 data: 0.0077 max mem: 31717 +Epoch: [0] [2600/2639] eta: 0:01:58 lr: 4.8889820770755715e-05 loss: 0.2068 (0.2289) time: 2.9742 data: 0.0077 max mem: 31717 +Epoch: [0] [2610/2639] eta: 0:01:27 lr: 4.8885547122761596e-05 loss: 0.2059 (0.2288) time: 3.0247 data: 0.0076 max mem: 31717 +Epoch: [0] [2620/2639] eta: 0:00:57 lr: 4.888127343325499e-05 loss: 0.2047 (0.2287) time: 3.0126 data: 0.0074 max mem: 31717 +Epoch: [0] [2630/2639] eta: 0:00:27 lr: 4.887699970223147e-05 loss: 0.2047 (0.2286) time: 3.0266 data: 0.0071 max mem: 31717 +Epoch: [0] Total time: 2:13:18 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 2:15:57 time: 3.1703 data: 3.0422 max mem: 31717 +Test: [ 100/2573] eta: 0:04:31 time: 0.0792 data: 0.0014 max mem: 31717 +Test: [ 200/2573] eta: 0:03:47 time: 0.0804 data: 0.0014 max mem: 31717 +Test: [ 300/2573] eta: 0:03:24 time: 0.0822 data: 0.0014 max mem: 31717 +Test: [ 400/2573] eta: 0:03:10 time: 0.0815 data: 0.0015 max mem: 31717 +Test: [ 500/2573] eta: 0:02:58 time: 0.0808 data: 0.0016 max mem: 31717 +Test: [ 600/2573] eta: 0:02:48 time: 0.0806 data: 0.0014 max mem: 31717 +Test: [ 700/2573] eta: 0:02:38 time: 0.0804 data: 0.0014 max mem: 31717 +Test: [ 800/2573] eta: 0:02:29 time: 0.0834 data: 0.0015 max mem: 31717 +Test: [ 900/2573] eta: 0:02:20 time: 0.0802 data: 0.0014 max mem: 31717 +Test: [1000/2573] eta: 0:02:11 time: 0.0812 data: 0.0015 max mem: 31717 +Test: [1100/2573] eta: 0:02:02 time: 0.0813 data: 0.0015 max mem: 31717 +Test: [1200/2573] eta: 0:01:54 time: 0.0820 data: 0.0014 max mem: 31717 +Test: [1300/2573] eta: 0:01:45 time: 0.0808 data: 0.0014 max mem: 31717 +Test: [1400/2573] eta: 0:01:37 time: 0.0787 data: 0.0015 max mem: 31717 +Test: [1500/2573] eta: 0:01:28 time: 0.0816 data: 0.0016 max mem: 31717 +Test: [1600/2573] eta: 0:01:20 time: 0.0838 data: 0.0014 max mem: 31717 +Test: [1700/2573] eta: 0:01:12 time: 0.0793 data: 0.0014 max mem: 31717 +Test: [1800/2573] eta: 0:01:03 time: 0.0822 data: 0.0014 max mem: 31717 +Test: [1900/2573] eta: 0:00:55 time: 0.0793 data: 0.0014 max mem: 31717 +Test: [2000/2573] eta: 0:00:47 time: 0.0816 data: 0.0015 max mem: 31717 +Test: [2100/2573] eta: 0:00:38 time: 0.0827 data: 0.0015 max mem: 31717 +Test: [2200/2573] eta: 0:00:30 time: 0.0818 data: 0.0013 max mem: 31717 +Test: [2300/2573] eta: 0:00:22 time: 0.0823 data: 0.0015 max mem: 31717 +Test: [2400/2573] eta: 0:00:14 time: 0.0779 data: 0.0015 max mem: 31717 +Test: [2500/2573] eta: 0:00:05 time: 0.0817 data: 0.0014 max mem: 31717 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: Total time: 0:03:32 +Final results: +Mean IoU is 22.88 + + precision@0.5 = 21.71 + precision@0.6 = 15.93 + precision@0.7 = 10.42 + precision@0.8 = 5.84 + precision@0.9 = 1.21 + overall IoU = 27.67 + +Average object IoU 22.87622364926515 +Overall IoU 27.667715072631836 +Better epoch: 0 + +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [1] [ 0/2639] eta: 4:22:49 lr: 4.887315330880966e-05 loss: 0.2291 (0.2291) time: 5.9754 data: 2.8058 max mem: 31717 +Epoch: [1] [ 10/2639] eta: 2:26:35 lr: 4.8868879498891765e-05 loss: 0.1692 (0.1702) time: 3.3455 data: 0.2617 max mem: 31717 +Epoch: [1] [ 20/2639] eta: 2:18:18 lr: 4.886460564744408e-05 loss: 0.1604 (0.1739) time: 3.0283 data: 0.0070 max mem: 31717 +Epoch: [1] [ 30/2639] eta: 2:16:05 lr: 4.8860331754462155e-05 loss: 0.1625 (0.1752) time: 3.0112 data: 0.0068 max mem: 31717 +Epoch: [1] [ 40/2639] eta: 2:13:56 lr: 4.885605781994157e-05 loss: 0.1664 (0.1788) time: 3.0121 data: 0.0073 max mem: 31717 +Epoch: [1] [ 50/2639] eta: 2:13:13 lr: 4.885178384387788e-05 loss: 0.1664 (0.1809) time: 3.0223 data: 0.0075 max mem: 31717 +Epoch: [1] [ 60/2639] eta: 2:11:49 lr: 4.884750982626663e-05 loss: 0.1547 (0.1809) time: 3.0148 data: 0.0079 max mem: 31717 +Epoch: [1] [ 70/2639] eta: 2:10:34 lr: 4.884323576710337e-05 loss: 0.1594 (0.1812) time: 2.9529 data: 0.0081 max mem: 31717 +Epoch: [1] [ 80/2639] eta: 2:09:11 lr: 4.883896166638368e-05 loss: 0.1896 (0.1838) time: 2.9146 data: 0.0082 max mem: 31717 +Epoch: [1] [ 90/2639] eta: 2:08:24 lr: 4.8834687524103106e-05 loss: 0.1783 (0.1847) time: 2.9260 data: 0.0085 max mem: 31717 +Epoch: [1] [ 100/2639] eta: 2:07:29 lr: 4.8830413340257195e-05 loss: 0.1809 (0.1845) time: 2.9456 data: 0.0080 max mem: 31717 +Epoch: [1] [ 110/2639] eta: 2:06:55 lr: 4.882613911484151e-05 loss: 0.1902 (0.1852) time: 2.9604 data: 0.0084 max mem: 31717 +Epoch: [1] [ 120/2639] eta: 2:06:18 lr: 4.88218648478516e-05 loss: 0.1852 (0.1855) time: 2.9869 data: 0.0085 max mem: 31717 +Epoch: [1] [ 130/2639] eta: 2:05:50 lr: 4.881759053928301e-05 loss: 0.1850 (0.1850) time: 2.9989 data: 0.0081 max mem: 31717 +Epoch: [1] [ 140/2639] eta: 2:05:28 lr: 4.8813316189131296e-05 loss: 0.1878 (0.1861) time: 3.0382 data: 0.0082 max mem: 31717 +Epoch: [1] [ 150/2639] eta: 2:04:52 lr: 4.880904179739201e-05 loss: 0.1892 (0.1851) time: 3.0154 data: 0.0084 max mem: 31717 +Epoch: [1] [ 160/2639] eta: 2:04:37 lr: 4.88047673640607e-05 loss: 0.1700 (0.1866) time: 3.0430 data: 0.0081 max mem: 31717 +Epoch: [1] [ 170/2639] eta: 2:04:06 lr: 4.880049288913291e-05 loss: 0.1700 (0.1861) time: 3.0607 data: 0.0080 max mem: 31717 +Epoch: [1] [ 180/2639] eta: 2:03:44 lr: 4.8796218372604184e-05 loss: 0.1831 (0.1865) time: 3.0420 data: 0.0087 max mem: 31717 +Epoch: [1] [ 190/2639] eta: 2:03:10 lr: 4.8791943814470074e-05 loss: 0.1815 (0.1865) time: 3.0312 data: 0.0088 max mem: 31717 +Epoch: [1] [ 200/2639] eta: 2:02:45 lr: 4.878766921472612e-05 loss: 0.1723 (0.1856) time: 3.0269 data: 0.0085 max mem: 31717 +Epoch: [1] [ 210/2639] eta: 2:02:17 lr: 4.878339457336788e-05 loss: 0.1589 (0.1845) time: 3.0496 data: 0.0088 max mem: 31717 +Epoch: [1] [ 220/2639] eta: 2:01:45 lr: 4.877911989039088e-05 loss: 0.1801 (0.1848) time: 3.0203 data: 0.0084 max mem: 31717 +Epoch: [1] [ 230/2639] eta: 2:01:08 lr: 4.877484516579067e-05 loss: 0.1893 (0.1856) time: 2.9793 data: 0.0078 max mem: 31717 +Epoch: [1] [ 240/2639] eta: 2:00:39 lr: 4.877057039956279e-05 loss: 0.2042 (0.1863) time: 2.9903 data: 0.0081 max mem: 31717 +Epoch: [1] [ 250/2639] eta: 2:00:16 lr: 4.8766295591702774e-05 loss: 0.1844 (0.1857) time: 3.0613 data: 0.0084 max mem: 31717 +Epoch: [1] [ 260/2639] eta: 1:59:44 lr: 4.876202074220617e-05 loss: 0.1692 (0.1862) time: 3.0500 data: 0.0088 max mem: 31717 +Epoch: [1] [ 270/2639] eta: 1:59:20 lr: 4.875774585106852e-05 loss: 0.1742 (0.1858) time: 3.0445 data: 0.0083 max mem: 31717 +Epoch: [1] [ 280/2639] eta: 1:58:45 lr: 4.875347091828536e-05 loss: 0.1826 (0.1867) time: 3.0264 data: 0.0079 max mem: 31717 +Epoch: [1] [ 290/2639] eta: 1:58:13 lr: 4.874919594385222e-05 loss: 0.1930 (0.1871) time: 2.9818 data: 0.0082 max mem: 31717 +Epoch: [1] [ 300/2639] eta: 1:57:42 lr: 4.874492092776463e-05 loss: 0.1689 (0.1865) time: 3.0027 data: 0.0084 max mem: 31717 +Epoch: [1] [ 310/2639] eta: 1:57:07 lr: 4.8740645870018144e-05 loss: 0.1679 (0.1867) time: 2.9830 data: 0.0083 max mem: 31717 +Epoch: [1] [ 320/2639] eta: 1:56:38 lr: 4.873637077060828e-05 loss: 0.1605 (0.1861) time: 2.9936 data: 0.0083 max mem: 31717 +Epoch: [1] [ 330/2639] eta: 1:56:04 lr: 4.873209562953058e-05 loss: 0.1605 (0.1856) time: 2.9997 data: 0.0082 max mem: 31717 +Epoch: [1] [ 340/2639] eta: 1:55:34 lr: 4.872782044678058e-05 loss: 0.1846 (0.1872) time: 2.9932 data: 0.0081 max mem: 31717 +Epoch: [1] [ 350/2639] eta: 1:55:03 lr: 4.872354522235379e-05 loss: 0.1730 (0.1871) time: 3.0091 data: 0.0084 max mem: 31717 +Epoch: [1] [ 360/2639] eta: 1:54:31 lr: 4.8719269956245765e-05 loss: 0.1623 (0.1872) time: 2.9972 data: 0.0083 max mem: 31717 +Epoch: [1] [ 370/2639] eta: 1:54:04 lr: 4.871499464845202e-05 loss: 0.1608 (0.1867) time: 3.0305 data: 0.0084 max mem: 31717 +Epoch: [1] [ 380/2639] eta: 1:53:33 lr: 4.87107192989681e-05 loss: 0.1642 (0.1864) time: 3.0331 data: 0.0083 max mem: 31717 +Epoch: [1] [ 390/2639] eta: 1:53:07 lr: 4.8706443907789505e-05 loss: 0.1689 (0.1869) time: 3.0445 data: 0.0077 max mem: 31717 +Epoch: [1] [ 400/2639] eta: 1:52:41 lr: 4.870216847491179e-05 loss: 0.1994 (0.1876) time: 3.0947 data: 0.0078 max mem: 31717 +Epoch: [1] [ 410/2639] eta: 1:52:08 lr: 4.8697893000330466e-05 loss: 0.2124 (0.1891) time: 3.0344 data: 0.0081 max mem: 31717 +Epoch: [1] [ 420/2639] eta: 1:51:36 lr: 4.869361748404106e-05 loss: 0.1726 (0.1884) time: 2.9702 data: 0.0080 max mem: 31717 +Epoch: [1] [ 430/2639] eta: 1:51:07 lr: 4.868934192603909e-05 loss: 0.1647 (0.1889) time: 3.0077 data: 0.0077 max mem: 31717 +Epoch: [1] [ 440/2639] eta: 1:50:33 lr: 4.868506632632009e-05 loss: 0.1984 (0.1895) time: 2.9975 data: 0.0081 max mem: 31717 +Epoch: [1] [ 450/2639] eta: 1:50:02 lr: 4.868079068487958e-05 loss: 0.1675 (0.1898) time: 2.9712 data: 0.0083 max mem: 31717 +Epoch: [1] [ 460/2639] eta: 1:49:29 lr: 4.867651500171308e-05 loss: 0.1700 (0.1898) time: 2.9776 data: 0.0079 max mem: 31717 +Epoch: [1] [ 470/2639] eta: 1:48:58 lr: 4.86722392768161e-05 loss: 0.1688 (0.1894) time: 2.9782 data: 0.0076 max mem: 31717 +Epoch: [1] [ 480/2639] eta: 1:48:26 lr: 4.866796351018418e-05 loss: 0.1669 (0.1896) time: 2.9841 data: 0.0076 max mem: 31717 +Epoch: [1] [ 490/2639] eta: 1:47:58 lr: 4.866368770181282e-05 loss: 0.2143 (0.1908) time: 3.0108 data: 0.0077 max mem: 31717 +Epoch: [1] [ 500/2639] eta: 1:47:27 lr: 4.865941185169755e-05 loss: 0.2081 (0.1908) time: 3.0235 data: 0.0080 max mem: 31717 +Epoch: [1] [ 510/2639] eta: 1:46:57 lr: 4.865513595983387e-05 loss: 0.1762 (0.1906) time: 3.0144 data: 0.0083 max mem: 31717 +Epoch: [1] [ 520/2639] eta: 1:46:26 lr: 4.865086002621732e-05 loss: 0.1762 (0.1904) time: 3.0072 data: 0.0083 max mem: 31717 +Epoch: [1] [ 530/2639] eta: 1:45:57 lr: 4.8646584050843396e-05 loss: 0.1804 (0.1906) time: 3.0095 data: 0.0083 max mem: 31717 +Epoch: [1] [ 540/2639] eta: 1:45:27 lr: 4.8642308033707624e-05 loss: 0.1750 (0.1904) time: 3.0279 data: 0.0083 max mem: 31717 +Epoch: [1] [ 550/2639] eta: 1:45:00 lr: 4.86380319748055e-05 loss: 0.1750 (0.1906) time: 3.0575 data: 0.0079 max mem: 31717 +Epoch: [1] [ 560/2639] eta: 1:44:30 lr: 4.863375587413255e-05 loss: 0.2049 (0.1911) time: 3.0604 data: 0.0076 max mem: 31717 +Epoch: [1] [ 570/2639] eta: 1:44:00 lr: 4.862947973168429e-05 loss: 0.1871 (0.1909) time: 3.0236 data: 0.0077 max mem: 31717 +Epoch: [1] [ 580/2639] eta: 1:43:28 lr: 4.86252035474562e-05 loss: 0.1871 (0.1913) time: 2.9908 data: 0.0076 max mem: 31717 +Epoch: [1] [ 590/2639] eta: 1:42:57 lr: 4.8620927321443834e-05 loss: 0.1939 (0.1916) time: 2.9775 data: 0.0076 max mem: 31717 +Epoch: [1] [ 600/2639] eta: 1:42:29 lr: 4.861665105364267e-05 loss: 0.1863 (0.1914) time: 3.0316 data: 0.0077 max mem: 31717 +Epoch: [1] [ 610/2639] eta: 1:41:58 lr: 4.8612374744048226e-05 loss: 0.1911 (0.1919) time: 3.0336 data: 0.0084 max mem: 31717 +Epoch: [1] [ 620/2639] eta: 1:41:28 lr: 4.8608098392656e-05 loss: 0.2119 (0.1919) time: 3.0131 data: 0.0085 max mem: 31717 +Epoch: [1] [ 630/2639] eta: 1:40:57 lr: 4.8603821999461515e-05 loss: 0.1892 (0.1918) time: 3.0031 data: 0.0076 max mem: 31717 +Epoch: [1] [ 640/2639] eta: 1:40:26 lr: 4.8599545564460246e-05 loss: 0.1729 (0.1914) time: 2.9845 data: 0.0078 max mem: 31717 +Epoch: [1] [ 650/2639] eta: 1:39:55 lr: 4.8595269087647724e-05 loss: 0.1494 (0.1912) time: 3.0009 data: 0.0083 max mem: 31717 +Epoch: [1] [ 660/2639] eta: 1:39:25 lr: 4.859099256901944e-05 loss: 0.1456 (0.1913) time: 2.9966 data: 0.0083 max mem: 31717 +Epoch: [1] [ 670/2639] eta: 1:38:55 lr: 4.858671600857091e-05 loss: 0.1732 (0.1912) time: 3.0129 data: 0.0084 max mem: 31717 +Epoch: [1] [ 680/2639] eta: 1:38:24 lr: 4.8582439406297606e-05 loss: 0.1732 (0.1911) time: 3.0179 data: 0.0082 max mem: 31717 +Epoch: [1] [ 690/2639] eta: 1:37:54 lr: 4.857816276219506e-05 loss: 0.1724 (0.1908) time: 3.0015 data: 0.0080 max mem: 31717 +Epoch: [1] [ 700/2639] eta: 1:37:24 lr: 4.857388607625875e-05 loss: 0.1708 (0.1910) time: 3.0143 data: 0.0079 max mem: 31717 +Epoch: [1] [ 710/2639] eta: 1:36:54 lr: 4.856960934848418e-05 loss: 0.1708 (0.1908) time: 3.0235 data: 0.0080 max mem: 31717 +Epoch: [1] [ 720/2639] eta: 1:36:26 lr: 4.8565332578866844e-05 loss: 0.1683 (0.1907) time: 3.0609 data: 0.0080 max mem: 31717 +Epoch: [1] [ 730/2639] eta: 1:35:57 lr: 4.856105576740225e-05 loss: 0.1960 (0.1914) time: 3.0678 data: 0.0078 max mem: 31717 +Epoch: [1] [ 740/2639] eta: 1:35:26 lr: 4.855677891408588e-05 loss: 0.2045 (0.1914) time: 3.0212 data: 0.0076 max mem: 31717 +Epoch: [1] [ 750/2639] eta: 1:34:58 lr: 4.855250201891324e-05 loss: 0.1760 (0.1915) time: 3.0441 data: 0.0078 max mem: 31717 +Epoch: [1] [ 760/2639] eta: 1:34:27 lr: 4.8548225081879814e-05 loss: 0.1776 (0.1916) time: 3.0332 data: 0.0080 max mem: 31717 +Epoch: [1] [ 770/2639] eta: 1:34:00 lr: 4.8543948102981106e-05 loss: 0.1776 (0.1915) time: 3.0659 data: 0.0078 max mem: 31717 +Epoch: [1] [ 780/2639] eta: 1:33:29 lr: 4.853967108221259e-05 loss: 0.1783 (0.1919) time: 3.0764 data: 0.0081 max mem: 31717 +Epoch: [1] [ 790/2639] eta: 1:33:00 lr: 4.8535394019569774e-05 loss: 0.1873 (0.1917) time: 3.0190 data: 0.0079 max mem: 31717 +Epoch: [1] [ 800/2639] eta: 1:32:30 lr: 4.853111691504814e-05 loss: 0.1752 (0.1915) time: 3.0396 data: 0.0081 max mem: 31717 +Epoch: [1] [ 810/2639] eta: 1:32:00 lr: 4.8526839768643176e-05 loss: 0.1752 (0.1912) time: 3.0301 data: 0.0084 max mem: 31717 +Epoch: [1] [ 820/2639] eta: 1:31:30 lr: 4.852256258035037e-05 loss: 0.1655 (0.1911) time: 3.0222 data: 0.0081 max mem: 31717 +Epoch: [1] [ 830/2639] eta: 1:31:00 lr: 4.851828535016521e-05 loss: 0.1706 (0.1910) time: 3.0263 data: 0.0079 max mem: 31717 +Epoch: [1] [ 840/2639] eta: 1:30:28 lr: 4.851400807808318e-05 loss: 0.1707 (0.1908) time: 2.9908 data: 0.0078 max mem: 31717 +Epoch: [1] [ 850/2639] eta: 1:29:59 lr: 4.850973076409978e-05 loss: 0.1604 (0.1905) time: 3.0130 data: 0.0080 max mem: 31717 +Epoch: [1] [ 860/2639] eta: 1:29:28 lr: 4.8505453408210476e-05 loss: 0.1701 (0.1905) time: 3.0286 data: 0.0078 max mem: 31717 +Epoch: [1] [ 870/2639] eta: 1:29:00 lr: 4.850117601041076e-05 loss: 0.1755 (0.1907) time: 3.0552 data: 0.0074 max mem: 31717 +Epoch: [1] [ 880/2639] eta: 1:28:30 lr: 4.8496898570696106e-05 loss: 0.1755 (0.1906) time: 3.0584 data: 0.0077 max mem: 31717 +Epoch: [1] [ 890/2639] eta: 1:28:00 lr: 4.8492621089062006e-05 loss: 0.1733 (0.1905) time: 3.0203 data: 0.0084 max mem: 31717 +Epoch: [1] [ 900/2639] eta: 1:27:31 lr: 4.848834356550394e-05 loss: 0.1902 (0.1906) time: 3.0693 data: 0.0081 max mem: 31717 +Epoch: [1] [ 910/2639] eta: 1:27:03 lr: 4.848406600001738e-05 loss: 0.1694 (0.1903) time: 3.0998 data: 0.0078 max mem: 31717 +Epoch: [1] [ 920/2639] eta: 1:26:33 lr: 4.8479788392597816e-05 loss: 0.1718 (0.1903) time: 3.0638 data: 0.0075 max mem: 31717 +Epoch: [1] [ 930/2639] eta: 1:26:03 lr: 4.847551074324071e-05 loss: 0.1845 (0.1901) time: 3.0429 data: 0.0075 max mem: 31717 +Epoch: [1] [ 940/2639] eta: 1:25:33 lr: 4.847123305194156e-05 loss: 0.1656 (0.1902) time: 3.0390 data: 0.0077 max mem: 31717 +Epoch: [1] [ 950/2639] eta: 1:25:03 lr: 4.846695531869581e-05 loss: 0.1678 (0.1901) time: 3.0433 data: 0.0077 max mem: 31717 +Epoch: [1] [ 960/2639] eta: 1:24:34 lr: 4.846267754349897e-05 loss: 0.1860 (0.1902) time: 3.0629 data: 0.0077 max mem: 31717 +Epoch: [1] [ 970/2639] eta: 1:24:03 lr: 4.8458399726346494e-05 loss: 0.1878 (0.1904) time: 3.0256 data: 0.0079 max mem: 31717 +Epoch: [1] [ 980/2639] eta: 1:23:34 lr: 4.845412186723386e-05 loss: 0.1894 (0.1906) time: 3.0368 data: 0.0081 max mem: 31717 +Epoch: [1] [ 990/2639] eta: 1:23:03 lr: 4.844984396615654e-05 loss: 0.1747 (0.1905) time: 3.0215 data: 0.0080 max mem: 31717 +Epoch: [1] [1000/2639] eta: 1:22:33 lr: 4.844556602311e-05 loss: 0.1697 (0.1905) time: 3.0252 data: 0.0079 max mem: 31717 +Epoch: [1] [1010/2639] eta: 1:22:03 lr: 4.8441288038089724e-05 loss: 0.1701 (0.1905) time: 3.0455 data: 0.0079 max mem: 31717 +Epoch: [1] [1020/2639] eta: 1:21:34 lr: 4.843701001109117e-05 loss: 0.1741 (0.1905) time: 3.0408 data: 0.0080 max mem: 31717 +Epoch: [1] [1030/2639] eta: 1:21:03 lr: 4.8432731942109806e-05 loss: 0.1741 (0.1903) time: 3.0525 data: 0.0081 max mem: 31717 +Epoch: [1] [1040/2639] eta: 1:20:35 lr: 4.84284538311411e-05 loss: 0.1779 (0.1902) time: 3.0693 data: 0.0081 max mem: 31717 +Epoch: [1] [1050/2639] eta: 1:20:04 lr: 4.842417567818053e-05 loss: 0.1779 (0.1901) time: 3.0448 data: 0.0078 max mem: 31717 +Epoch: [1] [1060/2639] eta: 1:19:35 lr: 4.8419897483223554e-05 loss: 0.1746 (0.1900) time: 3.0452 data: 0.0074 max mem: 31717 +Epoch: [1] [1070/2639] eta: 1:19:04 lr: 4.8415619246265624e-05 loss: 0.1696 (0.1898) time: 3.0562 data: 0.0074 max mem: 31717 +Epoch: [1] [1080/2639] eta: 1:18:34 lr: 4.841134096730222e-05 loss: 0.1894 (0.1900) time: 3.0227 data: 0.0075 max mem: 31717 +Epoch: [1] [1090/2639] eta: 1:18:03 lr: 4.840706264632881e-05 loss: 0.1894 (0.1899) time: 3.0063 data: 0.0074 max mem: 31717 +Epoch: [1] [1100/2639] eta: 1:17:33 lr: 4.8402784283340835e-05 loss: 0.1753 (0.1897) time: 3.0084 data: 0.0075 max mem: 31717 +Epoch: [1] [1110/2639] eta: 1:17:03 lr: 4.839850587833378e-05 loss: 0.1661 (0.1896) time: 3.0240 data: 0.0075 max mem: 31717 +Epoch: [1] [1120/2639] eta: 1:16:32 lr: 4.839422743130308e-05 loss: 0.1716 (0.1895) time: 3.0087 data: 0.0075 max mem: 31717 +Epoch: [1] [1130/2639] eta: 1:16:02 lr: 4.8389948942244215e-05 loss: 0.1741 (0.1894) time: 3.0308 data: 0.0075 max mem: 31717 +Epoch: [1] [1140/2639] eta: 1:15:32 lr: 4.838567041115263e-05 loss: 0.1698 (0.1896) time: 3.0433 data: 0.0074 max mem: 31717 +Epoch: [1] [1150/2639] eta: 1:15:02 lr: 4.838139183802379e-05 loss: 0.1670 (0.1894) time: 3.0257 data: 0.0076 max mem: 31717 +Epoch: [1] [1160/2639] eta: 1:14:32 lr: 4.8377113222853146e-05 loss: 0.1653 (0.1892) time: 3.0224 data: 0.0076 max mem: 31717 +Epoch: [1] [1170/2639] eta: 1:14:02 lr: 4.837283456563615e-05 loss: 0.1612 (0.1891) time: 3.0262 data: 0.0070 max mem: 31717 +Epoch: [1] [1180/2639] eta: 1:13:32 lr: 4.836855586636827e-05 loss: 0.1665 (0.1891) time: 3.0536 data: 0.0071 max mem: 31717 +Epoch: [1] [1190/2639] eta: 1:13:01 lr: 4.836427712504496e-05 loss: 0.1696 (0.1889) time: 3.0222 data: 0.0073 max mem: 31717 +Epoch: [1] [1200/2639] eta: 1:12:31 lr: 4.835999834166164e-05 loss: 0.1594 (0.1887) time: 3.0072 data: 0.0074 max mem: 31717 +Epoch: [1] [1210/2639] eta: 1:12:01 lr: 4.835571951621381e-05 loss: 0.1711 (0.1888) time: 3.0199 data: 0.0075 max mem: 31717 +Epoch: [1] [1220/2639] eta: 1:11:30 lr: 4.8351440648696885e-05 loss: 0.1809 (0.1885) time: 3.0112 data: 0.0076 max mem: 31717 +Epoch: [1] [1230/2639] eta: 1:11:00 lr: 4.834716173910633e-05 loss: 0.1567 (0.1883) time: 3.0381 data: 0.0077 max mem: 31717 +Epoch: [1] [1240/2639] eta: 1:10:30 lr: 4.8342882787437584e-05 loss: 0.1567 (0.1881) time: 3.0373 data: 0.0077 max mem: 31717 +Epoch: [1] [1250/2639] eta: 1:10:00 lr: 4.833860379368611e-05 loss: 0.1630 (0.1881) time: 3.0507 data: 0.0075 max mem: 31717 +Epoch: [1] [1260/2639] eta: 1:09:30 lr: 4.833432475784733e-05 loss: 0.1663 (0.1881) time: 3.0335 data: 0.0077 max mem: 31717 +Epoch: [1] [1270/2639] eta: 1:09:00 lr: 4.8330045679916724e-05 loss: 0.1615 (0.1880) time: 3.0402 data: 0.0078 max mem: 31717 +Epoch: [1] [1280/2639] eta: 1:08:30 lr: 4.8325766559889704e-05 loss: 0.1615 (0.1878) time: 3.0441 data: 0.0079 max mem: 31717 +Epoch: [1] [1290/2639] eta: 1:08:00 lr: 4.832148739776174e-05 loss: 0.1544 (0.1879) time: 3.0477 data: 0.0078 max mem: 31717 +Epoch: [1] [1300/2639] eta: 1:07:31 lr: 4.831720819352826e-05 loss: 0.1742 (0.1879) time: 3.0956 data: 0.0075 max mem: 31717 +Epoch: [1] [1310/2639] eta: 1:07:00 lr: 4.831292894718471e-05 loss: 0.1848 (0.1880) time: 3.0419 data: 0.0077 max mem: 31717 +Epoch: [1] [1320/2639] eta: 1:06:30 lr: 4.8308649658726526e-05 loss: 0.1853 (0.1879) time: 2.9988 data: 0.0080 max mem: 31717 +Epoch: [1] [1330/2639] eta: 1:06:00 lr: 4.830437032814916e-05 loss: 0.1824 (0.1879) time: 3.0245 data: 0.0079 max mem: 31717 +Epoch: [1] [1340/2639] eta: 1:05:29 lr: 4.830009095544805e-05 loss: 0.1813 (0.1878) time: 3.0144 data: 0.0082 max mem: 31717 +Epoch: [1] [1350/2639] eta: 1:04:59 lr: 4.829581154061861e-05 loss: 0.1648 (0.1877) time: 3.0291 data: 0.0081 max mem: 31717 +Epoch: [1] [1360/2639] eta: 1:04:28 lr: 4.829153208365632e-05 loss: 0.1648 (0.1877) time: 3.0104 data: 0.0077 max mem: 31717 +Epoch: [1] [1370/2639] eta: 1:03:58 lr: 4.828725258455658e-05 loss: 0.1570 (0.1875) time: 3.0114 data: 0.0076 max mem: 31717 +Epoch: [1] [1380/2639] eta: 1:03:28 lr: 4.8282973043314844e-05 loss: 0.1684 (0.1875) time: 3.0207 data: 0.0076 max mem: 31717 +Epoch: [1] [1390/2639] eta: 1:02:58 lr: 4.827869345992654e-05 loss: 0.1769 (0.1875) time: 3.0027 data: 0.0077 max mem: 31717 +Epoch: [1] [1400/2639] eta: 1:02:27 lr: 4.8274413834387107e-05 loss: 0.1641 (0.1873) time: 3.0095 data: 0.0077 max mem: 31717 +Epoch: [1] [1410/2639] eta: 1:01:57 lr: 4.8270134166691974e-05 loss: 0.1516 (0.1873) time: 3.0042 data: 0.0077 max mem: 31717 +Epoch: [1] [1420/2639] eta: 1:01:27 lr: 4.826585445683657e-05 loss: 0.1517 (0.1871) time: 3.0331 data: 0.0074 max mem: 31717 +Epoch: [1] [1430/2639] eta: 1:00:57 lr: 4.826157470481633e-05 loss: 0.1636 (0.1870) time: 3.0601 data: 0.0072 max mem: 31717 +Epoch: [1] [1440/2639] eta: 1:00:26 lr: 4.825729491062669e-05 loss: 0.1885 (0.1872) time: 3.0055 data: 0.0074 max mem: 31717 +Epoch: [1] [1450/2639] eta: 0:59:56 lr: 4.825301507426306e-05 loss: 0.1885 (0.1872) time: 3.0068 data: 0.0075 max mem: 31717 +Epoch: [1] [1460/2639] eta: 0:59:25 lr: 4.824873519572088e-05 loss: 0.1743 (0.1872) time: 3.0301 data: 0.0073 max mem: 31717 +Epoch: [1] [1470/2639] eta: 0:58:56 lr: 4.824445527499559e-05 loss: 0.1744 (0.1873) time: 3.0407 data: 0.0075 max mem: 31717 +Epoch: [1] [1480/2639] eta: 0:58:26 lr: 4.82401753120826e-05 loss: 0.1705 (0.1872) time: 3.0676 data: 0.0075 max mem: 31717 +Epoch: [1] [1490/2639] eta: 0:57:55 lr: 4.823589530697733e-05 loss: 0.1704 (0.1872) time: 3.0209 data: 0.0075 max mem: 31717 +Epoch: [1] [1500/2639] eta: 0:57:24 lr: 4.823161525967522e-05 loss: 0.1704 (0.1872) time: 2.9742 data: 0.0077 max mem: 31717 +Epoch: [1] [1510/2639] eta: 0:56:54 lr: 4.822733517017168e-05 loss: 0.1674 (0.1872) time: 2.9939 data: 0.0076 max mem: 31717 +Epoch: [1] [1520/2639] eta: 0:56:24 lr: 4.8223055038462146e-05 loss: 0.1573 (0.1871) time: 3.0180 data: 0.0075 max mem: 31717 +Epoch: [1] [1530/2639] eta: 0:55:53 lr: 4.821877486454203e-05 loss: 0.1656 (0.1870) time: 2.9666 data: 0.0081 max mem: 31717 +Epoch: [1] [1540/2639] eta: 0:55:22 lr: 4.8214494648406744e-05 loss: 0.1743 (0.1872) time: 2.9477 data: 0.0082 max mem: 31717 +Epoch: [1] [1550/2639] eta: 0:54:52 lr: 4.8210214390051726e-05 loss: 0.1692 (0.1870) time: 2.9941 data: 0.0081 max mem: 31717 +Epoch: [1] [1560/2639] eta: 0:54:21 lr: 4.8205934089472394e-05 loss: 0.1547 (0.1868) time: 3.0014 data: 0.0081 max mem: 31717 +Epoch: [1] [1570/2639] eta: 0:53:51 lr: 4.820165374666415e-05 loss: 0.1547 (0.1869) time: 2.9856 data: 0.0077 max mem: 31717 +Epoch: [1] [1580/2639] eta: 0:53:21 lr: 4.8197373361622414e-05 loss: 0.1469 (0.1867) time: 3.0096 data: 0.0076 max mem: 31717 +Epoch: [1] [1590/2639] eta: 0:52:50 lr: 4.819309293434261e-05 loss: 0.1671 (0.1867) time: 3.0102 data: 0.0076 max mem: 31717 +Epoch: [1] [1600/2639] eta: 0:52:21 lr: 4.818881246482015e-05 loss: 0.1671 (0.1865) time: 3.0604 data: 0.0080 max mem: 31717 +Epoch: [1] [1610/2639] eta: 0:51:50 lr: 4.8184531953050455e-05 loss: 0.1624 (0.1865) time: 3.0306 data: 0.0081 max mem: 31717 +Epoch: [1] [1620/2639] eta: 0:51:20 lr: 4.8180251399028917e-05 loss: 0.1870 (0.1865) time: 3.0090 data: 0.0079 max mem: 31717 +Epoch: [1] [1630/2639] eta: 0:50:50 lr: 4.817597080275097e-05 loss: 0.1870 (0.1864) time: 3.0413 data: 0.0079 max mem: 31717 +Epoch: [1] [1640/2639] eta: 0:50:20 lr: 4.817169016421201e-05 loss: 0.1889 (0.1865) time: 3.0422 data: 0.0077 max mem: 31717 +Epoch: [1] [1650/2639] eta: 0:49:50 lr: 4.816740948340746e-05 loss: 0.1947 (0.1865) time: 3.0702 data: 0.0075 max mem: 31717 +Epoch: [1] [1660/2639] eta: 0:49:19 lr: 4.816312876033272e-05 loss: 0.1791 (0.1864) time: 3.0250 data: 0.0079 max mem: 31717 +Epoch: [1] [1670/2639] eta: 0:48:50 lr: 4.8158847994983195e-05 loss: 0.1660 (0.1864) time: 3.0478 data: 0.0082 max mem: 31717 +Epoch: [1] [1680/2639] eta: 0:48:19 lr: 4.815456718735431e-05 loss: 0.1645 (0.1862) time: 3.0637 data: 0.0079 max mem: 31717 +Epoch: [1] [1690/2639] eta: 0:47:49 lr: 4.815028633744144e-05 loss: 0.1511 (0.1862) time: 3.0098 data: 0.0080 max mem: 31717 +Epoch: [1] [1700/2639] eta: 0:47:19 lr: 4.814600544524002e-05 loss: 0.1519 (0.1863) time: 3.0103 data: 0.0082 max mem: 31717 +Epoch: [1] [1710/2639] eta: 0:46:48 lr: 4.814172451074544e-05 loss: 0.1737 (0.1862) time: 2.9980 data: 0.0079 max mem: 31717 +Epoch: [1] [1720/2639] eta: 0:46:18 lr: 4.8137443533953106e-05 loss: 0.1743 (0.1861) time: 3.0084 data: 0.0078 max mem: 31717 +Epoch: [1] [1730/2639] eta: 0:45:48 lr: 4.8133162514858424e-05 loss: 0.1596 (0.1861) time: 3.0534 data: 0.0080 max mem: 31717 +Epoch: [1] [1740/2639] eta: 0:45:18 lr: 4.8128881453456785e-05 loss: 0.1707 (0.1860) time: 3.0329 data: 0.0081 max mem: 31717 +Epoch: [1] [1750/2639] eta: 0:44:48 lr: 4.812460034974361e-05 loss: 0.1731 (0.1860) time: 3.0170 data: 0.0079 max mem: 31717 +Epoch: [1] [1760/2639] eta: 0:44:17 lr: 4.812031920371427e-05 loss: 0.1585 (0.1859) time: 3.0219 data: 0.0080 max mem: 31717 +Epoch: [1] [1770/2639] eta: 0:43:47 lr: 4.8116038015364184e-05 loss: 0.1521 (0.1857) time: 3.0468 data: 0.0079 max mem: 31717 +Epoch: [1] [1780/2639] eta: 0:43:17 lr: 4.811175678468874e-05 loss: 0.1557 (0.1856) time: 3.0669 data: 0.0076 max mem: 31717 +Epoch: [1] [1790/2639] eta: 0:42:47 lr: 4.8107475511683345e-05 loss: 0.1597 (0.1856) time: 3.0257 data: 0.0076 max mem: 31717 +Epoch: [1] [1800/2639] eta: 0:42:16 lr: 4.810319419634339e-05 loss: 0.1571 (0.1855) time: 2.9920 data: 0.0081 max mem: 31717 +Epoch: [1] [1810/2639] eta: 0:41:46 lr: 4.8098912838664276e-05 loss: 0.1473 (0.1853) time: 2.9983 data: 0.0082 max mem: 31717 +Epoch: [1] [1820/2639] eta: 0:41:16 lr: 4.8094631438641375e-05 loss: 0.1473 (0.1853) time: 2.9888 data: 0.0077 max mem: 31717 +Epoch: [1] [1830/2639] eta: 0:40:46 lr: 4.809034999627009e-05 loss: 0.1722 (0.1853) time: 3.0069 data: 0.0077 max mem: 31717 +Epoch: [1] [1840/2639] eta: 0:40:15 lr: 4.8086068511545836e-05 loss: 0.1740 (0.1853) time: 3.0288 data: 0.0077 max mem: 31717 +Epoch: [1] [1850/2639] eta: 0:39:45 lr: 4.808178698446397e-05 loss: 0.1758 (0.1853) time: 3.0295 data: 0.0077 max mem: 31717 +Epoch: [1] [1860/2639] eta: 0:39:15 lr: 4.80775054150199e-05 loss: 0.1719 (0.1853) time: 3.0372 data: 0.0078 max mem: 31717 +Epoch: [1] [1870/2639] eta: 0:38:44 lr: 4.8073223803209016e-05 loss: 0.1656 (0.1852) time: 3.0012 data: 0.0080 max mem: 31717 +Epoch: [1] [1880/2639] eta: 0:38:14 lr: 4.8068942149026704e-05 loss: 0.1656 (0.1852) time: 2.9829 data: 0.0080 max mem: 31717 +Epoch: [1] [1890/2639] eta: 0:37:44 lr: 4.806466045246834e-05 loss: 0.1990 (0.1854) time: 3.0100 data: 0.0075 max mem: 31717 +Epoch: [1] [1900/2639] eta: 0:37:14 lr: 4.8060378713529324e-05 loss: 0.1884 (0.1854) time: 3.0504 data: 0.0074 max mem: 31717 +Epoch: [1] [1910/2639] eta: 0:36:44 lr: 4.8056096932205035e-05 loss: 0.1618 (0.1852) time: 3.0376 data: 0.0076 max mem: 31717 +Epoch: [1] [1920/2639] eta: 0:36:13 lr: 4.805181510849086e-05 loss: 0.1594 (0.1851) time: 2.9633 data: 0.0078 max mem: 31717 +Epoch: [1] [1930/2639] eta: 0:35:43 lr: 4.804753324238218e-05 loss: 0.1579 (0.1851) time: 2.9727 data: 0.0076 max mem: 31717 +Epoch: [1] [1940/2639] eta: 0:35:12 lr: 4.804325133387438e-05 loss: 0.1696 (0.1851) time: 2.9796 data: 0.0076 max mem: 31717 +Epoch: [1] [1950/2639] eta: 0:34:42 lr: 4.803896938296284e-05 loss: 0.1647 (0.1850) time: 2.9701 data: 0.0075 max mem: 31717 +Epoch: [1] [1960/2639] eta: 0:34:12 lr: 4.803468738964294e-05 loss: 0.1564 (0.1850) time: 3.0002 data: 0.0074 max mem: 31717 +Epoch: [1] [1970/2639] eta: 0:33:42 lr: 4.803040535391006e-05 loss: 0.1661 (0.1851) time: 3.0537 data: 0.0073 max mem: 31717 +Epoch: [1] [1980/2639] eta: 0:33:12 lr: 4.802612327575957e-05 loss: 0.1884 (0.1852) time: 3.1030 data: 0.0075 max mem: 31717 +Epoch: [1] [1990/2639] eta: 0:32:41 lr: 4.802184115518686e-05 loss: 0.2029 (0.1853) time: 3.0469 data: 0.0076 max mem: 31717 +Epoch: [1] [2000/2639] eta: 0:32:11 lr: 4.801755899218731e-05 loss: 0.1946 (0.1854) time: 3.0463 data: 0.0076 max mem: 31717 +Epoch: [1] [2010/2639] eta: 0:31:41 lr: 4.801327678675627e-05 loss: 0.1840 (0.1854) time: 3.0782 data: 0.0077 max mem: 31717 +Epoch: [1] [2020/2639] eta: 0:31:11 lr: 4.800899453888915e-05 loss: 0.1647 (0.1853) time: 3.0112 data: 0.0078 max mem: 31717 +Epoch: [1] [2030/2639] eta: 0:30:41 lr: 4.800471224858129e-05 loss: 0.1575 (0.1853) time: 3.0047 data: 0.0079 max mem: 31717 +Epoch: [1] [2040/2639] eta: 0:30:10 lr: 4.8000429915828084e-05 loss: 0.1779 (0.1854) time: 3.0146 data: 0.0079 max mem: 31717 +Epoch: [1] [2050/2639] eta: 0:29:40 lr: 4.7996147540624906e-05 loss: 0.1810 (0.1854) time: 3.0162 data: 0.0076 max mem: 31717 +Epoch: [1] [2060/2639] eta: 0:29:10 lr: 4.799186512296711e-05 loss: 0.1810 (0.1854) time: 3.0157 data: 0.0077 max mem: 31717 +Epoch: [1] [2070/2639] eta: 0:28:40 lr: 4.798758266285008e-05 loss: 0.1935 (0.1855) time: 3.0400 data: 0.0078 max mem: 31717 +Epoch: [1] [2080/2639] eta: 0:28:10 lr: 4.798330016026917e-05 loss: 0.2019 (0.1855) time: 3.0650 data: 0.0077 max mem: 31717 +Epoch: [1] [2090/2639] eta: 0:27:39 lr: 4.7979017615219765e-05 loss: 0.1807 (0.1855) time: 3.0058 data: 0.0074 max mem: 31717 +Epoch: [1] [2100/2639] eta: 0:27:09 lr: 4.797473502769722e-05 loss: 0.1397 (0.1852) time: 2.9953 data: 0.0076 max mem: 31717 +Epoch: [1] [2110/2639] eta: 0:26:39 lr: 4.797045239769691e-05 loss: 0.1469 (0.1852) time: 2.9974 data: 0.0078 max mem: 31717 +Epoch: [1] [2120/2639] eta: 0:26:08 lr: 4.796616972521419e-05 loss: 0.1569 (0.1850) time: 2.9708 data: 0.0074 max mem: 31717 +Epoch: [1] [2130/2639] eta: 0:25:38 lr: 4.796188701024443e-05 loss: 0.1511 (0.1850) time: 3.0313 data: 0.0073 max mem: 31717 +Epoch: [1] [2140/2639] eta: 0:25:08 lr: 4.7957604252783e-05 loss: 0.1769 (0.1850) time: 3.0423 data: 0.0075 max mem: 31717 +Epoch: [1] [2150/2639] eta: 0:24:38 lr: 4.795332145282525e-05 loss: 0.1769 (0.1850) time: 2.9898 data: 0.0078 max mem: 31717 +Epoch: [1] [2160/2639] eta: 0:24:07 lr: 4.794903861036653e-05 loss: 0.1794 (0.1850) time: 2.9970 data: 0.0074 max mem: 31717 +Epoch: [1] [2170/2639] eta: 0:23:37 lr: 4.7944755725402234e-05 loss: 0.1871 (0.1850) time: 3.0136 data: 0.0075 max mem: 31717 +Epoch: [1] [2180/2639] eta: 0:23:07 lr: 4.794047279792769e-05 loss: 0.1724 (0.1849) time: 2.9812 data: 0.0076 max mem: 31717 +Epoch: [1] [2190/2639] eta: 0:22:37 lr: 4.7936189827938284e-05 loss: 0.1532 (0.1848) time: 2.9879 data: 0.0075 max mem: 31717 +Epoch: [1] [2200/2639] eta: 0:22:06 lr: 4.7931906815429346e-05 loss: 0.1505 (0.1847) time: 3.0407 data: 0.0074 max mem: 31717 +Epoch: [1] [2210/2639] eta: 0:21:36 lr: 4.7927623760396244e-05 loss: 0.1455 (0.1845) time: 3.0389 data: 0.0072 max mem: 31717 +Epoch: [1] [2220/2639] eta: 0:21:06 lr: 4.7923340662834335e-05 loss: 0.1603 (0.1846) time: 3.0234 data: 0.0074 max mem: 31717 +Epoch: [1] [2230/2639] eta: 0:20:36 lr: 4.791905752273898e-05 loss: 0.1759 (0.1845) time: 3.0210 data: 0.0077 max mem: 31717 +Epoch: [1] [2240/2639] eta: 0:20:05 lr: 4.791477434010552e-05 loss: 0.1683 (0.1845) time: 3.0322 data: 0.0075 max mem: 33406 +Epoch: [1] [2250/2639] eta: 0:19:35 lr: 4.791049111492931e-05 loss: 0.1638 (0.1845) time: 3.0057 data: 0.0071 max mem: 33406 +Epoch: [1] [2260/2639] eta: 0:19:05 lr: 4.79062078472057e-05 loss: 0.1654 (0.1844) time: 2.9889 data: 0.0073 max mem: 33406 +Epoch: [1] [2270/2639] eta: 0:18:35 lr: 4.790192453693004e-05 loss: 0.1844 (0.1845) time: 2.9873 data: 0.0078 max mem: 33406 +Epoch: [1] [2280/2639] eta: 0:18:04 lr: 4.789764118409769e-05 loss: 0.1948 (0.1845) time: 3.0119 data: 0.0077 max mem: 33406 +Epoch: [1] [2290/2639] eta: 0:17:34 lr: 4.789335778870399e-05 loss: 0.1803 (0.1845) time: 2.9929 data: 0.0072 max mem: 33406 +Epoch: [1] [2300/2639] eta: 0:17:04 lr: 4.788907435074429e-05 loss: 0.1480 (0.1843) time: 3.0326 data: 0.0072 max mem: 33406 +Epoch: [1] [2310/2639] eta: 0:16:34 lr: 4.788479087021393e-05 loss: 0.1451 (0.1843) time: 3.0724 data: 0.0074 max mem: 33406 +Epoch: [1] [2320/2639] eta: 0:16:04 lr: 4.788050734710827e-05 loss: 0.1611 (0.1843) time: 3.0146 data: 0.0073 max mem: 33406 +Epoch: [1] [2330/2639] eta: 0:15:33 lr: 4.787622378142264e-05 loss: 0.1611 (0.1843) time: 2.9953 data: 0.0076 max mem: 33406 +Epoch: [1] [2340/2639] eta: 0:15:03 lr: 4.7871940173152394e-05 loss: 0.1621 (0.1842) time: 2.9802 data: 0.0076 max mem: 33406 +Epoch: [1] [2350/2639] eta: 0:14:33 lr: 4.7867656522292864e-05 loss: 0.1733 (0.1842) time: 3.0478 data: 0.0071 max mem: 33406 +Epoch: [1] [2360/2639] eta: 0:14:03 lr: 4.78633728288394e-05 loss: 0.1675 (0.1841) time: 3.0924 data: 0.0070 max mem: 33406 +Epoch: [1] [2370/2639] eta: 0:13:33 lr: 4.785908909278734e-05 loss: 0.1582 (0.1841) time: 3.0468 data: 0.0078 max mem: 33406 +Epoch: [1] [2380/2639] eta: 0:13:02 lr: 4.785480531413203e-05 loss: 0.1610 (0.1841) time: 3.0766 data: 0.0083 max mem: 33406 +Epoch: [1] [2390/2639] eta: 0:12:32 lr: 4.7850521492868797e-05 loss: 0.1679 (0.1840) time: 3.0667 data: 0.0078 max mem: 33406 +Epoch: [1] [2400/2639] eta: 0:12:02 lr: 4.784623762899298e-05 loss: 0.1682 (0.1840) time: 3.0002 data: 0.0075 max mem: 33406 +Epoch: [1] [2410/2639] eta: 0:11:32 lr: 4.784195372249993e-05 loss: 0.1587 (0.1840) time: 3.0509 data: 0.0074 max mem: 33406 +Epoch: [1] [2420/2639] eta: 0:11:02 lr: 4.783766977338498e-05 loss: 0.1637 (0.1839) time: 3.0547 data: 0.0075 max mem: 33406 +Epoch: [1] [2430/2639] eta: 0:10:31 lr: 4.783338578164344e-05 loss: 0.1717 (0.1840) time: 2.9947 data: 0.0075 max mem: 33406 +Epoch: [1] [2440/2639] eta: 0:10:01 lr: 4.7829101747270676e-05 loss: 0.1622 (0.1838) time: 2.9926 data: 0.0077 max mem: 33406 +Epoch: [1] [2450/2639] eta: 0:09:31 lr: 4.7824817670262e-05 loss: 0.1500 (0.1838) time: 3.0309 data: 0.0077 max mem: 33406 +Epoch: [1] [2460/2639] eta: 0:09:01 lr: 4.7820533550612755e-05 loss: 0.1744 (0.1838) time: 3.0707 data: 0.0074 max mem: 33406 +Epoch: [1] [2470/2639] eta: 0:08:30 lr: 4.781624938831827e-05 loss: 0.1671 (0.1837) time: 3.0435 data: 0.0074 max mem: 33406 +Epoch: [1] [2480/2639] eta: 0:08:00 lr: 4.781196518337387e-05 loss: 0.1542 (0.1835) time: 3.0270 data: 0.0074 max mem: 33406 +Epoch: [1] [2490/2639] eta: 0:07:30 lr: 4.780768093577489e-05 loss: 0.1383 (0.1834) time: 3.0095 data: 0.0073 max mem: 33406 +Epoch: [1] [2500/2639] eta: 0:07:00 lr: 4.780339664551666e-05 loss: 0.1655 (0.1834) time: 2.9976 data: 0.0074 max mem: 33406 +Epoch: [1] [2510/2639] eta: 0:06:29 lr: 4.779911231259449e-05 loss: 0.1711 (0.1835) time: 2.9854 data: 0.0073 max mem: 33406 +Epoch: [1] [2520/2639] eta: 0:05:59 lr: 4.779482793700373e-05 loss: 0.1669 (0.1834) time: 3.0093 data: 0.0071 max mem: 33406 +Epoch: [1] [2530/2639] eta: 0:05:29 lr: 4.779054351873968e-05 loss: 0.1533 (0.1833) time: 3.0182 data: 0.0072 max mem: 33406 +Epoch: [1] [2540/2639] eta: 0:04:59 lr: 4.778625905779769e-05 loss: 0.1756 (0.1834) time: 3.0127 data: 0.0073 max mem: 33406 +Epoch: [1] [2550/2639] eta: 0:04:28 lr: 4.778197455417307e-05 loss: 0.1908 (0.1833) time: 2.9924 data: 0.0072 max mem: 33406 +Epoch: [1] [2560/2639] eta: 0:03:58 lr: 4.777769000786114e-05 loss: 0.1609 (0.1833) time: 2.9853 data: 0.0074 max mem: 33406 +Epoch: [1] [2570/2639] eta: 0:03:28 lr: 4.777340541885722e-05 loss: 0.1563 (0.1832) time: 3.0190 data: 0.0074 max mem: 33406 +Epoch: [1] [2580/2639] eta: 0:02:58 lr: 4.776912078715664e-05 loss: 0.1626 (0.1832) time: 2.9921 data: 0.0073 max mem: 33406 +Epoch: [1] [2590/2639] eta: 0:02:28 lr: 4.776483611275472e-05 loss: 0.1528 (0.1831) time: 2.9895 data: 0.0075 max mem: 33406 +Epoch: [1] [2600/2639] eta: 0:01:57 lr: 4.776055139564676e-05 loss: 0.1515 (0.1830) time: 2.9927 data: 0.0075 max mem: 33406 +Epoch: [1] [2610/2639] eta: 0:01:27 lr: 4.77562666358281e-05 loss: 0.1518 (0.1829) time: 3.0418 data: 0.0071 max mem: 33406 +Epoch: [1] [2620/2639] eta: 0:00:57 lr: 4.775198183329404e-05 loss: 0.1679 (0.1829) time: 3.0636 data: 0.0073 max mem: 33406 +Epoch: [1] [2630/2639] eta: 0:00:27 lr: 4.774769698803991e-05 loss: 0.1742 (0.1829) time: 3.0142 data: 0.0073 max mem: 33406 +Epoch: [1] Total time: 2:12:55 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 2:17:41 time: 3.2109 data: 3.1160 max mem: 33406 +Test: [ 100/2573] eta: 0:04:30 time: 0.0788 data: 0.0015 max mem: 33406 +Test: [ 200/2573] eta: 0:03:46 time: 0.0805 data: 0.0014 max mem: 33406 +Test: [ 300/2573] eta: 0:03:23 time: 0.0816 data: 0.0014 max mem: 33406 +Test: [ 400/2573] eta: 0:03:09 time: 0.0811 data: 0.0013 max mem: 33406 +Test: [ 500/2573] eta: 0:02:57 time: 0.0799 data: 0.0015 max mem: 33406 +Test: [ 600/2573] eta: 0:02:47 time: 0.0793 data: 0.0014 max mem: 33406 +Test: [ 700/2573] eta: 0:02:38 time: 0.0804 data: 0.0014 max mem: 33406 +Test: [ 800/2573] eta: 0:02:28 time: 0.0827 data: 0.0013 max mem: 33406 +Test: [ 900/2573] eta: 0:02:20 time: 0.0822 data: 0.0014 max mem: 33406 +Test: [1000/2573] eta: 0:02:11 time: 0.0809 data: 0.0015 max mem: 33406 +Test: [1100/2573] eta: 0:02:02 time: 0.0810 data: 0.0015 max mem: 33406 +Test: [1200/2573] eta: 0:01:54 time: 0.0800 data: 0.0015 max mem: 33406 +Test: [1300/2573] eta: 0:01:45 time: 0.0793 data: 0.0013 max mem: 33406 +Test: [1400/2573] eta: 0:01:36 time: 0.0803 data: 0.0014 max mem: 33406 +Test: [1500/2573] eta: 0:01:28 time: 0.0803 data: 0.0016 max mem: 33406 +Test: [1600/2573] eta: 0:01:20 time: 0.0836 data: 0.0015 max mem: 33406 +Test: [1700/2573] eta: 0:01:11 time: 0.0779 data: 0.0013 max mem: 33406 +Test: [1800/2573] eta: 0:01:03 time: 0.0821 data: 0.0014 max mem: 33406 +Test: [1900/2573] eta: 0:00:55 time: 0.0780 data: 0.0014 max mem: 33406 +Test: [2000/2573] eta: 0:00:46 time: 0.0808 data: 0.0014 max mem: 33406 +Test: [2100/2573] eta: 0:00:38 time: 0.0818 data: 0.0014 max mem: 33406 +Test: [2200/2573] eta: 0:00:30 time: 0.0815 data: 0.0015 max mem: 33406 +Test: [2300/2573] eta: 0:00:22 time: 0.0820 data: 0.0014 max mem: 33406 +Test: [2400/2573] eta: 0:00:14 time: 0.0783 data: 0.0014 max mem: 33406 +Test: [2500/2573] eta: 0:00:05 time: 0.0802 data: 0.0015 max mem: 33406 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: Total time: 0:03:31 +Final results: +Mean IoU is 45.29 + + precision@0.5 = 46.02 + precision@0.6 = 35.33 + precision@0.7 = 25.41 + precision@0.8 = 15.95 + precision@0.9 = 4.88 + overall IoU = 46.91 + +Average object IoU 45.28854299988563 +Overall IoU 46.909114837646484 +Better epoch: 1 + +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [2] [ 0/2639] eta: 3:50:52 lr: 4.7743840590781646e-05 loss: 0.1238 (0.1238) time: 5.2490 data: 2.2133 max mem: 33406 +Epoch: [2] [ 10/2639] eta: 2:20:54 lr: 4.773955566434645e-05 loss: 0.1701 (0.1696) time: 3.2160 data: 0.2080 max mem: 33406 +Epoch: [2] [ 20/2639] eta: 2:16:17 lr: 4.773527069517758e-05 loss: 0.1790 (0.1753) time: 3.0160 data: 0.0074 max mem: 33406 +Epoch: [2] [ 30/2639] eta: 2:14:03 lr: 4.7730985683270355e-05 loss: 0.1578 (0.1734) time: 3.0097 data: 0.0076 max mem: 33406 +Epoch: [2] [ 40/2639] eta: 2:12:55 lr: 4.7726700628620086e-05 loss: 0.1449 (0.1720) time: 3.0127 data: 0.0078 max mem: 33406 +Epoch: [2] [ 50/2639] eta: 2:11:25 lr: 4.7722415531222076e-05 loss: 0.1488 (0.1696) time: 2.9880 data: 0.0077 max mem: 33406 +Epoch: [2] [ 60/2639] eta: 2:10:25 lr: 4.771813039107164e-05 loss: 0.1368 (0.1655) time: 2.9635 data: 0.0078 max mem: 33406 +Epoch: [2] [ 70/2639] eta: 2:10:38 lr: 4.771384520816407e-05 loss: 0.1326 (0.1636) time: 3.0657 data: 0.0080 max mem: 33406 +Epoch: [2] [ 80/2639] eta: 2:09:29 lr: 4.7709559982494694e-05 loss: 0.1623 (0.1708) time: 3.0423 data: 0.0082 max mem: 33406 +Epoch: [2] [ 90/2639] eta: 2:09:16 lr: 4.7705274714058804e-05 loss: 0.1703 (0.1697) time: 3.0139 data: 0.0081 max mem: 33406 +Epoch: [2] [ 100/2639] eta: 2:09:03 lr: 4.7700989402851715e-05 loss: 0.1475 (0.1679) time: 3.1053 data: 0.0077 max mem: 33406 +Epoch: [2] [ 110/2639] eta: 2:08:12 lr: 4.769670404886872e-05 loss: 0.1458 (0.1675) time: 3.0355 data: 0.0077 max mem: 33406 +Epoch: [2] [ 120/2639] eta: 2:07:45 lr: 4.7692418652105127e-05 loss: 0.1458 (0.1676) time: 3.0082 data: 0.0081 max mem: 33406 +Epoch: [2] [ 130/2639] eta: 2:07:09 lr: 4.7688133212556235e-05 loss: 0.1920 (0.1711) time: 3.0373 data: 0.0079 max mem: 33406 +Epoch: [2] [ 140/2639] eta: 2:06:57 lr: 4.7683847730217354e-05 loss: 0.1863 (0.1711) time: 3.0806 data: 0.0075 max mem: 33406 +Epoch: [2] [ 150/2639] eta: 2:06:10 lr: 4.767956220508376e-05 loss: 0.1500 (0.1698) time: 3.0445 data: 0.0080 max mem: 33406 +Epoch: [2] [ 160/2639] eta: 2:05:45 lr: 4.767527663715078e-05 loss: 0.1496 (0.1689) time: 3.0098 data: 0.0081 max mem: 33406 +Epoch: [2] [ 170/2639] eta: 2:05:09 lr: 4.76709910264137e-05 loss: 0.1577 (0.1695) time: 3.0419 data: 0.0079 max mem: 33406 +Epoch: [2] [ 180/2639] eta: 2:04:36 lr: 4.766670537286781e-05 loss: 0.1467 (0.1680) time: 3.0146 data: 0.0079 max mem: 33406 +Epoch: [2] [ 190/2639] eta: 2:03:58 lr: 4.7662419676508415e-05 loss: 0.1355 (0.1675) time: 3.0019 data: 0.0081 max mem: 33406 +Epoch: [2] [ 200/2639] eta: 2:03:28 lr: 4.765813393733081e-05 loss: 0.1433 (0.1665) time: 3.0111 data: 0.0082 max mem: 33406 +Epoch: [2] [ 210/2639] eta: 2:02:54 lr: 4.7653848155330276e-05 loss: 0.1479 (0.1658) time: 3.0250 data: 0.0077 max mem: 33406 +Epoch: [2] [ 220/2639] eta: 2:02:25 lr: 4.764956233050212e-05 loss: 0.1498 (0.1659) time: 3.0294 data: 0.0076 max mem: 33406 +Epoch: [2] [ 230/2639] eta: 2:01:52 lr: 4.7645276462841635e-05 loss: 0.1408 (0.1644) time: 3.0284 data: 0.0079 max mem: 33406 +Epoch: [2] [ 240/2639] eta: 2:01:24 lr: 4.76409905523441e-05 loss: 0.1378 (0.1645) time: 3.0327 data: 0.0081 max mem: 33406 +Epoch: [2] [ 250/2639] eta: 2:00:47 lr: 4.7636704599004816e-05 loss: 0.1610 (0.1647) time: 3.0147 data: 0.0084 max mem: 33406 +Epoch: [2] [ 260/2639] eta: 2:00:21 lr: 4.763241860281906e-05 loss: 0.1602 (0.1646) time: 3.0248 data: 0.0082 max mem: 33406 +Epoch: [2] [ 270/2639] eta: 1:59:45 lr: 4.7628132563782134e-05 loss: 0.1583 (0.1652) time: 3.0231 data: 0.0080 max mem: 33406 +Epoch: [2] [ 280/2639] eta: 1:59:10 lr: 4.762384648188931e-05 loss: 0.1528 (0.1651) time: 2.9738 data: 0.0080 max mem: 33406 +Epoch: [2] [ 290/2639] eta: 1:58:35 lr: 4.761956035713589e-05 loss: 0.1528 (0.1655) time: 2.9759 data: 0.0080 max mem: 33406 +Epoch: [2] [ 300/2639] eta: 1:58:01 lr: 4.7615274189517144e-05 loss: 0.1422 (0.1645) time: 2.9787 data: 0.0080 max mem: 33406 +Epoch: [2] [ 310/2639] eta: 1:57:29 lr: 4.761098797902837e-05 loss: 0.1548 (0.1648) time: 2.9931 data: 0.0081 max mem: 33406 +Epoch: [2] [ 320/2639] eta: 1:56:54 lr: 4.760670172566483e-05 loss: 0.1634 (0.1646) time: 2.9849 data: 0.0079 max mem: 33406 +Epoch: [2] [ 330/2639] eta: 1:56:19 lr: 4.760241542942183e-05 loss: 0.1517 (0.1641) time: 2.9559 data: 0.0079 max mem: 33406 +Epoch: [2] [ 340/2639] eta: 1:55:49 lr: 4.759812909029463e-05 loss: 0.1488 (0.1641) time: 2.9877 data: 0.0081 max mem: 33406 +Epoch: [2] [ 350/2639] eta: 1:55:18 lr: 4.759384270827853e-05 loss: 0.1429 (0.1636) time: 3.0245 data: 0.0078 max mem: 33406 +Epoch: [2] [ 360/2639] eta: 1:54:52 lr: 4.758955628336879e-05 loss: 0.1372 (0.1630) time: 3.0489 data: 0.0079 max mem: 33406 +Epoch: [2] [ 370/2639] eta: 1:54:26 lr: 4.75852698155607e-05 loss: 0.1462 (0.1628) time: 3.0918 data: 0.0082 max mem: 33406 +Epoch: [2] [ 380/2639] eta: 1:53:56 lr: 4.758098330484953e-05 loss: 0.1541 (0.1635) time: 3.0613 data: 0.0082 max mem: 33406 +Epoch: [2] [ 390/2639] eta: 1:53:24 lr: 4.757669675123057e-05 loss: 0.1776 (0.1642) time: 3.0129 data: 0.0084 max mem: 33406 +Epoch: [2] [ 400/2639] eta: 1:52:53 lr: 4.7572410154699075e-05 loss: 0.1678 (0.1638) time: 3.0082 data: 0.0083 max mem: 33406 +Epoch: [2] [ 410/2639] eta: 1:52:24 lr: 4.756812351525034e-05 loss: 0.1431 (0.1636) time: 3.0300 data: 0.0081 max mem: 33406 +Epoch: [2] [ 420/2639] eta: 1:51:52 lr: 4.756383683287961e-05 loss: 0.1482 (0.1636) time: 3.0182 data: 0.0082 max mem: 33406 +Epoch: [2] [ 430/2639] eta: 1:51:21 lr: 4.755955010758218e-05 loss: 0.1548 (0.1637) time: 2.9992 data: 0.0083 max mem: 33406 +Epoch: [2] [ 440/2639] eta: 1:50:48 lr: 4.7555263339353316e-05 loss: 0.1548 (0.1635) time: 2.9922 data: 0.0087 max mem: 33406 +Epoch: [2] [ 450/2639] eta: 1:50:24 lr: 4.7550976528188286e-05 loss: 0.1623 (0.1639) time: 3.0571 data: 0.0086 max mem: 33406 +Epoch: [2] [ 460/2639] eta: 1:49:53 lr: 4.7546689674082365e-05 loss: 0.1850 (0.1642) time: 3.0759 data: 0.0084 max mem: 33406 +Epoch: [2] [ 470/2639] eta: 1:49:27 lr: 4.75424027770308e-05 loss: 0.1555 (0.1641) time: 3.0626 data: 0.0081 max mem: 33406 +Epoch: [2] [ 480/2639] eta: 1:48:56 lr: 4.753811583702889e-05 loss: 0.1494 (0.1639) time: 3.0746 data: 0.0079 max mem: 33406 +Epoch: [2] [ 490/2639] eta: 1:48:25 lr: 4.753382885407187e-05 loss: 0.1502 (0.1642) time: 3.0162 data: 0.0078 max mem: 33406 +Epoch: [2] [ 500/2639] eta: 1:47:54 lr: 4.7529541828155034e-05 loss: 0.1709 (0.1641) time: 3.0081 data: 0.0076 max mem: 33406 +Epoch: [2] [ 510/2639] eta: 1:47:26 lr: 4.752525475927362e-05 loss: 0.1385 (0.1640) time: 3.0464 data: 0.0076 max mem: 33406 +Epoch: [2] [ 520/2639] eta: 1:47:01 lr: 4.7520967647422916e-05 loss: 0.1387 (0.1638) time: 3.1175 data: 0.0076 max mem: 33406 +Epoch: [2] [ 530/2639] eta: 1:46:29 lr: 4.751668049259816e-05 loss: 0.1387 (0.1639) time: 3.0688 data: 0.0079 max mem: 33406 +Epoch: [2] [ 540/2639] eta: 1:45:58 lr: 4.751239329479463e-05 loss: 0.1453 (0.1635) time: 2.9984 data: 0.0082 max mem: 33406 +Epoch: [2] [ 550/2639] eta: 1:45:26 lr: 4.750810605400757e-05 loss: 0.1401 (0.1631) time: 2.9977 data: 0.0079 max mem: 33406 +Epoch: [2] [ 560/2639] eta: 1:44:55 lr: 4.750381877023225e-05 loss: 0.1498 (0.1639) time: 3.0023 data: 0.0078 max mem: 33406 +Epoch: [2] [ 570/2639] eta: 1:44:24 lr: 4.7499531443463937e-05 loss: 0.1642 (0.1638) time: 3.0106 data: 0.0080 max mem: 33406 +Epoch: [2] [ 580/2639] eta: 1:43:55 lr: 4.749524407369787e-05 loss: 0.1642 (0.1643) time: 3.0258 data: 0.0083 max mem: 33406 +Epoch: [2] [ 590/2639] eta: 1:43:26 lr: 4.7490956660929315e-05 loss: 0.1505 (0.1639) time: 3.0614 data: 0.0084 max mem: 33406 +Epoch: [2] [ 600/2639] eta: 1:42:56 lr: 4.7486669205153524e-05 loss: 0.1409 (0.1638) time: 3.0561 data: 0.0082 max mem: 33406 +Epoch: [2] [ 610/2639] eta: 1:42:25 lr: 4.748238170636575e-05 loss: 0.1524 (0.1638) time: 3.0319 data: 0.0077 max mem: 33406 +Epoch: [2] [ 620/2639] eta: 1:41:54 lr: 4.7478094164561255e-05 loss: 0.1546 (0.1641) time: 3.0075 data: 0.0078 max mem: 33406 +Epoch: [2] [ 630/2639] eta: 1:41:25 lr: 4.747380657973528e-05 loss: 0.1623 (0.1642) time: 3.0327 data: 0.0079 max mem: 33406 +Epoch: [2] [ 640/2639] eta: 1:40:55 lr: 4.7469518951883076e-05 loss: 0.1623 (0.1644) time: 3.0543 data: 0.0077 max mem: 33406 +Epoch: [2] [ 650/2639] eta: 1:40:25 lr: 4.74652312809999e-05 loss: 0.1495 (0.1639) time: 3.0479 data: 0.0081 max mem: 33406 +Epoch: [2] [ 660/2639] eta: 1:39:57 lr: 4.7460943567081e-05 loss: 0.1400 (0.1639) time: 3.0784 data: 0.0079 max mem: 33406 +Epoch: [2] [ 670/2639] eta: 1:39:25 lr: 4.7456655810121616e-05 loss: 0.1450 (0.1640) time: 3.0399 data: 0.0077 max mem: 33406 +Epoch: [2] [ 680/2639] eta: 1:38:54 lr: 4.7452368010117e-05 loss: 0.1567 (0.1640) time: 2.9865 data: 0.0079 max mem: 33406 +Epoch: [2] [ 690/2639] eta: 1:38:23 lr: 4.744808016706241e-05 loss: 0.1567 (0.1645) time: 3.0017 data: 0.0079 max mem: 33406 +Epoch: [2] [ 700/2639] eta: 1:37:54 lr: 4.7443792280953076e-05 loss: 0.1567 (0.1644) time: 3.0375 data: 0.0079 max mem: 33406 +Epoch: [2] [ 710/2639] eta: 1:37:26 lr: 4.7439504351784245e-05 loss: 0.1567 (0.1645) time: 3.0947 data: 0.0078 max mem: 33406 +Epoch: [2] [ 720/2639] eta: 1:36:55 lr: 4.743521637955116e-05 loss: 0.1703 (0.1644) time: 3.0614 data: 0.0077 max mem: 33406 +Epoch: [2] [ 730/2639] eta: 1:36:23 lr: 4.743092836424907e-05 loss: 0.1707 (0.1646) time: 2.9893 data: 0.0082 max mem: 33406 +Epoch: [2] [ 740/2639] eta: 1:35:51 lr: 4.74266403058732e-05 loss: 0.1410 (0.1641) time: 2.9611 data: 0.0083 max mem: 33406 +Epoch: [2] [ 750/2639] eta: 1:35:21 lr: 4.7422352204418815e-05 loss: 0.1505 (0.1642) time: 2.9976 data: 0.0079 max mem: 33406 +Epoch: [2] [ 760/2639] eta: 1:34:50 lr: 4.7418064059881124e-05 loss: 0.1612 (0.1645) time: 3.0247 data: 0.0076 max mem: 33406 +Epoch: [2] [ 770/2639] eta: 1:34:22 lr: 4.741377587225539e-05 loss: 0.1537 (0.1648) time: 3.0651 data: 0.0075 max mem: 33406 +Epoch: [2] [ 780/2639] eta: 1:33:53 lr: 4.740948764153683e-05 loss: 0.1539 (0.1647) time: 3.0941 data: 0.0077 max mem: 33406 +Epoch: [2] [ 790/2639] eta: 1:33:21 lr: 4.74051993677207e-05 loss: 0.1539 (0.1646) time: 3.0218 data: 0.0075 max mem: 33406 +Epoch: [2] [ 800/2639] eta: 1:32:53 lr: 4.740091105080223e-05 loss: 0.1389 (0.1645) time: 3.0534 data: 0.0074 max mem: 33406 +Epoch: [2] [ 810/2639] eta: 1:32:22 lr: 4.739662269077664e-05 loss: 0.1524 (0.1644) time: 3.0505 data: 0.0075 max mem: 33406 +Epoch: [2] [ 820/2639] eta: 1:31:52 lr: 4.739233428763917e-05 loss: 0.1530 (0.1643) time: 3.0182 data: 0.0077 max mem: 33406 +Epoch: [2] [ 830/2639] eta: 1:31:21 lr: 4.7388045841385064e-05 loss: 0.1577 (0.1643) time: 3.0333 data: 0.0079 max mem: 33406 +Epoch: [2] [ 840/2639] eta: 1:30:50 lr: 4.738375735200953e-05 loss: 0.1510 (0.1640) time: 2.9910 data: 0.0080 max mem: 33406 +Epoch: [2] [ 850/2639] eta: 1:30:19 lr: 4.737946881950783e-05 loss: 0.1391 (0.1638) time: 2.9998 data: 0.0077 max mem: 33406 +Epoch: [2] [ 860/2639] eta: 1:29:49 lr: 4.7375180243875157e-05 loss: 0.1391 (0.1637) time: 3.0185 data: 0.0078 max mem: 33406 +Epoch: [2] [ 870/2639] eta: 1:29:17 lr: 4.7370891625106764e-05 loss: 0.1400 (0.1635) time: 2.9931 data: 0.0079 max mem: 33406 +Epoch: [2] [ 880/2639] eta: 1:28:45 lr: 4.736660296319787e-05 loss: 0.1410 (0.1635) time: 2.9598 data: 0.0080 max mem: 33406 +Epoch: [2] [ 890/2639] eta: 1:28:15 lr: 4.7362314258143696e-05 loss: 0.1565 (0.1637) time: 2.9932 data: 0.0078 max mem: 33406 +Epoch: [2] [ 900/2639] eta: 1:27:44 lr: 4.7358025509939474e-05 loss: 0.1452 (0.1634) time: 3.0134 data: 0.0078 max mem: 33406 +Epoch: [2] [ 910/2639] eta: 1:27:15 lr: 4.7353736718580433e-05 loss: 0.1473 (0.1636) time: 3.0224 data: 0.0080 max mem: 33406 +Epoch: [2] [ 920/2639] eta: 1:26:44 lr: 4.7349447884061785e-05 loss: 0.1773 (0.1638) time: 3.0376 data: 0.0079 max mem: 33406 +Epoch: [2] [ 930/2639] eta: 1:26:13 lr: 4.7345159006378744e-05 loss: 0.1792 (0.1639) time: 3.0070 data: 0.0076 max mem: 33406 +Epoch: [2] [ 940/2639] eta: 1:25:43 lr: 4.7340870085526554e-05 loss: 0.1482 (0.1637) time: 3.0104 data: 0.0075 max mem: 33406 +Epoch: [2] [ 950/2639] eta: 1:25:13 lr: 4.7336581121500417e-05 loss: 0.1511 (0.1639) time: 3.0224 data: 0.0077 max mem: 33406 +Epoch: [2] [ 960/2639] eta: 1:24:42 lr: 4.733229211429557e-05 loss: 0.1511 (0.1637) time: 3.0104 data: 0.0076 max mem: 33406 +Epoch: [2] [ 970/2639] eta: 1:24:12 lr: 4.7328003063907206e-05 loss: 0.1374 (0.1635) time: 3.0247 data: 0.0075 max mem: 33406 +Epoch: [2] [ 980/2639] eta: 1:23:41 lr: 4.7323713970330564e-05 loss: 0.1345 (0.1633) time: 3.0167 data: 0.0075 max mem: 33406 +Epoch: [2] [ 990/2639] eta: 1:23:10 lr: 4.731942483356084e-05 loss: 0.1365 (0.1634) time: 2.9856 data: 0.0073 max mem: 33406 +Epoch: [2] [1000/2639] eta: 1:22:39 lr: 4.731513565359327e-05 loss: 0.1559 (0.1634) time: 2.9971 data: 0.0072 max mem: 33408 +Epoch: [2] [1010/2639] eta: 1:22:09 lr: 4.731084643042305e-05 loss: 0.1470 (0.1634) time: 3.0105 data: 0.0074 max mem: 33408 +Epoch: [2] [1020/2639] eta: 1:21:38 lr: 4.730655716404541e-05 loss: 0.1408 (0.1633) time: 3.0099 data: 0.0077 max mem: 33408 +Epoch: [2] [1030/2639] eta: 1:21:08 lr: 4.730226785445554e-05 loss: 0.1476 (0.1633) time: 3.0271 data: 0.0078 max mem: 33408 +Epoch: [2] [1040/2639] eta: 1:20:38 lr: 4.729797850164866e-05 loss: 0.1510 (0.1632) time: 3.0369 data: 0.0076 max mem: 33408 +Epoch: [2] [1050/2639] eta: 1:20:09 lr: 4.7293689105619995e-05 loss: 0.1386 (0.1631) time: 3.0599 data: 0.0078 max mem: 33408 +Epoch: [2] [1060/2639] eta: 1:19:38 lr: 4.7289399666364735e-05 loss: 0.1625 (0.1632) time: 3.0426 data: 0.0079 max mem: 33408 +Epoch: [2] [1070/2639] eta: 1:19:08 lr: 4.728511018387809e-05 loss: 0.1568 (0.1630) time: 3.0036 data: 0.0078 max mem: 33408 +Epoch: [2] [1080/2639] eta: 1:18:37 lr: 4.728082065815528e-05 loss: 0.1349 (0.1629) time: 2.9986 data: 0.0076 max mem: 33408 +Epoch: [2] [1090/2639] eta: 1:18:08 lr: 4.72765310891915e-05 loss: 0.1509 (0.1629) time: 3.0609 data: 0.0078 max mem: 33408 +Epoch: [2] [1100/2639] eta: 1:17:39 lr: 4.727224147698195e-05 loss: 0.1326 (0.1628) time: 3.1275 data: 0.0080 max mem: 33408 +Epoch: [2] [1110/2639] eta: 1:17:08 lr: 4.726795182152184e-05 loss: 0.1468 (0.1627) time: 3.0326 data: 0.0078 max mem: 33408 +Epoch: [2] [1120/2639] eta: 1:16:37 lr: 4.7263662122806376e-05 loss: 0.1564 (0.1629) time: 2.9692 data: 0.0076 max mem: 33408 +Epoch: [2] [1130/2639] eta: 1:16:07 lr: 4.725937238083074e-05 loss: 0.1753 (0.1630) time: 3.0147 data: 0.0074 max mem: 33408 +Epoch: [2] [1140/2639] eta: 1:15:37 lr: 4.725508259559017e-05 loss: 0.1656 (0.1630) time: 3.0617 data: 0.0075 max mem: 33408 +Epoch: [2] [1150/2639] eta: 1:15:07 lr: 4.725079276707984e-05 loss: 0.1593 (0.1630) time: 3.0366 data: 0.0075 max mem: 33408 +Epoch: [2] [1160/2639] eta: 1:14:36 lr: 4.724650289529495e-05 loss: 0.1500 (0.1632) time: 2.9941 data: 0.0074 max mem: 33408 +Epoch: [2] [1170/2639] eta: 1:14:05 lr: 4.7242212980230693e-05 loss: 0.1485 (0.1632) time: 2.9956 data: 0.0073 max mem: 33408 +Epoch: [2] [1180/2639] eta: 1:13:36 lr: 4.7237923021882276e-05 loss: 0.1295 (0.1630) time: 3.0628 data: 0.0075 max mem: 33408 +Epoch: [2] [1190/2639] eta: 1:13:05 lr: 4.723363302024489e-05 loss: 0.1271 (0.1628) time: 3.0458 data: 0.0075 max mem: 33408 +Epoch: [2] [1200/2639] eta: 1:12:35 lr: 4.7229342975313736e-05 loss: 0.1288 (0.1626) time: 2.9938 data: 0.0073 max mem: 33408 +Epoch: [2] [1210/2639] eta: 1:12:05 lr: 4.7225052887084e-05 loss: 0.1340 (0.1626) time: 3.0170 data: 0.0073 max mem: 33408 +Epoch: [2] [1220/2639] eta: 1:11:35 lr: 4.722076275555087e-05 loss: 0.1596 (0.1626) time: 3.0328 data: 0.0072 max mem: 33408 +Epoch: [2] [1230/2639] eta: 1:11:04 lr: 4.721647258070956e-05 loss: 0.1596 (0.1627) time: 3.0306 data: 0.0073 max mem: 33408 +Epoch: [2] [1240/2639] eta: 1:10:34 lr: 4.721218236255523e-05 loss: 0.1374 (0.1626) time: 3.0343 data: 0.0075 max mem: 33408 +Epoch: [2] [1250/2639] eta: 1:10:04 lr: 4.720789210108309e-05 loss: 0.1357 (0.1626) time: 3.0271 data: 0.0077 max mem: 33408 +Epoch: [2] [1260/2639] eta: 1:09:33 lr: 4.720360179628832e-05 loss: 0.1687 (0.1627) time: 3.0065 data: 0.0074 max mem: 33408 +Epoch: [2] [1270/2639] eta: 1:09:02 lr: 4.719931144816612e-05 loss: 0.1455 (0.1624) time: 2.9954 data: 0.0072 max mem: 33408 +Epoch: [2] [1280/2639] eta: 1:08:32 lr: 4.719502105671165e-05 loss: 0.1430 (0.1627) time: 3.0038 data: 0.0072 max mem: 33408 +Epoch: [2] [1290/2639] eta: 1:08:01 lr: 4.719073062192012e-05 loss: 0.1513 (0.1626) time: 3.0078 data: 0.0071 max mem: 33408 +Epoch: [2] [1300/2639] eta: 1:07:32 lr: 4.7186440143786705e-05 loss: 0.1506 (0.1625) time: 3.0219 data: 0.0071 max mem: 33408 +Epoch: [2] [1310/2639] eta: 1:07:01 lr: 4.7182149622306586e-05 loss: 0.1403 (0.1624) time: 3.0472 data: 0.0073 max mem: 33408 +Epoch: [2] [1320/2639] eta: 1:06:31 lr: 4.717785905747495e-05 loss: 0.1309 (0.1625) time: 3.0131 data: 0.0073 max mem: 33408 +Epoch: [2] [1330/2639] eta: 1:06:01 lr: 4.717356844928698e-05 loss: 0.1739 (0.1626) time: 3.0170 data: 0.0074 max mem: 33408 +Epoch: [2] [1340/2639] eta: 1:05:30 lr: 4.7169277797737845e-05 loss: 0.1590 (0.1626) time: 3.0145 data: 0.0077 max mem: 33408 +Epoch: [2] [1350/2639] eta: 1:05:00 lr: 4.7164987102822737e-05 loss: 0.1377 (0.1624) time: 3.0216 data: 0.0074 max mem: 33408 +Epoch: [2] [1360/2639] eta: 1:04:30 lr: 4.7160696364536824e-05 loss: 0.1301 (0.1623) time: 3.0281 data: 0.0072 max mem: 33408 +Epoch: [2] [1370/2639] eta: 1:03:59 lr: 4.71564055828753e-05 loss: 0.1515 (0.1627) time: 3.0150 data: 0.0073 max mem: 33408 +Epoch: [2] [1380/2639] eta: 1:03:29 lr: 4.715211475783332e-05 loss: 0.1762 (0.1626) time: 3.0014 data: 0.0076 max mem: 33408 +Epoch: [2] [1390/2639] eta: 1:02:58 lr: 4.714782388940607e-05 loss: 0.1521 (0.1625) time: 2.9801 data: 0.0077 max mem: 33408 +Epoch: [2] [1400/2639] eta: 1:02:28 lr: 4.7143532977588725e-05 loss: 0.1212 (0.1623) time: 3.0155 data: 0.0074 max mem: 33408 +Epoch: [2] [1410/2639] eta: 1:01:57 lr: 4.7139242022376455e-05 loss: 0.1208 (0.1622) time: 3.0262 data: 0.0075 max mem: 33408 +Epoch: [2] [1420/2639] eta: 1:01:27 lr: 4.713495102376443e-05 loss: 0.1505 (0.1623) time: 3.0258 data: 0.0076 max mem: 33408 +Epoch: [2] [1430/2639] eta: 1:00:57 lr: 4.713065998174782e-05 loss: 0.1505 (0.1621) time: 3.0423 data: 0.0074 max mem: 33408 +Epoch: [2] [1440/2639] eta: 1:00:27 lr: 4.7126368896321804e-05 loss: 0.1411 (0.1620) time: 3.0201 data: 0.0076 max mem: 33408 +Epoch: [2] [1450/2639] eta: 0:59:57 lr: 4.712207776748154e-05 loss: 0.1411 (0.1619) time: 3.0193 data: 0.0080 max mem: 33408 +Epoch: [2] [1460/2639] eta: 0:59:26 lr: 4.7117786595222215e-05 loss: 0.1469 (0.1618) time: 3.0062 data: 0.0080 max mem: 33408 +Epoch: [2] [1470/2639] eta: 0:58:56 lr: 4.711349537953897e-05 loss: 0.1405 (0.1618) time: 3.0453 data: 0.0076 max mem: 33408 +Epoch: [2] [1480/2639] eta: 0:58:27 lr: 4.710920412042699e-05 loss: 0.1448 (0.1618) time: 3.1069 data: 0.0072 max mem: 33408 +Epoch: [2] [1490/2639] eta: 0:57:56 lr: 4.7104912817881424e-05 loss: 0.1448 (0.1618) time: 3.0529 data: 0.0071 max mem: 33408 +Epoch: [2] [1500/2639] eta: 0:57:26 lr: 4.7100621471897456e-05 loss: 0.1417 (0.1618) time: 3.0303 data: 0.0073 max mem: 33408 +Epoch: [2] [1510/2639] eta: 0:56:56 lr: 4.709633008247023e-05 loss: 0.1396 (0.1617) time: 3.0496 data: 0.0075 max mem: 33408 +Epoch: [2] [1520/2639] eta: 0:56:26 lr: 4.709203864959492e-05 loss: 0.1447 (0.1616) time: 3.0175 data: 0.0074 max mem: 33408 +Epoch: [2] [1530/2639] eta: 0:55:56 lr: 4.7087747173266676e-05 loss: 0.1585 (0.1617) time: 3.0258 data: 0.0075 max mem: 33408 +Epoch: [2] [1540/2639] eta: 0:55:25 lr: 4.7083455653480675e-05 loss: 0.1566 (0.1616) time: 3.0428 data: 0.0077 max mem: 33408 +Epoch: [2] [1550/2639] eta: 0:54:55 lr: 4.707916409023205e-05 loss: 0.1544 (0.1616) time: 3.0302 data: 0.0076 max mem: 33408 +Epoch: [2] [1560/2639] eta: 0:54:25 lr: 4.707487248351599e-05 loss: 0.1494 (0.1616) time: 3.0096 data: 0.0075 max mem: 33408 +Epoch: [2] [1570/2639] eta: 0:53:54 lr: 4.707058083332762e-05 loss: 0.1482 (0.1615) time: 2.9866 data: 0.0076 max mem: 33408 +Epoch: [2] [1580/2639] eta: 0:53:23 lr: 4.7066289139662116e-05 loss: 0.1358 (0.1614) time: 2.9673 data: 0.0077 max mem: 33408 +Epoch: [2] [1590/2639] eta: 0:52:53 lr: 4.7061997402514627e-05 loss: 0.1405 (0.1616) time: 2.9817 data: 0.0076 max mem: 33408 +Epoch: [2] [1600/2639] eta: 0:52:23 lr: 4.70577056218803e-05 loss: 0.1600 (0.1617) time: 3.0098 data: 0.0074 max mem: 33408 +Epoch: [2] [1610/2639] eta: 0:51:53 lr: 4.7053413797754307e-05 loss: 0.1610 (0.1617) time: 3.0303 data: 0.0074 max mem: 33408 +Epoch: [2] [1620/2639] eta: 0:51:22 lr: 4.704912193013177e-05 loss: 0.1665 (0.1618) time: 2.9986 data: 0.0076 max mem: 33408 +Epoch: [2] [1630/2639] eta: 0:50:52 lr: 4.704483001900787e-05 loss: 0.1530 (0.1621) time: 2.9984 data: 0.0074 max mem: 33408 +Epoch: [2] [1640/2639] eta: 0:50:22 lr: 4.704053806437773e-05 loss: 0.1251 (0.1621) time: 3.0551 data: 0.0073 max mem: 33408 +Epoch: [2] [1650/2639] eta: 0:49:51 lr: 4.703624606623652e-05 loss: 0.1528 (0.1623) time: 3.0158 data: 0.0073 max mem: 33408 +Epoch: [2] [1660/2639] eta: 0:49:21 lr: 4.703195402457938e-05 loss: 0.1598 (0.1623) time: 3.0115 data: 0.0072 max mem: 33408 +Epoch: [2] [1670/2639] eta: 0:48:51 lr: 4.702766193940145e-05 loss: 0.1425 (0.1622) time: 3.0326 data: 0.0073 max mem: 33408 +Epoch: [2] [1680/2639] eta: 0:48:21 lr: 4.702336981069787e-05 loss: 0.1363 (0.1622) time: 3.0969 data: 0.0078 max mem: 33408 +Epoch: [2] [1690/2639] eta: 0:47:51 lr: 4.701907763846381e-05 loss: 0.1483 (0.1621) time: 3.0836 data: 0.0078 max mem: 33408 +Epoch: [2] [1700/2639] eta: 0:47:21 lr: 4.7014785422694386e-05 loss: 0.1462 (0.1620) time: 3.0447 data: 0.0076 max mem: 33408 +Epoch: [2] [1710/2639] eta: 0:46:51 lr: 4.7010493163384755e-05 loss: 0.1405 (0.1620) time: 3.0802 data: 0.0080 max mem: 33408 +Epoch: [2] [1720/2639] eta: 0:46:20 lr: 4.700620086053005e-05 loss: 0.1569 (0.1622) time: 3.0255 data: 0.0080 max mem: 33408 +Epoch: [2] [1730/2639] eta: 0:45:50 lr: 4.700190851412542e-05 loss: 0.1651 (0.1622) time: 2.9773 data: 0.0078 max mem: 33408 +Epoch: [2] [1740/2639] eta: 0:45:19 lr: 4.699761612416599e-05 loss: 0.1516 (0.1622) time: 2.9671 data: 0.0079 max mem: 33408 +Epoch: [2] [1750/2639] eta: 0:44:49 lr: 4.699332369064692e-05 loss: 0.1719 (0.1624) time: 2.9628 data: 0.0081 max mem: 33408 +Epoch: [2] [1760/2639] eta: 0:44:18 lr: 4.698903121356333e-05 loss: 0.1834 (0.1626) time: 2.9840 data: 0.0082 max mem: 33408 +Epoch: [2] [1770/2639] eta: 0:43:48 lr: 4.698473869291036e-05 loss: 0.1734 (0.1626) time: 2.9928 data: 0.0082 max mem: 33408 +Epoch: [2] [1780/2639] eta: 0:43:17 lr: 4.6980446128683144e-05 loss: 0.1608 (0.1627) time: 2.9455 data: 0.0083 max mem: 33408 +Epoch: [2] [1790/2639] eta: 0:42:47 lr: 4.6976153520876816e-05 loss: 0.1388 (0.1626) time: 2.9245 data: 0.0083 max mem: 33408 +Epoch: [2] [1800/2639] eta: 0:42:16 lr: 4.6971860869486504e-05 loss: 0.1368 (0.1625) time: 2.9508 data: 0.0082 max mem: 33408 +Epoch: [2] [1810/2639] eta: 0:41:46 lr: 4.696756817450736e-05 loss: 0.1557 (0.1625) time: 2.9832 data: 0.0079 max mem: 33408 +Epoch: [2] [1820/2639] eta: 0:41:15 lr: 4.696327543593449e-05 loss: 0.1555 (0.1625) time: 2.9900 data: 0.0078 max mem: 33408 +Epoch: [2] [1830/2639] eta: 0:40:45 lr: 4.695898265376304e-05 loss: 0.1376 (0.1624) time: 2.9969 data: 0.0076 max mem: 33408 +Epoch: [2] [1840/2639] eta: 0:40:15 lr: 4.6954689827988126e-05 loss: 0.1334 (0.1623) time: 3.0138 data: 0.0079 max mem: 33408 +Epoch: [2] [1850/2639] eta: 0:39:44 lr: 4.6950396958604885e-05 loss: 0.1412 (0.1623) time: 3.0036 data: 0.0079 max mem: 33408 +Epoch: [2] [1860/2639] eta: 0:39:14 lr: 4.6946104045608433e-05 loss: 0.1457 (0.1624) time: 3.0267 data: 0.0077 max mem: 33408 +Epoch: [2] [1870/2639] eta: 0:38:44 lr: 4.694181108899392e-05 loss: 0.1384 (0.1622) time: 3.0312 data: 0.0083 max mem: 33408 +Epoch: [2] [1880/2639] eta: 0:38:14 lr: 4.693751808875644e-05 loss: 0.1464 (0.1624) time: 3.0284 data: 0.0089 max mem: 33408 +Epoch: [2] [1890/2639] eta: 0:37:44 lr: 4.6933225044891135e-05 loss: 0.1487 (0.1624) time: 3.0503 data: 0.0085 max mem: 33408 +Epoch: [2] [1900/2639] eta: 0:37:13 lr: 4.692893195739312e-05 loss: 0.1485 (0.1626) time: 3.0264 data: 0.0082 max mem: 33408 +Epoch: [2] [1910/2639] eta: 0:36:43 lr: 4.692463882625753e-05 loss: 0.1628 (0.1626) time: 2.9904 data: 0.0080 max mem: 33408 +Epoch: [2] [1920/2639] eta: 0:36:13 lr: 4.692034565147946e-05 loss: 0.1642 (0.1627) time: 3.0275 data: 0.0077 max mem: 33408 +Epoch: [2] [1930/2639] eta: 0:35:42 lr: 4.6916052433054056e-05 loss: 0.1600 (0.1626) time: 3.0091 data: 0.0075 max mem: 33408 +Epoch: [2] [1940/2639] eta: 0:35:12 lr: 4.691175917097642e-05 loss: 0.1312 (0.1625) time: 2.9824 data: 0.0075 max mem: 33408 +Epoch: [2] [1950/2639] eta: 0:34:42 lr: 4.690746586524167e-05 loss: 0.1308 (0.1624) time: 3.0586 data: 0.0081 max mem: 33408 +Epoch: [2] [1960/2639] eta: 0:34:12 lr: 4.6903172515844934e-05 loss: 0.1282 (0.1623) time: 3.0667 data: 0.0084 max mem: 33408 +Epoch: [2] [1970/2639] eta: 0:33:42 lr: 4.689887912278131e-05 loss: 0.1151 (0.1621) time: 3.0404 data: 0.0082 max mem: 33408 +Epoch: [2] [1980/2639] eta: 0:33:12 lr: 4.689458568604593e-05 loss: 0.1323 (0.1621) time: 3.0293 data: 0.0080 max mem: 33408 +Epoch: [2] [1990/2639] eta: 0:32:41 lr: 4.689029220563388e-05 loss: 0.1632 (0.1623) time: 3.0219 data: 0.0075 max mem: 33408 +Epoch: [2] [2000/2639] eta: 0:32:11 lr: 4.688599868154031e-05 loss: 0.1561 (0.1623) time: 3.0004 data: 0.0073 max mem: 33408 +Epoch: [2] [2010/2639] eta: 0:31:41 lr: 4.68817051137603e-05 loss: 0.1610 (0.1623) time: 3.0323 data: 0.0075 max mem: 33408 +Epoch: [2] [2020/2639] eta: 0:31:11 lr: 4.6877411502288975e-05 loss: 0.1610 (0.1623) time: 3.0512 data: 0.0079 max mem: 33408 +Epoch: [2] [2030/2639] eta: 0:30:41 lr: 4.6873117847121435e-05 loss: 0.1533 (0.1623) time: 3.0391 data: 0.0079 max mem: 33408 +Epoch: [2] [2040/2639] eta: 0:30:11 lr: 4.68688241482528e-05 loss: 0.1451 (0.1622) time: 3.0509 data: 0.0078 max mem: 33408 +Epoch: [2] [2050/2639] eta: 0:29:40 lr: 4.686453040567816e-05 loss: 0.1387 (0.1621) time: 3.0174 data: 0.0075 max mem: 33408 +Epoch: [2] [2060/2639] eta: 0:29:10 lr: 4.686023661939264e-05 loss: 0.1319 (0.1620) time: 2.9829 data: 0.0074 max mem: 33408 +Epoch: [2] [2070/2639] eta: 0:28:40 lr: 4.685594278939132e-05 loss: 0.1319 (0.1619) time: 2.9977 data: 0.0076 max mem: 33408 +Epoch: [2] [2080/2639] eta: 0:28:09 lr: 4.685164891566933e-05 loss: 0.1255 (0.1618) time: 3.0105 data: 0.0079 max mem: 33408 +Epoch: [2] [2090/2639] eta: 0:27:39 lr: 4.684735499822176e-05 loss: 0.1255 (0.1617) time: 3.0215 data: 0.0079 max mem: 33408 +Epoch: [2] [2100/2639] eta: 0:27:09 lr: 4.684306103704371e-05 loss: 0.1274 (0.1617) time: 3.0131 data: 0.0074 max mem: 33408 +Epoch: [2] [2110/2639] eta: 0:26:38 lr: 4.683876703213028e-05 loss: 0.1258 (0.1616) time: 2.9871 data: 0.0074 max mem: 33408 +Epoch: [2] [2120/2639] eta: 0:26:08 lr: 4.683447298347658e-05 loss: 0.1201 (0.1614) time: 3.0037 data: 0.0079 max mem: 33408 +Epoch: [2] [2130/2639] eta: 0:25:38 lr: 4.6830178891077696e-05 loss: 0.1428 (0.1615) time: 3.0030 data: 0.0077 max mem: 33408 +Epoch: [2] [2140/2639] eta: 0:25:08 lr: 4.682588475492873e-05 loss: 0.1830 (0.1617) time: 3.0067 data: 0.0073 max mem: 33408 +Epoch: [2] [2150/2639] eta: 0:24:37 lr: 4.682159057502478e-05 loss: 0.1499 (0.1616) time: 3.0176 data: 0.0075 max mem: 33408 +Epoch: [2] [2160/2639] eta: 0:24:07 lr: 4.681729635136095e-05 loss: 0.1403 (0.1616) time: 3.0097 data: 0.0078 max mem: 33408 +Epoch: [2] [2170/2639] eta: 0:23:37 lr: 4.6813002083932304e-05 loss: 0.1689 (0.1617) time: 3.0019 data: 0.0080 max mem: 33408 +Epoch: [2] [2180/2639] eta: 0:23:07 lr: 4.680870777273396e-05 loss: 0.1729 (0.1616) time: 3.0122 data: 0.0080 max mem: 33408 +Epoch: [2] [2190/2639] eta: 0:22:37 lr: 4.680441341776102e-05 loss: 0.1413 (0.1616) time: 3.0364 data: 0.0081 max mem: 33408 +Epoch: [2] [2200/2639] eta: 0:22:06 lr: 4.680011901900854e-05 loss: 0.1581 (0.1617) time: 3.0313 data: 0.0077 max mem: 33408 +Epoch: [2] [2210/2639] eta: 0:21:36 lr: 4.6795824576471646e-05 loss: 0.1581 (0.1616) time: 2.9977 data: 0.0076 max mem: 33408 +Epoch: [2] [2220/2639] eta: 0:21:06 lr: 4.67915300901454e-05 loss: 0.1508 (0.1617) time: 3.0213 data: 0.0075 max mem: 33408 +Epoch: [2] [2230/2639] eta: 0:20:36 lr: 4.6787235560024914e-05 loss: 0.1523 (0.1617) time: 3.0076 data: 0.0077 max mem: 33408 +Epoch: [2] [2240/2639] eta: 0:20:06 lr: 4.678294098610525e-05 loss: 0.1523 (0.1617) time: 3.0545 data: 0.0078 max mem: 33408 +Epoch: [2] [2250/2639] eta: 0:19:35 lr: 4.677864636838151e-05 loss: 0.1776 (0.1618) time: 3.0976 data: 0.0078 max mem: 33408 +Epoch: [2] [2260/2639] eta: 0:19:05 lr: 4.6774351706848774e-05 loss: 0.1865 (0.1620) time: 3.0187 data: 0.0083 max mem: 33408 +Epoch: [2] [2270/2639] eta: 0:18:35 lr: 4.677005700150213e-05 loss: 0.1737 (0.1621) time: 3.0536 data: 0.0084 max mem: 33408 +Epoch: [2] [2280/2639] eta: 0:18:05 lr: 4.676576225233665e-05 loss: 0.1518 (0.1621) time: 3.0453 data: 0.0081 max mem: 33408 +Epoch: [2] [2290/2639] eta: 0:17:34 lr: 4.676146745934743e-05 loss: 0.1700 (0.1622) time: 3.0138 data: 0.0078 max mem: 33408 +Epoch: [2] [2300/2639] eta: 0:17:04 lr: 4.675717262252954e-05 loss: 0.1500 (0.1621) time: 3.0385 data: 0.0077 max mem: 33408 +Epoch: [2] [2310/2639] eta: 0:16:34 lr: 4.675287774187806e-05 loss: 0.1359 (0.1620) time: 3.0400 data: 0.0077 max mem: 33408 +Epoch: [2] [2320/2639] eta: 0:16:04 lr: 4.674858281738807e-05 loss: 0.1359 (0.1620) time: 3.0405 data: 0.0078 max mem: 33408 +Epoch: [2] [2330/2639] eta: 0:15:34 lr: 4.6744287849054656e-05 loss: 0.1615 (0.1620) time: 3.0286 data: 0.0079 max mem: 33408 +Epoch: [2] [2340/2639] eta: 0:15:03 lr: 4.6739992836872876e-05 loss: 0.1559 (0.1619) time: 3.0458 data: 0.0080 max mem: 33408 +Epoch: [2] [2350/2639] eta: 0:14:33 lr: 4.673569778083783e-05 loss: 0.1473 (0.1619) time: 3.0379 data: 0.0077 max mem: 33408 +Epoch: [2] [2360/2639] eta: 0:14:03 lr: 4.673140268094456e-05 loss: 0.1473 (0.1619) time: 3.0249 data: 0.0079 max mem: 33408 +Epoch: [2] [2370/2639] eta: 0:13:33 lr: 4.672710753718817e-05 loss: 0.1635 (0.1619) time: 3.0094 data: 0.0081 max mem: 33408 +Epoch: [2] [2380/2639] eta: 0:13:02 lr: 4.672281234956371e-05 loss: 0.1356 (0.1618) time: 2.9840 data: 0.0079 max mem: 33408 +Epoch: [2] [2390/2639] eta: 0:12:32 lr: 4.6718517118066266e-05 loss: 0.1356 (0.1617) time: 2.9953 data: 0.0078 max mem: 33408 +Epoch: [2] [2400/2639] eta: 0:12:02 lr: 4.6714221842690905e-05 loss: 0.1403 (0.1617) time: 3.0075 data: 0.0076 max mem: 33408 +Epoch: [2] [2410/2639] eta: 0:11:32 lr: 4.670992652343269e-05 loss: 0.1470 (0.1617) time: 3.0281 data: 0.0072 max mem: 33408 +Epoch: [2] [2420/2639] eta: 0:11:01 lr: 4.6705631160286694e-05 loss: 0.1200 (0.1616) time: 3.0240 data: 0.0072 max mem: 33408 +Epoch: [2] [2430/2639] eta: 0:10:31 lr: 4.670133575324798e-05 loss: 0.1200 (0.1615) time: 3.0149 data: 0.0075 max mem: 33408 +Epoch: [2] [2440/2639] eta: 0:10:01 lr: 4.6697040302311615e-05 loss: 0.1537 (0.1616) time: 3.0193 data: 0.0076 max mem: 33408 +Epoch: [2] [2450/2639] eta: 0:09:31 lr: 4.669274480747266e-05 loss: 0.1533 (0.1615) time: 3.0448 data: 0.0079 max mem: 33408 +Epoch: [2] [2460/2639] eta: 0:09:01 lr: 4.668844926872619e-05 loss: 0.1533 (0.1615) time: 3.0509 data: 0.0080 max mem: 33408 +Epoch: [2] [2470/2639] eta: 0:08:30 lr: 4.668415368606726e-05 loss: 0.1588 (0.1615) time: 3.0137 data: 0.0075 max mem: 33408 +Epoch: [2] [2480/2639] eta: 0:08:00 lr: 4.667985805949093e-05 loss: 0.1606 (0.1617) time: 2.9733 data: 0.0074 max mem: 33408 +Epoch: [2] [2490/2639] eta: 0:07:30 lr: 4.667556238899226e-05 loss: 0.1520 (0.1615) time: 3.0210 data: 0.0078 max mem: 33408 +Epoch: [2] [2500/2639] eta: 0:07:00 lr: 4.6671266674566314e-05 loss: 0.1393 (0.1616) time: 3.0408 data: 0.0077 max mem: 33408 +Epoch: [2] [2510/2639] eta: 0:06:29 lr: 4.6666970916208146e-05 loss: 0.1543 (0.1616) time: 3.0313 data: 0.0073 max mem: 33408 +Epoch: [2] [2520/2639] eta: 0:05:59 lr: 4.666267511391282e-05 loss: 0.1493 (0.1616) time: 3.0424 data: 0.0073 max mem: 33408 +Epoch: [2] [2530/2639] eta: 0:05:29 lr: 4.6658379267675384e-05 loss: 0.1333 (0.1615) time: 2.9991 data: 0.0079 max mem: 33408 +Epoch: [2] [2540/2639] eta: 0:04:59 lr: 4.66540833774909e-05 loss: 0.1404 (0.1615) time: 2.9931 data: 0.0082 max mem: 33408 +Epoch: [2] [2550/2639] eta: 0:04:29 lr: 4.664978744335441e-05 loss: 0.1512 (0.1615) time: 3.0357 data: 0.0081 max mem: 33408 +Epoch: [2] [2560/2639] eta: 0:03:58 lr: 4.664549146526099e-05 loss: 0.1716 (0.1616) time: 3.0248 data: 0.0079 max mem: 33408 +Epoch: [2] [2570/2639] eta: 0:03:28 lr: 4.664119544320566e-05 loss: 0.1621 (0.1616) time: 3.0247 data: 0.0075 max mem: 33408 +Epoch: [2] [2580/2639] eta: 0:02:58 lr: 4.6636899377183505e-05 loss: 0.1430 (0.1615) time: 3.0306 data: 0.0079 max mem: 33408 +Epoch: [2] [2590/2639] eta: 0:02:28 lr: 4.663260326718955e-05 loss: 0.1428 (0.1615) time: 3.0061 data: 0.0078 max mem: 33408 +Epoch: [2] [2600/2639] eta: 0:01:57 lr: 4.662830711321886e-05 loss: 0.1497 (0.1616) time: 3.0073 data: 0.0077 max mem: 33408 +Epoch: [2] [2610/2639] eta: 0:01:27 lr: 4.6624010915266466e-05 loss: 0.1334 (0.1615) time: 3.0017 data: 0.0080 max mem: 33408 +Epoch: [2] [2620/2639] eta: 0:00:57 lr: 4.6619714673327424e-05 loss: 0.1402 (0.1616) time: 3.0291 data: 0.0079 max mem: 33408 +Epoch: [2] [2630/2639] eta: 0:00:27 lr: 4.6615418387396776e-05 loss: 0.1602 (0.1615) time: 3.0610 data: 0.0076 max mem: 33408 +Epoch: [2] Total time: 2:12:58 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 2:26:21 time: 3.4130 data: 3.3165 max mem: 33408 +Test: [ 100/2573] eta: 0:04:35 time: 0.0782 data: 0.0014 max mem: 33408 +Test: [ 200/2573] eta: 0:03:47 time: 0.0797 data: 0.0016 max mem: 33408 +Test: [ 300/2573] eta: 0:03:25 time: 0.0816 data: 0.0015 max mem: 33408 +Test: [ 400/2573] eta: 0:03:10 time: 0.0809 data: 0.0014 max mem: 33408 +Test: [ 500/2573] eta: 0:02:58 time: 0.0802 data: 0.0015 max mem: 33408 +Test: [ 600/2573] eta: 0:02:48 time: 0.0795 data: 0.0015 max mem: 33408 +Test: [ 700/2573] eta: 0:02:38 time: 0.0803 data: 0.0014 max mem: 33408 +Test: [ 800/2573] eta: 0:02:29 time: 0.0830 data: 0.0014 max mem: 33408 +Test: [ 900/2573] eta: 0:02:20 time: 0.0805 data: 0.0014 max mem: 33408 +Test: [1000/2573] eta: 0:02:11 time: 0.0797 data: 0.0014 max mem: 33408 +Test: [1100/2573] eta: 0:02:02 time: 0.0805 data: 0.0015 max mem: 33408 +Test: [1200/2573] eta: 0:01:54 time: 0.0804 data: 0.0014 max mem: 33408 +Test: [1300/2573] eta: 0:01:45 time: 0.0811 data: 0.0014 max mem: 33408 +Test: [1400/2573] eta: 0:01:37 time: 0.0791 data: 0.0014 max mem: 33408 +Test: [1500/2573] eta: 0:01:28 time: 0.0814 data: 0.0016 max mem: 33408 +Test: [1600/2573] eta: 0:01:20 time: 0.0835 data: 0.0014 max mem: 33408 +Test: [1700/2573] eta: 0:01:12 time: 0.0789 data: 0.0014 max mem: 33408 +Test: [1800/2573] eta: 0:01:03 time: 0.0817 data: 0.0014 max mem: 33408 +Test: [1900/2573] eta: 0:00:55 time: 0.0782 data: 0.0014 max mem: 33408 +Test: [2000/2573] eta: 0:00:47 time: 0.0816 data: 0.0014 max mem: 33408 +Test: [2100/2573] eta: 0:00:38 time: 0.0836 data: 0.0014 max mem: 33408 +Test: [2200/2573] eta: 0:00:30 time: 0.0820 data: 0.0014 max mem: 33408 +Test: [2300/2573] eta: 0:00:22 time: 0.0836 data: 0.0014 max mem: 33408 +Test: [2400/2573] eta: 0:00:14 time: 0.0774 data: 0.0014 max mem: 33408 +Test: [2500/2573] eta: 0:00:05 time: 0.0809 data: 0.0016 max mem: 33408 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: Total time: 0:03:31 +Final results: +Mean IoU is 49.04 + + precision@0.5 = 53.82 + precision@0.6 = 45.75 + precision@0.7 = 35.87 + precision@0.8 = 23.16 + precision@0.9 = 7.62 + overall IoU = 50.29 + +Average object IoU 49.04420976428872 +Overall IoU 50.293060302734375 +Better epoch: 2 + +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [3] [ 0/2639] eta: 4:17:42 lr: 4.6611551692442284e-05 loss: 0.1014 (0.1014) time: 5.8593 data: 2.6608 max mem: 33408 +Epoch: [3] [ 10/2639] eta: 2:22:54 lr: 4.660725532291394e-05 loss: 0.1099 (0.1468) time: 3.2615 data: 0.2491 max mem: 33408 +Epoch: [3] [ 20/2639] eta: 2:16:25 lr: 4.660295890937962e-05 loss: 0.1099 (0.1306) time: 2.9887 data: 0.0077 max mem: 33408 +Epoch: [3] [ 30/2639] eta: 2:14:44 lr: 4.6598662451834365e-05 loss: 0.1040 (0.1279) time: 3.0090 data: 0.0080 max mem: 33408 +Epoch: [3] [ 40/2639] eta: 2:13:25 lr: 4.659436595027322e-05 loss: 0.1292 (0.1331) time: 3.0329 data: 0.0084 max mem: 33408 +Epoch: [3] [ 50/2639] eta: 2:12:06 lr: 4.659006940469121e-05 loss: 0.1298 (0.1322) time: 3.0045 data: 0.0080 max mem: 33408 +Epoch: [3] [ 60/2639] eta: 2:11:00 lr: 4.658577281508339e-05 loss: 0.1193 (0.1322) time: 2.9818 data: 0.0076 max mem: 33408 +Epoch: [3] [ 70/2639] eta: 2:10:28 lr: 4.658147618144478e-05 loss: 0.1201 (0.1324) time: 3.0112 data: 0.0074 max mem: 33408 +Epoch: [3] [ 80/2639] eta: 2:10:00 lr: 4.6577179503770434e-05 loss: 0.1350 (0.1344) time: 3.0494 data: 0.0074 max mem: 33408 +Epoch: [3] [ 90/2639] eta: 2:09:43 lr: 4.657288278205537e-05 loss: 0.1336 (0.1338) time: 3.0753 data: 0.0076 max mem: 33408 +Epoch: [3] [ 100/2639] eta: 2:08:52 lr: 4.656858601629464e-05 loss: 0.1280 (0.1336) time: 3.0336 data: 0.0075 max mem: 33408 +Epoch: [3] [ 110/2639] eta: 2:08:30 lr: 4.656428920648326e-05 loss: 0.1225 (0.1351) time: 3.0266 data: 0.0075 max mem: 33408 +Epoch: [3] [ 120/2639] eta: 2:07:36 lr: 4.655999235261628e-05 loss: 0.1214 (0.1340) time: 3.0096 data: 0.0075 max mem: 33408 +Epoch: [3] [ 130/2639] eta: 2:07:11 lr: 4.655569545468871e-05 loss: 0.1404 (0.1364) time: 3.0028 data: 0.0075 max mem: 33408 +Epoch: [3] [ 140/2639] eta: 2:06:32 lr: 4.6551398512695596e-05 loss: 0.1404 (0.1366) time: 3.0314 data: 0.0074 max mem: 33408 +Epoch: [3] [ 150/2639] eta: 2:05:58 lr: 4.654710152663195e-05 loss: 0.1206 (0.1352) time: 3.0046 data: 0.0073 max mem: 33408 +Epoch: [3] [ 160/2639] eta: 2:05:27 lr: 4.6542804496492816e-05 loss: 0.1171 (0.1360) time: 3.0248 data: 0.0072 max mem: 33408 +Epoch: [3] [ 170/2639] eta: 2:04:45 lr: 4.6538507422273206e-05 loss: 0.1342 (0.1369) time: 2.9932 data: 0.0072 max mem: 33408 +Epoch: [3] [ 180/2639] eta: 2:04:20 lr: 4.653421030396817e-05 loss: 0.1414 (0.1382) time: 3.0120 data: 0.0073 max mem: 33408 +Epoch: [3] [ 190/2639] eta: 2:03:38 lr: 4.65299131415727e-05 loss: 0.1359 (0.1372) time: 3.0068 data: 0.0079 max mem: 33408 +Epoch: [3] [ 200/2639] eta: 2:03:14 lr: 4.652561593508185e-05 loss: 0.1202 (0.1378) time: 3.0124 data: 0.0081 max mem: 33408 +Epoch: [3] [ 210/2639] eta: 2:02:53 lr: 4.652131868449061e-05 loss: 0.1338 (0.1388) time: 3.0970 data: 0.0077 max mem: 33408 +Epoch: [3] [ 220/2639] eta: 2:02:17 lr: 4.651702138979403e-05 loss: 0.1328 (0.1387) time: 3.0473 data: 0.0077 max mem: 33408 +Epoch: [3] [ 230/2639] eta: 2:01:43 lr: 4.651272405098711e-05 loss: 0.1248 (0.1391) time: 2.9917 data: 0.0075 max mem: 33408 +Epoch: [3] [ 240/2639] eta: 2:01:12 lr: 4.6508426668064875e-05 loss: 0.1381 (0.1392) time: 3.0142 data: 0.0075 max mem: 33408 +Epoch: [3] [ 250/2639] eta: 2:00:38 lr: 4.650412924102235e-05 loss: 0.1357 (0.1390) time: 3.0069 data: 0.0080 max mem: 33408 +Epoch: [3] [ 260/2639] eta: 2:00:06 lr: 4.6499831769854554e-05 loss: 0.1292 (0.1386) time: 3.0013 data: 0.0083 max mem: 33408 +Epoch: [3] [ 270/2639] eta: 1:59:34 lr: 4.649553425455649e-05 loss: 0.1228 (0.1385) time: 3.0117 data: 0.0080 max mem: 33408 +Epoch: [3] [ 280/2639] eta: 1:59:04 lr: 4.649123669512317e-05 loss: 0.1307 (0.1383) time: 3.0206 data: 0.0077 max mem: 33408 +Epoch: [3] [ 290/2639] eta: 1:58:31 lr: 4.648693909154962e-05 loss: 0.1307 (0.1389) time: 3.0136 data: 0.0080 max mem: 33408 +Epoch: [3] [ 300/2639] eta: 1:58:09 lr: 4.648264144383086e-05 loss: 0.1203 (0.1386) time: 3.0645 data: 0.0083 max mem: 33408 +Epoch: [3] [ 310/2639] eta: 1:57:43 lr: 4.647834375196187e-05 loss: 0.0970 (0.1378) time: 3.1150 data: 0.0080 max mem: 33408 +Epoch: [3] [ 320/2639] eta: 1:57:09 lr: 4.6474046015937686e-05 loss: 0.1224 (0.1388) time: 3.0370 data: 0.0080 max mem: 33408 +Epoch: [3] [ 330/2639] eta: 1:56:40 lr: 4.646974823575332e-05 loss: 0.1329 (0.1388) time: 3.0161 data: 0.0080 max mem: 33408 +Epoch: [3] [ 340/2639] eta: 1:56:08 lr: 4.646545041140377e-05 loss: 0.1430 (0.1396) time: 3.0286 data: 0.0079 max mem: 33408 +Epoch: [3] [ 350/2639] eta: 1:55:36 lr: 4.646115254288403e-05 loss: 0.1432 (0.1399) time: 3.0032 data: 0.0079 max mem: 33408 +Epoch: [3] [ 360/2639] eta: 1:55:03 lr: 4.645685463018913e-05 loss: 0.1407 (0.1396) time: 2.9914 data: 0.0078 max mem: 33408 +Epoch: [3] [ 370/2639] eta: 1:54:29 lr: 4.6452556673314075e-05 loss: 0.1339 (0.1396) time: 2.9813 data: 0.0083 max mem: 33408 +Epoch: [3] [ 380/2639] eta: 1:53:59 lr: 4.6448258672253844e-05 loss: 0.1339 (0.1396) time: 3.0057 data: 0.0086 max mem: 33408 +Epoch: [3] [ 390/2639] eta: 1:53:33 lr: 4.644396062700346e-05 loss: 0.1538 (0.1398) time: 3.0662 data: 0.0083 max mem: 33408 +Epoch: [3] [ 400/2639] eta: 1:52:58 lr: 4.643966253755792e-05 loss: 0.1516 (0.1397) time: 3.0194 data: 0.0077 max mem: 33408 +Epoch: [3] [ 410/2639] eta: 1:52:23 lr: 4.643536440391222e-05 loss: 0.1516 (0.1401) time: 2.9359 data: 0.0078 max mem: 33408 +Epoch: [3] [ 420/2639] eta: 1:51:56 lr: 4.643106622606137e-05 loss: 0.1449 (0.1402) time: 3.0137 data: 0.0076 max mem: 33408 +Epoch: [3] [ 430/2639] eta: 1:51:23 lr: 4.642676800400036e-05 loss: 0.1386 (0.1406) time: 3.0310 data: 0.0073 max mem: 33408 +Epoch: [3] [ 440/2639] eta: 1:50:52 lr: 4.6422469737724186e-05 loss: 0.1386 (0.1403) time: 2.9970 data: 0.0077 max mem: 33408 +Epoch: [3] [ 450/2639] eta: 1:50:22 lr: 4.641817142722785e-05 loss: 0.1240 (0.1400) time: 3.0223 data: 0.0077 max mem: 33408 +Epoch: [3] [ 460/2639] eta: 1:49:52 lr: 4.6413873072506345e-05 loss: 0.1255 (0.1399) time: 3.0304 data: 0.0074 max mem: 33408 +Epoch: [3] [ 470/2639] eta: 1:49:22 lr: 4.6409574673554676e-05 loss: 0.1424 (0.1402) time: 3.0355 data: 0.0081 max mem: 33408 +Epoch: [3] [ 480/2639] eta: 1:48:47 lr: 4.6405276230367803e-05 loss: 0.1363 (0.1401) time: 2.9716 data: 0.0086 max mem: 33408 +Epoch: [3] [ 490/2639] eta: 1:48:16 lr: 4.640097774294075e-05 loss: 0.1316 (0.1402) time: 2.9554 data: 0.0079 max mem: 33408 +Epoch: [3] [ 500/2639] eta: 1:47:45 lr: 4.639667921126851e-05 loss: 0.1363 (0.1403) time: 3.0050 data: 0.0077 max mem: 33408 +Epoch: [3] [ 510/2639] eta: 1:47:11 lr: 4.639238063534605e-05 loss: 0.1373 (0.1403) time: 2.9791 data: 0.0077 max mem: 33408 +Epoch: [3] [ 520/2639] eta: 1:46:41 lr: 4.638808201516837e-05 loss: 0.1223 (0.1402) time: 2.9736 data: 0.0076 max mem: 33408 +Epoch: [3] [ 530/2639] eta: 1:46:07 lr: 4.638378335073046e-05 loss: 0.1223 (0.1403) time: 2.9659 data: 0.0078 max mem: 33408 +Epoch: [3] [ 540/2639] eta: 1:45:37 lr: 4.6379484642027306e-05 loss: 0.1425 (0.1404) time: 2.9841 data: 0.0076 max mem: 33408 +Epoch: [3] [ 550/2639] eta: 1:45:07 lr: 4.637518588905389e-05 loss: 0.1371 (0.1404) time: 3.0225 data: 0.0078 max mem: 33408 +Epoch: [3] [ 560/2639] eta: 1:44:38 lr: 4.6370887091805196e-05 loss: 0.1357 (0.1403) time: 3.0372 data: 0.0082 max mem: 33408 +Epoch: [3] [ 570/2639] eta: 1:44:08 lr: 4.63665882502762e-05 loss: 0.1545 (0.1412) time: 3.0401 data: 0.0080 max mem: 33408 +Epoch: [3] [ 580/2639] eta: 1:43:39 lr: 4.636228936446191e-05 loss: 0.1691 (0.1414) time: 3.0341 data: 0.0084 max mem: 33408 +Epoch: [3] [ 590/2639] eta: 1:43:08 lr: 4.635799043435728e-05 loss: 0.1268 (0.1413) time: 3.0368 data: 0.0084 max mem: 33408 +Epoch: [3] [ 600/2639] eta: 1:42:40 lr: 4.635369145995731e-05 loss: 0.1117 (0.1411) time: 3.0496 data: 0.0079 max mem: 33408 +Epoch: [3] [ 610/2639] eta: 1:42:10 lr: 4.634939244125695e-05 loss: 0.1175 (0.1411) time: 3.0454 data: 0.0077 max mem: 33408 +Epoch: [3] [ 620/2639] eta: 1:41:41 lr: 4.6345093378251215e-05 loss: 0.1240 (0.1409) time: 3.0455 data: 0.0075 max mem: 33408 +Epoch: [3] [ 630/2639] eta: 1:41:12 lr: 4.6340794270935054e-05 loss: 0.1271 (0.1409) time: 3.0602 data: 0.0080 max mem: 33408 +Epoch: [3] [ 640/2639] eta: 1:40:41 lr: 4.6336495119303465e-05 loss: 0.1447 (0.1411) time: 3.0182 data: 0.0081 max mem: 33408 +Epoch: [3] [ 650/2639] eta: 1:40:10 lr: 4.63321959233514e-05 loss: 0.1327 (0.1411) time: 2.9966 data: 0.0079 max mem: 33408 +Epoch: [3] [ 660/2639] eta: 1:39:39 lr: 4.632789668307385e-05 loss: 0.1327 (0.1412) time: 2.9980 data: 0.0078 max mem: 33408 +Epoch: [3] [ 670/2639] eta: 1:39:09 lr: 4.6323597398465776e-05 loss: 0.1466 (0.1417) time: 3.0128 data: 0.0075 max mem: 33408 +Epoch: [3] [ 680/2639] eta: 1:38:41 lr: 4.631929806952216e-05 loss: 0.1474 (0.1417) time: 3.0597 data: 0.0076 max mem: 33408 +Epoch: [3] [ 690/2639] eta: 1:38:09 lr: 4.631499869623795e-05 loss: 0.1410 (0.1417) time: 3.0376 data: 0.0078 max mem: 33408 +Epoch: [3] [ 700/2639] eta: 1:37:38 lr: 4.6310699278608145e-05 loss: 0.1351 (0.1418) time: 2.9791 data: 0.0079 max mem: 33408 +Epoch: [3] [ 710/2639] eta: 1:37:06 lr: 4.6306399816627695e-05 loss: 0.1415 (0.1421) time: 2.9705 data: 0.0081 max mem: 33408 +Epoch: [3] [ 720/2639] eta: 1:36:36 lr: 4.630210031029157e-05 loss: 0.1472 (0.1423) time: 2.9921 data: 0.0084 max mem: 33408 +Epoch: [3] [ 730/2639] eta: 1:36:06 lr: 4.629780075959474e-05 loss: 0.1472 (0.1422) time: 3.0186 data: 0.0081 max mem: 33408 +Epoch: [3] [ 740/2639] eta: 1:35:35 lr: 4.629350116453217e-05 loss: 0.1383 (0.1422) time: 3.0117 data: 0.0076 max mem: 33408 +Epoch: [3] [ 750/2639] eta: 1:35:06 lr: 4.628920152509881e-05 loss: 0.1326 (0.1420) time: 3.0287 data: 0.0075 max mem: 33408 +Epoch: [3] [ 760/2639] eta: 1:34:35 lr: 4.628490184128965e-05 loss: 0.1299 (0.1420) time: 3.0284 data: 0.0076 max mem: 33408 +Epoch: [3] [ 770/2639] eta: 1:34:06 lr: 4.628060211309962e-05 loss: 0.1299 (0.1419) time: 3.0482 data: 0.0078 max mem: 33408 +Epoch: [3] [ 780/2639] eta: 1:33:35 lr: 4.62763023405237e-05 loss: 0.1259 (0.1419) time: 3.0319 data: 0.0078 max mem: 33408 +Epoch: [3] [ 790/2639] eta: 1:33:05 lr: 4.6272002523556844e-05 loss: 0.1344 (0.1418) time: 3.0027 data: 0.0080 max mem: 33408 +Epoch: [3] [ 800/2639] eta: 1:32:33 lr: 4.626770266219401e-05 loss: 0.1412 (0.1420) time: 2.9857 data: 0.0082 max mem: 33408 +Epoch: [3] [ 810/2639] eta: 1:32:04 lr: 4.626340275643016e-05 loss: 0.1482 (0.1418) time: 2.9943 data: 0.0080 max mem: 33408 +Epoch: [3] [ 820/2639] eta: 1:31:33 lr: 4.625910280626025e-05 loss: 0.1136 (0.1416) time: 3.0252 data: 0.0079 max mem: 33408 +Epoch: [3] [ 830/2639] eta: 1:31:03 lr: 4.6254802811679224e-05 loss: 0.1183 (0.1417) time: 3.0178 data: 0.0079 max mem: 33408 +Epoch: [3] [ 840/2639] eta: 1:30:32 lr: 4.625050277268204e-05 loss: 0.1357 (0.1416) time: 3.0085 data: 0.0077 max mem: 33408 +Epoch: [3] [ 850/2639] eta: 1:30:02 lr: 4.6246202689263665e-05 loss: 0.1299 (0.1414) time: 3.0150 data: 0.0079 max mem: 33408 +Epoch: [3] [ 860/2639] eta: 1:29:31 lr: 4.624190256141903e-05 loss: 0.1218 (0.1413) time: 3.0081 data: 0.0077 max mem: 33408 +Epoch: [3] [ 870/2639] eta: 1:29:02 lr: 4.6237602389143095e-05 loss: 0.1266 (0.1416) time: 3.0275 data: 0.0076 max mem: 33408 +Epoch: [3] [ 880/2639] eta: 1:28:32 lr: 4.623330217243082e-05 loss: 0.1296 (0.1415) time: 3.0490 data: 0.0080 max mem: 33408 +Epoch: [3] [ 890/2639] eta: 1:28:02 lr: 4.6229001911277134e-05 loss: 0.1217 (0.1414) time: 3.0197 data: 0.0086 max mem: 33408 +Epoch: [3] [ 900/2639] eta: 1:27:30 lr: 4.622470160567699e-05 loss: 0.1293 (0.1414) time: 2.9804 data: 0.0086 max mem: 33408 +Epoch: [3] [ 910/2639] eta: 1:27:00 lr: 4.6220401255625346e-05 loss: 0.1414 (0.1415) time: 2.9792 data: 0.0080 max mem: 33408 +Epoch: [3] [ 920/2639] eta: 1:26:30 lr: 4.6216100861117126e-05 loss: 0.1292 (0.1415) time: 3.0337 data: 0.0076 max mem: 33408 +Epoch: [3] [ 930/2639] eta: 1:26:00 lr: 4.6211800422147306e-05 loss: 0.1181 (0.1414) time: 3.0309 data: 0.0080 max mem: 33408 +Epoch: [3] [ 940/2639] eta: 1:25:29 lr: 4.62074999387108e-05 loss: 0.1253 (0.1414) time: 2.9984 data: 0.0079 max mem: 33408 +Epoch: [3] [ 950/2639] eta: 1:24:58 lr: 4.620319941080256e-05 loss: 0.1304 (0.1414) time: 2.9867 data: 0.0076 max mem: 33408 +Epoch: [3] [ 960/2639] eta: 1:24:29 lr: 4.619889883841752e-05 loss: 0.1315 (0.1416) time: 3.0228 data: 0.0074 max mem: 33408 +Epoch: [3] [ 970/2639] eta: 1:23:57 lr: 4.619459822155063e-05 loss: 0.1387 (0.1415) time: 3.0023 data: 0.0076 max mem: 33408 +Epoch: [3] [ 980/2639] eta: 1:23:27 lr: 4.619029756019682e-05 loss: 0.1311 (0.1414) time: 2.9893 data: 0.0081 max mem: 33408 +Epoch: [3] [ 990/2639] eta: 1:22:57 lr: 4.618599685435104e-05 loss: 0.1242 (0.1413) time: 3.0300 data: 0.0083 max mem: 33408 +Epoch: [3] [1000/2639] eta: 1:22:28 lr: 4.6181696104008213e-05 loss: 0.1281 (0.1415) time: 3.0463 data: 0.0083 max mem: 33408 +Epoch: [3] [1010/2639] eta: 1:21:58 lr: 4.617739530916329e-05 loss: 0.1428 (0.1415) time: 3.0419 data: 0.0082 max mem: 33408 +Epoch: [3] [1020/2639] eta: 1:21:26 lr: 4.617309446981118e-05 loss: 0.1503 (0.1418) time: 2.9874 data: 0.0078 max mem: 33408 +Epoch: [3] [1030/2639] eta: 1:20:57 lr: 4.616879358594683e-05 loss: 0.1477 (0.1419) time: 2.9949 data: 0.0076 max mem: 33408 +Epoch: [3] [1040/2639] eta: 1:20:26 lr: 4.6164492657565175e-05 loss: 0.1347 (0.1420) time: 3.0044 data: 0.0078 max mem: 33408 +Epoch: [3] [1050/2639] eta: 1:19:55 lr: 4.616019168466115e-05 loss: 0.1392 (0.1420) time: 2.9876 data: 0.0081 max mem: 33408 +Epoch: [3] [1060/2639] eta: 1:19:25 lr: 4.6155890667229674e-05 loss: 0.1224 (0.1417) time: 3.0207 data: 0.0082 max mem: 33408 +Epoch: [3] [1070/2639] eta: 1:18:56 lr: 4.615158960526568e-05 loss: 0.1158 (0.1418) time: 3.0558 data: 0.0080 max mem: 33408 +Epoch: [3] [1080/2639] eta: 1:18:26 lr: 4.6147288498764094e-05 loss: 0.1266 (0.1418) time: 3.0415 data: 0.0081 max mem: 33408 +Epoch: [3] [1090/2639] eta: 1:17:56 lr: 4.614298734771984e-05 loss: 0.1308 (0.1417) time: 3.0271 data: 0.0081 max mem: 33408 +Epoch: [3] [1100/2639] eta: 1:17:26 lr: 4.613868615212785e-05 loss: 0.1308 (0.1418) time: 3.0263 data: 0.0078 max mem: 33408 +Epoch: [3] [1110/2639] eta: 1:16:54 lr: 4.613438491198305e-05 loss: 0.1371 (0.1420) time: 2.9800 data: 0.0081 max mem: 33408 +Epoch: [3] [1120/2639] eta: 1:16:24 lr: 4.613008362728035e-05 loss: 0.1447 (0.1421) time: 2.9848 data: 0.0079 max mem: 33408 +Epoch: [3] [1130/2639] eta: 1:15:54 lr: 4.612578229801468e-05 loss: 0.1447 (0.1421) time: 3.0268 data: 0.0074 max mem: 33408 +Epoch: [3] [1140/2639] eta: 1:15:24 lr: 4.6121480924180966e-05 loss: 0.1492 (0.1424) time: 3.0314 data: 0.0074 max mem: 33408 +Epoch: [3] [1150/2639] eta: 1:14:55 lr: 4.611717950577412e-05 loss: 0.1497 (0.1424) time: 3.0538 data: 0.0075 max mem: 33408 +Epoch: [3] [1160/2639] eta: 1:14:25 lr: 4.6112878042789065e-05 loss: 0.1168 (0.1423) time: 3.0518 data: 0.0078 max mem: 33408 +Epoch: [3] [1170/2639] eta: 1:13:55 lr: 4.6108576535220714e-05 loss: 0.1195 (0.1423) time: 3.0441 data: 0.0079 max mem: 33408 +Epoch: [3] [1180/2639] eta: 1:13:26 lr: 4.6104274983063986e-05 loss: 0.1522 (0.1424) time: 3.0826 data: 0.0076 max mem: 33408 +Epoch: [3] [1190/2639] eta: 1:12:56 lr: 4.60999733863138e-05 loss: 0.1420 (0.1423) time: 3.0768 data: 0.0083 max mem: 33408 +Epoch: [3] [1200/2639] eta: 1:12:26 lr: 4.609567174496507e-05 loss: 0.1133 (0.1422) time: 3.0238 data: 0.0082 max mem: 33408 +Epoch: [3] [1210/2639] eta: 1:11:56 lr: 4.60913700590127e-05 loss: 0.1208 (0.1422) time: 3.0304 data: 0.0075 max mem: 33408 +Epoch: [3] [1220/2639] eta: 1:11:25 lr: 4.608706832845161e-05 loss: 0.1266 (0.1421) time: 3.0254 data: 0.0076 max mem: 33408 +Epoch: [3] [1230/2639] eta: 1:10:55 lr: 4.608276655327671e-05 loss: 0.1271 (0.1422) time: 2.9972 data: 0.0079 max mem: 33408 +Epoch: [3] [1240/2639] eta: 1:10:25 lr: 4.6078464733482906e-05 loss: 0.1256 (0.1422) time: 3.0102 data: 0.0078 max mem: 33408 +Epoch: [3] [1250/2639] eta: 1:09:55 lr: 4.607416286906511e-05 loss: 0.1322 (0.1422) time: 3.0184 data: 0.0077 max mem: 33408 +Epoch: [3] [1260/2639] eta: 1:09:24 lr: 4.606986096001823e-05 loss: 0.1332 (0.1422) time: 3.0265 data: 0.0078 max mem: 33408 +Epoch: [3] [1270/2639] eta: 1:08:55 lr: 4.606555900633718e-05 loss: 0.1398 (0.1423) time: 3.0426 data: 0.0076 max mem: 33408 +Epoch: [3] [1280/2639] eta: 1:08:24 lr: 4.606125700801684e-05 loss: 0.1406 (0.1423) time: 3.0228 data: 0.0077 max mem: 33408 +Epoch: [3] [1290/2639] eta: 1:07:54 lr: 4.6056954965052146e-05 loss: 0.1414 (0.1425) time: 3.0216 data: 0.0077 max mem: 33408 +Epoch: [3] [1300/2639] eta: 1:07:24 lr: 4.605265287743798e-05 loss: 0.1435 (0.1425) time: 3.0548 data: 0.0079 max mem: 33408 +Epoch: [3] [1310/2639] eta: 1:06:54 lr: 4.6048350745169254e-05 loss: 0.1428 (0.1427) time: 3.0049 data: 0.0081 max mem: 33408 +Epoch: [3] [1320/2639] eta: 1:06:22 lr: 4.604404856824086e-05 loss: 0.1382 (0.1427) time: 2.9489 data: 0.0079 max mem: 33408 +Epoch: [3] [1330/2639] eta: 1:05:52 lr: 4.603974634664771e-05 loss: 0.1291 (0.1427) time: 2.9682 data: 0.0075 max mem: 33408 +Epoch: [3] [1340/2639] eta: 1:05:22 lr: 4.603544408038469e-05 loss: 0.1334 (0.1426) time: 2.9961 data: 0.0076 max mem: 33408 +Epoch: [3] [1350/2639] eta: 1:04:51 lr: 4.6031141769446714e-05 loss: 0.1163 (0.1425) time: 2.9830 data: 0.0076 max mem: 33408 +Epoch: [3] [1360/2639] eta: 1:04:21 lr: 4.602683941382865e-05 loss: 0.1163 (0.1424) time: 3.0260 data: 0.0073 max mem: 33408 +Epoch: [3] [1370/2639] eta: 1:03:52 lr: 4.602253701352543e-05 loss: 0.1300 (0.1425) time: 3.0721 data: 0.0074 max mem: 33408 +Epoch: [3] [1380/2639] eta: 1:03:21 lr: 4.601823456853192e-05 loss: 0.1420 (0.1426) time: 3.0360 data: 0.0075 max mem: 33408 +Epoch: [3] [1390/2639] eta: 1:02:52 lr: 4.601393207884303e-05 loss: 0.1537 (0.1427) time: 3.0462 data: 0.0078 max mem: 33408 +Epoch: [3] [1400/2639] eta: 1:02:22 lr: 4.6009629544453636e-05 loss: 0.1453 (0.1427) time: 3.0542 data: 0.0081 max mem: 33408 +Epoch: [3] [1410/2639] eta: 1:01:51 lr: 4.600532696535864e-05 loss: 0.1441 (0.1427) time: 3.0315 data: 0.0077 max mem: 33408 +Epoch: [3] [1420/2639] eta: 1:01:21 lr: 4.600102434155293e-05 loss: 0.1263 (0.1426) time: 2.9857 data: 0.0074 max mem: 33408 +Epoch: [3] [1430/2639] eta: 1:00:50 lr: 4.5996721673031404e-05 loss: 0.1304 (0.1426) time: 2.9751 data: 0.0073 max mem: 33408 +Epoch: [3] [1440/2639] eta: 1:00:20 lr: 4.599241895978893e-05 loss: 0.1328 (0.1425) time: 3.0123 data: 0.0076 max mem: 33408 +Epoch: [3] [1450/2639] eta: 0:59:50 lr: 4.598811620182041e-05 loss: 0.1318 (0.1424) time: 3.0305 data: 0.0077 max mem: 33408 +Epoch: [3] [1460/2639] eta: 0:59:20 lr: 4.598381339912071e-05 loss: 0.1318 (0.1426) time: 3.0412 data: 0.0075 max mem: 33408 +Epoch: [3] [1470/2639] eta: 0:58:50 lr: 4.5979510551684745e-05 loss: 0.1288 (0.1426) time: 3.0540 data: 0.0073 max mem: 33408 +Epoch: [3] [1480/2639] eta: 0:58:20 lr: 4.597520765950737e-05 loss: 0.1310 (0.1425) time: 3.0522 data: 0.0077 max mem: 33408 +Epoch: [3] [1490/2639] eta: 0:57:50 lr: 4.597090472258348e-05 loss: 0.1326 (0.1426) time: 3.0322 data: 0.0079 max mem: 33408 +Epoch: [3] [1500/2639] eta: 0:57:20 lr: 4.596660174090796e-05 loss: 0.1332 (0.1425) time: 3.0505 data: 0.0076 max mem: 33408 +Epoch: [3] [1510/2639] eta: 0:56:49 lr: 4.596229871447568e-05 loss: 0.1280 (0.1425) time: 3.0105 data: 0.0078 max mem: 33408 +Epoch: [3] [1520/2639] eta: 0:56:19 lr: 4.5957995643281526e-05 loss: 0.1368 (0.1426) time: 2.9662 data: 0.0079 max mem: 33408 +Epoch: [3] [1530/2639] eta: 0:55:49 lr: 4.5953692527320366e-05 loss: 0.1191 (0.1425) time: 2.9956 data: 0.0079 max mem: 33408 +Epoch: [3] [1540/2639] eta: 0:55:18 lr: 4.5949389366587085e-05 loss: 0.1090 (0.1424) time: 3.0115 data: 0.0077 max mem: 33408 +Epoch: [3] [1550/2639] eta: 0:54:48 lr: 4.594508616107655e-05 loss: 0.1090 (0.1422) time: 3.0095 data: 0.0072 max mem: 33408 +Epoch: [3] [1560/2639] eta: 0:54:18 lr: 4.594078291078365e-05 loss: 0.1099 (0.1422) time: 3.0028 data: 0.0074 max mem: 33408 +Epoch: [3] [1570/2639] eta: 0:53:47 lr: 4.593647961570324e-05 loss: 0.1275 (0.1423) time: 2.9981 data: 0.0076 max mem: 33408 +Epoch: [3] [1580/2639] eta: 0:53:17 lr: 4.5932176275830216e-05 loss: 0.1325 (0.1424) time: 3.0298 data: 0.0074 max mem: 33408 +Epoch: [3] [1590/2639] eta: 0:52:47 lr: 4.592787289115942e-05 loss: 0.1401 (0.1425) time: 3.0375 data: 0.0078 max mem: 33408 +Epoch: [3] [1600/2639] eta: 0:52:17 lr: 4.5923569461685734e-05 loss: 0.1457 (0.1424) time: 3.0152 data: 0.0077 max mem: 33408 +Epoch: [3] [1610/2639] eta: 0:51:47 lr: 4.591926598740403e-05 loss: 0.1371 (0.1424) time: 3.0024 data: 0.0071 max mem: 33408 +Epoch: [3] [1620/2639] eta: 0:51:17 lr: 4.591496246830918e-05 loss: 0.1328 (0.1426) time: 3.0152 data: 0.0070 max mem: 33408 +Epoch: [3] [1630/2639] eta: 0:50:46 lr: 4.591065890439604e-05 loss: 0.1278 (0.1425) time: 3.0100 data: 0.0071 max mem: 33408 +Epoch: [3] [1640/2639] eta: 0:50:16 lr: 4.5906355295659474e-05 loss: 0.1167 (0.1425) time: 2.9813 data: 0.0071 max mem: 33408 +Epoch: [3] [1650/2639] eta: 0:49:46 lr: 4.590205164209435e-05 loss: 0.1466 (0.1427) time: 3.0098 data: 0.0071 max mem: 33408 +Epoch: [3] [1660/2639] eta: 0:49:16 lr: 4.589774794369554e-05 loss: 0.1575 (0.1427) time: 3.0953 data: 0.0071 max mem: 33408 +Epoch: [3] [1670/2639] eta: 0:48:46 lr: 4.589344420045789e-05 loss: 0.1446 (0.1431) time: 3.0732 data: 0.0075 max mem: 33408 +Epoch: [3] [1680/2639] eta: 0:48:16 lr: 4.588914041237627e-05 loss: 0.1529 (0.1432) time: 3.0166 data: 0.0074 max mem: 33408 +Epoch: [3] [1690/2639] eta: 0:47:45 lr: 4.588483657944554e-05 loss: 0.1460 (0.1432) time: 3.0035 data: 0.0072 max mem: 33408 +Epoch: [3] [1700/2639] eta: 0:47:15 lr: 4.5880532701660555e-05 loss: 0.1255 (0.1430) time: 3.0035 data: 0.0076 max mem: 33408 +Epoch: [3] [1710/2639] eta: 0:46:45 lr: 4.587622877901617e-05 loss: 0.0994 (0.1429) time: 3.0120 data: 0.0077 max mem: 33408 +Epoch: [3] [1720/2639] eta: 0:46:15 lr: 4.587192481150725e-05 loss: 0.1365 (0.1430) time: 2.9967 data: 0.0075 max mem: 33408 +Epoch: [3] [1730/2639] eta: 0:45:44 lr: 4.586762079912864e-05 loss: 0.1358 (0.1429) time: 3.0138 data: 0.0071 max mem: 33408 +Epoch: [3] [1740/2639] eta: 0:45:14 lr: 4.58633167418752e-05 loss: 0.1251 (0.1429) time: 3.0087 data: 0.0071 max mem: 33408 +Epoch: [3] [1750/2639] eta: 0:44:44 lr: 4.585901263974178e-05 loss: 0.1251 (0.1429) time: 3.0312 data: 0.0072 max mem: 33408 +Epoch: [3] [1760/2639] eta: 0:44:14 lr: 4.585470849272324e-05 loss: 0.1235 (0.1428) time: 3.0452 data: 0.0075 max mem: 33408 +Epoch: [3] [1770/2639] eta: 0:43:44 lr: 4.585040430081442e-05 loss: 0.1418 (0.1429) time: 3.0217 data: 0.0075 max mem: 33408 +Epoch: [3] [1780/2639] eta: 0:43:13 lr: 4.584610006401017e-05 loss: 0.1442 (0.1428) time: 2.9856 data: 0.0073 max mem: 33408 +Epoch: [3] [1790/2639] eta: 0:42:43 lr: 4.5841795782305344e-05 loss: 0.1273 (0.1428) time: 3.0066 data: 0.0075 max mem: 33408 +Epoch: [3] [1800/2639] eta: 0:42:13 lr: 4.5837491455694786e-05 loss: 0.1245 (0.1427) time: 3.0207 data: 0.0075 max mem: 33408 +Epoch: [3] [1810/2639] eta: 0:41:43 lr: 4.583318708417335e-05 loss: 0.1245 (0.1427) time: 3.0241 data: 0.0074 max mem: 33408 +Epoch: [3] [1820/2639] eta: 0:41:13 lr: 4.582888266773586e-05 loss: 0.1423 (0.1428) time: 3.0315 data: 0.0075 max mem: 33408 +Epoch: [3] [1830/2639] eta: 0:40:42 lr: 4.582457820637718e-05 loss: 0.1534 (0.1429) time: 3.0151 data: 0.0074 max mem: 33408 +Epoch: [3] [1840/2639] eta: 0:40:12 lr: 4.582027370009215e-05 loss: 0.1398 (0.1429) time: 3.0100 data: 0.0077 max mem: 33408 +Epoch: [3] [1850/2639] eta: 0:39:42 lr: 4.581596914887561e-05 loss: 0.1341 (0.1429) time: 2.9914 data: 0.0080 max mem: 33408 +Epoch: [3] [1860/2639] eta: 0:39:11 lr: 4.581166455272238e-05 loss: 0.1299 (0.1428) time: 2.9824 data: 0.0077 max mem: 33408 +Epoch: [3] [1870/2639] eta: 0:38:41 lr: 4.580735991162733e-05 loss: 0.1309 (0.1429) time: 3.0124 data: 0.0076 max mem: 33408 +Epoch: [3] [1880/2639] eta: 0:38:11 lr: 4.580305522558528e-05 loss: 0.1326 (0.1430) time: 3.0254 data: 0.0077 max mem: 33408 +Epoch: [3] [1890/2639] eta: 0:37:41 lr: 4.5798750494591085e-05 loss: 0.1289 (0.1430) time: 3.0724 data: 0.0076 max mem: 33408 +Epoch: [3] [1900/2639] eta: 0:37:11 lr: 4.579444571863956e-05 loss: 0.1481 (0.1431) time: 3.1127 data: 0.0076 max mem: 33408 +Epoch: [3] [1910/2639] eta: 0:36:41 lr: 4.579014089772555e-05 loss: 0.1444 (0.1430) time: 3.0372 data: 0.0077 max mem: 33408 +Epoch: [3] [1920/2639] eta: 0:36:11 lr: 4.5785836031843875e-05 loss: 0.1200 (0.1429) time: 3.0231 data: 0.0076 max mem: 33408 +Epoch: [3] [1930/2639] eta: 0:35:41 lr: 4.5781531120989394e-05 loss: 0.1351 (0.1430) time: 3.0086 data: 0.0075 max mem: 33408 +Epoch: [3] [1940/2639] eta: 0:35:10 lr: 4.5777226165156914e-05 loss: 0.1449 (0.1430) time: 2.9657 data: 0.0076 max mem: 33408 +Epoch: [3] [1950/2639] eta: 0:34:40 lr: 4.577292116434128e-05 loss: 0.1266 (0.1428) time: 2.9755 data: 0.0080 max mem: 33408 +Epoch: [3] [1960/2639] eta: 0:34:09 lr: 4.576861611853731e-05 loss: 0.1150 (0.1427) time: 2.9681 data: 0.0081 max mem: 33408 +Epoch: [3] [1970/2639] eta: 0:33:39 lr: 4.576431102773984e-05 loss: 0.1311 (0.1426) time: 2.9614 data: 0.0078 max mem: 33408 +Epoch: [3] [1980/2639] eta: 0:33:09 lr: 4.5760005891943694e-05 loss: 0.1220 (0.1426) time: 2.9965 data: 0.0081 max mem: 33408 +Epoch: [3] [1990/2639] eta: 0:32:39 lr: 4.5755700711143695e-05 loss: 0.1235 (0.1426) time: 2.9842 data: 0.0082 max mem: 33408 +Epoch: [3] [2000/2639] eta: 0:32:08 lr: 4.575139548533468e-05 loss: 0.1362 (0.1426) time: 2.9584 data: 0.0080 max mem: 33408 +Epoch: [3] [2010/2639] eta: 0:31:38 lr: 4.5747090214511453e-05 loss: 0.1310 (0.1426) time: 2.9919 data: 0.0083 max mem: 33408 +Epoch: [3] [2020/2639] eta: 0:31:08 lr: 4.574278489866885e-05 loss: 0.1303 (0.1425) time: 3.0068 data: 0.0083 max mem: 33408 +Epoch: [3] [2030/2639] eta: 0:30:38 lr: 4.573847953780169e-05 loss: 0.1198 (0.1425) time: 3.0608 data: 0.0078 max mem: 33408 +Epoch: [3] [2040/2639] eta: 0:30:08 lr: 4.573417413190479e-05 loss: 0.1198 (0.1425) time: 3.1049 data: 0.0077 max mem: 33408 +Epoch: [3] [2050/2639] eta: 0:29:38 lr: 4.572986868097297e-05 loss: 0.1271 (0.1426) time: 3.0425 data: 0.0077 max mem: 33408 +Epoch: [3] [2060/2639] eta: 0:29:08 lr: 4.572556318500105e-05 loss: 0.1477 (0.1426) time: 3.0300 data: 0.0076 max mem: 33408 +Epoch: [3] [2070/2639] eta: 0:28:37 lr: 4.572125764398384e-05 loss: 0.1370 (0.1426) time: 3.0432 data: 0.0080 max mem: 33408 +Epoch: [3] [2080/2639] eta: 0:28:07 lr: 4.5716952057916154e-05 loss: 0.1359 (0.1425) time: 3.0175 data: 0.0082 max mem: 33408 +Epoch: [3] [2090/2639] eta: 0:27:37 lr: 4.571264642679282e-05 loss: 0.1083 (0.1424) time: 2.9801 data: 0.0082 max mem: 33408 +Epoch: [3] [2100/2639] eta: 0:27:07 lr: 4.570834075060865e-05 loss: 0.1193 (0.1424) time: 3.0388 data: 0.0083 max mem: 33408 +Epoch: [3] [2110/2639] eta: 0:26:37 lr: 4.570403502935843e-05 loss: 0.1302 (0.1423) time: 3.0402 data: 0.0082 max mem: 33408 +Epoch: [3] [2120/2639] eta: 0:26:06 lr: 4.569972926303701e-05 loss: 0.1320 (0.1423) time: 3.0209 data: 0.0080 max mem: 33408 +Epoch: [3] [2130/2639] eta: 0:25:36 lr: 4.5695423451639166e-05 loss: 0.1417 (0.1423) time: 3.0612 data: 0.0081 max mem: 33408 +Epoch: [3] [2140/2639] eta: 0:25:06 lr: 4.5691117595159725e-05 loss: 0.1253 (0.1423) time: 3.0120 data: 0.0083 max mem: 33408 +Epoch: [3] [2150/2639] eta: 0:24:36 lr: 4.568681169359349e-05 loss: 0.1257 (0.1422) time: 3.0342 data: 0.0081 max mem: 33408 +Epoch: [3] [2160/2639] eta: 0:24:06 lr: 4.568250574693527e-05 loss: 0.1278 (0.1421) time: 3.0427 data: 0.0078 max mem: 33408 +Epoch: [3] [2170/2639] eta: 0:23:36 lr: 4.5678199755179864e-05 loss: 0.1238 (0.1421) time: 3.0171 data: 0.0082 max mem: 33408 +Epoch: [3] [2180/2639] eta: 0:23:06 lr: 4.567389371832208e-05 loss: 0.1238 (0.1422) time: 3.0511 data: 0.0082 max mem: 33408 +Epoch: [3] [2190/2639] eta: 0:22:35 lr: 4.5669587636356715e-05 loss: 0.1275 (0.1422) time: 3.0322 data: 0.0075 max mem: 33408 +Epoch: [3] [2200/2639] eta: 0:22:05 lr: 4.5665281509278586e-05 loss: 0.1083 (0.1420) time: 3.0250 data: 0.0078 max mem: 33408 +Epoch: [3] [2210/2639] eta: 0:21:35 lr: 4.5660975337082474e-05 loss: 0.1020 (0.1419) time: 3.0495 data: 0.0080 max mem: 33408 +Epoch: [3] [2220/2639] eta: 0:21:05 lr: 4.565666911976319e-05 loss: 0.1265 (0.1419) time: 3.0798 data: 0.0078 max mem: 33408 +Epoch: [3] [2230/2639] eta: 0:20:35 lr: 4.565236285731553e-05 loss: 0.1416 (0.1419) time: 3.0703 data: 0.0078 max mem: 33408 +Epoch: [3] [2240/2639] eta: 0:20:05 lr: 4.5648056549734283e-05 loss: 0.1542 (0.1422) time: 3.0190 data: 0.0075 max mem: 33408 +Epoch: [3] [2250/2639] eta: 0:19:34 lr: 4.564375019701427e-05 loss: 0.1676 (0.1422) time: 3.0226 data: 0.0074 max mem: 33408 +Epoch: [3] [2260/2639] eta: 0:19:04 lr: 4.563944379915026e-05 loss: 0.1240 (0.1421) time: 3.0260 data: 0.0075 max mem: 33408 +Epoch: [3] [2270/2639] eta: 0:18:34 lr: 4.563513735613706e-05 loss: 0.1284 (0.1422) time: 3.0201 data: 0.0077 max mem: 33408 +Epoch: [3] [2280/2639] eta: 0:18:04 lr: 4.5630830867969446e-05 loss: 0.1284 (0.1422) time: 3.0198 data: 0.0078 max mem: 33408 +Epoch: [3] [2290/2639] eta: 0:17:34 lr: 4.562652433464224e-05 loss: 0.1293 (0.1423) time: 2.9951 data: 0.0078 max mem: 33408 +Epoch: [3] [2300/2639] eta: 0:17:03 lr: 4.56222177561502e-05 loss: 0.1367 (0.1423) time: 3.0067 data: 0.0078 max mem: 33408 +Epoch: [3] [2310/2639] eta: 0:16:33 lr: 4.5617911132488136e-05 loss: 0.1276 (0.1423) time: 3.0808 data: 0.0074 max mem: 33408 +Epoch: [3] [2320/2639] eta: 0:16:03 lr: 4.561360446365083e-05 loss: 0.1381 (0.1423) time: 3.0579 data: 0.0077 max mem: 33408 +Epoch: [3] [2330/2639] eta: 0:15:33 lr: 4.5609297749633065e-05 loss: 0.1252 (0.1423) time: 3.0270 data: 0.0077 max mem: 33408 +Epoch: [3] [2340/2639] eta: 0:15:03 lr: 4.560499099042962e-05 loss: 0.1315 (0.1424) time: 3.0414 data: 0.0079 max mem: 33408 +Epoch: [3] [2350/2639] eta: 0:14:32 lr: 4.560068418603531e-05 loss: 0.1417 (0.1424) time: 2.9947 data: 0.0079 max mem: 33408 +Epoch: [3] [2360/2639] eta: 0:14:02 lr: 4.559637733644488e-05 loss: 0.1362 (0.1424) time: 2.9599 data: 0.0075 max mem: 33408 +Epoch: [3] [2370/2639] eta: 0:13:32 lr: 4.559207044165314e-05 loss: 0.1291 (0.1423) time: 3.0403 data: 0.0076 max mem: 33408 +Epoch: [3] [2380/2639] eta: 0:13:02 lr: 4.558776350165485e-05 loss: 0.1291 (0.1423) time: 3.0692 data: 0.0078 max mem: 33408 +Epoch: [3] [2390/2639] eta: 0:12:32 lr: 4.558345651644481e-05 loss: 0.1250 (0.1424) time: 2.9984 data: 0.0080 max mem: 33408 +Epoch: [3] [2400/2639] eta: 0:12:01 lr: 4.557914948601779e-05 loss: 0.1102 (0.1423) time: 2.9997 data: 0.0080 max mem: 33408 +Epoch: [3] [2410/2639] eta: 0:11:31 lr: 4.557484241036856e-05 loss: 0.1128 (0.1423) time: 3.0140 data: 0.0078 max mem: 33408 +Epoch: [3] [2420/2639] eta: 0:11:01 lr: 4.55705352894919e-05 loss: 0.1364 (0.1423) time: 3.0115 data: 0.0077 max mem: 33408 +Epoch: [3] [2430/2639] eta: 0:10:31 lr: 4.556622812338261e-05 loss: 0.1288 (0.1422) time: 2.9813 data: 0.0077 max mem: 33408 +Epoch: [3] [2440/2639] eta: 0:10:01 lr: 4.5561920912035424e-05 loss: 0.1354 (0.1424) time: 3.0297 data: 0.0073 max mem: 33408 +Epoch: [3] [2450/2639] eta: 0:09:30 lr: 4.555761365544514e-05 loss: 0.1464 (0.1423) time: 3.0357 data: 0.0076 max mem: 33408 +Epoch: [3] [2460/2639] eta: 0:09:00 lr: 4.555330635360652e-05 loss: 0.1464 (0.1423) time: 2.9957 data: 0.0077 max mem: 33408 +Epoch: [3] [2470/2639] eta: 0:08:30 lr: 4.5548999006514345e-05 loss: 0.1210 (0.1422) time: 3.0211 data: 0.0075 max mem: 33408 +Epoch: [3] [2480/2639] eta: 0:08:00 lr: 4.5544691614163376e-05 loss: 0.1227 (0.1423) time: 3.0196 data: 0.0074 max mem: 33408 +Epoch: [3] [2490/2639] eta: 0:07:30 lr: 4.5540384176548376e-05 loss: 0.1446 (0.1423) time: 3.0585 data: 0.0074 max mem: 33408 +Epoch: [3] [2500/2639] eta: 0:06:59 lr: 4.5536076693664134e-05 loss: 0.1299 (0.1423) time: 3.0927 data: 0.0076 max mem: 33408 +Epoch: [3] [2510/2639] eta: 0:06:29 lr: 4.55317691655054e-05 loss: 0.1389 (0.1423) time: 3.0551 data: 0.0076 max mem: 33408 +Epoch: [3] [2520/2639] eta: 0:05:59 lr: 4.552746159206693e-05 loss: 0.1397 (0.1423) time: 3.0324 data: 0.0078 max mem: 33408 +Epoch: [3] [2530/2639] eta: 0:05:29 lr: 4.55231539733435e-05 loss: 0.1303 (0.1424) time: 3.0330 data: 0.0079 max mem: 33408 +Epoch: [3] [2540/2639] eta: 0:04:59 lr: 4.551884630932988e-05 loss: 0.1317 (0.1424) time: 3.0469 data: 0.0076 max mem: 33408 +Epoch: [3] [2550/2639] eta: 0:04:28 lr: 4.5514538600020816e-05 loss: 0.1400 (0.1424) time: 3.0411 data: 0.0077 max mem: 33408 +Epoch: [3] [2560/2639] eta: 0:03:58 lr: 4.551023084541108e-05 loss: 0.1305 (0.1424) time: 3.0266 data: 0.0075 max mem: 33408 +Epoch: [3] [2570/2639] eta: 0:03:28 lr: 4.5505923045495424e-05 loss: 0.1227 (0.1424) time: 3.0042 data: 0.0081 max mem: 33408 +Epoch: [3] [2580/2639] eta: 0:02:58 lr: 4.5501615200268614e-05 loss: 0.1227 (0.1424) time: 2.9670 data: 0.0084 max mem: 33408 +Epoch: [3] [2590/2639] eta: 0:02:28 lr: 4.549730730972539e-05 loss: 0.1385 (0.1425) time: 2.9893 data: 0.0075 max mem: 33408 +Epoch: [3] [2600/2639] eta: 0:01:57 lr: 4.5492999373860526e-05 loss: 0.1393 (0.1425) time: 3.0179 data: 0.0074 max mem: 33408 +Epoch: [3] [2610/2639] eta: 0:01:27 lr: 4.548869139266877e-05 loss: 0.1393 (0.1426) time: 3.0316 data: 0.0075 max mem: 33408 +Epoch: [3] [2620/2639] eta: 0:00:57 lr: 4.5484383366144873e-05 loss: 0.1387 (0.1426) time: 3.0207 data: 0.0073 max mem: 33408 +Epoch: [3] [2630/2639] eta: 0:00:27 lr: 4.548007529428358e-05 loss: 0.1391 (0.1426) time: 2.9989 data: 0.0071 max mem: 33408 +Epoch: [3] Total time: 2:12:52 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 2:22:47 time: 3.3297 data: 3.2437 max mem: 33408 +Test: [ 100/2573] eta: 0:04:32 time: 0.0775 data: 0.0014 max mem: 33408 +Test: [ 200/2573] eta: 0:03:46 time: 0.0788 data: 0.0014 max mem: 33408 +Test: [ 300/2573] eta: 0:03:23 time: 0.0805 data: 0.0014 max mem: 33408 +Test: [ 400/2573] eta: 0:03:09 time: 0.0824 data: 0.0015 max mem: 33408 +Test: [ 500/2573] eta: 0:02:58 time: 0.0808 data: 0.0014 max mem: 33408 +Test: [ 600/2573] eta: 0:02:48 time: 0.0822 data: 0.0014 max mem: 33408 +Test: [ 700/2573] eta: 0:02:39 time: 0.0805 data: 0.0015 max mem: 33408 +Test: [ 800/2573] eta: 0:02:29 time: 0.0823 data: 0.0014 max mem: 33408 +Test: [ 900/2573] eta: 0:02:20 time: 0.0805 data: 0.0014 max mem: 33408 +Test: [1000/2573] eta: 0:02:11 time: 0.0798 data: 0.0015 max mem: 33408 +Test: [1100/2573] eta: 0:02:02 time: 0.0802 data: 0.0014 max mem: 33408 +Test: [1200/2573] eta: 0:01:54 time: 0.0802 data: 0.0015 max mem: 33408 +Test: [1300/2573] eta: 0:01:45 time: 0.0804 data: 0.0014 max mem: 33408 +Test: [1400/2573] eta: 0:01:37 time: 0.0802 data: 0.0016 max mem: 33408 +Test: [1500/2573] eta: 0:01:28 time: 0.0801 data: 0.0014 max mem: 33408 +Test: [1600/2573] eta: 0:01:20 time: 0.0840 data: 0.0014 max mem: 33408 +Test: [1700/2573] eta: 0:01:12 time: 0.0803 data: 0.0014 max mem: 33408 +Test: [1800/2573] eta: 0:01:03 time: 0.0823 data: 0.0011 max mem: 33408 +Test: [1900/2573] eta: 0:00:55 time: 0.0795 data: 0.0015 max mem: 33408 +Test: [2000/2573] eta: 0:00:47 time: 0.0798 data: 0.0015 max mem: 33408 +Test: [2100/2573] eta: 0:00:38 time: 0.0815 data: 0.0014 max mem: 33408 +Test: [2200/2573] eta: 0:00:30 time: 0.0816 data: 0.0014 max mem: 33408 +Test: [2300/2573] eta: 0:00:22 time: 0.0818 data: 0.0014 max mem: 33408 +Test: [2400/2573] eta: 0:00:14 time: 0.0772 data: 0.0014 max mem: 33408 +Test: [2500/2573] eta: 0:00:05 time: 0.0805 data: 0.0015 max mem: 33408 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: Total time: 0:03:31 +Final results: +Mean IoU is 50.17 + + precision@0.5 = 55.41 + precision@0.6 = 48.39 + precision@0.7 = 40.28 + precision@0.8 = 28.08 + precision@0.9 = 10.52 + overall IoU = 51.28 + +Average object IoU 50.17256179248412 +Overall IoU 51.282798767089844 +Better epoch: 3 + +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [4] [ 0/2639] eta: 4:03:25 lr: 4.5476197990840624e-05 loss: 0.1080 (0.1080) time: 5.5346 data: 2.3406 max mem: 33408 +Epoch: [4] [ 10/2639] eta: 2:21:41 lr: 4.5471889832823845e-05 loss: 0.1257 (0.1365) time: 3.2336 data: 0.2196 max mem: 33408 +Epoch: [4] [ 20/2639] eta: 2:18:01 lr: 4.546758162945445e-05 loss: 0.1257 (0.1313) time: 3.0433 data: 0.0070 max mem: 33408 +Epoch: [4] [ 30/2639] eta: 2:17:10 lr: 4.546327338072719e-05 loss: 0.1295 (0.1405) time: 3.1112 data: 0.0069 max mem: 33408 +Epoch: [4] [ 40/2639] eta: 2:14:55 lr: 4.545896508663681e-05 loss: 0.1097 (0.1302) time: 3.0658 data: 0.0074 max mem: 33408 +Epoch: [4] [ 50/2639] eta: 2:14:12 lr: 4.5454656747178066e-05 loss: 0.1029 (0.1289) time: 3.0411 data: 0.0075 max mem: 33408 +Epoch: [4] [ 60/2639] eta: 2:12:54 lr: 4.545034836234568e-05 loss: 0.1134 (0.1295) time: 3.0445 data: 0.0076 max mem: 33408 +Epoch: [4] [ 70/2639] eta: 2:11:51 lr: 4.544603993213442e-05 loss: 0.1228 (0.1303) time: 3.0021 data: 0.0077 max mem: 33408 +Epoch: [4] [ 80/2639] eta: 2:10:49 lr: 4.544173145653901e-05 loss: 0.1384 (0.1304) time: 2.9927 data: 0.0076 max mem: 33408 +Epoch: [4] [ 90/2639] eta: 2:10:30 lr: 4.5437422935554206e-05 loss: 0.1290 (0.1279) time: 3.0454 data: 0.0077 max mem: 33408 +Epoch: [4] [ 100/2639] eta: 2:09:59 lr: 4.5433114369174725e-05 loss: 0.1022 (0.1258) time: 3.0894 data: 0.0080 max mem: 33408 +Epoch: [4] [ 110/2639] eta: 2:09:25 lr: 4.542880575739533e-05 loss: 0.1095 (0.1260) time: 3.0625 data: 0.0079 max mem: 33408 +Epoch: [4] [ 120/2639] eta: 2:08:37 lr: 4.542449710021074e-05 loss: 0.1184 (0.1255) time: 3.0228 data: 0.0079 max mem: 33408 +Epoch: [4] [ 130/2639] eta: 2:08:10 lr: 4.54201883976157e-05 loss: 0.1249 (0.1251) time: 3.0349 data: 0.0079 max mem: 33408 +Epoch: [4] [ 140/2639] eta: 2:07:30 lr: 4.5415879649604945e-05 loss: 0.1318 (0.1265) time: 3.0490 data: 0.0084 max mem: 33408 +Epoch: [4] [ 150/2639] eta: 2:06:54 lr: 4.541157085617321e-05 loss: 0.1351 (0.1268) time: 3.0218 data: 0.0083 max mem: 33408 +Epoch: [4] [ 160/2639] eta: 2:06:23 lr: 4.540726201731521e-05 loss: 0.1299 (0.1270) time: 3.0423 data: 0.0078 max mem: 33408 +Epoch: [4] [ 170/2639] eta: 2:05:44 lr: 4.54029531330257e-05 loss: 0.1133 (0.1281) time: 3.0275 data: 0.0078 max mem: 33408 +Epoch: [4] [ 180/2639] eta: 2:05:07 lr: 4.539864420329941e-05 loss: 0.1238 (0.1300) time: 3.0044 data: 0.0079 max mem: 33408 +Epoch: [4] [ 190/2639] eta: 2:04:34 lr: 4.539433522813105e-05 loss: 0.1275 (0.1300) time: 3.0212 data: 0.0078 max mem: 33408 +Epoch: [4] [ 200/2639] eta: 2:03:54 lr: 4.5390026207515356e-05 loss: 0.1297 (0.1301) time: 3.0051 data: 0.0074 max mem: 33408 +Epoch: [4] [ 210/2639] eta: 2:03:19 lr: 4.5385717141447056e-05 loss: 0.1289 (0.1306) time: 2.9903 data: 0.0074 max mem: 33408 +Epoch: [4] [ 220/2639] eta: 2:02:46 lr: 4.5381408029920884e-05 loss: 0.1191 (0.1307) time: 3.0144 data: 0.0082 max mem: 33408 +Epoch: [4] [ 230/2639] eta: 2:02:15 lr: 4.537709887293155e-05 loss: 0.1448 (0.1323) time: 3.0320 data: 0.0086 max mem: 33408 +Epoch: [4] [ 240/2639] eta: 2:01:51 lr: 4.537278967047379e-05 loss: 0.1217 (0.1312) time: 3.0770 data: 0.0078 max mem: 33408 +Epoch: [4] [ 250/2639] eta: 2:01:14 lr: 4.5368480422542314e-05 loss: 0.1067 (0.1305) time: 3.0464 data: 0.0076 max mem: 33408 +Epoch: [4] [ 260/2639] eta: 2:00:45 lr: 4.5364171129131856e-05 loss: 0.1107 (0.1313) time: 3.0151 data: 0.0083 max mem: 33408 +Epoch: [4] [ 270/2639] eta: 2:00:07 lr: 4.535986179023712e-05 loss: 0.1107 (0.1307) time: 3.0107 data: 0.0085 max mem: 33408 +Epoch: [4] [ 280/2639] eta: 1:59:38 lr: 4.535555240585284e-05 loss: 0.1183 (0.1310) time: 3.0108 data: 0.0084 max mem: 33408 +Epoch: [4] [ 290/2639] eta: 1:59:04 lr: 4.535124297597372e-05 loss: 0.1186 (0.1312) time: 3.0298 data: 0.0081 max mem: 33408 +Epoch: [4] [ 300/2639] eta: 1:58:33 lr: 4.534693350059449e-05 loss: 0.1168 (0.1312) time: 3.0189 data: 0.0077 max mem: 33408 +Epoch: [4] [ 310/2639] eta: 1:58:05 lr: 4.534262397970985e-05 loss: 0.1223 (0.1319) time: 3.0534 data: 0.0076 max mem: 33408 +Epoch: [4] [ 320/2639] eta: 1:57:33 lr: 4.533831441331453e-05 loss: 0.1223 (0.1318) time: 3.0490 data: 0.0078 max mem: 33408 +Epoch: [4] [ 330/2639] eta: 1:57:03 lr: 4.5334004801403216e-05 loss: 0.1293 (0.1331) time: 3.0347 data: 0.0083 max mem: 33408 +Epoch: [4] [ 340/2639] eta: 1:56:30 lr: 4.5329695143970644e-05 loss: 0.1173 (0.1336) time: 3.0239 data: 0.0081 max mem: 33408 +Epoch: [4] [ 350/2639] eta: 1:55:58 lr: 4.532538544101153e-05 loss: 0.1138 (0.1339) time: 3.0086 data: 0.0077 max mem: 33408 +Epoch: [4] [ 360/2639] eta: 1:55:28 lr: 4.5321075692520565e-05 loss: 0.1299 (0.1340) time: 3.0285 data: 0.0078 max mem: 33408 +Epoch: [4] [ 370/2639] eta: 1:54:57 lr: 4.531676589849246e-05 loss: 0.1231 (0.1337) time: 3.0405 data: 0.0079 max mem: 33408 +Epoch: [4] [ 380/2639] eta: 1:54:31 lr: 4.5312456058921926e-05 loss: 0.1199 (0.1337) time: 3.0711 data: 0.0077 max mem: 33408 +Epoch: [4] [ 390/2639] eta: 1:53:56 lr: 4.5308146173803666e-05 loss: 0.1185 (0.1336) time: 3.0321 data: 0.0078 max mem: 33408 +Epoch: [4] [ 400/2639] eta: 1:53:28 lr: 4.530383624313239e-05 loss: 0.1185 (0.1333) time: 3.0212 data: 0.0078 max mem: 33408 +Epoch: [4] [ 410/2639] eta: 1:52:55 lr: 4.529952626690279e-05 loss: 0.1005 (0.1327) time: 3.0432 data: 0.0077 max mem: 33408 +Epoch: [4] [ 420/2639] eta: 1:52:23 lr: 4.529521624510958e-05 loss: 0.1264 (0.1326) time: 3.0045 data: 0.0077 max mem: 33408 +Epoch: [4] [ 430/2639] eta: 1:51:48 lr: 4.529090617774746e-05 loss: 0.1264 (0.1320) time: 2.9726 data: 0.0077 max mem: 33408 +Epoch: [4] [ 440/2639] eta: 1:51:17 lr: 4.5286596064811116e-05 loss: 0.1236 (0.1325) time: 2.9830 data: 0.0083 max mem: 33408 +Epoch: [4] [ 450/2639] eta: 1:50:47 lr: 4.5282285906295266e-05 loss: 0.1489 (0.1326) time: 3.0376 data: 0.0082 max mem: 33408 +Epoch: [4] [ 460/2639] eta: 1:50:16 lr: 4.527797570219459e-05 loss: 0.1226 (0.1322) time: 3.0390 data: 0.0078 max mem: 33408 +Epoch: [4] [ 470/2639] eta: 1:49:47 lr: 4.52736654525038e-05 loss: 0.1105 (0.1318) time: 3.0427 data: 0.0079 max mem: 33408 +Epoch: [4] [ 480/2639] eta: 1:49:15 lr: 4.5269355157217576e-05 loss: 0.1135 (0.1317) time: 3.0293 data: 0.0077 max mem: 33408 +Epoch: [4] [ 490/2639] eta: 1:48:45 lr: 4.526504481633062e-05 loss: 0.1265 (0.1317) time: 3.0252 data: 0.0073 max mem: 33408 +Epoch: [4] [ 500/2639] eta: 1:48:12 lr: 4.526073442983763e-05 loss: 0.1196 (0.1316) time: 3.0067 data: 0.0078 max mem: 33408 +Epoch: [4] [ 510/2639] eta: 1:47:43 lr: 4.525642399773328e-05 loss: 0.1201 (0.1325) time: 3.0163 data: 0.0081 max mem: 33408 +Epoch: [4] [ 520/2639] eta: 1:47:12 lr: 4.525211352001228e-05 loss: 0.1209 (0.1325) time: 3.0469 data: 0.0078 max mem: 33408 +Epoch: [4] [ 530/2639] eta: 1:46:44 lr: 4.524780299666931e-05 loss: 0.1245 (0.1325) time: 3.0635 data: 0.0077 max mem: 33408 +Epoch: [4] [ 540/2639] eta: 1:46:12 lr: 4.5243492427699054e-05 loss: 0.1212 (0.1324) time: 3.0536 data: 0.0080 max mem: 33408 +Epoch: [4] [ 550/2639] eta: 1:45:42 lr: 4.5239181813096206e-05 loss: 0.1093 (0.1319) time: 3.0187 data: 0.0084 max mem: 33408 +Epoch: [4] [ 560/2639] eta: 1:45:13 lr: 4.5234871152855454e-05 loss: 0.1093 (0.1321) time: 3.0532 data: 0.0083 max mem: 33408 +Epoch: [4] [ 570/2639] eta: 1:44:41 lr: 4.523056044697147e-05 loss: 0.1122 (0.1319) time: 3.0350 data: 0.0078 max mem: 33408 +Epoch: [4] [ 580/2639] eta: 1:44:11 lr: 4.5226249695438944e-05 loss: 0.1122 (0.1320) time: 3.0151 data: 0.0084 max mem: 33408 +Epoch: [4] [ 590/2639] eta: 1:43:39 lr: 4.522193889825256e-05 loss: 0.1307 (0.1322) time: 3.0228 data: 0.0086 max mem: 33408 +Epoch: [4] [ 600/2639] eta: 1:43:08 lr: 4.5217628055407e-05 loss: 0.1307 (0.1323) time: 3.0023 data: 0.0081 max mem: 33408 +Epoch: [4] [ 610/2639] eta: 1:42:37 lr: 4.521331716689694e-05 loss: 0.1181 (0.1320) time: 3.0076 data: 0.0079 max mem: 33408 +Epoch: [4] [ 620/2639] eta: 1:42:05 lr: 4.520900623271706e-05 loss: 0.1180 (0.1323) time: 2.9972 data: 0.0079 max mem: 33408 +Epoch: [4] [ 630/2639] eta: 1:41:35 lr: 4.520469525286203e-05 loss: 0.1397 (0.1324) time: 3.0120 data: 0.0077 max mem: 33408 +Epoch: [4] [ 640/2639] eta: 1:41:02 lr: 4.5200384227326544e-05 loss: 0.1329 (0.1324) time: 3.0055 data: 0.0079 max mem: 33408 +Epoch: [4] [ 650/2639] eta: 1:40:34 lr: 4.5196073156105264e-05 loss: 0.1183 (0.1321) time: 3.0270 data: 0.0081 max mem: 33408 +Epoch: [4] [ 660/2639] eta: 1:40:05 lr: 4.5191762039192864e-05 loss: 0.1134 (0.1317) time: 3.0998 data: 0.0078 max mem: 33408 +Epoch: [4] [ 670/2639] eta: 1:39:34 lr: 4.518745087658401e-05 loss: 0.1130 (0.1316) time: 3.0510 data: 0.0078 max mem: 33408 +Epoch: [4] [ 680/2639] eta: 1:39:01 lr: 4.51831396682734e-05 loss: 0.1435 (0.1321) time: 2.9750 data: 0.0081 max mem: 33408 +Epoch: [4] [ 690/2639] eta: 1:38:29 lr: 4.517882841425567e-05 loss: 0.1426 (0.1321) time: 2.9648 data: 0.0081 max mem: 33408 +Epoch: [4] [ 700/2639] eta: 1:37:58 lr: 4.517451711452551e-05 loss: 0.1023 (0.1318) time: 2.9767 data: 0.0080 max mem: 33408 +Epoch: [4] [ 710/2639] eta: 1:37:27 lr: 4.517020576907758e-05 loss: 0.1064 (0.1317) time: 2.9928 data: 0.0080 max mem: 33408 +Epoch: [4] [ 720/2639] eta: 1:36:54 lr: 4.516589437790656e-05 loss: 0.1230 (0.1317) time: 2.9764 data: 0.0080 max mem: 33408 +Epoch: [4] [ 730/2639] eta: 1:36:22 lr: 4.5161582941007094e-05 loss: 0.1327 (0.1320) time: 2.9489 data: 0.0082 max mem: 33408 +Epoch: [4] [ 740/2639] eta: 1:35:50 lr: 4.515727145837386e-05 loss: 0.1434 (0.1321) time: 2.9602 data: 0.0081 max mem: 33408 +Epoch: [4] [ 750/2639] eta: 1:35:19 lr: 4.515295993000152e-05 loss: 0.1296 (0.1322) time: 2.9916 data: 0.0081 max mem: 33408 +Epoch: [4] [ 760/2639] eta: 1:34:48 lr: 4.514864835588473e-05 loss: 0.1197 (0.1322) time: 3.0032 data: 0.0082 max mem: 33408 +Epoch: [4] [ 770/2639] eta: 1:34:18 lr: 4.514433673601816e-05 loss: 0.1138 (0.1320) time: 3.0131 data: 0.0082 max mem: 33408 +Epoch: [4] [ 780/2639] eta: 1:33:48 lr: 4.514002507039646e-05 loss: 0.1226 (0.1321) time: 3.0462 data: 0.0085 max mem: 33408 +Epoch: [4] [ 790/2639] eta: 1:33:16 lr: 4.5135713359014296e-05 loss: 0.1317 (0.1323) time: 3.0044 data: 0.0082 max mem: 33408 +Epoch: [4] [ 800/2639] eta: 1:32:47 lr: 4.5131401601866324e-05 loss: 0.1317 (0.1323) time: 3.0124 data: 0.0078 max mem: 33408 +Epoch: [4] [ 810/2639] eta: 1:32:16 lr: 4.512708979894719e-05 loss: 0.1174 (0.1320) time: 3.0390 data: 0.0078 max mem: 33408 +Epoch: [4] [ 820/2639] eta: 1:31:48 lr: 4.512277795025157e-05 loss: 0.0996 (0.1319) time: 3.0530 data: 0.0081 max mem: 33408 +Epoch: [4] [ 830/2639] eta: 1:31:16 lr: 4.511846605577409e-05 loss: 0.1135 (0.1319) time: 3.0278 data: 0.0080 max mem: 33408 +Epoch: [4] [ 840/2639] eta: 1:30:44 lr: 4.511415411550942e-05 loss: 0.1278 (0.1318) time: 2.9608 data: 0.0078 max mem: 33408 +Epoch: [4] [ 850/2639] eta: 1:30:13 lr: 4.510984212945221e-05 loss: 0.1263 (0.1318) time: 2.9782 data: 0.0079 max mem: 33408 +Epoch: [4] [ 860/2639] eta: 1:29:41 lr: 4.510553009759711e-05 loss: 0.1250 (0.1319) time: 2.9724 data: 0.0079 max mem: 33408 +Epoch: [4] [ 870/2639] eta: 1:29:10 lr: 4.510121801993876e-05 loss: 0.1115 (0.1317) time: 2.9686 data: 0.0078 max mem: 33408 +Epoch: [4] [ 880/2639] eta: 1:28:40 lr: 4.509690589647182e-05 loss: 0.1124 (0.1319) time: 2.9914 data: 0.0078 max mem: 33408 +Epoch: [4] [ 890/2639] eta: 1:28:11 lr: 4.509259372719093e-05 loss: 0.1211 (0.1321) time: 3.0552 data: 0.0076 max mem: 33408 +Epoch: [4] [ 900/2639] eta: 1:27:40 lr: 4.508828151209073e-05 loss: 0.1131 (0.1320) time: 3.0344 data: 0.0080 max mem: 33408 +Epoch: [4] [ 910/2639] eta: 1:27:12 lr: 4.5083969251165875e-05 loss: 0.1113 (0.1320) time: 3.0722 data: 0.0080 max mem: 33408 +Epoch: [4] [ 920/2639] eta: 1:26:42 lr: 4.5079656944411e-05 loss: 0.1226 (0.1322) time: 3.1012 data: 0.0076 max mem: 33408 +Epoch: [4] [ 930/2639] eta: 1:26:13 lr: 4.507534459182075e-05 loss: 0.1191 (0.1322) time: 3.0507 data: 0.0083 max mem: 33408 +Epoch: [4] [ 940/2639] eta: 1:25:44 lr: 4.5071032193389755e-05 loss: 0.1113 (0.1321) time: 3.0977 data: 0.0085 max mem: 33408 +Epoch: [4] [ 950/2639] eta: 1:25:14 lr: 4.506671974911268e-05 loss: 0.1070 (0.1317) time: 3.0732 data: 0.0078 max mem: 33408 +Epoch: [4] [ 960/2639] eta: 1:24:43 lr: 4.5062407258984135e-05 loss: 0.1073 (0.1316) time: 3.0318 data: 0.0078 max mem: 33408 +Epoch: [4] [ 970/2639] eta: 1:24:12 lr: 4.5058094722998774e-05 loss: 0.1092 (0.1314) time: 2.9979 data: 0.0080 max mem: 33408 +Epoch: [4] [ 980/2639] eta: 1:23:42 lr: 4.505378214115123e-05 loss: 0.1076 (0.1315) time: 3.0149 data: 0.0077 max mem: 33408 +Epoch: [4] [ 990/2639] eta: 1:23:12 lr: 4.504946951343613e-05 loss: 0.1170 (0.1315) time: 3.0433 data: 0.0080 max mem: 33408 +Epoch: [4] [1000/2639] eta: 1:22:42 lr: 4.504515683984811e-05 loss: 0.1243 (0.1314) time: 3.0373 data: 0.0080 max mem: 33408 +Epoch: [4] [1010/2639] eta: 1:22:11 lr: 4.5040844120381804e-05 loss: 0.1244 (0.1314) time: 3.0152 data: 0.0080 max mem: 33408 +Epoch: [4] [1020/2639] eta: 1:21:41 lr: 4.503653135503184e-05 loss: 0.1244 (0.1315) time: 3.0069 data: 0.0082 max mem: 33408 +Epoch: [4] [1030/2639] eta: 1:21:11 lr: 4.5032218543792856e-05 loss: 0.1215 (0.1315) time: 3.0363 data: 0.0080 max mem: 33408 +Epoch: [4] [1040/2639] eta: 1:20:41 lr: 4.502790568665947e-05 loss: 0.1222 (0.1315) time: 3.0466 data: 0.0081 max mem: 33408 +Epoch: [4] [1050/2639] eta: 1:20:11 lr: 4.502359278362632e-05 loss: 0.1306 (0.1315) time: 3.0572 data: 0.0081 max mem: 33408 +Epoch: [4] [1060/2639] eta: 1:19:41 lr: 4.5019279834688025e-05 loss: 0.1344 (0.1318) time: 3.0329 data: 0.0082 max mem: 33408 +Epoch: [4] [1070/2639] eta: 1:19:10 lr: 4.5014966839839214e-05 loss: 0.1456 (0.1320) time: 2.9963 data: 0.0086 max mem: 33408 +Epoch: [4] [1080/2639] eta: 1:18:40 lr: 4.50106537990745e-05 loss: 0.1235 (0.1317) time: 3.0318 data: 0.0082 max mem: 33408 +Epoch: [4] [1090/2639] eta: 1:18:10 lr: 4.5006340712388515e-05 loss: 0.1125 (0.1318) time: 3.0504 data: 0.0078 max mem: 33408 +Epoch: [4] [1100/2639] eta: 1:17:39 lr: 4.500202757977588e-05 loss: 0.1144 (0.1316) time: 3.0053 data: 0.0077 max mem: 33408 +Epoch: [4] [1110/2639] eta: 1:17:08 lr: 4.499771440123121e-05 loss: 0.1229 (0.1316) time: 2.9889 data: 0.0079 max mem: 33408 +Epoch: [4] [1120/2639] eta: 1:16:38 lr: 4.499340117674913e-05 loss: 0.1188 (0.1315) time: 3.0086 data: 0.0083 max mem: 33408 +Epoch: [4] [1130/2639] eta: 1:16:07 lr: 4.498908790632425e-05 loss: 0.1106 (0.1314) time: 3.0023 data: 0.0079 max mem: 33408 +Epoch: [4] [1140/2639] eta: 1:15:38 lr: 4.4984774589951196e-05 loss: 0.1250 (0.1316) time: 3.0493 data: 0.0076 max mem: 33408 +Epoch: [4] [1150/2639] eta: 1:15:07 lr: 4.4980461227624574e-05 loss: 0.1229 (0.1314) time: 3.0585 data: 0.0076 max mem: 33408 +Epoch: [4] [1160/2639] eta: 1:14:37 lr: 4.497614781933901e-05 loss: 0.1121 (0.1314) time: 3.0095 data: 0.0079 max mem: 33408 +Epoch: [4] [1170/2639] eta: 1:14:07 lr: 4.49718343650891e-05 loss: 0.1130 (0.1314) time: 3.0297 data: 0.0079 max mem: 33408 +Epoch: [4] [1180/2639] eta: 1:13:36 lr: 4.496752086486947e-05 loss: 0.1194 (0.1314) time: 3.0084 data: 0.0077 max mem: 33408 +Epoch: [4] [1190/2639] eta: 1:13:05 lr: 4.496320731867472e-05 loss: 0.1279 (0.1314) time: 2.9894 data: 0.0078 max mem: 33408 +Epoch: [4] [1200/2639] eta: 1:12:36 lr: 4.495889372649947e-05 loss: 0.1201 (0.1313) time: 3.0370 data: 0.0078 max mem: 33408 +Epoch: [4] [1210/2639] eta: 1:12:06 lr: 4.4954580088338316e-05 loss: 0.1338 (0.1316) time: 3.0638 data: 0.0079 max mem: 33408 +Epoch: [4] [1220/2639] eta: 1:11:35 lr: 4.4950266404185877e-05 loss: 0.1256 (0.1316) time: 3.0241 data: 0.0078 max mem: 33408 +Epoch: [4] [1230/2639] eta: 1:11:05 lr: 4.494595267403675e-05 loss: 0.1198 (0.1315) time: 3.0302 data: 0.0076 max mem: 33408 +Epoch: [4] [1240/2639] eta: 1:10:34 lr: 4.494163889788554e-05 loss: 0.1150 (0.1315) time: 3.0238 data: 0.0081 max mem: 33408 +Epoch: [4] [1250/2639] eta: 1:10:05 lr: 4.4937325075726856e-05 loss: 0.1198 (0.1315) time: 3.0412 data: 0.0082 max mem: 33408 +Epoch: [4] [1260/2639] eta: 1:09:34 lr: 4.4933011207555295e-05 loss: 0.1237 (0.1315) time: 3.0559 data: 0.0082 max mem: 33408 +Epoch: [4] [1270/2639] eta: 1:09:04 lr: 4.492869729336546e-05 loss: 0.1108 (0.1314) time: 3.0070 data: 0.0085 max mem: 33408 +Epoch: [4] [1280/2639] eta: 1:08:34 lr: 4.492438333315194e-05 loss: 0.1103 (0.1314) time: 3.0141 data: 0.0081 max mem: 33408 +Epoch: [4] [1290/2639] eta: 1:08:04 lr: 4.492006932690935e-05 loss: 0.1235 (0.1314) time: 3.0474 data: 0.0082 max mem: 33408 +Epoch: [4] [1300/2639] eta: 1:07:33 lr: 4.4915755274632284e-05 loss: 0.1262 (0.1314) time: 3.0448 data: 0.0083 max mem: 33408 +Epoch: [4] [1310/2639] eta: 1:07:03 lr: 4.491144117631532e-05 loss: 0.1266 (0.1314) time: 3.0287 data: 0.0083 max mem: 33408 +Epoch: [4] [1320/2639] eta: 1:06:33 lr: 4.490712703195308e-05 loss: 0.1151 (0.1311) time: 3.0312 data: 0.0084 max mem: 33408 +Epoch: [4] [1330/2639] eta: 1:06:03 lr: 4.4902812841540134e-05 loss: 0.1094 (0.1311) time: 3.0348 data: 0.0080 max mem: 33408 +Epoch: [4] [1340/2639] eta: 1:05:33 lr: 4.489849860507108e-05 loss: 0.1181 (0.1309) time: 3.0354 data: 0.0079 max mem: 33408 +Epoch: [4] [1350/2639] eta: 1:05:02 lr: 4.489418432254053e-05 loss: 0.1190 (0.1308) time: 3.0352 data: 0.0079 max mem: 33408 +Epoch: [4] [1360/2639] eta: 1:04:32 lr: 4.488986999394305e-05 loss: 0.1206 (0.1310) time: 3.0368 data: 0.0082 max mem: 33408 +Epoch: [4] [1370/2639] eta: 1:04:02 lr: 4.488555561927323e-05 loss: 0.1422 (0.1311) time: 3.0252 data: 0.0080 max mem: 33408 +Epoch: [4] [1380/2639] eta: 1:03:32 lr: 4.4881241198525656e-05 loss: 0.1434 (0.1313) time: 3.0348 data: 0.0075 max mem: 33408 +Epoch: [4] [1390/2639] eta: 1:03:01 lr: 4.487692673169493e-05 loss: 0.1053 (0.1311) time: 3.0234 data: 0.0074 max mem: 33408 +Epoch: [4] [1400/2639] eta: 1:02:32 lr: 4.487261221877563e-05 loss: 0.0941 (0.1311) time: 3.0517 data: 0.0078 max mem: 33408 +Epoch: [4] [1410/2639] eta: 1:02:01 lr: 4.4868297659762335e-05 loss: 0.1178 (0.1311) time: 3.0619 data: 0.0078 max mem: 33408 +Epoch: [4] [1420/2639] eta: 1:01:31 lr: 4.486398305464963e-05 loss: 0.0989 (0.1309) time: 3.0324 data: 0.0077 max mem: 33408 +Epoch: [4] [1430/2639] eta: 1:01:01 lr: 4.4859668403432095e-05 loss: 0.0976 (0.1308) time: 3.0290 data: 0.0079 max mem: 33408 +Epoch: [4] [1440/2639] eta: 1:00:30 lr: 4.485535370610431e-05 loss: 0.1061 (0.1307) time: 2.9961 data: 0.0083 max mem: 33408 +Epoch: [4] [1450/2639] eta: 1:00:00 lr: 4.4851038962660865e-05 loss: 0.1097 (0.1307) time: 3.0100 data: 0.0081 max mem: 33408 +Epoch: [4] [1460/2639] eta: 0:59:30 lr: 4.484672417309632e-05 loss: 0.1083 (0.1306) time: 3.0835 data: 0.0076 max mem: 33408 +Epoch: [4] [1470/2639] eta: 0:59:00 lr: 4.484240933740526e-05 loss: 0.1089 (0.1307) time: 3.0447 data: 0.0077 max mem: 33408 +Epoch: [4] [1480/2639] eta: 0:58:30 lr: 4.483809445558226e-05 loss: 0.1161 (0.1306) time: 3.0196 data: 0.0081 max mem: 33408 +Epoch: [4] [1490/2639] eta: 0:58:00 lr: 4.483377952762189e-05 loss: 0.1076 (0.1306) time: 3.0814 data: 0.0082 max mem: 33408 +Epoch: [4] [1500/2639] eta: 0:57:29 lr: 4.4829464553518734e-05 loss: 0.0874 (0.1304) time: 3.0430 data: 0.0076 max mem: 33408 +Epoch: [4] [1510/2639] eta: 0:56:59 lr: 4.482514953326736e-05 loss: 0.1139 (0.1304) time: 3.0436 data: 0.0078 max mem: 33408 +Epoch: [4] [1520/2639] eta: 0:56:29 lr: 4.4820834466862323e-05 loss: 0.1292 (0.1304) time: 3.0355 data: 0.0079 max mem: 33408 +Epoch: [4] [1530/2639] eta: 0:55:59 lr: 4.481651935429821e-05 loss: 0.1290 (0.1306) time: 3.0472 data: 0.0077 max mem: 33408 +Epoch: [4] [1540/2639] eta: 0:55:29 lr: 4.481220419556958e-05 loss: 0.1357 (0.1307) time: 3.0723 data: 0.0081 max mem: 33408 +Epoch: [4] [1550/2639] eta: 0:54:58 lr: 4.4807888990671e-05 loss: 0.1323 (0.1307) time: 3.0129 data: 0.0080 max mem: 33408 +Epoch: [4] [1560/2639] eta: 0:54:28 lr: 4.480357373959704e-05 loss: 0.1327 (0.1309) time: 3.0229 data: 0.0078 max mem: 33408 +Epoch: [4] [1570/2639] eta: 0:53:58 lr: 4.479925844234227e-05 loss: 0.1327 (0.1309) time: 3.0209 data: 0.0081 max mem: 33408 +Epoch: [4] [1580/2639] eta: 0:53:28 lr: 4.479494309890123e-05 loss: 0.1176 (0.1308) time: 3.0478 data: 0.0079 max mem: 33408 +Epoch: [4] [1590/2639] eta: 0:52:57 lr: 4.4790627709268505e-05 loss: 0.1173 (0.1308) time: 3.0442 data: 0.0079 max mem: 33408 +Epoch: [4] [1600/2639] eta: 0:52:27 lr: 4.478631227343865e-05 loss: 0.1173 (0.1309) time: 3.0122 data: 0.0076 max mem: 33408 +Epoch: [4] [1610/2639] eta: 0:51:57 lr: 4.478199679140622e-05 loss: 0.1253 (0.1309) time: 3.0596 data: 0.0073 max mem: 33408 +Epoch: [4] [1620/2639] eta: 0:51:26 lr: 4.4777681263165776e-05 loss: 0.1128 (0.1307) time: 3.0056 data: 0.0073 max mem: 33408 +Epoch: [4] [1630/2639] eta: 0:50:56 lr: 4.477336568871187e-05 loss: 0.1075 (0.1307) time: 2.9853 data: 0.0074 max mem: 33408 +Epoch: [4] [1640/2639] eta: 0:50:25 lr: 4.476905006803906e-05 loss: 0.1014 (0.1306) time: 2.9997 data: 0.0076 max mem: 33408 +Epoch: [4] [1650/2639] eta: 0:49:55 lr: 4.476473440114191e-05 loss: 0.1111 (0.1307) time: 3.0239 data: 0.0075 max mem: 33408 +Epoch: [4] [1660/2639] eta: 0:49:25 lr: 4.476041868801497e-05 loss: 0.1359 (0.1306) time: 3.0507 data: 0.0080 max mem: 33408 +Epoch: [4] [1670/2639] eta: 0:48:54 lr: 4.475610292865277e-05 loss: 0.1359 (0.1308) time: 2.9810 data: 0.0081 max mem: 33408 +Epoch: [4] [1680/2639] eta: 0:48:24 lr: 4.4751787123049884e-05 loss: 0.1242 (0.1308) time: 2.9827 data: 0.0074 max mem: 33408 +Epoch: [4] [1690/2639] eta: 0:47:53 lr: 4.4747471271200866e-05 loss: 0.1258 (0.1309) time: 3.0245 data: 0.0073 max mem: 33408 +Epoch: [4] [1700/2639] eta: 0:47:23 lr: 4.4743155373100245e-05 loss: 0.1324 (0.1308) time: 3.0124 data: 0.0072 max mem: 33408 +Epoch: [4] [1710/2639] eta: 0:46:53 lr: 4.473883942874257e-05 loss: 0.1293 (0.1310) time: 3.0758 data: 0.0072 max mem: 33408 +Epoch: [4] [1720/2639] eta: 0:46:23 lr: 4.473452343812241e-05 loss: 0.1271 (0.1310) time: 3.1068 data: 0.0077 max mem: 33408 +Epoch: [4] [1730/2639] eta: 0:45:53 lr: 4.473020740123429e-05 loss: 0.1245 (0.1309) time: 3.0410 data: 0.0077 max mem: 33408 +Epoch: [4] [1740/2639] eta: 0:45:23 lr: 4.472589131807276e-05 loss: 0.1262 (0.1309) time: 3.0479 data: 0.0072 max mem: 33408 +Epoch: [4] [1750/2639] eta: 0:44:52 lr: 4.472157518863234e-05 loss: 0.1215 (0.1309) time: 3.0336 data: 0.0072 max mem: 33408 +Epoch: [4] [1760/2639] eta: 0:44:22 lr: 4.471725901290761e-05 loss: 0.1239 (0.1310) time: 3.0179 data: 0.0081 max mem: 33408 +Epoch: [4] [1770/2639] eta: 0:43:52 lr: 4.471294279089308e-05 loss: 0.1382 (0.1309) time: 3.0243 data: 0.0081 max mem: 33408 +Epoch: [4] [1780/2639] eta: 0:43:22 lr: 4.470862652258331e-05 loss: 0.1132 (0.1308) time: 3.0253 data: 0.0076 max mem: 33408 +Epoch: [4] [1790/2639] eta: 0:42:51 lr: 4.470431020797281e-05 loss: 0.1147 (0.1307) time: 3.0304 data: 0.0078 max mem: 33408 +Epoch: [4] [1800/2639] eta: 0:42:21 lr: 4.4699993847056146e-05 loss: 0.1183 (0.1307) time: 3.0317 data: 0.0076 max mem: 33408 +Epoch: [4] [1810/2639] eta: 0:41:51 lr: 4.4695677439827824e-05 loss: 0.1183 (0.1307) time: 3.0265 data: 0.0075 max mem: 33408 +Epoch: [4] [1820/2639] eta: 0:41:20 lr: 4.469136098628241e-05 loss: 0.1156 (0.1306) time: 3.0229 data: 0.0073 max mem: 33408 +Epoch: [4] [1830/2639] eta: 0:40:50 lr: 4.468704448641441e-05 loss: 0.1156 (0.1306) time: 3.0448 data: 0.0076 max mem: 33408 +Epoch: [4] [1840/2639] eta: 0:40:20 lr: 4.468272794021836e-05 loss: 0.1234 (0.1307) time: 3.0387 data: 0.0079 max mem: 33408 +Epoch: [4] [1850/2639] eta: 0:39:50 lr: 4.4678411347688796e-05 loss: 0.1234 (0.1308) time: 3.0280 data: 0.0074 max mem: 33408 +Epoch: [4] [1860/2639] eta: 0:39:19 lr: 4.4674094708820254e-05 loss: 0.1292 (0.1307) time: 3.0211 data: 0.0078 max mem: 33408 +Epoch: [4] [1870/2639] eta: 0:38:49 lr: 4.466977802360724e-05 loss: 0.1398 (0.1308) time: 3.0277 data: 0.0084 max mem: 33408 +Epoch: [4] [1880/2639] eta: 0:38:19 lr: 4.466546129204429e-05 loss: 0.1423 (0.1309) time: 3.0201 data: 0.0080 max mem: 33408 +Epoch: [4] [1890/2639] eta: 0:37:48 lr: 4.466114451412594e-05 loss: 0.1168 (0.1308) time: 3.0169 data: 0.0075 max mem: 33408 +Epoch: [4] [1900/2639] eta: 0:37:18 lr: 4.46568276898467e-05 loss: 0.1141 (0.1309) time: 3.0098 data: 0.0073 max mem: 33408 +Epoch: [4] [1910/2639] eta: 0:36:48 lr: 4.4652510819201105e-05 loss: 0.1129 (0.1309) time: 3.0240 data: 0.0072 max mem: 33408 +Epoch: [4] [1920/2639] eta: 0:36:17 lr: 4.464819390218366e-05 loss: 0.1281 (0.1310) time: 3.0243 data: 0.0071 max mem: 33408 +Epoch: [4] [1930/2639] eta: 0:35:47 lr: 4.46438769387889e-05 loss: 0.1173 (0.1310) time: 3.0213 data: 0.0076 max mem: 33408 +Epoch: [4] [1940/2639] eta: 0:35:17 lr: 4.463955992901133e-05 loss: 0.1153 (0.1310) time: 3.0437 data: 0.0079 max mem: 33408 +Epoch: [4] [1950/2639] eta: 0:34:47 lr: 4.463524287284548e-05 loss: 0.1225 (0.1310) time: 3.0748 data: 0.0076 max mem: 33408 +Epoch: [4] [1960/2639] eta: 0:34:16 lr: 4.463092577028586e-05 loss: 0.1193 (0.1310) time: 3.0256 data: 0.0078 max mem: 33408 +Epoch: [4] [1970/2639] eta: 0:33:46 lr: 4.462660862132699e-05 loss: 0.1222 (0.1311) time: 2.9745 data: 0.0077 max mem: 33408 +Epoch: [4] [1980/2639] eta: 0:33:16 lr: 4.462229142596337e-05 loss: 0.1351 (0.1311) time: 3.0498 data: 0.0073 max mem: 33408 +Epoch: [4] [1990/2639] eta: 0:32:45 lr: 4.461797418418953e-05 loss: 0.1136 (0.1310) time: 3.0431 data: 0.0072 max mem: 33408 +Epoch: [4] [2000/2639] eta: 0:32:15 lr: 4.461365689599997e-05 loss: 0.1132 (0.1309) time: 3.0233 data: 0.0071 max mem: 33408 +Epoch: [4] [2010/2639] eta: 0:31:45 lr: 4.460933956138921e-05 loss: 0.1127 (0.1308) time: 3.0524 data: 0.0073 max mem: 33408 +Epoch: [4] [2020/2639] eta: 0:31:15 lr: 4.460502218035175e-05 loss: 0.1127 (0.1309) time: 3.0319 data: 0.0077 max mem: 33408 +Epoch: [4] [2030/2639] eta: 0:30:44 lr: 4.4600704752882104e-05 loss: 0.1171 (0.1309) time: 3.0336 data: 0.0078 max mem: 33408 +Epoch: [4] [2040/2639] eta: 0:30:14 lr: 4.459638727897476e-05 loss: 0.1171 (0.1309) time: 3.0397 data: 0.0079 max mem: 33408 +Epoch: [4] [2050/2639] eta: 0:29:44 lr: 4.459206975862426e-05 loss: 0.1078 (0.1307) time: 3.0042 data: 0.0075 max mem: 33408 +Epoch: [4] [2060/2639] eta: 0:29:13 lr: 4.4587752191825074e-05 loss: 0.1091 (0.1308) time: 3.0062 data: 0.0073 max mem: 33408 +Epoch: [4] [2070/2639] eta: 0:28:43 lr: 4.458343457857172e-05 loss: 0.1279 (0.1308) time: 3.0121 data: 0.0077 max mem: 33408 +Epoch: [4] [2080/2639] eta: 0:28:12 lr: 4.457911691885869e-05 loss: 0.1127 (0.1307) time: 2.9783 data: 0.0076 max mem: 33408 +Epoch: [4] [2090/2639] eta: 0:27:42 lr: 4.4574799212680496e-05 loss: 0.1231 (0.1307) time: 3.0116 data: 0.0076 max mem: 33408 +Epoch: [4] [2100/2639] eta: 0:27:12 lr: 4.4570481460031635e-05 loss: 0.1278 (0.1307) time: 3.0641 data: 0.0083 max mem: 33408 +Epoch: [4] [2110/2639] eta: 0:26:42 lr: 4.45661636609066e-05 loss: 0.1088 (0.1306) time: 3.0578 data: 0.0080 max mem: 33408 +Epoch: [4] [2120/2639] eta: 0:26:12 lr: 4.456184581529988e-05 loss: 0.1190 (0.1306) time: 3.0498 data: 0.0075 max mem: 33408 +Epoch: [4] [2130/2639] eta: 0:25:41 lr: 4.4557527923205985e-05 loss: 0.1172 (0.1305) time: 3.0316 data: 0.0079 max mem: 33408 +Epoch: [4] [2140/2639] eta: 0:25:11 lr: 4.45532099846194e-05 loss: 0.1016 (0.1304) time: 2.9935 data: 0.0080 max mem: 33408 +Epoch: [4] [2150/2639] eta: 0:24:40 lr: 4.454889199953462e-05 loss: 0.1283 (0.1306) time: 2.9746 data: 0.0080 max mem: 33408 +Epoch: [4] [2160/2639] eta: 0:24:10 lr: 4.454457396794614e-05 loss: 0.1396 (0.1305) time: 2.9757 data: 0.0083 max mem: 33408 +Epoch: [4] [2170/2639] eta: 0:23:40 lr: 4.4540255889848445e-05 loss: 0.1129 (0.1306) time: 2.9558 data: 0.0082 max mem: 33408 +Epoch: [4] [2180/2639] eta: 0:23:09 lr: 4.453593776523603e-05 loss: 0.1105 (0.1305) time: 2.9558 data: 0.0078 max mem: 33408 +Epoch: [4] [2190/2639] eta: 0:22:39 lr: 4.453161959410338e-05 loss: 0.1116 (0.1305) time: 2.9652 data: 0.0080 max mem: 33408 +Epoch: [4] [2200/2639] eta: 0:22:08 lr: 4.4527301376444975e-05 loss: 0.1143 (0.1305) time: 2.9783 data: 0.0081 max mem: 33408 +Epoch: [4] [2210/2639] eta: 0:21:38 lr: 4.45229831122553e-05 loss: 0.1222 (0.1305) time: 3.0043 data: 0.0079 max mem: 33408 +Epoch: [4] [2220/2639] eta: 0:21:08 lr: 4.451866480152885e-05 loss: 0.1237 (0.1306) time: 3.0314 data: 0.0083 max mem: 33408 +Epoch: [4] [2230/2639] eta: 0:20:38 lr: 4.451434644426011e-05 loss: 0.1237 (0.1306) time: 3.0340 data: 0.0083 max mem: 33408 +Epoch: [4] [2240/2639] eta: 0:20:07 lr: 4.451002804044355e-05 loss: 0.1121 (0.1306) time: 2.9967 data: 0.0079 max mem: 33408 +Epoch: [4] [2250/2639] eta: 0:19:37 lr: 4.4505709590073645e-05 loss: 0.1402 (0.1307) time: 2.9795 data: 0.0088 max mem: 33408 +Epoch: [4] [2260/2639] eta: 0:19:07 lr: 4.4501391093144895e-05 loss: 0.1168 (0.1306) time: 3.0480 data: 0.0090 max mem: 33408 +Epoch: [4] [2270/2639] eta: 0:18:37 lr: 4.4497072549651756e-05 loss: 0.1104 (0.1307) time: 3.0874 data: 0.0079 max mem: 33408 +Epoch: [4] [2280/2639] eta: 0:18:06 lr: 4.4492753959588725e-05 loss: 0.1204 (0.1307) time: 3.0408 data: 0.0077 max mem: 33408 +Epoch: [4] [2290/2639] eta: 0:17:36 lr: 4.448843532295026e-05 loss: 0.1162 (0.1307) time: 3.0429 data: 0.0076 max mem: 33408 +Epoch: [4] [2300/2639] eta: 0:17:06 lr: 4.4484116639730836e-05 loss: 0.1110 (0.1307) time: 3.0307 data: 0.0078 max mem: 33408 +Epoch: [4] [2310/2639] eta: 0:16:36 lr: 4.447979790992494e-05 loss: 0.1026 (0.1306) time: 3.0307 data: 0.0079 max mem: 33408 +Epoch: [4] [2320/2639] eta: 0:16:05 lr: 4.447547913352703e-05 loss: 0.1202 (0.1306) time: 3.0425 data: 0.0077 max mem: 33408 +Epoch: [4] [2330/2639] eta: 0:15:35 lr: 4.447116031053158e-05 loss: 0.1202 (0.1305) time: 3.0249 data: 0.0075 max mem: 33408 +Epoch: [4] [2340/2639] eta: 0:15:05 lr: 4.446684144093306e-05 loss: 0.1040 (0.1305) time: 3.0356 data: 0.0080 max mem: 33408 +Epoch: [4] [2350/2639] eta: 0:14:34 lr: 4.4462522524725944e-05 loss: 0.1177 (0.1305) time: 3.0384 data: 0.0084 max mem: 33408 +Epoch: [4] [2360/2639] eta: 0:14:04 lr: 4.445820356190469e-05 loss: 0.1175 (0.1304) time: 3.0189 data: 0.0085 max mem: 33408 +Epoch: [4] [2370/2639] eta: 0:13:34 lr: 4.445388455246376e-05 loss: 0.1042 (0.1304) time: 3.0223 data: 0.0083 max mem: 33408 +Epoch: [4] [2380/2639] eta: 0:13:04 lr: 4.4449565496397634e-05 loss: 0.1042 (0.1303) time: 2.9972 data: 0.0077 max mem: 33408 +Epoch: [4] [2390/2639] eta: 0:12:33 lr: 4.4445246393700756e-05 loss: 0.1125 (0.1303) time: 2.9956 data: 0.0075 max mem: 33408 +Epoch: [4] [2400/2639] eta: 0:12:03 lr: 4.44409272443676e-05 loss: 0.1371 (0.1304) time: 3.0244 data: 0.0076 max mem: 33408 +Epoch: [4] [2410/2639] eta: 0:11:33 lr: 4.443660804839262e-05 loss: 0.1248 (0.1304) time: 3.0466 data: 0.0076 max mem: 33408 +Epoch: [4] [2420/2639] eta: 0:11:02 lr: 4.443228880577027e-05 loss: 0.1167 (0.1303) time: 3.0555 data: 0.0075 max mem: 33408 +Epoch: [4] [2430/2639] eta: 0:10:32 lr: 4.442796951649503e-05 loss: 0.1107 (0.1303) time: 3.0077 data: 0.0077 max mem: 33408 +Epoch: [4] [2440/2639] eta: 0:10:02 lr: 4.442365018056132e-05 loss: 0.1115 (0.1304) time: 3.0146 data: 0.0079 max mem: 33408 +Epoch: [4] [2450/2639] eta: 0:09:32 lr: 4.441933079796363e-05 loss: 0.1330 (0.1304) time: 3.0143 data: 0.0077 max mem: 33408 +Epoch: [4] [2460/2639] eta: 0:09:01 lr: 4.44150113686964e-05 loss: 0.1190 (0.1304) time: 3.0228 data: 0.0073 max mem: 33408 +Epoch: [4] [2470/2639] eta: 0:08:31 lr: 4.441069189275408e-05 loss: 0.1108 (0.1304) time: 3.0215 data: 0.0077 max mem: 33408 +Epoch: [4] [2480/2639] eta: 0:08:01 lr: 4.440637237013112e-05 loss: 0.1200 (0.1305) time: 3.0317 data: 0.0081 max mem: 33408 +Epoch: [4] [2490/2639] eta: 0:07:31 lr: 4.440205280082198e-05 loss: 0.1201 (0.1304) time: 3.0523 data: 0.0080 max mem: 33408 +Epoch: [4] [2500/2639] eta: 0:07:00 lr: 4.43977331848211e-05 loss: 0.1236 (0.1304) time: 3.0059 data: 0.0078 max mem: 33408 +Epoch: [4] [2510/2639] eta: 0:06:30 lr: 4.4393413522122936e-05 loss: 0.1439 (0.1305) time: 3.0303 data: 0.0080 max mem: 33408 +Epoch: [4] [2520/2639] eta: 0:06:00 lr: 4.438909381272192e-05 loss: 0.1246 (0.1305) time: 3.0614 data: 0.0083 max mem: 33408 +Epoch: [4] [2530/2639] eta: 0:05:29 lr: 4.4384774056612516e-05 loss: 0.1104 (0.1305) time: 3.0236 data: 0.0082 max mem: 33408 +Epoch: [4] [2540/2639] eta: 0:04:59 lr: 4.438045425378915e-05 loss: 0.1104 (0.1305) time: 3.0208 data: 0.0078 max mem: 33408 +Epoch: [4] [2550/2639] eta: 0:04:29 lr: 4.437613440424628e-05 loss: 0.1317 (0.1305) time: 3.0341 data: 0.0076 max mem: 33408 +Epoch: [4] [2560/2639] eta: 0:03:59 lr: 4.437181450797833e-05 loss: 0.1317 (0.1305) time: 3.0477 data: 0.0076 max mem: 33408 +Epoch: [4] [2570/2639] eta: 0:03:28 lr: 4.436749456497975e-05 loss: 0.1186 (0.1304) time: 3.0185 data: 0.0078 max mem: 33408 +Epoch: [4] [2580/2639] eta: 0:02:58 lr: 4.436317457524499e-05 loss: 0.1064 (0.1303) time: 3.0235 data: 0.0077 max mem: 33408 +Epoch: [4] [2590/2639] eta: 0:02:28 lr: 4.4358854538768466e-05 loss: 0.1051 (0.1304) time: 3.0163 data: 0.0075 max mem: 33408 +Epoch: [4] [2600/2639] eta: 0:01:58 lr: 4.435453445554463e-05 loss: 0.1013 (0.1303) time: 3.0150 data: 0.0079 max mem: 33408 +Epoch: [4] [2610/2639] eta: 0:01:27 lr: 4.435021432556791e-05 loss: 0.1000 (0.1302) time: 3.0210 data: 0.0080 max mem: 33408 +Epoch: [4] [2620/2639] eta: 0:00:57 lr: 4.434589414883274e-05 loss: 0.1031 (0.1301) time: 2.9989 data: 0.0075 max mem: 33408 +Epoch: [4] [2630/2639] eta: 0:00:27 lr: 4.434157392533355e-05 loss: 0.1032 (0.1301) time: 3.0348 data: 0.0073 max mem: 33408 +Epoch: [4] Total time: 2:13:09 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 2:31:55 time: 3.5426 data: 3.4600 max mem: 33408 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 100/2573] eta: 0:04:38 time: 0.0778 data: 0.0014 max mem: 33408 +Test: [ 200/2573] eta: 0:03:49 time: 0.0788 data: 0.0013 max mem: 33408 +Test: [ 300/2573] eta: 0:03:25 time: 0.0805 data: 0.0013 max mem: 33408 +Test: [ 400/2573] eta: 0:03:10 time: 0.0804 data: 0.0013 max mem: 33408 +Test: [ 500/2573] eta: 0:02:57 time: 0.0798 data: 0.0015 max mem: 33408 +Test: [ 600/2573] eta: 0:02:47 time: 0.0794 data: 0.0015 max mem: 33408 +Test: [ 700/2573] eta: 0:02:38 time: 0.0809 data: 0.0015 max mem: 33408 +Test: [ 800/2573] eta: 0:02:29 time: 0.0826 data: 0.0013 max mem: 33408 +Test: [ 900/2573] eta: 0:02:20 time: 0.0797 data: 0.0014 max mem: 33408 +Test: [1000/2573] eta: 0:02:11 time: 0.0807 data: 0.0014 max mem: 33408 +Test: [1100/2573] eta: 0:02:02 time: 0.0805 data: 0.0015 max mem: 33408 +Test: [1200/2573] eta: 0:01:53 time: 0.0801 data: 0.0014 max mem: 33408 +Test: [1300/2573] eta: 0:01:45 time: 0.0804 data: 0.0015 max mem: 33408 +Test: [1400/2573] eta: 0:01:36 time: 0.0799 data: 0.0016 max mem: 33408 +Test: [1500/2573] eta: 0:01:28 time: 0.0799 data: 0.0014 max mem: 33408 +Test: [1600/2573] eta: 0:01:20 time: 0.0842 data: 0.0015 max mem: 33408 +Test: [1700/2573] eta: 0:01:11 time: 0.0784 data: 0.0014 max mem: 33408 +Test: [1800/2573] eta: 0:01:03 time: 0.0823 data: 0.0014 max mem: 33408 +Test: [1900/2573] eta: 0:00:55 time: 0.0789 data: 0.0014 max mem: 33408 +Test: [2000/2573] eta: 0:00:46 time: 0.0804 data: 0.0014 max mem: 33408 +Test: [2100/2573] eta: 0:00:38 time: 0.0833 data: 0.0015 max mem: 33408 +Test: [2200/2573] eta: 0:00:30 time: 0.0820 data: 0.0014 max mem: 33408 +Test: [2300/2573] eta: 0:00:22 time: 0.0827 data: 0.0014 max mem: 33408 +Test: [2400/2573] eta: 0:00:14 time: 0.0770 data: 0.0014 max mem: 33408 +Test: [2500/2573] eta: 0:00:05 time: 0.0810 data: 0.0016 max mem: 33408 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: Total time: 0:03:31 +Final results: +Mean IoU is 53.06 + + precision@0.5 = 59.17 + precision@0.6 = 51.94 + precision@0.7 = 43.53 + precision@0.8 = 31.41 + precision@0.9 = 12.62 + overall IoU = 54.40 + +Average object IoU 53.05934462613138 +Overall IoU 54.40000534057617 +Better epoch: 4 + +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [5] [ 0/2639] eta: 4:02:34 lr: 4.433768568419645e-05 loss: 0.1642 (0.1642) time: 5.5153 data: 2.3489 max mem: 33408 +Epoch: [5] [ 10/2639] eta: 2:21:05 lr: 4.433336537183029e-05 loss: 0.0935 (0.1046) time: 3.2200 data: 0.2205 max mem: 33408 +Epoch: [5] [ 20/2639] eta: 2:18:00 lr: 4.432904501268396e-05 loss: 0.0977 (0.1097) time: 3.0438 data: 0.0078 max mem: 33408 +Epoch: [5] [ 30/2639] eta: 2:15:44 lr: 4.432472460675189e-05 loss: 0.1169 (0.1117) time: 3.0678 data: 0.0082 max mem: 33408 +Epoch: [5] [ 40/2639] eta: 2:14:08 lr: 4.43204041540285e-05 loss: 0.1169 (0.1168) time: 3.0291 data: 0.0084 max mem: 33408 +Epoch: [5] [ 50/2639] eta: 2:12:52 lr: 4.431608365450822e-05 loss: 0.1183 (0.1197) time: 3.0136 data: 0.0083 max mem: 33408 +Epoch: [5] [ 60/2639] eta: 2:11:51 lr: 4.431176310818548e-05 loss: 0.1138 (0.1177) time: 3.0077 data: 0.0084 max mem: 33408 +Epoch: [5] [ 70/2639] eta: 2:11:15 lr: 4.4307442515054684e-05 loss: 0.0889 (0.1175) time: 3.0309 data: 0.0084 max mem: 33408 +Epoch: [5] [ 80/2639] eta: 2:10:44 lr: 4.430312187511028e-05 loss: 0.0920 (0.1155) time: 3.0583 data: 0.0080 max mem: 33408 +Epoch: [5] [ 90/2639] eta: 2:10:14 lr: 4.429880118834666e-05 loss: 0.1094 (0.1150) time: 3.0650 data: 0.0079 max mem: 33408 +Epoch: [5] [ 100/2639] eta: 2:09:38 lr: 4.429448045475826e-05 loss: 0.1015 (0.1130) time: 3.0572 data: 0.0076 max mem: 33408 +Epoch: [5] [ 110/2639] eta: 2:09:00 lr: 4.429015967433949e-05 loss: 0.0944 (0.1138) time: 3.0395 data: 0.0074 max mem: 33408 +Epoch: [5] [ 120/2639] eta: 2:08:29 lr: 4.428583884708477e-05 loss: 0.1044 (0.1131) time: 3.0437 data: 0.0074 max mem: 33408 +Epoch: [5] [ 130/2639] eta: 2:07:58 lr: 4.4281517972988514e-05 loss: 0.1117 (0.1147) time: 3.0587 data: 0.0075 max mem: 33408 +Epoch: [5] [ 140/2639] eta: 2:07:14 lr: 4.4277197052045135e-05 loss: 0.1150 (0.1149) time: 3.0228 data: 0.0077 max mem: 33408 +Epoch: [5] [ 150/2639] eta: 2:06:45 lr: 4.427287608424906e-05 loss: 0.1146 (0.1165) time: 3.0228 data: 0.0078 max mem: 33408 +Epoch: [5] [ 160/2639] eta: 2:06:07 lr: 4.426855506959466e-05 loss: 0.1235 (0.1174) time: 3.0342 data: 0.0075 max mem: 33408 +Epoch: [5] [ 170/2639] eta: 2:05:24 lr: 4.4264234008076386e-05 loss: 0.1120 (0.1168) time: 2.9889 data: 0.0074 max mem: 33408 +Epoch: [5] [ 180/2639] eta: 2:05:11 lr: 4.425991289968863e-05 loss: 0.1006 (0.1163) time: 3.0716 data: 0.0076 max mem: 33408 +Epoch: [5] [ 190/2639] eta: 2:04:37 lr: 4.425559174442579e-05 loss: 0.0976 (0.1161) time: 3.1021 data: 0.0080 max mem: 33408 +Epoch: [5] [ 200/2639] eta: 2:04:05 lr: 4.425127054228229e-05 loss: 0.1078 (0.1158) time: 3.0341 data: 0.0079 max mem: 33408 +Epoch: [5] [ 210/2639] eta: 2:03:39 lr: 4.424694929325253e-05 loss: 0.1150 (0.1173) time: 3.0659 data: 0.0076 max mem: 33408 +Epoch: [5] [ 220/2639] eta: 2:03:03 lr: 4.4242627997330896e-05 loss: 0.1207 (0.1173) time: 3.0510 data: 0.0078 max mem: 33408 +Epoch: [5] [ 230/2639] eta: 2:02:33 lr: 4.4238306654511814e-05 loss: 0.1113 (0.1179) time: 3.0314 data: 0.0079 max mem: 33408 +Epoch: [5] [ 240/2639] eta: 2:01:57 lr: 4.423398526478967e-05 loss: 0.1184 (0.1199) time: 3.0277 data: 0.0079 max mem: 33408 +Epoch: [5] [ 250/2639] eta: 2:01:23 lr: 4.422966382815888e-05 loss: 0.1134 (0.1194) time: 3.0040 data: 0.0081 max mem: 33408 +Epoch: [5] [ 260/2639] eta: 2:00:50 lr: 4.4225342344613816e-05 loss: 0.1060 (0.1193) time: 3.0141 data: 0.0079 max mem: 33408 +Epoch: [5] [ 270/2639] eta: 2:00:15 lr: 4.4221020814148896e-05 loss: 0.1035 (0.1189) time: 3.0088 data: 0.0080 max mem: 33408 +Epoch: [5] [ 280/2639] eta: 1:59:39 lr: 4.4216699236758506e-05 loss: 0.1035 (0.1194) time: 2.9869 data: 0.0084 max mem: 33408 +Epoch: [5] [ 290/2639] eta: 1:59:04 lr: 4.421237761243704e-05 loss: 0.1138 (0.1191) time: 2.9849 data: 0.0084 max mem: 33408 +Epoch: [5] [ 300/2639] eta: 1:58:42 lr: 4.420805594117891e-05 loss: 0.1132 (0.1194) time: 3.0721 data: 0.0081 max mem: 33408 +Epoch: [5] [ 310/2639] eta: 1:58:09 lr: 4.420373422297848e-05 loss: 0.1070 (0.1185) time: 3.0778 data: 0.0078 max mem: 33408 +Epoch: [5] [ 320/2639] eta: 1:57:37 lr: 4.4199412457830166e-05 loss: 0.0917 (0.1182) time: 3.0144 data: 0.0077 max mem: 33408 +Epoch: [5] [ 330/2639] eta: 1:57:03 lr: 4.419509064572833e-05 loss: 0.0979 (0.1182) time: 3.0091 data: 0.0080 max mem: 33408 +Epoch: [5] [ 340/2639] eta: 1:56:33 lr: 4.419076878666738e-05 loss: 0.1104 (0.1192) time: 3.0243 data: 0.0078 max mem: 33408 +Epoch: [5] [ 350/2639] eta: 1:56:03 lr: 4.41864468806417e-05 loss: 0.1223 (0.1190) time: 3.0482 data: 0.0076 max mem: 33408 +Epoch: [5] [ 360/2639] eta: 1:55:31 lr: 4.4182124927645666e-05 loss: 0.1193 (0.1190) time: 3.0257 data: 0.0077 max mem: 33408 +Epoch: [5] [ 370/2639] eta: 1:55:00 lr: 4.417780292767368e-05 loss: 0.1108 (0.1189) time: 3.0225 data: 0.0077 max mem: 33408 +Epoch: [5] [ 380/2639] eta: 1:54:27 lr: 4.417348088072011e-05 loss: 0.1126 (0.1196) time: 3.0197 data: 0.0078 max mem: 33408 +Epoch: [5] [ 390/2639] eta: 1:54:00 lr: 4.4169158786779335e-05 loss: 0.1250 (0.1194) time: 3.0492 data: 0.0079 max mem: 33408 +Epoch: [5] [ 400/2639] eta: 1:53:27 lr: 4.416483664584575e-05 loss: 0.1086 (0.1193) time: 3.0478 data: 0.0080 max mem: 33408 +Epoch: [5] [ 410/2639] eta: 1:52:57 lr: 4.416051445791371e-05 loss: 0.1105 (0.1191) time: 3.0177 data: 0.0079 max mem: 33408 +Epoch: [5] [ 420/2639] eta: 1:52:22 lr: 4.415619222297763e-05 loss: 0.1105 (0.1193) time: 2.9991 data: 0.0083 max mem: 33408 +Epoch: [5] [ 430/2639] eta: 1:51:55 lr: 4.4151869941031854e-05 loss: 0.1144 (0.1196) time: 3.0300 data: 0.0084 max mem: 33408 +Epoch: [5] [ 440/2639] eta: 1:51:23 lr: 4.4147547612070764e-05 loss: 0.1177 (0.1195) time: 3.0527 data: 0.0078 max mem: 33408 +Epoch: [5] [ 450/2639] eta: 1:50:54 lr: 4.414322523608875e-05 loss: 0.1055 (0.1195) time: 3.0413 data: 0.0076 max mem: 33408 +Epoch: [5] [ 460/2639] eta: 1:50:26 lr: 4.413890281308017e-05 loss: 0.1073 (0.1194) time: 3.0809 data: 0.0075 max mem: 33408 +Epoch: [5] [ 470/2639] eta: 1:49:55 lr: 4.41345803430394e-05 loss: 0.1258 (0.1198) time: 3.0553 data: 0.0075 max mem: 33408 +Epoch: [5] [ 480/2639] eta: 1:49:24 lr: 4.41302578259608e-05 loss: 0.1288 (0.1196) time: 3.0303 data: 0.0076 max mem: 33408 +Epoch: [5] [ 490/2639] eta: 1:48:52 lr: 4.4125935261838754e-05 loss: 0.1180 (0.1200) time: 3.0232 data: 0.0076 max mem: 33408 +Epoch: [5] [ 500/2639] eta: 1:48:20 lr: 4.4121612650667624e-05 loss: 0.1185 (0.1202) time: 3.0065 data: 0.0074 max mem: 33408 +Epoch: [5] [ 510/2639] eta: 1:47:47 lr: 4.4117289992441774e-05 loss: 0.1042 (0.1202) time: 2.9875 data: 0.0074 max mem: 33408 +Epoch: [5] [ 520/2639] eta: 1:47:18 lr: 4.4112967287155566e-05 loss: 0.0979 (0.1198) time: 3.0201 data: 0.0075 max mem: 33408 +Epoch: [5] [ 530/2639] eta: 1:46:45 lr: 4.4108644534803376e-05 loss: 0.0966 (0.1195) time: 3.0169 data: 0.0080 max mem: 33408 +Epoch: [5] [ 540/2639] eta: 1:46:17 lr: 4.4104321735379546e-05 loss: 0.1009 (0.1192) time: 3.0312 data: 0.0079 max mem: 33408 +Epoch: [5] [ 550/2639] eta: 1:45:45 lr: 4.409999888887846e-05 loss: 0.1026 (0.1194) time: 3.0482 data: 0.0077 max mem: 33408 +Epoch: [5] [ 560/2639] eta: 1:45:16 lr: 4.4095675995294454e-05 loss: 0.1241 (0.1197) time: 3.0441 data: 0.0076 max mem: 33408 +Epoch: [5] [ 570/2639] eta: 1:44:44 lr: 4.409135305462191e-05 loss: 0.1264 (0.1206) time: 3.0439 data: 0.0073 max mem: 33408 +Epoch: [5] [ 580/2639] eta: 1:44:13 lr: 4.408703006685517e-05 loss: 0.0978 (0.1202) time: 3.0064 data: 0.0072 max mem: 33408 +Epoch: [5] [ 590/2639] eta: 1:43:41 lr: 4.4082707031988595e-05 loss: 0.0986 (0.1202) time: 2.9952 data: 0.0072 max mem: 33408 +Epoch: [5] [ 600/2639] eta: 1:43:10 lr: 4.4078383950016536e-05 loss: 0.1050 (0.1199) time: 2.9954 data: 0.0072 max mem: 33408 +Epoch: [5] [ 610/2639] eta: 1:42:44 lr: 4.407406082093336e-05 loss: 0.0973 (0.1198) time: 3.0894 data: 0.0071 max mem: 33408 +Epoch: [5] [ 620/2639] eta: 1:42:15 lr: 4.4069737644733396e-05 loss: 0.1105 (0.1199) time: 3.1288 data: 0.0073 max mem: 33408 +Epoch: [5] [ 630/2639] eta: 1:41:43 lr: 4.406541442141101e-05 loss: 0.1161 (0.1196) time: 3.0430 data: 0.0073 max mem: 33408 +Epoch: [5] [ 640/2639] eta: 1:41:12 lr: 4.406109115096055e-05 loss: 0.0952 (0.1195) time: 3.0031 data: 0.0073 max mem: 33408 +Epoch: [5] [ 650/2639] eta: 1:40:41 lr: 4.405676783337636e-05 loss: 0.1092 (0.1199) time: 3.0144 data: 0.0080 max mem: 33408 +Epoch: [5] [ 660/2639] eta: 1:40:12 lr: 4.405244446865279e-05 loss: 0.1110 (0.1199) time: 3.0448 data: 0.0081 max mem: 33408 +Epoch: [5] [ 670/2639] eta: 1:39:41 lr: 4.4048121056784194e-05 loss: 0.0943 (0.1195) time: 3.0435 data: 0.0076 max mem: 33408 +Epoch: [5] [ 680/2639] eta: 1:39:10 lr: 4.404379759776489e-05 loss: 0.0961 (0.1195) time: 3.0206 data: 0.0079 max mem: 33408 +Epoch: [5] [ 690/2639] eta: 1:38:39 lr: 4.403947409158925e-05 loss: 0.1106 (0.1195) time: 3.0151 data: 0.0082 max mem: 33408 +Epoch: [5] [ 700/2639] eta: 1:38:07 lr: 4.4035150538251604e-05 loss: 0.1041 (0.1191) time: 2.9981 data: 0.0079 max mem: 33408 +Epoch: [5] [ 710/2639] eta: 1:37:36 lr: 4.403082693774629e-05 loss: 0.1037 (0.1189) time: 3.0000 data: 0.0078 max mem: 33408 +Epoch: [5] [ 720/2639] eta: 1:37:04 lr: 4.402650329006764e-05 loss: 0.1045 (0.1192) time: 2.9976 data: 0.0076 max mem: 33408 +Epoch: [5] [ 730/2639] eta: 1:36:32 lr: 4.4022179595210014e-05 loss: 0.1220 (0.1192) time: 2.9821 data: 0.0072 max mem: 33408 +Epoch: [5] [ 740/2639] eta: 1:36:02 lr: 4.401785585316773e-05 loss: 0.1148 (0.1192) time: 3.0049 data: 0.0070 max mem: 33408 +Epoch: [5] [ 750/2639] eta: 1:35:33 lr: 4.401353206393513e-05 loss: 0.1095 (0.1189) time: 3.0614 data: 0.0072 max mem: 33408 +Epoch: [5] [ 760/2639] eta: 1:35:02 lr: 4.4009208227506545e-05 loss: 0.1015 (0.1188) time: 3.0526 data: 0.0072 max mem: 33408 +Epoch: [5] [ 770/2639] eta: 1:34:31 lr: 4.400488434387631e-05 loss: 0.1072 (0.1188) time: 3.0030 data: 0.0072 max mem: 33408 +Epoch: [5] [ 780/2639] eta: 1:34:00 lr: 4.4000560413038755e-05 loss: 0.1187 (0.1191) time: 3.0079 data: 0.0075 max mem: 33408 +Epoch: [5] [ 790/2639] eta: 1:33:29 lr: 4.399623643498821e-05 loss: 0.1124 (0.1190) time: 3.0094 data: 0.0075 max mem: 33408 +Epoch: [5] [ 800/2639] eta: 1:32:57 lr: 4.3991912409719006e-05 loss: 0.1002 (0.1189) time: 2.9793 data: 0.0074 max mem: 33408 +Epoch: [5] [ 810/2639] eta: 1:32:26 lr: 4.398758833722546e-05 loss: 0.0832 (0.1185) time: 2.9922 data: 0.0074 max mem: 33408 +Epoch: [5] [ 820/2639] eta: 1:31:55 lr: 4.398326421750191e-05 loss: 0.1013 (0.1186) time: 2.9953 data: 0.0071 max mem: 33408 +Epoch: [5] [ 830/2639] eta: 1:31:25 lr: 4.397894005054268e-05 loss: 0.1112 (0.1185) time: 3.0190 data: 0.0070 max mem: 33408 +Epoch: [5] [ 840/2639] eta: 1:30:53 lr: 4.3974615836342096e-05 loss: 0.1165 (0.1185) time: 3.0036 data: 0.0072 max mem: 33408 +Epoch: [5] [ 850/2639] eta: 1:30:23 lr: 4.3970291574894465e-05 loss: 0.1165 (0.1185) time: 3.0017 data: 0.0073 max mem: 33408 +Epoch: [5] [ 860/2639] eta: 1:29:51 lr: 4.3965967266194126e-05 loss: 0.1025 (0.1185) time: 3.0137 data: 0.0072 max mem: 33408 +Epoch: [5] [ 870/2639] eta: 1:29:22 lr: 4.3961642910235386e-05 loss: 0.1071 (0.1186) time: 3.0237 data: 0.0072 max mem: 33408 +Epoch: [5] [ 880/2639] eta: 1:28:52 lr: 4.3957318507012566e-05 loss: 0.1067 (0.1185) time: 3.0695 data: 0.0073 max mem: 33408 +Epoch: [5] [ 890/2639] eta: 1:28:21 lr: 4.395299405651999e-05 loss: 0.1033 (0.1184) time: 3.0231 data: 0.0077 max mem: 33408 +Epoch: [5] [ 900/2639] eta: 1:27:51 lr: 4.3948669558751955e-05 loss: 0.1073 (0.1185) time: 3.0173 data: 0.0080 max mem: 33408 +Epoch: [5] [ 910/2639] eta: 1:27:21 lr: 4.39443450137028e-05 loss: 0.1125 (0.1185) time: 3.0408 data: 0.0079 max mem: 33408 +Epoch: [5] [ 920/2639] eta: 1:26:49 lr: 4.394002042136683e-05 loss: 0.1068 (0.1185) time: 2.9986 data: 0.0077 max mem: 33408 +Epoch: [5] [ 930/2639] eta: 1:26:18 lr: 4.393569578173834e-05 loss: 0.0961 (0.1183) time: 2.9717 data: 0.0075 max mem: 33408 +Epoch: [5] [ 940/2639] eta: 1:25:46 lr: 4.3931371094811655e-05 loss: 0.0998 (0.1185) time: 2.9682 data: 0.0077 max mem: 33408 +Epoch: [5] [ 950/2639] eta: 1:25:16 lr: 4.39270463605811e-05 loss: 0.1109 (0.1185) time: 2.9858 data: 0.0080 max mem: 33408 +Epoch: [5] [ 960/2639] eta: 1:24:46 lr: 4.3922721579040955e-05 loss: 0.0996 (0.1184) time: 3.0451 data: 0.0081 max mem: 33408 +Epoch: [5] [ 970/2639] eta: 1:24:16 lr: 4.391839675018553e-05 loss: 0.0951 (0.1182) time: 3.0382 data: 0.0082 max mem: 33408 +Epoch: [5] [ 980/2639] eta: 1:23:45 lr: 4.3914071874009145e-05 loss: 0.1066 (0.1184) time: 3.0092 data: 0.0083 max mem: 33408 +Epoch: [5] [ 990/2639] eta: 1:23:15 lr: 4.390974695050609e-05 loss: 0.1021 (0.1182) time: 3.0185 data: 0.0083 max mem: 33408 +Epoch: [5] [1000/2639] eta: 1:22:45 lr: 4.390542197967068e-05 loss: 0.0930 (0.1180) time: 3.0439 data: 0.0082 max mem: 33408 +Epoch: [5] [1010/2639] eta: 1:22:15 lr: 4.3901096961497213e-05 loss: 0.0947 (0.1180) time: 3.0671 data: 0.0079 max mem: 33408 +Epoch: [5] [1020/2639] eta: 1:21:44 lr: 4.3896771895979976e-05 loss: 0.0964 (0.1179) time: 3.0139 data: 0.0077 max mem: 33408 +Epoch: [5] [1030/2639] eta: 1:21:14 lr: 4.3892446783113286e-05 loss: 0.1141 (0.1180) time: 3.0054 data: 0.0075 max mem: 33408 +Epoch: [5] [1040/2639] eta: 1:20:44 lr: 4.388812162289143e-05 loss: 0.1182 (0.1181) time: 3.0671 data: 0.0076 max mem: 33408 +Epoch: [5] [1050/2639] eta: 1:20:14 lr: 4.38837964153087e-05 loss: 0.1176 (0.1181) time: 3.0487 data: 0.0080 max mem: 33408 +Epoch: [5] [1060/2639] eta: 1:19:45 lr: 4.38794711603594e-05 loss: 0.1241 (0.1183) time: 3.0708 data: 0.0080 max mem: 33408 +Epoch: [5] [1070/2639] eta: 1:19:15 lr: 4.387514585803782e-05 loss: 0.1297 (0.1183) time: 3.0724 data: 0.0080 max mem: 33408 +Epoch: [5] [1080/2639] eta: 1:18:44 lr: 4.387082050833825e-05 loss: 0.1138 (0.1184) time: 3.0084 data: 0.0081 max mem: 33408 +Epoch: [5] [1090/2639] eta: 1:18:12 lr: 4.3866495111254997e-05 loss: 0.1090 (0.1182) time: 2.9706 data: 0.0079 max mem: 33408 +Epoch: [5] [1100/2639] eta: 1:17:41 lr: 4.386216966678232e-05 loss: 0.1058 (0.1182) time: 2.9648 data: 0.0079 max mem: 33408 +Epoch: [5] [1110/2639] eta: 1:17:12 lr: 4.385784417491454e-05 loss: 0.1142 (0.1183) time: 3.0399 data: 0.0080 max mem: 33408 +Epoch: [5] [1120/2639] eta: 1:16:42 lr: 4.3853518635645906e-05 loss: 0.1142 (0.1185) time: 3.0906 data: 0.0080 max mem: 33408 +Epoch: [5] [1130/2639] eta: 1:16:11 lr: 4.384919304897074e-05 loss: 0.1040 (0.1185) time: 3.0342 data: 0.0079 max mem: 33408 +Epoch: [5] [1140/2639] eta: 1:15:42 lr: 4.3844867414883304e-05 loss: 0.0994 (0.1183) time: 3.0271 data: 0.0078 max mem: 33408 +Epoch: [5] [1150/2639] eta: 1:15:11 lr: 4.384054173337789e-05 loss: 0.0971 (0.1183) time: 3.0517 data: 0.0075 max mem: 33408 +Epoch: [5] [1160/2639] eta: 1:14:41 lr: 4.383621600444878e-05 loss: 0.1209 (0.1185) time: 3.0288 data: 0.0077 max mem: 33408 +Epoch: [5] [1170/2639] eta: 1:14:10 lr: 4.3831890228090254e-05 loss: 0.1259 (0.1185) time: 2.9976 data: 0.0078 max mem: 33408 +Epoch: [5] [1180/2639] eta: 1:13:40 lr: 4.3827564404296586e-05 loss: 0.1024 (0.1185) time: 3.0152 data: 0.0079 max mem: 33408 +Epoch: [5] [1190/2639] eta: 1:13:09 lr: 4.382323853306205e-05 loss: 0.0946 (0.1183) time: 3.0183 data: 0.0080 max mem: 33408 +Epoch: [5] [1200/2639] eta: 1:12:40 lr: 4.381891261438094e-05 loss: 0.1001 (0.1184) time: 3.0455 data: 0.0079 max mem: 33408 +Epoch: [5] [1210/2639] eta: 1:12:10 lr: 4.3814586648247515e-05 loss: 0.1123 (0.1184) time: 3.0779 data: 0.0082 max mem: 33408 +Epoch: [5] [1220/2639] eta: 1:11:40 lr: 4.381026063465605e-05 loss: 0.1296 (0.1186) time: 3.0646 data: 0.0079 max mem: 33408 +Epoch: [5] [1230/2639] eta: 1:11:10 lr: 4.380593457360082e-05 loss: 0.1331 (0.1186) time: 3.0813 data: 0.0075 max mem: 33408 +Epoch: [5] [1240/2639] eta: 1:10:39 lr: 4.3801608465076104e-05 loss: 0.1118 (0.1185) time: 3.0241 data: 0.0076 max mem: 33408 +Epoch: [5] [1250/2639] eta: 1:10:09 lr: 4.379728230907617e-05 loss: 0.1127 (0.1186) time: 3.0141 data: 0.0075 max mem: 33408 +Epoch: [5] [1260/2639] eta: 1:09:38 lr: 4.379295610559526e-05 loss: 0.1170 (0.1186) time: 3.0045 data: 0.0075 max mem: 33408 +Epoch: [5] [1270/2639] eta: 1:09:08 lr: 4.378862985462767e-05 loss: 0.1035 (0.1186) time: 3.0138 data: 0.0075 max mem: 33408 +Epoch: [5] [1280/2639] eta: 1:08:38 lr: 4.378430355616767e-05 loss: 0.0985 (0.1186) time: 3.0422 data: 0.0074 max mem: 33408 +Epoch: [5] [1290/2639] eta: 1:08:08 lr: 4.37799772102095e-05 loss: 0.1137 (0.1186) time: 3.0380 data: 0.0076 max mem: 33408 +Epoch: [5] [1300/2639] eta: 1:07:37 lr: 4.377565081674744e-05 loss: 0.1144 (0.1186) time: 3.0233 data: 0.0077 max mem: 33408 +Epoch: [5] [1310/2639] eta: 1:07:07 lr: 4.377132437577574e-05 loss: 0.1173 (0.1187) time: 2.9951 data: 0.0079 max mem: 33408 +Epoch: [5] [1320/2639] eta: 1:06:36 lr: 4.376699788728868e-05 loss: 0.1285 (0.1188) time: 3.0112 data: 0.0080 max mem: 33408 +Epoch: [5] [1330/2639] eta: 1:06:06 lr: 4.3762671351280495e-05 loss: 0.1127 (0.1187) time: 3.0305 data: 0.0081 max mem: 33408 +Epoch: [5] [1340/2639] eta: 1:05:35 lr: 4.375834476774546e-05 loss: 0.1064 (0.1188) time: 3.0226 data: 0.0079 max mem: 33408 +Epoch: [5] [1350/2639] eta: 1:05:05 lr: 4.375401813667782e-05 loss: 0.0982 (0.1186) time: 2.9911 data: 0.0078 max mem: 33408 +Epoch: [5] [1360/2639] eta: 1:04:34 lr: 4.374969145807184e-05 loss: 0.1022 (0.1187) time: 2.9962 data: 0.0079 max mem: 33408 +Epoch: [5] [1370/2639] eta: 1:04:04 lr: 4.374536473192177e-05 loss: 0.1151 (0.1186) time: 3.0449 data: 0.0081 max mem: 33408 +Epoch: [5] [1380/2639] eta: 1:03:34 lr: 4.3741037958221866e-05 loss: 0.1023 (0.1186) time: 3.0360 data: 0.0080 max mem: 33408 +Epoch: [5] [1390/2639] eta: 1:03:04 lr: 4.373671113696637e-05 loss: 0.1160 (0.1188) time: 3.0417 data: 0.0077 max mem: 33408 +Epoch: [5] [1400/2639] eta: 1:02:34 lr: 4.3732384268149534e-05 loss: 0.1128 (0.1187) time: 3.0551 data: 0.0078 max mem: 33408 +Epoch: [5] [1410/2639] eta: 1:02:03 lr: 4.3728057351765615e-05 loss: 0.1127 (0.1188) time: 3.0419 data: 0.0081 max mem: 33408 +Epoch: [5] [1420/2639] eta: 1:01:34 lr: 4.3723730387808856e-05 loss: 0.1058 (0.1186) time: 3.0818 data: 0.0079 max mem: 33408 +Epoch: [5] [1430/2639] eta: 1:01:03 lr: 4.37194033762735e-05 loss: 0.0928 (0.1184) time: 3.0490 data: 0.0076 max mem: 33408 +Epoch: [5] [1440/2639] eta: 1:00:33 lr: 4.371507631715379e-05 loss: 0.0954 (0.1184) time: 3.0079 data: 0.0079 max mem: 33408 +Epoch: [5] [1450/2639] eta: 1:00:02 lr: 4.371074921044398e-05 loss: 0.1166 (0.1186) time: 3.0060 data: 0.0083 max mem: 33408 +Epoch: [5] [1460/2639] eta: 0:59:32 lr: 4.37064220561383e-05 loss: 0.1276 (0.1186) time: 3.0254 data: 0.0077 max mem: 33408 +Epoch: [5] [1470/2639] eta: 0:59:02 lr: 4.3702094854231e-05 loss: 0.1017 (0.1185) time: 3.0773 data: 0.0076 max mem: 33408 +Epoch: [5] [1480/2639] eta: 0:58:33 lr: 4.3697767604716306e-05 loss: 0.1064 (0.1184) time: 3.0929 data: 0.0080 max mem: 33408 +Epoch: [5] [1490/2639] eta: 0:58:02 lr: 4.369344030758847e-05 loss: 0.1316 (0.1187) time: 3.0154 data: 0.0079 max mem: 33408 +Epoch: [5] [1500/2639] eta: 0:57:31 lr: 4.368911296284172e-05 loss: 0.1370 (0.1187) time: 2.9817 data: 0.0078 max mem: 33408 +Epoch: [5] [1510/2639] eta: 0:57:00 lr: 4.368478557047029e-05 loss: 0.1069 (0.1188) time: 2.9920 data: 0.0078 max mem: 33408 +Epoch: [5] [1520/2639] eta: 0:56:30 lr: 4.3680458130468425e-05 loss: 0.1129 (0.1188) time: 2.9643 data: 0.0076 max mem: 33408 +Epoch: [5] [1530/2639] eta: 0:56:00 lr: 4.367613064283035e-05 loss: 0.1081 (0.1188) time: 3.0319 data: 0.0079 max mem: 33408 +Epoch: [5] [1540/2639] eta: 0:55:29 lr: 4.367180310755029e-05 loss: 0.0959 (0.1189) time: 3.0633 data: 0.0079 max mem: 33408 +Epoch: [5] [1550/2639] eta: 0:54:59 lr: 4.3667475524622493e-05 loss: 0.1089 (0.1190) time: 3.0230 data: 0.0076 max mem: 33408 +Epoch: [5] [1560/2639] eta: 0:54:29 lr: 4.366314789404117e-05 loss: 0.1089 (0.1189) time: 3.0235 data: 0.0078 max mem: 33408 +Epoch: [5] [1570/2639] eta: 0:53:59 lr: 4.3658820215800547e-05 loss: 0.1153 (0.1189) time: 3.0378 data: 0.0078 max mem: 33408 +Epoch: [5] [1580/2639] eta: 0:53:28 lr: 4.3654492489894866e-05 loss: 0.1293 (0.1190) time: 3.0006 data: 0.0076 max mem: 33408 +Epoch: [5] [1590/2639] eta: 0:52:58 lr: 4.365016471631834e-05 loss: 0.1189 (0.1191) time: 3.0051 data: 0.0078 max mem: 33408 +Epoch: [5] [1600/2639] eta: 0:52:27 lr: 4.36458368950652e-05 loss: 0.1128 (0.1191) time: 3.0310 data: 0.0080 max mem: 33408 +Epoch: [5] [1610/2639] eta: 0:51:57 lr: 4.3641509026129655e-05 loss: 0.1089 (0.1192) time: 3.0103 data: 0.0080 max mem: 33408 +Epoch: [5] [1620/2639] eta: 0:51:27 lr: 4.3637181109505935e-05 loss: 0.0903 (0.1190) time: 3.0598 data: 0.0084 max mem: 33408 +Epoch: [5] [1630/2639] eta: 0:50:57 lr: 4.363285314518826e-05 loss: 0.0902 (0.1189) time: 3.0637 data: 0.0079 max mem: 33408 +Epoch: [5] [1640/2639] eta: 0:50:27 lr: 4.3628525133170844e-05 loss: 0.1069 (0.1190) time: 3.0560 data: 0.0074 max mem: 33408 +Epoch: [5] [1650/2639] eta: 0:49:56 lr: 4.36241970734479e-05 loss: 0.1087 (0.1189) time: 3.0413 data: 0.0074 max mem: 33408 +Epoch: [5] [1660/2639] eta: 0:49:26 lr: 4.361986896601366e-05 loss: 0.1156 (0.1191) time: 3.0321 data: 0.0077 max mem: 33408 +Epoch: [5] [1670/2639] eta: 0:48:56 lr: 4.3615540810862315e-05 loss: 0.1126 (0.1189) time: 3.0773 data: 0.0078 max mem: 33408 +Epoch: [5] [1680/2639] eta: 0:48:25 lr: 4.361121260798809e-05 loss: 0.1031 (0.1189) time: 3.0273 data: 0.0078 max mem: 33408 +Epoch: [5] [1690/2639] eta: 0:47:55 lr: 4.36068843573852e-05 loss: 0.1063 (0.1189) time: 3.0031 data: 0.0076 max mem: 33408 +Epoch: [5] [1700/2639] eta: 0:47:25 lr: 4.360255605904785e-05 loss: 0.0995 (0.1188) time: 3.0249 data: 0.0073 max mem: 33408 +Epoch: [5] [1710/2639] eta: 0:46:54 lr: 4.359822771297024e-05 loss: 0.1095 (0.1188) time: 2.9903 data: 0.0078 max mem: 33408 +Epoch: [5] [1720/2639] eta: 0:46:24 lr: 4.3593899319146585e-05 loss: 0.1162 (0.1189) time: 3.0290 data: 0.0079 max mem: 33408 +Epoch: [5] [1730/2639] eta: 0:45:54 lr: 4.35895708775711e-05 loss: 0.1074 (0.1188) time: 3.0400 data: 0.0075 max mem: 33408 +Epoch: [5] [1740/2639] eta: 0:45:24 lr: 4.358524238823797e-05 loss: 0.1149 (0.1189) time: 3.0213 data: 0.0077 max mem: 33408 +Epoch: [5] [1750/2639] eta: 0:44:53 lr: 4.358091385114142e-05 loss: 0.1149 (0.1189) time: 3.0389 data: 0.0080 max mem: 33408 +Epoch: [5] [1760/2639] eta: 0:44:23 lr: 4.357658526627563e-05 loss: 0.1001 (0.1189) time: 2.9987 data: 0.0080 max mem: 33408 +Epoch: [5] [1770/2639] eta: 0:43:52 lr: 4.357225663363481e-05 loss: 0.1073 (0.1189) time: 2.9896 data: 0.0078 max mem: 33408 +Epoch: [5] [1780/2639] eta: 0:43:22 lr: 4.356792795321317e-05 loss: 0.1112 (0.1189) time: 3.0196 data: 0.0075 max mem: 33408 +Epoch: [5] [1790/2639] eta: 0:42:52 lr: 4.356359922500489e-05 loss: 0.1030 (0.1189) time: 3.0571 data: 0.0074 max mem: 33408 +Epoch: [5] [1800/2639] eta: 0:42:22 lr: 4.355927044900418e-05 loss: 0.0912 (0.1189) time: 3.0516 data: 0.0077 max mem: 33408 +Epoch: [5] [1810/2639] eta: 0:41:51 lr: 4.355494162520522e-05 loss: 0.0930 (0.1188) time: 3.0520 data: 0.0077 max mem: 33408 +Epoch: [5] [1820/2639] eta: 0:41:21 lr: 4.355061275360222e-05 loss: 0.0996 (0.1188) time: 3.0362 data: 0.0078 max mem: 33408 +Epoch: [5] [1830/2639] eta: 0:40:51 lr: 4.354628383418936e-05 loss: 0.1145 (0.1188) time: 2.9978 data: 0.0078 max mem: 33408 +Epoch: [5] [1840/2639] eta: 0:40:20 lr: 4.354195486696084e-05 loss: 0.1202 (0.1189) time: 3.0296 data: 0.0073 max mem: 33408 +Epoch: [5] [1850/2639] eta: 0:39:50 lr: 4.3537625851910844e-05 loss: 0.1123 (0.1188) time: 3.0417 data: 0.0074 max mem: 33408 +Epoch: [5] [1860/2639] eta: 0:39:20 lr: 4.353329678903356e-05 loss: 0.0981 (0.1188) time: 3.0195 data: 0.0077 max mem: 33408 +Epoch: [5] [1870/2639] eta: 0:38:49 lr: 4.3528967678323174e-05 loss: 0.0876 (0.1188) time: 3.0136 data: 0.0075 max mem: 33408 +Epoch: [5] [1880/2639] eta: 0:38:19 lr: 4.352463851977388e-05 loss: 0.1184 (0.1189) time: 3.0144 data: 0.0073 max mem: 33408 +Epoch: [5] [1890/2639] eta: 0:37:49 lr: 4.352030931337985e-05 loss: 0.1431 (0.1191) time: 3.0385 data: 0.0078 max mem: 33408 +Epoch: [5] [1900/2639] eta: 0:37:18 lr: 4.351598005913528e-05 loss: 0.1316 (0.1191) time: 3.0304 data: 0.0080 max mem: 33408 +Epoch: [5] [1910/2639] eta: 0:36:48 lr: 4.351165075703435e-05 loss: 0.1133 (0.1190) time: 3.0075 data: 0.0075 max mem: 33408 +Epoch: [5] [1920/2639] eta: 0:36:18 lr: 4.3507321407071234e-05 loss: 0.1172 (0.1192) time: 3.0036 data: 0.0071 max mem: 33408 +Epoch: [5] [1930/2639] eta: 0:35:47 lr: 4.3502992009240104e-05 loss: 0.1224 (0.1192) time: 3.0115 data: 0.0072 max mem: 33408 +Epoch: [5] [1940/2639] eta: 0:35:17 lr: 4.349866256353515e-05 loss: 0.1070 (0.1191) time: 3.0683 data: 0.0074 max mem: 33408 +Epoch: [5] [1950/2639] eta: 0:34:47 lr: 4.349433306995054e-05 loss: 0.1034 (0.1193) time: 3.0321 data: 0.0075 max mem: 33408 +Epoch: [5] [1960/2639] eta: 0:34:16 lr: 4.349000352848046e-05 loss: 0.1111 (0.1194) time: 2.9799 data: 0.0077 max mem: 33408 +Epoch: [5] [1970/2639] eta: 0:33:46 lr: 4.348567393911908e-05 loss: 0.1111 (0.1193) time: 2.9968 data: 0.0078 max mem: 33408 +Epoch: [5] [1980/2639] eta: 0:33:16 lr: 4.348134430186055e-05 loss: 0.1052 (0.1193) time: 3.0392 data: 0.0076 max mem: 33408 +Epoch: [5] [1990/2639] eta: 0:32:46 lr: 4.347701461669908e-05 loss: 0.1090 (0.1193) time: 3.0531 data: 0.0076 max mem: 33408 +Epoch: [5] [2000/2639] eta: 0:32:15 lr: 4.347268488362881e-05 loss: 0.1166 (0.1193) time: 3.0491 data: 0.0074 max mem: 33408 +Epoch: [5] [2010/2639] eta: 0:31:45 lr: 4.346835510264391e-05 loss: 0.1126 (0.1193) time: 3.0781 data: 0.0070 max mem: 33408 +Epoch: [5] [2020/2639] eta: 0:31:15 lr: 4.3464025273738556e-05 loss: 0.1105 (0.1193) time: 3.0513 data: 0.0074 max mem: 33408 +Epoch: [5] [2030/2639] eta: 0:30:45 lr: 4.345969539690691e-05 loss: 0.1202 (0.1194) time: 3.0470 data: 0.0078 max mem: 33408 +Epoch: [5] [2040/2639] eta: 0:30:14 lr: 4.3455365472143146e-05 loss: 0.1221 (0.1194) time: 3.0091 data: 0.0076 max mem: 33408 +Epoch: [5] [2050/2639] eta: 0:29:44 lr: 4.3451035499441414e-05 loss: 0.1189 (0.1194) time: 3.0222 data: 0.0075 max mem: 33408 +Epoch: [5] [2060/2639] eta: 0:29:14 lr: 4.344670547879587e-05 loss: 0.1109 (0.1194) time: 3.0797 data: 0.0075 max mem: 33408 +Epoch: [5] [2070/2639] eta: 0:28:43 lr: 4.344237541020068e-05 loss: 0.1154 (0.1194) time: 3.0289 data: 0.0074 max mem: 33408 +Epoch: [5] [2080/2639] eta: 0:28:13 lr: 4.3438045293650015e-05 loss: 0.1039 (0.1193) time: 3.0127 data: 0.0076 max mem: 33408 +Epoch: [5] [2090/2639] eta: 0:27:43 lr: 4.3433715129138025e-05 loss: 0.0972 (0.1192) time: 3.0180 data: 0.0077 max mem: 33408 +Epoch: [5] [2100/2639] eta: 0:27:13 lr: 4.3429384916658856e-05 loss: 0.1073 (0.1193) time: 3.0242 data: 0.0077 max mem: 33408 +Epoch: [5] [2110/2639] eta: 0:26:42 lr: 4.342505465620667e-05 loss: 0.1213 (0.1193) time: 3.0067 data: 0.0078 max mem: 33408 +Epoch: [5] [2120/2639] eta: 0:26:12 lr: 4.3420724347775616e-05 loss: 0.1023 (0.1193) time: 2.9654 data: 0.0078 max mem: 33408 +Epoch: [5] [2130/2639] eta: 0:25:42 lr: 4.3416393991359854e-05 loss: 0.0999 (0.1193) time: 3.0255 data: 0.0076 max mem: 33408 +Epoch: [5] [2140/2639] eta: 0:25:11 lr: 4.341206358695353e-05 loss: 0.1316 (0.1194) time: 3.0802 data: 0.0075 max mem: 33408 +Epoch: [5] [2150/2639] eta: 0:24:41 lr: 4.340773313455079e-05 loss: 0.1363 (0.1195) time: 3.0305 data: 0.0075 max mem: 33408 +Epoch: [5] [2160/2639] eta: 0:24:11 lr: 4.340340263414578e-05 loss: 0.1018 (0.1195) time: 3.0207 data: 0.0075 max mem: 33408 +Epoch: [5] [2170/2639] eta: 0:23:40 lr: 4.339907208573266e-05 loss: 0.0996 (0.1195) time: 3.0214 data: 0.0072 max mem: 33408 +Epoch: [5] [2180/2639] eta: 0:23:10 lr: 4.3394741489305555e-05 loss: 0.1014 (0.1194) time: 3.0401 data: 0.0072 max mem: 33408 +Epoch: [5] [2190/2639] eta: 0:22:40 lr: 4.3390410844858625e-05 loss: 0.1008 (0.1194) time: 3.0472 data: 0.0074 max mem: 33408 +Epoch: [5] [2200/2639] eta: 0:22:09 lr: 4.3386080152386004e-05 loss: 0.0988 (0.1193) time: 3.0199 data: 0.0072 max mem: 33408 +Epoch: [5] [2210/2639] eta: 0:21:39 lr: 4.3381749411881845e-05 loss: 0.0956 (0.1193) time: 3.0169 data: 0.0073 max mem: 33408 +Epoch: [5] [2220/2639] eta: 0:21:09 lr: 4.3377418623340265e-05 loss: 0.1184 (0.1194) time: 3.0202 data: 0.0074 max mem: 33408 +Epoch: [5] [2230/2639] eta: 0:20:39 lr: 4.337308778675541e-05 loss: 0.1156 (0.1194) time: 3.0581 data: 0.0075 max mem: 33408 +Epoch: [5] [2240/2639] eta: 0:20:08 lr: 4.336875690212144e-05 loss: 0.1134 (0.1194) time: 3.0270 data: 0.0075 max mem: 33408 +Epoch: [5] [2250/2639] eta: 0:19:38 lr: 4.336442596943246e-05 loss: 0.1134 (0.1194) time: 3.0281 data: 0.0071 max mem: 33408 +Epoch: [5] [2260/2639] eta: 0:19:08 lr: 4.3360094988682615e-05 loss: 0.1122 (0.1195) time: 3.0336 data: 0.0073 max mem: 33408 +Epoch: [5] [2270/2639] eta: 0:18:37 lr: 4.335576395986604e-05 loss: 0.1142 (0.1195) time: 3.0005 data: 0.0075 max mem: 33408 +Epoch: [5] [2280/2639] eta: 0:18:07 lr: 4.3351432882976865e-05 loss: 0.1142 (0.1196) time: 2.9799 data: 0.0073 max mem: 33408 +Epoch: [5] [2290/2639] eta: 0:17:37 lr: 4.3347101758009215e-05 loss: 0.0996 (0.1196) time: 2.9970 data: 0.0073 max mem: 33408 +Epoch: [5] [2300/2639] eta: 0:17:06 lr: 4.334277058495723e-05 loss: 0.1082 (0.1196) time: 3.0181 data: 0.0076 max mem: 33408 +Epoch: [5] [2310/2639] eta: 0:16:36 lr: 4.333843936381503e-05 loss: 0.0919 (0.1195) time: 3.0335 data: 0.0076 max mem: 33408 +Epoch: [5] [2320/2639] eta: 0:16:06 lr: 4.3334108094576735e-05 loss: 0.0801 (0.1195) time: 3.0581 data: 0.0078 max mem: 33408 +Epoch: [5] [2330/2639] eta: 0:15:36 lr: 4.332977677723648e-05 loss: 0.1000 (0.1195) time: 3.0539 data: 0.0074 max mem: 33408 +Epoch: [5] [2340/2639] eta: 0:15:05 lr: 4.332544541178839e-05 loss: 0.1215 (0.1196) time: 3.0017 data: 0.0073 max mem: 33408 +Epoch: [5] [2350/2639] eta: 0:14:35 lr: 4.332111399822656e-05 loss: 0.1356 (0.1196) time: 2.9508 data: 0.0081 max mem: 33408 +Epoch: [5] [2360/2639] eta: 0:14:05 lr: 4.331678253654515e-05 loss: 0.1179 (0.1196) time: 2.9943 data: 0.0085 max mem: 33408 +Epoch: [5] [2370/2639] eta: 0:13:34 lr: 4.331245102673825e-05 loss: 0.1100 (0.1196) time: 2.9785 data: 0.0082 max mem: 33408 +Epoch: [5] [2380/2639] eta: 0:13:04 lr: 4.330811946879999e-05 loss: 0.1089 (0.1195) time: 2.9514 data: 0.0082 max mem: 33408 +Epoch: [5] [2390/2639] eta: 0:12:33 lr: 4.3303787862724485e-05 loss: 0.1192 (0.1196) time: 2.9931 data: 0.0086 max mem: 33408 +Epoch: [5] [2400/2639] eta: 0:12:03 lr: 4.329945620850584e-05 loss: 0.1145 (0.1196) time: 3.0167 data: 0.0082 max mem: 33408 +Epoch: [5] [2410/2639] eta: 0:11:33 lr: 4.3295124506138185e-05 loss: 0.1028 (0.1195) time: 3.0209 data: 0.0081 max mem: 33408 +Epoch: [5] [2420/2639] eta: 0:11:03 lr: 4.329079275561562e-05 loss: 0.1142 (0.1195) time: 3.0088 data: 0.0083 max mem: 33408 +Epoch: [5] [2430/2639] eta: 0:10:32 lr: 4.3286460956932264e-05 loss: 0.1201 (0.1195) time: 3.0105 data: 0.0085 max mem: 33408 +Epoch: [5] [2440/2639] eta: 0:10:02 lr: 4.328212911008221e-05 loss: 0.1086 (0.1195) time: 3.0342 data: 0.0086 max mem: 33408 +Epoch: [5] [2450/2639] eta: 0:09:32 lr: 4.327779721505959e-05 loss: 0.1086 (0.1195) time: 3.0647 data: 0.0081 max mem: 33408 +Epoch: [5] [2460/2639] eta: 0:09:02 lr: 4.327346527185849e-05 loss: 0.1025 (0.1195) time: 3.0642 data: 0.0081 max mem: 33408 +Epoch: [5] [2470/2639] eta: 0:08:31 lr: 4.326913328047303e-05 loss: 0.1067 (0.1195) time: 3.0033 data: 0.0079 max mem: 33408 +Epoch: [5] [2480/2639] eta: 0:08:01 lr: 4.3264801240897304e-05 loss: 0.1125 (0.1195) time: 2.9945 data: 0.0076 max mem: 33408 +Epoch: [5] [2490/2639] eta: 0:07:31 lr: 4.3260469153125416e-05 loss: 0.1125 (0.1196) time: 3.0523 data: 0.0078 max mem: 33408 +Epoch: [5] [2500/2639] eta: 0:07:00 lr: 4.325613701715147e-05 loss: 0.1155 (0.1196) time: 3.0301 data: 0.0083 max mem: 33408 +Epoch: [5] [2510/2639] eta: 0:06:30 lr: 4.325180483296956e-05 loss: 0.1131 (0.1196) time: 2.9959 data: 0.0082 max mem: 33408 +Epoch: [5] [2520/2639] eta: 0:06:00 lr: 4.3247472600573796e-05 loss: 0.1121 (0.1196) time: 2.9896 data: 0.0080 max mem: 33408 +Epoch: [5] [2530/2639] eta: 0:05:30 lr: 4.324314031995826e-05 loss: 0.0986 (0.1196) time: 3.0372 data: 0.0081 max mem: 33408 +Epoch: [5] [2540/2639] eta: 0:04:59 lr: 4.323880799111706e-05 loss: 0.1133 (0.1196) time: 3.0418 data: 0.0077 max mem: 33408 +Epoch: [5] [2550/2639] eta: 0:04:29 lr: 4.323447561404429e-05 loss: 0.1085 (0.1196) time: 2.9836 data: 0.0079 max mem: 33408 +Epoch: [5] [2560/2639] eta: 0:03:59 lr: 4.323014318873403e-05 loss: 0.1068 (0.1195) time: 2.9893 data: 0.0082 max mem: 33408 +Epoch: [5] [2570/2639] eta: 0:03:28 lr: 4.3225810715180386e-05 loss: 0.1104 (0.1196) time: 3.0485 data: 0.0079 max mem: 33408 +Epoch: [5] [2580/2639] eta: 0:02:58 lr: 4.322147819337744e-05 loss: 0.1202 (0.1196) time: 3.0763 data: 0.0079 max mem: 33408 +Epoch: [5] [2590/2639] eta: 0:02:28 lr: 4.321714562331928e-05 loss: 0.1138 (0.1196) time: 3.0138 data: 0.0084 max mem: 33408 +Epoch: [5] [2600/2639] eta: 0:01:58 lr: 4.321281300499999e-05 loss: 0.1163 (0.1196) time: 2.9973 data: 0.0088 max mem: 33408 +Epoch: [5] [2610/2639] eta: 0:01:27 lr: 4.320848033841367e-05 loss: 0.1147 (0.1196) time: 3.0531 data: 0.0088 max mem: 33408 +Epoch: [5] [2620/2639] eta: 0:00:57 lr: 4.3204147623554394e-05 loss: 0.1116 (0.1196) time: 3.0706 data: 0.0088 max mem: 33408 +Epoch: [5] [2630/2639] eta: 0:00:27 lr: 4.319981486041624e-05 loss: 0.1026 (0.1195) time: 3.0207 data: 0.0082 max mem: 33408 +Epoch: [5] Total time: 2:13:10 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 2:15:45 time: 3.1659 data: 3.0803 max mem: 33408 +Test: [ 100/2573] eta: 0:04:30 time: 0.0790 data: 0.0014 max mem: 33408 +Test: [ 200/2573] eta: 0:03:45 time: 0.0800 data: 0.0014 max mem: 33408 +Test: [ 300/2573] eta: 0:03:24 time: 0.0823 data: 0.0017 max mem: 33408 +Test: [ 400/2573] eta: 0:03:09 time: 0.0814 data: 0.0013 max mem: 33408 +Test: [ 500/2573] eta: 0:02:57 time: 0.0798 data: 0.0014 max mem: 33408 +Test: [ 600/2573] eta: 0:02:47 time: 0.0798 data: 0.0013 max mem: 33408 +Test: [ 700/2573] eta: 0:02:38 time: 0.0803 data: 0.0015 max mem: 33408 +Test: [ 800/2573] eta: 0:02:29 time: 0.0838 data: 0.0013 max mem: 33408 +Test: [ 900/2573] eta: 0:02:20 time: 0.0803 data: 0.0013 max mem: 33408 +Test: [1000/2573] eta: 0:02:11 time: 0.0811 data: 0.0014 max mem: 33408 +Test: [1100/2573] eta: 0:02:02 time: 0.0804 data: 0.0013 max mem: 33408 +Test: [1200/2573] eta: 0:01:54 time: 0.0803 data: 0.0014 max mem: 33408 +Test: [1300/2573] eta: 0:01:45 time: 0.0814 data: 0.0015 max mem: 33408 +Test: [1400/2573] eta: 0:01:37 time: 0.0799 data: 0.0014 max mem: 33408 +Test: [1500/2573] eta: 0:01:28 time: 0.0830 data: 0.0015 max mem: 33408 +Test: [1600/2573] eta: 0:01:20 time: 0.0846 data: 0.0013 max mem: 33408 +Test: [1700/2573] eta: 0:01:12 time: 0.0793 data: 0.0013 max mem: 33408 +Test: [1800/2573] eta: 0:01:03 time: 0.0823 data: 0.0015 max mem: 33408 +Test: [1900/2573] eta: 0:00:55 time: 0.0790 data: 0.0015 max mem: 33408 +Test: [2000/2573] eta: 0:00:47 time: 0.0807 data: 0.0015 max mem: 33408 +Test: [2100/2573] eta: 0:00:38 time: 0.0828 data: 0.0015 max mem: 33408 +Test: [2200/2573] eta: 0:00:30 time: 0.0819 data: 0.0015 max mem: 33408 +Test: [2300/2573] eta: 0:00:22 time: 0.0816 data: 0.0014 max mem: 33408 +Test: [2400/2573] eta: 0:00:14 time: 0.0778 data: 0.0015 max mem: 33408 +Test: [2500/2573] eta: 0:00:05 time: 0.0808 data: 0.0015 max mem: 33408 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: Total time: 0:03:32 +Final results: +Mean IoU is 56.56 + + precision@0.5 = 63.09 + precision@0.6 = 55.94 + precision@0.7 = 47.71 + precision@0.8 = 35.17 + precision@0.9 = 15.20 + overall IoU = 56.35 + +Average object IoU 56.5615976224848 +Overall IoU 56.35387420654297 +Better epoch: 5 + +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [6] [ 0/2639] eta: 4:01:25 lr: 4.319591533230858e-05 loss: 0.0721 (0.0721) time: 5.4891 data: 2.2346 max mem: 33408 +Epoch: [6] [ 10/2639] eta: 2:26:09 lr: 4.319158247742427e-05 loss: 0.1284 (0.1169) time: 3.3358 data: 0.2099 max mem: 33408 +Epoch: [6] [ 20/2639] eta: 2:19:47 lr: 4.3187249574243926e-05 loss: 0.1284 (0.1222) time: 3.0881 data: 0.0071 max mem: 33408 +Epoch: [6] [ 30/2639] eta: 2:16:18 lr: 4.3182916622761615e-05 loss: 0.1047 (0.1183) time: 3.0242 data: 0.0074 max mem: 33408 +Epoch: [6] [ 40/2639] eta: 2:14:30 lr: 4.317858362297142e-05 loss: 0.1014 (0.1148) time: 3.0031 data: 0.0077 max mem: 33408 +Epoch: [6] [ 50/2639] eta: 2:12:55 lr: 4.3174250574867425e-05 loss: 0.1014 (0.1134) time: 2.9966 data: 0.0077 max mem: 33408 +Epoch: [6] [ 60/2639] eta: 2:12:33 lr: 4.316991747844369e-05 loss: 0.0976 (0.1108) time: 3.0407 data: 0.0077 max mem: 33408 +Epoch: [6] [ 70/2639] eta: 2:11:22 lr: 4.316558433369429e-05 loss: 0.0953 (0.1110) time: 3.0373 data: 0.0075 max mem: 33408 +Epoch: [6] [ 80/2639] eta: 2:10:38 lr: 4.31612511406133e-05 loss: 0.0953 (0.1103) time: 2.9991 data: 0.0081 max mem: 33408 +Epoch: [6] [ 90/2639] eta: 2:10:04 lr: 4.315691789919478e-05 loss: 0.0941 (0.1093) time: 3.0387 data: 0.0084 max mem: 33408 +Epoch: [6] [ 100/2639] eta: 2:09:26 lr: 4.315258460943282e-05 loss: 0.0974 (0.1089) time: 3.0411 data: 0.0082 max mem: 33408 +Epoch: [6] [ 110/2639] eta: 2:08:54 lr: 4.314825127132145e-05 loss: 0.0908 (0.1083) time: 3.0419 data: 0.0081 max mem: 33408 +Epoch: [6] [ 120/2639] eta: 2:08:03 lr: 4.314391788485477e-05 loss: 0.1053 (0.1097) time: 3.0080 data: 0.0079 max mem: 33408 +Epoch: [6] [ 130/2639] eta: 2:07:16 lr: 4.3139584450026835e-05 loss: 0.1171 (0.1096) time: 2.9612 data: 0.0077 max mem: 33408 +Epoch: [6] [ 140/2639] eta: 2:06:48 lr: 4.3135250966831694e-05 loss: 0.0936 (0.1089) time: 3.0110 data: 0.0075 max mem: 33408 +Epoch: [6] [ 150/2639] eta: 2:06:01 lr: 4.3130917435263415e-05 loss: 0.0924 (0.1079) time: 3.0010 data: 0.0075 max mem: 33408 +Epoch: [6] [ 160/2639] eta: 2:05:31 lr: 4.3126583855316064e-05 loss: 0.0924 (0.1074) time: 2.9916 data: 0.0081 max mem: 33408 +Epoch: [6] [ 170/2639] eta: 2:04:57 lr: 4.3122250226983704e-05 loss: 0.0927 (0.1074) time: 3.0259 data: 0.0085 max mem: 33408 +Epoch: [6] [ 180/2639] eta: 2:04:37 lr: 4.3117916550260365e-05 loss: 0.0927 (0.1064) time: 3.0610 data: 0.0080 max mem: 33408 +Epoch: [6] [ 190/2639] eta: 2:03:56 lr: 4.311358282514013e-05 loss: 0.0917 (0.1061) time: 3.0355 data: 0.0076 max mem: 33408 +Epoch: [6] [ 200/2639] eta: 2:03:34 lr: 4.310924905161705e-05 loss: 0.0903 (0.1053) time: 3.0348 data: 0.0079 max mem: 33408 +Epoch: [6] [ 210/2639] eta: 2:03:00 lr: 4.310491522968516e-05 loss: 0.0835 (0.1062) time: 3.0608 data: 0.0080 max mem: 33408 +Epoch: [6] [ 220/2639] eta: 2:02:31 lr: 4.310058135933852e-05 loss: 0.1001 (0.1062) time: 3.0265 data: 0.0079 max mem: 33408 +Epoch: [6] [ 230/2639] eta: 2:02:00 lr: 4.309624744057119e-05 loss: 0.1157 (0.1066) time: 3.0386 data: 0.0081 max mem: 33408 +Epoch: [6] [ 240/2639] eta: 2:01:26 lr: 4.3091913473377206e-05 loss: 0.1066 (0.1069) time: 3.0211 data: 0.0080 max mem: 33408 +Epoch: [6] [ 250/2639] eta: 2:00:55 lr: 4.3087579457750625e-05 loss: 0.1072 (0.1078) time: 3.0208 data: 0.0080 max mem: 33408 +Epoch: [6] [ 260/2639] eta: 2:00:20 lr: 4.308324539368548e-05 loss: 0.1091 (0.1078) time: 3.0089 data: 0.0080 max mem: 33408 +Epoch: [6] [ 270/2639] eta: 1:59:46 lr: 4.3078911281175835e-05 loss: 0.0982 (0.1073) time: 2.9899 data: 0.0077 max mem: 33408 +Epoch: [6] [ 280/2639] eta: 1:59:11 lr: 4.3074577120215706e-05 loss: 0.0871 (0.1065) time: 2.9857 data: 0.0077 max mem: 33408 +Epoch: [6] [ 290/2639] eta: 1:58:40 lr: 4.3070242910799154e-05 loss: 0.0917 (0.1067) time: 2.9992 data: 0.0077 max mem: 33408 +Epoch: [6] [ 300/2639] eta: 1:58:09 lr: 4.3065908652920215e-05 loss: 0.0917 (0.1062) time: 3.0192 data: 0.0080 max mem: 33408 +Epoch: [6] [ 310/2639] eta: 1:57:40 lr: 4.306157434657293e-05 loss: 0.0844 (0.1060) time: 3.0359 data: 0.0081 max mem: 33408 +Epoch: [6] [ 320/2639] eta: 1:57:05 lr: 4.305723999175133e-05 loss: 0.0883 (0.1061) time: 3.0096 data: 0.0080 max mem: 33408 +Epoch: [6] [ 330/2639] eta: 1:56:33 lr: 4.305290558844946e-05 loss: 0.1047 (0.1067) time: 2.9864 data: 0.0080 max mem: 33408 +Epoch: [6] [ 340/2639] eta: 1:56:01 lr: 4.304857113666134e-05 loss: 0.1052 (0.1065) time: 3.0062 data: 0.0080 max mem: 33408 +Epoch: [6] [ 350/2639] eta: 1:55:32 lr: 4.304423663638101e-05 loss: 0.1052 (0.1069) time: 3.0236 data: 0.0080 max mem: 33408 +Epoch: [6] [ 360/2639] eta: 1:54:58 lr: 4.303990208760251e-05 loss: 0.0966 (0.1067) time: 3.0075 data: 0.0079 max mem: 33408 +Epoch: [6] [ 370/2639] eta: 1:54:29 lr: 4.303556749031986e-05 loss: 0.1146 (0.1069) time: 3.0100 data: 0.0080 max mem: 33408 +Epoch: [6] [ 380/2639] eta: 1:53:56 lr: 4.3031232844527095e-05 loss: 0.1130 (0.1073) time: 3.0177 data: 0.0076 max mem: 33408 +Epoch: [6] [ 390/2639] eta: 1:53:31 lr: 4.302689815021824e-05 loss: 0.1056 (0.1072) time: 3.0480 data: 0.0072 max mem: 33408 +Epoch: [6] [ 400/2639] eta: 1:53:00 lr: 4.302256340738732e-05 loss: 0.1087 (0.1075) time: 3.0605 data: 0.0074 max mem: 33408 +Epoch: [6] [ 410/2639] eta: 1:52:29 lr: 4.3018228616028364e-05 loss: 0.0970 (0.1075) time: 3.0159 data: 0.0075 max mem: 33408 +Epoch: [6] [ 420/2639] eta: 1:51:54 lr: 4.301389377613539e-05 loss: 0.0938 (0.1075) time: 2.9838 data: 0.0075 max mem: 33408 +Epoch: [6] [ 430/2639] eta: 1:51:26 lr: 4.3009558887702415e-05 loss: 0.0983 (0.1086) time: 3.0060 data: 0.0076 max mem: 33408 +Epoch: [6] [ 440/2639] eta: 1:50:59 lr: 4.300522395072348e-05 loss: 0.0983 (0.1083) time: 3.0737 data: 0.0077 max mem: 33408 +Epoch: [6] [ 450/2639] eta: 1:50:27 lr: 4.300088896519258e-05 loss: 0.1004 (0.1082) time: 3.0367 data: 0.0077 max mem: 33408 +Epoch: [6] [ 460/2639] eta: 1:49:53 lr: 4.2996553931103745e-05 loss: 0.1039 (0.1081) time: 2.9779 data: 0.0077 max mem: 33408 +Epoch: [6] [ 470/2639] eta: 1:49:25 lr: 4.299221884845099e-05 loss: 0.1157 (0.1088) time: 3.0213 data: 0.0079 max mem: 33408 +Epoch: [6] [ 480/2639] eta: 1:48:54 lr: 4.298788371722833e-05 loss: 0.1168 (0.1092) time: 3.0350 data: 0.0079 max mem: 33408 +Epoch: [6] [ 490/2639] eta: 1:48:22 lr: 4.298354853742977e-05 loss: 0.1035 (0.1094) time: 2.9976 data: 0.0083 max mem: 33408 +Epoch: [6] [ 500/2639] eta: 1:47:52 lr: 4.297921330904934e-05 loss: 0.1098 (0.1096) time: 3.0130 data: 0.0085 max mem: 33408 +Epoch: [6] [ 510/2639] eta: 1:47:22 lr: 4.297487803208104e-05 loss: 0.1063 (0.1095) time: 3.0235 data: 0.0084 max mem: 33408 +Epoch: [6] [ 520/2639] eta: 1:46:50 lr: 4.297054270651888e-05 loss: 0.0932 (0.1090) time: 3.0104 data: 0.0082 max mem: 33408 +Epoch: [6] [ 530/2639] eta: 1:46:20 lr: 4.296620733235686e-05 loss: 0.0913 (0.1093) time: 3.0132 data: 0.0080 max mem: 33408 +Epoch: [6] [ 540/2639] eta: 1:45:49 lr: 4.2961871909588994e-05 loss: 0.0949 (0.1092) time: 3.0201 data: 0.0077 max mem: 33408 +Epoch: [6] [ 550/2639] eta: 1:45:18 lr: 4.295753643820929e-05 loss: 0.0949 (0.1091) time: 3.0067 data: 0.0074 max mem: 33408 +Epoch: [6] [ 560/2639] eta: 1:44:48 lr: 4.295320091821175e-05 loss: 0.1034 (0.1094) time: 3.0178 data: 0.0075 max mem: 33408 +Epoch: [6] [ 570/2639] eta: 1:44:17 lr: 4.294886534959037e-05 loss: 0.1002 (0.1096) time: 3.0097 data: 0.0075 max mem: 33408 +Epoch: [6] [ 580/2639] eta: 1:43:48 lr: 4.294452973233916e-05 loss: 0.1049 (0.1098) time: 3.0340 data: 0.0078 max mem: 33408 +Epoch: [6] [ 590/2639] eta: 1:43:17 lr: 4.29401940664521e-05 loss: 0.1049 (0.1097) time: 3.0335 data: 0.0080 max mem: 33408 +Epoch: [6] [ 600/2639] eta: 1:42:48 lr: 4.2935858351923225e-05 loss: 0.0866 (0.1097) time: 3.0289 data: 0.0077 max mem: 33408 +Epoch: [6] [ 610/2639] eta: 1:42:19 lr: 4.2931522588746493e-05 loss: 0.0842 (0.1092) time: 3.0592 data: 0.0077 max mem: 33408 +Epoch: [6] [ 620/2639] eta: 1:41:49 lr: 4.292718677691591e-05 loss: 0.0878 (0.1091) time: 3.0464 data: 0.0079 max mem: 33408 +Epoch: [6] [ 630/2639] eta: 1:41:19 lr: 4.292285091642549e-05 loss: 0.1057 (0.1093) time: 3.0471 data: 0.0075 max mem: 33408 +Epoch: [6] [ 640/2639] eta: 1:40:48 lr: 4.29185150072692e-05 loss: 0.1045 (0.1092) time: 3.0162 data: 0.0076 max mem: 33408 +Epoch: [6] [ 650/2639] eta: 1:40:17 lr: 4.291417904944104e-05 loss: 0.1048 (0.1093) time: 3.0010 data: 0.0076 max mem: 33408 +Epoch: [6] [ 660/2639] eta: 1:39:46 lr: 4.290984304293501e-05 loss: 0.1271 (0.1095) time: 3.0094 data: 0.0074 max mem: 33408 +Epoch: [6] [ 670/2639] eta: 1:39:16 lr: 4.290550698774508e-05 loss: 0.0987 (0.1093) time: 3.0064 data: 0.0077 max mem: 33408 +Epoch: [6] [ 680/2639] eta: 1:38:45 lr: 4.290117088386524e-05 loss: 0.1083 (0.1097) time: 3.0035 data: 0.0076 max mem: 33408 +Epoch: [6] [ 690/2639] eta: 1:38:16 lr: 4.2896834731289485e-05 loss: 0.1228 (0.1100) time: 3.0322 data: 0.0072 max mem: 33408 +Epoch: [6] [ 700/2639] eta: 1:37:46 lr: 4.2892498530011796e-05 loss: 0.1046 (0.1099) time: 3.0578 data: 0.0073 max mem: 33408 +Epoch: [6] [ 710/2639] eta: 1:37:17 lr: 4.288816228002615e-05 loss: 0.0988 (0.1098) time: 3.0672 data: 0.0073 max mem: 33408 +Epoch: [6] [ 720/2639] eta: 1:36:47 lr: 4.2883825981326524e-05 loss: 0.0988 (0.1100) time: 3.0582 data: 0.0076 max mem: 33408 +Epoch: [6] [ 730/2639] eta: 1:36:17 lr: 4.287948963390691e-05 loss: 0.1005 (0.1099) time: 3.0207 data: 0.0080 max mem: 33408 +Epoch: [6] [ 740/2639] eta: 1:35:46 lr: 4.287515323776128e-05 loss: 0.0947 (0.1099) time: 3.0231 data: 0.0087 max mem: 33408 +Epoch: [6] [ 750/2639] eta: 1:35:17 lr: 4.287081679288361e-05 loss: 0.0872 (0.1098) time: 3.0464 data: 0.0084 max mem: 33408 +Epoch: [6] [ 760/2639] eta: 1:34:46 lr: 4.286648029926787e-05 loss: 0.1182 (0.1103) time: 3.0178 data: 0.0076 max mem: 33408 +Epoch: [6] [ 770/2639] eta: 1:34:16 lr: 4.2862143756908054e-05 loss: 0.1223 (0.1103) time: 3.0235 data: 0.0076 max mem: 33408 +Epoch: [6] [ 780/2639] eta: 1:33:47 lr: 4.285780716579811e-05 loss: 0.1091 (0.1104) time: 3.0725 data: 0.0075 max mem: 33408 +Epoch: [6] [ 790/2639] eta: 1:33:17 lr: 4.285347052593202e-05 loss: 0.1051 (0.1104) time: 3.0610 data: 0.0084 max mem: 33408 +Epoch: [6] [ 800/2639] eta: 1:32:47 lr: 4.284913383730375e-05 loss: 0.1072 (0.1104) time: 3.0323 data: 0.0083 max mem: 33408 +Epoch: [6] [ 810/2639] eta: 1:32:18 lr: 4.284479709990728e-05 loss: 0.1072 (0.1104) time: 3.0470 data: 0.0073 max mem: 33408 +Epoch: [6] [ 820/2639] eta: 1:31:48 lr: 4.284046031373656e-05 loss: 0.0894 (0.1103) time: 3.0575 data: 0.0073 max mem: 33408 +Epoch: [6] [ 830/2639] eta: 1:31:18 lr: 4.2836123478785554e-05 loss: 0.0874 (0.1102) time: 3.0528 data: 0.0073 max mem: 33408 +Epoch: [6] [ 840/2639] eta: 1:30:49 lr: 4.283178659504825e-05 loss: 0.1060 (0.1103) time: 3.0696 data: 0.0075 max mem: 33408 +Epoch: [6] [ 850/2639] eta: 1:30:19 lr: 4.2827449662518593e-05 loss: 0.1020 (0.1101) time: 3.0507 data: 0.0074 max mem: 33408 +Epoch: [6] [ 860/2639] eta: 1:29:48 lr: 4.2823112681190536e-05 loss: 0.0931 (0.1104) time: 3.0251 data: 0.0074 max mem: 33408 +Epoch: [6] [ 870/2639] eta: 1:29:17 lr: 4.2818775651058054e-05 loss: 0.1160 (0.1104) time: 3.0070 data: 0.0075 max mem: 33408 +Epoch: [6] [ 880/2639] eta: 1:28:46 lr: 4.28144385721151e-05 loss: 0.1160 (0.1105) time: 2.9964 data: 0.0077 max mem: 33408 +Epoch: [6] [ 890/2639] eta: 1:28:16 lr: 4.281010144435563e-05 loss: 0.1198 (0.1108) time: 3.0271 data: 0.0078 max mem: 33408 +Epoch: [6] [ 900/2639] eta: 1:27:48 lr: 4.2805764267773594e-05 loss: 0.1309 (0.1110) time: 3.0783 data: 0.0076 max mem: 33408 +Epoch: [6] [ 910/2639] eta: 1:27:17 lr: 4.280142704236296e-05 loss: 0.1008 (0.1108) time: 3.0575 data: 0.0077 max mem: 33408 +Epoch: [6] [ 920/2639] eta: 1:26:47 lr: 4.2797089768117666e-05 loss: 0.0998 (0.1109) time: 3.0341 data: 0.0076 max mem: 33408 +Epoch: [6] [ 930/2639] eta: 1:26:16 lr: 4.279275244503166e-05 loss: 0.0889 (0.1107) time: 3.0229 data: 0.0073 max mem: 33408 +Epoch: [6] [ 940/2639] eta: 1:25:47 lr: 4.278841507309892e-05 loss: 0.0889 (0.1106) time: 3.0285 data: 0.0074 max mem: 33408 +Epoch: [6] [ 950/2639] eta: 1:25:15 lr: 4.278407765231336e-05 loss: 0.1018 (0.1106) time: 3.0236 data: 0.0075 max mem: 33408 +Epoch: [6] [ 960/2639] eta: 1:24:47 lr: 4.2779740182668946e-05 loss: 0.1110 (0.1106) time: 3.0492 data: 0.0077 max mem: 33408 +Epoch: [6] [ 970/2639] eta: 1:24:16 lr: 4.2775402664159614e-05 loss: 0.0978 (0.1105) time: 3.0731 data: 0.0079 max mem: 33408 +Epoch: [6] [ 980/2639] eta: 1:23:47 lr: 4.277106509677932e-05 loss: 0.0826 (0.1102) time: 3.0452 data: 0.0078 max mem: 33408 +Epoch: [6] [ 990/2639] eta: 1:23:16 lr: 4.276672748052199e-05 loss: 0.0826 (0.1102) time: 3.0313 data: 0.0076 max mem: 33408 +Epoch: [6] [1000/2639] eta: 1:22:45 lr: 4.276238981538157e-05 loss: 0.0912 (0.1100) time: 3.0110 data: 0.0072 max mem: 33408 +Epoch: [6] [1010/2639] eta: 1:22:15 lr: 4.2758052101352014e-05 loss: 0.0945 (0.1099) time: 3.0268 data: 0.0071 max mem: 33408 +Epoch: [6] [1020/2639] eta: 1:21:45 lr: 4.275371433842724e-05 loss: 0.1040 (0.1099) time: 3.0287 data: 0.0074 max mem: 33408 +Epoch: [6] [1030/2639] eta: 1:21:13 lr: 4.27493765266012e-05 loss: 0.0857 (0.1097) time: 2.9907 data: 0.0077 max mem: 33408 +Epoch: [6] [1040/2639] eta: 1:20:44 lr: 4.2745038665867815e-05 loss: 0.0855 (0.1097) time: 3.0202 data: 0.0075 max mem: 33408 +Epoch: [6] [1050/2639] eta: 1:20:12 lr: 4.274070075622103e-05 loss: 0.1138 (0.1098) time: 3.0217 data: 0.0074 max mem: 33408 +Epoch: [6] [1060/2639] eta: 1:19:42 lr: 4.273636279765478e-05 loss: 0.0955 (0.1096) time: 2.9914 data: 0.0074 max mem: 33408 +Epoch: [6] [1070/2639] eta: 1:19:11 lr: 4.2732024790162975e-05 loss: 0.0934 (0.1096) time: 3.0003 data: 0.0071 max mem: 33408 +Epoch: [6] [1080/2639] eta: 1:18:41 lr: 4.272768673373957e-05 loss: 0.0944 (0.1095) time: 2.9997 data: 0.0074 max mem: 33408 +Epoch: [6] [1090/2639] eta: 1:18:09 lr: 4.272334862837848e-05 loss: 0.1043 (0.1096) time: 2.9701 data: 0.0080 max mem: 33408 +Epoch: [6] [1100/2639] eta: 1:17:37 lr: 4.271901047407364e-05 loss: 0.1061 (0.1096) time: 2.9218 data: 0.0078 max mem: 33408 +Epoch: [6] [1110/2639] eta: 1:17:06 lr: 4.271467227081896e-05 loss: 0.1027 (0.1095) time: 2.9498 data: 0.0077 max mem: 33408 +Epoch: [6] [1120/2639] eta: 1:16:35 lr: 4.2710334018608375e-05 loss: 0.1020 (0.1095) time: 2.9742 data: 0.0080 max mem: 33408 +Epoch: [6] [1130/2639] eta: 1:16:05 lr: 4.27059957174358e-05 loss: 0.0979 (0.1094) time: 2.9870 data: 0.0080 max mem: 33408 +Epoch: [6] [1140/2639] eta: 1:15:34 lr: 4.2701657367295164e-05 loss: 0.0931 (0.1093) time: 2.9939 data: 0.0078 max mem: 33408 +Epoch: [6] [1150/2639] eta: 1:15:04 lr: 4.269731896818039e-05 loss: 0.0961 (0.1094) time: 3.0207 data: 0.0078 max mem: 33408 +Epoch: [6] [1160/2639] eta: 1:14:34 lr: 4.2692980520085377e-05 loss: 0.0925 (0.1092) time: 3.0413 data: 0.0079 max mem: 33408 +Epoch: [6] [1170/2639] eta: 1:14:04 lr: 4.2688642023004064e-05 loss: 0.0925 (0.1093) time: 3.0450 data: 0.0078 max mem: 33408 +Epoch: [6] [1180/2639] eta: 1:13:34 lr: 4.2684303476930346e-05 loss: 0.1082 (0.1093) time: 3.0559 data: 0.0078 max mem: 33408 +Epoch: [6] [1190/2639] eta: 1:13:03 lr: 4.267996488185816e-05 loss: 0.1105 (0.1092) time: 3.0244 data: 0.0082 max mem: 33408 +Epoch: [6] [1200/2639] eta: 1:12:34 lr: 4.267562623778139e-05 loss: 0.1044 (0.1092) time: 3.0268 data: 0.0082 max mem: 33408 +Epoch: [6] [1210/2639] eta: 1:12:03 lr: 4.267128754469397e-05 loss: 0.0929 (0.1091) time: 3.0458 data: 0.0083 max mem: 33408 +Epoch: [6] [1220/2639] eta: 1:11:33 lr: 4.2666948802589794e-05 loss: 0.0921 (0.1091) time: 3.0204 data: 0.0082 max mem: 33408 +Epoch: [6] [1230/2639] eta: 1:11:02 lr: 4.266261001146278e-05 loss: 0.1032 (0.1091) time: 2.9774 data: 0.0076 max mem: 33408 +Epoch: [6] [1240/2639] eta: 1:10:32 lr: 4.265827117130683e-05 loss: 0.1035 (0.1091) time: 3.0030 data: 0.0077 max mem: 33408 +Epoch: [6] [1250/2639] eta: 1:10:01 lr: 4.2653932282115845e-05 loss: 0.1071 (0.1091) time: 3.0288 data: 0.0081 max mem: 33408 +Epoch: [6] [1260/2639] eta: 1:09:31 lr: 4.2649593343883735e-05 loss: 0.1130 (0.1092) time: 2.9955 data: 0.0081 max mem: 33408 +Epoch: [6] [1270/2639] eta: 1:09:00 lr: 4.2645254356604405e-05 loss: 0.0997 (0.1091) time: 2.9978 data: 0.0079 max mem: 33408 +Epoch: [6] [1280/2639] eta: 1:08:31 lr: 4.2640915320271744e-05 loss: 0.0923 (0.1092) time: 3.0558 data: 0.0080 max mem: 33408 +Epoch: [6] [1290/2639] eta: 1:08:01 lr: 4.263657623487966e-05 loss: 0.0964 (0.1091) time: 3.0871 data: 0.0083 max mem: 33408 +Epoch: [6] [1300/2639] eta: 1:07:30 lr: 4.2632237100422054e-05 loss: 0.0953 (0.1091) time: 3.0270 data: 0.0081 max mem: 33408 +Epoch: [6] [1310/2639] eta: 1:07:01 lr: 4.2627897916892814e-05 loss: 0.0953 (0.1091) time: 3.0320 data: 0.0077 max mem: 33408 +Epoch: [6] [1320/2639] eta: 1:06:30 lr: 4.262355868428583e-05 loss: 0.1077 (0.1093) time: 3.0514 data: 0.0080 max mem: 33408 +Epoch: [6] [1330/2639] eta: 1:06:00 lr: 4.261921940259501e-05 loss: 0.1083 (0.1093) time: 3.0046 data: 0.0080 max mem: 33408 +Epoch: [6] [1340/2639] eta: 1:05:30 lr: 4.2614880071814234e-05 loss: 0.0953 (0.1093) time: 3.0460 data: 0.0080 max mem: 33408 +Epoch: [6] [1350/2639] eta: 1:05:00 lr: 4.2610540691937404e-05 loss: 0.0891 (0.1092) time: 3.0667 data: 0.0083 max mem: 33408 +Epoch: [6] [1360/2639] eta: 1:04:29 lr: 4.26062012629584e-05 loss: 0.0973 (0.1093) time: 2.9737 data: 0.0082 max mem: 33408 +Epoch: [6] [1370/2639] eta: 1:03:59 lr: 4.26018617848711e-05 loss: 0.1067 (0.1093) time: 2.9845 data: 0.0078 max mem: 33408 +Epoch: [6] [1380/2639] eta: 1:03:28 lr: 4.2597522257669415e-05 loss: 0.1027 (0.1092) time: 2.9969 data: 0.0078 max mem: 33408 +Epoch: [6] [1390/2639] eta: 1:02:58 lr: 4.259318268134721e-05 loss: 0.1027 (0.1093) time: 3.0073 data: 0.0080 max mem: 33408 +Epoch: [6] [1400/2639] eta: 1:02:28 lr: 4.258884305589838e-05 loss: 0.1027 (0.1091) time: 3.0395 data: 0.0081 max mem: 33408 +Epoch: [6] [1410/2639] eta: 1:01:57 lr: 4.25845033813168e-05 loss: 0.0947 (0.1090) time: 3.0200 data: 0.0081 max mem: 33408 +Epoch: [6] [1420/2639] eta: 1:01:27 lr: 4.258016365759635e-05 loss: 0.0991 (0.1090) time: 3.0337 data: 0.0079 max mem: 33408 +Epoch: [6] [1430/2639] eta: 1:00:57 lr: 4.257582388473091e-05 loss: 0.1045 (0.1090) time: 3.0492 data: 0.0079 max mem: 33408 +Epoch: [6] [1440/2639] eta: 1:00:27 lr: 4.257148406271436e-05 loss: 0.1044 (0.1091) time: 3.0450 data: 0.0077 max mem: 33408 +Epoch: [6] [1450/2639] eta: 0:59:57 lr: 4.256714419154057e-05 loss: 0.0942 (0.1090) time: 3.0505 data: 0.0076 max mem: 33408 +Epoch: [6] [1460/2639] eta: 0:59:27 lr: 4.256280427120342e-05 loss: 0.0982 (0.1091) time: 3.0376 data: 0.0080 max mem: 33408 +Epoch: [6] [1470/2639] eta: 0:58:57 lr: 4.255846430169678e-05 loss: 0.1015 (0.1092) time: 3.0434 data: 0.0083 max mem: 33408 +Epoch: [6] [1480/2639] eta: 0:58:26 lr: 4.255412428301453e-05 loss: 0.1001 (0.1093) time: 3.0360 data: 0.0078 max mem: 33408 +Epoch: [6] [1490/2639] eta: 0:57:57 lr: 4.254978421515052e-05 loss: 0.0882 (0.1092) time: 3.0370 data: 0.0082 max mem: 33408 +Epoch: [6] [1500/2639] eta: 0:57:26 lr: 4.254544409809864e-05 loss: 0.0880 (0.1091) time: 3.0600 data: 0.0082 max mem: 33408 +Epoch: [6] [1510/2639] eta: 0:56:56 lr: 4.2541103931852746e-05 loss: 0.0895 (0.1090) time: 3.0493 data: 0.0079 max mem: 33408 +Epoch: [6] [1520/2639] eta: 0:56:26 lr: 4.253676371640671e-05 loss: 0.0895 (0.1091) time: 3.0218 data: 0.0083 max mem: 33408 +Epoch: [6] [1530/2639] eta: 0:55:56 lr: 4.2532423451754386e-05 loss: 0.1055 (0.1092) time: 3.0325 data: 0.0080 max mem: 33408 +Epoch: [6] [1540/2639] eta: 0:55:26 lr: 4.252808313788965e-05 loss: 0.1129 (0.1093) time: 3.0557 data: 0.0079 max mem: 33408 +Epoch: [6] [1550/2639] eta: 0:54:56 lr: 4.2523742774806355e-05 loss: 0.1129 (0.1094) time: 3.0364 data: 0.0081 max mem: 33408 +Epoch: [6] [1560/2639] eta: 0:54:25 lr: 4.251940236249836e-05 loss: 0.1096 (0.1095) time: 3.0296 data: 0.0082 max mem: 33408 +Epoch: [6] [1570/2639] eta: 0:53:55 lr: 4.251506190095953e-05 loss: 0.0947 (0.1094) time: 3.0049 data: 0.0082 max mem: 33408 +Epoch: [6] [1580/2639] eta: 0:53:24 lr: 4.251072139018371e-05 loss: 0.0911 (0.1095) time: 3.0015 data: 0.0078 max mem: 33408 +Epoch: [6] [1590/2639] eta: 0:52:54 lr: 4.250638083016477e-05 loss: 0.1163 (0.1096) time: 3.0427 data: 0.0077 max mem: 33408 +Epoch: [6] [1600/2639] eta: 0:52:24 lr: 4.250204022089656e-05 loss: 0.1192 (0.1097) time: 3.0614 data: 0.0078 max mem: 33408 +Epoch: [6] [1610/2639] eta: 0:51:54 lr: 4.2497699562372924e-05 loss: 0.1020 (0.1098) time: 3.0248 data: 0.0080 max mem: 33408 +Epoch: [6] [1620/2639] eta: 0:51:24 lr: 4.2493358854587716e-05 loss: 0.0970 (0.1097) time: 3.0192 data: 0.0080 max mem: 33408 +Epoch: [6] [1630/2639] eta: 0:50:53 lr: 4.2489018097534795e-05 loss: 0.0947 (0.1096) time: 3.0025 data: 0.0077 max mem: 33408 +Epoch: [6] [1640/2639] eta: 0:50:23 lr: 4.2484677291207996e-05 loss: 0.0947 (0.1097) time: 3.0099 data: 0.0082 max mem: 33408 +Epoch: [6] [1650/2639] eta: 0:49:53 lr: 4.248033643560118e-05 loss: 0.0826 (0.1097) time: 3.0600 data: 0.0081 max mem: 33408 +Epoch: [6] [1660/2639] eta: 0:49:23 lr: 4.247599553070818e-05 loss: 0.0971 (0.1097) time: 3.0537 data: 0.0076 max mem: 33408 +Epoch: [6] [1670/2639] eta: 0:48:53 lr: 4.247165457652285e-05 loss: 0.1117 (0.1098) time: 3.0390 data: 0.0078 max mem: 33408 +Epoch: [6] [1680/2639] eta: 0:48:22 lr: 4.2467313573039013e-05 loss: 0.1023 (0.1098) time: 3.0369 data: 0.0079 max mem: 33408 +Epoch: [6] [1690/2639] eta: 0:47:52 lr: 4.2462972520250536e-05 loss: 0.1001 (0.1100) time: 3.0319 data: 0.0080 max mem: 33408 +Epoch: [6] [1700/2639] eta: 0:47:22 lr: 4.2458631418151243e-05 loss: 0.0925 (0.1099) time: 3.0501 data: 0.0083 max mem: 33408 +Epoch: [6] [1710/2639] eta: 0:46:52 lr: 4.2454290266734975e-05 loss: 0.0925 (0.1100) time: 3.0321 data: 0.0090 max mem: 33408 +Epoch: [6] [1720/2639] eta: 0:46:21 lr: 4.2449949065995565e-05 loss: 0.0908 (0.1100) time: 3.0317 data: 0.0082 max mem: 33408 +Epoch: [6] [1730/2639] eta: 0:45:51 lr: 4.244560781592685e-05 loss: 0.1053 (0.1101) time: 3.0651 data: 0.0074 max mem: 33408 +Epoch: [6] [1740/2639] eta: 0:45:21 lr: 4.2441266516522667e-05 loss: 0.0986 (0.1101) time: 3.0482 data: 0.0077 max mem: 33408 +Epoch: [6] [1750/2639] eta: 0:44:51 lr: 4.243692516777684e-05 loss: 0.0981 (0.1102) time: 3.0363 data: 0.0075 max mem: 33408 +Epoch: [6] [1760/2639] eta: 0:44:21 lr: 4.243258376968321e-05 loss: 0.1227 (0.1104) time: 3.0479 data: 0.0077 max mem: 33408 +Epoch: [6] [1770/2639] eta: 0:43:50 lr: 4.242824232223561e-05 loss: 0.1049 (0.1103) time: 3.0238 data: 0.0078 max mem: 33408 +Epoch: [6] [1780/2639] eta: 0:43:20 lr: 4.242390082542784e-05 loss: 0.1026 (0.1104) time: 2.9874 data: 0.0078 max mem: 33408 +Epoch: [6] [1790/2639] eta: 0:42:49 lr: 4.241955927925375e-05 loss: 0.1130 (0.1104) time: 2.9935 data: 0.0080 max mem: 33408 +Epoch: [6] [1800/2639] eta: 0:42:19 lr: 4.2415217683707167e-05 loss: 0.0950 (0.1104) time: 3.0055 data: 0.0079 max mem: 33408 +Epoch: [6] [1810/2639] eta: 0:41:49 lr: 4.2410876038781897e-05 loss: 0.1008 (0.1104) time: 3.0434 data: 0.0079 max mem: 33408 +Epoch: [6] [1820/2639] eta: 0:41:19 lr: 4.240653434447177e-05 loss: 0.0994 (0.1104) time: 3.0227 data: 0.0078 max mem: 33408 +Epoch: [6] [1830/2639] eta: 0:40:48 lr: 4.240219260077062e-05 loss: 0.1074 (0.1107) time: 3.0076 data: 0.0077 max mem: 33408 +Epoch: [6] [1840/2639] eta: 0:40:19 lr: 4.239785080767225e-05 loss: 0.1251 (0.1107) time: 3.0898 data: 0.0077 max mem: 33408 +Epoch: [6] [1850/2639] eta: 0:39:48 lr: 4.239350896517047e-05 loss: 0.0864 (0.1106) time: 3.0801 data: 0.0075 max mem: 33408 +Epoch: [6] [1860/2639] eta: 0:39:18 lr: 4.2389167073259114e-05 loss: 0.0979 (0.1107) time: 3.0157 data: 0.0075 max mem: 33408 +Epoch: [6] [1870/2639] eta: 0:38:48 lr: 4.238482513193198e-05 loss: 0.1051 (0.1106) time: 3.0101 data: 0.0075 max mem: 33408 +Epoch: [6] [1880/2639] eta: 0:38:17 lr: 4.2380483141182895e-05 loss: 0.0947 (0.1106) time: 3.0169 data: 0.0074 max mem: 33408 +Epoch: [6] [1890/2639] eta: 0:37:47 lr: 4.237614110100566e-05 loss: 0.1269 (0.1107) time: 3.0165 data: 0.0074 max mem: 33408 +Epoch: [6] [1900/2639] eta: 0:37:17 lr: 4.2371799011394094e-05 loss: 0.1079 (0.1107) time: 3.0408 data: 0.0078 max mem: 33408 +Epoch: [6] [1910/2639] eta: 0:36:47 lr: 4.236745687234199e-05 loss: 0.1079 (0.1108) time: 3.0579 data: 0.0083 max mem: 33408 +Epoch: [6] [1920/2639] eta: 0:36:16 lr: 4.236311468384318e-05 loss: 0.1082 (0.1108) time: 3.0572 data: 0.0082 max mem: 33408 +Epoch: [6] [1930/2639] eta: 0:35:46 lr: 4.235877244589144e-05 loss: 0.0993 (0.1108) time: 3.0383 data: 0.0081 max mem: 33408 +Epoch: [6] [1940/2639] eta: 0:35:16 lr: 4.23544301584806e-05 loss: 0.0993 (0.1108) time: 3.0091 data: 0.0085 max mem: 33408 +Epoch: [6] [1950/2639] eta: 0:34:46 lr: 4.2350087821604446e-05 loss: 0.0985 (0.1107) time: 3.0130 data: 0.0083 max mem: 33408 +Epoch: [6] [1960/2639] eta: 0:34:15 lr: 4.234574543525679e-05 loss: 0.1063 (0.1107) time: 3.0433 data: 0.0080 max mem: 33408 +Epoch: [6] [1970/2639] eta: 0:33:45 lr: 4.234140299943142e-05 loss: 0.1036 (0.1107) time: 3.0451 data: 0.0079 max mem: 33408 +Epoch: [6] [1980/2639] eta: 0:33:15 lr: 4.233706051412214e-05 loss: 0.0989 (0.1107) time: 3.0332 data: 0.0079 max mem: 33408 +Epoch: [6] [1990/2639] eta: 0:32:45 lr: 4.2332717979322745e-05 loss: 0.0964 (0.1107) time: 3.0286 data: 0.0082 max mem: 33408 +Epoch: [6] [2000/2639] eta: 0:32:14 lr: 4.2328375395027026e-05 loss: 0.0996 (0.1107) time: 2.9980 data: 0.0083 max mem: 33408 +Epoch: [6] [2010/2639] eta: 0:31:44 lr: 4.2324032761228785e-05 loss: 0.1064 (0.1108) time: 3.0478 data: 0.0080 max mem: 33408 +Epoch: [6] [2020/2639] eta: 0:31:14 lr: 4.231969007792182e-05 loss: 0.1066 (0.1108) time: 3.0803 data: 0.0080 max mem: 33408 +Epoch: [6] [2030/2639] eta: 0:30:44 lr: 4.2315347345099905e-05 loss: 0.1052 (0.1108) time: 3.0408 data: 0.0083 max mem: 33408 +Epoch: [6] [2040/2639] eta: 0:30:13 lr: 4.231100456275683e-05 loss: 0.0911 (0.1108) time: 3.0358 data: 0.0077 max mem: 33408 +Epoch: [6] [2050/2639] eta: 0:29:43 lr: 4.23066617308864e-05 loss: 0.0911 (0.1108) time: 2.9998 data: 0.0076 max mem: 33408 +Epoch: [6] [2060/2639] eta: 0:29:13 lr: 4.230231884948238e-05 loss: 0.1066 (0.1108) time: 3.0231 data: 0.0078 max mem: 33408 +Epoch: [6] [2070/2639] eta: 0:28:42 lr: 4.2297975918538566e-05 loss: 0.1144 (0.1108) time: 3.0417 data: 0.0077 max mem: 33408 +Epoch: [6] [2080/2639] eta: 0:28:12 lr: 4.2293632938048743e-05 loss: 0.1064 (0.1108) time: 3.0541 data: 0.0076 max mem: 33408 +Epoch: [6] [2090/2639] eta: 0:27:42 lr: 4.2289289908006694e-05 loss: 0.0932 (0.1107) time: 3.0737 data: 0.0072 max mem: 33408 +Epoch: [6] [2100/2639] eta: 0:27:12 lr: 4.228494682840618e-05 loss: 0.1110 (0.1108) time: 3.0471 data: 0.0073 max mem: 33408 +Epoch: [6] [2110/2639] eta: 0:26:42 lr: 4.2280603699241003e-05 loss: 0.1116 (0.1108) time: 3.0581 data: 0.0080 max mem: 33408 +Epoch: [6] [2120/2639] eta: 0:26:11 lr: 4.227626052050493e-05 loss: 0.0848 (0.1107) time: 3.0404 data: 0.0079 max mem: 33408 +Epoch: [6] [2130/2639] eta: 0:25:41 lr: 4.2271917292191744e-05 loss: 0.0848 (0.1108) time: 3.0591 data: 0.0078 max mem: 33408 +Epoch: [6] [2140/2639] eta: 0:25:11 lr: 4.22675740142952e-05 loss: 0.1044 (0.1108) time: 3.0434 data: 0.0078 max mem: 33408 +Epoch: [6] [2150/2639] eta: 0:24:41 lr: 4.22632306868091e-05 loss: 0.0966 (0.1107) time: 3.0130 data: 0.0074 max mem: 33408 +Epoch: [6] [2160/2639] eta: 0:24:10 lr: 4.225888730972718e-05 loss: 0.0966 (0.1107) time: 3.0126 data: 0.0075 max mem: 33408 +Epoch: [6] [2170/2639] eta: 0:23:40 lr: 4.225454388304324e-05 loss: 0.0956 (0.1107) time: 3.0213 data: 0.0075 max mem: 33408 +Epoch: [6] [2180/2639] eta: 0:23:10 lr: 4.225020040675103e-05 loss: 0.1025 (0.1108) time: 3.0311 data: 0.0075 max mem: 33408 +Epoch: [6] [2190/2639] eta: 0:22:39 lr: 4.224585688084433e-05 loss: 0.1047 (0.1108) time: 3.0458 data: 0.0077 max mem: 33408 +Epoch: [6] [2200/2639] eta: 0:22:09 lr: 4.2241513305316896e-05 loss: 0.1089 (0.1109) time: 3.0314 data: 0.0076 max mem: 33408 +Epoch: [6] [2210/2639] eta: 0:21:39 lr: 4.2237169680162494e-05 loss: 0.1054 (0.1109) time: 3.0540 data: 0.0076 max mem: 33408 +Epoch: [6] [2220/2639] eta: 0:21:09 lr: 4.223282600537489e-05 loss: 0.0969 (0.1110) time: 3.0487 data: 0.0078 max mem: 33408 +Epoch: [6] [2230/2639] eta: 0:20:38 lr: 4.222848228094784e-05 loss: 0.1152 (0.1110) time: 3.0348 data: 0.0077 max mem: 33408 +Epoch: [6] [2240/2639] eta: 0:20:08 lr: 4.22241385068751e-05 loss: 0.0943 (0.1109) time: 3.0752 data: 0.0076 max mem: 33408 +Epoch: [6] [2250/2639] eta: 0:19:38 lr: 4.221979468315043e-05 loss: 0.0900 (0.1110) time: 3.0260 data: 0.0076 max mem: 33408 +Epoch: [6] [2260/2639] eta: 0:19:08 lr: 4.2215450809767596e-05 loss: 0.0967 (0.1110) time: 3.0315 data: 0.0079 max mem: 33408 +Epoch: [6] [2270/2639] eta: 0:18:37 lr: 4.221110688672034e-05 loss: 0.0998 (0.1110) time: 3.0279 data: 0.0077 max mem: 33408 +Epoch: [6] [2280/2639] eta: 0:18:07 lr: 4.220676291400242e-05 loss: 0.0987 (0.1109) time: 3.0769 data: 0.0075 max mem: 33408 +Epoch: [6] [2290/2639] eta: 0:17:37 lr: 4.220241889160759e-05 loss: 0.0973 (0.1109) time: 3.1186 data: 0.0073 max mem: 33408 +Epoch: [6] [2300/2639] eta: 0:17:07 lr: 4.2198074819529605e-05 loss: 0.0988 (0.1109) time: 3.0283 data: 0.0074 max mem: 33408 +Epoch: [6] [2310/2639] eta: 0:16:36 lr: 4.21937306977622e-05 loss: 0.0950 (0.1109) time: 3.0132 data: 0.0076 max mem: 33408 +Epoch: [6] [2320/2639] eta: 0:16:06 lr: 4.218938652629913e-05 loss: 0.1025 (0.1109) time: 3.0492 data: 0.0078 max mem: 33408 +Epoch: [6] [2330/2639] eta: 0:15:36 lr: 4.218504230513414e-05 loss: 0.1102 (0.1110) time: 3.0202 data: 0.0078 max mem: 33408 +Epoch: [6] [2340/2639] eta: 0:15:05 lr: 4.2180698034260974e-05 loss: 0.1095 (0.1110) time: 2.9902 data: 0.0074 max mem: 33408 +Epoch: [6] [2350/2639] eta: 0:14:35 lr: 4.217635371367338e-05 loss: 0.1095 (0.1110) time: 3.0250 data: 0.0070 max mem: 33408 +Epoch: [6] [2360/2639] eta: 0:14:05 lr: 4.217200934336508e-05 loss: 0.1129 (0.1110) time: 3.0188 data: 0.0073 max mem: 33408 +Epoch: [6] [2370/2639] eta: 0:13:34 lr: 4.2167664923329834e-05 loss: 0.1015 (0.1110) time: 3.0380 data: 0.0077 max mem: 33408 +Epoch: [6] [2380/2639] eta: 0:13:04 lr: 4.216332045356138e-05 loss: 0.1006 (0.1110) time: 3.0468 data: 0.0077 max mem: 33408 +Epoch: [6] [2390/2639] eta: 0:12:34 lr: 4.2158975934053445e-05 loss: 0.1006 (0.1110) time: 3.0333 data: 0.0078 max mem: 33408 +Epoch: [6] [2400/2639] eta: 0:12:04 lr: 4.2154631364799766e-05 loss: 0.1003 (0.1110) time: 3.0582 data: 0.0077 max mem: 33408 +Epoch: [6] [2410/2639] eta: 0:11:33 lr: 4.215028674579408e-05 loss: 0.1007 (0.1110) time: 3.0131 data: 0.0074 max mem: 33408 +Epoch: [6] [2420/2639] eta: 0:11:03 lr: 4.214594207703012e-05 loss: 0.0730 (0.1108) time: 2.9852 data: 0.0072 max mem: 33408 +Epoch: [6] [2430/2639] eta: 0:10:33 lr: 4.2141597358501614e-05 loss: 0.0778 (0.1108) time: 2.9933 data: 0.0072 max mem: 33408 +Epoch: [6] [2440/2639] eta: 0:10:02 lr: 4.2137252590202294e-05 loss: 0.0998 (0.1107) time: 2.9973 data: 0.0068 max mem: 33408 +Epoch: [6] [2450/2639] eta: 0:09:32 lr: 4.213290777212588e-05 loss: 0.0999 (0.1108) time: 3.0469 data: 0.0068 max mem: 33408 +Epoch: [6] [2460/2639] eta: 0:09:02 lr: 4.212856290426611e-05 loss: 0.0974 (0.1108) time: 3.0921 data: 0.0073 max mem: 33408 +Epoch: [6] [2470/2639] eta: 0:08:31 lr: 4.2124217986616684e-05 loss: 0.0923 (0.1108) time: 3.0400 data: 0.0077 max mem: 33408 +Epoch: [6] [2480/2639] eta: 0:08:01 lr: 4.211987301917136e-05 loss: 0.0960 (0.1108) time: 3.0246 data: 0.0074 max mem: 33408 +Epoch: [6] [2490/2639] eta: 0:07:31 lr: 4.211552800192384e-05 loss: 0.1270 (0.1109) time: 3.0337 data: 0.0073 max mem: 33408 +Epoch: [6] [2500/2639] eta: 0:07:01 lr: 4.2111182934867846e-05 loss: 0.1078 (0.1109) time: 3.0355 data: 0.0075 max mem: 33408 +Epoch: [6] [2510/2639] eta: 0:06:30 lr: 4.2106837817997094e-05 loss: 0.1062 (0.1109) time: 3.0272 data: 0.0073 max mem: 33408 +Epoch: [6] [2520/2639] eta: 0:06:00 lr: 4.210249265130531e-05 loss: 0.1000 (0.1109) time: 3.0142 data: 0.0071 max mem: 33408 +Epoch: [6] [2530/2639] eta: 0:05:30 lr: 4.20981474347862e-05 loss: 0.0984 (0.1109) time: 3.0164 data: 0.0072 max mem: 33408 +Epoch: [6] [2540/2639] eta: 0:04:59 lr: 4.2093802168433476e-05 loss: 0.1150 (0.1110) time: 2.9949 data: 0.0077 max mem: 33408 +Epoch: [6] [2550/2639] eta: 0:04:29 lr: 4.208945685224087e-05 loss: 0.1092 (0.1110) time: 2.9854 data: 0.0081 max mem: 33408 +Epoch: [6] [2560/2639] eta: 0:03:59 lr: 4.208511148620208e-05 loss: 0.1045 (0.1111) time: 2.9712 data: 0.0081 max mem: 33408 +Epoch: [6] [2570/2639] eta: 0:03:28 lr: 4.20807660703108e-05 loss: 0.0950 (0.1111) time: 2.9576 data: 0.0081 max mem: 33408 +Epoch: [6] [2580/2639] eta: 0:02:58 lr: 4.2076420604560764e-05 loss: 0.0950 (0.1111) time: 2.9787 data: 0.0083 max mem: 33408 +Epoch: [6] [2590/2639] eta: 0:02:28 lr: 4.207207508894566e-05 loss: 0.0968 (0.1111) time: 2.9948 data: 0.0082 max mem: 33408 +Epoch: [6] [2600/2639] eta: 0:01:58 lr: 4.206772952345921e-05 loss: 0.0968 (0.1111) time: 2.9817 data: 0.0080 max mem: 33408 +Epoch: [6] [2610/2639] eta: 0:01:27 lr: 4.20633839080951e-05 loss: 0.1281 (0.1112) time: 2.9881 data: 0.0082 max mem: 33408 +Epoch: [6] [2620/2639] eta: 0:00:57 lr: 4.2059038242847045e-05 loss: 0.1266 (0.1112) time: 3.0121 data: 0.0081 max mem: 33408 +Epoch: [6] [2630/2639] eta: 0:00:27 lr: 4.2054692527708737e-05 loss: 0.1256 (0.1113) time: 3.0247 data: 0.0077 max mem: 33408 +Epoch: [6] Total time: 2:13:12 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 1:54:48 time: 2.6773 data: 2.5560 max mem: 33408 +Test: [ 100/2573] eta: 0:04:16 time: 0.0783 data: 0.0014 max mem: 33408 +Test: [ 200/2573] eta: 0:03:39 time: 0.0808 data: 0.0015 max mem: 33408 +Test: [ 300/2573] eta: 0:03:20 time: 0.0817 data: 0.0014 max mem: 33408 +Test: [ 400/2573] eta: 0:03:06 time: 0.0812 data: 0.0014 max mem: 33408 +Test: [ 500/2573] eta: 0:02:56 time: 0.0807 data: 0.0014 max mem: 33408 +Test: [ 600/2573] eta: 0:02:46 time: 0.0817 data: 0.0015 max mem: 33408 +Test: [ 700/2573] eta: 0:02:37 time: 0.0824 data: 0.0014 max mem: 33408 +Test: [ 800/2573] eta: 0:02:28 time: 0.0837 data: 0.0015 max mem: 33408 +Test: [ 900/2573] eta: 0:02:19 time: 0.0803 data: 0.0014 max mem: 33408 +Test: [1000/2573] eta: 0:02:10 time: 0.0805 data: 0.0014 max mem: 33408 +Test: [1100/2573] eta: 0:02:02 time: 0.0799 data: 0.0016 max mem: 33408 +Test: [1200/2573] eta: 0:01:53 time: 0.0808 data: 0.0014 max mem: 33408 +Test: [1300/2573] eta: 0:01:45 time: 0.0816 data: 0.0015 max mem: 33408 +Test: [1400/2573] eta: 0:01:36 time: 0.0784 data: 0.0014 max mem: 33408 +Test: [1500/2573] eta: 0:01:28 time: 0.0826 data: 0.0015 max mem: 33408 +Test: [1600/2573] eta: 0:01:20 time: 0.0836 data: 0.0014 max mem: 33408 +Test: [1700/2573] eta: 0:01:11 time: 0.0787 data: 0.0014 max mem: 33408 +Test: [1800/2573] eta: 0:01:03 time: 0.0816 data: 0.0016 max mem: 33408 +Test: [1900/2573] eta: 0:00:55 time: 0.0796 data: 0.0014 max mem: 33408 +Test: [2000/2573] eta: 0:00:46 time: 0.0807 data: 0.0015 max mem: 33408 +Test: [2100/2573] eta: 0:00:38 time: 0.0824 data: 0.0014 max mem: 33408 +Test: [2200/2573] eta: 0:00:30 time: 0.0828 data: 0.0014 max mem: 33408 +Test: [2300/2573] eta: 0:00:22 time: 0.0814 data: 0.0014 max mem: 33408 +Test: [2400/2573] eta: 0:00:14 time: 0.0775 data: 0.0015 max mem: 33408 +Test: [2500/2573] eta: 0:00:05 time: 0.0802 data: 0.0014 max mem: 33408 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: Total time: 0:03:31 +Final results: +Mean IoU is 57.43 + + precision@0.5 = 63.91 + precision@0.6 = 56.41 + precision@0.7 = 47.77 + precision@0.8 = 36.17 + precision@0.9 = 15.18 + overall IoU = 57.15 + +Average object IoU 57.42859063849697 +Overall IoU 57.15378952026367 +Better epoch: 6 + +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [7] [ 0/2639] eta: 4:02:46 lr: 4.205078134142289e-05 loss: 0.1083 (0.1083) time: 5.5196 data: 2.3164 max mem: 33408 +Epoch: [7] [ 10/2639] eta: 2:23:21 lr: 4.204643553147575e-05 loss: 0.1083 (0.1058) time: 3.2716 data: 0.2174 max mem: 33408 +Epoch: [7] [ 20/2639] eta: 2:17:55 lr: 4.2042089671620086e-05 loss: 0.0965 (0.1036) time: 3.0419 data: 0.0073 max mem: 33408 +Epoch: [7] [ 30/2639] eta: 2:15:18 lr: 4.203774376184958e-05 loss: 0.0950 (0.1000) time: 3.0235 data: 0.0075 max mem: 33408 +Epoch: [7] [ 40/2639] eta: 2:13:28 lr: 4.2033397802157936e-05 loss: 0.0905 (0.1002) time: 2.9987 data: 0.0076 max mem: 33408 +Epoch: [7] [ 50/2639] eta: 2:12:31 lr: 4.2029051792538845e-05 loss: 0.0905 (0.1000) time: 3.0085 data: 0.0077 max mem: 33408 +Epoch: [7] [ 60/2639] eta: 2:12:03 lr: 4.2024705732986e-05 loss: 0.0771 (0.0966) time: 3.0545 data: 0.0076 max mem: 33408 +Epoch: [7] [ 70/2639] eta: 2:11:21 lr: 4.2020359623493075e-05 loss: 0.0717 (0.0940) time: 3.0597 data: 0.0074 max mem: 33408 +Epoch: [7] [ 80/2639] eta: 2:10:27 lr: 4.2016013464053784e-05 loss: 0.0686 (0.0932) time: 3.0169 data: 0.0076 max mem: 33408 +Epoch: [7] [ 90/2639] eta: 2:10:01 lr: 4.2011667254661776e-05 loss: 0.0820 (0.0949) time: 3.0348 data: 0.0081 max mem: 33408 +Epoch: [7] [ 100/2639] eta: 2:09:18 lr: 4.200732099531077e-05 loss: 0.0820 (0.0959) time: 3.0436 data: 0.0088 max mem: 33408 +Epoch: [7] [ 110/2639] eta: 2:08:25 lr: 4.200297468599442e-05 loss: 0.1042 (0.0981) time: 2.9842 data: 0.0086 max mem: 33408 +Epoch: [7] [ 120/2639] eta: 2:07:53 lr: 4.1998628326706426e-05 loss: 0.1040 (0.0977) time: 2.9970 data: 0.0077 max mem: 33408 +Epoch: [7] [ 130/2639] eta: 2:07:23 lr: 4.199428191744046e-05 loss: 0.1042 (0.0992) time: 3.0440 data: 0.0078 max mem: 33408 +Epoch: [7] [ 140/2639] eta: 2:06:40 lr: 4.198993545819019e-05 loss: 0.1109 (0.0993) time: 3.0144 data: 0.0082 max mem: 33408 +Epoch: [7] [ 150/2639] eta: 2:06:17 lr: 4.1985588948949314e-05 loss: 0.1062 (0.0999) time: 3.0318 data: 0.0077 max mem: 33408 +Epoch: [7] [ 160/2639] eta: 2:05:33 lr: 4.19812423897115e-05 loss: 0.0968 (0.0999) time: 3.0196 data: 0.0080 max mem: 33408 +Epoch: [7] [ 170/2639] eta: 2:05:13 lr: 4.19768957804704e-05 loss: 0.0916 (0.1005) time: 3.0312 data: 0.0085 max mem: 33408 +Epoch: [7] [ 180/2639] eta: 2:04:28 lr: 4.197254912121971e-05 loss: 0.0864 (0.1003) time: 3.0258 data: 0.0082 max mem: 33408 +Epoch: [7] [ 190/2639] eta: 2:04:06 lr: 4.196820241195309e-05 loss: 0.0848 (0.1006) time: 3.0207 data: 0.0077 max mem: 33408 +Epoch: [7] [ 200/2639] eta: 2:03:30 lr: 4.196385565266422e-05 loss: 0.0949 (0.1017) time: 3.0475 data: 0.0075 max mem: 33408 +Epoch: [7] [ 210/2639] eta: 2:03:03 lr: 4.195950884334675e-05 loss: 0.1015 (0.1014) time: 3.0329 data: 0.0076 max mem: 33408 +Epoch: [7] [ 220/2639] eta: 2:02:30 lr: 4.195516198399434e-05 loss: 0.0853 (0.1011) time: 3.0392 data: 0.0077 max mem: 33408 +Epoch: [7] [ 230/2639] eta: 2:02:02 lr: 4.195081507460068e-05 loss: 0.0917 (0.1015) time: 3.0370 data: 0.0078 max mem: 33408 +Epoch: [7] [ 240/2639] eta: 2:01:41 lr: 4.1946468115159416e-05 loss: 0.0917 (0.1019) time: 3.0974 data: 0.0076 max mem: 33408 +Epoch: [7] [ 250/2639] eta: 2:01:01 lr: 4.194212110566422e-05 loss: 0.0862 (0.1013) time: 3.0399 data: 0.0075 max mem: 33408 +Epoch: [7] [ 260/2639] eta: 2:00:25 lr: 4.193777404610873e-05 loss: 0.0898 (0.1009) time: 2.9634 data: 0.0077 max mem: 33408 +Epoch: [7] [ 270/2639] eta: 1:59:49 lr: 4.1933426936486625e-05 loss: 0.0873 (0.1006) time: 2.9726 data: 0.0080 max mem: 33408 +Epoch: [7] [ 280/2639] eta: 1:59:11 lr: 4.192907977679155e-05 loss: 0.1003 (0.1016) time: 2.9597 data: 0.0084 max mem: 33408 +Epoch: [7] [ 290/2639] eta: 1:58:43 lr: 4.1924732567017166e-05 loss: 0.1135 (0.1020) time: 3.0048 data: 0.0083 max mem: 33408 +Epoch: [7] [ 300/2639] eta: 1:58:12 lr: 4.1920385307157116e-05 loss: 0.0848 (0.1019) time: 3.0371 data: 0.0079 max mem: 33408 +Epoch: [7] [ 310/2639] eta: 1:57:42 lr: 4.191603799720507e-05 loss: 0.0763 (0.1011) time: 3.0297 data: 0.0077 max mem: 33408 +Epoch: [7] [ 320/2639] eta: 1:57:08 lr: 4.191169063715466e-05 loss: 0.0797 (0.1007) time: 3.0149 data: 0.0075 max mem: 33408 +Epoch: [7] [ 330/2639] eta: 1:56:41 lr: 4.1907343226999546e-05 loss: 0.0862 (0.1001) time: 3.0303 data: 0.0077 max mem: 33408 +Epoch: [7] [ 340/2639] eta: 1:56:09 lr: 4.1902995766733365e-05 loss: 0.0890 (0.0999) time: 3.0371 data: 0.0080 max mem: 33408 +Epoch: [7] [ 350/2639] eta: 1:55:40 lr: 4.1898648256349775e-05 loss: 0.0937 (0.1001) time: 3.0281 data: 0.0077 max mem: 33408 +Epoch: [7] [ 360/2639] eta: 1:55:10 lr: 4.189430069584241e-05 loss: 0.0937 (0.1002) time: 3.0450 data: 0.0077 max mem: 33408 +Epoch: [7] [ 370/2639] eta: 1:54:39 lr: 4.188995308520492e-05 loss: 0.0929 (0.0999) time: 3.0305 data: 0.0080 max mem: 33408 +Epoch: [7] [ 380/2639] eta: 1:54:10 lr: 4.1885605424430935e-05 loss: 0.0929 (0.1000) time: 3.0390 data: 0.0079 max mem: 33408 +Epoch: [7] [ 390/2639] eta: 1:53:39 lr: 4.18812577135141e-05 loss: 0.0933 (0.1000) time: 3.0388 data: 0.0080 max mem: 33408 +Epoch: [7] [ 400/2639] eta: 1:53:14 lr: 4.1876909952448065e-05 loss: 0.0895 (0.0997) time: 3.0721 data: 0.0080 max mem: 33408 +Epoch: [7] [ 410/2639] eta: 1:52:40 lr: 4.1872562141226446e-05 loss: 0.0815 (0.0994) time: 3.0458 data: 0.0079 max mem: 33408 +Epoch: [7] [ 420/2639] eta: 1:52:10 lr: 4.1868214279842886e-05 loss: 0.0814 (0.0991) time: 3.0016 data: 0.0080 max mem: 33408 +Epoch: [7] [ 430/2639] eta: 1:51:36 lr: 4.186386636829102e-05 loss: 0.0923 (0.0991) time: 3.0041 data: 0.0080 max mem: 33408 +Epoch: [7] [ 440/2639] eta: 1:51:06 lr: 4.185951840656448e-05 loss: 0.0923 (0.0993) time: 3.0060 data: 0.0078 max mem: 33408 +Epoch: [7] [ 450/2639] eta: 1:50:34 lr: 4.1855170394656906e-05 loss: 0.0856 (0.0994) time: 3.0182 data: 0.0080 max mem: 33408 +Epoch: [7] [ 460/2639] eta: 1:50:06 lr: 4.18508223325619e-05 loss: 0.0789 (0.0992) time: 3.0408 data: 0.0079 max mem: 33408 +Epoch: [7] [ 470/2639] eta: 1:49:38 lr: 4.1846474220273116e-05 loss: 0.0866 (0.0993) time: 3.0756 data: 0.0084 max mem: 33408 +Epoch: [7] [ 480/2639] eta: 1:49:07 lr: 4.184212605778416e-05 loss: 0.0886 (0.0992) time: 3.0510 data: 0.0087 max mem: 33408 +Epoch: [7] [ 490/2639] eta: 1:48:36 lr: 4.1837777845088666e-05 loss: 0.1055 (0.0993) time: 3.0125 data: 0.0081 max mem: 33408 +Epoch: [7] [ 500/2639] eta: 1:48:07 lr: 4.183342958218026e-05 loss: 0.0892 (0.0995) time: 3.0342 data: 0.0077 max mem: 33408 +Epoch: [7] [ 510/2639] eta: 1:47:37 lr: 4.1829081269052545e-05 loss: 0.0977 (0.0997) time: 3.0522 data: 0.0074 max mem: 33408 +Epoch: [7] [ 520/2639] eta: 1:47:05 lr: 4.182473290569917e-05 loss: 0.0867 (0.0994) time: 3.0198 data: 0.0080 max mem: 33408 +Epoch: [7] [ 530/2639] eta: 1:46:34 lr: 4.1820384492113715e-05 loss: 0.0889 (0.0994) time: 3.0098 data: 0.0081 max mem: 33408 +Epoch: [7] [ 540/2639] eta: 1:46:02 lr: 4.181603602828983e-05 loss: 0.0951 (0.0994) time: 3.0022 data: 0.0081 max mem: 33408 +Epoch: [7] [ 550/2639] eta: 1:45:30 lr: 4.181168751422111e-05 loss: 0.1044 (0.0996) time: 2.9846 data: 0.0085 max mem: 33408 +Epoch: [7] [ 560/2639] eta: 1:45:02 lr: 4.180733894990118e-05 loss: 0.0974 (0.0995) time: 3.0369 data: 0.0085 max mem: 33408 +Epoch: [7] [ 570/2639] eta: 1:44:35 lr: 4.180299033532364e-05 loss: 0.0911 (0.0994) time: 3.1107 data: 0.0082 max mem: 33408 +Epoch: [7] [ 580/2639] eta: 1:44:02 lr: 4.179864167048211e-05 loss: 0.0911 (0.0993) time: 3.0347 data: 0.0083 max mem: 33408 +Epoch: [7] [ 590/2639] eta: 1:43:34 lr: 4.179429295537019e-05 loss: 0.0975 (0.0993) time: 3.0327 data: 0.0087 max mem: 33408 +Epoch: [7] [ 600/2639] eta: 1:43:03 lr: 4.17899441899815e-05 loss: 0.1023 (0.0997) time: 3.0564 data: 0.0088 max mem: 33408 +Epoch: [7] [ 610/2639] eta: 1:42:36 lr: 4.178559537430963e-05 loss: 0.1057 (0.0997) time: 3.0652 data: 0.0083 max mem: 33408 +Epoch: [7] [ 620/2639] eta: 1:42:07 lr: 4.178124650834819e-05 loss: 0.0967 (0.0997) time: 3.1124 data: 0.0078 max mem: 33408 +Epoch: [7] [ 630/2639] eta: 1:41:35 lr: 4.177689759209078e-05 loss: 0.0988 (0.0996) time: 3.0318 data: 0.0080 max mem: 33408 +Epoch: [7] [ 640/2639] eta: 1:41:07 lr: 4.1772548625531004e-05 loss: 0.0963 (0.0997) time: 3.0481 data: 0.0080 max mem: 33408 +Epoch: [7] [ 650/2639] eta: 1:40:36 lr: 4.176819960866247e-05 loss: 0.0932 (0.0999) time: 3.0627 data: 0.0082 max mem: 33408 +Epoch: [7] [ 660/2639] eta: 1:40:07 lr: 4.176385054147876e-05 loss: 0.0921 (0.0999) time: 3.0381 data: 0.0080 max mem: 33408 +Epoch: [7] [ 670/2639] eta: 1:39:35 lr: 4.175950142397347e-05 loss: 0.1007 (0.1003) time: 3.0223 data: 0.0075 max mem: 33408 +Epoch: [7] [ 680/2639] eta: 1:39:06 lr: 4.175515225614021e-05 loss: 0.1192 (0.1006) time: 3.0307 data: 0.0077 max mem: 33408 +Epoch: [7] [ 690/2639] eta: 1:38:35 lr: 4.1750803037972556e-05 loss: 0.1065 (0.1006) time: 3.0616 data: 0.0082 max mem: 33408 +Epoch: [7] [ 700/2639] eta: 1:38:05 lr: 4.174645376946412e-05 loss: 0.0833 (0.1005) time: 3.0370 data: 0.0082 max mem: 33408 +Epoch: [7] [ 710/2639] eta: 1:37:35 lr: 4.174210445060846e-05 loss: 0.0858 (0.1004) time: 3.0378 data: 0.0079 max mem: 33408 +Epoch: [7] [ 720/2639] eta: 1:37:04 lr: 4.173775508139919e-05 loss: 0.0835 (0.1001) time: 3.0198 data: 0.0078 max mem: 33408 +Epoch: [7] [ 730/2639] eta: 1:36:33 lr: 4.1733405661829894e-05 loss: 0.0869 (0.1002) time: 3.0153 data: 0.0077 max mem: 33408 +Epoch: [7] [ 740/2639] eta: 1:36:01 lr: 4.172905619189414e-05 loss: 0.1023 (0.1003) time: 2.9928 data: 0.0079 max mem: 33408 +Epoch: [7] [ 750/2639] eta: 1:35:30 lr: 4.172470667158554e-05 loss: 0.0974 (0.1001) time: 2.9949 data: 0.0079 max mem: 33408 +Epoch: [7] [ 760/2639] eta: 1:34:59 lr: 4.1720357100897654e-05 loss: 0.1012 (0.1004) time: 3.0091 data: 0.0077 max mem: 33408 +Epoch: [7] [ 770/2639] eta: 1:34:28 lr: 4.171600747982407e-05 loss: 0.0972 (0.1001) time: 3.0018 data: 0.0077 max mem: 33408 +Epoch: [7] [ 780/2639] eta: 1:33:58 lr: 4.1711657808358356e-05 loss: 0.0771 (0.0999) time: 3.0192 data: 0.0079 max mem: 33408 +Epoch: [7] [ 790/2639] eta: 1:33:25 lr: 4.1707308086494114e-05 loss: 0.0963 (0.1000) time: 2.9878 data: 0.0079 max mem: 33408 +Epoch: [7] [ 800/2639] eta: 1:32:56 lr: 4.170295831422489e-05 loss: 0.1107 (0.1002) time: 3.0124 data: 0.0075 max mem: 33408 +Epoch: [7] [ 810/2639] eta: 1:32:24 lr: 4.169860849154428e-05 loss: 0.0955 (0.1003) time: 3.0123 data: 0.0074 max mem: 33408 +Epoch: [7] [ 820/2639] eta: 1:31:52 lr: 4.169425861844585e-05 loss: 0.0937 (0.1003) time: 2.9648 data: 0.0077 max mem: 33408 +Epoch: [7] [ 830/2639] eta: 1:31:22 lr: 4.168990869492317e-05 loss: 0.0842 (0.1002) time: 3.0049 data: 0.0075 max mem: 33408 +Epoch: [7] [ 840/2639] eta: 1:30:51 lr: 4.168555872096981e-05 loss: 0.0842 (0.1001) time: 3.0215 data: 0.0074 max mem: 33408 +Epoch: [7] [ 850/2639] eta: 1:30:20 lr: 4.1681208696579335e-05 loss: 0.0810 (0.0998) time: 3.0041 data: 0.0078 max mem: 33408 +Epoch: [7] [ 860/2639] eta: 1:29:49 lr: 4.167685862174531e-05 loss: 0.0822 (0.0998) time: 2.9966 data: 0.0078 max mem: 33408 +Epoch: [7] [ 870/2639] eta: 1:29:21 lr: 4.167250849646132e-05 loss: 0.0822 (0.0996) time: 3.0542 data: 0.0076 max mem: 33408 +Epoch: [7] [ 880/2639] eta: 1:28:51 lr: 4.1668158320720894e-05 loss: 0.0848 (0.0996) time: 3.0927 data: 0.0075 max mem: 33408 +Epoch: [7] [ 890/2639] eta: 1:28:20 lr: 4.166380809451762e-05 loss: 0.0906 (0.0994) time: 3.0384 data: 0.0075 max mem: 33408 +Epoch: [7] [ 900/2639] eta: 1:27:50 lr: 4.165945781784505e-05 loss: 0.0906 (0.0995) time: 3.0245 data: 0.0075 max mem: 33408 +Epoch: [7] [ 910/2639] eta: 1:27:20 lr: 4.165510749069674e-05 loss: 0.0815 (0.0994) time: 3.0437 data: 0.0078 max mem: 33408 +Epoch: [7] [ 920/2639] eta: 1:26:50 lr: 4.1650757113066254e-05 loss: 0.0792 (0.0994) time: 3.0392 data: 0.0079 max mem: 33408 +Epoch: [7] [ 930/2639] eta: 1:26:20 lr: 4.164640668494714e-05 loss: 0.0923 (0.0994) time: 3.0413 data: 0.0077 max mem: 33408 +Epoch: [7] [ 940/2639] eta: 1:25:50 lr: 4.1642056206332955e-05 loss: 0.1040 (0.0996) time: 3.0594 data: 0.0076 max mem: 33408 +Epoch: [7] [ 950/2639] eta: 1:25:20 lr: 4.163770567721725e-05 loss: 0.1117 (0.0999) time: 3.0488 data: 0.0077 max mem: 33408 +Epoch: [7] [ 960/2639] eta: 1:24:49 lr: 4.1633355097593575e-05 loss: 0.0955 (0.0999) time: 3.0148 data: 0.0076 max mem: 33408 +Epoch: [7] [ 970/2639] eta: 1:24:20 lr: 4.1629004467455476e-05 loss: 0.0955 (0.1000) time: 3.0375 data: 0.0074 max mem: 33408 +Epoch: [7] [ 980/2639] eta: 1:23:49 lr: 4.162465378679652e-05 loss: 0.1022 (0.1001) time: 3.0482 data: 0.0077 max mem: 33408 +Epoch: [7] [ 990/2639] eta: 1:23:19 lr: 4.162030305561022e-05 loss: 0.0997 (0.1002) time: 3.0388 data: 0.0080 max mem: 33408 +Epoch: [7] [1000/2639] eta: 1:22:49 lr: 4.1615952273890155e-05 loss: 0.0944 (0.1003) time: 3.0570 data: 0.0078 max mem: 33408 +Epoch: [7] [1010/2639] eta: 1:22:18 lr: 4.1611601441629835e-05 loss: 0.0877 (0.1002) time: 3.0265 data: 0.0077 max mem: 33408 +Epoch: [7] [1020/2639] eta: 1:21:48 lr: 4.160725055882284e-05 loss: 0.0893 (0.1002) time: 3.0104 data: 0.0082 max mem: 33408 +Epoch: [7] [1030/2639] eta: 1:21:17 lr: 4.1602899625462666e-05 loss: 0.0893 (0.1003) time: 3.0126 data: 0.0084 max mem: 33408 +Epoch: [7] [1040/2639] eta: 1:20:47 lr: 4.159854864154288e-05 loss: 0.0845 (0.1002) time: 3.0257 data: 0.0084 max mem: 33408 +Epoch: [7] [1050/2639] eta: 1:20:17 lr: 4.159419760705701e-05 loss: 0.0845 (0.1001) time: 3.0365 data: 0.0081 max mem: 33408 +Epoch: [7] [1060/2639] eta: 1:19:45 lr: 4.1589846521998594e-05 loss: 0.0857 (0.1000) time: 2.9894 data: 0.0077 max mem: 33408 +Epoch: [7] [1070/2639] eta: 1:19:16 lr: 4.158549538636115e-05 loss: 0.0956 (0.1002) time: 3.0294 data: 0.0079 max mem: 33408 +Epoch: [7] [1080/2639] eta: 1:18:46 lr: 4.158114420013824e-05 loss: 0.0928 (0.1000) time: 3.0651 data: 0.0081 max mem: 33408 +Epoch: [7] [1090/2639] eta: 1:18:16 lr: 4.157679296332337e-05 loss: 0.0771 (0.0998) time: 3.0571 data: 0.0076 max mem: 33408 +Epoch: [7] [1100/2639] eta: 1:17:47 lr: 4.1572441675910067e-05 loss: 0.0826 (0.0998) time: 3.0885 data: 0.0073 max mem: 33408 +Epoch: [7] [1110/2639] eta: 1:17:16 lr: 4.156809033789188e-05 loss: 0.0861 (0.0999) time: 3.0355 data: 0.0076 max mem: 33408 +Epoch: [7] [1120/2639] eta: 1:16:46 lr: 4.1563738949262316e-05 loss: 0.0800 (0.0998) time: 3.0334 data: 0.0075 max mem: 33408 +Epoch: [7] [1130/2639] eta: 1:16:15 lr: 4.15593875100149e-05 loss: 0.0864 (0.0997) time: 3.0412 data: 0.0078 max mem: 33408 +Epoch: [7] [1140/2639] eta: 1:15:45 lr: 4.155503602014316e-05 loss: 0.1019 (0.0999) time: 3.0123 data: 0.0082 max mem: 33408 +Epoch: [7] [1150/2639] eta: 1:15:15 lr: 4.155068447964062e-05 loss: 0.1040 (0.0999) time: 3.0504 data: 0.0079 max mem: 33408 +Epoch: [7] [1160/2639] eta: 1:14:44 lr: 4.154633288850079e-05 loss: 0.1060 (0.1001) time: 3.0247 data: 0.0076 max mem: 33408 +Epoch: [7] [1170/2639] eta: 1:14:14 lr: 4.154198124671719e-05 loss: 0.1004 (0.1002) time: 3.0265 data: 0.0073 max mem: 33408 +Epoch: [7] [1180/2639] eta: 1:13:44 lr: 4.153762955428333e-05 loss: 0.1004 (0.1002) time: 3.0792 data: 0.0073 max mem: 33408 +Epoch: [7] [1190/2639] eta: 1:13:13 lr: 4.153327781119274e-05 loss: 0.1118 (0.1005) time: 3.0287 data: 0.0073 max mem: 33408 +Epoch: [7] [1200/2639] eta: 1:12:43 lr: 4.152892601743893e-05 loss: 0.1118 (0.1005) time: 3.0165 data: 0.0072 max mem: 33408 +Epoch: [7] [1210/2639] eta: 1:12:13 lr: 4.15245741730154e-05 loss: 0.0908 (0.1005) time: 3.0223 data: 0.0072 max mem: 33408 +Epoch: [7] [1220/2639] eta: 1:11:43 lr: 4.152022227791565e-05 loss: 0.0966 (0.1006) time: 3.0213 data: 0.0072 max mem: 33408 +Epoch: [7] [1230/2639] eta: 1:11:12 lr: 4.1515870332133224e-05 loss: 0.0966 (0.1007) time: 3.0422 data: 0.0073 max mem: 33408 +Epoch: [7] [1240/2639] eta: 1:10:42 lr: 4.1511518335661606e-05 loss: 0.1031 (0.1009) time: 3.0218 data: 0.0079 max mem: 33408 +Epoch: [7] [1250/2639] eta: 1:10:11 lr: 4.1507166288494294e-05 loss: 0.1103 (0.1009) time: 2.9914 data: 0.0080 max mem: 33408 +Epoch: [7] [1260/2639] eta: 1:09:41 lr: 4.15028141906248e-05 loss: 0.1021 (0.1009) time: 3.0298 data: 0.0076 max mem: 33408 +Epoch: [7] [1270/2639] eta: 1:09:10 lr: 4.149846204204663e-05 loss: 0.0941 (0.1010) time: 3.0546 data: 0.0076 max mem: 33408 +Epoch: [7] [1280/2639] eta: 1:08:40 lr: 4.1494109842753274e-05 loss: 0.0893 (0.1009) time: 3.0048 data: 0.0076 max mem: 33408 +Epoch: [7] [1290/2639] eta: 1:08:09 lr: 4.148975759273824e-05 loss: 0.0858 (0.1010) time: 2.9758 data: 0.0075 max mem: 33408 +Epoch: [7] [1300/2639] eta: 1:07:37 lr: 4.148540529199502e-05 loss: 0.0858 (0.1009) time: 2.9496 data: 0.0076 max mem: 33408 +Epoch: [7] [1310/2639] eta: 1:07:07 lr: 4.1481052940517114e-05 loss: 0.0843 (0.1009) time: 2.9919 data: 0.0078 max mem: 33408 +Epoch: [7] [1320/2639] eta: 1:06:36 lr: 4.1476700538298005e-05 loss: 0.1035 (0.1010) time: 2.9993 data: 0.0077 max mem: 33408 +Epoch: [7] [1330/2639] eta: 1:06:05 lr: 4.1472348085331194e-05 loss: 0.1128 (0.1014) time: 2.9646 data: 0.0079 max mem: 33408 +Epoch: [7] [1340/2639] eta: 1:05:35 lr: 4.146799558161017e-05 loss: 0.1128 (0.1014) time: 2.9829 data: 0.0082 max mem: 33408 +Epoch: [7] [1350/2639] eta: 1:05:04 lr: 4.146364302712842e-05 loss: 0.0872 (0.1013) time: 3.0005 data: 0.0084 max mem: 33408 +Epoch: [7] [1360/2639] eta: 1:04:34 lr: 4.1459290421879434e-05 loss: 0.0927 (0.1014) time: 3.0162 data: 0.0083 max mem: 33408 +Epoch: [7] [1370/2639] eta: 1:04:03 lr: 4.1454937765856694e-05 loss: 0.1051 (0.1015) time: 3.0104 data: 0.0080 max mem: 33408 +Epoch: [7] [1380/2639] eta: 1:03:33 lr: 4.1450585059053685e-05 loss: 0.0878 (0.1013) time: 3.0021 data: 0.0078 max mem: 33408 +Epoch: [7] [1390/2639] eta: 1:03:02 lr: 4.144623230146389e-05 loss: 0.0869 (0.1013) time: 2.9914 data: 0.0076 max mem: 33408 +Epoch: [7] [1400/2639] eta: 1:02:31 lr: 4.14418794930808e-05 loss: 0.1003 (0.1014) time: 2.9528 data: 0.0078 max mem: 33408 +Epoch: [7] [1410/2639] eta: 1:02:01 lr: 4.143752663389788e-05 loss: 0.1031 (0.1013) time: 2.9891 data: 0.0080 max mem: 33408 +Epoch: [7] [1420/2639] eta: 1:01:30 lr: 4.1433173723908605e-05 loss: 0.0928 (0.1013) time: 3.0285 data: 0.0078 max mem: 33408 +Epoch: [7] [1430/2639] eta: 1:01:00 lr: 4.142882076310647e-05 loss: 0.0927 (0.1013) time: 3.0484 data: 0.0078 max mem: 33408 +Epoch: [7] [1440/2639] eta: 1:00:29 lr: 4.142446775148493e-05 loss: 0.0887 (0.1012) time: 3.0108 data: 0.0080 max mem: 33408 +Epoch: [7] [1450/2639] eta: 0:59:59 lr: 4.142011468903748e-05 loss: 0.0887 (0.1012) time: 2.9858 data: 0.0079 max mem: 33408 +Epoch: [7] [1460/2639] eta: 0:59:29 lr: 4.1415761575757565e-05 loss: 0.0846 (0.1010) time: 3.0244 data: 0.0081 max mem: 33408 +Epoch: [7] [1470/2639] eta: 0:58:59 lr: 4.141140841163867e-05 loss: 0.0807 (0.1011) time: 3.0255 data: 0.0081 max mem: 33408 +Epoch: [7] [1480/2639] eta: 0:58:28 lr: 4.140705519667426e-05 loss: 0.0928 (0.1011) time: 3.0119 data: 0.0079 max mem: 33408 +Epoch: [7] [1490/2639] eta: 0:57:58 lr: 4.1402701930857806e-05 loss: 0.0969 (0.1011) time: 3.0541 data: 0.0078 max mem: 33408 +Epoch: [7] [1500/2639] eta: 0:57:28 lr: 4.139834861418277e-05 loss: 0.0834 (0.1011) time: 3.0659 data: 0.0076 max mem: 33408 +Epoch: [7] [1510/2639] eta: 0:56:58 lr: 4.139399524664261e-05 loss: 0.0894 (0.1012) time: 3.0156 data: 0.0075 max mem: 33408 +Epoch: [7] [1520/2639] eta: 0:56:27 lr: 4.1389641828230794e-05 loss: 0.0919 (0.1012) time: 2.9994 data: 0.0082 max mem: 33408 +Epoch: [7] [1530/2639] eta: 0:55:57 lr: 4.138528835894078e-05 loss: 0.0911 (0.1011) time: 2.9880 data: 0.0083 max mem: 33408 +Epoch: [7] [1540/2639] eta: 0:55:26 lr: 4.1380934838766036e-05 loss: 0.0911 (0.1012) time: 2.9824 data: 0.0082 max mem: 33408 +Epoch: [7] [1550/2639] eta: 0:54:56 lr: 4.1376581267699993e-05 loss: 0.0949 (0.1012) time: 3.0114 data: 0.0084 max mem: 33408 +Epoch: [7] [1560/2639] eta: 0:54:25 lr: 4.1372227645736134e-05 loss: 0.0877 (0.1012) time: 3.0261 data: 0.0079 max mem: 33408 +Epoch: [7] [1570/2639] eta: 0:53:55 lr: 4.13678739728679e-05 loss: 0.0949 (0.1014) time: 3.0079 data: 0.0081 max mem: 33408 +Epoch: [7] [1580/2639] eta: 0:53:24 lr: 4.136352024908875e-05 loss: 0.0982 (0.1015) time: 2.9995 data: 0.0085 max mem: 33408 +Epoch: [7] [1590/2639] eta: 0:52:55 lr: 4.1359166474392114e-05 loss: 0.0910 (0.1015) time: 3.0418 data: 0.0085 max mem: 33408 +Epoch: [7] [1600/2639] eta: 0:52:24 lr: 4.135481264877146e-05 loss: 0.0907 (0.1015) time: 3.0608 data: 0.0082 max mem: 33408 +Epoch: [7] [1610/2639] eta: 0:51:54 lr: 4.135045877222024e-05 loss: 0.0966 (0.1016) time: 3.0190 data: 0.0080 max mem: 33408 +Epoch: [7] [1620/2639] eta: 0:51:24 lr: 4.1346104844731896e-05 loss: 0.1080 (0.1017) time: 3.0223 data: 0.0079 max mem: 33408 +Epoch: [7] [1630/2639] eta: 0:50:53 lr: 4.134175086629986e-05 loss: 0.0912 (0.1016) time: 3.0211 data: 0.0078 max mem: 33408 +Epoch: [7] [1640/2639] eta: 0:50:23 lr: 4.1337396836917575e-05 loss: 0.0854 (0.1016) time: 3.0254 data: 0.0080 max mem: 33408 +Epoch: [7] [1650/2639] eta: 0:49:53 lr: 4.1333042756578496e-05 loss: 0.0918 (0.1016) time: 3.0077 data: 0.0076 max mem: 33408 +Epoch: [7] [1660/2639] eta: 0:49:22 lr: 4.132868862527605e-05 loss: 0.1012 (0.1019) time: 2.9855 data: 0.0075 max mem: 33408 +Epoch: [7] [1670/2639] eta: 0:48:52 lr: 4.132433444300368e-05 loss: 0.0991 (0.1020) time: 3.0109 data: 0.0078 max mem: 33408 +Epoch: [7] [1680/2639] eta: 0:48:22 lr: 4.1319980209754824e-05 loss: 0.1005 (0.1020) time: 3.0653 data: 0.0076 max mem: 33408 +Epoch: [7] [1690/2639] eta: 0:47:52 lr: 4.131562592552291e-05 loss: 0.1029 (0.1021) time: 3.0326 data: 0.0076 max mem: 33408 +Epoch: [7] [1700/2639] eta: 0:47:21 lr: 4.131127159030138e-05 loss: 0.1054 (0.1022) time: 2.9663 data: 0.0076 max mem: 33408 +Epoch: [7] [1710/2639] eta: 0:46:51 lr: 4.130691720408365e-05 loss: 0.1070 (0.1023) time: 3.0223 data: 0.0077 max mem: 33408 +Epoch: [7] [1720/2639] eta: 0:46:21 lr: 4.1302562766863165e-05 loss: 0.0960 (0.1022) time: 3.0488 data: 0.0078 max mem: 33408 +Epoch: [7] [1730/2639] eta: 0:45:51 lr: 4.129820827863336e-05 loss: 0.0907 (0.1023) time: 3.0786 data: 0.0076 max mem: 33408 +Epoch: [7] [1740/2639] eta: 0:45:21 lr: 4.129385373938763e-05 loss: 0.0952 (0.1023) time: 3.0631 data: 0.0075 max mem: 33408 +Epoch: [7] [1750/2639] eta: 0:44:50 lr: 4.128949914911942e-05 loss: 0.1048 (0.1024) time: 3.0129 data: 0.0074 max mem: 33408 +Epoch: [7] [1760/2639] eta: 0:44:20 lr: 4.128514450782215e-05 loss: 0.1028 (0.1024) time: 3.0665 data: 0.0074 max mem: 33408 +Epoch: [7] [1770/2639] eta: 0:43:50 lr: 4.1280789815489253e-05 loss: 0.0979 (0.1025) time: 3.0517 data: 0.0077 max mem: 33408 +Epoch: [7] [1780/2639] eta: 0:43:20 lr: 4.127643507211413e-05 loss: 0.0892 (0.1025) time: 3.0566 data: 0.0078 max mem: 33408 +Epoch: [7] [1790/2639] eta: 0:42:50 lr: 4.1272080277690203e-05 loss: 0.0911 (0.1024) time: 3.0323 data: 0.0078 max mem: 33408 +Epoch: [7] [1800/2639] eta: 0:42:19 lr: 4.12677254322109e-05 loss: 0.0938 (0.1025) time: 3.0120 data: 0.0079 max mem: 33408 +Epoch: [7] [1810/2639] eta: 0:41:50 lr: 4.126337053566963e-05 loss: 0.0882 (0.1024) time: 3.0836 data: 0.0078 max mem: 33408 +Epoch: [7] [1820/2639] eta: 0:41:19 lr: 4.12590155880598e-05 loss: 0.0942 (0.1023) time: 3.0604 data: 0.0078 max mem: 33408 +Epoch: [7] [1830/2639] eta: 0:40:50 lr: 4.1254660589374836e-05 loss: 0.0949 (0.1023) time: 3.0905 data: 0.0079 max mem: 33408 +Epoch: [7] [1840/2639] eta: 0:40:19 lr: 4.125030553960813e-05 loss: 0.0955 (0.1023) time: 3.1104 data: 0.0075 max mem: 33408 +Epoch: [7] [1850/2639] eta: 0:39:49 lr: 4.124595043875309e-05 loss: 0.0852 (0.1023) time: 3.0138 data: 0.0073 max mem: 33408 +Epoch: [7] [1860/2639] eta: 0:39:19 lr: 4.124159528680315e-05 loss: 0.0953 (0.1023) time: 3.0208 data: 0.0075 max mem: 33408 +Epoch: [7] [1870/2639] eta: 0:38:48 lr: 4.123724008375169e-05 loss: 0.0953 (0.1023) time: 3.0400 data: 0.0077 max mem: 33408 +Epoch: [7] [1880/2639] eta: 0:38:18 lr: 4.1232884829592125e-05 loss: 0.0944 (0.1023) time: 3.0398 data: 0.0079 max mem: 33408 +Epoch: [7] [1890/2639] eta: 0:37:48 lr: 4.1228529524317846e-05 loss: 0.0896 (0.1022) time: 3.1110 data: 0.0079 max mem: 33408 +Epoch: [7] [1900/2639] eta: 0:37:18 lr: 4.122417416792226e-05 loss: 0.0832 (0.1021) time: 3.0659 data: 0.0082 max mem: 33408 +Epoch: [7] [1910/2639] eta: 0:36:48 lr: 4.1219818760398774e-05 loss: 0.0895 (0.1022) time: 3.0164 data: 0.0077 max mem: 33408 +Epoch: [7] [1920/2639] eta: 0:36:18 lr: 4.1215463301740774e-05 loss: 0.0953 (0.1022) time: 3.0595 data: 0.0075 max mem: 33408 +Epoch: [7] [1930/2639] eta: 0:35:47 lr: 4.1211107791941655e-05 loss: 0.0953 (0.1022) time: 3.0508 data: 0.0079 max mem: 33408 +Epoch: [7] [1940/2639] eta: 0:35:17 lr: 4.1206752230994825e-05 loss: 0.0971 (0.1024) time: 3.0880 data: 0.0074 max mem: 33408 +Epoch: [7] [1950/2639] eta: 0:34:47 lr: 4.1202396618893655e-05 loss: 0.0923 (0.1024) time: 3.0737 data: 0.0072 max mem: 33408 +Epoch: [7] [1960/2639] eta: 0:34:17 lr: 4.119804095563155e-05 loss: 0.0922 (0.1025) time: 3.0314 data: 0.0078 max mem: 33408 +Epoch: [7] [1970/2639] eta: 0:33:47 lr: 4.119368524120189e-05 loss: 0.1111 (0.1025) time: 3.0673 data: 0.0084 max mem: 33408 +Epoch: [7] [1980/2639] eta: 0:33:16 lr: 4.118932947559807e-05 loss: 0.1072 (0.1025) time: 3.0296 data: 0.0083 max mem: 33408 +Epoch: [7] [1990/2639] eta: 0:32:46 lr: 4.118497365881348e-05 loss: 0.0914 (0.1026) time: 3.0108 data: 0.0080 max mem: 33408 +Epoch: [7] [2000/2639] eta: 0:32:16 lr: 4.118061779084148e-05 loss: 0.0894 (0.1025) time: 3.0139 data: 0.0084 max mem: 33408 +Epoch: [7] [2010/2639] eta: 0:31:45 lr: 4.117626187167549e-05 loss: 0.0981 (0.1025) time: 3.0276 data: 0.0080 max mem: 33408 +Epoch: [7] [2020/2639] eta: 0:31:15 lr: 4.117190590130886e-05 loss: 0.0888 (0.1025) time: 3.0275 data: 0.0078 max mem: 33408 +Epoch: [7] [2030/2639] eta: 0:30:45 lr: 4.116754987973498e-05 loss: 0.0888 (0.1026) time: 3.0293 data: 0.0079 max mem: 33408 +Epoch: [7] [2040/2639] eta: 0:30:14 lr: 4.116319380694723e-05 loss: 0.0885 (0.1026) time: 3.0213 data: 0.0079 max mem: 33408 +Epoch: [7] [2050/2639] eta: 0:29:44 lr: 4.115883768293897e-05 loss: 0.0874 (0.1025) time: 3.0380 data: 0.0076 max mem: 33408 +Epoch: [7] [2060/2639] eta: 0:29:14 lr: 4.11544815077036e-05 loss: 0.0856 (0.1025) time: 3.0511 data: 0.0076 max mem: 33408 +Epoch: [7] [2070/2639] eta: 0:28:43 lr: 4.1150125281234474e-05 loss: 0.0803 (0.1024) time: 3.0109 data: 0.0080 max mem: 33408 +Epoch: [7] [2080/2639] eta: 0:28:13 lr: 4.1145769003524975e-05 loss: 0.0807 (0.1023) time: 3.0237 data: 0.0081 max mem: 33408 +Epoch: [7] [2090/2639] eta: 0:27:43 lr: 4.1141412674568466e-05 loss: 0.0913 (0.1023) time: 3.0310 data: 0.0079 max mem: 33408 +Epoch: [7] [2100/2639] eta: 0:27:13 lr: 4.1137056294358304e-05 loss: 0.0955 (0.1023) time: 3.0236 data: 0.0075 max mem: 33408 +Epoch: [7] [2110/2639] eta: 0:26:42 lr: 4.113269986288788e-05 loss: 0.0866 (0.1023) time: 3.0160 data: 0.0076 max mem: 33408 +Epoch: [7] [2120/2639] eta: 0:26:12 lr: 4.1128343380150536e-05 loss: 0.0873 (0.1023) time: 3.0516 data: 0.0078 max mem: 33408 +Epoch: [7] [2130/2639] eta: 0:25:42 lr: 4.112398684613964e-05 loss: 0.1024 (0.1024) time: 3.0175 data: 0.0080 max mem: 33408 +Epoch: [7] [2140/2639] eta: 0:25:11 lr: 4.1119630260848554e-05 loss: 0.0969 (0.1024) time: 2.9956 data: 0.0077 max mem: 33408 +Epoch: [7] [2150/2639] eta: 0:24:41 lr: 4.111527362427064e-05 loss: 0.1000 (0.1024) time: 2.9965 data: 0.0078 max mem: 33408 +Epoch: [7] [2160/2639] eta: 0:24:10 lr: 4.111091693639927e-05 loss: 0.0959 (0.1024) time: 2.9759 data: 0.0077 max mem: 33408 +Epoch: [7] [2170/2639] eta: 0:23:40 lr: 4.1106560197227774e-05 loss: 0.0887 (0.1024) time: 2.9755 data: 0.0077 max mem: 33408 +Epoch: [7] [2180/2639] eta: 0:23:10 lr: 4.110220340674951e-05 loss: 0.0874 (0.1024) time: 3.0163 data: 0.0079 max mem: 33408 +Epoch: [7] [2190/2639] eta: 0:22:39 lr: 4.1097846564957854e-05 loss: 0.0847 (0.1024) time: 3.0275 data: 0.0077 max mem: 33408 +Epoch: [7] [2200/2639] eta: 0:22:09 lr: 4.1093489671846136e-05 loss: 0.0803 (0.1023) time: 3.0172 data: 0.0074 max mem: 33408 +Epoch: [7] [2210/2639] eta: 0:21:39 lr: 4.108913272740771e-05 loss: 0.0861 (0.1024) time: 3.0253 data: 0.0073 max mem: 33408 +Epoch: [7] [2220/2639] eta: 0:21:09 lr: 4.1084775731635925e-05 loss: 0.1044 (0.1024) time: 3.0157 data: 0.0073 max mem: 33408 +Epoch: [7] [2230/2639] eta: 0:20:38 lr: 4.1080418684524137e-05 loss: 0.0909 (0.1024) time: 3.0071 data: 0.0074 max mem: 33408 +Epoch: [7] [2240/2639] eta: 0:20:08 lr: 4.1076061586065665e-05 loss: 0.0890 (0.1023) time: 3.0237 data: 0.0074 max mem: 33408 +Epoch: [7] [2250/2639] eta: 0:19:38 lr: 4.1071704436253883e-05 loss: 0.0991 (0.1024) time: 3.0269 data: 0.0074 max mem: 33408 +Epoch: [7] [2260/2639] eta: 0:19:07 lr: 4.106734723508212e-05 loss: 0.0991 (0.1024) time: 3.0295 data: 0.0076 max mem: 33408 +Epoch: [7] [2270/2639] eta: 0:18:37 lr: 4.1062989982543704e-05 loss: 0.1000 (0.1024) time: 3.0196 data: 0.0077 max mem: 33408 +Epoch: [7] [2280/2639] eta: 0:18:07 lr: 4.1058632678631984e-05 loss: 0.1000 (0.1025) time: 2.9930 data: 0.0074 max mem: 33408 +Epoch: [7] [2290/2639] eta: 0:17:36 lr: 4.10542753233403e-05 loss: 0.0970 (0.1025) time: 3.0142 data: 0.0072 max mem: 33408 +Epoch: [7] [2300/2639] eta: 0:17:06 lr: 4.104991791666198e-05 loss: 0.0917 (0.1025) time: 3.0181 data: 0.0073 max mem: 33408 +Epoch: [7] [2310/2639] eta: 0:16:36 lr: 4.104556045859036e-05 loss: 0.0818 (0.1025) time: 3.0199 data: 0.0074 max mem: 33408 +Epoch: [7] [2320/2639] eta: 0:16:06 lr: 4.1041202949118776e-05 loss: 0.1050 (0.1025) time: 3.0430 data: 0.0076 max mem: 33408 +Epoch: [7] [2330/2639] eta: 0:15:35 lr: 4.103684538824055e-05 loss: 0.1054 (0.1025) time: 3.0334 data: 0.0073 max mem: 33408 +Epoch: [7] [2340/2639] eta: 0:15:05 lr: 4.1032487775949e-05 loss: 0.0859 (0.1025) time: 3.0050 data: 0.0072 max mem: 33408 +Epoch: [7] [2350/2639] eta: 0:14:35 lr: 4.102813011223748e-05 loss: 0.0875 (0.1025) time: 3.0198 data: 0.0074 max mem: 33408 +Epoch: [7] [2360/2639] eta: 0:14:04 lr: 4.10237723970993e-05 loss: 0.0941 (0.1026) time: 3.0651 data: 0.0071 max mem: 33408 +Epoch: [7] [2370/2639] eta: 0:13:34 lr: 4.101941463052778e-05 loss: 0.1017 (0.1027) time: 3.0569 data: 0.0076 max mem: 33408 +Epoch: [7] [2380/2639] eta: 0:13:04 lr: 4.101505681251624e-05 loss: 0.1017 (0.1027) time: 2.9667 data: 0.0076 max mem: 33408 +Epoch: [7] [2390/2639] eta: 0:12:33 lr: 4.101069894305801e-05 loss: 0.0943 (0.1027) time: 2.9758 data: 0.0071 max mem: 33408 +Epoch: [7] [2400/2639] eta: 0:12:03 lr: 4.100634102214641e-05 loss: 0.0881 (0.1027) time: 3.0111 data: 0.0073 max mem: 33408 +Epoch: [7] [2410/2639] eta: 0:11:33 lr: 4.100198304977474e-05 loss: 0.0809 (0.1026) time: 3.0080 data: 0.0075 max mem: 33408 +Epoch: [7] [2420/2639] eta: 0:11:03 lr: 4.099762502593633e-05 loss: 0.1009 (0.1027) time: 3.0188 data: 0.0077 max mem: 33408 +Epoch: [7] [2430/2639] eta: 0:10:32 lr: 4.099326695062448e-05 loss: 0.1190 (0.1028) time: 3.0620 data: 0.0076 max mem: 33408 +Epoch: [7] [2440/2639] eta: 0:10:02 lr: 4.098890882383252e-05 loss: 0.0898 (0.1028) time: 3.0679 data: 0.0074 max mem: 33408 +Epoch: [7] [2450/2639] eta: 0:09:32 lr: 4.0984550645553744e-05 loss: 0.0764 (0.1027) time: 3.0477 data: 0.0073 max mem: 33408 +Epoch: [7] [2460/2639] eta: 0:09:02 lr: 4.0980192415781466e-05 loss: 0.0933 (0.1028) time: 3.0253 data: 0.0077 max mem: 33408 +Epoch: [7] [2470/2639] eta: 0:08:31 lr: 4.097583413450899e-05 loss: 0.0955 (0.1029) time: 3.0422 data: 0.0076 max mem: 33408 +Epoch: [7] [2480/2639] eta: 0:08:01 lr: 4.097147580172963e-05 loss: 0.0955 (0.1028) time: 3.0862 data: 0.0074 max mem: 33408 +Epoch: [7] [2490/2639] eta: 0:07:31 lr: 4.096711741743668e-05 loss: 0.0709 (0.1028) time: 3.0401 data: 0.0077 max mem: 33408 +Epoch: [7] [2500/2639] eta: 0:07:00 lr: 4.096275898162345e-05 loss: 0.0723 (0.1028) time: 3.0234 data: 0.0074 max mem: 33408 +Epoch: [7] [2510/2639] eta: 0:06:30 lr: 4.095840049428323e-05 loss: 0.1047 (0.1028) time: 3.0110 data: 0.0070 max mem: 33408 +Epoch: [7] [2520/2639] eta: 0:06:00 lr: 4.095404195540932e-05 loss: 0.0992 (0.1027) time: 3.0166 data: 0.0072 max mem: 33408 +Epoch: [7] [2530/2639] eta: 0:05:30 lr: 4.094968336499502e-05 loss: 0.0879 (0.1027) time: 3.0203 data: 0.0078 max mem: 33408 +Epoch: [7] [2540/2639] eta: 0:04:59 lr: 4.094532472303363e-05 loss: 0.0879 (0.1027) time: 3.0211 data: 0.0081 max mem: 33408 +Epoch: [7] [2550/2639] eta: 0:04:29 lr: 4.0940966029518434e-05 loss: 0.0928 (0.1028) time: 3.0200 data: 0.0077 max mem: 33408 +Epoch: [7] [2560/2639] eta: 0:03:59 lr: 4.0936607284442726e-05 loss: 0.1002 (0.1028) time: 3.0214 data: 0.0074 max mem: 33408 +Epoch: [7] [2570/2639] eta: 0:03:28 lr: 4.09322484877998e-05 loss: 0.0999 (0.1028) time: 3.0242 data: 0.0072 max mem: 33408 +Epoch: [7] [2580/2639] eta: 0:02:58 lr: 4.0927889639582945e-05 loss: 0.0976 (0.1028) time: 2.9635 data: 0.0073 max mem: 33408 +Epoch: [7] [2590/2639] eta: 0:02:28 lr: 4.0923530739785434e-05 loss: 0.1030 (0.1029) time: 2.9576 data: 0.0077 max mem: 33408 +Epoch: [7] [2600/2639] eta: 0:01:58 lr: 4.0919171788400575e-05 loss: 0.1197 (0.1029) time: 2.9870 data: 0.0076 max mem: 33408 +Epoch: [7] [2610/2639] eta: 0:01:27 lr: 4.091481278542164e-05 loss: 0.1009 (0.1029) time: 2.9668 data: 0.0078 max mem: 33408 +Epoch: [7] [2620/2639] eta: 0:00:57 lr: 4.09104537308419e-05 loss: 0.0932 (0.1029) time: 3.0201 data: 0.0077 max mem: 33408 +Epoch: [7] [2630/2639] eta: 0:00:27 lr: 4.0906094624654654e-05 loss: 0.1019 (0.1030) time: 3.0486 data: 0.0075 max mem: 33408 +Epoch: [7] Total time: 2:13:09 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 2:08:12 time: 2.9897 data: 2.8781 max mem: 33408 +Test: [ 100/2573] eta: 0:04:25 time: 0.0777 data: 0.0014 max mem: 33408 +Test: [ 200/2573] eta: 0:03:42 time: 0.0803 data: 0.0014 max mem: 33408 +Test: [ 300/2573] eta: 0:03:21 time: 0.0818 data: 0.0014 max mem: 33408 +Test: [ 400/2573] eta: 0:03:08 time: 0.0823 data: 0.0013 max mem: 33408 +Test: [ 500/2573] eta: 0:02:57 time: 0.0800 data: 0.0015 max mem: 33408 +Test: [ 600/2573] eta: 0:02:47 time: 0.0807 data: 0.0015 max mem: 33408 +Test: [ 700/2573] eta: 0:02:38 time: 0.0802 data: 0.0015 max mem: 33408 +Test: [ 800/2573] eta: 0:02:29 time: 0.0824 data: 0.0013 max mem: 33408 +Test: [ 900/2573] eta: 0:02:20 time: 0.0812 data: 0.0014 max mem: 33408 +Test: [1000/2573] eta: 0:02:11 time: 0.0826 data: 0.0016 max mem: 33408 +Test: [1100/2573] eta: 0:02:02 time: 0.0803 data: 0.0015 max mem: 33408 +Test: [1200/2573] eta: 0:01:54 time: 0.0814 data: 0.0014 max mem: 33408 +Test: [1300/2573] eta: 0:01:45 time: 0.0801 data: 0.0014 max mem: 33408 +Test: [1400/2573] eta: 0:01:37 time: 0.0799 data: 0.0016 max mem: 33408 +Test: [1500/2573] eta: 0:01:28 time: 0.0802 data: 0.0015 max mem: 33408 +Test: [1600/2573] eta: 0:01:20 time: 0.0850 data: 0.0014 max mem: 33408 +Test: [1700/2573] eta: 0:01:12 time: 0.0790 data: 0.0013 max mem: 33408 +Test: [1800/2573] eta: 0:01:03 time: 0.0819 data: 0.0014 max mem: 33408 +Test: [1900/2573] eta: 0:00:55 time: 0.0797 data: 0.0014 max mem: 33408 +Test: [2000/2573] eta: 0:00:47 time: 0.0807 data: 0.0014 max mem: 33408 +Test: [2100/2573] eta: 0:00:38 time: 0.0827 data: 0.0014 max mem: 33408 +Test: [2200/2573] eta: 0:00:30 time: 0.0818 data: 0.0014 max mem: 33408 +Test: [2300/2573] eta: 0:00:22 time: 0.0819 data: 0.0014 max mem: 33408 +Test: [2400/2573] eta: 0:00:14 time: 0.0779 data: 0.0013 max mem: 33408 +Test: [2500/2573] eta: 0:00:05 time: 0.0812 data: 0.0015 max mem: 33408 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: Total time: 0:03:32 +Final results: +Mean IoU is 56.52 + + precision@0.5 = 63.19 + precision@0.6 = 56.50 + precision@0.7 = 48.71 + precision@0.8 = 36.97 + precision@0.9 = 16.44 + overall IoU = 57.30 + +Average object IoU 56.51857552776883 +Overall IoU 57.29549789428711 +Better epoch: 7 + +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [8] [ 0/2639] eta: 4:04:32 lr: 4.090217138495614e-05 loss: 0.1339 (0.1339) time: 5.5599 data: 2.4742 max mem: 33408 +Epoch: [8] [ 10/2639] eta: 2:21:17 lr: 4.0897812180696095e-05 loss: 0.0825 (0.0845) time: 3.2247 data: 0.2321 max mem: 33408 +Epoch: [8] [ 20/2639] eta: 2:16:11 lr: 4.089345292480903e-05 loss: 0.0825 (0.0873) time: 2.9982 data: 0.0077 max mem: 33408 +Epoch: [8] [ 30/2639] eta: 2:13:58 lr: 4.088909361728822e-05 loss: 0.0818 (0.0867) time: 3.0023 data: 0.0077 max mem: 33408 +Epoch: [8] [ 40/2639] eta: 2:12:48 lr: 4.088473425812695e-05 loss: 0.0878 (0.0940) time: 3.0087 data: 0.0079 max mem: 33408 +Epoch: [8] [ 50/2639] eta: 2:11:28 lr: 4.088037484731849e-05 loss: 0.0964 (0.0955) time: 2.9936 data: 0.0081 max mem: 33408 +Epoch: [8] [ 60/2639] eta: 2:10:26 lr: 4.0876015384856095e-05 loss: 0.0852 (0.0939) time: 2.9710 data: 0.0080 max mem: 33408 +Epoch: [8] [ 70/2639] eta: 2:09:31 lr: 4.0871655870733025e-05 loss: 0.0861 (0.0933) time: 2.9693 data: 0.0079 max mem: 33408 +Epoch: [8] [ 80/2639] eta: 2:08:44 lr: 4.086729630494258e-05 loss: 0.0815 (0.0932) time: 2.9694 data: 0.0081 max mem: 33408 +Epoch: [8] [ 90/2639] eta: 2:07:54 lr: 4.0862936687477984e-05 loss: 0.0794 (0.0932) time: 2.9597 data: 0.0078 max mem: 33408 +Epoch: [8] [ 100/2639] eta: 2:07:26 lr: 4.085857701833252e-05 loss: 0.0801 (0.0925) time: 2.9838 data: 0.0080 max mem: 33408 +Epoch: [8] [ 110/2639] eta: 2:07:03 lr: 4.0854217297499444e-05 loss: 0.0845 (0.0927) time: 3.0309 data: 0.0082 max mem: 33408 +Epoch: [8] [ 120/2639] eta: 2:06:31 lr: 4.0849857524972026e-05 loss: 0.0995 (0.0951) time: 3.0235 data: 0.0079 max mem: 33408 +Epoch: [8] [ 130/2639] eta: 2:06:05 lr: 4.08454977007435e-05 loss: 0.0951 (0.0947) time: 3.0205 data: 0.0081 max mem: 33408 +Epoch: [8] [ 140/2639] eta: 2:05:37 lr: 4.0841137824807134e-05 loss: 0.0869 (0.0946) time: 3.0322 data: 0.0082 max mem: 33408 +Epoch: [8] [ 150/2639] eta: 2:05:06 lr: 4.083677789715618e-05 loss: 0.0804 (0.0954) time: 3.0192 data: 0.0083 max mem: 33408 +Epoch: [8] [ 160/2639] eta: 2:04:40 lr: 4.083241791778389e-05 loss: 0.0804 (0.0949) time: 3.0249 data: 0.0082 max mem: 33408 +Epoch: [8] [ 170/2639] eta: 2:04:06 lr: 4.0828057886683514e-05 loss: 0.0908 (0.0960) time: 3.0161 data: 0.0081 max mem: 33408 +Epoch: [8] [ 180/2639] eta: 2:03:48 lr: 4.08236978038483e-05 loss: 0.0901 (0.0955) time: 3.0516 data: 0.0085 max mem: 33408 +Epoch: [8] [ 190/2639] eta: 2:03:24 lr: 4.081933766927149e-05 loss: 0.0917 (0.0958) time: 3.0905 data: 0.0085 max mem: 33408 +Epoch: [8] [ 200/2639] eta: 2:02:45 lr: 4.0814977482946337e-05 loss: 0.0950 (0.0952) time: 3.0103 data: 0.0086 max mem: 33408 +Epoch: [8] [ 210/2639] eta: 2:02:18 lr: 4.081061724486607e-05 loss: 0.0886 (0.0950) time: 2.9980 data: 0.0085 max mem: 33408 +Epoch: [8] [ 220/2639] eta: 2:01:44 lr: 4.080625695502396e-05 loss: 0.0866 (0.0945) time: 3.0172 data: 0.0080 max mem: 33408 +Epoch: [8] [ 230/2639] eta: 2:01:07 lr: 4.080189661341321e-05 loss: 0.0721 (0.0941) time: 2.9725 data: 0.0081 max mem: 33408 +Epoch: [8] [ 240/2639] eta: 2:00:38 lr: 4.079753622002708e-05 loss: 0.0843 (0.0938) time: 2.9918 data: 0.0083 max mem: 33408 +Epoch: [8] [ 250/2639] eta: 2:00:05 lr: 4.079317577485881e-05 loss: 0.0908 (0.0942) time: 3.0064 data: 0.0079 max mem: 33408 +Epoch: [8] [ 260/2639] eta: 1:59:36 lr: 4.078881527790163e-05 loss: 0.1023 (0.0962) time: 3.0081 data: 0.0078 max mem: 33408 +Epoch: [8] [ 270/2639] eta: 1:59:05 lr: 4.0784454729148766e-05 loss: 0.1087 (0.0965) time: 3.0169 data: 0.0080 max mem: 33408 +Epoch: [8] [ 280/2639] eta: 1:58:43 lr: 4.078009412859344e-05 loss: 0.0784 (0.0959) time: 3.0592 data: 0.0079 max mem: 33408 +Epoch: [8] [ 290/2639] eta: 1:58:12 lr: 4.077573347622892e-05 loss: 0.0784 (0.0962) time: 3.0631 data: 0.0078 max mem: 33408 +Epoch: [8] [ 300/2639] eta: 1:57:44 lr: 4.077137277204839e-05 loss: 0.0829 (0.0966) time: 3.0302 data: 0.0078 max mem: 33408 +Epoch: [8] [ 310/2639] eta: 1:57:11 lr: 4.0767012016045105e-05 loss: 0.0857 (0.0966) time: 3.0177 data: 0.0079 max mem: 33408 +Epoch: [8] [ 320/2639] eta: 1:56:46 lr: 4.076265120821228e-05 loss: 0.0982 (0.0968) time: 3.0372 data: 0.0081 max mem: 33408 +Epoch: [8] [ 330/2639] eta: 1:56:16 lr: 4.0758290348543146e-05 loss: 0.0897 (0.0962) time: 3.0575 data: 0.0084 max mem: 33408 +Epoch: [8] [ 340/2639] eta: 1:55:47 lr: 4.07539294370309e-05 loss: 0.0733 (0.0957) time: 3.0273 data: 0.0080 max mem: 33408 +Epoch: [8] [ 350/2639] eta: 1:55:14 lr: 4.07495684736688e-05 loss: 0.0832 (0.0963) time: 3.0099 data: 0.0076 max mem: 33408 +Epoch: [8] [ 360/2639] eta: 1:54:45 lr: 4.074520745845003e-05 loss: 0.0937 (0.0965) time: 3.0132 data: 0.0073 max mem: 33408 +Epoch: [8] [ 370/2639] eta: 1:54:19 lr: 4.074084639136782e-05 loss: 0.0946 (0.0971) time: 3.0616 data: 0.0073 max mem: 33408 +Epoch: [8] [ 380/2639] eta: 1:53:46 lr: 4.073648527241538e-05 loss: 0.0821 (0.0968) time: 3.0280 data: 0.0078 max mem: 33408 +Epoch: [8] [ 390/2639] eta: 1:53:19 lr: 4.073212410158593e-05 loss: 0.0748 (0.0964) time: 3.0291 data: 0.0079 max mem: 33408 +Epoch: [8] [ 400/2639] eta: 1:52:48 lr: 4.072776287887268e-05 loss: 0.0804 (0.0964) time: 3.0472 data: 0.0084 max mem: 33408 +Epoch: [8] [ 410/2639] eta: 1:52:22 lr: 4.072340160426884e-05 loss: 0.0986 (0.0965) time: 3.0566 data: 0.0082 max mem: 33408 +Epoch: [8] [ 420/2639] eta: 1:51:58 lr: 4.0719040277767606e-05 loss: 0.0847 (0.0961) time: 3.1196 data: 0.0073 max mem: 33408 +Epoch: [8] [ 430/2639] eta: 1:51:23 lr: 4.07146788993622e-05 loss: 0.0725 (0.0958) time: 3.0412 data: 0.0078 max mem: 33408 +Epoch: [8] [ 440/2639] eta: 1:50:51 lr: 4.071031746904581e-05 loss: 0.0703 (0.0952) time: 2.9681 data: 0.0080 max mem: 33408 +Epoch: [8] [ 450/2639] eta: 1:50:21 lr: 4.070595598681166e-05 loss: 0.0755 (0.0953) time: 3.0020 data: 0.0080 max mem: 33408 +Epoch: [8] [ 460/2639] eta: 1:49:53 lr: 4.070159445265293e-05 loss: 0.0892 (0.0954) time: 3.0528 data: 0.0082 max mem: 33408 +Epoch: [8] [ 470/2639] eta: 1:49:20 lr: 4.069723286656283e-05 loss: 0.0811 (0.0951) time: 3.0225 data: 0.0080 max mem: 33408 +Epoch: [8] [ 480/2639] eta: 1:48:53 lr: 4.0692871228534556e-05 loss: 0.0836 (0.0955) time: 3.0297 data: 0.0077 max mem: 33408 +Epoch: [8] [ 490/2639] eta: 1:48:22 lr: 4.06885095385613e-05 loss: 0.0982 (0.0955) time: 3.0550 data: 0.0076 max mem: 33408 +Epoch: [8] [ 500/2639] eta: 1:47:52 lr: 4.068414779663627e-05 loss: 0.0903 (0.0953) time: 3.0165 data: 0.0075 max mem: 33408 +Epoch: [8] [ 510/2639] eta: 1:47:20 lr: 4.0679786002752645e-05 loss: 0.0933 (0.0956) time: 3.0067 data: 0.0075 max mem: 33408 +Epoch: [8] [ 520/2639] eta: 1:46:51 lr: 4.067542415690361e-05 loss: 0.0972 (0.0957) time: 3.0282 data: 0.0078 max mem: 33408 +Epoch: [8] [ 530/2639] eta: 1:46:19 lr: 4.067106225908237e-05 loss: 0.0978 (0.0960) time: 3.0208 data: 0.0079 max mem: 33408 +Epoch: [8] [ 540/2639] eta: 1:45:53 lr: 4.066670030928211e-05 loss: 0.0959 (0.0961) time: 3.0485 data: 0.0077 max mem: 33408 +Epoch: [8] [ 550/2639] eta: 1:45:24 lr: 4.0662338307496e-05 loss: 0.0841 (0.0961) time: 3.1012 data: 0.0075 max mem: 33408 +Epoch: [8] [ 560/2639] eta: 1:44:54 lr: 4.065797625371724e-05 loss: 0.0863 (0.0960) time: 3.0537 data: 0.0080 max mem: 33408 +Epoch: [8] [ 570/2639] eta: 1:44:30 lr: 4.0653614147939e-05 loss: 0.0966 (0.0967) time: 3.1108 data: 0.0083 max mem: 33408 +Epoch: [8] [ 580/2639] eta: 1:43:57 lr: 4.064925199015448e-05 loss: 0.1034 (0.0967) time: 3.0749 data: 0.0080 max mem: 33408 +Epoch: [8] [ 590/2639] eta: 1:43:26 lr: 4.0644889780356836e-05 loss: 0.0888 (0.0968) time: 2.9837 data: 0.0078 max mem: 33408 +Epoch: [8] [ 600/2639] eta: 1:42:56 lr: 4.0640527518539264e-05 loss: 0.0857 (0.0968) time: 3.0175 data: 0.0080 max mem: 33408 +Epoch: [8] [ 610/2639] eta: 1:42:24 lr: 4.0636165204694924e-05 loss: 0.0857 (0.0968) time: 3.0099 data: 0.0076 max mem: 33408 +Epoch: [8] [ 620/2639] eta: 1:41:56 lr: 4.0631802838817004e-05 loss: 0.0770 (0.0967) time: 3.0393 data: 0.0076 max mem: 33408 +Epoch: [8] [ 630/2639] eta: 1:41:24 lr: 4.062744042089866e-05 loss: 0.0770 (0.0965) time: 3.0360 data: 0.0078 max mem: 33408 +Epoch: [8] [ 640/2639] eta: 1:40:57 lr: 4.0623077950933076e-05 loss: 0.0815 (0.0965) time: 3.0613 data: 0.0076 max mem: 33408 +Epoch: [8] [ 650/2639] eta: 1:40:26 lr: 4.0618715428913414e-05 loss: 0.0801 (0.0962) time: 3.0768 data: 0.0078 max mem: 33408 +Epoch: [8] [ 660/2639] eta: 1:39:56 lr: 4.0614352854832844e-05 loss: 0.0867 (0.0962) time: 3.0292 data: 0.0079 max mem: 33408 +Epoch: [8] [ 670/2639] eta: 1:39:26 lr: 4.060999022868452e-05 loss: 0.0963 (0.0964) time: 3.0332 data: 0.0077 max mem: 33408 +Epoch: [8] [ 680/2639] eta: 1:38:55 lr: 4.060562755046163e-05 loss: 0.0886 (0.0964) time: 3.0186 data: 0.0077 max mem: 33408 +Epoch: [8] [ 690/2639] eta: 1:38:25 lr: 4.060126482015731e-05 loss: 0.0988 (0.0964) time: 3.0139 data: 0.0080 max mem: 33408 +Epoch: [8] [ 700/2639] eta: 1:37:53 lr: 4.059690203776474e-05 loss: 0.0988 (0.0965) time: 2.9988 data: 0.0079 max mem: 33408 +Epoch: [8] [ 710/2639] eta: 1:37:24 lr: 4.059253920327705e-05 loss: 0.0899 (0.0967) time: 3.0282 data: 0.0078 max mem: 33408 +Epoch: [8] [ 720/2639] eta: 1:36:55 lr: 4.058817631668743e-05 loss: 0.0961 (0.0972) time: 3.0792 data: 0.0077 max mem: 33408 +Epoch: [8] [ 730/2639] eta: 1:36:24 lr: 4.058381337798901e-05 loss: 0.0972 (0.0972) time: 3.0489 data: 0.0079 max mem: 33408 +Epoch: [8] [ 740/2639] eta: 1:35:57 lr: 4.057945038717496e-05 loss: 0.0929 (0.0972) time: 3.0750 data: 0.0079 max mem: 33408 +Epoch: [8] [ 750/2639] eta: 1:35:27 lr: 4.057508734423843e-05 loss: 0.0892 (0.0972) time: 3.1002 data: 0.0082 max mem: 33408 +Epoch: [8] [ 760/2639] eta: 1:34:56 lr: 4.057072424917256e-05 loss: 0.0797 (0.0970) time: 3.0376 data: 0.0080 max mem: 33408 +Epoch: [8] [ 770/2639] eta: 1:34:24 lr: 4.05663611019705e-05 loss: 0.0735 (0.0970) time: 2.9788 data: 0.0076 max mem: 33408 +Epoch: [8] [ 780/2639] eta: 1:33:55 lr: 4.05619979026254e-05 loss: 0.0936 (0.0971) time: 3.0237 data: 0.0080 max mem: 33408 +Epoch: [8] [ 790/2639] eta: 1:33:24 lr: 4.055763465113041e-05 loss: 0.0866 (0.0970) time: 3.0364 data: 0.0081 max mem: 33408 +Epoch: [8] [ 800/2639] eta: 1:32:54 lr: 4.0553271347478655e-05 loss: 0.0866 (0.0971) time: 3.0274 data: 0.0080 max mem: 33408 +Epoch: [8] [ 810/2639] eta: 1:32:22 lr: 4.054890799166329e-05 loss: 0.0873 (0.0970) time: 3.0153 data: 0.0079 max mem: 33408 +Epoch: [8] [ 820/2639] eta: 1:31:52 lr: 4.0544544583677446e-05 loss: 0.0789 (0.0969) time: 2.9978 data: 0.0081 max mem: 33408 +Epoch: [8] [ 830/2639] eta: 1:31:22 lr: 4.054018112351427e-05 loss: 0.0789 (0.0967) time: 3.0287 data: 0.0082 max mem: 33408 +Epoch: [8] [ 840/2639] eta: 1:30:51 lr: 4.05358176111669e-05 loss: 0.0914 (0.0969) time: 3.0251 data: 0.0081 max mem: 33408 +Epoch: [8] [ 850/2639] eta: 1:30:21 lr: 4.0531454046628456e-05 loss: 0.1026 (0.0969) time: 3.0369 data: 0.0081 max mem: 33408 +Epoch: [8] [ 860/2639] eta: 1:29:52 lr: 4.0527090429892083e-05 loss: 0.0880 (0.0967) time: 3.0684 data: 0.0077 max mem: 33408 +Epoch: [8] [ 870/2639] eta: 1:29:21 lr: 4.052272676095091e-05 loss: 0.0819 (0.0966) time: 3.0402 data: 0.0076 max mem: 33408 +Epoch: [8] [ 880/2639] eta: 1:28:51 lr: 4.0518363039798053e-05 loss: 0.0909 (0.0967) time: 3.0049 data: 0.0076 max mem: 33408 +Epoch: [8] [ 890/2639] eta: 1:28:20 lr: 4.051399926642666e-05 loss: 0.0950 (0.0966) time: 3.0176 data: 0.0075 max mem: 33408 +Epoch: [8] [ 900/2639] eta: 1:27:51 lr: 4.050963544082984e-05 loss: 0.0741 (0.0965) time: 3.0523 data: 0.0076 max mem: 33408 +Epoch: [8] [ 910/2639] eta: 1:27:21 lr: 4.0505271563000724e-05 loss: 0.0753 (0.0964) time: 3.0772 data: 0.0077 max mem: 33408 +Epoch: [8] [ 920/2639] eta: 1:26:51 lr: 4.050090763293243e-05 loss: 0.0753 (0.0962) time: 3.0518 data: 0.0077 max mem: 33408 +Epoch: [8] [ 930/2639] eta: 1:26:21 lr: 4.049654365061809e-05 loss: 0.0835 (0.0963) time: 3.0509 data: 0.0077 max mem: 33408 +Epoch: [8] [ 940/2639] eta: 1:25:50 lr: 4.0492179616050804e-05 loss: 0.1037 (0.0963) time: 3.0306 data: 0.0080 max mem: 33408 +Epoch: [8] [ 950/2639] eta: 1:25:20 lr: 4.04878155292237e-05 loss: 0.0854 (0.0962) time: 3.0120 data: 0.0079 max mem: 33408 +Epoch: [8] [ 960/2639] eta: 1:24:50 lr: 4.04834513901299e-05 loss: 0.0886 (0.0962) time: 3.0346 data: 0.0076 max mem: 33408 +Epoch: [8] [ 970/2639] eta: 1:24:19 lr: 4.0479087198762516e-05 loss: 0.0861 (0.0961) time: 3.0341 data: 0.0078 max mem: 33408 +Epoch: [8] [ 980/2639] eta: 1:23:50 lr: 4.0474722955114643e-05 loss: 0.0843 (0.0960) time: 3.0676 data: 0.0081 max mem: 33408 +Epoch: [8] [ 990/2639] eta: 1:23:20 lr: 4.04703586591794e-05 loss: 0.0775 (0.0960) time: 3.0649 data: 0.0079 max mem: 33408 +Epoch: [8] [1000/2639] eta: 1:22:50 lr: 4.046599431094989e-05 loss: 0.0775 (0.0960) time: 3.0287 data: 0.0077 max mem: 33408 +Epoch: [8] [1010/2639] eta: 1:22:19 lr: 4.046162991041924e-05 loss: 0.0781 (0.0959) time: 3.0289 data: 0.0080 max mem: 33408 +Epoch: [8] [1020/2639] eta: 1:21:48 lr: 4.0457265457580534e-05 loss: 0.0815 (0.0960) time: 3.0090 data: 0.0082 max mem: 33408 +Epoch: [8] [1030/2639] eta: 1:21:19 lr: 4.045290095242688e-05 loss: 0.0881 (0.0959) time: 3.0525 data: 0.0083 max mem: 33408 +Epoch: [8] [1040/2639] eta: 1:20:48 lr: 4.0448536394951395e-05 loss: 0.0881 (0.0960) time: 3.0522 data: 0.0079 max mem: 33408 +Epoch: [8] [1050/2639] eta: 1:20:19 lr: 4.044417178514715e-05 loss: 0.0938 (0.0959) time: 3.0436 data: 0.0077 max mem: 33408 +Epoch: [8] [1060/2639] eta: 1:19:48 lr: 4.043980712300726e-05 loss: 0.0892 (0.0958) time: 3.0473 data: 0.0080 max mem: 33408 +Epoch: [8] [1070/2639] eta: 1:19:18 lr: 4.043544240852482e-05 loss: 0.0860 (0.0960) time: 3.0266 data: 0.0079 max mem: 33408 +Epoch: [8] [1080/2639] eta: 1:18:48 lr: 4.043107764169292e-05 loss: 0.0860 (0.0962) time: 3.0614 data: 0.0078 max mem: 33408 +Epoch: [8] [1090/2639] eta: 1:18:17 lr: 4.042671282250466e-05 loss: 0.0830 (0.0961) time: 3.0265 data: 0.0082 max mem: 33408 +Epoch: [8] [1100/2639] eta: 1:17:48 lr: 4.042234795095313e-05 loss: 0.0808 (0.0959) time: 3.0573 data: 0.0084 max mem: 33408 +Epoch: [8] [1110/2639] eta: 1:17:17 lr: 4.041798302703141e-05 loss: 0.0731 (0.0959) time: 3.0721 data: 0.0082 max mem: 33408 +Epoch: [8] [1120/2639] eta: 1:16:47 lr: 4.0413618050732596e-05 loss: 0.0878 (0.0959) time: 3.0097 data: 0.0080 max mem: 33408 +Epoch: [8] [1130/2639] eta: 1:16:16 lr: 4.040925302204976e-05 loss: 0.0979 (0.0959) time: 3.0092 data: 0.0080 max mem: 33408 +Epoch: [8] [1140/2639] eta: 1:15:47 lr: 4.040488794097602e-05 loss: 0.0865 (0.0959) time: 3.0464 data: 0.0078 max mem: 33408 +Epoch: [8] [1150/2639] eta: 1:15:16 lr: 4.0400522807504414e-05 loss: 0.0860 (0.0959) time: 3.0547 data: 0.0075 max mem: 33408 +Epoch: [8] [1160/2639] eta: 1:14:45 lr: 4.0396157621628055e-05 loss: 0.0955 (0.0961) time: 3.0140 data: 0.0073 max mem: 33408 +Epoch: [8] [1170/2639] eta: 1:14:15 lr: 4.039179238334e-05 loss: 0.0946 (0.0960) time: 3.0211 data: 0.0075 max mem: 33408 +Epoch: [8] [1180/2639] eta: 1:13:44 lr: 4.0387427092633345e-05 loss: 0.0836 (0.0959) time: 3.0185 data: 0.0075 max mem: 33408 +Epoch: [8] [1190/2639] eta: 1:13:14 lr: 4.038306174950115e-05 loss: 0.0721 (0.0959) time: 3.0124 data: 0.0074 max mem: 33408 +Epoch: [8] [1200/2639] eta: 1:12:44 lr: 4.0378696353936494e-05 loss: 0.0704 (0.0958) time: 3.0531 data: 0.0079 max mem: 33408 +Epoch: [8] [1210/2639] eta: 1:12:14 lr: 4.037433090593245e-05 loss: 0.0789 (0.0959) time: 3.0708 data: 0.0078 max mem: 33408 +Epoch: [8] [1220/2639] eta: 1:11:44 lr: 4.03699654054821e-05 loss: 0.0986 (0.0959) time: 3.0318 data: 0.0073 max mem: 33408 +Epoch: [8] [1230/2639] eta: 1:11:13 lr: 4.036559985257848e-05 loss: 0.0976 (0.0960) time: 3.0131 data: 0.0074 max mem: 33408 +Epoch: [8] [1240/2639] eta: 1:10:43 lr: 4.0361234247214686e-05 loss: 0.0935 (0.0960) time: 3.0270 data: 0.0077 max mem: 33408 +Epoch: [8] [1250/2639] eta: 1:10:12 lr: 4.035686858938377e-05 loss: 0.0907 (0.0960) time: 3.0184 data: 0.0080 max mem: 33408 +Epoch: [8] [1260/2639] eta: 1:09:42 lr: 4.035250287907881e-05 loss: 0.0805 (0.0959) time: 3.0115 data: 0.0078 max mem: 33408 +Epoch: [8] [1270/2639] eta: 1:09:11 lr: 4.034813711629284e-05 loss: 0.0845 (0.0960) time: 3.0098 data: 0.0076 max mem: 33408 +Epoch: [8] [1280/2639] eta: 1:08:41 lr: 4.0343771301018934e-05 loss: 0.0976 (0.0960) time: 3.0207 data: 0.0077 max mem: 33408 +Epoch: [8] [1290/2639] eta: 1:08:10 lr: 4.033940543325015e-05 loss: 0.0960 (0.0961) time: 3.0132 data: 0.0077 max mem: 33408 +Epoch: [8] [1300/2639] eta: 1:07:39 lr: 4.033503951297956e-05 loss: 0.0928 (0.0961) time: 3.0022 data: 0.0077 max mem: 33408 +Epoch: [8] [1310/2639] eta: 1:07:09 lr: 4.0330673540200184e-05 loss: 0.0928 (0.0961) time: 3.0175 data: 0.0078 max mem: 33408 +Epoch: [8] [1320/2639] eta: 1:06:39 lr: 4.0326307514905094e-05 loss: 0.0931 (0.0962) time: 3.0212 data: 0.0077 max mem: 33408 +Epoch: [8] [1330/2639] eta: 1:06:08 lr: 4.032194143708734e-05 loss: 0.0889 (0.0962) time: 3.0035 data: 0.0075 max mem: 33408 +Epoch: [8] [1340/2639] eta: 1:05:38 lr: 4.031757530673997e-05 loss: 0.0972 (0.0963) time: 3.0282 data: 0.0073 max mem: 33408 +Epoch: [8] [1350/2639] eta: 1:05:07 lr: 4.031320912385604e-05 loss: 0.0909 (0.0962) time: 3.0448 data: 0.0075 max mem: 33408 +Epoch: [8] [1360/2639] eta: 1:04:38 lr: 4.0308842888428577e-05 loss: 0.0859 (0.0961) time: 3.0586 data: 0.0076 max mem: 33408 +Epoch: [8] [1370/2639] eta: 1:04:07 lr: 4.030447660045064e-05 loss: 0.0732 (0.0961) time: 3.0483 data: 0.0081 max mem: 33408 +Epoch: [8] [1380/2639] eta: 1:03:37 lr: 4.030011025991526e-05 loss: 0.0732 (0.0959) time: 3.0021 data: 0.0084 max mem: 33408 +Epoch: [8] [1390/2639] eta: 1:03:06 lr: 4.029574386681549e-05 loss: 0.0725 (0.0958) time: 3.0053 data: 0.0074 max mem: 33408 +Epoch: [8] [1400/2639] eta: 1:02:36 lr: 4.029137742114435e-05 loss: 0.0725 (0.0958) time: 3.0278 data: 0.0072 max mem: 33408 +Epoch: [8] [1410/2639] eta: 1:02:05 lr: 4.0287010922894895e-05 loss: 0.0917 (0.0959) time: 3.0393 data: 0.0074 max mem: 33408 +Epoch: [8] [1420/2639] eta: 1:01:35 lr: 4.0282644372060144e-05 loss: 0.0807 (0.0958) time: 3.0310 data: 0.0073 max mem: 33408 +Epoch: [8] [1430/2639] eta: 1:01:05 lr: 4.027827776863315e-05 loss: 0.0807 (0.0958) time: 3.0420 data: 0.0072 max mem: 33408 +Epoch: [8] [1440/2639] eta: 1:00:34 lr: 4.027391111260693e-05 loss: 0.1077 (0.0960) time: 3.0250 data: 0.0070 max mem: 33408 +Epoch: [8] [1450/2639] eta: 1:00:04 lr: 4.026954440397451e-05 loss: 0.1054 (0.0960) time: 3.0194 data: 0.0074 max mem: 33408 +Epoch: [8] [1460/2639] eta: 0:59:33 lr: 4.0265177642728925e-05 loss: 0.0919 (0.0960) time: 3.0059 data: 0.0077 max mem: 33408 +Epoch: [8] [1470/2639] eta: 0:59:03 lr: 4.02608108288632e-05 loss: 0.0926 (0.0960) time: 3.0021 data: 0.0077 max mem: 33408 +Epoch: [8] [1480/2639] eta: 0:58:32 lr: 4.025644396237036e-05 loss: 0.0903 (0.0961) time: 3.0139 data: 0.0078 max mem: 33408 +Epoch: [8] [1490/2639] eta: 0:58:02 lr: 4.025207704324342e-05 loss: 0.0821 (0.0963) time: 2.9903 data: 0.0077 max mem: 33408 +Epoch: [8] [1500/2639] eta: 0:57:31 lr: 4.024771007147542e-05 loss: 0.0892 (0.0963) time: 2.9671 data: 0.0076 max mem: 33408 +Epoch: [8] [1510/2639] eta: 0:57:00 lr: 4.024334304705937e-05 loss: 0.0892 (0.0963) time: 2.9609 data: 0.0079 max mem: 33408 +Epoch: [8] [1520/2639] eta: 0:56:30 lr: 4.023897596998827e-05 loss: 0.0984 (0.0963) time: 2.9876 data: 0.0084 max mem: 33408 +Epoch: [8] [1530/2639] eta: 0:55:59 lr: 4.023460884025515e-05 loss: 0.0875 (0.0964) time: 3.0062 data: 0.0083 max mem: 33408 +Epoch: [8] [1540/2639] eta: 0:55:28 lr: 4.023024165785303e-05 loss: 0.0912 (0.0964) time: 2.9824 data: 0.0082 max mem: 33408 +Epoch: [8] [1550/2639] eta: 0:54:58 lr: 4.022587442277491e-05 loss: 0.0950 (0.0963) time: 2.9871 data: 0.0081 max mem: 33408 +Epoch: [8] [1560/2639] eta: 0:54:27 lr: 4.0221507135013806e-05 loss: 0.0847 (0.0963) time: 3.0002 data: 0.0080 max mem: 33408 +Epoch: [8] [1570/2639] eta: 0:53:58 lr: 4.0217139794562724e-05 loss: 0.0835 (0.0962) time: 3.0480 data: 0.0081 max mem: 33408 +Epoch: [8] [1580/2639] eta: 0:53:27 lr: 4.021277240141467e-05 loss: 0.0882 (0.0962) time: 3.0403 data: 0.0083 max mem: 33408 +Epoch: [8] [1590/2639] eta: 0:52:57 lr: 4.020840495556265e-05 loss: 0.0770 (0.0962) time: 3.0087 data: 0.0079 max mem: 33408 +Epoch: [8] [1600/2639] eta: 0:52:26 lr: 4.020403745699968e-05 loss: 0.0890 (0.0963) time: 3.0064 data: 0.0079 max mem: 33408 +Epoch: [8] [1610/2639] eta: 0:51:56 lr: 4.019966990571873e-05 loss: 0.1015 (0.0964) time: 3.0185 data: 0.0081 max mem: 33408 +Epoch: [8] [1620/2639] eta: 0:51:25 lr: 4.0195302301712834e-05 loss: 0.0890 (0.0964) time: 3.0219 data: 0.0081 max mem: 33408 +Epoch: [8] [1630/2639] eta: 0:50:55 lr: 4.019093464497497e-05 loss: 0.0851 (0.0963) time: 3.0183 data: 0.0085 max mem: 33408 +Epoch: [8] [1640/2639] eta: 0:50:25 lr: 4.018656693549813e-05 loss: 0.0799 (0.0963) time: 3.0093 data: 0.0083 max mem: 33408 +Epoch: [8] [1650/2639] eta: 0:49:55 lr: 4.018219917327532e-05 loss: 0.0856 (0.0964) time: 3.0450 data: 0.0081 max mem: 33408 +Epoch: [8] [1660/2639] eta: 0:49:24 lr: 4.0177831358299536e-05 loss: 0.0901 (0.0966) time: 3.0464 data: 0.0081 max mem: 33408 +Epoch: [8] [1670/2639] eta: 0:48:54 lr: 4.017346349056375e-05 loss: 0.1003 (0.0966) time: 2.9753 data: 0.0078 max mem: 33408 +Epoch: [8] [1680/2639] eta: 0:48:23 lr: 4.0169095570060974e-05 loss: 0.1056 (0.0968) time: 2.9698 data: 0.0077 max mem: 33408 +Epoch: [8] [1690/2639] eta: 0:47:53 lr: 4.016472759678417e-05 loss: 0.1036 (0.0967) time: 3.0310 data: 0.0078 max mem: 33408 +Epoch: [8] [1700/2639] eta: 0:47:23 lr: 4.016035957072634e-05 loss: 0.0874 (0.0967) time: 3.0906 data: 0.0080 max mem: 33408 +Epoch: [8] [1710/2639] eta: 0:46:53 lr: 4.015599149188047e-05 loss: 0.0933 (0.0968) time: 3.0237 data: 0.0081 max mem: 33408 +Epoch: [8] [1720/2639] eta: 0:46:22 lr: 4.0151623360239534e-05 loss: 0.0918 (0.0967) time: 3.0016 data: 0.0078 max mem: 33408 +Epoch: [8] [1730/2639] eta: 0:45:52 lr: 4.01472551757965e-05 loss: 0.0892 (0.0967) time: 3.0004 data: 0.0076 max mem: 33408 +Epoch: [8] [1740/2639] eta: 0:45:21 lr: 4.0142886938544374e-05 loss: 0.0949 (0.0967) time: 2.9711 data: 0.0077 max mem: 33408 +Epoch: [8] [1750/2639] eta: 0:44:51 lr: 4.0138518648476117e-05 loss: 0.0967 (0.0968) time: 3.0289 data: 0.0078 max mem: 33408 +Epoch: [8] [1760/2639] eta: 0:44:21 lr: 4.01341503055847e-05 loss: 0.0967 (0.0968) time: 3.0535 data: 0.0076 max mem: 33408 +Epoch: [8] [1770/2639] eta: 0:43:50 lr: 4.01297819098631e-05 loss: 0.0986 (0.0969) time: 3.0092 data: 0.0077 max mem: 33408 +Epoch: [8] [1780/2639] eta: 0:43:20 lr: 4.012541346130429e-05 loss: 0.0989 (0.0969) time: 3.0336 data: 0.0082 max mem: 33408 +Epoch: [8] [1790/2639] eta: 0:42:50 lr: 4.012104495990124e-05 loss: 0.1000 (0.0970) time: 3.0427 data: 0.0079 max mem: 33408 +Epoch: [8] [1800/2639] eta: 0:42:20 lr: 4.011667640564692e-05 loss: 0.1032 (0.0971) time: 2.9945 data: 0.0076 max mem: 33408 +Epoch: [8] [1810/2639] eta: 0:41:49 lr: 4.011230779853428e-05 loss: 0.0922 (0.0972) time: 3.0210 data: 0.0081 max mem: 33408 +Epoch: [8] [1820/2639] eta: 0:41:19 lr: 4.01079391385563e-05 loss: 0.0914 (0.0972) time: 3.0217 data: 0.0079 max mem: 33408 +Epoch: [8] [1830/2639] eta: 0:40:49 lr: 4.010357042570593e-05 loss: 0.0914 (0.0971) time: 3.0058 data: 0.0077 max mem: 33408 +Epoch: [8] [1840/2639] eta: 0:40:18 lr: 4.0099201659976136e-05 loss: 0.0902 (0.0971) time: 3.0207 data: 0.0079 max mem: 33408 +Epoch: [8] [1850/2639] eta: 0:39:48 lr: 4.009483284135989e-05 loss: 0.0881 (0.0971) time: 3.0241 data: 0.0077 max mem: 33408 +Epoch: [8] [1860/2639] eta: 0:39:18 lr: 4.009046396985012e-05 loss: 0.0838 (0.0972) time: 3.0184 data: 0.0075 max mem: 33408 +Epoch: [8] [1870/2639] eta: 0:38:48 lr: 4.0086095045439816e-05 loss: 0.0741 (0.0971) time: 3.0548 data: 0.0077 max mem: 33408 +Epoch: [8] [1880/2639] eta: 0:38:17 lr: 4.00817260681219e-05 loss: 0.0859 (0.0972) time: 3.0518 data: 0.0078 max mem: 33408 +Epoch: [8] [1890/2639] eta: 0:37:47 lr: 4.0077357037889335e-05 loss: 0.1012 (0.0973) time: 2.9937 data: 0.0076 max mem: 33408 +Epoch: [8] [1900/2639] eta: 0:37:17 lr: 4.0072987954735076e-05 loss: 0.0930 (0.0973) time: 2.9985 data: 0.0078 max mem: 33408 +Epoch: [8] [1910/2639] eta: 0:36:47 lr: 4.006861881865206e-05 loss: 0.0849 (0.0973) time: 3.0526 data: 0.0078 max mem: 33408 +Epoch: [8] [1920/2639] eta: 0:36:17 lr: 4.006424962963324e-05 loss: 0.0894 (0.0974) time: 3.0932 data: 0.0077 max mem: 33408 +Epoch: [8] [1930/2639] eta: 0:35:46 lr: 4.005988038767157e-05 loss: 0.0860 (0.0974) time: 3.0270 data: 0.0080 max mem: 33408 +Epoch: [8] [1940/2639] eta: 0:35:16 lr: 4.005551109275996e-05 loss: 0.0840 (0.0973) time: 2.9767 data: 0.0080 max mem: 33408 +Epoch: [8] [1950/2639] eta: 0:34:45 lr: 4.0051141744891384e-05 loss: 0.0814 (0.0973) time: 3.0043 data: 0.0078 max mem: 33408 +Epoch: [8] [1960/2639] eta: 0:34:15 lr: 4.004677234405877e-05 loss: 0.0769 (0.0972) time: 3.0085 data: 0.0081 max mem: 33408 +Epoch: [8] [1970/2639] eta: 0:33:45 lr: 4.004240289025505e-05 loss: 0.0772 (0.0973) time: 3.0400 data: 0.0081 max mem: 33408 +Epoch: [8] [1980/2639] eta: 0:33:15 lr: 4.003803338347317e-05 loss: 0.0821 (0.0973) time: 3.0566 data: 0.0078 max mem: 33408 +Epoch: [8] [1990/2639] eta: 0:32:44 lr: 4.003366382370605e-05 loss: 0.0834 (0.0973) time: 3.0331 data: 0.0076 max mem: 33408 +Epoch: [8] [2000/2639] eta: 0:32:14 lr: 4.002929421094663e-05 loss: 0.0923 (0.0973) time: 3.0533 data: 0.0075 max mem: 33408 +Epoch: [8] [2010/2639] eta: 0:31:44 lr: 4.002492454518784e-05 loss: 0.0952 (0.0973) time: 3.0223 data: 0.0077 max mem: 33408 +Epoch: [8] [2020/2639] eta: 0:31:14 lr: 4.00205548264226e-05 loss: 0.0933 (0.0974) time: 3.0204 data: 0.0082 max mem: 33408 +Epoch: [8] [2030/2639] eta: 0:30:43 lr: 4.0016185054643834e-05 loss: 0.0879 (0.0974) time: 3.0380 data: 0.0081 max mem: 33408 +Epoch: [8] [2040/2639] eta: 0:30:13 lr: 4.001181522984449e-05 loss: 0.0879 (0.0975) time: 3.0349 data: 0.0079 max mem: 33408 +Epoch: [8] [2050/2639] eta: 0:29:43 lr: 4.000744535201746e-05 loss: 0.0950 (0.0975) time: 3.0417 data: 0.0078 max mem: 33408 +Epoch: [8] [2060/2639] eta: 0:29:13 lr: 4.0003075421155686e-05 loss: 0.0907 (0.0975) time: 3.0727 data: 0.0083 max mem: 33408 +Epoch: [8] [2070/2639] eta: 0:28:42 lr: 3.999870543725208e-05 loss: 0.0907 (0.0976) time: 3.0553 data: 0.0088 max mem: 33408 +Epoch: [8] [2080/2639] eta: 0:28:12 lr: 3.9994335400299565e-05 loss: 0.0856 (0.0976) time: 3.0128 data: 0.0087 max mem: 33408 +Epoch: [8] [2090/2639] eta: 0:27:42 lr: 3.9989965310291044e-05 loss: 0.0849 (0.0977) time: 3.0363 data: 0.0081 max mem: 33408 +Epoch: [8] [2100/2639] eta: 0:27:12 lr: 3.998559516721944e-05 loss: 0.0867 (0.0976) time: 3.0417 data: 0.0075 max mem: 33408 +Epoch: [8] [2110/2639] eta: 0:26:41 lr: 3.998122497107766e-05 loss: 0.0868 (0.0977) time: 3.0114 data: 0.0077 max mem: 33408 +Epoch: [8] [2120/2639] eta: 0:26:11 lr: 3.997685472185862e-05 loss: 0.1020 (0.0977) time: 3.0051 data: 0.0078 max mem: 33408 +Epoch: [8] [2130/2639] eta: 0:25:41 lr: 3.997248441955522e-05 loss: 0.0900 (0.0977) time: 3.0126 data: 0.0084 max mem: 33408 +Epoch: [8] [2140/2639] eta: 0:25:10 lr: 3.9968114064160373e-05 loss: 0.0816 (0.0976) time: 3.0001 data: 0.0082 max mem: 33408 +Epoch: [8] [2150/2639] eta: 0:24:40 lr: 3.996374365566698e-05 loss: 0.1024 (0.0977) time: 2.9846 data: 0.0077 max mem: 33408 +Epoch: [8] [2160/2639] eta: 0:24:10 lr: 3.995937319406794e-05 loss: 0.1022 (0.0977) time: 3.0408 data: 0.0084 max mem: 33408 +Epoch: [8] [2170/2639] eta: 0:23:39 lr: 3.995500267935616e-05 loss: 0.0927 (0.0978) time: 3.0350 data: 0.0087 max mem: 33408 +Epoch: [8] [2180/2639] eta: 0:23:09 lr: 3.995063211152454e-05 loss: 0.0859 (0.0978) time: 2.9724 data: 0.0084 max mem: 33408 +Epoch: [8] [2190/2639] eta: 0:22:39 lr: 3.994626149056597e-05 loss: 0.0859 (0.0977) time: 2.9961 data: 0.0079 max mem: 33408 +Epoch: [8] [2200/2639] eta: 0:22:08 lr: 3.994189081647335e-05 loss: 0.0887 (0.0977) time: 2.9960 data: 0.0080 max mem: 33408 +Epoch: [8] [2210/2639] eta: 0:21:38 lr: 3.9937520089239586e-05 loss: 0.0857 (0.0977) time: 3.0137 data: 0.0079 max mem: 33408 +Epoch: [8] [2220/2639] eta: 0:21:08 lr: 3.9933149308857553e-05 loss: 0.0857 (0.0977) time: 3.0090 data: 0.0078 max mem: 33408 +Epoch: [8] [2230/2639] eta: 0:20:38 lr: 3.992877847532014e-05 loss: 0.0838 (0.0977) time: 3.0186 data: 0.0083 max mem: 33408 +Epoch: [8] [2240/2639] eta: 0:20:07 lr: 3.9924407588620243e-05 loss: 0.0838 (0.0977) time: 3.0357 data: 0.0079 max mem: 33408 +Epoch: [8] [2250/2639] eta: 0:19:37 lr: 3.992003664875075e-05 loss: 0.0904 (0.0977) time: 3.0237 data: 0.0076 max mem: 33408 +Epoch: [8] [2260/2639] eta: 0:19:07 lr: 3.9915665655704534e-05 loss: 0.0871 (0.0977) time: 3.0475 data: 0.0074 max mem: 33408 +Epoch: [8] [2270/2639] eta: 0:18:37 lr: 3.991129460947449e-05 loss: 0.0837 (0.0977) time: 3.0473 data: 0.0076 max mem: 33408 +Epoch: [8] [2280/2639] eta: 0:18:06 lr: 3.990692351005349e-05 loss: 0.0935 (0.0979) time: 3.0210 data: 0.0082 max mem: 33408 +Epoch: [8] [2290/2639] eta: 0:17:36 lr: 3.990255235743443e-05 loss: 0.0888 (0.0978) time: 2.9953 data: 0.0081 max mem: 33408 +Epoch: [8] [2300/2639] eta: 0:17:06 lr: 3.989818115161016e-05 loss: 0.0780 (0.0977) time: 3.0378 data: 0.0078 max mem: 33408 +Epoch: [8] [2310/2639] eta: 0:16:35 lr: 3.989380989257358e-05 loss: 0.0930 (0.0978) time: 3.0369 data: 0.0076 max mem: 33408 +Epoch: [8] [2320/2639] eta: 0:16:05 lr: 3.988943858031755e-05 loss: 0.1112 (0.0978) time: 3.0268 data: 0.0076 max mem: 33408 +Epoch: [8] [2330/2639] eta: 0:15:35 lr: 3.9885067214834943e-05 loss: 0.1112 (0.0978) time: 3.0709 data: 0.0076 max mem: 33408 +Epoch: [8] [2340/2639] eta: 0:15:05 lr: 3.9880695796118636e-05 loss: 0.1018 (0.0979) time: 3.0223 data: 0.0077 max mem: 33408 +Epoch: [8] [2350/2639] eta: 0:14:34 lr: 3.987632432416149e-05 loss: 0.0815 (0.0979) time: 3.0101 data: 0.0079 max mem: 33408 +Epoch: [8] [2360/2639] eta: 0:14:04 lr: 3.987195279895637e-05 loss: 0.0859 (0.0980) time: 3.0145 data: 0.0079 max mem: 33408 +Epoch: [8] [2370/2639] eta: 0:13:34 lr: 3.986758122049615e-05 loss: 0.1085 (0.0981) time: 3.0042 data: 0.0077 max mem: 33408 +Epoch: [8] [2380/2639] eta: 0:13:03 lr: 3.9863209588773685e-05 loss: 0.1130 (0.0981) time: 3.0132 data: 0.0083 max mem: 33408 +Epoch: [8] [2390/2639] eta: 0:12:33 lr: 3.9858837903781844e-05 loss: 0.0925 (0.0981) time: 3.0036 data: 0.0090 max mem: 33408 +Epoch: [8] [2400/2639] eta: 0:12:03 lr: 3.985446616551347e-05 loss: 0.0849 (0.0981) time: 3.0002 data: 0.0089 max mem: 33408 +Epoch: [8] [2410/2639] eta: 0:11:33 lr: 3.985009437396144e-05 loss: 0.0765 (0.0980) time: 3.0410 data: 0.0081 max mem: 33408 +Epoch: [8] [2420/2639] eta: 0:11:02 lr: 3.9845722529118596e-05 loss: 0.0873 (0.0980) time: 3.0540 data: 0.0077 max mem: 33408 +Epoch: [8] [2430/2639] eta: 0:10:32 lr: 3.984135063097779e-05 loss: 0.0862 (0.0980) time: 3.0239 data: 0.0077 max mem: 33408 +Epoch: [8] [2440/2639] eta: 0:10:02 lr: 3.983697867953188e-05 loss: 0.0862 (0.0980) time: 3.0105 data: 0.0075 max mem: 33408 +Epoch: [8] [2450/2639] eta: 0:09:32 lr: 3.983260667477372e-05 loss: 0.0897 (0.0980) time: 3.0193 data: 0.0073 max mem: 33408 +Epoch: [8] [2460/2639] eta: 0:09:01 lr: 3.982823461669615e-05 loss: 0.0968 (0.0980) time: 3.0373 data: 0.0073 max mem: 33408 +Epoch: [8] [2470/2639] eta: 0:08:31 lr: 3.982386250529203e-05 loss: 0.0968 (0.0981) time: 3.0140 data: 0.0072 max mem: 33408 +Epoch: [8] [2480/2639] eta: 0:08:01 lr: 3.981949034055418e-05 loss: 0.0807 (0.0981) time: 3.0534 data: 0.0072 max mem: 33408 +Epoch: [8] [2490/2639] eta: 0:07:31 lr: 3.9815118122475455e-05 loss: 0.0824 (0.0980) time: 3.0582 data: 0.0076 max mem: 33408 +Epoch: [8] [2500/2639] eta: 0:07:00 lr: 3.98107458510487e-05 loss: 0.0824 (0.0981) time: 3.0078 data: 0.0075 max mem: 33408 +Epoch: [8] [2510/2639] eta: 0:06:30 lr: 3.980637352626676e-05 loss: 0.0853 (0.0980) time: 3.0286 data: 0.0073 max mem: 33408 +Epoch: [8] [2520/2639] eta: 0:06:00 lr: 3.9802001148122446e-05 loss: 0.0768 (0.0980) time: 3.0533 data: 0.0074 max mem: 33408 +Epoch: [8] [2530/2639] eta: 0:05:29 lr: 3.979762871660862e-05 loss: 0.0846 (0.0979) time: 3.0178 data: 0.0075 max mem: 33408 +Epoch: [8] [2540/2639] eta: 0:04:59 lr: 3.9793256231718104e-05 loss: 0.1039 (0.0980) time: 3.0385 data: 0.0078 max mem: 33408 +Epoch: [8] [2550/2639] eta: 0:04:29 lr: 3.978888369344374e-05 loss: 0.1100 (0.0980) time: 3.0715 data: 0.0084 max mem: 33408 +Epoch: [8] [2560/2639] eta: 0:03:59 lr: 3.9784511101778336e-05 loss: 0.0828 (0.0981) time: 3.0262 data: 0.0087 max mem: 33408 +Epoch: [8] [2570/2639] eta: 0:03:28 lr: 3.978013845671473e-05 loss: 0.0991 (0.0982) time: 3.0359 data: 0.0085 max mem: 33408 +Epoch: [8] [2580/2639] eta: 0:02:58 lr: 3.977576575824575e-05 loss: 0.0866 (0.0982) time: 3.0275 data: 0.0081 max mem: 33408 +Epoch: [8] [2590/2639] eta: 0:02:28 lr: 3.977139300636423e-05 loss: 0.0880 (0.0982) time: 3.0314 data: 0.0078 max mem: 33408 +Epoch: [8] [2600/2639] eta: 0:01:58 lr: 3.9767020201062984e-05 loss: 0.0880 (0.0982) time: 3.0404 data: 0.0080 max mem: 33408 +Epoch: [8] [2610/2639] eta: 0:01:27 lr: 3.9762647342334816e-05 loss: 0.0855 (0.0982) time: 3.0523 data: 0.0078 max mem: 33408 +Epoch: [8] [2620/2639] eta: 0:00:57 lr: 3.975827443017258e-05 loss: 0.0871 (0.0981) time: 3.0928 data: 0.0072 max mem: 33408 +Epoch: [8] [2630/2639] eta: 0:00:27 lr: 3.975390146456906e-05 loss: 0.0884 (0.0981) time: 3.0435 data: 0.0071 max mem: 33408 +Epoch: [8] Total time: 2:13:10 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 2:06:43 time: 2.9553 data: 2.8493 max mem: 33408 +Test: [ 100/2573] eta: 0:04:25 time: 0.0780 data: 0.0014 max mem: 33408 +Test: [ 200/2573] eta: 0:03:43 time: 0.0800 data: 0.0015 max mem: 33408 +Test: [ 300/2573] eta: 0:03:22 time: 0.0807 data: 0.0013 max mem: 33408 +Test: [ 400/2573] eta: 0:03:08 time: 0.0818 data: 0.0014 max mem: 33408 +Test: [ 500/2573] eta: 0:02:57 time: 0.0798 data: 0.0014 max mem: 33408 +Test: [ 600/2573] eta: 0:02:46 time: 0.0801 data: 0.0014 max mem: 33408 +Test: [ 700/2573] eta: 0:02:38 time: 0.0798 data: 0.0014 max mem: 33408 +Test: [ 800/2573] eta: 0:02:28 time: 0.0831 data: 0.0013 max mem: 33408 +Test: [ 900/2573] eta: 0:02:19 time: 0.0800 data: 0.0015 max mem: 33408 +Test: [1000/2573] eta: 0:02:11 time: 0.0804 data: 0.0014 max mem: 33408 +Test: [1100/2573] eta: 0:02:02 time: 0.0808 data: 0.0015 max mem: 33408 +Test: [1200/2573] eta: 0:01:53 time: 0.0812 data: 0.0013 max mem: 33408 +Test: [1300/2573] eta: 0:01:45 time: 0.0810 data: 0.0014 max mem: 33408 +Test: [1400/2573] eta: 0:01:36 time: 0.0791 data: 0.0015 max mem: 33408 +Test: [1500/2573] eta: 0:01:28 time: 0.0804 data: 0.0014 max mem: 33408 +Test: [1600/2573] eta: 0:01:20 time: 0.0848 data: 0.0015 max mem: 33408 +Test: [1700/2573] eta: 0:01:11 time: 0.0786 data: 0.0014 max mem: 33408 +Test: [1800/2573] eta: 0:01:03 time: 0.0822 data: 0.0015 max mem: 33408 +Test: [1900/2573] eta: 0:00:55 time: 0.0801 data: 0.0014 max mem: 33408 +Test: [2000/2573] eta: 0:00:46 time: 0.0799 data: 0.0014 max mem: 33408 +Test: [2100/2573] eta: 0:00:38 time: 0.0828 data: 0.0014 max mem: 33408 +Test: [2200/2573] eta: 0:00:30 time: 0.0827 data: 0.0014 max mem: 33408 +Test: [2300/2573] eta: 0:00:22 time: 0.0831 data: 0.0015 max mem: 33408 +Test: [2400/2573] eta: 0:00:14 time: 0.0786 data: 0.0014 max mem: 33408 +Test: [2500/2573] eta: 0:00:05 time: 0.0802 data: 0.0014 max mem: 33408 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: Total time: 0:03:31 +Final results: +Mean IoU is 59.70 + + precision@0.5 = 66.65 + precision@0.6 = 60.19 + precision@0.7 = 52.47 + precision@0.8 = 40.44 + precision@0.9 = 17.59 + overall IoU = 58.66 + +Average object IoU 59.703461941923386 +Overall IoU 58.65558624267578 +Better epoch: 8 + +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [9] [ 0/2639] eta: 3:58:50 lr: 3.9749965749827665e-05 loss: 0.0941 (0.0941) time: 5.4301 data: 2.1661 max mem: 33408 +Epoch: [9] [ 10/2639] eta: 2:25:05 lr: 3.9745592682665946e-05 loss: 0.0895 (0.0990) time: 3.3113 data: 0.2043 max mem: 33408 +Epoch: [9] [ 20/2639] eta: 2:19:16 lr: 3.9741219562042095e-05 loss: 0.0797 (0.0942) time: 3.0786 data: 0.0074 max mem: 33408 +Epoch: [9] [ 30/2639] eta: 2:16:10 lr: 3.973684638794896e-05 loss: 0.0859 (0.0984) time: 3.0326 data: 0.0073 max mem: 33408 +Epoch: [9] [ 40/2639] eta: 2:14:41 lr: 3.973247316037931e-05 loss: 0.0905 (0.0978) time: 3.0245 data: 0.0077 max mem: 33408 +Epoch: [9] [ 50/2639] eta: 2:13:10 lr: 3.9728099879325984e-05 loss: 0.0795 (0.0964) time: 3.0166 data: 0.0075 max mem: 33408 +Epoch: [9] [ 60/2639] eta: 2:12:13 lr: 3.972372654478177e-05 loss: 0.0795 (0.0979) time: 3.0073 data: 0.0075 max mem: 33408 +Epoch: [9] [ 70/2639] eta: 2:11:05 lr: 3.971935315673947e-05 loss: 0.0846 (0.0995) time: 2.9992 data: 0.0078 max mem: 33408 +Epoch: [9] [ 80/2639] eta: 2:10:22 lr: 3.9714979715191894e-05 loss: 0.0846 (0.0975) time: 2.9985 data: 0.0080 max mem: 33408 +Epoch: [9] [ 90/2639] eta: 2:09:39 lr: 3.9710606220131824e-05 loss: 0.0823 (0.0973) time: 3.0173 data: 0.0078 max mem: 33408 +Epoch: [9] [ 100/2639] eta: 2:08:51 lr: 3.970623267155207e-05 loss: 0.0823 (0.0967) time: 2.9973 data: 0.0076 max mem: 33408 +Epoch: [9] [ 110/2639] eta: 2:08:36 lr: 3.970185906944543e-05 loss: 0.0735 (0.0945) time: 3.0469 data: 0.0077 max mem: 33408 +Epoch: [9] [ 120/2639] eta: 2:08:15 lr: 3.969748541380469e-05 loss: 0.0806 (0.0943) time: 3.1050 data: 0.0077 max mem: 33408 +Epoch: [9] [ 130/2639] eta: 2:07:35 lr: 3.9693111704622624e-05 loss: 0.0914 (0.0958) time: 3.0514 data: 0.0077 max mem: 33408 +Epoch: [9] [ 140/2639] eta: 2:06:51 lr: 3.968873794189206e-05 loss: 0.0948 (0.0954) time: 2.9909 data: 0.0076 max mem: 33408 +Epoch: [9] [ 150/2639] eta: 2:06:27 lr: 3.9684364125605754e-05 loss: 0.0706 (0.0941) time: 3.0306 data: 0.0074 max mem: 33408 +Epoch: [9] [ 160/2639] eta: 2:05:47 lr: 3.96799902557565e-05 loss: 0.0703 (0.0940) time: 3.0360 data: 0.0074 max mem: 33408 +Epoch: [9] [ 170/2639] eta: 2:05:18 lr: 3.9675616332337084e-05 loss: 0.0737 (0.0931) time: 3.0194 data: 0.0080 max mem: 33408 +Epoch: [9] [ 180/2639] eta: 2:04:52 lr: 3.967124235534029e-05 loss: 0.0800 (0.0937) time: 3.0669 data: 0.0080 max mem: 33408 +Epoch: [9] [ 190/2639] eta: 2:04:14 lr: 3.9666868324758894e-05 loss: 0.0999 (0.0938) time: 3.0346 data: 0.0083 max mem: 33408 +Epoch: [9] [ 200/2639] eta: 2:03:41 lr: 3.966249424058568e-05 loss: 0.0948 (0.0941) time: 3.0062 data: 0.0080 max mem: 33408 +Epoch: [9] [ 210/2639] eta: 2:03:04 lr: 3.9658120102813415e-05 loss: 0.0899 (0.0941) time: 3.0030 data: 0.0073 max mem: 33408 +Epoch: [9] [ 220/2639] eta: 2:02:41 lr: 3.9653745911434874e-05 loss: 0.0787 (0.0931) time: 3.0448 data: 0.0079 max mem: 33408 +Epoch: [9] [ 230/2639] eta: 2:02:03 lr: 3.9649371666442834e-05 loss: 0.0825 (0.0928) time: 3.0391 data: 0.0082 max mem: 33408 +Epoch: [9] [ 240/2639] eta: 2:01:26 lr: 3.964499736783007e-05 loss: 0.0832 (0.0929) time: 2.9731 data: 0.0080 max mem: 33408 +Epoch: [9] [ 250/2639] eta: 2:00:53 lr: 3.964062301558935e-05 loss: 0.0706 (0.0923) time: 2.9919 data: 0.0077 max mem: 33408 +Epoch: [9] [ 260/2639] eta: 2:00:19 lr: 3.963624860971343e-05 loss: 0.0798 (0.0925) time: 3.0023 data: 0.0080 max mem: 33408 +Epoch: [9] [ 270/2639] eta: 1:59:47 lr: 3.963187415019508e-05 loss: 0.0843 (0.0927) time: 3.0051 data: 0.0082 max mem: 33408 +Epoch: [9] [ 280/2639] eta: 1:59:12 lr: 3.962749963702707e-05 loss: 0.0875 (0.0927) time: 2.9994 data: 0.0084 max mem: 33408 +Epoch: [9] [ 290/2639] eta: 1:58:40 lr: 3.962312507020216e-05 loss: 0.0862 (0.0924) time: 2.9971 data: 0.0084 max mem: 33408 +Epoch: [9] [ 300/2639] eta: 1:58:08 lr: 3.96187504497131e-05 loss: 0.0862 (0.0924) time: 3.0099 data: 0.0083 max mem: 33408 +Epoch: [9] [ 310/2639] eta: 1:57:36 lr: 3.961437577555265e-05 loss: 0.0716 (0.0916) time: 3.0101 data: 0.0087 max mem: 33408 +Epoch: [9] [ 320/2639] eta: 1:57:07 lr: 3.961000104771358e-05 loss: 0.0652 (0.0910) time: 3.0255 data: 0.0085 max mem: 33408 +Epoch: [9] [ 330/2639] eta: 1:56:34 lr: 3.9605626266188625e-05 loss: 0.0652 (0.0905) time: 3.0197 data: 0.0083 max mem: 33408 +Epoch: [9] [ 340/2639] eta: 1:56:03 lr: 3.960125143097055e-05 loss: 0.0701 (0.0905) time: 3.0027 data: 0.0081 max mem: 33408 +Epoch: [9] [ 350/2639] eta: 1:55:36 lr: 3.95968765420521e-05 loss: 0.0687 (0.0899) time: 3.0471 data: 0.0080 max mem: 33408 +Epoch: [9] [ 360/2639] eta: 1:55:05 lr: 3.9592501599426027e-05 loss: 0.0687 (0.0901) time: 3.0487 data: 0.0082 max mem: 33408 +Epoch: [9] [ 370/2639] eta: 1:54:36 lr: 3.958812660308507e-05 loss: 0.0839 (0.0898) time: 3.0328 data: 0.0084 max mem: 33408 +Epoch: [9] [ 380/2639] eta: 1:54:05 lr: 3.958375155302198e-05 loss: 0.0839 (0.0900) time: 3.0378 data: 0.0083 max mem: 33408 +Epoch: [9] [ 390/2639] eta: 1:53:38 lr: 3.9579376449229504e-05 loss: 0.0901 (0.0904) time: 3.0551 data: 0.0080 max mem: 33408 +Epoch: [9] [ 400/2639] eta: 1:53:06 lr: 3.9575001291700375e-05 loss: 0.0977 (0.0905) time: 3.0429 data: 0.0082 max mem: 33408 +Epoch: [9] [ 410/2639] eta: 1:52:39 lr: 3.9570626080427325e-05 loss: 0.0977 (0.0907) time: 3.0450 data: 0.0078 max mem: 33408 +Epoch: [9] [ 420/2639] eta: 1:52:07 lr: 3.956625081540311e-05 loss: 0.0814 (0.0903) time: 3.0469 data: 0.0079 max mem: 33408 +Epoch: [9] [ 430/2639] eta: 1:51:36 lr: 3.956187549662044e-05 loss: 0.0785 (0.0902) time: 3.0091 data: 0.0083 max mem: 33408 +Epoch: [9] [ 440/2639] eta: 1:51:02 lr: 3.955750012407208e-05 loss: 0.0785 (0.0899) time: 2.9913 data: 0.0079 max mem: 33408 +Epoch: [9] [ 450/2639] eta: 1:50:33 lr: 3.955312469775074e-05 loss: 0.0704 (0.0901) time: 3.0056 data: 0.0076 max mem: 33408 +Epoch: [9] [ 460/2639] eta: 1:50:02 lr: 3.9548749217649145e-05 loss: 0.0637 (0.0894) time: 3.0384 data: 0.0081 max mem: 33408 +Epoch: [9] [ 470/2639] eta: 1:49:33 lr: 3.954437368376004e-05 loss: 0.0637 (0.0892) time: 3.0430 data: 0.0081 max mem: 33408 +Epoch: [9] [ 480/2639] eta: 1:49:03 lr: 3.953999809607614e-05 loss: 0.0779 (0.0892) time: 3.0465 data: 0.0077 max mem: 33408 +Epoch: [9] [ 490/2639] eta: 1:48:32 lr: 3.9535622454590184e-05 loss: 0.0925 (0.0893) time: 3.0268 data: 0.0084 max mem: 33408 +Epoch: [9] [ 500/2639] eta: 1:47:59 lr: 3.953124675929487e-05 loss: 0.0839 (0.0891) time: 2.9856 data: 0.0083 max mem: 33408 +Epoch: [9] [ 510/2639] eta: 1:47:28 lr: 3.952687101018293e-05 loss: 0.0731 (0.0890) time: 2.9892 data: 0.0079 max mem: 33408 +Epoch: [9] [ 520/2639] eta: 1:46:56 lr: 3.952249520724708e-05 loss: 0.0765 (0.0891) time: 3.0017 data: 0.0082 max mem: 33408 +Epoch: [9] [ 530/2639] eta: 1:46:28 lr: 3.951811935048005e-05 loss: 0.0727 (0.0891) time: 3.0300 data: 0.0080 max mem: 33408 +Epoch: [9] [ 540/2639] eta: 1:45:55 lr: 3.9513743439874535e-05 loss: 0.0701 (0.0889) time: 3.0239 data: 0.0074 max mem: 33408 +Epoch: [9] [ 550/2639] eta: 1:45:25 lr: 3.950936747542326e-05 loss: 0.0761 (0.0889) time: 2.9989 data: 0.0082 max mem: 33408 +Epoch: [9] [ 560/2639] eta: 1:44:52 lr: 3.9504991457118925e-05 loss: 0.0714 (0.0888) time: 3.0008 data: 0.0085 max mem: 33408 +Epoch: [9] [ 570/2639] eta: 1:44:23 lr: 3.950061538495426e-05 loss: 0.0640 (0.0886) time: 3.0108 data: 0.0079 max mem: 33408 +Epoch: [9] [ 580/2639] eta: 1:43:51 lr: 3.949623925892194e-05 loss: 0.0730 (0.0884) time: 3.0071 data: 0.0079 max mem: 33408 +Epoch: [9] [ 590/2639] eta: 1:43:20 lr: 3.9491863079014695e-05 loss: 0.0719 (0.0882) time: 2.9906 data: 0.0077 max mem: 33408 +Epoch: [9] [ 600/2639] eta: 1:42:48 lr: 3.948748684522523e-05 loss: 0.0719 (0.0881) time: 3.0036 data: 0.0078 max mem: 33408 +Epoch: [9] [ 610/2639] eta: 1:42:17 lr: 3.948311055754623e-05 loss: 0.0793 (0.0884) time: 2.9923 data: 0.0078 max mem: 33408 +Epoch: [9] [ 620/2639] eta: 1:41:47 lr: 3.94787342159704e-05 loss: 0.0858 (0.0886) time: 3.0064 data: 0.0077 max mem: 33408 +Epoch: [9] [ 630/2639] eta: 1:41:18 lr: 3.947435782049044e-05 loss: 0.0858 (0.0886) time: 3.0400 data: 0.0079 max mem: 33408 +Epoch: [9] [ 640/2639] eta: 1:40:49 lr: 3.9469981371099054e-05 loss: 0.0954 (0.0886) time: 3.0642 data: 0.0077 max mem: 33408 +Epoch: [9] [ 650/2639] eta: 1:40:20 lr: 3.946560486778892e-05 loss: 0.0758 (0.0887) time: 3.0774 data: 0.0073 max mem: 33408 +Epoch: [9] [ 660/2639] eta: 1:39:49 lr: 3.9461228310552735e-05 loss: 0.0805 (0.0886) time: 3.0368 data: 0.0078 max mem: 33408 +Epoch: [9] [ 670/2639] eta: 1:39:20 lr: 3.945685169938319e-05 loss: 0.0797 (0.0886) time: 3.0240 data: 0.0080 max mem: 33408 +Epoch: [9] [ 680/2639] eta: 1:38:50 lr: 3.945247503427298e-05 loss: 0.0797 (0.0886) time: 3.0560 data: 0.0081 max mem: 33408 +Epoch: [9] [ 690/2639] eta: 1:38:19 lr: 3.944809831521478e-05 loss: 0.0802 (0.0884) time: 3.0341 data: 0.0079 max mem: 33408 +Epoch: [9] [ 700/2639] eta: 1:37:50 lr: 3.944372154220129e-05 loss: 0.0752 (0.0883) time: 3.0297 data: 0.0077 max mem: 33408 +Epoch: [9] [ 710/2639] eta: 1:37:19 lr: 3.943934471522517e-05 loss: 0.0739 (0.0883) time: 3.0304 data: 0.0077 max mem: 33408 +Epoch: [9] [ 720/2639] eta: 1:36:48 lr: 3.943496783427912e-05 loss: 0.0659 (0.0879) time: 3.0134 data: 0.0074 max mem: 33408 +Epoch: [9] [ 730/2639] eta: 1:36:19 lr: 3.9430590899355806e-05 loss: 0.0697 (0.0879) time: 3.0391 data: 0.0074 max mem: 33408 +Epoch: [9] [ 740/2639] eta: 1:35:49 lr: 3.942621391044792e-05 loss: 0.0697 (0.0878) time: 3.0525 data: 0.0073 max mem: 33408 +Epoch: [9] [ 750/2639] eta: 1:35:17 lr: 3.9421836867548113e-05 loss: 0.0695 (0.0878) time: 2.9896 data: 0.0079 max mem: 33408 +Epoch: [9] [ 760/2639] eta: 1:34:45 lr: 3.941745977064908e-05 loss: 0.0803 (0.0879) time: 2.9478 data: 0.0080 max mem: 33408 +Epoch: [9] [ 770/2639] eta: 1:34:16 lr: 3.941308261974349e-05 loss: 0.0901 (0.0880) time: 3.0204 data: 0.0077 max mem: 33408 +Epoch: [9] [ 780/2639] eta: 1:33:46 lr: 3.940870541482399e-05 loss: 0.0852 (0.0879) time: 3.0587 data: 0.0076 max mem: 33408 +Epoch: [9] [ 790/2639] eta: 1:33:15 lr: 3.9404328155883276e-05 loss: 0.0846 (0.0880) time: 3.0214 data: 0.0076 max mem: 33408 +Epoch: [9] [ 800/2639] eta: 1:32:44 lr: 3.9399950842914e-05 loss: 0.0923 (0.0880) time: 2.9937 data: 0.0078 max mem: 33408 +Epoch: [9] [ 810/2639] eta: 1:32:13 lr: 3.939557347590882e-05 loss: 0.0816 (0.0879) time: 2.9925 data: 0.0078 max mem: 33408 +Epoch: [9] [ 820/2639] eta: 1:31:43 lr: 3.939119605486041e-05 loss: 0.0698 (0.0879) time: 3.0345 data: 0.0079 max mem: 33408 +Epoch: [9] [ 830/2639] eta: 1:31:14 lr: 3.938681857976142e-05 loss: 0.0768 (0.0879) time: 3.0672 data: 0.0082 max mem: 33408 +Epoch: [9] [ 840/2639] eta: 1:30:45 lr: 3.9382441050604516e-05 loss: 0.0775 (0.0877) time: 3.0789 data: 0.0082 max mem: 33408 +Epoch: [9] [ 850/2639] eta: 1:30:14 lr: 3.9378063467382345e-05 loss: 0.0779 (0.0879) time: 3.0348 data: 0.0081 max mem: 33408 +Epoch: [9] [ 860/2639] eta: 1:29:44 lr: 3.937368583008757e-05 loss: 0.0778 (0.0877) time: 3.0171 data: 0.0079 max mem: 33408 +Epoch: [9] [ 870/2639] eta: 1:29:14 lr: 3.936930813871283e-05 loss: 0.0748 (0.0878) time: 3.0323 data: 0.0080 max mem: 33408 +Epoch: [9] [ 880/2639] eta: 1:28:45 lr: 3.936493039325079e-05 loss: 0.0986 (0.0879) time: 3.0657 data: 0.0080 max mem: 33408 +Epoch: [9] [ 890/2639] eta: 1:28:14 lr: 3.9360552593694086e-05 loss: 0.0907 (0.0879) time: 3.0347 data: 0.0078 max mem: 33408 +Epoch: [9] [ 900/2639] eta: 1:27:44 lr: 3.9356174740035376e-05 loss: 0.0849 (0.0878) time: 3.0060 data: 0.0078 max mem: 33408 +Epoch: [9] [ 910/2639] eta: 1:27:14 lr: 3.935179683226729e-05 loss: 0.0700 (0.0876) time: 3.0459 data: 0.0078 max mem: 33408 +Epoch: [9] [ 920/2639] eta: 1:26:44 lr: 3.9347418870382486e-05 loss: 0.0700 (0.0875) time: 3.0451 data: 0.0079 max mem: 33408 +Epoch: [9] [ 930/2639] eta: 1:26:14 lr: 3.9343040854373594e-05 loss: 0.0771 (0.0876) time: 3.0505 data: 0.0077 max mem: 33408 +Epoch: [9] [ 940/2639] eta: 1:25:43 lr: 3.933866278423326e-05 loss: 0.0771 (0.0877) time: 3.0108 data: 0.0076 max mem: 33408 +Epoch: [9] [ 950/2639] eta: 1:25:13 lr: 3.933428465995411e-05 loss: 0.0722 (0.0875) time: 3.0096 data: 0.0080 max mem: 33408 +Epoch: [9] [ 960/2639] eta: 1:24:42 lr: 3.932990648152879e-05 loss: 0.0627 (0.0878) time: 3.0151 data: 0.0081 max mem: 33408 +Epoch: [9] [ 970/2639] eta: 1:24:11 lr: 3.9325528248949934e-05 loss: 0.0684 (0.0876) time: 2.9944 data: 0.0081 max mem: 33408 +Epoch: [9] [ 980/2639] eta: 1:23:41 lr: 3.9321149962210156e-05 loss: 0.0690 (0.0877) time: 3.0072 data: 0.0084 max mem: 33408 +Epoch: [9] [ 990/2639] eta: 1:23:11 lr: 3.9316771621302106e-05 loss: 0.0749 (0.0876) time: 3.0248 data: 0.0081 max mem: 33408 +Epoch: [9] [1000/2639] eta: 1:22:40 lr: 3.93123932262184e-05 loss: 0.0785 (0.0877) time: 3.0152 data: 0.0077 max mem: 33408 +Epoch: [9] [1010/2639] eta: 1:22:09 lr: 3.9308014776951666e-05 loss: 0.1060 (0.0879) time: 3.0034 data: 0.0083 max mem: 33408 +Epoch: [9] [1020/2639] eta: 1:21:39 lr: 3.9303636273494524e-05 loss: 0.0880 (0.0878) time: 3.0144 data: 0.0084 max mem: 33408 +Epoch: [9] [1030/2639] eta: 1:21:08 lr: 3.92992577158396e-05 loss: 0.0712 (0.0879) time: 3.0026 data: 0.0082 max mem: 33408 +Epoch: [9] [1040/2639] eta: 1:20:37 lr: 3.9294879103979506e-05 loss: 0.0792 (0.0879) time: 2.9846 data: 0.0081 max mem: 33408 +Epoch: [9] [1050/2639] eta: 1:20:07 lr: 3.929050043790687e-05 loss: 0.0892 (0.0880) time: 3.0079 data: 0.0076 max mem: 33408 +Epoch: [9] [1060/2639] eta: 1:19:36 lr: 3.92861217176143e-05 loss: 0.0892 (0.0880) time: 3.0114 data: 0.0076 max mem: 33408 +Epoch: [9] [1070/2639] eta: 1:19:06 lr: 3.928174294309443e-05 loss: 0.0804 (0.0880) time: 3.0167 data: 0.0081 max mem: 33408 +Epoch: [9] [1080/2639] eta: 1:18:37 lr: 3.9277364114339825e-05 loss: 0.0710 (0.0880) time: 3.0870 data: 0.0084 max mem: 33408 +Epoch: [9] [1090/2639] eta: 1:18:07 lr: 3.9272985231343143e-05 loss: 0.0683 (0.0878) time: 3.0680 data: 0.0080 max mem: 33408 +Epoch: [9] [1100/2639] eta: 1:17:36 lr: 3.926860629409697e-05 loss: 0.0681 (0.0877) time: 3.0042 data: 0.0082 max mem: 33408 +Epoch: [9] [1110/2639] eta: 1:17:06 lr: 3.926422730259392e-05 loss: 0.0729 (0.0876) time: 3.0004 data: 0.0087 max mem: 33408 +Epoch: [9] [1120/2639] eta: 1:16:35 lr: 3.925984825682658e-05 loss: 0.0828 (0.0880) time: 2.9981 data: 0.0085 max mem: 33408 +Epoch: [9] [1130/2639] eta: 1:16:05 lr: 3.925546915678757e-05 loss: 0.0863 (0.0880) time: 3.0030 data: 0.0080 max mem: 33408 +Epoch: [9] [1140/2639] eta: 1:15:34 lr: 3.9251090002469494e-05 loss: 0.0664 (0.0879) time: 2.9994 data: 0.0082 max mem: 33408 +Epoch: [9] [1150/2639] eta: 1:15:04 lr: 3.924671079386494e-05 loss: 0.0792 (0.0878) time: 3.0330 data: 0.0080 max mem: 33408 +Epoch: [9] [1160/2639] eta: 1:14:34 lr: 3.92423315309665e-05 loss: 0.0740 (0.0877) time: 3.0702 data: 0.0078 max mem: 33408 +Epoch: [9] [1170/2639] eta: 1:14:04 lr: 3.923795221376677e-05 loss: 0.0721 (0.0878) time: 3.0220 data: 0.0078 max mem: 33408 +Epoch: [9] [1180/2639] eta: 1:13:34 lr: 3.923357284225836e-05 loss: 0.1012 (0.0881) time: 3.0239 data: 0.0078 max mem: 33408 +Epoch: [9] [1190/2639] eta: 1:13:03 lr: 3.922919341643384e-05 loss: 0.0898 (0.0882) time: 3.0339 data: 0.0081 max mem: 33408 +Epoch: [9] [1200/2639] eta: 1:12:33 lr: 3.922481393628581e-05 loss: 0.0739 (0.0883) time: 3.0187 data: 0.0081 max mem: 33408 +Epoch: [9] [1210/2639] eta: 1:12:03 lr: 3.922043440180685e-05 loss: 0.0834 (0.0883) time: 3.0335 data: 0.0078 max mem: 33408 +Epoch: [9] [1220/2639] eta: 1:11:33 lr: 3.9216054812989554e-05 loss: 0.0806 (0.0884) time: 3.0360 data: 0.0077 max mem: 33408 +Epoch: [9] [1230/2639] eta: 1:11:03 lr: 3.9211675169826495e-05 loss: 0.0808 (0.0885) time: 3.0481 data: 0.0076 max mem: 33408 +Epoch: [9] [1240/2639] eta: 1:10:33 lr: 3.920729547231026e-05 loss: 0.0816 (0.0885) time: 3.0518 data: 0.0074 max mem: 33408 +Epoch: [9] [1250/2639] eta: 1:10:02 lr: 3.920291572043342e-05 loss: 0.0816 (0.0885) time: 3.0186 data: 0.0075 max mem: 33408 +Epoch: [9] [1260/2639] eta: 1:09:31 lr: 3.919853591418857e-05 loss: 0.0876 (0.0884) time: 2.9652 data: 0.0076 max mem: 33408 +Epoch: [9] [1270/2639] eta: 1:09:01 lr: 3.9194156053568266e-05 loss: 0.0764 (0.0883) time: 2.9779 data: 0.0075 max mem: 33408 +Epoch: [9] [1280/2639] eta: 1:08:30 lr: 3.918977613856509e-05 loss: 0.0818 (0.0885) time: 2.9949 data: 0.0073 max mem: 33408 +Epoch: [9] [1290/2639] eta: 1:08:00 lr: 3.918539616917161e-05 loss: 0.0924 (0.0885) time: 3.0148 data: 0.0072 max mem: 33408 +Epoch: [9] [1300/2639] eta: 1:07:29 lr: 3.91810161453804e-05 loss: 0.0894 (0.0886) time: 3.0059 data: 0.0074 max mem: 33408 +Epoch: [9] [1310/2639] eta: 1:06:59 lr: 3.917663606718403e-05 loss: 0.0799 (0.0886) time: 2.9799 data: 0.0077 max mem: 33408 +Epoch: [9] [1320/2639] eta: 1:06:28 lr: 3.917225593457506e-05 loss: 0.0799 (0.0887) time: 2.9955 data: 0.0077 max mem: 33408 +Epoch: [9] [1330/2639] eta: 1:05:58 lr: 3.916787574754605e-05 loss: 0.0889 (0.0889) time: 3.0250 data: 0.0074 max mem: 33408 +Epoch: [9] [1340/2639] eta: 1:05:28 lr: 3.916349550608957e-05 loss: 0.0924 (0.0890) time: 3.0335 data: 0.0076 max mem: 33408 +Epoch: [9] [1350/2639] eta: 1:04:57 lr: 3.915911521019817e-05 loss: 0.0881 (0.0893) time: 3.0039 data: 0.0076 max mem: 33408 +Epoch: [9] [1360/2639] eta: 1:04:27 lr: 3.915473485986442e-05 loss: 0.0866 (0.0893) time: 2.9983 data: 0.0078 max mem: 33408 +Epoch: [9] [1370/2639] eta: 1:03:57 lr: 3.915035445508086e-05 loss: 0.0767 (0.0892) time: 3.0205 data: 0.0079 max mem: 33408 +Epoch: [9] [1380/2639] eta: 1:03:26 lr: 3.9145973995840055e-05 loss: 0.0767 (0.0893) time: 3.0251 data: 0.0077 max mem: 33408 +Epoch: [9] [1390/2639] eta: 1:02:56 lr: 3.914159348213456e-05 loss: 0.0992 (0.0896) time: 3.0002 data: 0.0075 max mem: 33408 +Epoch: [9] [1400/2639] eta: 1:02:26 lr: 3.913721291395692e-05 loss: 0.0910 (0.0896) time: 3.0134 data: 0.0073 max mem: 33408 +Epoch: [9] [1410/2639] eta: 1:01:56 lr: 3.913283229129968e-05 loss: 0.0776 (0.0897) time: 3.0472 data: 0.0078 max mem: 33408 +Epoch: [9] [1420/2639] eta: 1:01:26 lr: 3.912845161415539e-05 loss: 0.0845 (0.0898) time: 3.0530 data: 0.0077 max mem: 33408 +Epoch: [9] [1430/2639] eta: 1:00:56 lr: 3.91240708825166e-05 loss: 0.0814 (0.0897) time: 3.0767 data: 0.0071 max mem: 33408 +Epoch: [9] [1440/2639] eta: 1:00:26 lr: 3.911969009637584e-05 loss: 0.0784 (0.0897) time: 3.0567 data: 0.0071 max mem: 33408 +Epoch: [9] [1450/2639] eta: 0:59:56 lr: 3.9115309255725656e-05 loss: 0.0810 (0.0897) time: 3.0106 data: 0.0073 max mem: 33408 +Epoch: [9] [1460/2639] eta: 0:59:25 lr: 3.9110928360558576e-05 loss: 0.0905 (0.0899) time: 3.0125 data: 0.0073 max mem: 33408 +Epoch: [9] [1470/2639] eta: 0:58:55 lr: 3.9106547410867166e-05 loss: 0.0942 (0.0902) time: 3.0125 data: 0.0075 max mem: 33408 +Epoch: [9] [1480/2639] eta: 0:58:24 lr: 3.910216640664392e-05 loss: 0.0939 (0.0902) time: 3.0084 data: 0.0082 max mem: 33408 +Epoch: [9] [1490/2639] eta: 0:57:54 lr: 3.909778534788141e-05 loss: 0.0723 (0.0902) time: 3.0022 data: 0.0083 max mem: 33408 +Epoch: [9] [1500/2639] eta: 0:57:25 lr: 3.909340423457214e-05 loss: 0.0756 (0.0902) time: 3.0625 data: 0.0079 max mem: 33408 +Epoch: [9] [1510/2639] eta: 0:56:54 lr: 3.908902306670865e-05 loss: 0.0736 (0.0901) time: 3.0537 data: 0.0086 max mem: 33408 +Epoch: [9] [1520/2639] eta: 0:56:24 lr: 3.908464184428345e-05 loss: 0.0917 (0.0903) time: 3.0191 data: 0.0085 max mem: 33408 +Epoch: [9] [1530/2639] eta: 0:55:54 lr: 3.90802605672891e-05 loss: 0.0931 (0.0902) time: 3.0843 data: 0.0077 max mem: 33408 +Epoch: [9] [1540/2639] eta: 0:55:24 lr: 3.9075879235718074e-05 loss: 0.0729 (0.0903) time: 3.0540 data: 0.0079 max mem: 33408 +Epoch: [9] [1550/2639] eta: 0:54:53 lr: 3.907149784956293e-05 loss: 0.0937 (0.0904) time: 2.9888 data: 0.0079 max mem: 33408 +Epoch: [9] [1560/2639] eta: 0:54:23 lr: 3.9067116408816184e-05 loss: 0.0976 (0.0905) time: 3.0074 data: 0.0076 max mem: 33408 +Epoch: [9] [1570/2639] eta: 0:53:53 lr: 3.9062734913470337e-05 loss: 0.0915 (0.0906) time: 3.0277 data: 0.0077 max mem: 33408 +Epoch: [9] [1580/2639] eta: 0:53:23 lr: 3.9058353363517915e-05 loss: 0.0785 (0.0905) time: 3.0232 data: 0.0076 max mem: 33408 +Epoch: [9] [1590/2639] eta: 0:52:53 lr: 3.905397175895142e-05 loss: 0.0749 (0.0904) time: 3.0382 data: 0.0075 max mem: 33408 +Epoch: [9] [1600/2639] eta: 0:52:22 lr: 3.904959009976338e-05 loss: 0.0687 (0.0905) time: 3.0255 data: 0.0079 max mem: 33408 +Epoch: [9] [1610/2639] eta: 0:51:52 lr: 3.9045208385946285e-05 loss: 0.0760 (0.0904) time: 2.9998 data: 0.0078 max mem: 33408 +Epoch: [9] [1620/2639] eta: 0:51:21 lr: 3.9040826617492655e-05 loss: 0.0809 (0.0906) time: 3.0085 data: 0.0077 max mem: 33408 +Epoch: [9] [1630/2639] eta: 0:50:51 lr: 3.903644479439499e-05 loss: 0.0761 (0.0905) time: 3.0185 data: 0.0076 max mem: 33408 +Epoch: [9] [1640/2639] eta: 0:50:21 lr: 3.903206291664579e-05 loss: 0.0784 (0.0905) time: 3.0021 data: 0.0074 max mem: 33408 +Epoch: [9] [1650/2639] eta: 0:49:50 lr: 3.902768098423758e-05 loss: 0.0904 (0.0905) time: 2.9941 data: 0.0073 max mem: 33408 +Epoch: [9] [1660/2639] eta: 0:49:20 lr: 3.902329899716282e-05 loss: 0.0904 (0.0905) time: 3.0374 data: 0.0072 max mem: 33408 +Epoch: [9] [1670/2639] eta: 0:48:50 lr: 3.901891695541403e-05 loss: 0.0784 (0.0905) time: 3.0640 data: 0.0072 max mem: 33408 +Epoch: [9] [1680/2639] eta: 0:48:20 lr: 3.90145348589837e-05 loss: 0.0729 (0.0904) time: 3.0691 data: 0.0078 max mem: 33408 +Epoch: [9] [1690/2639] eta: 0:47:50 lr: 3.9010152707864326e-05 loss: 0.0764 (0.0904) time: 3.0074 data: 0.0083 max mem: 33408 +Epoch: [9] [1700/2639] eta: 0:47:19 lr: 3.9005770502048405e-05 loss: 0.0824 (0.0903) time: 2.9845 data: 0.0084 max mem: 33408 +Epoch: [9] [1710/2639] eta: 0:46:49 lr: 3.900138824152841e-05 loss: 0.0867 (0.0904) time: 3.0105 data: 0.0081 max mem: 33408 +Epoch: [9] [1720/2639] eta: 0:46:19 lr: 3.899700592629685e-05 loss: 0.0886 (0.0903) time: 2.9961 data: 0.0081 max mem: 33408 +Epoch: [9] [1730/2639] eta: 0:45:48 lr: 3.899262355634619e-05 loss: 0.0854 (0.0903) time: 2.9792 data: 0.0081 max mem: 33408 +Epoch: [9] [1740/2639] eta: 0:45:18 lr: 3.8988241131668926e-05 loss: 0.0900 (0.0904) time: 2.9663 data: 0.0079 max mem: 33408 +Epoch: [9] [1750/2639] eta: 0:44:47 lr: 3.898385865225753e-05 loss: 0.0900 (0.0904) time: 2.9683 data: 0.0081 max mem: 33408 +Epoch: [9] [1760/2639] eta: 0:44:17 lr: 3.897947611810449e-05 loss: 0.0781 (0.0903) time: 3.0098 data: 0.0085 max mem: 33408 +Epoch: [9] [1770/2639] eta: 0:43:47 lr: 3.897509352920228e-05 loss: 0.0795 (0.0904) time: 3.0289 data: 0.0085 max mem: 33408 +Epoch: [9] [1780/2639] eta: 0:43:16 lr: 3.897071088554338e-05 loss: 0.0795 (0.0904) time: 3.0227 data: 0.0086 max mem: 33408 +Epoch: [9] [1790/2639] eta: 0:42:46 lr: 3.896632818712025e-05 loss: 0.0792 (0.0904) time: 3.0399 data: 0.0081 max mem: 33408 +Epoch: [9] [1800/2639] eta: 0:42:16 lr: 3.896194543392537e-05 loss: 0.0821 (0.0904) time: 3.0735 data: 0.0077 max mem: 33408 +Epoch: [9] [1810/2639] eta: 0:41:46 lr: 3.895756262595122e-05 loss: 0.0838 (0.0905) time: 3.0380 data: 0.0080 max mem: 33408 +Epoch: [9] [1820/2639] eta: 0:41:16 lr: 3.895317976319026e-05 loss: 0.0833 (0.0906) time: 3.0017 data: 0.0082 max mem: 33408 +Epoch: [9] [1830/2639] eta: 0:40:45 lr: 3.894879684563495e-05 loss: 0.0970 (0.0906) time: 3.0086 data: 0.0082 max mem: 33408 +Epoch: [9] [1840/2639] eta: 0:40:15 lr: 3.894441387327775e-05 loss: 0.0825 (0.0906) time: 3.0082 data: 0.0080 max mem: 33408 +Epoch: [9] [1850/2639] eta: 0:39:45 lr: 3.894003084611114e-05 loss: 0.0751 (0.0906) time: 3.0232 data: 0.0080 max mem: 33408 +Epoch: [9] [1860/2639] eta: 0:39:15 lr: 3.893564776412757e-05 loss: 0.0770 (0.0906) time: 3.0011 data: 0.0081 max mem: 33408 +Epoch: [9] [1870/2639] eta: 0:38:44 lr: 3.893126462731948e-05 loss: 0.0818 (0.0907) time: 3.0079 data: 0.0082 max mem: 33408 +Epoch: [9] [1880/2639] eta: 0:38:14 lr: 3.8926881435679355e-05 loss: 0.0858 (0.0907) time: 3.0157 data: 0.0084 max mem: 33408 +Epoch: [9] [1890/2639] eta: 0:37:44 lr: 3.8922498189199635e-05 loss: 0.0717 (0.0906) time: 3.0085 data: 0.0081 max mem: 33408 +Epoch: [9] [1900/2639] eta: 0:37:13 lr: 3.891811488787277e-05 loss: 0.0742 (0.0908) time: 3.0031 data: 0.0076 max mem: 33408 +Epoch: [9] [1910/2639] eta: 0:36:43 lr: 3.891373153169121e-05 loss: 0.0888 (0.0908) time: 3.0359 data: 0.0073 max mem: 33408 +Epoch: [9] [1920/2639] eta: 0:36:13 lr: 3.890934812064741e-05 loss: 0.0731 (0.0907) time: 3.0247 data: 0.0079 max mem: 33408 +Epoch: [9] [1930/2639] eta: 0:35:43 lr: 3.890496465473381e-05 loss: 0.0716 (0.0906) time: 3.0356 data: 0.0081 max mem: 33408 +Epoch: [9] [1940/2639] eta: 0:35:13 lr: 3.890058113394285e-05 loss: 0.0756 (0.0906) time: 3.0706 data: 0.0077 max mem: 33408 +Epoch: [9] [1950/2639] eta: 0:34:43 lr: 3.889619755826699e-05 loss: 0.0722 (0.0904) time: 3.0183 data: 0.0080 max mem: 33408 +Epoch: [9] [1960/2639] eta: 0:34:12 lr: 3.889181392769865e-05 loss: 0.0673 (0.0906) time: 3.0101 data: 0.0078 max mem: 33408 +Epoch: [9] [1970/2639] eta: 0:33:42 lr: 3.888743024223027e-05 loss: 0.0916 (0.0907) time: 3.0236 data: 0.0077 max mem: 33408 +Epoch: [9] [1980/2639] eta: 0:33:12 lr: 3.8883046501854295e-05 loss: 0.0962 (0.0907) time: 3.0339 data: 0.0078 max mem: 33408 +Epoch: [9] [1990/2639] eta: 0:32:41 lr: 3.887866270656315e-05 loss: 0.0883 (0.0908) time: 3.0079 data: 0.0075 max mem: 33408 +Epoch: [9] [2000/2639] eta: 0:32:12 lr: 3.887427885634928e-05 loss: 0.0775 (0.0907) time: 3.0516 data: 0.0074 max mem: 33408 +Epoch: [9] [2010/2639] eta: 0:31:42 lr: 3.88698949512051e-05 loss: 0.0765 (0.0907) time: 3.1057 data: 0.0081 max mem: 33408 +Epoch: [9] [2020/2639] eta: 0:31:11 lr: 3.886551099112304e-05 loss: 0.0822 (0.0906) time: 3.0310 data: 0.0086 max mem: 33408 +Epoch: [9] [2030/2639] eta: 0:30:41 lr: 3.886112697609554e-05 loss: 0.0857 (0.0907) time: 3.0242 data: 0.0078 max mem: 33408 +Epoch: [9] [2040/2639] eta: 0:30:11 lr: 3.8856742906115e-05 loss: 0.0769 (0.0907) time: 3.0322 data: 0.0077 max mem: 33408 +Epoch: [9] [2050/2639] eta: 0:29:41 lr: 3.8852358781173865e-05 loss: 0.0849 (0.0907) time: 3.0183 data: 0.0079 max mem: 33408 +Epoch: [9] [2060/2639] eta: 0:29:10 lr: 3.884797460126455e-05 loss: 0.0849 (0.0907) time: 3.0325 data: 0.0079 max mem: 33408 +Epoch: [9] [2070/2639] eta: 0:28:40 lr: 3.884359036637946e-05 loss: 0.0857 (0.0908) time: 3.0099 data: 0.0082 max mem: 33408 +Epoch: [9] [2080/2639] eta: 0:28:10 lr: 3.8839206076511025e-05 loss: 0.0741 (0.0907) time: 2.9939 data: 0.0079 max mem: 33408 +Epoch: [9] [2090/2639] eta: 0:27:40 lr: 3.883482173165165e-05 loss: 0.0765 (0.0907) time: 3.0546 data: 0.0077 max mem: 33408 +Epoch: [9] [2100/2639] eta: 0:27:09 lr: 3.883043733179376e-05 loss: 0.0933 (0.0907) time: 3.0409 data: 0.0080 max mem: 33408 +Epoch: [9] [2110/2639] eta: 0:26:39 lr: 3.882605287692974e-05 loss: 0.0957 (0.0907) time: 3.0130 data: 0.0082 max mem: 33408 +Epoch: [9] [2120/2639] eta: 0:26:09 lr: 3.8821668367052025e-05 loss: 0.0835 (0.0907) time: 3.0279 data: 0.0083 max mem: 33408 +Epoch: [9] [2130/2639] eta: 0:25:39 lr: 3.881728380215301e-05 loss: 0.0928 (0.0908) time: 3.0433 data: 0.0077 max mem: 33408 +Epoch: [9] [2140/2639] eta: 0:25:09 lr: 3.8812899182225084e-05 loss: 0.0974 (0.0908) time: 3.0746 data: 0.0074 max mem: 33408 +Epoch: [9] [2150/2639] eta: 0:24:38 lr: 3.880851450726068e-05 loss: 0.0739 (0.0908) time: 3.0500 data: 0.0082 max mem: 33408 +Epoch: [9] [2160/2639] eta: 0:24:08 lr: 3.8804129777252174e-05 loss: 0.0732 (0.0908) time: 3.0334 data: 0.0085 max mem: 33408 +Epoch: [9] [2170/2639] eta: 0:23:38 lr: 3.8799744992191966e-05 loss: 0.0843 (0.0907) time: 2.9951 data: 0.0082 max mem: 33408 +Epoch: [9] [2180/2639] eta: 0:23:08 lr: 3.879536015207247e-05 loss: 0.0871 (0.0907) time: 3.0127 data: 0.0079 max mem: 33408 +Epoch: [9] [2190/2639] eta: 0:22:37 lr: 3.879097525688606e-05 loss: 0.0973 (0.0908) time: 3.0292 data: 0.0075 max mem: 33408 +Epoch: [9] [2200/2639] eta: 0:22:07 lr: 3.878659030662513e-05 loss: 0.0899 (0.0908) time: 3.0596 data: 0.0074 max mem: 33408 +Epoch: [9] [2210/2639] eta: 0:21:37 lr: 3.878220530128208e-05 loss: 0.0777 (0.0908) time: 3.0778 data: 0.0078 max mem: 33408 +Epoch: [9] [2220/2639] eta: 0:21:07 lr: 3.87778202408493e-05 loss: 0.0830 (0.0908) time: 3.0589 data: 0.0078 max mem: 33408 +Epoch: [9] [2230/2639] eta: 0:20:37 lr: 3.8773435125319154e-05 loss: 0.0758 (0.0907) time: 3.0597 data: 0.0082 max mem: 33408 +Epoch: [9] [2240/2639] eta: 0:20:06 lr: 3.8769049954684054e-05 loss: 0.0739 (0.0908) time: 3.0338 data: 0.0088 max mem: 33408 +Epoch: [9] [2250/2639] eta: 0:19:36 lr: 3.876466472893636e-05 loss: 0.0968 (0.0909) time: 3.0405 data: 0.0080 max mem: 33408 +Epoch: [9] [2260/2639] eta: 0:19:06 lr: 3.876027944806847e-05 loss: 0.0885 (0.0908) time: 3.0456 data: 0.0078 max mem: 33408 +Epoch: [9] [2270/2639] eta: 0:18:36 lr: 3.8755894112072735e-05 loss: 0.0795 (0.0908) time: 3.0528 data: 0.0079 max mem: 33408 +Epoch: [9] [2280/2639] eta: 0:18:06 lr: 3.875150872094157e-05 loss: 0.0795 (0.0908) time: 3.0382 data: 0.0074 max mem: 33408 +Epoch: [9] [2290/2639] eta: 0:17:35 lr: 3.874712327466731e-05 loss: 0.0823 (0.0907) time: 3.0210 data: 0.0072 max mem: 33408 +Epoch: [9] [2300/2639] eta: 0:17:05 lr: 3.874273777324234e-05 loss: 0.0778 (0.0907) time: 3.0337 data: 0.0075 max mem: 33408 +Epoch: [9] [2310/2639] eta: 0:16:35 lr: 3.8738352216659044e-05 loss: 0.0792 (0.0906) time: 3.0279 data: 0.0080 max mem: 33408 +Epoch: [9] [2320/2639] eta: 0:16:05 lr: 3.8733966604909785e-05 loss: 0.0874 (0.0907) time: 3.0225 data: 0.0079 max mem: 33408 +Epoch: [9] [2330/2639] eta: 0:15:34 lr: 3.872958093798691e-05 loss: 0.0875 (0.0907) time: 3.0795 data: 0.0085 max mem: 33408 +Epoch: [9] [2340/2639] eta: 0:15:04 lr: 3.8725195215882806e-05 loss: 0.0668 (0.0906) time: 3.1021 data: 0.0084 max mem: 33408 +Epoch: [9] [2350/2639] eta: 0:14:34 lr: 3.872080943858982e-05 loss: 0.0663 (0.0906) time: 3.0403 data: 0.0080 max mem: 33408 +Epoch: [9] [2360/2639] eta: 0:14:04 lr: 3.8716423606100325e-05 loss: 0.0871 (0.0907) time: 3.0124 data: 0.0081 max mem: 33408 +Epoch: [9] [2370/2639] eta: 0:13:33 lr: 3.871203771840665e-05 loss: 0.0871 (0.0906) time: 3.0257 data: 0.0083 max mem: 33408 +Epoch: [9] [2380/2639] eta: 0:13:03 lr: 3.8707651775501186e-05 loss: 0.0857 (0.0906) time: 3.0331 data: 0.0085 max mem: 33408 +Epoch: [9] [2390/2639] eta: 0:12:33 lr: 3.870326577737627e-05 loss: 0.0869 (0.0907) time: 3.0345 data: 0.0079 max mem: 33408 +Epoch: [9] [2400/2639] eta: 0:12:03 lr: 3.8698879724024253e-05 loss: 0.0717 (0.0907) time: 3.0151 data: 0.0073 max mem: 33408 +Epoch: [9] [2410/2639] eta: 0:11:32 lr: 3.8694493615437485e-05 loss: 0.0671 (0.0907) time: 3.0312 data: 0.0076 max mem: 33408 +Epoch: [9] [2420/2639] eta: 0:11:02 lr: 3.869010745160832e-05 loss: 0.0842 (0.0908) time: 3.0543 data: 0.0081 max mem: 33408 +Epoch: [9] [2430/2639] eta: 0:10:32 lr: 3.8685721232529096e-05 loss: 0.0996 (0.0908) time: 3.0252 data: 0.0077 max mem: 33408 +Epoch: [9] [2440/2639] eta: 0:10:02 lr: 3.868133495819215e-05 loss: 0.0956 (0.0908) time: 3.0094 data: 0.0080 max mem: 33408 +Epoch: [9] [2450/2639] eta: 0:09:31 lr: 3.8676948628589845e-05 loss: 0.0789 (0.0908) time: 3.0101 data: 0.0083 max mem: 33408 +Epoch: [9] [2460/2639] eta: 0:09:01 lr: 3.86725622437145e-05 loss: 0.0675 (0.0907) time: 3.0307 data: 0.0077 max mem: 33408 +Epoch: [9] [2470/2639] eta: 0:08:31 lr: 3.866817580355847e-05 loss: 0.0943 (0.0908) time: 3.0279 data: 0.0073 max mem: 33408 +Epoch: [9] [2480/2639] eta: 0:08:01 lr: 3.866378930811407e-05 loss: 0.0943 (0.0909) time: 3.0055 data: 0.0072 max mem: 33408 +Epoch: [9] [2490/2639] eta: 0:07:30 lr: 3.865940275737366e-05 loss: 0.0820 (0.0908) time: 3.0354 data: 0.0073 max mem: 33408 +Epoch: [9] [2500/2639] eta: 0:07:00 lr: 3.865501615132954e-05 loss: 0.0742 (0.0908) time: 3.0367 data: 0.0076 max mem: 33408 +Epoch: [9] [2510/2639] eta: 0:06:30 lr: 3.865062948997407e-05 loss: 0.0761 (0.0908) time: 3.0040 data: 0.0077 max mem: 33408 +Epoch: [9] [2520/2639] eta: 0:06:00 lr: 3.8646242773299553e-05 loss: 0.0749 (0.0907) time: 3.0043 data: 0.0078 max mem: 33408 +Epoch: [9] [2530/2639] eta: 0:05:29 lr: 3.8641856001298325e-05 loss: 0.0778 (0.0907) time: 3.0212 data: 0.0081 max mem: 33408 +Epoch: [9] [2540/2639] eta: 0:04:59 lr: 3.863746917396271e-05 loss: 0.0889 (0.0907) time: 3.0418 data: 0.0080 max mem: 33408 +Epoch: [9] [2550/2639] eta: 0:04:29 lr: 3.863308229128502e-05 loss: 0.0864 (0.0908) time: 3.0318 data: 0.0076 max mem: 33408 +Epoch: [9] [2560/2639] eta: 0:03:59 lr: 3.8628695353257596e-05 loss: 0.0827 (0.0908) time: 3.0442 data: 0.0078 max mem: 33408 +Epoch: [9] [2570/2639] eta: 0:03:28 lr: 3.862430835987273e-05 loss: 0.1024 (0.0908) time: 3.0537 data: 0.0079 max mem: 33408 +Epoch: [9] [2580/2639] eta: 0:02:58 lr: 3.861992131112275e-05 loss: 0.0784 (0.0908) time: 3.0563 data: 0.0079 max mem: 33408 +Epoch: [9] [2590/2639] eta: 0:02:28 lr: 3.861553420699997e-05 loss: 0.0779 (0.0908) time: 3.0719 data: 0.0081 max mem: 33408 +Epoch: [9] [2600/2639] eta: 0:01:58 lr: 3.861114704749669e-05 loss: 0.0770 (0.0908) time: 3.0253 data: 0.0078 max mem: 33408 +Epoch: [9] [2610/2639] eta: 0:01:27 lr: 3.860675983260523e-05 loss: 0.0844 (0.0910) time: 3.0356 data: 0.0075 max mem: 33408 +Epoch: [9] [2620/2639] eta: 0:00:57 lr: 3.86023725623179e-05 loss: 0.0797 (0.0910) time: 3.0339 data: 0.0072 max mem: 33408 +Epoch: [9] [2630/2639] eta: 0:00:27 lr: 3.8597985236626986e-05 loss: 0.0740 (0.0909) time: 3.0202 data: 0.0072 max mem: 33408 +Epoch: [9] Total time: 2:13:07 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 2:15:00 time: 3.1485 data: 3.0593 max mem: 33408 +Test: [ 100/2573] eta: 0:04:28 time: 0.0790 data: 0.0015 max mem: 33408 +Test: [ 200/2573] eta: 0:03:45 time: 0.0804 data: 0.0013 max mem: 33408 +Test: [ 300/2573] eta: 0:03:24 time: 0.0817 data: 0.0015 max mem: 33408 +Test: [ 400/2573] eta: 0:03:09 time: 0.0816 data: 0.0014 max mem: 33408 +Test: [ 500/2573] eta: 0:02:58 time: 0.0799 data: 0.0015 max mem: 33408 +Test: [ 600/2573] eta: 0:02:47 time: 0.0798 data: 0.0016 max mem: 33408 +Test: [ 700/2573] eta: 0:02:38 time: 0.0800 data: 0.0014 max mem: 33408 +Test: [ 800/2573] eta: 0:02:29 time: 0.0840 data: 0.0014 max mem: 33408 +Test: [ 900/2573] eta: 0:02:20 time: 0.0806 data: 0.0014 max mem: 33408 +Test: [1000/2573] eta: 0:02:11 time: 0.0811 data: 0.0015 max mem: 33408 +Test: [1100/2573] eta: 0:02:02 time: 0.0803 data: 0.0015 max mem: 33408 +Test: [1200/2573] eta: 0:01:54 time: 0.0809 data: 0.0014 max mem: 33408 +Test: [1300/2573] eta: 0:01:45 time: 0.0814 data: 0.0015 max mem: 33408 +Test: [1400/2573] eta: 0:01:37 time: 0.0802 data: 0.0015 max mem: 33408 +Test: [1500/2573] eta: 0:01:28 time: 0.0814 data: 0.0015 max mem: 33408 +Test: [1600/2573] eta: 0:01:20 time: 0.0833 data: 0.0014 max mem: 33408 +Test: [1700/2573] eta: 0:01:12 time: 0.0787 data: 0.0014 max mem: 33408 +Test: [1800/2573] eta: 0:01:03 time: 0.0821 data: 0.0016 max mem: 33408 +Test: [1900/2573] eta: 0:00:55 time: 0.0785 data: 0.0014 max mem: 33408 +Test: [2000/2573] eta: 0:00:47 time: 0.0803 data: 0.0015 max mem: 33408 +Test: [2100/2573] eta: 0:00:38 time: 0.0829 data: 0.0015 max mem: 33408 +Test: [2200/2573] eta: 0:00:30 time: 0.0820 data: 0.0014 max mem: 33408 +Test: [2300/2573] eta: 0:00:22 time: 0.0829 data: 0.0016 max mem: 33408 +Test: [2400/2573] eta: 0:00:14 time: 0.0784 data: 0.0015 max mem: 33408 +Test: [2500/2573] eta: 0:00:05 time: 0.0799 data: 0.0014 max mem: 33408 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: Total time: 0:03:31 +Final results: +Mean IoU is 59.70 + + precision@0.5 = 66.95 + precision@0.6 = 61.15 + precision@0.7 = 53.33 + precision@0.8 = 40.79 + precision@0.9 = 18.10 + overall IoU = 58.99 + +Average object IoU 59.704086131323805 +Overall IoU 58.99250411987305 +Better epoch: 9 + +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [10] [ 0/2639] eta: 4:00:11 lr: 3.8594036596128766e-05 loss: 0.1091 (0.1091) time: 5.4609 data: 2.2363 max mem: 33408 +Epoch: [10] [ 10/2639] eta: 2:26:31 lr: 3.8589649165149864e-05 loss: 0.0947 (0.0879) time: 3.3441 data: 0.2108 max mem: 33408 +Epoch: [10] [ 20/2639] eta: 2:22:20 lr: 3.858526167874506e-05 loss: 0.0820 (0.0865) time: 3.1510 data: 0.0078 max mem: 33408 +Epoch: [10] [ 30/2639] eta: 2:19:29 lr: 3.858087413690667e-05 loss: 0.0820 (0.0861) time: 3.1333 data: 0.0074 max mem: 33408 +Epoch: [10] [ 40/2639] eta: 2:17:07 lr: 3.8576486539626965e-05 loss: 0.0759 (0.0858) time: 3.0653 data: 0.0079 max mem: 33408 +Epoch: [10] [ 50/2639] eta: 2:15:45 lr: 3.8572098886898245e-05 loss: 0.0705 (0.0826) time: 3.0502 data: 0.0080 max mem: 33408 +Epoch: [10] [ 60/2639] eta: 2:13:57 lr: 3.85677111787128e-05 loss: 0.0728 (0.0848) time: 3.0157 data: 0.0079 max mem: 33408 +Epoch: [10] [ 70/2639] eta: 2:12:52 lr: 3.856332341506292e-05 loss: 0.0857 (0.0871) time: 2.9936 data: 0.0078 max mem: 33408 +Epoch: [10] [ 80/2639] eta: 2:11:42 lr: 3.85589355959409e-05 loss: 0.0741 (0.0871) time: 3.0018 data: 0.0076 max mem: 33408 +Epoch: [10] [ 90/2639] eta: 2:11:11 lr: 3.855454772133902e-05 loss: 0.0730 (0.0853) time: 3.0337 data: 0.0076 max mem: 33408 +Epoch: [10] [ 100/2639] eta: 2:10:04 lr: 3.855015979124954e-05 loss: 0.0730 (0.0847) time: 3.0164 data: 0.0074 max mem: 33408 +Epoch: [10] [ 110/2639] eta: 2:09:42 lr: 3.854577180566478e-05 loss: 0.0789 (0.0858) time: 3.0288 data: 0.0077 max mem: 33408 +Epoch: [10] [ 120/2639] eta: 2:09:01 lr: 3.8541383764577e-05 loss: 0.0892 (0.0853) time: 3.0691 data: 0.0079 max mem: 33408 +Epoch: [10] [ 130/2639] eta: 2:08:17 lr: 3.853699566797846e-05 loss: 0.0801 (0.0858) time: 3.0156 data: 0.0080 max mem: 33408 +Epoch: [10] [ 140/2639] eta: 2:07:33 lr: 3.853260751586146e-05 loss: 0.0801 (0.0849) time: 2.9985 data: 0.0079 max mem: 33408 +Epoch: [10] [ 150/2639] eta: 2:06:59 lr: 3.8528219308218254e-05 loss: 0.0807 (0.0849) time: 3.0177 data: 0.0078 max mem: 33408 +Epoch: [10] [ 160/2639] eta: 2:06:13 lr: 3.852383104504113e-05 loss: 0.0771 (0.0843) time: 3.0010 data: 0.0079 max mem: 33408 +Epoch: [10] [ 170/2639] eta: 2:05:42 lr: 3.851944272632235e-05 loss: 0.0770 (0.0846) time: 3.0074 data: 0.0076 max mem: 33408 +Epoch: [10] [ 180/2639] eta: 2:05:13 lr: 3.851505435205416e-05 loss: 0.0770 (0.0838) time: 3.0609 data: 0.0074 max mem: 33408 +Epoch: [10] [ 190/2639] eta: 2:04:36 lr: 3.851066592222885e-05 loss: 0.0705 (0.0838) time: 3.0368 data: 0.0078 max mem: 33408 +Epoch: [10] [ 200/2639] eta: 2:04:00 lr: 3.850627743683868e-05 loss: 0.0705 (0.0840) time: 3.0052 data: 0.0077 max mem: 33408 +Epoch: [10] [ 210/2639] eta: 2:03:25 lr: 3.8501888895875895e-05 loss: 0.0700 (0.0837) time: 3.0093 data: 0.0078 max mem: 33408 +Epoch: [10] [ 220/2639] eta: 2:02:54 lr: 3.849750029933276e-05 loss: 0.0700 (0.0837) time: 3.0295 data: 0.0085 max mem: 33408 +Epoch: [10] [ 230/2639] eta: 2:02:27 lr: 3.849311164720153e-05 loss: 0.0693 (0.0831) time: 3.0598 data: 0.0084 max mem: 33408 +Epoch: [10] [ 240/2639] eta: 2:01:56 lr: 3.848872293947447e-05 loss: 0.0693 (0.0831) time: 3.0609 data: 0.0079 max mem: 33408 +Epoch: [10] [ 250/2639] eta: 2:01:22 lr: 3.848433417614382e-05 loss: 0.0831 (0.0837) time: 3.0329 data: 0.0080 max mem: 33408 +Epoch: [10] [ 260/2639] eta: 2:00:47 lr: 3.847994535720183e-05 loss: 0.0862 (0.0840) time: 3.0079 data: 0.0082 max mem: 33408 +Epoch: [10] [ 270/2639] eta: 2:00:14 lr: 3.847555648264075e-05 loss: 0.0844 (0.0838) time: 3.0092 data: 0.0080 max mem: 33408 +Epoch: [10] [ 280/2639] eta: 1:59:55 lr: 3.847116755245283e-05 loss: 0.0815 (0.0842) time: 3.0990 data: 0.0076 max mem: 33408 +Epoch: [10] [ 290/2639] eta: 1:59:20 lr: 3.846677856663031e-05 loss: 0.0781 (0.0838) time: 3.0850 data: 0.0075 max mem: 33408 +Epoch: [10] [ 300/2639] eta: 1:58:47 lr: 3.8462389525165424e-05 loss: 0.0781 (0.0842) time: 3.0028 data: 0.0078 max mem: 33408 +Epoch: [10] [ 310/2639] eta: 1:58:08 lr: 3.8458000428050414e-05 loss: 0.0737 (0.0837) time: 2.9780 data: 0.0079 max mem: 33408 +Epoch: [10] [ 320/2639] eta: 1:57:32 lr: 3.845361127527753e-05 loss: 0.0651 (0.0836) time: 2.9557 data: 0.0080 max mem: 33408 +Epoch: [10] [ 330/2639] eta: 1:57:02 lr: 3.844922206683901e-05 loss: 0.0759 (0.0837) time: 3.0024 data: 0.0081 max mem: 33408 +Epoch: [10] [ 340/2639] eta: 1:56:30 lr: 3.8444832802727055e-05 loss: 0.0782 (0.0838) time: 3.0334 data: 0.0078 max mem: 33408 +Epoch: [10] [ 350/2639] eta: 1:55:58 lr: 3.844044348293393e-05 loss: 0.0691 (0.0833) time: 3.0200 data: 0.0077 max mem: 33408 +Epoch: [10] [ 360/2639] eta: 1:55:29 lr: 3.843605410745184e-05 loss: 0.0627 (0.0827) time: 3.0332 data: 0.0075 max mem: 33408 +Epoch: [10] [ 370/2639] eta: 1:54:57 lr: 3.843166467627303e-05 loss: 0.0579 (0.0826) time: 3.0388 data: 0.0077 max mem: 33408 +Epoch: [10] [ 380/2639] eta: 1:54:27 lr: 3.8427275189389725e-05 loss: 0.0650 (0.0822) time: 3.0369 data: 0.0077 max mem: 33408 +Epoch: [10] [ 390/2639] eta: 1:53:59 lr: 3.842288564679413e-05 loss: 0.0695 (0.0822) time: 3.0594 data: 0.0078 max mem: 33408 +Epoch: [10] [ 400/2639] eta: 1:53:26 lr: 3.8418496048478474e-05 loss: 0.0700 (0.0821) time: 3.0314 data: 0.0078 max mem: 33408 +Epoch: [10] [ 410/2639] eta: 1:52:54 lr: 3.841410639443499e-05 loss: 0.0758 (0.0819) time: 3.0099 data: 0.0077 max mem: 33408 +Epoch: [10] [ 420/2639] eta: 1:52:20 lr: 3.840971668465588e-05 loss: 0.0758 (0.0822) time: 2.9982 data: 0.0079 max mem: 33408 +Epoch: [10] [ 430/2639] eta: 1:51:48 lr: 3.840532691913336e-05 loss: 0.0578 (0.0821) time: 2.9867 data: 0.0078 max mem: 33408 +Epoch: [10] [ 440/2639] eta: 1:51:14 lr: 3.840093709785964e-05 loss: 0.0610 (0.0822) time: 2.9768 data: 0.0080 max mem: 33408 +Epoch: [10] [ 450/2639] eta: 1:50:41 lr: 3.839654722082694e-05 loss: 0.0906 (0.0827) time: 2.9746 data: 0.0082 max mem: 33408 +Epoch: [10] [ 460/2639] eta: 1:50:07 lr: 3.8392157288027466e-05 loss: 0.0875 (0.0826) time: 2.9676 data: 0.0080 max mem: 33408 +Epoch: [10] [ 470/2639] eta: 1:49:31 lr: 3.8387767299453416e-05 loss: 0.0664 (0.0824) time: 2.9324 data: 0.0084 max mem: 33408 +Epoch: [10] [ 480/2639] eta: 1:48:57 lr: 3.8383377255096996e-05 loss: 0.0664 (0.0823) time: 2.9284 data: 0.0085 max mem: 33408 +Epoch: [10] [ 490/2639] eta: 1:48:27 lr: 3.837898715495042e-05 loss: 0.0745 (0.0825) time: 2.9911 data: 0.0080 max mem: 33408 +Epoch: [10] [ 500/2639] eta: 1:47:57 lr: 3.837459699900588e-05 loss: 0.0825 (0.0826) time: 3.0435 data: 0.0083 max mem: 33408 +Epoch: [10] [ 510/2639] eta: 1:47:25 lr: 3.837020678725556e-05 loss: 0.0718 (0.0825) time: 3.0031 data: 0.0084 max mem: 33408 +Epoch: [10] [ 520/2639] eta: 1:46:55 lr: 3.836581651969168e-05 loss: 0.0808 (0.0827) time: 3.0028 data: 0.0079 max mem: 33408 +Epoch: [10] [ 530/2639] eta: 1:46:22 lr: 3.836142619630642e-05 loss: 0.0855 (0.0827) time: 2.9999 data: 0.0081 max mem: 33408 +Epoch: [10] [ 540/2639] eta: 1:45:54 lr: 3.8357035817091974e-05 loss: 0.0769 (0.0826) time: 3.0230 data: 0.0081 max mem: 33408 +Epoch: [10] [ 550/2639] eta: 1:45:22 lr: 3.835264538204053e-05 loss: 0.0718 (0.0826) time: 3.0367 data: 0.0077 max mem: 33408 +Epoch: [10] [ 560/2639] eta: 1:44:52 lr: 3.834825489114428e-05 loss: 0.0674 (0.0822) time: 3.0071 data: 0.0079 max mem: 33408 +Epoch: [10] [ 570/2639] eta: 1:44:21 lr: 3.834386434439541e-05 loss: 0.0693 (0.0822) time: 3.0229 data: 0.0084 max mem: 33408 +Epoch: [10] [ 580/2639] eta: 1:43:51 lr: 3.83394737417861e-05 loss: 0.0693 (0.0822) time: 3.0232 data: 0.0083 max mem: 33408 +Epoch: [10] [ 590/2639] eta: 1:43:19 lr: 3.833508308330853e-05 loss: 0.0644 (0.0821) time: 3.0028 data: 0.0083 max mem: 33408 +Epoch: [10] [ 600/2639] eta: 1:42:50 lr: 3.8330692368954874e-05 loss: 0.0688 (0.0820) time: 3.0202 data: 0.0082 max mem: 33408 +Epoch: [10] [ 610/2639] eta: 1:42:20 lr: 3.8326301598717326e-05 loss: 0.0729 (0.0819) time: 3.0404 data: 0.0078 max mem: 33408 +Epoch: [10] [ 620/2639] eta: 1:41:50 lr: 3.8321910772588045e-05 loss: 0.0783 (0.0820) time: 3.0408 data: 0.0078 max mem: 33408 +Epoch: [10] [ 630/2639] eta: 1:41:21 lr: 3.831751989055922e-05 loss: 0.0712 (0.0818) time: 3.0592 data: 0.0078 max mem: 33408 +Epoch: [10] [ 640/2639] eta: 1:40:50 lr: 3.8313128952623e-05 loss: 0.0830 (0.0821) time: 3.0276 data: 0.0077 max mem: 33408 +Epoch: [10] [ 650/2639] eta: 1:40:23 lr: 3.8308737958771564e-05 loss: 0.0909 (0.0822) time: 3.0688 data: 0.0077 max mem: 33408 +Epoch: [10] [ 660/2639] eta: 1:39:52 lr: 3.8304346908997084e-05 loss: 0.0703 (0.0820) time: 3.0763 data: 0.0080 max mem: 33408 +Epoch: [10] [ 670/2639] eta: 1:39:24 lr: 3.829995580329172e-05 loss: 0.0604 (0.0819) time: 3.0425 data: 0.0081 max mem: 33408 +Epoch: [10] [ 680/2639] eta: 1:38:55 lr: 3.829556464164764e-05 loss: 0.0574 (0.0817) time: 3.0764 data: 0.0078 max mem: 33408 +Epoch: [10] [ 690/2639] eta: 1:38:25 lr: 3.8291173424056985e-05 loss: 0.0691 (0.0816) time: 3.0571 data: 0.0087 max mem: 33408 +Epoch: [10] [ 700/2639] eta: 1:37:55 lr: 3.828678215051194e-05 loss: 0.0682 (0.0814) time: 3.0422 data: 0.0090 max mem: 33408 +Epoch: [10] [ 710/2639] eta: 1:37:26 lr: 3.828239082100465e-05 loss: 0.0685 (0.0818) time: 3.0612 data: 0.0088 max mem: 33408 +Epoch: [10] [ 720/2639] eta: 1:36:54 lr: 3.827799943552726e-05 loss: 0.0744 (0.0817) time: 3.0247 data: 0.0087 max mem: 33408 +Epoch: [10] [ 730/2639] eta: 1:36:24 lr: 3.827360799407192e-05 loss: 0.0775 (0.0819) time: 3.0136 data: 0.0082 max mem: 33408 +Epoch: [10] [ 740/2639] eta: 1:35:54 lr: 3.826921649663081e-05 loss: 0.0775 (0.0819) time: 3.0350 data: 0.0081 max mem: 33408 +Epoch: [10] [ 750/2639] eta: 1:35:22 lr: 3.826482494319605e-05 loss: 0.0652 (0.0818) time: 2.9969 data: 0.0084 max mem: 33408 +Epoch: [10] [ 760/2639] eta: 1:34:52 lr: 3.826043333375978e-05 loss: 0.0652 (0.0816) time: 3.0193 data: 0.0083 max mem: 33408 +Epoch: [10] [ 770/2639] eta: 1:34:23 lr: 3.8256041668314165e-05 loss: 0.0649 (0.0816) time: 3.0613 data: 0.0084 max mem: 33408 +Epoch: [10] [ 780/2639] eta: 1:33:53 lr: 3.825164994685134e-05 loss: 0.0690 (0.0817) time: 3.0459 data: 0.0085 max mem: 33408 +Epoch: [10] [ 790/2639] eta: 1:33:23 lr: 3.8247258169363446e-05 loss: 0.0762 (0.0820) time: 3.0412 data: 0.0082 max mem: 33408 +Epoch: [10] [ 800/2639] eta: 1:32:52 lr: 3.82428663358426e-05 loss: 0.0762 (0.0819) time: 3.0293 data: 0.0079 max mem: 33408 +Epoch: [10] [ 810/2639] eta: 1:32:21 lr: 3.823847444628096e-05 loss: 0.0789 (0.0819) time: 2.9956 data: 0.0079 max mem: 33408 +Epoch: [10] [ 820/2639] eta: 1:31:50 lr: 3.8234082500670656e-05 loss: 0.0805 (0.0820) time: 2.9933 data: 0.0082 max mem: 33408 +Epoch: [10] [ 830/2639] eta: 1:31:18 lr: 3.822969049900381e-05 loss: 0.0869 (0.0821) time: 2.9948 data: 0.0083 max mem: 33408 +Epoch: [10] [ 840/2639] eta: 1:30:48 lr: 3.822529844127256e-05 loss: 0.0670 (0.0821) time: 3.0073 data: 0.0079 max mem: 33408 +Epoch: [10] [ 850/2639] eta: 1:30:20 lr: 3.822090632746902e-05 loss: 0.0604 (0.0820) time: 3.0733 data: 0.0078 max mem: 33408 +Epoch: [10] [ 860/2639] eta: 1:29:50 lr: 3.8216514157585324e-05 loss: 0.0655 (0.0819) time: 3.0832 data: 0.0081 max mem: 33408 +Epoch: [10] [ 870/2639] eta: 1:29:20 lr: 3.8212121931613595e-05 loss: 0.0697 (0.0819) time: 3.0457 data: 0.0079 max mem: 33408 +Epoch: [10] [ 880/2639] eta: 1:28:51 lr: 3.820772964954596e-05 loss: 0.0698 (0.0819) time: 3.0748 data: 0.0081 max mem: 33408 +Epoch: [10] [ 890/2639] eta: 1:28:20 lr: 3.820333731137452e-05 loss: 0.0720 (0.0820) time: 3.0595 data: 0.0081 max mem: 33408 +Epoch: [10] [ 900/2639] eta: 1:27:51 lr: 3.819894491709139e-05 loss: 0.0871 (0.0822) time: 3.0381 data: 0.0078 max mem: 33408 +Epoch: [10] [ 910/2639] eta: 1:27:20 lr: 3.819455246668871e-05 loss: 0.0912 (0.0823) time: 3.0292 data: 0.0079 max mem: 33408 +Epoch: [10] [ 920/2639] eta: 1:26:50 lr: 3.8190159960158575e-05 loss: 0.0733 (0.0823) time: 3.0237 data: 0.0077 max mem: 33408 +Epoch: [10] [ 930/2639] eta: 1:26:19 lr: 3.818576739749308e-05 loss: 0.0733 (0.0823) time: 3.0322 data: 0.0077 max mem: 33408 +Epoch: [10] [ 940/2639] eta: 1:25:47 lr: 3.818137477868436e-05 loss: 0.0835 (0.0824) time: 2.9822 data: 0.0077 max mem: 33408 +Epoch: [10] [ 950/2639] eta: 1:25:17 lr: 3.81769821037245e-05 loss: 0.0883 (0.0826) time: 2.9826 data: 0.0075 max mem: 33408 +Epoch: [10] [ 960/2639] eta: 1:24:47 lr: 3.8172589372605624e-05 loss: 0.0784 (0.0827) time: 3.0216 data: 0.0077 max mem: 33408 +Epoch: [10] [ 970/2639] eta: 1:24:17 lr: 3.8168196585319805e-05 loss: 0.0754 (0.0827) time: 3.0456 data: 0.0084 max mem: 33408 +Epoch: [10] [ 980/2639] eta: 1:23:45 lr: 3.816380374185917e-05 loss: 0.0734 (0.0826) time: 3.0147 data: 0.0083 max mem: 33408 +Epoch: [10] [ 990/2639] eta: 1:23:16 lr: 3.8159410842215796e-05 loss: 0.0856 (0.0828) time: 3.0222 data: 0.0078 max mem: 33408 +Epoch: [10] [1000/2639] eta: 1:22:45 lr: 3.815501788638179e-05 loss: 0.0798 (0.0827) time: 3.0312 data: 0.0082 max mem: 33408 +Epoch: [10] [1010/2639] eta: 1:22:14 lr: 3.815062487434924e-05 loss: 0.0798 (0.0829) time: 2.9995 data: 0.0083 max mem: 33408 +Epoch: [10] [1020/2639] eta: 1:21:44 lr: 3.814623180611023e-05 loss: 0.0885 (0.0830) time: 3.0059 data: 0.0079 max mem: 33408 +Epoch: [10] [1030/2639] eta: 1:21:14 lr: 3.8141838681656864e-05 loss: 0.0827 (0.0830) time: 3.0279 data: 0.0078 max mem: 33408 +Epoch: [10] [1040/2639] eta: 1:20:42 lr: 3.813744550098122e-05 loss: 0.0718 (0.0830) time: 3.0132 data: 0.0081 max mem: 33408 +Epoch: [10] [1050/2639] eta: 1:20:13 lr: 3.813305226407538e-05 loss: 0.0688 (0.0829) time: 3.0180 data: 0.0083 max mem: 33408 +Epoch: [10] [1060/2639] eta: 1:19:42 lr: 3.812865897093143e-05 loss: 0.0671 (0.0829) time: 3.0372 data: 0.0086 max mem: 33408 +Epoch: [10] [1070/2639] eta: 1:19:12 lr: 3.812426562154145e-05 loss: 0.0662 (0.0828) time: 3.0177 data: 0.0084 max mem: 33408 +Epoch: [10] [1080/2639] eta: 1:18:43 lr: 3.8119872215897515e-05 loss: 0.0662 (0.0827) time: 3.0726 data: 0.0081 max mem: 33408 +Epoch: [10] [1090/2639] eta: 1:18:13 lr: 3.81154787539917e-05 loss: 0.0794 (0.0827) time: 3.0756 data: 0.0084 max mem: 33408 +Epoch: [10] [1100/2639] eta: 1:17:42 lr: 3.811108523581608e-05 loss: 0.0850 (0.0828) time: 3.0324 data: 0.0081 max mem: 33408 +Epoch: [10] [1110/2639] eta: 1:17:12 lr: 3.810669166136272e-05 loss: 0.0887 (0.0829) time: 3.0139 data: 0.0077 max mem: 33408 +Epoch: [10] [1120/2639] eta: 1:16:40 lr: 3.8102298030623714e-05 loss: 0.0890 (0.0831) time: 2.9815 data: 0.0078 max mem: 33408 +Epoch: [10] [1130/2639] eta: 1:16:10 lr: 3.8097904343591106e-05 loss: 0.0856 (0.0831) time: 3.0094 data: 0.0082 max mem: 33408 +Epoch: [10] [1140/2639] eta: 1:15:40 lr: 3.809351060025696e-05 loss: 0.0920 (0.0833) time: 3.0181 data: 0.0084 max mem: 33408 +Epoch: [10] [1150/2639] eta: 1:15:10 lr: 3.8089116800613344e-05 loss: 0.0911 (0.0833) time: 3.0258 data: 0.0079 max mem: 33408 +Epoch: [10] [1160/2639] eta: 1:14:39 lr: 3.808472294465233e-05 loss: 0.0808 (0.0833) time: 3.0456 data: 0.0076 max mem: 33408 +Epoch: [10] [1170/2639] eta: 1:14:09 lr: 3.808032903236597e-05 loss: 0.0808 (0.0833) time: 3.0155 data: 0.0081 max mem: 33408 +Epoch: [10] [1180/2639] eta: 1:13:40 lr: 3.8075935063746305e-05 loss: 0.0840 (0.0833) time: 3.0928 data: 0.0084 max mem: 33408 +Epoch: [10] [1190/2639] eta: 1:13:11 lr: 3.807154103878541e-05 loss: 0.0778 (0.0833) time: 3.1249 data: 0.0083 max mem: 33408 +Epoch: [10] [1200/2639] eta: 1:12:40 lr: 3.806714695747532e-05 loss: 0.0666 (0.0832) time: 3.0199 data: 0.0078 max mem: 33408 +Epoch: [10] [1210/2639] eta: 1:12:10 lr: 3.806275281980811e-05 loss: 0.0722 (0.0832) time: 3.0316 data: 0.0075 max mem: 33408 +Epoch: [10] [1220/2639] eta: 1:11:40 lr: 3.8058358625775805e-05 loss: 0.0787 (0.0832) time: 3.0855 data: 0.0081 max mem: 33408 +Epoch: [10] [1230/2639] eta: 1:11:09 lr: 3.805396437537045e-05 loss: 0.0715 (0.0833) time: 3.0250 data: 0.0082 max mem: 33408 +Epoch: [10] [1240/2639] eta: 1:10:39 lr: 3.804957006858411e-05 loss: 0.0674 (0.0832) time: 3.0144 data: 0.0077 max mem: 33408 +Epoch: [10] [1250/2639] eta: 1:10:08 lr: 3.8045175705408806e-05 loss: 0.0641 (0.0832) time: 3.0063 data: 0.0080 max mem: 33408 +Epoch: [10] [1260/2639] eta: 1:09:39 lr: 3.8040781285836585e-05 loss: 0.0705 (0.0831) time: 3.0384 data: 0.0079 max mem: 33408 +Epoch: [10] [1270/2639] eta: 1:09:08 lr: 3.8036386809859486e-05 loss: 0.0733 (0.0833) time: 3.0340 data: 0.0075 max mem: 33408 +Epoch: [10] [1280/2639] eta: 1:08:37 lr: 3.8031992277469544e-05 loss: 0.0776 (0.0833) time: 2.9680 data: 0.0081 max mem: 33408 +Epoch: [10] [1290/2639] eta: 1:08:07 lr: 3.802759768865879e-05 loss: 0.0988 (0.0835) time: 3.0113 data: 0.0080 max mem: 33408 +Epoch: [10] [1300/2639] eta: 1:07:37 lr: 3.8023203043419255e-05 loss: 0.0877 (0.0834) time: 3.0630 data: 0.0079 max mem: 33408 +Epoch: [10] [1310/2639] eta: 1:07:07 lr: 3.8018808341742955e-05 loss: 0.0634 (0.0834) time: 3.0571 data: 0.0086 max mem: 33408 +Epoch: [10] [1320/2639] eta: 1:06:37 lr: 3.8014413583621945e-05 loss: 0.0704 (0.0834) time: 3.0486 data: 0.0092 max mem: 33408 +Epoch: [10] [1330/2639] eta: 1:06:07 lr: 3.8010018769048236e-05 loss: 0.0622 (0.0832) time: 3.0599 data: 0.0089 max mem: 33408 +Epoch: [10] [1340/2639] eta: 1:05:36 lr: 3.800562389801383e-05 loss: 0.0689 (0.0832) time: 3.0409 data: 0.0083 max mem: 33408 +Epoch: [10] [1350/2639] eta: 1:05:06 lr: 3.8001228970510776e-05 loss: 0.0781 (0.0832) time: 3.0292 data: 0.0083 max mem: 33408 +Epoch: [10] [1360/2639] eta: 1:04:36 lr: 3.799683398653108e-05 loss: 0.0781 (0.0832) time: 3.0264 data: 0.0080 max mem: 33408 +Epoch: [10] [1370/2639] eta: 1:04:05 lr: 3.7992438946066755e-05 loss: 0.0729 (0.0832) time: 3.0324 data: 0.0075 max mem: 33408 +Epoch: [10] [1380/2639] eta: 1:03:34 lr: 3.7988043849109825e-05 loss: 0.0754 (0.0831) time: 2.9963 data: 0.0083 max mem: 33408 +Epoch: [10] [1390/2639] eta: 1:03:05 lr: 3.798364869565229e-05 loss: 0.0746 (0.0830) time: 3.0245 data: 0.0083 max mem: 33408 +Epoch: [10] [1400/2639] eta: 1:02:34 lr: 3.797925348568616e-05 loss: 0.0776 (0.0831) time: 3.0329 data: 0.0077 max mem: 33408 +Epoch: [10] [1410/2639] eta: 1:02:05 lr: 3.797485821920345e-05 loss: 0.0769 (0.0830) time: 3.0626 data: 0.0076 max mem: 33408 +Epoch: [10] [1420/2639] eta: 1:01:34 lr: 3.7970462896196164e-05 loss: 0.0657 (0.0829) time: 3.0727 data: 0.0080 max mem: 33408 +Epoch: [10] [1430/2639] eta: 1:01:04 lr: 3.7966067516656296e-05 loss: 0.0712 (0.0829) time: 3.0139 data: 0.0079 max mem: 33408 +Epoch: [10] [1440/2639] eta: 1:00:33 lr: 3.796167208057585e-05 loss: 0.0712 (0.0828) time: 3.0294 data: 0.0074 max mem: 33408 +Epoch: [10] [1450/2639] eta: 1:00:03 lr: 3.795727658794683e-05 loss: 0.0778 (0.0829) time: 3.0232 data: 0.0077 max mem: 33408 +Epoch: [10] [1460/2639] eta: 0:59:33 lr: 3.795288103876124e-05 loss: 0.0778 (0.0829) time: 3.0305 data: 0.0079 max mem: 33408 +Epoch: [10] [1470/2639] eta: 0:59:02 lr: 3.794848543301105e-05 loss: 0.0699 (0.0829) time: 3.0210 data: 0.0078 max mem: 33408 +Epoch: [10] [1480/2639] eta: 0:58:32 lr: 3.794408977068826e-05 loss: 0.0724 (0.0829) time: 3.0568 data: 0.0077 max mem: 33408 +Epoch: [10] [1490/2639] eta: 0:58:03 lr: 3.793969405178488e-05 loss: 0.0870 (0.0831) time: 3.0926 data: 0.0080 max mem: 33408 +Epoch: [10] [1500/2639] eta: 0:57:32 lr: 3.7935298276292874e-05 loss: 0.0879 (0.0832) time: 3.0396 data: 0.0081 max mem: 33408 +Epoch: [10] [1510/2639] eta: 0:57:01 lr: 3.7930902444204235e-05 loss: 0.0790 (0.0832) time: 3.0006 data: 0.0083 max mem: 33408 +Epoch: [10] [1520/2639] eta: 0:56:31 lr: 3.7926506555510946e-05 loss: 0.0883 (0.0833) time: 3.0021 data: 0.0085 max mem: 33408 +Epoch: [10] [1530/2639] eta: 0:56:01 lr: 3.7922110610205e-05 loss: 0.0883 (0.0833) time: 3.0456 data: 0.0083 max mem: 33408 +Epoch: [10] [1540/2639] eta: 0:55:30 lr: 3.7917714608278364e-05 loss: 0.0758 (0.0833) time: 3.0391 data: 0.0079 max mem: 33408 +Epoch: [10] [1550/2639] eta: 0:55:00 lr: 3.791331854972301e-05 loss: 0.0757 (0.0833) time: 3.0315 data: 0.0076 max mem: 33408 +Epoch: [10] [1560/2639] eta: 0:54:30 lr: 3.7908922434530916e-05 loss: 0.0757 (0.0833) time: 3.0314 data: 0.0076 max mem: 33408 +Epoch: [10] [1570/2639] eta: 0:53:59 lr: 3.790452626269407e-05 loss: 0.0753 (0.0833) time: 3.0060 data: 0.0078 max mem: 33408 +Epoch: [10] [1580/2639] eta: 0:53:29 lr: 3.790013003420442e-05 loss: 0.0753 (0.0833) time: 2.9922 data: 0.0075 max mem: 33408 +Epoch: [10] [1590/2639] eta: 0:52:59 lr: 3.789573374905394e-05 loss: 0.0793 (0.0834) time: 3.0263 data: 0.0076 max mem: 33408 +Epoch: [10] [1600/2639] eta: 0:52:29 lr: 3.7891337407234605e-05 loss: 0.0840 (0.0835) time: 3.0620 data: 0.0078 max mem: 33408 +Epoch: [10] [1610/2639] eta: 0:51:58 lr: 3.7886941008738375e-05 loss: 0.0839 (0.0834) time: 3.0230 data: 0.0076 max mem: 33408 +Epoch: [10] [1620/2639] eta: 0:51:28 lr: 3.788254455355721e-05 loss: 0.0797 (0.0835) time: 3.0274 data: 0.0074 max mem: 33408 +Epoch: [10] [1630/2639] eta: 0:50:57 lr: 3.787814804168308e-05 loss: 0.0797 (0.0835) time: 3.0278 data: 0.0080 max mem: 33408 +Epoch: [10] [1640/2639] eta: 0:50:28 lr: 3.787375147310791e-05 loss: 0.0797 (0.0835) time: 3.0708 data: 0.0083 max mem: 33408 +Epoch: [10] [1650/2639] eta: 0:49:58 lr: 3.786935484782369e-05 loss: 0.0793 (0.0835) time: 3.1229 data: 0.0079 max mem: 33408 +Epoch: [10] [1660/2639] eta: 0:49:27 lr: 3.786495816582236e-05 loss: 0.0729 (0.0835) time: 3.0554 data: 0.0077 max mem: 33408 +Epoch: [10] [1670/2639] eta: 0:48:57 lr: 3.786056142709587e-05 loss: 0.0733 (0.0835) time: 3.0474 data: 0.0074 max mem: 33408 +Epoch: [10] [1680/2639] eta: 0:48:27 lr: 3.785616463163616e-05 loss: 0.0655 (0.0835) time: 3.0479 data: 0.0076 max mem: 33408 +Epoch: [10] [1690/2639] eta: 0:47:57 lr: 3.78517677794352e-05 loss: 0.0730 (0.0835) time: 3.0285 data: 0.0075 max mem: 33408 +Epoch: [10] [1700/2639] eta: 0:47:27 lr: 3.7847370870484915e-05 loss: 0.0798 (0.0836) time: 3.0713 data: 0.0070 max mem: 33408 +Epoch: [10] [1710/2639] eta: 0:46:56 lr: 3.784297390477725e-05 loss: 0.0840 (0.0836) time: 3.0515 data: 0.0075 max mem: 33408 +Epoch: [10] [1720/2639] eta: 0:46:26 lr: 3.7838576882304146e-05 loss: 0.0852 (0.0836) time: 3.0476 data: 0.0078 max mem: 33408 +Epoch: [10] [1730/2639] eta: 0:45:56 lr: 3.783417980305754e-05 loss: 0.0777 (0.0836) time: 3.0504 data: 0.0078 max mem: 33408 +Epoch: [10] [1740/2639] eta: 0:45:25 lr: 3.782978266702937e-05 loss: 0.0777 (0.0836) time: 3.0090 data: 0.0077 max mem: 33408 +Epoch: [10] [1750/2639] eta: 0:44:55 lr: 3.782538547421157e-05 loss: 0.0867 (0.0837) time: 2.9873 data: 0.0077 max mem: 33408 +Epoch: [10] [1760/2639] eta: 0:44:25 lr: 3.782098822459607e-05 loss: 0.0725 (0.0836) time: 3.0382 data: 0.0076 max mem: 33408 +Epoch: [10] [1770/2639] eta: 0:43:55 lr: 3.781659091817479e-05 loss: 0.0682 (0.0836) time: 3.0782 data: 0.0074 max mem: 33408 +Epoch: [10] [1780/2639] eta: 0:43:24 lr: 3.781219355493967e-05 loss: 0.0749 (0.0835) time: 3.0367 data: 0.0074 max mem: 33408 +Epoch: [10] [1790/2639] eta: 0:42:54 lr: 3.780779613488263e-05 loss: 0.0742 (0.0835) time: 2.9920 data: 0.0074 max mem: 33408 +Epoch: [10] [1800/2639] eta: 0:42:23 lr: 3.780339865799559e-05 loss: 0.0708 (0.0835) time: 3.0168 data: 0.0076 max mem: 33408 +Epoch: [10] [1810/2639] eta: 0:41:53 lr: 3.7799001124270465e-05 loss: 0.0783 (0.0835) time: 3.0421 data: 0.0077 max mem: 33408 +Epoch: [10] [1820/2639] eta: 0:41:23 lr: 3.7794603533699184e-05 loss: 0.0834 (0.0835) time: 3.0150 data: 0.0077 max mem: 33408 +Epoch: [10] [1830/2639] eta: 0:40:53 lr: 3.7790205886273656e-05 loss: 0.0813 (0.0835) time: 3.0525 data: 0.0076 max mem: 33408 +Epoch: [10] [1840/2639] eta: 0:40:22 lr: 3.77858081819858e-05 loss: 0.0819 (0.0836) time: 3.0631 data: 0.0082 max mem: 33408 +Epoch: [10] [1850/2639] eta: 0:39:52 lr: 3.778141042082752e-05 loss: 0.0882 (0.0836) time: 3.0518 data: 0.0082 max mem: 33408 +Epoch: [10] [1860/2639] eta: 0:39:22 lr: 3.7777012602790726e-05 loss: 0.0861 (0.0837) time: 3.0499 data: 0.0078 max mem: 33408 +Epoch: [10] [1870/2639] eta: 0:38:52 lr: 3.777261472786734e-05 loss: 0.0849 (0.0837) time: 3.0396 data: 0.0078 max mem: 33408 +Epoch: [10] [1880/2639] eta: 0:38:21 lr: 3.776821679604925e-05 loss: 0.0779 (0.0837) time: 3.0307 data: 0.0079 max mem: 33408 +Epoch: [10] [1890/2639] eta: 0:37:50 lr: 3.7763818807328354e-05 loss: 0.0783 (0.0837) time: 2.9775 data: 0.0082 max mem: 33408 +Epoch: [10] [1900/2639] eta: 0:37:20 lr: 3.7759420761696564e-05 loss: 0.0833 (0.0837) time: 2.9851 data: 0.0089 max mem: 33408 +Epoch: [10] [1910/2639] eta: 0:36:50 lr: 3.7755022659145787e-05 loss: 0.0944 (0.0838) time: 3.0022 data: 0.0087 max mem: 33408 +Epoch: [10] [1920/2639] eta: 0:36:19 lr: 3.7750624499667896e-05 loss: 0.0838 (0.0838) time: 2.9702 data: 0.0082 max mem: 33408 +Epoch: [10] [1930/2639] eta: 0:35:48 lr: 3.7746226283254796e-05 loss: 0.0754 (0.0838) time: 2.9660 data: 0.0082 max mem: 33408 +Epoch: [10] [1940/2639] eta: 0:35:18 lr: 3.7741828009898374e-05 loss: 0.0904 (0.0838) time: 2.9837 data: 0.0080 max mem: 33408 +Epoch: [10] [1950/2639] eta: 0:34:48 lr: 3.7737429679590534e-05 loss: 0.0837 (0.0838) time: 3.0225 data: 0.0078 max mem: 33408 +Epoch: [10] [1960/2639] eta: 0:34:17 lr: 3.7733031292323156e-05 loss: 0.0800 (0.0838) time: 3.0236 data: 0.0078 max mem: 33408 +Epoch: [10] [1970/2639] eta: 0:33:47 lr: 3.772863284808811e-05 loss: 0.0838 (0.0838) time: 3.0351 data: 0.0077 max mem: 33408 +Epoch: [10] [1980/2639] eta: 0:33:17 lr: 3.77242343468773e-05 loss: 0.0823 (0.0839) time: 3.0177 data: 0.0076 max mem: 33408 +Epoch: [10] [1990/2639] eta: 0:32:46 lr: 3.7719835788682596e-05 loss: 0.0744 (0.0839) time: 2.9984 data: 0.0078 max mem: 33408 +Epoch: [10] [2000/2639] eta: 0:32:16 lr: 3.771543717349587e-05 loss: 0.0744 (0.0840) time: 3.0246 data: 0.0077 max mem: 33408 +Epoch: [10] [2010/2639] eta: 0:31:46 lr: 3.771103850130901e-05 loss: 0.0753 (0.0839) time: 3.0132 data: 0.0080 max mem: 33408 +Epoch: [10] [2020/2639] eta: 0:31:15 lr: 3.770663977211388e-05 loss: 0.0820 (0.0841) time: 2.9848 data: 0.0082 max mem: 33408 +Epoch: [10] [2030/2639] eta: 0:30:45 lr: 3.770224098590237e-05 loss: 0.0865 (0.0841) time: 2.9757 data: 0.0082 max mem: 33408 +Epoch: [10] [2040/2639] eta: 0:30:14 lr: 3.769784214266633e-05 loss: 0.0865 (0.0841) time: 2.9988 data: 0.0084 max mem: 33408 +Epoch: [10] [2050/2639] eta: 0:29:44 lr: 3.769344324239763e-05 loss: 0.0912 (0.0841) time: 3.0053 data: 0.0082 max mem: 33408 +Epoch: [10] [2060/2639] eta: 0:29:14 lr: 3.768904428508814e-05 loss: 0.0887 (0.0843) time: 2.9910 data: 0.0080 max mem: 33408 +Epoch: [10] [2070/2639] eta: 0:28:43 lr: 3.768464527072972e-05 loss: 0.0863 (0.0843) time: 2.9952 data: 0.0080 max mem: 33408 +Epoch: [10] [2080/2639] eta: 0:28:13 lr: 3.768024619931423e-05 loss: 0.0734 (0.0843) time: 2.9971 data: 0.0079 max mem: 33408 +Epoch: [10] [2090/2639] eta: 0:27:43 lr: 3.7675847070833535e-05 loss: 0.0580 (0.0842) time: 3.0512 data: 0.0078 max mem: 33408 +Epoch: [10] [2100/2639] eta: 0:27:12 lr: 3.767144788527948e-05 loss: 0.0700 (0.0842) time: 3.0585 data: 0.0079 max mem: 33408 +Epoch: [10] [2110/2639] eta: 0:26:42 lr: 3.766704864264393e-05 loss: 0.0792 (0.0842) time: 3.0192 data: 0.0080 max mem: 33408 +Epoch: [10] [2120/2639] eta: 0:26:12 lr: 3.7662649342918736e-05 loss: 0.0800 (0.0842) time: 3.0141 data: 0.0079 max mem: 33408 +Epoch: [10] [2130/2639] eta: 0:25:41 lr: 3.765824998609574e-05 loss: 0.0725 (0.0841) time: 3.0165 data: 0.0078 max mem: 33408 +Epoch: [10] [2140/2639] eta: 0:25:11 lr: 3.765385057216679e-05 loss: 0.0725 (0.0843) time: 3.0038 data: 0.0079 max mem: 33408 +Epoch: [10] [2150/2639] eta: 0:24:41 lr: 3.764945110112373e-05 loss: 0.0945 (0.0844) time: 3.0166 data: 0.0079 max mem: 33408 +Epoch: [10] [2160/2639] eta: 0:24:10 lr: 3.764505157295842e-05 loss: 0.0935 (0.0844) time: 3.0559 data: 0.0081 max mem: 33408 +Epoch: [10] [2170/2639] eta: 0:23:40 lr: 3.7640651987662676e-05 loss: 0.0783 (0.0844) time: 3.0388 data: 0.0082 max mem: 33408 +Epoch: [10] [2180/2639] eta: 0:23:10 lr: 3.763625234522835e-05 loss: 0.0783 (0.0844) time: 3.0183 data: 0.0083 max mem: 33408 +Epoch: [10] [2190/2639] eta: 0:22:40 lr: 3.7631852645647276e-05 loss: 0.0786 (0.0845) time: 2.9970 data: 0.0081 max mem: 33408 +Epoch: [10] [2200/2639] eta: 0:22:09 lr: 3.762745288891129e-05 loss: 0.0685 (0.0844) time: 3.0013 data: 0.0083 max mem: 33408 +Epoch: [10] [2210/2639] eta: 0:21:39 lr: 3.7623053075012215e-05 loss: 0.0556 (0.0844) time: 3.0430 data: 0.0082 max mem: 33408 +Epoch: [10] [2220/2639] eta: 0:21:09 lr: 3.761865320394189e-05 loss: 0.0655 (0.0845) time: 3.0644 data: 0.0079 max mem: 33408 +Epoch: [10] [2230/2639] eta: 0:20:38 lr: 3.7614253275692136e-05 loss: 0.0784 (0.0845) time: 3.0145 data: 0.0079 max mem: 33408 +Epoch: [10] [2240/2639] eta: 0:20:08 lr: 3.7609853290254784e-05 loss: 0.0784 (0.0844) time: 2.9778 data: 0.0076 max mem: 33408 +Epoch: [10] [2250/2639] eta: 0:19:38 lr: 3.7605453247621655e-05 loss: 0.0807 (0.0847) time: 3.0369 data: 0.0079 max mem: 33408 +Epoch: [10] [2260/2639] eta: 0:19:08 lr: 3.760105314778456e-05 loss: 0.0815 (0.0847) time: 3.0660 data: 0.0082 max mem: 33408 +Epoch: [10] [2270/2639] eta: 0:18:37 lr: 3.759665299073533e-05 loss: 0.0744 (0.0847) time: 3.0150 data: 0.0085 max mem: 33408 +Epoch: [10] [2280/2639] eta: 0:18:07 lr: 3.759225277646578e-05 loss: 0.0820 (0.0847) time: 3.0182 data: 0.0085 max mem: 33408 +Epoch: [10] [2290/2639] eta: 0:17:37 lr: 3.7587852504967726e-05 loss: 0.0800 (0.0847) time: 3.0562 data: 0.0085 max mem: 33408 +Epoch: [10] [2300/2639] eta: 0:17:06 lr: 3.7583452176232956e-05 loss: 0.0796 (0.0847) time: 3.0373 data: 0.0083 max mem: 33408 +Epoch: [10] [2310/2639] eta: 0:16:36 lr: 3.757905179025331e-05 loss: 0.0746 (0.0847) time: 3.0005 data: 0.0076 max mem: 33408 +Epoch: [10] [2320/2639] eta: 0:16:06 lr: 3.757465134702057e-05 loss: 0.0798 (0.0848) time: 3.0229 data: 0.0076 max mem: 33408 +Epoch: [10] [2330/2639] eta: 0:15:35 lr: 3.757025084652657e-05 loss: 0.0798 (0.0847) time: 3.0294 data: 0.0080 max mem: 33408 +Epoch: [10] [2340/2639] eta: 0:15:05 lr: 3.756585028876308e-05 loss: 0.0700 (0.0847) time: 3.0006 data: 0.0081 max mem: 33408 +Epoch: [10] [2350/2639] eta: 0:14:35 lr: 3.7561449673721925e-05 loss: 0.0700 (0.0847) time: 3.0385 data: 0.0081 max mem: 33408 +Epoch: [10] [2360/2639] eta: 0:14:05 lr: 3.755704900139489e-05 loss: 0.0804 (0.0847) time: 3.0474 data: 0.0078 max mem: 33408 +Epoch: [10] [2370/2639] eta: 0:13:34 lr: 3.7552648271773775e-05 loss: 0.0828 (0.0847) time: 3.0402 data: 0.0075 max mem: 33408 +Epoch: [10] [2380/2639] eta: 0:13:04 lr: 3.754824748485038e-05 loss: 0.0721 (0.0847) time: 3.0373 data: 0.0076 max mem: 33408 +Epoch: [10] [2390/2639] eta: 0:12:34 lr: 3.7543846640616483e-05 loss: 0.0762 (0.0847) time: 3.0064 data: 0.0074 max mem: 33408 +Epoch: [10] [2400/2639] eta: 0:12:03 lr: 3.7539445739063885e-05 loss: 0.0784 (0.0847) time: 3.0013 data: 0.0073 max mem: 33408 +Epoch: [10] [2410/2639] eta: 0:11:33 lr: 3.753504478018436e-05 loss: 0.0741 (0.0846) time: 2.9994 data: 0.0076 max mem: 33408 +Epoch: [10] [2420/2639] eta: 0:11:03 lr: 3.753064376396971e-05 loss: 0.0790 (0.0847) time: 2.9972 data: 0.0076 max mem: 33408 +Epoch: [10] [2430/2639] eta: 0:10:32 lr: 3.7526242690411705e-05 loss: 0.0866 (0.0847) time: 3.0249 data: 0.0075 max mem: 33408 +Epoch: [10] [2440/2639] eta: 0:10:02 lr: 3.752184155950213e-05 loss: 0.0812 (0.0847) time: 3.0408 data: 0.0074 max mem: 33408 +Epoch: [10] [2450/2639] eta: 0:09:32 lr: 3.7517440371232766e-05 loss: 0.0821 (0.0848) time: 2.9982 data: 0.0074 max mem: 33408 +Epoch: [10] [2460/2639] eta: 0:09:02 lr: 3.751303912559538e-05 loss: 0.0821 (0.0848) time: 2.9874 data: 0.0077 max mem: 33408 +Epoch: [10] [2470/2639] eta: 0:08:31 lr: 3.7508637822581745e-05 loss: 0.0792 (0.0848) time: 3.0575 data: 0.0075 max mem: 33408 +Epoch: [10] [2480/2639] eta: 0:08:01 lr: 3.7504236462183634e-05 loss: 0.0821 (0.0848) time: 3.0656 data: 0.0074 max mem: 33408 +Epoch: [10] [2490/2639] eta: 0:07:31 lr: 3.7499835044392826e-05 loss: 0.0802 (0.0848) time: 3.0332 data: 0.0078 max mem: 33408 +Epoch: [10] [2500/2639] eta: 0:07:00 lr: 3.749543356920108e-05 loss: 0.0748 (0.0848) time: 3.0055 data: 0.0078 max mem: 33408 +Epoch: [10] [2510/2639] eta: 0:06:30 lr: 3.749103203660016e-05 loss: 0.0748 (0.0848) time: 3.0391 data: 0.0080 max mem: 33408 +Epoch: [10] [2520/2639] eta: 0:06:00 lr: 3.748663044658182e-05 loss: 0.0754 (0.0849) time: 3.0543 data: 0.0079 max mem: 33408 +Epoch: [10] [2530/2639] eta: 0:05:30 lr: 3.7482228799137844e-05 loss: 0.0754 (0.0850) time: 3.0421 data: 0.0077 max mem: 33408 +Epoch: [10] [2540/2639] eta: 0:04:59 lr: 3.747782709425997e-05 loss: 0.0781 (0.0850) time: 3.0401 data: 0.0078 max mem: 33408 +Epoch: [10] [2550/2639] eta: 0:04:29 lr: 3.747342533193995e-05 loss: 0.0781 (0.0849) time: 3.0154 data: 0.0080 max mem: 33408 +Epoch: [10] [2560/2639] eta: 0:03:59 lr: 3.746902351216955e-05 loss: 0.0765 (0.0849) time: 3.0454 data: 0.0080 max mem: 33408 +Epoch: [10] [2570/2639] eta: 0:03:28 lr: 3.746462163494051e-05 loss: 0.0736 (0.0849) time: 3.0529 data: 0.0076 max mem: 33408 +Epoch: [10] [2580/2639] eta: 0:02:58 lr: 3.7460219700244593e-05 loss: 0.0652 (0.0848) time: 3.0579 data: 0.0075 max mem: 33408 +Epoch: [10] [2590/2639] eta: 0:02:28 lr: 3.7455817708073534e-05 loss: 0.0741 (0.0848) time: 3.0498 data: 0.0080 max mem: 33408 +Epoch: [10] [2600/2639] eta: 0:01:58 lr: 3.745141565841908e-05 loss: 0.0838 (0.0848) time: 3.0448 data: 0.0077 max mem: 33408 +Epoch: [10] [2610/2639] eta: 0:01:27 lr: 3.744701355127297e-05 loss: 0.0929 (0.0849) time: 3.0161 data: 0.0073 max mem: 33408 +Epoch: [10] [2620/2639] eta: 0:00:57 lr: 3.7442611386626945e-05 loss: 0.0773 (0.0849) time: 3.0334 data: 0.0077 max mem: 33408 +Epoch: [10] [2630/2639] eta: 0:00:27 lr: 3.743820916447275e-05 loss: 0.0772 (0.0849) time: 3.0345 data: 0.0075 max mem: 33408 +Epoch: [10] Total time: 2:13:14 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 2:18:32 time: 3.2308 data: 3.0820 max mem: 33408 +Test: [ 100/2573] eta: 0:04:32 time: 0.0802 data: 0.0014 max mem: 33408 +Test: [ 200/2573] eta: 0:03:47 time: 0.0802 data: 0.0014 max mem: 33408 +Test: [ 300/2573] eta: 0:03:26 time: 0.0815 data: 0.0015 max mem: 33408 +Test: [ 400/2573] eta: 0:03:11 time: 0.0830 data: 0.0016 max mem: 33408 +Test: [ 500/2573] eta: 0:02:59 time: 0.0813 data: 0.0015 max mem: 33408 +Test: [ 600/2573] eta: 0:02:49 time: 0.0800 data: 0.0014 max mem: 33408 +Test: [ 700/2573] eta: 0:02:39 time: 0.0808 data: 0.0015 max mem: 33408 +Test: [ 800/2573] eta: 0:02:30 time: 0.0828 data: 0.0013 max mem: 33408 +Test: [ 900/2573] eta: 0:02:21 time: 0.0802 data: 0.0015 max mem: 33408 +Test: [1000/2573] eta: 0:02:12 time: 0.0808 data: 0.0015 max mem: 33408 +Test: [1100/2573] eta: 0:02:03 time: 0.0797 data: 0.0015 max mem: 33408 +Test: [1200/2573] eta: 0:01:54 time: 0.0813 data: 0.0013 max mem: 33408 +Test: [1300/2573] eta: 0:01:46 time: 0.0820 data: 0.0014 max mem: 33408 +Test: [1400/2573] eta: 0:01:37 time: 0.0792 data: 0.0015 max mem: 33408 +Test: [1500/2573] eta: 0:01:29 time: 0.0807 data: 0.0016 max mem: 33408 +Test: [1600/2573] eta: 0:01:20 time: 0.0838 data: 0.0015 max mem: 33408 +Test: [1700/2573] eta: 0:01:12 time: 0.0789 data: 0.0014 max mem: 33408 +Test: [1800/2573] eta: 0:01:03 time: 0.0818 data: 0.0015 max mem: 33408 +Test: [1900/2573] eta: 0:00:55 time: 0.0797 data: 0.0015 max mem: 33408 +Test: [2000/2573] eta: 0:00:47 time: 0.0807 data: 0.0014 max mem: 33408 +Test: [2100/2573] eta: 0:00:38 time: 0.0823 data: 0.0014 max mem: 33408 +Test: [2200/2573] eta: 0:00:30 time: 0.0822 data: 0.0015 max mem: 33408 +Test: [2300/2573] eta: 0:00:22 time: 0.0835 data: 0.0015 max mem: 33408 +Test: [2400/2573] eta: 0:00:14 time: 0.0768 data: 0.0014 max mem: 33408 +Test: [2500/2573] eta: 0:00:05 time: 0.0814 data: 0.0015 max mem: 33408 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: Total time: 0:03:32 +Final results: +Mean IoU is 60.86 + + precision@0.5 = 68.38 + precision@0.6 = 62.75 + precision@0.7 = 54.45 + precision@0.8 = 41.91 + precision@0.9 = 18.65 + overall IoU = 59.20 + +Average object IoU 60.858725579651626 +Overall IoU 59.19902038574219 +Better epoch: 10 + +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [11] [ 0/2639] eta: 3:55:08 lr: 3.7434247115357644e-05 loss: 0.0675 (0.0675) time: 5.3462 data: 2.2876 max mem: 33408 +Epoch: [11] [ 10/2639] eta: 2:25:18 lr: 3.742984478391514e-05 loss: 0.0669 (0.0715) time: 3.3163 data: 0.2147 max mem: 33408 +Epoch: [11] [ 20/2639] eta: 2:20:37 lr: 3.7425442394940486e-05 loss: 0.0638 (0.0713) time: 3.1154 data: 0.0076 max mem: 33408 +Epoch: [11] [ 30/2639] eta: 2:16:54 lr: 3.74210399484254e-05 loss: 0.0646 (0.0716) time: 3.0563 data: 0.0079 max mem: 33408 +Epoch: [11] [ 40/2639] eta: 2:15:42 lr: 3.741663744436163e-05 loss: 0.0646 (0.0717) time: 3.0402 data: 0.0077 max mem: 33408 +Epoch: [11] [ 50/2639] eta: 2:14:31 lr: 3.7412234882740875e-05 loss: 0.0646 (0.0727) time: 3.0701 data: 0.0080 max mem: 33408 +Epoch: [11] [ 60/2639] eta: 2:13:26 lr: 3.7407832263554876e-05 loss: 0.0642 (0.0712) time: 3.0459 data: 0.0083 max mem: 33408 +Epoch: [11] [ 70/2639] eta: 2:12:18 lr: 3.740342958679534e-05 loss: 0.0637 (0.0724) time: 3.0198 data: 0.0078 max mem: 33408 +Epoch: [11] [ 80/2639] eta: 2:11:19 lr: 3.739902685245399e-05 loss: 0.0664 (0.0714) time: 3.0016 data: 0.0077 max mem: 33408 +Epoch: [11] [ 90/2639] eta: 2:10:52 lr: 3.7394624060522545e-05 loss: 0.0717 (0.0736) time: 3.0471 data: 0.0077 max mem: 33408 +Epoch: [11] [ 100/2639] eta: 2:09:55 lr: 3.739022121099271e-05 loss: 0.0703 (0.0739) time: 3.0354 data: 0.0075 max mem: 33408 +Epoch: [11] [ 110/2639] eta: 2:09:18 lr: 3.7385818303856197e-05 loss: 0.0631 (0.0741) time: 3.0084 data: 0.0076 max mem: 33408 +Epoch: [11] [ 120/2639] eta: 2:08:50 lr: 3.738141533910471e-05 loss: 0.0576 (0.0727) time: 3.0615 data: 0.0076 max mem: 33408 +Epoch: [11] [ 130/2639] eta: 2:08:07 lr: 3.7377012316729964e-05 loss: 0.0582 (0.0728) time: 3.0442 data: 0.0077 max mem: 33408 +Epoch: [11] [ 140/2639] eta: 2:07:23 lr: 3.737260923672366e-05 loss: 0.0638 (0.0720) time: 2.9959 data: 0.0081 max mem: 33408 +Epoch: [11] [ 150/2639] eta: 2:06:42 lr: 3.7368206099077493e-05 loss: 0.0587 (0.0734) time: 2.9901 data: 0.0082 max mem: 33408 +Epoch: [11] [ 160/2639] eta: 2:06:06 lr: 3.736380290378316e-05 loss: 0.0797 (0.0746) time: 3.0079 data: 0.0081 max mem: 33408 +Epoch: [11] [ 170/2639] eta: 2:05:35 lr: 3.735939965083238e-05 loss: 0.0801 (0.0751) time: 3.0358 data: 0.0078 max mem: 33408 +Epoch: [11] [ 180/2639] eta: 2:05:07 lr: 3.735499634021682e-05 loss: 0.0751 (0.0758) time: 3.0577 data: 0.0077 max mem: 33408 +Epoch: [11] [ 190/2639] eta: 2:04:26 lr: 3.735059297192818e-05 loss: 0.0752 (0.0761) time: 3.0212 data: 0.0076 max mem: 33408 +Epoch: [11] [ 200/2639] eta: 2:04:03 lr: 3.734618954595816e-05 loss: 0.0752 (0.0761) time: 3.0403 data: 0.0077 max mem: 33408 +Epoch: [11] [ 210/2639] eta: 2:03:26 lr: 3.734178606229843e-05 loss: 0.0651 (0.0754) time: 3.0530 data: 0.0081 max mem: 33408 +Epoch: [11] [ 220/2639] eta: 2:02:55 lr: 3.733738252094069e-05 loss: 0.0644 (0.0756) time: 3.0234 data: 0.0080 max mem: 33408 +Epoch: [11] [ 230/2639] eta: 2:02:14 lr: 3.733297892187662e-05 loss: 0.0732 (0.0761) time: 2.9962 data: 0.0080 max mem: 33408 +Epoch: [11] [ 240/2639] eta: 2:01:49 lr: 3.732857526509789e-05 loss: 0.0631 (0.0756) time: 3.0205 data: 0.0079 max mem: 33408 +Epoch: [11] [ 250/2639] eta: 2:01:16 lr: 3.7324171550596195e-05 loss: 0.0608 (0.0753) time: 3.0606 data: 0.0075 max mem: 33408 +Epoch: [11] [ 260/2639] eta: 2:00:43 lr: 3.73197677783632e-05 loss: 0.0582 (0.0747) time: 3.0231 data: 0.0074 max mem: 33408 +Epoch: [11] [ 270/2639] eta: 2:00:04 lr: 3.731536394839058e-05 loss: 0.0623 (0.0750) time: 2.9802 data: 0.0074 max mem: 33408 +Epoch: [11] [ 280/2639] eta: 1:59:34 lr: 3.731096006067001e-05 loss: 0.0641 (0.0746) time: 2.9933 data: 0.0078 max mem: 33408 +Epoch: [11] [ 290/2639] eta: 1:58:58 lr: 3.7306556115193146e-05 loss: 0.0577 (0.0749) time: 3.0107 data: 0.0078 max mem: 33408 +Epoch: [11] [ 300/2639] eta: 1:58:25 lr: 3.730215211195168e-05 loss: 0.0812 (0.0751) time: 2.9894 data: 0.0075 max mem: 33408 +Epoch: [11] [ 310/2639] eta: 1:57:52 lr: 3.729774805093726e-05 loss: 0.0774 (0.0755) time: 3.0026 data: 0.0079 max mem: 33408 +Epoch: [11] [ 320/2639] eta: 1:57:15 lr: 3.7293343932141546e-05 loss: 0.0708 (0.0754) time: 2.9719 data: 0.0084 max mem: 33408 +Epoch: [11] [ 330/2639] eta: 1:56:48 lr: 3.7288939755556196e-05 loss: 0.0618 (0.0750) time: 3.0170 data: 0.0080 max mem: 33408 +Epoch: [11] [ 340/2639] eta: 1:56:20 lr: 3.728453552117288e-05 loss: 0.0652 (0.0750) time: 3.0760 data: 0.0078 max mem: 33408 +Epoch: [11] [ 350/2639] eta: 1:55:48 lr: 3.728013122898325e-05 loss: 0.0680 (0.0749) time: 3.0357 data: 0.0078 max mem: 33408 +Epoch: [11] [ 360/2639] eta: 1:55:24 lr: 3.727572687897895e-05 loss: 0.0728 (0.0753) time: 3.0734 data: 0.0075 max mem: 33408 +Epoch: [11] [ 370/2639] eta: 1:54:51 lr: 3.727132247115164e-05 loss: 0.0728 (0.0754) time: 3.0718 data: 0.0076 max mem: 33408 +Epoch: [11] [ 380/2639] eta: 1:54:22 lr: 3.7266918005492964e-05 loss: 0.0699 (0.0754) time: 3.0285 data: 0.0082 max mem: 33408 +Epoch: [11] [ 390/2639] eta: 1:53:49 lr: 3.726251348199457e-05 loss: 0.0624 (0.0753) time: 3.0264 data: 0.0083 max mem: 33408 +Epoch: [11] [ 400/2639] eta: 1:53:18 lr: 3.72581089006481e-05 loss: 0.0726 (0.0753) time: 3.0126 data: 0.0081 max mem: 33408 +Epoch: [11] [ 410/2639] eta: 1:52:43 lr: 3.725370426144519e-05 loss: 0.0706 (0.0755) time: 2.9828 data: 0.0081 max mem: 33408 +Epoch: [11] [ 420/2639] eta: 1:52:10 lr: 3.72492995643775e-05 loss: 0.0703 (0.0754) time: 2.9645 data: 0.0078 max mem: 33408 +Epoch: [11] [ 430/2639] eta: 1:51:37 lr: 3.724489480943665e-05 loss: 0.0650 (0.0752) time: 2.9818 data: 0.0080 max mem: 33408 +Epoch: [11] [ 440/2639] eta: 1:51:04 lr: 3.724048999661426e-05 loss: 0.0650 (0.0753) time: 2.9804 data: 0.0080 max mem: 33408 +Epoch: [11] [ 450/2639] eta: 1:50:30 lr: 3.7236085125901994e-05 loss: 0.0726 (0.0755) time: 2.9661 data: 0.0077 max mem: 33408 +Epoch: [11] [ 460/2639] eta: 1:49:58 lr: 3.7231680197291466e-05 loss: 0.0648 (0.0752) time: 2.9787 data: 0.0077 max mem: 33408 +Epoch: [11] [ 470/2639] eta: 1:49:31 lr: 3.7227275210774296e-05 loss: 0.0702 (0.0755) time: 3.0534 data: 0.0078 max mem: 33408 +Epoch: [11] [ 480/2639] eta: 1:48:57 lr: 3.7222870166342136e-05 loss: 0.0790 (0.0762) time: 3.0203 data: 0.0083 max mem: 33408 +Epoch: [11] [ 490/2639] eta: 1:48:27 lr: 3.721846506398658e-05 loss: 0.0773 (0.0764) time: 2.9817 data: 0.0083 max mem: 33408 +Epoch: [11] [ 500/2639] eta: 1:47:56 lr: 3.7214059903699256e-05 loss: 0.0716 (0.0762) time: 3.0172 data: 0.0083 max mem: 33408 +Epoch: [11] [ 510/2639] eta: 1:47:24 lr: 3.720965468547179e-05 loss: 0.0841 (0.0766) time: 3.0013 data: 0.0081 max mem: 33408 +Epoch: [11] [ 520/2639] eta: 1:46:54 lr: 3.72052494092958e-05 loss: 0.0901 (0.0769) time: 3.0113 data: 0.0081 max mem: 33408 +Epoch: [11] [ 530/2639] eta: 1:46:21 lr: 3.720084407516289e-05 loss: 0.0716 (0.0769) time: 2.9979 data: 0.0086 max mem: 33408 +Epoch: [11] [ 540/2639] eta: 1:45:49 lr: 3.7196438683064674e-05 loss: 0.0851 (0.0775) time: 2.9790 data: 0.0079 max mem: 33408 +Epoch: [11] [ 550/2639] eta: 1:45:22 lr: 3.719203323299276e-05 loss: 0.0892 (0.0775) time: 3.0475 data: 0.0075 max mem: 33408 +Epoch: [11] [ 560/2639] eta: 1:44:50 lr: 3.718762772493877e-05 loss: 0.0655 (0.0773) time: 3.0451 data: 0.0077 max mem: 33408 +Epoch: [11] [ 570/2639] eta: 1:44:18 lr: 3.718322215889428e-05 loss: 0.0533 (0.0770) time: 2.9824 data: 0.0076 max mem: 33408 +Epoch: [11] [ 580/2639] eta: 1:43:47 lr: 3.717881653485092e-05 loss: 0.0648 (0.0770) time: 2.9833 data: 0.0078 max mem: 33408 +Epoch: [11] [ 590/2639] eta: 1:43:17 lr: 3.7174410852800274e-05 loss: 0.0771 (0.0770) time: 3.0061 data: 0.0079 max mem: 33408 +Epoch: [11] [ 600/2639] eta: 1:42:48 lr: 3.7170005112733945e-05 loss: 0.0710 (0.0769) time: 3.0441 data: 0.0079 max mem: 33408 +Epoch: [11] [ 610/2639] eta: 1:42:16 lr: 3.716559931464352e-05 loss: 0.0656 (0.0769) time: 3.0238 data: 0.0080 max mem: 33408 +Epoch: [11] [ 620/2639] eta: 1:41:45 lr: 3.7161193458520605e-05 loss: 0.0625 (0.0768) time: 2.9834 data: 0.0082 max mem: 33408 +Epoch: [11] [ 630/2639] eta: 1:41:13 lr: 3.715678754435678e-05 loss: 0.0620 (0.0768) time: 2.9852 data: 0.0084 max mem: 33408 +Epoch: [11] [ 640/2639] eta: 1:40:41 lr: 3.715238157214365e-05 loss: 0.0684 (0.0771) time: 2.9702 data: 0.0088 max mem: 33408 +Epoch: [11] [ 650/2639] eta: 1:40:09 lr: 3.714797554187278e-05 loss: 0.0779 (0.0774) time: 2.9574 data: 0.0085 max mem: 33408 +Epoch: [11] [ 660/2639] eta: 1:39:37 lr: 3.714356945353576e-05 loss: 0.0779 (0.0774) time: 2.9722 data: 0.0081 max mem: 33408 +Epoch: [11] [ 670/2639] eta: 1:39:07 lr: 3.7139163307124176e-05 loss: 0.0713 (0.0773) time: 3.0010 data: 0.0081 max mem: 33408 +Epoch: [11] [ 680/2639] eta: 1:38:35 lr: 3.71347571026296e-05 loss: 0.0821 (0.0775) time: 2.9875 data: 0.0078 max mem: 33408 +Epoch: [11] [ 690/2639] eta: 1:38:04 lr: 3.7130350840043614e-05 loss: 0.0804 (0.0775) time: 2.9674 data: 0.0078 max mem: 33408 +Epoch: [11] [ 700/2639] eta: 1:37:34 lr: 3.7125944519357794e-05 loss: 0.0636 (0.0773) time: 3.0129 data: 0.0079 max mem: 33408 +Epoch: [11] [ 710/2639] eta: 1:37:04 lr: 3.7121538140563706e-05 loss: 0.0615 (0.0771) time: 3.0315 data: 0.0076 max mem: 33408 +Epoch: [11] [ 720/2639] eta: 1:36:35 lr: 3.7117131703652925e-05 loss: 0.0620 (0.0771) time: 3.0355 data: 0.0077 max mem: 33408 +Epoch: [11] [ 730/2639] eta: 1:36:04 lr: 3.7112725208617015e-05 loss: 0.0698 (0.0770) time: 3.0228 data: 0.0082 max mem: 33408 +Epoch: [11] [ 740/2639] eta: 1:35:33 lr: 3.710831865544754e-05 loss: 0.0687 (0.0772) time: 2.9956 data: 0.0081 max mem: 33408 +Epoch: [11] [ 750/2639] eta: 1:35:03 lr: 3.7103912044136056e-05 loss: 0.0687 (0.0772) time: 3.0116 data: 0.0079 max mem: 33408 +Epoch: [11] [ 760/2639] eta: 1:34:33 lr: 3.709950537467415e-05 loss: 0.0725 (0.0771) time: 3.0236 data: 0.0079 max mem: 33408 +Epoch: [11] [ 770/2639] eta: 1:34:02 lr: 3.709509864705335e-05 loss: 0.0777 (0.0772) time: 3.0077 data: 0.0078 max mem: 33408 +Epoch: [11] [ 780/2639] eta: 1:33:34 lr: 3.709069186126522e-05 loss: 0.0751 (0.0775) time: 3.0445 data: 0.0080 max mem: 33408 +Epoch: [11] [ 790/2639] eta: 1:33:03 lr: 3.7086285017301315e-05 loss: 0.0722 (0.0774) time: 3.0544 data: 0.0082 max mem: 33408 +Epoch: [11] [ 800/2639] eta: 1:32:33 lr: 3.7081878115153195e-05 loss: 0.0700 (0.0775) time: 3.0130 data: 0.0084 max mem: 33408 +Epoch: [11] [ 810/2639] eta: 1:32:04 lr: 3.70774711548124e-05 loss: 0.0804 (0.0775) time: 3.0459 data: 0.0085 max mem: 33408 +Epoch: [11] [ 820/2639] eta: 1:31:32 lr: 3.707306413627047e-05 loss: 0.0704 (0.0775) time: 3.0083 data: 0.0083 max mem: 33408 +Epoch: [11] [ 830/2639] eta: 1:31:03 lr: 3.7068657059518954e-05 loss: 0.0713 (0.0780) time: 3.0077 data: 0.0083 max mem: 33408 +Epoch: [11] [ 840/2639] eta: 1:30:32 lr: 3.70642499245494e-05 loss: 0.0713 (0.0780) time: 3.0251 data: 0.0089 max mem: 33408 +Epoch: [11] [ 850/2639] eta: 1:30:03 lr: 3.705984273135335e-05 loss: 0.0829 (0.0781) time: 3.0199 data: 0.0087 max mem: 33408 +Epoch: [11] [ 860/2639] eta: 1:29:31 lr: 3.7055435479922315e-05 loss: 0.0774 (0.0779) time: 3.0128 data: 0.0077 max mem: 33408 +Epoch: [11] [ 870/2639] eta: 1:29:02 lr: 3.7051028170247854e-05 loss: 0.0646 (0.0778) time: 3.0110 data: 0.0078 max mem: 33408 +Epoch: [11] [ 880/2639] eta: 1:28:32 lr: 3.70466208023215e-05 loss: 0.0619 (0.0775) time: 3.0592 data: 0.0078 max mem: 33408 +Epoch: [11] [ 890/2639] eta: 1:28:01 lr: 3.704221337613476e-05 loss: 0.0639 (0.0775) time: 3.0207 data: 0.0077 max mem: 33408 +Epoch: [11] [ 900/2639] eta: 1:27:31 lr: 3.7037805891679187e-05 loss: 0.0681 (0.0775) time: 2.9871 data: 0.0077 max mem: 33408 +Epoch: [11] [ 910/2639] eta: 1:27:01 lr: 3.703339834894629e-05 loss: 0.0592 (0.0774) time: 3.0237 data: 0.0075 max mem: 33408 +Epoch: [11] [ 920/2639] eta: 1:26:29 lr: 3.7028990747927606e-05 loss: 0.0712 (0.0774) time: 2.9967 data: 0.0077 max mem: 33408 +Epoch: [11] [ 930/2639] eta: 1:26:00 lr: 3.702458308861465e-05 loss: 0.0793 (0.0775) time: 2.9969 data: 0.0081 max mem: 33408 +Epoch: [11] [ 940/2639] eta: 1:25:31 lr: 3.702017537099891e-05 loss: 0.0686 (0.0775) time: 3.0681 data: 0.0080 max mem: 33408 +Epoch: [11] [ 950/2639] eta: 1:25:00 lr: 3.701576759507195e-05 loss: 0.0670 (0.0776) time: 3.0186 data: 0.0078 max mem: 33408 +Epoch: [11] [ 960/2639] eta: 1:24:30 lr: 3.701135976082525e-05 loss: 0.0803 (0.0775) time: 3.0131 data: 0.0080 max mem: 33408 +Epoch: [11] [ 970/2639] eta: 1:23:59 lr: 3.700695186825034e-05 loss: 0.0691 (0.0776) time: 3.0231 data: 0.0081 max mem: 33408 +Epoch: [11] [ 980/2639] eta: 1:23:30 lr: 3.700254391733873e-05 loss: 0.0691 (0.0777) time: 3.0303 data: 0.0080 max mem: 33408 +Epoch: [11] [ 990/2639] eta: 1:23:00 lr: 3.69981359080819e-05 loss: 0.0655 (0.0775) time: 3.0557 data: 0.0080 max mem: 33408 +Epoch: [11] [1000/2639] eta: 1:22:29 lr: 3.6993727840471374e-05 loss: 0.0679 (0.0775) time: 3.0095 data: 0.0079 max mem: 33408 +Epoch: [11] [1010/2639] eta: 1:21:59 lr: 3.698931971449866e-05 loss: 0.0877 (0.0777) time: 2.9985 data: 0.0079 max mem: 33408 +Epoch: [11] [1020/2639] eta: 1:21:29 lr: 3.6984911530155234e-05 loss: 0.0860 (0.0777) time: 3.0228 data: 0.0079 max mem: 33408 +Epoch: [11] [1030/2639] eta: 1:20:58 lr: 3.698050328743262e-05 loss: 0.0659 (0.0777) time: 3.0038 data: 0.0074 max mem: 33408 +Epoch: [11] [1040/2639] eta: 1:20:28 lr: 3.697609498632228e-05 loss: 0.0644 (0.0776) time: 3.0019 data: 0.0075 max mem: 33408 +Epoch: [11] [1050/2639] eta: 1:19:58 lr: 3.697168662681574e-05 loss: 0.0602 (0.0776) time: 3.0307 data: 0.0077 max mem: 33408 +Epoch: [11] [1060/2639] eta: 1:19:28 lr: 3.696727820890447e-05 loss: 0.0606 (0.0775) time: 3.0390 data: 0.0077 max mem: 33408 +Epoch: [11] [1070/2639] eta: 1:18:59 lr: 3.696286973257996e-05 loss: 0.0664 (0.0775) time: 3.0522 data: 0.0078 max mem: 33408 +Epoch: [11] [1080/2639] eta: 1:18:28 lr: 3.695846119783369e-05 loss: 0.0692 (0.0776) time: 3.0347 data: 0.0077 max mem: 33408 +Epoch: [11] [1090/2639] eta: 1:17:58 lr: 3.695405260465716e-05 loss: 0.0819 (0.0776) time: 3.0153 data: 0.0076 max mem: 33408 +Epoch: [11] [1100/2639] eta: 1:17:28 lr: 3.694964395304183e-05 loss: 0.0815 (0.0777) time: 3.0192 data: 0.0077 max mem: 33408 +Epoch: [11] [1110/2639] eta: 1:16:58 lr: 3.694523524297919e-05 loss: 0.0788 (0.0778) time: 3.0327 data: 0.0078 max mem: 33408 +Epoch: [11] [1120/2639] eta: 1:16:27 lr: 3.694082647446071e-05 loss: 0.0736 (0.0778) time: 3.0203 data: 0.0080 max mem: 33408 +Epoch: [11] [1130/2639] eta: 1:15:58 lr: 3.693641764747787e-05 loss: 0.0741 (0.0779) time: 3.0512 data: 0.0080 max mem: 33408 +Epoch: [11] [1140/2639] eta: 1:15:28 lr: 3.693200876202214e-05 loss: 0.0775 (0.0779) time: 3.0553 data: 0.0079 max mem: 33408 +Epoch: [11] [1150/2639] eta: 1:14:58 lr: 3.6927599818084965e-05 loss: 0.0723 (0.0778) time: 3.0325 data: 0.0078 max mem: 33408 +Epoch: [11] [1160/2639] eta: 1:14:28 lr: 3.692319081565784e-05 loss: 0.0670 (0.0778) time: 3.0235 data: 0.0080 max mem: 33408 +Epoch: [11] [1170/2639] eta: 1:13:58 lr: 3.6918781754732225e-05 loss: 0.0780 (0.0779) time: 3.0351 data: 0.0080 max mem: 33408 +Epoch: [11] [1180/2639] eta: 1:13:28 lr: 3.691437263529957e-05 loss: 0.0847 (0.0779) time: 3.0389 data: 0.0077 max mem: 33408 +Epoch: [11] [1190/2639] eta: 1:12:57 lr: 3.6909963457351336e-05 loss: 0.0737 (0.0780) time: 2.9881 data: 0.0079 max mem: 33408 +Epoch: [11] [1200/2639] eta: 1:12:27 lr: 3.690555422087898e-05 loss: 0.0583 (0.0779) time: 3.0314 data: 0.0082 max mem: 33408 +Epoch: [11] [1210/2639] eta: 1:11:57 lr: 3.690114492587396e-05 loss: 0.0543 (0.0780) time: 3.0472 data: 0.0085 max mem: 33408 +Epoch: [11] [1220/2639] eta: 1:11:27 lr: 3.6896735572327726e-05 loss: 0.0761 (0.0781) time: 3.0298 data: 0.0082 max mem: 33408 +Epoch: [11] [1230/2639] eta: 1:10:57 lr: 3.6892326160231736e-05 loss: 0.0804 (0.0781) time: 3.0280 data: 0.0078 max mem: 33408 +Epoch: [11] [1240/2639] eta: 1:10:26 lr: 3.688791668957741e-05 loss: 0.0755 (0.0783) time: 2.9838 data: 0.0079 max mem: 33408 +Epoch: [11] [1250/2639] eta: 1:09:55 lr: 3.688350716035622e-05 loss: 0.0843 (0.0783) time: 2.9707 data: 0.0078 max mem: 33408 +Epoch: [11] [1260/2639] eta: 1:09:24 lr: 3.6879097572559594e-05 loss: 0.0753 (0.0783) time: 2.9692 data: 0.0078 max mem: 33408 +Epoch: [11] [1270/2639] eta: 1:08:54 lr: 3.687468792617898e-05 loss: 0.0751 (0.0783) time: 2.9966 data: 0.0080 max mem: 33408 +Epoch: [11] [1280/2639] eta: 1:08:24 lr: 3.68702782212058e-05 loss: 0.0695 (0.0782) time: 3.0301 data: 0.0077 max mem: 33408 +Epoch: [11] [1290/2639] eta: 1:07:54 lr: 3.686586845763151e-05 loss: 0.0696 (0.0782) time: 3.0443 data: 0.0079 max mem: 33408 +Epoch: [11] [1300/2639] eta: 1:07:25 lr: 3.686145863544754e-05 loss: 0.0703 (0.0786) time: 3.0703 data: 0.0080 max mem: 33408 +Epoch: [11] [1310/2639] eta: 1:06:55 lr: 3.68570487546453e-05 loss: 0.0709 (0.0787) time: 3.0724 data: 0.0074 max mem: 33408 +Epoch: [11] [1320/2639] eta: 1:06:25 lr: 3.685263881521623e-05 loss: 0.0729 (0.0786) time: 3.0391 data: 0.0076 max mem: 33408 +Epoch: [11] [1330/2639] eta: 1:05:54 lr: 3.684822881715176e-05 loss: 0.0627 (0.0785) time: 2.9938 data: 0.0086 max mem: 33408 +Epoch: [11] [1340/2639] eta: 1:05:23 lr: 3.684381876044331e-05 loss: 0.0693 (0.0786) time: 2.9782 data: 0.0090 max mem: 33408 +Epoch: [11] [1350/2639] eta: 1:04:54 lr: 3.68394086450823e-05 loss: 0.0641 (0.0785) time: 3.0160 data: 0.0083 max mem: 33408 +Epoch: [11] [1360/2639] eta: 1:04:23 lr: 3.6834998471060145e-05 loss: 0.0685 (0.0785) time: 3.0313 data: 0.0077 max mem: 33408 +Epoch: [11] [1370/2639] eta: 1:03:53 lr: 3.683058823836826e-05 loss: 0.0781 (0.0785) time: 3.0312 data: 0.0080 max mem: 33408 +Epoch: [11] [1380/2639] eta: 1:03:23 lr: 3.682617794699806e-05 loss: 0.0772 (0.0785) time: 3.0104 data: 0.0081 max mem: 33408 +Epoch: [11] [1390/2639] eta: 1:02:52 lr: 3.682176759694097e-05 loss: 0.0641 (0.0786) time: 2.9925 data: 0.0080 max mem: 33408 +Epoch: [11] [1400/2639] eta: 1:02:22 lr: 3.681735718818838e-05 loss: 0.0641 (0.0786) time: 3.0199 data: 0.0078 max mem: 33408 +Epoch: [11] [1410/2639] eta: 1:01:52 lr: 3.6812946720731695e-05 loss: 0.0855 (0.0787) time: 3.0229 data: 0.0075 max mem: 33408 +Epoch: [11] [1420/2639] eta: 1:01:22 lr: 3.680853619456233e-05 loss: 0.0704 (0.0786) time: 3.0278 data: 0.0074 max mem: 33408 +Epoch: [11] [1430/2639] eta: 1:00:52 lr: 3.680412560967168e-05 loss: 0.0613 (0.0785) time: 3.0566 data: 0.0075 max mem: 33408 +Epoch: [11] [1440/2639] eta: 1:00:22 lr: 3.679971496605115e-05 loss: 0.0674 (0.0785) time: 3.0519 data: 0.0076 max mem: 33408 +Epoch: [11] [1450/2639] eta: 0:59:52 lr: 3.679530426369213e-05 loss: 0.0720 (0.0786) time: 3.0657 data: 0.0073 max mem: 33408 +Epoch: [11] [1460/2639] eta: 0:59:23 lr: 3.679089350258602e-05 loss: 0.0684 (0.0786) time: 3.0831 data: 0.0074 max mem: 33408 +Epoch: [11] [1470/2639] eta: 0:58:52 lr: 3.678648268272421e-05 loss: 0.0717 (0.0787) time: 3.0122 data: 0.0078 max mem: 33408 +Epoch: [11] [1480/2639] eta: 0:58:22 lr: 3.678207180409809e-05 loss: 0.0860 (0.0788) time: 3.0176 data: 0.0078 max mem: 33408 +Epoch: [11] [1490/2639] eta: 0:57:52 lr: 3.6777660866699036e-05 loss: 0.0788 (0.0788) time: 3.0454 data: 0.0077 max mem: 33408 +Epoch: [11] [1500/2639] eta: 0:57:22 lr: 3.677324987051844e-05 loss: 0.0656 (0.0788) time: 3.0335 data: 0.0078 max mem: 33408 +Epoch: [11] [1510/2639] eta: 0:56:51 lr: 3.67688388155477e-05 loss: 0.0732 (0.0788) time: 3.0028 data: 0.0077 max mem: 33408 +Epoch: [11] [1520/2639] eta: 0:56:21 lr: 3.676442770177818e-05 loss: 0.0703 (0.0788) time: 3.0256 data: 0.0078 max mem: 33408 +Epoch: [11] [1530/2639] eta: 0:55:51 lr: 3.6760016529201246e-05 loss: 0.0756 (0.0788) time: 3.0167 data: 0.0077 max mem: 33408 +Epoch: [11] [1540/2639] eta: 0:55:21 lr: 3.6755605297808285e-05 loss: 0.0756 (0.0788) time: 3.0053 data: 0.0077 max mem: 33408 +Epoch: [11] [1550/2639] eta: 0:54:50 lr: 3.675119400759068e-05 loss: 0.0696 (0.0788) time: 3.0345 data: 0.0076 max mem: 33408 +Epoch: [11] [1560/2639] eta: 0:54:21 lr: 3.6746782658539794e-05 loss: 0.0735 (0.0789) time: 3.0529 data: 0.0077 max mem: 33408 +Epoch: [11] [1570/2639] eta: 0:53:51 lr: 3.674237125064698e-05 loss: 0.0764 (0.0789) time: 3.0689 data: 0.0082 max mem: 33408 +Epoch: [11] [1580/2639] eta: 0:53:20 lr: 3.6737959783903616e-05 loss: 0.0770 (0.0789) time: 3.0180 data: 0.0081 max mem: 33408 +Epoch: [11] [1590/2639] eta: 0:52:50 lr: 3.6733548258301065e-05 loss: 0.0668 (0.0788) time: 3.0504 data: 0.0078 max mem: 33408 +Epoch: [11] [1600/2639] eta: 0:52:20 lr: 3.672913667383069e-05 loss: 0.0668 (0.0788) time: 3.0489 data: 0.0077 max mem: 33408 +Epoch: [11] [1610/2639] eta: 0:51:50 lr: 3.6724725030483834e-05 loss: 0.0621 (0.0787) time: 3.0199 data: 0.0074 max mem: 33408 +Epoch: [11] [1620/2639] eta: 0:51:20 lr: 3.672031332825187e-05 loss: 0.0621 (0.0788) time: 3.0370 data: 0.0076 max mem: 33408 +Epoch: [11] [1630/2639] eta: 0:50:50 lr: 3.671590156712615e-05 loss: 0.0813 (0.0788) time: 3.0620 data: 0.0082 max mem: 33408 +Epoch: [11] [1640/2639] eta: 0:50:20 lr: 3.6711489747098014e-05 loss: 0.0739 (0.0788) time: 3.0713 data: 0.0080 max mem: 33408 +Epoch: [11] [1650/2639] eta: 0:49:50 lr: 3.670707786815881e-05 loss: 0.0789 (0.0789) time: 3.0326 data: 0.0075 max mem: 33408 +Epoch: [11] [1660/2639] eta: 0:49:19 lr: 3.67026659302999e-05 loss: 0.0807 (0.0790) time: 2.9943 data: 0.0076 max mem: 33408 +Epoch: [11] [1670/2639] eta: 0:48:49 lr: 3.669825393351261e-05 loss: 0.0781 (0.0790) time: 3.0227 data: 0.0080 max mem: 33408 +Epoch: [11] [1680/2639] eta: 0:48:19 lr: 3.669384187778828e-05 loss: 0.0745 (0.0790) time: 3.0294 data: 0.0079 max mem: 33408 +Epoch: [11] [1690/2639] eta: 0:47:48 lr: 3.668942976311827e-05 loss: 0.0767 (0.0790) time: 3.0026 data: 0.0076 max mem: 33408 +Epoch: [11] [1700/2639] eta: 0:47:18 lr: 3.668501758949389e-05 loss: 0.0825 (0.0791) time: 3.0165 data: 0.0079 max mem: 33408 +Epoch: [11] [1710/2639] eta: 0:46:48 lr: 3.668060535690649e-05 loss: 0.0768 (0.0790) time: 3.0503 data: 0.0078 max mem: 33408 +Epoch: [11] [1720/2639] eta: 0:46:18 lr: 3.66761930653474e-05 loss: 0.0642 (0.0790) time: 3.0495 data: 0.0077 max mem: 33408 +Epoch: [11] [1730/2639] eta: 0:45:48 lr: 3.667178071480795e-05 loss: 0.0642 (0.0789) time: 3.0462 data: 0.0077 max mem: 33408 +Epoch: [11] [1740/2639] eta: 0:45:18 lr: 3.666736830527945e-05 loss: 0.0630 (0.0789) time: 3.0211 data: 0.0074 max mem: 33408 +Epoch: [11] [1750/2639] eta: 0:44:48 lr: 3.6662955836753235e-05 loss: 0.0602 (0.0788) time: 3.0475 data: 0.0073 max mem: 33408 +Epoch: [11] [1760/2639] eta: 0:44:18 lr: 3.665854330922063e-05 loss: 0.0541 (0.0787) time: 3.0764 data: 0.0077 max mem: 33408 +Epoch: [11] [1770/2639] eta: 0:43:47 lr: 3.6654130722672967e-05 loss: 0.0585 (0.0786) time: 3.0205 data: 0.0080 max mem: 33408 +Epoch: [11] [1780/2639] eta: 0:43:17 lr: 3.664971807710153e-05 loss: 0.0612 (0.0786) time: 3.0380 data: 0.0075 max mem: 33408 +Epoch: [11] [1790/2639] eta: 0:42:47 lr: 3.664530537249765e-05 loss: 0.0675 (0.0785) time: 3.0360 data: 0.0072 max mem: 33408 +Epoch: [11] [1800/2639] eta: 0:42:17 lr: 3.6640892608852644e-05 loss: 0.0742 (0.0786) time: 3.0238 data: 0.0074 max mem: 33408 +Epoch: [11] [1810/2639] eta: 0:41:47 lr: 3.663647978615782e-05 loss: 0.0674 (0.0785) time: 3.0453 data: 0.0076 max mem: 33408 +Epoch: [11] [1820/2639] eta: 0:41:16 lr: 3.663206690440447e-05 loss: 0.0659 (0.0785) time: 3.0412 data: 0.0075 max mem: 33408 +Epoch: [11] [1830/2639] eta: 0:40:46 lr: 3.662765396358392e-05 loss: 0.0659 (0.0785) time: 3.0129 data: 0.0070 max mem: 33408 +Epoch: [11] [1840/2639] eta: 0:40:16 lr: 3.662324096368746e-05 loss: 0.0701 (0.0786) time: 2.9900 data: 0.0074 max mem: 33408 +Epoch: [11] [1850/2639] eta: 0:39:46 lr: 3.661882790470639e-05 loss: 0.0754 (0.0786) time: 3.0144 data: 0.0078 max mem: 33408 +Epoch: [11] [1860/2639] eta: 0:39:15 lr: 3.6614414786632e-05 loss: 0.0665 (0.0785) time: 3.0351 data: 0.0077 max mem: 33408 +Epoch: [11] [1870/2639] eta: 0:38:45 lr: 3.66100016094556e-05 loss: 0.0618 (0.0785) time: 3.0752 data: 0.0076 max mem: 33408 +Epoch: [11] [1880/2639] eta: 0:38:15 lr: 3.660558837316848e-05 loss: 0.0740 (0.0785) time: 3.0713 data: 0.0078 max mem: 33408 +Epoch: [11] [1890/2639] eta: 0:37:45 lr: 3.660117507776192e-05 loss: 0.0710 (0.0786) time: 3.0278 data: 0.0079 max mem: 33408 +Epoch: [11] [1900/2639] eta: 0:37:15 lr: 3.6596761723227205e-05 loss: 0.0688 (0.0785) time: 3.0130 data: 0.0080 max mem: 33408 +Epoch: [11] [1910/2639] eta: 0:36:45 lr: 3.659234830955563e-05 loss: 0.0670 (0.0785) time: 3.0593 data: 0.0077 max mem: 33408 +Epoch: [11] [1920/2639] eta: 0:36:14 lr: 3.658793483673848e-05 loss: 0.0618 (0.0784) time: 3.0652 data: 0.0076 max mem: 33408 +Epoch: [11] [1930/2639] eta: 0:35:44 lr: 3.658352130476702e-05 loss: 0.0602 (0.0783) time: 3.0115 data: 0.0079 max mem: 33408 +Epoch: [11] [1940/2639] eta: 0:35:14 lr: 3.6579107713632545e-05 loss: 0.0634 (0.0783) time: 3.0329 data: 0.0076 max mem: 33408 +Epoch: [11] [1950/2639] eta: 0:34:44 lr: 3.6574694063326315e-05 loss: 0.0678 (0.0783) time: 3.0341 data: 0.0074 max mem: 33408 +Epoch: [11] [1960/2639] eta: 0:34:14 lr: 3.65702803538396e-05 loss: 0.0679 (0.0783) time: 3.0742 data: 0.0072 max mem: 33408 +Epoch: [11] [1970/2639] eta: 0:33:44 lr: 3.65658665851637e-05 loss: 0.0655 (0.0783) time: 3.0673 data: 0.0073 max mem: 33408 +Epoch: [11] [1980/2639] eta: 0:33:13 lr: 3.6561452757289855e-05 loss: 0.0655 (0.0782) time: 3.0133 data: 0.0074 max mem: 33408 +Epoch: [11] [1990/2639] eta: 0:32:43 lr: 3.655703887020933e-05 loss: 0.0589 (0.0782) time: 3.0146 data: 0.0077 max mem: 33408 +Epoch: [11] [2000/2639] eta: 0:32:13 lr: 3.655262492391339e-05 loss: 0.0710 (0.0782) time: 3.0284 data: 0.0081 max mem: 33408 +Epoch: [11] [2010/2639] eta: 0:31:42 lr: 3.654821091839331e-05 loss: 0.0710 (0.0782) time: 3.0367 data: 0.0080 max mem: 33408 +Epoch: [11] [2020/2639] eta: 0:31:13 lr: 3.6543796853640336e-05 loss: 0.0652 (0.0782) time: 3.0773 data: 0.0077 max mem: 33408 +Epoch: [11] [2030/2639] eta: 0:30:42 lr: 3.653938272964573e-05 loss: 0.0587 (0.0781) time: 3.0586 data: 0.0075 max mem: 33408 +Epoch: [11] [2040/2639] eta: 0:30:12 lr: 3.653496854640073e-05 loss: 0.0606 (0.0781) time: 3.0197 data: 0.0077 max mem: 33408 +Epoch: [11] [2050/2639] eta: 0:29:42 lr: 3.65305543038966e-05 loss: 0.0667 (0.0782) time: 3.0201 data: 0.0083 max mem: 33408 +Epoch: [11] [2060/2639] eta: 0:29:11 lr: 3.652614000212459e-05 loss: 0.0716 (0.0782) time: 2.9956 data: 0.0082 max mem: 33408 +Epoch: [11] [2070/2639] eta: 0:28:41 lr: 3.6521725641075925e-05 loss: 0.0716 (0.0782) time: 2.9889 data: 0.0076 max mem: 33408 +Epoch: [11] [2080/2639] eta: 0:28:10 lr: 3.651731122074187e-05 loss: 0.0682 (0.0782) time: 2.9726 data: 0.0081 max mem: 33408 +Epoch: [11] [2090/2639] eta: 0:27:40 lr: 3.651289674111366e-05 loss: 0.0692 (0.0783) time: 2.9466 data: 0.0082 max mem: 33408 +Epoch: [11] [2100/2639] eta: 0:27:10 lr: 3.650848220218253e-05 loss: 0.0762 (0.0783) time: 2.9626 data: 0.0080 max mem: 33408 +Epoch: [11] [2110/2639] eta: 0:26:39 lr: 3.6504067603939714e-05 loss: 0.0827 (0.0783) time: 3.0214 data: 0.0083 max mem: 33408 +Epoch: [11] [2120/2639] eta: 0:26:09 lr: 3.649965294637644e-05 loss: 0.0827 (0.0783) time: 3.0343 data: 0.0086 max mem: 33408 +Epoch: [11] [2130/2639] eta: 0:25:39 lr: 3.6495238229483966e-05 loss: 0.0612 (0.0782) time: 2.9880 data: 0.0086 max mem: 33408 +Epoch: [11] [2140/2639] eta: 0:25:08 lr: 3.649082345325349e-05 loss: 0.0586 (0.0782) time: 2.9547 data: 0.0086 max mem: 33408 +Epoch: [11] [2150/2639] eta: 0:24:38 lr: 3.648640861767625e-05 loss: 0.0582 (0.0782) time: 2.9965 data: 0.0087 max mem: 33408 +Epoch: [11] [2160/2639] eta: 0:24:08 lr: 3.6481993722743454e-05 loss: 0.0750 (0.0784) time: 3.0234 data: 0.0088 max mem: 33408 +Epoch: [11] [2170/2639] eta: 0:23:38 lr: 3.6477578768446346e-05 loss: 0.0778 (0.0784) time: 2.9896 data: 0.0087 max mem: 33408 +Epoch: [11] [2180/2639] eta: 0:23:08 lr: 3.647316375477614e-05 loss: 0.0835 (0.0784) time: 3.0542 data: 0.0081 max mem: 33408 +Epoch: [11] [2190/2639] eta: 0:22:37 lr: 3.646874868172405e-05 loss: 0.0632 (0.0784) time: 3.0477 data: 0.0083 max mem: 33408 +Epoch: [11] [2200/2639] eta: 0:22:07 lr: 3.646433354928127e-05 loss: 0.0584 (0.0783) time: 3.0033 data: 0.0088 max mem: 33408 +Epoch: [11] [2210/2639] eta: 0:21:37 lr: 3.645991835743903e-05 loss: 0.0690 (0.0783) time: 3.0689 data: 0.0083 max mem: 33408 +Epoch: [11] [2220/2639] eta: 0:21:07 lr: 3.6455503106188535e-05 loss: 0.0690 (0.0783) time: 3.0312 data: 0.0080 max mem: 33408 +Epoch: [11] [2230/2639] eta: 0:20:36 lr: 3.6451087795520996e-05 loss: 0.0677 (0.0783) time: 3.0171 data: 0.0079 max mem: 33408 +Epoch: [11] [2240/2639] eta: 0:20:06 lr: 3.6446672425427605e-05 loss: 0.0703 (0.0784) time: 3.0168 data: 0.0081 max mem: 33408 +Epoch: [11] [2250/2639] eta: 0:19:36 lr: 3.644225699589957e-05 loss: 0.0683 (0.0783) time: 2.9888 data: 0.0084 max mem: 33408 +Epoch: [11] [2260/2639] eta: 0:19:06 lr: 3.643784150692809e-05 loss: 0.0548 (0.0783) time: 3.0322 data: 0.0086 max mem: 33408 +Epoch: [11] [2270/2639] eta: 0:18:35 lr: 3.643342595850436e-05 loss: 0.0699 (0.0783) time: 3.0586 data: 0.0085 max mem: 33408 +Epoch: [11] [2280/2639] eta: 0:18:05 lr: 3.6429010350619565e-05 loss: 0.0739 (0.0783) time: 3.0198 data: 0.0086 max mem: 33408 +Epoch: [11] [2290/2639] eta: 0:17:35 lr: 3.64245946832649e-05 loss: 0.0732 (0.0783) time: 3.0214 data: 0.0086 max mem: 33408 +Epoch: [11] [2300/2639] eta: 0:17:05 lr: 3.642017895643157e-05 loss: 0.0663 (0.0783) time: 3.0865 data: 0.0082 max mem: 33408 +Epoch: [11] [2310/2639] eta: 0:16:35 lr: 3.641576317011074e-05 loss: 0.0661 (0.0783) time: 3.0428 data: 0.0079 max mem: 33408 +Epoch: [11] [2320/2639] eta: 0:16:04 lr: 3.64113473242936e-05 loss: 0.0661 (0.0783) time: 3.0341 data: 0.0076 max mem: 33408 +Epoch: [11] [2330/2639] eta: 0:15:34 lr: 3.640693141897133e-05 loss: 0.0593 (0.0782) time: 3.0394 data: 0.0081 max mem: 33408 +Epoch: [11] [2340/2639] eta: 0:15:04 lr: 3.640251545413511e-05 loss: 0.0635 (0.0782) time: 3.0325 data: 0.0082 max mem: 33408 +Epoch: [11] [2350/2639] eta: 0:14:34 lr: 3.6398099429776125e-05 loss: 0.0681 (0.0782) time: 3.0395 data: 0.0078 max mem: 33408 +Epoch: [11] [2360/2639] eta: 0:14:03 lr: 3.639368334588553e-05 loss: 0.0806 (0.0782) time: 3.0062 data: 0.0078 max mem: 33408 +Epoch: [11] [2370/2639] eta: 0:13:33 lr: 3.6389267202454505e-05 loss: 0.0770 (0.0782) time: 2.9791 data: 0.0078 max mem: 33408 +Epoch: [11] [2380/2639] eta: 0:13:03 lr: 3.638485099947422e-05 loss: 0.0693 (0.0782) time: 2.9714 data: 0.0077 max mem: 33408 +Epoch: [11] [2390/2639] eta: 0:12:33 lr: 3.638043473693584e-05 loss: 0.0726 (0.0782) time: 3.0211 data: 0.0076 max mem: 33408 +Epoch: [11] [2400/2639] eta: 0:12:02 lr: 3.637601841483053e-05 loss: 0.0635 (0.0782) time: 3.0067 data: 0.0079 max mem: 33408 +Epoch: [11] [2410/2639] eta: 0:11:32 lr: 3.637160203314944e-05 loss: 0.0616 (0.0782) time: 3.0128 data: 0.0078 max mem: 33408 +Epoch: [11] [2420/2639] eta: 0:11:02 lr: 3.6367185591883746e-05 loss: 0.0873 (0.0783) time: 3.0142 data: 0.0084 max mem: 33408 +Epoch: [11] [2430/2639] eta: 0:10:32 lr: 3.63627690910246e-05 loss: 0.0872 (0.0783) time: 3.0123 data: 0.0089 max mem: 33408 +Epoch: [11] [2440/2639] eta: 0:10:01 lr: 3.6358352530563145e-05 loss: 0.0751 (0.0784) time: 3.0152 data: 0.0083 max mem: 33408 +Epoch: [11] [2450/2639] eta: 0:09:31 lr: 3.6353935910490535e-05 loss: 0.0796 (0.0784) time: 3.0157 data: 0.0079 max mem: 33408 +Epoch: [11] [2460/2639] eta: 0:09:01 lr: 3.634951923079792e-05 loss: 0.0796 (0.0784) time: 3.0270 data: 0.0077 max mem: 33408 +Epoch: [11] [2470/2639] eta: 0:08:31 lr: 3.634510249147645e-05 loss: 0.0685 (0.0785) time: 3.0374 data: 0.0076 max mem: 33408 +Epoch: [11] [2480/2639] eta: 0:08:00 lr: 3.634068569251727e-05 loss: 0.0684 (0.0784) time: 3.0350 data: 0.0074 max mem: 33408 +Epoch: [11] [2490/2639] eta: 0:07:30 lr: 3.633626883391151e-05 loss: 0.0745 (0.0785) time: 3.0363 data: 0.0076 max mem: 33408 +Epoch: [11] [2500/2639] eta: 0:07:00 lr: 3.633185191565032e-05 loss: 0.0818 (0.0785) time: 3.0311 data: 0.0076 max mem: 33408 +Epoch: [11] [2510/2639] eta: 0:06:30 lr: 3.6327434937724826e-05 loss: 0.0732 (0.0784) time: 3.0160 data: 0.0076 max mem: 33408 +Epoch: [11] [2520/2639] eta: 0:05:59 lr: 3.632301790012617e-05 loss: 0.0644 (0.0784) time: 3.0179 data: 0.0075 max mem: 33408 +Epoch: [11] [2530/2639] eta: 0:05:29 lr: 3.631860080284547e-05 loss: 0.0631 (0.0784) time: 3.0249 data: 0.0075 max mem: 33408 +Epoch: [11] [2540/2639] eta: 0:04:59 lr: 3.631418364587386e-05 loss: 0.0700 (0.0784) time: 3.0235 data: 0.0075 max mem: 33408 +Epoch: [11] [2550/2639] eta: 0:04:29 lr: 3.630976642920248e-05 loss: 0.0717 (0.0784) time: 2.9982 data: 0.0073 max mem: 33408 +Epoch: [11] [2560/2639] eta: 0:03:58 lr: 3.6305349152822443e-05 loss: 0.0698 (0.0784) time: 3.0154 data: 0.0073 max mem: 33408 +Epoch: [11] [2570/2639] eta: 0:03:28 lr: 3.6300931816724856e-05 loss: 0.0736 (0.0784) time: 3.0325 data: 0.0075 max mem: 33408 +Epoch: [11] [2580/2639] eta: 0:02:58 lr: 3.6296514420900855e-05 loss: 0.0750 (0.0784) time: 3.0409 data: 0.0078 max mem: 33408 +Epoch: [11] [2590/2639] eta: 0:02:28 lr: 3.6292096965341556e-05 loss: 0.0727 (0.0785) time: 3.0080 data: 0.0079 max mem: 33408 +Epoch: [11] [2600/2639] eta: 0:01:57 lr: 3.628767945003806e-05 loss: 0.0720 (0.0785) time: 2.9918 data: 0.0078 max mem: 33408 +Epoch: [11] [2610/2639] eta: 0:01:27 lr: 3.628326187498149e-05 loss: 0.0717 (0.0785) time: 2.9944 data: 0.0075 max mem: 33408 +Epoch: [11] [2620/2639] eta: 0:00:57 lr: 3.627884424016294e-05 loss: 0.0744 (0.0785) time: 3.0299 data: 0.0075 max mem: 33408 +Epoch: [11] [2630/2639] eta: 0:00:27 lr: 3.627442654557353e-05 loss: 0.0851 (0.0785) time: 3.0246 data: 0.0073 max mem: 33408 +Epoch: [11] Total time: 2:13:00 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 2:27:55 time: 3.4497 data: 3.3364 max mem: 33408 +Test: [ 100/2573] eta: 0:04:38 time: 0.0803 data: 0.0015 max mem: 33408 +Test: [ 200/2573] eta: 0:03:50 time: 0.0811 data: 0.0015 max mem: 33408 +Test: [ 300/2573] eta: 0:03:27 time: 0.0812 data: 0.0015 max mem: 33408 +Test: [ 400/2573] eta: 0:03:11 time: 0.0809 data: 0.0014 max mem: 33408 +Test: [ 500/2573] eta: 0:02:59 time: 0.0797 data: 0.0014 max mem: 33408 +Test: [ 600/2573] eta: 0:02:49 time: 0.0802 data: 0.0015 max mem: 33408 +Test: [ 700/2573] eta: 0:02:39 time: 0.0802 data: 0.0015 max mem: 33408 +Test: [ 800/2573] eta: 0:02:30 time: 0.0837 data: 0.0014 max mem: 33408 +Test: [ 900/2573] eta: 0:02:21 time: 0.0803 data: 0.0015 max mem: 33408 +Test: [1000/2573] eta: 0:02:12 time: 0.0807 data: 0.0015 max mem: 33408 +Test: [1100/2573] eta: 0:02:03 time: 0.0820 data: 0.0014 max mem: 33408 +Test: [1200/2573] eta: 0:01:54 time: 0.0806 data: 0.0014 max mem: 33408 +Test: [1300/2573] eta: 0:01:46 time: 0.0808 data: 0.0014 max mem: 33408 +Test: [1400/2573] eta: 0:01:37 time: 0.0799 data: 0.0015 max mem: 33408 +Test: [1500/2573] eta: 0:01:29 time: 0.0801 data: 0.0015 max mem: 33408 +Test: [1600/2573] eta: 0:01:20 time: 0.0843 data: 0.0014 max mem: 33408 +Test: [1700/2573] eta: 0:01:12 time: 0.0793 data: 0.0014 max mem: 33408 +Test: [1800/2573] eta: 0:01:03 time: 0.0822 data: 0.0014 max mem: 33408 +Test: [1900/2573] eta: 0:00:55 time: 0.0785 data: 0.0014 max mem: 33408 +Test: [2000/2573] eta: 0:00:47 time: 0.0810 data: 0.0015 max mem: 33408 +Test: [2100/2573] eta: 0:00:38 time: 0.0819 data: 0.0014 max mem: 33408 +Test: [2200/2573] eta: 0:00:30 time: 0.0829 data: 0.0014 max mem: 33408 +Test: [2300/2573] eta: 0:00:22 time: 0.0830 data: 0.0015 max mem: 33408 +Test: [2400/2573] eta: 0:00:14 time: 0.0773 data: 0.0014 max mem: 33408 +Test: [2500/2573] eta: 0:00:05 time: 0.0811 data: 0.0015 max mem: 33408 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: Total time: 0:03:32 +Final results: +Mean IoU is 61.14 + + precision@0.5 = 69.12 + precision@0.6 = 63.75 + precision@0.7 = 55.76 + precision@0.8 = 43.75 + precision@0.9 = 20.38 + overall IoU = 60.16 + +Average object IoU 61.141450851500245 +Overall IoU 60.16259002685547 +Better epoch: 11 + +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [12] [ 0/2639] eta: 4:01:36 lr: 3.627045056933162e-05 loss: 0.0682 (0.0682) time: 5.4932 data: 2.2405 max mem: 33408 +Epoch: [12] [ 10/2639] eta: 2:25:50 lr: 3.6266032761153045e-05 loss: 0.0680 (0.0783) time: 3.3283 data: 0.2105 max mem: 33408 +Epoch: [12] [ 20/2639] eta: 2:18:13 lr: 3.62616148931778e-05 loss: 0.0680 (0.0761) time: 3.0505 data: 0.0075 max mem: 33408 +Epoch: [12] [ 30/2639] eta: 2:15:50 lr: 3.6257196965396984e-05 loss: 0.0721 (0.0765) time: 3.0119 data: 0.0078 max mem: 33408 +Epoch: [12] [ 40/2639] eta: 2:13:56 lr: 3.6252778977801674e-05 loss: 0.0721 (0.0784) time: 3.0140 data: 0.0084 max mem: 33408 +Epoch: [12] [ 50/2639] eta: 2:13:19 lr: 3.624836093038296e-05 loss: 0.0650 (0.0783) time: 3.0368 data: 0.0086 max mem: 33408 +Epoch: [12] [ 60/2639] eta: 2:12:03 lr: 3.6243942823131956e-05 loss: 0.0641 (0.0803) time: 3.0308 data: 0.0084 max mem: 33408 +Epoch: [12] [ 70/2639] eta: 2:11:37 lr: 3.6239524656039726e-05 loss: 0.0671 (0.0799) time: 3.0341 data: 0.0078 max mem: 33408 +Epoch: [12] [ 80/2639] eta: 2:10:56 lr: 3.623510642909736e-05 loss: 0.0614 (0.0783) time: 3.0643 data: 0.0079 max mem: 33408 +Epoch: [12] [ 90/2639] eta: 2:10:02 lr: 3.623068814229593e-05 loss: 0.0646 (0.0789) time: 3.0136 data: 0.0085 max mem: 33408 +Epoch: [12] [ 100/2639] eta: 2:09:15 lr: 3.622626979562652e-05 loss: 0.0667 (0.0776) time: 2.9915 data: 0.0078 max mem: 33408 +Epoch: [12] [ 110/2639] eta: 2:08:30 lr: 3.622185138908021e-05 loss: 0.0667 (0.0789) time: 2.9940 data: 0.0073 max mem: 33408 +Epoch: [12] [ 120/2639] eta: 2:08:01 lr: 3.621743292264808e-05 loss: 0.0695 (0.0783) time: 3.0231 data: 0.0076 max mem: 33408 +Epoch: [12] [ 130/2639] eta: 2:07:22 lr: 3.621301439632118e-05 loss: 0.0578 (0.0773) time: 3.0317 data: 0.0080 max mem: 33408 +Epoch: [12] [ 140/2639] eta: 2:07:02 lr: 3.620859581009058e-05 loss: 0.0583 (0.0768) time: 3.0560 data: 0.0080 max mem: 33408 +Epoch: [12] [ 150/2639] eta: 2:06:24 lr: 3.620417716394736e-05 loss: 0.0664 (0.0766) time: 3.0536 data: 0.0078 max mem: 33408 +Epoch: [12] [ 160/2639] eta: 2:05:45 lr: 3.6199758457882576e-05 loss: 0.0602 (0.0759) time: 2.9976 data: 0.0078 max mem: 33408 +Epoch: [12] [ 170/2639] eta: 2:05:16 lr: 3.619533969188728e-05 loss: 0.0602 (0.0753) time: 3.0218 data: 0.0080 max mem: 33408 +Epoch: [12] [ 180/2639] eta: 2:04:41 lr: 3.619092086595254e-05 loss: 0.0673 (0.0759) time: 3.0306 data: 0.0084 max mem: 33408 +Epoch: [12] [ 190/2639] eta: 2:04:18 lr: 3.618650198006941e-05 loss: 0.0712 (0.0757) time: 3.0571 data: 0.0084 max mem: 33408 +Epoch: [12] [ 200/2639] eta: 2:03:56 lr: 3.618208303422894e-05 loss: 0.0618 (0.0749) time: 3.1078 data: 0.0080 max mem: 33408 +Epoch: [12] [ 210/2639] eta: 2:03:24 lr: 3.617766402842218e-05 loss: 0.0515 (0.0744) time: 3.0765 data: 0.0077 max mem: 33408 +Epoch: [12] [ 220/2639] eta: 2:02:44 lr: 3.617324496264018e-05 loss: 0.0649 (0.0745) time: 3.0008 data: 0.0080 max mem: 33408 +Epoch: [12] [ 230/2639] eta: 2:02:12 lr: 3.616882583687398e-05 loss: 0.0709 (0.0749) time: 2.9957 data: 0.0079 max mem: 33408 +Epoch: [12] [ 240/2639] eta: 2:01:33 lr: 3.616440665111463e-05 loss: 0.0644 (0.0749) time: 2.9932 data: 0.0079 max mem: 33408 +Epoch: [12] [ 250/2639] eta: 2:00:58 lr: 3.615998740535316e-05 loss: 0.0644 (0.0749) time: 2.9743 data: 0.0078 max mem: 33408 +Epoch: [12] [ 260/2639] eta: 2:00:24 lr: 3.615556809958061e-05 loss: 0.0697 (0.0756) time: 2.9941 data: 0.0076 max mem: 33408 +Epoch: [12] [ 270/2639] eta: 1:59:58 lr: 3.615114873378803e-05 loss: 0.0627 (0.0750) time: 3.0404 data: 0.0078 max mem: 33408 +Epoch: [12] [ 280/2639] eta: 1:59:24 lr: 3.6146729307966424e-05 loss: 0.0578 (0.0747) time: 3.0432 data: 0.0083 max mem: 33408 +Epoch: [12] [ 290/2639] eta: 1:58:54 lr: 3.614230982210684e-05 loss: 0.0650 (0.0747) time: 3.0206 data: 0.0083 max mem: 33408 +Epoch: [12] [ 300/2639] eta: 1:58:19 lr: 3.6137890276200305e-05 loss: 0.0634 (0.0746) time: 3.0091 data: 0.0077 max mem: 33408 +Epoch: [12] [ 310/2639] eta: 1:57:54 lr: 3.613347067023783e-05 loss: 0.0634 (0.0742) time: 3.0441 data: 0.0078 max mem: 33408 +Epoch: [12] [ 320/2639] eta: 1:57:21 lr: 3.6129051004210464e-05 loss: 0.0636 (0.0741) time: 3.0536 data: 0.0081 max mem: 33408 +Epoch: [12] [ 330/2639] eta: 1:56:56 lr: 3.61246312781092e-05 loss: 0.0661 (0.0746) time: 3.0573 data: 0.0084 max mem: 33408 +Epoch: [12] [ 340/2639] eta: 1:56:26 lr: 3.612021149192506e-05 loss: 0.0707 (0.0746) time: 3.0771 data: 0.0081 max mem: 33408 +Epoch: [12] [ 350/2639] eta: 1:55:55 lr: 3.611579164564907e-05 loss: 0.0700 (0.0745) time: 3.0371 data: 0.0076 max mem: 33408 +Epoch: [12] [ 360/2639] eta: 1:55:20 lr: 3.6111371739272225e-05 loss: 0.0693 (0.0748) time: 2.9976 data: 0.0077 max mem: 33408 +Epoch: [12] [ 370/2639] eta: 1:54:48 lr: 3.6106951772785554e-05 loss: 0.0728 (0.0748) time: 2.9836 data: 0.0078 max mem: 33408 +Epoch: [12] [ 380/2639] eta: 1:54:16 lr: 3.610253174618004e-05 loss: 0.0721 (0.0748) time: 3.0114 data: 0.0075 max mem: 33408 +Epoch: [12] [ 390/2639] eta: 1:53:46 lr: 3.60981116594467e-05 loss: 0.0664 (0.0747) time: 3.0298 data: 0.0077 max mem: 33408 +Epoch: [12] [ 400/2639] eta: 1:53:16 lr: 3.609369151257655e-05 loss: 0.0607 (0.0748) time: 3.0379 data: 0.0082 max mem: 33408 +Epoch: [12] [ 410/2639] eta: 1:52:42 lr: 3.6089271305560564e-05 loss: 0.0578 (0.0748) time: 3.0057 data: 0.0084 max mem: 33408 +Epoch: [12] [ 420/2639] eta: 1:52:11 lr: 3.6084851038389746e-05 loss: 0.0652 (0.0746) time: 2.9981 data: 0.0081 max mem: 33408 +Epoch: [12] [ 430/2639] eta: 1:51:41 lr: 3.6080430711055085e-05 loss: 0.0652 (0.0743) time: 3.0272 data: 0.0083 max mem: 33408 +Epoch: [12] [ 440/2639] eta: 1:51:08 lr: 3.607601032354759e-05 loss: 0.0647 (0.0745) time: 3.0146 data: 0.0083 max mem: 33408 +Epoch: [12] [ 450/2639] eta: 1:50:40 lr: 3.607158987585823e-05 loss: 0.0707 (0.0746) time: 3.0346 data: 0.0078 max mem: 33408 +Epoch: [12] [ 460/2639] eta: 1:50:12 lr: 3.6067169367978e-05 loss: 0.0799 (0.0749) time: 3.0809 data: 0.0077 max mem: 33408 +Epoch: [12] [ 470/2639] eta: 1:49:41 lr: 3.6062748799897875e-05 loss: 0.0773 (0.0749) time: 3.0420 data: 0.0077 max mem: 33408 +Epoch: [12] [ 480/2639] eta: 1:49:10 lr: 3.605832817160885e-05 loss: 0.0758 (0.0749) time: 3.0190 data: 0.0077 max mem: 33408 +Epoch: [12] [ 490/2639] eta: 1:48:40 lr: 3.6053907483101904e-05 loss: 0.0860 (0.0753) time: 3.0350 data: 0.0077 max mem: 33408 +Epoch: [12] [ 500/2639] eta: 1:48:09 lr: 3.6049486734367986e-05 loss: 0.0875 (0.0757) time: 3.0287 data: 0.0077 max mem: 33408 +Epoch: [12] [ 510/2639] eta: 1:47:37 lr: 3.60450659253981e-05 loss: 0.0717 (0.0755) time: 3.0117 data: 0.0076 max mem: 33408 +Epoch: [12] [ 520/2639] eta: 1:47:07 lr: 3.6040645056183206e-05 loss: 0.0661 (0.0756) time: 3.0212 data: 0.0081 max mem: 33408 +Epoch: [12] [ 530/2639] eta: 1:46:36 lr: 3.603622412671426e-05 loss: 0.0625 (0.0754) time: 3.0280 data: 0.0083 max mem: 33408 +Epoch: [12] [ 540/2639] eta: 1:46:05 lr: 3.603180313698224e-05 loss: 0.0713 (0.0758) time: 3.0076 data: 0.0079 max mem: 33408 +Epoch: [12] [ 550/2639] eta: 1:45:35 lr: 3.6027382086978104e-05 loss: 0.0793 (0.0758) time: 3.0184 data: 0.0076 max mem: 33408 +Epoch: [12] [ 560/2639] eta: 1:45:01 lr: 3.602296097669281e-05 loss: 0.0748 (0.0759) time: 2.9865 data: 0.0074 max mem: 33408 +Epoch: [12] [ 570/2639] eta: 1:44:28 lr: 3.6018539806117327e-05 loss: 0.0673 (0.0757) time: 2.9541 data: 0.0075 max mem: 33408 +Epoch: [12] [ 580/2639] eta: 1:44:00 lr: 3.60141185752426e-05 loss: 0.0620 (0.0756) time: 3.0324 data: 0.0076 max mem: 33408 +Epoch: [12] [ 590/2639] eta: 1:43:31 lr: 3.600969728405958e-05 loss: 0.0604 (0.0753) time: 3.0729 data: 0.0079 max mem: 33408 +Epoch: [12] [ 600/2639] eta: 1:43:00 lr: 3.6005275932559216e-05 loss: 0.0568 (0.0753) time: 3.0449 data: 0.0081 max mem: 33408 +Epoch: [12] [ 610/2639] eta: 1:42:31 lr: 3.600085452073247e-05 loss: 0.0535 (0.0750) time: 3.0407 data: 0.0078 max mem: 33408 +Epoch: [12] [ 620/2639] eta: 1:41:59 lr: 3.599643304857027e-05 loss: 0.0476 (0.0749) time: 3.0106 data: 0.0080 max mem: 33408 +Epoch: [12] [ 630/2639] eta: 1:41:27 lr: 3.5992011516063565e-05 loss: 0.0637 (0.0751) time: 2.9920 data: 0.0083 max mem: 33408 +Epoch: [12] [ 640/2639] eta: 1:40:57 lr: 3.5987589923203284e-05 loss: 0.0674 (0.0752) time: 3.0099 data: 0.0081 max mem: 33408 +Epoch: [12] [ 650/2639] eta: 1:40:26 lr: 3.5983168269980385e-05 loss: 0.0759 (0.0752) time: 3.0238 data: 0.0079 max mem: 33408 +Epoch: [12] [ 660/2639] eta: 1:39:56 lr: 3.597874655638578e-05 loss: 0.0707 (0.0752) time: 3.0254 data: 0.0079 max mem: 33408 +Epoch: [12] [ 670/2639] eta: 1:39:28 lr: 3.597432478241041e-05 loss: 0.0615 (0.0750) time: 3.0662 data: 0.0077 max mem: 33408 +Epoch: [12] [ 680/2639] eta: 1:38:57 lr: 3.5969902948045206e-05 loss: 0.0545 (0.0749) time: 3.0677 data: 0.0077 max mem: 33408 +Epoch: [12] [ 690/2639] eta: 1:38:26 lr: 3.59654810532811e-05 loss: 0.0672 (0.0750) time: 3.0155 data: 0.0077 max mem: 33408 +Epoch: [12] [ 700/2639] eta: 1:37:58 lr: 3.5961059098109e-05 loss: 0.0670 (0.0749) time: 3.0516 data: 0.0077 max mem: 33408 +Epoch: [12] [ 710/2639] eta: 1:37:27 lr: 3.595663708251984e-05 loss: 0.0612 (0.0749) time: 3.0476 data: 0.0078 max mem: 33408 +Epoch: [12] [ 720/2639] eta: 1:36:56 lr: 3.595221500650453e-05 loss: 0.0783 (0.0752) time: 3.0128 data: 0.0079 max mem: 33408 +Epoch: [12] [ 730/2639] eta: 1:36:24 lr: 3.594779287005399e-05 loss: 0.0768 (0.0751) time: 2.9969 data: 0.0079 max mem: 33408 +Epoch: [12] [ 740/2639] eta: 1:35:55 lr: 3.594337067315913e-05 loss: 0.0618 (0.0750) time: 3.0130 data: 0.0074 max mem: 33408 +Epoch: [12] [ 750/2639] eta: 1:35:26 lr: 3.5938948415810866e-05 loss: 0.0616 (0.0749) time: 3.0780 data: 0.0073 max mem: 33408 +Epoch: [12] [ 760/2639] eta: 1:34:55 lr: 3.59345260980001e-05 loss: 0.0771 (0.0752) time: 3.0425 data: 0.0075 max mem: 33408 +Epoch: [12] [ 770/2639] eta: 1:34:27 lr: 3.593010371971775e-05 loss: 0.0655 (0.0751) time: 3.0602 data: 0.0072 max mem: 33408 +Epoch: [12] [ 780/2639] eta: 1:33:55 lr: 3.592568128095471e-05 loss: 0.0655 (0.0751) time: 3.0541 data: 0.0074 max mem: 33408 +Epoch: [12] [ 790/2639] eta: 1:33:24 lr: 3.5921258781701875e-05 loss: 0.0712 (0.0750) time: 2.9900 data: 0.0074 max mem: 33408 +Epoch: [12] [ 800/2639] eta: 1:32:52 lr: 3.591683622195014e-05 loss: 0.0720 (0.0750) time: 2.9817 data: 0.0073 max mem: 33408 +Epoch: [12] [ 810/2639] eta: 1:32:22 lr: 3.591241360169042e-05 loss: 0.0749 (0.0750) time: 3.0065 data: 0.0075 max mem: 33408 +Epoch: [12] [ 820/2639] eta: 1:31:52 lr: 3.590799092091359e-05 loss: 0.0622 (0.0748) time: 3.0443 data: 0.0078 max mem: 33408 +Epoch: [12] [ 830/2639] eta: 1:31:21 lr: 3.590356817961055e-05 loss: 0.0527 (0.0746) time: 3.0118 data: 0.0080 max mem: 33408 +Epoch: [12] [ 840/2639] eta: 1:30:50 lr: 3.5899145377772174e-05 loss: 0.0565 (0.0746) time: 2.9936 data: 0.0078 max mem: 33408 +Epoch: [12] [ 850/2639] eta: 1:30:18 lr: 3.5894722515389354e-05 loss: 0.0568 (0.0745) time: 2.9660 data: 0.0078 max mem: 33408 +Epoch: [12] [ 860/2639] eta: 1:29:46 lr: 3.589029959245299e-05 loss: 0.0665 (0.0744) time: 2.9413 data: 0.0081 max mem: 33408 +Epoch: [12] [ 870/2639] eta: 1:29:14 lr: 3.588587660895393e-05 loss: 0.0676 (0.0744) time: 2.9541 data: 0.0084 max mem: 33408 +Epoch: [12] [ 880/2639] eta: 1:28:44 lr: 3.5881453564883064e-05 loss: 0.0733 (0.0745) time: 2.9937 data: 0.0080 max mem: 33408 +Epoch: [12] [ 890/2639] eta: 1:28:15 lr: 3.587703046023126e-05 loss: 0.0768 (0.0746) time: 3.0545 data: 0.0077 max mem: 33408 +Epoch: [12] [ 900/2639] eta: 1:27:44 lr: 3.5872607294989414e-05 loss: 0.0620 (0.0744) time: 3.0494 data: 0.0080 max mem: 33408 +Epoch: [12] [ 910/2639] eta: 1:27:15 lr: 3.586818406914837e-05 loss: 0.0607 (0.0744) time: 3.0398 data: 0.0082 max mem: 33408 +Epoch: [12] [ 920/2639] eta: 1:26:45 lr: 3.5863760782699e-05 loss: 0.0610 (0.0743) time: 3.0610 data: 0.0082 max mem: 33408 +Epoch: [12] [ 930/2639] eta: 1:26:15 lr: 3.585933743563216e-05 loss: 0.0590 (0.0742) time: 3.0473 data: 0.0081 max mem: 33408 +Epoch: [12] [ 940/2639] eta: 1:25:44 lr: 3.585491402793873e-05 loss: 0.0611 (0.0742) time: 3.0221 data: 0.0082 max mem: 33408 +Epoch: [12] [ 950/2639] eta: 1:25:13 lr: 3.585049055960955e-05 loss: 0.0629 (0.0742) time: 2.9973 data: 0.0081 max mem: 33408 +Epoch: [12] [ 960/2639] eta: 1:24:42 lr: 3.584606703063549e-05 loss: 0.0642 (0.0742) time: 2.9893 data: 0.0080 max mem: 33408 +Epoch: [12] [ 970/2639] eta: 1:24:13 lr: 3.58416434410074e-05 loss: 0.0644 (0.0741) time: 3.0473 data: 0.0080 max mem: 33408 +Epoch: [12] [ 980/2639] eta: 1:23:43 lr: 3.583721979071613e-05 loss: 0.0706 (0.0741) time: 3.0611 data: 0.0078 max mem: 33408 +Epoch: [12] [ 990/2639] eta: 1:23:13 lr: 3.583279607975251e-05 loss: 0.0706 (0.0742) time: 3.0248 data: 0.0079 max mem: 33408 +Epoch: [12] [1000/2639] eta: 1:22:42 lr: 3.58283723081074e-05 loss: 0.0623 (0.0742) time: 3.0362 data: 0.0080 max mem: 33408 +Epoch: [12] [1010/2639] eta: 1:22:12 lr: 3.582394847577165e-05 loss: 0.0632 (0.0744) time: 3.0418 data: 0.0079 max mem: 33408 +Epoch: [12] [1020/2639] eta: 1:21:42 lr: 3.58195245827361e-05 loss: 0.0744 (0.0744) time: 3.0167 data: 0.0081 max mem: 33408 +Epoch: [12] [1030/2639] eta: 1:21:12 lr: 3.581510062899157e-05 loss: 0.0695 (0.0745) time: 3.0226 data: 0.0078 max mem: 33408 +Epoch: [12] [1040/2639] eta: 1:20:41 lr: 3.58106766145289e-05 loss: 0.0666 (0.0744) time: 3.0172 data: 0.0081 max mem: 33408 +Epoch: [12] [1050/2639] eta: 1:20:10 lr: 3.580625253933893e-05 loss: 0.0637 (0.0743) time: 2.9970 data: 0.0083 max mem: 33408 +Epoch: [12] [1060/2639] eta: 1:19:40 lr: 3.580182840341248e-05 loss: 0.0590 (0.0743) time: 3.0095 data: 0.0077 max mem: 33408 +Epoch: [12] [1070/2639] eta: 1:19:10 lr: 3.5797404206740395e-05 loss: 0.0706 (0.0743) time: 3.0278 data: 0.0080 max mem: 33408 +Epoch: [12] [1080/2639] eta: 1:18:39 lr: 3.5792979949313474e-05 loss: 0.0706 (0.0744) time: 3.0166 data: 0.0083 max mem: 33408 +Epoch: [12] [1090/2639] eta: 1:18:07 lr: 3.578855563112255e-05 loss: 0.0627 (0.0743) time: 2.9567 data: 0.0079 max mem: 33408 +Epoch: [12] [1100/2639] eta: 1:17:38 lr: 3.578413125215844e-05 loss: 0.0653 (0.0745) time: 3.0110 data: 0.0081 max mem: 33408 +Epoch: [12] [1110/2639] eta: 1:17:07 lr: 3.5779706812411975e-05 loss: 0.0803 (0.0746) time: 3.0523 data: 0.0082 max mem: 33408 +Epoch: [12] [1120/2639] eta: 1:16:37 lr: 3.577528231187395e-05 loss: 0.0729 (0.0747) time: 3.0250 data: 0.0081 max mem: 33408 +Epoch: [12] [1130/2639] eta: 1:16:07 lr: 3.5770857750535175e-05 loss: 0.0702 (0.0746) time: 3.0533 data: 0.0082 max mem: 33408 +Epoch: [12] [1140/2639] eta: 1:15:37 lr: 3.5766433128386465e-05 loss: 0.0618 (0.0745) time: 3.0274 data: 0.0081 max mem: 33408 +Epoch: [12] [1150/2639] eta: 1:15:07 lr: 3.576200844541863e-05 loss: 0.0572 (0.0744) time: 3.0324 data: 0.0080 max mem: 33408 +Epoch: [12] [1160/2639] eta: 1:14:37 lr: 3.575758370162246e-05 loss: 0.0647 (0.0743) time: 3.0729 data: 0.0079 max mem: 33408 +Epoch: [12] [1170/2639] eta: 1:14:07 lr: 3.575315889698876e-05 loss: 0.0679 (0.0743) time: 3.0398 data: 0.0079 max mem: 33408 +Epoch: [12] [1180/2639] eta: 1:13:37 lr: 3.5748734031508337e-05 loss: 0.0634 (0.0741) time: 3.0579 data: 0.0080 max mem: 33408 +Epoch: [12] [1190/2639] eta: 1:13:07 lr: 3.574430910517198e-05 loss: 0.0604 (0.0741) time: 3.0438 data: 0.0078 max mem: 33408 +Epoch: [12] [1200/2639] eta: 1:12:38 lr: 3.5739884117970476e-05 loss: 0.0670 (0.0740) time: 3.0533 data: 0.0080 max mem: 33408 +Epoch: [12] [1210/2639] eta: 1:12:07 lr: 3.5735459069894616e-05 loss: 0.0682 (0.0743) time: 3.0436 data: 0.0085 max mem: 33408 +Epoch: [12] [1220/2639] eta: 1:11:37 lr: 3.5731033960935186e-05 loss: 0.0825 (0.0743) time: 3.0356 data: 0.0080 max mem: 33408 +Epoch: [12] [1230/2639] eta: 1:11:07 lr: 3.5726608791082985e-05 loss: 0.0667 (0.0743) time: 3.0710 data: 0.0076 max mem: 33408 +Epoch: [12] [1240/2639] eta: 1:10:36 lr: 3.572218356032878e-05 loss: 0.0668 (0.0742) time: 3.0267 data: 0.0080 max mem: 33408 +Epoch: [12] [1250/2639] eta: 1:10:06 lr: 3.571775826866335e-05 loss: 0.0668 (0.0742) time: 2.9970 data: 0.0083 max mem: 33408 +Epoch: [12] [1260/2639] eta: 1:09:35 lr: 3.5713332916077466e-05 loss: 0.0720 (0.0743) time: 2.9912 data: 0.0086 max mem: 33408 +Epoch: [12] [1270/2639] eta: 1:09:05 lr: 3.570890750256192e-05 loss: 0.0682 (0.0742) time: 3.0342 data: 0.0084 max mem: 33408 +Epoch: [12] [1280/2639] eta: 1:08:36 lr: 3.570448202810747e-05 loss: 0.0598 (0.0741) time: 3.0789 data: 0.0079 max mem: 33408 +Epoch: [12] [1290/2639] eta: 1:08:05 lr: 3.570005649270488e-05 loss: 0.0629 (0.0741) time: 3.0465 data: 0.0082 max mem: 33408 +Epoch: [12] [1300/2639] eta: 1:07:34 lr: 3.569563089634492e-05 loss: 0.0641 (0.0740) time: 2.9932 data: 0.0086 max mem: 33408 +Epoch: [12] [1310/2639] eta: 1:07:05 lr: 3.569120523901836e-05 loss: 0.0602 (0.0739) time: 3.0352 data: 0.0084 max mem: 33408 +Epoch: [12] [1320/2639] eta: 1:06:35 lr: 3.568677952071596e-05 loss: 0.0602 (0.0740) time: 3.0671 data: 0.0082 max mem: 33408 +Epoch: [12] [1330/2639] eta: 1:06:04 lr: 3.568235374142847e-05 loss: 0.0602 (0.0739) time: 3.0266 data: 0.0081 max mem: 33408 +Epoch: [12] [1340/2639] eta: 1:05:33 lr: 3.567792790114664e-05 loss: 0.0638 (0.0740) time: 2.9810 data: 0.0079 max mem: 33408 +Epoch: [12] [1350/2639] eta: 1:05:03 lr: 3.567350199986123e-05 loss: 0.0647 (0.0739) time: 2.9938 data: 0.0077 max mem: 33408 +Epoch: [12] [1360/2639] eta: 1:04:32 lr: 3.566907603756299e-05 loss: 0.0588 (0.0738) time: 3.0016 data: 0.0076 max mem: 33408 +Epoch: [12] [1370/2639] eta: 1:04:02 lr: 3.566465001424267e-05 loss: 0.0630 (0.0738) time: 3.0169 data: 0.0076 max mem: 33408 +Epoch: [12] [1380/2639] eta: 1:03:31 lr: 3.566022392989101e-05 loss: 0.0605 (0.0738) time: 3.0197 data: 0.0077 max mem: 33408 +Epoch: [12] [1390/2639] eta: 1:03:01 lr: 3.5655797784498744e-05 loss: 0.0605 (0.0738) time: 2.9935 data: 0.0078 max mem: 33408 +Epoch: [12] [1400/2639] eta: 1:02:30 lr: 3.565137157805663e-05 loss: 0.0690 (0.0738) time: 3.0124 data: 0.0077 max mem: 33408 +Epoch: [12] [1410/2639] eta: 1:02:00 lr: 3.564694531055538e-05 loss: 0.0711 (0.0738) time: 3.0326 data: 0.0075 max mem: 33408 +Epoch: [12] [1420/2639] eta: 1:01:30 lr: 3.564251898198573e-05 loss: 0.0581 (0.0737) time: 3.0424 data: 0.0078 max mem: 33408 +Epoch: [12] [1430/2639] eta: 1:01:00 lr: 3.563809259233843e-05 loss: 0.0534 (0.0736) time: 3.0136 data: 0.0082 max mem: 33408 +Epoch: [12] [1440/2639] eta: 1:00:29 lr: 3.563366614160421e-05 loss: 0.0532 (0.0736) time: 2.9801 data: 0.0081 max mem: 33408 +Epoch: [12] [1450/2639] eta: 0:59:59 lr: 3.562923962977377e-05 loss: 0.0658 (0.0736) time: 3.0154 data: 0.0078 max mem: 33408 +Epoch: [12] [1460/2639] eta: 0:59:28 lr: 3.562481305683785e-05 loss: 0.0704 (0.0735) time: 3.0241 data: 0.0078 max mem: 33408 +Epoch: [12] [1470/2639] eta: 0:58:58 lr: 3.5620386422787155e-05 loss: 0.0613 (0.0735) time: 3.0271 data: 0.0075 max mem: 33408 +Epoch: [12] [1480/2639] eta: 0:58:29 lr: 3.561595972761242e-05 loss: 0.0663 (0.0736) time: 3.0799 data: 0.0072 max mem: 33408 +Epoch: [12] [1490/2639] eta: 0:57:58 lr: 3.561153297130436e-05 loss: 0.0796 (0.0736) time: 3.0644 data: 0.0075 max mem: 33408 +Epoch: [12] [1500/2639] eta: 0:57:29 lr: 3.560710615385367e-05 loss: 0.0709 (0.0736) time: 3.0695 data: 0.0077 max mem: 33408 +Epoch: [12] [1510/2639] eta: 0:56:59 lr: 3.560267927525107e-05 loss: 0.0712 (0.0736) time: 3.0862 data: 0.0077 max mem: 33408 +Epoch: [12] [1520/2639] eta: 0:56:28 lr: 3.559825233548726e-05 loss: 0.0705 (0.0736) time: 3.0311 data: 0.0078 max mem: 33408 +Epoch: [12] [1530/2639] eta: 0:55:59 lr: 3.5593825334552955e-05 loss: 0.0666 (0.0736) time: 3.0610 data: 0.0079 max mem: 33408 +Epoch: [12] [1540/2639] eta: 0:55:28 lr: 3.5589398272438853e-05 loss: 0.0663 (0.0737) time: 3.0470 data: 0.0078 max mem: 33408 +Epoch: [12] [1550/2639] eta: 0:54:58 lr: 3.558497114913564e-05 loss: 0.0663 (0.0738) time: 3.0180 data: 0.0076 max mem: 33408 +Epoch: [12] [1560/2639] eta: 0:54:27 lr: 3.558054396463402e-05 loss: 0.0687 (0.0738) time: 3.0303 data: 0.0076 max mem: 33408 +Epoch: [12] [1570/2639] eta: 0:53:57 lr: 3.557611671892469e-05 loss: 0.0711 (0.0739) time: 3.0292 data: 0.0075 max mem: 33408 +Epoch: [12] [1580/2639] eta: 0:53:27 lr: 3.5571689411998344e-05 loss: 0.0833 (0.0740) time: 3.0393 data: 0.0074 max mem: 33408 +Epoch: [12] [1590/2639] eta: 0:52:56 lr: 3.556726204384565e-05 loss: 0.0774 (0.0740) time: 3.0119 data: 0.0078 max mem: 33408 +Epoch: [12] [1600/2639] eta: 0:52:26 lr: 3.5562834614457315e-05 loss: 0.0761 (0.0740) time: 3.0083 data: 0.0077 max mem: 33408 +Epoch: [12] [1610/2639] eta: 0:51:56 lr: 3.555840712382401e-05 loss: 0.0630 (0.0739) time: 3.0133 data: 0.0076 max mem: 33408 +Epoch: [12] [1620/2639] eta: 0:51:25 lr: 3.5553979571936414e-05 loss: 0.0654 (0.0740) time: 2.9889 data: 0.0076 max mem: 33408 +Epoch: [12] [1630/2639] eta: 0:50:55 lr: 3.5549551958785204e-05 loss: 0.0715 (0.0740) time: 3.0126 data: 0.0076 max mem: 33408 +Epoch: [12] [1640/2639] eta: 0:50:25 lr: 3.5545124284361055e-05 loss: 0.0709 (0.0743) time: 3.0535 data: 0.0076 max mem: 33408 +Epoch: [12] [1650/2639] eta: 0:49:54 lr: 3.554069654865464e-05 loss: 0.0792 (0.0743) time: 3.0169 data: 0.0077 max mem: 33408 +Epoch: [12] [1660/2639] eta: 0:49:24 lr: 3.553626875165663e-05 loss: 0.0714 (0.0743) time: 3.0404 data: 0.0077 max mem: 33408 +Epoch: [12] [1670/2639] eta: 0:48:54 lr: 3.553184089335768e-05 loss: 0.0665 (0.0743) time: 3.0327 data: 0.0081 max mem: 33408 +Epoch: [12] [1680/2639] eta: 0:48:23 lr: 3.552741297374847e-05 loss: 0.0680 (0.0743) time: 2.9813 data: 0.0085 max mem: 33408 +Epoch: [12] [1690/2639] eta: 0:47:53 lr: 3.5522984992819645e-05 loss: 0.0682 (0.0743) time: 2.9864 data: 0.0082 max mem: 33408 +Epoch: [12] [1700/2639] eta: 0:47:23 lr: 3.551855695056187e-05 loss: 0.0648 (0.0742) time: 3.0259 data: 0.0078 max mem: 33408 +Epoch: [12] [1710/2639] eta: 0:46:52 lr: 3.55141288469658e-05 loss: 0.0629 (0.0742) time: 3.0333 data: 0.0077 max mem: 33408 +Epoch: [12] [1720/2639] eta: 0:46:22 lr: 3.5509700682022076e-05 loss: 0.0643 (0.0742) time: 3.0651 data: 0.0075 max mem: 33408 +Epoch: [12] [1730/2639] eta: 0:45:52 lr: 3.5505272455721375e-05 loss: 0.0647 (0.0742) time: 3.0804 data: 0.0075 max mem: 33408 +Epoch: [12] [1740/2639] eta: 0:45:22 lr: 3.550084416805432e-05 loss: 0.0618 (0.0741) time: 3.0179 data: 0.0078 max mem: 33408 +Epoch: [12] [1750/2639] eta: 0:44:51 lr: 3.549641581901156e-05 loss: 0.0640 (0.0743) time: 3.0137 data: 0.0078 max mem: 33408 +Epoch: [12] [1760/2639] eta: 0:44:21 lr: 3.549198740858373e-05 loss: 0.0675 (0.0742) time: 3.0310 data: 0.0079 max mem: 33408 +Epoch: [12] [1770/2639] eta: 0:43:51 lr: 3.5487558936761486e-05 loss: 0.0675 (0.0742) time: 3.0550 data: 0.0081 max mem: 33408 +Epoch: [12] [1780/2639] eta: 0:43:21 lr: 3.5483130403535456e-05 loss: 0.0646 (0.0743) time: 3.0293 data: 0.0081 max mem: 33408 +Epoch: [12] [1790/2639] eta: 0:42:50 lr: 3.547870180889627e-05 loss: 0.0651 (0.0743) time: 3.0043 data: 0.0084 max mem: 33408 +Epoch: [12] [1800/2639] eta: 0:42:20 lr: 3.547427315283456e-05 loss: 0.0666 (0.0743) time: 3.0156 data: 0.0088 max mem: 33408 +Epoch: [12] [1810/2639] eta: 0:41:50 lr: 3.546984443534095e-05 loss: 0.0699 (0.0743) time: 3.0225 data: 0.0083 max mem: 33408 +Epoch: [12] [1820/2639] eta: 0:41:20 lr: 3.546541565640608e-05 loss: 0.0725 (0.0744) time: 3.0438 data: 0.0076 max mem: 33408 +Epoch: [12] [1830/2639] eta: 0:40:50 lr: 3.546098681602055e-05 loss: 0.0689 (0.0744) time: 3.0661 data: 0.0076 max mem: 33408 +Epoch: [12] [1840/2639] eta: 0:40:19 lr: 3.5456557914175e-05 loss: 0.0607 (0.0744) time: 3.0590 data: 0.0077 max mem: 33408 +Epoch: [12] [1850/2639] eta: 0:39:49 lr: 3.545212895086003e-05 loss: 0.0795 (0.0745) time: 3.0366 data: 0.0074 max mem: 33408 +Epoch: [12] [1860/2639] eta: 0:39:19 lr: 3.544769992606627e-05 loss: 0.0767 (0.0745) time: 3.0597 data: 0.0077 max mem: 33408 +Epoch: [12] [1870/2639] eta: 0:38:49 lr: 3.544327083978433e-05 loss: 0.0704 (0.0746) time: 3.0363 data: 0.0078 max mem: 33408 +Epoch: [12] [1880/2639] eta: 0:38:18 lr: 3.543884169200479e-05 loss: 0.0658 (0.0745) time: 3.0109 data: 0.0080 max mem: 33408 +Epoch: [12] [1890/2639] eta: 0:37:48 lr: 3.543441248271829e-05 loss: 0.0690 (0.0746) time: 3.0048 data: 0.0079 max mem: 33408 +Epoch: [12] [1900/2639] eta: 0:37:17 lr: 3.542998321191543e-05 loss: 0.0768 (0.0746) time: 2.9989 data: 0.0072 max mem: 33408 +Epoch: [12] [1910/2639] eta: 0:36:47 lr: 3.5425553879586795e-05 loss: 0.0691 (0.0747) time: 3.0334 data: 0.0071 max mem: 33408 +Epoch: [12] [1920/2639] eta: 0:36:17 lr: 3.5421124485722984e-05 loss: 0.0676 (0.0748) time: 3.0247 data: 0.0072 max mem: 33408 +Epoch: [12] [1930/2639] eta: 0:35:47 lr: 3.54166950303146e-05 loss: 0.0713 (0.0748) time: 3.0471 data: 0.0075 max mem: 33408 +Epoch: [12] [1940/2639] eta: 0:35:16 lr: 3.5412265513352236e-05 loss: 0.0732 (0.0748) time: 3.0229 data: 0.0075 max mem: 33408 +Epoch: [12] [1950/2639] eta: 0:34:46 lr: 3.540783593482648e-05 loss: 0.0722 (0.0748) time: 3.0020 data: 0.0076 max mem: 33408 +Epoch: [12] [1960/2639] eta: 0:34:16 lr: 3.5403406294727916e-05 loss: 0.0605 (0.0747) time: 3.0384 data: 0.0074 max mem: 33408 +Epoch: [12] [1970/2639] eta: 0:33:45 lr: 3.5398976593047115e-05 loss: 0.0608 (0.0747) time: 3.0178 data: 0.0073 max mem: 33408 +Epoch: [12] [1980/2639] eta: 0:33:15 lr: 3.5394546829774685e-05 loss: 0.0688 (0.0748) time: 2.9851 data: 0.0078 max mem: 33408 +Epoch: [12] [1990/2639] eta: 0:32:45 lr: 3.5390117004901195e-05 loss: 0.0766 (0.0749) time: 3.0018 data: 0.0079 max mem: 33408 +Epoch: [12] [2000/2639] eta: 0:32:14 lr: 3.538568711841721e-05 loss: 0.0667 (0.0749) time: 3.0390 data: 0.0077 max mem: 33408 +Epoch: [12] [2010/2639] eta: 0:31:44 lr: 3.538125717031331e-05 loss: 0.0754 (0.0750) time: 3.0105 data: 0.0075 max mem: 33408 +Epoch: [12] [2020/2639] eta: 0:31:13 lr: 3.537682716058007e-05 loss: 0.0788 (0.0751) time: 2.9715 data: 0.0072 max mem: 33408 +Epoch: [12] [2030/2639] eta: 0:30:43 lr: 3.5372397089208045e-05 loss: 0.0805 (0.0752) time: 3.0080 data: 0.0077 max mem: 33408 +Epoch: [12] [2040/2639] eta: 0:30:13 lr: 3.536796695618782e-05 loss: 0.0778 (0.0752) time: 3.0585 data: 0.0078 max mem: 33408 +Epoch: [12] [2050/2639] eta: 0:29:43 lr: 3.536353676150993e-05 loss: 0.0750 (0.0753) time: 3.0515 data: 0.0072 max mem: 33408 +Epoch: [12] [2060/2639] eta: 0:29:13 lr: 3.535910650516495e-05 loss: 0.0578 (0.0753) time: 3.0799 data: 0.0078 max mem: 33408 +Epoch: [12] [2070/2639] eta: 0:28:43 lr: 3.535467618714344e-05 loss: 0.0516 (0.0753) time: 3.0775 data: 0.0081 max mem: 33408 +Epoch: [12] [2080/2639] eta: 0:28:12 lr: 3.535024580743595e-05 loss: 0.0623 (0.0753) time: 3.0242 data: 0.0077 max mem: 33408 +Epoch: [12] [2090/2639] eta: 0:27:42 lr: 3.534581536603303e-05 loss: 0.0681 (0.0753) time: 3.0243 data: 0.0078 max mem: 33408 +Epoch: [12] [2100/2639] eta: 0:27:12 lr: 3.534138486292522e-05 loss: 0.0640 (0.0753) time: 3.0317 data: 0.0080 max mem: 33408 +Epoch: [12] [2110/2639] eta: 0:26:42 lr: 3.533695429810307e-05 loss: 0.0607 (0.0753) time: 3.0637 data: 0.0079 max mem: 33408 +Epoch: [12] [2120/2639] eta: 0:26:11 lr: 3.533252367155715e-05 loss: 0.0610 (0.0752) time: 3.0437 data: 0.0074 max mem: 33408 +Epoch: [12] [2130/2639] eta: 0:25:41 lr: 3.532809298327795e-05 loss: 0.0718 (0.0754) time: 2.9850 data: 0.0076 max mem: 33408 +Epoch: [12] [2140/2639] eta: 0:25:11 lr: 3.532366223325603e-05 loss: 0.0718 (0.0753) time: 3.0054 data: 0.0078 max mem: 33408 +Epoch: [12] [2150/2639] eta: 0:24:40 lr: 3.5319231421481945e-05 loss: 0.0638 (0.0753) time: 3.0347 data: 0.0076 max mem: 33408 +Epoch: [12] [2160/2639] eta: 0:24:10 lr: 3.5314800547946206e-05 loss: 0.0738 (0.0753) time: 3.0184 data: 0.0075 max mem: 33408 +Epoch: [12] [2170/2639] eta: 0:23:40 lr: 3.5310369612639336e-05 loss: 0.0738 (0.0753) time: 3.0208 data: 0.0074 max mem: 33408 +Epoch: [12] [2180/2639] eta: 0:23:09 lr: 3.530593861555187e-05 loss: 0.0684 (0.0753) time: 2.9949 data: 0.0079 max mem: 33408 +Epoch: [12] [2190/2639] eta: 0:22:39 lr: 3.530150755667432e-05 loss: 0.0603 (0.0752) time: 2.9905 data: 0.0079 max mem: 33408 +Epoch: [12] [2200/2639] eta: 0:22:09 lr: 3.529707643599723e-05 loss: 0.0543 (0.0751) time: 3.0203 data: 0.0073 max mem: 33408 +Epoch: [12] [2210/2639] eta: 0:21:38 lr: 3.5292645253511104e-05 loss: 0.0609 (0.0751) time: 2.9892 data: 0.0072 max mem: 33408 +Epoch: [12] [2220/2639] eta: 0:21:08 lr: 3.528821400920645e-05 loss: 0.0623 (0.0751) time: 2.9751 data: 0.0074 max mem: 33408 +Epoch: [12] [2230/2639] eta: 0:20:38 lr: 3.528378270307379e-05 loss: 0.0696 (0.0752) time: 2.9819 data: 0.0077 max mem: 33408 +Epoch: [12] [2240/2639] eta: 0:20:07 lr: 3.527935133510364e-05 loss: 0.0696 (0.0752) time: 2.9977 data: 0.0077 max mem: 33408 +Epoch: [12] [2250/2639] eta: 0:19:37 lr: 3.527491990528649e-05 loss: 0.0601 (0.0752) time: 3.0028 data: 0.0073 max mem: 33408 +Epoch: [12] [2260/2639] eta: 0:19:07 lr: 3.527048841361284e-05 loss: 0.0851 (0.0753) time: 3.0442 data: 0.0073 max mem: 33408 +Epoch: [12] [2270/2639] eta: 0:18:36 lr: 3.5266056860073207e-05 loss: 0.0851 (0.0754) time: 3.0294 data: 0.0078 max mem: 33408 +Epoch: [12] [2280/2639] eta: 0:18:06 lr: 3.5261625244658084e-05 loss: 0.0689 (0.0754) time: 2.9462 data: 0.0086 max mem: 33408 +Epoch: [12] [2290/2639] eta: 0:17:36 lr: 3.5257193567357975e-05 loss: 0.0676 (0.0754) time: 2.9513 data: 0.0087 max mem: 33408 +Epoch: [12] [2300/2639] eta: 0:17:05 lr: 3.525276182816335e-05 loss: 0.0679 (0.0755) time: 2.9848 data: 0.0081 max mem: 33408 +Epoch: [12] [2310/2639] eta: 0:16:35 lr: 3.524833002706472e-05 loss: 0.0720 (0.0755) time: 2.9755 data: 0.0079 max mem: 33408 +Epoch: [12] [2320/2639] eta: 0:16:05 lr: 3.5243898164052566e-05 loss: 0.0641 (0.0755) time: 2.9643 data: 0.0077 max mem: 33408 +Epoch: [12] [2330/2639] eta: 0:15:34 lr: 3.5239466239117375e-05 loss: 0.0671 (0.0755) time: 2.9665 data: 0.0076 max mem: 33408 +Epoch: [12] [2340/2639] eta: 0:15:04 lr: 3.5235034252249614e-05 loss: 0.0697 (0.0755) time: 2.9621 data: 0.0081 max mem: 33408 +Epoch: [12] [2350/2639] eta: 0:14:34 lr: 3.523060220343978e-05 loss: 0.0636 (0.0755) time: 3.0175 data: 0.0084 max mem: 33408 +Epoch: [12] [2360/2639] eta: 0:14:04 lr: 3.5226170092678336e-05 loss: 0.0608 (0.0755) time: 3.0585 data: 0.0080 max mem: 33408 +Epoch: [12] [2370/2639] eta: 0:13:33 lr: 3.522173791995576e-05 loss: 0.0608 (0.0754) time: 3.0102 data: 0.0080 max mem: 33408 +Epoch: [12] [2380/2639] eta: 0:13:03 lr: 3.521730568526252e-05 loss: 0.0519 (0.0754) time: 3.0205 data: 0.0083 max mem: 33408 +Epoch: [12] [2390/2639] eta: 0:12:33 lr: 3.5212873388589086e-05 loss: 0.0630 (0.0754) time: 3.0270 data: 0.0086 max mem: 33408 +Epoch: [12] [2400/2639] eta: 0:12:02 lr: 3.5208441029925923e-05 loss: 0.0565 (0.0753) time: 3.0058 data: 0.0087 max mem: 33408 +Epoch: [12] [2410/2639] eta: 0:11:32 lr: 3.52040086092635e-05 loss: 0.0528 (0.0753) time: 3.0029 data: 0.0080 max mem: 33408 +Epoch: [12] [2420/2639] eta: 0:11:02 lr: 3.5199576126592254e-05 loss: 0.0725 (0.0753) time: 3.0308 data: 0.0080 max mem: 33408 +Epoch: [12] [2430/2639] eta: 0:10:32 lr: 3.5195143581902665e-05 loss: 0.0801 (0.0754) time: 3.0312 data: 0.0082 max mem: 33408 +Epoch: [12] [2440/2639] eta: 0:10:01 lr: 3.519071097518517e-05 loss: 0.0739 (0.0754) time: 3.0042 data: 0.0079 max mem: 33408 +Epoch: [12] [2450/2639] eta: 0:09:31 lr: 3.5186278306430234e-05 loss: 0.0688 (0.0754) time: 3.0328 data: 0.0080 max mem: 33408 +Epoch: [12] [2460/2639] eta: 0:09:01 lr: 3.518184557562829e-05 loss: 0.0688 (0.0754) time: 3.0354 data: 0.0083 max mem: 33408 +Epoch: [12] [2470/2639] eta: 0:08:31 lr: 3.517741278276978e-05 loss: 0.0613 (0.0754) time: 3.0445 data: 0.0082 max mem: 33408 +Epoch: [12] [2480/2639] eta: 0:08:00 lr: 3.517297992784518e-05 loss: 0.0662 (0.0754) time: 3.0381 data: 0.0081 max mem: 33408 +Epoch: [12] [2490/2639] eta: 0:07:30 lr: 3.51685470108449e-05 loss: 0.0662 (0.0754) time: 3.0480 data: 0.0079 max mem: 33408 +Epoch: [12] [2500/2639] eta: 0:07:00 lr: 3.5164114031759374e-05 loss: 0.0623 (0.0754) time: 3.0202 data: 0.0074 max mem: 33408 +Epoch: [12] [2510/2639] eta: 0:06:30 lr: 3.515968099057904e-05 loss: 0.0686 (0.0754) time: 2.9889 data: 0.0075 max mem: 33408 +Epoch: [12] [2520/2639] eta: 0:05:59 lr: 3.515524788729434e-05 loss: 0.0738 (0.0754) time: 3.0162 data: 0.0075 max mem: 33408 +Epoch: [12] [2530/2639] eta: 0:05:29 lr: 3.5150814721895695e-05 loss: 0.0683 (0.0753) time: 2.9977 data: 0.0077 max mem: 33408 +Epoch: [12] [2540/2639] eta: 0:04:59 lr: 3.514638149437353e-05 loss: 0.0635 (0.0753) time: 3.0517 data: 0.0077 max mem: 33408 +Epoch: [12] [2550/2639] eta: 0:04:29 lr: 3.514194820471827e-05 loss: 0.0652 (0.0753) time: 3.1027 data: 0.0078 max mem: 33408 +Epoch: [12] [2560/2639] eta: 0:03:59 lr: 3.5137514852920326e-05 loss: 0.0652 (0.0753) time: 3.0399 data: 0.0080 max mem: 33408 +Epoch: [12] [2570/2639] eta: 0:03:28 lr: 3.5133081438970135e-05 loss: 0.0595 (0.0753) time: 3.0059 data: 0.0080 max mem: 33408 +Epoch: [12] [2580/2639] eta: 0:02:58 lr: 3.512864796285809e-05 loss: 0.0621 (0.0753) time: 3.0091 data: 0.0079 max mem: 33408 +Epoch: [12] [2590/2639] eta: 0:02:28 lr: 3.5124214424574604e-05 loss: 0.0641 (0.0753) time: 2.9917 data: 0.0078 max mem: 33408 +Epoch: [12] [2600/2639] eta: 0:01:57 lr: 3.5119780824110095e-05 loss: 0.0571 (0.0752) time: 3.0264 data: 0.0078 max mem: 33408 +Epoch: [12] [2610/2639] eta: 0:01:27 lr: 3.511534716145497e-05 loss: 0.0571 (0.0752) time: 3.0234 data: 0.0078 max mem: 33408 +Epoch: [12] [2620/2639] eta: 0:00:57 lr: 3.511091343659962e-05 loss: 0.0675 (0.0752) time: 3.0040 data: 0.0079 max mem: 33408 +Epoch: [12] [2630/2639] eta: 0:00:27 lr: 3.510647964953446e-05 loss: 0.0707 (0.0753) time: 3.0552 data: 0.0078 max mem: 33408 +Epoch: [12] Total time: 2:13:04 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 2:24:41 time: 3.3741 data: 3.2827 max mem: 33408 +Test: [ 100/2573] eta: 0:04:33 time: 0.0777 data: 0.0014 max mem: 33408 +Test: [ 200/2573] eta: 0:03:46 time: 0.0788 data: 0.0014 max mem: 33408 +Test: [ 300/2573] eta: 0:03:22 time: 0.0805 data: 0.0014 max mem: 33408 +Test: [ 400/2573] eta: 0:03:08 time: 0.0818 data: 0.0014 max mem: 33408 +Test: [ 500/2573] eta: 0:02:56 time: 0.0792 data: 0.0013 max mem: 33408 +Test: [ 600/2573] eta: 0:02:46 time: 0.0800 data: 0.0014 max mem: 33408 +Test: [ 700/2573] eta: 0:02:37 time: 0.0801 data: 0.0014 max mem: 33408 +Test: [ 800/2573] eta: 0:02:28 time: 0.0828 data: 0.0014 max mem: 33408 +Test: [ 900/2573] eta: 0:02:19 time: 0.0808 data: 0.0014 max mem: 33408 +Test: [1000/2573] eta: 0:02:10 time: 0.0801 data: 0.0014 max mem: 33408 +Test: [1100/2573] eta: 0:02:02 time: 0.0817 data: 0.0015 max mem: 33408 +Test: [1200/2573] eta: 0:01:53 time: 0.0816 data: 0.0014 max mem: 33408 +Test: [1300/2573] eta: 0:01:45 time: 0.0801 data: 0.0014 max mem: 33408 +Test: [1400/2573] eta: 0:01:36 time: 0.0806 data: 0.0014 max mem: 33408 +Test: [1500/2573] eta: 0:01:28 time: 0.0819 data: 0.0014 max mem: 33408 +Test: [1600/2573] eta: 0:01:20 time: 0.0837 data: 0.0015 max mem: 33408 +Test: [1700/2573] eta: 0:01:11 time: 0.0787 data: 0.0014 max mem: 33408 +Test: [1800/2573] eta: 0:01:03 time: 0.0827 data: 0.0014 max mem: 33408 +Test: [1900/2573] eta: 0:00:55 time: 0.0786 data: 0.0014 max mem: 33408 +Test: [2000/2573] eta: 0:00:46 time: 0.0801 data: 0.0016 max mem: 33408 +Test: [2100/2573] eta: 0:00:38 time: 0.0829 data: 0.0014 max mem: 33408 +Test: [2200/2573] eta: 0:00:30 time: 0.0837 data: 0.0015 max mem: 33408 +Test: [2300/2573] eta: 0:00:22 time: 0.0823 data: 0.0015 max mem: 33408 +Test: [2400/2573] eta: 0:00:14 time: 0.0771 data: 0.0015 max mem: 33408 +Test: [2500/2573] eta: 0:00:05 time: 0.0815 data: 0.0014 max mem: 33408 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: Total time: 0:03:31 +Final results: +Mean IoU is 61.05 + + precision@0.5 = 68.57 + precision@0.6 = 63.05 + precision@0.7 = 55.21 + precision@0.8 = 42.52 + precision@0.9 = 20.00 + overall IoU = 59.66 + +Average object IoU 61.05222926646111 +Overall IoU 59.655433654785156 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [13] [ 0/2639] eta: 4:05:32 lr: 3.510248918797848e-05 loss: 0.1031 (0.1031) time: 5.5826 data: 2.3279 max mem: 33408 +Epoch: [13] [ 10/2639] eta: 2:21:16 lr: 3.50980552826882e-05 loss: 0.0857 (0.0931) time: 3.2244 data: 0.2188 max mem: 33408 +Epoch: [13] [ 20/2639] eta: 2:16:52 lr: 3.509362131516024e-05 loss: 0.0593 (0.0745) time: 3.0132 data: 0.0072 max mem: 33408 +Epoch: [13] [ 30/2639] eta: 2:15:03 lr: 3.5089187285385e-05 loss: 0.0648 (0.0776) time: 3.0410 data: 0.0076 max mem: 33408 +Epoch: [13] [ 40/2639] eta: 2:13:50 lr: 3.508475319335286e-05 loss: 0.0666 (0.0744) time: 3.0422 data: 0.0081 max mem: 33408 +Epoch: [13] [ 50/2639] eta: 2:12:35 lr: 3.508031903905421e-05 loss: 0.0632 (0.0729) time: 3.0211 data: 0.0074 max mem: 33408 +Epoch: [13] [ 60/2639] eta: 2:11:52 lr: 3.507588482247941e-05 loss: 0.0591 (0.0696) time: 3.0228 data: 0.0074 max mem: 33408 +Epoch: [13] [ 70/2639] eta: 2:11:03 lr: 3.507145054361886e-05 loss: 0.0559 (0.0682) time: 3.0305 data: 0.0076 max mem: 33408 +Epoch: [13] [ 80/2639] eta: 2:10:26 lr: 3.506701620246293e-05 loss: 0.0575 (0.0669) time: 3.0298 data: 0.0080 max mem: 33408 +Epoch: [13] [ 90/2639] eta: 2:10:02 lr: 3.506258179900198e-05 loss: 0.0576 (0.0668) time: 3.0607 data: 0.0079 max mem: 33408 +Epoch: [13] [ 100/2639] eta: 2:09:18 lr: 3.505814733322639e-05 loss: 0.0550 (0.0672) time: 3.0444 data: 0.0077 max mem: 33408 +Epoch: [13] [ 110/2639] eta: 2:08:44 lr: 3.505371280512652e-05 loss: 0.0677 (0.0680) time: 3.0246 data: 0.0076 max mem: 33408 +Epoch: [13] [ 120/2639] eta: 2:08:01 lr: 3.5049278214692735e-05 loss: 0.0642 (0.0674) time: 3.0182 data: 0.0078 max mem: 33408 +Epoch: [13] [ 130/2639] eta: 2:07:22 lr: 3.504484356191541e-05 loss: 0.0588 (0.0672) time: 3.0013 data: 0.0081 max mem: 33408 +Epoch: [13] [ 140/2639] eta: 2:06:38 lr: 3.504040884678488e-05 loss: 0.0553 (0.0671) time: 2.9877 data: 0.0083 max mem: 33408 +Epoch: [13] [ 150/2639] eta: 2:06:02 lr: 3.503597406929151e-05 loss: 0.0543 (0.0671) time: 2.9884 data: 0.0081 max mem: 33408 +Epoch: [13] [ 160/2639] eta: 2:05:27 lr: 3.503153922942564e-05 loss: 0.0569 (0.0667) time: 3.0058 data: 0.0076 max mem: 33408 +Epoch: [13] [ 170/2639] eta: 2:04:57 lr: 3.502710432717764e-05 loss: 0.0541 (0.0662) time: 3.0240 data: 0.0077 max mem: 33408 +Epoch: [13] [ 180/2639] eta: 2:04:30 lr: 3.5022669362537855e-05 loss: 0.0587 (0.0662) time: 3.0506 data: 0.0082 max mem: 33408 +Epoch: [13] [ 190/2639] eta: 2:03:53 lr: 3.5018234335496614e-05 loss: 0.0604 (0.0670) time: 3.0217 data: 0.0082 max mem: 33408 +Epoch: [13] [ 200/2639] eta: 2:03:25 lr: 3.501379924604426e-05 loss: 0.0693 (0.0671) time: 3.0214 data: 0.0077 max mem: 33408 +Epoch: [13] [ 210/2639] eta: 2:02:50 lr: 3.5009364094171136e-05 loss: 0.0689 (0.0679) time: 3.0254 data: 0.0076 max mem: 33408 +Epoch: [13] [ 220/2639] eta: 2:02:21 lr: 3.5004928879867574e-05 loss: 0.0558 (0.0677) time: 3.0190 data: 0.0076 max mem: 33408 +Epoch: [13] [ 230/2639] eta: 2:01:42 lr: 3.5000493603123914e-05 loss: 0.0521 (0.0671) time: 3.0020 data: 0.0075 max mem: 33408 +Epoch: [13] [ 240/2639] eta: 2:01:16 lr: 3.4996058263930466e-05 loss: 0.0497 (0.0667) time: 3.0164 data: 0.0075 max mem: 33408 +Epoch: [13] [ 250/2639] eta: 2:00:42 lr: 3.499162286227758e-05 loss: 0.0567 (0.0668) time: 3.0336 data: 0.0074 max mem: 33408 +Epoch: [13] [ 260/2639] eta: 2:00:12 lr: 3.498718739815556e-05 loss: 0.0567 (0.0666) time: 3.0107 data: 0.0079 max mem: 33408 +Epoch: [13] [ 270/2639] eta: 1:59:37 lr: 3.498275187155473e-05 loss: 0.0609 (0.0667) time: 3.0064 data: 0.0084 max mem: 33408 +Epoch: [13] [ 280/2639] eta: 1:59:10 lr: 3.4978316282465424e-05 loss: 0.0717 (0.0676) time: 3.0287 data: 0.0082 max mem: 33408 +Epoch: [13] [ 290/2639] eta: 1:58:39 lr: 3.4973880630877945e-05 loss: 0.0648 (0.0676) time: 3.0419 data: 0.0083 max mem: 33408 +Epoch: [13] [ 300/2639] eta: 1:58:02 lr: 3.49694449167826e-05 loss: 0.0580 (0.0674) time: 2.9815 data: 0.0082 max mem: 33408 +Epoch: [13] [ 310/2639] eta: 1:57:27 lr: 3.4965009140169695e-05 loss: 0.0580 (0.0675) time: 2.9588 data: 0.0079 max mem: 33408 +Epoch: [13] [ 320/2639] eta: 1:57:03 lr: 3.496057330102955e-05 loss: 0.0626 (0.0678) time: 3.0419 data: 0.0081 max mem: 33408 +Epoch: [13] [ 330/2639] eta: 1:56:28 lr: 3.495613739935247e-05 loss: 0.0626 (0.0678) time: 3.0384 data: 0.0081 max mem: 33408 +Epoch: [13] [ 340/2639] eta: 1:55:56 lr: 3.495170143512874e-05 loss: 0.0544 (0.0673) time: 2.9807 data: 0.0076 max mem: 33408 +Epoch: [13] [ 350/2639] eta: 1:55:28 lr: 3.494726540834867e-05 loss: 0.0544 (0.0678) time: 3.0265 data: 0.0075 max mem: 33408 +Epoch: [13] [ 360/2639] eta: 1:54:57 lr: 3.494282931900254e-05 loss: 0.0651 (0.0678) time: 3.0322 data: 0.0076 max mem: 33408 +Epoch: [13] [ 370/2639] eta: 1:54:25 lr: 3.4938393167080656e-05 loss: 0.0644 (0.0677) time: 3.0075 data: 0.0080 max mem: 33408 +Epoch: [13] [ 380/2639] eta: 1:53:53 lr: 3.493395695257331e-05 loss: 0.0643 (0.0679) time: 3.0008 data: 0.0080 max mem: 33408 +Epoch: [13] [ 390/2639] eta: 1:53:24 lr: 3.4929520675470774e-05 loss: 0.0536 (0.0680) time: 3.0236 data: 0.0076 max mem: 33408 +Epoch: [13] [ 400/2639] eta: 1:52:49 lr: 3.492508433576334e-05 loss: 0.0508 (0.0677) time: 2.9945 data: 0.0078 max mem: 33408 +Epoch: [13] [ 410/2639] eta: 1:52:25 lr: 3.492064793344128e-05 loss: 0.0555 (0.0678) time: 3.0427 data: 0.0080 max mem: 33408 +Epoch: [13] [ 420/2639] eta: 1:51:56 lr: 3.4916211468494885e-05 loss: 0.0622 (0.0678) time: 3.0957 data: 0.0082 max mem: 33408 +Epoch: [13] [ 430/2639] eta: 1:51:25 lr: 3.491177494091443e-05 loss: 0.0617 (0.0678) time: 3.0311 data: 0.0083 max mem: 33408 +Epoch: [13] [ 440/2639] eta: 1:50:56 lr: 3.490733835069016e-05 loss: 0.0617 (0.0682) time: 3.0286 data: 0.0081 max mem: 33408 +Epoch: [13] [ 450/2639] eta: 1:50:25 lr: 3.4902901697812376e-05 loss: 0.0623 (0.0686) time: 3.0231 data: 0.0082 max mem: 33408 +Epoch: [13] [ 460/2639] eta: 1:49:56 lr: 3.489846498227133e-05 loss: 0.0623 (0.0685) time: 3.0350 data: 0.0082 max mem: 33408 +Epoch: [13] [ 470/2639] eta: 1:49:26 lr: 3.489402820405728e-05 loss: 0.0633 (0.0686) time: 3.0528 data: 0.0081 max mem: 33408 +Epoch: [13] [ 480/2639] eta: 1:48:56 lr: 3.48895913631605e-05 loss: 0.0637 (0.0688) time: 3.0300 data: 0.0081 max mem: 33408 +Epoch: [13] [ 490/2639] eta: 1:48:24 lr: 3.488515445957123e-05 loss: 0.0604 (0.0687) time: 3.0028 data: 0.0080 max mem: 33408 +Epoch: [13] [ 500/2639] eta: 1:47:55 lr: 3.488071749327973e-05 loss: 0.0578 (0.0687) time: 3.0219 data: 0.0078 max mem: 33408 +Epoch: [13] [ 510/2639] eta: 1:47:26 lr: 3.487628046427627e-05 loss: 0.0505 (0.0687) time: 3.0561 data: 0.0077 max mem: 33408 +Epoch: [13] [ 520/2639] eta: 1:46:55 lr: 3.4871843372551075e-05 loss: 0.0505 (0.0687) time: 3.0362 data: 0.0077 max mem: 33408 +Epoch: [13] [ 530/2639] eta: 1:46:24 lr: 3.48674062180944e-05 loss: 0.0657 (0.0688) time: 3.0148 data: 0.0078 max mem: 33408 +Epoch: [13] [ 540/2639] eta: 1:45:55 lr: 3.486296900089649e-05 loss: 0.0657 (0.0690) time: 3.0306 data: 0.0079 max mem: 33408 +Epoch: [13] [ 550/2639] eta: 1:45:27 lr: 3.4858531720947577e-05 loss: 0.0609 (0.0690) time: 3.0696 data: 0.0081 max mem: 33408 +Epoch: [13] [ 560/2639] eta: 1:44:56 lr: 3.4854094378237906e-05 loss: 0.0718 (0.0691) time: 3.0528 data: 0.0080 max mem: 33408 +Epoch: [13] [ 570/2639] eta: 1:44:27 lr: 3.484965697275771e-05 loss: 0.0644 (0.0691) time: 3.0424 data: 0.0078 max mem: 33408 +Epoch: [13] [ 580/2639] eta: 1:43:57 lr: 3.484521950449721e-05 loss: 0.0585 (0.0688) time: 3.0473 data: 0.0079 max mem: 33408 +Epoch: [13] [ 590/2639] eta: 1:43:27 lr: 3.484078197344665e-05 loss: 0.0530 (0.0687) time: 3.0299 data: 0.0079 max mem: 33408 +Epoch: [13] [ 600/2639] eta: 1:42:55 lr: 3.483634437959624e-05 loss: 0.0632 (0.0686) time: 3.0130 data: 0.0082 max mem: 33408 +Epoch: [13] [ 610/2639] eta: 1:42:26 lr: 3.4831906722936214e-05 loss: 0.0516 (0.0683) time: 3.0369 data: 0.0079 max mem: 33408 +Epoch: [13] [ 620/2639] eta: 1:41:54 lr: 3.482746900345679e-05 loss: 0.0463 (0.0681) time: 3.0245 data: 0.0075 max mem: 33408 +Epoch: [13] [ 630/2639] eta: 1:41:25 lr: 3.4823031221148187e-05 loss: 0.0591 (0.0681) time: 3.0229 data: 0.0074 max mem: 33408 +Epoch: [13] [ 640/2639] eta: 1:40:56 lr: 3.4818593376000595e-05 loss: 0.0684 (0.0683) time: 3.0726 data: 0.0077 max mem: 33408 +Epoch: [13] [ 650/2639] eta: 1:40:24 lr: 3.4814155468004256e-05 loss: 0.0763 (0.0686) time: 3.0107 data: 0.0080 max mem: 33408 +Epoch: [13] [ 660/2639] eta: 1:39:55 lr: 3.4809717497149366e-05 loss: 0.0679 (0.0685) time: 3.0225 data: 0.0076 max mem: 33408 +Epoch: [13] [ 670/2639] eta: 1:39:26 lr: 3.4805279463426125e-05 loss: 0.0598 (0.0685) time: 3.0845 data: 0.0084 max mem: 33408 +Epoch: [13] [ 680/2639] eta: 1:38:56 lr: 3.480084136682475e-05 loss: 0.0589 (0.0687) time: 3.0480 data: 0.0087 max mem: 33408 +Epoch: [13] [ 690/2639] eta: 1:38:27 lr: 3.479640320733542e-05 loss: 0.0633 (0.0688) time: 3.0491 data: 0.0081 max mem: 33408 +Epoch: [13] [ 700/2639] eta: 1:37:55 lr: 3.4791964984948346e-05 loss: 0.0575 (0.0689) time: 3.0331 data: 0.0079 max mem: 33408 +Epoch: [13] [ 710/2639] eta: 1:37:25 lr: 3.478752669965372e-05 loss: 0.0600 (0.0690) time: 3.0166 data: 0.0074 max mem: 33408 +Epoch: [13] [ 720/2639] eta: 1:36:54 lr: 3.4783088351441725e-05 loss: 0.0635 (0.0690) time: 3.0134 data: 0.0076 max mem: 33408 +Epoch: [13] [ 730/2639] eta: 1:36:23 lr: 3.477864994030255e-05 loss: 0.0639 (0.0692) time: 2.9898 data: 0.0076 max mem: 33408 +Epoch: [13] [ 740/2639] eta: 1:35:52 lr: 3.4774211466226375e-05 loss: 0.0629 (0.0694) time: 3.0027 data: 0.0077 max mem: 33408 +Epoch: [13] [ 750/2639] eta: 1:35:22 lr: 3.47697729292034e-05 loss: 0.0585 (0.0692) time: 3.0190 data: 0.0077 max mem: 33408 +Epoch: [13] [ 760/2639] eta: 1:34:51 lr: 3.4765334329223794e-05 loss: 0.0647 (0.0692) time: 3.0251 data: 0.0078 max mem: 33408 +Epoch: [13] [ 770/2639] eta: 1:34:21 lr: 3.476089566627772e-05 loss: 0.0708 (0.0692) time: 3.0272 data: 0.0079 max mem: 33408 +Epoch: [13] [ 780/2639] eta: 1:33:52 lr: 3.475645694035537e-05 loss: 0.0617 (0.0692) time: 3.0585 data: 0.0078 max mem: 33408 +Epoch: [13] [ 790/2639] eta: 1:33:22 lr: 3.475201815144691e-05 loss: 0.0593 (0.0693) time: 3.0733 data: 0.0078 max mem: 33408 +Epoch: [13] [ 800/2639] eta: 1:32:53 lr: 3.47475792995425e-05 loss: 0.0519 (0.0691) time: 3.0736 data: 0.0077 max mem: 33408 +Epoch: [13] [ 810/2639] eta: 1:32:23 lr: 3.47431403846323e-05 loss: 0.0572 (0.0692) time: 3.0590 data: 0.0076 max mem: 33408 +Epoch: [13] [ 820/2639] eta: 1:31:54 lr: 3.4738701406706484e-05 loss: 0.0659 (0.0692) time: 3.0499 data: 0.0078 max mem: 33408 +Epoch: [13] [ 830/2639] eta: 1:31:24 lr: 3.4734262365755196e-05 loss: 0.0654 (0.0692) time: 3.0626 data: 0.0082 max mem: 33408 +Epoch: [13] [ 840/2639] eta: 1:30:53 lr: 3.472982326176861e-05 loss: 0.0654 (0.0693) time: 3.0441 data: 0.0084 max mem: 33408 +Epoch: [13] [ 850/2639] eta: 1:30:22 lr: 3.472538409473687e-05 loss: 0.0650 (0.0695) time: 3.0142 data: 0.0084 max mem: 33408 +Epoch: [13] [ 860/2639] eta: 1:29:52 lr: 3.472094486465011e-05 loss: 0.0665 (0.0696) time: 3.0180 data: 0.0083 max mem: 33408 +Epoch: [13] [ 870/2639] eta: 1:29:21 lr: 3.47165055714985e-05 loss: 0.0674 (0.0696) time: 3.0208 data: 0.0082 max mem: 33408 +Epoch: [13] [ 880/2639] eta: 1:28:51 lr: 3.471206621527218e-05 loss: 0.0690 (0.0697) time: 3.0161 data: 0.0080 max mem: 33408 +Epoch: [13] [ 890/2639] eta: 1:28:21 lr: 3.470762679596127e-05 loss: 0.0669 (0.0698) time: 3.0460 data: 0.0077 max mem: 33408 +Epoch: [13] [ 900/2639] eta: 1:27:50 lr: 3.4703187313555925e-05 loss: 0.0665 (0.0699) time: 3.0301 data: 0.0075 max mem: 33408 +Epoch: [13] [ 910/2639] eta: 1:27:21 lr: 3.4698747768046273e-05 loss: 0.0651 (0.0699) time: 3.0441 data: 0.0077 max mem: 33408 +Epoch: [13] [ 920/2639] eta: 1:26:51 lr: 3.4694308159422456e-05 loss: 0.0745 (0.0702) time: 3.0645 data: 0.0080 max mem: 33408 +Epoch: [13] [ 930/2639] eta: 1:26:21 lr: 3.46898684876746e-05 loss: 0.0705 (0.0701) time: 3.0308 data: 0.0079 max mem: 33408 +Epoch: [13] [ 940/2639] eta: 1:25:51 lr: 3.4685428752792815e-05 loss: 0.0666 (0.0701) time: 3.0632 data: 0.0076 max mem: 33408 +Epoch: [13] [ 950/2639] eta: 1:25:20 lr: 3.468098895476724e-05 loss: 0.0653 (0.0700) time: 3.0458 data: 0.0073 max mem: 33408 +Epoch: [13] [ 960/2639] eta: 1:24:51 lr: 3.467654909358799e-05 loss: 0.0673 (0.0702) time: 3.0231 data: 0.0075 max mem: 33408 +Epoch: [13] [ 970/2639] eta: 1:24:19 lr: 3.467210916924519e-05 loss: 0.0683 (0.0702) time: 2.9942 data: 0.0078 max mem: 33408 +Epoch: [13] [ 980/2639] eta: 1:23:48 lr: 3.466766918172894e-05 loss: 0.0577 (0.0701) time: 2.9649 data: 0.0078 max mem: 33408 +Epoch: [13] [ 990/2639] eta: 1:23:17 lr: 3.466322913102936e-05 loss: 0.0577 (0.0701) time: 3.0083 data: 0.0077 max mem: 33408 +Epoch: [13] [1000/2639] eta: 1:22:47 lr: 3.465878901713656e-05 loss: 0.0616 (0.0701) time: 3.0373 data: 0.0076 max mem: 33408 +Epoch: [13] [1010/2639] eta: 1:22:17 lr: 3.465434884004063e-05 loss: 0.0625 (0.0701) time: 3.0446 data: 0.0080 max mem: 33408 +Epoch: [13] [1020/2639] eta: 1:21:46 lr: 3.464990859973169e-05 loss: 0.0728 (0.0702) time: 3.0278 data: 0.0080 max mem: 33408 +Epoch: [13] [1030/2639] eta: 1:21:15 lr: 3.464546829619983e-05 loss: 0.0722 (0.0702) time: 2.9909 data: 0.0080 max mem: 33408 +Epoch: [13] [1040/2639] eta: 1:20:43 lr: 3.4641027929435155e-05 loss: 0.0722 (0.0704) time: 2.9511 data: 0.0078 max mem: 33408 +Epoch: [13] [1050/2639] eta: 1:20:12 lr: 3.463658749942775e-05 loss: 0.0711 (0.0706) time: 2.9330 data: 0.0078 max mem: 33408 +Epoch: [13] [1060/2639] eta: 1:19:41 lr: 3.4632147006167706e-05 loss: 0.0688 (0.0707) time: 2.9667 data: 0.0081 max mem: 33408 +Epoch: [13] [1070/2639] eta: 1:19:10 lr: 3.4627706449645106e-05 loss: 0.0688 (0.0708) time: 3.0024 data: 0.0081 max mem: 33408 +Epoch: [13] [1080/2639] eta: 1:18:38 lr: 3.4623265829850046e-05 loss: 0.0704 (0.0707) time: 2.9611 data: 0.0078 max mem: 33408 +Epoch: [13] [1090/2639] eta: 1:18:08 lr: 3.4618825146772605e-05 loss: 0.0727 (0.0709) time: 2.9648 data: 0.0080 max mem: 33408 +Epoch: [13] [1100/2639] eta: 1:17:38 lr: 3.461438440040286e-05 loss: 0.0802 (0.0709) time: 3.0406 data: 0.0080 max mem: 33408 +Epoch: [13] [1110/2639] eta: 1:17:08 lr: 3.4609943590730874e-05 loss: 0.0572 (0.0707) time: 3.0578 data: 0.0080 max mem: 33408 +Epoch: [13] [1120/2639] eta: 1:16:38 lr: 3.460550271774674e-05 loss: 0.0533 (0.0708) time: 3.0466 data: 0.0083 max mem: 33408 +Epoch: [13] [1130/2639] eta: 1:16:08 lr: 3.460106178144052e-05 loss: 0.0650 (0.0709) time: 3.0379 data: 0.0079 max mem: 33408 +Epoch: [13] [1140/2639] eta: 1:15:39 lr: 3.459662078180227e-05 loss: 0.0650 (0.0709) time: 3.0604 data: 0.0078 max mem: 33408 +Epoch: [13] [1150/2639] eta: 1:15:07 lr: 3.459217971882206e-05 loss: 0.0699 (0.0709) time: 3.0263 data: 0.0080 max mem: 33408 +Epoch: [13] [1160/2639] eta: 1:14:39 lr: 3.458773859248996e-05 loss: 0.0588 (0.0708) time: 3.0771 data: 0.0084 max mem: 33408 +Epoch: [13] [1170/2639] eta: 1:14:10 lr: 3.4583297402796025e-05 loss: 0.0526 (0.0708) time: 3.1420 data: 0.0085 max mem: 33408 +Epoch: [13] [1180/2639] eta: 1:13:39 lr: 3.457885614973031e-05 loss: 0.0543 (0.0708) time: 3.0408 data: 0.0086 max mem: 33408 +Epoch: [13] [1190/2639] eta: 1:13:09 lr: 3.457441483328284e-05 loss: 0.0639 (0.0707) time: 3.0121 data: 0.0081 max mem: 33408 +Epoch: [13] [1200/2639] eta: 1:12:39 lr: 3.45699734534437e-05 loss: 0.0632 (0.0707) time: 3.0335 data: 0.0076 max mem: 33408 +Epoch: [13] [1210/2639] eta: 1:12:08 lr: 3.4565532010202926e-05 loss: 0.0632 (0.0708) time: 3.0300 data: 0.0079 max mem: 33408 +Epoch: [13] [1220/2639] eta: 1:11:39 lr: 3.456109050355055e-05 loss: 0.0615 (0.0708) time: 3.0720 data: 0.0080 max mem: 33408 +Epoch: [13] [1230/2639] eta: 1:11:09 lr: 3.455664893347662e-05 loss: 0.0618 (0.0709) time: 3.0757 data: 0.0083 max mem: 33408 +Epoch: [13] [1240/2639] eta: 1:10:38 lr: 3.455220729997117e-05 loss: 0.0626 (0.0708) time: 3.0256 data: 0.0083 max mem: 33408 +Epoch: [13] [1250/2639] eta: 1:10:07 lr: 3.454776560302424e-05 loss: 0.0584 (0.0707) time: 2.9958 data: 0.0086 max mem: 33408 +Epoch: [13] [1260/2639] eta: 1:09:38 lr: 3.4543323842625857e-05 loss: 0.0572 (0.0707) time: 3.0447 data: 0.0084 max mem: 33408 +Epoch: [13] [1270/2639] eta: 1:09:08 lr: 3.453888201876604e-05 loss: 0.0653 (0.0707) time: 3.0700 data: 0.0080 max mem: 33408 +Epoch: [13] [1280/2639] eta: 1:08:38 lr: 3.453444013143482e-05 loss: 0.0554 (0.0706) time: 3.0509 data: 0.0078 max mem: 33408 +Epoch: [13] [1290/2639] eta: 1:08:06 lr: 3.452999818062224e-05 loss: 0.0642 (0.0705) time: 3.0076 data: 0.0075 max mem: 33408 +Epoch: [13] [1300/2639] eta: 1:07:37 lr: 3.452555616631828e-05 loss: 0.0689 (0.0706) time: 2.9976 data: 0.0075 max mem: 33408 +Epoch: [13] [1310/2639] eta: 1:07:06 lr: 3.452111408851298e-05 loss: 0.0680 (0.0706) time: 3.0479 data: 0.0079 max mem: 33408 +Epoch: [13] [1320/2639] eta: 1:06:36 lr: 3.451667194719634e-05 loss: 0.0621 (0.0705) time: 3.0308 data: 0.0081 max mem: 33408 +Epoch: [13] [1330/2639] eta: 1:06:05 lr: 3.4512229742358395e-05 loss: 0.0636 (0.0705) time: 3.0178 data: 0.0080 max mem: 33408 +Epoch: [13] [1340/2639] eta: 1:05:35 lr: 3.450778747398913e-05 loss: 0.0638 (0.0706) time: 3.0273 data: 0.0079 max mem: 33408 +Epoch: [13] [1350/2639] eta: 1:05:05 lr: 3.4503345142078544e-05 loss: 0.0581 (0.0707) time: 3.0251 data: 0.0077 max mem: 33408 +Epoch: [13] [1360/2639] eta: 1:04:35 lr: 3.449890274661665e-05 loss: 0.0581 (0.0706) time: 3.0266 data: 0.0075 max mem: 33408 +Epoch: [13] [1370/2639] eta: 1:04:04 lr: 3.449446028759345e-05 loss: 0.0539 (0.0705) time: 3.0376 data: 0.0076 max mem: 33408 +Epoch: [13] [1380/2639] eta: 1:03:34 lr: 3.4490017764998935e-05 loss: 0.0577 (0.0705) time: 3.0295 data: 0.0079 max mem: 33408 +Epoch: [13] [1390/2639] eta: 1:03:03 lr: 3.448557517882309e-05 loss: 0.0613 (0.0705) time: 3.0106 data: 0.0079 max mem: 33408 +Epoch: [13] [1400/2639] eta: 1:02:33 lr: 3.4481132529055896e-05 loss: 0.0598 (0.0704) time: 3.0013 data: 0.0083 max mem: 33408 +Epoch: [13] [1410/2639] eta: 1:02:03 lr: 3.4476689815687366e-05 loss: 0.0598 (0.0704) time: 3.0390 data: 0.0083 max mem: 33408 +Epoch: [13] [1420/2639] eta: 1:01:32 lr: 3.447224703870746e-05 loss: 0.0603 (0.0704) time: 3.0192 data: 0.0077 max mem: 33408 +Epoch: [13] [1430/2639] eta: 1:01:03 lr: 3.446780419810617e-05 loss: 0.0519 (0.0703) time: 3.0516 data: 0.0082 max mem: 33408 +Epoch: [13] [1440/2639] eta: 1:00:32 lr: 3.4463361293873466e-05 loss: 0.0625 (0.0703) time: 3.0395 data: 0.0089 max mem: 33408 +Epoch: [13] [1450/2639] eta: 1:00:02 lr: 3.4458918325999324e-05 loss: 0.0653 (0.0703) time: 3.0155 data: 0.0082 max mem: 33408 +Epoch: [13] [1460/2639] eta: 0:59:31 lr: 3.445447529447371e-05 loss: 0.0696 (0.0704) time: 3.0202 data: 0.0081 max mem: 33408 +Epoch: [13] [1470/2639] eta: 0:59:01 lr: 3.445003219928661e-05 loss: 0.0747 (0.0704) time: 3.0147 data: 0.0083 max mem: 33408 +Epoch: [13] [1480/2639] eta: 0:58:30 lr: 3.4445589040427965e-05 loss: 0.0747 (0.0706) time: 3.0154 data: 0.0078 max mem: 33408 +Epoch: [13] [1490/2639] eta: 0:58:01 lr: 3.4441145817887744e-05 loss: 0.0736 (0.0707) time: 3.0399 data: 0.0078 max mem: 33408 +Epoch: [13] [1500/2639] eta: 0:57:30 lr: 3.443670253165592e-05 loss: 0.0635 (0.0706) time: 3.0766 data: 0.0082 max mem: 33408 +Epoch: [13] [1510/2639] eta: 0:57:00 lr: 3.443225918172243e-05 loss: 0.0600 (0.0707) time: 3.0333 data: 0.0082 max mem: 33408 +Epoch: [13] [1520/2639] eta: 0:56:29 lr: 3.442781576807723e-05 loss: 0.0704 (0.0708) time: 3.0010 data: 0.0078 max mem: 33408 +Epoch: [13] [1530/2639] eta: 0:55:59 lr: 3.442337229071028e-05 loss: 0.0628 (0.0708) time: 2.9729 data: 0.0079 max mem: 33408 +Epoch: [13] [1540/2639] eta: 0:55:28 lr: 3.441892874961152e-05 loss: 0.0651 (0.0709) time: 3.0072 data: 0.0077 max mem: 33408 +Epoch: [13] [1550/2639] eta: 0:54:59 lr: 3.44144851447709e-05 loss: 0.0702 (0.0709) time: 3.0642 data: 0.0076 max mem: 33408 +Epoch: [13] [1560/2639] eta: 0:54:28 lr: 3.441004147617834e-05 loss: 0.0752 (0.0710) time: 3.0643 data: 0.0077 max mem: 33408 +Epoch: [13] [1570/2639] eta: 0:53:58 lr: 3.440559774382379e-05 loss: 0.0693 (0.0710) time: 3.0241 data: 0.0077 max mem: 33408 +Epoch: [13] [1580/2639] eta: 0:53:27 lr: 3.44011539476972e-05 loss: 0.0688 (0.0710) time: 2.9879 data: 0.0074 max mem: 33408 +Epoch: [13] [1590/2639] eta: 0:52:57 lr: 3.439671008778848e-05 loss: 0.0725 (0.0710) time: 3.0161 data: 0.0074 max mem: 33408 +Epoch: [13] [1600/2639] eta: 0:52:27 lr: 3.4392266164087575e-05 loss: 0.0515 (0.0710) time: 3.0638 data: 0.0074 max mem: 33408 +Epoch: [13] [1610/2639] eta: 0:51:57 lr: 3.438782217658439e-05 loss: 0.0599 (0.0710) time: 3.0379 data: 0.0075 max mem: 33408 +Epoch: [13] [1620/2639] eta: 0:51:26 lr: 3.438337812526886e-05 loss: 0.0594 (0.0710) time: 3.0192 data: 0.0076 max mem: 33408 +Epoch: [13] [1630/2639] eta: 0:50:56 lr: 3.4378934010130904e-05 loss: 0.0564 (0.0709) time: 3.0118 data: 0.0076 max mem: 33408 +Epoch: [13] [1640/2639] eta: 0:50:25 lr: 3.437448983116044e-05 loss: 0.0663 (0.0709) time: 3.0027 data: 0.0080 max mem: 33408 +Epoch: [13] [1650/2639] eta: 0:49:55 lr: 3.437004558834738e-05 loss: 0.0691 (0.0709) time: 3.0195 data: 0.0080 max mem: 33408 +Epoch: [13] [1660/2639] eta: 0:49:25 lr: 3.4365601281681624e-05 loss: 0.0610 (0.0708) time: 3.0415 data: 0.0077 max mem: 33408 +Epoch: [13] [1670/2639] eta: 0:48:54 lr: 3.4361156911153096e-05 loss: 0.0610 (0.0708) time: 3.0205 data: 0.0076 max mem: 33408 +Epoch: [13] [1680/2639] eta: 0:48:24 lr: 3.435671247675169e-05 loss: 0.0690 (0.0708) time: 2.9852 data: 0.0078 max mem: 33408 +Epoch: [13] [1690/2639] eta: 0:47:54 lr: 3.43522679784673e-05 loss: 0.0595 (0.0708) time: 3.0172 data: 0.0080 max mem: 33408 +Epoch: [13] [1700/2639] eta: 0:47:24 lr: 3.4347823416289846e-05 loss: 0.0544 (0.0706) time: 3.0498 data: 0.0079 max mem: 33408 +Epoch: [13] [1710/2639] eta: 0:46:53 lr: 3.43433787902092e-05 loss: 0.0575 (0.0707) time: 3.0457 data: 0.0075 max mem: 33408 +Epoch: [13] [1720/2639] eta: 0:46:23 lr: 3.433893410021528e-05 loss: 0.0638 (0.0707) time: 3.0465 data: 0.0073 max mem: 33408 +Epoch: [13] [1730/2639] eta: 0:45:53 lr: 3.433448934629794e-05 loss: 0.0638 (0.0706) time: 3.0268 data: 0.0080 max mem: 33408 +Epoch: [13] [1740/2639] eta: 0:45:23 lr: 3.433004452844708e-05 loss: 0.0638 (0.0706) time: 3.0283 data: 0.0082 max mem: 33408 +Epoch: [13] [1750/2639] eta: 0:44:53 lr: 3.43255996466526e-05 loss: 0.0665 (0.0706) time: 3.0641 data: 0.0080 max mem: 33408 +Epoch: [13] [1760/2639] eta: 0:44:22 lr: 3.432115470090437e-05 loss: 0.0557 (0.0706) time: 3.0692 data: 0.0082 max mem: 33408 +Epoch: [13] [1770/2639] eta: 0:43:52 lr: 3.431670969119225e-05 loss: 0.0654 (0.0706) time: 3.0244 data: 0.0080 max mem: 33408 +Epoch: [13] [1780/2639] eta: 0:43:22 lr: 3.431226461750613e-05 loss: 0.0654 (0.0706) time: 3.0122 data: 0.0082 max mem: 33408 +Epoch: [13] [1790/2639] eta: 0:42:51 lr: 3.430781947983588e-05 loss: 0.0592 (0.0705) time: 3.0090 data: 0.0081 max mem: 33408 +Epoch: [13] [1800/2639] eta: 0:42:21 lr: 3.430337427817137e-05 loss: 0.0634 (0.0705) time: 3.0356 data: 0.0078 max mem: 33408 +Epoch: [13] [1810/2639] eta: 0:41:51 lr: 3.429892901250245e-05 loss: 0.0681 (0.0705) time: 3.1004 data: 0.0081 max mem: 33408 +Epoch: [13] [1820/2639] eta: 0:41:21 lr: 3.429448368281898e-05 loss: 0.0678 (0.0705) time: 3.0323 data: 0.0080 max mem: 33408 +Epoch: [13] [1830/2639] eta: 0:40:51 lr: 3.429003828911085e-05 loss: 0.0652 (0.0705) time: 3.0328 data: 0.0079 max mem: 33408 +Epoch: [13] [1840/2639] eta: 0:40:21 lr: 3.428559283136788e-05 loss: 0.0679 (0.0705) time: 3.1122 data: 0.0079 max mem: 33408 +Epoch: [13] [1850/2639] eta: 0:39:50 lr: 3.428114730957994e-05 loss: 0.0714 (0.0705) time: 3.0455 data: 0.0078 max mem: 33408 +Epoch: [13] [1860/2639] eta: 0:39:20 lr: 3.427670172373687e-05 loss: 0.0714 (0.0706) time: 3.0097 data: 0.0079 max mem: 33408 +Epoch: [13] [1870/2639] eta: 0:38:50 lr: 3.4272256073828523e-05 loss: 0.0672 (0.0706) time: 3.0349 data: 0.0080 max mem: 33408 +Epoch: [13] [1880/2639] eta: 0:38:19 lr: 3.426781035984474e-05 loss: 0.0747 (0.0706) time: 3.0111 data: 0.0079 max mem: 33408 +Epoch: [13] [1890/2639] eta: 0:37:49 lr: 3.426336458177536e-05 loss: 0.0610 (0.0707) time: 3.0257 data: 0.0075 max mem: 33408 +Epoch: [13] [1900/2639] eta: 0:37:19 lr: 3.425891873961021e-05 loss: 0.0597 (0.0707) time: 3.0829 data: 0.0073 max mem: 33408 +Epoch: [13] [1910/2639] eta: 0:36:49 lr: 3.425447283333914e-05 loss: 0.0664 (0.0708) time: 3.0608 data: 0.0075 max mem: 33408 +Epoch: [13] [1920/2639] eta: 0:36:18 lr: 3.4250026862951986e-05 loss: 0.0664 (0.0708) time: 3.0335 data: 0.0074 max mem: 33408 +Epoch: [13] [1930/2639] eta: 0:35:48 lr: 3.424558082843855e-05 loss: 0.0631 (0.0707) time: 3.0146 data: 0.0075 max mem: 33408 +Epoch: [13] [1940/2639] eta: 0:35:17 lr: 3.424113472978867e-05 loss: 0.0631 (0.0708) time: 2.9733 data: 0.0078 max mem: 33408 +Epoch: [13] [1950/2639] eta: 0:34:47 lr: 3.423668856699216e-05 loss: 0.0652 (0.0708) time: 2.9985 data: 0.0077 max mem: 33408 +Epoch: [13] [1960/2639] eta: 0:34:17 lr: 3.423224234003886e-05 loss: 0.0652 (0.0708) time: 3.0114 data: 0.0075 max mem: 33408 +Epoch: [13] [1970/2639] eta: 0:33:47 lr: 3.422779604891857e-05 loss: 0.0581 (0.0708) time: 3.0431 data: 0.0075 max mem: 33408 +Epoch: [13] [1980/2639] eta: 0:33:16 lr: 3.422334969362109e-05 loss: 0.0604 (0.0709) time: 3.0659 data: 0.0081 max mem: 33408 +Epoch: [13] [1990/2639] eta: 0:32:46 lr: 3.421890327413625e-05 loss: 0.0604 (0.0709) time: 3.0653 data: 0.0082 max mem: 33408 +Epoch: [13] [2000/2639] eta: 0:32:16 lr: 3.4214456790453845e-05 loss: 0.0633 (0.0710) time: 3.0922 data: 0.0077 max mem: 33408 +Epoch: [13] [2010/2639] eta: 0:31:46 lr: 3.421001024256369e-05 loss: 0.0644 (0.0710) time: 3.0465 data: 0.0075 max mem: 33408 +Epoch: [13] [2020/2639] eta: 0:31:15 lr: 3.420556363045556e-05 loss: 0.0636 (0.0710) time: 3.0266 data: 0.0075 max mem: 33408 +Epoch: [13] [2030/2639] eta: 0:30:45 lr: 3.420111695411927e-05 loss: 0.0626 (0.0710) time: 3.0738 data: 0.0078 max mem: 33408 +Epoch: [13] [2040/2639] eta: 0:30:15 lr: 3.419667021354461e-05 loss: 0.0659 (0.0710) time: 3.0261 data: 0.0078 max mem: 33408 +Epoch: [13] [2050/2639] eta: 0:29:45 lr: 3.4192223408721373e-05 loss: 0.0714 (0.0710) time: 3.0101 data: 0.0080 max mem: 33408 +Epoch: [13] [2060/2639] eta: 0:29:14 lr: 3.418777653963934e-05 loss: 0.0693 (0.0710) time: 3.0383 data: 0.0079 max mem: 33408 +Epoch: [13] [2070/2639] eta: 0:28:44 lr: 3.4183329606288295e-05 loss: 0.0643 (0.0710) time: 3.0199 data: 0.0083 max mem: 33408 +Epoch: [13] [2080/2639] eta: 0:28:14 lr: 3.417888260865803e-05 loss: 0.0608 (0.0710) time: 3.0215 data: 0.0082 max mem: 33408 +Epoch: [13] [2090/2639] eta: 0:27:43 lr: 3.417443554673831e-05 loss: 0.0641 (0.0710) time: 3.0534 data: 0.0075 max mem: 33408 +Epoch: [13] [2100/2639] eta: 0:27:13 lr: 3.416998842051892e-05 loss: 0.0641 (0.0710) time: 3.0600 data: 0.0079 max mem: 33408 +Epoch: [13] [2110/2639] eta: 0:26:43 lr: 3.416554122998962e-05 loss: 0.0670 (0.0710) time: 3.0532 data: 0.0079 max mem: 33408 +Epoch: [13] [2120/2639] eta: 0:26:13 lr: 3.4161093975140204e-05 loss: 0.0721 (0.0710) time: 3.0596 data: 0.0077 max mem: 33408 +Epoch: [13] [2130/2639] eta: 0:25:42 lr: 3.4156646655960404e-05 loss: 0.0668 (0.0710) time: 3.0286 data: 0.0079 max mem: 33408 +Epoch: [13] [2140/2639] eta: 0:25:12 lr: 3.415219927244e-05 loss: 0.0668 (0.0710) time: 2.9911 data: 0.0083 max mem: 33408 +Epoch: [13] [2150/2639] eta: 0:24:42 lr: 3.4147751824568744e-05 loss: 0.0626 (0.0710) time: 3.0014 data: 0.0081 max mem: 33408 +Epoch: [13] [2160/2639] eta: 0:24:11 lr: 3.4143304312336406e-05 loss: 0.0648 (0.0711) time: 3.0166 data: 0.0077 max mem: 33408 +Epoch: [13] [2170/2639] eta: 0:23:41 lr: 3.4138856735732736e-05 loss: 0.0724 (0.0711) time: 3.0197 data: 0.0081 max mem: 33408 +Epoch: [13] [2180/2639] eta: 0:23:11 lr: 3.413440909474747e-05 loss: 0.0686 (0.0711) time: 3.0207 data: 0.0082 max mem: 33408 +Epoch: [13] [2190/2639] eta: 0:22:40 lr: 3.412996138937036e-05 loss: 0.0670 (0.0711) time: 3.0547 data: 0.0078 max mem: 33408 +Epoch: [13] [2200/2639] eta: 0:22:10 lr: 3.412551361959116e-05 loss: 0.0637 (0.0711) time: 3.0652 data: 0.0076 max mem: 33408 +Epoch: [13] [2210/2639] eta: 0:21:40 lr: 3.41210657853996e-05 loss: 0.0637 (0.0711) time: 3.0318 data: 0.0075 max mem: 33408 +Epoch: [13] [2220/2639] eta: 0:21:09 lr: 3.411661788678543e-05 loss: 0.0655 (0.0712) time: 3.0390 data: 0.0074 max mem: 33408 +Epoch: [13] [2230/2639] eta: 0:20:39 lr: 3.411216992373837e-05 loss: 0.0571 (0.0711) time: 3.0315 data: 0.0077 max mem: 33408 +Epoch: [13] [2240/2639] eta: 0:20:09 lr: 3.410772189624815e-05 loss: 0.0520 (0.0711) time: 3.0283 data: 0.0075 max mem: 33408 +Epoch: [13] [2250/2639] eta: 0:19:38 lr: 3.410327380430452e-05 loss: 0.0593 (0.0711) time: 3.0113 data: 0.0072 max mem: 33408 +Epoch: [13] [2260/2639] eta: 0:19:08 lr: 3.409882564789719e-05 loss: 0.0553 (0.0711) time: 3.0467 data: 0.0072 max mem: 33408 +Epoch: [13] [2270/2639] eta: 0:18:38 lr: 3.409437742701587e-05 loss: 0.0521 (0.0711) time: 3.0859 data: 0.0071 max mem: 33408 +Epoch: [13] [2280/2639] eta: 0:18:08 lr: 3.4089929141650295e-05 loss: 0.0492 (0.0710) time: 3.0505 data: 0.0071 max mem: 33408 +Epoch: [13] [2290/2639] eta: 0:17:37 lr: 3.408548079179018e-05 loss: 0.0535 (0.0710) time: 3.0154 data: 0.0074 max mem: 33408 +Epoch: [13] [2300/2639] eta: 0:17:07 lr: 3.408103237742524e-05 loss: 0.0525 (0.0710) time: 3.0218 data: 0.0077 max mem: 33408 +Epoch: [13] [2310/2639] eta: 0:16:37 lr: 3.4076583898545166e-05 loss: 0.0549 (0.0710) time: 3.0194 data: 0.0079 max mem: 33408 +Epoch: [13] [2320/2639] eta: 0:16:06 lr: 3.407213535513968e-05 loss: 0.0608 (0.0710) time: 3.0318 data: 0.0075 max mem: 33408 +Epoch: [13] [2330/2639] eta: 0:15:36 lr: 3.4067686747198494e-05 loss: 0.0632 (0.0711) time: 3.0466 data: 0.0071 max mem: 33408 +Epoch: [13] [2340/2639] eta: 0:15:06 lr: 3.406323807471129e-05 loss: 0.0660 (0.0711) time: 3.0441 data: 0.0073 max mem: 33408 +Epoch: [13] [2350/2639] eta: 0:14:36 lr: 3.405878933766776e-05 loss: 0.0610 (0.0710) time: 3.0515 data: 0.0073 max mem: 33408 +Epoch: [13] [2360/2639] eta: 0:14:05 lr: 3.4054340536057614e-05 loss: 0.0610 (0.0710) time: 2.9957 data: 0.0073 max mem: 33408 +Epoch: [13] [2370/2639] eta: 0:13:35 lr: 3.404989166987054e-05 loss: 0.0596 (0.0710) time: 2.9602 data: 0.0075 max mem: 33408 +Epoch: [13] [2380/2639] eta: 0:13:04 lr: 3.404544273909623e-05 loss: 0.0596 (0.0710) time: 3.0067 data: 0.0076 max mem: 33408 +Epoch: [13] [2390/2639] eta: 0:12:34 lr: 3.404099374372435e-05 loss: 0.0523 (0.0709) time: 3.0101 data: 0.0075 max mem: 33408 +Epoch: [13] [2400/2639] eta: 0:12:04 lr: 3.40365446837446e-05 loss: 0.0566 (0.0709) time: 3.0470 data: 0.0075 max mem: 33408 +Epoch: [13] [2410/2639] eta: 0:11:34 lr: 3.4032095559146644e-05 loss: 0.0556 (0.0709) time: 3.0788 data: 0.0076 max mem: 33408 +Epoch: [13] [2420/2639] eta: 0:11:03 lr: 3.402764636992017e-05 loss: 0.0556 (0.0709) time: 3.0298 data: 0.0074 max mem: 33408 +Epoch: [13] [2430/2639] eta: 0:10:33 lr: 3.402319711605483e-05 loss: 0.0576 (0.0708) time: 3.0307 data: 0.0074 max mem: 33408 +Epoch: [13] [2440/2639] eta: 0:10:03 lr: 3.401874779754032e-05 loss: 0.0657 (0.0709) time: 2.9938 data: 0.0079 max mem: 33408 +Epoch: [13] [2450/2639] eta: 0:09:32 lr: 3.401429841436627e-05 loss: 0.0709 (0.0710) time: 3.0266 data: 0.0080 max mem: 33408 +Epoch: [13] [2460/2639] eta: 0:09:02 lr: 3.4009848966522386e-05 loss: 0.0685 (0.0710) time: 3.0672 data: 0.0081 max mem: 33408 +Epoch: [13] [2470/2639] eta: 0:08:32 lr: 3.400539945399829e-05 loss: 0.0736 (0.0710) time: 3.0146 data: 0.0078 max mem: 33408 +Epoch: [13] [2480/2639] eta: 0:08:01 lr: 3.4000949876783654e-05 loss: 0.0690 (0.0710) time: 2.9929 data: 0.0081 max mem: 33408 +Epoch: [13] [2490/2639] eta: 0:07:31 lr: 3.399650023486813e-05 loss: 0.0646 (0.0711) time: 2.9834 data: 0.0087 max mem: 33408 +Epoch: [13] [2500/2639] eta: 0:07:01 lr: 3.399205052824137e-05 loss: 0.0599 (0.0710) time: 2.9920 data: 0.0083 max mem: 33408 +Epoch: [13] [2510/2639] eta: 0:06:30 lr: 3.3987600756893015e-05 loss: 0.0616 (0.0710) time: 2.9984 data: 0.0084 max mem: 33408 +Epoch: [13] [2520/2639] eta: 0:06:00 lr: 3.39831509208127e-05 loss: 0.0692 (0.0710) time: 2.9690 data: 0.0086 max mem: 33408 +Epoch: [13] [2530/2639] eta: 0:05:30 lr: 3.3978701019990076e-05 loss: 0.0699 (0.0711) time: 2.9359 data: 0.0081 max mem: 33408 +Epoch: [13] [2540/2639] eta: 0:04:59 lr: 3.397425105441479e-05 loss: 0.0637 (0.0711) time: 2.9296 data: 0.0078 max mem: 33408 +Epoch: [13] [2550/2639] eta: 0:04:29 lr: 3.396980102407646e-05 loss: 0.0637 (0.0711) time: 2.9991 data: 0.0076 max mem: 33408 +Epoch: [13] [2560/2639] eta: 0:03:59 lr: 3.396535092896472e-05 loss: 0.0700 (0.0712) time: 3.0623 data: 0.0077 max mem: 33408 +Epoch: [13] [2570/2639] eta: 0:03:29 lr: 3.396090076906919e-05 loss: 0.0712 (0.0712) time: 3.0192 data: 0.0078 max mem: 33408 +Epoch: [13] [2580/2639] eta: 0:02:58 lr: 3.395645054437951e-05 loss: 0.0607 (0.0711) time: 2.9973 data: 0.0084 max mem: 33408 +Epoch: [13] [2590/2639] eta: 0:02:28 lr: 3.39520002548853e-05 loss: 0.0517 (0.0711) time: 3.0413 data: 0.0082 max mem: 33408 +Epoch: [13] [2600/2639] eta: 0:01:58 lr: 3.394754990057617e-05 loss: 0.0584 (0.0711) time: 3.0347 data: 0.0075 max mem: 33408 +Epoch: [13] [2610/2639] eta: 0:01:27 lr: 3.3943099481441724e-05 loss: 0.0622 (0.0711) time: 2.9961 data: 0.0076 max mem: 33408 +Epoch: [13] [2620/2639] eta: 0:00:57 lr: 3.3938648997471594e-05 loss: 0.0671 (0.0711) time: 2.9918 data: 0.0077 max mem: 33408 +Epoch: [13] [2630/2639] eta: 0:00:27 lr: 3.393419844865539e-05 loss: 0.0619 (0.0711) time: 3.0127 data: 0.0075 max mem: 33408 +Epoch: [13] Total time: 2:13:12 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 2:15:28 time: 3.1590 data: 3.0262 max mem: 33408 +Test: [ 100/2573] eta: 0:04:31 time: 0.0804 data: 0.0015 max mem: 33408 +Test: [ 200/2573] eta: 0:03:46 time: 0.0801 data: 0.0014 max mem: 33408 +Test: [ 300/2573] eta: 0:03:24 time: 0.0807 data: 0.0015 max mem: 33408 +Test: [ 400/2573] eta: 0:03:09 time: 0.0804 data: 0.0013 max mem: 33408 +Test: [ 500/2573] eta: 0:02:57 time: 0.0803 data: 0.0015 max mem: 33408 +Test: [ 600/2573] eta: 0:02:47 time: 0.0805 data: 0.0014 max mem: 33408 +Test: [ 700/2573] eta: 0:02:38 time: 0.0799 data: 0.0014 max mem: 33408 +Test: [ 800/2573] eta: 0:02:28 time: 0.0826 data: 0.0013 max mem: 33408 +Test: [ 900/2573] eta: 0:02:19 time: 0.0800 data: 0.0014 max mem: 33408 +Test: [1000/2573] eta: 0:02:11 time: 0.0802 data: 0.0015 max mem: 33408 +Test: [1100/2573] eta: 0:02:02 time: 0.0800 data: 0.0014 max mem: 33408 +Test: [1200/2573] eta: 0:01:53 time: 0.0804 data: 0.0014 max mem: 33408 +Test: [1300/2573] eta: 0:01:45 time: 0.0810 data: 0.0014 max mem: 33408 +Test: [1400/2573] eta: 0:01:36 time: 0.0789 data: 0.0016 max mem: 33408 +Test: [1500/2573] eta: 0:01:28 time: 0.0817 data: 0.0015 max mem: 33408 +Test: [1600/2573] eta: 0:01:20 time: 0.0833 data: 0.0014 max mem: 33408 +Test: [1700/2573] eta: 0:01:11 time: 0.0810 data: 0.0014 max mem: 33408 +Test: [1800/2573] eta: 0:01:03 time: 0.0825 data: 0.0014 max mem: 33408 +Test: [1900/2573] eta: 0:00:55 time: 0.0790 data: 0.0014 max mem: 33408 +Test: [2000/2573] eta: 0:00:46 time: 0.0804 data: 0.0015 max mem: 33408 +Test: [2100/2573] eta: 0:00:38 time: 0.0829 data: 0.0015 max mem: 33408 +Test: [2200/2573] eta: 0:00:30 time: 0.0822 data: 0.0015 max mem: 33408 +Test: [2300/2573] eta: 0:00:22 time: 0.0836 data: 0.0015 max mem: 33408 +Test: [2400/2573] eta: 0:00:14 time: 0.0779 data: 0.0015 max mem: 33408 +Test: [2500/2573] eta: 0:00:05 time: 0.0802 data: 0.0014 max mem: 33408 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: Total time: 0:03:31 +Final results: +Mean IoU is 61.40 + + precision@0.5 = 68.87 + precision@0.6 = 63.54 + precision@0.7 = 55.60 + precision@0.8 = 43.81 + precision@0.9 = 20.69 + overall IoU = 60.03 + +Average object IoU 61.402749345524775 +Overall IoU 60.02535629272461 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [14] [ 0/2639] eta: 3:54:02 lr: 3.3930192899268806e-05 loss: 0.0445 (0.0445) time: 5.3213 data: 2.2012 max mem: 33408 +Epoch: [14] [ 10/2639] eta: 2:22:06 lr: 3.3925742227216386e-05 loss: 0.0530 (0.0550) time: 3.2432 data: 0.2074 max mem: 33408 +Epoch: [14] [ 20/2639] eta: 2:16:26 lr: 3.392129149028774e-05 loss: 0.0550 (0.0630) time: 3.0159 data: 0.0079 max mem: 33408 +Epoch: [14] [ 30/2639] eta: 2:14:37 lr: 3.391684068847245e-05 loss: 0.0617 (0.0658) time: 3.0150 data: 0.0076 max mem: 33408 +Epoch: [14] [ 40/2639] eta: 2:13:39 lr: 3.391238982176011e-05 loss: 0.0578 (0.0629) time: 3.0432 data: 0.0077 max mem: 33408 +Epoch: [14] [ 50/2639] eta: 2:12:23 lr: 3.390793889014031e-05 loss: 0.0528 (0.0610) time: 3.0255 data: 0.0080 max mem: 33408 +Epoch: [14] [ 60/2639] eta: 2:11:27 lr: 3.3903487893602645e-05 loss: 0.0538 (0.0603) time: 3.0032 data: 0.0079 max mem: 33408 +Epoch: [14] [ 70/2639] eta: 2:10:34 lr: 3.389903683213668e-05 loss: 0.0577 (0.0603) time: 3.0019 data: 0.0077 max mem: 33408 +Epoch: [14] [ 80/2639] eta: 2:10:03 lr: 3.3894585705732013e-05 loss: 0.0604 (0.0612) time: 3.0220 data: 0.0074 max mem: 33408 +Epoch: [14] [ 90/2639] eta: 2:09:00 lr: 3.389013451437821e-05 loss: 0.0647 (0.0628) time: 2.9914 data: 0.0076 max mem: 33408 +Epoch: [14] [ 100/2639] eta: 2:08:38 lr: 3.388568325806485e-05 loss: 0.0563 (0.0623) time: 3.0020 data: 0.0076 max mem: 33408 +Epoch: [14] [ 110/2639] eta: 2:08:06 lr: 3.3881231936781504e-05 loss: 0.0658 (0.0635) time: 3.0517 data: 0.0075 max mem: 33408 +Epoch: [14] [ 120/2639] eta: 2:07:34 lr: 3.387678055051773e-05 loss: 0.0664 (0.0642) time: 3.0325 data: 0.0076 max mem: 33408 +Epoch: [14] [ 130/2639] eta: 2:07:01 lr: 3.3872329099263104e-05 loss: 0.0598 (0.0641) time: 3.0287 data: 0.0078 max mem: 33408 +Epoch: [14] [ 140/2639] eta: 2:06:30 lr: 3.386787758300718e-05 loss: 0.0552 (0.0638) time: 3.0301 data: 0.0078 max mem: 33408 +Epoch: [14] [ 150/2639] eta: 2:05:58 lr: 3.386342600173952e-05 loss: 0.0577 (0.0637) time: 3.0297 data: 0.0081 max mem: 33408 +Epoch: [14] [ 160/2639] eta: 2:05:28 lr: 3.385897435544967e-05 loss: 0.0604 (0.0638) time: 3.0337 data: 0.0084 max mem: 33408 +Epoch: [14] [ 170/2639] eta: 2:04:50 lr: 3.3854522644127193e-05 loss: 0.0678 (0.0644) time: 3.0130 data: 0.0089 max mem: 33408 +Epoch: [14] [ 180/2639] eta: 2:04:24 lr: 3.385007086776163e-05 loss: 0.0562 (0.0640) time: 3.0243 data: 0.0088 max mem: 33408 +Epoch: [14] [ 190/2639] eta: 2:04:02 lr: 3.384561902634252e-05 loss: 0.0562 (0.0638) time: 3.0827 data: 0.0081 max mem: 33408 +Epoch: [14] [ 200/2639] eta: 2:03:28 lr: 3.384116711985942e-05 loss: 0.0605 (0.0645) time: 3.0558 data: 0.0084 max mem: 33408 +Epoch: [14] [ 210/2639] eta: 2:03:00 lr: 3.383671514830185e-05 loss: 0.0661 (0.0651) time: 3.0335 data: 0.0081 max mem: 33408 +Epoch: [14] [ 220/2639] eta: 2:02:26 lr: 3.383226311165937e-05 loss: 0.0593 (0.0648) time: 3.0281 data: 0.0077 max mem: 33408 +Epoch: [14] [ 230/2639] eta: 2:02:01 lr: 3.382781100992149e-05 loss: 0.0593 (0.0652) time: 3.0452 data: 0.0078 max mem: 33408 +Epoch: [14] [ 240/2639] eta: 2:01:31 lr: 3.382335884307774e-05 loss: 0.0616 (0.0657) time: 3.0683 data: 0.0081 max mem: 33408 +Epoch: [14] [ 250/2639] eta: 2:00:56 lr: 3.3818906611117655e-05 loss: 0.0635 (0.0655) time: 3.0207 data: 0.0081 max mem: 33408 +Epoch: [14] [ 260/2639] eta: 2:00:24 lr: 3.381445431403075e-05 loss: 0.0635 (0.0663) time: 3.0022 data: 0.0078 max mem: 33408 +Epoch: [14] [ 270/2639] eta: 1:59:58 lr: 3.381000195180656e-05 loss: 0.0696 (0.0665) time: 3.0523 data: 0.0078 max mem: 33408 +Epoch: [14] [ 280/2639] eta: 1:59:30 lr: 3.380554952443458e-05 loss: 0.0661 (0.0663) time: 3.0804 data: 0.0080 max mem: 33408 +Epoch: [14] [ 290/2639] eta: 1:58:53 lr: 3.380109703190433e-05 loss: 0.0617 (0.0663) time: 3.0093 data: 0.0080 max mem: 33408 +Epoch: [14] [ 300/2639] eta: 1:58:24 lr: 3.3796644474205325e-05 loss: 0.0636 (0.0666) time: 3.0067 data: 0.0078 max mem: 33408 +Epoch: [14] [ 310/2639] eta: 1:57:51 lr: 3.379219185132707e-05 loss: 0.0590 (0.0664) time: 3.0283 data: 0.0078 max mem: 33408 +Epoch: [14] [ 320/2639] eta: 1:57:25 lr: 3.378773916325906e-05 loss: 0.0494 (0.0665) time: 3.0495 data: 0.0078 max mem: 33408 +Epoch: [14] [ 330/2639] eta: 1:56:56 lr: 3.378328640999081e-05 loss: 0.0535 (0.0663) time: 3.0801 data: 0.0078 max mem: 33408 +Epoch: [14] [ 340/2639] eta: 1:56:22 lr: 3.377883359151179e-05 loss: 0.0581 (0.0660) time: 3.0188 data: 0.0079 max mem: 33408 +Epoch: [14] [ 350/2639] eta: 1:55:51 lr: 3.377438070781152e-05 loss: 0.0581 (0.0661) time: 3.0046 data: 0.0080 max mem: 33408 +Epoch: [14] [ 360/2639] eta: 1:55:17 lr: 3.3769927758879474e-05 loss: 0.0629 (0.0662) time: 3.0078 data: 0.0078 max mem: 33408 +Epoch: [14] [ 370/2639] eta: 1:54:49 lr: 3.376547474470515e-05 loss: 0.0675 (0.0663) time: 3.0240 data: 0.0079 max mem: 33408 +Epoch: [14] [ 380/2639] eta: 1:54:14 lr: 3.376102166527802e-05 loss: 0.0567 (0.0662) time: 3.0148 data: 0.0086 max mem: 33408 +Epoch: [14] [ 390/2639] eta: 1:53:44 lr: 3.375656852058758e-05 loss: 0.0540 (0.0661) time: 3.0034 data: 0.0086 max mem: 33408 +Epoch: [14] [ 400/2639] eta: 1:53:12 lr: 3.375211531062329e-05 loss: 0.0684 (0.0667) time: 3.0234 data: 0.0077 max mem: 33408 +Epoch: [14] [ 410/2639] eta: 1:52:44 lr: 3.3747662035374635e-05 loss: 0.0680 (0.0668) time: 3.0380 data: 0.0079 max mem: 33408 +Epoch: [14] [ 420/2639] eta: 1:52:09 lr: 3.3743208694831075e-05 loss: 0.0608 (0.0667) time: 3.0134 data: 0.0079 max mem: 33408 +Epoch: [14] [ 430/2639] eta: 1:51:44 lr: 3.3738755288982095e-05 loss: 0.0508 (0.0666) time: 3.0409 data: 0.0075 max mem: 33408 +Epoch: [14] [ 440/2639] eta: 1:51:11 lr: 3.3734301817817144e-05 loss: 0.0508 (0.0665) time: 3.0520 data: 0.0077 max mem: 33408 +Epoch: [14] [ 450/2639] eta: 1:50:37 lr: 3.3729848281325684e-05 loss: 0.0524 (0.0664) time: 2.9768 data: 0.0082 max mem: 33408 +Epoch: [14] [ 460/2639] eta: 1:50:04 lr: 3.372539467949718e-05 loss: 0.0524 (0.0664) time: 2.9675 data: 0.0081 max mem: 33408 +Epoch: [14] [ 470/2639] eta: 1:49:31 lr: 3.372094101232109e-05 loss: 0.0492 (0.0660) time: 2.9740 data: 0.0078 max mem: 33408 +Epoch: [14] [ 480/2639] eta: 1:49:00 lr: 3.3716487279786854e-05 loss: 0.0492 (0.0659) time: 2.9954 data: 0.0077 max mem: 33408 +Epoch: [14] [ 490/2639] eta: 1:48:28 lr: 3.371203348188392e-05 loss: 0.0533 (0.0657) time: 2.9938 data: 0.0078 max mem: 33408 +Epoch: [14] [ 500/2639] eta: 1:47:56 lr: 3.370757961860173e-05 loss: 0.0533 (0.0654) time: 2.9953 data: 0.0080 max mem: 33408 +Epoch: [14] [ 510/2639] eta: 1:47:25 lr: 3.3703125689929736e-05 loss: 0.0497 (0.0655) time: 3.0058 data: 0.0083 max mem: 33408 +Epoch: [14] [ 520/2639] eta: 1:46:54 lr: 3.369867169585738e-05 loss: 0.0505 (0.0653) time: 3.0100 data: 0.0081 max mem: 33408 +Epoch: [14] [ 530/2639] eta: 1:46:25 lr: 3.3694217636374085e-05 loss: 0.0561 (0.0654) time: 3.0377 data: 0.0079 max mem: 33408 +Epoch: [14] [ 540/2639] eta: 1:45:55 lr: 3.368976351146929e-05 loss: 0.0560 (0.0653) time: 3.0456 data: 0.0082 max mem: 33408 +Epoch: [14] [ 550/2639] eta: 1:45:26 lr: 3.368530932113241e-05 loss: 0.0558 (0.0653) time: 3.0465 data: 0.0084 max mem: 33408 +Epoch: [14] [ 560/2639] eta: 1:44:56 lr: 3.368085506535289e-05 loss: 0.0579 (0.0654) time: 3.0420 data: 0.0084 max mem: 33408 +Epoch: [14] [ 570/2639] eta: 1:44:23 lr: 3.367640074412014e-05 loss: 0.0668 (0.0656) time: 2.9966 data: 0.0080 max mem: 33408 +Epoch: [14] [ 580/2639] eta: 1:43:52 lr: 3.3671946357423575e-05 loss: 0.0646 (0.0656) time: 2.9818 data: 0.0079 max mem: 33408 +Epoch: [14] [ 590/2639] eta: 1:43:20 lr: 3.3667491905252616e-05 loss: 0.0537 (0.0655) time: 2.9844 data: 0.0079 max mem: 33408 +Epoch: [14] [ 600/2639] eta: 1:42:51 lr: 3.366303738759669e-05 loss: 0.0504 (0.0654) time: 3.0205 data: 0.0079 max mem: 33408 +Epoch: [14] [ 610/2639] eta: 1:42:19 lr: 3.3658582804445175e-05 loss: 0.0539 (0.0655) time: 3.0243 data: 0.0078 max mem: 33408 +Epoch: [14] [ 620/2639] eta: 1:41:48 lr: 3.3654128155787496e-05 loss: 0.0539 (0.0654) time: 2.9899 data: 0.0076 max mem: 33408 +Epoch: [14] [ 630/2639] eta: 1:41:22 lr: 3.364967344161305e-05 loss: 0.0567 (0.0654) time: 3.0777 data: 0.0079 max mem: 33408 +Epoch: [14] [ 640/2639] eta: 1:40:52 lr: 3.3645218661911244e-05 loss: 0.0593 (0.0654) time: 3.1008 data: 0.0081 max mem: 33408 +Epoch: [14] [ 650/2639] eta: 1:40:22 lr: 3.364076381667147e-05 loss: 0.0554 (0.0654) time: 3.0291 data: 0.0080 max mem: 33408 +Epoch: [14] [ 660/2639] eta: 1:39:54 lr: 3.36363089058831e-05 loss: 0.0571 (0.0653) time: 3.0602 data: 0.0080 max mem: 33408 +Epoch: [14] [ 670/2639] eta: 1:39:22 lr: 3.363185392953556e-05 loss: 0.0665 (0.0657) time: 3.0491 data: 0.0081 max mem: 33408 +Epoch: [14] [ 680/2639] eta: 1:38:51 lr: 3.36273988876182e-05 loss: 0.0621 (0.0656) time: 2.9889 data: 0.0083 max mem: 33408 +Epoch: [14] [ 690/2639] eta: 1:38:19 lr: 3.362294378012044e-05 loss: 0.0604 (0.0657) time: 2.9823 data: 0.0082 max mem: 33408 +Epoch: [14] [ 700/2639] eta: 1:37:50 lr: 3.361848860703162e-05 loss: 0.0572 (0.0655) time: 3.0266 data: 0.0077 max mem: 33408 +Epoch: [14] [ 710/2639] eta: 1:37:23 lr: 3.361403336834114e-05 loss: 0.0553 (0.0656) time: 3.1065 data: 0.0075 max mem: 33408 +Epoch: [14] [ 720/2639] eta: 1:36:51 lr: 3.3609578064038365e-05 loss: 0.0659 (0.0656) time: 3.0610 data: 0.0078 max mem: 33408 +Epoch: [14] [ 730/2639] eta: 1:36:22 lr: 3.3605122694112676e-05 loss: 0.0586 (0.0655) time: 3.0233 data: 0.0077 max mem: 33408 +Epoch: [14] [ 740/2639] eta: 1:35:52 lr: 3.360066725855342e-05 loss: 0.0545 (0.0654) time: 3.0444 data: 0.0075 max mem: 33408 +Epoch: [14] [ 750/2639] eta: 1:35:22 lr: 3.359621175734997e-05 loss: 0.0539 (0.0653) time: 3.0339 data: 0.0074 max mem: 33408 +Epoch: [14] [ 760/2639] eta: 1:34:50 lr: 3.359175619049169e-05 loss: 0.0526 (0.0653) time: 3.0107 data: 0.0080 max mem: 33408 +Epoch: [14] [ 770/2639] eta: 1:34:19 lr: 3.3587300557967934e-05 loss: 0.0526 (0.0653) time: 2.9967 data: 0.0083 max mem: 33408 +Epoch: [14] [ 780/2639] eta: 1:33:48 lr: 3.358284485976805e-05 loss: 0.0503 (0.0652) time: 2.9991 data: 0.0079 max mem: 33408 +Epoch: [14] [ 790/2639] eta: 1:33:18 lr: 3.3578389095881385e-05 loss: 0.0526 (0.0654) time: 3.0137 data: 0.0078 max mem: 33408 +Epoch: [14] [ 800/2639] eta: 1:32:47 lr: 3.357393326629729e-05 loss: 0.0546 (0.0655) time: 3.0104 data: 0.0077 max mem: 33408 +Epoch: [14] [ 810/2639] eta: 1:32:18 lr: 3.356947737100512e-05 loss: 0.0540 (0.0654) time: 3.0264 data: 0.0078 max mem: 33408 +Epoch: [14] [ 820/2639] eta: 1:31:46 lr: 3.35650214099942e-05 loss: 0.0531 (0.0654) time: 3.0213 data: 0.0080 max mem: 33408 +Epoch: [14] [ 830/2639] eta: 1:31:17 lr: 3.356056538325386e-05 loss: 0.0640 (0.0655) time: 3.0289 data: 0.0079 max mem: 33408 +Epoch: [14] [ 840/2639] eta: 1:30:46 lr: 3.3556109290773455e-05 loss: 0.0568 (0.0655) time: 3.0370 data: 0.0076 max mem: 33408 +Epoch: [14] [ 850/2639] eta: 1:30:16 lr: 3.35516531325423e-05 loss: 0.0568 (0.0655) time: 3.0131 data: 0.0075 max mem: 33408 +Epoch: [14] [ 860/2639] eta: 1:29:45 lr: 3.354719690854972e-05 loss: 0.0656 (0.0657) time: 3.0161 data: 0.0083 max mem: 33408 +Epoch: [14] [ 870/2639] eta: 1:29:15 lr: 3.354274061878505e-05 loss: 0.0607 (0.0657) time: 3.0172 data: 0.0082 max mem: 33408 +Epoch: [14] [ 880/2639] eta: 1:28:43 lr: 3.353828426323759e-05 loss: 0.0525 (0.0656) time: 3.0010 data: 0.0079 max mem: 33408 +Epoch: [14] [ 890/2639] eta: 1:28:13 lr: 3.353382784189668e-05 loss: 0.0522 (0.0654) time: 2.9907 data: 0.0080 max mem: 33408 +Epoch: [14] [ 900/2639] eta: 1:27:42 lr: 3.352937135475163e-05 loss: 0.0577 (0.0654) time: 3.0104 data: 0.0075 max mem: 33408 +Epoch: [14] [ 910/2639] eta: 1:27:12 lr: 3.352491480179173e-05 loss: 0.0590 (0.0654) time: 3.0228 data: 0.0075 max mem: 33408 +Epoch: [14] [ 920/2639] eta: 1:26:41 lr: 3.35204581830063e-05 loss: 0.0734 (0.0656) time: 3.0184 data: 0.0081 max mem: 33408 +Epoch: [14] [ 930/2639] eta: 1:26:11 lr: 3.351600149838465e-05 loss: 0.0642 (0.0657) time: 3.0198 data: 0.0082 max mem: 33408 +Epoch: [14] [ 940/2639] eta: 1:25:41 lr: 3.3511544747916065e-05 loss: 0.0576 (0.0655) time: 3.0259 data: 0.0077 max mem: 33408 +Epoch: [14] [ 950/2639] eta: 1:25:10 lr: 3.3507087931589855e-05 loss: 0.0596 (0.0657) time: 2.9933 data: 0.0075 max mem: 33408 +Epoch: [14] [ 960/2639] eta: 1:24:39 lr: 3.350263104939531e-05 loss: 0.0660 (0.0657) time: 2.9802 data: 0.0075 max mem: 33408 +Epoch: [14] [ 970/2639] eta: 1:24:08 lr: 3.349817410132171e-05 loss: 0.0562 (0.0656) time: 2.9941 data: 0.0074 max mem: 33408 +Epoch: [14] [ 980/2639] eta: 1:23:38 lr: 3.3493717087358364e-05 loss: 0.0622 (0.0656) time: 3.0079 data: 0.0075 max mem: 33408 +Epoch: [14] [ 990/2639] eta: 1:23:07 lr: 3.348926000749453e-05 loss: 0.0681 (0.0656) time: 3.0031 data: 0.0076 max mem: 33408 +Epoch: [14] [1000/2639] eta: 1:22:37 lr: 3.3484802861719496e-05 loss: 0.0587 (0.0656) time: 3.0190 data: 0.0077 max mem: 33408 +Epoch: [14] [1010/2639] eta: 1:22:08 lr: 3.3480345650022545e-05 loss: 0.0562 (0.0655) time: 3.0711 data: 0.0076 max mem: 33408 +Epoch: [14] [1020/2639] eta: 1:21:38 lr: 3.3475888372392956e-05 loss: 0.0623 (0.0655) time: 3.0673 data: 0.0075 max mem: 33408 +Epoch: [14] [1030/2639] eta: 1:21:08 lr: 3.347143102881999e-05 loss: 0.0647 (0.0655) time: 3.0279 data: 0.0076 max mem: 33408 +Epoch: [14] [1040/2639] eta: 1:20:38 lr: 3.346697361929291e-05 loss: 0.0630 (0.0655) time: 3.0387 data: 0.0077 max mem: 33408 +Epoch: [14] [1050/2639] eta: 1:20:07 lr: 3.3462516143800984e-05 loss: 0.0537 (0.0654) time: 3.0192 data: 0.0078 max mem: 33408 +Epoch: [14] [1060/2639] eta: 1:19:36 lr: 3.345805860233347e-05 loss: 0.0537 (0.0653) time: 3.0060 data: 0.0078 max mem: 33408 +Epoch: [14] [1070/2639] eta: 1:19:06 lr: 3.3453600994879635e-05 loss: 0.0590 (0.0653) time: 3.0162 data: 0.0077 max mem: 33408 +Epoch: [14] [1080/2639] eta: 1:18:35 lr: 3.344914332142872e-05 loss: 0.0636 (0.0654) time: 2.9928 data: 0.0079 max mem: 33408 +Epoch: [14] [1090/2639] eta: 1:18:06 lr: 3.344468558196997e-05 loss: 0.0550 (0.0653) time: 3.0348 data: 0.0082 max mem: 33408 +Epoch: [14] [1100/2639] eta: 1:17:35 lr: 3.344022777649266e-05 loss: 0.0550 (0.0653) time: 3.0546 data: 0.0080 max mem: 33408 +Epoch: [14] [1110/2639] eta: 1:17:05 lr: 3.343576990498601e-05 loss: 0.0544 (0.0652) time: 3.0266 data: 0.0076 max mem: 33408 +Epoch: [14] [1120/2639] eta: 1:16:35 lr: 3.343131196743925e-05 loss: 0.0522 (0.0651) time: 3.0136 data: 0.0073 max mem: 33408 +Epoch: [14] [1130/2639] eta: 1:16:04 lr: 3.3426853963841645e-05 loss: 0.0522 (0.0650) time: 3.0101 data: 0.0075 max mem: 33408 +Epoch: [14] [1140/2639] eta: 1:15:34 lr: 3.342239589418241e-05 loss: 0.0536 (0.0651) time: 3.0381 data: 0.0079 max mem: 33408 +Epoch: [14] [1150/2639] eta: 1:15:04 lr: 3.341793775845079e-05 loss: 0.0657 (0.0650) time: 3.0197 data: 0.0078 max mem: 33408 +Epoch: [14] [1160/2639] eta: 1:14:35 lr: 3.341347955663599e-05 loss: 0.0640 (0.0650) time: 3.0532 data: 0.0075 max mem: 33408 +Epoch: [14] [1170/2639] eta: 1:14:04 lr: 3.340902128872725e-05 loss: 0.0613 (0.0650) time: 3.0539 data: 0.0075 max mem: 33408 +Epoch: [14] [1180/2639] eta: 1:13:34 lr: 3.340456295471378e-05 loss: 0.0584 (0.0651) time: 3.0313 data: 0.0077 max mem: 33408 +Epoch: [14] [1190/2639] eta: 1:13:03 lr: 3.340010455458481e-05 loss: 0.0631 (0.0650) time: 3.0124 data: 0.0075 max mem: 33408 +Epoch: [14] [1200/2639] eta: 1:12:34 lr: 3.339564608832953e-05 loss: 0.0631 (0.0652) time: 3.0314 data: 0.0075 max mem: 33408 +Epoch: [14] [1210/2639] eta: 1:12:04 lr: 3.3391187555937184e-05 loss: 0.0741 (0.0654) time: 3.0849 data: 0.0074 max mem: 33408 +Epoch: [14] [1220/2639] eta: 1:11:33 lr: 3.338672895739694e-05 loss: 0.0722 (0.0655) time: 3.0163 data: 0.0077 max mem: 33408 +Epoch: [14] [1230/2639] eta: 1:11:02 lr: 3.3382270292698034e-05 loss: 0.0680 (0.0655) time: 2.9524 data: 0.0085 max mem: 33408 +Epoch: [14] [1240/2639] eta: 1:10:31 lr: 3.337781156182965e-05 loss: 0.0567 (0.0656) time: 2.9394 data: 0.0087 max mem: 33408 +Epoch: [14] [1250/2639] eta: 1:10:00 lr: 3.337335276478098e-05 loss: 0.0638 (0.0656) time: 2.9647 data: 0.0081 max mem: 33408 +Epoch: [14] [1260/2639] eta: 1:09:30 lr: 3.3368893901541224e-05 loss: 0.0592 (0.0655) time: 2.9945 data: 0.0076 max mem: 33408 +Epoch: [14] [1270/2639] eta: 1:08:59 lr: 3.336443497209958e-05 loss: 0.0592 (0.0658) time: 2.9847 data: 0.0080 max mem: 33408 +Epoch: [14] [1280/2639] eta: 1:08:29 lr: 3.335997597644523e-05 loss: 0.0634 (0.0658) time: 3.0004 data: 0.0086 max mem: 33408 +Epoch: [14] [1290/2639] eta: 1:07:58 lr: 3.335551691456733e-05 loss: 0.0707 (0.0659) time: 2.9965 data: 0.0086 max mem: 33408 +Epoch: [14] [1300/2639] eta: 1:07:28 lr: 3.335105778645509e-05 loss: 0.0718 (0.0660) time: 3.0041 data: 0.0086 max mem: 33408 +Epoch: [14] [1310/2639] eta: 1:06:57 lr: 3.334659859209769e-05 loss: 0.0635 (0.0660) time: 3.0106 data: 0.0085 max mem: 33408 +Epoch: [14] [1320/2639] eta: 1:06:27 lr: 3.3342139331484284e-05 loss: 0.0601 (0.0659) time: 3.0027 data: 0.0080 max mem: 33408 +Epoch: [14] [1330/2639] eta: 1:05:56 lr: 3.333768000460405e-05 loss: 0.0557 (0.0660) time: 3.0070 data: 0.0080 max mem: 33408 +Epoch: [14] [1340/2639] eta: 1:05:26 lr: 3.3333220611446145e-05 loss: 0.0571 (0.0660) time: 3.0257 data: 0.0081 max mem: 33408 +Epoch: [14] [1350/2639] eta: 1:04:56 lr: 3.332876115199975e-05 loss: 0.0608 (0.0661) time: 3.0610 data: 0.0081 max mem: 33408 +Epoch: [14] [1360/2639] eta: 1:04:27 lr: 3.3324301626254004e-05 loss: 0.0593 (0.0660) time: 3.0680 data: 0.0082 max mem: 33408 +Epoch: [14] [1370/2639] eta: 1:03:57 lr: 3.331984203419808e-05 loss: 0.0542 (0.0660) time: 3.0600 data: 0.0077 max mem: 33408 +Epoch: [14] [1380/2639] eta: 1:03:26 lr: 3.331538237582111e-05 loss: 0.0562 (0.0660) time: 3.0255 data: 0.0076 max mem: 33408 +Epoch: [14] [1390/2639] eta: 1:02:57 lr: 3.331092265111227e-05 loss: 0.0610 (0.0660) time: 3.0525 data: 0.0080 max mem: 33408 +Epoch: [14] [1400/2639] eta: 1:02:26 lr: 3.3306462860060686e-05 loss: 0.0583 (0.0660) time: 3.0594 data: 0.0083 max mem: 33408 +Epoch: [14] [1410/2639] eta: 1:01:57 lr: 3.3302003002655505e-05 loss: 0.0574 (0.0660) time: 3.0434 data: 0.0079 max mem: 33408 +Epoch: [14] [1420/2639] eta: 1:01:26 lr: 3.329754307888587e-05 loss: 0.0574 (0.0661) time: 3.0174 data: 0.0078 max mem: 33408 +Epoch: [14] [1430/2639] eta: 1:00:56 lr: 3.329308308874091e-05 loss: 0.0575 (0.0661) time: 3.0200 data: 0.0081 max mem: 33408 +Epoch: [14] [1440/2639] eta: 1:00:26 lr: 3.328862303220977e-05 loss: 0.0666 (0.0661) time: 3.0320 data: 0.0084 max mem: 33408 +Epoch: [14] [1450/2639] eta: 0:59:55 lr: 3.328416290928156e-05 loss: 0.0666 (0.0661) time: 3.0207 data: 0.0082 max mem: 33408 +Epoch: [14] [1460/2639] eta: 0:59:25 lr: 3.3279702719945416e-05 loss: 0.0518 (0.0660) time: 3.0516 data: 0.0078 max mem: 33408 +Epoch: [14] [1470/2639] eta: 0:58:55 lr: 3.327524246419046e-05 loss: 0.0469 (0.0660) time: 3.0508 data: 0.0077 max mem: 33408 +Epoch: [14] [1480/2639] eta: 0:58:25 lr: 3.327078214200581e-05 loss: 0.0695 (0.0661) time: 3.0196 data: 0.0076 max mem: 33408 +Epoch: [14] [1490/2639] eta: 0:57:55 lr: 3.326632175338058e-05 loss: 0.0694 (0.0661) time: 3.0410 data: 0.0077 max mem: 33408 +Epoch: [14] [1500/2639] eta: 0:57:25 lr: 3.326186129830388e-05 loss: 0.0649 (0.0661) time: 3.0353 data: 0.0079 max mem: 33408 +Epoch: [14] [1510/2639] eta: 0:56:55 lr: 3.325740077676482e-05 loss: 0.0579 (0.0661) time: 3.0182 data: 0.0080 max mem: 33408 +Epoch: [14] [1520/2639] eta: 0:56:24 lr: 3.3252940188752514e-05 loss: 0.0498 (0.0661) time: 3.0109 data: 0.0078 max mem: 33408 +Epoch: [14] [1530/2639] eta: 0:55:54 lr: 3.324847953425605e-05 loss: 0.0519 (0.0661) time: 3.0209 data: 0.0077 max mem: 33408 +Epoch: [14] [1540/2639] eta: 0:55:24 lr: 3.324401881326453e-05 loss: 0.0664 (0.0661) time: 3.0441 data: 0.0076 max mem: 33408 +Epoch: [14] [1550/2639] eta: 0:54:53 lr: 3.3239558025767045e-05 loss: 0.0521 (0.0660) time: 3.0208 data: 0.0074 max mem: 33408 +Epoch: [14] [1560/2639] eta: 0:54:23 lr: 3.3235097171752696e-05 loss: 0.0597 (0.0661) time: 3.0316 data: 0.0076 max mem: 33408 +Epoch: [14] [1570/2639] eta: 0:53:53 lr: 3.323063625121057e-05 loss: 0.0588 (0.0662) time: 3.0069 data: 0.0077 max mem: 33408 +Epoch: [14] [1580/2639] eta: 0:53:23 lr: 3.3226175264129744e-05 loss: 0.0649 (0.0663) time: 3.0336 data: 0.0079 max mem: 33408 +Epoch: [14] [1590/2639] eta: 0:52:52 lr: 3.322171421049931e-05 loss: 0.0649 (0.0663) time: 3.0428 data: 0.0083 max mem: 33408 +Epoch: [14] [1600/2639] eta: 0:52:22 lr: 3.3217253090308325e-05 loss: 0.0541 (0.0663) time: 3.0309 data: 0.0079 max mem: 33408 +Epoch: [14] [1610/2639] eta: 0:51:52 lr: 3.3212791903545885e-05 loss: 0.0541 (0.0662) time: 3.0231 data: 0.0081 max mem: 33408 +Epoch: [14] [1620/2639] eta: 0:51:22 lr: 3.3208330650201044e-05 loss: 0.0621 (0.0663) time: 3.0044 data: 0.0082 max mem: 33408 +Epoch: [14] [1630/2639] eta: 0:50:52 lr: 3.320386933026288e-05 loss: 0.0652 (0.0664) time: 3.0314 data: 0.0080 max mem: 33408 +Epoch: [14] [1640/2639] eta: 0:50:21 lr: 3.319940794372046e-05 loss: 0.0627 (0.0663) time: 3.0468 data: 0.0079 max mem: 33408 +Epoch: [14] [1650/2639] eta: 0:49:51 lr: 3.319494649056285e-05 loss: 0.0627 (0.0664) time: 3.0622 data: 0.0078 max mem: 33408 +Epoch: [14] [1660/2639] eta: 0:49:21 lr: 3.319048497077907e-05 loss: 0.0700 (0.0664) time: 3.0415 data: 0.0081 max mem: 33408 +Epoch: [14] [1670/2639] eta: 0:48:51 lr: 3.318602338435821e-05 loss: 0.0605 (0.0664) time: 2.9984 data: 0.0081 max mem: 33408 +Epoch: [14] [1680/2639] eta: 0:48:21 lr: 3.318156173128932e-05 loss: 0.0605 (0.0663) time: 3.0222 data: 0.0077 max mem: 33408 +Epoch: [14] [1690/2639] eta: 0:47:50 lr: 3.317710001156142e-05 loss: 0.0620 (0.0664) time: 3.0362 data: 0.0078 max mem: 33408 +Epoch: [14] [1700/2639] eta: 0:47:20 lr: 3.317263822516358e-05 loss: 0.0662 (0.0665) time: 3.0099 data: 0.0077 max mem: 33408 +Epoch: [14] [1710/2639] eta: 0:46:50 lr: 3.316817637208482e-05 loss: 0.0662 (0.0665) time: 3.0414 data: 0.0075 max mem: 33408 +Epoch: [14] [1720/2639] eta: 0:46:20 lr: 3.3163714452314205e-05 loss: 0.0600 (0.0665) time: 3.0578 data: 0.0077 max mem: 33408 +Epoch: [14] [1730/2639] eta: 0:45:50 lr: 3.3159252465840726e-05 loss: 0.0483 (0.0664) time: 3.0701 data: 0.0076 max mem: 33408 +Epoch: [14] [1740/2639] eta: 0:45:20 lr: 3.3154790412653455e-05 loss: 0.0481 (0.0665) time: 3.0516 data: 0.0079 max mem: 33408 +Epoch: [14] [1750/2639] eta: 0:44:49 lr: 3.3150328292741387e-05 loss: 0.0608 (0.0666) time: 3.0128 data: 0.0079 max mem: 33408 +Epoch: [14] [1760/2639] eta: 0:44:19 lr: 3.314586610609356e-05 loss: 0.0521 (0.0665) time: 3.0038 data: 0.0080 max mem: 33408 +Epoch: [14] [1770/2639] eta: 0:43:49 lr: 3.314140385269899e-05 loss: 0.0598 (0.0665) time: 3.0221 data: 0.0081 max mem: 33408 +Epoch: [14] [1780/2639] eta: 0:43:19 lr: 3.3136941532546693e-05 loss: 0.0641 (0.0665) time: 3.0496 data: 0.0080 max mem: 33408 +Epoch: [14] [1790/2639] eta: 0:42:48 lr: 3.3132479145625676e-05 loss: 0.0580 (0.0664) time: 3.0182 data: 0.0079 max mem: 33408 +Epoch: [14] [1800/2639] eta: 0:42:18 lr: 3.3128016691924954e-05 loss: 0.0484 (0.0664) time: 3.0562 data: 0.0080 max mem: 33408 +Epoch: [14] [1810/2639] eta: 0:41:48 lr: 3.3123554171433536e-05 loss: 0.0469 (0.0663) time: 3.0463 data: 0.0079 max mem: 33408 +Epoch: [14] [1820/2639] eta: 0:41:18 lr: 3.3119091584140424e-05 loss: 0.0507 (0.0663) time: 3.0425 data: 0.0072 max mem: 33408 +Epoch: [14] [1830/2639] eta: 0:40:47 lr: 3.31146289300346e-05 loss: 0.0588 (0.0664) time: 3.0428 data: 0.0073 max mem: 33408 +Epoch: [14] [1840/2639] eta: 0:40:17 lr: 3.3110166209105066e-05 loss: 0.0577 (0.0664) time: 3.0190 data: 0.0076 max mem: 33408 +Epoch: [14] [1850/2639] eta: 0:39:47 lr: 3.310570342134083e-05 loss: 0.0555 (0.0664) time: 3.0327 data: 0.0077 max mem: 33408 +Epoch: [14] [1860/2639] eta: 0:39:17 lr: 3.310124056673086e-05 loss: 0.0533 (0.0663) time: 3.0248 data: 0.0079 max mem: 33408 +Epoch: [14] [1870/2639] eta: 0:38:47 lr: 3.309677764526415e-05 loss: 0.0568 (0.0663) time: 3.0597 data: 0.0078 max mem: 33408 +Epoch: [14] [1880/2639] eta: 0:38:16 lr: 3.309231465692968e-05 loss: 0.0622 (0.0663) time: 3.0355 data: 0.0078 max mem: 33408 +Epoch: [14] [1890/2639] eta: 0:37:46 lr: 3.3087851601716435e-05 loss: 0.0677 (0.0664) time: 3.0119 data: 0.0081 max mem: 33408 +Epoch: [14] [1900/2639] eta: 0:37:16 lr: 3.3083388479613375e-05 loss: 0.0609 (0.0663) time: 3.0247 data: 0.0077 max mem: 33408 +Epoch: [14] [1910/2639] eta: 0:36:45 lr: 3.3078925290609484e-05 loss: 0.0511 (0.0664) time: 2.9977 data: 0.0072 max mem: 33408 +Epoch: [14] [1920/2639] eta: 0:36:15 lr: 3.307446203469371e-05 loss: 0.0558 (0.0664) time: 2.9689 data: 0.0076 max mem: 33408 +Epoch: [14] [1930/2639] eta: 0:35:45 lr: 3.3069998711855035e-05 loss: 0.0510 (0.0664) time: 2.9861 data: 0.0078 max mem: 33408 +Epoch: [14] [1940/2639] eta: 0:35:15 lr: 3.306553532208242e-05 loss: 0.0473 (0.0664) time: 3.0568 data: 0.0075 max mem: 33408 +Epoch: [14] [1950/2639] eta: 0:34:45 lr: 3.3061071865364815e-05 loss: 0.0492 (0.0663) time: 3.1076 data: 0.0073 max mem: 33408 +Epoch: [14] [1960/2639] eta: 0:34:14 lr: 3.3056608341691166e-05 loss: 0.0618 (0.0664) time: 3.0652 data: 0.0074 max mem: 33408 +Epoch: [14] [1970/2639] eta: 0:33:44 lr: 3.3052144751050435e-05 loss: 0.0655 (0.0664) time: 3.0493 data: 0.0075 max mem: 33408 +Epoch: [14] [1980/2639] eta: 0:33:14 lr: 3.304768109343156e-05 loss: 0.0635 (0.0665) time: 3.0066 data: 0.0076 max mem: 33408 +Epoch: [14] [1990/2639] eta: 0:32:44 lr: 3.3043217368823504e-05 loss: 0.0582 (0.0664) time: 3.0283 data: 0.0078 max mem: 33408 +Epoch: [14] [2000/2639] eta: 0:32:14 lr: 3.3038753577215173e-05 loss: 0.0545 (0.0664) time: 3.0782 data: 0.0080 max mem: 33408 +Epoch: [14] [2010/2639] eta: 0:31:43 lr: 3.303428971859553e-05 loss: 0.0648 (0.0664) time: 3.0400 data: 0.0083 max mem: 33408 +Epoch: [14] [2020/2639] eta: 0:31:13 lr: 3.30298257929535e-05 loss: 0.0661 (0.0664) time: 3.0536 data: 0.0078 max mem: 33408 +Epoch: [14] [2030/2639] eta: 0:30:43 lr: 3.3025361800278007e-05 loss: 0.0662 (0.0664) time: 3.0167 data: 0.0074 max mem: 33408 +Epoch: [14] [2040/2639] eta: 0:30:12 lr: 3.3020897740557985e-05 loss: 0.0563 (0.0664) time: 2.9848 data: 0.0075 max mem: 33408 +Epoch: [14] [2050/2639] eta: 0:29:42 lr: 3.3016433613782335e-05 loss: 0.0531 (0.0664) time: 3.0313 data: 0.0078 max mem: 33408 +Epoch: [14] [2060/2639] eta: 0:29:12 lr: 3.3011969419940006e-05 loss: 0.0579 (0.0664) time: 3.0611 data: 0.0079 max mem: 33408 +Epoch: [14] [2070/2639] eta: 0:28:42 lr: 3.3007505159019905e-05 loss: 0.0584 (0.0664) time: 3.0448 data: 0.0078 max mem: 33408 +Epoch: [14] [2080/2639] eta: 0:28:11 lr: 3.3003040831010924e-05 loss: 0.0500 (0.0664) time: 2.9995 data: 0.0081 max mem: 33408 +Epoch: [14] [2090/2639] eta: 0:27:41 lr: 3.2998576435901986e-05 loss: 0.0514 (0.0664) time: 3.0194 data: 0.0081 max mem: 33408 +Epoch: [14] [2100/2639] eta: 0:27:11 lr: 3.299411197368199e-05 loss: 0.0722 (0.0665) time: 3.0553 data: 0.0075 max mem: 33408 +Epoch: [14] [2110/2639] eta: 0:26:41 lr: 3.298964744433985e-05 loss: 0.0714 (0.0665) time: 3.0467 data: 0.0078 max mem: 33408 +Epoch: [14] [2120/2639] eta: 0:26:10 lr: 3.298518284786445e-05 loss: 0.0564 (0.0666) time: 3.0271 data: 0.0081 max mem: 33408 +Epoch: [14] [2130/2639] eta: 0:25:40 lr: 3.298071818424468e-05 loss: 0.0551 (0.0666) time: 3.0201 data: 0.0083 max mem: 33408 +Epoch: [14] [2140/2639] eta: 0:25:10 lr: 3.297625345346945e-05 loss: 0.0564 (0.0666) time: 3.0113 data: 0.0083 max mem: 33408 +Epoch: [14] [2150/2639] eta: 0:24:40 lr: 3.2971788655527636e-05 loss: 0.0588 (0.0665) time: 3.0254 data: 0.0076 max mem: 33408 +Epoch: [14] [2160/2639] eta: 0:24:09 lr: 3.296732379040811e-05 loss: 0.0500 (0.0665) time: 3.0190 data: 0.0071 max mem: 33408 +Epoch: [14] [2170/2639] eta: 0:23:39 lr: 3.2962858858099766e-05 loss: 0.0558 (0.0665) time: 2.9954 data: 0.0078 max mem: 33408 +Epoch: [14] [2180/2639] eta: 0:23:09 lr: 3.2958393858591485e-05 loss: 0.0591 (0.0665) time: 3.0167 data: 0.0083 max mem: 33408 +Epoch: [14] [2190/2639] eta: 0:22:39 lr: 3.295392879187213e-05 loss: 0.0516 (0.0664) time: 3.1097 data: 0.0082 max mem: 33408 +Epoch: [14] [2200/2639] eta: 0:22:09 lr: 3.2949463657930564e-05 loss: 0.0559 (0.0665) time: 3.1331 data: 0.0087 max mem: 33408 +Epoch: [14] [2210/2639] eta: 0:21:38 lr: 3.2944998456755664e-05 loss: 0.0595 (0.0665) time: 3.0190 data: 0.0086 max mem: 33408 +Epoch: [14] [2220/2639] eta: 0:21:08 lr: 3.294053318833629e-05 loss: 0.0578 (0.0665) time: 2.9819 data: 0.0078 max mem: 33408 +Epoch: [14] [2230/2639] eta: 0:20:38 lr: 3.2936067852661306e-05 loss: 0.0578 (0.0665) time: 2.9938 data: 0.0074 max mem: 33408 +Epoch: [14] [2240/2639] eta: 0:20:07 lr: 3.293160244971956e-05 loss: 0.0652 (0.0666) time: 3.0093 data: 0.0077 max mem: 33408 +Epoch: [14] [2250/2639] eta: 0:19:37 lr: 3.2927136979499905e-05 loss: 0.0635 (0.0665) time: 3.0135 data: 0.0079 max mem: 33408 +Epoch: [14] [2260/2639] eta: 0:19:07 lr: 3.2922671441991194e-05 loss: 0.0594 (0.0666) time: 3.0339 data: 0.0075 max mem: 33408 +Epoch: [14] [2270/2639] eta: 0:18:36 lr: 3.2918205837182265e-05 loss: 0.0590 (0.0666) time: 3.0362 data: 0.0078 max mem: 33408 +Epoch: [14] [2280/2639] eta: 0:18:06 lr: 3.291374016506196e-05 loss: 0.0590 (0.0666) time: 3.0381 data: 0.0078 max mem: 33408 +Epoch: [14] [2290/2639] eta: 0:17:36 lr: 3.2909274425619124e-05 loss: 0.0601 (0.0666) time: 3.0742 data: 0.0078 max mem: 33408 +Epoch: [14] [2300/2639] eta: 0:17:06 lr: 3.2904808618842575e-05 loss: 0.0531 (0.0666) time: 3.0283 data: 0.0081 max mem: 33408 +Epoch: [14] [2310/2639] eta: 0:16:36 lr: 3.290034274472117e-05 loss: 0.0556 (0.0667) time: 3.0380 data: 0.0080 max mem: 33408 +Epoch: [14] [2320/2639] eta: 0:16:05 lr: 3.2895876803243714e-05 loss: 0.0590 (0.0666) time: 3.0345 data: 0.0079 max mem: 33408 +Epoch: [14] [2330/2639] eta: 0:15:35 lr: 3.289141079439903e-05 loss: 0.0590 (0.0667) time: 3.0113 data: 0.0078 max mem: 33408 +Epoch: [14] [2340/2639] eta: 0:15:05 lr: 3.288694471817595e-05 loss: 0.0675 (0.0666) time: 3.0307 data: 0.0076 max mem: 33408 +Epoch: [14] [2350/2639] eta: 0:14:34 lr: 3.288247857456329e-05 loss: 0.0626 (0.0667) time: 3.0379 data: 0.0077 max mem: 33408 +Epoch: [14] [2360/2639] eta: 0:14:04 lr: 3.287801236354985e-05 loss: 0.0579 (0.0667) time: 3.0595 data: 0.0079 max mem: 33408 +Epoch: [14] [2370/2639] eta: 0:13:34 lr: 3.287354608512445e-05 loss: 0.0558 (0.0666) time: 3.0318 data: 0.0076 max mem: 33408 +Epoch: [14] [2380/2639] eta: 0:13:04 lr: 3.286907973927589e-05 loss: 0.0575 (0.0667) time: 3.0096 data: 0.0076 max mem: 33408 +Epoch: [14] [2390/2639] eta: 0:12:33 lr: 3.286461332599299e-05 loss: 0.0607 (0.0667) time: 3.0321 data: 0.0076 max mem: 33408 +Epoch: [14] [2400/2639] eta: 0:12:03 lr: 3.2860146845264525e-05 loss: 0.0571 (0.0666) time: 3.0237 data: 0.0073 max mem: 33408 +Epoch: [14] [2410/2639] eta: 0:11:33 lr: 3.28556802970793e-05 loss: 0.0565 (0.0667) time: 3.0079 data: 0.0078 max mem: 33408 +Epoch: [14] [2420/2639] eta: 0:11:02 lr: 3.2851213681426104e-05 loss: 0.0573 (0.0667) time: 2.9854 data: 0.0080 max mem: 33408 +Epoch: [14] [2430/2639] eta: 0:10:32 lr: 3.284674699829373e-05 loss: 0.0654 (0.0667) time: 2.9702 data: 0.0078 max mem: 33408 +Epoch: [14] [2440/2639] eta: 0:10:02 lr: 3.2842280247670964e-05 loss: 0.0726 (0.0667) time: 3.0038 data: 0.0078 max mem: 33408 +Epoch: [14] [2450/2639] eta: 0:09:32 lr: 3.283781342954658e-05 loss: 0.0623 (0.0667) time: 3.0528 data: 0.0077 max mem: 33408 +Epoch: [14] [2460/2639] eta: 0:09:01 lr: 3.283334654390935e-05 loss: 0.0678 (0.0669) time: 3.0501 data: 0.0075 max mem: 33408 +Epoch: [14] [2470/2639] eta: 0:08:31 lr: 3.2828879590748055e-05 loss: 0.0678 (0.0669) time: 3.0309 data: 0.0075 max mem: 33408 +Epoch: [14] [2480/2639] eta: 0:08:01 lr: 3.282441257005148e-05 loss: 0.0669 (0.0669) time: 3.0159 data: 0.0077 max mem: 33408 +Epoch: [14] [2490/2639] eta: 0:07:30 lr: 3.281994548180837e-05 loss: 0.0603 (0.0669) time: 2.9969 data: 0.0080 max mem: 33408 +Epoch: [14] [2500/2639] eta: 0:07:00 lr: 3.2815478326007495e-05 loss: 0.0524 (0.0669) time: 2.9999 data: 0.0082 max mem: 33408 +Epoch: [14] [2510/2639] eta: 0:06:30 lr: 3.2811011102637616e-05 loss: 0.0594 (0.0669) time: 3.0301 data: 0.0078 max mem: 33408 +Epoch: [14] [2520/2639] eta: 0:06:00 lr: 3.28065438116875e-05 loss: 0.0618 (0.0669) time: 3.0536 data: 0.0077 max mem: 33408 +Epoch: [14] [2530/2639] eta: 0:05:29 lr: 3.280207645314587e-05 loss: 0.0606 (0.0669) time: 3.0112 data: 0.0075 max mem: 33408 +Epoch: [14] [2540/2639] eta: 0:04:59 lr: 3.27976090270015e-05 loss: 0.0606 (0.0669) time: 3.0105 data: 0.0075 max mem: 33408 +Epoch: [14] [2550/2639] eta: 0:04:29 lr: 3.279314153324313e-05 loss: 0.0644 (0.0669) time: 3.0257 data: 0.0079 max mem: 33408 +Epoch: [14] [2560/2639] eta: 0:03:59 lr: 3.2788673971859494e-05 loss: 0.0589 (0.0668) time: 3.0314 data: 0.0081 max mem: 33408 +Epoch: [14] [2570/2639] eta: 0:03:28 lr: 3.278420634283934e-05 loss: 0.0557 (0.0668) time: 3.0434 data: 0.0079 max mem: 33408 +Epoch: [14] [2580/2639] eta: 0:02:58 lr: 3.2779738646171394e-05 loss: 0.0705 (0.0669) time: 3.0716 data: 0.0075 max mem: 33408 +Epoch: [14] [2590/2639] eta: 0:02:28 lr: 3.277527088184439e-05 loss: 0.0645 (0.0669) time: 3.0555 data: 0.0073 max mem: 33408 +Epoch: [14] [2600/2639] eta: 0:01:58 lr: 3.2770803049847065e-05 loss: 0.0564 (0.0669) time: 3.0160 data: 0.0074 max mem: 33408 +Epoch: [14] [2610/2639] eta: 0:01:27 lr: 3.2766335150168134e-05 loss: 0.0569 (0.0669) time: 3.0247 data: 0.0078 max mem: 33408 +Epoch: [14] [2620/2639] eta: 0:00:57 lr: 3.276186718279631e-05 loss: 0.0602 (0.0669) time: 3.0869 data: 0.0078 max mem: 33408 +Epoch: [14] [2630/2639] eta: 0:00:27 lr: 3.275739914772031e-05 loss: 0.0485 (0.0669) time: 3.1201 data: 0.0072 max mem: 33408 +Epoch: [14] Total time: 2:13:10 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 2:09:35 time: 3.0221 data: 2.9212 max mem: 33408 +Test: [ 100/2573] eta: 0:04:24 time: 0.0776 data: 0.0015 max mem: 33408 +Test: [ 200/2573] eta: 0:03:42 time: 0.0796 data: 0.0013 max mem: 33408 +Test: [ 300/2573] eta: 0:03:21 time: 0.0809 data: 0.0014 max mem: 33408 +Test: [ 400/2573] eta: 0:03:08 time: 0.0817 data: 0.0014 max mem: 33408 +Test: [ 500/2573] eta: 0:02:56 time: 0.0806 data: 0.0016 max mem: 33408 +Test: [ 600/2573] eta: 0:02:47 time: 0.0811 data: 0.0014 max mem: 33408 +Test: [ 700/2573] eta: 0:02:37 time: 0.0799 data: 0.0014 max mem: 33408 +Test: [ 800/2573] eta: 0:02:28 time: 0.0838 data: 0.0015 max mem: 33408 +Test: [ 900/2573] eta: 0:02:19 time: 0.0794 data: 0.0015 max mem: 33408 +Test: [1000/2573] eta: 0:02:11 time: 0.0812 data: 0.0015 max mem: 33408 +Test: [1100/2573] eta: 0:02:02 time: 0.0810 data: 0.0014 max mem: 33408 +Test: [1200/2573] eta: 0:01:53 time: 0.0812 data: 0.0014 max mem: 33408 +Test: [1300/2573] eta: 0:01:45 time: 0.0794 data: 0.0014 max mem: 33408 +Test: [1400/2573] eta: 0:01:36 time: 0.0795 data: 0.0015 max mem: 33408 +Test: [1500/2573] eta: 0:01:28 time: 0.0813 data: 0.0015 max mem: 33408 +Test: [1600/2573] eta: 0:01:20 time: 0.0838 data: 0.0014 max mem: 33408 +Test: [1700/2573] eta: 0:01:11 time: 0.0800 data: 0.0015 max mem: 33408 +Test: [1800/2573] eta: 0:01:03 time: 0.0829 data: 0.0015 max mem: 33408 +Test: [1900/2573] eta: 0:00:55 time: 0.0791 data: 0.0015 max mem: 33408 +Test: [2000/2573] eta: 0:00:47 time: 0.0813 data: 0.0014 max mem: 33408 +Test: [2100/2573] eta: 0:00:38 time: 0.0826 data: 0.0015 max mem: 33408 +Test: [2200/2573] eta: 0:00:30 time: 0.0834 data: 0.0014 max mem: 33408 +Test: [2300/2573] eta: 0:00:22 time: 0.0827 data: 0.0015 max mem: 33408 +Test: [2400/2573] eta: 0:00:14 time: 0.0792 data: 0.0014 max mem: 33408 +Test: [2500/2573] eta: 0:00:05 time: 0.0813 data: 0.0015 max mem: 33408 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: Total time: 0:03:32 +Final results: +Mean IoU is 61.83 + + precision@0.5 = 69.71 + precision@0.6 = 64.11 + precision@0.7 = 56.80 + precision@0.8 = 43.85 + precision@0.9 = 20.51 + overall IoU = 59.88 + +Average object IoU 61.82855366218909 +Overall IoU 59.87661361694336 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [15] [ 0/2639] eta: 3:58:22 lr: 3.275337785825553e-05 loss: 0.0441 (0.0441) time: 5.4195 data: 2.1454 max mem: 33408 +Epoch: [15] [ 10/2639] eta: 2:21:04 lr: 3.2748909694510515e-05 loss: 0.0519 (0.0546) time: 3.2196 data: 0.2026 max mem: 33408 +Epoch: [15] [ 20/2639] eta: 2:16:41 lr: 3.274444146302859e-05 loss: 0.0499 (0.0536) time: 3.0172 data: 0.0075 max mem: 33408 +Epoch: [15] [ 30/2639] eta: 2:13:31 lr: 3.273997316379846e-05 loss: 0.0437 (0.0575) time: 2.9886 data: 0.0075 max mem: 33408 +Epoch: [15] [ 40/2639] eta: 2:11:53 lr: 3.2735504796808816e-05 loss: 0.0514 (0.0624) time: 2.9539 data: 0.0081 max mem: 33408 +Epoch: [15] [ 50/2639] eta: 2:11:15 lr: 3.2731036362048364e-05 loss: 0.0567 (0.0629) time: 2.9972 data: 0.0080 max mem: 33408 +Epoch: [15] [ 60/2639] eta: 2:10:16 lr: 3.272656785950578e-05 loss: 0.0561 (0.0630) time: 3.0017 data: 0.0080 max mem: 33408 +Epoch: [15] [ 70/2639] eta: 2:10:00 lr: 3.2722099289169764e-05 loss: 0.0530 (0.0619) time: 3.0225 data: 0.0079 max mem: 33408 +Epoch: [15] [ 80/2639] eta: 2:09:08 lr: 3.271763065102901e-05 loss: 0.0534 (0.0606) time: 3.0192 data: 0.0082 max mem: 33408 +Epoch: [15] [ 90/2639] eta: 2:08:48 lr: 3.271316194507217e-05 loss: 0.0534 (0.0608) time: 3.0163 data: 0.0081 max mem: 33408 +Epoch: [15] [ 100/2639] eta: 2:08:02 lr: 3.270869317128794e-05 loss: 0.0517 (0.0598) time: 3.0177 data: 0.0075 max mem: 33408 +Epoch: [15] [ 110/2639] eta: 2:07:22 lr: 3.2704224329664996e-05 loss: 0.0509 (0.0601) time: 2.9768 data: 0.0077 max mem: 33408 +Epoch: [15] [ 120/2639] eta: 2:06:59 lr: 3.2699755420192e-05 loss: 0.0630 (0.0610) time: 3.0187 data: 0.0078 max mem: 33408 +Epoch: [15] [ 130/2639] eta: 2:06:24 lr: 3.269528644285763e-05 loss: 0.0518 (0.0608) time: 3.0282 data: 0.0076 max mem: 33408 +Epoch: [15] [ 140/2639] eta: 2:06:10 lr: 3.2690817397650536e-05 loss: 0.0503 (0.0607) time: 3.0576 data: 0.0076 max mem: 33408 +Epoch: [15] [ 150/2639] eta: 2:05:29 lr: 3.268634828455938e-05 loss: 0.0530 (0.0625) time: 3.0389 data: 0.0076 max mem: 33408 +Epoch: [15] [ 160/2639] eta: 2:05:06 lr: 3.268187910357283e-05 loss: 0.0555 (0.0621) time: 3.0182 data: 0.0074 max mem: 33408 +Epoch: [15] [ 170/2639] eta: 2:04:28 lr: 3.2677409854679525e-05 loss: 0.0555 (0.0619) time: 3.0241 data: 0.0076 max mem: 33408 +Epoch: [15] [ 180/2639] eta: 2:03:59 lr: 3.267294053786811e-05 loss: 0.0553 (0.0617) time: 3.0057 data: 0.0079 max mem: 33408 +Epoch: [15] [ 190/2639] eta: 2:03:23 lr: 3.266847115312724e-05 loss: 0.0577 (0.0623) time: 3.0072 data: 0.0079 max mem: 33408 +Epoch: [15] [ 200/2639] eta: 2:02:50 lr: 3.2664001700445555e-05 loss: 0.0586 (0.0622) time: 2.9894 data: 0.0081 max mem: 33408 +Epoch: [15] [ 210/2639] eta: 2:02:17 lr: 3.2659532179811693e-05 loss: 0.0586 (0.0629) time: 2.9989 data: 0.0080 max mem: 33408 +Epoch: [15] [ 220/2639] eta: 2:01:53 lr: 3.265506259121428e-05 loss: 0.0641 (0.0629) time: 3.0363 data: 0.0078 max mem: 33408 +Epoch: [15] [ 230/2639] eta: 2:01:32 lr: 3.265059293464195e-05 loss: 0.0591 (0.0627) time: 3.0944 data: 0.0083 max mem: 33408 +Epoch: [15] [ 240/2639] eta: 2:01:02 lr: 3.2646123210083336e-05 loss: 0.0511 (0.0623) time: 3.0722 data: 0.0085 max mem: 33408 +Epoch: [15] [ 250/2639] eta: 2:00:34 lr: 3.264165341752705e-05 loss: 0.0555 (0.0631) time: 3.0421 data: 0.0078 max mem: 33408 +Epoch: [15] [ 260/2639] eta: 2:00:04 lr: 3.263718355696172e-05 loss: 0.0620 (0.0637) time: 3.0411 data: 0.0077 max mem: 33408 +Epoch: [15] [ 270/2639] eta: 1:59:33 lr: 3.263271362837596e-05 loss: 0.0613 (0.0642) time: 3.0242 data: 0.0077 max mem: 33408 +Epoch: [15] [ 280/2639] eta: 1:59:06 lr: 3.262824363175838e-05 loss: 0.0547 (0.0638) time: 3.0434 data: 0.0075 max mem: 33408 +Epoch: [15] [ 290/2639] eta: 1:58:32 lr: 3.26237735670976e-05 loss: 0.0547 (0.0636) time: 3.0237 data: 0.0078 max mem: 33408 +Epoch: [15] [ 300/2639] eta: 1:58:02 lr: 3.2619303434382195e-05 loss: 0.0555 (0.0634) time: 3.0085 data: 0.0080 max mem: 33408 +Epoch: [15] [ 310/2639] eta: 1:57:29 lr: 3.261483323360079e-05 loss: 0.0581 (0.0631) time: 3.0159 data: 0.0081 max mem: 33408 +Epoch: [15] [ 320/2639] eta: 1:57:08 lr: 3.261036296474199e-05 loss: 0.0587 (0.0630) time: 3.0755 data: 0.0080 max mem: 33408 +Epoch: [15] [ 330/2639] eta: 1:56:40 lr: 3.2605892627794377e-05 loss: 0.0577 (0.0631) time: 3.1053 data: 0.0079 max mem: 33408 +Epoch: [15] [ 340/2639] eta: 1:56:10 lr: 3.2601422222746534e-05 loss: 0.0523 (0.0630) time: 3.0512 data: 0.0080 max mem: 33408 +Epoch: [15] [ 350/2639] eta: 1:55:42 lr: 3.259695174958705e-05 loss: 0.0602 (0.0631) time: 3.0512 data: 0.0080 max mem: 33408 +Epoch: [15] [ 360/2639] eta: 1:55:13 lr: 3.259248120830452e-05 loss: 0.0531 (0.0629) time: 3.0543 data: 0.0082 max mem: 33408 +Epoch: [15] [ 370/2639] eta: 1:54:44 lr: 3.258801059888752e-05 loss: 0.0476 (0.0626) time: 3.0579 data: 0.0079 max mem: 33408 +Epoch: [15] [ 380/2639] eta: 1:54:14 lr: 3.258353992132462e-05 loss: 0.0487 (0.0627) time: 3.0470 data: 0.0074 max mem: 33408 +Epoch: [15] [ 390/2639] eta: 1:53:51 lr: 3.257906917560439e-05 loss: 0.0561 (0.0627) time: 3.0969 data: 0.0075 max mem: 33408 +Epoch: [15] [ 400/2639] eta: 1:53:19 lr: 3.25745983617154e-05 loss: 0.0569 (0.0628) time: 3.0891 data: 0.0083 max mem: 33408 +Epoch: [15] [ 410/2639] eta: 1:52:47 lr: 3.257012747964622e-05 loss: 0.0611 (0.0627) time: 3.0110 data: 0.0085 max mem: 33408 +Epoch: [15] [ 420/2639] eta: 1:52:14 lr: 3.2565656529385406e-05 loss: 0.0619 (0.0630) time: 2.9979 data: 0.0082 max mem: 33408 +Epoch: [15] [ 430/2639] eta: 1:51:43 lr: 3.256118551092152e-05 loss: 0.0629 (0.0630) time: 2.9992 data: 0.0080 max mem: 33408 +Epoch: [15] [ 440/2639] eta: 1:51:10 lr: 3.2556714424243104e-05 loss: 0.0674 (0.0632) time: 2.9959 data: 0.0077 max mem: 33408 +Epoch: [15] [ 450/2639] eta: 1:50:42 lr: 3.255224326933873e-05 loss: 0.0669 (0.0633) time: 3.0325 data: 0.0076 max mem: 33408 +Epoch: [15] [ 460/2639] eta: 1:50:12 lr: 3.254777204619693e-05 loss: 0.0524 (0.0633) time: 3.0707 data: 0.0077 max mem: 33408 +Epoch: [15] [ 470/2639] eta: 1:49:40 lr: 3.2543300754806235e-05 loss: 0.0578 (0.0635) time: 3.0216 data: 0.0081 max mem: 33408 +Epoch: [15] [ 480/2639] eta: 1:49:12 lr: 3.25388293951552e-05 loss: 0.0589 (0.0635) time: 3.0414 data: 0.0081 max mem: 33408 +Epoch: [15] [ 490/2639] eta: 1:48:40 lr: 3.2534357967232364e-05 loss: 0.0556 (0.0633) time: 3.0476 data: 0.0077 max mem: 33408 +Epoch: [15] [ 500/2639] eta: 1:48:13 lr: 3.252988647102625e-05 loss: 0.0556 (0.0635) time: 3.0555 data: 0.0075 max mem: 33408 +Epoch: [15] [ 510/2639] eta: 1:47:42 lr: 3.252541490652539e-05 loss: 0.0659 (0.0637) time: 3.0585 data: 0.0079 max mem: 33408 +Epoch: [15] [ 520/2639] eta: 1:47:11 lr: 3.252094327371829e-05 loss: 0.0557 (0.0635) time: 3.0176 data: 0.0081 max mem: 33408 +Epoch: [15] [ 530/2639] eta: 1:46:38 lr: 3.251647157259351e-05 loss: 0.0556 (0.0634) time: 3.0003 data: 0.0080 max mem: 33408 +Epoch: [15] [ 540/2639] eta: 1:46:05 lr: 3.2511999803139524e-05 loss: 0.0585 (0.0635) time: 2.9658 data: 0.0080 max mem: 33408 +Epoch: [15] [ 550/2639] eta: 1:45:34 lr: 3.250752796534487e-05 loss: 0.0691 (0.0636) time: 2.9828 data: 0.0079 max mem: 33408 +Epoch: [15] [ 560/2639] eta: 1:45:03 lr: 3.250305605919805e-05 loss: 0.0581 (0.0636) time: 3.0108 data: 0.0076 max mem: 33408 +Epoch: [15] [ 570/2639] eta: 1:44:34 lr: 3.249858408468758e-05 loss: 0.0581 (0.0638) time: 3.0428 data: 0.0076 max mem: 33408 +Epoch: [15] [ 580/2639] eta: 1:44:06 lr: 3.249411204180195e-05 loss: 0.0632 (0.0638) time: 3.0910 data: 0.0077 max mem: 33408 +Epoch: [15] [ 590/2639] eta: 1:43:35 lr: 3.2489639930529655e-05 loss: 0.0611 (0.0639) time: 3.0618 data: 0.0078 max mem: 33408 +Epoch: [15] [ 600/2639] eta: 1:43:06 lr: 3.2485167750859195e-05 loss: 0.0555 (0.0637) time: 3.0363 data: 0.0079 max mem: 33408 +Epoch: [15] [ 610/2639] eta: 1:42:33 lr: 3.248069550277907e-05 loss: 0.0548 (0.0636) time: 3.0153 data: 0.0083 max mem: 33408 +Epoch: [15] [ 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33408 +Epoch: [15] [ 700/2639] eta: 1:37:59 lr: 3.2440442189721906e-05 loss: 0.0596 (0.0636) time: 3.0339 data: 0.0077 max mem: 33408 +Epoch: [15] [ 710/2639] eta: 1:37:32 lr: 3.2435969256911254e-05 loss: 0.0767 (0.0638) time: 3.0793 data: 0.0077 max mem: 33408 +Epoch: [15] [ 720/2639] eta: 1:37:00 lr: 3.243149625556409e-05 loss: 0.0612 (0.0637) time: 3.0733 data: 0.0073 max mem: 33408 +Epoch: [15] [ 730/2639] eta: 1:36:30 lr: 3.242702318566885e-05 loss: 0.0554 (0.0636) time: 3.0036 data: 0.0073 max mem: 33408 +Epoch: [15] [ 740/2639] eta: 1:36:00 lr: 3.2422550047213996e-05 loss: 0.0485 (0.0636) time: 3.0520 data: 0.0076 max mem: 33408 +Epoch: [15] [ 750/2639] eta: 1:35:29 lr: 3.2418076840187954e-05 loss: 0.0458 (0.0634) time: 3.0375 data: 0.0081 max mem: 33408 +Epoch: [15] [ 760/2639] eta: 1:34:57 lr: 3.241360356457915e-05 loss: 0.0560 (0.0634) time: 2.9851 data: 0.0081 max mem: 33408 +Epoch: [15] [ 770/2639] eta: 1:34:27 lr: 3.240913022037604e-05 loss: 0.0537 (0.0633) time: 3.0022 data: 0.0077 max mem: 33408 +Epoch: [15] [ 780/2639] eta: 1:33:56 lr: 3.240465680756704e-05 loss: 0.0550 (0.0633) time: 3.0228 data: 0.0078 max mem: 33408 +Epoch: [15] [ 790/2639] eta: 1:33:27 lr: 3.2400183326140565e-05 loss: 0.0613 (0.0633) time: 3.0444 data: 0.0080 max mem: 33408 +Epoch: [15] [ 800/2639] eta: 1:32:59 lr: 3.2395709776085044e-05 loss: 0.0537 (0.0633) time: 3.1032 data: 0.0075 max mem: 33408 +Epoch: [15] [ 810/2639] eta: 1:32:27 lr: 3.2391236157388894e-05 loss: 0.0525 (0.0633) time: 3.0500 data: 0.0081 max mem: 33408 +Epoch: [15] [ 820/2639] eta: 1:31:56 lr: 3.2386762470040526e-05 loss: 0.0512 (0.0633) time: 2.9833 data: 0.0086 max mem: 33408 +Epoch: [15] [ 830/2639] eta: 1:31:26 lr: 3.238228871402836e-05 loss: 0.0501 (0.0633) time: 3.0192 data: 0.0084 max mem: 33408 +Epoch: [15] [ 840/2639] eta: 1:30:56 lr: 3.237781488934078e-05 loss: 0.0491 (0.0633) time: 3.0509 data: 0.0081 max mem: 33408 +Epoch: [15] [ 850/2639] eta: 1:30:25 lr: 3.237334099596621e-05 loss: 0.0551 (0.0633) time: 3.0191 data: 0.0075 max mem: 33408 +Epoch: [15] [ 860/2639] eta: 1:29:54 lr: 3.2368867033893025e-05 loss: 0.0551 (0.0632) time: 3.0037 data: 0.0076 max mem: 33408 +Epoch: [15] [ 870/2639] eta: 1:29:23 lr: 3.2364393003109647e-05 loss: 0.0581 (0.0633) time: 3.0182 data: 0.0079 max mem: 33408 +Epoch: [15] [ 880/2639] eta: 1:28:53 lr: 3.2359918903604446e-05 loss: 0.0670 (0.0633) time: 3.0306 data: 0.0078 max mem: 33408 +Epoch: [15] [ 890/2639] eta: 1:28:24 lr: 3.2355444735365814e-05 loss: 0.0517 (0.0632) time: 3.0574 data: 0.0077 max mem: 33408 +Epoch: [15] [ 900/2639] eta: 1:27:54 lr: 3.235097049838213e-05 loss: 0.0517 (0.0633) time: 3.0582 data: 0.0078 max mem: 33408 +Epoch: [15] [ 910/2639] eta: 1:27:23 lr: 3.2346496192641796e-05 loss: 0.0501 (0.0632) time: 3.0377 data: 0.0080 max mem: 33408 +Epoch: [15] [ 920/2639] eta: 1:26:52 lr: 3.234202181813316e-05 loss: 0.0541 (0.0631) time: 2.9987 data: 0.0080 max mem: 33408 +Epoch: [15] [ 930/2639] eta: 1:26:22 lr: 3.23375473748446e-05 loss: 0.0569 (0.0632) time: 3.0232 data: 0.0079 max mem: 33408 +Epoch: [15] [ 940/2639] eta: 1:25:51 lr: 3.233307286276449e-05 loss: 0.0519 (0.0632) time: 3.0273 data: 0.0078 max mem: 33408 +Epoch: [15] [ 950/2639] eta: 1:25:21 lr: 3.2328598281881196e-05 loss: 0.0519 (0.0631) time: 3.0294 data: 0.0078 max mem: 33408 +Epoch: [15] [ 960/2639] eta: 1:24:50 lr: 3.232412363218308e-05 loss: 0.0620 (0.0632) time: 3.0279 data: 0.0080 max mem: 33408 +Epoch: [15] [ 970/2639] eta: 1:24:20 lr: 3.231964891365848e-05 loss: 0.0620 (0.0631) time: 3.0204 data: 0.0079 max mem: 33408 +Epoch: [15] [ 980/2639] eta: 1:23:50 lr: 3.2315174126295764e-05 loss: 0.0514 (0.0630) time: 3.0559 data: 0.0077 max mem: 33408 +Epoch: [15] [ 990/2639] eta: 1:23:20 lr: 3.231069927008329e-05 loss: 0.0573 (0.0630) time: 3.0404 data: 0.0078 max mem: 33408 +Epoch: [15] [1000/2639] eta: 1:22:50 lr: 3.230622434500939e-05 loss: 0.0503 (0.0628) time: 3.0427 data: 0.0076 max mem: 33408 +Epoch: [15] [1010/2639] eta: 1:22:21 lr: 3.230174935106241e-05 loss: 0.0474 (0.0628) time: 3.0876 data: 0.0080 max mem: 33408 +Epoch: [15] [1020/2639] eta: 1:21:50 lr: 3.229727428823069e-05 loss: 0.0495 (0.0627) time: 3.0643 data: 0.0081 max mem: 33408 +Epoch: [15] [1030/2639] eta: 1:21:21 lr: 3.229279915650256e-05 loss: 0.0520 (0.0628) time: 3.0364 data: 0.0074 max mem: 33408 +Epoch: [15] [1040/2639] eta: 1:20:48 lr: 3.228832395586635e-05 loss: 0.0571 (0.0627) time: 2.9904 data: 0.0076 max mem: 33408 +Epoch: [15] [1050/2639] eta: 1:20:19 lr: 3.228384868631039e-05 loss: 0.0589 (0.0628) time: 2.9944 data: 0.0077 max mem: 33408 +Epoch: [15] [1060/2639] eta: 1:19:49 lr: 3.2279373347823e-05 loss: 0.0574 (0.0633) time: 3.0579 data: 0.0075 max mem: 33408 +Epoch: [15] [1070/2639] eta: 1:19:18 lr: 3.227489794039251e-05 loss: 0.0548 (0.0632) time: 3.0377 data: 0.0076 max mem: 33408 +Epoch: [15] [1080/2639] eta: 1:18:48 lr: 3.227042246400722e-05 loss: 0.0548 (0.0632) time: 3.0345 data: 0.0076 max mem: 33408 +Epoch: [15] [1090/2639] eta: 1:18:17 lr: 3.226594691865544e-05 loss: 0.0546 (0.0632) time: 3.0169 data: 0.0074 max mem: 33408 +Epoch: [15] [1100/2639] eta: 1:17:46 lr: 3.226147130432549e-05 loss: 0.0591 (0.0632) time: 2.9756 data: 0.0073 max mem: 33408 +Epoch: [15] [1110/2639] eta: 1:17:16 lr: 3.225699562100567e-05 loss: 0.0600 (0.0632) time: 3.0236 data: 0.0070 max mem: 33408 +Epoch: [15] [1120/2639] eta: 1:16:45 lr: 3.225251986868429e-05 loss: 0.0679 (0.0633) time: 3.0197 data: 0.0073 max mem: 33408 +Epoch: [15] [1130/2639] eta: 1:16:13 lr: 3.224804404734963e-05 loss: 0.0625 (0.0632) time: 2.9542 data: 0.0078 max mem: 33408 +Epoch: [15] [1140/2639] eta: 1:15:44 lr: 3.2243568156989984e-05 loss: 0.0492 (0.0631) time: 3.0113 data: 0.0077 max mem: 33408 +Epoch: [15] [1150/2639] eta: 1:15:14 lr: 3.223909219759364e-05 loss: 0.0558 (0.0632) time: 3.0639 data: 0.0077 max mem: 33408 +Epoch: [15] [1160/2639] eta: 1:14:43 lr: 3.2234616169148903e-05 loss: 0.0569 (0.0631) time: 3.0357 data: 0.0078 max mem: 33408 +Epoch: [15] [1170/2639] eta: 1:14:13 lr: 3.223014007164404e-05 loss: 0.0586 (0.0633) time: 3.0465 data: 0.0075 max mem: 33408 +Epoch: [15] [1180/2639] eta: 1:13:43 lr: 3.2225663905067326e-05 loss: 0.0652 (0.0633) time: 3.0495 data: 0.0074 max mem: 33408 +Epoch: [15] [1190/2639] eta: 1:13:12 lr: 3.2221187669407035e-05 loss: 0.0674 (0.0634) time: 3.0175 data: 0.0075 max mem: 33408 +Epoch: [15] [1200/2639] eta: 1:12:42 lr: 3.221671136465144e-05 loss: 0.0671 (0.0634) time: 3.0163 data: 0.0073 max mem: 33408 +Epoch: [15] [1210/2639] eta: 1:12:12 lr: 3.2212234990788814e-05 loss: 0.0558 (0.0634) time: 3.0515 data: 0.0075 max mem: 33408 +Epoch: [15] [1220/2639] eta: 1:11:41 lr: 3.22077585478074e-05 loss: 0.0592 (0.0635) time: 3.0344 data: 0.0078 max mem: 33408 +Epoch: [15] [1230/2639] eta: 1:11:11 lr: 3.220328203569547e-05 loss: 0.0586 (0.0635) time: 3.0140 data: 0.0078 max mem: 33408 +Epoch: [15] [1240/2639] eta: 1:10:41 lr: 3.2198805454441275e-05 loss: 0.0546 (0.0634) time: 3.0675 data: 0.0076 max mem: 33408 +Epoch: [15] [1250/2639] eta: 1:10:11 lr: 3.2194328804033084e-05 loss: 0.0601 (0.0635) time: 3.0640 data: 0.0075 max mem: 33408 +Epoch: [15] [1260/2639] eta: 1:09:42 lr: 3.21898520844591e-05 loss: 0.0691 (0.0635) time: 3.0680 data: 0.0075 max mem: 33408 +Epoch: [15] [1270/2639] eta: 1:09:11 lr: 3.218537529570761e-05 loss: 0.0519 (0.0634) time: 3.0366 data: 0.0075 max mem: 33408 +Epoch: [15] [1280/2639] eta: 1:08:41 lr: 3.218089843776684e-05 loss: 0.0554 (0.0635) time: 3.0313 data: 0.0080 max mem: 33408 +Epoch: [15] [1290/2639] eta: 1:08:10 lr: 3.217642151062502e-05 loss: 0.0653 (0.0635) time: 3.0303 data: 0.0081 max mem: 33408 +Epoch: [15] [1300/2639] eta: 1:07:40 lr: 3.217194451427038e-05 loss: 0.0626 (0.0636) time: 3.0096 data: 0.0075 max mem: 33408 +Epoch: [15] [1310/2639] eta: 1:07:09 lr: 3.216746744869115e-05 loss: 0.0596 (0.0635) time: 3.0236 data: 0.0075 max mem: 33408 +Epoch: [15] [1320/2639] eta: 1:06:39 lr: 3.216299031387556e-05 loss: 0.0530 (0.0636) time: 3.0052 data: 0.0077 max mem: 33408 +Epoch: [15] [1330/2639] eta: 1:06:08 lr: 3.2158513109811834e-05 loss: 0.0511 (0.0635) time: 3.0072 data: 0.0075 max mem: 33408 +Epoch: [15] [1340/2639] eta: 1:05:37 lr: 3.215403583648817e-05 loss: 0.0511 (0.0636) time: 2.9914 data: 0.0077 max mem: 33408 +Epoch: [15] [1350/2639] eta: 1:05:07 lr: 3.2149558493892795e-05 loss: 0.0600 (0.0636) time: 3.0310 data: 0.0077 max mem: 33408 +Epoch: [15] [1360/2639] eta: 1:04:37 lr: 3.214508108201392e-05 loss: 0.0529 (0.0636) time: 3.0493 data: 0.0076 max mem: 33408 +Epoch: [15] [1370/2639] eta: 1:04:07 lr: 3.214060360083974e-05 loss: 0.0588 (0.0636) time: 3.0225 data: 0.0078 max mem: 33408 +Epoch: [15] [1380/2639] eta: 1:03:36 lr: 3.2136126050358463e-05 loss: 0.0596 (0.0636) time: 3.0214 data: 0.0075 max mem: 33408 +Epoch: [15] [1390/2639] eta: 1:03:07 lr: 3.213164843055828e-05 loss: 0.0583 (0.0636) time: 3.0588 data: 0.0074 max mem: 33408 +Epoch: [15] [1400/2639] eta: 1:02:36 lr: 3.2127170741427384e-05 loss: 0.0616 (0.0636) time: 3.0571 data: 0.0077 max mem: 33408 +Epoch: [15] [1410/2639] eta: 1:02:06 lr: 3.212269298295398e-05 loss: 0.0647 (0.0637) time: 3.0300 data: 0.0075 max mem: 33408 +Epoch: [15] [1420/2639] eta: 1:01:36 lr: 3.211821515512624e-05 loss: 0.0545 (0.0637) time: 3.0533 data: 0.0073 max mem: 33408 +Epoch: [15] [1430/2639] eta: 1:01:05 lr: 3.2113737257932346e-05 loss: 0.0518 (0.0636) time: 3.0092 data: 0.0077 max mem: 33408 +Epoch: [15] [1440/2639] eta: 1:00:34 lr: 3.210925929136048e-05 loss: 0.0561 (0.0637) time: 2.9918 data: 0.0080 max mem: 33408 +Epoch: [15] [1450/2639] eta: 1:00:03 lr: 3.210478125539882e-05 loss: 0.0633 (0.0636) time: 2.9583 data: 0.0082 max mem: 33408 +Epoch: [15] [1460/2639] eta: 0:59:32 lr: 3.2100303150035525e-05 loss: 0.0537 (0.0635) time: 2.9315 data: 0.0082 max mem: 33408 +Epoch: [15] [1470/2639] eta: 0:59:01 lr: 3.2095824975258764e-05 loss: 0.0526 (0.0635) time: 2.9517 data: 0.0080 max mem: 33408 +Epoch: [15] [1480/2639] eta: 0:58:30 lr: 3.209134673105671e-05 loss: 0.0535 (0.0635) time: 2.9665 data: 0.0081 max mem: 33408 +Epoch: [15] [1490/2639] eta: 0:57:59 lr: 3.2086868417417516e-05 loss: 0.0508 (0.0636) time: 2.9577 data: 0.0078 max mem: 33408 +Epoch: [15] [1500/2639] eta: 0:57:29 lr: 3.208239003432933e-05 loss: 0.0508 (0.0636) time: 2.9510 data: 0.0077 max mem: 33408 +Epoch: [15] [1510/2639] eta: 0:57:00 lr: 3.207791158178032e-05 loss: 0.0598 (0.0638) time: 3.0818 data: 0.0078 max mem: 33408 +Epoch: [15] [1520/2639] eta: 0:56:30 lr: 3.207343305975861e-05 loss: 0.0598 (0.0637) time: 3.1221 data: 0.0079 max mem: 33408 +Epoch: [15] [1530/2639] eta: 0:55:59 lr: 3.206895446825237e-05 loss: 0.0495 (0.0639) time: 3.0569 data: 0.0080 max mem: 33408 +Epoch: [15] [1540/2639] eta: 0:55:30 lr: 3.206447580724972e-05 loss: 0.0570 (0.0639) time: 3.0859 data: 0.0080 max mem: 33408 +Epoch: [15] [1550/2639] eta: 0:54:59 lr: 3.20599970767388e-05 loss: 0.0601 (0.0639) time: 3.0626 data: 0.0079 max mem: 33408 +Epoch: [15] [1560/2639] eta: 0:54:29 lr: 3.205551827670774e-05 loss: 0.0586 (0.0639) time: 3.0383 data: 0.0078 max mem: 33408 +Epoch: [15] [1570/2639] eta: 0:53:59 lr: 3.205103940714468e-05 loss: 0.0556 (0.0639) time: 3.0264 data: 0.0078 max mem: 33408 +Epoch: [15] [1580/2639] eta: 0:53:28 lr: 3.204656046803773e-05 loss: 0.0547 (0.0639) time: 3.0127 data: 0.0083 max mem: 33408 +Epoch: [15] [1590/2639] eta: 0:52:58 lr: 3.2042081459375015e-05 loss: 0.0485 (0.0640) time: 3.0229 data: 0.0083 max mem: 33408 +Epoch: [15] [1600/2639] eta: 0:52:28 lr: 3.203760238114465e-05 loss: 0.0550 (0.0641) time: 3.0211 data: 0.0081 max mem: 33408 +Epoch: [15] [1610/2639] eta: 0:51:57 lr: 3.203312323333475e-05 loss: 0.0586 (0.0640) time: 3.0141 data: 0.0081 max mem: 33408 +Epoch: [15] [1620/2639] eta: 0:51:27 lr: 3.202864401593343e-05 loss: 0.0586 (0.0640) time: 2.9985 data: 0.0078 max mem: 33408 +Epoch: [15] [1630/2639] eta: 0:50:56 lr: 3.2024164728928784e-05 loss: 0.0567 (0.0640) time: 3.0047 data: 0.0078 max mem: 33408 +Epoch: [15] [1640/2639] eta: 0:50:26 lr: 3.2019685372308914e-05 loss: 0.0554 (0.0639) time: 3.0276 data: 0.0079 max mem: 33408 +Epoch: [15] [1650/2639] eta: 0:49:56 lr: 3.201520594606192e-05 loss: 0.0423 (0.0639) time: 3.0368 data: 0.0079 max mem: 33408 +Epoch: [15] [1660/2639] eta: 0:49:26 lr: 3.2010726450175886e-05 loss: 0.0437 (0.0638) time: 3.0587 data: 0.0077 max mem: 33408 +Epoch: [15] [1670/2639] eta: 0:48:55 lr: 3.2006246884638924e-05 loss: 0.0437 (0.0638) time: 3.0382 data: 0.0074 max mem: 33408 +Epoch: [15] [1680/2639] eta: 0:48:25 lr: 3.20017672494391e-05 loss: 0.0547 (0.0638) time: 3.0100 data: 0.0074 max mem: 33408 +Epoch: [15] [1690/2639] eta: 0:47:55 lr: 3.199728754456449e-05 loss: 0.0590 (0.0638) time: 3.0323 data: 0.0075 max mem: 33408 +Epoch: [15] [1700/2639] eta: 0:47:25 lr: 3.199280777000319e-05 loss: 0.0619 (0.0639) time: 3.0510 data: 0.0081 max mem: 33408 +Epoch: [15] [1710/2639] eta: 0:46:55 lr: 3.198832792574327e-05 loss: 0.0646 (0.0639) time: 3.0792 data: 0.0082 max mem: 33408 +Epoch: [15] [1720/2639] eta: 0:46:24 lr: 3.1983848011772784e-05 loss: 0.0595 (0.0640) time: 3.0447 data: 0.0085 max mem: 33408 +Epoch: [15] [1730/2639] eta: 0:45:54 lr: 3.1979368028079806e-05 loss: 0.0521 (0.0640) time: 3.0275 data: 0.0088 max mem: 33408 +Epoch: [15] [1740/2639] eta: 0:45:23 lr: 3.1974887974652415e-05 loss: 0.0523 (0.0641) time: 3.0094 data: 0.0085 max mem: 33408 +Epoch: [15] [1750/2639] eta: 0:44:53 lr: 3.1970407851478644e-05 loss: 0.0604 (0.0641) time: 3.0400 data: 0.0081 max mem: 33408 +Epoch: [15] [1760/2639] eta: 0:44:24 lr: 3.196592765854656e-05 loss: 0.0557 (0.0640) time: 3.1069 data: 0.0079 max mem: 33408 +Epoch: [15] [1770/2639] eta: 0:43:53 lr: 3.19614473958442e-05 loss: 0.0581 (0.0640) time: 3.0367 data: 0.0083 max mem: 33408 +Epoch: [15] [1780/2639] eta: 0:43:23 lr: 3.195696706335963e-05 loss: 0.0551 (0.0640) time: 2.9925 data: 0.0080 max mem: 33408 +Epoch: [15] [1790/2639] eta: 0:42:52 lr: 3.1952486661080895e-05 loss: 0.0525 (0.0640) time: 2.9920 data: 0.0076 max mem: 33408 +Epoch: [15] [1800/2639] eta: 0:42:22 lr: 3.1948006188996005e-05 loss: 0.0486 (0.0639) time: 3.0199 data: 0.0078 max mem: 33408 +Epoch: [15] [1810/2639] eta: 0:41:51 lr: 3.194352564709301e-05 loss: 0.0531 (0.0639) time: 3.0318 data: 0.0076 max mem: 33408 +Epoch: [15] [1820/2639] eta: 0:41:21 lr: 3.193904503535995e-05 loss: 0.0511 (0.0639) time: 3.0478 data: 0.0081 max mem: 33408 +Epoch: [15] [1830/2639] eta: 0:40:51 lr: 3.193456435378484e-05 loss: 0.0511 (0.0638) time: 3.0583 data: 0.0084 max mem: 33408 +Epoch: [15] [1840/2639] eta: 0:40:21 lr: 3.1930083602355705e-05 loss: 0.0631 (0.0639) time: 3.0066 data: 0.0080 max mem: 33408 +Epoch: [15] [1850/2639] eta: 0:39:50 lr: 3.192560278106056e-05 loss: 0.0607 (0.0639) time: 2.9895 data: 0.0078 max mem: 33408 +Epoch: [15] [1860/2639] eta: 0:39:20 lr: 3.1921121889887426e-05 loss: 0.0495 (0.0639) time: 3.0019 data: 0.0075 max mem: 33408 +Epoch: [15] [1870/2639] eta: 0:38:50 lr: 3.191664092882433e-05 loss: 0.0539 (0.0639) time: 3.0321 data: 0.0076 max mem: 33408 +Epoch: [15] [1880/2639] eta: 0:38:19 lr: 3.1912159897859244e-05 loss: 0.0672 (0.0640) time: 3.0303 data: 0.0075 max mem: 33408 +Epoch: [15] [1890/2639] eta: 0:37:49 lr: 3.19076787969802e-05 loss: 0.0670 (0.0639) time: 3.0386 data: 0.0077 max mem: 33408 +Epoch: [15] [1900/2639] eta: 0:37:19 lr: 3.1903197626175166e-05 loss: 0.0576 (0.0640) time: 3.0436 data: 0.0082 max mem: 33408 +Epoch: [15] [1910/2639] eta: 0:36:48 lr: 3.1898716385432175e-05 loss: 0.0603 (0.0640) time: 3.0385 data: 0.0083 max mem: 33408 +Epoch: [15] [1920/2639] eta: 0:36:18 lr: 3.18942350747392e-05 loss: 0.0541 (0.0639) time: 2.9961 data: 0.0084 max mem: 33408 +Epoch: [15] [1930/2639] eta: 0:35:47 lr: 3.188975369408422e-05 loss: 0.0550 (0.0640) time: 2.9824 data: 0.0081 max mem: 33408 +Epoch: [15] [1940/2639] eta: 0:35:17 lr: 3.1885272243455234e-05 loss: 0.0608 (0.0641) time: 3.0008 data: 0.0076 max mem: 33408 +Epoch: [15] [1950/2639] eta: 0:34:47 lr: 3.188079072284021e-05 loss: 0.0615 (0.0641) time: 3.0537 data: 0.0076 max mem: 33408 +Epoch: [15] [1960/2639] eta: 0:34:17 lr: 3.187630913222714e-05 loss: 0.0568 (0.0640) time: 3.1034 data: 0.0077 max mem: 33408 +Epoch: [15] [1970/2639] eta: 0:33:47 lr: 3.187182747160397e-05 loss: 0.0568 (0.0641) time: 3.0379 data: 0.0082 max mem: 33408 +Epoch: [15] [1980/2639] eta: 0:33:16 lr: 3.186734574095869e-05 loss: 0.0617 (0.0641) time: 3.0120 data: 0.0080 max mem: 33408 +Epoch: [15] [1990/2639] eta: 0:32:46 lr: 3.1862863940279255e-05 loss: 0.0632 (0.0641) time: 2.9852 data: 0.0078 max mem: 33408 +Epoch: [15] [2000/2639] eta: 0:32:15 lr: 3.1858382069553627e-05 loss: 0.0632 (0.0641) time: 2.9732 data: 0.0075 max mem: 33408 +Epoch: [15] [2010/2639] eta: 0:31:45 lr: 3.1853900128769754e-05 loss: 0.0537 (0.0641) time: 3.0000 data: 0.0073 max mem: 33408 +Epoch: [15] [2020/2639] eta: 0:31:15 lr: 3.184941811791559e-05 loss: 0.0497 (0.0640) time: 3.0310 data: 0.0077 max mem: 33408 +Epoch: [15] [2030/2639] eta: 0:30:44 lr: 3.18449360369791e-05 loss: 0.0497 (0.0641) time: 3.0437 data: 0.0075 max mem: 33408 +Epoch: [15] [2040/2639] eta: 0:30:14 lr: 3.1840453885948215e-05 loss: 0.0614 (0.0641) time: 2.9915 data: 0.0073 max mem: 33408 +Epoch: [15] [2050/2639] eta: 0:29:43 lr: 3.183597166481086e-05 loss: 0.0625 (0.0642) time: 2.9634 data: 0.0074 max mem: 33408 +Epoch: [15] [2060/2639] eta: 0:29:13 lr: 3.183148937355499e-05 loss: 0.0576 (0.0642) time: 3.0255 data: 0.0076 max mem: 33408 +Epoch: [15] [2070/2639] eta: 0:28:43 lr: 3.182700701216855e-05 loss: 0.0571 (0.0641) time: 3.0320 data: 0.0082 max mem: 33408 +Epoch: [15] [2080/2639] eta: 0:28:13 lr: 3.1822524580639426e-05 loss: 0.0540 (0.0641) time: 3.0191 data: 0.0078 max mem: 33408 +Epoch: [15] [2090/2639] eta: 0:27:42 lr: 3.181804207895559e-05 loss: 0.0491 (0.0641) time: 3.0533 data: 0.0072 max mem: 33408 +Epoch: [15] [2100/2639] eta: 0:27:12 lr: 3.181355950710492e-05 loss: 0.0439 (0.0641) time: 3.0362 data: 0.0076 max mem: 33408 +Epoch: [15] [2110/2639] eta: 0:26:42 lr: 3.180907686507536e-05 loss: 0.0609 (0.0642) time: 3.0377 data: 0.0076 max mem: 33408 +Epoch: [15] [2120/2639] eta: 0:26:12 lr: 3.1804594152854814e-05 loss: 0.0658 (0.0641) time: 3.0382 data: 0.0075 max mem: 33408 +Epoch: [15] [2130/2639] eta: 0:25:41 lr: 3.1800111370431195e-05 loss: 0.0590 (0.0641) time: 3.0207 data: 0.0076 max mem: 33408 +Epoch: [15] [2140/2639] eta: 0:25:11 lr: 3.17956285177924e-05 loss: 0.0554 (0.0641) time: 3.0438 data: 0.0075 max mem: 33408 +Epoch: [15] [2150/2639] eta: 0:24:41 lr: 3.179114559492633e-05 loss: 0.0554 (0.0641) time: 3.0432 data: 0.0075 max mem: 33408 +Epoch: [15] [2160/2639] eta: 0:24:11 lr: 3.1786662601820874e-05 loss: 0.0575 (0.0641) time: 3.0806 data: 0.0079 max mem: 33408 +Epoch: [15] [2170/2639] eta: 0:23:40 lr: 3.1782179538463945e-05 loss: 0.0598 (0.0642) time: 3.1025 data: 0.0074 max mem: 33408 +Epoch: [15] [2180/2639] eta: 0:23:10 lr: 3.177769640484342e-05 loss: 0.0598 (0.0641) time: 3.0077 data: 0.0071 max mem: 33408 +Epoch: [15] [2190/2639] eta: 0:22:40 lr: 3.1773213200947174e-05 loss: 0.0514 (0.0642) time: 3.0130 data: 0.0077 max mem: 33408 +Epoch: [15] [2200/2639] eta: 0:22:09 lr: 3.17687299267631e-05 loss: 0.0572 (0.0641) time: 3.0440 data: 0.0077 max mem: 33408 +Epoch: [15] [2210/2639] eta: 0:21:39 lr: 3.176424658227908e-05 loss: 0.0588 (0.0641) time: 3.0256 data: 0.0075 max mem: 33408 +Epoch: [15] [2220/2639] eta: 0:21:09 lr: 3.175976316748296e-05 loss: 0.0539 (0.0641) time: 3.0736 data: 0.0077 max mem: 33408 +Epoch: [15] [2230/2639] eta: 0:20:39 lr: 3.1755279682362634e-05 loss: 0.0512 (0.0641) time: 3.0544 data: 0.0079 max mem: 33408 +Epoch: [15] [2240/2639] eta: 0:20:08 lr: 3.175079612690596e-05 loss: 0.0568 (0.0641) time: 3.0397 data: 0.0078 max mem: 33408 +Epoch: [15] [2250/2639] eta: 0:19:38 lr: 3.17463125011008e-05 loss: 0.0579 (0.0641) time: 3.1078 data: 0.0079 max mem: 33408 +Epoch: [15] [2260/2639] eta: 0:19:08 lr: 3.1741828804934995e-05 loss: 0.0573 (0.0641) time: 3.0293 data: 0.0080 max mem: 33408 +Epoch: [15] [2270/2639] eta: 0:18:38 lr: 3.173734503839642e-05 loss: 0.0519 (0.0640) time: 2.9715 data: 0.0078 max mem: 33408 +Epoch: [15] [2280/2639] eta: 0:18:07 lr: 3.17328612014729e-05 loss: 0.0535 (0.0640) time: 3.0114 data: 0.0079 max mem: 33408 +Epoch: [15] [2290/2639] eta: 0:17:37 lr: 3.1728377294152306e-05 loss: 0.0565 (0.0640) time: 3.0413 data: 0.0078 max mem: 33408 +Epoch: [15] [2300/2639] eta: 0:17:07 lr: 3.1723893316422456e-05 loss: 0.0595 (0.0640) time: 3.0257 data: 0.0074 max mem: 33408 +Epoch: [15] [2310/2639] eta: 0:16:36 lr: 3.171940926827119e-05 loss: 0.0618 (0.0640) time: 2.9829 data: 0.0075 max mem: 33408 +Epoch: [15] [2320/2639] eta: 0:16:06 lr: 3.1714925149686346e-05 loss: 0.0615 (0.0640) time: 2.9932 data: 0.0074 max mem: 33408 +Epoch: [15] [2330/2639] eta: 0:15:36 lr: 3.171044096065576e-05 loss: 0.0581 (0.0641) time: 3.0439 data: 0.0078 max mem: 33408 +Epoch: [15] [2340/2639] eta: 0:15:05 lr: 3.1705956701167244e-05 loss: 0.0581 (0.0640) time: 3.0291 data: 0.0080 max mem: 33408 +Epoch: [15] [2350/2639] eta: 0:14:35 lr: 3.1701472371208616e-05 loss: 0.0542 (0.0640) time: 2.9920 data: 0.0079 max mem: 33408 +Epoch: [15] [2360/2639] eta: 0:14:05 lr: 3.16969879707677e-05 loss: 0.0432 (0.0640) time: 3.0168 data: 0.0080 max mem: 33408 +Epoch: [15] [2370/2639] eta: 0:13:34 lr: 3.169250349983231e-05 loss: 0.0501 (0.0640) time: 3.0438 data: 0.0081 max mem: 33408 +Epoch: [15] [2380/2639] eta: 0:13:04 lr: 3.1688018958390256e-05 loss: 0.0664 (0.0641) time: 3.0424 data: 0.0080 max mem: 33408 +Epoch: [15] [2390/2639] eta: 0:12:34 lr: 3.168353434642932e-05 loss: 0.0669 (0.0641) time: 3.0367 data: 0.0074 max mem: 33408 +Epoch: [15] [2400/2639] eta: 0:12:04 lr: 3.167904966393733e-05 loss: 0.0658 (0.0641) time: 3.0447 data: 0.0073 max mem: 33408 +Epoch: [15] [2410/2639] eta: 0:11:33 lr: 3.167456491090207e-05 loss: 0.0594 (0.0641) time: 3.0369 data: 0.0074 max mem: 33408 +Epoch: [15] [2420/2639] eta: 0:11:03 lr: 3.1670080087311335e-05 loss: 0.0605 (0.0641) time: 3.0325 data: 0.0076 max mem: 33408 +Epoch: [15] [2430/2639] eta: 0:10:33 lr: 3.166559519315291e-05 loss: 0.0635 (0.0641) time: 3.0319 data: 0.0077 max mem: 33408 +Epoch: [15] [2440/2639] eta: 0:10:02 lr: 3.166111022841458e-05 loss: 0.0584 (0.0641) time: 3.0211 data: 0.0075 max mem: 33408 +Epoch: [15] [2450/2639] eta: 0:09:32 lr: 3.165662519308412e-05 loss: 0.0595 (0.0642) time: 2.9941 data: 0.0073 max mem: 33408 +Epoch: [15] [2460/2639] eta: 0:09:02 lr: 3.165214008714932e-05 loss: 0.0632 (0.0642) time: 3.0273 data: 0.0072 max mem: 33408 +Epoch: [15] [2470/2639] eta: 0:08:31 lr: 3.164765491059794e-05 loss: 0.0637 (0.0643) time: 3.0384 data: 0.0072 max mem: 33408 +Epoch: [15] [2480/2639] eta: 0:08:01 lr: 3.1643169663417743e-05 loss: 0.0600 (0.0643) time: 3.0583 data: 0.0076 max mem: 33408 +Epoch: [15] [2490/2639] eta: 0:07:31 lr: 3.1638684345596505e-05 loss: 0.0589 (0.0643) time: 3.0591 data: 0.0082 max mem: 33408 +Epoch: [15] [2500/2639] eta: 0:07:01 lr: 3.163419895712199e-05 loss: 0.0500 (0.0642) time: 3.0354 data: 0.0078 max mem: 33408 +Epoch: [15] [2510/2639] eta: 0:06:30 lr: 3.162971349798194e-05 loss: 0.0549 (0.0642) time: 3.0399 data: 0.0074 max mem: 33408 +Epoch: [15] [2520/2639] eta: 0:06:00 lr: 3.1625227968164104e-05 loss: 0.0573 (0.0643) time: 3.0144 data: 0.0076 max mem: 33408 +Epoch: [15] [2530/2639] eta: 0:05:30 lr: 3.162074236765625e-05 loss: 0.0591 (0.0642) time: 3.0596 data: 0.0078 max mem: 33408 +Epoch: [15] [2540/2639] eta: 0:04:59 lr: 3.161625669644611e-05 loss: 0.0555 (0.0642) time: 3.0233 data: 0.0080 max mem: 33408 +Epoch: [15] [2550/2639] eta: 0:04:29 lr: 3.1611770954521414e-05 loss: 0.0670 (0.0643) time: 2.9428 data: 0.0080 max mem: 33408 +Epoch: [15] [2560/2639] eta: 0:03:59 lr: 3.1607285141869904e-05 loss: 0.0699 (0.0643) time: 2.9963 data: 0.0076 max mem: 33408 +Epoch: [15] [2570/2639] eta: 0:03:29 lr: 3.160279925847932e-05 loss: 0.0660 (0.0644) time: 3.0239 data: 0.0075 max mem: 33408 +Epoch: [15] [2580/2639] eta: 0:02:58 lr: 3.159831330433739e-05 loss: 0.0595 (0.0644) time: 3.0264 data: 0.0073 max mem: 33408 +Epoch: [15] [2590/2639] eta: 0:02:28 lr: 3.159382727943182e-05 loss: 0.0594 (0.0644) time: 3.0027 data: 0.0071 max mem: 33408 +Epoch: [15] [2600/2639] eta: 0:01:58 lr: 3.158934118375034e-05 loss: 0.0637 (0.0644) time: 2.9987 data: 0.0073 max mem: 33408 +Epoch: [15] [2610/2639] eta: 0:01:27 lr: 3.1584855017280665e-05 loss: 0.0638 (0.0645) time: 3.0209 data: 0.0072 max mem: 33408 +Epoch: [15] [2620/2639] eta: 0:00:57 lr: 3.158036878001051e-05 loss: 0.0526 (0.0645) time: 3.0303 data: 0.0073 max mem: 33408 +Epoch: [15] [2630/2639] eta: 0:00:27 lr: 3.157588247192758e-05 loss: 0.0538 (0.0644) time: 3.0334 data: 0.0071 max mem: 33408 +Epoch: [15] Total time: 2:13:14 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 2:28:26 time: 3.4615 data: 3.2947 max mem: 33408 +Test: [ 100/2573] eta: 0:04:37 time: 0.0788 data: 0.0014 max mem: 33408 +Test: [ 200/2573] eta: 0:03:48 time: 0.0797 data: 0.0014 max mem: 33408 +Test: [ 300/2573] eta: 0:03:25 time: 0.0814 data: 0.0016 max mem: 33408 +Test: [ 400/2573] eta: 0:03:10 time: 0.0816 data: 0.0013 max mem: 33408 +Test: [ 500/2573] eta: 0:02:58 time: 0.0810 data: 0.0014 max mem: 33408 +Test: [ 600/2573] eta: 0:02:48 time: 0.0801 data: 0.0015 max mem: 33408 +Test: [ 700/2573] eta: 0:02:39 time: 0.0808 data: 0.0014 max mem: 33408 +Test: [ 800/2573] eta: 0:02:29 time: 0.0835 data: 0.0014 max mem: 33408 +Test: [ 900/2573] eta: 0:02:20 time: 0.0796 data: 0.0014 max mem: 33408 +Test: [1000/2573] eta: 0:02:11 time: 0.0809 data: 0.0015 max mem: 33408 +Test: [1100/2573] eta: 0:02:02 time: 0.0809 data: 0.0014 max mem: 33408 +Test: [1200/2573] eta: 0:01:54 time: 0.0808 data: 0.0015 max mem: 33408 +Test: [1300/2573] eta: 0:01:45 time: 0.0808 data: 0.0014 max mem: 33408 +Test: [1400/2573] eta: 0:01:37 time: 0.0796 data: 0.0015 max mem: 33408 +Test: [1500/2573] eta: 0:01:28 time: 0.0813 data: 0.0012 max mem: 33408 +Test: [1600/2573] eta: 0:01:20 time: 0.0837 data: 0.0014 max mem: 33408 +Test: [1700/2573] eta: 0:01:12 time: 0.0791 data: 0.0015 max mem: 33408 +Test: [1800/2573] eta: 0:01:03 time: 0.0815 data: 0.0014 max mem: 33408 +Test: [1900/2573] eta: 0:00:55 time: 0.0790 data: 0.0015 max mem: 33408 +Test: [2000/2573] eta: 0:00:47 time: 0.0814 data: 0.0015 max mem: 33408 +Test: [2100/2573] eta: 0:00:38 time: 0.0828 data: 0.0015 max mem: 33408 +Test: [2200/2573] eta: 0:00:30 time: 0.0825 data: 0.0013 max mem: 33408 +Test: [2300/2573] eta: 0:00:22 time: 0.0825 data: 0.0015 max mem: 33408 +Test: [2400/2573] eta: 0:00:14 time: 0.0767 data: 0.0015 max mem: 33408 +Test: [2500/2573] eta: 0:00:05 time: 0.0814 data: 0.0015 max mem: 33408 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: Total time: 0:03:32 +Final results: +Mean IoU is 62.21 + + precision@0.5 = 70.22 + precision@0.6 = 64.11 + precision@0.7 = 56.00 + precision@0.8 = 44.30 + precision@0.9 = 20.98 + overall IoU = 59.64 + +Average object IoU 62.20924323097441 +Overall IoU 59.636505126953125 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [16] [ 0/2639] eta: 3:50:34 lr: 3.157184473409784e-05 loss: 0.0504 (0.0504) time: 5.2425 data: 2.2241 max mem: 33408 +Epoch: [16] [ 10/2639] eta: 2:23:07 lr: 3.1567358291436746e-05 loss: 0.0502 (0.0538) time: 3.2666 data: 0.2089 max mem: 33408 +Epoch: [16] [ 20/2639] eta: 2:17:22 lr: 3.156287177792721e-05 loss: 0.0481 (0.0522) time: 3.0424 data: 0.0074 max mem: 33408 +Epoch: [16] [ 30/2639] eta: 2:15:25 lr: 3.1558385193556906e-05 loss: 0.0475 (0.0529) time: 3.0304 data: 0.0075 max mem: 33408 +Epoch: [16] [ 40/2639] eta: 2:13:59 lr: 3.1553898538313525e-05 loss: 0.0477 (0.0535) time: 3.0369 data: 0.0077 max mem: 33408 +Epoch: [16] [ 50/2639] eta: 2:12:55 lr: 3.154941181218476e-05 loss: 0.0501 (0.0525) time: 3.0287 data: 0.0082 max mem: 33408 +Epoch: [16] [ 60/2639] eta: 2:11:58 lr: 3.15449250151583e-05 loss: 0.0506 (0.0549) time: 3.0233 data: 0.0081 max mem: 33408 +Epoch: [16] [ 70/2639] eta: 2:11:10 lr: 3.154043814722178e-05 loss: 0.0555 (0.0542) time: 3.0207 data: 0.0080 max mem: 33408 +Epoch: [16] [ 80/2639] eta: 2:10:55 lr: 3.15359512083629e-05 loss: 0.0572 (0.0555) time: 3.0680 data: 0.0080 max mem: 33408 +Epoch: [16] [ 90/2639] eta: 2:10:16 lr: 3.1531464198569334e-05 loss: 0.0572 (0.0546) time: 3.0765 data: 0.0079 max mem: 33408 +Epoch: [16] [ 100/2639] eta: 2:09:27 lr: 3.152697711782873e-05 loss: 0.0415 (0.0530) time: 3.0159 data: 0.0080 max mem: 33408 +Epoch: [16] [ 110/2639] eta: 2:09:05 lr: 3.152248996612874e-05 loss: 0.0415 (0.0528) time: 3.0439 data: 0.0079 max mem: 33408 +Epoch: [16] [ 120/2639] eta: 2:08:20 lr: 3.1518002743457024e-05 loss: 0.0497 (0.0533) time: 3.0462 data: 0.0081 max mem: 33408 +Epoch: [16] [ 130/2639] eta: 2:07:51 lr: 3.1513515449801244e-05 loss: 0.0526 (0.0533) time: 3.0310 data: 0.0080 max mem: 33408 +Epoch: [16] [ 140/2639] eta: 2:07:09 lr: 3.150902808514903e-05 loss: 0.0566 (0.0547) time: 3.0282 data: 0.0076 max mem: 33408 +Epoch: [16] [ 150/2639] eta: 2:06:32 lr: 3.150454064948804e-05 loss: 0.0586 (0.0554) time: 3.0026 data: 0.0078 max mem: 33408 +Epoch: [16] [ 160/2639] eta: 2:06:00 lr: 3.150005314280589e-05 loss: 0.0533 (0.0555) time: 3.0286 data: 0.0079 max mem: 33408 +Epoch: [16] [ 170/2639] eta: 2:05:29 lr: 3.149556556509024e-05 loss: 0.0535 (0.0561) time: 3.0439 data: 0.0078 max mem: 33408 +Epoch: [16] [ 180/2639] eta: 2:04:51 lr: 3.14910779163287e-05 loss: 0.0533 (0.0560) time: 3.0189 data: 0.0078 max mem: 33408 +Epoch: [16] [ 190/2639] eta: 2:04:11 lr: 3.1486590196508896e-05 loss: 0.0523 (0.0560) time: 2.9820 data: 0.0080 max mem: 33408 +Epoch: [16] [ 200/2639] eta: 2:03:39 lr: 3.1482102405618464e-05 loss: 0.0538 (0.0568) time: 3.0032 data: 0.0080 max mem: 33408 +Epoch: [16] [ 210/2639] eta: 2:02:59 lr: 3.1477614543645e-05 loss: 0.0637 (0.0571) time: 2.9939 data: 0.0082 max mem: 33408 +Epoch: [16] [ 220/2639] eta: 2:02:24 lr: 3.1473126610576144e-05 loss: 0.0516 (0.0569) time: 2.9763 data: 0.0083 max mem: 33408 +Epoch: [16] [ 230/2639] eta: 2:01:47 lr: 3.146863860639949e-05 loss: 0.0459 (0.0568) time: 2.9849 data: 0.0079 max mem: 33408 +Epoch: [16] [ 240/2639] eta: 2:01:12 lr: 3.1464150531102634e-05 loss: 0.0519 (0.0576) time: 2.9776 data: 0.0078 max mem: 33408 +Epoch: [16] [ 250/2639] eta: 2:00:40 lr: 3.1459662384673185e-05 loss: 0.0571 (0.0576) time: 3.0004 data: 0.0084 max mem: 33408 +Epoch: [16] [ 260/2639] eta: 2:00:08 lr: 3.145517416709875e-05 loss: 0.0518 (0.0580) time: 3.0134 data: 0.0085 max mem: 33408 +Epoch: [16] [ 270/2639] eta: 1:59:35 lr: 3.145068587836691e-05 loss: 0.0518 (0.0579) time: 3.0046 data: 0.0082 max mem: 33408 +Epoch: [16] [ 280/2639] eta: 1:59:07 lr: 3.144619751846525e-05 loss: 0.0510 (0.0575) time: 3.0263 data: 0.0080 max mem: 33408 +Epoch: [16] [ 290/2639] eta: 1:58:31 lr: 3.144170908738136e-05 loss: 0.0511 (0.0576) time: 3.0117 data: 0.0079 max mem: 33408 +Epoch: [16] [ 300/2639] eta: 1:58:05 lr: 3.143722058510283e-05 loss: 0.0510 (0.0574) time: 3.0263 data: 0.0080 max mem: 33408 +Epoch: [16] [ 310/2639] eta: 1:57:32 lr: 3.143273201161722e-05 loss: 0.0456 (0.0573) time: 3.0387 data: 0.0079 max mem: 33408 +Epoch: [16] [ 320/2639] eta: 1:57:12 lr: 3.142824336691211e-05 loss: 0.0557 (0.0573) time: 3.0799 data: 0.0078 max mem: 33408 +Epoch: [16] [ 330/2639] eta: 1:56:42 lr: 3.142375465097506e-05 loss: 0.0526 (0.0574) time: 3.1021 data: 0.0080 max mem: 33408 +Epoch: [16] [ 340/2639] eta: 1:56:12 lr: 3.1419265863793646e-05 loss: 0.0530 (0.0574) time: 3.0369 data: 0.0078 max mem: 33408 +Epoch: [16] [ 350/2639] eta: 1:55:39 lr: 3.1414777005355417e-05 loss: 0.0578 (0.0579) time: 3.0114 data: 0.0077 max mem: 33408 +Epoch: [16] [ 360/2639] eta: 1:55:12 lr: 3.141028807564793e-05 loss: 0.0578 (0.0580) time: 3.0345 data: 0.0080 max mem: 33408 +Epoch: [16] [ 370/2639] eta: 1:54:38 lr: 3.140579907465874e-05 loss: 0.0490 (0.0579) time: 3.0328 data: 0.0080 max mem: 33408 +Epoch: [16] [ 380/2639] eta: 1:54:10 lr: 3.140131000237539e-05 loss: 0.0516 (0.0577) time: 3.0233 data: 0.0079 max mem: 33408 +Epoch: [16] [ 390/2639] eta: 1:53:36 lr: 3.139682085878543e-05 loss: 0.0511 (0.0575) time: 3.0174 data: 0.0079 max mem: 33408 +Epoch: [16] [ 400/2639] eta: 1:53:05 lr: 3.13923316438764e-05 loss: 0.0516 (0.0578) time: 2.9944 data: 0.0080 max mem: 33408 +Epoch: [16] [ 410/2639] eta: 1:52:33 lr: 3.138784235763581e-05 loss: 0.0564 (0.0580) time: 3.0100 data: 0.0078 max mem: 33408 +Epoch: [16] [ 420/2639] eta: 1:52:04 lr: 3.138335300005122e-05 loss: 0.0564 (0.0581) time: 3.0293 data: 0.0081 max mem: 33408 +Epoch: [16] [ 430/2639] eta: 1:51:31 lr: 3.1378863571110146e-05 loss: 0.0465 (0.0579) time: 3.0162 data: 0.0086 max mem: 33408 +Epoch: [16] [ 440/2639] eta: 1:51:00 lr: 3.13743740708001e-05 loss: 0.0412 (0.0577) time: 2.9972 data: 0.0081 max mem: 33408 +Epoch: [16] [ 450/2639] eta: 1:50:31 lr: 3.136988449910861e-05 loss: 0.0475 (0.0577) time: 3.0383 data: 0.0077 max mem: 33408 +Epoch: [16] [ 460/2639] eta: 1:49:59 lr: 3.136539485602319e-05 loss: 0.0525 (0.0575) time: 3.0190 data: 0.0082 max mem: 33408 +Epoch: [16] [ 470/2639] eta: 1:49:31 lr: 3.136090514153135e-05 loss: 0.0536 (0.0575) time: 3.0266 data: 0.0081 max mem: 33408 +Epoch: [16] [ 480/2639] eta: 1:48:58 lr: 3.1356415355620594e-05 loss: 0.0536 (0.0573) time: 3.0287 data: 0.0080 max mem: 33408 +Epoch: [16] [ 490/2639] eta: 1:48:28 lr: 3.1351925498278416e-05 loss: 0.0486 (0.0573) time: 3.0082 data: 0.0086 max mem: 33408 +Epoch: [16] [ 500/2639] eta: 1:47:57 lr: 3.134743556949232e-05 loss: 0.0457 (0.0573) time: 3.0253 data: 0.0083 max mem: 33408 +Epoch: [16] [ 510/2639] eta: 1:47:24 lr: 3.134294556924981e-05 loss: 0.0589 (0.0575) time: 2.9920 data: 0.0078 max mem: 33408 +Epoch: [16] [ 520/2639] eta: 1:46:54 lr: 3.133845549753835e-05 loss: 0.0559 (0.0574) time: 2.9978 data: 0.0076 max mem: 33408 +Epoch: [16] [ 530/2639] eta: 1:46:21 lr: 3.133396535434544e-05 loss: 0.0457 (0.0573) time: 2.9846 data: 0.0075 max mem: 33408 +Epoch: [16] [ 540/2639] eta: 1:45:50 lr: 3.132947513965855e-05 loss: 0.0564 (0.0574) time: 2.9782 data: 0.0081 max mem: 33408 +Epoch: [16] [ 550/2639] eta: 1:45:20 lr: 3.132498485346518e-05 loss: 0.0548 (0.0574) time: 3.0282 data: 0.0082 max mem: 33408 +Epoch: [16] [ 560/2639] eta: 1:44:54 lr: 3.132049449575278e-05 loss: 0.0519 (0.0573) time: 3.0895 data: 0.0076 max mem: 33408 +Epoch: [16] [ 570/2639] eta: 1:44:23 lr: 3.131600406650881e-05 loss: 0.0530 (0.0575) time: 3.0674 data: 0.0077 max mem: 33408 +Epoch: [16] [ 580/2639] eta: 1:43:53 lr: 3.131151356572076e-05 loss: 0.0563 (0.0576) time: 3.0248 data: 0.0077 max mem: 33408 +Epoch: [16] [ 590/2639] eta: 1:43:24 lr: 3.1307022993376073e-05 loss: 0.0563 (0.0577) time: 3.0486 data: 0.0078 max mem: 33408 +Epoch: [16] [ 600/2639] eta: 1:42:52 lr: 3.130253234946221e-05 loss: 0.0515 (0.0575) time: 3.0156 data: 0.0080 max mem: 33408 +Epoch: [16] [ 610/2639] eta: 1:42:24 lr: 3.129804163396661e-05 loss: 0.0517 (0.0576) time: 3.0374 data: 0.0081 max mem: 33408 +Epoch: [16] [ 620/2639] eta: 1:41:53 lr: 3.1293550846876725e-05 loss: 0.0533 (0.0575) time: 3.0452 data: 0.0083 max mem: 33408 +Epoch: [16] [ 630/2639] eta: 1:41:23 lr: 3.128905998818001e-05 loss: 0.0496 (0.0575) time: 3.0284 data: 0.0080 max mem: 33408 +Epoch: [16] [ 640/2639] eta: 1:40:51 lr: 3.1284569057863894e-05 loss: 0.0503 (0.0576) time: 3.0167 data: 0.0081 max mem: 33408 +Epoch: [16] [ 650/2639] eta: 1:40:21 lr: 3.128007805591581e-05 loss: 0.0525 (0.0576) time: 2.9947 data: 0.0078 max mem: 33408 +Epoch: [16] [ 660/2639] eta: 1:39:50 lr: 3.127558698232319e-05 loss: 0.0470 (0.0577) time: 3.0070 data: 0.0076 max mem: 33408 +Epoch: [16] [ 670/2639] eta: 1:39:21 lr: 3.127109583707346e-05 loss: 0.0415 (0.0580) time: 3.0381 data: 0.0077 max mem: 33408 +Epoch: [16] [ 680/2639] eta: 1:38:50 lr: 3.1266604620154035e-05 loss: 0.0583 (0.0581) time: 3.0438 data: 0.0076 max mem: 33408 +Epoch: [16] [ 690/2639] eta: 1:38:21 lr: 3.1262113331552334e-05 loss: 0.0596 (0.0581) time: 3.0496 data: 0.0077 max mem: 33408 +Epoch: [16] [ 700/2639] eta: 1:37:51 lr: 3.125762197125578e-05 loss: 0.0543 (0.0581) time: 3.0517 data: 0.0075 max mem: 33408 +Epoch: [16] [ 710/2639] eta: 1:37:21 lr: 3.125313053925177e-05 loss: 0.0586 (0.0582) time: 3.0306 data: 0.0075 max mem: 33408 +Epoch: [16] [ 720/2639] eta: 1:36:50 lr: 3.1248639035527724e-05 loss: 0.0575 (0.0581) time: 3.0191 data: 0.0078 max mem: 33408 +Epoch: [16] [ 730/2639] eta: 1:36:21 lr: 3.1244147460071024e-05 loss: 0.0548 (0.0581) time: 3.0460 data: 0.0079 max mem: 33408 +Epoch: [16] [ 740/2639] eta: 1:35:50 lr: 3.123965581286908e-05 loss: 0.0660 (0.0582) time: 3.0333 data: 0.0075 max mem: 33408 +Epoch: [16] [ 750/2639] eta: 1:35:19 lr: 3.123516409390927e-05 loss: 0.0629 (0.0582) time: 2.9957 data: 0.0073 max mem: 33408 +Epoch: [16] [ 760/2639] eta: 1:34:47 lr: 3.123067230317901e-05 loss: 0.0534 (0.0582) time: 2.9869 data: 0.0074 max mem: 33408 +Epoch: [16] [ 770/2639] eta: 1:34:18 lr: 3.1226180440665646e-05 loss: 0.0608 (0.0583) time: 3.0246 data: 0.0078 max mem: 33408 +Epoch: [16] [ 780/2639] eta: 1:33:46 lr: 3.1221688506356574e-05 loss: 0.0608 (0.0582) time: 3.0249 data: 0.0080 max mem: 33408 +Epoch: [16] [ 790/2639] eta: 1:33:17 lr: 3.121719650023917e-05 loss: 0.0436 (0.0581) time: 3.0005 data: 0.0080 max mem: 33408 +Epoch: [16] [ 800/2639] eta: 1:32:46 lr: 3.1212704422300816e-05 loss: 0.0492 (0.0583) time: 3.0213 data: 0.0076 max mem: 33408 +Epoch: [16] [ 810/2639] eta: 1:32:16 lr: 3.1208212272528856e-05 loss: 0.0647 (0.0584) time: 3.0345 data: 0.0077 max mem: 33408 +Epoch: [16] [ 820/2639] eta: 1:31:45 lr: 3.120372005091067e-05 loss: 0.0647 (0.0584) time: 3.0208 data: 0.0077 max mem: 33408 +Epoch: [16] [ 830/2639] eta: 1:31:17 lr: 3.11992277574336e-05 loss: 0.0483 (0.0584) time: 3.0667 data: 0.0073 max mem: 33408 +Epoch: [16] [ 840/2639] eta: 1:30:49 lr: 3.1194735392085016e-05 loss: 0.0458 (0.0584) time: 3.1425 data: 0.0072 max mem: 33408 +Epoch: [16] [ 850/2639] eta: 1:30:19 lr: 3.119024295485226e-05 loss: 0.0476 (0.0583) time: 3.0682 data: 0.0074 max mem: 33408 +Epoch: [16] [ 860/2639] eta: 1:29:47 lr: 3.1185750445722674e-05 loss: 0.0550 (0.0584) time: 3.0021 data: 0.0076 max mem: 33408 +Epoch: [16] [ 870/2639] eta: 1:29:16 lr: 3.11812578646836e-05 loss: 0.0595 (0.0585) time: 2.9785 data: 0.0077 max mem: 33408 +Epoch: [16] [ 880/2639] eta: 1:28:47 lr: 3.1176765211722384e-05 loss: 0.0582 (0.0585) time: 3.0289 data: 0.0075 max mem: 33408 +Epoch: [16] [ 890/2639] eta: 1:28:18 lr: 3.1172272486826355e-05 loss: 0.0501 (0.0584) time: 3.0816 data: 0.0076 max mem: 33408 +Epoch: [16] [ 900/2639] eta: 1:27:47 lr: 3.1167779689982826e-05 loss: 0.0416 (0.0583) time: 3.0387 data: 0.0075 max mem: 33408 +Epoch: [16] [ 910/2639] eta: 1:27:16 lr: 3.116328682117914e-05 loss: 0.0433 (0.0583) time: 3.0142 data: 0.0072 max mem: 33408 +Epoch: [16] [ 920/2639] eta: 1:26:46 lr: 3.115879388040261e-05 loss: 0.0433 (0.0581) time: 3.0193 data: 0.0075 max mem: 33408 +Epoch: [16] [ 930/2639] eta: 1:26:18 lr: 3.115430086764055e-05 loss: 0.0422 (0.0580) time: 3.0791 data: 0.0074 max mem: 33408 +Epoch: [16] [ 940/2639] eta: 1:25:47 lr: 3.114980778288027e-05 loss: 0.0519 (0.0581) time: 3.0734 data: 0.0072 max mem: 33408 +Epoch: [16] [ 950/2639] eta: 1:25:17 lr: 3.114531462610908e-05 loss: 0.0572 (0.0581) time: 3.0342 data: 0.0075 max mem: 33408 +Epoch: [16] [ 960/2639] eta: 1:24:47 lr: 3.114082139731428e-05 loss: 0.0505 (0.0581) time: 3.0400 data: 0.0076 max mem: 33408 +Epoch: [16] [ 970/2639] eta: 1:24:17 lr: 3.113632809648318e-05 loss: 0.0541 (0.0582) time: 3.0353 data: 0.0077 max mem: 33408 +Epoch: [16] [ 980/2639] eta: 1:23:48 lr: 3.1131834723603054e-05 loss: 0.0623 (0.0582) time: 3.0818 data: 0.0081 max mem: 33408 +Epoch: [16] [ 990/2639] eta: 1:23:17 lr: 3.11273412786612e-05 loss: 0.0596 (0.0584) time: 3.0405 data: 0.0080 max mem: 33408 +Epoch: [16] [1000/2639] eta: 1:22:46 lr: 3.112284776164491e-05 loss: 0.0596 (0.0585) time: 3.0056 data: 0.0078 max mem: 33408 +Epoch: [16] [1010/2639] eta: 1:22:15 lr: 3.111835417254146e-05 loss: 0.0586 (0.0585) time: 3.0138 data: 0.0078 max mem: 33408 +Epoch: [16] [1020/2639] eta: 1:21:46 lr: 3.1113860511338135e-05 loss: 0.0605 (0.0586) time: 3.0333 data: 0.0078 max mem: 33408 +Epoch: [16] [1030/2639] eta: 1:21:15 lr: 3.110936677802219e-05 loss: 0.0610 (0.0587) time: 3.0357 data: 0.0083 max mem: 33408 +Epoch: [16] [1040/2639] eta: 1:20:45 lr: 3.110487297258091e-05 loss: 0.0504 (0.0588) time: 3.0177 data: 0.0083 max mem: 33408 +Epoch: [16] [1050/2639] eta: 1:20:14 lr: 3.110037909500155e-05 loss: 0.0504 (0.0589) time: 3.0067 data: 0.0079 max mem: 33408 +Epoch: [16] [1060/2639] eta: 1:19:44 lr: 3.1095885145271375e-05 loss: 0.0548 (0.0589) time: 3.0084 data: 0.0077 max mem: 33408 +Epoch: [16] [1070/2639] eta: 1:19:14 lr: 3.1091391123377634e-05 loss: 0.0531 (0.0589) time: 3.0489 data: 0.0077 max mem: 33408 +Epoch: [16] [1080/2639] eta: 1:18:43 lr: 3.108689702930758e-05 loss: 0.0578 (0.0590) time: 3.0382 data: 0.0078 max mem: 33408 +Epoch: [16] [1090/2639] eta: 1:18:12 lr: 3.108240286304847e-05 loss: 0.0583 (0.0591) time: 3.0070 data: 0.0075 max mem: 33408 +Epoch: [16] [1100/2639] eta: 1:17:43 lr: 3.107790862458753e-05 loss: 0.0567 (0.0592) time: 3.0328 data: 0.0075 max mem: 33408 +Epoch: [16] [1110/2639] eta: 1:17:11 lr: 3.107341431391201e-05 loss: 0.0525 (0.0591) time: 3.0068 data: 0.0074 max mem: 33408 +Epoch: [16] [1120/2639] eta: 1:16:40 lr: 3.106891993100914e-05 loss: 0.0504 (0.0591) time: 2.9504 data: 0.0076 max mem: 33408 +Epoch: [16] [1130/2639] eta: 1:16:10 lr: 3.106442547586615e-05 loss: 0.0475 (0.0590) time: 2.9948 data: 0.0078 max mem: 33408 +Epoch: [16] [1140/2639] eta: 1:15:40 lr: 3.105993094847027e-05 loss: 0.0474 (0.0589) time: 3.0451 data: 0.0075 max mem: 33408 +Epoch: [16] [1150/2639] eta: 1:15:09 lr: 3.1055436348808716e-05 loss: 0.0624 (0.0590) time: 3.0323 data: 0.0077 max mem: 33408 +Epoch: [16] [1160/2639] eta: 1:14:38 lr: 3.1050941676868694e-05 loss: 0.0558 (0.0590) time: 3.0012 data: 0.0079 max mem: 33408 +Epoch: [16] [1170/2639] eta: 1:14:08 lr: 3.104644693263744e-05 loss: 0.0549 (0.0591) time: 3.0122 data: 0.0079 max mem: 33408 +Epoch: [16] [1180/2639] eta: 1:13:38 lr: 3.104195211610215e-05 loss: 0.0574 (0.0591) time: 3.0235 data: 0.0081 max mem: 33408 +Epoch: [16] [1190/2639] eta: 1:13:07 lr: 3.103745722725002e-05 loss: 0.0551 (0.0592) time: 3.0148 data: 0.0079 max mem: 33408 +Epoch: [16] [1200/2639] eta: 1:12:36 lr: 3.103296226606826e-05 loss: 0.0541 (0.0592) time: 2.9798 data: 0.0079 max mem: 33408 +Epoch: [16] [1210/2639] eta: 1:12:06 lr: 3.1028467232544065e-05 loss: 0.0606 (0.0592) time: 3.0001 data: 0.0078 max mem: 33408 +Epoch: [16] [1220/2639] eta: 1:11:35 lr: 3.1023972126664626e-05 loss: 0.0612 (0.0593) time: 3.0096 data: 0.0076 max mem: 33408 +Epoch: [16] [1230/2639] eta: 1:11:06 lr: 3.1019476948417124e-05 loss: 0.0574 (0.0593) time: 3.0644 data: 0.0077 max mem: 33408 +Epoch: [16] [1240/2639] eta: 1:10:36 lr: 3.101498169778874e-05 loss: 0.0574 (0.0593) time: 3.0822 data: 0.0075 max mem: 33408 +Epoch: [16] [1250/2639] eta: 1:10:06 lr: 3.101048637476665e-05 loss: 0.0528 (0.0594) time: 3.0264 data: 0.0074 max mem: 33408 +Epoch: [16] [1260/2639] eta: 1:09:36 lr: 3.1005990979338044e-05 loss: 0.0509 (0.0594) time: 3.0715 data: 0.0072 max mem: 33408 +Epoch: [16] [1270/2639] eta: 1:09:06 lr: 3.100149551149008e-05 loss: 0.0509 (0.0594) time: 3.0529 data: 0.0073 max mem: 33408 +Epoch: [16] [1280/2639] eta: 1:08:36 lr: 3.0996999971209914e-05 loss: 0.0509 (0.0594) time: 3.0342 data: 0.0076 max mem: 33408 +Epoch: [16] [1290/2639] eta: 1:08:05 lr: 3.099250435848472e-05 loss: 0.0541 (0.0594) time: 3.0311 data: 0.0076 max mem: 33408 +Epoch: [16] [1300/2639] eta: 1:07:35 lr: 3.098800867330165e-05 loss: 0.0599 (0.0595) time: 2.9985 data: 0.0080 max mem: 33408 +Epoch: [16] [1310/2639] eta: 1:07:04 lr: 3.098351291564785e-05 loss: 0.0599 (0.0595) time: 3.0048 data: 0.0082 max mem: 33408 +Epoch: [16] [1320/2639] eta: 1:06:34 lr: 3.097901708551047e-05 loss: 0.0491 (0.0595) time: 3.0216 data: 0.0079 max mem: 33408 +Epoch: [16] [1330/2639] eta: 1:06:04 lr: 3.097452118287667e-05 loss: 0.0491 (0.0594) time: 3.0467 data: 0.0076 max mem: 33408 +Epoch: [16] [1340/2639] eta: 1:05:34 lr: 3.097002520773356e-05 loss: 0.0460 (0.0593) time: 3.0658 data: 0.0072 max mem: 33408 +Epoch: [16] [1350/2639] eta: 1:05:03 lr: 3.0965529160068295e-05 loss: 0.0455 (0.0593) time: 3.0354 data: 0.0074 max mem: 33408 +Epoch: [16] [1360/2639] eta: 1:04:33 lr: 3.096103303986799e-05 loss: 0.0498 (0.0592) time: 3.0187 data: 0.0074 max mem: 33408 +Epoch: [16] [1370/2639] eta: 1:04:02 lr: 3.095653684711979e-05 loss: 0.0534 (0.0593) time: 3.0052 data: 0.0076 max mem: 33408 +Epoch: [16] [1380/2639] eta: 1:03:32 lr: 3.09520405818108e-05 loss: 0.0619 (0.0594) time: 2.9984 data: 0.0075 max mem: 33408 +Epoch: [16] [1390/2639] eta: 1:03:01 lr: 3.0947544243928137e-05 loss: 0.0635 (0.0594) time: 2.9965 data: 0.0073 max mem: 33408 +Epoch: [16] [1400/2639] eta: 1:02:32 lr: 3.094304783345892e-05 loss: 0.0528 (0.0597) time: 3.0437 data: 0.0073 max mem: 33408 +Epoch: [16] [1410/2639] eta: 1:02:01 lr: 3.093855135039026e-05 loss: 0.0462 (0.0598) time: 3.0660 data: 0.0074 max mem: 33408 +Epoch: [16] [1420/2639] eta: 1:01:31 lr: 3.0934054794709256e-05 loss: 0.0556 (0.0598) time: 3.0175 data: 0.0078 max mem: 33408 +Epoch: [16] [1430/2639] eta: 1:01:01 lr: 3.0929558166403e-05 loss: 0.0559 (0.0598) time: 3.0216 data: 0.0080 max mem: 33408 +Epoch: [16] [1440/2639] eta: 1:00:30 lr: 3.0925061465458604e-05 loss: 0.0534 (0.0598) time: 3.0201 data: 0.0081 max mem: 33408 +Epoch: [16] [1450/2639] eta: 1:00:00 lr: 3.0920564691863143e-05 loss: 0.0478 (0.0597) time: 2.9992 data: 0.0077 max mem: 33408 +Epoch: [16] [1460/2639] eta: 0:59:29 lr: 3.091606784560371e-05 loss: 0.0510 (0.0600) time: 2.9885 data: 0.0073 max mem: 33408 +Epoch: [16] [1470/2639] eta: 0:58:59 lr: 3.091157092666739e-05 loss: 0.0531 (0.0600) time: 3.0081 data: 0.0076 max mem: 33408 +Epoch: [16] [1480/2639] eta: 0:58:28 lr: 3.090707393504125e-05 loss: 0.0478 (0.0600) time: 3.0030 data: 0.0078 max mem: 33408 +Epoch: [16] [1490/2639] eta: 0:57:58 lr: 3.0902576870712376e-05 loss: 0.0480 (0.0600) time: 2.9947 data: 0.0074 max mem: 33408 +Epoch: [16] [1500/2639] eta: 0:57:27 lr: 3.0898079733667824e-05 loss: 0.0575 (0.0600) time: 3.0006 data: 0.0074 max mem: 33408 +Epoch: [16] [1510/2639] eta: 0:56:57 lr: 3.089358252389467e-05 loss: 0.0575 (0.0600) time: 3.0310 data: 0.0078 max mem: 33408 +Epoch: [16] [1520/2639] eta: 0:56:28 lr: 3.088908524137997e-05 loss: 0.0527 (0.0600) time: 3.0950 data: 0.0077 max mem: 33408 +Epoch: [16] [1530/2639] eta: 0:55:57 lr: 3.0884587886110775e-05 loss: 0.0571 (0.0601) time: 3.0397 data: 0.0078 max mem: 33408 +Epoch: [16] [1540/2639] eta: 0:55:27 lr: 3.088009045807413e-05 loss: 0.0559 (0.0600) time: 2.9925 data: 0.0080 max mem: 33408 +Epoch: [16] [1550/2639] eta: 0:54:56 lr: 3.087559295725711e-05 loss: 0.0535 (0.0600) time: 3.0064 data: 0.0078 max mem: 33408 +Epoch: [16] [1560/2639] eta: 0:54:26 lr: 3.087109538364673e-05 loss: 0.0586 (0.0601) time: 3.0261 data: 0.0076 max mem: 33408 +Epoch: [16] [1570/2639] eta: 0:53:56 lr: 3.086659773723003e-05 loss: 0.0529 (0.0601) time: 3.0372 data: 0.0076 max mem: 33408 +Epoch: [16] [1580/2639] eta: 0:53:25 lr: 3.086210001799405e-05 loss: 0.0527 (0.0601) time: 3.0025 data: 0.0078 max mem: 33408 +Epoch: [16] [1590/2639] eta: 0:52:55 lr: 3.085760222592583e-05 loss: 0.0541 (0.0600) time: 2.9947 data: 0.0078 max mem: 33408 +Epoch: [16] [1600/2639] eta: 0:52:25 lr: 3.085310436101238e-05 loss: 0.0463 (0.0600) time: 3.0185 data: 0.0078 max mem: 33408 +Epoch: [16] [1610/2639] eta: 0:51:54 lr: 3.0848606423240725e-05 loss: 0.0465 (0.0600) time: 3.0026 data: 0.0078 max mem: 33408 +Epoch: [16] [1620/2639] eta: 0:51:24 lr: 3.0844108412597874e-05 loss: 0.0514 (0.0601) time: 2.9925 data: 0.0076 max mem: 33408 +Epoch: [16] [1630/2639] eta: 0:50:53 lr: 3.0839610329070846e-05 loss: 0.0537 (0.0601) time: 2.9903 data: 0.0078 max mem: 33408 +Epoch: [16] [1640/2639] eta: 0:50:22 lr: 3.0835112172646645e-05 loss: 0.0472 (0.0600) time: 2.9756 data: 0.0077 max mem: 33408 +Epoch: [16] [1650/2639] eta: 0:49:52 lr: 3.0830613943312273e-05 loss: 0.0541 (0.0600) time: 2.9916 data: 0.0076 max mem: 33408 +Epoch: [16] [1660/2639] eta: 0:49:21 lr: 3.082611564105473e-05 loss: 0.0559 (0.0600) time: 2.9843 data: 0.0081 max mem: 33408 +Epoch: [16] [1670/2639] eta: 0:48:51 lr: 3.082161726586101e-05 loss: 0.0540 (0.0600) time: 2.9885 data: 0.0081 max mem: 33408 +Epoch: [16] [1680/2639] eta: 0:48:21 lr: 3.08171188177181e-05 loss: 0.0563 (0.0600) time: 2.9931 data: 0.0083 max mem: 33408 +Epoch: [16] [1690/2639] eta: 0:47:50 lr: 3.0812620296613e-05 loss: 0.0619 (0.0600) time: 2.9899 data: 0.0082 max mem: 33408 +Epoch: [16] [1700/2639] eta: 0:47:20 lr: 3.080812170253266e-05 loss: 0.0480 (0.0600) time: 3.0054 data: 0.0080 max mem: 33408 +Epoch: [16] [1710/2639] eta: 0:46:49 lr: 3.080362303546408e-05 loss: 0.0480 (0.0600) time: 3.0159 data: 0.0081 max mem: 33408 +Epoch: [16] [1720/2639] eta: 0:46:19 lr: 3.079912429539423e-05 loss: 0.0613 (0.0600) time: 3.0023 data: 0.0084 max mem: 33408 +Epoch: [16] [1730/2639] eta: 0:45:49 lr: 3.079462548231007e-05 loss: 0.0613 (0.0601) time: 2.9895 data: 0.0087 max mem: 33408 +Epoch: [16] [1740/2639] eta: 0:45:18 lr: 3.079012659619856e-05 loss: 0.0533 (0.0600) time: 3.0041 data: 0.0086 max mem: 33408 +Epoch: [16] [1750/2639] eta: 0:44:48 lr: 3.078562763704666e-05 loss: 0.0512 (0.0601) time: 3.0161 data: 0.0084 max mem: 33408 +Epoch: [16] [1760/2639] eta: 0:44:18 lr: 3.078112860484133e-05 loss: 0.0509 (0.0600) time: 3.0472 data: 0.0080 max mem: 33408 +Epoch: [16] [1770/2639] eta: 0:43:48 lr: 3.077662949956952e-05 loss: 0.0501 (0.0600) time: 3.0670 data: 0.0080 max mem: 33408 +Epoch: [16] [1780/2639] eta: 0:43:18 lr: 3.077213032121817e-05 loss: 0.0561 (0.0600) time: 3.0266 data: 0.0081 max mem: 33408 +Epoch: [16] [1790/2639] eta: 0:42:47 lr: 3.076763106977421e-05 loss: 0.0585 (0.0600) time: 2.9946 data: 0.0079 max mem: 33408 +Epoch: [16] [1800/2639] eta: 0:42:17 lr: 3.0763131745224596e-05 loss: 0.0561 (0.0602) time: 3.0013 data: 0.0082 max mem: 33408 +Epoch: [16] [1810/2639] eta: 0:41:47 lr: 3.075863234755626e-05 loss: 0.0543 (0.0602) time: 3.0190 data: 0.0083 max mem: 33408 +Epoch: [16] [1820/2639] eta: 0:41:17 lr: 3.075413287675611e-05 loss: 0.0529 (0.0602) time: 3.0844 data: 0.0081 max mem: 33408 +Epoch: [16] [1830/2639] eta: 0:40:47 lr: 3.0749633332811074e-05 loss: 0.0508 (0.0601) time: 3.1204 data: 0.0081 max mem: 33408 +Epoch: [16] [1840/2639] eta: 0:40:17 lr: 3.074513371570808e-05 loss: 0.0408 (0.0600) time: 3.0325 data: 0.0081 max mem: 33408 +Epoch: [16] [1850/2639] eta: 0:39:46 lr: 3.074063402543404e-05 loss: 0.0408 (0.0600) time: 2.9759 data: 0.0078 max mem: 33408 +Epoch: [16] [1860/2639] eta: 0:39:16 lr: 3.073613426197585e-05 loss: 0.0498 (0.0600) time: 3.0114 data: 0.0076 max mem: 33408 +Epoch: [16] [1870/2639] eta: 0:38:46 lr: 3.0731634425320425e-05 loss: 0.0513 (0.0599) time: 3.0486 data: 0.0075 max mem: 33408 +Epoch: [16] [1880/2639] eta: 0:38:15 lr: 3.0727134515454675e-05 loss: 0.0533 (0.0599) time: 3.0279 data: 0.0075 max mem: 33408 +Epoch: [16] [1890/2639] eta: 0:37:45 lr: 3.072263453236548e-05 loss: 0.0523 (0.0599) time: 3.0307 data: 0.0079 max mem: 33408 +Epoch: [16] [1900/2639] eta: 0:37:15 lr: 3.071813447603973e-05 loss: 0.0473 (0.0599) time: 3.0344 data: 0.0083 max mem: 33408 +Epoch: [16] [1910/2639] eta: 0:36:45 lr: 3.071363434646432e-05 loss: 0.0512 (0.0599) time: 3.0473 data: 0.0077 max mem: 33408 +Epoch: [16] [1920/2639] eta: 0:36:15 lr: 3.070913414362614e-05 loss: 0.0553 (0.0599) time: 3.0526 data: 0.0077 max mem: 33408 +Epoch: [16] [1930/2639] eta: 0:35:44 lr: 3.070463386751205e-05 loss: 0.0548 (0.0600) time: 3.0237 data: 0.0081 max mem: 33408 +Epoch: [16] [1940/2639] eta: 0:35:14 lr: 3.070013351810894e-05 loss: 0.0548 (0.0600) time: 2.9898 data: 0.0083 max mem: 33408 +Epoch: [16] [1950/2639] eta: 0:34:44 lr: 3.0695633095403654e-05 loss: 0.0545 (0.0600) time: 3.0262 data: 0.0080 max mem: 33408 +Epoch: [16] [1960/2639] eta: 0:34:14 lr: 3.069113259938308e-05 loss: 0.0514 (0.0600) time: 3.0804 data: 0.0074 max mem: 33408 +Epoch: [16] [1970/2639] eta: 0:33:43 lr: 3.068663203003408e-05 loss: 0.0502 (0.0599) time: 3.0179 data: 0.0076 max mem: 33408 +Epoch: [16] [1980/2639] eta: 0:33:13 lr: 3.06821313873435e-05 loss: 0.0533 (0.0600) time: 3.0060 data: 0.0079 max mem: 33408 +Epoch: [16] [1990/2639] eta: 0:32:43 lr: 3.067763067129818e-05 loss: 0.0623 (0.0601) time: 3.0291 data: 0.0080 max mem: 33408 +Epoch: [16] [2000/2639] eta: 0:32:13 lr: 3.067312988188498e-05 loss: 0.0523 (0.0600) time: 3.0457 data: 0.0079 max mem: 33408 +Epoch: [16] [2010/2639] eta: 0:31:43 lr: 3.0668629019090746e-05 loss: 0.0545 (0.0601) time: 3.0553 data: 0.0080 max mem: 33408 +Epoch: [16] [2020/2639] eta: 0:31:12 lr: 3.0664128082902306e-05 loss: 0.0587 (0.0601) time: 2.9899 data: 0.0079 max mem: 33408 +Epoch: [16] [2030/2639] eta: 0:30:42 lr: 3.0659627073306494e-05 loss: 0.0620 (0.0602) time: 2.9701 data: 0.0080 max mem: 33408 +Epoch: [16] [2040/2639] eta: 0:30:12 lr: 3.065512599029014e-05 loss: 0.0594 (0.0603) time: 3.0187 data: 0.0083 max mem: 33408 +Epoch: [16] [2050/2639] eta: 0:29:41 lr: 3.065062483384007e-05 loss: 0.0553 (0.0602) time: 3.0058 data: 0.0082 max mem: 33408 +Epoch: [16] [2060/2639] eta: 0:29:11 lr: 3.06461236039431e-05 loss: 0.0556 (0.0602) time: 3.0700 data: 0.0084 max mem: 33408 +Epoch: [16] [2070/2639] eta: 0:28:41 lr: 3.064162230058605e-05 loss: 0.0582 (0.0602) time: 3.1111 data: 0.0081 max mem: 33408 +Epoch: [16] [2080/2639] eta: 0:28:11 lr: 3.0637120923755714e-05 loss: 0.0580 (0.0603) time: 3.0209 data: 0.0074 max mem: 33408 +Epoch: [16] [2090/2639] eta: 0:27:41 lr: 3.063261947343892e-05 loss: 0.0501 (0.0602) time: 3.0161 data: 0.0074 max mem: 33408 +Epoch: [16] [2100/2639] eta: 0:27:10 lr: 3.0628117949622466e-05 loss: 0.0435 (0.0602) time: 3.0275 data: 0.0076 max mem: 33408 +Epoch: [16] [2110/2639] eta: 0:26:40 lr: 3.0623616352293125e-05 loss: 0.0524 (0.0602) time: 3.0230 data: 0.0078 max mem: 33408 +Epoch: [16] [2120/2639] eta: 0:26:10 lr: 3.061911468143772e-05 loss: 0.0550 (0.0602) time: 3.0129 data: 0.0078 max mem: 33408 +Epoch: [16] [2130/2639] eta: 0:25:39 lr: 3.061461293704302e-05 loss: 0.0547 (0.0602) time: 2.9988 data: 0.0081 max mem: 33408 +Epoch: [16] [2140/2639] eta: 0:25:09 lr: 3.061011111909581e-05 loss: 0.0547 (0.0602) time: 3.0087 data: 0.0082 max mem: 33408 +Epoch: [16] [2150/2639] eta: 0:24:39 lr: 3.0605609227582874e-05 loss: 0.0516 (0.0602) time: 2.9972 data: 0.0081 max mem: 33408 +Epoch: [16] [2160/2639] eta: 0:24:09 lr: 3.060110726249098e-05 loss: 0.0508 (0.0602) time: 3.0059 data: 0.0080 max mem: 33408 +Epoch: [16] [2170/2639] eta: 0:23:38 lr: 3.05966052238069e-05 loss: 0.0494 (0.0602) time: 3.0059 data: 0.0079 max mem: 33408 +Epoch: [16] [2180/2639] eta: 0:23:08 lr: 3.059210311151741e-05 loss: 0.0413 (0.0601) time: 3.0232 data: 0.0082 max mem: 33408 +Epoch: [16] [2190/2639] eta: 0:22:38 lr: 3.058760092560926e-05 loss: 0.0448 (0.0601) time: 3.0146 data: 0.0079 max mem: 33408 +Epoch: [16] [2200/2639] eta: 0:22:07 lr: 3.05830986660692e-05 loss: 0.0479 (0.0600) time: 2.9818 data: 0.0078 max mem: 33408 +Epoch: [16] [2210/2639] eta: 0:21:37 lr: 3.0578596332883983e-05 loss: 0.0466 (0.0600) time: 2.9926 data: 0.0079 max mem: 33408 +Epoch: [16] [2220/2639] eta: 0:21:07 lr: 3.0574093926040376e-05 loss: 0.0562 (0.0600) time: 3.0475 data: 0.0079 max mem: 33408 +Epoch: [16] [2230/2639] eta: 0:20:37 lr: 3.0569591445525095e-05 loss: 0.0562 (0.0600) time: 3.0890 data: 0.0077 max mem: 33408 +Epoch: [16] [2240/2639] eta: 0:20:06 lr: 3.0565088891324887e-05 loss: 0.0518 (0.0600) time: 3.0380 data: 0.0076 max mem: 33408 +Epoch: [16] [2250/2639] eta: 0:19:36 lr: 3.056058626342649e-05 loss: 0.0537 (0.0601) time: 3.0410 data: 0.0079 max mem: 33408 +Epoch: [16] [2260/2639] eta: 0:19:06 lr: 3.0556083561816636e-05 loss: 0.0537 (0.0601) time: 3.0331 data: 0.0076 max mem: 33408 +Epoch: [16] [2270/2639] eta: 0:18:36 lr: 3.055158078648203e-05 loss: 0.0465 (0.0600) time: 3.0017 data: 0.0075 max mem: 33408 +Epoch: [16] [2280/2639] eta: 0:18:05 lr: 3.0547077937409406e-05 loss: 0.0466 (0.0600) time: 2.9959 data: 0.0073 max mem: 33408 +Epoch: [16] [2290/2639] eta: 0:17:35 lr: 3.054257501458548e-05 loss: 0.0530 (0.0600) time: 3.0470 data: 0.0071 max mem: 33408 +Epoch: [16] [2300/2639] eta: 0:17:05 lr: 3.053807201799696e-05 loss: 0.0508 (0.0600) time: 3.0708 data: 0.0076 max mem: 33408 +Epoch: [16] [2310/2639] eta: 0:16:35 lr: 3.0533568947630545e-05 loss: 0.0509 (0.0600) time: 3.0354 data: 0.0075 max mem: 33408 +Epoch: [16] [2320/2639] eta: 0:16:05 lr: 3.0529065803472946e-05 loss: 0.0502 (0.0600) time: 3.0111 data: 0.0077 max mem: 33408 +Epoch: [16] [2330/2639] eta: 0:15:34 lr: 3.052456258551085e-05 loss: 0.0564 (0.0600) time: 3.0279 data: 0.0080 max mem: 33408 +Epoch: [16] [2340/2639] eta: 0:15:04 lr: 3.052005929373096e-05 loss: 0.0612 (0.0600) time: 3.0315 data: 0.0079 max mem: 33408 +Epoch: [16] [2350/2639] eta: 0:14:34 lr: 3.051555592811996e-05 loss: 0.0591 (0.0601) time: 3.0371 data: 0.0077 max mem: 33408 +Epoch: [16] [2360/2639] eta: 0:14:04 lr: 3.051105248866452e-05 loss: 0.0579 (0.0601) time: 3.0440 data: 0.0076 max mem: 33408 +Epoch: [16] [2370/2639] eta: 0:13:33 lr: 3.050654897535133e-05 loss: 0.0551 (0.0601) time: 3.0146 data: 0.0077 max mem: 33408 +Epoch: [16] [2380/2639] eta: 0:13:03 lr: 3.0502045388167065e-05 loss: 0.0603 (0.0601) time: 3.0328 data: 0.0076 max mem: 33408 +Epoch: [16] [2390/2639] eta: 0:12:33 lr: 3.0497541727098394e-05 loss: 0.0617 (0.0601) time: 3.0103 data: 0.0076 max mem: 33408 +Epoch: [16] [2400/2639] eta: 0:12:03 lr: 3.0493037992131974e-05 loss: 0.0625 (0.0602) time: 3.0087 data: 0.0074 max mem: 33408 +Epoch: [16] [2410/2639] eta: 0:11:32 lr: 3.0488534183254468e-05 loss: 0.0625 (0.0602) time: 2.9908 data: 0.0077 max mem: 33408 +Epoch: [16] [2420/2639] eta: 0:11:02 lr: 3.048403030045253e-05 loss: 0.0508 (0.0602) time: 2.9667 data: 0.0081 max mem: 33408 +Epoch: [16] [2430/2639] eta: 0:10:32 lr: 3.0479526343712827e-05 loss: 0.0533 (0.0602) time: 2.9873 data: 0.0076 max mem: 33408 +Epoch: [16] [2440/2639] eta: 0:10:01 lr: 3.0475022313021983e-05 loss: 0.0604 (0.0603) time: 2.9871 data: 0.0075 max mem: 33408 +Epoch: [16] [2450/2639] eta: 0:09:31 lr: 3.0470518208366644e-05 loss: 0.0570 (0.0603) time: 2.9656 data: 0.0077 max mem: 33408 +Epoch: [16] [2460/2639] eta: 0:09:01 lr: 3.0466014029733453e-05 loss: 0.0539 (0.0603) time: 3.0881 data: 0.0074 max mem: 33408 +Epoch: [16] [2470/2639] eta: 0:08:31 lr: 3.0461509777109043e-05 loss: 0.0525 (0.0602) time: 3.1137 data: 0.0079 max mem: 33408 +Epoch: [16] [2480/2639] eta: 0:08:00 lr: 3.0457005450480043e-05 loss: 0.0501 (0.0603) time: 3.0415 data: 0.0082 max mem: 33408 +Epoch: [16] [2490/2639] eta: 0:07:30 lr: 3.045250104983306e-05 loss: 0.0495 (0.0603) time: 3.0413 data: 0.0077 max mem: 33408 +Epoch: [16] [2500/2639] eta: 0:07:00 lr: 3.0447996575154724e-05 loss: 0.0491 (0.0603) time: 3.0333 data: 0.0076 max mem: 33408 +Epoch: [16] [2510/2639] eta: 0:06:30 lr: 3.044349202643166e-05 loss: 0.0641 (0.0603) time: 3.0142 data: 0.0076 max mem: 33408 +Epoch: [16] [2520/2639] eta: 0:05:59 lr: 3.043898740365046e-05 loss: 0.0580 (0.0603) time: 2.9582 data: 0.0075 max mem: 33408 +Epoch: [16] [2530/2639] eta: 0:05:29 lr: 3.0434482706797727e-05 loss: 0.0530 (0.0603) time: 3.0262 data: 0.0079 max mem: 33408 +Epoch: [16] [2540/2639] eta: 0:04:59 lr: 3.0429977935860078e-05 loss: 0.0468 (0.0602) time: 3.0654 data: 0.0078 max mem: 33408 +Epoch: [16] [2550/2639] eta: 0:04:29 lr: 3.04254730908241e-05 loss: 0.0468 (0.0602) time: 3.0169 data: 0.0074 max mem: 33408 +Epoch: [16] [2560/2639] eta: 0:03:58 lr: 3.042096817167637e-05 loss: 0.0486 (0.0602) time: 3.0232 data: 0.0075 max mem: 33408 +Epoch: [16] [2570/2639] eta: 0:03:28 lr: 3.0416463178403497e-05 loss: 0.0569 (0.0603) time: 3.0173 data: 0.0075 max mem: 33408 +Epoch: [16] [2580/2639] eta: 0:02:58 lr: 3.0411958110992044e-05 loss: 0.0593 (0.0603) time: 3.0102 data: 0.0073 max mem: 33408 +Epoch: [16] [2590/2639] eta: 0:02:28 lr: 3.04074529694286e-05 loss: 0.0632 (0.0604) time: 3.0077 data: 0.0076 max mem: 33408 +Epoch: [16] [2600/2639] eta: 0:01:57 lr: 3.0402947753699734e-05 loss: 0.0544 (0.0603) time: 3.0220 data: 0.0078 max mem: 33408 +Epoch: [16] [2610/2639] eta: 0:01:27 lr: 3.0398442463792004e-05 loss: 0.0488 (0.0603) time: 3.0355 data: 0.0075 max mem: 33408 +Epoch: [16] [2620/2639] eta: 0:00:57 lr: 3.039393709969198e-05 loss: 0.0495 (0.0603) time: 3.0388 data: 0.0074 max mem: 33408 +Epoch: [16] [2630/2639] eta: 0:00:27 lr: 3.038943166138623e-05 loss: 0.0531 (0.0603) time: 3.0697 data: 0.0073 max mem: 33408 +Epoch: [16] Total time: 2:13:03 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 2:11:04 time: 3.0564 data: 2.9427 max mem: 33408 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 100/2573] eta: 0:04:28 time: 0.0801 data: 0.0014 max mem: 33408 +Test: [ 200/2573] eta: 0:03:45 time: 0.0798 data: 0.0015 max mem: 33408 +Test: [ 300/2573] eta: 0:03:24 time: 0.0825 data: 0.0015 max mem: 33408 +Test: [ 400/2573] eta: 0:03:09 time: 0.0808 data: 0.0013 max mem: 33408 +Test: [ 500/2573] eta: 0:02:57 time: 0.0808 data: 0.0015 max mem: 33408 +Test: [ 600/2573] eta: 0:02:47 time: 0.0804 data: 0.0014 max mem: 33408 +Test: [ 700/2573] eta: 0:02:38 time: 0.0811 data: 0.0015 max mem: 33408 +Test: [ 800/2573] eta: 0:02:29 time: 0.0833 data: 0.0015 max mem: 33408 +Test: [ 900/2573] eta: 0:02:20 time: 0.0801 data: 0.0014 max mem: 33408 +Test: [1000/2573] eta: 0:02:11 time: 0.0804 data: 0.0014 max mem: 33408 +Test: [1100/2573] eta: 0:02:02 time: 0.0802 data: 0.0013 max mem: 33408 +Test: [1200/2573] eta: 0:01:54 time: 0.0799 data: 0.0013 max mem: 33408 +Test: [1300/2573] eta: 0:01:45 time: 0.0806 data: 0.0013 max mem: 33408 +Test: [1400/2573] eta: 0:01:37 time: 0.0812 data: 0.0015 max mem: 33408 +Test: [1500/2573] eta: 0:01:28 time: 0.0801 data: 0.0014 max mem: 33408 +Test: [1600/2573] eta: 0:01:20 time: 0.0830 data: 0.0014 max mem: 33408 +Test: [1700/2573] eta: 0:01:11 time: 0.0805 data: 0.0014 max mem: 33408 +Test: [1800/2573] eta: 0:01:03 time: 0.0824 data: 0.0015 max mem: 33408 +Test: [1900/2573] eta: 0:00:55 time: 0.0783 data: 0.0015 max mem: 33408 +Test: [2000/2573] eta: 0:00:47 time: 0.0807 data: 0.0015 max mem: 33408 +Test: [2100/2573] eta: 0:00:38 time: 0.0821 data: 0.0015 max mem: 33408 +Test: [2200/2573] eta: 0:00:30 time: 0.0820 data: 0.0014 max mem: 33408 +Test: [2300/2573] eta: 0:00:22 time: 0.0816 data: 0.0014 max mem: 33408 +Test: [2400/2573] eta: 0:00:14 time: 0.0778 data: 0.0015 max mem: 33408 +Test: [2500/2573] eta: 0:00:05 time: 0.0798 data: 0.0014 max mem: 33408 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: Total time: 0:03:31 +Final results: +Mean IoU is 62.43 + + precision@0.5 = 70.22 + precision@0.6 = 64.83 + precision@0.7 = 57.70 + precision@0.8 = 45.73 + precision@0.9 = 21.73 + overall IoU = 60.24 + +Average object IoU 62.43181174537196 +Overall IoU 60.243900299072266 +Better epoch: 16 + +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [17] [ 0/2639] eta: 4:00:05 lr: 3.038537670345404e-05 loss: 0.0352 (0.0352) time: 5.4587 data: 2.3299 max mem: 33408 +Epoch: [17] [ 10/2639] eta: 2:19:34 lr: 3.0380871124120335e-05 loss: 0.0507 (0.0498) time: 3.1856 data: 0.2185 max mem: 33408 +Epoch: [17] [ 20/2639] eta: 2:17:34 lr: 3.037636547054189e-05 loss: 0.0491 (0.0533) time: 3.0363 data: 0.0071 max mem: 33408 +Epoch: [17] [ 30/2639] eta: 2:15:52 lr: 3.037185974270525e-05 loss: 0.0491 (0.0569) time: 3.0914 data: 0.0076 max mem: 33408 +Epoch: [17] [ 40/2639] eta: 2:13:32 lr: 3.0367353940596933e-05 loss: 0.0460 (0.0538) time: 3.0107 data: 0.0081 max mem: 33408 +Epoch: [17] [ 50/2639] eta: 2:12:13 lr: 3.0362848064203476e-05 loss: 0.0471 (0.0567) time: 2.9709 data: 0.0082 max mem: 33408 +Epoch: [17] [ 60/2639] eta: 2:11:29 lr: 3.0358342113511412e-05 loss: 0.0525 (0.0554) time: 3.0100 data: 0.0085 max mem: 33408 +Epoch: [17] [ 70/2639] eta: 2:10:34 lr: 3.0353836088507265e-05 loss: 0.0504 (0.0552) time: 3.0113 data: 0.0085 max mem: 33408 +Epoch: [17] [ 80/2639] eta: 2:09:44 lr: 3.0349329989177538e-05 loss: 0.0474 (0.0550) time: 2.9907 data: 0.0080 max mem: 33408 +Epoch: [17] [ 90/2639] eta: 2:09:03 lr: 3.034482381550875e-05 loss: 0.0495 (0.0546) time: 2.9971 data: 0.0076 max mem: 33408 +Epoch: [17] [ 100/2639] eta: 2:08:30 lr: 3.0340317567487407e-05 loss: 0.0505 (0.0541) time: 3.0155 data: 0.0078 max mem: 33408 +Epoch: [17] [ 110/2639] eta: 2:07:56 lr: 3.033581124510002e-05 loss: 0.0505 (0.0554) time: 3.0231 data: 0.0077 max mem: 33408 +Epoch: [17] [ 120/2639] eta: 2:07:27 lr: 3.033130484833308e-05 loss: 0.0501 (0.0547) time: 3.0319 data: 0.0079 max mem: 33408 +Epoch: [17] [ 130/2639] eta: 2:07:02 lr: 3.0326798377173072e-05 loss: 0.0505 (0.0570) time: 3.0535 data: 0.0083 max mem: 33408 +Epoch: [17] [ 140/2639] eta: 2:06:31 lr: 3.0322291831606497e-05 loss: 0.0556 (0.0569) time: 3.0481 data: 0.0080 max mem: 33408 +Epoch: [17] [ 150/2639] eta: 2:06:06 lr: 3.0317785211619837e-05 loss: 0.0582 (0.0575) time: 3.0520 data: 0.0080 max mem: 33408 +Epoch: [17] [ 160/2639] eta: 2:05:29 lr: 3.031327851719957e-05 loss: 0.0517 (0.0571) time: 3.0332 data: 0.0080 max mem: 33408 +Epoch: [17] [ 170/2639] eta: 2:05:09 lr: 3.0308771748332166e-05 loss: 0.0516 (0.0577) time: 3.0547 data: 0.0082 max mem: 33408 +Epoch: [17] [ 180/2639] eta: 2:04:31 lr: 3.0304264905004098e-05 loss: 0.0567 (0.0574) time: 3.0486 data: 0.0087 max mem: 33408 +Epoch: [17] [ 190/2639] eta: 2:04:05 lr: 3.0299757987201833e-05 loss: 0.0517 (0.0575) time: 3.0262 data: 0.0085 max mem: 33408 +Epoch: [17] [ 200/2639] eta: 2:03:38 lr: 3.0295250994911833e-05 loss: 0.0563 (0.0574) time: 3.0692 data: 0.0077 max mem: 33408 +Epoch: [17] [ 210/2639] eta: 2:02:59 lr: 3.0290743928120545e-05 loss: 0.0497 (0.0568) time: 3.0215 data: 0.0075 max mem: 33408 +Epoch: [17] [ 220/2639] eta: 2:02:35 lr: 3.0286236786814427e-05 loss: 0.0497 (0.0569) time: 3.0311 data: 0.0076 max mem: 33408 +Epoch: [17] [ 230/2639] eta: 2:01:58 lr: 3.0281729570979927e-05 loss: 0.0486 (0.0563) time: 3.0347 data: 0.0077 max mem: 33408 +Epoch: [17] [ 240/2639] eta: 2:01:28 lr: 3.027722228060349e-05 loss: 0.0450 (0.0560) time: 3.0136 data: 0.0081 max mem: 33408 +Epoch: [17] [ 250/2639] eta: 2:00:50 lr: 3.0272714915671534e-05 loss: 0.0464 (0.0560) time: 3.0019 data: 0.0084 max mem: 33408 +Epoch: [17] [ 260/2639] eta: 2:00:17 lr: 3.0268207476170513e-05 loss: 0.0464 (0.0563) time: 2.9791 data: 0.0078 max mem: 33408 +Epoch: [17] [ 270/2639] eta: 1:59:43 lr: 3.0263699962086846e-05 loss: 0.0510 (0.0561) time: 2.9953 data: 0.0080 max mem: 33408 +Epoch: [17] [ 280/2639] eta: 1:59:15 lr: 3.025919237340695e-05 loss: 0.0510 (0.0561) time: 3.0264 data: 0.0082 max mem: 33408 +Epoch: [17] [ 290/2639] eta: 1:58:43 lr: 3.0254684710117247e-05 loss: 0.0562 (0.0562) time: 3.0362 data: 0.0081 max mem: 33408 +Epoch: [17] [ 300/2639] eta: 1:58:13 lr: 3.0250176972204157e-05 loss: 0.0523 (0.0562) time: 3.0242 data: 0.0081 max mem: 33408 +Epoch: [17] [ 310/2639] eta: 1:57:41 lr: 3.024566915965408e-05 loss: 0.0485 (0.0561) time: 3.0223 data: 0.0077 max mem: 33408 +Epoch: [17] [ 320/2639] eta: 1:57:08 lr: 3.0241161272453427e-05 loss: 0.0448 (0.0566) time: 3.0056 data: 0.0074 max mem: 33408 +Epoch: [17] [ 330/2639] eta: 1:56:37 lr: 3.0236653310588597e-05 loss: 0.0490 (0.0566) time: 3.0127 data: 0.0075 max mem: 33408 +Epoch: [17] [ 340/2639] eta: 1:56:11 lr: 3.0232145274045975e-05 loss: 0.0492 (0.0566) time: 3.0533 data: 0.0078 max mem: 33408 +Epoch: [17] [ 350/2639] eta: 1:55:39 lr: 3.0227637162811956e-05 loss: 0.0472 (0.0563) time: 3.0503 data: 0.0079 max mem: 33408 +Epoch: [17] [ 360/2639] eta: 1:55:10 lr: 3.022312897687293e-05 loss: 0.0481 (0.0562) time: 3.0297 data: 0.0077 max mem: 33408 +Epoch: [17] [ 370/2639] eta: 1:54:41 lr: 3.0218620716215275e-05 loss: 0.0468 (0.0560) time: 3.0509 data: 0.0081 max mem: 33408 +Epoch: [17] [ 380/2639] eta: 1:54:10 lr: 3.0214112380825355e-05 loss: 0.0468 (0.0561) time: 3.0390 data: 0.0088 max mem: 33408 +Epoch: [17] [ 390/2639] eta: 1:53:37 lr: 3.0209603970689554e-05 loss: 0.0515 (0.0561) time: 3.0057 data: 0.0084 max mem: 33408 +Epoch: [17] [ 400/2639] eta: 1:53:03 lr: 3.020509548579424e-05 loss: 0.0564 (0.0562) time: 2.9747 data: 0.0078 max mem: 33408 +Epoch: [17] [ 410/2639] eta: 1:52:27 lr: 3.020058692612577e-05 loss: 0.0548 (0.0564) time: 2.9452 data: 0.0078 max mem: 33408 +Epoch: [17] [ 420/2639] eta: 1:51:58 lr: 3.0196078291670486e-05 loss: 0.0548 (0.0564) time: 2.9889 data: 0.0077 max mem: 33408 +Epoch: [17] [ 430/2639] eta: 1:51:23 lr: 3.0191569582414765e-05 loss: 0.0540 (0.0564) time: 2.9899 data: 0.0078 max mem: 33408 +Epoch: [17] [ 440/2639] eta: 1:50:55 lr: 3.0187060798344936e-05 loss: 0.0475 (0.0564) time: 2.9998 data: 0.0080 max mem: 33408 +Epoch: [17] [ 450/2639] eta: 1:50:27 lr: 3.0182551939447353e-05 loss: 0.0484 (0.0564) time: 3.0694 data: 0.0082 max mem: 33408 +Epoch: [17] [ 460/2639] eta: 1:49:56 lr: 3.017804300570834e-05 loss: 0.0496 (0.0563) time: 3.0515 data: 0.0083 max mem: 33408 +Epoch: [17] [ 470/2639] eta: 1:49:26 lr: 3.0173533997114235e-05 loss: 0.0496 (0.0562) time: 3.0315 data: 0.0085 max mem: 33408 +Epoch: [17] [ 480/2639] eta: 1:48:55 lr: 3.0169024913651378e-05 loss: 0.0432 (0.0561) time: 3.0218 data: 0.0089 max mem: 33408 +Epoch: [17] [ 490/2639] eta: 1:48:25 lr: 3.016451575530608e-05 loss: 0.0403 (0.0560) time: 3.0215 data: 0.0085 max mem: 33408 +Epoch: [17] [ 500/2639] eta: 1:47:55 lr: 3.0160006522064653e-05 loss: 0.0509 (0.0560) time: 3.0242 data: 0.0079 max mem: 33408 +Epoch: [17] [ 510/2639] eta: 1:47:24 lr: 3.0155497213913425e-05 loss: 0.0459 (0.0560) time: 3.0155 data: 0.0078 max mem: 33408 +Epoch: [17] [ 520/2639] eta: 1:46:54 lr: 3.0150987830838705e-05 loss: 0.0432 (0.0560) time: 3.0323 data: 0.0083 max mem: 33408 +Epoch: [17] [ 530/2639] eta: 1:46:22 lr: 3.0146478372826786e-05 loss: 0.0430 (0.0560) time: 3.0171 data: 0.0084 max mem: 33408 +Epoch: [17] [ 540/2639] eta: 1:45:52 lr: 3.014196883986397e-05 loss: 0.0494 (0.0561) time: 2.9991 data: 0.0085 max mem: 33408 +Epoch: [17] [ 550/2639] eta: 1:45:22 lr: 3.013745923193656e-05 loss: 0.0540 (0.0562) time: 3.0246 data: 0.0084 max mem: 33408 +Epoch: [17] [ 560/2639] eta: 1:44:50 lr: 3.013294954903083e-05 loss: 0.0545 (0.0563) time: 3.0091 data: 0.0084 max mem: 33408 +Epoch: [17] [ 570/2639] eta: 1:44:20 lr: 3.012843979113309e-05 loss: 0.0495 (0.0563) time: 3.0064 data: 0.0086 max mem: 33408 +Epoch: [17] [ 580/2639] eta: 1:43:49 lr: 3.0123929958229597e-05 loss: 0.0519 (0.0565) time: 3.0184 data: 0.0081 max mem: 33408 +Epoch: [17] [ 590/2639] eta: 1:43:21 lr: 3.0119420050306628e-05 loss: 0.0494 (0.0565) time: 3.0446 data: 0.0083 max mem: 33408 +Epoch: [17] [ 600/2639] eta: 1:42:49 lr: 3.0114910067350465e-05 loss: 0.0490 (0.0566) time: 3.0377 data: 0.0087 max mem: 33408 +Epoch: [17] [ 610/2639] eta: 1:42:20 lr: 3.0110400009347377e-05 loss: 0.0525 (0.0567) time: 3.0195 data: 0.0082 max mem: 33408 +Epoch: [17] [ 620/2639] eta: 1:41:51 lr: 3.010588987628361e-05 loss: 0.0438 (0.0566) time: 3.0578 data: 0.0081 max mem: 33408 +Epoch: [17] [ 630/2639] eta: 1:41:20 lr: 3.0101379668145425e-05 loss: 0.0428 (0.0564) time: 3.0467 data: 0.0084 max mem: 33408 +Epoch: [17] [ 640/2639] eta: 1:40:50 lr: 3.0096869384919074e-05 loss: 0.0477 (0.0567) time: 3.0238 data: 0.0079 max mem: 33408 +Epoch: [17] [ 650/2639] eta: 1:40:19 lr: 3.0092359026590812e-05 loss: 0.0541 (0.0567) time: 3.0186 data: 0.0076 max mem: 33408 +Epoch: [17] [ 660/2639] eta: 1:39:49 lr: 3.008784859314687e-05 loss: 0.0500 (0.0566) time: 3.0206 data: 0.0079 max mem: 33408 +Epoch: [17] [ 670/2639] eta: 1:39:20 lr: 3.0083338084573486e-05 loss: 0.0453 (0.0565) time: 3.0518 data: 0.0080 max mem: 33408 +Epoch: [17] [ 680/2639] eta: 1:38:49 lr: 3.0078827500856892e-05 loss: 0.0452 (0.0563) time: 3.0290 data: 0.0077 max mem: 33408 +Epoch: [17] [ 690/2639] eta: 1:38:20 lr: 3.007431684198333e-05 loss: 0.0409 (0.0562) time: 3.0378 data: 0.0075 max mem: 33408 +Epoch: [17] [ 700/2639] eta: 1:37:50 lr: 3.0069806107939002e-05 loss: 0.0515 (0.0562) time: 3.0625 data: 0.0075 max mem: 33408 +Epoch: [17] [ 710/2639] eta: 1:37:23 lr: 3.0065295298710134e-05 loss: 0.0515 (0.0561) time: 3.0844 data: 0.0077 max mem: 33408 +Epoch: [17] [ 720/2639] eta: 1:36:51 lr: 3.006078441428294e-05 loss: 0.0439 (0.0560) time: 3.0472 data: 0.0077 max mem: 33408 +Epoch: [17] [ 730/2639] eta: 1:36:22 lr: 3.0056273454643625e-05 loss: 0.0432 (0.0559) time: 3.0183 data: 0.0077 max mem: 33408 +Epoch: [17] [ 740/2639] eta: 1:35:50 lr: 3.00517624197784e-05 loss: 0.0414 (0.0558) time: 3.0297 data: 0.0078 max mem: 33408 +Epoch: [17] [ 750/2639] eta: 1:35:19 lr: 3.0047251309673452e-05 loss: 0.0475 (0.0557) time: 2.9794 data: 0.0078 max mem: 33408 +Epoch: [17] [ 760/2639] eta: 1:34:49 lr: 3.004274012431498e-05 loss: 0.0510 (0.0557) time: 3.0070 data: 0.0081 max mem: 33408 +Epoch: [17] [ 770/2639] eta: 1:34:20 lr: 3.0038228863689172e-05 loss: 0.0559 (0.0558) time: 3.0716 data: 0.0086 max mem: 33408 +Epoch: [17] [ 780/2639] eta: 1:33:51 lr: 3.0033717527782218e-05 loss: 0.0491 (0.0557) time: 3.0813 data: 0.0083 max mem: 33408 +Epoch: [17] [ 790/2639] eta: 1:33:20 lr: 3.0029206116580282e-05 loss: 0.0453 (0.0556) time: 3.0373 data: 0.0078 max mem: 33408 +Epoch: [17] [ 800/2639] eta: 1:32:51 lr: 3.0024694630069548e-05 loss: 0.0465 (0.0557) time: 3.0493 data: 0.0080 max mem: 33408 +Epoch: [17] [ 810/2639] eta: 1:32:21 lr: 3.002018306823619e-05 loss: 0.0472 (0.0556) time: 3.0606 data: 0.0084 max mem: 33408 +Epoch: [17] [ 820/2639] eta: 1:31:52 lr: 3.001567143106637e-05 loss: 0.0483 (0.0557) time: 3.0610 data: 0.0085 max mem: 33408 +Epoch: [17] [ 830/2639] eta: 1:31:20 lr: 3.0011159718546244e-05 loss: 0.0508 (0.0557) time: 3.0123 data: 0.0089 max mem: 33408 +Epoch: [17] [ 840/2639] eta: 1:30:49 lr: 3.0006647930661967e-05 loss: 0.0545 (0.0556) time: 2.9835 data: 0.0087 max mem: 33408 +Epoch: [17] [ 850/2639] eta: 1:30:19 lr: 3.0002136067399683e-05 loss: 0.0434 (0.0557) time: 3.0314 data: 0.0080 max mem: 33408 +Epoch: [17] [ 860/2639] eta: 1:29:49 lr: 2.9997624128745557e-05 loss: 0.0519 (0.0557) time: 3.0524 data: 0.0078 max mem: 33408 +Epoch: [17] [ 870/2639] eta: 1:29:19 lr: 2.9993112114685705e-05 loss: 0.0523 (0.0557) time: 3.0389 data: 0.0078 max mem: 33408 +Epoch: [17] [ 880/2639] eta: 1:28:49 lr: 2.9988600025206277e-05 loss: 0.0493 (0.0557) time: 3.0380 data: 0.0077 max mem: 33408 +Epoch: [17] [ 890/2639] eta: 1:28:18 lr: 2.998408786029339e-05 loss: 0.0486 (0.0557) time: 3.0171 data: 0.0079 max mem: 33408 +Epoch: [17] [ 900/2639] eta: 1:27:47 lr: 2.9979575619933194e-05 loss: 0.0486 (0.0556) time: 2.9938 data: 0.0079 max mem: 33408 +Epoch: [17] [ 910/2639] eta: 1:27:16 lr: 2.997506330411179e-05 loss: 0.0420 (0.0556) time: 3.0047 data: 0.0077 max mem: 33408 +Epoch: [17] [ 920/2639] eta: 1:26:46 lr: 2.9970550912815292e-05 loss: 0.0503 (0.0555) time: 3.0065 data: 0.0079 max mem: 33408 +Epoch: [17] [ 930/2639] eta: 1:26:15 lr: 2.996603844602982e-05 loss: 0.0503 (0.0555) time: 3.0081 data: 0.0080 max mem: 33408 +Epoch: [17] [ 940/2639] eta: 1:25:46 lr: 2.9961525903741484e-05 loss: 0.0502 (0.0556) time: 3.0446 data: 0.0079 max mem: 33408 +Epoch: [17] [ 950/2639] eta: 1:25:14 lr: 2.9957013285936375e-05 loss: 0.0523 (0.0556) time: 3.0291 data: 0.0076 max mem: 33408 +Epoch: [17] [ 960/2639] eta: 1:24:44 lr: 2.9952500592600592e-05 loss: 0.0520 (0.0557) time: 3.0061 data: 0.0077 max mem: 33408 +Epoch: [17] [ 970/2639] eta: 1:24:14 lr: 2.9947987823720225e-05 loss: 0.0432 (0.0556) time: 3.0305 data: 0.0078 max mem: 33408 +Epoch: [17] [ 980/2639] eta: 1:23:44 lr: 2.9943474979281368e-05 loss: 0.0532 (0.0556) time: 3.0368 data: 0.0080 max mem: 33408 +Epoch: [17] [ 990/2639] eta: 1:23:14 lr: 2.99389620592701e-05 loss: 0.0532 (0.0555) time: 3.0461 data: 0.0076 max mem: 33408 +Epoch: [17] [1000/2639] eta: 1:22:44 lr: 2.9934449063672483e-05 loss: 0.0469 (0.0555) time: 3.0294 data: 0.0077 max mem: 33408 +Epoch: [17] [1010/2639] eta: 1:22:14 lr: 2.9929935992474605e-05 loss: 0.0482 (0.0555) time: 3.0360 data: 0.0078 max mem: 33408 +Epoch: [17] [1020/2639] eta: 1:21:43 lr: 2.9925422845662533e-05 loss: 0.0464 (0.0554) time: 3.0352 data: 0.0077 max mem: 33408 +Epoch: [17] [1030/2639] eta: 1:21:13 lr: 2.9920909623222327e-05 loss: 0.0495 (0.0555) time: 3.0151 data: 0.0076 max mem: 33408 +Epoch: [17] [1040/2639] eta: 1:20:43 lr: 2.991639632514004e-05 loss: 0.0507 (0.0556) time: 3.0269 data: 0.0076 max mem: 33408 +Epoch: [17] [1050/2639] eta: 1:20:13 lr: 2.991188295140172e-05 loss: 0.0534 (0.0557) time: 3.0712 data: 0.0075 max mem: 33408 +Epoch: [17] [1060/2639] eta: 1:19:43 lr: 2.9907369501993422e-05 loss: 0.0553 (0.0557) time: 3.0584 data: 0.0075 max mem: 33408 +Epoch: [17] [1070/2639] eta: 1:19:12 lr: 2.9902855976901196e-05 loss: 0.0542 (0.0557) time: 3.0225 data: 0.0078 max mem: 33408 +Epoch: [17] [1080/2639] eta: 1:18:42 lr: 2.9898342376111065e-05 loss: 0.0542 (0.0558) time: 3.0064 data: 0.0078 max mem: 33408 +Epoch: [17] [1090/2639] eta: 1:18:11 lr: 2.989382869960906e-05 loss: 0.0456 (0.0558) time: 3.0106 data: 0.0076 max mem: 33408 +Epoch: [17] [1100/2639] eta: 1:17:41 lr: 2.9889314947381225e-05 loss: 0.0455 (0.0557) time: 3.0115 data: 0.0076 max mem: 33408 +Epoch: [17] [1110/2639] eta: 1:17:10 lr: 2.9884801119413568e-05 loss: 0.0507 (0.0558) time: 3.0161 data: 0.0080 max mem: 33408 +Epoch: [17] [1120/2639] eta: 1:16:39 lr: 2.9880287215692122e-05 loss: 0.0518 (0.0557) time: 2.9843 data: 0.0079 max mem: 33408 +Epoch: [17] [1130/2639] eta: 1:16:07 lr: 2.9875773236202875e-05 loss: 0.0518 (0.0557) time: 2.9392 data: 0.0078 max mem: 33408 +Epoch: [17] [1140/2639] eta: 1:15:38 lr: 2.987125918093186e-05 loss: 0.0525 (0.0558) time: 3.0093 data: 0.0078 max mem: 33408 +Epoch: [17] [1150/2639] eta: 1:15:07 lr: 2.986674504986507e-05 loss: 0.0507 (0.0558) time: 3.0256 data: 0.0077 max mem: 33408 +Epoch: [17] [1160/2639] eta: 1:14:37 lr: 2.98622308429885e-05 loss: 0.0461 (0.0558) time: 3.0279 data: 0.0076 max mem: 33408 +Epoch: [17] [1170/2639] eta: 1:14:07 lr: 2.985771656028814e-05 loss: 0.0465 (0.0558) time: 3.0423 data: 0.0074 max mem: 33408 +Epoch: [17] [1180/2639] eta: 1:13:37 lr: 2.985320220174999e-05 loss: 0.0507 (0.0558) time: 3.0471 data: 0.0075 max mem: 33408 +Epoch: [17] [1190/2639] eta: 1:13:06 lr: 2.9848687767360028e-05 loss: 0.0473 (0.0558) time: 3.0349 data: 0.0079 max mem: 33408 +Epoch: [17] [1200/2639] eta: 1:12:37 lr: 2.9844173257104235e-05 loss: 0.0584 (0.0560) time: 3.0362 data: 0.0083 max mem: 33408 +Epoch: [17] [1210/2639] eta: 1:12:07 lr: 2.9839658670968574e-05 loss: 0.0560 (0.0559) time: 3.0681 data: 0.0083 max mem: 33408 +Epoch: [17] [1220/2639] eta: 1:11:36 lr: 2.983514400893902e-05 loss: 0.0538 (0.0561) time: 3.0379 data: 0.0081 max mem: 33408 +Epoch: [17] [1230/2639] eta: 1:11:06 lr: 2.9830629271001535e-05 loss: 0.0539 (0.0560) time: 3.0400 data: 0.0077 max mem: 33408 +Epoch: [17] [1240/2639] eta: 1:10:36 lr: 2.982611445714209e-05 loss: 0.0584 (0.0562) time: 3.0194 data: 0.0080 max mem: 33408 +Epoch: [17] [1250/2639] eta: 1:10:06 lr: 2.982159956734662e-05 loss: 0.0584 (0.0563) time: 3.0259 data: 0.0080 max mem: 33408 +Epoch: [17] [1260/2639] eta: 1:09:35 lr: 2.9817084601601074e-05 loss: 0.0598 (0.0563) time: 3.0318 data: 0.0083 max mem: 33408 +Epoch: [17] [1270/2639] eta: 1:09:05 lr: 2.981256955989142e-05 loss: 0.0593 (0.0563) time: 3.0295 data: 0.0091 max mem: 33408 +Epoch: [17] [1280/2639] eta: 1:08:35 lr: 2.980805444220357e-05 loss: 0.0593 (0.0565) time: 3.0518 data: 0.0083 max mem: 33408 +Epoch: [17] [1290/2639] eta: 1:08:05 lr: 2.9803539248523465e-05 loss: 0.0496 (0.0564) time: 3.0298 data: 0.0072 max mem: 33408 +Epoch: [17] [1300/2639] eta: 1:07:34 lr: 2.979902397883703e-05 loss: 0.0496 (0.0564) time: 3.0028 data: 0.0075 max mem: 33408 +Epoch: [17] [1310/2639] eta: 1:07:04 lr: 2.9794508633130202e-05 loss: 0.0541 (0.0566) time: 3.0070 data: 0.0080 max mem: 33408 +Epoch: [17] [1320/2639] eta: 1:06:34 lr: 2.9789993211388895e-05 loss: 0.0501 (0.0565) time: 3.0403 data: 0.0078 max mem: 33408 +Epoch: [17] [1330/2639] eta: 1:06:03 lr: 2.978547771359902e-05 loss: 0.0499 (0.0565) time: 3.0388 data: 0.0074 max mem: 33408 +Epoch: [17] [1340/2639] eta: 1:05:33 lr: 2.978096213974648e-05 loss: 0.0654 (0.0566) time: 3.0187 data: 0.0081 max mem: 33408 +Epoch: [17] [1350/2639] eta: 1:05:04 lr: 2.9776446489817182e-05 loss: 0.0544 (0.0566) time: 3.0661 data: 0.0083 max mem: 33408 +Epoch: [17] [1360/2639] eta: 1:04:34 lr: 2.9771930763797036e-05 loss: 0.0480 (0.0566) time: 3.0991 data: 0.0078 max mem: 33408 +Epoch: [17] [1370/2639] eta: 1:04:03 lr: 2.9767414961671925e-05 loss: 0.0506 (0.0566) time: 3.0411 data: 0.0080 max mem: 33408 +Epoch: [17] [1380/2639] eta: 1:03:34 lr: 2.9762899083427738e-05 loss: 0.0531 (0.0567) time: 3.0579 data: 0.0077 max mem: 33408 +Epoch: [17] [1390/2639] eta: 1:03:03 lr: 2.9758383129050355e-05 loss: 0.0534 (0.0567) time: 3.0232 data: 0.0075 max mem: 33408 +Epoch: [17] [1400/2639] eta: 1:02:32 lr: 2.9753867098525666e-05 loss: 0.0534 (0.0567) time: 2.9567 data: 0.0075 max mem: 33408 +Epoch: [17] [1410/2639] eta: 1:02:01 lr: 2.9749350991839542e-05 loss: 0.0488 (0.0567) time: 2.9832 data: 0.0072 max mem: 33408 +Epoch: [17] [1420/2639] eta: 1:01:31 lr: 2.974483480897784e-05 loss: 0.0534 (0.0568) time: 2.9871 data: 0.0072 max mem: 33408 +Epoch: [17] [1430/2639] eta: 1:01:01 lr: 2.9740318549926434e-05 loss: 0.0534 (0.0568) time: 3.0276 data: 0.0072 max mem: 33408 +Epoch: [17] [1440/2639] eta: 1:00:30 lr: 2.973580221467119e-05 loss: 0.0484 (0.0568) time: 3.0402 data: 0.0077 max mem: 33408 +Epoch: [17] [1450/2639] eta: 1:00:00 lr: 2.9731285803197945e-05 loss: 0.0506 (0.0568) time: 3.0202 data: 0.0076 max mem: 33408 +Epoch: [17] [1460/2639] eta: 0:59:29 lr: 2.972676931549256e-05 loss: 0.0534 (0.0568) time: 3.0124 data: 0.0074 max mem: 33408 +Epoch: [17] [1470/2639] eta: 0:58:59 lr: 2.972225275154087e-05 loss: 0.0504 (0.0568) time: 2.9978 data: 0.0080 max mem: 33408 +Epoch: [17] [1480/2639] eta: 0:58:28 lr: 2.971773611132872e-05 loss: 0.0487 (0.0568) time: 2.9887 data: 0.0076 max mem: 33408 +Epoch: [17] [1490/2639] eta: 0:57:58 lr: 2.9713219394841946e-05 loss: 0.0453 (0.0568) time: 2.9952 data: 0.0077 max mem: 33408 +Epoch: [17] [1500/2639] eta: 0:57:27 lr: 2.9708702602066368e-05 loss: 0.0472 (0.0567) time: 3.0117 data: 0.0084 max mem: 33408 +Epoch: [17] [1510/2639] eta: 0:56:58 lr: 2.9704185732987816e-05 loss: 0.0461 (0.0567) time: 3.0653 data: 0.0081 max mem: 33408 +Epoch: [17] [1520/2639] eta: 0:56:28 lr: 2.969966878759211e-05 loss: 0.0442 (0.0567) time: 3.1006 data: 0.0075 max mem: 33408 +Epoch: [17] [1530/2639] eta: 0:55:57 lr: 2.9695151765865052e-05 loss: 0.0485 (0.0568) time: 3.0252 data: 0.0076 max mem: 33408 +Epoch: [17] [1540/2639] eta: 0:55:27 lr: 2.9690634667792468e-05 loss: 0.0584 (0.0568) time: 3.0075 data: 0.0075 max mem: 33408 +Epoch: [17] [1550/2639] eta: 0:54:57 lr: 2.968611749336015e-05 loss: 0.0633 (0.0569) time: 3.0309 data: 0.0075 max mem: 33408 +Epoch: [17] [1560/2639] eta: 0:54:27 lr: 2.9681600242553892e-05 loss: 0.0559 (0.0570) time: 3.0479 data: 0.0078 max mem: 33408 +Epoch: [17] [1570/2639] eta: 0:53:57 lr: 2.9677082915359505e-05 loss: 0.0559 (0.0569) time: 3.0579 data: 0.0077 max mem: 33408 +Epoch: [17] [1580/2639] eta: 0:53:26 lr: 2.9672565511762764e-05 loss: 0.0508 (0.0569) time: 3.0187 data: 0.0076 max mem: 33408 +Epoch: [17] [1590/2639] eta: 0:52:56 lr: 2.966804803174945e-05 loss: 0.0490 (0.0570) time: 3.0054 data: 0.0076 max mem: 33408 +Epoch: [17] [1600/2639] eta: 0:52:26 lr: 2.9663530475305346e-05 loss: 0.0563 (0.0570) time: 3.0980 data: 0.0074 max mem: 33408 +Epoch: [17] [1610/2639] eta: 0:51:56 lr: 2.9659012842416233e-05 loss: 0.0559 (0.0570) time: 3.1023 data: 0.0074 max mem: 33408 +Epoch: [17] [1620/2639] eta: 0:51:26 lr: 2.965449513306787e-05 loss: 0.0507 (0.0570) time: 3.0397 data: 0.0074 max mem: 33408 +Epoch: [17] [1630/2639] eta: 0:50:56 lr: 2.9649977347246015e-05 loss: 0.0516 (0.0571) time: 3.0351 data: 0.0075 max mem: 33408 +Epoch: [17] [1640/2639] eta: 0:50:25 lr: 2.964545948493644e-05 loss: 0.0537 (0.0570) time: 3.0057 data: 0.0075 max mem: 33408 +Epoch: [17] [1650/2639] eta: 0:49:56 lr: 2.964094154612489e-05 loss: 0.0518 (0.0571) time: 3.0795 data: 0.0074 max mem: 33408 +Epoch: [17] [1660/2639] eta: 0:49:25 lr: 2.9636423530797112e-05 loss: 0.0578 (0.0572) time: 3.0800 data: 0.0074 max mem: 33408 +Epoch: [17] [1670/2639] eta: 0:48:55 lr: 2.963190543893885e-05 loss: 0.0569 (0.0571) time: 3.0068 data: 0.0074 max mem: 33408 +Epoch: [17] [1680/2639] eta: 0:48:25 lr: 2.9627387270535843e-05 loss: 0.0506 (0.0572) time: 3.0467 data: 0.0076 max mem: 33408 +Epoch: [17] [1690/2639] eta: 0:47:54 lr: 2.9622869025573828e-05 loss: 0.0556 (0.0572) time: 3.0346 data: 0.0077 max mem: 33408 +Epoch: [17] [1700/2639] eta: 0:47:24 lr: 2.9618350704038523e-05 loss: 0.0496 (0.0572) time: 3.0207 data: 0.0074 max mem: 33408 +Epoch: [17] [1710/2639] eta: 0:46:53 lr: 2.9613832305915658e-05 loss: 0.0434 (0.0572) time: 3.0016 data: 0.0076 max mem: 33408 +Epoch: [17] [1720/2639] eta: 0:46:23 lr: 2.9609313831190938e-05 loss: 0.0490 (0.0572) time: 3.0033 data: 0.0075 max mem: 33408 +Epoch: [17] [1730/2639] eta: 0:45:53 lr: 2.9604795279850095e-05 loss: 0.0512 (0.0571) time: 3.0275 data: 0.0075 max mem: 33408 +Epoch: [17] [1740/2639] eta: 0:45:23 lr: 2.960027665187883e-05 loss: 0.0547 (0.0572) time: 3.0400 data: 0.0077 max mem: 33408 +Epoch: [17] [1750/2639] eta: 0:44:52 lr: 2.959575794726283e-05 loss: 0.0555 (0.0572) time: 3.0455 data: 0.0077 max mem: 33408 +Epoch: [17] [1760/2639] eta: 0:44:23 lr: 2.9591239165987804e-05 loss: 0.0557 (0.0572) time: 3.0754 data: 0.0081 max mem: 33408 +Epoch: [17] [1770/2639] eta: 0:43:52 lr: 2.9586720308039456e-05 loss: 0.0551 (0.0573) time: 3.0579 data: 0.0079 max mem: 33408 +Epoch: [17] [1780/2639] eta: 0:43:22 lr: 2.9582201373403452e-05 loss: 0.0579 (0.0573) time: 2.9985 data: 0.0073 max mem: 33408 +Epoch: [17] [1790/2639] eta: 0:42:52 lr: 2.9577682362065484e-05 loss: 0.0583 (0.0573) time: 3.0432 data: 0.0073 max mem: 33408 +Epoch: [17] [1800/2639] eta: 0:42:21 lr: 2.9573163274011224e-05 loss: 0.0556 (0.0573) time: 3.0263 data: 0.0073 max mem: 33408 +Epoch: [17] [1810/2639] eta: 0:41:51 lr: 2.9568644109226346e-05 loss: 0.0519 (0.0574) time: 2.9891 data: 0.0074 max mem: 33408 +Epoch: [17] [1820/2639] eta: 0:41:21 lr: 2.9564124867696525e-05 loss: 0.0558 (0.0574) time: 3.0360 data: 0.0075 max mem: 33408 +Epoch: [17] [1830/2639] eta: 0:40:50 lr: 2.955960554940741e-05 loss: 0.0581 (0.0575) time: 3.0250 data: 0.0077 max mem: 33408 +Epoch: [17] [1840/2639] eta: 0:40:20 lr: 2.955508615434466e-05 loss: 0.0612 (0.0575) time: 2.9822 data: 0.0081 max mem: 33408 +Epoch: [17] [1850/2639] eta: 0:39:49 lr: 2.9550566682493926e-05 loss: 0.0608 (0.0576) time: 3.0037 data: 0.0084 max mem: 33408 +Epoch: [17] [1860/2639] eta: 0:39:19 lr: 2.954604713384086e-05 loss: 0.0526 (0.0575) time: 2.9787 data: 0.0083 max mem: 33408 +Epoch: [17] [1870/2639] eta: 0:38:48 lr: 2.95415275083711e-05 loss: 0.0485 (0.0575) time: 2.9403 data: 0.0081 max mem: 33408 +Epoch: [17] [1880/2639] eta: 0:38:18 lr: 2.9537007806070276e-05 loss: 0.0490 (0.0575) time: 2.9650 data: 0.0081 max mem: 33408 +Epoch: [17] [1890/2639] eta: 0:37:47 lr: 2.9532488026924022e-05 loss: 0.0490 (0.0575) time: 2.9622 data: 0.0082 max mem: 33408 +Epoch: [17] [1900/2639] eta: 0:37:17 lr: 2.9527968170917976e-05 loss: 0.0458 (0.0575) time: 2.9766 data: 0.0081 max mem: 33408 +Epoch: [17] [1910/2639] eta: 0:36:46 lr: 2.9523448238037736e-05 loss: 0.0458 (0.0574) time: 2.9993 data: 0.0079 max mem: 33408 +Epoch: [17] [1920/2639] eta: 0:36:16 lr: 2.951892822826893e-05 loss: 0.0500 (0.0574) time: 2.9995 data: 0.0080 max mem: 33408 +Epoch: [17] [1930/2639] eta: 0:35:46 lr: 2.9514408141597165e-05 loss: 0.0564 (0.0575) time: 3.0302 data: 0.0082 max mem: 33408 +Epoch: [17] [1940/2639] eta: 0:35:15 lr: 2.950988797800805e-05 loss: 0.0484 (0.0574) time: 3.0270 data: 0.0083 max mem: 33408 +Epoch: [17] [1950/2639] eta: 0:34:45 lr: 2.950536773748719e-05 loss: 0.0429 (0.0574) time: 2.9929 data: 0.0081 max mem: 33408 +Epoch: [17] [1960/2639] eta: 0:34:15 lr: 2.9500847420020154e-05 loss: 0.0515 (0.0575) time: 3.0118 data: 0.0078 max mem: 33408 +Epoch: [17] [1970/2639] eta: 0:33:44 lr: 2.9496327025592556e-05 loss: 0.0515 (0.0574) time: 3.0288 data: 0.0079 max mem: 33408 +Epoch: [17] [1980/2639] eta: 0:33:14 lr: 2.9491806554189982e-05 loss: 0.0525 (0.0575) time: 3.0486 data: 0.0080 max mem: 33408 +Epoch: [17] [1990/2639] eta: 0:32:44 lr: 2.9487286005797998e-05 loss: 0.0569 (0.0576) time: 3.0949 data: 0.0077 max mem: 33408 +Epoch: [17] [2000/2639] eta: 0:32:14 lr: 2.9482765380402177e-05 loss: 0.0529 (0.0576) time: 3.0291 data: 0.0078 max mem: 33408 +Epoch: [17] [2010/2639] eta: 0:31:43 lr: 2.9478244677988097e-05 loss: 0.0457 (0.0576) time: 2.9894 data: 0.0083 max mem: 33408 +Epoch: [17] [2020/2639] eta: 0:31:13 lr: 2.947372389854132e-05 loss: 0.0456 (0.0576) time: 3.0142 data: 0.0083 max mem: 33408 +Epoch: [17] [2030/2639] eta: 0:30:43 lr: 2.94692030420474e-05 loss: 0.0395 (0.0575) time: 3.0173 data: 0.0082 max mem: 33408 +Epoch: [17] [2040/2639] eta: 0:30:13 lr: 2.9464682108491897e-05 loss: 0.0452 (0.0575) time: 3.0206 data: 0.0082 max mem: 33408 +Epoch: [17] [2050/2639] eta: 0:29:43 lr: 2.9460161097860355e-05 loss: 0.0558 (0.0575) time: 3.0642 data: 0.0082 max mem: 33408 +Epoch: [17] [2060/2639] eta: 0:29:12 lr: 2.9455640010138313e-05 loss: 0.0533 (0.0574) time: 3.0518 data: 0.0082 max mem: 33408 +Epoch: [17] [2070/2639] eta: 0:28:42 lr: 2.945111884531132e-05 loss: 0.0500 (0.0574) time: 3.0165 data: 0.0079 max mem: 33408 +Epoch: [17] [2080/2639] eta: 0:28:12 lr: 2.94465976033649e-05 loss: 0.0485 (0.0574) time: 3.0398 data: 0.0080 max mem: 33408 +Epoch: [17] [2090/2639] eta: 0:27:42 lr: 2.944207628428458e-05 loss: 0.0433 (0.0573) time: 3.0550 data: 0.0081 max mem: 33408 +Epoch: [17] [2100/2639] eta: 0:27:11 lr: 2.9437554888055886e-05 loss: 0.0440 (0.0573) time: 3.0329 data: 0.0080 max mem: 33408 +Epoch: [17] [2110/2639] eta: 0:26:41 lr: 2.9433033414664333e-05 loss: 0.0525 (0.0573) time: 2.9940 data: 0.0077 max mem: 33408 +Epoch: [17] [2120/2639] eta: 0:26:10 lr: 2.9428511864095438e-05 loss: 0.0530 (0.0574) time: 2.9597 data: 0.0076 max mem: 33408 +Epoch: [17] [2130/2639] eta: 0:25:40 lr: 2.94239902363347e-05 loss: 0.0542 (0.0574) time: 3.0115 data: 0.0079 max mem: 33408 +Epoch: [17] [2140/2639] eta: 0:25:10 lr: 2.941946853136762e-05 loss: 0.0510 (0.0574) time: 3.0361 data: 0.0078 max mem: 33408 +Epoch: [17] [2150/2639] eta: 0:24:40 lr: 2.9414946749179704e-05 loss: 0.0467 (0.0574) time: 3.0146 data: 0.0079 max mem: 33408 +Epoch: [17] [2160/2639] eta: 0:24:09 lr: 2.9410424889756443e-05 loss: 0.0463 (0.0574) time: 3.0092 data: 0.0080 max mem: 33408 +Epoch: [17] [2170/2639] eta: 0:23:39 lr: 2.940590295308331e-05 loss: 0.0557 (0.0575) time: 2.9970 data: 0.0082 max mem: 33408 +Epoch: [17] [2180/2639] eta: 0:23:09 lr: 2.940138093914579e-05 loss: 0.0502 (0.0575) time: 3.0117 data: 0.0080 max mem: 33408 +Epoch: [17] [2190/2639] eta: 0:22:38 lr: 2.9396858847929364e-05 loss: 0.0471 (0.0575) time: 3.0262 data: 0.0079 max mem: 33408 +Epoch: [17] [2200/2639] eta: 0:22:08 lr: 2.9392336679419508e-05 loss: 0.0489 (0.0574) time: 3.0783 data: 0.0080 max mem: 33408 +Epoch: [17] [2210/2639] eta: 0:21:38 lr: 2.938781443360167e-05 loss: 0.0470 (0.0574) time: 3.0366 data: 0.0076 max mem: 33408 +Epoch: [17] [2220/2639] eta: 0:21:08 lr: 2.9383292110461318e-05 loss: 0.0502 (0.0574) time: 3.0022 data: 0.0078 max mem: 33408 +Epoch: [17] [2230/2639] eta: 0:20:37 lr: 2.937876970998391e-05 loss: 0.0527 (0.0575) time: 3.0203 data: 0.0085 max mem: 33408 +Epoch: [17] [2240/2639] eta: 0:20:07 lr: 2.93742472321549e-05 loss: 0.0573 (0.0575) time: 3.0234 data: 0.0082 max mem: 33408 +Epoch: [17] [2250/2639] eta: 0:19:37 lr: 2.9369724676959716e-05 loss: 0.0526 (0.0575) time: 3.0447 data: 0.0080 max mem: 33408 +Epoch: [17] [2260/2639] eta: 0:19:07 lr: 2.9365202044383805e-05 loss: 0.0550 (0.0575) time: 3.0258 data: 0.0083 max mem: 33408 +Epoch: [17] [2270/2639] eta: 0:18:36 lr: 2.9360679334412606e-05 loss: 0.0556 (0.0575) time: 3.0150 data: 0.0080 max mem: 33408 +Epoch: [17] [2280/2639] eta: 0:18:06 lr: 2.9356156547031545e-05 loss: 0.0515 (0.0575) time: 3.0111 data: 0.0079 max mem: 33408 +Epoch: [17] [2290/2639] eta: 0:17:36 lr: 2.9351633682226044e-05 loss: 0.0489 (0.0575) time: 3.0281 data: 0.0078 max mem: 33408 +Epoch: [17] [2300/2639] eta: 0:17:05 lr: 2.9347110739981515e-05 loss: 0.0556 (0.0575) time: 3.0360 data: 0.0079 max mem: 33408 +Epoch: [17] [2310/2639] eta: 0:16:35 lr: 2.9342587720283378e-05 loss: 0.0550 (0.0575) time: 3.0294 data: 0.0085 max mem: 33408 +Epoch: [17] [2320/2639] eta: 0:16:05 lr: 2.9338064623117044e-05 loss: 0.0504 (0.0575) time: 3.0108 data: 0.0082 max mem: 33408 +Epoch: [17] [2330/2639] eta: 0:15:35 lr: 2.9333541448467904e-05 loss: 0.0604 (0.0575) time: 3.0260 data: 0.0074 max mem: 33408 +Epoch: [17] [2340/2639] eta: 0:15:04 lr: 2.9329018196321362e-05 loss: 0.0524 (0.0575) time: 3.0316 data: 0.0074 max mem: 33408 +Epoch: [17] [2350/2639] eta: 0:14:34 lr: 2.932449486666281e-05 loss: 0.0510 (0.0576) time: 2.9769 data: 0.0077 max mem: 33408 +Epoch: [17] [2360/2639] eta: 0:14:04 lr: 2.9319971459477635e-05 loss: 0.0514 (0.0576) time: 2.9976 data: 0.0078 max mem: 33408 +Epoch: [17] [2370/2639] eta: 0:13:34 lr: 2.931544797475122e-05 loss: 0.0508 (0.0576) time: 3.0505 data: 0.0078 max mem: 33408 +Epoch: [17] [2380/2639] eta: 0:13:03 lr: 2.9310924412468928e-05 loss: 0.0487 (0.0576) time: 3.0302 data: 0.0079 max mem: 33408 +Epoch: [17] [2390/2639] eta: 0:12:33 lr: 2.9306400772616144e-05 loss: 0.0476 (0.0577) time: 2.9910 data: 0.0079 max mem: 33408 +Epoch: [17] [2400/2639] eta: 0:12:03 lr: 2.930187705517823e-05 loss: 0.0516 (0.0576) time: 2.9901 data: 0.0075 max mem: 33408 +Epoch: [17] [2410/2639] eta: 0:11:32 lr: 2.9297353260140542e-05 loss: 0.0549 (0.0577) time: 3.0213 data: 0.0073 max mem: 33408 +Epoch: [17] [2420/2639] eta: 0:11:02 lr: 2.929282938748844e-05 loss: 0.0605 (0.0577) time: 3.0243 data: 0.0075 max mem: 33408 +Epoch: [17] [2430/2639] eta: 0:10:32 lr: 2.9288305437207263e-05 loss: 0.0559 (0.0577) time: 3.0174 data: 0.0074 max mem: 33408 +Epoch: [17] [2440/2639] eta: 0:10:02 lr: 2.9283781409282373e-05 loss: 0.0526 (0.0576) time: 3.0068 data: 0.0074 max mem: 33408 +Epoch: [17] [2450/2639] eta: 0:09:31 lr: 2.9279257303699105e-05 loss: 0.0505 (0.0577) time: 3.0353 data: 0.0072 max mem: 33408 +Epoch: [17] [2460/2639] eta: 0:09:01 lr: 2.9274733120442776e-05 loss: 0.0601 (0.0577) time: 3.0521 data: 0.0074 max mem: 33408 +Epoch: [17] [2470/2639] eta: 0:08:31 lr: 2.9270208859498726e-05 loss: 0.0571 (0.0577) time: 3.0090 data: 0.0077 max mem: 33408 +Epoch: [17] [2480/2639] eta: 0:08:01 lr: 2.926568452085229e-05 loss: 0.0474 (0.0577) time: 3.0093 data: 0.0077 max mem: 33408 +Epoch: [17] [2490/2639] eta: 0:07:30 lr: 2.9261160104488766e-05 loss: 0.0503 (0.0577) time: 3.0278 data: 0.0078 max mem: 33408 +Epoch: [17] [2500/2639] eta: 0:07:00 lr: 2.925663561039347e-05 loss: 0.0476 (0.0577) time: 3.0667 data: 0.0080 max mem: 33408 +Epoch: [17] [2510/2639] eta: 0:06:30 lr: 2.9252111038551716e-05 loss: 0.0423 (0.0577) time: 3.0374 data: 0.0079 max mem: 33408 +Epoch: [17] [2520/2639] eta: 0:06:00 lr: 2.9247586388948804e-05 loss: 0.0524 (0.0577) time: 3.0254 data: 0.0073 max mem: 33408 +Epoch: [17] [2530/2639] eta: 0:05:29 lr: 2.9243061661570036e-05 loss: 0.0545 (0.0577) time: 3.0170 data: 0.0076 max mem: 33408 +Epoch: [17] [2540/2639] eta: 0:04:59 lr: 2.92385368564007e-05 loss: 0.0499 (0.0577) time: 3.0226 data: 0.0076 max mem: 33408 +Epoch: [17] [2550/2639] eta: 0:04:29 lr: 2.9234011973426067e-05 loss: 0.0509 (0.0577) time: 3.0429 data: 0.0076 max mem: 33408 +Epoch: [17] [2560/2639] eta: 0:03:59 lr: 2.922948701263144e-05 loss: 0.0509 (0.0577) time: 3.0193 data: 0.0076 max mem: 33408 +Epoch: [17] [2570/2639] eta: 0:03:28 lr: 2.9224961974002084e-05 loss: 0.0500 (0.0577) time: 3.0121 data: 0.0074 max mem: 33408 +Epoch: [17] [2580/2639] eta: 0:02:58 lr: 2.9220436857523275e-05 loss: 0.0504 (0.0577) time: 3.0170 data: 0.0074 max mem: 33408 +Epoch: [17] [2590/2639] eta: 0:02:28 lr: 2.9215911663180268e-05 loss: 0.0471 (0.0576) time: 3.0190 data: 0.0075 max mem: 33408 +Epoch: [17] [2600/2639] eta: 0:01:58 lr: 2.9211386390958324e-05 loss: 0.0471 (0.0577) time: 3.0221 data: 0.0077 max mem: 33408 +Epoch: [17] [2610/2639] eta: 0:01:27 lr: 2.9206861040842702e-05 loss: 0.0503 (0.0577) time: 3.0104 data: 0.0078 max mem: 33408 +Epoch: [17] [2620/2639] eta: 0:00:57 lr: 2.920233561281866e-05 loss: 0.0503 (0.0577) time: 3.0073 data: 0.0078 max mem: 33408 +Epoch: [17] [2630/2639] eta: 0:00:27 lr: 2.9197810106871422e-05 loss: 0.0529 (0.0577) time: 3.0134 data: 0.0077 max mem: 33408 +Epoch: [17] Total time: 2:13:05 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 2:20:44 time: 3.2820 data: 3.1782 max mem: 33408 +Test: [ 100/2573] eta: 0:04:33 time: 0.0794 data: 0.0015 max mem: 33408 +Test: [ 200/2573] eta: 0:03:47 time: 0.0809 data: 0.0015 max mem: 33408 +Test: [ 300/2573] eta: 0:03:25 time: 0.0819 data: 0.0013 max mem: 33408 +Test: [ 400/2573] eta: 0:03:10 time: 0.0815 data: 0.0014 max mem: 33408 +Test: [ 500/2573] eta: 0:02:58 time: 0.0793 data: 0.0014 max mem: 33408 +Test: [ 600/2573] eta: 0:02:48 time: 0.0796 data: 0.0014 max mem: 33408 +Test: [ 700/2573] eta: 0:02:38 time: 0.0803 data: 0.0016 max mem: 33408 +Test: [ 800/2573] eta: 0:02:29 time: 0.0828 data: 0.0013 max mem: 33408 +Test: [ 900/2573] eta: 0:02:20 time: 0.0816 data: 0.0014 max mem: 33408 +Test: [1000/2573] eta: 0:02:11 time: 0.0795 data: 0.0014 max mem: 33408 +Test: [1100/2573] eta: 0:02:02 time: 0.0812 data: 0.0014 max mem: 33408 +Test: [1200/2573] eta: 0:01:54 time: 0.0805 data: 0.0014 max mem: 33408 +Test: [1300/2573] eta: 0:01:45 time: 0.0793 data: 0.0013 max mem: 33408 +Test: [1400/2573] eta: 0:01:37 time: 0.0780 data: 0.0014 max mem: 33408 +Test: [1500/2573] eta: 0:01:28 time: 0.0799 data: 0.0014 max mem: 33408 +Test: [1600/2573] eta: 0:01:20 time: 0.0839 data: 0.0016 max mem: 33408 +Test: [1700/2573] eta: 0:01:11 time: 0.0783 data: 0.0014 max mem: 33408 +Test: [1800/2573] eta: 0:01:03 time: 0.0815 data: 0.0014 max mem: 33408 +Test: [1900/2573] eta: 0:00:55 time: 0.0791 data: 0.0016 max mem: 33408 +Test: [2000/2573] eta: 0:00:46 time: 0.0804 data: 0.0014 max mem: 33408 +Test: [2100/2573] eta: 0:00:38 time: 0.0825 data: 0.0014 max mem: 33408 +Test: [2200/2573] eta: 0:00:30 time: 0.0831 data: 0.0015 max mem: 33408 +Test: [2300/2573] eta: 0:00:22 time: 0.0833 data: 0.0015 max mem: 33408 +Test: [2400/2573] eta: 0:00:14 time: 0.0780 data: 0.0014 max mem: 33408 +Test: [2500/2573] eta: 0:00:05 time: 0.0811 data: 0.0016 max mem: 33408 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: Total time: 0:03:31 +Final results: +Mean IoU is 63.34 + + precision@0.5 = 71.24 + precision@0.6 = 65.87 + precision@0.7 = 57.58 + precision@0.8 = 45.94 + precision@0.9 = 21.88 + overall IoU = 60.66 + +Average object IoU 63.33930101787053 +Overall IoU 60.6615104675293 +Better epoch: 17 + +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [18] [ 0/2639] eta: 3:55:50 lr: 2.9193737084882377e-05 loss: 0.0397 (0.0397) time: 5.3620 data: 2.2268 max mem: 33408 +Epoch: [18] [ 10/2639] eta: 2:23:50 lr: 2.9189211430840417e-05 loss: 0.0458 (0.0490) time: 3.2829 data: 0.2097 max mem: 33408 +Epoch: [18] [ 20/2639] eta: 2:19:10 lr: 2.918468569883244e-05 loss: 0.0464 (0.0525) time: 3.0797 data: 0.0073 max mem: 33408 +Epoch: [18] [ 30/2639] eta: 2:16:11 lr: 2.9180159888843673e-05 loss: 0.0552 (0.0547) time: 3.0492 data: 0.0073 max mem: 33408 +Epoch: [18] [ 40/2639] eta: 2:15:09 lr: 2.9175634000859337e-05 loss: 0.0586 (0.0556) time: 3.0486 data: 0.0079 max mem: 33408 +Epoch: [18] [ 50/2639] eta: 2:14:02 lr: 2.9171108034864643e-05 loss: 0.0519 (0.0548) time: 3.0664 data: 0.0081 max mem: 33408 +Epoch: [18] [ 60/2639] eta: 2:13:09 lr: 2.9166581990844794e-05 loss: 0.0519 (0.0576) time: 3.0521 data: 0.0082 max mem: 33408 +Epoch: [18] [ 70/2639] eta: 2:11:50 lr: 2.9162055868784994e-05 loss: 0.0476 (0.0562) time: 3.0103 data: 0.0083 max mem: 33408 +Epoch: [18] [ 80/2639] eta: 2:11:01 lr: 2.9157529668670437e-05 loss: 0.0476 (0.0558) time: 2.9940 data: 0.0083 max mem: 33408 +Epoch: [18] [ 90/2639] eta: 2:10:06 lr: 2.915300339048632e-05 loss: 0.0439 (0.0548) time: 3.0024 data: 0.0082 max mem: 33408 +Epoch: [18] [ 100/2639] eta: 2:09:34 lr: 2.9148477034217818e-05 loss: 0.0406 (0.0548) time: 3.0215 data: 0.0081 max mem: 33408 +Epoch: [18] [ 110/2639] eta: 2:08:55 lr: 2.9143950599850116e-05 loss: 0.0447 (0.0541) time: 3.0424 data: 0.0078 max mem: 33408 +Epoch: [18] [ 120/2639] eta: 2:08:30 lr: 2.913942408736839e-05 loss: 0.0419 (0.0533) time: 3.0545 data: 0.0081 max mem: 33408 +Epoch: [18] [ 130/2639] eta: 2:07:46 lr: 2.9134897496757813e-05 loss: 0.0419 (0.0531) time: 3.0387 data: 0.0083 max mem: 33408 +Epoch: [18] [ 140/2639] eta: 2:07:28 lr: 2.9130370828003535e-05 loss: 0.0489 (0.0529) time: 3.0594 data: 0.0078 max mem: 33408 +Epoch: [18] [ 150/2639] eta: 2:06:48 lr: 2.9125844081090718e-05 loss: 0.0449 (0.0523) time: 3.0643 data: 0.0080 max mem: 33408 +Epoch: [18] [ 160/2639] eta: 2:06:20 lr: 2.9121317256004526e-05 loss: 0.0428 (0.0528) time: 3.0370 data: 0.0082 max mem: 33408 +Epoch: [18] [ 170/2639] eta: 2:05:57 lr: 2.91167903527301e-05 loss: 0.0489 (0.0529) time: 3.0912 data: 0.0081 max mem: 33408 +Epoch: [18] [ 180/2639] eta: 2:05:16 lr: 2.9112263371252584e-05 loss: 0.0484 (0.0525) time: 3.0485 data: 0.0084 max mem: 33408 +Epoch: [18] [ 190/2639] eta: 2:04:44 lr: 2.910773631155711e-05 loss: 0.0410 (0.0520) time: 3.0161 data: 0.0083 max mem: 33408 +Epoch: [18] [ 200/2639] eta: 2:04:05 lr: 2.9103209173628802e-05 loss: 0.0398 (0.0519) time: 3.0146 data: 0.0080 max mem: 33408 +Epoch: [18] [ 210/2639] eta: 2:03:36 lr: 2.909868195745281e-05 loss: 0.0484 (0.0521) time: 3.0255 data: 0.0079 max mem: 33408 +Epoch: [18] [ 220/2639] eta: 2:03:00 lr: 2.909415466301424e-05 loss: 0.0453 (0.0521) time: 3.0365 data: 0.0081 max mem: 33408 +Epoch: [18] [ 230/2639] eta: 2:02:25 lr: 2.90896272902982e-05 loss: 0.0470 (0.0522) time: 3.0064 data: 0.0080 max mem: 33408 +Epoch: [18] [ 240/2639] eta: 2:01:46 lr: 2.908509983928981e-05 loss: 0.0432 (0.0522) time: 2.9865 data: 0.0082 max mem: 33408 +Epoch: [18] [ 250/2639] eta: 2:01:18 lr: 2.9080572309974174e-05 loss: 0.0417 (0.0520) time: 3.0159 data: 0.0082 max mem: 33408 +Epoch: [18] [ 260/2639] eta: 2:00:44 lr: 2.9076044702336387e-05 loss: 0.0518 (0.0528) time: 3.0407 data: 0.0080 max mem: 33408 +Epoch: [18] [ 270/2639] eta: 2:00:19 lr: 2.9071517016361537e-05 loss: 0.0521 (0.0527) time: 3.0617 data: 0.0077 max mem: 33408 +Epoch: [18] [ 280/2639] eta: 1:59:47 lr: 2.9066989252034726e-05 loss: 0.0467 (0.0527) time: 3.0647 data: 0.0077 max mem: 33408 +Epoch: [18] [ 290/2639] eta: 1:59:15 lr: 2.906246140934103e-05 loss: 0.0467 (0.0526) time: 3.0239 data: 0.0085 max mem: 33408 +Epoch: [18] [ 300/2639] eta: 1:58:48 lr: 2.9057933488265527e-05 loss: 0.0450 (0.0525) time: 3.0578 data: 0.0083 max mem: 33408 +Epoch: [18] [ 310/2639] eta: 1:58:14 lr: 2.9053405488793284e-05 loss: 0.0407 (0.0524) time: 3.0455 data: 0.0083 max mem: 33408 +Epoch: [18] [ 320/2639] eta: 1:57:42 lr: 2.904887741090937e-05 loss: 0.0446 (0.0525) time: 3.0188 data: 0.0084 max mem: 33408 +Epoch: [18] [ 330/2639] eta: 1:57:13 lr: 2.9044349254598852e-05 loss: 0.0515 (0.0529) time: 3.0449 data: 0.0082 max mem: 33408 +Epoch: [18] [ 340/2639] eta: 1:56:40 lr: 2.903982101984678e-05 loss: 0.0470 (0.0528) time: 3.0345 data: 0.0083 max mem: 33408 +Epoch: [18] [ 350/2639] eta: 1:56:05 lr: 2.90352927066382e-05 loss: 0.0512 (0.0534) time: 2.9967 data: 0.0078 max mem: 33408 +Epoch: [18] [ 360/2639] eta: 1:55:30 lr: 2.9030764314958164e-05 loss: 0.0516 (0.0534) time: 2.9739 data: 0.0075 max mem: 33408 +Epoch: [18] [ 370/2639] eta: 1:54:59 lr: 2.902623584479171e-05 loss: 0.0500 (0.0532) time: 2.9978 data: 0.0077 max mem: 33408 +Epoch: [18] [ 380/2639] eta: 1:54:30 lr: 2.9021707296123873e-05 loss: 0.0454 (0.0532) time: 3.0499 data: 0.0075 max mem: 33408 +Epoch: [18] [ 390/2639] eta: 1:54:04 lr: 2.901717866893967e-05 loss: 0.0467 (0.0533) time: 3.0907 data: 0.0074 max mem: 33408 +Epoch: [18] [ 400/2639] eta: 1:53:29 lr: 2.9012649963224138e-05 loss: 0.0469 (0.0531) time: 3.0391 data: 0.0079 max mem: 33408 +Epoch: [18] [ 410/2639] eta: 1:53:00 lr: 2.900812117896228e-05 loss: 0.0474 (0.0531) time: 3.0135 data: 0.0077 max mem: 33408 +Epoch: [18] [ 420/2639] eta: 1:52:30 lr: 2.9003592316139126e-05 loss: 0.0526 (0.0530) time: 3.0520 data: 0.0074 max mem: 33408 +Epoch: [18] [ 430/2639] eta: 1:51:57 lr: 2.8999063374739675e-05 loss: 0.0545 (0.0533) time: 3.0223 data: 0.0077 max mem: 33408 +Epoch: [18] [ 440/2639] eta: 1:51:24 lr: 2.899453435474892e-05 loss: 0.0444 (0.0531) time: 2.9920 data: 0.0075 max mem: 33408 +Epoch: [18] [ 450/2639] eta: 1:50:54 lr: 2.8990005256151863e-05 loss: 0.0436 (0.0530) time: 3.0151 data: 0.0074 max mem: 33408 +Epoch: [18] [ 460/2639] eta: 1:50:19 lr: 2.89854760789335e-05 loss: 0.0476 (0.0530) time: 3.0033 data: 0.0073 max mem: 33408 +Epoch: [18] [ 470/2639] eta: 1:49:49 lr: 2.898094682307881e-05 loss: 0.0452 (0.0529) time: 2.9992 data: 0.0073 max mem: 33408 +Epoch: [18] [ 480/2639] eta: 1:49:16 lr: 2.897641748857276e-05 loss: 0.0452 (0.0528) time: 3.0073 data: 0.0081 max mem: 33408 +Epoch: [18] [ 490/2639] eta: 1:48:44 lr: 2.897188807540034e-05 loss: 0.0447 (0.0527) time: 2.9842 data: 0.0080 max mem: 33408 +Epoch: [18] [ 500/2639] eta: 1:48:11 lr: 2.8967358583546515e-05 loss: 0.0456 (0.0527) time: 2.9876 data: 0.0073 max mem: 33408 +Epoch: [18] [ 510/2639] eta: 1:47:41 lr: 2.896282901299625e-05 loss: 0.0472 (0.0528) time: 3.0175 data: 0.0073 max mem: 33408 +Epoch: [18] [ 520/2639] eta: 1:47:11 lr: 2.895829936373449e-05 loss: 0.0472 (0.0532) time: 3.0402 data: 0.0074 max mem: 33408 +Epoch: [18] [ 530/2639] eta: 1:46:43 lr: 2.8953769635746202e-05 loss: 0.0536 (0.0533) time: 3.0650 data: 0.0075 max mem: 33408 +Epoch: [18] [ 540/2639] eta: 1:46:11 lr: 2.8949239829016327e-05 loss: 0.0512 (0.0531) time: 3.0414 data: 0.0074 max mem: 33408 +Epoch: [18] [ 550/2639] eta: 1:45:43 lr: 2.8944709943529802e-05 loss: 0.0454 (0.0530) time: 3.0400 data: 0.0076 max mem: 33408 +Epoch: [18] [ 560/2639] eta: 1:45:10 lr: 2.894017997927156e-05 loss: 0.0486 (0.0534) time: 3.0337 data: 0.0077 max mem: 33408 +Epoch: [18] [ 570/2639] eta: 1:44:39 lr: 2.893564993622653e-05 loss: 0.0541 (0.0536) time: 2.9956 data: 0.0078 max mem: 33408 +Epoch: [18] [ 580/2639] eta: 1:44:06 lr: 2.8931119814379655e-05 loss: 0.0524 (0.0535) time: 2.9926 data: 0.0078 max mem: 33408 +Epoch: [18] [ 590/2639] eta: 1:43:34 lr: 2.8926589613715833e-05 loss: 0.0462 (0.0539) time: 2.9785 data: 0.0081 max mem: 33408 +Epoch: [18] [ 600/2639] eta: 1:43:04 lr: 2.892205933421998e-05 loss: 0.0462 (0.0539) time: 3.0117 data: 0.0080 max mem: 33408 +Epoch: [18] [ 610/2639] eta: 1:42:30 lr: 2.8917528975877005e-05 loss: 0.0476 (0.0540) time: 2.9864 data: 0.0077 max mem: 33408 +Epoch: [18] [ 620/2639] eta: 1:41:59 lr: 2.891299853867182e-05 loss: 0.0614 (0.0541) time: 2.9693 data: 0.0080 max mem: 33408 +Epoch: [18] [ 630/2639] eta: 1:41:27 lr: 2.890846802258932e-05 loss: 0.0471 (0.0542) time: 2.9848 data: 0.0079 max mem: 33408 +Epoch: [18] [ 640/2639] eta: 1:40:57 lr: 2.890393742761438e-05 loss: 0.0492 (0.0541) time: 3.0013 data: 0.0077 max mem: 33408 +Epoch: [18] [ 650/2639] eta: 1:40:29 lr: 2.8899406753731895e-05 loss: 0.0474 (0.0540) time: 3.0710 data: 0.0077 max mem: 33408 +Epoch: [18] [ 660/2639] eta: 1:39:57 lr: 2.8894876000926747e-05 loss: 0.0503 (0.0541) time: 3.0478 data: 0.0078 max mem: 33408 +Epoch: [18] [ 670/2639] eta: 1:39:28 lr: 2.8890345169183813e-05 loss: 0.0538 (0.0541) time: 3.0292 data: 0.0076 max mem: 33408 +Epoch: [18] [ 680/2639] eta: 1:38:59 lr: 2.8885814258487966e-05 loss: 0.0440 (0.0540) time: 3.0733 data: 0.0075 max mem: 33408 +Epoch: [18] [ 690/2639] eta: 1:38:28 lr: 2.888128326882405e-05 loss: 0.0443 (0.0542) time: 3.0401 data: 0.0077 max mem: 33408 +Epoch: [18] [ 700/2639] eta: 1:37:57 lr: 2.8876752200176938e-05 loss: 0.0510 (0.0541) time: 3.0027 data: 0.0077 max mem: 33408 +Epoch: [18] [ 710/2639] eta: 1:37:27 lr: 2.8872221052531478e-05 loss: 0.0457 (0.0543) time: 3.0257 data: 0.0077 max mem: 33408 +Epoch: [18] [ 720/2639] eta: 1:36:57 lr: 2.8867689825872524e-05 loss: 0.0405 (0.0542) time: 3.0513 data: 0.0077 max mem: 33408 +Epoch: [18] [ 730/2639] eta: 1:36:25 lr: 2.886315852018491e-05 loss: 0.0393 (0.0542) time: 3.0148 data: 0.0078 max mem: 33408 +Epoch: [18] [ 740/2639] eta: 1:35:57 lr: 2.8858627135453466e-05 loss: 0.0454 (0.0542) time: 3.0357 data: 0.0084 max mem: 33408 +Epoch: [18] [ 750/2639] eta: 1:35:25 lr: 2.885409567166304e-05 loss: 0.0428 (0.0541) time: 3.0358 data: 0.0084 max mem: 33408 +Epoch: [18] [ 760/2639] eta: 1:34:56 lr: 2.884956412879844e-05 loss: 0.0401 (0.0540) time: 3.0236 data: 0.0080 max mem: 33408 +Epoch: [18] [ 770/2639] eta: 1:34:25 lr: 2.884503250684449e-05 loss: 0.0401 (0.0541) time: 3.0407 data: 0.0077 max mem: 33408 +Epoch: [18] [ 780/2639] eta: 1:33:53 lr: 2.8840500805786003e-05 loss: 0.0401 (0.0541) time: 2.9909 data: 0.0077 max mem: 33408 +Epoch: [18] [ 790/2639] eta: 1:33:23 lr: 2.8835969025607796e-05 loss: 0.0438 (0.0540) time: 2.9960 data: 0.0077 max mem: 33408 +Epoch: [18] [ 800/2639] eta: 1:32:52 lr: 2.8831437166294656e-05 loss: 0.0475 (0.0540) time: 3.0104 data: 0.0078 max mem: 33408 +Epoch: [18] [ 810/2639] eta: 1:32:22 lr: 2.8826905227831392e-05 loss: 0.0582 (0.0541) time: 3.0341 data: 0.0083 max mem: 33408 +Epoch: [18] [ 820/2639] eta: 1:31:54 lr: 2.8822373210202786e-05 loss: 0.0518 (0.0541) time: 3.0904 data: 0.0084 max mem: 33408 +Epoch: [18] [ 830/2639] eta: 1:31:21 lr: 2.8817841113393628e-05 loss: 0.0442 (0.0541) time: 3.0234 data: 0.0079 max mem: 33408 +Epoch: [18] [ 840/2639] eta: 1:30:53 lr: 2.8813308937388706e-05 loss: 0.0461 (0.0540) time: 3.0311 data: 0.0081 max mem: 33408 +Epoch: [18] [ 850/2639] eta: 1:30:21 lr: 2.8808776682172782e-05 loss: 0.0482 (0.0540) time: 3.0429 data: 0.0084 max mem: 33408 +Epoch: [18] [ 860/2639] eta: 1:29:52 lr: 2.8804244347730625e-05 loss: 0.0501 (0.0540) time: 3.0257 data: 0.0081 max mem: 33408 +Epoch: [18] [ 870/2639] eta: 1:29:21 lr: 2.8799711934047007e-05 loss: 0.0488 (0.0540) time: 3.0339 data: 0.0079 max mem: 33408 +Epoch: [18] [ 880/2639] eta: 1:28:52 lr: 2.879517944110669e-05 loss: 0.0453 (0.0539) time: 3.0483 data: 0.0080 max mem: 33408 +Epoch: [18] [ 890/2639] eta: 1:28:20 lr: 2.8790646868894404e-05 loss: 0.0480 (0.0539) time: 3.0189 data: 0.0081 max mem: 33408 +Epoch: [18] [ 900/2639] eta: 1:27:50 lr: 2.878611421739491e-05 loss: 0.0498 (0.0539) time: 2.9840 data: 0.0081 max mem: 33408 +Epoch: [18] [ 910/2639] eta: 1:27:19 lr: 2.878158148659295e-05 loss: 0.0537 (0.0541) time: 3.0215 data: 0.0078 max mem: 33408 +Epoch: [18] [ 920/2639] eta: 1:26:50 lr: 2.8777048676473262e-05 loss: 0.0537 (0.0541) time: 3.0511 data: 0.0077 max mem: 33408 +Epoch: [18] [ 930/2639] eta: 1:26:19 lr: 2.8772515787020572e-05 loss: 0.0510 (0.0542) time: 3.0604 data: 0.0080 max mem: 33408 +Epoch: [18] [ 940/2639] eta: 1:25:50 lr: 2.8767982818219597e-05 loss: 0.0476 (0.0542) time: 3.0418 data: 0.0080 max mem: 33408 +Epoch: [18] [ 950/2639] eta: 1:25:19 lr: 2.8763449770055058e-05 loss: 0.0360 (0.0540) time: 3.0348 data: 0.0080 max mem: 33408 +Epoch: [18] [ 960/2639] eta: 1:24:48 lr: 2.8758916642511676e-05 loss: 0.0409 (0.0540) time: 3.0142 data: 0.0079 max mem: 33408 +Epoch: [18] [ 970/2639] eta: 1:24:17 lr: 2.8754383435574158e-05 loss: 0.0531 (0.0540) time: 3.0115 data: 0.0079 max mem: 33408 +Epoch: [18] [ 980/2639] eta: 1:23:47 lr: 2.8749850149227192e-05 loss: 0.0559 (0.0541) time: 3.0020 data: 0.0078 max mem: 33408 +Epoch: [18] [ 990/2639] eta: 1:23:15 lr: 2.874531678345548e-05 loss: 0.0538 (0.0542) time: 2.9860 data: 0.0075 max mem: 33408 +Epoch: [18] [1000/2639] eta: 1:22:45 lr: 2.8740783338243727e-05 loss: 0.0517 (0.0543) time: 3.0073 data: 0.0078 max mem: 33408 +Epoch: [18] [1010/2639] eta: 1:22:14 lr: 2.8736249813576598e-05 loss: 0.0442 (0.0542) time: 2.9995 data: 0.0081 max mem: 33408 +Epoch: [18] [1020/2639] eta: 1:21:45 lr: 2.8731716209438774e-05 loss: 0.0436 (0.0541) time: 3.0319 data: 0.0081 max mem: 33408 +Epoch: [18] [1030/2639] eta: 1:21:15 lr: 2.872718252581494e-05 loss: 0.0436 (0.0540) time: 3.0745 data: 0.0082 max mem: 33408 +Epoch: [18] [1040/2639] eta: 1:20:44 lr: 2.8722648762689763e-05 loss: 0.0514 (0.0540) time: 3.0183 data: 0.0078 max mem: 33408 +Epoch: [18] [1050/2639] eta: 1:20:13 lr: 2.8718114920047896e-05 loss: 0.0586 (0.0542) time: 2.9885 data: 0.0081 max mem: 33408 +Epoch: [18] [1060/2639] eta: 1:19:42 lr: 2.8713580997873995e-05 loss: 0.0569 (0.0545) time: 2.9720 data: 0.0083 max mem: 33408 +Epoch: [18] [1070/2639] eta: 1:19:12 lr: 2.870904699615271e-05 loss: 0.0468 (0.0544) time: 3.0166 data: 0.0079 max mem: 33408 +Epoch: [18] [1080/2639] eta: 1:18:40 lr: 2.8704512914868705e-05 loss: 0.0470 (0.0545) time: 2.9871 data: 0.0081 max mem: 33408 +Epoch: [18] [1090/2639] eta: 1:18:09 lr: 2.86999787540066e-05 loss: 0.0601 (0.0548) time: 2.9522 data: 0.0080 max mem: 33408 +Epoch: [18] [1100/2639] eta: 1:17:39 lr: 2.8695444513551028e-05 loss: 0.0597 (0.0549) time: 3.0157 data: 0.0077 max mem: 33408 +Epoch: [18] [1110/2639] eta: 1:17:08 lr: 2.8690910193486626e-05 loss: 0.0519 (0.0548) time: 3.0091 data: 0.0077 max mem: 33408 +Epoch: [18] [1120/2639] eta: 1:16:38 lr: 2.868637579379802e-05 loss: 0.0461 (0.0548) time: 3.0269 data: 0.0077 max mem: 33408 +Epoch: [18] [1130/2639] eta: 1:16:09 lr: 2.8681841314469814e-05 loss: 0.0437 (0.0547) time: 3.0760 data: 0.0076 max mem: 33408 +Epoch: [18] [1140/2639] eta: 1:15:38 lr: 2.8677306755486626e-05 loss: 0.0501 (0.0548) time: 3.0326 data: 0.0077 max mem: 33408 +Epoch: [18] [1150/2639] eta: 1:15:08 lr: 2.8672772116833065e-05 loss: 0.0431 (0.0547) time: 3.0023 data: 0.0079 max mem: 33408 +Epoch: [18] [1160/2639] eta: 1:14:37 lr: 2.866823739849372e-05 loss: 0.0393 (0.0548) time: 3.0092 data: 0.0082 max mem: 33408 +Epoch: [18] [1170/2639] eta: 1:14:07 lr: 2.8663702600453196e-05 loss: 0.0456 (0.0548) time: 3.0146 data: 0.0084 max mem: 33408 +Epoch: [18] [1180/2639] eta: 1:13:36 lr: 2.8659167722696084e-05 loss: 0.0487 (0.0547) time: 3.0238 data: 0.0084 max mem: 33408 +Epoch: [18] [1190/2639] eta: 1:13:06 lr: 2.865463276520695e-05 loss: 0.0476 (0.0547) time: 3.0248 data: 0.0082 max mem: 33408 +Epoch: [18] [1200/2639] eta: 1:12:35 lr: 2.865009772797038e-05 loss: 0.0435 (0.0546) time: 3.0067 data: 0.0078 max mem: 33408 +Epoch: [18] [1210/2639] eta: 1:12:05 lr: 2.8645562610970955e-05 loss: 0.0523 (0.0547) time: 2.9845 data: 0.0076 max mem: 33408 +Epoch: [18] [1220/2639] eta: 1:11:34 lr: 2.8641027414193232e-05 loss: 0.0542 (0.0548) time: 2.9977 data: 0.0075 max mem: 33408 +Epoch: [18] [1230/2639] eta: 1:11:04 lr: 2.8636492137621764e-05 loss: 0.0534 (0.0548) time: 3.0134 data: 0.0076 max mem: 33408 +Epoch: [18] [1240/2639] eta: 1:10:34 lr: 2.863195678124111e-05 loss: 0.0526 (0.0548) time: 3.0296 data: 0.0080 max mem: 33408 +Epoch: [18] [1250/2639] eta: 1:10:03 lr: 2.8627421345035832e-05 loss: 0.0511 (0.0548) time: 3.0393 data: 0.0078 max mem: 33408 +Epoch: [18] [1260/2639] eta: 1:09:32 lr: 2.8622885828990453e-05 loss: 0.0511 (0.0548) time: 2.9894 data: 0.0078 max mem: 33408 +Epoch: [18] [1270/2639] eta: 1:09:02 lr: 2.861835023308952e-05 loss: 0.0513 (0.0549) time: 2.9736 data: 0.0075 max mem: 33408 +Epoch: [18] [1280/2639] eta: 1:08:31 lr: 2.8613814557317557e-05 loss: 0.0513 (0.0549) time: 3.0143 data: 0.0073 max mem: 33408 +Epoch: [18] [1290/2639] eta: 1:08:01 lr: 2.8609278801659107e-05 loss: 0.0492 (0.0550) time: 3.0175 data: 0.0077 max mem: 33408 +Epoch: [18] [1300/2639] eta: 1:07:31 lr: 2.8604742966098674e-05 loss: 0.0554 (0.0550) time: 3.0025 data: 0.0080 max mem: 33408 +Epoch: [18] [1310/2639] eta: 1:07:01 lr: 2.860020705062077e-05 loss: 0.0511 (0.0549) time: 3.0375 data: 0.0080 max mem: 33408 +Epoch: [18] [1320/2639] eta: 1:06:30 lr: 2.859567105520991e-05 loss: 0.0420 (0.0549) time: 3.0371 data: 0.0076 max mem: 33408 +Epoch: [18] [1330/2639] eta: 1:06:00 lr: 2.8591134979850605e-05 loss: 0.0420 (0.0548) time: 3.0070 data: 0.0074 max mem: 33408 +Epoch: [18] [1340/2639] eta: 1:05:29 lr: 2.858659882452734e-05 loss: 0.0471 (0.0549) time: 2.9987 data: 0.0076 max mem: 33408 +Epoch: [18] [1350/2639] eta: 1:04:59 lr: 2.8582062589224607e-05 loss: 0.0471 (0.0549) time: 3.0085 data: 0.0076 max mem: 33408 +Epoch: [18] [1360/2639] eta: 1:04:29 lr: 2.857752627392689e-05 loss: 0.0462 (0.0549) time: 3.0466 data: 0.0079 max mem: 33408 +Epoch: [18] [1370/2639] eta: 1:03:59 lr: 2.8572989878618683e-05 loss: 0.0487 (0.0548) time: 3.0448 data: 0.0080 max mem: 33408 +Epoch: [18] [1380/2639] eta: 1:03:29 lr: 2.8568453403284445e-05 loss: 0.0487 (0.0547) time: 3.0401 data: 0.0077 max mem: 33408 +Epoch: [18] [1390/2639] eta: 1:02:58 lr: 2.8563916847908644e-05 loss: 0.0468 (0.0547) time: 3.0079 data: 0.0077 max mem: 33408 +Epoch: [18] [1400/2639] eta: 1:02:28 lr: 2.8559380212475757e-05 loss: 0.0468 (0.0548) time: 3.0286 data: 0.0078 max mem: 33408 +Epoch: [18] [1410/2639] eta: 1:01:58 lr: 2.855484349697022e-05 loss: 0.0485 (0.0548) time: 3.0615 data: 0.0076 max mem: 33408 +Epoch: [18] [1420/2639] eta: 1:01:28 lr: 2.8550306701376504e-05 loss: 0.0443 (0.0547) time: 3.0606 data: 0.0074 max mem: 33408 +Epoch: [18] [1430/2639] eta: 1:00:58 lr: 2.854576982567905e-05 loss: 0.0451 (0.0547) time: 3.0450 data: 0.0074 max mem: 33408 +Epoch: [18] [1440/2639] eta: 1:00:28 lr: 2.8541232869862282e-05 loss: 0.0452 (0.0547) time: 3.0277 data: 0.0077 max mem: 33408 +Epoch: [18] [1450/2639] eta: 0:59:57 lr: 2.8536695833910642e-05 loss: 0.0431 (0.0546) time: 3.0142 data: 0.0080 max mem: 33408 +Epoch: [18] [1460/2639] eta: 0:59:27 lr: 2.853215871780857e-05 loss: 0.0438 (0.0547) time: 3.0232 data: 0.0080 max mem: 33408 +Epoch: [18] [1470/2639] eta: 0:58:57 lr: 2.852762152154048e-05 loss: 0.0444 (0.0546) time: 3.0230 data: 0.0080 max mem: 33408 +Epoch: [18] [1480/2639] eta: 0:58:27 lr: 2.852308424509078e-05 loss: 0.0431 (0.0546) time: 3.0367 data: 0.0078 max mem: 33408 +Epoch: [18] [1490/2639] eta: 0:57:57 lr: 2.8518546888443887e-05 loss: 0.0434 (0.0546) time: 3.0630 data: 0.0075 max mem: 33408 +Epoch: [18] [1500/2639] eta: 0:57:27 lr: 2.851400945158421e-05 loss: 0.0434 (0.0545) time: 3.0410 data: 0.0076 max mem: 33408 +Epoch: [18] [1510/2639] eta: 0:56:56 lr: 2.8509471934496146e-05 loss: 0.0469 (0.0545) time: 3.0332 data: 0.0076 max mem: 33408 +Epoch: [18] [1520/2639] eta: 0:56:26 lr: 2.850493433716408e-05 loss: 0.0567 (0.0546) time: 2.9996 data: 0.0077 max mem: 33408 +Epoch: [18] [1530/2639] eta: 0:55:55 lr: 2.8500396659572404e-05 loss: 0.0507 (0.0546) time: 2.9822 data: 0.0080 max mem: 33408 +Epoch: [18] [1540/2639] eta: 0:55:25 lr: 2.8495858901705507e-05 loss: 0.0507 (0.0547) time: 3.0023 data: 0.0079 max mem: 33408 +Epoch: [18] [1550/2639] eta: 0:54:55 lr: 2.849132106354776e-05 loss: 0.0515 (0.0546) time: 3.0463 data: 0.0078 max mem: 33408 +Epoch: [18] [1560/2639] eta: 0:54:25 lr: 2.848678314508353e-05 loss: 0.0433 (0.0546) time: 3.0738 data: 0.0079 max mem: 33408 +Epoch: [18] [1570/2639] eta: 0:53:55 lr: 2.8482245146297175e-05 loss: 0.0433 (0.0546) time: 3.0778 data: 0.0085 max mem: 33408 +Epoch: [18] [1580/2639] eta: 0:53:25 lr: 2.847770706717307e-05 loss: 0.0503 (0.0546) time: 3.0531 data: 0.0089 max mem: 33408 +Epoch: [18] [1590/2639] eta: 0:52:55 lr: 2.8473168907695563e-05 loss: 0.0487 (0.0546) time: 3.0236 data: 0.0084 max mem: 33408 +Epoch: [18] [1600/2639] eta: 0:52:24 lr: 2.8468630667848985e-05 loss: 0.0478 (0.0546) time: 3.0137 data: 0.0081 max mem: 33408 +Epoch: [18] [1610/2639] eta: 0:51:54 lr: 2.8464092347617692e-05 loss: 0.0636 (0.0547) time: 3.0207 data: 0.0076 max mem: 33408 +Epoch: [18] [1620/2639] eta: 0:51:24 lr: 2.8459553946986016e-05 loss: 0.0592 (0.0548) time: 3.0395 data: 0.0075 max mem: 33408 +Epoch: [18] [1630/2639] eta: 0:50:54 lr: 2.8455015465938285e-05 loss: 0.0539 (0.0548) time: 3.0726 data: 0.0077 max mem: 33408 +Epoch: [18] [1640/2639] eta: 0:50:24 lr: 2.845047690445883e-05 loss: 0.0511 (0.0548) time: 3.0632 data: 0.0078 max mem: 33408 +Epoch: [18] [1650/2639] eta: 0:49:53 lr: 2.8445938262531952e-05 loss: 0.0511 (0.0549) time: 3.0150 data: 0.0077 max mem: 33408 +Epoch: [18] [1660/2639] eta: 0:49:23 lr: 2.8441399540141973e-05 loss: 0.0501 (0.0549) time: 2.9952 data: 0.0078 max mem: 33408 +Epoch: [18] [1670/2639] eta: 0:48:53 lr: 2.84368607372732e-05 loss: 0.0540 (0.0550) time: 3.0241 data: 0.0076 max mem: 33408 +Epoch: [18] [1680/2639] eta: 0:48:22 lr: 2.8432321853909936e-05 loss: 0.0515 (0.0550) time: 3.0287 data: 0.0074 max mem: 33408 +Epoch: [18] [1690/2639] eta: 0:47:52 lr: 2.8427782890036464e-05 loss: 0.0467 (0.0550) time: 3.0524 data: 0.0075 max mem: 33408 +Epoch: [18] [1700/2639] eta: 0:47:22 lr: 2.8423243845637078e-05 loss: 0.0509 (0.0549) time: 3.0564 data: 0.0076 max mem: 33408 +Epoch: [18] [1710/2639] eta: 0:46:52 lr: 2.8418704720696066e-05 loss: 0.0509 (0.0550) time: 3.0300 data: 0.0078 max mem: 33408 +Epoch: [18] [1720/2639] eta: 0:46:22 lr: 2.8414165515197698e-05 loss: 0.0497 (0.0550) time: 3.0861 data: 0.0077 max mem: 33408 +Epoch: [18] [1730/2639] eta: 0:45:52 lr: 2.8409626229126245e-05 loss: 0.0496 (0.0551) time: 3.0782 data: 0.0077 max mem: 33408 +Epoch: [18] [1740/2639] eta: 0:45:22 lr: 2.8405086862465974e-05 loss: 0.0442 (0.0551) time: 3.0466 data: 0.0077 max mem: 33408 +Epoch: [18] [1750/2639] eta: 0:44:52 lr: 2.8400547415201147e-05 loss: 0.0431 (0.0551) time: 3.0490 data: 0.0077 max mem: 33408 +Epoch: [18] [1760/2639] eta: 0:44:22 lr: 2.839600788731601e-05 loss: 0.0448 (0.0550) time: 3.0675 data: 0.0079 max mem: 33408 +Epoch: [18] [1770/2639] eta: 0:43:52 lr: 2.8391468278794813e-05 loss: 0.0525 (0.0551) time: 3.0921 data: 0.0076 max mem: 33408 +Epoch: [18] [1780/2639] eta: 0:43:21 lr: 2.8386928589621797e-05 loss: 0.0536 (0.0551) time: 3.0040 data: 0.0075 max mem: 33408 +Epoch: [18] [1790/2639] eta: 0:42:50 lr: 2.8382388819781202e-05 loss: 0.0471 (0.0551) time: 2.9508 data: 0.0083 max mem: 33408 +Epoch: [18] [1800/2639] eta: 0:42:20 lr: 2.8377848969257253e-05 loss: 0.0473 (0.0551) time: 3.0298 data: 0.0084 max mem: 33408 +Epoch: [18] [1810/2639] eta: 0:41:50 lr: 2.8373309038034174e-05 loss: 0.0561 (0.0551) time: 3.0252 data: 0.0086 max mem: 33408 +Epoch: [18] [1820/2639] eta: 0:41:20 lr: 2.836876902609618e-05 loss: 0.0507 (0.0551) time: 3.0093 data: 0.0088 max mem: 33408 +Epoch: [18] [1830/2639] eta: 0:40:49 lr: 2.8364228933427494e-05 loss: 0.0445 (0.0551) time: 3.0339 data: 0.0078 max mem: 33408 +Epoch: [18] [1840/2639] eta: 0:40:19 lr: 2.8359688760012322e-05 loss: 0.0482 (0.0550) time: 3.0540 data: 0.0075 max mem: 33408 +Epoch: [18] [1850/2639] eta: 0:39:49 lr: 2.835514850583484e-05 loss: 0.0482 (0.0550) time: 3.0436 data: 0.0076 max mem: 33408 +Epoch: [18] [1860/2639] eta: 0:39:19 lr: 2.8350608170879266e-05 loss: 0.0518 (0.0550) time: 3.0217 data: 0.0075 max mem: 33408 +Epoch: [18] [1870/2639] eta: 0:38:48 lr: 2.8346067755129784e-05 loss: 0.0510 (0.0550) time: 3.0037 data: 0.0074 max mem: 33408 +Epoch: [18] [1880/2639] eta: 0:38:18 lr: 2.834152725857057e-05 loss: 0.0409 (0.0549) time: 2.9949 data: 0.0075 max mem: 33408 +Epoch: [18] [1890/2639] eta: 0:37:47 lr: 2.8336986681185812e-05 loss: 0.0412 (0.0550) time: 2.9939 data: 0.0076 max mem: 33408 +Epoch: [18] [1900/2639] eta: 0:37:17 lr: 2.8332446022959664e-05 loss: 0.0474 (0.0550) time: 3.0287 data: 0.0076 max mem: 33408 +Epoch: [18] [1910/2639] eta: 0:36:47 lr: 2.8327905283876306e-05 loss: 0.0548 (0.0550) time: 3.0352 data: 0.0078 max mem: 33408 +Epoch: [18] [1920/2639] eta: 0:36:17 lr: 2.832336446391989e-05 loss: 0.0517 (0.0550) time: 3.0439 data: 0.0075 max mem: 33408 +Epoch: [18] [1930/2639] eta: 0:35:46 lr: 2.831882356307457e-05 loss: 0.0534 (0.0552) time: 3.0687 data: 0.0073 max mem: 33408 +Epoch: [18] [1940/2639] eta: 0:35:16 lr: 2.831428258132449e-05 loss: 0.0626 (0.0553) time: 3.0170 data: 0.0075 max mem: 33408 +Epoch: [18] [1950/2639] eta: 0:34:46 lr: 2.8309741518653794e-05 loss: 0.0589 (0.0553) time: 2.9956 data: 0.0078 max mem: 33408 +Epoch: [18] [1960/2639] eta: 0:34:15 lr: 2.830520037504662e-05 loss: 0.0548 (0.0555) time: 3.0020 data: 0.0078 max mem: 33408 +Epoch: [18] [1970/2639] eta: 0:33:45 lr: 2.830065915048709e-05 loss: 0.0637 (0.0555) time: 3.0126 data: 0.0076 max mem: 33408 +Epoch: [18] [1980/2639] eta: 0:33:15 lr: 2.829611784495933e-05 loss: 0.0576 (0.0555) time: 3.0338 data: 0.0078 max mem: 33408 +Epoch: [18] [1990/2639] eta: 0:32:45 lr: 2.829157645844746e-05 loss: 0.0590 (0.0556) time: 3.0745 data: 0.0083 max mem: 33408 +Epoch: [18] [2000/2639] eta: 0:32:14 lr: 2.828703499093559e-05 loss: 0.0523 (0.0556) time: 3.0289 data: 0.0080 max mem: 33408 +Epoch: [18] [2010/2639] eta: 0:31:44 lr: 2.8282493442407826e-05 loss: 0.0517 (0.0557) time: 3.0031 data: 0.0075 max mem: 33408 +Epoch: [18] [2020/2639] eta: 0:31:14 lr: 2.8277951812848265e-05 loss: 0.0660 (0.0558) time: 3.0579 data: 0.0079 max mem: 33408 +Epoch: [18] [2030/2639] eta: 0:30:44 lr: 2.8273410102241e-05 loss: 0.0660 (0.0558) time: 3.0338 data: 0.0079 max mem: 33408 +Epoch: [18] [2040/2639] eta: 0:30:13 lr: 2.8268868310570118e-05 loss: 0.0515 (0.0557) time: 2.9986 data: 0.0078 max mem: 33408 +Epoch: [18] [2050/2639] eta: 0:29:43 lr: 2.826432643781971e-05 loss: 0.0476 (0.0557) time: 2.9987 data: 0.0080 max mem: 33408 +Epoch: [18] [2060/2639] eta: 0:29:12 lr: 2.8259784483973833e-05 loss: 0.0500 (0.0557) time: 2.9822 data: 0.0078 max mem: 33408 +Epoch: [18] [2070/2639] eta: 0:28:42 lr: 2.825524244901657e-05 loss: 0.0486 (0.0557) time: 2.9948 data: 0.0078 max mem: 33408 +Epoch: [18] [2080/2639] eta: 0:28:12 lr: 2.825070033293199e-05 loss: 0.0539 (0.0558) time: 2.9779 data: 0.0079 max mem: 33408 +Epoch: [18] [2090/2639] eta: 0:27:41 lr: 2.8246158135704144e-05 loss: 0.0538 (0.0557) time: 2.9606 data: 0.0079 max mem: 33408 +Epoch: [18] [2100/2639] eta: 0:27:11 lr: 2.824161585731707e-05 loss: 0.0453 (0.0557) time: 2.9791 data: 0.0078 max mem: 33408 +Epoch: [18] [2110/2639] eta: 0:26:41 lr: 2.823707349775483e-05 loss: 0.0479 (0.0557) time: 3.0406 data: 0.0077 max mem: 33408 +Epoch: [18] [2120/2639] eta: 0:26:10 lr: 2.8232531057001464e-05 loss: 0.0559 (0.0557) time: 3.0600 data: 0.0078 max mem: 33408 +Epoch: [18] [2130/2639] eta: 0:25:40 lr: 2.8227988535040994e-05 loss: 0.0526 (0.0557) time: 3.0036 data: 0.0078 max mem: 33408 +Epoch: [18] [2140/2639] eta: 0:25:10 lr: 2.822344593185746e-05 loss: 0.0515 (0.0557) time: 2.9609 data: 0.0078 max mem: 33408 +Epoch: [18] [2150/2639] eta: 0:24:39 lr: 2.8218903247434875e-05 loss: 0.0465 (0.0557) time: 2.9881 data: 0.0080 max mem: 33408 +Epoch: [18] [2160/2639] eta: 0:24:09 lr: 2.8214360481757256e-05 loss: 0.0521 (0.0557) time: 3.0265 data: 0.0082 max mem: 33408 +Epoch: [18] [2170/2639] eta: 0:23:39 lr: 2.8209817634808628e-05 loss: 0.0545 (0.0558) time: 3.0217 data: 0.0083 max mem: 33408 +Epoch: [18] [2180/2639] eta: 0:23:08 lr: 2.820527470657297e-05 loss: 0.0478 (0.0557) time: 3.0115 data: 0.0080 max mem: 33408 +Epoch: [18] [2190/2639] eta: 0:22:38 lr: 2.8200731697034292e-05 loss: 0.0446 (0.0557) time: 3.0017 data: 0.0079 max mem: 33408 +Epoch: [18] [2200/2639] eta: 0:22:08 lr: 2.819618860617658e-05 loss: 0.0452 (0.0557) time: 2.9956 data: 0.0076 max mem: 33408 +Epoch: [18] [2210/2639] eta: 0:21:38 lr: 2.819164543398383e-05 loss: 0.0470 (0.0557) time: 3.0369 data: 0.0072 max mem: 33408 +Epoch: [18] [2220/2639] eta: 0:21:07 lr: 2.8187102180440022e-05 loss: 0.0507 (0.0557) time: 3.0447 data: 0.0080 max mem: 33408 +Epoch: [18] [2230/2639] eta: 0:20:37 lr: 2.818255884552911e-05 loss: 0.0529 (0.0557) time: 3.0763 data: 0.0083 max mem: 33408 +Epoch: [18] [2240/2639] eta: 0:20:07 lr: 2.8178015429235082e-05 loss: 0.0571 (0.0557) time: 3.1055 data: 0.0080 max mem: 33408 +Epoch: [18] [2250/2639] eta: 0:19:37 lr: 2.8173471931541897e-05 loss: 0.0490 (0.0557) time: 3.0271 data: 0.0081 max mem: 33408 +Epoch: [18] [2260/2639] eta: 0:19:07 lr: 2.81689283524335e-05 loss: 0.0481 (0.0557) time: 3.0239 data: 0.0081 max mem: 33408 +Epoch: [18] [2270/2639] eta: 0:18:36 lr: 2.8164384691893842e-05 loss: 0.0466 (0.0556) time: 3.0540 data: 0.0079 max mem: 33408 +Epoch: [18] [2280/2639] eta: 0:18:06 lr: 2.8159840949906868e-05 loss: 0.0438 (0.0556) time: 3.0460 data: 0.0079 max mem: 33408 +Epoch: [18] [2290/2639] eta: 0:17:36 lr: 2.8155297126456527e-05 loss: 0.0449 (0.0556) time: 3.0298 data: 0.0079 max mem: 33408 +Epoch: [18] [2300/2639] eta: 0:17:06 lr: 2.8150753221526742e-05 loss: 0.0425 (0.0556) time: 3.0306 data: 0.0081 max mem: 33408 +Epoch: [18] [2310/2639] eta: 0:16:35 lr: 2.8146209235101428e-05 loss: 0.0425 (0.0556) time: 3.0207 data: 0.0081 max mem: 33408 +Epoch: [18] [2320/2639] eta: 0:16:05 lr: 2.8141665167164516e-05 loss: 0.0385 (0.0555) time: 3.0159 data: 0.0082 max mem: 33408 +Epoch: [18] [2330/2639] eta: 0:15:35 lr: 2.813712101769992e-05 loss: 0.0408 (0.0555) time: 3.0083 data: 0.0080 max mem: 33408 +Epoch: [18] [2340/2639] eta: 0:15:04 lr: 2.8132576786691543e-05 loss: 0.0436 (0.0554) time: 2.9917 data: 0.0078 max mem: 33408 +Epoch: [18] [2350/2639] eta: 0:14:34 lr: 2.8128032474123284e-05 loss: 0.0373 (0.0555) time: 2.9669 data: 0.0080 max mem: 33408 +Epoch: [18] [2360/2639] eta: 0:14:04 lr: 2.812348807997904e-05 loss: 0.0438 (0.0554) time: 3.0034 data: 0.0077 max mem: 33408 +Epoch: [18] [2370/2639] eta: 0:13:33 lr: 2.8118943604242697e-05 loss: 0.0463 (0.0555) time: 2.9812 data: 0.0078 max mem: 33408 +Epoch: [18] [2380/2639] eta: 0:13:03 lr: 2.8114399046898144e-05 loss: 0.0513 (0.0555) time: 2.9696 data: 0.0080 max mem: 33408 +Epoch: [18] [2390/2639] eta: 0:12:33 lr: 2.810985440792926e-05 loss: 0.0489 (0.0555) time: 3.0349 data: 0.0077 max mem: 33408 +Epoch: [18] [2400/2639] eta: 0:12:03 lr: 2.8105309687319902e-05 loss: 0.0489 (0.0555) time: 3.0478 data: 0.0078 max mem: 33408 +Epoch: [18] [2410/2639] eta: 0:11:32 lr: 2.8100764885053944e-05 loss: 0.0492 (0.0555) time: 3.0450 data: 0.0080 max mem: 33408 +Epoch: [18] [2420/2639] eta: 0:11:02 lr: 2.8096220001115246e-05 loss: 0.0514 (0.0555) time: 3.0400 data: 0.0080 max mem: 33408 +Epoch: [18] [2430/2639] eta: 0:10:32 lr: 2.8091675035487664e-05 loss: 0.0478 (0.0554) time: 3.0359 data: 0.0079 max mem: 33408 +Epoch: [18] [2440/2639] eta: 0:10:02 lr: 2.8087129988155026e-05 loss: 0.0449 (0.0554) time: 3.0208 data: 0.0077 max mem: 33408 +Epoch: [18] [2450/2639] eta: 0:09:31 lr: 2.8082584859101185e-05 loss: 0.0439 (0.0554) time: 3.0010 data: 0.0073 max mem: 33408 +Epoch: [18] [2460/2639] eta: 0:09:01 lr: 2.807803964830998e-05 loss: 0.0447 (0.0554) time: 3.0041 data: 0.0075 max mem: 33408 +Epoch: [18] [2470/2639] eta: 0:08:31 lr: 2.8073494355765227e-05 loss: 0.0460 (0.0554) time: 3.0289 data: 0.0076 max mem: 33408 +Epoch: [18] [2480/2639] eta: 0:08:01 lr: 2.8068948981450753e-05 loss: 0.0550 (0.0554) time: 3.0161 data: 0.0075 max mem: 33408 +Epoch: [18] [2490/2639] eta: 0:07:30 lr: 2.8064403525350376e-05 loss: 0.0550 (0.0554) time: 2.9911 data: 0.0079 max mem: 33408 +Epoch: [18] [2500/2639] eta: 0:07:00 lr: 2.8059857987447907e-05 loss: 0.0608 (0.0554) time: 3.0142 data: 0.0084 max mem: 33408 +Epoch: [18] [2510/2639] eta: 0:06:30 lr: 2.805531236772715e-05 loss: 0.0648 (0.0555) time: 3.0123 data: 0.0081 max mem: 33408 +Epoch: [18] [2520/2639] eta: 0:06:00 lr: 2.8050766666171883e-05 loss: 0.0505 (0.0556) time: 3.0048 data: 0.0080 max mem: 33408 +Epoch: [18] [2530/2639] eta: 0:05:29 lr: 2.8046220882765924e-05 loss: 0.0527 (0.0556) time: 3.0169 data: 0.0079 max mem: 33408 +Epoch: [18] [2540/2639] eta: 0:04:59 lr: 2.8041675017493048e-05 loss: 0.0528 (0.0556) time: 3.0216 data: 0.0076 max mem: 33408 +Epoch: [18] [2550/2639] eta: 0:04:29 lr: 2.8037129070337032e-05 loss: 0.0477 (0.0556) time: 3.0215 data: 0.0074 max mem: 33408 +Epoch: [18] [2560/2639] eta: 0:03:59 lr: 2.8032583041281645e-05 loss: 0.0460 (0.0556) time: 3.0164 data: 0.0076 max mem: 33408 +Epoch: [18] [2570/2639] eta: 0:03:28 lr: 2.8028036930310657e-05 loss: 0.0463 (0.0556) time: 3.0091 data: 0.0079 max mem: 33408 +Epoch: [18] [2580/2639] eta: 0:02:58 lr: 2.8023490737407835e-05 loss: 0.0506 (0.0556) time: 2.9985 data: 0.0083 max mem: 33408 +Epoch: [18] [2590/2639] eta: 0:02:28 lr: 2.8018944462556928e-05 loss: 0.0555 (0.0556) time: 3.0212 data: 0.0081 max mem: 33408 +Epoch: [18] [2600/2639] eta: 0:01:57 lr: 2.801439810574168e-05 loss: 0.0456 (0.0556) time: 3.0305 data: 0.0075 max mem: 33408 +Epoch: [18] [2610/2639] eta: 0:01:27 lr: 2.8009851666945842e-05 loss: 0.0512 (0.0556) time: 3.0200 data: 0.0079 max mem: 33408 +Epoch: [18] [2620/2639] eta: 0:00:57 lr: 2.8005305146153138e-05 loss: 0.0532 (0.0556) time: 2.9936 data: 0.0081 max mem: 33408 +Epoch: [18] [2630/2639] eta: 0:00:27 lr: 2.8000758543347315e-05 loss: 0.0532 (0.0556) time: 2.9846 data: 0.0077 max mem: 33408 +Epoch: [18] Total time: 2:13:03 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 2:15:55 time: 3.1696 data: 3.0425 max mem: 33408 +Test: [ 100/2573] eta: 0:04:28 time: 0.0787 data: 0.0014 max mem: 33408 +Test: [ 200/2573] eta: 0:03:44 time: 0.0802 data: 0.0015 max mem: 33408 +Test: [ 300/2573] eta: 0:03:23 time: 0.0824 data: 0.0015 max mem: 33408 +Test: [ 400/2573] eta: 0:03:09 time: 0.0808 data: 0.0015 max mem: 33408 +Test: [ 500/2573] eta: 0:02:57 time: 0.0809 data: 0.0014 max mem: 33408 +Test: [ 600/2573] eta: 0:02:47 time: 0.0792 data: 0.0015 max mem: 33408 +Test: [ 700/2573] eta: 0:02:38 time: 0.0796 data: 0.0014 max mem: 33408 +Test: [ 800/2573] eta: 0:02:29 time: 0.0839 data: 0.0015 max mem: 33408 +Test: [ 900/2573] eta: 0:02:20 time: 0.0809 data: 0.0014 max mem: 33408 +Test: [1000/2573] eta: 0:02:11 time: 0.0814 data: 0.0015 max mem: 33408 +Test: [1100/2573] eta: 0:02:02 time: 0.0808 data: 0.0015 max mem: 33408 +Test: [1200/2573] eta: 0:01:54 time: 0.0805 data: 0.0014 max mem: 33408 +Test: [1300/2573] eta: 0:01:45 time: 0.0813 data: 0.0015 max mem: 33408 +Test: [1400/2573] eta: 0:01:37 time: 0.0801 data: 0.0014 max mem: 33408 +Test: [1500/2573] eta: 0:01:28 time: 0.0817 data: 0.0015 max mem: 33408 +Test: [1600/2573] eta: 0:01:20 time: 0.0838 data: 0.0014 max mem: 33408 +Test: [1700/2573] eta: 0:01:12 time: 0.0786 data: 0.0014 max mem: 33408 +Test: [1800/2573] eta: 0:01:03 time: 0.0829 data: 0.0014 max mem: 33408 +Test: [1900/2573] eta: 0:00:55 time: 0.0789 data: 0.0015 max mem: 33408 +Test: [2000/2573] eta: 0:00:47 time: 0.0809 data: 0.0014 max mem: 33408 +Test: [2100/2573] eta: 0:00:38 time: 0.0829 data: 0.0014 max mem: 33408 +Test: [2200/2573] eta: 0:00:30 time: 0.0824 data: 0.0014 max mem: 33408 +Test: [2300/2573] eta: 0:00:22 time: 0.0825 data: 0.0014 max mem: 33408 +Test: [2400/2573] eta: 0:00:14 time: 0.0775 data: 0.0014 max mem: 33408 +Test: [2500/2573] eta: 0:00:05 time: 0.0809 data: 0.0014 max mem: 33408 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: Total time: 0:03:32 +Final results: +Mean IoU is 63.54 + + precision@0.5 = 71.59 + precision@0.6 = 66.42 + precision@0.7 = 58.91 + precision@0.8 = 47.16 + precision@0.9 = 22.51 + overall IoU = 61.11 + +Average object IoU 63.538532883472534 +Overall IoU 61.10651779174805 +Better epoch: 18 + +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [19] [ 0/2639] eta: 4:05:50 lr: 2.7996666530687395e-05 loss: 0.0469 (0.0469) time: 5.5895 data: 2.3109 max mem: 33408 +Epoch: [19] [ 10/2639] eta: 2:22:04 lr: 2.7992119772011772e-05 loss: 0.0463 (0.0535) time: 3.2424 data: 0.2172 max mem: 33408 +Epoch: [19] [ 20/2639] eta: 2:17:19 lr: 2.7987572931275808e-05 loss: 0.0539 (0.0558) time: 3.0238 data: 0.0079 max mem: 33408 +Epoch: [19] [ 30/2639] eta: 2:14:52 lr: 2.7983026008463205e-05 loss: 0.0516 (0.0522) time: 3.0244 data: 0.0078 max mem: 33408 +Epoch: [19] [ 40/2639] eta: 2:13:56 lr: 2.797847900355765e-05 loss: 0.0467 (0.0528) time: 3.0355 data: 0.0076 max mem: 33408 +Epoch: [19] [ 50/2639] eta: 2:12:48 lr: 2.7973931916542844e-05 loss: 0.0467 (0.0536) time: 3.0405 data: 0.0079 max mem: 33408 +Epoch: [19] [ 60/2639] eta: 2:12:11 lr: 2.796938474740249e-05 loss: 0.0434 (0.0522) time: 3.0410 data: 0.0078 max mem: 33408 +Epoch: [19] [ 70/2639] eta: 2:11:22 lr: 2.796483749612025e-05 loss: 0.0367 (0.0516) time: 3.0442 data: 0.0076 max mem: 33408 +Epoch: [19] [ 80/2639] eta: 2:10:37 lr: 2.7960290162679796e-05 loss: 0.0457 (0.0517) time: 3.0246 data: 0.0082 max mem: 33408 +Epoch: [19] [ 90/2639] eta: 2:09:57 lr: 2.795574274706481e-05 loss: 0.0440 (0.0512) time: 3.0262 data: 0.0084 max mem: 33408 +Epoch: [19] [ 100/2639] eta: 2:09:18 lr: 2.7951195249258954e-05 loss: 0.0417 (0.0509) time: 3.0262 data: 0.0082 max mem: 33408 +Epoch: [19] [ 110/2639] eta: 2:08:49 lr: 2.7946647669245878e-05 loss: 0.0498 (0.0514) time: 3.0448 data: 0.0078 max mem: 33408 +Epoch: [19] [ 120/2639] eta: 2:08:19 lr: 2.7942100007009226e-05 loss: 0.0519 (0.0521) time: 3.0609 data: 0.0075 max mem: 33408 +Epoch: [19] [ 130/2639] eta: 2:07:46 lr: 2.793755226253265e-05 loss: 0.0476 (0.0524) time: 3.0503 data: 0.0075 max mem: 33408 +Epoch: [19] [ 140/2639] eta: 2:07:10 lr: 2.7933004435799792e-05 loss: 0.0472 (0.0524) time: 3.0354 data: 0.0078 max mem: 33408 +Epoch: [19] [ 150/2639] eta: 2:06:34 lr: 2.7928456526794278e-05 loss: 0.0470 (0.0523) time: 3.0219 data: 0.0080 max mem: 33408 +Epoch: [19] [ 160/2639] eta: 2:05:55 lr: 2.7923908535499725e-05 loss: 0.0470 (0.0520) time: 3.0075 data: 0.0082 max mem: 33408 +Epoch: [19] [ 170/2639] eta: 2:05:11 lr: 2.7919360461899764e-05 loss: 0.0462 (0.0519) time: 2.9770 data: 0.0085 max mem: 33408 +Epoch: [19] [ 180/2639] eta: 2:04:32 lr: 2.7914812305978006e-05 loss: 0.0445 (0.0520) time: 2.9686 data: 0.0082 max mem: 33408 +Epoch: [19] [ 190/2639] eta: 2:04:01 lr: 2.7910264067718056e-05 loss: 0.0480 (0.0518) time: 3.0067 data: 0.0078 max mem: 33408 +Epoch: [19] [ 200/2639] eta: 2:03:21 lr: 2.7905715747103507e-05 loss: 0.0521 (0.0519) time: 2.9964 data: 0.0075 max mem: 33408 +Epoch: [19] [ 210/2639] eta: 2:02:49 lr: 2.7901167344117963e-05 loss: 0.0511 (0.0518) time: 2.9892 data: 0.0075 max mem: 33408 +Epoch: [19] [ 220/2639] eta: 2:02:19 lr: 2.7896618858745006e-05 loss: 0.0515 (0.0520) time: 3.0278 data: 0.0079 max mem: 33408 +Epoch: [19] [ 230/2639] eta: 2:01:51 lr: 2.789207029096822e-05 loss: 0.0525 (0.0521) time: 3.0461 data: 0.0082 max mem: 33408 +Epoch: [19] [ 240/2639] eta: 2:01:24 lr: 2.7887521640771176e-05 loss: 0.0512 (0.0525) time: 3.0643 data: 0.0081 max mem: 33408 +Epoch: [19] [ 250/2639] eta: 2:00:51 lr: 2.788297290813745e-05 loss: 0.0552 (0.0526) time: 3.0404 data: 0.0077 max mem: 33408 +Epoch: [19] [ 260/2639] eta: 2:00:23 lr: 2.7878424093050594e-05 loss: 0.0424 (0.0521) time: 3.0324 data: 0.0075 max mem: 33408 +Epoch: [19] [ 270/2639] eta: 1:59:47 lr: 2.787387519549418e-05 loss: 0.0439 (0.0523) time: 3.0148 data: 0.0078 max mem: 33408 +Epoch: [19] [ 280/2639] eta: 1:59:22 lr: 2.7869326215451753e-05 loss: 0.0480 (0.0521) time: 3.0367 data: 0.0078 max mem: 33408 +Epoch: [19] [ 290/2639] eta: 1:58:47 lr: 2.7864777152906847e-05 loss: 0.0409 (0.0517) time: 3.0389 data: 0.0080 max mem: 33408 +Epoch: [19] [ 300/2639] eta: 1:58:21 lr: 2.7860228007843005e-05 loss: 0.0379 (0.0519) time: 3.0346 data: 0.0078 max mem: 33408 +Epoch: [19] [ 310/2639] eta: 1:57:49 lr: 2.785567878024376e-05 loss: 0.0398 (0.0524) time: 3.0530 data: 0.0075 max mem: 33408 +Epoch: [19] [ 320/2639] eta: 1:57:20 lr: 2.785112947009264e-05 loss: 0.0407 (0.0527) time: 3.0299 data: 0.0078 max mem: 33408 +Epoch: [19] [ 330/2639] eta: 1:56:49 lr: 2.7846580077373157e-05 loss: 0.0510 (0.0530) time: 3.0377 data: 0.0076 max mem: 33408 +Epoch: [19] [ 340/2639] eta: 1:56:15 lr: 2.784203060206883e-05 loss: 0.0514 (0.0528) time: 3.0044 data: 0.0076 max mem: 33408 +Epoch: [19] [ 350/2639] eta: 1:55:48 lr: 2.7837481044163167e-05 loss: 0.0441 (0.0527) time: 3.0320 data: 0.0081 max mem: 33408 +Epoch: [19] [ 360/2639] eta: 1:55:17 lr: 2.783293140363966e-05 loss: 0.0456 (0.0526) time: 3.0573 data: 0.0082 max mem: 33408 +Epoch: [19] [ 370/2639] eta: 1:54:45 lr: 2.78283816804818e-05 loss: 0.0473 (0.0525) time: 3.0213 data: 0.0077 max mem: 33408 +Epoch: [19] [ 380/2639] eta: 1:54:15 lr: 2.7823831874673083e-05 loss: 0.0480 (0.0528) time: 3.0263 data: 0.0075 max mem: 33408 +Epoch: [19] [ 390/2639] eta: 1:53:45 lr: 2.7819281986196992e-05 loss: 0.0445 (0.0525) time: 3.0360 data: 0.0077 max mem: 33408 +Epoch: [19] [ 400/2639] eta: 1:53:15 lr: 2.7814732015036997e-05 loss: 0.0403 (0.0523) time: 3.0431 data: 0.0083 max mem: 33408 +Epoch: [19] [ 410/2639] eta: 1:52:44 lr: 2.7810181961176568e-05 loss: 0.0411 (0.0527) time: 3.0319 data: 0.0082 max mem: 33408 +Epoch: [19] [ 420/2639] eta: 1:52:17 lr: 2.780563182459916e-05 loss: 0.0488 (0.0528) time: 3.0542 data: 0.0081 max mem: 33408 +Epoch: [19] [ 430/2639] eta: 1:51:46 lr: 2.780108160528824e-05 loss: 0.0488 (0.0528) time: 3.0634 data: 0.0081 max mem: 33408 +Epoch: [19] [ 440/2639] eta: 1:51:13 lr: 2.7796531303227253e-05 loss: 0.0587 (0.0531) time: 3.0091 data: 0.0074 max mem: 33408 +Epoch: [19] [ 450/2639] eta: 1:50:43 lr: 2.779198091839964e-05 loss: 0.0491 (0.0529) time: 3.0161 data: 0.0076 max mem: 33408 +Epoch: [19] [ 460/2639] eta: 1:50:12 lr: 2.7787430450788837e-05 loss: 0.0442 (0.0529) time: 3.0305 data: 0.0078 max mem: 33408 +Epoch: [19] [ 470/2639] eta: 1:49:45 lr: 2.7782879900378283e-05 loss: 0.0453 (0.0528) time: 3.0660 data: 0.0079 max mem: 33408 +Epoch: [19] [ 480/2639] eta: 1:49:15 lr: 2.7778329267151394e-05 loss: 0.0510 (0.0528) time: 3.0751 data: 0.0079 max mem: 33408 +Epoch: [19] [ 490/2639] eta: 1:48:45 lr: 2.7773778551091583e-05 loss: 0.0481 (0.0526) time: 3.0358 data: 0.0076 max mem: 33408 +Epoch: [19] [ 500/2639] eta: 1:48:12 lr: 2.7769227752182275e-05 loss: 0.0409 (0.0529) time: 3.0098 data: 0.0077 max mem: 33408 +Epoch: [19] [ 510/2639] eta: 1:47:45 lr: 2.776467687040687e-05 loss: 0.0416 (0.0530) time: 3.0446 data: 0.0079 max mem: 33408 +Epoch: [19] [ 520/2639] eta: 1:47:14 lr: 2.7760125905748763e-05 loss: 0.0476 (0.0530) time: 3.0679 data: 0.0078 max mem: 33408 +Epoch: [19] [ 530/2639] eta: 1:46:44 lr: 2.7755574858191357e-05 loss: 0.0476 (0.0529) time: 3.0451 data: 0.0075 max mem: 33408 +Epoch: [19] [ 540/2639] eta: 1:46:15 lr: 2.775102372771802e-05 loss: 0.0479 (0.0528) time: 3.0632 data: 0.0076 max mem: 33408 +Epoch: [19] [ 550/2639] eta: 1:45:43 lr: 2.7746472514312144e-05 loss: 0.0493 (0.0528) time: 3.0336 data: 0.0079 max mem: 33408 +Epoch: [19] [ 560/2639] eta: 1:45:16 lr: 2.7741921217957105e-05 loss: 0.0452 (0.0527) time: 3.0584 data: 0.0078 max mem: 33408 +Epoch: [19] [ 570/2639] eta: 1:44:44 lr: 2.7737369838636274e-05 loss: 0.0452 (0.0528) time: 3.0558 data: 0.0079 max mem: 33408 +Epoch: [19] [ 580/2639] eta: 1:44:17 lr: 2.7732818376332987e-05 loss: 0.0466 (0.0527) time: 3.0579 data: 0.0078 max mem: 33408 +Epoch: [19] [ 590/2639] eta: 1:43:47 lr: 2.772826683103062e-05 loss: 0.0474 (0.0527) time: 3.0906 data: 0.0075 max mem: 33408 +Epoch: [19] [ 600/2639] eta: 1:43:14 lr: 2.7723715202712526e-05 loss: 0.0464 (0.0526) time: 3.0042 data: 0.0074 max mem: 33408 +Epoch: [19] [ 610/2639] eta: 1:42:43 lr: 2.7719163491362026e-05 loss: 0.0451 (0.0525) time: 2.9831 data: 0.0074 max mem: 33408 +Epoch: [19] [ 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33408 +Epoch: [19] [ 700/2639] eta: 1:38:02 lr: 2.7678194349997943e-05 loss: 0.0439 (0.0521) time: 3.0265 data: 0.0071 max mem: 33408 +Epoch: [19] [ 710/2639] eta: 1:37:31 lr: 2.767364180740587e-05 loss: 0.0425 (0.0520) time: 3.0158 data: 0.0074 max mem: 33408 +Epoch: [19] [ 720/2639] eta: 1:37:01 lr: 2.766908918159774e-05 loss: 0.0412 (0.0520) time: 3.0141 data: 0.0078 max mem: 33408 +Epoch: [19] [ 730/2639] eta: 1:36:29 lr: 2.766453647255682e-05 loss: 0.0430 (0.0519) time: 3.0158 data: 0.0075 max mem: 33408 +Epoch: [19] [ 740/2639] eta: 1:35:59 lr: 2.765998368026635e-05 loss: 0.0470 (0.0520) time: 3.0105 data: 0.0074 max mem: 33408 +Epoch: [19] [ 750/2639] eta: 1:35:27 lr: 2.7655430804709592e-05 loss: 0.0475 (0.0520) time: 3.0068 data: 0.0075 max mem: 33408 +Epoch: [19] [ 760/2639] eta: 1:34:58 lr: 2.76508778458698e-05 loss: 0.0508 (0.0521) time: 3.0241 data: 0.0078 max mem: 33408 +Epoch: [19] [ 770/2639] eta: 1:34:26 lr: 2.7646324803730213e-05 loss: 0.0462 (0.0520) time: 3.0098 data: 0.0078 max mem: 33408 +Epoch: [19] [ 780/2639] eta: 1:33:55 lr: 2.7641771678274054e-05 loss: 0.0462 (0.0520) time: 2.9891 data: 0.0077 max mem: 33408 +Epoch: [19] [ 790/2639] eta: 1:33:24 lr: 2.7637218469484548e-05 loss: 0.0472 (0.0519) time: 3.0015 data: 0.0079 max mem: 33408 +Epoch: [19] [ 800/2639] eta: 1:32:52 lr: 2.7632665177344923e-05 loss: 0.0506 (0.0521) time: 2.9837 data: 0.0077 max mem: 33408 +Epoch: [19] [ 810/2639] eta: 1:32:21 lr: 2.762811180183839e-05 loss: 0.0483 (0.0521) time: 2.9829 data: 0.0079 max mem: 33408 +Epoch: [19] [ 820/2639] eta: 1:31:49 lr: 2.762355834294816e-05 loss: 0.0511 (0.0522) time: 2.9704 data: 0.0079 max mem: 33408 +Epoch: [19] [ 830/2639] eta: 1:31:18 lr: 2.7619004800657418e-05 loss: 0.0505 (0.0523) time: 2.9904 data: 0.0079 max mem: 33408 +Epoch: [19] [ 840/2639] eta: 1:30:47 lr: 2.7614451174949367e-05 loss: 0.0416 (0.0523) time: 2.9892 data: 0.0080 max mem: 33408 +Epoch: [19] [ 850/2639] eta: 1:30:16 lr: 2.76098974658072e-05 loss: 0.0481 (0.0525) time: 2.9899 data: 0.0083 max mem: 33408 +Epoch: [19] [ 860/2639] eta: 1:29:45 lr: 2.7605343673214094e-05 loss: 0.0530 (0.0525) time: 3.0091 data: 0.0082 max mem: 33408 +Epoch: [19] [ 870/2639] eta: 1:29:15 lr: 2.7600789797153222e-05 loss: 0.0462 (0.0525) time: 3.0155 data: 0.0076 max mem: 33408 +Epoch: [19] [ 880/2639] eta: 1:28:46 lr: 2.7596235837607748e-05 loss: 0.0437 (0.0525) time: 3.0532 data: 0.0076 max mem: 33408 +Epoch: [19] [ 890/2639] eta: 1:28:15 lr: 2.7591681794560842e-05 loss: 0.0436 (0.0524) time: 3.0382 data: 0.0078 max mem: 33408 +Epoch: [19] [ 900/2639] eta: 1:27:45 lr: 2.758712766799566e-05 loss: 0.0498 (0.0525) time: 3.0150 data: 0.0082 max mem: 33408 +Epoch: [19] [ 910/2639] eta: 1:27:14 lr: 2.7582573457895334e-05 loss: 0.0540 (0.0526) time: 3.0201 data: 0.0083 max mem: 33408 +Epoch: [19] [ 920/2639] eta: 1:26:44 lr: 2.757801916424302e-05 loss: 0.0481 (0.0528) time: 3.0268 data: 0.0080 max mem: 33408 +Epoch: [19] [ 930/2639] eta: 1:26:15 lr: 2.7573464787021857e-05 loss: 0.0525 (0.0528) time: 3.0745 data: 0.0078 max mem: 33408 +Epoch: [19] [ 940/2639] eta: 1:25:44 lr: 2.756891032621497e-05 loss: 0.0523 (0.0528) time: 3.0517 data: 0.0077 max mem: 33408 +Epoch: [19] [ 950/2639] eta: 1:25:16 lr: 2.7564355781805468e-05 loss: 0.0523 (0.0528) time: 3.0575 data: 0.0080 max mem: 33408 +Epoch: [19] [ 960/2639] eta: 1:24:46 lr: 2.7559801153776483e-05 loss: 0.0477 (0.0528) time: 3.0926 data: 0.0084 max mem: 33408 +Epoch: [19] [ 970/2639] eta: 1:24:15 lr: 2.7555246442111126e-05 loss: 0.0462 (0.0528) time: 3.0258 data: 0.0085 max mem: 33408 +Epoch: [19] [ 980/2639] eta: 1:23:46 lr: 2.7550691646792494e-05 loss: 0.0477 (0.0527) time: 3.0296 data: 0.0084 max mem: 33408 +Epoch: [19] [ 990/2639] eta: 1:23:14 lr: 2.754613676780367e-05 loss: 0.0458 (0.0527) time: 3.0128 data: 0.0082 max mem: 33408 +Epoch: [19] [1000/2639] eta: 1:22:45 lr: 2.7541581805127763e-05 loss: 0.0464 (0.0527) time: 3.0274 data: 0.0078 max mem: 33408 +Epoch: [19] [1010/2639] eta: 1:22:15 lr: 2.7537026758747854e-05 loss: 0.0478 (0.0527) time: 3.0640 data: 0.0079 max mem: 33408 +Epoch: [19] [1020/2639] eta: 1:21:45 lr: 2.753247162864702e-05 loss: 0.0430 (0.0526) time: 3.0392 data: 0.0080 max mem: 33408 +Epoch: [19] [1030/2639] eta: 1:21:14 lr: 2.752791641480833e-05 loss: 0.0464 (0.0526) time: 3.0365 data: 0.0077 max mem: 33408 +Epoch: [19] [1040/2639] eta: 1:20:44 lr: 2.7523361117214836e-05 loss: 0.0498 (0.0526) time: 3.0299 data: 0.0077 max mem: 33408 +Epoch: [19] [1050/2639] eta: 1:20:14 lr: 2.7518805735849605e-05 loss: 0.0415 (0.0525) time: 3.0454 data: 0.0077 max mem: 33408 +Epoch: [19] [1060/2639] eta: 1:19:43 lr: 2.7514250270695696e-05 loss: 0.0432 (0.0525) time: 3.0039 data: 0.0081 max mem: 33408 +Epoch: [19] [1070/2639] eta: 1:19:12 lr: 2.7509694721736146e-05 loss: 0.0541 (0.0526) time: 2.9671 data: 0.0083 max mem: 33408 +Epoch: [19] [1080/2639] eta: 1:18:41 lr: 2.7505139088953986e-05 loss: 0.0541 (0.0528) time: 2.9815 data: 0.0080 max mem: 33408 +Epoch: [19] [1090/2639] eta: 1:18:11 lr: 2.750058337233225e-05 loss: 0.0435 (0.0527) time: 3.0093 data: 0.0081 max mem: 33408 +Epoch: [19] [1100/2639] eta: 1:17:41 lr: 2.7496027571853972e-05 loss: 0.0397 (0.0526) time: 3.0705 data: 0.0083 max mem: 33408 +Epoch: [19] [1110/2639] eta: 1:17:10 lr: 2.7491471687502162e-05 loss: 0.0439 (0.0528) time: 3.0322 data: 0.0078 max mem: 33408 +Epoch: [19] [1120/2639] eta: 1:16:40 lr: 2.748691571925983e-05 loss: 0.0576 (0.0528) time: 3.0001 data: 0.0079 max mem: 33408 +Epoch: [19] [1130/2639] eta: 1:16:11 lr: 2.7482359667109987e-05 loss: 0.0530 (0.0528) time: 3.0672 data: 0.0084 max mem: 33408 +Epoch: [19] [1140/2639] eta: 1:15:40 lr: 2.747780353103563e-05 loss: 0.0445 (0.0528) time: 3.0523 data: 0.0082 max mem: 33408 +Epoch: [19] [1150/2639] eta: 1:15:10 lr: 2.7473247311019746e-05 loss: 0.0445 (0.0528) time: 3.0122 data: 0.0077 max mem: 33408 +Epoch: [19] [1160/2639] eta: 1:14:40 lr: 2.7468691007045317e-05 loss: 0.0397 (0.0527) time: 3.0587 data: 0.0075 max mem: 33408 +Epoch: [19] [1170/2639] eta: 1:14:10 lr: 2.7464134619095327e-05 loss: 0.0382 (0.0527) time: 3.0744 data: 0.0079 max mem: 33408 +Epoch: [19] [1180/2639] eta: 1:13:40 lr: 2.7459578147152754e-05 loss: 0.0418 (0.0527) time: 3.0656 data: 0.0081 max mem: 33408 +Epoch: [19] [1190/2639] eta: 1:13:10 lr: 2.745502159120056e-05 loss: 0.0406 (0.0527) time: 3.0487 data: 0.0078 max mem: 33408 +Epoch: [19] [1200/2639] eta: 1:12:40 lr: 2.745046495122169e-05 loss: 0.0380 (0.0528) time: 3.0269 data: 0.0075 max mem: 33408 +Epoch: [19] [1210/2639] eta: 1:12:09 lr: 2.744590822719911e-05 loss: 0.0388 (0.0528) time: 3.0346 data: 0.0078 max mem: 33408 +Epoch: [19] [1220/2639] eta: 1:11:39 lr: 2.744135141911577e-05 loss: 0.0393 (0.0527) time: 3.0351 data: 0.0078 max mem: 33408 +Epoch: [19] [1230/2639] eta: 1:11:09 lr: 2.74367945269546e-05 loss: 0.0462 (0.0527) time: 3.0285 data: 0.0079 max mem: 33408 +Epoch: [19] [1240/2639] eta: 1:10:39 lr: 2.7432237550698524e-05 loss: 0.0509 (0.0528) time: 3.0256 data: 0.0085 max mem: 33408 +Epoch: [19] [1250/2639] eta: 1:10:08 lr: 2.742768049033048e-05 loss: 0.0449 (0.0527) time: 3.0418 data: 0.0081 max mem: 33408 +Epoch: [19] [1260/2639] eta: 1:09:38 lr: 2.742312334583339e-05 loss: 0.0433 (0.0527) time: 3.0236 data: 0.0082 max mem: 33408 +Epoch: [19] [1270/2639] eta: 1:09:08 lr: 2.7418566117190165e-05 loss: 0.0535 (0.0528) time: 3.0303 data: 0.0081 max mem: 33408 +Epoch: [19] [1280/2639] eta: 1:08:37 lr: 2.74140088043837e-05 loss: 0.0587 (0.0529) time: 3.0393 data: 0.0077 max mem: 33408 +Epoch: [19] [1290/2639] eta: 1:08:08 lr: 2.7409451407396903e-05 loss: 0.0499 (0.0528) time: 3.0520 data: 0.0076 max mem: 33408 +Epoch: [19] [1300/2639] eta: 1:07:37 lr: 2.740489392621266e-05 loss: 0.0499 (0.0528) time: 3.0303 data: 0.0079 max mem: 33408 +Epoch: [19] [1310/2639] eta: 1:07:06 lr: 2.7400336360813868e-05 loss: 0.0498 (0.0528) time: 2.9906 data: 0.0080 max mem: 33408 +Epoch: [19] [1320/2639] eta: 1:06:36 lr: 2.73957787111834e-05 loss: 0.0430 (0.0528) time: 3.0385 data: 0.0075 max mem: 33408 +Epoch: [19] [1330/2639] eta: 1:06:05 lr: 2.7391220977304122e-05 loss: 0.0443 (0.0528) time: 3.0179 data: 0.0080 max mem: 33408 +Epoch: [19] [1340/2639] eta: 1:05:35 lr: 2.738666315915891e-05 loss: 0.0443 (0.0528) time: 3.0038 data: 0.0082 max mem: 33408 +Epoch: [19] [1350/2639] eta: 1:05:05 lr: 2.738210525673062e-05 loss: 0.0405 (0.0529) time: 3.0345 data: 0.0078 max mem: 33408 +Epoch: [19] [1360/2639] eta: 1:04:34 lr: 2.7377547270002108e-05 loss: 0.0409 (0.0528) time: 3.0181 data: 0.0078 max mem: 33408 +Epoch: [19] [1370/2639] eta: 1:04:05 lr: 2.7372989198956205e-05 loss: 0.0484 (0.0528) time: 3.0644 data: 0.0077 max mem: 33408 +Epoch: [19] [1380/2639] eta: 1:03:35 lr: 2.736843104357577e-05 loss: 0.0465 (0.0527) time: 3.0821 data: 0.0078 max mem: 33408 +Epoch: [19] [1390/2639] eta: 1:03:04 lr: 2.7363872803843626e-05 loss: 0.0454 (0.0527) time: 3.0170 data: 0.0078 max mem: 33408 +Epoch: [19] [1400/2639] eta: 1:02:34 lr: 2.7359314479742604e-05 loss: 0.0454 (0.0527) time: 3.0262 data: 0.0077 max mem: 33408 +Epoch: [19] [1410/2639] eta: 1:02:04 lr: 2.735475607125551e-05 loss: 0.0450 (0.0528) time: 3.0463 data: 0.0080 max mem: 33408 +Epoch: [19] [1420/2639] eta: 1:01:34 lr: 2.7350197578365172e-05 loss: 0.0495 (0.0529) time: 3.0363 data: 0.0078 max mem: 33408 +Epoch: [19] [1430/2639] eta: 1:01:04 lr: 2.734563900105439e-05 loss: 0.0514 (0.0529) time: 3.0498 data: 0.0078 max mem: 33408 +Epoch: [19] [1440/2639] eta: 1:00:33 lr: 2.734108033930597e-05 loss: 0.0504 (0.0529) time: 3.0290 data: 0.0081 max mem: 33408 +Epoch: [19] [1450/2639] eta: 1:00:02 lr: 2.7336521593102687e-05 loss: 0.0445 (0.0529) time: 2.9859 data: 0.0081 max mem: 33408 +Epoch: [19] [1460/2639] eta: 0:59:33 lr: 2.7331962762427337e-05 loss: 0.0474 (0.0530) time: 3.0398 data: 0.0084 max mem: 33408 +Epoch: [19] [1470/2639] eta: 0:59:03 lr: 2.732740384726271e-05 loss: 0.0453 (0.0529) time: 3.1034 data: 0.0085 max mem: 33408 +Epoch: [19] [1480/2639] eta: 0:58:32 lr: 2.732284484759156e-05 loss: 0.0419 (0.0529) time: 3.0597 data: 0.0083 max mem: 33408 +Epoch: [19] [1490/2639] eta: 0:58:02 lr: 2.7318285763396668e-05 loss: 0.0483 (0.0530) time: 3.0227 data: 0.0086 max mem: 33408 +Epoch: [19] [1500/2639] eta: 0:57:32 lr: 2.7313726594660782e-05 loss: 0.0514 (0.0531) time: 3.0299 data: 0.0085 max mem: 33408 +Epoch: [19] [1510/2639] eta: 0:57:02 lr: 2.7309167341366654e-05 loss: 0.0514 (0.0531) time: 3.0510 data: 0.0080 max mem: 33408 +Epoch: [19] [1520/2639] eta: 0:56:32 lr: 2.7304608003497045e-05 loss: 0.0491 (0.0531) time: 3.0706 data: 0.0078 max mem: 33408 +Epoch: [19] [1530/2639] eta: 0:56:01 lr: 2.7300048581034682e-05 loss: 0.0473 (0.0532) time: 3.0373 data: 0.0079 max mem: 33408 +Epoch: [19] [1540/2639] eta: 0:55:31 lr: 2.7295489073962286e-05 loss: 0.0499 (0.0532) time: 3.0176 data: 0.0077 max mem: 33408 +Epoch: [19] [1550/2639] eta: 0:55:01 lr: 2.7290929482262606e-05 loss: 0.0507 (0.0532) time: 3.0504 data: 0.0075 max mem: 33408 +Epoch: [19] [1560/2639] eta: 0:54:30 lr: 2.728636980591835e-05 loss: 0.0507 (0.0532) time: 3.0447 data: 0.0078 max mem: 33408 +Epoch: [19] [1570/2639] eta: 0:54:00 lr: 2.7281810044912226e-05 loss: 0.0511 (0.0532) time: 3.0045 data: 0.0079 max mem: 33408 +Epoch: [19] [1580/2639] eta: 0:53:29 lr: 2.727725019922694e-05 loss: 0.0479 (0.0532) time: 2.9872 data: 0.0080 max mem: 33408 +Epoch: [19] [1590/2639] eta: 0:52:59 lr: 2.727269026884519e-05 loss: 0.0428 (0.0531) time: 2.9985 data: 0.0080 max mem: 33408 +Epoch: [19] [1600/2639] eta: 0:52:28 lr: 2.7268130253749685e-05 loss: 0.0484 (0.0532) time: 2.9960 data: 0.0081 max mem: 33408 +Epoch: [19] [1610/2639] eta: 0:51:58 lr: 2.726357015392309e-05 loss: 0.0452 (0.0532) time: 3.0403 data: 0.0079 max mem: 33408 +Epoch: [19] [1620/2639] eta: 0:51:28 lr: 2.7259009969348082e-05 loss: 0.0443 (0.0532) time: 3.0755 data: 0.0075 max mem: 33408 +Epoch: [19] [1630/2639] eta: 0:50:58 lr: 2.725444970000734e-05 loss: 0.0386 (0.0531) time: 3.0457 data: 0.0076 max mem: 33408 +Epoch: [19] [1640/2639] eta: 0:50:28 lr: 2.7249889345883534e-05 loss: 0.0419 (0.0531) time: 3.1106 data: 0.0077 max mem: 33408 +Epoch: [19] [1650/2639] eta: 0:49:58 lr: 2.7245328906959317e-05 loss: 0.0479 (0.0531) time: 3.1044 data: 0.0075 max mem: 33408 +Epoch: [19] [1660/2639] eta: 0:49:27 lr: 2.7240768383217337e-05 loss: 0.0451 (0.0531) time: 3.0011 data: 0.0076 max mem: 33408 +Epoch: [19] [1670/2639] eta: 0:48:57 lr: 2.7236207774640237e-05 loss: 0.0494 (0.0531) time: 2.9893 data: 0.0075 max mem: 33408 +Epoch: [19] [1680/2639] eta: 0:48:26 lr: 2.7231647081210663e-05 loss: 0.0494 (0.0531) time: 2.9912 data: 0.0075 max mem: 33408 +Epoch: [19] [1690/2639] eta: 0:47:56 lr: 2.722708630291124e-05 loss: 0.0510 (0.0531) time: 2.9882 data: 0.0077 max mem: 33408 +Epoch: [19] [1700/2639] eta: 0:47:26 lr: 2.7222525439724595e-05 loss: 0.0490 (0.0531) time: 3.0605 data: 0.0075 max mem: 33408 +Epoch: [19] [1710/2639] eta: 0:46:56 lr: 2.7217964491633336e-05 loss: 0.0399 (0.0531) time: 3.0912 data: 0.0076 max mem: 33408 +Epoch: [19] [1720/2639] eta: 0:46:25 lr: 2.7213403458620085e-05 loss: 0.0475 (0.0532) time: 3.0241 data: 0.0079 max mem: 33408 +Epoch: [19] [1730/2639] eta: 0:45:55 lr: 2.720884234066744e-05 loss: 0.0544 (0.0532) time: 3.0348 data: 0.0078 max mem: 33408 +Epoch: [19] [1740/2639] eta: 0:45:25 lr: 2.7204281137758004e-05 loss: 0.0544 (0.0533) time: 3.0667 data: 0.0080 max mem: 33408 +Epoch: [19] [1750/2639] eta: 0:44:55 lr: 2.7199719849874355e-05 loss: 0.0663 (0.0533) time: 3.0607 data: 0.0079 max mem: 33408 +Epoch: [19] [1760/2639] eta: 0:44:25 lr: 2.7195158476999085e-05 loss: 0.0553 (0.0534) time: 3.0389 data: 0.0076 max mem: 33408 +Epoch: [19] [1770/2639] eta: 0:43:54 lr: 2.719059701911477e-05 loss: 0.0486 (0.0534) time: 3.0151 data: 0.0080 max mem: 33408 +Epoch: [19] [1780/2639] eta: 0:43:24 lr: 2.7186035476203986e-05 loss: 0.0483 (0.0534) time: 3.0205 data: 0.0081 max mem: 33408 +Epoch: [19] [1790/2639] eta: 0:42:53 lr: 2.7181473848249276e-05 loss: 0.0468 (0.0534) time: 3.0226 data: 0.0079 max mem: 33408 +Epoch: [19] [1800/2639] eta: 0:42:23 lr: 2.717691213523321e-05 loss: 0.0409 (0.0534) time: 3.0320 data: 0.0074 max mem: 33408 +Epoch: [19] [1810/2639] eta: 0:41:53 lr: 2.717235033713834e-05 loss: 0.0397 (0.0534) time: 3.0121 data: 0.0074 max mem: 33408 +Epoch: [19] [1820/2639] eta: 0:41:22 lr: 2.7167788453947208e-05 loss: 0.0519 (0.0534) time: 3.0244 data: 0.0075 max mem: 33408 +Epoch: [19] [1830/2639] eta: 0:40:52 lr: 2.7163226485642328e-05 loss: 0.0524 (0.0534) time: 3.0464 data: 0.0078 max mem: 33408 +Epoch: [19] [1840/2639] eta: 0:40:22 lr: 2.7158664432206255e-05 loss: 0.0546 (0.0534) time: 3.0575 data: 0.0078 max mem: 33408 +Epoch: [19] [1850/2639] eta: 0:39:52 lr: 2.71541022936215e-05 loss: 0.0508 (0.0535) time: 3.0508 data: 0.0075 max mem: 33408 +Epoch: [19] [1860/2639] eta: 0:39:21 lr: 2.7149540069870587e-05 loss: 0.0484 (0.0535) time: 3.0189 data: 0.0074 max mem: 33408 +Epoch: [19] [1870/2639] eta: 0:38:51 lr: 2.7144977760936e-05 loss: 0.0532 (0.0535) time: 2.9951 data: 0.0072 max mem: 33408 +Epoch: [19] [1880/2639] eta: 0:38:21 lr: 2.7140415366800265e-05 loss: 0.0510 (0.0535) time: 3.0188 data: 0.0076 max mem: 33408 +Epoch: [19] [1890/2639] eta: 0:37:50 lr: 2.7135852887445866e-05 loss: 0.0425 (0.0535) time: 3.0218 data: 0.0081 max mem: 33408 +Epoch: [19] [1900/2639] eta: 0:37:20 lr: 2.7131290322855297e-05 loss: 0.0459 (0.0534) time: 3.0005 data: 0.0080 max mem: 33408 +Epoch: [19] [1910/2639] eta: 0:36:49 lr: 2.7126727673011027e-05 loss: 0.0448 (0.0534) time: 3.0227 data: 0.0077 max mem: 33408 +Epoch: [19] [1920/2639] eta: 0:36:19 lr: 2.7122164937895534e-05 loss: 0.0416 (0.0533) time: 3.0088 data: 0.0078 max mem: 33408 +Epoch: [19] [1930/2639] eta: 0:35:49 lr: 2.7117602117491288e-05 loss: 0.0465 (0.0533) time: 3.0151 data: 0.0076 max mem: 33408 +Epoch: [19] [1940/2639] eta: 0:35:18 lr: 2.711303921178075e-05 loss: 0.0480 (0.0533) time: 3.0236 data: 0.0078 max mem: 33408 +Epoch: [19] [1950/2639] eta: 0:34:48 lr: 2.7108476220746365e-05 loss: 0.0480 (0.0533) time: 3.0453 data: 0.0076 max mem: 33408 +Epoch: [19] [1960/2639] eta: 0:34:18 lr: 2.710391314437059e-05 loss: 0.0485 (0.0534) time: 3.0358 data: 0.0076 max mem: 33408 +Epoch: [19] [1970/2639] eta: 0:33:47 lr: 2.709934998263586e-05 loss: 0.0490 (0.0534) time: 3.0400 data: 0.0079 max mem: 33408 +Epoch: [19] [1980/2639] eta: 0:33:17 lr: 2.7094786735524595e-05 loss: 0.0562 (0.0535) time: 3.0253 data: 0.0078 max mem: 33408 +Epoch: [19] [1990/2639] eta: 0:32:47 lr: 2.7090223403019245e-05 loss: 0.0583 (0.0535) time: 3.0176 data: 0.0078 max mem: 33408 +Epoch: [19] [2000/2639] eta: 0:32:16 lr: 2.7085659985102206e-05 loss: 0.0464 (0.0535) time: 3.0203 data: 0.0078 max mem: 33408 +Epoch: [19] [2010/2639] eta: 0:31:46 lr: 2.70810964817559e-05 loss: 0.0514 (0.0536) time: 3.0177 data: 0.0078 max mem: 33408 +Epoch: [19] [2020/2639] eta: 0:31:16 lr: 2.7076532892962734e-05 loss: 0.0552 (0.0538) time: 3.0338 data: 0.0078 max mem: 33408 +Epoch: [19] [2030/2639] eta: 0:30:46 lr: 2.7071969218705106e-05 loss: 0.0504 (0.0539) time: 3.0704 data: 0.0079 max mem: 33408 +Epoch: [19] [2040/2639] eta: 0:30:15 lr: 2.7067405458965393e-05 loss: 0.0511 (0.0539) time: 3.0998 data: 0.0078 max mem: 33408 +Epoch: [19] [2050/2639] eta: 0:29:45 lr: 2.7062841613725992e-05 loss: 0.0511 (0.0539) time: 3.0338 data: 0.0076 max mem: 33408 +Epoch: [19] [2060/2639] eta: 0:29:15 lr: 2.705827768296928e-05 loss: 0.0525 (0.0539) time: 3.0344 data: 0.0073 max mem: 33408 +Epoch: [19] [2070/2639] eta: 0:28:44 lr: 2.705371366667762e-05 loss: 0.0444 (0.0539) time: 3.0114 data: 0.0071 max mem: 33408 +Epoch: [19] [2080/2639] eta: 0:28:14 lr: 2.7049149564833383e-05 loss: 0.0477 (0.0539) time: 2.9687 data: 0.0075 max mem: 33408 +Epoch: [19] [2090/2639] eta: 0:27:44 lr: 2.7044585377418912e-05 loss: 0.0547 (0.0539) time: 2.9988 data: 0.0079 max mem: 33408 +Epoch: [19] [2100/2639] eta: 0:27:13 lr: 2.7040021104416573e-05 loss: 0.0530 (0.0539) time: 3.0140 data: 0.0078 max mem: 33408 +Epoch: [19] [2110/2639] eta: 0:26:43 lr: 2.7035456745808707e-05 loss: 0.0530 (0.0539) time: 3.0123 data: 0.0073 max mem: 33408 +Epoch: [19] [2120/2639] eta: 0:26:12 lr: 2.703089230157763e-05 loss: 0.0484 (0.0539) time: 2.9927 data: 0.0077 max mem: 33408 +Epoch: [19] [2130/2639] eta: 0:25:42 lr: 2.702632777170569e-05 loss: 0.0454 (0.0538) time: 3.0021 data: 0.0079 max mem: 33408 +Epoch: [19] [2140/2639] eta: 0:25:12 lr: 2.70217631561752e-05 loss: 0.0429 (0.0538) time: 3.0361 data: 0.0079 max mem: 33408 +Epoch: [19] [2150/2639] eta: 0:24:42 lr: 2.7017198454968478e-05 loss: 0.0428 (0.0538) time: 3.0551 data: 0.0080 max mem: 33408 +Epoch: [19] [2160/2639] eta: 0:24:11 lr: 2.7012633668067828e-05 loss: 0.0469 (0.0538) time: 3.0639 data: 0.0078 max mem: 33408 +Epoch: [19] [2170/2639] eta: 0:23:41 lr: 2.7008068795455545e-05 loss: 0.0500 (0.0538) time: 3.0334 data: 0.0076 max mem: 33408 +Epoch: [19] [2180/2639] eta: 0:23:11 lr: 2.7003503837113942e-05 loss: 0.0504 (0.0539) time: 3.0239 data: 0.0076 max mem: 33408 +Epoch: [19] [2190/2639] eta: 0:22:40 lr: 2.6998938793025287e-05 loss: 0.0473 (0.0538) time: 3.0167 data: 0.0079 max mem: 33408 +Epoch: [19] [2200/2639] eta: 0:22:10 lr: 2.6994373663171862e-05 loss: 0.0472 (0.0539) time: 2.9912 data: 0.0077 max mem: 33408 +Epoch: [19] [2210/2639] eta: 0:21:40 lr: 2.698980844753594e-05 loss: 0.0561 (0.0539) time: 3.0022 data: 0.0078 max mem: 33408 +Epoch: [19] [2220/2639] eta: 0:21:09 lr: 2.698524314609979e-05 loss: 0.0483 (0.0539) time: 3.0082 data: 0.0075 max mem: 33408 +Epoch: [19] [2230/2639] eta: 0:20:39 lr: 2.698067775884568e-05 loss: 0.0417 (0.0538) time: 3.0536 data: 0.0072 max mem: 33408 +Epoch: [19] [2240/2639] eta: 0:20:09 lr: 2.697611228575585e-05 loss: 0.0520 (0.0538) time: 3.0416 data: 0.0080 max mem: 33408 +Epoch: [19] [2250/2639] eta: 0:19:38 lr: 2.697154672681254e-05 loss: 0.0567 (0.0540) time: 2.9999 data: 0.0084 max mem: 33408 +Epoch: [19] [2260/2639] eta: 0:19:08 lr: 2.6966981081997993e-05 loss: 0.0567 (0.0540) time: 3.0114 data: 0.0085 max mem: 33408 +Epoch: [19] [2270/2639] eta: 0:18:38 lr: 2.6962415351294445e-05 loss: 0.0537 (0.0540) time: 3.0072 data: 0.0083 max mem: 33408 +Epoch: [19] [2280/2639] eta: 0:18:07 lr: 2.6957849534684115e-05 loss: 0.0546 (0.0540) time: 3.0164 data: 0.0080 max mem: 33408 +Epoch: [19] [2290/2639] eta: 0:17:37 lr: 2.695328363214921e-05 loss: 0.0458 (0.0540) time: 2.9796 data: 0.0080 max mem: 33408 +Epoch: [19] [2300/2639] eta: 0:17:06 lr: 2.6948717643671956e-05 loss: 0.0431 (0.0540) time: 2.9595 data: 0.0079 max mem: 33408 +Epoch: [19] [2310/2639] eta: 0:16:36 lr: 2.6944151569234548e-05 loss: 0.0438 (0.0540) time: 2.9754 data: 0.0082 max mem: 33408 +Epoch: [19] [2320/2639] eta: 0:16:06 lr: 2.693958540881918e-05 loss: 0.0523 (0.0540) time: 2.9879 data: 0.0085 max mem: 33408 +Epoch: [19] [2330/2639] eta: 0:15:35 lr: 2.6935019162408038e-05 loss: 0.0523 (0.0540) time: 3.0052 data: 0.0084 max mem: 33408 +Epoch: [19] [2340/2639] eta: 0:15:05 lr: 2.6930452829983303e-05 loss: 0.0481 (0.0540) time: 3.0441 data: 0.0083 max mem: 33408 +Epoch: [19] [2350/2639] eta: 0:14:35 lr: 2.6925886411527164e-05 loss: 0.0472 (0.0540) time: 3.0195 data: 0.0082 max mem: 33408 +Epoch: [19] [2360/2639] eta: 0:14:05 lr: 2.692131990702177e-05 loss: 0.0533 (0.0540) time: 2.9771 data: 0.0081 max mem: 33408 +Epoch: [19] [2370/2639] eta: 0:13:34 lr: 2.6916753316449284e-05 loss: 0.0428 (0.0542) time: 3.0125 data: 0.0080 max mem: 33408 +Epoch: [19] [2380/2639] eta: 0:13:04 lr: 2.6912186639791864e-05 loss: 0.0488 (0.0542) time: 3.0479 data: 0.0082 max mem: 33408 +Epoch: [19] [2390/2639] eta: 0:12:34 lr: 2.6907619877031658e-05 loss: 0.0542 (0.0542) time: 3.0395 data: 0.0080 max mem: 33408 +Epoch: [19] [2400/2639] eta: 0:12:03 lr: 2.6903053028150803e-05 loss: 0.0452 (0.0542) time: 2.9973 data: 0.0076 max mem: 33408 +Epoch: [19] [2410/2639] eta: 0:11:33 lr: 2.6898486093131427e-05 loss: 0.0418 (0.0542) time: 3.0178 data: 0.0077 max mem: 33408 +Epoch: [19] [2420/2639] eta: 0:11:03 lr: 2.6893919071955654e-05 loss: 0.0512 (0.0541) time: 3.0263 data: 0.0082 max mem: 33408 +Epoch: [19] [2430/2639] eta: 0:10:33 lr: 2.6889351964605613e-05 loss: 0.0504 (0.0542) time: 3.0264 data: 0.0084 max mem: 33408 +Epoch: [19] [2440/2639] eta: 0:10:02 lr: 2.6884784771063403e-05 loss: 0.0473 (0.0542) time: 3.0379 data: 0.0083 max mem: 33408 +Epoch: [19] [2450/2639] eta: 0:09:32 lr: 2.6880217491311128e-05 loss: 0.0471 (0.0542) time: 3.0223 data: 0.0082 max mem: 33408 +Epoch: [19] [2460/2639] eta: 0:09:02 lr: 2.6875650125330885e-05 loss: 0.0471 (0.0543) time: 2.9954 data: 0.0082 max mem: 33408 +Epoch: [19] [2470/2639] eta: 0:08:31 lr: 2.6871082673104762e-05 loss: 0.0451 (0.0542) time: 2.9961 data: 0.0083 max mem: 33408 +Epoch: [19] [2480/2639] eta: 0:08:01 lr: 2.6866515134614856e-05 loss: 0.0435 (0.0542) time: 2.9997 data: 0.0081 max mem: 33408 +Epoch: [19] [2490/2639] eta: 0:07:31 lr: 2.6861947509843232e-05 loss: 0.0512 (0.0542) time: 3.0101 data: 0.0082 max mem: 33408 +Epoch: [19] [2500/2639] eta: 0:07:00 lr: 2.6857379798771948e-05 loss: 0.0544 (0.0542) time: 3.0621 data: 0.0079 max mem: 33408 +Epoch: [19] [2510/2639] eta: 0:06:30 lr: 2.685281200138307e-05 loss: 0.0546 (0.0543) time: 3.0394 data: 0.0078 max mem: 33408 +Epoch: [19] [2520/2639] eta: 0:06:00 lr: 2.6848244117658665e-05 loss: 0.0604 (0.0543) time: 3.0472 data: 0.0080 max mem: 33408 +Epoch: [19] [2530/2639] eta: 0:05:30 lr: 2.684367614758077e-05 loss: 0.0518 (0.0543) time: 3.0348 data: 0.0079 max mem: 33408 +Epoch: [19] [2540/2639] eta: 0:04:59 lr: 2.6839108091131415e-05 loss: 0.0512 (0.0543) time: 3.0423 data: 0.0080 max mem: 33408 +Epoch: [19] [2550/2639] eta: 0:04:29 lr: 2.6834539948292648e-05 loss: 0.0492 (0.0542) time: 3.0523 data: 0.0080 max mem: 33408 +Epoch: [19] [2560/2639] eta: 0:03:59 lr: 2.682997171904649e-05 loss: 0.0490 (0.0542) time: 3.0441 data: 0.0082 max mem: 33408 +Epoch: [19] [2570/2639] eta: 0:03:28 lr: 2.6825403403374956e-05 loss: 0.0481 (0.0543) time: 3.0579 data: 0.0081 max mem: 33408 +Epoch: [19] [2580/2639] eta: 0:02:58 lr: 2.6820835001260048e-05 loss: 0.0439 (0.0543) time: 3.0377 data: 0.0077 max mem: 33408 +Epoch: [19] [2590/2639] eta: 0:02:28 lr: 2.6816266512683784e-05 loss: 0.0491 (0.0543) time: 3.0427 data: 0.0079 max mem: 33408 +Epoch: [19] [2600/2639] eta: 0:01:58 lr: 2.681169793762816e-05 loss: 0.0519 (0.0543) time: 3.0254 data: 0.0082 max mem: 33408 +Epoch: [19] [2610/2639] eta: 0:01:27 lr: 2.6807129276075162e-05 loss: 0.0493 (0.0543) time: 3.0384 data: 0.0080 max mem: 33408 +Epoch: [19] [2620/2639] eta: 0:00:57 lr: 2.6802560528006763e-05 loss: 0.0516 (0.0543) time: 3.0547 data: 0.0080 max mem: 33408 +Epoch: [19] [2630/2639] eta: 0:00:27 lr: 2.6797991693404957e-05 loss: 0.0493 (0.0542) time: 3.0014 data: 0.0079 max mem: 33408 +Epoch: [19] Total time: 2:13:13 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 2:20:55 time: 3.2862 data: 3.1950 max mem: 33408 +Test: [ 100/2573] eta: 0:04:31 time: 0.0773 data: 0.0013 max mem: 33408 +Test: [ 200/2573] eta: 0:03:45 time: 0.0804 data: 0.0015 max mem: 33408 +Test: [ 300/2573] eta: 0:03:24 time: 0.0828 data: 0.0015 max mem: 33408 +Test: [ 400/2573] eta: 0:03:10 time: 0.0829 data: 0.0015 max mem: 33408 +Test: [ 500/2573] eta: 0:02:58 time: 0.0798 data: 0.0015 max mem: 33408 +Test: [ 600/2573] eta: 0:02:48 time: 0.0797 data: 0.0014 max mem: 33408 +Test: [ 700/2573] eta: 0:02:39 time: 0.0798 data: 0.0015 max mem: 33408 +Test: [ 800/2573] eta: 0:02:29 time: 0.0839 data: 0.0013 max mem: 33408 +Test: [ 900/2573] eta: 0:02:21 time: 0.0820 data: 0.0015 max mem: 33408 +Test: [1000/2573] eta: 0:02:12 time: 0.0807 data: 0.0015 max mem: 33408 +Test: [1100/2573] eta: 0:02:03 time: 0.0797 data: 0.0014 max mem: 33408 +Test: [1200/2573] eta: 0:01:54 time: 0.0823 data: 0.0014 max mem: 33408 +Test: [1300/2573] eta: 0:01:46 time: 0.0816 data: 0.0015 max mem: 33408 +Test: [1400/2573] eta: 0:01:37 time: 0.0792 data: 0.0014 max mem: 33408 +Test: [1500/2573] eta: 0:01:29 time: 0.0810 data: 0.0014 max mem: 33408 +Test: [1600/2573] eta: 0:01:20 time: 0.0837 data: 0.0015 max mem: 33408 +Test: [1700/2573] eta: 0:01:12 time: 0.0806 data: 0.0015 max mem: 33408 +Test: [1800/2573] eta: 0:01:03 time: 0.0813 data: 0.0014 max mem: 33408 +Test: [1900/2573] eta: 0:00:55 time: 0.0789 data: 0.0015 max mem: 33408 +Test: [2000/2573] eta: 0:00:47 time: 0.0796 data: 0.0014 max mem: 33408 +Test: [2100/2573] eta: 0:00:38 time: 0.0826 data: 0.0015 max mem: 33408 +Test: [2200/2573] eta: 0:00:30 time: 0.0819 data: 0.0014 max mem: 33408 +Test: [2300/2573] eta: 0:00:22 time: 0.0822 data: 0.0016 max mem: 33408 +Test: [2400/2573] eta: 0:00:14 time: 0.0778 data: 0.0016 max mem: 33408 +Test: [2500/2573] eta: 0:00:05 time: 0.0816 data: 0.0013 max mem: 33408 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: Total time: 0:03:32 +Final results: +Mean IoU is 63.39 + + precision@0.5 = 71.34 + precision@0.6 = 65.52 + precision@0.7 = 58.60 + precision@0.8 = 46.77 + precision@0.9 = 23.02 + overall IoU = 60.84 + +Average object IoU 63.39298661524404 +Overall IoU 60.84182357788086 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [20] [ 0/2639] eta: 3:49:14 lr: 2.679387966826235e-05 loss: 0.0510 (0.0510) time: 5.2119 data: 2.1026 max mem: 33408 +Epoch: [20] [ 10/2639] eta: 2:22:59 lr: 2.6789310669197365e-05 loss: 0.0479 (0.0452) time: 3.2633 data: 0.1978 max mem: 33408 +Epoch: [20] [ 20/2639] eta: 2:17:59 lr: 2.6784741583546646e-05 loss: 0.0416 (0.0440) time: 3.0590 data: 0.0075 max mem: 33408 +Epoch: [20] [ 30/2639] eta: 2:15:30 lr: 2.6780172411292147e-05 loss: 0.0405 (0.0439) time: 3.0356 data: 0.0077 max mem: 33408 +Epoch: [20] [ 40/2639] eta: 2:14:44 lr: 2.6775603152415803e-05 loss: 0.0429 (0.0444) time: 3.0572 data: 0.0075 max mem: 33408 +Epoch: [20] [ 50/2639] eta: 2:13:26 lr: 2.677103380689955e-05 loss: 0.0429 (0.0453) time: 3.0551 data: 0.0075 max mem: 33408 +Epoch: [20] [ 60/2639] eta: 2:11:56 lr: 2.676646437472531e-05 loss: 0.0506 (0.0523) time: 2.9852 data: 0.0076 max mem: 33408 +Epoch: [20] [ 70/2639] eta: 2:10:55 lr: 2.6761894855875008e-05 loss: 0.0488 (0.0518) time: 2.9696 data: 0.0077 max mem: 33408 +Epoch: [20] [ 80/2639] eta: 2:10:30 lr: 2.6757325250330546e-05 loss: 0.0488 (0.0523) time: 3.0316 data: 0.0081 max mem: 33408 +Epoch: [20] [ 90/2639] eta: 2:09:37 lr: 2.675275555807384e-05 loss: 0.0486 (0.0515) time: 3.0274 data: 0.0082 max mem: 33408 +Epoch: [20] [ 100/2639] eta: 2:09:12 lr: 2.674818577908677e-05 loss: 0.0427 (0.0514) time: 3.0262 data: 0.0078 max mem: 33408 +Epoch: [20] [ 110/2639] eta: 2:09:13 lr: 2.674361591335124e-05 loss: 0.0420 (0.0513) time: 3.1318 data: 0.0078 max mem: 33408 +Epoch: [20] [ 120/2639] eta: 2:08:23 lr: 2.6739045960849123e-05 loss: 0.0489 (0.0517) time: 3.0809 data: 0.0082 max mem: 33408 +Epoch: [20] [ 130/2639] eta: 2:07:44 lr: 2.6734475921562307e-05 loss: 0.0489 (0.0518) time: 2.9935 data: 0.0083 max mem: 33408 +Epoch: [20] [ 140/2639] eta: 2:07:00 lr: 2.6729905795472642e-05 loss: 0.0442 (0.0515) time: 2.9980 data: 0.0082 max mem: 33408 +Epoch: [20] [ 150/2639] eta: 2:06:23 lr: 2.6725335582562006e-05 loss: 0.0488 (0.0517) time: 2.9945 data: 0.0079 max mem: 33408 +Epoch: [20] [ 160/2639] eta: 2:05:44 lr: 2.6720765282812237e-05 loss: 0.0508 (0.0517) time: 3.0007 data: 0.0081 max mem: 33408 +Epoch: [20] [ 170/2639] eta: 2:05:19 lr: 2.6716194896205192e-05 loss: 0.0491 (0.0518) time: 3.0362 data: 0.0079 max mem: 33408 +Epoch: [20] [ 180/2639] eta: 2:04:39 lr: 2.6711624422722705e-05 loss: 0.0463 (0.0513) time: 3.0285 data: 0.0078 max mem: 33408 +Epoch: [20] [ 190/2639] eta: 2:04:14 lr: 2.670705386234661e-05 loss: 0.0417 (0.0512) time: 3.0300 data: 0.0078 max mem: 33408 +Epoch: [20] [ 200/2639] eta: 2:03:40 lr: 2.6702483215058725e-05 loss: 0.0504 (0.0511) time: 3.0478 data: 0.0077 max mem: 33408 +Epoch: [20] [ 210/2639] eta: 2:03:03 lr: 2.6697912480840882e-05 loss: 0.0447 (0.0510) time: 2.9998 data: 0.0079 max mem: 33408 +Epoch: [20] [ 220/2639] eta: 2:02:28 lr: 2.669334165967487e-05 loss: 0.0446 (0.0510) time: 2.9910 data: 0.0079 max mem: 33408 +Epoch: [20] [ 230/2639] eta: 2:01:48 lr: 2.6688770751542507e-05 loss: 0.0431 (0.0507) time: 2.9727 data: 0.0078 max mem: 33408 +Epoch: [20] [ 240/2639] eta: 2:01:25 lr: 2.6684199756425587e-05 loss: 0.0432 (0.0506) time: 3.0253 data: 0.0078 max mem: 33408 +Epoch: [20] [ 250/2639] eta: 2:00:52 lr: 2.667962867430589e-05 loss: 0.0396 (0.0506) time: 3.0559 data: 0.0079 max mem: 33408 +Epoch: [20] [ 260/2639] eta: 2:00:26 lr: 2.667505750516521e-05 loss: 0.0410 (0.0506) time: 3.0502 data: 0.0081 max mem: 33408 +Epoch: [20] [ 270/2639] eta: 1:59:45 lr: 2.6670486248985297e-05 loss: 0.0464 (0.0504) time: 3.0040 data: 0.0079 max mem: 33408 +Epoch: [20] [ 280/2639] eta: 1:59:15 lr: 2.6665914905747946e-05 loss: 0.0464 (0.0507) time: 2.9747 data: 0.0077 max mem: 33408 +Epoch: [20] [ 290/2639] eta: 1:58:40 lr: 2.666134347543489e-05 loss: 0.0428 (0.0504) time: 3.0043 data: 0.0080 max mem: 33408 +Epoch: [20] [ 300/2639] eta: 1:58:04 lr: 2.6656771958027903e-05 loss: 0.0428 (0.0505) time: 2.9677 data: 0.0080 max mem: 33408 +Epoch: [20] [ 310/2639] eta: 1:57:33 lr: 2.6652200353508715e-05 loss: 0.0434 (0.0503) time: 2.9893 data: 0.0079 max mem: 33408 +Epoch: [20] [ 320/2639] eta: 1:57:04 lr: 2.664762866185907e-05 loss: 0.0426 (0.0510) time: 3.0352 data: 0.0077 max mem: 33408 +Epoch: [20] [ 330/2639] eta: 1:56:32 lr: 2.664305688306069e-05 loss: 0.0411 (0.0514) time: 3.0240 data: 0.0082 max mem: 33408 +Epoch: [20] [ 340/2639] eta: 1:56:06 lr: 2.6638485017095305e-05 loss: 0.0393 (0.0513) time: 3.0441 data: 0.0083 max mem: 33408 +Epoch: [20] [ 350/2639] eta: 1:55:39 lr: 2.6633913063944623e-05 loss: 0.0490 (0.0516) time: 3.0874 data: 0.0078 max mem: 33408 +Epoch: [20] [ 360/2639] eta: 1:55:09 lr: 2.662934102359036e-05 loss: 0.0464 (0.0513) time: 3.0591 data: 0.0078 max mem: 33408 +Epoch: [20] [ 370/2639] eta: 1:54:38 lr: 2.662476889601421e-05 loss: 0.0437 (0.0511) time: 3.0305 data: 0.0079 max mem: 33408 +Epoch: [20] [ 380/2639] eta: 1:54:08 lr: 2.6620196681197868e-05 loss: 0.0389 (0.0509) time: 3.0297 data: 0.0078 max mem: 33408 +Epoch: [20] [ 390/2639] eta: 1:53:37 lr: 2.6615624379123015e-05 loss: 0.0420 (0.0507) time: 3.0306 data: 0.0080 max mem: 33408 +Epoch: [20] [ 400/2639] eta: 1:53:05 lr: 2.661105198977134e-05 loss: 0.0420 (0.0504) time: 3.0100 data: 0.0082 max mem: 33408 +Epoch: [20] [ 410/2639] eta: 1:52:37 lr: 2.6606479513124505e-05 loss: 0.0439 (0.0507) time: 3.0358 data: 0.0078 max mem: 33408 +Epoch: [20] [ 420/2639] eta: 1:52:09 lr: 2.6601906949164185e-05 loss: 0.0439 (0.0506) time: 3.0761 data: 0.0079 max mem: 33408 +Epoch: [20] [ 430/2639] eta: 1:51:37 lr: 2.6597334297872018e-05 loss: 0.0376 (0.0503) time: 3.0323 data: 0.0080 max mem: 33408 +Epoch: [20] [ 440/2639] eta: 1:51:08 lr: 2.659276155922967e-05 loss: 0.0404 (0.0505) time: 3.0329 data: 0.0078 max mem: 33408 +Epoch: [20] [ 450/2639] eta: 1:50:36 lr: 2.6588188733218768e-05 loss: 0.0461 (0.0505) time: 3.0332 data: 0.0079 max mem: 33408 +Epoch: [20] [ 460/2639] eta: 1:50:04 lr: 2.6583615819820955e-05 loss: 0.0470 (0.0507) time: 2.9870 data: 0.0078 max mem: 33408 +Epoch: [20] [ 470/2639] eta: 1:49:31 lr: 2.6579042819017857e-05 loss: 0.0524 (0.0510) time: 2.9854 data: 0.0080 max mem: 33408 +Epoch: [20] [ 480/2639] eta: 1:49:01 lr: 2.6574469730791095e-05 loss: 0.0507 (0.0509) time: 3.0092 data: 0.0079 max mem: 33408 +Epoch: [20] [ 490/2639] eta: 1:48:30 lr: 2.656989655512228e-05 loss: 0.0450 (0.0509) time: 3.0228 data: 0.0080 max mem: 33408 +Epoch: [20] [ 500/2639] eta: 1:48:00 lr: 2.656532329199301e-05 loss: 0.0475 (0.0513) time: 3.0292 data: 0.0083 max mem: 33408 +Epoch: [20] [ 510/2639] eta: 1:47:32 lr: 2.6560749941384898e-05 loss: 0.0476 (0.0513) time: 3.0558 data: 0.0079 max mem: 33408 +Epoch: [20] [ 520/2639] eta: 1:47:01 lr: 2.6556176503279516e-05 loss: 0.0427 (0.0512) time: 3.0463 data: 0.0076 max mem: 33408 +Epoch: [20] [ 530/2639] eta: 1:46:32 lr: 2.655160297765846e-05 loss: 0.0490 (0.0511) time: 3.0396 data: 0.0073 max mem: 33408 +Epoch: [20] [ 540/2639] eta: 1:46:01 lr: 2.6547029364503296e-05 loss: 0.0512 (0.0511) time: 3.0355 data: 0.0074 max mem: 33408 +Epoch: [20] [ 550/2639] eta: 1:45:33 lr: 2.6542455663795596e-05 loss: 0.0427 (0.0510) time: 3.0536 data: 0.0076 max mem: 33408 +Epoch: [20] [ 560/2639] eta: 1:45:07 lr: 2.6537881875516917e-05 loss: 0.0417 (0.0509) time: 3.1168 data: 0.0078 max mem: 33408 +Epoch: [20] [ 570/2639] eta: 1:44:36 lr: 2.653330799964882e-05 loss: 0.0445 (0.0509) time: 3.0770 data: 0.0082 max mem: 33408 +Epoch: [20] [ 580/2639] eta: 1:44:08 lr: 2.6528734036172842e-05 loss: 0.0453 (0.0509) time: 3.0604 data: 0.0081 max mem: 33408 +Epoch: [20] [ 590/2639] eta: 1:43:39 lr: 2.652415998507053e-05 loss: 0.0474 (0.0508) time: 3.0983 data: 0.0078 max mem: 33408 +Epoch: [20] [ 600/2639] eta: 1:43:08 lr: 2.6519585846323396e-05 loss: 0.0524 (0.0511) time: 3.0452 data: 0.0079 max mem: 33408 +Epoch: [20] [ 610/2639] eta: 1:42:37 lr: 2.6515011619912988e-05 loss: 0.0503 (0.0510) time: 3.0047 data: 0.0075 max mem: 33408 +Epoch: [20] [ 620/2639] eta: 1:42:04 lr: 2.6510437305820802e-05 loss: 0.0454 (0.0510) time: 2.9932 data: 0.0073 max mem: 33408 +Epoch: [20] [ 630/2639] eta: 1:41:36 lr: 2.650586290402836e-05 loss: 0.0505 (0.0512) time: 3.0341 data: 0.0077 max mem: 33408 +Epoch: [20] [ 640/2639] eta: 1:41:04 lr: 2.650128841451715e-05 loss: 0.0500 (0.0511) time: 3.0446 data: 0.0079 max mem: 33408 +Epoch: [20] [ 650/2639] eta: 1:40:33 lr: 2.649671383726868e-05 loss: 0.0438 (0.0510) time: 2.9971 data: 0.0080 max mem: 33408 +Epoch: [20] [ 660/2639] eta: 1:40:01 lr: 2.6492139172264418e-05 loss: 0.0438 (0.0511) time: 2.9930 data: 0.0082 max mem: 33408 +Epoch: [20] [ 670/2639] eta: 1:39:31 lr: 2.6487564419485862e-05 loss: 0.0436 (0.0509) time: 3.0162 data: 0.0080 max mem: 33408 +Epoch: [20] [ 680/2639] eta: 1:39:01 lr: 2.648298957891447e-05 loss: 0.0466 (0.0510) time: 3.0365 data: 0.0078 max mem: 33408 +Epoch: [20] [ 690/2639] eta: 1:38:30 lr: 2.6478414650531707e-05 loss: 0.0486 (0.0513) time: 3.0262 data: 0.0078 max mem: 33408 +Epoch: [20] [ 700/2639] eta: 1:38:00 lr: 2.647383963431903e-05 loss: 0.0581 (0.0515) time: 3.0319 data: 0.0079 max mem: 33408 +Epoch: [20] [ 710/2639] eta: 1:37:30 lr: 2.6469264530257898e-05 loss: 0.0559 (0.0515) time: 3.0325 data: 0.0080 max mem: 33408 +Epoch: [20] [ 720/2639] eta: 1:36:59 lr: 2.6464689338329734e-05 loss: 0.0479 (0.0514) time: 3.0154 data: 0.0077 max mem: 33408 +Epoch: [20] [ 730/2639] eta: 1:36:28 lr: 2.6460114058515983e-05 loss: 0.0467 (0.0514) time: 3.0090 data: 0.0074 max mem: 33408 +Epoch: [20] [ 740/2639] eta: 1:35:56 lr: 2.645553869079807e-05 loss: 0.0467 (0.0514) time: 2.9967 data: 0.0076 max mem: 33408 +Epoch: [20] [ 750/2639] eta: 1:35:28 lr: 2.645096323515741e-05 loss: 0.0468 (0.0514) time: 3.0423 data: 0.0078 max mem: 33408 +Epoch: [20] [ 760/2639] eta: 1:34:56 lr: 2.644638769157542e-05 loss: 0.0468 (0.0514) time: 3.0401 data: 0.0086 max mem: 33408 +Epoch: [20] [ 770/2639] eta: 1:34:26 lr: 2.6441812060033495e-05 loss: 0.0460 (0.0514) time: 3.0073 data: 0.0085 max mem: 33408 +Epoch: [20] [ 780/2639] eta: 1:33:54 lr: 2.6437236340513045e-05 loss: 0.0489 (0.0515) time: 2.9995 data: 0.0075 max mem: 33408 +Epoch: [20] [ 790/2639] eta: 1:33:22 lr: 2.643266053299544e-05 loss: 0.0549 (0.0515) time: 2.9677 data: 0.0075 max mem: 33408 +Epoch: [20] [ 800/2639] eta: 1:32:51 lr: 2.6428084637462076e-05 loss: 0.0491 (0.0515) time: 2.9813 data: 0.0075 max mem: 33408 +Epoch: [20] [ 810/2639] eta: 1:32:21 lr: 2.6423508653894318e-05 loss: 0.0494 (0.0514) time: 3.0109 data: 0.0078 max mem: 33408 +Epoch: [20] [ 820/2639] eta: 1:31:50 lr: 2.641893258227354e-05 loss: 0.0460 (0.0515) time: 3.0167 data: 0.0081 max mem: 33408 +Epoch: [20] [ 830/2639] eta: 1:31:20 lr: 2.6414356422581094e-05 loss: 0.0487 (0.0514) time: 3.0372 data: 0.0078 max mem: 33408 +Epoch: [20] [ 840/2639] eta: 1:30:50 lr: 2.6409780174798338e-05 loss: 0.0396 (0.0513) time: 3.0490 data: 0.0076 max mem: 33408 +Epoch: [20] [ 850/2639] eta: 1:30:20 lr: 2.6405203838906605e-05 loss: 0.0378 (0.0512) time: 3.0265 data: 0.0076 max mem: 33408 +Epoch: [20] [ 860/2639] eta: 1:29:49 lr: 2.640062741488724e-05 loss: 0.0383 (0.0512) time: 3.0210 data: 0.0074 max mem: 33408 +Epoch: [20] [ 870/2639] eta: 1:29:19 lr: 2.6396050902721565e-05 loss: 0.0436 (0.0512) time: 3.0336 data: 0.0073 max mem: 33408 +Epoch: [20] [ 880/2639] eta: 1:28:48 lr: 2.6391474302390906e-05 loss: 0.0436 (0.0513) time: 3.0073 data: 0.0075 max mem: 33408 +Epoch: [20] [ 890/2639] eta: 1:28:18 lr: 2.6386897613876566e-05 loss: 0.0423 (0.0521) time: 3.0267 data: 0.0074 max mem: 33408 +Epoch: [20] [ 900/2639] eta: 1:27:48 lr: 2.6382320837159868e-05 loss: 0.0449 (0.0522) time: 3.0677 data: 0.0076 max mem: 33408 +Epoch: [20] [ 910/2639] eta: 1:27:19 lr: 2.6377743972222097e-05 loss: 0.0502 (0.0522) time: 3.0632 data: 0.0077 max mem: 33408 +Epoch: [20] [ 920/2639] eta: 1:26:48 lr: 2.6373167019044546e-05 loss: 0.0487 (0.0522) time: 3.0376 data: 0.0078 max mem: 33408 +Epoch: [20] [ 930/2639] eta: 1:26:18 lr: 2.6368589977608497e-05 loss: 0.0487 (0.0522) time: 3.0135 data: 0.0077 max mem: 33408 +Epoch: [20] [ 940/2639] eta: 1:25:47 lr: 2.6364012847895237e-05 loss: 0.0431 (0.0521) time: 3.0270 data: 0.0078 max mem: 33408 +Epoch: [20] [ 950/2639] eta: 1:25:17 lr: 2.6359435629886015e-05 loss: 0.0431 (0.0521) time: 3.0157 data: 0.0077 max mem: 33408 +Epoch: [20] [ 960/2639] eta: 1:24:47 lr: 2.635485832356211e-05 loss: 0.0422 (0.0520) time: 3.0306 data: 0.0079 max mem: 33408 +Epoch: [20] [ 970/2639] eta: 1:24:17 lr: 2.635028092890476e-05 loss: 0.0451 (0.0520) time: 3.0496 data: 0.0079 max mem: 33408 +Epoch: [20] [ 980/2639] eta: 1:23:47 lr: 2.634570344589521e-05 loss: 0.0416 (0.0519) time: 3.0456 data: 0.0077 max mem: 33408 +Epoch: [20] [ 990/2639] eta: 1:23:16 lr: 2.6341125874514704e-05 loss: 0.0424 (0.0520) time: 3.0109 data: 0.0079 max mem: 33408 +Epoch: [20] [1000/2639] eta: 1:22:44 lr: 2.633654821474447e-05 loss: 0.0540 (0.0520) time: 2.9702 data: 0.0078 max mem: 33408 +Epoch: [20] [1010/2639] eta: 1:22:13 lr: 2.6331970466565743e-05 loss: 0.0528 (0.0520) time: 2.9684 data: 0.0077 max mem: 33408 +Epoch: [20] [1020/2639] eta: 1:21:42 lr: 2.6327392629959714e-05 loss: 0.0468 (0.0521) time: 2.9781 data: 0.0080 max mem: 33408 +Epoch: [20] [1030/2639] eta: 1:21:11 lr: 2.63228147049076e-05 loss: 0.0515 (0.0522) time: 2.9660 data: 0.0080 max mem: 33408 +Epoch: [20] [1040/2639] eta: 1:20:40 lr: 2.6318236691390603e-05 loss: 0.0491 (0.0522) time: 2.9727 data: 0.0076 max mem: 33408 +Epoch: [20] [1050/2639] eta: 1:20:10 lr: 2.6313658589389916e-05 loss: 0.0472 (0.0521) time: 3.0337 data: 0.0077 max mem: 33408 +Epoch: [20] [1060/2639] eta: 1:19:40 lr: 2.6309080398886714e-05 loss: 0.0428 (0.0521) time: 3.0572 data: 0.0083 max mem: 33408 +Epoch: [20] [1070/2639] eta: 1:19:11 lr: 2.630450211986219e-05 loss: 0.0453 (0.0521) time: 3.0697 data: 0.0083 max mem: 33408 +Epoch: [20] [1080/2639] eta: 1:18:42 lr: 2.6299923752297494e-05 loss: 0.0397 (0.0520) time: 3.0964 data: 0.0078 max mem: 33408 +Epoch: [20] [1090/2639] eta: 1:18:10 lr: 2.62953452961738e-05 loss: 0.0429 (0.0520) time: 3.0315 data: 0.0085 max mem: 33408 +Epoch: [20] [1100/2639] eta: 1:17:40 lr: 2.629076675147225e-05 loss: 0.0446 (0.0519) time: 3.0015 data: 0.0091 max mem: 33408 +Epoch: [20] [1110/2639] eta: 1:17:10 lr: 2.6286188118174005e-05 loss: 0.0411 (0.0519) time: 3.0254 data: 0.0092 max mem: 33408 +Epoch: [20] [1120/2639] eta: 1:16:40 lr: 2.6281609396260194e-05 loss: 0.0480 (0.0519) time: 3.0480 data: 0.0088 max mem: 33408 +Epoch: [20] [1130/2639] eta: 1:16:09 lr: 2.627703058571194e-05 loss: 0.0516 (0.0519) time: 3.0267 data: 0.0084 max mem: 33408 +Epoch: [20] [1140/2639] eta: 1:15:40 lr: 2.627245168651038e-05 loss: 0.0408 (0.0519) time: 3.0268 data: 0.0082 max mem: 33408 +Epoch: [20] [1150/2639] eta: 1:15:09 lr: 2.6267872698636624e-05 loss: 0.0423 (0.0519) time: 3.0548 data: 0.0081 max mem: 33408 +Epoch: [20] [1160/2639] eta: 1:14:38 lr: 2.6263293622071778e-05 loss: 0.0444 (0.0518) time: 3.0095 data: 0.0080 max mem: 33408 +Epoch: [20] [1170/2639] eta: 1:14:08 lr: 2.6258714456796945e-05 loss: 0.0439 (0.0517) time: 3.0180 data: 0.0079 max mem: 33408 +Epoch: [20] [1180/2639] eta: 1:13:38 lr: 2.6254135202793212e-05 loss: 0.0394 (0.0518) time: 3.0420 data: 0.0080 max mem: 33408 +Epoch: [20] [1190/2639] eta: 1:13:08 lr: 2.6249555860041663e-05 loss: 0.0464 (0.0518) time: 3.0341 data: 0.0080 max mem: 33408 +Epoch: [20] [1200/2639] eta: 1:12:37 lr: 2.624497642852338e-05 loss: 0.0434 (0.0517) time: 3.0176 data: 0.0081 max mem: 33408 +Epoch: [20] [1210/2639] eta: 1:12:08 lr: 2.624039690821943e-05 loss: 0.0395 (0.0517) time: 3.0498 data: 0.0080 max mem: 33408 +Epoch: [20] [1220/2639] eta: 1:11:38 lr: 2.6235817299110875e-05 loss: 0.0438 (0.0518) time: 3.0663 data: 0.0082 max mem: 33408 +Epoch: [20] [1230/2639] eta: 1:11:07 lr: 2.623123760117876e-05 loss: 0.0553 (0.0518) time: 3.0130 data: 0.0083 max mem: 33408 +Epoch: [20] [1240/2639] eta: 1:10:36 lr: 2.6226657814404147e-05 loss: 0.0456 (0.0517) time: 2.9755 data: 0.0079 max mem: 33408 +Epoch: [20] [1250/2639] eta: 1:10:05 lr: 2.6222077938768063e-05 loss: 0.0455 (0.0518) time: 2.9853 data: 0.0080 max mem: 33408 +Epoch: [20] [1260/2639] eta: 1:09:35 lr: 2.6217497974251542e-05 loss: 0.0439 (0.0517) time: 3.0053 data: 0.0082 max mem: 33408 +Epoch: [20] [1270/2639] eta: 1:09:04 lr: 2.62129179208356e-05 loss: 0.0474 (0.0518) time: 3.0088 data: 0.0082 max mem: 33408 +Epoch: [20] [1280/2639] eta: 1:08:34 lr: 2.6208337778501262e-05 loss: 0.0497 (0.0518) time: 2.9960 data: 0.0082 max mem: 33408 +Epoch: [20] [1290/2639] eta: 1:08:04 lr: 2.620375754722953e-05 loss: 0.0438 (0.0518) time: 3.0301 data: 0.0079 max mem: 33408 +Epoch: [20] [1300/2639] eta: 1:07:33 lr: 2.6199177227001403e-05 loss: 0.0418 (0.0518) time: 3.0311 data: 0.0076 max mem: 33408 +Epoch: [20] [1310/2639] eta: 1:07:03 lr: 2.6194596817797873e-05 loss: 0.0500 (0.0519) time: 2.9959 data: 0.0076 max mem: 33408 +Epoch: [20] [1320/2639] eta: 1:06:33 lr: 2.6190016319599926e-05 loss: 0.0540 (0.0519) time: 3.0374 data: 0.0076 max mem: 33408 +Epoch: [20] [1330/2639] eta: 1:06:03 lr: 2.618543573238853e-05 loss: 0.0456 (0.0518) time: 3.0602 data: 0.0079 max mem: 33408 +Epoch: [20] [1340/2639] eta: 1:05:32 lr: 2.618085505614467e-05 loss: 0.0467 (0.0518) time: 3.0219 data: 0.0085 max mem: 33408 +Epoch: [20] [1350/2639] eta: 1:05:03 lr: 2.617627429084929e-05 loss: 0.0579 (0.0519) time: 3.0399 data: 0.0083 max mem: 33408 +Epoch: [20] [1360/2639] eta: 1:04:32 lr: 2.6171693436483352e-05 loss: 0.0573 (0.0519) time: 3.0392 data: 0.0080 max mem: 33408 +Epoch: [20] [1370/2639] eta: 1:04:01 lr: 2.6167112493027797e-05 loss: 0.0510 (0.0519) time: 2.9993 data: 0.0079 max mem: 33408 +Epoch: [20] [1380/2639] eta: 1:03:31 lr: 2.616253146046357e-05 loss: 0.0460 (0.0519) time: 3.0081 data: 0.0076 max mem: 33408 +Epoch: [20] [1390/2639] eta: 1:03:00 lr: 2.6157950338771582e-05 loss: 0.0475 (0.0519) time: 2.9994 data: 0.0077 max mem: 33408 +Epoch: [20] [1400/2639] eta: 1:02:31 lr: 2.6153369127932774e-05 loss: 0.0450 (0.0518) time: 3.0367 data: 0.0078 max mem: 33408 +Epoch: [20] [1410/2639] eta: 1:02:00 lr: 2.6148787827928052e-05 loss: 0.0507 (0.0520) time: 3.0273 data: 0.0078 max mem: 33408 +Epoch: [20] [1420/2639] eta: 1:01:30 lr: 2.614420643873833e-05 loss: 0.0446 (0.0520) time: 3.0061 data: 0.0081 max mem: 33408 +Epoch: [20] [1430/2639] eta: 1:00:59 lr: 2.613962496034449e-05 loss: 0.0439 (0.0520) time: 3.0118 data: 0.0082 max mem: 33408 +Epoch: [20] [1440/2639] eta: 1:00:29 lr: 2.6135043392727433e-05 loss: 0.0432 (0.0520) time: 3.0523 data: 0.0078 max mem: 33408 +Epoch: [20] [1450/2639] eta: 0:59:58 lr: 2.6130461735868038e-05 loss: 0.0416 (0.0519) time: 3.0187 data: 0.0078 max mem: 33408 +Epoch: [20] [1460/2639] eta: 0:59:28 lr: 2.6125879989747187e-05 loss: 0.0424 (0.0519) time: 2.9984 data: 0.0080 max mem: 33408 +Epoch: [20] [1470/2639] eta: 0:58:58 lr: 2.6121298154345742e-05 loss: 0.0419 (0.0519) time: 3.0364 data: 0.0079 max mem: 33408 +Epoch: [20] [1480/2639] eta: 0:58:28 lr: 2.611671622964456e-05 loss: 0.0472 (0.0519) time: 3.0237 data: 0.0082 max mem: 33408 +Epoch: [20] [1490/2639] eta: 0:57:57 lr: 2.61121342156245e-05 loss: 0.0472 (0.0519) time: 3.0293 data: 0.0088 max mem: 33408 +Epoch: [20] [1500/2639] eta: 0:57:27 lr: 2.6107552112266393e-05 loss: 0.0426 (0.0518) time: 2.9943 data: 0.0084 max mem: 33408 +Epoch: [20] [1510/2639] eta: 0:56:57 lr: 2.6102969919551086e-05 loss: 0.0420 (0.0518) time: 3.0385 data: 0.0079 max mem: 33408 +Epoch: [20] [1520/2639] eta: 0:56:27 lr: 2.60983876374594e-05 loss: 0.0434 (0.0518) time: 3.0712 data: 0.0079 max mem: 33408 +Epoch: [20] [1530/2639] eta: 0:55:56 lr: 2.6093805265972165e-05 loss: 0.0392 (0.0517) time: 3.0193 data: 0.0078 max mem: 33408 +Epoch: [20] [1540/2639] eta: 0:55:27 lr: 2.608922280507018e-05 loss: 0.0435 (0.0519) time: 3.0500 data: 0.0079 max mem: 33408 +Epoch: [20] [1550/2639] eta: 0:54:56 lr: 2.6084640254734256e-05 loss: 0.0435 (0.0519) time: 3.0223 data: 0.0078 max mem: 33408 +Epoch: [20] [1560/2639] eta: 0:54:26 lr: 2.6080057614945185e-05 loss: 0.0421 (0.0519) time: 2.9893 data: 0.0082 max mem: 33408 +Epoch: [20] [1570/2639] eta: 0:53:56 lr: 2.6075474885683766e-05 loss: 0.0466 (0.0519) time: 3.0623 data: 0.0082 max mem: 33408 +Epoch: [20] [1580/2639] eta: 0:53:26 lr: 2.6070892066930764e-05 loss: 0.0395 (0.0519) time: 3.0622 data: 0.0083 max mem: 33408 +Epoch: [20] [1590/2639] eta: 0:52:55 lr: 2.6066309158666967e-05 loss: 0.0395 (0.0519) time: 3.0206 data: 0.0084 max mem: 33408 +Epoch: [20] [1600/2639] eta: 0:52:25 lr: 2.6061726160873128e-05 loss: 0.0473 (0.0519) time: 3.0268 data: 0.0079 max mem: 33408 +Epoch: [20] [1610/2639] eta: 0:51:55 lr: 2.6057143073530015e-05 loss: 0.0434 (0.0519) time: 3.0296 data: 0.0080 max mem: 33408 +Epoch: [20] [1620/2639] eta: 0:51:24 lr: 2.6052559896618368e-05 loss: 0.0451 (0.0519) time: 3.0193 data: 0.0079 max mem: 33408 +Epoch: [20] [1630/2639] eta: 0:50:54 lr: 2.6047976630118936e-05 loss: 0.0458 (0.0519) time: 3.0208 data: 0.0082 max mem: 33408 +Epoch: [20] [1640/2639] eta: 0:50:24 lr: 2.604339327401244e-05 loss: 0.0538 (0.0520) time: 3.0300 data: 0.0084 max mem: 33408 +Epoch: [20] [1650/2639] eta: 0:49:54 lr: 2.6038809828279614e-05 loss: 0.0505 (0.0520) time: 3.0409 data: 0.0079 max mem: 33408 +Epoch: [20] [1660/2639] eta: 0:49:23 lr: 2.6034226292901178e-05 loss: 0.0493 (0.0520) time: 3.0279 data: 0.0078 max mem: 33408 +Epoch: [20] [1670/2639] eta: 0:48:53 lr: 2.6029642667857836e-05 loss: 0.0436 (0.0519) time: 3.0362 data: 0.0084 max mem: 33408 +Epoch: [20] [1680/2639] eta: 0:48:23 lr: 2.602505895313029e-05 loss: 0.0437 (0.0519) time: 3.0109 data: 0.0084 max mem: 33408 +Epoch: [20] [1690/2639] eta: 0:47:52 lr: 2.6020475148699237e-05 loss: 0.0441 (0.0519) time: 3.0011 data: 0.0080 max mem: 33408 +Epoch: [20] [1700/2639] eta: 0:47:22 lr: 2.601589125454536e-05 loss: 0.0490 (0.0520) time: 3.0301 data: 0.0083 max mem: 33408 +Epoch: [20] [1710/2639] eta: 0:46:51 lr: 2.6011307270649333e-05 loss: 0.0516 (0.0520) time: 3.0001 data: 0.0082 max mem: 33408 +Epoch: [20] [1720/2639] eta: 0:46:21 lr: 2.6006723196991833e-05 loss: 0.0517 (0.0519) time: 3.0079 data: 0.0082 max mem: 33408 +Epoch: [20] [1730/2639] eta: 0:45:51 lr: 2.600213903355352e-05 loss: 0.0492 (0.0519) time: 3.0183 data: 0.0080 max mem: 33408 +Epoch: [20] [1740/2639] eta: 0:45:21 lr: 2.5997554780315053e-05 loss: 0.0464 (0.0519) time: 3.0307 data: 0.0076 max mem: 33408 +Epoch: [20] [1750/2639] eta: 0:44:50 lr: 2.5992970437257064e-05 loss: 0.0417 (0.0519) time: 3.0349 data: 0.0079 max mem: 33408 +Epoch: [20] [1760/2639] eta: 0:44:20 lr: 2.59883860043602e-05 loss: 0.0498 (0.0519) time: 3.0163 data: 0.0081 max mem: 33408 +Epoch: [20] [1770/2639] eta: 0:43:50 lr: 2.598380148160509e-05 loss: 0.0526 (0.0520) time: 3.0509 data: 0.0082 max mem: 33408 +Epoch: [20] [1780/2639] eta: 0:43:20 lr: 2.597921686897236e-05 loss: 0.0473 (0.0519) time: 3.0766 data: 0.0079 max mem: 33408 +Epoch: [20] [1790/2639] eta: 0:42:50 lr: 2.5974632166442616e-05 loss: 0.0423 (0.0518) time: 3.0865 data: 0.0077 max mem: 33408 +Epoch: [20] [1800/2639] eta: 0:42:20 lr: 2.597004737399647e-05 loss: 0.0423 (0.0519) time: 3.0292 data: 0.0076 max mem: 33408 +Epoch: [20] [1810/2639] eta: 0:41:50 lr: 2.596546249161451e-05 loss: 0.0482 (0.0519) time: 3.0300 data: 0.0074 max mem: 33408 +Epoch: [20] [1820/2639] eta: 0:41:19 lr: 2.5960877519277348e-05 loss: 0.0482 (0.0519) time: 3.0240 data: 0.0075 max mem: 33408 +Epoch: [20] [1830/2639] eta: 0:40:49 lr: 2.5956292456965543e-05 loss: 0.0516 (0.0519) time: 3.0242 data: 0.0078 max mem: 33408 +Epoch: [20] [1840/2639] eta: 0:40:19 lr: 2.5951707304659682e-05 loss: 0.0520 (0.0519) time: 3.0769 data: 0.0080 max mem: 33408 +Epoch: [20] [1850/2639] eta: 0:39:49 lr: 2.594712206234033e-05 loss: 0.0466 (0.0519) time: 3.0446 data: 0.0078 max mem: 33408 +Epoch: [20] [1860/2639] eta: 0:39:18 lr: 2.5942536729988037e-05 loss: 0.0472 (0.0520) time: 3.0177 data: 0.0078 max mem: 33408 +Epoch: [20] [1870/2639] eta: 0:38:48 lr: 2.593795130758336e-05 loss: 0.0477 (0.0519) time: 3.0046 data: 0.0080 max mem: 33408 +Epoch: [20] [1880/2639] eta: 0:38:17 lr: 2.5933365795106845e-05 loss: 0.0451 (0.0520) time: 3.0057 data: 0.0077 max mem: 33408 +Epoch: [20] [1890/2639] eta: 0:37:47 lr: 2.5928780192539015e-05 loss: 0.0471 (0.0520) time: 3.0380 data: 0.0076 max mem: 33408 +Epoch: [20] [1900/2639] eta: 0:37:17 lr: 2.5924194499860405e-05 loss: 0.0471 (0.0520) time: 3.0294 data: 0.0079 max mem: 33408 +Epoch: [20] [1910/2639] eta: 0:36:47 lr: 2.5919608717051523e-05 loss: 0.0391 (0.0519) time: 3.0206 data: 0.0079 max mem: 33408 +Epoch: [20] [1920/2639] eta: 0:36:16 lr: 2.5915022844092894e-05 loss: 0.0397 (0.0519) time: 3.0169 data: 0.0076 max mem: 33408 +Epoch: [20] [1930/2639] eta: 0:35:46 lr: 2.5910436880965006e-05 loss: 0.0450 (0.0519) time: 3.0092 data: 0.0077 max mem: 33408 +Epoch: [20] [1940/2639] eta: 0:35:16 lr: 2.590585082764836e-05 loss: 0.0450 (0.0519) time: 2.9974 data: 0.0075 max mem: 33408 +Epoch: [20] [1950/2639] eta: 0:34:45 lr: 2.590126468412344e-05 loss: 0.0550 (0.0520) time: 3.0132 data: 0.0074 max mem: 33408 +Epoch: [20] [1960/2639] eta: 0:34:15 lr: 2.5896678450370713e-05 loss: 0.0470 (0.0520) time: 3.0332 data: 0.0077 max mem: 33408 +Epoch: [20] [1970/2639] eta: 0:33:45 lr: 2.5892092126370675e-05 loss: 0.0478 (0.0520) time: 3.0110 data: 0.0078 max mem: 33408 +Epoch: [20] [1980/2639] eta: 0:33:14 lr: 2.5887505712103766e-05 loss: 0.0527 (0.0520) time: 3.0261 data: 0.0075 max mem: 33408 +Epoch: [20] [1990/2639] eta: 0:32:44 lr: 2.5882919207550443e-05 loss: 0.0519 (0.0520) time: 3.0269 data: 0.0080 max mem: 33408 +Epoch: [20] [2000/2639] eta: 0:32:14 lr: 2.5878332612691152e-05 loss: 0.0416 (0.0521) time: 3.0223 data: 0.0079 max mem: 33408 +Epoch: [20] [2010/2639] eta: 0:31:44 lr: 2.5873745927506338e-05 loss: 0.0426 (0.0520) time: 3.0537 data: 0.0083 max mem: 33408 +Epoch: [20] [2020/2639] eta: 0:31:13 lr: 2.5869159151976417e-05 loss: 0.0462 (0.0520) time: 3.0301 data: 0.0087 max mem: 33408 +Epoch: [20] [2030/2639] eta: 0:30:43 lr: 2.5864572286081827e-05 loss: 0.0501 (0.0520) time: 3.0080 data: 0.0080 max mem: 33408 +Epoch: [20] [2040/2639] eta: 0:30:13 lr: 2.585998532980296e-05 loss: 0.0460 (0.0520) time: 3.0447 data: 0.0080 max mem: 33408 +Epoch: [20] [2050/2639] eta: 0:29:43 lr: 2.5855398283120242e-05 loss: 0.0439 (0.0520) time: 3.0452 data: 0.0078 max mem: 33408 +Epoch: [20] [2060/2639] eta: 0:29:12 lr: 2.5850811146014047e-05 loss: 0.0414 (0.0520) time: 3.0221 data: 0.0076 max mem: 33408 +Epoch: [20] [2070/2639] eta: 0:28:42 lr: 2.584622391846479e-05 loss: 0.0431 (0.0520) time: 3.0286 data: 0.0075 max mem: 33408 +Epoch: [20] [2080/2639] eta: 0:28:12 lr: 2.584163660045283e-05 loss: 0.0475 (0.0520) time: 3.0095 data: 0.0078 max mem: 33408 +Epoch: [20] [2090/2639] eta: 0:27:42 lr: 2.5837049191958544e-05 loss: 0.0499 (0.0520) time: 3.0216 data: 0.0079 max mem: 33408 +Epoch: [20] [2100/2639] eta: 0:27:11 lr: 2.5832461692962306e-05 loss: 0.0470 (0.0520) time: 3.0222 data: 0.0076 max mem: 33408 +Epoch: [20] [2110/2639] eta: 0:26:41 lr: 2.5827874103444467e-05 loss: 0.0457 (0.0520) time: 3.0037 data: 0.0077 max mem: 33408 +Epoch: [20] [2120/2639] eta: 0:26:10 lr: 2.5823286423385362e-05 loss: 0.0457 (0.0520) time: 2.9999 data: 0.0078 max mem: 33408 +Epoch: [20] [2130/2639] eta: 0:25:40 lr: 2.5818698652765357e-05 loss: 0.0444 (0.0520) time: 2.9866 data: 0.0079 max mem: 33408 +Epoch: [20] [2140/2639] eta: 0:25:10 lr: 2.5814110791564756e-05 loss: 0.0466 (0.0519) time: 3.0067 data: 0.0076 max mem: 33408 +Epoch: [20] [2150/2639] eta: 0:24:39 lr: 2.5809522839763905e-05 loss: 0.0511 (0.0520) time: 2.9674 data: 0.0076 max mem: 33408 +Epoch: [20] [2160/2639] eta: 0:24:09 lr: 2.5804934797343105e-05 loss: 0.0549 (0.0520) time: 2.9724 data: 0.0082 max mem: 33408 +Epoch: [20] [2170/2639] eta: 0:23:39 lr: 2.5800346664282675e-05 loss: 0.0484 (0.0520) time: 3.0278 data: 0.0084 max mem: 33408 +Epoch: [20] [2180/2639] eta: 0:23:09 lr: 2.57957584405629e-05 loss: 0.0430 (0.0520) time: 3.0235 data: 0.0081 max mem: 33408 +Epoch: [20] [2190/2639] eta: 0:22:38 lr: 2.5791170126164083e-05 loss: 0.0437 (0.0520) time: 3.0104 data: 0.0078 max mem: 33408 +Epoch: [20] [2200/2639] eta: 0:22:08 lr: 2.5786581721066493e-05 loss: 0.0430 (0.0519) time: 3.0223 data: 0.0075 max mem: 33408 +Epoch: [20] [2210/2639] eta: 0:21:38 lr: 2.5781993225250424e-05 loss: 0.0388 (0.0519) time: 3.0254 data: 0.0073 max mem: 33408 +Epoch: [20] [2220/2639] eta: 0:21:07 lr: 2.577740463869613e-05 loss: 0.0458 (0.0519) time: 3.0245 data: 0.0079 max mem: 33408 +Epoch: [20] [2230/2639] eta: 0:20:37 lr: 2.577281596138386e-05 loss: 0.0446 (0.0518) time: 3.0108 data: 0.0086 max mem: 33408 +Epoch: [20] [2240/2639] eta: 0:20:07 lr: 2.5768227193293886e-05 loss: 0.0478 (0.0519) time: 3.0380 data: 0.0085 max mem: 33408 +Epoch: [20] [2250/2639] eta: 0:19:37 lr: 2.5763638334406438e-05 loss: 0.0513 (0.0519) time: 3.0518 data: 0.0083 max mem: 33408 +Epoch: [20] [2260/2639] eta: 0:19:07 lr: 2.575904938470175e-05 loss: 0.0501 (0.0518) time: 3.0698 data: 0.0078 max mem: 33408 +Epoch: [20] [2270/2639] eta: 0:18:36 lr: 2.5754460344160043e-05 loss: 0.0478 (0.0518) time: 3.0297 data: 0.0078 max mem: 33408 +Epoch: [20] [2280/2639] eta: 0:18:06 lr: 2.574987121276154e-05 loss: 0.0486 (0.0519) time: 3.0042 data: 0.0080 max mem: 33408 +Epoch: [20] [2290/2639] eta: 0:17:36 lr: 2.574528199048644e-05 loss: 0.0552 (0.0518) time: 3.0353 data: 0.0079 max mem: 33408 +Epoch: [20] [2300/2639] eta: 0:17:05 lr: 2.5740692677314965e-05 loss: 0.0473 (0.0519) time: 3.0240 data: 0.0076 max mem: 33408 +Epoch: [20] [2310/2639] eta: 0:16:35 lr: 2.5736103273227286e-05 loss: 0.0440 (0.0519) time: 3.0283 data: 0.0075 max mem: 33408 +Epoch: [20] [2320/2639] eta: 0:16:05 lr: 2.5731513778203597e-05 loss: 0.0440 (0.0518) time: 3.0190 data: 0.0076 max mem: 33408 +Epoch: [20] [2330/2639] eta: 0:15:35 lr: 2.5726924192224073e-05 loss: 0.0461 (0.0519) time: 3.0055 data: 0.0077 max mem: 33408 +Epoch: [20] [2340/2639] eta: 0:15:04 lr: 2.572233451526888e-05 loss: 0.0552 (0.0519) time: 3.0340 data: 0.0079 max mem: 33408 +Epoch: [20] [2350/2639] eta: 0:14:34 lr: 2.571774474731818e-05 loss: 0.0507 (0.0519) time: 3.0359 data: 0.0078 max mem: 33408 +Epoch: [20] [2360/2639] eta: 0:14:04 lr: 2.571315488835212e-05 loss: 0.0507 (0.0520) time: 3.0341 data: 0.0078 max mem: 33408 +Epoch: [20] [2370/2639] eta: 0:13:34 lr: 2.570856493835084e-05 loss: 0.0475 (0.0520) time: 3.0694 data: 0.0078 max mem: 33408 +Epoch: [20] [2380/2639] eta: 0:13:03 lr: 2.5703974897294485e-05 loss: 0.0471 (0.0520) time: 3.0488 data: 0.0082 max mem: 33408 +Epoch: [20] [2390/2639] eta: 0:12:33 lr: 2.569938476516317e-05 loss: 0.0470 (0.0520) time: 3.0048 data: 0.0081 max mem: 33408 +Epoch: [20] [2400/2639] eta: 0:12:03 lr: 2.569479454193703e-05 loss: 0.0494 (0.0520) time: 2.9976 data: 0.0077 max mem: 33408 +Epoch: [20] [2410/2639] eta: 0:11:32 lr: 2.5690204227596155e-05 loss: 0.0462 (0.0520) time: 2.9891 data: 0.0076 max mem: 33408 +Epoch: [20] [2420/2639] eta: 0:11:02 lr: 2.5685613822120657e-05 loss: 0.0456 (0.0520) time: 3.0514 data: 0.0077 max mem: 33408 +Epoch: [20] [2430/2639] eta: 0:10:32 lr: 2.568102332549062e-05 loss: 0.0427 (0.0520) time: 3.0521 data: 0.0076 max mem: 33408 +Epoch: [20] [2440/2639] eta: 0:10:02 lr: 2.5676432737686145e-05 loss: 0.0406 (0.0520) time: 2.9922 data: 0.0078 max mem: 33408 +Epoch: [20] [2450/2639] eta: 0:09:31 lr: 2.5671842058687296e-05 loss: 0.0447 (0.0520) time: 2.9945 data: 0.0079 max mem: 33408 +Epoch: [20] [2460/2639] eta: 0:09:01 lr: 2.5667251288474143e-05 loss: 0.0458 (0.0520) time: 2.9646 data: 0.0082 max mem: 33408 +Epoch: [20] [2470/2639] eta: 0:08:31 lr: 2.5662660427026746e-05 loss: 0.0462 (0.0521) time: 2.9796 data: 0.0083 max mem: 33408 +Epoch: [20] [2480/2639] eta: 0:08:01 lr: 2.5658069474325158e-05 loss: 0.0545 (0.0522) time: 2.9641 data: 0.0079 max mem: 33408 +Epoch: [20] [2490/2639] eta: 0:07:30 lr: 2.5653478430349425e-05 loss: 0.0503 (0.0522) time: 2.9713 data: 0.0083 max mem: 33408 +Epoch: [20] [2500/2639] eta: 0:07:00 lr: 2.5648887295079576e-05 loss: 0.0457 (0.0522) time: 2.9849 data: 0.0082 max mem: 33408 +Epoch: [20] [2510/2639] eta: 0:06:30 lr: 2.5644296068495648e-05 loss: 0.0557 (0.0522) time: 3.0163 data: 0.0080 max mem: 33408 +Epoch: [20] [2520/2639] eta: 0:05:59 lr: 2.5639704750577642e-05 loss: 0.0478 (0.0522) time: 3.0321 data: 0.0080 max mem: 33408 +Epoch: [20] [2530/2639] eta: 0:05:29 lr: 2.5635113341305584e-05 loss: 0.0496 (0.0523) time: 3.0111 data: 0.0081 max mem: 33408 +Epoch: [20] [2540/2639] eta: 0:04:59 lr: 2.5630521840659467e-05 loss: 0.0466 (0.0522) time: 3.0244 data: 0.0086 max mem: 33408 +Epoch: [20] [2550/2639] eta: 0:04:29 lr: 2.5625930248619285e-05 loss: 0.0433 (0.0522) time: 3.0272 data: 0.0083 max mem: 33408 +Epoch: [20] [2560/2639] eta: 0:03:58 lr: 2.562133856516502e-05 loss: 0.0425 (0.0522) time: 3.0312 data: 0.0083 max mem: 33408 +Epoch: [20] [2570/2639] eta: 0:03:28 lr: 2.5616746790276662e-05 loss: 0.0425 (0.0522) time: 3.0225 data: 0.0085 max mem: 33408 +Epoch: [20] [2580/2639] eta: 0:02:58 lr: 2.5612154923934163e-05 loss: 0.0444 (0.0522) time: 3.0140 data: 0.0079 max mem: 33408 +Epoch: [20] [2590/2639] eta: 0:02:28 lr: 2.5607562966117494e-05 loss: 0.0446 (0.0522) time: 3.0469 data: 0.0075 max mem: 33408 +Epoch: [20] [2600/2639] eta: 0:01:57 lr: 2.560297091680659e-05 loss: 0.0454 (0.0522) time: 3.0162 data: 0.0075 max mem: 33408 +Epoch: [20] [2610/2639] eta: 0:01:27 lr: 2.559837877598142e-05 loss: 0.0513 (0.0522) time: 2.9994 data: 0.0078 max mem: 33408 +Epoch: [20] [2620/2639] eta: 0:00:57 lr: 2.559378654362189e-05 loss: 0.0482 (0.0522) time: 3.0109 data: 0.0082 max mem: 33408 +Epoch: [20] [2630/2639] eta: 0:00:27 lr: 2.5589194219707952e-05 loss: 0.0468 (0.0522) time: 3.0250 data: 0.0083 max mem: 33408 +Epoch: [20] Total time: 2:13:03 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 1:52:06 time: 2.6141 data: 2.5077 max mem: 33408 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 100/2573] eta: 0:04:20 time: 0.0774 data: 0.0014 max mem: 33408 +Test: [ 200/2573] eta: 0:03:40 time: 0.0792 data: 0.0014 max mem: 33408 +Test: [ 300/2573] eta: 0:03:19 time: 0.0810 data: 0.0014 max mem: 33408 +Test: [ 400/2573] eta: 0:03:06 time: 0.0810 data: 0.0013 max mem: 33408 +Test: [ 500/2573] eta: 0:02:55 time: 0.0801 data: 0.0015 max mem: 33408 +Test: [ 600/2573] eta: 0:02:45 time: 0.0803 data: 0.0014 max mem: 33408 +Test: [ 700/2573] eta: 0:02:36 time: 0.0816 data: 0.0015 max mem: 33408 +Test: [ 800/2573] eta: 0:02:28 time: 0.0836 data: 0.0013 max mem: 33408 +Test: [ 900/2573] eta: 0:02:19 time: 0.0812 data: 0.0015 max mem: 33408 +Test: [1000/2573] eta: 0:02:10 time: 0.0801 data: 0.0014 max mem: 33408 +Test: [1100/2573] eta: 0:02:01 time: 0.0796 data: 0.0015 max mem: 33408 +Test: [1200/2573] eta: 0:01:53 time: 0.0809 data: 0.0014 max mem: 33408 +Test: [1300/2573] eta: 0:01:45 time: 0.0810 data: 0.0013 max mem: 33408 +Test: [1400/2573] eta: 0:01:36 time: 0.0791 data: 0.0015 max mem: 33408 +Test: [1500/2573] eta: 0:01:28 time: 0.0796 data: 0.0014 max mem: 33408 +Test: [1600/2573] eta: 0:01:19 time: 0.0827 data: 0.0015 max mem: 33408 +Test: [1700/2573] eta: 0:01:11 time: 0.0786 data: 0.0015 max mem: 33408 +Test: [1800/2573] eta: 0:01:03 time: 0.0827 data: 0.0015 max mem: 33408 +Test: [1900/2573] eta: 0:00:55 time: 0.0796 data: 0.0016 max mem: 33408 +Test: [2000/2573] eta: 0:00:46 time: 0.0809 data: 0.0015 max mem: 33408 +Test: [2100/2573] eta: 0:00:38 time: 0.0815 data: 0.0013 max mem: 33408 +Test: [2200/2573] eta: 0:00:30 time: 0.0835 data: 0.0014 max mem: 33408 +Test: [2300/2573] eta: 0:00:22 time: 0.0827 data: 0.0014 max mem: 33408 +Test: [2400/2573] eta: 0:00:14 time: 0.0778 data: 0.0014 max mem: 33408 +Test: [2500/2573] eta: 0:00:05 time: 0.0807 data: 0.0015 max mem: 33408 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: Total time: 0:03:31 +Final results: +Mean IoU is 63.33 + + precision@0.5 = 71.41 + precision@0.6 = 65.62 + precision@0.7 = 58.37 + precision@0.8 = 46.59 + precision@0.9 = 22.22 + overall IoU = 60.93 + +Average object IoU 63.326648663415995 +Overall IoU 60.930206298828125 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [21] [ 0/2639] eta: 3:38:51 lr: 2.558506104988977e-05 loss: 0.0326 (0.0326) time: 4.9760 data: 2.0604 max mem: 33408 +Epoch: [21] [ 10/2639] eta: 2:20:04 lr: 2.558046855196709e-05 loss: 0.0477 (0.0467) time: 3.1969 data: 0.1941 max mem: 33408 +Epoch: [21] [ 20/2639] eta: 2:17:15 lr: 2.557587596243174e-05 loss: 0.0489 (0.0497) time: 3.0528 data: 0.0074 max mem: 33408 +Epoch: [21] [ 30/2639] eta: 2:14:41 lr: 2.5571283281263586e-05 loss: 0.0368 (0.0472) time: 3.0427 data: 0.0078 max mem: 33408 +Epoch: [21] [ 40/2639] eta: 2:13:24 lr: 2.5566690508442538e-05 loss: 0.0395 (0.0470) time: 3.0120 data: 0.0081 max mem: 33408 +Epoch: [21] [ 50/2639] eta: 2:12:13 lr: 2.556209764394846e-05 loss: 0.0455 (0.0465) time: 3.0131 data: 0.0082 max mem: 33408 +Epoch: [21] [ 60/2639] eta: 2:11:41 lr: 2.555750468776122e-05 loss: 0.0415 (0.0455) time: 3.0310 data: 0.0089 max mem: 33408 +Epoch: [21] [ 70/2639] eta: 2:10:48 lr: 2.5552911639860676e-05 loss: 0.0445 (0.0465) time: 3.0313 data: 0.0091 max mem: 33408 +Epoch: [21] [ 80/2639] eta: 2:10:29 lr: 2.5548318500226688e-05 loss: 0.0455 (0.0467) time: 3.0463 data: 0.0086 max mem: 33408 +Epoch: [21] [ 90/2639] eta: 2:09:51 lr: 2.554372526883909e-05 loss: 0.0457 (0.0478) time: 3.0630 data: 0.0085 max mem: 33408 +Epoch: [21] [ 100/2639] eta: 2:09:00 lr: 2.553913194567772e-05 loss: 0.0465 (0.0476) time: 3.0047 data: 0.0085 max mem: 33408 +Epoch: [21] [ 110/2639] eta: 2:08:31 lr: 2.5534538530722406e-05 loss: 0.0411 (0.0474) time: 3.0137 data: 0.0079 max mem: 33408 +Epoch: [21] [ 120/2639] eta: 2:07:48 lr: 2.552994502395296e-05 loss: 0.0405 (0.0468) time: 3.0210 data: 0.0076 max mem: 33408 +Epoch: [21] [ 130/2639] eta: 2:07:22 lr: 2.5525351425349203e-05 loss: 0.0405 (0.0471) time: 3.0287 data: 0.0080 max mem: 33408 +Epoch: [21] [ 140/2639] eta: 2:06:37 lr: 2.5520757734890915e-05 loss: 0.0420 (0.0467) time: 3.0159 data: 0.0082 max mem: 33408 +Epoch: [21] [ 150/2639] eta: 2:06:03 lr: 2.5516163952557904e-05 loss: 0.0390 (0.0465) time: 2.9907 data: 0.0079 max mem: 33408 +Epoch: [21] [ 160/2639] eta: 2:05:32 lr: 2.5511570078329944e-05 loss: 0.0415 (0.0463) time: 3.0287 data: 0.0078 max mem: 33408 +Epoch: [21] [ 170/2639] eta: 2:04:54 lr: 2.5506976112186816e-05 loss: 0.0423 (0.0468) time: 3.0105 data: 0.0078 max mem: 33408 +Epoch: [21] [ 180/2639] eta: 2:04:17 lr: 2.550238205410828e-05 loss: 0.0405 (0.0467) time: 2.9861 data: 0.0076 max mem: 33408 +Epoch: [21] [ 190/2639] eta: 2:03:48 lr: 2.5497787904074104e-05 loss: 0.0447 (0.0470) time: 3.0147 data: 0.0077 max mem: 33408 +Epoch: [21] [ 200/2639] eta: 2:03:14 lr: 2.5493193662064024e-05 loss: 0.0447 (0.0468) time: 3.0231 data: 0.0078 max mem: 33408 +Epoch: [21] [ 210/2639] eta: 2:02:52 lr: 2.5488599328057794e-05 loss: 0.0410 (0.0467) time: 3.0532 data: 0.0077 max mem: 33408 +Epoch: [21] [ 220/2639] eta: 2:02:15 lr: 2.5484004902035136e-05 loss: 0.0400 (0.0468) time: 3.0399 data: 0.0080 max mem: 33408 +Epoch: [21] [ 230/2639] eta: 2:01:45 lr: 2.5479410383975782e-05 loss: 0.0379 (0.0464) time: 3.0077 data: 0.0079 max mem: 33408 +Epoch: [21] [ 240/2639] eta: 2:01:12 lr: 2.547481577385944e-05 loss: 0.0385 (0.0465) time: 3.0207 data: 0.0076 max mem: 33408 +Epoch: [21] [ 250/2639] eta: 2:00:37 lr: 2.5470221071665824e-05 loss: 0.0432 (0.0469) time: 2.9915 data: 0.0078 max mem: 33408 +Epoch: [21] [ 260/2639] eta: 2:00:12 lr: 2.5465626277374617e-05 loss: 0.0430 (0.0468) time: 3.0343 data: 0.0076 max mem: 33408 +Epoch: [21] [ 270/2639] eta: 1:59:44 lr: 2.546103139096553e-05 loss: 0.0406 (0.0467) time: 3.0718 data: 0.0075 max mem: 33408 +Epoch: [21] [ 280/2639] eta: 1:59:08 lr: 2.545643641241823e-05 loss: 0.0395 (0.0466) time: 3.0092 data: 0.0079 max mem: 33408 +Epoch: [21] [ 290/2639] eta: 1:58:37 lr: 2.545184134171239e-05 loss: 0.0395 (0.0472) time: 2.9950 data: 0.0080 max mem: 33408 +Epoch: [21] [ 300/2639] eta: 1:58:07 lr: 2.5447246178827678e-05 loss: 0.0382 (0.0469) time: 3.0287 data: 0.0079 max mem: 33408 +Epoch: [21] [ 310/2639] eta: 1:57:35 lr: 2.5442650923743754e-05 loss: 0.0388 (0.0471) time: 3.0235 data: 0.0077 max mem: 33408 +Epoch: [21] [ 320/2639] eta: 1:57:05 lr: 2.543805557644025e-05 loss: 0.0483 (0.0473) time: 3.0201 data: 0.0080 max mem: 33408 +Epoch: [21] [ 330/2639] eta: 1:56:35 lr: 2.5433460136896818e-05 loss: 0.0483 (0.0476) time: 3.0291 data: 0.0081 max mem: 33408 +Epoch: [21] [ 340/2639] eta: 1:56:02 lr: 2.5428864605093085e-05 loss: 0.0468 (0.0477) time: 3.0140 data: 0.0078 max mem: 33408 +Epoch: [21] [ 350/2639] eta: 1:55:34 lr: 2.5424268981008666e-05 loss: 0.0442 (0.0479) time: 3.0266 data: 0.0078 max mem: 33408 +Epoch: [21] [ 360/2639] eta: 1:55:02 lr: 2.541967326462318e-05 loss: 0.0423 (0.0480) time: 3.0319 data: 0.0080 max mem: 33408 +Epoch: [21] [ 370/2639] eta: 1:54:33 lr: 2.541507745591622e-05 loss: 0.0370 (0.0478) time: 3.0254 data: 0.0080 max mem: 33408 +Epoch: [21] [ 380/2639] eta: 1:53:59 lr: 2.54104815548674e-05 loss: 0.0360 (0.0479) time: 3.0070 data: 0.0083 max mem: 33408 +Epoch: [21] [ 390/2639] eta: 1:53:31 lr: 2.540588556145629e-05 loss: 0.0364 (0.0478) time: 3.0182 data: 0.0081 max mem: 33408 +Epoch: [21] [ 400/2639] eta: 1:53:00 lr: 2.5401289475662475e-05 loss: 0.0407 (0.0477) time: 3.0419 data: 0.0081 max mem: 33408 +Epoch: [21] [ 410/2639] eta: 1:52:30 lr: 2.5396693297465524e-05 loss: 0.0425 (0.0477) time: 3.0243 data: 0.0079 max mem: 33408 +Epoch: [21] [ 420/2639] eta: 1:51:58 lr: 2.5392097026844997e-05 loss: 0.0405 (0.0476) time: 3.0185 data: 0.0077 max mem: 33408 +Epoch: [21] [ 430/2639] eta: 1:51:34 lr: 2.5387500663780446e-05 loss: 0.0433 (0.0477) time: 3.0764 data: 0.0077 max mem: 33408 +Epoch: [21] [ 440/2639] eta: 1:51:06 lr: 2.5382904208251413e-05 loss: 0.0431 (0.0476) time: 3.1101 data: 0.0080 max mem: 33408 +Epoch: [21] [ 450/2639] eta: 1:50:34 lr: 2.5378307660237432e-05 loss: 0.0423 (0.0475) time: 3.0354 data: 0.0081 max mem: 33408 +Epoch: [21] [ 460/2639] eta: 1:50:05 lr: 2.5373711019718037e-05 loss: 0.0410 (0.0475) time: 3.0229 data: 0.0077 max mem: 33408 +Epoch: [21] [ 470/2639] eta: 1:49:32 lr: 2.5369114286672733e-05 loss: 0.0388 (0.0474) time: 3.0128 data: 0.0082 max mem: 33408 +Epoch: [21] [ 480/2639] eta: 1:49:00 lr: 2.5364517461081044e-05 loss: 0.0439 (0.0475) time: 2.9889 data: 0.0085 max mem: 33408 +Epoch: [21] [ 490/2639] eta: 1:48:31 lr: 2.5359920542922456e-05 loss: 0.0514 (0.0477) time: 3.0286 data: 0.0083 max mem: 33408 +Epoch: [21] [ 500/2639] eta: 1:48:04 lr: 2.5355323532176473e-05 loss: 0.0555 (0.0478) time: 3.0868 data: 0.0081 max mem: 33408 +Epoch: [21] [ 510/2639] eta: 1:47:33 lr: 2.5350726428822565e-05 loss: 0.0476 (0.0478) time: 3.0559 data: 0.0086 max mem: 33408 +Epoch: [21] [ 520/2639] eta: 1:47:03 lr: 2.5346129232840216e-05 loss: 0.0435 (0.0476) time: 3.0194 data: 0.0084 max mem: 33408 +Epoch: [21] [ 530/2639] eta: 1:46:32 lr: 2.534153194420888e-05 loss: 0.0434 (0.0477) time: 3.0319 data: 0.0077 max mem: 33408 +Epoch: [21] [ 540/2639] eta: 1:46:05 lr: 2.533693456290803e-05 loss: 0.0441 (0.0476) time: 3.0640 data: 0.0079 max mem: 33408 +Epoch: [21] [ 550/2639] eta: 1:45:32 lr: 2.5332337088917103e-05 loss: 0.0401 (0.0476) time: 3.0431 data: 0.0079 max mem: 33408 +Epoch: [21] [ 560/2639] eta: 1:45:01 lr: 2.5327739522215543e-05 loss: 0.0395 (0.0474) time: 2.9878 data: 0.0079 max mem: 33408 +Epoch: [21] [ 570/2639] eta: 1:44:29 lr: 2.532314186278278e-05 loss: 0.0438 (0.0476) time: 2.9923 data: 0.0081 max mem: 33408 +Epoch: [21] [ 580/2639] eta: 1:44:04 lr: 2.531854411059823e-05 loss: 0.0466 (0.0477) time: 3.0876 data: 0.0078 max mem: 33408 +Epoch: [21] [ 590/2639] eta: 1:43:32 lr: 2.5313946265641314e-05 loss: 0.0453 (0.0477) time: 3.0883 data: 0.0080 max mem: 33408 +Epoch: [21] [ 600/2639] eta: 1:43:03 lr: 2.530934832789143e-05 loss: 0.0398 (0.0476) time: 3.0213 data: 0.0081 max mem: 33408 +Epoch: [21] [ 610/2639] eta: 1:42:29 lr: 2.5304750297327984e-05 loss: 0.0432 (0.0476) time: 2.9935 data: 0.0080 max mem: 33408 +Epoch: [21] [ 620/2639] eta: 1:41:58 lr: 2.5300152173930353e-05 loss: 0.0451 (0.0477) time: 2.9646 data: 0.0079 max mem: 33408 +Epoch: [21] [ 630/2639] eta: 1:41:25 lr: 2.529555395767792e-05 loss: 0.0451 (0.0477) time: 2.9780 data: 0.0079 max mem: 33408 +Epoch: [21] [ 640/2639] eta: 1:40:54 lr: 2.5290955648550054e-05 loss: 0.0511 (0.0478) time: 2.9789 data: 0.0081 max mem: 33408 +Epoch: [21] [ 650/2639] eta: 1:40:22 lr: 2.528635724652611e-05 loss: 0.0519 (0.0480) time: 2.9893 data: 0.0080 max mem: 33408 +Epoch: [21] [ 660/2639] eta: 1:39:52 lr: 2.528175875158545e-05 loss: 0.0516 (0.0483) time: 3.0049 data: 0.0081 max mem: 33408 +Epoch: [21] [ 670/2639] eta: 1:39:21 lr: 2.5277160163707413e-05 loss: 0.0516 (0.0484) time: 3.0274 data: 0.0077 max mem: 33408 +Epoch: [21] [ 680/2639] eta: 1:38:52 lr: 2.5272561482871327e-05 loss: 0.0524 (0.0486) time: 3.0346 data: 0.0076 max mem: 33408 +Epoch: [21] [ 690/2639] eta: 1:38:20 lr: 2.526796270905653e-05 loss: 0.0488 (0.0485) time: 3.0179 data: 0.0078 max mem: 33408 +Epoch: [21] [ 700/2639] eta: 1:37:49 lr: 2.5263363842242327e-05 loss: 0.0406 (0.0484) time: 2.9918 data: 0.0077 max mem: 33408 +Epoch: [21] [ 710/2639] eta: 1:37:19 lr: 2.5258764882408036e-05 loss: 0.0364 (0.0484) time: 3.0089 data: 0.0075 max mem: 33408 +Epoch: [21] [ 720/2639] eta: 1:36:48 lr: 2.525416582953295e-05 loss: 0.0388 (0.0484) time: 3.0158 data: 0.0077 max mem: 33408 +Epoch: [21] [ 730/2639] eta: 1:36:19 lr: 2.5249566683596365e-05 loss: 0.0461 (0.0484) time: 3.0356 data: 0.0079 max mem: 33408 +Epoch: [21] [ 740/2639] eta: 1:35:48 lr: 2.5244967444577554e-05 loss: 0.0450 (0.0483) time: 3.0432 data: 0.0077 max mem: 33408 +Epoch: [21] [ 750/2639] eta: 1:35:18 lr: 2.5240368112455803e-05 loss: 0.0389 (0.0483) time: 3.0182 data: 0.0077 max mem: 33408 +Epoch: [21] [ 760/2639] eta: 1:34:47 lr: 2.5235768687210365e-05 loss: 0.0437 (0.0482) time: 3.0082 data: 0.0078 max mem: 33408 +Epoch: [21] [ 770/2639] eta: 1:34:17 lr: 2.5231169168820502e-05 loss: 0.0321 (0.0481) time: 3.0217 data: 0.0079 max mem: 33408 +Epoch: [21] [ 780/2639] eta: 1:33:49 lr: 2.522656955726545e-05 loss: 0.0337 (0.0480) time: 3.0792 data: 0.0077 max mem: 33408 +Epoch: [21] [ 790/2639] eta: 1:33:18 lr: 2.5221969852524464e-05 loss: 0.0385 (0.0479) time: 3.0552 data: 0.0075 max mem: 33408 +Epoch: [21] [ 800/2639] eta: 1:32:49 lr: 2.5217370054576757e-05 loss: 0.0336 (0.0478) time: 3.0564 data: 0.0075 max mem: 33408 +Epoch: [21] [ 810/2639] eta: 1:32:19 lr: 2.5212770163401554e-05 loss: 0.0373 (0.0479) time: 3.0675 data: 0.0076 max mem: 33408 +Epoch: [21] [ 820/2639] eta: 1:31:50 lr: 2.520817017897807e-05 loss: 0.0485 (0.0479) time: 3.0585 data: 0.0075 max mem: 33408 +Epoch: [21] [ 830/2639] eta: 1:31:21 lr: 2.52035701012855e-05 loss: 0.0455 (0.0479) time: 3.0855 data: 0.0075 max mem: 33408 +Epoch: [21] [ 840/2639] eta: 1:30:50 lr: 2.519896993030305e-05 loss: 0.0455 (0.0479) time: 3.0286 data: 0.0077 max mem: 33408 +Epoch: [21] [ 850/2639] eta: 1:30:20 lr: 2.5194369666009893e-05 loss: 0.0477 (0.0479) time: 3.0253 data: 0.0076 max mem: 33408 +Epoch: [21] [ 860/2639] eta: 1:29:49 lr: 2.5189769308385207e-05 loss: 0.0438 (0.0479) time: 3.0369 data: 0.0078 max mem: 33408 +Epoch: [21] [ 870/2639] eta: 1:29:19 lr: 2.518516885740816e-05 loss: 0.0443 (0.0479) time: 3.0262 data: 0.0075 max mem: 33408 +Epoch: [21] [ 880/2639] eta: 1:28:48 lr: 2.518056831305792e-05 loss: 0.0440 (0.0479) time: 3.0198 data: 0.0075 max mem: 33408 +Epoch: [21] [ 890/2639] eta: 1:28:19 lr: 2.517596767531361e-05 loss: 0.0443 (0.0479) time: 3.0299 data: 0.0080 max mem: 33408 +Epoch: [21] [ 900/2639] eta: 1:27:46 lr: 2.51713669441544e-05 loss: 0.0481 (0.0480) time: 2.9901 data: 0.0082 max mem: 33408 +Epoch: [21] [ 910/2639] eta: 1:27:16 lr: 2.51667661195594e-05 loss: 0.0427 (0.0480) time: 2.9791 data: 0.0084 max mem: 33408 +Epoch: [21] [ 920/2639] eta: 1:26:45 lr: 2.5162165201507748e-05 loss: 0.0423 (0.0480) time: 3.0205 data: 0.0080 max mem: 33408 +Epoch: [21] [ 930/2639] eta: 1:26:14 lr: 2.5157564189978546e-05 loss: 0.0423 (0.0480) time: 2.9883 data: 0.0078 max mem: 33408 +Epoch: [21] [ 940/2639] eta: 1:25:45 lr: 2.51529630849509e-05 loss: 0.0414 (0.0480) time: 3.0343 data: 0.0079 max mem: 33408 +Epoch: [21] [ 950/2639] eta: 1:25:16 lr: 2.514836188640391e-05 loss: 0.0510 (0.0481) time: 3.0988 data: 0.0079 max mem: 33408 +Epoch: [21] [ 960/2639] eta: 1:24:45 lr: 2.514376059431666e-05 loss: 0.0479 (0.0481) time: 3.0535 data: 0.0085 max mem: 33408 +Epoch: [21] [ 970/2639] eta: 1:24:15 lr: 2.513915920866823e-05 loss: 0.0463 (0.0481) time: 3.0249 data: 0.0081 max mem: 33408 +Epoch: [21] [ 980/2639] eta: 1:23:45 lr: 2.5134557729437687e-05 loss: 0.0472 (0.0482) time: 3.0369 data: 0.0077 max mem: 33408 +Epoch: [21] [ 990/2639] eta: 1:23:15 lr: 2.512995615660409e-05 loss: 0.0439 (0.0482) time: 3.0329 data: 0.0080 max mem: 33408 +Epoch: [21] [1000/2639] eta: 1:22:45 lr: 2.5125354490146497e-05 loss: 0.0480 (0.0482) time: 3.0579 data: 0.0080 max mem: 33408 +Epoch: [21] [1010/2639] eta: 1:22:16 lr: 2.5120752730043935e-05 loss: 0.0421 (0.0482) time: 3.0689 data: 0.0083 max mem: 33408 +Epoch: [21] [1020/2639] eta: 1:21:44 lr: 2.511615087627545e-05 loss: 0.0427 (0.0481) time: 3.0135 data: 0.0081 max mem: 33408 +Epoch: [21] [1030/2639] eta: 1:21:14 lr: 2.5111548928820066e-05 loss: 0.0460 (0.0482) time: 2.9897 data: 0.0082 max mem: 33408 +Epoch: [21] [1040/2639] eta: 1:20:43 lr: 2.5106946887656797e-05 loss: 0.0493 (0.0482) time: 3.0167 data: 0.0086 max mem: 33408 +Epoch: [21] [1050/2639] eta: 1:20:13 lr: 2.510234475276464e-05 loss: 0.0475 (0.0484) time: 3.0158 data: 0.0081 max mem: 33408 +Epoch: [21] [1060/2639] eta: 1:19:42 lr: 2.50977425241226e-05 loss: 0.0479 (0.0484) time: 3.0162 data: 0.0076 max mem: 33408 +Epoch: [21] [1070/2639] eta: 1:19:11 lr: 2.5093140201709663e-05 loss: 0.0476 (0.0484) time: 2.9785 data: 0.0081 max mem: 33408 +Epoch: [21] [1080/2639] eta: 1:18:42 lr: 2.5088537785504813e-05 loss: 0.0469 (0.0486) time: 3.0532 data: 0.0081 max mem: 33408 +Epoch: [21] [1090/2639] eta: 1:18:11 lr: 2.508393527548702e-05 loss: 0.0503 (0.0487) time: 3.0452 data: 0.0076 max mem: 33408 +Epoch: [21] [1100/2639] eta: 1:17:40 lr: 2.5079332671635236e-05 loss: 0.0452 (0.0487) time: 2.9735 data: 0.0077 max mem: 33408 +Epoch: [21] [1110/2639] eta: 1:17:10 lr: 2.5074729973928425e-05 loss: 0.0427 (0.0486) time: 3.0296 data: 0.0076 max mem: 33408 +Epoch: [21] [1120/2639] eta: 1:16:40 lr: 2.5070127182345515e-05 loss: 0.0440 (0.0486) time: 3.0461 data: 0.0073 max mem: 33408 +Epoch: [21] [1130/2639] eta: 1:16:10 lr: 2.5065524296865456e-05 loss: 0.0442 (0.0486) time: 3.0499 data: 0.0078 max mem: 33408 +Epoch: [21] [1140/2639] eta: 1:15:39 lr: 2.5060921317467166e-05 loss: 0.0442 (0.0486) time: 3.0120 data: 0.0080 max mem: 33408 +Epoch: [21] [1150/2639] eta: 1:15:08 lr: 2.505631824412956e-05 loss: 0.0370 (0.0485) time: 2.9762 data: 0.0077 max mem: 33408 +Epoch: [21] [1160/2639] eta: 1:14:38 lr: 2.505171507683155e-05 loss: 0.0366 (0.0486) time: 3.0185 data: 0.0077 max mem: 33408 +Epoch: [21] [1170/2639] eta: 1:14:07 lr: 2.5047111815552032e-05 loss: 0.0406 (0.0485) time: 3.0210 data: 0.0076 max mem: 33408 +Epoch: [21] [1180/2639] eta: 1:13:38 lr: 2.5042508460269885e-05 loss: 0.0406 (0.0485) time: 3.0337 data: 0.0075 max mem: 33408 +Epoch: [21] [1190/2639] eta: 1:13:07 lr: 2.5037905010964008e-05 loss: 0.0479 (0.0486) time: 3.0352 data: 0.0075 max mem: 33408 +Epoch: [21] [1200/2639] eta: 1:12:35 lr: 2.5033301467613252e-05 loss: 0.0495 (0.0486) time: 2.9537 data: 0.0078 max mem: 33408 +Epoch: [21] [1210/2639] eta: 1:12:04 lr: 2.5028697830196495e-05 loss: 0.0484 (0.0489) time: 2.9322 data: 0.0082 max mem: 33408 +Epoch: [21] [1220/2639] eta: 1:11:33 lr: 2.502409409869258e-05 loss: 0.0408 (0.0488) time: 2.9443 data: 0.0082 max mem: 33408 +Epoch: [21] [1230/2639] eta: 1:11:02 lr: 2.501949027308036e-05 loss: 0.0391 (0.0488) time: 2.9732 data: 0.0079 max mem: 33408 +Epoch: [21] [1240/2639] eta: 1:10:32 lr: 2.5014886353338657e-05 loss: 0.0406 (0.0488) time: 2.9998 data: 0.0077 max mem: 33408 +Epoch: [21] [1250/2639] eta: 1:10:01 lr: 2.5010282339446306e-05 loss: 0.0443 (0.0488) time: 2.9956 data: 0.0077 max mem: 33408 +Epoch: [21] [1260/2639] eta: 1:09:30 lr: 2.5005678231382113e-05 loss: 0.0530 (0.0489) time: 2.9731 data: 0.0078 max mem: 33408 +Epoch: [21] [1270/2639] eta: 1:08:59 lr: 2.50010740291249e-05 loss: 0.0454 (0.0489) time: 2.9540 data: 0.0076 max mem: 33408 +Epoch: [21] [1280/2639] eta: 1:08:28 lr: 2.4996469732653452e-05 loss: 0.0472 (0.0490) time: 2.9224 data: 0.0074 max mem: 33408 +Epoch: [21] [1290/2639] eta: 1:07:56 lr: 2.499186534194657e-05 loss: 0.0491 (0.0490) time: 2.8876 data: 0.0079 max mem: 33408 +Epoch: [21] [1300/2639] eta: 1:07:25 lr: 2.498726085698302e-05 loss: 0.0448 (0.0490) time: 2.9133 data: 0.0078 max mem: 33408 +Epoch: [21] [1310/2639] eta: 1:06:54 lr: 2.498265627774158e-05 loss: 0.0470 (0.0491) time: 2.9507 data: 0.0076 max mem: 33408 +Epoch: [21] [1320/2639] eta: 1:06:23 lr: 2.4978051604201015e-05 loss: 0.0463 (0.0490) time: 2.9383 data: 0.0078 max mem: 33408 +Epoch: [21] [1330/2639] eta: 1:05:52 lr: 2.4973446836340074e-05 loss: 0.0433 (0.0491) time: 2.9532 data: 0.0078 max mem: 33408 +Epoch: [21] [1340/2639] eta: 1:05:21 lr: 2.4968841974137504e-05 loss: 0.0426 (0.0490) time: 2.9517 data: 0.0078 max mem: 33408 +Epoch: [21] [1350/2639] eta: 1:04:51 lr: 2.4964237017572032e-05 loss: 0.0453 (0.0490) time: 2.9670 data: 0.0081 max mem: 33408 +Epoch: [21] [1360/2639] eta: 1:04:20 lr: 2.4959631966622394e-05 loss: 0.0422 (0.0490) time: 3.0055 data: 0.0084 max mem: 33408 +Epoch: [21] [1370/2639] eta: 1:03:50 lr: 2.495502682126729e-05 loss: 0.0489 (0.0491) time: 2.9738 data: 0.0083 max mem: 33408 +Epoch: [21] [1380/2639] eta: 1:03:19 lr: 2.4950421581485443e-05 loss: 0.0518 (0.0492) time: 2.9504 data: 0.0079 max mem: 33408 +Epoch: [21] [1390/2639] eta: 1:02:48 lr: 2.494581624725554e-05 loss: 0.0475 (0.0492) time: 2.9585 data: 0.0079 max mem: 33408 +Epoch: [21] [1400/2639] eta: 1:02:18 lr: 2.4941210818556274e-05 loss: 0.0515 (0.0493) time: 2.9874 data: 0.0079 max mem: 33408 +Epoch: [21] [1410/2639] eta: 1:01:47 lr: 2.493660529536632e-05 loss: 0.0570 (0.0494) time: 2.9452 data: 0.0073 max mem: 33408 +Epoch: [21] [1420/2639] eta: 1:01:16 lr: 2.4931999677664354e-05 loss: 0.0474 (0.0493) time: 2.9075 data: 0.0072 max mem: 33408 +Epoch: [21] [1430/2639] eta: 1:00:45 lr: 2.4927393965429033e-05 loss: 0.0448 (0.0493) time: 2.9344 data: 0.0072 max mem: 33408 +Epoch: [21] [1440/2639] eta: 1:00:14 lr: 2.4922788158639017e-05 loss: 0.0442 (0.0493) time: 2.9340 data: 0.0073 max mem: 33408 +Epoch: [21] [1450/2639] eta: 0:59:43 lr: 2.4918182257272928e-05 loss: 0.0442 (0.0493) time: 2.9072 data: 0.0075 max mem: 33408 +Epoch: [21] [1460/2639] eta: 0:59:12 lr: 2.4913576261309423e-05 loss: 0.0430 (0.0493) time: 2.8982 data: 0.0074 max mem: 33408 +Epoch: [21] [1470/2639] eta: 0:58:41 lr: 2.490897017072711e-05 loss: 0.0430 (0.0494) time: 2.9209 data: 0.0076 max mem: 33408 +Epoch: [21] [1480/2639] eta: 0:58:11 lr: 2.4904363985504613e-05 loss: 0.0490 (0.0494) time: 2.9421 data: 0.0078 max mem: 33408 +Epoch: [21] [1490/2639] eta: 0:57:39 lr: 2.489975770562053e-05 loss: 0.0485 (0.0494) time: 2.9275 data: 0.0080 max mem: 33408 +Epoch: [21] [1500/2639] eta: 0:57:08 lr: 2.4895151331053467e-05 loss: 0.0445 (0.0494) time: 2.8946 data: 0.0077 max mem: 33408 +Epoch: [21] [1510/2639] eta: 0:56:38 lr: 2.4890544861782e-05 loss: 0.0471 (0.0494) time: 2.8957 data: 0.0076 max mem: 33408 +Epoch: [21] [1520/2639] eta: 0:56:07 lr: 2.4885938297784718e-05 loss: 0.0471 (0.0494) time: 2.9437 data: 0.0082 max mem: 33408 +Epoch: [21] [1530/2639] eta: 0:55:37 lr: 2.488133163904017e-05 loss: 0.0462 (0.0494) time: 2.9539 data: 0.0080 max mem: 33408 +Epoch: [21] [1540/2639] eta: 0:55:06 lr: 2.4876724885526943e-05 loss: 0.0462 (0.0494) time: 2.9393 data: 0.0078 max mem: 33408 +Epoch: [21] [1550/2639] eta: 0:54:36 lr: 2.487211803722357e-05 loss: 0.0455 (0.0494) time: 2.9659 data: 0.0076 max mem: 33408 +Epoch: [21] [1560/2639] eta: 0:54:05 lr: 2.4867511094108588e-05 loss: 0.0439 (0.0494) time: 2.9282 data: 0.0074 max mem: 33408 +Epoch: [21] [1570/2639] eta: 0:53:34 lr: 2.4862904056160547e-05 loss: 0.0444 (0.0494) time: 2.9133 data: 0.0075 max mem: 33408 +Epoch: [21] [1580/2639] eta: 0:53:04 lr: 2.4858296923357946e-05 loss: 0.0583 (0.0495) time: 2.9333 data: 0.0075 max mem: 33408 +Epoch: [21] [1590/2639] eta: 0:52:33 lr: 2.485368969567932e-05 loss: 0.0493 (0.0494) time: 2.9351 data: 0.0076 max mem: 33408 +Epoch: [21] [1600/2639] eta: 0:52:03 lr: 2.4849082373103156e-05 loss: 0.0443 (0.0495) time: 2.9720 data: 0.0076 max mem: 33408 +Epoch: [21] [1610/2639] eta: 0:51:33 lr: 2.4844474955607956e-05 loss: 0.0467 (0.0494) time: 2.9634 data: 0.0077 max mem: 33408 +Epoch: [21] [1620/2639] eta: 0:51:03 lr: 2.4839867443172204e-05 loss: 0.0452 (0.0494) time: 2.9804 data: 0.0074 max mem: 33408 +Epoch: [21] [1630/2639] eta: 0:50:32 lr: 2.483525983577438e-05 loss: 0.0448 (0.0494) time: 2.9729 data: 0.0072 max mem: 33408 +Epoch: [21] [1640/2639] eta: 0:50:02 lr: 2.483065213339294e-05 loss: 0.0398 (0.0494) time: 2.9374 data: 0.0073 max mem: 33408 +Epoch: [21] [1650/2639] eta: 0:49:31 lr: 2.482604433600635e-05 loss: 0.0398 (0.0494) time: 2.9510 data: 0.0074 max mem: 33408 +Epoch: [21] [1660/2639] eta: 0:49:01 lr: 2.4821436443593053e-05 loss: 0.0488 (0.0494) time: 2.9268 data: 0.0074 max mem: 33408 +Epoch: [21] [1670/2639] eta: 0:48:30 lr: 2.481682845613149e-05 loss: 0.0451 (0.0494) time: 2.9136 data: 0.0078 max mem: 33408 +Epoch: [21] [1680/2639] eta: 0:47:59 lr: 2.4812220373600088e-05 loss: 0.0415 (0.0494) time: 2.9081 data: 0.0080 max mem: 33408 +Epoch: [21] [1690/2639] eta: 0:47:29 lr: 2.480761219597727e-05 loss: 0.0433 (0.0494) time: 2.9336 data: 0.0078 max mem: 33408 +Epoch: [21] [1700/2639] eta: 0:46:58 lr: 2.480300392324144e-05 loss: 0.0433 (0.0494) time: 2.9210 data: 0.0077 max mem: 33408 +Epoch: [21] [1710/2639] eta: 0:46:28 lr: 2.4798395555371012e-05 loss: 0.0484 (0.0496) time: 2.9105 data: 0.0077 max mem: 33408 +Epoch: [21] [1720/2639] eta: 0:45:58 lr: 2.4793787092344363e-05 loss: 0.0484 (0.0496) time: 2.9534 data: 0.0077 max mem: 33408 +Epoch: [21] [1730/2639] eta: 0:45:28 lr: 2.4789178534139884e-05 loss: 0.0445 (0.0496) time: 2.9465 data: 0.0078 max mem: 33408 +Epoch: [21] [1740/2639] eta: 0:44:57 lr: 2.4784569880735946e-05 loss: 0.0438 (0.0496) time: 2.9398 data: 0.0074 max mem: 33408 +Epoch: [21] [1750/2639] eta: 0:44:27 lr: 2.477996113211091e-05 loss: 0.0374 (0.0495) time: 2.9625 data: 0.0071 max mem: 33408 +Epoch: [21] [1760/2639] eta: 0:43:57 lr: 2.4775352288243132e-05 loss: 0.0389 (0.0495) time: 2.9637 data: 0.0070 max mem: 33408 +Epoch: [21] [1770/2639] eta: 0:43:27 lr: 2.477074334911096e-05 loss: 0.0503 (0.0495) time: 2.9864 data: 0.0071 max mem: 33408 +Epoch: [21] [1780/2639] eta: 0:42:57 lr: 2.4766134314692723e-05 loss: 0.0454 (0.0495) time: 2.9832 data: 0.0075 max mem: 33408 +Epoch: [21] [1790/2639] eta: 0:42:26 lr: 2.476152518496675e-05 loss: 0.0475 (0.0495) time: 2.9271 data: 0.0075 max mem: 33408 +Epoch: [21] [1800/2639] eta: 0:41:56 lr: 2.4756915959911358e-05 loss: 0.0514 (0.0495) time: 2.9121 data: 0.0072 max mem: 33408 +Epoch: [21] [1810/2639] eta: 0:41:26 lr: 2.475230663950485e-05 loss: 0.0448 (0.0495) time: 2.9431 data: 0.0075 max mem: 33408 +Epoch: [21] [1820/2639] eta: 0:40:56 lr: 2.4747697223725537e-05 loss: 0.0374 (0.0495) time: 2.9822 data: 0.0077 max mem: 33408 +Epoch: [21] [1830/2639] eta: 0:40:25 lr: 2.474308771255169e-05 loss: 0.0544 (0.0497) time: 2.9547 data: 0.0075 max mem: 33408 +Epoch: [21] [1840/2639] eta: 0:39:55 lr: 2.47384781059616e-05 loss: 0.0544 (0.0497) time: 2.9005 data: 0.0078 max mem: 33408 +Epoch: [21] [1850/2639] eta: 0:39:25 lr: 2.4733868403933525e-05 loss: 0.0592 (0.0498) time: 2.9257 data: 0.0080 max mem: 33408 +Epoch: [21] [1860/2639] eta: 0:38:55 lr: 2.4729258606445736e-05 loss: 0.0475 (0.0498) time: 2.9545 data: 0.0075 max mem: 33408 +Epoch: [21] [1870/2639] eta: 0:38:24 lr: 2.472464871347648e-05 loss: 0.0392 (0.0498) time: 2.9310 data: 0.0073 max mem: 33408 +Epoch: [21] [1880/2639] eta: 0:37:54 lr: 2.4720038725003998e-05 loss: 0.0403 (0.0498) time: 2.9541 data: 0.0075 max mem: 33408 +Epoch: [21] [1890/2639] eta: 0:37:24 lr: 2.471542864100652e-05 loss: 0.0429 (0.0498) time: 2.9606 data: 0.0077 max mem: 33408 +Epoch: [21] [1900/2639] eta: 0:36:54 lr: 2.4710818461462272e-05 loss: 0.0369 (0.0497) time: 2.9333 data: 0.0077 max mem: 33408 +Epoch: [21] [1910/2639] eta: 0:36:24 lr: 2.4706208186349457e-05 loss: 0.0459 (0.0497) time: 2.9242 data: 0.0076 max mem: 33408 +Epoch: [21] [1920/2639] eta: 0:35:54 lr: 2.4701597815646286e-05 loss: 0.0568 (0.0498) time: 2.9613 data: 0.0077 max mem: 33408 +Epoch: [21] [1930/2639] eta: 0:35:23 lr: 2.469698734933095e-05 loss: 0.0498 (0.0499) time: 2.9511 data: 0.0077 max mem: 33408 +Epoch: [21] [1940/2639] eta: 0:34:53 lr: 2.4692376787381643e-05 loss: 0.0420 (0.0499) time: 2.9015 data: 0.0075 max mem: 33408 +Epoch: [21] [1950/2639] eta: 0:34:23 lr: 2.468776612977652e-05 loss: 0.0463 (0.0499) time: 2.9299 data: 0.0075 max mem: 33408 +Epoch: [21] [1960/2639] eta: 0:33:53 lr: 2.4683155376493766e-05 loss: 0.0464 (0.0498) time: 2.9484 data: 0.0074 max mem: 33408 +Epoch: [21] [1970/2639] eta: 0:33:23 lr: 2.467854452751152e-05 loss: 0.0362 (0.0498) time: 2.9264 data: 0.0074 max mem: 33408 +Epoch: [21] [1980/2639] eta: 0:32:53 lr: 2.4673933582807943e-05 loss: 0.0361 (0.0498) time: 2.9353 data: 0.0074 max mem: 33408 +Epoch: [21] [1990/2639] eta: 0:32:23 lr: 2.4669322542361157e-05 loss: 0.0442 (0.0497) time: 2.9815 data: 0.0076 max mem: 33408 +Epoch: [21] [2000/2639] eta: 0:31:52 lr: 2.4664711406149298e-05 loss: 0.0444 (0.0498) time: 2.9648 data: 0.0075 max mem: 33408 +Epoch: [21] [2010/2639] eta: 0:31:22 lr: 2.466010017415048e-05 loss: 0.0466 (0.0498) time: 2.9287 data: 0.0074 max mem: 33408 +Epoch: [21] [2020/2639] eta: 0:30:52 lr: 2.4655488846342817e-05 loss: 0.0498 (0.0499) time: 2.9243 data: 0.0074 max mem: 33408 +Epoch: [21] [2030/2639] eta: 0:30:22 lr: 2.4650877422704398e-05 loss: 0.0466 (0.0499) time: 2.9285 data: 0.0071 max mem: 33408 +Epoch: [21] [2040/2639] eta: 0:29:52 lr: 2.464626590321332e-05 loss: 0.0406 (0.0498) time: 2.9048 data: 0.0071 max mem: 33408 +Epoch: [21] [2050/2639] eta: 0:29:22 lr: 2.4641654287847653e-05 loss: 0.0416 (0.0499) time: 2.9343 data: 0.0074 max mem: 33408 +Epoch: [21] [2060/2639] eta: 0:28:52 lr: 2.4637042576585474e-05 loss: 0.0522 (0.0499) time: 3.0009 data: 0.0073 max mem: 33408 +Epoch: [21] [2070/2639] eta: 0:28:22 lr: 2.4632430769404844e-05 loss: 0.0438 (0.0499) time: 2.9841 data: 0.0073 max mem: 33408 +Epoch: [21] [2080/2639] eta: 0:27:52 lr: 2.4627818866283808e-05 loss: 0.0411 (0.0499) time: 2.9369 data: 0.0074 max mem: 33408 +Epoch: [21] [2090/2639] eta: 0:27:22 lr: 2.4623206867200414e-05 loss: 0.0416 (0.0499) time: 2.9296 data: 0.0072 max mem: 33408 +Epoch: [21] [2100/2639] eta: 0:26:52 lr: 2.4618594772132682e-05 loss: 0.0398 (0.0499) time: 2.9278 data: 0.0073 max mem: 33408 +Epoch: [21] [2110/2639] eta: 0:26:22 lr: 2.4613982581058648e-05 loss: 0.0422 (0.0498) time: 2.9080 data: 0.0074 max mem: 33408 +Epoch: [21] [2120/2639] eta: 0:25:51 lr: 2.460937029395631e-05 loss: 0.0421 (0.0498) time: 2.9104 data: 0.0077 max mem: 33408 +Epoch: [21] [2130/2639] eta: 0:25:21 lr: 2.4604757910803684e-05 loss: 0.0395 (0.0498) time: 2.9188 data: 0.0084 max mem: 33408 +Epoch: [21] [2140/2639] eta: 0:24:51 lr: 2.4600145431578748e-05 loss: 0.0377 (0.0498) time: 2.9058 data: 0.0081 max mem: 33408 +Epoch: [21] [2150/2639] eta: 0:24:21 lr: 2.45955328562595e-05 loss: 0.0450 (0.0498) time: 2.9218 data: 0.0077 max mem: 33408 +Epoch: [21] [2160/2639] eta: 0:23:51 lr: 2.45909201848239e-05 loss: 0.0451 (0.0497) time: 2.9424 data: 0.0074 max mem: 33408 +Epoch: [21] [2170/2639] eta: 0:23:21 lr: 2.458630741724993e-05 loss: 0.0425 (0.0497) time: 2.9501 data: 0.0071 max mem: 33408 +Epoch: [21] [2180/2639] eta: 0:22:51 lr: 2.4581694553515522e-05 loss: 0.0373 (0.0497) time: 2.9420 data: 0.0071 max mem: 33408 +Epoch: [21] [2190/2639] eta: 0:22:21 lr: 2.4577081593598636e-05 loss: 0.0405 (0.0497) time: 2.9312 data: 0.0072 max mem: 33408 +Epoch: [21] [2200/2639] eta: 0:21:51 lr: 2.45724685374772e-05 loss: 0.0412 (0.0496) time: 2.9351 data: 0.0075 max mem: 33408 +Epoch: [21] [2210/2639] eta: 0:21:21 lr: 2.4567855385129146e-05 loss: 0.0416 (0.0496) time: 2.9199 data: 0.0076 max mem: 33408 +Epoch: [21] [2220/2639] eta: 0:20:51 lr: 2.456324213653238e-05 loss: 0.0420 (0.0496) time: 2.9523 data: 0.0075 max mem: 33408 +Epoch: [21] [2230/2639] eta: 0:20:21 lr: 2.4558628791664818e-05 loss: 0.0420 (0.0496) time: 2.9412 data: 0.0075 max mem: 33408 +Epoch: [21] [2240/2639] eta: 0:19:51 lr: 2.4554015350504348e-05 loss: 0.0432 (0.0498) time: 2.9175 data: 0.0073 max mem: 33408 +Epoch: [21] [2250/2639] eta: 0:19:21 lr: 2.4549401813028862e-05 loss: 0.0443 (0.0498) time: 2.9323 data: 0.0073 max mem: 33408 +Epoch: [21] [2260/2639] eta: 0:18:51 lr: 2.4544788179216234e-05 loss: 0.0462 (0.0498) time: 2.9348 data: 0.0075 max mem: 33408 +Epoch: [21] [2270/2639] eta: 0:18:21 lr: 2.4540174449044334e-05 loss: 0.0516 (0.0499) time: 2.9293 data: 0.0073 max mem: 33408 +Epoch: [21] [2280/2639] eta: 0:17:52 lr: 2.4535560622491015e-05 loss: 0.0438 (0.0498) time: 2.9129 data: 0.0074 max mem: 33408 +Epoch: [21] [2290/2639] eta: 0:17:22 lr: 2.453094669953413e-05 loss: 0.0428 (0.0498) time: 2.9494 data: 0.0073 max mem: 33408 +Epoch: [21] [2300/2639] eta: 0:16:52 lr: 2.4526332680151516e-05 loss: 0.0428 (0.0498) time: 2.9812 data: 0.0076 max mem: 33408 +Epoch: [21] [2310/2639] eta: 0:16:22 lr: 2.4521718564320992e-05 loss: 0.0446 (0.0499) time: 2.9516 data: 0.0078 max mem: 33408 +Epoch: [21] [2320/2639] eta: 0:15:52 lr: 2.451710435202039e-05 loss: 0.0525 (0.0499) time: 2.9389 data: 0.0076 max mem: 33408 +Epoch: [21] [2330/2639] eta: 0:15:22 lr: 2.4512490043227512e-05 loss: 0.0470 (0.0499) time: 2.9327 data: 0.0076 max mem: 33408 +Epoch: [21] [2340/2639] eta: 0:14:52 lr: 2.4507875637920165e-05 loss: 0.0471 (0.0499) time: 2.9208 data: 0.0075 max mem: 33408 +Epoch: [21] [2350/2639] eta: 0:14:22 lr: 2.4503261136076124e-05 loss: 0.0550 (0.0500) time: 2.9317 data: 0.0076 max mem: 33408 +Epoch: [21] [2360/2639] eta: 0:13:52 lr: 2.449864653767318e-05 loss: 0.0441 (0.0500) time: 2.9478 data: 0.0077 max mem: 33408 +Epoch: [21] [2370/2639] eta: 0:13:22 lr: 2.4494031842689096e-05 loss: 0.0447 (0.0500) time: 2.9679 data: 0.0079 max mem: 33408 +Epoch: [21] [2380/2639] eta: 0:12:52 lr: 2.4489417051101636e-05 loss: 0.0445 (0.0500) time: 2.9510 data: 0.0076 max mem: 33408 +Epoch: [21] [2390/2639] eta: 0:12:23 lr: 2.4484802162888544e-05 loss: 0.0437 (0.0500) time: 2.9245 data: 0.0074 max mem: 33408 +Epoch: [21] [2400/2639] eta: 0:11:53 lr: 2.4480187178027577e-05 loss: 0.0394 (0.0499) time: 2.9262 data: 0.0076 max mem: 33408 +Epoch: [21] [2410/2639] eta: 0:11:23 lr: 2.4475572096496443e-05 loss: 0.0388 (0.0499) time: 2.9601 data: 0.0075 max mem: 33408 +Epoch: [21] [2420/2639] eta: 0:10:53 lr: 2.4470956918272883e-05 loss: 0.0486 (0.0499) time: 2.9672 data: 0.0075 max mem: 33408 +Epoch: [21] [2430/2639] eta: 0:10:23 lr: 2.4466341643334594e-05 loss: 0.0500 (0.0500) time: 2.9359 data: 0.0078 max mem: 33408 +Epoch: [21] [2440/2639] eta: 0:09:53 lr: 2.4461726271659286e-05 loss: 0.0434 (0.0499) time: 2.9603 data: 0.0080 max mem: 33408 +Epoch: [21] [2450/2639] eta: 0:09:23 lr: 2.445711080322464e-05 loss: 0.0428 (0.0499) time: 2.9554 data: 0.0077 max mem: 33408 +Epoch: [21] [2460/2639] eta: 0:08:54 lr: 2.4452495238008353e-05 loss: 0.0429 (0.0499) time: 2.9450 data: 0.0074 max mem: 33408 +Epoch: [21] [2470/2639] eta: 0:08:24 lr: 2.4447879575988085e-05 loss: 0.0429 (0.0499) time: 2.9353 data: 0.0075 max mem: 33408 +Epoch: [21] [2480/2639] eta: 0:07:54 lr: 2.4443263817141503e-05 loss: 0.0399 (0.0499) time: 2.9376 data: 0.0075 max mem: 33408 +Epoch: [21] [2490/2639] eta: 0:07:24 lr: 2.4438647961446253e-05 loss: 0.0399 (0.0499) time: 2.9465 data: 0.0074 max mem: 33408 +Epoch: [21] [2500/2639] eta: 0:06:54 lr: 2.443403200887999e-05 loss: 0.0418 (0.0499) time: 2.9103 data: 0.0074 max mem: 33408 +Epoch: [21] [2510/2639] eta: 0:06:24 lr: 2.442941595942033e-05 loss: 0.0455 (0.0499) time: 2.9066 data: 0.0077 max mem: 33408 +Epoch: [21] [2520/2639] eta: 0:05:54 lr: 2.4424799813044908e-05 loss: 0.0453 (0.0499) time: 2.9209 data: 0.0075 max mem: 33408 +Epoch: [21] [2530/2639] eta: 0:05:25 lr: 2.442018356973133e-05 loss: 0.0436 (0.0499) time: 2.9292 data: 0.0076 max mem: 33408 +Epoch: [21] [2540/2639] eta: 0:04:55 lr: 2.4415567229457194e-05 loss: 0.0436 (0.0499) time: 2.9332 data: 0.0082 max mem: 33408 +Epoch: [21] [2550/2639] eta: 0:04:25 lr: 2.4410950792200114e-05 loss: 0.0429 (0.0499) time: 2.9505 data: 0.0080 max mem: 33408 +Epoch: [21] [2560/2639] eta: 0:03:55 lr: 2.440633425793765e-05 loss: 0.0448 (0.0499) time: 2.9414 data: 0.0072 max mem: 33408 +Epoch: [21] [2570/2639] eta: 0:03:25 lr: 2.440171762664739e-05 loss: 0.0418 (0.0499) time: 2.9306 data: 0.0072 max mem: 33408 +Epoch: [21] [2580/2639] eta: 0:02:55 lr: 2.4397100898306885e-05 loss: 0.0425 (0.0499) time: 2.9447 data: 0.0077 max mem: 33408 +Epoch: [21] [2590/2639] eta: 0:02:26 lr: 2.4392484072893697e-05 loss: 0.0454 (0.0499) time: 2.9366 data: 0.0082 max mem: 33408 +Epoch: [21] [2600/2639] eta: 0:01:56 lr: 2.4387867150385367e-05 loss: 0.0454 (0.0499) time: 2.9033 data: 0.0080 max mem: 33408 +Epoch: [21] [2610/2639] eta: 0:01:26 lr: 2.4383250130759435e-05 loss: 0.0419 (0.0499) time: 2.8995 data: 0.0078 max mem: 33408 +Epoch: [21] [2620/2639] eta: 0:00:56 lr: 2.437863301399341e-05 loss: 0.0441 (0.0500) time: 2.9186 data: 0.0081 max mem: 33408 +Epoch: [21] [2630/2639] eta: 0:00:26 lr: 2.4374015800064816e-05 loss: 0.0422 (0.0499) time: 2.9353 data: 0.0077 max mem: 33408 +Epoch: [21] Total time: 2:11:04 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 2:01:17 time: 2.8282 data: 2.7421 max mem: 33408 +Test: [ 100/2573] eta: 0:04:21 time: 0.0786 data: 0.0014 max mem: 33408 +Test: [ 200/2573] eta: 0:03:41 time: 0.0798 data: 0.0013 max mem: 33408 +Test: [ 300/2573] eta: 0:03:20 time: 0.0821 data: 0.0013 max mem: 33408 +Test: [ 400/2573] eta: 0:03:07 time: 0.0828 data: 0.0013 max mem: 33408 +Test: [ 500/2573] eta: 0:02:56 time: 0.0797 data: 0.0013 max mem: 33408 +Test: [ 600/2573] eta: 0:02:46 time: 0.0801 data: 0.0013 max mem: 33408 +Test: [ 700/2573] eta: 0:02:37 time: 0.0804 data: 0.0013 max mem: 33408 +Test: [ 800/2573] eta: 0:02:28 time: 0.0836 data: 0.0012 max mem: 33408 +Test: [ 900/2573] eta: 0:02:19 time: 0.0800 data: 0.0013 max mem: 33408 +Test: [1000/2573] eta: 0:02:10 time: 0.0802 data: 0.0013 max mem: 33408 +Test: [1100/2573] eta: 0:02:02 time: 0.0800 data: 0.0012 max mem: 33408 +Test: [1200/2573] eta: 0:01:53 time: 0.0797 data: 0.0013 max mem: 33408 +Test: [1300/2573] eta: 0:01:45 time: 0.0799 data: 0.0013 max mem: 33408 +Test: [1400/2573] eta: 0:01:36 time: 0.0792 data: 0.0013 max mem: 33408 +Test: [1500/2573] eta: 0:01:28 time: 0.0797 data: 0.0013 max mem: 33408 +Test: [1600/2573] eta: 0:01:19 time: 0.0830 data: 0.0013 max mem: 33408 +Test: [1700/2573] eta: 0:01:11 time: 0.0799 data: 0.0013 max mem: 33408 +Test: [1800/2573] eta: 0:01:03 time: 0.0826 data: 0.0013 max mem: 33408 +Test: [1900/2573] eta: 0:00:55 time: 0.0795 data: 0.0013 max mem: 33408 +Test: [2000/2573] eta: 0:00:46 time: 0.0802 data: 0.0013 max mem: 33408 +Test: [2100/2573] eta: 0:00:38 time: 0.0818 data: 0.0013 max mem: 33408 +Test: [2200/2573] eta: 0:00:30 time: 0.0827 data: 0.0013 max mem: 33408 +Test: [2300/2573] eta: 0:00:22 time: 0.0821 data: 0.0014 max mem: 33408 +Test: [2400/2573] eta: 0:00:14 time: 0.0765 data: 0.0013 max mem: 33408 +Test: [2500/2573] eta: 0:00:05 time: 0.0796 data: 0.0013 max mem: 33408 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: Total time: 0:03:30 +Final results: +Mean IoU is 63.67 + + precision@0.5 = 71.83 + precision@0.6 = 66.05 + precision@0.7 = 58.54 + precision@0.8 = 47.22 + precision@0.9 = 22.63 + overall IoU = 61.44 + +Average object IoU 63.666135443538266 +Overall IoU 61.44166946411133 +Better epoch: 21 + +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [22] [ 0/2639] eta: 3:50:38 lr: 2.4369860224436493e-05 loss: 0.0418 (0.0418) time: 5.2438 data: 2.0651 max mem: 33408 +Epoch: [22] [ 10/2639] eta: 2:19:00 lr: 2.4365242825837025e-05 loss: 0.0403 (0.0428) time: 3.1726 data: 0.1943 max mem: 33408 +Epoch: [22] [ 20/2639] eta: 2:13:43 lr: 2.4360625330009725e-05 loss: 0.0401 (0.0426) time: 2.9544 data: 0.0071 max mem: 33408 +Epoch: [22] [ 30/2639] eta: 2:12:14 lr: 2.435600773693206e-05 loss: 0.0363 (0.0426) time: 2.9689 data: 0.0072 max mem: 33408 +Epoch: [22] [ 40/2639] eta: 2:10:42 lr: 2.4351390046581497e-05 loss: 0.0383 (0.0434) time: 2.9695 data: 0.0076 max mem: 33408 +Epoch: [22] [ 50/2639] eta: 2:09:20 lr: 2.4346772258935487e-05 loss: 0.0402 (0.0448) time: 2.9297 data: 0.0076 max mem: 33408 +Epoch: [22] [ 60/2639] eta: 2:08:31 lr: 2.4342154373971483e-05 loss: 0.0402 (0.0442) time: 2.9333 data: 0.0072 max mem: 33408 +Epoch: [22] [ 70/2639] eta: 2:07:46 lr: 2.4337536391666914e-05 loss: 0.0423 (0.0454) time: 2.9512 data: 0.0071 max mem: 33408 +Epoch: [22] [ 80/2639] eta: 2:07:05 lr: 2.4332918311999207e-05 loss: 0.0487 (0.0458) time: 2.9494 data: 0.0071 max mem: 33408 +Epoch: [22] [ 90/2639] eta: 2:06:32 lr: 2.4328300134945778e-05 loss: 0.0457 (0.0471) time: 2.9572 data: 0.0072 max mem: 33408 +Epoch: [22] [ 100/2639] eta: 2:05:43 lr: 2.432368186048403e-05 loss: 0.0408 (0.0467) time: 2.9349 data: 0.0073 max mem: 33408 +Epoch: [22] [ 110/2639] eta: 2:05:09 lr: 2.4319063488591353e-05 loss: 0.0429 (0.0467) time: 2.9273 data: 0.0071 max mem: 33408 +Epoch: [22] [ 120/2639] eta: 2:04:37 lr: 2.4314445019245146e-05 loss: 0.0437 (0.0467) time: 2.9552 data: 0.0073 max mem: 33408 +Epoch: [22] [ 130/2639] eta: 2:04:04 lr: 2.4309826452422767e-05 loss: 0.0429 (0.0461) time: 2.9563 data: 0.0074 max mem: 33408 +Epoch: [22] [ 140/2639] eta: 2:03:34 lr: 2.4305207788101597e-05 loss: 0.0395 (0.0458) time: 2.9591 data: 0.0074 max mem: 33408 +Epoch: [22] [ 150/2639] eta: 2:02:52 lr: 2.4300589026258976e-05 loss: 0.0407 (0.0469) time: 2.9279 data: 0.0076 max mem: 33408 +Epoch: [22] [ 160/2639] eta: 2:02:17 lr: 2.429597016687226e-05 loss: 0.0382 (0.0464) time: 2.9098 data: 0.0077 max mem: 33408 +Epoch: [22] [ 170/2639] eta: 2:01:52 lr: 2.4291351209918775e-05 loss: 0.0375 (0.0462) time: 2.9585 data: 0.0077 max mem: 33408 +Epoch: [22] [ 180/2639] eta: 2:01:14 lr: 2.4286732155375848e-05 loss: 0.0407 (0.0460) time: 2.9465 data: 0.0080 max mem: 33408 +Epoch: [22] [ 190/2639] eta: 2:00:43 lr: 2.4282113003220804e-05 loss: 0.0468 (0.0463) time: 2.9254 data: 0.0079 max mem: 33408 +Epoch: [22] [ 200/2639] eta: 2:00:14 lr: 2.427749375343093e-05 loss: 0.0423 (0.0460) time: 2.9540 data: 0.0078 max mem: 33408 +Epoch: [22] [ 210/2639] eta: 1:59:53 lr: 2.427287440598354e-05 loss: 0.0413 (0.0458) time: 2.9955 data: 0.0076 max mem: 33408 +Epoch: [22] [ 220/2639] eta: 1:59:22 lr: 2.42682549608559e-05 loss: 0.0455 (0.0460) time: 2.9911 data: 0.0074 max mem: 33408 +Epoch: [22] [ 230/2639] eta: 1:58:47 lr: 2.42636354180253e-05 loss: 0.0472 (0.0461) time: 2.9284 data: 0.0076 max mem: 33408 +Epoch: [22] [ 240/2639] eta: 1:58:13 lr: 2.4259015777468988e-05 loss: 0.0467 (0.0462) time: 2.9107 data: 0.0073 max mem: 33408 +Epoch: [22] [ 250/2639] eta: 1:57:38 lr: 2.425439603916423e-05 loss: 0.0467 (0.0462) time: 2.9080 data: 0.0073 max mem: 33408 +Epoch: [22] [ 260/2639] eta: 1:57:04 lr: 2.4249776203088266e-05 loss: 0.0461 (0.0461) time: 2.9051 data: 0.0073 max mem: 33408 +Epoch: [22] [ 270/2639] eta: 1:56:28 lr: 2.4245156269218332e-05 loss: 0.0430 (0.0465) time: 2.8958 data: 0.0073 max mem: 33408 +Epoch: [22] [ 280/2639] eta: 1:56:00 lr: 2.4240536237531648e-05 loss: 0.0422 (0.0465) time: 2.9185 data: 0.0074 max mem: 33408 +Epoch: [22] [ 290/2639] eta: 1:55:30 lr: 2.4235916108005435e-05 loss: 0.0418 (0.0464) time: 2.9564 data: 0.0075 max mem: 33408 +Epoch: [22] [ 300/2639] eta: 1:54:58 lr: 2.4231295880616885e-05 loss: 0.0416 (0.0466) time: 2.9334 data: 0.0077 max mem: 33408 +Epoch: [22] [ 310/2639] eta: 1:54:30 lr: 2.4226675555343204e-05 loss: 0.0413 (0.0465) time: 2.9388 data: 0.0078 max mem: 33408 +Epoch: [22] [ 320/2639] eta: 1:54:05 lr: 2.422205513216156e-05 loss: 0.0410 (0.0462) time: 2.9883 data: 0.0080 max mem: 33408 +Epoch: [22] [ 330/2639] eta: 1:53:40 lr: 2.4217434611049144e-05 loss: 0.0364 (0.0460) time: 3.0150 data: 0.0080 max mem: 33408 +Epoch: [22] [ 340/2639] eta: 1:53:15 lr: 2.4212813991983106e-05 loss: 0.0364 (0.0461) time: 3.0195 data: 0.0076 max mem: 33408 +Epoch: [22] [ 350/2639] eta: 1:52:47 lr: 2.4208193274940604e-05 loss: 0.0399 (0.0460) time: 3.0038 data: 0.0075 max mem: 33408 +Epoch: [22] [ 360/2639] eta: 1:52:25 lr: 2.4203572459898775e-05 loss: 0.0411 (0.0460) time: 3.0296 data: 0.0079 max mem: 33408 +Epoch: [22] [ 370/2639] eta: 1:52:02 lr: 2.419895154683476e-05 loss: 0.0421 (0.0460) time: 3.0721 data: 0.0083 max mem: 33408 +Epoch: [22] [ 380/2639] eta: 1:51:35 lr: 2.419433053572567e-05 loss: 0.0377 (0.0460) time: 3.0380 data: 0.0081 max mem: 33408 +Epoch: [22] [ 390/2639] eta: 1:51:09 lr: 2.4189709426548632e-05 loss: 0.0411 (0.0462) time: 3.0129 data: 0.0078 max mem: 33408 +Epoch: [22] [ 400/2639] eta: 1:50:50 lr: 2.4185088219280733e-05 loss: 0.0417 (0.0462) time: 3.0906 data: 0.0081 max mem: 33408 +Epoch: [22] [ 410/2639] eta: 1:50:29 lr: 2.4180466913899074e-05 loss: 0.0417 (0.0463) time: 3.1436 data: 0.0083 max mem: 33408 +Epoch: [22] [ 420/2639] eta: 1:50:03 lr: 2.417584551038073e-05 loss: 0.0447 (0.0463) time: 3.0888 data: 0.0079 max mem: 33408 +Epoch: [22] [ 430/2639] eta: 1:49:38 lr: 2.417122400870277e-05 loss: 0.0413 (0.0461) time: 3.0594 data: 0.0078 max mem: 33408 +Epoch: [22] [ 440/2639] eta: 1:49:14 lr: 2.4166602408842274e-05 loss: 0.0355 (0.0460) time: 3.0865 data: 0.0079 max mem: 33408 +Epoch: [22] [ 450/2639] eta: 1:48:50 lr: 2.4161980710776268e-05 loss: 0.0420 (0.0461) time: 3.0950 data: 0.0080 max mem: 33408 +Epoch: [22] [ 460/2639] eta: 1:48:25 lr: 2.4157358914481813e-05 loss: 0.0448 (0.0462) time: 3.0841 data: 0.0080 max mem: 33408 +Epoch: [22] [ 470/2639] eta: 1:47:54 lr: 2.415273701993592e-05 loss: 0.0496 (0.0463) time: 3.0201 data: 0.0079 max mem: 33408 +Epoch: [22] [ 480/2639] eta: 1:47:26 lr: 2.4148115027115623e-05 loss: 0.0423 (0.0462) time: 3.0008 data: 0.0080 max mem: 33408 +Epoch: [22] [ 490/2639] eta: 1:47:00 lr: 2.414349293599792e-05 loss: 0.0423 (0.0462) time: 3.0560 data: 0.0076 max mem: 33408 +Epoch: [22] [ 500/2639] eta: 1:46:33 lr: 2.413887074655983e-05 loss: 0.0487 (0.0462) time: 3.0670 data: 0.0077 max mem: 33408 +Epoch: [22] [ 510/2639] eta: 1:46:05 lr: 2.4134248458778318e-05 loss: 0.0443 (0.0462) time: 3.0483 data: 0.0078 max mem: 33408 +Epoch: [22] [ 520/2639] eta: 1:45:36 lr: 2.4129626072630383e-05 loss: 0.0466 (0.0462) time: 3.0189 data: 0.0077 max mem: 33408 +Epoch: [22] [ 530/2639] eta: 1:45:07 lr: 2.4125003588092975e-05 loss: 0.0402 (0.0461) time: 3.0049 data: 0.0075 max mem: 33408 +Epoch: [22] [ 540/2639] eta: 1:44:37 lr: 2.412038100514307e-05 loss: 0.0348 (0.0459) time: 2.9999 data: 0.0074 max mem: 33408 +Epoch: [22] [ 550/2639] eta: 1:44:09 lr: 2.41157583237576e-05 loss: 0.0345 (0.0460) time: 3.0126 data: 0.0076 max mem: 33408 +Epoch: [22] [ 560/2639] eta: 1:43:38 lr: 2.411113554391352e-05 loss: 0.0433 (0.0460) time: 2.9975 data: 0.0074 max mem: 33408 +Epoch: [22] [ 570/2639] eta: 1:43:09 lr: 2.410651266558774e-05 loss: 0.0424 (0.0460) time: 3.0003 data: 0.0075 max mem: 33408 +Epoch: [22] [ 580/2639] eta: 1:42:40 lr: 2.4101889688757188e-05 loss: 0.0451 (0.0460) time: 3.0226 data: 0.0078 max mem: 33408 +Epoch: [22] [ 590/2639] eta: 1:42:14 lr: 2.4097266613398764e-05 loss: 0.0395 (0.0460) time: 3.0505 data: 0.0074 max mem: 33408 +Epoch: [22] [ 600/2639] eta: 1:41:45 lr: 2.409264343948937e-05 loss: 0.0373 (0.0459) time: 3.0568 data: 0.0076 max mem: 33408 +Epoch: [22] [ 610/2639] eta: 1:41:18 lr: 2.4088020167005886e-05 loss: 0.0411 (0.0459) time: 3.0538 data: 0.0078 max mem: 33408 +Epoch: [22] [ 620/2639] eta: 1:40:51 lr: 2.40833967959252e-05 loss: 0.0411 (0.0460) time: 3.0874 data: 0.0073 max mem: 33408 +Epoch: [22] [ 630/2639] eta: 1:40:22 lr: 2.407877332622416e-05 loss: 0.0392 (0.0458) time: 3.0573 data: 0.0074 max mem: 33408 +Epoch: [22] [ 640/2639] eta: 1:39:53 lr: 2.4074149757879634e-05 loss: 0.0393 (0.0458) time: 3.0322 data: 0.0073 max mem: 33408 +Epoch: [22] [ 650/2639] eta: 1:39:26 lr: 2.4069526090868456e-05 loss: 0.0393 (0.0458) time: 3.0681 data: 0.0072 max mem: 33408 +Epoch: [22] [ 660/2639] eta: 1:38:58 lr: 2.406490232516747e-05 loss: 0.0377 (0.0457) time: 3.0847 data: 0.0075 max mem: 33408 +Epoch: [22] [ 670/2639] eta: 1:38:29 lr: 2.4060278460753493e-05 loss: 0.0377 (0.0458) time: 3.0502 data: 0.0078 max mem: 33408 +Epoch: [22] [ 680/2639] eta: 1:38:01 lr: 2.405565449760334e-05 loss: 0.0412 (0.0458) time: 3.0443 data: 0.0078 max mem: 33408 +Epoch: [22] [ 690/2639] eta: 1:37:30 lr: 2.405103043569382e-05 loss: 0.0420 (0.0459) time: 3.0244 data: 0.0076 max mem: 33408 +Epoch: [22] [ 700/2639] eta: 1:37:03 lr: 2.4046406275001715e-05 loss: 0.0440 (0.0458) time: 3.0392 data: 0.0074 max mem: 33408 +Epoch: [22] [ 710/2639] eta: 1:36:34 lr: 2.4041782015503815e-05 loss: 0.0443 (0.0459) time: 3.0646 data: 0.0076 max mem: 33408 +Epoch: [22] [ 720/2639] eta: 1:36:06 lr: 2.403715765717689e-05 loss: 0.0450 (0.0458) time: 3.0637 data: 0.0078 max mem: 33408 +Epoch: [22] [ 730/2639] eta: 1:35:36 lr: 2.40325331999977e-05 loss: 0.0342 (0.0458) time: 3.0568 data: 0.0078 max mem: 33408 +Epoch: [22] [ 740/2639] eta: 1:35:09 lr: 2.4027908643942994e-05 loss: 0.0434 (0.0460) time: 3.0568 data: 0.0079 max mem: 33408 +Epoch: [22] [ 750/2639] eta: 1:34:39 lr: 2.402328398898952e-05 loss: 0.0438 (0.0459) time: 3.0598 data: 0.0077 max mem: 33408 +Epoch: [22] [ 760/2639] eta: 1:34:10 lr: 2.4018659235113997e-05 loss: 0.0387 (0.0459) time: 3.0441 data: 0.0073 max mem: 33408 +Epoch: [22] [ 770/2639] eta: 1:33:40 lr: 2.4014034382293156e-05 loss: 0.0464 (0.0460) time: 3.0282 data: 0.0077 max mem: 33408 +Epoch: [22] [ 780/2639] eta: 1:33:12 lr: 2.400940943050369e-05 loss: 0.0487 (0.0461) time: 3.0507 data: 0.0082 max mem: 33408 +Epoch: [22] [ 790/2639] eta: 1:32:42 lr: 2.4004784379722316e-05 loss: 0.0401 (0.0461) time: 3.0639 data: 0.0077 max mem: 33408 +Epoch: [22] [ 800/2639] eta: 1:32:11 lr: 2.400015922992571e-05 loss: 0.0417 (0.0460) time: 2.9821 data: 0.0078 max mem: 33408 +Epoch: [22] [ 810/2639] eta: 1:31:41 lr: 2.3995533981090556e-05 loss: 0.0404 (0.0460) time: 2.9699 data: 0.0082 max mem: 33408 +Epoch: [22] [ 820/2639] eta: 1:31:12 lr: 2.399090863319352e-05 loss: 0.0462 (0.0461) time: 3.0308 data: 0.0077 max mem: 33408 +Epoch: [22] [ 830/2639] eta: 1:30:41 lr: 2.3986283186211253e-05 loss: 0.0413 (0.0460) time: 3.0225 data: 0.0076 max mem: 33408 +Epoch: [22] [ 840/2639] eta: 1:30:11 lr: 2.3981657640120407e-05 loss: 0.0385 (0.0460) time: 3.0006 data: 0.0075 max mem: 33408 +Epoch: [22] [ 850/2639] eta: 1:29:42 lr: 2.3977031994897618e-05 loss: 0.0374 (0.0459) time: 3.0263 data: 0.0077 max mem: 33408 +Epoch: [22] [ 860/2639] eta: 1:29:13 lr: 2.3972406250519502e-05 loss: 0.0390 (0.0459) time: 3.0455 data: 0.0081 max mem: 33408 +Epoch: [22] [ 870/2639] eta: 1:28:44 lr: 2.3967780406962688e-05 loss: 0.0421 (0.0459) time: 3.0676 data: 0.0080 max mem: 33408 +Epoch: [22] [ 880/2639] eta: 1:28:15 lr: 2.3963154464203764e-05 loss: 0.0413 (0.0459) time: 3.0735 data: 0.0081 max mem: 33408 +Epoch: [22] [ 890/2639] eta: 1:27:46 lr: 2.3958528422219342e-05 loss: 0.0360 (0.0459) time: 3.0604 data: 0.0084 max mem: 33408 +Epoch: [22] [ 900/2639] eta: 1:27:15 lr: 2.395390228098599e-05 loss: 0.0390 (0.0459) time: 3.0258 data: 0.0082 max mem: 33408 +Epoch: [22] [ 910/2639] eta: 1:26:47 lr: 2.3949276040480286e-05 loss: 0.0390 (0.0459) time: 3.0544 data: 0.0081 max mem: 33408 +Epoch: [22] [ 920/2639] eta: 1:26:19 lr: 2.3944649700678788e-05 loss: 0.0427 (0.0459) time: 3.1129 data: 0.0079 max mem: 33408 +Epoch: [22] [ 930/2639] eta: 1:25:49 lr: 2.3940023261558052e-05 loss: 0.0450 (0.0459) time: 3.0781 data: 0.0078 max mem: 33408 +Epoch: [22] [ 940/2639] eta: 1:25:20 lr: 2.3935396723094623e-05 loss: 0.0386 (0.0458) time: 3.0634 data: 0.0083 max mem: 33408 +Epoch: [22] [ 950/2639] eta: 1:24:52 lr: 2.3930770085265016e-05 loss: 0.0382 (0.0458) time: 3.1033 data: 0.0084 max mem: 33408 +Epoch: [22] [ 960/2639] eta: 1:24:22 lr: 2.392614334804577e-05 loss: 0.0382 (0.0457) time: 3.0636 data: 0.0077 max mem: 33408 +Epoch: [22] [ 970/2639] eta: 1:23:51 lr: 2.3921516511413372e-05 loss: 0.0404 (0.0459) time: 3.0007 data: 0.0079 max mem: 33408 +Epoch: [22] [ 980/2639] eta: 1:23:22 lr: 2.3916889575344342e-05 loss: 0.0502 (0.0460) time: 3.0193 data: 0.0080 max mem: 33408 +Epoch: [22] [ 990/2639] eta: 1:22:51 lr: 2.3912262539815152e-05 loss: 0.0496 (0.0460) time: 3.0073 data: 0.0077 max mem: 33408 +Epoch: [22] [1000/2639] eta: 1:22:20 lr: 2.390763540480229e-05 loss: 0.0427 (0.0460) time: 2.9666 data: 0.0082 max mem: 33408 +Epoch: [22] [1010/2639] eta: 1:21:49 lr: 2.3903008170282208e-05 loss: 0.0358 (0.0459) time: 2.9758 data: 0.0081 max mem: 33408 +Epoch: [22] [1020/2639] eta: 1:21:21 lr: 2.3898380836231383e-05 loss: 0.0358 (0.0459) time: 3.0443 data: 0.0074 max mem: 33408 +Epoch: [22] [1030/2639] eta: 1:20:50 lr: 2.389375340262624e-05 loss: 0.0453 (0.0458) time: 3.0385 data: 0.0075 max mem: 33408 +Epoch: [22] [1040/2639] eta: 1:20:19 lr: 2.3889125869443226e-05 loss: 0.0380 (0.0458) time: 2.9875 data: 0.0083 max mem: 33408 +Epoch: [22] [1050/2639] eta: 1:19:50 lr: 2.388449823665876e-05 loss: 0.0415 (0.0458) time: 3.0166 data: 0.0084 max mem: 33408 +Epoch: [22] [1060/2639] eta: 1:19:20 lr: 2.3879870504249253e-05 loss: 0.0423 (0.0459) time: 3.0360 data: 0.0078 max mem: 33408 +Epoch: [22] [1070/2639] eta: 1:18:49 lr: 2.3875242672191113e-05 loss: 0.0457 (0.0460) time: 2.9932 data: 0.0078 max mem: 33408 +Epoch: [22] [1080/2639] eta: 1:18:19 lr: 2.3870614740460735e-05 loss: 0.0475 (0.0460) time: 2.9881 data: 0.0077 max mem: 33408 +Epoch: [22] [1090/2639] eta: 1:17:48 lr: 2.3865986709034485e-05 loss: 0.0382 (0.0459) time: 2.9891 data: 0.0076 max mem: 33408 +Epoch: [22] [1100/2639] eta: 1:17:18 lr: 2.386135857788875e-05 loss: 0.0451 (0.0460) time: 3.0054 data: 0.0078 max mem: 33408 +Epoch: [22] [1110/2639] eta: 1:16:48 lr: 2.385673034699988e-05 loss: 0.0556 (0.0461) time: 3.0455 data: 0.0077 max mem: 33408 +Epoch: [22] [1120/2639] eta: 1:16:17 lr: 2.3852102016344233e-05 loss: 0.0455 (0.0461) time: 2.9989 data: 0.0076 max mem: 33408 +Epoch: [22] [1130/2639] eta: 1:15:47 lr: 2.3847473585898132e-05 loss: 0.0425 (0.0461) time: 2.9799 data: 0.0078 max mem: 33408 +Epoch: [22] [1140/2639] eta: 1:15:18 lr: 2.3842845055637926e-05 loss: 0.0399 (0.0461) time: 3.0301 data: 0.0075 max mem: 33408 +Epoch: [22] [1150/2639] eta: 1:14:47 lr: 2.3838216425539912e-05 loss: 0.0399 (0.0461) time: 3.0321 data: 0.0074 max mem: 33408 +Epoch: [22] [1160/2639] eta: 1:14:18 lr: 2.3833587695580406e-05 loss: 0.0405 (0.0460) time: 3.0265 data: 0.0077 max mem: 33408 +Epoch: [22] [1170/2639] eta: 1:13:47 lr: 2.3828958865735706e-05 loss: 0.0417 (0.0461) time: 3.0048 data: 0.0081 max mem: 33408 +Epoch: [22] [1180/2639] eta: 1:13:16 lr: 2.382432993598209e-05 loss: 0.0432 (0.0461) time: 2.9786 data: 0.0076 max mem: 33408 +Epoch: [22] [1190/2639] eta: 1:12:47 lr: 2.381970090629584e-05 loss: 0.0379 (0.0461) time: 3.0320 data: 0.0071 max mem: 33408 +Epoch: [22] [1200/2639] eta: 1:12:17 lr: 2.381507177665321e-05 loss: 0.0406 (0.0461) time: 3.0324 data: 0.0072 max mem: 33408 +Epoch: [22] [1210/2639] eta: 1:11:46 lr: 2.381044254703046e-05 loss: 0.0464 (0.0462) time: 2.9934 data: 0.0077 max mem: 33408 +Epoch: [22] [1220/2639] eta: 1:11:16 lr: 2.3805813217403824e-05 loss: 0.0494 (0.0463) time: 3.0187 data: 0.0077 max mem: 33408 +Epoch: [22] [1230/2639] eta: 1:10:46 lr: 2.3801183787749547e-05 loss: 0.0420 (0.0463) time: 3.0228 data: 0.0073 max mem: 33408 +Epoch: [22] [1240/2639] eta: 1:10:16 lr: 2.379655425804383e-05 loss: 0.0362 (0.0463) time: 2.9919 data: 0.0077 max mem: 33408 +Epoch: [22] [1250/2639] eta: 1:09:45 lr: 2.3791924628262898e-05 loss: 0.0404 (0.0462) time: 2.9974 data: 0.0080 max mem: 33408 +Epoch: [22] [1260/2639] eta: 1:09:16 lr: 2.3787294898382943e-05 loss: 0.0432 (0.0463) time: 3.0175 data: 0.0079 max mem: 33408 +Epoch: [22] [1270/2639] eta: 1:08:47 lr: 2.3782665068380156e-05 loss: 0.0398 (0.0463) time: 3.0868 data: 0.0080 max mem: 33408 +Epoch: [22] [1280/2639] eta: 1:08:17 lr: 2.3778035138230706e-05 loss: 0.0406 (0.0463) time: 3.1018 data: 0.0077 max mem: 33408 +Epoch: [22] [1290/2639] eta: 1:07:46 lr: 2.377340510791077e-05 loss: 0.0415 (0.0463) time: 3.0083 data: 0.0076 max mem: 33408 +Epoch: [22] [1300/2639] eta: 1:07:16 lr: 2.3768774977396492e-05 loss: 0.0402 (0.0462) time: 2.9893 data: 0.0080 max mem: 33408 +Epoch: [22] [1310/2639] eta: 1:06:47 lr: 2.376414474666403e-05 loss: 0.0410 (0.0463) time: 3.0458 data: 0.0081 max mem: 33408 +Epoch: [22] [1320/2639] eta: 1:06:16 lr: 2.3759514415689503e-05 loss: 0.0414 (0.0462) time: 3.0218 data: 0.0080 max mem: 33408 +Epoch: [22] [1330/2639] eta: 1:05:46 lr: 2.375488398444905e-05 loss: 0.0382 (0.0462) time: 3.0129 data: 0.0079 max mem: 33408 +Epoch: [22] [1340/2639] eta: 1:05:17 lr: 2.3750253452918766e-05 loss: 0.0382 (0.0462) time: 3.0590 data: 0.0085 max mem: 33408 +Epoch: [22] [1350/2639] eta: 1:04:47 lr: 2.3745622821074764e-05 loss: 0.0434 (0.0462) time: 3.0615 data: 0.0085 max mem: 33408 +Epoch: [22] [1360/2639] eta: 1:04:16 lr: 2.3740992088893126e-05 loss: 0.0498 (0.0463) time: 3.0218 data: 0.0079 max mem: 33408 +Epoch: [22] [1370/2639] eta: 1:03:46 lr: 2.3736361256349943e-05 loss: 0.0441 (0.0463) time: 2.9861 data: 0.0081 max mem: 33408 +Epoch: [22] [1380/2639] eta: 1:03:16 lr: 2.3731730323421266e-05 loss: 0.0388 (0.0463) time: 2.9859 data: 0.0081 max mem: 33408 +Epoch: [22] [1390/2639] eta: 1:02:46 lr: 2.3727099290083173e-05 loss: 0.0399 (0.0463) time: 3.0402 data: 0.0078 max mem: 33408 +Epoch: [22] [1400/2639] eta: 1:02:16 lr: 2.3722468156311688e-05 loss: 0.0401 (0.0463) time: 3.0488 data: 0.0076 max mem: 33408 +Epoch: [22] [1410/2639] eta: 1:01:46 lr: 2.3717836922082865e-05 loss: 0.0409 (0.0463) time: 3.0081 data: 0.0077 max mem: 33408 +Epoch: [22] [1420/2639] eta: 1:01:16 lr: 2.3713205587372723e-05 loss: 0.0388 (0.0463) time: 3.0308 data: 0.0079 max mem: 33408 +Epoch: [22] [1430/2639] eta: 1:00:46 lr: 2.370857415215727e-05 loss: 0.0386 (0.0463) time: 3.0328 data: 0.0075 max mem: 33408 +Epoch: [22] [1440/2639] eta: 1:00:16 lr: 2.3703942616412523e-05 loss: 0.0436 (0.0463) time: 3.0273 data: 0.0076 max mem: 33408 +Epoch: [22] [1450/2639] eta: 0:59:46 lr: 2.3699310980114457e-05 loss: 0.0456 (0.0463) time: 3.0716 data: 0.0081 max mem: 33408 +Epoch: [22] [1460/2639] eta: 0:59:16 lr: 2.3694679243239065e-05 loss: 0.0456 (0.0464) time: 3.0562 data: 0.0079 max mem: 33408 +Epoch: [22] [1470/2639] eta: 0:58:46 lr: 2.3690047405762308e-05 loss: 0.0445 (0.0463) time: 3.0410 data: 0.0078 max mem: 33408 +Epoch: [22] [1480/2639] eta: 0:58:16 lr: 2.3685415467660158e-05 loss: 0.0445 (0.0464) time: 3.0507 data: 0.0078 max mem: 33408 +Epoch: [22] [1490/2639] eta: 0:57:47 lr: 2.368078342890855e-05 loss: 0.0396 (0.0464) time: 3.0614 data: 0.0082 max mem: 33408 +Epoch: [22] [1500/2639] eta: 0:57:17 lr: 2.3676151289483428e-05 loss: 0.0456 (0.0465) time: 3.0761 data: 0.0081 max mem: 33408 +Epoch: [22] [1510/2639] eta: 0:56:47 lr: 2.3671519049360717e-05 loss: 0.0456 (0.0465) time: 3.0296 data: 0.0077 max mem: 33408 +Epoch: [22] [1520/2639] eta: 0:56:16 lr: 2.3666886708516332e-05 loss: 0.0378 (0.0465) time: 3.0203 data: 0.0079 max mem: 33408 +Epoch: [22] [1530/2639] eta: 0:55:47 lr: 2.3662254266926173e-05 loss: 0.0431 (0.0465) time: 3.0497 data: 0.0077 max mem: 33408 +Epoch: [22] [1540/2639] eta: 0:55:16 lr: 2.365762172456614e-05 loss: 0.0413 (0.0465) time: 3.0176 data: 0.0075 max mem: 33408 +Epoch: [22] [1550/2639] eta: 0:54:46 lr: 2.365298908141211e-05 loss: 0.0424 (0.0465) time: 2.9949 data: 0.0079 max mem: 33408 +Epoch: [22] [1560/2639] eta: 0:54:16 lr: 2.364835633743996e-05 loss: 0.0430 (0.0465) time: 3.0278 data: 0.0080 max mem: 33408 +Epoch: [22] [1570/2639] eta: 0:53:46 lr: 2.3643723492625544e-05 loss: 0.0430 (0.0466) time: 3.0351 data: 0.0075 max mem: 33408 +Epoch: [22] [1580/2639] eta: 0:53:15 lr: 2.3639090546944717e-05 loss: 0.0451 (0.0465) time: 3.0034 data: 0.0075 max mem: 33408 +Epoch: [22] [1590/2639] eta: 0:52:45 lr: 2.3634457500373307e-05 loss: 0.0456 (0.0465) time: 2.9592 data: 0.0075 max mem: 33408 +Epoch: [22] [1600/2639] eta: 0:52:14 lr: 2.3629824352887157e-05 loss: 0.0466 (0.0466) time: 2.9671 data: 0.0075 max mem: 33408 +Epoch: [22] [1610/2639] eta: 0:51:44 lr: 2.3625191104462064e-05 loss: 0.0460 (0.0466) time: 2.9831 data: 0.0075 max mem: 33408 +Epoch: [22] [1620/2639] eta: 0:51:14 lr: 2.362055775507385e-05 loss: 0.0460 (0.0466) time: 3.0118 data: 0.0073 max mem: 33408 +Epoch: [22] [1630/2639] eta: 0:50:44 lr: 2.361592430469829e-05 loss: 0.0487 (0.0466) time: 3.0606 data: 0.0073 max mem: 33408 +Epoch: [22] [1640/2639] eta: 0:50:14 lr: 2.361129075331119e-05 loss: 0.0482 (0.0466) time: 3.0665 data: 0.0074 max mem: 33408 +Epoch: [22] [1650/2639] eta: 0:49:44 lr: 2.36066571008883e-05 loss: 0.0416 (0.0466) time: 3.0768 data: 0.0078 max mem: 33408 +Epoch: [22] [1660/2639] eta: 0:49:15 lr: 2.360202334740539e-05 loss: 0.0377 (0.0465) time: 3.0829 data: 0.0080 max mem: 33408 +Epoch: [22] [1670/2639] eta: 0:48:45 lr: 2.3597389492838214e-05 loss: 0.0345 (0.0465) time: 3.0604 data: 0.0077 max mem: 33408 +Epoch: [22] [1680/2639] eta: 0:48:14 lr: 2.3592755537162504e-05 loss: 0.0337 (0.0464) time: 3.0117 data: 0.0077 max mem: 33408 +Epoch: [22] [1690/2639] eta: 0:47:44 lr: 2.358812148035399e-05 loss: 0.0352 (0.0464) time: 3.0192 data: 0.0077 max mem: 33408 +Epoch: [22] [1700/2639] eta: 0:47:14 lr: 2.358348732238838e-05 loss: 0.0424 (0.0464) time: 3.0626 data: 0.0073 max mem: 33408 +Epoch: [22] [1710/2639] eta: 0:46:44 lr: 2.3578853063241394e-05 loss: 0.0429 (0.0465) time: 3.0283 data: 0.0074 max mem: 33408 +Epoch: [22] [1720/2639] eta: 0:46:14 lr: 2.357421870288871e-05 loss: 0.0434 (0.0465) time: 2.9983 data: 0.0076 max mem: 33408 +Epoch: [22] [1730/2639] eta: 0:45:44 lr: 2.3569584241306024e-05 loss: 0.0434 (0.0466) time: 3.0449 data: 0.0076 max mem: 33408 +Epoch: [22] [1740/2639] eta: 0:45:14 lr: 2.3564949678468996e-05 loss: 0.0453 (0.0466) time: 3.0448 data: 0.0072 max mem: 33408 +Epoch: [22] [1750/2639] eta: 0:44:44 lr: 2.3560315014353295e-05 loss: 0.0422 (0.0466) time: 3.0306 data: 0.0074 max mem: 33408 +Epoch: [22] [1760/2639] eta: 0:44:13 lr: 2.3555680248934564e-05 loss: 0.0405 (0.0466) time: 3.0248 data: 0.0077 max mem: 33408 +Epoch: [22] [1770/2639] eta: 0:43:43 lr: 2.3551045382188447e-05 loss: 0.0524 (0.0468) time: 3.0333 data: 0.0074 max mem: 33408 +Epoch: [22] [1780/2639] eta: 0:43:13 lr: 2.354641041409056e-05 loss: 0.0414 (0.0469) time: 3.0589 data: 0.0073 max mem: 33408 +Epoch: [22] [1790/2639] eta: 0:42:43 lr: 2.3541775344616537e-05 loss: 0.0419 (0.0468) time: 3.0742 data: 0.0070 max mem: 33408 +Epoch: [22] [1800/2639] eta: 0:42:13 lr: 2.3537140173741963e-05 loss: 0.0433 (0.0469) time: 3.0513 data: 0.0073 max mem: 33408 +Epoch: [22] [1810/2639] eta: 0:41:43 lr: 2.3532504901442444e-05 loss: 0.0413 (0.0468) time: 3.0267 data: 0.0073 max mem: 33408 +Epoch: [22] [1820/2639] eta: 0:41:13 lr: 2.352786952769355e-05 loss: 0.0431 (0.0469) time: 3.0417 data: 0.0078 max mem: 33408 +Epoch: [22] [1830/2639] eta: 0:40:43 lr: 2.3523234052470867e-05 loss: 0.0473 (0.0469) time: 3.0122 data: 0.0080 max mem: 33408 +Epoch: [22] [1840/2639] eta: 0:40:12 lr: 2.351859847574994e-05 loss: 0.0478 (0.0469) time: 3.0051 data: 0.0075 max mem: 33408 +Epoch: [22] [1850/2639] eta: 0:39:42 lr: 2.351396279750633e-05 loss: 0.0463 (0.0469) time: 3.0328 data: 0.0075 max mem: 33408 +Epoch: [22] [1860/2639] eta: 0:39:12 lr: 2.350932701771556e-05 loss: 0.0439 (0.0469) time: 2.9968 data: 0.0077 max mem: 33408 +Epoch: [22] [1870/2639] eta: 0:38:42 lr: 2.3504691136353173e-05 loss: 0.0439 (0.0469) time: 2.9707 data: 0.0073 max mem: 33408 +Epoch: [22] [1880/2639] eta: 0:38:11 lr: 2.3500055153394664e-05 loss: 0.0473 (0.0469) time: 2.9960 data: 0.0074 max mem: 33408 +Epoch: [22] [1890/2639] eta: 0:37:41 lr: 2.3495419068815553e-05 loss: 0.0383 (0.0468) time: 3.0211 data: 0.0075 max mem: 33408 +Epoch: [22] [1900/2639] eta: 0:37:11 lr: 2.349078288259132e-05 loss: 0.0431 (0.0469) time: 3.0376 data: 0.0074 max mem: 33408 +Epoch: [22] [1910/2639] eta: 0:36:41 lr: 2.3486146594697446e-05 loss: 0.0457 (0.0469) time: 3.0234 data: 0.0073 max mem: 33408 +Epoch: [22] [1920/2639] eta: 0:36:10 lr: 2.3481510205109417e-05 loss: 0.0484 (0.0470) time: 3.0045 data: 0.0071 max mem: 33408 +Epoch: [22] [1930/2639] eta: 0:35:40 lr: 2.347687371380267e-05 loss: 0.0451 (0.0470) time: 3.0120 data: 0.0078 max mem: 33408 +Epoch: [22] [1940/2639] eta: 0:35:10 lr: 2.3472237120752664e-05 loss: 0.0391 (0.0470) time: 3.0169 data: 0.0078 max mem: 33408 +Epoch: [22] [1950/2639] eta: 0:34:40 lr: 2.346760042593483e-05 loss: 0.0485 (0.0470) time: 3.0124 data: 0.0075 max mem: 33408 +Epoch: [22] [1960/2639] eta: 0:34:10 lr: 2.3462963629324593e-05 loss: 0.0413 (0.0469) time: 3.0087 data: 0.0078 max mem: 33408 +Epoch: [22] [1970/2639] eta: 0:33:40 lr: 2.3458326730897364e-05 loss: 0.0382 (0.0469) time: 3.0373 data: 0.0078 max mem: 33408 +Epoch: [22] [1980/2639] eta: 0:33:09 lr: 2.345368973062855e-05 loss: 0.0387 (0.0469) time: 3.0386 data: 0.0080 max mem: 33408 +Epoch: [22] [1990/2639] eta: 0:32:39 lr: 2.3449052628493535e-05 loss: 0.0370 (0.0469) time: 3.0110 data: 0.0080 max mem: 33408 +Epoch: [22] [2000/2639] eta: 0:32:09 lr: 2.34444154244677e-05 loss: 0.0351 (0.0468) time: 3.0093 data: 0.0075 max mem: 33408 +Epoch: [22] [2010/2639] eta: 0:31:39 lr: 2.343977811852641e-05 loss: 0.0340 (0.0468) time: 3.0185 data: 0.0075 max mem: 33408 +Epoch: [22] [2020/2639] eta: 0:31:09 lr: 2.3435140710645025e-05 loss: 0.0358 (0.0467) time: 3.0429 data: 0.0077 max mem: 33408 +Epoch: [22] [2030/2639] eta: 0:30:38 lr: 2.3430503200798888e-05 loss: 0.0356 (0.0467) time: 3.0045 data: 0.0077 max mem: 33408 +Epoch: [22] [2040/2639] eta: 0:30:08 lr: 2.3425865588963333e-05 loss: 0.0356 (0.0467) time: 2.9768 data: 0.0082 max mem: 33408 +Epoch: [22] [2050/2639] eta: 0:29:38 lr: 2.3421227875113674e-05 loss: 0.0466 (0.0468) time: 2.9612 data: 0.0089 max mem: 33408 +Epoch: [22] [2060/2639] eta: 0:29:07 lr: 2.341659005922524e-05 loss: 0.0470 (0.0467) time: 2.9910 data: 0.0081 max mem: 33408 +Epoch: [22] [2070/2639] eta: 0:28:37 lr: 2.3411952141273306e-05 loss: 0.0384 (0.0467) time: 3.0611 data: 0.0074 max mem: 33408 +Epoch: [22] [2080/2639] eta: 0:28:07 lr: 2.340731412123318e-05 loss: 0.0370 (0.0467) time: 3.0581 data: 0.0080 max mem: 33408 +Epoch: [22] [2090/2639] eta: 0:27:37 lr: 2.3402675999080122e-05 loss: 0.0463 (0.0467) time: 3.0260 data: 0.0079 max mem: 33408 +Epoch: [22] [2100/2639] eta: 0:27:07 lr: 2.3398037774789412e-05 loss: 0.0473 (0.0467) time: 3.0057 data: 0.0075 max mem: 33408 +Epoch: [22] [2110/2639] eta: 0:26:37 lr: 2.3393399448336287e-05 loss: 0.0379 (0.0467) time: 3.0026 data: 0.0078 max mem: 33408 +Epoch: [22] [2120/2639] eta: 0:26:07 lr: 2.3388761019696005e-05 loss: 0.0352 (0.0467) time: 3.0438 data: 0.0079 max mem: 33408 +Epoch: [22] [2130/2639] eta: 0:25:36 lr: 2.3384122488843783e-05 loss: 0.0394 (0.0466) time: 3.0290 data: 0.0074 max mem: 33408 +Epoch: [22] [2140/2639] eta: 0:25:06 lr: 2.337948385575485e-05 loss: 0.0436 (0.0466) time: 2.9883 data: 0.0072 max mem: 33408 +Epoch: [22] [2150/2639] eta: 0:24:36 lr: 2.3374845120404407e-05 loss: 0.0395 (0.0466) time: 3.0091 data: 0.0075 max mem: 33408 +Epoch: [22] [2160/2639] eta: 0:24:06 lr: 2.337020628276765e-05 loss: 0.0341 (0.0466) time: 3.0229 data: 0.0076 max mem: 33408 +Epoch: [22] [2170/2639] eta: 0:23:36 lr: 2.3365567342819772e-05 loss: 0.0360 (0.0465) time: 3.0426 data: 0.0076 max mem: 33408 +Epoch: [22] [2180/2639] eta: 0:23:05 lr: 2.3360928300535935e-05 loss: 0.0365 (0.0465) time: 3.0617 data: 0.0077 max mem: 33408 +Epoch: [22] [2190/2639] eta: 0:22:35 lr: 2.335628915589131e-05 loss: 0.0392 (0.0465) time: 3.0169 data: 0.0085 max mem: 33408 +Epoch: [22] [2200/2639] eta: 0:22:05 lr: 2.3351649908861032e-05 loss: 0.0378 (0.0464) time: 3.0373 data: 0.0088 max mem: 33408 +Epoch: [22] [2210/2639] eta: 0:21:35 lr: 2.334701055942026e-05 loss: 0.0364 (0.0464) time: 3.0476 data: 0.0082 max mem: 33408 +Epoch: [22] [2220/2639] eta: 0:21:05 lr: 2.33423711075441e-05 loss: 0.0432 (0.0464) time: 3.0120 data: 0.0077 max mem: 33408 +Epoch: [22] [2230/2639] eta: 0:20:35 lr: 2.3337731553207687e-05 loss: 0.0455 (0.0464) time: 3.0364 data: 0.0075 max mem: 33408 +Epoch: [22] [2240/2639] eta: 0:20:04 lr: 2.333309189638611e-05 loss: 0.0384 (0.0464) time: 3.0449 data: 0.0076 max mem: 33408 +Epoch: [22] [2250/2639] eta: 0:19:34 lr: 2.3328452137054468e-05 loss: 0.0445 (0.0464) time: 3.0282 data: 0.0080 max mem: 33408 +Epoch: [22] [2260/2639] eta: 0:19:04 lr: 2.3323812275187836e-05 loss: 0.0472 (0.0466) time: 2.9921 data: 0.0082 max mem: 33408 +Epoch: [22] [2270/2639] eta: 0:18:34 lr: 2.3319172310761296e-05 loss: 0.0508 (0.0466) time: 2.9742 data: 0.0078 max mem: 33408 +Epoch: [22] [2280/2639] eta: 0:18:03 lr: 2.331453224374989e-05 loss: 0.0518 (0.0466) time: 2.9624 data: 0.0080 max mem: 33408 +Epoch: [22] [2290/2639] eta: 0:17:33 lr: 2.3309892074128675e-05 loss: 0.0511 (0.0467) time: 3.0241 data: 0.0085 max mem: 33408 +Epoch: [22] [2300/2639] eta: 0:17:03 lr: 2.3305251801872675e-05 loss: 0.0422 (0.0467) time: 3.0503 data: 0.0084 max mem: 33408 +Epoch: [22] [2310/2639] eta: 0:16:33 lr: 2.3300611426956927e-05 loss: 0.0407 (0.0466) time: 3.0414 data: 0.0077 max mem: 33408 +Epoch: [22] [2320/2639] eta: 0:16:03 lr: 2.329597094935643e-05 loss: 0.0389 (0.0466) time: 3.0453 data: 0.0073 max mem: 33408 +Epoch: [22] [2330/2639] eta: 0:15:33 lr: 2.329133036904619e-05 loss: 0.0396 (0.0466) time: 2.9948 data: 0.0071 max mem: 33408 +Epoch: [22] [2340/2639] eta: 0:15:02 lr: 2.328668968600119e-05 loss: 0.0404 (0.0466) time: 2.9974 data: 0.0077 max mem: 33408 +Epoch: [22] [2350/2639] eta: 0:14:32 lr: 2.3282048900196414e-05 loss: 0.0415 (0.0466) time: 3.0592 data: 0.0080 max mem: 33408 +Epoch: [22] [2360/2639] eta: 0:14:02 lr: 2.3277408011606815e-05 loss: 0.0446 (0.0466) time: 3.0480 data: 0.0076 max mem: 33408 +Epoch: [22] [2370/2639] eta: 0:13:32 lr: 2.327276702020736e-05 loss: 0.0430 (0.0466) time: 3.0615 data: 0.0074 max mem: 33408 +Epoch: [22] [2380/2639] eta: 0:13:02 lr: 2.326812592597298e-05 loss: 0.0352 (0.0466) time: 3.0816 data: 0.0074 max mem: 33408 +Epoch: [22] [2390/2639] eta: 0:12:32 lr: 2.326348472887861e-05 loss: 0.0372 (0.0466) time: 3.0521 data: 0.0076 max mem: 33408 +Epoch: [22] [2400/2639] eta: 0:12:01 lr: 2.3258843428899157e-05 loss: 0.0393 (0.0465) time: 3.0822 data: 0.0078 max mem: 33408 +Epoch: [22] [2410/2639] eta: 0:11:31 lr: 2.3254202026009543e-05 loss: 0.0384 (0.0465) time: 3.0795 data: 0.0077 max mem: 33408 +Epoch: [22] [2420/2639] eta: 0:11:01 lr: 2.3249560520184657e-05 loss: 0.0454 (0.0466) time: 3.0561 data: 0.0076 max mem: 33408 +Epoch: [22] [2430/2639] eta: 0:10:31 lr: 2.3244918911399378e-05 loss: 0.0454 (0.0466) time: 3.0101 data: 0.0076 max mem: 33408 +Epoch: [22] [2440/2639] eta: 0:10:01 lr: 2.324027719962858e-05 loss: 0.0445 (0.0466) time: 2.9893 data: 0.0076 max mem: 33408 +Epoch: [22] [2450/2639] eta: 0:09:30 lr: 2.3235635384847123e-05 loss: 0.0450 (0.0467) time: 3.0347 data: 0.0075 max mem: 33408 +Epoch: [22] [2460/2639] eta: 0:09:00 lr: 2.323099346702986e-05 loss: 0.0443 (0.0467) time: 3.0346 data: 0.0076 max mem: 33408 +Epoch: [22] [2470/2639] eta: 0:08:30 lr: 2.3226351446151618e-05 loss: 0.0480 (0.0468) time: 3.0346 data: 0.0079 max mem: 33408 +Epoch: [22] [2480/2639] eta: 0:08:00 lr: 2.3221709322187226e-05 loss: 0.0480 (0.0468) time: 3.0927 data: 0.0078 max mem: 33408 +Epoch: [22] [2490/2639] eta: 0:07:30 lr: 2.321706709511149e-05 loss: 0.0440 (0.0468) time: 3.0878 data: 0.0080 max mem: 33408 +Epoch: [22] [2500/2639] eta: 0:07:00 lr: 2.3212424764899226e-05 loss: 0.0440 (0.0468) time: 3.0524 data: 0.0078 max mem: 33408 +Epoch: [22] [2510/2639] eta: 0:06:29 lr: 2.3207782331525208e-05 loss: 0.0418 (0.0468) time: 3.0702 data: 0.0073 max mem: 33408 +Epoch: [22] [2520/2639] eta: 0:05:59 lr: 2.320313979496422e-05 loss: 0.0478 (0.0468) time: 3.0673 data: 0.0072 max mem: 33408 +Epoch: [22] [2530/2639] eta: 0:05:29 lr: 2.3198497155191025e-05 loss: 0.0436 (0.0468) time: 3.0453 data: 0.0077 max mem: 33408 +Epoch: [22] [2540/2639] eta: 0:04:59 lr: 2.3193854412180383e-05 loss: 0.0440 (0.0468) time: 3.0492 data: 0.0079 max mem: 33408 +Epoch: [22] [2550/2639] eta: 0:04:28 lr: 2.3189211565907027e-05 loss: 0.0454 (0.0468) time: 3.0454 data: 0.0076 max mem: 33408 +Epoch: [22] [2560/2639] eta: 0:03:58 lr: 2.3184568616345693e-05 loss: 0.0424 (0.0468) time: 3.0122 data: 0.0074 max mem: 33408 +Epoch: [22] [2570/2639] eta: 0:03:28 lr: 2.31799255634711e-05 loss: 0.0438 (0.0468) time: 3.0046 data: 0.0075 max mem: 33408 +Epoch: [22] [2580/2639] eta: 0:02:58 lr: 2.3175282407257953e-05 loss: 0.0413 (0.0468) time: 3.0477 data: 0.0076 max mem: 33408 +Epoch: [22] [2590/2639] eta: 0:02:28 lr: 2.317063914768094e-05 loss: 0.0413 (0.0468) time: 3.0780 data: 0.0076 max mem: 33408 +Epoch: [22] [2600/2639] eta: 0:01:57 lr: 2.3165995784714763e-05 loss: 0.0420 (0.0469) time: 3.0570 data: 0.0078 max mem: 33408 +Epoch: [22] [2610/2639] eta: 0:01:27 lr: 2.3161352318334067e-05 loss: 0.0499 (0.0469) time: 3.0499 data: 0.0079 max mem: 33408 +Epoch: [22] [2620/2639] eta: 0:00:57 lr: 2.3156708748513532e-05 loss: 0.0449 (0.0469) time: 3.0326 data: 0.0082 max mem: 33408 +Epoch: [22] [2630/2639] eta: 0:00:27 lr: 2.3152065075227794e-05 loss: 0.0413 (0.0469) time: 3.0390 data: 0.0081 max mem: 33408 +Epoch: [22] Total time: 2:12:58 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 2:15:29 time: 3.1596 data: 3.0316 max mem: 33408 +Test: [ 100/2573] eta: 0:04:31 time: 0.0799 data: 0.0015 max mem: 33408 +Test: [ 200/2573] eta: 0:03:47 time: 0.0810 data: 0.0015 max mem: 33408 +Test: [ 300/2573] eta: 0:03:25 time: 0.0821 data: 0.0014 max mem: 33408 +Test: [ 400/2573] eta: 0:03:11 time: 0.0822 data: 0.0015 max mem: 33408 +Test: [ 500/2573] eta: 0:02:58 time: 0.0796 data: 0.0015 max mem: 33408 +Test: [ 600/2573] eta: 0:02:48 time: 0.0808 data: 0.0015 max mem: 33408 +Test: [ 700/2573] eta: 0:02:39 time: 0.0806 data: 0.0014 max mem: 33408 +Test: [ 800/2573] eta: 0:02:30 time: 0.0837 data: 0.0014 max mem: 33408 +Test: [ 900/2573] eta: 0:02:21 time: 0.0820 data: 0.0014 max mem: 33408 +Test: [1000/2573] eta: 0:02:12 time: 0.0811 data: 0.0014 max mem: 33408 +Test: [1100/2573] eta: 0:02:03 time: 0.0818 data: 0.0014 max mem: 33408 +Test: [1200/2573] eta: 0:01:55 time: 0.0807 data: 0.0013 max mem: 33408 +Test: [1300/2573] eta: 0:01:46 time: 0.0807 data: 0.0014 max mem: 33408 +Test: [1400/2573] eta: 0:01:37 time: 0.0801 data: 0.0015 max mem: 33408 +Test: [1500/2573] eta: 0:01:29 time: 0.0807 data: 0.0014 max mem: 33408 +Test: [1600/2573] eta: 0:01:20 time: 0.0850 data: 0.0015 max mem: 33408 +Test: [1700/2573] eta: 0:01:12 time: 0.0797 data: 0.0014 max mem: 33408 +Test: [1800/2573] eta: 0:01:04 time: 0.0829 data: 0.0015 max mem: 33408 +Test: [1900/2573] eta: 0:00:55 time: 0.0791 data: 0.0014 max mem: 33408 +Test: [2000/2573] eta: 0:00:47 time: 0.0815 data: 0.0015 max mem: 33408 +Test: [2100/2573] eta: 0:00:39 time: 0.0837 data: 0.0015 max mem: 33408 +Test: [2200/2573] eta: 0:00:30 time: 0.0819 data: 0.0014 max mem: 33408 +Test: [2300/2573] eta: 0:00:22 time: 0.0839 data: 0.0016 max mem: 33408 +Test: [2400/2573] eta: 0:00:14 time: 0.0776 data: 0.0015 max mem: 33408 +Test: [2500/2573] eta: 0:00:06 time: 0.0812 data: 0.0016 max mem: 33408 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: Total time: 0:03:33 +Final results: +Mean IoU is 63.36 + + precision@0.5 = 71.36 + precision@0.6 = 65.40 + precision@0.7 = 58.03 + precision@0.8 = 46.88 + precision@0.9 = 22.98 + overall IoU = 60.64 + +Average object IoU 63.355290168282316 +Overall IoU 60.63835525512695 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [23] [ 0/2639] eta: 3:56:40 lr: 2.3147885680786924e-05 loss: 0.0688 (0.0688) time: 5.3811 data: 2.1000 max mem: 33408 +Epoch: [23] [ 10/2639] eta: 2:19:08 lr: 2.3143241810847423e-05 loss: 0.0464 (0.0513) time: 3.1754 data: 0.1978 max mem: 33408 +Epoch: [23] [ 20/2639] eta: 2:16:02 lr: 2.313859783736913e-05 loss: 0.0464 (0.0491) time: 3.0035 data: 0.0071 max mem: 33408 +Epoch: [23] [ 30/2639] eta: 2:13:49 lr: 2.3133953760326647e-05 loss: 0.0449 (0.0484) time: 3.0238 data: 0.0072 max mem: 33408 +Epoch: [23] [ 40/2639] eta: 2:12:29 lr: 2.3129309579694574e-05 loss: 0.0432 (0.0509) time: 2.9975 data: 0.0078 max mem: 33408 +Epoch: [23] [ 50/2639] eta: 2:11:47 lr: 2.3124665295447474e-05 loss: 0.0432 (0.0503) time: 3.0179 data: 0.0078 max mem: 33408 +Epoch: [23] [ 60/2639] eta: 2:11:04 lr: 2.3120020907559923e-05 loss: 0.0356 (0.0479) time: 3.0309 data: 0.0080 max mem: 33408 +Epoch: [23] [ 70/2639] eta: 2:10:48 lr: 2.3115376416006463e-05 loss: 0.0353 (0.0465) time: 3.0573 data: 0.0080 max mem: 33408 +Epoch: [23] [ 80/2639] eta: 2:10:00 lr: 2.3110731820761648e-05 loss: 0.0423 (0.0463) time: 3.0438 data: 0.0080 max mem: 33408 +Epoch: [23] [ 90/2639] eta: 2:09:28 lr: 2.3106087121799994e-05 loss: 0.0395 (0.0462) time: 3.0212 data: 0.0080 max mem: 33408 +Epoch: [23] [ 100/2639] eta: 2:09:05 lr: 2.3101442319096034e-05 loss: 0.0362 (0.0452) time: 3.0608 data: 0.0079 max mem: 33408 +Epoch: [23] [ 110/2639] eta: 2:08:27 lr: 2.309679741262426e-05 loss: 0.0362 (0.0455) time: 3.0471 data: 0.0079 max mem: 33408 +Epoch: [23] [ 120/2639] eta: 2:07:53 lr: 2.309215240235918e-05 loss: 0.0376 (0.0449) time: 3.0240 data: 0.0079 max mem: 33408 +Epoch: [23] [ 130/2639] eta: 2:07:17 lr: 2.3087507288275258e-05 loss: 0.0359 (0.0443) time: 3.0248 data: 0.0078 max mem: 33408 +Epoch: [23] [ 140/2639] eta: 2:06:43 lr: 2.308286207034698e-05 loss: 0.0359 (0.0441) time: 3.0216 data: 0.0077 max mem: 33408 +Epoch: [23] [ 150/2639] eta: 2:06:25 lr: 2.3078216748548788e-05 loss: 0.0364 (0.0438) time: 3.0706 data: 0.0077 max mem: 33408 +Epoch: [23] [ 160/2639] eta: 2:06:03 lr: 2.3073571322855145e-05 loss: 0.0347 (0.0438) time: 3.1095 data: 0.0077 max mem: 33408 +Epoch: [23] [ 170/2639] eta: 2:05:22 lr: 2.3068925793240474e-05 loss: 0.0375 (0.0442) time: 3.0426 data: 0.0081 max mem: 33408 +Epoch: [23] [ 180/2639] eta: 2:04:41 lr: 2.30642801596792e-05 loss: 0.0408 (0.0440) time: 2.9745 data: 0.0081 max mem: 33408 +Epoch: [23] [ 190/2639] eta: 2:04:02 lr: 2.3059634422145725e-05 loss: 0.0377 (0.0437) time: 2.9711 data: 0.0080 max mem: 33408 +Epoch: [23] [ 200/2639] eta: 2:03:28 lr: 2.305498858061446e-05 loss: 0.0378 (0.0436) time: 2.9937 data: 0.0083 max mem: 33408 +Epoch: [23] [ 210/2639] eta: 2:02:58 lr: 2.305034263505978e-05 loss: 0.0378 (0.0442) time: 3.0230 data: 0.0089 max mem: 33408 +Epoch: [23] [ 220/2639] eta: 2:02:35 lr: 2.3045696585456065e-05 loss: 0.0378 (0.0444) time: 3.0707 data: 0.0091 max mem: 33408 +Epoch: [23] [ 230/2639] eta: 2:02:02 lr: 2.3041050431777676e-05 loss: 0.0378 (0.0443) time: 3.0617 data: 0.0081 max mem: 33408 +Epoch: [23] [ 240/2639] eta: 2:01:29 lr: 2.303640417399896e-05 loss: 0.0410 (0.0444) time: 3.0154 data: 0.0075 max mem: 33408 +Epoch: [23] [ 250/2639] eta: 2:00:59 lr: 2.303175781209425e-05 loss: 0.0407 (0.0443) time: 3.0274 data: 0.0077 max mem: 33408 +Epoch: [23] [ 260/2639] eta: 2:00:30 lr: 2.3027111346037884e-05 loss: 0.0399 (0.0443) time: 3.0480 data: 0.0081 max mem: 33408 +Epoch: [23] [ 270/2639] eta: 1:59:58 lr: 2.3022464775804158e-05 loss: 0.0411 (0.0443) time: 3.0394 data: 0.0080 max mem: 33408 +Epoch: [23] [ 280/2639] eta: 1:59:23 lr: 2.3017818101367385e-05 loss: 0.0371 (0.0444) time: 3.0039 data: 0.0077 max mem: 33408 +Epoch: [23] [ 290/2639] eta: 1:58:56 lr: 2.3013171322701856e-05 loss: 0.0377 (0.0443) time: 3.0332 data: 0.0075 max mem: 33408 +Epoch: [23] [ 300/2639] eta: 1:58:26 lr: 2.3008524439781838e-05 loss: 0.0380 (0.0443) time: 3.0588 data: 0.0075 max mem: 33408 +Epoch: [23] [ 310/2639] eta: 1:57:59 lr: 2.300387745258161e-05 loss: 0.0389 (0.0443) time: 3.0595 data: 0.0075 max mem: 33408 +Epoch: [23] [ 320/2639] eta: 1:57:27 lr: 2.299923036107541e-05 loss: 0.0388 (0.0445) time: 3.0511 data: 0.0077 max mem: 33408 +Epoch: [23] [ 330/2639] eta: 1:56:56 lr: 2.299458316523749e-05 loss: 0.0388 (0.0446) time: 3.0255 data: 0.0080 max mem: 33408 +Epoch: [23] [ 340/2639] eta: 1:56:25 lr: 2.2989935865042064e-05 loss: 0.0376 (0.0445) time: 3.0283 data: 0.0078 max mem: 33408 +Epoch: [23] [ 350/2639] eta: 1:55:57 lr: 2.2985288460463365e-05 loss: 0.0370 (0.0444) time: 3.0523 data: 0.0076 max mem: 33408 +Epoch: [23] [ 360/2639] eta: 1:55:30 lr: 2.2980640951475583e-05 loss: 0.0379 (0.0443) time: 3.0828 data: 0.0075 max mem: 33408 +Epoch: [23] [ 370/2639] eta: 1:55:04 lr: 2.2975993338052922e-05 loss: 0.0398 (0.0445) time: 3.1063 data: 0.0079 max mem: 33408 +Epoch: [23] [ 380/2639] eta: 1:54:35 lr: 2.2971345620169553e-05 loss: 0.0430 (0.0447) time: 3.0946 data: 0.0078 max mem: 33408 +Epoch: [23] [ 390/2639] eta: 1:54:05 lr: 2.296669779779965e-05 loss: 0.0378 (0.0445) time: 3.0536 data: 0.0077 max mem: 33408 +Epoch: [23] [ 400/2639] eta: 1:53:32 lr: 2.2962049870917357e-05 loss: 0.0337 (0.0445) time: 3.0223 data: 0.0079 max mem: 33408 +Epoch: [23] [ 410/2639] eta: 1:53:04 lr: 2.2957401839496835e-05 loss: 0.0381 (0.0444) time: 3.0447 data: 0.0081 max mem: 33408 +Epoch: [23] [ 420/2639] eta: 1:52:33 lr: 2.2952753703512196e-05 loss: 0.0378 (0.0442) time: 3.0562 data: 0.0079 max mem: 33408 +Epoch: [23] [ 430/2639] eta: 1:52:00 lr: 2.2948105462937572e-05 loss: 0.0332 (0.0441) time: 3.0171 data: 0.0078 max mem: 33408 +Epoch: [23] [ 440/2639] eta: 1:51:31 lr: 2.294345711774706e-05 loss: 0.0381 (0.0442) time: 3.0391 data: 0.0083 max mem: 33408 +Epoch: [23] [ 450/2639] eta: 1:50:58 lr: 2.2938808667914766e-05 loss: 0.0426 (0.0441) time: 3.0212 data: 0.0079 max mem: 33408 +Epoch: [23] [ 460/2639] eta: 1:50:28 lr: 2.2934160113414756e-05 loss: 0.0470 (0.0442) time: 3.0180 data: 0.0074 max mem: 33408 +Epoch: [23] [ 470/2639] eta: 1:49:56 lr: 2.2929511454221118e-05 loss: 0.0513 (0.0444) time: 3.0391 data: 0.0075 max mem: 33408 +Epoch: [23] [ 480/2639] eta: 1:49:25 lr: 2.2924862690307892e-05 loss: 0.0450 (0.0443) time: 3.0147 data: 0.0074 max mem: 33408 +Epoch: [23] [ 490/2639] eta: 1:48:53 lr: 2.292021382164914e-05 loss: 0.0352 (0.0444) time: 3.0062 data: 0.0080 max mem: 33408 +Epoch: [23] [ 500/2639] eta: 1:48:18 lr: 2.2915564848218878e-05 loss: 0.0433 (0.0445) time: 2.9722 data: 0.0082 max mem: 33408 +Epoch: [23] [ 510/2639] eta: 1:47:46 lr: 2.2910915769991136e-05 loss: 0.0440 (0.0446) time: 2.9694 data: 0.0080 max mem: 33408 +Epoch: [23] [ 520/2639] eta: 1:47:16 lr: 2.2906266586939922e-05 loss: 0.0386 (0.0445) time: 3.0165 data: 0.0077 max mem: 33408 +Epoch: [23] [ 530/2639] eta: 1:46:47 lr: 2.2901617299039227e-05 loss: 0.0362 (0.0444) time: 3.0638 data: 0.0077 max mem: 33408 +Epoch: [23] [ 540/2639] eta: 1:46:18 lr: 2.2896967906263045e-05 loss: 0.0362 (0.0443) time: 3.0800 data: 0.0083 max mem: 33408 +Epoch: [23] [ 550/2639] eta: 1:45:50 lr: 2.2892318408585336e-05 loss: 0.0373 (0.0444) time: 3.0796 data: 0.0084 max mem: 33408 +Epoch: [23] [ 560/2639] eta: 1:45:16 lr: 2.288766880598007e-05 loss: 0.0403 (0.0444) time: 3.0263 data: 0.0084 max mem: 33408 +Epoch: [23] [ 570/2639] eta: 1:44:45 lr: 2.288301909842118e-05 loss: 0.0433 (0.0445) time: 2.9942 data: 0.0084 max mem: 33408 +Epoch: [23] [ 580/2639] eta: 1:44:16 lr: 2.2878369285882615e-05 loss: 0.0357 (0.0443) time: 3.0403 data: 0.0080 max mem: 33408 +Epoch: [23] [ 590/2639] eta: 1:43:45 lr: 2.287371936833828e-05 loss: 0.0357 (0.0444) time: 3.0394 data: 0.0078 max mem: 33408 +Epoch: [23] [ 600/2639] eta: 1:43:15 lr: 2.2869069345762105e-05 loss: 0.0418 (0.0444) time: 3.0342 data: 0.0078 max mem: 33408 +Epoch: [23] [ 610/2639] eta: 1:42:45 lr: 2.2864419218127968e-05 loss: 0.0395 (0.0444) time: 3.0567 data: 0.0081 max mem: 33408 +Epoch: [23] [ 620/2639] eta: 1:42:16 lr: 2.285976898540977e-05 loss: 0.0417 (0.0443) time: 3.0711 data: 0.0084 max mem: 33408 +Epoch: [23] [ 630/2639] eta: 1:41:46 lr: 2.2855118647581367e-05 loss: 0.0434 (0.0443) time: 3.0614 data: 0.0083 max mem: 33408 +Epoch: [23] [ 640/2639] eta: 1:41:17 lr: 2.285046820461663e-05 loss: 0.0449 (0.0444) time: 3.0596 data: 0.0078 max mem: 33408 +Epoch: [23] [ 650/2639] eta: 1:40:44 lr: 2.2845817656489403e-05 loss: 0.0449 (0.0445) time: 3.0240 data: 0.0077 max mem: 33408 +Epoch: [23] [ 660/2639] eta: 1:40:13 lr: 2.284116700317353e-05 loss: 0.0374 (0.0444) time: 2.9861 data: 0.0077 max mem: 33408 +Epoch: [23] [ 670/2639] eta: 1:39:42 lr: 2.2836516244642818e-05 loss: 0.0413 (0.0444) time: 3.0182 data: 0.0076 max mem: 33408 +Epoch: [23] [ 680/2639] eta: 1:39:12 lr: 2.283186538087109e-05 loss: 0.0450 (0.0444) time: 3.0381 data: 0.0077 max mem: 33408 +Epoch: [23] [ 690/2639] eta: 1:38:39 lr: 2.282721441183213e-05 loss: 0.0386 (0.0445) time: 2.9894 data: 0.0073 max mem: 33408 +Epoch: [23] [ 700/2639] eta: 1:38:05 lr: 2.2822563337499745e-05 loss: 0.0407 (0.0445) time: 2.9242 data: 0.0078 max mem: 33408 +Epoch: [23] [ 710/2639] eta: 1:37:34 lr: 2.2817912157847683e-05 loss: 0.0372 (0.0445) time: 2.9596 data: 0.0087 max mem: 33408 +Epoch: [23] [ 720/2639] eta: 1:37:04 lr: 2.281326087284973e-05 loss: 0.0344 (0.0444) time: 3.0325 data: 0.0081 max mem: 33408 +Epoch: [23] [ 730/2639] eta: 1:36:33 lr: 2.2808609482479608e-05 loss: 0.0378 (0.0443) time: 3.0299 data: 0.0077 max mem: 33408 +Epoch: [23] [ 740/2639] eta: 1:36:01 lr: 2.2803957986711075e-05 loss: 0.0400 (0.0443) time: 3.0032 data: 0.0080 max mem: 33408 +Epoch: [23] [ 750/2639] eta: 1:35:29 lr: 2.2799306385517834e-05 loss: 0.0416 (0.0444) time: 2.9740 data: 0.0078 max mem: 33408 +Epoch: [23] [ 760/2639] eta: 1:34:59 lr: 2.2794654678873615e-05 loss: 0.0442 (0.0446) time: 2.9895 data: 0.0077 max mem: 33408 +Epoch: [23] [ 770/2639] eta: 1:34:27 lr: 2.27900028667521e-05 loss: 0.0469 (0.0446) time: 3.0072 data: 0.0078 max mem: 33408 +Epoch: [23] [ 780/2639] eta: 1:33:56 lr: 2.278535094912698e-05 loss: 0.0425 (0.0446) time: 2.9841 data: 0.0082 max mem: 33408 +Epoch: [23] [ 790/2639] eta: 1:33:25 lr: 2.2780698925971937e-05 loss: 0.0414 (0.0447) time: 3.0102 data: 0.0081 max mem: 33408 +Epoch: [23] [ 800/2639] eta: 1:32:54 lr: 2.2776046797260613e-05 loss: 0.0511 (0.0448) time: 3.0198 data: 0.0075 max mem: 33408 +Epoch: [23] [ 810/2639] eta: 1:32:24 lr: 2.2771394562966676e-05 loss: 0.0489 (0.0448) time: 3.0086 data: 0.0074 max mem: 33408 +Epoch: [23] [ 820/2639] eta: 1:31:52 lr: 2.2766742223063743e-05 loss: 0.0398 (0.0448) time: 2.9902 data: 0.0077 max mem: 33408 +Epoch: [23] [ 830/2639] eta: 1:31:20 lr: 2.2762089777525447e-05 loss: 0.0372 (0.0447) time: 2.9509 data: 0.0080 max mem: 33408 +Epoch: [23] [ 840/2639] eta: 1:30:48 lr: 2.2757437226325395e-05 loss: 0.0351 (0.0447) time: 2.9476 data: 0.0078 max mem: 33408 +Epoch: [23] [ 850/2639] eta: 1:30:18 lr: 2.2752784569437187e-05 loss: 0.0372 (0.0447) time: 2.9970 data: 0.0074 max mem: 33408 +Epoch: [23] [ 860/2639] eta: 1:29:49 lr: 2.2748131806834405e-05 loss: 0.0466 (0.0447) time: 3.0610 data: 0.0083 max mem: 33408 +Epoch: [23] [ 870/2639] eta: 1:29:17 lr: 2.2743478938490625e-05 loss: 0.0468 (0.0447) time: 3.0165 data: 0.0088 max mem: 33408 +Epoch: [23] [ 880/2639] eta: 1:28:46 lr: 2.27388259643794e-05 loss: 0.0423 (0.0447) time: 2.9882 data: 0.0082 max mem: 33408 +Epoch: [23] [ 890/2639] eta: 1:28:15 lr: 2.2734172884474284e-05 loss: 0.0399 (0.0447) time: 3.0087 data: 0.0076 max mem: 33408 +Epoch: [23] [ 900/2639] eta: 1:27:43 lr: 2.2729519698748803e-05 loss: 0.0351 (0.0446) time: 2.9563 data: 0.0073 max mem: 33408 +Epoch: [23] [ 910/2639] eta: 1:27:12 lr: 2.272486640717649e-05 loss: 0.0400 (0.0447) time: 2.9627 data: 0.0075 max mem: 33408 +Epoch: [23] [ 920/2639] eta: 1:26:42 lr: 2.2720213009730842e-05 loss: 0.0466 (0.0447) time: 3.0154 data: 0.0075 max mem: 33408 +Epoch: [23] [ 930/2639] eta: 1:26:11 lr: 2.271555950638537e-05 loss: 0.0356 (0.0446) time: 3.0210 data: 0.0077 max mem: 33408 +Epoch: [23] [ 940/2639] eta: 1:25:40 lr: 2.271090589711354e-05 loss: 0.0382 (0.0447) time: 2.9964 data: 0.0081 max mem: 33408 +Epoch: [23] [ 950/2639] eta: 1:25:10 lr: 2.270625218188884e-05 loss: 0.0457 (0.0446) time: 2.9962 data: 0.0086 max mem: 33408 +Epoch: [23] [ 960/2639] eta: 1:24:39 lr: 2.2701598360684716e-05 loss: 0.0347 (0.0445) time: 3.0061 data: 0.0088 max mem: 33408 +Epoch: [23] [ 970/2639] eta: 1:24:11 lr: 2.2696944433474623e-05 loss: 0.0315 (0.0445) time: 3.0592 data: 0.0083 max mem: 33408 +Epoch: [23] [ 980/2639] eta: 1:23:40 lr: 2.2692290400231984e-05 loss: 0.0346 (0.0445) time: 3.0574 data: 0.0081 max mem: 33408 +Epoch: [23] [ 990/2639] eta: 1:23:09 lr: 2.268763626093023e-05 loss: 0.0365 (0.0445) time: 3.0015 data: 0.0079 max mem: 33408 +Epoch: [23] [1000/2639] eta: 1:22:39 lr: 2.2682982015542757e-05 loss: 0.0380 (0.0445) time: 3.0284 data: 0.0077 max mem: 33408 +Epoch: [23] [1010/2639] eta: 1:22:09 lr: 2.267832766404297e-05 loss: 0.0402 (0.0445) time: 3.0222 data: 0.0082 max mem: 33408 +Epoch: [23] [1020/2639] eta: 1:21:37 lr: 2.267367320640425e-05 loss: 0.0377 (0.0446) time: 2.9828 data: 0.0083 max mem: 33408 +Epoch: [23] [1030/2639] eta: 1:21:07 lr: 2.2669018642599955e-05 loss: 0.0452 (0.0447) time: 3.0061 data: 0.0081 max mem: 33408 +Epoch: [23] [1040/2639] eta: 1:20:38 lr: 2.266436397260346e-05 loss: 0.0434 (0.0447) time: 3.0494 data: 0.0080 max mem: 33408 +Epoch: [23] [1050/2639] eta: 1:20:08 lr: 2.265970919638809e-05 loss: 0.0394 (0.0447) time: 3.0504 data: 0.0075 max mem: 33408 +Epoch: [23] [1060/2639] eta: 1:19:38 lr: 2.2655054313927192e-05 loss: 0.0366 (0.0447) time: 3.0413 data: 0.0072 max mem: 33408 +Epoch: [23] [1070/2639] eta: 1:19:07 lr: 2.2650399325194075e-05 loss: 0.0363 (0.0446) time: 3.0346 data: 0.0072 max mem: 33408 +Epoch: [23] [1080/2639] eta: 1:18:37 lr: 2.2645744230162046e-05 loss: 0.0362 (0.0447) time: 3.0330 data: 0.0075 max mem: 33408 +Epoch: [23] [1090/2639] eta: 1:18:06 lr: 2.2641089028804398e-05 loss: 0.0354 (0.0446) time: 3.0030 data: 0.0077 max mem: 33408 +Epoch: [23] [1100/2639] eta: 1:17:35 lr: 2.2636433721094418e-05 loss: 0.0351 (0.0445) time: 2.9571 data: 0.0076 max mem: 33408 +Epoch: [23] [1110/2639] eta: 1:17:04 lr: 2.2631778307005356e-05 loss: 0.0351 (0.0445) time: 2.9575 data: 0.0075 max mem: 33408 +Epoch: [23] [1120/2639] eta: 1:16:34 lr: 2.2627122786510484e-05 loss: 0.0324 (0.0445) time: 3.0058 data: 0.0074 max mem: 33408 +Epoch: [23] [1130/2639] eta: 1:16:04 lr: 2.262246715958303e-05 loss: 0.0389 (0.0445) time: 3.0424 data: 0.0075 max mem: 33408 +Epoch: [23] [1140/2639] eta: 1:15:34 lr: 2.261781142619623e-05 loss: 0.0413 (0.0446) time: 3.0579 data: 0.0079 max mem: 33408 +Epoch: [23] [1150/2639] eta: 1:15:05 lr: 2.2613155586323297e-05 loss: 0.0413 (0.0445) time: 3.0819 data: 0.0079 max mem: 33408 +Epoch: [23] [1160/2639] eta: 1:14:34 lr: 2.260849963993744e-05 loss: 0.0409 (0.0445) time: 3.0530 data: 0.0077 max mem: 33408 +Epoch: [23] [1170/2639] eta: 1:14:04 lr: 2.2603843587011833e-05 loss: 0.0371 (0.0444) time: 3.0336 data: 0.0078 max mem: 33408 +Epoch: [23] [1180/2639] eta: 1:13:35 lr: 2.2599187427519673e-05 loss: 0.0353 (0.0444) time: 3.0627 data: 0.0076 max mem: 33408 +Epoch: [23] [1190/2639] eta: 1:13:04 lr: 2.259453116143411e-05 loss: 0.0420 (0.0444) time: 3.0373 data: 0.0080 max mem: 33408 +Epoch: [23] [1200/2639] eta: 1:12:34 lr: 2.2589874788728303e-05 loss: 0.0454 (0.0445) time: 3.0044 data: 0.0080 max mem: 33408 +Epoch: [23] [1210/2639] eta: 1:12:04 lr: 2.2585218309375383e-05 loss: 0.0399 (0.0444) time: 3.0211 data: 0.0073 max mem: 33408 +Epoch: [23] [1220/2639] eta: 1:11:33 lr: 2.2580561723348483e-05 loss: 0.0452 (0.0445) time: 3.0081 data: 0.0080 max mem: 33408 +Epoch: [23] [1230/2639] eta: 1:11:02 lr: 2.2575905030620707e-05 loss: 0.0452 (0.0445) time: 2.9912 data: 0.0079 max mem: 33408 +Epoch: [23] [1240/2639] eta: 1:10:32 lr: 2.2571248231165164e-05 loss: 0.0417 (0.0446) time: 2.9967 data: 0.0075 max mem: 33408 +Epoch: [23] [1250/2639] eta: 1:10:01 lr: 2.2566591324954934e-05 loss: 0.0482 (0.0446) time: 3.0039 data: 0.0074 max mem: 33408 +Epoch: [23] [1260/2639] eta: 1:09:30 lr: 2.256193431196309e-05 loss: 0.0403 (0.0446) time: 2.9807 data: 0.0077 max mem: 33408 +Epoch: [23] [1270/2639] eta: 1:09:00 lr: 2.25572771921627e-05 loss: 0.0420 (0.0447) time: 2.9845 data: 0.0080 max mem: 33408 +Epoch: [23] [1280/2639] eta: 1:08:29 lr: 2.2552619965526802e-05 loss: 0.0465 (0.0447) time: 3.0064 data: 0.0078 max mem: 33408 +Epoch: [23] [1290/2639] eta: 1:07:59 lr: 2.254796263202844e-05 loss: 0.0431 (0.0447) time: 2.9890 data: 0.0075 max mem: 33408 +Epoch: [23] [1300/2639] eta: 1:07:28 lr: 2.2543305191640627e-05 loss: 0.0407 (0.0446) time: 2.9634 data: 0.0071 max mem: 33408 +Epoch: [23] [1310/2639] eta: 1:06:57 lr: 2.253864764433638e-05 loss: 0.0407 (0.0447) time: 2.9597 data: 0.0071 max mem: 33408 +Epoch: [23] [1320/2639] eta: 1:06:27 lr: 2.2533989990088685e-05 loss: 0.0355 (0.0446) time: 2.9975 data: 0.0074 max mem: 33408 +Epoch: [23] [1330/2639] eta: 1:05:57 lr: 2.2529332228870534e-05 loss: 0.0434 (0.0446) time: 3.0333 data: 0.0077 max mem: 33408 +Epoch: [23] [1340/2639] eta: 1:05:27 lr: 2.252467436065489e-05 loss: 0.0439 (0.0447) time: 3.0712 data: 0.0076 max mem: 33408 +Epoch: [23] [1350/2639] eta: 1:04:57 lr: 2.2520016385414717e-05 loss: 0.0397 (0.0447) time: 3.0433 data: 0.0073 max mem: 33408 +Epoch: [23] [1360/2639] eta: 1:04:26 lr: 2.2515358303122944e-05 loss: 0.0412 (0.0447) time: 3.0020 data: 0.0076 max mem: 33408 +Epoch: [23] [1370/2639] eta: 1:03:57 lr: 2.251070011375252e-05 loss: 0.0440 (0.0447) time: 3.0500 data: 0.0078 max mem: 33408 +Epoch: [23] [1380/2639] eta: 1:03:26 lr: 2.2506041817276348e-05 loss: 0.0449 (0.0447) time: 3.0605 data: 0.0076 max mem: 33408 +Epoch: [23] [1390/2639] eta: 1:02:56 lr: 2.2501383413667342e-05 loss: 0.0368 (0.0447) time: 2.9973 data: 0.0077 max mem: 33408 +Epoch: [23] [1400/2639] eta: 1:02:25 lr: 2.2496724902898382e-05 loss: 0.0306 (0.0447) time: 2.9802 data: 0.0077 max mem: 33408 +Epoch: [23] [1410/2639] eta: 1:01:55 lr: 2.2492066284942356e-05 loss: 0.0405 (0.0447) time: 3.0128 data: 0.0078 max mem: 33408 +Epoch: [23] [1420/2639] eta: 1:01:24 lr: 2.2487407559772125e-05 loss: 0.0497 (0.0447) time: 2.9973 data: 0.0077 max mem: 33408 +Epoch: [23] [1430/2639] eta: 1:00:54 lr: 2.2482748727360543e-05 loss: 0.0411 (0.0447) time: 2.9841 data: 0.0077 max mem: 33408 +Epoch: [23] [1440/2639] eta: 1:00:23 lr: 2.2478089787680445e-05 loss: 0.0404 (0.0448) time: 2.9934 data: 0.0079 max mem: 33408 +Epoch: [23] [1450/2639] eta: 0:59:53 lr: 2.2473430740704664e-05 loss: 0.0415 (0.0448) time: 2.9939 data: 0.0078 max mem: 33408 +Epoch: [23] [1460/2639] eta: 0:59:22 lr: 2.2468771586406e-05 loss: 0.0368 (0.0448) time: 2.9962 data: 0.0074 max mem: 33408 +Epoch: [23] [1470/2639] eta: 0:58:52 lr: 2.2464112324757267e-05 loss: 0.0374 (0.0448) time: 2.9848 data: 0.0071 max mem: 33408 +Epoch: [23] [1480/2639] eta: 0:58:22 lr: 2.2459452955731238e-05 loss: 0.0379 (0.0448) time: 3.0199 data: 0.0074 max mem: 33408 +Epoch: [23] [1490/2639] eta: 0:57:52 lr: 2.2454793479300696e-05 loss: 0.0392 (0.0448) time: 3.0396 data: 0.0074 max mem: 33408 +Epoch: [23] [1500/2639] eta: 0:57:22 lr: 2.245013389543839e-05 loss: 0.0392 (0.0448) time: 3.0334 data: 0.0074 max mem: 33408 +Epoch: [23] [1510/2639] eta: 0:56:51 lr: 2.2445474204117074e-05 loss: 0.0400 (0.0448) time: 3.0048 data: 0.0073 max mem: 33408 +Epoch: [23] [1520/2639] eta: 0:56:21 lr: 2.244081440530949e-05 loss: 0.0416 (0.0449) time: 2.9781 data: 0.0073 max mem: 33408 +Epoch: [23] [1530/2639] eta: 0:55:51 lr: 2.2436154498988337e-05 loss: 0.0476 (0.0449) time: 3.0132 data: 0.0077 max mem: 33408 +Epoch: [23] [1540/2639] eta: 0:55:21 lr: 2.243149448512634e-05 loss: 0.0372 (0.0449) time: 3.0476 data: 0.0075 max mem: 33408 +Epoch: [23] [1550/2639] eta: 0:54:50 lr: 2.2426834363696184e-05 loss: 0.0373 (0.0449) time: 3.0181 data: 0.0073 max mem: 33408 +Epoch: [23] [1560/2639] eta: 0:54:20 lr: 2.2422174134670557e-05 loss: 0.0373 (0.0449) time: 3.0138 data: 0.0076 max mem: 33408 +Epoch: [23] [1570/2639] eta: 0:53:50 lr: 2.2417513798022112e-05 loss: 0.0392 (0.0449) time: 3.0397 data: 0.0077 max mem: 33408 +Epoch: [23] [1580/2639] eta: 0:53:20 lr: 2.241285335372352e-05 loss: 0.0439 (0.0449) time: 3.0448 data: 0.0080 max mem: 33408 +Epoch: [23] [1590/2639] eta: 0:52:50 lr: 2.2408192801747406e-05 loss: 0.0419 (0.0449) time: 3.0288 data: 0.0082 max mem: 33408 +Epoch: [23] [1600/2639] eta: 0:52:19 lr: 2.240353214206641e-05 loss: 0.0416 (0.0449) time: 3.0025 data: 0.0079 max mem: 33408 +Epoch: [23] [1610/2639] eta: 0:51:49 lr: 2.239887137465314e-05 loss: 0.0418 (0.0450) time: 3.0379 data: 0.0081 max mem: 33408 +Epoch: [23] [1620/2639] eta: 0:51:19 lr: 2.2394210499480198e-05 loss: 0.0386 (0.0449) time: 3.0194 data: 0.0082 max mem: 33408 +Epoch: [23] [1630/2639] eta: 0:50:48 lr: 2.238954951652017e-05 loss: 0.0376 (0.0450) time: 2.9794 data: 0.0080 max mem: 33408 +Epoch: [23] [1640/2639] eta: 0:50:18 lr: 2.2384888425745634e-05 loss: 0.0391 (0.0450) time: 3.0285 data: 0.0081 max mem: 33408 +Epoch: [23] [1650/2639] eta: 0:49:48 lr: 2.2380227227129144e-05 loss: 0.0389 (0.0450) time: 3.0541 data: 0.0077 max mem: 33408 +Epoch: [23] [1660/2639] eta: 0:49:18 lr: 2.237556592064326e-05 loss: 0.0392 (0.0450) time: 3.0045 data: 0.0075 max mem: 33408 +Epoch: [23] [1670/2639] eta: 0:48:48 lr: 2.23709045062605e-05 loss: 0.0396 (0.0450) time: 3.0108 data: 0.0079 max mem: 33408 +Epoch: [23] [1680/2639] eta: 0:48:18 lr: 2.23662429839534e-05 loss: 0.0436 (0.0451) time: 3.0625 data: 0.0077 max mem: 33408 +Epoch: [23] [1690/2639] eta: 0:47:48 lr: 2.2361581353694454e-05 loss: 0.0428 (0.0450) time: 3.0512 data: 0.0074 max mem: 33408 +Epoch: [23] [1700/2639] eta: 0:47:17 lr: 2.235691961545617e-05 loss: 0.0373 (0.0450) time: 2.9940 data: 0.0076 max mem: 33408 +Epoch: [23] [1710/2639] eta: 0:46:47 lr: 2.2352257769211014e-05 loss: 0.0345 (0.0449) time: 2.9932 data: 0.0077 max mem: 33408 +Epoch: [23] [1720/2639] eta: 0:46:17 lr: 2.2347595814931468e-05 loss: 0.0431 (0.0450) time: 3.0250 data: 0.0080 max mem: 33408 +Epoch: [23] [1730/2639] eta: 0:45:46 lr: 2.2342933752589972e-05 loss: 0.0392 (0.0449) time: 3.0200 data: 0.0080 max mem: 33408 +Epoch: [23] [1740/2639] eta: 0:45:16 lr: 2.2338271582158982e-05 loss: 0.0390 (0.0451) time: 3.0407 data: 0.0073 max mem: 33408 +Epoch: [23] [1750/2639] eta: 0:44:46 lr: 2.2333609303610907e-05 loss: 0.0393 (0.0451) time: 3.0221 data: 0.0073 max mem: 33408 +Epoch: [23] [1760/2639] eta: 0:44:15 lr: 2.232894691691817e-05 loss: 0.0369 (0.0450) time: 2.9678 data: 0.0076 max mem: 33408 +Epoch: [23] [1770/2639] eta: 0:43:45 lr: 2.232428442205318e-05 loss: 0.0370 (0.0450) time: 2.9988 data: 0.0074 max mem: 33408 +Epoch: [23] [1780/2639] eta: 0:43:15 lr: 2.231962181898831e-05 loss: 0.0379 (0.0451) time: 3.0148 data: 0.0071 max mem: 33408 +Epoch: [23] [1790/2639] eta: 0:42:44 lr: 2.231495910769594e-05 loss: 0.0393 (0.0451) time: 2.9707 data: 0.0072 max mem: 33408 +Epoch: [23] [1800/2639] eta: 0:42:14 lr: 2.2310296288148426e-05 loss: 0.0391 (0.0451) time: 2.9365 data: 0.0073 max mem: 33408 +Epoch: [23] [1810/2639] eta: 0:41:44 lr: 2.230563336031812e-05 loss: 0.0375 (0.0451) time: 2.9845 data: 0.0074 max mem: 33408 +Epoch: [23] [1820/2639] eta: 0:41:14 lr: 2.2300970324177347e-05 loss: 0.0427 (0.0451) time: 3.0545 data: 0.0074 max mem: 33408 +Epoch: [23] [1830/2639] eta: 0:40:43 lr: 2.2296307179698437e-05 loss: 0.0508 (0.0451) time: 3.0403 data: 0.0073 max mem: 33408 +Epoch: [23] [1840/2639] eta: 0:40:13 lr: 2.2291643926853683e-05 loss: 0.0440 (0.0451) time: 3.0393 data: 0.0075 max mem: 33408 +Epoch: [23] [1850/2639] eta: 0:39:43 lr: 2.228698056561539e-05 loss: 0.0427 (0.0452) time: 3.0179 data: 0.0074 max mem: 33408 +Epoch: [23] [1860/2639] eta: 0:39:13 lr: 2.2282317095955828e-05 loss: 0.0427 (0.0453) time: 2.9850 data: 0.0074 max mem: 33408 +Epoch: [23] [1870/2639] eta: 0:38:43 lr: 2.2277653517847267e-05 loss: 0.0410 (0.0453) time: 3.0257 data: 0.0074 max mem: 33408 +Epoch: [23] [1880/2639] eta: 0:38:12 lr: 2.2272989831261954e-05 loss: 0.0425 (0.0453) time: 3.0285 data: 0.0076 max mem: 33408 +Epoch: [23] [1890/2639] eta: 0:37:42 lr: 2.2268326036172135e-05 loss: 0.0440 (0.0453) time: 3.0027 data: 0.0076 max mem: 33408 +Epoch: [23] [1900/2639] eta: 0:37:12 lr: 2.2263662132550022e-05 loss: 0.0417 (0.0452) time: 3.0430 data: 0.0074 max mem: 33408 +Epoch: [23] [1910/2639] eta: 0:36:42 lr: 2.2258998120367843e-05 loss: 0.0417 (0.0452) time: 3.0427 data: 0.0072 max mem: 33408 +Epoch: [23] [1920/2639] eta: 0:36:11 lr: 2.225433399959778e-05 loss: 0.0430 (0.0452) time: 3.0090 data: 0.0072 max mem: 33408 +Epoch: [23] [1930/2639] eta: 0:35:41 lr: 2.224966977021203e-05 loss: 0.0420 (0.0452) time: 3.0011 data: 0.0074 max mem: 33408 +Epoch: [23] [1940/2639] eta: 0:35:11 lr: 2.2245005432182747e-05 loss: 0.0420 (0.0453) time: 3.0366 data: 0.0075 max mem: 33408 +Epoch: [23] [1950/2639] eta: 0:34:41 lr: 2.2240340985482106e-05 loss: 0.0378 (0.0452) time: 3.0682 data: 0.0075 max mem: 33408 +Epoch: [23] [1960/2639] eta: 0:34:11 lr: 2.2235676430082235e-05 loss: 0.0415 (0.0453) time: 3.0394 data: 0.0073 max mem: 33408 +Epoch: [23] [1970/2639] eta: 0:33:41 lr: 2.2231011765955273e-05 loss: 0.0470 (0.0453) time: 3.0193 data: 0.0070 max mem: 33408 +Epoch: [23] [1980/2639] eta: 0:33:10 lr: 2.222634699307333e-05 loss: 0.0453 (0.0454) time: 3.0024 data: 0.0073 max mem: 33408 +Epoch: [23] [1990/2639] eta: 0:32:40 lr: 2.2221682111408514e-05 loss: 0.0453 (0.0454) time: 2.9801 data: 0.0072 max mem: 33408 +Epoch: [23] [2000/2639] eta: 0:32:10 lr: 2.2217017120932904e-05 loss: 0.0456 (0.0454) time: 3.0281 data: 0.0070 max mem: 33408 +Epoch: [23] [2010/2639] eta: 0:31:40 lr: 2.221235202161858e-05 loss: 0.0435 (0.0454) time: 3.0557 data: 0.0073 max mem: 33408 +Epoch: [23] [2020/2639] eta: 0:31:10 lr: 2.220768681343761e-05 loss: 0.0435 (0.0454) time: 3.0270 data: 0.0076 max mem: 33408 +Epoch: [23] [2030/2639] eta: 0:30:40 lr: 2.220302149636203e-05 loss: 0.0402 (0.0454) time: 3.0632 data: 0.0073 max mem: 33408 +Epoch: [23] [2040/2639] eta: 0:30:09 lr: 2.2198356070363885e-05 loss: 0.0393 (0.0454) time: 3.0435 data: 0.0071 max mem: 33408 +Epoch: [23] [2050/2639] eta: 0:29:39 lr: 2.219369053541518e-05 loss: 0.0399 (0.0455) time: 3.0163 data: 0.0076 max mem: 33408 +Epoch: [23] [2060/2639] eta: 0:29:09 lr: 2.2189024891487936e-05 loss: 0.0380 (0.0454) time: 3.0248 data: 0.0075 max mem: 33408 +Epoch: [23] [2070/2639] eta: 0:28:39 lr: 2.2184359138554134e-05 loss: 0.0382 (0.0454) time: 3.0170 data: 0.0074 max mem: 33408 +Epoch: [23] [2080/2639] eta: 0:28:08 lr: 2.2179693276585762e-05 loss: 0.0458 (0.0454) time: 3.0230 data: 0.0075 max mem: 33408 +Epoch: [23] [2090/2639] eta: 0:27:38 lr: 2.217502730555478e-05 loss: 0.0450 (0.0454) time: 2.9865 data: 0.0076 max mem: 33408 +Epoch: [23] [2100/2639] eta: 0:27:08 lr: 2.2170361225433144e-05 loss: 0.0450 (0.0455) time: 2.9674 data: 0.0077 max mem: 33408 +Epoch: [23] [2110/2639] eta: 0:26:37 lr: 2.2165695036192776e-05 loss: 0.0469 (0.0456) time: 2.9776 data: 0.0077 max mem: 33408 +Epoch: [23] [2120/2639] eta: 0:26:07 lr: 2.2161028737805623e-05 loss: 0.0447 (0.0455) time: 3.0042 data: 0.0079 max mem: 33408 +Epoch: [23] [2130/2639] eta: 0:25:37 lr: 2.2156362330243577e-05 loss: 0.0447 (0.0456) time: 3.0428 data: 0.0078 max mem: 33408 +Epoch: [23] [2140/2639] eta: 0:25:07 lr: 2.2151695813478543e-05 loss: 0.0444 (0.0456) time: 3.0235 data: 0.0081 max mem: 33408 +Epoch: [23] [2150/2639] eta: 0:24:37 lr: 2.2147029187482397e-05 loss: 0.0439 (0.0456) time: 3.0007 data: 0.0083 max mem: 33408 +Epoch: [23] [2160/2639] eta: 0:24:07 lr: 2.2142362452227014e-05 loss: 0.0350 (0.0455) time: 3.0574 data: 0.0077 max mem: 33408 +Epoch: [23] [2170/2639] eta: 0:23:36 lr: 2.213769560768424e-05 loss: 0.0356 (0.0455) time: 3.0587 data: 0.0078 max mem: 33408 +Epoch: [23] [2180/2639] eta: 0:23:06 lr: 2.213302865382593e-05 loss: 0.0381 (0.0455) time: 3.0405 data: 0.0078 max mem: 33408 +Epoch: [23] [2190/2639] eta: 0:22:36 lr: 2.2128361590623894e-05 loss: 0.0375 (0.0455) time: 3.0736 data: 0.0072 max mem: 33408 +Epoch: [23] [2200/2639] eta: 0:22:06 lr: 2.212369441804996e-05 loss: 0.0385 (0.0455) time: 3.0423 data: 0.0071 max mem: 33408 +Epoch: [23] [2210/2639] eta: 0:21:36 lr: 2.211902713607591e-05 loss: 0.0475 (0.0455) time: 2.9986 data: 0.0075 max mem: 33408 +Epoch: [23] [2220/2639] eta: 0:21:05 lr: 2.211435974467355e-05 loss: 0.0390 (0.0455) time: 3.0115 data: 0.0078 max mem: 33408 +Epoch: [23] [2230/2639] eta: 0:20:35 lr: 2.210969224381463e-05 loss: 0.0387 (0.0455) time: 3.0555 data: 0.0075 max mem: 33408 +Epoch: [23] [2240/2639] eta: 0:20:05 lr: 2.2105024633470928e-05 loss: 0.0424 (0.0455) time: 3.0622 data: 0.0074 max mem: 33408 +Epoch: [23] [2250/2639] eta: 0:19:35 lr: 2.2100356913614174e-05 loss: 0.0500 (0.0456) time: 3.0336 data: 0.0073 max mem: 33408 +Epoch: [23] [2260/2639] eta: 0:19:05 lr: 2.2095689084216094e-05 loss: 0.0448 (0.0455) time: 3.0089 data: 0.0072 max mem: 33408 +Epoch: [23] [2270/2639] eta: 0:18:35 lr: 2.2091021145248424e-05 loss: 0.0429 (0.0455) time: 3.0233 data: 0.0075 max mem: 33408 +Epoch: [23] [2280/2639] eta: 0:18:04 lr: 2.2086353096682845e-05 loss: 0.0408 (0.0455) time: 3.0346 data: 0.0076 max mem: 33408 +Epoch: [23] [2290/2639] eta: 0:17:34 lr: 2.2081684938491054e-05 loss: 0.0404 (0.0455) time: 3.0649 data: 0.0073 max mem: 33408 +Epoch: [23] [2300/2639] eta: 0:17:04 lr: 2.2077016670644722e-05 loss: 0.0417 (0.0455) time: 3.0856 data: 0.0074 max mem: 33408 +Epoch: [23] [2310/2639] eta: 0:16:34 lr: 2.2072348293115514e-05 loss: 0.0350 (0.0455) time: 3.0238 data: 0.0072 max mem: 33408 +Epoch: [23] [2320/2639] eta: 0:16:04 lr: 2.2067679805875065e-05 loss: 0.0415 (0.0455) time: 3.0175 data: 0.0073 max mem: 33408 +Epoch: [23] [2330/2639] eta: 0:15:33 lr: 2.2063011208895024e-05 loss: 0.0415 (0.0455) time: 3.0257 data: 0.0075 max mem: 33408 +Epoch: [23] [2340/2639] eta: 0:15:03 lr: 2.205834250214699e-05 loss: 0.0383 (0.0455) time: 3.0144 data: 0.0076 max mem: 33408 +Epoch: [23] [2350/2639] eta: 0:14:33 lr: 2.205367368560258e-05 loss: 0.0394 (0.0456) time: 2.9945 data: 0.0075 max mem: 33408 +Epoch: [23] [2360/2639] eta: 0:14:03 lr: 2.2049004759233377e-05 loss: 0.0435 (0.0456) time: 3.0287 data: 0.0072 max mem: 33408 +Epoch: [23] [2370/2639] eta: 0:13:32 lr: 2.204433572301096e-05 loss: 0.0457 (0.0456) time: 3.0188 data: 0.0076 max mem: 33408 +Epoch: [23] [2380/2639] eta: 0:13:02 lr: 2.203966657690689e-05 loss: 0.0481 (0.0456) time: 2.9742 data: 0.0079 max mem: 33408 +Epoch: [23] [2390/2639] eta: 0:12:32 lr: 2.2034997320892716e-05 loss: 0.0397 (0.0456) time: 3.0417 data: 0.0075 max mem: 33408 +Epoch: [23] [2400/2639] eta: 0:12:02 lr: 2.2030327954939966e-05 loss: 0.0397 (0.0456) time: 3.0634 data: 0.0074 max mem: 33408 +Epoch: [23] [2410/2639] eta: 0:11:32 lr: 2.202565847902017e-05 loss: 0.0379 (0.0456) time: 3.0346 data: 0.0075 max mem: 33408 +Epoch: [23] [2420/2639] eta: 0:11:01 lr: 2.202098889310482e-05 loss: 0.0379 (0.0456) time: 3.0145 data: 0.0071 max mem: 33408 +Epoch: [23] [2430/2639] eta: 0:10:31 lr: 2.2016319197165418e-05 loss: 0.0387 (0.0456) time: 2.9938 data: 0.0075 max mem: 33408 +Epoch: [23] [2440/2639] eta: 0:10:01 lr: 2.2011649391173434e-05 loss: 0.0371 (0.0456) time: 2.9817 data: 0.0083 max mem: 33408 +Epoch: [23] [2450/2639] eta: 0:09:31 lr: 2.200697947510034e-05 loss: 0.0411 (0.0456) time: 3.0039 data: 0.0080 max mem: 33408 +Epoch: [23] [2460/2639] eta: 0:09:00 lr: 2.2002309448917574e-05 loss: 0.0386 (0.0455) time: 2.9993 data: 0.0072 max mem: 33408 +Epoch: [23] [2470/2639] eta: 0:08:30 lr: 2.1997639312596582e-05 loss: 0.0391 (0.0455) time: 2.9966 data: 0.0073 max mem: 33408 +Epoch: [23] [2480/2639] eta: 0:08:00 lr: 2.1992969066108773e-05 loss: 0.0412 (0.0456) time: 3.0298 data: 0.0073 max mem: 33408 +Epoch: [23] [2490/2639] eta: 0:07:30 lr: 2.1988298709425566e-05 loss: 0.0484 (0.0456) time: 3.0453 data: 0.0074 max mem: 33408 +Epoch: [23] [2500/2639] eta: 0:06:59 lr: 2.198362824251834e-05 loss: 0.0448 (0.0456) time: 3.0102 data: 0.0080 max mem: 33408 +Epoch: [23] [2510/2639] eta: 0:06:29 lr: 2.197895766535848e-05 loss: 0.0435 (0.0456) time: 3.0195 data: 0.0081 max mem: 33408 +Epoch: [23] [2520/2639] eta: 0:05:59 lr: 2.197428697791736e-05 loss: 0.0399 (0.0456) time: 3.0316 data: 0.0079 max mem: 33408 +Epoch: [23] [2530/2639] eta: 0:05:29 lr: 2.196961618016631e-05 loss: 0.0435 (0.0456) time: 2.9889 data: 0.0076 max mem: 33408 +Epoch: [23] [2540/2639] eta: 0:04:59 lr: 2.196494527207668e-05 loss: 0.0458 (0.0457) time: 3.0227 data: 0.0072 max mem: 33408 +Epoch: [23] [2550/2639] eta: 0:04:28 lr: 2.1960274253619783e-05 loss: 0.0458 (0.0457) time: 3.0369 data: 0.0073 max mem: 33408 +Epoch: [23] [2560/2639] eta: 0:03:58 lr: 2.195560312476694e-05 loss: 0.0448 (0.0457) time: 3.0168 data: 0.0074 max mem: 33408 +Epoch: [23] [2570/2639] eta: 0:03:28 lr: 2.195093188548942e-05 loss: 0.0402 (0.0457) time: 3.0304 data: 0.0074 max mem: 33408 +Epoch: [23] [2580/2639] eta: 0:02:58 lr: 2.194626053575852e-05 loss: 0.0363 (0.0457) time: 3.0310 data: 0.0077 max mem: 33408 +Epoch: [23] [2590/2639] eta: 0:02:28 lr: 2.1941589075545503e-05 loss: 0.0390 (0.0457) time: 3.0310 data: 0.0078 max mem: 33408 +Epoch: [23] [2600/2639] eta: 0:01:57 lr: 2.1936917504821614e-05 loss: 0.0390 (0.0456) time: 3.0206 data: 0.0077 max mem: 33408 +Epoch: [23] [2610/2639] eta: 0:01:27 lr: 2.1932245823558086e-05 loss: 0.0387 (0.0456) time: 3.0020 data: 0.0074 max mem: 33408 +Epoch: [23] [2620/2639] eta: 0:00:57 lr: 2.1927574031726153e-05 loss: 0.0413 (0.0456) time: 3.0304 data: 0.0077 max mem: 33408 +Epoch: [23] [2630/2639] eta: 0:00:27 lr: 2.1922902129297006e-05 loss: 0.0430 (0.0456) time: 2.9961 data: 0.0074 max mem: 33408 +Epoch: [23] Total time: 2:12:54 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 2:10:17 time: 3.0382 data: 2.9307 max mem: 33408 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 100/2573] eta: 0:04:26 time: 0.0777 data: 0.0015 max mem: 33408 +Test: [ 200/2573] eta: 0:03:42 time: 0.0793 data: 0.0014 max mem: 33408 +Test: [ 300/2573] eta: 0:03:21 time: 0.0808 data: 0.0014 max mem: 33408 +Test: [ 400/2573] eta: 0:03:07 time: 0.0819 data: 0.0014 max mem: 33408 +Test: [ 500/2573] eta: 0:02:56 time: 0.0804 data: 0.0014 max mem: 33408 +Test: [ 600/2573] eta: 0:02:46 time: 0.0798 data: 0.0014 max mem: 33408 +Test: [ 700/2573] eta: 0:02:37 time: 0.0800 data: 0.0015 max mem: 33408 +Test: [ 800/2573] eta: 0:02:28 time: 0.0831 data: 0.0014 max mem: 33408 +Test: [ 900/2573] eta: 0:02:19 time: 0.0808 data: 0.0015 max mem: 33408 +Test: [1000/2573] eta: 0:02:11 time: 0.0809 data: 0.0016 max mem: 33408 +Test: [1100/2573] eta: 0:02:02 time: 0.0815 data: 0.0016 max mem: 33408 +Test: [1200/2573] eta: 0:01:54 time: 0.0806 data: 0.0014 max mem: 33408 +Test: [1300/2573] eta: 0:01:45 time: 0.0809 data: 0.0015 max mem: 33408 +Test: [1400/2573] eta: 0:01:37 time: 0.0789 data: 0.0015 max mem: 33408 +Test: [1500/2573] eta: 0:01:28 time: 0.0813 data: 0.0016 max mem: 33408 +Test: [1600/2573] eta: 0:01:20 time: 0.0847 data: 0.0015 max mem: 33408 +Test: [1700/2573] eta: 0:01:12 time: 0.0791 data: 0.0013 max mem: 33408 +Test: [1800/2573] eta: 0:01:03 time: 0.0833 data: 0.0014 max mem: 33408 +Test: [1900/2573] eta: 0:00:55 time: 0.0803 data: 0.0015 max mem: 33408 +Test: [2000/2573] eta: 0:00:47 time: 0.0806 data: 0.0014 max mem: 33408 +Test: [2100/2573] eta: 0:00:38 time: 0.0827 data: 0.0014 max mem: 33408 +Test: [2200/2573] eta: 0:00:30 time: 0.0830 data: 0.0014 max mem: 33408 +Test: [2300/2573] eta: 0:00:22 time: 0.0823 data: 0.0015 max mem: 33408 +Test: [2400/2573] eta: 0:00:14 time: 0.0790 data: 0.0014 max mem: 33408 +Test: [2500/2573] eta: 0:00:05 time: 0.0810 data: 0.0015 max mem: 33408 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: Total time: 0:03:32 +Final results: +Mean IoU is 63.55 + + precision@0.5 = 71.75 + precision@0.6 = 66.44 + precision@0.7 = 59.23 + precision@0.8 = 47.83 + precision@0.9 = 23.69 + overall IoU = 61.21 + +Average object IoU 63.54587069715366 +Overall IoU 61.21061325073242 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [24] [ 0/2639] eta: 4:00:23 lr: 2.1918697322526357e-05 loss: 0.0632 (0.0632) time: 5.4656 data: 2.2503 max mem: 33408 +Epoch: [24] [ 10/2639] eta: 2:23:41 lr: 2.191402520988315e-05 loss: 0.0390 (0.0448) time: 3.2794 data: 0.2108 max mem: 33408 +Epoch: [24] [ 20/2639] eta: 2:17:36 lr: 2.190935298655915e-05 loss: 0.0360 (0.0415) time: 3.0371 data: 0.0072 max mem: 33408 +Epoch: [24] [ 30/2639] eta: 2:15:40 lr: 2.190468065252552e-05 loss: 0.0360 (0.0405) time: 3.0324 data: 0.0076 max mem: 33408 +Epoch: [24] [ 40/2639] eta: 2:13:50 lr: 2.190000820775339e-05 loss: 0.0401 (0.0423) time: 3.0240 data: 0.0078 max mem: 33408 +Epoch: [24] [ 50/2639] eta: 2:12:53 lr: 2.1895335652213885e-05 loss: 0.0367 (0.0416) time: 3.0173 data: 0.0079 max mem: 33408 +Epoch: [24] [ 60/2639] eta: 2:11:58 lr: 2.189066298587811e-05 loss: 0.0365 (0.0429) time: 3.0299 data: 0.0078 max mem: 33408 +Epoch: [24] [ 70/2639] eta: 2:10:55 lr: 2.1885990208717168e-05 loss: 0.0389 (0.0427) time: 3.0014 data: 0.0082 max mem: 33408 +Epoch: [24] [ 80/2639] eta: 2:10:04 lr: 2.1881317320702124e-05 loss: 0.0392 (0.0430) time: 2.9883 data: 0.0083 max mem: 33408 +Epoch: [24] [ 90/2639] eta: 2:09:36 lr: 2.1876644321804056e-05 loss: 0.0380 (0.0427) time: 3.0265 data: 0.0082 max mem: 33408 +Epoch: [24] [ 100/2639] eta: 2:09:01 lr: 2.1871971211994004e-05 loss: 0.0382 (0.0425) time: 3.0460 data: 0.0082 max mem: 33408 +Epoch: [24] [ 110/2639] eta: 2:08:09 lr: 2.186729799124302e-05 loss: 0.0385 (0.0424) time: 2.9927 data: 0.0078 max mem: 33408 +Epoch: [24] [ 120/2639] eta: 2:07:27 lr: 2.18626246595221e-05 loss: 0.0373 (0.0429) time: 2.9691 data: 0.0077 max mem: 33408 +Epoch: [24] [ 130/2639] eta: 2:06:44 lr: 2.1857951216802276e-05 loss: 0.0371 (0.0424) time: 2.9776 data: 0.0080 max mem: 33408 +Epoch: [24] [ 140/2639] eta: 2:06:02 lr: 2.185327766305453e-05 loss: 0.0371 (0.0424) time: 2.9662 data: 0.0080 max mem: 33408 +Epoch: [24] [ 150/2639] eta: 2:05:24 lr: 2.184860399824984e-05 loss: 0.0394 (0.0423) time: 2.9742 data: 0.0080 max mem: 33408 +Epoch: [24] [ 160/2639] eta: 2:04:47 lr: 2.184393022235917e-05 loss: 0.0380 (0.0424) time: 2.9805 data: 0.0078 max mem: 33408 +Epoch: [24] [ 170/2639] eta: 2:04:20 lr: 2.1839256335353472e-05 loss: 0.0355 (0.0421) time: 3.0111 data: 0.0076 max mem: 33408 +Epoch: [24] [ 180/2639] eta: 2:03:49 lr: 2.183458233720368e-05 loss: 0.0367 (0.0421) time: 3.0275 data: 0.0081 max mem: 33408 +Epoch: [24] [ 190/2639] eta: 2:03:25 lr: 2.182990822788071e-05 loss: 0.0389 (0.0424) time: 3.0402 data: 0.0082 max mem: 33408 +Epoch: [24] [ 200/2639] eta: 2:03:00 lr: 2.1825234007355477e-05 loss: 0.0360 (0.0423) time: 3.0704 data: 0.0078 max mem: 33408 +Epoch: [24] [ 210/2639] eta: 2:02:25 lr: 2.182055967559886e-05 loss: 0.0353 (0.0420) time: 3.0287 data: 0.0081 max mem: 33408 +Epoch: [24] [ 220/2639] eta: 2:01:58 lr: 2.1815885232581747e-05 loss: 0.0377 (0.0421) time: 3.0209 data: 0.0080 max mem: 33408 +Epoch: [24] [ 230/2639] eta: 2:01:24 lr: 2.1811210678274988e-05 loss: 0.0377 (0.0421) time: 3.0195 data: 0.0077 max mem: 33408 +Epoch: [24] [ 240/2639] eta: 2:00:49 lr: 2.1806536012649445e-05 loss: 0.0399 (0.0422) time: 2.9816 data: 0.0084 max mem: 33408 +Epoch: [24] [ 250/2639] eta: 2:00:18 lr: 2.180186123567594e-05 loss: 0.0348 (0.0419) time: 2.9958 data: 0.0090 max mem: 33408 +Epoch: [24] [ 260/2639] eta: 1:59:46 lr: 2.1797186347325298e-05 loss: 0.0329 (0.0417) time: 3.0094 data: 0.0084 max mem: 33408 +Epoch: [24] [ 270/2639] eta: 1:59:20 lr: 2.1792511347568313e-05 loss: 0.0348 (0.0416) time: 3.0357 data: 0.0080 max mem: 33408 +Epoch: [24] [ 280/2639] eta: 1:58:52 lr: 2.1787836236375786e-05 loss: 0.0374 (0.0418) time: 3.0562 data: 0.0080 max mem: 33408 +Epoch: [24] [ 290/2639] eta: 1:58:22 lr: 2.178316101371848e-05 loss: 0.0384 (0.0417) time: 3.0379 data: 0.0079 max mem: 33408 +Epoch: [24] [ 300/2639] eta: 1:57:55 lr: 2.177848567956717e-05 loss: 0.0409 (0.0418) time: 3.0438 data: 0.0086 max mem: 33408 +Epoch: [24] [ 310/2639] eta: 1:57:26 lr: 2.1773810233892582e-05 loss: 0.0413 (0.0419) time: 3.0542 data: 0.0089 max mem: 33408 +Epoch: [24] [ 320/2639] eta: 1:56:58 lr: 2.1769134676665464e-05 loss: 0.0448 (0.0423) time: 3.0538 data: 0.0084 max mem: 33408 +Epoch: [24] [ 330/2639] eta: 1:56:30 lr: 2.1764459007856518e-05 loss: 0.0388 (0.0421) time: 3.0534 data: 0.0088 max mem: 33408 +Epoch: [24] [ 340/2639] eta: 1:56:01 lr: 2.1759783227436462e-05 loss: 0.0361 (0.0420) time: 3.0513 data: 0.0085 max mem: 33408 +Epoch: [24] [ 350/2639] eta: 1:55:31 lr: 2.1755107335375964e-05 loss: 0.0404 (0.0425) time: 3.0420 data: 0.0078 max mem: 33408 +Epoch: [24] [ 360/2639] eta: 1:55:05 lr: 2.1750431331645707e-05 loss: 0.0367 (0.0425) time: 3.0595 data: 0.0080 max mem: 33408 +Epoch: [24] [ 370/2639] eta: 1:54:34 lr: 2.1745755216216342e-05 loss: 0.0348 (0.0423) time: 3.0548 data: 0.0080 max mem: 33408 +Epoch: [24] [ 380/2639] eta: 1:53:58 lr: 2.1741078989058513e-05 loss: 0.0395 (0.0425) time: 2.9815 data: 0.0080 max mem: 33408 +Epoch: [24] [ 390/2639] eta: 1:53:28 lr: 2.173640265014286e-05 loss: 0.0410 (0.0425) time: 2.9833 data: 0.0086 max mem: 33408 +Epoch: [24] [ 400/2639] eta: 1:53:01 lr: 2.1731726199439974e-05 loss: 0.0380 (0.0425) time: 3.0545 data: 0.0088 max mem: 33408 +Epoch: [24] [ 410/2639] eta: 1:52:30 lr: 2.172704963692047e-05 loss: 0.0380 (0.0425) time: 3.0493 data: 0.0081 max mem: 33408 +Epoch: [24] [ 420/2639] eta: 1:52:00 lr: 2.172237296255492e-05 loss: 0.0443 (0.0430) time: 3.0279 data: 0.0076 max mem: 33408 +Epoch: [24] [ 430/2639] eta: 1:51:32 lr: 2.1717696176313905e-05 loss: 0.0505 (0.0431) time: 3.0534 data: 0.0079 max mem: 33408 +Epoch: [24] [ 440/2639] eta: 1:50:59 lr: 2.1713019278167967e-05 loss: 0.0398 (0.0430) time: 3.0270 data: 0.0078 max mem: 33408 +Epoch: [24] [ 450/2639] eta: 1:50:27 lr: 2.1708342268087654e-05 loss: 0.0413 (0.0431) time: 2.9912 data: 0.0079 max mem: 33408 +Epoch: [24] [ 460/2639] eta: 1:50:00 lr: 2.1703665146043484e-05 loss: 0.0435 (0.0432) time: 3.0368 data: 0.0079 max mem: 33408 +Epoch: [24] [ 470/2639] eta: 1:49:29 lr: 2.1698987912005973e-05 loss: 0.0429 (0.0431) time: 3.0572 data: 0.0081 max mem: 33408 +Epoch: [24] [ 480/2639] eta: 1:49:00 lr: 2.1694310565945603e-05 loss: 0.0357 (0.0433) time: 3.0412 data: 0.0082 max mem: 33408 +Epoch: [24] [ 490/2639] eta: 1:48:31 lr: 2.1689633107832864e-05 loss: 0.0363 (0.0432) time: 3.0518 data: 0.0076 max mem: 33408 +Epoch: [24] [ 500/2639] eta: 1:48:00 lr: 2.1684955537638222e-05 loss: 0.0397 (0.0433) time: 3.0379 data: 0.0076 max mem: 33408 +Epoch: [24] [ 510/2639] eta: 1:47:31 lr: 2.1680277855332122e-05 loss: 0.0386 (0.0431) time: 3.0377 data: 0.0075 max mem: 33408 +Epoch: [24] [ 520/2639] eta: 1:47:01 lr: 2.1675600060885e-05 loss: 0.0422 (0.0434) time: 3.0430 data: 0.0078 max mem: 33408 +Epoch: [24] [ 530/2639] eta: 1:46:30 lr: 2.1670922154267278e-05 loss: 0.0437 (0.0434) time: 3.0279 data: 0.0081 max mem: 33408 +Epoch: [24] [ 540/2639] eta: 1:45:59 lr: 2.1666244135449357e-05 loss: 0.0371 (0.0433) time: 3.0199 data: 0.0075 max mem: 33408 +Epoch: [24] [ 550/2639] eta: 1:45:28 lr: 2.1661566004401634e-05 loss: 0.0351 (0.0433) time: 3.0166 data: 0.0073 max mem: 33408 +Epoch: [24] [ 560/2639] eta: 1:45:00 lr: 2.165688776109448e-05 loss: 0.0346 (0.0431) time: 3.0449 data: 0.0076 max mem: 33408 +Epoch: [24] [ 570/2639] eta: 1:44:30 lr: 2.1652209405498257e-05 loss: 0.0385 (0.0431) time: 3.0618 data: 0.0076 max mem: 33408 +Epoch: [24] [ 580/2639] eta: 1:44:00 lr: 2.1647530937583308e-05 loss: 0.0412 (0.0430) time: 3.0401 data: 0.0076 max mem: 33408 +Epoch: [24] [ 590/2639] eta: 1:43:29 lr: 2.164285235731997e-05 loss: 0.0356 (0.0430) time: 3.0274 data: 0.0077 max mem: 33408 +Epoch: [24] [ 600/2639] eta: 1:43:01 lr: 2.163817366467855e-05 loss: 0.0364 (0.0429) time: 3.0498 data: 0.0077 max mem: 33408 +Epoch: [24] [ 610/2639] eta: 1:42:31 lr: 2.163349485962936e-05 loss: 0.0351 (0.0430) time: 3.0574 data: 0.0076 max mem: 33408 +Epoch: [24] [ 620/2639] eta: 1:41:59 lr: 2.1628815942142668e-05 loss: 0.0358 (0.0430) time: 3.0160 data: 0.0078 max mem: 33408 +Epoch: [24] [ 630/2639] eta: 1:41:28 lr: 2.162413691218876e-05 loss: 0.0373 (0.0430) time: 3.0044 data: 0.0080 max mem: 33408 +Epoch: [24] [ 640/2639] eta: 1:40:57 lr: 2.1619457769737892e-05 loss: 0.0373 (0.0430) time: 3.0057 data: 0.0082 max mem: 33408 +Epoch: [24] [ 650/2639] eta: 1:40:28 lr: 2.1614778514760294e-05 loss: 0.0396 (0.0430) time: 3.0461 data: 0.0080 max mem: 33408 +Epoch: [24] [ 660/2639] eta: 1:39:55 lr: 2.1610099147226204e-05 loss: 0.0369 (0.0428) time: 3.0083 data: 0.0081 max mem: 33408 +Epoch: [24] [ 670/2639] eta: 1:39:23 lr: 2.1605419667105823e-05 loss: 0.0360 (0.0429) time: 2.9463 data: 0.0082 max mem: 33408 +Epoch: [24] [ 680/2639] eta: 1:38:54 lr: 2.160074007436935e-05 loss: 0.0403 (0.0428) time: 3.0188 data: 0.0079 max mem: 33408 +Epoch: [24] [ 690/2639] eta: 1:38:22 lr: 2.1596060368986965e-05 loss: 0.0367 (0.0428) time: 3.0310 data: 0.0079 max mem: 33408 +Epoch: [24] [ 700/2639] eta: 1:37:53 lr: 2.1591380550928836e-05 loss: 0.0391 (0.0428) time: 3.0360 data: 0.0079 max mem: 33408 +Epoch: [24] [ 710/2639] eta: 1:37:24 lr: 2.1586700620165108e-05 loss: 0.0382 (0.0427) time: 3.0626 data: 0.0078 max mem: 33408 +Epoch: [24] [ 720/2639] eta: 1:36:54 lr: 2.1582020576665925e-05 loss: 0.0382 (0.0427) time: 3.0440 data: 0.0080 max mem: 33408 +Epoch: [24] [ 730/2639] eta: 1:36:24 lr: 2.1577340420401392e-05 loss: 0.0406 (0.0428) time: 3.0504 data: 0.0084 max mem: 33408 +Epoch: [24] [ 740/2639] eta: 1:35:55 lr: 2.1572660151341635e-05 loss: 0.0397 (0.0426) time: 3.0636 data: 0.0083 max mem: 33408 +Epoch: [24] [ 750/2639] eta: 1:35:24 lr: 2.156797976945672e-05 loss: 0.0378 (0.0428) time: 3.0288 data: 0.0082 max mem: 33408 +Epoch: [24] [ 760/2639] eta: 1:34:53 lr: 2.1563299274716744e-05 loss: 0.0448 (0.0428) time: 3.0181 data: 0.0081 max mem: 33408 +Epoch: [24] [ 770/2639] eta: 1:34:25 lr: 2.1558618667091748e-05 loss: 0.0424 (0.0428) time: 3.0755 data: 0.0078 max mem: 33408 +Epoch: [24] [ 780/2639] eta: 1:33:54 lr: 2.1553937946551795e-05 loss: 0.0431 (0.0428) time: 3.0518 data: 0.0081 max mem: 33408 +Epoch: [24] [ 790/2639] eta: 1:33:24 lr: 2.1549257113066894e-05 loss: 0.0390 (0.0429) time: 3.0300 data: 0.0081 max mem: 33408 +Epoch: [24] [ 800/2639] eta: 1:32:55 lr: 2.154457616660708e-05 loss: 0.0379 (0.0428) time: 3.0773 data: 0.0080 max mem: 33408 +Epoch: [24] [ 810/2639] eta: 1:32:25 lr: 2.153989510714233e-05 loss: 0.0417 (0.0429) time: 3.0573 data: 0.0081 max mem: 33408 +Epoch: [24] [ 820/2639] eta: 1:31:56 lr: 2.1535213934642645e-05 loss: 0.0457 (0.0429) time: 3.0538 data: 0.0076 max mem: 33408 +Epoch: [24] [ 830/2639] eta: 1:31:25 lr: 2.1530532649077984e-05 loss: 0.0433 (0.0432) time: 3.0421 data: 0.0076 max mem: 33408 +Epoch: [24] [ 840/2639] eta: 1:30:55 lr: 2.1525851250418304e-05 loss: 0.0422 (0.0433) time: 3.0266 data: 0.0082 max mem: 33408 +Epoch: [24] [ 850/2639] eta: 1:30:25 lr: 2.152116973863354e-05 loss: 0.0387 (0.0433) time: 3.0591 data: 0.0080 max mem: 33408 +Epoch: [24] [ 860/2639] eta: 1:29:53 lr: 2.151648811369362e-05 loss: 0.0377 (0.0432) time: 3.0125 data: 0.0078 max mem: 33408 +Epoch: [24] [ 870/2639] eta: 1:29:23 lr: 2.151180637556845e-05 loss: 0.0356 (0.0432) time: 2.9861 data: 0.0081 max mem: 33408 +Epoch: [24] [ 880/2639] eta: 1:28:53 lr: 2.150712452422791e-05 loss: 0.0375 (0.0432) time: 3.0345 data: 0.0080 max mem: 33408 +Epoch: [24] [ 890/2639] eta: 1:28:23 lr: 2.15024425596419e-05 loss: 0.0419 (0.0432) time: 3.0572 data: 0.0080 max mem: 33408 +Epoch: [24] [ 900/2639] eta: 1:27:51 lr: 2.1497760481780258e-05 loss: 0.0419 (0.0431) time: 3.0129 data: 0.0080 max mem: 33408 +Epoch: [24] [ 910/2639] eta: 1:27:20 lr: 2.1493078290612846e-05 loss: 0.0372 (0.0431) time: 2.9792 data: 0.0079 max mem: 33408 +Epoch: [24] [ 920/2639] eta: 1:26:51 lr: 2.1488395986109485e-05 loss: 0.0436 (0.0432) time: 3.0428 data: 0.0078 max mem: 33408 +Epoch: [24] [ 930/2639] eta: 1:26:20 lr: 2.1483713568240002e-05 loss: 0.0436 (0.0432) time: 3.0470 data: 0.0081 max mem: 33408 +Epoch: [24] [ 940/2639] eta: 1:25:51 lr: 2.147903103697418e-05 loss: 0.0415 (0.0434) time: 3.0504 data: 0.0081 max mem: 33408 +Epoch: [24] [ 950/2639] eta: 1:25:21 lr: 2.1474348392281822e-05 loss: 0.0423 (0.0434) time: 3.0625 data: 0.0077 max mem: 33408 +Epoch: [24] [ 960/2639] eta: 1:24:51 lr: 2.1469665634132686e-05 loss: 0.0451 (0.0435) time: 3.0472 data: 0.0079 max mem: 33408 +Epoch: [24] [ 970/2639] eta: 1:24:19 lr: 2.1464982762496534e-05 loss: 0.0437 (0.0435) time: 3.0051 data: 0.0085 max mem: 33408 +Epoch: [24] [ 980/2639] eta: 1:23:50 lr: 2.146029977734309e-05 loss: 0.0409 (0.0435) time: 3.0086 data: 0.0085 max mem: 33408 +Epoch: [24] [ 990/2639] eta: 1:23:18 lr: 2.1455616678642095e-05 loss: 0.0406 (0.0435) time: 3.0179 data: 0.0080 max mem: 33408 +Epoch: [24] [1000/2639] eta: 1:22:47 lr: 2.1450933466363247e-05 loss: 0.0380 (0.0435) time: 2.9694 data: 0.0079 max mem: 33408 +Epoch: [24] [1010/2639] eta: 1:22:16 lr: 2.144625014047624e-05 loss: 0.0377 (0.0435) time: 2.9950 data: 0.0083 max mem: 33408 +Epoch: [24] [1020/2639] eta: 1:21:45 lr: 2.144156670095075e-05 loss: 0.0335 (0.0434) time: 3.0002 data: 0.0082 max mem: 33408 +Epoch: [24] [1030/2639] eta: 1:21:15 lr: 2.1436883147756442e-05 loss: 0.0402 (0.0435) time: 3.0085 data: 0.0080 max mem: 33408 +Epoch: [24] [1040/2639] eta: 1:20:43 lr: 2.1432199480862954e-05 loss: 0.0401 (0.0435) time: 2.9817 data: 0.0088 max mem: 33408 +Epoch: [24] [1050/2639] eta: 1:20:12 lr: 2.1427515700239927e-05 loss: 0.0366 (0.0434) time: 2.9538 data: 0.0090 max mem: 33408 +Epoch: [24] [1060/2639] eta: 1:19:42 lr: 2.1422831805856967e-05 loss: 0.0325 (0.0433) time: 3.0144 data: 0.0080 max mem: 33408 +Epoch: [24] [1070/2639] eta: 1:19:13 lr: 2.1418147797683686e-05 loss: 0.0325 (0.0433) time: 3.0626 data: 0.0077 max mem: 33408 +Epoch: [24] [1080/2639] eta: 1:18:43 lr: 2.141346367568965e-05 loss: 0.0345 (0.0432) time: 3.0657 data: 0.0079 max mem: 33408 +Epoch: [24] [1090/2639] eta: 1:18:12 lr: 2.1408779439844446e-05 loss: 0.0357 (0.0432) time: 3.0261 data: 0.0077 max mem: 33408 +Epoch: [24] [1100/2639] eta: 1:17:41 lr: 2.140409509011761e-05 loss: 0.0421 (0.0432) time: 2.9760 data: 0.0075 max mem: 33408 +Epoch: [24] [1110/2639] eta: 1:17:11 lr: 2.1399410626478688e-05 loss: 0.0382 (0.0433) time: 3.0180 data: 0.0077 max mem: 33408 +Epoch: [24] [1120/2639] eta: 1:16:41 lr: 2.1394726048897208e-05 loss: 0.0327 (0.0433) time: 3.0606 data: 0.0079 max mem: 33408 +Epoch: [24] [1130/2639] eta: 1:16:10 lr: 2.1390041357342664e-05 loss: 0.0359 (0.0433) time: 3.0118 data: 0.0079 max mem: 33408 +Epoch: [24] [1140/2639] eta: 1:15:39 lr: 2.1385356551784557e-05 loss: 0.0524 (0.0434) time: 2.9795 data: 0.0078 max mem: 33408 +Epoch: [24] [1150/2639] eta: 1:15:08 lr: 2.1380671632192355e-05 loss: 0.0521 (0.0434) time: 2.9943 data: 0.0075 max mem: 33408 +Epoch: [24] [1160/2639] eta: 1:14:38 lr: 2.137598659853552e-05 loss: 0.0421 (0.0438) time: 3.0230 data: 0.0073 max mem: 33408 +Epoch: [24] [1170/2639] eta: 1:14:07 lr: 2.1371301450783493e-05 loss: 0.0396 (0.0438) time: 3.0092 data: 0.0073 max mem: 33408 +Epoch: [24] [1180/2639] eta: 1:13:38 lr: 2.136661618890571e-05 loss: 0.0423 (0.0438) time: 3.0201 data: 0.0075 max mem: 33408 +Epoch: [24] [1190/2639] eta: 1:13:07 lr: 2.1361930812871575e-05 loss: 0.0480 (0.0439) time: 3.0505 data: 0.0076 max mem: 33408 +Epoch: [24] [1200/2639] eta: 1:12:37 lr: 2.1357245322650492e-05 loss: 0.0429 (0.0439) time: 3.0130 data: 0.0074 max mem: 33408 +Epoch: [24] [1210/2639] eta: 1:12:06 lr: 2.1352559718211834e-05 loss: 0.0348 (0.0439) time: 2.9943 data: 0.0073 max mem: 33408 +Epoch: [24] [1220/2639] eta: 1:11:36 lr: 2.134787399952498e-05 loss: 0.0387 (0.0440) time: 3.0350 data: 0.0073 max mem: 33408 +Epoch: [24] [1230/2639] eta: 1:11:06 lr: 2.134318816655926e-05 loss: 0.0400 (0.0441) time: 3.0535 data: 0.0071 max mem: 33408 +Epoch: [24] [1240/2639] eta: 1:10:36 lr: 2.1338502219284028e-05 loss: 0.0400 (0.0441) time: 3.0332 data: 0.0073 max mem: 33408 +Epoch: [24] [1250/2639] eta: 1:10:06 lr: 2.133381615766859e-05 loss: 0.0411 (0.0443) time: 3.0276 data: 0.0072 max mem: 33408 +Epoch: [24] [1260/2639] eta: 1:09:35 lr: 2.132912998168226e-05 loss: 0.0444 (0.0443) time: 3.0210 data: 0.0071 max mem: 33408 +Epoch: [24] [1270/2639] eta: 1:09:05 lr: 2.1324443691294308e-05 loss: 0.0356 (0.0443) time: 3.0438 data: 0.0072 max mem: 33408 +Epoch: [24] [1280/2639] eta: 1:08:34 lr: 2.1319757286474025e-05 loss: 0.0408 (0.0443) time: 3.0040 data: 0.0073 max mem: 33408 +Epoch: [24] [1290/2639] eta: 1:08:03 lr: 2.131507076719065e-05 loss: 0.0424 (0.0443) time: 2.9545 data: 0.0075 max mem: 33408 +Epoch: [24] [1300/2639] eta: 1:07:33 lr: 2.131038413341343e-05 loss: 0.0405 (0.0443) time: 3.0156 data: 0.0076 max mem: 33408 +Epoch: [24] [1310/2639] eta: 1:07:03 lr: 2.1305697385111587e-05 loss: 0.0388 (0.0444) time: 3.0318 data: 0.0077 max mem: 33408 +Epoch: [24] [1320/2639] eta: 1:06:32 lr: 2.1301010522254337e-05 loss: 0.0388 (0.0443) time: 2.9846 data: 0.0077 max mem: 33408 +Epoch: [24] [1330/2639] eta: 1:06:02 lr: 2.1296323544810857e-05 loss: 0.0369 (0.0443) time: 3.0141 data: 0.0080 max mem: 33408 +Epoch: [24] [1340/2639] eta: 1:05:32 lr: 2.129163645275034e-05 loss: 0.0379 (0.0443) time: 3.0509 data: 0.0076 max mem: 33408 +Epoch: [24] [1350/2639] eta: 1:05:01 lr: 2.1286949246041934e-05 loss: 0.0376 (0.0443) time: 2.9866 data: 0.0076 max mem: 33408 +Epoch: [24] [1360/2639] eta: 1:04:30 lr: 2.128226192465479e-05 loss: 0.0388 (0.0443) time: 2.9584 data: 0.0078 max mem: 33408 +Epoch: [24] [1370/2639] eta: 1:04:00 lr: 2.127757448855804e-05 loss: 0.0437 (0.0443) time: 3.0043 data: 0.0077 max mem: 33408 +Epoch: [24] [1380/2639] eta: 1:03:30 lr: 2.127288693772079e-05 loss: 0.0390 (0.0442) time: 3.0518 data: 0.0080 max mem: 33408 +Epoch: [24] [1390/2639] eta: 1:03:00 lr: 2.1268199272112144e-05 loss: 0.0396 (0.0442) time: 3.0797 data: 0.0082 max mem: 33408 +Epoch: [24] [1400/2639] eta: 1:02:29 lr: 2.1263511491701173e-05 loss: 0.0408 (0.0442) time: 3.0285 data: 0.0078 max mem: 33408 +Epoch: [24] [1410/2639] eta: 1:02:00 lr: 2.1258823596456956e-05 loss: 0.0408 (0.0442) time: 3.0256 data: 0.0075 max mem: 33408 +Epoch: [24] [1420/2639] eta: 1:01:30 lr: 2.125413558634853e-05 loss: 0.0403 (0.0442) time: 3.0805 data: 0.0079 max mem: 33408 +Epoch: [24] [1430/2639] eta: 1:01:00 lr: 2.1249447461344943e-05 loss: 0.0380 (0.0442) time: 3.0661 data: 0.0078 max mem: 33408 +Epoch: [24] [1440/2639] eta: 1:00:30 lr: 2.1244759221415193e-05 loss: 0.0380 (0.0442) time: 3.0513 data: 0.0078 max mem: 33408 +Epoch: [24] [1450/2639] eta: 1:00:00 lr: 2.1240070866528303e-05 loss: 0.0390 (0.0442) time: 3.0799 data: 0.0080 max mem: 33408 +Epoch: [24] [1460/2639] eta: 0:59:29 lr: 2.123538239665324e-05 loss: 0.0422 (0.0442) time: 3.0446 data: 0.0075 max mem: 33408 +Epoch: [24] [1470/2639] eta: 0:58:59 lr: 2.1230693811758993e-05 loss: 0.0382 (0.0442) time: 3.0119 data: 0.0074 max mem: 33408 +Epoch: [24] [1480/2639] eta: 0:58:30 lr: 2.1226005111814492e-05 loss: 0.0356 (0.0442) time: 3.0814 data: 0.0075 max mem: 33408 +Epoch: [24] [1490/2639] eta: 0:57:59 lr: 2.12213162967887e-05 loss: 0.0356 (0.0442) time: 3.0473 data: 0.0077 max mem: 33408 +Epoch: [24] [1500/2639] eta: 0:57:28 lr: 2.1216627366650517e-05 loss: 0.0346 (0.0442) time: 2.9560 data: 0.0076 max mem: 33408 +Epoch: [24] [1510/2639] eta: 0:56:58 lr: 2.1211938321368864e-05 loss: 0.0346 (0.0441) time: 2.9878 data: 0.0075 max mem: 33408 +Epoch: [24] [1520/2639] eta: 0:56:28 lr: 2.120724916091262e-05 loss: 0.0372 (0.0441) time: 3.0404 data: 0.0076 max mem: 33408 +Epoch: [24] [1530/2639] eta: 0:55:57 lr: 2.120255988525067e-05 loss: 0.0351 (0.0441) time: 3.0088 data: 0.0073 max mem: 33408 +Epoch: [24] [1540/2639] eta: 0:55:27 lr: 2.119787049435186e-05 loss: 0.0303 (0.0440) time: 3.0327 data: 0.0075 max mem: 33408 +Epoch: [24] [1550/2639] eta: 0:54:57 lr: 2.1193180988185043e-05 loss: 0.0375 (0.0441) time: 3.0620 data: 0.0076 max mem: 33408 +Epoch: [24] [1560/2639] eta: 0:54:26 lr: 2.1188491366719033e-05 loss: 0.0376 (0.0440) time: 3.0181 data: 0.0077 max mem: 33408 +Epoch: [24] [1570/2639] eta: 0:53:56 lr: 2.1183801629922646e-05 loss: 0.0427 (0.0441) time: 3.0134 data: 0.0078 max mem: 33408 +Epoch: [24] [1580/2639] eta: 0:53:26 lr: 2.1179111777764672e-05 loss: 0.0427 (0.0441) time: 3.0408 data: 0.0075 max mem: 33408 +Epoch: [24] [1590/2639] eta: 0:52:56 lr: 2.1174421810213895e-05 loss: 0.0354 (0.0440) time: 3.0287 data: 0.0072 max mem: 33408 +Epoch: [24] [1600/2639] eta: 0:52:25 lr: 2.1169731727239063e-05 loss: 0.0337 (0.0440) time: 3.0248 data: 0.0073 max mem: 33408 +Epoch: [24] [1610/2639] eta: 0:51:56 lr: 2.116504152880893e-05 loss: 0.0385 (0.0440) time: 3.0804 data: 0.0076 max mem: 33408 +Epoch: [24] [1620/2639] eta: 0:51:26 lr: 2.1160351214892226e-05 loss: 0.0375 (0.0440) time: 3.0879 data: 0.0080 max mem: 33408 +Epoch: [24] [1630/2639] eta: 0:50:55 lr: 2.115566078545766e-05 loss: 0.0350 (0.0440) time: 3.0585 data: 0.0077 max mem: 33408 +Epoch: [24] [1640/2639] eta: 0:50:25 lr: 2.115097024047393e-05 loss: 0.0459 (0.0441) time: 3.0629 data: 0.0075 max mem: 33408 +Epoch: [24] [1650/2639] eta: 0:49:55 lr: 2.114627957990971e-05 loss: 0.0410 (0.0441) time: 3.0627 data: 0.0075 max mem: 33408 +Epoch: [24] [1660/2639] eta: 0:49:25 lr: 2.1141588803733678e-05 loss: 0.0402 (0.0441) time: 3.0126 data: 0.0073 max mem: 33408 +Epoch: [24] [1670/2639] eta: 0:48:54 lr: 2.1136897911914468e-05 loss: 0.0390 (0.0440) time: 2.9537 data: 0.0073 max mem: 33408 +Epoch: [24] [1680/2639] eta: 0:48:24 lr: 2.1132206904420714e-05 loss: 0.0379 (0.0440) time: 2.9889 data: 0.0076 max mem: 33408 +Epoch: [24] [1690/2639] eta: 0:47:54 lr: 2.1127515781221033e-05 loss: 0.0411 (0.0440) time: 3.0522 data: 0.0075 max mem: 33408 +Epoch: [24] [1700/2639] eta: 0:47:23 lr: 2.1122824542284028e-05 loss: 0.0411 (0.0441) time: 3.0358 data: 0.0071 max mem: 33408 +Epoch: [24] [1710/2639] eta: 0:46:53 lr: 2.1118133187578272e-05 loss: 0.0384 (0.0440) time: 2.9919 data: 0.0073 max mem: 33408 +Epoch: [24] [1720/2639] eta: 0:46:22 lr: 2.1113441717072342e-05 loss: 0.0410 (0.0440) time: 3.0059 data: 0.0075 max mem: 33408 +Epoch: [24] [1730/2639] eta: 0:45:52 lr: 2.110875013073478e-05 loss: 0.0385 (0.0441) time: 3.0040 data: 0.0075 max mem: 33408 +Epoch: [24] [1740/2639] eta: 0:45:21 lr: 2.1104058428534126e-05 loss: 0.0360 (0.0440) time: 2.9551 data: 0.0080 max mem: 33408 +Epoch: [24] [1750/2639] eta: 0:44:51 lr: 2.1099366610438888e-05 loss: 0.0360 (0.0440) time: 2.9977 data: 0.0080 max mem: 33408 +Epoch: [24] [1760/2639] eta: 0:44:21 lr: 2.109467467641758e-05 loss: 0.0343 (0.0440) time: 3.0611 data: 0.0076 max mem: 33408 +Epoch: [24] [1770/2639] eta: 0:43:50 lr: 2.1089982626438673e-05 loss: 0.0383 (0.0441) time: 3.0399 data: 0.0075 max mem: 33408 +Epoch: [24] [1780/2639] eta: 0:43:20 lr: 2.108529046047065e-05 loss: 0.0378 (0.0441) time: 3.0069 data: 0.0073 max mem: 33408 +Epoch: [24] [1790/2639] eta: 0:42:50 lr: 2.108059817848195e-05 loss: 0.0378 (0.0442) time: 3.0066 data: 0.0076 max mem: 33408 +Epoch: [24] [1800/2639] eta: 0:42:20 lr: 2.1075905780441016e-05 loss: 0.0414 (0.0442) time: 3.0400 data: 0.0077 max mem: 33408 +Epoch: [24] [1810/2639] eta: 0:41:49 lr: 2.107121326631626e-05 loss: 0.0415 (0.0442) time: 3.0532 data: 0.0075 max mem: 33408 +Epoch: [24] [1820/2639] eta: 0:41:19 lr: 2.10665206360761e-05 loss: 0.0412 (0.0442) time: 3.0275 data: 0.0080 max mem: 33408 +Epoch: [24] [1830/2639] eta: 0:40:49 lr: 2.1061827889688902e-05 loss: 0.0380 (0.0442) time: 2.9939 data: 0.0082 max mem: 33408 +Epoch: [24] [1840/2639] eta: 0:40:18 lr: 2.105713502712305e-05 loss: 0.0380 (0.0442) time: 3.0097 data: 0.0079 max mem: 33408 +Epoch: [24] [1850/2639] eta: 0:39:48 lr: 2.1052442048346892e-05 loss: 0.0415 (0.0442) time: 3.0676 data: 0.0077 max mem: 33408 +Epoch: [24] [1860/2639] eta: 0:39:18 lr: 2.1047748953328765e-05 loss: 0.0415 (0.0442) time: 3.0440 data: 0.0076 max mem: 33408 +Epoch: [24] [1870/2639] eta: 0:38:48 lr: 2.1043055742037e-05 loss: 0.0399 (0.0442) time: 3.0152 data: 0.0076 max mem: 33408 +Epoch: [24] [1880/2639] eta: 0:38:18 lr: 2.1038362414439883e-05 loss: 0.0370 (0.0442) time: 3.0554 data: 0.0077 max mem: 33408 +Epoch: [24] [1890/2639] eta: 0:37:48 lr: 2.1033668970505717e-05 loss: 0.0372 (0.0441) time: 3.0916 data: 0.0079 max mem: 33408 +Epoch: [24] [1900/2639] eta: 0:37:17 lr: 2.1028975410202762e-05 loss: 0.0360 (0.0441) time: 3.0623 data: 0.0076 max mem: 33408 +Epoch: [24] [1910/2639] eta: 0:36:47 lr: 2.1024281733499283e-05 loss: 0.0455 (0.0442) time: 3.0275 data: 0.0074 max mem: 33408 +Epoch: [24] [1920/2639] eta: 0:36:17 lr: 2.1019587940363505e-05 loss: 0.0428 (0.0442) time: 3.0568 data: 0.0074 max mem: 33408 +Epoch: [24] [1930/2639] eta: 0:35:47 lr: 2.1014894030763665e-05 loss: 0.0366 (0.0442) time: 3.0522 data: 0.0074 max mem: 33408 +Epoch: [24] [1940/2639] eta: 0:35:17 lr: 2.1010200004667955e-05 loss: 0.0350 (0.0441) time: 3.0437 data: 0.0078 max mem: 33408 +Epoch: [24] [1950/2639] eta: 0:34:46 lr: 2.100550586204457e-05 loss: 0.0339 (0.0441) time: 3.0576 data: 0.0083 max mem: 33408 +Epoch: [24] [1960/2639] eta: 0:34:16 lr: 2.1000811602861677e-05 loss: 0.0387 (0.0441) time: 3.0267 data: 0.0086 max mem: 33408 +Epoch: [24] [1970/2639] eta: 0:33:46 lr: 2.099611722708744e-05 loss: 0.0394 (0.0441) time: 3.0246 data: 0.0082 max mem: 33408 +Epoch: [24] [1980/2639] eta: 0:33:15 lr: 2.0991422734689982e-05 loss: 0.0408 (0.0441) time: 3.0240 data: 0.0076 max mem: 33408 +Epoch: [24] [1990/2639] eta: 0:32:45 lr: 2.0986728125637446e-05 loss: 0.0408 (0.0441) time: 3.0498 data: 0.0077 max mem: 33408 +Epoch: [24] [2000/2639] eta: 0:32:15 lr: 2.0982033399897916e-05 loss: 0.0359 (0.0441) time: 3.0596 data: 0.0076 max mem: 33408 +Epoch: [24] [2010/2639] eta: 0:31:45 lr: 2.0977338557439495e-05 loss: 0.0358 (0.0441) time: 3.0153 data: 0.0077 max mem: 33408 +Epoch: [24] [2020/2639] eta: 0:31:14 lr: 2.0972643598230247e-05 loss: 0.0370 (0.0441) time: 3.0156 data: 0.0081 max mem: 33408 +Epoch: [24] [2030/2639] eta: 0:30:44 lr: 2.0967948522238232e-05 loss: 0.0409 (0.0441) time: 2.9896 data: 0.0080 max mem: 33408 +Epoch: [24] [2040/2639] eta: 0:30:14 lr: 2.0963253329431484e-05 loss: 0.0368 (0.0441) time: 3.0157 data: 0.0080 max mem: 33408 +Epoch: [24] [2050/2639] eta: 0:29:44 lr: 2.095855801977803e-05 loss: 0.0368 (0.0441) time: 3.0726 data: 0.0078 max mem: 33408 +Epoch: [24] [2060/2639] eta: 0:29:13 lr: 2.0953862593245873e-05 loss: 0.0419 (0.0441) time: 3.0227 data: 0.0073 max mem: 33408 +Epoch: [24] [2070/2639] eta: 0:28:43 lr: 2.0949167049803002e-05 loss: 0.0399 (0.0441) time: 2.9896 data: 0.0077 max mem: 33408 +Epoch: [24] [2080/2639] eta: 0:28:12 lr: 2.0944471389417387e-05 loss: 0.0399 (0.0441) time: 3.0024 data: 0.0081 max mem: 33408 +Epoch: [24] [2090/2639] eta: 0:27:42 lr: 2.0939775612056986e-05 loss: 0.0414 (0.0440) time: 3.0435 data: 0.0081 max mem: 33408 +Epoch: [24] [2100/2639] eta: 0:27:12 lr: 2.093507971768973e-05 loss: 0.0406 (0.0440) time: 3.0565 data: 0.0078 max mem: 33408 +Epoch: [24] [2110/2639] eta: 0:26:42 lr: 2.0930383706283545e-05 loss: 0.0408 (0.0441) time: 3.0359 data: 0.0079 max mem: 33408 +Epoch: [24] [2120/2639] eta: 0:26:11 lr: 2.092568757780634e-05 loss: 0.0392 (0.0441) time: 3.0214 data: 0.0078 max mem: 33408 +Epoch: [24] [2130/2639] eta: 0:25:41 lr: 2.0920991332225997e-05 loss: 0.0404 (0.0441) time: 3.0082 data: 0.0077 max mem: 33408 +Epoch: [24] [2140/2639] eta: 0:25:11 lr: 2.0916294969510393e-05 loss: 0.0362 (0.0441) time: 3.0417 data: 0.0077 max mem: 33408 +Epoch: [24] [2150/2639] eta: 0:24:40 lr: 2.0911598489627367e-05 loss: 0.0328 (0.0441) time: 3.0312 data: 0.0074 max mem: 33408 +Epoch: [24] [2160/2639] eta: 0:24:10 lr: 2.0906901892544777e-05 loss: 0.0407 (0.0441) time: 2.9981 data: 0.0074 max mem: 33408 +Epoch: [24] [2170/2639] eta: 0:23:40 lr: 2.0902205178230428e-05 loss: 0.0407 (0.0441) time: 3.0134 data: 0.0076 max mem: 33408 +Epoch: [24] [2180/2639] eta: 0:23:10 lr: 2.0897508346652133e-05 loss: 0.0380 (0.0441) time: 3.0485 data: 0.0077 max mem: 33408 +Epoch: [24] [2190/2639] eta: 0:22:39 lr: 2.089281139777767e-05 loss: 0.0405 (0.0441) time: 3.0596 data: 0.0075 max mem: 33408 +Epoch: [24] [2200/2639] eta: 0:22:09 lr: 2.0888114331574817e-05 loss: 0.0358 (0.0441) time: 3.0191 data: 0.0076 max mem: 33408 +Epoch: [24] [2210/2639] eta: 0:21:39 lr: 2.088341714801132e-05 loss: 0.0354 (0.0441) time: 3.0060 data: 0.0077 max mem: 33408 +Epoch: [24] [2220/2639] eta: 0:21:08 lr: 2.087871984705492e-05 loss: 0.0519 (0.0442) time: 3.0278 data: 0.0078 max mem: 33408 +Epoch: [24] [2230/2639] eta: 0:20:38 lr: 2.087402242867333e-05 loss: 0.0458 (0.0442) time: 3.0258 data: 0.0076 max mem: 33408 +Epoch: [24] [2240/2639] eta: 0:20:08 lr: 2.086932489283426e-05 loss: 0.0357 (0.0441) time: 3.0027 data: 0.0075 max mem: 33408 +Epoch: [24] [2250/2639] eta: 0:19:38 lr: 2.0864627239505387e-05 loss: 0.0380 (0.0441) time: 3.0335 data: 0.0077 max mem: 33408 +Epoch: [24] [2260/2639] eta: 0:19:07 lr: 2.085992946865439e-05 loss: 0.0438 (0.0441) time: 3.0253 data: 0.0076 max mem: 33408 +Epoch: [24] [2270/2639] eta: 0:18:37 lr: 2.0855231580248907e-05 loss: 0.0454 (0.0442) time: 2.9975 data: 0.0076 max mem: 33408 +Epoch: [24] [2280/2639] eta: 0:18:07 lr: 2.085053357425658e-05 loss: 0.0474 (0.0442) time: 3.0420 data: 0.0075 max mem: 33408 +Epoch: [24] [2290/2639] eta: 0:17:36 lr: 2.0845835450645023e-05 loss: 0.0440 (0.0441) time: 3.0399 data: 0.0074 max mem: 33408 +Epoch: [24] [2300/2639] eta: 0:17:06 lr: 2.0841137209381842e-05 loss: 0.0371 (0.0441) time: 3.0407 data: 0.0072 max mem: 33408 +Epoch: [24] [2310/2639] eta: 0:16:36 lr: 2.0836438850434608e-05 loss: 0.0371 (0.0441) time: 3.0086 data: 0.0073 max mem: 33408 +Epoch: [24] [2320/2639] eta: 0:16:05 lr: 2.08317403737709e-05 loss: 0.0397 (0.0441) time: 2.9968 data: 0.0075 max mem: 33408 +Epoch: [24] [2330/2639] eta: 0:15:35 lr: 2.082704177935826e-05 loss: 0.0404 (0.0442) time: 3.0505 data: 0.0075 max mem: 33408 +Epoch: [24] [2340/2639] eta: 0:15:05 lr: 2.082234306716422e-05 loss: 0.0404 (0.0441) time: 3.0211 data: 0.0078 max mem: 33408 +Epoch: [24] [2350/2639] eta: 0:14:35 lr: 2.0817644237156295e-05 loss: 0.0402 (0.0442) time: 3.0017 data: 0.0080 max mem: 33408 +Epoch: [24] [2360/2639] eta: 0:14:04 lr: 2.081294528930198e-05 loss: 0.0471 (0.0442) time: 3.0258 data: 0.0080 max mem: 33408 +Epoch: [24] [2370/2639] eta: 0:13:34 lr: 2.0808246223568767e-05 loss: 0.0451 (0.0442) time: 2.9792 data: 0.0077 max mem: 33408 +Epoch: [24] [2380/2639] eta: 0:13:04 lr: 2.0803547039924105e-05 loss: 0.0394 (0.0442) time: 3.0165 data: 0.0074 max mem: 33408 +Epoch: [24] [2390/2639] eta: 0:12:33 lr: 2.079884773833545e-05 loss: 0.0388 (0.0442) time: 3.0719 data: 0.0071 max mem: 33408 +Epoch: [24] [2400/2639] eta: 0:12:03 lr: 2.079414831877022e-05 loss: 0.0425 (0.0442) time: 3.0204 data: 0.0072 max mem: 33408 +Epoch: [24] [2410/2639] eta: 0:11:33 lr: 2.078944878119584e-05 loss: 0.0431 (0.0442) time: 3.0007 data: 0.0074 max mem: 33408 +Epoch: [24] [2420/2639] eta: 0:11:03 lr: 2.0784749125579697e-05 loss: 0.0397 (0.0443) time: 3.0420 data: 0.0074 max mem: 33408 +Epoch: [24] [2430/2639] eta: 0:10:32 lr: 2.078004935188917e-05 loss: 0.0397 (0.0443) time: 3.0550 data: 0.0079 max mem: 33408 +Epoch: [24] [2440/2639] eta: 0:10:02 lr: 2.077534946009162e-05 loss: 0.0468 (0.0443) time: 3.0299 data: 0.0079 max mem: 33408 +Epoch: [24] [2450/2639] eta: 0:09:32 lr: 2.077064945015439e-05 loss: 0.0428 (0.0443) time: 3.0266 data: 0.0075 max mem: 33408 +Epoch: [24] [2460/2639] eta: 0:09:02 lr: 2.07659493220448e-05 loss: 0.0394 (0.0443) time: 3.0270 data: 0.0076 max mem: 33408 +Epoch: [24] [2470/2639] eta: 0:08:31 lr: 2.076124907573017e-05 loss: 0.0404 (0.0443) time: 3.0366 data: 0.0075 max mem: 33408 +Epoch: [24] [2480/2639] eta: 0:08:01 lr: 2.075654871117778e-05 loss: 0.0404 (0.0443) time: 3.0318 data: 0.0072 max mem: 33408 +Epoch: [24] [2490/2639] eta: 0:07:31 lr: 2.0751848228354914e-05 loss: 0.0403 (0.0443) time: 2.9875 data: 0.0070 max mem: 33408 +Epoch: [24] [2500/2639] eta: 0:07:00 lr: 2.0747147627228818e-05 loss: 0.0425 (0.0443) time: 2.9681 data: 0.0070 max mem: 33408 +Epoch: [24] [2510/2639] eta: 0:06:30 lr: 2.074244690776674e-05 loss: 0.0422 (0.0444) time: 2.9997 data: 0.0074 max mem: 33408 +Epoch: [24] [2520/2639] eta: 0:06:00 lr: 2.0737746069935894e-05 loss: 0.0476 (0.0444) time: 3.0191 data: 0.0076 max mem: 33408 +Epoch: [24] [2530/2639] eta: 0:05:30 lr: 2.0733045113703496e-05 loss: 0.0466 (0.0444) time: 3.0342 data: 0.0076 max mem: 33408 +Epoch: [24] [2540/2639] eta: 0:04:59 lr: 2.072834403903672e-05 loss: 0.0445 (0.0444) time: 3.0507 data: 0.0076 max mem: 33408 +Epoch: [24] [2550/2639] eta: 0:04:29 lr: 2.072364284590275e-05 loss: 0.0419 (0.0444) time: 3.0572 data: 0.0077 max mem: 33408 +Epoch: [24] [2560/2639] eta: 0:03:59 lr: 2.0718941534268723e-05 loss: 0.0397 (0.0444) time: 3.0632 data: 0.0076 max mem: 33408 +Epoch: [24] [2570/2639] eta: 0:03:28 lr: 2.071424010410179e-05 loss: 0.0405 (0.0444) time: 3.0589 data: 0.0072 max mem: 33408 +Epoch: [24] [2580/2639] eta: 0:02:58 lr: 2.0709538555369057e-05 loss: 0.0405 (0.0444) time: 3.0360 data: 0.0074 max mem: 33408 +Epoch: [24] [2590/2639] eta: 0:02:28 lr: 2.0704836888037626e-05 loss: 0.0423 (0.0444) time: 3.0031 data: 0.0078 max mem: 33408 +Epoch: [24] [2600/2639] eta: 0:01:58 lr: 2.070013510207459e-05 loss: 0.0447 (0.0444) time: 3.0330 data: 0.0077 max mem: 33408 +Epoch: [24] [2610/2639] eta: 0:01:27 lr: 2.0695433197446997e-05 loss: 0.0374 (0.0444) time: 3.0443 data: 0.0075 max mem: 33408 +Epoch: [24] [2620/2639] eta: 0:00:57 lr: 2.0690731174121913e-05 loss: 0.0366 (0.0444) time: 2.9745 data: 0.0076 max mem: 33408 +Epoch: [24] [2630/2639] eta: 0:00:27 lr: 2.0686029032066358e-05 loss: 0.0383 (0.0444) time: 2.9635 data: 0.0076 max mem: 33408 +Epoch: [24] Total time: 2:13:10 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 1:58:57 time: 2.7738 data: 2.6821 max mem: 33408 +Test: [ 100/2573] eta: 0:04:20 time: 0.0788 data: 0.0015 max mem: 33408 +Test: [ 200/2573] eta: 0:03:41 time: 0.0805 data: 0.0015 max mem: 33408 +Test: [ 300/2573] eta: 0:03:21 time: 0.0826 data: 0.0014 max mem: 33408 +Test: [ 400/2573] eta: 0:03:08 time: 0.0814 data: 0.0014 max mem: 33408 +Test: [ 500/2573] eta: 0:02:57 time: 0.0797 data: 0.0015 max mem: 33408 +Test: [ 600/2573] eta: 0:02:46 time: 0.0801 data: 0.0015 max mem: 33408 +Test: [ 700/2573] eta: 0:02:37 time: 0.0815 data: 0.0016 max mem: 33408 +Test: [ 800/2573] eta: 0:02:28 time: 0.0841 data: 0.0014 max mem: 33408 +Test: [ 900/2573] eta: 0:02:20 time: 0.0805 data: 0.0017 max mem: 33408 +Test: [1000/2573] eta: 0:02:11 time: 0.0811 data: 0.0014 max mem: 33408 +Test: [1100/2573] eta: 0:02:02 time: 0.0817 data: 0.0014 max mem: 33408 +Test: [1200/2573] eta: 0:01:54 time: 0.0817 data: 0.0014 max mem: 33408 +Test: [1300/2573] eta: 0:01:45 time: 0.0815 data: 0.0014 max mem: 33408 +Test: [1400/2573] eta: 0:01:37 time: 0.0799 data: 0.0014 max mem: 33408 +Test: [1500/2573] eta: 0:01:28 time: 0.0803 data: 0.0014 max mem: 33408 +Test: [1600/2573] eta: 0:01:20 time: 0.0843 data: 0.0015 max mem: 33408 +Test: [1700/2573] eta: 0:01:12 time: 0.0797 data: 0.0013 max mem: 33408 +Test: [1800/2573] eta: 0:01:03 time: 0.0830 data: 0.0015 max mem: 33408 +Test: [1900/2573] eta: 0:00:55 time: 0.0811 data: 0.0014 max mem: 33408 +Test: [2000/2573] eta: 0:00:47 time: 0.0810 data: 0.0014 max mem: 33408 +Test: [2100/2573] eta: 0:00:38 time: 0.0828 data: 0.0014 max mem: 33408 +Test: [2200/2573] eta: 0:00:30 time: 0.0831 data: 0.0015 max mem: 33408 +Test: [2300/2573] eta: 0:00:22 time: 0.0826 data: 0.0015 max mem: 33408 +Test: [2400/2573] eta: 0:00:14 time: 0.0776 data: 0.0014 max mem: 33408 +Test: [2500/2573] eta: 0:00:06 time: 0.0819 data: 0.0014 max mem: 33408 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: Total time: 0:03:32 +Final results: +Mean IoU is 64.07 + + precision@0.5 = 72.55 + precision@0.6 = 67.20 + precision@0.7 = 59.97 + precision@0.8 = 48.77 + precision@0.9 = 23.57 + overall IoU = 61.68 + +Average object IoU 64.06851906035597 +Overall IoU 61.67729949951172 +Better epoch: 24 + +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [25] [ 0/2639] eta: 3:55:19 lr: 2.0681797002674545e-05 loss: 0.0310 (0.0310) time: 5.3503 data: 2.3922 max mem: 33408 +Epoch: [25] [ 10/2639] eta: 2:25:55 lr: 2.067709463494021e-05 loss: 0.0423 (0.0401) time: 3.3302 data: 0.2239 max mem: 33408 +Epoch: [25] [ 20/2639] eta: 2:19:49 lr: 2.0672392148379688e-05 loss: 0.0390 (0.0393) time: 3.0961 data: 0.0069 max mem: 33408 +Epoch: [25] [ 30/2639] eta: 2:16:20 lr: 2.0667689542959956e-05 loss: 0.0366 (0.0391) time: 3.0285 data: 0.0072 max mem: 33408 +Epoch: [25] [ 40/2639] eta: 2:14:03 lr: 2.066298681864795e-05 loss: 0.0318 (0.0405) time: 2.9808 data: 0.0076 max mem: 33408 +Epoch: [25] [ 50/2639] eta: 2:12:56 lr: 2.0658283975410604e-05 loss: 0.0370 (0.0405) time: 2.9958 data: 0.0077 max mem: 33408 +Epoch: [25] [ 60/2639] eta: 2:11:47 lr: 2.0653581013214815e-05 loss: 0.0332 (0.0390) time: 3.0071 data: 0.0078 max mem: 33408 +Epoch: [25] [ 70/2639] eta: 2:10:48 lr: 2.0648877932027488e-05 loss: 0.0339 (0.0400) time: 2.9900 data: 0.0077 max mem: 33408 +Epoch: [25] [ 80/2639] eta: 2:10:09 lr: 2.0644174731815487e-05 loss: 0.0373 (0.0402) time: 3.0079 data: 0.0079 max mem: 33408 +Epoch: [25] [ 90/2639] eta: 2:09:32 lr: 2.0639471412545684e-05 loss: 0.0349 (0.0398) time: 3.0289 data: 0.0079 max mem: 33408 +Epoch: [25] [ 100/2639] eta: 2:08:55 lr: 2.0634767974184902e-05 loss: 0.0339 (0.0399) time: 3.0265 data: 0.0078 max mem: 33408 +Epoch: [25] [ 110/2639] eta: 2:08:02 lr: 2.063006441669997e-05 loss: 0.0345 (0.0400) time: 2.9847 data: 0.0077 max mem: 33408 +Epoch: [25] [ 120/2639] eta: 2:07:19 lr: 2.0625360740057688e-05 loss: 0.0387 (0.0404) time: 2.9611 data: 0.0079 max mem: 33408 +Epoch: [25] [ 130/2639] eta: 2:06:50 lr: 2.0620656944224852e-05 loss: 0.0367 (0.0401) time: 3.0075 data: 0.0079 max mem: 33408 +Epoch: [25] [ 140/2639] eta: 2:06:24 lr: 2.061595302916822e-05 loss: 0.0359 (0.0399) time: 3.0485 data: 0.0079 max mem: 33408 +Epoch: [25] [ 150/2639] eta: 2:05:49 lr: 2.0611248994854547e-05 loss: 0.0375 (0.0400) time: 3.0325 data: 0.0081 max mem: 33408 +Epoch: [25] [ 160/2639] eta: 2:05:05 lr: 2.0606544841250562e-05 loss: 0.0390 (0.0402) time: 2.9757 data: 0.0082 max mem: 33408 +Epoch: [25] [ 170/2639] eta: 2:04:33 lr: 2.0601840568322993e-05 loss: 0.0372 (0.0403) time: 2.9823 data: 0.0081 max mem: 33408 +Epoch: [25] [ 180/2639] eta: 2:03:56 lr: 2.0597136176038524e-05 loss: 0.0366 (0.0406) time: 2.9978 data: 0.0082 max mem: 33408 +Epoch: [25] [ 190/2639] eta: 2:03:26 lr: 2.059243166436384e-05 loss: 0.0366 (0.0406) time: 3.0017 data: 0.0080 max mem: 33408 +Epoch: [25] [ 200/2639] eta: 2:02:54 lr: 2.0587727033265603e-05 loss: 0.0333 (0.0407) time: 3.0178 data: 0.0081 max mem: 33408 +Epoch: [25] [ 210/2639] eta: 2:02:19 lr: 2.058302228271046e-05 loss: 0.0394 (0.0408) time: 2.9955 data: 0.0081 max mem: 33408 +Epoch: [25] [ 220/2639] eta: 2:01:54 lr: 2.057831741266503e-05 loss: 0.0436 (0.0407) time: 3.0276 data: 0.0080 max mem: 33408 +Epoch: [25] [ 230/2639] eta: 2:01:25 lr: 2.0573612423095927e-05 loss: 0.0436 (0.0408) time: 3.0533 data: 0.0082 max mem: 33408 +Epoch: [25] [ 240/2639] eta: 2:00:57 lr: 2.0568907313969748e-05 loss: 0.0420 (0.0408) time: 3.0400 data: 0.0085 max mem: 33408 +Epoch: [25] [ 250/2639] eta: 2:00:24 lr: 2.0564202085253057e-05 loss: 0.0392 (0.0409) time: 3.0211 data: 0.0081 max mem: 33408 +Epoch: [25] [ 260/2639] eta: 1:59:47 lr: 2.0559496736912414e-05 loss: 0.0385 (0.0413) time: 2.9699 data: 0.0077 max mem: 33408 +Epoch: [25] [ 270/2639] eta: 1:59:14 lr: 2.0554791268914354e-05 loss: 0.0370 (0.0413) time: 2.9701 data: 0.0077 max mem: 33408 +Epoch: [25] [ 280/2639] eta: 1:58:44 lr: 2.05500856812254e-05 loss: 0.0359 (0.0412) time: 3.0070 data: 0.0078 max mem: 33408 +Epoch: [25] [ 290/2639] eta: 1:58:16 lr: 2.0545379973812045e-05 loss: 0.0374 (0.0413) time: 3.0344 data: 0.0080 max mem: 33408 +Epoch: [25] [ 300/2639] eta: 1:57:42 lr: 2.054067414664079e-05 loss: 0.0375 (0.0412) time: 3.0105 data: 0.0076 max mem: 33408 +Epoch: [25] [ 310/2639] eta: 1:57:06 lr: 2.053596819967808e-05 loss: 0.0374 (0.0411) time: 2.9576 data: 0.0078 max mem: 33408 +Epoch: [25] [ 320/2639] eta: 1:56:40 lr: 2.053126213289038e-05 loss: 0.0353 (0.0411) time: 3.0079 data: 0.0079 max mem: 33408 +Epoch: [25] [ 330/2639] eta: 1:56:13 lr: 2.052655594624411e-05 loss: 0.0353 (0.0410) time: 3.0695 data: 0.0079 max mem: 33408 +Epoch: [25] [ 340/2639] eta: 1:55:43 lr: 2.0521849639705683e-05 loss: 0.0398 (0.0412) time: 3.0429 data: 0.0079 max mem: 33408 +Epoch: [25] [ 350/2639] eta: 1:55:14 lr: 2.0517143213241498e-05 loss: 0.0371 (0.0410) time: 3.0330 data: 0.0076 max mem: 33408 +Epoch: [25] [ 360/2639] eta: 1:54:47 lr: 2.051243666681793e-05 loss: 0.0363 (0.0412) time: 3.0590 data: 0.0077 max mem: 33408 +Epoch: [25] [ 370/2639] eta: 1:54:19 lr: 2.0507730000401333e-05 loss: 0.0371 (0.0411) time: 3.0588 data: 0.0082 max mem: 33408 +Epoch: [25] [ 380/2639] eta: 1:53:49 lr: 2.050302321395805e-05 loss: 0.0353 (0.0410) time: 3.0435 data: 0.0085 max mem: 33408 +Epoch: [25] [ 390/2639] eta: 1:53:17 lr: 2.04983163074544e-05 loss: 0.0362 (0.0411) time: 3.0153 data: 0.0081 max mem: 33408 +Epoch: [25] [ 400/2639] eta: 1:52:43 lr: 2.0493609280856695e-05 loss: 0.0362 (0.0410) time: 2.9665 data: 0.0079 max mem: 33408 +Epoch: [25] [ 410/2639] eta: 1:52:09 lr: 2.048890213413121e-05 loss: 0.0365 (0.0410) time: 2.9496 data: 0.0082 max mem: 33408 +Epoch: [25] [ 420/2639] eta: 1:51:40 lr: 2.0484194867244224e-05 loss: 0.0377 (0.0409) time: 2.9982 data: 0.0080 max mem: 33408 +Epoch: [25] [ 430/2639] eta: 1:51:12 lr: 2.0479487480161975e-05 loss: 0.0364 (0.0410) time: 3.0496 data: 0.0076 max mem: 33408 +Epoch: [25] [ 440/2639] eta: 1:50:44 lr: 2.0474779972850708e-05 loss: 0.0362 (0.0411) time: 3.0635 data: 0.0077 max mem: 33408 +Epoch: [25] [ 450/2639] eta: 1:50:15 lr: 2.0470072345276622e-05 loss: 0.0353 (0.0411) time: 3.0536 data: 0.0081 max mem: 33408 +Epoch: [25] [ 460/2639] eta: 1:49:47 lr: 2.0465364597405924e-05 loss: 0.0358 (0.0411) time: 3.0568 data: 0.0081 max mem: 33408 +Epoch: [25] [ 470/2639] eta: 1:49:14 lr: 2.0460656729204784e-05 loss: 0.0381 (0.0411) time: 3.0237 data: 0.0077 max mem: 33408 +Epoch: [25] [ 480/2639] eta: 1:48:44 lr: 2.0455948740639368e-05 loss: 0.0324 (0.0409) time: 2.9995 data: 0.0077 max mem: 33408 +Epoch: [25] [ 490/2639] eta: 1:48:15 lr: 2.0451240631675814e-05 loss: 0.0357 (0.0409) time: 3.0321 data: 0.0081 max mem: 33408 +Epoch: [25] [ 500/2639] eta: 1:47:43 lr: 2.044653240228024e-05 loss: 0.0378 (0.0409) time: 3.0107 data: 0.0081 max mem: 33408 +Epoch: [25] [ 510/2639] eta: 1:47:15 lr: 2.044182405241876e-05 loss: 0.0411 (0.0411) time: 3.0275 data: 0.0079 max mem: 33408 +Epoch: [25] [ 520/2639] eta: 1:46:42 lr: 2.043711558205745e-05 loss: 0.0459 (0.0413) time: 3.0141 data: 0.0076 max mem: 33408 +Epoch: [25] [ 530/2639] eta: 1:46:10 lr: 2.0432406991162384e-05 loss: 0.0413 (0.0413) time: 2.9639 data: 0.0073 max mem: 33408 +Epoch: [25] [ 540/2639] eta: 1:45:37 lr: 2.042769827969961e-05 loss: 0.0381 (0.0414) time: 2.9700 data: 0.0075 max mem: 33408 +Epoch: [25] [ 550/2639] eta: 1:45:11 lr: 2.0422989447635165e-05 loss: 0.0358 (0.0413) time: 3.0489 data: 0.0076 max mem: 33408 +Epoch: [25] [ 560/2639] eta: 1:44:39 lr: 2.0418280494935052e-05 loss: 0.0358 (0.0413) time: 3.0502 data: 0.0074 max mem: 33408 +Epoch: [25] [ 570/2639] eta: 1:44:11 lr: 2.0413571421565277e-05 loss: 0.0328 (0.0413) time: 3.0193 data: 0.0076 max mem: 33408 +Epoch: [25] [ 580/2639] eta: 1:43:39 lr: 2.0408862227491806e-05 loss: 0.0335 (0.0416) time: 3.0198 data: 0.0076 max mem: 33408 +Epoch: [25] [ 590/2639] eta: 1:43:10 lr: 2.0404152912680612e-05 loss: 0.0432 (0.0417) time: 3.0170 data: 0.0076 max mem: 33408 +Epoch: [25] [ 600/2639] eta: 1:42:38 lr: 2.0399443477097617e-05 loss: 0.0449 (0.0417) time: 3.0199 data: 0.0076 max mem: 33408 +Epoch: [25] [ 610/2639] eta: 1:42:07 lr: 2.0394733920708757e-05 loss: 0.0394 (0.0418) time: 2.9765 data: 0.0078 max mem: 33408 +Epoch: [25] [ 620/2639] eta: 1:41:38 lr: 2.0390024243479928e-05 loss: 0.0355 (0.0418) time: 3.0164 data: 0.0080 max mem: 33408 +Epoch: [25] [ 630/2639] eta: 1:41:07 lr: 2.038531444537702e-05 loss: 0.0355 (0.0417) time: 3.0274 data: 0.0076 max mem: 33408 +Epoch: [25] [ 640/2639] eta: 1:40:36 lr: 2.0380604526365894e-05 loss: 0.0299 (0.0416) time: 2.9975 data: 0.0077 max mem: 33408 +Epoch: [25] [ 650/2639] eta: 1:40:04 lr: 2.0375894486412403e-05 loss: 0.0338 (0.0415) time: 2.9782 data: 0.0078 max mem: 33408 +Epoch: [25] [ 660/2639] eta: 1:39:32 lr: 2.037118432548237e-05 loss: 0.0386 (0.0416) time: 2.9657 data: 0.0082 max mem: 33408 +Epoch: [25] [ 670/2639] eta: 1:39:01 lr: 2.0366474043541618e-05 loss: 0.0345 (0.0415) time: 2.9827 data: 0.0082 max mem: 33408 +Epoch: [25] [ 680/2639] eta: 1:38:33 lr: 2.0361763640555928e-05 loss: 0.0345 (0.0415) time: 3.0452 data: 0.0080 max mem: 33408 +Epoch: [25] [ 690/2639] eta: 1:38:05 lr: 2.0357053116491086e-05 loss: 0.0384 (0.0415) time: 3.0933 data: 0.0080 max mem: 33408 +Epoch: [25] [ 700/2639] eta: 1:37:35 lr: 2.0352342471312835e-05 loss: 0.0348 (0.0415) time: 3.0505 data: 0.0078 max mem: 33408 +Epoch: [25] [ 710/2639] eta: 1:37:07 lr: 2.0347631704986924e-05 loss: 0.0348 (0.0414) time: 3.0610 data: 0.0081 max mem: 33408 +Epoch: [25] [ 720/2639] eta: 1:36:38 lr: 2.0342920817479062e-05 loss: 0.0338 (0.0414) time: 3.0916 data: 0.0079 max mem: 33408 +Epoch: [25] [ 730/2639] eta: 1:36:07 lr: 2.0338209808754955e-05 loss: 0.0341 (0.0413) time: 3.0329 data: 0.0075 max mem: 33408 +Epoch: [25] [ 740/2639] eta: 1:35:37 lr: 2.033349867878029e-05 loss: 0.0346 (0.0413) time: 3.0136 data: 0.0075 max mem: 33408 +Epoch: [25] [ 750/2639] eta: 1:35:06 lr: 2.0328787427520716e-05 loss: 0.0375 (0.0413) time: 3.0099 data: 0.0075 max mem: 33408 +Epoch: [25] [ 760/2639] eta: 1:34:34 lr: 2.0324076054941893e-05 loss: 0.0382 (0.0412) time: 2.9703 data: 0.0076 max mem: 33408 +Epoch: [25] [ 770/2639] eta: 1:34:05 lr: 2.0319364561009435e-05 loss: 0.0386 (0.0413) time: 3.0002 data: 0.0076 max mem: 33408 +Epoch: [25] [ 780/2639] eta: 1:33:35 lr: 2.0314652945688964e-05 loss: 0.0353 (0.0412) time: 3.0527 data: 0.0074 max mem: 33408 +Epoch: [25] [ 790/2639] eta: 1:33:05 lr: 2.0309941208946052e-05 loss: 0.0325 (0.0412) time: 3.0314 data: 0.0075 max mem: 33408 +Epoch: [25] [ 800/2639] eta: 1:32:36 lr: 2.0305229350746283e-05 loss: 0.0373 (0.0412) time: 3.0351 data: 0.0082 max mem: 33408 +Epoch: [25] [ 810/2639] eta: 1:32:06 lr: 2.0300517371055196e-05 loss: 0.0416 (0.0412) time: 3.0462 data: 0.0081 max mem: 33408 +Epoch: [25] [ 820/2639] eta: 1:31:36 lr: 2.0295805269838337e-05 loss: 0.0416 (0.0412) time: 3.0277 data: 0.0076 max mem: 33408 +Epoch: [25] [ 830/2639] eta: 1:31:06 lr: 2.0291093047061212e-05 loss: 0.0383 (0.0413) time: 3.0497 data: 0.0078 max mem: 33408 +Epoch: [25] [ 840/2639] eta: 1:30:36 lr: 2.0286380702689322e-05 loss: 0.0383 (0.0414) time: 3.0454 data: 0.0077 max mem: 33408 +Epoch: [25] [ 850/2639] eta: 1:30:07 lr: 2.028166823668814e-05 loss: 0.0396 (0.0414) time: 3.0473 data: 0.0074 max mem: 33408 +Epoch: [25] [ 860/2639] eta: 1:29:37 lr: 2.027695564902313e-05 loss: 0.0369 (0.0413) time: 3.0635 data: 0.0074 max mem: 33408 +Epoch: [25] [ 870/2639] eta: 1:29:06 lr: 2.0272242939659717e-05 loss: 0.0365 (0.0413) time: 3.0204 data: 0.0074 max mem: 33408 +Epoch: [25] [ 880/2639] eta: 1:28:37 lr: 2.026753010856334e-05 loss: 0.0365 (0.0414) time: 3.0162 data: 0.0074 max mem: 33408 +Epoch: [25] [ 890/2639] eta: 1:28:07 lr: 2.0262817155699386e-05 loss: 0.0392 (0.0414) time: 3.0413 data: 0.0074 max mem: 33408 +Epoch: [25] [ 900/2639] eta: 1:27:37 lr: 2.0258104081033253e-05 loss: 0.0409 (0.0414) time: 3.0394 data: 0.0073 max mem: 33408 +Epoch: [25] [ 910/2639] eta: 1:27:07 lr: 2.025339088453029e-05 loss: 0.0364 (0.0413) time: 3.0328 data: 0.0074 max mem: 33408 +Epoch: [25] [ 920/2639] eta: 1:26:36 lr: 2.0248677566155858e-05 loss: 0.0364 (0.0413) time: 3.0206 data: 0.0075 max mem: 33408 +Epoch: [25] [ 930/2639] eta: 1:26:06 lr: 2.024396412587527e-05 loss: 0.0365 (0.0413) time: 3.0138 data: 0.0077 max mem: 33408 +Epoch: [25] [ 940/2639] eta: 1:25:35 lr: 2.023925056365384e-05 loss: 0.0365 (0.0414) time: 3.0076 data: 0.0078 max mem: 33408 +Epoch: [25] [ 950/2639] eta: 1:25:05 lr: 2.023453687945686e-05 loss: 0.0409 (0.0414) time: 3.0079 data: 0.0078 max mem: 33408 +Epoch: [25] [ 960/2639] eta: 1:24:35 lr: 2.0229823073249597e-05 loss: 0.0409 (0.0414) time: 3.0193 data: 0.0077 max mem: 33408 +Epoch: [25] [ 970/2639] eta: 1:24:03 lr: 2.02251091449973e-05 loss: 0.0333 (0.0413) time: 2.9846 data: 0.0076 max mem: 33408 +Epoch: [25] [ 980/2639] eta: 1:23:33 lr: 2.0220395094665205e-05 loss: 0.0321 (0.0413) time: 2.9934 data: 0.0075 max mem: 33408 +Epoch: [25] [ 990/2639] eta: 1:23:05 lr: 2.0215680922218528e-05 loss: 0.0335 (0.0412) time: 3.0836 data: 0.0076 max mem: 33408 +Epoch: [25] [1000/2639] eta: 1:22:35 lr: 2.0210966627622456e-05 loss: 0.0359 (0.0412) time: 3.0871 data: 0.0078 max mem: 33408 +Epoch: [25] [1010/2639] eta: 1:22:04 lr: 2.0206252210842176e-05 loss: 0.0394 (0.0413) time: 3.0086 data: 0.0077 max mem: 33408 +Epoch: [25] [1020/2639] eta: 1:21:34 lr: 2.0201537671842828e-05 loss: 0.0382 (0.0412) time: 3.0068 data: 0.0077 max mem: 33408 +Epoch: [25] [1030/2639] eta: 1:21:04 lr: 2.019682301058957e-05 loss: 0.0355 (0.0412) time: 3.0461 data: 0.0077 max mem: 33408 +Epoch: [25] [1040/2639] eta: 1:20:35 lr: 2.0192108227047505e-05 loss: 0.0390 (0.0413) time: 3.0595 data: 0.0080 max mem: 33408 +Epoch: [25] [1050/2639] eta: 1:20:05 lr: 2.018739332118174e-05 loss: 0.0405 (0.0414) time: 3.0664 data: 0.0080 max mem: 33408 +Epoch: [25] [1060/2639] eta: 1:19:35 lr: 2.0182678292957352e-05 loss: 0.0407 (0.0414) time: 3.0440 data: 0.0078 max mem: 33408 +Epoch: [25] [1070/2639] eta: 1:19:04 lr: 2.017796314233941e-05 loss: 0.0364 (0.0413) time: 3.0149 data: 0.0077 max mem: 33408 +Epoch: [25] [1080/2639] eta: 1:18:33 lr: 2.0173247869292943e-05 loss: 0.0381 (0.0413) time: 2.9986 data: 0.0075 max mem: 33408 +Epoch: [25] [1090/2639] eta: 1:18:04 lr: 2.0168532473782993e-05 loss: 0.0365 (0.0413) time: 3.0348 data: 0.0076 max mem: 33408 +Epoch: [25] [1100/2639] eta: 1:17:33 lr: 2.0163816955774544e-05 loss: 0.0382 (0.0415) time: 3.0115 data: 0.0077 max mem: 33408 +Epoch: [25] [1110/2639] eta: 1:17:01 lr: 2.0159101315232602e-05 loss: 0.0407 (0.0414) time: 2.9341 data: 0.0078 max mem: 33408 +Epoch: [25] [1120/2639] eta: 1:16:30 lr: 2.0154385552122117e-05 loss: 0.0374 (0.0414) time: 2.9359 data: 0.0077 max mem: 33408 +Epoch: [25] [1130/2639] eta: 1:16:00 lr: 2.0149669666408043e-05 loss: 0.0372 (0.0414) time: 2.9871 data: 0.0076 max mem: 33408 +Epoch: [25] [1140/2639] eta: 1:15:29 lr: 2.014495365805531e-05 loss: 0.0421 (0.0415) time: 2.9986 data: 0.0077 max mem: 33408 +Epoch: [25] [1150/2639] eta: 1:14:58 lr: 2.0140237527028825e-05 loss: 0.0401 (0.0415) time: 2.9791 data: 0.0076 max mem: 33408 +Epoch: [25] [1160/2639] eta: 1:14:27 lr: 2.013552127329347e-05 loss: 0.0383 (0.0415) time: 2.9870 data: 0.0079 max mem: 33408 +Epoch: [25] [1170/2639] eta: 1:13:58 lr: 2.0130804896814132e-05 loss: 0.0362 (0.0414) time: 3.0162 data: 0.0080 max mem: 33408 +Epoch: [25] [1180/2639] eta: 1:13:27 lr: 2.0126088397555646e-05 loss: 0.0347 (0.0414) time: 3.0160 data: 0.0078 max mem: 33408 +Epoch: [25] [1190/2639] eta: 1:12:57 lr: 2.0121371775482855e-05 loss: 0.0347 (0.0414) time: 3.0204 data: 0.0077 max mem: 33408 +Epoch: [25] [1200/2639] eta: 1:12:27 lr: 2.0116655030560563e-05 loss: 0.0379 (0.0414) time: 3.0436 data: 0.0081 max mem: 33408 +Epoch: [25] [1210/2639] eta: 1:11:57 lr: 2.0111938162753573e-05 loss: 0.0383 (0.0414) time: 3.0400 data: 0.0080 max mem: 33408 +Epoch: [25] [1220/2639] eta: 1:11:27 lr: 2.0107221172026656e-05 loss: 0.0446 (0.0414) time: 3.0374 data: 0.0078 max mem: 33408 +Epoch: [25] [1230/2639] eta: 1:10:57 lr: 2.0102504058344558e-05 loss: 0.0416 (0.0414) time: 3.0418 data: 0.0079 max mem: 33408 +Epoch: [25] [1240/2639] eta: 1:10:27 lr: 2.0097786821672033e-05 loss: 0.0352 (0.0415) time: 3.0454 data: 0.0080 max mem: 33408 +Epoch: [25] [1250/2639] eta: 1:09:57 lr: 2.009306946197378e-05 loss: 0.0347 (0.0415) time: 3.0166 data: 0.0078 max mem: 33408 +Epoch: [25] [1260/2639] eta: 1:09:26 lr: 2.008835197921451e-05 loss: 0.0478 (0.0416) time: 3.0067 data: 0.0073 max mem: 33408 +Epoch: [25] [1270/2639] eta: 1:08:56 lr: 2.0083634373358887e-05 loss: 0.0481 (0.0416) time: 3.0283 data: 0.0074 max mem: 33408 +Epoch: [25] [1280/2639] eta: 1:08:27 lr: 2.0078916644371582e-05 loss: 0.0370 (0.0416) time: 3.0609 data: 0.0072 max mem: 33408 +Epoch: [25] [1290/2639] eta: 1:07:56 lr: 2.0074198792217223e-05 loss: 0.0333 (0.0416) time: 3.0325 data: 0.0072 max mem: 33408 +Epoch: [25] [1300/2639] eta: 1:07:26 lr: 2.0069480816860438e-05 loss: 0.0393 (0.0416) time: 3.0192 data: 0.0073 max mem: 33408 +Epoch: [25] [1310/2639] eta: 1:06:56 lr: 2.0064762718265824e-05 loss: 0.0394 (0.0416) time: 3.0522 data: 0.0074 max mem: 33408 +Epoch: [25] [1320/2639] eta: 1:06:26 lr: 2.0060044496397965e-05 loss: 0.0407 (0.0416) time: 3.0257 data: 0.0078 max mem: 33408 +Epoch: [25] [1330/2639] eta: 1:05:55 lr: 2.005532615122141e-05 loss: 0.0368 (0.0416) time: 3.0052 data: 0.0076 max mem: 33408 +Epoch: [25] [1340/2639] eta: 1:05:25 lr: 2.0050607682700722e-05 loss: 0.0360 (0.0416) time: 3.0222 data: 0.0075 max mem: 33408 +Epoch: [25] [1350/2639] eta: 1:04:55 lr: 2.0045889090800408e-05 loss: 0.0392 (0.0416) time: 3.0457 data: 0.0077 max mem: 33408 +Epoch: [25] [1360/2639] eta: 1:04:26 lr: 2.0041170375484974e-05 loss: 0.0423 (0.0416) time: 3.0508 data: 0.0078 max mem: 33408 +Epoch: [25] [1370/2639] eta: 1:03:56 lr: 2.0036451536718903e-05 loss: 0.0348 (0.0416) time: 3.0517 data: 0.0078 max mem: 33408 +Epoch: [25] [1380/2639] eta: 1:03:24 lr: 2.0031732574466667e-05 loss: 0.0336 (0.0416) time: 2.9866 data: 0.0078 max mem: 33408 +Epoch: [25] [1390/2639] eta: 1:02:54 lr: 2.0027013488692693e-05 loss: 0.0328 (0.0415) time: 2.9532 data: 0.0078 max mem: 33408 +Epoch: [25] [1400/2639] eta: 1:02:24 lr: 2.0022294279361427e-05 loss: 0.0341 (0.0415) time: 3.0233 data: 0.0075 max mem: 33408 +Epoch: [25] [1410/2639] eta: 1:01:54 lr: 2.0017574946437256e-05 loss: 0.0372 (0.0416) time: 3.0444 data: 0.0074 max mem: 33408 +Epoch: [25] [1420/2639] eta: 1:01:24 lr: 2.001285548988458e-05 loss: 0.0386 (0.0416) time: 3.0392 data: 0.0074 max mem: 33408 +Epoch: [25] [1430/2639] eta: 1:00:53 lr: 2.0008135909667752e-05 loss: 0.0353 (0.0415) time: 3.0122 data: 0.0073 max mem: 33408 +Epoch: [25] [1440/2639] eta: 1:00:23 lr: 2.000341620575113e-05 loss: 0.0348 (0.0415) time: 3.0050 data: 0.0075 max mem: 33408 +Epoch: [25] [1450/2639] eta: 0:59:53 lr: 1.9998696378099032e-05 loss: 0.0362 (0.0414) time: 3.0594 data: 0.0076 max mem: 33408 +Epoch: [25] [1460/2639] eta: 0:59:23 lr: 1.999397642667577e-05 loss: 0.0363 (0.0414) time: 3.0516 data: 0.0074 max mem: 33408 +Epoch: [25] [1470/2639] eta: 0:58:53 lr: 1.9989256351445633e-05 loss: 0.0398 (0.0414) time: 3.0491 data: 0.0076 max mem: 33408 +Epoch: [25] [1480/2639] eta: 0:58:24 lr: 1.998453615237289e-05 loss: 0.0335 (0.0414) time: 3.0853 data: 0.0079 max mem: 33408 +Epoch: [25] [1490/2639] eta: 0:57:53 lr: 1.997981582942178e-05 loss: 0.0335 (0.0414) time: 3.0348 data: 0.0078 max mem: 33408 +Epoch: [25] [1500/2639] eta: 0:57:22 lr: 1.997509538255654e-05 loss: 0.0387 (0.0415) time: 2.9599 data: 0.0078 max mem: 33408 +Epoch: [25] [1510/2639] eta: 0:56:52 lr: 1.9970374811741377e-05 loss: 0.0398 (0.0415) time: 2.9962 data: 0.0075 max mem: 33408 +Epoch: [25] [1520/2639] eta: 0:56:22 lr: 1.9965654116940476e-05 loss: 0.0349 (0.0415) time: 3.0126 data: 0.0071 max mem: 33408 +Epoch: [25] [1530/2639] eta: 0:55:52 lr: 1.9960933298118014e-05 loss: 0.0405 (0.0415) time: 3.0088 data: 0.0073 max mem: 33408 +Epoch: [25] [1540/2639] eta: 0:55:22 lr: 1.9956212355238134e-05 loss: 0.0405 (0.0415) time: 3.0468 data: 0.0075 max mem: 33408 +Epoch: [25] [1550/2639] eta: 0:54:51 lr: 1.995149128826497e-05 loss: 0.0438 (0.0415) time: 3.0336 data: 0.0078 max mem: 33408 +Epoch: [25] [1560/2639] eta: 0:54:22 lr: 1.9946770097162622e-05 loss: 0.0503 (0.0416) time: 3.0563 data: 0.0079 max mem: 33408 +Epoch: [25] [1570/2639] eta: 0:53:51 lr: 1.9942048781895197e-05 loss: 0.0428 (0.0417) time: 3.0534 data: 0.0076 max mem: 33408 +Epoch: [25] [1580/2639] eta: 0:53:21 lr: 1.993732734242675e-05 loss: 0.0428 (0.0417) time: 3.0165 data: 0.0074 max mem: 33408 +Epoch: [25] [1590/2639] eta: 0:52:51 lr: 1.9932605778721343e-05 loss: 0.0447 (0.0417) time: 3.0354 data: 0.0073 max mem: 33408 +Epoch: [25] [1600/2639] eta: 0:52:20 lr: 1.9927884090742994e-05 loss: 0.0380 (0.0418) time: 3.0083 data: 0.0073 max mem: 33408 +Epoch: [25] [1610/2639] eta: 0:51:50 lr: 1.9923162278455727e-05 loss: 0.0367 (0.0417) time: 2.9973 data: 0.0076 max mem: 33408 +Epoch: [25] [1620/2639] eta: 0:51:20 lr: 1.991844034182352e-05 loss: 0.0389 (0.0418) time: 3.0314 data: 0.0075 max mem: 33408 +Epoch: [25] [1630/2639] eta: 0:50:50 lr: 1.9913718280810353e-05 loss: 0.0395 (0.0417) time: 3.0301 data: 0.0075 max mem: 33408 +Epoch: [25] [1640/2639] eta: 0:50:19 lr: 1.9908996095380173e-05 loss: 0.0359 (0.0417) time: 3.0012 data: 0.0078 max mem: 33408 +Epoch: [25] [1650/2639] eta: 0:49:49 lr: 1.9904273785496916e-05 loss: 0.0359 (0.0417) time: 3.0245 data: 0.0079 max mem: 33408 +Epoch: [25] [1660/2639] eta: 0:49:19 lr: 1.9899551351124482e-05 loss: 0.0384 (0.0417) time: 3.0481 data: 0.0077 max mem: 33408 +Epoch: [25] [1670/2639] eta: 0:48:49 lr: 1.9894828792226776e-05 loss: 0.0401 (0.0417) time: 3.0029 data: 0.0077 max mem: 33408 +Epoch: [25] [1680/2639] eta: 0:48:19 lr: 1.9890106108767654e-05 loss: 0.0399 (0.0417) time: 3.0133 data: 0.0076 max mem: 33408 +Epoch: [25] [1690/2639] eta: 0:47:48 lr: 1.9885383300710982e-05 loss: 0.0383 (0.0418) time: 3.0481 data: 0.0072 max mem: 33408 +Epoch: [25] [1700/2639] eta: 0:47:18 lr: 1.9880660368020574e-05 loss: 0.0420 (0.0418) time: 3.0130 data: 0.0071 max mem: 33408 +Epoch: [25] [1710/2639] eta: 0:46:47 lr: 1.9875937310660252e-05 loss: 0.0352 (0.0417) time: 2.9746 data: 0.0072 max mem: 33408 +Epoch: [25] [1720/2639] eta: 0:46:17 lr: 1.9871214128593817e-05 loss: 0.0352 (0.0418) time: 2.9507 data: 0.0074 max mem: 33408 +Epoch: [25] [1730/2639] eta: 0:45:47 lr: 1.9866490821785012e-05 loss: 0.0421 (0.0418) time: 2.9801 data: 0.0080 max mem: 33408 +Epoch: [25] [1740/2639] eta: 0:45:16 lr: 1.9861767390197616e-05 loss: 0.0406 (0.0418) time: 3.0262 data: 0.0079 max mem: 33408 +Epoch: [25] [1750/2639] eta: 0:44:46 lr: 1.985704383379534e-05 loss: 0.0344 (0.0418) time: 3.0140 data: 0.0075 max mem: 33408 +Epoch: [25] [1760/2639] eta: 0:44:16 lr: 1.985232015254191e-05 loss: 0.0365 (0.0418) time: 3.0216 data: 0.0077 max mem: 33408 +Epoch: [25] [1770/2639] eta: 0:43:46 lr: 1.9847596346400997e-05 loss: 0.0420 (0.0418) time: 3.0699 data: 0.0076 max mem: 33408 +Epoch: [25] [1780/2639] eta: 0:43:15 lr: 1.984287241533629e-05 loss: 0.0371 (0.0418) time: 3.0261 data: 0.0072 max mem: 33408 +Epoch: [25] [1790/2639] eta: 0:42:45 lr: 1.9838148359311424e-05 loss: 0.0333 (0.0418) time: 2.9631 data: 0.0072 max mem: 33408 +Epoch: [25] [1800/2639] eta: 0:42:15 lr: 1.9833424178290042e-05 loss: 0.0332 (0.0418) time: 2.9999 data: 0.0074 max mem: 33408 +Epoch: [25] [1810/2639] eta: 0:41:45 lr: 1.982869987223574e-05 loss: 0.0408 (0.0418) time: 3.0331 data: 0.0078 max mem: 33408 +Epoch: [25] [1820/2639] eta: 0:41:15 lr: 1.982397544111212e-05 loss: 0.0409 (0.0418) time: 3.0599 data: 0.0080 max mem: 33408 +Epoch: [25] [1830/2639] eta: 0:40:44 lr: 1.9819250884882738e-05 loss: 0.0336 (0.0418) time: 3.0305 data: 0.0079 max mem: 33408 +Epoch: [25] [1840/2639] eta: 0:40:14 lr: 1.9814526203511154e-05 loss: 0.0325 (0.0417) time: 3.0117 data: 0.0077 max mem: 33408 +Epoch: [25] [1850/2639] eta: 0:39:44 lr: 1.980980139696089e-05 loss: 0.0380 (0.0417) time: 3.0434 data: 0.0077 max mem: 33408 +Epoch: [25] [1860/2639] eta: 0:39:14 lr: 1.9805076465195464e-05 loss: 0.0382 (0.0417) time: 3.0385 data: 0.0076 max mem: 33408 +Epoch: [25] [1870/2639] eta: 0:38:44 lr: 1.9800351408178344e-05 loss: 0.0381 (0.0417) time: 3.0637 data: 0.0074 max mem: 33408 +Epoch: [25] [1880/2639] eta: 0:38:14 lr: 1.979562622587302e-05 loss: 0.0353 (0.0418) time: 3.0617 data: 0.0073 max mem: 33408 +Epoch: [25] [1890/2639] eta: 0:37:44 lr: 1.9790900918242923e-05 loss: 0.0363 (0.0417) time: 3.0338 data: 0.0071 max mem: 33408 +Epoch: [25] [1900/2639] eta: 0:37:13 lr: 1.9786175485251486e-05 loss: 0.0320 (0.0417) time: 3.0180 data: 0.0074 max mem: 33408 +Epoch: [25] [1910/2639] eta: 0:36:43 lr: 1.9781449926862114e-05 loss: 0.0350 (0.0417) time: 3.0126 data: 0.0077 max mem: 33408 +Epoch: [25] [1920/2639] eta: 0:36:13 lr: 1.97767242430382e-05 loss: 0.0356 (0.0417) time: 3.0213 data: 0.0074 max mem: 33408 +Epoch: [25] [1930/2639] eta: 0:35:43 lr: 1.9771998433743093e-05 loss: 0.0379 (0.0417) time: 3.0073 data: 0.0073 max mem: 33408 +Epoch: [25] [1940/2639] eta: 0:35:12 lr: 1.976727249894016e-05 loss: 0.0373 (0.0416) time: 3.0433 data: 0.0074 max mem: 33408 +Epoch: [25] [1950/2639] eta: 0:34:42 lr: 1.9762546438592706e-05 loss: 0.0323 (0.0416) time: 3.0330 data: 0.0073 max mem: 33408 +Epoch: [25] [1960/2639] eta: 0:34:12 lr: 1.9757820252664043e-05 loss: 0.0383 (0.0416) time: 2.9867 data: 0.0073 max mem: 33408 +Epoch: [25] [1970/2639] eta: 0:33:41 lr: 1.975309394111746e-05 loss: 0.0440 (0.0416) time: 2.9971 data: 0.0077 max mem: 33408 +Epoch: [25] [1980/2639] eta: 0:33:11 lr: 1.9748367503916216e-05 loss: 0.0411 (0.0416) time: 3.0092 data: 0.0080 max mem: 33408 +Epoch: [25] [1990/2639] eta: 0:32:41 lr: 1.9743640941023556e-05 loss: 0.0359 (0.0416) time: 3.0430 data: 0.0077 max mem: 33408 +Epoch: [25] [2000/2639] eta: 0:32:11 lr: 1.973891425240269e-05 loss: 0.0300 (0.0415) time: 3.0718 data: 0.0073 max mem: 33408 +Epoch: [25] [2010/2639] eta: 0:31:41 lr: 1.973418743801684e-05 loss: 0.0363 (0.0416) time: 3.0673 data: 0.0074 max mem: 33408 +Epoch: [25] [2020/2639] eta: 0:31:11 lr: 1.972946049782917e-05 loss: 0.0374 (0.0415) time: 3.0581 data: 0.0075 max mem: 33408 +Epoch: [25] [2030/2639] eta: 0:30:41 lr: 1.972473343180285e-05 loss: 0.0408 (0.0415) time: 3.0281 data: 0.0073 max mem: 33408 +Epoch: [25] [2040/2639] eta: 0:30:10 lr: 1.9720006239901012e-05 loss: 0.0414 (0.0415) time: 2.9842 data: 0.0073 max mem: 33408 +Epoch: [25] [2050/2639] eta: 0:29:40 lr: 1.9715278922086786e-05 loss: 0.0415 (0.0416) time: 2.9851 data: 0.0079 max mem: 33408 +Epoch: [25] [2060/2639] eta: 0:29:10 lr: 1.971055147832326e-05 loss: 0.0400 (0.0416) time: 3.0417 data: 0.0083 max mem: 33408 +Epoch: [25] [2070/2639] eta: 0:28:40 lr: 1.970582390857352e-05 loss: 0.0387 (0.0416) time: 3.0742 data: 0.0080 max mem: 33408 +Epoch: [25] [2080/2639] eta: 0:28:10 lr: 1.9701096212800615e-05 loss: 0.0361 (0.0416) time: 3.0574 data: 0.0077 max mem: 33408 +Epoch: [25] [2090/2639] eta: 0:27:39 lr: 1.9696368390967595e-05 loss: 0.0290 (0.0416) time: 3.0248 data: 0.0076 max mem: 33408 +Epoch: [25] [2100/2639] eta: 0:27:09 lr: 1.969164044303746e-05 loss: 0.0304 (0.0415) time: 2.9898 data: 0.0077 max mem: 33408 +Epoch: [25] [2110/2639] eta: 0:26:39 lr: 1.968691236897322e-05 loss: 0.0355 (0.0415) time: 2.9860 data: 0.0080 max mem: 33408 +Epoch: [25] [2120/2639] eta: 0:26:08 lr: 1.9682184168737836e-05 loss: 0.0355 (0.0415) time: 2.9996 data: 0.0079 max mem: 33408 +Epoch: [25] [2130/2639] eta: 0:25:38 lr: 1.9677455842294275e-05 loss: 0.0370 (0.0415) time: 3.0341 data: 0.0074 max mem: 33408 +Epoch: [25] [2140/2639] eta: 0:25:08 lr: 1.9672727389605455e-05 loss: 0.0375 (0.0415) time: 3.0323 data: 0.0075 max mem: 33408 +Epoch: [25] [2150/2639] eta: 0:24:38 lr: 1.96679988106343e-05 loss: 0.0397 (0.0415) time: 2.9926 data: 0.0074 max mem: 33408 +Epoch: [25] [2160/2639] eta: 0:24:08 lr: 1.9663270105343702e-05 loss: 0.0396 (0.0415) time: 3.0320 data: 0.0071 max mem: 33408 +Epoch: [25] [2170/2639] eta: 0:23:37 lr: 1.9658541273696522e-05 loss: 0.0396 (0.0416) time: 3.0925 data: 0.0076 max mem: 33408 +Epoch: [25] [2180/2639] eta: 0:23:07 lr: 1.9653812315655614e-05 loss: 0.0471 (0.0416) time: 3.0964 data: 0.0079 max mem: 33408 +Epoch: [25] [2190/2639] eta: 0:22:37 lr: 1.9649083231183814e-05 loss: 0.0410 (0.0416) time: 3.0232 data: 0.0077 max mem: 33408 +Epoch: [25] [2200/2639] eta: 0:22:07 lr: 1.964435402024392e-05 loss: 0.0366 (0.0416) time: 3.0343 data: 0.0076 max mem: 33408 +Epoch: [25] [2210/2639] eta: 0:21:37 lr: 1.9639624682798717e-05 loss: 0.0378 (0.0416) time: 3.0389 data: 0.0074 max mem: 33408 +Epoch: [25] [2220/2639] eta: 0:21:06 lr: 1.9634895218810986e-05 loss: 0.0393 (0.0416) time: 2.9878 data: 0.0073 max mem: 33408 +Epoch: [25] [2230/2639] eta: 0:20:36 lr: 1.9630165628243458e-05 loss: 0.0389 (0.0416) time: 3.0196 data: 0.0073 max mem: 33408 +Epoch: [25] [2240/2639] eta: 0:20:06 lr: 1.9625435911058866e-05 loss: 0.0370 (0.0416) time: 3.0319 data: 0.0071 max mem: 33408 +Epoch: [25] [2250/2639] eta: 0:19:36 lr: 1.962070606721991e-05 loss: 0.0398 (0.0417) time: 3.0616 data: 0.0072 max mem: 33408 +Epoch: [25] [2260/2639] eta: 0:19:06 lr: 1.9615976096689273e-05 loss: 0.0399 (0.0417) time: 3.0921 data: 0.0072 max mem: 33408 +Epoch: [25] [2270/2639] eta: 0:18:35 lr: 1.961124599942961e-05 loss: 0.0399 (0.0417) time: 3.0524 data: 0.0075 max mem: 33408 +Epoch: [25] [2280/2639] eta: 0:18:05 lr: 1.9606515775403576e-05 loss: 0.0394 (0.0417) time: 2.9883 data: 0.0080 max mem: 33408 +Epoch: [25] [2290/2639] eta: 0:17:35 lr: 1.9601785424573772e-05 loss: 0.0374 (0.0417) time: 2.9460 data: 0.0077 max mem: 33408 +Epoch: [25] [2300/2639] eta: 0:17:04 lr: 1.9597054946902814e-05 loss: 0.0367 (0.0417) time: 2.9500 data: 0.0075 max mem: 33408 +Epoch: [25] [2310/2639] eta: 0:16:34 lr: 1.9592324342353263e-05 loss: 0.0395 (0.0417) time: 2.9763 data: 0.0078 max mem: 33408 +Epoch: [25] [2320/2639] eta: 0:16:04 lr: 1.958759361088769e-05 loss: 0.0385 (0.0417) time: 2.9815 data: 0.0082 max mem: 33408 +Epoch: [25] [2330/2639] eta: 0:15:34 lr: 1.9582862752468618e-05 loss: 0.0404 (0.0417) time: 3.0362 data: 0.0082 max mem: 33408 +Epoch: [25] [2340/2639] eta: 0:15:03 lr: 1.957813176705857e-05 loss: 0.0415 (0.0417) time: 3.0462 data: 0.0077 max mem: 33408 +Epoch: [25] [2350/2639] eta: 0:14:33 lr: 1.9573400654620026e-05 loss: 0.0391 (0.0417) time: 2.9994 data: 0.0078 max mem: 33408 +Epoch: [25] [2360/2639] eta: 0:14:03 lr: 1.956866941511548e-05 loss: 0.0361 (0.0417) time: 3.0473 data: 0.0085 max mem: 33408 +Epoch: [25] [2370/2639] eta: 0:13:33 lr: 1.956393804850736e-05 loss: 0.0391 (0.0417) time: 3.0387 data: 0.0084 max mem: 33408 +Epoch: [25] [2380/2639] eta: 0:13:03 lr: 1.9559206554758104e-05 loss: 0.0374 (0.0417) time: 3.0200 data: 0.0080 max mem: 33408 +Epoch: [25] [2390/2639] eta: 0:12:32 lr: 1.955447493383012e-05 loss: 0.0330 (0.0417) time: 3.0547 data: 0.0080 max mem: 33408 +Epoch: [25] [2400/2639] eta: 0:12:02 lr: 1.9549743185685798e-05 loss: 0.0394 (0.0417) time: 3.0313 data: 0.0077 max mem: 33408 +Epoch: [25] [2410/2639] eta: 0:11:32 lr: 1.9545011310287495e-05 loss: 0.0394 (0.0417) time: 3.0009 data: 0.0071 max mem: 33408 +Epoch: [25] [2420/2639] eta: 0:11:02 lr: 1.9540279307597568e-05 loss: 0.0348 (0.0417) time: 2.9860 data: 0.0072 max mem: 33408 +Epoch: [25] [2430/2639] eta: 0:10:31 lr: 1.9535547177578324e-05 loss: 0.0395 (0.0417) time: 3.0181 data: 0.0073 max mem: 33408 +Epoch: [25] [2440/2639] eta: 0:10:01 lr: 1.9530814920192082e-05 loss: 0.0400 (0.0417) time: 3.0698 data: 0.0072 max mem: 33408 +Epoch: [25] [2450/2639] eta: 0:09:31 lr: 1.9526082535401107e-05 loss: 0.0400 (0.0418) time: 3.0410 data: 0.0074 max mem: 33408 +Epoch: [25] [2460/2639] eta: 0:09:01 lr: 1.9521350023167665e-05 loss: 0.0385 (0.0418) time: 3.0232 data: 0.0075 max mem: 33408 +Epoch: [25] [2470/2639] eta: 0:08:30 lr: 1.9516617383453996e-05 loss: 0.0396 (0.0418) time: 3.0220 data: 0.0076 max mem: 33408 +Epoch: [25] [2480/2639] eta: 0:08:00 lr: 1.9511884616222312e-05 loss: 0.0375 (0.0418) time: 3.0150 data: 0.0077 max mem: 33408 +Epoch: [25] [2490/2639] eta: 0:07:30 lr: 1.9507151721434815e-05 loss: 0.0383 (0.0418) time: 3.0043 data: 0.0075 max mem: 33408 +Epoch: [25] [2500/2639] eta: 0:07:00 lr: 1.950241869905367e-05 loss: 0.0401 (0.0418) time: 3.0196 data: 0.0077 max mem: 33408 +Epoch: [25] [2510/2639] eta: 0:06:29 lr: 1.9497685549041038e-05 loss: 0.0401 (0.0418) time: 3.0295 data: 0.0077 max mem: 33408 +Epoch: [25] [2520/2639] eta: 0:05:59 lr: 1.9492952271359036e-05 loss: 0.0390 (0.0418) time: 3.0349 data: 0.0076 max mem: 33408 +Epoch: [25] [2530/2639] eta: 0:05:29 lr: 1.948821886596979e-05 loss: 0.0393 (0.0418) time: 3.0592 data: 0.0077 max mem: 33408 +Epoch: [25] [2540/2639] eta: 0:04:59 lr: 1.9483485332835372e-05 loss: 0.0395 (0.0418) time: 3.0486 data: 0.0078 max mem: 33408 +Epoch: [25] [2550/2639] eta: 0:04:29 lr: 1.947875167191786e-05 loss: 0.0416 (0.0418) time: 3.0579 data: 0.0079 max mem: 33408 +Epoch: [25] [2560/2639] eta: 0:03:58 lr: 1.9474017883179292e-05 loss: 0.0419 (0.0418) time: 3.0496 data: 0.0079 max mem: 33408 +Epoch: [25] [2570/2639] eta: 0:03:28 lr: 1.94692839665817e-05 loss: 0.0381 (0.0418) time: 3.0188 data: 0.0082 max mem: 33408 +Epoch: [25] [2580/2639] eta: 0:02:58 lr: 1.9464549922087073e-05 loss: 0.0387 (0.0419) time: 2.9884 data: 0.0086 max mem: 33408 +Epoch: [25] [2590/2639] eta: 0:02:28 lr: 1.9459815749657403e-05 loss: 0.0376 (0.0418) time: 3.0514 data: 0.0083 max mem: 33408 +Epoch: [25] [2600/2639] eta: 0:01:57 lr: 1.9455081449254638e-05 loss: 0.0354 (0.0419) time: 3.0525 data: 0.0079 max mem: 33408 +Epoch: [25] [2610/2639] eta: 0:01:27 lr: 1.9450347020840728e-05 loss: 0.0418 (0.0419) time: 3.0004 data: 0.0079 max mem: 33408 +Epoch: [25] [2620/2639] eta: 0:00:57 lr: 1.9445612464377575e-05 loss: 0.0390 (0.0419) time: 3.0398 data: 0.0080 max mem: 33408 +Epoch: [25] [2630/2639] eta: 0:00:27 lr: 1.9440877779827082e-05 loss: 0.0340 (0.0419) time: 3.0661 data: 0.0076 max mem: 33408 +Epoch: [25] Total time: 2:13:00 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 2:03:54 time: 2.8893 data: 2.7919 max mem: 33408 +Test: [ 100/2573] eta: 0:04:27 time: 0.0806 data: 0.0016 max mem: 33408 +Test: [ 200/2573] eta: 0:03:46 time: 0.0811 data: 0.0014 max mem: 33408 +Test: [ 300/2573] eta: 0:03:24 time: 0.0825 data: 0.0014 max mem: 33408 +Test: [ 400/2573] eta: 0:03:11 time: 0.0824 data: 0.0013 max mem: 33408 +Test: [ 500/2573] eta: 0:02:59 time: 0.0816 data: 0.0015 max mem: 33408 +Test: [ 600/2573] eta: 0:02:49 time: 0.0810 data: 0.0015 max mem: 33408 +Test: [ 700/2573] eta: 0:02:40 time: 0.0825 data: 0.0015 max mem: 33408 +Test: [ 800/2573] eta: 0:02:30 time: 0.0844 data: 0.0014 max mem: 33408 +Test: [ 900/2573] eta: 0:02:22 time: 0.0824 data: 0.0016 max mem: 33408 +Test: [1000/2573] eta: 0:02:13 time: 0.0826 data: 0.0015 max mem: 33408 +Test: [1100/2573] eta: 0:02:04 time: 0.0813 data: 0.0015 max mem: 33408 +Test: [1200/2573] eta: 0:01:55 time: 0.0820 data: 0.0014 max mem: 33408 +Test: [1300/2573] eta: 0:01:47 time: 0.0826 data: 0.0014 max mem: 33408 +Test: [1400/2573] eta: 0:01:38 time: 0.0809 data: 0.0015 max mem: 33408 +Test: [1500/2573] eta: 0:01:30 time: 0.0823 data: 0.0016 max mem: 33408 +Test: [1600/2573] eta: 0:01:21 time: 0.0865 data: 0.0014 max mem: 33408 +Test: [1700/2573] eta: 0:01:13 time: 0.0804 data: 0.0014 max mem: 33408 +Test: [1800/2573] eta: 0:01:04 time: 0.0839 data: 0.0014 max mem: 33408 +Test: [1900/2573] eta: 0:00:56 time: 0.0808 data: 0.0014 max mem: 33408 +Test: [2000/2573] eta: 0:00:47 time: 0.0812 data: 0.0014 max mem: 33408 +Test: [2100/2573] eta: 0:00:39 time: 0.0849 data: 0.0015 max mem: 33408 +Test: [2200/2573] eta: 0:00:31 time: 0.0840 data: 0.0015 max mem: 33408 +Test: [2300/2573] eta: 0:00:22 time: 0.0837 data: 0.0015 max mem: 33408 +Test: [2400/2573] eta: 0:00:14 time: 0.0797 data: 0.0014 max mem: 33408 +Test: [2500/2573] eta: 0:00:06 time: 0.0813 data: 0.0014 max mem: 33408 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: Total time: 0:03:35 +Final results: +Mean IoU is 63.78 + + precision@0.5 = 71.79 + precision@0.6 = 66.83 + precision@0.7 = 59.76 + precision@0.8 = 48.71 + precision@0.9 = 24.18 + overall IoU = 61.54 + +Average object IoU 63.78217491630069 +Overall IoU 61.540863037109375 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [26] [ 0/2639] eta: 3:55:34 lr: 1.9436616454185443e-05 loss: 0.0254 (0.0254) time: 5.3561 data: 2.2542 max mem: 33408 +Epoch: [26] [ 10/2639] eta: 2:22:13 lr: 1.9431881526163935e-05 loss: 0.0352 (0.0412) time: 3.2459 data: 0.2120 max mem: 33408 +Epoch: [26] [ 20/2639] eta: 2:17:13 lr: 1.9427146469944455e-05 loss: 0.0352 (0.0447) time: 3.0333 data: 0.0080 max mem: 33408 +Epoch: [26] [ 30/2639] eta: 2:15:22 lr: 1.9422411285488805e-05 loss: 0.0340 (0.0418) time: 3.0400 data: 0.0088 max mem: 33408 +Epoch: [26] [ 40/2639] eta: 2:14:04 lr: 1.941767597275878e-05 loss: 0.0301 (0.0395) time: 3.0440 data: 0.0089 max mem: 33408 +Epoch: [26] [ 50/2639] eta: 2:13:20 lr: 1.9412940531716138e-05 loss: 0.0316 (0.0390) time: 3.0551 data: 0.0087 max mem: 33408 +Epoch: [26] [ 60/2639] eta: 2:12:46 lr: 1.9408204962322638e-05 loss: 0.0316 (0.0388) time: 3.0768 data: 0.0082 max mem: 33408 +Epoch: [26] [ 70/2639] eta: 2:11:53 lr: 1.9403469264539984e-05 loss: 0.0372 (0.0402) time: 3.0556 data: 0.0079 max mem: 33408 +Epoch: [26] [ 80/2639] eta: 2:10:49 lr: 1.9398733438329882e-05 loss: 0.0390 (0.0395) time: 3.0010 data: 0.0081 max mem: 33408 +Epoch: [26] [ 90/2639] eta: 2:09:59 lr: 1.9393997483654023e-05 loss: 0.0339 (0.0393) time: 2.9860 data: 0.0079 max mem: 33408 +Epoch: [26] [ 100/2639] eta: 2:09:33 lr: 1.9389261400474044e-05 loss: 0.0348 (0.0389) time: 3.0387 data: 0.0077 max mem: 33408 +Epoch: [26] [ 110/2639] eta: 2:08:39 lr: 1.9384525188751594e-05 loss: 0.0397 (0.0388) time: 3.0185 data: 0.0078 max mem: 33408 +Epoch: [26] [ 120/2639] eta: 2:08:00 lr: 1.937978884844828e-05 loss: 0.0359 (0.0385) time: 2.9844 data: 0.0083 max mem: 33408 +Epoch: [26] [ 130/2639] eta: 2:07:10 lr: 1.9375052379525698e-05 loss: 0.0359 (0.0386) time: 2.9806 data: 0.0083 max mem: 33408 +Epoch: [26] [ 140/2639] eta: 2:06:37 lr: 1.937031578194541e-05 loss: 0.0341 (0.0381) time: 2.9889 data: 0.0080 max mem: 33408 +Epoch: [26] [ 150/2639] eta: 2:06:03 lr: 1.936557905566897e-05 loss: 0.0344 (0.0380) time: 3.0201 data: 0.0077 max mem: 33408 +Epoch: [26] [ 160/2639] eta: 2:05:32 lr: 1.9360842200657898e-05 loss: 0.0360 (0.0383) time: 3.0269 data: 0.0078 max mem: 33408 +Epoch: [26] [ 170/2639] eta: 2:05:10 lr: 1.9356105216873702e-05 loss: 0.0348 (0.0384) time: 3.0665 data: 0.0082 max mem: 33408 +Epoch: [26] [ 180/2639] eta: 2:04:37 lr: 1.935136810427785e-05 loss: 0.0313 (0.0382) time: 3.0591 data: 0.0080 max mem: 33408 +Epoch: [26] [ 190/2639] eta: 2:04:09 lr: 1.9346630862831827e-05 loss: 0.0366 (0.0381) time: 3.0428 data: 0.0077 max mem: 33408 +Epoch: [26] [ 200/2639] eta: 2:03:46 lr: 1.9341893492497047e-05 loss: 0.0367 (0.0383) time: 3.0818 data: 0.0076 max mem: 33408 +Epoch: [26] [ 210/2639] eta: 2:03:21 lr: 1.933715599323494e-05 loss: 0.0375 (0.0382) time: 3.0977 data: 0.0078 max mem: 33408 +Epoch: [26] [ 220/2639] eta: 2:02:54 lr: 1.9332418365006884e-05 loss: 0.0368 (0.0382) time: 3.0830 data: 0.0078 max mem: 33408 +Epoch: [26] [ 230/2639] eta: 2:02:13 lr: 1.9327680607774268e-05 loss: 0.0368 (0.0387) time: 3.0111 data: 0.0079 max mem: 33408 +Epoch: [26] [ 240/2639] eta: 2:01:37 lr: 1.932294272149843e-05 loss: 0.0387 (0.0391) time: 2.9691 data: 0.0079 max mem: 33408 +Epoch: [26] [ 250/2639] eta: 2:01:08 lr: 1.9318204706140697e-05 loss: 0.0388 (0.0391) time: 3.0216 data: 0.0075 max mem: 33408 +Epoch: [26] [ 260/2639] eta: 2:00:42 lr: 1.9313466561662375e-05 loss: 0.0353 (0.0390) time: 3.0725 data: 0.0077 max mem: 33408 +Epoch: [26] [ 270/2639] eta: 2:00:16 lr: 1.9308728288024748e-05 loss: 0.0337 (0.0392) time: 3.0941 data: 0.0080 max mem: 33408 +Epoch: [26] [ 280/2639] eta: 1:59:39 lr: 1.9303989885189078e-05 loss: 0.0402 (0.0393) time: 3.0325 data: 0.0081 max mem: 33408 +Epoch: [26] [ 290/2639] eta: 1:59:13 lr: 1.92992513531166e-05 loss: 0.0372 (0.0392) time: 3.0369 data: 0.0078 max mem: 33408 +Epoch: [26] [ 300/2639] eta: 1:58:45 lr: 1.929451269176853e-05 loss: 0.0329 (0.0391) time: 3.0879 data: 0.0075 max mem: 33408 +Epoch: [26] [ 310/2639] eta: 1:58:15 lr: 1.928977390110607e-05 loss: 0.0331 (0.0389) time: 3.0650 data: 0.0079 max mem: 33408 +Epoch: [26] [ 320/2639] eta: 1:57:44 lr: 1.9285034981090377e-05 loss: 0.0348 (0.0388) time: 3.0496 data: 0.0081 max mem: 33408 +Epoch: [26] [ 330/2639] eta: 1:57:11 lr: 1.9280295931682607e-05 loss: 0.0330 (0.0388) time: 3.0200 data: 0.0080 max mem: 33408 +Epoch: [26] [ 340/2639] eta: 1:56:39 lr: 1.9275556752843895e-05 loss: 0.0336 (0.0388) time: 3.0120 data: 0.0078 max mem: 33408 +Epoch: [26] [ 350/2639] eta: 1:56:08 lr: 1.9270817444535337e-05 loss: 0.0336 (0.0389) time: 3.0299 data: 0.0076 max mem: 33408 +Epoch: [26] [ 360/2639] eta: 1:55:35 lr: 1.926607800671802e-05 loss: 0.0314 (0.0389) time: 3.0204 data: 0.0078 max mem: 33408 +Epoch: [26] [ 370/2639] eta: 1:55:05 lr: 1.9261338439352993e-05 loss: 0.0371 (0.0391) time: 3.0322 data: 0.0080 max mem: 33408 +Epoch: [26] [ 380/2639] eta: 1:54:32 lr: 1.9256598742401314e-05 loss: 0.0401 (0.0391) time: 3.0292 data: 0.0078 max mem: 33408 +Epoch: [26] [ 390/2639] eta: 1:54:04 lr: 1.925185891582398e-05 loss: 0.0356 (0.0390) time: 3.0370 data: 0.0080 max mem: 33408 +Epoch: [26] [ 400/2639] eta: 1:53:34 lr: 1.9247118959581993e-05 loss: 0.0367 (0.0392) time: 3.0654 data: 0.0080 max mem: 33408 +Epoch: [26] [ 410/2639] eta: 1:53:03 lr: 1.9242378873636318e-05 loss: 0.0367 (0.0394) time: 3.0441 data: 0.0076 max mem: 33408 +Epoch: [26] [ 420/2639] eta: 1:52:28 lr: 1.9237638657947913e-05 loss: 0.0350 (0.0394) time: 2.9970 data: 0.0077 max mem: 33408 +Epoch: [26] [ 430/2639] eta: 1:51:58 lr: 1.9232898312477686e-05 loss: 0.0350 (0.0394) time: 3.0024 data: 0.0078 max mem: 33408 +Epoch: [26] [ 440/2639] eta: 1:51:26 lr: 1.9228157837186564e-05 loss: 0.0349 (0.0395) time: 3.0254 data: 0.0076 max mem: 33408 +Epoch: [26] [ 450/2639] eta: 1:50:56 lr: 1.9223417232035405e-05 loss: 0.0412 (0.0395) time: 3.0287 data: 0.0075 max mem: 33408 +Epoch: [26] [ 460/2639] eta: 1:50:26 lr: 1.9218676496985086e-05 loss: 0.0411 (0.0397) time: 3.0482 data: 0.0075 max mem: 33408 +Epoch: [26] [ 470/2639] eta: 1:49:53 lr: 1.9213935631996427e-05 loss: 0.0411 (0.0398) time: 3.0171 data: 0.0083 max mem: 33408 +Epoch: [26] [ 480/2639] eta: 1:49:25 lr: 1.9209194637030253e-05 loss: 0.0423 (0.0399) time: 3.0382 data: 0.0082 max mem: 33408 +Epoch: [26] [ 490/2639] eta: 1:48:54 lr: 1.9204453512047348e-05 loss: 0.0400 (0.0399) time: 3.0640 data: 0.0075 max mem: 33408 +Epoch: [26] [ 500/2639] eta: 1:48:20 lr: 1.9199712257008483e-05 loss: 0.0317 (0.0397) time: 2.9991 data: 0.0074 max mem: 33408 +Epoch: [26] [ 510/2639] eta: 1:47:48 lr: 1.9194970871874397e-05 loss: 0.0297 (0.0396) time: 2.9801 data: 0.0077 max mem: 33408 +Epoch: [26] [ 520/2639] eta: 1:47:16 lr: 1.919022935660582e-05 loss: 0.0306 (0.0399) time: 2.9913 data: 0.0081 max mem: 33408 +Epoch: [26] [ 530/2639] eta: 1:46:45 lr: 1.918548771116345e-05 loss: 0.0321 (0.0400) time: 3.0040 data: 0.0078 max mem: 33408 +Epoch: [26] [ 540/2639] eta: 1:46:13 lr: 1.918074593550797e-05 loss: 0.0328 (0.0399) time: 3.0136 data: 0.0078 max mem: 33408 +Epoch: [26] [ 550/2639] eta: 1:45:42 lr: 1.917600402960002e-05 loss: 0.0356 (0.0398) time: 3.0143 data: 0.0076 max mem: 33408 +Epoch: [26] [ 560/2639] eta: 1:45:14 lr: 1.9171261993400248e-05 loss: 0.0359 (0.0400) time: 3.0653 data: 0.0075 max mem: 33408 +Epoch: [26] [ 570/2639] eta: 1:44:43 lr: 1.916651982686925e-05 loss: 0.0359 (0.0399) time: 3.0583 data: 0.0078 max mem: 33408 +Epoch: [26] [ 580/2639] eta: 1:44:14 lr: 1.9161777529967618e-05 loss: 0.0384 (0.0399) time: 3.0411 data: 0.0082 max mem: 33408 +Epoch: [26] [ 590/2639] eta: 1:43:44 lr: 1.9157035102655923e-05 loss: 0.0359 (0.0399) time: 3.0603 data: 0.0083 max mem: 33408 +Epoch: [26] [ 600/2639] eta: 1:43:14 lr: 1.9152292544894697e-05 loss: 0.0304 (0.0398) time: 3.0529 data: 0.0082 max mem: 33408 +Epoch: [26] [ 610/2639] eta: 1:42:42 lr: 1.914754985664446e-05 loss: 0.0296 (0.0398) time: 3.0184 data: 0.0079 max mem: 33408 +Epoch: [26] [ 620/2639] eta: 1:42:13 lr: 1.9142807037865708e-05 loss: 0.0296 (0.0397) time: 3.0292 data: 0.0079 max mem: 33408 +Epoch: [26] [ 630/2639] eta: 1:41:44 lr: 1.913806408851892e-05 loss: 0.0296 (0.0395) time: 3.0724 data: 0.0078 max mem: 33408 +Epoch: [26] [ 640/2639] eta: 1:41:13 lr: 1.9133321008564532e-05 loss: 0.0298 (0.0395) time: 3.0519 data: 0.0075 max mem: 33408 +Epoch: [26] [ 650/2639] eta: 1:40:41 lr: 1.9128577797962986e-05 loss: 0.0331 (0.0395) time: 3.0021 data: 0.0075 max mem: 33408 +Epoch: [26] [ 660/2639] eta: 1:40:10 lr: 1.912383445667467e-05 loss: 0.0361 (0.0394) time: 2.9928 data: 0.0078 max mem: 33408 +Epoch: [26] [ 670/2639] eta: 1:39:39 lr: 1.9119090984659983e-05 loss: 0.0385 (0.0396) time: 3.0267 data: 0.0080 max mem: 33408 +Epoch: [26] [ 680/2639] eta: 1:39:09 lr: 1.9114347381879268e-05 loss: 0.0375 (0.0395) time: 3.0413 data: 0.0079 max mem: 33408 +Epoch: [26] [ 690/2639] eta: 1:38:39 lr: 1.9109603648292867e-05 loss: 0.0312 (0.0394) time: 3.0547 data: 0.0081 max mem: 33408 +Epoch: [26] [ 700/2639] eta: 1:38:09 lr: 1.9104859783861086e-05 loss: 0.0300 (0.0394) time: 3.0519 data: 0.0080 max mem: 33408 +Epoch: [26] [ 710/2639] eta: 1:37:38 lr: 1.910011578854423e-05 loss: 0.0356 (0.0395) time: 3.0232 data: 0.0076 max mem: 33408 +Epoch: [26] [ 720/2639] eta: 1:37:07 lr: 1.9095371662302543e-05 loss: 0.0468 (0.0395) time: 3.0065 data: 0.0076 max mem: 33408 +Epoch: [26] [ 730/2639] eta: 1:36:35 lr: 1.9090627405096286e-05 loss: 0.0421 (0.0395) time: 2.9970 data: 0.0078 max mem: 33408 +Epoch: [26] [ 740/2639] eta: 1:36:05 lr: 1.908588301688567e-05 loss: 0.0390 (0.0396) time: 3.0250 data: 0.0077 max mem: 33408 +Epoch: [26] [ 750/2639] eta: 1:35:36 lr: 1.9081138497630898e-05 loss: 0.0407 (0.0397) time: 3.0622 data: 0.0077 max mem: 33408 +Epoch: [26] [ 760/2639] eta: 1:35:04 lr: 1.9076393847292136e-05 loss: 0.0407 (0.0398) time: 3.0305 data: 0.0080 max mem: 33408 +Epoch: [26] [ 770/2639] eta: 1:34:32 lr: 1.907164906582954e-05 loss: 0.0356 (0.0398) time: 2.9843 data: 0.0081 max mem: 33408 +Epoch: [26] [ 780/2639] eta: 1:34:01 lr: 1.906690415320324e-05 loss: 0.0361 (0.0399) time: 2.9800 data: 0.0084 max mem: 33408 +Epoch: [26] [ 790/2639] eta: 1:33:31 lr: 1.9062159109373336e-05 loss: 0.0367 (0.0399) time: 3.0219 data: 0.0083 max mem: 33408 +Epoch: [26] [ 800/2639] eta: 1:33:02 lr: 1.9057413934299906e-05 loss: 0.0354 (0.0398) time: 3.0774 data: 0.0079 max mem: 33408 +Epoch: [26] [ 810/2639] eta: 1:32:31 lr: 1.905266862794302e-05 loss: 0.0362 (0.0399) time: 3.0571 data: 0.0082 max mem: 33408 +Epoch: [26] [ 820/2639] eta: 1:32:01 lr: 1.90479231902627e-05 loss: 0.0373 (0.0399) time: 3.0153 data: 0.0084 max mem: 33408 +Epoch: [26] [ 830/2639] eta: 1:31:31 lr: 1.9043177621218962e-05 loss: 0.0373 (0.0399) time: 3.0364 data: 0.0080 max mem: 33408 +Epoch: [26] [ 840/2639] eta: 1:31:01 lr: 1.9038431920771802e-05 loss: 0.0377 (0.0400) time: 3.0587 data: 0.0078 max mem: 33408 +Epoch: [26] [ 850/2639] eta: 1:30:31 lr: 1.9033686088881175e-05 loss: 0.0365 (0.0399) time: 3.0532 data: 0.0080 max mem: 33408 +Epoch: [26] [ 860/2639] eta: 1:30:01 lr: 1.902894012550703e-05 loss: 0.0365 (0.0399) time: 3.0472 data: 0.0084 max mem: 33408 +Epoch: [26] [ 870/2639] eta: 1:29:31 lr: 1.9024194030609277e-05 loss: 0.0414 (0.0399) time: 3.0603 data: 0.0082 max mem: 33408 +Epoch: [26] [ 880/2639] eta: 1:28:58 lr: 1.9019447804147823e-05 loss: 0.0371 (0.0399) time: 2.9801 data: 0.0075 max mem: 33408 +Epoch: [26] [ 890/2639] eta: 1:28:26 lr: 1.9014701446082528e-05 loss: 0.0382 (0.0400) time: 2.9272 data: 0.0071 max mem: 33408 +Epoch: [26] [ 900/2639] eta: 1:27:55 lr: 1.9009954956373252e-05 loss: 0.0406 (0.0400) time: 2.9845 data: 0.0074 max mem: 33408 +Epoch: [26] [ 910/2639] eta: 1:27:25 lr: 1.9005208334979807e-05 loss: 0.0444 (0.0401) time: 3.0373 data: 0.0077 max mem: 33408 +Epoch: [26] [ 920/2639] eta: 1:26:56 lr: 1.900046158186201e-05 loss: 0.0384 (0.0400) time: 3.0821 data: 0.0076 max mem: 33408 +Epoch: [26] [ 930/2639] eta: 1:26:25 lr: 1.8995714696979624e-05 loss: 0.0312 (0.0399) time: 3.0284 data: 0.0076 max mem: 33408 +Epoch: [26] [ 940/2639] eta: 1:25:53 lr: 1.8990967680292416e-05 loss: 0.0312 (0.0398) time: 2.9607 data: 0.0077 max mem: 33408 +Epoch: [26] [ 950/2639] eta: 1:25:22 lr: 1.8986220531760108e-05 loss: 0.0375 (0.0399) time: 2.9735 data: 0.0079 max mem: 33408 +Epoch: [26] [ 960/2639] eta: 1:24:52 lr: 1.8981473251342415e-05 loss: 0.0397 (0.0399) time: 3.0325 data: 0.0081 max mem: 33408 +Epoch: [26] [ 970/2639] eta: 1:24:21 lr: 1.8976725838999015e-05 loss: 0.0353 (0.0399) time: 3.0303 data: 0.0079 max mem: 33408 +Epoch: [26] [ 980/2639] eta: 1:23:51 lr: 1.897197829468958e-05 loss: 0.0339 (0.0398) time: 3.0189 data: 0.0080 max mem: 33408 +Epoch: [26] [ 990/2639] eta: 1:23:21 lr: 1.896723061837373e-05 loss: 0.0339 (0.0398) time: 3.0556 data: 0.0082 max mem: 33408 +Epoch: [26] [1000/2639] eta: 1:22:51 lr: 1.8962482810011096e-05 loss: 0.0338 (0.0398) time: 3.0493 data: 0.0078 max mem: 33408 +Epoch: [26] [1010/2639] eta: 1:22:20 lr: 1.895773486956125e-05 loss: 0.0329 (0.0397) time: 3.0216 data: 0.0075 max mem: 33408 +Epoch: [26] [1020/2639] eta: 1:21:49 lr: 1.895298679698378e-05 loss: 0.0351 (0.0397) time: 2.9997 data: 0.0079 max mem: 33408 +Epoch: [26] [1030/2639] eta: 1:21:19 lr: 1.894823859223821e-05 loss: 0.0380 (0.0398) time: 3.0268 data: 0.0082 max mem: 33408 +Epoch: [26] [1040/2639] eta: 1:20:49 lr: 1.894349025528407e-05 loss: 0.0397 (0.0398) time: 3.0534 data: 0.0080 max mem: 33408 +Epoch: [26] [1050/2639] eta: 1:20:20 lr: 1.893874178608085e-05 loss: 0.0353 (0.0398) time: 3.0639 data: 0.0076 max mem: 33408 +Epoch: [26] [1060/2639] eta: 1:19:50 lr: 1.8933993184588018e-05 loss: 0.0360 (0.0398) time: 3.0925 data: 0.0078 max mem: 33408 +Epoch: [26] [1070/2639] eta: 1:19:20 lr: 1.892924445076504e-05 loss: 0.0349 (0.0397) time: 3.0586 data: 0.0081 max mem: 33408 +Epoch: [26] [1080/2639] eta: 1:18:49 lr: 1.892449558457132e-05 loss: 0.0299 (0.0396) time: 3.0120 data: 0.0079 max mem: 33408 +Epoch: [26] [1090/2639] eta: 1:18:18 lr: 1.8919746585966273e-05 loss: 0.0318 (0.0396) time: 3.0130 data: 0.0080 max mem: 33408 +Epoch: [26] [1100/2639] eta: 1:17:48 lr: 1.8914997454909262e-05 loss: 0.0360 (0.0397) time: 3.0239 data: 0.0081 max mem: 33408 +Epoch: [26] [1110/2639] eta: 1:17:18 lr: 1.8910248191359656e-05 loss: 0.0346 (0.0397) time: 3.0340 data: 0.0079 max mem: 33408 +Epoch: [26] [1120/2639] eta: 1:16:47 lr: 1.890549879527677e-05 loss: 0.0345 (0.0397) time: 3.0133 data: 0.0077 max mem: 33408 +Epoch: [26] [1130/2639] eta: 1:16:16 lr: 1.8900749266619918e-05 loss: 0.0352 (0.0396) time: 2.9929 data: 0.0076 max mem: 33408 +Epoch: [26] [1140/2639] eta: 1:15:46 lr: 1.8895999605348376e-05 loss: 0.0372 (0.0396) time: 3.0310 data: 0.0075 max mem: 33408 +Epoch: [26] [1150/2639] eta: 1:15:16 lr: 1.889124981142141e-05 loss: 0.0372 (0.0396) time: 3.0588 data: 0.0079 max mem: 33408 +Epoch: [26] [1160/2639] eta: 1:14:46 lr: 1.888649988479824e-05 loss: 0.0337 (0.0396) time: 3.0548 data: 0.0079 max mem: 33408 +Epoch: [26] [1170/2639] eta: 1:14:16 lr: 1.8881749825438093e-05 loss: 0.0337 (0.0396) time: 3.0445 data: 0.0077 max mem: 33408 +Epoch: [26] [1180/2639] eta: 1:13:45 lr: 1.8876999633300134e-05 loss: 0.0361 (0.0396) time: 3.0314 data: 0.0077 max mem: 33408 +Epoch: [26] [1190/2639] eta: 1:13:16 lr: 1.8872249308343546e-05 loss: 0.0362 (0.0396) time: 3.0611 data: 0.0079 max mem: 33408 +Epoch: [26] [1200/2639] eta: 1:12:46 lr: 1.8867498850527453e-05 loss: 0.0362 (0.0396) time: 3.0863 data: 0.0079 max mem: 33408 +Epoch: [26] [1210/2639] eta: 1:12:16 lr: 1.886274825981097e-05 loss: 0.0362 (0.0396) time: 3.0878 data: 0.0076 max mem: 33408 +Epoch: [26] [1220/2639] eta: 1:11:46 lr: 1.8857997536153194e-05 loss: 0.0373 (0.0397) time: 3.0556 data: 0.0076 max mem: 33408 +Epoch: [26] [1230/2639] eta: 1:11:15 lr: 1.8853246679513188e-05 loss: 0.0373 (0.0397) time: 3.0123 data: 0.0076 max mem: 33408 +Epoch: [26] [1240/2639] eta: 1:10:44 lr: 1.884849568984999e-05 loss: 0.0391 (0.0397) time: 2.9956 data: 0.0079 max mem: 33408 +Epoch: [26] [1250/2639] eta: 1:10:14 lr: 1.8843744567122623e-05 loss: 0.0366 (0.0398) time: 3.0268 data: 0.0079 max mem: 33408 +Epoch: [26] [1260/2639] eta: 1:09:44 lr: 1.883899331129007e-05 loss: 0.0351 (0.0398) time: 3.0812 data: 0.0075 max mem: 33408 +Epoch: [26] [1270/2639] eta: 1:09:14 lr: 1.8834241922311315e-05 loss: 0.0355 (0.0398) time: 3.0725 data: 0.0078 max mem: 33408 +Epoch: [26] [1280/2639] eta: 1:08:44 lr: 1.8829490400145296e-05 loss: 0.0367 (0.0398) time: 3.0286 data: 0.0080 max mem: 33408 +Epoch: [26] [1290/2639] eta: 1:08:13 lr: 1.8824738744750934e-05 loss: 0.0354 (0.0398) time: 3.0187 data: 0.0077 max mem: 33408 +Epoch: [26] [1300/2639] eta: 1:07:43 lr: 1.8819986956087122e-05 loss: 0.0357 (0.0398) time: 3.0495 data: 0.0076 max mem: 33408 +Epoch: [26] [1310/2639] eta: 1:07:12 lr: 1.8815235034112736e-05 loss: 0.0371 (0.0398) time: 3.0101 data: 0.0074 max mem: 33408 +Epoch: [26] [1320/2639] eta: 1:06:41 lr: 1.881048297878663e-05 loss: 0.0371 (0.0399) time: 2.9749 data: 0.0076 max mem: 33408 +Epoch: [26] [1330/2639] eta: 1:06:11 lr: 1.8805730790067617e-05 loss: 0.0390 (0.0399) time: 3.0082 data: 0.0075 max mem: 33408 +Epoch: [26] [1340/2639] eta: 1:05:41 lr: 1.8800978467914514e-05 loss: 0.0348 (0.0398) time: 3.0372 data: 0.0073 max mem: 33408 +Epoch: [26] [1350/2639] eta: 1:05:11 lr: 1.8796226012286077e-05 loss: 0.0370 (0.0399) time: 3.0668 data: 0.0074 max mem: 33408 +Epoch: [26] [1360/2639] eta: 1:04:41 lr: 1.879147342314107e-05 loss: 0.0382 (0.0399) time: 3.0635 data: 0.0074 max mem: 33408 +Epoch: [26] [1370/2639] eta: 1:04:10 lr: 1.878672070043821e-05 loss: 0.0358 (0.0398) time: 3.0447 data: 0.0076 max mem: 33408 +Epoch: [26] [1380/2639] eta: 1:03:40 lr: 1.8781967844136214e-05 loss: 0.0333 (0.0399) time: 3.0463 data: 0.0075 max mem: 33408 +Epoch: [26] [1390/2639] eta: 1:03:10 lr: 1.8777214854193746e-05 loss: 0.0339 (0.0398) time: 3.0350 data: 0.0075 max mem: 33408 +Epoch: [26] [1400/2639] eta: 1:02:39 lr: 1.8772461730569468e-05 loss: 0.0339 (0.0398) time: 2.9986 data: 0.0075 max mem: 33408 +Epoch: [26] [1410/2639] eta: 1:02:08 lr: 1.8767708473222005e-05 loss: 0.0337 (0.0398) time: 2.9887 data: 0.0077 max mem: 33408 +Epoch: [26] [1420/2639] eta: 1:01:38 lr: 1.8762955082109964e-05 loss: 0.0337 (0.0399) time: 3.0124 data: 0.0079 max mem: 33408 +Epoch: [26] [1430/2639] eta: 1:01:08 lr: 1.8758201557191922e-05 loss: 0.0380 (0.0399) time: 3.0416 data: 0.0077 max mem: 33408 +Epoch: [26] [1440/2639] eta: 1:00:37 lr: 1.8753447898426442e-05 loss: 0.0360 (0.0398) time: 3.0372 data: 0.0075 max mem: 33408 +Epoch: [26] [1450/2639] eta: 1:00:07 lr: 1.874869410577205e-05 loss: 0.0359 (0.0398) time: 3.0276 data: 0.0075 max mem: 33408 +Epoch: [26] [1460/2639] eta: 0:59:37 lr: 1.8743940179187257e-05 loss: 0.0397 (0.0398) time: 3.0591 data: 0.0079 max mem: 33408 +Epoch: [26] [1470/2639] eta: 0:59:06 lr: 1.8739186118630535e-05 loss: 0.0397 (0.0399) time: 3.0556 data: 0.0076 max mem: 33408 +Epoch: [26] [1480/2639] eta: 0:58:37 lr: 1.8734431924060358e-05 loss: 0.0369 (0.0399) time: 3.0589 data: 0.0077 max mem: 33408 +Epoch: [26] [1490/2639] eta: 0:58:06 lr: 1.8729677595435144e-05 loss: 0.0369 (0.0399) time: 3.0657 data: 0.0080 max mem: 33408 +Epoch: [26] [1500/2639] eta: 0:57:36 lr: 1.8724923132713312e-05 loss: 0.0379 (0.0399) time: 3.0477 data: 0.0080 max mem: 33408 +Epoch: [26] [1510/2639] eta: 0:57:06 lr: 1.8720168535853236e-05 loss: 0.0342 (0.0399) time: 3.0656 data: 0.0080 max mem: 33408 +Epoch: [26] [1520/2639] eta: 0:56:36 lr: 1.871541380481329e-05 loss: 0.0401 (0.0399) time: 3.0617 data: 0.0078 max mem: 33408 +Epoch: [26] [1530/2639] eta: 0:56:05 lr: 1.871065893955179e-05 loss: 0.0391 (0.0398) time: 3.0317 data: 0.0075 max mem: 33408 +Epoch: [26] [1540/2639] eta: 0:55:35 lr: 1.8705903940027063e-05 loss: 0.0344 (0.0398) time: 3.0471 data: 0.0073 max mem: 33408 +Epoch: [26] [1550/2639] eta: 0:55:05 lr: 1.8701148806197378e-05 loss: 0.0361 (0.0398) time: 3.0382 data: 0.0074 max mem: 33408 +Epoch: [26] [1560/2639] eta: 0:54:34 lr: 1.8696393538021007e-05 loss: 0.0375 (0.0398) time: 3.0108 data: 0.0077 max mem: 33408 +Epoch: [26] [1570/2639] eta: 0:54:04 lr: 1.8691638135456184e-05 loss: 0.0345 (0.0398) time: 3.0267 data: 0.0077 max mem: 33408 +Epoch: [26] [1580/2639] eta: 0:53:34 lr: 1.8686882598461117e-05 loss: 0.0336 (0.0398) time: 3.0727 data: 0.0075 max mem: 33408 +Epoch: [26] [1590/2639] eta: 0:53:04 lr: 1.8682126926993996e-05 loss: 0.0339 (0.0399) time: 3.1083 data: 0.0077 max mem: 33408 +Epoch: [26] [1600/2639] eta: 0:52:34 lr: 1.8677371121012974e-05 loss: 0.0328 (0.0399) time: 3.0728 data: 0.0074 max mem: 33408 +Epoch: [26] [1610/2639] eta: 0:52:03 lr: 1.8672615180476198e-05 loss: 0.0322 (0.0399) time: 3.0026 data: 0.0075 max mem: 33408 +Epoch: [26] [1620/2639] eta: 0:51:32 lr: 1.8667859105341763e-05 loss: 0.0326 (0.0399) time: 2.9674 data: 0.0077 max mem: 33408 +Epoch: [26] [1630/2639] eta: 0:51:02 lr: 1.866310289556778e-05 loss: 0.0326 (0.0399) time: 2.9893 data: 0.0077 max mem: 33408 +Epoch: [26] [1640/2639] eta: 0:50:32 lr: 1.8658346551112287e-05 loss: 0.0333 (0.0399) time: 3.0498 data: 0.0077 max mem: 33408 +Epoch: [26] [1650/2639] eta: 0:50:01 lr: 1.8653590071933334e-05 loss: 0.0357 (0.0399) time: 3.0431 data: 0.0075 max mem: 33408 +Epoch: [26] [1660/2639] eta: 0:49:31 lr: 1.864883345798893e-05 loss: 0.0338 (0.0399) time: 3.0035 data: 0.0079 max mem: 33408 +Epoch: [26] [1670/2639] eta: 0:49:00 lr: 1.864407670923706e-05 loss: 0.0317 (0.0399) time: 2.9766 data: 0.0082 max mem: 33408 +Epoch: [26] [1680/2639] eta: 0:48:29 lr: 1.8639319825635684e-05 loss: 0.0432 (0.0399) time: 2.9177 data: 0.0077 max mem: 33408 +Epoch: [26] [1690/2639] eta: 0:47:58 lr: 1.8634562807142743e-05 loss: 0.0435 (0.0399) time: 2.9581 data: 0.0077 max mem: 33408 +Epoch: [26] [1700/2639] eta: 0:47:28 lr: 1.8629805653716145e-05 loss: 0.0402 (0.0399) time: 3.0411 data: 0.0078 max mem: 33408 +Epoch: [26] [1710/2639] eta: 0:46:57 lr: 1.8625048365313784e-05 loss: 0.0354 (0.0399) time: 3.0288 data: 0.0076 max mem: 33408 +Epoch: [26] [1720/2639] eta: 0:46:27 lr: 1.8620290941893507e-05 loss: 0.0364 (0.0399) time: 3.0057 data: 0.0078 max mem: 33408 +Epoch: [26] [1730/2639] eta: 0:45:57 lr: 1.8615533383413165e-05 loss: 0.0375 (0.0399) time: 3.0355 data: 0.0078 max mem: 33408 +Epoch: [26] [1740/2639] eta: 0:45:27 lr: 1.8610775689830557e-05 loss: 0.0365 (0.0399) time: 3.0663 data: 0.0077 max mem: 33408 +Epoch: [26] [1750/2639] eta: 0:44:56 lr: 1.8606017861103477e-05 loss: 0.0411 (0.0400) time: 3.0392 data: 0.0079 max mem: 33408 +Epoch: [26] [1760/2639] eta: 0:44:26 lr: 1.8601259897189684e-05 loss: 0.0375 (0.0400) time: 3.0256 data: 0.0081 max mem: 33408 +Epoch: [26] [1770/2639] eta: 0:43:56 lr: 1.8596501798046914e-05 loss: 0.0346 (0.0399) time: 3.0424 data: 0.0078 max mem: 33408 +Epoch: [26] [1780/2639] eta: 0:43:25 lr: 1.859174356363287e-05 loss: 0.0345 (0.0399) time: 3.0135 data: 0.0074 max mem: 33408 +Epoch: [26] [1790/2639] eta: 0:42:55 lr: 1.858698519390525e-05 loss: 0.0409 (0.0399) time: 3.0018 data: 0.0077 max mem: 33408 +Epoch: [26] [1800/2639] eta: 0:42:25 lr: 1.85822266888217e-05 loss: 0.0369 (0.0399) time: 3.0613 data: 0.0076 max mem: 33408 +Epoch: [26] [1810/2639] eta: 0:41:54 lr: 1.8577468048339867e-05 loss: 0.0294 (0.0399) time: 3.0615 data: 0.0075 max mem: 33408 +Epoch: [26] [1820/2639] eta: 0:41:24 lr: 1.8572709272417357e-05 loss: 0.0346 (0.0399) time: 3.0182 data: 0.0074 max mem: 33408 +Epoch: [26] [1830/2639] eta: 0:40:54 lr: 1.8567950361011746e-05 loss: 0.0427 (0.0399) time: 3.0434 data: 0.0077 max mem: 33408 +Epoch: [26] [1840/2639] eta: 0:40:23 lr: 1.8563191314080604e-05 loss: 0.0375 (0.0399) time: 3.0394 data: 0.0076 max mem: 33408 +Epoch: [26] [1850/2639] eta: 0:39:53 lr: 1.8558432131581448e-05 loss: 0.0371 (0.0399) time: 3.0304 data: 0.0074 max mem: 33408 +Epoch: [26] [1860/2639] eta: 0:39:23 lr: 1.8553672813471806e-05 loss: 0.0388 (0.0399) time: 3.0486 data: 0.0079 max mem: 33408 +Epoch: [26] [1870/2639] eta: 0:38:52 lr: 1.8548913359709143e-05 loss: 0.0379 (0.0399) time: 3.0418 data: 0.0081 max mem: 33408 +Epoch: [26] [1880/2639] eta: 0:38:22 lr: 1.8544153770250928e-05 loss: 0.0362 (0.0399) time: 3.0326 data: 0.0078 max mem: 33408 +Epoch: [26] [1890/2639] eta: 0:37:51 lr: 1.853939404505458e-05 loss: 0.0344 (0.0399) time: 3.0102 data: 0.0076 max mem: 33408 +Epoch: [26] [1900/2639] eta: 0:37:21 lr: 1.8534634184077522e-05 loss: 0.0342 (0.0399) time: 2.9786 data: 0.0075 max mem: 33408 +Epoch: [26] [1910/2639] eta: 0:36:51 lr: 1.8529874187277113e-05 loss: 0.0377 (0.0399) time: 2.9919 data: 0.0075 max mem: 33408 +Epoch: [26] [1920/2639] eta: 0:36:20 lr: 1.8525114054610723e-05 loss: 0.0377 (0.0398) time: 3.0466 data: 0.0078 max mem: 33408 +Epoch: [26] [1930/2639] eta: 0:35:50 lr: 1.8520353786035673e-05 loss: 0.0347 (0.0398) time: 3.0839 data: 0.0081 max mem: 33408 +Epoch: [26] [1940/2639] eta: 0:35:20 lr: 1.851559338150928e-05 loss: 0.0347 (0.0398) time: 3.0294 data: 0.0078 max mem: 33408 +Epoch: [26] [1950/2639] eta: 0:34:49 lr: 1.85108328409888e-05 loss: 0.0325 (0.0398) time: 2.9629 data: 0.0074 max mem: 33408 +Epoch: [26] [1960/2639] eta: 0:34:19 lr: 1.8506072164431507e-05 loss: 0.0356 (0.0398) time: 2.9830 data: 0.0075 max mem: 33408 +Epoch: [26] [1970/2639] eta: 0:33:48 lr: 1.850131135179461e-05 loss: 0.0357 (0.0398) time: 3.0274 data: 0.0074 max mem: 33408 +Epoch: [26] [1980/2639] eta: 0:33:18 lr: 1.8496550403035327e-05 loss: 0.0376 (0.0398) time: 3.0619 data: 0.0073 max mem: 33408 +Epoch: [26] [1990/2639] eta: 0:32:48 lr: 1.8491789318110817e-05 loss: 0.0376 (0.0399) time: 3.0233 data: 0.0071 max mem: 33408 +Epoch: [26] [2000/2639] eta: 0:32:17 lr: 1.8487028096978243e-05 loss: 0.0376 (0.0399) time: 3.0083 data: 0.0073 max mem: 33408 +Epoch: [26] [2010/2639] eta: 0:31:47 lr: 1.8482266739594713e-05 loss: 0.0347 (0.0399) time: 3.0637 data: 0.0077 max mem: 33408 +Epoch: [26] [2020/2639] eta: 0:31:17 lr: 1.8477505245917345e-05 loss: 0.0347 (0.0399) time: 3.0601 data: 0.0075 max mem: 33408 +Epoch: [26] [2030/2639] eta: 0:30:47 lr: 1.8472743615903193e-05 loss: 0.0379 (0.0399) time: 3.0459 data: 0.0079 max mem: 33408 +Epoch: [26] [2040/2639] eta: 0:30:16 lr: 1.8467981849509317e-05 loss: 0.0359 (0.0399) time: 3.0290 data: 0.0084 max mem: 33408 +Epoch: [26] [2050/2639] eta: 0:29:46 lr: 1.8463219946692725e-05 loss: 0.0380 (0.0399) time: 2.9620 data: 0.0081 max mem: 33408 +Epoch: [26] [2060/2639] eta: 0:29:15 lr: 1.845845790741042e-05 loss: 0.0385 (0.0399) time: 2.9668 data: 0.0080 max mem: 33408 +Epoch: [26] [2070/2639] eta: 0:28:45 lr: 1.845369573161937e-05 loss: 0.0351 (0.0399) time: 3.0446 data: 0.0084 max mem: 33408 +Epoch: [26] [2080/2639] eta: 0:28:15 lr: 1.8448933419276517e-05 loss: 0.0384 (0.0399) time: 3.0360 data: 0.0082 max mem: 33408 +Epoch: [26] [2090/2639] eta: 0:27:44 lr: 1.8444170970338783e-05 loss: 0.0360 (0.0399) time: 2.9833 data: 0.0076 max mem: 33408 +Epoch: [26] [2100/2639] eta: 0:27:14 lr: 1.8439408384763043e-05 loss: 0.0313 (0.0399) time: 2.9529 data: 0.0074 max mem: 33408 +Epoch: [26] [2110/2639] eta: 0:26:43 lr: 1.8434645662506184e-05 loss: 0.0337 (0.0399) time: 2.9946 data: 0.0074 max mem: 33408 +Epoch: [26] [2120/2639] eta: 0:26:13 lr: 1.8429882803525024e-05 loss: 0.0364 (0.0400) time: 3.0609 data: 0.0074 max mem: 33408 +Epoch: [26] [2130/2639] eta: 0:25:43 lr: 1.842511980777639e-05 loss: 0.0339 (0.0399) time: 3.0667 data: 0.0077 max mem: 33408 +Epoch: [26] [2140/2639] eta: 0:25:12 lr: 1.8420356675217064e-05 loss: 0.0327 (0.0399) time: 3.0558 data: 0.0077 max mem: 33408 +Epoch: [26] [2150/2639] eta: 0:24:42 lr: 1.8415593405803813e-05 loss: 0.0363 (0.0399) time: 3.0586 data: 0.0078 max mem: 33408 +Epoch: [26] [2160/2639] eta: 0:24:12 lr: 1.8410829999493358e-05 loss: 0.0343 (0.0400) time: 3.0452 data: 0.0078 max mem: 33408 +Epoch: [26] [2170/2639] eta: 0:23:42 lr: 1.8406066456242422e-05 loss: 0.0345 (0.0400) time: 3.0203 data: 0.0078 max mem: 33408 +Epoch: [26] [2180/2639] eta: 0:23:11 lr: 1.8401302776007674e-05 loss: 0.0354 (0.0400) time: 3.0373 data: 0.0076 max mem: 33408 +Epoch: [26] [2190/2639] eta: 0:22:41 lr: 1.8396538958745785e-05 loss: 0.0399 (0.0400) time: 3.0232 data: 0.0077 max mem: 33408 +Epoch: [26] [2200/2639] eta: 0:22:11 lr: 1.839177500441337e-05 loss: 0.0438 (0.0400) time: 3.0360 data: 0.0079 max mem: 33408 +Epoch: [26] [2210/2639] eta: 0:21:40 lr: 1.8387010912967048e-05 loss: 0.0394 (0.0401) time: 3.0531 data: 0.0078 max mem: 33408 +Epoch: [26] [2220/2639] eta: 0:21:10 lr: 1.8382246684363384e-05 loss: 0.0380 (0.0401) time: 3.0171 data: 0.0080 max mem: 33408 +Epoch: [26] [2230/2639] eta: 0:20:40 lr: 1.837748231855894e-05 loss: 0.0380 (0.0401) time: 3.0430 data: 0.0078 max mem: 33408 +Epoch: [26] [2240/2639] eta: 0:20:09 lr: 1.837271781551023e-05 loss: 0.0398 (0.0401) time: 3.0142 data: 0.0073 max mem: 33408 +Epoch: [26] [2250/2639] eta: 0:19:39 lr: 1.8367953175173765e-05 loss: 0.0383 (0.0401) time: 3.0382 data: 0.0073 max mem: 33408 +Epoch: [26] [2260/2639] eta: 0:19:09 lr: 1.8363188397506e-05 loss: 0.0362 (0.0401) time: 3.0895 data: 0.0074 max mem: 33408 +Epoch: [26] [2270/2639] eta: 0:18:38 lr: 1.8358423482463404e-05 loss: 0.0362 (0.0401) time: 3.0264 data: 0.0075 max mem: 33408 +Epoch: [26] [2280/2639] eta: 0:18:08 lr: 1.8353658430002376e-05 loss: 0.0377 (0.0402) time: 2.9861 data: 0.0079 max mem: 33408 +Epoch: [26] [2290/2639] eta: 0:17:38 lr: 1.8348893240079326e-05 loss: 0.0373 (0.0401) time: 3.0362 data: 0.0078 max mem: 33408 +Epoch: [26] [2300/2639] eta: 0:17:07 lr: 1.8344127912650604e-05 loss: 0.0327 (0.0401) time: 3.0696 data: 0.0073 max mem: 33408 +Epoch: [26] [2310/2639] eta: 0:16:37 lr: 1.8339362447672564e-05 loss: 0.0363 (0.0401) time: 3.0507 data: 0.0075 max mem: 33408 +Epoch: [26] [2320/2639] eta: 0:16:07 lr: 1.8334596845101517e-05 loss: 0.0363 (0.0401) time: 3.0685 data: 0.0077 max mem: 33408 +Epoch: [26] [2330/2639] eta: 0:15:37 lr: 1.8329831104893748e-05 loss: 0.0337 (0.0401) time: 3.0732 data: 0.0075 max mem: 33408 +Epoch: [26] [2340/2639] eta: 0:15:06 lr: 1.8325065227005524e-05 loss: 0.0381 (0.0401) time: 3.0591 data: 0.0074 max mem: 33408 +Epoch: [26] [2350/2639] eta: 0:14:36 lr: 1.8320299211393066e-05 loss: 0.0437 (0.0402) time: 3.0317 data: 0.0072 max mem: 33408 +Epoch: [26] [2360/2639] eta: 0:14:06 lr: 1.83155330580126e-05 loss: 0.0409 (0.0402) time: 3.0070 data: 0.0074 max mem: 33408 +Epoch: [26] [2370/2639] eta: 0:13:35 lr: 1.831076676682029e-05 loss: 0.0371 (0.0402) time: 3.0448 data: 0.0076 max mem: 33408 +Epoch: [26] [2380/2639] eta: 0:13:05 lr: 1.83060003377723e-05 loss: 0.0371 (0.0402) time: 3.0712 data: 0.0076 max mem: 33408 +Epoch: [26] [2390/2639] eta: 0:12:35 lr: 1.8301233770824757e-05 loss: 0.0356 (0.0402) time: 3.0727 data: 0.0076 max mem: 33408 +Epoch: [26] [2400/2639] eta: 0:12:04 lr: 1.8296467065933766e-05 loss: 0.0429 (0.0402) time: 3.0409 data: 0.0075 max mem: 33408 +Epoch: [26] [2410/2639] eta: 0:11:34 lr: 1.8291700223055393e-05 loss: 0.0343 (0.0402) time: 2.9883 data: 0.0079 max mem: 33408 +Epoch: [26] [2420/2639] eta: 0:11:04 lr: 1.8286933242145693e-05 loss: 0.0329 (0.0402) time: 3.0108 data: 0.0085 max mem: 33408 +Epoch: [26] [2430/2639] eta: 0:10:33 lr: 1.828216612316068e-05 loss: 0.0334 (0.0402) time: 3.0206 data: 0.0082 max mem: 33408 +Epoch: [26] [2440/2639] eta: 0:10:03 lr: 1.8277398866056362e-05 loss: 0.0338 (0.0402) time: 2.9954 data: 0.0080 max mem: 33408 +Epoch: [26] [2450/2639] eta: 0:09:33 lr: 1.8272631470788688e-05 loss: 0.0309 (0.0402) time: 3.0341 data: 0.0081 max mem: 33408 +Epoch: [26] [2460/2639] eta: 0:09:02 lr: 1.826786393731362e-05 loss: 0.0330 (0.0402) time: 3.0319 data: 0.0078 max mem: 33408 +Epoch: [26] [2470/2639] eta: 0:08:32 lr: 1.826309626558705e-05 loss: 0.0350 (0.0402) time: 3.0089 data: 0.0078 max mem: 33408 +Epoch: [26] [2480/2639] eta: 0:08:02 lr: 1.825832845556488e-05 loss: 0.0358 (0.0401) time: 3.0096 data: 0.0084 max mem: 33408 +Epoch: [26] [2490/2639] eta: 0:07:31 lr: 1.8253560507202964e-05 loss: 0.0339 (0.0402) time: 3.0307 data: 0.0086 max mem: 33408 +Epoch: [26] [2500/2639] eta: 0:07:01 lr: 1.8248792420457145e-05 loss: 0.0402 (0.0402) time: 3.0518 data: 0.0079 max mem: 33408 +Epoch: [26] [2510/2639] eta: 0:06:31 lr: 1.8244024195283215e-05 loss: 0.0340 (0.0402) time: 3.0532 data: 0.0079 max mem: 33408 +Epoch: [26] [2520/2639] eta: 0:06:00 lr: 1.823925583163697e-05 loss: 0.0303 (0.0401) time: 3.0107 data: 0.0080 max mem: 33408 +Epoch: [26] [2530/2639] eta: 0:05:30 lr: 1.8234487329474143e-05 loss: 0.0335 (0.0402) time: 2.9789 data: 0.0077 max mem: 33408 +Epoch: [26] [2540/2639] eta: 0:05:00 lr: 1.822971868875047e-05 loss: 0.0389 (0.0402) time: 3.0370 data: 0.0077 max mem: 33408 +Epoch: [26] [2550/2639] eta: 0:04:29 lr: 1.8224949909421657e-05 loss: 0.0389 (0.0402) time: 3.0507 data: 0.0076 max mem: 33408 +Epoch: [26] [2560/2639] eta: 0:03:59 lr: 1.8220180991443365e-05 loss: 0.0367 (0.0401) time: 3.0124 data: 0.0077 max mem: 33408 +Epoch: [26] [2570/2639] eta: 0:03:29 lr: 1.8215411934771244e-05 loss: 0.0358 (0.0401) time: 2.9949 data: 0.0077 max mem: 33408 +Epoch: [26] [2580/2639] eta: 0:02:58 lr: 1.8210642739360904e-05 loss: 0.0357 (0.0401) time: 3.0097 data: 0.0077 max mem: 33408 +Epoch: [26] [2590/2639] eta: 0:02:28 lr: 1.8205873405167945e-05 loss: 0.0351 (0.0401) time: 3.0557 data: 0.0079 max mem: 33408 +Epoch: [26] [2600/2639] eta: 0:01:58 lr: 1.820110393214792e-05 loss: 0.0345 (0.0401) time: 3.0636 data: 0.0077 max mem: 33408 +Epoch: [26] [2610/2639] eta: 0:01:27 lr: 1.8196334320256375e-05 loss: 0.0379 (0.0401) time: 3.0111 data: 0.0077 max mem: 33408 +Epoch: [26] [2620/2639] eta: 0:00:57 lr: 1.8191564569448807e-05 loss: 0.0403 (0.0401) time: 2.9734 data: 0.0081 max mem: 33408 +Epoch: [26] [2630/2639] eta: 0:00:27 lr: 1.8186794679680715e-05 loss: 0.0395 (0.0401) time: 2.9662 data: 0.0077 max mem: 33408 +Epoch: [26] Total time: 2:13:21 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 2:06:18 time: 2.9453 data: 2.8543 max mem: 33408 +Test: [ 100/2573] eta: 0:04:27 time: 0.0797 data: 0.0014 max mem: 33408 +Test: [ 200/2573] eta: 0:03:45 time: 0.0813 data: 0.0014 max mem: 33408 +Test: [ 300/2573] eta: 0:03:25 time: 0.0835 data: 0.0013 max mem: 33408 +Test: [ 400/2573] eta: 0:03:11 time: 0.0836 data: 0.0013 max mem: 33408 +Test: [ 500/2573] eta: 0:03:00 time: 0.0818 data: 0.0015 max mem: 33408 +Test: [ 600/2573] eta: 0:02:49 time: 0.0817 data: 0.0014 max mem: 33408 +Test: [ 700/2573] eta: 0:02:40 time: 0.0839 data: 0.0016 max mem: 33408 +Test: [ 800/2573] eta: 0:02:31 time: 0.0850 data: 0.0013 max mem: 33408 +Test: [ 900/2573] eta: 0:02:22 time: 0.0824 data: 0.0015 max mem: 33408 +Test: [1000/2573] eta: 0:02:13 time: 0.0819 data: 0.0014 max mem: 33408 +Test: [1100/2573] eta: 0:02:04 time: 0.0820 data: 0.0015 max mem: 33408 +Test: [1200/2573] eta: 0:01:56 time: 0.0814 data: 0.0015 max mem: 33408 +Test: [1300/2573] eta: 0:01:47 time: 0.0826 data: 0.0014 max mem: 33408 +Test: [1400/2573] eta: 0:01:38 time: 0.0806 data: 0.0014 max mem: 33408 +Test: [1500/2573] eta: 0:01:30 time: 0.0820 data: 0.0015 max mem: 33408 +Test: [1600/2573] eta: 0:01:21 time: 0.0845 data: 0.0014 max mem: 33408 +Test: [1700/2573] eta: 0:01:13 time: 0.0812 data: 0.0015 max mem: 33408 +Test: [1800/2573] eta: 0:01:04 time: 0.0829 data: 0.0015 max mem: 33408 +Test: [1900/2573] eta: 0:00:56 time: 0.0809 data: 0.0014 max mem: 33408 +Test: [2000/2573] eta: 0:00:47 time: 0.0806 data: 0.0014 max mem: 33408 +Test: [2100/2573] eta: 0:00:39 time: 0.0830 data: 0.0014 max mem: 33408 +Test: [2200/2573] eta: 0:00:31 time: 0.0840 data: 0.0015 max mem: 33408 +Test: [2300/2573] eta: 0:00:22 time: 0.0830 data: 0.0015 max mem: 33408 +Test: [2400/2573] eta: 0:00:14 time: 0.0778 data: 0.0015 max mem: 33408 +Test: [2500/2573] eta: 0:00:06 time: 0.0815 data: 0.0015 max mem: 33408 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: Total time: 0:03:35 +Final results: +Mean IoU is 64.05 + + precision@0.5 = 72.30 + precision@0.6 = 67.36 + precision@0.7 = 60.50 + precision@0.8 = 49.29 + precision@0.9 = 24.26 + overall IoU = 61.92 + +Average object IoU 64.05487156384604 +Overall IoU 61.9169807434082 +Better epoch: 26 + +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [27] [ 0/2639] eta: 4:10:00 lr: 1.818250166004135e-05 loss: 0.0328 (0.0328) time: 5.6842 data: 2.2472 max mem: 33408 +Epoch: [27] [ 10/2639] eta: 2:24:33 lr: 1.8177731506125488e-05 loss: 0.0351 (0.0352) time: 3.2993 data: 0.2112 max mem: 33408 +Epoch: [27] [ 20/2639] eta: 2:18:06 lr: 1.8172961213119836e-05 loss: 0.0344 (0.0356) time: 3.0379 data: 0.0075 max mem: 33408 +Epoch: [27] [ 30/2639] eta: 2:15:41 lr: 1.8168190780979762e-05 loss: 0.0334 (0.0361) time: 3.0225 data: 0.0074 max mem: 33408 +Epoch: [27] [ 40/2639] eta: 2:14:42 lr: 1.8163420209660625e-05 loss: 0.0318 (0.0369) time: 3.0529 data: 0.0076 max mem: 33408 +Epoch: [27] [ 50/2639] eta: 2:13:02 lr: 1.8158649499117732e-05 loss: 0.0356 (0.0374) time: 3.0248 data: 0.0083 max mem: 33408 +Epoch: [27] [ 60/2639] eta: 2:11:40 lr: 1.8153878649306386e-05 loss: 0.0356 (0.0380) time: 2.9682 data: 0.0083 max mem: 33408 +Epoch: [27] [ 70/2639] eta: 2:10:44 lr: 1.8149107660181848e-05 loss: 0.0338 (0.0380) time: 2.9782 data: 0.0079 max mem: 33408 +Epoch: [27] [ 80/2639] eta: 2:10:02 lr: 1.8144336531699356e-05 loss: 0.0338 (0.0379) time: 3.0060 data: 0.0078 max mem: 33408 +Epoch: [27] [ 90/2639] eta: 2:09:38 lr: 1.813956526381412e-05 loss: 0.0379 (0.0380) time: 3.0446 data: 0.0076 max mem: 33408 +Epoch: [27] [ 100/2639] eta: 2:08:49 lr: 1.8134793856481334e-05 loss: 0.0370 (0.0388) time: 3.0244 data: 0.0079 max mem: 33408 +Epoch: [27] [ 110/2639] eta: 2:08:14 lr: 1.8130022309656134e-05 loss: 0.0342 (0.0384) time: 3.0017 data: 0.0079 max mem: 33408 +Epoch: [27] [ 120/2639] eta: 2:07:50 lr: 1.8125250623293667e-05 loss: 0.0338 (0.0383) time: 3.0484 data: 0.0082 max mem: 33408 +Epoch: [27] [ 130/2639] eta: 2:07:19 lr: 1.8120478797349017e-05 loss: 0.0359 (0.0383) time: 3.0560 data: 0.0084 max mem: 33408 +Epoch: [27] [ 140/2639] eta: 2:06:47 lr: 1.8115706831777274e-05 loss: 0.0378 (0.0387) time: 3.0409 data: 0.0080 max mem: 33408 +Epoch: [27] [ 150/2639] eta: 2:06:25 lr: 1.8110934726533467e-05 loss: 0.0359 (0.0385) time: 3.0672 data: 0.0082 max mem: 33408 +Epoch: [27] [ 160/2639] eta: 2:05:50 lr: 1.810616248157263e-05 loss: 0.0370 (0.0387) time: 3.0545 data: 0.0081 max mem: 33408 +Epoch: [27] [ 170/2639] eta: 2:05:22 lr: 1.8101390096849732e-05 loss: 0.0357 (0.0385) time: 3.0412 data: 0.0080 max mem: 33408 +Epoch: [27] [ 180/2639] eta: 2:04:50 lr: 1.8096617572319754e-05 loss: 0.0357 (0.0388) time: 3.0495 data: 0.0080 max mem: 33408 +Epoch: [27] [ 190/2639] eta: 2:04:16 lr: 1.8091844907937627e-05 loss: 0.0361 (0.0386) time: 3.0250 data: 0.0082 max mem: 33408 +Epoch: [27] [ 200/2639] eta: 2:03:54 lr: 1.808707210365825e-05 loss: 0.0362 (0.0387) time: 3.0665 data: 0.0082 max mem: 33408 +Epoch: [27] [ 210/2639] eta: 2:03:20 lr: 1.8082299159436512e-05 loss: 0.0404 (0.0389) time: 3.0672 data: 0.0079 max mem: 33408 +Epoch: [27] [ 220/2639] eta: 2:02:49 lr: 1.8077526075227258e-05 loss: 0.0403 (0.0389) time: 3.0314 data: 0.0080 max mem: 33408 +Epoch: [27] [ 230/2639] eta: 2:02:20 lr: 1.8072752850985318e-05 loss: 0.0371 (0.0388) time: 3.0502 data: 0.0079 max mem: 33408 +Epoch: [27] [ 240/2639] eta: 2:01:46 lr: 1.8067979486665473e-05 loss: 0.0319 (0.0386) time: 3.0371 data: 0.0083 max mem: 33408 +Epoch: [27] [ 250/2639] eta: 2:01:21 lr: 1.806320598222251e-05 loss: 0.0312 (0.0384) time: 3.0608 data: 0.0081 max mem: 33408 +Epoch: [27] [ 260/2639] eta: 2:00:50 lr: 1.8058432337611152e-05 loss: 0.0312 (0.0387) time: 3.0680 data: 0.0076 max mem: 33408 +Epoch: [27] [ 270/2639] eta: 2:00:19 lr: 1.8053658552786127e-05 loss: 0.0313 (0.0386) time: 3.0412 data: 0.0077 max mem: 33408 +Epoch: [27] [ 280/2639] eta: 1:59:44 lr: 1.8048884627702103e-05 loss: 0.0345 (0.0386) time: 3.0201 data: 0.0077 max mem: 33408 +Epoch: [27] [ 290/2639] eta: 1:59:06 lr: 1.804411056231375e-05 loss: 0.0388 (0.0387) time: 2.9722 data: 0.0078 max mem: 33408 +Epoch: [27] [ 300/2639] eta: 1:58:30 lr: 1.8039336356575684e-05 loss: 0.0388 (0.0385) time: 2.9587 data: 0.0077 max mem: 33408 +Epoch: [27] [ 310/2639] eta: 1:58:03 lr: 1.8034562010442518e-05 loss: 0.0317 (0.0384) time: 3.0253 data: 0.0077 max mem: 33408 +Epoch: [27] [ 320/2639] eta: 1:57:32 lr: 1.802978752386881e-05 loss: 0.0367 (0.0385) time: 3.0598 data: 0.0075 max mem: 33408 +Epoch: [27] [ 330/2639] eta: 1:57:02 lr: 1.8025012896809117e-05 loss: 0.0373 (0.0385) time: 3.0448 data: 0.0076 max mem: 33408 +Epoch: [27] [ 340/2639] eta: 1:56:26 lr: 1.8020238129217944e-05 loss: 0.0321 (0.0384) time: 3.0086 data: 0.0082 max mem: 33408 +Epoch: [27] [ 350/2639] eta: 1:55:53 lr: 1.8015463221049788e-05 loss: 0.0347 (0.0385) time: 2.9792 data: 0.0079 max mem: 33408 +Epoch: [27] [ 360/2639] eta: 1:55:23 lr: 1.80106881722591e-05 loss: 0.0364 (0.0385) time: 3.0212 data: 0.0074 max mem: 33408 +Epoch: [27] [ 370/2639] eta: 1:54:50 lr: 1.8005912982800317e-05 loss: 0.0364 (0.0385) time: 3.0137 data: 0.0072 max mem: 33408 +Epoch: [27] [ 380/2639] eta: 1:54:21 lr: 1.800113765262784e-05 loss: 0.0334 (0.0383) time: 3.0282 data: 0.0072 max mem: 33408 +Epoch: [27] [ 390/2639] eta: 1:53:52 lr: 1.7996362181696054e-05 loss: 0.0352 (0.0384) time: 3.0619 data: 0.0078 max mem: 33408 +Epoch: [27] [ 400/2639] eta: 1:53:20 lr: 1.7991586569959286e-05 loss: 0.0371 (0.0384) time: 3.0289 data: 0.0078 max mem: 33408 +Epoch: [27] [ 410/2639] eta: 1:52:49 lr: 1.798681081737187e-05 loss: 0.0343 (0.0383) time: 3.0199 data: 0.0079 max mem: 33408 +Epoch: [27] [ 420/2639] eta: 1:52:16 lr: 1.7982034923888087e-05 loss: 0.0381 (0.0387) time: 3.0111 data: 0.0080 max mem: 33408 +Epoch: [27] [ 430/2639] eta: 1:51:47 lr: 1.7977258889462203e-05 loss: 0.0371 (0.0385) time: 3.0183 data: 0.0078 max mem: 33408 +Epoch: [27] [ 440/2639] eta: 1:51:16 lr: 1.7972482714048458e-05 loss: 0.0363 (0.0385) time: 3.0369 data: 0.0078 max mem: 33408 +Epoch: [27] [ 450/2639] eta: 1:50:45 lr: 1.7967706397601044e-05 loss: 0.0403 (0.0385) time: 3.0256 data: 0.0076 max mem: 33408 +Epoch: [27] [ 460/2639] eta: 1:50:16 lr: 1.7962929940074153e-05 loss: 0.0335 (0.0387) time: 3.0507 data: 0.0074 max mem: 33408 +Epoch: [27] [ 470/2639] eta: 1:49:44 lr: 1.7958153341421917e-05 loss: 0.0316 (0.0386) time: 3.0350 data: 0.0073 max mem: 33408 +Epoch: [27] [ 480/2639] eta: 1:49:15 lr: 1.7953376601598467e-05 loss: 0.0319 (0.0386) time: 3.0256 data: 0.0080 max mem: 33408 +Epoch: [27] [ 490/2639] eta: 1:48:44 lr: 1.794859972055789e-05 loss: 0.0365 (0.0386) time: 3.0406 data: 0.0080 max mem: 33408 +Epoch: [27] [ 500/2639] eta: 1:48:13 lr: 1.7943822698254252e-05 loss: 0.0404 (0.0388) time: 3.0297 data: 0.0075 max mem: 33408 +Epoch: [27] [ 510/2639] eta: 1:47:44 lr: 1.7939045534641584e-05 loss: 0.0411 (0.0388) time: 3.0495 data: 0.0076 max mem: 33408 +Epoch: [27] [ 520/2639] eta: 1:47:14 lr: 1.7934268229673893e-05 loss: 0.0395 (0.0388) time: 3.0565 data: 0.0080 max mem: 33408 +Epoch: [27] [ 530/2639] eta: 1:46:44 lr: 1.7929490783305154e-05 loss: 0.0395 (0.0389) time: 3.0426 data: 0.0084 max mem: 33408 +Epoch: [27] [ 540/2639] eta: 1:46:14 lr: 1.792471319548932e-05 loss: 0.0385 (0.0389) time: 3.0473 data: 0.0089 max mem: 33408 +Epoch: [27] [ 550/2639] eta: 1:45:45 lr: 1.7919935466180304e-05 loss: 0.0369 (0.0390) time: 3.0641 data: 0.0089 max mem: 33408 +Epoch: [27] [ 560/2639] eta: 1:45:15 lr: 1.7915157595332008e-05 loss: 0.0352 (0.0391) time: 3.0514 data: 0.0082 max mem: 33408 +Epoch: [27] [ 570/2639] eta: 1:44:45 lr: 1.7910379582898286e-05 loss: 0.0364 (0.0390) time: 3.0479 data: 0.0079 max mem: 33408 +Epoch: [27] [ 580/2639] eta: 1:44:15 lr: 1.7905601428832974e-05 loss: 0.0341 (0.0390) time: 3.0568 data: 0.0079 max mem: 33408 +Epoch: [27] [ 590/2639] eta: 1:43:45 lr: 1.790082313308987e-05 loss: 0.0332 (0.0392) time: 3.0458 data: 0.0080 max mem: 33408 +Epoch: [27] [ 600/2639] eta: 1:43:14 lr: 1.789604469562277e-05 loss: 0.0333 (0.0392) time: 3.0319 data: 0.0079 max mem: 33408 +Epoch: [27] [ 610/2639] eta: 1:42:43 lr: 1.7891266116385396e-05 loss: 0.0345 (0.0391) time: 3.0230 data: 0.0076 max mem: 33408 +Epoch: [27] [ 620/2639] eta: 1:42:14 lr: 1.788648739533149e-05 loss: 0.0324 (0.0390) time: 3.0413 data: 0.0076 max mem: 33408 +Epoch: [27] [ 630/2639] eta: 1:41:43 lr: 1.7881708532414723e-05 loss: 0.0429 (0.0392) time: 3.0487 data: 0.0077 max mem: 33408 +Epoch: [27] [ 640/2639] eta: 1:41:11 lr: 1.787692952758877e-05 loss: 0.0446 (0.0392) time: 3.0051 data: 0.0078 max mem: 33408 +Epoch: [27] [ 650/2639] eta: 1:40:40 lr: 1.7872150380807254e-05 loss: 0.0399 (0.0393) time: 2.9977 data: 0.0076 max mem: 33408 +Epoch: [27] [ 660/2639] eta: 1:40:11 lr: 1.7867371092023786e-05 loss: 0.0370 (0.0393) time: 3.0485 data: 0.0080 max mem: 33408 +Epoch: [27] [ 670/2639] eta: 1:39:40 lr: 1.7862591661191926e-05 loss: 0.0377 (0.0393) time: 3.0430 data: 0.0081 max mem: 33408 +Epoch: [27] [ 680/2639] eta: 1:39:08 lr: 1.7857812088265234e-05 loss: 0.0377 (0.0393) time: 3.0052 data: 0.0083 max mem: 33408 +Epoch: [27] [ 690/2639] eta: 1:38:37 lr: 1.7853032373197222e-05 loss: 0.0370 (0.0393) time: 3.0016 data: 0.0083 max mem: 33408 +Epoch: [27] [ 700/2639] eta: 1:38:07 lr: 1.784825251594137e-05 loss: 0.0357 (0.0392) time: 3.0346 data: 0.0082 max mem: 33408 +Epoch: [27] [ 710/2639] eta: 1:37:36 lr: 1.7843472516451153e-05 loss: 0.0366 (0.0392) time: 3.0298 data: 0.0084 max mem: 33408 +Epoch: [27] [ 720/2639] eta: 1:37:04 lr: 1.7838692374679977e-05 loss: 0.0379 (0.0393) time: 2.9982 data: 0.0081 max mem: 33408 +Epoch: [27] [ 730/2639] eta: 1:36:34 lr: 1.783391209058126e-05 loss: 0.0377 (0.0393) time: 3.0167 data: 0.0078 max mem: 33408 +Epoch: [27] [ 740/2639] eta: 1:36:04 lr: 1.7829131664108366e-05 loss: 0.0404 (0.0394) time: 3.0355 data: 0.0076 max mem: 33408 +Epoch: [27] [ 750/2639] eta: 1:35:33 lr: 1.7824351095214636e-05 loss: 0.0379 (0.0393) time: 3.0327 data: 0.0078 max mem: 33408 +Epoch: [27] [ 760/2639] eta: 1:35:01 lr: 1.781957038385338e-05 loss: 0.0329 (0.0393) time: 2.9984 data: 0.0077 max mem: 33408 +Epoch: [27] [ 770/2639] eta: 1:34:31 lr: 1.781478952997789e-05 loss: 0.0361 (0.0393) time: 3.0037 data: 0.0076 max mem: 33408 +Epoch: [27] [ 780/2639] eta: 1:34:00 lr: 1.7810008533541407e-05 loss: 0.0399 (0.0393) time: 3.0299 data: 0.0076 max mem: 33408 +Epoch: [27] [ 790/2639] eta: 1:33:29 lr: 1.780522739449717e-05 loss: 0.0408 (0.0393) time: 3.0187 data: 0.0079 max mem: 33408 +Epoch: [27] [ 800/2639] eta: 1:33:00 lr: 1.7800446112798357e-05 loss: 0.0306 (0.0393) time: 3.0518 data: 0.0083 max mem: 33408 +Epoch: [27] [ 810/2639] eta: 1:32:29 lr: 1.779566468839815e-05 loss: 0.0329 (0.0393) time: 3.0496 data: 0.0079 max mem: 33408 +Epoch: [27] [ 820/2639] eta: 1:31:58 lr: 1.779088312124968e-05 loss: 0.0378 (0.0394) time: 2.9961 data: 0.0080 max mem: 33408 +Epoch: [27] [ 830/2639] eta: 1:31:27 lr: 1.778610141130605e-05 loss: 0.0384 (0.0394) time: 2.9984 data: 0.0081 max mem: 33408 +Epoch: [27] [ 840/2639] eta: 1:30:57 lr: 1.7781319558520343e-05 loss: 0.0361 (0.0394) time: 3.0359 data: 0.0079 max mem: 33408 +Epoch: [27] [ 850/2639] eta: 1:30:26 lr: 1.7776537562845607e-05 loss: 0.0362 (0.0394) time: 3.0296 data: 0.0077 max mem: 33408 +Epoch: [27] [ 860/2639] eta: 1:29:56 lr: 1.7771755424234854e-05 loss: 0.0401 (0.0394) time: 3.0202 data: 0.0076 max mem: 33408 +Epoch: [27] [ 870/2639] eta: 1:29:26 lr: 1.7766973142641084e-05 loss: 0.0440 (0.0394) time: 3.0309 data: 0.0075 max mem: 33408 +Epoch: [27] [ 880/2639] eta: 1:28:55 lr: 1.7762190718017246e-05 loss: 0.0395 (0.0394) time: 3.0206 data: 0.0078 max mem: 33408 +Epoch: [27] [ 890/2639] eta: 1:28:24 lr: 1.775740815031628e-05 loss: 0.0383 (0.0394) time: 3.0208 data: 0.0081 max mem: 33408 +Epoch: [27] [ 900/2639] eta: 1:27:54 lr: 1.7752625439491076e-05 loss: 0.0301 (0.0393) time: 3.0278 data: 0.0081 max mem: 33408 +Epoch: [27] [ 910/2639] eta: 1:27:24 lr: 1.7747842585494518e-05 loss: 0.0335 (0.0393) time: 3.0321 data: 0.0082 max mem: 33408 +Epoch: [27] [ 920/2639] eta: 1:26:53 lr: 1.7743059588279433e-05 loss: 0.0392 (0.0394) time: 3.0155 data: 0.0082 max mem: 33408 +Epoch: [27] [ 930/2639] eta: 1:26:23 lr: 1.7738276447798642e-05 loss: 0.0365 (0.0393) time: 3.0195 data: 0.0081 max mem: 33408 +Epoch: [27] [ 940/2639] eta: 1:25:50 lr: 1.773349316400493e-05 loss: 0.0365 (0.0394) time: 2.9836 data: 0.0077 max mem: 33408 +Epoch: [27] [ 950/2639] eta: 1:25:21 lr: 1.7728709736851037e-05 loss: 0.0397 (0.0394) time: 2.9943 data: 0.0080 max mem: 33408 +Epoch: [27] [ 960/2639] eta: 1:24:50 lr: 1.77239261662897e-05 loss: 0.0390 (0.0395) time: 3.0439 data: 0.0081 max mem: 33408 +Epoch: [27] [ 970/2639] eta: 1:24:20 lr: 1.77191424522736e-05 loss: 0.0377 (0.0395) time: 3.0369 data: 0.0076 max mem: 33408 +Epoch: [27] [ 980/2639] eta: 1:23:50 lr: 1.771435859475541e-05 loss: 0.0273 (0.0395) time: 3.0598 data: 0.0075 max mem: 33408 +Epoch: [27] [ 990/2639] eta: 1:23:20 lr: 1.7709574593687754e-05 loss: 0.0313 (0.0395) time: 3.0476 data: 0.0076 max mem: 33408 +Epoch: [27] [1000/2639] eta: 1:22:50 lr: 1.7704790449023244e-05 loss: 0.0394 (0.0396) time: 3.0402 data: 0.0077 max mem: 33408 +Epoch: [27] [1010/2639] eta: 1:22:19 lr: 1.7700006160714445e-05 loss: 0.0391 (0.0397) time: 3.0158 data: 0.0083 max mem: 33408 +Epoch: [27] [1020/2639] eta: 1:21:49 lr: 1.7695221728713907e-05 loss: 0.0389 (0.0397) time: 3.0274 data: 0.0082 max mem: 33408 +Epoch: [27] [1030/2639] eta: 1:21:19 lr: 1.7690437152974134e-05 loss: 0.0328 (0.0397) time: 3.0482 data: 0.0077 max mem: 33408 +Epoch: [27] [1040/2639] eta: 1:20:49 lr: 1.7685652433447624e-05 loss: 0.0340 (0.0398) time: 3.0327 data: 0.0077 max mem: 33408 +Epoch: [27] [1050/2639] eta: 1:20:18 lr: 1.768086757008682e-05 loss: 0.0342 (0.0397) time: 3.0327 data: 0.0080 max mem: 33408 +Epoch: [27] [1060/2639] eta: 1:19:47 lr: 1.767608256284415e-05 loss: 0.0340 (0.0397) time: 3.0094 data: 0.0085 max mem: 33408 +Epoch: [27] [1070/2639] eta: 1:19:17 lr: 1.7671297411672005e-05 loss: 0.0387 (0.0397) time: 3.0120 data: 0.0081 max mem: 33408 +Epoch: [27] [1080/2639] eta: 1:18:46 lr: 1.7666512116522755e-05 loss: 0.0389 (0.0398) time: 3.0064 data: 0.0075 max mem: 33408 +Epoch: [27] [1090/2639] eta: 1:18:15 lr: 1.766172667734872e-05 loss: 0.0383 (0.0397) time: 2.9988 data: 0.0078 max mem: 33408 +Epoch: [27] [1100/2639] eta: 1:17:45 lr: 1.7656941094102215e-05 loss: 0.0261 (0.0396) time: 3.0097 data: 0.0077 max mem: 33408 +Epoch: [27] [1110/2639] eta: 1:17:14 lr: 1.765215536673551e-05 loss: 0.0319 (0.0396) time: 3.0113 data: 0.0075 max mem: 33408 +Epoch: [27] [1120/2639] eta: 1:16:43 lr: 1.7647369495200847e-05 loss: 0.0434 (0.0396) time: 3.0077 data: 0.0078 max mem: 33408 +Epoch: [27] [1130/2639] eta: 1:16:14 lr: 1.7642583479450436e-05 loss: 0.0428 (0.0397) time: 3.0446 data: 0.0082 max mem: 33408 +Epoch: [27] [1140/2639] eta: 1:15:43 lr: 1.7637797319436468e-05 loss: 0.0412 (0.0397) time: 3.0598 data: 0.0080 max mem: 33408 +Epoch: [27] [1150/2639] eta: 1:15:13 lr: 1.7633011015111084e-05 loss: 0.0372 (0.0396) time: 3.0341 data: 0.0073 max mem: 33408 +Epoch: [27] [1160/2639] eta: 1:14:43 lr: 1.762822456642641e-05 loss: 0.0303 (0.0396) time: 3.0453 data: 0.0075 max mem: 33408 +Epoch: [27] [1170/2639] eta: 1:14:12 lr: 1.7623437973334544e-05 loss: 0.0355 (0.0396) time: 3.0100 data: 0.0079 max mem: 33408 +Epoch: [27] [1180/2639] eta: 1:13:42 lr: 1.7618651235787535e-05 loss: 0.0365 (0.0395) time: 3.0098 data: 0.0076 max mem: 33408 +Epoch: [27] [1190/2639] eta: 1:13:12 lr: 1.761386435373743e-05 loss: 0.0343 (0.0395) time: 3.0587 data: 0.0077 max mem: 33408 +Epoch: [27] [1200/2639] eta: 1:12:41 lr: 1.760907732713621e-05 loss: 0.0316 (0.0395) time: 3.0279 data: 0.0079 max mem: 33408 +Epoch: [27] [1210/2639] eta: 1:12:11 lr: 1.760429015593586e-05 loss: 0.0325 (0.0395) time: 3.0204 data: 0.0079 max mem: 33408 +Epoch: [27] [1220/2639] eta: 1:11:42 lr: 1.7599502840088312e-05 loss: 0.0341 (0.0395) time: 3.0648 data: 0.0078 max mem: 33408 +Epoch: [27] [1230/2639] eta: 1:11:11 lr: 1.7594715379545483e-05 loss: 0.0341 (0.0394) time: 3.0692 data: 0.0076 max mem: 33408 +Epoch: [27] [1240/2639] eta: 1:10:41 lr: 1.7589927774259237e-05 loss: 0.0310 (0.0394) time: 3.0369 data: 0.0078 max mem: 33408 +Epoch: [27] [1250/2639] eta: 1:10:11 lr: 1.7585140024181437e-05 loss: 0.0324 (0.0393) time: 3.0251 data: 0.0080 max mem: 33408 +Epoch: [27] [1260/2639] eta: 1:09:40 lr: 1.7580352129263886e-05 loss: 0.0334 (0.0393) time: 3.0331 data: 0.0079 max mem: 33408 +Epoch: [27] [1270/2639] eta: 1:09:09 lr: 1.7575564089458385e-05 loss: 0.0356 (0.0393) time: 2.9941 data: 0.0080 max mem: 33408 +Epoch: [27] [1280/2639] eta: 1:08:40 lr: 1.7570775904716673e-05 loss: 0.0368 (0.0393) time: 3.0254 data: 0.0082 max mem: 33408 +Epoch: [27] [1290/2639] eta: 1:08:10 lr: 1.7565987574990493e-05 loss: 0.0325 (0.0393) time: 3.0801 data: 0.0081 max mem: 33408 +Epoch: [27] [1300/2639] eta: 1:07:39 lr: 1.7561199100231527e-05 loss: 0.0320 (0.0393) time: 3.0314 data: 0.0080 max mem: 33408 +Epoch: [27] [1310/2639] eta: 1:07:08 lr: 1.755641048039145e-05 loss: 0.0327 (0.0393) time: 2.9951 data: 0.0078 max mem: 33408 +Epoch: [27] [1320/2639] eta: 1:06:38 lr: 1.755162171542188e-05 loss: 0.0411 (0.0394) time: 3.0354 data: 0.0078 max mem: 33408 +Epoch: [27] [1330/2639] eta: 1:06:09 lr: 1.7546832805274433e-05 loss: 0.0355 (0.0393) time: 3.1027 data: 0.0077 max mem: 33408 +Epoch: [27] [1340/2639] eta: 1:05:39 lr: 1.754204374990067e-05 loss: 0.0355 (0.0394) time: 3.1014 data: 0.0075 max mem: 33408 +Epoch: [27] [1350/2639] eta: 1:05:09 lr: 1.753725454925214e-05 loss: 0.0422 (0.0394) time: 3.0491 data: 0.0075 max mem: 33408 +Epoch: [27] [1360/2639] eta: 1:04:38 lr: 1.7532465203280345e-05 loss: 0.0408 (0.0394) time: 3.0025 data: 0.0076 max mem: 33408 +Epoch: [27] [1370/2639] eta: 1:04:08 lr: 1.7527675711936772e-05 loss: 0.0331 (0.0393) time: 3.0310 data: 0.0075 max mem: 33408 +Epoch: [27] [1380/2639] eta: 1:03:38 lr: 1.7522886075172862e-05 loss: 0.0353 (0.0393) time: 3.0520 data: 0.0075 max mem: 33408 +Epoch: [27] [1390/2639] eta: 1:03:07 lr: 1.751809629294004e-05 loss: 0.0371 (0.0393) time: 3.0383 data: 0.0077 max mem: 33408 +Epoch: [27] [1400/2639] eta: 1:02:37 lr: 1.7513306365189677e-05 loss: 0.0360 (0.0393) time: 3.0503 data: 0.0079 max mem: 33408 +Epoch: [27] [1410/2639] eta: 1:02:07 lr: 1.750851629187314e-05 loss: 0.0357 (0.0393) time: 3.0335 data: 0.0078 max mem: 33408 +Epoch: [27] [1420/2639] eta: 1:01:37 lr: 1.7503726072941755e-05 loss: 0.0369 (0.0393) time: 3.0578 data: 0.0077 max mem: 33408 +Epoch: [27] [1430/2639] eta: 1:01:07 lr: 1.7498935708346805e-05 loss: 0.0369 (0.0393) time: 3.0887 data: 0.0077 max mem: 33408 +Epoch: [27] [1440/2639] eta: 1:00:36 lr: 1.7494145198039565e-05 loss: 0.0416 (0.0394) time: 3.0238 data: 0.0075 max mem: 33408 +Epoch: [27] [1450/2639] eta: 1:00:06 lr: 1.7489354541971246e-05 loss: 0.0416 (0.0394) time: 3.0074 data: 0.0076 max mem: 33408 +Epoch: [27] [1460/2639] eta: 0:59:35 lr: 1.7484563740093067e-05 loss: 0.0354 (0.0393) time: 3.0287 data: 0.0078 max mem: 33408 +Epoch: [27] [1470/2639] eta: 0:59:05 lr: 1.747977279235618e-05 loss: 0.0366 (0.0393) time: 2.9992 data: 0.0082 max mem: 33408 +Epoch: [27] [1480/2639] eta: 0:58:34 lr: 1.7474981698711735e-05 loss: 0.0401 (0.0393) time: 2.9917 data: 0.0086 max mem: 33408 +Epoch: [27] [1490/2639] eta: 0:58:04 lr: 1.7470190459110824e-05 loss: 0.0359 (0.0395) time: 3.0232 data: 0.0083 max mem: 33408 +Epoch: [27] [1500/2639] eta: 0:57:33 lr: 1.7465399073504538e-05 loss: 0.0373 (0.0395) time: 3.0125 data: 0.0080 max mem: 33408 +Epoch: [27] [1510/2639] eta: 0:57:02 lr: 1.7460607541843903e-05 loss: 0.0373 (0.0395) time: 2.9689 data: 0.0081 max mem: 33408 +Epoch: [27] [1520/2639] eta: 0:56:32 lr: 1.7455815864079947e-05 loss: 0.0355 (0.0395) time: 3.0080 data: 0.0082 max mem: 33408 +Epoch: [27] [1530/2639] eta: 0:56:02 lr: 1.7451024040163634e-05 loss: 0.0336 (0.0395) time: 3.0213 data: 0.0081 max mem: 33408 +Epoch: [27] [1540/2639] eta: 0:55:31 lr: 1.7446232070045928e-05 loss: 0.0336 (0.0395) time: 3.0066 data: 0.0078 max mem: 33408 +Epoch: [27] [1550/2639] eta: 0:55:00 lr: 1.744143995367773e-05 loss: 0.0342 (0.0395) time: 2.9942 data: 0.0074 max mem: 33408 +Epoch: [27] [1560/2639] eta: 0:54:30 lr: 1.7436647691009946e-05 loss: 0.0403 (0.0395) time: 3.0028 data: 0.0074 max mem: 33408 +Epoch: [27] [1570/2639] eta: 0:54:00 lr: 1.743185528199341e-05 loss: 0.0435 (0.0395) time: 3.0539 data: 0.0075 max mem: 33408 +Epoch: [27] [1580/2639] eta: 0:53:30 lr: 1.7427062726578964e-05 loss: 0.0349 (0.0395) time: 3.0410 data: 0.0076 max mem: 33408 +Epoch: [27] [1590/2639] eta: 0:52:59 lr: 1.742227002471738e-05 loss: 0.0340 (0.0395) time: 3.0270 data: 0.0079 max mem: 33408 +Epoch: [27] [1600/2639] eta: 0:52:29 lr: 1.7417477176359437e-05 loss: 0.0320 (0.0395) time: 3.0574 data: 0.0082 max mem: 33408 +Epoch: [27] [1610/2639] eta: 0:51:59 lr: 1.7412684181455843e-05 loss: 0.0334 (0.0395) time: 3.0100 data: 0.0079 max mem: 33408 +Epoch: [27] [1620/2639] eta: 0:51:28 lr: 1.7407891039957318e-05 loss: 0.0355 (0.0395) time: 2.9499 data: 0.0077 max mem: 33408 +Epoch: [27] [1630/2639] eta: 0:50:57 lr: 1.7403097751814502e-05 loss: 0.0390 (0.0395) time: 2.9778 data: 0.0078 max mem: 33408 +Epoch: [27] [1640/2639] eta: 0:50:27 lr: 1.739830431697805e-05 loss: 0.0396 (0.0395) time: 3.0149 data: 0.0077 max mem: 33408 +Epoch: [27] [1650/2639] eta: 0:49:56 lr: 1.7393510735398544e-05 loss: 0.0344 (0.0395) time: 2.9932 data: 0.0077 max mem: 33408 +Epoch: [27] [1660/2639] eta: 0:49:26 lr: 1.7388717007026567e-05 loss: 0.0319 (0.0394) time: 2.9747 data: 0.0076 max mem: 33408 +Epoch: [27] [1670/2639] eta: 0:48:55 lr: 1.7383923131812656e-05 loss: 0.0322 (0.0394) time: 3.0001 data: 0.0076 max mem: 33408 +Epoch: [27] [1680/2639] eta: 0:48:25 lr: 1.737912910970731e-05 loss: 0.0322 (0.0394) time: 3.0349 data: 0.0075 max mem: 33408 +Epoch: [27] [1690/2639] eta: 0:47:55 lr: 1.7374334940661012e-05 loss: 0.0323 (0.0394) time: 3.0285 data: 0.0075 max mem: 33408 +Epoch: [27] [1700/2639] eta: 0:47:24 lr: 1.73695406246242e-05 loss: 0.0381 (0.0395) time: 3.0184 data: 0.0078 max mem: 33408 +Epoch: [27] [1710/2639] eta: 0:46:54 lr: 1.736474616154728e-05 loss: 0.0398 (0.0395) time: 3.0510 data: 0.0078 max mem: 33408 +Epoch: [27] [1720/2639] eta: 0:46:24 lr: 1.7359951551380636e-05 loss: 0.0301 (0.0394) time: 3.0633 data: 0.0075 max mem: 33408 +Epoch: [27] [1730/2639] eta: 0:45:54 lr: 1.7355156794074613e-05 loss: 0.0322 (0.0395) time: 3.0317 data: 0.0074 max mem: 33408 +Epoch: [27] [1740/2639] eta: 0:45:23 lr: 1.7350361889579523e-05 loss: 0.0384 (0.0395) time: 2.9846 data: 0.0078 max mem: 33408 +Epoch: [27] [1750/2639] eta: 0:44:53 lr: 1.7345566837845654e-05 loss: 0.0383 (0.0395) time: 3.0159 data: 0.0080 max mem: 33408 +Epoch: [27] [1760/2639] eta: 0:44:23 lr: 1.7340771638823246e-05 loss: 0.0322 (0.0394) time: 3.0607 data: 0.0082 max mem: 33408 +Epoch: [27] [1770/2639] eta: 0:43:53 lr: 1.7335976292462532e-05 loss: 0.0307 (0.0395) time: 3.0699 data: 0.0078 max mem: 33408 +Epoch: [27] [1780/2639] eta: 0:43:22 lr: 1.7331180798713685e-05 loss: 0.0389 (0.0396) time: 3.0382 data: 0.0074 max mem: 33408 +Epoch: [27] [1790/2639] eta: 0:42:52 lr: 1.7326385157526867e-05 loss: 0.0374 (0.0396) time: 3.0571 data: 0.0076 max mem: 33408 +Epoch: [27] [1800/2639] eta: 0:42:22 lr: 1.7321589368852193e-05 loss: 0.0383 (0.0396) time: 3.0502 data: 0.0075 max mem: 33408 +Epoch: [27] [1810/2639] eta: 0:41:52 lr: 1.731679343263976e-05 loss: 0.0328 (0.0396) time: 3.0067 data: 0.0077 max mem: 33408 +Epoch: [27] [1820/2639] eta: 0:41:21 lr: 1.7311997348839618e-05 loss: 0.0321 (0.0395) time: 3.0483 data: 0.0078 max mem: 33408 +Epoch: [27] [1830/2639] eta: 0:40:51 lr: 1.7307201117401797e-05 loss: 0.0321 (0.0395) time: 3.0733 data: 0.0078 max mem: 33408 +Epoch: [27] [1840/2639] eta: 0:40:21 lr: 1.730240473827629e-05 loss: 0.0326 (0.0395) time: 3.0344 data: 0.0079 max mem: 33408 +Epoch: [27] [1850/2639] eta: 0:39:51 lr: 1.729760821141305e-05 loss: 0.0342 (0.0395) time: 3.0363 data: 0.0078 max mem: 33408 +Epoch: [27] [1860/2639] eta: 0:39:20 lr: 1.729281153676201e-05 loss: 0.0321 (0.0395) time: 3.0350 data: 0.0078 max mem: 33408 +Epoch: [27] [1870/2639] eta: 0:38:50 lr: 1.728801471427307e-05 loss: 0.0350 (0.0395) time: 3.0338 data: 0.0076 max mem: 33408 +Epoch: [27] [1880/2639] eta: 0:38:20 lr: 1.7283217743896085e-05 loss: 0.0354 (0.0395) time: 3.0755 data: 0.0077 max mem: 33408 +Epoch: [27] [1890/2639] eta: 0:37:50 lr: 1.7278420625580895e-05 loss: 0.0334 (0.0395) time: 3.0470 data: 0.0078 max mem: 33408 +Epoch: [27] [1900/2639] eta: 0:37:20 lr: 1.727362335927728e-05 loss: 0.0326 (0.0395) time: 3.0605 data: 0.0074 max mem: 33408 +Epoch: [27] [1910/2639] eta: 0:36:49 lr: 1.7268825944935026e-05 loss: 0.0324 (0.0395) time: 3.0756 data: 0.0078 max mem: 33408 +Epoch: [27] [1920/2639] eta: 0:36:19 lr: 1.726402838250386e-05 loss: 0.0334 (0.0394) time: 3.0101 data: 0.0079 max mem: 33408 +Epoch: [27] [1930/2639] eta: 0:35:48 lr: 1.7259230671933474e-05 loss: 0.0340 (0.0394) time: 2.9833 data: 0.0075 max mem: 33408 +Epoch: [27] [1940/2639] eta: 0:35:18 lr: 1.725443281317355e-05 loss: 0.0340 (0.0394) time: 3.0036 data: 0.0078 max mem: 33408 +Epoch: [27] [1950/2639] eta: 0:34:48 lr: 1.7249634806173706e-05 loss: 0.0324 (0.0394) time: 3.0303 data: 0.0079 max mem: 33408 +Epoch: [27] [1960/2639] eta: 0:34:18 lr: 1.7244836650883562e-05 loss: 0.0363 (0.0394) time: 3.0466 data: 0.0078 max mem: 33408 +Epoch: [27] [1970/2639] eta: 0:33:47 lr: 1.724003834725267e-05 loss: 0.0342 (0.0394) time: 3.0507 data: 0.0073 max mem: 33408 +Epoch: [27] [1980/2639] eta: 0:33:17 lr: 1.7235239895230583e-05 loss: 0.0296 (0.0394) time: 3.0744 data: 0.0071 max mem: 33408 +Epoch: [27] [1990/2639] eta: 0:32:47 lr: 1.7230441294766794e-05 loss: 0.0348 (0.0394) time: 3.0330 data: 0.0077 max mem: 33408 +Epoch: [27] [2000/2639] eta: 0:32:17 lr: 1.7225642545810787e-05 loss: 0.0372 (0.0394) time: 3.0353 data: 0.0077 max mem: 33408 +Epoch: [27] [2010/2639] eta: 0:31:46 lr: 1.722084364831198e-05 loss: 0.0390 (0.0394) time: 3.0556 data: 0.0073 max mem: 33408 +Epoch: [27] [2020/2639] eta: 0:31:16 lr: 1.7216044602219798e-05 loss: 0.0406 (0.0394) time: 3.0265 data: 0.0076 max mem: 33408 +Epoch: [27] [2030/2639] eta: 0:30:46 lr: 1.7211245407483602e-05 loss: 0.0384 (0.0394) time: 3.0643 data: 0.0077 max mem: 33408 +Epoch: [27] [2040/2639] eta: 0:30:16 lr: 1.720644606405274e-05 loss: 0.0333 (0.0394) time: 3.0856 data: 0.0081 max mem: 33408 +Epoch: [27] [2050/2639] eta: 0:29:45 lr: 1.7201646571876514e-05 loss: 0.0333 (0.0393) time: 3.0509 data: 0.0081 max mem: 33408 +Epoch: [27] [2060/2639] eta: 0:29:15 lr: 1.7196846930904202e-05 loss: 0.0311 (0.0393) time: 3.0020 data: 0.0077 max mem: 33408 +Epoch: [27] [2070/2639] eta: 0:28:44 lr: 1.7192047141085036e-05 loss: 0.0355 (0.0393) time: 2.9949 data: 0.0076 max mem: 33408 +Epoch: [27] [2080/2639] eta: 0:28:14 lr: 1.7187247202368235e-05 loss: 0.0355 (0.0395) time: 2.9855 data: 0.0073 max mem: 33408 +Epoch: [27] [2090/2639] eta: 0:27:44 lr: 1.718244711470296e-05 loss: 0.0300 (0.0395) time: 2.9841 data: 0.0073 max mem: 33408 +Epoch: [27] [2100/2639] eta: 0:27:13 lr: 1.7177646878038367e-05 loss: 0.0337 (0.0395) time: 3.0380 data: 0.0075 max mem: 33408 +Epoch: [27] [2110/2639] eta: 0:26:43 lr: 1.7172846492323554e-05 loss: 0.0363 (0.0395) time: 3.0690 data: 0.0079 max mem: 33408 +Epoch: [27] [2120/2639] eta: 0:26:13 lr: 1.71680459575076e-05 loss: 0.0349 (0.0396) time: 3.0521 data: 0.0080 max mem: 33408 +Epoch: [27] [2130/2639] eta: 0:25:43 lr: 1.7163245273539548e-05 loss: 0.0356 (0.0396) time: 3.0574 data: 0.0078 max mem: 33408 +Epoch: [27] [2140/2639] eta: 0:25:12 lr: 1.7158444440368403e-05 loss: 0.0427 (0.0396) time: 3.0877 data: 0.0078 max mem: 33408 +Epoch: [27] [2150/2639] eta: 0:24:42 lr: 1.7153643457943144e-05 loss: 0.0439 (0.0396) time: 3.0201 data: 0.0079 max mem: 33408 +Epoch: [27] [2160/2639] eta: 0:24:11 lr: 1.714884232621271e-05 loss: 0.0378 (0.0396) time: 2.9455 data: 0.0078 max mem: 33408 +Epoch: [27] [2170/2639] eta: 0:23:41 lr: 1.7144041045126015e-05 loss: 0.0309 (0.0396) time: 2.9415 data: 0.0078 max mem: 33408 +Epoch: [27] [2180/2639] eta: 0:23:11 lr: 1.7139239614631925e-05 loss: 0.0308 (0.0395) time: 2.9861 data: 0.0081 max mem: 33408 +Epoch: [27] [2190/2639] eta: 0:22:40 lr: 1.713443803467929e-05 loss: 0.0330 (0.0395) time: 3.0491 data: 0.0082 max mem: 33408 +Epoch: [27] [2200/2639] eta: 0:22:10 lr: 1.7129636305216916e-05 loss: 0.0361 (0.0395) time: 3.0417 data: 0.0083 max mem: 33408 +Epoch: [27] [2210/2639] eta: 0:21:40 lr: 1.7124834426193578e-05 loss: 0.0349 (0.0395) time: 3.0532 data: 0.0080 max mem: 33408 +Epoch: [27] [2220/2639] eta: 0:21:10 lr: 1.7120032397558014e-05 loss: 0.0370 (0.0395) time: 3.0906 data: 0.0079 max mem: 33408 +Epoch: [27] [2230/2639] eta: 0:20:39 lr: 1.711523021925894e-05 loss: 0.0385 (0.0395) time: 3.0701 data: 0.0080 max mem: 33408 +Epoch: [27] [2240/2639] eta: 0:20:09 lr: 1.711042789124502e-05 loss: 0.0333 (0.0395) time: 3.0602 data: 0.0080 max mem: 33408 +Epoch: [27] [2250/2639] eta: 0:19:39 lr: 1.7105625413464902e-05 loss: 0.0392 (0.0395) time: 3.0900 data: 0.0076 max mem: 33408 +Epoch: [27] [2260/2639] eta: 0:19:09 lr: 1.710082278586719e-05 loss: 0.0392 (0.0395) time: 3.0803 data: 0.0073 max mem: 33408 +Epoch: [27] [2270/2639] eta: 0:18:38 lr: 1.709602000840046e-05 loss: 0.0327 (0.0395) time: 3.0493 data: 0.0074 max mem: 33408 +Epoch: [27] [2280/2639] eta: 0:18:08 lr: 1.7091217081013246e-05 loss: 0.0384 (0.0395) time: 3.0441 data: 0.0081 max mem: 33408 +Epoch: [27] [2290/2639] eta: 0:17:38 lr: 1.7086414003654064e-05 loss: 0.0345 (0.0395) time: 3.0220 data: 0.0081 max mem: 33408 +Epoch: [27] [2300/2639] eta: 0:17:07 lr: 1.7081610776271374e-05 loss: 0.0325 (0.0395) time: 2.9817 data: 0.0078 max mem: 33408 +Epoch: [27] [2310/2639] eta: 0:16:37 lr: 1.7076807398813623e-05 loss: 0.0327 (0.0395) time: 2.9873 data: 0.0081 max mem: 33408 +Epoch: [27] [2320/2639] eta: 0:16:07 lr: 1.707200387122921e-05 loss: 0.0327 (0.0395) time: 3.0308 data: 0.0077 max mem: 33408 +Epoch: [27] [2330/2639] eta: 0:15:36 lr: 1.706720019346651e-05 loss: 0.0376 (0.0395) time: 3.0201 data: 0.0078 max mem: 33408 +Epoch: [27] [2340/2639] eta: 0:15:06 lr: 1.7062396365473853e-05 loss: 0.0365 (0.0395) time: 3.0037 data: 0.0080 max mem: 33408 +Epoch: [27] [2350/2639] eta: 0:14:36 lr: 1.7057592387199552e-05 loss: 0.0377 (0.0395) time: 3.0147 data: 0.0081 max mem: 33408 +Epoch: [27] [2360/2639] eta: 0:14:05 lr: 1.7052788258591865e-05 loss: 0.0390 (0.0395) time: 2.9790 data: 0.0079 max mem: 33408 +Epoch: [27] [2370/2639] eta: 0:13:35 lr: 1.704798397959904e-05 loss: 0.0336 (0.0395) time: 2.9831 data: 0.0077 max mem: 33408 +Epoch: [27] [2380/2639] eta: 0:13:05 lr: 1.7043179550169257e-05 loss: 0.0336 (0.0395) time: 3.0117 data: 0.0078 max mem: 33408 +Epoch: [27] [2390/2639] eta: 0:12:34 lr: 1.7038374970250706e-05 loss: 0.0330 (0.0394) time: 3.0151 data: 0.0080 max mem: 33408 +Epoch: [27] [2400/2639] eta: 0:12:04 lr: 1.70335702397915e-05 loss: 0.0345 (0.0395) time: 3.0224 data: 0.0078 max mem: 33408 +Epoch: [27] [2410/2639] eta: 0:11:34 lr: 1.7028765358739747e-05 loss: 0.0411 (0.0395) time: 3.0175 data: 0.0078 max mem: 33408 +Epoch: [27] [2420/2639] eta: 0:11:03 lr: 1.702396032704352e-05 loss: 0.0315 (0.0395) time: 2.9904 data: 0.0078 max mem: 33408 +Epoch: [27] [2430/2639] eta: 0:10:33 lr: 1.7019155144650827e-05 loss: 0.0328 (0.0395) time: 2.9656 data: 0.0081 max mem: 33408 +Epoch: [27] [2440/2639] eta: 0:10:03 lr: 1.7014349811509685e-05 loss: 0.0408 (0.0395) time: 3.0050 data: 0.0084 max mem: 33408 +Epoch: [27] [2450/2639] eta: 0:09:32 lr: 1.700954432756804e-05 loss: 0.0398 (0.0395) time: 3.0323 data: 0.0081 max mem: 33408 +Epoch: [27] [2460/2639] eta: 0:09:02 lr: 1.700473869277383e-05 loss: 0.0346 (0.0395) time: 3.0381 data: 0.0079 max mem: 33408 +Epoch: [27] [2470/2639] eta: 0:08:32 lr: 1.6999932907074943e-05 loss: 0.0369 (0.0395) time: 3.0619 data: 0.0082 max mem: 33408 +Epoch: [27] [2480/2639] eta: 0:08:01 lr: 1.699512697041924e-05 loss: 0.0377 (0.0395) time: 3.0702 data: 0.0080 max mem: 33408 +Epoch: [27] [2490/2639] eta: 0:07:31 lr: 1.6990320882754536e-05 loss: 0.0359 (0.0395) time: 3.0513 data: 0.0076 max mem: 33408 +Epoch: [27] [2500/2639] eta: 0:07:01 lr: 1.6985514644028637e-05 loss: 0.0359 (0.0395) time: 3.0257 data: 0.0077 max mem: 33408 +Epoch: [27] [2510/2639] eta: 0:06:30 lr: 1.698070825418928e-05 loss: 0.0430 (0.0395) time: 3.0392 data: 0.0077 max mem: 33408 +Epoch: [27] [2520/2639] eta: 0:06:00 lr: 1.6975901713184202e-05 loss: 0.0433 (0.0395) time: 3.0323 data: 0.0082 max mem: 33408 +Epoch: [27] [2530/2639] eta: 0:05:30 lr: 1.697109502096107e-05 loss: 0.0368 (0.0395) time: 3.0040 data: 0.0083 max mem: 33408 +Epoch: [27] [2540/2639] eta: 0:05:00 lr: 1.696628817746756e-05 loss: 0.0306 (0.0395) time: 3.0047 data: 0.0079 max mem: 33408 +Epoch: [27] [2550/2639] eta: 0:04:29 lr: 1.696148118265127e-05 loss: 0.0306 (0.0395) time: 2.9943 data: 0.0081 max mem: 33408 +Epoch: [27] [2560/2639] eta: 0:03:59 lr: 1.6956674036459786e-05 loss: 0.0322 (0.0395) time: 2.9957 data: 0.0078 max mem: 33408 +Epoch: [27] [2570/2639] eta: 0:03:29 lr: 1.695186673884066e-05 loss: 0.0340 (0.0395) time: 3.0013 data: 0.0075 max mem: 33408 +Epoch: [27] [2580/2639] eta: 0:02:58 lr: 1.6947059289741406e-05 loss: 0.0354 (0.0395) time: 2.9754 data: 0.0076 max mem: 33408 +Epoch: [27] [2590/2639] eta: 0:02:28 lr: 1.6942251689109497e-05 loss: 0.0336 (0.0394) time: 2.9913 data: 0.0078 max mem: 33408 +Epoch: [27] [2600/2639] eta: 0:01:58 lr: 1.693744393689238e-05 loss: 0.0329 (0.0394) time: 3.0393 data: 0.0082 max mem: 33408 +Epoch: [27] [2610/2639] eta: 0:01:27 lr: 1.693263603303746e-05 loss: 0.0348 (0.0395) time: 3.0490 data: 0.0085 max mem: 33408 +Epoch: [27] [2620/2639] eta: 0:00:57 lr: 1.6927827977492113e-05 loss: 0.0340 (0.0394) time: 3.0336 data: 0.0087 max mem: 33408 +Epoch: [27] [2630/2639] eta: 0:00:27 lr: 1.6923019770203673e-05 loss: 0.0306 (0.0394) time: 3.0438 data: 0.0084 max mem: 33408 +Epoch: [27] Total time: 2:13:38 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 2:05:26 time: 2.9253 data: 2.7799 max mem: 33408 +Test: [ 100/2573] eta: 0:04:26 time: 0.0805 data: 0.0015 max mem: 33408 +Test: [ 200/2573] eta: 0:03:44 time: 0.0799 data: 0.0015 max mem: 33408 +Test: [ 300/2573] eta: 0:03:23 time: 0.0815 data: 0.0015 max mem: 33408 +Test: [ 400/2573] eta: 0:03:09 time: 0.0820 data: 0.0014 max mem: 33408 +Test: [ 500/2573] eta: 0:02:57 time: 0.0802 data: 0.0016 max mem: 33408 +Test: [ 600/2573] eta: 0:02:47 time: 0.0805 data: 0.0014 max mem: 33408 +Test: [ 700/2573] eta: 0:02:38 time: 0.0821 data: 0.0014 max mem: 33408 +Test: [ 800/2573] eta: 0:02:29 time: 0.0837 data: 0.0014 max mem: 33408 +Test: [ 900/2573] eta: 0:02:20 time: 0.0802 data: 0.0016 max mem: 33408 +Test: [1000/2573] eta: 0:02:11 time: 0.0805 data: 0.0014 max mem: 33408 +Test: [1100/2573] eta: 0:02:02 time: 0.0812 data: 0.0015 max mem: 33408 +Test: [1200/2573] eta: 0:01:54 time: 0.0807 data: 0.0015 max mem: 33408 +Test: [1300/2573] eta: 0:01:45 time: 0.0805 data: 0.0015 max mem: 33408 +Test: [1400/2573] eta: 0:01:37 time: 0.0814 data: 0.0014 max mem: 33408 +Test: [1500/2573] eta: 0:01:28 time: 0.0812 data: 0.0018 max mem: 33408 +Test: [1600/2573] eta: 0:01:20 time: 0.0846 data: 0.0014 max mem: 33408 +Test: [1700/2573] eta: 0:01:12 time: 0.0790 data: 0.0015 max mem: 33408 +Test: [1800/2573] eta: 0:01:03 time: 0.0828 data: 0.0015 max mem: 33408 +Test: [1900/2573] eta: 0:00:55 time: 0.0799 data: 0.0015 max mem: 33408 +Test: [2000/2573] eta: 0:00:47 time: 0.0800 data: 0.0014 max mem: 33408 +Test: [2100/2573] eta: 0:00:38 time: 0.0817 data: 0.0014 max mem: 33408 +Test: [2200/2573] eta: 0:00:30 time: 0.0821 data: 0.0015 max mem: 33408 +Test: [2300/2573] eta: 0:00:22 time: 0.0829 data: 0.0014 max mem: 33408 +Test: [2400/2573] eta: 0:00:14 time: 0.0796 data: 0.0015 max mem: 33408 +Test: [2500/2573] eta: 0:00:05 time: 0.0811 data: 0.0014 max mem: 33408 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: Total time: 0:03:32 +Final results: +Mean IoU is 64.84 + + precision@0.5 = 72.67 + precision@0.6 = 67.65 + precision@0.7 = 60.23 + precision@0.8 = 49.41 + precision@0.9 = 25.06 + overall IoU = 62.17 + +Average object IoU 64.83580905146263 +Overall IoU 62.172996520996094 +Better epoch: 27 + +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [28] [ 0/2639] eta: 3:48:05 lr: 1.6918692253860188e-05 loss: 0.0471 (0.0471) time: 5.1860 data: 1.8675 max mem: 33408 +Epoch: [28] [ 10/2639] eta: 2:23:21 lr: 1.6913883758114682e-05 loss: 0.0372 (0.0360) time: 3.2716 data: 0.1770 max mem: 33408 +Epoch: [28] [ 20/2639] eta: 2:17:57 lr: 1.6909075110473163e-05 loss: 0.0321 (0.0352) time: 3.0593 data: 0.0076 max mem: 33408 +Epoch: [28] [ 30/2639] eta: 2:14:57 lr: 1.6904266310882847e-05 loss: 0.0334 (0.0355) time: 3.0114 data: 0.0081 max mem: 33408 +Epoch: [28] [ 40/2639] eta: 2:13:41 lr: 1.68994573592909e-05 loss: 0.0364 (0.0361) time: 3.0087 data: 0.0090 max mem: 33408 +Epoch: [28] [ 50/2639] eta: 2:13:01 lr: 1.689464825564445e-05 loss: 0.0349 (0.0366) time: 3.0503 data: 0.0087 max mem: 33408 +Epoch: [28] [ 60/2639] eta: 2:11:58 lr: 1.68898389998906e-05 loss: 0.0357 (0.0369) time: 3.0368 data: 0.0083 max mem: 33408 +Epoch: [28] [ 70/2639] eta: 2:10:57 lr: 1.6885029591976403e-05 loss: 0.0357 (0.0369) time: 2.9964 data: 0.0083 max mem: 33408 +Epoch: [28] [ 80/2639] eta: 2:10:15 lr: 1.68802200318489e-05 loss: 0.0343 (0.0372) time: 3.0050 data: 0.0083 max mem: 33408 +Epoch: [28] [ 90/2639] eta: 2:09:46 lr: 1.6875410319455066e-05 loss: 0.0343 (0.0375) time: 3.0424 data: 0.0081 max mem: 33408 +Epoch: [28] [ 100/2639] eta: 2:09:21 lr: 1.687060045474187e-05 loss: 0.0362 (0.0381) time: 3.0676 data: 0.0079 max mem: 33408 +Epoch: [28] [ 110/2639] eta: 2:08:36 lr: 1.6865790437656225e-05 loss: 0.0342 (0.0376) time: 3.0348 data: 0.0078 max mem: 33408 +Epoch: [28] [ 120/2639] eta: 2:07:55 lr: 1.6860980268145022e-05 loss: 0.0284 (0.0374) time: 2.9971 data: 0.0078 max mem: 33408 +Epoch: [28] [ 130/2639] eta: 2:07:32 lr: 1.6856169946155106e-05 loss: 0.0303 (0.0369) time: 3.0422 data: 0.0078 max mem: 33408 +Epoch: [28] [ 140/2639] eta: 2:06:42 lr: 1.6851359471633302e-05 loss: 0.0320 (0.0372) time: 3.0125 data: 0.0079 max mem: 33408 +Epoch: [28] [ 150/2639] eta: 2:06:04 lr: 1.684654884452638e-05 loss: 0.0318 (0.0369) time: 2.9679 data: 0.0080 max mem: 33408 +Epoch: [28] [ 160/2639] eta: 2:05:37 lr: 1.6841738064781092e-05 loss: 0.0301 (0.0367) time: 3.0286 data: 0.0076 max mem: 33408 +Epoch: [28] [ 170/2639] eta: 2:05:00 lr: 1.683692713234414e-05 loss: 0.0320 (0.0365) time: 3.0301 data: 0.0079 max mem: 33408 +Epoch: [28] [ 180/2639] eta: 2:04:39 lr: 1.68321160471622e-05 loss: 0.0336 (0.0365) time: 3.0515 data: 0.0086 max mem: 33408 +Epoch: [28] [ 190/2639] eta: 2:03:57 lr: 1.6827304809181906e-05 loss: 0.0327 (0.0363) time: 3.0286 data: 0.0086 max mem: 33408 +Epoch: [28] [ 200/2639] eta: 2:03:29 lr: 1.682249341834987e-05 loss: 0.0318 (0.0366) time: 3.0057 data: 0.0081 max mem: 33408 +Epoch: [28] [ 210/2639] eta: 2:02:55 lr: 1.6817681874612646e-05 loss: 0.0317 (0.0366) time: 3.0318 data: 0.0077 max mem: 33408 +Epoch: [28] [ 220/2639] eta: 2:02:21 lr: 1.6812870177916774e-05 loss: 0.0336 (0.0369) time: 3.0059 data: 0.0078 max mem: 33408 +Epoch: [28] [ 230/2639] eta: 2:01:48 lr: 1.680805832820874e-05 loss: 0.0336 (0.0367) time: 3.0031 data: 0.0078 max mem: 33408 +Epoch: [28] [ 240/2639] eta: 2:01:14 lr: 1.680324632543502e-05 loss: 0.0335 (0.0366) time: 3.0002 data: 0.0079 max mem: 33408 +Epoch: [28] [ 250/2639] eta: 2:00:43 lr: 1.6798434169542014e-05 loss: 0.0347 (0.0370) time: 3.0126 data: 0.0083 max mem: 33408 +Epoch: [28] [ 260/2639] eta: 2:00:04 lr: 1.679362186047613e-05 loss: 0.0317 (0.0369) time: 2.9802 data: 0.0080 max mem: 33408 +Epoch: [28] [ 270/2639] eta: 1:59:32 lr: 1.6788809398183706e-05 loss: 0.0341 (0.0369) time: 2.9709 data: 0.0076 max mem: 33408 +Epoch: [28] [ 280/2639] eta: 1:59:00 lr: 1.678399678261106e-05 loss: 0.0325 (0.0367) time: 3.0083 data: 0.0075 max mem: 33408 +Epoch: [28] [ 290/2639] eta: 1:58:28 lr: 1.6779184013704488e-05 loss: 0.0325 (0.0370) time: 3.0072 data: 0.0077 max mem: 33408 +Epoch: [28] [ 300/2639] eta: 1:57:54 lr: 1.6774371091410214e-05 loss: 0.0386 (0.0371) time: 2.9922 data: 0.0077 max mem: 33408 +Epoch: [28] [ 310/2639] eta: 1:57:24 lr: 1.6769558015674454e-05 loss: 0.0386 (0.0372) time: 3.0063 data: 0.0076 max mem: 33408 +Epoch: [28] [ 320/2639] eta: 1:56:55 lr: 1.676474478644338e-05 loss: 0.0385 (0.0373) time: 3.0390 data: 0.0076 max mem: 33408 +Epoch: [28] [ 330/2639] eta: 1:56:26 lr: 1.6759931403663133e-05 loss: 0.0355 (0.0373) time: 3.0422 data: 0.0075 max mem: 33408 +Epoch: [28] [ 340/2639] eta: 1:55:57 lr: 1.6755117867279797e-05 loss: 0.0330 (0.0372) time: 3.0390 data: 0.0078 max mem: 33408 +Epoch: [28] [ 350/2639] eta: 1:55:28 lr: 1.6750304177239458e-05 loss: 0.0364 (0.0374) time: 3.0418 data: 0.0087 max mem: 33408 +Epoch: [28] [ 360/2639] eta: 1:54:58 lr: 1.6745490333488123e-05 loss: 0.0389 (0.0376) time: 3.0412 data: 0.0086 max mem: 33408 +Epoch: [28] [ 370/2639] eta: 1:54:28 lr: 1.6740676335971798e-05 loss: 0.0356 (0.0376) time: 3.0349 data: 0.0082 max mem: 33408 +Epoch: [28] [ 380/2639] eta: 1:53:56 lr: 1.6735862184636428e-05 loss: 0.0338 (0.0376) time: 3.0123 data: 0.0082 max mem: 33408 +Epoch: [28] [ 390/2639] eta: 1:53:27 lr: 1.673104787942794e-05 loss: 0.0345 (0.0377) time: 3.0239 data: 0.0081 max mem: 33408 +Epoch: [28] [ 400/2639] eta: 1:52:57 lr: 1.6726233420292212e-05 loss: 0.0362 (0.0376) time: 3.0428 data: 0.0081 max mem: 33408 +Epoch: [28] [ 410/2639] eta: 1:52:25 lr: 1.6721418807175092e-05 loss: 0.0350 (0.0376) time: 3.0090 data: 0.0081 max mem: 33408 +Epoch: [28] [ 420/2639] eta: 1:51:57 lr: 1.6716604040022384e-05 loss: 0.0318 (0.0374) time: 3.0305 data: 0.0079 max mem: 33408 +Epoch: [28] [ 430/2639] eta: 1:51:26 lr: 1.6711789118779875e-05 loss: 0.0348 (0.0375) time: 3.0408 data: 0.0080 max mem: 33408 +Epoch: [28] [ 440/2639] eta: 1:50:54 lr: 1.6706974043393284e-05 loss: 0.0337 (0.0375) time: 3.0044 data: 0.0079 max mem: 33408 +Epoch: [28] [ 450/2639] eta: 1:50:25 lr: 1.6702158813808326e-05 loss: 0.0327 (0.0376) time: 3.0240 data: 0.0080 max mem: 33408 +Epoch: [28] [ 460/2639] eta: 1:49:53 lr: 1.669734342997066e-05 loss: 0.0339 (0.0375) time: 3.0213 data: 0.0084 max mem: 33408 +Epoch: [28] [ 470/2639] eta: 1:49:21 lr: 1.6692527891825913e-05 loss: 0.0337 (0.0374) time: 2.9882 data: 0.0087 max mem: 33408 +Epoch: [28] [ 480/2639] eta: 1:48:53 lr: 1.668771219931967e-05 loss: 0.0322 (0.0374) time: 3.0319 data: 0.0089 max mem: 33408 +Epoch: [28] [ 490/2639] eta: 1:48:23 lr: 1.66828963523975e-05 loss: 0.0333 (0.0374) time: 3.0506 data: 0.0082 max mem: 33408 +Epoch: [28] [ 500/2639] eta: 1:47:51 lr: 1.66780803510049e-05 loss: 0.0358 (0.0375) time: 3.0030 data: 0.0081 max mem: 33408 +Epoch: [28] [ 510/2639] eta: 1:47:20 lr: 1.6673264195087375e-05 loss: 0.0408 (0.0378) time: 3.0070 data: 0.0086 max mem: 33408 +Epoch: [28] [ 520/2639] eta: 1:46:52 lr: 1.6668447884590344e-05 loss: 0.0408 (0.0378) time: 3.0518 data: 0.0084 max mem: 33408 +Epoch: [28] [ 530/2639] eta: 1:46:21 lr: 1.666363141945923e-05 loss: 0.0367 (0.0378) time: 3.0445 data: 0.0079 max mem: 33408 +Epoch: [28] [ 540/2639] eta: 1:45:49 lr: 1.6658814799639403e-05 loss: 0.0353 (0.0379) time: 2.9883 data: 0.0078 max mem: 33408 +Epoch: [28] [ 550/2639] eta: 1:45:17 lr: 1.6653998025076188e-05 loss: 0.0372 (0.0379) time: 2.9725 data: 0.0079 max mem: 33408 +Epoch: [28] [ 560/2639] eta: 1:44:45 lr: 1.6649181095714894e-05 loss: 0.0362 (0.0378) time: 2.9737 data: 0.0079 max mem: 33408 +Epoch: [28] [ 570/2639] eta: 1:44:15 lr: 1.6644364011500767e-05 loss: 0.0383 (0.0378) time: 3.0057 data: 0.0086 max mem: 33408 +Epoch: [28] [ 580/2639] eta: 1:43:46 lr: 1.6639546772379043e-05 loss: 0.0370 (0.0377) time: 3.0506 data: 0.0090 max mem: 33408 +Epoch: [28] [ 590/2639] eta: 1:43:15 lr: 1.663472937829489e-05 loss: 0.0357 (0.0378) time: 3.0326 data: 0.0083 max mem: 33408 +Epoch: [28] [ 600/2639] eta: 1:42:42 lr: 1.662991182919348e-05 loss: 0.0338 (0.0380) time: 2.9774 data: 0.0081 max mem: 33408 +Epoch: [28] [ 610/2639] eta: 1:42:14 lr: 1.6625094125019906e-05 loss: 0.0347 (0.0380) time: 3.0093 data: 0.0083 max mem: 33408 +Epoch: [28] [ 620/2639] eta: 1:41:45 lr: 1.6620276265719252e-05 loss: 0.0352 (0.0379) time: 3.0643 data: 0.0081 max mem: 33408 +Epoch: [28] [ 630/2639] eta: 1:41:14 lr: 1.6615458251236547e-05 loss: 0.0304 (0.0379) time: 3.0387 data: 0.0079 max mem: 33408 +Epoch: [28] [ 640/2639] eta: 1:40:44 lr: 1.66106400815168e-05 loss: 0.0365 (0.0379) time: 3.0208 data: 0.0082 max mem: 33408 +Epoch: [28] [ 650/2639] eta: 1:40:15 lr: 1.6605821756504966e-05 loss: 0.0365 (0.0379) time: 3.0499 data: 0.0080 max mem: 33408 +Epoch: [28] [ 660/2639] eta: 1:39:45 lr: 1.6601003276145982e-05 loss: 0.0368 (0.0379) time: 3.0534 data: 0.0078 max mem: 33408 +Epoch: [28] [ 670/2639] eta: 1:39:16 lr: 1.659618464038472e-05 loss: 0.0365 (0.0379) time: 3.0346 data: 0.0085 max mem: 33408 +Epoch: [28] [ 680/2639] eta: 1:38:46 lr: 1.659136584916605e-05 loss: 0.0355 (0.0379) time: 3.0379 data: 0.0088 max mem: 33408 +Epoch: [28] [ 690/2639] eta: 1:38:16 lr: 1.6586546902434767e-05 loss: 0.0355 (0.0378) time: 3.0486 data: 0.0082 max mem: 33408 +Epoch: [28] [ 700/2639] eta: 1:37:46 lr: 1.6581727800135665e-05 loss: 0.0291 (0.0378) time: 3.0400 data: 0.0085 max mem: 33408 +Epoch: [28] [ 710/2639] eta: 1:37:14 lr: 1.6576908542213466e-05 loss: 0.0323 (0.0377) time: 2.9879 data: 0.0086 max mem: 33408 +Epoch: [28] [ 720/2639] eta: 1:36:44 lr: 1.6572089128612886e-05 loss: 0.0317 (0.0377) time: 3.0049 data: 0.0082 max mem: 33408 +Epoch: [28] [ 730/2639] eta: 1:36:14 lr: 1.6567269559278574e-05 loss: 0.0313 (0.0377) time: 3.0434 data: 0.0079 max mem: 33408 +Epoch: [28] [ 740/2639] eta: 1:35:46 lr: 1.6562449834155173e-05 loss: 0.0365 (0.0377) time: 3.0624 data: 0.0078 max mem: 33408 +Epoch: [28] [ 750/2639] eta: 1:35:15 lr: 1.6557629953187258e-05 loss: 0.0336 (0.0376) time: 3.0557 data: 0.0079 max mem: 33408 +Epoch: [28] [ 760/2639] eta: 1:34:45 lr: 1.6552809916319388e-05 loss: 0.0279 (0.0376) time: 3.0313 data: 0.0076 max mem: 33408 +Epoch: [28] [ 770/2639] eta: 1:34:16 lr: 1.654798972349607e-05 loss: 0.0279 (0.0376) time: 3.0565 data: 0.0076 max mem: 33408 +Epoch: [28] [ 780/2639] eta: 1:33:46 lr: 1.6543169374661778e-05 loss: 0.0356 (0.0375) time: 3.0522 data: 0.0077 max mem: 33408 +Epoch: [28] [ 790/2639] eta: 1:33:16 lr: 1.6538348869760964e-05 loss: 0.0337 (0.0375) time: 3.0336 data: 0.0076 max mem: 33408 +Epoch: [28] [ 800/2639] eta: 1:32:46 lr: 1.6533528208738012e-05 loss: 0.0402 (0.0376) time: 3.0441 data: 0.0076 max mem: 33408 +Epoch: [28] [ 810/2639] eta: 1:32:16 lr: 1.65287073915373e-05 loss: 0.0359 (0.0376) time: 3.0350 data: 0.0074 max mem: 33408 +Epoch: [28] [ 820/2639] eta: 1:31:47 lr: 1.652388641810313e-05 loss: 0.0335 (0.0376) time: 3.0491 data: 0.0074 max mem: 33408 +Epoch: [28] [ 830/2639] eta: 1:31:17 lr: 1.6519065288379814e-05 loss: 0.0359 (0.0376) time: 3.0587 data: 0.0077 max mem: 33408 +Epoch: [28] [ 840/2639] eta: 1:30:45 lr: 1.651424400231158e-05 loss: 0.0358 (0.0376) time: 2.9991 data: 0.0081 max mem: 33408 +Epoch: [28] [ 850/2639] eta: 1:30:16 lr: 1.6509422559842654e-05 loss: 0.0330 (0.0376) time: 3.0222 data: 0.0081 max mem: 33408 +Epoch: [28] [ 860/2639] eta: 1:29:47 lr: 1.6504600960917192e-05 loss: 0.0326 (0.0376) time: 3.0808 data: 0.0081 max mem: 33408 +Epoch: [28] [ 870/2639] eta: 1:29:17 lr: 1.6499779205479348e-05 loss: 0.0370 (0.0376) time: 3.0637 data: 0.0083 max mem: 33408 +Epoch: [28] [ 880/2639] eta: 1:28:46 lr: 1.64949572934732e-05 loss: 0.0326 (0.0376) time: 3.0331 data: 0.0079 max mem: 33408 +Epoch: [28] [ 890/2639] eta: 1:28:16 lr: 1.6490135224842818e-05 loss: 0.0326 (0.0376) time: 3.0246 data: 0.0075 max mem: 33408 +Epoch: [28] [ 900/2639] eta: 1:27:47 lr: 1.6485312999532216e-05 loss: 0.0359 (0.0376) time: 3.0677 data: 0.0075 max mem: 33408 +Epoch: [28] [ 910/2639] eta: 1:27:17 lr: 1.648049061748538e-05 loss: 0.0335 (0.0375) time: 3.0560 data: 0.0075 max mem: 33408 +Epoch: [28] [ 920/2639] eta: 1:26:46 lr: 1.6475668078646248e-05 loss: 0.0335 (0.0377) time: 3.0070 data: 0.0078 max mem: 33408 +Epoch: [28] [ 930/2639] eta: 1:26:16 lr: 1.6470845382958735e-05 loss: 0.0389 (0.0377) time: 3.0401 data: 0.0080 max mem: 33408 +Epoch: [28] [ 940/2639] eta: 1:25:47 lr: 1.64660225303667e-05 loss: 0.0381 (0.0378) time: 3.0605 data: 0.0080 max mem: 33408 +Epoch: [28] [ 950/2639] eta: 1:25:16 lr: 1.6461199520813974e-05 loss: 0.0315 (0.0377) time: 3.0418 data: 0.0078 max mem: 33408 +Epoch: [28] [ 960/2639] eta: 1:24:46 lr: 1.6456376354244342e-05 loss: 0.0281 (0.0377) time: 3.0211 data: 0.0075 max mem: 33408 +Epoch: [28] [ 970/2639] eta: 1:24:15 lr: 1.6451553030601567e-05 loss: 0.0320 (0.0377) time: 2.9953 data: 0.0075 max mem: 33408 +Epoch: [28] [ 980/2639] eta: 1:23:45 lr: 1.6446729549829353e-05 loss: 0.0317 (0.0377) time: 3.0252 data: 0.0075 max mem: 33408 +Epoch: [28] [ 990/2639] eta: 1:23:13 lr: 1.644190591187138e-05 loss: 0.0323 (0.0377) time: 3.0121 data: 0.0079 max mem: 33408 +Epoch: [28] [1000/2639] eta: 1:22:44 lr: 1.643708211667128e-05 loss: 0.0294 (0.0376) time: 3.0162 data: 0.0080 max mem: 33408 +Epoch: [28] [1010/2639] eta: 1:22:13 lr: 1.6432258164172655e-05 loss: 0.0308 (0.0376) time: 3.0422 data: 0.0082 max mem: 33408 +Epoch: [28] [1020/2639] eta: 1:21:45 lr: 1.642743405431906e-05 loss: 0.0356 (0.0376) time: 3.0679 data: 0.0080 max mem: 33408 +Epoch: [28] [1030/2639] eta: 1:21:14 lr: 1.642260978705401e-05 loss: 0.0350 (0.0376) time: 3.0749 data: 0.0078 max mem: 33408 +Epoch: [28] [1040/2639] eta: 1:20:45 lr: 1.6417785362321002e-05 loss: 0.0350 (0.0377) time: 3.0497 data: 0.0082 max mem: 33408 +Epoch: [28] [1050/2639] eta: 1:20:14 lr: 1.6412960780063467e-05 loss: 0.0379 (0.0377) time: 3.0454 data: 0.0083 max mem: 33408 +Epoch: [28] [1060/2639] eta: 1:19:44 lr: 1.6408136040224817e-05 loss: 0.0363 (0.0377) time: 3.0424 data: 0.0078 max mem: 33408 +Epoch: [28] [1070/2639] eta: 1:19:13 lr: 1.6403311142748405e-05 loss: 0.0335 (0.0377) time: 3.0286 data: 0.0076 max mem: 33408 +Epoch: [28] [1080/2639] eta: 1:18:43 lr: 1.6398486087577576e-05 loss: 0.0333 (0.0377) time: 3.0103 data: 0.0079 max mem: 33408 +Epoch: [28] [1090/2639] eta: 1:18:13 lr: 1.6393660874655595e-05 loss: 0.0351 (0.0377) time: 3.0357 data: 0.0082 max mem: 33408 +Epoch: [28] [1100/2639] eta: 1:17:43 lr: 1.6388835503925732e-05 loss: 0.0287 (0.0377) time: 3.0561 data: 0.0079 max mem: 33408 +Epoch: [28] [1110/2639] eta: 1:17:12 lr: 1.6384009975331177e-05 loss: 0.0329 (0.0377) time: 3.0084 data: 0.0077 max mem: 33408 +Epoch: [28] [1120/2639] eta: 1:16:41 lr: 1.6379184288815118e-05 loss: 0.0324 (0.0376) time: 2.9803 data: 0.0076 max mem: 33408 +Epoch: [28] [1130/2639] eta: 1:16:11 lr: 1.6374358444320672e-05 loss: 0.0294 (0.0376) time: 3.0389 data: 0.0073 max mem: 33408 +Epoch: [28] [1140/2639] eta: 1:15:41 lr: 1.6369532441790942e-05 loss: 0.0306 (0.0375) time: 3.0494 data: 0.0073 max mem: 33408 +Epoch: [28] [1150/2639] eta: 1:15:10 lr: 1.6364706281168974e-05 loss: 0.0312 (0.0376) time: 3.0102 data: 0.0076 max mem: 33408 +Epoch: [28] [1160/2639] eta: 1:14:40 lr: 1.635987996239779e-05 loss: 0.0311 (0.0376) time: 2.9982 data: 0.0077 max mem: 33408 +Epoch: [28] [1170/2639] eta: 1:14:10 lr: 1.6355053485420352e-05 loss: 0.0316 (0.0376) time: 3.0232 data: 0.0082 max mem: 33408 +Epoch: [28] [1180/2639] eta: 1:13:39 lr: 1.6350226850179606e-05 loss: 0.0325 (0.0376) time: 3.0067 data: 0.0085 max mem: 33408 +Epoch: [28] [1190/2639] eta: 1:13:09 lr: 1.634540005661844e-05 loss: 0.0325 (0.0376) time: 3.0368 data: 0.0083 max mem: 33408 +Epoch: [28] [1200/2639] eta: 1:12:39 lr: 1.6340573104679727e-05 loss: 0.0335 (0.0376) time: 3.0660 data: 0.0085 max mem: 33408 +Epoch: [28] [1210/2639] eta: 1:12:08 lr: 1.6335745994306264e-05 loss: 0.0331 (0.0376) time: 3.0020 data: 0.0082 max mem: 33408 +Epoch: [28] [1220/2639] eta: 1:11:38 lr: 1.6330918725440845e-05 loss: 0.0348 (0.0376) time: 3.0049 data: 0.0080 max mem: 33408 +Epoch: [28] [1230/2639] eta: 1:11:08 lr: 1.6326091298026193e-05 loss: 0.0379 (0.0376) time: 3.0352 data: 0.0081 max mem: 33408 +Epoch: [28] [1240/2639] eta: 1:10:37 lr: 1.6321263712005024e-05 loss: 0.0336 (0.0376) time: 3.0218 data: 0.0077 max mem: 33408 +Epoch: [28] [1250/2639] eta: 1:10:07 lr: 1.6316435967319985e-05 loss: 0.0328 (0.0376) time: 3.0467 data: 0.0075 max mem: 33408 +Epoch: [28] [1260/2639] eta: 1:09:38 lr: 1.63116080639137e-05 loss: 0.0342 (0.0376) time: 3.0840 data: 0.0081 max mem: 33408 +Epoch: [28] [1270/2639] eta: 1:09:08 lr: 1.6306780001728753e-05 loss: 0.0356 (0.0376) time: 3.0751 data: 0.0084 max mem: 33408 +Epoch: [28] [1280/2639] eta: 1:08:38 lr: 1.6301951780707676e-05 loss: 0.0354 (0.0376) time: 3.0702 data: 0.0081 max mem: 33408 +Epoch: [28] [1290/2639] eta: 1:08:07 lr: 1.6297123400792978e-05 loss: 0.0404 (0.0376) time: 3.0335 data: 0.0078 max mem: 33408 +Epoch: [28] [1300/2639] eta: 1:07:37 lr: 1.6292294861927114e-05 loss: 0.0338 (0.0376) time: 3.0251 data: 0.0074 max mem: 33408 +Epoch: [28] [1310/2639] eta: 1:07:07 lr: 1.6287466164052514e-05 loss: 0.0315 (0.0376) time: 3.0261 data: 0.0072 max mem: 33408 +Epoch: [28] [1320/2639] eta: 1:06:36 lr: 1.6282637307111548e-05 loss: 0.0317 (0.0376) time: 3.0092 data: 0.0076 max mem: 33408 +Epoch: [28] [1330/2639] eta: 1:06:06 lr: 1.627780829104657e-05 loss: 0.0315 (0.0376) time: 3.0476 data: 0.0076 max mem: 33408 +Epoch: [28] [1340/2639] eta: 1:05:36 lr: 1.6272979115799864e-05 loss: 0.0387 (0.0376) time: 3.0679 data: 0.0075 max mem: 33408 +Epoch: [28] [1350/2639] eta: 1:05:07 lr: 1.6268149781313712e-05 loss: 0.0383 (0.0376) time: 3.0806 data: 0.0076 max mem: 33408 +Epoch: [28] [1360/2639] eta: 1:04:37 lr: 1.6263320287530323e-05 loss: 0.0331 (0.0376) time: 3.0902 data: 0.0076 max mem: 33408 +Epoch: [28] [1370/2639] eta: 1:04:07 lr: 1.6258490634391885e-05 loss: 0.0331 (0.0376) time: 3.0990 data: 0.0078 max mem: 33408 +Epoch: [28] [1380/2639] eta: 1:03:37 lr: 1.6253660821840534e-05 loss: 0.0333 (0.0376) time: 3.0628 data: 0.0077 max mem: 33408 +Epoch: [28] [1390/2639] eta: 1:03:07 lr: 1.624883084981838e-05 loss: 0.0309 (0.0376) time: 3.0404 data: 0.0077 max mem: 33408 +Epoch: [28] [1400/2639] eta: 1:02:36 lr: 1.624400071826747e-05 loss: 0.0309 (0.0376) time: 3.0182 data: 0.0081 max mem: 33408 +Epoch: [28] [1410/2639] eta: 1:02:06 lr: 1.6239170427129838e-05 loss: 0.0339 (0.0376) time: 3.0078 data: 0.0080 max mem: 33408 +Epoch: [28] [1420/2639] eta: 1:01:36 lr: 1.623433997634746e-05 loss: 0.0340 (0.0376) time: 3.0455 data: 0.0075 max mem: 33408 +Epoch: [28] [1430/2639] eta: 1:01:06 lr: 1.622950936586228e-05 loss: 0.0308 (0.0375) time: 3.0660 data: 0.0074 max mem: 33408 +Epoch: [28] [1440/2639] eta: 1:00:35 lr: 1.6224678595616195e-05 loss: 0.0316 (0.0375) time: 3.0385 data: 0.0078 max mem: 33408 +Epoch: [28] [1450/2639] eta: 1:00:05 lr: 1.6219847665551065e-05 loss: 0.0316 (0.0375) time: 3.0214 data: 0.0078 max mem: 33408 +Epoch: [28] [1460/2639] eta: 0:59:35 lr: 1.621501657560871e-05 loss: 0.0360 (0.0375) time: 3.0688 data: 0.0077 max mem: 33408 +Epoch: [28] [1470/2639] eta: 0:59:04 lr: 1.6210185325730913e-05 loss: 0.0349 (0.0375) time: 3.0418 data: 0.0078 max mem: 33408 +Epoch: [28] [1480/2639] eta: 0:58:34 lr: 1.6205353915859403e-05 loss: 0.0310 (0.0375) time: 2.9978 data: 0.0078 max mem: 33408 +Epoch: [28] [1490/2639] eta: 0:58:04 lr: 1.620052234593589e-05 loss: 0.0298 (0.0375) time: 3.0319 data: 0.0080 max mem: 33408 +Epoch: [28] [1500/2639] eta: 0:57:34 lr: 1.619569061590202e-05 loss: 0.0298 (0.0374) time: 3.0687 data: 0.0082 max mem: 33408 +Epoch: [28] [1510/2639] eta: 0:57:03 lr: 1.6190858725699417e-05 loss: 0.0329 (0.0375) time: 3.0654 data: 0.0079 max mem: 33408 +Epoch: [28] [1520/2639] eta: 0:56:33 lr: 1.618602667526966e-05 loss: 0.0368 (0.0375) time: 3.0455 data: 0.0081 max mem: 33408 +Epoch: [28] [1530/2639] eta: 0:56:03 lr: 1.618119446455428e-05 loss: 0.0362 (0.0375) time: 3.0155 data: 0.0082 max mem: 33408 +Epoch: [28] [1540/2639] eta: 0:55:32 lr: 1.617636209349477e-05 loss: 0.0299 (0.0375) time: 2.9987 data: 0.0082 max mem: 33408 +Epoch: [28] [1550/2639] eta: 0:55:02 lr: 1.6171529562032583e-05 loss: 0.0299 (0.0375) time: 3.0339 data: 0.0080 max mem: 33408 +Epoch: [28] [1560/2639] eta: 0:54:32 lr: 1.6166696870109145e-05 loss: 0.0317 (0.0375) time: 3.0482 data: 0.0078 max mem: 33408 +Epoch: [28] [1570/2639] eta: 0:54:01 lr: 1.616186401766581e-05 loss: 0.0321 (0.0375) time: 3.0426 data: 0.0079 max mem: 33408 +Epoch: [28] [1580/2639] eta: 0:53:31 lr: 1.6157031004643922e-05 loss: 0.0363 (0.0375) time: 3.0387 data: 0.0076 max mem: 33408 +Epoch: [28] [1590/2639] eta: 0:53:00 lr: 1.6152197830984762e-05 loss: 0.0404 (0.0375) time: 3.0077 data: 0.0076 max mem: 33408 +Epoch: [28] [1600/2639] eta: 0:52:30 lr: 1.6147364496629595e-05 loss: 0.0352 (0.0375) time: 3.0381 data: 0.0075 max mem: 33408 +Epoch: [28] [1610/2639] eta: 0:52:00 lr: 1.614253100151961e-05 loss: 0.0349 (0.0375) time: 3.0823 data: 0.0073 max mem: 33408 +Epoch: [28] [1620/2639] eta: 0:51:30 lr: 1.6137697345595993e-05 loss: 0.0374 (0.0375) time: 3.0494 data: 0.0074 max mem: 33408 +Epoch: [28] [1630/2639] eta: 0:51:00 lr: 1.613286352879985e-05 loss: 0.0338 (0.0375) time: 3.0346 data: 0.0078 max mem: 33408 +Epoch: [28] [1640/2639] eta: 0:50:29 lr: 1.6128029551072288e-05 loss: 0.0338 (0.0375) time: 3.0190 data: 0.0081 max mem: 33408 +Epoch: [28] [1650/2639] eta: 0:49:59 lr: 1.6123195412354332e-05 loss: 0.0355 (0.0375) time: 3.0023 data: 0.0079 max mem: 33408 +Epoch: [28] [1660/2639] eta: 0:49:28 lr: 1.6118361112587e-05 loss: 0.0362 (0.0376) time: 3.0288 data: 0.0076 max mem: 33408 +Epoch: [28] [1670/2639] eta: 0:48:58 lr: 1.6113526651711238e-05 loss: 0.0403 (0.0376) time: 3.0469 data: 0.0075 max mem: 33408 +Epoch: [28] [1680/2639] eta: 0:48:28 lr: 1.6108692029667985e-05 loss: 0.0353 (0.0376) time: 3.0377 data: 0.0075 max mem: 33408 +Epoch: [28] [1690/2639] eta: 0:47:57 lr: 1.61038572463981e-05 loss: 0.0334 (0.0376) time: 3.0026 data: 0.0075 max mem: 33408 +Epoch: [28] [1700/2639] eta: 0:47:27 lr: 1.6099022301842433e-05 loss: 0.0325 (0.0377) time: 2.9942 data: 0.0079 max mem: 33408 +Epoch: [28] [1710/2639] eta: 0:46:57 lr: 1.609418719594177e-05 loss: 0.0315 (0.0377) time: 3.0208 data: 0.0077 max mem: 33408 +Epoch: [28] [1720/2639] eta: 0:46:26 lr: 1.608935192863688e-05 loss: 0.0306 (0.0377) time: 2.9863 data: 0.0076 max mem: 33408 +Epoch: [28] [1730/2639] eta: 0:45:55 lr: 1.608451649986846e-05 loss: 0.0344 (0.0377) time: 2.9909 data: 0.0078 max mem: 33408 +Epoch: [28] [1740/2639] eta: 0:45:25 lr: 1.6079680909577192e-05 loss: 0.0318 (0.0377) time: 3.0441 data: 0.0080 max mem: 33408 +Epoch: [28] [1750/2639] eta: 0:44:55 lr: 1.6074845157703698e-05 loss: 0.0310 (0.0377) time: 3.0028 data: 0.0078 max mem: 33408 +Epoch: [28] [1760/2639] eta: 0:44:24 lr: 1.6070009244188565e-05 loss: 0.0348 (0.0377) time: 2.9981 data: 0.0074 max mem: 33408 +Epoch: [28] [1770/2639] eta: 0:43:54 lr: 1.6065173168972352e-05 loss: 0.0325 (0.0376) time: 3.0393 data: 0.0073 max mem: 33408 +Epoch: [28] [1780/2639] eta: 0:43:23 lr: 1.6060336931995547e-05 loss: 0.0295 (0.0376) time: 2.9920 data: 0.0078 max mem: 33408 +Epoch: [28] [1790/2639] eta: 0:42:52 lr: 1.605550053319863e-05 loss: 0.0295 (0.0376) time: 2.9356 data: 0.0084 max mem: 33408 +Epoch: [28] [1800/2639] eta: 0:42:22 lr: 1.6050663972522004e-05 loss: 0.0306 (0.0375) time: 2.9437 data: 0.0077 max mem: 33408 +Epoch: [28] [1810/2639] eta: 0:41:51 lr: 1.6045827249906058e-05 loss: 0.0339 (0.0375) time: 2.9577 data: 0.0074 max mem: 33408 +Epoch: [28] [1820/2639] eta: 0:41:20 lr: 1.6040990365291124e-05 loss: 0.0349 (0.0375) time: 2.9467 data: 0.0073 max mem: 33408 +Epoch: [28] [1830/2639] eta: 0:40:50 lr: 1.603615331861751e-05 loss: 0.0325 (0.0375) time: 2.9634 data: 0.0071 max mem: 33408 +Epoch: [28] [1840/2639] eta: 0:40:20 lr: 1.6031316109825445e-05 loss: 0.0316 (0.0375) time: 3.0158 data: 0.0073 max mem: 33408 +Epoch: [28] [1850/2639] eta: 0:39:50 lr: 1.602647873885516e-05 loss: 0.0313 (0.0375) time: 3.0574 data: 0.0076 max mem: 33408 +Epoch: [28] [1860/2639] eta: 0:39:19 lr: 1.602164120564681e-05 loss: 0.0332 (0.0375) time: 3.0625 data: 0.0078 max mem: 33408 +Epoch: [28] [1870/2639] eta: 0:38:49 lr: 1.601680351014054e-05 loss: 0.0308 (0.0375) time: 3.0252 data: 0.0080 max mem: 33408 +Epoch: [28] [1880/2639] eta: 0:38:19 lr: 1.6011965652276413e-05 loss: 0.0307 (0.0375) time: 3.0000 data: 0.0078 max mem: 33408 +Epoch: [28] [1890/2639] eta: 0:37:48 lr: 1.6007127631994486e-05 loss: 0.0342 (0.0375) time: 3.0195 data: 0.0075 max mem: 33408 +Epoch: [28] [1900/2639] eta: 0:37:18 lr: 1.6002289449234746e-05 loss: 0.0303 (0.0374) time: 3.0522 data: 0.0074 max mem: 33408 +Epoch: [28] [1910/2639] eta: 0:36:48 lr: 1.5997451103937166e-05 loss: 0.0317 (0.0374) time: 3.0583 data: 0.0072 max mem: 33408 +Epoch: [28] [1920/2639] eta: 0:36:17 lr: 1.5992612596041648e-05 loss: 0.0320 (0.0374) time: 2.9997 data: 0.0075 max mem: 33408 +Epoch: [28] [1930/2639] eta: 0:35:47 lr: 1.5987773925488075e-05 loss: 0.0337 (0.0374) time: 2.9638 data: 0.0078 max mem: 33408 +Epoch: [28] [1940/2639] eta: 0:35:17 lr: 1.598293509221627e-05 loss: 0.0369 (0.0374) time: 3.0242 data: 0.0080 max mem: 33408 +Epoch: [28] [1950/2639] eta: 0:34:46 lr: 1.597809609616602e-05 loss: 0.0352 (0.0374) time: 3.0418 data: 0.0078 max mem: 33408 +Epoch: [28] [1960/2639] eta: 0:34:16 lr: 1.597325693727707e-05 loss: 0.0325 (0.0374) time: 3.0260 data: 0.0080 max mem: 33408 +Epoch: [28] [1970/2639] eta: 0:33:46 lr: 1.596841761548913e-05 loss: 0.0312 (0.0374) time: 3.0426 data: 0.0080 max mem: 33408 +Epoch: [28] [1980/2639] eta: 0:33:16 lr: 1.5963578130741853e-05 loss: 0.0327 (0.0374) time: 3.0595 data: 0.0080 max mem: 33408 +Epoch: [28] [1990/2639] eta: 0:32:46 lr: 1.5958738482974864e-05 loss: 0.0384 (0.0374) time: 3.0609 data: 0.0081 max mem: 33408 +Epoch: [28] [2000/2639] eta: 0:32:15 lr: 1.5953898672127726e-05 loss: 0.0329 (0.0374) time: 3.0395 data: 0.0078 max mem: 33408 +Epoch: [28] [2010/2639] eta: 0:31:45 lr: 1.5949058698139976e-05 loss: 0.0325 (0.0373) time: 3.0325 data: 0.0077 max mem: 33408 +Epoch: [28] [2020/2639] eta: 0:31:15 lr: 1.594421856095111e-05 loss: 0.0343 (0.0374) time: 3.0571 data: 0.0080 max mem: 33408 +Epoch: [28] [2030/2639] eta: 0:30:45 lr: 1.593937826050056e-05 loss: 0.0375 (0.0374) time: 3.0521 data: 0.0080 max mem: 33408 +Epoch: [28] [2040/2639] eta: 0:30:14 lr: 1.5934537796727744e-05 loss: 0.0346 (0.0374) time: 3.0391 data: 0.0075 max mem: 33408 +Epoch: [28] [2050/2639] eta: 0:29:44 lr: 1.592969716957201e-05 loss: 0.0316 (0.0374) time: 3.0383 data: 0.0079 max mem: 33408 +Epoch: [28] [2060/2639] eta: 0:29:14 lr: 1.5924856378972685e-05 loss: 0.0320 (0.0373) time: 3.0379 data: 0.0083 max mem: 33408 +Epoch: [28] [2070/2639] eta: 0:28:43 lr: 1.5920015424869034e-05 loss: 0.0325 (0.0374) time: 3.0239 data: 0.0078 max mem: 33408 +Epoch: [28] [2080/2639] eta: 0:28:13 lr: 1.59151743072003e-05 loss: 0.0337 (0.0374) time: 3.0107 data: 0.0081 max mem: 33408 +Epoch: [28] [2090/2639] eta: 0:27:43 lr: 1.591033302590565e-05 loss: 0.0325 (0.0373) time: 3.0328 data: 0.0079 max mem: 33408 +Epoch: [28] [2100/2639] eta: 0:27:13 lr: 1.5905491580924256e-05 loss: 0.0360 (0.0374) time: 3.0531 data: 0.0077 max mem: 33408 +Epoch: [28] [2110/2639] eta: 0:26:42 lr: 1.5900649972195196e-05 loss: 0.0333 (0.0374) time: 3.0389 data: 0.0080 max mem: 33408 +Epoch: [28] [2120/2639] eta: 0:26:12 lr: 1.5895808199657548e-05 loss: 0.0314 (0.0373) time: 3.0025 data: 0.0076 max mem: 33408 +Epoch: [28] [2130/2639] eta: 0:25:42 lr: 1.5890966263250306e-05 loss: 0.0326 (0.0374) time: 3.0041 data: 0.0075 max mem: 33408 +Epoch: [28] [2140/2639] eta: 0:25:11 lr: 1.588612416291246e-05 loss: 0.0355 (0.0374) time: 3.0159 data: 0.0076 max mem: 33408 +Epoch: [28] [2150/2639] eta: 0:24:41 lr: 1.5881281898582926e-05 loss: 0.0333 (0.0374) time: 3.0142 data: 0.0081 max mem: 33408 +Epoch: [28] [2160/2639] eta: 0:24:11 lr: 1.58764394702006e-05 loss: 0.0344 (0.0374) time: 3.0192 data: 0.0081 max mem: 33408 +Epoch: [28] [2170/2639] eta: 0:23:40 lr: 1.587159687770431e-05 loss: 0.0353 (0.0374) time: 3.0222 data: 0.0075 max mem: 33408 +Epoch: [28] [2180/2639] eta: 0:23:10 lr: 1.5866754121032866e-05 loss: 0.0374 (0.0374) time: 2.9939 data: 0.0076 max mem: 33408 +Epoch: [28] [2190/2639] eta: 0:22:40 lr: 1.586191120012501e-05 loss: 0.0333 (0.0374) time: 3.0005 data: 0.0080 max mem: 33408 +Epoch: [28] [2200/2639] eta: 0:22:09 lr: 1.5857068114919464e-05 loss: 0.0337 (0.0374) time: 3.0196 data: 0.0079 max mem: 33408 +Epoch: [28] [2210/2639] eta: 0:21:39 lr: 1.585222486535489e-05 loss: 0.0399 (0.0375) time: 2.9975 data: 0.0080 max mem: 33408 +Epoch: [28] [2220/2639] eta: 0:21:08 lr: 1.584738145136991e-05 loss: 0.0368 (0.0375) time: 2.9944 data: 0.0081 max mem: 33408 +Epoch: [28] [2230/2639] eta: 0:20:38 lr: 1.5842537872903103e-05 loss: 0.0368 (0.0375) time: 2.9906 data: 0.0078 max mem: 33408 +Epoch: [28] [2240/2639] eta: 0:20:08 lr: 1.5837694129893007e-05 loss: 0.0359 (0.0375) time: 2.9989 data: 0.0080 max mem: 33408 +Epoch: [28] [2250/2639] eta: 0:19:38 lr: 1.583285022227811e-05 loss: 0.0341 (0.0375) time: 3.0525 data: 0.0082 max mem: 33408 +Epoch: [28] [2260/2639] eta: 0:19:07 lr: 1.582800614999686e-05 loss: 0.0341 (0.0375) time: 3.0751 data: 0.0082 max mem: 33408 +Epoch: [28] [2270/2639] eta: 0:18:37 lr: 1.582316191298767e-05 loss: 0.0386 (0.0375) time: 3.0320 data: 0.0078 max mem: 33408 +Epoch: [28] [2280/2639] eta: 0:18:07 lr: 1.5818317511188887e-05 loss: 0.0376 (0.0375) time: 3.0250 data: 0.0075 max mem: 33408 +Epoch: [28] [2290/2639] eta: 0:17:37 lr: 1.581347294453884e-05 loss: 0.0371 (0.0375) time: 3.0272 data: 0.0078 max mem: 33408 +Epoch: [28] [2300/2639] eta: 0:17:06 lr: 1.5808628212975785e-05 loss: 0.0399 (0.0376) time: 3.0268 data: 0.0083 max mem: 33408 +Epoch: [28] [2310/2639] eta: 0:16:36 lr: 1.5803783316437963e-05 loss: 0.0406 (0.0376) time: 3.0295 data: 0.0087 max mem: 33408 +Epoch: [28] [2320/2639] eta: 0:16:06 lr: 1.5798938254863543e-05 loss: 0.0324 (0.0376) time: 3.0508 data: 0.0082 max mem: 33408 +Epoch: [28] [2330/2639] eta: 0:15:35 lr: 1.5794093028190682e-05 loss: 0.0320 (0.0375) time: 3.0542 data: 0.0076 max mem: 33408 +Epoch: [28] [2340/2639] eta: 0:15:05 lr: 1.578924763635746e-05 loss: 0.0320 (0.0375) time: 3.0247 data: 0.0080 max mem: 33408 +Epoch: [28] [2350/2639] eta: 0:14:35 lr: 1.5784402079301938e-05 loss: 0.0324 (0.0376) time: 3.0281 data: 0.0080 max mem: 33408 +Epoch: [28] [2360/2639] eta: 0:14:05 lr: 1.577955635696211e-05 loss: 0.0334 (0.0376) time: 3.0229 data: 0.0079 max mem: 33408 +Epoch: [28] [2370/2639] eta: 0:13:34 lr: 1.577471046927595e-05 loss: 0.0306 (0.0375) time: 3.0289 data: 0.0080 max mem: 33408 +Epoch: [28] [2380/2639] eta: 0:13:04 lr: 1.5769864416181366e-05 loss: 0.0303 (0.0375) time: 3.0227 data: 0.0081 max mem: 33408 +Epoch: [28] [2390/2639] eta: 0:12:34 lr: 1.5765018197616237e-05 loss: 0.0330 (0.0375) time: 3.0081 data: 0.0083 max mem: 33408 +Epoch: [28] [2400/2639] eta: 0:12:03 lr: 1.5760171813518387e-05 loss: 0.0336 (0.0375) time: 3.0209 data: 0.0079 max mem: 33408 +Epoch: [28] [2410/2639] eta: 0:11:33 lr: 1.5755325263825606e-05 loss: 0.0327 (0.0375) time: 3.0261 data: 0.0076 max mem: 33408 +Epoch: [28] [2420/2639] eta: 0:11:03 lr: 1.575047854847562e-05 loss: 0.0326 (0.0375) time: 3.0038 data: 0.0078 max mem: 33408 +Epoch: [28] [2430/2639] eta: 0:10:32 lr: 1.5745631667406135e-05 loss: 0.0346 (0.0376) time: 2.9887 data: 0.0080 max mem: 33408 +Epoch: [28] [2440/2639] eta: 0:10:02 lr: 1.5740784620554795e-05 loss: 0.0374 (0.0376) time: 2.9819 data: 0.0079 max mem: 33408 +Epoch: [28] [2450/2639] eta: 0:09:32 lr: 1.573593740785921e-05 loss: 0.0361 (0.0376) time: 2.9798 data: 0.0079 max mem: 33408 +Epoch: [28] [2460/2639] eta: 0:09:02 lr: 1.5731090029256926e-05 loss: 0.0359 (0.0376) time: 3.0263 data: 0.0078 max mem: 33408 +Epoch: [28] [2470/2639] eta: 0:08:31 lr: 1.5726242484685476e-05 loss: 0.0338 (0.0376) time: 3.0310 data: 0.0081 max mem: 33408 +Epoch: [28] [2480/2639] eta: 0:08:01 lr: 1.5721394774082314e-05 loss: 0.0361 (0.0376) time: 2.9783 data: 0.0086 max mem: 33408 +Epoch: [28] [2490/2639] eta: 0:07:31 lr: 1.5716546897384882e-05 loss: 0.0343 (0.0376) time: 2.9944 data: 0.0085 max mem: 33408 +Epoch: [28] [2500/2639] eta: 0:07:00 lr: 1.571169885453054e-05 loss: 0.0351 (0.0376) time: 3.0458 data: 0.0083 max mem: 33408 +Epoch: [28] [2510/2639] eta: 0:06:30 lr: 1.5706850645456633e-05 loss: 0.0409 (0.0376) time: 3.0470 data: 0.0083 max mem: 33408 +Epoch: [28] [2520/2639] eta: 0:06:00 lr: 1.570200227010046e-05 loss: 0.0388 (0.0376) time: 3.0687 data: 0.0082 max mem: 33408 +Epoch: [28] [2530/2639] eta: 0:05:30 lr: 1.5697153728399245e-05 loss: 0.0330 (0.0376) time: 3.0632 data: 0.0082 max mem: 33408 +Epoch: [28] [2540/2639] eta: 0:04:59 lr: 1.5692305020290206e-05 loss: 0.0355 (0.0377) time: 3.0138 data: 0.0082 max mem: 33408 +Epoch: [28] [2550/2639] eta: 0:04:29 lr: 1.5687456145710482e-05 loss: 0.0378 (0.0377) time: 3.0266 data: 0.0079 max mem: 33408 +Epoch: [28] [2560/2639] eta: 0:03:59 lr: 1.5682607104597195e-05 loss: 0.0373 (0.0377) time: 3.0460 data: 0.0077 max mem: 33408 +Epoch: [28] [2570/2639] eta: 0:03:28 lr: 1.5677757896887392e-05 loss: 0.0325 (0.0377) time: 3.0726 data: 0.0079 max mem: 33408 +Epoch: [28] [2580/2639] eta: 0:02:58 lr: 1.5672908522518114e-05 loss: 0.0366 (0.0377) time: 3.0710 data: 0.0079 max mem: 33408 +Epoch: [28] [2590/2639] eta: 0:02:28 lr: 1.5668058981426307e-05 loss: 0.0360 (0.0377) time: 2.9914 data: 0.0076 max mem: 33408 +Epoch: [28] [2600/2639] eta: 0:01:58 lr: 1.566320927354892e-05 loss: 0.0333 (0.0377) time: 2.9542 data: 0.0079 max mem: 33408 +Epoch: [28] [2610/2639] eta: 0:01:27 lr: 1.5658359398822817e-05 loss: 0.0344 (0.0377) time: 2.9900 data: 0.0084 max mem: 33408 +Epoch: [28] [2620/2639] eta: 0:00:57 lr: 1.565350935718485e-05 loss: 0.0353 (0.0377) time: 3.0301 data: 0.0087 max mem: 33408 +Epoch: [28] [2630/2639] eta: 0:00:27 lr: 1.564865914857179e-05 loss: 0.0329 (0.0377) time: 3.0175 data: 0.0081 max mem: 33408 +Epoch: [28] Total time: 2:13:11 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 2:04:44 time: 2.9089 data: 2.8185 max mem: 33408 +Test: [ 100/2573] eta: 0:04:23 time: 0.0786 data: 0.0014 max mem: 33408 +Test: [ 200/2573] eta: 0:03:41 time: 0.0799 data: 0.0014 max mem: 33408 +Test: [ 300/2573] eta: 0:03:21 time: 0.0810 data: 0.0015 max mem: 33408 +Test: [ 400/2573] eta: 0:03:07 time: 0.0810 data: 0.0014 max mem: 33408 +Test: [ 500/2573] eta: 0:02:56 time: 0.0802 data: 0.0014 max mem: 33408 +Test: [ 600/2573] eta: 0:02:46 time: 0.0809 data: 0.0015 max mem: 33408 +Test: [ 700/2573] eta: 0:02:38 time: 0.0811 data: 0.0014 max mem: 33408 +Test: [ 800/2573] eta: 0:02:29 time: 0.0841 data: 0.0014 max mem: 33408 +Test: [ 900/2573] eta: 0:02:20 time: 0.0806 data: 0.0013 max mem: 33408 +Test: [1000/2573] eta: 0:02:11 time: 0.0817 data: 0.0015 max mem: 33408 +Test: [1100/2573] eta: 0:02:03 time: 0.0814 data: 0.0015 max mem: 33408 +Test: [1200/2573] eta: 0:01:54 time: 0.0820 data: 0.0015 max mem: 33408 +Test: [1300/2573] eta: 0:01:46 time: 0.0822 data: 0.0015 max mem: 33408 +Test: [1400/2573] eta: 0:01:37 time: 0.0798 data: 0.0015 max mem: 33408 +Test: [1500/2573] eta: 0:01:29 time: 0.0806 data: 0.0014 max mem: 33408 +Test: [1600/2573] eta: 0:01:20 time: 0.0849 data: 0.0014 max mem: 33408 +Test: [1700/2573] eta: 0:01:12 time: 0.0809 data: 0.0016 max mem: 33408 +Test: [1800/2573] eta: 0:01:04 time: 0.0839 data: 0.0015 max mem: 33408 +Test: [1900/2573] eta: 0:00:55 time: 0.0797 data: 0.0015 max mem: 33408 +Test: [2000/2573] eta: 0:00:47 time: 0.0816 data: 0.0014 max mem: 33408 +Test: [2100/2573] eta: 0:00:39 time: 0.0826 data: 0.0015 max mem: 33408 +Test: [2200/2573] eta: 0:00:30 time: 0.0837 data: 0.0015 max mem: 33408 +Test: [2300/2573] eta: 0:00:22 time: 0.0822 data: 0.0016 max mem: 33408 +Test: [2400/2573] eta: 0:00:14 time: 0.0783 data: 0.0015 max mem: 33408 +Test: [2500/2573] eta: 0:00:06 time: 0.0824 data: 0.0014 max mem: 33408 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: Total time: 0:03:33 +Final results: +Mean IoU is 64.80 + + precision@0.5 = 72.88 + precision@0.6 = 67.83 + precision@0.7 = 60.54 + precision@0.8 = 49.78 + precision@0.9 = 24.71 + overall IoU = 62.22 + +Average object IoU 64.79711395870395 +Overall IoU 62.220767974853516 +Better epoch: 28 + +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [29] [ 0/2639] eta: 3:55:22 lr: 1.5644293818004067e-05 loss: 0.0229 (0.0229) time: 5.3515 data: 2.0898 max mem: 33408 +Epoch: [29] [ 10/2639] eta: 2:20:31 lr: 1.563944329196405e-05 loss: 0.0285 (0.0425) time: 3.2072 data: 0.1969 max mem: 33408 +Epoch: [29] [ 20/2639] eta: 2:14:34 lr: 1.5634592598765377e-05 loss: 0.0327 (0.0408) time: 2.9698 data: 0.0077 max mem: 33408 +Epoch: [29] [ 30/2639] eta: 2:12:38 lr: 1.562974173834467e-05 loss: 0.0393 (0.0428) time: 2.9645 data: 0.0077 max mem: 33408 +Epoch: [29] [ 40/2639] eta: 2:11:25 lr: 1.5624890710638484e-05 loss: 0.0349 (0.0417) time: 2.9822 data: 0.0079 max mem: 33408 +Epoch: [29] [ 50/2639] eta: 2:11:03 lr: 1.562003951558335e-05 loss: 0.0380 (0.0423) time: 3.0169 data: 0.0083 max mem: 33408 +Epoch: [29] [ 60/2639] eta: 2:10:28 lr: 1.561518815311573e-05 loss: 0.0371 (0.0412) time: 3.0391 data: 0.0081 max mem: 33408 +Epoch: [29] [ 70/2639] eta: 2:09:54 lr: 1.5610336623172064e-05 loss: 0.0328 (0.0399) time: 3.0261 data: 0.0079 max mem: 33408 +Epoch: [29] [ 80/2639] eta: 2:09:15 lr: 1.560548492568872e-05 loss: 0.0323 (0.0404) time: 3.0162 data: 0.0081 max mem: 33408 +Epoch: [29] [ 90/2639] eta: 2:08:45 lr: 1.5600633060602048e-05 loss: 0.0362 (0.0402) time: 3.0185 data: 0.0080 max mem: 33408 +Epoch: [29] [ 100/2639] eta: 2:08:20 lr: 1.5595781027848318e-05 loss: 0.0338 (0.0408) time: 3.0419 data: 0.0080 max mem: 33408 +Epoch: [29] [ 110/2639] eta: 2:07:51 lr: 1.5590928827363792e-05 loss: 0.0331 (0.0405) time: 3.0455 data: 0.0086 max mem: 33408 +Epoch: [29] [ 120/2639] eta: 2:07:19 lr: 1.5586076459084648e-05 loss: 0.0306 (0.0400) time: 3.0309 data: 0.0086 max mem: 33408 +Epoch: [29] [ 130/2639] eta: 2:06:29 lr: 1.5581223922947047e-05 loss: 0.0325 (0.0397) time: 2.9783 data: 0.0079 max mem: 33408 +Epoch: [29] [ 140/2639] eta: 2:05:57 lr: 1.55763712188871e-05 loss: 0.0357 (0.0392) time: 2.9728 data: 0.0081 max mem: 33408 +Epoch: [29] [ 150/2639] eta: 2:05:36 lr: 1.5571518346840846e-05 loss: 0.0312 (0.0388) time: 3.0478 data: 0.0086 max mem: 33408 +Epoch: [29] [ 160/2639] eta: 2:05:05 lr: 1.5566665306744317e-05 loss: 0.0310 (0.0385) time: 3.0536 data: 0.0083 max mem: 33408 +Epoch: [29] [ 170/2639] eta: 2:04:36 lr: 1.5561812098533456e-05 loss: 0.0355 (0.0392) time: 3.0289 data: 0.0083 max mem: 33408 +Epoch: [29] [ 180/2639] eta: 2:04:09 lr: 1.5556958722144196e-05 loss: 0.0355 (0.0388) time: 3.0427 data: 0.0082 max mem: 33408 +Epoch: [29] [ 190/2639] eta: 2:03:35 lr: 1.5552105177512397e-05 loss: 0.0310 (0.0386) time: 3.0260 data: 0.0082 max mem: 33408 +Epoch: [29] [ 200/2639] eta: 2:03:03 lr: 1.5547251464573894e-05 loss: 0.0320 (0.0384) time: 3.0084 data: 0.0082 max mem: 33408 +Epoch: [29] [ 210/2639] eta: 2:02:38 lr: 1.5542397583264452e-05 loss: 0.0329 (0.0382) time: 3.0440 data: 0.0077 max mem: 33408 +Epoch: [29] [ 220/2639] eta: 2:02:07 lr: 1.553754353351982e-05 loss: 0.0329 (0.0380) time: 3.0456 data: 0.0080 max mem: 33408 +Epoch: [29] [ 230/2639] eta: 2:01:39 lr: 1.5532689315275662e-05 loss: 0.0354 (0.0381) time: 3.0391 data: 0.0082 max mem: 33408 +Epoch: [29] [ 240/2639] eta: 2:01:10 lr: 1.5527834928467627e-05 loss: 0.0354 (0.0381) time: 3.0484 data: 0.0078 max mem: 33408 +Epoch: [29] [ 250/2639] eta: 2:00:33 lr: 1.55229803730313e-05 loss: 0.0343 (0.0380) time: 2.9979 data: 0.0079 max mem: 33408 +Epoch: [29] [ 260/2639] eta: 1:59:59 lr: 1.5518125648902225e-05 loss: 0.0322 (0.0378) time: 2.9732 data: 0.0081 max mem: 33408 +Epoch: [29] [ 270/2639] eta: 1:59:31 lr: 1.55132707560159e-05 loss: 0.0312 (0.0380) time: 3.0242 data: 0.0087 max mem: 33408 +Epoch: [29] [ 280/2639] eta: 1:59:01 lr: 1.5508415694307774e-05 loss: 0.0335 (0.0379) time: 3.0429 data: 0.0089 max mem: 33408 +Epoch: [29] [ 290/2639] eta: 1:58:28 lr: 1.550356046371324e-05 loss: 0.0325 (0.0377) time: 3.0115 data: 0.0083 max mem: 33408 +Epoch: [29] [ 300/2639] eta: 1:58:00 lr: 1.5498705064167667e-05 loss: 0.0293 (0.0374) time: 3.0220 data: 0.0079 max mem: 33408 +Epoch: [29] [ 310/2639] eta: 1:57:27 lr: 1.549384949560635e-05 loss: 0.0355 (0.0374) time: 3.0239 data: 0.0083 max mem: 33408 +Epoch: [29] [ 320/2639] eta: 1:57:00 lr: 1.548899375796456e-05 loss: 0.0360 (0.0374) time: 3.0350 data: 0.0084 max mem: 33408 +Epoch: [29] [ 330/2639] eta: 1:56:28 lr: 1.5484137851177497e-05 loss: 0.0292 (0.0371) time: 3.0354 data: 0.0079 max mem: 33408 +Epoch: [29] [ 340/2639] eta: 1:55:58 lr: 1.547928177518034e-05 loss: 0.0290 (0.0370) time: 3.0139 data: 0.0079 max mem: 33408 +Epoch: [29] [ 350/2639] eta: 1:55:31 lr: 1.5474425529908186e-05 loss: 0.0335 (0.0370) time: 3.0508 data: 0.0076 max mem: 33408 +Epoch: [29] [ 360/2639] eta: 1:55:02 lr: 1.5469569115296133e-05 loss: 0.0388 (0.0370) time: 3.0644 data: 0.0076 max mem: 33408 +Epoch: [29] [ 370/2639] eta: 1:54:27 lr: 1.5464712531279177e-05 loss: 0.0394 (0.0371) time: 3.0022 data: 0.0080 max mem: 33408 +Epoch: [29] [ 380/2639] eta: 1:53:54 lr: 1.5459855777792308e-05 loss: 0.0386 (0.0370) time: 2.9607 data: 0.0081 max mem: 33408 +Epoch: [29] [ 390/2639] eta: 1:53:20 lr: 1.5454998854770456e-05 loss: 0.0318 (0.0370) time: 2.9702 data: 0.0081 max mem: 33408 +Epoch: [29] [ 400/2639] eta: 1:52:50 lr: 1.5450141762148488e-05 loss: 0.0318 (0.0371) time: 2.9938 data: 0.0079 max mem: 33408 +Epoch: [29] [ 410/2639] eta: 1:52:22 lr: 1.544528449986125e-05 loss: 0.0326 (0.0371) time: 3.0504 data: 0.0077 max mem: 33408 +Epoch: [29] [ 420/2639] eta: 1:51:48 lr: 1.544042706784351e-05 loss: 0.0319 (0.0370) time: 3.0171 data: 0.0078 max mem: 33408 +Epoch: [29] [ 430/2639] eta: 1:51:15 lr: 1.543556946603002e-05 loss: 0.0319 (0.0370) time: 2.9590 data: 0.0080 max mem: 33408 +Epoch: [29] [ 440/2639] eta: 1:50:49 lr: 1.5430711694355456e-05 loss: 0.0315 (0.0370) time: 3.0353 data: 0.0078 max mem: 33408 +Epoch: [29] [ 450/2639] eta: 1:50:18 lr: 1.5425853752754473e-05 loss: 0.0300 (0.0369) time: 3.0603 data: 0.0080 max mem: 33408 +Epoch: [29] [ 460/2639] eta: 1:49:46 lr: 1.542099564116164e-05 loss: 0.0330 (0.0369) time: 2.9974 data: 0.0083 max mem: 33408 +Epoch: [29] [ 470/2639] eta: 1:49:19 lr: 1.5416137359511528e-05 loss: 0.0332 (0.0368) time: 3.0298 data: 0.0078 max mem: 33408 +Epoch: [29] [ 480/2639] eta: 1:48:49 lr: 1.541127890773861e-05 loss: 0.0308 (0.0368) time: 3.0650 data: 0.0077 max mem: 33408 +Epoch: [29] [ 490/2639] eta: 1:48:18 lr: 1.540642028577735e-05 loss: 0.0287 (0.0367) time: 3.0276 data: 0.0077 max mem: 33408 +Epoch: [29] [ 500/2639] eta: 1:47:46 lr: 1.5401561493562133e-05 loss: 0.0327 (0.0367) time: 2.9911 data: 0.0077 max mem: 33408 +Epoch: [29] [ 510/2639] eta: 1:47:18 lr: 1.5396702531027326e-05 loss: 0.0341 (0.0366) time: 3.0296 data: 0.0080 max mem: 33408 +Epoch: [29] [ 520/2639] eta: 1:46:47 lr: 1.5391843398107218e-05 loss: 0.0345 (0.0366) time: 3.0376 data: 0.0080 max mem: 33408 +Epoch: [29] [ 530/2639] eta: 1:46:19 lr: 1.5386984094736075e-05 loss: 0.0366 (0.0366) time: 3.0335 data: 0.0080 max mem: 33408 +Epoch: [29] [ 540/2639] eta: 1:45:48 lr: 1.5382124620848095e-05 loss: 0.0343 (0.0367) time: 3.0460 data: 0.0078 max mem: 33408 +Epoch: [29] [ 550/2639] eta: 1:45:18 lr: 1.5377264976377444e-05 loss: 0.0348 (0.0367) time: 3.0252 data: 0.0075 max mem: 33408 +Epoch: [29] [ 560/2639] eta: 1:44:49 lr: 1.537240516125822e-05 loss: 0.0342 (0.0366) time: 3.0452 data: 0.0079 max mem: 33408 +Epoch: [29] [ 570/2639] eta: 1:44:20 lr: 1.5367545175424496e-05 loss: 0.0308 (0.0368) time: 3.0566 data: 0.0081 max mem: 33408 +Epoch: [29] [ 580/2639] eta: 1:43:48 lr: 1.5362685018810267e-05 loss: 0.0342 (0.0367) time: 3.0132 data: 0.0083 max mem: 33408 +Epoch: [29] [ 590/2639] eta: 1:43:17 lr: 1.5357824691349514e-05 loss: 0.0345 (0.0368) time: 2.9937 data: 0.0083 max mem: 33408 +Epoch: [29] [ 600/2639] eta: 1:42:46 lr: 1.5352964192976137e-05 loss: 0.0363 (0.0369) time: 3.0073 data: 0.0078 max mem: 33408 +Epoch: [29] [ 610/2639] eta: 1:42:18 lr: 1.5348103523624016e-05 loss: 0.0311 (0.0367) time: 3.0433 data: 0.0075 max mem: 33408 +Epoch: [29] [ 620/2639] eta: 1:41:47 lr: 1.534324268322695e-05 loss: 0.0308 (0.0367) time: 3.0484 data: 0.0075 max mem: 33408 +Epoch: [29] [ 630/2639] eta: 1:41:16 lr: 1.533838167171872e-05 loss: 0.0334 (0.0367) time: 3.0086 data: 0.0075 max mem: 33408 +Epoch: [29] [ 640/2639] eta: 1:40:46 lr: 1.5333520489033042e-05 loss: 0.0356 (0.0367) time: 3.0192 data: 0.0078 max mem: 33408 +Epoch: [29] [ 650/2639] eta: 1:40:17 lr: 1.5328659135103584e-05 loss: 0.0338 (0.0367) time: 3.0414 data: 0.0081 max mem: 33408 +Epoch: [29] [ 660/2639] eta: 1:39:45 lr: 1.532379760986397e-05 loss: 0.0316 (0.0365) time: 3.0190 data: 0.0083 max mem: 33408 +Epoch: [29] [ 670/2639] eta: 1:39:14 lr: 1.531893591324776e-05 loss: 0.0278 (0.0365) time: 2.9810 data: 0.0084 max mem: 33408 +Epoch: [29] [ 680/2639] eta: 1:38:45 lr: 1.5314074045188495e-05 loss: 0.0326 (0.0364) time: 3.0249 data: 0.0080 max mem: 33408 +Epoch: [29] [ 690/2639] eta: 1:38:16 lr: 1.5309212005619632e-05 loss: 0.0314 (0.0365) time: 3.0659 data: 0.0078 max mem: 33408 +Epoch: [29] [ 700/2639] eta: 1:37:47 lr: 1.5304349794474603e-05 loss: 0.0364 (0.0365) time: 3.0625 data: 0.0077 max mem: 33408 +Epoch: [29] [ 710/2639] eta: 1:37:18 lr: 1.5299487411686777e-05 loss: 0.0363 (0.0364) time: 3.0745 data: 0.0080 max mem: 33408 +Epoch: [29] [ 720/2639] eta: 1:36:47 lr: 1.529462485718949e-05 loss: 0.0301 (0.0363) time: 3.0529 data: 0.0082 max mem: 33408 +Epoch: [29] [ 730/2639] eta: 1:36:17 lr: 1.5289762130915996e-05 loss: 0.0301 (0.0363) time: 3.0195 data: 0.0079 max mem: 33408 +Epoch: [29] [ 740/2639] eta: 1:35:47 lr: 1.5284899232799545e-05 loss: 0.0339 (0.0363) time: 3.0369 data: 0.0079 max mem: 33408 +Epoch: [29] [ 750/2639] eta: 1:35:19 lr: 1.5280036162773296e-05 loss: 0.0287 (0.0362) time: 3.0820 data: 0.0079 max mem: 33408 +Epoch: [29] [ 760/2639] eta: 1:34:50 lr: 1.527517292077039e-05 loss: 0.0287 (0.0363) time: 3.0942 data: 0.0084 max mem: 33408 +Epoch: [29] [ 770/2639] eta: 1:34:19 lr: 1.5270309506723888e-05 loss: 0.0341 (0.0363) time: 3.0397 data: 0.0085 max mem: 33408 +Epoch: [29] [ 780/2639] eta: 1:33:48 lr: 1.5265445920566833e-05 loss: 0.0341 (0.0362) time: 2.9962 data: 0.0077 max mem: 33408 +Epoch: [29] [ 790/2639] eta: 1:33:16 lr: 1.5260582162232188e-05 loss: 0.0298 (0.0362) time: 2.9761 data: 0.0081 max mem: 33408 +Epoch: [29] [ 800/2639] eta: 1:32:45 lr: 1.5255718231652896e-05 loss: 0.0316 (0.0362) time: 2.9773 data: 0.0084 max mem: 33408 +Epoch: [29] [ 810/2639] eta: 1:32:16 lr: 1.5250854128761821e-05 loss: 0.0347 (0.0362) time: 3.0286 data: 0.0078 max mem: 33408 +Epoch: [29] [ 820/2639] eta: 1:31:44 lr: 1.5245989853491801e-05 loss: 0.0355 (0.0363) time: 3.0033 data: 0.0079 max mem: 33408 +Epoch: [29] [ 830/2639] eta: 1:31:14 lr: 1.5241125405775605e-05 loss: 0.0334 (0.0362) time: 2.9983 data: 0.0085 max mem: 33408 +Epoch: [29] [ 840/2639] eta: 1:30:44 lr: 1.5236260785545973e-05 loss: 0.0329 (0.0362) time: 3.0388 data: 0.0079 max mem: 33408 +Epoch: [29] [ 850/2639] eta: 1:30:12 lr: 1.5231395992735566e-05 loss: 0.0329 (0.0363) time: 2.9823 data: 0.0075 max mem: 33408 +Epoch: [29] [ 860/2639] eta: 1:29:40 lr: 1.522653102727703e-05 loss: 0.0380 (0.0363) time: 2.9539 data: 0.0077 max mem: 33408 +Epoch: [29] [ 870/2639] eta: 1:29:09 lr: 1.5221665889102924e-05 loss: 0.0389 (0.0364) time: 2.9828 data: 0.0078 max mem: 33408 +Epoch: [29] [ 880/2639] eta: 1:28:37 lr: 1.5216800578145785e-05 loss: 0.0356 (0.0363) time: 2.9669 data: 0.0081 max mem: 33408 +Epoch: [29] [ 890/2639] eta: 1:28:06 lr: 1.5211935094338095e-05 loss: 0.0330 (0.0363) time: 2.9403 data: 0.0079 max mem: 33408 +Epoch: [29] [ 900/2639] eta: 1:27:35 lr: 1.5207069437612268e-05 loss: 0.0323 (0.0363) time: 2.9784 data: 0.0077 max mem: 33408 +Epoch: [29] [ 910/2639] eta: 1:27:05 lr: 1.5202203607900692e-05 loss: 0.0321 (0.0362) time: 3.0191 data: 0.0077 max mem: 33408 +Epoch: [29] [ 920/2639] eta: 1:26:35 lr: 1.5197337605135678e-05 loss: 0.0326 (0.0362) time: 3.0171 data: 0.0077 max mem: 33408 +Epoch: [29] [ 930/2639] eta: 1:26:04 lr: 1.5192471429249516e-05 loss: 0.0327 (0.0364) time: 2.9954 data: 0.0078 max mem: 33408 +Epoch: [29] [ 940/2639] eta: 1:25:34 lr: 1.5187605080174418e-05 loss: 0.0360 (0.0365) time: 3.0084 data: 0.0079 max mem: 33408 +Epoch: [29] [ 950/2639] eta: 1:25:04 lr: 1.5182738557842569e-05 loss: 0.0353 (0.0365) time: 3.0565 data: 0.0082 max mem: 33408 +Epoch: [29] [ 960/2639] eta: 1:24:35 lr: 1.5177871862186075e-05 loss: 0.0329 (0.0365) time: 3.0750 data: 0.0083 max mem: 33408 +Epoch: [29] [ 970/2639] eta: 1:24:04 lr: 1.5173004993137028e-05 loss: 0.0329 (0.0364) time: 3.0221 data: 0.0082 max mem: 33408 +Epoch: [29] [ 980/2639] eta: 1:23:33 lr: 1.5168137950627429e-05 loss: 0.0314 (0.0364) time: 2.9765 data: 0.0080 max mem: 33408 +Epoch: [29] [ 990/2639] eta: 1:23:05 lr: 1.5163270734589267e-05 loss: 0.0312 (0.0364) time: 3.0561 data: 0.0078 max mem: 33408 +Epoch: [29] [1000/2639] eta: 1:22:34 lr: 1.5158403344954448e-05 loss: 0.0334 (0.0364) time: 3.0650 data: 0.0082 max mem: 33408 +Epoch: [29] [1010/2639] eta: 1:22:04 lr: 1.5153535781654845e-05 loss: 0.0360 (0.0365) time: 3.0121 data: 0.0083 max mem: 33408 +Epoch: [29] [1020/2639] eta: 1:21:35 lr: 1.5148668044622275e-05 loss: 0.0360 (0.0364) time: 3.0564 data: 0.0078 max mem: 33408 +Epoch: [29] [1030/2639] eta: 1:21:03 lr: 1.5143800133788506e-05 loss: 0.0333 (0.0364) time: 3.0156 data: 0.0078 max mem: 33408 +Epoch: [29] [1040/2639] eta: 1:20:33 lr: 1.5138932049085247e-05 loss: 0.0286 (0.0363) time: 2.9810 data: 0.0077 max mem: 33408 +Epoch: [29] [1050/2639] eta: 1:20:03 lr: 1.513406379044417e-05 loss: 0.0298 (0.0363) time: 3.0352 data: 0.0076 max mem: 33408 +Epoch: [29] [1060/2639] eta: 1:19:32 lr: 1.5129195357796877e-05 loss: 0.0342 (0.0363) time: 3.0138 data: 0.0078 max mem: 33408 +Epoch: [29] [1070/2639] eta: 1:19:01 lr: 1.5124326751074937e-05 loss: 0.0300 (0.0363) time: 2.9674 data: 0.0078 max mem: 33408 +Epoch: [29] [1080/2639] eta: 1:18:31 lr: 1.5119457970209858e-05 loss: 0.0300 (0.0363) time: 3.0052 data: 0.0079 max mem: 33408 +Epoch: [29] [1090/2639] eta: 1:18:01 lr: 1.5114589015133098e-05 loss: 0.0323 (0.0362) time: 3.0572 data: 0.0080 max mem: 33408 +Epoch: [29] [1100/2639] eta: 1:17:32 lr: 1.510971988577606e-05 loss: 0.0323 (0.0362) time: 3.0594 data: 0.0079 max mem: 33408 +Epoch: [29] [1110/2639] eta: 1:17:02 lr: 1.5104850582070101e-05 loss: 0.0305 (0.0362) time: 3.0455 data: 0.0080 max mem: 33408 +Epoch: [29] [1120/2639] eta: 1:16:32 lr: 1.509998110394653e-05 loss: 0.0284 (0.0362) time: 3.0422 data: 0.0077 max mem: 33408 +Epoch: [29] [1130/2639] eta: 1:16:02 lr: 1.509511145133659e-05 loss: 0.0284 (0.0362) time: 3.0425 data: 0.0077 max mem: 33408 +Epoch: [29] [1140/2639] eta: 1:15:31 lr: 1.5090241624171491e-05 loss: 0.0313 (0.0362) time: 3.0148 data: 0.0080 max mem: 33408 +Epoch: [29] [1150/2639] eta: 1:15:01 lr: 1.508537162238237e-05 loss: 0.0337 (0.0362) time: 3.0050 data: 0.0078 max mem: 33408 +Epoch: [29] [1160/2639] eta: 1:14:31 lr: 1.508050144590033e-05 loss: 0.0347 (0.0362) time: 3.0412 data: 0.0078 max mem: 33408 +Epoch: [29] [1170/2639] eta: 1:14:00 lr: 1.507563109465641e-05 loss: 0.0326 (0.0363) time: 3.0219 data: 0.0085 max mem: 33408 +Epoch: [29] [1180/2639] eta: 1:13:30 lr: 1.5070760568581613e-05 loss: 0.0338 (0.0363) time: 3.0005 data: 0.0083 max mem: 33408 +Epoch: [29] [1190/2639] eta: 1:12:59 lr: 1.5065889867606863e-05 loss: 0.0369 (0.0363) time: 2.9959 data: 0.0080 max mem: 33408 +Epoch: [29] [1200/2639] eta: 1:12:29 lr: 1.5061018991663067e-05 loss: 0.0359 (0.0363) time: 2.9912 data: 0.0083 max mem: 33408 +Epoch: [29] [1210/2639] eta: 1:11:59 lr: 1.5056147940681042e-05 loss: 0.0334 (0.0363) time: 3.0209 data: 0.0078 max mem: 33408 +Epoch: [29] [1220/2639] eta: 1:11:28 lr: 1.5051276714591591e-05 loss: 0.0353 (0.0363) time: 3.0262 data: 0.0076 max mem: 33408 +Epoch: [29] [1230/2639] eta: 1:10:59 lr: 1.504640531332543e-05 loss: 0.0374 (0.0363) time: 3.0528 data: 0.0077 max mem: 33408 +Epoch: [29] [1240/2639] eta: 1:10:28 lr: 1.5041533736813246e-05 loss: 0.0328 (0.0363) time: 3.0396 data: 0.0074 max mem: 33408 +Epoch: [29] [1250/2639] eta: 1:09:58 lr: 1.5036661984985662e-05 loss: 0.0301 (0.0363) time: 3.0143 data: 0.0078 max mem: 33408 +Epoch: [29] [1260/2639] eta: 1:09:29 lr: 1.5031790057773256e-05 loss: 0.0301 (0.0362) time: 3.0621 data: 0.0079 max mem: 33408 +Epoch: [29] [1270/2639] eta: 1:08:59 lr: 1.5026917955106545e-05 loss: 0.0352 (0.0363) time: 3.0846 data: 0.0078 max mem: 33408 +Epoch: [29] [1280/2639] eta: 1:08:29 lr: 1.5022045676916008e-05 loss: 0.0337 (0.0363) time: 3.0615 data: 0.0079 max mem: 33408 +Epoch: [29] [1290/2639] eta: 1:07:59 lr: 1.501717322313205e-05 loss: 0.0337 (0.0363) time: 3.0208 data: 0.0076 max mem: 33408 +Epoch: [29] [1300/2639] eta: 1:07:29 lr: 1.5012300593685044e-05 loss: 0.0347 (0.0363) time: 3.0203 data: 0.0076 max mem: 33408 +Epoch: [29] [1310/2639] eta: 1:06:58 lr: 1.5007427788505293e-05 loss: 0.0347 (0.0363) time: 3.0223 data: 0.0078 max mem: 33408 +Epoch: [29] [1320/2639] eta: 1:06:28 lr: 1.5002554807523067e-05 loss: 0.0326 (0.0363) time: 2.9989 data: 0.0078 max mem: 33408 +Epoch: [29] [1330/2639] eta: 1:05:58 lr: 1.4997681650668557e-05 loss: 0.0311 (0.0363) time: 3.0217 data: 0.0079 max mem: 33408 +Epoch: [29] [1340/2639] eta: 1:05:27 lr: 1.4992808317871931e-05 loss: 0.0368 (0.0363) time: 3.0332 data: 0.0079 max mem: 33408 +Epoch: [29] [1350/2639] eta: 1:04:57 lr: 1.4987934809063275e-05 loss: 0.0376 (0.0363) time: 3.0396 data: 0.0076 max mem: 33408 +Epoch: [29] [1360/2639] eta: 1:04:28 lr: 1.4983061124172642e-05 loss: 0.0355 (0.0363) time: 3.0627 data: 0.0076 max mem: 33408 +Epoch: [29] [1370/2639] eta: 1:03:58 lr: 1.497818726313003e-05 loss: 0.0347 (0.0363) time: 3.0599 data: 0.0075 max mem: 33408 +Epoch: [29] [1380/2639] eta: 1:03:28 lr: 1.4973313225865374e-05 loss: 0.0404 (0.0364) time: 3.0475 data: 0.0078 max mem: 33408 +Epoch: [29] [1390/2639] eta: 1:02:58 lr: 1.4968439012308563e-05 loss: 0.0359 (0.0364) time: 3.0472 data: 0.0082 max mem: 33408 +Epoch: [29] [1400/2639] eta: 1:02:27 lr: 1.4963564622389425e-05 loss: 0.0347 (0.0364) time: 3.0211 data: 0.0083 max mem: 33408 +Epoch: [29] [1410/2639] eta: 1:01:57 lr: 1.4958690056037752e-05 loss: 0.0373 (0.0364) time: 3.0239 data: 0.0081 max mem: 33408 +Epoch: [29] [1420/2639] eta: 1:01:27 lr: 1.4953815313183261e-05 loss: 0.0352 (0.0364) time: 3.0548 data: 0.0077 max mem: 33408 +Epoch: [29] [1430/2639] eta: 1:00:57 lr: 1.4948940393755633e-05 loss: 0.0328 (0.0364) time: 3.0560 data: 0.0078 max mem: 33408 +Epoch: [29] [1440/2639] eta: 1:00:27 lr: 1.4944065297684484e-05 loss: 0.0366 (0.0365) time: 3.0417 data: 0.0085 max mem: 33408 +Epoch: [29] [1450/2639] eta: 0:59:56 lr: 1.4939190024899382e-05 loss: 0.0383 (0.0365) time: 2.9838 data: 0.0089 max mem: 33408 +Epoch: [29] [1460/2639] eta: 0:59:25 lr: 1.4934314575329838e-05 loss: 0.0327 (0.0365) time: 2.9568 data: 0.0091 max mem: 33408 +Epoch: [29] [1470/2639] eta: 0:58:55 lr: 1.4929438948905319e-05 loss: 0.0340 (0.0365) time: 3.0121 data: 0.0091 max mem: 33408 +Epoch: [29] [1480/2639] eta: 0:58:25 lr: 1.4924563145555217e-05 loss: 0.0332 (0.0365) time: 3.0511 data: 0.0080 max mem: 33408 +Epoch: [29] [1490/2639] eta: 0:57:54 lr: 1.4919687165208897e-05 loss: 0.0327 (0.0365) time: 3.0074 data: 0.0072 max mem: 33408 +Epoch: [29] [1500/2639] eta: 0:57:24 lr: 1.4914811007795647e-05 loss: 0.0355 (0.0365) time: 3.0136 data: 0.0076 max mem: 33408 +Epoch: [29] [1510/2639] eta: 0:56:54 lr: 1.4909934673244725e-05 loss: 0.0368 (0.0365) time: 3.0409 data: 0.0076 max mem: 33408 +Epoch: [29] [1520/2639] eta: 0:56:24 lr: 1.4905058161485299e-05 loss: 0.0375 (0.0365) time: 3.0501 data: 0.0075 max mem: 33408 +Epoch: [29] [1530/2639] eta: 0:55:54 lr: 1.4900181472446528e-05 loss: 0.0341 (0.0365) time: 3.0661 data: 0.0077 max mem: 33408 +Epoch: [29] [1540/2639] eta: 0:55:24 lr: 1.4895304606057475e-05 loss: 0.0313 (0.0366) time: 3.0363 data: 0.0078 max mem: 33408 +Epoch: [29] [1550/2639] eta: 0:54:54 lr: 1.4890427562247183e-05 loss: 0.0351 (0.0366) time: 3.0097 data: 0.0081 max mem: 33408 +Epoch: [29] [1560/2639] eta: 0:54:23 lr: 1.4885550340944612e-05 loss: 0.0339 (0.0366) time: 3.0239 data: 0.0078 max mem: 33408 +Epoch: [29] [1570/2639] eta: 0:53:53 lr: 1.4880672942078694e-05 loss: 0.0334 (0.0366) time: 3.0438 data: 0.0075 max mem: 33408 +Epoch: [29] [1580/2639] eta: 0:53:23 lr: 1.4875795365578282e-05 loss: 0.0404 (0.0367) time: 3.0081 data: 0.0076 max mem: 33408 +Epoch: [29] [1590/2639] eta: 0:52:53 lr: 1.4870917611372195e-05 loss: 0.0340 (0.0367) time: 3.0134 data: 0.0077 max mem: 33408 +Epoch: [29] [1600/2639] eta: 0:52:23 lr: 1.4866039679389179e-05 loss: 0.0331 (0.0368) time: 3.0619 data: 0.0075 max mem: 33408 +Epoch: [29] [1610/2639] eta: 0:51:53 lr: 1.4861161569557943e-05 loss: 0.0327 (0.0367) time: 3.0586 data: 0.0074 max mem: 33408 +Epoch: [29] [1620/2639] eta: 0:51:23 lr: 1.485628328180714e-05 loss: 0.0350 (0.0367) time: 3.0669 data: 0.0076 max mem: 33408 +Epoch: [29] [1630/2639] eta: 0:50:53 lr: 1.4851404816065346e-05 loss: 0.0350 (0.0367) time: 3.0687 data: 0.0074 max mem: 33408 +Epoch: [29] [1640/2639] eta: 0:50:22 lr: 1.4846526172261111e-05 loss: 0.0306 (0.0367) time: 3.0203 data: 0.0074 max mem: 33408 +Epoch: [29] [1650/2639] eta: 0:49:52 lr: 1.484164735032291e-05 loss: 0.0356 (0.0367) time: 3.0006 data: 0.0075 max mem: 33408 +Epoch: [29] [1660/2639] eta: 0:49:22 lr: 1.4836768350179176e-05 loss: 0.0356 (0.0367) time: 3.0138 data: 0.0071 max mem: 33408 +Epoch: [29] [1670/2639] eta: 0:48:51 lr: 1.4831889171758276e-05 loss: 0.0354 (0.0367) time: 3.0068 data: 0.0073 max mem: 33408 +Epoch: [29] [1680/2639] eta: 0:48:21 lr: 1.4827009814988536e-05 loss: 0.0342 (0.0367) time: 2.9921 data: 0.0078 max mem: 33408 +Epoch: [29] [1690/2639] eta: 0:47:50 lr: 1.4822130279798205e-05 loss: 0.0378 (0.0367) time: 3.0082 data: 0.0076 max mem: 33408 +Epoch: [29] [1700/2639] eta: 0:47:20 lr: 1.4817250566115507e-05 loss: 0.0380 (0.0368) time: 3.0321 data: 0.0074 max mem: 33408 +Epoch: [29] [1710/2639] eta: 0:46:50 lr: 1.4812370673868578e-05 loss: 0.0359 (0.0367) time: 3.0097 data: 0.0077 max mem: 33408 +Epoch: [29] [1720/2639] eta: 0:46:20 lr: 1.4807490602985533e-05 loss: 0.0359 (0.0368) time: 3.0094 data: 0.0079 max mem: 33408 +Epoch: [29] [1730/2639] eta: 0:45:49 lr: 1.4802610353394397e-05 loss: 0.0325 (0.0368) time: 3.0367 data: 0.0076 max mem: 33408 +Epoch: [29] [1740/2639] eta: 0:45:19 lr: 1.4797729925023169e-05 loss: 0.0311 (0.0368) time: 3.0391 data: 0.0075 max mem: 33408 +Epoch: [29] [1750/2639] eta: 0:44:49 lr: 1.4792849317799768e-05 loss: 0.0342 (0.0368) time: 3.0188 data: 0.0075 max mem: 33408 +Epoch: [29] [1760/2639] eta: 0:44:19 lr: 1.4787968531652083e-05 loss: 0.0349 (0.0368) time: 3.0374 data: 0.0074 max mem: 33408 +Epoch: [29] [1770/2639] eta: 0:43:49 lr: 1.4783087566507922e-05 loss: 0.0339 (0.0368) time: 3.0776 data: 0.0076 max mem: 33408 +Epoch: [29] [1780/2639] eta: 0:43:18 lr: 1.477820642229506e-05 loss: 0.0315 (0.0367) time: 3.0398 data: 0.0077 max mem: 33408 +Epoch: [29] [1790/2639] eta: 0:42:48 lr: 1.4773325098941197e-05 loss: 0.0310 (0.0367) time: 3.0077 data: 0.0077 max mem: 33408 +Epoch: [29] [1800/2639] eta: 0:42:18 lr: 1.4768443596373994e-05 loss: 0.0280 (0.0367) time: 3.0279 data: 0.0078 max mem: 33408 +Epoch: [29] [1810/2639] eta: 0:41:48 lr: 1.4763561914521038e-05 loss: 0.0359 (0.0368) time: 3.0688 data: 0.0076 max mem: 33408 +Epoch: [29] [1820/2639] eta: 0:41:18 lr: 1.475868005330988e-05 loss: 0.0380 (0.0368) time: 3.0823 data: 0.0073 max mem: 33408 +Epoch: [29] [1830/2639] eta: 0:40:48 lr: 1.4753798012667997e-05 loss: 0.0379 (0.0368) time: 3.0640 data: 0.0074 max mem: 33408 +Epoch: [29] [1840/2639] eta: 0:40:17 lr: 1.474891579252283e-05 loss: 0.0361 (0.0368) time: 3.0148 data: 0.0080 max mem: 33408 +Epoch: [29] [1850/2639] eta: 0:39:47 lr: 1.474403339280174e-05 loss: 0.0317 (0.0368) time: 2.9895 data: 0.0081 max mem: 33408 +Epoch: [29] [1860/2639] eta: 0:39:17 lr: 1.4739150813432049e-05 loss: 0.0305 (0.0368) time: 3.0150 data: 0.0079 max mem: 33408 +Epoch: [29] [1870/2639] eta: 0:38:47 lr: 1.4734268054341022e-05 loss: 0.0353 (0.0368) time: 3.0335 data: 0.0081 max mem: 33408 +Epoch: [29] [1880/2639] eta: 0:38:16 lr: 1.4729385115455856e-05 loss: 0.0354 (0.0368) time: 3.0437 data: 0.0084 max mem: 33408 +Epoch: [29] [1890/2639] eta: 0:37:46 lr: 1.472450199670371e-05 loss: 0.0346 (0.0368) time: 3.0280 data: 0.0082 max mem: 33408 +Epoch: [29] [1900/2639] eta: 0:37:16 lr: 1.4719618698011667e-05 loss: 0.0346 (0.0368) time: 3.0306 data: 0.0081 max mem: 33408 +Epoch: [29] [1910/2639] eta: 0:36:46 lr: 1.4714735219306768e-05 loss: 0.0355 (0.0368) time: 3.0502 data: 0.0080 max mem: 33408 +Epoch: [29] [1920/2639] eta: 0:36:15 lr: 1.4709851560515986e-05 loss: 0.0347 (0.0368) time: 3.0368 data: 0.0080 max mem: 33408 +Epoch: [29] [1930/2639] eta: 0:35:45 lr: 1.4704967721566253e-05 loss: 0.0309 (0.0368) time: 3.0107 data: 0.0081 max mem: 33408 +Epoch: [29] [1940/2639] eta: 0:35:15 lr: 1.4700083702384426e-05 loss: 0.0310 (0.0368) time: 2.9908 data: 0.0081 max mem: 33408 +Epoch: [29] [1950/2639] eta: 0:34:44 lr: 1.4695199502897322e-05 loss: 0.0322 (0.0368) time: 3.0112 data: 0.0082 max mem: 33408 +Epoch: [29] [1960/2639] eta: 0:34:14 lr: 1.4690315123031683e-05 loss: 0.0331 (0.0368) time: 3.0360 data: 0.0082 max mem: 33408 +Epoch: [29] [1970/2639] eta: 0:33:44 lr: 1.468543056271422e-05 loss: 0.0344 (0.0368) time: 3.0269 data: 0.0083 max mem: 33408 +Epoch: [29] [1980/2639] eta: 0:33:14 lr: 1.4680545821871555e-05 loss: 0.0333 (0.0368) time: 3.0336 data: 0.0086 max mem: 33408 +Epoch: [29] [1990/2639] eta: 0:32:43 lr: 1.4675660900430285e-05 loss: 0.0333 (0.0368) time: 3.0372 data: 0.0082 max mem: 33408 +Epoch: [29] [2000/2639] eta: 0:32:13 lr: 1.4670775798316921e-05 loss: 0.0313 (0.0367) time: 3.0054 data: 0.0078 max mem: 33408 +Epoch: [29] [2010/2639] eta: 0:31:43 lr: 1.4665890515457945e-05 loss: 0.0298 (0.0367) time: 3.0322 data: 0.0076 max mem: 33408 +Epoch: [29] [2020/2639] eta: 0:31:13 lr: 1.4661005051779752e-05 loss: 0.0316 (0.0367) time: 3.0877 data: 0.0075 max mem: 33408 +Epoch: [29] [2030/2639] eta: 0:30:43 lr: 1.465611940720871e-05 loss: 0.0300 (0.0367) time: 3.0811 data: 0.0076 max mem: 33408 +Epoch: [29] [2040/2639] eta: 0:30:12 lr: 1.4651233581671103e-05 loss: 0.0312 (0.0367) time: 3.0376 data: 0.0078 max mem: 33408 +Epoch: [29] [2050/2639] eta: 0:29:42 lr: 1.464634757509318e-05 loss: 0.0343 (0.0366) time: 2.9946 data: 0.0081 max mem: 33408 +Epoch: [29] [2060/2639] eta: 0:29:12 lr: 1.4641461387401115e-05 loss: 0.0348 (0.0367) time: 2.9922 data: 0.0079 max mem: 33408 +Epoch: [29] [2070/2639] eta: 0:28:41 lr: 1.4636575018521037e-05 loss: 0.0373 (0.0368) time: 3.0022 data: 0.0079 max mem: 33408 +Epoch: [29] [2080/2639] eta: 0:28:11 lr: 1.4631688468379008e-05 loss: 0.0370 (0.0368) time: 2.9916 data: 0.0085 max mem: 33408 +Epoch: [29] [2090/2639] eta: 0:27:41 lr: 1.4626801736901039e-05 loss: 0.0299 (0.0367) time: 2.9596 data: 0.0083 max mem: 33408 +Epoch: [29] [2100/2639] eta: 0:27:10 lr: 1.4621914824013078e-05 loss: 0.0294 (0.0367) time: 2.9585 data: 0.0080 max mem: 33408 +Epoch: [29] [2110/2639] eta: 0:26:40 lr: 1.461702772964102e-05 loss: 0.0340 (0.0367) time: 3.0186 data: 0.0079 max mem: 33408 +Epoch: [29] [2120/2639] eta: 0:26:10 lr: 1.4612140453710708e-05 loss: 0.0361 (0.0367) time: 3.0070 data: 0.0080 max mem: 33408 +Epoch: [29] [2130/2639] eta: 0:25:39 lr: 1.4607252996147902e-05 loss: 0.0341 (0.0367) time: 2.9985 data: 0.0080 max mem: 33408 +Epoch: [29] [2140/2639] eta: 0:25:09 lr: 1.4602365356878342e-05 loss: 0.0342 (0.0367) time: 3.0362 data: 0.0081 max mem: 33408 +Epoch: [29] [2150/2639] eta: 0:24:39 lr: 1.4597477535827671e-05 loss: 0.0352 (0.0367) time: 3.0206 data: 0.0080 max mem: 33408 +Epoch: [29] [2160/2639] eta: 0:24:08 lr: 1.459258953292151e-05 loss: 0.0286 (0.0367) time: 2.9969 data: 0.0079 max mem: 33408 +Epoch: [29] [2170/2639] eta: 0:23:38 lr: 1.458770134808539e-05 loss: 0.0300 (0.0367) time: 3.0122 data: 0.0081 max mem: 33408 +Epoch: [29] [2180/2639] eta: 0:23:08 lr: 1.458281298124481e-05 loss: 0.0329 (0.0367) time: 3.0591 data: 0.0083 max mem: 33408 +Epoch: [29] [2190/2639] eta: 0:22:38 lr: 1.4577924432325185e-05 loss: 0.0328 (0.0368) time: 3.0379 data: 0.0080 max mem: 33408 +Epoch: [29] [2200/2639] eta: 0:22:08 lr: 1.4573035701251897e-05 loss: 0.0328 (0.0368) time: 3.0051 data: 0.0077 max mem: 33408 +Epoch: [29] [2210/2639] eta: 0:21:37 lr: 1.4568146787950252e-05 loss: 0.0332 (0.0368) time: 3.0526 data: 0.0079 max mem: 33408 +Epoch: [29] [2220/2639] eta: 0:21:07 lr: 1.4563257692345508e-05 loss: 0.0329 (0.0368) time: 3.0837 data: 0.0078 max mem: 33408 +Epoch: [29] [2230/2639] eta: 0:20:37 lr: 1.4558368414362855e-05 loss: 0.0328 (0.0368) time: 3.0711 data: 0.0079 max mem: 33408 +Epoch: [29] [2240/2639] eta: 0:20:07 lr: 1.4553478953927435e-05 loss: 0.0338 (0.0368) time: 3.0348 data: 0.0083 max mem: 33408 +Epoch: [29] [2250/2639] eta: 0:19:36 lr: 1.454858931096432e-05 loss: 0.0290 (0.0367) time: 2.9917 data: 0.0080 max mem: 33408 +Epoch: [29] [2260/2639] eta: 0:19:06 lr: 1.4543699485398534e-05 loss: 0.0324 (0.0367) time: 2.9973 data: 0.0079 max mem: 33408 +Epoch: [29] [2270/2639] eta: 0:18:36 lr: 1.4538809477155033e-05 loss: 0.0340 (0.0367) time: 3.0409 data: 0.0079 max mem: 33408 +Epoch: [29] [2280/2639] eta: 0:18:06 lr: 1.4533919286158723e-05 loss: 0.0323 (0.0367) time: 3.0207 data: 0.0080 max mem: 33408 +Epoch: [29] [2290/2639] eta: 0:17:35 lr: 1.4529028912334438e-05 loss: 0.0292 (0.0367) time: 3.0256 data: 0.0084 max mem: 33408 +Epoch: [29] [2300/2639] eta: 0:17:05 lr: 1.4524138355606975e-05 loss: 0.0303 (0.0367) time: 3.0718 data: 0.0083 max mem: 33408 +Epoch: [29] [2310/2639] eta: 0:16:35 lr: 1.4519247615901044e-05 loss: 0.0284 (0.0367) time: 3.0642 data: 0.0082 max mem: 33408 +Epoch: [29] [2320/2639] eta: 0:16:05 lr: 1.4514356693141317e-05 loss: 0.0284 (0.0367) time: 3.0251 data: 0.0082 max mem: 33408 +Epoch: [29] [2330/2639] eta: 0:15:34 lr: 1.4509465587252396e-05 loss: 0.0331 (0.0367) time: 2.9927 data: 0.0085 max mem: 33408 +Epoch: [29] [2340/2639] eta: 0:15:04 lr: 1.4504574298158837e-05 loss: 0.0324 (0.0367) time: 3.0021 data: 0.0086 max mem: 33408 +Epoch: [29] [2350/2639] eta: 0:14:34 lr: 1.4499682825785112e-05 loss: 0.0324 (0.0367) time: 3.0048 data: 0.0081 max mem: 33408 +Epoch: [29] [2360/2639] eta: 0:14:04 lr: 1.449479117005566e-05 loss: 0.0341 (0.0367) time: 3.0117 data: 0.0080 max mem: 33408 +Epoch: [29] [2370/2639] eta: 0:13:33 lr: 1.448989933089485e-05 loss: 0.0315 (0.0367) time: 3.0011 data: 0.0079 max mem: 33408 +Epoch: [29] [2380/2639] eta: 0:13:03 lr: 1.4485007308226977e-05 loss: 0.0315 (0.0367) time: 2.9796 data: 0.0079 max mem: 33408 +Epoch: [29] [2390/2639] eta: 0:12:33 lr: 1.448011510197631e-05 loss: 0.0385 (0.0367) time: 2.9649 data: 0.0080 max mem: 33408 +Epoch: [29] [2400/2639] eta: 0:12:02 lr: 1.447522271206702e-05 loss: 0.0347 (0.0367) time: 2.9654 data: 0.0083 max mem: 33408 +Epoch: [29] [2410/2639] eta: 0:11:32 lr: 1.4470330138423249e-05 loss: 0.0397 (0.0367) time: 2.9834 data: 0.0083 max mem: 33408 +Epoch: [29] [2420/2639] eta: 0:11:02 lr: 1.4465437380969057e-05 loss: 0.0388 (0.0367) time: 3.0026 data: 0.0081 max mem: 33408 +Epoch: [29] [2430/2639] eta: 0:10:32 lr: 1.4460544439628462e-05 loss: 0.0314 (0.0367) time: 3.0039 data: 0.0086 max mem: 33408 +Epoch: [29] [2440/2639] eta: 0:10:01 lr: 1.4455651314325404e-05 loss: 0.0306 (0.0367) time: 3.0272 data: 0.0085 max mem: 33408 +Epoch: [29] [2450/2639] eta: 0:09:31 lr: 1.4450758004983787e-05 loss: 0.0298 (0.0367) time: 3.0465 data: 0.0080 max mem: 33408 +Epoch: [29] [2460/2639] eta: 0:09:01 lr: 1.4445864511527423e-05 loss: 0.0304 (0.0367) time: 3.0267 data: 0.0080 max mem: 33408 +Epoch: [29] [2470/2639] eta: 0:08:31 lr: 1.4440970833880097e-05 loss: 0.0349 (0.0367) time: 3.0246 data: 0.0081 max mem: 33408 +Epoch: [29] [2480/2639] eta: 0:08:00 lr: 1.4436076971965504e-05 loss: 0.0349 (0.0367) time: 3.0253 data: 0.0080 max mem: 33408 +Epoch: [29] [2490/2639] eta: 0:07:30 lr: 1.4431182925707304e-05 loss: 0.0321 (0.0367) time: 3.0249 data: 0.0079 max mem: 33408 +Epoch: [29] [2500/2639] eta: 0:07:00 lr: 1.4426288695029075e-05 loss: 0.0321 (0.0367) time: 3.0089 data: 0.0084 max mem: 33408 +Epoch: [29] [2510/2639] eta: 0:06:30 lr: 1.4421394279854355e-05 loss: 0.0360 (0.0367) time: 3.0060 data: 0.0082 max mem: 33408 +Epoch: [29] [2520/2639] eta: 0:05:59 lr: 1.4416499680106601e-05 loss: 0.0357 (0.0367) time: 3.0433 data: 0.0079 max mem: 33408 +Epoch: [29] [2530/2639] eta: 0:05:29 lr: 1.4411604895709229e-05 loss: 0.0312 (0.0367) time: 3.0296 data: 0.0080 max mem: 33408 +Epoch: [29] [2540/2639] eta: 0:04:59 lr: 1.4406709926585577e-05 loss: 0.0291 (0.0367) time: 3.0331 data: 0.0080 max mem: 33408 +Epoch: [29] [2550/2639] eta: 0:04:29 lr: 1.440181477265894e-05 loss: 0.0306 (0.0367) time: 3.0297 data: 0.0076 max mem: 33408 +Epoch: [29] [2560/2639] eta: 0:03:58 lr: 1.4396919433852527e-05 loss: 0.0317 (0.0367) time: 2.9507 data: 0.0075 max mem: 33408 +Epoch: [29] [2570/2639] eta: 0:03:28 lr: 1.4392023910089514e-05 loss: 0.0328 (0.0367) time: 2.9691 data: 0.0077 max mem: 33408 +Epoch: [29] [2580/2639] eta: 0:02:58 lr: 1.4387128201292995e-05 loss: 0.0348 (0.0367) time: 3.0153 data: 0.0077 max mem: 33408 +Epoch: [29] [2590/2639] eta: 0:02:28 lr: 1.4382232307386015e-05 loss: 0.0342 (0.0367) time: 3.0011 data: 0.0079 max mem: 33408 +Epoch: [29] [2600/2639] eta: 0:01:57 lr: 1.437733622829156e-05 loss: 0.0342 (0.0367) time: 3.0276 data: 0.0078 max mem: 33408 +Epoch: [29] [2610/2639] eta: 0:01:27 lr: 1.4372439963932535e-05 loss: 0.0329 (0.0367) time: 3.0771 data: 0.0078 max mem: 33408 +Epoch: [29] [2620/2639] eta: 0:00:57 lr: 1.4367543514231812e-05 loss: 0.0299 (0.0367) time: 3.0495 data: 0.0079 max mem: 33408 +Epoch: [29] [2630/2639] eta: 0:00:27 lr: 1.4362646879112177e-05 loss: 0.0311 (0.0367) time: 3.0206 data: 0.0077 max mem: 33408 +Epoch: [29] Total time: 2:13:01 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 2:16:14 time: 3.1769 data: 3.0417 max mem: 33408 +Test: [ 100/2573] eta: 0:04:28 time: 0.0777 data: 0.0015 max mem: 33408 +Test: [ 200/2573] eta: 0:03:44 time: 0.0801 data: 0.0014 max mem: 33408 +Test: [ 300/2573] eta: 0:03:22 time: 0.0807 data: 0.0014 max mem: 33408 +Test: [ 400/2573] eta: 0:03:08 time: 0.0831 data: 0.0015 max mem: 33408 +Test: [ 500/2573] eta: 0:02:57 time: 0.0811 data: 0.0015 max mem: 33408 +Test: [ 600/2573] eta: 0:02:47 time: 0.0795 data: 0.0014 max mem: 33408 +Test: [ 700/2573] eta: 0:02:38 time: 0.0804 data: 0.0015 max mem: 33408 +Test: [ 800/2573] eta: 0:02:29 time: 0.0829 data: 0.0014 max mem: 33408 +Test: [ 900/2573] eta: 0:02:20 time: 0.0804 data: 0.0015 max mem: 33408 +Test: [1000/2573] eta: 0:02:11 time: 0.0803 data: 0.0015 max mem: 33408 +Test: [1100/2573] eta: 0:02:02 time: 0.0818 data: 0.0014 max mem: 33408 +Test: [1200/2573] eta: 0:01:54 time: 0.0807 data: 0.0014 max mem: 33408 +Test: [1300/2573] eta: 0:01:45 time: 0.0819 data: 0.0015 max mem: 33408 +Test: [1400/2573] eta: 0:01:37 time: 0.0806 data: 0.0015 max mem: 33408 +Test: [1500/2573] eta: 0:01:28 time: 0.0811 data: 0.0015 max mem: 33408 +Test: [1600/2573] eta: 0:01:20 time: 0.0840 data: 0.0015 max mem: 33408 +Test: [1700/2573] eta: 0:01:12 time: 0.0793 data: 0.0014 max mem: 33408 +Test: [1800/2573] eta: 0:01:03 time: 0.0831 data: 0.0016 max mem: 33408 +Test: [1900/2573] eta: 0:00:55 time: 0.0809 data: 0.0015 max mem: 33408 +Test: [2000/2573] eta: 0:00:47 time: 0.0805 data: 0.0015 max mem: 33408 +Test: [2100/2573] eta: 0:00:38 time: 0.0825 data: 0.0014 max mem: 33408 +Test: [2200/2573] eta: 0:00:30 time: 0.0824 data: 0.0015 max mem: 33408 +Test: [2300/2573] eta: 0:00:22 time: 0.0824 data: 0.0016 max mem: 33408 +Test: [2400/2573] eta: 0:00:14 time: 0.0773 data: 0.0014 max mem: 33408 +Test: [2500/2573] eta: 0:00:05 time: 0.0807 data: 0.0013 max mem: 33408 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: Total time: 0:03:32 +Final results: +Mean IoU is 64.37 + + precision@0.5 = 72.00 + precision@0.6 = 66.91 + precision@0.7 = 59.93 + precision@0.8 = 49.16 + precision@0.9 = 24.96 + overall IoU = 61.80 + +Average object IoU 64.37310788072155 +Overall IoU 61.79759216308594 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [30] [ 0/2639] eta: 3:55:35 lr: 1.4358239748907481e-05 loss: 0.0486 (0.0486) time: 5.3563 data: 2.3004 max mem: 33408 +Epoch: [30] [ 10/2639] eta: 2:24:49 lr: 1.4353342761279007e-05 loss: 0.0324 (0.0345) time: 3.3052 data: 0.2162 max mem: 33408 +Epoch: [30] [ 20/2639] eta: 2:17:33 lr: 1.4348445588007381e-05 loss: 0.0324 (0.0343) time: 3.0410 data: 0.0077 max mem: 33408 +Epoch: [30] [ 30/2639] eta: 2:15:08 lr: 1.4343548229015172e-05 loss: 0.0320 (0.0337) time: 2.9992 data: 0.0079 max mem: 33408 +Epoch: [30] [ 40/2639] eta: 2:14:05 lr: 1.4338650684224858e-05 loss: 0.0303 (0.0339) time: 3.0371 data: 0.0079 max mem: 33408 +Epoch: [30] [ 50/2639] eta: 2:12:32 lr: 1.4333752953558887e-05 loss: 0.0354 (0.0353) time: 3.0159 data: 0.0078 max mem: 33408 +Epoch: [30] [ 60/2639] eta: 2:11:35 lr: 1.432885503693962e-05 loss: 0.0356 (0.0355) time: 2.9912 data: 0.0080 max mem: 33408 +Epoch: [30] [ 70/2639] eta: 2:11:22 lr: 1.4323956934289376e-05 loss: 0.0340 (0.0351) time: 3.0593 data: 0.0083 max mem: 33408 +Epoch: [30] [ 80/2639] eta: 2:10:10 lr: 1.4319058645530389e-05 loss: 0.0317 (0.0348) time: 3.0239 data: 0.0086 max mem: 33408 +Epoch: [30] [ 90/2639] eta: 2:09:20 lr: 1.4314160170584856e-05 loss: 0.0317 (0.0342) time: 2.9606 data: 0.0089 max mem: 33408 +Epoch: [30] [ 100/2639] eta: 2:08:36 lr: 1.4309261509374888e-05 loss: 0.0323 (0.0344) time: 2.9862 data: 0.0087 max mem: 33408 +Epoch: [30] [ 110/2639] eta: 2:08:10 lr: 1.430436266182256e-05 loss: 0.0331 (0.0345) time: 3.0235 data: 0.0083 max mem: 33408 +Epoch: [30] [ 120/2639] eta: 2:07:51 lr: 1.4299463627849855e-05 loss: 0.0322 (0.0351) time: 3.0772 data: 0.0085 max mem: 33408 +Epoch: [30] [ 130/2639] eta: 2:07:33 lr: 1.4294564407378724e-05 loss: 0.0322 (0.0351) time: 3.1050 data: 0.0088 max mem: 33408 +Epoch: [30] [ 140/2639] eta: 2:07:07 lr: 1.4289665000331026e-05 loss: 0.0337 (0.0356) time: 3.0928 data: 0.0088 max mem: 33408 +Epoch: [30] [ 150/2639] eta: 2:06:37 lr: 1.4284765406628587e-05 loss: 0.0352 (0.0354) time: 3.0643 data: 0.0086 max mem: 33408 +Epoch: [30] [ 160/2639] eta: 2:05:55 lr: 1.427986562619314e-05 loss: 0.0330 (0.0354) time: 3.0170 data: 0.0084 max mem: 33408 +Epoch: [30] [ 170/2639] eta: 2:05:09 lr: 1.4274965658946385e-05 loss: 0.0330 (0.0356) time: 2.9585 data: 0.0084 max mem: 33408 +Epoch: [30] [ 180/2639] eta: 2:04:34 lr: 1.4270065504809934e-05 loss: 0.0324 (0.0355) time: 2.9756 data: 0.0082 max mem: 33408 +Epoch: [30] [ 190/2639] eta: 2:04:10 lr: 1.4265165163705358e-05 loss: 0.0313 (0.0353) time: 3.0490 data: 0.0080 max mem: 33408 +Epoch: [30] [ 200/2639] eta: 2:03:40 lr: 1.4260264635554141e-05 loss: 0.0303 (0.0353) time: 3.0667 data: 0.0079 max mem: 33408 +Epoch: [30] [ 210/2639] eta: 2:03:20 lr: 1.425536392027773e-05 loss: 0.0317 (0.0354) time: 3.0882 data: 0.0078 max mem: 33408 +Epoch: [30] [ 220/2639] eta: 2:02:44 lr: 1.425046301779749e-05 loss: 0.0353 (0.0355) time: 3.0663 data: 0.0079 max mem: 33408 +Epoch: [30] [ 230/2639] eta: 2:02:11 lr: 1.4245561928034726e-05 loss: 0.0334 (0.0353) time: 3.0096 data: 0.0079 max mem: 33408 +Epoch: [30] [ 240/2639] eta: 2:01:38 lr: 1.4240660650910694e-05 loss: 0.0330 (0.0354) time: 3.0180 data: 0.0082 max mem: 33408 +Epoch: [30] [ 250/2639] eta: 2:01:11 lr: 1.4235759186346567e-05 loss: 0.0330 (0.0354) time: 3.0471 data: 0.0085 max mem: 33408 +Epoch: [30] [ 260/2639] eta: 2:00:42 lr: 1.423085753426347e-05 loss: 0.0347 (0.0357) time: 3.0680 data: 0.0082 max mem: 33408 +Epoch: [30] [ 270/2639] eta: 2:00:15 lr: 1.4225955694582452e-05 loss: 0.0318 (0.0354) time: 3.0736 data: 0.0081 max mem: 33408 +Epoch: [30] [ 280/2639] eta: 1:59:46 lr: 1.422105366722451e-05 loss: 0.0335 (0.0357) time: 3.0709 data: 0.0082 max mem: 33408 +Epoch: [30] [ 290/2639] eta: 1:59:06 lr: 1.4216151452110565e-05 loss: 0.0350 (0.0357) time: 2.9977 data: 0.0081 max mem: 33408 +Epoch: [30] [ 300/2639] eta: 1:58:32 lr: 1.421124904916149e-05 loss: 0.0347 (0.0357) time: 2.9663 data: 0.0083 max mem: 33408 +Epoch: [30] [ 310/2639] eta: 1:58:01 lr: 1.4206346458298078e-05 loss: 0.0339 (0.0356) time: 3.0091 data: 0.0085 max mem: 33408 +Epoch: [30] [ 320/2639] eta: 1:57:29 lr: 1.4201443679441079e-05 loss: 0.0302 (0.0355) time: 3.0273 data: 0.0079 max mem: 33408 +Epoch: [30] [ 330/2639] eta: 1:56:53 lr: 1.4196540712511147e-05 loss: 0.0282 (0.0353) time: 2.9914 data: 0.0079 max mem: 33408 +Epoch: [30] [ 340/2639] eta: 1:56:17 lr: 1.419163755742891e-05 loss: 0.0280 (0.0351) time: 2.9547 data: 0.0080 max mem: 33408 +Epoch: [30] [ 350/2639] eta: 1:55:47 lr: 1.4186734214114896e-05 loss: 0.0293 (0.0351) time: 2.9980 data: 0.0077 max mem: 33408 +Epoch: [30] [ 360/2639] eta: 1:55:17 lr: 1.4181830682489605e-05 loss: 0.0326 (0.0351) time: 3.0378 data: 0.0076 max mem: 33408 +Epoch: [30] [ 370/2639] eta: 1:54:49 lr: 1.4176926962473439e-05 loss: 0.0328 (0.0351) time: 3.0563 data: 0.0076 max mem: 33408 +Epoch: [30] [ 380/2639] eta: 1:54:16 lr: 1.4172023053986758e-05 loss: 0.0303 (0.0351) time: 3.0337 data: 0.0077 max mem: 33408 +Epoch: [30] [ 390/2639] eta: 1:53:44 lr: 1.4167118956949846e-05 loss: 0.0340 (0.0351) time: 2.9978 data: 0.0078 max mem: 33408 +Epoch: [30] [ 400/2639] eta: 1:53:15 lr: 1.4162214671282933e-05 loss: 0.0349 (0.0355) time: 3.0327 data: 0.0083 max mem: 33408 +Epoch: [30] [ 410/2639] eta: 1:52:46 lr: 1.4157310196906173e-05 loss: 0.0306 (0.0354) time: 3.0647 data: 0.0085 max mem: 33408 +Epoch: [30] [ 420/2639] eta: 1:52:16 lr: 1.4152405533739669e-05 loss: 0.0298 (0.0354) time: 3.0501 data: 0.0083 max mem: 33408 +Epoch: [30] [ 430/2639] eta: 1:51:49 lr: 1.4147500681703437e-05 loss: 0.0316 (0.0353) time: 3.0714 data: 0.0083 max mem: 33408 +Epoch: [30] [ 440/2639] eta: 1:51:16 lr: 1.414259564071746e-05 loss: 0.0368 (0.0355) time: 3.0475 data: 0.0082 max mem: 33408 +Epoch: [30] [ 450/2639] eta: 1:50:45 lr: 1.4137690410701627e-05 loss: 0.0379 (0.0356) time: 2.9968 data: 0.0083 max mem: 33408 +Epoch: [30] [ 460/2639] eta: 1:50:15 lr: 1.4132784991575782e-05 loss: 0.0306 (0.0355) time: 3.0276 data: 0.0085 max mem: 33408 +Epoch: [30] [ 470/2639] eta: 1:49:45 lr: 1.4127879383259684e-05 loss: 0.0274 (0.0353) time: 3.0466 data: 0.0085 max mem: 33408 +Epoch: [30] [ 480/2639] eta: 1:49:14 lr: 1.4122973585673052e-05 loss: 0.0295 (0.0352) time: 3.0372 data: 0.0085 max mem: 33408 +Epoch: [30] [ 490/2639] eta: 1:48:44 lr: 1.411806759873553e-05 loss: 0.0289 (0.0352) time: 3.0373 data: 0.0082 max mem: 33408 +Epoch: [30] [ 500/2639] eta: 1:48:15 lr: 1.4113161422366678e-05 loss: 0.0285 (0.0351) time: 3.0569 data: 0.0083 max mem: 33408 +Epoch: [30] [ 510/2639] eta: 1:47:42 lr: 1.4108255056486022e-05 loss: 0.0330 (0.0352) time: 3.0189 data: 0.0082 max mem: 33408 +Epoch: [30] [ 520/2639] eta: 1:47:15 lr: 1.4103348501012998e-05 loss: 0.0375 (0.0352) time: 3.0451 data: 0.0083 max mem: 33408 +Epoch: [30] [ 530/2639] eta: 1:46:46 lr: 1.4098441755866992e-05 loss: 0.0338 (0.0352) time: 3.0919 data: 0.0084 max mem: 33408 +Epoch: [30] [ 540/2639] eta: 1:46:18 lr: 1.409353482096731e-05 loss: 0.0310 (0.0353) time: 3.0792 data: 0.0080 max mem: 33408 +Epoch: [30] [ 550/2639] eta: 1:45:50 lr: 1.4088627696233217e-05 loss: 0.0367 (0.0355) time: 3.0997 data: 0.0082 max mem: 33408 +Epoch: [30] [ 560/2639] eta: 1:45:19 lr: 1.4083720381583879e-05 loss: 0.0346 (0.0354) time: 3.0670 data: 0.0082 max mem: 33408 +Epoch: [30] [ 570/2639] eta: 1:44:48 lr: 1.4078812876938424e-05 loss: 0.0343 (0.0355) time: 3.0303 data: 0.0084 max mem: 33408 +Epoch: [30] [ 580/2639] eta: 1:44:19 lr: 1.4073905182215899e-05 loss: 0.0383 (0.0356) time: 3.0479 data: 0.0082 max mem: 33408 +Epoch: [30] [ 590/2639] eta: 1:43:47 lr: 1.4068997297335296e-05 loss: 0.0303 (0.0355) time: 3.0264 data: 0.0077 max mem: 33408 +Epoch: [30] [ 600/2639] eta: 1:43:14 lr: 1.4064089222215529e-05 loss: 0.0301 (0.0356) time: 2.9769 data: 0.0081 max mem: 33408 +Epoch: [30] [ 610/2639] eta: 1:42:44 lr: 1.4059180956775455e-05 loss: 0.0342 (0.0357) time: 3.0112 data: 0.0082 max mem: 33408 +Epoch: [30] [ 620/2639] eta: 1:42:13 lr: 1.405427250093386e-05 loss: 0.0351 (0.0357) time: 3.0325 data: 0.0079 max mem: 33408 +Epoch: [30] [ 630/2639] eta: 1:41:40 lr: 1.4049363854609474e-05 loss: 0.0357 (0.0357) time: 2.9943 data: 0.0081 max mem: 33408 +Epoch: [30] [ 640/2639] eta: 1:41:09 lr: 1.4044455017720937e-05 loss: 0.0372 (0.0357) time: 2.9857 data: 0.0083 max mem: 33408 +Epoch: [30] [ 650/2639] eta: 1:40:38 lr: 1.4039545990186853e-05 loss: 0.0372 (0.0357) time: 3.0119 data: 0.0079 max mem: 33408 +Epoch: [30] [ 660/2639] eta: 1:40:07 lr: 1.4034636771925736e-05 loss: 0.0314 (0.0356) time: 3.0186 data: 0.0075 max mem: 33408 +Epoch: [30] [ 670/2639] eta: 1:39:37 lr: 1.402972736285605e-05 loss: 0.0352 (0.0358) time: 3.0332 data: 0.0077 max mem: 33408 +Epoch: [30] [ 680/2639] eta: 1:39:07 lr: 1.4024817762896172e-05 loss: 0.0350 (0.0357) time: 3.0426 data: 0.0080 max mem: 33408 +Epoch: [30] [ 690/2639] eta: 1:38:37 lr: 1.401990797196444e-05 loss: 0.0302 (0.0358) time: 3.0381 data: 0.0080 max mem: 33408 +Epoch: [30] [ 700/2639] eta: 1:38:07 lr: 1.4014997989979097e-05 loss: 0.0302 (0.0358) time: 3.0519 data: 0.0077 max mem: 33408 +Epoch: [30] [ 710/2639] eta: 1:37:37 lr: 1.4010087816858347e-05 loss: 0.0360 (0.0358) time: 3.0580 data: 0.0076 max mem: 33408 +Epoch: [30] [ 720/2639] eta: 1:37:07 lr: 1.4005177452520296e-05 loss: 0.0353 (0.0358) time: 3.0524 data: 0.0079 max mem: 33408 +Epoch: [30] [ 730/2639] eta: 1:36:36 lr: 1.400026689688301e-05 loss: 0.0307 (0.0357) time: 3.0345 data: 0.0081 max mem: 33408 +Epoch: [30] [ 740/2639] eta: 1:36:07 lr: 1.399535614986448e-05 loss: 0.0303 (0.0357) time: 3.0470 data: 0.0077 max mem: 33408 +Epoch: [30] [ 750/2639] eta: 1:35:36 lr: 1.3990445211382615e-05 loss: 0.0323 (0.0357) time: 3.0420 data: 0.0080 max mem: 33408 +Epoch: [30] [ 760/2639] eta: 1:35:05 lr: 1.3985534081355287e-05 loss: 0.0323 (0.0357) time: 3.0136 data: 0.0083 max mem: 33408 +Epoch: [30] [ 770/2639] eta: 1:34:34 lr: 1.3980622759700262e-05 loss: 0.0307 (0.0356) time: 3.0170 data: 0.0081 max mem: 33408 +Epoch: [30] [ 780/2639] eta: 1:34:05 lr: 1.397571124633528e-05 loss: 0.0313 (0.0356) time: 3.0569 data: 0.0086 max mem: 33408 +Epoch: [30] [ 790/2639] eta: 1:33:34 lr: 1.3970799541177975e-05 loss: 0.0344 (0.0356) time: 3.0557 data: 0.0084 max mem: 33408 +Epoch: [30] [ 800/2639] eta: 1:33:05 lr: 1.3965887644145948e-05 loss: 0.0317 (0.0356) time: 3.0607 data: 0.0078 max mem: 33408 +Epoch: [30] [ 810/2639] eta: 1:32:37 lr: 1.3960975555156699e-05 loss: 0.0288 (0.0355) time: 3.1080 data: 0.0079 max mem: 33408 +Epoch: [30] [ 820/2639] eta: 1:32:06 lr: 1.3956063274127689e-05 loss: 0.0268 (0.0354) time: 3.0788 data: 0.0078 max mem: 33408 +Epoch: [30] [ 830/2639] eta: 1:31:36 lr: 1.3951150800976296e-05 loss: 0.0277 (0.0354) time: 3.0293 data: 0.0079 max mem: 33408 +Epoch: [30] [ 840/2639] eta: 1:31:07 lr: 1.3946238135619835e-05 loss: 0.0318 (0.0354) time: 3.0586 data: 0.0079 max mem: 33408 +Epoch: [30] [ 850/2639] eta: 1:30:37 lr: 1.3941325277975542e-05 loss: 0.0320 (0.0354) time: 3.0969 data: 0.0079 max mem: 33408 +Epoch: [30] [ 860/2639] eta: 1:30:07 lr: 1.393641222796061e-05 loss: 0.0343 (0.0354) time: 3.0723 data: 0.0079 max mem: 33408 +Epoch: [30] [ 870/2639] eta: 1:29:36 lr: 1.3931498985492134e-05 loss: 0.0349 (0.0354) time: 3.0286 data: 0.0079 max mem: 33408 +Epoch: [30] [ 880/2639] eta: 1:29:06 lr: 1.3926585550487167e-05 loss: 0.0361 (0.0355) time: 3.0289 data: 0.0077 max mem: 33408 +Epoch: [30] [ 890/2639] eta: 1:28:36 lr: 1.3921671922862669e-05 loss: 0.0311 (0.0355) time: 3.0538 data: 0.0078 max mem: 33408 +Epoch: [30] [ 900/2639] eta: 1:28:06 lr: 1.3916758102535556e-05 loss: 0.0315 (0.0355) time: 3.0518 data: 0.0079 max mem: 33408 +Epoch: [30] [ 910/2639] eta: 1:27:34 lr: 1.3911844089422654e-05 loss: 0.0299 (0.0355) time: 3.0018 data: 0.0077 max mem: 33408 +Epoch: [30] [ 920/2639] eta: 1:27:03 lr: 1.3906929883440742e-05 loss: 0.0296 (0.0354) time: 2.9964 data: 0.0084 max mem: 33408 +Epoch: [30] [ 930/2639] eta: 1:26:33 lr: 1.3902015484506506e-05 loss: 0.0374 (0.0356) time: 3.0449 data: 0.0086 max mem: 33408 +Epoch: [30] [ 940/2639] eta: 1:26:02 lr: 1.3897100892536585e-05 loss: 0.0352 (0.0356) time: 3.0349 data: 0.0082 max mem: 33408 +Epoch: [30] [ 950/2639] eta: 1:25:32 lr: 1.3892186107447533e-05 loss: 0.0318 (0.0355) time: 3.0374 data: 0.0080 max mem: 33408 +Epoch: [30] [ 960/2639] eta: 1:25:01 lr: 1.3887271129155852e-05 loss: 0.0318 (0.0355) time: 3.0287 data: 0.0076 max mem: 33408 +Epoch: [30] [ 970/2639] eta: 1:24:30 lr: 1.3882355957577955e-05 loss: 0.0341 (0.0355) time: 3.0042 data: 0.0074 max mem: 33408 +Epoch: [30] [ 980/2639] eta: 1:24:00 lr: 1.3877440592630201e-05 loss: 0.0313 (0.0355) time: 3.0331 data: 0.0077 max mem: 33408 +Epoch: [30] [ 990/2639] eta: 1:23:29 lr: 1.3872525034228877e-05 loss: 0.0330 (0.0354) time: 3.0361 data: 0.0077 max mem: 33408 +Epoch: [30] [1000/2639] eta: 1:22:58 lr: 1.3867609282290198e-05 loss: 0.0330 (0.0354) time: 2.9973 data: 0.0083 max mem: 33408 +Epoch: [30] [1010/2639] eta: 1:22:27 lr: 1.3862693336730309e-05 loss: 0.0353 (0.0354) time: 2.9827 data: 0.0085 max mem: 33408 +Epoch: [30] [1020/2639] eta: 1:21:57 lr: 1.3857777197465286e-05 loss: 0.0392 (0.0355) time: 3.0382 data: 0.0082 max mem: 33408 +Epoch: [30] [1030/2639] eta: 1:21:27 lr: 1.3852860864411144e-05 loss: 0.0362 (0.0355) time: 3.0727 data: 0.0085 max mem: 33408 +Epoch: [30] [1040/2639] eta: 1:20:58 lr: 1.3847944337483809e-05 loss: 0.0344 (0.0355) time: 3.0674 data: 0.0080 max mem: 33408 +Epoch: [30] [1050/2639] eta: 1:20:26 lr: 1.3843027616599164e-05 loss: 0.0339 (0.0355) time: 3.0357 data: 0.0079 max mem: 33408 +Epoch: [30] [1060/2639] eta: 1:19:56 lr: 1.3838110701672993e-05 loss: 0.0320 (0.0355) time: 3.0013 data: 0.0082 max mem: 33408 +Epoch: [30] [1070/2639] eta: 1:19:25 lr: 1.383319359262104e-05 loss: 0.0299 (0.0355) time: 3.0121 data: 0.0080 max mem: 33408 +Epoch: [30] [1080/2639] eta: 1:18:54 lr: 1.3828276289358949e-05 loss: 0.0339 (0.0356) time: 3.0202 data: 0.0078 max mem: 33408 +Epoch: [30] [1090/2639] eta: 1:18:23 lr: 1.3823358791802324e-05 loss: 0.0334 (0.0356) time: 2.9959 data: 0.0083 max mem: 33408 +Epoch: [30] [1100/2639] eta: 1:17:52 lr: 1.3818441099866672e-05 loss: 0.0327 (0.0355) time: 2.9930 data: 0.0086 max mem: 33408 +Epoch: [30] [1110/2639] eta: 1:17:22 lr: 1.381352321346745e-05 loss: 0.0321 (0.0356) time: 3.0384 data: 0.0086 max mem: 33408 +Epoch: [30] [1120/2639] eta: 1:16:51 lr: 1.380860513252003e-05 loss: 0.0345 (0.0356) time: 3.0287 data: 0.0087 max mem: 33408 +Epoch: [30] [1130/2639] eta: 1:16:21 lr: 1.3803686856939729e-05 loss: 0.0326 (0.0356) time: 3.0265 data: 0.0085 max mem: 33408 +Epoch: [30] [1140/2639] eta: 1:15:50 lr: 1.3798768386641775e-05 loss: 0.0323 (0.0357) time: 3.0204 data: 0.0082 max mem: 33408 +Epoch: [30] [1150/2639] eta: 1:15:19 lr: 1.3793849721541344e-05 loss: 0.0354 (0.0357) time: 2.9592 data: 0.0079 max mem: 33408 +Epoch: [30] [1160/2639] eta: 1:14:48 lr: 1.3788930861553526e-05 loss: 0.0357 (0.0357) time: 2.9698 data: 0.0080 max mem: 33408 +Epoch: [30] [1170/2639] eta: 1:14:17 lr: 1.3784011806593352e-05 loss: 0.0322 (0.0357) time: 3.0136 data: 0.0083 max mem: 33408 +Epoch: [30] [1180/2639] eta: 1:13:47 lr: 1.3779092556575773e-05 loss: 0.0335 (0.0357) time: 3.0226 data: 0.0082 max mem: 33408 +Epoch: [30] [1190/2639] eta: 1:13:16 lr: 1.3774173111415684e-05 loss: 0.0335 (0.0357) time: 3.0181 data: 0.0078 max mem: 33408 +Epoch: [30] [1200/2639] eta: 1:12:46 lr: 1.3769253471027882e-05 loss: 0.0319 (0.0357) time: 3.0228 data: 0.0084 max mem: 33408 +Epoch: [30] [1210/2639] eta: 1:12:15 lr: 1.376433363532712e-05 loss: 0.0305 (0.0357) time: 3.0091 data: 0.0088 max mem: 33408 +Epoch: [30] [1220/2639] eta: 1:11:45 lr: 1.3759413604228074e-05 loss: 0.0354 (0.0357) time: 3.0325 data: 0.0080 max mem: 33408 +Epoch: [30] [1230/2639] eta: 1:11:15 lr: 1.3754493377645336e-05 loss: 0.0335 (0.0358) time: 3.0510 data: 0.0078 max mem: 33408 +Epoch: [30] [1240/2639] eta: 1:10:44 lr: 1.3749572955493439e-05 loss: 0.0321 (0.0358) time: 3.0293 data: 0.0079 max mem: 33408 +Epoch: [30] [1250/2639] eta: 1:10:14 lr: 1.3744652337686836e-05 loss: 0.0330 (0.0358) time: 3.0301 data: 0.0076 max mem: 33408 +Epoch: [30] [1260/2639] eta: 1:09:43 lr: 1.3739731524139923e-05 loss: 0.0349 (0.0357) time: 2.9889 data: 0.0079 max mem: 33408 +Epoch: [30] [1270/2639] eta: 1:09:13 lr: 1.3734810514767003e-05 loss: 0.0324 (0.0357) time: 3.0068 data: 0.0080 max mem: 33408 +Epoch: [30] [1280/2639] eta: 1:08:43 lr: 1.3729889309482327e-05 loss: 0.0287 (0.0357) time: 3.0675 data: 0.0076 max mem: 33408 +Epoch: [30] [1290/2639] eta: 1:08:12 lr: 1.3724967908200059e-05 loss: 0.0286 (0.0357) time: 3.0311 data: 0.0075 max mem: 33408 +Epoch: [30] [1300/2639] eta: 1:07:41 lr: 1.3720046310834312e-05 loss: 0.0262 (0.0356) time: 2.9990 data: 0.0075 max mem: 33408 +Epoch: [30] [1310/2639] eta: 1:07:11 lr: 1.3715124517299097e-05 loss: 0.0264 (0.0356) time: 3.0170 data: 0.0079 max mem: 33408 +Epoch: [30] [1320/2639] eta: 1:06:40 lr: 1.371020252750838e-05 loss: 0.0309 (0.0357) time: 2.9842 data: 0.0083 max mem: 33408 +Epoch: [30] [1330/2639] eta: 1:06:10 lr: 1.3705280341376039e-05 loss: 0.0357 (0.0357) time: 3.0016 data: 0.0078 max mem: 33408 +Epoch: [30] [1340/2639] eta: 1:05:39 lr: 1.3700357958815896e-05 loss: 0.0351 (0.0357) time: 3.0414 data: 0.0074 max mem: 33408 +Epoch: [30] [1350/2639] eta: 1:05:09 lr: 1.3695435379741675e-05 loss: 0.0316 (0.0357) time: 3.0435 data: 0.0082 max mem: 33408 +Epoch: [30] [1360/2639] eta: 1:04:39 lr: 1.3690512604067054e-05 loss: 0.0337 (0.0357) time: 3.0579 data: 0.0083 max mem: 33408 +Epoch: [30] [1370/2639] eta: 1:04:09 lr: 1.368558963170562e-05 loss: 0.0338 (0.0356) time: 3.0484 data: 0.0078 max mem: 33408 +Epoch: [30] [1380/2639] eta: 1:03:38 lr: 1.3680666462570904e-05 loss: 0.0300 (0.0356) time: 3.0326 data: 0.0077 max mem: 33408 +Epoch: [30] [1390/2639] eta: 1:03:08 lr: 1.3675743096576343e-05 loss: 0.0331 (0.0356) time: 3.0091 data: 0.0077 max mem: 33408 +Epoch: [30] [1400/2639] eta: 1:02:37 lr: 1.3670819533635326e-05 loss: 0.0331 (0.0356) time: 2.9966 data: 0.0078 max mem: 33408 +Epoch: [30] [1410/2639] eta: 1:02:07 lr: 1.3665895773661148e-05 loss: 0.0347 (0.0356) time: 3.0147 data: 0.0076 max mem: 33408 +Epoch: [30] [1420/2639] eta: 1:01:36 lr: 1.3660971816567042e-05 loss: 0.0333 (0.0356) time: 3.0330 data: 0.0078 max mem: 33408 +Epoch: [30] [1430/2639] eta: 1:01:06 lr: 1.3656047662266164e-05 loss: 0.0319 (0.0356) time: 3.0517 data: 0.0078 max mem: 33408 +Epoch: [30] [1440/2639] eta: 1:00:35 lr: 1.3651123310671607e-05 loss: 0.0331 (0.0356) time: 3.0132 data: 0.0076 max mem: 33408 +Epoch: [30] [1450/2639] eta: 1:00:05 lr: 1.364619876169637e-05 loss: 0.0355 (0.0356) time: 2.9753 data: 0.0075 max mem: 33408 +Epoch: [30] [1460/2639] eta: 0:59:34 lr: 1.3641274015253396e-05 loss: 0.0311 (0.0357) time: 2.9998 data: 0.0079 max mem: 33408 +Epoch: [30] [1470/2639] eta: 0:59:04 lr: 1.363634907125556e-05 loss: 0.0313 (0.0357) time: 2.9999 data: 0.0081 max mem: 33408 +Epoch: [30] [1480/2639] eta: 0:58:33 lr: 1.3631423929615638e-05 loss: 0.0335 (0.0357) time: 2.9859 data: 0.0078 max mem: 33408 +Epoch: [30] [1490/2639] eta: 0:58:03 lr: 1.3626498590246365e-05 loss: 0.0381 (0.0357) time: 3.0098 data: 0.0080 max mem: 33408 +Epoch: [30] [1500/2639] eta: 0:57:33 lr: 1.3621573053060366e-05 loss: 0.0359 (0.0357) time: 3.0536 data: 0.0081 max mem: 33408 +Epoch: [30] [1510/2639] eta: 0:57:02 lr: 1.361664731797023e-05 loss: 0.0315 (0.0357) time: 3.0383 data: 0.0080 max mem: 33408 +Epoch: [30] [1520/2639] eta: 0:56:32 lr: 1.3611721384888437e-05 loss: 0.0319 (0.0357) time: 3.0065 data: 0.0080 max mem: 33408 +Epoch: [30] [1530/2639] eta: 0:56:02 lr: 1.3606795253727425e-05 loss: 0.0329 (0.0357) time: 3.0309 data: 0.0078 max mem: 33408 +Epoch: [30] [1540/2639] eta: 0:55:31 lr: 1.360186892439953e-05 loss: 0.0291 (0.0356) time: 3.0506 data: 0.0075 max mem: 33408 +Epoch: [30] [1550/2639] eta: 0:55:01 lr: 1.3596942396817041e-05 loss: 0.0280 (0.0356) time: 3.0104 data: 0.0074 max mem: 33408 +Epoch: [30] [1560/2639] eta: 0:54:31 lr: 1.3592015670892145e-05 loss: 0.0299 (0.0356) time: 3.0263 data: 0.0075 max mem: 33408 +Epoch: [30] [1570/2639] eta: 0:54:00 lr: 1.358708874653698e-05 loss: 0.0331 (0.0356) time: 3.0635 data: 0.0077 max mem: 33408 +Epoch: [30] [1580/2639] eta: 0:53:30 lr: 1.358216162366359e-05 loss: 0.0331 (0.0356) time: 3.0464 data: 0.0079 max mem: 33408 +Epoch: [30] [1590/2639] eta: 0:53:00 lr: 1.3577234302183958e-05 loss: 0.0318 (0.0356) time: 3.0317 data: 0.0076 max mem: 33408 +Epoch: [30] [1600/2639] eta: 0:52:30 lr: 1.357230678200998e-05 loss: 0.0281 (0.0356) time: 3.0568 data: 0.0076 max mem: 33408 +Epoch: [30] [1610/2639] eta: 0:51:59 lr: 1.3567379063053496e-05 loss: 0.0322 (0.0356) time: 3.0571 data: 0.0079 max mem: 33408 +Epoch: [30] [1620/2639] eta: 0:51:30 lr: 1.3562451145226245e-05 loss: 0.0304 (0.0356) time: 3.0666 data: 0.0079 max mem: 33408 +Epoch: [30] [1630/2639] eta: 0:50:59 lr: 1.3557523028439922e-05 loss: 0.0286 (0.0356) time: 3.0791 data: 0.0077 max mem: 33408 +Epoch: [30] [1640/2639] eta: 0:50:29 lr: 1.3552594712606118e-05 loss: 0.0286 (0.0356) time: 3.0302 data: 0.0079 max mem: 33408 +Epoch: [30] [1650/2639] eta: 0:49:58 lr: 1.3547666197636372e-05 loss: 0.0318 (0.0355) time: 2.9867 data: 0.0079 max mem: 33408 +Epoch: [30] [1660/2639] eta: 0:49:28 lr: 1.3542737483442128e-05 loss: 0.0318 (0.0355) time: 2.9950 data: 0.0076 max mem: 33408 +Epoch: [30] [1670/2639] eta: 0:48:58 lr: 1.3537808569934777e-05 loss: 0.0338 (0.0356) time: 3.0501 data: 0.0075 max mem: 33408 +Epoch: [30] [1680/2639] eta: 0:48:27 lr: 1.3532879457025607e-05 loss: 0.0342 (0.0355) time: 3.0436 data: 0.0080 max mem: 33408 +Epoch: [30] [1690/2639] eta: 0:47:57 lr: 1.3527950144625861e-05 loss: 0.0342 (0.0356) time: 2.9965 data: 0.0080 max mem: 33408 +Epoch: [30] [1700/2639] eta: 0:47:26 lr: 1.3523020632646683e-05 loss: 0.0343 (0.0355) time: 2.9967 data: 0.0076 max mem: 33408 +Epoch: [30] [1710/2639] eta: 0:46:56 lr: 1.3518090920999152e-05 loss: 0.0338 (0.0356) time: 3.0463 data: 0.0076 max mem: 33408 +Epoch: [30] [1720/2639] eta: 0:46:26 lr: 1.3513161009594272e-05 loss: 0.0337 (0.0355) time: 3.0640 data: 0.0077 max mem: 33408 +Epoch: [30] [1730/2639] eta: 0:45:55 lr: 1.3508230898342963e-05 loss: 0.0323 (0.0355) time: 3.0102 data: 0.0077 max mem: 33408 +Epoch: [30] [1740/2639] eta: 0:45:25 lr: 1.3503300587156087e-05 loss: 0.0356 (0.0356) time: 3.0251 data: 0.0077 max mem: 33408 +Epoch: [30] [1750/2639] eta: 0:44:55 lr: 1.34983700759444e-05 loss: 0.0348 (0.0356) time: 3.0451 data: 0.0079 max mem: 33408 +Epoch: [30] [1760/2639] eta: 0:44:24 lr: 1.3493439364618616e-05 loss: 0.0317 (0.0356) time: 2.9987 data: 0.0079 max mem: 33408 +Epoch: [30] [1770/2639] eta: 0:43:54 lr: 1.3488508453089341e-05 loss: 0.0344 (0.0356) time: 3.0141 data: 0.0075 max mem: 33408 +Epoch: [30] [1780/2639] eta: 0:43:24 lr: 1.3483577341267136e-05 loss: 0.0309 (0.0356) time: 3.0185 data: 0.0075 max mem: 33408 +Epoch: [30] [1790/2639] eta: 0:42:53 lr: 1.3478646029062462e-05 loss: 0.0310 (0.0355) time: 3.0068 data: 0.0077 max mem: 33408 +Epoch: [30] [1800/2639] eta: 0:42:23 lr: 1.3473714516385713e-05 loss: 0.0322 (0.0355) time: 3.0468 data: 0.0081 max mem: 33408 +Epoch: [30] [1810/2639] eta: 0:41:53 lr: 1.3468782803147201e-05 loss: 0.0322 (0.0355) time: 3.0766 data: 0.0079 max mem: 33408 +Epoch: [30] [1820/2639] eta: 0:41:22 lr: 1.3463850889257174e-05 loss: 0.0315 (0.0355) time: 3.0274 data: 0.0077 max mem: 33408 +Epoch: [30] [1830/2639] eta: 0:40:52 lr: 1.3458918774625784e-05 loss: 0.0351 (0.0356) time: 2.9885 data: 0.0081 max mem: 33408 +Epoch: [30] [1840/2639] eta: 0:40:22 lr: 1.3453986459163129e-05 loss: 0.0351 (0.0356) time: 3.0093 data: 0.0080 max mem: 33408 +Epoch: [30] [1850/2639] eta: 0:39:51 lr: 1.3449053942779205e-05 loss: 0.0304 (0.0356) time: 3.0139 data: 0.0080 max mem: 33408 +Epoch: [30] [1860/2639] eta: 0:39:21 lr: 1.3444121225383957e-05 loss: 0.0355 (0.0356) time: 3.0299 data: 0.0079 max mem: 33408 +Epoch: [30] [1870/2639] eta: 0:38:51 lr: 1.3439188306887229e-05 loss: 0.0335 (0.0356) time: 3.0479 data: 0.0072 max mem: 33408 +Epoch: [30] [1880/2639] eta: 0:38:21 lr: 1.3434255187198811e-05 loss: 0.0301 (0.0355) time: 3.0564 data: 0.0075 max mem: 33408 +Epoch: [30] [1890/2639] eta: 0:37:50 lr: 1.3429321866228387e-05 loss: 0.0322 (0.0356) time: 3.0800 data: 0.0078 max mem: 33408 +Epoch: [30] [1900/2639] eta: 0:37:20 lr: 1.3424388343885594e-05 loss: 0.0353 (0.0356) time: 3.0852 data: 0.0078 max mem: 33408 +Epoch: [30] [1910/2639] eta: 0:36:50 lr: 1.3419454620079966e-05 loss: 0.0322 (0.0356) time: 3.0563 data: 0.0079 max mem: 33408 +Epoch: [30] [1920/2639] eta: 0:36:19 lr: 1.3414520694720983e-05 loss: 0.0295 (0.0356) time: 2.9855 data: 0.0077 max mem: 33408 +Epoch: [30] [1930/2639] eta: 0:35:49 lr: 1.3409586567718027e-05 loss: 0.0292 (0.0356) time: 2.9558 data: 0.0075 max mem: 33408 +Epoch: [30] [1940/2639] eta: 0:35:18 lr: 1.3404652238980415e-05 loss: 0.0301 (0.0356) time: 2.9773 data: 0.0084 max mem: 33408 +Epoch: [30] [1950/2639] eta: 0:34:48 lr: 1.3399717708417372e-05 loss: 0.0327 (0.0356) time: 3.0120 data: 0.0083 max mem: 33408 +Epoch: [30] [1960/2639] eta: 0:34:18 lr: 1.3394782975938063e-05 loss: 0.0305 (0.0356) time: 3.0271 data: 0.0077 max mem: 33408 +Epoch: [30] [1970/2639] eta: 0:33:47 lr: 1.3389848041451571e-05 loss: 0.0282 (0.0355) time: 2.9859 data: 0.0083 max mem: 33408 +Epoch: [30] [1980/2639] eta: 0:33:17 lr: 1.3384912904866884e-05 loss: 0.0306 (0.0355) time: 2.9673 data: 0.0083 max mem: 33408 +Epoch: [30] [1990/2639] eta: 0:32:46 lr: 1.3379977566092935e-05 loss: 0.0311 (0.0355) time: 2.9921 data: 0.0079 max mem: 33408 +Epoch: [30] [2000/2639] eta: 0:32:16 lr: 1.3375042025038556e-05 loss: 0.0320 (0.0355) time: 3.0285 data: 0.0083 max mem: 33408 +Epoch: [30] [2010/2639] eta: 0:31:46 lr: 1.3370106281612525e-05 loss: 0.0324 (0.0355) time: 3.0246 data: 0.0081 max mem: 33408 +Epoch: [30] [2020/2639] eta: 0:31:15 lr: 1.3365170335723514e-05 loss: 0.0300 (0.0355) time: 3.0402 data: 0.0079 max mem: 33408 +Epoch: [30] [2030/2639] eta: 0:30:45 lr: 1.3360234187280146e-05 loss: 0.0272 (0.0355) time: 3.0534 data: 0.0079 max mem: 33408 +Epoch: [30] [2040/2639] eta: 0:30:15 lr: 1.3355297836190937e-05 loss: 0.0288 (0.0354) time: 3.0092 data: 0.0075 max mem: 33408 +Epoch: [30] [2050/2639] eta: 0:29:44 lr: 1.3350361282364345e-05 loss: 0.0312 (0.0354) time: 3.0224 data: 0.0077 max mem: 33408 +Epoch: [30] [2060/2639] eta: 0:29:14 lr: 1.3345424525708739e-05 loss: 0.0362 (0.0354) time: 3.0644 data: 0.0077 max mem: 33408 +Epoch: [30] [2070/2639] eta: 0:28:44 lr: 1.3340487566132409e-05 loss: 0.0341 (0.0354) time: 3.0628 data: 0.0076 max mem: 33408 +Epoch: [30] [2080/2639] eta: 0:28:14 lr: 1.3335550403543567e-05 loss: 0.0313 (0.0354) time: 3.0290 data: 0.0077 max mem: 33408 +Epoch: [30] [2090/2639] eta: 0:27:43 lr: 1.3330613037850353e-05 loss: 0.0345 (0.0354) time: 3.0035 data: 0.0078 max mem: 33408 +Epoch: [30] [2100/2639] eta: 0:27:13 lr: 1.3325675468960813e-05 loss: 0.0374 (0.0355) time: 3.0592 data: 0.0078 max mem: 33408 +Epoch: [30] [2110/2639] eta: 0:26:43 lr: 1.3320737696782928e-05 loss: 0.0310 (0.0355) time: 3.0780 data: 0.0080 max mem: 33408 +Epoch: [30] [2120/2639] eta: 0:26:12 lr: 1.3315799721224586e-05 loss: 0.0319 (0.0354) time: 3.0150 data: 0.0085 max mem: 33408 +Epoch: [30] [2130/2639] eta: 0:25:42 lr: 1.3310861542193614e-05 loss: 0.0339 (0.0355) time: 3.0066 data: 0.0084 max mem: 33408 +Epoch: [30] [2140/2639] eta: 0:25:12 lr: 1.3305923159597733e-05 loss: 0.0355 (0.0355) time: 3.0061 data: 0.0078 max mem: 33408 +Epoch: [30] [2150/2639] eta: 0:24:41 lr: 1.3300984573344611e-05 loss: 0.0356 (0.0355) time: 2.9722 data: 0.0079 max mem: 33408 +Epoch: [30] [2160/2639] eta: 0:24:11 lr: 1.329604578334181e-05 loss: 0.0339 (0.0355) time: 3.0156 data: 0.0077 max mem: 33408 +Epoch: [30] [2170/2639] eta: 0:23:41 lr: 1.3291106789496844e-05 loss: 0.0294 (0.0355) time: 3.0505 data: 0.0076 max mem: 33408 +Epoch: [30] [2180/2639] eta: 0:23:10 lr: 1.3286167591717108e-05 loss: 0.0302 (0.0355) time: 2.9901 data: 0.0078 max mem: 33408 +Epoch: [30] [2190/2639] eta: 0:22:40 lr: 1.3281228189909953e-05 loss: 0.0310 (0.0355) time: 2.9842 data: 0.0078 max mem: 33408 +Epoch: [30] [2200/2639] eta: 0:22:10 lr: 1.3276288583982621e-05 loss: 0.0324 (0.0355) time: 3.0223 data: 0.0079 max mem: 33408 +Epoch: [30] [2210/2639] eta: 0:21:39 lr: 1.3271348773842293e-05 loss: 0.0342 (0.0355) time: 3.0226 data: 0.0077 max mem: 33408 +Epoch: [30] [2220/2639] eta: 0:21:09 lr: 1.3266408759396068e-05 loss: 0.0293 (0.0355) time: 3.0460 data: 0.0076 max mem: 33408 +Epoch: [30] [2230/2639] eta: 0:20:39 lr: 1.3261468540550946e-05 loss: 0.0301 (0.0355) time: 3.0395 data: 0.0075 max mem: 33408 +Epoch: [30] [2240/2639] eta: 0:20:09 lr: 1.325652811721387e-05 loss: 0.0302 (0.0355) time: 3.0341 data: 0.0077 max mem: 33408 +Epoch: [30] [2250/2639] eta: 0:19:38 lr: 1.325158748929168e-05 loss: 0.0381 (0.0355) time: 3.0291 data: 0.0085 max mem: 33408 +Epoch: [30] [2260/2639] eta: 0:19:08 lr: 1.3246646656691158e-05 loss: 0.0382 (0.0355) time: 3.0101 data: 0.0083 max mem: 33408 +Epoch: [30] [2270/2639] eta: 0:18:38 lr: 1.324170561931898e-05 loss: 0.0378 (0.0355) time: 3.0345 data: 0.0077 max mem: 33408 +Epoch: [30] [2280/2639] eta: 0:18:07 lr: 1.3236764377081767e-05 loss: 0.0326 (0.0355) time: 3.0515 data: 0.0078 max mem: 33408 +Epoch: [30] [2290/2639] eta: 0:17:37 lr: 1.3231822929886032e-05 loss: 0.0325 (0.0355) time: 3.0381 data: 0.0078 max mem: 33408 +Epoch: [30] [2300/2639] eta: 0:17:07 lr: 1.3226881277638232e-05 loss: 0.0303 (0.0355) time: 3.0099 data: 0.0077 max mem: 33408 +Epoch: [30] [2310/2639] eta: 0:16:36 lr: 1.3221939420244714e-05 loss: 0.0362 (0.0355) time: 2.9886 data: 0.0077 max mem: 33408 +Epoch: [30] [2320/2639] eta: 0:16:06 lr: 1.321699735761178e-05 loss: 0.0369 (0.0355) time: 2.9553 data: 0.0077 max mem: 33408 +Epoch: [30] [2330/2639] eta: 0:15:36 lr: 1.3212055089645609e-05 loss: 0.0368 (0.0355) time: 2.9634 data: 0.0080 max mem: 33408 +Epoch: [30] [2340/2639] eta: 0:15:05 lr: 1.3207112616252335e-05 loss: 0.0353 (0.0355) time: 3.0145 data: 0.0082 max mem: 33408 +Epoch: [30] [2350/2639] eta: 0:14:35 lr: 1.3202169937337983e-05 loss: 0.0352 (0.0356) time: 3.0395 data: 0.0081 max mem: 33408 +Epoch: [30] [2360/2639] eta: 0:14:05 lr: 1.3197227052808513e-05 loss: 0.0337 (0.0355) time: 3.0432 data: 0.0080 max mem: 33408 +Epoch: [30] [2370/2639] eta: 0:13:34 lr: 1.3192283962569792e-05 loss: 0.0331 (0.0356) time: 2.9900 data: 0.0078 max mem: 33408 +Epoch: [30] [2380/2639] eta: 0:13:04 lr: 1.3187340666527617e-05 loss: 0.0360 (0.0356) time: 2.9906 data: 0.0077 max mem: 33408 +Epoch: [30] [2390/2639] eta: 0:12:34 lr: 1.3182397164587685e-05 loss: 0.0319 (0.0356) time: 3.0249 data: 0.0083 max mem: 33408 +Epoch: [30] [2400/2639] eta: 0:12:03 lr: 1.3177453456655628e-05 loss: 0.0306 (0.0356) time: 3.0386 data: 0.0085 max mem: 33408 +Epoch: [30] [2410/2639] eta: 0:11:33 lr: 1.317250954263698e-05 loss: 0.0307 (0.0356) time: 3.0029 data: 0.0081 max mem: 33408 +Epoch: [30] [2420/2639] eta: 0:11:03 lr: 1.3167565422437208e-05 loss: 0.0361 (0.0356) time: 2.9656 data: 0.0080 max mem: 33408 +Epoch: [30] [2430/2639] eta: 0:10:32 lr: 1.3162621095961683e-05 loss: 0.0362 (0.0356) time: 3.0178 data: 0.0084 max mem: 33408 +Epoch: [30] [2440/2639] eta: 0:10:02 lr: 1.3157676563115703e-05 loss: 0.0326 (0.0356) time: 3.0527 data: 0.0090 max mem: 33408 +Epoch: [30] [2450/2639] eta: 0:09:32 lr: 1.3152731823804468e-05 loss: 0.0337 (0.0356) time: 3.0464 data: 0.0087 max mem: 33408 +Epoch: [30] [2460/2639] eta: 0:09:02 lr: 1.3147786877933114e-05 loss: 0.0373 (0.0356) time: 3.0047 data: 0.0081 max mem: 33408 +Epoch: [30] [2470/2639] eta: 0:08:31 lr: 1.3142841725406684e-05 loss: 0.0304 (0.0356) time: 3.0132 data: 0.0081 max mem: 33408 +Epoch: [30] [2480/2639] eta: 0:08:01 lr: 1.3137896366130136e-05 loss: 0.0298 (0.0356) time: 3.0380 data: 0.0081 max mem: 33408 +Epoch: [30] [2490/2639] eta: 0:07:31 lr: 1.3132950800008354e-05 loss: 0.0300 (0.0356) time: 3.0316 data: 0.0079 max mem: 33408 +Epoch: [30] [2500/2639] eta: 0:07:00 lr: 1.3128005026946116e-05 loss: 0.0355 (0.0356) time: 3.0370 data: 0.0080 max mem: 33408 +Epoch: [30] [2510/2639] eta: 0:06:30 lr: 1.3123059046848146e-05 loss: 0.0355 (0.0356) time: 3.0390 data: 0.0079 max mem: 33408 +Epoch: [30] [2520/2639] eta: 0:06:00 lr: 1.311811285961906e-05 loss: 0.0322 (0.0356) time: 3.0078 data: 0.0080 max mem: 33408 +Epoch: [30] [2530/2639] eta: 0:05:30 lr: 1.311316646516341e-05 loss: 0.0331 (0.0356) time: 3.0052 data: 0.0082 max mem: 33408 +Epoch: [30] [2540/2639] eta: 0:04:59 lr: 1.3108219863385643e-05 loss: 0.0352 (0.0356) time: 3.0413 data: 0.0082 max mem: 33408 +Epoch: [30] [2550/2639] eta: 0:04:29 lr: 1.3103273054190144e-05 loss: 0.0352 (0.0357) time: 3.0496 data: 0.0081 max mem: 33408 +Epoch: [30] [2560/2639] eta: 0:03:59 lr: 1.3098326037481187e-05 loss: 0.0359 (0.0357) time: 3.0711 data: 0.0082 max mem: 33408 +Epoch: [30] [2570/2639] eta: 0:03:28 lr: 1.3093378813162995e-05 loss: 0.0328 (0.0357) time: 3.0512 data: 0.0083 max mem: 33408 +Epoch: [30] [2580/2639] eta: 0:02:58 lr: 1.3088431381139674e-05 loss: 0.0305 (0.0356) time: 2.9954 data: 0.0083 max mem: 33408 +Epoch: [30] [2590/2639] eta: 0:02:28 lr: 1.3083483741315273e-05 loss: 0.0278 (0.0356) time: 3.0168 data: 0.0080 max mem: 33408 +Epoch: [30] [2600/2639] eta: 0:01:58 lr: 1.3078535893593728e-05 loss: 0.0275 (0.0356) time: 3.0176 data: 0.0080 max mem: 33408 +Epoch: [30] [2610/2639] eta: 0:01:27 lr: 1.3073587837878922e-05 loss: 0.0329 (0.0356) time: 3.0327 data: 0.0082 max mem: 33408 +Epoch: [30] [2620/2639] eta: 0:00:57 lr: 1.3068639574074624e-05 loss: 0.0329 (0.0357) time: 3.0501 data: 0.0083 max mem: 33408 +Epoch: [30] [2630/2639] eta: 0:00:27 lr: 1.3063691102084538e-05 loss: 0.0310 (0.0357) time: 3.0429 data: 0.0081 max mem: 33408 +Epoch: [30] Total time: 2:13:13 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 2:11:44 time: 3.0723 data: 2.9711 max mem: 33408 +Test: [ 100/2573] eta: 0:04:26 time: 0.0787 data: 0.0014 max mem: 33408 +Test: [ 200/2573] eta: 0:03:43 time: 0.0795 data: 0.0016 max mem: 33408 +Test: [ 300/2573] eta: 0:03:22 time: 0.0816 data: 0.0015 max mem: 33408 +Test: [ 400/2573] eta: 0:03:08 time: 0.0834 data: 0.0014 max mem: 33408 +Test: [ 500/2573] eta: 0:02:57 time: 0.0811 data: 0.0014 max mem: 33408 +Test: [ 600/2573] eta: 0:02:48 time: 0.0816 data: 0.0015 max mem: 33408 +Test: [ 700/2573] eta: 0:02:38 time: 0.0803 data: 0.0014 max mem: 33408 +Test: [ 800/2573] eta: 0:02:29 time: 0.0849 data: 0.0014 max mem: 33408 +Test: [ 900/2573] eta: 0:02:20 time: 0.0802 data: 0.0015 max mem: 33408 +Test: [1000/2573] eta: 0:02:11 time: 0.0803 data: 0.0014 max mem: 33408 +Test: [1100/2573] eta: 0:02:03 time: 0.0810 data: 0.0015 max mem: 33408 +Test: [1200/2573] eta: 0:01:54 time: 0.0819 data: 0.0015 max mem: 33408 +Test: [1300/2573] eta: 0:01:46 time: 0.0825 data: 0.0015 max mem: 33408 +Test: [1400/2573] eta: 0:01:37 time: 0.0807 data: 0.0017 max mem: 33408 +Test: [1500/2573] eta: 0:01:29 time: 0.0816 data: 0.0015 max mem: 33408 +Test: [1600/2573] eta: 0:01:20 time: 0.0849 data: 0.0014 max mem: 33408 +Test: [1700/2573] eta: 0:01:12 time: 0.0800 data: 0.0014 max mem: 33408 +Test: [1800/2573] eta: 0:01:04 time: 0.0826 data: 0.0014 max mem: 33408 +Test: [1900/2573] eta: 0:00:55 time: 0.0792 data: 0.0015 max mem: 33408 +Test: [2000/2573] eta: 0:00:47 time: 0.0822 data: 0.0015 max mem: 33408 +Test: [2100/2573] eta: 0:00:39 time: 0.0844 data: 0.0015 max mem: 33408 +Test: [2200/2573] eta: 0:00:30 time: 0.0832 data: 0.0015 max mem: 33408 +Test: [2300/2573] eta: 0:00:22 time: 0.0826 data: 0.0016 max mem: 33408 +Test: [2400/2573] eta: 0:00:14 time: 0.0786 data: 0.0014 max mem: 33408 +Test: [2500/2573] eta: 0:00:06 time: 0.0816 data: 0.0015 max mem: 33408 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: Total time: 0:03:33 +Final results: +Mean IoU is 64.87 + + precision@0.5 = 72.75 + precision@0.6 = 67.73 + precision@0.7 = 60.58 + precision@0.8 = 50.20 + precision@0.9 = 25.29 + overall IoU = 62.27 + +Average object IoU 64.86574107121285 +Overall IoU 62.27113723754883 +Better epoch: 30 + +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [31] [ 0/2639] eta: 3:46:43 lr: 1.3059237299214946e-05 loss: 0.0888 (0.0888) time: 5.1548 data: 2.0660 max mem: 33408 +Epoch: [31] [ 10/2639] eta: 2:22:44 lr: 1.3054288431406237e-05 loss: 0.0349 (0.0381) time: 3.2577 data: 0.1956 max mem: 33408 +Epoch: [31] [ 20/2639] eta: 2:17:37 lr: 1.3049339355131979e-05 loss: 0.0327 (0.0377) time: 3.0530 data: 0.0078 max mem: 33408 +Epoch: [31] [ 30/2639] eta: 2:15:57 lr: 1.3044390070295528e-05 loss: 0.0315 (0.0355) time: 3.0547 data: 0.0081 max mem: 33408 +Epoch: [31] [ 40/2639] eta: 2:14:36 lr: 1.3039440576800174e-05 loss: 0.0297 (0.0351) time: 3.0598 data: 0.0087 max mem: 33408 +Epoch: [31] [ 50/2639] eta: 2:12:50 lr: 1.3034490874549098e-05 loss: 0.0301 (0.0346) time: 3.0037 data: 0.0079 max mem: 33408 +Epoch: [31] [ 60/2639] eta: 2:11:27 lr: 1.3029540963445419e-05 loss: 0.0291 (0.0354) time: 2.9574 data: 0.0078 max mem: 33408 +Epoch: [31] [ 70/2639] eta: 2:10:12 lr: 1.3024590843392149e-05 loss: 0.0336 (0.0364) time: 2.9460 data: 0.0080 max mem: 33408 +Epoch: [31] [ 80/2639] eta: 2:09:33 lr: 1.3019640514292223e-05 loss: 0.0349 (0.0361) time: 2.9750 data: 0.0084 max mem: 33408 +Epoch: [31] [ 90/2639] eta: 2:09:18 lr: 1.3014689976048502e-05 loss: 0.0327 (0.0359) time: 3.0522 data: 0.0085 max mem: 33408 +Epoch: [31] [ 100/2639] eta: 2:09:06 lr: 1.3009739228563733e-05 loss: 0.0319 (0.0360) time: 3.1037 data: 0.0081 max mem: 33408 +Epoch: [31] [ 110/2639] eta: 2:08:38 lr: 1.3004788271740606e-05 loss: 0.0353 (0.0358) time: 3.0893 data: 0.0081 max mem: 33408 +Epoch: [31] [ 120/2639] eta: 2:08:00 lr: 1.2999837105481699e-05 loss: 0.0353 (0.0364) time: 3.0398 data: 0.0083 max mem: 33408 +Epoch: [31] [ 130/2639] eta: 2:07:18 lr: 1.299488572968953e-05 loss: 0.0358 (0.0363) time: 3.0045 data: 0.0084 max mem: 33408 +Epoch: [31] [ 140/2639] eta: 2:06:38 lr: 1.29899341442665e-05 loss: 0.0322 (0.0362) time: 2.9893 data: 0.0081 max mem: 33408 +Epoch: [31] [ 150/2639] eta: 2:05:58 lr: 1.2984982349114952e-05 loss: 0.0314 (0.0359) time: 2.9867 data: 0.0082 max mem: 33408 +Epoch: [31] [ 160/2639] eta: 2:05:29 lr: 1.2980030344137118e-05 loss: 0.0293 (0.0358) time: 3.0160 data: 0.0084 max mem: 33408 +Epoch: [31] [ 170/2639] eta: 2:05:03 lr: 1.2975078129235163e-05 loss: 0.0331 (0.0360) time: 3.0564 data: 0.0079 max mem: 33408 +Epoch: [31] [ 180/2639] eta: 2:04:24 lr: 1.2970125704311148e-05 loss: 0.0347 (0.0359) time: 3.0210 data: 0.0078 max mem: 33408 +Epoch: [31] [ 190/2639] eta: 2:03:58 lr: 1.2965173069267067e-05 loss: 0.0344 (0.0358) time: 3.0211 data: 0.0079 max mem: 33408 +Epoch: [31] [ 200/2639] eta: 2:03:27 lr: 1.2960220224004798e-05 loss: 0.0316 (0.0356) time: 3.0519 data: 0.0077 max mem: 33408 +Epoch: [31] [ 210/2639] eta: 2:02:53 lr: 1.2955267168426163e-05 loss: 0.0343 (0.0358) time: 3.0182 data: 0.0078 max mem: 33408 +Epoch: [31] [ 220/2639] eta: 2:02:29 lr: 1.295031390243287e-05 loss: 0.0357 (0.0357) time: 3.0488 data: 0.0078 max mem: 33408 +Epoch: [31] [ 230/2639] eta: 2:01:51 lr: 1.2945360425926562e-05 loss: 0.0308 (0.0354) time: 3.0312 data: 0.0079 max mem: 33408 +Epoch: [31] [ 240/2639] eta: 2:01:17 lr: 1.2940406738808766e-05 loss: 0.0284 (0.0356) time: 2.9794 data: 0.0080 max mem: 33408 +Epoch: [31] [ 250/2639] eta: 2:00:52 lr: 1.2935452840980958e-05 loss: 0.0354 (0.0357) time: 3.0432 data: 0.0081 max mem: 33408 +Epoch: [31] [ 260/2639] eta: 2:00:21 lr: 1.2930498732344487e-05 loss: 0.0333 (0.0356) time: 3.0603 data: 0.0084 max mem: 33408 +Epoch: [31] [ 270/2639] eta: 1:59:56 lr: 1.2925544412800643e-05 loss: 0.0322 (0.0357) time: 3.0656 data: 0.0083 max mem: 33408 +Epoch: [31] [ 280/2639] eta: 1:59:26 lr: 1.2920589882250613e-05 loss: 0.0317 (0.0356) time: 3.0712 data: 0.0085 max mem: 33408 +Epoch: [31] [ 290/2639] eta: 1:58:52 lr: 1.2915635140595509e-05 loss: 0.0285 (0.0353) time: 3.0171 data: 0.0084 max mem: 33408 +Epoch: [31] [ 300/2639] eta: 1:58:18 lr: 1.2910680187736328e-05 loss: 0.0262 (0.0352) time: 2.9929 data: 0.0085 max mem: 33408 +Epoch: [31] [ 310/2639] eta: 1:57:47 lr: 1.2905725023574014e-05 loss: 0.0315 (0.0352) time: 3.0044 data: 0.0085 max mem: 33408 +Epoch: [31] [ 320/2639] eta: 1:57:18 lr: 1.2900769648009389e-05 loss: 0.0315 (0.0351) time: 3.0349 data: 0.0082 max mem: 33408 +Epoch: [31] [ 330/2639] eta: 1:56:43 lr: 1.2895814060943208e-05 loss: 0.0289 (0.0349) time: 3.0108 data: 0.0083 max mem: 33408 +Epoch: [31] [ 340/2639] eta: 1:56:15 lr: 1.2890858262276135e-05 loss: 0.0337 (0.0351) time: 3.0176 data: 0.0084 max mem: 33408 +Epoch: [31] [ 350/2639] eta: 1:55:48 lr: 1.2885902251908727e-05 loss: 0.0371 (0.0352) time: 3.0760 data: 0.0082 max mem: 33408 +Epoch: [31] [ 360/2639] eta: 1:55:18 lr: 1.2880946029741478e-05 loss: 0.0388 (0.0352) time: 3.0670 data: 0.0083 max mem: 33408 +Epoch: [31] [ 370/2639] eta: 1:54:48 lr: 1.2875989595674766e-05 loss: 0.0341 (0.0351) time: 3.0427 data: 0.0084 max mem: 33408 +Epoch: [31] [ 380/2639] eta: 1:54:16 lr: 1.287103294960891e-05 loss: 0.0288 (0.0350) time: 3.0256 data: 0.0080 max mem: 33408 +Epoch: [31] [ 390/2639] eta: 1:53:45 lr: 1.2866076091444101e-05 loss: 0.0345 (0.0351) time: 3.0180 data: 0.0079 max mem: 33408 +Epoch: [31] [ 400/2639] eta: 1:53:17 lr: 1.2861119021080482e-05 loss: 0.0361 (0.0351) time: 3.0444 data: 0.0081 max mem: 33408 +Epoch: [31] [ 410/2639] eta: 1:52:45 lr: 1.2856161738418069e-05 loss: 0.0329 (0.0351) time: 3.0361 data: 0.0081 max mem: 33408 +Epoch: [31] [ 420/2639] eta: 1:52:12 lr: 1.2851204243356819e-05 loss: 0.0340 (0.0353) time: 3.0015 data: 0.0082 max mem: 33408 +Epoch: [31] [ 430/2639] eta: 1:51:39 lr: 1.2846246535796569e-05 loss: 0.0351 (0.0354) time: 2.9866 data: 0.0081 max mem: 33408 +Epoch: [31] [ 440/2639] eta: 1:51:07 lr: 1.2841288615637098e-05 loss: 0.0322 (0.0353) time: 2.9922 data: 0.0080 max mem: 33408 +Epoch: [31] [ 450/2639] eta: 1:50:35 lr: 1.2836330482778065e-05 loss: 0.0288 (0.0352) time: 2.9967 data: 0.0081 max mem: 33408 +Epoch: [31] [ 460/2639] eta: 1:50:01 lr: 1.2831372137119061e-05 loss: 0.0310 (0.0352) time: 2.9756 data: 0.0079 max mem: 33408 +Epoch: [31] [ 470/2639] eta: 1:49:29 lr: 1.2826413578559568e-05 loss: 0.0310 (0.0352) time: 2.9809 data: 0.0083 max mem: 33408 +Epoch: [31] [ 480/2639] eta: 1:48:58 lr: 1.2821454806998997e-05 loss: 0.0329 (0.0352) time: 2.9971 data: 0.0081 max mem: 33408 +Epoch: [31] [ 490/2639] eta: 1:48:29 lr: 1.281649582233665e-05 loss: 0.0324 (0.0351) time: 3.0307 data: 0.0076 max mem: 33408 +Epoch: [31] [ 500/2639] eta: 1:48:01 lr: 1.2811536624471752e-05 loss: 0.0319 (0.0352) time: 3.0683 data: 0.0075 max mem: 33408 +Epoch: [31] [ 510/2639] eta: 1:47:29 lr: 1.2806577213303419e-05 loss: 0.0341 (0.0352) time: 3.0349 data: 0.0079 max mem: 33408 +Epoch: [31] [ 520/2639] eta: 1:46:59 lr: 1.2801617588730702e-05 loss: 0.0316 (0.0351) time: 3.0117 data: 0.0081 max mem: 33408 +Epoch: [31] [ 530/2639] eta: 1:46:28 lr: 1.2796657750652536e-05 loss: 0.0285 (0.0350) time: 3.0288 data: 0.0079 max mem: 33408 +Epoch: [31] [ 540/2639] eta: 1:45:55 lr: 1.2791697698967783e-05 loss: 0.0290 (0.0350) time: 2.9901 data: 0.0079 max mem: 33408 +Epoch: [31] [ 550/2639] eta: 1:45:25 lr: 1.2786737433575199e-05 loss: 0.0305 (0.0349) time: 2.9942 data: 0.0080 max mem: 33408 +Epoch: [31] [ 560/2639] eta: 1:44:54 lr: 1.2781776954373461e-05 loss: 0.0282 (0.0349) time: 3.0214 data: 0.0079 max mem: 33408 +Epoch: [31] [ 570/2639] eta: 1:44:24 lr: 1.2776816261261138e-05 loss: 0.0275 (0.0348) time: 3.0204 data: 0.0078 max mem: 33408 +Epoch: [31] [ 580/2639] eta: 1:43:54 lr: 1.2771855354136724e-05 loss: 0.0280 (0.0347) time: 3.0326 data: 0.0080 max mem: 33408 +Epoch: [31] [ 590/2639] eta: 1:43:25 lr: 1.276689423289862e-05 loss: 0.0296 (0.0347) time: 3.0459 data: 0.0082 max mem: 33408 +Epoch: [31] [ 600/2639] eta: 1:42:53 lr: 1.2761932897445117e-05 loss: 0.0329 (0.0348) time: 3.0246 data: 0.0083 max mem: 33408 +Epoch: [31] [ 610/2639] eta: 1:42:23 lr: 1.2756971347674437e-05 loss: 0.0374 (0.0348) time: 3.0065 data: 0.0083 max mem: 33408 +Epoch: [31] [ 620/2639] eta: 1:41:51 lr: 1.2752009583484687e-05 loss: 0.0336 (0.0349) time: 3.0120 data: 0.0081 max mem: 33408 +Epoch: [31] [ 630/2639] eta: 1:41:21 lr: 1.2747047604773906e-05 loss: 0.0331 (0.0348) time: 3.0157 data: 0.0078 max mem: 33408 +Epoch: [31] [ 640/2639] eta: 1:40:52 lr: 1.2742085411440013e-05 loss: 0.0323 (0.0348) time: 3.0392 data: 0.0081 max mem: 33408 +Epoch: [31] [ 650/2639] eta: 1:40:22 lr: 1.2737123003380863e-05 loss: 0.0323 (0.0348) time: 3.0471 data: 0.0083 max mem: 33408 +Epoch: [31] [ 660/2639] eta: 1:39:53 lr: 1.2732160380494187e-05 loss: 0.0312 (0.0347) time: 3.0554 data: 0.0079 max mem: 33408 +Epoch: [31] [ 670/2639] eta: 1:39:22 lr: 1.2727197542677657e-05 loss: 0.0327 (0.0347) time: 3.0305 data: 0.0080 max mem: 33408 +Epoch: [31] [ 680/2639] eta: 1:38:50 lr: 1.2722234489828821e-05 loss: 0.0362 (0.0348) time: 2.9992 data: 0.0081 max mem: 33408 +Epoch: [31] [ 690/2639] eta: 1:38:20 lr: 1.271727122184516e-05 loss: 0.0325 (0.0348) time: 3.0025 data: 0.0080 max mem: 33408 +Epoch: [31] [ 700/2639] eta: 1:37:48 lr: 1.2712307738624036e-05 loss: 0.0322 (0.0349) time: 3.0001 data: 0.0082 max mem: 33408 +Epoch: [31] [ 710/2639] eta: 1:37:19 lr: 1.2707344040062739e-05 loss: 0.0322 (0.0350) time: 3.0263 data: 0.0078 max mem: 33408 +Epoch: [31] [ 720/2639] eta: 1:36:48 lr: 1.270238012605845e-05 loss: 0.0319 (0.0349) time: 3.0282 data: 0.0076 max mem: 33408 +Epoch: [31] [ 730/2639] eta: 1:36:16 lr: 1.2697415996508271e-05 loss: 0.0317 (0.0349) time: 2.9814 data: 0.0086 max mem: 33408 +Epoch: [31] [ 740/2639] eta: 1:35:46 lr: 1.2692451651309195e-05 loss: 0.0359 (0.0350) time: 2.9992 data: 0.0088 max mem: 33408 +Epoch: [31] [ 750/2639] eta: 1:35:17 lr: 1.2687487090358135e-05 loss: 0.0362 (0.0350) time: 3.0600 data: 0.0078 max mem: 33408 +Epoch: [31] [ 760/2639] eta: 1:34:47 lr: 1.2682522313551893e-05 loss: 0.0348 (0.0351) time: 3.0655 data: 0.0076 max mem: 33408 +Epoch: [31] [ 770/2639] eta: 1:34:15 lr: 1.26775573207872e-05 loss: 0.0326 (0.0351) time: 2.9924 data: 0.0078 max mem: 33408 +Epoch: [31] [ 780/2639] eta: 1:33:46 lr: 1.2672592111960665e-05 loss: 0.0296 (0.0351) time: 3.0123 data: 0.0079 max mem: 33408 +Epoch: [31] [ 790/2639] eta: 1:33:17 lr: 1.2667626686968833e-05 loss: 0.0323 (0.0351) time: 3.0715 data: 0.0080 max mem: 33408 +Epoch: [31] [ 800/2639] eta: 1:32:48 lr: 1.2662661045708122e-05 loss: 0.0311 (0.0351) time: 3.0741 data: 0.0084 max mem: 33408 +Epoch: [31] [ 810/2639] eta: 1:32:17 lr: 1.2657695188074886e-05 loss: 0.0344 (0.0351) time: 3.0556 data: 0.0086 max mem: 33408 +Epoch: [31] [ 820/2639] eta: 1:31:49 lr: 1.2652729113965357e-05 loss: 0.0346 (0.0351) time: 3.0745 data: 0.0082 max mem: 33408 +Epoch: [31] [ 830/2639] eta: 1:31:19 lr: 1.2647762823275686e-05 loss: 0.0323 (0.0351) time: 3.0841 data: 0.0084 max mem: 33408 +Epoch: [31] [ 840/2639] eta: 1:30:49 lr: 1.264279631590194e-05 loss: 0.0330 (0.0351) time: 3.0294 data: 0.0082 max mem: 33408 +Epoch: [31] [ 850/2639] eta: 1:30:17 lr: 1.2637829591740064e-05 loss: 0.0285 (0.0351) time: 2.9927 data: 0.0082 max mem: 33408 +Epoch: [31] [ 860/2639] eta: 1:29:48 lr: 1.2632862650685931e-05 loss: 0.0284 (0.0350) time: 3.0219 data: 0.0082 max mem: 33408 +Epoch: [31] [ 870/2639] eta: 1:29:18 lr: 1.2627895492635304e-05 loss: 0.0299 (0.0350) time: 3.0699 data: 0.0079 max mem: 33408 +Epoch: [31] [ 880/2639] eta: 1:28:48 lr: 1.2622928117483857e-05 loss: 0.0295 (0.0349) time: 3.0399 data: 0.0086 max mem: 33408 +Epoch: [31] [ 890/2639] eta: 1:28:18 lr: 1.2617960525127165e-05 loss: 0.0283 (0.0349) time: 3.0426 data: 0.0083 max mem: 33408 +Epoch: [31] [ 900/2639] eta: 1:27:49 lr: 1.2612992715460712e-05 loss: 0.0298 (0.0349) time: 3.0757 data: 0.0077 max mem: 33408 +Epoch: [31] [ 910/2639] eta: 1:27:19 lr: 1.2608024688379877e-05 loss: 0.0318 (0.0349) time: 3.0729 data: 0.0077 max mem: 33408 +Epoch: [31] [ 920/2639] eta: 1:26:48 lr: 1.2603056443779959e-05 loss: 0.0319 (0.0349) time: 3.0095 data: 0.0076 max mem: 33408 +Epoch: [31] [ 930/2639] eta: 1:26:16 lr: 1.259808798155614e-05 loss: 0.0294 (0.0349) time: 2.9535 data: 0.0078 max mem: 33408 +Epoch: [31] [ 940/2639] eta: 1:25:45 lr: 1.259311930160352e-05 loss: 0.0301 (0.0349) time: 2.9737 data: 0.0078 max mem: 33408 +Epoch: [31] [ 950/2639] eta: 1:25:15 lr: 1.2588150403817095e-05 loss: 0.0294 (0.0349) time: 3.0115 data: 0.0075 max mem: 33408 +Epoch: [31] [ 960/2639] eta: 1:24:44 lr: 1.2583181288091775e-05 loss: 0.0299 (0.0348) time: 3.0185 data: 0.0076 max mem: 33408 +Epoch: [31] [ 970/2639] eta: 1:24:13 lr: 1.2578211954322353e-05 loss: 0.0311 (0.0348) time: 3.0092 data: 0.0082 max mem: 33408 +Epoch: [31] [ 980/2639] eta: 1:23:44 lr: 1.2573242402403554e-05 loss: 0.0294 (0.0348) time: 3.0336 data: 0.0085 max mem: 33408 +Epoch: [31] [ 990/2639] eta: 1:23:12 lr: 1.2568272632229972e-05 loss: 0.0297 (0.0348) time: 3.0138 data: 0.0083 max mem: 33408 +Epoch: [31] [1000/2639] eta: 1:22:43 lr: 1.2563302643696137e-05 loss: 0.0359 (0.0349) time: 3.0192 data: 0.0082 max mem: 33408 +Epoch: [31] [1010/2639] eta: 1:22:13 lr: 1.2558332436696451e-05 loss: 0.0324 (0.0348) time: 3.0668 data: 0.0081 max mem: 33408 +Epoch: [31] [1020/2639] eta: 1:21:42 lr: 1.255336201112525e-05 loss: 0.0306 (0.0348) time: 3.0237 data: 0.0078 max mem: 33408 +Epoch: [31] [1030/2639] eta: 1:21:11 lr: 1.2548391366876741e-05 loss: 0.0302 (0.0348) time: 2.9915 data: 0.0079 max mem: 33408 +Epoch: [31] [1040/2639] eta: 1:20:42 lr: 1.2543420503845057e-05 loss: 0.0302 (0.0349) time: 3.0331 data: 0.0078 max mem: 33408 +Epoch: [31] [1050/2639] eta: 1:20:11 lr: 1.2538449421924217e-05 loss: 0.0297 (0.0348) time: 3.0184 data: 0.0076 max mem: 33408 +Epoch: [31] [1060/2639] eta: 1:19:40 lr: 1.2533478121008153e-05 loss: 0.0269 (0.0348) time: 2.9824 data: 0.0077 max mem: 33408 +Epoch: [31] [1070/2639] eta: 1:19:10 lr: 1.25285066009907e-05 loss: 0.0298 (0.0348) time: 3.0221 data: 0.0076 max mem: 33408 +Epoch: [31] [1080/2639] eta: 1:18:40 lr: 1.2523534861765579e-05 loss: 0.0351 (0.0348) time: 3.0465 data: 0.0078 max mem: 33408 +Epoch: [31] [1090/2639] eta: 1:18:08 lr: 1.2518562903226433e-05 loss: 0.0328 (0.0348) time: 2.9949 data: 0.0078 max mem: 33408 +Epoch: [31] [1100/2639] eta: 1:17:38 lr: 1.2513590725266785e-05 loss: 0.0304 (0.0348) time: 2.9758 data: 0.0074 max mem: 33408 +Epoch: [31] [1110/2639] eta: 1:17:07 lr: 1.2508618327780087e-05 loss: 0.0303 (0.0348) time: 2.9826 data: 0.0076 max mem: 33408 +Epoch: [31] [1120/2639] eta: 1:16:37 lr: 1.2503645710659658e-05 loss: 0.0350 (0.0348) time: 3.0309 data: 0.0081 max mem: 33408 +Epoch: [31] [1130/2639] eta: 1:16:08 lr: 1.2498672873798753e-05 loss: 0.0343 (0.0348) time: 3.0905 data: 0.0083 max mem: 33408 +Epoch: [31] [1140/2639] eta: 1:15:38 lr: 1.2493699817090496e-05 loss: 0.0337 (0.0348) time: 3.0897 data: 0.0084 max mem: 33408 +Epoch: [31] [1150/2639] eta: 1:15:08 lr: 1.248872654042794e-05 loss: 0.0357 (0.0348) time: 3.0565 data: 0.0081 max mem: 33408 +Epoch: [31] [1160/2639] eta: 1:14:38 lr: 1.2483753043704009e-05 loss: 0.0321 (0.0348) time: 3.0212 data: 0.0080 max mem: 33408 +Epoch: [31] [1170/2639] eta: 1:14:08 lr: 1.2478779326811561e-05 loss: 0.0299 (0.0348) time: 3.0630 data: 0.0078 max mem: 33408 +Epoch: [31] [1180/2639] eta: 1:13:39 lr: 1.2473805389643324e-05 loss: 0.0303 (0.0348) time: 3.0839 data: 0.0075 max mem: 33408 +Epoch: [31] [1190/2639] eta: 1:13:09 lr: 1.246883123209195e-05 loss: 0.0300 (0.0347) time: 3.0672 data: 0.0079 max mem: 33408 +Epoch: [31] [1200/2639] eta: 1:12:38 lr: 1.2463856854049969e-05 loss: 0.0278 (0.0347) time: 3.0440 data: 0.0082 max mem: 33408 +Epoch: [31] [1210/2639] eta: 1:12:09 lr: 1.2458882255409832e-05 loss: 0.0348 (0.0349) time: 3.0483 data: 0.0081 max mem: 33408 +Epoch: [31] [1220/2639] eta: 1:11:38 lr: 1.2453907436063871e-05 loss: 0.0348 (0.0348) time: 3.0323 data: 0.0078 max mem: 33408 +Epoch: [31] [1230/2639] eta: 1:11:06 lr: 1.2448932395904338e-05 loss: 0.0317 (0.0348) time: 2.9629 data: 0.0078 max mem: 33408 +Epoch: [31] [1240/2639] eta: 1:10:36 lr: 1.244395713482336e-05 loss: 0.0322 (0.0348) time: 2.9570 data: 0.0082 max mem: 33408 +Epoch: [31] [1250/2639] eta: 1:10:06 lr: 1.2438981652712988e-05 loss: 0.0345 (0.0349) time: 3.0296 data: 0.0080 max mem: 33408 +Epoch: [31] [1260/2639] eta: 1:09:36 lr: 1.2434005949465152e-05 loss: 0.0295 (0.0348) time: 3.0539 data: 0.0082 max mem: 33408 +Epoch: [31] [1270/2639] eta: 1:09:05 lr: 1.24290300249717e-05 loss: 0.0292 (0.0348) time: 3.0253 data: 0.0082 max mem: 33408 +Epoch: [31] [1280/2639] eta: 1:08:35 lr: 1.2424053879124354e-05 loss: 0.0324 (0.0348) time: 3.0113 data: 0.0080 max mem: 33408 +Epoch: [31] [1290/2639] eta: 1:08:04 lr: 1.2419077511814767e-05 loss: 0.0320 (0.0348) time: 3.0002 data: 0.0079 max mem: 33408 +Epoch: [31] [1300/2639] eta: 1:07:35 lr: 1.2414100922934459e-05 loss: 0.0304 (0.0348) time: 3.0615 data: 0.0081 max mem: 33408 +Epoch: [31] [1310/2639] eta: 1:07:04 lr: 1.2409124112374867e-05 loss: 0.0310 (0.0348) time: 3.0757 data: 0.0082 max mem: 33408 +Epoch: [31] [1320/2639] eta: 1:06:34 lr: 1.240414708002733e-05 loss: 0.0303 (0.0348) time: 3.0247 data: 0.0078 max mem: 33408 +Epoch: [31] [1330/2639] eta: 1:06:04 lr: 1.2399169825783064e-05 loss: 0.0300 (0.0348) time: 3.0158 data: 0.0079 max mem: 33408 +Epoch: [31] [1340/2639] eta: 1:05:33 lr: 1.2394192349533213e-05 loss: 0.0321 (0.0348) time: 3.0071 data: 0.0082 max mem: 33408 +Epoch: [31] [1350/2639] eta: 1:05:03 lr: 1.2389214651168784e-05 loss: 0.0358 (0.0349) time: 3.0410 data: 0.0078 max mem: 33408 +Epoch: [31] [1360/2639] eta: 1:04:32 lr: 1.2384236730580719e-05 loss: 0.0326 (0.0349) time: 3.0118 data: 0.0078 max mem: 33408 +Epoch: [31] [1370/2639] eta: 1:04:01 lr: 1.2379258587659823e-05 loss: 0.0340 (0.0349) time: 2.9515 data: 0.0083 max mem: 33408 +Epoch: [31] [1380/2639] eta: 1:03:31 lr: 1.2374280222296827e-05 loss: 0.0355 (0.0349) time: 3.0125 data: 0.0084 max mem: 33408 +Epoch: [31] [1390/2639] eta: 1:03:02 lr: 1.2369301634382337e-05 loss: 0.0355 (0.0349) time: 3.0717 data: 0.0083 max mem: 33408 +Epoch: [31] [1400/2639] eta: 1:02:31 lr: 1.2364322823806877e-05 loss: 0.0380 (0.0350) time: 3.0493 data: 0.0081 max mem: 33408 +Epoch: [31] [1410/2639] eta: 1:02:01 lr: 1.2359343790460845e-05 loss: 0.0312 (0.0349) time: 3.0060 data: 0.0080 max mem: 33408 +Epoch: [31] [1420/2639] eta: 1:01:31 lr: 1.235436453423456e-05 loss: 0.0300 (0.0350) time: 3.0282 data: 0.0077 max mem: 33408 +Epoch: [31] [1430/2639] eta: 1:01:01 lr: 1.2349385055018218e-05 loss: 0.0337 (0.0349) time: 3.0633 data: 0.0078 max mem: 33408 +Epoch: [31] [1440/2639] eta: 1:00:30 lr: 1.234440535270193e-05 loss: 0.0301 (0.0349) time: 3.0093 data: 0.0076 max mem: 33408 +Epoch: [31] [1450/2639] eta: 0:59:59 lr: 1.2339425427175679e-05 loss: 0.0261 (0.0349) time: 2.9646 data: 0.0078 max mem: 33408 +Epoch: [31] [1460/2639] eta: 0:59:29 lr: 1.2334445278329373e-05 loss: 0.0261 (0.0349) time: 3.0158 data: 0.0078 max mem: 33408 +Epoch: [31] [1470/2639] eta: 0:58:59 lr: 1.2329464906052791e-05 loss: 0.0288 (0.0349) time: 3.0519 data: 0.0077 max mem: 33408 +Epoch: [31] [1480/2639] eta: 0:58:29 lr: 1.232448431023563e-05 loss: 0.0324 (0.0349) time: 3.0410 data: 0.0082 max mem: 33408 +Epoch: [31] [1490/2639] eta: 0:57:58 lr: 1.2319503490767462e-05 loss: 0.0325 (0.0349) time: 2.9974 data: 0.0081 max mem: 33408 +Epoch: [31] [1500/2639] eta: 0:57:27 lr: 1.2314522447537775e-05 loss: 0.0335 (0.0348) time: 2.9694 data: 0.0077 max mem: 33408 +Epoch: [31] [1510/2639] eta: 0:56:57 lr: 1.2309541180435931e-05 loss: 0.0306 (0.0348) time: 2.9982 data: 0.0077 max mem: 33408 +Epoch: [31] [1520/2639] eta: 0:56:27 lr: 1.2304559689351213e-05 loss: 0.0310 (0.0348) time: 3.0518 data: 0.0080 max mem: 33408 +Epoch: [31] [1530/2639] eta: 0:55:57 lr: 1.2299577974172774e-05 loss: 0.0310 (0.0348) time: 3.0698 data: 0.0084 max mem: 33408 +Epoch: [31] [1540/2639] eta: 0:55:27 lr: 1.2294596034789683e-05 loss: 0.0312 (0.0349) time: 3.0373 data: 0.0086 max mem: 33408 +Epoch: [31] [1550/2639] eta: 0:54:56 lr: 1.2289613871090888e-05 loss: 0.0330 (0.0349) time: 3.0057 data: 0.0083 max mem: 33408 +Epoch: [31] [1560/2639] eta: 0:54:26 lr: 1.228463148296524e-05 loss: 0.0358 (0.0349) time: 3.0345 data: 0.0079 max mem: 33408 +Epoch: [31] [1570/2639] eta: 0:53:56 lr: 1.2279648870301493e-05 loss: 0.0365 (0.0350) time: 3.0774 data: 0.0081 max mem: 33408 +Epoch: [31] [1580/2639] eta: 0:53:26 lr: 1.2274666032988274e-05 loss: 0.0418 (0.0350) time: 3.0737 data: 0.0085 max mem: 33408 +Epoch: [31] [1590/2639] eta: 0:52:56 lr: 1.2269682970914126e-05 loss: 0.0347 (0.0350) time: 3.0282 data: 0.0085 max mem: 33408 +Epoch: [31] [1600/2639] eta: 0:52:25 lr: 1.226469968396747e-05 loss: 0.0292 (0.0350) time: 2.9557 data: 0.0084 max mem: 33408 +Epoch: [31] [1610/2639] eta: 0:51:54 lr: 1.2259716172036638e-05 loss: 0.0339 (0.0350) time: 2.9625 data: 0.0086 max mem: 33408 +Epoch: [31] [1620/2639] eta: 0:51:24 lr: 1.2254732435009837e-05 loss: 0.0320 (0.0350) time: 3.0354 data: 0.0086 max mem: 33408 +Epoch: [31] [1630/2639] eta: 0:50:54 lr: 1.2249748472775187e-05 loss: 0.0314 (0.0349) time: 3.0592 data: 0.0082 max mem: 33408 +Epoch: [31] [1640/2639] eta: 0:50:24 lr: 1.2244764285220681e-05 loss: 0.0346 (0.0349) time: 3.0420 data: 0.0082 max mem: 33408 +Epoch: [31] [1650/2639] eta: 0:49:54 lr: 1.223977987223423e-05 loss: 0.0379 (0.0350) time: 3.0395 data: 0.0082 max mem: 33408 +Epoch: [31] [1660/2639] eta: 0:49:23 lr: 1.2234795233703612e-05 loss: 0.0327 (0.0350) time: 3.0308 data: 0.0076 max mem: 33408 +Epoch: [31] [1670/2639] eta: 0:48:53 lr: 1.2229810369516527e-05 loss: 0.0293 (0.0350) time: 2.9872 data: 0.0073 max mem: 33408 +Epoch: [31] [1680/2639] eta: 0:48:23 lr: 1.2224825279560536e-05 loss: 0.0315 (0.0349) time: 2.9964 data: 0.0074 max mem: 33408 +Epoch: [31] [1690/2639] eta: 0:47:53 lr: 1.2219839963723128e-05 loss: 0.0321 (0.0349) time: 3.0573 data: 0.0073 max mem: 33408 +Epoch: [31] [1700/2639] eta: 0:47:22 lr: 1.221485442189165e-05 loss: 0.0320 (0.0349) time: 3.0214 data: 0.0073 max mem: 33408 +Epoch: [31] [1710/2639] eta: 0:46:52 lr: 1.2209868653953373e-05 loss: 0.0274 (0.0349) time: 3.0039 data: 0.0072 max mem: 33408 +Epoch: [31] [1720/2639] eta: 0:46:22 lr: 1.2204882659795433e-05 loss: 0.0309 (0.0349) time: 3.0372 data: 0.0073 max mem: 33408 +Epoch: [31] [1730/2639] eta: 0:45:52 lr: 1.2199896439304884e-05 loss: 0.0300 (0.0349) time: 3.0908 data: 0.0075 max mem: 33408 +Epoch: [31] [1740/2639] eta: 0:45:21 lr: 1.2194909992368648e-05 loss: 0.0294 (0.0349) time: 3.0642 data: 0.0077 max mem: 33408 +Epoch: [31] [1750/2639] eta: 0:44:51 lr: 1.2189923318873564e-05 loss: 0.0328 (0.0349) time: 3.0335 data: 0.0074 max mem: 33408 +Epoch: [31] [1760/2639] eta: 0:44:21 lr: 1.2184936418706337e-05 loss: 0.0342 (0.0349) time: 3.0613 data: 0.0074 max mem: 33408 +Epoch: [31] [1770/2639] eta: 0:43:51 lr: 1.217994929175359e-05 loss: 0.0342 (0.0349) time: 3.0292 data: 0.0076 max mem: 33408 +Epoch: [31] [1780/2639] eta: 0:43:21 lr: 1.217496193790181e-05 loss: 0.0305 (0.0349) time: 3.0213 data: 0.0076 max mem: 33408 +Epoch: [31] [1790/2639] eta: 0:42:50 lr: 1.2169974357037404e-05 loss: 0.0278 (0.0349) time: 3.0040 data: 0.0078 max mem: 33408 +Epoch: [31] [1800/2639] eta: 0:42:20 lr: 1.2164986549046643e-05 loss: 0.0275 (0.0349) time: 3.0602 data: 0.0079 max mem: 33408 +Epoch: [31] [1810/2639] eta: 0:41:50 lr: 1.215999851381571e-05 loss: 0.0337 (0.0349) time: 3.0533 data: 0.0081 max mem: 33408 +Epoch: [31] [1820/2639] eta: 0:41:19 lr: 1.2155010251230676e-05 loss: 0.0332 (0.0349) time: 2.9875 data: 0.0083 max mem: 33408 +Epoch: [31] [1830/2639] eta: 0:40:49 lr: 1.2150021761177487e-05 loss: 0.0295 (0.0349) time: 3.0308 data: 0.0083 max mem: 33408 +Epoch: [31] [1840/2639] eta: 0:40:19 lr: 1.2145033043542005e-05 loss: 0.0295 (0.0349) time: 3.0442 data: 0.0083 max mem: 33408 +Epoch: [31] [1850/2639] eta: 0:39:48 lr: 1.2140044098209956e-05 loss: 0.0286 (0.0349) time: 2.9906 data: 0.0080 max mem: 33408 +Epoch: [31] [1860/2639] eta: 0:39:18 lr: 1.2135054925066978e-05 loss: 0.0290 (0.0349) time: 2.9724 data: 0.0076 max mem: 33408 +Epoch: [31] [1870/2639] eta: 0:38:48 lr: 1.2130065523998583e-05 loss: 0.0326 (0.0349) time: 3.0134 data: 0.0076 max mem: 33408 +Epoch: [31] [1880/2639] eta: 0:38:17 lr: 1.212507589489019e-05 loss: 0.0295 (0.0349) time: 3.0203 data: 0.0077 max mem: 33408 +Epoch: [31] [1890/2639] eta: 0:37:47 lr: 1.2120086037627088e-05 loss: 0.0289 (0.0348) time: 3.0101 data: 0.0081 max mem: 33408 +Epoch: [31] [1900/2639] eta: 0:37:17 lr: 1.2115095952094479e-05 loss: 0.0303 (0.0349) time: 3.0071 data: 0.0082 max mem: 33408 +Epoch: [31] [1910/2639] eta: 0:36:46 lr: 1.2110105638177426e-05 loss: 0.0329 (0.0349) time: 3.0029 data: 0.0083 max mem: 33408 +Epoch: [31] [1920/2639] eta: 0:36:16 lr: 1.2105115095760917e-05 loss: 0.0296 (0.0348) time: 2.9790 data: 0.0086 max mem: 33408 +Epoch: [31] [1930/2639] eta: 0:35:45 lr: 1.210012432472979e-05 loss: 0.0313 (0.0349) time: 2.9811 data: 0.0081 max mem: 33408 +Epoch: [31] [1940/2639] eta: 0:35:15 lr: 1.2095133324968807e-05 loss: 0.0332 (0.0348) time: 2.9841 data: 0.0081 max mem: 33408 +Epoch: [31] [1950/2639] eta: 0:34:45 lr: 1.2090142096362593e-05 loss: 0.0337 (0.0348) time: 2.9851 data: 0.0085 max mem: 33408 +Epoch: [31] [1960/2639] eta: 0:34:15 lr: 1.2085150638795685e-05 loss: 0.0284 (0.0348) time: 3.0539 data: 0.0079 max mem: 33408 +Epoch: [31] [1970/2639] eta: 0:33:44 lr: 1.2080158952152486e-05 loss: 0.0270 (0.0348) time: 3.0836 data: 0.0075 max mem: 33408 +Epoch: [31] [1980/2639] eta: 0:33:14 lr: 1.2075167036317306e-05 loss: 0.0284 (0.0348) time: 3.0692 data: 0.0078 max mem: 33408 +Epoch: [31] [1990/2639] eta: 0:32:44 lr: 1.2070174891174327e-05 loss: 0.0297 (0.0347) time: 3.0443 data: 0.0085 max mem: 33408 +Epoch: [31] [2000/2639] eta: 0:32:14 lr: 1.206518251660764e-05 loss: 0.0312 (0.0347) time: 3.0293 data: 0.0085 max mem: 33408 +Epoch: [31] [2010/2639] eta: 0:31:44 lr: 1.2060189912501198e-05 loss: 0.0292 (0.0347) time: 3.0394 data: 0.0082 max mem: 33408 +Epoch: [31] [2020/2639] eta: 0:31:13 lr: 1.2055197078738868e-05 loss: 0.0311 (0.0347) time: 3.0563 data: 0.0080 max mem: 33408 +Epoch: [31] [2030/2639] eta: 0:30:43 lr: 1.2050204015204382e-05 loss: 0.0359 (0.0347) time: 3.0496 data: 0.0077 max mem: 33408 +Epoch: [31] [2040/2639] eta: 0:30:13 lr: 1.2045210721781383e-05 loss: 0.0340 (0.0347) time: 3.0374 data: 0.0081 max mem: 33408 +Epoch: [31] [2050/2639] eta: 0:29:43 lr: 1.2040217198353371e-05 loss: 0.0335 (0.0347) time: 3.0530 data: 0.0081 max mem: 33408 +Epoch: [31] [2060/2639] eta: 0:29:12 lr: 1.2035223444803766e-05 loss: 0.0340 (0.0347) time: 3.0494 data: 0.0079 max mem: 33408 +Epoch: [31] [2070/2639] eta: 0:28:42 lr: 1.2030229461015859e-05 loss: 0.0332 (0.0347) time: 3.0509 data: 0.0087 max mem: 33408 +Epoch: [31] [2080/2639] eta: 0:28:12 lr: 1.202523524687282e-05 loss: 0.0346 (0.0348) time: 3.0123 data: 0.0087 max mem: 33408 +Epoch: [31] [2090/2639] eta: 0:27:42 lr: 1.2020240802257725e-05 loss: 0.0339 (0.0348) time: 3.0118 data: 0.0084 max mem: 33408 +Epoch: [31] [2100/2639] eta: 0:27:11 lr: 1.2015246127053516e-05 loss: 0.0258 (0.0348) time: 3.0406 data: 0.0083 max mem: 33408 +Epoch: [31] [2110/2639] eta: 0:26:41 lr: 1.2010251221143042e-05 loss: 0.0258 (0.0348) time: 3.0235 data: 0.0080 max mem: 33408 +Epoch: [31] [2120/2639] eta: 0:26:11 lr: 1.2005256084409018e-05 loss: 0.0303 (0.0348) time: 3.0291 data: 0.0086 max mem: 33408 +Epoch: [31] [2130/2639] eta: 0:25:41 lr: 1.2000260716734067e-05 loss: 0.0326 (0.0348) time: 3.0505 data: 0.0087 max mem: 33408 +Epoch: [31] [2140/2639] eta: 0:25:10 lr: 1.1995265118000673e-05 loss: 0.0306 (0.0347) time: 3.0629 data: 0.0081 max mem: 33408 +Epoch: [31] [2150/2639] eta: 0:24:40 lr: 1.1990269288091233e-05 loss: 0.0306 (0.0348) time: 3.0905 data: 0.0078 max mem: 33408 +Epoch: [31] [2160/2639] eta: 0:24:10 lr: 1.1985273226888002e-05 loss: 0.0333 (0.0348) time: 3.0977 data: 0.0077 max mem: 33408 +Epoch: [31] [2170/2639] eta: 0:23:40 lr: 1.1980276934273145e-05 loss: 0.0342 (0.0348) time: 3.0296 data: 0.0077 max mem: 33408 +Epoch: [31] [2180/2639] eta: 0:23:10 lr: 1.1975280410128693e-05 loss: 0.0309 (0.0348) time: 3.0193 data: 0.0077 max mem: 33408 +Epoch: [31] [2190/2639] eta: 0:22:39 lr: 1.197028365433658e-05 loss: 0.0294 (0.0347) time: 2.9961 data: 0.0079 max mem: 33408 +Epoch: [31] [2200/2639] eta: 0:22:09 lr: 1.1965286666778607e-05 loss: 0.0326 (0.0347) time: 2.9939 data: 0.0081 max mem: 33408 +Epoch: [31] [2210/2639] eta: 0:21:39 lr: 1.1960289447336478e-05 loss: 0.0309 (0.0347) time: 3.0448 data: 0.0081 max mem: 33408 +Epoch: [31] [2220/2639] eta: 0:21:08 lr: 1.1955291995891758e-05 loss: 0.0284 (0.0347) time: 3.0308 data: 0.0080 max mem: 33408 +Epoch: [31] [2230/2639] eta: 0:20:38 lr: 1.1950294312325925e-05 loss: 0.0323 (0.0347) time: 3.0080 data: 0.0080 max mem: 33408 +Epoch: [31] [2240/2639] eta: 0:20:08 lr: 1.1945296396520317e-05 loss: 0.0335 (0.0347) time: 2.9976 data: 0.0083 max mem: 33408 +Epoch: [31] [2250/2639] eta: 0:19:37 lr: 1.1940298248356175e-05 loss: 0.0332 (0.0347) time: 2.9932 data: 0.0083 max mem: 33408 +Epoch: [31] [2260/2639] eta: 0:19:07 lr: 1.1935299867714605e-05 loss: 0.0330 (0.0348) time: 2.9966 data: 0.0078 max mem: 33408 +Epoch: [31] [2270/2639] eta: 0:18:37 lr: 1.1930301254476617e-05 loss: 0.0369 (0.0348) time: 2.9739 data: 0.0077 max mem: 33408 +Epoch: [31] [2280/2639] eta: 0:18:06 lr: 1.1925302408523084e-05 loss: 0.0353 (0.0348) time: 2.9879 data: 0.0079 max mem: 33408 +Epoch: [31] [2290/2639] eta: 0:17:36 lr: 1.1920303329734785e-05 loss: 0.0326 (0.0348) time: 3.0166 data: 0.0078 max mem: 33408 +Epoch: [31] [2300/2639] eta: 0:17:06 lr: 1.1915304017992359e-05 loss: 0.0326 (0.0348) time: 3.0186 data: 0.0076 max mem: 33408 +Epoch: [31] [2310/2639] eta: 0:16:35 lr: 1.1910304473176343e-05 loss: 0.0355 (0.0348) time: 3.0219 data: 0.0085 max mem: 33408 +Epoch: [31] [2320/2639] eta: 0:16:05 lr: 1.1905304695167162e-05 loss: 0.0340 (0.0348) time: 3.0378 data: 0.0089 max mem: 33408 +Epoch: [31] [2330/2639] eta: 0:15:35 lr: 1.1900304683845102e-05 loss: 0.0328 (0.0348) time: 3.0404 data: 0.0084 max mem: 33408 +Epoch: [31] [2340/2639] eta: 0:15:05 lr: 1.1895304439090359e-05 loss: 0.0340 (0.0348) time: 3.0072 data: 0.0082 max mem: 33408 +Epoch: [31] [2350/2639] eta: 0:14:34 lr: 1.1890303960782982e-05 loss: 0.0354 (0.0348) time: 3.0402 data: 0.0079 max mem: 33408 +Epoch: [31] [2360/2639] eta: 0:14:04 lr: 1.1885303248802932e-05 loss: 0.0334 (0.0348) time: 3.0670 data: 0.0082 max mem: 33408 +Epoch: [31] [2370/2639] eta: 0:13:34 lr: 1.1880302303030027e-05 loss: 0.0311 (0.0348) time: 3.0519 data: 0.0082 max mem: 33408 +Epoch: [31] [2380/2639] eta: 0:13:04 lr: 1.187530112334399e-05 loss: 0.0329 (0.0348) time: 3.0564 data: 0.0080 max mem: 33408 +Epoch: [31] [2390/2639] eta: 0:12:33 lr: 1.1870299709624397e-05 loss: 0.0326 (0.0348) time: 3.0818 data: 0.0082 max mem: 33408 +Epoch: [31] [2400/2639] eta: 0:12:03 lr: 1.186529806175074e-05 loss: 0.0299 (0.0348) time: 3.0849 data: 0.0083 max mem: 33408 +Epoch: [31] [2410/2639] eta: 0:11:33 lr: 1.186029617960236e-05 loss: 0.0321 (0.0348) time: 3.0607 data: 0.0085 max mem: 33408 +Epoch: [31] [2420/2639] eta: 0:11:03 lr: 1.1855294063058506e-05 loss: 0.0298 (0.0348) time: 3.0433 data: 0.0084 max mem: 33408 +Epoch: [31] [2430/2639] eta: 0:10:32 lr: 1.1850291711998285e-05 loss: 0.0270 (0.0348) time: 3.0076 data: 0.0085 max mem: 33408 +Epoch: [31] [2440/2639] eta: 0:10:02 lr: 1.1845289126300706e-05 loss: 0.0300 (0.0349) time: 2.9857 data: 0.0085 max mem: 33408 +Epoch: [31] [2450/2639] eta: 0:09:32 lr: 1.1840286305844638e-05 loss: 0.0298 (0.0349) time: 2.9860 data: 0.0086 max mem: 33408 +Epoch: [31] [2460/2639] eta: 0:09:01 lr: 1.1835283250508856e-05 loss: 0.0346 (0.0349) time: 2.9624 data: 0.0090 max mem: 33408 +Epoch: [31] [2470/2639] eta: 0:08:31 lr: 1.1830279960171983e-05 loss: 0.0346 (0.0349) time: 2.9710 data: 0.0086 max mem: 33408 +Epoch: [31] [2480/2639] eta: 0:08:01 lr: 1.1825276434712558e-05 loss: 0.0329 (0.0349) time: 3.0128 data: 0.0084 max mem: 33408 +Epoch: [31] [2490/2639] eta: 0:07:31 lr: 1.1820272674008966e-05 loss: 0.0305 (0.0349) time: 3.0618 data: 0.0080 max mem: 33408 +Epoch: [31] [2500/2639] eta: 0:07:00 lr: 1.1815268677939502e-05 loss: 0.0307 (0.0349) time: 3.0637 data: 0.0076 max mem: 33408 +Epoch: [31] [2510/2639] eta: 0:06:30 lr: 1.1810264446382314e-05 loss: 0.0310 (0.0349) time: 3.0119 data: 0.0081 max mem: 33408 +Epoch: [31] [2520/2639] eta: 0:06:00 lr: 1.1805259979215454e-05 loss: 0.0307 (0.0349) time: 3.0026 data: 0.0086 max mem: 33408 +Epoch: [31] [2530/2639] eta: 0:05:29 lr: 1.180025527631683e-05 loss: 0.0307 (0.0349) time: 3.0021 data: 0.0086 max mem: 33408 +Epoch: [31] [2540/2639] eta: 0:04:59 lr: 1.1795250337564246e-05 loss: 0.0296 (0.0349) time: 3.0385 data: 0.0084 max mem: 33408 +Epoch: [31] [2550/2639] eta: 0:04:29 lr: 1.1790245162835387e-05 loss: 0.0296 (0.0349) time: 3.0863 data: 0.0084 max mem: 33408 +Epoch: [31] [2560/2639] eta: 0:03:59 lr: 1.1785239752007797e-05 loss: 0.0288 (0.0348) time: 3.0202 data: 0.0085 max mem: 33408 +Epoch: [31] [2570/2639] eta: 0:03:28 lr: 1.1780234104958923e-05 loss: 0.0293 (0.0348) time: 3.0077 data: 0.0086 max mem: 33408 +Epoch: [31] [2580/2639] eta: 0:02:58 lr: 1.1775228221566065e-05 loss: 0.0302 (0.0348) time: 3.0203 data: 0.0087 max mem: 33408 +Epoch: [31] [2590/2639] eta: 0:02:28 lr: 1.1770222101706432e-05 loss: 0.0318 (0.0348) time: 3.0329 data: 0.0081 max mem: 33408 +Epoch: [31] [2600/2639] eta: 0:01:58 lr: 1.1765215745257076e-05 loss: 0.0334 (0.0348) time: 3.0392 data: 0.0078 max mem: 33408 +Epoch: [31] [2610/2639] eta: 0:01:27 lr: 1.1760209152094963e-05 loss: 0.0341 (0.0349) time: 3.0072 data: 0.0082 max mem: 33408 +Epoch: [31] [2620/2639] eta: 0:00:57 lr: 1.1755202322096902e-05 loss: 0.0343 (0.0349) time: 3.0764 data: 0.0089 max mem: 33408 +Epoch: [31] [2630/2639] eta: 0:00:27 lr: 1.1750195255139611e-05 loss: 0.0296 (0.0349) time: 3.0811 data: 0.0083 max mem: 33408 +Epoch: [31] Total time: 2:13:11 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 2:15:29 time: 3.1594 data: 3.0506 max mem: 33408 +Test: [ 100/2573] eta: 0:04:32 time: 0.0790 data: 0.0014 max mem: 33408 +Test: [ 200/2573] eta: 0:03:48 time: 0.0808 data: 0.0015 max mem: 33408 +Test: [ 300/2573] eta: 0:03:26 time: 0.0822 data: 0.0014 max mem: 33408 +Test: [ 400/2573] eta: 0:03:12 time: 0.0827 data: 0.0015 max mem: 33408 +Test: [ 500/2573] eta: 0:03:00 time: 0.0826 data: 0.0015 max mem: 33408 +Test: [ 600/2573] eta: 0:02:50 time: 0.0820 data: 0.0015 max mem: 33408 +Test: [ 700/2573] eta: 0:02:41 time: 0.0842 data: 0.0016 max mem: 33408 +Test: [ 800/2573] eta: 0:02:32 time: 0.0845 data: 0.0013 max mem: 33408 +Test: [ 900/2573] eta: 0:02:22 time: 0.0827 data: 0.0016 max mem: 33408 +Test: [1000/2573] eta: 0:02:13 time: 0.0826 data: 0.0014 max mem: 33408 +Test: [1100/2573] eta: 0:02:05 time: 0.0822 data: 0.0014 max mem: 33408 +Test: [1200/2573] eta: 0:01:56 time: 0.0815 data: 0.0014 max mem: 33408 +Test: [1300/2573] eta: 0:01:47 time: 0.0821 data: 0.0013 max mem: 33408 +Test: [1400/2573] eta: 0:01:38 time: 0.0811 data: 0.0014 max mem: 33408 +Test: [1500/2573] eta: 0:01:30 time: 0.0822 data: 0.0015 max mem: 33408 +Test: [1600/2573] eta: 0:01:21 time: 0.0860 data: 0.0015 max mem: 33408 +Test: [1700/2573] eta: 0:01:13 time: 0.0803 data: 0.0014 max mem: 33408 +Test: [1800/2573] eta: 0:01:04 time: 0.0838 data: 0.0015 max mem: 33408 +Test: [1900/2573] eta: 0:00:56 time: 0.0805 data: 0.0015 max mem: 33408 +Test: [2000/2573] eta: 0:00:47 time: 0.0815 data: 0.0015 max mem: 33408 +Test: [2100/2573] eta: 0:00:39 time: 0.0842 data: 0.0015 max mem: 33408 +Test: [2200/2573] eta: 0:00:31 time: 0.0832 data: 0.0014 max mem: 33408 +Test: [2300/2573] eta: 0:00:22 time: 0.0847 data: 0.0015 max mem: 33408 +Test: [2400/2573] eta: 0:00:14 time: 0.0787 data: 0.0015 max mem: 33408 +Test: [2500/2573] eta: 0:00:06 time: 0.0808 data: 0.0014 max mem: 33408 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: Total time: 0:03:35 +Final results: +Mean IoU is 64.38 + + precision@0.5 = 72.34 + precision@0.6 = 67.28 + precision@0.7 = 60.46 + precision@0.8 = 49.80 + precision@0.9 = 25.02 + overall IoU = 61.97 + +Average object IoU 64.37763695473654 +Overall IoU 61.970455169677734 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [32] [ 0/2639] eta: 3:53:58 lr: 1.1745688692175894e-05 loss: 0.0447 (0.0447) time: 5.3195 data: 2.0180 max mem: 33408 +Epoch: [32] [ 10/2639] eta: 2:22:51 lr: 1.1740681174655926e-05 loss: 0.0378 (0.0355) time: 3.2603 data: 0.1915 max mem: 33408 +Epoch: [32] [ 20/2639] eta: 2:18:03 lr: 1.1735673419818473e-05 loss: 0.0302 (0.0330) time: 3.0552 data: 0.0084 max mem: 33408 +Epoch: [32] [ 30/2639] eta: 2:15:33 lr: 1.1730665427539747e-05 loss: 0.0290 (0.0340) time: 3.0389 data: 0.0082 max mem: 33408 +Epoch: [32] [ 40/2639] eta: 2:14:07 lr: 1.1725657197695861e-05 loss: 0.0317 (0.0329) time: 3.0263 data: 0.0083 max mem: 33408 +Epoch: [32] [ 50/2639] eta: 2:13:14 lr: 1.172064873016278e-05 loss: 0.0317 (0.0339) time: 3.0423 data: 0.0083 max mem: 33408 +Epoch: [32] [ 60/2639] eta: 2:12:24 lr: 1.1715640024816373e-05 loss: 0.0318 (0.0339) time: 3.0473 data: 0.0084 max mem: 33408 +Epoch: [32] [ 70/2639] eta: 2:12:12 lr: 1.1710631081532353e-05 loss: 0.0282 (0.0330) time: 3.0869 data: 0.0081 max mem: 33408 +Epoch: [32] [ 80/2639] eta: 2:11:28 lr: 1.1705621900186343e-05 loss: 0.0271 (0.0323) time: 3.0895 data: 0.0081 max mem: 33408 +Epoch: [32] [ 90/2639] eta: 2:10:44 lr: 1.1700612480653807e-05 loss: 0.0289 (0.0321) time: 3.0415 data: 0.0081 max mem: 33408 +Epoch: [32] [ 100/2639] eta: 2:10:01 lr: 1.1695602822810118e-05 loss: 0.0324 (0.0320) time: 3.0329 data: 0.0081 max mem: 33408 +Epoch: [32] [ 110/2639] eta: 2:09:29 lr: 1.1690592926530499e-05 loss: 0.0332 (0.0322) time: 3.0478 data: 0.0080 max mem: 33408 +Epoch: [32] [ 120/2639] eta: 2:08:52 lr: 1.1685582791690064e-05 loss: 0.0305 (0.0322) time: 3.0537 data: 0.0082 max mem: 33408 +Epoch: [32] [ 130/2639] eta: 2:08:18 lr: 1.168057241816379e-05 loss: 0.0291 (0.0320) time: 3.0459 data: 0.0080 max mem: 33408 +Epoch: [32] [ 140/2639] eta: 2:07:44 lr: 1.1675561805826541e-05 loss: 0.0311 (0.0328) time: 3.0521 data: 0.0077 max mem: 33408 +Epoch: [32] [ 150/2639] eta: 2:07:10 lr: 1.1670550954553043e-05 loss: 0.0275 (0.0324) time: 3.0480 data: 0.0080 max mem: 33408 +Epoch: [32] [ 160/2639] eta: 2:06:37 lr: 1.166553986421791e-05 loss: 0.0275 (0.0325) time: 3.0476 data: 0.0081 max mem: 33408 +Epoch: [32] [ 170/2639] eta: 2:06:10 lr: 1.1660528534695616e-05 loss: 0.0305 (0.0324) time: 3.0707 data: 0.0084 max mem: 33408 +Epoch: [32] [ 180/2639] eta: 2:05:33 lr: 1.165551696586052e-05 loss: 0.0303 (0.0324) time: 3.0540 data: 0.0084 max mem: 33408 +Epoch: [32] [ 190/2639] eta: 2:04:59 lr: 1.1650505157586858e-05 loss: 0.0282 (0.0321) time: 3.0305 data: 0.0079 max mem: 33408 +Epoch: [32] [ 200/2639] eta: 2:04:25 lr: 1.164549310974872e-05 loss: 0.0275 (0.0321) time: 3.0387 data: 0.0080 max mem: 33408 +Epoch: [32] [ 210/2639] eta: 2:03:49 lr: 1.1640480822220096e-05 loss: 0.0283 (0.0321) time: 3.0225 data: 0.0082 max mem: 33408 +Epoch: [32] [ 220/2639] eta: 2:03:09 lr: 1.1635468294874825e-05 loss: 0.0287 (0.0321) time: 2.9932 data: 0.0080 max mem: 33408 +Epoch: [32] [ 230/2639] eta: 2:02:40 lr: 1.1630455527586641e-05 loss: 0.0284 (0.0321) time: 3.0241 data: 0.0082 max mem: 33408 +Epoch: [32] [ 240/2639] eta: 2:02:10 lr: 1.1625442520229127e-05 loss: 0.0321 (0.0323) time: 3.0618 data: 0.0084 max mem: 33408 +Epoch: [32] [ 250/2639] eta: 2:01:41 lr: 1.1620429272675768e-05 loss: 0.0324 (0.0326) time: 3.0629 data: 0.0080 max mem: 33408 +Epoch: [32] [ 260/2639] eta: 2:01:02 lr: 1.161541578479989e-05 loss: 0.0293 (0.0325) time: 3.0219 data: 0.0079 max mem: 33408 +Epoch: [32] [ 270/2639] eta: 2:00:37 lr: 1.161040205647472e-05 loss: 0.0293 (0.0326) time: 3.0418 data: 0.0081 max mem: 33408 +Epoch: [32] [ 280/2639] eta: 2:00:02 lr: 1.1605388087573333e-05 loss: 0.0288 (0.0324) time: 3.0601 data: 0.0081 max mem: 33408 +Epoch: [32] [ 290/2639] eta: 1:59:29 lr: 1.1600373877968699e-05 loss: 0.0279 (0.0323) time: 3.0132 data: 0.0081 max mem: 33408 +Epoch: [32] [ 300/2639] eta: 1:59:04 lr: 1.159535942753364e-05 loss: 0.0291 (0.0326) time: 3.0700 data: 0.0081 max mem: 33408 +Epoch: [32] [ 310/2639] eta: 1:58:35 lr: 1.1590344736140864e-05 loss: 0.0313 (0.0328) time: 3.0993 data: 0.0079 max mem: 33408 +Epoch: [32] [ 320/2639] eta: 1:58:02 lr: 1.1585329803662936e-05 loss: 0.0316 (0.0327) time: 3.0501 data: 0.0080 max mem: 33408 +Epoch: [32] [ 330/2639] eta: 1:57:29 lr: 1.1580314629972311e-05 loss: 0.0316 (0.0328) time: 3.0190 data: 0.0080 max mem: 33408 +Epoch: [32] [ 340/2639] eta: 1:56:53 lr: 1.1575299214941295e-05 loss: 0.0333 (0.0329) time: 2.9929 data: 0.0079 max mem: 33408 +Epoch: [32] [ 350/2639] eta: 1:56:18 lr: 1.1570283558442085e-05 loss: 0.0295 (0.0327) time: 2.9764 data: 0.0079 max mem: 33408 +Epoch: [32] [ 360/2639] eta: 1:55:47 lr: 1.1565267660346727e-05 loss: 0.0298 (0.0328) time: 3.0114 data: 0.0081 max mem: 33408 +Epoch: [32] [ 370/2639] eta: 1:55:17 lr: 1.1560251520527163e-05 loss: 0.0322 (0.0328) time: 3.0461 data: 0.0083 max mem: 33408 +Epoch: [32] [ 380/2639] eta: 1:54:44 lr: 1.1555235138855175e-05 loss: 0.0318 (0.0329) time: 3.0315 data: 0.0086 max mem: 33408 +Epoch: [32] [ 390/2639] eta: 1:54:10 lr: 1.1550218515202448e-05 loss: 0.0313 (0.0329) time: 3.0025 data: 0.0088 max mem: 33408 +Epoch: [32] [ 400/2639] eta: 1:53:35 lr: 1.1545201649440505e-05 loss: 0.0293 (0.0329) time: 2.9797 data: 0.0086 max mem: 33408 +Epoch: [32] [ 410/2639] eta: 1:53:04 lr: 1.154018454144077e-05 loss: 0.0296 (0.0330) time: 2.9939 data: 0.0083 max mem: 33408 +Epoch: [32] [ 420/2639] eta: 1:52:30 lr: 1.1535167191074504e-05 loss: 0.0320 (0.0332) time: 3.0018 data: 0.0080 max mem: 33408 +Epoch: [32] [ 430/2639] eta: 1:51:57 lr: 1.1530149598212862e-05 loss: 0.0308 (0.0331) time: 2.9850 data: 0.0081 max mem: 33408 +Epoch: [32] [ 440/2639] eta: 1:51:27 lr: 1.1525131762726868e-05 loss: 0.0305 (0.0331) time: 3.0167 data: 0.0086 max mem: 33408 +Epoch: [32] [ 450/2639] eta: 1:50:57 lr: 1.1520113684487393e-05 loss: 0.0298 (0.0331) time: 3.0501 data: 0.0087 max mem: 33408 +Epoch: [32] [ 460/2639] eta: 1:50:22 lr: 1.1515095363365204e-05 loss: 0.0266 (0.0330) time: 3.0053 data: 0.0087 max mem: 33408 +Epoch: [32] [ 470/2639] eta: 1:49:51 lr: 1.1510076799230912e-05 loss: 0.0311 (0.0331) time: 2.9826 data: 0.0086 max mem: 33408 +Epoch: [32] [ 480/2639] eta: 1:49:20 lr: 1.1505057991955018e-05 loss: 0.0342 (0.0333) time: 3.0230 data: 0.0084 max mem: 33408 +Epoch: [32] [ 490/2639] eta: 1:48:51 lr: 1.150003894140787e-05 loss: 0.0298 (0.0332) time: 3.0508 data: 0.0083 max mem: 33408 +Epoch: [32] [ 500/2639] eta: 1:48:20 lr: 1.1495019647459706e-05 loss: 0.0275 (0.0331) time: 3.0486 data: 0.0084 max mem: 33408 +Epoch: [32] [ 510/2639] eta: 1:47:50 lr: 1.1490000109980611e-05 loss: 0.0267 (0.0330) time: 3.0332 data: 0.0080 max mem: 33408 +Epoch: [32] [ 520/2639] eta: 1:47:17 lr: 1.1484980328840558e-05 loss: 0.0272 (0.0329) time: 3.0137 data: 0.0081 max mem: 33408 +Epoch: [32] [ 530/2639] eta: 1:46:43 lr: 1.1479960303909364e-05 loss: 0.0335 (0.0331) time: 2.9680 data: 0.0088 max mem: 33408 +Epoch: [32] [ 540/2639] eta: 1:46:13 lr: 1.147494003505674e-05 loss: 0.0363 (0.0331) time: 2.9922 data: 0.0086 max mem: 33408 +Epoch: [32] [ 550/2639] eta: 1:45:43 lr: 1.1469919522152238e-05 loss: 0.0289 (0.0330) time: 3.0453 data: 0.0082 max mem: 33408 +Epoch: [32] [ 560/2639] eta: 1:45:12 lr: 1.1464898765065297e-05 loss: 0.0277 (0.0330) time: 3.0279 data: 0.0080 max mem: 33408 +Epoch: [32] [ 570/2639] eta: 1:44:41 lr: 1.1459877763665207e-05 loss: 0.0286 (0.0330) time: 3.0116 data: 0.0080 max mem: 33408 +Epoch: [32] [ 580/2639] eta: 1:44:12 lr: 1.1454856517821138e-05 loss: 0.0298 (0.0330) time: 3.0495 data: 0.0082 max mem: 33408 +Epoch: [32] [ 590/2639] eta: 1:43:44 lr: 1.1449835027402115e-05 loss: 0.0274 (0.0330) time: 3.0873 data: 0.0082 max mem: 33408 +Epoch: [32] [ 600/2639] eta: 1:43:14 lr: 1.144481329227704e-05 loss: 0.0299 (0.0330) time: 3.0721 data: 0.0082 max mem: 33408 +Epoch: [32] [ 610/2639] eta: 1:42:41 lr: 1.1439791312314663e-05 loss: 0.0265 (0.0329) time: 3.0151 data: 0.0083 max mem: 33408 +Epoch: [32] [ 620/2639] eta: 1:42:12 lr: 1.1434769087383625e-05 loss: 0.0295 (0.0329) time: 3.0243 data: 0.0080 max mem: 33408 +Epoch: [32] [ 630/2639] eta: 1:41:41 lr: 1.1429746617352406e-05 loss: 0.0306 (0.0329) time: 3.0406 data: 0.0082 max mem: 33408 +Epoch: [32] [ 640/2639] eta: 1:41:10 lr: 1.1424723902089374e-05 loss: 0.0306 (0.0330) time: 3.0107 data: 0.0082 max mem: 33408 +Epoch: [32] [ 650/2639] eta: 1:40:41 lr: 1.1419700941462743e-05 loss: 0.0280 (0.0329) time: 3.0539 data: 0.0084 max mem: 33408 +Epoch: [32] [ 660/2639] eta: 1:40:09 lr: 1.1414677735340611e-05 loss: 0.0303 (0.0330) time: 3.0374 data: 0.0085 max mem: 33408 +Epoch: [32] [ 670/2639] eta: 1:39:38 lr: 1.1409654283590914e-05 loss: 0.0306 (0.0329) time: 2.9974 data: 0.0081 max mem: 33408 +Epoch: [32] [ 680/2639] eta: 1:39:07 lr: 1.140463058608148e-05 loss: 0.0289 (0.0329) time: 3.0213 data: 0.0079 max mem: 33408 +Epoch: [32] [ 690/2639] eta: 1:38:38 lr: 1.1399606642679992e-05 loss: 0.0289 (0.0329) time: 3.0490 data: 0.0078 max mem: 33408 +Epoch: [32] [ 700/2639] eta: 1:38:07 lr: 1.1394582453253984e-05 loss: 0.0291 (0.0329) time: 3.0498 data: 0.0079 max mem: 33408 +Epoch: [32] [ 710/2639] eta: 1:37:38 lr: 1.1389558017670873e-05 loss: 0.0319 (0.0329) time: 3.0494 data: 0.0078 max mem: 33408 +Epoch: [32] [ 720/2639] eta: 1:37:08 lr: 1.138453333579792e-05 loss: 0.0305 (0.0328) time: 3.0719 data: 0.0080 max mem: 33408 +Epoch: [32] [ 730/2639] eta: 1:36:37 lr: 1.1379508407502274e-05 loss: 0.0318 (0.0328) time: 3.0240 data: 0.0081 max mem: 33408 +Epoch: [32] [ 740/2639] eta: 1:36:06 lr: 1.1374483232650917e-05 loss: 0.0335 (0.0329) time: 3.0060 data: 0.0081 max mem: 33408 +Epoch: [32] [ 750/2639] eta: 1:35:37 lr: 1.1369457811110725e-05 loss: 0.0326 (0.0328) time: 3.0581 data: 0.0081 max mem: 33408 +Epoch: [32] [ 760/2639] eta: 1:35:06 lr: 1.1364432142748408e-05 loss: 0.0300 (0.0328) time: 3.0446 data: 0.0079 max mem: 33408 +Epoch: [32] [ 770/2639] eta: 1:34:36 lr: 1.1359406227430564e-05 loss: 0.0323 (0.0329) time: 3.0439 data: 0.0078 max mem: 33408 +Epoch: [32] [ 780/2639] eta: 1:34:05 lr: 1.1354380065023629e-05 loss: 0.0345 (0.0329) time: 3.0452 data: 0.0076 max mem: 33408 +Epoch: [32] [ 790/2639] eta: 1:33:36 lr: 1.1349353655393923e-05 loss: 0.0335 (0.0329) time: 3.0335 data: 0.0076 max mem: 33408 +Epoch: [32] [ 800/2639] eta: 1:33:05 lr: 1.1344326998407612e-05 loss: 0.0291 (0.0329) time: 3.0379 data: 0.0077 max mem: 33408 +Epoch: [32] [ 810/2639] eta: 1:32:33 lr: 1.1339300093930736e-05 loss: 0.0306 (0.0329) time: 3.0021 data: 0.0080 max mem: 33408 +Epoch: [32] [ 820/2639] eta: 1:32:02 lr: 1.1334272941829183e-05 loss: 0.0312 (0.0330) time: 2.9857 data: 0.0080 max mem: 33408 +Epoch: [32] [ 830/2639] eta: 1:31:31 lr: 1.1329245541968715e-05 loss: 0.0312 (0.0330) time: 2.9989 data: 0.0077 max mem: 33408 +Epoch: [32] [ 840/2639] eta: 1:30:59 lr: 1.1324217894214943e-05 loss: 0.0344 (0.0330) time: 2.9939 data: 0.0078 max mem: 33408 +Epoch: [32] [ 850/2639] eta: 1:30:29 lr: 1.1319189998433354e-05 loss: 0.0286 (0.0330) time: 3.0106 data: 0.0081 max mem: 33408 +Epoch: [32] [ 860/2639] eta: 1:29:59 lr: 1.1314161854489278e-05 loss: 0.0298 (0.0330) time: 3.0370 data: 0.0078 max mem: 33408 +Epoch: [32] [ 870/2639] eta: 1:29:27 lr: 1.1309133462247921e-05 loss: 0.0298 (0.0329) time: 3.0108 data: 0.0078 max mem: 33408 +Epoch: [32] [ 880/2639] eta: 1:28:57 lr: 1.1304104821574334e-05 loss: 0.0281 (0.0329) time: 3.0023 data: 0.0084 max mem: 33408 +Epoch: [32] [ 890/2639] eta: 1:28:26 lr: 1.1299075932333446e-05 loss: 0.0338 (0.0331) time: 3.0230 data: 0.0086 max mem: 33408 +Epoch: [32] [ 900/2639] eta: 1:27:56 lr: 1.1294046794390024e-05 loss: 0.0349 (0.0331) time: 3.0273 data: 0.0079 max mem: 33408 +Epoch: [32] [ 910/2639] eta: 1:27:25 lr: 1.128901740760872e-05 loss: 0.0278 (0.0330) time: 3.0139 data: 0.0078 max mem: 33408 +Epoch: [32] [ 920/2639] eta: 1:26:53 lr: 1.128398777185402e-05 loss: 0.0265 (0.0330) time: 2.9840 data: 0.0081 max mem: 33408 +Epoch: [32] [ 930/2639] eta: 1:26:22 lr: 1.1278957886990282e-05 loss: 0.0281 (0.0330) time: 2.9655 data: 0.0077 max mem: 33408 +Epoch: [32] [ 940/2639] eta: 1:25:51 lr: 1.1273927752881733e-05 loss: 0.0302 (0.0330) time: 2.9922 data: 0.0076 max mem: 33408 +Epoch: [32] [ 950/2639] eta: 1:25:19 lr: 1.126889736939243e-05 loss: 0.0282 (0.0330) time: 2.9818 data: 0.0078 max mem: 33408 +Epoch: [32] [ 960/2639] eta: 1:24:49 lr: 1.1263866736386322e-05 loss: 0.0326 (0.0330) time: 2.9937 data: 0.0080 max mem: 33408 +Epoch: [32] [ 970/2639] eta: 1:24:19 lr: 1.1258835853727186e-05 loss: 0.0351 (0.0331) time: 3.0338 data: 0.0082 max mem: 33408 +Epoch: [32] [ 980/2639] eta: 1:23:48 lr: 1.1253804721278682e-05 loss: 0.0338 (0.0330) time: 3.0306 data: 0.0080 max mem: 33408 +Epoch: [32] [ 990/2639] eta: 1:23:18 lr: 1.1248773338904305e-05 loss: 0.0258 (0.0330) time: 3.0250 data: 0.0079 max mem: 33408 +Epoch: [32] [1000/2639] eta: 1:22:48 lr: 1.1243741706467432e-05 loss: 0.0260 (0.0330) time: 3.0479 data: 0.0079 max mem: 33408 +Epoch: [32] [1010/2639] eta: 1:22:18 lr: 1.123870982383127e-05 loss: 0.0267 (0.0329) time: 3.0408 data: 0.0077 max mem: 33408 +Epoch: [32] [1020/2639] eta: 1:21:48 lr: 1.1233677690858912e-05 loss: 0.0281 (0.0329) time: 3.0327 data: 0.0079 max mem: 33408 +Epoch: [32] [1030/2639] eta: 1:21:17 lr: 1.1228645307413279e-05 loss: 0.0298 (0.0329) time: 3.0280 data: 0.0087 max mem: 33408 +Epoch: [32] [1040/2639] eta: 1:20:46 lr: 1.1223612673357178e-05 loss: 0.0341 (0.0330) time: 3.0103 data: 0.0085 max mem: 33408 +Epoch: [32] [1050/2639] eta: 1:20:16 lr: 1.121857978855324e-05 loss: 0.0341 (0.0330) time: 3.0360 data: 0.0077 max mem: 33408 +Epoch: [32] [1060/2639] eta: 1:19:46 lr: 1.1213546652863988e-05 loss: 0.0322 (0.0330) time: 3.0381 data: 0.0077 max mem: 33408 +Epoch: [32] [1070/2639] eta: 1:19:16 lr: 1.1208513266151767e-05 loss: 0.0308 (0.0330) time: 3.0274 data: 0.0076 max mem: 33408 +Epoch: [32] [1080/2639] eta: 1:18:46 lr: 1.1203479628278806e-05 loss: 0.0313 (0.0331) time: 3.0464 data: 0.0077 max mem: 33408 +Epoch: [32] [1090/2639] eta: 1:18:15 lr: 1.1198445739107163e-05 loss: 0.0309 (0.0330) time: 3.0364 data: 0.0079 max mem: 33408 +Epoch: [32] [1100/2639] eta: 1:17:45 lr: 1.1193411598498781e-05 loss: 0.0303 (0.0330) time: 3.0159 data: 0.0081 max mem: 33408 +Epoch: [32] [1110/2639] eta: 1:17:15 lr: 1.1188377206315428e-05 loss: 0.0327 (0.0330) time: 3.0538 data: 0.0082 max mem: 33408 +Epoch: [32] [1120/2639] eta: 1:16:45 lr: 1.1183342562418754e-05 loss: 0.0318 (0.0330) time: 3.0541 data: 0.0083 max mem: 33408 +Epoch: [32] [1130/2639] eta: 1:16:13 lr: 1.117830766667024e-05 loss: 0.0314 (0.0330) time: 2.9852 data: 0.0080 max mem: 33408 +Epoch: [32] [1140/2639] eta: 1:15:42 lr: 1.1173272518931239e-05 loss: 0.0303 (0.0330) time: 2.9682 data: 0.0081 max mem: 33408 +Epoch: [32] [1150/2639] eta: 1:15:12 lr: 1.1168237119062946e-05 loss: 0.0331 (0.0330) time: 2.9930 data: 0.0082 max mem: 33408 +Epoch: [32] [1160/2639] eta: 1:14:42 lr: 1.1163201466926419e-05 loss: 0.0325 (0.0330) time: 3.0579 data: 0.0077 max mem: 33408 +Epoch: [32] [1170/2639] eta: 1:14:12 lr: 1.1158165562382572e-05 loss: 0.0305 (0.0330) time: 3.0674 data: 0.0073 max mem: 33408 +Epoch: [32] [1180/2639] eta: 1:13:41 lr: 1.1153129405292154e-05 loss: 0.0323 (0.0330) time: 2.9866 data: 0.0075 max mem: 33408 +Epoch: [32] [1190/2639] eta: 1:13:11 lr: 1.1148092995515792e-05 loss: 0.0333 (0.0331) time: 3.0048 data: 0.0081 max mem: 33408 +Epoch: [32] [1200/2639] eta: 1:12:41 lr: 1.1143056332913943e-05 loss: 0.0336 (0.0331) time: 3.0693 data: 0.0078 max mem: 33408 +Epoch: [32] [1210/2639] eta: 1:12:11 lr: 1.1138019417346943e-05 loss: 0.0350 (0.0331) time: 3.0695 data: 0.0077 max mem: 33408 +Epoch: [32] [1220/2639] eta: 1:11:41 lr: 1.1132982248674947e-05 loss: 0.0346 (0.0331) time: 3.0382 data: 0.0077 max mem: 33408 +Epoch: [32] [1230/2639] eta: 1:11:11 lr: 1.1127944826757997e-05 loss: 0.0313 (0.0331) time: 3.0402 data: 0.0077 max mem: 33408 +Epoch: [32] [1240/2639] eta: 1:10:40 lr: 1.1122907151455958e-05 loss: 0.0313 (0.0332) time: 3.0453 data: 0.0075 max mem: 33408 +Epoch: [32] [1250/2639] eta: 1:10:10 lr: 1.1117869222628572e-05 loss: 0.0315 (0.0332) time: 3.0557 data: 0.0072 max mem: 33408 +Epoch: [32] [1260/2639] eta: 1:09:40 lr: 1.1112831040135409e-05 loss: 0.0351 (0.0332) time: 3.0590 data: 0.0074 max mem: 33408 +Epoch: [32] [1270/2639] eta: 1:09:10 lr: 1.1107792603835914e-05 loss: 0.0315 (0.0332) time: 3.0599 data: 0.0075 max mem: 33408 +Epoch: [32] [1280/2639] eta: 1:08:40 lr: 1.1102753913589359e-05 loss: 0.0291 (0.0332) time: 3.0398 data: 0.0075 max mem: 33408 +Epoch: [32] [1290/2639] eta: 1:08:09 lr: 1.1097714969254891e-05 loss: 0.0320 (0.0332) time: 2.9951 data: 0.0078 max mem: 33408 +Epoch: [32] [1300/2639] eta: 1:07:38 lr: 1.1092675770691485e-05 loss: 0.0358 (0.0332) time: 2.9736 data: 0.0086 max mem: 33408 +Epoch: [32] [1310/2639] eta: 1:07:08 lr: 1.1087636317757988e-05 loss: 0.0331 (0.0332) time: 2.9981 data: 0.0090 max mem: 33408 +Epoch: [32] [1320/2639] eta: 1:06:38 lr: 1.1082596610313078e-05 loss: 0.0328 (0.0333) time: 3.0625 data: 0.0081 max mem: 33408 +Epoch: [32] [1330/2639] eta: 1:06:07 lr: 1.1077556648215299e-05 loss: 0.0326 (0.0333) time: 3.0490 data: 0.0076 max mem: 33408 +Epoch: [32] [1340/2639] eta: 1:05:38 lr: 1.107251643132303e-05 loss: 0.0330 (0.0333) time: 3.0403 data: 0.0075 max mem: 33408 +Epoch: [32] [1350/2639] eta: 1:05:07 lr: 1.1067475959494518e-05 loss: 0.0352 (0.0334) time: 3.0620 data: 0.0074 max mem: 33408 +Epoch: [32] [1360/2639] eta: 1:04:37 lr: 1.1062435232587836e-05 loss: 0.0350 (0.0334) time: 3.0362 data: 0.0073 max mem: 33408 +Epoch: [32] [1370/2639] eta: 1:04:07 lr: 1.1057394250460931e-05 loss: 0.0295 (0.0333) time: 3.0208 data: 0.0075 max mem: 33408 +Epoch: [32] [1380/2639] eta: 1:03:37 lr: 1.1052353012971575e-05 loss: 0.0295 (0.0333) time: 3.0500 data: 0.0080 max mem: 33408 +Epoch: [32] [1390/2639] eta: 1:03:06 lr: 1.1047311519977411e-05 loss: 0.0313 (0.0333) time: 3.0625 data: 0.0079 max mem: 33408 +Epoch: [32] [1400/2639] eta: 1:02:36 lr: 1.104226977133591e-05 loss: 0.0305 (0.0333) time: 3.0557 data: 0.0081 max mem: 33408 +Epoch: [32] [1410/2639] eta: 1:02:07 lr: 1.1037227766904403e-05 loss: 0.0317 (0.0333) time: 3.0731 data: 0.0082 max mem: 33408 +Epoch: [32] [1420/2639] eta: 1:01:36 lr: 1.1032185506540076e-05 loss: 0.0304 (0.0333) time: 3.0280 data: 0.0080 max mem: 33408 +Epoch: [32] [1430/2639] eta: 1:01:05 lr: 1.102714299009994e-05 loss: 0.0281 (0.0333) time: 2.9911 data: 0.0081 max mem: 33408 +Epoch: [32] [1440/2639] eta: 1:00:35 lr: 1.1022100217440882e-05 loss: 0.0323 (0.0333) time: 3.0411 data: 0.0078 max mem: 33408 +Epoch: [32] [1450/2639] eta: 1:00:04 lr: 1.1017057188419603e-05 loss: 0.0324 (0.0333) time: 3.0234 data: 0.0079 max mem: 33408 +Epoch: [32] [1460/2639] eta: 0:59:35 lr: 1.1012013902892686e-05 loss: 0.0318 (0.0333) time: 3.0460 data: 0.0079 max mem: 33408 +Epoch: [32] [1470/2639] eta: 0:59:04 lr: 1.1006970360716529e-05 loss: 0.0302 (0.0333) time: 3.0416 data: 0.0080 max mem: 33408 +Epoch: [32] [1480/2639] eta: 0:58:33 lr: 1.1001926561747404e-05 loss: 0.0313 (0.0333) time: 2.9823 data: 0.0080 max mem: 33408 +Epoch: [32] [1490/2639] eta: 0:58:03 lr: 1.0996882505841407e-05 loss: 0.0315 (0.0333) time: 2.9957 data: 0.0079 max mem: 33408 +Epoch: [32] [1500/2639] eta: 0:57:33 lr: 1.0991838192854495e-05 loss: 0.0287 (0.0333) time: 3.0179 data: 0.0079 max mem: 33408 +Epoch: [32] [1510/2639] eta: 0:57:02 lr: 1.098679362264246e-05 loss: 0.0287 (0.0333) time: 3.0379 data: 0.0081 max mem: 33408 +Epoch: [32] [1520/2639] eta: 0:56:32 lr: 1.0981748795060952e-05 loss: 0.0331 (0.0333) time: 3.0179 data: 0.0083 max mem: 33408 +Epoch: [32] [1530/2639] eta: 0:56:01 lr: 1.097670370996545e-05 loss: 0.0345 (0.0334) time: 2.9932 data: 0.0085 max mem: 33408 +Epoch: [32] [1540/2639] eta: 0:55:31 lr: 1.0971658367211296e-05 loss: 0.0317 (0.0334) time: 3.0240 data: 0.0085 max mem: 33408 +Epoch: [32] [1550/2639] eta: 0:55:00 lr: 1.0966612766653656e-05 loss: 0.0314 (0.0334) time: 3.0333 data: 0.0080 max mem: 33408 +Epoch: [32] [1560/2639] eta: 0:54:29 lr: 1.0961566908147568e-05 loss: 0.0283 (0.0333) time: 2.9642 data: 0.0078 max mem: 33408 +Epoch: [32] [1570/2639] eta: 0:53:59 lr: 1.0956520791547884e-05 loss: 0.0283 (0.0334) time: 2.9452 data: 0.0077 max mem: 33408 +Epoch: [32] [1580/2639] eta: 0:53:29 lr: 1.0951474416709323e-05 loss: 0.0325 (0.0333) time: 3.0116 data: 0.0074 max mem: 33408 +Epoch: [32] [1590/2639] eta: 0:52:58 lr: 1.0946427783486433e-05 loss: 0.0296 (0.0333) time: 3.0283 data: 0.0077 max mem: 33408 +Epoch: [32] [1600/2639] eta: 0:52:28 lr: 1.094138089173362e-05 loss: 0.0300 (0.0333) time: 2.9997 data: 0.0076 max mem: 33408 +Epoch: [32] [1610/2639] eta: 0:51:57 lr: 1.0936333741305117e-05 loss: 0.0300 (0.0334) time: 3.0102 data: 0.0074 max mem: 33408 +Epoch: [32] [1620/2639] eta: 0:51:27 lr: 1.0931286332055015e-05 loss: 0.0289 (0.0333) time: 3.0408 data: 0.0077 max mem: 33408 +Epoch: [32] [1630/2639] eta: 0:50:57 lr: 1.0926238663837232e-05 loss: 0.0278 (0.0333) time: 3.0448 data: 0.0080 max mem: 33408 +Epoch: [32] [1640/2639] eta: 0:50:27 lr: 1.0921190736505548e-05 loss: 0.0280 (0.0333) time: 3.0804 data: 0.0079 max mem: 33408 +Epoch: [32] [1650/2639] eta: 0:49:57 lr: 1.0916142549913564e-05 loss: 0.0299 (0.0333) time: 3.0989 data: 0.0079 max mem: 33408 +Epoch: [32] [1660/2639] eta: 0:49:27 lr: 1.091109410391474e-05 loss: 0.0326 (0.0334) time: 3.0451 data: 0.0081 max mem: 33408 +Epoch: [32] [1670/2639] eta: 0:48:56 lr: 1.0906045398362377e-05 loss: 0.0305 (0.0334) time: 3.0355 data: 0.0077 max mem: 33408 +Epoch: [32] [1680/2639] eta: 0:48:26 lr: 1.09009964331096e-05 loss: 0.0305 (0.0334) time: 3.0260 data: 0.0074 max mem: 33408 +Epoch: [32] [1690/2639] eta: 0:47:56 lr: 1.0895947208009398e-05 loss: 0.0282 (0.0334) time: 3.0143 data: 0.0076 max mem: 33408 +Epoch: [32] [1700/2639] eta: 0:47:25 lr: 1.089089772291458e-05 loss: 0.0282 (0.0334) time: 2.9995 data: 0.0077 max mem: 33408 +Epoch: [32] [1710/2639] eta: 0:46:55 lr: 1.0885847977677817e-05 loss: 0.0310 (0.0334) time: 2.9934 data: 0.0079 max mem: 33408 +Epoch: [32] [1720/2639] eta: 0:46:25 lr: 1.0880797972151598e-05 loss: 0.0310 (0.0334) time: 3.0475 data: 0.0079 max mem: 33408 +Epoch: [32] [1730/2639] eta: 0:45:54 lr: 1.0875747706188277e-05 loss: 0.0318 (0.0334) time: 3.0343 data: 0.0074 max mem: 33408 +Epoch: [32] [1740/2639] eta: 0:45:24 lr: 1.0870697179640022e-05 loss: 0.0318 (0.0334) time: 2.9987 data: 0.0080 max mem: 33408 +Epoch: [32] [1750/2639] eta: 0:44:53 lr: 1.0865646392358865e-05 loss: 0.0294 (0.0334) time: 3.0179 data: 0.0081 max mem: 33408 +Epoch: [32] [1760/2639] eta: 0:44:23 lr: 1.0860595344196656e-05 loss: 0.0254 (0.0334) time: 2.9973 data: 0.0082 max mem: 33408 +Epoch: [32] [1770/2639] eta: 0:43:53 lr: 1.0855544035005104e-05 loss: 0.0283 (0.0334) time: 3.0189 data: 0.0083 max mem: 33408 +Epoch: [32] [1780/2639] eta: 0:43:22 lr: 1.0850492464635736e-05 loss: 0.0284 (0.0334) time: 3.0668 data: 0.0080 max mem: 33408 +Epoch: [32] [1790/2639] eta: 0:42:52 lr: 1.0845440632939943e-05 loss: 0.0316 (0.0334) time: 3.0660 data: 0.0082 max mem: 33408 +Epoch: [32] [1800/2639] eta: 0:42:22 lr: 1.0840388539768926e-05 loss: 0.0302 (0.0334) time: 3.0209 data: 0.0081 max mem: 33408 +Epoch: [32] [1810/2639] eta: 0:41:52 lr: 1.0835336184973752e-05 loss: 0.0274 (0.0334) time: 3.0088 data: 0.0083 max mem: 33408 +Epoch: [32] [1820/2639] eta: 0:41:21 lr: 1.0830283568405298e-05 loss: 0.0290 (0.0334) time: 3.0543 data: 0.0086 max mem: 33408 +Epoch: [32] [1830/2639] eta: 0:40:51 lr: 1.082523068991431e-05 loss: 0.0329 (0.0334) time: 3.0380 data: 0.0082 max mem: 33408 +Epoch: [32] [1840/2639] eta: 0:40:20 lr: 1.082017754935134e-05 loss: 0.0316 (0.0334) time: 2.9785 data: 0.0081 max mem: 33408 +Epoch: [32] [1850/2639] eta: 0:39:50 lr: 1.0815124146566803e-05 loss: 0.0318 (0.0334) time: 2.9755 data: 0.0084 max mem: 33408 +Epoch: [32] [1860/2639] eta: 0:39:20 lr: 1.0810070481410931e-05 loss: 0.0367 (0.0334) time: 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0.0328 (0.0335) time: 3.0174 data: 0.0083 max mem: 33408 +Epoch: [32] [1950/2639] eta: 0:34:47 lr: 1.0764575663506849e-05 loss: 0.0329 (0.0335) time: 3.0303 data: 0.0081 max mem: 33408 +Epoch: [32] [1960/2639] eta: 0:34:16 lr: 1.0759519366364841e-05 loss: 0.0332 (0.0335) time: 3.0096 data: 0.0082 max mem: 33408 +Epoch: [32] [1970/2639] eta: 0:33:46 lr: 1.0754462805193305e-05 loss: 0.0323 (0.0335) time: 3.0189 data: 0.0086 max mem: 33408 +Epoch: [32] [1980/2639] eta: 0:33:16 lr: 1.0749405979840515e-05 loss: 0.0332 (0.0335) time: 3.0369 data: 0.0083 max mem: 33408 +Epoch: [32] [1990/2639] eta: 0:32:46 lr: 1.0744348890154554e-05 loss: 0.0321 (0.0335) time: 3.0363 data: 0.0078 max mem: 33408 +Epoch: [32] [2000/2639] eta: 0:32:15 lr: 1.0739291535983365e-05 loss: 0.0313 (0.0336) time: 3.0299 data: 0.0079 max mem: 33408 +Epoch: [32] [2010/2639] eta: 0:31:45 lr: 1.0734233917174699e-05 loss: 0.0326 (0.0336) time: 3.0501 data: 0.0082 max mem: 33408 +Epoch: [32] [2020/2639] eta: 0:31:15 lr: 1.0729176033576159e-05 loss: 0.0306 (0.0336) time: 3.0202 data: 0.0081 max mem: 33408 +Epoch: [32] [2030/2639] eta: 0:30:44 lr: 1.0724117885035164e-05 loss: 0.0288 (0.0336) time: 2.9711 data: 0.0080 max mem: 33408 +Epoch: [32] [2040/2639] eta: 0:30:14 lr: 1.0719059471398985e-05 loss: 0.0273 (0.0336) time: 2.9690 data: 0.0079 max mem: 33408 +Epoch: [32] [2050/2639] eta: 0:29:43 lr: 1.0714000792514701e-05 loss: 0.0291 (0.0336) time: 3.0020 data: 0.0078 max mem: 33408 +Epoch: [32] [2060/2639] eta: 0:29:13 lr: 1.0708941848229246e-05 loss: 0.0300 (0.0336) time: 3.0800 data: 0.0082 max mem: 33408 +Epoch: [32] [2070/2639] eta: 0:28:43 lr: 1.0703882638389364e-05 loss: 0.0298 (0.0336) time: 3.0770 data: 0.0081 max mem: 33408 +Epoch: [32] [2080/2639] eta: 0:28:13 lr: 1.0698823162841648e-05 loss: 0.0351 (0.0336) time: 3.0503 data: 0.0079 max mem: 33408 +Epoch: [32] [2090/2639] eta: 0:27:42 lr: 1.0693763421432505e-05 loss: 0.0375 (0.0336) time: 3.0213 data: 0.0077 max mem: 33408 +Epoch: [32] [2100/2639] eta: 0:27:12 lr: 1.0688703414008193e-05 loss: 0.0335 (0.0336) time: 3.0234 data: 0.0077 max mem: 33408 +Epoch: [32] [2110/2639] eta: 0:26:42 lr: 1.0683643140414772e-05 loss: 0.0304 (0.0336) time: 3.0230 data: 0.0079 max mem: 33408 +Epoch: [32] [2120/2639] eta: 0:26:11 lr: 1.0678582600498167e-05 loss: 0.0304 (0.0336) time: 2.9721 data: 0.0080 max mem: 33408 +Epoch: [32] [2130/2639] eta: 0:25:41 lr: 1.0673521794104097e-05 loss: 0.0301 (0.0336) time: 2.9989 data: 0.0078 max mem: 33408 +Epoch: [32] [2140/2639] eta: 0:25:11 lr: 1.0668460721078142e-05 loss: 0.0351 (0.0336) time: 3.0341 data: 0.0079 max mem: 33408 +Epoch: [32] [2150/2639] eta: 0:24:41 lr: 1.066339938126568e-05 loss: 0.0345 (0.0337) time: 3.0224 data: 0.0081 max mem: 33408 +Epoch: [32] [2160/2639] eta: 0:24:10 lr: 1.0658337774511943e-05 loss: 0.0310 (0.0337) time: 2.9742 data: 0.0079 max mem: 33408 +Epoch: [32] [2170/2639] eta: 0:23:40 lr: 1.0653275900661988e-05 loss: 0.0310 (0.0337) time: 2.9751 data: 0.0084 max mem: 33408 +Epoch: [32] [2180/2639] eta: 0:23:09 lr: 1.0648213759560683e-05 loss: 0.0323 (0.0337) time: 3.0061 data: 0.0085 max mem: 33408 +Epoch: [32] [2190/2639] eta: 0:22:39 lr: 1.0643151351052745e-05 loss: 0.0359 (0.0337) time: 3.0007 data: 0.0083 max mem: 33408 +Epoch: [32] [2200/2639] eta: 0:22:09 lr: 1.06380886749827e-05 loss: 0.0359 (0.0337) time: 2.9862 data: 0.0083 max mem: 33408 +Epoch: [32] [2210/2639] eta: 0:21:38 lr: 1.063302573119492e-05 loss: 0.0331 (0.0337) time: 3.0140 data: 0.0087 max mem: 33408 +Epoch: [32] [2220/2639] eta: 0:21:08 lr: 1.0627962519533587e-05 loss: 0.0324 (0.0337) time: 3.0501 data: 0.0087 max mem: 33408 +Epoch: [32] [2230/2639] eta: 0:20:38 lr: 1.0622899039842724e-05 loss: 0.0339 (0.0337) time: 3.0750 data: 0.0082 max mem: 33408 +Epoch: [32] [2240/2639] eta: 0:20:08 lr: 1.0617835291966163e-05 loss: 0.0381 (0.0337) time: 3.0577 data: 0.0080 max mem: 33408 +Epoch: [32] [2250/2639] eta: 0:19:37 lr: 1.0612771275747588e-05 loss: 0.0323 (0.0338) time: 3.0039 data: 0.0079 max mem: 33408 +Epoch: [32] [2260/2639] eta: 0:19:07 lr: 1.060770699103048e-05 loss: 0.0305 (0.0337) time: 2.9942 data: 0.0080 max mem: 33408 +Epoch: [32] [2270/2639] eta: 0:18:37 lr: 1.0602642437658169e-05 loss: 0.0303 (0.0337) time: 2.9937 data: 0.0083 max mem: 33408 +Epoch: [32] [2280/2639] eta: 0:18:06 lr: 1.0597577615473794e-05 loss: 0.0296 (0.0337) time: 3.0223 data: 0.0081 max mem: 33408 +Epoch: [32] [2290/2639] eta: 0:17:36 lr: 1.0592512524320337e-05 loss: 0.0292 (0.0337) time: 3.0236 data: 0.0080 max mem: 33408 +Epoch: [32] [2300/2639] eta: 0:17:06 lr: 1.0587447164040578e-05 loss: 0.0324 (0.0337) time: 2.9947 data: 0.0084 max mem: 33408 +Epoch: [32] [2310/2639] eta: 0:16:36 lr: 1.0582381534477153e-05 loss: 0.0313 (0.0337) time: 3.0234 data: 0.0085 max mem: 33408 +Epoch: [32] [2320/2639] eta: 0:16:05 lr: 1.0577315635472495e-05 loss: 0.0313 (0.0337) time: 3.0218 data: 0.0082 max mem: 33408 +Epoch: [32] [2330/2639] eta: 0:15:35 lr: 1.0572249466868881e-05 loss: 0.0371 (0.0337) time: 3.0310 data: 0.0079 max mem: 33408 +Epoch: [32] [2340/2639] eta: 0:15:05 lr: 1.0567183028508396e-05 loss: 0.0338 (0.0337) time: 3.0165 data: 0.0078 max mem: 33408 +Epoch: [32] [2350/2639] eta: 0:14:34 lr: 1.0562116320232963e-05 loss: 0.0303 (0.0337) time: 2.9507 data: 0.0077 max mem: 33408 +Epoch: [32] [2360/2639] eta: 0:14:04 lr: 1.055704934188431e-05 loss: 0.0265 (0.0337) time: 2.9898 data: 0.0080 max mem: 33408 +Epoch: [32] [2370/2639] eta: 0:13:34 lr: 1.0551982093304012e-05 loss: 0.0271 (0.0337) time: 3.0643 data: 0.0081 max mem: 33408 +Epoch: [32] [2380/2639] eta: 0:13:03 lr: 1.0546914574333438e-05 loss: 0.0271 (0.0337) time: 3.0175 data: 0.0079 max mem: 33408 +Epoch: [32] [2390/2639] eta: 0:12:33 lr: 1.0541846784813809e-05 loss: 0.0311 (0.0337) time: 2.9809 data: 0.0078 max mem: 33408 +Epoch: [32] [2400/2639] eta: 0:12:03 lr: 1.0536778724586137e-05 loss: 0.0308 (0.0337) time: 3.0108 data: 0.0081 max mem: 33408 +Epoch: [32] [2410/2639] eta: 0:11:33 lr: 1.053171039349128e-05 loss: 0.0282 (0.0337) time: 3.0600 data: 0.0082 max mem: 33408 +Epoch: [32] [2420/2639] eta: 0:11:02 lr: 1.0526641791369912e-05 loss: 0.0287 (0.0337) time: 3.0804 data: 0.0079 max mem: 33408 +Epoch: [32] [2430/2639] eta: 0:10:32 lr: 1.0521572918062517e-05 loss: 0.0297 (0.0337) time: 3.0157 data: 0.0080 max mem: 33408 +Epoch: [32] [2440/2639] eta: 0:10:02 lr: 1.0516503773409416e-05 loss: 0.0337 (0.0337) time: 2.9700 data: 0.0079 max mem: 33408 +Epoch: [32] [2450/2639] eta: 0:09:32 lr: 1.051143435725073e-05 loss: 0.0312 (0.0337) time: 2.9730 data: 0.0080 max mem: 33408 +Epoch: [32] [2460/2639] eta: 0:09:01 lr: 1.0506364669426423e-05 loss: 0.0307 (0.0337) time: 3.0410 data: 0.0080 max mem: 33408 +Epoch: [32] [2470/2639] eta: 0:08:31 lr: 1.0501294709776258e-05 loss: 0.0288 (0.0337) time: 3.0463 data: 0.0082 max mem: 33408 +Epoch: [32] [2480/2639] eta: 0:08:01 lr: 1.0496224478139836e-05 loss: 0.0278 (0.0337) time: 3.0190 data: 0.0085 max mem: 33408 +Epoch: [32] [2490/2639] eta: 0:07:31 lr: 1.049115397435656e-05 loss: 0.0290 (0.0337) time: 3.0550 data: 0.0079 max mem: 33408 +Epoch: [32] [2500/2639] eta: 0:07:00 lr: 1.0486083198265669e-05 loss: 0.0313 (0.0337) time: 3.0514 data: 0.0075 max mem: 33408 +Epoch: [32] [2510/2639] eta: 0:06:30 lr: 1.0481012149706202e-05 loss: 0.0262 (0.0337) time: 3.0168 data: 0.0079 max mem: 33408 +Epoch: [32] [2520/2639] eta: 0:06:00 lr: 1.0475940828517034e-05 loss: 0.0327 (0.0337) time: 3.0346 data: 0.0079 max mem: 33408 +Epoch: [32] [2530/2639] eta: 0:05:29 lr: 1.0470869234536844e-05 loss: 0.0352 (0.0337) time: 3.0866 data: 0.0077 max mem: 33408 +Epoch: [32] [2540/2639] eta: 0:04:59 lr: 1.0465797367604141e-05 loss: 0.0316 (0.0337) time: 3.0709 data: 0.0078 max mem: 33408 +Epoch: [32] [2550/2639] eta: 0:04:29 lr: 1.0460725227557236e-05 loss: 0.0285 (0.0337) time: 3.0492 data: 0.0080 max mem: 33408 +Epoch: [32] [2560/2639] eta: 0:03:59 lr: 1.0455652814234277e-05 loss: 0.0321 (0.0337) time: 3.0427 data: 0.0084 max mem: 33408 +Epoch: [32] [2570/2639] eta: 0:03:28 lr: 1.0450580127473207e-05 loss: 0.0337 (0.0337) time: 3.0241 data: 0.0082 max mem: 33408 +Epoch: [32] [2580/2639] eta: 0:02:58 lr: 1.0445507167111807e-05 loss: 0.0324 (0.0337) time: 3.0734 data: 0.0077 max mem: 33408 +Epoch: [32] [2590/2639] eta: 0:02:28 lr: 1.0440433932987653e-05 loss: 0.0311 (0.0337) time: 3.1068 data: 0.0078 max mem: 33408 +Epoch: [32] [2600/2639] eta: 0:01:58 lr: 1.0435360424938158e-05 loss: 0.0311 (0.0338) time: 3.0447 data: 0.0078 max mem: 33408 +Epoch: [32] [2610/2639] eta: 0:01:27 lr: 1.0430286642800528e-05 loss: 0.0336 (0.0338) time: 3.0211 data: 0.0074 max mem: 33408 +Epoch: [32] [2620/2639] eta: 0:00:57 lr: 1.0425212586411808e-05 loss: 0.0336 (0.0338) time: 3.0104 data: 0.0081 max mem: 33408 +Epoch: [32] [2630/2639] eta: 0:00:27 lr: 1.0420138255608834e-05 loss: 0.0318 (0.0338) time: 2.9719 data: 0.0082 max mem: 33408 +Epoch: [32] Total time: 2:13:11 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 1:59:59 time: 2.7980 data: 2.6845 max mem: 33408 +Test: [ 100/2573] eta: 0:04:21 time: 0.0787 data: 0.0015 max mem: 33408 +Test: [ 200/2573] eta: 0:03:42 time: 0.0806 data: 0.0015 max mem: 33408 +Test: [ 300/2573] eta: 0:03:21 time: 0.0817 data: 0.0014 max mem: 33408 +Test: [ 400/2573] eta: 0:03:08 time: 0.0830 data: 0.0014 max mem: 33408 +Test: [ 500/2573] eta: 0:02:58 time: 0.0818 data: 0.0015 max mem: 33408 +Test: [ 600/2573] eta: 0:02:47 time: 0.0801 data: 0.0015 max mem: 33408 +Test: [ 700/2573] eta: 0:02:38 time: 0.0804 data: 0.0015 max mem: 33408 +Test: [ 800/2573] eta: 0:02:29 time: 0.0838 data: 0.0014 max mem: 33408 +Test: [ 900/2573] eta: 0:02:20 time: 0.0815 data: 0.0014 max mem: 33408 +Test: [1000/2573] eta: 0:02:12 time: 0.0820 data: 0.0016 max mem: 33408 +Test: [1100/2573] eta: 0:02:03 time: 0.0808 data: 0.0015 max mem: 33408 +Test: [1200/2573] eta: 0:01:54 time: 0.0817 data: 0.0015 max mem: 33408 +Test: [1300/2573] eta: 0:01:46 time: 0.0811 data: 0.0015 max mem: 33408 +Test: [1400/2573] eta: 0:01:37 time: 0.0798 data: 0.0015 max mem: 33408 +Test: [1500/2573] eta: 0:01:29 time: 0.0803 data: 0.0014 max mem: 33408 +Test: [1600/2573] eta: 0:01:20 time: 0.0848 data: 0.0014 max mem: 33408 +Test: [1700/2573] eta: 0:01:12 time: 0.0799 data: 0.0015 max mem: 33408 +Test: [1800/2573] eta: 0:01:04 time: 0.0834 data: 0.0016 max mem: 33408 +Test: [1900/2573] eta: 0:00:55 time: 0.0808 data: 0.0014 max mem: 33408 +Test: [2000/2573] eta: 0:00:47 time: 0.0819 data: 0.0014 max mem: 33408 +Test: [2100/2573] eta: 0:00:39 time: 0.0837 data: 0.0015 max mem: 33408 +Test: [2200/2573] eta: 0:00:30 time: 0.0836 data: 0.0015 max mem: 33408 +Test: [2300/2573] eta: 0:00:22 time: 0.0827 data: 0.0015 max mem: 33408 +Test: [2400/2573] eta: 0:00:14 time: 0.0780 data: 0.0014 max mem: 33408 +Test: [2500/2573] eta: 0:00:06 time: 0.0816 data: 0.0014 max mem: 33408 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: Total time: 0:03:33 +Final results: +Mean IoU is 64.51 + + precision@0.5 = 72.47 + precision@0.6 = 68.06 + precision@0.7 = 61.13 + precision@0.8 = 49.98 + precision@0.9 = 24.75 + overall IoU = 61.79 + +Average object IoU 64.5063260367534 +Overall IoU 61.791656494140625 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [33] [ 0/2639] eta: 3:58:28 lr: 1.0415571123126986e-05 loss: 0.0294 (0.0294) time: 5.4218 data: 2.1852 max mem: 33408 +Epoch: [33] [ 10/2639] eta: 2:22:38 lr: 1.0410496270486799e-05 loss: 0.0330 (0.0317) time: 3.2555 data: 0.2060 max mem: 33408 +Epoch: [33] [ 20/2639] eta: 2:16:07 lr: 1.0405421142958168e-05 loss: 0.0313 (0.0316) time: 3.0033 data: 0.0077 max mem: 33408 +Epoch: [33] [ 30/2639] eta: 2:13:58 lr: 1.0400345740377224e-05 loss: 0.0306 (0.0318) time: 2.9851 data: 0.0079 max mem: 33408 +Epoch: [33] [ 40/2639] eta: 2:12:57 lr: 1.0395270062579907e-05 loss: 0.0351 (0.0337) time: 3.0182 data: 0.0082 max mem: 33408 +Epoch: [33] [ 50/2639] eta: 2:12:14 lr: 1.0390194109401955e-05 loss: 0.0356 (0.0331) time: 3.0392 data: 0.0081 max mem: 33408 +Epoch: [33] [ 60/2639] eta: 2:11:08 lr: 1.0385117880678942e-05 loss: 0.0257 (0.0322) time: 3.0128 data: 0.0082 max mem: 33408 +Epoch: [33] [ 70/2639] eta: 2:10:26 lr: 1.0380041376246232e-05 loss: 0.0306 (0.0324) time: 3.0004 data: 0.0080 max mem: 33408 +Epoch: [33] [ 80/2639] eta: 2:10:13 lr: 1.0374964595939023e-05 loss: 0.0335 (0.0329) time: 3.0600 data: 0.0080 max mem: 33408 +Epoch: [33] [ 90/2639] eta: 2:09:40 lr: 1.0369887539592305e-05 loss: 0.0318 (0.0325) time: 3.0727 data: 0.0080 max mem: 33408 +Epoch: [33] [ 100/2639] eta: 2:08:58 lr: 1.0364810207040895e-05 loss: 0.0318 (0.0329) time: 3.0271 data: 0.0079 max mem: 33408 +Epoch: [33] [ 110/2639] eta: 2:08:15 lr: 1.0359732598119406e-05 loss: 0.0316 (0.0329) time: 2.9996 data: 0.0078 max mem: 33408 +Epoch: [33] [ 120/2639] eta: 2:07:30 lr: 1.0354654712662282e-05 loss: 0.0309 (0.0328) time: 2.9823 data: 0.0078 max mem: 33408 +Epoch: [33] [ 130/2639] eta: 2:07:01 lr: 1.0349576550503752e-05 loss: 0.0311 (0.0331) time: 3.0096 data: 0.0082 max mem: 33408 +Epoch: [33] [ 140/2639] eta: 2:06:39 lr: 1.0344498111477883e-05 loss: 0.0315 (0.0335) time: 3.0635 data: 0.0082 max mem: 33408 +Epoch: [33] [ 150/2639] eta: 2:06:03 lr: 1.0339419395418524e-05 loss: 0.0290 (0.0334) time: 3.0444 data: 0.0078 max mem: 33408 +Epoch: [33] [ 160/2639] eta: 2:05:29 lr: 1.0334340402159363e-05 loss: 0.0285 (0.0334) time: 3.0124 data: 0.0079 max mem: 33408 +Epoch: [33] [ 170/2639] eta: 2:05:04 lr: 1.0329261131533865e-05 loss: 0.0278 (0.0331) time: 3.0449 data: 0.0080 max mem: 33408 +Epoch: [33] [ 180/2639] eta: 2:04:25 lr: 1.0324181583375338e-05 loss: 0.0297 (0.0333) time: 3.0263 data: 0.0078 max mem: 33408 +Epoch: [33] [ 190/2639] eta: 2:03:59 lr: 1.0319101757516866e-05 loss: 0.0346 (0.0336) time: 3.0237 data: 0.0077 max mem: 33408 +Epoch: [33] [ 200/2639] eta: 2:03:29 lr: 1.0314021653791366e-05 loss: 0.0312 (0.0333) time: 3.0554 data: 0.0078 max mem: 33408 +Epoch: [33] [ 210/2639] eta: 2:03:03 lr: 1.0308941272031549e-05 loss: 0.0262 (0.0330) time: 3.0574 data: 0.0080 max mem: 33408 +Epoch: [33] [ 220/2639] eta: 2:02:25 lr: 1.0303860612069943e-05 loss: 0.0270 (0.0329) time: 3.0210 data: 0.0082 max mem: 33408 +Epoch: [33] [ 230/2639] eta: 2:02:04 lr: 1.0298779673738871e-05 loss: 0.0280 (0.0327) time: 3.0502 data: 0.0082 max mem: 33408 +Epoch: [33] [ 240/2639] eta: 2:01:30 lr: 1.029369845687048e-05 loss: 0.0295 (0.0330) time: 3.0679 data: 0.0082 max mem: 33408 +Epoch: [33] [ 250/2639] eta: 2:01:00 lr: 1.0288616961296705e-05 loss: 0.0308 (0.0331) time: 3.0215 data: 0.0082 max mem: 33408 +Epoch: [33] [ 260/2639] eta: 2:00:27 lr: 1.0283535186849305e-05 loss: 0.0276 (0.0330) time: 3.0272 data: 0.0080 max mem: 33408 +Epoch: [33] [ 270/2639] eta: 1:59:52 lr: 1.0278453133359826e-05 loss: 0.0256 (0.0329) time: 3.0003 data: 0.0079 max mem: 33408 +Epoch: [33] [ 280/2639] eta: 1:59:22 lr: 1.0273370800659637e-05 loss: 0.0287 (0.0329) time: 3.0091 data: 0.0082 max mem: 33408 +Epoch: [33] [ 290/2639] eta: 1:58:49 lr: 1.0268288188579909e-05 loss: 0.0319 (0.0330) time: 3.0209 data: 0.0077 max mem: 33408 +Epoch: [33] [ 300/2639] eta: 1:58:14 lr: 1.0263205296951603e-05 loss: 0.0344 (0.0332) time: 2.9929 data: 0.0075 max mem: 33408 +Epoch: [33] [ 310/2639] eta: 1:57:44 lr: 1.025812212560551e-05 loss: 0.0336 (0.0333) time: 3.0103 data: 0.0081 max mem: 33408 +Epoch: [33] [ 320/2639] eta: 1:57:17 lr: 1.02530386743722e-05 loss: 0.0317 (0.0332) time: 3.0579 data: 0.0084 max mem: 33408 +Epoch: [33] [ 330/2639] eta: 1:56:46 lr: 1.0247954943082065e-05 loss: 0.0287 (0.0331) time: 3.0518 data: 0.0081 max mem: 33408 +Epoch: [33] [ 340/2639] eta: 1:56:22 lr: 1.0242870931565288e-05 loss: 0.0308 (0.0332) time: 3.0754 data: 0.0078 max mem: 33408 +Epoch: [33] [ 350/2639] eta: 1:55:51 lr: 1.023778663965187e-05 loss: 0.0308 (0.0331) time: 3.0736 data: 0.0076 max mem: 33408 +Epoch: [33] [ 360/2639] eta: 1:55:17 lr: 1.0232702067171596e-05 loss: 0.0293 (0.0330) time: 3.0004 data: 0.0080 max mem: 33408 +Epoch: [33] [ 370/2639] eta: 1:54:44 lr: 1.0227617213954077e-05 loss: 0.0301 (0.0330) time: 2.9850 data: 0.0081 max mem: 33408 +Epoch: [33] [ 380/2639] eta: 1:54:14 lr: 1.0222532079828698e-05 loss: 0.0332 (0.0331) time: 3.0220 data: 0.0078 max mem: 33408 +Epoch: [33] [ 390/2639] eta: 1:53:46 lr: 1.0217446664624675e-05 loss: 0.0337 (0.0332) time: 3.0562 data: 0.0079 max mem: 33408 +Epoch: [33] [ 400/2639] eta: 1:53:19 lr: 1.0212360968171e-05 loss: 0.0315 (0.0332) time: 3.0790 data: 0.0080 max mem: 33408 +Epoch: [33] [ 410/2639] eta: 1:52:49 lr: 1.020727499029649e-05 loss: 0.0322 (0.0332) time: 3.0694 data: 0.0080 max mem: 33408 +Epoch: [33] [ 420/2639] eta: 1:52:19 lr: 1.020218873082974e-05 loss: 0.0336 (0.0333) time: 3.0512 data: 0.0078 max mem: 33408 +Epoch: [33] [ 430/2639] eta: 1:51:46 lr: 1.0197102189599169e-05 loss: 0.0345 (0.0333) time: 3.0236 data: 0.0077 max mem: 33408 +Epoch: [33] [ 440/2639] eta: 1:51:10 lr: 1.019201536643297e-05 loss: 0.0292 (0.0332) time: 2.9511 data: 0.0080 max mem: 33408 +Epoch: [33] [ 450/2639] eta: 1:50:38 lr: 1.0186928261159162e-05 loss: 0.0257 (0.0331) time: 2.9523 data: 0.0084 max mem: 33408 +Epoch: [33] [ 460/2639] eta: 1:50:09 lr: 1.0181840873605542e-05 loss: 0.0261 (0.0331) time: 3.0269 data: 0.0082 max mem: 33408 +Epoch: [33] [ 470/2639] eta: 1:49:36 lr: 1.0176753203599726e-05 loss: 0.0271 (0.0330) time: 3.0221 data: 0.0079 max mem: 33408 +Epoch: [33] [ 480/2639] eta: 1:49:07 lr: 1.0171665250969109e-05 loss: 0.0271 (0.0330) time: 3.0209 data: 0.0080 max mem: 33408 +Epoch: [33] [ 490/2639] eta: 1:48:40 lr: 1.0166577015540902e-05 loss: 0.0358 (0.0331) time: 3.0833 data: 0.0078 max mem: 33408 +Epoch: [33] [ 500/2639] eta: 1:48:08 lr: 1.0161488497142098e-05 loss: 0.0301 (0.0331) time: 3.0542 data: 0.0077 max mem: 33408 +Epoch: [33] [ 510/2639] eta: 1:47:37 lr: 1.0156399695599506e-05 loss: 0.0290 (0.0330) time: 3.0076 data: 0.0082 max mem: 33408 +Epoch: [33] [ 520/2639] eta: 1:47:07 lr: 1.0151310610739715e-05 loss: 0.0286 (0.0329) time: 3.0214 data: 0.0085 max mem: 33408 +Epoch: [33] [ 530/2639] eta: 1:46:35 lr: 1.014622124238912e-05 loss: 0.0277 (0.0329) time: 3.0195 data: 0.0078 max mem: 33408 +Epoch: [33] [ 540/2639] eta: 1:46:05 lr: 1.0141131590373919e-05 loss: 0.0296 (0.0329) time: 3.0251 data: 0.0080 max mem: 33408 +Epoch: [33] [ 550/2639] eta: 1:45:34 lr: 1.0136041654520088e-05 loss: 0.0296 (0.0329) time: 3.0231 data: 0.0082 max mem: 33408 +Epoch: [33] [ 560/2639] eta: 1:45:05 lr: 1.0130951434653423e-05 loss: 0.0283 (0.0328) time: 3.0419 data: 0.0079 max mem: 33408 +Epoch: [33] [ 570/2639] eta: 1:44:36 lr: 1.0125860930599488e-05 loss: 0.0283 (0.0328) time: 3.0721 data: 0.0082 max mem: 33408 +Epoch: [33] [ 580/2639] eta: 1:44:03 lr: 1.0120770142183673e-05 loss: 0.0287 (0.0327) time: 3.0167 data: 0.0078 max mem: 33408 +Epoch: [33] [ 590/2639] eta: 1:43:31 lr: 1.0115679069231135e-05 loss: 0.0312 (0.0327) time: 2.9658 data: 0.0077 max mem: 33408 +Epoch: [33] [ 600/2639] eta: 1:43:01 lr: 1.0110587711566847e-05 loss: 0.0313 (0.0328) time: 3.0082 data: 0.0079 max mem: 33408 +Epoch: [33] [ 610/2639] eta: 1:42:30 lr: 1.0105496069015558e-05 loss: 0.0308 (0.0328) time: 3.0255 data: 0.0078 max mem: 33408 +Epoch: [33] [ 620/2639] eta: 1:42:00 lr: 1.0100404141401832e-05 loss: 0.0267 (0.0327) time: 3.0198 data: 0.0077 max mem: 33408 +Epoch: [33] [ 630/2639] eta: 1:41:30 lr: 1.009531192855e-05 loss: 0.0275 (0.0326) time: 3.0385 data: 0.0077 max mem: 33408 +Epoch: [33] [ 640/2639] eta: 1:41:00 lr: 1.009021943028422e-05 loss: 0.0275 (0.0325) time: 3.0443 data: 0.0081 max mem: 33408 +Epoch: [33] [ 650/2639] eta: 1:40:28 lr: 1.0085126646428407e-05 loss: 0.0311 (0.0327) time: 3.0233 data: 0.0085 max mem: 33408 +Epoch: [33] [ 660/2639] eta: 1:39:55 lr: 1.0080033576806298e-05 loss: 0.0324 (0.0327) time: 2.9616 data: 0.0087 max mem: 33408 +Epoch: [33] [ 670/2639] eta: 1:39:24 lr: 1.0074940221241401e-05 loss: 0.0287 (0.0326) time: 2.9714 data: 0.0081 max mem: 33408 +Epoch: [33] [ 680/2639] eta: 1:38:55 lr: 1.0069846579557033e-05 loss: 0.0274 (0.0326) time: 3.0355 data: 0.0082 max mem: 33408 +Epoch: [33] [ 690/2639] eta: 1:38:24 lr: 1.0064752651576282e-05 loss: 0.0298 (0.0326) time: 3.0292 data: 0.0084 max mem: 33408 +Epoch: [33] [ 700/2639] eta: 1:37:54 lr: 1.0059658437122055e-05 loss: 0.0286 (0.0325) time: 3.0167 data: 0.0084 max mem: 33408 +Epoch: [33] [ 710/2639] eta: 1:37:24 lr: 1.0054563936017018e-05 loss: 0.0273 (0.0325) time: 3.0383 data: 0.0085 max mem: 33408 +Epoch: [33] [ 720/2639] eta: 1:36:53 lr: 1.0049469148083658e-05 loss: 0.0299 (0.0325) time: 3.0266 data: 0.0080 max mem: 33408 +Epoch: [33] [ 730/2639] eta: 1:36:22 lr: 1.0044374073144223e-05 loss: 0.0313 (0.0325) time: 3.0042 data: 0.0080 max mem: 33408 +Epoch: [33] [ 740/2639] eta: 1:35:50 lr: 1.003927871102078e-05 loss: 0.0280 (0.0325) time: 2.9847 data: 0.0090 max mem: 33408 +Epoch: [33] [ 750/2639] eta: 1:35:21 lr: 1.0034183061535153e-05 loss: 0.0309 (0.0325) time: 3.0306 data: 0.0089 max mem: 33408 +Epoch: [33] [ 760/2639] eta: 1:34:52 lr: 1.002908712450899e-05 loss: 0.0309 (0.0325) time: 3.0773 data: 0.0081 max mem: 33408 +Epoch: [33] [ 770/2639] eta: 1:34:21 lr: 1.0023990899763691e-05 loss: 0.0307 (0.0325) time: 3.0284 data: 0.0078 max mem: 33408 +Epoch: [33] [ 780/2639] eta: 1:33:49 lr: 1.0018894387120474e-05 loss: 0.0301 (0.0324) time: 2.9862 data: 0.0077 max mem: 33408 +Epoch: [33] [ 790/2639] eta: 1:33:20 lr: 1.0013797586400338e-05 loss: 0.0297 (0.0324) time: 3.0283 data: 0.0079 max mem: 33408 +Epoch: [33] [ 800/2639] eta: 1:32:49 lr: 1.0008700497424052e-05 loss: 0.0287 (0.0324) time: 3.0393 data: 0.0080 max mem: 33408 +Epoch: [33] [ 810/2639] eta: 1:32:19 lr: 1.0003603120012197e-05 loss: 0.0308 (0.0324) time: 3.0245 data: 0.0077 max mem: 33408 +Epoch: [33] [ 820/2639] eta: 1:31:50 lr: 9.998505453985117e-06 loss: 0.0308 (0.0325) time: 3.0556 data: 0.0077 max mem: 33408 +Epoch: [33] [ 830/2639] eta: 1:31:18 lr: 9.993407499162966e-06 loss: 0.0284 (0.0324) time: 3.0216 data: 0.0080 max mem: 33408 +Epoch: [33] [ 840/2639] eta: 1:30:48 lr: 9.988309255365658e-06 loss: 0.0275 (0.0324) time: 3.0143 data: 0.0080 max mem: 33408 +Epoch: [33] [ 850/2639] eta: 1:30:18 lr: 9.98321072241292e-06 loss: 0.0273 (0.0324) time: 3.0250 data: 0.0079 max mem: 33408 +Epoch: [33] [ 860/2639] eta: 1:29:45 lr: 9.978111900124236e-06 loss: 0.0273 (0.0324) time: 2.9664 data: 0.0077 max mem: 33408 +Epoch: [33] [ 870/2639] eta: 1:29:16 lr: 9.973012788318904e-06 loss: 0.0309 (0.0324) time: 3.0095 data: 0.0078 max mem: 33408 +Epoch: [33] [ 880/2639] eta: 1:28:46 lr: 9.967913386815978e-06 loss: 0.0299 (0.0324) time: 3.0648 data: 0.0082 max mem: 33408 +Epoch: [33] [ 890/2639] eta: 1:28:17 lr: 9.962813695434322e-06 loss: 0.0305 (0.0324) time: 3.0528 data: 0.0082 max mem: 33408 +Epoch: [33] [ 900/2639] eta: 1:27:46 lr: 9.957713713992559e-06 loss: 0.0304 (0.0324) time: 3.0328 data: 0.0080 max mem: 33408 +Epoch: [33] [ 910/2639] eta: 1:27:16 lr: 9.952613442309118e-06 loss: 0.0279 (0.0323) time: 3.0272 data: 0.0079 max mem: 33408 +Epoch: [33] [ 920/2639] eta: 1:26:46 lr: 9.94751288020219e-06 loss: 0.0292 (0.0323) time: 3.0502 data: 0.0079 max mem: 33408 +Epoch: [33] [ 930/2639] eta: 1:26:17 lr: 9.94241202748977e-06 loss: 0.0314 (0.0323) time: 3.0641 data: 0.0078 max mem: 33408 +Epoch: [33] [ 940/2639] eta: 1:25:47 lr: 9.937310883989613e-06 loss: 0.0314 (0.0323) time: 3.0824 data: 0.0080 max mem: 33408 +Epoch: [33] [ 950/2639] eta: 1:25:17 lr: 9.932209449519276e-06 loss: 0.0297 (0.0324) time: 3.0459 data: 0.0079 max mem: 33408 +Epoch: [33] [ 960/2639] eta: 1:24:45 lr: 9.927107723896079e-06 loss: 0.0297 (0.0324) time: 2.9887 data: 0.0076 max mem: 33408 +Epoch: [33] [ 970/2639] eta: 1:24:16 lr: 9.922005706937141e-06 loss: 0.0326 (0.0324) time: 3.0236 data: 0.0079 max mem: 33408 +Epoch: [33] [ 980/2639] eta: 1:23:46 lr: 9.916903398459341e-06 loss: 0.0326 (0.0324) time: 3.0721 data: 0.0086 max mem: 33408 +Epoch: [33] [ 990/2639] eta: 1:23:16 lr: 9.911800798279364e-06 loss: 0.0315 (0.0325) time: 3.0642 data: 0.0085 max mem: 33408 +Epoch: [33] [1000/2639] eta: 1:22:46 lr: 9.906697906213645e-06 loss: 0.0322 (0.0324) time: 3.0281 data: 0.0078 max mem: 33408 +Epoch: [33] [1010/2639] eta: 1:22:16 lr: 9.901594722078427e-06 loss: 0.0309 (0.0324) time: 3.0350 data: 0.0078 max mem: 33408 +Epoch: [33] [1020/2639] eta: 1:21:46 lr: 9.896491245689707e-06 loss: 0.0319 (0.0325) time: 3.0482 data: 0.0077 max mem: 33408 +Epoch: [33] [1030/2639] eta: 1:21:15 lr: 9.891387476863279e-06 loss: 0.0323 (0.0325) time: 3.0095 data: 0.0078 max mem: 33408 +Epoch: [33] [1040/2639] eta: 1:20:45 lr: 9.886283415414711e-06 loss: 0.0323 (0.0325) time: 3.0345 data: 0.0085 max mem: 33408 +Epoch: [33] [1050/2639] eta: 1:20:15 lr: 9.881179061159337e-06 loss: 0.0312 (0.0325) time: 3.0544 data: 0.0084 max mem: 33408 +Epoch: [33] [1060/2639] eta: 1:19:44 lr: 9.876074413912291e-06 loss: 0.0296 (0.0325) time: 3.0173 data: 0.0077 max mem: 33408 +Epoch: [33] [1070/2639] eta: 1:19:14 lr: 9.870969473488456e-06 loss: 0.0310 (0.0325) time: 3.0298 data: 0.0079 max mem: 33408 +Epoch: [33] [1080/2639] eta: 1:18:45 lr: 9.86586423970252e-06 loss: 0.0312 (0.0325) time: 3.0748 data: 0.0081 max mem: 33408 +Epoch: [33] [1090/2639] eta: 1:18:15 lr: 9.860758712368919e-06 loss: 0.0311 (0.0325) time: 3.0713 data: 0.0079 max mem: 33408 +Epoch: [33] [1100/2639] eta: 1:17:44 lr: 9.855652891301894e-06 loss: 0.0268 (0.0325) time: 3.0114 data: 0.0075 max mem: 33408 +Epoch: [33] [1110/2639] eta: 1:17:14 lr: 9.850546776315434e-06 loss: 0.0280 (0.0325) time: 3.0071 data: 0.0076 max mem: 33408 +Epoch: [33] [1120/2639] eta: 1:16:43 lr: 9.845440367223328e-06 loss: 0.0319 (0.0325) time: 3.0423 data: 0.0079 max mem: 33408 +Epoch: [33] [1130/2639] eta: 1:16:13 lr: 9.840333663839116e-06 loss: 0.0319 (0.0325) time: 3.0233 data: 0.0086 max mem: 33408 +Epoch: [33] [1140/2639] eta: 1:15:42 lr: 9.835226665976133e-06 loss: 0.0328 (0.0325) time: 3.0055 data: 0.0088 max mem: 33408 +Epoch: [33] [1150/2639] eta: 1:15:11 lr: 9.83011937344747e-06 loss: 0.0307 (0.0326) time: 3.0013 data: 0.0080 max mem: 33408 +Epoch: [33] [1160/2639] eta: 1:14:41 lr: 9.82501178606601e-06 loss: 0.0292 (0.0325) time: 3.0202 data: 0.0079 max mem: 33408 +Epoch: [33] [1170/2639] eta: 1:14:11 lr: 9.819903903644385e-06 loss: 0.0297 (0.0325) time: 3.0282 data: 0.0082 max mem: 33408 +Epoch: [33] [1180/2639] eta: 1:13:41 lr: 9.814795725995028e-06 loss: 0.0336 (0.0325) time: 3.0495 data: 0.0089 max mem: 33408 +Epoch: [33] [1190/2639] eta: 1:13:11 lr: 9.809687252930118e-06 loss: 0.0299 (0.0325) time: 3.0633 data: 0.0089 max mem: 33408 +Epoch: [33] [1200/2639] eta: 1:12:40 lr: 9.804578484261629e-06 loss: 0.0269 (0.0325) time: 3.0131 data: 0.0086 max mem: 33408 +Epoch: [33] [1210/2639] eta: 1:12:10 lr: 9.79946941980128e-06 loss: 0.0275 (0.0325) time: 3.0158 data: 0.0089 max mem: 33408 +Epoch: [33] [1220/2639] eta: 1:11:40 lr: 9.794360059360592e-06 loss: 0.0295 (0.0325) time: 3.0416 data: 0.0080 max mem: 33408 +Epoch: [33] [1230/2639] eta: 1:11:10 lr: 9.789250402750827e-06 loss: 0.0310 (0.0326) time: 3.0537 data: 0.0079 max mem: 33408 +Epoch: [33] [1240/2639] eta: 1:10:39 lr: 9.784140449783041e-06 loss: 0.0314 (0.0326) time: 3.0448 data: 0.0079 max mem: 33408 +Epoch: [33] [1250/2639] eta: 1:10:10 lr: 9.779030200268038e-06 loss: 0.0296 (0.0325) time: 3.0597 data: 0.0076 max mem: 33408 +Epoch: [33] [1260/2639] eta: 1:09:40 lr: 9.773919654016407e-06 loss: 0.0329 (0.0326) time: 3.0827 data: 0.0075 max mem: 33408 +Epoch: [33] [1270/2639] eta: 1:09:10 lr: 9.76880881083851e-06 loss: 0.0325 (0.0326) time: 3.0659 data: 0.0076 max mem: 33408 +Epoch: [33] [1280/2639] eta: 1:08:39 lr: 9.763697670544455e-06 loss: 0.0289 (0.0325) time: 3.0212 data: 0.0080 max mem: 33408 +Epoch: [33] [1290/2639] eta: 1:08:09 lr: 9.758586232944145e-06 loss: 0.0289 (0.0325) time: 3.0049 data: 0.0081 max mem: 33408 +Epoch: [33] [1300/2639] eta: 1:07:39 lr: 9.753474497847226e-06 loss: 0.0277 (0.0325) time: 3.0388 data: 0.0080 max mem: 33408 +Epoch: [33] [1310/2639] eta: 1:07:08 lr: 9.748362465063132e-06 loss: 0.0277 (0.0325) time: 3.0318 data: 0.0077 max mem: 33408 +Epoch: [33] [1320/2639] eta: 1:06:38 lr: 9.743250134401044e-06 loss: 0.0295 (0.0325) time: 3.0262 data: 0.0076 max mem: 33408 +Epoch: [33] [1330/2639] eta: 1:06:08 lr: 9.738137505669934e-06 loss: 0.0288 (0.0325) time: 3.0354 data: 0.0076 max mem: 33408 +Epoch: [33] [1340/2639] eta: 1:05:37 lr: 9.73302457867851e-06 loss: 0.0252 (0.0324) time: 3.0236 data: 0.0075 max mem: 33408 +Epoch: [33] [1350/2639] eta: 1:05:07 lr: 9.727911353235277e-06 loss: 0.0248 (0.0324) time: 3.0074 data: 0.0075 max mem: 33408 +Epoch: [33] [1360/2639] eta: 1:04:37 lr: 9.722797829148476e-06 loss: 0.0315 (0.0324) time: 3.0346 data: 0.0075 max mem: 33408 +Epoch: [33] [1370/2639] eta: 1:04:06 lr: 9.717684006226137e-06 loss: 0.0322 (0.0324) time: 3.0316 data: 0.0075 max mem: 33408 +Epoch: [33] [1380/2639] eta: 1:03:36 lr: 9.712569884276033e-06 loss: 0.0292 (0.0324) time: 3.0459 data: 0.0079 max mem: 33408 +Epoch: [33] [1390/2639] eta: 1:03:06 lr: 9.707455463105725e-06 loss: 0.0288 (0.0324) time: 3.0765 data: 0.0080 max mem: 33408 +Epoch: [33] [1400/2639] eta: 1:02:36 lr: 9.702340742522507e-06 loss: 0.0288 (0.0324) time: 3.0583 data: 0.0076 max mem: 33408 +Epoch: [33] [1410/2639] eta: 1:02:06 lr: 9.697225722333468e-06 loss: 0.0285 (0.0324) time: 3.0684 data: 0.0077 max mem: 33408 +Epoch: [33] [1420/2639] eta: 1:01:36 lr: 9.692110402345431e-06 loss: 0.0315 (0.0324) time: 3.0572 data: 0.0076 max mem: 33408 +Epoch: [33] [1430/2639] eta: 1:01:05 lr: 9.686994782365008e-06 loss: 0.0328 (0.0324) time: 2.9931 data: 0.0073 max mem: 33408 +Epoch: [33] [1440/2639] eta: 1:00:34 lr: 9.681878862198545e-06 loss: 0.0312 (0.0324) time: 2.9453 data: 0.0074 max mem: 33408 +Epoch: [33] [1450/2639] eta: 1:00:03 lr: 9.676762641652175e-06 loss: 0.0314 (0.0324) time: 2.9824 data: 0.0080 max mem: 33408 +Epoch: [33] [1460/2639] eta: 0:59:33 lr: 9.67164612053177e-06 loss: 0.0315 (0.0324) time: 3.0117 data: 0.0079 max mem: 33408 +Epoch: [33] [1470/2639] eta: 0:59:03 lr: 9.666529298642983e-06 loss: 0.0296 (0.0324) time: 3.0251 data: 0.0076 max mem: 33408 +Epoch: [33] [1480/2639] eta: 0:58:33 lr: 9.661412175791203e-06 loss: 0.0271 (0.0324) time: 3.0516 data: 0.0080 max mem: 33408 +Epoch: [33] [1490/2639] eta: 0:58:02 lr: 9.656294751781608e-06 loss: 0.0276 (0.0324) time: 3.0185 data: 0.0080 max mem: 33408 +Epoch: [33] [1500/2639] eta: 0:57:32 lr: 9.651177026419104e-06 loss: 0.0277 (0.0323) time: 3.0244 data: 0.0078 max mem: 33408 +Epoch: [33] [1510/2639] eta: 0:57:01 lr: 9.646058999508374e-06 loss: 0.0289 (0.0323) time: 2.9960 data: 0.0072 max mem: 33408 +Epoch: [33] [1520/2639] eta: 0:56:30 lr: 9.640940670853866e-06 loss: 0.0289 (0.0323) time: 2.9640 data: 0.0069 max mem: 33408 +Epoch: [33] [1530/2639] eta: 0:56:00 lr: 9.635822040259763e-06 loss: 0.0288 (0.0323) time: 3.0119 data: 0.0072 max mem: 33408 +Epoch: [33] [1540/2639] eta: 0:55:30 lr: 9.630703107530025e-06 loss: 0.0338 (0.0324) time: 3.0577 data: 0.0073 max mem: 33408 +Epoch: [33] [1550/2639] eta: 0:55:00 lr: 9.625583872468356e-06 loss: 0.0316 (0.0324) time: 3.0673 data: 0.0073 max mem: 33408 +Epoch: [33] [1560/2639] eta: 0:54:29 lr: 9.620464334878228e-06 loss: 0.0280 (0.0324) time: 2.9991 data: 0.0077 max mem: 33408 +Epoch: [33] [1570/2639] eta: 0:53:58 lr: 9.615344494562858e-06 loss: 0.0267 (0.0323) time: 2.9778 data: 0.0077 max mem: 33408 +Epoch: [33] [1580/2639] eta: 0:53:29 lr: 9.610224351325227e-06 loss: 0.0264 (0.0323) time: 3.0581 data: 0.0075 max mem: 33408 +Epoch: [33] [1590/2639] eta: 0:52:58 lr: 9.605103904968062e-06 loss: 0.0288 (0.0324) time: 3.0735 data: 0.0074 max mem: 33408 +Epoch: [33] [1600/2639] eta: 0:52:28 lr: 9.599983155293858e-06 loss: 0.0351 (0.0324) time: 2.9970 data: 0.0072 max mem: 33408 +Epoch: [33] [1610/2639] eta: 0:51:58 lr: 9.594862102104846e-06 loss: 0.0317 (0.0324) time: 3.0086 data: 0.0075 max mem: 33408 +Epoch: [33] [1620/2639] eta: 0:51:27 lr: 9.589740745203033e-06 loss: 0.0314 (0.0324) time: 3.0396 data: 0.0078 max mem: 33408 +Epoch: [33] [1630/2639] eta: 0:50:57 lr: 9.584619084390153e-06 loss: 0.0339 (0.0324) time: 3.0113 data: 0.0077 max mem: 33408 +Epoch: [33] [1640/2639] eta: 0:50:26 lr: 9.579497119467723e-06 loss: 0.0311 (0.0324) time: 2.9850 data: 0.0077 max mem: 33408 +Epoch: [33] [1650/2639] eta: 0:49:56 lr: 9.574374850236981e-06 loss: 0.0312 (0.0324) time: 2.9949 data: 0.0078 max mem: 33408 +Epoch: [33] [1660/2639] eta: 0:49:26 lr: 9.569252276498944e-06 loss: 0.0312 (0.0324) time: 3.0381 data: 0.0077 max mem: 33408 +Epoch: [33] [1670/2639] eta: 0:48:55 lr: 9.564129398054358e-06 loss: 0.0304 (0.0324) time: 3.0255 data: 0.0078 max mem: 33408 +Epoch: [33] [1680/2639] eta: 0:48:25 lr: 9.559006214703744e-06 loss: 0.0315 (0.0324) time: 3.0403 data: 0.0079 max mem: 33408 +Epoch: [33] [1690/2639] eta: 0:47:55 lr: 9.553882726247344e-06 loss: 0.0315 (0.0324) time: 3.0526 data: 0.0082 max mem: 33408 +Epoch: [33] [1700/2639] eta: 0:47:24 lr: 9.548758932485181e-06 loss: 0.0324 (0.0325) time: 3.0219 data: 0.0082 max mem: 33408 +Epoch: [33] [1710/2639] eta: 0:46:54 lr: 9.543634833217e-06 loss: 0.0326 (0.0325) time: 3.0469 data: 0.0078 max mem: 33408 +Epoch: [33] [1720/2639] eta: 0:46:24 lr: 9.538510428242322e-06 loss: 0.0318 (0.0325) time: 3.0390 data: 0.0078 max mem: 33408 +Epoch: [33] [1730/2639] eta: 0:45:54 lr: 9.533385717360387e-06 loss: 0.0301 (0.0325) time: 3.0321 data: 0.0079 max mem: 33408 +Epoch: [33] [1740/2639] eta: 0:45:24 lr: 9.528260700370211e-06 loss: 0.0282 (0.0325) time: 3.0749 data: 0.0082 max mem: 33408 +Epoch: [33] [1750/2639] eta: 0:44:54 lr: 9.523135377070534e-06 loss: 0.0262 (0.0325) time: 3.0664 data: 0.0082 max mem: 33408 +Epoch: [33] [1760/2639] eta: 0:44:23 lr: 9.518009747259863e-06 loss: 0.0277 (0.0325) time: 3.0628 data: 0.0079 max mem: 33408 +Epoch: [33] [1770/2639] eta: 0:43:53 lr: 9.512883810736446e-06 loss: 0.0318 (0.0325) time: 3.0826 data: 0.0081 max mem: 33408 +Epoch: [33] [1780/2639] eta: 0:43:23 lr: 9.507757567298265e-06 loss: 0.0364 (0.0325) time: 3.0504 data: 0.0082 max mem: 33408 +Epoch: [33] [1790/2639] eta: 0:42:53 lr: 9.502631016743069e-06 loss: 0.0361 (0.0325) time: 3.0514 data: 0.0081 max mem: 33408 +Epoch: [33] [1800/2639] eta: 0:42:23 lr: 9.497504158868328e-06 loss: 0.0291 (0.0325) time: 3.0797 data: 0.0080 max mem: 33408 +Epoch: [33] [1810/2639] eta: 0:41:53 lr: 9.492376993471283e-06 loss: 0.0260 (0.0325) time: 3.0504 data: 0.0084 max mem: 33408 +Epoch: [33] [1820/2639] eta: 0:41:22 lr: 9.487249520348894e-06 loss: 0.0254 (0.0324) time: 3.0554 data: 0.0085 max mem: 33408 +Epoch: [33] [1830/2639] eta: 0:40:52 lr: 9.48212173929789e-06 loss: 0.0281 (0.0325) time: 3.0407 data: 0.0079 max mem: 33408 +Epoch: [33] [1840/2639] eta: 0:40:22 lr: 9.476993650114718e-06 loss: 0.0302 (0.0325) time: 3.0329 data: 0.0077 max mem: 33408 +Epoch: [33] [1850/2639] eta: 0:39:52 lr: 9.471865252595592e-06 loss: 0.0290 (0.0324) time: 3.0801 data: 0.0077 max mem: 33408 +Epoch: [33] [1860/2639] eta: 0:39:21 lr: 9.466736546536444e-06 loss: 0.0303 (0.0325) time: 3.0365 data: 0.0076 max mem: 33408 +Epoch: [33] [1870/2639] eta: 0:38:51 lr: 9.461607531732978e-06 loss: 0.0272 (0.0324) time: 2.9947 data: 0.0075 max mem: 33408 +Epoch: [33] [1880/2639] eta: 0:38:20 lr: 9.456478207980609e-06 loss: 0.0295 (0.0324) time: 2.9817 data: 0.0079 max mem: 33408 +Epoch: [33] [1890/2639] eta: 0:37:50 lr: 9.451348575074515e-06 loss: 0.0306 (0.0324) time: 2.9741 data: 0.0083 max mem: 33408 +Epoch: [33] [1900/2639] eta: 0:37:20 lr: 9.446218632809601e-06 loss: 0.0304 (0.0325) time: 3.0339 data: 0.0079 max mem: 33408 +Epoch: [33] [1910/2639] eta: 0:36:49 lr: 9.441088380980524e-06 loss: 0.0309 (0.0325) time: 3.0361 data: 0.0077 max mem: 33408 +Epoch: [33] [1920/2639] eta: 0:36:19 lr: 9.435957819381665e-06 loss: 0.0320 (0.0325) time: 3.0211 data: 0.0081 max mem: 33408 +Epoch: [33] [1930/2639] eta: 0:35:49 lr: 9.430826947807165e-06 loss: 0.0287 (0.0325) time: 3.0530 data: 0.0081 max mem: 33408 +Epoch: [33] [1940/2639] eta: 0:35:18 lr: 9.42569576605088e-06 loss: 0.0279 (0.0325) time: 2.9987 data: 0.0082 max mem: 33408 +Epoch: [33] [1950/2639] eta: 0:34:48 lr: 9.420564273906427e-06 loss: 0.0269 (0.0324) time: 2.9605 data: 0.0079 max mem: 33408 +Epoch: [33] [1960/2639] eta: 0:34:17 lr: 9.41543247116714e-06 loss: 0.0269 (0.0324) time: 2.9691 data: 0.0078 max mem: 33408 +Epoch: [33] [1970/2639] eta: 0:33:47 lr: 9.41030035762611e-06 loss: 0.0260 (0.0324) time: 2.9968 data: 0.0081 max mem: 33408 +Epoch: [33] [1980/2639] eta: 0:33:16 lr: 9.405167933076142e-06 loss: 0.0275 (0.0325) time: 3.0423 data: 0.0080 max mem: 33408 +Epoch: [33] [1990/2639] eta: 0:32:46 lr: 9.400035197309805e-06 loss: 0.0302 (0.0324) time: 3.0481 data: 0.0078 max mem: 33408 +Epoch: [33] [2000/2639] eta: 0:32:16 lr: 9.394902150119374e-06 loss: 0.0326 (0.0325) time: 3.0305 data: 0.0079 max mem: 33408 +Epoch: [33] [2010/2639] eta: 0:31:46 lr: 9.38976879129688e-06 loss: 0.0304 (0.0325) time: 3.0543 data: 0.0078 max mem: 33408 +Epoch: [33] [2020/2639] eta: 0:31:15 lr: 9.384635120634089e-06 loss: 0.0298 (0.0325) time: 3.0580 data: 0.0079 max mem: 33408 +Epoch: [33] [2030/2639] eta: 0:30:45 lr: 9.379501137922481e-06 loss: 0.0304 (0.0325) time: 3.0260 data: 0.0083 max mem: 33408 +Epoch: [33] [2040/2639] eta: 0:30:15 lr: 9.3743668429533e-06 loss: 0.0302 (0.0325) time: 3.0396 data: 0.0082 max mem: 33408 +Epoch: [33] [2050/2639] eta: 0:29:45 lr: 9.369232235517488e-06 loss: 0.0309 (0.0325) time: 3.0341 data: 0.0077 max mem: 33408 +Epoch: [33] [2060/2639] eta: 0:29:14 lr: 9.364097315405755e-06 loss: 0.0279 (0.0324) time: 3.0357 data: 0.0076 max mem: 33408 +Epoch: [33] [2070/2639] eta: 0:28:44 lr: 9.358962082408509e-06 loss: 0.0287 (0.0325) time: 3.0281 data: 0.0081 max mem: 33408 +Epoch: [33] [2080/2639] eta: 0:28:14 lr: 9.353826536315925e-06 loss: 0.0377 (0.0325) time: 2.9980 data: 0.0090 max mem: 33408 +Epoch: [33] [2090/2639] eta: 0:27:43 lr: 9.348690676917876e-06 loss: 0.0283 (0.0325) time: 2.9783 data: 0.0086 max mem: 33408 +Epoch: [33] [2100/2639] eta: 0:27:13 lr: 9.343554504003993e-06 loss: 0.0273 (0.0325) time: 2.9627 data: 0.0082 max mem: 33408 +Epoch: [33] [2110/2639] eta: 0:26:42 lr: 9.338418017363612e-06 loss: 0.0323 (0.0325) time: 2.9405 data: 0.0084 max mem: 33408 +Epoch: [33] [2120/2639] eta: 0:26:12 lr: 9.333281216785827e-06 loss: 0.0345 (0.0325) time: 2.9433 data: 0.0082 max mem: 33408 +Epoch: [33] [2130/2639] eta: 0:25:41 lr: 9.328144102059428e-06 loss: 0.0310 (0.0325) time: 2.9529 data: 0.0080 max mem: 33408 +Epoch: [33] [2140/2639] eta: 0:25:11 lr: 9.323006672972969e-06 loss: 0.0290 (0.0325) time: 2.9900 data: 0.0083 max mem: 33408 +Epoch: [33] [2150/2639] eta: 0:24:41 lr: 9.317868929314699e-06 loss: 0.0300 (0.0325) time: 3.0440 data: 0.0082 max mem: 33408 +Epoch: [33] [2160/2639] eta: 0:24:10 lr: 9.312730870872622e-06 loss: 0.0301 (0.0325) time: 3.0642 data: 0.0079 max mem: 33408 +Epoch: [33] [2170/2639] eta: 0:23:40 lr: 9.307592497434446e-06 loss: 0.0332 (0.0325) time: 3.0302 data: 0.0079 max mem: 33408 +Epoch: [33] [2180/2639] eta: 0:23:10 lr: 9.302453808787627e-06 loss: 0.0367 (0.0325) time: 2.9940 data: 0.0081 max mem: 33408 +Epoch: [33] [2190/2639] eta: 0:22:39 lr: 9.297314804719326e-06 loss: 0.0316 (0.0325) time: 3.0418 data: 0.0080 max mem: 33408 +Epoch: [33] [2200/2639] eta: 0:22:09 lr: 9.292175485016452e-06 loss: 0.0307 (0.0325) time: 3.0486 data: 0.0076 max mem: 33408 +Epoch: [33] [2210/2639] eta: 0:21:39 lr: 9.287035849465614e-06 loss: 0.0307 (0.0325) time: 2.9996 data: 0.0076 max mem: 33408 +Epoch: [33] [2220/2639] eta: 0:21:08 lr: 9.28189589785317e-06 loss: 0.0331 (0.0326) time: 2.9737 data: 0.0077 max mem: 33408 +Epoch: [33] [2230/2639] eta: 0:20:38 lr: 9.27675562996518e-06 loss: 0.0300 (0.0326) time: 3.0072 data: 0.0079 max mem: 33408 +Epoch: [33] [2240/2639] eta: 0:20:08 lr: 9.271615045587451e-06 loss: 0.0284 (0.0325) time: 3.0317 data: 0.0081 max mem: 33408 +Epoch: [33] [2250/2639] eta: 0:19:37 lr: 9.266474144505483e-06 loss: 0.0299 (0.0325) time: 3.0122 data: 0.0082 max mem: 33408 +Epoch: [33] [2260/2639] eta: 0:19:07 lr: 9.261332926504524e-06 loss: 0.0307 (0.0325) time: 3.0043 data: 0.0086 max mem: 33408 +Epoch: [33] [2270/2639] eta: 0:18:37 lr: 9.25619139136954e-06 loss: 0.0303 (0.0325) time: 3.0011 data: 0.0086 max mem: 33408 +Epoch: [33] [2280/2639] eta: 0:18:07 lr: 9.251049538885203e-06 loss: 0.0303 (0.0326) time: 3.0709 data: 0.0083 max mem: 33408 +Epoch: [33] [2290/2639] eta: 0:17:36 lr: 9.245907368835924e-06 loss: 0.0314 (0.0326) time: 3.0713 data: 0.0083 max mem: 33408 +Epoch: [33] [2300/2639] eta: 0:17:06 lr: 9.240764881005814e-06 loss: 0.0337 (0.0326) time: 2.9760 data: 0.0086 max mem: 33408 +Epoch: [33] [2310/2639] eta: 0:16:36 lr: 9.235622075178731e-06 loss: 0.0338 (0.0326) time: 3.0071 data: 0.0087 max mem: 33408 +Epoch: [33] [2320/2639] eta: 0:16:06 lr: 9.230478951138225e-06 loss: 0.0334 (0.0326) time: 3.0529 data: 0.0084 max mem: 33408 +Epoch: [33] [2330/2639] eta: 0:15:35 lr: 9.225335508667585e-06 loss: 0.0319 (0.0326) time: 3.0289 data: 0.0084 max mem: 33408 +Epoch: [33] [2340/2639] eta: 0:15:05 lr: 9.220191747549797e-06 loss: 0.0308 (0.0326) time: 3.0421 data: 0.0085 max mem: 33408 +Epoch: [33] [2350/2639] eta: 0:14:35 lr: 9.215047667567593e-06 loss: 0.0319 (0.0326) time: 3.0593 data: 0.0083 max mem: 33408 +Epoch: [33] [2360/2639] eta: 0:14:04 lr: 9.209903268503391e-06 loss: 0.0315 (0.0326) time: 3.0511 data: 0.0079 max mem: 33408 +Epoch: [33] [2370/2639] eta: 0:13:34 lr: 9.204758550139351e-06 loss: 0.0305 (0.0326) time: 3.0576 data: 0.0082 max mem: 33408 +Epoch: [33] [2380/2639] eta: 0:13:04 lr: 9.19961351225733e-06 loss: 0.0340 (0.0326) time: 3.0431 data: 0.0083 max mem: 33408 +Epoch: [33] [2390/2639] eta: 0:12:34 lr: 9.194468154638918e-06 loss: 0.0335 (0.0326) time: 3.0443 data: 0.0082 max mem: 33408 +Epoch: [33] [2400/2639] eta: 0:12:03 lr: 9.189322477065397e-06 loss: 0.0287 (0.0326) time: 3.0233 data: 0.0088 max mem: 33408 +Epoch: [33] [2410/2639] eta: 0:11:33 lr: 9.184176479317792e-06 loss: 0.0283 (0.0326) time: 2.9803 data: 0.0085 max mem: 33408 +Epoch: [33] [2420/2639] eta: 0:11:03 lr: 9.179030161176809e-06 loss: 0.0288 (0.0326) time: 3.0357 data: 0.0079 max mem: 33408 +Epoch: [33] [2430/2639] eta: 0:10:32 lr: 9.173883522422902e-06 loss: 0.0313 (0.0326) time: 3.0456 data: 0.0079 max mem: 33408 +Epoch: [33] [2440/2639] eta: 0:10:02 lr: 9.168736562836205e-06 loss: 0.0308 (0.0326) time: 2.9935 data: 0.0079 max mem: 33408 +Epoch: [33] [2450/2639] eta: 0:09:32 lr: 9.163589282196588e-06 loss: 0.0320 (0.0326) time: 3.0066 data: 0.0079 max mem: 33408 +Epoch: [33] [2460/2639] eta: 0:09:02 lr: 9.158441680283618e-06 loss: 0.0364 (0.0327) time: 3.0297 data: 0.0078 max mem: 33408 +Epoch: [33] [2470/2639] eta: 0:08:31 lr: 9.153293756876583e-06 loss: 0.0275 (0.0326) time: 3.0406 data: 0.0076 max mem: 33408 +Epoch: [33] [2480/2639] eta: 0:08:01 lr: 9.148145511754472e-06 loss: 0.0279 (0.0326) time: 3.0231 data: 0.0076 max mem: 33408 +Epoch: [33] [2490/2639] eta: 0:07:31 lr: 9.142996944695993e-06 loss: 0.0343 (0.0327) time: 3.0242 data: 0.0078 max mem: 33408 +Epoch: [33] [2500/2639] eta: 0:07:00 lr: 9.137848055479552e-06 loss: 0.0319 (0.0326) time: 3.0126 data: 0.0076 max mem: 33408 +Epoch: [33] [2510/2639] eta: 0:06:30 lr: 9.132698843883272e-06 loss: 0.0312 (0.0326) time: 2.9679 data: 0.0074 max mem: 33408 +Epoch: [33] [2520/2639] eta: 0:06:00 lr: 9.12754930968499e-06 loss: 0.0319 (0.0326) time: 3.0065 data: 0.0084 max mem: 33408 +Epoch: [33] [2530/2639] eta: 0:05:30 lr: 9.122399452662233e-06 loss: 0.0319 (0.0326) time: 3.0612 data: 0.0086 max mem: 33408 +Epoch: [33] [2540/2639] eta: 0:04:59 lr: 9.117249272592254e-06 loss: 0.0307 (0.0326) time: 3.0661 data: 0.0080 max mem: 33408 +Epoch: [33] [2550/2639] eta: 0:04:29 lr: 9.11209876925199e-06 loss: 0.0307 (0.0326) time: 3.0416 data: 0.0078 max mem: 33408 +Epoch: [33] [2560/2639] eta: 0:03:59 lr: 9.106947942418111e-06 loss: 0.0285 (0.0326) time: 3.0075 data: 0.0074 max mem: 33408 +Epoch: [33] [2570/2639] eta: 0:03:28 lr: 9.101796791866968e-06 loss: 0.0292 (0.0326) time: 3.0035 data: 0.0075 max mem: 33408 +Epoch: [33] [2580/2639] eta: 0:02:58 lr: 9.096645317374634e-06 loss: 0.0280 (0.0326) time: 2.9882 data: 0.0083 max mem: 33408 +Epoch: [33] [2590/2639] eta: 0:02:28 lr: 9.09149351871687e-06 loss: 0.0293 (0.0326) time: 2.9896 data: 0.0083 max mem: 33408 +Epoch: [33] [2600/2639] eta: 0:01:58 lr: 9.086341395669161e-06 loss: 0.0339 (0.0326) time: 3.0650 data: 0.0077 max mem: 33408 +Epoch: [33] [2610/2639] eta: 0:01:27 lr: 9.08118894800667e-06 loss: 0.0294 (0.0326) time: 3.0745 data: 0.0078 max mem: 33408 +Epoch: [33] [2620/2639] eta: 0:00:57 lr: 9.07603617550429e-06 loss: 0.0294 (0.0326) time: 3.0706 data: 0.0081 max mem: 33408 +Epoch: [33] [2630/2639] eta: 0:00:27 lr: 9.070883077936586e-06 loss: 0.0285 (0.0326) time: 3.0593 data: 0.0077 max mem: 33408 +Epoch: [33] Total time: 2:13:12 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 2:16:47 time: 3.1900 data: 3.1071 max mem: 33408 +Test: [ 100/2573] eta: 0:04:29 time: 0.0784 data: 0.0014 max mem: 33408 +Test: [ 200/2573] eta: 0:03:45 time: 0.0804 data: 0.0015 max mem: 33408 +Test: [ 300/2573] eta: 0:03:24 time: 0.0814 data: 0.0015 max mem: 33408 +Test: [ 400/2573] eta: 0:03:09 time: 0.0823 data: 0.0015 max mem: 33408 +Test: [ 500/2573] eta: 0:02:58 time: 0.0801 data: 0.0015 max mem: 33408 +Test: [ 600/2573] eta: 0:02:47 time: 0.0798 data: 0.0015 max mem: 33408 +Test: [ 700/2573] eta: 0:02:38 time: 0.0812 data: 0.0014 max mem: 33408 +Test: [ 800/2573] eta: 0:02:29 time: 0.0843 data: 0.0014 max mem: 33408 +Test: [ 900/2573] eta: 0:02:20 time: 0.0805 data: 0.0014 max mem: 33408 +Test: [1000/2573] eta: 0:02:11 time: 0.0812 data: 0.0014 max mem: 33408 +Test: [1100/2573] eta: 0:02:03 time: 0.0806 data: 0.0016 max mem: 33408 +Test: [1200/2573] eta: 0:01:54 time: 0.0808 data: 0.0014 max mem: 33408 +Test: [1300/2573] eta: 0:01:46 time: 0.0810 data: 0.0013 max mem: 33408 +Test: [1400/2573] eta: 0:01:37 time: 0.0797 data: 0.0014 max mem: 33408 +Test: [1500/2573] eta: 0:01:29 time: 0.0805 data: 0.0014 max mem: 33408 +Test: [1600/2573] eta: 0:01:20 time: 0.0847 data: 0.0015 max mem: 33408 +Test: [1700/2573] eta: 0:01:12 time: 0.0801 data: 0.0014 max mem: 33408 +Test: [1800/2573] eta: 0:01:03 time: 0.0831 data: 0.0016 max mem: 33408 +Test: [1900/2573] eta: 0:00:55 time: 0.0794 data: 0.0015 max mem: 33408 +Test: [2000/2573] eta: 0:00:47 time: 0.0811 data: 0.0014 max mem: 33408 +Test: [2100/2573] eta: 0:00:38 time: 0.0833 data: 0.0014 max mem: 33408 +Test: [2200/2573] eta: 0:00:30 time: 0.0829 data: 0.0015 max mem: 33408 +Test: [2300/2573] eta: 0:00:22 time: 0.0831 data: 0.0015 max mem: 33408 +Test: [2400/2573] eta: 0:00:14 time: 0.0782 data: 0.0014 max mem: 33408 +Test: [2500/2573] eta: 0:00:06 time: 0.0821 data: 0.0015 max mem: 33408 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: Total time: 0:03:32 +Final results: +Mean IoU is 65.21 + + precision@0.5 = 73.02 + precision@0.6 = 68.20 + precision@0.7 = 61.44 + precision@0.8 = 50.53 + precision@0.9 = 25.61 + overall IoU = 62.55 + +Average object IoU 65.2111791579052 +Overall IoU 62.545658111572266 +Better epoch: 33 + +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [34] [ 0/2639] eta: 3:57:37 lr: 9.066245012008258e-06 loss: 0.0130 (0.0130) time: 5.4025 data: 2.3550 max mem: 33408 +Epoch: [34] [ 10/2639] eta: 2:20:34 lr: 9.06109129619436e-06 loss: 0.0271 (0.0276) time: 3.2084 data: 0.2214 max mem: 33408 +Epoch: [34] [ 20/2639] eta: 2:16:00 lr: 9.05593725465973e-06 loss: 0.0273 (0.0287) time: 3.0016 data: 0.0077 max mem: 33408 +Epoch: [34] [ 30/2639] eta: 2:14:30 lr: 9.05078288717779e-06 loss: 0.0289 (0.0291) time: 3.0298 data: 0.0076 max mem: 33408 +Epoch: [34] [ 40/2639] eta: 2:12:20 lr: 9.045628193521643e-06 loss: 0.0289 (0.0302) time: 2.9919 data: 0.0077 max mem: 33408 +Epoch: [34] [ 50/2639] eta: 2:11:32 lr: 9.040473173464108e-06 loss: 0.0317 (0.0303) time: 2.9794 data: 0.0076 max mem: 33408 +Epoch: [34] [ 60/2639] eta: 2:11:11 lr: 9.035317826777679e-06 loss: 0.0279 (0.0302) time: 3.0459 data: 0.0076 max mem: 33408 +Epoch: [34] [ 70/2639] eta: 2:10:30 lr: 9.030162153234572e-06 loss: 0.0278 (0.0298) time: 3.0470 data: 0.0081 max mem: 33408 +Epoch: [34] [ 80/2639] eta: 2:09:40 lr: 9.025006152606676e-06 loss: 0.0283 (0.0302) time: 3.0042 data: 0.0080 max mem: 33408 +Epoch: [34] [ 90/2639] eta: 2:09:11 lr: 9.019849824665596e-06 loss: 0.0295 (0.0299) time: 3.0154 data: 0.0078 max mem: 33408 +Epoch: [34] [ 100/2639] eta: 2:08:18 lr: 9.014693169182615e-06 loss: 0.0276 (0.0298) time: 2.9993 data: 0.0079 max mem: 33408 +Epoch: [34] [ 110/2639] eta: 2:07:37 lr: 9.00953618592873e-06 loss: 0.0289 (0.0302) time: 2.9691 data: 0.0077 max mem: 33408 +Epoch: [34] [ 120/2639] eta: 2:07:05 lr: 9.00437887467461e-06 loss: 0.0293 (0.0301) time: 3.0018 data: 0.0081 max mem: 33408 +Epoch: [34] [ 130/2639] eta: 2:06:50 lr: 8.999221235190633e-06 loss: 0.0283 (0.0300) time: 3.0620 data: 0.0081 max mem: 33408 +Epoch: [34] [ 140/2639] eta: 2:06:26 lr: 8.994063267246872e-06 loss: 0.0261 (0.0299) time: 3.0873 data: 0.0077 max mem: 33408 +Epoch: [34] [ 150/2639] eta: 2:05:57 lr: 8.988904970613074e-06 loss: 0.0294 (0.0303) time: 3.0562 data: 0.0078 max mem: 33408 +Epoch: [34] [ 160/2639] eta: 2:05:27 lr: 8.983746345058701e-06 loss: 0.0272 (0.0301) time: 3.0409 data: 0.0081 max mem: 33408 +Epoch: [34] [ 170/2639] eta: 2:04:55 lr: 8.978587390352884e-06 loss: 0.0286 (0.0306) time: 3.0322 data: 0.0078 max mem: 33408 +Epoch: [34] [ 180/2639] eta: 2:04:22 lr: 8.973428106264467e-06 loss: 0.0291 (0.0304) time: 3.0229 data: 0.0075 max mem: 33408 +Epoch: [34] [ 190/2639] eta: 2:03:49 lr: 8.96826849256196e-06 loss: 0.0286 (0.0306) time: 3.0175 data: 0.0081 max mem: 33408 +Epoch: [34] [ 200/2639] eta: 2:03:22 lr: 8.963108549013586e-06 loss: 0.0312 (0.0308) time: 3.0383 data: 0.0083 max mem: 33408 +Epoch: [34] [ 210/2639] eta: 2:02:50 lr: 8.957948275387232e-06 loss: 0.0283 (0.0306) time: 3.0375 data: 0.0082 max mem: 33408 +Epoch: [34] [ 220/2639] eta: 2:02:21 lr: 8.952787671450498e-06 loss: 0.0274 (0.0307) time: 3.0309 data: 0.0080 max mem: 33408 +Epoch: [34] [ 230/2639] eta: 2:01:52 lr: 8.947626736970648e-06 loss: 0.0285 (0.0306) time: 3.0487 data: 0.0079 max mem: 33408 +Epoch: [34] [ 240/2639] eta: 2:01:23 lr: 8.94246547171466e-06 loss: 0.0271 (0.0308) time: 3.0507 data: 0.0077 max mem: 33408 +Epoch: [34] [ 250/2639] eta: 2:00:53 lr: 8.937303875449161e-06 loss: 0.0289 (0.0307) time: 3.0439 data: 0.0077 max mem: 33408 +Epoch: [34] [ 260/2639] eta: 2:00:25 lr: 8.932141947940505e-06 loss: 0.0297 (0.0313) time: 3.0494 data: 0.0079 max mem: 33408 +Epoch: [34] [ 270/2639] eta: 1:59:44 lr: 8.926979688954694e-06 loss: 0.0288 (0.0312) time: 2.9917 data: 0.0077 max mem: 33408 +Epoch: [34] [ 280/2639] eta: 1:59:15 lr: 8.921817098257446e-06 loss: 0.0271 (0.0312) time: 2.9826 data: 0.0076 max mem: 33408 +Epoch: [34] [ 290/2639] eta: 1:58:46 lr: 8.916654175614133e-06 loss: 0.0296 (0.0313) time: 3.0444 data: 0.0075 max mem: 33408 +Epoch: [34] [ 300/2639] eta: 1:58:18 lr: 8.911490920789836e-06 loss: 0.0313 (0.0313) time: 3.0561 data: 0.0078 max mem: 33408 +Epoch: [34] [ 310/2639] eta: 1:57:41 lr: 8.906327333549296e-06 loss: 0.0322 (0.0314) time: 3.0109 data: 0.0079 max mem: 33408 +Epoch: [34] [ 320/2639] eta: 1:57:12 lr: 8.901163413656962e-06 loss: 0.0266 (0.0313) time: 2.9994 data: 0.0078 max mem: 33408 +Epoch: [34] [ 330/2639] eta: 1:56:41 lr: 8.895999160876932e-06 loss: 0.0261 (0.0313) time: 3.0307 data: 0.0079 max mem: 33408 +Epoch: [34] [ 340/2639] eta: 1:56:09 lr: 8.890834574973015e-06 loss: 0.0286 (0.0312) time: 3.0173 data: 0.0078 max mem: 33408 +Epoch: [34] [ 350/2639] eta: 1:55:36 lr: 8.885669655708673e-06 loss: 0.0305 (0.0313) time: 3.0034 data: 0.0077 max mem: 33408 +Epoch: [34] [ 360/2639] eta: 1:55:05 lr: 8.880504402847072e-06 loss: 0.0293 (0.0313) time: 3.0005 data: 0.0078 max mem: 33408 +Epoch: [34] [ 370/2639] eta: 1:54:33 lr: 8.875338816151038e-06 loss: 0.0275 (0.0312) time: 3.0061 data: 0.0078 max mem: 33408 +Epoch: [34] [ 380/2639] eta: 1:54:05 lr: 8.870172895383079e-06 loss: 0.0296 (0.0312) time: 3.0367 data: 0.0077 max mem: 33408 +Epoch: [34] [ 390/2639] eta: 1:53:32 lr: 8.865006640305395e-06 loss: 0.0276 (0.0311) time: 3.0273 data: 0.0077 max mem: 33408 +Epoch: [34] [ 400/2639] eta: 1:52:57 lr: 8.859840050679838e-06 loss: 0.0264 (0.0310) time: 2.9609 data: 0.0083 max mem: 33408 +Epoch: [34] [ 410/2639] eta: 1:52:27 lr: 8.854673126267958e-06 loss: 0.0289 (0.0310) time: 2.9935 data: 0.0086 max mem: 33408 +Epoch: [34] [ 420/2639] eta: 1:51:57 lr: 8.84950586683096e-06 loss: 0.0303 (0.0310) time: 3.0360 data: 0.0081 max mem: 33408 +Epoch: [34] [ 430/2639] eta: 1:51:25 lr: 8.844338272129746e-06 loss: 0.0300 (0.0310) time: 3.0069 data: 0.0084 max mem: 33408 +Epoch: [34] [ 440/2639] eta: 1:50:55 lr: 8.839170341924868e-06 loss: 0.0300 (0.0310) time: 3.0078 data: 0.0085 max mem: 33408 +Epoch: [34] [ 450/2639] eta: 1:50:24 lr: 8.83400207597658e-06 loss: 0.0301 (0.0311) time: 3.0200 data: 0.0078 max mem: 33408 +Epoch: [34] [ 460/2639] eta: 1:49:55 lr: 8.828833474044773e-06 loss: 0.0314 (0.0313) time: 3.0346 data: 0.0078 max mem: 33408 +Epoch: [34] [ 470/2639] eta: 1:49:25 lr: 8.823664535889046e-06 loss: 0.0316 (0.0313) time: 3.0465 data: 0.0079 max mem: 33408 +Epoch: [34] [ 480/2639] eta: 1:48:57 lr: 8.818495261268642e-06 loss: 0.0308 (0.0314) time: 3.0552 data: 0.0078 max mem: 33408 +Epoch: [34] [ 490/2639] eta: 1:48:27 lr: 8.813325649942495e-06 loss: 0.0322 (0.0316) time: 3.0582 data: 0.0081 max mem: 33408 +Epoch: [34] [ 500/2639] eta: 1:47:57 lr: 8.808155701669188e-06 loss: 0.0333 (0.0317) time: 3.0331 data: 0.0081 max mem: 33408 +Epoch: [34] [ 510/2639] eta: 1:47:27 lr: 8.802985416206997e-06 loss: 0.0305 (0.0316) time: 3.0364 data: 0.0077 max mem: 33408 +Epoch: [34] [ 520/2639] eta: 1:46:58 lr: 8.79781479331384e-06 loss: 0.0306 (0.0316) time: 3.0508 data: 0.0077 max mem: 33408 +Epoch: [34] [ 530/2639] eta: 1:46:26 lr: 8.792643832747336e-06 loss: 0.0306 (0.0316) time: 3.0147 data: 0.0079 max mem: 33408 +Epoch: [34] [ 540/2639] eta: 1:45:54 lr: 8.787472534264734e-06 loss: 0.0259 (0.0316) time: 2.9879 data: 0.0080 max mem: 33408 +Epoch: [34] [ 550/2639] eta: 1:45:26 lr: 8.782300897622987e-06 loss: 0.0259 (0.0318) time: 3.0391 data: 0.0083 max mem: 33408 +Epoch: [34] [ 560/2639] eta: 1:44:54 lr: 8.777128922578677e-06 loss: 0.0344 (0.0318) time: 3.0255 data: 0.0083 max mem: 33408 +Epoch: [34] [ 570/2639] eta: 1:44:23 lr: 8.771956608888087e-06 loss: 0.0320 (0.0318) time: 2.9935 data: 0.0077 max mem: 33408 +Epoch: [34] [ 580/2639] eta: 1:43:50 lr: 8.766783956307132e-06 loss: 0.0295 (0.0319) time: 2.9837 data: 0.0074 max mem: 33408 +Epoch: [34] [ 590/2639] eta: 1:43:18 lr: 8.761610964591423e-06 loss: 0.0309 (0.0320) time: 2.9718 data: 0.0075 max mem: 33408 +Epoch: [34] [ 600/2639] eta: 1:42:48 lr: 8.756437633496201e-06 loss: 0.0309 (0.0320) time: 3.0008 data: 0.0079 max mem: 33408 +Epoch: [34] [ 610/2639] eta: 1:42:17 lr: 8.751263962776402e-06 loss: 0.0297 (0.0320) time: 3.0066 data: 0.0082 max mem: 33408 +Epoch: [34] [ 620/2639] eta: 1:41:45 lr: 8.746089952186593e-06 loss: 0.0297 (0.0323) time: 2.9951 data: 0.0080 max mem: 33408 +Epoch: [34] [ 630/2639] eta: 1:41:13 lr: 8.740915601481027e-06 loss: 0.0323 (0.0324) time: 2.9727 data: 0.0078 max mem: 33408 +Epoch: [34] [ 640/2639] eta: 1:40:44 lr: 8.73574091041361e-06 loss: 0.0323 (0.0324) time: 3.0045 data: 0.0078 max mem: 33408 +Epoch: [34] [ 650/2639] eta: 1:40:13 lr: 8.730565878737899e-06 loss: 0.0337 (0.0325) time: 3.0339 data: 0.0081 max mem: 33408 +Epoch: [34] [ 660/2639] eta: 1:39:43 lr: 8.725390506207125e-06 loss: 0.0280 (0.0325) time: 3.0287 data: 0.0077 max mem: 33408 +Epoch: [34] [ 670/2639] eta: 1:39:14 lr: 8.720214792574158e-06 loss: 0.0308 (0.0325) time: 3.0545 data: 0.0072 max mem: 33408 +Epoch: [34] [ 680/2639] eta: 1:38:44 lr: 8.715038737591552e-06 loss: 0.0281 (0.0324) time: 3.0413 data: 0.0076 max mem: 33408 +Epoch: [34] [ 690/2639] eta: 1:38:13 lr: 8.709862341011486e-06 loss: 0.0293 (0.0324) time: 3.0059 data: 0.0081 max mem: 33408 +Epoch: [34] [ 700/2639] eta: 1:37:42 lr: 8.704685602585829e-06 loss: 0.0304 (0.0324) time: 3.0013 data: 0.0083 max mem: 33408 +Epoch: [34] [ 710/2639] eta: 1:37:13 lr: 8.699508522066078e-06 loss: 0.0327 (0.0325) time: 3.0347 data: 0.0080 max mem: 33408 +Epoch: [34] [ 720/2639] eta: 1:36:44 lr: 8.694331099203403e-06 loss: 0.0318 (0.0324) time: 3.0629 data: 0.0080 max mem: 33408 +Epoch: [34] [ 730/2639] eta: 1:36:13 lr: 8.689153333748613e-06 loss: 0.0268 (0.0323) time: 3.0273 data: 0.0081 max mem: 33408 +Epoch: [34] [ 740/2639] eta: 1:35:42 lr: 8.68397522545219e-06 loss: 0.0277 (0.0323) time: 3.0001 data: 0.0080 max mem: 33408 +Epoch: [34] [ 750/2639] eta: 1:35:13 lr: 8.678796774064247e-06 loss: 0.0277 (0.0323) time: 3.0418 data: 0.0076 max mem: 33408 +Epoch: [34] [ 760/2639] eta: 1:34:43 lr: 8.67361797933457e-06 loss: 0.0297 (0.0324) time: 3.0470 data: 0.0076 max mem: 33408 +Epoch: [34] [ 770/2639] eta: 1:34:11 lr: 8.668438841012575e-06 loss: 0.0336 (0.0324) time: 2.9968 data: 0.0077 max mem: 33408 +Epoch: [34] [ 780/2639] eta: 1:33:42 lr: 8.66325935884735e-06 loss: 0.0305 (0.0323) time: 3.0207 data: 0.0077 max mem: 33408 +Epoch: [34] [ 790/2639] eta: 1:33:13 lr: 8.658079532587614e-06 loss: 0.0288 (0.0324) time: 3.0656 data: 0.0077 max mem: 33408 +Epoch: [34] [ 800/2639] eta: 1:32:43 lr: 8.652899361981753e-06 loss: 0.0300 (0.0324) time: 3.0506 data: 0.0075 max mem: 33408 +Epoch: [34] [ 810/2639] eta: 1:32:12 lr: 8.647718846777783e-06 loss: 0.0322 (0.0324) time: 3.0201 data: 0.0073 max mem: 33408 +Epoch: [34] [ 820/2639] eta: 1:31:41 lr: 8.642537986723387e-06 loss: 0.0349 (0.0325) time: 2.9968 data: 0.0075 max mem: 33408 +Epoch: [34] [ 830/2639] eta: 1:31:08 lr: 8.637356781565873e-06 loss: 0.0349 (0.0325) time: 2.9528 data: 0.0079 max mem: 33408 +Epoch: [34] [ 840/2639] eta: 1:30:38 lr: 8.632175231052221e-06 loss: 0.0305 (0.0325) time: 2.9719 data: 0.0078 max mem: 33408 +Epoch: [34] [ 850/2639] eta: 1:30:09 lr: 8.626993334929031e-06 loss: 0.0336 (0.0326) time: 3.0545 data: 0.0077 max mem: 33408 +Epoch: [34] [ 860/2639] eta: 1:29:38 lr: 8.621811092942572e-06 loss: 0.0336 (0.0326) time: 3.0265 data: 0.0077 max mem: 33408 +Epoch: [34] [ 870/2639] eta: 1:29:06 lr: 8.616628504838733e-06 loss: 0.0296 (0.0326) time: 2.9657 data: 0.0076 max mem: 33408 +Epoch: [34] [ 880/2639] eta: 1:28:36 lr: 8.61144557036306e-06 loss: 0.0296 (0.0326) time: 2.9940 data: 0.0081 max mem: 33408 +Epoch: [34] [ 890/2639] eta: 1:28:07 lr: 8.606262289260754e-06 loss: 0.0347 (0.0327) time: 3.0506 data: 0.0081 max mem: 33408 +Epoch: [34] [ 900/2639] eta: 1:27:37 lr: 8.601078661276626e-06 loss: 0.0297 (0.0327) time: 3.0426 data: 0.0077 max mem: 33408 +Epoch: [34] [ 910/2639] eta: 1:27:06 lr: 8.595894686155162e-06 loss: 0.0284 (0.0327) time: 3.0004 data: 0.0079 max mem: 33408 +Epoch: [34] [ 920/2639] eta: 1:26:36 lr: 8.590710363640458e-06 loss: 0.0291 (0.0327) time: 3.0131 data: 0.0080 max mem: 33408 +Epoch: [34] [ 930/2639] eta: 1:26:06 lr: 8.585525693476275e-06 loss: 0.0302 (0.0327) time: 3.0313 data: 0.0079 max mem: 33408 +Epoch: [34] [ 940/2639] eta: 1:25:36 lr: 8.580340675405992e-06 loss: 0.0307 (0.0328) time: 3.0293 data: 0.0079 max mem: 33408 +Epoch: [34] [ 950/2639] eta: 1:25:06 lr: 8.575155309172649e-06 loss: 0.0290 (0.0327) time: 3.0354 data: 0.0078 max mem: 33408 +Epoch: [34] [ 960/2639] eta: 1:24:36 lr: 8.569969594518896e-06 loss: 0.0259 (0.0327) time: 3.0506 data: 0.0075 max mem: 33408 +Epoch: [34] [ 970/2639] eta: 1:24:07 lr: 8.56478353118705e-06 loss: 0.0304 (0.0327) time: 3.0782 data: 0.0074 max mem: 33408 +Epoch: [34] [ 980/2639] eta: 1:23:36 lr: 8.559597118919032e-06 loss: 0.0311 (0.0327) time: 3.0465 data: 0.0075 max mem: 33408 +Epoch: [34] [ 990/2639] eta: 1:23:06 lr: 8.554410357456428e-06 loss: 0.0303 (0.0327) time: 3.0023 data: 0.0077 max mem: 33408 +Epoch: [34] [1000/2639] eta: 1:22:36 lr: 8.549223246540433e-06 loss: 0.0298 (0.0327) time: 3.0246 data: 0.0079 max mem: 33408 +Epoch: [34] [1010/2639] eta: 1:22:07 lr: 8.544035785911899e-06 loss: 0.0295 (0.0327) time: 3.0804 data: 0.0079 max mem: 33408 +Epoch: [34] [1020/2639] eta: 1:21:36 lr: 8.538847975311285e-06 loss: 0.0292 (0.0327) time: 3.0342 data: 0.0076 max mem: 33408 +Epoch: [34] [1030/2639] eta: 1:21:04 lr: 8.533659814478714e-06 loss: 0.0283 (0.0326) time: 2.9520 data: 0.0074 max mem: 33408 +Epoch: [34] [1040/2639] eta: 1:20:34 lr: 8.528471303153902e-06 loss: 0.0310 (0.0327) time: 2.9857 data: 0.0076 max mem: 33408 +Epoch: [34] [1050/2639] eta: 1:20:04 lr: 8.523282441076235e-06 loss: 0.0302 (0.0327) time: 3.0295 data: 0.0076 max mem: 33408 +Epoch: [34] [1060/2639] eta: 1:19:34 lr: 8.518093227984693e-06 loss: 0.0286 (0.0326) time: 3.0523 data: 0.0076 max mem: 33408 +Epoch: [34] [1070/2639] eta: 1:19:04 lr: 8.512903663617916e-06 loss: 0.0275 (0.0327) time: 3.0253 data: 0.0074 max mem: 33408 +Epoch: [34] [1080/2639] eta: 1:18:32 lr: 8.507713747714145e-06 loss: 0.0306 (0.0327) time: 2.9690 data: 0.0074 max mem: 33408 +Epoch: [34] [1090/2639] eta: 1:18:01 lr: 8.502523480011276e-06 loss: 0.0303 (0.0327) time: 2.9401 data: 0.0073 max mem: 33408 +Epoch: [34] [1100/2639] eta: 1:17:30 lr: 8.4973328602468e-06 loss: 0.0303 (0.0327) time: 2.9552 data: 0.0070 max mem: 33408 +Epoch: [34] [1110/2639] eta: 1:17:00 lr: 8.492141888157859e-06 loss: 0.0274 (0.0327) time: 3.0163 data: 0.0073 max mem: 33408 +Epoch: [34] [1120/2639] eta: 1:16:30 lr: 8.486950563481218e-06 loss: 0.0281 (0.0327) time: 3.0534 data: 0.0074 max mem: 33408 +Epoch: [34] [1130/2639] eta: 1:16:00 lr: 8.481758885953248e-06 loss: 0.0319 (0.0327) time: 3.0157 data: 0.0076 max mem: 33408 +Epoch: [34] [1140/2639] eta: 1:15:29 lr: 8.476566855309965e-06 loss: 0.0358 (0.0327) time: 2.9779 data: 0.0077 max mem: 33408 +Epoch: [34] [1150/2639] eta: 1:14:59 lr: 8.471374471286991e-06 loss: 0.0321 (0.0327) time: 2.9998 data: 0.0079 max mem: 33408 +Epoch: [34] [1160/2639] eta: 1:14:28 lr: 8.466181733619586e-06 loss: 0.0307 (0.0327) time: 3.0178 data: 0.0080 max mem: 33408 +Epoch: [34] [1170/2639] eta: 1:13:57 lr: 8.46098864204261e-06 loss: 0.0289 (0.0327) time: 2.9940 data: 0.0076 max mem: 33408 +Epoch: [34] [1180/2639] eta: 1:13:27 lr: 8.455795196290567e-06 loss: 0.0289 (0.0327) time: 2.9806 data: 0.0078 max mem: 33408 +Epoch: [34] [1190/2639] eta: 1:12:57 lr: 8.450601396097557e-06 loss: 0.0264 (0.0327) time: 3.0223 data: 0.0080 max mem: 33408 +Epoch: [34] [1200/2639] eta: 1:12:27 lr: 8.445407241197324e-06 loss: 0.0261 (0.0326) time: 3.0489 data: 0.0080 max mem: 33408 +Epoch: [34] [1210/2639] eta: 1:11:57 lr: 8.440212731323204e-06 loss: 0.0271 (0.0326) time: 3.0340 data: 0.0078 max mem: 33408 +Epoch: [34] [1220/2639] eta: 1:11:26 lr: 8.435017866208172e-06 loss: 0.0281 (0.0326) time: 2.9967 data: 0.0075 max mem: 33408 +Epoch: [34] [1230/2639] eta: 1:10:56 lr: 8.429822645584801e-06 loss: 0.0278 (0.0326) time: 2.9900 data: 0.0076 max mem: 33408 +Epoch: [34] [1240/2639] eta: 1:10:27 lr: 8.424627069185298e-06 loss: 0.0289 (0.0326) time: 3.0576 data: 0.0078 max mem: 33408 +Epoch: [34] [1250/2639] eta: 1:09:57 lr: 8.419431136741464e-06 loss: 0.0289 (0.0325) time: 3.0744 data: 0.0080 max mem: 33408 +Epoch: [34] [1260/2639] eta: 1:09:27 lr: 8.414234847984734e-06 loss: 0.0245 (0.0325) time: 3.0530 data: 0.0077 max mem: 33408 +Epoch: [34] [1270/2639] eta: 1:08:56 lr: 8.409038202646137e-06 loss: 0.0318 (0.0325) time: 3.0256 data: 0.0075 max mem: 33408 +Epoch: [34] [1280/2639] eta: 1:08:26 lr: 8.403841200456335e-06 loss: 0.0272 (0.0325) time: 3.0020 data: 0.0079 max mem: 33408 +Epoch: [34] [1290/2639] eta: 1:07:56 lr: 8.398643841145577e-06 loss: 0.0279 (0.0325) time: 3.0461 data: 0.0077 max mem: 33408 +Epoch: [34] [1300/2639] eta: 1:07:26 lr: 8.393446124443747e-06 loss: 0.0306 (0.0325) time: 3.0684 data: 0.0074 max mem: 33408 +Epoch: [34] [1310/2639] eta: 1:06:56 lr: 8.388248050080318e-06 loss: 0.0262 (0.0324) time: 3.0383 data: 0.0076 max mem: 33408 +Epoch: [34] [1320/2639] eta: 1:06:26 lr: 8.38304961778439e-06 loss: 0.0271 (0.0324) time: 3.0434 data: 0.0076 max mem: 33408 +Epoch: [34] [1330/2639] eta: 1:05:56 lr: 8.37785082728465e-06 loss: 0.0329 (0.0324) time: 3.0366 data: 0.0072 max mem: 33408 +Epoch: [34] [1340/2639] eta: 1:05:26 lr: 8.372651678309417e-06 loss: 0.0296 (0.0324) time: 3.0274 data: 0.0073 max mem: 33408 +Epoch: [34] [1350/2639] eta: 1:04:57 lr: 8.36745217058659e-06 loss: 0.0263 (0.0324) time: 3.0768 data: 0.0072 max mem: 33408 +Epoch: [34] [1360/2639] eta: 1:04:26 lr: 8.362252303843695e-06 loss: 0.0273 (0.0324) time: 3.0464 data: 0.0073 max mem: 33408 +Epoch: [34] [1370/2639] eta: 1:03:56 lr: 8.357052077807859e-06 loss: 0.0300 (0.0324) time: 3.0086 data: 0.0076 max mem: 33408 +Epoch: [34] [1380/2639] eta: 1:03:25 lr: 8.351851492205795e-06 loss: 0.0289 (0.0324) time: 2.9991 data: 0.0076 max mem: 33408 +Epoch: [34] [1390/2639] eta: 1:02:55 lr: 8.346650546763846e-06 loss: 0.0289 (0.0324) time: 3.0132 data: 0.0076 max mem: 33408 +Epoch: [34] [1400/2639] eta: 1:02:25 lr: 8.34144924120793e-06 loss: 0.0283 (0.0324) time: 3.0407 data: 0.0080 max mem: 33408 +Epoch: [34] [1410/2639] eta: 1:01:54 lr: 8.336247575263592e-06 loss: 0.0264 (0.0324) time: 2.9906 data: 0.0083 max mem: 33408 +Epoch: [34] [1420/2639] eta: 1:01:24 lr: 8.331045548655952e-06 loss: 0.0276 (0.0324) time: 3.0065 data: 0.0080 max mem: 33408 +Epoch: [34] [1430/2639] eta: 1:00:54 lr: 8.325843161109756e-06 loss: 0.0301 (0.0324) time: 3.0624 data: 0.0076 max mem: 33408 +Epoch: [34] [1440/2639] eta: 1:00:24 lr: 8.32064041234932e-06 loss: 0.0297 (0.0324) time: 3.0341 data: 0.0075 max mem: 33408 +Epoch: [34] [1450/2639] eta: 0:59:54 lr: 8.315437302098588e-06 loss: 0.0282 (0.0324) time: 3.0199 data: 0.0074 max mem: 33408 +Epoch: [34] [1460/2639] eta: 0:59:24 lr: 8.31023383008107e-06 loss: 0.0287 (0.0323) time: 3.0374 data: 0.0075 max mem: 33408 +Epoch: [34] [1470/2639] eta: 0:58:54 lr: 8.305029996019902e-06 loss: 0.0302 (0.0323) time: 3.0518 data: 0.0075 max mem: 33408 +Epoch: [34] [1480/2639] eta: 0:58:24 lr: 8.299825799637786e-06 loss: 0.0269 (0.0323) time: 3.0581 data: 0.0076 max mem: 33408 +Epoch: [34] [1490/2639] eta: 0:57:54 lr: 8.294621240657049e-06 loss: 0.0282 (0.0323) time: 3.0388 data: 0.0076 max mem: 33408 +Epoch: [34] [1500/2639] eta: 0:57:24 lr: 8.289416318799582e-06 loss: 0.0289 (0.0323) time: 3.0393 data: 0.0074 max mem: 33408 +Epoch: [34] [1510/2639] eta: 0:56:53 lr: 8.284211033786894e-06 loss: 0.0273 (0.0323) time: 2.9885 data: 0.0076 max mem: 33408 +Epoch: [34] [1520/2639] eta: 0:56:23 lr: 8.279005385340059e-06 loss: 0.0273 (0.0323) time: 2.9830 data: 0.0080 max mem: 33408 +Epoch: [34] [1530/2639] eta: 0:55:52 lr: 8.273799373179771e-06 loss: 0.0303 (0.0323) time: 3.0365 data: 0.0078 max mem: 33408 +Epoch: [34] [1540/2639] eta: 0:55:23 lr: 8.268592997026287e-06 loss: 0.0287 (0.0323) time: 3.0602 data: 0.0078 max mem: 33408 +Epoch: [34] [1550/2639] eta: 0:54:53 lr: 8.263386256599478e-06 loss: 0.0299 (0.0322) time: 3.0694 data: 0.0077 max mem: 33408 +Epoch: [34] [1560/2639] eta: 0:54:22 lr: 8.258179151618776e-06 loss: 0.0299 (0.0322) time: 3.0484 data: 0.0076 max mem: 33408 +Epoch: [34] [1570/2639] eta: 0:53:52 lr: 8.25297168180323e-06 loss: 0.0290 (0.0322) time: 3.0123 data: 0.0081 max mem: 33408 +Epoch: [34] [1580/2639] eta: 0:53:22 lr: 8.247763846871443e-06 loss: 0.0286 (0.0322) time: 3.0450 data: 0.0082 max mem: 33408 +Epoch: [34] [1590/2639] eta: 0:52:52 lr: 8.242555646541636e-06 loss: 0.0302 (0.0322) time: 3.0378 data: 0.0082 max mem: 33408 +Epoch: [34] [1600/2639] eta: 0:52:21 lr: 8.237347080531586e-06 loss: 0.0309 (0.0322) time: 2.9487 data: 0.0087 max mem: 33408 +Epoch: [34] [1610/2639] eta: 0:51:51 lr: 8.232138148558672e-06 loss: 0.0281 (0.0322) time: 2.9898 data: 0.0085 max mem: 33408 +Epoch: [34] [1620/2639] eta: 0:51:20 lr: 8.226928850339858e-06 loss: 0.0265 (0.0322) time: 3.0328 data: 0.0077 max mem: 33408 +Epoch: [34] [1630/2639] eta: 0:50:50 lr: 8.221719185591668e-06 loss: 0.0265 (0.0322) time: 3.0054 data: 0.0078 max mem: 33408 +Epoch: [34] [1640/2639] eta: 0:50:20 lr: 8.216509154030232e-06 loss: 0.0323 (0.0322) time: 2.9888 data: 0.0079 max mem: 33408 +Epoch: [34] [1650/2639] eta: 0:49:50 lr: 8.211298755371236e-06 loss: 0.0264 (0.0322) time: 3.0428 data: 0.0080 max mem: 33408 +Epoch: [34] [1660/2639] eta: 0:49:20 lr: 8.206087989329975e-06 loss: 0.0266 (0.0322) time: 3.0858 data: 0.0082 max mem: 33408 +Epoch: [34] [1670/2639] eta: 0:48:49 lr: 8.200876855621286e-06 loss: 0.0327 (0.0322) time: 3.0358 data: 0.0079 max mem: 33408 +Epoch: [34] [1680/2639] eta: 0:48:20 lr: 8.19566535395962e-06 loss: 0.0314 (0.0322) time: 3.0443 data: 0.0079 max mem: 33408 +Epoch: [34] [1690/2639] eta: 0:47:49 lr: 8.190453484058969e-06 loss: 0.0264 (0.0322) time: 3.0619 data: 0.0080 max mem: 33408 +Epoch: [34] [1700/2639] eta: 0:47:19 lr: 8.185241245632932e-06 loss: 0.0258 (0.0322) time: 3.0311 data: 0.0078 max mem: 33408 +Epoch: [34] [1710/2639] eta: 0:46:49 lr: 8.18002863839466e-06 loss: 0.0288 (0.0322) time: 3.0391 data: 0.0077 max mem: 33408 +Epoch: [34] [1720/2639] eta: 0:46:19 lr: 8.174815662056889e-06 loss: 0.0283 (0.0322) time: 3.0061 data: 0.0076 max mem: 33408 +Epoch: [34] [1730/2639] eta: 0:45:48 lr: 8.16960231633192e-06 loss: 0.0288 (0.0322) time: 2.9572 data: 0.0076 max mem: 33408 +Epoch: [34] [1740/2639] eta: 0:45:17 lr: 8.164388600931636e-06 loss: 0.0311 (0.0322) time: 2.9546 data: 0.0076 max mem: 33408 +Epoch: [34] [1750/2639] eta: 0:44:47 lr: 8.159174515567476e-06 loss: 0.0343 (0.0322) time: 2.9383 data: 0.0077 max mem: 33408 +Epoch: [34] [1760/2639] eta: 0:44:17 lr: 8.153960059950467e-06 loss: 0.0282 (0.0322) time: 2.9916 data: 0.0078 max mem: 33408 +Epoch: [34] [1770/2639] eta: 0:43:47 lr: 8.148745233791183e-06 loss: 0.0280 (0.0322) time: 3.0719 data: 0.0080 max mem: 33408 +Epoch: [34] [1780/2639] eta: 0:43:16 lr: 8.143530036799792e-06 loss: 0.0275 (0.0322) time: 3.0587 data: 0.0082 max mem: 33408 +Epoch: [34] [1790/2639] eta: 0:42:46 lr: 8.138314468685998e-06 loss: 0.0304 (0.0321) time: 3.0560 data: 0.0077 max mem: 33408 +Epoch: [34] [1800/2639] eta: 0:42:16 lr: 8.133098529159103e-06 loss: 0.0304 (0.0322) time: 3.0785 data: 0.0077 max mem: 33408 +Epoch: [34] [1810/2639] eta: 0:41:46 lr: 8.127882217927943e-06 loss: 0.0270 (0.0322) time: 3.0277 data: 0.0078 max mem: 33408 +Epoch: [34] [1820/2639] eta: 0:41:15 lr: 8.12266553470095e-06 loss: 0.0300 (0.0322) time: 2.9640 data: 0.0078 max mem: 33408 +Epoch: [34] [1830/2639] eta: 0:40:45 lr: 8.117448479186085e-06 loss: 0.0308 (0.0322) time: 2.9962 data: 0.0078 max mem: 33408 +Epoch: [34] [1840/2639] eta: 0:40:15 lr: 8.112231051090903e-06 loss: 0.0287 (0.0321) time: 3.0233 data: 0.0075 max mem: 33408 +Epoch: [34] [1850/2639] eta: 0:39:45 lr: 8.107013250122493e-06 loss: 0.0278 (0.0321) time: 3.0357 data: 0.0074 max mem: 33408 +Epoch: [34] [1860/2639] eta: 0:39:15 lr: 8.101795075987523e-06 loss: 0.0274 (0.0321) time: 3.0344 data: 0.0074 max mem: 33408 +Epoch: [34] [1870/2639] eta: 0:38:44 lr: 8.09657652839222e-06 loss: 0.0304 (0.0321) time: 3.0184 data: 0.0074 max mem: 33408 +Epoch: [34] [1880/2639] eta: 0:38:14 lr: 8.091357607042346e-06 loss: 0.0312 (0.0321) time: 2.9901 data: 0.0077 max mem: 33408 +Epoch: [34] [1890/2639] eta: 0:37:44 lr: 8.086138311643256e-06 loss: 0.0292 (0.0321) time: 2.9864 data: 0.0079 max mem: 33408 +Epoch: [34] [1900/2639] eta: 0:37:14 lr: 8.080918641899826e-06 loss: 0.0304 (0.0321) time: 3.0457 data: 0.0077 max mem: 33408 +Epoch: [34] [1910/2639] eta: 0:36:43 lr: 8.075698597516515e-06 loss: 0.0285 (0.0321) time: 3.0510 data: 0.0077 max mem: 33408 +Epoch: [34] [1920/2639] eta: 0:36:13 lr: 8.070478178197314e-06 loss: 0.0279 (0.0321) time: 3.0486 data: 0.0076 max mem: 33408 +Epoch: [34] [1930/2639] eta: 0:35:43 lr: 8.06525738364579e-06 loss: 0.0279 (0.0321) time: 3.0423 data: 0.0078 max mem: 33408 +Epoch: [34] [1940/2639] eta: 0:35:13 lr: 8.060036213565037e-06 loss: 0.0284 (0.0321) time: 3.0382 data: 0.0079 max mem: 33408 +Epoch: [34] [1950/2639] eta: 0:34:43 lr: 8.054814667657725e-06 loss: 0.0296 (0.0321) time: 3.0446 data: 0.0079 max mem: 33408 +Epoch: [34] [1960/2639] eta: 0:34:13 lr: 8.04959274562605e-06 loss: 0.0301 (0.0321) time: 3.0234 data: 0.0079 max mem: 33408 +Epoch: [34] [1970/2639] eta: 0:33:42 lr: 8.044370447171783e-06 loss: 0.0301 (0.0321) time: 2.9961 data: 0.0076 max mem: 33408 +Epoch: [34] [1980/2639] eta: 0:33:12 lr: 8.039147771996215e-06 loss: 0.0290 (0.0321) time: 3.0017 data: 0.0075 max mem: 33408 +Epoch: [34] [1990/2639] eta: 0:32:41 lr: 8.033924719800213e-06 loss: 0.0295 (0.0321) time: 2.9905 data: 0.0075 max mem: 33408 +Epoch: [34] [2000/2639] eta: 0:32:11 lr: 8.028701290284164e-06 loss: 0.0302 (0.0321) time: 2.9760 data: 0.0079 max mem: 33408 +Epoch: [34] [2010/2639] eta: 0:31:41 lr: 8.023477483148026e-06 loss: 0.0313 (0.0321) time: 3.0030 data: 0.0082 max mem: 33408 +Epoch: [34] [2020/2639] eta: 0:31:10 lr: 8.018253298091271e-06 loss: 0.0266 (0.0321) time: 2.9691 data: 0.0082 max mem: 33408 +Epoch: [34] [2030/2639] eta: 0:30:40 lr: 8.013028734812946e-06 loss: 0.0251 (0.0321) time: 2.9850 data: 0.0082 max mem: 33408 +Epoch: [34] [2040/2639] eta: 0:30:10 lr: 8.007803793011611e-06 loss: 0.0282 (0.0321) time: 3.0498 data: 0.0078 max mem: 33408 +Epoch: [34] [2050/2639] eta: 0:29:40 lr: 8.002578472385394e-06 loss: 0.0310 (0.0321) time: 3.0004 data: 0.0078 max mem: 33408 +Epoch: [34] [2060/2639] eta: 0:29:10 lr: 7.997352772631936e-06 loss: 0.0268 (0.0321) time: 3.0127 data: 0.0080 max mem: 33408 +Epoch: [34] [2070/2639] eta: 0:28:39 lr: 7.992126693448442e-06 loss: 0.0252 (0.0321) time: 3.0756 data: 0.0078 max mem: 33408 +Epoch: [34] [2080/2639] eta: 0:28:09 lr: 7.986900234531635e-06 loss: 0.0304 (0.0321) time: 3.0390 data: 0.0078 max mem: 33408 +Epoch: [34] [2090/2639] eta: 0:27:39 lr: 7.981673395577795e-06 loss: 0.0332 (0.0321) time: 3.0468 data: 0.0078 max mem: 33408 +Epoch: [34] [2100/2639] eta: 0:27:09 lr: 7.976446176282711e-06 loss: 0.0322 (0.0321) time: 3.0229 data: 0.0075 max mem: 33408 +Epoch: [34] [2110/2639] eta: 0:26:39 lr: 7.971218576341729e-06 loss: 0.0305 (0.0321) time: 2.9972 data: 0.0073 max mem: 33408 +Epoch: [34] [2120/2639] eta: 0:26:09 lr: 7.965990595449732e-06 loss: 0.0313 (0.0321) time: 3.0824 data: 0.0075 max mem: 33408 +Epoch: [34] [2130/2639] eta: 0:25:38 lr: 7.96076223330111e-06 loss: 0.0283 (0.0321) time: 3.0766 data: 0.0077 max mem: 33408 +Epoch: [34] [2140/2639] eta: 0:25:08 lr: 7.955533489589813e-06 loss: 0.0283 (0.0321) time: 3.0642 data: 0.0079 max mem: 33408 +Epoch: [34] [2150/2639] eta: 0:24:38 lr: 7.950304364009297e-06 loss: 0.0284 (0.0321) time: 3.1146 data: 0.0077 max mem: 33408 +Epoch: [34] [2160/2639] eta: 0:24:08 lr: 7.94507485625257e-06 loss: 0.0284 (0.0321) time: 3.1112 data: 0.0075 max mem: 33408 +Epoch: [34] [2170/2639] eta: 0:23:38 lr: 7.93984496601215e-06 loss: 0.0283 (0.0321) time: 3.0822 data: 0.0075 max mem: 33408 +Epoch: [34] [2180/2639] eta: 0:23:08 lr: 7.934614692980099e-06 loss: 0.0307 (0.0321) time: 3.0495 data: 0.0075 max mem: 33408 +Epoch: [34] [2190/2639] eta: 0:22:38 lr: 7.929384036847985e-06 loss: 0.0328 (0.0321) time: 3.0351 data: 0.0080 max mem: 33408 +Epoch: [34] [2200/2639] eta: 0:22:07 lr: 7.924152997306926e-06 loss: 0.0248 (0.0320) time: 3.0402 data: 0.0081 max mem: 33408 +Epoch: [34] [2210/2639] eta: 0:21:37 lr: 7.918921574047539e-06 loss: 0.0246 (0.0320) time: 3.0322 data: 0.0079 max mem: 33408 +Epoch: [34] [2220/2639] eta: 0:21:07 lr: 7.913689766759987e-06 loss: 0.0271 (0.0320) time: 3.0326 data: 0.0081 max mem: 33408 +Epoch: [34] [2230/2639] eta: 0:20:37 lr: 7.908457575133933e-06 loss: 0.0273 (0.0320) time: 3.0135 data: 0.0084 max mem: 33408 +Epoch: [34] [2240/2639] eta: 0:20:06 lr: 7.903224998858583e-06 loss: 0.0268 (0.0320) time: 2.9936 data: 0.0083 max mem: 33408 +Epoch: [34] [2250/2639] eta: 0:19:36 lr: 7.897992037622643e-06 loss: 0.0278 (0.0320) time: 3.0612 data: 0.0078 max mem: 33408 +Epoch: [34] [2260/2639] eta: 0:19:06 lr: 7.892758691114353e-06 loss: 0.0305 (0.0320) time: 3.0872 data: 0.0077 max mem: 33408 +Epoch: [34] [2270/2639] eta: 0:18:36 lr: 7.887524959021458e-06 loss: 0.0266 (0.0320) time: 3.0562 data: 0.0081 max mem: 33408 +Epoch: [34] [2280/2639] eta: 0:18:06 lr: 7.882290841031236e-06 loss: 0.0283 (0.0320) time: 3.0781 data: 0.0081 max mem: 33408 +Epoch: [34] [2290/2639] eta: 0:17:35 lr: 7.877056336830455e-06 loss: 0.0287 (0.0320) time: 3.0411 data: 0.0078 max mem: 33408 +Epoch: [34] [2300/2639] eta: 0:17:05 lr: 7.871821446105428e-06 loss: 0.0303 (0.0320) time: 2.9902 data: 0.0080 max mem: 33408 +Epoch: [34] [2310/2639] eta: 0:16:35 lr: 7.866586168541954e-06 loss: 0.0253 (0.0319) time: 3.0470 data: 0.0082 max mem: 33408 +Epoch: [34] [2320/2639] eta: 0:16:05 lr: 7.861350503825364e-06 loss: 0.0261 (0.0319) time: 3.0677 data: 0.0079 max mem: 33408 +Epoch: [34] [2330/2639] eta: 0:15:34 lr: 7.856114451640482e-06 loss: 0.0312 (0.0320) time: 3.0481 data: 0.0079 max mem: 33408 +Epoch: [34] [2340/2639] eta: 0:15:04 lr: 7.850878011671665e-06 loss: 0.0285 (0.0320) time: 3.0638 data: 0.0083 max mem: 33408 +Epoch: [34] [2350/2639] eta: 0:14:34 lr: 7.84564118360275e-06 loss: 0.0258 (0.0320) time: 3.0583 data: 0.0082 max mem: 33408 +Epoch: [34] [2360/2639] eta: 0:14:04 lr: 7.840403967117105e-06 loss: 0.0269 (0.0320) time: 3.0774 data: 0.0081 max mem: 33408 +Epoch: [34] [2370/2639] eta: 0:13:34 lr: 7.835166361897601e-06 loss: 0.0328 (0.0320) time: 3.1017 data: 0.0081 max mem: 33408 +Epoch: [34] [2380/2639] eta: 0:13:03 lr: 7.8299283676266e-06 loss: 0.0311 (0.0320) time: 3.0655 data: 0.0079 max mem: 33408 +Epoch: [34] [2390/2639] eta: 0:12:33 lr: 7.824689983985986e-06 loss: 0.0271 (0.0320) time: 3.0244 data: 0.0083 max mem: 33408 +Epoch: [34] [2400/2639] eta: 0:12:03 lr: 7.819451210657129e-06 loss: 0.0292 (0.0320) time: 2.9954 data: 0.0084 max mem: 33408 +Epoch: [34] [2410/2639] eta: 0:11:33 lr: 7.814212047320919e-06 loss: 0.0276 (0.0320) time: 3.0350 data: 0.0079 max mem: 33408 +Epoch: [34] [2420/2639] eta: 0:11:02 lr: 7.808972493657726e-06 loss: 0.0255 (0.0320) time: 3.0636 data: 0.0077 max mem: 33408 +Epoch: [34] [2430/2639] eta: 0:10:32 lr: 7.803732549347445e-06 loss: 0.0257 (0.0319) time: 2.9811 data: 0.0076 max mem: 33408 +Epoch: [34] [2440/2639] eta: 0:10:02 lr: 7.79849221406944e-06 loss: 0.0285 (0.0319) time: 2.9851 data: 0.0080 max mem: 33408 +Epoch: [34] [2450/2639] eta: 0:09:32 lr: 7.793251487502603e-06 loss: 0.0306 (0.0319) time: 3.0932 data: 0.0086 max mem: 33408 +Epoch: [34] [2460/2639] eta: 0:09:01 lr: 7.78801036932529e-06 loss: 0.0306 (0.0320) time: 3.0750 data: 0.0085 max mem: 33408 +Epoch: [34] [2470/2639] eta: 0:08:31 lr: 7.782768859215387e-06 loss: 0.0295 (0.0319) time: 3.0071 data: 0.0079 max mem: 33408 +Epoch: [34] [2480/2639] eta: 0:08:01 lr: 7.777526956850238e-06 loss: 0.0288 (0.0319) time: 3.0387 data: 0.0078 max mem: 33408 +Epoch: [34] [2490/2639] eta: 0:07:30 lr: 7.77228466190671e-06 loss: 0.0288 (0.0319) time: 3.0290 data: 0.0082 max mem: 33408 +Epoch: [34] [2500/2639] eta: 0:07:00 lr: 7.767041974061137e-06 loss: 0.0270 (0.0319) time: 3.0036 data: 0.0081 max mem: 33408 +Epoch: [34] [2510/2639] eta: 0:06:30 lr: 7.761798892989367e-06 loss: 0.0270 (0.0319) time: 3.0284 data: 0.0077 max mem: 33408 +Epoch: [34] [2520/2639] eta: 0:06:00 lr: 7.756555418366713e-06 loss: 0.0270 (0.0320) time: 3.0516 data: 0.0076 max mem: 33408 +Epoch: [34] [2530/2639] eta: 0:05:29 lr: 7.751311549867997e-06 loss: 0.0260 (0.0320) time: 3.0221 data: 0.0075 max mem: 33408 +Epoch: [34] [2540/2639] eta: 0:04:59 lr: 7.746067287167508e-06 loss: 0.0297 (0.0320) time: 2.9901 data: 0.0075 max mem: 33408 +Epoch: [34] [2550/2639] eta: 0:04:29 lr: 7.740822629939042e-06 loss: 0.0301 (0.0320) time: 3.0441 data: 0.0077 max mem: 33408 +Epoch: [34] [2560/2639] eta: 0:03:59 lr: 7.735577577855853e-06 loss: 0.0308 (0.0320) time: 3.0495 data: 0.0077 max mem: 33408 +Epoch: [34] [2570/2639] eta: 0:03:28 lr: 7.730332130590709e-06 loss: 0.0308 (0.0320) time: 3.0296 data: 0.0079 max mem: 33408 +Epoch: [34] [2580/2639] eta: 0:02:58 lr: 7.72508628781583e-06 loss: 0.0330 (0.0320) time: 3.0061 data: 0.0079 max mem: 33408 +Epoch: [34] [2590/2639] eta: 0:02:28 lr: 7.719840049202936e-06 loss: 0.0303 (0.0320) time: 2.9962 data: 0.0074 max mem: 33408 +Epoch: [34] [2600/2639] eta: 0:01:58 lr: 7.714593414423226e-06 loss: 0.0274 (0.0320) time: 3.0074 data: 0.0077 max mem: 33408 +Epoch: [34] [2610/2639] eta: 0:01:27 lr: 7.709346383147361e-06 loss: 0.0298 (0.0320) time: 3.0078 data: 0.0080 max mem: 33408 +Epoch: [34] [2620/2639] eta: 0:00:57 lr: 7.7040989550455e-06 loss: 0.0337 (0.0320) time: 3.0592 data: 0.0079 max mem: 33408 +Epoch: [34] [2630/2639] eta: 0:00:27 lr: 7.698851129787256e-06 loss: 0.0329 (0.0321) time: 3.0446 data: 0.0077 max mem: 33408 +Epoch: [34] Total time: 2:13:07 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 2:22:03 time: 3.3128 data: 3.2265 max mem: 33408 +Test: [ 100/2573] eta: 0:04:49 time: 0.0790 data: 0.0014 max mem: 33408 +Test: [ 200/2573] eta: 0:03:56 time: 0.0810 data: 0.0014 max mem: 33408 +Test: [ 300/2573] eta: 0:03:30 time: 0.0817 data: 0.0015 max mem: 33408 +Test: [ 400/2573] eta: 0:03:14 time: 0.0826 data: 0.0014 max mem: 33408 +Test: [ 500/2573] eta: 0:03:02 time: 0.0810 data: 0.0015 max mem: 33408 +Test: [ 600/2573] eta: 0:02:51 time: 0.0816 data: 0.0014 max mem: 33408 +Test: [ 700/2573] eta: 0:02:42 time: 0.0817 data: 0.0015 max mem: 33408 +Test: [ 800/2573] eta: 0:02:32 time: 0.0842 data: 0.0014 max mem: 33408 +Test: [ 900/2573] eta: 0:02:23 time: 0.0817 data: 0.0015 max mem: 33408 +Test: [1000/2573] eta: 0:02:14 time: 0.0821 data: 0.0015 max mem: 33408 +Test: [1100/2573] eta: 0:02:05 time: 0.0809 data: 0.0014 max mem: 33408 +Test: [1200/2573] eta: 0:01:56 time: 0.0813 data: 0.0013 max mem: 33408 +Test: [1300/2573] eta: 0:01:47 time: 0.0817 data: 0.0014 max mem: 33408 +Test: [1400/2573] eta: 0:01:38 time: 0.0808 data: 0.0016 max mem: 33408 +Test: [1500/2573] eta: 0:01:30 time: 0.0806 data: 0.0015 max mem: 33408 +Test: [1600/2573] eta: 0:01:21 time: 0.0843 data: 0.0014 max mem: 33408 +Test: [1700/2573] eta: 0:01:13 time: 0.0794 data: 0.0014 max mem: 33408 +Test: [1800/2573] eta: 0:01:04 time: 0.0833 data: 0.0017 max mem: 33408 +Test: [1900/2573] eta: 0:00:56 time: 0.0788 data: 0.0014 max mem: 33408 +Test: [2000/2573] eta: 0:00:47 time: 0.0808 data: 0.0014 max mem: 33408 +Test: [2100/2573] eta: 0:00:39 time: 0.0827 data: 0.0014 max mem: 33408 +Test: [2200/2573] eta: 0:00:30 time: 0.0831 data: 0.0015 max mem: 33408 +Test: [2300/2573] eta: 0:00:22 time: 0.0829 data: 0.0016 max mem: 33408 +Test: [2400/2573] eta: 0:00:14 time: 0.0789 data: 0.0014 max mem: 33408 +Test: [2500/2573] eta: 0:00:06 time: 0.0813 data: 0.0015 max mem: 33408 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: Total time: 0:03:34 +Final results: +Mean IoU is 65.12 + + precision@0.5 = 73.10 + precision@0.6 = 67.79 + precision@0.7 = 61.05 + precision@0.8 = 50.61 + precision@0.9 = 25.49 + overall IoU = 62.53 + +Average object IoU 65.11766165160518 +Overall IoU 62.52547073364258 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [35] [ 0/2639] eta: 4:00:24 lr: 7.694127747212657e-06 loss: 0.0266 (0.0266) time: 5.4658 data: 2.1518 max mem: 33408 +Epoch: [35] [ 10/2639] eta: 2:21:41 lr: 7.688879166445238e-06 loss: 0.0288 (0.0294) time: 3.2337 data: 0.2018 max mem: 33408 +Epoch: [35] [ 20/2639] eta: 2:16:43 lr: 7.68363018756037e-06 loss: 0.0305 (0.0303) time: 3.0156 data: 0.0072 max mem: 33408 +Epoch: [35] [ 30/2639] eta: 2:15:43 lr: 7.678380810225635e-06 loss: 0.0305 (0.0329) time: 3.0598 data: 0.0079 max mem: 33408 +Epoch: [35] [ 40/2639] eta: 2:14:24 lr: 7.673131034108056e-06 loss: 0.0291 (0.0320) time: 3.0724 data: 0.0080 max mem: 33408 +Epoch: [35] [ 50/2639] eta: 2:13:26 lr: 7.667880858874153e-06 loss: 0.0280 (0.0319) time: 3.0476 data: 0.0077 max mem: 33408 +Epoch: [35] [ 60/2639] eta: 2:12:52 lr: 7.662630284189888e-06 loss: 0.0265 (0.0319) time: 3.0671 data: 0.0076 max mem: 33408 +Epoch: [35] [ 70/2639] eta: 2:11:27 lr: 7.657379309720712e-06 loss: 0.0271 (0.0317) time: 3.0140 data: 0.0075 max mem: 33408 +Epoch: [35] [ 80/2639] eta: 2:10:33 lr: 7.652127935131516e-06 loss: 0.0270 (0.0312) time: 2.9688 data: 0.0078 max mem: 33408 +Epoch: [35] [ 90/2639] eta: 2:09:49 lr: 7.64687616008668e-06 loss: 0.0270 (0.0310) time: 3.0043 data: 0.0085 max mem: 33408 +Epoch: [35] [ 100/2639] eta: 2:09:10 lr: 7.64162398425002e-06 loss: 0.0285 (0.0307) time: 3.0182 data: 0.0085 max mem: 33408 +Epoch: [35] [ 110/2639] eta: 2:08:50 lr: 7.63637140728484e-06 loss: 0.0318 (0.0315) time: 3.0612 data: 0.0082 max mem: 33408 +Epoch: [35] [ 120/2639] eta: 2:08:21 lr: 7.631118428853874e-06 loss: 0.0295 (0.0310) time: 3.0823 data: 0.0078 max mem: 33408 +Epoch: [35] [ 130/2639] eta: 2:07:36 lr: 7.6258650486193475e-06 loss: 0.0274 (0.0309) time: 3.0221 data: 0.0076 max mem: 33408 +Epoch: [35] [ 140/2639] eta: 2:06:59 lr: 7.620611266242908e-06 loss: 0.0302 (0.0309) time: 2.9987 data: 0.0078 max mem: 33408 +Epoch: [35] [ 150/2639] eta: 2:06:26 lr: 7.615357081385692e-06 loss: 0.0296 (0.0310) time: 3.0256 data: 0.0079 max mem: 33408 +Epoch: [35] [ 160/2639] eta: 2:05:45 lr: 7.610102493708262e-06 loss: 0.0298 (0.0311) time: 3.0062 data: 0.0077 max mem: 33408 +Epoch: [35] [ 170/2639] eta: 2:05:01 lr: 7.604847502870654e-06 loss: 0.0287 (0.0311) time: 2.9624 data: 0.0076 max mem: 33408 +Epoch: [35] [ 180/2639] eta: 2:04:18 lr: 7.599592108532341e-06 loss: 0.0285 (0.0310) time: 2.9474 data: 0.0078 max mem: 33408 +Epoch: [35] [ 190/2639] eta: 2:03:48 lr: 7.594336310352264e-06 loss: 0.0296 (0.0311) time: 2.9931 data: 0.0077 max mem: 33408 +Epoch: [35] [ 200/2639] eta: 2:03:27 lr: 7.58908010798879e-06 loss: 0.0322 (0.0311) time: 3.0728 data: 0.0077 max mem: 33408 +Epoch: [35] [ 210/2639] eta: 2:03:01 lr: 7.583823501099758e-06 loss: 0.0311 (0.0311) time: 3.0898 data: 0.0079 max mem: 33408 +Epoch: [35] [ 220/2639] eta: 2:02:27 lr: 7.578566489342433e-06 loss: 0.0311 (0.0312) time: 3.0419 data: 0.0078 max mem: 33408 +Epoch: [35] [ 230/2639] eta: 2:01:49 lr: 7.5733090723735355e-06 loss: 0.0299 (0.0311) time: 2.9893 data: 0.0076 max mem: 33408 +Epoch: [35] [ 240/2639] eta: 2:01:16 lr: 7.5680512498492396e-06 loss: 0.0256 (0.0311) time: 2.9828 data: 0.0075 max mem: 33408 +Epoch: [35] [ 250/2639] eta: 2:00:37 lr: 7.562793021425135e-06 loss: 0.0314 (0.0315) time: 2.9725 data: 0.0079 max mem: 33408 +Epoch: [35] [ 260/2639] eta: 2:00:06 lr: 7.557534386756284e-06 loss: 0.0293 (0.0313) time: 2.9826 data: 0.0079 max mem: 33408 +Epoch: [35] [ 270/2639] eta: 1:59:34 lr: 7.552275345497159e-06 loss: 0.0271 (0.0313) time: 3.0167 data: 0.0079 max mem: 33408 +Epoch: [35] [ 280/2639] eta: 1:59:07 lr: 7.5470158973017e-06 loss: 0.0297 (0.0317) time: 3.0375 data: 0.0079 max mem: 33408 +Epoch: [35] [ 290/2639] eta: 1:58:35 lr: 7.541756041823255e-06 loss: 0.0297 (0.0316) time: 3.0363 data: 0.0077 max mem: 33408 +Epoch: [35] [ 300/2639] eta: 1:58:03 lr: 7.536495778714636e-06 loss: 0.0284 (0.0315) time: 3.0083 data: 0.0080 max mem: 33408 +Epoch: [35] [ 310/2639] eta: 1:57:33 lr: 7.531235107628065e-06 loss: 0.0277 (0.0314) time: 3.0224 data: 0.0081 max mem: 33408 +Epoch: [35] [ 320/2639] eta: 1:57:06 lr: 7.525974028215218e-06 loss: 0.0286 (0.0314) time: 3.0522 data: 0.0077 max mem: 33408 +Epoch: [35] [ 330/2639] eta: 1:56:38 lr: 7.520712540127184e-06 loss: 0.0270 (0.0313) time: 3.0675 data: 0.0075 max mem: 33408 +Epoch: [35] [ 340/2639] eta: 1:56:11 lr: 7.5154506430145004e-06 loss: 0.0263 (0.0311) time: 3.0756 data: 0.0083 max mem: 33408 +Epoch: [35] [ 350/2639] eta: 1:55:38 lr: 7.510188336527114e-06 loss: 0.0282 (0.0312) time: 3.0330 data: 0.0089 max mem: 33408 +Epoch: [35] [ 360/2639] eta: 1:55:11 lr: 7.504925620314422e-06 loss: 0.0326 (0.0313) time: 3.0335 data: 0.0081 max mem: 33408 +Epoch: [35] [ 370/2639] eta: 1:54:40 lr: 7.499662494025222e-06 loss: 0.0276 (0.0311) time: 3.0534 data: 0.0079 max mem: 33408 +Epoch: [35] [ 380/2639] eta: 1:54:09 lr: 7.494398957307766e-06 loss: 0.0288 (0.0312) time: 3.0247 data: 0.0084 max mem: 33408 +Epoch: [35] [ 390/2639] eta: 1:53:38 lr: 7.4891350098096985e-06 loss: 0.0293 (0.0312) time: 3.0177 data: 0.0083 max mem: 33408 +Epoch: [35] [ 400/2639] eta: 1:53:09 lr: 7.483870651178114e-06 loss: 0.0272 (0.0311) time: 3.0407 data: 0.0081 max mem: 33408 +Epoch: [35] [ 410/2639] eta: 1:52:36 lr: 7.478605881059504e-06 loss: 0.0307 (0.0312) time: 3.0275 data: 0.0075 max mem: 33408 +Epoch: [35] [ 420/2639] eta: 1:52:08 lr: 7.473340699099801e-06 loss: 0.0320 (0.0313) time: 3.0260 data: 0.0077 max mem: 33408 +Epoch: [35] [ 430/2639] eta: 1:51:37 lr: 7.468075104944334e-06 loss: 0.0296 (0.0313) time: 3.0399 data: 0.0079 max mem: 33408 +Epoch: [35] [ 440/2639] eta: 1:51:08 lr: 7.46280909823787e-06 loss: 0.0273 (0.0312) time: 3.0335 data: 0.0080 max mem: 33408 +Epoch: [35] [ 450/2639] eta: 1:50:39 lr: 7.45754267862457e-06 loss: 0.0305 (0.0314) time: 3.0590 data: 0.0080 max mem: 33408 +Epoch: [35] [ 460/2639] eta: 1:50:08 lr: 7.4522758457480285e-06 loss: 0.0296 (0.0313) time: 3.0425 data: 0.0082 max mem: 33408 +Epoch: [35] [ 470/2639] eta: 1:49:36 lr: 7.447008599251233e-06 loss: 0.0244 (0.0312) time: 3.0148 data: 0.0083 max mem: 33408 +Epoch: [35] [ 480/2639] eta: 1:49:08 lr: 7.4417409387765965e-06 loss: 0.0276 (0.0311) time: 3.0441 data: 0.0081 max mem: 33408 +Epoch: [35] [ 490/2639] eta: 1:48:38 lr: 7.4364728639659405e-06 loss: 0.0277 (0.0310) time: 3.0571 data: 0.0083 max mem: 33408 +Epoch: [35] [ 500/2639] eta: 1:48:05 lr: 7.43120437446048e-06 loss: 0.0277 (0.0310) time: 3.0001 data: 0.0081 max mem: 33408 +Epoch: [35] [ 510/2639] eta: 1:47:35 lr: 7.425935469900859e-06 loss: 0.0300 (0.0311) time: 3.0045 data: 0.0077 max mem: 33408 +Epoch: [35] [ 520/2639] eta: 1:47:05 lr: 7.4206661499270995e-06 loss: 0.0310 (0.0311) time: 3.0485 data: 0.0075 max mem: 33408 +Epoch: [35] [ 530/2639] eta: 1:46:30 lr: 7.415396414178656e-06 loss: 0.0307 (0.0312) time: 2.9851 data: 0.0076 max mem: 33408 +Epoch: [35] [ 540/2639] eta: 1:45:58 lr: 7.410126262294358e-06 loss: 0.0285 (0.0311) time: 2.9419 data: 0.0076 max mem: 33408 +Epoch: [35] [ 550/2639] eta: 1:45:30 lr: 7.4048556939124605e-06 loss: 0.0274 (0.0310) time: 3.0284 data: 0.0075 max mem: 33408 +Epoch: [35] [ 560/2639] eta: 1:45:00 lr: 7.399584708670591e-06 loss: 0.0284 (0.0311) time: 3.0617 data: 0.0081 max mem: 33408 +Epoch: [35] [ 570/2639] eta: 1:44:28 lr: 7.394313306205804e-06 loss: 0.0293 (0.0311) time: 3.0079 data: 0.0083 max mem: 33408 +Epoch: [35] [ 580/2639] eta: 1:43:58 lr: 7.389041486154523e-06 loss: 0.0299 (0.0312) time: 3.0177 data: 0.0078 max mem: 33408 +Epoch: [35] [ 590/2639] eta: 1:43:29 lr: 7.3837692481525885e-06 loss: 0.0315 (0.0312) time: 3.0643 data: 0.0077 max mem: 33408 +Epoch: [35] [ 600/2639] eta: 1:42:59 lr: 7.378496591835214e-06 loss: 0.0325 (0.0312) time: 3.0463 data: 0.0078 max mem: 33408 +Epoch: [35] [ 610/2639] eta: 1:42:26 lr: 7.373223516837026e-06 loss: 0.0247 (0.0312) time: 2.9910 data: 0.0081 max mem: 33408 +Epoch: [35] [ 620/2639] eta: 1:41:57 lr: 7.367950022792018e-06 loss: 0.0265 (0.0312) time: 3.0205 data: 0.0082 max mem: 33408 +Epoch: [35] [ 630/2639] eta: 1:41:27 lr: 7.362676109333598e-06 loss: 0.0263 (0.0312) time: 3.0540 data: 0.0077 max mem: 33408 +Epoch: [35] [ 640/2639] eta: 1:40:56 lr: 7.3574017760945345e-06 loss: 0.0263 (0.0311) time: 3.0242 data: 0.0078 max mem: 33408 +Epoch: [35] [ 650/2639] eta: 1:40:26 lr: 7.352127022707006e-06 loss: 0.0299 (0.0311) time: 3.0238 data: 0.0082 max mem: 33408 +Epoch: [35] [ 660/2639] eta: 1:39:57 lr: 7.3468518488025524e-06 loss: 0.0273 (0.0311) time: 3.0525 data: 0.0082 max mem: 33408 +Epoch: [35] [ 670/2639] eta: 1:39:24 lr: 7.34157625401212e-06 loss: 0.0268 (0.0311) time: 3.0027 data: 0.0084 max mem: 33408 +Epoch: [35] [ 680/2639] eta: 1:38:55 lr: 7.3363002379660126e-06 loss: 0.0292 (0.0311) time: 3.0067 data: 0.0088 max mem: 33408 +Epoch: [35] [ 690/2639] eta: 1:38:27 lr: 7.331023800293937e-06 loss: 0.0323 (0.0311) time: 3.0881 data: 0.0086 max mem: 33408 +Epoch: [35] [ 700/2639] eta: 1:37:58 lr: 7.325746940624953e-06 loss: 0.0317 (0.0311) time: 3.0909 data: 0.0079 max mem: 33408 +Epoch: [35] [ 710/2639] eta: 1:37:28 lr: 7.320469658587524e-06 loss: 0.0267 (0.0310) time: 3.0610 data: 0.0077 max mem: 33408 +Epoch: [35] [ 720/2639] eta: 1:36:57 lr: 7.315191953809459e-06 loss: 0.0300 (0.0311) time: 3.0272 data: 0.0079 max mem: 33408 +Epoch: [35] [ 730/2639] eta: 1:36:26 lr: 7.309913825917966e-06 loss: 0.0336 (0.0311) time: 3.0045 data: 0.0081 max mem: 33408 +Epoch: [35] [ 740/2639] eta: 1:35:55 lr: 7.304635274539618e-06 loss: 0.0318 (0.0311) time: 3.0016 data: 0.0082 max mem: 33408 +Epoch: [35] [ 750/2639] eta: 1:35:24 lr: 7.299356299300343e-06 loss: 0.0312 (0.0312) time: 3.0181 data: 0.0079 max mem: 33408 +Epoch: [35] [ 760/2639] eta: 1:34:55 lr: 7.294076899825464e-06 loss: 0.0279 (0.0311) time: 3.0487 data: 0.0077 max mem: 33408 +Epoch: [35] [ 770/2639] eta: 1:34:25 lr: 7.288797075739642e-06 loss: 0.0296 (0.0312) time: 3.0596 data: 0.0078 max mem: 33408 +Epoch: [35] [ 780/2639] eta: 1:33:56 lr: 7.283516826666932e-06 loss: 0.0308 (0.0312) time: 3.0683 data: 0.0080 max mem: 33408 +Epoch: [35] [ 790/2639] eta: 1:33:26 lr: 7.2782361522307274e-06 loss: 0.0293 (0.0312) time: 3.0664 data: 0.0079 max mem: 33408 +Epoch: [35] [ 800/2639] eta: 1:32:54 lr: 7.2729550520538074e-06 loss: 0.0279 (0.0312) time: 2.9995 data: 0.0077 max mem: 33408 +Epoch: [35] [ 810/2639] eta: 1:32:22 lr: 7.26767352575829e-06 loss: 0.0312 (0.0312) time: 2.9647 data: 0.0077 max mem: 33408 +Epoch: [35] [ 820/2639] eta: 1:31:52 lr: 7.262391572965672e-06 loss: 0.0321 (0.0312) time: 3.0001 data: 0.0080 max mem: 33408 +Epoch: [35] [ 830/2639] eta: 1:31:22 lr: 7.25710919329679e-06 loss: 0.0305 (0.0312) time: 3.0347 data: 0.0081 max mem: 33408 +Epoch: [35] [ 840/2639] eta: 1:30:51 lr: 7.2518263863718555e-06 loss: 0.0295 (0.0312) time: 3.0142 data: 0.0077 max mem: 33408 +Epoch: [35] [ 850/2639] eta: 1:30:21 lr: 7.246543151810414e-06 loss: 0.0265 (0.0312) time: 3.0200 data: 0.0076 max mem: 33408 +Epoch: [35] [ 860/2639] eta: 1:29:49 lr: 7.241259489231385e-06 loss: 0.0265 (0.0312) time: 3.0087 data: 0.0075 max mem: 33408 +Epoch: [35] [ 870/2639] eta: 1:29:18 lr: 7.235975398253014e-06 loss: 0.0260 (0.0312) time: 2.9838 data: 0.0074 max mem: 33408 +Epoch: [35] [ 880/2639] eta: 1:28:49 lr: 7.230690878492927e-06 loss: 0.0272 (0.0312) time: 3.0252 data: 0.0075 max mem: 33408 +Epoch: [35] [ 890/2639] eta: 1:28:18 lr: 7.2254059295680645e-06 loss: 0.0323 (0.0312) time: 3.0415 data: 0.0074 max mem: 33408 +Epoch: [35] [ 900/2639] eta: 1:27:48 lr: 7.220120551094744e-06 loss: 0.0308 (0.0312) time: 3.0273 data: 0.0076 max mem: 33408 +Epoch: [35] [ 910/2639] eta: 1:27:19 lr: 7.214834742688602e-06 loss: 0.0282 (0.0313) time: 3.0613 data: 0.0076 max mem: 33408 +Epoch: [35] [ 920/2639] eta: 1:26:47 lr: 7.209548503964639e-06 loss: 0.0301 (0.0312) time: 3.0194 data: 0.0072 max mem: 33408 +Epoch: [35] [ 930/2639] eta: 1:26:17 lr: 7.204261834537175e-06 loss: 0.0285 (0.0313) time: 3.0009 data: 0.0073 max mem: 33408 +Epoch: [35] [ 940/2639] eta: 1:25:48 lr: 7.198974734019895e-06 loss: 0.0287 (0.0313) time: 3.0824 data: 0.0076 max mem: 33408 +Epoch: [35] [ 950/2639] eta: 1:25:19 lr: 7.193687202025797e-06 loss: 0.0284 (0.0312) time: 3.1018 data: 0.0078 max mem: 33408 +Epoch: [35] [ 960/2639] eta: 1:24:49 lr: 7.188399238167236e-06 loss: 0.0289 (0.0313) time: 3.0805 data: 0.0075 max mem: 33408 +Epoch: [35] [ 970/2639] eta: 1:24:19 lr: 7.183110842055882e-06 loss: 0.0275 (0.0313) time: 3.0489 data: 0.0076 max mem: 33408 +Epoch: [35] [ 980/2639] eta: 1:23:48 lr: 7.177822013302753e-06 loss: 0.0272 (0.0312) time: 3.0110 data: 0.0076 max mem: 33408 +Epoch: [35] [ 990/2639] eta: 1:23:17 lr: 7.1725327515182015e-06 loss: 0.0282 (0.0312) time: 2.9703 data: 0.0075 max mem: 33408 +Epoch: [35] [1000/2639] eta: 1:22:45 lr: 7.167243056311887e-06 loss: 0.0318 (0.0313) time: 2.9547 data: 0.0079 max mem: 33408 +Epoch: [35] [1010/2639] eta: 1:22:14 lr: 7.161952927292824e-06 loss: 0.0322 (0.0312) time: 2.9737 data: 0.0080 max mem: 33408 +Epoch: [35] [1020/2639] eta: 1:21:44 lr: 7.156662364069326e-06 loss: 0.0332 (0.0313) time: 3.0036 data: 0.0082 max mem: 33408 +Epoch: [35] [1030/2639] eta: 1:21:13 lr: 7.15137136624906e-06 loss: 0.0313 (0.0313) time: 3.0042 data: 0.0079 max mem: 33408 +Epoch: [35] [1040/2639] eta: 1:20:43 lr: 7.1460799334389875e-06 loss: 0.0302 (0.0313) time: 3.0364 data: 0.0076 max mem: 33408 +Epoch: [35] [1050/2639] eta: 1:20:13 lr: 7.140788065245416e-06 loss: 0.0284 (0.0313) time: 3.0690 data: 0.0079 max mem: 33408 +Epoch: [35] [1060/2639] eta: 1:19:43 lr: 7.135495761273946e-06 loss: 0.0294 (0.0312) time: 3.0452 data: 0.0077 max mem: 33408 +Epoch: [35] [1070/2639] eta: 1:19:13 lr: 7.130203021129524e-06 loss: 0.0294 (0.0312) time: 3.0508 data: 0.0077 max mem: 33408 +Epoch: [35] [1080/2639] eta: 1:18:43 lr: 7.124909844416384e-06 loss: 0.0279 (0.0312) time: 3.0562 data: 0.0078 max mem: 33408 +Epoch: [35] [1090/2639] eta: 1:18:13 lr: 7.1196162307381005e-06 loss: 0.0284 (0.0312) time: 3.0500 data: 0.0077 max mem: 33408 +Epoch: [35] [1100/2639] eta: 1:17:43 lr: 7.114322179697536e-06 loss: 0.0333 (0.0312) time: 3.0607 data: 0.0079 max mem: 33408 +Epoch: [35] [1110/2639] eta: 1:17:13 lr: 7.1090276908968845e-06 loss: 0.0335 (0.0312) time: 3.0545 data: 0.0082 max mem: 33408 +Epoch: [35] [1120/2639] eta: 1:16:43 lr: 7.103732763937627e-06 loss: 0.0312 (0.0312) time: 3.0297 data: 0.0079 max mem: 33408 +Epoch: [35] [1130/2639] eta: 1:16:12 lr: 7.098437398420578e-06 loss: 0.0301 (0.0312) time: 3.0017 data: 0.0074 max mem: 33408 +Epoch: [35] [1140/2639] eta: 1:15:41 lr: 7.093141593945828e-06 loss: 0.0315 (0.0313) time: 2.9830 data: 0.0076 max mem: 33408 +Epoch: [35] [1150/2639] eta: 1:15:11 lr: 7.087845350112797e-06 loss: 0.0284 (0.0312) time: 3.0146 data: 0.0078 max mem: 33408 +Epoch: [35] [1160/2639] eta: 1:14:41 lr: 7.082548666520182e-06 loss: 0.0284 (0.0312) time: 3.0611 data: 0.0077 max mem: 33408 +Epoch: [35] [1170/2639] eta: 1:14:11 lr: 7.077251542766005e-06 loss: 0.0242 (0.0312) time: 3.0587 data: 0.0076 max mem: 33408 +Epoch: [35] [1180/2639] eta: 1:13:42 lr: 7.071953978447561e-06 loss: 0.0260 (0.0312) time: 3.0687 data: 0.0078 max mem: 33408 +Epoch: [35] [1190/2639] eta: 1:13:12 lr: 7.066655973161465e-06 loss: 0.0277 (0.0312) time: 3.0718 data: 0.0082 max mem: 33408 +Epoch: [35] [1200/2639] eta: 1:12:41 lr: 7.061357526503604e-06 loss: 0.0308 (0.0312) time: 3.0412 data: 0.0081 max mem: 33408 +Epoch: [35] [1210/2639] eta: 1:12:11 lr: 7.0560586380691714e-06 loss: 0.0294 (0.0312) time: 3.0293 data: 0.0077 max mem: 33408 +Epoch: [35] [1220/2639] eta: 1:11:41 lr: 7.050759307452655e-06 loss: 0.0277 (0.0312) time: 3.0301 data: 0.0079 max mem: 33408 +Epoch: [35] [1230/2639] eta: 1:11:10 lr: 7.04545953424781e-06 loss: 0.0269 (0.0312) time: 3.0033 data: 0.0079 max mem: 33408 +Epoch: [35] [1240/2639] eta: 1:10:40 lr: 7.040159318047708e-06 loss: 0.0268 (0.0311) time: 3.0387 data: 0.0076 max mem: 33408 +Epoch: [35] [1250/2639] eta: 1:10:09 lr: 7.034858658444676e-06 loss: 0.0261 (0.0311) time: 3.0487 data: 0.0076 max mem: 33408 +Epoch: [35] [1260/2639] eta: 1:09:40 lr: 7.029557555030352e-06 loss: 0.0261 (0.0311) time: 3.0577 data: 0.0076 max mem: 33408 +Epoch: [35] [1270/2639] eta: 1:09:10 lr: 7.024256007395627e-06 loss: 0.0298 (0.0311) time: 3.0793 data: 0.0080 max mem: 33408 +Epoch: [35] [1280/2639] eta: 1:08:40 lr: 7.018954015130702e-06 loss: 0.0299 (0.0311) time: 3.0547 data: 0.0081 max mem: 33408 +Epoch: [35] [1290/2639] eta: 1:08:08 lr: 7.013651577825024e-06 loss: 0.0266 (0.0311) time: 2.9857 data: 0.0077 max mem: 33408 +Epoch: [35] [1300/2639] eta: 1:07:37 lr: 7.008348695067347e-06 loss: 0.0295 (0.0311) time: 2.9436 data: 0.0080 max mem: 33408 +Epoch: [35] [1310/2639] eta: 1:07:07 lr: 7.003045366445669e-06 loss: 0.0316 (0.0312) time: 3.0097 data: 0.0084 max mem: 33408 +Epoch: [35] [1320/2639] eta: 1:06:37 lr: 6.99774159154729e-06 loss: 0.0299 (0.0311) time: 3.0147 data: 0.0083 max mem: 33408 +Epoch: [35] [1330/2639] eta: 1:06:06 lr: 6.992437369958747e-06 loss: 0.0287 (0.0311) time: 3.0228 data: 0.0080 max mem: 33408 +Epoch: [35] [1340/2639] eta: 1:05:36 lr: 6.987132701265881e-06 loss: 0.0284 (0.0311) time: 3.0593 data: 0.0080 max mem: 33408 +Epoch: [35] [1350/2639] eta: 1:05:06 lr: 6.981827585053763e-06 loss: 0.0284 (0.0311) time: 3.0307 data: 0.0079 max mem: 33408 +Epoch: [35] [1360/2639] eta: 1:04:36 lr: 6.976522020906761e-06 loss: 0.0291 (0.0311) time: 3.0265 data: 0.0077 max mem: 33408 +Epoch: [35] [1370/2639] eta: 1:04:06 lr: 6.971216008408481e-06 loss: 0.0291 (0.0311) time: 3.0679 data: 0.0075 max mem: 33408 +Epoch: [35] [1380/2639] eta: 1:03:36 lr: 6.9659095471418065e-06 loss: 0.0278 (0.0311) time: 3.0558 data: 0.0075 max mem: 33408 +Epoch: [35] [1390/2639] eta: 1:03:05 lr: 6.960602636688862e-06 loss: 0.0300 (0.0311) time: 3.0164 data: 0.0073 max mem: 33408 +Epoch: [35] [1400/2639] eta: 1:02:35 lr: 6.955295276631052e-06 loss: 0.0280 (0.0311) time: 3.0345 data: 0.0074 max mem: 33408 +Epoch: [35] [1410/2639] eta: 1:02:05 lr: 6.949987466549008e-06 loss: 0.0268 (0.0311) time: 3.0448 data: 0.0074 max mem: 33408 +Epoch: [35] [1420/2639] eta: 1:01:34 lr: 6.944679206022642e-06 loss: 0.0302 (0.0311) time: 3.0276 data: 0.0075 max mem: 33408 +Epoch: [35] [1430/2639] eta: 1:01:04 lr: 6.9393704946310894e-06 loss: 0.0322 (0.0311) time: 3.0192 data: 0.0078 max mem: 33408 +Epoch: [35] [1440/2639] eta: 1:00:33 lr: 6.934061331952761e-06 loss: 0.0278 (0.0311) time: 3.0147 data: 0.0077 max mem: 33408 +Epoch: [35] [1450/2639] eta: 1:00:04 lr: 6.928751717565289e-06 loss: 0.0284 (0.0311) time: 3.0652 data: 0.0077 max mem: 33408 +Epoch: [35] [1460/2639] eta: 0:59:34 lr: 6.923441651045569e-06 loss: 0.0282 (0.0311) time: 3.0739 data: 0.0077 max mem: 33408 +Epoch: [35] [1470/2639] eta: 0:59:03 lr: 6.918131131969738e-06 loss: 0.0245 (0.0310) time: 3.0486 data: 0.0077 max mem: 33408 +Epoch: [35] [1480/2639] eta: 0:58:34 lr: 6.912820159913158e-06 loss: 0.0295 (0.0310) time: 3.0754 data: 0.0080 max mem: 33408 +Epoch: [35] [1490/2639] eta: 0:58:03 lr: 6.907508734450452e-06 loss: 0.0272 (0.0310) time: 3.0475 data: 0.0078 max mem: 33408 +Epoch: [35] [1500/2639] eta: 0:57:33 lr: 6.902196855155454e-06 loss: 0.0264 (0.0311) time: 3.0206 data: 0.0079 max mem: 33408 +Epoch: [35] [1510/2639] eta: 0:57:03 lr: 6.896884521601263e-06 loss: 0.0283 (0.0311) time: 3.0593 data: 0.0078 max mem: 33408 +Epoch: [35] [1520/2639] eta: 0:56:33 lr: 6.891571733360179e-06 loss: 0.0281 (0.0310) time: 3.0802 data: 0.0080 max mem: 33408 +Epoch: [35] [1530/2639] eta: 0:56:02 lr: 6.88625849000376e-06 loss: 0.0270 (0.0310) time: 3.0262 data: 0.0083 max mem: 33408 +Epoch: [35] [1540/2639] eta: 0:55:31 lr: 6.880944791102772e-06 loss: 0.0274 (0.0310) time: 2.9628 data: 0.0081 max mem: 33408 +Epoch: [35] [1550/2639] eta: 0:55:01 lr: 6.875630636227225e-06 loss: 0.0291 (0.0311) time: 2.9820 data: 0.0084 max mem: 33408 +Epoch: [35] [1560/2639] eta: 0:54:30 lr: 6.870316024946333e-06 loss: 0.0283 (0.0310) time: 2.9957 data: 0.0082 max mem: 33408 +Epoch: [35] [1570/2639] eta: 0:54:00 lr: 6.8650009568285575e-06 loss: 0.0276 (0.0310) time: 3.0411 data: 0.0079 max mem: 33408 +Epoch: [35] [1580/2639] eta: 0:53:30 lr: 6.859685431441554e-06 loss: 0.0269 (0.0310) time: 3.0554 data: 0.0077 max mem: 33408 +Epoch: [35] [1590/2639] eta: 0:52:59 lr: 6.85436944835222e-06 loss: 0.0271 (0.0311) time: 2.9882 data: 0.0080 max mem: 33408 +Epoch: [35] [1600/2639] eta: 0:52:29 lr: 6.849053007126647e-06 loss: 0.0258 (0.0310) time: 2.9892 data: 0.0083 max mem: 33408 +Epoch: [35] [1610/2639] eta: 0:51:59 lr: 6.843736107330165e-06 loss: 0.0254 (0.0310) time: 3.0460 data: 0.0084 max mem: 33408 +Epoch: [35] [1620/2639] eta: 0:51:28 lr: 6.838418748527289e-06 loss: 0.0267 (0.0310) time: 3.0357 data: 0.0083 max mem: 33408 +Epoch: [35] [1630/2639] eta: 0:50:57 lr: 6.83310093028177e-06 loss: 0.0272 (0.0310) time: 2.9853 data: 0.0081 max mem: 33408 +Epoch: [35] [1640/2639] eta: 0:50:28 lr: 6.827782652156545e-06 loss: 0.0295 (0.0311) time: 3.0410 data: 0.0080 max mem: 33408 +Epoch: [35] [1650/2639] eta: 0:49:57 lr: 6.822463913713773e-06 loss: 0.0293 (0.0311) time: 3.0314 data: 0.0081 max mem: 33408 +Epoch: [35] [1660/2639] eta: 0:49:26 lr: 6.8171447145148e-06 loss: 0.0291 (0.0311) time: 2.9894 data: 0.0081 max mem: 33408 +Epoch: [35] [1670/2639] eta: 0:48:57 lr: 6.811825054120197e-06 loss: 0.0271 (0.0311) time: 3.0651 data: 0.0078 max mem: 33408 +Epoch: [35] [1680/2639] eta: 0:48:27 lr: 6.806504932089704e-06 loss: 0.0271 (0.0311) time: 3.0928 data: 0.0077 max mem: 33408 +Epoch: [35] [1690/2639] eta: 0:47:56 lr: 6.801184347982287e-06 loss: 0.0288 (0.0311) time: 3.0247 data: 0.0078 max mem: 33408 +Epoch: [35] [1700/2639] eta: 0:47:26 lr: 6.795863301356081e-06 loss: 0.0262 (0.0311) time: 2.9930 data: 0.0078 max mem: 33408 +Epoch: [35] [1710/2639] eta: 0:46:55 lr: 6.790541791768436e-06 loss: 0.0279 (0.0311) time: 3.0311 data: 0.0075 max mem: 33408 +Epoch: [35] [1720/2639] eta: 0:46:25 lr: 6.785219818775884e-06 loss: 0.0299 (0.0311) time: 3.0125 data: 0.0080 max mem: 33408 +Epoch: [35] [1730/2639] eta: 0:45:54 lr: 6.779897381934136e-06 loss: 0.0266 (0.0310) time: 3.0118 data: 0.0084 max mem: 33408 +Epoch: [35] [1740/2639] eta: 0:45:24 lr: 6.774574480798108e-06 loss: 0.0265 (0.0310) time: 3.0177 data: 0.0082 max mem: 33408 +Epoch: [35] [1750/2639] eta: 0:44:54 lr: 6.769251114921878e-06 loss: 0.0232 (0.0310) time: 3.0207 data: 0.0084 max mem: 33408 +Epoch: [35] [1760/2639] eta: 0:44:23 lr: 6.763927283858728e-06 loss: 0.0247 (0.0310) time: 3.0182 data: 0.0082 max mem: 33408 +Epoch: [35] [1770/2639] eta: 0:43:53 lr: 6.758602987161096e-06 loss: 0.0276 (0.0310) time: 3.0280 data: 0.0081 max mem: 33408 +Epoch: [35] [1780/2639] eta: 0:43:23 lr: 6.753278224380623e-06 loss: 0.0277 (0.0310) time: 3.0664 data: 0.0081 max mem: 33408 +Epoch: [35] [1790/2639] eta: 0:42:53 lr: 6.747952995068099e-06 loss: 0.0303 (0.0310) time: 3.0532 data: 0.0078 max mem: 33408 +Epoch: [35] [1800/2639] eta: 0:42:22 lr: 6.742627298773513e-06 loss: 0.0266 (0.0310) time: 2.9946 data: 0.0076 max mem: 33408 +Epoch: [35] [1810/2639] eta: 0:41:52 lr: 6.737301135045997e-06 loss: 0.0256 (0.0309) time: 2.9818 data: 0.0079 max mem: 33408 +Epoch: [35] [1820/2639] eta: 0:41:22 lr: 6.731974503433877e-06 loss: 0.0288 (0.0309) time: 3.0477 data: 0.0082 max mem: 33408 +Epoch: [35] [1830/2639] eta: 0:40:51 lr: 6.726647403484625e-06 loss: 0.0247 (0.0309) time: 3.0181 data: 0.0078 max mem: 33408 +Epoch: [35] [1840/2639] eta: 0:40:21 lr: 6.7213198347448936e-06 loss: 0.0251 (0.0309) time: 2.9938 data: 0.0079 max mem: 33408 +Epoch: [35] [1850/2639] eta: 0:39:50 lr: 6.715991796760478e-06 loss: 0.0324 (0.0309) time: 3.0311 data: 0.0080 max mem: 33408 +Epoch: [35] [1860/2639] eta: 0:39:20 lr: 6.710663289076353e-06 loss: 0.0276 (0.0309) time: 3.0604 data: 0.0077 max mem: 33408 +Epoch: [35] [1870/2639] eta: 0:38:50 lr: 6.70533431123663e-06 loss: 0.0299 (0.0310) time: 3.0674 data: 0.0079 max mem: 33408 +Epoch: [35] [1880/2639] eta: 0:38:20 lr: 6.700004862784598e-06 loss: 0.0371 (0.0310) time: 3.0269 data: 0.0082 max mem: 33408 +Epoch: [35] [1890/2639] eta: 0:37:49 lr: 6.694674943262672e-06 loss: 0.0280 (0.0310) time: 3.0319 data: 0.0080 max mem: 33408 +Epoch: [35] [1900/2639] eta: 0:37:19 lr: 6.689344552212441e-06 loss: 0.0284 (0.0310) time: 3.0364 data: 0.0080 max mem: 33408 +Epoch: [35] [1910/2639] eta: 0:36:49 lr: 6.68401368917462e-06 loss: 0.0302 (0.0310) time: 3.0162 data: 0.0079 max mem: 33408 +Epoch: [35] [1920/2639] eta: 0:36:18 lr: 6.6786823536890934e-06 loss: 0.0252 (0.0310) time: 3.0124 data: 0.0080 max mem: 33408 +Epoch: [35] [1930/2639] eta: 0:35:48 lr: 6.673350545294862e-06 loss: 0.0269 (0.0310) time: 3.0054 data: 0.0087 max mem: 33408 +Epoch: [35] [1940/2639] eta: 0:35:18 lr: 6.668018263530092e-06 loss: 0.0309 (0.0310) time: 3.0198 data: 0.0083 max mem: 33408 +Epoch: [35] [1950/2639] eta: 0:34:47 lr: 6.662685507932064e-06 loss: 0.0301 (0.0310) time: 3.0153 data: 0.0079 max mem: 33408 +Epoch: [35] [1960/2639] eta: 0:34:17 lr: 6.657352278037213e-06 loss: 0.0294 (0.0311) time: 3.0096 data: 0.0080 max mem: 33408 +Epoch: [35] [1970/2639] eta: 0:33:46 lr: 6.652018573381107e-06 loss: 0.0300 (0.0311) time: 2.9876 data: 0.0078 max mem: 33408 +Epoch: [35] [1980/2639] eta: 0:33:16 lr: 6.646684393498425e-06 loss: 0.0256 (0.0311) time: 2.9747 data: 0.0075 max mem: 33408 +Epoch: [35] [1990/2639] eta: 0:32:45 lr: 6.641349737923003e-06 loss: 0.0299 (0.0311) time: 2.9938 data: 0.0077 max mem: 33408 +Epoch: [35] [2000/2639] eta: 0:32:15 lr: 6.636014606187775e-06 loss: 0.0327 (0.0311) time: 3.0181 data: 0.0079 max mem: 33408 +Epoch: [35] [2010/2639] eta: 0:31:45 lr: 6.630678997824824e-06 loss: 0.0297 (0.0311) time: 3.0508 data: 0.0079 max mem: 33408 +Epoch: [35] [2020/2639] eta: 0:31:15 lr: 6.625342912365332e-06 loss: 0.0297 (0.0312) time: 3.0281 data: 0.0079 max mem: 33408 +Epoch: [35] [2030/2639] eta: 0:30:44 lr: 6.620006349339622e-06 loss: 0.0297 (0.0312) time: 2.9929 data: 0.0081 max mem: 33408 +Epoch: [35] [2040/2639] eta: 0:30:14 lr: 6.614669308277109e-06 loss: 0.0271 (0.0311) time: 3.0091 data: 0.0084 max mem: 33408 +Epoch: [35] [2050/2639] eta: 0:29:44 lr: 6.609331788706349e-06 loss: 0.0259 (0.0311) time: 3.0185 data: 0.0081 max mem: 33408 +Epoch: [35] [2060/2639] eta: 0:29:13 lr: 6.603993790154983e-06 loss: 0.0306 (0.0312) time: 2.9858 data: 0.0078 max mem: 33408 +Epoch: [35] [2070/2639] eta: 0:28:43 lr: 6.598655312149786e-06 loss: 0.0325 (0.0311) time: 2.9742 data: 0.0080 max mem: 33408 +Epoch: [35] [2080/2639] eta: 0:28:12 lr: 6.593316354216614e-06 loss: 0.0303 (0.0312) time: 3.0173 data: 0.0082 max mem: 33408 +Epoch: [35] [2090/2639] eta: 0:27:42 lr: 6.587976915880452e-06 loss: 0.0278 (0.0311) time: 3.0598 data: 0.0080 max mem: 33408 +Epoch: [35] [2100/2639] eta: 0:27:12 lr: 6.582636996665364e-06 loss: 0.0281 (0.0311) time: 3.0401 data: 0.0081 max mem: 33408 +Epoch: [35] [2110/2639] eta: 0:26:42 lr: 6.577296596094537e-06 loss: 0.0290 (0.0311) time: 3.0204 data: 0.0084 max mem: 33408 +Epoch: [35] [2120/2639] eta: 0:26:11 lr: 6.5719557136902265e-06 loss: 0.0276 (0.0311) time: 3.0351 data: 0.0080 max mem: 33408 +Epoch: [35] [2130/2639] eta: 0:25:41 lr: 6.5666143489738125e-06 loss: 0.0277 (0.0311) time: 3.0341 data: 0.0079 max mem: 33408 +Epoch: [35] [2140/2639] eta: 0:25:11 lr: 6.561272501465737e-06 loss: 0.0306 (0.0311) time: 3.0323 data: 0.0082 max mem: 33408 +Epoch: [35] [2150/2639] eta: 0:24:41 lr: 6.5559301706855564e-06 loss: 0.0284 (0.0312) time: 3.0528 data: 0.0081 max mem: 33408 +Epoch: [35] [2160/2639] eta: 0:24:10 lr: 6.550587356151892e-06 loss: 0.0278 (0.0311) time: 3.0471 data: 0.0082 max mem: 33408 +Epoch: [35] [2170/2639] eta: 0:23:40 lr: 6.54524405738247e-06 loss: 0.0283 (0.0311) time: 2.9988 data: 0.0083 max mem: 33408 +Epoch: [35] [2180/2639] eta: 0:23:10 lr: 6.539900273894074e-06 loss: 0.0285 (0.0311) time: 3.0110 data: 0.0080 max mem: 33408 +Epoch: [35] [2190/2639] eta: 0:22:39 lr: 6.534556005202592e-06 loss: 0.0279 (0.0312) time: 3.0481 data: 0.0080 max mem: 33408 +Epoch: [35] [2200/2639] eta: 0:22:09 lr: 6.5292112508229645e-06 loss: 0.0260 (0.0311) time: 3.0217 data: 0.0084 max mem: 33408 +Epoch: [35] [2210/2639] eta: 0:21:39 lr: 6.523866010269218e-06 loss: 0.0293 (0.0311) time: 3.0133 data: 0.0084 max mem: 33408 +Epoch: [35] [2220/2639] eta: 0:21:09 lr: 6.518520283054458e-06 loss: 0.0301 (0.0311) time: 3.0727 data: 0.0079 max mem: 33408 +Epoch: [35] [2230/2639] eta: 0:20:39 lr: 6.513174068690833e-06 loss: 0.0292 (0.0312) time: 3.1004 data: 0.0078 max mem: 33408 +Epoch: [35] [2240/2639] eta: 0:20:08 lr: 6.507827366689588e-06 loss: 0.0308 (0.0312) time: 3.0853 data: 0.0078 max mem: 33408 +Epoch: [35] [2250/2639] eta: 0:19:38 lr: 6.5024801765609985e-06 loss: 0.0237 (0.0311) time: 3.0451 data: 0.0074 max mem: 33408 +Epoch: [35] [2260/2639] eta: 0:19:08 lr: 6.497132497814433e-06 loss: 0.0243 (0.0311) time: 3.0770 data: 0.0077 max mem: 33408 +Epoch: [35] [2270/2639] eta: 0:18:38 lr: 6.491784329958286e-06 loss: 0.0313 (0.0311) time: 3.0869 data: 0.0078 max mem: 33408 +Epoch: [35] [2280/2639] eta: 0:18:07 lr: 6.486435672500038e-06 loss: 0.0313 (0.0311) time: 3.0028 data: 0.0077 max mem: 33408 +Epoch: [35] [2290/2639] eta: 0:17:37 lr: 6.481086524946191e-06 loss: 0.0315 (0.0311) time: 2.9754 data: 0.0080 max mem: 33408 +Epoch: [35] [2300/2639] eta: 0:17:06 lr: 6.475736886802325e-06 loss: 0.0315 (0.0312) time: 2.9682 data: 0.0080 max mem: 33408 +Epoch: [35] [2310/2639] eta: 0:16:36 lr: 6.470386757573041e-06 loss: 0.0319 (0.0312) time: 2.9661 data: 0.0082 max mem: 33408 +Epoch: [35] [2320/2639] eta: 0:16:06 lr: 6.465036136762011e-06 loss: 0.0310 (0.0312) time: 2.9784 data: 0.0085 max mem: 33408 +Epoch: [35] [2330/2639] eta: 0:15:35 lr: 6.459685023871919e-06 loss: 0.0270 (0.0312) time: 3.0274 data: 0.0081 max mem: 33408 +Epoch: [35] [2340/2639] eta: 0:15:05 lr: 6.454333418404518e-06 loss: 0.0238 (0.0311) time: 3.0537 data: 0.0075 max mem: 33408 +Epoch: [35] [2350/2639] eta: 0:14:35 lr: 6.448981319860565e-06 loss: 0.0289 (0.0311) time: 3.0257 data: 0.0077 max mem: 33408 +Epoch: [35] [2360/2639] eta: 0:14:05 lr: 6.443628727739885e-06 loss: 0.0295 (0.0311) time: 3.0477 data: 0.0079 max mem: 33408 +Epoch: [35] [2370/2639] eta: 0:13:34 lr: 6.4382756415413e-06 loss: 0.0295 (0.0311) time: 3.0641 data: 0.0078 max mem: 33408 +Epoch: [35] [2380/2639] eta: 0:13:04 lr: 6.432922060762686e-06 loss: 0.0290 (0.0311) time: 3.0142 data: 0.0077 max mem: 33408 +Epoch: [35] [2390/2639] eta: 0:12:34 lr: 6.427567984900923e-06 loss: 0.0274 (0.0311) time: 3.0369 data: 0.0077 max mem: 33408 +Epoch: [35] [2400/2639] eta: 0:12:03 lr: 6.422213413451934e-06 loss: 0.0263 (0.0311) time: 3.0117 data: 0.0077 max mem: 33408 +Epoch: [35] [2410/2639] eta: 0:11:33 lr: 6.416858345910638e-06 loss: 0.0263 (0.0311) time: 2.9793 data: 0.0079 max mem: 33408 +Epoch: [35] [2420/2639] eta: 0:11:03 lr: 6.411502781770995e-06 loss: 0.0330 (0.0311) time: 3.0255 data: 0.0081 max mem: 33408 +Epoch: [35] [2430/2639] eta: 0:10:33 lr: 6.406146720525953e-06 loss: 0.0295 (0.0311) time: 3.0398 data: 0.0082 max mem: 33408 +Epoch: [35] [2440/2639] eta: 0:10:02 lr: 6.400790161667497e-06 loss: 0.0285 (0.0311) time: 3.0430 data: 0.0080 max mem: 33408 +Epoch: [35] [2450/2639] eta: 0:09:32 lr: 6.395433104686595e-06 loss: 0.0292 (0.0311) time: 3.0454 data: 0.0075 max mem: 33408 +Epoch: [35] [2460/2639] eta: 0:09:02 lr: 6.390075549073236e-06 loss: 0.0287 (0.0311) time: 3.0016 data: 0.0080 max mem: 33408 +Epoch: [35] [2470/2639] eta: 0:08:31 lr: 6.384717494316415e-06 loss: 0.0281 (0.0311) time: 2.9840 data: 0.0080 max mem: 33408 +Epoch: [35] [2480/2639] eta: 0:08:01 lr: 6.379358939904105e-06 loss: 0.0298 (0.0311) time: 3.0220 data: 0.0078 max mem: 33408 +Epoch: [35] [2490/2639] eta: 0:07:31 lr: 6.3739998853233e-06 loss: 0.0295 (0.0311) time: 2.9901 data: 0.0079 max mem: 33408 +Epoch: [35] [2500/2639] eta: 0:07:00 lr: 6.368640330059967e-06 loss: 0.0298 (0.0311) time: 2.9502 data: 0.0075 max mem: 33408 +Epoch: [35] [2510/2639] eta: 0:06:30 lr: 6.3632802735990815e-06 loss: 0.0315 (0.0311) time: 2.9470 data: 0.0079 max mem: 33408 +Epoch: [35] [2520/2639] eta: 0:06:00 lr: 6.357919715424587e-06 loss: 0.0317 (0.0311) time: 2.9887 data: 0.0081 max mem: 33408 +Epoch: [35] [2530/2639] eta: 0:05:30 lr: 6.352558655019435e-06 loss: 0.0317 (0.0311) time: 3.0464 data: 0.0077 max mem: 33408 +Epoch: [35] [2540/2639] eta: 0:04:59 lr: 6.347197091865533e-06 loss: 0.0264 (0.0311) time: 3.0424 data: 0.0080 max mem: 33408 +Epoch: [35] [2550/2639] eta: 0:04:29 lr: 6.341835025443793e-06 loss: 0.0263 (0.0311) time: 3.0503 data: 0.0082 max mem: 33408 +Epoch: [35] [2560/2639] eta: 0:03:59 lr: 6.336472455234077e-06 loss: 0.0263 (0.0311) time: 3.0509 data: 0.0078 max mem: 33408 +Epoch: [35] [2570/2639] eta: 0:03:28 lr: 6.331109380715247e-06 loss: 0.0257 (0.0311) time: 3.0134 data: 0.0079 max mem: 33408 +Epoch: [35] [2580/2639] eta: 0:02:58 lr: 6.325745801365108e-06 loss: 0.0265 (0.0311) time: 3.0012 data: 0.0086 max mem: 33408 +Epoch: [35] [2590/2639] eta: 0:02:28 lr: 6.320381716660458e-06 loss: 0.0299 (0.0311) time: 3.0238 data: 0.0084 max mem: 33408 +Epoch: [35] [2600/2639] eta: 0:01:58 lr: 6.315017126077032e-06 loss: 0.0299 (0.0311) time: 3.0629 data: 0.0077 max mem: 33408 +Epoch: [35] [2610/2639] eta: 0:01:27 lr: 6.309652029089551e-06 loss: 0.0308 (0.0311) time: 3.0942 data: 0.0076 max mem: 33408 +Epoch: [35] [2620/2639] eta: 0:00:57 lr: 6.30428642517167e-06 loss: 0.0308 (0.0311) time: 3.0502 data: 0.0076 max mem: 33408 +Epoch: [35] [2630/2639] eta: 0:00:27 lr: 6.298920313796022e-06 loss: 0.0327 (0.0311) time: 3.0288 data: 0.0074 max mem: 33408 +Epoch: [35] Total time: 2:13:13 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 2:17:16 time: 3.2011 data: 3.1136 max mem: 33408 +Test: [ 100/2573] eta: 0:04:32 time: 0.0796 data: 0.0014 max mem: 33408 +Test: [ 200/2573] eta: 0:03:47 time: 0.0808 data: 0.0014 max mem: 33408 +Test: [ 300/2573] eta: 0:03:25 time: 0.0818 data: 0.0013 max mem: 33408 +Test: [ 400/2573] eta: 0:03:11 time: 0.0831 data: 0.0014 max mem: 33408 +Test: [ 500/2573] eta: 0:02:59 time: 0.0817 data: 0.0015 max mem: 33408 +Test: [ 600/2573] eta: 0:02:49 time: 0.0808 data: 0.0014 max mem: 33408 +Test: [ 700/2573] eta: 0:02:40 time: 0.0822 data: 0.0014 max mem: 33408 +Test: [ 800/2573] eta: 0:02:31 time: 0.0840 data: 0.0013 max mem: 33408 +Test: [ 900/2573] eta: 0:02:21 time: 0.0808 data: 0.0015 max mem: 33408 +Test: [1000/2573] eta: 0:02:13 time: 0.0825 data: 0.0015 max mem: 33408 +Test: [1100/2573] eta: 0:02:04 time: 0.0815 data: 0.0015 max mem: 33408 +Test: [1200/2573] eta: 0:01:55 time: 0.0814 data: 0.0015 max mem: 33408 +Test: [1300/2573] eta: 0:01:46 time: 0.0816 data: 0.0014 max mem: 33408 +Test: [1400/2573] eta: 0:01:38 time: 0.0799 data: 0.0014 max mem: 33408 +Test: [1500/2573] eta: 0:01:29 time: 0.0816 data: 0.0014 max mem: 33408 +Test: [1600/2573] eta: 0:01:21 time: 0.0855 data: 0.0014 max mem: 33408 +Test: [1700/2573] eta: 0:01:12 time: 0.0794 data: 0.0014 max mem: 33408 +Test: [1800/2573] eta: 0:01:04 time: 0.0836 data: 0.0015 max mem: 33408 +Test: [1900/2573] eta: 0:00:55 time: 0.0790 data: 0.0014 max mem: 33408 +Test: [2000/2573] eta: 0:00:47 time: 0.0811 data: 0.0014 max mem: 33408 +Test: [2100/2573] eta: 0:00:39 time: 0.0829 data: 0.0014 max mem: 33408 +Test: [2200/2573] eta: 0:00:30 time: 0.0836 data: 0.0014 max mem: 33408 +Test: [2300/2573] eta: 0:00:22 time: 0.0832 data: 0.0015 max mem: 33408 +Test: [2400/2573] eta: 0:00:14 time: 0.0785 data: 0.0014 max mem: 33408 +Test: [2500/2573] eta: 0:00:06 time: 0.0816 data: 0.0014 max mem: 33408 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: Total time: 0:03:34 +Final results: +Mean IoU is 65.21 + + precision@0.5 = 73.35 + precision@0.6 = 68.28 + precision@0.7 = 61.34 + precision@0.8 = 50.80 + precision@0.9 = 25.74 + overall IoU = 62.61 + +Average object IoU 65.2148539556023 +Overall IoU 62.61172103881836 +Better epoch: 35 + +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [36] [ 0/2639] eta: 3:56:16 lr: 6.294090379244818e-06 loss: 0.0391 (0.0391) time: 5.3721 data: 2.1713 max mem: 33408 +Epoch: [36] [ 10/2639] eta: 2:18:34 lr: 6.2887233022427135e-06 loss: 0.0275 (0.0296) time: 3.1627 data: 0.2040 max mem: 33408 +Epoch: [36] [ 20/2639] eta: 2:15:30 lr: 6.2833557162475044e-06 loss: 0.0283 (0.0305) time: 2.9909 data: 0.0074 max mem: 33408 +Epoch: [36] [ 30/2639] eta: 2:15:04 lr: 6.2779876207276964e-06 loss: 0.0288 (0.0312) time: 3.0755 data: 0.0076 max mem: 33408 +Epoch: [36] [ 40/2639] eta: 2:14:14 lr: 6.272619015150753e-06 loss: 0.0269 (0.0303) time: 3.0935 data: 0.0079 max mem: 33408 +Epoch: [36] [ 50/2639] eta: 2:12:53 lr: 6.267249898983057e-06 loss: 0.0278 (0.0308) time: 3.0384 data: 0.0081 max mem: 33408 +Epoch: [36] [ 60/2639] eta: 2:11:37 lr: 6.261880271689942e-06 loss: 0.0277 (0.0303) time: 2.9872 data: 0.0082 max mem: 33408 +Epoch: [36] [ 70/2639] eta: 2:10:53 lr: 6.256510132735653e-06 loss: 0.0271 (0.0299) time: 2.9997 data: 0.0081 max mem: 33408 +Epoch: [36] [ 80/2639] eta: 2:10:29 lr: 6.251139481583375e-06 loss: 0.0285 (0.0309) time: 3.0518 data: 0.0076 max mem: 33408 +Epoch: [36] [ 90/2639] eta: 2:09:32 lr: 6.24576831769522e-06 loss: 0.0320 (0.0322) time: 3.0216 data: 0.0073 max mem: 33408 +Epoch: [36] [ 100/2639] eta: 2:08:48 lr: 6.240396640532202e-06 loss: 0.0301 (0.0321) time: 2.9792 data: 0.0074 max mem: 33408 +Epoch: [36] [ 110/2639] eta: 2:08:13 lr: 6.235024449554276e-06 loss: 0.0262 (0.0316) time: 3.0086 data: 0.0080 max mem: 33408 +Epoch: [36] [ 120/2639] eta: 2:07:40 lr: 6.229651744220288e-06 loss: 0.0257 (0.0314) time: 3.0275 data: 0.0081 max mem: 33408 +Epoch: [36] [ 130/2639] eta: 2:07:06 lr: 6.2242785239880165e-06 loss: 0.0257 (0.0311) time: 3.0258 data: 0.0080 max mem: 33408 +Epoch: [36] [ 140/2639] eta: 2:06:34 lr: 6.218904788314126e-06 loss: 0.0288 (0.0311) time: 3.0250 data: 0.0083 max mem: 33408 +Epoch: [36] [ 150/2639] eta: 2:05:54 lr: 6.213530536654209e-06 loss: 0.0277 (0.0308) time: 3.0049 data: 0.0081 max mem: 33408 +Epoch: [36] [ 160/2639] eta: 2:05:15 lr: 6.2081557684627356e-06 loss: 0.0277 (0.0310) time: 2.9797 data: 0.0075 max mem: 33408 +Epoch: [36] [ 170/2639] eta: 2:04:35 lr: 6.202780483193095e-06 loss: 0.0301 (0.0309) time: 2.9722 data: 0.0076 max mem: 33408 +Epoch: [36] [ 180/2639] eta: 2:04:08 lr: 6.197404680297551e-06 loss: 0.0279 (0.0312) time: 3.0092 data: 0.0077 max mem: 33408 +Epoch: [36] [ 190/2639] eta: 2:03:36 lr: 6.192028359227281e-06 loss: 0.0346 (0.0313) time: 3.0344 data: 0.0077 max mem: 33408 +Epoch: [36] [ 200/2639] eta: 2:03:07 lr: 6.186651519432324e-06 loss: 0.0315 (0.0311) time: 3.0265 data: 0.0077 max mem: 33408 +Epoch: [36] [ 210/2639] eta: 2:02:35 lr: 6.181274160361632e-06 loss: 0.0260 (0.0309) time: 3.0257 data: 0.0079 max mem: 33408 +Epoch: [36] [ 220/2639] eta: 2:02:00 lr: 6.175896281463011e-06 loss: 0.0285 (0.0310) time: 3.0018 data: 0.0079 max mem: 33408 +Epoch: [36] [ 230/2639] eta: 2:01:33 lr: 6.170517882183171e-06 loss: 0.0311 (0.0310) time: 3.0217 data: 0.0076 max mem: 33408 +Epoch: [36] [ 240/2639] eta: 2:01:05 lr: 6.165138961967671e-06 loss: 0.0290 (0.0309) time: 3.0522 data: 0.0076 max mem: 33408 +Epoch: [36] [ 250/2639] eta: 2:00:36 lr: 6.159759520260965e-06 loss: 0.0290 (0.0309) time: 3.0480 data: 0.0076 max mem: 33408 +Epoch: [36] [ 260/2639] eta: 2:00:03 lr: 6.154379556506354e-06 loss: 0.0296 (0.0309) time: 3.0202 data: 0.0075 max mem: 33408 +Epoch: [36] [ 270/2639] eta: 1:59:26 lr: 6.148999070146023e-06 loss: 0.0286 (0.0307) time: 2.9753 data: 0.0074 max mem: 33408 +Epoch: [36] [ 280/2639] eta: 1:58:56 lr: 6.143618060620997e-06 loss: 0.0258 (0.0306) time: 2.9910 data: 0.0075 max mem: 33408 +Epoch: [36] [ 290/2639] eta: 1:58:25 lr: 6.138236527371182e-06 loss: 0.0256 (0.0305) time: 3.0194 data: 0.0076 max mem: 33408 +Epoch: [36] [ 300/2639] eta: 1:57:58 lr: 6.132854469835311e-06 loss: 0.0257 (0.0304) time: 3.0383 data: 0.0083 max mem: 33408 +Epoch: [36] [ 310/2639] eta: 1:57:23 lr: 6.127471887450998e-06 loss: 0.0260 (0.0303) time: 3.0156 data: 0.0085 max mem: 33408 +Epoch: [36] [ 320/2639] eta: 1:56:58 lr: 6.122088779654675e-06 loss: 0.0266 (0.0302) time: 3.0294 data: 0.0078 max mem: 33408 +Epoch: [36] [ 330/2639] eta: 1:56:31 lr: 6.116705145881636e-06 loss: 0.0256 (0.0303) time: 3.0861 data: 0.0078 max mem: 33408 +Epoch: [36] [ 340/2639] eta: 1:56:02 lr: 6.111320985566017e-06 loss: 0.0236 (0.0301) time: 3.0651 data: 0.0079 max mem: 33408 +Epoch: [36] [ 350/2639] eta: 1:55:31 lr: 6.105936298140772e-06 loss: 0.0273 (0.0301) time: 3.0353 data: 0.0079 max mem: 33408 +Epoch: [36] [ 360/2639] eta: 1:55:03 lr: 6.100551083037712e-06 loss: 0.0287 (0.0303) time: 3.0428 data: 0.0081 max mem: 33408 +Epoch: [36] [ 370/2639] eta: 1:54:30 lr: 6.095165339687453e-06 loss: 0.0260 (0.0302) time: 3.0182 data: 0.0083 max mem: 33408 +Epoch: [36] [ 380/2639] eta: 1:53:58 lr: 6.0897790675194625e-06 loss: 0.0288 (0.0303) time: 2.9909 data: 0.0078 max mem: 33408 +Epoch: [36] [ 390/2639] eta: 1:53:32 lr: 6.084392265962004e-06 loss: 0.0323 (0.0303) time: 3.0534 data: 0.0075 max mem: 33408 +Epoch: [36] [ 400/2639] eta: 1:53:04 lr: 6.079004934442187e-06 loss: 0.0286 (0.0303) time: 3.0804 data: 0.0078 max mem: 33408 +Epoch: [36] [ 410/2639] eta: 1:52:34 lr: 6.073617072385908e-06 loss: 0.0264 (0.0302) time: 3.0516 data: 0.0082 max mem: 33408 +Epoch: [36] [ 420/2639] eta: 1:52:05 lr: 6.068228679217904e-06 loss: 0.0284 (0.0302) time: 3.0491 data: 0.0080 max mem: 33408 +Epoch: [36] [ 430/2639] eta: 1:51:31 lr: 6.0628397543616905e-06 loss: 0.0299 (0.0303) time: 3.0124 data: 0.0081 max mem: 33408 +Epoch: [36] [ 440/2639] eta: 1:51:03 lr: 6.057450297239617e-06 loss: 0.0264 (0.0302) time: 3.0135 data: 0.0083 max mem: 33408 +Epoch: [36] [ 450/2639] eta: 1:50:32 lr: 6.052060307272806e-06 loss: 0.0253 (0.0301) time: 3.0447 data: 0.0083 max mem: 33408 +Epoch: [36] [ 460/2639] eta: 1:49:59 lr: 6.0466697838812e-06 loss: 0.0261 (0.0302) time: 2.9995 data: 0.0083 max mem: 33408 +Epoch: [36] [ 470/2639] eta: 1:49:30 lr: 6.041278726483515e-06 loss: 0.0270 (0.0301) time: 3.0141 data: 0.0080 max mem: 33408 +Epoch: [36] [ 480/2639] eta: 1:49:02 lr: 6.035887134497278e-06 loss: 0.0281 (0.0301) time: 3.0644 data: 0.0079 max mem: 33408 +Epoch: [36] [ 490/2639] eta: 1:48:28 lr: 6.030495007338776e-06 loss: 0.0267 (0.0303) time: 3.0150 data: 0.0079 max mem: 33408 +Epoch: [36] [ 500/2639] eta: 1:47:57 lr: 6.025102344423107e-06 loss: 0.0262 (0.0303) time: 2.9790 data: 0.0083 max mem: 33408 +Epoch: [36] [ 510/2639] eta: 1:47:28 lr: 6.019709145164117e-06 loss: 0.0267 (0.0303) time: 3.0362 data: 0.0085 max mem: 33408 +Epoch: [36] [ 520/2639] eta: 1:47:01 lr: 6.014315408974455e-06 loss: 0.0287 (0.0303) time: 3.0833 data: 0.0084 max mem: 33408 +Epoch: [36] [ 530/2639] eta: 1:46:28 lr: 6.008921135265517e-06 loss: 0.0286 (0.0303) time: 3.0351 data: 0.0083 max mem: 33408 +Epoch: [36] [ 540/2639] eta: 1:45:58 lr: 6.0035263234474884e-06 loss: 0.0286 (0.0303) time: 2.9978 data: 0.0079 max mem: 33408 +Epoch: [36] [ 550/2639] eta: 1:45:29 lr: 5.998130972929293e-06 loss: 0.0289 (0.0304) time: 3.0471 data: 0.0078 max mem: 33408 +Epoch: [36] [ 560/2639] eta: 1:44:58 lr: 5.992735083118639e-06 loss: 0.0310 (0.0304) time: 3.0378 data: 0.0082 max mem: 33408 +Epoch: [36] [ 570/2639] eta: 1:44:25 lr: 5.987338653421968e-06 loss: 0.0310 (0.0304) time: 2.9779 data: 0.0084 max mem: 33408 +Epoch: [36] [ 580/2639] eta: 1:43:55 lr: 5.981941683244487e-06 loss: 0.0296 (0.0304) time: 2.9995 data: 0.0083 max mem: 33408 +Epoch: [36] [ 590/2639] eta: 1:43:24 lr: 5.976544171990153e-06 loss: 0.0288 (0.0306) time: 3.0296 data: 0.0081 max mem: 33408 +Epoch: [36] [ 600/2639] eta: 1:42:53 lr: 5.971146119061651e-06 loss: 0.0270 (0.0305) time: 3.0068 data: 0.0081 max mem: 33408 +Epoch: [36] [ 610/2639] eta: 1:42:24 lr: 5.965747523860426e-06 loss: 0.0280 (0.0305) time: 3.0330 data: 0.0082 max mem: 33408 +Epoch: [36] [ 620/2639] eta: 1:41:52 lr: 5.960348385786636e-06 loss: 0.0280 (0.0305) time: 3.0283 data: 0.0083 max mem: 33408 +Epoch: [36] [ 630/2639] eta: 1:41:23 lr: 5.954948704239198e-06 loss: 0.0284 (0.0305) time: 3.0143 data: 0.0082 max mem: 33408 +Epoch: [36] [ 640/2639] eta: 1:40:54 lr: 5.94954847861573e-06 loss: 0.0323 (0.0305) time: 3.0550 data: 0.0079 max mem: 33408 +Epoch: [36] [ 650/2639] eta: 1:40:21 lr: 5.944147708312598e-06 loss: 0.0266 (0.0305) time: 3.0134 data: 0.0076 max mem: 33408 +Epoch: [36] [ 660/2639] eta: 1:39:49 lr: 5.938746392724866e-06 loss: 0.0271 (0.0304) time: 2.9628 data: 0.0080 max mem: 33408 +Epoch: [36] [ 670/2639] eta: 1:39:18 lr: 5.933344531246339e-06 loss: 0.0275 (0.0304) time: 2.9822 data: 0.0082 max mem: 33408 +Epoch: [36] [ 680/2639] eta: 1:38:48 lr: 5.927942123269504e-06 loss: 0.0282 (0.0305) time: 3.0108 data: 0.0082 max mem: 33408 +Epoch: [36] [ 690/2639] eta: 1:38:18 lr: 5.922539168185588e-06 loss: 0.0291 (0.0305) time: 3.0291 data: 0.0081 max mem: 33408 +Epoch: [36] [ 700/2639] eta: 1:37:48 lr: 5.9171356653844926e-06 loss: 0.0287 (0.0305) time: 3.0475 data: 0.0084 max mem: 33408 +Epoch: [36] [ 710/2639] eta: 1:37:19 lr: 5.911731614254846e-06 loss: 0.0268 (0.0305) time: 3.0687 data: 0.0086 max mem: 33408 +Epoch: [36] [ 720/2639] eta: 1:36:49 lr: 5.906327014183947e-06 loss: 0.0312 (0.0306) time: 3.0444 data: 0.0080 max mem: 33408 +Epoch: [36] [ 730/2639] eta: 1:36:19 lr: 5.900921864557811e-06 loss: 0.0333 (0.0306) time: 3.0273 data: 0.0076 max mem: 33408 +Epoch: [36] [ 740/2639] eta: 1:35:49 lr: 5.8955161647611145e-06 loss: 0.0319 (0.0306) time: 3.0498 data: 0.0079 max mem: 33408 +Epoch: [36] [ 750/2639] eta: 1:35:20 lr: 5.890109914177246e-06 loss: 0.0267 (0.0307) time: 3.0642 data: 0.0078 max mem: 33408 +Epoch: [36] [ 760/2639] eta: 1:34:50 lr: 5.884703112188243e-06 loss: 0.0299 (0.0307) time: 3.0531 data: 0.0073 max mem: 33408 +Epoch: [36] [ 770/2639] eta: 1:34:19 lr: 5.879295758174849e-06 loss: 0.0290 (0.0307) time: 3.0232 data: 0.0078 max mem: 33408 +Epoch: [36] [ 780/2639] eta: 1:33:50 lr: 5.8738878515164486e-06 loss: 0.0290 (0.0307) time: 3.0432 data: 0.0083 max mem: 33408 +Epoch: [36] [ 790/2639] eta: 1:33:22 lr: 5.868479391591121e-06 loss: 0.0273 (0.0307) time: 3.0927 data: 0.0080 max mem: 33408 +Epoch: [36] [ 800/2639] eta: 1:32:51 lr: 5.863070377775582e-06 loss: 0.0273 (0.0306) time: 3.0651 data: 0.0077 max mem: 33408 +Epoch: [36] [ 810/2639] eta: 1:32:22 lr: 5.857660809445229e-06 loss: 0.0263 (0.0306) time: 3.0426 data: 0.0077 max mem: 33408 +Epoch: [36] [ 820/2639] eta: 1:31:51 lr: 5.85225068597409e-06 loss: 0.0273 (0.0306) time: 3.0268 data: 0.0077 max mem: 33408 +Epoch: [36] [ 830/2639] eta: 1:31:20 lr: 5.846840006734862e-06 loss: 0.0286 (0.0306) time: 3.0065 data: 0.0078 max mem: 33408 +Epoch: [36] [ 840/2639] eta: 1:30:49 lr: 5.841428771098888e-06 loss: 0.0263 (0.0306) time: 3.0141 data: 0.0078 max mem: 33408 +Epoch: [36] [ 850/2639] eta: 1:30:19 lr: 5.836016978436128e-06 loss: 0.0278 (0.0307) time: 3.0102 data: 0.0076 max mem: 33408 +Epoch: [36] [ 860/2639] eta: 1:29:50 lr: 5.83060462811521e-06 loss: 0.0331 (0.0306) time: 3.0563 data: 0.0078 max mem: 33408 +Epoch: [36] [ 870/2639] eta: 1:29:19 lr: 5.825191719503365e-06 loss: 0.0293 (0.0306) time: 3.0434 data: 0.0081 max mem: 33408 +Epoch: [36] [ 880/2639] eta: 1:28:50 lr: 5.8197782519664796e-06 loss: 0.0250 (0.0306) time: 3.0549 data: 0.0080 max mem: 33408 +Epoch: [36] [ 890/2639] eta: 1:28:20 lr: 5.814364224869038e-06 loss: 0.0279 (0.0306) time: 3.0718 data: 0.0080 max mem: 33408 +Epoch: [36] [ 900/2639] eta: 1:27:49 lr: 5.808949637574167e-06 loss: 0.0272 (0.0306) time: 3.0144 data: 0.0084 max mem: 33408 +Epoch: [36] [ 910/2639] eta: 1:27:20 lr: 5.8035344894435866e-06 loss: 0.0246 (0.0306) time: 3.0568 data: 0.0084 max mem: 33408 +Epoch: [36] [ 920/2639] eta: 1:26:49 lr: 5.798118779837648e-06 loss: 0.0257 (0.0306) time: 3.0396 data: 0.0080 max mem: 33408 +Epoch: [36] [ 930/2639] eta: 1:26:18 lr: 5.792702508115286e-06 loss: 0.0294 (0.0306) time: 3.0021 data: 0.0078 max mem: 33408 +Epoch: [36] [ 940/2639] eta: 1:25:48 lr: 5.787285673634061e-06 loss: 0.0301 (0.0306) time: 3.0284 data: 0.0076 max mem: 33408 +Epoch: [36] [ 950/2639] eta: 1:25:17 lr: 5.781868275750105e-06 loss: 0.0281 (0.0306) time: 2.9992 data: 0.0077 max mem: 33408 +Epoch: [36] [ 960/2639] eta: 1:24:47 lr: 5.776450313818166e-06 loss: 0.0299 (0.0307) time: 3.0102 data: 0.0079 max mem: 33408 +Epoch: [36] [ 970/2639] eta: 1:24:17 lr: 5.771031787191557e-06 loss: 0.0317 (0.0307) time: 3.0517 data: 0.0079 max mem: 33408 +Epoch: [36] [ 980/2639] eta: 1:23:46 lr: 5.7656126952221965e-06 loss: 0.0303 (0.0307) time: 3.0327 data: 0.0079 max mem: 33408 +Epoch: [36] [ 990/2639] eta: 1:23:16 lr: 5.760193037260559e-06 loss: 0.0292 (0.0307) time: 3.0159 data: 0.0076 max mem: 33408 +Epoch: [36] [1000/2639] eta: 1:22:45 lr: 5.754772812655717e-06 loss: 0.0276 (0.0306) time: 3.0209 data: 0.0077 max mem: 33408 +Epoch: [36] [1010/2639] eta: 1:22:14 lr: 5.749352020755286e-06 loss: 0.0276 (0.0306) time: 2.9806 data: 0.0079 max mem: 33408 +Epoch: [36] [1020/2639] eta: 1:21:44 lr: 5.743930660905473e-06 loss: 0.0310 (0.0306) time: 2.9959 data: 0.0077 max mem: 33408 +Epoch: [36] [1030/2639] eta: 1:21:13 lr: 5.73850873245102e-06 loss: 0.0303 (0.0306) time: 3.0384 data: 0.0075 max mem: 33408 +Epoch: [36] [1040/2639] eta: 1:20:43 lr: 5.733086234735247e-06 loss: 0.0298 (0.0306) time: 3.0291 data: 0.0076 max mem: 33408 +Epoch: [36] [1050/2639] eta: 1:20:14 lr: 5.727663167100002e-06 loss: 0.0290 (0.0306) time: 3.0560 data: 0.0076 max mem: 33408 +Epoch: [36] [1060/2639] eta: 1:19:43 lr: 5.722239528885696e-06 loss: 0.0290 (0.0306) time: 3.0490 data: 0.0075 max mem: 33408 +Epoch: [36] [1070/2639] eta: 1:19:13 lr: 5.716815319431282e-06 loss: 0.0304 (0.0306) time: 3.0143 data: 0.0077 max mem: 33408 +Epoch: [36] [1080/2639] eta: 1:18:42 lr: 5.711390538074232e-06 loss: 0.0307 (0.0306) time: 3.0302 data: 0.0078 max mem: 33408 +Epoch: [36] [1090/2639] eta: 1:18:12 lr: 5.70596518415057e-06 loss: 0.0276 (0.0307) time: 3.0481 data: 0.0080 max mem: 33408 +Epoch: [36] [1100/2639] eta: 1:17:42 lr: 5.7005392569948275e-06 loss: 0.0260 (0.0306) time: 3.0229 data: 0.0086 max mem: 33408 +Epoch: [36] [1110/2639] eta: 1:17:12 lr: 5.695112755940079e-06 loss: 0.0260 (0.0306) time: 3.0236 data: 0.0084 max mem: 33408 +Epoch: [36] [1120/2639] eta: 1:16:41 lr: 5.689685680317891e-06 loss: 0.0268 (0.0306) time: 3.0321 data: 0.0076 max mem: 33408 +Epoch: [36] [1130/2639] eta: 1:16:11 lr: 5.684258029458369e-06 loss: 0.0267 (0.0306) time: 3.0166 data: 0.0078 max mem: 33408 +Epoch: [36] [1140/2639] eta: 1:15:41 lr: 5.678829802690102e-06 loss: 0.0283 (0.0305) time: 3.0613 data: 0.0077 max mem: 33408 +Epoch: [36] [1150/2639] eta: 1:15:12 lr: 5.673400999340202e-06 loss: 0.0294 (0.0305) time: 3.0818 data: 0.0077 max mem: 33408 +Epoch: [36] [1160/2639] eta: 1:14:41 lr: 5.6679716187342555e-06 loss: 0.0317 (0.0306) time: 3.0511 data: 0.0077 max mem: 33408 +Epoch: [36] [1170/2639] eta: 1:14:12 lr: 5.6625416601963705e-06 loss: 0.0304 (0.0305) time: 3.0580 data: 0.0079 max mem: 33408 +Epoch: [36] [1180/2639] eta: 1:13:42 lr: 5.6571111230491095e-06 loss: 0.0289 (0.0306) time: 3.0831 data: 0.0081 max mem: 33408 +Epoch: [36] [1190/2639] eta: 1:13:12 lr: 5.65168000661355e-06 loss: 0.0289 (0.0306) time: 3.0760 data: 0.0076 max mem: 33408 +Epoch: [36] [1200/2639] eta: 1:12:41 lr: 5.6462483102092175e-06 loss: 0.0284 (0.0305) time: 3.0218 data: 0.0076 max mem: 33408 +Epoch: [36] [1210/2639] eta: 1:12:10 lr: 5.640816033154136e-06 loss: 0.0305 (0.0306) time: 2.9734 data: 0.0078 max mem: 33408 +Epoch: [36] [1220/2639] eta: 1:11:40 lr: 5.635383174764773e-06 loss: 0.0302 (0.0305) time: 3.0032 data: 0.0077 max mem: 33408 +Epoch: [36] [1230/2639] eta: 1:11:10 lr: 5.629949734356082e-06 loss: 0.0259 (0.0305) time: 3.0593 data: 0.0074 max mem: 33408 +Epoch: [36] [1240/2639] eta: 1:10:40 lr: 5.6245157112414485e-06 loss: 0.0267 (0.0305) time: 3.0636 data: 0.0078 max mem: 33408 +Epoch: [36] [1250/2639] eta: 1:10:10 lr: 5.619081104732737e-06 loss: 0.0300 (0.0305) time: 3.0471 data: 0.0078 max mem: 33408 +Epoch: [36] [1260/2639] eta: 1:09:39 lr: 5.613645914140232e-06 loss: 0.0282 (0.0305) time: 3.0305 data: 0.0082 max mem: 33408 +Epoch: [36] [1270/2639] eta: 1:09:08 lr: 5.608210138772684e-06 loss: 0.0298 (0.0305) time: 2.9718 data: 0.0085 max mem: 33408 +Epoch: [36] [1280/2639] eta: 1:08:37 lr: 5.602773777937257e-06 loss: 0.0320 (0.0305) time: 2.9462 data: 0.0079 max mem: 33408 +Epoch: [36] [1290/2639] eta: 1:08:07 lr: 5.59733683093957e-06 loss: 0.0307 (0.0306) time: 2.9895 data: 0.0083 max mem: 33408 +Epoch: [36] [1300/2639] eta: 1:07:36 lr: 5.591899297083644e-06 loss: 0.0307 (0.0306) time: 3.0001 data: 0.0087 max mem: 33408 +Epoch: [36] [1310/2639] eta: 1:07:06 lr: 5.586461175671938e-06 loss: 0.0276 (0.0305) time: 3.0118 data: 0.0085 max mem: 33408 +Epoch: [36] [1320/2639] eta: 1:06:35 lr: 5.581022466005328e-06 loss: 0.0287 (0.0306) time: 3.0419 data: 0.0081 max mem: 33408 +Epoch: [36] [1330/2639] eta: 1:06:05 lr: 5.575583167383081e-06 loss: 0.0285 (0.0306) time: 3.0398 data: 0.0085 max mem: 33408 +Epoch: [36] [1340/2639] eta: 1:05:35 lr: 5.570143279102892e-06 loss: 0.0285 (0.0306) time: 3.0520 data: 0.0088 max mem: 33408 +Epoch: [36] [1350/2639] eta: 1:05:06 lr: 5.564702800460833e-06 loss: 0.0270 (0.0306) time: 3.0831 data: 0.0082 max mem: 33408 +Epoch: [36] [1360/2639] eta: 1:04:35 lr: 5.559261730751394e-06 loss: 0.0264 (0.0306) time: 3.0471 data: 0.0078 max mem: 33408 +Epoch: [36] [1370/2639] eta: 1:04:04 lr: 5.553820069267428e-06 loss: 0.0272 (0.0306) time: 2.9867 data: 0.0076 max mem: 33408 +Epoch: [36] [1380/2639] eta: 1:03:34 lr: 5.548377815300197e-06 loss: 0.0299 (0.0306) time: 3.0017 data: 0.0080 max mem: 33408 +Epoch: [36] [1390/2639] eta: 1:03:04 lr: 5.542934968139315e-06 loss: 0.0290 (0.0306) time: 3.0380 data: 0.0081 max mem: 33408 +Epoch: [36] [1400/2639] eta: 1:02:34 lr: 5.537491527072792e-06 loss: 0.0278 (0.0306) time: 3.0427 data: 0.0083 max mem: 33408 +Epoch: [36] [1410/2639] eta: 1:02:03 lr: 5.532047491386984e-06 loss: 0.0288 (0.0306) time: 3.0310 data: 0.0081 max mem: 33408 +Epoch: [36] [1420/2639] eta: 1:01:33 lr: 5.526602860366629e-06 loss: 0.0263 (0.0306) time: 3.0438 data: 0.0082 max mem: 33408 +Epoch: [36] [1430/2639] eta: 1:01:04 lr: 5.5211576332947985e-06 loss: 0.0263 (0.0306) time: 3.1035 data: 0.0084 max mem: 33408 +Epoch: [36] [1440/2639] eta: 1:00:33 lr: 5.515711809452935e-06 loss: 0.0308 (0.0306) time: 3.0709 data: 0.0081 max mem: 33408 +Epoch: [36] [1450/2639] eta: 1:00:03 lr: 5.5102653881208045e-06 loss: 0.0306 (0.0306) time: 3.0102 data: 0.0081 max mem: 33408 +Epoch: [36] [1460/2639] eta: 0:59:32 lr: 5.5048183685765354e-06 loss: 0.0287 (0.0306) time: 3.0096 data: 0.0080 max mem: 33408 +Epoch: [36] [1470/2639] eta: 0:59:02 lr: 5.499370750096564e-06 loss: 0.0270 (0.0306) time: 2.9936 data: 0.0077 max mem: 33408 +Epoch: [36] [1480/2639] eta: 0:58:32 lr: 5.493922531955678e-06 loss: 0.0281 (0.0306) time: 3.0488 data: 0.0076 max mem: 33408 +Epoch: [36] [1490/2639] eta: 0:58:02 lr: 5.488473713426964e-06 loss: 0.0310 (0.0306) time: 3.0601 data: 0.0082 max mem: 33408 +Epoch: [36] [1500/2639] eta: 0:57:31 lr: 5.483024293781848e-06 loss: 0.0310 (0.0306) time: 2.9913 data: 0.0086 max mem: 33408 +Epoch: [36] [1510/2639] eta: 0:57:01 lr: 5.47757427229004e-06 loss: 0.0319 (0.0306) time: 3.0484 data: 0.0084 max mem: 33408 +Epoch: [36] [1520/2639] eta: 0:56:31 lr: 5.472123648219583e-06 loss: 0.0290 (0.0306) time: 3.0917 data: 0.0082 max mem: 33408 +Epoch: [36] [1530/2639] eta: 0:56:01 lr: 5.466672420836792e-06 loss: 0.0284 (0.0306) time: 3.0306 data: 0.0079 max mem: 33408 +Epoch: [36] [1540/2639] eta: 0:55:30 lr: 5.461220589406298e-06 loss: 0.0286 (0.0306) time: 2.9910 data: 0.0076 max mem: 33408 +Epoch: [36] [1550/2639] eta: 0:55:00 lr: 5.455768153190995e-06 loss: 0.0285 (0.0305) time: 3.0147 data: 0.0076 max mem: 33408 +Epoch: [36] [1560/2639] eta: 0:54:30 lr: 5.450315111452078e-06 loss: 0.0246 (0.0305) time: 3.0494 data: 0.0075 max mem: 33408 +Epoch: [36] [1570/2639] eta: 0:54:00 lr: 5.444861463449016e-06 loss: 0.0248 (0.0306) time: 3.0751 data: 0.0077 max mem: 33408 +Epoch: [36] [1580/2639] eta: 0:53:29 lr: 5.439407208439527e-06 loss: 0.0281 (0.0305) time: 3.0550 data: 0.0080 max mem: 33408 +Epoch: [36] [1590/2639] eta: 0:52:59 lr: 5.4339523456796205e-06 loss: 0.0290 (0.0306) time: 3.0179 data: 0.0084 max mem: 33408 +Epoch: [36] [1600/2639] eta: 0:52:29 lr: 5.4284968744235335e-06 loss: 0.0277 (0.0306) time: 3.0334 data: 0.0088 max mem: 33408 +Epoch: [36] [1610/2639] eta: 0:51:59 lr: 5.423040793923784e-06 loss: 0.0243 (0.0306) time: 3.0550 data: 0.0082 max mem: 33408 +Epoch: [36] [1620/2639] eta: 0:51:28 lr: 5.417584103431106e-06 loss: 0.0257 (0.0306) time: 3.0561 data: 0.0076 max mem: 33408 +Epoch: [36] [1630/2639] eta: 0:50:58 lr: 5.4121268021945e-06 loss: 0.0274 (0.0305) time: 3.0421 data: 0.0076 max mem: 33408 +Epoch: [36] [1640/2639] eta: 0:50:28 lr: 5.4066688894611725e-06 loss: 0.0275 (0.0305) time: 3.0199 data: 0.0080 max mem: 33408 +Epoch: [36] [1650/2639] eta: 0:49:57 lr: 5.401210364476584e-06 loss: 0.0315 (0.0305) time: 3.0048 data: 0.0086 max mem: 33408 +Epoch: [36] [1660/2639] eta: 0:49:27 lr: 5.395751226484388e-06 loss: 0.0256 (0.0305) time: 3.0277 data: 0.0086 max mem: 33408 +Epoch: [36] [1670/2639] eta: 0:48:57 lr: 5.390291474726478e-06 loss: 0.0265 (0.0305) time: 3.0275 data: 0.0078 max mem: 33408 +Epoch: [36] [1680/2639] eta: 0:48:27 lr: 5.384831108442932e-06 loss: 0.0279 (0.0305) time: 3.0583 data: 0.0077 max mem: 33408 +Epoch: [36] [1690/2639] eta: 0:47:56 lr: 5.3793701268720526e-06 loss: 0.0279 (0.0305) time: 3.0759 data: 0.0079 max mem: 33408 +Epoch: [36] [1700/2639] eta: 0:47:26 lr: 5.373908529250315e-06 loss: 0.0304 (0.0305) time: 3.0357 data: 0.0079 max mem: 33408 +Epoch: [36] [1710/2639] eta: 0:46:56 lr: 5.368446314812407e-06 loss: 0.0299 (0.0305) time: 3.0530 data: 0.0084 max mem: 33408 +Epoch: [36] [1720/2639] eta: 0:46:26 lr: 5.362983482791175e-06 loss: 0.0285 (0.0305) time: 3.0755 data: 0.0082 max mem: 33408 +Epoch: [36] [1730/2639] eta: 0:45:56 lr: 5.357520032417667e-06 loss: 0.0285 (0.0306) time: 3.0472 data: 0.0081 max mem: 33408 +Epoch: [36] [1740/2639] eta: 0:45:25 lr: 5.352055962921075e-06 loss: 0.0323 (0.0306) time: 3.0078 data: 0.0085 max mem: 33408 +Epoch: [36] [1750/2639] eta: 0:44:55 lr: 5.346591273528781e-06 loss: 0.0302 (0.0306) time: 3.0261 data: 0.0084 max mem: 33408 +Epoch: [36] [1760/2639] eta: 0:44:25 lr: 5.341125963466298e-06 loss: 0.0271 (0.0306) time: 3.1040 data: 0.0084 max mem: 33408 +Epoch: [36] [1770/2639] eta: 0:43:54 lr: 5.335660031957317e-06 loss: 0.0281 (0.0305) time: 3.0555 data: 0.0087 max mem: 33408 +Epoch: [36] [1780/2639] eta: 0:43:24 lr: 5.330193478223644e-06 loss: 0.0287 (0.0305) time: 3.0178 data: 0.0085 max mem: 33408 +Epoch: [36] [1790/2639] eta: 0:42:54 lr: 5.324726301485251e-06 loss: 0.0262 (0.0305) time: 3.0325 data: 0.0080 max mem: 33408 +Epoch: [36] [1800/2639] eta: 0:42:24 lr: 5.319258500960216e-06 loss: 0.0259 (0.0305) time: 3.0352 data: 0.0081 max mem: 33408 +Epoch: [36] [1810/2639] eta: 0:41:53 lr: 5.313790075864757e-06 loss: 0.0286 (0.0305) time: 3.0647 data: 0.0084 max mem: 33408 +Epoch: [36] [1820/2639] eta: 0:41:23 lr: 5.308321025413212e-06 loss: 0.0303 (0.0305) time: 3.0218 data: 0.0080 max mem: 33408 +Epoch: [36] [1830/2639] eta: 0:40:53 lr: 5.302851348818014e-06 loss: 0.0294 (0.0305) time: 3.0107 data: 0.0076 max mem: 33408 +Epoch: [36] [1840/2639] eta: 0:40:22 lr: 5.29738104528972e-06 loss: 0.0260 (0.0305) time: 3.0275 data: 0.0078 max mem: 33408 +Epoch: [36] [1850/2639] eta: 0:39:52 lr: 5.291910114036962e-06 loss: 0.0251 (0.0305) time: 3.0042 data: 0.0080 max mem: 33408 +Epoch: [36] [1860/2639] eta: 0:39:21 lr: 5.286438554266489e-06 loss: 0.0262 (0.0305) time: 3.0003 data: 0.0079 max mem: 33408 +Epoch: [36] [1870/2639] eta: 0:38:51 lr: 5.280966365183106e-06 loss: 0.0236 (0.0304) time: 3.0219 data: 0.0079 max mem: 33408 +Epoch: [36] [1880/2639] eta: 0:38:21 lr: 5.2754935459897245e-06 loss: 0.0259 (0.0304) time: 3.0261 data: 0.0080 max mem: 33408 +Epoch: [36] [1890/2639] eta: 0:37:50 lr: 5.270020095887297e-06 loss: 0.0284 (0.0304) time: 3.0164 data: 0.0079 max mem: 33408 +Epoch: [36] [1900/2639] eta: 0:37:20 lr: 5.264546014074867e-06 loss: 0.0277 (0.0304) time: 2.9859 data: 0.0077 max mem: 33408 +Epoch: [36] [1910/2639] eta: 0:36:49 lr: 5.259071299749508e-06 loss: 0.0325 (0.0305) time: 3.0018 data: 0.0079 max mem: 33408 +Epoch: [36] [1920/2639] eta: 0:36:19 lr: 5.25359595210637e-06 loss: 0.0307 (0.0305) time: 3.0217 data: 0.0080 max mem: 33408 +Epoch: [36] [1930/2639] eta: 0:35:49 lr: 5.248119970338618e-06 loss: 0.0255 (0.0304) time: 3.0359 data: 0.0077 max mem: 33408 +Epoch: [36] [1940/2639] eta: 0:35:18 lr: 5.24264335363748e-06 loss: 0.0257 (0.0305) time: 3.0497 data: 0.0076 max mem: 33408 +Epoch: [36] [1950/2639] eta: 0:34:48 lr: 5.2371661011921835e-06 loss: 0.0305 (0.0305) time: 3.0545 data: 0.0078 max mem: 33408 +Epoch: [36] [1960/2639] eta: 0:34:18 lr: 5.231688212190007e-06 loss: 0.0291 (0.0305) time: 3.0700 data: 0.0083 max mem: 33408 +Epoch: [36] [1970/2639] eta: 0:33:47 lr: 5.226209685816215e-06 loss: 0.0277 (0.0305) time: 3.0033 data: 0.0084 max mem: 33408 +Epoch: [36] [1980/2639] eta: 0:33:17 lr: 5.2207305212541056e-06 loss: 0.0287 (0.0305) time: 2.9796 data: 0.0081 max mem: 33408 +Epoch: [36] [1990/2639] eta: 0:32:47 lr: 5.21525071768495e-06 loss: 0.0319 (0.0305) time: 3.0517 data: 0.0079 max mem: 33408 +Epoch: [36] [2000/2639] eta: 0:32:17 lr: 5.209770274288039e-06 loss: 0.0319 (0.0305) time: 3.0694 data: 0.0081 max mem: 33408 +Epoch: [36] [2010/2639] eta: 0:31:46 lr: 5.204289190240621e-06 loss: 0.0305 (0.0305) time: 3.0208 data: 0.0081 max mem: 33408 +Epoch: [36] [2020/2639] eta: 0:31:16 lr: 5.19880746471795e-06 loss: 0.0262 (0.0305) time: 3.0179 data: 0.0078 max mem: 33408 +Epoch: [36] [2030/2639] eta: 0:30:46 lr: 5.193325096893225e-06 loss: 0.0262 (0.0305) time: 3.0136 data: 0.0077 max mem: 33408 +Epoch: [36] [2040/2639] eta: 0:30:15 lr: 5.187842085937631e-06 loss: 0.0317 (0.0305) time: 3.0083 data: 0.0079 max mem: 33408 +Epoch: [36] [2050/2639] eta: 0:29:45 lr: 5.182358431020287e-06 loss: 0.0284 (0.0305) time: 3.0307 data: 0.0079 max mem: 33408 +Epoch: [36] [2060/2639] eta: 0:29:15 lr: 5.176874131308276e-06 loss: 0.0284 (0.0305) time: 3.0251 data: 0.0080 max mem: 33408 +Epoch: [36] [2070/2639] eta: 0:28:44 lr: 5.171389185966625e-06 loss: 0.0258 (0.0305) time: 3.0275 data: 0.0082 max mem: 33408 +Epoch: [36] [2080/2639] eta: 0:28:14 lr: 5.165903594158273e-06 loss: 0.0325 (0.0305) time: 3.0404 data: 0.0081 max mem: 33408 +Epoch: [36] [2090/2639] eta: 0:27:44 lr: 5.160417355044112e-06 loss: 0.0318 (0.0305) time: 3.0396 data: 0.0080 max mem: 33408 +Epoch: [36] [2100/2639] eta: 0:27:13 lr: 5.154930467782924e-06 loss: 0.0294 (0.0305) time: 3.0257 data: 0.0078 max mem: 33408 +Epoch: [36] [2110/2639] eta: 0:26:43 lr: 5.14944293153143e-06 loss: 0.0315 (0.0305) time: 3.0457 data: 0.0077 max mem: 33408 +Epoch: [36] [2120/2639] eta: 0:26:13 lr: 5.143954745444226e-06 loss: 0.0315 (0.0305) time: 3.0818 data: 0.0079 max mem: 33408 +Epoch: [36] [2130/2639] eta: 0:25:43 lr: 5.138465908673833e-06 loss: 0.0277 (0.0305) time: 3.0336 data: 0.0080 max mem: 33408 +Epoch: [36] [2140/2639] eta: 0:25:12 lr: 5.132976420370627e-06 loss: 0.0256 (0.0305) time: 2.9597 data: 0.0078 max mem: 33408 +Epoch: [36] [2150/2639] eta: 0:24:42 lr: 5.127486279682894e-06 loss: 0.0303 (0.0305) time: 2.9539 data: 0.0077 max mem: 33408 +Epoch: [36] [2160/2639] eta: 0:24:11 lr: 5.121995485756766e-06 loss: 0.0272 (0.0305) time: 3.0023 data: 0.0078 max mem: 33408 +Epoch: [36] [2170/2639] eta: 0:23:41 lr: 5.116504037736263e-06 loss: 0.0272 (0.0305) time: 3.0610 data: 0.0077 max mem: 33408 +Epoch: [36] [2180/2639] eta: 0:23:11 lr: 5.111011934763236e-06 loss: 0.0288 (0.0305) time: 3.0965 data: 0.0075 max mem: 33408 +Epoch: [36] [2190/2639] eta: 0:22:41 lr: 5.105519175977411e-06 loss: 0.0281 (0.0305) time: 3.0625 data: 0.0079 max mem: 33408 +Epoch: [36] [2200/2639] eta: 0:22:10 lr: 5.100025760516327e-06 loss: 0.0288 (0.0305) time: 3.0084 data: 0.0083 max mem: 33408 +Epoch: [36] [2210/2639] eta: 0:21:40 lr: 5.09453168751538e-06 loss: 0.0336 (0.0305) time: 3.0040 data: 0.0082 max mem: 33408 +Epoch: [36] [2220/2639] eta: 0:21:10 lr: 5.089036956107767e-06 loss: 0.0322 (0.0305) time: 3.0209 data: 0.0084 max mem: 33408 +Epoch: [36] [2230/2639] eta: 0:20:39 lr: 5.083541565424525e-06 loss: 0.0328 (0.0306) time: 3.0346 data: 0.0084 max mem: 33408 +Epoch: [36] [2240/2639] eta: 0:20:09 lr: 5.078045514594472e-06 loss: 0.0335 (0.0306) time: 3.0258 data: 0.0081 max mem: 33408 +Epoch: [36] [2250/2639] eta: 0:19:38 lr: 5.072548802744255e-06 loss: 0.0340 (0.0306) time: 2.9947 data: 0.0081 max mem: 33408 +Epoch: [36] [2260/2639] eta: 0:19:08 lr: 5.067051428998284e-06 loss: 0.0271 (0.0306) time: 2.9885 data: 0.0083 max mem: 33408 +Epoch: [36] [2270/2639] eta: 0:18:38 lr: 5.061553392478777e-06 loss: 0.0263 (0.0306) time: 3.0463 data: 0.0081 max mem: 33408 +Epoch: [36] [2280/2639] eta: 0:18:08 lr: 5.056054692305705e-06 loss: 0.0269 (0.0306) time: 3.0422 data: 0.0077 max mem: 33408 +Epoch: [36] [2290/2639] eta: 0:17:37 lr: 5.050555327596828e-06 loss: 0.0283 (0.0306) time: 2.9897 data: 0.0081 max mem: 33408 +Epoch: [36] [2300/2639] eta: 0:17:07 lr: 5.045055297467639e-06 loss: 0.0259 (0.0306) time: 3.0109 data: 0.0082 max mem: 33408 +Epoch: [36] [2310/2639] eta: 0:16:37 lr: 5.039554601031401e-06 loss: 0.0271 (0.0306) time: 3.0328 data: 0.0078 max mem: 33408 +Epoch: [36] [2320/2639] eta: 0:16:06 lr: 5.034053237399119e-06 loss: 0.0287 (0.0306) time: 2.9931 data: 0.0075 max mem: 33408 +Epoch: [36] [2330/2639] eta: 0:15:36 lr: 5.028551205679509e-06 loss: 0.0256 (0.0305) time: 2.9662 data: 0.0075 max mem: 33408 +Epoch: [36] [2340/2639] eta: 0:15:05 lr: 5.023048504979039e-06 loss: 0.0249 (0.0305) time: 2.9856 data: 0.0080 max mem: 33408 +Epoch: [36] [2350/2639] eta: 0:14:35 lr: 5.017545134401866e-06 loss: 0.0253 (0.0305) time: 3.0168 data: 0.0080 max mem: 33408 +Epoch: [36] [2360/2639] eta: 0:14:05 lr: 5.012041093049881e-06 loss: 0.0253 (0.0305) time: 3.0164 data: 0.0078 max mem: 33408 +Epoch: [36] [2370/2639] eta: 0:13:35 lr: 5.006536380022647e-06 loss: 0.0280 (0.0305) time: 3.0191 data: 0.0079 max mem: 33408 +Epoch: [36] [2380/2639] eta: 0:13:04 lr: 5.00103099441744e-06 loss: 0.0276 (0.0305) time: 3.0058 data: 0.0084 max mem: 33408 +Epoch: [36] [2390/2639] eta: 0:12:34 lr: 4.995524935329197e-06 loss: 0.0269 (0.0305) time: 3.0066 data: 0.0087 max mem: 33408 +Epoch: [36] [2400/2639] eta: 0:12:04 lr: 4.990018201850546e-06 loss: 0.0269 (0.0305) time: 3.0599 data: 0.0080 max mem: 33408 +Epoch: [36] [2410/2639] eta: 0:11:33 lr: 4.984510793071759e-06 loss: 0.0253 (0.0305) time: 3.0629 data: 0.0077 max mem: 33408 +Epoch: [36] [2420/2639] eta: 0:11:03 lr: 4.9790027080807826e-06 loss: 0.0260 (0.0305) time: 3.0053 data: 0.0080 max mem: 33408 +Epoch: [36] [2430/2639] eta: 0:10:33 lr: 4.973493945963185e-06 loss: 0.0266 (0.0305) time: 2.9907 data: 0.0081 max mem: 33408 +Epoch: [36] [2440/2639] eta: 0:10:02 lr: 4.9679845058021975e-06 loss: 0.0269 (0.0305) time: 3.0414 data: 0.0084 max mem: 33408 +Epoch: [36] [2450/2639] eta: 0:09:32 lr: 4.962474386678654e-06 loss: 0.0239 (0.0305) time: 3.0506 data: 0.0090 max mem: 33408 +Epoch: [36] [2460/2639] eta: 0:09:02 lr: 4.956963587671029e-06 loss: 0.0273 (0.0305) time: 3.0169 data: 0.0084 max mem: 33408 +Epoch: [36] [2470/2639] eta: 0:08:32 lr: 4.951452107855384e-06 loss: 0.0284 (0.0305) time: 3.0148 data: 0.0080 max mem: 33408 +Epoch: [36] [2480/2639] eta: 0:08:01 lr: 4.945939946305403e-06 loss: 0.0263 (0.0305) time: 3.0694 data: 0.0081 max mem: 33408 +Epoch: [36] [2490/2639] eta: 0:07:31 lr: 4.940427102092338e-06 loss: 0.0268 (0.0305) time: 3.0611 data: 0.0078 max mem: 33408 +Epoch: [36] [2500/2639] eta: 0:07:01 lr: 4.934913574285046e-06 loss: 0.0283 (0.0305) time: 3.0100 data: 0.0075 max mem: 33408 +Epoch: [36] [2510/2639] eta: 0:06:30 lr: 4.929399361949933e-06 loss: 0.0333 (0.0305) time: 3.0444 data: 0.0078 max mem: 33408 +Epoch: [36] [2520/2639] eta: 0:06:00 lr: 4.923884464150993e-06 loss: 0.0313 (0.0305) time: 3.0995 data: 0.0081 max mem: 33408 +Epoch: [36] [2530/2639] eta: 0:05:30 lr: 4.918368879949744e-06 loss: 0.0271 (0.0305) time: 3.1050 data: 0.0078 max mem: 33408 +Epoch: [36] [2540/2639] eta: 0:05:00 lr: 4.912852608405272e-06 loss: 0.0260 (0.0305) time: 3.0892 data: 0.0078 max mem: 33408 +Epoch: [36] [2550/2639] eta: 0:04:29 lr: 4.907335648574197e-06 loss: 0.0263 (0.0305) time: 3.0873 data: 0.0077 max mem: 33408 +Epoch: [36] [2560/2639] eta: 0:03:59 lr: 4.901817999510641e-06 loss: 0.0275 (0.0305) time: 3.0402 data: 0.0077 max mem: 33408 +Epoch: [36] [2570/2639] eta: 0:03:29 lr: 4.896299660266273e-06 loss: 0.0287 (0.0305) time: 2.9851 data: 0.0078 max mem: 33408 +Epoch: [36] [2580/2639] eta: 0:02:58 lr: 4.8907806298902365e-06 loss: 0.0302 (0.0305) time: 3.0056 data: 0.0077 max mem: 33408 +Epoch: [36] [2590/2639] eta: 0:02:28 lr: 4.885260907429199e-06 loss: 0.0269 (0.0305) time: 3.0345 data: 0.0077 max mem: 33408 +Epoch: [36] [2600/2639] eta: 0:01:58 lr: 4.879740491927289e-06 loss: 0.0263 (0.0305) time: 3.0303 data: 0.0078 max mem: 33408 +Epoch: [36] [2610/2639] eta: 0:01:27 lr: 4.874219382426137e-06 loss: 0.0290 (0.0305) time: 3.0209 data: 0.0077 max mem: 33408 +Epoch: [36] [2620/2639] eta: 0:00:57 lr: 4.868697577964815e-06 loss: 0.0285 (0.0305) time: 3.0019 data: 0.0076 max mem: 33408 +Epoch: [36] [2630/2639] eta: 0:00:27 lr: 4.863175077579876e-06 loss: 0.0272 (0.0305) time: 2.9888 data: 0.0075 max mem: 33408 +Epoch: [36] Total time: 2:13:17 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 2:04:51 time: 2.9114 data: 2.8201 max mem: 33408 +Test: [ 100/2573] eta: 0:04:26 time: 0.0798 data: 0.0015 max mem: 33408 +Test: [ 200/2573] eta: 0:03:44 time: 0.0803 data: 0.0014 max mem: 33408 +Test: [ 300/2573] eta: 0:03:24 time: 0.0838 data: 0.0014 max mem: 33408 +Test: [ 400/2573] eta: 0:03:10 time: 0.0823 data: 0.0015 max mem: 33408 +Test: [ 500/2573] eta: 0:02:58 time: 0.0811 data: 0.0015 max mem: 33408 +Test: [ 600/2573] eta: 0:02:48 time: 0.0802 data: 0.0015 max mem: 33408 +Test: [ 700/2573] eta: 0:02:39 time: 0.0821 data: 0.0015 max mem: 33408 +Test: [ 800/2573] eta: 0:02:30 time: 0.0847 data: 0.0013 max mem: 33408 +Test: [ 900/2573] eta: 0:02:21 time: 0.0823 data: 0.0015 max mem: 33408 +Test: [1000/2573] eta: 0:02:12 time: 0.0809 data: 0.0015 max mem: 33408 +Test: [1100/2573] eta: 0:02:03 time: 0.0822 data: 0.0015 max mem: 33408 +Test: [1200/2573] eta: 0:01:55 time: 0.0818 data: 0.0014 max mem: 33408 +Test: [1300/2573] eta: 0:01:46 time: 0.0812 data: 0.0014 max mem: 33408 +Test: [1400/2573] eta: 0:01:37 time: 0.0801 data: 0.0015 max mem: 33408 +Test: [1500/2573] eta: 0:01:29 time: 0.0810 data: 0.0016 max mem: 33408 +Test: [1600/2573] eta: 0:01:21 time: 0.0848 data: 0.0016 max mem: 33408 +Test: [1700/2573] eta: 0:01:12 time: 0.0802 data: 0.0015 max mem: 33408 +Test: [1800/2573] eta: 0:01:04 time: 0.0828 data: 0.0015 max mem: 33408 +Test: [1900/2573] eta: 0:00:55 time: 0.0800 data: 0.0015 max mem: 33408 +Test: [2000/2573] eta: 0:00:47 time: 0.0810 data: 0.0014 max mem: 33408 +Test: [2100/2573] eta: 0:00:39 time: 0.0830 data: 0.0015 max mem: 33408 +Test: [2200/2573] eta: 0:00:30 time: 0.0824 data: 0.0013 max mem: 33408 +Test: [2300/2573] eta: 0:00:22 time: 0.0836 data: 0.0016 max mem: 33408 +Test: [2400/2573] eta: 0:00:14 time: 0.0790 data: 0.0016 max mem: 33408 +Test: [2500/2573] eta: 0:00:06 time: 0.0809 data: 0.0015 max mem: 33408 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: Total time: 0:03:33 +Final results: +Mean IoU is 65.22 + + precision@0.5 = 73.20 + precision@0.6 = 68.20 + precision@0.7 = 61.54 + precision@0.8 = 51.12 + precision@0.9 = 25.94 + overall IoU = 62.77 + +Average object IoU 65.22403316778426 +Overall IoU 62.77012634277344 +Better epoch: 36 + +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [37] [ 0/2639] eta: 3:55:28 lr: 4.858204231420373e-06 loss: 0.0245 (0.0245) time: 5.3537 data: 2.2303 max mem: 33408 +Epoch: [37] [ 10/2639] eta: 2:22:29 lr: 4.852680406117061e-06 loss: 0.0269 (0.0288) time: 3.2521 data: 0.2099 max mem: 33408 +Epoch: [37] [ 20/2639] eta: 2:18:15 lr: 4.8471558820816275e-06 loss: 0.0264 (0.0292) time: 3.0579 data: 0.0076 max mem: 33408 +Epoch: [37] [ 30/2639] eta: 2:16:04 lr: 4.841630658340586e-06 loss: 0.0264 (0.0296) time: 3.0615 data: 0.0079 max mem: 33408 +Epoch: [37] [ 40/2639] eta: 2:14:34 lr: 4.8361047339178825e-06 loss: 0.0299 (0.0303) time: 3.0435 data: 0.0084 max mem: 33408 +Epoch: [37] [ 50/2639] eta: 2:14:04 lr: 4.830578107834837e-06 loss: 0.0309 (0.0302) time: 3.0731 data: 0.0082 max mem: 33408 +Epoch: [37] [ 60/2639] eta: 2:13:05 lr: 4.825050779110181e-06 loss: 0.0309 (0.0306) time: 3.0747 data: 0.0077 max mem: 33408 +Epoch: [37] [ 70/2639] eta: 2:12:09 lr: 4.819522746759996e-06 loss: 0.0304 (0.0305) time: 3.0346 data: 0.0082 max mem: 33408 +Epoch: [37] [ 80/2639] eta: 2:11:15 lr: 4.81399400979776e-06 loss: 0.0314 (0.0308) time: 3.0198 data: 0.0083 max mem: 33408 +Epoch: [37] [ 90/2639] eta: 2:10:49 lr: 4.808464567234274e-06 loss: 0.0301 (0.0305) time: 3.0527 data: 0.0078 max mem: 33408 +Epoch: [37] [ 100/2639] eta: 2:10:18 lr: 4.8029344180777165e-06 loss: 0.0294 (0.0306) time: 3.0879 data: 0.0078 max mem: 33408 +Epoch: [37] [ 110/2639] eta: 2:09:41 lr: 4.797403561333572e-06 loss: 0.0293 (0.0307) time: 3.0666 data: 0.0079 max mem: 33408 +Epoch: [37] [ 120/2639] eta: 2:09:04 lr: 4.791871996004678e-06 loss: 0.0282 (0.0302) time: 3.0489 data: 0.0086 max mem: 33408 +Epoch: [37] [ 130/2639] eta: 2:08:32 lr: 4.786339721091154e-06 loss: 0.0250 (0.0300) time: 3.0578 data: 0.0083 max mem: 33408 +Epoch: [37] [ 140/2639] eta: 2:07:42 lr: 4.780806735590456e-06 loss: 0.0282 (0.0302) time: 3.0169 data: 0.0079 max mem: 33408 +Epoch: [37] [ 150/2639] eta: 2:07:12 lr: 4.775273038497301e-06 loss: 0.0287 (0.0301) time: 3.0165 data: 0.0085 max mem: 33408 +Epoch: [37] [ 160/2639] eta: 2:06:39 lr: 4.769738628803717e-06 loss: 0.0290 (0.0303) time: 3.0604 data: 0.0084 max mem: 33408 +Epoch: [37] [ 170/2639] eta: 2:05:59 lr: 4.764203505498972e-06 loss: 0.0317 (0.0304) time: 3.0261 data: 0.0077 max mem: 33408 +Epoch: [37] [ 180/2639] eta: 2:05:29 lr: 4.758667667569619e-06 loss: 0.0319 (0.0304) time: 3.0340 data: 0.0076 max mem: 33408 +Epoch: [37] [ 190/2639] eta: 2:05:02 lr: 4.753131113999455e-06 loss: 0.0262 (0.0301) time: 3.0802 data: 0.0076 max mem: 33408 +Epoch: [37] [ 200/2639] eta: 2:04:24 lr: 4.747593843769497e-06 loss: 0.0262 (0.0302) time: 3.0441 data: 0.0074 max mem: 33408 +Epoch: [37] [ 210/2639] eta: 2:03:50 lr: 4.742055855858015e-06 loss: 0.0277 (0.0301) time: 3.0160 data: 0.0079 max mem: 33408 +Epoch: [37] [ 220/2639] eta: 2:03:19 lr: 4.736517149240468e-06 loss: 0.0277 (0.0302) time: 3.0463 data: 0.0080 max mem: 33408 +Epoch: [37] [ 230/2639] eta: 2:02:43 lr: 4.730977722889544e-06 loss: 0.0273 (0.0302) time: 3.0304 data: 0.0077 max mem: 33408 +Epoch: [37] [ 240/2639] eta: 2:02:14 lr: 4.725437575775101e-06 loss: 0.0285 (0.0301) time: 3.0375 data: 0.0080 max mem: 33408 +Epoch: [37] [ 250/2639] eta: 2:01:37 lr: 4.7198967068642015e-06 loss: 0.0258 (0.0300) time: 3.0322 data: 0.0084 max mem: 33408 +Epoch: [37] [ 260/2639] eta: 2:00:59 lr: 4.714355115121052e-06 loss: 0.0223 (0.0297) time: 2.9825 data: 0.0086 max mem: 33408 +Epoch: [37] [ 270/2639] eta: 2:00:26 lr: 4.7088127995070476e-06 loss: 0.0240 (0.0296) time: 2.9966 data: 0.0085 max mem: 33408 +Epoch: [37] [ 280/2639] eta: 1:59:51 lr: 4.7032697589807e-06 loss: 0.0271 (0.0296) time: 3.0118 data: 0.0079 max mem: 33408 +Epoch: [37] [ 290/2639] eta: 1:59:22 lr: 4.6977259924976846e-06 loss: 0.0283 (0.0298) time: 3.0319 data: 0.0079 max mem: 33408 +Epoch: [37] [ 300/2639] eta: 1:58:55 lr: 4.692181499010776e-06 loss: 0.0293 (0.0298) time: 3.0757 data: 0.0084 max mem: 33408 +Epoch: [37] [ 310/2639] eta: 1:58:29 lr: 4.686636277469884e-06 loss: 0.0297 (0.0298) time: 3.1025 data: 0.0082 max mem: 33408 +Epoch: [37] [ 320/2639] eta: 1:57:53 lr: 4.681090326821997e-06 loss: 0.0284 (0.0298) time: 3.0480 data: 0.0078 max mem: 33408 +Epoch: [37] [ 330/2639] eta: 1:57:24 lr: 4.675543646011214e-06 loss: 0.0283 (0.0298) time: 3.0284 data: 0.0079 max mem: 33408 +Epoch: [37] [ 340/2639] eta: 1:56:53 lr: 4.669996233978688e-06 loss: 0.0270 (0.0297) time: 3.0578 data: 0.0078 max mem: 33408 +Epoch: [37] [ 350/2639] eta: 1:56:22 lr: 4.664448089662659e-06 loss: 0.0276 (0.0299) time: 3.0364 data: 0.0078 max mem: 33408 +Epoch: [37] [ 360/2639] eta: 1:55:47 lr: 4.658899211998398e-06 loss: 0.0301 (0.0300) time: 3.0086 data: 0.0076 max mem: 33408 +Epoch: [37] [ 370/2639] eta: 1:55:13 lr: 4.6533495999182405e-06 loss: 0.0330 (0.0301) time: 2.9901 data: 0.0078 max mem: 33408 +Epoch: [37] [ 380/2639] eta: 1:54:44 lr: 4.647799252351525e-06 loss: 0.0265 (0.0299) time: 3.0316 data: 0.0079 max mem: 33408 +Epoch: [37] [ 390/2639] eta: 1:54:13 lr: 4.64224816822463e-06 loss: 0.0252 (0.0300) time: 3.0550 data: 0.0077 max mem: 33408 +Epoch: [37] [ 400/2639] eta: 1:53:44 lr: 4.636696346460917e-06 loss: 0.0267 (0.0299) time: 3.0545 data: 0.0077 max mem: 33408 +Epoch: [37] [ 410/2639] eta: 1:53:13 lr: 4.63114378598076e-06 loss: 0.0284 (0.0299) time: 3.0565 data: 0.0081 max mem: 33408 +Epoch: [37] [ 420/2639] eta: 1:52:43 lr: 4.625590485701491e-06 loss: 0.0292 (0.0300) time: 3.0516 data: 0.0084 max mem: 33408 +Epoch: [37] [ 430/2639] eta: 1:52:13 lr: 4.620036444537424e-06 loss: 0.0276 (0.0300) time: 3.0521 data: 0.0084 max mem: 33408 +Epoch: [37] [ 440/2639] eta: 1:51:44 lr: 4.614481661399829e-06 loss: 0.0270 (0.0300) time: 3.0642 data: 0.0080 max mem: 33408 +Epoch: [37] [ 450/2639] eta: 1:51:15 lr: 4.608926135196899e-06 loss: 0.0296 (0.0300) time: 3.0847 data: 0.0078 max mem: 33408 +Epoch: [37] [ 460/2639] eta: 1:50:42 lr: 4.603369864833779e-06 loss: 0.0311 (0.0300) time: 3.0450 data: 0.0080 max mem: 33408 +Epoch: [37] [ 470/2639] eta: 1:50:11 lr: 4.597812849212508e-06 loss: 0.0295 (0.0300) time: 3.0123 data: 0.0079 max mem: 33408 +Epoch: [37] [ 480/2639] eta: 1:49:43 lr: 4.59225508723205e-06 loss: 0.0273 (0.0299) time: 3.0705 data: 0.0081 max mem: 33408 +Epoch: [37] [ 490/2639] eta: 1:49:10 lr: 4.586696577788237e-06 loss: 0.0272 (0.0299) time: 3.0533 data: 0.0082 max mem: 33408 +Epoch: [37] [ 500/2639] eta: 1:48:42 lr: 4.581137319773802e-06 loss: 0.0250 (0.0299) time: 3.0474 data: 0.0078 max mem: 33408 +Epoch: [37] [ 510/2639] eta: 1:48:08 lr: 4.575577312078318e-06 loss: 0.0251 (0.0298) time: 3.0290 data: 0.0080 max mem: 33408 +Epoch: [37] [ 520/2639] eta: 1:47:33 lr: 4.570016553588234e-06 loss: 0.0257 (0.0298) time: 2.9444 data: 0.0087 max mem: 33408 +Epoch: [37] [ 530/2639] eta: 1:46:59 lr: 4.56445504318681e-06 loss: 0.0257 (0.0297) time: 2.9524 data: 0.0082 max mem: 33408 +Epoch: [37] [ 540/2639] eta: 1:46:27 lr: 4.558892779754159e-06 loss: 0.0297 (0.0298) time: 2.9873 data: 0.0077 max mem: 33408 +Epoch: [37] [ 550/2639] eta: 1:45:57 lr: 4.553329762167178e-06 loss: 0.0295 (0.0297) time: 3.0232 data: 0.0079 max mem: 33408 +Epoch: [37] [ 560/2639] eta: 1:45:24 lr: 4.547765989299589e-06 loss: 0.0330 (0.0298) time: 3.0165 data: 0.0081 max mem: 33408 +Epoch: [37] [ 570/2639] eta: 1:44:51 lr: 4.542201460021869e-06 loss: 0.0330 (0.0298) time: 2.9786 data: 0.0082 max mem: 33408 +Epoch: [37] [ 580/2639] eta: 1:44:19 lr: 4.536636173201297e-06 loss: 0.0283 (0.0298) time: 2.9703 data: 0.0082 max mem: 33408 +Epoch: [37] [ 590/2639] eta: 1:43:50 lr: 4.53107012770188e-06 loss: 0.0283 (0.0298) time: 3.0324 data: 0.0079 max mem: 33408 +Epoch: [37] [ 600/2639] eta: 1:43:17 lr: 4.525503322384394e-06 loss: 0.0254 (0.0297) time: 3.0277 data: 0.0076 max mem: 33408 +Epoch: [37] [ 610/2639] eta: 1:42:44 lr: 4.519935756106321e-06 loss: 0.0261 (0.0297) time: 2.9706 data: 0.0075 max mem: 33408 +Epoch: [37] [ 620/2639] eta: 1:42:13 lr: 4.514367427721883e-06 loss: 0.0256 (0.0297) time: 2.9992 data: 0.0076 max mem: 33408 +Epoch: [37] [ 630/2639] eta: 1:41:43 lr: 4.508798336081979e-06 loss: 0.0248 (0.0297) time: 3.0323 data: 0.0078 max mem: 33408 +Epoch: [37] [ 640/2639] eta: 1:41:11 lr: 4.503228480034221e-06 loss: 0.0258 (0.0297) time: 3.0131 data: 0.0083 max mem: 33408 +Epoch: [37] [ 650/2639] eta: 1:40:41 lr: 4.497657858422869e-06 loss: 0.0304 (0.0297) time: 3.0099 data: 0.0085 max mem: 33408 +Epoch: [37] [ 660/2639] eta: 1:40:13 lr: 4.49208647008887e-06 loss: 0.0260 (0.0297) time: 3.0720 data: 0.0079 max mem: 33408 +Epoch: [37] [ 670/2639] eta: 1:39:41 lr: 4.486514313869786e-06 loss: 0.0260 (0.0298) time: 3.0556 data: 0.0080 max mem: 33408 +Epoch: [37] [ 680/2639] eta: 1:39:09 lr: 4.4809413885998335e-06 loss: 0.0316 (0.0299) time: 2.9881 data: 0.0081 max mem: 33408 +Epoch: [37] [ 690/2639] eta: 1:38:38 lr: 4.475367693109844e-06 loss: 0.0308 (0.0299) time: 3.0023 data: 0.0076 max mem: 33408 +Epoch: [37] [ 700/2639] eta: 1:38:08 lr: 4.469793226227232e-06 loss: 0.0264 (0.0299) time: 3.0337 data: 0.0075 max mem: 33408 +Epoch: [37] [ 710/2639] eta: 1:37:39 lr: 4.464217986776025e-06 loss: 0.0260 (0.0299) time: 3.0612 data: 0.0082 max mem: 33408 +Epoch: [37] [ 720/2639] eta: 1:37:08 lr: 4.458641973576796e-06 loss: 0.0258 (0.0298) time: 3.0552 data: 0.0086 max mem: 33408 +Epoch: [37] [ 730/2639] eta: 1:36:36 lr: 4.453065185446704e-06 loss: 0.0292 (0.0298) time: 3.0030 data: 0.0082 max mem: 33408 +Epoch: [37] [ 740/2639] eta: 1:36:06 lr: 4.447487621199423e-06 loss: 0.0282 (0.0298) time: 3.0096 data: 0.0080 max mem: 33408 +Epoch: [37] [ 750/2639] eta: 1:35:35 lr: 4.441909279645183e-06 loss: 0.0282 (0.0298) time: 3.0344 data: 0.0078 max mem: 33408 +Epoch: [37] [ 760/2639] eta: 1:35:04 lr: 4.4363301595907e-06 loss: 0.0288 (0.0298) time: 3.0027 data: 0.0075 max mem: 33408 +Epoch: [37] [ 770/2639] eta: 1:34:32 lr: 4.430750259839213e-06 loss: 0.0288 (0.0298) time: 2.9899 data: 0.0076 max mem: 33408 +Epoch: [37] [ 780/2639] eta: 1:34:03 lr: 4.42516957919042e-06 loss: 0.0283 (0.0298) time: 3.0402 data: 0.0077 max mem: 33408 +Epoch: [37] [ 790/2639] eta: 1:33:33 lr: 4.419588116440512e-06 loss: 0.0268 (0.0297) time: 3.0713 data: 0.0078 max mem: 33408 +Epoch: [37] [ 800/2639] eta: 1:33:01 lr: 4.414005870382104e-06 loss: 0.0263 (0.0297) time: 3.0013 data: 0.0078 max mem: 33408 +Epoch: [37] [ 810/2639] eta: 1:32:30 lr: 4.408422839804277e-06 loss: 0.0244 (0.0297) time: 2.9734 data: 0.0078 max mem: 33408 +Epoch: [37] [ 820/2639] eta: 1:31:59 lr: 4.402839023492504e-06 loss: 0.0301 (0.0297) time: 3.0106 data: 0.0081 max mem: 33408 +Epoch: [37] [ 830/2639] eta: 1:31:30 lr: 4.397254420228692e-06 loss: 0.0312 (0.0297) time: 3.0583 data: 0.0080 max mem: 33408 +Epoch: [37] [ 840/2639] eta: 1:31:00 lr: 4.391669028791109e-06 loss: 0.0298 (0.0298) time: 3.0622 data: 0.0077 max mem: 33408 +Epoch: [37] [ 850/2639] eta: 1:30:30 lr: 4.386082847954426e-06 loss: 0.0298 (0.0298) time: 3.0388 data: 0.0079 max mem: 33408 +Epoch: [37] [ 860/2639] eta: 1:29:58 lr: 4.380495876489645e-06 loss: 0.0278 (0.0298) time: 3.0182 data: 0.0079 max mem: 33408 +Epoch: [37] [ 870/2639] eta: 1:29:28 lr: 4.374908113164133e-06 loss: 0.0278 (0.0298) time: 3.0090 data: 0.0080 max mem: 33408 +Epoch: [37] [ 880/2639] eta: 1:28:57 lr: 4.369319556741564e-06 loss: 0.0264 (0.0298) time: 3.0269 data: 0.0081 max mem: 33408 +Epoch: [37] [ 890/2639] eta: 1:28:25 lr: 4.3637302059819395e-06 loss: 0.0308 (0.0299) time: 2.9792 data: 0.0083 max mem: 33408 +Epoch: [37] [ 900/2639] eta: 1:27:53 lr: 4.358140059641535e-06 loss: 0.0281 (0.0298) time: 2.9570 data: 0.0088 max mem: 33408 +Epoch: [37] [ 910/2639] eta: 1:27:24 lr: 4.352549116472925e-06 loss: 0.0263 (0.0298) time: 3.0251 data: 0.0088 max mem: 33408 +Epoch: [37] [ 920/2639] eta: 1:26:55 lr: 4.34695737522492e-06 loss: 0.0257 (0.0298) time: 3.0793 data: 0.0084 max mem: 33408 +Epoch: [37] [ 930/2639] eta: 1:26:24 lr: 4.341364834642595e-06 loss: 0.0260 (0.0298) time: 3.0395 data: 0.0084 max mem: 33408 +Epoch: [37] [ 940/2639] eta: 1:25:52 lr: 4.335771493467251e-06 loss: 0.0276 (0.0298) time: 2.9880 data: 0.0085 max mem: 33408 +Epoch: [37] [ 950/2639] eta: 1:25:21 lr: 4.330177350436381e-06 loss: 0.0302 (0.0298) time: 2.9842 data: 0.0081 max mem: 33408 +Epoch: [37] [ 960/2639] eta: 1:24:51 lr: 4.324582404283698e-06 loss: 0.0302 (0.0298) time: 3.0161 data: 0.0083 max mem: 33408 +Epoch: [37] [ 970/2639] eta: 1:24:21 lr: 4.318986653739064e-06 loss: 0.0245 (0.0297) time: 3.0397 data: 0.0085 max mem: 33408 +Epoch: [37] [ 980/2639] eta: 1:23:51 lr: 4.313390097528528e-06 loss: 0.0296 (0.0298) time: 3.0510 data: 0.0079 max mem: 33408 +Epoch: [37] [ 990/2639] eta: 1:23:21 lr: 4.307792734374256e-06 loss: 0.0318 (0.0298) time: 3.0439 data: 0.0075 max mem: 33408 +Epoch: [37] [1000/2639] eta: 1:22:50 lr: 4.3021945629945645e-06 loss: 0.0276 (0.0298) time: 3.0198 data: 0.0074 max mem: 33408 +Epoch: [37] [1010/2639] eta: 1:22:18 lr: 4.296595582103853e-06 loss: 0.0269 (0.0297) time: 2.9840 data: 0.0077 max mem: 33408 +Epoch: [37] [1020/2639] eta: 1:21:48 lr: 4.290995790412636e-06 loss: 0.0262 (0.0298) time: 2.9823 data: 0.0075 max mem: 33408 +Epoch: [37] [1030/2639] eta: 1:21:17 lr: 4.285395186627474e-06 loss: 0.0262 (0.0297) time: 3.0207 data: 0.0073 max mem: 33408 +Epoch: [37] [1040/2639] eta: 1:20:48 lr: 4.2797937694510135e-06 loss: 0.0228 (0.0297) time: 3.0556 data: 0.0073 max mem: 33408 +Epoch: [37] [1050/2639] eta: 1:20:16 lr: 4.274191537581907e-06 loss: 0.0291 (0.0297) time: 3.0214 data: 0.0073 max mem: 33408 +Epoch: [37] [1060/2639] eta: 1:19:46 lr: 4.2685884897148545e-06 loss: 0.0284 (0.0298) time: 2.9871 data: 0.0075 max mem: 33408 +Epoch: [37] [1070/2639] eta: 1:19:15 lr: 4.262984624540533e-06 loss: 0.0284 (0.0298) time: 3.0053 data: 0.0076 max mem: 33408 +Epoch: [37] [1080/2639] eta: 1:18:45 lr: 4.257379940745627e-06 loss: 0.0278 (0.0298) time: 3.0277 data: 0.0075 max mem: 33408 +Epoch: [37] [1090/2639] eta: 1:18:15 lr: 4.25177443701276e-06 loss: 0.0258 (0.0297) time: 3.0466 data: 0.0075 max mem: 33408 +Epoch: [37] [1100/2639] eta: 1:17:45 lr: 4.246168112020529e-06 loss: 0.0261 (0.0297) time: 3.0593 data: 0.0078 max mem: 33408 +Epoch: [37] [1110/2639] eta: 1:17:15 lr: 4.240560964443435e-06 loss: 0.0290 (0.0297) time: 3.0485 data: 0.0079 max mem: 33408 +Epoch: [37] [1120/2639] eta: 1:16:44 lr: 4.234952992951913e-06 loss: 0.0287 (0.0297) time: 3.0022 data: 0.0079 max mem: 33408 +Epoch: [37] [1130/2639] eta: 1:16:14 lr: 4.229344196212263e-06 loss: 0.0280 (0.0298) time: 3.0322 data: 0.0077 max mem: 33408 +Epoch: [37] [1140/2639] eta: 1:15:44 lr: 4.2237345728866855e-06 loss: 0.0280 (0.0298) time: 3.0565 data: 0.0078 max mem: 33408 +Epoch: [37] [1150/2639] eta: 1:15:14 lr: 4.218124121633206e-06 loss: 0.0291 (0.0298) time: 3.0717 data: 0.0079 max mem: 33408 +Epoch: [37] [1160/2639] eta: 1:14:43 lr: 4.212512841105706e-06 loss: 0.0281 (0.0298) time: 3.0359 data: 0.0078 max mem: 33408 +Epoch: [37] [1170/2639] eta: 1:14:13 lr: 4.20690072995388e-06 loss: 0.0253 (0.0298) time: 2.9972 data: 0.0078 max mem: 33408 +Epoch: [37] [1180/2639] eta: 1:13:42 lr: 4.201287786823204e-06 loss: 0.0286 (0.0298) time: 3.0177 data: 0.0080 max mem: 33408 +Epoch: [37] [1190/2639] eta: 1:13:12 lr: 4.195674010354951e-06 loss: 0.0268 (0.0298) time: 3.0129 data: 0.0078 max mem: 33408 +Epoch: [37] [1200/2639] eta: 1:12:41 lr: 4.190059399186129e-06 loss: 0.0268 (0.0298) time: 2.9980 data: 0.0079 max mem: 33408 +Epoch: [37] [1210/2639] eta: 1:12:12 lr: 4.184443951949511e-06 loss: 0.0321 (0.0298) time: 3.0464 data: 0.0079 max mem: 33408 +Epoch: [37] [1220/2639] eta: 1:11:41 lr: 4.178827667273559e-06 loss: 0.0258 (0.0298) time: 3.0582 data: 0.0079 max mem: 33408 +Epoch: [37] [1230/2639] eta: 1:11:10 lr: 4.173210543782459e-06 loss: 0.0271 (0.0298) time: 3.0037 data: 0.0081 max mem: 33408 +Epoch: [37] [1240/2639] eta: 1:10:40 lr: 4.167592580096054e-06 loss: 0.0271 (0.0298) time: 3.0191 data: 0.0082 max mem: 33408 +Epoch: [37] [1250/2639] eta: 1:10:11 lr: 4.161973774829865e-06 loss: 0.0262 (0.0298) time: 3.0715 data: 0.0077 max mem: 33408 +Epoch: [37] [1260/2639] eta: 1:09:40 lr: 4.15635412659503e-06 loss: 0.0260 (0.0298) time: 3.0804 data: 0.0075 max mem: 33408 +Epoch: [37] [1270/2639] eta: 1:09:10 lr: 4.150733633998329e-06 loss: 0.0251 (0.0298) time: 3.0248 data: 0.0082 max mem: 33408 +Epoch: [37] [1280/2639] eta: 1:08:39 lr: 4.145112295642113e-06 loss: 0.0259 (0.0298) time: 3.0012 data: 0.0083 max mem: 33408 +Epoch: [37] [1290/2639] eta: 1:08:09 lr: 4.139490110124337e-06 loss: 0.0259 (0.0299) time: 3.0357 data: 0.0078 max mem: 33408 +Epoch: [37] [1300/2639] eta: 1:07:40 lr: 4.133867076038482e-06 loss: 0.0271 (0.0299) time: 3.0872 data: 0.0081 max mem: 33408 +Epoch: [37] [1310/2639] eta: 1:07:09 lr: 4.1282431919735985e-06 loss: 0.0291 (0.0299) time: 3.0566 data: 0.0083 max mem: 33408 +Epoch: [37] [1320/2639] eta: 1:06:40 lr: 4.122618456514216e-06 loss: 0.0313 (0.0299) time: 3.0580 data: 0.0080 max mem: 33408 +Epoch: [37] [1330/2639] eta: 1:06:09 lr: 4.11699286824039e-06 loss: 0.0316 (0.0299) time: 3.0714 data: 0.0083 max mem: 33408 +Epoch: [37] [1340/2639] eta: 1:05:39 lr: 4.111366425727618e-06 loss: 0.0265 (0.0299) time: 3.0396 data: 0.0082 max mem: 33408 +Epoch: [37] [1350/2639] eta: 1:05:08 lr: 4.105739127546876e-06 loss: 0.0272 (0.0299) time: 3.0053 data: 0.0077 max mem: 33408 +Epoch: [37] [1360/2639] eta: 1:04:38 lr: 4.100110972264544e-06 loss: 0.0272 (0.0299) time: 3.0173 data: 0.0077 max mem: 33408 +Epoch: [37] [1370/2639] eta: 1:04:07 lr: 4.094481958442432e-06 loss: 0.0267 (0.0299) time: 3.0353 data: 0.0079 max mem: 33408 +Epoch: [37] [1380/2639] eta: 1:03:37 lr: 4.0888520846377135e-06 loss: 0.0271 (0.0299) time: 3.0157 data: 0.0083 max mem: 33408 +Epoch: [37] [1390/2639] eta: 1:03:07 lr: 4.08322134940295e-06 loss: 0.0271 (0.0299) time: 3.0239 data: 0.0079 max mem: 33408 +Epoch: [37] [1400/2639] eta: 1:02:36 lr: 4.077589751286019e-06 loss: 0.0286 (0.0300) time: 2.9835 data: 0.0076 max mem: 33408 +Epoch: [37] [1410/2639] eta: 1:02:06 lr: 4.07195728883014e-06 loss: 0.0310 (0.0300) time: 3.0106 data: 0.0076 max mem: 33408 +Epoch: [37] [1420/2639] eta: 1:01:35 lr: 4.066323960573824e-06 loss: 0.0310 (0.0300) time: 3.0429 data: 0.0076 max mem: 33408 +Epoch: [37] [1430/2639] eta: 1:01:04 lr: 4.060689765050844e-06 loss: 0.0273 (0.0300) time: 2.9896 data: 0.0078 max mem: 33408 +Epoch: [37] [1440/2639] eta: 1:00:34 lr: 4.055054700790246e-06 loss: 0.0302 (0.0300) time: 2.9826 data: 0.0079 max mem: 33408 +Epoch: [37] [1450/2639] eta: 1:00:04 lr: 4.049418766316284e-06 loss: 0.0302 (0.0300) time: 3.0427 data: 0.0079 max mem: 33408 +Epoch: [37] [1460/2639] eta: 0:59:34 lr: 4.0437819601484425e-06 loss: 0.0255 (0.0300) time: 3.0810 data: 0.0079 max mem: 33408 +Epoch: [37] [1470/2639] eta: 0:59:03 lr: 4.0381442808013635e-06 loss: 0.0250 (0.0299) time: 3.0350 data: 0.0080 max mem: 33408 +Epoch: [37] [1480/2639] eta: 0:58:33 lr: 4.0325057267848766e-06 loss: 0.0287 (0.0300) time: 2.9966 data: 0.0080 max mem: 33408 +Epoch: [37] [1490/2639] eta: 0:58:03 lr: 4.026866296603923e-06 loss: 0.0299 (0.0300) time: 3.0232 data: 0.0077 max mem: 33408 +Epoch: [37] [1500/2639] eta: 0:57:32 lr: 4.021225988758581e-06 loss: 0.0324 (0.0300) time: 3.0262 data: 0.0079 max mem: 33408 +Epoch: [37] [1510/2639] eta: 0:57:01 lr: 4.0155848017439985e-06 loss: 0.0294 (0.0300) time: 3.0017 data: 0.0079 max mem: 33408 +Epoch: [37] [1520/2639] eta: 0:56:30 lr: 4.00994273405041e-06 loss: 0.0274 (0.0300) time: 2.9563 data: 0.0077 max mem: 33408 +Epoch: [37] [1530/2639] eta: 0:56:00 lr: 4.00429978416307e-06 loss: 0.0282 (0.0299) time: 2.9422 data: 0.0077 max mem: 33408 +Epoch: [37] [1540/2639] eta: 0:55:29 lr: 3.998655950562277e-06 loss: 0.0251 (0.0299) time: 2.9762 data: 0.0077 max mem: 33408 +Epoch: [37] [1550/2639] eta: 0:54:58 lr: 3.993011231723297e-06 loss: 0.0252 (0.0299) time: 2.9764 data: 0.0076 max mem: 33408 +Epoch: [37] [1560/2639] eta: 0:54:28 lr: 3.987365626116392e-06 loss: 0.0277 (0.0299) time: 3.0003 data: 0.0078 max mem: 33408 +Epoch: [37] [1570/2639] eta: 0:53:58 lr: 3.9817191322067445e-06 loss: 0.0295 (0.0299) time: 3.0304 data: 0.0082 max mem: 33408 +Epoch: [37] [1580/2639] eta: 0:53:27 lr: 3.976071748454483e-06 loss: 0.0295 (0.0299) time: 3.0220 data: 0.0081 max mem: 33408 +Epoch: [37] [1590/2639] eta: 0:52:57 lr: 3.970423473314604e-06 loss: 0.0288 (0.0299) time: 2.9947 data: 0.0081 max mem: 33408 +Epoch: [37] [1600/2639] eta: 0:52:26 lr: 3.964774305237005e-06 loss: 0.0282 (0.0299) time: 3.0132 data: 0.0079 max mem: 33408 +Epoch: [37] [1610/2639] eta: 0:51:56 lr: 3.959124242666398e-06 loss: 0.0271 (0.0299) time: 3.0584 data: 0.0078 max mem: 33408 +Epoch: [37] [1620/2639] eta: 0:51:26 lr: 3.953473284042345e-06 loss: 0.0316 (0.0300) time: 3.0374 data: 0.0078 max mem: 33408 +Epoch: [37] [1630/2639] eta: 0:50:56 lr: 3.947821427799175e-06 loss: 0.0316 (0.0300) time: 3.0012 data: 0.0077 max mem: 33408 +Epoch: [37] [1640/2639] eta: 0:50:25 lr: 3.942168672366015e-06 loss: 0.0263 (0.0300) time: 3.0170 data: 0.0076 max mem: 33408 +Epoch: [37] [1650/2639] eta: 0:49:55 lr: 3.9365150161667035e-06 loss: 0.0263 (0.0300) time: 3.0219 data: 0.0077 max mem: 33408 +Epoch: [37] [1660/2639] eta: 0:49:25 lr: 3.9308604576198205e-06 loss: 0.0247 (0.0299) time: 3.0153 data: 0.0080 max mem: 33408 +Epoch: [37] [1670/2639] eta: 0:48:54 lr: 3.925204995138637e-06 loss: 0.0251 (0.0299) time: 3.0378 data: 0.0077 max mem: 33408 +Epoch: [37] [1680/2639] eta: 0:48:24 lr: 3.919548627131066e-06 loss: 0.0272 (0.0299) time: 3.0563 data: 0.0076 max mem: 33408 +Epoch: [37] [1690/2639] eta: 0:47:54 lr: 3.913891351999689e-06 loss: 0.0308 (0.0299) time: 3.0574 data: 0.0080 max mem: 33408 +Epoch: [37] [1700/2639] eta: 0:47:24 lr: 3.908233168141669e-06 loss: 0.0308 (0.0299) time: 3.0253 data: 0.0083 max mem: 33408 +Epoch: [37] [1710/2639] eta: 0:46:53 lr: 3.902574073948781e-06 loss: 0.0329 (0.0300) time: 3.0006 data: 0.0079 max mem: 33408 +Epoch: [37] [1720/2639] eta: 0:46:23 lr: 3.896914067807333e-06 loss: 0.0285 (0.0300) time: 2.9971 data: 0.0079 max mem: 33408 +Epoch: [37] [1730/2639] eta: 0:45:52 lr: 3.8912531480981866e-06 loss: 0.0273 (0.0300) time: 3.0070 data: 0.0084 max mem: 33408 +Epoch: [37] [1740/2639] eta: 0:45:22 lr: 3.885591313196684e-06 loss: 0.0263 (0.0299) time: 3.0299 data: 0.0080 max mem: 33408 +Epoch: [37] [1750/2639] eta: 0:44:52 lr: 3.879928561472665e-06 loss: 0.0262 (0.0299) time: 3.0009 data: 0.0076 max mem: 33408 +Epoch: [37] [1760/2639] eta: 0:44:21 lr: 3.8742648912903935e-06 loss: 0.0266 (0.0300) time: 2.9837 data: 0.0080 max mem: 33408 +Epoch: [37] [1770/2639] eta: 0:43:50 lr: 3.868600301008577e-06 loss: 0.0277 (0.0300) time: 2.9668 data: 0.0080 max mem: 33408 +Epoch: [37] [1780/2639] eta: 0:43:20 lr: 3.862934788980291e-06 loss: 0.0284 (0.0300) time: 2.9852 data: 0.0080 max mem: 33408 +Epoch: [37] [1790/2639] eta: 0:42:50 lr: 3.8572683535529975e-06 loss: 0.0261 (0.0300) time: 3.0005 data: 0.0080 max mem: 33408 +Epoch: [37] [1800/2639] eta: 0:42:19 lr: 3.851600993068468e-06 loss: 0.0253 (0.0299) time: 2.9754 data: 0.0081 max mem: 33408 +Epoch: [37] [1810/2639] eta: 0:41:49 lr: 3.845932705862806e-06 loss: 0.0283 (0.0299) time: 3.0303 data: 0.0084 max mem: 33408 +Epoch: [37] [1820/2639] eta: 0:41:19 lr: 3.840263490266366e-06 loss: 0.0267 (0.0299) time: 3.0291 data: 0.0082 max mem: 33408 +Epoch: [37] [1830/2639] eta: 0:40:49 lr: 3.834593344603778e-06 loss: 0.0259 (0.0299) time: 3.0287 data: 0.0081 max mem: 33408 +Epoch: [37] [1840/2639] eta: 0:40:18 lr: 3.82892226719386e-06 loss: 0.0312 (0.0299) time: 3.0505 data: 0.0079 max mem: 33408 +Epoch: [37] [1850/2639] eta: 0:39:48 lr: 3.8232502563496496e-06 loss: 0.0296 (0.0299) time: 3.0111 data: 0.0079 max mem: 33408 +Epoch: [37] [1860/2639] eta: 0:39:18 lr: 3.817577310378315e-06 loss: 0.0247 (0.0299) time: 3.0407 data: 0.0083 max mem: 33408 +Epoch: [37] [1870/2639] eta: 0:38:48 lr: 3.8119034275811825e-06 loss: 0.0256 (0.0299) time: 3.0623 data: 0.0082 max mem: 33408 +Epoch: [37] [1880/2639] eta: 0:38:18 lr: 3.8062286062536477e-06 loss: 0.0275 (0.0299) time: 3.0561 data: 0.0080 max mem: 33408 +Epoch: [37] [1890/2639] eta: 0:37:47 lr: 3.8005528446852053e-06 loss: 0.0286 (0.0299) time: 3.0385 data: 0.0081 max mem: 33408 +Epoch: [37] [1900/2639] eta: 0:37:17 lr: 3.7948761411593604e-06 loss: 0.0293 (0.0299) time: 2.9908 data: 0.0081 max mem: 33408 +Epoch: [37] [1910/2639] eta: 0:36:47 lr: 3.7891984939536456e-06 loss: 0.0279 (0.0299) time: 3.0229 data: 0.0082 max mem: 33408 +Epoch: [37] [1920/2639] eta: 0:36:16 lr: 3.7835199013395695e-06 loss: 0.0246 (0.0299) time: 3.0661 data: 0.0087 max mem: 33408 +Epoch: [37] [1930/2639] eta: 0:35:46 lr: 3.777840361582569e-06 loss: 0.0236 (0.0299) time: 3.0761 data: 0.0083 max mem: 33408 +Epoch: [37] [1940/2639] eta: 0:35:16 lr: 3.7721598729420207e-06 loss: 0.0284 (0.0299) time: 3.0759 data: 0.0080 max mem: 33408 +Epoch: [37] [1950/2639] eta: 0:34:46 lr: 3.766478433671157e-06 loss: 0.0267 (0.0299) time: 3.0837 data: 0.0081 max mem: 33408 +Epoch: [37] [1960/2639] eta: 0:34:16 lr: 3.7607960420170875e-06 loss: 0.0261 (0.0298) time: 3.0619 data: 0.0079 max mem: 33408 +Epoch: [37] [1970/2639] eta: 0:33:46 lr: 3.755112696220716e-06 loss: 0.0287 (0.0298) time: 3.0300 data: 0.0080 max mem: 33408 +Epoch: [37] [1980/2639] eta: 0:33:15 lr: 3.749428394516757e-06 loss: 0.0275 (0.0298) time: 3.0295 data: 0.0078 max mem: 33408 +Epoch: [37] [1990/2639] eta: 0:32:45 lr: 3.743743135133655e-06 loss: 0.0264 (0.0298) time: 3.0028 data: 0.0079 max mem: 33408 +Epoch: [37] [2000/2639] eta: 0:32:15 lr: 3.738056916293602e-06 loss: 0.0274 (0.0298) time: 3.0018 data: 0.0079 max mem: 33408 +Epoch: [37] [2010/2639] eta: 0:31:44 lr: 3.7323697362124523e-06 loss: 0.0288 (0.0298) time: 3.0500 data: 0.0077 max mem: 33408 +Epoch: [37] [2020/2639] eta: 0:31:14 lr: 3.7266815930997422e-06 loss: 0.0302 (0.0298) time: 3.0190 data: 0.0076 max mem: 33408 +Epoch: [37] [2030/2639] eta: 0:30:44 lr: 3.7209924851586025e-06 loss: 0.0280 (0.0298) time: 2.9848 data: 0.0078 max mem: 33408 +Epoch: [37] [2040/2639] eta: 0:30:13 lr: 3.7153024105857816e-06 loss: 0.0263 (0.0298) time: 3.0141 data: 0.0082 max mem: 33408 +Epoch: [37] [2050/2639] eta: 0:29:43 lr: 3.709611367571554e-06 loss: 0.0295 (0.0298) time: 3.0478 data: 0.0082 max mem: 33408 +Epoch: [37] [2060/2639] eta: 0:29:13 lr: 3.7039193542997433e-06 loss: 0.0302 (0.0298) time: 3.0634 data: 0.0083 max mem: 33408 +Epoch: [37] [2070/2639] eta: 0:28:43 lr: 3.698226368947632e-06 loss: 0.0277 (0.0298) time: 3.0667 data: 0.0084 max mem: 33408 +Epoch: [37] [2080/2639] eta: 0:28:13 lr: 3.69253240968598e-06 loss: 0.0259 (0.0298) time: 3.0968 data: 0.0083 max mem: 33408 +Epoch: [37] [2090/2639] eta: 0:27:43 lr: 3.6868374746789407e-06 loss: 0.0292 (0.0298) time: 3.1085 data: 0.0081 max mem: 33408 +Epoch: [37] [2100/2639] eta: 0:27:13 lr: 3.6811415620840735e-06 loss: 0.0292 (0.0298) time: 3.0912 data: 0.0081 max mem: 33408 +Epoch: [37] [2110/2639] eta: 0:26:42 lr: 3.675444670052259e-06 loss: 0.0269 (0.0298) time: 3.0821 data: 0.0085 max mem: 33408 +Epoch: [37] [2120/2639] eta: 0:26:12 lr: 3.6697467967277154e-06 loss: 0.0272 (0.0298) time: 3.0581 data: 0.0086 max mem: 33408 +Epoch: [37] [2130/2639] eta: 0:25:42 lr: 3.664047940247911e-06 loss: 0.0273 (0.0298) time: 3.0421 data: 0.0082 max mem: 33408 +Epoch: [37] [2140/2639] eta: 0:25:12 lr: 3.6583480987435784e-06 loss: 0.0282 (0.0298) time: 3.0441 data: 0.0082 max mem: 33408 +Epoch: [37] [2150/2639] eta: 0:24:41 lr: 3.652647270338628e-06 loss: 0.0264 (0.0298) time: 3.0092 data: 0.0086 max mem: 33408 +Epoch: [37] [2160/2639] eta: 0:24:11 lr: 3.646945453150156e-06 loss: 0.0268 (0.0298) time: 3.0058 data: 0.0085 max mem: 33408 +Epoch: [37] [2170/2639] eta: 0:23:41 lr: 3.6412426452883897e-06 loss: 0.0286 (0.0298) time: 3.0657 data: 0.0084 max mem: 33408 +Epoch: [37] [2180/2639] eta: 0:23:10 lr: 3.6355388448566278e-06 loss: 0.0286 (0.0298) time: 3.0805 data: 0.0087 max mem: 33408 +Epoch: [37] [2190/2639] eta: 0:22:40 lr: 3.6298340499512516e-06 loss: 0.0260 (0.0298) time: 3.0385 data: 0.0083 max mem: 33408 +Epoch: [37] [2200/2639] eta: 0:22:10 lr: 3.624128258661634e-06 loss: 0.0308 (0.0298) time: 3.0419 data: 0.0076 max mem: 33408 +Epoch: [37] [2210/2639] eta: 0:21:40 lr: 3.6184214690701545e-06 loss: 0.0356 (0.0298) time: 3.0451 data: 0.0077 max mem: 33408 +Epoch: [37] [2220/2639] eta: 0:21:09 lr: 3.6127136792521074e-06 loss: 0.0260 (0.0298) time: 3.0502 data: 0.0075 max mem: 33408 +Epoch: [37] [2230/2639] eta: 0:20:39 lr: 3.607004887275717e-06 loss: 0.0263 (0.0298) time: 3.0640 data: 0.0075 max mem: 33408 +Epoch: [37] [2240/2639] eta: 0:20:09 lr: 3.6012950912020455e-06 loss: 0.0263 (0.0298) time: 3.0455 data: 0.0076 max mem: 33408 +Epoch: [37] [2250/2639] eta: 0:19:38 lr: 3.5955842890850087e-06 loss: 0.0244 (0.0298) time: 3.0055 data: 0.0076 max mem: 33408 +Epoch: [37] [2260/2639] eta: 0:19:08 lr: 3.5898724789712796e-06 loss: 0.0297 (0.0298) time: 3.0224 data: 0.0079 max mem: 33408 +Epoch: [37] [2270/2639] eta: 0:18:38 lr: 3.5841596589003087e-06 loss: 0.0287 (0.0298) time: 3.0369 data: 0.0081 max mem: 33408 +Epoch: [37] [2280/2639] eta: 0:18:08 lr: 3.578445826904224e-06 loss: 0.0268 (0.0298) time: 3.0503 data: 0.0084 max mem: 33408 +Epoch: [37] [2290/2639] eta: 0:17:37 lr: 3.5727309810078475e-06 loss: 0.0271 (0.0298) time: 3.0648 data: 0.0083 max mem: 33408 +Epoch: [37] [2300/2639] eta: 0:17:07 lr: 3.5670151192286025e-06 loss: 0.0262 (0.0298) time: 3.0290 data: 0.0079 max mem: 33408 +Epoch: [37] [2310/2639] eta: 0:16:37 lr: 3.5612982395765234e-06 loss: 0.0306 (0.0298) time: 3.0570 data: 0.0077 max mem: 33408 +Epoch: [37] [2320/2639] eta: 0:16:06 lr: 3.555580340054164e-06 loss: 0.0327 (0.0298) time: 3.0493 data: 0.0076 max mem: 33408 +Epoch: [37] [2330/2639] eta: 0:15:36 lr: 3.5498614186566073e-06 loss: 0.0305 (0.0298) time: 3.0227 data: 0.0076 max mem: 33408 +Epoch: [37] [2340/2639] eta: 0:15:06 lr: 3.5441414733713728e-06 loss: 0.0296 (0.0299) time: 3.0192 data: 0.0076 max mem: 33408 +Epoch: [37] [2350/2639] eta: 0:14:35 lr: 3.5384205021784253e-06 loss: 0.0284 (0.0299) time: 2.9899 data: 0.0075 max mem: 33408 +Epoch: [37] [2360/2639] eta: 0:14:05 lr: 3.532698503050081e-06 loss: 0.0252 (0.0298) time: 3.0522 data: 0.0076 max mem: 33408 +Epoch: [37] [2370/2639] eta: 0:13:35 lr: 3.5269754739510204e-06 loss: 0.0259 (0.0298) time: 3.0933 data: 0.0077 max mem: 33408 +Epoch: [37] [2380/2639] eta: 0:13:04 lr: 3.521251412838186e-06 loss: 0.0265 (0.0298) time: 3.0027 data: 0.0079 max mem: 33408 +Epoch: [37] [2390/2639] eta: 0:12:34 lr: 3.5155263176608e-06 loss: 0.0257 (0.0298) time: 2.9762 data: 0.0079 max mem: 33408 +Epoch: [37] [2400/2639] eta: 0:12:04 lr: 3.509800186360261e-06 loss: 0.0258 (0.0298) time: 3.0544 data: 0.0082 max mem: 33408 +Epoch: [37] [2410/2639] eta: 0:11:34 lr: 3.504073016870152e-06 loss: 0.0304 (0.0298) time: 3.0804 data: 0.0079 max mem: 33408 +Epoch: [37] [2420/2639] eta: 0:11:03 lr: 3.498344807116171e-06 loss: 0.0238 (0.0298) time: 3.0789 data: 0.0074 max mem: 33408 +Epoch: [37] [2430/2639] eta: 0:10:33 lr: 3.492615555016071e-06 loss: 0.0245 (0.0298) time: 3.0400 data: 0.0080 max mem: 33408 +Epoch: [37] [2440/2639] eta: 0:10:03 lr: 3.4868852584796613e-06 loss: 0.0250 (0.0298) time: 3.0100 data: 0.0083 max mem: 33408 +Epoch: [37] [2450/2639] eta: 0:09:32 lr: 3.4811539154087066e-06 loss: 0.0270 (0.0298) time: 3.0679 data: 0.0079 max mem: 33408 +Epoch: [37] [2460/2639] eta: 0:09:02 lr: 3.4754215236969366e-06 loss: 0.0290 (0.0298) time: 3.0589 data: 0.0080 max mem: 33408 +Epoch: [37] [2470/2639] eta: 0:08:32 lr: 3.4696880812299473e-06 loss: 0.0317 (0.0299) time: 3.0191 data: 0.0081 max mem: 33408 +Epoch: [37] [2480/2639] eta: 0:08:02 lr: 3.463953585885205e-06 loss: 0.0293 (0.0299) time: 3.0498 data: 0.0077 max mem: 33408 +Epoch: [37] [2490/2639] eta: 0:07:31 lr: 3.4582180355319524e-06 loss: 0.0247 (0.0298) time: 3.0571 data: 0.0076 max mem: 33408 +Epoch: [37] [2500/2639] eta: 0:07:01 lr: 3.452481428031209e-06 loss: 0.0272 (0.0298) time: 3.0539 data: 0.0082 max mem: 33408 +Epoch: [37] [2510/2639] eta: 0:06:31 lr: 3.446743761235674e-06 loss: 0.0264 (0.0298) time: 3.0948 data: 0.0083 max mem: 33408 +Epoch: [37] [2520/2639] eta: 0:06:00 lr: 3.4410050329897315e-06 loss: 0.0248 (0.0298) time: 3.0897 data: 0.0080 max mem: 33408 +Epoch: [37] [2530/2639] eta: 0:05:30 lr: 3.435265241129348e-06 loss: 0.0251 (0.0298) time: 3.0617 data: 0.0082 max mem: 33408 +Epoch: [37] [2540/2639] eta: 0:05:00 lr: 3.4295243834820795e-06 loss: 0.0289 (0.0298) time: 3.0504 data: 0.0084 max mem: 33408 +Epoch: [37] [2550/2639] eta: 0:04:29 lr: 3.423782457866967e-06 loss: 0.0285 (0.0298) time: 3.0407 data: 0.0085 max mem: 33408 +Epoch: [37] [2560/2639] eta: 0:03:59 lr: 3.418039462094544e-06 loss: 0.0280 (0.0298) time: 3.0620 data: 0.0078 max mem: 33408 +Epoch: [37] [2570/2639] eta: 0:03:29 lr: 3.4122953939667293e-06 loss: 0.0285 (0.0298) time: 3.0073 data: 0.0072 max mem: 33408 +Epoch: [37] [2580/2639] eta: 0:02:58 lr: 3.406550251276837e-06 loss: 0.0267 (0.0298) time: 2.9837 data: 0.0076 max mem: 33408 +Epoch: [37] [2590/2639] eta: 0:02:28 lr: 3.4008040318094645e-06 loss: 0.0267 (0.0298) time: 3.0403 data: 0.0079 max mem: 33408 +Epoch: [37] [2600/2639] eta: 0:01:58 lr: 3.3950567333405034e-06 loss: 0.0280 (0.0298) time: 3.0594 data: 0.0077 max mem: 33408 +Epoch: [37] [2610/2639] eta: 0:01:27 lr: 3.389308353637031e-06 loss: 0.0314 (0.0298) time: 3.0404 data: 0.0075 max mem: 33408 +Epoch: [37] [2620/2639] eta: 0:00:57 lr: 3.383558890457312e-06 loss: 0.0304 (0.0298) time: 2.9579 data: 0.0079 max mem: 33408 +Epoch: [37] [2630/2639] eta: 0:00:27 lr: 3.3778083415506957e-06 loss: 0.0282 (0.0298) time: 2.9704 data: 0.0078 max mem: 33408 +Epoch: [37] Total time: 2:13:22 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 2:14:17 time: 3.1316 data: 3.0205 max mem: 33408 +Test: [ 100/2573] eta: 0:04:29 time: 0.0788 data: 0.0014 max mem: 33408 +Test: [ 200/2573] eta: 0:03:45 time: 0.0810 data: 0.0014 max mem: 33408 +Test: [ 300/2573] eta: 0:03:23 time: 0.0812 data: 0.0014 max mem: 33408 +Test: [ 400/2573] eta: 0:03:09 time: 0.0819 data: 0.0014 max mem: 33408 +Test: [ 500/2573] eta: 0:02:58 time: 0.0811 data: 0.0016 max mem: 33408 +Test: [ 600/2573] eta: 0:02:48 time: 0.0813 data: 0.0014 max mem: 33408 +Test: [ 700/2573] eta: 0:02:39 time: 0.0811 data: 0.0014 max mem: 33408 +Test: [ 800/2573] eta: 0:02:30 time: 0.0835 data: 0.0013 max mem: 33408 +Test: [ 900/2573] eta: 0:02:21 time: 0.0811 data: 0.0014 max mem: 33408 +Test: [1000/2573] eta: 0:02:12 time: 0.0814 data: 0.0015 max mem: 33408 +Test: [1100/2573] eta: 0:02:03 time: 0.0817 data: 0.0014 max mem: 33408 +Test: [1200/2573] eta: 0:01:54 time: 0.0813 data: 0.0014 max mem: 33408 +Test: [1300/2573] eta: 0:01:46 time: 0.0804 data: 0.0013 max mem: 33408 +Test: [1400/2573] eta: 0:01:37 time: 0.0797 data: 0.0015 max mem: 33408 +Test: [1500/2573] eta: 0:01:29 time: 0.0810 data: 0.0015 max mem: 33408 +Test: [1600/2573] eta: 0:01:20 time: 0.0853 data: 0.0014 max mem: 33408 +Test: [1700/2573] eta: 0:01:12 time: 0.0803 data: 0.0014 max mem: 33408 +Test: [1800/2573] eta: 0:01:04 time: 0.0823 data: 0.0014 max mem: 33408 +Test: [1900/2573] eta: 0:00:55 time: 0.0795 data: 0.0014 max mem: 33408 +Test: [2000/2573] eta: 0:00:47 time: 0.0803 data: 0.0014 max mem: 33408 +Test: [2100/2573] eta: 0:00:39 time: 0.0831 data: 0.0014 max mem: 33408 +Test: [2200/2573] eta: 0:00:30 time: 0.0836 data: 0.0014 max mem: 33408 +Test: [2300/2573] eta: 0:00:22 time: 0.0841 data: 0.0015 max mem: 33408 +Test: [2400/2573] eta: 0:00:14 time: 0.0793 data: 0.0014 max mem: 33408 +Test: [2500/2573] eta: 0:00:06 time: 0.0813 data: 0.0015 max mem: 33408 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: Total time: 0:03:33 +Final results: +Mean IoU is 65.18 + + precision@0.5 = 73.55 + precision@0.6 = 68.34 + precision@0.7 = 61.70 + precision@0.8 = 51.27 + precision@0.9 = 25.90 + overall IoU = 62.53 + +Average object IoU 65.17910884318589 +Overall IoU 62.530513763427734 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [38] [ 0/2639] eta: 3:55:17 lr: 3.3726319173708947e-06 loss: 0.0196 (0.0196) time: 5.3496 data: 2.1929 max mem: 33408 +Epoch: [38] [ 10/2639] eta: 2:25:25 lr: 3.366879299350617e-06 loss: 0.0270 (0.0282) time: 3.3190 data: 0.2060 max mem: 33408 +Epoch: [38] [ 20/2639] eta: 2:17:54 lr: 3.3611255890258356e-06 loss: 0.0277 (0.0312) time: 3.0498 data: 0.0070 max mem: 33408 +Epoch: [38] [ 30/2639] eta: 2:14:49 lr: 3.3553707841107466e-06 loss: 0.0308 (0.0322) time: 2.9807 data: 0.0074 max mem: 33408 +Epoch: [38] [ 40/2639] eta: 2:13:41 lr: 3.349614882310397e-06 loss: 0.0287 (0.0319) time: 3.0099 data: 0.0081 max mem: 33408 +Epoch: [38] [ 50/2639] eta: 2:13:07 lr: 3.343857881320609e-06 loss: 0.0325 (0.0330) time: 3.0607 data: 0.0083 max mem: 33408 +Epoch: [38] [ 60/2639] eta: 2:12:15 lr: 3.3380997788279757e-06 loss: 0.0298 (0.0320) time: 3.0578 data: 0.0080 max mem: 33408 +Epoch: [38] [ 70/2639] eta: 2:11:07 lr: 3.332340572509748e-06 loss: 0.0279 (0.0315) time: 3.0054 data: 0.0080 max mem: 33408 +Epoch: [38] [ 80/2639] eta: 2:10:48 lr: 3.3265802600338356e-06 loss: 0.0279 (0.0320) time: 3.0362 data: 0.0085 max mem: 33408 +Epoch: [38] [ 90/2639] eta: 2:10:08 lr: 3.320818839058698e-06 loss: 0.0331 (0.0325) time: 3.0657 data: 0.0085 max mem: 33408 +Epoch: [38] [ 100/2639] eta: 2:09:18 lr: 3.315056307233339e-06 loss: 0.0333 (0.0323) time: 3.0095 data: 0.0082 max mem: 33408 +Epoch: [38] [ 110/2639] eta: 2:08:55 lr: 3.3092926621972004e-06 loss: 0.0283 (0.0316) time: 3.0383 data: 0.0084 max mem: 33408 +Epoch: [38] [ 120/2639] eta: 2:08:18 lr: 3.303527901580153e-06 loss: 0.0283 (0.0315) time: 3.0586 data: 0.0080 max mem: 33408 +Epoch: [38] [ 130/2639] eta: 2:07:48 lr: 3.2977620230023903e-06 loss: 0.0294 (0.0318) time: 3.0428 data: 0.0079 max mem: 33408 +Epoch: [38] [ 140/2639] eta: 2:07:17 lr: 3.291995024074423e-06 loss: 0.0285 (0.0317) time: 3.0572 data: 0.0081 max mem: 33408 +Epoch: [38] [ 150/2639] eta: 2:06:50 lr: 3.286226902396962e-06 loss: 0.0249 (0.0312) time: 3.0651 data: 0.0079 max mem: 33408 +Epoch: [38] [ 160/2639] eta: 2:06:18 lr: 3.28045765556092e-06 loss: 0.0283 (0.0312) time: 3.0628 data: 0.0083 max mem: 33408 +Epoch: [38] [ 170/2639] eta: 2:05:49 lr: 3.274687281147294e-06 loss: 0.0260 (0.0312) time: 3.0597 data: 0.0089 max mem: 33408 +Epoch: [38] [ 180/2639] eta: 2:05:09 lr: 3.2689157767271606e-06 loss: 0.0258 (0.0309) time: 3.0265 data: 0.0089 max mem: 33408 +Epoch: [38] [ 190/2639] eta: 2:04:37 lr: 3.2631431398615596e-06 loss: 0.0281 (0.0308) time: 3.0142 data: 0.0087 max mem: 33408 +Epoch: [38] [ 200/2639] eta: 2:04:02 lr: 3.257369368101489e-06 loss: 0.0295 (0.0308) time: 3.0309 data: 0.0085 max mem: 33408 +Epoch: [38] [ 210/2639] eta: 2:03:27 lr: 3.251594458987791e-06 loss: 0.0326 (0.0310) time: 3.0152 data: 0.0081 max mem: 33408 +Epoch: [38] [ 220/2639] eta: 2:02:47 lr: 3.245818410051138e-06 loss: 0.0315 (0.0311) time: 2.9893 data: 0.0078 max mem: 33408 +Epoch: [38] [ 230/2639] eta: 2:02:16 lr: 3.2400412188119227e-06 loss: 0.0259 (0.0309) time: 3.0001 data: 0.0080 max mem: 33408 +Epoch: [38] [ 240/2639] eta: 2:01:45 lr: 3.2342628827802464e-06 loss: 0.0249 (0.0308) time: 3.0396 data: 0.0080 max mem: 33408 +Epoch: [38] [ 250/2639] eta: 2:01:13 lr: 3.2284833994558013e-06 loss: 0.0252 (0.0307) time: 3.0380 data: 0.0077 max mem: 33408 +Epoch: [38] [ 260/2639] eta: 2:00:48 lr: 3.222702766327859e-06 loss: 0.0280 (0.0307) time: 3.0662 data: 0.0082 max mem: 33408 +Epoch: [38] [ 270/2639] eta: 2:00:15 lr: 3.2169209808751565e-06 loss: 0.0277 (0.0305) time: 3.0582 data: 0.0085 max mem: 33408 +Epoch: [38] [ 280/2639] eta: 1:59:42 lr: 3.211138040565874e-06 loss: 0.0277 (0.0307) time: 3.0151 data: 0.0081 max mem: 33408 +Epoch: [38] [ 290/2639] eta: 1:59:09 lr: 3.2053539428575495e-06 loss: 0.0265 (0.0306) time: 3.0178 data: 0.0078 max mem: 33408 +Epoch: [38] [ 300/2639] eta: 1:58:34 lr: 3.1995686851969958e-06 loss: 0.0265 (0.0306) time: 2.9986 data: 0.0081 max mem: 33408 +Epoch: [38] [ 310/2639] eta: 1:58:01 lr: 3.1937822650202764e-06 loss: 0.0261 (0.0304) time: 2.9913 data: 0.0080 max mem: 33408 +Epoch: [38] [ 320/2639] eta: 1:57:31 lr: 3.1879946797525893e-06 loss: 0.0255 (0.0304) time: 3.0263 data: 0.0077 max mem: 33408 +Epoch: [38] [ 330/2639] eta: 1:56:56 lr: 3.182205926808247e-06 loss: 0.0296 (0.0304) time: 3.0152 data: 0.0082 max mem: 33408 +Epoch: [38] [ 340/2639] eta: 1:56:26 lr: 3.1764160035905614e-06 loss: 0.0273 (0.0302) time: 3.0151 data: 0.0084 max mem: 33408 +Epoch: [38] [ 350/2639] eta: 1:55:58 lr: 3.1706249074918216e-06 loss: 0.0245 (0.0302) time: 3.0602 data: 0.0081 max mem: 33408 +Epoch: [38] [ 360/2639] eta: 1:55:27 lr: 3.164832635893176e-06 loss: 0.0305 (0.0302) time: 3.0461 data: 0.0081 max mem: 33408 +Epoch: [38] [ 370/2639] eta: 1:54:53 lr: 3.1590391861646126e-06 loss: 0.0323 (0.0302) time: 3.0052 data: 0.0081 max mem: 33408 +Epoch: [38] [ 380/2639] eta: 1:54:23 lr: 3.1532445556648367e-06 loss: 0.0263 (0.0301) time: 3.0154 data: 0.0078 max mem: 33408 +Epoch: [38] [ 390/2639] eta: 1:53:51 lr: 3.147448741741253e-06 loss: 0.0254 (0.0301) time: 3.0279 data: 0.0073 max mem: 33408 +Epoch: [38] [ 400/2639] eta: 1:53:19 lr: 3.1416517417298397e-06 loss: 0.0273 (0.0300) time: 3.0133 data: 0.0077 max mem: 33408 +Epoch: [38] [ 410/2639] eta: 1:52:52 lr: 3.135853552955127e-06 loss: 0.0273 (0.0300) time: 3.0466 data: 0.0082 max mem: 33408 +Epoch: [38] [ 420/2639] eta: 1:52:23 lr: 3.1300541727300773e-06 loss: 0.0323 (0.0301) time: 3.0751 data: 0.0079 max mem: 33408 +Epoch: [38] [ 430/2639] eta: 1:51:53 lr: 3.124253598356056e-06 loss: 0.0323 (0.0301) time: 3.0609 data: 0.0077 max mem: 33408 +Epoch: [38] [ 440/2639] eta: 1:51:21 lr: 3.1184518271227128e-06 loss: 0.0286 (0.0301) time: 3.0308 data: 0.0077 max mem: 33408 +Epoch: [38] [ 450/2639] eta: 1:50:50 lr: 3.112648856307953e-06 loss: 0.0261 (0.0300) time: 3.0119 data: 0.0076 max mem: 33408 +Epoch: [38] [ 460/2639] eta: 1:50:15 lr: 3.106844683177812e-06 loss: 0.0255 (0.0299) time: 2.9803 data: 0.0080 max mem: 33408 +Epoch: [38] [ 470/2639] eta: 1:49:43 lr: 3.1010393049864333e-06 loss: 0.0274 (0.0300) time: 2.9707 data: 0.0081 max mem: 33408 +Epoch: [38] [ 480/2639] eta: 1:49:12 lr: 3.0952327189759343e-06 loss: 0.0276 (0.0299) time: 3.0163 data: 0.0077 max mem: 33408 +Epoch: [38] [ 490/2639] eta: 1:48:43 lr: 3.0894249223763867e-06 loss: 0.0253 (0.0298) time: 3.0455 data: 0.0078 max mem: 33408 +Epoch: [38] [ 500/2639] eta: 1:48:14 lr: 3.083615912405681e-06 loss: 0.0239 (0.0298) time: 3.0636 data: 0.0080 max mem: 33408 +Epoch: [38] [ 510/2639] eta: 1:47:44 lr: 3.0778056862695044e-06 loss: 0.0276 (0.0299) time: 3.0556 data: 0.0081 max mem: 33408 +Epoch: [38] [ 520/2639] eta: 1:47:11 lr: 3.0719942411612054e-06 loss: 0.0295 (0.0299) time: 3.0079 data: 0.0081 max mem: 33408 +Epoch: [38] [ 530/2639] eta: 1:46:38 lr: 3.0661815742617605e-06 loss: 0.0295 (0.0299) time: 2.9686 data: 0.0080 max mem: 33408 +Epoch: [38] [ 540/2639] eta: 1:46:08 lr: 3.0603676827396764e-06 loss: 0.0283 (0.0299) time: 3.0077 data: 0.0078 max mem: 33408 +Epoch: [38] [ 550/2639] eta: 1:45:37 lr: 3.054552563750883e-06 loss: 0.0289 (0.0299) time: 3.0268 data: 0.0082 max mem: 33408 +Epoch: [38] [ 560/2639] eta: 1:45:04 lr: 3.0487362144387025e-06 loss: 0.0300 (0.0300) time: 2.9918 data: 0.0083 max mem: 33408 +Epoch: [38] [ 570/2639] eta: 1:44:33 lr: 3.04291863193371e-06 loss: 0.0293 (0.0300) time: 3.0005 data: 0.0080 max mem: 33408 +Epoch: [38] [ 580/2639] eta: 1:44:04 lr: 3.037099813353705e-06 loss: 0.0290 (0.0300) time: 3.0307 data: 0.0077 max mem: 33408 +Epoch: [38] [ 590/2639] eta: 1:43:32 lr: 3.031279755803572e-06 loss: 0.0278 (0.0301) time: 3.0238 data: 0.0074 max mem: 33408 +Epoch: [38] [ 600/2639] eta: 1:43:01 lr: 3.0254584563752497e-06 loss: 0.0270 (0.0300) time: 3.0019 data: 0.0076 max mem: 33408 +Epoch: [38] [ 610/2639] eta: 1:42:31 lr: 3.0196359121475918e-06 loss: 0.0294 (0.0300) time: 3.0233 data: 0.0078 max mem: 33408 +Epoch: [38] [ 620/2639] eta: 1:42:00 lr: 3.0138121201863318e-06 loss: 0.0271 (0.0300) time: 3.0307 data: 0.0077 max mem: 33408 +Epoch: [38] [ 630/2639] eta: 1:41:30 lr: 3.007987077543944e-06 loss: 0.0271 (0.0300) time: 3.0242 data: 0.0079 max mem: 33408 +Epoch: [38] [ 640/2639] eta: 1:41:02 lr: 3.002160781259609e-06 loss: 0.0294 (0.0300) time: 3.0636 data: 0.0084 max mem: 33408 +Epoch: [38] [ 650/2639] eta: 1:40:29 lr: 2.996333228359069e-06 loss: 0.0310 (0.0300) time: 3.0204 data: 0.0086 max mem: 33408 +Epoch: [38] [ 660/2639] eta: 1:39:57 lr: 2.9905044158545923e-06 loss: 0.0277 (0.0300) time: 2.9694 data: 0.0079 max mem: 33408 +Epoch: [38] [ 670/2639] eta: 1:39:27 lr: 2.984674340744831e-06 loss: 0.0243 (0.0300) time: 3.0188 data: 0.0076 max mem: 33408 +Epoch: [38] [ 680/2639] eta: 1:38:57 lr: 2.9788430000147798e-06 loss: 0.0258 (0.0300) time: 3.0425 data: 0.0078 max mem: 33408 +Epoch: [38] [ 690/2639] eta: 1:38:27 lr: 2.9730103906356334e-06 loss: 0.0266 (0.0299) time: 3.0396 data: 0.0081 max mem: 33408 +Epoch: [38] [ 700/2639] eta: 1:37:56 lr: 2.9671765095647444e-06 loss: 0.0266 (0.0299) time: 3.0250 data: 0.0080 max mem: 33408 +Epoch: [38] [ 710/2639] eta: 1:37:26 lr: 2.961341353745477e-06 loss: 0.0284 (0.0300) time: 3.0225 data: 0.0077 max mem: 33408 +Epoch: [38] [ 720/2639] eta: 1:36:56 lr: 2.9555049201071666e-06 loss: 0.0280 (0.0299) time: 3.0371 data: 0.0075 max mem: 33408 +Epoch: [38] [ 730/2639] eta: 1:36:24 lr: 2.9496672055649687e-06 loss: 0.0271 (0.0299) time: 3.0065 data: 0.0077 max mem: 33408 +Epoch: [38] [ 740/2639] eta: 1:35:52 lr: 2.9438282070198164e-06 loss: 0.0251 (0.0299) time: 2.9717 data: 0.0081 max mem: 33408 +Epoch: [38] [ 750/2639] eta: 1:35:21 lr: 2.9379879213582714e-06 loss: 0.0276 (0.0299) time: 2.9748 data: 0.0084 max mem: 33408 +Epoch: [38] [ 760/2639] eta: 1:34:51 lr: 2.932146345452477e-06 loss: 0.0273 (0.0298) time: 3.0081 data: 0.0084 max mem: 33408 +Epoch: [38] [ 770/2639] eta: 1:34:21 lr: 2.926303476160006e-06 loss: 0.0273 (0.0299) time: 3.0414 data: 0.0082 max mem: 33408 +Epoch: [38] [ 780/2639] eta: 1:33:50 lr: 2.920459310323809e-06 loss: 0.0291 (0.0299) time: 3.0310 data: 0.0082 max mem: 33408 +Epoch: [38] [ 790/2639] eta: 1:33:20 lr: 2.9146138447720907e-06 loss: 0.0261 (0.0299) time: 3.0298 data: 0.0078 max mem: 33408 +Epoch: [38] [ 800/2639] eta: 1:32:49 lr: 2.908767076318191e-06 loss: 0.0251 (0.0299) time: 3.0058 data: 0.0081 max mem: 33408 +Epoch: [38] [ 810/2639] eta: 1:32:17 lr: 2.902919001760526e-06 loss: 0.0259 (0.0299) time: 2.9639 data: 0.0085 max mem: 33408 +Epoch: [38] [ 820/2639] eta: 1:31:45 lr: 2.8970696178824325e-06 loss: 0.0263 (0.0299) time: 2.9673 data: 0.0083 max mem: 33408 +Epoch: [38] [ 830/2639] eta: 1:31:16 lr: 2.8912189214521173e-06 loss: 0.0310 (0.0299) time: 3.0239 data: 0.0080 max mem: 33408 +Epoch: [38] [ 840/2639] eta: 1:30:46 lr: 2.885366909222496e-06 loss: 0.0291 (0.0299) time: 3.0485 data: 0.0080 max mem: 33408 +Epoch: [38] [ 850/2639] eta: 1:30:16 lr: 2.879513577931142e-06 loss: 0.0273 (0.0299) time: 3.0459 data: 0.0077 max mem: 33408 +Epoch: [38] [ 860/2639] eta: 1:29:46 lr: 2.873658924300124e-06 loss: 0.0264 (0.0298) time: 3.0459 data: 0.0074 max mem: 33408 +Epoch: [38] [ 870/2639] eta: 1:29:14 lr: 2.867802945035951e-06 loss: 0.0232 (0.0297) time: 2.9960 data: 0.0078 max mem: 33408 +Epoch: [38] [ 880/2639] eta: 1:28:43 lr: 2.8619456368294096e-06 loss: 0.0238 (0.0297) time: 2.9667 data: 0.0075 max mem: 33408 +Epoch: [38] [ 890/2639] eta: 1:28:12 lr: 2.856086996355507e-06 loss: 0.0246 (0.0297) time: 2.9885 data: 0.0074 max mem: 33408 +Epoch: [38] [ 900/2639] eta: 1:27:41 lr: 2.850227020273305e-06 loss: 0.0246 (0.0297) time: 2.9998 data: 0.0077 max mem: 33408 +Epoch: [38] [ 910/2639] eta: 1:27:12 lr: 2.8443657052258607e-06 loss: 0.0257 (0.0296) time: 3.0370 data: 0.0076 max mem: 33408 +Epoch: [38] [ 920/2639] eta: 1:26:42 lr: 2.8385030478400616e-06 loss: 0.0274 (0.0296) time: 3.0699 data: 0.0077 max mem: 33408 +Epoch: [38] [ 930/2639] eta: 1:26:12 lr: 2.832639044726559e-06 loss: 0.0283 (0.0296) time: 3.0399 data: 0.0080 max mem: 33408 +Epoch: [38] [ 940/2639] eta: 1:25:42 lr: 2.8267736924796054e-06 loss: 0.0274 (0.0296) time: 3.0330 data: 0.0080 max mem: 33408 +Epoch: [38] [ 950/2639] eta: 1:25:13 lr: 2.8209069876769843e-06 loss: 0.0262 (0.0296) time: 3.0730 data: 0.0074 max mem: 33408 +Epoch: [38] [ 960/2639] eta: 1:24:44 lr: 2.8150389268798437e-06 loss: 0.0290 (0.0296) time: 3.0840 data: 0.0079 max mem: 33408 +Epoch: [38] [ 970/2639] eta: 1:24:14 lr: 2.809169506632627e-06 loss: 0.0285 (0.0296) time: 3.0602 data: 0.0082 max mem: 33408 +Epoch: [38] [ 980/2639] eta: 1:23:43 lr: 2.803298723462901e-06 loss: 0.0267 (0.0296) time: 3.0216 data: 0.0082 max mem: 33408 +Epoch: [38] [ 990/2639] eta: 1:23:12 lr: 2.7974265738812864e-06 loss: 0.0274 (0.0296) time: 2.9829 data: 0.0082 max mem: 33408 +Epoch: [38] [1000/2639] eta: 1:22:42 lr: 2.7915530543812824e-06 loss: 0.0263 (0.0295) time: 3.0240 data: 0.0077 max mem: 33408 +Epoch: [38] [1010/2639] eta: 1:22:13 lr: 2.785678161439196e-06 loss: 0.0242 (0.0295) time: 3.0672 data: 0.0076 max mem: 33408 +Epoch: [38] [1020/2639] eta: 1:21:41 lr: 2.779801891513964e-06 loss: 0.0243 (0.0295) time: 2.9979 data: 0.0080 max mem: 33408 +Epoch: [38] [1030/2639] eta: 1:21:11 lr: 2.7739242410470726e-06 loss: 0.0256 (0.0295) time: 2.9844 data: 0.0079 max mem: 33408 +Epoch: [38] [1040/2639] eta: 1:20:40 lr: 2.7680452064624104e-06 loss: 0.0256 (0.0295) time: 3.0091 data: 0.0077 max mem: 33408 +Epoch: [38] [1050/2639] eta: 1:20:09 lr: 2.762164784166119e-06 loss: 0.0250 (0.0295) time: 2.9925 data: 0.0081 max mem: 33408 +Epoch: [38] [1060/2639] eta: 1:19:37 lr: 2.75628297054651e-06 loss: 0.0285 (0.0294) time: 2.9714 data: 0.0082 max mem: 33408 +Epoch: [38] [1070/2639] eta: 1:19:06 lr: 2.750399761973881e-06 loss: 0.0288 (0.0295) time: 2.9519 data: 0.0082 max mem: 33408 +Epoch: [38] [1080/2639] eta: 1:18:36 lr: 2.7445151548004354e-06 loss: 0.0278 (0.0295) time: 3.0051 data: 0.0084 max mem: 33408 +Epoch: [38] [1090/2639] eta: 1:18:05 lr: 2.738629145360096e-06 loss: 0.0249 (0.0294) time: 2.9922 data: 0.0081 max mem: 33408 +Epoch: [38] [1100/2639] eta: 1:17:34 lr: 2.7327417299684223e-06 loss: 0.0249 (0.0294) time: 2.9547 data: 0.0080 max mem: 33408 +Epoch: [38] [1110/2639] eta: 1:17:03 lr: 2.7268529049224214e-06 loss: 0.0258 (0.0294) time: 2.9801 data: 0.0084 max mem: 33408 +Epoch: [38] [1120/2639] eta: 1:16:33 lr: 2.7209626665004632e-06 loss: 0.0294 (0.0294) time: 3.0120 data: 0.0081 max mem: 33408 +Epoch: [38] [1130/2639] eta: 1:16:03 lr: 2.715071010962088e-06 loss: 0.0299 (0.0294) time: 3.0411 data: 0.0077 max mem: 33408 +Epoch: [38] [1140/2639] eta: 1:15:33 lr: 2.7091779345479194e-06 loss: 0.0260 (0.0294) time: 3.0453 data: 0.0079 max mem: 33408 +Epoch: [38] [1150/2639] eta: 1:15:02 lr: 2.703283433479468e-06 loss: 0.0260 (0.0294) time: 3.0091 data: 0.0080 max mem: 33408 +Epoch: [38] [1160/2639] eta: 1:14:32 lr: 2.6973875039590436e-06 loss: 0.0276 (0.0294) time: 3.0154 data: 0.0078 max mem: 33408 +Epoch: [38] [1170/2639] eta: 1:14:02 lr: 2.6914901421695536e-06 loss: 0.0280 (0.0294) time: 3.0389 data: 0.0080 max mem: 33408 +Epoch: [38] [1180/2639] eta: 1:13:32 lr: 2.685591344274414e-06 loss: 0.0301 (0.0294) time: 3.0260 data: 0.0086 max mem: 33408 +Epoch: [38] [1190/2639] eta: 1:13:01 lr: 2.679691106417344e-06 loss: 0.0301 (0.0294) time: 2.9936 data: 0.0088 max mem: 33408 +Epoch: [38] [1200/2639] eta: 1:12:31 lr: 2.6737894247222755e-06 loss: 0.0307 (0.0294) time: 3.0035 data: 0.0084 max mem: 33408 +Epoch: [38] [1210/2639] eta: 1:12:00 lr: 2.667886295293144e-06 loss: 0.0295 (0.0295) time: 3.0221 data: 0.0081 max mem: 33408 +Epoch: [38] [1220/2639] eta: 1:11:30 lr: 2.6619817142137937e-06 loss: 0.0287 (0.0295) time: 3.0024 data: 0.0080 max mem: 33408 +Epoch: [38] [1230/2639] eta: 1:11:00 lr: 2.6560756775477652e-06 loss: 0.0268 (0.0294) time: 3.0442 data: 0.0079 max mem: 33408 +Epoch: [38] [1240/2639] eta: 1:10:30 lr: 2.650168181338201e-06 loss: 0.0273 (0.0297) time: 3.0611 data: 0.0079 max mem: 33408 +Epoch: [38] [1250/2639] eta: 1:09:59 lr: 2.644259221607628e-06 loss: 0.0284 (0.0297) time: 3.0065 data: 0.0084 max mem: 33408 +Epoch: [38] [1260/2639] eta: 1:09:29 lr: 2.6383487943578502e-06 loss: 0.0280 (0.0297) time: 2.9958 data: 0.0091 max mem: 33408 +Epoch: [38] [1270/2639] eta: 1:09:00 lr: 2.6324368955697674e-06 loss: 0.0280 (0.0297) time: 3.0635 data: 0.0097 max mem: 33408 +Epoch: [38] [1280/2639] eta: 1:08:30 lr: 2.6265235212031925e-06 loss: 0.0300 (0.0297) time: 3.0818 data: 0.0093 max mem: 33408 +Epoch: [38] [1290/2639] eta: 1:07:59 lr: 2.6206086671967363e-06 loss: 0.0295 (0.0297) time: 3.0172 data: 0.0083 max mem: 33408 +Epoch: [38] [1300/2639] eta: 1:07:29 lr: 2.6146923294675865e-06 loss: 0.0313 (0.0297) time: 3.0177 data: 0.0082 max mem: 33408 +Epoch: [38] [1310/2639] eta: 1:06:59 lr: 2.608774503911399e-06 loss: 0.0316 (0.0298) time: 3.0462 data: 0.0079 max mem: 33408 +Epoch: [38] [1320/2639] eta: 1:06:29 lr: 2.60285518640207e-06 loss: 0.0284 (0.0298) time: 3.0270 data: 0.0078 max mem: 33408 +Epoch: [38] [1330/2639] eta: 1:05:59 lr: 2.596934372791625e-06 loss: 0.0276 (0.0297) time: 3.0495 data: 0.0079 max mem: 33408 +Epoch: [38] [1340/2639] eta: 1:05:30 lr: 2.5910120589099884e-06 loss: 0.0276 (0.0297) time: 3.0868 data: 0.0079 max mem: 33408 +Epoch: [38] [1350/2639] eta: 1:04:59 lr: 2.585088240564866e-06 loss: 0.0267 (0.0297) time: 3.0253 data: 0.0077 max mem: 33408 +Epoch: [38] [1360/2639] eta: 1:04:29 lr: 2.5791629135415156e-06 loss: 0.0267 (0.0297) time: 3.0095 data: 0.0078 max mem: 33408 +Epoch: [38] [1370/2639] eta: 1:03:59 lr: 2.5732360736026225e-06 loss: 0.0296 (0.0297) time: 3.0671 data: 0.0077 max mem: 33408 +Epoch: [38] [1380/2639] eta: 1:03:28 lr: 2.567307716488066e-06 loss: 0.0296 (0.0297) time: 3.0092 data: 0.0076 max mem: 33408 +Epoch: [38] [1390/2639] eta: 1:02:57 lr: 2.561377837914793e-06 loss: 0.0298 (0.0297) time: 2.9638 data: 0.0079 max mem: 33408 +Epoch: [38] [1400/2639] eta: 1:02:28 lr: 2.555446433576581e-06 loss: 0.0260 (0.0297) time: 3.0397 data: 0.0082 max mem: 33408 +Epoch: [38] [1410/2639] eta: 1:01:58 lr: 2.5495134991439065e-06 loss: 0.0242 (0.0296) time: 3.0870 data: 0.0081 max mem: 33408 +Epoch: [38] [1420/2639] eta: 1:01:28 lr: 2.5435790302637026e-06 loss: 0.0233 (0.0296) time: 3.0599 data: 0.0081 max mem: 33408 +Epoch: [38] [1430/2639] eta: 1:00:57 lr: 2.5376430225592273e-06 loss: 0.0245 (0.0296) time: 3.0157 data: 0.0081 max mem: 33408 +Epoch: [38] [1440/2639] eta: 1:00:27 lr: 2.531705471629816e-06 loss: 0.0245 (0.0296) time: 3.0117 data: 0.0075 max mem: 33408 +Epoch: [38] [1450/2639] eta: 0:59:57 lr: 2.5257663730507427e-06 loss: 0.0248 (0.0296) time: 3.0397 data: 0.0077 max mem: 33408 +Epoch: [38] [1460/2639] eta: 0:59:27 lr: 2.519825722372971e-06 loss: 0.0270 (0.0296) time: 3.0573 data: 0.0079 max mem: 33408 +Epoch: [38] [1470/2639] eta: 0:58:56 lr: 2.513883515123012e-06 loss: 0.0291 (0.0296) time: 3.0068 data: 0.0081 max mem: 33408 +Epoch: [38] [1480/2639] eta: 0:58:26 lr: 2.507939746802668e-06 loss: 0.0270 (0.0295) time: 2.9957 data: 0.0086 max mem: 33408 +Epoch: [38] [1490/2639] eta: 0:57:56 lr: 2.5019944128888895e-06 loss: 0.0251 (0.0295) time: 3.0332 data: 0.0085 max mem: 33408 +Epoch: [38] [1500/2639] eta: 0:57:26 lr: 2.4960475088335133e-06 loss: 0.0285 (0.0295) time: 3.0565 data: 0.0080 max mem: 33408 +Epoch: [38] [1510/2639] eta: 0:56:56 lr: 2.4900990300631046e-06 loss: 0.0283 (0.0295) time: 3.0535 data: 0.0078 max mem: 33408 +Epoch: [38] [1520/2639] eta: 0:56:25 lr: 2.4841489719787325e-06 loss: 0.0275 (0.0295) time: 3.0228 data: 0.0080 max mem: 33408 +Epoch: [38] [1530/2639] eta: 0:55:56 lr: 2.478197329955733e-06 loss: 0.0273 (0.0295) time: 3.0757 data: 0.0079 max mem: 33408 +Epoch: [38] [1540/2639] eta: 0:55:25 lr: 2.4722440993435483e-06 loss: 0.0270 (0.0295) time: 3.0437 data: 0.0080 max mem: 33408 +Epoch: [38] [1550/2639] eta: 0:54:54 lr: 2.4662892754654566e-06 loss: 0.0284 (0.0295) time: 2.9572 data: 0.0083 max mem: 33408 +Epoch: [38] [1560/2639] eta: 0:54:24 lr: 2.460332853618407e-06 loss: 0.0324 (0.0295) time: 2.9605 data: 0.0082 max mem: 33408 +Epoch: [38] [1570/2639] eta: 0:53:54 lr: 2.4543748290727477e-06 loss: 0.0284 (0.0295) time: 3.0216 data: 0.0080 max mem: 33408 +Epoch: [38] [1580/2639] eta: 0:53:24 lr: 2.4484151970720576e-06 loss: 0.0279 (0.0295) time: 3.0692 data: 0.0079 max mem: 33408 +Epoch: [38] [1590/2639] eta: 0:52:54 lr: 2.442453952832866e-06 loss: 0.0275 (0.0295) time: 3.0435 data: 0.0080 max mem: 33408 +Epoch: [38] [1600/2639] eta: 0:52:23 lr: 2.4364910915444807e-06 loss: 0.0285 (0.0295) time: 2.9749 data: 0.0080 max mem: 33408 +Epoch: [38] [1610/2639] eta: 0:51:52 lr: 2.4305266083687035e-06 loss: 0.0268 (0.0295) time: 2.9686 data: 0.0078 max mem: 33408 +Epoch: [38] [1620/2639] eta: 0:51:22 lr: 2.424560498439653e-06 loss: 0.0267 (0.0295) time: 3.0037 data: 0.0074 max mem: 33408 +Epoch: [38] [1630/2639] eta: 0:50:52 lr: 2.418592756863474e-06 loss: 0.0293 (0.0295) time: 3.0353 data: 0.0076 max mem: 33408 +Epoch: [38] [1640/2639] eta: 0:50:21 lr: 2.4126233787181555e-06 loss: 0.0257 (0.0295) time: 3.0303 data: 0.0080 max mem: 33408 +Epoch: [38] [1650/2639] eta: 0:49:51 lr: 2.4066523590532354e-06 loss: 0.0247 (0.0295) time: 2.9874 data: 0.0082 max mem: 33408 +Epoch: [38] [1660/2639] eta: 0:49:21 lr: 2.4006796928896126e-06 loss: 0.0247 (0.0295) time: 2.9907 data: 0.0083 max mem: 33408 +Epoch: [38] [1670/2639] eta: 0:48:51 lr: 2.394705375219245e-06 loss: 0.0249 (0.0295) time: 3.0452 data: 0.0082 max mem: 33408 +Epoch: [38] [1680/2639] eta: 0:48:20 lr: 2.388729401004959e-06 loss: 0.0247 (0.0295) time: 3.0479 data: 0.0082 max mem: 33408 +Epoch: [38] [1690/2639] eta: 0:47:50 lr: 2.3827517651801386e-06 loss: 0.0247 (0.0295) time: 3.0317 data: 0.0086 max mem: 33408 +Epoch: [38] [1700/2639] eta: 0:47:20 lr: 2.3767724626485313e-06 loss: 0.0276 (0.0295) time: 3.0302 data: 0.0090 max mem: 33408 +Epoch: [38] [1710/2639] eta: 0:46:49 lr: 2.3707914882839312e-06 loss: 0.0269 (0.0295) time: 2.9982 data: 0.0085 max mem: 33408 +Epoch: [38] [1720/2639] eta: 0:46:19 lr: 2.3648088369299787e-06 loss: 0.0244 (0.0295) time: 3.0146 data: 0.0078 max mem: 33408 +Epoch: [38] [1730/2639] eta: 0:45:49 lr: 2.358824503399837e-06 loss: 0.0262 (0.0295) time: 3.0190 data: 0.0079 max mem: 33408 +Epoch: [38] [1740/2639] eta: 0:45:18 lr: 2.3528384824759857e-06 loss: 0.0298 (0.0296) time: 2.9750 data: 0.0082 max mem: 33408 +Epoch: [38] [1750/2639] eta: 0:44:48 lr: 2.346850768909894e-06 loss: 0.0325 (0.0296) time: 2.9770 data: 0.0083 max mem: 33408 +Epoch: [38] [1760/2639] eta: 0:44:17 lr: 2.3408613574217972e-06 loss: 0.0284 (0.0296) time: 2.9857 data: 0.0083 max mem: 33408 +Epoch: [38] [1770/2639] eta: 0:43:47 lr: 2.3348702427004007e-06 loss: 0.0286 (0.0296) time: 3.0064 data: 0.0080 max mem: 33408 +Epoch: [38] [1780/2639] eta: 0:43:17 lr: 2.3288774194025806e-06 loss: 0.0276 (0.0295) time: 3.0340 data: 0.0080 max mem: 33408 +Epoch: [38] [1790/2639] eta: 0:42:47 lr: 2.322882882153149e-06 loss: 0.0276 (0.0295) time: 3.0386 data: 0.0085 max mem: 33408 +Epoch: [38] [1800/2639] eta: 0:42:17 lr: 2.3168866255445133e-06 loss: 0.0292 (0.0295) time: 3.0651 data: 0.0086 max mem: 33408 +Epoch: [38] [1810/2639] eta: 0:41:47 lr: 2.310888644136447e-06 loss: 0.0282 (0.0295) time: 3.0313 data: 0.0083 max mem: 33408 +Epoch: [38] [1820/2639] eta: 0:41:16 lr: 2.304888932455735e-06 loss: 0.0277 (0.0295) time: 3.0119 data: 0.0081 max mem: 33408 +Epoch: [38] [1830/2639] eta: 0:40:46 lr: 2.2988874849959397e-06 loss: 0.0280 (0.0295) time: 3.0550 data: 0.0079 max mem: 33408 +Epoch: [38] [1840/2639] eta: 0:40:16 lr: 2.2928842962170436e-06 loss: 0.0281 (0.0295) time: 3.0890 data: 0.0080 max mem: 33408 +Epoch: [38] [1850/2639] eta: 0:39:46 lr: 2.286879360545202e-06 loss: 0.0235 (0.0295) time: 3.0833 data: 0.0080 max mem: 33408 +Epoch: [38] [1860/2639] eta: 0:39:16 lr: 2.280872672372381e-06 loss: 0.0232 (0.0295) time: 3.0387 data: 0.0078 max mem: 33408 +Epoch: [38] [1870/2639] eta: 0:38:46 lr: 2.2748642260561075e-06 loss: 0.0237 (0.0295) time: 3.0213 data: 0.0081 max mem: 33408 +Epoch: [38] [1880/2639] eta: 0:38:16 lr: 2.2688540159190915e-06 loss: 0.0244 (0.0295) time: 3.0519 data: 0.0083 max mem: 33408 +Epoch: [38] [1890/2639] eta: 0:37:46 lr: 2.262842036248972e-06 loss: 0.0244 (0.0295) time: 3.0550 data: 0.0080 max mem: 33408 +Epoch: [38] [1900/2639] eta: 0:37:15 lr: 2.2568282812979368e-06 loss: 0.0277 (0.0295) time: 3.0526 data: 0.0082 max mem: 33408 +Epoch: [38] [1910/2639] eta: 0:36:45 lr: 2.2508127452824517e-06 loss: 0.0255 (0.0295) time: 3.0742 data: 0.0085 max mem: 33408 +Epoch: [38] [1920/2639] eta: 0:36:15 lr: 2.244795422382879e-06 loss: 0.0252 (0.0294) time: 3.0858 data: 0.0082 max mem: 33408 +Epoch: [38] [1930/2639] eta: 0:35:45 lr: 2.2387763067431967e-06 loss: 0.0259 (0.0294) time: 3.0906 data: 0.0082 max mem: 33408 +Epoch: [38] [1940/2639] eta: 0:35:15 lr: 2.2327553924706077e-06 loss: 0.0269 (0.0294) time: 3.0323 data: 0.0081 max mem: 33408 +Epoch: [38] [1950/2639] eta: 0:34:44 lr: 2.2267326736352527e-06 loss: 0.0270 (0.0294) time: 2.9676 data: 0.0079 max mem: 33408 +Epoch: [38] [1960/2639] eta: 0:34:14 lr: 2.220708144269811e-06 loss: 0.0303 (0.0294) time: 3.0262 data: 0.0079 max mem: 33408 +Epoch: [38] [1970/2639] eta: 0:33:44 lr: 2.2146817983692017e-06 loss: 0.0291 (0.0294) time: 3.0653 data: 0.0079 max mem: 33408 +Epoch: [38] [1980/2639] eta: 0:33:14 lr: 2.2086536298901795e-06 loss: 0.0260 (0.0294) time: 3.0311 data: 0.0079 max mem: 33408 +Epoch: [38] [1990/2639] eta: 0:32:44 lr: 2.202623632751028e-06 loss: 0.0254 (0.0294) time: 3.0311 data: 0.0078 max mem: 33408 +Epoch: [38] [2000/2639] eta: 0:32:13 lr: 2.1965918008311424e-06 loss: 0.0264 (0.0294) time: 3.0164 data: 0.0077 max mem: 33408 +Epoch: [38] [2010/2639] eta: 0:31:43 lr: 2.1905581279707087e-06 loss: 0.0282 (0.0294) time: 2.9803 data: 0.0076 max mem: 33408 +Epoch: [38] [2020/2639] eta: 0:31:13 lr: 2.184522607970314e-06 loss: 0.0276 (0.0294) time: 2.9835 data: 0.0080 max mem: 33408 +Epoch: [38] [2030/2639] eta: 0:30:42 lr: 2.1784852345905437e-06 loss: 0.0270 (0.0294) time: 3.0404 data: 0.0079 max mem: 33408 +Epoch: [38] [2040/2639] eta: 0:30:12 lr: 2.172446001551654e-06 loss: 0.0284 (0.0294) time: 3.0265 data: 0.0076 max mem: 33408 +Epoch: [38] [2050/2639] eta: 0:29:42 lr: 2.166404902533126e-06 loss: 0.0284 (0.0294) time: 2.9736 data: 0.0081 max mem: 33408 +Epoch: [38] [2060/2639] eta: 0:29:11 lr: 2.160361931173329e-06 loss: 0.0296 (0.0294) time: 2.9767 data: 0.0078 max mem: 33408 +Epoch: [38] [2070/2639] eta: 0:28:41 lr: 2.154317081069073e-06 loss: 0.0308 (0.0294) time: 2.9754 data: 0.0078 max mem: 33408 +Epoch: [38] [2080/2639] eta: 0:28:10 lr: 2.148270345775258e-06 loss: 0.0265 (0.0294) time: 2.9752 data: 0.0084 max mem: 33408 +Epoch: [38] [2090/2639] eta: 0:27:40 lr: 2.1422217188044147e-06 loss: 0.0257 (0.0294) time: 3.0240 data: 0.0084 max mem: 33408 +Epoch: [38] [2100/2639] eta: 0:27:10 lr: 2.1361711936263465e-06 loss: 0.0263 (0.0294) time: 3.0729 data: 0.0081 max mem: 33408 +Epoch: [38] [2110/2639] eta: 0:26:40 lr: 2.1301187636676578e-06 loss: 0.0286 (0.0294) time: 3.0805 data: 0.0079 max mem: 33408 +Epoch: [38] [2120/2639] eta: 0:26:10 lr: 2.1240644223113846e-06 loss: 0.0275 (0.0294) time: 3.0473 data: 0.0077 max mem: 33408 +Epoch: [38] [2130/2639] eta: 0:25:39 lr: 2.1180081628965154e-06 loss: 0.0258 (0.0294) time: 3.0070 data: 0.0078 max mem: 33408 +Epoch: [38] [2140/2639] eta: 0:25:09 lr: 2.1119499787176087e-06 loss: 0.0267 (0.0294) time: 3.0308 data: 0.0078 max mem: 33408 +Epoch: [38] [2150/2639] eta: 0:24:39 lr: 2.1058898630242986e-06 loss: 0.0265 (0.0294) time: 3.0627 data: 0.0077 max mem: 33408 +Epoch: [38] [2160/2639] eta: 0:24:09 lr: 2.099827809020908e-06 loss: 0.0265 (0.0294) time: 3.0423 data: 0.0082 max mem: 33408 +Epoch: [38] [2170/2639] eta: 0:23:39 lr: 2.093763809865939e-06 loss: 0.0265 (0.0294) time: 3.0489 data: 0.0082 max mem: 33408 +Epoch: [38] [2180/2639] eta: 0:23:08 lr: 2.087697858671673e-06 loss: 0.0275 (0.0294) time: 3.0134 data: 0.0082 max mem: 33408 +Epoch: [38] [2190/2639] eta: 0:22:38 lr: 2.0816299485036516e-06 loss: 0.0275 (0.0294) time: 2.9814 data: 0.0079 max mem: 33408 +Epoch: [38] [2200/2639] eta: 0:22:08 lr: 2.075560072380264e-06 loss: 0.0302 (0.0294) time: 3.0231 data: 0.0078 max mem: 33408 +Epoch: [38] [2210/2639] eta: 0:21:38 lr: 2.0694882232722148e-06 loss: 0.0302 (0.0294) time: 3.0596 data: 0.0080 max mem: 33408 +Epoch: [38] [2220/2639] eta: 0:21:07 lr: 2.063414394102098e-06 loss: 0.0285 (0.0294) time: 3.0616 data: 0.0080 max mem: 33408 +Epoch: [38] [2230/2639] eta: 0:20:37 lr: 2.0573385777438527e-06 loss: 0.0278 (0.0294) time: 2.9920 data: 0.0086 max mem: 33408 +Epoch: [38] [2240/2639] eta: 0:20:07 lr: 2.0512607670223263e-06 loss: 0.0272 (0.0294) time: 2.9862 data: 0.0087 max mem: 33408 +Epoch: [38] [2250/2639] eta: 0:19:36 lr: 2.045180954712714e-06 loss: 0.0298 (0.0295) time: 3.0309 data: 0.0080 max mem: 33408 +Epoch: [38] [2260/2639] eta: 0:19:06 lr: 2.0390991335401023e-06 loss: 0.0351 (0.0295) time: 3.0209 data: 0.0078 max mem: 33408 +Epoch: [38] [2270/2639] eta: 0:18:36 lr: 2.033015296178931e-06 loss: 0.0260 (0.0294) time: 3.0616 data: 0.0081 max mem: 33408 +Epoch: [38] [2280/2639] eta: 0:18:06 lr: 2.02692943525245e-06 loss: 0.0224 (0.0294) time: 3.1046 data: 0.0082 max mem: 33408 +Epoch: [38] [2290/2639] eta: 0:17:36 lr: 2.020841543332241e-06 loss: 0.0245 (0.0294) time: 3.0483 data: 0.0079 max mem: 33408 +Epoch: [38] [2300/2639] eta: 0:17:05 lr: 2.01475161293762e-06 loss: 0.0255 (0.0294) time: 2.9888 data: 0.0077 max mem: 33408 +Epoch: [38] [2310/2639] eta: 0:16:35 lr: 2.0086596365351576e-06 loss: 0.0258 (0.0294) time: 3.0018 data: 0.0077 max mem: 33408 +Epoch: [38] [2320/2639] eta: 0:16:05 lr: 2.0025656065380617e-06 loss: 0.0302 (0.0294) time: 3.0339 data: 0.0075 max mem: 33408 +Epoch: [38] [2330/2639] eta: 0:15:35 lr: 1.9964695153056823e-06 loss: 0.0274 (0.0294) time: 3.0694 data: 0.0081 max mem: 33408 +Epoch: [38] [2340/2639] eta: 0:15:04 lr: 1.990371355142883e-06 loss: 0.0267 (0.0294) time: 3.0545 data: 0.0083 max mem: 33408 +Epoch: [38] [2350/2639] eta: 0:14:34 lr: 1.9842711182995268e-06 loss: 0.0273 (0.0294) time: 3.0356 data: 0.0078 max mem: 33408 +Epoch: [38] [2360/2639] eta: 0:14:04 lr: 1.9781687969698327e-06 loss: 0.0269 (0.0294) time: 3.0735 data: 0.0079 max mem: 33408 +Epoch: [38] [2370/2639] eta: 0:13:34 lr: 1.9720643832918437e-06 loss: 0.0257 (0.0294) time: 3.0395 data: 0.0080 max mem: 33408 +Epoch: [38] [2380/2639] eta: 0:13:03 lr: 1.9659578693467696e-06 loss: 0.0311 (0.0294) time: 3.0264 data: 0.0079 max mem: 33408 +Epoch: [38] [2390/2639] eta: 0:12:33 lr: 1.959849247158437e-06 loss: 0.0311 (0.0294) time: 3.0449 data: 0.0078 max mem: 33408 +Epoch: [38] [2400/2639] eta: 0:12:03 lr: 1.953738508692614e-06 loss: 0.0282 (0.0295) time: 3.0113 data: 0.0076 max mem: 33408 +Epoch: [38] [2410/2639] eta: 0:11:33 lr: 1.947625645856443e-06 loss: 0.0296 (0.0295) time: 3.0112 data: 0.0077 max mem: 33408 +Epoch: [38] [2420/2639] eta: 0:11:02 lr: 1.9415106504977494e-06 loss: 0.0302 (0.0295) time: 3.0050 data: 0.0078 max mem: 33408 +Epoch: [38] [2430/2639] eta: 0:10:32 lr: 1.9353935144044545e-06 loss: 0.0287 (0.0295) time: 2.9773 data: 0.0079 max mem: 33408 +Epoch: [38] [2440/2639] eta: 0:10:02 lr: 1.929274229303866e-06 loss: 0.0295 (0.0295) time: 3.0368 data: 0.0084 max mem: 33408 +Epoch: [38] [2450/2639] eta: 0:09:31 lr: 1.9231527868620742e-06 loss: 0.0279 (0.0295) time: 3.0446 data: 0.0083 max mem: 33408 +Epoch: [38] [2460/2639] eta: 0:09:01 lr: 1.9170291786832204e-06 loss: 0.0253 (0.0295) time: 3.0148 data: 0.0084 max mem: 33408 +Epoch: [38] [2470/2639] eta: 0:08:31 lr: 1.9109033963088755e-06 loss: 0.0246 (0.0295) time: 3.0685 data: 0.0085 max mem: 33408 +Epoch: [38] [2480/2639] eta: 0:08:01 lr: 1.9047754312172892e-06 loss: 0.0236 (0.0295) time: 3.0667 data: 0.0083 max mem: 33408 +Epoch: [38] [2490/2639] eta: 0:07:30 lr: 1.8986452748227469e-06 loss: 0.0256 (0.0294) time: 3.0019 data: 0.0084 max mem: 33408 +Epoch: [38] [2500/2639] eta: 0:07:00 lr: 1.8925129184747998e-06 loss: 0.0275 (0.0295) time: 2.9899 data: 0.0082 max mem: 33408 +Epoch: [38] [2510/2639] eta: 0:06:30 lr: 1.8863783534575924e-06 loss: 0.0275 (0.0295) time: 3.0513 data: 0.0079 max mem: 33408 +Epoch: [38] [2520/2639] eta: 0:06:00 lr: 1.8802415709891094e-06 loss: 0.0266 (0.0294) time: 3.0592 data: 0.0079 max mem: 33408 +Epoch: [38] [2530/2639] eta: 0:05:29 lr: 1.8741025622204079e-06 loss: 0.0272 (0.0295) time: 3.0441 data: 0.0078 max mem: 33408 +Epoch: [38] [2540/2639] eta: 0:04:59 lr: 1.8679613182349138e-06 loss: 0.0297 (0.0295) time: 3.0838 data: 0.0075 max mem: 33408 +Epoch: [38] [2550/2639] eta: 0:04:29 lr: 1.8618178300475973e-06 loss: 0.0293 (0.0295) time: 3.0759 data: 0.0078 max mem: 33408 +Epoch: [38] [2560/2639] eta: 0:03:59 lr: 1.8556720886042537e-06 loss: 0.0319 (0.0295) time: 3.0422 data: 0.0080 max mem: 33408 +Epoch: [38] [2570/2639] eta: 0:03:28 lr: 1.849524084780654e-06 loss: 0.0319 (0.0295) time: 3.0719 data: 0.0078 max mem: 33408 +Epoch: [38] [2580/2639] eta: 0:02:58 lr: 1.8433738093818026e-06 loss: 0.0274 (0.0295) time: 3.0953 data: 0.0076 max mem: 33408 +Epoch: [38] [2590/2639] eta: 0:02:28 lr: 1.837221253141064e-06 loss: 0.0263 (0.0295) time: 3.0759 data: 0.0079 max mem: 33408 +Epoch: [38] [2600/2639] eta: 0:01:58 lr: 1.8310664067193968e-06 loss: 0.0271 (0.0295) time: 3.0398 data: 0.0081 max mem: 33408 +Epoch: [38] [2610/2639] eta: 0:01:27 lr: 1.8249092607044538e-06 loss: 0.0271 (0.0295) time: 3.0040 data: 0.0080 max mem: 33408 +Epoch: [38] [2620/2639] eta: 0:00:57 lr: 1.8187498056097902e-06 loss: 0.0288 (0.0295) time: 3.0067 data: 0.0079 max mem: 33408 +Epoch: [38] [2630/2639] eta: 0:00:27 lr: 1.8125880318739397e-06 loss: 0.0266 (0.0295) time: 3.0305 data: 0.0075 max mem: 33408 +Epoch: [38] Total time: 2:13:10 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 2:16:07 time: 3.1744 data: 3.0869 max mem: 33408 +Test: [ 100/2573] eta: 0:04:28 time: 0.0780 data: 0.0015 max mem: 33408 +Test: [ 200/2573] eta: 0:03:43 time: 0.0791 data: 0.0014 max mem: 33408 +Test: [ 300/2573] eta: 0:03:22 time: 0.0817 data: 0.0014 max mem: 33408 +Test: [ 400/2573] eta: 0:03:08 time: 0.0816 data: 0.0013 max mem: 33408 +Test: [ 500/2573] eta: 0:02:57 time: 0.0813 data: 0.0014 max mem: 33408 +Test: [ 600/2573] eta: 0:02:47 time: 0.0808 data: 0.0016 max mem: 33408 +Test: [ 700/2573] eta: 0:02:38 time: 0.0810 data: 0.0016 max mem: 33408 +Test: [ 800/2573] eta: 0:02:29 time: 0.0844 data: 0.0014 max mem: 33408 +Test: [ 900/2573] eta: 0:02:20 time: 0.0800 data: 0.0014 max mem: 33408 +Test: [1000/2573] eta: 0:02:11 time: 0.0815 data: 0.0014 max mem: 33408 +Test: [1100/2573] eta: 0:02:03 time: 0.0803 data: 0.0015 max mem: 33408 +Test: [1200/2573] eta: 0:01:54 time: 0.0807 data: 0.0014 max mem: 33408 +Test: [1300/2573] eta: 0:01:45 time: 0.0812 data: 0.0014 max mem: 33408 +Test: [1400/2573] eta: 0:01:37 time: 0.0801 data: 0.0016 max mem: 33408 +Test: [1500/2573] eta: 0:01:28 time: 0.0809 data: 0.0014 max mem: 33408 +Test: [1600/2573] eta: 0:01:20 time: 0.0842 data: 0.0014 max mem: 33408 +Test: [1700/2573] eta: 0:01:12 time: 0.0797 data: 0.0014 max mem: 33408 +Test: [1800/2573] eta: 0:01:03 time: 0.0830 data: 0.0014 max mem: 33408 +Test: [1900/2573] eta: 0:00:55 time: 0.0799 data: 0.0015 max mem: 33408 +Test: [2000/2573] eta: 0:00:47 time: 0.0806 data: 0.0014 max mem: 33408 +Test: [2100/2573] eta: 0:00:38 time: 0.0841 data: 0.0014 max mem: 33408 +Test: [2200/2573] eta: 0:00:30 time: 0.0832 data: 0.0014 max mem: 33408 +Test: [2300/2573] eta: 0:00:22 time: 0.0829 data: 0.0015 max mem: 33408 +Test: [2400/2573] eta: 0:00:14 time: 0.0767 data: 0.0014 max mem: 33408 +Test: [2500/2573] eta: 0:00:06 time: 0.0816 data: 0.0014 max mem: 33408 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: Total time: 0:03:32 +Final results: +Mean IoU is 65.47 + + precision@0.5 = 74.00 + precision@0.6 = 68.67 + precision@0.7 = 61.76 + precision@0.8 = 51.45 + precision@0.9 = 25.53 + overall IoU = 62.80 + +Average object IoU 65.47092924039434 +Overall IoU 62.80475997924805 +Better epoch: 38 + +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [39] [ 0/2639] eta: 4:04:58 lr: 1.807040445109804e-06 loss: 0.0259 (0.0259) time: 5.5697 data: 2.1890 max mem: 33408 +Epoch: [39] [ 10/2639] eta: 2:24:17 lr: 1.8008742393414706e-06 loss: 0.0261 (0.0272) time: 3.2931 data: 0.2068 max mem: 33408 +Epoch: [39] [ 20/2639] eta: 2:18:13 lr: 1.7947056867714853e-06 loss: 0.0263 (0.0275) time: 3.0467 data: 0.0077 max mem: 33408 +Epoch: [39] [ 30/2639] eta: 2:15:12 lr: 1.78853477753742e-06 loss: 0.0271 (0.0274) time: 3.0082 data: 0.0078 max mem: 33408 +Epoch: [39] [ 40/2639] eta: 2:13:52 lr: 1.7823615016973883e-06 loss: 0.0236 (0.0267) time: 3.0109 data: 0.0085 max mem: 33408 +Epoch: [39] [ 50/2639] eta: 2:12:36 lr: 1.7761858492291547e-06 loss: 0.0236 (0.0266) time: 3.0171 data: 0.0084 max mem: 33408 +Epoch: [39] [ 60/2639] eta: 2:12:06 lr: 1.7700078100291148e-06 loss: 0.0235 (0.0265) time: 3.0385 data: 0.0081 max mem: 33408 +Epoch: [39] [ 70/2639] eta: 2:11:19 lr: 1.7638273739113738e-06 loss: 0.0267 (0.0266) time: 3.0525 data: 0.0078 max mem: 33408 +Epoch: [39] [ 80/2639] eta: 2:10:34 lr: 1.7576445306066953e-06 loss: 0.0279 (0.0269) time: 3.0243 data: 0.0079 max mem: 33408 +Epoch: [39] [ 90/2639] eta: 2:10:01 lr: 1.7514592697615485e-06 loss: 0.0254 (0.0266) time: 3.0370 data: 0.0080 max mem: 33408 +Epoch: [39] [ 100/2639] eta: 2:09:26 lr: 1.7452715809370263e-06 loss: 0.0269 (0.0273) time: 3.0490 data: 0.0080 max mem: 33408 +Epoch: [39] [ 110/2639] eta: 2:08:50 lr: 1.7390814536078575e-06 loss: 0.0280 (0.0272) time: 3.0385 data: 0.0084 max mem: 33408 +Epoch: [39] [ 120/2639] eta: 2:08:06 lr: 1.7328888771612922e-06 loss: 0.0262 (0.0271) time: 3.0133 data: 0.0086 max mem: 33408 +Epoch: [39] [ 130/2639] eta: 2:07:39 lr: 1.7266938408960726e-06 loss: 0.0262 (0.0273) time: 3.0302 data: 0.0084 max mem: 33408 +Epoch: [39] [ 140/2639] eta: 2:07:00 lr: 1.7204963340213202e-06 loss: 0.0271 (0.0274) time: 3.0375 data: 0.0083 max mem: 33408 +Epoch: [39] [ 150/2639] eta: 2:06:35 lr: 1.7142963456553988e-06 loss: 0.0270 (0.0274) time: 3.0466 data: 0.0083 max mem: 33408 +Epoch: [39] [ 160/2639] eta: 2:05:55 lr: 1.7080938648248356e-06 loss: 0.0267 (0.0274) time: 3.0353 data: 0.0082 max mem: 33408 +Epoch: [39] [ 170/2639] eta: 2:05:20 lr: 1.7018888804631143e-06 loss: 0.0264 (0.0277) time: 3.0031 data: 0.0080 max mem: 33408 +Epoch: [39] [ 180/2639] eta: 2:04:44 lr: 1.6956813814095633e-06 loss: 0.0253 (0.0277) time: 3.0112 data: 0.0079 max mem: 33408 +Epoch: [39] [ 190/2639] eta: 2:04:10 lr: 1.6894713564081102e-06 loss: 0.0277 (0.0279) time: 3.0095 data: 0.0079 max mem: 33408 +Epoch: [39] [ 200/2639] eta: 2:03:41 lr: 1.6832587941061316e-06 loss: 0.0291 (0.0280) time: 3.0357 data: 0.0080 max mem: 33408 +Epoch: [39] [ 210/2639] eta: 2:03:17 lr: 1.6770436830531672e-06 loss: 0.0279 (0.0281) time: 3.0768 data: 0.0077 max mem: 33408 +Epoch: [39] [ 220/2639] eta: 2:02:48 lr: 1.6708260116997286e-06 loss: 0.0279 (0.0282) time: 3.0782 data: 0.0078 max mem: 33408 +Epoch: [39] [ 230/2639] eta: 2:02:15 lr: 1.664605768395971e-06 loss: 0.0280 (0.0284) time: 3.0374 data: 0.0079 max mem: 33408 +Epoch: [39] [ 240/2639] eta: 2:01:33 lr: 1.658382941390459e-06 loss: 0.0280 (0.0285) time: 2.9757 data: 0.0077 max mem: 33408 +Epoch: [39] [ 250/2639] eta: 2:00:59 lr: 1.652157518828795e-06 loss: 0.0297 (0.0285) time: 2.9702 data: 0.0078 max mem: 33408 +Epoch: [39] [ 260/2639] eta: 2:00:26 lr: 1.6459294887523402e-06 loss: 0.0282 (0.0285) time: 3.0071 data: 0.0080 max mem: 33408 +Epoch: [39] [ 270/2639] eta: 1:59:53 lr: 1.6396988390967982e-06 loss: 0.0266 (0.0285) time: 3.0046 data: 0.0080 max mem: 33408 +Epoch: [39] [ 280/2639] eta: 1:59:25 lr: 1.6334655576908892e-06 loss: 0.0276 (0.0285) time: 3.0355 data: 0.0075 max mem: 33408 +Epoch: [39] [ 290/2639] eta: 1:58:52 lr: 1.6272296322548834e-06 loss: 0.0276 (0.0285) time: 3.0342 data: 0.0074 max mem: 33408 +Epoch: [39] [ 300/2639] eta: 1:58:12 lr: 1.6209910503992297e-06 loss: 0.0249 (0.0284) time: 2.9598 data: 0.0075 max mem: 33408 +Epoch: [39] [ 310/2639] eta: 1:57:41 lr: 1.6147497996230394e-06 loss: 0.0243 (0.0284) time: 2.9673 data: 0.0075 max mem: 33408 +Epoch: [39] [ 320/2639] eta: 1:57:13 lr: 1.6085058673126616e-06 loss: 0.0297 (0.0284) time: 3.0425 data: 0.0077 max mem: 33408 +Epoch: [39] [ 330/2639] eta: 1:56:43 lr: 1.6022592407401175e-06 loss: 0.0281 (0.0283) time: 3.0569 data: 0.0076 max mem: 33408 +Epoch: [39] [ 340/2639] eta: 1:56:11 lr: 1.5960099070616213e-06 loss: 0.0281 (0.0285) time: 3.0245 data: 0.0077 max mem: 33408 +Epoch: [39] [ 350/2639] eta: 1:55:43 lr: 1.5897578533159603e-06 loss: 0.0295 (0.0286) time: 3.0323 data: 0.0079 max mem: 33408 +Epoch: [39] [ 360/2639] eta: 1:55:14 lr: 1.583503066422962e-06 loss: 0.0268 (0.0286) time: 3.0560 data: 0.0079 max mem: 33408 +Epoch: [39] [ 370/2639] eta: 1:54:47 lr: 1.5772455331818158e-06 loss: 0.0264 (0.0286) time: 3.0723 data: 0.0079 max mem: 33408 +Epoch: [39] [ 380/2639] eta: 1:54:17 lr: 1.570985240269475e-06 loss: 0.0264 (0.0285) time: 3.0700 data: 0.0076 max mem: 33408 +Epoch: [39] [ 390/2639] eta: 1:53:43 lr: 1.5647221742389562e-06 loss: 0.0267 (0.0286) time: 3.0108 data: 0.0078 max mem: 33408 +Epoch: [39] [ 400/2639] eta: 1:53:12 lr: 1.5584563215176094e-06 loss: 0.0284 (0.0287) time: 2.9932 data: 0.0078 max mem: 33408 +Epoch: [39] [ 410/2639] eta: 1:52:43 lr: 1.552187668405425e-06 loss: 0.0274 (0.0286) time: 3.0350 data: 0.0079 max mem: 33408 +Epoch: [39] [ 420/2639] eta: 1:52:13 lr: 1.5459162010732058e-06 loss: 0.0243 (0.0286) time: 3.0539 data: 0.0085 max mem: 33408 +Epoch: [39] [ 430/2639] eta: 1:51:38 lr: 1.5396419055608177e-06 loss: 0.0256 (0.0285) time: 2.9962 data: 0.0084 max mem: 33408 +Epoch: [39] [ 440/2639] eta: 1:51:07 lr: 1.533364767775293e-06 loss: 0.0255 (0.0286) time: 2.9780 data: 0.0079 max mem: 33408 +Epoch: [39] [ 450/2639] eta: 1:50:38 lr: 1.5270847734890161e-06 loss: 0.0253 (0.0287) time: 3.0384 data: 0.0078 max mem: 33408 +Epoch: [39] [ 460/2639] eta: 1:50:08 lr: 1.520801908337754e-06 loss: 0.0289 (0.0287) time: 3.0522 data: 0.0078 max mem: 33408 +Epoch: [39] [ 470/2639] eta: 1:49:41 lr: 1.5145161578187727e-06 loss: 0.0240 (0.0286) time: 3.0679 data: 0.0078 max mem: 33408 +Epoch: [39] [ 480/2639] eta: 1:49:11 lr: 1.5082275072887958e-06 loss: 0.0233 (0.0286) time: 3.0765 data: 0.0078 max mem: 33408 +Epoch: [39] [ 490/2639] eta: 1:48:40 lr: 1.5019359419620458e-06 loss: 0.0248 (0.0286) time: 3.0398 data: 0.0080 max mem: 33408 +Epoch: [39] [ 500/2639] eta: 1:48:09 lr: 1.4956414469081257e-06 loss: 0.0294 (0.0287) time: 3.0122 data: 0.0081 max mem: 33408 +Epoch: [39] [ 510/2639] eta: 1:47:34 lr: 1.4893440070499819e-06 loss: 0.0276 (0.0286) time: 2.9666 data: 0.0082 max mem: 33408 +Epoch: [39] [ 520/2639] eta: 1:47:01 lr: 1.4830436071617089e-06 loss: 0.0237 (0.0286) time: 2.9473 data: 0.0086 max mem: 33408 +Epoch: [39] [ 530/2639] eta: 1:46:31 lr: 1.4767402318664276e-06 loss: 0.0274 (0.0286) time: 2.9970 data: 0.0082 max mem: 33408 +Epoch: [39] [ 540/2639] eta: 1:46:00 lr: 1.4704338656340061e-06 loss: 0.0272 (0.0286) time: 3.0186 data: 0.0077 max mem: 33408 +Epoch: [39] [ 550/2639] eta: 1:45:31 lr: 1.4641244927788546e-06 loss: 0.0272 (0.0287) time: 3.0449 data: 0.0076 max mem: 33408 +Epoch: [39] [ 560/2639] eta: 1:45:00 lr: 1.4578120974575557e-06 loss: 0.0319 (0.0287) time: 3.0419 data: 0.0080 max mem: 33408 +Epoch: [39] [ 570/2639] eta: 1:44:25 lr: 1.451496663666571e-06 loss: 0.0309 (0.0287) time: 2.9541 data: 0.0085 max mem: 33408 +Epoch: [39] [ 580/2639] eta: 1:43:55 lr: 1.4451781752397784e-06 loss: 0.0314 (0.0288) time: 2.9770 data: 0.0086 max mem: 33408 +Epoch: [39] [ 590/2639] eta: 1:43:27 lr: 1.4388566158460838e-06 loss: 0.0324 (0.0289) time: 3.0626 data: 0.0082 max mem: 33408 +Epoch: [39] [ 600/2639] eta: 1:42:57 lr: 1.4325319689868626e-06 loss: 0.0272 (0.0289) time: 3.0628 data: 0.0081 max mem: 33408 +Epoch: [39] [ 610/2639] eta: 1:42:26 lr: 1.4262042179934711e-06 loss: 0.0293 (0.0289) time: 3.0282 data: 0.0079 max mem: 33408 +Epoch: [39] [ 620/2639] eta: 1:41:56 lr: 1.4198733460245866e-06 loss: 0.0293 (0.0290) time: 3.0216 data: 0.0079 max mem: 33408 +Epoch: [39] [ 630/2639] eta: 1:41:25 lr: 1.413539336063607e-06 loss: 0.0251 (0.0289) time: 3.0185 data: 0.0078 max mem: 33408 +Epoch: [39] [ 640/2639] eta: 1:40:54 lr: 1.407202170915921e-06 loss: 0.0264 (0.0290) time: 3.0089 data: 0.0082 max mem: 33408 +Epoch: [39] [ 650/2639] eta: 1:40:24 lr: 1.4008618332061233e-06 loss: 0.0278 (0.0290) time: 3.0259 data: 0.0085 max mem: 33408 +Epoch: [39] [ 660/2639] eta: 1:39:55 lr: 1.3945183053752472e-06 loss: 0.0255 (0.0290) time: 3.0556 data: 0.0085 max mem: 33408 +Epoch: [39] [ 670/2639] eta: 1:39:24 lr: 1.3881715696778265e-06 loss: 0.0286 (0.0290) time: 3.0456 data: 0.0085 max mem: 33408 +Epoch: [39] [ 680/2639] eta: 1:38:55 lr: 1.3818216081790177e-06 loss: 0.0286 (0.0291) time: 3.0428 data: 0.0082 max mem: 33408 +Epoch: [39] [ 690/2639] eta: 1:38:24 lr: 1.3754684027515405e-06 loss: 0.0267 (0.0290) time: 3.0364 data: 0.0084 max mem: 33408 +Epoch: [39] [ 700/2639] eta: 1:37:55 lr: 1.369111935072674e-06 loss: 0.0263 (0.0290) time: 3.0337 data: 0.0086 max mem: 33408 +Epoch: [39] [ 710/2639] eta: 1:37:24 lr: 1.362752186621071e-06 loss: 0.0243 (0.0291) time: 3.0306 data: 0.0082 max mem: 33408 +Epoch: [39] [ 720/2639] eta: 1:36:55 lr: 1.3563891386736214e-06 loss: 0.0243 (0.0290) time: 3.0379 data: 0.0080 max mem: 33408 +Epoch: [39] [ 730/2639] eta: 1:36:25 lr: 1.3500227723021329e-06 loss: 0.0282 (0.0291) time: 3.0592 data: 0.0078 max mem: 33408 +Epoch: [39] [ 740/2639] eta: 1:35:56 lr: 1.343653068370055e-06 loss: 0.0307 (0.0291) time: 3.0604 data: 0.0078 max mem: 33408 +Epoch: [39] [ 750/2639] eta: 1:35:26 lr: 1.337280007529018e-06 loss: 0.0307 (0.0291) time: 3.0639 data: 0.0078 max mem: 33408 +Epoch: [39] [ 760/2639] eta: 1:34:56 lr: 1.3309035702154111e-06 loss: 0.0281 (0.0291) time: 3.0519 data: 0.0078 max mem: 33408 +Epoch: [39] [ 770/2639] eta: 1:34:27 lr: 1.3245237366467714e-06 loss: 0.0259 (0.0291) time: 3.0699 data: 0.0081 max mem: 33408 +Epoch: [39] [ 780/2639] eta: 1:33:57 lr: 1.3181404868182082e-06 loss: 0.0304 (0.0291) time: 3.0561 data: 0.0081 max mem: 33408 +Epoch: [39] [ 790/2639] eta: 1:33:27 lr: 1.3117538004986322e-06 loss: 0.0299 (0.0291) time: 3.0426 data: 0.0081 max mem: 33408 +Epoch: [39] [ 800/2639] eta: 1:32:56 lr: 1.3053636572270203e-06 loss: 0.0255 (0.0292) time: 3.0293 data: 0.0077 max mem: 33408 +Epoch: [39] [ 810/2639] eta: 1:32:25 lr: 1.2989700363084755e-06 loss: 0.0251 (0.0292) time: 3.0016 data: 0.0078 max mem: 33408 +Epoch: [39] [ 820/2639] eta: 1:31:53 lr: 1.29257291681032e-06 loss: 0.0263 (0.0292) time: 2.9801 data: 0.0079 max mem: 33408 +Epoch: [39] [ 830/2639] eta: 1:31:22 lr: 1.2861722775579791e-06 loss: 0.0277 (0.0292) time: 2.9730 data: 0.0080 max mem: 33408 +Epoch: [39] [ 840/2639] eta: 1:30:51 lr: 1.2797680971308933e-06 loss: 0.0260 (0.0291) time: 3.0101 data: 0.0080 max mem: 33408 +Epoch: [39] [ 850/2639] eta: 1:30:22 lr: 1.2733603538582149e-06 loss: 0.0244 (0.0291) time: 3.0597 data: 0.0075 max mem: 33408 +Epoch: [39] [ 860/2639] eta: 1:29:52 lr: 1.2669490258145274e-06 loss: 0.0278 (0.0291) time: 3.0491 data: 0.0077 max mem: 33408 +Epoch: [39] [ 870/2639] eta: 1:29:21 lr: 1.2605340908153463e-06 loss: 0.0278 (0.0291) time: 3.0256 data: 0.0082 max mem: 33408 +Epoch: [39] [ 880/2639] eta: 1:28:51 lr: 1.2541155264126276e-06 loss: 0.0268 (0.0291) time: 3.0433 data: 0.0080 max mem: 33408 +Epoch: [39] [ 890/2639] eta: 1:28:21 lr: 1.2476933098900958e-06 loss: 0.0250 (0.0290) time: 3.0311 data: 0.0077 max mem: 33408 +Epoch: [39] [ 900/2639] eta: 1:27:50 lr: 1.2412674182584628e-06 loss: 0.0231 (0.0290) time: 3.0045 data: 0.0076 max mem: 33408 +Epoch: [39] [ 910/2639] eta: 1:27:20 lr: 1.234837828250611e-06 loss: 0.0231 (0.0290) time: 3.0249 data: 0.0075 max mem: 33408 +Epoch: [39] [ 920/2639] eta: 1:26:49 lr: 1.2284045163165451e-06 loss: 0.0284 (0.0291) time: 3.0306 data: 0.0078 max mem: 33408 +Epoch: [39] [ 930/2639] eta: 1:26:18 lr: 1.221967458618348e-06 loss: 0.0284 (0.0290) time: 3.0054 data: 0.0080 max mem: 33408 +Epoch: [39] [ 940/2639] eta: 1:25:48 lr: 1.215526631024893e-06 loss: 0.0273 (0.0291) time: 3.0282 data: 0.0076 max mem: 33408 +Epoch: [39] [ 950/2639] eta: 1:25:17 lr: 1.2090820091065481e-06 loss: 0.0268 (0.0290) time: 3.0234 data: 0.0075 max mem: 33408 +Epoch: [39] [ 960/2639] eta: 1:24:47 lr: 1.2026335681296339e-06 loss: 0.0253 (0.0290) time: 3.0019 data: 0.0083 max mem: 33408 +Epoch: [39] [ 970/2639] eta: 1:24:17 lr: 1.196181283050863e-06 loss: 0.0253 (0.0290) time: 3.0398 data: 0.0086 max mem: 33408 +Epoch: [39] [ 980/2639] eta: 1:23:46 lr: 1.1897251285115254e-06 loss: 0.0253 (0.0289) time: 3.0185 data: 0.0083 max mem: 33408 +Epoch: [39] [ 990/2639] eta: 1:23:14 lr: 1.1832650788316482e-06 loss: 0.0261 (0.0291) time: 2.9516 data: 0.0083 max mem: 33408 +Epoch: [39] [1000/2639] eta: 1:22:44 lr: 1.176801108003891e-06 loss: 0.0265 (0.0291) time: 2.9829 data: 0.0081 max mem: 33408 +Epoch: [39] [1010/2639] eta: 1:22:14 lr: 1.1703331896874073e-06 loss: 0.0283 (0.0291) time: 3.0406 data: 0.0083 max mem: 33408 +Epoch: [39] [1020/2639] eta: 1:21:44 lr: 1.1638612972014334e-06 loss: 0.0270 (0.0290) time: 3.0485 data: 0.0084 max mem: 33408 +Epoch: [39] [1030/2639] eta: 1:21:13 lr: 1.1573854035188323e-06 loss: 0.0254 (0.0291) time: 3.0107 data: 0.0081 max mem: 33408 +Epoch: [39] [1040/2639] eta: 1:20:43 lr: 1.1509054812593544e-06 loss: 0.0301 (0.0291) time: 3.0267 data: 0.0080 max mem: 33408 +Epoch: [39] [1050/2639] eta: 1:20:12 lr: 1.144421502682845e-06 loss: 0.0313 (0.0291) time: 3.0428 data: 0.0080 max mem: 33408 +Epoch: [39] [1060/2639] eta: 1:19:42 lr: 1.1379334396821557e-06 loss: 0.0306 (0.0291) time: 3.0205 data: 0.0079 max mem: 33408 +Epoch: [39] [1070/2639] eta: 1:19:11 lr: 1.131441263775993e-06 loss: 0.0286 (0.0291) time: 3.0122 data: 0.0083 max mem: 33408 +Epoch: [39] [1080/2639] eta: 1:18:42 lr: 1.1249449461014583e-06 loss: 0.0260 (0.0291) time: 3.0392 data: 0.0086 max mem: 33408 +Epoch: [39] [1090/2639] eta: 1:18:12 lr: 1.1184444574065123e-06 loss: 0.0263 (0.0291) time: 3.0607 data: 0.0079 max mem: 33408 +Epoch: [39] [1100/2639] eta: 1:17:41 lr: 1.1119397680421193e-06 loss: 0.0281 (0.0291) time: 3.0187 data: 0.0074 max mem: 33408 +Epoch: [39] [1110/2639] eta: 1:17:11 lr: 1.1054308479542957e-06 loss: 0.0281 (0.0291) time: 3.0374 data: 0.0078 max mem: 33408 +Epoch: [39] [1120/2639] eta: 1:16:40 lr: 1.0989176666758682e-06 loss: 0.0262 (0.0291) time: 3.0241 data: 0.0080 max mem: 33408 +Epoch: [39] [1130/2639] eta: 1:16:10 lr: 1.0924001933180108e-06 loss: 0.0248 (0.0291) time: 3.0062 data: 0.0078 max mem: 33408 +Epoch: [39] [1140/2639] eta: 1:15:40 lr: 1.0858783965616259e-06 loss: 0.0276 (0.0291) time: 3.0490 data: 0.0080 max mem: 33408 +Epoch: [39] [1150/2639] eta: 1:15:10 lr: 1.0793522446483766e-06 loss: 0.0255 (0.0290) time: 3.0437 data: 0.0085 max mem: 33408 +Epoch: [39] [1160/2639] eta: 1:14:41 lr: 1.0728217053715944e-06 loss: 0.0255 (0.0290) time: 3.0728 data: 0.0084 max mem: 33408 +Epoch: [39] [1170/2639] eta: 1:14:10 lr: 1.0662867460668094e-06 loss: 0.0249 (0.0290) time: 3.0557 data: 0.0079 max mem: 33408 +Epoch: [39] [1180/2639] eta: 1:13:39 lr: 1.059747333602142e-06 loss: 0.0292 (0.0290) time: 2.9670 data: 0.0081 max mem: 33408 +Epoch: [39] [1190/2639] eta: 1:13:09 lr: 1.0532034343682991e-06 loss: 0.0292 (0.0290) time: 3.0029 data: 0.0083 max mem: 33408 +Epoch: [39] [1200/2639] eta: 1:12:38 lr: 1.0466550142684107e-06 loss: 0.0264 (0.0290) time: 3.0298 data: 0.0086 max mem: 33408 +Epoch: [39] [1210/2639] eta: 1:12:07 lr: 1.0401020387074538e-06 loss: 0.0295 (0.0290) time: 2.9646 data: 0.0088 max mem: 33408 +Epoch: [39] [1220/2639] eta: 1:11:37 lr: 1.0335444725814952e-06 loss: 0.0295 (0.0290) time: 2.9913 data: 0.0078 max mem: 33408 +Epoch: [39] [1230/2639] eta: 1:11:07 lr: 1.0269822802665007e-06 loss: 0.0296 (0.0291) time: 3.0832 data: 0.0074 max mem: 33408 +Epoch: [39] [1240/2639] eta: 1:10:37 lr: 1.0204154256069393e-06 loss: 0.0296 (0.0291) time: 3.0532 data: 0.0079 max mem: 33408 +Epoch: [39] [1250/2639] eta: 1:10:07 lr: 1.0138438719039344e-06 loss: 0.0275 (0.0291) time: 3.0237 data: 0.0082 max mem: 33408 +Epoch: [39] [1260/2639] eta: 1:09:36 lr: 1.007267581903182e-06 loss: 0.0269 (0.0291) time: 3.0421 data: 0.0079 max mem: 33408 +Epoch: [39] [1270/2639] eta: 1:09:06 lr: 1.0006865177823913e-06 loss: 0.0286 (0.0291) time: 3.0297 data: 0.0080 max mem: 33408 +Epoch: [39] [1280/2639] eta: 1:08:37 lr: 9.941006411384698e-07 loss: 0.0282 (0.0291) time: 3.0637 data: 0.0087 max mem: 33408 +Epoch: [39] [1290/2639] eta: 1:08:06 lr: 9.875099129741968e-07 loss: 0.0278 (0.0291) time: 3.0600 data: 0.0087 max mem: 33408 +Epoch: [39] [1300/2639] eta: 1:07:35 lr: 9.809142936846176e-07 loss: 0.0289 (0.0291) time: 2.9864 data: 0.0081 max mem: 33408 +Epoch: [39] [1310/2639] eta: 1:07:04 lr: 9.743137430428951e-07 loss: 0.0269 (0.0291) time: 2.9500 data: 0.0080 max mem: 33408 +Epoch: [39] [1320/2639] eta: 1:06:33 lr: 9.677082201858486e-07 loss: 0.0257 (0.0291) time: 2.9685 data: 0.0081 max mem: 33408 +Epoch: [39] [1330/2639] eta: 1:06:03 lr: 9.610976835989181e-07 loss: 0.0284 (0.0291) time: 2.9892 data: 0.0078 max mem: 33408 +Epoch: [39] [1340/2639] eta: 1:05:33 lr: 9.544820911007832e-07 loss: 0.0307 (0.0292) time: 3.0203 data: 0.0075 max mem: 33408 +Epoch: [39] [1350/2639] eta: 1:05:02 lr: 9.478613998273692e-07 loss: 0.0298 (0.0292) time: 3.0298 data: 0.0077 max mem: 33408 +Epoch: [39] [1360/2639] eta: 1:04:32 lr: 9.412355662154615e-07 loss: 0.0259 (0.0292) time: 3.0525 data: 0.0082 max mem: 33408 +Epoch: [39] [1370/2639] eta: 1:04:02 lr: 9.346045459857169e-07 loss: 0.0274 (0.0292) time: 3.0307 data: 0.0086 max mem: 33408 +Epoch: [39] [1380/2639] eta: 1:03:32 lr: 9.279682941251244e-07 loss: 0.0274 (0.0292) time: 3.0106 data: 0.0087 max mem: 33408 +Epoch: [39] [1390/2639] eta: 1:03:02 lr: 9.213267648689721e-07 loss: 0.0264 (0.0292) time: 3.0594 data: 0.0090 max mem: 33408 +Epoch: [39] [1400/2639] eta: 1:02:31 lr: 9.146799116821058e-07 loss: 0.0264 (0.0292) time: 3.0412 data: 0.0087 max mem: 33408 +Epoch: [39] [1410/2639] eta: 1:02:01 lr: 9.080276872396893e-07 loss: 0.0273 (0.0292) time: 3.0414 data: 0.0082 max mem: 33408 +Epoch: [39] [1420/2639] eta: 1:01:31 lr: 9.013700434071985e-07 loss: 0.0280 (0.0292) time: 3.0442 data: 0.0080 max mem: 33408 +Epoch: [39] [1430/2639] eta: 1:01:01 lr: 8.94706931219867e-07 loss: 0.0267 (0.0292) time: 3.0548 data: 0.0079 max mem: 33408 +Epoch: [39] [1440/2639] eta: 1:00:31 lr: 8.880383008613076e-07 loss: 0.0263 (0.0292) time: 3.0533 data: 0.0079 max mem: 33408 +Epoch: [39] [1450/2639] eta: 1:00:01 lr: 8.81364101641528e-07 loss: 0.0274 (0.0292) time: 3.0331 data: 0.0079 max mem: 33408 +Epoch: [39] [1460/2639] eta: 0:59:30 lr: 8.746842819740607e-07 loss: 0.0288 (0.0292) time: 3.0376 data: 0.0078 max mem: 33408 +Epoch: [39] [1470/2639] eta: 0:59:00 lr: 8.679987893524243e-07 loss: 0.0294 (0.0292) time: 3.0370 data: 0.0078 max mem: 33408 +Epoch: [39] [1480/2639] eta: 0:58:30 lr: 8.613075703256302e-07 loss: 0.0252 (0.0292) time: 3.0646 data: 0.0077 max mem: 33408 +Epoch: [39] [1490/2639] eta: 0:58:00 lr: 8.546105704729485e-07 loss: 0.0271 (0.0292) time: 3.0384 data: 0.0079 max mem: 33408 +Epoch: [39] [1500/2639] eta: 0:57:29 lr: 8.479077343776467e-07 loss: 0.0275 (0.0292) time: 3.0021 data: 0.0080 max mem: 33408 +Epoch: [39] [1510/2639] eta: 0:56:59 lr: 8.411990055999068e-07 loss: 0.0270 (0.0292) time: 3.0302 data: 0.0080 max mem: 33408 +Epoch: [39] [1520/2639] eta: 0:56:29 lr: 8.344843266486317e-07 loss: 0.0244 (0.0292) time: 3.0580 data: 0.0079 max mem: 33408 +Epoch: [39] [1530/2639] eta: 0:55:59 lr: 8.277636389523446e-07 loss: 0.0240 (0.0291) time: 3.0640 data: 0.0082 max mem: 33408 +Epoch: [39] [1540/2639] eta: 0:55:29 lr: 8.210368828288822e-07 loss: 0.0273 (0.0291) time: 3.0649 data: 0.0082 max mem: 33408 +Epoch: [39] [1550/2639] eta: 0:54:59 lr: 8.14303997454085e-07 loss: 0.0298 (0.0291) time: 3.0446 data: 0.0080 max mem: 33408 +Epoch: [39] [1560/2639] eta: 0:54:28 lr: 8.075649208291777e-07 loss: 0.0278 (0.0291) time: 3.0122 data: 0.0077 max mem: 33408 +Epoch: [39] [1570/2639] eta: 0:53:58 lr: 8.008195897470376e-07 loss: 0.0278 (0.0291) time: 2.9837 data: 0.0078 max mem: 33408 +Epoch: [39] [1580/2639] eta: 0:53:28 lr: 7.940679397570379e-07 loss: 0.0312 (0.0292) time: 3.0110 data: 0.0079 max mem: 33408 +Epoch: [39] [1590/2639] eta: 0:52:57 lr: 7.873099051286583e-07 loss: 0.0285 (0.0292) time: 3.0341 data: 0.0076 max mem: 33408 +Epoch: [39] [1600/2639] eta: 0:52:26 lr: 7.805454188135392e-07 loss: 0.0285 (0.0292) time: 2.9871 data: 0.0080 max mem: 33408 +Epoch: [39] [1610/2639] eta: 0:51:56 lr: 7.737744124061614e-07 loss: 0.0289 (0.0292) time: 2.9608 data: 0.0083 max mem: 33408 +Epoch: [39] [1620/2639] eta: 0:51:25 lr: 7.669968161028715e-07 loss: 0.0287 (0.0292) time: 2.9955 data: 0.0083 max mem: 33408 +Epoch: [39] [1630/2639] eta: 0:50:55 lr: 7.602125586592597e-07 loss: 0.0266 (0.0292) time: 3.0053 data: 0.0084 max mem: 33408 +Epoch: [39] [1640/2639] eta: 0:50:24 lr: 7.534215673458819e-07 loss: 0.0284 (0.0292) time: 2.9917 data: 0.0084 max mem: 33408 +Epoch: [39] [1650/2639] eta: 0:49:54 lr: 7.466237679020414e-07 loss: 0.0299 (0.0293) time: 2.9935 data: 0.0082 max mem: 33408 +Epoch: [39] [1660/2639] eta: 0:49:23 lr: 7.398190844877795e-07 loss: 0.0298 (0.0293) time: 2.9662 data: 0.0082 max mem: 33408 +Epoch: [39] [1670/2639] eta: 0:48:52 lr: 7.330074396337245e-07 loss: 0.0285 (0.0293) time: 2.9551 data: 0.0083 max mem: 33408 +Epoch: [39] [1680/2639] eta: 0:48:22 lr: 7.261887541889441e-07 loss: 0.0258 (0.0293) time: 2.9842 data: 0.0085 max mem: 33408 +Epoch: [39] [1690/2639] eta: 0:47:52 lr: 7.193629472664343e-07 loss: 0.0294 (0.0293) time: 3.0325 data: 0.0084 max mem: 33408 +Epoch: [39] [1700/2639] eta: 0:47:21 lr: 7.1252993618638e-07 loss: 0.0284 (0.0293) time: 3.0190 data: 0.0079 max mem: 33408 +Epoch: [39] [1710/2639] eta: 0:46:51 lr: 7.056896364168037e-07 loss: 0.0260 (0.0293) time: 2.9907 data: 0.0081 max mem: 33408 +Epoch: [39] [1720/2639] eta: 0:46:21 lr: 6.988419615117211e-07 loss: 0.0296 (0.0293) time: 3.0210 data: 0.0084 max mem: 33408 +Epoch: [39] [1730/2639] eta: 0:45:51 lr: 6.919868230464006e-07 loss: 0.0282 (0.0293) time: 3.0462 data: 0.0082 max mem: 33408 +Epoch: [39] [1740/2639] eta: 0:45:20 lr: 6.851241305498308e-07 loss: 0.0239 (0.0292) time: 3.0201 data: 0.0078 max mem: 33408 +Epoch: [39] [1750/2639] eta: 0:44:50 lr: 6.782537914339695e-07 loss: 0.0252 (0.0292) time: 2.9968 data: 0.0075 max mem: 33408 +Epoch: [39] [1760/2639] eta: 0:44:20 lr: 6.713757109198568e-07 loss: 0.0288 (0.0292) time: 3.0423 data: 0.0077 max mem: 33408 +Epoch: [39] [1770/2639] eta: 0:43:50 lr: 6.644897919601425e-07 loss: 0.0290 (0.0292) time: 3.0432 data: 0.0079 max mem: 33408 +Epoch: [39] [1780/2639] eta: 0:43:19 lr: 6.575959351580849e-07 loss: 0.0284 (0.0292) time: 2.9936 data: 0.0084 max mem: 33408 +Epoch: [39] [1790/2639] eta: 0:42:49 lr: 6.506940386825428e-07 loss: 0.0299 (0.0292) time: 3.0154 data: 0.0087 max mem: 33408 +Epoch: [39] [1800/2639] eta: 0:42:18 lr: 6.437839981789882e-07 loss: 0.0320 (0.0293) time: 3.0206 data: 0.0087 max mem: 33408 +Epoch: [39] [1810/2639] eta: 0:41:48 lr: 6.368657066760285e-07 loss: 0.0295 (0.0293) time: 3.0291 data: 0.0088 max mem: 33408 +Epoch: [39] [1820/2639] eta: 0:41:18 lr: 6.299390544874298e-07 loss: 0.0271 (0.0293) time: 3.0248 data: 0.0084 max mem: 33408 +Epoch: [39] [1830/2639] eta: 0:40:47 lr: 6.230039291090929e-07 loss: 0.0255 (0.0292) time: 2.9772 data: 0.0083 max mem: 33408 +Epoch: [39] [1840/2639] eta: 0:40:17 lr: 6.160602151109309e-07 loss: 0.0257 (0.0293) time: 2.9602 data: 0.0084 max mem: 33408 +Epoch: [39] [1850/2639] eta: 0:39:46 lr: 6.091077940230542e-07 loss: 0.0261 (0.0293) time: 2.9623 data: 0.0083 max mem: 33408 +Epoch: [39] [1860/2639] eta: 0:39:16 lr: 6.02146544216154e-07 loss: 0.0261 (0.0292) time: 3.0061 data: 0.0081 max mem: 33408 +Epoch: [39] [1870/2639] eta: 0:38:46 lr: 5.951763407754933e-07 loss: 0.0266 (0.0293) time: 3.0461 data: 0.0081 max mem: 33408 +Epoch: [39] [1880/2639] eta: 0:38:16 lr: 5.881970553681669e-07 loss: 0.0263 (0.0293) time: 3.0765 data: 0.0083 max mem: 33408 +Epoch: [39] [1890/2639] eta: 0:37:46 lr: 5.812085561032592e-07 loss: 0.0235 (0.0292) time: 3.0594 data: 0.0083 max mem: 33408 +Epoch: [39] [1900/2639] eta: 0:37:15 lr: 5.742107073842028e-07 loss: 0.0239 (0.0292) time: 3.0194 data: 0.0084 max mem: 33408 +Epoch: [39] [1910/2639] eta: 0:36:45 lr: 5.672033697530656e-07 loss: 0.0263 (0.0292) time: 3.0401 data: 0.0081 max mem: 33408 +Epoch: [39] [1920/2639] eta: 0:36:15 lr: 5.601863997259244e-07 loss: 0.0260 (0.0292) time: 3.0384 data: 0.0077 max mem: 33408 +Epoch: [39] [1930/2639] eta: 0:35:45 lr: 5.531596496189649e-07 loss: 0.0279 (0.0292) time: 3.0618 data: 0.0078 max mem: 33408 +Epoch: [39] [1940/2639] eta: 0:35:15 lr: 5.461229673643678e-07 loss: 0.0286 (0.0292) time: 3.0612 data: 0.0082 max mem: 33408 +Epoch: [39] [1950/2639] eta: 0:34:45 lr: 5.390761963155063e-07 loss: 0.0277 (0.0292) time: 3.0383 data: 0.0085 max mem: 33408 +Epoch: [39] [1960/2639] eta: 0:34:15 lr: 5.320191750403883e-07 loss: 0.0269 (0.0292) time: 3.0589 data: 0.0083 max mem: 33408 +Epoch: [39] [1970/2639] eta: 0:33:44 lr: 5.249517371027315e-07 loss: 0.0277 (0.0292) time: 3.0055 data: 0.0077 max mem: 33408 +Epoch: [39] [1980/2639] eta: 0:33:14 lr: 5.17873710829455e-07 loss: 0.0266 (0.0292) time: 2.9698 data: 0.0074 max mem: 33408 +Epoch: [39] [1990/2639] eta: 0:32:43 lr: 5.107849190638034e-07 loss: 0.0255 (0.0292) time: 2.9946 data: 0.0075 max mem: 33408 +Epoch: [39] [2000/2639] eta: 0:32:13 lr: 5.036851789027012e-07 loss: 0.0278 (0.0292) time: 3.0592 data: 0.0075 max mem: 33408 +Epoch: [39] [2010/2639] eta: 0:31:43 lr: 4.96574301417348e-07 loss: 0.0280 (0.0292) time: 3.0691 data: 0.0079 max mem: 33408 +Epoch: [39] [2020/2639] eta: 0:31:13 lr: 4.894520913554173e-07 loss: 0.0262 (0.0292) time: 3.0484 data: 0.0082 max mem: 33408 +Epoch: [39] [2030/2639] eta: 0:30:43 lr: 4.823183468236159e-07 loss: 0.0266 (0.0292) time: 3.0696 data: 0.0077 max mem: 33408 +Epoch: [39] [2040/2639] eta: 0:30:12 lr: 4.751728589486756e-07 loss: 0.0264 (0.0292) time: 3.0261 data: 0.0076 max mem: 33408 +Epoch: [39] [2050/2639] eta: 0:29:42 lr: 4.680154115152184e-07 loss: 0.0256 (0.0292) time: 3.0072 data: 0.0076 max mem: 33408 +Epoch: [39] [2060/2639] eta: 0:29:12 lr: 4.608457805782017e-07 loss: 0.0282 (0.0292) time: 3.0551 data: 0.0077 max mem: 33408 +Epoch: [39] [2070/2639] eta: 0:28:42 lr: 4.536637340479835e-07 loss: 0.0273 (0.0292) time: 3.0338 data: 0.0081 max mem: 33408 +Epoch: [39] [2080/2639] eta: 0:28:11 lr: 4.4646903124526287e-07 loss: 0.0248 (0.0291) time: 2.9909 data: 0.0081 max mem: 33408 +Epoch: [39] [2090/2639] eta: 0:27:41 lr: 4.3926142242342023e-07 loss: 0.0260 (0.0291) time: 2.9940 data: 0.0078 max mem: 33408 +Epoch: [39] [2100/2639] eta: 0:27:11 lr: 4.320406482549395e-07 loss: 0.0276 (0.0291) time: 3.0168 data: 0.0077 max mem: 33408 +Epoch: [39] [2110/2639] eta: 0:26:41 lr: 4.2480643927877586e-07 loss: 0.0290 (0.0292) time: 3.0525 data: 0.0079 max mem: 33408 +Epoch: [39] [2120/2639] eta: 0:26:10 lr: 4.175585153046684e-07 loss: 0.0280 (0.0292) time: 3.0476 data: 0.0080 max mem: 33408 +Epoch: [39] [2130/2639] eta: 0:25:40 lr: 4.102965847702475e-07 loss: 0.0255 (0.0291) time: 3.0410 data: 0.0079 max mem: 33408 +Epoch: [39] [2140/2639] eta: 0:25:10 lr: 4.0302034404627457e-07 loss: 0.0254 (0.0291) time: 3.0335 data: 0.0080 max mem: 33408 +Epoch: [39] [2150/2639] eta: 0:24:39 lr: 3.95729476684475e-07 loss: 0.0264 (0.0291) time: 3.0144 data: 0.0081 max mem: 33408 +Epoch: [39] [2160/2639] eta: 0:24:09 lr: 3.8842365260223343e-07 loss: 0.0278 (0.0291) time: 3.0330 data: 0.0079 max mem: 33408 +Epoch: [39] [2170/2639] eta: 0:23:39 lr: 3.811025271971174e-07 loss: 0.0274 (0.0291) time: 3.0084 data: 0.0076 max mem: 33408 +Epoch: [39] [2180/2639] eta: 0:23:09 lr: 3.737657403838596e-07 loss: 0.0271 (0.0291) time: 2.9740 data: 0.0076 max mem: 33408 +Epoch: [39] [2190/2639] eta: 0:22:38 lr: 3.6641291554486204e-07 loss: 0.0267 (0.0291) time: 2.9856 data: 0.0078 max mem: 33408 +Epoch: [39] [2200/2639] eta: 0:22:08 lr: 3.590436583846511e-07 loss: 0.0265 (0.0291) time: 3.0479 data: 0.0078 max mem: 33408 +Epoch: [39] [2210/2639] eta: 0:21:38 lr: 3.516575556767922e-07 loss: 0.0241 (0.0291) time: 3.0436 data: 0.0080 max mem: 33408 +Epoch: [39] [2220/2639] eta: 0:21:07 lr: 3.442541738907181e-07 loss: 0.0241 (0.0291) time: 2.9713 data: 0.0081 max mem: 33408 +Epoch: [39] [2230/2639] eta: 0:20:37 lr: 3.3683305768350376e-07 loss: 0.0254 (0.0291) time: 3.0135 data: 0.0080 max mem: 33408 +Epoch: [39] [2240/2639] eta: 0:20:07 lr: 3.2939372823996685e-07 loss: 0.0288 (0.0291) time: 3.0432 data: 0.0079 max mem: 33408 +Epoch: [39] [2250/2639] eta: 0:19:37 lr: 3.219356814413302e-07 loss: 0.0288 (0.0291) time: 3.0137 data: 0.0077 max mem: 33408 +Epoch: [39] [2260/2639] eta: 0:19:06 lr: 3.1445838584016387e-07 loss: 0.0258 (0.0291) time: 2.9972 data: 0.0080 max mem: 33408 +Epoch: [39] [2270/2639] eta: 0:18:36 lr: 3.06961280415122e-07 loss: 0.0258 (0.0291) time: 3.0433 data: 0.0080 max mem: 33408 +Epoch: [39] [2280/2639] eta: 0:18:06 lr: 2.9944377207519256e-07 loss: 0.0267 (0.0291) time: 3.0581 data: 0.0080 max mem: 33408 +Epoch: [39] [2290/2639] eta: 0:17:36 lr: 2.9190523287740245e-07 loss: 0.0262 (0.0291) time: 2.9978 data: 0.0083 max mem: 33408 +Epoch: [39] [2300/2639] eta: 0:17:05 lr: 2.8434499691619174e-07 loss: 0.0262 (0.0291) time: 2.9878 data: 0.0079 max mem: 33408 +Epoch: [39] [2310/2639] eta: 0:16:35 lr: 2.7676235683450313e-07 loss: 0.0260 (0.0291) time: 3.0157 data: 0.0079 max mem: 33408 +Epoch: [39] [2320/2639] eta: 0:16:05 lr: 2.691565598979306e-07 loss: 0.0254 (0.0291) time: 3.0111 data: 0.0080 max mem: 33408 +Epoch: [39] [2330/2639] eta: 0:15:34 lr: 2.6152680356137467e-07 loss: 0.0277 (0.0291) time: 3.0023 data: 0.0077 max mem: 33408 +Epoch: [39] [2340/2639] eta: 0:15:04 lr: 2.538722304442624e-07 loss: 0.0268 (0.0291) time: 3.0305 data: 0.0076 max mem: 33408 +Epoch: [39] [2350/2639] eta: 0:14:34 lr: 2.4619192261253055e-07 loss: 0.0259 (0.0291) time: 3.0270 data: 0.0078 max mem: 33408 +Epoch: [39] [2360/2639] eta: 0:14:04 lr: 2.3848489504456857e-07 loss: 0.0274 (0.0291) time: 2.9994 data: 0.0084 max mem: 33408 +Epoch: [39] [2370/2639] eta: 0:13:33 lr: 2.307500881307244e-07 loss: 0.0325 (0.0291) time: 3.0177 data: 0.0088 max mem: 33408 +Epoch: [39] [2380/2639] eta: 0:13:03 lr: 2.2298635902199563e-07 loss: 0.0301 (0.0291) time: 3.0243 data: 0.0083 max mem: 33408 +Epoch: [39] [2390/2639] eta: 0:12:33 lr: 2.1519247159976585e-07 loss: 0.0270 (0.0291) time: 3.0157 data: 0.0078 max mem: 33408 +Epoch: [39] [2400/2639] eta: 0:12:03 lr: 2.0736708478178274e-07 loss: 0.0278 (0.0291) time: 3.0707 data: 0.0077 max mem: 33408 +Epoch: [39] [2410/2639] eta: 0:11:32 lr: 1.995087388068646e-07 loss: 0.0256 (0.0291) time: 3.0920 data: 0.0078 max mem: 33408 +Epoch: [39] [2420/2639] eta: 0:11:02 lr: 1.9161583904412294e-07 loss: 0.0256 (0.0291) time: 3.0311 data: 0.0080 max mem: 33408 +Epoch: [39] [2430/2639] eta: 0:10:32 lr: 1.8368663674550398e-07 loss: 0.0262 (0.0290) time: 2.9589 data: 0.0085 max mem: 33408 +Epoch: [39] [2440/2639] eta: 0:10:02 lr: 1.7571920598852315e-07 loss: 0.0248 (0.0290) time: 2.9995 data: 0.0083 max mem: 33408 +Epoch: [39] [2450/2639] eta: 0:09:31 lr: 1.6771141582355341e-07 loss: 0.0248 (0.0290) time: 3.0426 data: 0.0083 max mem: 33408 +Epoch: [39] [2460/2639] eta: 0:09:01 lr: 1.5966089631778305e-07 loss: 0.0254 (0.0290) time: 3.0188 data: 0.0088 max mem: 33408 +Epoch: [39] [2470/2639] eta: 0:08:31 lr: 1.5156499673780186e-07 loss: 0.0283 (0.0290) time: 3.0195 data: 0.0081 max mem: 33408 +Epoch: [39] [2480/2639] eta: 0:08:01 lr: 1.4342073346962213e-07 loss: 0.0287 (0.0290) time: 3.0156 data: 0.0075 max mem: 33408 +Epoch: [39] [2490/2639] eta: 0:07:30 lr: 1.3522472434208778e-07 loss: 0.0276 (0.0290) time: 3.0476 data: 0.0073 max mem: 33408 +Epoch: [39] [2500/2639] eta: 0:07:00 lr: 1.269731046340577e-07 loss: 0.0267 (0.0290) time: 3.0256 data: 0.0074 max mem: 33408 +Epoch: [39] [2510/2639] eta: 0:06:30 lr: 1.1866141794230447e-07 loss: 0.0283 (0.0290) time: 3.0186 data: 0.0079 max mem: 33408 +Epoch: [39] [2520/2639] eta: 0:06:00 lr: 1.1028447180330967e-07 loss: 0.0289 (0.0290) time: 3.0456 data: 0.0083 max mem: 33408 +Epoch: [39] [2530/2639] eta: 0:05:29 lr: 1.0183614268114759e-07 loss: 0.0257 (0.0290) time: 3.0085 data: 0.0087 max mem: 33408 +Epoch: [39] [2540/2639] eta: 0:04:59 lr: 9.330910613295523e-08 loss: 0.0257 (0.0290) time: 2.9854 data: 0.0088 max mem: 33408 +Epoch: [39] [2550/2639] eta: 0:04:29 lr: 8.46944526897065e-08 loss: 0.0272 (0.0290) time: 3.0054 data: 0.0087 max mem: 33408 +Epoch: [39] [2560/2639] eta: 0:03:59 lr: 7.59811221657123e-08 loss: 0.0287 (0.0290) time: 3.0771 data: 0.0082 max mem: 33408 +Epoch: [39] [2570/2639] eta: 0:03:28 lr: 6.715503540092055e-08 loss: 0.0287 (0.0290) time: 3.0595 data: 0.0079 max mem: 33408 +Epoch: [39] [2580/2639] eta: 0:02:58 lr: 5.8197691112651246e-08 loss: 0.0274 (0.0290) time: 2.9960 data: 0.0081 max mem: 33408 +Epoch: [39] [2590/2639] eta: 0:02:28 lr: 4.908374312237755e-08 loss: 0.0278 (0.0290) time: 3.0112 data: 0.0079 max mem: 33408 +Epoch: [39] [2600/2639] eta: 0:01:58 lr: 3.9776429634041595e-08 loss: 0.0299 (0.0290) time: 3.0563 data: 0.0076 max mem: 33408 +Epoch: [39] [2610/2639] eta: 0:01:27 lr: 3.0217796291920384e-08 loss: 0.0252 (0.0290) time: 3.0627 data: 0.0081 max mem: 33408 +Epoch: [39] [2620/2639] eta: 0:00:57 lr: 2.0303261840977132e-08 loss: 0.0249 (0.0290) time: 3.0523 data: 0.0084 max mem: 33408 +Epoch: [39] [2630/2639] eta: 0:00:27 lr: 9.785917479894317e-09 loss: 0.0265 (0.0290) time: 3.0265 data: 0.0078 max mem: 33408 +Epoch: [39] Total time: 2:13:06 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 2:05:50 time: 2.9345 data: 2.7887 max mem: 33408 +Test: [ 100/2573] eta: 0:04:24 time: 0.0789 data: 0.0015 max mem: 33408 +Test: [ 200/2573] eta: 0:03:43 time: 0.0803 data: 0.0014 max mem: 33408 +Test: [ 300/2573] eta: 0:03:22 time: 0.0817 data: 0.0014 max mem: 33408 +Test: [ 400/2573] eta: 0:03:09 time: 0.0823 data: 0.0014 max mem: 33408 +Test: [ 500/2573] eta: 0:02:58 time: 0.0819 data: 0.0015 max mem: 33408 +Test: [ 600/2573] eta: 0:02:48 time: 0.0824 data: 0.0014 max mem: 33408 +Test: [ 700/2573] eta: 0:02:39 time: 0.0822 data: 0.0014 max mem: 33408 +Test: [ 800/2573] eta: 0:02:30 time: 0.0853 data: 0.0013 max mem: 33408 +Test: [ 900/2573] eta: 0:02:21 time: 0.0813 data: 0.0013 max mem: 33408 +Test: [1000/2573] eta: 0:02:13 time: 0.0825 data: 0.0014 max mem: 33408 +Test: [1100/2573] eta: 0:02:04 time: 0.0834 data: 0.0016 max mem: 33408 +Test: [1200/2573] eta: 0:01:55 time: 0.0822 data: 0.0015 max mem: 33408 +Test: [1300/2573] eta: 0:01:47 time: 0.0813 data: 0.0015 max mem: 33408 +Test: [1400/2573] eta: 0:01:38 time: 0.0797 data: 0.0014 max mem: 33408 +Test: [1500/2573] eta: 0:01:29 time: 0.0814 data: 0.0015 max mem: 33408 +Test: [1600/2573] eta: 0:01:21 time: 0.0850 data: 0.0015 max mem: 33408 +Test: [1700/2573] eta: 0:01:12 time: 0.0802 data: 0.0014 max mem: 33408 +Test: [1800/2573] eta: 0:01:04 time: 0.0834 data: 0.0015 max mem: 33408 +Test: [1900/2573] eta: 0:00:56 time: 0.0793 data: 0.0015 max mem: 33408 +Test: [2000/2573] eta: 0:00:47 time: 0.0813 data: 0.0015 max mem: 33408 +Test: [2100/2573] eta: 0:00:39 time: 0.0832 data: 0.0014 max mem: 33408 +Test: [2200/2573] eta: 0:00:30 time: 0.0828 data: 0.0014 max mem: 33408 +Test: [2300/2573] eta: 0:00:22 time: 0.0826 data: 0.0014 max mem: 33408 +Test: [2400/2573] eta: 0:00:14 time: 0.0777 data: 0.0014 max mem: 33408 +Test: [2500/2573] eta: 0:00:06 time: 0.0814 data: 0.0015 max mem: 33408 +Test: Total time: 0:03:33 +Final results: +Mean IoU is 65.41 + + precision@0.5 = 73.86 + precision@0.6 = 68.83 + precision@0.7 = 61.60 + precision@0.8 = 51.33 + precision@0.9 = 25.57 + overall IoU = 62.80 + +Average object IoU 65.41126966324683 +Overall IoU 62.79727554321289 +Training time 3 days, 19:09:38 diff --git a/LAVT-RIS/logs/old/gref_m10_mg10_tmp010_4gpu_bs32_ang.log b/LAVT-RIS/logs/old/gref_m10_mg10_tmp010_4gpu_bs32_ang.log new file mode 100644 index 0000000000000000000000000000000000000000..c3317ac95bdf6fdaacbe18389228aabb0ec190fa --- /dev/null +++ b/LAVT-RIS/logs/old/gref_m10_mg10_tmp010_4gpu_bs32_ang.log @@ -0,0 +1,12095 @@ +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torch/distributed/launch.py:178: FutureWarning: The module torch.distributed.launch is deprecated +and will be removed in future. Use torchrun. +Note that --use_env is set by default in torchrun. +If your script expects `--local_rank` argument to be set, please +change it to read from `os.environ['LOCAL_RANK']` instead. See +https://pytorch.org/docs/stable/distributed.html#launch-utility for +further instructions + + warnings.warn( +WARNING:torch.distributed.run: +***************************************** +Setting OMP_NUM_THREADS environment variable for each process to be 1 in default, to avoid your system being overloaded, please further tune the variable for optimal performance in your application as needed. +***************************************** +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/timm/models/layers/__init__.py:48: FutureWarning: Importing from timm.models.layers is deprecated, please import via timm.layers + warnings.warn(f"Importing from {__name__} is deprecated, please import via timm.layers", FutureWarning) +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/timm/models/layers/__init__.py:48: FutureWarning: Importing from timm.models.layers is deprecated, please import via timm.layers + warnings.warn(f"Importing from {__name__} is deprecated, please import via timm.layers", FutureWarning) +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/timm/models/layers/__init__.py:48: FutureWarning: Importing from timm.models.layers is deprecated, please import via timm.layers + warnings.warn(f"Importing from {__name__} is deprecated, please import via timm.layers", FutureWarning) +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/timm/models/layers/__init__.py:48: FutureWarning: Importing from timm.models.layers is deprecated, please import via timm.layers + warnings.warn(f"Importing from {__name__} is deprecated, please import via timm.layers", FutureWarning) +RANK and WORLD_SIZE in environment: 2/4RANK and WORLD_SIZE in environment: 1/4 + +RANK and WORLD_SIZE in environment: 3/4 +RANK and WORLD_SIZE in environment: 0/4 +Image size: 480 +loading dataset refcocog into memory... +creating index... +index created. +DONE (t=5.40s) +loading dataset refcocog into memory... +creating index... +index created. +DONE (t=5.21s) +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torch/functional.py:478: UserWarning: torch.meshgrid: in an upcoming release, it will be required to pass the indexing argument. (Triggered internally at ../aten/src/ATen/native/TensorShape.cpp:2894.) + return _VF.meshgrid(tensors, **kwargs) # type: ignore[attr-defined] +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torch/functional.py:478: UserWarning: torch.meshgrid: in an upcoming release, it will be required to pass the indexing argument. (Triggered internally at ../aten/src/ATen/native/TensorShape.cpp:2894.) + return _VF.meshgrid(tensors, **kwargs) # type: ignore[attr-defined] +local rank 0 / global rank 0 successfully built train dataset. +lavt_one +Window size 12! +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torch/functional.py:478: UserWarning: torch.meshgrid: in an upcoming release, it will be required to pass the indexing argument. (Triggered internally at ../aten/src/ATen/native/TensorShape.cpp:2894.) + return _VF.meshgrid(tensors, **kwargs) # type: ignore[attr-defined] +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torch/functional.py:478: UserWarning: torch.meshgrid: in an upcoming release, it will be required to pass the indexing argument. (Triggered internally at ../aten/src/ATen/native/TensorShape.cpp:2894.) + return _VF.meshgrid(tensors, **kwargs) # type: ignore[attr-defined] +Initializing Multi-modal Swin Transformer weights from ./pretrained_weights/swin_base_patch4_window12_384_22k.pth +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [0] [ 0/1319] eta: 2:56:57 lr: 4.9999147080313756e-05 loss: 0.6045 (0.6045) time: 8.0493 data: 2.7042 max mem: 20156 +Epoch: [0] [ 10/1319] eta: 1:07:34 lr: 4.999061779453083e-05 loss: 0.3795 (0.4112) time: 3.0977 data: 0.2528 max mem: 28288 +Epoch: [0] [ 20/1319] eta: 1:01:55 lr: 4.9982088347050674e-05 loss: 0.3398 (0.3693) time: 2.6004 data: 0.0065 max mem: 28288 +Epoch: [0] [ 30/1319] eta: 1:00:08 lr: 4.9973558737839576e-05 loss: 0.2939 (0.3487) time: 2.6360 data: 0.0057 max mem: 28288 +Epoch: [0] [ 40/1319] eta: 0:58:52 lr: 4.9965028966863786e-05 loss: 0.2871 (0.3336) time: 2.6586 data: 0.0060 max mem: 28288 +Epoch: [0] [ 50/1319] eta: 0:57:56 lr: 4.995649903408956e-05 loss: 0.2776 (0.3270) time: 2.6459 data: 0.0060 max mem: 28288 +Epoch: [0] [ 60/1319] eta: 0:56:57 lr: 4.9947968939483133e-05 loss: 0.2879 (0.3283) time: 2.6178 data: 0.0061 max mem: 28288 +Epoch: [0] [ 70/1319] eta: 0:56:10 lr: 4.993943868301072e-05 loss: 0.2906 (0.3218) time: 2.5951 data: 0.0062 max mem: 28288 +Epoch: [0] [ 80/1319] eta: 0:55:25 lr: 4.993090826463852e-05 loss: 0.2606 (0.3142) time: 2.5925 data: 0.0060 max mem: 28288 +Epoch: [0] [ 90/1319] eta: 0:54:53 lr: 4.9922377684332736e-05 loss: 0.2563 (0.3092) time: 2.6111 data: 0.0058 max mem: 28288 +Epoch: [0] [ 100/1319] eta: 0:54:16 lr: 4.991384694205954e-05 loss: 0.2405 (0.3041) time: 2.6197 data: 0.0059 max mem: 28288 +Epoch: [0] [ 110/1319] eta: 0:53:46 lr: 4.990531603778512e-05 loss: 0.2742 (0.3047) time: 2.6195 data: 0.0059 max mem: 29995 +Epoch: [0] [ 120/1319] eta: 0:53:15 lr: 4.98967849714756e-05 loss: 0.2742 (0.3009) time: 2.6327 data: 0.0059 max mem: 29995 +Epoch: [0] [ 130/1319] eta: 0:52:45 lr: 4.988825374309713e-05 loss: 0.2469 (0.2979) time: 2.6259 data: 0.0060 max mem: 31677 +Epoch: [0] [ 140/1319] eta: 0:52:12 lr: 4.987972235261584e-05 loss: 0.2472 (0.2941) time: 2.6093 data: 0.0062 max mem: 31677 +Epoch: [0] [ 150/1319] eta: 0:51:42 lr: 4.987119079999784e-05 loss: 0.2479 (0.2934) time: 2.6032 data: 0.0060 max mem: 31677 +Epoch: [0] [ 160/1319] eta: 0:51:08 lr: 4.986265908520923e-05 loss: 0.2486 (0.2902) time: 2.5825 data: 0.0060 max mem: 31677 +Epoch: [0] [ 170/1319] eta: 0:50:38 lr: 4.985412720821609e-05 loss: 0.2447 (0.2888) time: 2.5697 data: 0.0061 max mem: 31677 +Epoch: [0] [ 180/1319] eta: 0:50:11 lr: 4.984559516898449e-05 loss: 0.2362 (0.2857) time: 2.6093 data: 0.0059 max mem: 31677 +Epoch: [0] [ 190/1319] eta: 0:49:42 lr: 4.98370629674805e-05 loss: 0.2423 (0.2843) time: 2.6211 data: 0.0059 max mem: 31677 +Epoch: [0] [ 200/1319] eta: 0:49:15 lr: 4.982853060367015e-05 loss: 0.2438 (0.2824) time: 2.6232 data: 0.0058 max mem: 31677 +Epoch: [0] [ 210/1319] eta: 0:48:49 lr: 4.9819998077519475e-05 loss: 0.2374 (0.2813) time: 2.6332 data: 0.0059 max mem: 31677 +Epoch: [0] [ 220/1319] eta: 0:48:21 lr: 4.98114653889945e-05 loss: 0.2246 (0.2787) time: 2.6200 data: 0.0059 max mem: 31677 +Epoch: [0] [ 230/1319] eta: 0:47:54 lr: 4.980293253806122e-05 loss: 0.2271 (0.2773) time: 2.6201 data: 0.0057 max mem: 31677 +Epoch: [0] [ 240/1319] eta: 0:47:22 lr: 4.9794399524685624e-05 loss: 0.2271 (0.2759) time: 2.5810 data: 0.0058 max mem: 31677 +Epoch: [0] [ 250/1319] eta: 0:46:54 lr: 4.97858663488337e-05 loss: 0.2256 (0.2740) time: 2.5630 data: 0.0058 max mem: 31677 +Epoch: [0] [ 260/1319] eta: 0:46:28 lr: 4.977733301047139e-05 loss: 0.2116 (0.2715) time: 2.6143 data: 0.0058 max mem: 33368 +Epoch: [0] [ 270/1319] eta: 0:46:03 lr: 4.9768799509564675e-05 loss: 0.2226 (0.2708) time: 2.6425 data: 0.0058 max mem: 33368 +Epoch: [0] [ 280/1319] eta: 0:45:35 lr: 4.976026584607946e-05 loss: 0.2226 (0.2690) time: 2.6329 data: 0.0058 max mem: 33368 +Epoch: [0] [ 290/1319] eta: 0:45:10 lr: 4.9751732019981684e-05 loss: 0.2219 (0.2687) time: 2.6310 data: 0.0059 max mem: 33368 +Epoch: [0] [ 300/1319] eta: 0:44:44 lr: 4.974319803123725e-05 loss: 0.2458 (0.2687) time: 2.6446 data: 0.0060 max mem: 33368 +Epoch: [0] [ 310/1319] eta: 0:44:18 lr: 4.973466387981205e-05 loss: 0.2354 (0.2689) time: 2.6499 data: 0.0060 max mem: 33368 +Epoch: [0] [ 320/1319] eta: 0:43:52 lr: 4.972612956567197e-05 loss: 0.2354 (0.2682) time: 2.6469 data: 0.0058 max mem: 33368 +Epoch: [0] [ 330/1319] eta: 0:43:24 lr: 4.971759508878288e-05 loss: 0.2180 (0.2673) time: 2.6160 data: 0.0056 max mem: 33368 +Epoch: [0] [ 340/1319] eta: 0:42:57 lr: 4.970906044911062e-05 loss: 0.2247 (0.2671) time: 2.6071 data: 0.0057 max mem: 33368 +Epoch: [0] [ 350/1319] eta: 0:42:31 lr: 4.970052564662105e-05 loss: 0.2346 (0.2658) time: 2.6178 data: 0.0059 max mem: 33368 +Epoch: [0] [ 360/1319] eta: 0:42:04 lr: 4.9691990681279974e-05 loss: 0.2063 (0.2646) time: 2.6125 data: 0.0057 max mem: 33368 +Epoch: [0] [ 370/1319] eta: 0:41:38 lr: 4.9683455553053225e-05 loss: 0.2001 (0.2637) time: 2.6274 data: 0.0056 max mem: 33368 +Epoch: [0] [ 380/1319] eta: 0:41:10 lr: 4.9674920261906595e-05 loss: 0.1990 (0.2624) time: 2.6175 data: 0.0057 max mem: 33368 +Epoch: [0] [ 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2.5871 data: 0.0058 max mem: 33369 +Epoch: [0] [ 710/1319] eta: 0:26:37 lr: 4.939316403135663e-05 loss: 0.2093 (0.2461) time: 2.6120 data: 0.0060 max mem: 33369 +Epoch: [0] [ 720/1319] eta: 0:26:11 lr: 4.938462318048596e-05 loss: 0.2191 (0.2457) time: 2.6186 data: 0.0059 max mem: 33369 +Epoch: [0] [ 730/1319] eta: 0:25:45 lr: 4.937608216548967e-05 loss: 0.1967 (0.2449) time: 2.6446 data: 0.0059 max mem: 33369 +Epoch: [0] [ 740/1319] eta: 0:25:19 lr: 4.936754098633307e-05 loss: 0.1967 (0.2448) time: 2.6274 data: 0.0060 max mem: 33369 +Epoch: [0] [ 750/1319] eta: 0:24:52 lr: 4.935899964298143e-05 loss: 0.2026 (0.2440) time: 2.6192 data: 0.0058 max mem: 33369 +Epoch: [0] [ 760/1319] eta: 0:24:26 lr: 4.9350458135400046e-05 loss: 0.1794 (0.2436) time: 2.6062 data: 0.0057 max mem: 33369 +Epoch: [0] [ 770/1319] eta: 0:24:00 lr: 4.934191646355415e-05 loss: 0.2031 (0.2433) time: 2.5968 data: 0.0056 max mem: 33369 +Epoch: [0] [ 780/1319] eta: 0:23:33 lr: 4.9333374627409e-05 loss: 0.2032 (0.2427) time: 2.6092 data: 0.0056 max mem: 33369 +Epoch: [0] [ 790/1319] eta: 0:23:07 lr: 4.932483262692982e-05 loss: 0.2109 (0.2423) time: 2.6035 data: 0.0057 max mem: 33369 +Epoch: [0] [ 800/1319] eta: 0:22:41 lr: 4.931629046208183e-05 loss: 0.2063 (0.2420) time: 2.6126 data: 0.0059 max mem: 33369 +Epoch: [0] [ 810/1319] eta: 0:22:14 lr: 4.9307748132830237e-05 loss: 0.2031 (0.2418) time: 2.6043 data: 0.0059 max mem: 33369 +Epoch: [0] [ 820/1319] eta: 0:21:48 lr: 4.929920563914022e-05 loss: 0.2080 (0.2415) time: 2.6152 data: 0.0057 max mem: 33369 +Epoch: [0] [ 830/1319] eta: 0:21:22 lr: 4.929066298097696e-05 loss: 0.2025 (0.2412) time: 2.6001 data: 0.0057 max mem: 33369 +Epoch: [0] [ 840/1319] eta: 0:20:55 lr: 4.928212015830561e-05 loss: 0.1909 (0.2406) time: 2.5902 data: 0.0058 max mem: 33369 +Epoch: [0] [ 850/1319] eta: 0:20:29 lr: 4.927357717109131e-05 loss: 0.1828 (0.2404) time: 2.6307 data: 0.0058 max mem: 33369 +Epoch: [0] [ 860/1319] eta: 0:20:03 lr: 4.926503401929921e-05 loss: 0.1895 (0.2401) time: 2.6158 data: 0.0058 max mem: 33369 +Epoch: [0] [ 870/1319] eta: 0:19:37 lr: 4.925649070289441e-05 loss: 0.2215 (0.2399) time: 2.6112 data: 0.0057 max mem: 33369 +Epoch: [0] [ 880/1319] eta: 0:19:10 lr: 4.9247947221842024e-05 loss: 0.2150 (0.2396) time: 2.6238 data: 0.0058 max mem: 33369 +Epoch: [0] [ 890/1319] eta: 0:18:44 lr: 4.923940357610714e-05 loss: 0.1971 (0.2390) time: 2.6222 data: 0.0058 max mem: 33369 +Epoch: [0] [ 900/1319] eta: 0:18:18 lr: 4.9230859765654824e-05 loss: 0.1773 (0.2386) time: 2.6326 data: 0.0060 max mem: 33369 +Epoch: [0] [ 910/1319] eta: 0:17:52 lr: 4.922231579045014e-05 loss: 0.1766 (0.2379) time: 2.6343 data: 0.0060 max mem: 33369 +Epoch: [0] [ 920/1319] eta: 0:17:26 lr: 4.921377165045815e-05 loss: 0.1945 (0.2377) time: 2.6246 data: 0.0058 max mem: 33369 +Epoch: [0] [ 930/1319] eta: 0:16:59 lr: 4.9205227345643864e-05 loss: 0.2049 (0.2375) time: 2.6198 data: 0.0058 max mem: 33369 +Epoch: [0] [ 940/1319] eta: 0:16:33 lr: 4.919668287597232e-05 loss: 0.2090 (0.2377) time: 2.5998 data: 0.0060 max mem: 33369 +Epoch: [0] [ 950/1319] eta: 0:16:07 lr: 4.918813824140851e-05 loss: 0.2090 (0.2374) time: 2.5851 data: 0.0060 max mem: 33369 +Epoch: [0] [ 960/1319] eta: 0:15:41 lr: 4.9179593441917424e-05 loss: 0.2004 (0.2369) time: 2.6065 data: 0.0059 max mem: 33369 +Epoch: [0] [ 970/1319] eta: 0:15:14 lr: 4.917104847746404e-05 loss: 0.1937 (0.2366) time: 2.6139 data: 0.0058 max mem: 33369 +Epoch: [0] [ 980/1319] eta: 0:14:48 lr: 4.916250334801333e-05 loss: 0.1899 (0.2362) time: 2.6065 data: 0.0058 max mem: 33369 +Epoch: [0] [ 990/1319] eta: 0:14:22 lr: 4.915395805353022e-05 loss: 0.1854 (0.2357) time: 2.6205 data: 0.0057 max mem: 33369 +Epoch: [0] [1000/1319] eta: 0:13:56 lr: 4.9145412593979664e-05 loss: 0.1808 (0.2355) time: 2.6339 data: 0.0057 max mem: 33369 +Epoch: [0] [1010/1319] eta: 0:13:29 lr: 4.913686696932656e-05 loss: 0.1966 (0.2353) time: 2.6368 data: 0.0056 max mem: 33369 +Epoch: [0] [1020/1319] eta: 0:13:03 lr: 4.9128321179535836e-05 loss: 0.1817 (0.2347) time: 2.6328 data: 0.0057 max mem: 33369 +Epoch: [0] [1030/1319] eta: 0:12:37 lr: 4.911977522457237e-05 loss: 0.1701 (0.2346) time: 2.6400 data: 0.0058 max mem: 33369 +Epoch: [0] [1040/1319] eta: 0:12:11 lr: 4.9111229104401044e-05 loss: 0.1940 (0.2343) time: 2.6246 data: 0.0058 max mem: 33369 +Epoch: [0] [1050/1319] eta: 0:11:45 lr: 4.910268281898671e-05 loss: 0.1905 (0.2342) time: 2.6003 data: 0.0059 max mem: 33369 +Epoch: [0] [1060/1319] eta: 0:11:18 lr: 4.9094136368294215e-05 loss: 0.2030 (0.2339) time: 2.6009 data: 0.0058 max mem: 33369 +Epoch: [0] [1070/1319] eta: 0:10:52 lr: 4.90855897522884e-05 loss: 0.1926 (0.2337) time: 2.6004 data: 0.0059 max mem: 33369 +Epoch: [0] [1080/1319] eta: 0:10:26 lr: 4.907704297093409e-05 loss: 0.1788 (0.2332) time: 2.5906 data: 0.0059 max mem: 33369 +Epoch: [0] [1090/1319] eta: 0:10:00 lr: 4.906849602419608e-05 loss: 0.1788 (0.2330) time: 2.5952 data: 0.0058 max mem: 33369 +Epoch: [0] [1100/1319] eta: 0:09:33 lr: 4.905994891203916e-05 loss: 0.2048 (0.2328) time: 2.5860 data: 0.0058 max mem: 33369 +Epoch: [0] [1110/1319] eta: 0:09:07 lr: 4.905140163442811e-05 loss: 0.2057 (0.2325) time: 2.5922 data: 0.0059 max mem: 33369 +Epoch: [0] [1120/1319] eta: 0:08:41 lr: 4.904285419132769e-05 loss: 0.2008 (0.2323) time: 2.6166 data: 0.0060 max mem: 33369 +Epoch: [0] [1130/1319] eta: 0:08:15 lr: 4.903430658270266e-05 loss: 0.1927 (0.2320) time: 2.6318 data: 0.0059 max mem: 33369 +Epoch: [0] [1140/1319] eta: 0:07:48 lr: 4.902575880851773e-05 loss: 0.1912 (0.2317) time: 2.6330 data: 0.0057 max mem: 33369 +Epoch: [0] [1150/1319] eta: 0:07:22 lr: 4.9017210868737634e-05 loss: 0.1953 (0.2314) time: 2.6087 data: 0.0058 max mem: 33369 +Epoch: [0] [1160/1319] eta: 0:06:56 lr: 4.900866276332707e-05 loss: 0.1817 (0.2310) time: 2.6245 data: 0.0058 max mem: 33369 +Epoch: [0] [1170/1319] eta: 0:06:30 lr: 4.9000114492250734e-05 loss: 0.1786 (0.2306) time: 2.6368 data: 0.0057 max mem: 33369 +Epoch: [0] [1180/1319] eta: 0:06:04 lr: 4.8991566055473306e-05 loss: 0.1770 (0.2303) time: 2.6237 data: 0.0059 max mem: 33369 +Epoch: [0] [1190/1319] eta: 0:05:37 lr: 4.8983017452959435e-05 loss: 0.1716 (0.2300) time: 2.6107 data: 0.0060 max mem: 33369 +Epoch: [0] [1200/1319] eta: 0:05:11 lr: 4.8974468684673776e-05 loss: 0.1927 (0.2298) time: 2.6090 data: 0.0060 max mem: 33369 +Epoch: [0] [1210/1319] eta: 0:04:45 lr: 4.896591975058095e-05 loss: 0.1927 (0.2294) time: 2.6169 data: 0.0059 max mem: 33369 +Epoch: [0] [1220/1319] eta: 0:04:19 lr: 4.89573706506456e-05 loss: 0.1804 (0.2292) time: 2.6080 data: 0.0058 max mem: 33369 +Epoch: [0] [1230/1319] eta: 0:03:53 lr: 4.89488213848323e-05 loss: 0.1888 (0.2290) time: 2.6343 data: 0.0058 max mem: 33369 +Epoch: [0] [1240/1319] eta: 0:03:26 lr: 4.894027195310566e-05 loss: 0.1888 (0.2287) time: 2.6434 data: 0.0059 max mem: 33369 +Epoch: [0] [1250/1319] eta: 0:03:00 lr: 4.893172235543025e-05 loss: 0.1926 (0.2286) time: 2.6052 data: 0.0061 max mem: 33369 +Epoch: [0] [1260/1319] eta: 0:02:34 lr: 4.892317259177062e-05 loss: 0.1969 (0.2284) time: 2.6103 data: 0.0061 max mem: 33369 +Epoch: [0] [1270/1319] eta: 0:02:08 lr: 4.8914622662091334e-05 loss: 0.1944 (0.2282) time: 2.6140 data: 0.0060 max mem: 33369 +Epoch: [0] [1280/1319] eta: 0:01:42 lr: 4.890607256635692e-05 loss: 0.1944 (0.2280) time: 2.6134 data: 0.0058 max mem: 33369 +Epoch: [0] [1290/1319] eta: 0:01:15 lr: 4.8897522304531876e-05 loss: 0.1907 (0.2278) time: 2.6051 data: 0.0056 max mem: 33369 +Epoch: [0] [1300/1319] eta: 0:00:49 lr: 4.888897187658072e-05 loss: 0.1893 (0.2275) time: 2.5885 data: 0.0058 max mem: 33369 +Epoch: [0] [1310/1319] eta: 0:00:23 lr: 4.888042128246795e-05 loss: 0.1893 (0.2274) time: 2.6102 data: 0.0059 max mem: 33369 +Epoch: [0] Total time: 0:57:35 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 2:03:50 time: 2.8877 data: 2.7946 max mem: 33369 +Test: [ 100/2573] eta: 0:04:06 time: 0.0714 data: 0.0011 max mem: 33369 +Test: [ 200/2573] eta: 0:03:26 time: 0.0733 data: 0.0012 max mem: 33369 +Test: [ 300/2573] eta: 0:03:06 time: 0.0748 data: 0.0011 max mem: 33369 +Test: [ 400/2573] eta: 0:02:53 time: 0.0749 data: 0.0011 max mem: 33369 +Test: [ 500/2573] eta: 0:02:42 time: 0.0734 data: 0.0011 max mem: 33369 +Test: [ 600/2573] eta: 0:02:33 time: 0.0735 data: 0.0011 max mem: 33369 +Test: [ 700/2573] eta: 0:02:24 time: 0.0735 data: 0.0011 max mem: 33369 +Test: [ 800/2573] eta: 0:02:16 time: 0.0769 data: 0.0011 max mem: 33369 +Test: [ 900/2573] eta: 0:02:08 time: 0.0737 data: 0.0011 max mem: 33369 +Test: [1000/2573] eta: 0:02:00 time: 0.0736 data: 0.0011 max mem: 33369 +Test: [1100/2573] eta: 0:01:52 time: 0.0736 data: 0.0011 max mem: 33369 +Test: [1200/2573] eta: 0:01:44 time: 0.0736 data: 0.0011 max mem: 33369 +Test: [1300/2573] eta: 0:01:36 time: 0.0736 data: 0.0011 max mem: 33369 +Test: [1400/2573] eta: 0:01:28 time: 0.0720 data: 0.0011 max mem: 33369 +Test: [1500/2573] eta: 0:01:21 time: 0.0737 data: 0.0011 max mem: 33369 +Test: [1600/2573] eta: 0:01:13 time: 0.0770 data: 0.0011 max mem: 33369 +Test: [1700/2573] eta: 0:01:05 time: 0.0720 data: 0.0011 max mem: 33369 +Test: [1800/2573] eta: 0:00:58 time: 0.0754 data: 0.0011 max mem: 33369 +Test: [1900/2573] eta: 0:00:50 time: 0.0721 data: 0.0011 max mem: 33369 +Test: [2000/2573] eta: 0:00:42 time: 0.0738 data: 0.0011 max mem: 33369 +Test: [2100/2573] eta: 0:00:35 time: 0.0754 data: 0.0011 max mem: 33369 +Test: [2200/2573] eta: 0:00:27 time: 0.0755 data: 0.0011 max mem: 33369 +Test: [2300/2573] eta: 0:00:20 time: 0.0754 data: 0.0011 max mem: 33369 +Test: [2400/2573] eta: 0:00:12 time: 0.0703 data: 0.0011 max mem: 33369 +Test: [2500/2573] eta: 0:00:05 time: 0.0737 data: 0.0011 max mem: 33369 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: Total time: 0:03:12 +Final results: +Mean IoU is 31.50 + + precision@0.5 = 30.13 + precision@0.6 = 22.28 + precision@0.7 = 14.67 + precision@0.8 = 7.82 + precision@0.9 = 1.80 + overall IoU = 37.65 + +Average object IoU 31.502434563159753 +Overall IoU 37.64847946166992 +Better epoch: 0 + +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [1] [ 0/1319] eta: 1:34:14 lr: 4.8872725605668895e-05 loss: 0.1774 (0.1774) time: 4.2868 data: 1.4677 max mem: 33369 +Epoch: [1] [ 10/1319] eta: 1:00:44 lr: 4.886417469575114e-05 loss: 0.1914 (0.1871) time: 2.7842 data: 0.1389 max mem: 33369 +Epoch: [1] [ 20/1319] eta: 0:58:45 lr: 4.88556236195687e-05 loss: 0.1906 (0.1817) time: 2.6353 data: 0.0058 max mem: 33369 +Epoch: [1] [ 30/1319] eta: 0:57:36 lr: 4.884707237708599e-05 loss: 0.1758 (0.1814) time: 2.6256 data: 0.0058 max mem: 33369 +Epoch: [1] [ 40/1319] eta: 0:56:33 lr: 4.883852096826744e-05 loss: 0.1858 (0.1865) time: 2.5891 data: 0.0061 max mem: 33369 +Epoch: [1] [ 50/1319] eta: 0:55:43 lr: 4.882996939307746e-05 loss: 0.1916 (0.1884) time: 2.5614 data: 0.0063 max mem: 33369 +Epoch: [1] [ 60/1319] eta: 0:55:09 lr: 4.882141765148041e-05 loss: 0.1878 (0.1893) time: 2.5790 data: 0.0062 max mem: 33369 +Epoch: [1] [ 70/1319] eta: 0:54:40 lr: 4.881286574344069e-05 loss: 0.1656 (0.1854) time: 2.6069 data: 0.0060 max mem: 33369 +Epoch: [1] [ 80/1319] eta: 0:54:08 lr: 4.8804313668922646e-05 loss: 0.1656 (0.1868) time: 2.6007 data: 0.0061 max mem: 33369 +Epoch: [1] [ 90/1319] eta: 0:53:39 lr: 4.879576142789063e-05 loss: 0.1606 (0.1852) time: 2.5929 data: 0.0060 max mem: 33369 +Epoch: [1] [ 100/1319] eta: 0:53:12 lr: 4.878720902030896e-05 loss: 0.1606 (0.1848) time: 2.6059 data: 0.0059 max mem: 33369 +Epoch: [1] [ 110/1319] eta: 0:52:44 lr: 4.877865644614197e-05 loss: 0.1589 (0.1825) time: 2.6084 data: 0.0059 max mem: 33369 +Epoch: [1] [ 120/1319] eta: 0:52:14 lr: 4.877010370535394e-05 loss: 0.1740 (0.1845) time: 2.5913 data: 0.0059 max mem: 33369 +Epoch: [1] [ 130/1319] eta: 0:51:53 lr: 4.8761550797909164e-05 loss: 0.1860 (0.1841) time: 2.6225 data: 0.0059 max mem: 33369 +Epoch: [1] [ 140/1319] eta: 0:51:25 lr: 4.875299772377192e-05 loss: 0.1857 (0.1844) time: 2.6338 data: 0.0060 max mem: 33369 +Epoch: [1] [ 150/1319] eta: 0:51:04 lr: 4.874444448290645e-05 loss: 0.1857 (0.1844) time: 2.6415 data: 0.0060 max mem: 33369 +Epoch: [1] [ 160/1319] eta: 0:50:34 lr: 4.873589107527701e-05 loss: 0.1719 (0.1835) time: 2.6283 data: 0.0059 max mem: 33369 +Epoch: [1] [ 170/1319] eta: 0:50:07 lr: 4.872733750084782e-05 loss: 0.1719 (0.1852) time: 2.5866 data: 0.0060 max mem: 33369 +Epoch: [1] [ 180/1319] eta: 0:49:42 lr: 4.871878375958309e-05 loss: 0.1945 (0.1855) time: 2.6202 data: 0.0060 max mem: 33369 +Epoch: [1] [ 190/1319] eta: 0:49:17 lr: 4.871022985144703e-05 loss: 0.1824 (0.1858) time: 2.6437 data: 0.0060 max mem: 33369 +Epoch: [1] [ 200/1319] eta: 0:48:52 lr: 4.870167577640381e-05 loss: 0.1818 (0.1872) time: 2.6406 data: 0.0061 max mem: 33369 +Epoch: [1] [ 210/1319] eta: 0:48:23 lr: 4.869312153441761e-05 loss: 0.1812 (0.1870) time: 2.6031 data: 0.0060 max mem: 33369 +Epoch: [1] [ 220/1319] eta: 0:47:56 lr: 4.868456712545258e-05 loss: 0.1725 (0.1881) time: 2.5834 data: 0.0059 max mem: 33369 +Epoch: [1] [ 230/1319] eta: 0:47:30 lr: 4.8676012549472854e-05 loss: 0.1877 (0.1874) time: 2.6075 data: 0.0058 max mem: 33369 +Epoch: [1] [ 240/1319] eta: 0:47:02 lr: 4.866745780644256e-05 loss: 0.1780 (0.1865) time: 2.5978 data: 0.0058 max mem: 33369 +Epoch: [1] [ 250/1319] eta: 0:46:35 lr: 4.865890289632581e-05 loss: 0.1780 (0.1864) time: 2.5928 data: 0.0059 max mem: 33369 +Epoch: [1] [ 260/1319] eta: 0:46:09 lr: 4.8650347819086694e-05 loss: 0.1869 (0.1861) time: 2.6095 data: 0.0059 max mem: 33369 +Epoch: [1] [ 270/1319] eta: 0:45:42 lr: 4.864179257468931e-05 loss: 0.1770 (0.1867) time: 2.5944 data: 0.0057 max mem: 33369 +Epoch: [1] [ 280/1319] eta: 0:45:19 lr: 4.8633237163097687e-05 loss: 0.1850 (0.1876) time: 2.6497 data: 0.0057 max mem: 33369 +Epoch: [1] [ 290/1319] eta: 0:44:51 lr: 4.862468158427592e-05 loss: 0.1850 (0.1876) time: 2.6434 data: 0.0058 max mem: 33369 +Epoch: [1] [ 300/1319] eta: 0:44:25 lr: 4.861612583818801e-05 loss: 0.1723 (0.1882) time: 2.5931 data: 0.0059 max mem: 33369 +Epoch: [1] [ 310/1319] eta: 0:44:00 lr: 4.860756992479799e-05 loss: 0.1945 (0.1888) time: 2.6264 data: 0.0059 max mem: 33369 +Epoch: [1] [ 320/1319] eta: 0:43:33 lr: 4.859901384406988e-05 loss: 0.1845 (0.1886) time: 2.6129 data: 0.0059 max mem: 33369 +Epoch: [1] [ 330/1319] eta: 0:43:06 lr: 4.8590457595967656e-05 loss: 0.1845 (0.1895) time: 2.5918 data: 0.0061 max mem: 33369 +Epoch: [1] [ 340/1319] eta: 0:42:39 lr: 4.85819011804553e-05 loss: 0.1681 (0.1885) time: 2.5983 data: 0.0062 max mem: 33369 +Epoch: [1] [ 350/1319] eta: 0:42:13 lr: 4.8573344597496775e-05 loss: 0.1702 (0.1893) time: 2.6112 data: 0.0060 max mem: 33369 +Epoch: [1] [ 360/1319] eta: 0:41:46 lr: 4.856478784705602e-05 loss: 0.1932 (0.1892) time: 2.6027 data: 0.0058 max mem: 33369 +Epoch: [1] [ 370/1319] eta: 0:41:21 lr: 4.8556230929096985e-05 loss: 0.1807 (0.1895) time: 2.6056 data: 0.0057 max mem: 33369 +Epoch: [1] [ 380/1319] eta: 0:40:54 lr: 4.854767384358357e-05 loss: 0.1800 (0.1892) time: 2.6051 data: 0.0057 max mem: 33369 +Epoch: [1] [ 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2.6281 data: 0.0059 max mem: 33369 +Epoch: [1] [ 710/1319] eta: 0:26:34 lr: 4.826519578660238e-05 loss: 0.1675 (0.1859) time: 2.6197 data: 0.0058 max mem: 33369 +Epoch: [1] [ 720/1319] eta: 0:26:07 lr: 4.825663298266489e-05 loss: 0.1787 (0.1859) time: 2.6011 data: 0.0057 max mem: 33369 +Epoch: [1] [ 730/1319] eta: 0:25:41 lr: 4.824807000990074e-05 loss: 0.1652 (0.1856) time: 2.6038 data: 0.0058 max mem: 33369 +Epoch: [1] [ 740/1319] eta: 0:25:15 lr: 4.82395068682733e-05 loss: 0.1633 (0.1855) time: 2.6100 data: 0.0060 max mem: 33369 +Epoch: [1] [ 750/1319] eta: 0:24:49 lr: 4.823094355774595e-05 loss: 0.1555 (0.1856) time: 2.6176 data: 0.0060 max mem: 33369 +Epoch: [1] [ 760/1319] eta: 0:24:23 lr: 4.822238007828201e-05 loss: 0.1840 (0.1855) time: 2.6113 data: 0.0059 max mem: 33369 +Epoch: [1] [ 770/1319] eta: 0:23:56 lr: 4.8213816429844826e-05 loss: 0.1840 (0.1856) time: 2.5838 data: 0.0059 max mem: 33369 +Epoch: [1] [ 780/1319] eta: 0:23:30 lr: 4.8205252612397726e-05 loss: 0.1684 (0.1852) time: 2.6130 data: 0.0062 max mem: 33369 +Epoch: [1] [ 790/1319] eta: 0:23:04 lr: 4.8196688625903984e-05 loss: 0.1590 (0.1854) time: 2.6215 data: 0.0062 max mem: 33369 +Epoch: [1] [ 800/1319] eta: 0:22:38 lr: 4.8188124470326915e-05 loss: 0.1590 (0.1852) time: 2.6397 data: 0.0059 max mem: 33369 +Epoch: [1] [ 810/1319] eta: 0:22:12 lr: 4.8179560145629784e-05 loss: 0.1864 (0.1855) time: 2.6577 data: 0.0059 max mem: 33369 +Epoch: [1] [ 820/1319] eta: 0:21:46 lr: 4.817099565177583e-05 loss: 0.1979 (0.1855) time: 2.6365 data: 0.0058 max mem: 33369 +Epoch: [1] [ 830/1319] eta: 0:21:20 lr: 4.8162430988728305e-05 loss: 0.1750 (0.1857) time: 2.6367 data: 0.0057 max mem: 33369 +Epoch: [1] [ 840/1319] eta: 0:20:54 lr: 4.815386615645044e-05 loss: 0.1678 (0.1853) time: 2.6265 data: 0.0058 max mem: 33369 +Epoch: [1] [ 850/1319] eta: 0:20:28 lr: 4.814530115490545e-05 loss: 0.1678 (0.1853) time: 2.6308 data: 0.0057 max mem: 33369 +Epoch: [1] [ 860/1319] eta: 0:20:01 lr: 4.813673598405651e-05 loss: 0.1796 (0.1852) time: 2.6225 data: 0.0059 max mem: 33369 +Epoch: [1] [ 870/1319] eta: 0:19:35 lr: 4.812817064386682e-05 loss: 0.1618 (0.1850) time: 2.6096 data: 0.0059 max mem: 33369 +Epoch: [1] [ 880/1319] eta: 0:19:09 lr: 4.8119605134299526e-05 loss: 0.1598 (0.1849) time: 2.6360 data: 0.0058 max mem: 33369 +Epoch: [1] [ 890/1319] eta: 0:18:43 lr: 4.81110394553178e-05 loss: 0.1557 (0.1846) time: 2.6255 data: 0.0058 max mem: 33369 +Epoch: [1] [ 900/1319] eta: 0:18:17 lr: 4.810247360688475e-05 loss: 0.1567 (0.1845) time: 2.6006 data: 0.0056 max mem: 33369 +Epoch: [1] [ 910/1319] eta: 0:17:50 lr: 4.809390758896352e-05 loss: 0.1424 (0.1841) time: 2.5870 data: 0.0058 max mem: 33369 +Epoch: [1] [ 920/1319] eta: 0:17:24 lr: 4.808534140151719e-05 loss: 0.1613 (0.1842) time: 2.5959 data: 0.0059 max mem: 33369 +Epoch: [1] [ 930/1319] eta: 0:16:58 lr: 4.807677504450886e-05 loss: 0.1613 (0.1840) time: 2.6200 data: 0.0058 max mem: 33369 +Epoch: [1] [ 940/1319] eta: 0:16:32 lr: 4.806820851790161e-05 loss: 0.1609 (0.1840) time: 2.6277 data: 0.0057 max mem: 33369 +Epoch: [1] [ 950/1319] eta: 0:16:06 lr: 4.805964182165848e-05 loss: 0.1793 (0.1840) time: 2.6185 data: 0.0058 max mem: 33369 +Epoch: [1] [ 960/1319] eta: 0:15:39 lr: 4.8051074955742525e-05 loss: 0.1692 (0.1839) time: 2.5925 data: 0.0057 max mem: 33369 +Epoch: [1] [ 970/1319] eta: 0:15:13 lr: 4.804250792011677e-05 loss: 0.1763 (0.1839) time: 2.5915 data: 0.0057 max mem: 33369 +Epoch: [1] [ 980/1319] eta: 0:14:47 lr: 4.803394071474422e-05 loss: 0.1794 (0.1840) time: 2.6028 data: 0.0058 max mem: 33369 +Epoch: [1] [ 990/1319] eta: 0:14:21 lr: 4.802537333958788e-05 loss: 0.1646 (0.1838) time: 2.6197 data: 0.0058 max mem: 33369 +Epoch: [1] [1000/1319] eta: 0:13:55 lr: 4.801680579461071e-05 loss: 0.1712 (0.1841) time: 2.6421 data: 0.0057 max mem: 33369 +Epoch: [1] [1010/1319] eta: 0:13:28 lr: 4.80082380797757e-05 loss: 0.1900 (0.1841) time: 2.6465 data: 0.0057 max mem: 33369 +Epoch: [1] [1020/1319] eta: 0:13:02 lr: 4.79996701950458e-05 loss: 0.1787 (0.1844) time: 2.6232 data: 0.0058 max mem: 33369 +Epoch: [1] [1030/1319] eta: 0:12:36 lr: 4.799110214038392e-05 loss: 0.1765 (0.1845) time: 2.6255 data: 0.0058 max mem: 33369 +Epoch: [1] [1040/1319] eta: 0:12:10 lr: 4.7982533915752995e-05 loss: 0.1884 (0.1846) time: 2.6562 data: 0.0058 max mem: 33369 +Epoch: [1] [1050/1319] eta: 0:11:44 lr: 4.797396552111593e-05 loss: 0.1798 (0.1843) time: 2.6496 data: 0.0059 max mem: 33369 +Epoch: [1] [1060/1319] eta: 0:11:18 lr: 4.7965396956435596e-05 loss: 0.1474 (0.1841) time: 2.6204 data: 0.0060 max mem: 33369 +Epoch: [1] [1070/1319] eta: 0:10:51 lr: 4.795682822167489e-05 loss: 0.1636 (0.1841) time: 2.5846 data: 0.0058 max mem: 33369 +Epoch: [1] [1080/1319] eta: 0:10:25 lr: 4.794825931679665e-05 loss: 0.1855 (0.1843) time: 2.5798 data: 0.0056 max mem: 33369 +Epoch: [1] [1090/1319] eta: 0:09:59 lr: 4.7939690241763725e-05 loss: 0.1696 (0.1841) time: 2.6045 data: 0.0058 max mem: 33369 +Epoch: [1] 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+Epoch: [1] [1180/1319] eta: 0:06:03 lr: 4.786256090336764e-05 loss: 0.1601 (0.1838) time: 2.6362 data: 0.0057 max mem: 33369 +Epoch: [1] [1190/1319] eta: 0:05:37 lr: 4.7853990124740705e-05 loss: 0.1622 (0.1835) time: 2.6470 data: 0.0057 max mem: 33369 +Epoch: [1] [1200/1319] eta: 0:05:11 lr: 4.784541917554932e-05 loss: 0.1672 (0.1834) time: 2.6272 data: 0.0058 max mem: 33369 +Epoch: [1] [1210/1319] eta: 0:04:45 lr: 4.783684805575612e-05 loss: 0.1711 (0.1834) time: 2.6120 data: 0.0057 max mem: 33369 +Epoch: [1] [1220/1319] eta: 0:04:19 lr: 4.782827676532376e-05 loss: 0.1687 (0.1833) time: 2.6152 data: 0.0058 max mem: 33369 +Epoch: [1] [1230/1319] eta: 0:03:53 lr: 4.781970530421487e-05 loss: 0.1672 (0.1831) time: 2.6443 data: 0.0059 max mem: 33369 +Epoch: [1] [1240/1319] eta: 0:03:26 lr: 4.7811133672392044e-05 loss: 0.1440 (0.1828) time: 2.6515 data: 0.0057 max mem: 33369 +Epoch: [1] [1250/1319] eta: 0:03:00 lr: 4.780256186981787e-05 loss: 0.1444 (0.1827) time: 2.6200 data: 0.0059 max mem: 33369 +Epoch: [1] [1260/1319] eta: 0:02:34 lr: 4.779398989645494e-05 loss: 0.1745 (0.1826) time: 2.6049 data: 0.0059 max mem: 33369 +Epoch: [1] [1270/1319] eta: 0:02:08 lr: 4.778541775226581e-05 loss: 0.1745 (0.1826) time: 2.6036 data: 0.0058 max mem: 33369 +Epoch: [1] [1280/1319] eta: 0:01:42 lr: 4.777684543721302e-05 loss: 0.1407 (0.1824) time: 2.6013 data: 0.0059 max mem: 33369 +Epoch: [1] [1290/1319] eta: 0:01:15 lr: 4.776827295125911e-05 loss: 0.1679 (0.1823) time: 2.6041 data: 0.0059 max mem: 33369 +Epoch: [1] [1300/1319] eta: 0:00:49 lr: 4.775970029436657e-05 loss: 0.1511 (0.1821) time: 2.6032 data: 0.0058 max mem: 33369 +Epoch: [1] [1310/1319] eta: 0:00:23 lr: 4.7751127466497925e-05 loss: 0.1707 (0.1822) time: 2.5905 data: 0.0059 max mem: 33369 +Epoch: [1] Total time: 0:57:33 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 2:08:23 time: 2.9939 data: 2.9155 max mem: 33369 +Test: [ 100/2573] eta: 0:04:09 time: 0.0714 data: 0.0011 max mem: 33369 +Test: [ 200/2573] eta: 0:03:27 time: 0.0732 data: 0.0011 max mem: 33369 +Test: [ 300/2573] eta: 0:03:07 time: 0.0750 data: 0.0011 max mem: 33369 +Test: [ 400/2573] eta: 0:02:53 time: 0.0751 data: 0.0011 max mem: 33369 +Test: [ 500/2573] eta: 0:02:43 time: 0.0735 data: 0.0011 max mem: 33369 +Test: [ 600/2573] eta: 0:02:33 time: 0.0736 data: 0.0012 max mem: 33369 +Test: [ 700/2573] eta: 0:02:25 time: 0.0736 data: 0.0011 max mem: 33369 +Test: [ 800/2573] eta: 0:02:17 time: 0.0771 data: 0.0011 max mem: 33369 +Test: [ 900/2573] eta: 0:02:08 time: 0.0737 data: 0.0011 max mem: 33369 +Test: [1000/2573] eta: 0:02:00 time: 0.0737 data: 0.0011 max mem: 33369 +Test: [1100/2573] eta: 0:01:52 time: 0.0736 data: 0.0011 max mem: 33369 +Test: [1200/2573] eta: 0:01:44 time: 0.0737 data: 0.0011 max mem: 33369 +Test: [1300/2573] eta: 0:01:36 time: 0.0736 data: 0.0011 max mem: 33369 +Test: [1400/2573] eta: 0:01:28 time: 0.0720 data: 0.0011 max mem: 33369 +Test: [1500/2573] eta: 0:01:21 time: 0.0738 data: 0.0011 max mem: 33369 +Test: [1600/2573] eta: 0:01:13 time: 0.0771 data: 0.0011 max mem: 33369 +Test: [1700/2573] eta: 0:01:05 time: 0.0720 data: 0.0011 max mem: 33369 +Test: [1800/2573] eta: 0:00:58 time: 0.0753 data: 0.0011 max mem: 33369 +Test: [1900/2573] eta: 0:00:50 time: 0.0721 data: 0.0011 max mem: 33369 +Test: [2000/2573] eta: 0:00:43 time: 0.0737 data: 0.0011 max mem: 33369 +Test: [2100/2573] eta: 0:00:35 time: 0.0752 data: 0.0011 max mem: 33369 +Test: [2200/2573] eta: 0:00:27 time: 0.0753 data: 0.0011 max mem: 33369 +Test: [2300/2573] eta: 0:00:20 time: 0.0752 data: 0.0011 max mem: 33369 +Test: [2400/2573] eta: 0:00:12 time: 0.0703 data: 0.0011 max mem: 33369 +Test: [2500/2573] eta: 0:00:05 time: 0.0736 data: 0.0011 max mem: 33369 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: Total time: 0:03:12 +Final results: +Mean IoU is 41.16 + + precision@0.5 = 40.22 + precision@0.6 = 30.21 + precision@0.7 = 21.28 + precision@0.8 = 12.77 + precision@0.9 = 3.80 + overall IoU = 44.82 + +Average object IoU 41.16155050934349 +Overall IoU 44.81966781616211 +Better epoch: 1 + +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [2] [ 0/1319] eta: 1:26:51 lr: 4.774341177520056e-05 loss: 0.1098 (0.1098) time: 3.9508 data: 1.2308 max mem: 33369 +Epoch: [2] [ 10/1319] eta: 0:59:21 lr: 4.773483862237391e-05 loss: 0.1643 (0.1760) time: 2.7207 data: 0.1170 max mem: 33369 +Epoch: [2] [ 20/1319] eta: 0:57:43 lr: 4.772626529846231e-05 loss: 0.1565 (0.1665) time: 2.6019 data: 0.0055 max mem: 33369 +Epoch: [2] [ 30/1319] eta: 0:56:38 lr: 4.771769180342819e-05 loss: 0.1507 (0.1643) time: 2.5903 data: 0.0057 max mem: 33369 +Epoch: [2] [ 40/1319] eta: 0:56:16 lr: 4.7709118137233964e-05 loss: 0.1507 (0.1629) time: 2.6131 data: 0.0061 max mem: 33369 +Epoch: [2] [ 50/1319] eta: 0:55:58 lr: 4.770054429984204e-05 loss: 0.1564 (0.1631) time: 2.6629 data: 0.0061 max mem: 33369 +Epoch: [2] [ 60/1319] eta: 0:55:30 lr: 4.769197029121481e-05 loss: 0.1556 (0.1644) time: 2.6559 data: 0.0059 max mem: 33369 +Epoch: [2] [ 70/1319] eta: 0:55:04 lr: 4.7683396111314645e-05 loss: 0.1640 (0.1708) time: 2.6426 data: 0.0059 max mem: 33369 +Epoch: [2] [ 80/1319] eta: 0:54:34 lr: 4.7674821760103904e-05 loss: 0.1640 (0.1685) time: 2.6337 data: 0.0058 max mem: 33369 +Epoch: [2] [ 90/1319] eta: 0:54:04 lr: 4.766624723754494e-05 loss: 0.1680 (0.1689) time: 2.6181 data: 0.0060 max mem: 33369 +Epoch: [2] [ 100/1319] eta: 0:53:35 lr: 4.7657672543600056e-05 loss: 0.1732 (0.1688) time: 2.6179 data: 0.0062 max mem: 33369 +Epoch: [2] [ 110/1319] eta: 0:53:07 lr: 4.764909767823158e-05 loss: 0.1574 (0.1677) time: 2.6207 data: 0.0061 max mem: 33369 +Epoch: [2] [ 120/1319] eta: 0:52:35 lr: 4.76405226414018e-05 loss: 0.1475 (0.1662) time: 2.6024 data: 0.0064 max mem: 33369 +Epoch: [2] [ 130/1319] eta: 0:52:08 lr: 4.7631947433073e-05 loss: 0.1426 (0.1644) time: 2.6042 data: 0.0063 max mem: 33369 +Epoch: [2] [ 140/1319] eta: 0:51:42 lr: 4.762337205320744e-05 loss: 0.1477 (0.1636) time: 2.6300 data: 0.0060 max mem: 33369 +Epoch: [2] [ 150/1319] eta: 0:51:14 lr: 4.7614796501767376e-05 loss: 0.1570 (0.1633) time: 2.6233 data: 0.0060 max mem: 33369 +Epoch: [2] [ 160/1319] eta: 0:50:50 lr: 4.760622077871502e-05 loss: 0.1638 (0.1639) time: 2.6350 data: 0.0060 max mem: 33369 +Epoch: [2] [ 170/1319] eta: 0:50:22 lr: 4.75976448840126e-05 loss: 0.1505 (0.1632) time: 2.6319 data: 0.0059 max mem: 33369 +Epoch: [2] [ 180/1319] eta: 0:49:56 lr: 4.7589068817622304e-05 loss: 0.1436 (0.1623) time: 2.6183 data: 0.0060 max mem: 33369 +Epoch: [2] [ 190/1319] eta: 0:49:30 lr: 4.758049257950633e-05 loss: 0.1453 (0.1623) time: 2.6383 data: 0.0061 max mem: 33369 +Epoch: [2] [ 200/1319] eta: 0:49:03 lr: 4.757191616962685e-05 loss: 0.1595 (0.1633) time: 2.6313 data: 0.0061 max mem: 33369 +Epoch: [2] [ 210/1319] eta: 0:48:36 lr: 4.756333958794601e-05 loss: 0.1592 (0.1629) time: 2.6118 data: 0.0062 max mem: 33369 +Epoch: [2] [ 220/1319] eta: 0:48:09 lr: 4.7554762834425936e-05 loss: 0.1531 (0.1629) time: 2.6152 data: 0.0060 max mem: 33369 +Epoch: [2] [ 230/1319] eta: 0:47:44 lr: 4.7546185909028754e-05 loss: 0.1658 (0.1640) time: 2.6412 data: 0.0059 max mem: 33369 +Epoch: [2] [ 240/1319] eta: 0:47:20 lr: 4.753760881171657e-05 loss: 0.1698 (0.1639) time: 2.6663 data: 0.0058 max mem: 33369 +Epoch: [2] [ 250/1319] eta: 0:46:52 lr: 4.7529031542451477e-05 loss: 0.1698 (0.1644) time: 2.6425 data: 0.0059 max mem: 33369 +Epoch: [2] [ 260/1319] eta: 0:46:29 lr: 4.7520454101195535e-05 loss: 0.1653 (0.1649) time: 2.6507 data: 0.0061 max mem: 33369 +Epoch: [2] [ 270/1319] eta: 0:46:02 lr: 4.751187648791081e-05 loss: 0.1614 (0.1645) time: 2.6531 data: 0.0062 max mem: 33369 +Epoch: [2] [ 280/1319] eta: 0:45:34 lr: 4.7503298702559326e-05 loss: 0.1613 (0.1646) time: 2.6090 data: 0.0061 max mem: 33369 +Epoch: [2] [ 290/1319] eta: 0:45:08 lr: 4.7494720745103136e-05 loss: 0.1608 (0.1649) time: 2.6164 data: 0.0059 max mem: 33369 +Epoch: [2] [ 300/1319] eta: 0:44:41 lr: 4.748614261550422e-05 loss: 0.1446 (0.1640) time: 2.6301 data: 0.0058 max mem: 33369 +Epoch: [2] [ 310/1319] eta: 0:44:14 lr: 4.7477564313724594e-05 loss: 0.1427 (0.1638) time: 2.6224 data: 0.0058 max mem: 33369 +Epoch: [2] [ 320/1319] eta: 0:43:50 lr: 4.746898583972622e-05 loss: 0.1653 (0.1645) time: 2.6614 data: 0.0060 max mem: 33369 +Epoch: [2] [ 330/1319] eta: 0:43:25 lr: 4.746040719347105e-05 loss: 0.1585 (0.1644) time: 2.6765 data: 0.0061 max mem: 33369 +Epoch: [2] [ 340/1319] eta: 0:42:57 lr: 4.745182837492104e-05 loss: 0.1540 (0.1648) time: 2.6258 data: 0.0061 max mem: 33369 +Epoch: [2] [ 350/1319] eta: 0:42:31 lr: 4.744324938403812e-05 loss: 0.1693 (0.1654) time: 2.6221 data: 0.0059 max mem: 33369 +Epoch: [2] [ 360/1319] eta: 0:42:04 lr: 4.7434670220784206e-05 loss: 0.1550 (0.1650) time: 2.6254 data: 0.0060 max mem: 33369 +Epoch: [2] [ 370/1319] eta: 0:41:36 lr: 4.7426090885121175e-05 loss: 0.1461 (0.1647) time: 2.5899 data: 0.0061 max mem: 33369 +Epoch: [2] [ 380/1319] eta: 0:41:10 lr: 4.741751137701092e-05 loss: 0.1627 (0.1649) time: 2.6049 data: 0.0059 max mem: 33369 +Epoch: [2] [ 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+Epoch: [2] [1260/1319] eta: 0:02:34 lr: 4.6661834838121084e-05 loss: 0.1470 (0.1644) time: 2.5975 data: 0.0057 max mem: 33369 +Epoch: [2] [1270/1319] eta: 0:02:08 lr: 4.665323982755382e-05 loss: 0.1520 (0.1643) time: 2.6121 data: 0.0058 max mem: 33369 +Epoch: [2] [1280/1319] eta: 0:01:42 lr: 4.664464464104137e-05 loss: 0.1520 (0.1643) time: 2.6243 data: 0.0060 max mem: 33369 +Epoch: [2] [1290/1319] eta: 0:01:16 lr: 4.6636049278544094e-05 loss: 0.1395 (0.1642) time: 2.6319 data: 0.0059 max mem: 33369 +Epoch: [2] [1300/1319] eta: 0:00:49 lr: 4.662745374002236e-05 loss: 0.1606 (0.1644) time: 2.6301 data: 0.0058 max mem: 33369 +Epoch: [2] [1310/1319] eta: 0:00:23 lr: 4.6618858025436495e-05 loss: 0.1606 (0.1646) time: 2.6385 data: 0.0058 max mem: 33369 +Epoch: [2] Total time: 0:57:40 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 1:56:33 time: 2.7179 data: 2.6392 max mem: 33369 +Test: [ 100/2573] eta: 0:04:02 time: 0.0718 data: 0.0011 max mem: 33369 +Test: [ 200/2573] eta: 0:03:24 time: 0.0734 data: 0.0011 max mem: 33369 +Test: [ 300/2573] eta: 0:03:05 time: 0.0750 data: 0.0011 max mem: 33369 +Test: [ 400/2573] eta: 0:02:52 time: 0.0750 data: 0.0011 max mem: 33369 +Test: [ 500/2573] eta: 0:02:42 time: 0.0734 data: 0.0011 max mem: 33369 +Test: [ 600/2573] eta: 0:02:32 time: 0.0736 data: 0.0011 max mem: 33369 +Test: [ 700/2573] eta: 0:02:24 time: 0.0736 data: 0.0011 max mem: 33369 +Test: [ 800/2573] eta: 0:02:16 time: 0.0770 data: 0.0011 max mem: 33369 +Test: [ 900/2573] eta: 0:02:08 time: 0.0737 data: 0.0011 max mem: 33369 +Test: [1000/2573] eta: 0:02:00 time: 0.0737 data: 0.0011 max mem: 33369 +Test: [1100/2573] eta: 0:01:52 time: 0.0738 data: 0.0011 max mem: 33369 +Test: [1200/2573] eta: 0:01:44 time: 0.0737 data: 0.0011 max mem: 33369 +Test: [1300/2573] eta: 0:01:36 time: 0.0738 data: 0.0011 max mem: 33369 +Test: [1400/2573] eta: 0:01:28 time: 0.0722 data: 0.0011 max mem: 33369 +Test: [1500/2573] eta: 0:01:21 time: 0.0738 data: 0.0011 max mem: 33369 +Test: [1600/2573] eta: 0:01:13 time: 0.0771 data: 0.0011 max mem: 33369 +Test: [1700/2573] eta: 0:01:05 time: 0.0721 data: 0.0011 max mem: 33369 +Test: [1800/2573] eta: 0:00:58 time: 0.0755 data: 0.0011 max mem: 33369 +Test: [1900/2573] eta: 0:00:50 time: 0.0721 data: 0.0011 max mem: 33369 +Test: [2000/2573] eta: 0:00:43 time: 0.0740 data: 0.0011 max mem: 33369 +Test: [2100/2573] eta: 0:00:35 time: 0.0757 data: 0.0011 max mem: 33369 +Test: [2200/2573] eta: 0:00:27 time: 0.0756 data: 0.0011 max mem: 33369 +Test: [2300/2573] eta: 0:00:20 time: 0.0755 data: 0.0011 max mem: 33369 +Test: [2400/2573] eta: 0:00:12 time: 0.0706 data: 0.0011 max mem: 33369 +Test: [2500/2573] eta: 0:00:05 time: 0.0739 data: 0.0011 max mem: 33369 +Test: Total time: 0:03:13 +Final results: +Mean IoU is 39.08 + + precision@0.5 = 39.81 + precision@0.6 = 31.76 + precision@0.7 = 24.22 + precision@0.8 = 14.81 + precision@0.9 = 4.58 + overall IoU = 44.02 + +Average object IoU 39.0760037658132 +Overall IoU 44.015201568603516 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [3] [ 0/1319] eta: 3:14:04 lr: 4.661112173174161e-05 loss: 0.1091 (0.1091) time: 8.8287 data: 1.4563 max mem: 33369 +Epoch: [3] [ 10/1319] eta: 1:09:34 lr: 4.660252568252458e-05 loss: 0.1245 (0.1327) time: 3.1893 data: 0.1380 max mem: 33369 +Epoch: [3] [ 20/1319] eta: 1:03:11 lr: 4.6593929457128314e-05 loss: 0.1267 (0.1296) time: 2.6229 data: 0.0058 max mem: 33369 +Epoch: [3] [ 30/1319] eta: 1:00:30 lr: 4.6585333055513096e-05 loss: 0.1294 (0.1323) time: 2.6120 data: 0.0058 max mem: 33369 +Epoch: [3] [ 40/1319] eta: 0:59:13 lr: 4.657673647763916e-05 loss: 0.1569 (0.1457) time: 2.6305 data: 0.0061 max mem: 33369 +Epoch: [3] [ 50/1319] eta: 0:58:16 lr: 4.656813972346675e-05 loss: 0.1482 (0.1440) time: 2.6604 data: 0.0060 max mem: 33369 +Epoch: [3] [ 60/1319] eta: 0:57:10 lr: 4.655954279295608e-05 loss: 0.1363 (0.1438) time: 2.6148 data: 0.0061 max mem: 33369 +Epoch: [3] [ 70/1319] eta: 0:56:30 lr: 4.655094568606738e-05 loss: 0.1207 (0.1444) time: 2.6103 data: 0.0061 max mem: 33369 +Epoch: [3] [ 80/1319] eta: 0:55:53 lr: 4.6542348402760813e-05 loss: 0.1358 (0.1468) time: 2.6526 data: 0.0060 max mem: 33369 +Epoch: [3] [ 90/1319] eta: 0:55:14 lr: 4.653375094299656e-05 loss: 0.1570 (0.1502) time: 2.6353 data: 0.0059 max mem: 33369 +Epoch: [3] [ 100/1319] eta: 0:54:39 lr: 4.652515330673476e-05 loss: 0.1555 (0.1486) time: 2.6247 data: 0.0059 max mem: 33369 +Epoch: [3] [ 110/1319] eta: 0:54:07 lr: 4.651655549393556e-05 loss: 0.1181 (0.1478) time: 2.6335 data: 0.0061 max mem: 33369 +Epoch: [3] [ 120/1319] eta: 0:53:32 lr: 4.650795750455908e-05 loss: 0.1321 (0.1471) time: 2.6233 data: 0.0060 max mem: 33369 +Epoch: [3] [ 130/1319] eta: 0:52:58 lr: 4.649935933856541e-05 loss: 0.1430 (0.1471) time: 2.6030 data: 0.0060 max mem: 33369 +Epoch: [3] [ 140/1319] eta: 0:52:25 lr: 4.6490760995914644e-05 loss: 0.1331 (0.1463) time: 2.6014 data: 0.0058 max mem: 33369 +Epoch: [3] [ 150/1319] eta: 0:51:59 lr: 4.648216247656684e-05 loss: 0.1499 (0.1465) time: 2.6377 data: 0.0058 max mem: 33369 +Epoch: [3] [ 160/1319] eta: 0:51:30 lr: 4.647356378048206e-05 loss: 0.1409 (0.1460) time: 2.6570 data: 0.0060 max mem: 33369 +Epoch: [3] [ 170/1319] eta: 0:51:01 lr: 4.646496490762032e-05 loss: 0.1409 (0.1474) time: 2.6335 data: 0.0059 max mem: 33369 +Epoch: [3] [ 180/1319] eta: 0:50:30 lr: 4.645636585794164e-05 loss: 0.1524 (0.1472) time: 2.6092 data: 0.0059 max mem: 33369 +Epoch: [3] [ 190/1319] eta: 0:49:59 lr: 4.644776663140602e-05 loss: 0.1502 (0.1477) time: 2.5889 data: 0.0060 max mem: 33369 +Epoch: [3] [ 200/1319] eta: 0:49:29 lr: 4.6439167227973446e-05 loss: 0.1446 (0.1488) time: 2.5962 data: 0.0061 max mem: 33369 +Epoch: [3] [ 210/1319] eta: 0:49:00 lr: 4.643056764760387e-05 loss: 0.1446 (0.1494) time: 2.6087 data: 0.0062 max mem: 33369 +Epoch: [3] [ 220/1319] eta: 0:48:31 lr: 4.642196789025724e-05 loss: 0.1532 (0.1494) time: 2.6025 data: 0.0061 max mem: 33369 +Epoch: [3] [ 230/1319] eta: 0:48:05 lr: 4.641336795589349e-05 loss: 0.1489 (0.1498) time: 2.6283 data: 0.0060 max mem: 33369 +Epoch: [3] [ 240/1319] eta: 0:47:36 lr: 4.6404767844472526e-05 loss: 0.1489 (0.1500) time: 2.6292 data: 0.0061 max mem: 33369 +Epoch: [3] [ 250/1319] eta: 0:47:10 lr: 4.639616755595424e-05 loss: 0.1393 (0.1492) time: 2.6202 data: 0.0061 max mem: 33369 +Epoch: [3] [ 260/1319] eta: 0:46:41 lr: 4.638756709029851e-05 loss: 0.1389 (0.1492) time: 2.6144 data: 0.0059 max mem: 33369 +Epoch: [3] [ 270/1319] eta: 0:46:13 lr: 4.6378966447465196e-05 loss: 0.1412 (0.1499) time: 2.6032 data: 0.0061 max mem: 33369 +Epoch: [3] [ 280/1319] eta: 0:45:47 lr: 4.637036562741414e-05 loss: 0.1475 (0.1503) time: 2.6391 data: 0.0062 max mem: 33369 +Epoch: [3] [ 290/1319] eta: 0:45:20 lr: 4.636176463010516e-05 loss: 0.1503 (0.1513) time: 2.6444 data: 0.0061 max mem: 33369 +Epoch: [3] [ 300/1319] eta: 0:44:53 lr: 4.635316345549808e-05 loss: 0.1315 (0.1509) time: 2.6280 data: 0.0060 max mem: 33369 +Epoch: [3] [ 310/1319] eta: 0:44:26 lr: 4.634456210355267e-05 loss: 0.1348 (0.1510) time: 2.6244 data: 0.0059 max mem: 33369 +Epoch: [3] [ 320/1319] eta: 0:43:59 lr: 4.633596057422871e-05 loss: 0.1482 (0.1506) time: 2.6255 data: 0.0058 max mem: 33369 +Epoch: [3] [ 330/1319] eta: 0:43:32 lr: 4.632735886748595e-05 loss: 0.1284 (0.1507) time: 2.6165 data: 0.0059 max mem: 33369 +Epoch: [3] [ 340/1319] eta: 0:43:05 lr: 4.6318756983284134e-05 loss: 0.1208 (0.1505) time: 2.6178 data: 0.0058 max mem: 33369 +Epoch: [3] [ 350/1319] eta: 0:42:38 lr: 4.6310154921582983e-05 loss: 0.1354 (0.1503) time: 2.6213 data: 0.0058 max mem: 33369 +Epoch: [3] [ 360/1319] eta: 0:42:11 lr: 4.630155268234219e-05 loss: 0.1452 (0.1503) time: 2.6098 data: 0.0058 max mem: 33369 +Epoch: [3] [ 370/1319] eta: 0:41:43 lr: 4.629295026552143e-05 loss: 0.1363 (0.1497) time: 2.6088 data: 0.0059 max mem: 33369 +Epoch: [3] [ 380/1319] eta: 0:41:16 lr: 4.6284347671080394e-05 loss: 0.1315 (0.1494) time: 2.5926 data: 0.0058 max mem: 33369 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0.0059 max mem: 33369 +Epoch: [3] [ 550/1319] eta: 0:33:41 lr: 4.613807635051161e-05 loss: 0.1333 (0.1492) time: 2.6159 data: 0.0058 max mem: 33369 +Epoch: [3] [ 560/1319] eta: 0:33:14 lr: 4.612947055198852e-05 loss: 0.1657 (0.1498) time: 2.6156 data: 0.0060 max mem: 33369 +Epoch: [3] [ 570/1319] eta: 0:32:48 lr: 4.612086457507548e-05 loss: 0.1730 (0.1504) time: 2.6300 data: 0.0061 max mem: 33369 +Epoch: [3] [ 580/1319] eta: 0:32:22 lr: 4.611225841973181e-05 loss: 0.1320 (0.1498) time: 2.6277 data: 0.0058 max mem: 33369 +Epoch: [3] [ 590/1319] eta: 0:31:56 lr: 4.610365208591681e-05 loss: 0.1054 (0.1497) time: 2.6260 data: 0.0058 max mem: 33369 +Epoch: [3] [ 600/1319] eta: 0:31:30 lr: 4.609504557358975e-05 loss: 0.1515 (0.1499) time: 2.6396 data: 0.0059 max mem: 33369 +Epoch: [3] [ 610/1319] eta: 0:31:03 lr: 4.60864388827099e-05 loss: 0.1523 (0.1499) time: 2.6186 data: 0.0058 max mem: 33369 +Epoch: [3] [ 620/1319] eta: 0:30:36 lr: 4.6077832013236505e-05 loss: 0.1542 (0.1499) time: 2.5969 data: 0.0060 max mem: 33369 +Epoch: [3] [ 630/1319] eta: 0:30:10 lr: 4.606922496512879e-05 loss: 0.1542 (0.1503) time: 2.6256 data: 0.0060 max mem: 33369 +Epoch: [3] [ 640/1319] eta: 0:29:44 lr: 4.606061773834596e-05 loss: 0.1431 (0.1503) time: 2.6200 data: 0.0058 max mem: 33369 +Epoch: [3] [ 650/1319] eta: 0:29:17 lr: 4.60520103328472e-05 loss: 0.1397 (0.1502) time: 2.6061 data: 0.0059 max mem: 33369 +Epoch: [3] [ 660/1319] eta: 0:28:50 lr: 4.60434027485917e-05 loss: 0.1410 (0.1503) time: 2.5964 data: 0.0060 max mem: 33369 +Epoch: [3] [ 670/1319] eta: 0:28:24 lr: 4.6034794985538615e-05 loss: 0.1374 (0.1500) time: 2.5785 data: 0.0058 max mem: 33369 +Epoch: [3] [ 680/1319] eta: 0:27:57 lr: 4.602618704364706e-05 loss: 0.1392 (0.1500) time: 2.6015 data: 0.0057 max mem: 33369 +Epoch: [3] [ 690/1319] eta: 0:27:31 lr: 4.601757892287618e-05 loss: 0.1462 (0.1501) time: 2.6223 data: 0.0059 max mem: 33369 +Epoch: [3] [ 700/1319] eta: 0:27:05 lr: 4.600897062318506e-05 loss: 0.1538 (0.1506) time: 2.6288 data: 0.0059 max mem: 33369 +Epoch: [3] [ 710/1319] eta: 0:26:38 lr: 4.600036214453279e-05 loss: 0.1574 (0.1508) time: 2.5926 data: 0.0057 max mem: 33369 +Epoch: [3] [ 720/1319] eta: 0:26:11 lr: 4.599175348687844e-05 loss: 0.1377 (0.1505) time: 2.5690 data: 0.0057 max mem: 33369 +Epoch: [3] [ 730/1319] eta: 0:25:45 lr: 4.598314465018106e-05 loss: 0.1273 (0.1509) time: 2.6054 data: 0.0058 max mem: 33369 +Epoch: [3] [ 740/1319] eta: 0:25:19 lr: 4.5974535634399665e-05 loss: 0.1339 (0.1508) time: 2.6162 data: 0.0059 max mem: 33369 +Epoch: [3] [ 750/1319] eta: 0:24:53 lr: 4.596592643949328e-05 loss: 0.1345 (0.1507) time: 2.6196 data: 0.0058 max mem: 33369 +Epoch: [3] [ 760/1319] eta: 0:24:27 lr: 4.595731706542089e-05 loss: 0.1393 (0.1508) time: 2.6366 data: 0.0058 max mem: 33369 +Epoch: [3] [ 770/1319] eta: 0:24:01 lr: 4.5948707512141485e-05 loss: 0.1393 (0.1509) time: 2.6532 data: 0.0060 max mem: 33369 +Epoch: [3] [ 780/1319] eta: 0:23:34 lr: 4.594009777961402e-05 loss: 0.1317 (0.1505) time: 2.6143 data: 0.0058 max mem: 33369 +Epoch: [3] [ 790/1319] eta: 0:23:08 lr: 4.593148786779743e-05 loss: 0.1377 (0.1511) time: 2.5843 data: 0.0058 max mem: 33369 +Epoch: [3] [ 800/1319] eta: 0:22:41 lr: 4.592287777665063e-05 loss: 0.1548 (0.1510) time: 2.6005 data: 0.0059 max mem: 33369 +Epoch: [3] [ 810/1319] eta: 0:22:15 lr: 4.5914267506132555e-05 loss: 0.1376 (0.1511) time: 2.6038 data: 0.0061 max mem: 33369 +Epoch: [3] [ 820/1319] eta: 0:21:48 lr: 4.590565705620206e-05 loss: 0.1342 (0.1510) time: 2.6030 data: 0.0059 max mem: 33369 +Epoch: [3] [ 830/1319] eta: 0:21:22 lr: 4.589704642681802e-05 loss: 0.1465 (0.1509) time: 2.6221 data: 0.0057 max mem: 33369 +Epoch: [3] [ 840/1319] eta: 0:20:56 lr: 4.58884356179393e-05 loss: 0.1496 (0.1514) time: 2.6107 data: 0.0059 max mem: 33369 +Epoch: [3] [ 850/1319] eta: 0:20:29 lr: 4.5879824629524725e-05 loss: 0.1402 (0.1512) time: 2.5916 data: 0.0058 max mem: 33369 +Epoch: [3] [ 860/1319] eta: 0:20:03 lr: 4.5871213461533106e-05 loss: 0.1314 (0.1512) time: 2.6112 data: 0.0057 max mem: 33369 +Epoch: [3] [ 870/1319] eta: 0:19:37 lr: 4.5862602113923244e-05 loss: 0.1344 (0.1511) time: 2.6181 data: 0.0057 max mem: 33369 +Epoch: [3] [ 880/1319] eta: 0:19:11 lr: 4.585399058665391e-05 loss: 0.1292 (0.1509) time: 2.6078 data: 0.0060 max mem: 33369 +Epoch: [3] [ 890/1319] eta: 0:18:44 lr: 4.5845378879683885e-05 loss: 0.1278 (0.1509) time: 2.5945 data: 0.0059 max mem: 33369 +Epoch: [3] [ 900/1319] eta: 0:18:18 lr: 4.583676699297189e-05 loss: 0.1333 (0.1508) time: 2.5909 data: 0.0057 max mem: 33369 +Epoch: [3] [ 910/1319] eta: 0:17:52 lr: 4.582815492647665e-05 loss: 0.1333 (0.1507) time: 2.6177 data: 0.0059 max mem: 33369 +Epoch: [3] [ 920/1319] eta: 0:17:26 lr: 4.5819542680156885e-05 loss: 0.1491 (0.1513) time: 2.6357 data: 0.0059 max mem: 33369 +Epoch: [3] [ 930/1319] eta: 0:16:59 lr: 4.5810930253971277e-05 loss: 0.1480 (0.1512) time: 2.6025 data: 0.0058 max mem: 33369 +Epoch: [3] [ 940/1319] eta: 0:16:33 lr: 4.580231764787849e-05 loss: 0.1547 (0.1515) time: 2.6054 data: 0.0060 max mem: 33369 +Epoch: [3] [ 950/1319] eta: 0:16:07 lr: 4.579370486183719e-05 loss: 0.1547 (0.1515) time: 2.6366 data: 0.0062 max mem: 33369 +Epoch: [3] [ 960/1319] eta: 0:15:41 lr: 4.5785091895806004e-05 loss: 0.1426 (0.1515) time: 2.6273 data: 0.0061 max mem: 33369 +Epoch: [3] [ 970/1319] eta: 0:15:14 lr: 4.577647874974354e-05 loss: 0.1360 (0.1515) time: 2.6016 data: 0.0059 max mem: 33369 +Epoch: [3] [ 980/1319] eta: 0:14:48 lr: 4.57678654236084e-05 loss: 0.1251 (0.1511) time: 2.6028 data: 0.0059 max mem: 33369 +Epoch: [3] [ 990/1319] eta: 0:14:22 lr: 4.575925191735917e-05 loss: 0.1273 (0.1510) time: 2.6099 data: 0.0059 max mem: 33369 +Epoch: [3] [1000/1319] eta: 0:13:56 lr: 4.57506382309544e-05 loss: 0.1339 (0.1510) time: 2.6112 data: 0.0059 max mem: 33369 +Epoch: [3] [1010/1319] eta: 0:13:29 lr: 4.574202436435264e-05 loss: 0.1460 (0.1510) time: 2.6070 data: 0.0057 max mem: 33369 +Epoch: [3] [1020/1319] eta: 0:13:03 lr: 4.573341031751242e-05 loss: 0.1552 (0.1509) time: 2.6256 data: 0.0057 max mem: 33369 +Epoch: [3] [1030/1319] eta: 0:12:37 lr: 4.5724796090392234e-05 loss: 0.1316 (0.1509) time: 2.6334 data: 0.0057 max mem: 33369 +Epoch: [3] [1040/1319] eta: 0:12:11 lr: 4.571618168295058e-05 loss: 0.1200 (0.1506) time: 2.6186 data: 0.0057 max mem: 33369 +Epoch: [3] [1050/1319] eta: 0:11:44 lr: 4.570756709514592e-05 loss: 0.1185 (0.1504) time: 2.6093 data: 0.0059 max mem: 33369 +Epoch: [3] [1060/1319] eta: 0:11:18 lr: 4.569895232693671e-05 loss: 0.1369 (0.1504) time: 2.6006 data: 0.0058 max mem: 33369 +Epoch: [3] [1070/1319] eta: 0:10:52 lr: 4.569033737828139e-05 loss: 0.1411 (0.1503) time: 2.6183 data: 0.0056 max mem: 33369 +Epoch: [3] [1080/1319] eta: 0:10:26 lr: 4.568172224913836e-05 loss: 0.1211 (0.1501) time: 2.6294 data: 0.0057 max mem: 33369 +Epoch: [3] [1090/1319] eta: 0:10:00 lr: 4.567310693946603e-05 loss: 0.1211 (0.1501) time: 2.6354 data: 0.0057 max mem: 33369 +Epoch: [3] [1100/1319] eta: 0:09:33 lr: 4.566449144922278e-05 loss: 0.1385 (0.1500) time: 2.6221 data: 0.0057 max mem: 33369 +Epoch: [3] [1110/1319] eta: 0:09:07 lr: 4.565587577836695e-05 loss: 0.1379 (0.1501) time: 2.6267 data: 0.0058 max mem: 33369 +Epoch: [3] [1120/1319] eta: 0:08:41 lr: 4.5647259926856906e-05 loss: 0.1631 (0.1502) time: 2.6453 data: 0.0058 max mem: 33369 +Epoch: [3] [1130/1319] eta: 0:08:15 lr: 4.563864389465096e-05 loss: 0.1392 (0.1500) time: 2.6236 data: 0.0058 max mem: 33369 +Epoch: [3] [1140/1319] eta: 0:07:49 lr: 4.563002768170741e-05 loss: 0.1269 (0.1500) time: 2.6196 data: 0.0060 max mem: 33369 +Epoch: [3] [1150/1319] eta: 0:07:23 lr: 4.562141128798457e-05 loss: 0.1360 (0.1501) time: 2.6331 data: 0.0060 max mem: 33369 +Epoch: [3] [1160/1319] eta: 0:06:56 lr: 4.561279471344068e-05 loss: 0.1467 (0.1502) time: 2.6359 data: 0.0058 max mem: 33369 +Epoch: [3] [1170/1319] eta: 0:06:30 lr: 4.5604177958034e-05 loss: 0.1467 (0.1503) time: 2.6364 data: 0.0059 max mem: 33369 +Epoch: [3] [1180/1319] eta: 0:06:04 lr: 4.559556102172276e-05 loss: 0.1420 (0.1502) time: 2.6106 data: 0.0058 max mem: 33369 +Epoch: [3] [1190/1319] eta: 0:05:38 lr: 4.5586943904465176e-05 loss: 0.1147 (0.1502) time: 2.6139 data: 0.0056 max mem: 33369 +Epoch: [3] [1200/1319] eta: 0:05:11 lr: 4.557832660621944e-05 loss: 0.1156 (0.1501) time: 2.6451 data: 0.0057 max mem: 33369 +Epoch: [3] [1210/1319] eta: 0:04:45 lr: 4.556970912694373e-05 loss: 0.1325 (0.1501) time: 2.6272 data: 0.0059 max mem: 33369 +Epoch: [3] [1220/1319] eta: 0:04:19 lr: 4.5561091466596205e-05 loss: 0.1459 (0.1502) time: 2.6047 data: 0.0058 max mem: 33369 +Epoch: [3] [1230/1319] eta: 0:03:53 lr: 4.555247362513501e-05 loss: 0.1307 (0.1500) time: 2.6070 data: 0.0060 max mem: 33369 +Epoch: [3] [1240/1319] eta: 0:03:27 lr: 4.5543855602518245e-05 loss: 0.1240 (0.1500) time: 2.6068 data: 0.0060 max mem: 33369 +Epoch: [3] [1250/1319] eta: 0:03:00 lr: 4.553523739870403e-05 loss: 0.1264 (0.1499) time: 2.6165 data: 0.0057 max mem: 33369 +Epoch: [3] [1260/1319] eta: 0:02:34 lr: 4.552661901365045e-05 loss: 0.1406 (0.1500) time: 2.6313 data: 0.0056 max mem: 33369 +Epoch: [3] [1270/1319] eta: 0:02:08 lr: 4.551800044731557e-05 loss: 0.1373 (0.1499) time: 2.6291 data: 0.0058 max mem: 33369 +Epoch: [3] [1280/1319] eta: 0:01:42 lr: 4.550938169965743e-05 loss: 0.1308 (0.1498) time: 2.6161 data: 0.0061 max mem: 33369 +Epoch: [3] [1290/1319] eta: 0:01:16 lr: 4.550076277063406e-05 loss: 0.1414 (0.1498) time: 2.5908 data: 0.0060 max mem: 33369 +Epoch: [3] [1300/1319] eta: 0:00:49 lr: 4.549214366020347e-05 loss: 0.1417 (0.1500) time: 2.5840 data: 0.0059 max mem: 33369 +Epoch: [3] [1310/1319] eta: 0:00:23 lr: 4.5483524368323656e-05 loss: 0.1592 (0.1502) time: 2.6048 data: 0.0059 max mem: 33369 +Epoch: [3] Total time: 0:57:37 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 2:07:11 time: 2.9661 data: 2.8871 max mem: 33369 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 100/2573] eta: 0:04:08 time: 0.0716 data: 0.0011 max mem: 33369 +Test: [ 200/2573] eta: 0:03:27 time: 0.0732 data: 0.0011 max mem: 33369 +Test: [ 300/2573] eta: 0:03:06 time: 0.0751 data: 0.0011 max mem: 33369 +Test: [ 400/2573] eta: 0:02:53 time: 0.0751 data: 0.0011 max mem: 33369 +Test: [ 500/2573] eta: 0:02:43 time: 0.0736 data: 0.0011 max mem: 33369 +Test: [ 600/2573] eta: 0:02:33 time: 0.0737 data: 0.0011 max mem: 33369 +Test: [ 700/2573] eta: 0:02:25 time: 0.0739 data: 0.0011 max mem: 33369 +Test: [ 800/2573] eta: 0:02:17 time: 0.0771 data: 0.0011 max mem: 33369 +Test: [ 900/2573] eta: 0:02:08 time: 0.0739 data: 0.0011 max mem: 33369 +Test: [1000/2573] eta: 0:02:00 time: 0.0739 data: 0.0011 max mem: 33369 +Test: [1100/2573] eta: 0:01:52 time: 0.0739 data: 0.0011 max mem: 33369 +Test: [1200/2573] eta: 0:01:44 time: 0.0739 data: 0.0011 max mem: 33369 +Test: [1300/2573] eta: 0:01:37 time: 0.0738 data: 0.0011 max mem: 33369 +Test: [1400/2573] eta: 0:01:29 time: 0.0723 data: 0.0011 max mem: 33369 +Test: [1500/2573] eta: 0:01:21 time: 0.0739 data: 0.0011 max mem: 33369 +Test: [1600/2573] eta: 0:01:13 time: 0.0772 data: 0.0011 max mem: 33369 +Test: [1700/2573] eta: 0:01:06 time: 0.0722 data: 0.0011 max mem: 33369 +Test: [1800/2573] eta: 0:00:58 time: 0.0756 data: 0.0011 max mem: 33369 +Test: [1900/2573] eta: 0:00:50 time: 0.0723 data: 0.0011 max mem: 33369 +Test: [2000/2573] eta: 0:00:43 time: 0.0739 data: 0.0011 max mem: 33369 +Test: [2100/2573] eta: 0:00:35 time: 0.0755 data: 0.0011 max mem: 33369 +Test: [2200/2573] eta: 0:00:28 time: 0.0755 data: 0.0011 max mem: 33369 +Test: [2300/2573] eta: 0:00:20 time: 0.0756 data: 0.0011 max mem: 33369 +Test: [2400/2573] eta: 0:00:12 time: 0.0706 data: 0.0011 max mem: 33369 +Test: [2500/2573] eta: 0:00:05 time: 0.0738 data: 0.0011 max mem: 33369 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: Total time: 0:03:13 +Final results: +Mean IoU is 50.27 + + precision@0.5 = 54.33 + precision@0.6 = 45.63 + precision@0.7 = 35.76 + precision@0.8 = 25.25 + precision@0.9 = 9.19 + overall IoU = 52.17 + +Average object IoU 50.27398527215043 +Overall IoU 52.16771697998047 +Better epoch: 3 + +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [4] [ 0/1319] eta: 1:31:33 lr: 4.547576685045799e-05 loss: 0.1068 (0.1068) time: 4.1646 data: 1.4942 max mem: 33369 +Epoch: [4] [ 10/1319] eta: 1:00:25 lr: 4.546714721370884e-05 loss: 0.1146 (0.1201) time: 2.7697 data: 0.1416 max mem: 33369 +Epoch: [4] [ 20/1319] eta: 0:58:28 lr: 4.5458527395388535e-05 loss: 0.1120 (0.1220) time: 2.6281 data: 0.0061 max mem: 33369 +Epoch: [4] [ 30/1319] eta: 0:57:20 lr: 4.544990739545498e-05 loss: 0.1120 (0.1276) time: 2.6142 data: 0.0060 max mem: 33369 +Epoch: [4] [ 40/1319] eta: 0:56:33 lr: 4.544128721386609e-05 loss: 0.1277 (0.1292) time: 2.6030 data: 0.0061 max mem: 33369 +Epoch: [4] [ 50/1319] eta: 0:56:14 lr: 4.543266685057974e-05 loss: 0.1138 (0.1246) time: 2.6438 data: 0.0060 max mem: 33369 +Epoch: [4] [ 60/1319] eta: 0:55:43 lr: 4.54240463055538e-05 loss: 0.1020 (0.1233) time: 2.6613 data: 0.0060 max mem: 33369 +Epoch: [4] [ 70/1319] eta: 0:55:16 lr: 4.541542557874611e-05 loss: 0.1161 (0.1232) time: 2.6449 data: 0.0061 max mem: 33369 +Epoch: [4] [ 80/1319] eta: 0:54:51 lr: 4.540680467011449e-05 loss: 0.1296 (0.1278) time: 2.6575 data: 0.0062 max mem: 33369 +Epoch: [4] [ 90/1319] eta: 0:54:24 lr: 4.5398183579616753e-05 loss: 0.1421 (0.1288) time: 2.6606 data: 0.0063 max mem: 33369 +Epoch: [4] [ 100/1319] eta: 0:53:52 lr: 4.5389562307210684e-05 loss: 0.1241 (0.1281) time: 2.6329 data: 0.0063 max mem: 33369 +Epoch: [4] [ 110/1319] eta: 0:53:19 lr: 4.5380940852854056e-05 loss: 0.1100 (0.1282) time: 2.6001 data: 0.0061 max mem: 33369 +Epoch: [4] [ 120/1319] eta: 0:52:58 lr: 4.537231921650461e-05 loss: 0.1160 (0.1285) time: 2.6486 data: 0.0059 max mem: 33369 +Epoch: [4] [ 130/1319] eta: 0:52:26 lr: 4.53636973981201e-05 loss: 0.1202 (0.1278) time: 2.6470 data: 0.0059 max mem: 33369 +Epoch: [4] [ 140/1319] eta: 0:51:55 lr: 4.535507539765821e-05 loss: 0.1364 (0.1291) time: 2.5891 data: 0.0060 max mem: 33369 +Epoch: [4] [ 150/1319] eta: 0:51:28 lr: 4.534645321507665e-05 loss: 0.1401 (0.1295) time: 2.6144 data: 0.0059 max mem: 33369 +Epoch: [4] [ 160/1319] eta: 0:51:02 lr: 4.53378308503331e-05 loss: 0.1292 (0.1303) time: 2.6421 data: 0.0058 max mem: 33369 +Epoch: [4] [ 170/1319] eta: 0:50:36 lr: 4.532920830338521e-05 loss: 0.1390 (0.1321) time: 2.6433 data: 0.0058 max mem: 33369 +Epoch: [4] [ 180/1319] eta: 0:50:08 lr: 4.5320585574190625e-05 loss: 0.1415 (0.1322) time: 2.6338 data: 0.0057 max mem: 33369 +Epoch: [4] [ 190/1319] eta: 0:49:41 lr: 4.5311962662706955e-05 loss: 0.1221 (0.1322) time: 2.6298 data: 0.0058 max mem: 33369 +Epoch: [4] [ 200/1319] eta: 0:49:13 lr: 4.5303339568891794e-05 loss: 0.1116 (0.1313) time: 2.6243 data: 0.0060 max mem: 33369 +Epoch: [4] [ 210/1319] eta: 0:48:46 lr: 4.529471629270274e-05 loss: 0.1131 (0.1309) time: 2.6202 data: 0.0059 max mem: 33369 +Epoch: [4] [ 220/1319] eta: 0:48:18 lr: 4.5286092834097356e-05 loss: 0.1137 (0.1309) time: 2.6156 data: 0.0058 max mem: 33369 +Epoch: [4] [ 230/1319] eta: 0:47:53 lr: 4.527746919303318e-05 loss: 0.1126 (0.1306) time: 2.6304 data: 0.0060 max mem: 33369 +Epoch: [4] [ 240/1319] eta: 0:47:25 lr: 4.5268845369467734e-05 loss: 0.1133 (0.1302) time: 2.6379 data: 0.0062 max mem: 33369 +Epoch: [4] [ 250/1319] eta: 0:46:57 lr: 4.526022136335852e-05 loss: 0.1315 (0.1305) time: 2.6066 data: 0.0061 max mem: 33369 +Epoch: [4] [ 260/1319] eta: 0:46:31 lr: 4.525159717466304e-05 loss: 0.1374 (0.1317) time: 2.6153 data: 0.0060 max mem: 33369 +Epoch: [4] [ 270/1319] eta: 0:46:03 lr: 4.524297280333875e-05 loss: 0.1341 (0.1316) time: 2.6125 data: 0.0061 max mem: 33369 +Epoch: [4] [ 280/1319] eta: 0:45:36 lr: 4.5234348249343114e-05 loss: 0.1129 (0.1313) time: 2.6038 data: 0.0059 max mem: 33369 +Epoch: [4] [ 290/1319] eta: 0:45:09 lr: 4.522572351263354e-05 loss: 0.1162 (0.1318) time: 2.6202 data: 0.0058 max mem: 33369 +Epoch: [4] [ 300/1319] eta: 0:44:42 lr: 4.521709859316746e-05 loss: 0.1338 (0.1320) time: 2.6162 data: 0.0059 max mem: 33369 +Epoch: [4] [ 310/1319] eta: 0:44:15 lr: 4.520847349090225e-05 loss: 0.1226 (0.1317) time: 2.6132 data: 0.0059 max mem: 33369 +Epoch: [4] [ 320/1319] eta: 0:43:47 lr: 4.5199848205795306e-05 loss: 0.1112 (0.1315) time: 2.6009 data: 0.0058 max mem: 33369 +Epoch: [4] [ 330/1319] eta: 0:43:20 lr: 4.519122273780396e-05 loss: 0.1133 (0.1312) time: 2.5969 data: 0.0057 max mem: 33369 +Epoch: [4] [ 340/1319] eta: 0:42:53 lr: 4.518259708688556e-05 loss: 0.1160 (0.1312) time: 2.6040 data: 0.0057 max mem: 33369 +Epoch: [4] [ 350/1319] eta: 0:42:27 lr: 4.5173971252997424e-05 loss: 0.1232 (0.1313) time: 2.6083 data: 0.0059 max mem: 33369 +Epoch: [4] [ 360/1319] eta: 0:42:00 lr: 4.5165345236096837e-05 loss: 0.1308 (0.1314) time: 2.6184 data: 0.0059 max mem: 33369 +Epoch: [4] [ 370/1319] eta: 0:41:33 lr: 4.5156719036141086e-05 loss: 0.1472 (0.1319) time: 2.6097 data: 0.0058 max mem: 33369 +Epoch: [4] [ 380/1319] eta: 0:41:06 lr: 4.5148092653087434e-05 loss: 0.1395 (0.1326) time: 2.6077 data: 0.0059 max mem: 33369 +Epoch: [4] [ 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(0.1320) time: 2.6341 data: 0.0058 max mem: 33369 +Epoch: [4] [ 790/1319] eta: 0:23:08 lr: 4.4794252770532266e-05 loss: 0.1128 (0.1318) time: 2.6501 data: 0.0058 max mem: 33369 +Epoch: [4] [ 800/1319] eta: 0:22:41 lr: 4.4785618658517975e-05 loss: 0.1128 (0.1319) time: 2.6324 data: 0.0058 max mem: 33369 +Epoch: [4] [ 810/1319] eta: 0:22:15 lr: 4.477698436154974e-05 loss: 0.1130 (0.1317) time: 2.6229 data: 0.0057 max mem: 33369 +Epoch: [4] [ 820/1319] eta: 0:21:49 lr: 4.476834987958398e-05 loss: 0.1085 (0.1318) time: 2.6181 data: 0.0057 max mem: 33369 +Epoch: [4] [ 830/1319] eta: 0:21:22 lr: 4.4759715212577086e-05 loss: 0.1184 (0.1319) time: 2.6105 data: 0.0058 max mem: 33369 +Epoch: [4] [ 840/1319] eta: 0:20:56 lr: 4.475108036048542e-05 loss: 0.1266 (0.1320) time: 2.5997 data: 0.0057 max mem: 33369 +Epoch: [4] [ 850/1319] eta: 0:20:30 lr: 4.4742445323265344e-05 loss: 0.1290 (0.1322) time: 2.6220 data: 0.0058 max mem: 33369 +Epoch: [4] [ 860/1319] eta: 0:20:04 lr: 4.473381010087318e-05 loss: 0.1218 (0.1320) time: 2.6476 data: 0.0059 max mem: 33369 +Epoch: [4] [ 870/1319] eta: 0:19:37 lr: 4.4725174693265234e-05 loss: 0.1114 (0.1320) time: 2.6185 data: 0.0058 max mem: 33369 +Epoch: [4] [ 880/1319] eta: 0:19:11 lr: 4.471653910039782e-05 loss: 0.1332 (0.1320) time: 2.5981 data: 0.0057 max mem: 33369 +Epoch: [4] [ 890/1319] eta: 0:18:45 lr: 4.4707903322227184e-05 loss: 0.1373 (0.1319) time: 2.6061 data: 0.0058 max mem: 33369 +Epoch: [4] [ 900/1319] eta: 0:18:19 lr: 4.469926735870959e-05 loss: 0.1109 (0.1318) time: 2.6270 data: 0.0060 max mem: 33369 +Epoch: [4] [ 910/1319] eta: 0:17:52 lr: 4.4690631209801266e-05 loss: 0.1137 (0.1317) time: 2.6425 data: 0.0059 max mem: 33369 +Epoch: [4] [ 920/1319] eta: 0:17:26 lr: 4.4681994875458425e-05 loss: 0.1183 (0.1317) time: 2.6318 data: 0.0060 max mem: 33369 +Epoch: [4] [ 930/1319] eta: 0:17:00 lr: 4.467335835563727e-05 loss: 0.1183 (0.1315) time: 2.6375 data: 0.0060 max mem: 33369 +Epoch: [4] [ 940/1319] eta: 0:16:34 lr: 4.466472165029396e-05 loss: 0.1173 (0.1316) time: 2.6494 data: 0.0059 max mem: 33369 +Epoch: [4] [ 950/1319] eta: 0:16:08 lr: 4.4656084759384645e-05 loss: 0.1319 (0.1316) time: 2.6393 data: 0.0059 max mem: 33369 +Epoch: [4] [ 960/1319] eta: 0:15:42 lr: 4.464744768286547e-05 loss: 0.1319 (0.1317) time: 2.6250 data: 0.0058 max mem: 33369 +Epoch: [4] [ 970/1319] eta: 0:15:15 lr: 4.463881042069255e-05 loss: 0.1268 (0.1316) time: 2.6258 data: 0.0058 max mem: 33369 +Epoch: [4] [ 980/1319] eta: 0:14:49 lr: 4.463017297282197e-05 loss: 0.1149 (0.1315) time: 2.6226 data: 0.0061 max mem: 33369 +Epoch: [4] [ 990/1319] eta: 0:14:23 lr: 4.4621535339209816e-05 loss: 0.1197 (0.1315) time: 2.6330 data: 0.0060 max mem: 33369 +Epoch: [4] [1000/1319] eta: 0:13:57 lr: 4.461289751981212e-05 loss: 0.1178 (0.1314) time: 2.6314 data: 0.0058 max mem: 33369 +Epoch: [4] [1010/1319] eta: 0:13:30 lr: 4.460425951458493e-05 loss: 0.1191 (0.1316) time: 2.6201 data: 0.0058 max mem: 33369 +Epoch: [4] [1020/1319] eta: 0:13:04 lr: 4.459562132348427e-05 loss: 0.1280 (0.1317) time: 2.6096 data: 0.0059 max mem: 33369 +Epoch: [4] [1030/1319] eta: 0:12:38 lr: 4.458698294646612e-05 loss: 0.1119 (0.1315) time: 2.5890 data: 0.0057 max mem: 33369 +Epoch: [4] [1040/1319] eta: 0:12:11 lr: 4.457834438348646e-05 loss: 0.1011 (0.1312) time: 2.5830 data: 0.0057 max mem: 33369 +Epoch: [4] [1050/1319] eta: 0:11:45 lr: 4.456970563450125e-05 loss: 0.1077 (0.1313) time: 2.5950 data: 0.0058 max mem: 33369 +Epoch: [4] [1060/1319] eta: 0:11:19 lr: 4.456106669946641e-05 loss: 0.1206 (0.1313) time: 2.6144 data: 0.0060 max mem: 33369 +Epoch: [4] [1070/1319] eta: 0:10:53 lr: 4.4552427578337865e-05 loss: 0.1155 (0.1312) time: 2.6123 data: 0.0059 max mem: 33369 +Epoch: [4] [1080/1319] eta: 0:10:26 lr: 4.45437882710715e-05 loss: 0.1161 (0.1313) time: 2.5990 data: 0.0057 max mem: 33369 +Epoch: [4] [1090/1319] eta: 0:10:00 lr: 4.453514877762321e-05 loss: 0.1151 (0.1313) time: 2.5943 data: 0.0057 max mem: 33369 +Epoch: [4] 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+Epoch: [4] [1180/1319] eta: 0:06:04 lr: 4.4457384951110855e-05 loss: 0.1176 (0.1319) time: 2.6177 data: 0.0059 max mem: 33369 +Epoch: [4] [1190/1319] eta: 0:05:38 lr: 4.44487435934119e-05 loss: 0.1198 (0.1319) time: 2.6173 data: 0.0059 max mem: 33369 +Epoch: [4] [1200/1319] eta: 0:05:12 lr: 4.4440102049044326e-05 loss: 0.1075 (0.1319) time: 2.6429 data: 0.0058 max mem: 33369 +Epoch: [4] [1210/1319] eta: 0:04:45 lr: 4.443146031796374e-05 loss: 0.1074 (0.1318) time: 2.6426 data: 0.0057 max mem: 33369 +Epoch: [4] [1220/1319] eta: 0:04:19 lr: 4.442281840012577e-05 loss: 0.1153 (0.1320) time: 2.6259 data: 0.0058 max mem: 33369 +Epoch: [4] [1230/1319] eta: 0:03:53 lr: 4.441417629548601e-05 loss: 0.1383 (0.1320) time: 2.6116 data: 0.0058 max mem: 33369 +Epoch: [4] [1240/1319] eta: 0:03:27 lr: 4.4405534004000035e-05 loss: 0.1345 (0.1322) time: 2.6118 data: 0.0058 max mem: 33369 +Epoch: [4] [1250/1319] eta: 0:03:00 lr: 4.439689152562339e-05 loss: 0.1333 (0.1322) time: 2.6158 data: 0.0057 max mem: 33369 +Epoch: [4] [1260/1319] eta: 0:02:34 lr: 4.438824886031161e-05 loss: 0.1326 (0.1323) time: 2.6176 data: 0.0058 max mem: 33369 +Epoch: [4] [1270/1319] eta: 0:02:08 lr: 4.437960600802022e-05 loss: 0.1230 (0.1322) time: 2.6501 data: 0.0058 max mem: 33369 +Epoch: [4] [1280/1319] eta: 0:01:42 lr: 4.4370962968704706e-05 loss: 0.1232 (0.1324) time: 2.6459 data: 0.0058 max mem: 33369 +Epoch: [4] [1290/1319] eta: 0:01:16 lr: 4.436231974232054e-05 loss: 0.1219 (0.1322) time: 2.6125 data: 0.0058 max mem: 33369 +Epoch: [4] [1300/1319] eta: 0:00:49 lr: 4.435367632882316e-05 loss: 0.1050 (0.1321) time: 2.5818 data: 0.0058 max mem: 33369 +Epoch: [4] [1310/1319] eta: 0:00:23 lr: 4.434503272816803e-05 loss: 0.1043 (0.1320) time: 2.5932 data: 0.0058 max mem: 33369 +Epoch: [4] Total time: 0:57:38 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 2:03:25 time: 2.8781 data: 2.7898 max mem: 33369 +Test: [ 100/2573] eta: 0:04:06 time: 0.0716 data: 0.0011 max mem: 33369 +Test: [ 200/2573] eta: 0:03:26 time: 0.0732 data: 0.0011 max mem: 33369 +Test: [ 300/2573] eta: 0:03:06 time: 0.0749 data: 0.0011 max mem: 33369 +Test: [ 400/2573] eta: 0:02:53 time: 0.0751 data: 0.0011 max mem: 33369 +Test: [ 500/2573] eta: 0:02:42 time: 0.0735 data: 0.0011 max mem: 33369 +Test: [ 600/2573] eta: 0:02:33 time: 0.0736 data: 0.0011 max mem: 33369 +Test: [ 700/2573] eta: 0:02:25 time: 0.0737 data: 0.0011 max mem: 33369 +Test: [ 800/2573] eta: 0:02:16 time: 0.0770 data: 0.0011 max mem: 33369 +Test: [ 900/2573] eta: 0:02:08 time: 0.0737 data: 0.0011 max mem: 33369 +Test: [1000/2573] eta: 0:02:00 time: 0.0738 data: 0.0011 max mem: 33369 +Test: [1100/2573] eta: 0:01:52 time: 0.0739 data: 0.0011 max mem: 33369 +Test: [1200/2573] eta: 0:01:44 time: 0.0737 data: 0.0011 max mem: 33369 +Test: [1300/2573] eta: 0:01:36 time: 0.0739 data: 0.0011 max mem: 33369 +Test: [1400/2573] eta: 0:01:28 time: 0.0722 data: 0.0011 max mem: 33369 +Test: [1500/2573] eta: 0:01:21 time: 0.0739 data: 0.0011 max mem: 33369 +Test: [1600/2573] eta: 0:01:13 time: 0.0771 data: 0.0011 max mem: 33369 +Test: [1700/2573] eta: 0:01:05 time: 0.0720 data: 0.0011 max mem: 33369 +Test: [1800/2573] eta: 0:00:58 time: 0.0755 data: 0.0011 max mem: 33369 +Test: [1900/2573] eta: 0:00:50 time: 0.0720 data: 0.0011 max mem: 33369 +Test: [2000/2573] eta: 0:00:43 time: 0.0737 data: 0.0011 max mem: 33369 +Test: [2100/2573] eta: 0:00:35 time: 0.0753 data: 0.0011 max mem: 33369 +Test: [2200/2573] eta: 0:00:27 time: 0.0754 data: 0.0011 max mem: 33369 +Test: [2300/2573] eta: 0:00:20 time: 0.0753 data: 0.0011 max mem: 33369 +Test: [2400/2573] eta: 0:00:12 time: 0.0704 data: 0.0011 max mem: 33369 +Test: [2500/2573] eta: 0:00:05 time: 0.0736 data: 0.0011 max mem: 33369 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: Total time: 0:03:12 +Final results: +Mean IoU is 49.63 + + precision@0.5 = 55.09 + precision@0.6 = 47.47 + precision@0.7 = 38.01 + precision@0.8 = 26.41 + precision@0.9 = 9.40 + overall IoU = 49.85 + +Average object IoU 49.628334676872015 +Overall IoU 49.84574508666992 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [5] [ 0/1319] eta: 3:08:23 lr: 4.433725332752167e-05 loss: 0.1324 (0.1324) time: 8.5696 data: 1.4883 max mem: 33369 +Epoch: [5] [ 10/1319] eta: 1:09:21 lr: 4.432860937114392e-05 loss: 0.1007 (0.1135) time: 3.1788 data: 0.1412 max mem: 33369 +Epoch: [5] [ 20/1319] eta: 1:03:06 lr: 4.4319965227479046e-05 loss: 0.1007 (0.1168) time: 2.6320 data: 0.0060 max mem: 33369 +Epoch: [5] [ 30/1319] eta: 1:00:30 lr: 4.43113208964824e-05 loss: 0.1144 (0.1183) time: 2.6170 data: 0.0059 max mem: 33369 +Epoch: [5] [ 40/1319] eta: 0:59:07 lr: 4.43026763781093e-05 loss: 0.1193 (0.1187) time: 2.6260 data: 0.0062 max mem: 33369 +Epoch: [5] [ 50/1319] eta: 0:58:08 lr: 4.429403167231508e-05 loss: 0.1235 (0.1227) time: 2.6443 data: 0.0061 max mem: 33369 +Epoch: [5] [ 60/1319] eta: 0:57:14 lr: 4.428538677905502e-05 loss: 0.1235 (0.1206) time: 2.6335 data: 0.0060 max mem: 33369 +Epoch: [5] [ 70/1319] eta: 0:56:29 lr: 4.4276741698284395e-05 loss: 0.1005 (0.1214) time: 2.6240 data: 0.0059 max mem: 33369 +Epoch: [5] [ 80/1319] eta: 0:55:50 lr: 4.4268096429958464e-05 loss: 0.1125 (0.1225) time: 2.6309 data: 0.0060 max mem: 33369 +Epoch: [5] [ 90/1319] eta: 0:55:09 lr: 4.425945097403244e-05 loss: 0.1098 (0.1207) time: 2.6187 data: 0.0064 max mem: 33369 +Epoch: [5] [ 100/1319] eta: 0:54:33 lr: 4.425080533046155e-05 loss: 0.0943 (0.1181) time: 2.6085 data: 0.0061 max mem: 33369 +Epoch: [5] [ 110/1319] eta: 0:53:58 lr: 4.424215949920098e-05 loss: 0.1021 (0.1198) time: 2.6125 data: 0.0059 max mem: 33369 +Epoch: [5] [ 120/1319] eta: 0:53:21 lr: 4.423351348020589e-05 loss: 0.1358 (0.1223) time: 2.5973 data: 0.0061 max mem: 33369 +Epoch: [5] [ 130/1319] eta: 0:52:49 lr: 4.4224867273431445e-05 loss: 0.1017 (0.1205) time: 2.5981 data: 0.0062 max mem: 33369 +Epoch: [5] [ 140/1319] eta: 0:52:19 lr: 4.421622087883277e-05 loss: 0.0942 (0.1202) time: 2.6179 data: 0.0061 max mem: 33369 +Epoch: [5] [ 150/1319] eta: 0:51:49 lr: 4.4207574296364965e-05 loss: 0.1023 (0.1189) time: 2.6194 data: 0.0061 max mem: 33369 +Epoch: [5] [ 160/1319] eta: 0:51:18 lr: 4.419892752598312e-05 loss: 0.0989 (0.1190) time: 2.6090 data: 0.0061 max mem: 33369 +Epoch: [5] [ 170/1319] eta: 0:50:53 lr: 4.419028056764231e-05 loss: 0.1139 (0.1208) time: 2.6391 data: 0.0060 max mem: 33369 +Epoch: [5] [ 180/1319] eta: 0:50:23 lr: 4.418163342129758e-05 loss: 0.1172 (0.1214) time: 2.6392 data: 0.0060 max mem: 33369 +Epoch: [5] [ 190/1319] eta: 0:49:56 lr: 4.417298608690395e-05 loss: 0.1109 (0.1214) time: 2.6217 data: 0.0064 max mem: 33369 +Epoch: [5] [ 200/1319] eta: 0:49:28 lr: 4.416433856441643e-05 loss: 0.1099 (0.1208) time: 2.6400 data: 0.0064 max mem: 33369 +Epoch: [5] [ 210/1319] eta: 0:48:59 lr: 4.415569085379001e-05 loss: 0.1042 (0.1210) time: 2.6222 data: 0.0063 max mem: 33369 +Epoch: [5] [ 220/1319] eta: 0:48:32 lr: 4.4147042954979643e-05 loss: 0.1224 (0.1216) time: 2.6182 data: 0.0061 max mem: 33369 +Epoch: [5] [ 230/1319] eta: 0:48:06 lr: 4.413839486794028e-05 loss: 0.1359 (0.1223) time: 2.6490 data: 0.0061 max mem: 33369 +Epoch: [5] [ 240/1319] eta: 0:47:36 lr: 4.412974659262685e-05 loss: 0.1209 (0.1228) time: 2.6203 data: 0.0061 max mem: 33369 +Epoch: [5] [ 250/1319] eta: 0:47:08 lr: 4.412109812899424e-05 loss: 0.1209 (0.1228) time: 2.5958 data: 0.0059 max mem: 33369 +Epoch: [5] [ 260/1319] eta: 0:46:41 lr: 4.411244947699735e-05 loss: 0.1141 (0.1226) time: 2.6248 data: 0.0059 max mem: 33369 +Epoch: [5] [ 270/1319] eta: 0:46:14 lr: 4.4103800636591036e-05 loss: 0.1191 (0.1225) time: 2.6291 data: 0.0060 max mem: 33369 +Epoch: [5] [ 280/1319] eta: 0:45:47 lr: 4.409515160773014e-05 loss: 0.1184 (0.1227) time: 2.6270 data: 0.0060 max mem: 33369 +Epoch: [5] [ 290/1319] eta: 0:45:19 lr: 4.408650239036947e-05 loss: 0.1176 (0.1225) time: 2.6134 data: 0.0061 max mem: 33369 +Epoch: [5] [ 300/1319] eta: 0:44:50 lr: 4.407785298446384e-05 loss: 0.1100 (0.1223) time: 2.5869 data: 0.0060 max mem: 33369 +Epoch: [5] [ 310/1319] eta: 0:44:25 lr: 4.406920338996803e-05 loss: 0.1162 (0.1222) time: 2.6231 data: 0.0059 max mem: 33369 +Epoch: [5] [ 320/1319] eta: 0:43:57 lr: 4.406055360683679e-05 loss: 0.1162 (0.1228) time: 2.6360 data: 0.0060 max mem: 33369 +Epoch: [5] [ 330/1319] eta: 0:43:31 lr: 4.4051903635024855e-05 loss: 0.1244 (0.1232) time: 2.6182 data: 0.0060 max mem: 33369 +Epoch: [5] [ 340/1319] eta: 0:43:04 lr: 4.404325347448695e-05 loss: 0.1293 (0.1232) time: 2.6346 data: 0.0058 max mem: 33369 +Epoch: [5] [ 350/1319] eta: 0:42:38 lr: 4.403460312517776e-05 loss: 0.1035 (0.1230) time: 2.6358 data: 0.0058 max mem: 33369 +Epoch: [5] [ 360/1319] eta: 0:42:10 lr: 4.402595258705198e-05 loss: 0.1211 (0.1232) time: 2.6100 data: 0.0060 max mem: 33369 +Epoch: [5] [ 370/1319] eta: 0:41:44 lr: 4.401730186006425e-05 loss: 0.1287 (0.1237) time: 2.6197 data: 0.0062 max mem: 33369 +Epoch: [5] [ 380/1319] eta: 0:41:17 lr: 4.40086509441692e-05 loss: 0.1201 (0.1238) time: 2.6466 data: 0.0061 max mem: 33369 +Epoch: [5] [ 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2.6421 data: 0.0060 max mem: 33369 +Epoch: [5] [ 710/1319] eta: 0:26:42 lr: 4.372306444447641e-05 loss: 0.1288 (0.1234) time: 2.6705 data: 0.0061 max mem: 33369 +Epoch: [5] [ 720/1319] eta: 0:26:16 lr: 4.3714407078590355e-05 loss: 0.1148 (0.1234) time: 2.6651 data: 0.0058 max mem: 33369 +Epoch: [5] [ 730/1319] eta: 0:25:49 lr: 4.370574952219595e-05 loss: 0.1016 (0.1233) time: 2.6258 data: 0.0058 max mem: 33369 +Epoch: [5] [ 740/1319] eta: 0:25:23 lr: 4.369709177524708e-05 loss: 0.1004 (0.1230) time: 2.6275 data: 0.0059 max mem: 33369 +Epoch: [5] [ 750/1319] eta: 0:24:56 lr: 4.36884338376976e-05 loss: 0.1023 (0.1231) time: 2.6060 data: 0.0057 max mem: 33369 +Epoch: [5] [ 760/1319] eta: 0:24:30 lr: 4.3679775709501325e-05 loss: 0.1252 (0.1233) time: 2.6166 data: 0.0059 max mem: 33369 +Epoch: [5] [ 770/1319] eta: 0:24:04 lr: 4.3671117390612085e-05 loss: 0.1357 (0.1232) time: 2.6480 data: 0.0061 max mem: 33369 +Epoch: [5] [ 780/1319] eta: 0:23:38 lr: 4.366245888098367e-05 loss: 0.1055 (0.1235) time: 2.6355 data: 0.0060 max mem: 33369 +Epoch: [5] [ 790/1319] eta: 0:23:11 lr: 4.3653800180569845e-05 loss: 0.1063 (0.1234) time: 2.6311 data: 0.0058 max mem: 33369 +Epoch: [5] [ 800/1319] eta: 0:22:45 lr: 4.364514128932435e-05 loss: 0.1117 (0.1234) time: 2.6371 data: 0.0058 max mem: 33369 +Epoch: [5] [ 810/1319] eta: 0:22:19 lr: 4.363648220720092e-05 loss: 0.0998 (0.1232) time: 2.6462 data: 0.0061 max mem: 33369 +Epoch: [5] [ 820/1319] eta: 0:21:52 lr: 4.3627822934153263e-05 loss: 0.0998 (0.1231) time: 2.6324 data: 0.0061 max mem: 33369 +Epoch: [5] [ 830/1319] eta: 0:21:26 lr: 4.361916347013505e-05 loss: 0.0998 (0.1231) time: 2.6134 data: 0.0059 max mem: 33369 +Epoch: [5] [ 840/1319] eta: 0:21:00 lr: 4.361050381509995e-05 loss: 0.1220 (0.1231) time: 2.6143 data: 0.0060 max mem: 33369 +Epoch: [5] [ 850/1319] eta: 0:20:33 lr: 4.3601843969001596e-05 loss: 0.1220 (0.1232) time: 2.6099 data: 0.0060 max mem: 33369 +Epoch: [5] [ 860/1319] eta: 0:20:07 lr: 4.359318393179363e-05 loss: 0.1220 (0.1234) time: 2.6049 data: 0.0059 max mem: 33369 +Epoch: [5] [ 870/1319] eta: 0:19:40 lr: 4.3584523703429616e-05 loss: 0.1290 (0.1237) time: 2.6057 data: 0.0059 max mem: 33369 +Epoch: [5] [ 880/1319] eta: 0:19:14 lr: 4.357586328386315e-05 loss: 0.1233 (0.1237) time: 2.5916 data: 0.0058 max mem: 33369 +Epoch: [5] [ 890/1319] eta: 0:18:47 lr: 4.356720267304778e-05 loss: 0.1085 (0.1236) time: 2.6056 data: 0.0058 max mem: 33369 +Epoch: [5] [ 900/1319] eta: 0:18:21 lr: 4.3558541870937056e-05 loss: 0.1098 (0.1234) time: 2.6391 data: 0.0059 max mem: 33369 +Epoch: [5] [ 910/1319] eta: 0:17:55 lr: 4.354988087748445e-05 loss: 0.0978 (0.1231) time: 2.6288 data: 0.0062 max mem: 33369 +Epoch: [5] [ 920/1319] eta: 0:17:28 lr: 4.35412196926435e-05 loss: 0.0978 (0.1231) time: 2.6045 data: 0.0061 max mem: 33369 +Epoch: [5] [ 930/1319] eta: 0:17:02 lr: 4.353255831636764e-05 loss: 0.1217 (0.1233) time: 2.6008 data: 0.0059 max mem: 33369 +Epoch: [5] [ 940/1319] eta: 0:16:36 lr: 4.352389674861032e-05 loss: 0.1109 (0.1233) time: 2.6163 data: 0.0060 max mem: 33369 +Epoch: [5] [ 950/1319] eta: 0:16:09 lr: 4.3515234989324975e-05 loss: 0.1109 (0.1236) time: 2.6311 data: 0.0061 max mem: 33369 +Epoch: [5] [ 960/1319] eta: 0:15:43 lr: 4.350657303846501e-05 loss: 0.1230 (0.1235) time: 2.6123 data: 0.0059 max mem: 33369 +Epoch: [5] [ 970/1319] eta: 0:15:17 lr: 4.34979108959838e-05 loss: 0.1076 (0.1236) time: 2.6246 data: 0.0060 max mem: 33369 +Epoch: [5] [ 980/1319] eta: 0:14:51 lr: 4.348924856183469e-05 loss: 0.1110 (0.1237) time: 2.6482 data: 0.0061 max mem: 33369 +Epoch: [5] [ 990/1319] eta: 0:14:25 lr: 4.348058603597104e-05 loss: 0.1338 (0.1237) time: 2.6613 data: 0.0058 max mem: 33369 +Epoch: [5] [1000/1319] eta: 0:13:58 lr: 4.347192331834616e-05 loss: 0.1147 (0.1238) time: 2.6471 data: 0.0057 max mem: 33369 +Epoch: [5] [1010/1319] eta: 0:13:32 lr: 4.346326040891335e-05 loss: 0.1229 (0.1238) time: 2.6398 data: 0.0060 max mem: 33369 +Epoch: [5] [1020/1319] eta: 0:13:06 lr: 4.345459730762588e-05 loss: 0.1221 (0.1241) time: 2.6362 data: 0.0060 max mem: 33369 +Epoch: [5] [1030/1319] eta: 0:12:39 lr: 4.344593401443699e-05 loss: 0.1187 (0.1242) time: 2.6373 data: 0.0059 max mem: 33369 +Epoch: [5] [1040/1319] eta: 0:12:13 lr: 4.343727052929992e-05 loss: 0.1266 (0.1243) time: 2.6393 data: 0.0059 max mem: 33369 +Epoch: [5] [1050/1319] eta: 0:11:47 lr: 4.342860685216788e-05 loss: 0.1256 (0.1242) time: 2.5980 data: 0.0060 max mem: 33369 +Epoch: [5] [1060/1319] eta: 0:11:20 lr: 4.341994298299405e-05 loss: 0.1158 (0.1241) time: 2.5798 data: 0.0060 max mem: 33369 +Epoch: [5] [1070/1319] eta: 0:10:54 lr: 4.341127892173159e-05 loss: 0.1158 (0.1241) time: 2.6181 data: 0.0058 max mem: 33369 +Epoch: [5] [1080/1319] eta: 0:10:28 lr: 4.3402614668333656e-05 loss: 0.1214 (0.1241) time: 2.6470 data: 0.0058 max mem: 33369 +Epoch: [5] [1090/1319] eta: 0:10:01 lr: 4.339395022275336e-05 loss: 0.1140 (0.1241) time: 2.6272 data: 0.0057 max mem: 33369 +Epoch: [5] [1100/1319] eta: 0:09:35 lr: 4.33852855849438e-05 loss: 0.1034 (0.1239) time: 2.6186 data: 0.0057 max mem: 33369 +Epoch: [5] [1110/1319] eta: 0:09:09 lr: 4.337662075485806e-05 loss: 0.1034 (0.1238) time: 2.6228 data: 0.0058 max mem: 33369 +Epoch: [5] [1120/1319] eta: 0:08:43 lr: 4.3367955732449175e-05 loss: 0.1197 (0.1239) time: 2.6017 data: 0.0058 max mem: 33369 +Epoch: [5] [1130/1319] eta: 0:08:16 lr: 4.3359290517670206e-05 loss: 0.1197 (0.1239) time: 2.5886 data: 0.0058 max mem: 33369 +Epoch: [5] [1140/1319] eta: 0:07:50 lr: 4.335062511047415e-05 loss: 0.1293 (0.1241) time: 2.5777 data: 0.0058 max mem: 33369 +Epoch: [5] [1150/1319] eta: 0:07:23 lr: 4.3341959510813994e-05 loss: 0.1186 (0.1241) time: 2.5598 data: 0.0060 max mem: 33369 +Epoch: [5] [1160/1319] eta: 0:06:57 lr: 4.33332937186427e-05 loss: 0.0993 (0.1239) time: 2.6140 data: 0.0059 max mem: 33369 +Epoch: [5] [1170/1319] eta: 0:06:31 lr: 4.332462773391324e-05 loss: 0.1148 (0.1239) time: 2.6445 data: 0.0060 max mem: 33369 +Epoch: [5] [1180/1319] eta: 0:06:05 lr: 4.331596155657851e-05 loss: 0.1202 (0.1240) time: 2.6135 data: 0.0060 max mem: 33369 +Epoch: [5] [1190/1319] eta: 0:05:38 lr: 4.3307295186591415e-05 loss: 0.1147 (0.1241) time: 2.6119 data: 0.0058 max mem: 33369 +Epoch: [5] [1200/1319] eta: 0:05:12 lr: 4.329862862390485e-05 loss: 0.1170 (0.1241) time: 2.6103 data: 0.0056 max mem: 33369 +Epoch: [5] [1210/1319] eta: 0:04:46 lr: 4.328996186847165e-05 loss: 0.1175 (0.1241) time: 2.5948 data: 0.0056 max mem: 33369 +Epoch: [5] [1220/1319] eta: 0:04:19 lr: 4.328129492024467e-05 loss: 0.1082 (0.1239) time: 2.5968 data: 0.0058 max mem: 33369 +Epoch: [5] [1230/1319] eta: 0:03:53 lr: 4.3272627779176715e-05 loss: 0.0990 (0.1239) time: 2.6249 data: 0.0058 max mem: 33369 +Epoch: [5] [1240/1319] eta: 0:03:27 lr: 4.326396044522058e-05 loss: 0.1134 (0.1239) time: 2.6289 data: 0.0057 max mem: 33369 +Epoch: [5] [1250/1319] eta: 0:03:01 lr: 4.3255292918329036e-05 loss: 0.1224 (0.1240) time: 2.6023 data: 0.0058 max mem: 33369 +Epoch: [5] [1260/1319] eta: 0:02:34 lr: 4.324662519845482e-05 loss: 0.1242 (0.1240) time: 2.5919 data: 0.0059 max mem: 33369 +Epoch: [5] [1270/1319] eta: 0:02:08 lr: 4.323795728555066e-05 loss: 0.1255 (0.1240) time: 2.6244 data: 0.0059 max mem: 33369 +Epoch: [5] [1280/1319] eta: 0:01:42 lr: 4.322928917956926e-05 loss: 0.1055 (0.1240) time: 2.6709 data: 0.0058 max mem: 33369 +Epoch: [5] [1290/1319] eta: 0:01:16 lr: 4.322062088046332e-05 loss: 0.1268 (0.1240) time: 2.6643 data: 0.0059 max mem: 33369 +Epoch: [5] [1300/1319] eta: 0:00:49 lr: 4.321195238818547e-05 loss: 0.1316 (0.1241) time: 2.6356 data: 0.0059 max mem: 33369 +Epoch: [5] [1310/1319] eta: 0:00:23 lr: 4.3203283702688355e-05 loss: 0.1125 (0.1240) time: 2.6470 data: 0.0057 max mem: 33369 +Epoch: [5] Total time: 0:57:45 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 2:28:00 time: 3.4515 data: 3.3626 max mem: 33369 +Test: [ 100/2573] eta: 0:04:20 time: 0.0715 data: 0.0011 max mem: 33369 +Test: [ 200/2573] eta: 0:03:32 time: 0.0731 data: 0.0011 max mem: 33369 +Test: [ 300/2573] eta: 0:03:10 time: 0.0748 data: 0.0011 max mem: 33369 +Test: [ 400/2573] eta: 0:02:56 time: 0.0750 data: 0.0011 max mem: 33369 +Test: [ 500/2573] eta: 0:02:44 time: 0.0735 data: 0.0011 max mem: 33369 +Test: [ 600/2573] eta: 0:02:35 time: 0.0735 data: 0.0011 max mem: 33369 +Test: [ 700/2573] eta: 0:02:26 time: 0.0738 data: 0.0011 max mem: 33369 +Test: [ 800/2573] eta: 0:02:18 time: 0.0771 data: 0.0011 max mem: 33369 +Test: [ 900/2573] eta: 0:02:09 time: 0.0738 data: 0.0011 max mem: 33369 +Test: [1000/2573] eta: 0:02:01 time: 0.0739 data: 0.0011 max mem: 33369 +Test: [1100/2573] eta: 0:01:53 time: 0.0734 data: 0.0008 max mem: 33369 +Test: [1200/2573] eta: 0:01:45 time: 0.0738 data: 0.0011 max mem: 33369 +Test: [1300/2573] eta: 0:01:37 time: 0.0737 data: 0.0011 max mem: 33369 +Test: [1400/2573] eta: 0:01:29 time: 0.0721 data: 0.0011 max mem: 33369 +Test: [1500/2573] eta: 0:01:21 time: 0.0738 data: 0.0011 max mem: 33369 +Test: [1600/2573] eta: 0:01:13 time: 0.0770 data: 0.0010 max mem: 33369 +Test: [1700/2573] eta: 0:01:06 time: 0.0721 data: 0.0011 max mem: 33369 +Test: [1800/2573] eta: 0:00:58 time: 0.0754 data: 0.0011 max mem: 33369 +Test: [1900/2573] eta: 0:00:50 time: 0.0721 data: 0.0011 max mem: 33369 +Test: [2000/2573] eta: 0:00:43 time: 0.0738 data: 0.0011 max mem: 33369 +Test: [2100/2573] eta: 0:00:35 time: 0.0755 data: 0.0011 max mem: 33369 +Test: [2200/2573] eta: 0:00:28 time: 0.0754 data: 0.0011 max mem: 33369 +Test: [2300/2573] eta: 0:00:20 time: 0.0753 data: 0.0011 max mem: 33369 +Test: [2400/2573] eta: 0:00:12 time: 0.0703 data: 0.0011 max mem: 33369 +Test: [2500/2573] eta: 0:00:05 time: 0.0734 data: 0.0010 max mem: 33369 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: Total time: 0:03:13 +Final results: +Mean IoU is 54.47 + + precision@0.5 = 60.31 + precision@0.6 = 52.98 + precision@0.7 = 44.61 + precision@0.8 = 32.39 + precision@0.9 = 13.19 + overall IoU = 54.84 + +Average object IoU 54.47368758482969 +Overall IoU 54.835575103759766 +Better epoch: 5 + +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [6] [ 0/1319] eta: 1:30:36 lr: 4.319548172049932e-05 loss: 0.0867 (0.0867) time: 4.1217 data: 1.2565 max mem: 33369 +Epoch: [6] [ 10/1319] eta: 1:00:29 lr: 4.318681266775505e-05 loss: 0.1172 (0.1193) time: 2.7725 data: 0.1196 max mem: 33369 +Epoch: [6] [ 20/1319] eta: 0:58:23 lr: 4.317814342165404e-05 loss: 0.1060 (0.1151) time: 2.6260 data: 0.0058 max mem: 33369 +Epoch: [6] [ 30/1319] eta: 0:57:07 lr: 4.316947398214883e-05 loss: 0.0988 (0.1095) time: 2.5968 data: 0.0059 max mem: 33369 +Epoch: [6] [ 40/1319] eta: 0:56:21 lr: 4.316080434919196e-05 loss: 0.0962 (0.1085) time: 2.5875 data: 0.0062 max mem: 33369 +Epoch: [6] [ 50/1319] eta: 0:56:01 lr: 4.315213452273593e-05 loss: 0.0962 (0.1082) time: 2.6335 data: 0.0062 max mem: 33369 +Epoch: [6] [ 60/1319] eta: 0:55:31 lr: 4.314346450273323e-05 loss: 0.1123 (0.1117) time: 2.6513 data: 0.0059 max mem: 33369 +Epoch: [6] [ 70/1319] eta: 0:54:59 lr: 4.313479428913631e-05 loss: 0.1088 (0.1116) time: 2.6233 data: 0.0058 max mem: 33369 +Epoch: [6] [ 80/1319] eta: 0:54:24 lr: 4.312612388189762e-05 loss: 0.0839 (0.1090) time: 2.6006 data: 0.0060 max mem: 33369 +Epoch: [6] [ 90/1319] eta: 0:53:59 lr: 4.311745328096956e-05 loss: 0.1043 (0.1111) time: 2.6135 data: 0.0060 max mem: 33369 +Epoch: [6] [ 100/1319] eta: 0:53:34 lr: 4.3108782486304546e-05 loss: 0.1081 (0.1098) time: 2.6450 data: 0.0060 max mem: 33369 +Epoch: [6] [ 110/1319] eta: 0:53:02 lr: 4.310011149785494e-05 loss: 0.0955 (0.1093) time: 2.6177 data: 0.0060 max mem: 33369 +Epoch: [6] [ 120/1319] eta: 0:52:36 lr: 4.309144031557308e-05 loss: 0.0951 (0.1090) time: 2.6126 data: 0.0060 max mem: 33369 +Epoch: [6] [ 130/1319] eta: 0:52:08 lr: 4.308276893941131e-05 loss: 0.1086 (0.1092) time: 2.6253 data: 0.0062 max mem: 33369 +Epoch: [6] [ 140/1319] eta: 0:51:40 lr: 4.307409736932192e-05 loss: 0.1042 (0.1085) time: 2.6080 data: 0.0062 max mem: 33369 +Epoch: [6] [ 150/1319] eta: 0:51:13 lr: 4.306542560525721e-05 loss: 0.0926 (0.1085) time: 2.6158 data: 0.0061 max mem: 33369 +Epoch: [6] [ 160/1319] eta: 0:50:43 lr: 4.305675364716942e-05 loss: 0.1075 (0.1087) time: 2.6030 data: 0.0061 max mem: 33369 +Epoch: [6] [ 170/1319] eta: 0:50:17 lr: 4.3048081495010805e-05 loss: 0.1075 (0.1090) time: 2.6053 data: 0.0060 max mem: 33369 +Epoch: [6] [ 180/1319] eta: 0:49:49 lr: 4.303940914873357e-05 loss: 0.1097 (0.1087) time: 2.6127 data: 0.0059 max mem: 33369 +Epoch: [6] [ 190/1319] eta: 0:49:22 lr: 4.30307366082899e-05 loss: 0.1065 (0.1089) time: 2.5996 data: 0.0057 max mem: 33369 +Epoch: [6] [ 200/1319] eta: 0:48:58 lr: 4.302206387363197e-05 loss: 0.1065 (0.1099) time: 2.6357 data: 0.0059 max mem: 33369 +Epoch: [6] [ 210/1319] eta: 0:48:31 lr: 4.301339094471194e-05 loss: 0.1071 (0.1095) time: 2.6381 data: 0.0059 max mem: 33369 +Epoch: [6] [ 220/1319] eta: 0:48:05 lr: 4.300471782148193e-05 loss: 0.1071 (0.1099) time: 2.6232 data: 0.0057 max mem: 33369 +Epoch: [6] [ 230/1319] eta: 0:47:38 lr: 4.299604450389403e-05 loss: 0.1056 (0.1094) time: 2.6219 data: 0.0058 max mem: 33369 +Epoch: [6] [ 240/1319] eta: 0:47:11 lr: 4.298737099190034e-05 loss: 0.0978 (0.1098) time: 2.6111 data: 0.0059 max mem: 33369 +Epoch: [6] [ 250/1319] eta: 0:46:45 lr: 4.297869728545289e-05 loss: 0.1027 (0.1096) time: 2.6218 data: 0.0059 max mem: 33369 +Epoch: [6] [ 260/1319] eta: 0:46:18 lr: 4.2970023384503735e-05 loss: 0.1053 (0.1096) time: 2.6214 data: 0.0058 max mem: 33369 +Epoch: [6] [ 270/1319] eta: 0:45:52 lr: 4.296134928900489e-05 loss: 0.1088 (0.1106) time: 2.6192 data: 0.0060 max mem: 33369 +Epoch: [6] [ 280/1319] eta: 0:45:26 lr: 4.295267499890832e-05 loss: 0.1105 (0.1109) time: 2.6228 data: 0.0059 max mem: 33369 +Epoch: [6] [ 290/1319] eta: 0:44:58 lr: 4.2944000514166015e-05 loss: 0.1006 (0.1111) time: 2.6015 data: 0.0057 max mem: 33369 +Epoch: [6] [ 300/1319] eta: 0:44:32 lr: 4.293532583472992e-05 loss: 0.0871 (0.1105) time: 2.6109 data: 0.0059 max mem: 33369 +Epoch: [6] [ 310/1319] eta: 0:44:05 lr: 4.292665096055194e-05 loss: 0.0881 (0.1102) time: 2.6188 data: 0.0060 max mem: 33369 +Epoch: [6] [ 320/1319] eta: 0:43:39 lr: 4.2917975891583976e-05 loss: 0.0874 (0.1097) time: 2.6074 data: 0.0059 max mem: 33369 +Epoch: [6] [ 330/1319] eta: 0:43:13 lr: 4.2909300627777926e-05 loss: 0.0874 (0.1095) time: 2.6190 data: 0.0058 max mem: 33369 +Epoch: [6] [ 340/1319] eta: 0:42:47 lr: 4.290062516908562e-05 loss: 0.0964 (0.1098) time: 2.6261 data: 0.0061 max mem: 33369 +Epoch: [6] [ 350/1319] eta: 0:42:20 lr: 4.2891949515458894e-05 loss: 0.1079 (0.1099) time: 2.6240 data: 0.0061 max mem: 33369 +Epoch: [6] [ 360/1319] eta: 0:41:55 lr: 4.288327366684957e-05 loss: 0.1008 (0.1104) time: 2.6251 data: 0.0058 max mem: 33369 +Epoch: [6] [ 370/1319] eta: 0:41:28 lr: 4.287459762320942e-05 loss: 0.0973 (0.1098) time: 2.6301 data: 0.0056 max mem: 33369 +Epoch: [6] [ 380/1319] eta: 0:41:03 lr: 4.28659213844902e-05 loss: 0.0908 (0.1095) time: 2.6331 data: 0.0055 max mem: 33369 +Epoch: [6] [ 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0.0060 max mem: 33369 +Epoch: [6] [ 630/1319] eta: 0:30:07 lr: 4.264895187425208e-05 loss: 0.1069 (0.1110) time: 2.6213 data: 0.0058 max mem: 33369 +Epoch: [6] [ 640/1319] eta: 0:29:41 lr: 4.264027054647094e-05 loss: 0.1063 (0.1109) time: 2.6310 data: 0.0056 max mem: 33369 +Epoch: [6] [ 650/1319] eta: 0:29:15 lr: 4.263158902229967e-05 loss: 0.0992 (0.1108) time: 2.6278 data: 0.0056 max mem: 33369 +Epoch: [6] [ 660/1319] eta: 0:28:49 lr: 4.262290730168937e-05 loss: 0.0992 (0.1114) time: 2.6250 data: 0.0057 max mem: 33369 +Epoch: [6] [ 670/1319] eta: 0:28:22 lr: 4.261422538459115e-05 loss: 0.0945 (0.1113) time: 2.6223 data: 0.0058 max mem: 33369 +Epoch: [6] [ 680/1319] eta: 0:27:56 lr: 4.260554327095607e-05 loss: 0.0963 (0.1115) time: 2.6240 data: 0.0057 max mem: 33369 +Epoch: [6] [ 690/1319] eta: 0:27:30 lr: 4.2596860960735204e-05 loss: 0.1107 (0.1118) time: 2.6110 data: 0.0058 max mem: 33369 +Epoch: [6] [ 700/1319] eta: 0:27:04 lr: 4.258817845387955e-05 loss: 0.1107 (0.1118) time: 2.6109 data: 0.0058 max mem: 33369 +Epoch: [6] [ 710/1319] eta: 0:26:37 lr: 4.257949575034011e-05 loss: 0.0966 (0.1115) time: 2.6153 data: 0.0058 max mem: 33369 +Epoch: [6] [ 720/1319] eta: 0:26:11 lr: 4.257081285006789e-05 loss: 0.0883 (0.1115) time: 2.5969 data: 0.0059 max mem: 33369 +Epoch: [6] [ 730/1319] eta: 0:25:44 lr: 4.256212975301382e-05 loss: 0.1057 (0.1117) time: 2.6035 data: 0.0059 max mem: 33369 +Epoch: [6] [ 740/1319] eta: 0:25:18 lr: 4.255344645912884e-05 loss: 0.1327 (0.1121) time: 2.6204 data: 0.0057 max mem: 33369 +Epoch: [6] [ 750/1319] eta: 0:24:52 lr: 4.254476296836386e-05 loss: 0.0960 (0.1119) time: 2.6317 data: 0.0056 max mem: 33369 +Epoch: [6] [ 760/1319] eta: 0:24:26 lr: 4.253607928066978e-05 loss: 0.0960 (0.1122) time: 2.6330 data: 0.0057 max mem: 33369 +Epoch: [6] [ 770/1319] eta: 0:24:00 lr: 4.252739539599743e-05 loss: 0.1299 (0.1127) time: 2.6274 data: 0.0056 max mem: 33369 +Epoch: [6] [ 780/1319] eta: 0:23:33 lr: 4.2518711314297674e-05 loss: 0.1144 (0.1127) time: 2.6211 data: 0.0056 max mem: 33369 +Epoch: [6] [ 790/1319] eta: 0:23:07 lr: 4.2510027035521314e-05 loss: 0.1088 (0.1129) time: 2.6077 data: 0.0059 max mem: 33369 +Epoch: [6] [ 800/1319] eta: 0:22:41 lr: 4.250134255961916e-05 loss: 0.1046 (0.1129) time: 2.6121 data: 0.0061 max mem: 33369 +Epoch: [6] [ 810/1319] eta: 0:22:15 lr: 4.2492657886541955e-05 loss: 0.1099 (0.1129) time: 2.6293 data: 0.0059 max mem: 33369 +Epoch: [6] [ 820/1319] eta: 0:21:49 lr: 4.2483973016240455e-05 loss: 0.1099 (0.1129) time: 2.6436 data: 0.0059 max mem: 33369 +Epoch: [6] [ 830/1319] eta: 0:21:22 lr: 4.247528794866539e-05 loss: 0.1112 (0.1133) time: 2.6369 data: 0.0058 max mem: 33369 +Epoch: [6] [ 840/1319] eta: 0:20:56 lr: 4.2466602683767445e-05 loss: 0.0946 (0.1131) time: 2.6102 data: 0.0056 max mem: 33369 +Epoch: [6] [ 850/1319] eta: 0:20:30 lr: 4.24579172214973e-05 loss: 0.1114 (0.1133) time: 2.6079 data: 0.0055 max mem: 33369 +Epoch: [6] [ 860/1319] eta: 0:20:03 lr: 4.244923156180561e-05 loss: 0.1040 (0.1132) time: 2.6119 data: 0.0057 max mem: 33369 +Epoch: [6] [ 870/1319] eta: 0:19:37 lr: 4.2440545704643e-05 loss: 0.0894 (0.1131) time: 2.6191 data: 0.0059 max mem: 33369 +Epoch: [6] [ 880/1319] eta: 0:19:11 lr: 4.243185964996007e-05 loss: 0.1232 (0.1135) time: 2.6225 data: 0.0057 max mem: 33369 +Epoch: [6] [ 890/1319] eta: 0:18:45 lr: 4.24231733977074e-05 loss: 0.1232 (0.1135) time: 2.6125 data: 0.0057 max mem: 33369 +Epoch: [6] [ 900/1319] eta: 0:18:18 lr: 4.2414486947835554e-05 loss: 0.1014 (0.1134) time: 2.6113 data: 0.0057 max mem: 33369 +Epoch: [6] [ 910/1319] eta: 0:17:52 lr: 4.240580030029505e-05 loss: 0.0998 (0.1134) time: 2.6091 data: 0.0056 max mem: 33369 +Epoch: [6] [ 920/1319] eta: 0:17:26 lr: 4.239711345503641e-05 loss: 0.1023 (0.1137) time: 2.6173 data: 0.0056 max mem: 33369 +Epoch: [6] [ 930/1319] eta: 0:17:00 lr: 4.2388426412010114e-05 loss: 0.1088 (0.1137) time: 2.6274 data: 0.0058 max mem: 33369 +Epoch: [6] [ 940/1319] eta: 0:16:33 lr: 4.237973917116662e-05 loss: 0.1061 (0.1138) time: 2.6092 data: 0.0058 max mem: 33369 +Epoch: [6] [ 950/1319] eta: 0:16:07 lr: 4.237105173245638e-05 loss: 0.1009 (0.1142) time: 2.6104 data: 0.0057 max mem: 33369 +Epoch: [6] [ 960/1319] eta: 0:15:41 lr: 4.23623640958298e-05 loss: 0.1015 (0.1141) time: 2.6260 data: 0.0057 max mem: 33369 +Epoch: [6] [ 970/1319] eta: 0:15:15 lr: 4.235367626123727e-05 loss: 0.0996 (0.1140) time: 2.6358 data: 0.0058 max mem: 33369 +Epoch: [6] [ 980/1319] eta: 0:14:49 lr: 4.234498822862916e-05 loss: 0.0937 (0.1139) time: 2.6441 data: 0.0057 max mem: 33369 +Epoch: [6] [ 990/1319] eta: 0:14:22 lr: 4.23362999979558e-05 loss: 0.0984 (0.1139) time: 2.6406 data: 0.0058 max mem: 33369 +Epoch: [6] [1000/1319] eta: 0:13:56 lr: 4.2327611569167524e-05 loss: 0.1085 (0.1141) time: 2.6138 data: 0.0059 max mem: 33369 +Epoch: [6] [1010/1319] eta: 0:13:30 lr: 4.2318922942214635e-05 loss: 0.1085 (0.1140) time: 2.6419 data: 0.0057 max mem: 33369 +Epoch: [6] [1020/1319] eta: 0:13:04 lr: 4.231023411704738e-05 loss: 0.1029 (0.1140) time: 2.6590 data: 0.0058 max mem: 33369 +Epoch: [6] [1030/1319] eta: 0:12:38 lr: 4.230154509361603e-05 loss: 0.1156 (0.1141) time: 2.6297 data: 0.0058 max mem: 33369 +Epoch: [6] [1040/1319] eta: 0:12:11 lr: 4.229285587187079e-05 loss: 0.1089 (0.1140) time: 2.6345 data: 0.0057 max mem: 33369 +Epoch: [6] [1050/1319] eta: 0:11:45 lr: 4.2284166451761876e-05 loss: 0.1047 (0.1140) time: 2.6264 data: 0.0058 max mem: 33369 +Epoch: [6] [1060/1319] eta: 0:11:19 lr: 4.2275476833239456e-05 loss: 0.0947 (0.1139) time: 2.6201 data: 0.0058 max mem: 33369 +Epoch: [6] [1070/1319] eta: 0:10:53 lr: 4.2266787016253686e-05 loss: 0.0913 (0.1139) time: 2.6481 data: 0.0058 max mem: 33369 +Epoch: [6] [1080/1319] eta: 0:10:27 lr: 4.22580970007547e-05 loss: 0.0999 (0.1139) time: 2.6458 data: 0.0059 max mem: 33369 +Epoch: [6] [1090/1319] eta: 0:10:00 lr: 4.224940678669259e-05 loss: 0.1042 (0.1140) time: 2.6162 data: 0.0060 max mem: 33369 +Epoch: [6] 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+Epoch: [6] [1180/1319] eta: 0:06:04 lr: 4.217118591654868e-05 loss: 0.0979 (0.1146) time: 2.6041 data: 0.0057 max mem: 33369 +Epoch: [6] [1190/1319] eta: 0:05:38 lr: 4.2162493714105874e-05 loss: 0.1058 (0.1147) time: 2.5997 data: 0.0057 max mem: 33369 +Epoch: [6] [1200/1319] eta: 0:05:12 lr: 4.2153801312549505e-05 loss: 0.1034 (0.1146) time: 2.6063 data: 0.0058 max mem: 33369 +Epoch: [6] [1210/1319] eta: 0:04:45 lr: 4.2145108711829405e-05 loss: 0.0819 (0.1144) time: 2.6230 data: 0.0059 max mem: 33369 +Epoch: [6] [1220/1319] eta: 0:04:19 lr: 4.213641591189537e-05 loss: 0.0874 (0.1143) time: 2.6188 data: 0.0056 max mem: 33369 +Epoch: [6] [1230/1319] eta: 0:03:53 lr: 4.212772291269716e-05 loss: 0.1093 (0.1143) time: 2.6124 data: 0.0056 max mem: 33369 +Epoch: [6] [1240/1319] eta: 0:03:27 lr: 4.2119029714184504e-05 loss: 0.1093 (0.1143) time: 2.6148 data: 0.0056 max mem: 33369 +Epoch: [6] [1250/1319] eta: 0:03:01 lr: 4.211033631630714e-05 loss: 0.1293 (0.1145) time: 2.6197 data: 0.0056 max mem: 33369 +Epoch: [6] [1260/1319] eta: 0:02:34 lr: 4.2101642719014764e-05 loss: 0.1219 (0.1144) time: 2.6293 data: 0.0057 max mem: 33369 +Epoch: [6] [1270/1319] eta: 0:02:08 lr: 4.2092948922257045e-05 loss: 0.1165 (0.1145) time: 2.6288 data: 0.0058 max mem: 33369 +Epoch: [6] [1280/1319] eta: 0:01:42 lr: 4.208425492598362e-05 loss: 0.1200 (0.1145) time: 2.6068 data: 0.0057 max mem: 33369 +Epoch: [6] [1290/1319] eta: 0:01:16 lr: 4.207556073014412e-05 loss: 0.1146 (0.1146) time: 2.5949 data: 0.0057 max mem: 33369 +Epoch: [6] [1300/1319] eta: 0:00:49 lr: 4.2066866334688144e-05 loss: 0.1077 (0.1145) time: 2.6151 data: 0.0057 max mem: 33369 +Epoch: [6] [1310/1319] eta: 0:00:23 lr: 4.205817173956526e-05 loss: 0.1077 (0.1146) time: 2.6284 data: 0.0057 max mem: 33369 +Epoch: [6] Total time: 0:57:39 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 2:10:36 time: 3.0455 data: 2.9626 max mem: 33369 +Test: [ 100/2573] eta: 0:04:10 time: 0.0714 data: 0.0011 max mem: 33369 +Test: [ 200/2573] eta: 0:03:28 time: 0.0733 data: 0.0011 max mem: 33369 +Test: [ 300/2573] eta: 0:03:07 time: 0.0748 data: 0.0011 max mem: 33369 +Test: [ 400/2573] eta: 0:02:53 time: 0.0749 data: 0.0011 max mem: 33369 +Test: [ 500/2573] eta: 0:02:43 time: 0.0734 data: 0.0011 max mem: 33369 +Test: [ 600/2573] eta: 0:02:33 time: 0.0734 data: 0.0011 max mem: 33369 +Test: [ 700/2573] eta: 0:02:25 time: 0.0735 data: 0.0011 max mem: 33369 +Test: [ 800/2573] eta: 0:02:16 time: 0.0768 data: 0.0011 max mem: 33369 +Test: [ 900/2573] eta: 0:02:08 time: 0.0735 data: 0.0011 max mem: 33369 +Test: [1000/2573] eta: 0:02:00 time: 0.0736 data: 0.0011 max mem: 33369 +Test: [1100/2573] eta: 0:01:52 time: 0.0736 data: 0.0011 max mem: 33369 +Test: [1200/2573] eta: 0:01:44 time: 0.0735 data: 0.0011 max mem: 33369 +Test: [1300/2573] eta: 0:01:36 time: 0.0736 data: 0.0011 max mem: 33369 +Test: [1400/2573] eta: 0:01:28 time: 0.0719 data: 0.0011 max mem: 33369 +Test: [1500/2573] eta: 0:01:21 time: 0.0737 data: 0.0011 max mem: 33369 +Test: [1600/2573] eta: 0:01:13 time: 0.0769 data: 0.0011 max mem: 33369 +Test: [1700/2573] eta: 0:01:05 time: 0.0720 data: 0.0011 max mem: 33369 +Test: [1800/2573] eta: 0:00:58 time: 0.0753 data: 0.0011 max mem: 33369 +Test: [1900/2573] eta: 0:00:50 time: 0.0719 data: 0.0011 max mem: 33369 +Test: [2000/2573] eta: 0:00:42 time: 0.0735 data: 0.0011 max mem: 33369 +Test: [2100/2573] eta: 0:00:35 time: 0.0753 data: 0.0011 max mem: 33369 +Test: [2200/2573] eta: 0:00:27 time: 0.0752 data: 0.0011 max mem: 33369 +Test: [2300/2573] eta: 0:00:20 time: 0.0752 data: 0.0011 max mem: 33369 +Test: [2400/2573] eta: 0:00:12 time: 0.0703 data: 0.0011 max mem: 33369 +Test: [2500/2573] eta: 0:00:05 time: 0.0735 data: 0.0011 max mem: 33369 +Test: Total time: 0:03:12 +Final results: +Mean IoU is 55.86 + + precision@0.5 = 62.13 + precision@0.6 = 55.04 + precision@0.7 = 46.41 + precision@0.8 = 34.38 + precision@0.9 = 13.64 + overall IoU = 55.76 + +Average object IoU 55.85999328920758 +Overall IoU 55.762935638427734 +Better epoch: 6 + +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [7] [ 0/1319] eta: 2:04:15 lr: 4.205034643319776e-05 loss: 0.1133 (0.1133) time: 5.6520 data: 2.8957 max mem: 33369 +Epoch: [7] [ 10/1319] eta: 1:03:38 lr: 4.204165145856875e-05 loss: 0.0929 (0.1005) time: 2.9171 data: 0.2679 max mem: 33369 +Epoch: [7] [ 20/1319] eta: 0:59:57 lr: 4.203295628412646e-05 loss: 0.0945 (0.1019) time: 2.6253 data: 0.0053 max mem: 33369 +Epoch: [7] [ 30/1319] eta: 0:58:47 lr: 4.202426090982037e-05 loss: 0.1054 (0.1022) time: 2.6372 data: 0.0057 max mem: 33369 +Epoch: [7] [ 40/1319] eta: 0:57:54 lr: 4.201556533559993e-05 loss: 0.0969 (0.1019) time: 2.6603 data: 0.0062 max mem: 33369 +Epoch: [7] [ 50/1319] eta: 0:56:59 lr: 4.2006869561414584e-05 loss: 0.0906 (0.1007) time: 2.6291 data: 0.0061 max mem: 33369 +Epoch: [7] [ 60/1319] eta: 0:56:05 lr: 4.199817358721372e-05 loss: 0.0834 (0.0981) time: 2.5860 data: 0.0060 max mem: 33369 +Epoch: [7] [ 70/1319] eta: 0:55:39 lr: 4.1989477412946735e-05 loss: 0.1006 (0.1069) time: 2.6212 data: 0.0061 max mem: 33369 +Epoch: [7] [ 80/1319] eta: 0:55:03 lr: 4.1980781038562975e-05 loss: 0.1287 (0.1070) time: 2.6450 data: 0.0064 max mem: 33369 +Epoch: [7] [ 90/1319] eta: 0:54:30 lr: 4.1972084464011784e-05 loss: 0.1066 (0.1062) time: 2.6161 data: 0.0063 max mem: 33369 +Epoch: [7] [ 100/1319] eta: 0:53:58 lr: 4.1963387689242456e-05 loss: 0.0894 (0.1058) time: 2.6174 data: 0.0058 max mem: 33369 +Epoch: [7] [ 110/1319] eta: 0:53:29 lr: 4.1954690714204276e-05 loss: 0.0850 (0.1060) time: 2.6262 data: 0.0059 max mem: 33369 +Epoch: [7] [ 120/1319] eta: 0:53:02 lr: 4.194599353884651e-05 loss: 0.1078 (0.1084) time: 2.6420 data: 0.0062 max mem: 33369 +Epoch: [7] [ 130/1319] eta: 0:52:28 lr: 4.193729616311839e-05 loss: 0.0916 (0.1072) time: 2.6109 data: 0.0063 max mem: 33369 +Epoch: [7] [ 140/1319] eta: 0:51:56 lr: 4.1928598586969124e-05 loss: 0.0916 (0.1082) time: 2.5772 data: 0.0061 max mem: 33369 +Epoch: [7] [ 150/1319] eta: 0:51:27 lr: 4.1919900810347894e-05 loss: 0.0985 (0.1071) time: 2.5988 data: 0.0061 max mem: 33369 +Epoch: [7] [ 160/1319] eta: 0:51:00 lr: 4.191120283320388e-05 loss: 0.0985 (0.1081) time: 2.6182 data: 0.0061 max mem: 33369 +Epoch: [7] [ 170/1319] eta: 0:50:33 lr: 4.190250465548619e-05 loss: 0.0934 (0.1071) time: 2.6277 data: 0.0061 max mem: 33369 +Epoch: [7] [ 180/1319] eta: 0:50:06 lr: 4.189380627714394e-05 loss: 0.0823 (0.1073) time: 2.6337 data: 0.0060 max mem: 33369 +Epoch: [7] [ 190/1319] eta: 0:49:38 lr: 4.188510769812624e-05 loss: 0.0855 (0.1064) time: 2.6194 data: 0.0061 max mem: 33369 +Epoch: [7] [ 200/1319] eta: 0:49:10 lr: 4.1876408918382123e-05 loss: 0.0964 (0.1062) time: 2.6146 data: 0.0061 max mem: 33369 +Epoch: [7] [ 210/1319] eta: 0:48:42 lr: 4.1867709937860646e-05 loss: 0.1020 (0.1064) time: 2.6086 data: 0.0060 max mem: 33369 +Epoch: [7] [ 220/1319] eta: 0:48:13 lr: 4.185901075651081e-05 loss: 0.0952 (0.1063) time: 2.5917 data: 0.0060 max mem: 33369 +Epoch: [7] [ 230/1319] eta: 0:47:45 lr: 4.185031137428161e-05 loss: 0.0904 (0.1057) time: 2.5908 data: 0.0060 max mem: 33369 +Epoch: [7] [ 240/1319] eta: 0:47:19 lr: 4.1841611791121996e-05 loss: 0.0873 (0.1048) time: 2.6193 data: 0.0059 max mem: 33369 +Epoch: [7] [ 250/1319] eta: 0:46:53 lr: 4.183291200698093e-05 loss: 0.0821 (0.1043) time: 2.6362 data: 0.0060 max mem: 33369 +Epoch: [7] [ 260/1319] eta: 0:46:26 lr: 4.182421202180731e-05 loss: 0.1046 (0.1045) time: 2.6197 data: 0.0062 max mem: 33369 +Epoch: [7] [ 270/1319] eta: 0:45:56 lr: 4.181551183555002e-05 loss: 0.1094 (0.1050) time: 2.5778 data: 0.0061 max mem: 33369 +Epoch: [7] [ 280/1319] eta: 0:45:29 lr: 4.180681144815793e-05 loss: 0.0967 (0.1052) time: 2.5827 data: 0.0060 max mem: 33369 +Epoch: [7] [ 290/1319] eta: 0:45:03 lr: 4.179811085957988e-05 loss: 0.0866 (0.1048) time: 2.6293 data: 0.0061 max mem: 33369 +Epoch: [7] [ 300/1319] eta: 0:44:37 lr: 4.178941006976469e-05 loss: 0.0799 (0.1040) time: 2.6364 data: 0.0061 max mem: 33369 +Epoch: [7] [ 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4.130184307482921e-05 loss: 0.1050 (0.1059) time: 2.6057 data: 0.0059 max mem: 33369 +Epoch: [7] [ 870/1319] eta: 0:19:36 lr: 4.1293130729069835e-05 loss: 0.0921 (0.1059) time: 2.6276 data: 0.0061 max mem: 33369 +Epoch: [7] [ 880/1319] eta: 0:19:10 lr: 4.128441817906139e-05 loss: 0.0842 (0.1058) time: 2.6362 data: 0.0061 max mem: 33369 +Epoch: [7] [ 890/1319] eta: 0:18:44 lr: 4.1275705424751206e-05 loss: 0.0842 (0.1058) time: 2.6261 data: 0.0059 max mem: 33369 +Epoch: [7] [ 900/1319] eta: 0:18:17 lr: 4.1266992466086555e-05 loss: 0.0920 (0.1056) time: 2.5974 data: 0.0057 max mem: 33369 +Epoch: [7] [ 910/1319] eta: 0:17:51 lr: 4.125827930301473e-05 loss: 0.0947 (0.1055) time: 2.6134 data: 0.0058 max mem: 33369 +Epoch: [7] [ 920/1319] eta: 0:17:25 lr: 4.124956593548294e-05 loss: 0.0979 (0.1057) time: 2.6559 data: 0.0059 max mem: 33369 +Epoch: [7] [ 930/1319] eta: 0:16:59 lr: 4.124085236343841e-05 loss: 0.0969 (0.1056) time: 2.6422 data: 0.0058 max mem: 33369 +Epoch: [7] [ 940/1319] eta: 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+Epoch: [7] [1100/1319] eta: 0:09:33 lr: 4.109269029695397e-05 loss: 0.1062 (0.1060) time: 2.6116 data: 0.0057 max mem: 33369 +Epoch: [7] [1110/1319] eta: 0:09:07 lr: 4.108397303462358e-05 loss: 0.1201 (0.1061) time: 2.6345 data: 0.0058 max mem: 33369 +Epoch: [7] [1120/1319] eta: 0:08:41 lr: 4.1075255566772506e-05 loss: 0.0909 (0.1061) time: 2.6062 data: 0.0060 max mem: 33369 +Epoch: [7] [1130/1319] eta: 0:08:14 lr: 4.106653789334745e-05 loss: 0.1011 (0.1063) time: 2.5924 data: 0.0059 max mem: 33369 +Epoch: [7] [1140/1319] eta: 0:07:48 lr: 4.105782001429505e-05 loss: 0.1209 (0.1065) time: 2.6086 data: 0.0058 max mem: 33369 +Epoch: [7] [1150/1319] eta: 0:07:22 lr: 4.104910192956196e-05 loss: 0.1144 (0.1065) time: 2.6112 data: 0.0060 max mem: 33369 +Epoch: [7] [1160/1319] eta: 0:06:56 lr: 4.104038363909479e-05 loss: 0.0919 (0.1064) time: 2.6305 data: 0.0059 max mem: 33369 +Epoch: [7] [1170/1319] eta: 0:06:30 lr: 4.1031665142840106e-05 loss: 0.0904 (0.1064) time: 2.6379 data: 0.0059 max mem: 33369 +Epoch: [7] [1180/1319] eta: 0:06:04 lr: 4.1022946440744476e-05 loss: 0.1058 (0.1068) time: 2.6588 data: 0.0060 max mem: 33369 +Epoch: [7] [1190/1319] eta: 0:05:37 lr: 4.1014227532754415e-05 loss: 0.0979 (0.1068) time: 2.6302 data: 0.0059 max mem: 33369 +Epoch: [7] [1200/1319] eta: 0:05:11 lr: 4.100550841881645e-05 loss: 0.0917 (0.1067) time: 2.6075 data: 0.0058 max mem: 33369 +Epoch: [7] [1210/1319] eta: 0:04:45 lr: 4.099678909887704e-05 loss: 0.0987 (0.1067) time: 2.6321 data: 0.0059 max mem: 33369 +Epoch: [7] [1220/1319] eta: 0:04:19 lr: 4.098806957288263e-05 loss: 0.0976 (0.1067) time: 2.6259 data: 0.0060 max mem: 33369 +Epoch: [7] [1230/1319] eta: 0:03:53 lr: 4.0979349840779665e-05 loss: 0.0940 (0.1066) time: 2.6317 data: 0.0058 max mem: 33369 +Epoch: [7] [1240/1319] eta: 0:03:26 lr: 4.0970629902514516e-05 loss: 0.0940 (0.1065) time: 2.6562 data: 0.0057 max mem: 33369 +Epoch: [7] [1250/1319] eta: 0:03:00 lr: 4.0961909758033565e-05 loss: 0.0953 (0.1065) time: 2.6517 data: 0.0057 max mem: 33369 +Epoch: [7] [1260/1319] eta: 0:02:34 lr: 4.095318940728316e-05 loss: 0.0914 (0.1064) time: 2.6159 data: 0.0061 max mem: 33369 +Epoch: [7] [1270/1319] eta: 0:02:08 lr: 4.0944468850209605e-05 loss: 0.0887 (0.1064) time: 2.6171 data: 0.0061 max mem: 33369 +Epoch: [7] [1280/1319] eta: 0:01:42 lr: 4.093574808675919e-05 loss: 0.0914 (0.1064) time: 2.6217 data: 0.0059 max mem: 33369 +Epoch: [7] [1290/1319] eta: 0:01:15 lr: 4.09270271168782e-05 loss: 0.0990 (0.1065) time: 2.5972 data: 0.0061 max mem: 33369 +Epoch: [7] [1300/1319] eta: 0:00:49 lr: 4.091830594051285e-05 loss: 0.0963 (0.1065) time: 2.5662 data: 0.0060 max mem: 33369 +Epoch: [7] [1310/1319] eta: 0:00:23 lr: 4.090958455760934e-05 loss: 0.0988 (0.1067) time: 2.5746 data: 0.0059 max mem: 33369 +Epoch: [7] Total time: 0:57:34 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 2:08:54 time: 3.0059 data: 2.9276 max mem: 33369 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 100/2573] eta: 0:04:09 time: 0.0714 data: 0.0011 max mem: 33369 +Test: [ 200/2573] eta: 0:03:27 time: 0.0734 data: 0.0011 max mem: 33369 +Test: [ 300/2573] eta: 0:03:07 time: 0.0750 data: 0.0011 max mem: 33369 +Test: [ 400/2573] eta: 0:02:54 time: 0.0752 data: 0.0011 max mem: 33369 +Test: [ 500/2573] eta: 0:02:43 time: 0.0737 data: 0.0011 max mem: 33369 +Test: [ 600/2573] eta: 0:02:34 time: 0.0736 data: 0.0011 max mem: 33369 +Test: [ 700/2573] eta: 0:02:25 time: 0.0737 data: 0.0011 max mem: 33369 +Test: [ 800/2573] eta: 0:02:17 time: 0.0770 data: 0.0011 max mem: 33369 +Test: [ 900/2573] eta: 0:02:08 time: 0.0737 data: 0.0011 max mem: 33369 +Test: [1000/2573] eta: 0:02:00 time: 0.0737 data: 0.0011 max mem: 33369 +Test: [1100/2573] eta: 0:01:52 time: 0.0737 data: 0.0011 max mem: 33369 +Test: [1200/2573] eta: 0:01:44 time: 0.0738 data: 0.0011 max mem: 33369 +Test: [1300/2573] eta: 0:01:36 time: 0.0738 data: 0.0011 max mem: 33369 +Test: [1400/2573] eta: 0:01:29 time: 0.0721 data: 0.0011 max mem: 33369 +Test: [1500/2573] eta: 0:01:21 time: 0.0737 data: 0.0011 max mem: 33369 +Test: [1600/2573] eta: 0:01:13 time: 0.0771 data: 0.0011 max mem: 33369 +Test: [1700/2573] eta: 0:01:06 time: 0.0722 data: 0.0011 max mem: 33369 +Test: [1800/2573] eta: 0:00:58 time: 0.0754 data: 0.0011 max mem: 33369 +Test: [1900/2573] eta: 0:00:50 time: 0.0721 data: 0.0011 max mem: 33369 +Test: [2000/2573] eta: 0:00:43 time: 0.0737 data: 0.0011 max mem: 33369 +Test: [2100/2573] eta: 0:00:35 time: 0.0754 data: 0.0011 max mem: 33369 +Test: [2200/2573] eta: 0:00:27 time: 0.0754 data: 0.0011 max mem: 33369 +Test: [2300/2573] eta: 0:00:20 time: 0.0754 data: 0.0011 max mem: 33369 +Test: [2400/2573] eta: 0:00:12 time: 0.0705 data: 0.0011 max mem: 33369 +Test: [2500/2573] eta: 0:00:05 time: 0.0736 data: 0.0010 max mem: 33369 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: Total time: 0:03:12 +Final results: +Mean IoU is 57.02 + + precision@0.5 = 63.64 + precision@0.6 = 56.84 + precision@0.7 = 48.67 + precision@0.8 = 36.85 + precision@0.9 = 15.62 + overall IoU = 57.22 + +Average object IoU 57.019229194216116 +Overall IoU 57.21522521972656 +Better epoch: 7 + +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [8] [ 0/1319] eta: 1:44:52 lr: 4.09017351363616e-05 loss: 0.0921 (0.0921) time: 4.7704 data: 2.0464 max mem: 33369 +Epoch: [8] [ 10/1319] eta: 1:01:43 lr: 4.089301336088734e-05 loss: 0.0911 (0.0945) time: 2.8291 data: 0.1914 max mem: 33369 +Epoch: [8] [ 20/1319] eta: 0:59:23 lr: 4.088429137871879e-05 loss: 0.0911 (0.0992) time: 2.6421 data: 0.0058 max mem: 33369 +Epoch: [8] [ 30/1319] eta: 0:57:57 lr: 4.087556918980205e-05 loss: 0.0899 (0.0962) time: 2.6255 data: 0.0061 max mem: 33369 +Epoch: [8] [ 40/1319] eta: 0:57:04 lr: 4.0866846794083216e-05 loss: 0.0730 (0.0905) time: 2.6085 data: 0.0063 max mem: 33369 +Epoch: [8] [ 50/1319] eta: 0:56:18 lr: 4.0858124191508315e-05 loss: 0.0743 (0.0899) time: 2.6070 data: 0.0061 max mem: 33369 +Epoch: [8] [ 60/1319] eta: 0:55:49 lr: 4.08494013820234e-05 loss: 0.0865 (0.0922) time: 2.6259 data: 0.0060 max mem: 33369 +Epoch: [8] [ 70/1319] eta: 0:55:22 lr: 4.0840678365574436e-05 loss: 0.0961 (0.0949) time: 2.6536 data: 0.0060 max mem: 33369 +Epoch: [8] [ 80/1319] eta: 0:54:50 lr: 4.083195514210742e-05 loss: 0.0884 (0.0924) time: 2.6400 data: 0.0062 max mem: 33369 +Epoch: [8] [ 90/1319] eta: 0:54:19 lr: 4.0823231711568287e-05 loss: 0.0756 (0.0943) time: 2.6266 data: 0.0060 max mem: 33369 +Epoch: [8] [ 100/1319] eta: 0:53:44 lr: 4.081450807390295e-05 loss: 0.0821 (0.0951) time: 2.6036 data: 0.0059 max mem: 33369 +Epoch: [8] [ 110/1319] eta: 0:53:11 lr: 4.0805784229057304e-05 loss: 0.0753 (0.0943) time: 2.5843 data: 0.0060 max mem: 33369 +Epoch: [8] [ 120/1319] eta: 0:52:41 lr: 4.079706017697721e-05 loss: 0.0761 (0.0940) time: 2.5962 data: 0.0060 max mem: 33369 +Epoch: [8] [ 130/1319] eta: 0:52:16 lr: 4.0788335917608504e-05 loss: 0.0856 (0.0941) time: 2.6228 data: 0.0061 max mem: 33369 +Epoch: [8] [ 140/1319] eta: 0:51:51 lr: 4.077961145089699e-05 loss: 0.0858 (0.0938) time: 2.6538 data: 0.0061 max mem: 33369 +Epoch: [8] [ 150/1319] eta: 0:51:25 lr: 4.0770886776788466e-05 loss: 0.0858 (0.0951) time: 2.6530 data: 0.0059 max mem: 33369 +Epoch: [8] [ 160/1319] eta: 0:50:57 lr: 4.076216189522867e-05 loss: 0.1090 (0.0969) time: 2.6301 data: 0.0059 max mem: 33369 +Epoch: [8] [ 170/1319] eta: 0:50:35 lr: 4.075343680616333e-05 loss: 0.0913 (0.0961) time: 2.6603 data: 0.0058 max mem: 33369 +Epoch: [8] [ 180/1319] eta: 0:50:07 lr: 4.074471150953815e-05 loss: 0.0729 (0.0965) time: 2.6554 data: 0.0059 max mem: 33369 +Epoch: [8] [ 190/1319] eta: 0:49:40 lr: 4.0735986005298814e-05 loss: 0.0835 (0.0965) time: 2.6232 data: 0.0059 max mem: 33369 +Epoch: [8] [ 200/1319] eta: 0:49:13 lr: 4.072726029339096e-05 loss: 0.0924 (0.0965) time: 2.6309 data: 0.0057 max mem: 33369 +Epoch: [8] [ 210/1319] eta: 0:48:46 lr: 4.07185343737602e-05 loss: 0.0972 (0.0964) time: 2.6259 data: 0.0058 max mem: 33369 +Epoch: [8] [ 220/1319] eta: 0:48:18 lr: 4.070980824635213e-05 loss: 0.0764 (0.0954) time: 2.6228 data: 0.0059 max mem: 33369 +Epoch: [8] [ 230/1319] eta: 0:47:50 lr: 4.070108191111232e-05 loss: 0.0683 (0.0947) time: 2.6065 data: 0.0059 max mem: 33369 +Epoch: [8] [ 240/1319] eta: 0:47:23 lr: 4.069235536798631e-05 loss: 0.0779 (0.0944) time: 2.6059 data: 0.0059 max mem: 33369 +Epoch: [8] [ 250/1319] eta: 0:46:57 lr: 4.0683628616919596e-05 loss: 0.0783 (0.0935) time: 2.6306 data: 0.0059 max mem: 33369 +Epoch: [8] [ 260/1319] eta: 0:46:30 lr: 4.0674901657857675e-05 loss: 0.0833 (0.0941) time: 2.6293 data: 0.0061 max mem: 33369 +Epoch: [8] [ 270/1319] eta: 0:46:04 lr: 4.066617449074599e-05 loss: 0.0886 (0.0942) time: 2.6288 data: 0.0062 max mem: 33369 +Epoch: [8] [ 280/1319] eta: 0:45:37 lr: 4.065744711552997e-05 loss: 0.0855 (0.0943) time: 2.6331 data: 0.0060 max mem: 33369 +Epoch: [8] [ 290/1319] eta: 0:45:10 lr: 4.064871953215503e-05 loss: 0.0998 (0.0956) time: 2.6180 data: 0.0060 max mem: 33369 +Epoch: [8] [ 300/1319] eta: 0:44:43 lr: 4.063999174056654e-05 loss: 0.1013 (0.0955) time: 2.6115 data: 0.0061 max mem: 33369 +Epoch: [8] [ 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2.6121 data: 0.0056 max mem: 33369 +Epoch: [8] [ 630/1319] eta: 0:30:10 lr: 4.0351857451192053e-05 loss: 0.0935 (0.0955) time: 2.6111 data: 0.0056 max mem: 33369 +Epoch: [8] [ 640/1319] eta: 0:29:44 lr: 4.034312254764333e-05 loss: 0.0804 (0.0953) time: 2.6021 data: 0.0058 max mem: 33369 +Epoch: [8] [ 650/1319] eta: 0:29:17 lr: 4.033438743395174e-05 loss: 0.0790 (0.0953) time: 2.5954 data: 0.0058 max mem: 33369 +Epoch: [8] [ 660/1319] eta: 0:28:51 lr: 4.032565211006165e-05 loss: 0.0872 (0.0951) time: 2.5910 data: 0.0058 max mem: 33369 +Epoch: [8] [ 670/1319] eta: 0:28:24 lr: 4.031691657591742e-05 loss: 0.0872 (0.0950) time: 2.5804 data: 0.0060 max mem: 33369 +Epoch: [8] [ 680/1319] eta: 0:27:57 lr: 4.030818083146336e-05 loss: 0.0810 (0.0948) time: 2.5846 data: 0.0060 max mem: 33369 +Epoch: [8] [ 690/1319] eta: 0:27:31 lr: 4.029944487664375e-05 loss: 0.0849 (0.0951) time: 2.5970 data: 0.0059 max mem: 33369 +Epoch: [8] [ 700/1319] eta: 0:27:04 lr: 4.0290708711402866e-05 loss: 0.0877 (0.0949) time: 2.5967 data: 0.0057 max mem: 33369 +Epoch: [8] [ 710/1319] eta: 0:26:38 lr: 4.028197233568494e-05 loss: 0.0861 (0.0951) time: 2.6259 data: 0.0056 max mem: 33369 +Epoch: [8] [ 720/1319] eta: 0:26:12 lr: 4.027323574943419e-05 loss: 0.1008 (0.0951) time: 2.6490 data: 0.0056 max mem: 33369 +Epoch: [8] [ 730/1319] eta: 0:25:46 lr: 4.0264498952594776e-05 loss: 0.0833 (0.0949) time: 2.6257 data: 0.0057 max mem: 33369 +Epoch: [8] [ 740/1319] eta: 0:25:20 lr: 4.0255761945110847e-05 loss: 0.0795 (0.0950) time: 2.6389 data: 0.0060 max mem: 33369 +Epoch: [8] [ 750/1319] eta: 0:24:53 lr: 4.0247024726926543e-05 loss: 0.0892 (0.0950) time: 2.6292 data: 0.0060 max mem: 33369 +Epoch: [8] [ 760/1319] eta: 0:24:27 lr: 4.0238287297985935e-05 loss: 0.0911 (0.0951) time: 2.6051 data: 0.0058 max mem: 33369 +Epoch: [8] [ 770/1319] eta: 0:24:01 lr: 4.022954965823311e-05 loss: 0.0930 (0.0950) time: 2.6339 data: 0.0059 max mem: 33369 +Epoch: [8] [ 780/1319] eta: 0:23:35 lr: 4.0220811807612084e-05 loss: 0.0930 (0.0951) time: 2.6399 data: 0.0058 max mem: 33369 +Epoch: [8] [ 790/1319] eta: 0:23:08 lr: 4.021207374606688e-05 loss: 0.1018 (0.0953) time: 2.6076 data: 0.0057 max mem: 33369 +Epoch: [8] [ 800/1319] eta: 0:22:42 lr: 4.0203335473541464e-05 loss: 0.0941 (0.0953) time: 2.5826 data: 0.0059 max mem: 33369 +Epoch: [8] [ 810/1319] eta: 0:22:15 lr: 4.01945969899798e-05 loss: 0.0941 (0.0953) time: 2.6070 data: 0.0057 max mem: 33369 +Epoch: [8] [ 820/1319] eta: 0:21:49 lr: 4.0185858295325805e-05 loss: 0.0949 (0.0953) time: 2.6276 data: 0.0058 max mem: 33369 +Epoch: [8] [ 830/1319] eta: 0:21:23 lr: 4.017711938952337e-05 loss: 0.0847 (0.0953) time: 2.6020 data: 0.0059 max mem: 33369 +Epoch: [8] [ 840/1319] eta: 0:20:56 lr: 4.0168380272516376e-05 loss: 0.1047 (0.0955) time: 2.5917 data: 0.0060 max mem: 33369 +Epoch: [8] [ 850/1319] eta: 0:20:30 lr: 4.0159640944248643e-05 loss: 0.0877 (0.0955) time: 2.6166 data: 0.0059 max mem: 33369 +Epoch: [8] [ 860/1319] eta: 0:20:04 lr: 4.0150901404663985e-05 loss: 0.0825 (0.0954) time: 2.6336 data: 0.0058 max mem: 33369 +Epoch: [8] [ 870/1319] eta: 0:19:38 lr: 4.0142161653706185e-05 loss: 0.0972 (0.0955) time: 2.6323 data: 0.0058 max mem: 33369 +Epoch: [8] [ 880/1319] eta: 0:19:12 lr: 4.013342169131899e-05 loss: 0.1027 (0.0956) time: 2.6495 data: 0.0057 max mem: 33369 +Epoch: [8] [ 890/1319] eta: 0:18:45 lr: 4.012468151744613e-05 loss: 0.1016 (0.0960) time: 2.6492 data: 0.0056 max mem: 33369 +Epoch: [8] [ 900/1319] eta: 0:18:19 lr: 4.01159411320313e-05 loss: 0.1007 (0.0962) time: 2.6194 data: 0.0057 max mem: 33369 +Epoch: [8] [ 910/1319] eta: 0:17:53 lr: 4.010720053501816e-05 loss: 0.0881 (0.0962) time: 2.6028 data: 0.0058 max mem: 33369 +Epoch: [8] [ 920/1319] eta: 0:17:26 lr: 4.009845972635034e-05 loss: 0.0797 (0.0960) time: 2.5939 data: 0.0058 max mem: 33369 +Epoch: [8] [ 930/1319] eta: 0:17:00 lr: 4.008971870597147e-05 loss: 0.0764 (0.0958) time: 2.6028 data: 0.0058 max mem: 33369 +Epoch: [8] [ 940/1319] eta: 0:16:34 lr: 4.008097747382511e-05 loss: 0.0885 (0.0959) time: 2.6469 data: 0.0058 max mem: 33369 +Epoch: [8] [ 950/1319] eta: 0:16:08 lr: 4.0072236029854826e-05 loss: 0.1078 (0.0962) time: 2.6421 data: 0.0057 max mem: 33369 +Epoch: [8] [ 960/1319] eta: 0:15:42 lr: 4.006349437400413e-05 loss: 0.1078 (0.0964) time: 2.6335 data: 0.0058 max mem: 33369 +Epoch: [8] [ 970/1319] eta: 0:15:15 lr: 4.005475250621652e-05 loss: 0.1013 (0.0964) time: 2.6403 data: 0.0059 max mem: 33369 +Epoch: [8] [ 980/1319] eta: 0:14:49 lr: 4.004601042643546e-05 loss: 0.0840 (0.0963) time: 2.6111 data: 0.0058 max mem: 33369 +Epoch: [8] [ 990/1319] eta: 0:14:23 lr: 4.003726813460439e-05 loss: 0.0844 (0.0963) time: 2.6230 data: 0.0058 max mem: 33369 +Epoch: [8] [1000/1319] eta: 0:13:57 lr: 4.0028525630666715e-05 loss: 0.0985 (0.0963) time: 2.6489 data: 0.0060 max mem: 33369 +Epoch: [8] [1010/1319] eta: 0:13:31 lr: 4.00197829145658e-05 loss: 0.1124 (0.0967) time: 2.6501 data: 0.0060 max mem: 33369 +Epoch: [8] [1020/1319] eta: 0:13:04 lr: 4.001103998624502e-05 loss: 0.1126 (0.0969) time: 2.6336 data: 0.0059 max mem: 33369 +Epoch: [8] [1030/1319] eta: 0:12:38 lr: 4.000229684564768e-05 loss: 0.0920 (0.0968) time: 2.6151 data: 0.0059 max mem: 33369 +Epoch: [8] [1040/1319] eta: 0:12:12 lr: 3.9993553492717074e-05 loss: 0.0851 (0.0969) time: 2.6151 data: 0.0057 max mem: 33369 +Epoch: [8] [1050/1319] eta: 0:11:45 lr: 3.998480992739647e-05 loss: 0.1132 (0.0973) time: 2.6017 data: 0.0057 max mem: 33369 +Epoch: [8] [1060/1319] eta: 0:11:19 lr: 3.9976066149629094e-05 loss: 0.0980 (0.0973) time: 2.6170 data: 0.0058 max mem: 33369 +Epoch: [8] [1070/1319] eta: 0:10:53 lr: 3.9967322159358156e-05 loss: 0.0897 (0.0973) time: 2.6422 data: 0.0059 max mem: 33369 +Epoch: [8] [1080/1319] eta: 0:10:27 lr: 3.995857795652683e-05 loss: 0.0965 (0.0975) time: 2.6111 data: 0.0058 max mem: 33369 +Epoch: [8] [1090/1319] eta: 0:10:00 lr: 3.994983354107826e-05 loss: 0.0980 (0.0975) time: 2.5909 data: 0.0059 max mem: 33369 +Epoch: [8] [1100/1319] eta: 0:09:34 lr: 3.994108891295557e-05 loss: 0.0832 (0.0975) time: 2.5908 data: 0.0060 max mem: 33369 +Epoch: [8] [1110/1319] eta: 0:09:08 lr: 3.9932344072101854e-05 loss: 0.0832 (0.0976) time: 2.6208 data: 0.0059 max mem: 33369 +Epoch: [8] [1120/1319] eta: 0:08:42 lr: 3.9923599018460164e-05 loss: 0.0933 (0.0975) time: 2.6461 data: 0.0059 max mem: 33369 +Epoch: [8] [1130/1319] eta: 0:08:16 lr: 3.991485375197353e-05 loss: 0.0967 (0.0976) time: 2.6470 data: 0.0059 max mem: 33369 +Epoch: [8] [1140/1319] eta: 0:07:49 lr: 3.990610827258495e-05 loss: 0.0926 (0.0975) time: 2.6232 data: 0.0058 max mem: 33369 +Epoch: [8] [1150/1319] eta: 0:07:23 lr: 3.9897362580237394e-05 loss: 0.0744 (0.0973) time: 2.6326 data: 0.0056 max mem: 33369 +Epoch: [8] [1160/1319] eta: 0:06:57 lr: 3.988861667487383e-05 loss: 0.0782 (0.0974) time: 2.6446 data: 0.0057 max mem: 33369 +Epoch: [8] [1170/1319] eta: 0:06:31 lr: 3.987987055643715e-05 loss: 0.0886 (0.0975) time: 2.6313 data: 0.0059 max mem: 33369 +Epoch: [8] [1180/1319] eta: 0:06:04 lr: 3.9871124224870237e-05 loss: 0.0948 (0.0976) time: 2.6371 data: 0.0058 max mem: 33369 +Epoch: [8] [1190/1319] eta: 0:05:38 lr: 3.986237768011596e-05 loss: 0.1052 (0.0976) time: 2.6386 data: 0.0058 max mem: 33369 +Epoch: [8] [1200/1319] eta: 0:05:12 lr: 3.985363092211714e-05 loss: 0.0858 (0.0975) time: 2.6237 data: 0.0059 max mem: 33369 +Epoch: [8] [1210/1319] eta: 0:04:46 lr: 3.984488395081657e-05 loss: 0.0834 (0.0975) time: 2.5940 data: 0.0058 max mem: 33369 +Epoch: [8] [1220/1319] eta: 0:04:19 lr: 3.9836136766157016e-05 loss: 0.0950 (0.0975) time: 2.5955 data: 0.0059 max mem: 33369 +Epoch: [8] [1230/1319] eta: 0:03:53 lr: 3.9827389368081224e-05 loss: 0.0963 (0.0975) time: 2.6028 data: 0.0060 max mem: 33369 +Epoch: [8] [1240/1319] eta: 0:03:27 lr: 3.9818641756531906e-05 loss: 0.1016 (0.0975) time: 2.5930 data: 0.0060 max mem: 33369 +Epoch: [8] [1250/1319] eta: 0:03:01 lr: 3.980989393145173e-05 loss: 0.0917 (0.0974) time: 2.6135 data: 0.0058 max mem: 33369 +Epoch: [8] [1260/1319] eta: 0:02:34 lr: 3.9801145892783356e-05 loss: 0.0839 (0.0974) time: 2.6271 data: 0.0059 max mem: 33369 +Epoch: [8] [1270/1319] eta: 0:02:08 lr: 3.97923976404694e-05 loss: 0.0828 (0.0973) time: 2.6015 data: 0.0061 max mem: 33369 +Epoch: [8] [1280/1319] eta: 0:01:42 lr: 3.978364917445246e-05 loss: 0.0896 (0.0974) time: 2.5890 data: 0.0061 max mem: 33369 +Epoch: [8] [1290/1319] eta: 0:01:16 lr: 3.9774900494675086e-05 loss: 0.0901 (0.0973) time: 2.6120 data: 0.0060 max mem: 33369 +Epoch: [8] [1300/1319] eta: 0:00:49 lr: 3.976615160107982e-05 loss: 0.1058 (0.0975) time: 2.6205 data: 0.0058 max mem: 33369 +Epoch: [8] [1310/1319] eta: 0:00:23 lr: 3.975740249360917e-05 loss: 0.1056 (0.0975) time: 2.6255 data: 0.0057 max mem: 33369 +Epoch: [8] Total time: 0:57:40 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 2:05:51 time: 2.9347 data: 2.8564 max mem: 33369 +Test: [ 100/2573] eta: 0:04:07 time: 0.0718 data: 0.0011 max mem: 33369 +Test: [ 200/2573] eta: 0:03:27 time: 0.0735 data: 0.0011 max mem: 33369 +Test: [ 300/2573] eta: 0:03:07 time: 0.0753 data: 0.0011 max mem: 33369 +Test: [ 400/2573] eta: 0:02:54 time: 0.0753 data: 0.0011 max mem: 33369 +Test: [ 500/2573] eta: 0:02:43 time: 0.0736 data: 0.0011 max mem: 33369 +Test: [ 600/2573] eta: 0:02:33 time: 0.0737 data: 0.0012 max mem: 33369 +Test: [ 700/2573] eta: 0:02:25 time: 0.0737 data: 0.0012 max mem: 33369 +Test: [ 800/2573] eta: 0:02:17 time: 0.0770 data: 0.0011 max mem: 33369 +Test: [ 900/2573] eta: 0:02:08 time: 0.0737 data: 0.0011 max mem: 33369 +Test: [1000/2573] eta: 0:02:00 time: 0.0741 data: 0.0012 max mem: 33369 +Test: [1100/2573] eta: 0:01:52 time: 0.0738 data: 0.0011 max mem: 33369 +Test: [1200/2573] eta: 0:01:44 time: 0.0738 data: 0.0011 max mem: 33369 +Test: [1300/2573] eta: 0:01:36 time: 0.0738 data: 0.0011 max mem: 33369 +Test: [1400/2573] eta: 0:01:29 time: 0.0721 data: 0.0011 max mem: 33369 +Test: [1500/2573] eta: 0:01:21 time: 0.0737 data: 0.0011 max mem: 33369 +Test: [1600/2573] eta: 0:01:13 time: 0.0771 data: 0.0011 max mem: 33369 +Test: [1700/2573] eta: 0:01:06 time: 0.0721 data: 0.0011 max mem: 33369 +Test: [1800/2573] eta: 0:00:58 time: 0.0754 data: 0.0011 max mem: 33369 +Test: [1900/2573] eta: 0:00:50 time: 0.0722 data: 0.0011 max mem: 33369 +Test: [2000/2573] eta: 0:00:43 time: 0.0739 data: 0.0011 max mem: 33369 +Test: [2100/2573] eta: 0:00:35 time: 0.0754 data: 0.0011 max mem: 33369 +Test: [2200/2573] eta: 0:00:27 time: 0.0754 data: 0.0011 max mem: 33369 +Test: [2300/2573] eta: 0:00:20 time: 0.0754 data: 0.0011 max mem: 33369 +Test: [2400/2573] eta: 0:00:12 time: 0.0705 data: 0.0011 max mem: 33369 +Test: [2500/2573] eta: 0:00:05 time: 0.0740 data: 0.0011 max mem: 33369 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: Total time: 0:03:13 +Final results: +Mean IoU is 57.01 + + precision@0.5 = 63.85 + precision@0.6 = 57.27 + precision@0.7 = 49.20 + precision@0.8 = 37.52 + precision@0.9 = 16.34 + overall IoU = 57.88 + +Average object IoU 57.01405726560294 +Overall IoU 57.87966537475586 +Better epoch: 8 + +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [9] [ 0/1319] eta: 1:33:00 lr: 3.974952811397457e-05 loss: 0.1469 (0.1469) time: 4.2306 data: 1.3419 max mem: 33369 +Epoch: [9] [ 10/1319] eta: 1:00:53 lr: 3.974077859998216e-05 loss: 0.1039 (0.1009) time: 2.7911 data: 0.1271 max mem: 33369 +Epoch: [9] [ 20/1319] eta: 0:58:20 lr: 3.9732028871947454e-05 loss: 0.0762 (0.0904) time: 2.6176 data: 0.0056 max mem: 33369 +Epoch: [9] [ 30/1319] eta: 0:57:14 lr: 3.972327892981283e-05 loss: 0.0652 (0.0906) time: 2.5949 data: 0.0058 max mem: 33369 +Epoch: [9] [ 40/1319] eta: 0:56:32 lr: 3.971452877352066e-05 loss: 0.0696 (0.0896) time: 2.6076 data: 0.0060 max mem: 33369 +Epoch: [9] [ 50/1319] eta: 0:55:48 lr: 3.9705778403013264e-05 loss: 0.0813 (0.0912) time: 2.5990 data: 0.0062 max mem: 33369 +Epoch: [9] [ 60/1319] eta: 0:55:20 lr: 3.969702781823294e-05 loss: 0.0759 (0.0894) time: 2.6062 data: 0.0062 max mem: 33369 +Epoch: [9] [ 70/1319] eta: 0:54:44 lr: 3.9688277019121967e-05 loss: 0.0759 (0.0889) time: 2.6073 data: 0.0063 max mem: 33369 +Epoch: [9] [ 80/1319] eta: 0:54:16 lr: 3.967952600562257e-05 loss: 0.0766 (0.0885) time: 2.6033 data: 0.0063 max mem: 33369 +Epoch: [9] [ 90/1319] eta: 0:53:52 lr: 3.967077477767697e-05 loss: 0.0833 (0.0888) time: 2.6305 data: 0.0060 max mem: 33369 +Epoch: [9] [ 100/1319] eta: 0:53:24 lr: 3.966202333522733e-05 loss: 0.0833 (0.0897) time: 2.6282 data: 0.0059 max mem: 33369 +Epoch: [9] [ 110/1319] eta: 0:52:57 lr: 3.965327167821583e-05 loss: 0.0788 (0.0883) time: 2.6217 data: 0.0060 max mem: 33369 +Epoch: [9] [ 120/1319] eta: 0:52:28 lr: 3.9644519806584564e-05 loss: 0.0762 (0.0879) time: 2.6149 data: 0.0059 max mem: 33369 +Epoch: [9] [ 130/1319] eta: 0:52:03 lr: 3.963576772027564e-05 loss: 0.0741 (0.0870) time: 2.6160 data: 0.0058 max mem: 33369 +Epoch: [9] [ 140/1319] eta: 0:51:35 lr: 3.96270154192311e-05 loss: 0.0762 (0.0867) time: 2.6218 data: 0.0058 max mem: 33369 +Epoch: [9] [ 150/1319] eta: 0:51:07 lr: 3.9618262903393e-05 loss: 0.0847 (0.0863) time: 2.6067 data: 0.0059 max mem: 33369 +Epoch: [9] [ 160/1319] eta: 0:50:41 lr: 3.960951017270332e-05 loss: 0.0705 (0.0852) time: 2.6148 data: 0.0059 max mem: 33369 +Epoch: [9] [ 170/1319] eta: 0:50:16 lr: 3.9600757227104046e-05 loss: 0.0720 (0.0861) time: 2.6322 data: 0.0059 max mem: 33369 +Epoch: [9] [ 180/1319] eta: 0:49:48 lr: 3.95920040665371e-05 loss: 0.0876 (0.0859) time: 2.6233 data: 0.0059 max mem: 33369 +Epoch: [9] [ 190/1319] eta: 0:49:20 lr: 3.958325069094442e-05 loss: 0.0833 (0.0863) time: 2.5994 data: 0.0060 max mem: 33369 +Epoch: [9] [ 200/1319] eta: 0:48:52 lr: 3.957449710026786e-05 loss: 0.0823 (0.0864) time: 2.5913 data: 0.0060 max mem: 33369 +Epoch: [9] [ 210/1319] eta: 0:48:25 lr: 3.9565743294449283e-05 loss: 0.0800 (0.0859) time: 2.6022 data: 0.0060 max mem: 33369 +Epoch: [9] [ 220/1319] eta: 0:47:59 lr: 3.955698927343052e-05 loss: 0.0810 (0.0857) time: 2.6089 data: 0.0059 max mem: 33369 +Epoch: [9] [ 230/1319] eta: 0:47:31 lr: 3.954823503715335e-05 loss: 0.0759 (0.0858) time: 2.6006 data: 0.0060 max mem: 33369 +Epoch: [9] [ 240/1319] eta: 0:47:02 lr: 3.953948058555954e-05 loss: 0.0748 (0.0857) time: 2.5760 data: 0.0061 max mem: 33369 +Epoch: [9] [ 250/1319] eta: 0:46:36 lr: 3.9530725918590825e-05 loss: 0.0789 (0.0858) time: 2.5852 data: 0.0061 max mem: 33369 +Epoch: [9] [ 260/1319] eta: 0:46:09 lr: 3.952197103618889e-05 loss: 0.0789 (0.0858) time: 2.6024 data: 0.0059 max mem: 33369 +Epoch: [9] [ 270/1319] eta: 0:45:44 lr: 3.951321593829542e-05 loss: 0.0849 (0.0861) time: 2.6187 data: 0.0059 max mem: 33369 +Epoch: [9] [ 280/1319] eta: 0:45:18 lr: 3.9504460624852056e-05 loss: 0.0875 (0.0862) time: 2.6332 data: 0.0059 max mem: 33369 +Epoch: [9] [ 290/1319] eta: 0:44:51 lr: 3.94957050958004e-05 loss: 0.0742 (0.0864) time: 2.6090 data: 0.0058 max mem: 33369 +Epoch: [9] [ 300/1319] eta: 0:44:24 lr: 3.9486949351082035e-05 loss: 0.0692 (0.0864) time: 2.5877 data: 0.0060 max mem: 33369 +Epoch: [9] [ 310/1319] eta: 0:43:57 lr: 3.9478193390638515e-05 loss: 0.0966 (0.0870) time: 2.5919 data: 0.0062 max mem: 33369 +Epoch: [9] [ 320/1319] eta: 0:43:32 lr: 3.946943721441136e-05 loss: 0.0975 (0.0872) time: 2.6256 data: 0.0060 max mem: 33369 +Epoch: [9] [ 330/1319] eta: 0:43:07 lr: 3.946068082234206e-05 loss: 0.0777 (0.0867) time: 2.6411 data: 0.0059 max mem: 33369 +Epoch: [9] [ 340/1319] eta: 0:42:41 lr: 3.945192421437206e-05 loss: 0.0819 (0.0874) time: 2.6337 data: 0.0060 max mem: 33369 +Epoch: [9] [ 350/1319] eta: 0:42:15 lr: 3.944316739044282e-05 loss: 0.0883 (0.0874) time: 2.6217 data: 0.0059 max mem: 33369 +Epoch: [9] [ 360/1319] eta: 0:41:48 lr: 3.94344103504957e-05 loss: 0.0854 (0.0875) time: 2.6066 data: 0.0059 max mem: 33369 +Epoch: [9] [ 370/1319] eta: 0:41:23 lr: 3.94256530944721e-05 loss: 0.0891 (0.0876) time: 2.6280 data: 0.0060 max mem: 33369 +Epoch: [9] [ 380/1319] eta: 0:40:56 lr: 3.9416895622313336e-05 loss: 0.0950 (0.0879) time: 2.6225 data: 0.0060 max mem: 33369 +Epoch: [9] [ 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(0.0907) time: 2.6117 data: 0.0062 max mem: 33369 +Epoch: [9] [ 790/1319] eta: 0:23:09 lr: 3.9057652443333534e-05 loss: 0.0879 (0.0907) time: 2.6060 data: 0.0061 max mem: 33369 +Epoch: [9] [ 800/1319] eta: 0:22:43 lr: 3.904888584012046e-05 loss: 0.0879 (0.0907) time: 2.6000 data: 0.0061 max mem: 33369 +Epoch: [9] [ 810/1319] eta: 0:22:16 lr: 3.904011901822068e-05 loss: 0.0954 (0.0908) time: 2.6033 data: 0.0063 max mem: 33369 +Epoch: [9] [ 820/1319] eta: 0:21:50 lr: 3.9031351977574175e-05 loss: 0.0842 (0.0907) time: 2.5825 data: 0.0063 max mem: 33369 +Epoch: [9] [ 830/1319] eta: 0:21:23 lr: 3.9022584718120886e-05 loss: 0.0918 (0.0909) time: 2.5785 data: 0.0063 max mem: 33369 +Epoch: [9] [ 840/1319] eta: 0:20:57 lr: 3.901381723980073e-05 loss: 0.0905 (0.0908) time: 2.5998 data: 0.0062 max mem: 33369 +Epoch: [9] [ 850/1319] eta: 0:20:31 lr: 3.900504954255358e-05 loss: 0.0792 (0.0907) time: 2.6179 data: 0.0062 max mem: 33369 +Epoch: [9] [ 860/1319] eta: 0:20:05 lr: 3.899628162631931e-05 loss: 0.0847 (0.0907) time: 2.6276 data: 0.0063 max mem: 33369 +Epoch: [9] [ 870/1319] eta: 0:19:38 lr: 3.898751349103772e-05 loss: 0.0847 (0.0907) time: 2.6266 data: 0.0063 max mem: 33369 +Epoch: [9] [ 880/1319] eta: 0:19:12 lr: 3.8978745136648617e-05 loss: 0.0776 (0.0907) time: 2.6198 data: 0.0065 max mem: 33369 +Epoch: [9] [ 890/1319] eta: 0:18:46 lr: 3.896997656309173e-05 loss: 0.0858 (0.0908) time: 2.6237 data: 0.0064 max mem: 33369 +Epoch: [9] [ 900/1319] eta: 0:18:20 lr: 3.896120777030681e-05 loss: 0.0801 (0.0907) time: 2.6468 data: 0.0062 max mem: 33369 +Epoch: [9] [ 910/1319] eta: 0:17:53 lr: 3.895243875823353e-05 loss: 0.0786 (0.0908) time: 2.6326 data: 0.0061 max mem: 33369 +Epoch: [9] [ 920/1319] eta: 0:17:27 lr: 3.894366952681158e-05 loss: 0.0860 (0.0908) time: 2.6210 data: 0.0063 max mem: 33369 +Epoch: [9] [ 930/1319] eta: 0:17:01 lr: 3.8934900075980555e-05 loss: 0.0910 (0.0909) time: 2.6355 data: 0.0064 max mem: 33369 +Epoch: [9] [ 940/1319] eta: 0:16:35 lr: 3.8926130405680076e-05 loss: 0.1002 (0.0909) time: 2.6559 data: 0.0064 max mem: 33369 +Epoch: [9] [ 950/1319] eta: 0:16:09 lr: 3.8917360515849704e-05 loss: 0.0729 (0.0908) time: 2.6742 data: 0.0067 max mem: 33369 +Epoch: [9] [ 960/1319] eta: 0:15:43 lr: 3.8908590406428975e-05 loss: 0.0722 (0.0907) time: 2.7110 data: 0.0067 max mem: 33369 +Epoch: [9] [ 970/1319] eta: 0:15:17 lr: 3.889982007735738e-05 loss: 0.0750 (0.0907) time: 2.7494 data: 0.0067 max mem: 33369 +Epoch: [9] [ 980/1319] eta: 0:14:51 lr: 3.889104952857442e-05 loss: 0.0714 (0.0906) time: 2.7142 data: 0.0065 max mem: 33369 +Epoch: [9] [ 990/1319] eta: 0:14:25 lr: 3.888227876001951e-05 loss: 0.0778 (0.0907) time: 2.7046 data: 0.0063 max mem: 33369 +Epoch: [9] [1000/1319] eta: 0:13:59 lr: 3.887350777163206e-05 loss: 0.0863 (0.0908) time: 2.7083 data: 0.0064 max mem: 33369 +Epoch: [9] [1010/1319] eta: 0:13:33 lr: 3.886473656335145e-05 loss: 0.0839 (0.0908) time: 2.6925 data: 0.0063 max mem: 33369 +Epoch: [9] [1020/1319] eta: 0:13:07 lr: 3.8855965135117015e-05 loss: 0.0831 (0.0908) time: 2.6773 data: 0.0063 max mem: 33369 +Epoch: [9] [1030/1319] eta: 0:12:40 lr: 3.8847193486868084e-05 loss: 0.0831 (0.0908) time: 2.6608 data: 0.0064 max mem: 33369 +Epoch: [9] [1040/1319] eta: 0:12:14 lr: 3.883842161854392e-05 loss: 0.0747 (0.0907) time: 2.6751 data: 0.0064 max mem: 33369 +Epoch: [9] [1050/1319] eta: 0:11:48 lr: 3.8829649530083775e-05 loss: 0.0852 (0.0909) time: 2.6762 data: 0.0062 max mem: 33369 +Epoch: [9] [1060/1319] eta: 0:11:22 lr: 3.882087722142687e-05 loss: 0.0961 (0.0911) time: 2.6797 data: 0.0064 max mem: 33369 +Epoch: [9] [1070/1319] eta: 0:10:56 lr: 3.8812104692512384e-05 loss: 0.0864 (0.0911) time: 2.7182 data: 0.0063 max mem: 33369 +Epoch: [9] [1080/1319] eta: 0:10:29 lr: 3.880333194327947e-05 loss: 0.0810 (0.0910) time: 2.7100 data: 0.0061 max mem: 33369 +Epoch: [9] [1090/1319] eta: 0:10:03 lr: 3.879455897366725e-05 loss: 0.0846 (0.0910) time: 2.6878 data: 0.0062 max mem: 33369 +Epoch: [9] 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+Epoch: [9] [1180/1319] eta: 0:06:06 lr: 3.871559232002716e-05 loss: 0.0801 (0.0905) time: 2.6762 data: 0.0064 max mem: 33369 +Epoch: [9] [1190/1319] eta: 0:05:40 lr: 3.870681714326634e-05 loss: 0.0870 (0.0907) time: 2.6669 data: 0.0064 max mem: 33369 +Epoch: [9] [1200/1319] eta: 0:05:14 lr: 3.86980417454544e-05 loss: 0.0788 (0.0906) time: 2.6612 data: 0.0065 max mem: 33369 +Epoch: [9] [1210/1319] eta: 0:04:47 lr: 3.8689266126530076e-05 loss: 0.0788 (0.0907) time: 2.6720 data: 0.0066 max mem: 33369 +Epoch: [9] [1220/1319] eta: 0:04:21 lr: 3.868049028643206e-05 loss: 0.0799 (0.0907) time: 2.6685 data: 0.0064 max mem: 33369 +Epoch: [9] [1230/1319] eta: 0:03:55 lr: 3.867171422509902e-05 loss: 0.0811 (0.0906) time: 2.6558 data: 0.0063 max mem: 33369 +Epoch: [9] [1240/1319] eta: 0:03:28 lr: 3.866293794246959e-05 loss: 0.0852 (0.0908) time: 2.6608 data: 0.0063 max mem: 33369 +Epoch: [9] [1250/1319] eta: 0:03:02 lr: 3.8654161438482394e-05 loss: 0.0854 (0.0908) time: 2.6692 data: 0.0066 max mem: 33369 +Epoch: [9] [1260/1319] eta: 0:02:35 lr: 3.864538471307598e-05 loss: 0.0768 (0.0907) time: 2.7074 data: 0.0068 max mem: 33369 +Epoch: [9] [1270/1319] eta: 0:02:09 lr: 3.863660776618888e-05 loss: 0.0864 (0.0907) time: 2.7140 data: 0.0067 max mem: 33369 +Epoch: [9] [1280/1319] eta: 0:01:43 lr: 3.8627830597759606e-05 loss: 0.0952 (0.0907) time: 2.7002 data: 0.0067 max mem: 33369 +Epoch: [9] [1290/1319] eta: 0:01:16 lr: 3.861905320772664e-05 loss: 0.0990 (0.0909) time: 2.6746 data: 0.0065 max mem: 33369 +Epoch: [9] [1300/1319] eta: 0:00:50 lr: 3.861027559602841e-05 loss: 0.0862 (0.0908) time: 2.6719 data: 0.0065 max mem: 33369 +Epoch: [9] [1310/1319] eta: 0:00:23 lr: 3.860149776260333e-05 loss: 0.0930 (0.0910) time: 2.6605 data: 0.0063 max mem: 33369 +Epoch: [9] Total time: 0:58:07 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 3:00:17 time: 4.2044 data: 4.0865 max mem: 33369 +Test: [ 100/2573] eta: 0:04:39 time: 0.0718 data: 0.0011 max mem: 33369 +Test: [ 200/2573] eta: 0:03:42 time: 0.0733 data: 0.0011 max mem: 33369 +Test: [ 300/2573] eta: 0:03:16 time: 0.0752 data: 0.0011 max mem: 33369 +Test: [ 400/2573] eta: 0:03:00 time: 0.0752 data: 0.0011 max mem: 33369 +Test: [ 500/2573] eta: 0:02:48 time: 0.0736 data: 0.0011 max mem: 33369 +Test: [ 600/2573] eta: 0:02:38 time: 0.0737 data: 0.0012 max mem: 33369 +Test: [ 700/2573] eta: 0:02:29 time: 0.0737 data: 0.0011 max mem: 33369 +Test: [ 800/2573] eta: 0:02:19 time: 0.0770 data: 0.0011 max mem: 33369 +Test: [ 900/2573] eta: 0:02:11 time: 0.0738 data: 0.0011 max mem: 33369 +Test: [1000/2573] eta: 0:02:02 time: 0.0738 data: 0.0011 max mem: 33369 +Test: [1100/2573] eta: 0:01:54 time: 0.0738 data: 0.0011 max mem: 33369 +Test: [1200/2573] eta: 0:01:46 time: 0.0738 data: 0.0011 max mem: 33369 +Test: [1300/2573] eta: 0:01:38 time: 0.0737 data: 0.0011 max mem: 33369 +Test: [1400/2573] eta: 0:01:30 time: 0.0721 data: 0.0011 max mem: 33369 +Test: [1500/2573] eta: 0:01:22 time: 0.0739 data: 0.0012 max mem: 33369 +Test: [1600/2573] eta: 0:01:14 time: 0.0772 data: 0.0012 max mem: 33369 +Test: [1700/2573] eta: 0:01:06 time: 0.0722 data: 0.0011 max mem: 33369 +Test: [1800/2573] eta: 0:00:58 time: 0.0755 data: 0.0012 max mem: 33369 +Test: [1900/2573] eta: 0:00:51 time: 0.0721 data: 0.0012 max mem: 33369 +Test: [2000/2573] eta: 0:00:43 time: 0.0738 data: 0.0011 max mem: 33369 +Test: [2100/2573] eta: 0:00:35 time: 0.0754 data: 0.0011 max mem: 33369 +Test: [2200/2573] eta: 0:00:28 time: 0.0752 data: 0.0011 max mem: 33369 +Test: [2300/2573] eta: 0:00:20 time: 0.0752 data: 0.0011 max mem: 33369 +Test: [2400/2573] eta: 0:00:13 time: 0.0704 data: 0.0011 max mem: 33369 +Test: [2500/2573] eta: 0:00:05 time: 0.0736 data: 0.0011 max mem: 33369 +Test: Total time: 0:03:14 +Final results: +Mean IoU is 58.32 + + precision@0.5 = 64.91 + precision@0.6 = 58.93 + precision@0.7 = 50.57 + precision@0.8 = 39.56 + precision@0.9 = 18.16 + overall IoU = 58.13 + +Average object IoU 58.3190575096401 +Overall IoU 58.12620544433594 +Better epoch: 9 + +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [10] [ 0/1319] eta: 1:35:32 lr: 3.859359752289337e-05 loss: 0.1117 (0.1117) time: 4.3460 data: 1.5099 max mem: 33369 +Epoch: [10] [ 10/1319] eta: 1:02:17 lr: 3.858481926801746e-05 loss: 0.0913 (0.0958) time: 2.8555 data: 0.1428 max mem: 33369 +Epoch: [10] [ 20/1319] eta: 0:59:52 lr: 3.857604079123589e-05 loss: 0.0842 (0.0910) time: 2.6868 data: 0.0060 max mem: 33369 +Epoch: [10] [ 30/1319] eta: 0:58:26 lr: 3.856726209248695e-05 loss: 0.0799 (0.0897) time: 2.6457 data: 0.0063 max mem: 33369 +Epoch: [10] [ 40/1319] eta: 0:57:45 lr: 3.855848317170887e-05 loss: 0.0791 (0.0892) time: 2.6508 data: 0.0064 max mem: 33369 +Epoch: [10] [ 50/1319] eta: 0:57:02 lr: 3.854970402883988e-05 loss: 0.0726 (0.0859) time: 2.6612 data: 0.0061 max mem: 33369 +Epoch: [10] [ 60/1319] eta: 0:56:34 lr: 3.854092466381814e-05 loss: 0.0698 (0.0840) time: 2.6674 data: 0.0063 max mem: 33369 +Epoch: [10] [ 70/1319] eta: 0:56:00 lr: 3.853214507658182e-05 loss: 0.0714 (0.0842) time: 2.6750 data: 0.0063 max mem: 33369 +Epoch: [10] [ 80/1319] eta: 0:55:26 lr: 3.852336526706903e-05 loss: 0.0791 (0.0876) time: 2.6501 data: 0.0062 max mem: 33369 +Epoch: [10] [ 90/1319] eta: 0:54:54 lr: 3.8514585235217835e-05 loss: 0.0754 (0.0867) time: 2.6448 data: 0.0063 max mem: 33369 +Epoch: [10] [ 100/1319] eta: 0:54:23 lr: 3.850580498096631e-05 loss: 0.0736 (0.0875) time: 2.6494 data: 0.0066 max mem: 33369 +Epoch: [10] [ 110/1319] eta: 0:53:58 lr: 3.849702450425245e-05 loss: 0.0743 (0.0866) time: 2.6684 data: 0.0066 max mem: 33369 +Epoch: [10] [ 120/1319] eta: 0:53:35 lr: 3.8488243805014244e-05 loss: 0.0822 (0.0866) time: 2.7024 data: 0.0066 max mem: 33369 +Epoch: [10] [ 130/1319] eta: 0:53:05 lr: 3.8479462883189646e-05 loss: 0.0929 (0.0886) time: 2.6846 data: 0.0067 max mem: 33369 +Epoch: [10] [ 140/1319] eta: 0:52:38 lr: 3.8470681738716575e-05 loss: 0.0835 (0.0887) time: 2.6599 data: 0.0065 max mem: 33369 +Epoch: [10] [ 150/1319] eta: 0:52:08 lr: 3.846190037153291e-05 loss: 0.0706 (0.0878) time: 2.6522 data: 0.0064 max mem: 33369 +Epoch: [10] [ 160/1319] eta: 0:51:42 lr: 3.84531187815765e-05 loss: 0.0761 (0.0872) time: 2.6647 data: 0.0068 max mem: 33369 +Epoch: [10] [ 170/1319] eta: 0:51:20 lr: 3.844433696878517e-05 loss: 0.0709 (0.0861) time: 2.7236 data: 0.0069 max mem: 33369 +Epoch: [10] [ 180/1319] eta: 0:50:55 lr: 3.843555493309671e-05 loss: 0.0702 (0.0858) time: 2.7316 data: 0.0066 max mem: 33369 +Epoch: [10] [ 190/1319] eta: 0:50:29 lr: 3.842677267444885e-05 loss: 0.0765 (0.0858) time: 2.7034 data: 0.0067 max mem: 33369 +Epoch: [10] [ 200/1319] eta: 0:50:03 lr: 3.8417990192779335e-05 loss: 0.0712 (0.0852) time: 2.6946 data: 0.0067 max mem: 33369 +Epoch: [10] [ 210/1319] eta: 0:49:36 lr: 3.8409207488025836e-05 loss: 0.0657 (0.0853) time: 2.6825 data: 0.0066 max mem: 33369 +Epoch: [10] [ 220/1319] eta: 0:49:11 lr: 3.8400424560126e-05 loss: 0.0794 (0.0853) time: 2.6976 data: 0.0063 max mem: 33369 +Epoch: [10] [ 230/1319] eta: 0:48:41 lr: 3.839164140901745e-05 loss: 0.0716 (0.0852) time: 2.6758 data: 0.0063 max mem: 33369 +Epoch: [10] [ 240/1319] eta: 0:48:13 lr: 3.838285803463778e-05 loss: 0.0732 (0.0846) time: 2.6470 data: 0.0065 max mem: 33369 +Epoch: [10] [ 250/1319] eta: 0:47:50 lr: 3.8374074436924536e-05 loss: 0.0736 (0.0851) time: 2.7117 data: 0.0065 max mem: 33369 +Epoch: [10] [ 260/1319] eta: 0:47:21 lr: 3.836529061581523e-05 loss: 0.0709 (0.0846) time: 2.6992 data: 0.0064 max mem: 33369 +Epoch: [10] [ 270/1319] eta: 0:46:53 lr: 3.8356506571247355e-05 loss: 0.0734 (0.0851) time: 2.6460 data: 0.0065 max mem: 33369 +Epoch: [10] [ 280/1319] eta: 0:46:25 lr: 3.834772230315837e-05 loss: 0.0747 (0.0848) time: 2.6482 data: 0.0064 max mem: 33369 +Epoch: [10] [ 290/1319] eta: 0:45:57 lr: 3.833893781148568e-05 loss: 0.0708 (0.0843) time: 2.6498 data: 0.0064 max mem: 33369 +Epoch: [10] [ 300/1319] eta: 0:45:31 lr: 3.833015309616668e-05 loss: 0.0735 (0.0844) time: 2.6779 data: 0.0065 max mem: 33369 +Epoch: [10] [ 310/1319] eta: 0:45:04 lr: 3.832136815713871e-05 loss: 0.0863 (0.0844) time: 2.6863 data: 0.0064 max mem: 33369 +Epoch: [10] [ 320/1319] eta: 0:44:38 lr: 3.83125829943391e-05 loss: 0.0699 (0.0839) time: 2.6862 data: 0.0065 max mem: 33369 +Epoch: [10] [ 330/1319] eta: 0:44:11 lr: 3.830379760770512e-05 loss: 0.0641 (0.0835) time: 2.6825 data: 0.0068 max mem: 33369 +Epoch: [10] [ 340/1319] eta: 0:43:45 lr: 3.829501199717404e-05 loss: 0.0727 (0.0833) time: 2.6922 data: 0.0065 max mem: 33369 +Epoch: [10] [ 350/1319] eta: 0:43:18 lr: 3.828622616268306e-05 loss: 0.0754 (0.0830) time: 2.6905 data: 0.0063 max mem: 33369 +Epoch: [10] [ 360/1319] eta: 0:42:51 lr: 3.8277440104169376e-05 loss: 0.0698 (0.0826) time: 2.6723 data: 0.0065 max mem: 33369 +Epoch: [10] [ 370/1319] eta: 0:42:24 lr: 3.826865382157014e-05 loss: 0.0707 (0.0836) time: 2.6781 data: 0.0066 max mem: 33369 +Epoch: [10] [ 380/1319] eta: 0:41:58 lr: 3.8259867314822454e-05 loss: 0.0806 (0.0835) time: 2.6938 data: 0.0063 max 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+/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 2:07:37 time: 2.9762 data: 2.8970 max mem: 33369 +Test: [ 100/2573] eta: 0:04:08 time: 0.0716 data: 0.0012 max mem: 33369 +Test: [ 200/2573] eta: 0:03:27 time: 0.0735 data: 0.0012 max mem: 33369 +Test: [ 300/2573] eta: 0:03:07 time: 0.0753 data: 0.0011 max mem: 33369 +Test: [ 400/2573] eta: 0:02:54 time: 0.0749 data: 0.0011 max mem: 33369 +Test: [ 500/2573] eta: 0:02:43 time: 0.0736 data: 0.0011 max mem: 33369 +Test: [ 600/2573] eta: 0:02:34 time: 0.0737 data: 0.0011 max mem: 33369 +Test: [ 700/2573] eta: 0:02:25 time: 0.0735 data: 0.0011 max mem: 33369 +Test: [ 800/2573] eta: 0:02:17 time: 0.0768 data: 0.0011 max mem: 33369 +Test: [ 900/2573] eta: 0:02:08 time: 0.0738 data: 0.0011 max mem: 33369 +Test: [1000/2573] eta: 0:02:00 time: 0.0739 data: 0.0012 max mem: 33369 +Test: [1100/2573] eta: 0:01:52 time: 0.0743 data: 0.0012 max mem: 33369 +Test: [1200/2573] eta: 0:01:44 time: 0.0743 data: 0.0012 max mem: 33369 +Test: [1300/2573] eta: 0:01:37 time: 0.0743 data: 0.0012 max mem: 33369 +Test: [1400/2573] eta: 0:01:29 time: 0.0724 data: 0.0012 max mem: 33369 +Test: [1500/2573] eta: 0:01:21 time: 0.0743 data: 0.0012 max mem: 33369 +Test: [1600/2573] eta: 0:01:13 time: 0.0777 data: 0.0012 max mem: 33369 +Test: [1700/2573] eta: 0:01:06 time: 0.0727 data: 0.0012 max mem: 33369 +Test: [1800/2573] eta: 0:00:58 time: 0.0758 data: 0.0012 max mem: 33369 +Test: [1900/2573] eta: 0:00:50 time: 0.0723 data: 0.0012 max mem: 33369 +Test: [2000/2573] eta: 0:00:43 time: 0.0740 data: 0.0012 max mem: 33369 +Test: [2100/2573] eta: 0:00:35 time: 0.0759 data: 0.0012 max mem: 33369 +Test: [2200/2573] eta: 0:00:28 time: 0.0758 data: 0.0011 max mem: 33369 +Test: [2300/2573] eta: 0:00:20 time: 0.0756 data: 0.0012 max mem: 33369 +Test: [2400/2573] eta: 0:00:13 time: 0.0707 data: 0.0011 max mem: 33369 +Test: [2500/2573] eta: 0:00:05 time: 0.0740 data: 0.0012 max mem: 33369 +Test: Total time: 0:03:13 +Final results: +Mean IoU is 60.29 + + precision@0.5 = 67.38 + precision@0.6 = 61.19 + precision@0.7 = 53.21 + precision@0.8 = 41.18 + precision@0.9 = 18.83 + overall IoU = 59.04 + +Average object IoU 60.28689212034056 +Overall IoU 59.042232513427734 +Better epoch: 10 + +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [11] [ 0/1319] eta: 1:39:59 lr: 3.743380655104104e-05 loss: 0.0750 (0.0750) time: 4.5488 data: 1.6211 max mem: 33369 +Epoch: [11] [ 10/1319] eta: 1:02:53 lr: 3.742499848141075e-05 loss: 0.0729 (0.0967) time: 2.8825 data: 0.1536 max mem: 33369 +Epoch: [11] [ 20/1319] eta: 1:00:25 lr: 3.741619018144089e-05 loss: 0.0670 (0.0829) time: 2.7034 data: 0.0061 max mem: 33369 +Epoch: [11] [ 30/1319] eta: 0:59:27 lr: 3.7407381651065185e-05 loss: 0.0651 (0.0785) time: 2.7041 data: 0.0060 max mem: 33369 +Epoch: [11] [ 40/1319] eta: 0:58:21 lr: 3.739857289021734e-05 loss: 0.0750 (0.0815) time: 2.6812 data: 0.0066 max mem: 33369 +Epoch: [11] [ 50/1319] eta: 0:57:46 lr: 3.738976389883098e-05 loss: 0.0758 (0.0868) time: 2.6762 data: 0.0066 max mem: 33369 +Epoch: [11] [ 60/1319] eta: 0:57:08 lr: 3.738095467683973e-05 loss: 0.0592 (0.0827) time: 2.6944 data: 0.0067 max mem: 33369 +Epoch: [11] [ 70/1319] eta: 0:56:25 lr: 3.737214522417717e-05 loss: 0.0610 (0.0816) time: 2.6558 data: 0.0065 max mem: 33369 +Epoch: [11] [ 80/1319] eta: 0:55:51 lr: 3.736333554077684e-05 loss: 0.0685 (0.0808) time: 2.6482 data: 0.0065 max mem: 33369 +Epoch: [11] [ 90/1319] eta: 0:55:24 lr: 3.735452562657224e-05 loss: 0.0788 (0.0819) time: 2.6850 data: 0.0068 max mem: 33369 +Epoch: [11] [ 100/1319] eta: 0:54:52 lr: 3.734571548149683e-05 loss: 0.0788 (0.0816) time: 2.6867 data: 0.0067 max mem: 33369 +Epoch: [11] [ 110/1319] eta: 0:54:19 lr: 3.733690510548406e-05 loss: 0.0696 (0.0805) time: 2.6579 data: 0.0067 max mem: 33369 +Epoch: [11] [ 120/1319] eta: 0:53:50 lr: 3.732809449846732e-05 loss: 0.0650 (0.0800) time: 2.6596 data: 0.0065 max mem: 33369 +Epoch: [11] [ 130/1319] eta: 0:53:16 lr: 3.7319283660379954e-05 loss: 0.0596 (0.0780) time: 2.6451 data: 0.0065 max mem: 33369 +Epoch: [11] [ 140/1319] eta: 0:52:44 lr: 3.7310472591155297e-05 loss: 0.0645 (0.0774) time: 2.6189 data: 0.0067 max mem: 33369 +Epoch: [11] [ 150/1319] eta: 0:52:12 lr: 3.7301661290726626e-05 loss: 0.0748 (0.0778) time: 2.6245 data: 0.0066 max mem: 33369 +Epoch: [11] [ 160/1319] eta: 0:51:43 lr: 3.729284975902719e-05 loss: 0.0755 (0.0778) time: 2.6342 data: 0.0066 max mem: 33369 +Epoch: [11] [ 170/1319] eta: 0:51:18 lr: 3.728403799599019e-05 loss: 0.0769 (0.0784) time: 2.6722 data: 0.0067 max mem: 33369 +Epoch: [11] [ 180/1319] eta: 0:50:50 lr: 3.727522600154881e-05 loss: 0.0769 (0.0798) time: 2.6853 data: 0.0066 max mem: 33369 +Epoch: [11] [ 190/1319] eta: 0:50:23 lr: 3.7266413775636196e-05 loss: 0.0864 (0.0811) time: 2.6682 data: 0.0066 max mem: 33369 +Epoch: [11] [ 200/1319] eta: 0:49:54 lr: 3.725760131818543e-05 loss: 0.0799 (0.0806) time: 2.6538 data: 0.0066 max mem: 33369 +Epoch: [11] [ 210/1319] eta: 0:49:24 lr: 3.724878862912958e-05 loss: 0.0656 (0.0807) time: 2.6291 data: 0.0066 max mem: 33369 +Epoch: [11] [ 220/1319] eta: 0:48:55 lr: 3.723997570840168e-05 loss: 0.0899 (0.0810) time: 2.6206 data: 0.0067 max mem: 33369 +Epoch: [11] [ 230/1319] eta: 0:48:27 lr: 3.723116255593471e-05 loss: 0.0739 (0.0809) time: 2.6298 data: 0.0067 max mem: 33369 +Epoch: [11] [ 240/1319] eta: 0:48:00 lr: 3.7222349171661633e-05 loss: 0.0739 (0.0813) time: 2.6587 data: 0.0065 max mem: 33369 +Epoch: [11] [ 250/1319] eta: 0:47:32 lr: 3.721353555551535e-05 loss: 0.0777 (0.0809) time: 2.6494 data: 0.0063 max mem: 33369 +Epoch: [11] [ 260/1319] eta: 0:47:05 lr: 3.720472170742875e-05 loss: 0.0749 (0.0812) time: 2.6515 data: 0.0065 max mem: 33369 +Epoch: [11] [ 270/1319] eta: 0:46:40 lr: 3.719590762733466e-05 loss: 0.0844 (0.0816) time: 2.6861 data: 0.0067 max mem: 33369 +Epoch: [11] [ 280/1319] eta: 0:46:14 lr: 3.718709331516589e-05 loss: 0.0869 (0.0817) time: 2.6940 data: 0.0067 max mem: 33369 +Epoch: [11] [ 290/1319] eta: 0:45:47 lr: 3.7178278770855225e-05 loss: 0.0869 (0.0825) time: 2.6825 data: 0.0068 max mem: 33369 +Epoch: [11] [ 300/1319] eta: 0:45:22 lr: 3.716946399433537e-05 loss: 0.0807 (0.0825) time: 2.6978 data: 0.0066 max mem: 33369 +Epoch: [11] [ 310/1319] eta: 0:44:56 lr: 3.716064898553902e-05 loss: 0.0728 (0.0821) time: 2.6992 data: 0.0065 max mem: 33369 +Epoch: [11] [ 320/1319] eta: 0:44:29 lr: 3.715183374439884e-05 loss: 0.0710 (0.0818) time: 2.6650 data: 0.0065 max mem: 33369 +Epoch: [11] [ 330/1319] eta: 0:44:02 lr: 3.7143018270847454e-05 loss: 0.0761 (0.0818) time: 2.6611 data: 0.0066 max mem: 33369 +Epoch: [11] [ 340/1319] eta: 0:43:35 lr: 3.713420256481742e-05 loss: 0.0664 (0.0812) time: 2.6708 data: 0.0065 max mem: 33369 +Epoch: [11] [ 350/1319] eta: 0:43:06 lr: 3.712538662624129e-05 loss: 0.0624 (0.0811) time: 2.6413 data: 0.0064 max mem: 33369 +Epoch: [11] [ 360/1319] eta: 0:42:39 lr: 3.7116570455051586e-05 loss: 0.0652 (0.0807) time: 2.6234 data: 0.0065 max mem: 33369 +Epoch: [11] [ 370/1319] eta: 0:42:10 lr: 3.710775405118075e-05 loss: 0.0654 (0.0809) time: 2.6110 data: 0.0065 max mem: 33369 +Epoch: [11] [ 380/1319] eta: 0:41:43 lr: 3.709893741456123e-05 loss: 0.0705 (0.0809) time: 2.6212 data: 0.0064 max 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+/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 2:06:41 time: 2.9543 data: 2.8753 max mem: 33369 +Test: [ 100/2573] eta: 0:04:07 time: 0.0715 data: 0.0011 max mem: 33369 +Test: [ 200/2573] eta: 0:03:27 time: 0.0732 data: 0.0011 max mem: 33369 +Test: [ 300/2573] eta: 0:03:06 time: 0.0749 data: 0.0011 max mem: 33369 +Test: [ 400/2573] eta: 0:02:53 time: 0.0750 data: 0.0011 max mem: 33369 +Test: [ 500/2573] eta: 0:02:42 time: 0.0734 data: 0.0011 max mem: 33369 +Test: [ 600/2573] eta: 0:02:33 time: 0.0734 data: 0.0011 max mem: 33369 +Test: [ 700/2573] eta: 0:02:25 time: 0.0736 data: 0.0011 max mem: 33369 +Test: [ 800/2573] eta: 0:02:16 time: 0.0768 data: 0.0011 max mem: 33369 +Test: [ 900/2573] eta: 0:02:08 time: 0.0737 data: 0.0011 max mem: 33369 +Test: [1000/2573] eta: 0:02:00 time: 0.0737 data: 0.0011 max mem: 33369 +Test: [1100/2573] eta: 0:01:52 time: 0.0738 data: 0.0011 max mem: 33369 +Test: [1200/2573] eta: 0:01:44 time: 0.0737 data: 0.0011 max mem: 33369 +Test: [1300/2573] eta: 0:01:36 time: 0.0738 data: 0.0011 max mem: 33369 +Test: [1400/2573] eta: 0:01:28 time: 0.0720 data: 0.0011 max mem: 33369 +Test: [1500/2573] eta: 0:01:21 time: 0.0737 data: 0.0011 max mem: 33369 +Test: [1600/2573] eta: 0:01:13 time: 0.0770 data: 0.0011 max mem: 33369 +Test: [1700/2573] eta: 0:01:05 time: 0.0720 data: 0.0011 max mem: 33369 +Test: [1800/2573] eta: 0:00:58 time: 0.0753 data: 0.0011 max mem: 33369 +Test: [1900/2573] eta: 0:00:50 time: 0.0720 data: 0.0011 max mem: 33369 +Test: [2000/2573] eta: 0:00:43 time: 0.0737 data: 0.0011 max mem: 33369 +Test: [2100/2573] eta: 0:00:35 time: 0.0753 data: 0.0011 max mem: 33369 +Test: [2200/2573] eta: 0:00:27 time: 0.0753 data: 0.0011 max mem: 33369 +Test: [2300/2573] eta: 0:00:20 time: 0.0753 data: 0.0011 max mem: 33369 +Test: [2400/2573] eta: 0:00:12 time: 0.0703 data: 0.0011 max mem: 33369 +Test: [2500/2573] eta: 0:00:05 time: 0.0735 data: 0.0011 max mem: 33369 +Test: Total time: 0:03:12 +Final results: +Mean IoU is 60.25 + + precision@0.5 = 67.48 + precision@0.6 = 61.62 + precision@0.7 = 54.21 + precision@0.8 = 42.85 + precision@0.9 = 18.91 + overall IoU = 59.22 + +Average object IoU 60.250618344733994 +Overall IoU 59.21639633178711 +Better epoch: 11 + +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [12] [ 0/1319] eta: 1:26:04 lr: 3.6270008456269996e-05 loss: 0.0592 (0.0592) time: 3.9158 data: 1.1595 max mem: 33369 +Epoch: [12] [ 10/1319] eta: 1:00:37 lr: 3.6261169418713356e-05 loss: 0.0592 (0.0648) time: 2.7787 data: 0.1110 max mem: 33369 +Epoch: [12] [ 20/1319] eta: 0:58:44 lr: 3.62523301417494e-05 loss: 0.0658 (0.0731) time: 2.6530 data: 0.0060 max mem: 33369 +Epoch: [12] [ 30/1319] eta: 0:57:26 lr: 3.624349062530679e-05 loss: 0.0658 (0.0726) time: 2.6156 data: 0.0060 max mem: 33369 +Epoch: [12] [ 40/1319] eta: 0:56:46 lr: 3.623465086931413e-05 loss: 0.0650 (0.0721) time: 2.6105 data: 0.0062 max mem: 33369 +Epoch: [12] [ 50/1319] eta: 0:56:00 lr: 3.62258108737e-05 loss: 0.0610 (0.0709) time: 2.6085 data: 0.0063 max mem: 33369 +Epoch: [12] [ 60/1319] eta: 0:55:34 lr: 3.621697063839292e-05 loss: 0.0634 (0.0728) time: 2.6179 data: 0.0061 max mem: 33369 +Epoch: [12] [ 70/1319] eta: 0:55:02 lr: 3.6208130163321375e-05 loss: 0.0685 (0.0739) time: 2.6338 data: 0.0059 max mem: 33369 +Epoch: [12] [ 80/1319] eta: 0:54:36 lr: 3.619928944841383e-05 loss: 0.0685 (0.0749) time: 2.6344 data: 0.0062 max mem: 33369 +Epoch: [12] [ 90/1319] eta: 0:54:07 lr: 3.6190448493598675e-05 loss: 0.0674 (0.0747) time: 2.6365 data: 0.0061 max mem: 33369 +Epoch: [12] [ 100/1319] eta: 0:53:40 lr: 3.61816072988043e-05 loss: 0.0685 (0.0739) time: 2.6321 data: 0.0059 max mem: 33369 +Epoch: [12] [ 110/1319] eta: 0:53:12 lr: 3.617276586395901e-05 loss: 0.0613 (0.0732) time: 2.6318 data: 0.0060 max mem: 33369 +Epoch: [12] [ 120/1319] eta: 0:52:39 lr: 3.61639241889911e-05 loss: 0.0533 (0.0713) time: 2.6005 data: 0.0060 max mem: 33369 +Epoch: [12] [ 130/1319] eta: 0:52:11 lr: 3.615508227382881e-05 loss: 0.0651 (0.0717) time: 2.5951 data: 0.0061 max mem: 33369 +Epoch: [12] [ 140/1319] eta: 0:51:43 lr: 3.614624011840035e-05 loss: 0.0725 (0.0720) time: 2.6128 data: 0.0061 max mem: 33369 +Epoch: [12] [ 150/1319] eta: 0:51:15 lr: 3.613739772263389e-05 loss: 0.0602 (0.0714) time: 2.6108 data: 0.0060 max mem: 33369 +Epoch: [12] [ 160/1319] eta: 0:50:49 lr: 3.6128555086457536e-05 loss: 0.0675 (0.0711) time: 2.6235 data: 0.0059 max mem: 33369 +Epoch: [12] [ 170/1319] eta: 0:50:22 lr: 3.6119712209799373e-05 loss: 0.0670 (0.0713) time: 2.6320 data: 0.0058 max mem: 33369 +Epoch: [12] [ 180/1319] eta: 0:49:55 lr: 3.6110869092587446e-05 loss: 0.0628 (0.0717) time: 2.6168 data: 0.0060 max mem: 33369 +Epoch: [12] [ 190/1319] eta: 0:49:31 lr: 3.610202573474975e-05 loss: 0.0534 (0.0710) time: 2.6459 data: 0.0061 max mem: 33369 +Epoch: [12] [ 200/1319] eta: 0:49:04 lr: 3.609318213621424e-05 loss: 0.0534 (0.0709) time: 2.6486 data: 0.0061 max mem: 33369 +Epoch: [12] [ 210/1319] eta: 0:48:38 lr: 3.608433829690883e-05 loss: 0.0704 (0.0715) time: 2.6231 data: 0.0061 max mem: 33369 +Epoch: [12] [ 220/1319] eta: 0:48:11 lr: 3.607549421676141e-05 loss: 0.0711 (0.0715) time: 2.6295 data: 0.0061 max mem: 33369 +Epoch: [12] [ 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eta: 0:30:36 lr: 3.5721532687286004e-05 loss: 0.0620 (0.0734) time: 2.6238 data: 0.0060 max mem: 33369 +Epoch: [12] [ 630/1319] eta: 0:30:09 lr: 3.571267867000252e-05 loss: 0.0591 (0.0732) time: 2.6214 data: 0.0059 max mem: 33369 +Epoch: [12] [ 640/1319] eta: 0:29:43 lr: 3.570382440881008e-05 loss: 0.0602 (0.0731) time: 2.6227 data: 0.0059 max mem: 33369 +Epoch: [12] [ 650/1319] eta: 0:29:16 lr: 3.5694969903634736e-05 loss: 0.0653 (0.0730) time: 2.5960 data: 0.0060 max mem: 33369 +Epoch: [12] [ 660/1319] eta: 0:28:50 lr: 3.568611515440253e-05 loss: 0.0631 (0.0730) time: 2.5893 data: 0.0059 max mem: 33369 +Epoch: [12] [ 670/1319] eta: 0:28:23 lr: 3.567726016103943e-05 loss: 0.0630 (0.0729) time: 2.5954 data: 0.0058 max mem: 33369 +Epoch: [12] [ 680/1319] eta: 0:27:57 lr: 3.5668404923471386e-05 loss: 0.0623 (0.0728) time: 2.5964 data: 0.0058 max mem: 33369 +Epoch: [12] [ 690/1319] eta: 0:27:30 lr: 3.565954944162429e-05 loss: 0.0722 (0.0730) time: 2.5969 data: 0.0057 max mem: 33369 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3.5376044597489155e-05 loss: 0.0610 (0.0756) time: 2.6293 data: 0.0058 max mem: 33369 +Epoch: [12] [1020/1319] eta: 0:13:04 lr: 3.536718101257892e-05 loss: 0.0681 (0.0758) time: 2.6320 data: 0.0059 max mem: 33369 +Epoch: [12] [1030/1319] eta: 0:12:38 lr: 3.5358317180844356e-05 loss: 0.0837 (0.0759) time: 2.6343 data: 0.0060 max mem: 33369 +Epoch: [12] [1040/1319] eta: 0:12:12 lr: 3.5349453102209835e-05 loss: 0.0673 (0.0757) time: 2.6338 data: 0.0058 max mem: 33369 +Epoch: [12] [1050/1319] eta: 0:11:45 lr: 3.534058877659969e-05 loss: 0.0543 (0.0756) time: 2.6215 data: 0.0058 max mem: 33369 +Epoch: [12] [1060/1319] eta: 0:11:19 lr: 3.5331724203938196e-05 loss: 0.0638 (0.0756) time: 2.6033 data: 0.0060 max mem: 33369 +Epoch: [12] [1070/1319] eta: 0:10:53 lr: 3.53228593841496e-05 loss: 0.0710 (0.0757) time: 2.5998 data: 0.0059 max mem: 33369 +Epoch: [12] [1080/1319] eta: 0:10:26 lr: 3.53139943171581e-05 loss: 0.0770 (0.0758) time: 2.6177 data: 0.0059 max mem: 33369 +Epoch: [12] [1090/1319] eta: 0:10:00 lr: 3.5305129002887835e-05 loss: 0.0752 (0.0758) time: 2.6249 data: 0.0060 max mem: 33369 +Epoch: [12] [1100/1319] eta: 0:09:34 lr: 3.529626344126292e-05 loss: 0.0672 (0.0757) time: 2.6315 data: 0.0060 max mem: 33369 +Epoch: [12] [1110/1319] eta: 0:09:08 lr: 3.5287397632207417e-05 loss: 0.0703 (0.0758) time: 2.6247 data: 0.0060 max mem: 33369 +Epoch: [12] [1120/1319] eta: 0:08:41 lr: 3.527853157564535e-05 loss: 0.0744 (0.0759) time: 2.6048 data: 0.0061 max mem: 33369 +Epoch: [12] [1130/1319] eta: 0:08:15 lr: 3.526966527150067e-05 loss: 0.0710 (0.0760) time: 2.6221 data: 0.0060 max mem: 33369 +Epoch: [12] [1140/1319] eta: 0:07:49 lr: 3.5260798719697326e-05 loss: 0.0851 (0.0762) time: 2.6045 data: 0.0058 max mem: 33369 +Epoch: [12] [1150/1319] eta: 0:07:23 lr: 3.52519319201592e-05 loss: 0.0755 (0.0761) time: 2.6108 data: 0.0058 max mem: 33369 +Epoch: [12] [1160/1319] eta: 0:06:57 lr: 3.524306487281011e-05 loss: 0.0583 (0.0760) time: 2.6376 data: 0.0061 max mem: 33369 +Epoch: [12] [1170/1319] eta: 0:06:30 lr: 3.523419757757387e-05 loss: 0.0539 (0.0758) time: 2.6258 data: 0.0060 max mem: 33369 +Epoch: [12] [1180/1319] eta: 0:06:04 lr: 3.5225330034374235e-05 loss: 0.0565 (0.0757) time: 2.6252 data: 0.0059 max mem: 33369 +Epoch: [12] [1190/1319] eta: 0:05:38 lr: 3.5216462243134885e-05 loss: 0.0608 (0.0757) time: 2.6127 data: 0.0058 max mem: 33369 +Epoch: [12] [1200/1319] eta: 0:05:12 lr: 3.52075942037795e-05 loss: 0.0598 (0.0757) time: 2.6244 data: 0.0059 max mem: 33369 +Epoch: [12] [1210/1319] eta: 0:04:45 lr: 3.519872591623169e-05 loss: 0.0598 (0.0756) time: 2.6338 data: 0.0059 max mem: 33369 +Epoch: [12] [1220/1319] eta: 0:04:19 lr: 3.518985738041502e-05 loss: 0.0698 (0.0758) time: 2.6008 data: 0.0059 max mem: 33369 +Epoch: [12] [1230/1319] eta: 0:03:53 lr: 3.518098859625303e-05 loss: 0.0802 (0.0758) time: 2.6116 data: 0.0059 max mem: 33369 +Epoch: [12] [1240/1319] eta: 0:03:27 lr: 3.517211956366918e-05 loss: 0.0630 (0.0757) time: 2.6377 data: 0.0058 max mem: 33369 +Epoch: [12] [1250/1319] eta: 0:03:00 lr: 3.5163250282586914e-05 loss: 0.0548 (0.0756) time: 2.6157 data: 0.0060 max mem: 33369 +Epoch: [12] [1260/1319] eta: 0:02:34 lr: 3.515438075292963e-05 loss: 0.0673 (0.0756) time: 2.6245 data: 0.0059 max mem: 33369 +Epoch: [12] [1270/1319] eta: 0:02:08 lr: 3.514551097462066e-05 loss: 0.0756 (0.0758) time: 2.6391 data: 0.0057 max mem: 33369 +Epoch: [12] [1280/1319] eta: 0:01:42 lr: 3.513664094758331e-05 loss: 0.0821 (0.0759) time: 2.6149 data: 0.0058 max mem: 33369 +Epoch: [12] [1290/1319] eta: 0:01:16 lr: 3.512777067174083e-05 loss: 0.0788 (0.0759) time: 2.5843 data: 0.0060 max mem: 33369 +Epoch: [12] [1300/1319] eta: 0:00:49 lr: 3.511890014701643e-05 loss: 0.0645 (0.0758) time: 2.5870 data: 0.0062 max mem: 33369 +Epoch: [12] [1310/1319] eta: 0:00:23 lr: 3.511002937333328e-05 loss: 0.0629 (0.0758) time: 2.6064 data: 0.0061 max mem: 33369 +Epoch: [12] Total time: 0:57:39 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 2:07:47 time: 2.9800 data: 2.8951 max mem: 33369 +Test: [ 100/2573] eta: 0:04:09 time: 0.0717 data: 0.0011 max mem: 33369 +Test: [ 200/2573] eta: 0:03:28 time: 0.0736 data: 0.0011 max mem: 33369 +Test: [ 300/2573] eta: 0:03:07 time: 0.0753 data: 0.0011 max mem: 33369 +Test: [ 400/2573] eta: 0:02:54 time: 0.0752 data: 0.0011 max mem: 33369 +Test: [ 500/2573] eta: 0:02:43 time: 0.0739 data: 0.0012 max mem: 33369 +Test: [ 600/2573] eta: 0:02:34 time: 0.0738 data: 0.0011 max mem: 33369 +Test: [ 700/2573] eta: 0:02:25 time: 0.0740 data: 0.0011 max mem: 33369 +Test: [ 800/2573] eta: 0:02:17 time: 0.0774 data: 0.0011 max mem: 33369 +Test: [ 900/2573] eta: 0:02:09 time: 0.0740 data: 0.0011 max mem: 33369 +Test: [1000/2573] eta: 0:02:01 time: 0.0740 data: 0.0011 max mem: 33369 +Test: [1100/2573] eta: 0:01:52 time: 0.0741 data: 0.0011 max mem: 33369 +Test: [1200/2573] eta: 0:01:45 time: 0.0741 data: 0.0011 max mem: 33369 +Test: [1300/2573] eta: 0:01:37 time: 0.0740 data: 0.0011 max mem: 33369 +Test: [1400/2573] eta: 0:01:29 time: 0.0724 data: 0.0011 max mem: 33369 +Test: [1500/2573] eta: 0:01:21 time: 0.0741 data: 0.0011 max mem: 33369 +Test: [1600/2573] eta: 0:01:13 time: 0.0773 data: 0.0011 max mem: 33369 +Test: [1700/2573] eta: 0:01:06 time: 0.0723 data: 0.0011 max mem: 33369 +Test: [1800/2573] eta: 0:00:58 time: 0.0756 data: 0.0011 max mem: 33369 +Test: [1900/2573] eta: 0:00:50 time: 0.0724 data: 0.0011 max mem: 33369 +Test: [2000/2573] eta: 0:00:43 time: 0.0741 data: 0.0011 max mem: 33369 +Test: [2100/2573] eta: 0:00:35 time: 0.0756 data: 0.0011 max mem: 33369 +Test: [2200/2573] eta: 0:00:28 time: 0.0755 data: 0.0011 max mem: 33369 +Test: [2300/2573] eta: 0:00:20 time: 0.0757 data: 0.0011 max mem: 33369 +Test: [2400/2573] eta: 0:00:12 time: 0.0706 data: 0.0011 max mem: 33369 +Test: [2500/2573] eta: 0:00:05 time: 0.0738 data: 0.0011 max mem: 33369 +Test: Total time: 0:03:13 +Final results: +Mean IoU is 60.73 + + precision@0.5 = 67.87 + precision@0.6 = 62.15 + precision@0.7 = 54.66 + precision@0.8 = 43.14 + precision@0.9 = 19.59 + overall IoU = 59.67 + +Average object IoU 60.73099933997773 +Overall IoU 59.66789627075195 +Better epoch: 12 + +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [13] [ 0/1319] eta: 1:28:37 lr: 3.510204546409517e-05 loss: 0.0586 (0.0586) time: 4.0311 data: 1.2447 max mem: 33369 +Epoch: [13] [ 10/1319] eta: 0:59:53 lr: 3.509317421717855e-05 loss: 0.0586 (0.0654) time: 2.7449 data: 0.1186 max mem: 33369 +Epoch: [13] [ 20/1319] eta: 0:58:05 lr: 3.50843027210801e-05 loss: 0.0604 (0.0678) time: 2.6158 data: 0.0058 max mem: 33369 +Epoch: [13] [ 30/1319] eta: 0:57:05 lr: 3.5075430975722793e-05 loss: 0.0659 (0.0712) time: 2.6091 data: 0.0059 max mem: 33369 +Epoch: [13] [ 40/1319] eta: 0:56:27 lr: 3.506655898102959e-05 loss: 0.0620 (0.0697) time: 2.6129 data: 0.0062 max mem: 33369 +Epoch: [13] [ 50/1319] eta: 0:55:45 lr: 3.505768673692337e-05 loss: 0.0581 (0.0671) time: 2.6044 data: 0.0062 max mem: 33369 +Epoch: [13] [ 60/1319] eta: 0:55:20 lr: 3.5048814243327e-05 loss: 0.0581 (0.0677) time: 2.6140 data: 0.0060 max mem: 33369 +Epoch: [13] [ 70/1319] eta: 0:54:51 lr: 3.503994150016327e-05 loss: 0.0613 (0.0666) time: 2.6322 data: 0.0058 max mem: 33369 +Epoch: [13] [ 80/1319] eta: 0:54:27 lr: 3.503106850735495e-05 loss: 0.0486 (0.0643) time: 2.6375 data: 0.0061 max mem: 33369 +Epoch: [13] [ 90/1319] eta: 0:54:02 lr: 3.502219526482476e-05 loss: 0.0524 (0.0646) time: 2.6494 data: 0.0061 max mem: 33369 +Epoch: [13] [ 100/1319] eta: 0:53:33 lr: 3.501332177249536e-05 loss: 0.0617 (0.0648) time: 2.6316 data: 0.0060 max mem: 33369 +Epoch: [13] [ 110/1319] eta: 0:53:04 lr: 3.500444803028936e-05 loss: 0.0576 (0.0642) time: 2.6116 data: 0.0062 max mem: 33369 +Epoch: [13] [ 120/1319] eta: 0:52:36 lr: 3.499557403812936e-05 loss: 0.0510 (0.0632) time: 2.6162 data: 0.0061 max mem: 33369 +Epoch: [13] [ 130/1319] eta: 0:52:11 lr: 3.498669979593787e-05 loss: 0.0540 (0.0640) time: 2.6353 data: 0.0061 max mem: 33369 +Epoch: [13] [ 140/1319] eta: 0:51:44 lr: 3.497782530363739e-05 loss: 0.0597 (0.0639) time: 2.6318 data: 0.0061 max mem: 33369 +Epoch: [13] [ 150/1319] eta: 0:51:16 lr: 3.4968950561150356e-05 loss: 0.0579 (0.0638) time: 2.6168 data: 0.0060 max mem: 33369 +Epoch: [13] [ 160/1319] eta: 0:50:46 lr: 3.496007556839915e-05 loss: 0.0568 (0.0655) time: 2.5955 data: 0.0060 max mem: 33369 +Epoch: [13] [ 170/1319] eta: 0:50:17 lr: 3.495120032530614e-05 loss: 0.0663 (0.0655) time: 2.5867 data: 0.0062 max mem: 33369 +Epoch: [13] [ 180/1319] eta: 0:49:49 lr: 3.49423248317936e-05 loss: 0.0549 (0.0652) time: 2.5987 data: 0.0062 max mem: 33369 +Epoch: [13] [ 190/1319] eta: 0:49:23 lr: 3.493344908778381e-05 loss: 0.0684 (0.0660) time: 2.6110 data: 0.0062 max mem: 33369 +Epoch: [13] [ 200/1319] eta: 0:48:55 lr: 3.4924573093198975e-05 loss: 0.0771 (0.0667) time: 2.6126 data: 0.0061 max mem: 33369 +Epoch: [13] [ 210/1319] eta: 0:48:28 lr: 3.491569684796125e-05 loss: 0.0686 (0.0670) time: 2.6068 data: 0.0060 max mem: 33369 +Epoch: [13] [ 220/1319] eta: 0:48:04 lr: 3.490682035199276e-05 loss: 0.0671 (0.0682) time: 2.6382 data: 0.0061 max mem: 33369 +Epoch: [13] [ 230/1319] eta: 0:47:40 lr: 3.4897943605215565e-05 loss: 0.0602 (0.0682) time: 2.6612 data: 0.0060 max mem: 33369 +Epoch: [13] [ 240/1319] eta: 0:47:13 lr: 3.488906660755169e-05 loss: 0.0551 (0.0676) time: 2.6429 data: 0.0060 max mem: 33369 +Epoch: [13] [ 250/1319] eta: 0:46:46 lr: 3.4880189358923125e-05 loss: 0.0481 (0.0672) time: 2.6131 data: 0.0065 max mem: 33369 +Epoch: [13] [ 260/1319] eta: 0:46:20 lr: 3.487131185925179e-05 loss: 0.0489 (0.0666) time: 2.6159 data: 0.0063 max mem: 33369 +Epoch: [13] [ 270/1319] eta: 0:45:54 lr: 3.486243410845958e-05 loss: 0.0493 (0.0661) time: 2.6279 data: 0.0060 max mem: 33369 +Epoch: [13] [ 280/1319] eta: 0:45:28 lr: 3.485355610646832e-05 loss: 0.0508 (0.0662) time: 2.6345 data: 0.0060 max mem: 33369 +Epoch: [13] [ 290/1319] eta: 0:45:02 lr: 3.484467785319982e-05 loss: 0.0575 (0.0658) time: 2.6418 data: 0.0059 max mem: 33369 +Epoch: [13] [ 300/1319] eta: 0:44:36 lr: 3.483579934857581e-05 loss: 0.0600 (0.0656) time: 2.6318 data: 0.0058 max mem: 33369 +Epoch: [13] [ 310/1319] eta: 0:44:09 lr: 3.4826920592518003e-05 loss: 0.0608 (0.0657) time: 2.6098 data: 0.0060 max mem: 33369 +Epoch: [13] [ 320/1319] eta: 0:43:42 lr: 3.481804158494804e-05 loss: 0.0670 (0.0658) time: 2.6073 data: 0.0062 max mem: 33369 +Epoch: [13] [ 330/1319] eta: 0:43:16 lr: 3.4809162325787535e-05 loss: 0.0611 (0.0659) time: 2.6150 data: 0.0063 max mem: 33369 +Epoch: [13] [ 340/1319] eta: 0:42:49 lr: 3.480028281495805e-05 loss: 0.0619 (0.0660) time: 2.6108 data: 0.0062 max mem: 33369 +Epoch: [13] [ 350/1319] eta: 0:42:22 lr: 3.479140305238109e-05 loss: 0.0619 (0.0663) time: 2.6138 data: 0.0062 max mem: 33369 +Epoch: [13] [ 360/1319] eta: 0:41:57 lr: 3.478252303797812e-05 loss: 0.0538 (0.0660) time: 2.6374 data: 0.0060 max mem: 33369 +Epoch: [13] [ 370/1319] eta: 0:41:31 lr: 3.4773642771670566e-05 loss: 0.0505 (0.0661) time: 2.6396 data: 0.0058 max mem: 33369 +Epoch: [13] [ 380/1319] eta: 0:41:04 lr: 3.47647622533798e-05 loss: 0.0555 (0.0660) time: 2.6220 data: 0.0060 max 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time: 2.6445 data: 0.0062 max mem: 33369 +Epoch: [13] [ 940/1319] eta: 0:16:33 lr: 3.426704861621893e-05 loss: 0.0627 (0.0688) time: 2.6289 data: 0.0063 max mem: 33369 +Epoch: [13] [ 950/1319] eta: 0:16:06 lr: 3.4258153603371135e-05 loss: 0.0626 (0.0690) time: 2.6042 data: 0.0061 max mem: 33369 +Epoch: [13] [ 960/1319] eta: 0:15:40 lr: 3.424925833389819e-05 loss: 0.0668 (0.0691) time: 2.5898 data: 0.0059 max mem: 33369 +Epoch: [13] [ 970/1319] eta: 0:15:14 lr: 3.424036280771861e-05 loss: 0.0682 (0.0691) time: 2.6021 data: 0.0058 max mem: 33369 +Epoch: [13] [ 980/1319] eta: 0:14:48 lr: 3.42314670247509e-05 loss: 0.0603 (0.0693) time: 2.6058 data: 0.0057 max mem: 33369 +Epoch: [13] [ 990/1319] eta: 0:14:21 lr: 3.422257098491348e-05 loss: 0.0715 (0.0694) time: 2.6079 data: 0.0058 max mem: 33369 +Epoch: [13] [1000/1319] eta: 0:13:55 lr: 3.4213674688124745e-05 loss: 0.0654 (0.0694) time: 2.6285 data: 0.0059 max mem: 33369 +Epoch: [13] [1010/1319] eta: 0:13:29 lr: 3.420477813430303e-05 loss: 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3.413359644072625e-05 loss: 0.0661 (0.0698) time: 2.6010 data: 0.0058 max mem: 33369 +Epoch: [13] [1100/1319] eta: 0:09:33 lr: 3.412469756992473e-05 loss: 0.0661 (0.0698) time: 2.6257 data: 0.0059 max mem: 33369 +Epoch: [13] [1110/1319] eta: 0:09:07 lr: 3.411579844127087e-05 loss: 0.0770 (0.0700) time: 2.6138 data: 0.0060 max mem: 33369 +Epoch: [13] [1120/1319] eta: 0:08:41 lr: 3.410689905468246e-05 loss: 0.0717 (0.0701) time: 2.6006 data: 0.0059 max mem: 33369 +Epoch: [13] [1130/1319] eta: 0:08:14 lr: 3.409799941007725e-05 loss: 0.0555 (0.0702) time: 2.6187 data: 0.0060 max mem: 33369 +Epoch: [13] [1140/1319] eta: 0:07:48 lr: 3.408909950737292e-05 loss: 0.0543 (0.0700) time: 2.6265 data: 0.0061 max mem: 33369 +Epoch: [13] [1150/1319] eta: 0:07:22 lr: 3.4080199346487104e-05 loss: 0.0586 (0.0700) time: 2.6237 data: 0.0059 max mem: 33369 +Epoch: [13] [1160/1319] eta: 0:06:56 lr: 3.4071298927337405e-05 loss: 0.0692 (0.0701) time: 2.6122 data: 0.0059 max mem: 33369 +Epoch: [13] [1170/1319] eta: 0:06:30 lr: 3.406239824984136e-05 loss: 0.0844 (0.0704) time: 2.6004 data: 0.0060 max mem: 33369 +Epoch: [13] [1180/1319] eta: 0:06:03 lr: 3.405349731391645e-05 loss: 0.0732 (0.0704) time: 2.6015 data: 0.0060 max mem: 33369 +Epoch: [13] [1190/1319] eta: 0:05:37 lr: 3.404459611948011e-05 loss: 0.0697 (0.0704) time: 2.5937 data: 0.0059 max mem: 33369 +Epoch: [13] [1200/1319] eta: 0:05:11 lr: 3.4035694666449745e-05 loss: 0.0682 (0.0704) time: 2.5973 data: 0.0059 max mem: 33369 +Epoch: [13] [1210/1319] eta: 0:04:45 lr: 3.402679295474268e-05 loss: 0.0607 (0.0703) time: 2.6177 data: 0.0059 max mem: 33369 +Epoch: [13] [1220/1319] eta: 0:04:19 lr: 3.401789098427621e-05 loss: 0.0570 (0.0703) time: 2.6145 data: 0.0058 max mem: 33369 +Epoch: [13] [1230/1319] eta: 0:03:52 lr: 3.400898875496756e-05 loss: 0.0573 (0.0702) time: 2.6190 data: 0.0058 max mem: 33369 +Epoch: [13] [1240/1319] eta: 0:03:26 lr: 3.400008626673392e-05 loss: 0.0614 (0.0702) time: 2.6235 data: 0.0060 max mem: 33369 +Epoch: [13] [1250/1319] eta: 0:03:00 lr: 3.399118351949243e-05 loss: 0.0614 (0.0703) time: 2.6159 data: 0.0059 max mem: 33369 +Epoch: [13] [1260/1319] eta: 0:02:34 lr: 3.398228051316017e-05 loss: 0.0698 (0.0704) time: 2.6194 data: 0.0060 max mem: 33369 +Epoch: [13] [1270/1319] eta: 0:02:08 lr: 3.397337724765419e-05 loss: 0.0639 (0.0704) time: 2.5975 data: 0.0060 max mem: 33369 +Epoch: [13] [1280/1319] eta: 0:01:42 lr: 3.396447372289146e-05 loss: 0.0729 (0.0706) time: 2.6065 data: 0.0059 max mem: 33369 +Epoch: [13] [1290/1319] eta: 0:01:15 lr: 3.395556993878891e-05 loss: 0.0751 (0.0705) time: 2.6345 data: 0.0058 max mem: 33369 +Epoch: [13] [1300/1319] eta: 0:00:49 lr: 3.394666589526343e-05 loss: 0.0586 (0.0708) time: 2.6303 data: 0.0057 max mem: 33369 +Epoch: [13] [1310/1319] eta: 0:00:23 lr: 3.393776159223184e-05 loss: 0.0708 (0.0707) time: 2.6154 data: 0.0057 max mem: 33369 +Epoch: [13] Total time: 0:57:32 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 2:06:28 time: 2.9493 data: 2.8704 max mem: 33369 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 100/2573] eta: 0:04:07 time: 0.0715 data: 0.0011 max mem: 33369 +Test: [ 200/2573] eta: 0:03:27 time: 0.0734 data: 0.0011 max mem: 33369 +Test: [ 300/2573] eta: 0:03:06 time: 0.0748 data: 0.0011 max mem: 33369 +Test: [ 400/2573] eta: 0:02:53 time: 0.0750 data: 0.0011 max mem: 33369 +Test: [ 500/2573] eta: 0:02:42 time: 0.0734 data: 0.0011 max mem: 33369 +Test: [ 600/2573] eta: 0:02:33 time: 0.0735 data: 0.0011 max mem: 33369 +Test: [ 700/2573] eta: 0:02:25 time: 0.0734 data: 0.0011 max mem: 33369 +Test: [ 800/2573] eta: 0:02:16 time: 0.0768 data: 0.0011 max mem: 33369 +Test: [ 900/2573] eta: 0:02:08 time: 0.0737 data: 0.0011 max mem: 33369 +Test: [1000/2573] eta: 0:02:00 time: 0.0736 data: 0.0011 max mem: 33369 +Test: [1100/2573] eta: 0:01:52 time: 0.0735 data: 0.0011 max mem: 33369 +Test: [1200/2573] eta: 0:01:44 time: 0.0735 data: 0.0010 max mem: 33369 +Test: [1300/2573] eta: 0:01:36 time: 0.0735 data: 0.0011 max mem: 33369 +Test: [1400/2573] eta: 0:01:28 time: 0.0718 data: 0.0011 max mem: 33369 +Test: [1500/2573] eta: 0:01:21 time: 0.0735 data: 0.0011 max mem: 33369 +Test: [1600/2573] eta: 0:01:13 time: 0.0769 data: 0.0011 max mem: 33369 +Test: [1700/2573] eta: 0:01:05 time: 0.0719 data: 0.0011 max mem: 33369 +Test: [1800/2573] eta: 0:00:58 time: 0.0753 data: 0.0011 max mem: 33369 +Test: [1900/2573] eta: 0:00:50 time: 0.0719 data: 0.0011 max mem: 33369 +Test: [2000/2573] eta: 0:00:42 time: 0.0736 data: 0.0011 max mem: 33369 +Test: [2100/2573] eta: 0:00:35 time: 0.0753 data: 0.0011 max mem: 33369 +Test: [2200/2573] eta: 0:00:27 time: 0.0752 data: 0.0011 max mem: 33369 +Test: [2300/2573] eta: 0:00:20 time: 0.0753 data: 0.0011 max mem: 33369 +Test: [2400/2573] eta: 0:00:12 time: 0.0703 data: 0.0011 max mem: 33369 +Test: [2500/2573] eta: 0:00:05 time: 0.0736 data: 0.0011 max mem: 33369 +Test: Total time: 0:03:12 +Final results: +Mean IoU is 61.32 + + precision@0.5 = 67.95 + precision@0.6 = 62.77 + precision@0.7 = 55.72 + precision@0.8 = 44.18 + precision@0.9 = 20.92 + overall IoU = 59.92 + +Average object IoU 61.31770757252325 +Overall IoU 59.92262268066406 +Better epoch: 13 + +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [14] [ 0/1319] eta: 1:30:44 lr: 3.392974749755691e-05 loss: 0.0496 (0.0496) time: 4.1281 data: 1.5427 max mem: 33369 +Epoch: [14] [ 10/1319] eta: 1:00:02 lr: 3.392084270123441e-05 loss: 0.0496 (0.0611) time: 2.7519 data: 0.1453 max mem: 33369 +Epoch: [14] [ 20/1319] eta: 0:58:17 lr: 3.391193764516433e-05 loss: 0.0567 (0.0617) time: 2.6205 data: 0.0055 max mem: 33369 +Epoch: [14] [ 30/1319] eta: 0:57:43 lr: 3.3903032329263314e-05 loss: 0.0613 (0.0638) time: 2.6518 data: 0.0060 max mem: 33369 +Epoch: [14] [ 40/1319] eta: 0:57:01 lr: 3.389412675344791e-05 loss: 0.0582 (0.0653) time: 2.6578 data: 0.0063 max mem: 33369 +Epoch: [14] [ 50/1319] eta: 0:56:30 lr: 3.388522091763468e-05 loss: 0.0574 (0.0663) time: 2.6469 data: 0.0061 max mem: 33369 +Epoch: [14] [ 60/1319] eta: 0:55:53 lr: 3.387631482174009e-05 loss: 0.0584 (0.0650) time: 2.6390 data: 0.0061 max mem: 33369 +Epoch: [14] [ 70/1319] eta: 0:55:22 lr: 3.386740846568057e-05 loss: 0.0551 (0.0640) time: 2.6303 data: 0.0061 max mem: 33369 +Epoch: [14] [ 80/1319] eta: 0:54:52 lr: 3.385850184937249e-05 loss: 0.0630 (0.0650) time: 2.6375 data: 0.0062 max mem: 33369 +Epoch: [14] [ 90/1319] eta: 0:54:18 lr: 3.3849594972732175e-05 loss: 0.0608 (0.0644) time: 2.6223 data: 0.0062 max mem: 33369 +Epoch: [14] [ 100/1319] eta: 0:53:50 lr: 3.38406878356759e-05 loss: 0.0527 (0.0644) time: 2.6225 data: 0.0063 max mem: 33369 +Epoch: [14] [ 110/1319] eta: 0:53:19 lr: 3.3831780438119907e-05 loss: 0.0595 (0.0656) time: 2.6243 data: 0.0064 max mem: 33369 +Epoch: [14] [ 120/1319] eta: 0:52:53 lr: 3.3822872779980336e-05 loss: 0.0760 (0.0664) time: 2.6298 data: 0.0063 max mem: 33369 +Epoch: [14] [ 130/1319] eta: 0:52:26 lr: 3.381396486117332e-05 loss: 0.0711 (0.0667) time: 2.6436 data: 0.0063 max mem: 33369 +Epoch: [14] [ 140/1319] eta: 0:51:57 lr: 3.380505668161494e-05 loss: 0.0662 (0.0666) time: 2.6284 data: 0.0064 max mem: 33369 +Epoch: [14] [ 150/1319] eta: 0:51:28 lr: 3.3796148241221185e-05 loss: 0.0525 (0.0661) time: 2.6154 data: 0.0062 max mem: 33369 +Epoch: [14] [ 160/1319] eta: 0:51:02 lr: 3.378723953990804e-05 loss: 0.0524 (0.0661) time: 2.6275 data: 0.0062 max mem: 33369 +Epoch: [14] [ 170/1319] eta: 0:50:37 lr: 3.3778330577591404e-05 loss: 0.0596 (0.0661) time: 2.6575 data: 0.0063 max mem: 33369 +Epoch: [14] [ 180/1319] eta: 0:50:06 lr: 3.3769421354187145e-05 loss: 0.0596 (0.0661) time: 2.6168 data: 0.0064 max mem: 33369 +Epoch: [14] [ 190/1319] eta: 0:49:37 lr: 3.376051186961107e-05 loss: 0.0633 (0.0665) time: 2.5781 data: 0.0063 max mem: 33369 +Epoch: [14] [ 200/1319] eta: 0:49:11 lr: 3.375160212377894e-05 loss: 0.0633 (0.0672) time: 2.6207 data: 0.0063 max mem: 33369 +Epoch: [14] [ 210/1319] eta: 0:48:43 lr: 3.374269211660646e-05 loss: 0.0579 (0.0670) time: 2.6314 data: 0.0065 max mem: 33369 +Epoch: [14] [ 220/1319] eta: 0:48:16 lr: 3.373378184800928e-05 loss: 0.0502 (0.0668) time: 2.6142 data: 0.0064 max mem: 33369 +Epoch: [14] [ 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33369 +Epoch: [14] [ 310/1319] eta: 0:44:14 lr: 3.365357765258022e-05 loss: 0.0525 (0.0647) time: 2.6056 data: 0.0063 max mem: 33369 +Epoch: [14] [ 320/1319] eta: 0:43:50 lr: 3.364466476508552e-05 loss: 0.0538 (0.0648) time: 2.6478 data: 0.0063 max mem: 33369 +Epoch: [14] [ 330/1319] eta: 0:43:25 lr: 3.363575161523487e-05 loss: 0.0587 (0.0645) time: 2.6930 data: 0.0063 max mem: 33369 +Epoch: [14] [ 340/1319] eta: 0:42:56 lr: 3.362683820294329e-05 loss: 0.0599 (0.0651) time: 2.6242 data: 0.0063 max mem: 33369 +Epoch: [14] [ 350/1319] eta: 0:42:30 lr: 3.361792452812576e-05 loss: 0.0655 (0.0654) time: 2.5998 data: 0.0061 max mem: 33369 +Epoch: [14] [ 360/1319] eta: 0:42:05 lr: 3.36090105906972e-05 loss: 0.0744 (0.0658) time: 2.6501 data: 0.0061 max mem: 33369 +Epoch: [14] [ 370/1319] eta: 0:41:39 lr: 3.3600096390572475e-05 loss: 0.0715 (0.0659) time: 2.6533 data: 0.0061 max mem: 33369 +Epoch: [14] [ 380/1319] eta: 0:41:11 lr: 3.3591181927666404e-05 loss: 0.0626 (0.0657) time: 2.6112 data: 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3.337715576110804e-05 loss: 0.0689 (0.0678) time: 2.6157 data: 0.0063 max mem: 33369 +Epoch: [14] [ 630/1319] eta: 0:30:11 lr: 3.336823470082831e-05 loss: 0.0606 (0.0676) time: 2.6397 data: 0.0061 max mem: 33369 +Epoch: [14] [ 640/1319] eta: 0:29:44 lr: 3.335931337553377e-05 loss: 0.0591 (0.0676) time: 2.6361 data: 0.0062 max mem: 33369 +Epoch: [14] [ 650/1319] eta: 0:29:18 lr: 3.3350391785137824e-05 loss: 0.0564 (0.0679) time: 2.6152 data: 0.0062 max mem: 33369 +Epoch: [14] [ 660/1319] eta: 0:28:52 lr: 3.334146992955378e-05 loss: 0.0623 (0.0678) time: 2.6289 data: 0.0062 max mem: 33369 +Epoch: [14] [ 670/1319] eta: 0:28:26 lr: 3.33325478086949e-05 loss: 0.0623 (0.0677) time: 2.6509 data: 0.0061 max mem: 33369 +Epoch: [14] [ 680/1319] eta: 0:28:00 lr: 3.332362542247442e-05 loss: 0.0669 (0.0678) time: 2.6497 data: 0.0062 max mem: 33369 +Epoch: [14] [ 690/1319] eta: 0:27:33 lr: 3.3314702770805464e-05 loss: 0.0651 (0.0677) time: 2.6302 data: 0.0061 max mem: 33369 +Epoch: [14] [ 700/1319] eta: 0:27:07 lr: 3.330577985360116e-05 loss: 0.0584 (0.0676) time: 2.6408 data: 0.0061 max mem: 33369 +Epoch: [14] [ 710/1319] eta: 0:26:41 lr: 3.329685667077455e-05 loss: 0.0584 (0.0674) time: 2.6272 data: 0.0062 max mem: 33369 +Epoch: [14] [ 720/1319] eta: 0:26:14 lr: 3.3287933222238623e-05 loss: 0.0525 (0.0673) time: 2.6123 data: 0.0060 max mem: 33369 +Epoch: [14] [ 730/1319] eta: 0:25:48 lr: 3.327900950790632e-05 loss: 0.0559 (0.0673) time: 2.6218 data: 0.0059 max mem: 33369 +Epoch: [14] [ 740/1319] eta: 0:25:22 lr: 3.327008552769054e-05 loss: 0.0629 (0.0673) time: 2.6205 data: 0.0060 max mem: 33369 +Epoch: [14] [ 750/1319] eta: 0:24:55 lr: 3.32611612815041e-05 loss: 0.0655 (0.0674) time: 2.6157 data: 0.0061 max mem: 33369 +Epoch: [14] [ 760/1319] eta: 0:24:29 lr: 3.325223676925979e-05 loss: 0.0579 (0.0673) time: 2.6100 data: 0.0061 max mem: 33369 +Epoch: [14] [ 770/1319] eta: 0:24:02 lr: 3.324331199087032e-05 loss: 0.0610 (0.0675) time: 2.5832 data: 0.0061 max mem: 33369 +Epoch: 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mem: 33369 +Epoch: [14] [ 860/1319] eta: 0:20:05 lr: 3.3162976994405264e-05 loss: 0.0514 (0.0674) time: 2.6217 data: 0.0060 max mem: 33369 +Epoch: [14] [ 870/1319] eta: 0:19:39 lr: 3.315404954975194e-05 loss: 0.0514 (0.0674) time: 2.6163 data: 0.0060 max mem: 33369 +Epoch: [14] [ 880/1319] eta: 0:19:12 lr: 3.314512183798977e-05 loss: 0.0603 (0.0674) time: 2.6070 data: 0.0061 max mem: 33369 +Epoch: [14] [ 890/1319] eta: 0:18:46 lr: 3.3136193859030854e-05 loss: 0.0603 (0.0674) time: 2.6142 data: 0.0062 max mem: 33369 +Epoch: [14] [ 900/1319] eta: 0:18:20 lr: 3.312726561278717e-05 loss: 0.0513 (0.0672) time: 2.6182 data: 0.0060 max mem: 33369 +Epoch: [14] [ 910/1319] eta: 0:17:54 lr: 3.311833709917069e-05 loss: 0.0505 (0.0672) time: 2.6329 data: 0.0060 max mem: 33369 +Epoch: [14] [ 920/1319] eta: 0:17:27 lr: 3.3109408318093296e-05 loss: 0.0561 (0.0671) time: 2.6252 data: 0.0061 max mem: 33369 +Epoch: [14] [ 930/1319] eta: 0:17:01 lr: 3.310047926946684e-05 loss: 0.0561 (0.0670) time: 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(0.0669) time: 2.6590 data: 0.0061 max mem: 33369 +Epoch: [14] [1020/1319] eta: 0:13:05 lr: 3.3020105777547046e-05 loss: 0.0649 (0.0673) time: 2.6255 data: 0.0060 max mem: 33369 +Epoch: [14] [1030/1319] eta: 0:12:39 lr: 3.301117404856897e-05 loss: 0.0649 (0.0672) time: 2.6317 data: 0.0060 max mem: 33369 +Epoch: [14] [1040/1319] eta: 0:12:12 lr: 3.300224205106842e-05 loss: 0.0571 (0.0672) time: 2.6392 data: 0.0059 max mem: 33369 +Epoch: [14] [1050/1319] eta: 0:11:46 lr: 3.2993309784956545e-05 loss: 0.0576 (0.0672) time: 2.6436 data: 0.0059 max mem: 33369 +Epoch: [14] [1060/1319] eta: 0:11:20 lr: 3.298437725014447e-05 loss: 0.0541 (0.0671) time: 2.6454 data: 0.0059 max mem: 33369 +Epoch: [14] [1070/1319] eta: 0:10:54 lr: 3.297544444654327e-05 loss: 0.0541 (0.0670) time: 2.6358 data: 0.0060 max mem: 33369 +Epoch: [14] [1080/1319] eta: 0:10:27 lr: 3.296651137406393e-05 loss: 0.0538 (0.0669) time: 2.6056 data: 0.0059 max mem: 33369 +Epoch: [14] [1090/1319] eta: 0:10:01 lr: 3.2957578032617413e-05 loss: 0.0579 (0.0671) time: 2.5923 data: 0.0061 max mem: 33369 +Epoch: [14] [1100/1319] eta: 0:09:35 lr: 3.29486444221146e-05 loss: 0.0647 (0.0672) time: 2.6214 data: 0.0063 max mem: 33369 +Epoch: [14] [1110/1319] eta: 0:09:08 lr: 3.293971054246633e-05 loss: 0.0635 (0.0671) time: 2.6116 data: 0.0062 max mem: 33369 +Epoch: [14] [1120/1319] eta: 0:08:42 lr: 3.293077639358339e-05 loss: 0.0601 (0.0672) time: 2.6103 data: 0.0059 max mem: 33369 +Epoch: [14] [1130/1319] eta: 0:08:16 lr: 3.2921841975376476e-05 loss: 0.0671 (0.0674) time: 2.6255 data: 0.0060 max mem: 33369 +Epoch: [14] [1140/1319] eta: 0:07:50 lr: 3.291290728775627e-05 loss: 0.0671 (0.0673) time: 2.6287 data: 0.0062 max mem: 33369 +Epoch: [14] [1150/1319] eta: 0:07:23 lr: 3.290397233063338e-05 loss: 0.0623 (0.0673) time: 2.6247 data: 0.0061 max mem: 33369 +Epoch: [14] [1160/1319] eta: 0:06:57 lr: 3.2895037103918356e-05 loss: 0.0593 (0.0673) time: 2.6179 data: 0.0060 max mem: 33369 +Epoch: [14] [1170/1319] eta: 0:06:31 lr: 3.2886101607521696e-05 loss: 0.0629 (0.0673) time: 2.6343 data: 0.0059 max mem: 33369 +Epoch: [14] [1180/1319] eta: 0:06:05 lr: 3.287716584135384e-05 loss: 0.0575 (0.0672) time: 2.6478 data: 0.0058 max mem: 33369 +Epoch: [14] [1190/1319] eta: 0:05:38 lr: 3.286822980532516e-05 loss: 0.0570 (0.0673) time: 2.6387 data: 0.0060 max mem: 33369 +Epoch: [14] [1200/1319] eta: 0:05:12 lr: 3.285929349934599e-05 loss: 0.0570 (0.0673) time: 2.6128 data: 0.0061 max mem: 33369 +Epoch: [14] [1210/1319] eta: 0:04:46 lr: 3.28503569233266e-05 loss: 0.0508 (0.0672) time: 2.6079 data: 0.0059 max mem: 33369 +Epoch: [14] [1220/1319] eta: 0:04:19 lr: 3.284142007717719e-05 loss: 0.0596 (0.0673) time: 2.6014 data: 0.0058 max mem: 33369 +Epoch: [14] [1230/1319] eta: 0:03:53 lr: 3.283248296080793e-05 loss: 0.0706 (0.0674) time: 2.6414 data: 0.0059 max mem: 33369 +Epoch: [14] [1240/1319] eta: 0:03:27 lr: 3.2823545574128904e-05 loss: 0.0706 (0.0675) time: 2.6585 data: 0.0060 max mem: 33369 +Epoch: [14] [1250/1319] eta: 0:03:01 lr: 3.2814607917050156e-05 loss: 0.0723 (0.0676) time: 2.6171 data: 0.0062 max mem: 33369 +Epoch: [14] [1260/1319] eta: 0:02:34 lr: 3.280566998948166e-05 loss: 0.0716 (0.0677) time: 2.6392 data: 0.0063 max mem: 33369 +Epoch: [14] [1270/1319] eta: 0:02:08 lr: 3.2796731791333364e-05 loss: 0.0647 (0.0677) time: 2.6395 data: 0.0061 max mem: 33369 +Epoch: [14] [1280/1319] eta: 0:01:42 lr: 3.278779332251511e-05 loss: 0.0629 (0.0676) time: 2.6209 data: 0.0060 max mem: 33369 +Epoch: [14] [1290/1319] eta: 0:01:16 lr: 3.277885458293673e-05 loss: 0.0621 (0.0676) time: 2.6229 data: 0.0060 max mem: 33369 +Epoch: [14] [1300/1319] eta: 0:00:49 lr: 3.276991557250796e-05 loss: 0.0659 (0.0677) time: 2.6227 data: 0.0060 max mem: 33369 +Epoch: [14] [1310/1319] eta: 0:00:23 lr: 3.276097629113851e-05 loss: 0.0704 (0.0679) time: 2.6305 data: 0.0060 max mem: 33369 +Epoch: [14] Total time: 0:57:45 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 1:46:00 time: 2.4721 data: 2.2489 max mem: 33369 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 100/2573] eta: 0:03:56 time: 0.0717 data: 0.0011 max mem: 33369 +Test: [ 200/2573] eta: 0:03:21 time: 0.0734 data: 0.0011 max mem: 33369 +Test: [ 300/2573] eta: 0:03:03 time: 0.0751 data: 0.0011 max mem: 33369 +Test: [ 400/2573] eta: 0:02:51 time: 0.0751 data: 0.0011 max mem: 33369 +Test: [ 500/2573] eta: 0:02:41 time: 0.0736 data: 0.0011 max mem: 33369 +Test: [ 600/2573] eta: 0:02:32 time: 0.0738 data: 0.0011 max mem: 33369 +Test: [ 700/2573] eta: 0:02:24 time: 0.0739 data: 0.0011 max mem: 33369 +Test: [ 800/2573] eta: 0:02:16 time: 0.0771 data: 0.0011 max mem: 33369 +Test: [ 900/2573] eta: 0:02:08 time: 0.0737 data: 0.0011 max mem: 33369 +Test: [1000/2573] eta: 0:02:00 time: 0.0738 data: 0.0011 max mem: 33369 +Test: [1100/2573] eta: 0:01:52 time: 0.0738 data: 0.0011 max mem: 33369 +Test: [1200/2573] eta: 0:01:44 time: 0.0739 data: 0.0011 max mem: 33369 +Test: [1300/2573] eta: 0:01:36 time: 0.0738 data: 0.0011 max mem: 33369 +Test: [1400/2573] eta: 0:01:28 time: 0.0722 data: 0.0011 max mem: 33369 +Test: [1500/2573] eta: 0:01:21 time: 0.0738 data: 0.0011 max mem: 33369 +Test: [1600/2573] eta: 0:01:13 time: 0.0772 data: 0.0012 max mem: 33369 +Test: [1700/2573] eta: 0:01:05 time: 0.0721 data: 0.0011 max mem: 33369 +Test: [1800/2573] eta: 0:00:58 time: 0.0755 data: 0.0011 max mem: 33369 +Test: [1900/2573] eta: 0:00:50 time: 0.0722 data: 0.0011 max mem: 33369 +Test: [2000/2573] eta: 0:00:42 time: 0.0738 data: 0.0011 max mem: 33369 +Test: [2100/2573] eta: 0:00:35 time: 0.0755 data: 0.0011 max mem: 33369 +Test: [2200/2573] eta: 0:00:27 time: 0.0755 data: 0.0011 max mem: 33369 +Test: [2300/2573] eta: 0:00:20 time: 0.0754 data: 0.0011 max mem: 33369 +Test: [2400/2573] eta: 0:00:12 time: 0.0704 data: 0.0011 max mem: 33369 +Test: [2500/2573] eta: 0:00:05 time: 0.0738 data: 0.0011 max mem: 33369 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: Total time: 0:03:12 +Final results: +Mean IoU is 61.08 + + precision@0.5 = 68.73 + precision@0.6 = 62.60 + precision@0.7 = 55.13 + precision@0.8 = 43.57 + precision@0.9 = 20.34 + overall IoU = 59.89 + +Average object IoU 61.078979076071846 +Overall IoU 59.893226623535156 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [15] [ 0/1319] eta: 3:14:05 lr: 3.275293070617704e-05 loss: 0.0594 (0.0594) time: 8.8292 data: 1.3928 max mem: 33369 +Epoch: [15] [ 10/1319] eta: 1:10:08 lr: 3.274399090977129e-05 loss: 0.0594 (0.0626) time: 3.2151 data: 0.1323 max mem: 33369 +Epoch: [15] [ 20/1319] eta: 1:02:55 lr: 3.2735050842162644e-05 loss: 0.0601 (0.0638) time: 2.6102 data: 0.0059 max mem: 33369 +Epoch: [15] [ 30/1319] eta: 1:00:08 lr: 3.2726110503260586e-05 loss: 0.0592 (0.0613) time: 2.5704 data: 0.0059 max mem: 33369 +Epoch: [15] [ 40/1319] eta: 0:58:47 lr: 3.271716989297451e-05 loss: 0.0487 (0.0597) time: 2.6020 data: 0.0063 max mem: 33369 +Epoch: [15] [ 50/1319] eta: 0:57:38 lr: 3.2708229011213794e-05 loss: 0.0512 (0.0615) time: 2.6108 data: 0.0062 max mem: 33369 +Epoch: [15] [ 60/1319] eta: 0:56:47 lr: 3.269928785788772e-05 loss: 0.0617 (0.0622) time: 2.6023 data: 0.0061 max mem: 33369 +Epoch: [15] [ 70/1319] eta: 0:56:12 lr: 3.2690346432905536e-05 loss: 0.0501 (0.0605) time: 2.6361 data: 0.0061 max mem: 33369 +Epoch: [15] [ 80/1319] eta: 0:55:34 lr: 3.268140473617642e-05 loss: 0.0523 (0.0609) time: 2.6450 data: 0.0059 max mem: 33369 +Epoch: [15] [ 90/1319] eta: 0:54:54 lr: 3.26724627676095e-05 loss: 0.0608 (0.0613) time: 2.6116 data: 0.0061 max mem: 33369 +Epoch: [15] [ 100/1319] eta: 0:54:20 lr: 3.266352052711384e-05 loss: 0.0622 (0.0633) time: 2.6058 data: 0.0061 max mem: 33369 +Epoch: [15] [ 110/1319] eta: 0:53:47 lr: 3.265457801459844e-05 loss: 0.0572 (0.0640) time: 2.6172 data: 0.0062 max mem: 33369 +Epoch: [15] [ 120/1319] eta: 0:53:19 lr: 3.2645635229972264e-05 loss: 0.0551 (0.0638) time: 2.6381 data: 0.0061 max mem: 33369 +Epoch: [15] [ 130/1319] eta: 0:52:50 lr: 3.2636692173144204e-05 loss: 0.0562 (0.0645) time: 2.6532 data: 0.0061 max mem: 33369 +Epoch: [15] [ 140/1319] eta: 0:52:21 lr: 3.2627748844023084e-05 loss: 0.0552 (0.0633) time: 2.6375 data: 0.0061 max mem: 33369 +Epoch: [15] [ 150/1319] eta: 0:51:51 lr: 3.261880524251768e-05 loss: 0.0537 (0.0631) time: 2.6288 data: 0.0061 max mem: 33369 +Epoch: [15] [ 160/1319] eta: 0:51:23 lr: 3.260986136853672e-05 loss: 0.0555 (0.0634) time: 2.6376 data: 0.0061 max mem: 33369 +Epoch: [15] [ 170/1319] eta: 0:50:56 lr: 3.2600917221988844e-05 loss: 0.0663 (0.0644) time: 2.6457 data: 0.0059 max mem: 33369 +Epoch: [15] [ 180/1319] eta: 0:50:28 lr: 3.259197280278268e-05 loss: 0.0582 (0.0640) time: 2.6442 data: 0.0059 max mem: 33369 +Epoch: [15] [ 190/1319] eta: 0:50:01 lr: 3.258302811082674e-05 loss: 0.0490 (0.0637) time: 2.6443 data: 0.0059 max mem: 33369 +Epoch: [15] [ 200/1319] eta: 0:49:32 lr: 3.257408314602953e-05 loss: 0.0534 (0.0633) time: 2.6340 data: 0.0059 max mem: 33369 +Epoch: [15] [ 210/1319] eta: 0:49:03 lr: 3.2565137908299456e-05 loss: 0.0607 (0.0648) time: 2.6178 data: 0.0060 max mem: 33369 +Epoch: [15] [ 220/1319] eta: 0:48:35 lr: 3.25561923975449e-05 loss: 0.0625 (0.0646) time: 2.6205 data: 0.0062 max mem: 33369 +Epoch: [15] [ 230/1319] eta: 0:48:10 lr: 3.2547246613674155e-05 loss: 0.0526 (0.0644) time: 2.6510 data: 0.0060 max mem: 33369 +Epoch: [15] [ 240/1319] eta: 0:47:42 lr: 3.253830055659547e-05 loss: 0.0511 (0.0642) time: 2.6513 data: 0.0059 max mem: 33369 +Epoch: [15] [ 250/1319] eta: 0:47:17 lr: 3.252935422621704e-05 loss: 0.0516 (0.0641) time: 2.6545 data: 0.0059 max mem: 33369 +Epoch: [15] [ 260/1319] eta: 0:46:49 lr: 3.252040762244701e-05 loss: 0.0516 (0.0639) time: 2.6494 data: 0.0060 max mem: 33369 +Epoch: [15] [ 270/1319] eta: 0:46:20 lr: 3.251146074519342e-05 loss: 0.0541 (0.0640) time: 2.6107 data: 0.0060 max mem: 33369 +Epoch: [15] [ 280/1319] eta: 0:45:51 lr: 3.2502513594364305e-05 loss: 0.0571 (0.0639) time: 2.5824 data: 0.0059 max mem: 33369 +Epoch: [15] [ 290/1319] eta: 0:45:24 lr: 3.2493566169867616e-05 loss: 0.0582 (0.0637) time: 2.6007 data: 0.0061 max mem: 33369 +Epoch: [15] [ 300/1319] eta: 0:44:57 lr: 3.248461847161124e-05 loss: 0.0582 (0.0636) time: 2.6342 data: 0.0061 max mem: 33369 +Epoch: [15] [ 310/1319] eta: 0:44:28 lr: 3.247567049950301e-05 loss: 0.0589 (0.0638) time: 2.6071 data: 0.0061 max mem: 33369 +Epoch: [15] [ 320/1319] eta: 0:44:02 lr: 3.246672225345071e-05 loss: 0.0589 (0.0636) time: 2.6173 data: 0.0060 max mem: 33369 +Epoch: [15] [ 330/1319] eta: 0:43:35 lr: 3.245777373336205e-05 loss: 0.0622 (0.0636) time: 2.6449 data: 0.0061 max mem: 33369 +Epoch: [15] [ 340/1319] eta: 0:43:08 lr: 3.244882493914469e-05 loss: 0.0608 (0.0638) time: 2.6246 data: 0.0058 max mem: 33369 +Epoch: [15] [ 350/1319] eta: 0:42:41 lr: 3.243987587070623e-05 loss: 0.0583 (0.0637) time: 2.6110 data: 0.0058 max mem: 33369 +Epoch: [15] [ 360/1319] eta: 0:42:13 lr: 3.24309265279542e-05 loss: 0.0628 (0.0637) time: 2.6098 data: 0.0061 max mem: 33369 +Epoch: [15] [ 370/1319] eta: 0:41:47 lr: 3.2421976910796087e-05 loss: 0.0628 (0.0638) time: 2.6214 data: 0.0062 max mem: 33369 +Epoch: [15] [ 380/1319] eta: 0:41:20 lr: 3.24130270191393e-05 loss: 0.0627 (0.0638) time: 2.6337 data: 0.0061 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eta: 0:27:10 lr: 3.212648499367893e-05 loss: 0.0533 (0.0645) time: 2.6200 data: 0.0060 max mem: 33369 +Epoch: [15] [ 710/1319] eta: 0:26:43 lr: 3.211752599123473e-05 loss: 0.0599 (0.0644) time: 2.6131 data: 0.0059 max mem: 33369 +Epoch: [15] [ 720/1319] eta: 0:26:17 lr: 3.210856671110825e-05 loss: 0.0537 (0.0643) time: 2.6175 data: 0.0059 max mem: 33369 +Epoch: [15] [ 730/1319] eta: 0:25:50 lr: 3.2099607153204766e-05 loss: 0.0474 (0.0641) time: 2.5958 data: 0.0059 max mem: 33369 +Epoch: [15] [ 740/1319] eta: 0:25:23 lr: 3.209064731742954e-05 loss: 0.0528 (0.0643) time: 2.5914 data: 0.0060 max mem: 33369 +Epoch: [15] [ 750/1319] eta: 0:24:57 lr: 3.208168720368771e-05 loss: 0.0720 (0.0645) time: 2.6192 data: 0.0061 max mem: 33369 +Epoch: [15] [ 760/1319] eta: 0:24:31 lr: 3.2072726811884414e-05 loss: 0.0720 (0.0646) time: 2.6370 data: 0.0059 max mem: 33369 +Epoch: [15] [ 770/1319] eta: 0:24:04 lr: 3.20637661419247e-05 loss: 0.0646 (0.0646) time: 2.6309 data: 0.0060 max mem: 33369 +Epoch: 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(0.0646) time: 2.6040 data: 0.0060 max mem: 33369 +Epoch: [15] [1020/1319] eta: 0:13:05 lr: 3.183965871309119e-05 loss: 0.0594 (0.0646) time: 2.5827 data: 0.0059 max mem: 33369 +Epoch: [15] [1030/1319] eta: 0:12:39 lr: 3.1830690777532884e-05 loss: 0.0600 (0.0645) time: 2.6142 data: 0.0058 max mem: 33369 +Epoch: [15] [1040/1319] eta: 0:12:13 lr: 3.182172256123091e-05 loss: 0.0523 (0.0645) time: 2.6452 data: 0.0057 max mem: 33369 +Epoch: [15] [1050/1319] eta: 0:11:47 lr: 3.181275406408854e-05 loss: 0.0664 (0.0646) time: 2.6511 data: 0.0058 max mem: 33369 +Epoch: [15] [1060/1319] eta: 0:11:20 lr: 3.180378528600901e-05 loss: 0.0667 (0.0648) time: 2.6374 data: 0.0059 max mem: 33369 +Epoch: [15] [1070/1319] eta: 0:10:54 lr: 3.17948162268955e-05 loss: 0.0637 (0.0648) time: 2.6112 data: 0.0059 max mem: 33369 +Epoch: [15] [1080/1319] eta: 0:10:28 lr: 3.17858468866511e-05 loss: 0.0619 (0.0649) time: 2.6191 data: 0.0058 max mem: 33369 +Epoch: [15] [1090/1319] eta: 0:10:01 lr: 3.177687726517885e-05 loss: 0.0591 (0.0649) time: 2.6003 data: 0.0059 max mem: 33369 +Epoch: [15] [1100/1319] eta: 0:09:35 lr: 3.1767907362381725e-05 loss: 0.0676 (0.0650) time: 2.5913 data: 0.0059 max mem: 33369 +Epoch: [15] [1110/1319] eta: 0:09:09 lr: 3.175893717816263e-05 loss: 0.0616 (0.0650) time: 2.6321 data: 0.0058 max mem: 33369 +Epoch: [15] [1120/1319] eta: 0:08:42 lr: 3.174996671242443e-05 loss: 0.0565 (0.0649) time: 2.6555 data: 0.0058 max mem: 33369 +Epoch: [15] [1130/1319] eta: 0:08:16 lr: 3.1740995965069895e-05 loss: 0.0520 (0.0648) time: 2.6379 data: 0.0059 max mem: 33369 +Epoch: [15] [1140/1319] eta: 0:07:50 lr: 3.173202493600174e-05 loss: 0.0520 (0.0649) time: 2.6295 data: 0.0058 max mem: 33369 +Epoch: [15] [1150/1319] eta: 0:07:24 lr: 3.172305362512263e-05 loss: 0.0647 (0.0649) time: 2.6252 data: 0.0059 max mem: 33369 +Epoch: [15] [1160/1319] eta: 0:06:57 lr: 3.171408203233514e-05 loss: 0.0740 (0.0651) time: 2.6093 data: 0.0059 max mem: 33369 +Epoch: [15] [1170/1319] eta: 0:06:31 lr: 3.170511015754181e-05 loss: 0.0770 (0.0651) time: 2.6350 data: 0.0059 max mem: 33369 +Epoch: [15] [1180/1319] eta: 0:06:05 lr: 3.16961380006451e-05 loss: 0.0519 (0.0651) time: 2.6375 data: 0.0058 max mem: 33369 +Epoch: [15] [1190/1319] eta: 0:05:39 lr: 3.16871655615474e-05 loss: 0.0538 (0.0650) time: 2.6376 data: 0.0058 max mem: 33369 +Epoch: [15] [1200/1319] eta: 0:05:12 lr: 3.1678192840151044e-05 loss: 0.0529 (0.0649) time: 2.6500 data: 0.0060 max mem: 33369 +Epoch: [15] [1210/1319] eta: 0:04:46 lr: 3.16692198363583e-05 loss: 0.0529 (0.0648) time: 2.6400 data: 0.0060 max mem: 33369 +Epoch: [15] [1220/1319] eta: 0:04:20 lr: 3.1660246550071386e-05 loss: 0.0567 (0.0649) time: 2.6410 data: 0.0060 max mem: 33369 +Epoch: [15] [1230/1319] eta: 0:03:53 lr: 3.165127298119242e-05 loss: 0.0645 (0.0649) time: 2.6394 data: 0.0060 max mem: 33369 +Epoch: [15] [1240/1319] eta: 0:03:27 lr: 3.164229912962349e-05 loss: 0.0645 (0.0650) time: 2.6333 data: 0.0060 max mem: 33369 +Epoch: [15] [1250/1319] eta: 0:03:01 lr: 3.163332499526659e-05 loss: 0.0555 (0.0650) time: 2.6413 data: 0.0059 max mem: 33369 +Epoch: [15] [1260/1319] eta: 0:02:35 lr: 3.162435057802369e-05 loss: 0.0555 (0.0649) time: 2.6258 data: 0.0058 max mem: 33369 +Epoch: [15] [1270/1319] eta: 0:02:08 lr: 3.161537587779665e-05 loss: 0.0584 (0.0650) time: 2.5957 data: 0.0058 max mem: 33369 +Epoch: [15] [1280/1319] eta: 0:01:42 lr: 3.1606400894487287e-05 loss: 0.0700 (0.0653) time: 2.6130 data: 0.0060 max mem: 33369 +Epoch: [15] [1290/1319] eta: 0:01:16 lr: 3.159742562799735e-05 loss: 0.0712 (0.0653) time: 2.6365 data: 0.0058 max mem: 33369 +Epoch: [15] [1300/1319] eta: 0:00:49 lr: 3.158845007822852e-05 loss: 0.0688 (0.0654) time: 2.6002 data: 0.0057 max mem: 33369 +Epoch: [15] [1310/1319] eta: 0:00:23 lr: 3.1579474245082424e-05 loss: 0.0713 (0.0655) time: 2.6161 data: 0.0058 max mem: 33369 +Epoch: [15] Total time: 0:57:47 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 1:51:32 time: 2.6010 data: 2.5223 max mem: 33369 +Test: [ 100/2573] eta: 0:04:00 time: 0.0721 data: 0.0011 max mem: 33369 +Test: [ 200/2573] eta: 0:03:24 time: 0.0738 data: 0.0011 max mem: 33369 +Test: [ 300/2573] eta: 0:03:05 time: 0.0756 data: 0.0011 max mem: 33369 +Test: [ 400/2573] eta: 0:02:52 time: 0.0754 data: 0.0011 max mem: 33369 +Test: [ 500/2573] eta: 0:02:42 time: 0.0739 data: 0.0011 max mem: 33369 +Test: [ 600/2573] eta: 0:02:33 time: 0.0740 data: 0.0011 max mem: 33369 +Test: [ 700/2573] eta: 0:02:25 time: 0.0740 data: 0.0011 max mem: 33369 +Test: [ 800/2573] eta: 0:02:16 time: 0.0774 data: 0.0011 max mem: 33369 +Test: [ 900/2573] eta: 0:02:08 time: 0.0741 data: 0.0011 max mem: 33369 +Test: [1000/2573] eta: 0:02:00 time: 0.0741 data: 0.0011 max mem: 33369 +Test: [1100/2573] eta: 0:01:52 time: 0.0740 data: 0.0011 max mem: 33369 +Test: [1200/2573] eta: 0:01:44 time: 0.0739 data: 0.0011 max mem: 33369 +Test: [1300/2573] eta: 0:01:36 time: 0.0740 data: 0.0011 max mem: 33369 +Test: [1400/2573] eta: 0:01:29 time: 0.0723 data: 0.0011 max mem: 33369 +Test: [1500/2573] eta: 0:01:21 time: 0.0739 data: 0.0011 max mem: 33369 +Test: [1600/2573] eta: 0:01:13 time: 0.0773 data: 0.0011 max mem: 33369 +Test: [1700/2573] eta: 0:01:06 time: 0.0723 data: 0.0011 max mem: 33369 +Test: [1800/2573] eta: 0:00:58 time: 0.0755 data: 0.0011 max mem: 33369 +Test: [1900/2573] eta: 0:00:50 time: 0.0721 data: 0.0011 max mem: 33369 +Test: [2000/2573] eta: 0:00:43 time: 0.0740 data: 0.0011 max mem: 33369 +Test: [2100/2573] eta: 0:00:35 time: 0.0756 data: 0.0011 max mem: 33369 +Test: [2200/2573] eta: 0:00:28 time: 0.0756 data: 0.0010 max mem: 33369 +Test: [2300/2573] eta: 0:00:20 time: 0.0756 data: 0.0011 max mem: 33369 +Test: [2400/2573] eta: 0:00:12 time: 0.0708 data: 0.0011 max mem: 33369 +Test: [2500/2573] eta: 0:00:05 time: 0.0740 data: 0.0011 max mem: 33369 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: Total time: 0:03:13 +Final results: +Mean IoU is 61.83 + + precision@0.5 = 69.06 + precision@0.6 = 63.38 + precision@0.7 = 55.94 + precision@0.8 = 44.42 + precision@0.9 = 21.47 + overall IoU = 60.35 + +Average object IoU 61.82580520825607 +Overall IoU 60.354496002197266 +Better epoch: 15 + +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [16] [ 0/1319] eta: 1:29:36 lr: 3.157139575288201e-05 loss: 0.0512 (0.0512) time: 4.0764 data: 1.3285 max mem: 33369 +Epoch: [16] [ 10/1319] eta: 0:59:51 lr: 3.1562419381047834e-05 loss: 0.0512 (0.0553) time: 2.7440 data: 0.1258 max mem: 33369 +Epoch: [16] [ 20/1319] eta: 0:57:51 lr: 3.155344272555071e-05 loss: 0.0473 (0.0524) time: 2.6021 data: 0.0054 max mem: 33369 +Epoch: [16] [ 30/1319] eta: 0:57:07 lr: 3.154446578629201e-05 loss: 0.0544 (0.0576) time: 2.6122 data: 0.0057 max mem: 33369 +Epoch: [16] [ 40/1319] eta: 0:56:17 lr: 3.153548856317304e-05 loss: 0.0610 (0.0569) time: 2.6076 data: 0.0061 max mem: 33369 +Epoch: [16] [ 50/1319] eta: 0:55:53 lr: 3.152651105609501e-05 loss: 0.0457 (0.0542) time: 2.6174 data: 0.0061 max mem: 33369 +Epoch: [16] [ 60/1319] eta: 0:55:24 lr: 3.1517533264959104e-05 loss: 0.0430 (0.0543) time: 2.6398 data: 0.0061 max mem: 33369 +Epoch: [16] [ 70/1319] eta: 0:54:53 lr: 3.150855518966642e-05 loss: 0.0516 (0.0571) time: 2.6212 data: 0.0061 max mem: 33369 +Epoch: [16] [ 80/1319] eta: 0:54:24 lr: 3.1499576830118e-05 loss: 0.0518 (0.0560) time: 2.6190 data: 0.0059 max mem: 33369 +Epoch: [16] [ 90/1319] eta: 0:54:01 lr: 3.14905981862148e-05 loss: 0.0480 (0.0565) time: 2.6403 data: 0.0060 max mem: 33369 +Epoch: [16] [ 100/1319] eta: 0:53:31 lr: 3.1481619257857746e-05 loss: 0.0531 (0.0572) time: 2.6321 data: 0.0062 max mem: 33369 +Epoch: [16] [ 110/1319] eta: 0:53:05 lr: 3.147264004494766e-05 loss: 0.0537 (0.0575) time: 2.6250 data: 0.0062 max mem: 33369 +Epoch: [16] [ 120/1319] eta: 0:52:35 lr: 3.1463660547385324e-05 loss: 0.0562 (0.0573) time: 2.6156 data: 0.0060 max mem: 33369 +Epoch: [16] [ 130/1319] eta: 0:52:02 lr: 3.1454680765071425e-05 loss: 0.0578 (0.0579) time: 2.5758 data: 0.0059 max mem: 33369 +Epoch: [16] [ 140/1319] eta: 0:51:34 lr: 3.1445700697906627e-05 loss: 0.0512 (0.0570) time: 2.5863 data: 0.0060 max mem: 33369 +Epoch: [16] [ 150/1319] eta: 0:51:07 lr: 3.1436720345791495e-05 loss: 0.0512 (0.0580) time: 2.6100 data: 0.0059 max mem: 33369 +Epoch: [16] [ 160/1319] eta: 0:50:42 lr: 3.1427739708626534e-05 loss: 0.0516 (0.0574) time: 2.6240 data: 0.0060 max mem: 33369 +Epoch: [16] [ 170/1319] eta: 0:50:15 lr: 3.141875878631219e-05 loss: 0.0479 (0.0569) time: 2.6298 data: 0.0060 max mem: 33369 +Epoch: [16] [ 180/1319] eta: 0:49:48 lr: 3.140977757874883e-05 loss: 0.0545 (0.0572) time: 2.6171 data: 0.0061 max mem: 33369 +Epoch: [16] [ 190/1319] eta: 0:49:21 lr: 3.140079608583676e-05 loss: 0.0583 (0.0570) time: 2.6104 data: 0.0061 max mem: 33369 +Epoch: [16] [ 200/1319] eta: 0:48:52 lr: 3.1391814307476244e-05 loss: 0.0403 (0.0565) time: 2.5876 data: 0.0062 max mem: 33369 +Epoch: [16] [ 210/1319] eta: 0:48:27 lr: 3.138283224356744e-05 loss: 0.0465 (0.0567) time: 2.6089 data: 0.0061 max mem: 33369 +Epoch: [16] [ 220/1319] eta: 0:47:59 lr: 3.137384989401046e-05 loss: 0.0478 (0.0568) time: 2.6195 data: 0.0059 max mem: 33369 +Epoch: [16] [ 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eta: 0:30:34 lr: 3.1014320525175755e-05 loss: 0.0536 (0.0587) time: 2.6213 data: 0.0060 max mem: 33369 +Epoch: [16] [ 630/1319] eta: 0:30:08 lr: 3.100532637720542e-05 loss: 0.0617 (0.0587) time: 2.6388 data: 0.0059 max mem: 33369 +Epoch: [16] [ 640/1319] eta: 0:29:42 lr: 3.099633193933038e-05 loss: 0.0617 (0.0587) time: 2.6502 data: 0.0058 max mem: 33369 +Epoch: [16] [ 650/1319] eta: 0:29:16 lr: 3.098733721144784e-05 loss: 0.0486 (0.0586) time: 2.6349 data: 0.0057 max mem: 33369 +Epoch: [16] [ 660/1319] eta: 0:28:49 lr: 3.097834219345489e-05 loss: 0.0486 (0.0587) time: 2.6174 data: 0.0057 max mem: 33369 +Epoch: [16] [ 670/1319] eta: 0:28:23 lr: 3.0969346885248574e-05 loss: 0.0552 (0.0586) time: 2.6094 data: 0.0057 max mem: 33369 +Epoch: [16] [ 680/1319] eta: 0:27:56 lr: 3.0960351286725865e-05 loss: 0.0462 (0.0585) time: 2.5982 data: 0.0059 max mem: 33369 +Epoch: [16] [ 690/1319] eta: 0:27:31 lr: 3.0951355397783653e-05 loss: 0.0531 (0.0587) time: 2.6268 data: 0.0058 max mem: 33369 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3.066333298950271e-05 loss: 0.0632 (0.0595) time: 2.6226 data: 0.0060 max mem: 33369 +Epoch: [16] [1020/1319] eta: 0:13:03 lr: 3.065432745841652e-05 loss: 0.0551 (0.0595) time: 2.5968 data: 0.0059 max mem: 33369 +Epoch: [16] [1030/1319] eta: 0:12:37 lr: 3.064532163336335e-05 loss: 0.0543 (0.0596) time: 2.6162 data: 0.0059 max mem: 33369 +Epoch: [16] [1040/1319] eta: 0:12:11 lr: 3.063631551423762e-05 loss: 0.0523 (0.0596) time: 2.6220 data: 0.0058 max mem: 33369 +Epoch: [16] [1050/1319] eta: 0:11:45 lr: 3.062730910093366e-05 loss: 0.0493 (0.0596) time: 2.6117 data: 0.0059 max mem: 33369 +Epoch: [16] [1060/1319] eta: 0:11:19 lr: 3.061830239334574e-05 loss: 0.0545 (0.0596) time: 2.6242 data: 0.0059 max mem: 33369 +Epoch: [16] [1070/1319] eta: 0:10:52 lr: 3.0609295391368055e-05 loss: 0.0592 (0.0597) time: 2.6189 data: 0.0058 max mem: 33369 +Epoch: [16] [1080/1319] eta: 0:10:26 lr: 3.060028809489473e-05 loss: 0.0538 (0.0597) time: 2.6206 data: 0.0058 max mem: 33369 +Epoch: [16] [1090/1319] eta: 0:10:00 lr: 3.059128050381978e-05 loss: 0.0418 (0.0595) time: 2.6219 data: 0.0057 max mem: 33369 +Epoch: [16] [1100/1319] eta: 0:09:34 lr: 3.058227261803723e-05 loss: 0.0414 (0.0596) time: 2.6177 data: 0.0058 max mem: 33369 +Epoch: [16] [1110/1319] eta: 0:09:07 lr: 3.0573264437440946e-05 loss: 0.0558 (0.0595) time: 2.6057 data: 0.0059 max mem: 33369 +Epoch: [16] [1120/1319] eta: 0:08:41 lr: 3.056425596192476e-05 loss: 0.0533 (0.0595) time: 2.6043 data: 0.0059 max mem: 33369 +Epoch: [16] [1130/1319] eta: 0:08:15 lr: 3.0555247191382436e-05 loss: 0.0474 (0.0594) time: 2.6177 data: 0.0059 max mem: 33369 +Epoch: [16] [1140/1319] eta: 0:07:49 lr: 3.054623812570766e-05 loss: 0.0474 (0.0593) time: 2.6185 data: 0.0059 max mem: 33369 +Epoch: [16] [1150/1319] eta: 0:07:23 lr: 3.053722876479403e-05 loss: 0.0559 (0.0594) time: 2.6237 data: 0.0059 max mem: 33369 +Epoch: [16] [1160/1319] eta: 0:06:56 lr: 3.0528219108535084e-05 loss: 0.0602 (0.0595) time: 2.6205 data: 0.0058 max mem: 33369 +Epoch: [16] [1170/1319] eta: 0:06:30 lr: 3.0519209156824297e-05 loss: 0.0601 (0.0595) time: 2.6166 data: 0.0058 max mem: 33369 +Epoch: [16] [1180/1319] eta: 0:06:04 lr: 3.0510198909555044e-05 loss: 0.0591 (0.0595) time: 2.6258 data: 0.0059 max mem: 33369 +Epoch: [16] [1190/1319] eta: 0:05:38 lr: 3.0501188366620653e-05 loss: 0.0619 (0.0596) time: 2.6311 data: 0.0059 max mem: 33369 +Epoch: [16] [1200/1319] eta: 0:05:11 lr: 3.0492177527914355e-05 loss: 0.0627 (0.0596) time: 2.6201 data: 0.0060 max mem: 33369 +Epoch: [16] [1210/1319] eta: 0:04:45 lr: 3.0483166393329327e-05 loss: 0.0594 (0.0596) time: 2.5893 data: 0.0059 max mem: 33369 +Epoch: [16] [1220/1319] eta: 0:04:19 lr: 3.0474154962758662e-05 loss: 0.0594 (0.0597) time: 2.5730 data: 0.0058 max mem: 33369 +Epoch: [16] [1230/1319] eta: 0:03:53 lr: 3.0465143236095372e-05 loss: 0.0555 (0.0597) time: 2.6035 data: 0.0059 max mem: 33369 +Epoch: [16] [1240/1319] eta: 0:03:27 lr: 3.045613121323242e-05 loss: 0.0555 (0.0598) time: 2.6472 data: 0.0058 max mem: 33369 +Epoch: [16] [1250/1319] eta: 0:03:00 lr: 3.044711889406267e-05 loss: 0.0472 (0.0598) time: 2.6402 data: 0.0058 max mem: 33369 +Epoch: [16] [1260/1319] eta: 0:02:34 lr: 3.0438106278478923e-05 loss: 0.0565 (0.0598) time: 2.5994 data: 0.0059 max mem: 33369 +Epoch: [16] [1270/1319] eta: 0:02:08 lr: 3.0429093366373907e-05 loss: 0.0594 (0.0598) time: 2.5854 data: 0.0061 max mem: 33369 +Epoch: [16] [1280/1319] eta: 0:01:42 lr: 3.0420080157640274e-05 loss: 0.0582 (0.0599) time: 2.6056 data: 0.0061 max mem: 33369 +Epoch: [16] [1290/1319] eta: 0:01:16 lr: 3.0411066652170593e-05 loss: 0.0603 (0.0601) time: 2.6413 data: 0.0060 max mem: 33369 +Epoch: [16] [1300/1319] eta: 0:00:49 lr: 3.040205284985739e-05 loss: 0.0618 (0.0600) time: 2.6569 data: 0.0058 max mem: 33369 +Epoch: [16] [1310/1319] eta: 0:00:23 lr: 3.039303875059306e-05 loss: 0.0571 (0.0600) time: 2.6512 data: 0.0058 max mem: 33369 +Epoch: [16] Total time: 0:57:37 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 1:58:40 time: 2.7676 data: 2.6785 max mem: 33369 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 100/2573] eta: 0:04:03 time: 0.0715 data: 0.0011 max mem: 33369 +Test: [ 200/2573] eta: 0:03:25 time: 0.0732 data: 0.0011 max mem: 33369 +Test: [ 300/2573] eta: 0:03:05 time: 0.0750 data: 0.0011 max mem: 33369 +Test: [ 400/2573] eta: 0:02:52 time: 0.0750 data: 0.0011 max mem: 33369 +Test: [ 500/2573] eta: 0:02:42 time: 0.0735 data: 0.0011 max mem: 33369 +Test: [ 600/2573] eta: 0:02:33 time: 0.0735 data: 0.0011 max mem: 33369 +Test: [ 700/2573] eta: 0:02:24 time: 0.0736 data: 0.0011 max mem: 33369 +Test: [ 800/2573] eta: 0:02:16 time: 0.0770 data: 0.0011 max mem: 33369 +Test: [ 900/2573] eta: 0:02:08 time: 0.0738 data: 0.0011 max mem: 33369 +Test: [1000/2573] eta: 0:02:00 time: 0.0738 data: 0.0011 max mem: 33369 +Test: [1100/2573] eta: 0:01:52 time: 0.0738 data: 0.0011 max mem: 33369 +Test: [1200/2573] eta: 0:01:44 time: 0.0736 data: 0.0011 max mem: 33369 +Test: [1300/2573] eta: 0:01:36 time: 0.0737 data: 0.0011 max mem: 33369 +Test: [1400/2573] eta: 0:01:28 time: 0.0721 data: 0.0011 max mem: 33369 +Test: [1500/2573] eta: 0:01:21 time: 0.0737 data: 0.0011 max mem: 33369 +Test: [1600/2573] eta: 0:01:13 time: 0.0770 data: 0.0011 max mem: 33369 +Test: [1700/2573] eta: 0:01:05 time: 0.0720 data: 0.0011 max mem: 33369 +Test: [1800/2573] eta: 0:00:58 time: 0.0753 data: 0.0011 max mem: 33369 +Test: [1900/2573] eta: 0:00:50 time: 0.0721 data: 0.0011 max mem: 33369 +Test: [2000/2573] eta: 0:00:42 time: 0.0737 data: 0.0011 max mem: 33369 +Test: [2100/2573] eta: 0:00:35 time: 0.0754 data: 0.0011 max mem: 33369 +Test: [2200/2573] eta: 0:00:27 time: 0.0754 data: 0.0011 max mem: 33369 +Test: [2300/2573] eta: 0:00:20 time: 0.0753 data: 0.0011 max mem: 33369 +Test: [2400/2573] eta: 0:00:12 time: 0.0704 data: 0.0011 max mem: 33369 +Test: [2500/2573] eta: 0:00:05 time: 0.0737 data: 0.0011 max mem: 33369 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: Total time: 0:03:12 +Final results: +Mean IoU is 61.68 + + precision@0.5 = 68.63 + precision@0.6 = 63.03 + precision@0.7 = 56.21 + precision@0.8 = 44.87 + precision@0.9 = 21.94 + overall IoU = 59.86 + +Average object IoU 61.67553116062897 +Overall IoU 59.85843276977539 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [17] [ 0/1319] eta: 3:09:56 lr: 3.0384925807273e-05 loss: 0.0562 (0.0562) time: 8.6400 data: 1.1891 max mem: 33369 +Epoch: [17] [ 10/1319] eta: 1:09:30 lr: 3.0375911143504937e-05 loss: 0.0562 (0.0518) time: 3.1860 data: 0.1134 max mem: 33369 +Epoch: [17] [ 20/1319] eta: 1:02:59 lr: 3.0366896182473385e-05 loss: 0.0482 (0.0553) time: 2.6231 data: 0.0058 max mem: 33369 +Epoch: [17] [ 30/1319] eta: 1:00:26 lr: 3.035788092407048e-05 loss: 0.0482 (0.0552) time: 2.6088 data: 0.0059 max mem: 33369 +Epoch: [17] [ 40/1319] eta: 0:58:55 lr: 3.034886536818829e-05 loss: 0.0551 (0.0582) time: 2.6115 data: 0.0061 max mem: 33369 +Epoch: [17] [ 50/1319] eta: 0:57:50 lr: 3.0339849514718806e-05 loss: 0.0466 (0.0583) time: 2.6120 data: 0.0061 max mem: 33369 +Epoch: [17] [ 60/1319] eta: 0:57:07 lr: 3.033083336355392e-05 loss: 0.0459 (0.0577) time: 2.6366 data: 0.0060 max mem: 33369 +Epoch: [17] [ 70/1319] eta: 0:56:21 lr: 3.03218169145855e-05 loss: 0.0459 (0.0573) time: 2.6371 data: 0.0060 max mem: 33369 +Epoch: [17] [ 80/1319] eta: 0:55:44 lr: 3.0312800167705292e-05 loss: 0.0472 (0.0588) time: 2.6300 data: 0.0060 max mem: 33369 +Epoch: [17] [ 90/1319] eta: 0:55:13 lr: 3.030378312280498e-05 loss: 0.0468 (0.0575) time: 2.6557 data: 0.0059 max mem: 33369 +Epoch: [17] [ 100/1319] eta: 0:54:37 lr: 3.0294765779776184e-05 loss: 0.0452 (0.0576) time: 2.6432 data: 0.0058 max mem: 33369 +Epoch: [17] [ 110/1319] eta: 0:54:03 lr: 3.0285748138510444e-05 loss: 0.0477 (0.0577) time: 2.6220 data: 0.0060 max mem: 33369 +Epoch: [17] [ 120/1319] eta: 0:53:26 lr: 3.0276730198899216e-05 loss: 0.0477 (0.0568) time: 2.6030 data: 0.0061 max mem: 33369 +Epoch: [17] [ 130/1319] eta: 0:52:53 lr: 3.0267711960833896e-05 loss: 0.0473 (0.0571) time: 2.5970 data: 0.0061 max mem: 33369 +Epoch: [17] [ 140/1319] eta: 0:52:18 lr: 3.0258693424205785e-05 loss: 0.0501 (0.0571) time: 2.5893 data: 0.0062 max mem: 33369 +Epoch: [17] [ 150/1319] eta: 0:51:46 lr: 3.024967458890613e-05 loss: 0.0463 (0.0563) time: 2.5758 data: 0.0063 max mem: 33369 +Epoch: [17] [ 160/1319] eta: 0:51:17 lr: 3.0240655454826085e-05 loss: 0.0532 (0.0574) time: 2.6033 data: 0.0062 max mem: 33369 +Epoch: [17] [ 170/1319] eta: 0:50:47 lr: 3.023163602185673e-05 loss: 0.0575 (0.0573) time: 2.6195 data: 0.0059 max mem: 33369 +Epoch: [17] [ 180/1319] eta: 0:50:18 lr: 3.022261628988908e-05 loss: 0.0548 (0.0575) time: 2.6142 data: 0.0060 max mem: 33369 +Epoch: [17] [ 190/1319] eta: 0:49:52 lr: 3.0213596258814065e-05 loss: 0.0586 (0.0578) time: 2.6369 data: 0.0062 max mem: 33369 +Epoch: [17] [ 200/1319] eta: 0:49:26 lr: 3.020457592852254e-05 loss: 0.0588 (0.0578) time: 2.6548 data: 0.0061 max mem: 33369 +Epoch: [17] [ 210/1319] eta: 0:49:00 lr: 3.0195555298905282e-05 loss: 0.0584 (0.0579) time: 2.6521 data: 0.0060 max mem: 33369 +Epoch: [17] [ 220/1319] eta: 0:48:30 lr: 3.0186534369853002e-05 loss: 0.0510 (0.0582) time: 2.6236 data: 0.0059 max mem: 33369 +Epoch: [17] [ 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33369 +Epoch: [17] [ 310/1319] eta: 0:44:22 lr: 3.010533251573493e-05 loss: 0.0437 (0.0572) time: 2.6017 data: 0.0059 max mem: 33369 +Epoch: [17] [ 320/1319] eta: 0:43:54 lr: 3.0096308586304355e-05 loss: 0.0457 (0.0571) time: 2.6145 data: 0.0060 max mem: 33369 +Epoch: [17] [ 330/1319] eta: 0:43:27 lr: 3.0087284356231465e-05 loss: 0.0466 (0.0570) time: 2.6118 data: 0.0061 max mem: 33369 +Epoch: [17] [ 340/1319] eta: 0:43:01 lr: 3.0078259825406035e-05 loss: 0.0442 (0.0570) time: 2.6365 data: 0.0060 max mem: 33369 +Epoch: [17] [ 350/1319] eta: 0:42:35 lr: 3.0069234993717783e-05 loss: 0.0475 (0.0573) time: 2.6532 data: 0.0060 max mem: 33369 +Epoch: [17] [ 360/1319] eta: 0:42:09 lr: 3.006020986105632e-05 loss: 0.0555 (0.0575) time: 2.6408 data: 0.0060 max mem: 33369 +Epoch: [17] [ 370/1319] eta: 0:41:41 lr: 3.005118442731122e-05 loss: 0.0520 (0.0574) time: 2.6095 data: 0.0060 max mem: 33369 +Epoch: [17] [ 380/1319] eta: 0:41:16 lr: 3.004215869237195e-05 loss: 0.0506 (0.0574) time: 2.6258 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2.989770588044718e-05 loss: 0.0509 (0.0574) time: 2.6258 data: 0.0060 max mem: 33369 +Epoch: [17] [ 550/1319] eta: 0:33:44 lr: 2.9888675008221372e-05 loss: 0.0484 (0.0574) time: 2.6172 data: 0.0059 max mem: 33369 +Epoch: [17] [ 560/1319] eta: 0:33:18 lr: 2.9879643832798625e-05 loss: 0.0509 (0.0573) time: 2.6079 data: 0.0059 max mem: 33369 +Epoch: [17] [ 570/1319] eta: 0:32:51 lr: 2.987061235406693e-05 loss: 0.0562 (0.0573) time: 2.6057 data: 0.0060 max mem: 33369 +Epoch: [17] [ 580/1319] eta: 0:32:24 lr: 2.98615805719142e-05 loss: 0.0528 (0.0572) time: 2.6002 data: 0.0060 max mem: 33369 +Epoch: [17] [ 590/1319] eta: 0:31:58 lr: 2.9852548486228266e-05 loss: 0.0517 (0.0573) time: 2.6228 data: 0.0059 max mem: 33369 +Epoch: [17] [ 600/1319] eta: 0:31:32 lr: 2.9843516096896873e-05 loss: 0.0537 (0.0573) time: 2.6356 data: 0.0061 max mem: 33369 +Epoch: [17] [ 610/1319] eta: 0:31:05 lr: 2.98344834038077e-05 loss: 0.0537 (0.0574) time: 2.6274 data: 0.0060 max mem: 33369 +Epoch: [17] [ 620/1319] eta: 0:30:39 lr: 2.9825450406848343e-05 loss: 0.0523 (0.0574) time: 2.6416 data: 0.0059 max mem: 33369 +Epoch: [17] [ 630/1319] eta: 0:30:13 lr: 2.981641710590631e-05 loss: 0.0567 (0.0574) time: 2.6448 data: 0.0060 max mem: 33369 +Epoch: [17] [ 640/1319] eta: 0:29:46 lr: 2.9807383500869036e-05 loss: 0.0561 (0.0575) time: 2.6104 data: 0.0061 max mem: 33369 +Epoch: [17] [ 650/1319] eta: 0:29:19 lr: 2.9798349591623877e-05 loss: 0.0554 (0.0575) time: 2.5935 data: 0.0060 max mem: 33369 +Epoch: [17] [ 660/1319] eta: 0:28:53 lr: 2.9789315378058107e-05 loss: 0.0692 (0.0578) time: 2.6205 data: 0.0060 max mem: 33369 +Epoch: [17] [ 670/1319] eta: 0:28:27 lr: 2.978028086005893e-05 loss: 0.0612 (0.0579) time: 2.6203 data: 0.0061 max mem: 33369 +Epoch: [17] [ 680/1319] eta: 0:28:01 lr: 2.977124603751345e-05 loss: 0.0523 (0.0578) time: 2.6443 data: 0.0059 max mem: 33369 +Epoch: [17] [ 690/1319] eta: 0:27:35 lr: 2.9762210910308712e-05 loss: 0.0507 (0.0578) time: 2.6616 data: 0.0057 max mem: 33369 +Epoch: [17] [ 700/1319] eta: 0:27:08 lr: 2.9753175478331675e-05 loss: 0.0597 (0.0579) time: 2.6049 data: 0.0058 max mem: 33369 +Epoch: [17] [ 710/1319] eta: 0:26:41 lr: 2.97441397414692e-05 loss: 0.0587 (0.0581) time: 2.5775 data: 0.0058 max mem: 33369 +Epoch: [17] [ 720/1319] eta: 0:26:15 lr: 2.973510369960809e-05 loss: 0.0481 (0.0580) time: 2.6110 data: 0.0058 max mem: 33369 +Epoch: [17] [ 730/1319] eta: 0:25:48 lr: 2.9726067352635072e-05 loss: 0.0540 (0.0581) time: 2.6261 data: 0.0058 max mem: 33369 +Epoch: [17] [ 740/1319] eta: 0:25:22 lr: 2.971703070043676e-05 loss: 0.0557 (0.0581) time: 2.6034 data: 0.0060 max mem: 33369 +Epoch: [17] [ 750/1319] eta: 0:24:56 lr: 2.970799374289972e-05 loss: 0.0539 (0.0580) time: 2.6160 data: 0.0061 max mem: 33369 +Epoch: [17] [ 760/1319] eta: 0:24:29 lr: 2.9698956479910424e-05 loss: 0.0475 (0.0579) time: 2.6415 data: 0.0060 max mem: 33369 +Epoch: [17] [ 770/1319] eta: 0:24:03 lr: 2.9689918911355265e-05 loss: 0.0508 (0.0581) time: 2.6654 data: 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time: 2.6250 data: 0.0059 max mem: 33369 +Epoch: [17] [ 860/1319] eta: 0:20:07 lr: 2.96085670251099e-05 loss: 0.0576 (0.0581) time: 2.6148 data: 0.0060 max mem: 33369 +Epoch: [17] [ 870/1319] eta: 0:19:40 lr: 2.959952639462995e-05 loss: 0.0604 (0.0582) time: 2.6145 data: 0.0062 max mem: 33369 +Epoch: [17] [ 880/1319] eta: 0:19:14 lr: 2.9590485457329127e-05 loss: 0.0559 (0.0582) time: 2.6335 data: 0.0061 max mem: 33369 +Epoch: [17] [ 890/1319] eta: 0:18:48 lr: 2.9581444213092834e-05 loss: 0.0543 (0.0581) time: 2.6329 data: 0.0058 max mem: 33369 +Epoch: [17] [ 900/1319] eta: 0:18:21 lr: 2.957240266180642e-05 loss: 0.0570 (0.0582) time: 2.6256 data: 0.0059 max mem: 33369 +Epoch: [17] [ 910/1319] eta: 0:17:55 lr: 2.956336080335514e-05 loss: 0.0642 (0.0583) time: 2.6215 data: 0.0061 max mem: 33369 +Epoch: [17] [ 920/1319] eta: 0:17:29 lr: 2.955431863762416e-05 loss: 0.0599 (0.0583) time: 2.6226 data: 0.0061 max mem: 33369 +Epoch: [17] [ 930/1319] eta: 0:17:03 lr: 2.9545276164498587e-05 loss: 0.0538 (0.0583) time: 2.6312 data: 0.0060 max mem: 33369 +Epoch: [17] [ 940/1319] eta: 0:16:36 lr: 2.953623338386342e-05 loss: 0.0513 (0.0583) time: 2.6130 data: 0.0059 max mem: 33369 +Epoch: [17] [ 950/1319] eta: 0:16:10 lr: 2.9527190295603586e-05 loss: 0.0513 (0.0582) time: 2.5970 data: 0.0058 max mem: 33369 +Epoch: [17] [ 960/1319] eta: 0:15:43 lr: 2.9518146899603932e-05 loss: 0.0502 (0.0582) time: 2.6251 data: 0.0059 max mem: 33369 +Epoch: [17] [ 970/1319] eta: 0:15:17 lr: 2.9509103195749226e-05 loss: 0.0563 (0.0583) time: 2.6288 data: 0.0058 max mem: 33369 +Epoch: [17] [ 980/1319] eta: 0:14:51 lr: 2.9500059183924145e-05 loss: 0.0572 (0.0584) time: 2.6138 data: 0.0060 max mem: 33369 +Epoch: [17] [ 990/1319] eta: 0:14:25 lr: 2.9491014864013282e-05 loss: 0.0538 (0.0583) time: 2.6264 data: 0.0063 max mem: 33369 +Epoch: [17] [1000/1319] eta: 0:13:58 lr: 2.9481970235901164e-05 loss: 0.0553 (0.0584) time: 2.6490 data: 0.0062 max mem: 33369 +Epoch: [17] [1010/1319] eta: 0:13:32 lr: 2.9472925299472214e-05 loss: 0.0556 (0.0585) time: 2.6539 data: 0.0061 max mem: 33369 +Epoch: [17] [1020/1319] eta: 0:13:06 lr: 2.9463880054610792e-05 loss: 0.0554 (0.0585) time: 2.6387 data: 0.0060 max mem: 33369 +Epoch: [17] [1030/1319] eta: 0:12:40 lr: 2.9454834501201163e-05 loss: 0.0554 (0.0585) time: 2.6392 data: 0.0058 max mem: 33369 +Epoch: [17] [1040/1319] eta: 0:12:13 lr: 2.9445788639127496e-05 loss: 0.0531 (0.0585) time: 2.6293 data: 0.0060 max mem: 33369 +Epoch: [17] [1050/1319] eta: 0:11:47 lr: 2.943674246827392e-05 loss: 0.0531 (0.0585) time: 2.6104 data: 0.0061 max mem: 33369 +Epoch: [17] [1060/1319] eta: 0:11:20 lr: 2.9427695988524433e-05 loss: 0.0588 (0.0586) time: 2.6010 data: 0.0060 max mem: 33369 +Epoch: [17] [1070/1319] eta: 0:10:54 lr: 2.941864919976297e-05 loss: 0.0534 (0.0586) time: 2.5993 data: 0.0059 max mem: 33369 +Epoch: [17] [1080/1319] eta: 0:10:28 lr: 2.9409602101873397e-05 loss: 0.0533 (0.0586) time: 2.5924 data: 0.0059 max mem: 33369 +Epoch: [17] [1090/1319] eta: 0:10:01 lr: 2.9400554694739468e-05 loss: 0.0552 (0.0587) time: 2.5939 data: 0.0059 max mem: 33369 +Epoch: [17] [1100/1319] eta: 0:09:35 lr: 2.9391506978244877e-05 loss: 0.0505 (0.0586) time: 2.6197 data: 0.0061 max mem: 33369 +Epoch: [17] [1110/1319] eta: 0:09:09 lr: 2.9382458952273217e-05 loss: 0.0442 (0.0586) time: 2.6289 data: 0.0062 max mem: 33369 +Epoch: [17] [1120/1319] eta: 0:08:43 lr: 2.937341061670802e-05 loss: 0.0563 (0.0586) time: 2.6268 data: 0.0060 max mem: 33369 +Epoch: [17] [1130/1319] eta: 0:08:16 lr: 2.9364361971432715e-05 loss: 0.0563 (0.0586) time: 2.6125 data: 0.0059 max mem: 33369 +Epoch: [17] [1140/1319] eta: 0:07:50 lr: 2.9355313016330638e-05 loss: 0.0612 (0.0588) time: 2.6215 data: 0.0059 max mem: 33369 +Epoch: [17] [1150/1319] eta: 0:07:24 lr: 2.934626375128508e-05 loss: 0.0660 (0.0588) time: 2.6199 data: 0.0059 max mem: 33369 +Epoch: [17] [1160/1319] eta: 0:06:57 lr: 2.93372141761792e-05 loss: 0.0514 (0.0588) time: 2.6053 data: 0.0059 max mem: 33369 +Epoch: [17] [1170/1319] eta: 0:06:31 lr: 2.9328164290896108e-05 loss: 0.0485 (0.0588) time: 2.6139 data: 0.0059 max mem: 33369 +Epoch: [17] [1180/1319] eta: 0:06:05 lr: 2.9319114095318817e-05 loss: 0.0535 (0.0588) time: 2.6084 data: 0.0059 max mem: 33369 +Epoch: [17] [1190/1319] eta: 0:05:38 lr: 2.9310063589330256e-05 loss: 0.0574 (0.0587) time: 2.6238 data: 0.0059 max mem: 33369 +Epoch: [17] [1200/1319] eta: 0:05:12 lr: 2.9301012772813273e-05 loss: 0.0548 (0.0588) time: 2.6493 data: 0.0058 max mem: 33369 +Epoch: [17] [1210/1319] eta: 0:04:46 lr: 2.9291961645650624e-05 loss: 0.0530 (0.0588) time: 2.6483 data: 0.0059 max mem: 33369 +Epoch: [17] [1220/1319] eta: 0:04:20 lr: 2.9282910207724996e-05 loss: 0.0530 (0.0588) time: 2.6349 data: 0.0060 max mem: 33369 +Epoch: [17] [1230/1319] eta: 0:03:53 lr: 2.9273858458918974e-05 loss: 0.0574 (0.0588) time: 2.6287 data: 0.0060 max mem: 33369 +Epoch: [17] [1240/1319] eta: 0:03:27 lr: 2.9264806399115058e-05 loss: 0.0548 (0.0588) time: 2.6524 data: 0.0060 max mem: 33369 +Epoch: [17] [1250/1319] eta: 0:03:01 lr: 2.925575402819568e-05 loss: 0.0518 (0.0588) time: 2.6571 data: 0.0060 max mem: 33369 +Epoch: [17] [1260/1319] eta: 0:02:35 lr: 2.9246701346043183e-05 loss: 0.0535 (0.0587) time: 2.6127 data: 0.0059 max mem: 33369 +Epoch: [17] [1270/1319] eta: 0:02:08 lr: 2.9237648352539803e-05 loss: 0.0587 (0.0587) time: 2.6330 data: 0.0059 max mem: 33369 +Epoch: [17] [1280/1319] eta: 0:01:42 lr: 2.9228595047567713e-05 loss: 0.0631 (0.0589) time: 2.6667 data: 0.0061 max mem: 33369 +Epoch: [17] [1290/1319] eta: 0:01:16 lr: 2.9219541431009008e-05 loss: 0.0556 (0.0589) time: 2.6365 data: 0.0059 max mem: 33369 +Epoch: [17] [1300/1319] eta: 0:00:49 lr: 2.921048750274567e-05 loss: 0.0539 (0.0589) time: 2.6338 data: 0.0059 max mem: 33369 +Epoch: [17] [1310/1319] eta: 0:00:23 lr: 2.9201433262659623e-05 loss: 0.0518 (0.0588) time: 2.6310 data: 0.0060 max mem: 33369 +Epoch: [17] Total time: 0:57:47 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 1:52:18 time: 2.6190 data: 2.5391 max mem: 33369 +Test: [ 100/2573] eta: 0:04:00 time: 0.0718 data: 0.0011 max mem: 33369 +Test: [ 200/2573] eta: 0:03:23 time: 0.0735 data: 0.0011 max mem: 33369 +Test: [ 300/2573] eta: 0:03:04 time: 0.0751 data: 0.0011 max mem: 33369 +Test: [ 400/2573] eta: 0:02:52 time: 0.0752 data: 0.0011 max mem: 33369 +Test: [ 500/2573] eta: 0:02:41 time: 0.0736 data: 0.0011 max mem: 33369 +Test: [ 600/2573] eta: 0:02:32 time: 0.0737 data: 0.0011 max mem: 33369 +Test: [ 700/2573] eta: 0:02:24 time: 0.0738 data: 0.0011 max mem: 33369 +Test: [ 800/2573] eta: 0:02:16 time: 0.0771 data: 0.0011 max mem: 33369 +Test: [ 900/2573] eta: 0:02:08 time: 0.0739 data: 0.0011 max mem: 33369 +Test: [1000/2573] eta: 0:02:00 time: 0.0738 data: 0.0011 max mem: 33369 +Test: [1100/2573] eta: 0:01:52 time: 0.0741 data: 0.0011 max mem: 33369 +Test: [1200/2573] eta: 0:01:44 time: 0.0737 data: 0.0011 max mem: 33369 +Test: [1300/2573] eta: 0:01:36 time: 0.0738 data: 0.0011 max mem: 33369 +Test: [1400/2573] eta: 0:01:28 time: 0.0723 data: 0.0012 max mem: 33369 +Test: [1500/2573] eta: 0:01:21 time: 0.0738 data: 0.0011 max mem: 33369 +Test: [1600/2573] eta: 0:01:13 time: 0.0771 data: 0.0011 max mem: 33369 +Test: [1700/2573] eta: 0:01:05 time: 0.0722 data: 0.0011 max mem: 33369 +Test: [1800/2573] eta: 0:00:58 time: 0.0755 data: 0.0011 max mem: 33369 +Test: [1900/2573] eta: 0:00:50 time: 0.0722 data: 0.0011 max mem: 33369 +Test: [2000/2573] eta: 0:00:43 time: 0.0738 data: 0.0011 max mem: 33369 +Test: [2100/2573] eta: 0:00:35 time: 0.0755 data: 0.0011 max mem: 33369 +Test: [2200/2573] eta: 0:00:27 time: 0.0756 data: 0.0011 max mem: 33369 +Test: [2300/2573] eta: 0:00:20 time: 0.0754 data: 0.0011 max mem: 33369 +Test: [2400/2573] eta: 0:00:12 time: 0.0707 data: 0.0011 max mem: 33369 +Test: [2500/2573] eta: 0:00:05 time: 0.0737 data: 0.0011 max mem: 33369 +Test: Total time: 0:03:12 +Final results: +Mean IoU is 62.53 + + precision@0.5 = 70.08 + precision@0.6 = 64.28 + precision@0.7 = 56.88 + precision@0.8 = 45.20 + precision@0.9 = 21.65 + overall IoU = 60.19 + +Average object IoU 62.52687256213137 +Overall IoU 60.187252044677734 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [18] [ 0/1319] eta: 3:11:46 lr: 2.9193284179876086e-05 loss: 0.0402 (0.0402) time: 8.7234 data: 1.9193 max mem: 33369 +Epoch: [18] [ 10/1319] eta: 1:09:41 lr: 2.9184229347001237e-05 loss: 0.0520 (0.0582) time: 3.1941 data: 0.1805 max mem: 33369 +Epoch: [18] [ 20/1319] eta: 1:03:13 lr: 2.9175174201960736e-05 loss: 0.0523 (0.0561) time: 2.6303 data: 0.0063 max mem: 33369 +Epoch: [18] [ 30/1319] eta: 1:00:53 lr: 2.9166118744636155e-05 loss: 0.0530 (0.0566) time: 2.6364 data: 0.0061 max mem: 33369 +Epoch: [18] [ 40/1319] eta: 0:59:09 lr: 2.9157062974908988e-05 loss: 0.0468 (0.0550) time: 2.6221 data: 0.0063 max mem: 33369 +Epoch: [18] [ 50/1319] eta: 0:57:55 lr: 2.9148006892660646e-05 loss: 0.0436 (0.0541) time: 2.5906 data: 0.0064 max mem: 33369 +Epoch: [18] [ 60/1319] eta: 0:57:07 lr: 2.9138950497772444e-05 loss: 0.0436 (0.0543) time: 2.6158 data: 0.0061 max mem: 33369 +Epoch: [18] [ 70/1319] eta: 0:56:30 lr: 2.9129893790125616e-05 loss: 0.0406 (0.0530) time: 2.6525 data: 0.0060 max mem: 33369 +Epoch: [18] [ 80/1319] eta: 0:55:46 lr: 2.9120836769601318e-05 loss: 0.0474 (0.0532) time: 2.6361 data: 0.0061 max mem: 33369 +Epoch: [18] [ 90/1319] eta: 0:55:09 lr: 2.9111779436080605e-05 loss: 0.0508 (0.0531) time: 2.6167 data: 0.0062 max mem: 33369 +Epoch: [18] [ 100/1319] eta: 0:54:32 lr: 2.910272178944446e-05 loss: 0.0464 (0.0527) time: 2.6152 data: 0.0061 max mem: 33369 +Epoch: [18] [ 110/1319] eta: 0:54:02 lr: 2.9093663829573763e-05 loss: 0.0464 (0.0533) time: 2.6317 data: 0.0062 max mem: 33369 +Epoch: [18] [ 120/1319] eta: 0:53:30 lr: 2.9084605556349322e-05 loss: 0.0530 (0.0533) time: 2.6420 data: 0.0061 max mem: 33369 +Epoch: [18] [ 130/1319] eta: 0:53:00 lr: 2.9075546969651845e-05 loss: 0.0524 (0.0544) time: 2.6369 data: 0.0061 max mem: 33369 +Epoch: [18] [ 140/1319] eta: 0:52:32 lr: 2.906648806936197e-05 loss: 0.0534 (0.0548) time: 2.6541 data: 0.0061 max mem: 33369 +Epoch: [18] [ 150/1319] eta: 0:52:04 lr: 2.9057428855360237e-05 loss: 0.0543 (0.0558) time: 2.6555 data: 0.0058 max mem: 33369 +Epoch: [18] [ 160/1319] eta: 0:51:30 lr: 2.9048369327527098e-05 loss: 0.0502 (0.0554) time: 2.6132 data: 0.0060 max mem: 33369 +Epoch: [18] [ 170/1319] eta: 0:51:00 lr: 2.903930948574293e-05 loss: 0.0469 (0.0552) time: 2.5994 data: 0.0060 max mem: 33369 +Epoch: [18] [ 180/1319] eta: 0:50:29 lr: 2.9030249329888e-05 loss: 0.0534 (0.0557) time: 2.6067 data: 0.0060 max mem: 33369 +Epoch: [18] [ 190/1319] eta: 0:50:00 lr: 2.9021188859842518e-05 loss: 0.0536 (0.0555) time: 2.6048 data: 0.0061 max mem: 33369 +Epoch: [18] [ 200/1319] eta: 0:49:34 lr: 2.9012128075486583e-05 loss: 0.0541 (0.0557) time: 2.6463 data: 0.0060 max mem: 33369 +Epoch: [18] [ 210/1319] eta: 0:49:07 lr: 2.900306697670022e-05 loss: 0.0541 (0.0562) time: 2.6552 data: 0.0059 max mem: 33369 +Epoch: [18] [ 220/1319] eta: 0:48:38 lr: 2.8994005563363352e-05 loss: 0.0518 (0.0562) time: 2.6223 data: 0.0060 max mem: 33369 +Epoch: [18] [ 230/1319] eta: 0:48:09 lr: 2.8984943835355838e-05 loss: 0.0506 (0.0561) time: 2.6046 data: 0.0060 max mem: 33369 +Epoch: [18] [ 240/1319] eta: 0:47:40 lr: 2.8975881792557412e-05 loss: 0.0518 (0.0565) time: 2.6045 data: 0.0060 max mem: 33369 +Epoch: [18] [ 250/1319] eta: 0:47:11 lr: 2.8966819434847762e-05 loss: 0.0533 (0.0564) time: 2.5974 data: 0.0061 max mem: 33369 +Epoch: [18] [ 260/1319] eta: 0:46:44 lr: 2.8957756762106468e-05 loss: 0.0533 (0.0565) time: 2.6108 data: 0.0061 max mem: 33369 +Epoch: [18] [ 270/1319] eta: 0:46:17 lr: 2.8948693774213014e-05 loss: 0.0519 (0.0563) time: 2.6352 data: 0.0061 max mem: 33369 +Epoch: [18] [ 280/1319] eta: 0:45:50 lr: 2.8939630471046815e-05 loss: 0.0519 (0.0564) time: 2.6335 data: 0.0062 max mem: 33369 +Epoch: [18] [ 290/1319] eta: 0:45:21 lr: 2.893056685248718e-05 loss: 0.0496 (0.0562) time: 2.6124 data: 0.0062 max mem: 33369 +Epoch: [18] [ 300/1319] eta: 0:44:56 lr: 2.892150291841334e-05 loss: 0.0499 (0.0563) time: 2.6327 data: 0.0061 max mem: 33369 +Epoch: [18] [ 310/1319] eta: 0:44:28 lr: 2.891243866870445e-05 loss: 0.0556 (0.0564) time: 2.6410 data: 0.0060 max mem: 33369 +Epoch: [18] [ 320/1319] eta: 0:44:01 lr: 2.8903374103239537e-05 loss: 0.0569 (0.0565) time: 2.6121 data: 0.0062 max mem: 33369 +Epoch: [18] [ 330/1319] eta: 0:43:33 lr: 2.889430922189758e-05 loss: 0.0526 (0.0563) time: 2.6054 data: 0.0062 max mem: 33369 +Epoch: [18] [ 340/1319] eta: 0:43:08 lr: 2.8885244024557463e-05 loss: 0.0437 (0.0559) time: 2.6381 data: 0.0061 max mem: 33369 +Epoch: [18] [ 350/1319] eta: 0:42:40 lr: 2.8876178511097952e-05 loss: 0.0518 (0.0567) time: 2.6462 data: 0.0061 max mem: 33369 +Epoch: [18] [ 360/1319] eta: 0:42:13 lr: 2.886711268139775e-05 loss: 0.0460 (0.0563) time: 2.6149 data: 0.0061 max mem: 33369 +Epoch: [18] [ 370/1319] eta: 0:41:47 lr: 2.8858046535335475e-05 loss: 0.0441 (0.0564) time: 2.6313 data: 0.0061 max mem: 33369 +Epoch: [18] [ 380/1319] eta: 0:41:20 lr: 2.8848980072789644e-05 loss: 0.0446 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2.877643696440781e-05 loss: 0.0575 (0.0559) time: 2.6244 data: 0.0061 max mem: 33369 +Epoch: [18] [ 470/1319] eta: 0:37:21 lr: 2.876736764802861e-05 loss: 0.0586 (0.0558) time: 2.6557 data: 0.0060 max mem: 33369 +Epoch: [18] [ 480/1319] eta: 0:36:54 lr: 2.8758298013946133e-05 loss: 0.0439 (0.0559) time: 2.6323 data: 0.0060 max mem: 33369 +Epoch: [18] [ 490/1319] eta: 0:36:27 lr: 2.8749228062037915e-05 loss: 0.0469 (0.0561) time: 2.6012 data: 0.0060 max mem: 33369 +Epoch: [18] [ 500/1319] eta: 0:36:00 lr: 2.87401577921814e-05 loss: 0.0540 (0.0559) time: 2.5962 data: 0.0060 max mem: 33369 +Epoch: [18] [ 510/1319] eta: 0:35:33 lr: 2.8731087204253943e-05 loss: 0.0436 (0.0557) time: 2.5980 data: 0.0060 max mem: 33369 +Epoch: [18] [ 520/1319] eta: 0:35:07 lr: 2.8722016298132803e-05 loss: 0.0477 (0.0558) time: 2.6132 data: 0.0059 max mem: 33369 +Epoch: [18] [ 530/1319] eta: 0:34:39 lr: 2.8712945073695164e-05 loss: 0.0555 (0.0558) time: 2.5908 data: 0.0059 max mem: 33369 +Epoch: [18] [ 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data: 0.0058 max mem: 33369 +Epoch: [18] [ 700/1319] eta: 0:27:08 lr: 2.8558685436370514e-05 loss: 0.0429 (0.0561) time: 2.6156 data: 0.0058 max mem: 33369 +Epoch: [18] [ 710/1319] eta: 0:26:42 lr: 2.854960846112869e-05 loss: 0.0476 (0.0560) time: 2.6478 data: 0.0058 max mem: 33369 +Epoch: [18] [ 720/1319] eta: 0:26:15 lr: 2.8540531165219343e-05 loss: 0.0492 (0.0560) time: 2.6494 data: 0.0060 max mem: 33369 +Epoch: [18] [ 730/1319] eta: 0:25:49 lr: 2.8531453548517806e-05 loss: 0.0487 (0.0559) time: 2.6299 data: 0.0061 max mem: 33369 +Epoch: [18] [ 740/1319] eta: 0:25:23 lr: 2.8522375610899337e-05 loss: 0.0544 (0.0562) time: 2.6384 data: 0.0058 max mem: 33369 +Epoch: [18] [ 750/1319] eta: 0:24:57 lr: 2.8513297352239087e-05 loss: 0.0573 (0.0562) time: 2.6633 data: 0.0058 max mem: 33369 +Epoch: [18] [ 760/1319] eta: 0:24:30 lr: 2.850421877241213e-05 loss: 0.0556 (0.0565) time: 2.6295 data: 0.0060 max mem: 33369 +Epoch: [18] [ 770/1319] eta: 0:24:04 lr: 2.8495139871293436e-05 loss: 0.0546 (0.0565) time: 2.5876 data: 0.0060 max mem: 33369 +Epoch: [18] [ 780/1319] eta: 0:23:38 lr: 2.8486060648757875e-05 loss: 0.0513 (0.0566) time: 2.6289 data: 0.0059 max mem: 33369 +Epoch: [18] [ 790/1319] eta: 0:23:11 lr: 2.8476981104680245e-05 loss: 0.0533 (0.0568) time: 2.6373 data: 0.0061 max mem: 33369 +Epoch: [18] [ 800/1319] eta: 0:22:45 lr: 2.846790123893523e-05 loss: 0.0508 (0.0568) time: 2.5960 data: 0.0060 max mem: 33369 +Epoch: [18] [ 810/1319] eta: 0:22:18 lr: 2.8458821051397444e-05 loss: 0.0531 (0.0569) time: 2.5991 data: 0.0060 max mem: 33369 +Epoch: [18] [ 820/1319] eta: 0:21:52 lr: 2.844974054194138e-05 loss: 0.0580 (0.0569) time: 2.6474 data: 0.0061 max mem: 33369 +Epoch: [18] [ 830/1319] eta: 0:21:26 lr: 2.844065971044146e-05 loss: 0.0423 (0.0567) time: 2.6402 data: 0.0059 max mem: 33369 +Epoch: [18] [ 840/1319] eta: 0:20:59 lr: 2.8431578556772e-05 loss: 0.0460 (0.0569) time: 2.6180 data: 0.0059 max mem: 33369 +Epoch: [18] [ 850/1319] eta: 0:20:33 lr: 2.8422497080807237e-05 loss: 0.0460 (0.0568) time: 2.6275 data: 0.0059 max mem: 33369 +Epoch: [18] [ 860/1319] eta: 0:20:07 lr: 2.8413415282421285e-05 loss: 0.0474 (0.0567) time: 2.6357 data: 0.0059 max mem: 33369 +Epoch: [18] [ 870/1319] eta: 0:19:41 lr: 2.840433316148819e-05 loss: 0.0527 (0.0567) time: 2.6362 data: 0.0058 max mem: 33369 +Epoch: [18] [ 880/1319] eta: 0:19:14 lr: 2.8395250717881906e-05 loss: 0.0543 (0.0568) time: 2.6480 data: 0.0060 max mem: 33369 +Epoch: [18] [ 890/1319] eta: 0:18:48 lr: 2.8386167951476273e-05 loss: 0.0514 (0.0568) time: 2.6341 data: 0.0060 max mem: 33369 +Epoch: [18] [ 900/1319] eta: 0:18:22 lr: 2.8377084862145048e-05 loss: 0.0508 (0.0569) time: 2.6160 data: 0.0059 max mem: 33369 +Epoch: [18] [ 910/1319] eta: 0:17:55 lr: 2.8368001449761894e-05 loss: 0.0527 (0.0570) time: 2.6119 data: 0.0059 max mem: 33369 +Epoch: [18] [ 920/1319] eta: 0:17:29 lr: 2.8358917714200377e-05 loss: 0.0526 (0.0570) time: 2.6092 data: 0.0061 max mem: 33369 +Epoch: [18] [ 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33369 +Epoch: [18] [1010/1319] eta: 0:13:32 lr: 2.8277149530212353e-05 loss: 0.0483 (0.0570) time: 2.6238 data: 0.0059 max mem: 33369 +Epoch: [18] [1020/1319] eta: 0:13:05 lr: 2.8268062555892616e-05 loss: 0.0492 (0.0571) time: 2.6228 data: 0.0058 max mem: 33369 +Epoch: [18] [1030/1319] eta: 0:12:39 lr: 2.82589752569975e-05 loss: 0.0460 (0.0569) time: 2.6507 data: 0.0058 max mem: 33369 +Epoch: [18] [1040/1319] eta: 0:12:13 lr: 2.8249887633399437e-05 loss: 0.0456 (0.0569) time: 2.6723 data: 0.0059 max mem: 33369 +Epoch: [18] [1050/1319] eta: 0:11:47 lr: 2.8240799684970753e-05 loss: 0.0442 (0.0569) time: 2.6386 data: 0.0060 max mem: 33369 +Epoch: [18] [1060/1319] eta: 0:11:20 lr: 2.8231711411583693e-05 loss: 0.0483 (0.0569) time: 2.6267 data: 0.0060 max mem: 33369 +Epoch: [18] [1070/1319] eta: 0:10:54 lr: 2.8222622813110382e-05 loss: 0.0521 (0.0569) time: 2.6087 data: 0.0058 max mem: 33369 +Epoch: [18] [1080/1319] eta: 0:10:28 lr: 2.821353388942287e-05 loss: 0.0521 (0.0569) time: 2.6340 data: 0.0057 max mem: 33369 +Epoch: [18] [1090/1319] eta: 0:10:01 lr: 2.820444464039311e-05 loss: 0.0494 (0.0568) time: 2.6354 data: 0.0059 max mem: 33369 +Epoch: [18] [1100/1319] eta: 0:09:35 lr: 2.819535506589294e-05 loss: 0.0468 (0.0568) time: 2.6028 data: 0.0060 max mem: 33369 +Epoch: [18] [1110/1319] eta: 0:09:09 lr: 2.8186265165794125e-05 loss: 0.0469 (0.0568) time: 2.6331 data: 0.0060 max mem: 33369 +Epoch: [18] [1120/1319] eta: 0:08:43 lr: 2.817717493996831e-05 loss: 0.0559 (0.0568) time: 2.6562 data: 0.0060 max mem: 33369 +Epoch: [18] [1130/1319] eta: 0:08:16 lr: 2.816808438828707e-05 loss: 0.0559 (0.0569) time: 2.6434 data: 0.0059 max mem: 33369 +Epoch: [18] [1140/1319] eta: 0:07:50 lr: 2.8158993510621856e-05 loss: 0.0401 (0.0567) time: 2.6390 data: 0.0058 max mem: 33369 +Epoch: [18] [1150/1319] eta: 0:07:24 lr: 2.814990230684405e-05 loss: 0.0394 (0.0567) time: 2.6437 data: 0.0059 max mem: 33369 +Epoch: [18] [1160/1319] eta: 0:06:58 lr: 2.814081077682491e-05 loss: 0.0467 (0.0567) time: 2.6519 data: 0.0058 max mem: 33369 +Epoch: [18] [1170/1319] eta: 0:06:31 lr: 2.8131718920435623e-05 loss: 0.0530 (0.0567) time: 2.6322 data: 0.0059 max mem: 33369 +Epoch: [18] [1180/1319] eta: 0:06:05 lr: 2.812262673754726e-05 loss: 0.0545 (0.0567) time: 2.5993 data: 0.0060 max mem: 33369 +Epoch: [18] [1190/1319] eta: 0:05:39 lr: 2.8113534228030784e-05 loss: 0.0478 (0.0567) time: 2.5978 data: 0.0059 max mem: 33369 +Epoch: [18] [1200/1319] eta: 0:05:12 lr: 2.8104441391757102e-05 loss: 0.0422 (0.0567) time: 2.6177 data: 0.0060 max mem: 33369 +Epoch: [18] [1210/1319] eta: 0:04:46 lr: 2.809534822859698e-05 loss: 0.0426 (0.0566) time: 2.6322 data: 0.0060 max mem: 33369 +Epoch: [18] [1220/1319] eta: 0:04:20 lr: 2.8086254738421114e-05 loss: 0.0445 (0.0565) time: 2.6291 data: 0.0059 max mem: 33369 +Epoch: [18] [1230/1319] eta: 0:03:53 lr: 2.8077160921100087e-05 loss: 0.0445 (0.0565) time: 2.6135 data: 0.0058 max mem: 33369 +Epoch: [18] [1240/1319] eta: 0:03:27 lr: 2.8068066776504393e-05 loss: 0.0435 (0.0565) time: 2.6307 data: 0.0059 max mem: 33369 +Epoch: [18] [1250/1319] eta: 0:03:01 lr: 2.8058972304504428e-05 loss: 0.0538 (0.0565) time: 2.6596 data: 0.0060 max mem: 33369 +Epoch: [18] [1260/1319] eta: 0:02:35 lr: 2.8049877504970483e-05 loss: 0.0504 (0.0566) time: 2.6512 data: 0.0059 max mem: 33369 +Epoch: [18] [1270/1319] eta: 0:02:08 lr: 2.8040782377772763e-05 loss: 0.0496 (0.0565) time: 2.6368 data: 0.0059 max mem: 33369 +Epoch: [18] [1280/1319] eta: 0:01:42 lr: 2.803168692278136e-05 loss: 0.0523 (0.0565) time: 2.6352 data: 0.0058 max mem: 33369 +Epoch: [18] [1290/1319] eta: 0:01:16 lr: 2.8022591139866265e-05 loss: 0.0489 (0.0565) time: 2.6256 data: 0.0057 max mem: 33369 +Epoch: [18] [1300/1319] eta: 0:00:49 lr: 2.80134950288974e-05 loss: 0.0441 (0.0564) time: 2.6293 data: 0.0059 max mem: 33369 +Epoch: [18] [1310/1319] eta: 0:00:23 lr: 2.800439858974456e-05 loss: 0.0493 (0.0566) time: 2.6346 data: 0.0058 max mem: 33369 +Epoch: [18] Total time: 0:57:48 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 1:57:42 time: 2.7447 data: 2.5880 max mem: 33369 +Test: [ 100/2573] eta: 0:04:03 time: 0.0719 data: 0.0011 max mem: 33369 +Test: [ 200/2573] eta: 0:03:25 time: 0.0735 data: 0.0011 max mem: 33369 +Test: [ 300/2573] eta: 0:03:05 time: 0.0753 data: 0.0011 max mem: 33369 +Test: [ 400/2573] eta: 0:02:53 time: 0.0754 data: 0.0011 max mem: 33369 +Test: [ 500/2573] eta: 0:02:42 time: 0.0737 data: 0.0011 max mem: 33369 +Test: [ 600/2573] eta: 0:02:33 time: 0.0738 data: 0.0011 max mem: 33369 +Test: [ 700/2573] eta: 0:02:25 time: 0.0739 data: 0.0011 max mem: 33369 +Test: [ 800/2573] eta: 0:02:16 time: 0.0771 data: 0.0011 max mem: 33369 +Test: [ 900/2573] eta: 0:02:08 time: 0.0740 data: 0.0011 max mem: 33369 +Test: [1000/2573] eta: 0:02:00 time: 0.0739 data: 0.0011 max mem: 33369 +Test: [1100/2573] eta: 0:01:52 time: 0.0740 data: 0.0011 max mem: 33369 +Test: [1200/2573] eta: 0:01:44 time: 0.0740 data: 0.0011 max mem: 33369 +Test: [1300/2573] eta: 0:01:36 time: 0.0738 data: 0.0011 max mem: 33369 +Test: [1400/2573] eta: 0:01:29 time: 0.0723 data: 0.0011 max mem: 33369 +Test: [1500/2573] eta: 0:01:21 time: 0.0740 data: 0.0011 max mem: 33369 +Test: [1600/2573] eta: 0:01:13 time: 0.0774 data: 0.0011 max mem: 33369 +Test: [1700/2573] eta: 0:01:06 time: 0.0723 data: 0.0011 max mem: 33369 +Test: [1800/2573] eta: 0:00:58 time: 0.0757 data: 0.0011 max mem: 33369 +Test: [1900/2573] eta: 0:00:50 time: 0.0723 data: 0.0011 max mem: 33369 +Test: [2000/2573] eta: 0:00:43 time: 0.0741 data: 0.0011 max mem: 33369 +Test: [2100/2573] eta: 0:00:35 time: 0.0756 data: 0.0011 max mem: 33369 +Test: [2200/2573] eta: 0:00:28 time: 0.0757 data: 0.0011 max mem: 33369 +Test: [2300/2573] eta: 0:00:20 time: 0.0757 data: 0.0011 max mem: 33369 +Test: [2400/2573] eta: 0:00:12 time: 0.0708 data: 0.0011 max mem: 33369 +Test: [2500/2573] eta: 0:00:05 time: 0.0741 data: 0.0011 max mem: 33369 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: Total time: 0:03:13 +Final results: +Mean IoU is 62.55 + + precision@0.5 = 70.47 + precision@0.6 = 64.30 + precision@0.7 = 57.11 + precision@0.8 = 45.32 + precision@0.9 = 21.98 + overall IoU = 60.56 + +Average object IoU 62.552944063534945 +Overall IoU 60.55826187133789 +Better epoch: 18 + +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [19] [ 0/1319] eta: 1:27:54 lr: 2.7996211513802005e-05 loss: 0.0431 (0.0431) time: 3.9986 data: 1.2898 max mem: 33369 +Epoch: [19] [ 10/1319] eta: 0:59:23 lr: 2.7987114450740563e-05 loss: 0.0456 (0.0514) time: 2.7222 data: 0.1226 max mem: 33369 +Epoch: [19] [ 20/1319] eta: 0:57:59 lr: 2.7978017059117013e-05 loss: 0.0477 (0.0519) time: 2.6127 data: 0.0057 max mem: 33369 +Epoch: [19] [ 30/1319] eta: 0:57:12 lr: 2.7968919338800786e-05 loss: 0.0511 (0.0510) time: 2.6298 data: 0.0059 max mem: 33369 +Epoch: [19] [ 40/1319] eta: 0:56:36 lr: 2.7959821289661182e-05 loss: 0.0493 (0.0509) time: 2.6315 data: 0.0062 max mem: 33369 +Epoch: [19] [ 50/1319] eta: 0:56:02 lr: 2.795072291156743e-05 loss: 0.0464 (0.0501) time: 2.6305 data: 0.0061 max mem: 33369 +Epoch: [19] [ 60/1319] eta: 0:55:28 lr: 2.7941624204388656e-05 loss: 0.0520 (0.0507) time: 2.6189 data: 0.0063 max mem: 33369 +Epoch: [19] [ 70/1319] eta: 0:54:52 lr: 2.7932525167993873e-05 loss: 0.0471 (0.0495) time: 2.6015 data: 0.0063 max mem: 33369 +Epoch: [19] [ 80/1319] eta: 0:54:18 lr: 2.7923425802252002e-05 loss: 0.0400 (0.0487) time: 2.5868 data: 0.0062 max mem: 33369 +Epoch: [19] [ 90/1319] eta: 0:53:48 lr: 2.791432610703186e-05 loss: 0.0445 (0.0489) time: 2.5926 data: 0.0061 max mem: 33369 +Epoch: [19] [ 100/1319] eta: 0:53:22 lr: 2.790522608220219e-05 loss: 0.0456 (0.0495) time: 2.6183 data: 0.0062 max mem: 33369 +Epoch: [19] [ 110/1319] eta: 0:52:53 lr: 2.789612572763159e-05 loss: 0.0494 (0.0493) time: 2.6181 data: 0.0062 max mem: 33369 +Epoch: [19] [ 120/1319] eta: 0:52:29 lr: 2.7887025043188598e-05 loss: 0.0402 (0.0487) time: 2.6238 data: 0.0061 max mem: 33369 +Epoch: [19] [ 130/1319] eta: 0:52:01 lr: 2.7877924028741625e-05 loss: 0.0448 (0.0492) time: 2.6260 data: 0.0060 max mem: 33369 +Epoch: [19] [ 140/1319] eta: 0:51:35 lr: 2.7868822684159008e-05 loss: 0.0460 (0.0485) time: 2.6171 data: 0.0061 max mem: 33369 +Epoch: [19] [ 150/1319] eta: 0:51:09 lr: 2.7859721009308947e-05 loss: 0.0371 (0.0484) time: 2.6285 data: 0.0062 max mem: 33369 +Epoch: [19] [ 160/1319] eta: 0:50:42 lr: 2.7850619004059574e-05 loss: 0.0503 (0.0495) time: 2.6221 data: 0.0061 max mem: 33369 +Epoch: [19] [ 170/1319] eta: 0:50:13 lr: 2.7841516668278917e-05 loss: 0.0487 (0.0492) time: 2.6029 data: 0.0060 max mem: 33369 +Epoch: [19] [ 180/1319] eta: 0:49:49 lr: 2.7832414001834883e-05 loss: 0.0427 (0.0491) time: 2.6259 data: 0.0060 max mem: 33369 +Epoch: [19] [ 190/1319] eta: 0:49:24 lr: 2.782331100459529e-05 loss: 0.0449 (0.0490) time: 2.6449 data: 0.0060 max mem: 33369 +Epoch: [19] [ 200/1319] eta: 0:48:56 lr: 2.781420767642787e-05 loss: 0.0459 (0.0490) time: 2.6208 data: 0.0061 max mem: 33369 +Epoch: [19] [ 210/1319] eta: 0:48:31 lr: 2.7805104017200224e-05 loss: 0.0507 (0.0492) time: 2.6237 data: 0.0062 max mem: 33369 +Epoch: [19] [ 220/1319] eta: 0:48:08 lr: 2.779600002677987e-05 loss: 0.0510 (0.0492) time: 2.6679 data: 0.0061 max mem: 33369 +Epoch: [19] [ 230/1319] eta: 0:47:42 lr: 2.778689570503424e-05 loss: 0.0476 (0.0492) time: 2.6670 data: 0.0061 max mem: 33369 +Epoch: [19] [ 240/1319] eta: 0:47:18 lr: 2.7777791051830626e-05 loss: 0.0503 (0.0497) time: 2.6546 data: 0.0063 max mem: 33369 +Epoch: [19] [ 250/1319] eta: 0:46:50 lr: 2.7768686067036253e-05 loss: 0.0545 (0.0498) time: 2.6324 data: 0.0061 max mem: 33369 +Epoch: [19] [ 260/1319] eta: 0:46:23 lr: 2.775958075051822e-05 loss: 0.0502 (0.0500) time: 2.6017 data: 0.0061 max mem: 33369 +Epoch: [19] [ 270/1319] eta: 0:45:58 lr: 2.7750475102143547e-05 loss: 0.0495 (0.0500) time: 2.6306 data: 0.0060 max mem: 33369 +Epoch: [19] [ 280/1319] eta: 0:45:30 lr: 2.7741369121779126e-05 loss: 0.0475 (0.0501) time: 2.6250 data: 0.0059 max mem: 33369 +Epoch: [19] [ 290/1319] eta: 0:45:04 lr: 2.7732262809291776e-05 loss: 0.0495 (0.0502) time: 2.6129 data: 0.0061 max mem: 33369 +Epoch: [19] [ 300/1319] eta: 0:44:38 lr: 2.7723156164548194e-05 loss: 0.0464 (0.0502) time: 2.6283 data: 0.0062 max mem: 33369 +Epoch: [19] [ 310/1319] eta: 0:44:10 lr: 2.771404918741497e-05 loss: 0.0491 (0.0503) time: 2.6166 data: 0.0062 max mem: 33369 +Epoch: [19] [ 320/1319] eta: 0:43:43 lr: 2.7704941877758615e-05 loss: 0.0494 (0.0503) time: 2.5995 data: 0.0065 max mem: 33369 +Epoch: [19] [ 330/1319] eta: 0:43:17 lr: 2.7695834235445526e-05 loss: 0.0390 (0.0504) time: 2.6114 data: 0.0063 max mem: 33369 +Epoch: [19] [ 340/1319] eta: 0:42:51 lr: 2.7686726260341988e-05 loss: 0.0420 (0.0502) time: 2.6335 data: 0.0059 max mem: 33369 +Epoch: [19] [ 350/1319] eta: 0:42:25 lr: 2.7677617952314193e-05 loss: 0.0464 (0.0505) time: 2.6340 data: 0.0059 max mem: 33369 +Epoch: [19] [ 360/1319] eta: 0:41:58 lr: 2.7668509311228242e-05 loss: 0.0518 (0.0505) time: 2.6222 data: 0.0060 max mem: 33369 +Epoch: [19] [ 370/1319] eta: 0:41:32 lr: 2.7659400336950098e-05 loss: 0.0497 (0.0506) time: 2.6244 data: 0.0061 max mem: 33369 +Epoch: [19] [ 380/1319] eta: 0:41:07 lr: 2.765029102934566e-05 loss: 0.0453 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data: 0.0060 max mem: 33369 +Epoch: [19] [ 700/1319] eta: 0:27:06 lr: 2.735861638171675e-05 loss: 0.0501 (0.0539) time: 2.6161 data: 0.0061 max mem: 33369 +Epoch: [19] [ 710/1319] eta: 0:26:40 lr: 2.7349495998423098e-05 loss: 0.0526 (0.0540) time: 2.6186 data: 0.0060 max mem: 33369 +Epoch: [19] [ 720/1319] eta: 0:26:14 lr: 2.7340375277181003e-05 loss: 0.0507 (0.0538) time: 2.6230 data: 0.0058 max mem: 33369 +Epoch: [19] [ 730/1319] eta: 0:25:48 lr: 2.733125421785267e-05 loss: 0.0466 (0.0541) time: 2.6336 data: 0.0060 max mem: 33369 +Epoch: [19] [ 740/1319] eta: 0:25:21 lr: 2.7322132820300196e-05 loss: 0.0576 (0.0541) time: 2.6380 data: 0.0059 max mem: 33369 +Epoch: [19] [ 750/1319] eta: 0:24:55 lr: 2.731301108438557e-05 loss: 0.0576 (0.0543) time: 2.6159 data: 0.0059 max mem: 33369 +Epoch: [19] [ 760/1319] eta: 0:24:29 lr: 2.7303889009970667e-05 loss: 0.0486 (0.0542) time: 2.6272 data: 0.0058 max mem: 33369 +Epoch: [19] [ 770/1319] eta: 0:24:02 lr: 2.7294766596917266e-05 loss: 0.0483 (0.0544) time: 2.6346 data: 0.0061 max mem: 33369 +Epoch: [19] [ 780/1319] eta: 0:23:36 lr: 2.7285643845087027e-05 loss: 0.0511 (0.0545) time: 2.6003 data: 0.0063 max mem: 33369 +Epoch: [19] [ 790/1319] eta: 0:23:09 lr: 2.7276520754341512e-05 loss: 0.0503 (0.0546) time: 2.6003 data: 0.0061 max mem: 33369 +Epoch: [19] [ 800/1319] eta: 0:22:43 lr: 2.726739732454216e-05 loss: 0.0430 (0.0545) time: 2.6149 data: 0.0060 max mem: 33369 +Epoch: [19] [ 810/1319] eta: 0:22:17 lr: 2.7258273555550322e-05 loss: 0.0459 (0.0544) time: 2.6246 data: 0.0060 max mem: 33369 +Epoch: [19] [ 820/1319] eta: 0:21:51 lr: 2.7249149447227223e-05 loss: 0.0526 (0.0544) time: 2.6283 data: 0.0060 max mem: 33369 +Epoch: [19] [ 830/1319] eta: 0:21:24 lr: 2.7240024999433987e-05 loss: 0.0537 (0.0545) time: 2.6258 data: 0.0061 max mem: 33369 +Epoch: [19] [ 840/1319] eta: 0:20:58 lr: 2.723090021203163e-05 loss: 0.0506 (0.0545) time: 2.5978 data: 0.0062 max mem: 33369 +Epoch: [19] [ 850/1319] eta: 0:20:31 lr: 2.7221775084881062e-05 loss: 0.0462 (0.0544) time: 2.5921 data: 0.0061 max mem: 33369 +Epoch: [19] [ 860/1319] eta: 0:20:05 lr: 2.7212649617843082e-05 loss: 0.0418 (0.0544) time: 2.5968 data: 0.0060 max mem: 33369 +Epoch: [19] [ 870/1319] eta: 0:19:39 lr: 2.7203523810778376e-05 loss: 0.0476 (0.0543) time: 2.6052 data: 0.0061 max mem: 33369 +Epoch: [19] [ 880/1319] eta: 0:19:12 lr: 2.7194397663547522e-05 loss: 0.0480 (0.0543) time: 2.6363 data: 0.0060 max mem: 33369 +Epoch: [19] [ 890/1319] eta: 0:18:46 lr: 2.7185271176010996e-05 loss: 0.0505 (0.0544) time: 2.6211 data: 0.0059 max mem: 33369 +Epoch: [19] [ 900/1319] eta: 0:18:20 lr: 2.7176144348029154e-05 loss: 0.0466 (0.0543) time: 2.6225 data: 0.0059 max mem: 33369 +Epoch: [19] [ 910/1319] eta: 0:17:53 lr: 2.7167017179462245e-05 loss: 0.0457 (0.0543) time: 2.6289 data: 0.0059 max mem: 33369 +Epoch: [19] [ 920/1319] eta: 0:17:27 lr: 2.7157889670170428e-05 loss: 0.0526 (0.0543) time: 2.6318 data: 0.0058 max mem: 33369 +Epoch: [19] [ 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33369 +Epoch: [19] [1010/1319] eta: 0:13:30 lr: 2.7075726730791712e-05 loss: 0.0554 (0.0546) time: 2.6312 data: 0.0059 max mem: 33369 +Epoch: [19] [1020/1319] eta: 0:13:04 lr: 2.706659580653433e-05 loss: 0.0466 (0.0547) time: 2.6318 data: 0.0060 max mem: 33369 +Epoch: [19] [1030/1319] eta: 0:12:38 lr: 2.7057464540006328e-05 loss: 0.0466 (0.0548) time: 2.6323 data: 0.0061 max mem: 33369 +Epoch: [19] [1040/1319] eta: 0:12:12 lr: 2.7048332931066517e-05 loss: 0.0558 (0.0549) time: 2.6075 data: 0.0061 max mem: 33369 +Epoch: [19] [1050/1319] eta: 0:11:45 lr: 2.7039200979573614e-05 loss: 0.0569 (0.0550) time: 2.5965 data: 0.0060 max mem: 33369 +Epoch: [19] [1060/1319] eta: 0:11:19 lr: 2.7030068685386206e-05 loss: 0.0533 (0.0549) time: 2.5797 data: 0.0059 max mem: 33369 +Epoch: [19] [1070/1319] eta: 0:10:53 lr: 2.7020936048362782e-05 loss: 0.0501 (0.0550) time: 2.5732 data: 0.0057 max mem: 33369 +Epoch: [19] [1080/1319] eta: 0:10:26 lr: 2.7011803068361714e-05 loss: 0.0557 (0.0550) time: 2.6178 data: 0.0058 max mem: 33369 +Epoch: [19] [1090/1319] eta: 0:10:00 lr: 2.700266974524126e-05 loss: 0.0575 (0.0552) time: 2.6394 data: 0.0059 max mem: 33369 +Epoch: [19] [1100/1319] eta: 0:09:34 lr: 2.699353607885957e-05 loss: 0.0659 (0.0552) time: 2.6226 data: 0.0059 max mem: 33369 +Epoch: [19] [1110/1319] eta: 0:09:08 lr: 2.6984402069074687e-05 loss: 0.0492 (0.0552) time: 2.6092 data: 0.0059 max mem: 33369 +Epoch: [19] [1120/1319] eta: 0:08:42 lr: 2.6975267715744523e-05 loss: 0.0505 (0.0552) time: 2.6314 data: 0.0059 max mem: 33369 +Epoch: [19] [1130/1319] eta: 0:08:15 lr: 2.6966133018726902e-05 loss: 0.0505 (0.0551) time: 2.6505 data: 0.0058 max mem: 33369 +Epoch: [19] [1140/1319] eta: 0:07:49 lr: 2.6956997977879505e-05 loss: 0.0520 (0.0552) time: 2.6347 data: 0.0058 max mem: 33369 +Epoch: [19] [1150/1319] eta: 0:07:23 lr: 2.6947862593059943e-05 loss: 0.0499 (0.0552) time: 2.6194 data: 0.0059 max mem: 33369 +Epoch: [19] [1160/1319] eta: 0:06:57 lr: 2.6938726864125667e-05 loss: 0.0463 (0.0551) time: 2.6174 data: 0.0060 max mem: 33369 +Epoch: [19] [1170/1319] eta: 0:06:30 lr: 2.6929590790934063e-05 loss: 0.0509 (0.0551) time: 2.6294 data: 0.0060 max mem: 33369 +Epoch: [19] [1180/1319] eta: 0:06:04 lr: 2.6920454373342357e-05 loss: 0.0491 (0.0551) time: 2.6105 data: 0.0060 max mem: 33369 +Epoch: [19] [1190/1319] eta: 0:05:38 lr: 2.6911317611207703e-05 loss: 0.0493 (0.0551) time: 2.6206 data: 0.0059 max mem: 33369 +Epoch: [19] [1200/1319] eta: 0:05:12 lr: 2.6902180504387114e-05 loss: 0.0588 (0.0551) time: 2.6465 data: 0.0058 max mem: 33369 +Epoch: [19] [1210/1319] eta: 0:04:45 lr: 2.689304305273751e-05 loss: 0.0536 (0.0551) time: 2.6329 data: 0.0060 max mem: 33369 +Epoch: [19] [1220/1319] eta: 0:04:19 lr: 2.6883905256115667e-05 loss: 0.0522 (0.0552) time: 2.6484 data: 0.0060 max mem: 33369 +Epoch: [19] [1230/1319] eta: 0:03:53 lr: 2.687476711437828e-05 loss: 0.0485 (0.0552) time: 2.6510 data: 0.0058 max mem: 33369 +Epoch: [19] [1240/1319] eta: 0:03:27 lr: 2.6865628627381928e-05 loss: 0.0481 (0.0554) time: 2.6134 data: 0.0059 max mem: 33369 +Epoch: [19] [1250/1319] eta: 0:03:01 lr: 2.6856489794983043e-05 loss: 0.0479 (0.0553) time: 2.6352 data: 0.0059 max mem: 33369 +Epoch: [19] [1260/1319] eta: 0:02:34 lr: 2.6847350617037976e-05 loss: 0.0439 (0.0553) time: 2.6589 data: 0.0059 max mem: 33369 +Epoch: [19] [1270/1319] eta: 0:02:08 lr: 2.683821109340296e-05 loss: 0.0543 (0.0553) time: 2.6450 data: 0.0059 max mem: 33369 +Epoch: [19] [1280/1319] eta: 0:01:42 lr: 2.68290712239341e-05 loss: 0.0543 (0.0553) time: 2.6427 data: 0.0059 max mem: 33369 +Epoch: [19] [1290/1319] eta: 0:01:16 lr: 2.681993100848739e-05 loss: 0.0535 (0.0554) time: 2.6573 data: 0.0059 max mem: 33369 +Epoch: [19] [1300/1319] eta: 0:00:49 lr: 2.6810790446918727e-05 loss: 0.0539 (0.0554) time: 2.6540 data: 0.0059 max mem: 33369 +Epoch: [19] [1310/1319] eta: 0:00:23 lr: 2.680164953908387e-05 loss: 0.0542 (0.0554) time: 2.6294 data: 0.0060 max mem: 33369 +Epoch: [19] Total time: 0:57:43 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 2:08:34 time: 2.9984 data: 2.9188 max mem: 33369 +Test: [ 100/2573] eta: 0:04:09 time: 0.0716 data: 0.0011 max mem: 33369 +Test: [ 200/2573] eta: 0:03:27 time: 0.0734 data: 0.0011 max mem: 33369 +Test: [ 300/2573] eta: 0:03:07 time: 0.0750 data: 0.0011 max mem: 33369 +Test: [ 400/2573] eta: 0:02:54 time: 0.0752 data: 0.0011 max mem: 33369 +Test: [ 500/2573] eta: 0:02:43 time: 0.0739 data: 0.0012 max mem: 33369 +Test: [ 600/2573] eta: 0:02:34 time: 0.0737 data: 0.0011 max mem: 33369 +Test: [ 700/2573] eta: 0:02:25 time: 0.0739 data: 0.0011 max mem: 33369 +Test: [ 800/2573] eta: 0:02:17 time: 0.0772 data: 0.0011 max mem: 33369 +Test: [ 900/2573] eta: 0:02:09 time: 0.0739 data: 0.0011 max mem: 33369 +Test: [1000/2573] eta: 0:02:00 time: 0.0738 data: 0.0011 max mem: 33369 +Test: [1100/2573] eta: 0:01:52 time: 0.0740 data: 0.0011 max mem: 33369 +Test: [1200/2573] eta: 0:01:44 time: 0.0738 data: 0.0011 max mem: 33369 +Test: [1300/2573] eta: 0:01:37 time: 0.0738 data: 0.0011 max mem: 33369 +Test: [1400/2573] eta: 0:01:29 time: 0.0723 data: 0.0011 max mem: 33369 +Test: [1500/2573] eta: 0:01:21 time: 0.0738 data: 0.0011 max mem: 33369 +Test: [1600/2573] eta: 0:01:13 time: 0.0772 data: 0.0011 max mem: 33369 +Test: [1700/2573] eta: 0:01:06 time: 0.0722 data: 0.0011 max mem: 33369 +Test: [1800/2573] eta: 0:00:58 time: 0.0755 data: 0.0011 max mem: 33369 +Test: [1900/2573] eta: 0:00:50 time: 0.0722 data: 0.0011 max mem: 33369 +Test: [2000/2573] eta: 0:00:43 time: 0.0738 data: 0.0011 max mem: 33369 +Test: [2100/2573] eta: 0:00:35 time: 0.0754 data: 0.0011 max mem: 33369 +Test: [2200/2573] eta: 0:00:28 time: 0.0754 data: 0.0011 max mem: 33369 +Test: [2300/2573] eta: 0:00:20 time: 0.0753 data: 0.0011 max mem: 33369 +Test: [2400/2573] eta: 0:00:12 time: 0.0703 data: 0.0011 max mem: 33369 +Test: [2500/2573] eta: 0:00:05 time: 0.0738 data: 0.0011 max mem: 33369 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: Total time: 0:03:13 +Final results: +Mean IoU is 62.88 + + precision@0.5 = 70.34 + precision@0.6 = 65.22 + precision@0.7 = 57.50 + precision@0.8 = 45.53 + precision@0.9 = 21.85 + overall IoU = 60.15 + +Average object IoU 62.88081603622807 +Overall IoU 60.153018951416016 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [20] [ 0/1319] eta: 3:05:49 lr: 2.6793422425855603e-05 loss: 0.0390 (0.0390) time: 8.4527 data: 1.2663 max mem: 33369 +Epoch: [20] [ 10/1319] eta: 1:08:47 lr: 2.678428085971722e-05 loss: 0.0422 (0.0421) time: 3.1529 data: 0.1210 max mem: 33369 +Epoch: [20] [ 20/1319] eta: 1:03:07 lr: 2.6775138946893718e-05 loss: 0.0445 (0.0529) time: 2.6385 data: 0.0061 max mem: 33369 +Epoch: [20] [ 30/1319] eta: 1:00:43 lr: 2.6765996687240426e-05 loss: 0.0479 (0.0544) time: 2.6466 data: 0.0060 max mem: 33369 +Epoch: [20] [ 40/1319] eta: 0:59:07 lr: 2.675685408061254e-05 loss: 0.0451 (0.0535) time: 2.6254 data: 0.0062 max mem: 33369 +Epoch: [20] [ 50/1319] eta: 0:58:10 lr: 2.6747711126865168e-05 loss: 0.0452 (0.0538) time: 2.6328 data: 0.0062 max mem: 33369 +Epoch: [20] [ 60/1319] eta: 0:57:19 lr: 2.6738567825853273e-05 loss: 0.0509 (0.0564) time: 2.6459 data: 0.0061 max mem: 33369 +Epoch: [20] [ 70/1319] eta: 0:56:32 lr: 2.6729424177431713e-05 loss: 0.0469 (0.0553) time: 2.6287 data: 0.0062 max mem: 33369 +Epoch: [20] [ 80/1319] eta: 0:55:48 lr: 2.6720280181455227e-05 loss: 0.0456 (0.0545) time: 2.6125 data: 0.0063 max mem: 33369 +Epoch: [20] [ 90/1319] eta: 0:55:10 lr: 2.671113583777845e-05 loss: 0.0466 (0.0539) time: 2.6152 data: 0.0062 max mem: 33369 +Epoch: [20] [ 100/1319] eta: 0:54:32 lr: 2.670199114625589e-05 loss: 0.0465 (0.0535) time: 2.6126 data: 0.0059 max mem: 33369 +Epoch: [20] [ 110/1319] eta: 0:53:54 lr: 2.6692846106741932e-05 loss: 0.0464 (0.0526) time: 2.5894 data: 0.0061 max mem: 33369 +Epoch: [20] [ 120/1319] eta: 0:53:21 lr: 2.668370071909087e-05 loss: 0.0469 (0.0525) time: 2.5949 data: 0.0061 max mem: 33369 +Epoch: [20] [ 130/1319] eta: 0:52:50 lr: 2.6674554983156852e-05 loss: 0.0491 (0.0523) time: 2.6191 data: 0.0061 max mem: 33369 +Epoch: [20] [ 140/1319] eta: 0:52:18 lr: 2.666540889879393e-05 loss: 0.0482 (0.0520) time: 2.6165 data: 0.0062 max mem: 33369 +Epoch: [20] [ 150/1319] eta: 0:51:50 lr: 2.6656262465856026e-05 loss: 0.0483 (0.0531) time: 2.6215 data: 0.0061 max mem: 33369 +Epoch: [20] [ 160/1319] eta: 0:51:19 lr: 2.6647115684196954e-05 loss: 0.0463 (0.0528) time: 2.6209 data: 0.0059 max mem: 33369 +Epoch: [20] [ 170/1319] eta: 0:50:50 lr: 2.663796855367041e-05 loss: 0.0460 (0.0524) time: 2.6154 data: 0.0060 max mem: 33369 +Epoch: [20] [ 180/1319] eta: 0:50:25 lr: 2.662882107412996e-05 loss: 0.0460 (0.0522) time: 2.6460 data: 0.0061 max mem: 33369 +Epoch: [20] [ 190/1319] eta: 0:49:57 lr: 2.661967324542908e-05 loss: 0.0464 (0.0521) time: 2.6527 data: 0.0059 max mem: 33369 +Epoch: [20] [ 200/1319] eta: 0:49:28 lr: 2.6610525067421092e-05 loss: 0.0481 (0.0520) time: 2.6277 data: 0.0059 max mem: 33369 +Epoch: [20] [ 210/1319] eta: 0:49:03 lr: 2.6601376539959238e-05 loss: 0.0483 (0.0518) time: 2.6496 data: 0.0061 max mem: 33369 +Epoch: [20] [ 220/1319] eta: 0:48:36 lr: 2.6592227662896617e-05 loss: 0.0501 (0.0518) time: 2.6587 data: 0.0061 max mem: 33369 +Epoch: [20] [ 230/1319] eta: 0:48:07 lr: 2.658307843608621e-05 loss: 0.0451 (0.0514) time: 2.6172 data: 0.0061 max mem: 33369 +Epoch: [20] [ 240/1319] eta: 0:47:38 lr: 2.65739288593809e-05 loss: 0.0405 (0.0519) time: 2.6019 data: 0.0061 max mem: 33369 +Epoch: [20] [ 250/1319] eta: 0:47:10 lr: 2.6564778932633426e-05 loss: 0.0454 (0.0517) time: 2.6130 data: 0.0061 max mem: 33369 +Epoch: [20] [ 260/1319] eta: 0:46:43 lr: 2.655562865569643e-05 loss: 0.0454 (0.0520) time: 2.6284 data: 0.0062 max mem: 33369 +Epoch: [20] [ 270/1319] eta: 0:46:16 lr: 2.654647802842242e-05 loss: 0.0440 (0.0520) time: 2.6352 data: 0.0062 max mem: 33369 +Epoch: [20] [ 280/1319] eta: 0:45:50 lr: 2.6537327050663813e-05 loss: 0.0440 (0.0523) time: 2.6354 data: 0.0060 max mem: 33369 +Epoch: [20] [ 290/1319] eta: 0:45:23 lr: 2.6528175722272857e-05 loss: 0.0532 (0.0523) time: 2.6375 data: 0.0059 max mem: 33369 +Epoch: [20] [ 300/1319] eta: 0:44:54 lr: 2.6519024043101733e-05 loss: 0.0527 (0.0534) time: 2.6093 data: 0.0061 max mem: 33369 +Epoch: [20] [ 310/1319] eta: 0:44:27 lr: 2.6509872013002462e-05 loss: 0.0481 (0.0533) time: 2.5969 data: 0.0063 max mem: 33369 +Epoch: [20] [ 320/1319] eta: 0:44:00 lr: 2.6500719631826982e-05 loss: 0.0379 (0.0528) time: 2.6219 data: 0.0062 max mem: 33369 +Epoch: [20] [ 330/1319] eta: 0:43:32 lr: 2.649156689942709e-05 loss: 0.0359 (0.0525) time: 2.6126 data: 0.0060 max mem: 33369 +Epoch: [20] [ 340/1319] eta: 0:43:05 lr: 2.648241381565446e-05 loss: 0.0394 (0.0521) time: 2.6099 data: 0.0062 max mem: 33369 +Epoch: [20] [ 350/1319] eta: 0:42:40 lr: 2.6473260380360663e-05 loss: 0.0447 (0.0526) time: 2.6480 data: 0.0063 max mem: 33369 +Epoch: [20] [ 360/1319] eta: 0:42:12 lr: 2.6464106593397137e-05 loss: 0.0449 (0.0524) time: 2.6388 data: 0.0063 max mem: 33369 +Epoch: [20] [ 370/1319] eta: 0:41:44 lr: 2.6454952454615202e-05 loss: 0.0449 (0.0523) time: 2.5901 data: 0.0061 max mem: 33369 +Epoch: [20] [ 380/1319] eta: 0:41:17 lr: 2.6445797963866064e-05 loss: 0.0428 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2.637254934915819e-05 loss: 0.0456 (0.0521) time: 2.6026 data: 0.0061 max mem: 33369 +Epoch: [20] [ 470/1319] eta: 0:37:13 lr: 2.6363391683988447e-05 loss: 0.0480 (0.0519) time: 2.6121 data: 0.0060 max mem: 33369 +Epoch: [20] [ 480/1319] eta: 0:36:47 lr: 2.6354233665356892e-05 loss: 0.0425 (0.0519) time: 2.6374 data: 0.0060 max mem: 33369 +Epoch: [20] [ 490/1319] eta: 0:36:21 lr: 2.6345075293113398e-05 loss: 0.0410 (0.0517) time: 2.6475 data: 0.0062 max mem: 33369 +Epoch: [20] [ 500/1319] eta: 0:35:55 lr: 2.633591656710771e-05 loss: 0.0410 (0.0516) time: 2.6281 data: 0.0060 max mem: 33369 +Epoch: [20] [ 510/1319] eta: 0:35:28 lr: 2.6326757487189457e-05 loss: 0.0426 (0.0517) time: 2.6192 data: 0.0059 max mem: 33369 +Epoch: [20] [ 520/1319] eta: 0:35:01 lr: 2.6317598053208148e-05 loss: 0.0479 (0.0518) time: 2.6070 data: 0.0061 max mem: 33369 +Epoch: [20] [ 530/1319] eta: 0:34:35 lr: 2.6308438265013168e-05 loss: 0.0438 (0.0517) time: 2.6097 data: 0.0060 max mem: 33369 +Epoch: [20] [ 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data: 0.0059 max mem: 33369 +Epoch: [20] [ 700/1319] eta: 0:27:08 lr: 2.615266752446517e-05 loss: 0.0429 (0.0519) time: 2.6329 data: 0.0058 max mem: 33369 +Epoch: [20] [ 710/1319] eta: 0:26:41 lr: 2.614350133452863e-05 loss: 0.0429 (0.0518) time: 2.6318 data: 0.0058 max mem: 33369 +Epoch: [20] [ 720/1319] eta: 0:26:14 lr: 2.6134334787493302e-05 loss: 0.0378 (0.0518) time: 2.5975 data: 0.0059 max mem: 33369 +Epoch: [20] [ 730/1319] eta: 0:25:48 lr: 2.6125167883206104e-05 loss: 0.0436 (0.0518) time: 2.6121 data: 0.0060 max mem: 33369 +Epoch: [20] [ 740/1319] eta: 0:25:22 lr: 2.61160006215138e-05 loss: 0.0489 (0.0520) time: 2.6400 data: 0.0060 max mem: 33369 +Epoch: [20] [ 750/1319] eta: 0:24:56 lr: 2.610683300226307e-05 loss: 0.0461 (0.0519) time: 2.6257 data: 0.0060 max mem: 33369 +Epoch: [20] [ 760/1319] eta: 0:24:29 lr: 2.6097665025300437e-05 loss: 0.0437 (0.0518) time: 2.6049 data: 0.0059 max mem: 33369 +Epoch: [20] [ 770/1319] eta: 0:24:03 lr: 2.608849669047231e-05 loss: 0.0418 (0.0518) time: 2.6077 data: 0.0058 max mem: 33369 +Epoch: [20] [ 780/1319] eta: 0:23:36 lr: 2.6079327997624963e-05 loss: 0.0459 (0.0518) time: 2.6011 data: 0.0060 max mem: 33369 +Epoch: [20] [ 790/1319] eta: 0:23:10 lr: 2.6070158946604555e-05 loss: 0.0495 (0.0518) time: 2.6146 data: 0.0061 max mem: 33369 +Epoch: [20] [ 800/1319] eta: 0:22:44 lr: 2.6060989537257118e-05 loss: 0.0470 (0.0518) time: 2.6317 data: 0.0061 max mem: 33369 +Epoch: [20] [ 810/1319] eta: 0:22:17 lr: 2.6051819769428553e-05 loss: 0.0429 (0.0518) time: 2.6379 data: 0.0061 max mem: 33369 +Epoch: [20] [ 820/1319] eta: 0:21:51 lr: 2.604264964296463e-05 loss: 0.0460 (0.0519) time: 2.6435 data: 0.0059 max mem: 33369 +Epoch: [20] [ 830/1319] eta: 0:21:25 lr: 2.6033479157711e-05 loss: 0.0452 (0.0518) time: 2.6317 data: 0.0060 max mem: 33369 +Epoch: [20] [ 840/1319] eta: 0:20:59 lr: 2.6024308313513185e-05 loss: 0.0428 (0.0518) time: 2.6202 data: 0.0060 max mem: 33369 +Epoch: [20] [ 850/1319] eta: 0:20:32 lr: 2.601513711021658e-05 loss: 0.0451 (0.0518) time: 2.6170 data: 0.0061 max mem: 33369 +Epoch: [20] [ 860/1319] eta: 0:20:06 lr: 2.6005965547666454e-05 loss: 0.0417 (0.0517) time: 2.6085 data: 0.0062 max mem: 33369 +Epoch: [20] [ 870/1319] eta: 0:19:39 lr: 2.599679362570795e-05 loss: 0.0395 (0.0517) time: 2.6067 data: 0.0060 max mem: 33369 +Epoch: [20] [ 880/1319] eta: 0:19:13 lr: 2.598762134418607e-05 loss: 0.0429 (0.0516) time: 2.6214 data: 0.0060 max mem: 33369 +Epoch: [20] [ 890/1319] eta: 0:18:47 lr: 2.5978448702945707e-05 loss: 0.0400 (0.0515) time: 2.6438 data: 0.0061 max mem: 33369 +Epoch: [20] [ 900/1319] eta: 0:18:21 lr: 2.596927570183162e-05 loss: 0.0381 (0.0514) time: 2.6224 data: 0.0060 max mem: 33369 +Epoch: [20] [ 910/1319] eta: 0:17:54 lr: 2.5960102340688436e-05 loss: 0.0420 (0.0514) time: 2.5824 data: 0.0058 max mem: 33369 +Epoch: [20] [ 920/1319] eta: 0:17:28 lr: 2.5950928619360655e-05 loss: 0.0479 (0.0514) time: 2.5928 data: 0.0058 max mem: 33369 +Epoch: [20] [ 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33369 +Epoch: [20] [1010/1319] eta: 0:13:31 lr: 2.586834889338287e-05 loss: 0.0421 (0.0512) time: 2.6045 data: 0.0059 max mem: 33369 +Epoch: [20] [1020/1319] eta: 0:13:05 lr: 2.58591715616284e-05 loss: 0.0470 (0.0512) time: 2.5796 data: 0.0059 max mem: 33369 +Epoch: [20] [1030/1319] eta: 0:12:39 lr: 2.584999386797035e-05 loss: 0.0382 (0.0511) time: 2.6275 data: 0.0061 max mem: 33369 +Epoch: [20] [1040/1319] eta: 0:12:12 lr: 2.5840815812251663e-05 loss: 0.0382 (0.0511) time: 2.6402 data: 0.0061 max mem: 33369 +Epoch: [20] [1050/1319] eta: 0:11:46 lr: 2.583163739431517e-05 loss: 0.0454 (0.0513) time: 2.6083 data: 0.0060 max mem: 33369 +Epoch: [20] [1060/1319] eta: 0:11:20 lr: 2.582245861400355e-05 loss: 0.0443 (0.0512) time: 2.6103 data: 0.0060 max mem: 33369 +Epoch: [20] [1070/1319] eta: 0:10:53 lr: 2.5813279471159375e-05 loss: 0.0392 (0.0511) time: 2.6237 data: 0.0059 max mem: 33369 +Epoch: [20] [1080/1319] eta: 0:10:27 lr: 2.5804099965625085e-05 loss: 0.0423 (0.0512) time: 2.6071 data: 0.0059 max mem: 33369 +Epoch: [20] [1090/1319] eta: 0:10:01 lr: 2.5794920097242954e-05 loss: 0.0429 (0.0511) time: 2.6185 data: 0.0061 max mem: 33369 +Epoch: [20] [1100/1319] eta: 0:09:35 lr: 2.5785739865855164e-05 loss: 0.0407 (0.0511) time: 2.6214 data: 0.0061 max mem: 33369 +Epoch: [20] [1110/1319] eta: 0:09:08 lr: 2.5776559271303753e-05 loss: 0.0477 (0.0510) time: 2.6141 data: 0.0060 max mem: 33369 +Epoch: [20] [1120/1319] eta: 0:08:42 lr: 2.5767378313430623e-05 loss: 0.0477 (0.0510) time: 2.6390 data: 0.0059 max mem: 33369 +Epoch: [20] [1130/1319] eta: 0:08:16 lr: 2.5758196992077554e-05 loss: 0.0500 (0.0511) time: 2.6222 data: 0.0062 max mem: 33369 +Epoch: [20] [1140/1319] eta: 0:07:49 lr: 2.574901530708619e-05 loss: 0.0551 (0.0512) time: 2.5991 data: 0.0060 max mem: 33369 +Epoch: [20] [1150/1319] eta: 0:07:23 lr: 2.573983325829803e-05 loss: 0.0571 (0.0513) time: 2.6177 data: 0.0059 max mem: 33369 +Epoch: [20] [1160/1319] eta: 0:06:57 lr: 2.573065084555446e-05 loss: 0.0552 (0.0513) time: 2.6382 data: 0.0060 max mem: 33369 +Epoch: [20] [1170/1319] eta: 0:06:31 lr: 2.572146806869673e-05 loss: 0.0456 (0.0513) time: 2.6482 data: 0.0060 max mem: 33369 +Epoch: [20] [1180/1319] eta: 0:06:05 lr: 2.5712284927565954e-05 loss: 0.0464 (0.0512) time: 2.6398 data: 0.0059 max mem: 33369 +Epoch: [20] [1190/1319] eta: 0:05:38 lr: 2.5703101422003118e-05 loss: 0.0480 (0.0512) time: 2.6218 data: 0.0058 max mem: 33369 +Epoch: [20] [1200/1319] eta: 0:05:12 lr: 2.569391755184906e-05 loss: 0.0480 (0.0512) time: 2.5990 data: 0.0059 max mem: 33369 +Epoch: [20] [1210/1319] eta: 0:04:46 lr: 2.5684733316944508e-05 loss: 0.0410 (0.0512) time: 2.6179 data: 0.0059 max mem: 33369 +Epoch: [20] [1220/1319] eta: 0:04:19 lr: 2.5675548717130043e-05 loss: 0.0442 (0.0512) time: 2.6286 data: 0.0059 max mem: 33369 +Epoch: [20] [1230/1319] eta: 0:03:53 lr: 2.5666363752246116e-05 loss: 0.0416 (0.0512) time: 2.6032 data: 0.0060 max mem: 33369 +Epoch: [20] [1240/1319] eta: 0:03:27 lr: 2.5657178422133044e-05 loss: 0.0537 (0.0515) time: 2.5756 data: 0.0060 max mem: 33369 +Epoch: [20] [1250/1319] eta: 0:03:01 lr: 2.564799272663101e-05 loss: 0.0613 (0.0515) time: 2.5844 data: 0.0060 max mem: 33369 +Epoch: [20] [1260/1319] eta: 0:02:34 lr: 2.5638806665580068e-05 loss: 0.0482 (0.0515) time: 2.6201 data: 0.0061 max mem: 33369 +Epoch: [20] [1270/1319] eta: 0:02:08 lr: 2.5629620238820134e-05 loss: 0.0467 (0.0515) time: 2.6238 data: 0.0060 max mem: 33369 +Epoch: [20] [1280/1319] eta: 0:01:42 lr: 2.562043344619099e-05 loss: 0.0464 (0.0515) time: 2.6292 data: 0.0059 max mem: 33369 +Epoch: [20] [1290/1319] eta: 0:01:16 lr: 2.5611246287532285e-05 loss: 0.0450 (0.0514) time: 2.6389 data: 0.0060 max mem: 33369 +Epoch: [20] [1300/1319] eta: 0:00:49 lr: 2.560205876268355e-05 loss: 0.0489 (0.0514) time: 2.6309 data: 0.0059 max mem: 33369 +Epoch: [20] [1310/1319] eta: 0:00:23 lr: 2.5592870871484144e-05 loss: 0.0486 (0.0514) time: 2.6324 data: 0.0059 max mem: 33369 +Epoch: [20] Total time: 0:57:42 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 1:52:16 time: 2.6183 data: 2.4842 max mem: 33369 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 100/2573] eta: 0:04:03 time: 0.0718 data: 0.0011 max mem: 33369 +Test: [ 200/2573] eta: 0:03:25 time: 0.0736 data: 0.0011 max mem: 33369 +Test: [ 300/2573] eta: 0:03:05 time: 0.0753 data: 0.0011 max mem: 33369 +Test: [ 400/2573] eta: 0:02:53 time: 0.0755 data: 0.0011 max mem: 33369 +Test: [ 500/2573] eta: 0:02:42 time: 0.0739 data: 0.0011 max mem: 33369 +Test: [ 600/2573] eta: 0:02:33 time: 0.0739 data: 0.0012 max mem: 33369 +Test: [ 700/2573] eta: 0:02:25 time: 0.0740 data: 0.0011 max mem: 33369 +Test: [ 800/2573] eta: 0:02:17 time: 0.0773 data: 0.0011 max mem: 33369 +Test: [ 900/2573] eta: 0:02:08 time: 0.0740 data: 0.0012 max mem: 33369 +Test: [1000/2573] eta: 0:02:00 time: 0.0740 data: 0.0011 max mem: 33369 +Test: [1100/2573] eta: 0:01:52 time: 0.0740 data: 0.0012 max mem: 33369 +Test: [1200/2573] eta: 0:01:44 time: 0.0739 data: 0.0011 max mem: 33369 +Test: [1300/2573] eta: 0:01:37 time: 0.0740 data: 0.0011 max mem: 33369 +Test: [1400/2573] eta: 0:01:29 time: 0.0723 data: 0.0011 max mem: 33369 +Test: [1500/2573] eta: 0:01:21 time: 0.0740 data: 0.0011 max mem: 33369 +Test: [1600/2573] eta: 0:01:13 time: 0.0773 data: 0.0011 max mem: 33369 +Test: [1700/2573] eta: 0:01:06 time: 0.0724 data: 0.0011 max mem: 33369 +Test: [1800/2573] eta: 0:00:58 time: 0.0756 data: 0.0011 max mem: 33369 +Test: [1900/2573] eta: 0:00:50 time: 0.0723 data: 0.0011 max mem: 33369 +Test: [2000/2573] eta: 0:00:43 time: 0.0739 data: 0.0011 max mem: 33369 +Test: [2100/2573] eta: 0:00:35 time: 0.0755 data: 0.0011 max mem: 33369 +Test: [2200/2573] eta: 0:00:28 time: 0.0757 data: 0.0011 max mem: 33369 +Test: [2300/2573] eta: 0:00:20 time: 0.0757 data: 0.0011 max mem: 33369 +Test: [2400/2573] eta: 0:00:12 time: 0.0707 data: 0.0011 max mem: 33369 +Test: [2500/2573] eta: 0:00:05 time: 0.0740 data: 0.0011 max mem: 33369 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: Total time: 0:03:13 +Final results: +Mean IoU is 62.61 + + precision@0.5 = 70.14 + precision@0.6 = 64.97 + precision@0.7 = 57.76 + precision@0.8 = 46.92 + precision@0.9 = 22.98 + overall IoU = 60.55 + +Average object IoU 62.607467018242104 +Overall IoU 60.546566009521484 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [21] [ 0/1319] eta: 3:00:58 lr: 2.5584601456041995e-05 loss: 0.0531 (0.0531) time: 8.2324 data: 1.8860 max mem: 33369 +Epoch: [21] [ 10/1319] eta: 1:08:52 lr: 2.5575412868333344e-05 loss: 0.0476 (0.0468) time: 3.1572 data: 0.1765 max mem: 33369 +Epoch: [21] [ 20/1319] eta: 1:02:45 lr: 2.5566223913807464e-05 loss: 0.0430 (0.0455) time: 2.6323 data: 0.0053 max mem: 33369 +Epoch: [21] [ 30/1319] eta: 1:00:13 lr: 2.5557034592303224e-05 loss: 0.0400 (0.0461) time: 2.6089 data: 0.0056 max mem: 33369 +Epoch: [21] [ 40/1319] eta: 0:58:50 lr: 2.5547844903659336e-05 loss: 0.0412 (0.0464) time: 2.6155 data: 0.0061 max mem: 33369 +Epoch: [21] [ 50/1319] eta: 0:57:48 lr: 2.5538654847714393e-05 loss: 0.0412 (0.0466) time: 2.6236 data: 0.0060 max mem: 33369 +Epoch: [21] [ 60/1319] eta: 0:56:56 lr: 2.552946442430683e-05 loss: 0.0409 (0.0466) time: 2.6177 data: 0.0061 max mem: 33369 +Epoch: [21] [ 70/1319] eta: 0:56:11 lr: 2.552027363327497e-05 loss: 0.0484 (0.0485) time: 2.6150 data: 0.0062 max mem: 33369 +Epoch: [21] [ 80/1319] eta: 0:55:29 lr: 2.551108247445699e-05 loss: 0.0462 (0.0483) time: 2.6049 data: 0.0062 max mem: 33369 +Epoch: [21] [ 90/1319] eta: 0:54:46 lr: 2.5501890947690927e-05 loss: 0.0441 (0.0480) time: 2.5835 data: 0.0062 max mem: 33369 +Epoch: [21] [ 100/1319] eta: 0:54:14 lr: 2.5492699052814688e-05 loss: 0.0488 (0.0486) time: 2.6026 data: 0.0061 max mem: 33369 +Epoch: [21] [ 110/1319] eta: 0:53:42 lr: 2.548350678966605e-05 loss: 0.0488 (0.0487) time: 2.6256 data: 0.0060 max mem: 33369 +Epoch: [21] [ 120/1319] eta: 0:53:08 lr: 2.547431415808263e-05 loss: 0.0383 (0.0481) time: 2.6035 data: 0.0060 max mem: 33369 +Epoch: [21] [ 130/1319] eta: 0:52:37 lr: 2.5465121157901932e-05 loss: 0.0383 (0.0476) time: 2.6013 data: 0.0061 max mem: 33369 +Epoch: [21] [ 140/1319] eta: 0:52:03 lr: 2.5455927788961316e-05 loss: 0.0430 (0.0476) time: 2.5918 data: 0.0059 max mem: 33369 +Epoch: [21] [ 150/1319] eta: 0:51:38 lr: 2.5446734051098e-05 loss: 0.0397 (0.0473) time: 2.6150 data: 0.0059 max mem: 33369 +Epoch: [21] [ 160/1319] eta: 0:51:07 lr: 2.5437539944149068e-05 loss: 0.0468 (0.0476) time: 2.6261 data: 0.0061 max mem: 33369 +Epoch: [21] [ 170/1319] eta: 0:50:39 lr: 2.542834546795147e-05 loss: 0.0474 (0.0477) time: 2.6086 data: 0.0061 max mem: 33369 +Epoch: [21] [ 180/1319] eta: 0:50:09 lr: 2.5419150622342014e-05 loss: 0.0472 (0.0480) time: 2.6044 data: 0.0059 max mem: 33369 +Epoch: [21] [ 190/1319] eta: 0:49:40 lr: 2.5409955407157366e-05 loss: 0.0447 (0.0476) time: 2.5940 data: 0.0060 max mem: 33369 +Epoch: [21] [ 200/1319] eta: 0:49:13 lr: 2.5400759822234066e-05 loss: 0.0361 (0.0472) time: 2.6144 data: 0.0062 max mem: 33369 +Epoch: [21] [ 210/1319] eta: 0:48:44 lr: 2.539156386740852e-05 loss: 0.0390 (0.0472) time: 2.6100 data: 0.0062 max mem: 33369 +Epoch: [21] [ 220/1319] eta: 0:48:19 lr: 2.538236754251696e-05 loss: 0.0390 (0.0472) time: 2.6272 data: 0.0061 max mem: 33369 +Epoch: [21] [ 230/1319] eta: 0:47:51 lr: 2.5373170847395516e-05 loss: 0.0366 (0.0471) time: 2.6342 data: 0.0062 max mem: 33369 +Epoch: [21] [ 240/1319] eta: 0:47:23 lr: 2.536397378188018e-05 loss: 0.0426 (0.0474) time: 2.6063 data: 0.0062 max mem: 33369 +Epoch: [21] [ 250/1319] eta: 0:46:57 lr: 2.5354776345806775e-05 loss: 0.0452 (0.0474) time: 2.6171 data: 0.0061 max mem: 33369 +Epoch: [21] [ 260/1319] eta: 0:46:30 lr: 2.534557853901102e-05 loss: 0.0448 (0.0474) time: 2.6285 data: 0.0065 max mem: 33369 +Epoch: [21] [ 270/1319] eta: 0:46:04 lr: 2.5336380361328465e-05 loss: 0.0463 (0.0474) time: 2.6403 data: 0.0063 max mem: 33369 +Epoch: [21] [ 280/1319] eta: 0:45:36 lr: 2.532718181259454e-05 loss: 0.0449 (0.0475) time: 2.6171 data: 0.0058 max mem: 33369 +Epoch: [21] [ 290/1319] eta: 0:45:10 lr: 2.531798289264453e-05 loss: 0.0469 (0.0477) time: 2.6070 data: 0.0058 max mem: 33369 +Epoch: [21] [ 300/1319] eta: 0:44:43 lr: 2.5308783601313586e-05 loss: 0.0469 (0.0477) time: 2.6279 data: 0.0059 max mem: 33369 +Epoch: [21] [ 310/1319] eta: 0:44:16 lr: 2.52995839384367e-05 loss: 0.0378 (0.0473) time: 2.6157 data: 0.0061 max mem: 33369 +Epoch: [21] [ 320/1319] eta: 0:43:50 lr: 2.5290383903848747e-05 loss: 0.0387 (0.0478) time: 2.6269 data: 0.0062 max mem: 33369 +Epoch: [21] [ 330/1319] eta: 0:43:23 lr: 2.5281183497384443e-05 loss: 0.0425 (0.0476) time: 2.6311 data: 0.0062 max mem: 33369 +Epoch: [21] [ 340/1319] eta: 0:42:57 lr: 2.5271982718878386e-05 loss: 0.0425 (0.0480) time: 2.6239 data: 0.0061 max mem: 33369 +Epoch: [21] [ 350/1319] eta: 0:42:29 lr: 2.5262781568165e-05 loss: 0.0482 (0.0480) time: 2.6105 data: 0.0059 max mem: 33369 +Epoch: [21] [ 360/1319] eta: 0:42:02 lr: 2.5253580045078606e-05 loss: 0.0436 (0.0481) time: 2.6036 data: 0.0059 max mem: 33369 +Epoch: [21] [ 370/1319] eta: 0:41:36 lr: 2.5244378149453368e-05 loss: 0.0420 (0.0482) time: 2.6290 data: 0.0061 max mem: 33369 +Epoch: [21] [ 380/1319] eta: 0:41:09 lr: 2.5235175881123296e-05 loss: 0.0398 (0.0479) time: 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2.4728472240253183e-05 loss: 0.0473 (0.0492) time: 2.6487 data: 0.0061 max mem: 33369 +Epoch: [21] [ 940/1319] eta: 0:16:35 lr: 2.4719248831116334e-05 loss: 0.0450 (0.0492) time: 2.6475 data: 0.0060 max mem: 33369 +Epoch: [21] [ 950/1319] eta: 0:16:09 lr: 2.4710025039574813e-05 loss: 0.0398 (0.0492) time: 2.6287 data: 0.0059 max mem: 33369 +Epoch: [21] [ 960/1319] eta: 0:15:43 lr: 2.4700800865454158e-05 loss: 0.0405 (0.0492) time: 2.6367 data: 0.0060 max mem: 33369 +Epoch: [21] [ 970/1319] eta: 0:15:16 lr: 2.469157630857973e-05 loss: 0.0417 (0.0492) time: 2.6314 data: 0.0061 max mem: 33369 +Epoch: [21] [ 980/1319] eta: 0:14:50 lr: 2.4682351368776758e-05 loss: 0.0412 (0.0491) time: 2.6326 data: 0.0060 max mem: 33369 +Epoch: [21] [ 990/1319] eta: 0:14:24 lr: 2.467312604587031e-05 loss: 0.0359 (0.0491) time: 2.6311 data: 0.0059 max mem: 33369 +Epoch: [21] [1000/1319] eta: 0:13:58 lr: 2.4663900339685314e-05 loss: 0.0386 (0.0491) time: 2.6502 data: 0.0059 max mem: 33369 +Epoch: [21] 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mem: 33369 +Epoch: [21] [1090/1319] eta: 0:10:01 lr: 2.4580851707520996e-05 loss: 0.0379 (0.0491) time: 2.6474 data: 0.0062 max mem: 33369 +Epoch: [21] [1100/1319] eta: 0:09:35 lr: 2.457162215888721e-05 loss: 0.0373 (0.0490) time: 2.6516 data: 0.0059 max mem: 33369 +Epoch: [21] [1110/1319] eta: 0:09:09 lr: 2.456239222503884e-05 loss: 0.0382 (0.0490) time: 2.6419 data: 0.0059 max mem: 33369 +Epoch: [21] [1120/1319] eta: 0:08:42 lr: 2.455316190579896e-05 loss: 0.0435 (0.0490) time: 2.6353 data: 0.0058 max mem: 33369 +Epoch: [21] [1130/1319] eta: 0:08:16 lr: 2.4543931200990468e-05 loss: 0.0453 (0.0490) time: 2.6317 data: 0.0059 max mem: 33369 +Epoch: [21] [1140/1319] eta: 0:07:50 lr: 2.4534700110436136e-05 loss: 0.0453 (0.0490) time: 2.6332 data: 0.0059 max mem: 33369 +Epoch: [21] [1150/1319] eta: 0:07:24 lr: 2.452546863395857e-05 loss: 0.0447 (0.0490) time: 2.6312 data: 0.0061 max mem: 33369 +Epoch: [21] [1160/1319] eta: 0:06:57 lr: 2.451623677138022e-05 loss: 0.0465 (0.0492) time: 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0.0435 (0.0494) time: 2.6352 data: 0.0058 max mem: 33369 +Epoch: [21] [1250/1319] eta: 0:03:01 lr: 2.4433132604266355e-05 loss: 0.0441 (0.0494) time: 2.6452 data: 0.0058 max mem: 33369 +Epoch: [21] [1260/1319] eta: 0:02:35 lr: 2.442389687088041e-05 loss: 0.0459 (0.0494) time: 2.6433 data: 0.0058 max mem: 33369 +Epoch: [21] [1270/1319] eta: 0:02:08 lr: 2.441466074943027e-05 loss: 0.0420 (0.0494) time: 2.6320 data: 0.0057 max mem: 33369 +Epoch: [21] [1280/1319] eta: 0:01:42 lr: 2.440542423973651e-05 loss: 0.0420 (0.0493) time: 2.6279 data: 0.0060 max mem: 33369 +Epoch: [21] [1290/1319] eta: 0:01:16 lr: 2.439618734161953e-05 loss: 0.0427 (0.0493) time: 2.6286 data: 0.0059 max mem: 33369 +Epoch: [21] [1300/1319] eta: 0:00:49 lr: 2.4386950054899575e-05 loss: 0.0427 (0.0493) time: 2.6108 data: 0.0056 max mem: 33369 +Epoch: [21] [1310/1319] eta: 0:00:23 lr: 2.4377712379396728e-05 loss: 0.0452 (0.0493) time: 2.6106 data: 0.0056 max mem: 33369 +Epoch: [21] Total time: 0:57:45 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 1:48:43 time: 2.5355 data: 2.4257 max mem: 33369 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 100/2573] eta: 0:03:58 time: 0.0715 data: 0.0011 max mem: 33369 +Test: [ 200/2573] eta: 0:03:22 time: 0.0733 data: 0.0011 max mem: 33369 +Test: [ 300/2573] eta: 0:03:04 time: 0.0751 data: 0.0011 max mem: 33369 +Test: [ 400/2573] eta: 0:02:51 time: 0.0751 data: 0.0011 max mem: 33369 +Test: [ 500/2573] eta: 0:02:41 time: 0.0736 data: 0.0011 max mem: 33369 +Test: [ 600/2573] eta: 0:02:32 time: 0.0738 data: 0.0011 max mem: 33369 +Test: [ 700/2573] eta: 0:02:24 time: 0.0738 data: 0.0011 max mem: 33369 +Test: [ 800/2573] eta: 0:02:16 time: 0.0771 data: 0.0011 max mem: 33369 +Test: [ 900/2573] eta: 0:02:08 time: 0.0738 data: 0.0011 max mem: 33369 +Test: [1000/2573] eta: 0:02:00 time: 0.0737 data: 0.0011 max mem: 33369 +Test: [1100/2573] eta: 0:01:52 time: 0.0738 data: 0.0011 max mem: 33369 +Test: [1200/2573] eta: 0:01:44 time: 0.0738 data: 0.0011 max mem: 33369 +Test: [1300/2573] eta: 0:01:36 time: 0.0738 data: 0.0011 max mem: 33369 +Test: [1400/2573] eta: 0:01:28 time: 0.0722 data: 0.0011 max mem: 33369 +Test: [1500/2573] eta: 0:01:21 time: 0.0739 data: 0.0011 max mem: 33369 +Test: [1600/2573] eta: 0:01:13 time: 0.0771 data: 0.0011 max mem: 33369 +Test: [1700/2573] eta: 0:01:05 time: 0.0720 data: 0.0011 max mem: 33369 +Test: [1800/2573] eta: 0:00:58 time: 0.0754 data: 0.0011 max mem: 33369 +Test: [1900/2573] eta: 0:00:50 time: 0.0722 data: 0.0011 max mem: 33369 +Test: [2000/2573] eta: 0:00:42 time: 0.0738 data: 0.0011 max mem: 33369 +Test: [2100/2573] eta: 0:00:35 time: 0.0754 data: 0.0011 max mem: 33369 +Test: [2200/2573] eta: 0:00:27 time: 0.0754 data: 0.0011 max mem: 33369 +Test: [2300/2573] eta: 0:00:20 time: 0.0757 data: 0.0012 max mem: 33369 +Test: [2400/2573] eta: 0:00:12 time: 0.0706 data: 0.0011 max mem: 33369 +Test: [2500/2573] eta: 0:00:05 time: 0.0739 data: 0.0012 max mem: 33369 +Test: Total time: 0:03:12 +Final results: +Mean IoU is 63.14 + + precision@0.5 = 70.87 + precision@0.6 = 65.28 + precision@0.7 = 58.76 + precision@0.8 = 47.26 + precision@0.9 = 23.24 + overall IoU = 61.07 + +Average object IoU 63.1365803843174 +Overall IoU 61.071563720703125 +Better epoch: 21 + +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [22] [ 0/1319] eta: 1:24:48 lr: 2.4369398138885975e-05 loss: 0.0568 (0.0568) time: 3.8579 data: 1.1978 max mem: 33369 +Epoch: [22] [ 10/1319] eta: 1:00:21 lr: 2.436015972419942e-05 loss: 0.0431 (0.0477) time: 2.7667 data: 0.1144 max mem: 33369 +Epoch: [22] [ 20/1319] eta: 0:58:39 lr: 2.4350920920207323e-05 loss: 0.0427 (0.0485) time: 2.6517 data: 0.0057 max mem: 33369 +Epoch: [22] [ 30/1319] eta: 0:57:34 lr: 2.4341681726729162e-05 loss: 0.0453 (0.0486) time: 2.6326 data: 0.0058 max mem: 33369 +Epoch: [22] [ 40/1319] eta: 0:56:52 lr: 2.4332442143584247e-05 loss: 0.0483 (0.0486) time: 2.6249 data: 0.0064 max mem: 33369 +Epoch: [22] [ 50/1319] eta: 0:56:06 lr: 2.4323202170591704e-05 loss: 0.0494 (0.0527) time: 2.6104 data: 0.0064 max mem: 33369 +Epoch: [22] [ 60/1319] eta: 0:55:32 lr: 2.4313961807570534e-05 loss: 0.0533 (0.0520) time: 2.6027 data: 0.0061 max mem: 33369 +Epoch: [22] [ 70/1319] eta: 0:55:00 lr: 2.430472105433956e-05 loss: 0.0397 (0.0506) time: 2.6176 data: 0.0061 max mem: 33369 +Epoch: [22] [ 80/1319] eta: 0:54:29 lr: 2.4295479910717442e-05 loss: 0.0408 (0.0499) time: 2.6157 data: 0.0063 max mem: 33369 +Epoch: [22] [ 90/1319] eta: 0:53:57 lr: 2.4286238376522685e-05 loss: 0.0382 (0.0486) time: 2.6032 data: 0.0062 max mem: 33369 +Epoch: [22] [ 100/1319] eta: 0:53:30 lr: 2.4276996451573638e-05 loss: 0.0355 (0.0481) time: 2.6136 data: 0.0061 max mem: 33369 +Epoch: [22] [ 110/1319] eta: 0:53:04 lr: 2.426775413568847e-05 loss: 0.0407 (0.0476) time: 2.6322 data: 0.0060 max mem: 33369 +Epoch: [22] [ 120/1319] eta: 0:52:33 lr: 2.4258511428685206e-05 loss: 0.0410 (0.0477) time: 2.6084 data: 0.0062 max mem: 33369 +Epoch: [22] [ 130/1319] eta: 0:52:07 lr: 2.4249268330381702e-05 loss: 0.0366 (0.0470) time: 2.6106 data: 0.0061 max mem: 33369 +Epoch: [22] [ 140/1319] eta: 0:51:37 lr: 2.4240024840595657e-05 loss: 0.0396 (0.0470) time: 2.6118 data: 0.0061 max mem: 33369 +Epoch: [22] [ 150/1319] eta: 0:51:11 lr: 2.4230780959144606e-05 loss: 0.0422 (0.0467) time: 2.6107 data: 0.0063 max mem: 33369 +Epoch: [22] [ 160/1319] eta: 0:50:42 lr: 2.4221536685845908e-05 loss: 0.0428 (0.0468) time: 2.6127 data: 0.0064 max mem: 33369 +Epoch: [22] [ 170/1319] eta: 0:50:14 lr: 2.421229202051678e-05 loss: 0.0428 (0.0464) time: 2.5918 data: 0.0062 max mem: 33369 +Epoch: [22] [ 180/1319] eta: 0:49:45 lr: 2.420304696297427e-05 loss: 0.0409 (0.0462) time: 2.5892 data: 0.0062 max mem: 33369 +Epoch: [22] [ 190/1319] eta: 0:49:21 lr: 2.419380151303525e-05 loss: 0.0372 (0.0462) time: 2.6159 data: 0.0064 max mem: 33369 +Epoch: [22] [ 200/1319] eta: 0:48:54 lr: 2.418455567051645e-05 loss: 0.0374 (0.0463) time: 2.6281 data: 0.0062 max mem: 33369 +Epoch: [22] [ 210/1319] eta: 0:48:31 lr: 2.417530943523442e-05 loss: 0.0437 (0.0463) time: 2.6495 data: 0.0059 max mem: 33369 +Epoch: [22] [ 220/1319] eta: 0:48:03 lr: 2.416606280700555e-05 loss: 0.0449 (0.0462) time: 2.6380 data: 0.0059 max mem: 33369 +Epoch: [22] [ 230/1319] eta: 0:47:38 lr: 2.4156815785646067e-05 loss: 0.0439 (0.0462) time: 2.6198 data: 0.0061 max mem: 33369 +Epoch: [22] [ 240/1319] eta: 0:47:11 lr: 2.414756837097204e-05 loss: 0.0467 (0.0463) time: 2.6264 data: 0.0060 max mem: 33369 +Epoch: [22] [ 250/1319] eta: 0:46:44 lr: 2.4138320562799363e-05 loss: 0.0452 (0.0463) time: 2.6093 data: 0.0060 max mem: 33369 +Epoch: [22] [ 260/1319] eta: 0:46:18 lr: 2.412907236094378e-05 loss: 0.0463 (0.0464) time: 2.6286 data: 0.0060 max mem: 33369 +Epoch: [22] [ 270/1319] eta: 0:45:52 lr: 2.411982376522085e-05 loss: 0.0468 (0.0464) time: 2.6297 data: 0.0060 max mem: 33369 +Epoch: [22] [ 280/1319] eta: 0:45:25 lr: 2.411057477544598e-05 loss: 0.0461 (0.0466) time: 2.6109 data: 0.0061 max mem: 33369 +Epoch: [22] [ 290/1319] eta: 0:45:00 lr: 2.4101325391434414e-05 loss: 0.0461 (0.0468) time: 2.6237 data: 0.0063 max mem: 33369 +Epoch: [22] [ 300/1319] eta: 0:44:33 lr: 2.4092075613001218e-05 loss: 0.0480 (0.0471) time: 2.6314 data: 0.0061 max mem: 33369 +Epoch: [22] [ 310/1319] eta: 0:44:08 lr: 2.4082825439961318e-05 loss: 0.0416 (0.0467) time: 2.6390 data: 0.0060 max mem: 33369 +Epoch: [22] [ 320/1319] eta: 0:43:43 lr: 2.4073574872129434e-05 loss: 0.0416 (0.0469) time: 2.6574 data: 0.0061 max mem: 33369 +Epoch: [22] [ 330/1319] eta: 0:43:16 lr: 2.4064323909320154e-05 loss: 0.0529 (0.0472) time: 2.6354 data: 0.0061 max mem: 33369 +Epoch: [22] [ 340/1319] eta: 0:42:50 lr: 2.405507255134789e-05 loss: 0.0542 (0.0474) time: 2.6290 data: 0.0062 max mem: 33369 +Epoch: [22] [ 350/1319] eta: 0:42:24 lr: 2.404582079802688e-05 loss: 0.0521 (0.0475) time: 2.6273 data: 0.0063 max mem: 33369 +Epoch: [22] [ 360/1319] eta: 0:41:58 lr: 2.4036568649171213e-05 loss: 0.0470 (0.0474) time: 2.6336 data: 0.0062 max mem: 33369 +Epoch: [22] [ 370/1319] eta: 0:41:32 lr: 2.402731610459478e-05 loss: 0.0469 (0.0474) time: 2.6327 data: 0.0060 max mem: 33369 +Epoch: [22] [ 380/1319] eta: 0:41:05 lr: 2.401806316411133e-05 loss: 0.0421 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(0.0474) time: 2.5999 data: 0.0059 max mem: 33369 +Epoch: [22] [ 780/1319] eta: 0:23:32 lr: 2.364761874190731e-05 loss: 0.0395 (0.0475) time: 2.6160 data: 0.0061 max mem: 33369 +Epoch: [22] [ 790/1319] eta: 0:23:06 lr: 2.363834940677452e-05 loss: 0.0408 (0.0476) time: 2.6425 data: 0.0062 max mem: 33369 +Epoch: [22] [ 800/1319] eta: 0:22:40 lr: 2.3629079667757912e-05 loss: 0.0515 (0.0477) time: 2.6183 data: 0.0061 max mem: 33369 +Epoch: [22] [ 810/1319] eta: 0:22:14 lr: 2.361980952466383e-05 loss: 0.0531 (0.0478) time: 2.6088 data: 0.0059 max mem: 33369 +Epoch: [22] [ 820/1319] eta: 0:21:47 lr: 2.3610538977298433e-05 loss: 0.0440 (0.0477) time: 2.6257 data: 0.0057 max mem: 33369 +Epoch: [22] [ 830/1319] eta: 0:21:21 lr: 2.3601268025467702e-05 loss: 0.0385 (0.0476) time: 2.6228 data: 0.0058 max mem: 33369 +Epoch: [22] [ 840/1319] eta: 0:20:55 lr: 2.3591996668977443e-05 loss: 0.0371 (0.0475) time: 2.6199 data: 0.0059 max mem: 33369 +Epoch: [22] [ 850/1319] eta: 0:20:29 lr: 2.3582724907633285e-05 loss: 0.0371 (0.0474) time: 2.6085 data: 0.0059 max mem: 33369 +Epoch: [22] [ 860/1319] eta: 0:20:03 lr: 2.3573452741240666e-05 loss: 0.0374 (0.0475) time: 2.6252 data: 0.0061 max mem: 33369 +Epoch: [22] [ 870/1319] eta: 0:19:36 lr: 2.3564180169604865e-05 loss: 0.0471 (0.0476) time: 2.6331 data: 0.0062 max mem: 33369 +Epoch: [22] [ 880/1319] eta: 0:19:10 lr: 2.3554907192530968e-05 loss: 0.0485 (0.0477) time: 2.6122 data: 0.0061 max mem: 33369 +Epoch: [22] [ 890/1319] eta: 0:18:44 lr: 2.3545633809823888e-05 loss: 0.0544 (0.0478) time: 2.6237 data: 0.0059 max mem: 33369 +Epoch: [22] [ 900/1319] eta: 0:18:18 lr: 2.353636002128836e-05 loss: 0.0437 (0.0478) time: 2.6357 data: 0.0060 max mem: 33369 +Epoch: [22] [ 910/1319] eta: 0:17:52 lr: 2.3527085826728933e-05 loss: 0.0399 (0.0477) time: 2.6303 data: 0.0060 max mem: 33369 +Epoch: [22] [ 920/1319] eta: 0:17:25 lr: 2.351781122594998e-05 loss: 0.0405 (0.0479) time: 2.6194 data: 0.0059 max mem: 33369 +Epoch: [22] [ 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33369 +Epoch: [22] [1010/1319] eta: 0:13:29 lr: 2.3434321506693e-05 loss: 0.0423 (0.0475) time: 2.6117 data: 0.0058 max mem: 33369 +Epoch: [22] [1020/1319] eta: 0:13:03 lr: 2.342504283291958e-05 loss: 0.0398 (0.0475) time: 2.6221 data: 0.0059 max mem: 33369 +Epoch: [22] [1030/1319] eta: 0:12:37 lr: 2.3415763750762803e-05 loss: 0.0377 (0.0475) time: 2.6267 data: 0.0061 max mem: 33369 +Epoch: [22] [1040/1319] eta: 0:12:10 lr: 2.3406484260024864e-05 loss: 0.0376 (0.0474) time: 2.6134 data: 0.0059 max mem: 33369 +Epoch: [22] [1050/1319] eta: 0:11:44 lr: 2.3397204360507778e-05 loss: 0.0409 (0.0474) time: 2.6069 data: 0.0060 max mem: 33369 +Epoch: [22] [1060/1319] eta: 0:11:18 lr: 2.3387924052013375e-05 loss: 0.0370 (0.0473) time: 2.6064 data: 0.0059 max mem: 33369 +Epoch: [22] [1070/1319] eta: 0:10:52 lr: 2.3378643334343302e-05 loss: 0.0331 (0.0473) time: 2.6047 data: 0.0059 max mem: 33369 +Epoch: [22] [1080/1319] eta: 0:10:25 lr: 2.3369362207299018e-05 loss: 0.0404 (0.0472) time: 2.5918 data: 0.0059 max mem: 33369 +Epoch: [22] [1090/1319] eta: 0:09:59 lr: 2.3360080670681804e-05 loss: 0.0373 (0.0473) time: 2.6253 data: 0.0058 max mem: 33369 +Epoch: [22] [1100/1319] eta: 0:09:33 lr: 2.335079872429276e-05 loss: 0.0373 (0.0472) time: 2.6596 data: 0.0058 max mem: 33369 +Epoch: [22] [1110/1319] eta: 0:09:07 lr: 2.334151636793279e-05 loss: 0.0380 (0.0472) time: 2.6321 data: 0.0058 max mem: 33369 +Epoch: [22] [1120/1319] eta: 0:08:41 lr: 2.333223360140262e-05 loss: 0.0429 (0.0472) time: 2.6431 data: 0.0058 max mem: 33369 +Epoch: [22] [1130/1319] eta: 0:08:15 lr: 2.3322950424502793e-05 loss: 0.0464 (0.0472) time: 2.6414 data: 0.0057 max mem: 33369 +Epoch: [22] [1140/1319] eta: 0:07:48 lr: 2.3313666837033663e-05 loss: 0.0443 (0.0471) time: 2.6070 data: 0.0058 max mem: 33369 +Epoch: [22] [1150/1319] eta: 0:07:22 lr: 2.33043828387954e-05 loss: 0.0379 (0.0472) time: 2.5985 data: 0.0060 max mem: 33369 +Epoch: [22] [1160/1319] eta: 0:06:56 lr: 2.3295098429587987e-05 loss: 0.0391 (0.0471) time: 2.6020 data: 0.0059 max mem: 33369 +Epoch: [22] [1170/1319] eta: 0:06:30 lr: 2.328581360921123e-05 loss: 0.0425 (0.0471) time: 2.6129 data: 0.0058 max mem: 33369 +Epoch: [22] [1180/1319] eta: 0:06:04 lr: 2.327652837746473e-05 loss: 0.0437 (0.0472) time: 2.6205 data: 0.0058 max mem: 33369 +Epoch: [22] [1190/1319] eta: 0:05:37 lr: 2.3267242734147912e-05 loss: 0.0399 (0.0471) time: 2.6187 data: 0.0057 max mem: 33369 +Epoch: [22] [1200/1319] eta: 0:05:11 lr: 2.325795667906002e-05 loss: 0.0381 (0.0471) time: 2.6116 data: 0.0059 max mem: 33369 +Epoch: [22] [1210/1319] eta: 0:04:45 lr: 2.3248670212000107e-05 loss: 0.0413 (0.0472) time: 2.6073 data: 0.0060 max mem: 33369 +Epoch: [22] [1220/1319] eta: 0:04:19 lr: 2.3239383332767037e-05 loss: 0.0413 (0.0471) time: 2.6106 data: 0.0060 max mem: 33369 +Epoch: [22] [1230/1319] eta: 0:03:53 lr: 2.323009604115948e-05 loss: 0.0357 (0.0471) time: 2.6234 data: 0.0060 max mem: 33369 +Epoch: [22] [1240/1319] eta: 0:03:26 lr: 2.322080833697593e-05 loss: 0.0452 (0.0471) time: 2.6259 data: 0.0060 max mem: 33369 +Epoch: [22] [1250/1319] eta: 0:03:00 lr: 2.3211520220014678e-05 loss: 0.0542 (0.0472) time: 2.6065 data: 0.0061 max mem: 33369 +Epoch: [22] [1260/1319] eta: 0:02:34 lr: 2.320223169007385e-05 loss: 0.0520 (0.0473) time: 2.6014 data: 0.0061 max mem: 33369 +Epoch: [22] [1270/1319] eta: 0:02:08 lr: 2.319294274695137e-05 loss: 0.0457 (0.0473) time: 2.6326 data: 0.0060 max mem: 33369 +Epoch: [22] [1280/1319] eta: 0:01:42 lr: 2.318365339044496e-05 loss: 0.0438 (0.0473) time: 2.6432 data: 0.0061 max mem: 33369 +Epoch: [22] [1290/1319] eta: 0:01:15 lr: 2.3174363620352174e-05 loss: 0.0438 (0.0473) time: 2.6363 data: 0.0061 max mem: 33369 +Epoch: [22] [1300/1319] eta: 0:00:49 lr: 2.3165073436470368e-05 loss: 0.0496 (0.0474) time: 2.6441 data: 0.0060 max mem: 33369 +Epoch: [22] [1310/1319] eta: 0:00:23 lr: 2.3155782838596706e-05 loss: 0.0529 (0.0475) time: 2.6323 data: 0.0058 max mem: 33369 +Epoch: [22] Total time: 0:57:36 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 2:18:49 time: 3.2373 data: 3.1566 max mem: 33369 +Test: [ 100/2573] eta: 0:04:15 time: 0.0717 data: 0.0011 max mem: 33369 +Test: [ 200/2573] eta: 0:03:30 time: 0.0733 data: 0.0011 max mem: 33369 +Test: [ 300/2573] eta: 0:03:09 time: 0.0750 data: 0.0011 max mem: 33369 +Test: [ 400/2573] eta: 0:02:55 time: 0.0751 data: 0.0011 max mem: 33369 +Test: [ 500/2573] eta: 0:02:44 time: 0.0735 data: 0.0011 max mem: 33369 +Test: [ 600/2573] eta: 0:02:34 time: 0.0738 data: 0.0011 max mem: 33369 +Test: [ 700/2573] eta: 0:02:26 time: 0.0737 data: 0.0011 max mem: 33369 +Test: [ 800/2573] eta: 0:02:17 time: 0.0772 data: 0.0011 max mem: 33369 +Test: [ 900/2573] eta: 0:02:09 time: 0.0737 data: 0.0011 max mem: 33369 +Test: [1000/2573] eta: 0:02:01 time: 0.0740 data: 0.0011 max mem: 33369 +Test: [1100/2573] eta: 0:01:53 time: 0.0737 data: 0.0011 max mem: 33369 +Test: [1200/2573] eta: 0:01:45 time: 0.0738 data: 0.0011 max mem: 33369 +Test: [1300/2573] eta: 0:01:37 time: 0.0738 data: 0.0011 max mem: 33369 +Test: [1400/2573] eta: 0:01:29 time: 0.0720 data: 0.0011 max mem: 33369 +Test: [1500/2573] eta: 0:01:21 time: 0.0737 data: 0.0011 max mem: 33369 +Test: [1600/2573] eta: 0:01:13 time: 0.0770 data: 0.0011 max mem: 33369 +Test: [1700/2573] eta: 0:01:06 time: 0.0721 data: 0.0011 max mem: 33369 +Test: [1800/2573] eta: 0:00:58 time: 0.0755 data: 0.0011 max mem: 33369 +Test: [1900/2573] eta: 0:00:50 time: 0.0722 data: 0.0011 max mem: 33369 +Test: [2000/2573] eta: 0:00:43 time: 0.0739 data: 0.0011 max mem: 33369 +Test: [2100/2573] eta: 0:00:35 time: 0.0754 data: 0.0011 max mem: 33369 +Test: [2200/2573] eta: 0:00:28 time: 0.0754 data: 0.0011 max mem: 33369 +Test: [2300/2573] eta: 0:00:20 time: 0.0755 data: 0.0011 max mem: 33369 +Test: [2400/2573] eta: 0:00:12 time: 0.0705 data: 0.0011 max mem: 33369 +Test: [2500/2573] eta: 0:00:05 time: 0.0739 data: 0.0011 max mem: 33369 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: Total time: 0:03:13 +Final results: +Mean IoU is 63.32 + + precision@0.5 = 70.77 + precision@0.6 = 65.36 + precision@0.7 = 58.60 + precision@0.8 = 47.43 + precision@0.9 = 23.00 + overall IoU = 61.25 + +Average object IoU 63.31713752999142 +Overall IoU 61.24873733520508 +Better epoch: 22 + +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [23] [ 0/1319] eta: 1:26:53 lr: 2.3147420946379584e-05 loss: 0.0849 (0.0849) time: 3.9523 data: 1.1542 max mem: 33369 +Epoch: [23] [ 10/1319] eta: 0:59:59 lr: 2.313812956136191e-05 loss: 0.0369 (0.0413) time: 2.7495 data: 0.1104 max mem: 33369 +Epoch: [23] [ 20/1319] eta: 0:58:23 lr: 2.3128837761763095e-05 loss: 0.0412 (0.0481) time: 2.6339 data: 0.0057 max mem: 33369 +Epoch: [23] [ 30/1319] eta: 0:57:20 lr: 2.3119545547379566e-05 loss: 0.0419 (0.0448) time: 2.6252 data: 0.0058 max mem: 33369 +Epoch: [23] [ 40/1319] eta: 0:56:58 lr: 2.3110252918007542e-05 loss: 0.0365 (0.0461) time: 2.6471 data: 0.0060 max mem: 33369 +Epoch: [23] [ 50/1319] eta: 0:56:25 lr: 2.3100959873443074e-05 loss: 0.0455 (0.0475) time: 2.6646 data: 0.0060 max mem: 33369 +Epoch: [23] [ 60/1319] eta: 0:55:53 lr: 2.3091666413482015e-05 loss: 0.0455 (0.0467) time: 2.6442 data: 0.0060 max mem: 33369 +Epoch: [23] [ 70/1319] eta: 0:55:28 lr: 2.3082372537920018e-05 loss: 0.0393 (0.0459) time: 2.6584 data: 0.0060 max mem: 33369 +Epoch: [23] [ 80/1319] eta: 0:54:59 lr: 2.307307824655256e-05 loss: 0.0407 (0.0464) time: 2.6638 data: 0.0060 max mem: 33369 +Epoch: [23] [ 90/1319] eta: 0:54:24 lr: 2.3063783539174907e-05 loss: 0.0362 (0.0457) time: 2.6261 data: 0.0060 max mem: 33369 +Epoch: [23] [ 100/1319] eta: 0:53:55 lr: 2.3054488415582145e-05 loss: 0.0383 (0.0454) time: 2.6184 data: 0.0060 max mem: 33369 +Epoch: [23] [ 110/1319] eta: 0:53:30 lr: 2.3045192875569164e-05 loss: 0.0446 (0.0454) time: 2.6515 data: 0.0060 max mem: 33369 +Epoch: [23] [ 120/1319] eta: 0:53:00 lr: 2.3035896918930662e-05 loss: 0.0431 (0.0451) time: 2.6422 data: 0.0059 max mem: 33369 +Epoch: [23] [ 130/1319] eta: 0:52:28 lr: 2.3026600545461138e-05 loss: 0.0399 (0.0452) time: 2.6056 data: 0.0061 max mem: 33369 +Epoch: [23] [ 140/1319] eta: 0:52:04 lr: 2.3017303754954915e-05 loss: 0.0337 (0.0448) time: 2.6352 data: 0.0059 max mem: 33369 +Epoch: [23] [ 150/1319] eta: 0:51:36 lr: 2.300800654720609e-05 loss: 0.0353 (0.0448) time: 2.6548 data: 0.0058 max mem: 33369 +Epoch: [23] [ 160/1319] eta: 0:51:10 lr: 2.2998708922008593e-05 loss: 0.0445 (0.0447) time: 2.6427 data: 0.0059 max mem: 33369 +Epoch: [23] [ 170/1319] eta: 0:50:40 lr: 2.2989410879156158e-05 loss: 0.0450 (0.0450) time: 2.6298 data: 0.0058 max mem: 33369 +Epoch: [23] [ 180/1319] eta: 0:50:15 lr: 2.298011241844231e-05 loss: 0.0471 (0.0451) time: 2.6360 data: 0.0060 max mem: 33369 +Epoch: [23] [ 190/1319] eta: 0:49:47 lr: 2.2970813539660394e-05 loss: 0.0405 (0.0447) time: 2.6446 data: 0.0061 max mem: 33369 +Epoch: [23] [ 200/1319] eta: 0:49:20 lr: 2.296151424260354e-05 loss: 0.0405 (0.0445) time: 2.6251 data: 0.0060 max mem: 33369 +Epoch: [23] [ 210/1319] eta: 0:48:51 lr: 2.2952214527064705e-05 loss: 0.0403 (0.0444) time: 2.6180 data: 0.0061 max mem: 33369 +Epoch: [23] [ 220/1319] eta: 0:48:24 lr: 2.294291439283664e-05 loss: 0.0400 (0.0444) time: 2.6140 data: 0.0062 max mem: 33369 +Epoch: [23] [ 230/1319] eta: 0:47:55 lr: 2.2933613839711898e-05 loss: 0.0402 (0.0448) time: 2.6053 data: 0.0063 max mem: 33369 +Epoch: [23] [ 240/1319] eta: 0:47:29 lr: 2.292431286748284e-05 loss: 0.0443 (0.0449) time: 2.6169 data: 0.0061 max mem: 33369 +Epoch: [23] [ 250/1319] eta: 0:47:02 lr: 2.2915011475941626e-05 loss: 0.0402 (0.0447) time: 2.6454 data: 0.0059 max mem: 33369 +Epoch: [23] [ 260/1319] eta: 0:46:34 lr: 2.2905709664880228e-05 loss: 0.0391 (0.0447) time: 2.6254 data: 0.0059 max mem: 33369 +Epoch: [23] [ 270/1319] eta: 0:46:07 lr: 2.28964074340904e-05 loss: 0.0352 (0.0445) time: 2.6109 data: 0.0060 max mem: 33369 +Epoch: [23] [ 280/1319] eta: 0:45:40 lr: 2.2887104783363728e-05 loss: 0.0353 (0.0447) time: 2.6163 data: 0.0059 max mem: 33369 +Epoch: [23] [ 290/1319] eta: 0:45:14 lr: 2.2877801712491578e-05 loss: 0.0378 (0.0446) time: 2.6240 data: 0.0060 max mem: 33369 +Epoch: [23] [ 300/1319] eta: 0:44:45 lr: 2.2868498221265136e-05 loss: 0.0401 (0.0446) time: 2.6090 data: 0.0061 max mem: 33369 +Epoch: [23] [ 310/1319] eta: 0:44:20 lr: 2.2859194309475363e-05 loss: 0.0418 (0.0446) time: 2.6272 data: 0.0059 max mem: 33369 +Epoch: [23] [ 320/1319] eta: 0:43:52 lr: 2.2849889976913045e-05 loss: 0.0417 (0.0446) time: 2.6309 data: 0.0060 max mem: 33369 +Epoch: [23] [ 330/1319] eta: 0:43:26 lr: 2.2840585223368763e-05 loss: 0.0406 (0.0447) time: 2.6087 data: 0.0061 max mem: 33369 +Epoch: [23] [ 340/1319] eta: 0:42:59 lr: 2.2831280048632893e-05 loss: 0.0405 (0.0446) time: 2.6167 data: 0.0062 max mem: 33369 +Epoch: [23] [ 350/1319] eta: 0:42:31 lr: 2.282197445249563e-05 loss: 0.0400 (0.0446) time: 2.5968 data: 0.0062 max mem: 33369 +Epoch: [23] [ 360/1319] eta: 0:42:04 lr: 2.2812668434746943e-05 loss: 0.0400 (0.0444) time: 2.6092 data: 0.0061 max mem: 33369 +Epoch: [23] [ 370/1319] eta: 0:41:38 lr: 2.2803361995176614e-05 loss: 0.0420 (0.0450) time: 2.6265 data: 0.0059 max mem: 33369 +Epoch: [23] [ 380/1319] eta: 0:41:11 lr: 2.279405513357423e-05 loss: 0.0510 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2.2719585022284628e-05 loss: 0.0387 (0.0446) time: 2.6153 data: 0.0059 max mem: 33369 +Epoch: [23] [ 470/1319] eta: 0:37:10 lr: 2.2710274352891738e-05 loss: 0.0413 (0.0446) time: 2.5832 data: 0.0061 max mem: 33369 +Epoch: [23] [ 480/1319] eta: 0:36:44 lr: 2.2700963259351535e-05 loss: 0.0436 (0.0446) time: 2.5921 data: 0.0060 max mem: 33369 +Epoch: [23] [ 490/1319] eta: 0:36:18 lr: 2.269165174145138e-05 loss: 0.0418 (0.0446) time: 2.6398 data: 0.0059 max mem: 33369 +Epoch: [23] [ 500/1319] eta: 0:35:52 lr: 2.2682339798978432e-05 loss: 0.0453 (0.0447) time: 2.6409 data: 0.0059 max mem: 33369 +Epoch: [23] [ 510/1319] eta: 0:35:25 lr: 2.2673027431719644e-05 loss: 0.0430 (0.0447) time: 2.6024 data: 0.0061 max mem: 33369 +Epoch: [23] [ 520/1319] eta: 0:34:58 lr: 2.266371463946176e-05 loss: 0.0397 (0.0447) time: 2.5910 data: 0.0059 max mem: 33369 +Epoch: [23] [ 530/1319] eta: 0:34:32 lr: 2.2654401421991334e-05 loss: 0.0414 (0.0447) time: 2.6115 data: 0.0058 max mem: 33369 +Epoch: [23] [ 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data: 0.0059 max mem: 33369 +Epoch: [23] [ 700/1319] eta: 0:27:04 lr: 2.2496011459639643e-05 loss: 0.0380 (0.0454) time: 2.6008 data: 0.0059 max mem: 33369 +Epoch: [23] [ 710/1319] eta: 0:26:38 lr: 2.2486690551607674e-05 loss: 0.0440 (0.0455) time: 2.5958 data: 0.0060 max mem: 33369 +Epoch: [23] [ 720/1319] eta: 0:26:11 lr: 2.2477369214268278e-05 loss: 0.0422 (0.0454) time: 2.5882 data: 0.0060 max mem: 33369 +Epoch: [23] [ 730/1319] eta: 0:25:45 lr: 2.246804744740384e-05 loss: 0.0422 (0.0455) time: 2.6119 data: 0.0060 max mem: 33369 +Epoch: [23] [ 740/1319] eta: 0:25:19 lr: 2.245872525079654e-05 loss: 0.0432 (0.0455) time: 2.6513 data: 0.0061 max mem: 33369 +Epoch: [23] [ 750/1319] eta: 0:24:53 lr: 2.244940262422835e-05 loss: 0.0427 (0.0455) time: 2.6372 data: 0.0060 max mem: 33369 +Epoch: [23] [ 760/1319] eta: 0:24:26 lr: 2.244007956748104e-05 loss: 0.0416 (0.0455) time: 2.5981 data: 0.0060 max mem: 33369 +Epoch: [23] [ 770/1319] eta: 0:24:00 lr: 2.243075608033615e-05 loss: 0.0392 (0.0455) time: 2.6021 data: 0.0060 max mem: 33369 +Epoch: [23] [ 780/1319] eta: 0:23:33 lr: 2.242143216257503e-05 loss: 0.0388 (0.0454) time: 2.6010 data: 0.0059 max mem: 33369 +Epoch: [23] [ 790/1319] eta: 0:23:07 lr: 2.2412107813978792e-05 loss: 0.0429 (0.0455) time: 2.5879 data: 0.0059 max mem: 33369 +Epoch: [23] [ 800/1319] eta: 0:22:40 lr: 2.240278303432835e-05 loss: 0.0419 (0.0455) time: 2.5853 data: 0.0061 max mem: 33369 +Epoch: [23] [ 810/1319] eta: 0:22:14 lr: 2.2393457823404408e-05 loss: 0.0415 (0.0457) time: 2.5939 data: 0.0062 max mem: 33369 +Epoch: [23] [ 820/1319] eta: 0:21:48 lr: 2.2384132180987457e-05 loss: 0.0415 (0.0456) time: 2.6241 data: 0.0061 max mem: 33369 +Epoch: [23] [ 830/1319] eta: 0:21:22 lr: 2.2374806106857758e-05 loss: 0.0363 (0.0455) time: 2.6209 data: 0.0060 max mem: 33369 +Epoch: [23] [ 840/1319] eta: 0:20:55 lr: 2.2365479600795384e-05 loss: 0.0424 (0.0455) time: 2.6004 data: 0.0059 max mem: 33369 +Epoch: [23] [ 850/1319] eta: 0:20:29 lr: 2.2356152662580173e-05 loss: 0.0409 (0.0455) time: 2.6025 data: 0.0060 max mem: 33369 +Epoch: [23] [ 860/1319] eta: 0:20:03 lr: 2.234682529199176e-05 loss: 0.0361 (0.0454) time: 2.6062 data: 0.0059 max mem: 33369 +Epoch: [23] [ 870/1319] eta: 0:19:36 lr: 2.2337497488809557e-05 loss: 0.0410 (0.0455) time: 2.6070 data: 0.0060 max mem: 33369 +Epoch: [23] [ 880/1319] eta: 0:19:10 lr: 2.232816925281277e-05 loss: 0.0414 (0.0455) time: 2.6057 data: 0.0061 max mem: 33369 +Epoch: [23] [ 890/1319] eta: 0:18:44 lr: 2.2318840583780386e-05 loss: 0.0445 (0.0456) time: 2.6102 data: 0.0059 max mem: 33369 +Epoch: [23] [ 900/1319] eta: 0:18:17 lr: 2.2309511481491173e-05 loss: 0.0456 (0.0455) time: 2.6054 data: 0.0059 max mem: 33369 +Epoch: [23] [ 910/1319] eta: 0:17:51 lr: 2.2300181945723685e-05 loss: 0.0413 (0.0455) time: 2.6089 data: 0.0060 max mem: 33369 +Epoch: [23] [ 920/1319] eta: 0:17:25 lr: 2.2290851976256266e-05 loss: 0.0460 (0.0456) time: 2.6405 data: 0.0060 max mem: 33369 +Epoch: [23] [ 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mem: 33369 +Epoch: [23] [1010/1319] eta: 0:13:29 lr: 2.2206862697871013e-05 loss: 0.0504 (0.0460) time: 2.6225 data: 0.0059 max mem: 33369 +Epoch: [23] [1020/1319] eta: 0:13:03 lr: 2.2197528379165116e-05 loss: 0.0446 (0.0460) time: 2.6391 data: 0.0059 max mem: 33369 +Epoch: [23] [1030/1319] eta: 0:12:37 lr: 2.218819362430666e-05 loss: 0.0368 (0.0458) time: 2.6488 data: 0.0058 max mem: 33369 +Epoch: [23] [1040/1319] eta: 0:12:11 lr: 2.217885843307136e-05 loss: 0.0345 (0.0460) time: 2.6324 data: 0.0058 max mem: 33369 +Epoch: [23] [1050/1319] eta: 0:11:45 lr: 2.2169522805234726e-05 loss: 0.0477 (0.0461) time: 2.5949 data: 0.0059 max mem: 33369 +Epoch: [23] [1060/1319] eta: 0:11:18 lr: 2.2160186740572026e-05 loss: 0.0472 (0.0461) time: 2.5879 data: 0.0058 max mem: 33369 +Epoch: [23] [1070/1319] eta: 0:10:52 lr: 2.215085023885832e-05 loss: 0.0453 (0.0461) time: 2.6193 data: 0.0058 max mem: 33369 +Epoch: [23] [1080/1319] eta: 0:10:26 lr: 2.2141513299868444e-05 loss: 0.0453 (0.0464) time: 2.6223 data: 0.0059 max mem: 33369 +Epoch: [23] [1090/1319] eta: 0:10:00 lr: 2.2132175923377022e-05 loss: 0.0415 (0.0463) time: 2.6245 data: 0.0060 max mem: 33369 +Epoch: [23] [1100/1319] eta: 0:09:34 lr: 2.2122838109158445e-05 loss: 0.0391 (0.0463) time: 2.6328 data: 0.0060 max mem: 33369 +Epoch: [23] [1110/1319] eta: 0:09:07 lr: 2.211349985698688e-05 loss: 0.0385 (0.0463) time: 2.6370 data: 0.0060 max mem: 33369 +Epoch: [23] [1120/1319] eta: 0:08:41 lr: 2.2104161166636274e-05 loss: 0.0371 (0.0463) time: 2.6409 data: 0.0059 max mem: 33369 +Epoch: [23] [1130/1319] eta: 0:08:15 lr: 2.2094822037880365e-05 loss: 0.0406 (0.0463) time: 2.6112 data: 0.0059 max mem: 33369 +Epoch: [23] [1140/1319] eta: 0:07:49 lr: 2.2085482470492644e-05 loss: 0.0429 (0.0464) time: 2.6200 data: 0.0059 max mem: 33369 +Epoch: [23] [1150/1319] eta: 0:07:23 lr: 2.20761424642464e-05 loss: 0.0352 (0.0463) time: 2.6331 data: 0.0059 max mem: 33369 +Epoch: [23] [1160/1319] eta: 0:06:56 lr: 2.2066802018914685e-05 loss: 0.0339 (0.0462) time: 2.6267 data: 0.0058 max mem: 33369 +Epoch: [23] [1170/1319] eta: 0:06:30 lr: 2.2057461134270328e-05 loss: 0.0350 (0.0462) time: 2.6259 data: 0.0058 max mem: 33369 +Epoch: [23] [1180/1319] eta: 0:06:04 lr: 2.2048119810085938e-05 loss: 0.0355 (0.0462) time: 2.6297 data: 0.0057 max mem: 33369 +Epoch: [23] [1190/1319] eta: 0:05:38 lr: 2.2038778046133896e-05 loss: 0.0471 (0.0464) time: 2.6269 data: 0.0058 max mem: 33369 +Epoch: [23] [1200/1319] eta: 0:05:12 lr: 2.2029435842186362e-05 loss: 0.0482 (0.0464) time: 2.6329 data: 0.0059 max mem: 33369 +Epoch: [23] [1210/1319] eta: 0:04:45 lr: 2.2020093198015273e-05 loss: 0.0409 (0.0463) time: 2.6267 data: 0.0060 max mem: 33369 +Epoch: [23] [1220/1319] eta: 0:04:19 lr: 2.2010750113392324e-05 loss: 0.0368 (0.0463) time: 2.6031 data: 0.0060 max mem: 33369 +Epoch: [23] [1230/1319] eta: 0:03:53 lr: 2.2001406588088997e-05 loss: 0.0433 (0.0463) time: 2.6058 data: 0.0060 max mem: 33369 +Epoch: [23] [1240/1319] eta: 0:03:27 lr: 2.199206262187655e-05 loss: 0.0429 (0.0463) time: 2.6035 data: 0.0059 max mem: 33369 +Epoch: [23] [1250/1319] eta: 0:03:00 lr: 2.1982718214526003e-05 loss: 0.0406 (0.0462) time: 2.6114 data: 0.0058 max mem: 33369 +Epoch: [23] [1260/1319] eta: 0:02:34 lr: 2.1973373365808168e-05 loss: 0.0452 (0.0462) time: 2.6339 data: 0.0060 max mem: 33369 +Epoch: [23] [1270/1319] eta: 0:02:08 lr: 2.1964028075493602e-05 loss: 0.0425 (0.0462) time: 2.6603 data: 0.0060 max mem: 33369 +Epoch: [23] [1280/1319] eta: 0:01:42 lr: 2.1954682343352655e-05 loss: 0.0425 (0.0463) time: 2.6527 data: 0.0059 max mem: 33369 +Epoch: [23] [1290/1319] eta: 0:01:16 lr: 2.1945336169155447e-05 loss: 0.0432 (0.0463) time: 2.6417 data: 0.0060 max mem: 33369 +Epoch: [23] [1300/1319] eta: 0:00:49 lr: 2.1935989552671862e-05 loss: 0.0432 (0.0463) time: 2.5965 data: 0.0060 max mem: 33369 +Epoch: [23] [1310/1319] eta: 0:00:23 lr: 2.192664249367156e-05 loss: 0.0446 (0.0463) time: 2.5895 data: 0.0059 max mem: 33369 +Epoch: [23] Total time: 0:57:38 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 2:11:00 time: 3.0548 data: 2.9761 max mem: 33369 +Test: [ 100/2573] eta: 0:04:10 time: 0.0715 data: 0.0011 max mem: 33369 +Test: [ 200/2573] eta: 0:03:28 time: 0.0734 data: 0.0011 max mem: 33369 +Test: [ 300/2573] eta: 0:03:07 time: 0.0751 data: 0.0011 max mem: 33369 +Test: [ 400/2573] eta: 0:02:54 time: 0.0751 data: 0.0011 max mem: 33369 +Test: [ 500/2573] eta: 0:02:43 time: 0.0736 data: 0.0011 max mem: 33369 +Test: [ 600/2573] eta: 0:02:34 time: 0.0737 data: 0.0011 max mem: 33369 +Test: [ 700/2573] eta: 0:02:25 time: 0.0738 data: 0.0011 max mem: 33369 +Test: [ 800/2573] eta: 0:02:17 time: 0.0771 data: 0.0011 max mem: 33369 +Test: [ 900/2573] eta: 0:02:09 time: 0.0739 data: 0.0011 max mem: 33369 +Test: [1000/2573] eta: 0:02:00 time: 0.0738 data: 0.0011 max mem: 33369 +Test: [1100/2573] eta: 0:01:52 time: 0.0739 data: 0.0011 max mem: 33369 +Test: [1200/2573] eta: 0:01:44 time: 0.0739 data: 0.0011 max mem: 33369 +Test: [1300/2573] eta: 0:01:37 time: 0.0738 data: 0.0011 max mem: 33369 +Test: [1400/2573] eta: 0:01:29 time: 0.0722 data: 0.0011 max mem: 33369 +Test: [1500/2573] eta: 0:01:21 time: 0.0739 data: 0.0011 max mem: 33369 +Test: [1600/2573] eta: 0:01:13 time: 0.0771 data: 0.0011 max mem: 33369 +Test: [1700/2573] eta: 0:01:06 time: 0.0722 data: 0.0011 max mem: 33369 +Test: [1800/2573] eta: 0:00:58 time: 0.0753 data: 0.0011 max mem: 33369 +Test: [1900/2573] eta: 0:00:50 time: 0.0721 data: 0.0011 max mem: 33369 +Test: [2000/2573] eta: 0:00:43 time: 0.0738 data: 0.0011 max mem: 33369 +Test: [2100/2573] eta: 0:00:35 time: 0.0756 data: 0.0012 max mem: 33369 +Test: [2200/2573] eta: 0:00:28 time: 0.0754 data: 0.0011 max mem: 33369 +Test: [2300/2573] eta: 0:00:20 time: 0.0755 data: 0.0011 max mem: 33369 +Test: [2400/2573] eta: 0:00:12 time: 0.0704 data: 0.0011 max mem: 33369 +Test: [2500/2573] eta: 0:00:05 time: 0.0738 data: 0.0012 max mem: 33369 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: Total time: 0:03:13 +Final results: +Mean IoU is 63.89 + + precision@0.5 = 71.51 + precision@0.6 = 66.03 + precision@0.7 = 59.60 + precision@0.8 = 48.02 + precision@0.9 = 23.61 + overall IoU = 61.48 + +Average object IoU 63.88990150304332 +Overall IoU 61.48343276977539 +Better epoch: 23 + +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [24] [ 0/1319] eta: 1:29:32 lr: 2.1918229762028934e-05 loss: 0.0770 (0.0770) time: 4.0729 data: 1.2989 max mem: 33369 +Epoch: [24] [ 10/1319] eta: 0:59:10 lr: 2.1908881861611456e-05 loss: 0.0391 (0.0414) time: 2.7122 data: 0.1231 max mem: 33369 +Epoch: [24] [ 20/1319] eta: 0:57:48 lr: 2.1899533518007982e-05 loss: 0.0400 (0.0512) time: 2.5997 data: 0.0056 max mem: 33369 +Epoch: [24] [ 30/1319] eta: 0:56:58 lr: 2.189018473098726e-05 loss: 0.0435 (0.0477) time: 2.6186 data: 0.0060 max mem: 33369 +Epoch: [24] [ 40/1319] eta: 0:56:06 lr: 2.188083550031783e-05 loss: 0.0340 (0.0439) time: 2.5923 data: 0.0063 max mem: 33369 +Epoch: [24] [ 50/1319] eta: 0:55:35 lr: 2.1871485825767997e-05 loss: 0.0364 (0.0442) time: 2.5926 data: 0.0063 max mem: 33369 +Epoch: [24] [ 60/1319] eta: 0:54:58 lr: 2.1862135707105826e-05 loss: 0.0412 (0.0435) time: 2.5946 data: 0.0062 max mem: 33369 +Epoch: [24] [ 70/1319] eta: 0:54:30 lr: 2.1852785144099174e-05 loss: 0.0387 (0.0430) time: 2.5923 data: 0.0061 max mem: 33369 +Epoch: [24] [ 80/1319] eta: 0:54:02 lr: 2.184343413651562e-05 loss: 0.0353 (0.0426) time: 2.6072 data: 0.0063 max mem: 33369 +Epoch: [24] [ 90/1319] eta: 0:53:37 lr: 2.1834082684122557e-05 loss: 0.0395 (0.0431) time: 2.6170 data: 0.0062 max mem: 33369 +Epoch: [24] [ 100/1319] eta: 0:53:12 lr: 2.1824730786687132e-05 loss: 0.0470 (0.0438) time: 2.6262 data: 0.0061 max mem: 33369 +Epoch: [24] [ 110/1319] eta: 0:52:45 lr: 2.181537844397624e-05 loss: 0.0394 (0.0433) time: 2.6195 data: 0.0064 max mem: 33369 +Epoch: [24] [ 120/1319] eta: 0:52:15 lr: 2.1806025655756576e-05 loss: 0.0394 (0.0432) time: 2.5965 data: 0.0065 max mem: 33369 +Epoch: [24] [ 130/1319] eta: 0:51:46 lr: 2.1796672421794575e-05 loss: 0.0365 (0.0427) time: 2.5841 data: 0.0063 max mem: 33369 +Epoch: [24] [ 140/1319] eta: 0:51:19 lr: 2.1787318741856443e-05 loss: 0.0365 (0.0429) time: 2.5967 data: 0.0060 max mem: 33369 +Epoch: [24] [ 150/1319] eta: 0:50:55 lr: 2.1777964615708157e-05 loss: 0.0392 (0.0425) time: 2.6208 data: 0.0062 max mem: 33369 +Epoch: [24] [ 160/1319] eta: 0:50:33 lr: 2.1768610043115462e-05 loss: 0.0413 (0.0427) time: 2.6558 data: 0.0062 max mem: 33369 +Epoch: [24] [ 170/1319] eta: 0:50:11 lr: 2.1759255023843863e-05 loss: 0.0435 (0.0427) time: 2.6720 data: 0.0060 max mem: 33369 +Epoch: [24] [ 180/1319] eta: 0:49:48 lr: 2.1749899557658636e-05 loss: 0.0386 (0.0427) time: 2.6703 data: 0.0061 max mem: 33369 +Epoch: [24] [ 190/1319] eta: 0:49:23 lr: 2.17405436443248e-05 loss: 0.0425 (0.0431) time: 2.6550 data: 0.0060 max mem: 33369 +Epoch: [24] [ 200/1319] eta: 0:48:56 lr: 2.1731187283607167e-05 loss: 0.0352 (0.0426) time: 2.6328 data: 0.0060 max mem: 33369 +Epoch: [24] [ 210/1319] eta: 0:48:33 lr: 2.17218304752703e-05 loss: 0.0350 (0.0429) time: 2.6558 data: 0.0059 max mem: 33369 +Epoch: [24] [ 220/1319] eta: 0:48:06 lr: 2.171247321907852e-05 loss: 0.0434 (0.0430) time: 2.6515 data: 0.0060 max mem: 33369 +Epoch: [24] [ 230/1319] eta: 0:47:42 lr: 2.1703115514795925e-05 loss: 0.0437 (0.0432) time: 2.6364 data: 0.0061 max mem: 33369 +Epoch: [24] [ 240/1319] eta: 0:47:17 lr: 2.1693757362186356e-05 loss: 0.0361 (0.0429) time: 2.6590 data: 0.0059 max mem: 33369 +Epoch: [24] [ 250/1319] eta: 0:46:50 lr: 2.1684398761013434e-05 loss: 0.0369 (0.0433) time: 2.6440 data: 0.0059 max mem: 33369 +Epoch: [24] [ 260/1319] eta: 0:46:22 lr: 2.1675039711040532e-05 loss: 0.0406 (0.0432) time: 2.6015 data: 0.0061 max mem: 33369 +Epoch: [24] [ 270/1319] eta: 0:45:55 lr: 2.166568021203079e-05 loss: 0.0408 (0.0434) time: 2.5949 data: 0.0061 max mem: 33369 +Epoch: [24] [ 280/1319] eta: 0:45:27 lr: 2.1656320263747106e-05 loss: 0.0405 (0.0431) time: 2.5937 data: 0.0059 max mem: 33369 +Epoch: [24] [ 290/1319] eta: 0:45:01 lr: 2.164695986595215e-05 loss: 0.0360 (0.0431) time: 2.6075 data: 0.0059 max mem: 33369 +Epoch: [24] [ 300/1319] eta: 0:44:35 lr: 2.163759901840832e-05 loss: 0.0415 (0.0432) time: 2.6306 data: 0.0062 max mem: 33369 +Epoch: [24] [ 310/1319] eta: 0:44:09 lr: 2.1628237720877814e-05 loss: 0.0444 (0.0435) time: 2.6318 data: 0.0061 max mem: 33369 +Epoch: [24] [ 320/1319] eta: 0:43:41 lr: 2.161887597312257e-05 loss: 0.0471 (0.0436) time: 2.6008 data: 0.0063 max mem: 33369 +Epoch: [24] [ 330/1319] eta: 0:43:13 lr: 2.160951377490428e-05 loss: 0.0405 (0.0436) time: 2.5687 data: 0.0064 max mem: 33369 +Epoch: [24] [ 340/1319] eta: 0:42:48 lr: 2.160015112598442e-05 loss: 0.0469 (0.0437) time: 2.6253 data: 0.0062 max mem: 33369 +Epoch: [24] [ 350/1319] eta: 0:42:22 lr: 2.1590788026124187e-05 loss: 0.0402 (0.0437) time: 2.6367 data: 0.0061 max mem: 33369 +Epoch: [24] [ 360/1319] eta: 0:41:55 lr: 2.158142447508457e-05 loss: 0.0398 (0.0436) time: 2.6080 data: 0.0062 max mem: 33369 +Epoch: [24] [ 370/1319] eta: 0:41:29 lr: 2.1572060472626296e-05 loss: 0.0434 (0.0437) time: 2.6186 data: 0.0061 max mem: 33369 +Epoch: [24] [ 380/1319] eta: 0:41:01 lr: 2.156269601850986e-05 loss: 0.0437 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data: 0.0058 max mem: 33369 +Epoch: [24] [ 700/1319] eta: 0:27:04 lr: 2.126279356522932e-05 loss: 0.0426 (0.0443) time: 2.6039 data: 0.0058 max mem: 33369 +Epoch: [24] [ 710/1319] eta: 0:26:38 lr: 2.1253414070421574e-05 loss: 0.0420 (0.0444) time: 2.6467 data: 0.0058 max mem: 33369 +Epoch: [24] [ 720/1319] eta: 0:26:12 lr: 2.1244034115665552e-05 loss: 0.0460 (0.0444) time: 2.6467 data: 0.0059 max mem: 33369 +Epoch: [24] [ 730/1319] eta: 0:25:45 lr: 2.1234653700713027e-05 loss: 0.0404 (0.0443) time: 2.6276 data: 0.0060 max mem: 33369 +Epoch: [24] [ 740/1319] eta: 0:25:19 lr: 2.122527282531552e-05 loss: 0.0418 (0.0443) time: 2.6225 data: 0.0060 max mem: 33369 +Epoch: [24] [ 750/1319] eta: 0:24:53 lr: 2.12158914892243e-05 loss: 0.0418 (0.0442) time: 2.6010 data: 0.0058 max mem: 33369 +Epoch: [24] [ 760/1319] eta: 0:24:27 lr: 2.120650969219037e-05 loss: 0.0368 (0.0442) time: 2.6373 data: 0.0058 max mem: 33369 +Epoch: [24] [ 770/1319] eta: 0:24:01 lr: 2.1197127433964487e-05 loss: 0.0383 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2.11220527352517e-05 loss: 0.0423 (0.0443) time: 2.6113 data: 0.0059 max mem: 33369 +Epoch: [24] [ 860/1319] eta: 0:20:04 lr: 2.111266631503932e-05 loss: 0.0419 (0.0443) time: 2.6251 data: 0.0059 max mem: 33369 +Epoch: [24] [ 870/1319] eta: 0:19:38 lr: 2.1103279431128255e-05 loss: 0.0408 (0.0443) time: 2.6057 data: 0.0060 max mem: 33369 +Epoch: [24] [ 880/1319] eta: 0:19:11 lr: 2.1093892083266405e-05 loss: 0.0471 (0.0443) time: 2.6012 data: 0.0063 max mem: 33369 +Epoch: [24] [ 890/1319] eta: 0:18:45 lr: 2.10845042712014e-05 loss: 0.0446 (0.0443) time: 2.6427 data: 0.0064 max mem: 33369 +Epoch: [24] [ 900/1319] eta: 0:18:19 lr: 2.1075115994680607e-05 loss: 0.0411 (0.0444) time: 2.6453 data: 0.0064 max mem: 33369 +Epoch: [24] [ 910/1319] eta: 0:17:53 lr: 2.106572725345115e-05 loss: 0.0406 (0.0443) time: 2.6382 data: 0.0062 max mem: 33369 +Epoch: [24] [ 920/1319] eta: 0:17:27 lr: 2.105633804725987e-05 loss: 0.0338 (0.0443) time: 2.6263 data: 0.0060 max mem: 33369 +Epoch: [24] [ 930/1319] eta: 0:17:01 lr: 2.104694837585335e-05 loss: 0.0376 (0.0443) time: 2.6386 data: 0.0059 max mem: 33369 +Epoch: [24] [ 940/1319] eta: 0:16:34 lr: 2.1037558238977907e-05 loss: 0.0376 (0.0442) time: 2.6554 data: 0.0058 max mem: 33369 +Epoch: [24] [ 950/1319] eta: 0:16:08 lr: 2.1028167636379597e-05 loss: 0.0409 (0.0442) time: 2.6214 data: 0.0058 max mem: 33369 +Epoch: [24] [ 960/1319] eta: 0:15:42 lr: 2.1018776567804213e-05 loss: 0.0372 (0.0442) time: 2.5968 data: 0.0060 max mem: 33369 +Epoch: [24] [ 970/1319] eta: 0:15:16 lr: 2.1009385032997278e-05 loss: 0.0375 (0.0442) time: 2.6137 data: 0.0062 max mem: 33369 +Epoch: [24] [ 980/1319] eta: 0:14:49 lr: 2.0999993031704057e-05 loss: 0.0428 (0.0441) time: 2.6101 data: 0.0063 max mem: 33369 +Epoch: [24] [ 990/1319] eta: 0:14:23 lr: 2.0990600563669546e-05 loss: 0.0359 (0.0441) time: 2.6112 data: 0.0060 max mem: 33369 +Epoch: [24] [1000/1319] eta: 0:13:57 lr: 2.0981207628638462e-05 loss: 0.0431 (0.0441) time: 2.6328 data: 0.0060 max mem: 33369 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data: 0.0059 max mem: 33369 +Epoch: [24] [1090/1319] eta: 0:10:00 lr: 2.0896650156261064e-05 loss: 0.0396 (0.0444) time: 2.6278 data: 0.0060 max mem: 33369 +Epoch: [24] [1100/1319] eta: 0:09:34 lr: 2.0887252537165494e-05 loss: 0.0396 (0.0443) time: 2.6274 data: 0.0060 max mem: 33369 +Epoch: [24] [1110/1319] eta: 0:09:08 lr: 2.087785444824768e-05 loss: 0.0398 (0.0445) time: 2.6163 data: 0.0060 max mem: 33369 +Epoch: [24] [1120/1319] eta: 0:08:42 lr: 2.086845588924912e-05 loss: 0.0408 (0.0444) time: 2.6282 data: 0.0060 max mem: 33369 +Epoch: [24] [1130/1319] eta: 0:08:15 lr: 2.0859056859911038e-05 loss: 0.0401 (0.0446) time: 2.6271 data: 0.0058 max mem: 33369 +Epoch: [24] [1140/1319] eta: 0:07:49 lr: 2.0849657359974397e-05 loss: 0.0498 (0.0447) time: 2.6555 data: 0.0058 max mem: 33369 +Epoch: [24] [1150/1319] eta: 0:07:23 lr: 2.084025738917989e-05 loss: 0.0413 (0.0447) time: 2.6481 data: 0.0059 max mem: 33369 +Epoch: [24] [1160/1319] eta: 0:06:57 lr: 2.083085694726791e-05 loss: 0.0371 (0.0446) time: 2.6221 data: 0.0060 max mem: 33369 +Epoch: [24] [1170/1319] eta: 0:06:31 lr: 2.0821456033978605e-05 loss: 0.0397 (0.0447) time: 2.6405 data: 0.0058 max mem: 33369 +Epoch: [24] [1180/1319] eta: 0:06:04 lr: 2.0812054649051834e-05 loss: 0.0423 (0.0447) time: 2.6257 data: 0.0058 max mem: 33369 +Epoch: [24] [1190/1319] eta: 0:05:38 lr: 2.0802652792227197e-05 loss: 0.0435 (0.0447) time: 2.6146 data: 0.0059 max mem: 33369 +Epoch: [24] [1200/1319] eta: 0:05:12 lr: 2.0793250463244006e-05 loss: 0.0456 (0.0448) time: 2.6168 data: 0.0058 max mem: 33369 +Epoch: [24] [1210/1319] eta: 0:04:46 lr: 2.07838476618413e-05 loss: 0.0417 (0.0448) time: 2.6166 data: 0.0058 max mem: 33369 +Epoch: [24] [1220/1319] eta: 0:04:19 lr: 2.077444438775784e-05 loss: 0.0417 (0.0448) time: 2.6316 data: 0.0059 max mem: 33369 +Epoch: [24] [1230/1319] eta: 0:03:53 lr: 2.0765040640732118e-05 loss: 0.0485 (0.0448) time: 2.6047 data: 0.0061 max mem: 33369 +Epoch: [24] [1240/1319] eta: 0:03:27 lr: 2.0755636420502354e-05 loss: 0.0460 (0.0449) time: 2.5802 data: 0.0060 max mem: 33369 +Epoch: [24] [1250/1319] eta: 0:03:01 lr: 2.074623172680648e-05 loss: 0.0440 (0.0449) time: 2.5986 data: 0.0060 max mem: 33369 +Epoch: [24] [1260/1319] eta: 0:02:34 lr: 2.0736826559382146e-05 loss: 0.0440 (0.0449) time: 2.6216 data: 0.0059 max mem: 33369 +Epoch: [24] [1270/1319] eta: 0:02:08 lr: 2.072742091796674e-05 loss: 0.0459 (0.0449) time: 2.6264 data: 0.0059 max mem: 33369 +Epoch: [24] [1280/1319] eta: 0:01:42 lr: 2.071801480229737e-05 loss: 0.0442 (0.0449) time: 2.6152 data: 0.0059 max mem: 33369 +Epoch: [24] [1290/1319] eta: 0:01:16 lr: 2.0708608212110852e-05 loss: 0.0418 (0.0449) time: 2.6352 data: 0.0060 max mem: 33369 +Epoch: [24] [1300/1319] eta: 0:00:49 lr: 2.0699201147143737e-05 loss: 0.0445 (0.0450) time: 2.6302 data: 0.0059 max mem: 33369 +Epoch: [24] [1310/1319] eta: 0:00:23 lr: 2.0689793607132295e-05 loss: 0.0400 (0.0450) time: 2.6045 data: 0.0057 max mem: 33369 +Epoch: [24] Total time: 0:57:40 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 2:04:48 time: 2.9104 data: 2.8315 max mem: 33369 +Test: [ 100/2573] eta: 0:04:07 time: 0.0716 data: 0.0011 max mem: 33369 +Test: [ 200/2573] eta: 0:03:26 time: 0.0733 data: 0.0011 max mem: 33369 +Test: [ 300/2573] eta: 0:03:06 time: 0.0751 data: 0.0011 max mem: 33369 +Test: [ 400/2573] eta: 0:02:53 time: 0.0751 data: 0.0011 max mem: 33369 +Test: [ 500/2573] eta: 0:02:43 time: 0.0735 data: 0.0011 max mem: 33369 +Test: [ 600/2573] eta: 0:02:33 time: 0.0737 data: 0.0011 max mem: 33369 +Test: [ 700/2573] eta: 0:02:25 time: 0.0736 data: 0.0011 max mem: 33369 +Test: [ 800/2573] eta: 0:02:16 time: 0.0770 data: 0.0011 max mem: 33369 +Test: [ 900/2573] eta: 0:02:08 time: 0.0738 data: 0.0011 max mem: 33369 +Test: [1000/2573] eta: 0:02:00 time: 0.0737 data: 0.0011 max mem: 33369 +Test: [1100/2573] eta: 0:01:52 time: 0.0737 data: 0.0011 max mem: 33369 +Test: [1200/2573] eta: 0:01:44 time: 0.0738 data: 0.0011 max mem: 33369 +Test: [1300/2573] eta: 0:01:36 time: 0.0737 data: 0.0011 max mem: 33369 +Test: [1400/2573] eta: 0:01:28 time: 0.0721 data: 0.0011 max mem: 33369 +Test: [1500/2573] eta: 0:01:21 time: 0.0738 data: 0.0011 max mem: 33369 +Test: [1600/2573] eta: 0:01:13 time: 0.0771 data: 0.0011 max mem: 33369 +Test: [1700/2573] eta: 0:01:05 time: 0.0722 data: 0.0011 max mem: 33369 +Test: [1800/2573] eta: 0:00:58 time: 0.0754 data: 0.0011 max mem: 33369 +Test: [1900/2573] eta: 0:00:50 time: 0.0720 data: 0.0011 max mem: 33369 +Test: [2000/2573] eta: 0:00:43 time: 0.0738 data: 0.0011 max mem: 33369 +Test: [2100/2573] eta: 0:00:35 time: 0.0754 data: 0.0011 max mem: 33369 +Test: [2200/2573] eta: 0:00:27 time: 0.0754 data: 0.0011 max mem: 33369 +Test: [2300/2573] eta: 0:00:20 time: 0.0753 data: 0.0011 max mem: 33369 +Test: [2400/2573] eta: 0:00:12 time: 0.0704 data: 0.0011 max mem: 33369 +Test: [2500/2573] eta: 0:00:05 time: 0.0739 data: 0.0011 max mem: 33369 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: Total time: 0:03:12 +Final results: +Mean IoU is 63.70 + + precision@0.5 = 71.30 + precision@0.6 = 66.65 + precision@0.7 = 59.70 + precision@0.8 = 48.16 + precision@0.9 = 23.84 + overall IoU = 60.99 + +Average object IoU 63.697240696677326 +Overall IoU 60.9853515625 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [25] [ 0/1319] eta: 3:07:19 lr: 2.0681326414740886e-05 loss: 0.0994 (0.0994) time: 8.5209 data: 1.2799 max mem: 33369 +Epoch: [25] [ 10/1319] eta: 1:09:42 lr: 2.0671917971417626e-05 loss: 0.0378 (0.0466) time: 3.1953 data: 0.1219 max mem: 33369 +Epoch: [25] [ 20/1319] eta: 1:03:29 lr: 2.0662509052283616e-05 loss: 0.0400 (0.0494) time: 2.6531 data: 0.0061 max mem: 33369 +Epoch: [25] [ 30/1319] eta: 1:01:03 lr: 2.0653099657074033e-05 loss: 0.0368 (0.0448) time: 2.6475 data: 0.0061 max mem: 33369 +Epoch: [25] [ 40/1319] eta: 0:59:27 lr: 2.064368978552377e-05 loss: 0.0331 (0.0435) time: 2.6386 data: 0.0062 max mem: 33369 +Epoch: [25] [ 50/1319] eta: 0:58:19 lr: 2.0634279437367437e-05 loss: 0.0327 (0.0422) time: 2.6270 data: 0.0061 max mem: 33369 +Epoch: [25] [ 60/1319] eta: 0:57:25 lr: 2.0624868612339364e-05 loss: 0.0323 (0.0408) time: 2.6294 data: 0.0060 max mem: 33369 +Epoch: [25] [ 70/1319] eta: 0:56:40 lr: 2.0615457310173584e-05 loss: 0.0315 (0.0409) time: 2.6339 data: 0.0060 max mem: 33369 +Epoch: [25] [ 80/1319] eta: 0:55:59 lr: 2.0606045530603866e-05 loss: 0.0350 (0.0407) time: 2.6347 data: 0.0059 max mem: 33369 +Epoch: [25] [ 90/1319] eta: 0:55:20 lr: 2.059663327336368e-05 loss: 0.0402 (0.0413) time: 2.6258 data: 0.0060 max mem: 33369 +Epoch: [25] [ 100/1319] eta: 0:54:46 lr: 2.058722053818622e-05 loss: 0.0358 (0.0405) time: 2.6339 data: 0.0062 max mem: 33369 +Epoch: [25] [ 110/1319] eta: 0:54:13 lr: 2.0577807324804403e-05 loss: 0.0364 (0.0415) time: 2.6449 data: 0.0061 max mem: 33369 +Epoch: [25] [ 120/1319] eta: 0:53:38 lr: 2.0568393632950847e-05 loss: 0.0388 (0.0416) time: 2.6236 data: 0.0061 max mem: 33369 +Epoch: [25] [ 130/1319] eta: 0:53:04 lr: 2.055897946235788e-05 loss: 0.0459 (0.0423) time: 2.6048 data: 0.0063 max mem: 33369 +Epoch: [25] [ 140/1319] eta: 0:52:31 lr: 2.054956481275756e-05 loss: 0.0425 (0.0420) time: 2.6044 data: 0.0062 max mem: 33369 +Epoch: [25] [ 150/1319] eta: 0:52:03 lr: 2.0540149683881653e-05 loss: 0.0385 (0.0423) time: 2.6333 data: 0.0059 max mem: 33369 +Epoch: [25] [ 160/1319] eta: 0:51:36 lr: 2.0530734075461633e-05 loss: 0.0375 (0.0421) time: 2.6654 data: 0.0060 max mem: 33369 +Epoch: [25] [ 170/1319] eta: 0:51:06 lr: 2.05213179872287e-05 loss: 0.0349 (0.0420) time: 2.6427 data: 0.0061 max mem: 33369 +Epoch: [25] [ 180/1319] eta: 0:50:36 lr: 2.051190141891374e-05 loss: 0.0349 (0.0417) time: 2.6198 data: 0.0061 max mem: 33369 +Epoch: [25] [ 190/1319] eta: 0:50:08 lr: 2.050248437024738e-05 loss: 0.0362 (0.0418) time: 2.6285 data: 0.0059 max mem: 33369 +Epoch: [25] [ 200/1319] eta: 0:49:38 lr: 2.049306684095994e-05 loss: 0.0375 (0.0416) time: 2.6227 data: 0.0060 max mem: 33369 +Epoch: [25] [ 210/1319] eta: 0:49:09 lr: 2.048364883078146e-05 loss: 0.0383 (0.0419) time: 2.6150 data: 0.0062 max mem: 33369 +Epoch: [25] [ 220/1319] eta: 0:48:41 lr: 2.0474230339441687e-05 loss: 0.0392 (0.0424) time: 2.6201 data: 0.0061 max mem: 33369 +Epoch: [25] [ 230/1319] eta: 0:48:13 lr: 2.0464811366670074e-05 loss: 0.0415 (0.0425) time: 2.6251 data: 0.0061 max mem: 33369 +Epoch: [25] [ 240/1319] eta: 0:47:43 lr: 2.0455391912195788e-05 loss: 0.0424 (0.0426) time: 2.6044 data: 0.0061 max mem: 33369 +Epoch: [25] [ 250/1319] eta: 0:47:15 lr: 2.0445971975747706e-05 loss: 0.0424 (0.0426) time: 2.5988 data: 0.0061 max mem: 33369 +Epoch: [25] [ 260/1319] eta: 0:46:46 lr: 2.0436551557054405e-05 loss: 0.0378 (0.0425) time: 2.6100 data: 0.0061 max mem: 33369 +Epoch: [25] [ 270/1319] eta: 0:46:17 lr: 2.0427130655844186e-05 loss: 0.0378 (0.0425) time: 2.5960 data: 0.0061 max mem: 33369 +Epoch: [25] [ 280/1319] eta: 0:45:50 lr: 2.041770927184505e-05 loss: 0.0352 (0.0423) time: 2.6120 data: 0.0060 max mem: 33369 +Epoch: [25] [ 290/1319] eta: 0:45:21 lr: 2.0408287404784693e-05 loss: 0.0318 (0.0421) time: 2.6071 data: 0.0059 max mem: 33369 +Epoch: [25] [ 300/1319] eta: 0:44:53 lr: 2.0398865054390533e-05 loss: 0.0346 (0.0423) time: 2.5904 data: 0.0060 max mem: 33369 +Epoch: [25] [ 310/1319] eta: 0:44:27 lr: 2.038944222038969e-05 loss: 0.0397 (0.0423) time: 2.6246 data: 0.0060 max mem: 33369 +Epoch: [25] [ 320/1319] eta: 0:44:00 lr: 2.0380018902508984e-05 loss: 0.0366 (0.0420) time: 2.6341 data: 0.0061 max mem: 33369 +Epoch: [25] [ 330/1319] eta: 0:43:32 lr: 2.0370595100474957e-05 loss: 0.0349 (0.0420) time: 2.6109 data: 0.0060 max mem: 33369 +Epoch: [25] [ 340/1319] eta: 0:43:04 lr: 2.036117081401383e-05 loss: 0.0362 (0.0419) time: 2.5867 data: 0.0059 max mem: 33369 +Epoch: [25] [ 350/1319] eta: 0:42:37 lr: 2.035174604285155e-05 loss: 0.0395 (0.0420) time: 2.5937 data: 0.0060 max mem: 33369 +Epoch: [25] [ 360/1319] eta: 0:42:11 lr: 2.0342320786713757e-05 loss: 0.0442 (0.0421) time: 2.6381 data: 0.0059 max mem: 33369 +Epoch: [25] [ 370/1319] eta: 0:41:43 lr: 2.03328950453258e-05 loss: 0.0375 (0.0420) time: 2.6278 data: 0.0059 max mem: 33369 +Epoch: [25] [ 380/1319] eta: 0:41:17 lr: 2.0323468818412736e-05 loss: 0.0388 (0.0420) time: 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(0.0427) time: 2.6210 data: 0.0059 max mem: 33369 +Epoch: [25] [ 860/1319] eta: 0:20:06 lr: 1.987043348451999e-05 loss: 0.0411 (0.0427) time: 2.5984 data: 0.0060 max mem: 33369 +Epoch: [25] [ 870/1319] eta: 0:19:39 lr: 1.9860983123743625e-05 loss: 0.0363 (0.0426) time: 2.5898 data: 0.0060 max mem: 33369 +Epoch: [25] [ 880/1319] eta: 0:19:13 lr: 1.9851532263305046e-05 loss: 0.0369 (0.0426) time: 2.6075 data: 0.0059 max mem: 33369 +Epoch: [25] [ 890/1319] eta: 0:18:47 lr: 1.98420809029135e-05 loss: 0.0438 (0.0427) time: 2.6059 data: 0.0059 max mem: 33369 +Epoch: [25] [ 900/1319] eta: 0:18:20 lr: 1.9832629042277908e-05 loss: 0.0412 (0.0426) time: 2.5918 data: 0.0059 max mem: 33369 +Epoch: [25] [ 910/1319] eta: 0:17:54 lr: 1.982317668110687e-05 loss: 0.0333 (0.0425) time: 2.5932 data: 0.0061 max mem: 33369 +Epoch: [25] [ 920/1319] eta: 0:17:27 lr: 1.981372381910867e-05 loss: 0.0337 (0.0425) time: 2.6016 data: 0.0062 max mem: 33369 +Epoch: [25] [ 930/1319] eta: 0:17:01 lr: 1.980427045599124e-05 loss: 0.0397 (0.0426) time: 2.6229 data: 0.0060 max mem: 33369 +Epoch: [25] [ 940/1319] eta: 0:16:35 lr: 1.9794816591462205e-05 loss: 0.0397 (0.0425) time: 2.6240 data: 0.0058 max mem: 33369 +Epoch: [25] [ 950/1319] eta: 0:16:09 lr: 1.9785362225228878e-05 loss: 0.0354 (0.0425) time: 2.6126 data: 0.0059 max mem: 33369 +Epoch: [25] [ 960/1319] eta: 0:15:42 lr: 1.9775907356998215e-05 loss: 0.0363 (0.0424) time: 2.6215 data: 0.0058 max mem: 33369 +Epoch: [25] [ 970/1319] eta: 0:15:16 lr: 1.976645198647688e-05 loss: 0.0385 (0.0424) time: 2.6593 data: 0.0058 max mem: 33369 +Epoch: [25] [ 980/1319] eta: 0:14:50 lr: 1.9756996113371165e-05 loss: 0.0373 (0.0424) time: 2.6594 data: 0.0059 max mem: 33369 +Epoch: [25] [ 990/1319] eta: 0:14:24 lr: 1.9747539737387077e-05 loss: 0.0407 (0.0424) time: 2.6232 data: 0.0059 max mem: 33369 +Epoch: [25] [1000/1319] eta: 0:13:57 lr: 1.973808285823027e-05 loss: 0.0424 (0.0424) time: 2.6236 data: 0.0057 max mem: 33369 +Epoch: [25] 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data: 0.0059 max mem: 33369 +Epoch: [25] [1170/1319] eta: 0:06:31 lr: 1.9577238640321492e-05 loss: 0.0356 (0.0427) time: 2.6238 data: 0.0059 max mem: 33369 +Epoch: [25] [1180/1319] eta: 0:06:05 lr: 1.9567772653346e-05 loss: 0.0396 (0.0427) time: 2.6302 data: 0.0059 max mem: 33369 +Epoch: [25] [1190/1319] eta: 0:05:38 lr: 1.9558306157542204e-05 loss: 0.0395 (0.0428) time: 2.6351 data: 0.0059 max mem: 33369 +Epoch: [25] [1200/1319] eta: 0:05:12 lr: 1.9548839152609067e-05 loss: 0.0395 (0.0428) time: 2.6211 data: 0.0059 max mem: 33369 +Epoch: [25] [1210/1319] eta: 0:04:46 lr: 1.9539371638245233e-05 loss: 0.0352 (0.0428) time: 2.6143 data: 0.0058 max mem: 33369 +Epoch: [25] [1220/1319] eta: 0:04:19 lr: 1.952990361414899e-05 loss: 0.0398 (0.0428) time: 2.6210 data: 0.0058 max mem: 33369 +Epoch: [25] [1230/1319] eta: 0:03:53 lr: 1.9520435080018294e-05 loss: 0.0440 (0.0428) time: 2.6252 data: 0.0060 max mem: 33369 +Epoch: [25] [1240/1319] eta: 0:03:27 lr: 1.9510966035550763e-05 loss: 0.0489 (0.0428) time: 2.6168 data: 0.0059 max mem: 33369 +Epoch: [25] [1250/1319] eta: 0:03:01 lr: 1.9501496480443652e-05 loss: 0.0510 (0.0429) time: 2.5982 data: 0.0058 max mem: 33369 +Epoch: [25] [1260/1319] eta: 0:02:34 lr: 1.9492026414393892e-05 loss: 0.0436 (0.0429) time: 2.6061 data: 0.0058 max mem: 33369 +Epoch: [25] [1270/1319] eta: 0:02:08 lr: 1.9482555837098063e-05 loss: 0.0436 (0.0430) time: 2.6195 data: 0.0058 max mem: 33369 +Epoch: [25] [1280/1319] eta: 0:01:42 lr: 1.9473084748252403e-05 loss: 0.0382 (0.0429) time: 2.6094 data: 0.0059 max mem: 33369 +Epoch: [25] [1290/1319] eta: 0:01:16 lr: 1.9463613147552807e-05 loss: 0.0374 (0.0429) time: 2.5944 data: 0.0060 max mem: 33369 +Epoch: [25] [1300/1319] eta: 0:00:49 lr: 1.9454141034694828e-05 loss: 0.0386 (0.0429) time: 2.6131 data: 0.0060 max mem: 33369 +Epoch: [25] [1310/1319] eta: 0:00:23 lr: 1.9444668409373652e-05 loss: 0.0355 (0.0429) time: 2.6106 data: 0.0059 max mem: 33369 +Epoch: [25] Total time: 0:57:42 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 1:49:08 time: 2.5452 data: 2.4387 max mem: 33369 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 100/2573] eta: 0:03:59 time: 0.0715 data: 0.0011 max mem: 33369 +Test: [ 200/2573] eta: 0:03:23 time: 0.0732 data: 0.0011 max mem: 33369 +Test: [ 300/2573] eta: 0:03:04 time: 0.0749 data: 0.0011 max mem: 33369 +Test: [ 400/2573] eta: 0:02:51 time: 0.0751 data: 0.0011 max mem: 33369 +Test: [ 500/2573] eta: 0:02:41 time: 0.0734 data: 0.0011 max mem: 33369 +Test: [ 600/2573] eta: 0:02:32 time: 0.0735 data: 0.0011 max mem: 33369 +Test: [ 700/2573] eta: 0:02:24 time: 0.0735 data: 0.0011 max mem: 33369 +Test: [ 800/2573] eta: 0:02:16 time: 0.0770 data: 0.0011 max mem: 33369 +Test: [ 900/2573] eta: 0:02:08 time: 0.0737 data: 0.0011 max mem: 33369 +Test: [1000/2573] eta: 0:02:00 time: 0.0736 data: 0.0011 max mem: 33369 +Test: [1100/2573] eta: 0:01:52 time: 0.0738 data: 0.0011 max mem: 33369 +Test: [1200/2573] eta: 0:01:44 time: 0.0736 data: 0.0010 max mem: 33369 +Test: [1300/2573] eta: 0:01:36 time: 0.0737 data: 0.0011 max mem: 33369 +Test: [1400/2573] eta: 0:01:28 time: 0.0721 data: 0.0012 max mem: 33369 +Test: [1500/2573] eta: 0:01:21 time: 0.0736 data: 0.0011 max mem: 33369 +Test: [1600/2573] eta: 0:01:13 time: 0.0770 data: 0.0011 max mem: 33369 +Test: [1700/2573] eta: 0:01:05 time: 0.0720 data: 0.0011 max mem: 33369 +Test: [1800/2573] eta: 0:00:58 time: 0.0753 data: 0.0011 max mem: 33369 +Test: [1900/2573] eta: 0:00:50 time: 0.0721 data: 0.0011 max mem: 33369 +Test: [2000/2573] eta: 0:00:42 time: 0.0737 data: 0.0011 max mem: 33369 +Test: [2100/2573] eta: 0:00:35 time: 0.0754 data: 0.0011 max mem: 33369 +Test: [2200/2573] eta: 0:00:27 time: 0.0754 data: 0.0011 max mem: 33369 +Test: [2300/2573] eta: 0:00:20 time: 0.0756 data: 0.0011 max mem: 33369 +Test: [2400/2573] eta: 0:00:12 time: 0.0704 data: 0.0011 max mem: 33369 +Test: [2500/2573] eta: 0:00:05 time: 0.0738 data: 0.0011 max mem: 33369 +Test: Total time: 0:03:12 +Final results: +Mean IoU is 63.53 + + precision@0.5 = 71.14 + precision@0.6 = 65.99 + precision@0.7 = 59.87 + precision@0.8 = 48.79 + precision@0.9 = 23.53 + overall IoU = 61.00 + +Average object IoU 63.52941584455662 +Overall IoU 60.995513916015625 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [26] [ 0/1319] eta: 3:18:21 lr: 1.943614260817638e-05 loss: 0.0381 (0.0381) time: 9.0230 data: 1.3254 max mem: 33369 +Epoch: [26] [ 10/1319] eta: 1:10:06 lr: 1.9426669008334188e-05 loss: 0.0381 (0.0398) time: 3.2134 data: 0.1255 max mem: 33369 +Epoch: [26] [ 20/1319] eta: 1:03:09 lr: 1.941719489514293e-05 loss: 0.0358 (0.0376) time: 2.6119 data: 0.0056 max mem: 33369 +Epoch: [26] [ 30/1319] eta: 1:00:17 lr: 1.9407720268296455e-05 loss: 0.0386 (0.0393) time: 2.5830 data: 0.0060 max mem: 33369 +Epoch: [26] [ 40/1319] eta: 0:58:46 lr: 1.9398245127488253e-05 loss: 0.0344 (0.0384) time: 2.5901 data: 0.0061 max mem: 33369 +Epoch: [26] [ 50/1319] eta: 0:57:48 lr: 1.9388769472411493e-05 loss: 0.0334 (0.0393) time: 2.6197 data: 0.0058 max mem: 33369 +Epoch: [26] [ 60/1319] eta: 0:56:56 lr: 1.9379293302758954e-05 loss: 0.0330 (0.0395) time: 2.6241 data: 0.0061 max mem: 33369 +Epoch: [26] [ 70/1319] eta: 0:56:02 lr: 1.936981661822309e-05 loss: 0.0368 (0.0416) time: 2.5864 data: 0.0061 max mem: 33369 +Epoch: [26] [ 80/1319] eta: 0:55:25 lr: 1.9360339418495996e-05 loss: 0.0389 (0.0416) time: 2.5930 data: 0.0060 max mem: 33369 +Epoch: [26] [ 90/1319] eta: 0:54:52 lr: 1.935086170326942e-05 loss: 0.0360 (0.0414) time: 2.6328 data: 0.0060 max mem: 33369 +Epoch: [26] [ 100/1319] eta: 0:54:19 lr: 1.934138347223476e-05 loss: 0.0372 (0.0415) time: 2.6327 data: 0.0060 max mem: 33369 +Epoch: [26] [ 110/1319] eta: 0:53:45 lr: 1.9331904725083057e-05 loss: 0.0409 (0.0417) time: 2.6176 data: 0.0060 max mem: 33369 +Epoch: [26] [ 120/1319] eta: 0:53:10 lr: 1.9322425461504988e-05 loss: 0.0430 (0.0417) time: 2.5939 data: 0.0059 max mem: 33369 +Epoch: [26] [ 130/1319] eta: 0:52:40 lr: 1.931294568119089e-05 loss: 0.0430 (0.0418) time: 2.6050 data: 0.0060 max mem: 33369 +Epoch: [26] [ 140/1319] eta: 0:52:06 lr: 1.930346538383074e-05 loss: 0.0422 (0.0419) time: 2.5995 data: 0.0062 max mem: 33369 +Epoch: [26] [ 150/1319] eta: 0:51:39 lr: 1.9293984569114164e-05 loss: 0.0403 (0.0419) time: 2.6093 data: 0.0062 max mem: 33369 +Epoch: [26] [ 160/1319] eta: 0:51:12 lr: 1.9284503236730435e-05 loss: 0.0370 (0.0417) time: 2.6467 data: 0.0062 max mem: 33369 +Epoch: [26] [ 170/1319] eta: 0:50:44 lr: 1.927502138636845e-05 loss: 0.0409 (0.0421) time: 2.6309 data: 0.0062 max mem: 33369 +Epoch: [26] [ 180/1319] eta: 0:50:16 lr: 1.9265539017716765e-05 loss: 0.0378 (0.0417) time: 2.6247 data: 0.0060 max mem: 33369 +Epoch: [26] [ 190/1319] eta: 0:49:46 lr: 1.9256056130463582e-05 loss: 0.0372 (0.0419) time: 2.6090 data: 0.0058 max mem: 33369 +Epoch: [26] [ 200/1319] eta: 0:49:18 lr: 1.9246572724296735e-05 loss: 0.0411 (0.0419) time: 2.6012 data: 0.0059 max mem: 33369 +Epoch: [26] [ 210/1319] eta: 0:48:50 lr: 1.9237088798903708e-05 loss: 0.0364 (0.0417) time: 2.6212 data: 0.0061 max mem: 33369 +Epoch: [26] [ 220/1319] eta: 0:48:21 lr: 1.922760435397161e-05 loss: 0.0364 (0.0418) time: 2.6063 data: 0.0060 max mem: 33369 +Epoch: [26] [ 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33369 +Epoch: [26] [ 310/1319] eta: 0:44:15 lr: 1.9142220918520593e-05 loss: 0.0319 (0.0413) time: 2.6352 data: 0.0059 max mem: 33369 +Epoch: [26] [ 320/1319] eta: 0:43:49 lr: 1.9132731260909836e-05 loss: 0.0320 (0.0416) time: 2.6432 data: 0.0060 max mem: 33369 +Epoch: [26] [ 330/1319] eta: 0:43:23 lr: 1.9123241080294413e-05 loss: 0.0343 (0.0416) time: 2.6312 data: 0.0060 max mem: 33369 +Epoch: [26] [ 340/1319] eta: 0:42:56 lr: 1.9113750376357084e-05 loss: 0.0368 (0.0416) time: 2.6184 data: 0.0061 max mem: 33369 +Epoch: [26] [ 350/1319] eta: 0:42:29 lr: 1.9104259148780233e-05 loss: 0.0325 (0.0413) time: 2.6206 data: 0.0062 max mem: 33369 +Epoch: [26] [ 360/1319] eta: 0:42:04 lr: 1.909476739724589e-05 loss: 0.0363 (0.0412) time: 2.6396 data: 0.0062 max mem: 33369 +Epoch: [26] [ 370/1319] eta: 0:41:37 lr: 1.9085275121435705e-05 loss: 0.0391 (0.0412) time: 2.6276 data: 0.0061 max mem: 33369 +Epoch: [26] [ 380/1319] eta: 0:41:11 lr: 1.907578232103095e-05 loss: 0.0416 (0.0412) time: 2.6245 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1.892382590817894e-05 loss: 0.0366 (0.0412) time: 2.6315 data: 0.0060 max mem: 33369 +Epoch: [26] [ 550/1319] eta: 0:33:39 lr: 1.8914324140541728e-05 loss: 0.0414 (0.0413) time: 2.6002 data: 0.0062 max mem: 33369 +Epoch: [26] [ 560/1319] eta: 0:33:13 lr: 1.8904821842509134e-05 loss: 0.0402 (0.0412) time: 2.6122 data: 0.0063 max mem: 33369 +Epoch: [26] [ 570/1319] eta: 0:32:47 lr: 1.889531901375529e-05 loss: 0.0366 (0.0412) time: 2.6362 data: 0.0064 max mem: 33369 +Epoch: [26] [ 580/1319] eta: 0:32:21 lr: 1.888581565395396e-05 loss: 0.0356 (0.0411) time: 2.6279 data: 0.0061 max mem: 33369 +Epoch: [26] [ 590/1319] eta: 0:31:54 lr: 1.8876311762778523e-05 loss: 0.0347 (0.0411) time: 2.6279 data: 0.0059 max mem: 33369 +Epoch: [26] [ 600/1319] eta: 0:31:28 lr: 1.8866807339901958e-05 loss: 0.0347 (0.0410) time: 2.6169 data: 0.0059 max mem: 33369 +Epoch: [26] [ 610/1319] eta: 0:31:02 lr: 1.885730238499688e-05 loss: 0.0370 (0.0411) time: 2.6212 data: 0.0059 max mem: 33369 +Epoch: [26] [ 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data: 0.0063 max mem: 33369 +Epoch: [26] [ 780/1319] eta: 0:23:34 lr: 1.8695636432127905e-05 loss: 0.0400 (0.0410) time: 2.6385 data: 0.0060 max mem: 33369 +Epoch: [26] [ 790/1319] eta: 0:23:08 lr: 1.8686121844283114e-05 loss: 0.0368 (0.0410) time: 2.6467 data: 0.0059 max mem: 33369 +Epoch: [26] [ 800/1319] eta: 0:22:42 lr: 1.8676606718115407e-05 loss: 0.0338 (0.0410) time: 2.6675 data: 0.0059 max mem: 33369 +Epoch: [26] [ 810/1319] eta: 0:22:16 lr: 1.866709105328956e-05 loss: 0.0348 (0.0410) time: 2.6399 data: 0.0059 max mem: 33369 +Epoch: [26] [ 820/1319] eta: 0:21:49 lr: 1.8657574849469954e-05 loss: 0.0334 (0.0409) time: 2.6166 data: 0.0058 max mem: 33369 +Epoch: [26] [ 830/1319] eta: 0:21:23 lr: 1.864805810632056e-05 loss: 0.0334 (0.0408) time: 2.6219 data: 0.0058 max mem: 33369 +Epoch: [26] [ 840/1319] eta: 0:20:57 lr: 1.8638540823504965e-05 loss: 0.0332 (0.0407) time: 2.6090 data: 0.0059 max mem: 33369 +Epoch: [26] [ 850/1319] eta: 0:20:30 lr: 1.8629023000686338e-05 loss: 0.0333 (0.0407) time: 2.5896 data: 0.0059 max mem: 33369 +Epoch: [26] [ 860/1319] eta: 0:20:04 lr: 1.8619504637527467e-05 loss: 0.0358 (0.0407) time: 2.6005 data: 0.0059 max mem: 33369 +Epoch: [26] [ 870/1319] eta: 0:19:38 lr: 1.8609985733690715e-05 loss: 0.0378 (0.0407) time: 2.6139 data: 0.0060 max mem: 33369 +Epoch: [26] [ 880/1319] eta: 0:19:11 lr: 1.860046628883806e-05 loss: 0.0382 (0.0407) time: 2.6055 data: 0.0060 max mem: 33369 +Epoch: [26] [ 890/1319] eta: 0:18:45 lr: 1.859094630263106e-05 loss: 0.0410 (0.0407) time: 2.5894 data: 0.0059 max mem: 33369 +Epoch: [26] [ 900/1319] eta: 0:18:19 lr: 1.8581425774730882e-05 loss: 0.0363 (0.0406) time: 2.6194 data: 0.0059 max mem: 33369 +Epoch: [26] [ 910/1319] eta: 0:17:53 lr: 1.8571904704798292e-05 loss: 0.0363 (0.0406) time: 2.6273 data: 0.0058 max mem: 33369 +Epoch: [26] [ 920/1319] eta: 0:17:26 lr: 1.856238309249363e-05 loss: 0.0367 (0.0407) time: 2.6129 data: 0.0057 max mem: 33369 +Epoch: [26] [ 930/1319] eta: 0:17:00 lr: 1.855286093747684e-05 loss: 0.0373 (0.0407) time: 2.6348 data: 0.0057 max mem: 33369 +Epoch: [26] [ 940/1319] eta: 0:16:34 lr: 1.854333823940747e-05 loss: 0.0376 (0.0406) time: 2.6409 data: 0.0058 max mem: 33369 +Epoch: [26] [ 950/1319] eta: 0:16:08 lr: 1.853381499794464e-05 loss: 0.0344 (0.0406) time: 2.6189 data: 0.0057 max mem: 33369 +Epoch: [26] [ 960/1319] eta: 0:15:41 lr: 1.8524291212747084e-05 loss: 0.0374 (0.0406) time: 2.6246 data: 0.0057 max mem: 33369 +Epoch: [26] [ 970/1319] eta: 0:15:15 lr: 1.85147668834731e-05 loss: 0.0362 (0.0406) time: 2.6380 data: 0.0057 max mem: 33369 +Epoch: [26] [ 980/1319] eta: 0:14:49 lr: 1.8505242009780593e-05 loss: 0.0338 (0.0406) time: 2.6082 data: 0.0059 max mem: 33369 +Epoch: [26] [ 990/1319] eta: 0:14:23 lr: 1.8495716591327057e-05 loss: 0.0353 (0.0405) time: 2.6101 data: 0.0059 max mem: 33369 +Epoch: [26] [1000/1319] eta: 0:13:56 lr: 1.848619062776957e-05 loss: 0.0367 (0.0406) time: 2.6364 data: 0.0057 max mem: 33369 +Epoch: [26] [1010/1319] eta: 0:13:30 lr: 1.8476664118764797e-05 loss: 0.0353 (0.0405) time: 2.6165 data: 0.0058 max mem: 33369 +Epoch: [26] [1020/1319] eta: 0:13:04 lr: 1.8467137063969e-05 loss: 0.0353 (0.0406) time: 2.5990 data: 0.0060 max mem: 33369 +Epoch: [26] [1030/1319] eta: 0:12:38 lr: 1.8457609463038007e-05 loss: 0.0388 (0.0406) time: 2.6125 data: 0.0059 max mem: 33369 +Epoch: [26] [1040/1319] eta: 0:12:12 lr: 1.8448081315627246e-05 loss: 0.0351 (0.0405) time: 2.6477 data: 0.0058 max mem: 33369 +Epoch: [26] [1050/1319] eta: 0:11:45 lr: 1.843855262139173e-05 loss: 0.0329 (0.0405) time: 2.6460 data: 0.0059 max mem: 33369 +Epoch: [26] [1060/1319] eta: 0:11:19 lr: 1.8429023379986053e-05 loss: 0.0351 (0.0405) time: 2.6200 data: 0.0061 max mem: 33369 +Epoch: [26] [1070/1319] eta: 0:10:53 lr: 1.8419493591064395e-05 loss: 0.0361 (0.0406) time: 2.6006 data: 0.0061 max mem: 33369 +Epoch: [26] [1080/1319] eta: 0:10:26 lr: 1.840996325428051e-05 loss: 0.0363 (0.0406) time: 2.6111 data: 0.0060 max mem: 33369 +Epoch: [26] [1090/1319] eta: 0:10:00 lr: 1.840043236928774e-05 loss: 0.0355 (0.0406) time: 2.6280 data: 0.0060 max mem: 33369 +Epoch: [26] [1100/1319] eta: 0:09:34 lr: 1.839090093573901e-05 loss: 0.0445 (0.0406) time: 2.6142 data: 0.0060 max mem: 33369 +Epoch: [26] [1110/1319] eta: 0:09:08 lr: 1.838136895328682e-05 loss: 0.0447 (0.0407) time: 2.6103 data: 0.0060 max mem: 33369 +Epoch: [26] [1120/1319] eta: 0:08:42 lr: 1.8371836421583257e-05 loss: 0.0370 (0.0406) time: 2.6190 data: 0.0060 max mem: 33369 +Epoch: [26] [1130/1319] eta: 0:08:15 lr: 1.836230334027998e-05 loss: 0.0358 (0.0406) time: 2.6604 data: 0.0059 max mem: 33369 +Epoch: [26] [1140/1319] eta: 0:07:49 lr: 1.8352769709028224e-05 loss: 0.0374 (0.0407) time: 2.6500 data: 0.0059 max mem: 33369 +Epoch: [26] [1150/1319] eta: 0:07:23 lr: 1.8343235527478807e-05 loss: 0.0334 (0.0406) time: 2.6096 data: 0.0059 max mem: 33369 +Epoch: [26] [1160/1319] eta: 0:06:57 lr: 1.8333700795282125e-05 loss: 0.0366 (0.0406) time: 2.6378 data: 0.0058 max mem: 33369 +Epoch: [26] [1170/1319] eta: 0:06:30 lr: 1.832416551208814e-05 loss: 0.0394 (0.0407) time: 2.6484 data: 0.0057 max mem: 33369 +Epoch: [26] [1180/1319] eta: 0:06:04 lr: 1.8314629677546413e-05 loss: 0.0379 (0.0406) time: 2.6249 data: 0.0059 max mem: 33369 +Epoch: [26] [1190/1319] eta: 0:05:38 lr: 1.8305093291306038e-05 loss: 0.0381 (0.0407) time: 2.6122 data: 0.0060 max mem: 33369 +Epoch: [26] [1200/1319] eta: 0:05:12 lr: 1.829555635301572e-05 loss: 0.0384 (0.0407) time: 2.6105 data: 0.0059 max mem: 33369 +Epoch: [26] [1210/1319] eta: 0:04:45 lr: 1.8286018862323718e-05 loss: 0.0369 (0.0407) time: 2.6173 data: 0.0058 max mem: 33369 +Epoch: [26] [1220/1319] eta: 0:04:19 lr: 1.8276480818877866e-05 loss: 0.0365 (0.0406) time: 2.6313 data: 0.0059 max mem: 33369 +Epoch: [26] [1230/1319] eta: 0:03:53 lr: 1.8266942222325584e-05 loss: 0.0385 (0.0407) time: 2.6393 data: 0.0058 max mem: 33369 +Epoch: [26] [1240/1319] eta: 0:03:27 lr: 1.8257403072313833e-05 loss: 0.0328 (0.0407) time: 2.6264 data: 0.0057 max mem: 33369 +Epoch: [26] [1250/1319] eta: 0:03:01 lr: 1.8247863368489165e-05 loss: 0.0344 (0.0407) time: 2.6199 data: 0.0059 max mem: 33369 +Epoch: [26] [1260/1319] eta: 0:02:34 lr: 1.8238323110497695e-05 loss: 0.0361 (0.0408) time: 2.6358 data: 0.0058 max mem: 33369 +Epoch: [26] [1270/1319] eta: 0:02:08 lr: 1.822878229798511e-05 loss: 0.0361 (0.0407) time: 2.6258 data: 0.0058 max mem: 33369 +Epoch: [26] [1280/1319] eta: 0:01:42 lr: 1.821924093059666e-05 loss: 0.0344 (0.0407) time: 2.6017 data: 0.0059 max mem: 33369 +Epoch: [26] [1290/1319] eta: 0:01:16 lr: 1.8209699007977167e-05 loss: 0.0346 (0.0406) time: 2.6101 data: 0.0059 max mem: 33369 +Epoch: [26] [1300/1319] eta: 0:00:49 lr: 1.8200156529771002e-05 loss: 0.0348 (0.0406) time: 2.6247 data: 0.0058 max mem: 33369 +Epoch: [26] [1310/1319] eta: 0:00:23 lr: 1.819061349562212e-05 loss: 0.0372 (0.0406) time: 2.6132 data: 0.0058 max mem: 33369 +Epoch: [26] Total time: 0:57:41 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 2:02:00 time: 2.8450 data: 2.7666 max mem: 33369 +Test: [ 100/2573] eta: 0:04:05 time: 0.0717 data: 0.0011 max mem: 33369 +Test: [ 200/2573] eta: 0:03:26 time: 0.0733 data: 0.0011 max mem: 33369 +Test: [ 300/2573] eta: 0:03:06 time: 0.0752 data: 0.0011 max mem: 33369 +Test: [ 400/2573] eta: 0:02:53 time: 0.0752 data: 0.0011 max mem: 33369 +Test: [ 500/2573] eta: 0:02:42 time: 0.0735 data: 0.0011 max mem: 33369 +Test: [ 600/2573] eta: 0:02:33 time: 0.0736 data: 0.0011 max mem: 33369 +Test: [ 700/2573] eta: 0:02:25 time: 0.0738 data: 0.0011 max mem: 33369 +Test: [ 800/2573] eta: 0:02:16 time: 0.0771 data: 0.0011 max mem: 33369 +Test: [ 900/2573] eta: 0:02:08 time: 0.0738 data: 0.0011 max mem: 33369 +Test: [1000/2573] eta: 0:02:00 time: 0.0738 data: 0.0011 max mem: 33369 +Test: [1100/2573] eta: 0:01:52 time: 0.0738 data: 0.0011 max mem: 33369 +Test: [1200/2573] eta: 0:01:44 time: 0.0738 data: 0.0011 max mem: 33369 +Test: [1300/2573] eta: 0:01:36 time: 0.0738 data: 0.0011 max mem: 33369 +Test: [1400/2573] eta: 0:01:28 time: 0.0721 data: 0.0011 max mem: 33369 +Test: [1500/2573] eta: 0:01:21 time: 0.0739 data: 0.0011 max mem: 33369 +Test: [1600/2573] eta: 0:01:13 time: 0.0772 data: 0.0012 max mem: 33369 +Test: [1700/2573] eta: 0:01:05 time: 0.0723 data: 0.0011 max mem: 33369 +Test: [1800/2573] eta: 0:00:58 time: 0.0754 data: 0.0011 max mem: 33369 +Test: [1900/2573] eta: 0:00:50 time: 0.0721 data: 0.0011 max mem: 33369 +Test: [2000/2573] eta: 0:00:43 time: 0.0737 data: 0.0011 max mem: 33369 +Test: [2100/2573] eta: 0:00:35 time: 0.0755 data: 0.0011 max mem: 33369 +Test: [2200/2573] eta: 0:00:27 time: 0.0755 data: 0.0011 max mem: 33369 +Test: [2300/2573] eta: 0:00:20 time: 0.0755 data: 0.0011 max mem: 33369 +Test: [2400/2573] eta: 0:00:12 time: 0.0706 data: 0.0011 max mem: 33369 +Test: [2500/2573] eta: 0:00:05 time: 0.0737 data: 0.0011 max mem: 33369 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: Total time: 0:03:13 +Final results: +Mean IoU is 63.85 + + precision@0.5 = 71.75 + precision@0.6 = 66.93 + precision@0.7 = 60.13 + precision@0.8 = 48.53 + precision@0.9 = 23.90 + overall IoU = 61.08 + +Average object IoU 63.85053880268141 +Overall IoU 61.08313751220703 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [27] [ 0/1319] eta: 3:03:18 lr: 1.818202428926248e-05 loss: 0.0242 (0.0242) time: 8.3384 data: 1.3649 max mem: 33369 +Epoch: [27] [ 10/1319] eta: 1:09:03 lr: 1.817248019783995e-05 loss: 0.0356 (0.0395) time: 3.1652 data: 0.1300 max mem: 33369 +Epoch: [27] [ 20/1319] eta: 1:03:23 lr: 1.8162935549439682e-05 loss: 0.0357 (0.0395) time: 2.6576 data: 0.0058 max mem: 33369 +Epoch: [27] [ 30/1319] eta: 1:00:26 lr: 1.8153390343703928e-05 loss: 0.0374 (0.0423) time: 2.6195 data: 0.0057 max mem: 33369 +Epoch: [27] [ 40/1319] eta: 0:58:58 lr: 1.8143844580274487e-05 loss: 0.0381 (0.0432) time: 2.5970 data: 0.0061 max mem: 33369 +Epoch: [27] [ 50/1319] eta: 0:57:58 lr: 1.813429825879272e-05 loss: 0.0342 (0.0420) time: 2.6297 data: 0.0060 max mem: 33369 +Epoch: [27] [ 60/1319] eta: 0:57:13 lr: 1.8124751378899558e-05 loss: 0.0354 (0.0414) time: 2.6464 data: 0.0063 max mem: 33369 +Epoch: [27] [ 70/1319] eta: 0:56:25 lr: 1.811520394023548e-05 loss: 0.0360 (0.0415) time: 2.6328 data: 0.0063 max mem: 33369 +Epoch: [27] [ 80/1319] eta: 0:55:45 lr: 1.8105655942440525e-05 loss: 0.0352 (0.0406) time: 2.6164 data: 0.0060 max mem: 33369 +Epoch: [27] [ 90/1319] eta: 0:55:08 lr: 1.8096107385154294e-05 loss: 0.0336 (0.0407) time: 2.6243 data: 0.0064 max mem: 33369 +Epoch: [27] [ 100/1319] eta: 0:54:32 lr: 1.8086558268015952e-05 loss: 0.0340 (0.0403) time: 2.6234 data: 0.0065 max mem: 33369 +Epoch: [27] [ 110/1319] eta: 0:54:04 lr: 1.807700859066419e-05 loss: 0.0346 (0.0401) time: 2.6472 data: 0.0061 max mem: 33369 +Epoch: [27] [ 120/1319] eta: 0:53:31 lr: 1.8067458352737284e-05 loss: 0.0361 (0.0402) time: 2.6468 data: 0.0060 max mem: 33369 +Epoch: [27] [ 130/1319] eta: 0:53:01 lr: 1.8057907553873043e-05 loss: 0.0376 (0.0401) time: 2.6322 data: 0.0060 max mem: 33369 +Epoch: [27] [ 140/1319] eta: 0:52:32 lr: 1.8048356193708847e-05 loss: 0.0342 (0.0400) time: 2.6481 data: 0.0062 max mem: 33369 +Epoch: [27] [ 150/1319] eta: 0:52:02 lr: 1.803880427188162e-05 loss: 0.0319 (0.0398) time: 2.6429 data: 0.0063 max mem: 33369 +Epoch: [27] [ 160/1319] eta: 0:51:34 lr: 1.802925178802783e-05 loss: 0.0325 (0.0397) time: 2.6414 data: 0.0062 max mem: 33369 +Epoch: [27] [ 170/1319] eta: 0:51:04 lr: 1.8019698741783504e-05 loss: 0.0319 (0.0390) time: 2.6372 data: 0.0061 max mem: 33369 +Epoch: [27] [ 180/1319] eta: 0:50:33 lr: 1.8010145132784217e-05 loss: 0.0319 (0.0391) time: 2.6114 data: 0.0060 max mem: 33369 +Epoch: [27] [ 190/1319] eta: 0:50:05 lr: 1.8000590960665095e-05 loss: 0.0344 (0.0389) time: 2.6199 data: 0.0060 max mem: 33369 +Epoch: [27] [ 200/1319] eta: 0:49:36 lr: 1.7991036225060814e-05 loss: 0.0336 (0.0392) time: 2.6278 data: 0.0060 max mem: 33369 +Epoch: [27] [ 210/1319] eta: 0:49:08 lr: 1.7981480925605583e-05 loss: 0.0361 (0.0395) time: 2.6232 data: 0.0059 max mem: 33369 +Epoch: [27] [ 220/1319] eta: 0:48:39 lr: 1.7971925061933174e-05 loss: 0.0361 (0.0393) time: 2.6248 data: 0.0059 max mem: 33369 +Epoch: [27] [ 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mem: 33369 +Epoch: [27] [ 310/1319] eta: 0:44:28 lr: 1.7885896838454187e-05 loss: 0.0353 (0.0394) time: 2.6134 data: 0.0059 max mem: 33369 +Epoch: [27] [ 320/1319] eta: 0:43:59 lr: 1.787633531236672e-05 loss: 0.0349 (0.0393) time: 2.6065 data: 0.0060 max mem: 33369 +Epoch: [27] [ 330/1319] eta: 0:43:33 lr: 1.786677321800332e-05 loss: 0.0364 (0.0394) time: 2.6070 data: 0.0061 max mem: 33369 +Epoch: [27] [ 340/1319] eta: 0:43:06 lr: 1.7857210554992246e-05 loss: 0.0369 (0.0394) time: 2.6370 data: 0.0062 max mem: 33369 +Epoch: [27] [ 350/1319] eta: 0:42:39 lr: 1.7847647322961293e-05 loss: 0.0351 (0.0392) time: 2.6323 data: 0.0061 max mem: 33369 +Epoch: [27] [ 360/1319] eta: 0:42:13 lr: 1.783808352153779e-05 loss: 0.0298 (0.0391) time: 2.6277 data: 0.0060 max mem: 33369 +Epoch: [27] [ 370/1319] eta: 0:41:45 lr: 1.782851915034859e-05 loss: 0.0372 (0.0391) time: 2.6197 data: 0.0060 max mem: 33369 +Epoch: [27] [ 380/1319] eta: 0:41:18 lr: 1.78189542090201e-05 loss: 0.0366 (0.0391) time: 2.5986 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1.7291993287130824e-05 loss: 0.0327 (0.0402) time: 2.6106 data: 0.0061 max mem: 33369 +Epoch: [27] [ 940/1319] eta: 0:16:34 lr: 1.728239580690995e-05 loss: 0.0327 (0.0402) time: 2.6195 data: 0.0060 max mem: 33369 +Epoch: [27] [ 950/1319] eta: 0:16:07 lr: 1.727279773445306e-05 loss: 0.0345 (0.0401) time: 2.6033 data: 0.0062 max mem: 33369 +Epoch: [27] [ 960/1319] eta: 0:15:41 lr: 1.7263199069357895e-05 loss: 0.0326 (0.0401) time: 2.5862 data: 0.0062 max mem: 33369 +Epoch: [27] [ 970/1319] eta: 0:15:15 lr: 1.725359981122169e-05 loss: 0.0321 (0.0401) time: 2.5986 data: 0.0062 max mem: 33369 +Epoch: [27] [ 980/1319] eta: 0:14:48 lr: 1.7243999959641156e-05 loss: 0.0437 (0.0402) time: 2.6282 data: 0.0062 max mem: 33369 +Epoch: [27] [ 990/1319] eta: 0:14:22 lr: 1.7234399514212475e-05 loss: 0.0450 (0.0402) time: 2.6358 data: 0.0059 max mem: 33369 +Epoch: [27] [1000/1319] eta: 0:13:56 lr: 1.7224798474531302e-05 loss: 0.0379 (0.0402) time: 2.6183 data: 0.0059 max mem: 33369 +Epoch: [27] 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+/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 1:55:09 time: 2.6854 data: 2.5784 max mem: 33369 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 100/2573] eta: 0:04:01 time: 0.0716 data: 0.0011 max mem: 33369 +Test: [ 200/2573] eta: 0:03:24 time: 0.0732 data: 0.0011 max mem: 33369 +Test: [ 300/2573] eta: 0:03:05 time: 0.0752 data: 0.0011 max mem: 33369 +Test: [ 400/2573] eta: 0:02:52 time: 0.0753 data: 0.0011 max mem: 33369 +Test: [ 500/2573] eta: 0:02:42 time: 0.0737 data: 0.0011 max mem: 33369 +Test: [ 600/2573] eta: 0:02:33 time: 0.0738 data: 0.0011 max mem: 33369 +Test: [ 700/2573] eta: 0:02:24 time: 0.0739 data: 0.0011 max mem: 33369 +Test: [ 800/2573] eta: 0:02:16 time: 0.0772 data: 0.0011 max mem: 33369 +Test: [ 900/2573] eta: 0:02:08 time: 0.0740 data: 0.0011 max mem: 33369 +Test: [1000/2573] eta: 0:02:00 time: 0.0740 data: 0.0011 max mem: 33369 +Test: [1100/2573] eta: 0:01:52 time: 0.0738 data: 0.0011 max mem: 33369 +Test: [1200/2573] eta: 0:01:44 time: 0.0739 data: 0.0011 max mem: 33369 +Test: [1300/2573] eta: 0:01:36 time: 0.0738 data: 0.0010 max mem: 33369 +Test: [1400/2573] eta: 0:01:28 time: 0.0723 data: 0.0011 max mem: 33369 +Test: [1500/2573] eta: 0:01:21 time: 0.0739 data: 0.0011 max mem: 33369 +Test: [1600/2573] eta: 0:01:13 time: 0.0773 data: 0.0011 max mem: 33369 +Test: [1700/2573] eta: 0:01:05 time: 0.0721 data: 0.0011 max mem: 33369 +Test: [1800/2573] eta: 0:00:58 time: 0.0756 data: 0.0011 max mem: 33369 +Test: [1900/2573] eta: 0:00:50 time: 0.0721 data: 0.0011 max mem: 33369 +Test: [2000/2573] eta: 0:00:43 time: 0.0739 data: 0.0011 max mem: 33369 +Test: [2100/2573] eta: 0:00:35 time: 0.0754 data: 0.0010 max mem: 33369 +Test: [2200/2573] eta: 0:00:27 time: 0.0756 data: 0.0011 max mem: 33369 +Test: [2300/2573] eta: 0:00:20 time: 0.0756 data: 0.0011 max mem: 33369 +Test: [2400/2573] eta: 0:00:12 time: 0.0707 data: 0.0011 max mem: 33369 +Test: [2500/2573] eta: 0:00:05 time: 0.0741 data: 0.0011 max mem: 33369 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: Total time: 0:03:13 +Final results: +Mean IoU is 63.60 + + precision@0.5 = 71.51 + precision@0.6 = 66.32 + precision@0.7 = 59.70 + precision@0.8 = 48.28 + precision@0.9 = 23.53 + overall IoU = 60.99 + +Average object IoU 63.59675789963581 +Overall IoU 60.993690490722656 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [28] [ 0/1319] eta: 3:10:36 lr: 1.69182110465679e-05 loss: 0.0332 (0.0332) time: 8.6705 data: 1.4218 max mem: 33369 +Epoch: [28] [ 10/1319] eta: 1:09:34 lr: 1.690859022703219e-05 loss: 0.0337 (0.0372) time: 3.1889 data: 0.1344 max mem: 33369 +Epoch: [28] [ 20/1319] eta: 1:03:07 lr: 1.6898968799219036e-05 loss: 0.0355 (0.0430) time: 2.6283 data: 0.0056 max mem: 33369 +Epoch: [28] [ 30/1319] eta: 1:00:36 lr: 1.6889346762705132e-05 loss: 0.0381 (0.0422) time: 2.6183 data: 0.0057 max mem: 33369 +Epoch: [28] [ 40/1319] eta: 0:59:10 lr: 1.6879724117066593e-05 loss: 0.0377 (0.0447) time: 2.6286 data: 0.0059 max mem: 33369 +Epoch: [28] [ 50/1319] eta: 0:58:18 lr: 1.6870100861878995e-05 loss: 0.0355 (0.0433) time: 2.6577 data: 0.0060 max mem: 33369 +Epoch: [28] [ 60/1319] eta: 0:57:23 lr: 1.6860476996717327e-05 loss: 0.0354 (0.0423) time: 2.6524 data: 0.0058 max mem: 33369 +Epoch: [28] [ 70/1319] eta: 0:56:37 lr: 1.6850852521156025e-05 loss: 0.0385 (0.0428) time: 2.6266 data: 0.0060 max mem: 33369 +Epoch: [28] [ 80/1319] eta: 0:55:53 lr: 1.684122743476896e-05 loss: 0.0359 (0.0418) time: 2.6178 data: 0.0062 max mem: 33369 +Epoch: [28] [ 90/1319] eta: 0:55:16 lr: 1.6831601737129412e-05 loss: 0.0342 (0.0411) time: 2.6210 data: 0.0062 max mem: 33369 +Epoch: [28] [ 100/1319] eta: 0:54:40 lr: 1.6821975427810122e-05 loss: 0.0347 (0.0407) time: 2.6288 data: 0.0062 max mem: 33369 +Epoch: [28] [ 110/1319] eta: 0:54:09 lr: 1.6812348506383245e-05 loss: 0.0365 (0.0402) time: 2.6374 data: 0.0062 max mem: 33369 +Epoch: [28] [ 120/1319] eta: 0:53:33 lr: 1.680272097242036e-05 loss: 0.0358 (0.0399) time: 2.6261 data: 0.0060 max mem: 33369 +Epoch: [28] [ 130/1319] eta: 0:53:01 lr: 1.6793092825492484e-05 loss: 0.0372 (0.0406) time: 2.6139 data: 0.0061 max mem: 33369 +Epoch: [28] [ 140/1319] eta: 0:52:29 lr: 1.6783464065170062e-05 loss: 0.0370 (0.0401) time: 2.6196 data: 0.0060 max mem: 33369 +Epoch: [28] [ 150/1319] eta: 0:51:56 lr: 1.6773834691022944e-05 loss: 0.0296 (0.0398) time: 2.5986 data: 0.0060 max mem: 33369 +Epoch: [28] [ 160/1319] eta: 0:51:27 lr: 1.6764204702620422e-05 loss: 0.0407 (0.0398) time: 2.6125 data: 0.0062 max mem: 33369 +Epoch: [28] [ 170/1319] eta: 0:50:57 lr: 1.6754574099531206e-05 loss: 0.0374 (0.0396) time: 2.6229 data: 0.0061 max mem: 33369 +Epoch: [28] [ 180/1319] eta: 0:50:26 lr: 1.6744942881323427e-05 loss: 0.0352 (0.0396) time: 2.5967 data: 0.0060 max mem: 33369 +Epoch: [28] [ 190/1319] eta: 0:49:58 lr: 1.6735311047564646e-05 loss: 0.0349 (0.0393) time: 2.6122 data: 0.0060 max mem: 33369 +Epoch: [28] [ 200/1319] eta: 0:49:32 lr: 1.6725678597821815e-05 loss: 0.0333 (0.0395) time: 2.6485 data: 0.0062 max mem: 33369 +Epoch: [28] [ 210/1319] eta: 0:49:03 lr: 1.6716045531661334e-05 loss: 0.0341 (0.0393) time: 2.6414 data: 0.0062 max mem: 33369 +Epoch: [28] [ 220/1319] eta: 0:48:36 lr: 1.6706411848649008e-05 loss: 0.0360 (0.0394) time: 2.6267 data: 0.0061 max mem: 33369 +Epoch: [28] [ 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mem: 33369 +Epoch: [28] [ 310/1319] eta: 0:44:29 lr: 1.6619680871272843e-05 loss: 0.0320 (0.0395) time: 2.6505 data: 0.0059 max mem: 33369 +Epoch: [28] [ 320/1319] eta: 0:44:02 lr: 1.6610040995732262e-05 loss: 0.0318 (0.0393) time: 2.6557 data: 0.0059 max mem: 33369 +Epoch: [28] [ 330/1319] eta: 0:43:35 lr: 1.6600400498524878e-05 loss: 0.0332 (0.0394) time: 2.6284 data: 0.0061 max mem: 33369 +Epoch: [28] [ 340/1319] eta: 0:43:08 lr: 1.659075937920942e-05 loss: 0.0385 (0.0399) time: 2.6319 data: 0.0061 max mem: 33369 +Epoch: [28] [ 350/1319] eta: 0:42:41 lr: 1.6581117637343994e-05 loss: 0.0361 (0.0398) time: 2.6171 data: 0.0059 max mem: 33369 +Epoch: [28] [ 360/1319] eta: 0:42:14 lr: 1.657147527248612e-05 loss: 0.0325 (0.0397) time: 2.6136 data: 0.0059 max mem: 33369 +Epoch: [28] [ 370/1319] eta: 0:41:46 lr: 1.6561832284192722e-05 loss: 0.0325 (0.0397) time: 2.6128 data: 0.0060 max mem: 33369 +Epoch: [28] [ 380/1319] eta: 0:41:19 lr: 1.6552188672020112e-05 loss: 0.0313 (0.0396) time: 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(0.0400) time: 2.5921 data: 0.0059 max mem: 33369 +Epoch: [28] [ 860/1319] eta: 0:20:07 lr: 1.608855275594644e-05 loss: 0.0369 (0.0400) time: 2.6022 data: 0.0059 max mem: 33369 +Epoch: [28] [ 870/1319] eta: 0:19:40 lr: 1.6078878017308325e-05 loss: 0.0356 (0.0400) time: 2.6205 data: 0.0060 max mem: 33369 +Epoch: [28] [ 880/1319] eta: 0:19:14 lr: 1.6069202631811695e-05 loss: 0.0353 (0.0399) time: 2.6110 data: 0.0061 max mem: 33369 +Epoch: [28] [ 890/1319] eta: 0:18:47 lr: 1.6059526598980493e-05 loss: 0.0347 (0.0399) time: 2.6012 data: 0.0060 max mem: 33369 +Epoch: [28] [ 900/1319] eta: 0:18:21 lr: 1.6049849918337977e-05 loss: 0.0381 (0.0399) time: 2.5905 data: 0.0060 max mem: 33369 +Epoch: [28] [ 910/1319] eta: 0:17:54 lr: 1.6040172589406754e-05 loss: 0.0365 (0.0399) time: 2.5666 data: 0.0060 max mem: 33369 +Epoch: [28] [ 920/1319] eta: 0:17:28 lr: 1.603049461170875e-05 loss: 0.0383 (0.0399) time: 2.5920 data: 0.0059 max mem: 33369 +Epoch: [28] [ 930/1319] eta: 0:17:02 lr: 1.602081598476522e-05 loss: 0.0383 (0.0399) time: 2.6277 data: 0.0058 max mem: 33369 +Epoch: [28] [ 940/1319] eta: 0:16:35 lr: 1.6011136708096744e-05 loss: 0.0355 (0.0399) time: 2.6159 data: 0.0058 max mem: 33369 +Epoch: [28] [ 950/1319] eta: 0:16:09 lr: 1.6001456781223216e-05 loss: 0.0386 (0.0399) time: 2.6054 data: 0.0059 max mem: 33369 +Epoch: [28] [ 960/1319] eta: 0:15:43 lr: 1.599177620366387e-05 loss: 0.0349 (0.0399) time: 2.5998 data: 0.0058 max mem: 33369 +Epoch: [28] [ 970/1319] eta: 0:15:16 lr: 1.598209497493724e-05 loss: 0.0333 (0.0399) time: 2.6013 data: 0.0058 max mem: 33369 +Epoch: [28] [ 980/1319] eta: 0:14:50 lr: 1.5972413094561205e-05 loss: 0.0403 (0.0399) time: 2.6158 data: 0.0059 max mem: 33369 +Epoch: [28] [ 990/1319] eta: 0:14:24 lr: 1.5962730562052938e-05 loss: 0.0332 (0.0399) time: 2.6342 data: 0.0058 max mem: 33369 +Epoch: [28] [1000/1319] eta: 0:13:57 lr: 1.5953047376928946e-05 loss: 0.0352 (0.0399) time: 2.6391 data: 0.0058 max mem: 33369 +Epoch: [28] 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mem: 33369 +Epoch: [28] [1090/1319] eta: 0:10:01 lr: 1.5865869262987425e-05 loss: 0.0410 (0.0399) time: 2.6186 data: 0.0062 max mem: 33369 +Epoch: [28] [1100/1319] eta: 0:09:35 lr: 1.5856179524962237e-05 loss: 0.0372 (0.0398) time: 2.6216 data: 0.0061 max mem: 33369 +Epoch: [28] [1110/1319] eta: 0:09:08 lr: 1.5846489128957288e-05 loss: 0.0351 (0.0399) time: 2.6236 data: 0.0059 max mem: 33369 +Epoch: [28] [1120/1319] eta: 0:08:42 lr: 1.5836798074480774e-05 loss: 0.0348 (0.0398) time: 2.6155 data: 0.0060 max mem: 33369 +Epoch: [28] [1130/1319] eta: 0:08:16 lr: 1.582710636104018e-05 loss: 0.0356 (0.0399) time: 2.6383 data: 0.0059 max mem: 33369 +Epoch: [28] [1140/1319] eta: 0:07:50 lr: 1.5817413988142284e-05 loss: 0.0374 (0.0399) time: 2.6252 data: 0.0058 max mem: 33369 +Epoch: [28] [1150/1319] eta: 0:07:23 lr: 1.5807720955293166e-05 loss: 0.0357 (0.0399) time: 2.6067 data: 0.0058 max mem: 33369 +Epoch: [28] [1160/1319] eta: 0:06:57 lr: 1.579802726199819e-05 loss: 0.0358 (0.0399) time: 2.6260 data: 0.0058 max mem: 33369 +Epoch: [28] [1170/1319] eta: 0:06:31 lr: 1.5788332907762015e-05 loss: 0.0367 (0.0400) time: 2.6343 data: 0.0059 max mem: 33369 +Epoch: [28] [1180/1319] eta: 0:06:05 lr: 1.577863789208859e-05 loss: 0.0378 (0.0400) time: 2.6151 data: 0.0060 max mem: 33369 +Epoch: [28] [1190/1319] eta: 0:05:38 lr: 1.576894221448116e-05 loss: 0.0370 (0.0400) time: 2.6164 data: 0.0059 max mem: 33369 +Epoch: [28] [1200/1319] eta: 0:05:12 lr: 1.5759245874442245e-05 loss: 0.0328 (0.0399) time: 2.6125 data: 0.0058 max mem: 33369 +Epoch: [28] [1210/1319] eta: 0:04:46 lr: 1.5749548871473663e-05 loss: 0.0363 (0.0400) time: 2.6048 data: 0.0058 max mem: 33369 +Epoch: [28] [1220/1319] eta: 0:04:19 lr: 1.57398512050765e-05 loss: 0.0369 (0.0400) time: 2.6155 data: 0.0058 max mem: 33369 +Epoch: [28] [1230/1319] eta: 0:03:53 lr: 1.5730152874751144e-05 loss: 0.0353 (0.0400) time: 2.6401 data: 0.0059 max mem: 33369 +Epoch: [28] [1240/1319] eta: 0:03:27 lr: 1.572045387999725e-05 loss: 0.0353 (0.0400) time: 2.6542 data: 0.0063 max mem: 33369 +Epoch: [28] [1250/1319] eta: 0:03:01 lr: 1.5710754220313764e-05 loss: 0.0369 (0.0400) time: 2.6298 data: 0.0062 max mem: 33369 +Epoch: [28] [1260/1319] eta: 0:02:34 lr: 1.5701053895198906e-05 loss: 0.0369 (0.0400) time: 2.6130 data: 0.0058 max mem: 33369 +Epoch: [28] [1270/1319] eta: 0:02:08 lr: 1.5691352904150157e-05 loss: 0.0368 (0.0400) time: 2.6220 data: 0.0058 max mem: 33369 +Epoch: [28] [1280/1319] eta: 0:01:42 lr: 1.5681651246664294e-05 loss: 0.0318 (0.0400) time: 2.6345 data: 0.0059 max mem: 33369 +Epoch: [28] [1290/1319] eta: 0:01:16 lr: 1.5671948922237363e-05 loss: 0.0387 (0.0400) time: 2.6536 data: 0.0060 max mem: 33369 +Epoch: [28] [1300/1319] eta: 0:00:49 lr: 1.5662245930364672e-05 loss: 0.0378 (0.0400) time: 2.6397 data: 0.0059 max mem: 33369 +Epoch: [28] [1310/1319] eta: 0:00:23 lr: 1.5652542270540813e-05 loss: 0.0363 (0.0400) time: 2.6107 data: 0.0059 max mem: 33369 +Epoch: [28] Total time: 0:57:44 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 1:50:32 time: 2.5779 data: 2.4991 max mem: 33369 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 100/2573] eta: 0:04:01 time: 0.0717 data: 0.0011 max mem: 33369 +Test: [ 200/2573] eta: 0:03:24 time: 0.0733 data: 0.0011 max mem: 33369 +Test: [ 300/2573] eta: 0:03:04 time: 0.0750 data: 0.0011 max mem: 33369 +Test: [ 400/2573] eta: 0:02:52 time: 0.0752 data: 0.0011 max mem: 33369 +Test: [ 500/2573] eta: 0:02:42 time: 0.0737 data: 0.0011 max mem: 33369 +Test: [ 600/2573] eta: 0:02:32 time: 0.0737 data: 0.0012 max mem: 33369 +Test: [ 700/2573] eta: 0:02:24 time: 0.0738 data: 0.0011 max mem: 33369 +Test: [ 800/2573] eta: 0:02:16 time: 0.0770 data: 0.0011 max mem: 33369 +Test: [ 900/2573] eta: 0:02:08 time: 0.0737 data: 0.0011 max mem: 33369 +Test: [1000/2573] eta: 0:02:00 time: 0.0737 data: 0.0011 max mem: 33369 +Test: [1100/2573] eta: 0:01:52 time: 0.0738 data: 0.0011 max mem: 33369 +Test: [1200/2573] eta: 0:01:44 time: 0.0738 data: 0.0011 max mem: 33369 +Test: [1300/2573] eta: 0:01:36 time: 0.0737 data: 0.0011 max mem: 33369 +Test: [1400/2573] eta: 0:01:28 time: 0.0722 data: 0.0011 max mem: 33369 +Test: [1500/2573] eta: 0:01:21 time: 0.0737 data: 0.0011 max mem: 33369 +Test: [1600/2573] eta: 0:01:13 time: 0.0771 data: 0.0011 max mem: 33369 +Test: [1700/2573] eta: 0:01:05 time: 0.0720 data: 0.0011 max mem: 33369 +Test: [1800/2573] eta: 0:00:58 time: 0.0755 data: 0.0011 max mem: 33369 +Test: [1900/2573] eta: 0:00:50 time: 0.0720 data: 0.0011 max mem: 33369 +Test: [2000/2573] eta: 0:00:43 time: 0.0738 data: 0.0011 max mem: 33369 +Test: [2100/2573] eta: 0:00:35 time: 0.0753 data: 0.0011 max mem: 33369 +Test: [2200/2573] eta: 0:00:27 time: 0.0753 data: 0.0011 max mem: 33369 +Test: [2300/2573] eta: 0:00:20 time: 0.0754 data: 0.0011 max mem: 33369 +Test: [2400/2573] eta: 0:00:12 time: 0.0706 data: 0.0011 max mem: 33369 +Test: [2500/2573] eta: 0:00:05 time: 0.0738 data: 0.0011 max mem: 33369 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: Total time: 0:03:12 +Final results: +Mean IoU is 63.65 + + precision@0.5 = 71.30 + precision@0.6 = 66.38 + precision@0.7 = 60.17 + precision@0.8 = 48.53 + precision@0.9 = 24.00 + overall IoU = 61.51 + +Average object IoU 63.65074885407906 +Overall IoU 61.508026123046875 +Better epoch: 28 + +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [29] [ 0/1319] eta: 1:30:08 lr: 1.5643808405182777e-05 loss: 0.0220 (0.0220) time: 4.1005 data: 1.1586 max mem: 33369 +Epoch: [29] [ 10/1319] eta: 0:59:21 lr: 1.563410347485666e-05 loss: 0.0353 (0.0377) time: 2.7211 data: 0.1109 max mem: 33369 +Epoch: [29] [ 20/1319] eta: 0:57:50 lr: 1.5624397875109532e-05 loss: 0.0356 (0.0389) time: 2.6005 data: 0.0059 max mem: 33369 +Epoch: [29] [ 30/1319] eta: 0:57:02 lr: 1.5614691605433113e-05 loss: 0.0379 (0.0401) time: 2.6190 data: 0.0059 max mem: 33369 +Epoch: [29] [ 40/1319] eta: 0:56:27 lr: 1.5604984665318397e-05 loss: 0.0384 (0.0396) time: 2.6244 data: 0.0059 max mem: 33369 +Epoch: [29] [ 50/1319] eta: 0:55:56 lr: 1.5595277054255625e-05 loss: 0.0339 (0.0391) time: 2.6288 data: 0.0059 max mem: 33369 +Epoch: [29] [ 60/1319] eta: 0:55:22 lr: 1.558556877173431e-05 loss: 0.0364 (0.0397) time: 2.6180 data: 0.0059 max mem: 33369 +Epoch: [29] [ 70/1319] eta: 0:54:50 lr: 1.557585981724323e-05 loss: 0.0347 (0.0392) time: 2.6094 data: 0.0061 max mem: 33369 +Epoch: [29] [ 80/1319] eta: 0:54:28 lr: 1.5566150190270393e-05 loss: 0.0335 (0.0388) time: 2.6374 data: 0.0062 max mem: 33369 +Epoch: [29] [ 90/1319] eta: 0:54:00 lr: 1.5556439890303075e-05 loss: 0.0351 (0.0392) time: 2.6424 data: 0.0061 max mem: 33369 +Epoch: [29] [ 100/1319] eta: 0:53:32 lr: 1.554672891682782e-05 loss: 0.0348 (0.0385) time: 2.6223 data: 0.0062 max mem: 33369 +Epoch: [29] [ 110/1319] eta: 0:53:07 lr: 1.55370172693304e-05 loss: 0.0328 (0.0381) time: 2.6382 data: 0.0061 max mem: 33369 +Epoch: [29] [ 120/1319] eta: 0:52:37 lr: 1.552730494729585e-05 loss: 0.0322 (0.0378) time: 2.6230 data: 0.0059 max mem: 33369 +Epoch: [29] [ 130/1319] eta: 0:52:09 lr: 1.551759195020846e-05 loss: 0.0322 (0.0377) time: 2.6043 data: 0.0060 max mem: 33369 +Epoch: [29] [ 140/1319] eta: 0:51:42 lr: 1.5507878277551742e-05 loss: 0.0329 (0.0381) time: 2.6189 data: 0.0061 max mem: 33369 +Epoch: [29] [ 150/1319] eta: 0:51:14 lr: 1.5498163928808475e-05 loss: 0.0312 (0.0377) time: 2.6171 data: 0.0060 max mem: 33369 +Epoch: [29] [ 160/1319] eta: 0:50:46 lr: 1.548844890346068e-05 loss: 0.0311 (0.0375) time: 2.6092 data: 0.0060 max mem: 33369 +Epoch: [29] [ 170/1319] eta: 0:50:18 lr: 1.547873320098961e-05 loss: 0.0339 (0.0373) time: 2.6041 data: 0.0061 max mem: 33369 +Epoch: [29] [ 180/1319] eta: 0:49:49 lr: 1.546901682087577e-05 loss: 0.0351 (0.0375) time: 2.5921 data: 0.0061 max mem: 33369 +Epoch: [29] [ 190/1319] eta: 0:49:23 lr: 1.5459299762598884e-05 loss: 0.0357 (0.0374) time: 2.6042 data: 0.0060 max mem: 33369 +Epoch: [29] [ 200/1319] eta: 0:48:55 lr: 1.5449582025637935e-05 loss: 0.0284 (0.0375) time: 2.6141 data: 0.0060 max mem: 33369 +Epoch: [29] [ 210/1319] eta: 0:48:26 lr: 1.543986360947113e-05 loss: 0.0293 (0.0373) time: 2.5854 data: 0.0061 max mem: 33369 +Epoch: [29] [ 220/1319] eta: 0:48:01 lr: 1.543014451357591e-05 loss: 0.0340 (0.0374) time: 2.6061 data: 0.0060 max mem: 33369 +Epoch: [29] [ 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1.4738317906666963e-05 loss: 0.0352 (0.0382) time: 2.6197 data: 0.0057 max mem: 33369 +Epoch: [29] [ 940/1319] eta: 0:16:33 lr: 1.4728548445256565e-05 loss: 0.0369 (0.0383) time: 2.6100 data: 0.0058 max mem: 33369 +Epoch: [29] [ 950/1319] eta: 0:16:06 lr: 1.471877826378261e-05 loss: 0.0372 (0.0383) time: 2.5950 data: 0.0060 max mem: 33369 +Epoch: [29] [ 960/1319] eta: 0:15:40 lr: 1.4709007361660864e-05 loss: 0.0355 (0.0383) time: 2.5959 data: 0.0060 max mem: 33369 +Epoch: [29] [ 970/1319] eta: 0:15:14 lr: 1.4699235738306196e-05 loss: 0.0395 (0.0383) time: 2.5926 data: 0.0060 max mem: 33369 +Epoch: [29] [ 980/1319] eta: 0:14:48 lr: 1.4689463393132561e-05 loss: 0.0405 (0.0383) time: 2.6073 data: 0.0059 max mem: 33369 +Epoch: [29] [ 990/1319] eta: 0:14:21 lr: 1.4679690325553006e-05 loss: 0.0369 (0.0384) time: 2.6175 data: 0.0059 max mem: 33369 +Epoch: [29] [1000/1319] eta: 0:13:55 lr: 1.466991653497966e-05 loss: 0.0361 (0.0384) time: 2.6120 data: 0.0060 max mem: 33369 +Epoch: [29] 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2.6367 data: 0.0059 max mem: 33369 +Epoch: [29] [1170/1319] eta: 0:06:30 lr: 1.4503650903081281e-05 loss: 0.0349 (0.0382) time: 2.5956 data: 0.0058 max mem: 33369 +Epoch: [29] [1180/1319] eta: 0:06:04 lr: 1.449386399704267e-05 loss: 0.0361 (0.0382) time: 2.5970 data: 0.0059 max mem: 33369 +Epoch: [29] [1190/1319] eta: 0:05:37 lr: 1.4484076356664761e-05 loss: 0.0361 (0.0382) time: 2.6032 data: 0.0060 max mem: 33369 +Epoch: [29] [1200/1319] eta: 0:05:11 lr: 1.447428798134101e-05 loss: 0.0335 (0.0382) time: 2.6072 data: 0.0060 max mem: 33369 +Epoch: [29] [1210/1319] eta: 0:04:45 lr: 1.4464498870463896e-05 loss: 0.0339 (0.0382) time: 2.5994 data: 0.0058 max mem: 33369 +Epoch: [29] [1220/1319] eta: 0:04:19 lr: 1.4454709023424959e-05 loss: 0.0344 (0.0382) time: 2.6057 data: 0.0058 max mem: 33369 +Epoch: [29] [1230/1319] eta: 0:03:53 lr: 1.444491843961477e-05 loss: 0.0359 (0.0382) time: 2.6342 data: 0.0058 max mem: 33369 +Epoch: [29] [1240/1319] eta: 0:03:26 lr: 1.4435127118422938e-05 loss: 0.0348 (0.0381) time: 2.6185 data: 0.0057 max mem: 33369 +Epoch: [29] [1250/1319] eta: 0:03:00 lr: 1.442533505923811e-05 loss: 0.0320 (0.0381) time: 2.6207 data: 0.0058 max mem: 33369 +Epoch: [29] [1260/1319] eta: 0:02:34 lr: 1.4415542261447945e-05 loss: 0.0340 (0.0381) time: 2.6420 data: 0.0057 max mem: 33369 +Epoch: [29] [1270/1319] eta: 0:02:08 lr: 1.4405748724439155e-05 loss: 0.0329 (0.0381) time: 2.6327 data: 0.0057 max mem: 33369 +Epoch: [29] [1280/1319] eta: 0:01:42 lr: 1.4395954447597464e-05 loss: 0.0320 (0.0380) time: 2.6101 data: 0.0059 max mem: 33369 +Epoch: [29] [1290/1319] eta: 0:01:15 lr: 1.4386159430307632e-05 loss: 0.0339 (0.0381) time: 2.5946 data: 0.0059 max mem: 33369 +Epoch: [29] [1300/1319] eta: 0:00:49 lr: 1.4376363671953435e-05 loss: 0.0353 (0.0381) time: 2.5905 data: 0.0059 max mem: 33369 +Epoch: [29] [1310/1319] eta: 0:00:23 lr: 1.4366567171917672e-05 loss: 0.0308 (0.0381) time: 2.6110 data: 0.0059 max mem: 33369 +Epoch: [29] Total time: 0:57:34 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 2:15:50 time: 3.1678 data: 3.0895 max mem: 33369 +Test: [ 100/2573] eta: 0:04:13 time: 0.0715 data: 0.0012 max mem: 33369 +Test: [ 200/2573] eta: 0:03:29 time: 0.0732 data: 0.0011 max mem: 33369 +Test: [ 300/2573] eta: 0:03:08 time: 0.0750 data: 0.0011 max mem: 33369 +Test: [ 400/2573] eta: 0:02:54 time: 0.0751 data: 0.0011 max mem: 33369 +Test: [ 500/2573] eta: 0:02:43 time: 0.0734 data: 0.0011 max mem: 33369 +Test: [ 600/2573] eta: 0:02:34 time: 0.0735 data: 0.0011 max mem: 33369 +Test: [ 700/2573] eta: 0:02:25 time: 0.0736 data: 0.0011 max mem: 33369 +Test: [ 800/2573] eta: 0:02:17 time: 0.0770 data: 0.0011 max mem: 33369 +Test: [ 900/2573] eta: 0:02:09 time: 0.0737 data: 0.0011 max mem: 33369 +Test: [1000/2573] eta: 0:02:00 time: 0.0737 data: 0.0011 max mem: 33369 +Test: [1100/2573] eta: 0:01:52 time: 0.0737 data: 0.0011 max mem: 33369 +Test: [1200/2573] eta: 0:01:44 time: 0.0738 data: 0.0011 max mem: 33369 +Test: [1300/2573] eta: 0:01:37 time: 0.0737 data: 0.0011 max mem: 33369 +Test: [1400/2573] eta: 0:01:29 time: 0.0721 data: 0.0011 max mem: 33369 +Test: [1500/2573] eta: 0:01:21 time: 0.0738 data: 0.0011 max mem: 33369 +Test: [1600/2573] eta: 0:01:13 time: 0.0770 data: 0.0011 max mem: 33369 +Test: [1700/2573] eta: 0:01:06 time: 0.0720 data: 0.0011 max mem: 33369 +Test: [1800/2573] eta: 0:00:58 time: 0.0754 data: 0.0011 max mem: 33369 +Test: [1900/2573] eta: 0:00:50 time: 0.0720 data: 0.0011 max mem: 33369 +Test: [2000/2573] eta: 0:00:43 time: 0.0738 data: 0.0011 max mem: 33369 +Test: [2100/2573] eta: 0:00:35 time: 0.0755 data: 0.0011 max mem: 33369 +Test: [2200/2573] eta: 0:00:27 time: 0.0754 data: 0.0011 max mem: 33369 +Test: [2300/2573] eta: 0:00:20 time: 0.0755 data: 0.0011 max mem: 33369 +Test: [2400/2573] eta: 0:00:12 time: 0.0705 data: 0.0011 max mem: 33369 +Test: [2500/2573] eta: 0:00:05 time: 0.0738 data: 0.0011 max mem: 33369 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: Total time: 0:03:13 +Final results: +Mean IoU is 64.23 + + precision@0.5 = 72.14 + precision@0.6 = 67.16 + precision@0.7 = 60.56 + precision@0.8 = 48.96 + precision@0.9 = 24.35 + overall IoU = 61.71 + +Average object IoU 64.2335608389078 +Overall IoU 61.707435607910156 +Better epoch: 29 + +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [30] [ 0/1319] eta: 1:25:43 lr: 1.4357749687236825e-05 loss: 0.0226 (0.0226) time: 3.8995 data: 1.2482 max mem: 33369 +Epoch: [30] [ 10/1319] eta: 0:59:59 lr: 1.4347951776302166e-05 loss: 0.0304 (0.0334) time: 2.7498 data: 0.1193 max mem: 33369 +Epoch: [30] [ 20/1319] eta: 0:58:11 lr: 1.433815312189048e-05 loss: 0.0314 (0.0355) time: 2.6273 data: 0.0058 max mem: 33369 +Epoch: [30] [ 30/1319] eta: 0:57:15 lr: 1.4328353723380728e-05 loss: 0.0362 (0.0357) time: 2.6191 data: 0.0057 max mem: 33369 +Epoch: [30] [ 40/1319] eta: 0:56:37 lr: 1.431855358015087e-05 loss: 0.0314 (0.0343) time: 2.6237 data: 0.0062 max mem: 33369 +Epoch: [30] [ 50/1319] eta: 0:55:59 lr: 1.4308752691577878e-05 loss: 0.0314 (0.0350) time: 2.6189 data: 0.0062 max mem: 33369 +Epoch: [30] [ 60/1319] eta: 0:55:25 lr: 1.4298951057037729e-05 loss: 0.0378 (0.0357) time: 2.6103 data: 0.0062 max mem: 33369 +Epoch: [30] [ 70/1319] eta: 0:54:58 lr: 1.4289148675905387e-05 loss: 0.0378 (0.0376) time: 2.6245 data: 0.0061 max mem: 33369 +Epoch: [30] [ 80/1319] eta: 0:54:22 lr: 1.4279345547554832e-05 loss: 0.0348 (0.0374) time: 2.6090 data: 0.0061 max mem: 33369 +Epoch: [30] [ 90/1319] eta: 0:53:57 lr: 1.4269541671359036e-05 loss: 0.0342 (0.0370) time: 2.6107 data: 0.0061 max mem: 33369 +Epoch: [30] [ 100/1319] eta: 0:53:31 lr: 1.4259737046689963e-05 loss: 0.0354 (0.0381) time: 2.6373 data: 0.0061 max mem: 33369 +Epoch: [30] [ 110/1319] eta: 0:53:07 lr: 1.424993167291858e-05 loss: 0.0354 (0.0378) time: 2.6473 data: 0.0060 max mem: 33369 +Epoch: [30] [ 120/1319] eta: 0:52:39 lr: 1.4240125549414829e-05 loss: 0.0361 (0.0379) time: 2.6381 data: 0.0061 max mem: 33369 +Epoch: [30] [ 130/1319] eta: 0:52:13 lr: 1.4230318675547643e-05 loss: 0.0361 (0.0377) time: 2.6296 data: 0.0061 max mem: 33369 +Epoch: [30] [ 140/1319] eta: 0:51:47 lr: 1.4220511050684946e-05 loss: 0.0360 (0.0378) time: 2.6393 data: 0.0060 max mem: 33369 +Epoch: [30] [ 150/1319] eta: 0:51:21 lr: 1.4210702674193643e-05 loss: 0.0383 (0.0378) time: 2.6371 data: 0.0060 max mem: 33369 +Epoch: [30] [ 160/1319] eta: 0:50:53 lr: 1.420089354543962e-05 loss: 0.0333 (0.0375) time: 2.6312 data: 0.0062 max mem: 33369 +Epoch: [30] [ 170/1319] eta: 0:50:27 lr: 1.419108366378774e-05 loss: 0.0317 (0.0373) time: 2.6286 data: 0.0060 max mem: 33369 +Epoch: [30] [ 180/1319] eta: 0:50:00 lr: 1.4181273028601838e-05 loss: 0.0302 (0.0368) time: 2.6283 data: 0.0061 max mem: 33369 +Epoch: [30] [ 190/1319] eta: 0:49:33 lr: 1.4171461639244721e-05 loss: 0.0307 (0.0369) time: 2.6240 data: 0.0063 max mem: 33369 +Epoch: [30] [ 200/1319] eta: 0:49:09 lr: 1.4161649495078178e-05 loss: 0.0333 (0.0370) time: 2.6527 data: 0.0061 max mem: 33369 +Epoch: [30] [ 210/1319] eta: 0:48:43 lr: 1.415183659546295e-05 loss: 0.0333 (0.0370) time: 2.6561 data: 0.0059 max mem: 33369 +Epoch: [30] [ 220/1319] eta: 0:48:16 lr: 1.4142022939758767e-05 loss: 0.0319 (0.0369) time: 2.6264 data: 0.0061 max mem: 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data: 0.0061 max mem: 33369 +Epoch: [30] [ 310/1319] eta: 0:44:17 lr: 1.4053665908255448e-05 loss: 0.0268 (0.0363) time: 2.6312 data: 0.0060 max mem: 33369 +Epoch: [30] [ 320/1319] eta: 0:43:50 lr: 1.4043844656216607e-05 loss: 0.0350 (0.0365) time: 2.6411 data: 0.0060 max mem: 33369 +Epoch: [30] [ 330/1319] eta: 0:43:22 lr: 1.4034022640976696e-05 loss: 0.0303 (0.0363) time: 2.5979 data: 0.0059 max mem: 33369 +Epoch: [30] [ 340/1319] eta: 0:42:56 lr: 1.4024199861882808e-05 loss: 0.0303 (0.0364) time: 2.6061 data: 0.0058 max mem: 33369 +Epoch: [30] [ 350/1319] eta: 0:42:31 lr: 1.4014376318280992e-05 loss: 0.0333 (0.0362) time: 2.6543 data: 0.0057 max mem: 33369 +Epoch: [30] [ 360/1319] eta: 0:42:05 lr: 1.4004552009516214e-05 loss: 0.0289 (0.0362) time: 2.6577 data: 0.0060 max mem: 33369 +Epoch: [30] [ 370/1319] eta: 0:41:38 lr: 1.3994726934932381e-05 loss: 0.0279 (0.0361) time: 2.6342 data: 0.0061 max mem: 33369 +Epoch: [30] [ 380/1319] eta: 0:41:12 lr: 1.3984901093872316e-05 loss: 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1.3522209617237661e-05 loss: 0.0372 (0.0363) time: 2.6133 data: 0.0060 max mem: 33369 +Epoch: [30] [ 860/1319] eta: 0:20:06 lr: 1.3512346190741623e-05 loss: 0.0410 (0.0364) time: 2.6527 data: 0.0060 max mem: 33369 +Epoch: [30] [ 870/1319] eta: 0:19:39 lr: 1.3502481964194685e-05 loss: 0.0410 (0.0365) time: 2.6444 data: 0.0059 max mem: 33369 +Epoch: [30] [ 880/1319] eta: 0:19:13 lr: 1.3492616936882415e-05 loss: 0.0388 (0.0365) time: 2.6050 data: 0.0059 max mem: 33369 +Epoch: [30] [ 890/1319] eta: 0:18:47 lr: 1.3482751108089178e-05 loss: 0.0377 (0.0365) time: 2.6269 data: 0.0058 max mem: 33369 +Epoch: [30] [ 900/1319] eta: 0:18:20 lr: 1.3472884477098122e-05 loss: 0.0284 (0.0365) time: 2.6244 data: 0.0059 max mem: 33369 +Epoch: [30] [ 910/1319] eta: 0:17:54 lr: 1.3463017043191156e-05 loss: 0.0322 (0.0365) time: 2.6125 data: 0.0060 max mem: 33369 +Epoch: [30] [ 920/1319] eta: 0:17:28 lr: 1.3453148805648974e-05 loss: 0.0332 (0.0366) time: 2.6158 data: 0.0057 max mem: 33369 +Epoch: [30] [ 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0.0403 (0.0369) time: 2.5788 data: 0.0059 max mem: 33369 +Epoch: [30] [1170/1319] eta: 0:06:31 lr: 1.320617955613944e-05 loss: 0.0338 (0.0369) time: 2.5774 data: 0.0059 max mem: 33369 +Epoch: [30] [1180/1319] eta: 0:06:04 lr: 1.3196290167504535e-05 loss: 0.0314 (0.0369) time: 2.6084 data: 0.0059 max mem: 33369 +Epoch: [30] [1190/1319] eta: 0:05:38 lr: 1.3186399955337153e-05 loss: 0.0376 (0.0369) time: 2.6057 data: 0.0059 max mem: 33369 +Epoch: [30] [1200/1319] eta: 0:05:12 lr: 1.3176508918882283e-05 loss: 0.0326 (0.0369) time: 2.5909 data: 0.0059 max mem: 33369 +Epoch: [30] [1210/1319] eta: 0:04:46 lr: 1.3166617057383607e-05 loss: 0.0326 (0.0369) time: 2.5997 data: 0.0060 max mem: 33369 +Epoch: [30] [1220/1319] eta: 0:04:19 lr: 1.3156724370083478e-05 loss: 0.0328 (0.0368) time: 2.5946 data: 0.0061 max mem: 33369 +Epoch: [30] [1230/1319] eta: 0:03:53 lr: 1.3146830856222919e-05 loss: 0.0319 (0.0368) time: 2.6264 data: 0.0060 max mem: 33369 +Epoch: [30] [1240/1319] eta: 0:03:27 lr: 1.3136936515041629e-05 loss: 0.0286 (0.0367) time: 2.6380 data: 0.0059 max mem: 33369 +Epoch: [30] [1250/1319] eta: 0:03:01 lr: 1.3127041345777947e-05 loss: 0.0303 (0.0367) time: 2.6226 data: 0.0058 max mem: 33369 +Epoch: [30] [1260/1319] eta: 0:02:34 lr: 1.3117145347668891e-05 loss: 0.0356 (0.0368) time: 2.6371 data: 0.0059 max mem: 33369 +Epoch: [30] [1270/1319] eta: 0:02:08 lr: 1.3107248519950133e-05 loss: 0.0356 (0.0368) time: 2.6063 data: 0.0059 max mem: 33369 +Epoch: [30] [1280/1319] eta: 0:01:42 lr: 1.3097350861856001e-05 loss: 0.0311 (0.0368) time: 2.5907 data: 0.0061 max mem: 33369 +Epoch: [30] [1290/1319] eta: 0:01:16 lr: 1.3087452372619463e-05 loss: 0.0299 (0.0368) time: 2.6029 data: 0.0060 max mem: 33369 +Epoch: [30] [1300/1319] eta: 0:00:49 lr: 1.3077553051472149e-05 loss: 0.0300 (0.0367) time: 2.5890 data: 0.0059 max mem: 33369 +Epoch: [30] [1310/1319] eta: 0:00:23 lr: 1.3067652897644308e-05 loss: 0.0300 (0.0368) time: 2.5936 data: 0.0060 max mem: 33369 +Epoch: [30] Total time: 0:57:40 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 1:56:28 time: 2.7162 data: 2.6289 max mem: 33369 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 100/2573] eta: 0:04:02 time: 0.0716 data: 0.0011 max mem: 33369 +Test: [ 200/2573] eta: 0:03:24 time: 0.0733 data: 0.0011 max mem: 33369 +Test: [ 300/2573] eta: 0:03:05 time: 0.0749 data: 0.0011 max mem: 33369 +Test: [ 400/2573] eta: 0:02:52 time: 0.0750 data: 0.0011 max mem: 33369 +Test: [ 500/2573] eta: 0:02:42 time: 0.0733 data: 0.0011 max mem: 33369 +Test: [ 600/2573] eta: 0:02:32 time: 0.0735 data: 0.0011 max mem: 33369 +Test: [ 700/2573] eta: 0:02:24 time: 0.0737 data: 0.0011 max mem: 33369 +Test: [ 800/2573] eta: 0:02:16 time: 0.0770 data: 0.0011 max mem: 33369 +Test: [ 900/2573] eta: 0:02:08 time: 0.0738 data: 0.0011 max mem: 33369 +Test: [1000/2573] eta: 0:02:00 time: 0.0737 data: 0.0011 max mem: 33369 +Test: [1100/2573] eta: 0:01:52 time: 0.0736 data: 0.0011 max mem: 33369 +Test: [1200/2573] eta: 0:01:44 time: 0.0738 data: 0.0011 max mem: 33369 +Test: [1300/2573] eta: 0:01:36 time: 0.0739 data: 0.0011 max mem: 33369 +Test: [1400/2573] eta: 0:01:28 time: 0.0721 data: 0.0011 max mem: 33369 +Test: [1500/2573] eta: 0:01:21 time: 0.0738 data: 0.0011 max mem: 33369 +Test: [1600/2573] eta: 0:01:13 time: 0.0771 data: 0.0011 max mem: 33369 +Test: [1700/2573] eta: 0:01:05 time: 0.0720 data: 0.0011 max mem: 33369 +Test: [1800/2573] eta: 0:00:58 time: 0.0752 data: 0.0011 max mem: 33369 +Test: [1900/2573] eta: 0:00:50 time: 0.0719 data: 0.0011 max mem: 33369 +Test: [2000/2573] eta: 0:00:42 time: 0.0739 data: 0.0011 max mem: 33369 +Test: [2100/2573] eta: 0:00:35 time: 0.0753 data: 0.0011 max mem: 33369 +Test: [2200/2573] eta: 0:00:27 time: 0.0753 data: 0.0011 max mem: 33369 +Test: [2300/2573] eta: 0:00:20 time: 0.0753 data: 0.0011 max mem: 33369 +Test: [2400/2573] eta: 0:00:12 time: 0.0703 data: 0.0011 max mem: 33369 +Test: [2500/2573] eta: 0:00:05 time: 0.0737 data: 0.0011 max mem: 33369 +Test: Total time: 0:03:12 +Final results: +Mean IoU is 64.02 + + precision@0.5 = 71.71 + precision@0.6 = 66.81 + precision@0.7 = 60.40 + precision@0.8 = 49.02 + precision@0.9 = 23.94 + overall IoU = 61.48 + +Average object IoU 64.02416477291912 +Overall IoU 61.481014251708984 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [31] [ 0/1319] eta: 3:01:05 lr: 1.3058742046620123e-05 loss: 0.0468 (0.0468) time: 8.2381 data: 1.3184 max mem: 33369 +Epoch: [31] [ 10/1319] eta: 1:08:56 lr: 1.3048840308573793e-05 loss: 0.0360 (0.0382) time: 3.1601 data: 0.1255 max mem: 33369 +Epoch: [31] [ 20/1319] eta: 1:03:06 lr: 1.3038937735606992e-05 loss: 0.0297 (0.0348) time: 2.6485 data: 0.0058 max mem: 33369 +Epoch: [31] [ 30/1319] eta: 1:00:21 lr: 1.3029034326944665e-05 loss: 0.0297 (0.0391) time: 2.6172 data: 0.0058 max mem: 33369 +Epoch: [31] [ 40/1319] eta: 0:58:59 lr: 1.3019130081810363e-05 loss: 0.0329 (0.0387) time: 2.6132 data: 0.0061 max mem: 33369 +Epoch: [31] [ 50/1319] eta: 0:58:00 lr: 1.3009224999426282e-05 loss: 0.0351 (0.0391) time: 2.6390 data: 0.0061 max mem: 33369 +Epoch: [31] [ 60/1319] eta: 0:57:08 lr: 1.2999319079013207e-05 loss: 0.0322 (0.0380) time: 2.6321 data: 0.0061 max mem: 33369 +Epoch: [31] [ 70/1319] eta: 0:56:12 lr: 1.298941231979056e-05 loss: 0.0323 (0.0376) time: 2.5901 data: 0.0060 max mem: 33369 +Epoch: [31] [ 80/1319] eta: 0:55:39 lr: 1.2979504720976363e-05 loss: 0.0338 (0.0370) time: 2.6114 data: 0.0061 max mem: 33369 +Epoch: [31] [ 90/1319] eta: 0:55:07 lr: 1.2969596281787253e-05 loss: 0.0296 (0.0371) time: 2.6599 data: 0.0061 max mem: 33369 +Epoch: [31] [ 100/1319] eta: 0:54:35 lr: 1.2959687001438464e-05 loss: 0.0351 (0.0373) time: 2.6544 data: 0.0060 max mem: 33369 +Epoch: [31] [ 110/1319] eta: 0:54:01 lr: 1.2949776879143838e-05 loss: 0.0347 (0.0369) time: 2.6380 data: 0.0061 max mem: 33369 +Epoch: [31] [ 120/1319] eta: 0:53:25 lr: 1.2939865914115796e-05 loss: 0.0315 (0.0369) time: 2.6031 data: 0.0063 max mem: 33369 +Epoch: [31] [ 130/1319] eta: 0:52:52 lr: 1.2929954105565368e-05 loss: 0.0320 (0.0366) time: 2.5932 data: 0.0063 max mem: 33369 +Epoch: [31] [ 140/1319] eta: 0:52:24 lr: 1.2920041452702167e-05 loss: 0.0330 (0.0368) time: 2.6279 data: 0.0061 max mem: 33369 +Epoch: [31] [ 150/1319] eta: 0:51:54 lr: 1.2910127954734388e-05 loss: 0.0339 (0.0368) time: 2.6414 data: 0.0061 max mem: 33369 +Epoch: [31] [ 160/1319] eta: 0:51:24 lr: 1.2900213610868823e-05 loss: 0.0329 (0.0368) time: 2.6194 data: 0.0060 max mem: 33369 +Epoch: [31] [ 170/1319] eta: 0:50:50 lr: 1.2890298420310808e-05 loss: 0.0307 (0.0366) time: 2.5864 data: 0.0059 max mem: 33369 +Epoch: [31] [ 180/1319] eta: 0:50:22 lr: 1.2880382382264284e-05 loss: 0.0288 (0.0365) time: 2.5929 data: 0.0062 max mem: 33369 +Epoch: [31] [ 190/1319] eta: 0:49:54 lr: 1.2870465495931752e-05 loss: 0.0253 (0.0359) time: 2.6296 data: 0.0062 max mem: 33369 +Epoch: [31] [ 200/1319] eta: 0:49:25 lr: 1.2860547760514275e-05 loss: 0.0272 (0.0363) time: 2.6192 data: 0.0061 max mem: 33369 +Epoch: [31] [ 210/1319] eta: 0:48:58 lr: 1.285062917521149e-05 loss: 0.0296 (0.0362) time: 2.6240 data: 0.0062 max mem: 33369 +Epoch: [31] [ 220/1319] eta: 0:48:29 lr: 1.2840709739221567e-05 loss: 0.0314 (0.0364) time: 2.6208 data: 0.0061 max mem: 33369 +Epoch: [31] [ 230/1319] eta: 0:48:00 lr: 1.2830789451741262e-05 loss: 0.0314 (0.0364) time: 2.5949 data: 0.0061 max mem: 33369 +Epoch: [31] [ 240/1319] eta: 0:47:31 lr: 1.2820868311965862e-05 loss: 0.0284 (0.0362) time: 2.5928 data: 0.0062 max mem: 33369 +Epoch: [31] [ 250/1319] eta: 0:47:02 lr: 1.2810946319089204e-05 loss: 0.0284 (0.0360) time: 2.5848 data: 0.0063 max mem: 33369 +Epoch: [31] [ 260/1319] eta: 0:46:34 lr: 1.2801023472303672e-05 loss: 0.0326 (0.0360) time: 2.5916 data: 0.0061 max mem: 33369 +Epoch: [31] [ 270/1319] eta: 0:46:07 lr: 1.2791099770800195e-05 loss: 0.0343 (0.0361) time: 2.6095 data: 0.0060 max mem: 33369 +Epoch: [31] [ 280/1319] eta: 0:45:39 lr: 1.2781175213768214e-05 loss: 0.0346 (0.0361) time: 2.6121 data: 0.0060 max mem: 33369 +Epoch: [31] [ 290/1319] eta: 0:45:12 lr: 1.277124980039573e-05 loss: 0.0342 (0.0360) time: 2.6057 data: 0.0059 max mem: 33369 +Epoch: [31] [ 300/1319] eta: 0:44:44 lr: 1.2761323529869248e-05 loss: 0.0371 (0.0366) time: 2.6005 data: 0.0060 max mem: 33369 +Epoch: [31] [ 310/1319] eta: 0:44:18 lr: 1.2751396401373813e-05 loss: 0.0409 (0.0367) time: 2.6137 data: 0.0061 max mem: 33369 +Epoch: [31] [ 320/1319] eta: 0:43:51 lr: 1.2741468414092989e-05 loss: 0.0339 (0.0367) time: 2.6335 data: 0.0062 max mem: 33369 +Epoch: [31] [ 330/1319] eta: 0:43:26 lr: 1.2731539567208833e-05 loss: 0.0335 (0.0366) time: 2.6526 data: 0.0061 max mem: 33369 +Epoch: [31] [ 340/1319] eta: 0:42:59 lr: 1.2721609859901942e-05 loss: 0.0337 (0.0366) time: 2.6379 data: 0.0060 max mem: 33369 +Epoch: [31] [ 350/1319] eta: 0:42:31 lr: 1.2711679291351405e-05 loss: 0.0337 (0.0366) time: 2.6019 data: 0.0060 max mem: 33369 +Epoch: [31] [ 360/1319] eta: 0:42:06 lr: 1.2701747860734819e-05 loss: 0.0337 (0.0366) time: 2.6354 data: 0.0062 max mem: 33369 +Epoch: [31] [ 370/1319] eta: 0:41:38 lr: 1.2691815567228285e-05 loss: 0.0374 (0.0368) time: 2.6263 data: 0.0060 max mem: 33369 +Epoch: [31] [ 380/1319] eta: 0:41:12 lr: 1.2681882410006382e-05 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1.2602385958929271e-05 loss: 0.0345 (0.0367) time: 2.6473 data: 0.0059 max mem: 33369 +Epoch: [31] [ 470/1319] eta: 0:37:14 lr: 1.2592444990875415e-05 loss: 0.0392 (0.0368) time: 2.6145 data: 0.0058 max mem: 33369 +Epoch: [31] [ 480/1319] eta: 0:36:47 lr: 1.258250315076846e-05 loss: 0.0362 (0.0367) time: 2.5887 data: 0.0061 max mem: 33369 +Epoch: [31] [ 490/1319] eta: 0:36:21 lr: 1.2572560437766163e-05 loss: 0.0289 (0.0366) time: 2.6220 data: 0.0061 max mem: 33369 +Epoch: [31] [ 500/1319] eta: 0:35:55 lr: 1.2562616851024742e-05 loss: 0.0341 (0.0369) time: 2.6395 data: 0.0059 max mem: 33369 +Epoch: [31] [ 510/1319] eta: 0:35:28 lr: 1.2552672389698855e-05 loss: 0.0340 (0.0368) time: 2.6149 data: 0.0058 max mem: 33369 +Epoch: [31] [ 520/1319] eta: 0:35:02 lr: 1.2542727052941597e-05 loss: 0.0309 (0.0367) time: 2.6161 data: 0.0060 max mem: 33369 +Epoch: [31] [ 530/1319] eta: 0:34:35 lr: 1.2532780839904498e-05 loss: 0.0294 (0.0366) time: 2.6007 data: 0.0061 max mem: 33369 +Epoch: [31] [ 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data: 0.0059 max mem: 33369 +Epoch: [31] [ 700/1319] eta: 0:27:08 lr: 1.236356031760655e-05 loss: 0.0314 (0.0363) time: 2.6463 data: 0.0062 max mem: 33369 +Epoch: [31] [ 710/1319] eta: 0:26:41 lr: 1.2353598184630927e-05 loss: 0.0360 (0.0363) time: 2.6480 data: 0.0061 max mem: 33369 +Epoch: [31] [ 720/1319] eta: 0:26:15 lr: 1.2343635158950937e-05 loss: 0.0338 (0.0363) time: 2.6318 data: 0.0060 max mem: 33369 +Epoch: [31] [ 730/1319] eta: 0:25:49 lr: 1.2333671239685849e-05 loss: 0.0326 (0.0362) time: 2.6573 data: 0.0060 max mem: 33369 +Epoch: [31] [ 740/1319] eta: 0:25:23 lr: 1.2323706425953264e-05 loss: 0.0304 (0.0362) time: 2.6846 data: 0.0059 max mem: 33369 +Epoch: [31] [ 750/1319] eta: 0:24:57 lr: 1.2313740716869131e-05 loss: 0.0304 (0.0361) time: 2.6545 data: 0.0058 max mem: 33369 +Epoch: [31] [ 760/1319] eta: 0:24:31 lr: 1.2303774111547706e-05 loss: 0.0320 (0.0364) time: 2.6422 data: 0.0060 max mem: 33369 +Epoch: [31] [ 770/1319] eta: 0:24:05 lr: 1.2293806609101593e-05 loss: 0.0394 (0.0365) time: 2.6552 data: 0.0061 max mem: 33369 +Epoch: [31] [ 780/1319] eta: 0:23:38 lr: 1.2283838208641708e-05 loss: 0.0404 (0.0365) time: 2.6349 data: 0.0059 max mem: 33369 +Epoch: [31] [ 790/1319] eta: 0:23:12 lr: 1.2273868909277286e-05 loss: 0.0378 (0.0365) time: 2.6230 data: 0.0061 max mem: 33369 +Epoch: [31] [ 800/1319] eta: 0:22:45 lr: 1.2263898710115878e-05 loss: 0.0300 (0.0365) time: 2.5980 data: 0.0061 max mem: 33369 +Epoch: [31] [ 810/1319] eta: 0:22:19 lr: 1.2253927610263324e-05 loss: 0.0303 (0.0366) time: 2.5996 data: 0.0059 max mem: 33369 +Epoch: [31] [ 820/1319] eta: 0:21:52 lr: 1.2243955608823781e-05 loss: 0.0329 (0.0367) time: 2.6305 data: 0.0059 max mem: 33369 +Epoch: [31] [ 830/1319] eta: 0:21:26 lr: 1.2233982704899707e-05 loss: 0.0355 (0.0367) time: 2.6064 data: 0.0060 max mem: 33369 +Epoch: [31] [ 840/1319] eta: 0:20:59 lr: 1.2224008897591841e-05 loss: 0.0357 (0.0367) time: 2.6042 data: 0.0060 max mem: 33369 +Epoch: [31] [ 850/1319] eta: 0:20:33 lr: 1.2214034185999218e-05 loss: 0.0308 (0.0367) time: 2.6402 data: 0.0059 max mem: 33369 +Epoch: [31] [ 860/1319] eta: 0:20:07 lr: 1.2204058569219158e-05 loss: 0.0307 (0.0367) time: 2.6570 data: 0.0060 max mem: 33369 +Epoch: [31] [ 870/1319] eta: 0:19:41 lr: 1.2194082046347242e-05 loss: 0.0341 (0.0367) time: 2.6417 data: 0.0059 max mem: 33369 +Epoch: [31] [ 880/1319] eta: 0:19:14 lr: 1.2184104616477345e-05 loss: 0.0353 (0.0367) time: 2.6239 data: 0.0060 max mem: 33369 +Epoch: [31] [ 890/1319] eta: 0:18:48 lr: 1.2174126278701602e-05 loss: 0.0331 (0.0367) time: 2.6308 data: 0.0060 max mem: 33369 +Epoch: [31] [ 900/1319] eta: 0:18:22 lr: 1.2164147032110409e-05 loss: 0.0344 (0.0367) time: 2.6468 data: 0.0058 max mem: 33369 +Epoch: [31] [ 910/1319] eta: 0:17:56 lr: 1.215416687579243e-05 loss: 0.0347 (0.0367) time: 2.6402 data: 0.0059 max mem: 33369 +Epoch: [31] [ 920/1319] eta: 0:17:29 lr: 1.2144185808834565e-05 loss: 0.0347 (0.0366) time: 2.6101 data: 0.0061 max mem: 33369 +Epoch: [31] [ 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33369 +Epoch: [31] [1010/1319] eta: 0:13:32 lr: 1.2054315075888731e-05 loss: 0.0328 (0.0366) time: 2.6136 data: 0.0062 max mem: 33369 +Epoch: [31] [1020/1319] eta: 0:13:06 lr: 1.2044324851924447e-05 loss: 0.0328 (0.0366) time: 2.6147 data: 0.0062 max mem: 33369 +Epoch: [31] [1030/1319] eta: 0:12:39 lr: 1.2034333707159618e-05 loss: 0.0351 (0.0366) time: 2.6362 data: 0.0059 max mem: 33369 +Epoch: [31] [1040/1319] eta: 0:12:13 lr: 1.2024341640659817e-05 loss: 0.0395 (0.0366) time: 2.6371 data: 0.0060 max mem: 33369 +Epoch: [31] [1050/1319] eta: 0:11:47 lr: 1.2014348651488794e-05 loss: 0.0293 (0.0365) time: 2.6373 data: 0.0060 max mem: 33369 +Epoch: [31] [1060/1319] eta: 0:11:21 lr: 1.2004354738708488e-05 loss: 0.0284 (0.0365) time: 2.6187 data: 0.0057 max mem: 33369 +Epoch: [31] [1070/1319] eta: 0:10:54 lr: 1.1994359901379014e-05 loss: 0.0326 (0.0365) time: 2.5899 data: 0.0058 max mem: 33369 +Epoch: [31] [1080/1319] eta: 0:10:28 lr: 1.1984364138558649e-05 loss: 0.0326 (0.0365) time: 2.6261 data: 0.0059 max mem: 33369 +Epoch: [31] [1090/1319] eta: 0:10:02 lr: 1.1974367449303851e-05 loss: 0.0316 (0.0365) time: 2.6488 data: 0.0059 max mem: 33369 +Epoch: [31] [1100/1319] eta: 0:09:35 lr: 1.1964369832669236e-05 loss: 0.0370 (0.0366) time: 2.6447 data: 0.0059 max mem: 33369 +Epoch: [31] [1110/1319] eta: 0:09:09 lr: 1.195437128770757e-05 loss: 0.0317 (0.0365) time: 2.6602 data: 0.0059 max mem: 33369 +Epoch: [31] [1120/1319] eta: 0:08:43 lr: 1.194437181346979e-05 loss: 0.0305 (0.0365) time: 2.6385 data: 0.0058 max mem: 33369 +Epoch: [31] [1130/1319] eta: 0:08:17 lr: 1.1934371409004944e-05 loss: 0.0311 (0.0365) time: 2.6120 data: 0.0058 max mem: 33369 +Epoch: [31] [1140/1319] eta: 0:07:50 lr: 1.192437007336025e-05 loss: 0.0341 (0.0365) time: 2.6246 data: 0.0061 max mem: 33369 +Epoch: [31] [1150/1319] eta: 0:07:24 lr: 1.1914367805581053e-05 loss: 0.0341 (0.0365) time: 2.6394 data: 0.0059 max mem: 33369 +Epoch: [31] [1160/1319] eta: 0:06:58 lr: 1.1904364604710826e-05 loss: 0.0352 (0.0365) time: 2.6016 data: 0.0057 max mem: 33369 +Epoch: [31] [1170/1319] eta: 0:06:31 lr: 1.1894360469791169e-05 loss: 0.0308 (0.0365) time: 2.6062 data: 0.0058 max mem: 33369 +Epoch: [31] [1180/1319] eta: 0:06:05 lr: 1.1884355399861802e-05 loss: 0.0308 (0.0365) time: 2.6546 data: 0.0058 max mem: 33369 +Epoch: [31] [1190/1319] eta: 0:05:39 lr: 1.1874349393960545e-05 loss: 0.0374 (0.0365) time: 2.6361 data: 0.0059 max mem: 33369 +Epoch: [31] [1200/1319] eta: 0:05:12 lr: 1.1864342451123342e-05 loss: 0.0344 (0.0365) time: 2.6271 data: 0.0060 max mem: 33369 +Epoch: [31] [1210/1319] eta: 0:04:46 lr: 1.1854334570384235e-05 loss: 0.0325 (0.0365) time: 2.6247 data: 0.0060 max mem: 33369 +Epoch: [31] [1220/1319] eta: 0:04:20 lr: 1.1844325750775364e-05 loss: 0.0291 (0.0364) time: 2.5986 data: 0.0060 max mem: 33369 +Epoch: [31] [1230/1319] eta: 0:03:53 lr: 1.183431599132696e-05 loss: 0.0348 (0.0364) time: 2.5896 data: 0.0061 max mem: 33369 +Epoch: [31] [1240/1319] eta: 0:03:27 lr: 1.1824305291067328e-05 loss: 0.0315 (0.0365) time: 2.6196 data: 0.0059 max mem: 33369 +Epoch: [31] [1250/1319] eta: 0:03:01 lr: 1.1814293649022872e-05 loss: 0.0308 (0.0364) time: 2.6305 data: 0.0059 max mem: 33369 +Epoch: [31] [1260/1319] eta: 0:02:35 lr: 1.180428106421806e-05 loss: 0.0316 (0.0364) time: 2.6290 data: 0.0059 max mem: 33369 +Epoch: [31] [1270/1319] eta: 0:02:08 lr: 1.1794267535675433e-05 loss: 0.0310 (0.0364) time: 2.6221 data: 0.0060 max mem: 33369 +Epoch: [31] [1280/1319] eta: 0:01:42 lr: 1.1784253062415594e-05 loss: 0.0310 (0.0364) time: 2.6056 data: 0.0059 max mem: 33369 +Epoch: [31] [1290/1319] eta: 0:01:16 lr: 1.1774237643457209e-05 loss: 0.0327 (0.0364) time: 2.6067 data: 0.0058 max mem: 33369 +Epoch: [31] [1300/1319] eta: 0:00:49 lr: 1.1764221277816978e-05 loss: 0.0373 (0.0364) time: 2.6143 data: 0.0059 max mem: 33369 +Epoch: [31] [1310/1319] eta: 0:00:23 lr: 1.1754203964509668e-05 loss: 0.0382 (0.0364) time: 2.6399 data: 0.0060 max mem: 33369 +Epoch: [31] Total time: 0:57:47 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 1:58:51 time: 2.7718 data: 2.6930 max mem: 33369 +Test: [ 100/2573] eta: 0:04:03 time: 0.0716 data: 0.0011 max mem: 33369 +Test: [ 200/2573] eta: 0:03:25 time: 0.0733 data: 0.0011 max mem: 33369 +Test: [ 300/2573] eta: 0:03:05 time: 0.0750 data: 0.0011 max mem: 33369 +Test: [ 400/2573] eta: 0:02:52 time: 0.0751 data: 0.0011 max mem: 33369 +Test: [ 500/2573] eta: 0:02:42 time: 0.0737 data: 0.0011 max mem: 33369 +Test: [ 600/2573] eta: 0:02:33 time: 0.0736 data: 0.0011 max mem: 33369 +Test: [ 700/2573] eta: 0:02:25 time: 0.0737 data: 0.0011 max mem: 33369 +Test: [ 800/2573] eta: 0:02:16 time: 0.0769 data: 0.0011 max mem: 33369 +Test: [ 900/2573] eta: 0:02:08 time: 0.0736 data: 0.0011 max mem: 33369 +Test: [1000/2573] eta: 0:02:00 time: 0.0739 data: 0.0011 max mem: 33369 +Test: [1100/2573] eta: 0:01:52 time: 0.0738 data: 0.0011 max mem: 33369 +Test: [1200/2573] eta: 0:01:44 time: 0.0737 data: 0.0011 max mem: 33369 +Test: [1300/2573] eta: 0:01:36 time: 0.0737 data: 0.0011 max mem: 33369 +Test: [1400/2573] eta: 0:01:28 time: 0.0721 data: 0.0011 max mem: 33369 +Test: [1500/2573] eta: 0:01:21 time: 0.0739 data: 0.0011 max mem: 33369 +Test: [1600/2573] eta: 0:01:13 time: 0.0770 data: 0.0011 max mem: 33369 +Test: [1700/2573] eta: 0:01:05 time: 0.0723 data: 0.0011 max mem: 33369 +Test: [1800/2573] eta: 0:00:58 time: 0.0754 data: 0.0011 max mem: 33369 +Test: [1900/2573] eta: 0:00:50 time: 0.0721 data: 0.0011 max mem: 33369 +Test: [2000/2573] eta: 0:00:43 time: 0.0738 data: 0.0011 max mem: 33369 +Test: [2100/2573] eta: 0:00:35 time: 0.0755 data: 0.0011 max mem: 33369 +Test: [2200/2573] eta: 0:00:27 time: 0.0756 data: 0.0011 max mem: 33369 +Test: [2300/2573] eta: 0:00:20 time: 0.0758 data: 0.0012 max mem: 33369 +Test: [2400/2573] eta: 0:00:12 time: 0.0704 data: 0.0011 max mem: 33369 +Test: [2500/2573] eta: 0:00:05 time: 0.0738 data: 0.0011 max mem: 33369 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: Total time: 0:03:12 +Final results: +Mean IoU is 64.22 + + precision@0.5 = 72.06 + precision@0.6 = 67.30 + precision@0.7 = 60.80 + precision@0.8 = 49.37 + precision@0.9 = 25.06 + overall IoU = 61.95 + +Average object IoU 64.21570301801938 +Overall IoU 61.951988220214844 +Better epoch: 31 + +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [32] [ 0/1319] eta: 1:23:39 lr: 1.1745187571461855e-05 loss: 0.0268 (0.0268) time: 3.8058 data: 1.1235 max mem: 33369 +Epoch: [32] [ 10/1319] eta: 0:59:26 lr: 1.1735168454865734e-05 loss: 0.0257 (0.0293) time: 2.7247 data: 0.1077 max mem: 33369 +Epoch: [32] [ 20/1319] eta: 0:57:34 lr: 1.1725148387734231e-05 loss: 0.0295 (0.0317) time: 2.6020 data: 0.0058 max mem: 33369 +Epoch: [32] [ 30/1319] eta: 0:56:36 lr: 1.1715127369074435e-05 loss: 0.0356 (0.0338) time: 2.5854 data: 0.0060 max mem: 33369 +Epoch: [32] [ 40/1319] eta: 0:55:51 lr: 1.1705105397891451e-05 loss: 0.0334 (0.0330) time: 2.5800 data: 0.0064 max mem: 33369 +Epoch: [32] [ 50/1319] eta: 0:55:21 lr: 1.1695082473188386e-05 loss: 0.0327 (0.0333) time: 2.5900 data: 0.0062 max mem: 33369 +Epoch: [32] [ 60/1319] eta: 0:54:49 lr: 1.1685058593966367e-05 loss: 0.0316 (0.0329) time: 2.5967 data: 0.0063 max mem: 33369 +Epoch: [32] [ 70/1319] eta: 0:54:29 lr: 1.1675033759224512e-05 loss: 0.0282 (0.0325) time: 2.6194 data: 0.0063 max mem: 33369 +Epoch: [32] [ 80/1319] eta: 0:53:56 lr: 1.1665007967959945e-05 loss: 0.0325 (0.0328) time: 2.6097 data: 0.0061 max mem: 33369 +Epoch: [32] [ 90/1319] eta: 0:53:38 lr: 1.1654981219167763e-05 loss: 0.0338 (0.0335) time: 2.6214 data: 0.0061 max mem: 33369 +Epoch: [32] [ 100/1319] eta: 0:53:12 lr: 1.1644953511841062e-05 loss: 0.0337 (0.0336) time: 2.6477 data: 0.0061 max mem: 33369 +Epoch: [32] [ 110/1319] eta: 0:52:46 lr: 1.1634924844970898e-05 loss: 0.0337 (0.0336) time: 2.6192 data: 0.0061 max mem: 33369 +Epoch: [32] [ 120/1319] eta: 0:52:25 lr: 1.1624895217546308e-05 loss: 0.0356 (0.0337) time: 2.6432 data: 0.0060 max mem: 33369 +Epoch: [32] [ 130/1319] eta: 0:51:54 lr: 1.1614864628554293e-05 loss: 0.0290 (0.0336) time: 2.6256 data: 0.0062 max mem: 33369 +Epoch: [32] [ 140/1319] eta: 0:51:29 lr: 1.160483307697981e-05 loss: 0.0279 (0.0340) time: 2.6022 data: 0.0062 max mem: 33369 +Epoch: [32] [ 150/1319] eta: 0:51:02 lr: 1.159480056180578e-05 loss: 0.0299 (0.0338) time: 2.6213 data: 0.0063 max mem: 33369 +Epoch: [32] [ 160/1319] eta: 0:50:35 lr: 1.1584767082013038e-05 loss: 0.0299 (0.0338) time: 2.6100 data: 0.0062 max mem: 33369 +Epoch: [32] [ 170/1319] eta: 0:50:09 lr: 1.1574732636580395e-05 loss: 0.0292 (0.0336) time: 2.6130 data: 0.0060 max mem: 33369 +Epoch: [32] [ 180/1319] eta: 0:49:41 lr: 1.1564697224484583e-05 loss: 0.0285 (0.0333) time: 2.6093 data: 0.0060 max mem: 33369 +Epoch: [32] [ 190/1319] eta: 0:49:14 lr: 1.1554660844700256e-05 loss: 0.0290 (0.0334) time: 2.5996 data: 0.0060 max mem: 33369 +Epoch: [32] [ 200/1319] eta: 0:48:49 lr: 1.1544623496200004e-05 loss: 0.0308 (0.0335) time: 2.6189 data: 0.0062 max mem: 33369 +Epoch: [32] [ 210/1319] eta: 0:48:24 lr: 1.153458517795431e-05 loss: 0.0319 (0.0336) time: 2.6370 data: 0.0061 max mem: 33369 +Epoch: [32] [ 220/1319] eta: 0:47:57 lr: 1.1524545888931584e-05 loss: 0.0312 (0.0336) time: 2.6236 data: 0.0059 max mem: 33369 +Epoch: [32] [ 230/1319] eta: 0:47:30 lr: 1.1514505628098139e-05 loss: 0.0303 (0.0335) time: 2.6000 data: 0.0061 max mem: 33369 +Epoch: [32] [ 240/1319] eta: 0:47:05 lr: 1.1504464394418176e-05 loss: 0.0315 (0.0339) time: 2.6156 data: 0.0062 max mem: 33369 +Epoch: [32] [ 250/1319] eta: 0:46:40 lr: 1.149442218685379e-05 loss: 0.0311 (0.0337) time: 2.6449 data: 0.0060 max mem: 33369 +Epoch: [32] [ 260/1319] eta: 0:46:13 lr: 1.1484379004364971e-05 loss: 0.0277 (0.0335) time: 2.6308 data: 0.0060 max mem: 33369 +Epoch: [32] [ 270/1319] eta: 0:45:47 lr: 1.147433484590956e-05 loss: 0.0314 (0.0340) time: 2.6091 data: 0.0061 max mem: 33369 +Epoch: [32] [ 280/1319] eta: 0:45:23 lr: 1.1464289710443295e-05 loss: 0.0342 (0.0341) time: 2.6514 data: 0.0060 max mem: 33369 +Epoch: [32] [ 290/1319] eta: 0:44:57 lr: 1.1454243596919765e-05 loss: 0.0347 (0.0346) time: 2.6611 data: 0.0059 max mem: 33369 +Epoch: [32] [ 300/1319] eta: 0:44:31 lr: 1.144419650429042e-05 loss: 0.0360 (0.0347) time: 2.6180 data: 0.0060 max mem: 33369 +Epoch: [32] [ 310/1319] eta: 0:44:05 lr: 1.1434148431504575e-05 loss: 0.0285 (0.0345) time: 2.6212 data: 0.0060 max mem: 33369 +Epoch: [32] [ 320/1319] eta: 0:43:39 lr: 1.1424099377509363e-05 loss: 0.0285 (0.0344) time: 2.6277 data: 0.0059 max mem: 33369 +Epoch: [32] [ 330/1319] eta: 0:43:11 lr: 1.141404934124978e-05 loss: 0.0294 (0.0342) time: 2.6042 data: 0.0062 max mem: 33369 +Epoch: [32] [ 340/1319] eta: 0:42:44 lr: 1.140399832166864e-05 loss: 0.0284 (0.0341) time: 2.5905 data: 0.0063 max mem: 33369 +Epoch: [32] [ 350/1319] eta: 0:42:18 lr: 1.1393946317706594e-05 loss: 0.0301 (0.0341) time: 2.6069 data: 0.0063 max mem: 33369 +Epoch: [32] [ 360/1319] eta: 0:41:52 lr: 1.138389332830211e-05 loss: 0.0326 (0.0341) time: 2.6284 data: 0.0062 max mem: 33369 +Epoch: [32] [ 370/1319] eta: 0:41:26 lr: 1.1373839352391454e-05 loss: 0.0369 (0.0342) time: 2.6171 data: 0.0060 max mem: 33369 +Epoch: [32] [ 380/1319] eta: 0:40:59 lr: 1.1363784388908714e-05 loss: 0.0369 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1.1283308999812288e-05 loss: 0.0335 (0.0351) time: 2.5970 data: 0.0059 max mem: 33369 +Epoch: [32] [ 470/1319] eta: 0:37:02 lr: 1.1273245099849142e-05 loss: 0.0315 (0.0349) time: 2.6192 data: 0.0058 max mem: 33369 +Epoch: [32] [ 480/1319] eta: 0:36:36 lr: 1.1263180201532567e-05 loss: 0.0292 (0.0350) time: 2.6001 data: 0.0058 max mem: 33369 +Epoch: [32] [ 490/1319] eta: 0:36:10 lr: 1.1253114303772065e-05 loss: 0.0291 (0.0349) time: 2.6176 data: 0.0057 max mem: 33369 +Epoch: [32] [ 500/1319] eta: 0:35:44 lr: 1.1243047405474862e-05 loss: 0.0272 (0.0348) time: 2.6418 data: 0.0059 max mem: 33369 +Epoch: [32] [ 510/1319] eta: 0:35:18 lr: 1.1232979505545897e-05 loss: 0.0277 (0.0348) time: 2.6396 data: 0.0060 max mem: 33369 +Epoch: [32] [ 520/1319] eta: 0:34:52 lr: 1.1222910602887823e-05 loss: 0.0312 (0.0347) time: 2.6258 data: 0.0061 max mem: 33369 +Epoch: [32] [ 530/1319] eta: 0:34:27 lr: 1.121284069640098e-05 loss: 0.0346 (0.0347) time: 2.6359 data: 0.0061 max mem: 33369 +Epoch: [32] [ 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2.6438 data: 0.0059 max mem: 33369 +Epoch: [32] [ 700/1319] eta: 0:27:02 lr: 1.1041497623487401e-05 loss: 0.0303 (0.0351) time: 2.6583 data: 0.0060 max mem: 33369 +Epoch: [32] [ 710/1319] eta: 0:26:36 lr: 1.103140945738074e-05 loss: 0.0320 (0.0351) time: 2.6412 data: 0.0061 max mem: 33369 +Epoch: [32] [ 720/1319] eta: 0:26:10 lr: 1.1021320266105851e-05 loss: 0.0360 (0.0352) time: 2.6309 data: 0.0059 max mem: 33369 +Epoch: [32] [ 730/1319] eta: 0:25:43 lr: 1.101123004851561e-05 loss: 0.0354 (0.0352) time: 2.6228 data: 0.0058 max mem: 33369 +Epoch: [32] [ 740/1319] eta: 0:25:17 lr: 1.1001138803460437e-05 loss: 0.0280 (0.0352) time: 2.5908 data: 0.0059 max mem: 33369 +Epoch: [32] [ 750/1319] eta: 0:24:51 lr: 1.099104652978828e-05 loss: 0.0280 (0.0351) time: 2.6066 data: 0.0061 max mem: 33369 +Epoch: [32] [ 760/1319] eta: 0:24:24 lr: 1.0980953226344629e-05 loss: 0.0317 (0.0351) time: 2.6172 data: 0.0061 max mem: 33369 +Epoch: [32] [ 770/1319] eta: 0:23:58 lr: 1.09708588919725e-05 loss: 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1.0890066963908222e-05 loss: 0.0317 (0.0351) time: 2.6207 data: 0.0061 max mem: 33369 +Epoch: [32] [ 860/1319] eta: 0:20:03 lr: 1.087996329870281e-05 loss: 0.0319 (0.0350) time: 2.6458 data: 0.0059 max mem: 33369 +Epoch: [32] [ 870/1319] eta: 0:19:37 lr: 1.0869858590861098e-05 loss: 0.0341 (0.0351) time: 2.6463 data: 0.0057 max mem: 33369 +Epoch: [32] [ 880/1319] eta: 0:19:10 lr: 1.085975283919833e-05 loss: 0.0328 (0.0350) time: 2.6236 data: 0.0059 max mem: 33369 +Epoch: [32] [ 890/1319] eta: 0:18:44 lr: 1.0849646042527184e-05 loss: 0.0320 (0.0351) time: 2.6109 data: 0.0058 max mem: 33369 +Epoch: [32] [ 900/1319] eta: 0:18:18 lr: 1.0839538199657755e-05 loss: 0.0327 (0.0350) time: 2.6086 data: 0.0058 max mem: 33369 +Epoch: [32] [ 910/1319] eta: 0:17:52 lr: 1.0829429309397535e-05 loss: 0.0294 (0.0351) time: 2.6029 data: 0.0059 max mem: 33369 +Epoch: [32] [ 920/1319] eta: 0:17:25 lr: 1.0819319370551438e-05 loss: 0.0336 (0.0351) time: 2.6296 data: 0.0060 max mem: 33369 +Epoch: [32] [ 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33369 +Epoch: [32] [1010/1319] eta: 0:13:29 lr: 1.0728282536084938e-05 loss: 0.0343 (0.0350) time: 2.6157 data: 0.0059 max mem: 33369 +Epoch: [32] [1020/1319] eta: 0:13:03 lr: 1.0718162045072395e-05 loss: 0.0325 (0.0349) time: 2.6029 data: 0.0059 max mem: 33369 +Epoch: [32] [1030/1319] eta: 0:12:37 lr: 1.0708040492154082e-05 loss: 0.0267 (0.0349) time: 2.6184 data: 0.0059 max mem: 33369 +Epoch: [32] [1040/1319] eta: 0:12:11 lr: 1.069791787610307e-05 loss: 0.0293 (0.0348) time: 2.6182 data: 0.0060 max mem: 33369 +Epoch: [32] [1050/1319] eta: 0:11:44 lr: 1.0687794195689722e-05 loss: 0.0317 (0.0349) time: 2.5873 data: 0.0060 max mem: 33369 +Epoch: [32] [1060/1319] eta: 0:11:18 lr: 1.0677669449681687e-05 loss: 0.0359 (0.0349) time: 2.5954 data: 0.0060 max mem: 33369 +Epoch: [32] [1070/1319] eta: 0:10:52 lr: 1.0667543636843873e-05 loss: 0.0364 (0.0349) time: 2.6111 data: 0.0061 max mem: 33369 +Epoch: [32] [1080/1319] eta: 0:10:26 lr: 1.0657416755938468e-05 loss: 0.0364 (0.0350) time: 2.6332 data: 0.0060 max mem: 33369 +Epoch: [32] [1090/1319] eta: 0:10:00 lr: 1.0647288805724908e-05 loss: 0.0319 (0.0350) time: 2.6394 data: 0.0058 max mem: 33369 +Epoch: [32] [1100/1319] eta: 0:09:33 lr: 1.0637159784959879e-05 loss: 0.0334 (0.0350) time: 2.6200 data: 0.0057 max mem: 33369 +Epoch: [32] [1110/1319] eta: 0:09:07 lr: 1.0627029692397306e-05 loss: 0.0361 (0.0350) time: 2.5932 data: 0.0057 max mem: 33369 +Epoch: [32] [1120/1319] eta: 0:08:41 lr: 1.0616898526788328e-05 loss: 0.0336 (0.0351) time: 2.6155 data: 0.0057 max mem: 33369 +Epoch: [32] [1130/1319] eta: 0:08:15 lr: 1.0606766286881316e-05 loss: 0.0332 (0.0350) time: 2.6286 data: 0.0057 max mem: 33369 +Epoch: [32] [1140/1319] eta: 0:07:48 lr: 1.059663297142185e-05 loss: 0.0306 (0.0350) time: 2.6018 data: 0.0058 max mem: 33369 +Epoch: [32] [1150/1319] eta: 0:07:22 lr: 1.058649857915271e-05 loss: 0.0312 (0.0350) time: 2.5875 data: 0.0059 max mem: 33369 +Epoch: [32] [1160/1319] eta: 0:06:56 lr: 1.0576363108813862e-05 loss: 0.0325 (0.0350) time: 2.6102 data: 0.0058 max mem: 33369 +Epoch: [32] [1170/1319] eta: 0:06:30 lr: 1.0566226559142468e-05 loss: 0.0355 (0.0350) time: 2.6058 data: 0.0057 max mem: 33369 +Epoch: [32] [1180/1319] eta: 0:06:04 lr: 1.0556088928872841e-05 loss: 0.0344 (0.0350) time: 2.6186 data: 0.0057 max mem: 33369 +Epoch: [32] [1190/1319] eta: 0:05:37 lr: 1.0545950216736473e-05 loss: 0.0294 (0.0350) time: 2.6317 data: 0.0058 max mem: 33369 +Epoch: [32] [1200/1319] eta: 0:05:11 lr: 1.0535810421462011e-05 loss: 0.0350 (0.0350) time: 2.6274 data: 0.0058 max mem: 33369 +Epoch: [32] [1210/1319] eta: 0:04:45 lr: 1.0525669541775238e-05 loss: 0.0359 (0.0350) time: 2.6356 data: 0.0057 max mem: 33369 +Epoch: [32] [1220/1319] eta: 0:04:19 lr: 1.0515527576399085e-05 loss: 0.0315 (0.0350) time: 2.6135 data: 0.0059 max mem: 33369 +Epoch: [32] [1230/1319] eta: 0:03:53 lr: 1.050538452405359e-05 loss: 0.0341 (0.0350) time: 2.6337 data: 0.0059 max mem: 33369 +Epoch: [32] [1240/1319] eta: 0:03:26 lr: 1.049524038345592e-05 loss: 0.0332 (0.0350) time: 2.6600 data: 0.0057 max mem: 33369 +Epoch: [32] [1250/1319] eta: 0:03:00 lr: 1.048509515332035e-05 loss: 0.0320 (0.0350) time: 2.6407 data: 0.0058 max mem: 33369 +Epoch: [32] [1260/1319] eta: 0:02:34 lr: 1.0474948832358245e-05 loss: 0.0332 (0.0349) time: 2.6185 data: 0.0058 max mem: 33369 +Epoch: [32] [1270/1319] eta: 0:02:08 lr: 1.0464801419278068e-05 loss: 0.0367 (0.0350) time: 2.6173 data: 0.0058 max mem: 33369 +Epoch: [32] [1280/1319] eta: 0:01:42 lr: 1.0454652912785337e-05 loss: 0.0345 (0.0350) time: 2.6394 data: 0.0057 max mem: 33369 +Epoch: [32] [1290/1319] eta: 0:01:16 lr: 1.0444503311582662e-05 loss: 0.0323 (0.0350) time: 2.6558 data: 0.0057 max mem: 33369 +Epoch: [32] [1300/1319] eta: 0:00:49 lr: 1.0434352614369702e-05 loss: 0.0331 (0.0351) time: 2.6358 data: 0.0058 max mem: 33369 +Epoch: [32] [1310/1319] eta: 0:00:23 lr: 1.0424200819843158e-05 loss: 0.0330 (0.0351) time: 2.6215 data: 0.0057 max mem: 33369 +Epoch: [32] Total time: 0:57:37 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 1:56:18 time: 2.7122 data: 2.6338 max mem: 33369 +Test: [ 100/2573] eta: 0:04:02 time: 0.0718 data: 0.0011 max mem: 33369 +Test: [ 200/2573] eta: 0:03:24 time: 0.0734 data: 0.0011 max mem: 33369 +Test: [ 300/2573] eta: 0:03:05 time: 0.0751 data: 0.0011 max mem: 33369 +Test: [ 400/2573] eta: 0:02:52 time: 0.0751 data: 0.0011 max mem: 33369 +Test: [ 500/2573] eta: 0:02:42 time: 0.0736 data: 0.0011 max mem: 33369 +Test: [ 600/2573] eta: 0:02:33 time: 0.0736 data: 0.0011 max mem: 33369 +Test: [ 700/2573] eta: 0:02:24 time: 0.0738 data: 0.0012 max mem: 33369 +Test: [ 800/2573] eta: 0:02:16 time: 0.0772 data: 0.0011 max mem: 33369 +Test: [ 900/2573] eta: 0:02:08 time: 0.0738 data: 0.0011 max mem: 33369 +Test: [1000/2573] eta: 0:02:00 time: 0.0739 data: 0.0011 max mem: 33369 +Test: [1100/2573] eta: 0:01:52 time: 0.0739 data: 0.0011 max mem: 33369 +Test: [1200/2573] eta: 0:01:44 time: 0.0738 data: 0.0011 max mem: 33369 +Test: [1300/2573] eta: 0:01:36 time: 0.0738 data: 0.0011 max mem: 33369 +Test: [1400/2573] eta: 0:01:28 time: 0.0721 data: 0.0011 max mem: 33369 +Test: [1500/2573] eta: 0:01:21 time: 0.0738 data: 0.0011 max mem: 33369 +Test: [1600/2573] eta: 0:01:13 time: 0.0772 data: 0.0011 max mem: 33369 +Test: [1700/2573] eta: 0:01:05 time: 0.0721 data: 0.0011 max mem: 33369 +Test: [1800/2573] eta: 0:00:58 time: 0.0755 data: 0.0011 max mem: 33369 +Test: [1900/2573] eta: 0:00:50 time: 0.0723 data: 0.0011 max mem: 33369 +Test: [2000/2573] eta: 0:00:43 time: 0.0739 data: 0.0011 max mem: 33369 +Test: [2100/2573] eta: 0:00:35 time: 0.0755 data: 0.0011 max mem: 33369 +Test: [2200/2573] eta: 0:00:27 time: 0.0754 data: 0.0011 max mem: 33369 +Test: [2300/2573] eta: 0:00:20 time: 0.0755 data: 0.0011 max mem: 33369 +Test: [2400/2573] eta: 0:00:12 time: 0.0706 data: 0.0011 max mem: 33369 +Test: [2500/2573] eta: 0:00:05 time: 0.0738 data: 0.0011 max mem: 33369 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: Total time: 0:03:13 +Final results: +Mean IoU is 64.29 + + precision@0.5 = 72.26 + precision@0.6 = 66.87 + precision@0.7 = 60.29 + precision@0.8 = 49.22 + precision@0.9 = 24.69 + overall IoU = 61.71 + +Average object IoU 64.29022282050298 +Overall IoU 61.70639419555664 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [33] [ 0/1319] eta: 3:02:06 lr: 1.04150632654866e-05 loss: 0.0267 (0.0267) time: 8.2837 data: 1.7119 max mem: 33369 +Epoch: [33] [ 10/1319] eta: 1:08:32 lr: 1.0404909382463066e-05 loss: 0.0247 (0.0266) time: 3.1420 data: 0.1614 max mem: 33369 +Epoch: [33] [ 20/1319] eta: 1:02:20 lr: 1.0394754398329612e-05 loss: 0.0291 (0.0312) time: 2.6095 data: 0.0061 max mem: 33369 +Epoch: [33] [ 30/1319] eta: 1:00:04 lr: 1.0384598311771345e-05 loss: 0.0302 (0.0311) time: 2.6068 data: 0.0060 max mem: 33369 +Epoch: [33] [ 40/1319] eta: 0:58:42 lr: 1.0374441121470351e-05 loss: 0.0287 (0.0317) time: 2.6229 data: 0.0060 max mem: 33369 +Epoch: [33] [ 50/1319] eta: 0:57:37 lr: 1.0364282826105723e-05 loss: 0.0303 (0.0331) time: 2.6137 data: 0.0062 max mem: 33369 +Epoch: [33] [ 60/1319] eta: 0:56:46 lr: 1.0354123424353528e-05 loss: 0.0325 (0.0335) time: 2.6059 data: 0.0061 max mem: 33369 +Epoch: [33] [ 70/1319] eta: 0:56:06 lr: 1.0343962914886797e-05 loss: 0.0333 (0.0336) time: 2.6200 data: 0.0061 max mem: 33369 +Epoch: [33] [ 80/1319] eta: 0:55:28 lr: 1.033380129637553e-05 loss: 0.0312 (0.0335) time: 2.6277 data: 0.0062 max mem: 33369 +Epoch: [33] [ 90/1319] eta: 0:54:54 lr: 1.0323638567486653e-05 loss: 0.0312 (0.0338) time: 2.6265 data: 0.0062 max mem: 33369 +Epoch: [33] [ 100/1319] eta: 0:54:19 lr: 1.0313474726884054e-05 loss: 0.0329 (0.0345) time: 2.6246 data: 0.0062 max mem: 33369 +Epoch: [33] [ 110/1319] eta: 0:53:51 lr: 1.0303309773228537e-05 loss: 0.0315 (0.0341) time: 2.6402 data: 0.0060 max mem: 33369 +Epoch: [33] [ 120/1319] eta: 0:53:20 lr: 1.0293143705177821e-05 loss: 0.0309 (0.0339) time: 2.6450 data: 0.0062 max mem: 33369 +Epoch: [33] [ 130/1319] eta: 0:52:43 lr: 1.0282976521386539e-05 loss: 0.0317 (0.0340) time: 2.5946 data: 0.0062 max mem: 33369 +Epoch: [33] [ 140/1319] eta: 0:52:12 lr: 1.0272808220506222e-05 loss: 0.0334 (0.0343) time: 2.5832 data: 0.0060 max mem: 33369 +Epoch: [33] [ 150/1319] eta: 0:51:42 lr: 1.026263880118526e-05 loss: 0.0367 (0.0346) time: 2.6092 data: 0.0060 max mem: 33369 +Epoch: [33] [ 160/1319] eta: 0:51:15 lr: 1.0252468262068951e-05 loss: 0.0298 (0.0343) time: 2.6282 data: 0.0064 max mem: 33369 +Epoch: [33] [ 170/1319] eta: 0:50:48 lr: 1.024229660179944e-05 loss: 0.0303 (0.0344) time: 2.6491 data: 0.0064 max mem: 33369 +Epoch: [33] [ 180/1319] eta: 0:50:22 lr: 1.023212381901573e-05 loss: 0.0321 (0.0345) time: 2.6536 data: 0.0061 max mem: 33369 +Epoch: [33] [ 190/1319] eta: 0:49:53 lr: 1.0221949912353669e-05 loss: 0.0319 (0.0344) time: 2.6303 data: 0.0062 max mem: 33369 +Epoch: [33] [ 200/1319] eta: 0:49:24 lr: 1.0211774880445919e-05 loss: 0.0298 (0.0344) time: 2.6109 data: 0.0061 max mem: 33369 +Epoch: [33] [ 210/1319] eta: 0:48:56 lr: 1.0201598721921983e-05 loss: 0.0298 (0.0344) time: 2.6143 data: 0.0059 max mem: 33369 +Epoch: [33] [ 220/1319] eta: 0:48:28 lr: 1.0191421435408169e-05 loss: 0.0353 (0.0350) time: 2.6193 data: 0.0059 max mem: 33369 +Epoch: [33] [ 230/1319] eta: 0:48:00 lr: 1.0181243019527578e-05 loss: 0.0314 (0.0349) time: 2.6199 data: 0.0058 max mem: 33369 +Epoch: [33] [ 240/1319] eta: 0:47:33 lr: 1.0171063472900106e-05 loss: 0.0267 (0.0348) time: 2.6200 data: 0.0058 max mem: 33369 +Epoch: [33] [ 250/1319] eta: 0:47:06 lr: 1.0160882794142423e-05 loss: 0.0284 (0.0349) time: 2.6343 data: 0.0060 max mem: 33369 +Epoch: [33] [ 260/1319] eta: 0:46:36 lr: 1.0150700981867957e-05 loss: 0.0284 (0.0348) time: 2.6013 data: 0.0062 max mem: 33369 +Epoch: [33] [ 270/1319] eta: 0:46:09 lr: 1.01405180346869e-05 loss: 0.0276 (0.0345) time: 2.5819 data: 0.0061 max mem: 33369 +Epoch: [33] [ 280/1319] eta: 0:45:42 lr: 1.0130333951206182e-05 loss: 0.0276 (0.0345) time: 2.6194 data: 0.0060 max mem: 33369 +Epoch: [33] [ 290/1319] eta: 0:45:16 lr: 1.0120148730029472e-05 loss: 0.0317 (0.0344) time: 2.6374 data: 0.0060 max mem: 33369 +Epoch: [33] [ 300/1319] eta: 0:44:48 lr: 1.0109962369757157e-05 loss: 0.0286 (0.0344) time: 2.6235 data: 0.0060 max mem: 33369 +Epoch: [33] [ 310/1319] eta: 0:44:22 lr: 1.0099774868986322e-05 loss: 0.0281 (0.0342) time: 2.6292 data: 0.0061 max mem: 33369 +Epoch: [33] [ 320/1319] eta: 0:43:54 lr: 1.008958622631076e-05 loss: 0.0289 (0.0343) time: 2.6145 data: 0.0061 max mem: 33369 +Epoch: [33] [ 330/1319] eta: 0:43:26 lr: 1.0079396440320953e-05 loss: 0.0347 (0.0343) time: 2.5755 data: 0.0061 max mem: 33369 +Epoch: [33] [ 340/1319] eta: 0:42:59 lr: 1.0069205509604051e-05 loss: 0.0333 (0.0343) time: 2.5943 data: 0.0061 max mem: 33369 +Epoch: [33] [ 350/1319] eta: 0:42:32 lr: 1.0059013432743876e-05 loss: 0.0312 (0.0344) time: 2.6226 data: 0.0060 max mem: 33369 +Epoch: [33] [ 360/1319] eta: 0:42:06 lr: 1.0048820208320883e-05 loss: 0.0312 (0.0343) time: 2.6283 data: 0.0059 max mem: 33369 +Epoch: [33] [ 370/1319] eta: 0:41:39 lr: 1.0038625834912186e-05 loss: 0.0316 (0.0342) time: 2.6164 data: 0.0060 max mem: 33369 +Epoch: [33] [ 380/1319] eta: 0:41:13 lr: 1.0028430311091521e-05 loss: 0.0316 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9.946824533421325e-06 loss: 0.0320 (0.0337) time: 2.6293 data: 0.0060 max mem: 33369 +Epoch: [33] [ 470/1319] eta: 0:37:14 lr: 9.936618591148734e-06 loss: 0.0322 (0.0337) time: 2.6277 data: 0.0060 max mem: 33369 +Epoch: [33] [ 480/1319] eta: 0:36:47 lr: 9.92641148401344e-06 loss: 0.0321 (0.0338) time: 2.6076 data: 0.0059 max mem: 33369 +Epoch: [33] [ 490/1319] eta: 0:36:20 lr: 9.916203210551294e-06 loss: 0.0344 (0.0339) time: 2.5970 data: 0.0061 max mem: 33369 +Epoch: [33] [ 500/1319] eta: 0:35:54 lr: 9.905993769294629e-06 loss: 0.0333 (0.0339) time: 2.6194 data: 0.0061 max mem: 33369 +Epoch: [33] [ 510/1319] eta: 0:35:27 lr: 9.895783158772255e-06 loss: 0.0332 (0.0340) time: 2.6138 data: 0.0061 max mem: 33369 +Epoch: [33] [ 520/1319] eta: 0:35:01 lr: 9.885571377509421e-06 loss: 0.0355 (0.0340) time: 2.6037 data: 0.0060 max mem: 33369 +Epoch: [33] [ 530/1319] eta: 0:34:34 lr: 9.875358424027841e-06 loss: 0.0320 (0.0341) time: 2.6073 data: 0.0058 max mem: 33369 +Epoch: [33] [ 540/1319] eta: 0:34:08 lr: 9.865144296845656e-06 loss: 0.0330 (0.0341) time: 2.6128 data: 0.0059 max mem: 33369 +Epoch: [33] [ 550/1319] eta: 0:33:41 lr: 9.85492899447742e-06 loss: 0.0334 (0.0341) time: 2.6120 data: 0.0060 max mem: 33369 +Epoch: [33] [ 560/1319] eta: 0:33:14 lr: 9.844712515434104e-06 loss: 0.0305 (0.0340) time: 2.5972 data: 0.0060 max mem: 33369 +Epoch: [33] [ 570/1319] eta: 0:32:48 lr: 9.83449485822307e-06 loss: 0.0315 (0.0341) time: 2.6127 data: 0.0063 max mem: 33369 +Epoch: [33] [ 580/1319] eta: 0:32:21 lr: 9.824276021348049e-06 loss: 0.0333 (0.0341) time: 2.6179 data: 0.0062 max mem: 33369 +Epoch: [33] [ 590/1319] eta: 0:31:55 lr: 9.814056003309152e-06 loss: 0.0332 (0.0341) time: 2.5985 data: 0.0059 max mem: 33369 +Epoch: [33] [ 600/1319] eta: 0:31:29 lr: 9.803834802602848e-06 loss: 0.0332 (0.0341) time: 2.6209 data: 0.0059 max mem: 33369 +Epoch: [33] [ 610/1319] eta: 0:31:02 lr: 9.793612417721937e-06 loss: 0.0311 (0.0341) time: 2.6373 data: 0.0059 max mem: 33369 +Epoch: 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mem: 33369 +Epoch: [33] [ 700/1319] eta: 0:27:05 lr: 9.701557415421759e-06 loss: 0.0316 (0.0342) time: 2.6292 data: 0.0058 max mem: 33369 +Epoch: [33] [ 710/1319] eta: 0:26:39 lr: 9.69132310508487e-06 loss: 0.0330 (0.0341) time: 2.6407 data: 0.0059 max mem: 33369 +Epoch: [33] [ 720/1319] eta: 0:26:13 lr: 9.681087593749006e-06 loss: 0.0317 (0.0341) time: 2.6270 data: 0.0058 max mem: 33369 +Epoch: [33] [ 730/1319] eta: 0:25:46 lr: 9.670850879862032e-06 loss: 0.0312 (0.0341) time: 2.6122 data: 0.0059 max mem: 33369 +Epoch: [33] [ 740/1319] eta: 0:25:20 lr: 9.660612961867972e-06 loss: 0.0309 (0.0341) time: 2.6113 data: 0.0061 max mem: 33369 +Epoch: [33] [ 750/1319] eta: 0:24:54 lr: 9.650373838207014e-06 loss: 0.0316 (0.0341) time: 2.6050 data: 0.0060 max mem: 33369 +Epoch: [33] [ 760/1319] eta: 0:24:27 lr: 9.640133507315477e-06 loss: 0.0334 (0.0342) time: 2.5797 data: 0.0060 max mem: 33369 +Epoch: [33] [ 770/1319] eta: 0:24:01 lr: 9.62989196762581e-06 loss: 0.0347 (0.0342) time: 2.6097 data: 0.0060 max mem: 33369 +Epoch: [33] [ 780/1319] eta: 0:23:35 lr: 9.61964921756657e-06 loss: 0.0310 (0.0341) time: 2.6394 data: 0.0060 max mem: 33369 +Epoch: [33] [ 790/1319] eta: 0:23:09 lr: 9.609405255562397e-06 loss: 0.0306 (0.0341) time: 2.6489 data: 0.0060 max mem: 33369 +Epoch: [33] [ 800/1319] eta: 0:22:42 lr: 9.599160080034027e-06 loss: 0.0300 (0.0341) time: 2.6456 data: 0.0060 max mem: 33369 +Epoch: [33] [ 810/1319] eta: 0:22:16 lr: 9.588913689398257e-06 loss: 0.0306 (0.0341) time: 2.6142 data: 0.0059 max mem: 33369 +Epoch: [33] [ 820/1319] eta: 0:21:50 lr: 9.578666082067937e-06 loss: 0.0284 (0.0341) time: 2.6126 data: 0.0058 max mem: 33369 +Epoch: [33] [ 830/1319] eta: 0:21:23 lr: 9.568417256451955e-06 loss: 0.0303 (0.0342) time: 2.6218 data: 0.0058 max mem: 33369 +Epoch: [33] [ 840/1319] eta: 0:20:57 lr: 9.558167210955227e-06 loss: 0.0352 (0.0342) time: 2.6259 data: 0.0059 max mem: 33369 +Epoch: [33] [ 850/1319] eta: 0:20:31 lr: 9.547915943978656e-06 loss: 0.0364 (0.0342) time: 2.6160 data: 0.0058 max mem: 33369 +Epoch: [33] [ 860/1319] eta: 0:20:05 lr: 9.537663453919165e-06 loss: 0.0392 (0.0342) time: 2.6550 data: 0.0060 max mem: 33369 +Epoch: [33] [ 870/1319] eta: 0:19:39 lr: 9.52740973916964e-06 loss: 0.0347 (0.0342) time: 2.6791 data: 0.0061 max mem: 33369 +Epoch: [33] [ 880/1319] eta: 0:19:13 lr: 9.517154798118936e-06 loss: 0.0303 (0.0342) time: 2.6450 data: 0.0059 max mem: 33369 +Epoch: [33] [ 890/1319] eta: 0:18:46 lr: 9.506898629151863e-06 loss: 0.0316 (0.0342) time: 2.6219 data: 0.0059 max mem: 33369 +Epoch: [33] [ 900/1319] eta: 0:18:20 lr: 9.496641230649144e-06 loss: 0.0316 (0.0342) time: 2.6362 data: 0.0062 max mem: 33369 +Epoch: [33] [ 910/1319] eta: 0:17:54 lr: 9.48638260098744e-06 loss: 0.0269 (0.0341) time: 2.6304 data: 0.0060 max mem: 33369 +Epoch: [33] [ 920/1319] eta: 0:17:27 lr: 9.476122738539313e-06 loss: 0.0269 (0.0341) time: 2.6084 data: 0.0061 max mem: 33369 +Epoch: [33] [ 930/1319] eta: 0:17:01 lr: 9.465861641673206e-06 loss: 0.0301 (0.0341) time: 2.6168 data: 0.0060 max mem: 33369 +Epoch: [33] [ 940/1319] eta: 0:16:35 lr: 9.455599308753445e-06 loss: 0.0318 (0.0341) time: 2.6164 data: 0.0059 max mem: 33369 +Epoch: [33] [ 950/1319] eta: 0:16:09 lr: 9.445335738140192e-06 loss: 0.0321 (0.0341) time: 2.6310 data: 0.0060 max mem: 33369 +Epoch: [33] [ 960/1319] eta: 0:15:43 lr: 9.435070928189476e-06 loss: 0.0304 (0.0340) time: 2.6515 data: 0.0059 max mem: 33369 +Epoch: [33] [ 970/1319] eta: 0:15:16 lr: 9.424804877253139e-06 loss: 0.0303 (0.0340) time: 2.6555 data: 0.0059 max mem: 33369 +Epoch: [33] [ 980/1319] eta: 0:14:50 lr: 9.414537583678836e-06 loss: 0.0320 (0.0341) time: 2.6153 data: 0.0059 max mem: 33369 +Epoch: [33] [ 990/1319] eta: 0:14:24 lr: 9.404269045810016e-06 loss: 0.0359 (0.0342) time: 2.6069 data: 0.0059 max mem: 33369 +Epoch: [33] [1000/1319] eta: 0:13:57 lr: 9.393999261985916e-06 loss: 0.0350 (0.0342) time: 2.6328 data: 0.0057 max mem: 33369 +Epoch: [33] [1010/1319] eta: 0:13:31 lr: 9.383728230541512e-06 loss: 0.0313 (0.0341) time: 2.6242 data: 0.0057 max mem: 33369 +Epoch: [33] [1020/1319] eta: 0:13:05 lr: 9.373455949807552e-06 loss: 0.0302 (0.0342) time: 2.6426 data: 0.0058 max mem: 33369 +Epoch: [33] [1030/1319] eta: 0:12:39 lr: 9.363182418110507e-06 loss: 0.0309 (0.0342) time: 2.6307 data: 0.0059 max mem: 33369 +Epoch: [33] [1040/1319] eta: 0:12:12 lr: 9.352907633772557e-06 loss: 0.0309 (0.0342) time: 2.6085 data: 0.0058 max mem: 33369 +Epoch: [33] [1050/1319] eta: 0:11:46 lr: 9.342631595111597e-06 loss: 0.0304 (0.0341) time: 2.6147 data: 0.0059 max mem: 33369 +Epoch: [33] [1060/1319] eta: 0:11:20 lr: 9.332354300441178e-06 loss: 0.0287 (0.0341) time: 2.5852 data: 0.0061 max mem: 33369 +Epoch: [33] [1070/1319] eta: 0:10:53 lr: 9.322075748070539e-06 loss: 0.0281 (0.0341) time: 2.5625 data: 0.0059 max mem: 33369 +Epoch: [33] [1080/1319] eta: 0:10:27 lr: 9.311795936304561e-06 loss: 0.0289 (0.0341) time: 2.5964 data: 0.0060 max mem: 33369 +Epoch: [33] [1090/1319] eta: 0:10:01 lr: 9.301514863443759e-06 loss: 0.0308 (0.0341) time: 2.6222 data: 0.0059 max mem: 33369 +Epoch: [33] [1100/1319] eta: 0:09:35 lr: 9.291232527784269e-06 loss: 0.0355 (0.0342) time: 2.6419 data: 0.0058 max mem: 33369 +Epoch: [33] [1110/1319] eta: 0:09:08 lr: 9.280948927617811e-06 loss: 0.0355 (0.0342) time: 2.6326 data: 0.0059 max mem: 33369 +Epoch: [33] [1120/1319] eta: 0:08:42 lr: 9.270664061231702e-06 loss: 0.0351 (0.0342) time: 2.6225 data: 0.0061 max mem: 33369 +Epoch: [33] [1130/1319] eta: 0:08:16 lr: 9.260377926908826e-06 loss: 0.0332 (0.0342) time: 2.6222 data: 0.0062 max mem: 33369 +Epoch: [33] [1140/1319] eta: 0:07:49 lr: 9.250090522927605e-06 loss: 0.0332 (0.0342) time: 2.6230 data: 0.0060 max mem: 33369 +Epoch: [33] [1150/1319] eta: 0:07:23 lr: 9.239801847562006e-06 loss: 0.0350 (0.0342) time: 2.6261 data: 0.0059 max mem: 33369 +Epoch: [33] [1160/1319] eta: 0:06:57 lr: 9.229511899081506e-06 loss: 0.0326 (0.0342) time: 2.6154 data: 0.0059 max mem: 33369 +Epoch: [33] [1170/1319] eta: 0:06:31 lr: 9.219220675751069e-06 loss: 0.0317 (0.0342) time: 2.6132 data: 0.0059 max mem: 33369 +Epoch: [33] [1180/1319] eta: 0:06:04 lr: 9.20892817583115e-06 loss: 0.0271 (0.0341) time: 2.6242 data: 0.0060 max mem: 33369 +Epoch: [33] [1190/1319] eta: 0:05:38 lr: 9.19863439757767e-06 loss: 0.0299 (0.0342) time: 2.6278 data: 0.0060 max mem: 33369 +Epoch: [33] [1200/1319] eta: 0:05:12 lr: 9.188339339241987e-06 loss: 0.0307 (0.0341) time: 2.6381 data: 0.0060 max mem: 33369 +Epoch: [33] [1210/1319] eta: 0:04:46 lr: 9.178042999070898e-06 loss: 0.0300 (0.0341) time: 2.6533 data: 0.0060 max mem: 33369 +Epoch: [33] [1220/1319] eta: 0:04:19 lr: 9.16774537530659e-06 loss: 0.0331 (0.0341) time: 2.6193 data: 0.0058 max mem: 33369 +Epoch: [33] [1230/1319] eta: 0:03:53 lr: 9.157446466186662e-06 loss: 0.0331 (0.0341) time: 2.5964 data: 0.0056 max mem: 33369 +Epoch: [33] [1240/1319] eta: 0:03:27 lr: 9.147146269944078e-06 loss: 0.0317 (0.0341) time: 2.5985 data: 0.0057 max mem: 33369 +Epoch: [33] [1250/1319] eta: 0:03:01 lr: 9.136844784807162e-06 loss: 0.0318 (0.0341) time: 2.5921 data: 0.0059 max mem: 33369 +Epoch: [33] [1260/1319] eta: 0:02:34 lr: 9.126542008999582e-06 loss: 0.0318 (0.0341) time: 2.5979 data: 0.0061 max mem: 33369 +Epoch: [33] [1270/1319] eta: 0:02:08 lr: 9.11623794074031e-06 loss: 0.0310 (0.0341) time: 2.6249 data: 0.0062 max mem: 33369 +Epoch: [33] [1280/1319] eta: 0:01:42 lr: 9.105932578243631e-06 loss: 0.0280 (0.0341) time: 2.6388 data: 0.0059 max mem: 33369 +Epoch: [33] [1290/1319] eta: 0:01:16 lr: 9.095625919719118e-06 loss: 0.0315 (0.0341) time: 2.6362 data: 0.0059 max mem: 33369 +Epoch: [33] [1300/1319] eta: 0:00:49 lr: 9.085317963371604e-06 loss: 0.0362 (0.0342) time: 2.6385 data: 0.0059 max mem: 33369 +Epoch: [33] [1310/1319] eta: 0:00:23 lr: 9.075008707401167e-06 loss: 0.0346 (0.0342) time: 2.6547 data: 0.0059 max mem: 33369 +Epoch: [33] Total time: 0:57:42 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 2:04:22 time: 2.9001 data: 2.8210 max mem: 33369 +Test: [ 100/2573] eta: 0:04:07 time: 0.0719 data: 0.0011 max mem: 33369 +Test: [ 200/2573] eta: 0:03:27 time: 0.0734 data: 0.0011 max mem: 33369 +Test: [ 300/2573] eta: 0:03:06 time: 0.0751 data: 0.0011 max mem: 33369 +Test: [ 400/2573] eta: 0:02:53 time: 0.0751 data: 0.0011 max mem: 33369 +Test: [ 500/2573] eta: 0:02:43 time: 0.0735 data: 0.0011 max mem: 33369 +Test: [ 600/2573] eta: 0:02:33 time: 0.0736 data: 0.0011 max mem: 33369 +Test: [ 700/2573] eta: 0:02:25 time: 0.0736 data: 0.0011 max mem: 33369 +Test: [ 800/2573] eta: 0:02:16 time: 0.0770 data: 0.0011 max mem: 33369 +Test: [ 900/2573] eta: 0:02:08 time: 0.0737 data: 0.0011 max mem: 33369 +Test: [1000/2573] eta: 0:02:00 time: 0.0736 data: 0.0011 max mem: 33369 +Test: [1100/2573] eta: 0:01:52 time: 0.0736 data: 0.0011 max mem: 33369 +Test: [1200/2573] eta: 0:01:44 time: 0.0737 data: 0.0011 max mem: 33369 +Test: [1300/2573] eta: 0:01:36 time: 0.0738 data: 0.0011 max mem: 33369 +Test: [1400/2573] eta: 0:01:28 time: 0.0721 data: 0.0011 max mem: 33369 +Test: [1500/2573] eta: 0:01:21 time: 0.0737 data: 0.0011 max mem: 33369 +Test: [1600/2573] eta: 0:01:13 time: 0.0771 data: 0.0011 max mem: 33369 +Test: [1700/2573] eta: 0:01:05 time: 0.0720 data: 0.0010 max mem: 33369 +Test: [1800/2573] eta: 0:00:58 time: 0.0755 data: 0.0011 max mem: 33369 +Test: [1900/2573] eta: 0:00:50 time: 0.0723 data: 0.0011 max mem: 33369 +Test: [2000/2573] eta: 0:00:43 time: 0.0738 data: 0.0011 max mem: 33369 +Test: [2100/2573] eta: 0:00:35 time: 0.0755 data: 0.0011 max mem: 33369 +Test: [2200/2573] eta: 0:00:27 time: 0.0755 data: 0.0010 max mem: 33369 +Test: [2300/2573] eta: 0:00:20 time: 0.0754 data: 0.0011 max mem: 33369 +Test: [2400/2573] eta: 0:00:12 time: 0.0705 data: 0.0011 max mem: 33369 +Test: [2500/2573] eta: 0:00:05 time: 0.0738 data: 0.0011 max mem: 33369 +Test: Total time: 0:03:12 +Final results: +Mean IoU is 64.18 + + precision@0.5 = 72.59 + precision@0.6 = 67.05 + precision@0.7 = 60.52 + precision@0.8 = 49.59 + precision@0.9 = 24.39 + overall IoU = 61.88 + +Average object IoU 64.182684906933 +Overall IoU 61.8770751953125 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [34] [ 0/1319] eta: 3:17:49 lr: 9.065729264358701e-06 loss: 0.0443 (0.0443) time: 8.9988 data: 1.8354 max mem: 33369 +Epoch: [34] [ 10/1319] eta: 1:09:58 lr: 9.05541753412883e-06 loss: 0.0330 (0.0323) time: 3.2075 data: 0.1724 max mem: 33369 +Epoch: [34] [ 20/1319] eta: 1:03:08 lr: 9.045104499029229e-06 loss: 0.0326 (0.0333) time: 2.6123 data: 0.0058 max mem: 33369 +Epoch: [34] [ 30/1319] eta: 1:00:52 lr: 9.03479015724125e-06 loss: 0.0325 (0.0326) time: 2.6276 data: 0.0058 max mem: 33369 +Epoch: [34] [ 40/1319] eta: 0:59:14 lr: 9.024474506941415e-06 loss: 0.0325 (0.0334) time: 2.6343 data: 0.0062 max mem: 33369 +Epoch: [34] [ 50/1319] eta: 0:57:59 lr: 9.014157546301385e-06 loss: 0.0325 (0.0333) time: 2.6006 data: 0.0062 max mem: 33369 +Epoch: [34] [ 60/1319] eta: 0:57:10 lr: 9.003839273487931e-06 loss: 0.0309 (0.0334) time: 2.6143 data: 0.0060 max mem: 33369 +Epoch: [34] [ 70/1319] eta: 0:56:30 lr: 8.99351968666293e-06 loss: 0.0307 (0.0328) time: 2.6444 data: 0.0059 max mem: 33369 +Epoch: [34] [ 80/1319] eta: 0:55:48 lr: 8.983198783983315e-06 loss: 0.0314 (0.0329) time: 2.6333 data: 0.0062 max mem: 33369 +Epoch: [34] [ 90/1319] eta: 0:55:08 lr: 8.972876563601101e-06 loss: 0.0305 (0.0328) time: 2.6118 data: 0.0061 max mem: 33369 +Epoch: [34] [ 100/1319] eta: 0:54:31 lr: 8.962553023663333e-06 loss: 0.0317 (0.0330) time: 2.6069 data: 0.0061 max mem: 33369 +Epoch: [34] [ 110/1319] eta: 0:53:58 lr: 8.952228162312077e-06 loss: 0.0320 (0.0329) time: 2.6185 data: 0.0061 max mem: 33369 +Epoch: [34] [ 120/1319] eta: 0:53:23 lr: 8.941901977684397e-06 loss: 0.0357 (0.0334) time: 2.6118 data: 0.0061 max mem: 33369 +Epoch: [34] [ 130/1319] eta: 0:52:54 lr: 8.93157446791234e-06 loss: 0.0348 (0.0334) time: 2.6226 data: 0.0061 max mem: 33369 +Epoch: [34] [ 140/1319] eta: 0:52:27 lr: 8.9212456311229e-06 loss: 0.0301 (0.0334) time: 2.6580 data: 0.0062 max mem: 33369 +Epoch: [34] [ 150/1319] eta: 0:51:59 lr: 8.910915465438025e-06 loss: 0.0333 (0.0340) time: 2.6552 data: 0.0061 max mem: 33369 +Epoch: [34] [ 160/1319] eta: 0:51:29 lr: 8.900583968974578e-06 loss: 0.0329 (0.0338) time: 2.6346 data: 0.0061 max mem: 33369 +Epoch: [34] [ 170/1319] eta: 0:50:59 lr: 8.89025113984432e-06 loss: 0.0319 (0.0340) time: 2.6202 data: 0.0062 max mem: 33369 +Epoch: [34] [ 180/1319] eta: 0:50:29 lr: 8.879916976153894e-06 loss: 0.0319 (0.0339) time: 2.6129 data: 0.0061 max mem: 33369 +Epoch: [34] [ 190/1319] eta: 0:49:58 lr: 8.869581476004788e-06 loss: 0.0337 (0.0343) time: 2.5991 data: 0.0060 max mem: 33369 +Epoch: [34] [ 200/1319] eta: 0:49:29 lr: 8.859244637493344e-06 loss: 0.0322 (0.0342) time: 2.5994 data: 0.0059 max mem: 33369 +Epoch: [34] [ 210/1319] eta: 0:49:01 lr: 8.84890645871071e-06 loss: 0.0306 (0.0341) time: 2.6221 data: 0.0060 max mem: 33369 +Epoch: [34] [ 220/1319] eta: 0:48:32 lr: 8.838566937742836e-06 loss: 0.0356 (0.0343) time: 2.6146 data: 0.0061 max mem: 33369 +Epoch: [34] [ 230/1319] eta: 0:48:03 lr: 8.828226072670449e-06 loss: 0.0322 (0.0342) time: 2.5976 data: 0.0062 max mem: 33369 +Epoch: [34] [ 240/1319] eta: 0:47:36 lr: 8.817883861569014e-06 loss: 0.0322 (0.0344) time: 2.6173 data: 0.0062 max mem: 33369 +Epoch: [34] [ 250/1319] eta: 0:47:10 lr: 8.807540302508743e-06 loss: 0.0306 (0.0343) time: 2.6435 data: 0.0061 max mem: 33369 +Epoch: [34] [ 260/1319] eta: 0:46:42 lr: 8.797195393554557e-06 loss: 0.0296 (0.0341) time: 2.6358 data: 0.0060 max mem: 33369 +Epoch: [34] [ 270/1319] eta: 0:46:16 lr: 8.786849132766063e-06 loss: 0.0285 (0.0340) time: 2.6313 data: 0.0059 max mem: 33369 +Epoch: [34] [ 280/1319] eta: 0:45:48 lr: 8.776501518197541e-06 loss: 0.0296 (0.0338) time: 2.6277 data: 0.0060 max mem: 33369 +Epoch: [34] [ 290/1319] eta: 0:45:19 lr: 8.76615254789792e-06 loss: 0.0302 (0.0338) time: 2.5897 data: 0.0060 max mem: 33369 +Epoch: [34] [ 300/1319] eta: 0:44:51 lr: 8.755802219910735e-06 loss: 0.0308 (0.0340) time: 2.5927 data: 0.0059 max mem: 33369 +Epoch: [34] [ 310/1319] eta: 0:44:24 lr: 8.745450532274145e-06 loss: 0.0305 (0.0339) time: 2.6109 data: 0.0060 max mem: 33369 +Epoch: [34] [ 320/1319] eta: 0:43:56 lr: 8.735097483020883e-06 loss: 0.0305 (0.0340) time: 2.5969 data: 0.0059 max mem: 33369 +Epoch: [34] [ 330/1319] eta: 0:43:29 lr: 8.724743070178239e-06 loss: 0.0375 (0.0341) time: 2.6065 data: 0.0058 max mem: 33369 +Epoch: [34] [ 340/1319] eta: 0:43:03 lr: 8.714387291768046e-06 loss: 0.0341 (0.0340) time: 2.6339 data: 0.0058 max mem: 33369 +Epoch: [34] [ 350/1319] eta: 0:42:35 lr: 8.704030145806636e-06 loss: 0.0277 (0.0339) time: 2.6121 data: 0.0059 max mem: 33369 +Epoch: [34] [ 360/1319] eta: 0:42:08 lr: 8.693671630304845e-06 loss: 0.0300 (0.0339) time: 2.6006 data: 0.0060 max mem: 33369 +Epoch: [34] [ 370/1319] eta: 0:41:40 lr: 8.683311743267978e-06 loss: 0.0307 (0.0338) time: 2.6074 data: 0.0059 max mem: 33369 +Epoch: [34] [ 380/1319] eta: 0:41:14 lr: 8.672950482695785e-06 loss: 0.0287 (0.0337) time: 2.6226 data: 0.0058 max 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0:27:07 lr: 8.340652648571916e-06 loss: 0.0306 (0.0334) time: 2.6058 data: 0.0060 max mem: 33369 +Epoch: [34] [ 710/1319] eta: 0:26:40 lr: 8.330244901449094e-06 loss: 0.0316 (0.0335) time: 2.6002 data: 0.0060 max mem: 33369 +Epoch: [34] [ 720/1319] eta: 0:26:14 lr: 8.319835709307101e-06 loss: 0.0312 (0.0334) time: 2.6051 data: 0.0059 max mem: 33369 +Epoch: [34] [ 730/1319] eta: 0:25:47 lr: 8.309425069935955e-06 loss: 0.0349 (0.0335) time: 2.6209 data: 0.0059 max mem: 33369 +Epoch: [34] [ 740/1319] eta: 0:25:21 lr: 8.299012981119228e-06 loss: 0.0339 (0.0334) time: 2.6347 data: 0.0057 max mem: 33369 +Epoch: [34] [ 750/1319] eta: 0:24:55 lr: 8.288599440633996e-06 loss: 0.0274 (0.0334) time: 2.6203 data: 0.0058 max mem: 33369 +Epoch: [34] [ 760/1319] eta: 0:24:29 lr: 8.278184446250822e-06 loss: 0.0265 (0.0334) time: 2.6144 data: 0.0061 max mem: 33369 +Epoch: [34] [ 770/1319] eta: 0:24:02 lr: 8.267767995733725e-06 loss: 0.0343 (0.0334) time: 2.6260 data: 0.0059 max mem: 33369 +Epoch: [34] [ 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+Epoch: [34] [ 860/1319] eta: 0:20:05 lr: 8.173954042838362e-06 loss: 0.0332 (0.0335) time: 2.6032 data: 0.0060 max mem: 33369 +Epoch: [34] [ 870/1319] eta: 0:19:39 lr: 8.163522906542168e-06 loss: 0.0322 (0.0336) time: 2.6087 data: 0.0061 max mem: 33369 +Epoch: [34] [ 880/1319] eta: 0:19:13 lr: 8.153090289075947e-06 loss: 0.0309 (0.0336) time: 2.6361 data: 0.0059 max mem: 33369 +Epoch: [34] [ 890/1319] eta: 0:18:47 lr: 8.142656188122887e-06 loss: 0.0309 (0.0335) time: 2.6364 data: 0.0057 max mem: 33369 +Epoch: [34] [ 900/1319] eta: 0:18:20 lr: 8.132220601359272e-06 loss: 0.0286 (0.0335) time: 2.6217 data: 0.0058 max mem: 33369 +Epoch: [34] [ 910/1319] eta: 0:17:54 lr: 8.121783526454415e-06 loss: 0.0294 (0.0335) time: 2.6007 data: 0.0058 max mem: 33369 +Epoch: [34] [ 920/1319] eta: 0:17:28 lr: 8.111344961070641e-06 loss: 0.0294 (0.0335) time: 2.6051 data: 0.0058 max mem: 33369 +Epoch: [34] [ 930/1319] eta: 0:17:01 lr: 8.100904902863262e-06 loss: 0.0311 (0.0335) time: 2.6234 data: 0.0060 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2.5992 data: 0.0061 max mem: 33369 +Epoch: [34] [1020/1319] eta: 0:13:05 lr: 8.006876811544029e-06 loss: 0.0283 (0.0334) time: 2.6410 data: 0.0059 max mem: 33369 +Epoch: [34] [1030/1319] eta: 0:12:39 lr: 7.996421694575264e-06 loss: 0.0281 (0.0333) time: 2.6636 data: 0.0058 max mem: 33369 +Epoch: [34] [1040/1319] eta: 0:12:12 lr: 7.985965058518847e-06 loss: 0.0314 (0.0334) time: 2.6377 data: 0.0058 max mem: 33369 +Epoch: [34] [1050/1319] eta: 0:11:46 lr: 7.97550690094334e-06 loss: 0.0340 (0.0334) time: 2.6242 data: 0.0058 max mem: 33369 +Epoch: [34] [1060/1319] eta: 0:11:20 lr: 7.965047219409881e-06 loss: 0.0324 (0.0335) time: 2.6337 data: 0.0059 max mem: 33369 +Epoch: [34] [1070/1319] eta: 0:10:54 lr: 7.95458601147213e-06 loss: 0.0326 (0.0335) time: 2.6395 data: 0.0059 max mem: 33369 +Epoch: [34] [1080/1319] eta: 0:10:27 lr: 7.944123274676236e-06 loss: 0.0295 (0.0334) time: 2.6577 data: 0.0059 max mem: 33369 +Epoch: [34] [1090/1319] eta: 0:10:01 lr: 7.933659006560817e-06 loss: 0.0311 (0.0334) time: 2.6624 data: 0.0058 max mem: 33369 +Epoch: [34] [1100/1319] eta: 0:09:35 lr: 7.923193204656895e-06 loss: 0.0297 (0.0334) time: 2.6426 data: 0.0059 max mem: 33369 +Epoch: [34] [1110/1319] eta: 0:09:09 lr: 7.912725866487896e-06 loss: 0.0269 (0.0334) time: 2.6200 data: 0.0061 max mem: 33369 +Epoch: [34] [1120/1319] eta: 0:08:42 lr: 7.902256989569599e-06 loss: 0.0271 (0.0334) time: 2.6137 data: 0.0059 max mem: 33369 +Epoch: [34] [1130/1319] eta: 0:08:16 lr: 7.891786571410098e-06 loss: 0.0293 (0.0334) time: 2.6329 data: 0.0059 max mem: 33369 +Epoch: [34] [1140/1319] eta: 0:07:50 lr: 7.881314609509776e-06 loss: 0.0293 (0.0333) time: 2.6191 data: 0.0060 max mem: 33369 +Epoch: [34] [1150/1319] eta: 0:07:24 lr: 7.870841101361268e-06 loss: 0.0266 (0.0333) time: 2.6142 data: 0.0059 max mem: 33369 +Epoch: [34] [1160/1319] eta: 0:06:57 lr: 7.860366044449406e-06 loss: 0.0268 (0.0333) time: 2.6101 data: 0.0059 max mem: 33369 +Epoch: [34] [1170/1319] eta: 0:06:31 lr: 7.849889436251218e-06 loss: 0.0276 (0.0333) time: 2.6032 data: 0.0059 max mem: 33369 +Epoch: [34] [1180/1319] eta: 0:06:05 lr: 7.839411274235871e-06 loss: 0.0276 (0.0332) time: 2.6238 data: 0.0059 max mem: 33369 +Epoch: [34] [1190/1319] eta: 0:05:38 lr: 7.82893155586463e-06 loss: 0.0293 (0.0333) time: 2.6360 data: 0.0058 max mem: 33369 +Epoch: [34] [1200/1319] eta: 0:05:12 lr: 7.818450278590844e-06 loss: 0.0310 (0.0332) time: 2.6201 data: 0.0059 max mem: 33369 +Epoch: [34] [1210/1319] eta: 0:04:46 lr: 7.80796743985987e-06 loss: 0.0283 (0.0332) time: 2.6307 data: 0.0060 max mem: 33369 +Epoch: [34] [1220/1319] eta: 0:04:20 lr: 7.797483037109084e-06 loss: 0.0283 (0.0332) time: 2.6363 data: 0.0061 max mem: 33369 +Epoch: [34] [1230/1319] eta: 0:03:53 lr: 7.786997067767811e-06 loss: 0.0300 (0.0332) time: 2.6323 data: 0.0060 max mem: 33369 +Epoch: [34] [1240/1319] eta: 0:03:27 lr: 7.776509529257303e-06 loss: 0.0288 (0.0332) time: 2.6368 data: 0.0059 max mem: 33369 +Epoch: [34] [1250/1319] eta: 0:03:01 lr: 7.766020418990693e-06 loss: 0.0305 (0.0332) time: 2.5994 data: 0.0059 max mem: 33369 +Epoch: [34] [1260/1319] eta: 0:02:34 lr: 7.755529734372952e-06 loss: 0.0307 (0.0332) time: 2.5921 data: 0.0059 max mem: 33369 +Epoch: [34] [1270/1319] eta: 0:02:08 lr: 7.74503747280087e-06 loss: 0.0279 (0.0332) time: 2.5902 data: 0.0058 max mem: 33369 +Epoch: [34] [1280/1319] eta: 0:01:42 lr: 7.734543631663006e-06 loss: 0.0292 (0.0332) time: 2.6031 data: 0.0058 max mem: 33369 +Epoch: [34] [1290/1319] eta: 0:01:16 lr: 7.724048208339646e-06 loss: 0.0320 (0.0332) time: 2.6106 data: 0.0059 max mem: 33369 +Epoch: [34] [1300/1319] eta: 0:00:49 lr: 7.713551200202774e-06 loss: 0.0315 (0.0331) time: 2.6062 data: 0.0060 max mem: 33369 +Epoch: [34] [1310/1319] eta: 0:00:23 lr: 7.703052604616029e-06 loss: 0.0305 (0.0332) time: 2.6386 data: 0.0061 max mem: 33369 +Epoch: [34] Total time: 0:57:44 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 2:01:15 time: 2.8275 data: 2.7139 max mem: 33369 +Test: [ 100/2573] eta: 0:04:05 time: 0.0716 data: 0.0011 max mem: 33369 +Test: [ 200/2573] eta: 0:03:25 time: 0.0734 data: 0.0011 max mem: 33369 +Test: [ 300/2573] eta: 0:03:06 time: 0.0750 data: 0.0011 max mem: 33369 +Test: [ 400/2573] eta: 0:02:53 time: 0.0751 data: 0.0011 max mem: 33369 +Test: [ 500/2573] eta: 0:02:42 time: 0.0735 data: 0.0011 max mem: 33369 +Test: [ 600/2573] eta: 0:02:33 time: 0.0736 data: 0.0011 max mem: 33369 +Test: [ 700/2573] eta: 0:02:25 time: 0.0735 data: 0.0011 max mem: 33369 +Test: [ 800/2573] eta: 0:02:16 time: 0.0769 data: 0.0011 max mem: 33369 +Test: [ 900/2573] eta: 0:02:08 time: 0.0736 data: 0.0011 max mem: 33369 +Test: [1000/2573] eta: 0:02:00 time: 0.0738 data: 0.0011 max mem: 33369 +Test: [1100/2573] eta: 0:01:52 time: 0.0738 data: 0.0011 max mem: 33369 +Test: [1200/2573] eta: 0:01:44 time: 0.0739 data: 0.0011 max mem: 33369 +Test: [1300/2573] eta: 0:01:36 time: 0.0738 data: 0.0011 max mem: 33369 +Test: [1400/2573] eta: 0:01:28 time: 0.0722 data: 0.0011 max mem: 33369 +Test: [1500/2573] eta: 0:01:21 time: 0.0738 data: 0.0011 max mem: 33369 +Test: [1600/2573] eta: 0:01:13 time: 0.0771 data: 0.0011 max mem: 33369 +Test: [1700/2573] eta: 0:01:05 time: 0.0721 data: 0.0011 max mem: 33369 +Test: [1800/2573] eta: 0:00:58 time: 0.0755 data: 0.0011 max mem: 33369 +Test: [1900/2573] eta: 0:00:50 time: 0.0722 data: 0.0011 max mem: 33369 +Test: [2000/2573] eta: 0:00:43 time: 0.0739 data: 0.0011 max mem: 33369 +Test: [2100/2573] eta: 0:00:35 time: 0.0755 data: 0.0011 max mem: 33369 +Test: [2200/2573] eta: 0:00:27 time: 0.0755 data: 0.0011 max mem: 33369 +Test: [2300/2573] eta: 0:00:20 time: 0.0755 data: 0.0011 max mem: 33369 +Test: [2400/2573] eta: 0:00:12 time: 0.0706 data: 0.0011 max mem: 33369 +Test: [2500/2573] eta: 0:00:05 time: 0.0739 data: 0.0011 max mem: 33369 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: Total time: 0:03:12 +Final results: +Mean IoU is 64.64 + + precision@0.5 = 73.08 + precision@0.6 = 67.30 + precision@0.7 = 61.07 + precision@0.8 = 49.90 + precision@0.9 = 24.82 + overall IoU = 62.01 + +Average object IoU 64.6414577926737 +Overall IoU 62.01374816894531 +Better epoch: 34 + +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [35] [ 0/1319] eta: 1:26:32 lr: 7.693602509132593e-06 loss: 0.0411 (0.0411) time: 3.9369 data: 1.1774 max mem: 33369 +Epoch: [35] [ 10/1319] eta: 0:59:26 lr: 7.683100890097833e-06 loss: 0.0293 (0.0298) time: 2.7245 data: 0.1124 max mem: 33369 +Epoch: [35] [ 20/1319] eta: 0:58:16 lr: 7.67259767592017e-06 loss: 0.0293 (0.0329) time: 2.6294 data: 0.0056 max mem: 33369 +Epoch: [35] [ 30/1319] eta: 0:57:07 lr: 7.66209286393032e-06 loss: 0.0317 (0.0338) time: 2.6232 data: 0.0060 max mem: 33369 +Epoch: [35] [ 40/1319] eta: 0:56:30 lr: 7.651586451450453e-06 loss: 0.0317 (0.0332) time: 2.6077 data: 0.0063 max mem: 33369 +Epoch: [35] [ 50/1319] eta: 0:55:55 lr: 7.641078435794154e-06 loss: 0.0314 (0.0332) time: 2.6214 data: 0.0064 max mem: 33369 +Epoch: [35] [ 60/1319] eta: 0:55:26 lr: 7.630568814266394e-06 loss: 0.0315 (0.0337) time: 2.6245 data: 0.0064 max mem: 33369 +Epoch: [35] [ 70/1319] eta: 0:54:53 lr: 7.62005758416347e-06 loss: 0.0340 (0.0341) time: 2.6180 data: 0.0063 max mem: 33369 +Epoch: [35] [ 80/1319] eta: 0:54:20 lr: 7.609544742772985e-06 loss: 0.0360 (0.0340) time: 2.5997 data: 0.0063 max mem: 33369 +Epoch: [35] [ 90/1319] eta: 0:53:50 lr: 7.599030287373793e-06 loss: 0.0338 (0.0343) time: 2.5982 data: 0.0061 max mem: 33369 +Epoch: [35] [ 100/1319] eta: 0:53:19 lr: 7.588514215235963e-06 loss: 0.0308 (0.0339) time: 2.5986 data: 0.0060 max mem: 33369 +Epoch: [35] [ 110/1319] eta: 0:52:54 lr: 7.5779965236207366e-06 loss: 0.0282 (0.0337) time: 2.6157 data: 0.0061 max mem: 33369 +Epoch: [35] [ 120/1319] eta: 0:52:25 lr: 7.5674772097804864e-06 loss: 0.0317 (0.0341) time: 2.6129 data: 0.0061 max mem: 33369 +Epoch: [35] [ 130/1319] eta: 0:51:57 lr: 7.556956270958658e-06 loss: 0.0303 (0.0334) time: 2.5992 data: 0.0062 max mem: 33369 +Epoch: [35] [ 140/1319] eta: 0:51:32 lr: 7.546433704389756e-06 loss: 0.0245 (0.0334) time: 2.6215 data: 0.0064 max mem: 33369 +Epoch: [35] [ 150/1319] eta: 0:51:03 lr: 7.535909507299282e-06 loss: 0.0277 (0.0332) time: 2.6128 data: 0.0061 max mem: 33369 +Epoch: [35] [ 160/1319] eta: 0:50:38 lr: 7.525383676903694e-06 loss: 0.0289 (0.0330) time: 2.6134 data: 0.0060 max mem: 33369 +Epoch: [35] [ 170/1319] eta: 0:50:10 lr: 7.514856210410369e-06 loss: 0.0291 (0.0329) time: 2.6168 data: 0.0060 max mem: 33369 +Epoch: [35] [ 180/1319] eta: 0:49:46 lr: 7.504327105017539e-06 loss: 0.0308 (0.0327) time: 2.6250 data: 0.0059 max mem: 33369 +Epoch: [35] [ 190/1319] eta: 0:49:19 lr: 7.493796357914276e-06 loss: 0.0313 (0.0330) time: 2.6318 data: 0.0061 max mem: 33369 +Epoch: [35] [ 200/1319] eta: 0:48:53 lr: 7.483263966280434e-06 loss: 0.0320 (0.0329) time: 2.6168 data: 0.0062 max mem: 33369 +Epoch: [35] [ 210/1319] eta: 0:48:26 lr: 7.4727299272865964e-06 loss: 0.0320 (0.0330) time: 2.6172 data: 0.0060 max mem: 33369 +Epoch: [35] [ 220/1319] eta: 0:47:58 lr: 7.462194238094052e-06 loss: 0.0329 (0.0331) time: 2.6004 data: 0.0059 max mem: 33369 +Epoch: [35] [ 230/1319] eta: 0:47:34 lr: 7.4516568958547115e-06 loss: 0.0329 (0.0330) time: 2.6176 data: 0.0062 max mem: 33369 +Epoch: [35] [ 240/1319] eta: 0:47:08 lr: 7.4411178977111085e-06 loss: 0.0292 (0.0329) time: 2.6411 data: 0.0061 max mem: 33369 +Epoch: [35] [ 250/1319] eta: 0:46:41 lr: 7.430577240796325e-06 loss: 0.0282 (0.0329) time: 2.6165 data: 0.0061 max mem: 33369 +Epoch: [35] [ 260/1319] eta: 0:46:16 lr: 7.420034922233955e-06 loss: 0.0274 (0.0327) time: 2.6280 data: 0.0062 max mem: 33369 +Epoch: [35] [ 270/1319] eta: 0:45:50 lr: 7.4094909391380505e-06 loss: 0.0292 (0.0328) time: 2.6405 data: 0.0061 max mem: 33369 +Epoch: [35] [ 280/1319] eta: 0:45:24 lr: 7.398945288613088e-06 loss: 0.0307 (0.0328) time: 2.6250 data: 0.0060 max mem: 33369 +Epoch: [35] [ 290/1319] eta: 0:44:57 lr: 7.388397967753893e-06 loss: 0.0319 (0.0332) time: 2.6110 data: 0.0060 max mem: 33369 +Epoch: [35] [ 300/1319] eta: 0:44:32 lr: 7.3778489736456335e-06 loss: 0.0326 (0.0332) time: 2.6361 data: 0.0060 max mem: 33369 +Epoch: [35] [ 310/1319] eta: 0:44:06 lr: 7.367298303363743e-06 loss: 0.0315 (0.0333) time: 2.6420 data: 0.0060 max mem: 33369 +Epoch: [35] [ 320/1319] eta: 0:43:39 lr: 7.35674595397388e-06 loss: 0.0294 (0.0331) time: 2.6112 data: 0.0060 max mem: 33369 +Epoch: [35] [ 330/1319] eta: 0:43:12 lr: 7.34619192253189e-06 loss: 0.0263 (0.0330) time: 2.6107 data: 0.0060 max mem: 33369 +Epoch: [35] [ 340/1319] eta: 0:42:47 lr: 7.335636206083729e-06 loss: 0.0322 (0.0331) time: 2.6182 data: 0.0059 max mem: 33369 +Epoch: [35] [ 350/1319] eta: 0:42:21 lr: 7.325078801665445e-06 loss: 0.0333 (0.0331) time: 2.6345 data: 0.0060 max mem: 33369 +Epoch: [35] [ 360/1319] eta: 0:41:54 lr: 7.31451970630312e-06 loss: 0.0303 (0.0332) time: 2.6192 data: 0.0061 max mem: 33369 +Epoch: [35] [ 370/1319] eta: 0:41:29 lr: 7.303958917012809e-06 loss: 0.0292 (0.0331) time: 2.6308 data: 0.0062 max mem: 33369 +Epoch: [35] [ 380/1319] eta: 0:41:03 lr: 7.293396430800509e-06 loss: 0.0292 (0.0332) time: 2.6591 data: 0.0060 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7.039379718907476e-06 loss: 0.0284 (0.0327) time: 2.6069 data: 0.0061 max mem: 33369 +Epoch: [35] [ 630/1319] eta: 0:30:08 lr: 7.0287738060785644e-06 loss: 0.0283 (0.0327) time: 2.6349 data: 0.0061 max mem: 33369 +Epoch: [35] [ 640/1319] eta: 0:29:42 lr: 7.018166114777613e-06 loss: 0.0299 (0.0326) time: 2.6246 data: 0.0060 max mem: 33369 +Epoch: [35] [ 650/1319] eta: 0:29:15 lr: 7.007556641718624e-06 loss: 0.0299 (0.0327) time: 2.6063 data: 0.0060 max mem: 33369 +Epoch: [35] [ 660/1319] eta: 0:28:49 lr: 6.9969453836039725e-06 loss: 0.0297 (0.0326) time: 2.5999 data: 0.0060 max mem: 33369 +Epoch: [35] [ 670/1319] eta: 0:28:23 lr: 6.986332337124384e-06 loss: 0.0294 (0.0326) time: 2.6355 data: 0.0060 max mem: 33369 +Epoch: [35] [ 680/1319] eta: 0:27:57 lr: 6.975717498958839e-06 loss: 0.0311 (0.0326) time: 2.6472 data: 0.0061 max mem: 33369 +Epoch: [35] [ 690/1319] eta: 0:27:31 lr: 6.965100865774533e-06 loss: 0.0319 (0.0326) time: 2.6193 data: 0.0061 max mem: 33369 +Epoch: [35] [ 700/1319] eta: 0:27:04 lr: 6.954482434226801e-06 loss: 0.0327 (0.0326) time: 2.6197 data: 0.0060 max mem: 33369 +Epoch: [35] [ 710/1319] eta: 0:26:38 lr: 6.9438622009590656e-06 loss: 0.0316 (0.0327) time: 2.6289 data: 0.0059 max mem: 33369 +Epoch: [35] [ 720/1319] eta: 0:26:12 lr: 6.933240162602753e-06 loss: 0.0324 (0.0327) time: 2.6223 data: 0.0058 max mem: 33369 +Epoch: [35] [ 730/1319] eta: 0:25:46 lr: 6.922616315777261e-06 loss: 0.0285 (0.0327) time: 2.6210 data: 0.0060 max mem: 33369 +Epoch: [35] [ 740/1319] eta: 0:25:19 lr: 6.911990657089877e-06 loss: 0.0276 (0.0327) time: 2.6356 data: 0.0061 max mem: 33369 +Epoch: [35] [ 750/1319] eta: 0:24:54 lr: 6.901363183135715e-06 loss: 0.0322 (0.0327) time: 2.6605 data: 0.0061 max mem: 33369 +Epoch: [35] [ 760/1319] eta: 0:24:27 lr: 6.890733890497658e-06 loss: 0.0311 (0.0327) time: 2.6542 data: 0.0061 max mem: 33369 +Epoch: [35] [ 770/1319] eta: 0:24:02 lr: 6.880102775746271e-06 loss: 0.0321 (0.0327) time: 2.6783 data: 0.0063 max mem: 33369 +Epoch: 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mem: 33369 +Epoch: [35] [ 860/1319] eta: 0:20:09 lr: 6.784340175855078e-06 loss: 0.0281 (0.0326) time: 2.7094 data: 0.0060 max mem: 33369 +Epoch: [35] [ 870/1319] eta: 0:19:43 lr: 6.7736906485984466e-06 loss: 0.0262 (0.0325) time: 2.7047 data: 0.0060 max mem: 33369 +Epoch: [35] [ 880/1319] eta: 0:19:17 lr: 6.763039260673876e-06 loss: 0.0256 (0.0326) time: 2.6803 data: 0.0061 max mem: 33369 +Epoch: [35] [ 890/1319] eta: 0:18:51 lr: 6.752386008499089e-06 loss: 0.0283 (0.0325) time: 2.6936 data: 0.0060 max mem: 33369 +Epoch: [35] [ 900/1319] eta: 0:18:25 lr: 6.741730888478615e-06 loss: 0.0269 (0.0325) time: 2.6860 data: 0.0061 max mem: 33369 +Epoch: [35] [ 910/1319] eta: 0:17:59 lr: 6.7310738970037205e-06 loss: 0.0258 (0.0325) time: 2.7115 data: 0.0063 max mem: 33369 +Epoch: [35] [ 920/1319] eta: 0:17:33 lr: 6.7204150304523424e-06 loss: 0.0252 (0.0324) time: 2.7259 data: 0.0060 max mem: 33369 +Epoch: [35] [ 930/1319] eta: 0:17:07 lr: 6.709754285188997e-06 loss: 0.0295 (0.0325) time: 2.7061 data: 0.0060 max mem: 33369 +Epoch: [35] [ 940/1319] eta: 0:16:41 lr: 6.699091657564736e-06 loss: 0.0341 (0.0325) time: 2.7331 data: 0.0060 max mem: 33369 +Epoch: [35] [ 950/1319] eta: 0:16:15 lr: 6.688427143917049e-06 loss: 0.0337 (0.0325) time: 2.7319 data: 0.0060 max mem: 33369 +Epoch: [35] [ 960/1319] eta: 0:15:48 lr: 6.677760740569799e-06 loss: 0.0256 (0.0324) time: 2.7008 data: 0.0059 max mem: 33369 +Epoch: [35] [ 970/1319] eta: 0:15:22 lr: 6.667092443833153e-06 loss: 0.0294 (0.0324) time: 2.7104 data: 0.0060 max mem: 33369 +Epoch: [35] [ 980/1319] eta: 0:14:56 lr: 6.656422250003478e-06 loss: 0.0337 (0.0324) time: 2.7300 data: 0.0061 max mem: 33369 +Epoch: [35] [ 990/1319] eta: 0:14:30 lr: 6.645750155363307e-06 loss: 0.0293 (0.0324) time: 2.7181 data: 0.0060 max mem: 33369 +Epoch: [35] [1000/1319] eta: 0:14:03 lr: 6.635076156181232e-06 loss: 0.0293 (0.0324) time: 2.6866 data: 0.0061 max mem: 33369 +Epoch: [35] [1010/1319] eta: 0:13:37 lr: 6.624400248711836e-06 loss: 0.0318 (0.0324) time: 2.6968 data: 0.0059 max mem: 33369 +Epoch: [35] [1020/1319] eta: 0:13:11 lr: 6.613722429195618e-06 loss: 0.0317 (0.0324) time: 2.6917 data: 0.0061 max mem: 33369 +Epoch: [35] [1030/1319] eta: 0:12:44 lr: 6.603042693858916e-06 loss: 0.0324 (0.0325) time: 2.6582 data: 0.0062 max mem: 33369 +Epoch: [35] [1040/1319] eta: 0:12:18 lr: 6.5923610389138055e-06 loss: 0.0315 (0.0324) time: 2.6770 data: 0.0062 max mem: 33369 +Epoch: [35] [1050/1319] eta: 0:11:52 lr: 6.581677460558057e-06 loss: 0.0286 (0.0324) time: 2.7181 data: 0.0061 max mem: 33369 +Epoch: [35] [1060/1319] eta: 0:11:25 lr: 6.570991954975031e-06 loss: 0.0278 (0.0324) time: 2.7218 data: 0.0060 max mem: 33369 +Epoch: [35] [1070/1319] eta: 0:10:59 lr: 6.560304518333606e-06 loss: 0.0322 (0.0325) time: 2.7249 data: 0.0060 max mem: 33369 +Epoch: [35] [1080/1319] eta: 0:10:33 lr: 6.549615146788095e-06 loss: 0.0327 (0.0325) time: 2.7462 data: 0.0061 max mem: 33369 +Epoch: [35] [1090/1319] eta: 0:10:07 lr: 6.538923836478152e-06 loss: 0.0286 (0.0325) time: 2.7354 data: 0.0060 max mem: 33369 +Epoch: [35] [1100/1319] eta: 0:09:40 lr: 6.528230583528713e-06 loss: 0.0274 (0.0325) time: 2.7375 data: 0.0060 max mem: 33369 +Epoch: [35] [1110/1319] eta: 0:09:14 lr: 6.5175353840499016e-06 loss: 0.0302 (0.0325) time: 2.7427 data: 0.0060 max mem: 33369 +Epoch: [35] [1120/1319] eta: 0:08:47 lr: 6.506838234136938e-06 loss: 0.0327 (0.0325) time: 2.7193 data: 0.0063 max mem: 33369 +Epoch: [35] [1130/1319] eta: 0:08:21 lr: 6.4961391298700616e-06 loss: 0.0306 (0.0325) time: 2.7166 data: 0.0064 max mem: 33369 +Epoch: [35] [1140/1319] eta: 0:07:55 lr: 6.485438067314456e-06 loss: 0.0265 (0.0325) time: 2.7341 data: 0.0061 max mem: 33369 +Epoch: [35] [1150/1319] eta: 0:07:28 lr: 6.4747350425201315e-06 loss: 0.0307 (0.0325) time: 2.7127 data: 0.0058 max mem: 33369 +Epoch: [35] [1160/1319] eta: 0:07:02 lr: 6.464030051521878e-06 loss: 0.0308 (0.0326) time: 2.7189 data: 0.0060 max mem: 33369 +Epoch: [35] 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33369 +Epoch: [35] [1250/1319] eta: 0:03:03 lr: 6.3675959914443046e-06 loss: 0.0331 (0.0325) time: 2.7460 data: 0.0060 max mem: 33369 +Epoch: [35] [1260/1319] eta: 0:02:36 lr: 6.356871116904475e-06 loss: 0.0334 (0.0326) time: 2.7070 data: 0.0061 max mem: 33369 +Epoch: [35] [1270/1319] eta: 0:02:10 lr: 6.34614423151228e-06 loss: 0.0333 (0.0326) time: 2.7076 data: 0.0061 max mem: 33369 +Epoch: [35] [1280/1319] eta: 0:01:43 lr: 6.335415331112665e-06 loss: 0.0298 (0.0325) time: 2.7406 data: 0.0061 max mem: 33369 +Epoch: [35] [1290/1319] eta: 0:01:17 lr: 6.324684411534165e-06 loss: 0.0303 (0.0325) time: 2.7437 data: 0.0059 max mem: 33369 +Epoch: [35] [1300/1319] eta: 0:00:50 lr: 6.313951468588795e-06 loss: 0.0310 (0.0325) time: 2.7000 data: 0.0060 max mem: 33369 +Epoch: [35] [1310/1319] eta: 0:00:23 lr: 6.3032164980719415e-06 loss: 0.0291 (0.0325) time: 2.6884 data: 0.0060 max mem: 33369 +Epoch: [35] Total time: 0:58:31 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 1:44:55 time: 2.4466 data: 2.2960 max mem: 33369 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 100/2573] eta: 0:03:59 time: 0.0721 data: 0.0012 max mem: 33369 +Test: [ 200/2573] eta: 0:03:22 time: 0.0732 data: 0.0012 max mem: 33369 +Test: [ 300/2573] eta: 0:03:04 time: 0.0749 data: 0.0012 max mem: 33369 +Test: [ 400/2573] eta: 0:02:51 time: 0.0750 data: 0.0011 max mem: 33369 +Test: [ 500/2573] eta: 0:02:41 time: 0.0736 data: 0.0012 max mem: 33369 +Test: [ 600/2573] eta: 0:02:32 time: 0.0735 data: 0.0012 max mem: 33369 +Test: [ 700/2573] eta: 0:02:24 time: 0.0736 data: 0.0012 max mem: 33369 +Test: [ 800/2573] eta: 0:02:16 time: 0.0770 data: 0.0011 max mem: 33369 +Test: [ 900/2573] eta: 0:02:08 time: 0.0737 data: 0.0011 max mem: 33369 +Test: [1000/2573] eta: 0:02:00 time: 0.0738 data: 0.0012 max mem: 33369 +Test: [1100/2573] eta: 0:01:52 time: 0.0738 data: 0.0012 max mem: 33369 +Test: [1200/2573] eta: 0:01:44 time: 0.0736 data: 0.0012 max mem: 33369 +Test: [1300/2573] eta: 0:01:36 time: 0.0736 data: 0.0011 max mem: 33369 +Test: [1400/2573] eta: 0:01:28 time: 0.0723 data: 0.0012 max mem: 33369 +Test: [1500/2573] eta: 0:01:21 time: 0.0737 data: 0.0011 max mem: 33369 +Test: [1600/2573] eta: 0:01:13 time: 0.0770 data: 0.0012 max mem: 33369 +Test: [1700/2573] eta: 0:01:05 time: 0.0721 data: 0.0011 max mem: 33369 +Test: [1800/2573] eta: 0:00:58 time: 0.0755 data: 0.0011 max mem: 33369 +Test: [1900/2573] eta: 0:00:50 time: 0.0721 data: 0.0012 max mem: 33369 +Test: [2000/2573] eta: 0:00:42 time: 0.0739 data: 0.0012 max mem: 33369 +Test: [2100/2573] eta: 0:00:35 time: 0.0754 data: 0.0011 max mem: 33369 +Test: [2200/2573] eta: 0:00:27 time: 0.0756 data: 0.0012 max mem: 33369 +Test: [2300/2573] eta: 0:00:20 time: 0.0755 data: 0.0012 max mem: 33369 +Test: [2400/2573] eta: 0:00:12 time: 0.0706 data: 0.0012 max mem: 33369 +Test: [2500/2573] eta: 0:00:05 time: 0.0741 data: 0.0012 max mem: 33369 +Test: Total time: 0:03:12 +Final results: +Mean IoU is 64.84 + + precision@0.5 = 72.81 + precision@0.6 = 67.75 + precision@0.7 = 61.38 + precision@0.8 = 50.31 + precision@0.9 = 24.78 + overall IoU = 62.05 + +Average object IoU 64.83917488795993 +Overall IoU 62.05073165893555 +Better epoch: 35 + +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [36] [ 0/1319] eta: 1:30:33 lr: 6.293553287544593e-06 loss: 0.0280 (0.0280) time: 4.1197 data: 1.4568 max mem: 33369 +Epoch: [36] [ 10/1319] eta: 1:01:22 lr: 6.282814452998321e-06 loss: 0.0295 (0.0336) time: 2.8130 data: 0.1386 max mem: 33369 +Epoch: [36] [ 20/1319] eta: 1:00:27 lr: 6.2720735785923675e-06 loss: 0.0317 (0.0348) time: 2.7264 data: 0.0062 max mem: 33369 +Epoch: [36] [ 30/1319] eta: 0:59:21 lr: 6.261330660056396e-06 loss: 0.0323 (0.0352) time: 2.7358 data: 0.0060 max mem: 33369 +Epoch: [36] [ 40/1319] eta: 0:58:48 lr: 6.250585693102968e-06 loss: 0.0323 (0.0355) time: 2.7229 data: 0.0062 max mem: 33369 +Epoch: [36] [ 50/1319] eta: 0:57:53 lr: 6.2398386734274585e-06 loss: 0.0328 (0.0350) time: 2.6966 data: 0.0063 max mem: 33369 +Epoch: [36] [ 60/1319] eta: 0:57:10 lr: 6.229089596707912e-06 loss: 0.0295 (0.0339) time: 2.6554 data: 0.0065 max mem: 33369 +Epoch: [36] [ 70/1319] eta: 0:56:26 lr: 6.218338458604991e-06 loss: 0.0277 (0.0338) time: 2.6469 data: 0.0067 max mem: 33369 +Epoch: [36] [ 80/1319] eta: 0:55:52 lr: 6.207585254761843e-06 loss: 0.0286 (0.0336) time: 2.6465 data: 0.0068 max mem: 33369 +Epoch: [36] [ 90/1319] eta: 0:55:20 lr: 6.196829980804001e-06 loss: 0.0286 (0.0330) time: 2.6660 data: 0.0067 max mem: 33369 +Epoch: [36] [ 100/1319] eta: 0:54:56 lr: 6.1860726323392754e-06 loss: 0.0272 (0.0328) time: 2.6978 data: 0.0065 max mem: 33369 +Epoch: [36] [ 110/1319] eta: 0:54:32 lr: 6.175313204957665e-06 loss: 0.0320 (0.0329) time: 2.7294 data: 0.0064 max mem: 33369 +Epoch: [36] [ 120/1319] eta: 0:54:08 lr: 6.164551694231212e-06 loss: 0.0362 (0.0332) time: 2.7371 data: 0.0062 max mem: 33369 +Epoch: [36] [ 130/1319] eta: 0:53:42 lr: 6.153788095713938e-06 loss: 0.0329 (0.0333) time: 2.7317 data: 0.0062 max mem: 33369 +Epoch: [36] [ 140/1319] eta: 0:53:13 lr: 6.143022404941713e-06 loss: 0.0328 (0.0332) time: 2.7052 data: 0.0062 max mem: 33369 +Epoch: [36] [ 150/1319] eta: 0:52:46 lr: 6.132254617432146e-06 loss: 0.0291 (0.0330) time: 2.6975 data: 0.0063 max mem: 33369 +Epoch: [36] [ 160/1319] eta: 0:52:19 lr: 6.121484728684484e-06 loss: 0.0284 (0.0330) time: 2.7082 data: 0.0066 max mem: 33369 +Epoch: [36] [ 170/1319] eta: 0:51:54 lr: 6.110712734179475e-06 loss: 0.0267 (0.0327) time: 2.7247 data: 0.0064 max mem: 33369 +Epoch: [36] [ 180/1319] eta: 0:51:26 lr: 6.099938629379293e-06 loss: 0.0259 (0.0328) time: 2.7219 data: 0.0064 max mem: 33369 +Epoch: [36] [ 190/1319] eta: 0:50:56 lr: 6.0891624097274035e-06 loss: 0.0265 (0.0327) time: 2.6789 data: 0.0064 max mem: 33369 +Epoch: [36] [ 200/1319] eta: 0:50:30 lr: 6.07838407064845e-06 loss: 0.0284 (0.0326) time: 2.6913 data: 0.0066 max mem: 33369 +Epoch: [36] [ 210/1319] eta: 0:50:06 lr: 6.067603607548146e-06 loss: 0.0278 (0.0323) time: 2.7467 data: 0.0066 max mem: 33369 +Epoch: [36] [ 220/1319] eta: 0:49:39 lr: 6.05682101581314e-06 loss: 0.0299 (0.0325) time: 2.7341 data: 0.0064 max mem: 33369 +Epoch: [36] [ 230/1319] eta: 0:49:12 lr: 6.0460362908109285e-06 loss: 0.0320 (0.0325) time: 2.7100 data: 0.0062 max mem: 33369 +Epoch: [36] [ 240/1319] eta: 0:48:46 lr: 6.035249427889721e-06 loss: 0.0306 (0.0325) time: 2.7315 data: 0.0064 max mem: 33369 +Epoch: [36] [ 250/1319] eta: 0:48:17 lr: 6.024460422378318e-06 loss: 0.0284 (0.0324) time: 2.7027 data: 0.0066 max mem: 33369 +Epoch: [36] [ 260/1319] eta: 0:47:51 lr: 6.013669269586002e-06 loss: 0.0301 (0.0325) time: 2.6951 data: 0.0064 max mem: 33369 +Epoch: [36] [ 270/1319] eta: 0:47:24 lr: 6.002875964802412e-06 loss: 0.0315 (0.0324) time: 2.7248 data: 0.0063 max mem: 33369 +Epoch: [36] [ 280/1319] eta: 0:46:56 lr: 5.992080503297408e-06 loss: 0.0280 (0.0326) time: 2.7084 data: 0.0065 max mem: 33369 +Epoch: [36] [ 290/1319] eta: 0:46:28 lr: 5.981282880320978e-06 loss: 0.0292 (0.0326) time: 2.6846 data: 0.0064 max mem: 33369 +Epoch: [36] [ 300/1319] eta: 0:46:00 lr: 5.97048309110309e-06 loss: 0.0311 (0.0325) time: 2.6892 data: 0.0064 max mem: 33369 +Epoch: [36] [ 310/1319] eta: 0:45:32 lr: 5.959681130853577e-06 loss: 0.0273 (0.0324) time: 2.6852 data: 0.0065 max mem: 33369 +Epoch: [36] [ 320/1319] eta: 0:45:05 lr: 5.948876994762015e-06 loss: 0.0271 (0.0324) time: 2.6825 data: 0.0067 max mem: 33369 +Epoch: [36] [ 330/1319] eta: 0:44:35 lr: 5.938070677997572e-06 loss: 0.0273 (0.0323) time: 2.6641 data: 0.0069 max mem: 33369 +Epoch: [36] [ 340/1319] eta: 0:44:06 lr: 5.927262175708919e-06 loss: 0.0310 (0.0324) time: 2.6271 data: 0.0069 max mem: 33369 +Epoch: [36] [ 350/1319] eta: 0:43:37 lr: 5.916451483024071e-06 loss: 0.0335 (0.0325) time: 2.6422 data: 0.0067 max mem: 33369 +Epoch: [36] [ 360/1319] eta: 0:43:09 lr: 5.905638595050271e-06 loss: 0.0316 (0.0326) time: 2.6517 data: 0.0068 max mem: 33369 +Epoch: [36] [ 370/1319] eta: 0:42:41 lr: 5.894823506873858e-06 loss: 0.0321 (0.0326) time: 2.6487 data: 0.0068 max mem: 33369 +Epoch: [36] [ 380/1319] eta: 0:42:13 lr: 5.884006213560114e-06 loss: 0.0324 (0.0326) time: 2.6615 data: 0.0068 max 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eta: 0:06:42 lr: 5.022009633423085e-06 loss: 0.0261 (0.0319) time: 2.6839 data: 0.0065 max mem: 33369 +Epoch: [36] [1180/1319] eta: 0:06:15 lr: 5.0109977949644845e-06 loss: 0.0286 (0.0319) time: 2.6726 data: 0.0064 max mem: 33369 +Epoch: [36] [1190/1319] eta: 0:05:48 lr: 4.999983267081064e-06 loss: 0.0293 (0.0320) time: 2.7006 data: 0.0062 max mem: 33369 +Epoch: [36] [1200/1319] eta: 0:05:21 lr: 4.988966042529905e-06 loss: 0.0289 (0.0319) time: 2.7564 data: 0.0062 max mem: 33369 +Epoch: [36] [1210/1319] eta: 0:04:54 lr: 4.977946114030749e-06 loss: 0.0269 (0.0319) time: 2.7271 data: 0.0065 max mem: 33369 +Epoch: [36] [1220/1319] eta: 0:04:27 lr: 4.966923474265728e-06 loss: 0.0282 (0.0319) time: 2.6784 data: 0.0066 max mem: 33369 +Epoch: [36] [1230/1319] eta: 0:04:00 lr: 4.9558981158790714e-06 loss: 0.0295 (0.0319) time: 2.6967 data: 0.0066 max mem: 33369 +Epoch: [36] [1240/1319] eta: 0:03:33 lr: 4.944870031476802e-06 loss: 0.0302 (0.0319) time: 2.7318 data: 0.0064 max mem: 33369 +Epoch: 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+/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 2:11:33 time: 3.0678 data: 2.9886 max mem: 33369 +Test: [ 100/2573] eta: 0:04:11 time: 0.0718 data: 0.0012 max mem: 33369 +Test: [ 200/2573] eta: 0:03:28 time: 0.0731 data: 0.0012 max mem: 33369 +Test: [ 300/2573] eta: 0:03:07 time: 0.0748 data: 0.0011 max mem: 33369 +Test: [ 400/2573] eta: 0:02:54 time: 0.0750 data: 0.0011 max mem: 33369 +Test: [ 500/2573] eta: 0:02:43 time: 0.0735 data: 0.0012 max mem: 33369 +Test: [ 600/2573] eta: 0:02:34 time: 0.0735 data: 0.0012 max mem: 33369 +Test: [ 700/2573] eta: 0:02:25 time: 0.0736 data: 0.0012 max mem: 33369 +Test: [ 800/2573] eta: 0:02:17 time: 0.0770 data: 0.0011 max mem: 33369 +Test: [ 900/2573] eta: 0:02:08 time: 0.0735 data: 0.0011 max mem: 33369 +Test: [1000/2573] eta: 0:02:00 time: 0.0736 data: 0.0012 max mem: 33369 +Test: [1100/2573] eta: 0:01:52 time: 0.0739 data: 0.0012 max mem: 33369 +Test: [1200/2573] eta: 0:01:44 time: 0.0739 data: 0.0012 max mem: 33369 +Test: [1300/2573] eta: 0:01:36 time: 0.0737 data: 0.0011 max mem: 33369 +Test: [1400/2573] eta: 0:01:29 time: 0.0723 data: 0.0012 max mem: 33369 +Test: [1500/2573] eta: 0:01:21 time: 0.0738 data: 0.0012 max mem: 33369 +Test: [1600/2573] eta: 0:01:13 time: 0.0771 data: 0.0012 max mem: 33369 +Test: [1700/2573] eta: 0:01:06 time: 0.0723 data: 0.0011 max mem: 33369 +Test: [1800/2573] eta: 0:00:58 time: 0.0757 data: 0.0012 max mem: 33369 +Test: [1900/2573] eta: 0:00:50 time: 0.0723 data: 0.0012 max mem: 33369 +Test: [2000/2573] eta: 0:00:43 time: 0.0739 data: 0.0012 max mem: 33369 +Test: [2100/2573] eta: 0:00:35 time: 0.0755 data: 0.0011 max mem: 33369 +Test: [2200/2573] eta: 0:00:28 time: 0.0756 data: 0.0011 max mem: 33369 +Test: [2300/2573] eta: 0:00:20 time: 0.0755 data: 0.0012 max mem: 33369 +Test: [2400/2573] eta: 0:00:12 time: 0.0705 data: 0.0012 max mem: 33369 +Test: [2500/2573] eta: 0:00:05 time: 0.0739 data: 0.0012 max mem: 33369 +Test: Total time: 0:03:13 +Final results: +Mean IoU is 64.87 + + precision@0.5 = 72.94 + precision@0.6 = 67.79 + precision@0.7 = 61.05 + precision@0.8 = 50.02 + precision@0.9 = 25.20 + overall IoU = 62.32 + +Average object IoU 64.86925424596191 +Overall IoU 62.322235107421875 +Better epoch: 36 + +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [37] [ 0/1319] eta: 1:25:07 lr: 4.85765146153759e-06 loss: 0.0240 (0.0240) time: 3.8719 data: 1.2307 max mem: 33369 +Epoch: [37] [ 10/1319] eta: 1:01:03 lr: 4.846598783599751e-06 loss: 0.0236 (0.0237) time: 2.7988 data: 0.1177 max mem: 33369 +Epoch: [37] [ 20/1319] eta: 0:59:07 lr: 4.835543304321068e-06 loss: 0.0250 (0.0281) time: 2.6740 data: 0.0063 max mem: 33369 +Epoch: [37] [ 30/1319] eta: 0:58:25 lr: 4.824485015871577e-06 loss: 0.0291 (0.0296) time: 2.6764 data: 0.0064 max mem: 33369 +Epoch: [37] [ 40/1319] eta: 0:57:31 lr: 4.813423910379438e-06 loss: 0.0320 (0.0304) time: 2.6653 data: 0.0069 max mem: 33369 +Epoch: [37] [ 50/1319] eta: 0:57:02 lr: 4.802359979930566e-06 loss: 0.0324 (0.0303) time: 2.6607 data: 0.0068 max mem: 33369 +Epoch: [37] [ 60/1319] eta: 0:56:27 lr: 4.791293216568347e-06 loss: 0.0270 (0.0303) time: 2.6738 data: 0.0065 max mem: 33369 +Epoch: [37] [ 70/1319] eta: 0:55:58 lr: 4.780223612293264e-06 loss: 0.0272 (0.0302) time: 2.6695 data: 0.0065 max mem: 33369 +Epoch: [37] [ 80/1319] eta: 0:55:28 lr: 4.7691511590625665e-06 loss: 0.0307 (0.0308) time: 2.6739 data: 0.0065 max mem: 33369 +Epoch: [37] [ 90/1319] eta: 0:54:53 lr: 4.75807584878992e-06 loss: 0.0339 (0.0314) time: 2.6484 data: 0.0066 max mem: 33369 +Epoch: [37] [ 100/1319] eta: 0:54:23 lr: 4.7469976733450685e-06 loss: 0.0291 (0.0313) time: 2.6385 data: 0.0067 max mem: 33369 +Epoch: [37] [ 110/1319] eta: 0:53:54 lr: 4.735916624553454e-06 loss: 0.0272 (0.0315) time: 2.6550 data: 0.0067 max mem: 33369 +Epoch: [37] [ 120/1319] eta: 0:53:26 lr: 4.724832694195895e-06 loss: 0.0308 (0.0317) time: 2.6604 data: 0.0066 max mem: 33369 +Epoch: [37] [ 130/1319] eta: 0:52:53 lr: 4.713745874008202e-06 loss: 0.0288 (0.0313) time: 2.6343 data: 0.0066 max mem: 33369 +Epoch: [37] [ 140/1319] eta: 0:52:27 lr: 4.702656155680819e-06 loss: 0.0255 (0.0311) time: 2.6392 data: 0.0066 max mem: 33369 +Epoch: [37] [ 150/1319] eta: 0:52:01 lr: 4.691563530858464e-06 loss: 0.0279 (0.0314) time: 2.6761 data: 0.0064 max mem: 33369 +Epoch: [37] [ 160/1319] eta: 0:51:37 lr: 4.6804679911397265e-06 loss: 0.0301 (0.0315) time: 2.6923 data: 0.0064 max mem: 33369 +Epoch: [37] [ 170/1319] eta: 0:51:13 lr: 4.66936952807673e-06 loss: 0.0301 (0.0315) time: 2.7094 data: 0.0064 max mem: 33369 +Epoch: [37] [ 180/1319] eta: 0:50:45 lr: 4.65826813317473e-06 loss: 0.0267 (0.0313) time: 2.6843 data: 0.0064 max mem: 33369 +Epoch: [37] [ 190/1319] eta: 0:50:19 lr: 4.64716379789173e-06 loss: 0.0281 (0.0313) time: 2.6680 data: 0.0065 max mem: 33369 +Epoch: [37] [ 200/1319] eta: 0:49:52 lr: 4.636056513638103e-06 loss: 0.0283 (0.0312) time: 2.6810 data: 0.0066 max mem: 33369 +Epoch: [37] [ 210/1319] eta: 0:49:29 lr: 4.6249462717761695e-06 loss: 0.0333 (0.0318) time: 2.7111 data: 0.0065 max mem: 33369 +Epoch: [37] [ 220/1319] eta: 0:49:04 lr: 4.6138330636198426e-06 loss: 0.0333 (0.0317) time: 2.7317 data: 0.0065 max mem: 33369 +Epoch: [37] [ 230/1319] eta: 0:48:41 lr: 4.602716880434195e-06 loss: 0.0266 (0.0316) time: 2.7329 data: 0.0065 max mem: 33369 +Epoch: [37] [ 240/1319] eta: 0:48:16 lr: 4.591597713435064e-06 loss: 0.0331 (0.0317) time: 2.7446 data: 0.0064 max mem: 33369 +Epoch: [37] [ 250/1319] eta: 0:47:51 lr: 4.580475553788638e-06 loss: 0.0333 (0.0317) time: 2.7249 data: 0.0068 max mem: 33369 +Epoch: [37] [ 260/1319] eta: 0:47:22 lr: 4.569350392611047e-06 loss: 0.0306 (0.0317) time: 2.6811 data: 0.0067 max mem: 33369 +Epoch: [37] [ 270/1319] eta: 0:46:55 lr: 4.558222220967921e-06 loss: 0.0305 (0.0316) time: 2.6653 data: 0.0063 max mem: 33369 +Epoch: [37] [ 280/1319] eta: 0:46:30 lr: 4.547091029873999e-06 loss: 0.0310 (0.0316) time: 2.7044 data: 0.0063 max mem: 33369 +Epoch: [37] [ 290/1319] eta: 0:46:02 lr: 4.5359568102926745e-06 loss: 0.0310 (0.0318) time: 2.6932 data: 0.0063 max mem: 33369 +Epoch: [37] [ 300/1319] eta: 0:45:35 lr: 4.524819553135574e-06 loss: 0.0276 (0.0317) time: 2.6570 data: 0.0062 max mem: 33369 +Epoch: [37] [ 310/1319] eta: 0:45:08 lr: 4.5136792492621144e-06 loss: 0.0288 (0.0317) time: 2.6768 data: 0.0063 max mem: 33369 +Epoch: [37] [ 320/1319] eta: 0:44:43 lr: 4.502535889479041e-06 loss: 0.0284 (0.0316) time: 2.7239 data: 0.0064 max mem: 33369 +Epoch: [37] [ 330/1319] eta: 0:44:17 lr: 4.491389464540016e-06 loss: 0.0273 (0.0315) time: 2.7362 data: 0.0064 max mem: 33369 +Epoch: [37] [ 340/1319] eta: 0:43:51 lr: 4.480239965145135e-06 loss: 0.0287 (0.0319) time: 2.7134 data: 0.0064 max mem: 33369 +Epoch: [37] [ 350/1319] eta: 0:43:24 lr: 4.469087381940477e-06 loss: 0.0353 (0.0321) time: 2.6913 data: 0.0062 max mem: 33369 +Epoch: [37] [ 360/1319] eta: 0:42:57 lr: 4.457931705517646e-06 loss: 0.0286 (0.0319) time: 2.6820 data: 0.0063 max mem: 33369 +Epoch: [37] [ 370/1319] eta: 0:42:29 lr: 4.446772926413276e-06 loss: 0.0266 (0.0320) time: 2.6730 data: 0.0066 max mem: 33369 +Epoch: [37] [ 380/1319] eta: 0:42:02 lr: 4.435611035108594e-06 loss: 0.0299 (0.0319) time: 2.6661 data: 0.0066 max 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4.166766212733477e-06 loss: 0.0269 (0.0319) time: 2.7588 data: 0.0063 max mem: 33369 +Epoch: [37] [ 630/1319] eta: 0:30:55 lr: 4.15552325028145e-06 loss: 0.0270 (0.0318) time: 2.7471 data: 0.0064 max mem: 33369 +Epoch: [37] [ 640/1319] eta: 0:30:28 lr: 4.1442769069903985e-06 loss: 0.0264 (0.0318) time: 2.7097 data: 0.0062 max mem: 33369 +Epoch: [37] [ 650/1319] eta: 0:30:02 lr: 4.133027171643516e-06 loss: 0.0270 (0.0317) time: 2.7149 data: 0.0061 max mem: 33369 +Epoch: [37] [ 660/1319] eta: 0:29:36 lr: 4.121774032952729e-06 loss: 0.0283 (0.0317) time: 2.7709 data: 0.0062 max mem: 33369 +Epoch: [37] [ 670/1319] eta: 0:29:09 lr: 4.110517479558032e-06 loss: 0.0299 (0.0317) time: 2.7716 data: 0.0062 max mem: 33369 +Epoch: [37] [ 680/1319] eta: 0:28:43 lr: 4.099257500026817e-06 loss: 0.0281 (0.0316) time: 2.7336 data: 0.0062 max mem: 33369 +Epoch: [37] [ 690/1319] eta: 0:28:16 lr: 4.087994082853156e-06 loss: 0.0273 (0.0316) time: 2.7090 data: 0.0063 max mem: 33369 +Epoch: [37] [ 700/1319] eta: 0:27:49 lr: 4.076727216457151e-06 loss: 0.0285 (0.0316) time: 2.6955 data: 0.0065 max mem: 33369 +Epoch: [37] [ 710/1319] eta: 0:27:22 lr: 4.065456889184196e-06 loss: 0.0292 (0.0316) time: 2.6871 data: 0.0065 max mem: 33369 +Epoch: [37] [ 720/1319] eta: 0:26:55 lr: 4.054183089304276e-06 loss: 0.0332 (0.0316) time: 2.6818 data: 0.0063 max mem: 33369 +Epoch: [37] [ 730/1319] eta: 0:26:28 lr: 4.0429058050112415e-06 loss: 0.0309 (0.0316) time: 2.7151 data: 0.0063 max mem: 33369 +Epoch: [37] [ 740/1319] eta: 0:26:01 lr: 4.031625024422082e-06 loss: 0.0297 (0.0316) time: 2.7435 data: 0.0063 max mem: 33369 +Epoch: [37] [ 750/1319] eta: 0:25:34 lr: 4.020340735576163e-06 loss: 0.0309 (0.0316) time: 2.7199 data: 0.0062 max mem: 33369 +Epoch: [37] [ 760/1319] eta: 0:25:08 lr: 4.0090529264345135e-06 loss: 0.0314 (0.0316) time: 2.7143 data: 0.0063 max mem: 33369 +Epoch: [37] [ 770/1319] eta: 0:24:40 lr: 3.997761584879033e-06 loss: 0.0309 (0.0316) time: 2.7002 data: 0.0065 max mem: 33369 +Epoch: 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time: 2.7056 data: 0.0065 max mem: 33369 +Epoch: [37] [1020/1319] eta: 0:13:27 lr: 3.714292849713318e-06 loss: 0.0292 (0.0314) time: 2.7439 data: 0.0064 max mem: 33369 +Epoch: [37] [1030/1319] eta: 0:13:00 lr: 3.7029051332087708e-06 loss: 0.0296 (0.0315) time: 2.7217 data: 0.0062 max mem: 33369 +Epoch: [37] [1040/1319] eta: 0:12:33 lr: 3.691513524125288e-06 loss: 0.0295 (0.0314) time: 2.7085 data: 0.0061 max mem: 33369 +Epoch: [37] [1050/1319] eta: 0:12:06 lr: 3.680118007776355e-06 loss: 0.0290 (0.0315) time: 2.7197 data: 0.0061 max mem: 33369 +Epoch: [37] [1060/1319] eta: 0:11:39 lr: 3.6687185693693123e-06 loss: 0.0300 (0.0315) time: 2.6819 data: 0.0065 max mem: 33369 +Epoch: [37] [1070/1319] eta: 0:11:12 lr: 3.657315194004196e-06 loss: 0.0294 (0.0315) time: 2.6772 data: 0.0066 max mem: 33369 +Epoch: [37] [1080/1319] eta: 0:10:45 lr: 3.6459078666726217e-06 loss: 0.0294 (0.0314) time: 2.7087 data: 0.0063 max mem: 33369 +Epoch: [37] [1090/1319] eta: 0:10:18 lr: 3.6344965722565904e-06 loss: 0.0282 (0.0315) time: 2.7176 data: 0.0066 max mem: 33369 +Epoch: [37] [1100/1319] eta: 0:09:51 lr: 3.6230812955273095e-06 loss: 0.0298 (0.0315) time: 2.6826 data: 0.0065 max mem: 33369 +Epoch: [37] [1110/1319] eta: 0:09:24 lr: 3.6116620211439967e-06 loss: 0.0298 (0.0315) time: 2.6671 data: 0.0064 max mem: 33369 +Epoch: [37] [1120/1319] eta: 0:08:56 lr: 3.6002387336526318e-06 loss: 0.0307 (0.0315) time: 2.6551 data: 0.0066 max mem: 33369 +Epoch: [37] [1130/1319] eta: 0:08:29 lr: 3.588811417484761e-06 loss: 0.0332 (0.0315) time: 2.6440 data: 0.0067 max mem: 33369 +Epoch: [37] [1140/1319] eta: 0:08:02 lr: 3.577380056956213e-06 loss: 0.0297 (0.0315) time: 2.6427 data: 0.0068 max mem: 33369 +Epoch: [37] [1150/1319] eta: 0:07:35 lr: 3.5659446362658317e-06 loss: 0.0300 (0.0316) time: 2.6359 data: 0.0068 max mem: 33369 +Epoch: [37] [1160/1319] eta: 0:07:08 lr: 3.5545051394941854e-06 loss: 0.0312 (0.0316) time: 2.6454 data: 0.0068 max mem: 33369 +Epoch: [37] [1170/1319] eta: 0:06:41 lr: 3.5430615506022587e-06 loss: 0.0312 (0.0316) time: 2.6630 data: 0.0066 max mem: 33369 +Epoch: [37] [1180/1319] eta: 0:06:14 lr: 3.531613853430098e-06 loss: 0.0283 (0.0315) time: 2.6580 data: 0.0064 max mem: 33369 +Epoch: [37] [1190/1319] eta: 0:05:47 lr: 3.5201620316954973e-06 loss: 0.0305 (0.0315) time: 2.6623 data: 0.0066 max mem: 33369 +Epoch: [37] [1200/1319] eta: 0:05:20 lr: 3.5087060689926057e-06 loss: 0.0302 (0.0315) time: 2.6762 data: 0.0066 max mem: 33369 +Epoch: [37] [1210/1319] eta: 0:04:53 lr: 3.4972459487905388e-06 loss: 0.0298 (0.0315) time: 2.6663 data: 0.0066 max mem: 33369 +Epoch: [37] [1220/1319] eta: 0:04:26 lr: 3.485781654431977e-06 loss: 0.0269 (0.0315) time: 2.6716 data: 0.0066 max mem: 33369 +Epoch: [37] [1230/1319] eta: 0:03:59 lr: 3.4743131691317023e-06 loss: 0.0311 (0.0316) time: 2.6579 data: 0.0067 max mem: 33369 +Epoch: [37] [1240/1319] eta: 0:03:32 lr: 3.462840475975186e-06 loss: 0.0317 (0.0316) time: 2.6354 data: 0.0066 max mem: 33369 +Epoch: [37] 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+/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 2:06:06 time: 2.9407 data: 2.8624 max mem: 33369 +Test: [ 100/2573] eta: 0:04:08 time: 0.0719 data: 0.0012 max mem: 33369 +Test: [ 200/2573] eta: 0:03:27 time: 0.0732 data: 0.0011 max mem: 33369 +Test: [ 300/2573] eta: 0:03:06 time: 0.0749 data: 0.0011 max mem: 33369 +Test: [ 400/2573] eta: 0:02:53 time: 0.0753 data: 0.0012 max mem: 33369 +Test: [ 500/2573] eta: 0:02:43 time: 0.0736 data: 0.0012 max mem: 33369 +Test: [ 600/2573] eta: 0:02:33 time: 0.0734 data: 0.0011 max mem: 33369 +Test: [ 700/2573] eta: 0:02:25 time: 0.0737 data: 0.0012 max mem: 33369 +Test: [ 800/2573] eta: 0:02:16 time: 0.0771 data: 0.0012 max mem: 33369 +Test: [ 900/2573] eta: 0:02:08 time: 0.0737 data: 0.0012 max mem: 33369 +Test: [1000/2573] eta: 0:02:00 time: 0.0737 data: 0.0012 max mem: 33369 +Test: [1100/2573] eta: 0:01:52 time: 0.0736 data: 0.0012 max mem: 33369 +Test: [1200/2573] eta: 0:01:44 time: 0.0738 data: 0.0011 max mem: 33369 +Test: [1300/2573] eta: 0:01:36 time: 0.0737 data: 0.0011 max mem: 33369 +Test: [1400/2573] eta: 0:01:28 time: 0.0722 data: 0.0012 max mem: 33369 +Test: [1500/2573] eta: 0:01:21 time: 0.0738 data: 0.0011 max mem: 33369 +Test: [1600/2573] eta: 0:01:13 time: 0.0771 data: 0.0012 max mem: 33369 +Test: [1700/2573] eta: 0:01:05 time: 0.0722 data: 0.0011 max mem: 33369 +Test: [1800/2573] eta: 0:00:58 time: 0.0754 data: 0.0011 max mem: 33369 +Test: [1900/2573] eta: 0:00:50 time: 0.0722 data: 0.0012 max mem: 33369 +Test: [2000/2573] eta: 0:00:43 time: 0.0739 data: 0.0011 max mem: 33369 +Test: [2100/2573] eta: 0:00:35 time: 0.0755 data: 0.0011 max mem: 33369 +Test: [2200/2573] eta: 0:00:27 time: 0.0757 data: 0.0011 max mem: 33369 +Test: [2300/2573] eta: 0:00:20 time: 0.0756 data: 0.0011 max mem: 33369 +Test: [2400/2573] eta: 0:00:12 time: 0.0705 data: 0.0011 max mem: 33369 +Test: [2500/2573] eta: 0:00:05 time: 0.0739 data: 0.0012 max mem: 33369 +Test: Total time: 0:03:12 +Final results: +Mean IoU is 64.91 + + precision@0.5 = 72.86 + precision@0.6 = 68.08 + precision@0.7 = 61.64 + precision@0.8 = 50.39 + precision@0.9 = 25.14 + overall IoU = 62.38 + +Average object IoU 64.90948714321323 +Overall IoU 62.380619049072266 +Better epoch: 37 + +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [38] [ 0/1319] eta: 1:25:44 lr: 3.3720562685558925e-06 loss: 0.0335 (0.0335) time: 3.9003 data: 1.1754 max mem: 33369 +Epoch: [38] [ 10/1319] eta: 1:00:29 lr: 3.3605453588871517e-06 loss: 0.0335 (0.0358) time: 2.7726 data: 0.1129 max mem: 33369 +Epoch: [38] [ 20/1319] eta: 0:59:24 lr: 3.349030066603249e-06 loss: 0.0314 (0.0353) time: 2.6864 data: 0.0065 max mem: 33369 +Epoch: [38] [ 30/1319] eta: 0:58:52 lr: 3.3375103732791936e-06 loss: 0.0330 (0.0349) time: 2.7232 data: 0.0063 max mem: 33369 +Epoch: [38] [ 40/1319] eta: 0:58:14 lr: 3.3259862603415314e-06 loss: 0.0326 (0.0343) time: 2.7195 data: 0.0064 max mem: 33369 +Epoch: [38] [ 50/1319] eta: 0:57:47 lr: 3.314457709066606e-06 loss: 0.0324 (0.0342) time: 2.7193 data: 0.0065 max mem: 33369 +Epoch: [38] [ 60/1319] eta: 0:57:18 lr: 3.302924700578736e-06 loss: 0.0321 (0.0342) time: 2.7296 data: 0.0064 max mem: 33369 +Epoch: [38] [ 70/1319] eta: 0:56:48 lr: 3.2913872158483893e-06 loss: 0.0276 (0.0338) time: 2.7204 data: 0.0063 max mem: 33369 +Epoch: [38] [ 80/1319] eta: 0:56:15 lr: 3.279845235690334e-06 loss: 0.0256 (0.0328) time: 2.7027 data: 0.0065 max mem: 33369 +Epoch: [38] [ 90/1319] eta: 0:55:42 lr: 3.268298740761722e-06 loss: 0.0263 (0.0325) time: 2.6852 data: 0.0065 max mem: 33369 +Epoch: [38] [ 100/1319] eta: 0:55:16 lr: 3.2567477115602124e-06 loss: 0.0311 (0.0335) time: 2.7061 data: 0.0065 max mem: 33369 +Epoch: [38] [ 110/1319] eta: 0:54:42 lr: 3.2451921284219928e-06 loss: 0.0312 (0.0335) time: 2.6968 data: 0.0065 max mem: 33369 +Epoch: [38] [ 120/1319] eta: 0:54:13 lr: 3.233631971519807e-06 loss: 0.0280 (0.0330) time: 2.6788 data: 0.0065 max mem: 33369 +Epoch: [38] [ 130/1319] eta: 0:53:48 lr: 3.2220672208609392e-06 loss: 0.0255 (0.0328) time: 2.7140 data: 0.0064 max mem: 33369 +Epoch: [38] [ 140/1319] eta: 0:53:19 lr: 3.2104978562851772e-06 loss: 0.0275 (0.0324) time: 2.7136 data: 0.0063 max mem: 33369 +Epoch: [38] [ 150/1319] eta: 0:52:49 lr: 3.1989238574627024e-06 loss: 0.0291 (0.0322) time: 2.6884 data: 0.0066 max mem: 33369 +Epoch: [38] [ 160/1319] eta: 0:52:24 lr: 3.18734520389202e-06 loss: 0.0277 (0.0319) time: 2.7096 data: 0.0066 max mem: 33369 +Epoch: [38] [ 170/1319] eta: 0:51:57 lr: 3.175761874897778e-06 loss: 0.0264 (0.0317) time: 2.7249 data: 0.0066 max mem: 33369 +Epoch: [38] [ 180/1319] eta: 0:51:32 lr: 3.1641738496285912e-06 loss: 0.0301 (0.0318) time: 2.7296 data: 0.0065 max mem: 33369 +Epoch: [38] [ 190/1319] eta: 0:51:07 lr: 3.1525811070548283e-06 loss: 0.0286 (0.0317) time: 2.7466 data: 0.0064 max mem: 33369 +Epoch: [38] [ 200/1319] eta: 0:50:42 lr: 3.1409836259663234e-06 loss: 0.0280 (0.0315) time: 2.7528 data: 0.0061 max mem: 33369 +Epoch: [38] [ 210/1319] eta: 0:50:13 lr: 3.1293813849701203e-06 loss: 0.0302 (0.0316) time: 2.7262 data: 0.0063 max mem: 33369 +Epoch: [38] [ 220/1319] eta: 0:49:45 lr: 3.1177743624881108e-06 loss: 0.0311 (0.0315) time: 2.6918 data: 0.0064 max mem: 33369 +Epoch: [38] [ 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33369 +Epoch: [38] [ 310/1319] eta: 0:45:34 lr: 3.013092338126003e-06 loss: 0.0277 (0.0312) time: 2.7043 data: 0.0063 max mem: 33369 +Epoch: [38] [ 320/1319] eta: 0:45:07 lr: 3.0014362715060913e-06 loss: 0.0318 (0.0313) time: 2.6969 data: 0.0064 max mem: 33369 +Epoch: [38] [ 330/1319] eta: 0:44:39 lr: 2.9897751731121923e-06 loss: 0.0305 (0.0313) time: 2.6995 data: 0.0065 max mem: 33369 +Epoch: [38] [ 340/1319] eta: 0:44:13 lr: 2.978109018946967e-06 loss: 0.0285 (0.0312) time: 2.7132 data: 0.0065 max mem: 33369 +Epoch: [38] [ 350/1319] eta: 0:43:44 lr: 2.9664377847936435e-06 loss: 0.0265 (0.0311) time: 2.7026 data: 0.0064 max mem: 33369 +Epoch: [38] [ 360/1319] eta: 0:43:17 lr: 2.954761446213011e-06 loss: 0.0265 (0.0311) time: 2.6798 data: 0.0066 max mem: 33369 +Epoch: [38] [ 370/1319] eta: 0:42:49 lr: 2.943079978540434e-06 loss: 0.0292 (0.0311) time: 2.6819 data: 0.0066 max mem: 33369 +Epoch: [38] [ 380/1319] eta: 0:42:22 lr: 2.931393356882739e-06 loss: 0.0311 (0.0311) time: 2.6924 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2.2798478534460264e-06 loss: 0.0301 (0.0306) time: 2.6884 data: 0.0066 max mem: 33369 +Epoch: [38] [ 940/1319] eta: 0:17:02 lr: 2.2678240375265906e-06 loss: 0.0294 (0.0306) time: 2.7060 data: 0.0066 max mem: 33369 +Epoch: [38] [ 950/1319] eta: 0:16:36 lr: 2.25579313413962e-06 loss: 0.0268 (0.0306) time: 2.7504 data: 0.0065 max mem: 33369 +Epoch: [38] [ 960/1319] eta: 0:16:09 lr: 2.243755097057401e-06 loss: 0.0261 (0.0306) time: 2.7421 data: 0.0065 max mem: 33369 +Epoch: [38] [ 970/1319] eta: 0:15:42 lr: 2.2317098794731506e-06 loss: 0.0275 (0.0306) time: 2.7024 data: 0.0065 max mem: 33369 +Epoch: [38] [ 980/1319] eta: 0:15:14 lr: 2.2196574339902486e-06 loss: 0.0307 (0.0306) time: 2.6602 data: 0.0067 max mem: 33369 +Epoch: [38] [ 990/1319] eta: 0:14:48 lr: 2.2075977126112046e-06 loss: 0.0318 (0.0306) time: 2.6685 data: 0.0065 max mem: 33369 +Epoch: [38] [1000/1319] eta: 0:14:21 lr: 2.195530666726346e-06 loss: 0.0296 (0.0306) time: 2.7015 data: 0.0064 max mem: 33369 +Epoch: [38] 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0.0245 (0.0306) time: 2.6791 data: 0.0067 max mem: 33369 +Epoch: [38] [1250/1319] eta: 0:03:06 lr: 1.8913178052569088e-06 loss: 0.0264 (0.0306) time: 2.6977 data: 0.0066 max mem: 33369 +Epoch: [38] [1260/1319] eta: 0:02:39 lr: 1.8790409395427117e-06 loss: 0.0269 (0.0306) time: 2.7388 data: 0.0065 max mem: 33369 +Epoch: [38] [1270/1319] eta: 0:02:12 lr: 1.8667551548466507e-06 loss: 0.0304 (0.0306) time: 2.7241 data: 0.0065 max mem: 33369 +Epoch: [38] [1280/1319] eta: 0:01:45 lr: 1.8544603793717773e-06 loss: 0.0327 (0.0306) time: 2.7033 data: 0.0064 max mem: 33369 +Epoch: [38] [1290/1319] eta: 0:01:18 lr: 1.8421565402096163e-06 loss: 0.0336 (0.0306) time: 2.7107 data: 0.0064 max mem: 33369 +Epoch: [38] [1300/1319] eta: 0:00:51 lr: 1.8298435633145817e-06 loss: 0.0296 (0.0306) time: 2.7099 data: 0.0064 max mem: 33369 +Epoch: [38] [1310/1319] eta: 0:00:24 lr: 1.8175213734776007e-06 loss: 0.0287 (0.0306) time: 2.6930 data: 0.0065 max mem: 33369 +Epoch: [38] Total time: 0:59:21 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 1:52:09 time: 2.6156 data: 2.4828 max mem: 33369 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 100/2573] eta: 0:04:00 time: 0.0716 data: 0.0012 max mem: 33369 +Test: [ 200/2573] eta: 0:03:23 time: 0.0732 data: 0.0012 max mem: 33369 +Test: [ 300/2573] eta: 0:03:04 time: 0.0750 data: 0.0012 max mem: 33369 +Test: [ 400/2573] eta: 0:02:52 time: 0.0750 data: 0.0011 max mem: 33369 +Test: [ 500/2573] eta: 0:02:41 time: 0.0735 data: 0.0012 max mem: 33369 +Test: [ 600/2573] eta: 0:02:32 time: 0.0736 data: 0.0012 max mem: 33369 +Test: [ 700/2573] eta: 0:02:24 time: 0.0736 data: 0.0012 max mem: 33369 +Test: [ 800/2573] eta: 0:02:16 time: 0.0770 data: 0.0011 max mem: 33369 +Test: [ 900/2573] eta: 0:02:08 time: 0.0737 data: 0.0012 max mem: 33369 +Test: [1000/2573] eta: 0:02:00 time: 0.0737 data: 0.0012 max mem: 33369 +Test: [1100/2573] eta: 0:01:52 time: 0.0738 data: 0.0012 max mem: 33369 +Test: [1200/2573] eta: 0:01:44 time: 0.0738 data: 0.0011 max mem: 33369 +Test: [1300/2573] eta: 0:01:36 time: 0.0737 data: 0.0011 max mem: 33369 +Test: [1400/2573] eta: 0:01:28 time: 0.0721 data: 0.0012 max mem: 33369 +Test: [1500/2573] eta: 0:01:21 time: 0.0738 data: 0.0012 max mem: 33369 +Test: [1600/2573] eta: 0:01:13 time: 0.0771 data: 0.0011 max mem: 33369 +Test: [1700/2573] eta: 0:01:05 time: 0.0721 data: 0.0011 max mem: 33369 +Test: [1800/2573] eta: 0:00:58 time: 0.0757 data: 0.0012 max mem: 33369 +Test: [1900/2573] eta: 0:00:50 time: 0.0723 data: 0.0012 max mem: 33369 +Test: [2000/2573] eta: 0:00:42 time: 0.0738 data: 0.0011 max mem: 33369 +Test: [2100/2573] eta: 0:00:35 time: 0.0756 data: 0.0011 max mem: 33369 +Test: [2200/2573] eta: 0:00:27 time: 0.0755 data: 0.0011 max mem: 33369 +Test: [2300/2573] eta: 0:00:20 time: 0.0758 data: 0.0012 max mem: 33369 +Test: [2400/2573] eta: 0:00:12 time: 0.0707 data: 0.0012 max mem: 33369 +Test: [2500/2573] eta: 0:00:05 time: 0.0740 data: 0.0012 max mem: 33369 +Test: Total time: 0:03:12 +Final results: +Mean IoU is 64.82 + + precision@0.5 = 72.79 + precision@0.6 = 67.77 + precision@0.7 = 61.32 + precision@0.8 = 50.31 + precision@0.9 = 25.18 + overall IoU = 62.25 + +Average object IoU 64.81888045763093 +Overall IoU 62.24959182739258 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [39] [ 0/1319] eta: 3:50:55 lr: 1.8064234624396156e-06 loss: 0.0341 (0.0341) time: 10.5043 data: 2.2872 max mem: 33369 +Epoch: [39] [ 10/1319] eta: 1:15:11 lr: 1.7940835565249508e-06 loss: 0.0269 (0.0274) time: 3.4466 data: 0.2139 max mem: 33369 +Epoch: [39] [ 20/1319] eta: 1:07:17 lr: 1.7817342127276263e-06 loss: 0.0252 (0.0274) time: 2.7380 data: 0.0065 max mem: 33369 +Epoch: [39] [ 30/1319] eta: 1:03:45 lr: 1.7693753510331764e-06 loss: 0.0250 (0.0272) time: 2.7041 data: 0.0064 max mem: 33369 +Epoch: [39] [ 40/1319] eta: 1:02:03 lr: 1.757006890122028e-06 loss: 0.0293 (0.0283) time: 2.7042 data: 0.0064 max mem: 33369 +Epoch: [39] [ 50/1319] eta: 1:00:55 lr: 1.7446287473378005e-06 loss: 0.0293 (0.0282) time: 2.7458 data: 0.0064 max mem: 33369 +Epoch: [39] [ 60/1319] eta: 0:59:49 lr: 1.7322408386546176e-06 loss: 0.0295 (0.0288) time: 2.7279 data: 0.0065 max mem: 33369 +Epoch: [39] [ 70/1319] eta: 0:59:01 lr: 1.7198430786433514e-06 loss: 0.0335 (0.0294) time: 2.7210 data: 0.0064 max mem: 33369 +Epoch: [39] [ 80/1319] eta: 0:58:13 lr: 1.7074353804367206e-06 loss: 0.0316 (0.0294) time: 2.7242 data: 0.0064 max mem: 33369 +Epoch: [39] [ 90/1319] eta: 0:57:32 lr: 1.6950176556933094e-06 loss: 0.0264 (0.0294) time: 2.7167 data: 0.0064 max mem: 33369 +Epoch: [39] [ 100/1319] eta: 0:56:53 lr: 1.682589814560305e-06 loss: 0.0327 (0.0300) time: 2.7208 data: 0.0065 max mem: 33369 +Epoch: [39] [ 110/1319] eta: 0:56:12 lr: 1.6701517656350208e-06 loss: 0.0330 (0.0303) time: 2.6990 data: 0.0064 max mem: 33369 +Epoch: [39] [ 120/1319] eta: 0:55:34 lr: 1.6577034159251048e-06 loss: 0.0281 (0.0302) time: 2.6833 data: 0.0062 max mem: 33369 +Epoch: [39] [ 130/1319] eta: 0:55:03 lr: 1.6452446708073954e-06 loss: 0.0302 (0.0304) time: 2.7158 data: 0.0060 max mem: 33369 +Epoch: [39] [ 140/1319] eta: 0:54:30 lr: 1.632775433985313e-06 loss: 0.0302 (0.0304) time: 2.7302 data: 0.0062 max mem: 33369 +Epoch: [39] [ 150/1319] eta: 0:53:53 lr: 1.62029560744485e-06 loss: 0.0285 (0.0302) time: 2.6870 data: 0.0065 max mem: 33369 +Epoch: [39] [ 160/1319] eta: 0:53:25 lr: 1.6078050914089353e-06 loss: 0.0291 (0.0302) time: 2.7137 data: 0.0066 max mem: 33369 +Epoch: [39] [ 170/1319] eta: 0:52:55 lr: 1.5953037842902214e-06 loss: 0.0298 (0.0305) time: 2.7455 data: 0.0065 max mem: 33369 +Epoch: [39] [ 180/1319] eta: 0:52:26 lr: 1.5827915826421849e-06 loss: 0.0308 (0.0304) time: 2.7337 data: 0.0065 max mem: 33369 +Epoch: [39] [ 190/1319] eta: 0:51:59 lr: 1.5702683811084266e-06 loss: 0.0282 (0.0304) time: 2.7557 data: 0.0065 max mem: 33369 +Epoch: [39] [ 200/1319] eta: 0:51:28 lr: 1.5577340723702017e-06 loss: 0.0281 (0.0303) time: 2.7403 data: 0.0064 max mem: 33369 +Epoch: [39] [ 210/1319] eta: 0:51:01 lr: 1.5451885470919527e-06 loss: 0.0265 (0.0302) time: 2.7368 data: 0.0065 max mem: 33369 +Epoch: [39] [ 220/1319] eta: 0:50:31 lr: 1.5326316938648584e-06 loss: 0.0270 (0.0302) time: 2.7408 data: 0.0064 max mem: 33369 +Epoch: [39] [ 230/1319] eta: 0:50:03 lr: 1.5200633991482792e-06 loss: 0.0281 (0.0301) time: 2.7351 data: 0.0063 max mem: 33369 +Epoch: [39] [ 240/1319] eta: 0:49:36 lr: 1.5074835472089545e-06 loss: 0.0268 (0.0302) time: 2.7589 data: 0.0063 max mem: 33369 +Epoch: [39] [ 250/1319] eta: 0:49:05 lr: 1.4948920200579605e-06 loss: 0.0268 (0.0302) time: 2.7198 data: 0.0066 max mem: 33369 +Epoch: [39] [ 260/1319] eta: 0:48:33 lr: 1.4822886973851744e-06 loss: 0.0279 (0.0302) time: 2.6651 data: 0.0067 max mem: 33369 +Epoch: [39] [ 270/1319] eta: 0:48:04 lr: 1.4696734564912314e-06 loss: 0.0277 (0.0303) time: 2.6809 data: 0.0064 max mem: 33369 +Epoch: [39] [ 280/1319] eta: 0:47:34 lr: 1.457046172216814e-06 loss: 0.0298 (0.0303) time: 2.6969 data: 0.0063 max mem: 33369 +Epoch: [39] [ 290/1319] eta: 0:47:05 lr: 1.444406716869153e-06 loss: 0.0321 (0.0304) time: 2.6943 data: 0.0064 max mem: 33369 +Epoch: [39] [ 300/1319] eta: 0:46:38 lr: 1.4317549601455566e-06 loss: 0.0278 (0.0304) time: 2.7279 data: 0.0064 max mem: 33369 +Epoch: [39] [ 310/1319] eta: 0:46:08 lr: 1.419090769053936e-06 loss: 0.0274 (0.0305) time: 2.7098 data: 0.0062 max mem: 33369 +Epoch: [39] [ 320/1319] eta: 0:45:39 lr: 1.4064140078300187e-06 loss: 0.0320 (0.0305) time: 2.6813 data: 0.0061 max mem: 33369 +Epoch: [39] [ 330/1319] eta: 0:45:10 lr: 1.3937245378511972e-06 loss: 0.0299 (0.0305) time: 2.6959 data: 0.0061 max mem: 33369 +Epoch: [39] [ 340/1319] eta: 0:44:42 lr: 1.3810222175468009e-06 loss: 0.0280 (0.0306) time: 2.6980 data: 0.0061 max mem: 33369 +Epoch: [39] [ 350/1319] eta: 0:44:13 lr: 1.3683069023045655e-06 loss: 0.0269 (0.0305) time: 2.6981 data: 0.0061 max mem: 33369 +Epoch: [39] [ 360/1319] eta: 0:43:45 lr: 1.355578444373217e-06 loss: 0.0263 (0.0304) time: 2.7084 data: 0.0064 max mem: 33369 +Epoch: [39] [ 370/1319] eta: 0:43:17 lr: 1.3428366927608033e-06 loss: 0.0280 (0.0305) time: 2.7151 data: 0.0063 max mem: 33369 +Epoch: [39] [ 380/1319] eta: 0:42:49 lr: 1.330081493128668e-06 loss: 0.0292 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1.2275360499121832e-06 loss: 0.0308 (0.0307) time: 2.6725 data: 0.0065 max mem: 33369 +Epoch: [39] [ 470/1319] eta: 0:38:39 lr: 1.2146522617323656e-06 loss: 0.0325 (0.0307) time: 2.7037 data: 0.0063 max mem: 33369 +Epoch: [39] [ 480/1319] eta: 0:38:10 lr: 1.2017532710741682e-06 loss: 0.0291 (0.0306) time: 2.6855 data: 0.0064 max mem: 33369 +Epoch: [39] [ 490/1319] eta: 0:37:41 lr: 1.1888388782538434e-06 loss: 0.0280 (0.0306) time: 2.6500 data: 0.0066 max mem: 33369 +Epoch: [39] [ 500/1319] eta: 0:37:12 lr: 1.175908878519789e-06 loss: 0.0294 (0.0306) time: 2.6410 data: 0.0067 max mem: 33369 +Epoch: [39] [ 510/1319] eta: 0:36:44 lr: 1.1629630618603247e-06 loss: 0.0306 (0.0307) time: 2.6582 data: 0.0065 max mem: 33369 +Epoch: [39] [ 520/1319] eta: 0:36:16 lr: 1.150001212801783e-06 loss: 0.0307 (0.0306) time: 2.6676 data: 0.0067 max mem: 33369 +Epoch: [39] [ 530/1319] eta: 0:35:48 lr: 1.1370231101961411e-06 loss: 0.0274 (0.0306) time: 2.6565 data: 0.0067 max mem: 33369 +Epoch: [39] [ 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data: 0.0067 max mem: 33369 +Epoch: [39] [ 700/1319] eta: 0:28:00 lr: 9.136614974653884e-07 loss: 0.0291 (0.0308) time: 2.6976 data: 0.0068 max mem: 33369 +Epoch: [39] [ 710/1319] eta: 0:27:32 lr: 9.003449179133091e-07 loss: 0.0291 (0.0308) time: 2.6897 data: 0.0066 max mem: 33369 +Epoch: [39] [ 720/1319] eta: 0:27:05 lr: 8.870064170319405e-07 loss: 0.0288 (0.0307) time: 2.6795 data: 0.0065 max mem: 33369 +Epoch: [39] [ 730/1319] eta: 0:26:38 lr: 8.736455912114245e-07 loss: 0.0286 (0.0307) time: 2.6785 data: 0.0066 max mem: 33369 +Epoch: [39] [ 740/1319] eta: 0:26:10 lr: 8.602620224130043e-07 loss: 0.0297 (0.0308) time: 2.6716 data: 0.0065 max mem: 33369 +Epoch: [39] [ 750/1319] eta: 0:25:43 lr: 8.468552773943076e-07 loss: 0.0295 (0.0308) time: 2.7060 data: 0.0063 max mem: 33369 +Epoch: [39] [ 760/1319] eta: 0:25:16 lr: 8.334249068786857e-07 loss: 0.0254 (0.0307) time: 2.7226 data: 0.0063 max mem: 33369 +Epoch: [39] [ 770/1319] eta: 0:24:49 lr: 8.199704446634483e-07 loss: 0.0269 (0.0307) time: 2.6919 data: 0.0063 max mem: 33369 +Epoch: [39] [ 780/1319] eta: 0:24:21 lr: 8.064914066612595e-07 loss: 0.0303 (0.0307) time: 2.6809 data: 0.0065 max mem: 33369 +Epoch: [39] [ 790/1319] eta: 0:23:54 lr: 7.92987289868475e-07 loss: 0.0303 (0.0307) time: 2.6697 data: 0.0068 max mem: 33369 +Epoch: [39] [ 800/1319] eta: 0:23:27 lr: 7.79457571253187e-07 loss: 0.0333 (0.0308) time: 2.6953 data: 0.0065 max mem: 33369 +Epoch: [39] [ 810/1319] eta: 0:23:00 lr: 7.659017065551902e-07 loss: 0.0351 (0.0308) time: 2.7386 data: 0.0062 max mem: 33369 +Epoch: [39] [ 820/1319] eta: 0:22:33 lr: 7.523191289889679e-07 loss: 0.0345 (0.0308) time: 2.7209 data: 0.0064 max mem: 33369 +Epoch: [39] [ 830/1319] eta: 0:22:06 lr: 7.387092478397154e-07 loss: 0.0312 (0.0309) time: 2.6946 data: 0.0065 max mem: 33369 +Epoch: [39] [ 840/1319] eta: 0:21:38 lr: 7.250714469413284e-07 loss: 0.0291 (0.0309) time: 2.6961 data: 0.0065 max mem: 33369 +Epoch: [39] [ 850/1319] eta: 0:21:11 lr: 7.114050830235778e-07 loss: 0.0274 (0.0308) time: 2.6733 data: 0.0065 max mem: 33369 +Epoch: [39] [ 860/1319] eta: 0:20:44 lr: 6.977094839143229e-07 loss: 0.0290 (0.0309) time: 2.7033 data: 0.0064 max mem: 33369 +Epoch: [39] [ 870/1319] eta: 0:20:17 lr: 6.839839465805414e-07 loss: 0.0299 (0.0309) time: 2.7264 data: 0.0064 max mem: 33369 +Epoch: [39] [ 880/1319] eta: 0:19:50 lr: 6.702277349898191e-07 loss: 0.0263 (0.0308) time: 2.7200 data: 0.0063 max mem: 33369 +Epoch: [39] [ 890/1319] eta: 0:19:23 lr: 6.564400777713066e-07 loss: 0.0341 (0.0309) time: 2.7455 data: 0.0062 max mem: 33369 +Epoch: [39] [ 900/1319] eta: 0:18:56 lr: 6.426201656523381e-07 loss: 0.0360 (0.0310) time: 2.7468 data: 0.0062 max mem: 33369 +Epoch: [39] [ 910/1319] eta: 0:18:29 lr: 6.287671486431178e-07 loss: 0.0324 (0.0310) time: 2.7119 data: 0.0063 max mem: 33369 +Epoch: [39] [ 920/1319] eta: 0:18:01 lr: 6.148801329380617e-07 loss: 0.0324 (0.0310) time: 2.6735 data: 0.0065 max mem: 33369 +Epoch: [39] [ 930/1319] eta: 0:17:34 lr: 6.009581774973726e-07 loss: 0.0267 (0.0310) time: 2.6515 data: 0.0064 max mem: 33369 +Epoch: [39] [ 940/1319] eta: 0:17:07 lr: 5.870002902666957e-07 loss: 0.0285 (0.0310) time: 2.6667 data: 0.0064 max mem: 33369 +Epoch: [39] [ 950/1319] eta: 0:16:40 lr: 5.7300542398606e-07 loss: 0.0285 (0.0310) time: 2.6957 data: 0.0066 max mem: 33369 +Epoch: [39] [ 960/1319] eta: 0:16:12 lr: 5.589724715308914e-07 loss: 0.0279 (0.0310) time: 2.6912 data: 0.0065 max mem: 33369 +Epoch: [39] [ 970/1319] eta: 0:15:45 lr: 5.449002607184345e-07 loss: 0.0279 (0.0310) time: 2.6830 data: 0.0063 max mem: 33369 +Epoch: [39] [ 980/1319] eta: 0:15:18 lr: 5.307875485010082e-07 loss: 0.0272 (0.0309) time: 2.6957 data: 0.0064 max mem: 33369 +Epoch: [39] [ 990/1319] eta: 0:14:51 lr: 5.166330144533874e-07 loss: 0.0326 (0.0310) time: 2.7184 data: 0.0065 max mem: 33369 +Epoch: [39] [1000/1319] eta: 0:14:24 lr: 5.024352534442401e-07 loss: 0.0329 (0.0310) time: 2.7318 data: 0.0064 max mem: 33369 +Epoch: [39] [1010/1319] eta: 0:13:57 lr: 4.881927673605746e-07 loss: 0.0311 (0.0310) time: 2.7104 data: 0.0063 max mem: 33369 +Epoch: [39] [1020/1319] eta: 0:13:30 lr: 4.7390395572780197e-07 loss: 0.0286 (0.0310) time: 2.7181 data: 0.0064 max mem: 33369 +Epoch: [39] [1030/1319] eta: 0:13:03 lr: 4.595671050360423e-07 loss: 0.0288 (0.0309) time: 2.7235 data: 0.0064 max mem: 33369 +Epoch: [39] [1040/1319] eta: 0:12:36 lr: 4.4518037654287396e-07 loss: 0.0290 (0.0309) time: 2.6949 data: 0.0065 max mem: 33369 +Epoch: [39] [1050/1319] eta: 0:12:08 lr: 4.3074179227215756e-07 loss: 0.0310 (0.0310) time: 2.6763 data: 0.0066 max mem: 33369 +Epoch: [39] [1060/1319] eta: 0:11:41 lr: 4.162492188647174e-07 loss: 0.0304 (0.0310) time: 2.6771 data: 0.0066 max mem: 33369 +Epoch: [39] [1070/1319] eta: 0:11:14 lr: 4.01700348854669e-07 loss: 0.0284 (0.0309) time: 2.6783 data: 0.0065 max mem: 33369 +Epoch: [39] [1080/1319] eta: 0:10:47 lr: 3.8709267884030336e-07 loss: 0.0277 (0.0309) time: 2.6798 data: 0.0068 max mem: 33369 +Epoch: [39] [1090/1319] eta: 0:10:20 lr: 3.724234838815835e-07 loss: 0.0279 (0.0309) time: 2.6853 data: 0.0064 max mem: 33369 +Epoch: [39] [1100/1319] eta: 0:09:53 lr: 3.5768978727688177e-07 loss: 0.0278 (0.0309) time: 2.6985 data: 0.0062 max mem: 33369 +Epoch: [39] [1110/1319] eta: 0:09:26 lr: 3.428883246336122e-07 loss: 0.0264 (0.0309) time: 2.6920 data: 0.0064 max mem: 33369 +Epoch: [39] [1120/1319] eta: 0:08:58 lr: 3.280155008272766e-07 loss: 0.0269 (0.0309) time: 2.6877 data: 0.0065 max mem: 33369 +Epoch: [39] [1130/1319] eta: 0:08:31 lr: 3.1306733800860497e-07 loss: 0.0300 (0.0309) time: 2.7046 data: 0.0065 max mem: 33369 +Epoch: [39] [1140/1319] eta: 0:08:04 lr: 2.9803941221786203e-07 loss: 0.0273 (0.0310) time: 2.7112 data: 0.0063 max mem: 33369 +Epoch: [39] [1150/1319] eta: 0:07:37 lr: 2.829267753240405e-07 loss: 0.0292 (0.0310) time: 2.6984 data: 0.0064 max mem: 33369 +Epoch: [39] [1160/1319] eta: 0:07:10 lr: 2.677238578071334e-07 loss: 0.0284 (0.0309) time: 2.7222 data: 0.0063 max mem: 33369 +Epoch: [39] [1170/1319] eta: 0:06:43 lr: 2.524243461593822e-07 loss: 0.0254 (0.0309) time: 2.7408 data: 0.0062 max mem: 33369 +Epoch: [39] [1180/1319] eta: 0:06:16 lr: 2.370210260957732e-07 loss: 0.0307 (0.0309) time: 2.6770 data: 0.0064 max mem: 33369 +Epoch: [39] [1190/1319] eta: 0:05:49 lr: 2.2150557883672493e-07 loss: 0.0303 (0.0309) time: 2.6824 data: 0.0063 max mem: 33369 +Epoch: [39] [1200/1319] eta: 0:05:22 lr: 2.058683115970694e-07 loss: 0.0303 (0.0309) time: 2.7532 data: 0.0063 max mem: 33369 +Epoch: [39] [1210/1319] eta: 0:04:55 lr: 1.9009779355624344e-07 loss: 0.0295 (0.0309) time: 2.7675 data: 0.0064 max mem: 33369 +Epoch: [39] [1220/1319] eta: 0:04:28 lr: 1.7418035215766808e-07 loss: 0.0271 (0.0309) time: 2.7363 data: 0.0062 max mem: 33369 +Epoch: [39] [1230/1319] eta: 0:04:01 lr: 1.5809935607220197e-07 loss: 0.0275 (0.0309) time: 2.6931 data: 0.0063 max mem: 33369 +Epoch: [39] [1240/1319] eta: 0:03:33 lr: 1.4183415922236583e-07 loss: 0.0303 (0.0309) time: 2.6815 data: 0.0062 max mem: 33369 +Epoch: [39] [1250/1319] eta: 0:03:06 lr: 1.2535848000328487e-07 loss: 0.0303 (0.0309) time: 2.7003 data: 0.0064 max mem: 33369 +Epoch: [39] [1260/1319] eta: 0:02:39 lr: 1.0863778202227116e-07 loss: 0.0319 (0.0309) time: 2.6856 data: 0.0065 max mem: 33369 +Epoch: [39] [1270/1319] eta: 0:02:12 lr: 9.162475150165058e-08 loss: 0.0330 (0.0309) time: 2.7114 data: 0.0063 max mem: 33369 +Epoch: [39] [1280/1319] eta: 0:01:45 lr: 7.425076510067331e-08 loss: 0.0293 (0.0309) time: 2.7227 data: 0.0065 max mem: 33369 +Epoch: [39] [1290/1319] eta: 0:01:18 lr: 5.640763927216541e-08 loss: 0.0322 (0.0310) time: 2.7045 data: 0.0067 max mem: 33369 +Epoch: [39] [1300/1319] eta: 0:00:51 lr: 3.790015191412361e-08 loss: 0.0325 (0.0310) time: 2.7068 data: 0.0064 max mem: 33369 +Epoch: [39] [1310/1319] eta: 0:00:24 lr: 1.8267397722216235e-08 loss: 0.0276 (0.0309) time: 2.7187 data: 0.0062 max mem: 33369 +Epoch: [39] Total time: 0:59:33 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 2:01:12 time: 2.8267 data: 2.7460 max mem: 33369 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 100/2573] eta: 0:04:05 time: 0.0721 data: 0.0012 max mem: 33369 +Test: [ 200/2573] eta: 0:03:26 time: 0.0731 data: 0.0012 max mem: 33369 +Test: [ 300/2573] eta: 0:03:06 time: 0.0749 data: 0.0012 max mem: 33369 +Test: [ 400/2573] eta: 0:02:53 time: 0.0749 data: 0.0011 max mem: 33369 +Test: [ 500/2573] eta: 0:02:42 time: 0.0737 data: 0.0012 max mem: 33369 +Test: [ 600/2573] eta: 0:02:33 time: 0.0738 data: 0.0012 max mem: 33369 +Test: [ 700/2573] eta: 0:02:25 time: 0.0737 data: 0.0012 max mem: 33369 +Test: [ 800/2573] eta: 0:02:16 time: 0.0772 data: 0.0012 max mem: 33369 +Test: [ 900/2573] eta: 0:02:08 time: 0.0739 data: 0.0011 max mem: 33369 +Test: [1000/2573] eta: 0:02:00 time: 0.0737 data: 0.0012 max mem: 33369 +Test: [1100/2573] eta: 0:01:52 time: 0.0738 data: 0.0012 max mem: 33369 +Test: [1200/2573] eta: 0:01:44 time: 0.0738 data: 0.0012 max mem: 33369 +Test: [1300/2573] eta: 0:01:36 time: 0.0738 data: 0.0012 max mem: 33369 +Test: [1400/2573] eta: 0:01:28 time: 0.0722 data: 0.0012 max mem: 33369 +Test: [1500/2573] eta: 0:01:21 time: 0.0739 data: 0.0012 max mem: 33369 +Test: [1600/2573] eta: 0:01:13 time: 0.0771 data: 0.0012 max mem: 33369 +Test: [1700/2573] eta: 0:01:05 time: 0.0722 data: 0.0011 max mem: 33369 +Test: [1800/2573] eta: 0:00:58 time: 0.0755 data: 0.0011 max mem: 33369 +Test: [1900/2573] eta: 0:00:50 time: 0.0721 data: 0.0012 max mem: 33369 +Test: [2000/2573] eta: 0:00:43 time: 0.0740 data: 0.0012 max mem: 33369 +Test: [2100/2573] eta: 0:00:35 time: 0.0754 data: 0.0011 max mem: 33369 +Test: [2200/2573] eta: 0:00:27 time: 0.0755 data: 0.0011 max mem: 33369 +Test: [2300/2573] eta: 0:00:20 time: 0.0756 data: 0.0012 max mem: 33369 +Test: [2400/2573] eta: 0:00:12 time: 0.0705 data: 0.0011 max mem: 33369 +Test: [2500/2573] eta: 0:00:05 time: 0.0738 data: 0.0012 max mem: 33369 +Test: Total time: 0:03:12 +Final results: +Mean IoU is 64.92 + + precision@0.5 = 72.86 + precision@0.6 = 67.83 + precision@0.7 = 61.36 + precision@0.8 = 50.43 + precision@0.9 = 25.22 + overall IoU = 62.31 + +Average object IoU 64.91520839954586 +Overall IoU 62.309085845947266 +Training time 1 day, 16:49:22 diff --git a/LAVT-RIS/logs/old/gref_m10_mg12_tmp007_2gpu_bs16_ang.log b/LAVT-RIS/logs/old/gref_m10_mg12_tmp007_2gpu_bs16_ang.log new file mode 100644 index 0000000000000000000000000000000000000000..3c8f4cc194aaa593518d4aefe1e0742f93ee7945 --- /dev/null +++ b/LAVT-RIS/logs/old/gref_m10_mg12_tmp007_2gpu_bs16_ang.log @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:c8c4e085a45c771842a44ae08d0c9c292520ef6014881bad55b82a48a48fc313 +size 1817501 diff --git a/LAVT-RIS/logs/old/gref_m10_mg12_tmp007_4gpu_bs32_ang.log b/LAVT-RIS/logs/old/gref_m10_mg12_tmp007_4gpu_bs32_ang.log new file mode 100644 index 0000000000000000000000000000000000000000..b9e7c3166c2941513ee4ab6bc0254b27d29186b0 --- /dev/null +++ b/LAVT-RIS/logs/old/gref_m10_mg12_tmp007_4gpu_bs32_ang.log @@ -0,0 +1,12095 @@ +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torch/distributed/launch.py:178: FutureWarning: The module torch.distributed.launch is deprecated +and will be removed in future. Use torchrun. +Note that --use_env is set by default in torchrun. +If your script expects `--local_rank` argument to be set, please +change it to read from `os.environ['LOCAL_RANK']` instead. See +https://pytorch.org/docs/stable/distributed.html#launch-utility for +further instructions + + warnings.warn( +WARNING:torch.distributed.run: +***************************************** +Setting OMP_NUM_THREADS environment variable for each process to be 1 in default, to avoid your system being overloaded, please further tune the variable for optimal performance in your application as needed. +***************************************** +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/timm/models/layers/__init__.py:48: FutureWarning: Importing from timm.models.layers is deprecated, please import via timm.layers + warnings.warn(f"Importing from {__name__} is deprecated, please import via timm.layers", FutureWarning) +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/timm/models/layers/__init__.py:48: FutureWarning: Importing from timm.models.layers is deprecated, please import via timm.layers + warnings.warn(f"Importing from {__name__} is deprecated, please import via timm.layers", FutureWarning) +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/timm/models/layers/__init__.py:48: FutureWarning: Importing from timm.models.layers is deprecated, please import via timm.layers + warnings.warn(f"Importing from {__name__} is deprecated, please import via timm.layers", FutureWarning) +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/timm/models/layers/__init__.py:48: FutureWarning: Importing from timm.models.layers is deprecated, please import via timm.layers + warnings.warn(f"Importing from {__name__} is deprecated, please import via timm.layers", FutureWarning) +RANK and WORLD_SIZE in environment: 2/4 +RANK and WORLD_SIZE in environment: 3/4 +RANK and WORLD_SIZE in environment: 1/4 +RANK and WORLD_SIZE in environment: 0/4 +Image size: 480 +loading dataset refcocog into memory... +creating index... +index created. +DONE (t=5.57s) +loading dataset refcocog into memory... +creating index... +index created. +DONE (t=5.38s) +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torch/functional.py:478: UserWarning: torch.meshgrid: in an upcoming release, it will be required to pass the indexing argument. (Triggered internally at ../aten/src/ATen/native/TensorShape.cpp:2894.) + return _VF.meshgrid(tensors, **kwargs) # type: ignore[attr-defined] +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torch/functional.py:478: UserWarning: torch.meshgrid: in an upcoming release, it will be required to pass the indexing argument. (Triggered internally at ../aten/src/ATen/native/TensorShape.cpp:2894.) + return _VF.meshgrid(tensors, **kwargs) # type: ignore[attr-defined] +local rank 0 / global rank 0 successfully built train dataset. +lavt_one +Window size 12! +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torch/functional.py:478: UserWarning: torch.meshgrid: in an upcoming release, it will be required to pass the indexing argument. (Triggered internally at ../aten/src/ATen/native/TensorShape.cpp:2894.) + return _VF.meshgrid(tensors, **kwargs) # type: ignore[attr-defined] +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torch/functional.py:478: UserWarning: torch.meshgrid: in an upcoming release, it will be required to pass the indexing argument. (Triggered internally at ../aten/src/ATen/native/TensorShape.cpp:2894.) + return _VF.meshgrid(tensors, **kwargs) # type: ignore[attr-defined] +Initializing Multi-modal Swin Transformer weights from ./pretrained_weights/swin_base_patch4_window12_384_22k.pth +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [0] [ 0/1319] eta: 2:59:29 lr: 4.9999147080313756e-05 loss: 0.6179 (0.6179) time: 8.1650 data: 3.1865 max mem: 20156 +Epoch: [0] [ 10/1319] eta: 1:09:00 lr: 4.999061779453083e-05 loss: 0.4041 (0.4065) time: 3.1629 data: 0.2962 max mem: 29995 +Epoch: [0] [ 20/1319] eta: 1:03:33 lr: 4.9982088347050674e-05 loss: 0.3136 (0.3650) time: 2.6740 data: 0.0065 max mem: 29995 +Epoch: [0] [ 30/1319] eta: 1:01:45 lr: 4.9973558737839576e-05 loss: 0.3071 (0.3418) time: 2.7165 data: 0.0060 max mem: 29995 +Epoch: [0] [ 40/1319] eta: 1:00:22 lr: 4.9965028966863786e-05 loss: 0.2748 (0.3274) time: 2.7245 data: 0.0061 max mem: 29995 +Epoch: [0] [ 50/1319] eta: 0:59:31 lr: 4.995649903408956e-05 loss: 0.2748 (0.3212) time: 2.7214 data: 0.0061 max mem: 29995 +Epoch: [0] [ 60/1319] eta: 0:58:42 lr: 4.9947968939483133e-05 loss: 0.2901 (0.3246) time: 2.7256 data: 0.0060 max mem: 29995 +Epoch: [0] [ 70/1319] eta: 0:58:04 lr: 4.993943868301072e-05 loss: 0.2901 (0.3178) time: 2.7268 data: 0.0059 max mem: 29995 +Epoch: [0] [ 80/1319] eta: 0:57:27 lr: 4.993090826463852e-05 loss: 0.2577 (0.3099) time: 2.7383 data: 0.0060 max mem: 29995 +Epoch: [0] [ 90/1319] eta: 0:56:53 lr: 4.9922377684332736e-05 loss: 0.2424 (0.3040) time: 2.7330 data: 0.0060 max mem: 29995 +Epoch: [0] [ 100/1319] eta: 0:56:17 lr: 4.991384694205954e-05 loss: 0.2375 (0.2993) time: 2.7225 data: 0.0062 max mem: 29995 +Epoch: [0] [ 110/1319] eta: 0:55:47 lr: 4.990531603778512e-05 loss: 0.2837 (0.3007) time: 2.7309 data: 0.0061 max mem: 29995 +Epoch: [0] [ 120/1319] eta: 0:55:14 lr: 4.98967849714756e-05 loss: 0.2837 (0.2979) time: 2.7338 data: 0.0060 max mem: 29995 +Epoch: [0] [ 130/1319] eta: 0:54:44 lr: 4.988825374309713e-05 loss: 0.2500 (0.2950) time: 2.7267 data: 0.0061 max mem: 29995 +Epoch: [0] [ 140/1319] eta: 0:54:09 lr: 4.987972235261584e-05 loss: 0.2417 (0.2915) time: 2.7022 data: 0.0063 max mem: 29995 +Epoch: [0] [ 150/1319] eta: 0:53:36 lr: 4.987119079999784e-05 loss: 0.2446 (0.2914) time: 2.6765 data: 0.0063 max mem: 29995 +Epoch: [0] [ 160/1319] eta: 0:53:00 lr: 4.986265908520923e-05 loss: 0.2414 (0.2879) time: 2.6580 data: 0.0061 max mem: 29995 +Epoch: [0] [ 170/1319] eta: 0:52:31 lr: 4.985412720821609e-05 loss: 0.2375 (0.2870) time: 2.6831 data: 0.0061 max mem: 29995 +Epoch: [0] [ 180/1319] eta: 0:52:03 lr: 4.984559516898449e-05 loss: 0.2375 (0.2837) time: 2.7292 data: 0.0061 max mem: 29995 +Epoch: [0] [ 190/1319] eta: 0:51:32 lr: 4.98370629674805e-05 loss: 0.2257 (0.2819) time: 2.7057 data: 0.0062 max mem: 29995 +Epoch: [0] [ 200/1319] eta: 0:51:02 lr: 4.982853060367015e-05 loss: 0.2584 (0.2806) time: 2.6872 data: 0.0063 max mem: 29995 +Epoch: [0] [ 210/1319] eta: 0:50:34 lr: 4.9819998077519475e-05 loss: 0.2386 (0.2797) time: 2.7027 data: 0.0063 max mem: 31677 +Epoch: [0] [ 220/1319] eta: 0:50:06 lr: 4.98114653889945e-05 loss: 0.2171 (0.2771) time: 2.7287 data: 0.0064 max mem: 31677 +Epoch: [0] [ 230/1319] eta: 0:49:39 lr: 4.980293253806122e-05 loss: 0.2248 (0.2753) time: 2.7430 data: 0.0062 max mem: 31677 +Epoch: [0] [ 240/1319] eta: 0:49:08 lr: 4.9794399524685624e-05 loss: 0.2382 (0.2741) time: 2.6938 data: 0.0061 max mem: 31677 +Epoch: [0] [ 250/1319] eta: 0:48:40 lr: 4.97858663488337e-05 loss: 0.2347 (0.2725) time: 2.6792 data: 0.0062 max mem: 31677 +Epoch: [0] [ 260/1319] eta: 0:48:10 lr: 4.977733301047139e-05 loss: 0.2294 (0.2700) time: 2.6903 data: 0.0064 max mem: 31677 +Epoch: [0] [ 270/1319] eta: 0:47:42 lr: 4.9768799509564675e-05 loss: 0.2294 (0.2694) time: 2.6853 data: 0.0065 max mem: 31677 +Epoch: [0] [ 280/1319] eta: 0:47:13 lr: 4.976026584607946e-05 loss: 0.2291 (0.2678) time: 2.6941 data: 0.0065 max mem: 31677 +Epoch: [0] [ 290/1319] eta: 0:46:45 lr: 4.9751732019981684e-05 loss: 0.2316 (0.2682) time: 2.6955 data: 0.0065 max mem: 31677 +Epoch: [0] [ 300/1319] eta: 0:46:17 lr: 4.974319803123725e-05 loss: 0.2457 (0.2683) time: 2.7057 data: 0.0066 max mem: 31677 +Epoch: [0] [ 310/1319] eta: 0:45:48 lr: 4.973466387981205e-05 loss: 0.2449 (0.2686) time: 2.6995 data: 0.0067 max mem: 31677 +Epoch: [0] [ 320/1319] eta: 0:45:20 lr: 4.972612956567197e-05 loss: 0.2475 (0.2679) time: 2.6838 data: 0.0067 max mem: 31677 +Epoch: [0] [ 330/1319] eta: 0:44:50 lr: 4.971759508878288e-05 loss: 0.2168 (0.2671) time: 2.6601 data: 0.0069 max mem: 31677 +Epoch: [0] [ 340/1319] eta: 0:44:21 lr: 4.970906044911062e-05 loss: 0.2404 (0.2669) time: 2.6504 data: 0.0068 max mem: 31677 +Epoch: [0] [ 350/1319] eta: 0:43:52 lr: 4.970052564662105e-05 loss: 0.2404 (0.2661) time: 2.6560 data: 0.0066 max mem: 31677 +Epoch: [0] [ 360/1319] eta: 0:43:24 lr: 4.9691990681279974e-05 loss: 0.2233 (0.2650) time: 2.6637 data: 0.0068 max mem: 31677 +Epoch: [0] [ 370/1319] eta: 0:42:56 lr: 4.9683455553053225e-05 loss: 0.2343 (0.2644) time: 2.6762 data: 0.0067 max mem: 31677 +Epoch: [0] [ 380/1319] eta: 0:42:27 lr: 4.9674920261906595e-05 loss: 0.1984 (0.2631) time: 2.6623 data: 0.0067 max mem: 31677 +Epoch: [0] [ 390/1319] eta: 0:42:00 lr: 4.966638480780586e-05 loss: 0.1902 (0.2619) time: 2.6774 data: 0.0067 max mem: 33368 +Epoch: [0] [ 400/1319] eta: 0:41:31 lr: 4.9657849190716805e-05 loss: 0.2184 (0.2614) time: 2.6800 data: 0.0066 max mem: 33368 +Epoch: [0] [ 410/1319] eta: 0:41:04 lr: 4.964931341060517e-05 loss: 0.2175 (0.2606) time: 2.6875 data: 0.0065 max mem: 33368 +Epoch: [0] [ 420/1319] eta: 0:40:36 lr: 4.964077746743672e-05 loss: 0.2151 (0.2601) time: 2.7055 data: 0.0066 max mem: 33368 +Epoch: [0] [ 430/1319] eta: 0:40:10 lr: 4.963224136117718e-05 loss: 0.2271 (0.2598) time: 2.7057 data: 0.0069 max mem: 33368 +Epoch: [0] [ 440/1319] eta: 0:39:42 lr: 4.962370509179226e-05 loss: 0.2277 (0.2594) time: 2.7163 data: 0.0067 max mem: 33368 +Epoch: [0] [ 450/1319] eta: 0:39:16 lr: 4.9615168659247665e-05 loss: 0.2143 (0.2580) time: 2.7148 data: 0.0065 max mem: 33368 +Epoch: [0] [ 460/1319] eta: 0:38:49 lr: 4.960663206350908e-05 loss: 0.2012 (0.2571) time: 2.7225 data: 0.0065 max mem: 33368 +Epoch: [0] [ 470/1319] eta: 0:38:22 lr: 4.959809530454219e-05 loss: 0.2031 (0.2561) time: 2.7150 data: 0.0065 max mem: 33368 +Epoch: [0] [ 480/1319] eta: 0:37:55 lr: 4.958955838231264e-05 loss: 0.2016 (0.2555) time: 2.7183 data: 0.0065 max mem: 33368 +Epoch: [0] [ 490/1319] eta: 0:37:28 lr: 4.9581021296786104e-05 loss: 0.2016 (0.2544) time: 2.7265 data: 0.0066 max mem: 33368 +Epoch: [0] [ 500/1319] eta: 0:37:00 lr: 4.957248404792819e-05 loss: 0.1976 (0.2536) time: 2.7033 data: 0.0067 max mem: 33368 +Epoch: [0] [ 510/1319] eta: 0:36:33 lr: 4.956394663570453e-05 loss: 0.2051 (0.2530) time: 2.6793 data: 0.0067 max mem: 33368 +Epoch: [0] [ 520/1319] eta: 0:36:05 lr: 4.955540906008073e-05 loss: 0.2051 (0.2522) time: 2.6733 data: 0.0066 max mem: 33368 +Epoch: [0] [ 530/1319] eta: 0:35:38 lr: 4.954687132102238e-05 loss: 0.1869 (0.2511) time: 2.7029 data: 0.0065 max mem: 33368 +Epoch: [0] [ 540/1319] eta: 0:35:12 lr: 4.9538333418495056e-05 loss: 0.1913 (0.2505) time: 2.7548 data: 0.0064 max mem: 33368 +Epoch: [0] [ 550/1319] eta: 0:34:46 lr: 4.952979535246434e-05 loss: 0.2184 (0.2506) time: 2.7699 data: 0.0064 max mem: 33368 +Epoch: [0] [ 560/1319] eta: 0:34:19 lr: 4.952125712289576e-05 loss: 0.2203 (0.2501) time: 2.7470 data: 0.0064 max mem: 33368 +Epoch: [0] [ 570/1319] eta: 0:33:52 lr: 4.9512718729754866e-05 loss: 0.2244 (0.2502) time: 2.7291 data: 0.0066 max mem: 33368 +Epoch: [0] [ 580/1319] eta: 0:33:25 lr: 4.9504180173007175e-05 loss: 0.2379 (0.2498) time: 2.7553 data: 0.0064 max mem: 33368 +Epoch: [0] [ 590/1319] eta: 0:32:59 lr: 4.9495641452618194e-05 loss: 0.2131 (0.2493) time: 2.7611 data: 0.0062 max mem: 33368 +Epoch: [0] [ 600/1319] eta: 0:32:32 lr: 4.948710256855343e-05 loss: 0.1979 (0.2488) time: 2.7464 data: 0.0063 max mem: 33368 +Epoch: [0] [ 610/1319] eta: 0:32:05 lr: 4.9478563520778356e-05 loss: 0.2157 (0.2495) time: 2.7294 data: 0.0066 max mem: 33368 +Epoch: [0] [ 620/1319] eta: 0:31:38 lr: 4.947002430925844e-05 loss: 0.2542 (0.2496) time: 2.7130 data: 0.0067 max mem: 33368 +Epoch: [0] [ 630/1319] eta: 0:31:10 lr: 4.946148493395914e-05 loss: 0.2376 (0.2496) time: 2.7187 data: 0.0065 max mem: 33368 +Epoch: [0] [ 640/1319] eta: 0:30:43 lr: 4.945294539484589e-05 loss: 0.2227 (0.2490) time: 2.7168 data: 0.0066 max mem: 33368 +Epoch: [0] [ 650/1319] eta: 0:30:16 lr: 4.944440569188412e-05 loss: 0.2055 (0.2483) time: 2.7000 data: 0.0067 max mem: 33368 +Epoch: [0] [ 660/1319] eta: 0:29:48 lr: 4.943586582503924e-05 loss: 0.2081 (0.2483) time: 2.6870 data: 0.0066 max mem: 33368 +Epoch: [0] [ 670/1319] eta: 0:29:21 lr: 4.942732579427665e-05 loss: 0.2325 (0.2481) time: 2.6966 data: 0.0067 max mem: 33368 +Epoch: [0] [ 680/1319] eta: 0:28:54 lr: 4.941878559956172e-05 loss: 0.2158 (0.2476) time: 2.7014 data: 0.0067 max mem: 33368 +Epoch: [0] [ 690/1319] eta: 0:28:27 lr: 4.941024524085985e-05 loss: 0.2107 (0.2475) time: 2.6916 data: 0.0063 max mem: 33368 +Epoch: [0] [ 700/1319] eta: 0:28:00 lr: 4.940170471813637e-05 loss: 0.1992 (0.2473) time: 2.7217 data: 0.0062 max mem: 33368 +Epoch: [0] [ 710/1319] eta: 0:27:33 lr: 4.939316403135663e-05 loss: 0.2106 (0.2471) time: 2.7307 data: 0.0064 max mem: 33368 +Epoch: [0] [ 720/1319] eta: 0:27:06 lr: 4.938462318048596e-05 loss: 0.2189 (0.2466) time: 2.7395 data: 0.0063 max mem: 33368 +Epoch: [0] [ 730/1319] eta: 0:26:39 lr: 4.937608216548967e-05 loss: 0.1939 (0.2457) time: 2.7514 data: 0.0062 max mem: 33368 +Epoch: [0] [ 740/1319] eta: 0:26:12 lr: 4.936754098633307e-05 loss: 0.1914 (0.2457) time: 2.7319 data: 0.0064 max mem: 33368 +Epoch: [0] [ 750/1319] eta: 0:25:45 lr: 4.935899964298143e-05 loss: 0.1849 (0.2448) time: 2.7248 data: 0.0063 max mem: 33368 +Epoch: [0] [ 760/1319] eta: 0:25:17 lr: 4.9350458135400046e-05 loss: 0.1826 (0.2443) time: 2.7053 data: 0.0062 max mem: 33368 +Epoch: [0] [ 770/1319] eta: 0:24:50 lr: 4.934191646355415e-05 loss: 0.1954 (0.2442) time: 2.6832 data: 0.0065 max mem: 33368 +Epoch: [0] [ 780/1319] eta: 0:24:22 lr: 4.9333374627409e-05 loss: 0.1911 (0.2437) time: 2.6755 data: 0.0066 max mem: 33368 +Epoch: [0] [ 790/1319] eta: 0:23:55 lr: 4.932483262692982e-05 loss: 0.1971 (0.2432) time: 2.7020 data: 0.0067 max mem: 33368 +Epoch: [0] [ 800/1319] eta: 0:23:28 lr: 4.931629046208183e-05 loss: 0.2037 (0.2427) time: 2.7315 data: 0.0065 max mem: 33368 +Epoch: [0] [ 810/1319] eta: 0:23:01 lr: 4.9307748132830237e-05 loss: 0.2184 (0.2424) time: 2.7233 data: 0.0064 max mem: 33368 +Epoch: [0] [ 820/1319] eta: 0:22:35 lr: 4.929920563914022e-05 loss: 0.2080 (0.2421) time: 2.7458 data: 0.0066 max mem: 33368 +Epoch: [0] [ 830/1319] eta: 0:22:07 lr: 4.929066298097696e-05 loss: 0.2071 (0.2417) time: 2.7184 data: 0.0066 max mem: 33368 +Epoch: [0] [ 840/1319] eta: 0:21:40 lr: 4.928212015830561e-05 loss: 0.1814 (0.2410) time: 2.7030 data: 0.0067 max mem: 33368 +Epoch: [0] [ 850/1319] eta: 0:21:13 lr: 4.927357717109131e-05 loss: 0.1863 (0.2407) time: 2.7466 data: 0.0065 max mem: 33368 +Epoch: [0] [ 860/1319] eta: 0:20:46 lr: 4.926503401929921e-05 loss: 0.1927 (0.2404) time: 2.7285 data: 0.0064 max mem: 33368 +Epoch: [0] [ 870/1319] eta: 0:20:19 lr: 4.925649070289441e-05 loss: 0.2116 (0.2402) time: 2.7194 data: 0.0064 max mem: 33368 +Epoch: [0] [ 880/1319] eta: 0:19:52 lr: 4.9247947221842024e-05 loss: 0.2034 (0.2399) time: 2.7381 data: 0.0067 max mem: 33368 +Epoch: [0] [ 890/1319] eta: 0:19:25 lr: 4.923940357610714e-05 loss: 0.1924 (0.2394) time: 2.7393 data: 0.0068 max mem: 33368 +Epoch: [0] [ 900/1319] eta: 0:18:58 lr: 4.9230859765654824e-05 loss: 0.1790 (0.2390) time: 2.7513 data: 0.0065 max mem: 33368 +Epoch: [0] [ 910/1319] eta: 0:18:31 lr: 4.922231579045014e-05 loss: 0.1758 (0.2383) time: 2.7588 data: 0.0065 max mem: 33368 +Epoch: [0] [ 920/1319] eta: 0:18:04 lr: 4.921377165045815e-05 loss: 0.1771 (0.2380) time: 2.7526 data: 0.0065 max mem: 33368 +Epoch: [0] [ 930/1319] eta: 0:17:37 lr: 4.9205227345643864e-05 loss: 0.1973 (0.2377) time: 2.7291 data: 0.0063 max mem: 33368 +Epoch: [0] [ 940/1319] eta: 0:17:09 lr: 4.919668287597232e-05 loss: 0.1997 (0.2377) time: 2.7075 data: 0.0063 max mem: 33368 +Epoch: [0] [ 950/1319] eta: 0:16:42 lr: 4.918813824140851e-05 loss: 0.2112 (0.2373) time: 2.7049 data: 0.0064 max mem: 33368 +Epoch: [0] [ 960/1319] eta: 0:16:15 lr: 4.9179593441917424e-05 loss: 0.1846 (0.2369) time: 2.7142 data: 0.0065 max mem: 33368 +Epoch: [0] [ 970/1319] eta: 0:15:48 lr: 4.917104847746404e-05 loss: 0.1903 (0.2365) time: 2.7240 data: 0.0065 max mem: 33368 +Epoch: [0] [ 980/1319] eta: 0:15:21 lr: 4.916250334801333e-05 loss: 0.1842 (0.2361) time: 2.7037 data: 0.0065 max mem: 33368 +Epoch: [0] [ 990/1319] eta: 0:14:53 lr: 4.915395805353022e-05 loss: 0.1794 (0.2357) time: 2.6880 data: 0.0066 max mem: 33368 +Epoch: [0] [1000/1319] eta: 0:14:26 lr: 4.9145412593979664e-05 loss: 0.1866 (0.2354) time: 2.6895 data: 0.0065 max mem: 33368 +Epoch: [0] [1010/1319] eta: 0:13:59 lr: 4.913686696932656e-05 loss: 0.1854 (0.2350) time: 2.7066 data: 0.0065 max mem: 33368 +Epoch: [0] [1020/1319] eta: 0:13:32 lr: 4.9128321179535836e-05 loss: 0.1824 (0.2346) time: 2.7439 data: 0.0063 max mem: 33368 +Epoch: [0] [1030/1319] eta: 0:13:05 lr: 4.911977522457237e-05 loss: 0.1912 (0.2344) time: 2.7690 data: 0.0062 max mem: 33368 +Epoch: [0] [1040/1319] eta: 0:12:38 lr: 4.9111229104401044e-05 loss: 0.1959 (0.2341) time: 2.7385 data: 0.0064 max mem: 33368 +Epoch: [0] [1050/1319] eta: 0:12:10 lr: 4.910268281898671e-05 loss: 0.1922 (0.2340) time: 2.7027 data: 0.0066 max mem: 33368 +Epoch: [0] [1060/1319] eta: 0:11:43 lr: 4.9094136368294215e-05 loss: 0.2112 (0.2338) time: 2.6769 data: 0.0065 max mem: 33368 +Epoch: [0] [1070/1319] eta: 0:11:16 lr: 4.90855897522884e-05 loss: 0.2263 (0.2337) time: 2.6782 data: 0.0066 max mem: 33368 +Epoch: [0] [1080/1319] eta: 0:10:49 lr: 4.907704297093409e-05 loss: 0.1851 (0.2332) time: 2.7190 data: 0.0066 max mem: 33368 +Epoch: [0] [1090/1319] eta: 0:10:22 lr: 4.906849602419608e-05 loss: 0.1802 (0.2330) time: 2.7303 data: 0.0064 max mem: 33368 +Epoch: [0] [1100/1319] eta: 0:09:54 lr: 4.905994891203916e-05 loss: 0.2145 (0.2329) time: 2.7139 data: 0.0065 max mem: 33368 +Epoch: [0] [1110/1319] eta: 0:09:27 lr: 4.905140163442811e-05 loss: 0.2090 (0.2326) time: 2.7239 data: 0.0065 max mem: 33368 +Epoch: [0] [1120/1319] eta: 0:09:00 lr: 4.904285419132769e-05 loss: 0.1992 (0.2323) time: 2.7255 data: 0.0065 max mem: 33368 +Epoch: [0] [1130/1319] eta: 0:08:33 lr: 4.903430658270266e-05 loss: 0.1992 (0.2322) time: 2.7383 data: 0.0066 max mem: 33368 +Epoch: [0] [1140/1319] eta: 0:08:06 lr: 4.902575880851773e-05 loss: 0.1997 (0.2319) time: 2.7356 data: 0.0066 max mem: 33368 +Epoch: [0] [1150/1319] eta: 0:07:39 lr: 4.9017210868737634e-05 loss: 0.1635 (0.2315) time: 2.7293 data: 0.0065 max mem: 33368 +Epoch: [0] [1160/1319] eta: 0:07:12 lr: 4.900866276332707e-05 loss: 0.1606 (0.2311) time: 2.7326 data: 0.0065 max mem: 33368 +Epoch: [0] [1170/1319] eta: 0:06:44 lr: 4.9000114492250734e-05 loss: 0.1768 (0.2308) time: 2.7116 data: 0.0065 max mem: 33368 +Epoch: [0] [1180/1319] eta: 0:06:17 lr: 4.8991566055473306e-05 loss: 0.1829 (0.2305) time: 2.7240 data: 0.0065 max mem: 33368 +Epoch: [0] [1190/1319] eta: 0:05:50 lr: 4.8983017452959435e-05 loss: 0.1789 (0.2302) time: 2.7472 data: 0.0064 max mem: 33368 +Epoch: [0] [1200/1319] eta: 0:05:23 lr: 4.8974468684673776e-05 loss: 0.1926 (0.2302) time: 2.7365 data: 0.0063 max mem: 33368 +Epoch: [0] [1210/1319] eta: 0:04:56 lr: 4.896591975058095e-05 loss: 0.2041 (0.2298) time: 2.7110 data: 0.0064 max mem: 33368 +Epoch: [0] [1220/1319] eta: 0:04:29 lr: 4.89573706506456e-05 loss: 0.1873 (0.2296) time: 2.7193 data: 0.0064 max mem: 33368 +Epoch: [0] [1230/1319] eta: 0:04:01 lr: 4.89488213848323e-05 loss: 0.1884 (0.2295) time: 2.7516 data: 0.0064 max mem: 33368 +Epoch: [0] [1240/1319] eta: 0:03:34 lr: 4.894027195310566e-05 loss: 0.1798 (0.2291) time: 2.7437 data: 0.0063 max mem: 33368 +Epoch: [0] [1250/1319] eta: 0:03:07 lr: 4.893172235543025e-05 loss: 0.2005 (0.2290) time: 2.7261 data: 0.0066 max mem: 33368 +Epoch: [0] [1260/1319] eta: 0:02:40 lr: 4.892317259177062e-05 loss: 0.2113 (0.2290) time: 2.7330 data: 0.0066 max mem: 33368 +Epoch: [0] [1270/1319] eta: 0:02:13 lr: 4.8914622662091334e-05 loss: 0.2012 (0.2288) time: 2.7425 data: 0.0065 max mem: 33368 +Epoch: [0] [1280/1319] eta: 0:01:46 lr: 4.890607256635692e-05 loss: 0.1990 (0.2286) time: 2.7264 data: 0.0067 max mem: 33368 +Epoch: [0] [1290/1319] eta: 0:01:18 lr: 4.8897522304531876e-05 loss: 0.1962 (0.2284) time: 2.7229 data: 0.0068 max mem: 33368 +Epoch: [0] [1300/1319] eta: 0:00:51 lr: 4.888897187658072e-05 loss: 0.1869 (0.2280) time: 2.7365 data: 0.0065 max mem: 33368 +Epoch: [0] [1310/1319] eta: 0:00:24 lr: 4.888042128246795e-05 loss: 0.1768 (0.2278) time: 2.7303 data: 0.0062 max mem: 33368 +Epoch: [0] Total time: 0:59:47 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 1:45:37 time: 2.4630 data: 2.2974 max mem: 33368 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 100/2573] eta: 0:04:03 time: 0.0715 data: 0.0012 max mem: 33368 +Test: [ 200/2573] eta: 0:03:24 time: 0.0732 data: 0.0012 max mem: 33368 +Test: [ 300/2573] eta: 0:03:05 time: 0.0750 data: 0.0012 max mem: 33368 +Test: [ 400/2573] eta: 0:02:52 time: 0.0750 data: 0.0011 max mem: 33368 +Test: [ 500/2573] eta: 0:02:42 time: 0.0738 data: 0.0012 max mem: 33368 +Test: [ 600/2573] eta: 0:02:33 time: 0.0736 data: 0.0012 max mem: 33368 +Test: [ 700/2573] eta: 0:02:24 time: 0.0738 data: 0.0012 max mem: 33368 +Test: [ 800/2573] eta: 0:02:16 time: 0.0775 data: 0.0012 max mem: 33368 +Test: [ 900/2573] eta: 0:02:08 time: 0.0738 data: 0.0011 max mem: 33368 +Test: [1000/2573] eta: 0:02:00 time: 0.0737 data: 0.0012 max mem: 33368 +Test: [1100/2573] eta: 0:01:52 time: 0.0740 data: 0.0012 max mem: 33368 +Test: [1200/2573] eta: 0:01:44 time: 0.0739 data: 0.0012 max mem: 33368 +Test: [1300/2573] eta: 0:01:36 time: 0.0741 data: 0.0011 max mem: 33368 +Test: [1400/2573] eta: 0:01:28 time: 0.0723 data: 0.0012 max mem: 33368 +Test: [1500/2573] eta: 0:01:21 time: 0.0741 data: 0.0012 max mem: 33368 +Test: [1600/2573] eta: 0:01:13 time: 0.0774 data: 0.0012 max mem: 33368 +Test: [1700/2573] eta: 0:01:06 time: 0.0725 data: 0.0012 max mem: 33368 +Test: [1800/2573] eta: 0:00:58 time: 0.0758 data: 0.0011 max mem: 33368 +Test: [1900/2573] eta: 0:00:50 time: 0.0726 data: 0.0012 max mem: 33368 +Test: [2000/2573] eta: 0:00:43 time: 0.0742 data: 0.0012 max mem: 33368 +Test: [2100/2573] eta: 0:00:35 time: 0.0760 data: 0.0012 max mem: 33368 +Test: [2200/2573] eta: 0:00:28 time: 0.0757 data: 0.0011 max mem: 33368 +Test: [2300/2573] eta: 0:00:20 time: 0.0762 data: 0.0012 max mem: 33368 +Test: [2400/2573] eta: 0:00:12 time: 0.0710 data: 0.0012 max mem: 33368 +Test: [2500/2573] eta: 0:00:05 time: 0.0744 data: 0.0012 max mem: 33368 +Test: Total time: 0:03:13 +Final results: +Mean IoU is 28.64 + + precision@0.5 = 25.59 + precision@0.6 = 18.26 + precision@0.7 = 11.81 + precision@0.8 = 5.51 + precision@0.9 = 1.06 + overall IoU = 34.06 + +Average object IoU 28.635294796192817 +Overall IoU 34.05582809448242 +Better epoch: 0 + +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [1] [ 0/1319] eta: 1:27:45 lr: 4.8872725605668895e-05 loss: 0.1816 (0.1816) time: 3.9921 data: 1.2085 max mem: 33368 +Epoch: [1] [ 10/1319] eta: 1:00:46 lr: 4.886417469575114e-05 loss: 0.1829 (0.1914) time: 2.7854 data: 0.1154 max mem: 33368 +Epoch: [1] [ 20/1319] eta: 0:59:10 lr: 4.88556236195687e-05 loss: 0.1829 (0.1814) time: 2.6703 data: 0.0061 max mem: 33368 +Epoch: [1] [ 30/1319] eta: 0:58:28 lr: 4.884707237708599e-05 loss: 0.1893 (0.1837) time: 2.6873 data: 0.0064 max mem: 33368 +Epoch: [1] [ 40/1319] eta: 0:57:14 lr: 4.883852096826744e-05 loss: 0.1918 (0.1875) time: 2.6351 data: 0.0069 max mem: 33368 +Epoch: [1] [ 50/1319] eta: 0:56:35 lr: 4.882996939307746e-05 loss: 0.1890 (0.1887) time: 2.6032 data: 0.0068 max mem: 33368 +Epoch: [1] [ 60/1319] eta: 0:56:11 lr: 4.882141765148041e-05 loss: 0.1782 (0.1879) time: 2.6636 data: 0.0063 max mem: 33368 +Epoch: [1] [ 70/1319] eta: 0:55:35 lr: 4.881286574344069e-05 loss: 0.1630 (0.1841) time: 2.6583 data: 0.0062 max mem: 33368 +Epoch: [1] [ 80/1319] eta: 0:55:08 lr: 4.8804313668922646e-05 loss: 0.1650 (0.1858) time: 2.6456 data: 0.0065 max mem: 33368 +Epoch: [1] [ 90/1319] eta: 0:54:35 lr: 4.879576142789063e-05 loss: 0.1650 (0.1844) time: 2.6461 data: 0.0067 max mem: 33368 +Epoch: [1] [ 100/1319] eta: 0:54:13 lr: 4.878720902030896e-05 loss: 0.1625 (0.1847) time: 2.6646 data: 0.0066 max mem: 33368 +Epoch: [1] [ 110/1319] eta: 0:53:54 lr: 4.877865644614197e-05 loss: 0.1683 (0.1835) time: 2.7229 data: 0.0065 max mem: 33368 +Epoch: [1] [ 120/1319] eta: 0:53:31 lr: 4.877010370535394e-05 loss: 0.1819 (0.1854) time: 2.7243 data: 0.0064 max mem: 33368 +Epoch: [1] [ 130/1319] eta: 0:53:13 lr: 4.8761550797909164e-05 loss: 0.1870 (0.1843) time: 2.7424 data: 0.0065 max mem: 33368 +Epoch: [1] [ 140/1319] eta: 0:52:47 lr: 4.875299772377192e-05 loss: 0.1868 (0.1842) time: 2.7395 data: 0.0065 max mem: 33368 +Epoch: [1] [ 150/1319] eta: 0:52:27 lr: 4.874444448290645e-05 loss: 0.1868 (0.1841) time: 2.7365 data: 0.0064 max mem: 33368 +Epoch: [1] [ 160/1319] eta: 0:52:01 lr: 4.873589107527701e-05 loss: 0.1772 (0.1831) time: 2.7354 data: 0.0065 max mem: 33368 +Epoch: [1] [ 170/1319] eta: 0:51:34 lr: 4.872733750084782e-05 loss: 0.1750 (0.1838) time: 2.7011 data: 0.0065 max mem: 33368 +Epoch: [1] [ 180/1319] eta: 0:51:10 lr: 4.871878375958309e-05 loss: 0.1786 (0.1845) time: 2.7189 data: 0.0063 max mem: 33368 +Epoch: [1] [ 190/1319] eta: 0:50:42 lr: 4.871022985144703e-05 loss: 0.1859 (0.1847) time: 2.7097 data: 0.0064 max mem: 33368 +Epoch: [1] [ 200/1319] eta: 0:50:17 lr: 4.870167577640381e-05 loss: 0.1863 (0.1858) time: 2.7016 data: 0.0065 max mem: 33368 +Epoch: [1] [ 210/1319] eta: 0:49:48 lr: 4.869312153441761e-05 loss: 0.1815 (0.1858) time: 2.6917 data: 0.0066 max mem: 33368 +Epoch: [1] [ 220/1319] eta: 0:49:19 lr: 4.868456712545258e-05 loss: 0.1821 (0.1866) time: 2.6623 data: 0.0068 max mem: 33368 +Epoch: [1] [ 230/1319] eta: 0:48:52 lr: 4.8676012549472854e-05 loss: 0.1869 (0.1861) time: 2.6732 data: 0.0067 max mem: 33368 +Epoch: [1] [ 240/1319] eta: 0:48:26 lr: 4.866745780644256e-05 loss: 0.1679 (0.1853) time: 2.6962 data: 0.0065 max mem: 33368 +Epoch: [1] [ 250/1319] eta: 0:47:58 lr: 4.865890289632581e-05 loss: 0.1679 (0.1851) time: 2.6908 data: 0.0067 max mem: 33368 +Epoch: [1] [ 260/1319] eta: 0:47:30 lr: 4.8650347819086694e-05 loss: 0.1827 (0.1850) time: 2.6754 data: 0.0067 max mem: 33368 +Epoch: [1] [ 270/1319] eta: 0:47:04 lr: 4.864179257468931e-05 loss: 0.1807 (0.1845) time: 2.6864 data: 0.0065 max mem: 33368 +Epoch: [1] [ 280/1319] eta: 0:46:40 lr: 4.8633237163097687e-05 loss: 0.1859 (0.1856) time: 2.7313 data: 0.0066 max mem: 33368 +Epoch: [1] [ 290/1319] eta: 0:46:12 lr: 4.862468158427592e-05 loss: 0.1866 (0.1861) time: 2.7207 data: 0.0064 max mem: 33368 +Epoch: [1] [ 300/1319] eta: 0:45:46 lr: 4.861612583818801e-05 loss: 0.1788 (0.1868) time: 2.6962 data: 0.0063 max mem: 33368 +Epoch: [1] [ 310/1319] eta: 0:45:18 lr: 4.860756992479799e-05 loss: 0.1833 (0.1876) time: 2.6989 data: 0.0063 max mem: 33368 +Epoch: [1] [ 320/1319] eta: 0:44:53 lr: 4.859901384406988e-05 loss: 0.1940 (0.1877) time: 2.7091 data: 0.0062 max mem: 33368 +Epoch: [1] [ 330/1319] eta: 0:44:27 lr: 4.8590457595967656e-05 loss: 0.1840 (0.1881) time: 2.7386 data: 0.0063 max mem: 33368 +Epoch: [1] [ 340/1319] eta: 0:44:00 lr: 4.85819011804553e-05 loss: 0.1736 (0.1873) time: 2.7096 data: 0.0066 max mem: 33368 +Epoch: [1] [ 350/1319] eta: 0:43:34 lr: 4.8573344597496775e-05 loss: 0.1687 (0.1876) time: 2.7049 data: 0.0066 max mem: 33368 +Epoch: [1] [ 360/1319] eta: 0:43:08 lr: 4.856478784705602e-05 loss: 0.1881 (0.1875) time: 2.7328 data: 0.0061 max mem: 33368 +Epoch: [1] [ 370/1319] eta: 0:42:40 lr: 4.8556230929096985e-05 loss: 0.1881 (0.1879) time: 2.7136 data: 0.0063 max mem: 33368 +Epoch: [1] [ 380/1319] eta: 0:42:13 lr: 4.854767384358357e-05 loss: 0.1740 (0.1874) time: 2.6853 data: 0.0065 max mem: 33368 +Epoch: [1] [ 390/1319] eta: 0:41:46 lr: 4.8539116590479686e-05 loss: 0.1740 (0.1875) time: 2.6786 data: 0.0068 max mem: 33368 +Epoch: [1] [ 400/1319] eta: 0:41:18 lr: 4.8530559169749225e-05 loss: 0.1767 (0.1873) time: 2.6725 data: 0.0068 max mem: 33368 +Epoch: [1] [ 410/1319] eta: 0:40:52 lr: 4.852200158135605e-05 loss: 0.1667 (0.1872) time: 2.7075 data: 0.0066 max mem: 33368 +Epoch: [1] [ 420/1319] eta: 0:40:25 lr: 4.851344382526403e-05 loss: 0.1667 (0.1868) time: 2.7133 data: 0.0067 max mem: 33368 +Epoch: [1] [ 430/1319] eta: 0:39:58 lr: 4.850488590143701e-05 loss: 0.1789 (0.1871) time: 2.7055 data: 0.0066 max mem: 33368 +Epoch: [1] [ 440/1319] eta: 0:39:32 lr: 4.84963278098388e-05 loss: 0.1809 (0.1870) time: 2.7277 data: 0.0065 max mem: 33368 +Epoch: [1] [ 450/1319] eta: 0:39:06 lr: 4.8487769550433236e-05 loss: 0.1531 (0.1871) time: 2.7310 data: 0.0065 max mem: 33368 +Epoch: [1] [ 460/1319] eta: 0:38:40 lr: 4.84792111231841e-05 loss: 0.1625 (0.1864) time: 2.7537 data: 0.0063 max mem: 33368 +Epoch: [1] [ 470/1319] eta: 0:38:12 lr: 4.847065252805519e-05 loss: 0.1686 (0.1866) time: 2.7207 data: 0.0063 max mem: 33368 +Epoch: [1] [ 480/1319] eta: 0:37:46 lr: 4.846209376501027e-05 loss: 0.1904 (0.1867) time: 2.7057 data: 0.0063 max mem: 33368 +Epoch: [1] [ 490/1319] eta: 0:37:20 lr: 4.8453534834013074e-05 loss: 0.1903 (0.1869) time: 2.7423 data: 0.0062 max mem: 33368 +Epoch: [1] [ 500/1319] eta: 0:36:53 lr: 4.844497573502737e-05 loss: 0.1906 (0.1870) time: 2.7180 data: 0.0061 max mem: 33368 +Epoch: [1] [ 510/1319] eta: 0:36:26 lr: 4.8436416468016874e-05 loss: 0.1845 (0.1873) time: 2.6998 data: 0.0064 max mem: 33368 +Epoch: [1] [ 520/1319] eta: 0:36:00 lr: 4.8427857032945285e-05 loss: 0.1689 (0.1871) time: 2.7452 data: 0.0065 max mem: 33368 +Epoch: [1] [ 530/1319] eta: 0:35:33 lr: 4.841929742977631e-05 loss: 0.1602 (0.1865) time: 2.7633 data: 0.0062 max mem: 33368 +Epoch: [1] [ 540/1319] eta: 0:35:06 lr: 4.841073765847362e-05 loss: 0.1781 (0.1868) time: 2.7240 data: 0.0062 max mem: 33368 +Epoch: [1] [ 550/1319] eta: 0:34:40 lr: 4.840217771900089e-05 loss: 0.1885 (0.1867) time: 2.7139 data: 0.0062 max mem: 33368 +Epoch: [1] [ 560/1319] eta: 0:34:13 lr: 4.8393617611321754e-05 loss: 0.1640 (0.1866) time: 2.7309 data: 0.0062 max mem: 33368 +Epoch: [1] [ 570/1319] eta: 0:33:46 lr: 4.838505733539985e-05 loss: 0.1732 (0.1866) time: 2.7369 data: 0.0063 max mem: 33368 +Epoch: [1] [ 580/1319] eta: 0:33:20 lr: 4.83764968911988e-05 loss: 0.1732 (0.1865) time: 2.7391 data: 0.0066 max mem: 33368 +Epoch: [1] [ 590/1319] eta: 0:32:53 lr: 4.836793627868222e-05 loss: 0.1769 (0.1864) time: 2.7185 data: 0.0064 max mem: 33368 +Epoch: [1] [ 600/1319] eta: 0:32:26 lr: 4.835937549781368e-05 loss: 0.1691 (0.1864) time: 2.7052 data: 0.0062 max mem: 33368 +Epoch: [1] [ 610/1319] eta: 0:31:58 lr: 4.835081454855677e-05 loss: 0.1629 (0.1861) time: 2.7092 data: 0.0065 max mem: 33368 +Epoch: [1] [ 620/1319] eta: 0:31:31 lr: 4.8342253430875026e-05 loss: 0.1552 (0.1862) time: 2.7115 data: 0.0064 max mem: 33368 +Epoch: [1] [ 630/1319] eta: 0:31:05 lr: 4.833369214473202e-05 loss: 0.1515 (0.1860) time: 2.7277 data: 0.0061 max mem: 33368 +Epoch: [1] [ 640/1319] eta: 0:30:37 lr: 4.832513069009127e-05 loss: 0.1473 (0.1855) time: 2.7002 data: 0.0062 max mem: 33368 +Epoch: [1] [ 650/1319] eta: 0:30:11 lr: 4.8316569066916287e-05 loss: 0.1537 (0.1856) time: 2.7109 data: 0.0062 max mem: 33368 +Epoch: [1] [ 660/1319] eta: 0:29:43 lr: 4.8308007275170564e-05 loss: 0.1792 (0.1855) time: 2.7177 data: 0.0065 max mem: 33368 +Epoch: [1] [ 670/1319] eta: 0:29:17 lr: 4.829944531481759e-05 loss: 0.1768 (0.1852) time: 2.7123 data: 0.0065 max mem: 33368 +Epoch: [1] [ 680/1319] eta: 0:28:50 lr: 4.8290883185820843e-05 loss: 0.1607 (0.1850) time: 2.7278 data: 0.0062 max mem: 33368 +Epoch: [1] [ 690/1319] eta: 0:28:23 lr: 4.828232088814377e-05 loss: 0.1816 (0.1852) time: 2.7166 data: 0.0063 max mem: 33368 +Epoch: [1] [ 700/1319] eta: 0:27:55 lr: 4.827375842174981e-05 loss: 0.1842 (0.1850) time: 2.7120 data: 0.0063 max mem: 33368 +Epoch: [1] [ 710/1319] eta: 0:27:28 lr: 4.826519578660238e-05 loss: 0.1594 (0.1849) time: 2.6999 data: 0.0065 max mem: 33368 +Epoch: [1] [ 720/1319] eta: 0:27:01 lr: 4.825663298266489e-05 loss: 0.1840 (0.1849) time: 2.6793 data: 0.0067 max mem: 33368 +Epoch: [1] [ 730/1319] eta: 0:26:34 lr: 4.824807000990074e-05 loss: 0.1740 (0.1848) time: 2.6660 data: 0.0064 max mem: 33368 +Epoch: [1] [ 740/1319] eta: 0:26:06 lr: 4.82395068682733e-05 loss: 0.1703 (0.1850) time: 2.6831 data: 0.0063 max mem: 33368 +Epoch: [1] [ 750/1319] eta: 0:25:39 lr: 4.823094355774595e-05 loss: 0.1703 (0.1851) time: 2.7075 data: 0.0063 max mem: 33368 +Epoch: [1] [ 760/1319] eta: 0:25:12 lr: 4.822238007828201e-05 loss: 0.1748 (0.1850) time: 2.7189 data: 0.0063 max mem: 33368 +Epoch: [1] [ 770/1319] eta: 0:24:45 lr: 4.8213816429844826e-05 loss: 0.1763 (0.1850) time: 2.6898 data: 0.0065 max mem: 33368 +Epoch: [1] [ 780/1319] eta: 0:24:18 lr: 4.8205252612397726e-05 loss: 0.1660 (0.1846) time: 2.7053 data: 0.0064 max mem: 33368 +Epoch: [1] [ 790/1319] eta: 0:23:51 lr: 4.8196688625903984e-05 loss: 0.1632 (0.1846) time: 2.7082 data: 0.0064 max mem: 33368 +Epoch: [1] [ 800/1319] eta: 0:23:24 lr: 4.8188124470326915e-05 loss: 0.1529 (0.1844) time: 2.7025 data: 0.0065 max mem: 33368 +Epoch: [1] [ 810/1319] eta: 0:22:57 lr: 4.8179560145629784e-05 loss: 0.1691 (0.1847) time: 2.7183 data: 0.0064 max mem: 33368 +Epoch: [1] [ 820/1319] eta: 0:22:30 lr: 4.817099565177583e-05 loss: 0.1922 (0.1847) time: 2.7250 data: 0.0062 max mem: 33368 +Epoch: [1] [ 830/1319] eta: 0:22:03 lr: 4.8162430988728305e-05 loss: 0.1880 (0.1849) time: 2.7205 data: 0.0064 max mem: 33368 +Epoch: [1] [ 840/1319] eta: 0:21:36 lr: 4.815386615645044e-05 loss: 0.1652 (0.1845) time: 2.6926 data: 0.0067 max mem: 33368 +Epoch: [1] [ 850/1319] eta: 0:21:09 lr: 4.814530115490545e-05 loss: 0.1612 (0.1844) time: 2.6869 data: 0.0066 max mem: 33368 +Epoch: [1] [ 860/1319] eta: 0:20:41 lr: 4.813673598405651e-05 loss: 0.1612 (0.1842) time: 2.6735 data: 0.0066 max mem: 33368 +Epoch: [1] [ 870/1319] eta: 0:20:14 lr: 4.812817064386682e-05 loss: 0.1560 (0.1840) time: 2.6745 data: 0.0065 max mem: 33368 +Epoch: [1] [ 880/1319] eta: 0:19:48 lr: 4.8119605134299526e-05 loss: 0.1600 (0.1838) time: 2.7281 data: 0.0064 max mem: 33368 +Epoch: [1] [ 890/1319] eta: 0:19:21 lr: 4.81110394553178e-05 loss: 0.1547 (0.1837) time: 2.7515 data: 0.0065 max mem: 33368 +Epoch: [1] [ 900/1319] eta: 0:18:54 lr: 4.810247360688475e-05 loss: 0.1547 (0.1835) time: 2.7297 data: 0.0063 max mem: 33368 +Epoch: [1] [ 910/1319] eta: 0:18:26 lr: 4.809390758896352e-05 loss: 0.1423 (0.1832) time: 2.6973 data: 0.0062 max mem: 33368 +Epoch: [1] [ 920/1319] eta: 0:17:59 lr: 4.808534140151719e-05 loss: 0.1549 (0.1832) time: 2.7045 data: 0.0063 max mem: 33368 +Epoch: [1] [ 930/1319] eta: 0:17:32 lr: 4.807677504450886e-05 loss: 0.1556 (0.1831) time: 2.7321 data: 0.0064 max mem: 33368 +Epoch: [1] [ 940/1319] eta: 0:17:06 lr: 4.806820851790161e-05 loss: 0.1565 (0.1831) time: 2.7348 data: 0.0064 max mem: 33368 +Epoch: [1] [ 950/1319] eta: 0:16:39 lr: 4.805964182165848e-05 loss: 0.1660 (0.1830) time: 2.7300 data: 0.0064 max mem: 33368 +Epoch: [1] [ 960/1319] eta: 0:16:11 lr: 4.8051074955742525e-05 loss: 0.1604 (0.1828) time: 2.6845 data: 0.0065 max mem: 33368 +Epoch: [1] [ 970/1319] eta: 0:15:44 lr: 4.804250792011677e-05 loss: 0.1742 (0.1828) time: 2.6601 data: 0.0066 max mem: 33368 +Epoch: [1] [ 980/1319] eta: 0:15:17 lr: 4.803394071474422e-05 loss: 0.1742 (0.1828) time: 2.6931 data: 0.0063 max mem: 33368 +Epoch: [1] [ 990/1319] eta: 0:14:50 lr: 4.802537333958788e-05 loss: 0.1568 (0.1827) time: 2.7260 data: 0.0062 max mem: 33368 +Epoch: [1] [1000/1319] eta: 0:14:23 lr: 4.801680579461071e-05 loss: 0.1687 (0.1829) time: 2.7457 data: 0.0064 max mem: 33368 +Epoch: [1] [1010/1319] eta: 0:13:56 lr: 4.80082380797757e-05 loss: 0.1810 (0.1828) time: 2.7357 data: 0.0063 max mem: 33368 +Epoch: [1] [1020/1319] eta: 0:13:29 lr: 4.79996701950458e-05 loss: 0.1845 (0.1832) time: 2.7412 data: 0.0063 max mem: 33368 +Epoch: [1] [1030/1319] eta: 0:13:02 lr: 4.799110214038392e-05 loss: 0.2017 (0.1833) time: 2.7353 data: 0.0064 max mem: 33368 +Epoch: [1] [1040/1319] eta: 0:12:35 lr: 4.7982533915752995e-05 loss: 0.1933 (0.1833) time: 2.6730 data: 0.0065 max mem: 33368 +Epoch: [1] [1050/1319] eta: 0:12:08 lr: 4.797396552111593e-05 loss: 0.1728 (0.1833) time: 2.6702 data: 0.0067 max mem: 33368 +Epoch: [1] [1060/1319] eta: 0:11:41 lr: 4.7965396956435596e-05 loss: 0.1573 (0.1831) time: 2.6858 data: 0.0068 max mem: 33368 +Epoch: [1] [1070/1319] eta: 0:11:13 lr: 4.795682822167489e-05 loss: 0.1603 (0.1831) time: 2.6727 data: 0.0068 max mem: 33368 +Epoch: [1] [1080/1319] eta: 0:10:46 lr: 4.794825931679665e-05 loss: 0.1896 (0.1832) time: 2.6400 data: 0.0069 max mem: 33368 +Epoch: [1] [1090/1319] eta: 0:10:19 lr: 4.7939690241763725e-05 loss: 0.1734 (0.1829) time: 2.6275 data: 0.0069 max mem: 33368 +Epoch: [1] [1100/1319] eta: 0:09:52 lr: 4.793112099653894e-05 loss: 0.1578 (0.1829) time: 2.6518 data: 0.0067 max mem: 33368 +Epoch: [1] [1110/1319] eta: 0:09:25 lr: 4.79225515810851e-05 loss: 0.1565 (0.1830) time: 2.6734 data: 0.0067 max mem: 33368 +Epoch: [1] [1120/1319] eta: 0:08:58 lr: 4.791398199536501e-05 loss: 0.1682 (0.1830) time: 2.6789 data: 0.0067 max mem: 33368 +Epoch: [1] [1130/1319] eta: 0:08:31 lr: 4.790541223934144e-05 loss: 0.1809 (0.1832) time: 2.6811 data: 0.0066 max mem: 33368 +Epoch: [1] [1140/1319] eta: 0:08:03 lr: 4.7896842312977156e-05 loss: 0.1932 (0.1833) time: 2.6766 data: 0.0065 max mem: 33368 +Epoch: [1] [1150/1319] eta: 0:07:36 lr: 4.788827221623491e-05 loss: 0.1841 (0.1831) time: 2.6805 data: 0.0067 max mem: 33368 +Epoch: [1] [1160/1319] eta: 0:07:09 lr: 4.787970194907743e-05 loss: 0.1801 (0.1832) time: 2.6687 data: 0.0072 max mem: 33368 +Epoch: [1] [1170/1319] eta: 0:06:42 lr: 4.787113151146744e-05 loss: 0.1748 (0.1831) time: 2.6480 data: 0.0071 max mem: 33368 +Epoch: [1] [1180/1319] eta: 0:06:15 lr: 4.786256090336764e-05 loss: 0.1682 (0.1830) time: 2.6877 data: 0.0066 max mem: 33368 +Epoch: [1] [1190/1319] eta: 0:05:48 lr: 4.7853990124740705e-05 loss: 0.1679 (0.1828) time: 2.7403 data: 0.0065 max mem: 33368 +Epoch: [1] [1200/1319] eta: 0:05:21 lr: 4.784541917554932e-05 loss: 0.1693 (0.1828) time: 2.7536 data: 0.0064 max mem: 33368 +Epoch: [1] [1210/1319] eta: 0:04:54 lr: 4.783684805575612e-05 loss: 0.1712 (0.1827) time: 2.7396 data: 0.0064 max mem: 33368 +Epoch: [1] [1220/1319] eta: 0:04:27 lr: 4.782827676532376e-05 loss: 0.1712 (0.1826) time: 2.7133 data: 0.0064 max mem: 33368 +Epoch: [1] [1230/1319] eta: 0:04:00 lr: 4.781970530421487e-05 loss: 0.1849 (0.1827) time: 2.7265 data: 0.0064 max mem: 33368 +Epoch: [1] [1240/1319] eta: 0:03:33 lr: 4.7811133672392044e-05 loss: 0.1582 (0.1824) time: 2.7497 data: 0.0065 max mem: 33368 +Epoch: [1] [1250/1319] eta: 0:03:06 lr: 4.780256186981787e-05 loss: 0.1526 (0.1823) time: 2.7037 data: 0.0064 max mem: 33368 +Epoch: [1] [1260/1319] eta: 0:02:39 lr: 4.779398989645494e-05 loss: 0.1670 (0.1823) time: 2.7041 data: 0.0063 max mem: 33368 +Epoch: [1] [1270/1319] eta: 0:02:12 lr: 4.778541775226581e-05 loss: 0.1658 (0.1822) time: 2.7448 data: 0.0064 max mem: 33368 +Epoch: [1] [1280/1319] eta: 0:01:45 lr: 4.777684543721302e-05 loss: 0.1566 (0.1822) time: 2.7474 data: 0.0064 max mem: 33368 +Epoch: [1] [1290/1319] eta: 0:01:18 lr: 4.776827295125911e-05 loss: 0.1483 (0.1820) time: 2.7515 data: 0.0063 max mem: 33368 +Epoch: [1] [1300/1319] eta: 0:00:51 lr: 4.775970029436657e-05 loss: 0.1503 (0.1818) time: 2.7427 data: 0.0064 max mem: 33368 +Epoch: [1] [1310/1319] eta: 0:00:24 lr: 4.7751127466497925e-05 loss: 0.1634 (0.1818) time: 2.7223 data: 0.0064 max mem: 33368 +Epoch: [1] Total time: 0:59:29 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 2:01:17 time: 2.8283 data: 2.7437 max mem: 33368 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 100/2573] eta: 0:04:06 time: 0.0715 data: 0.0011 max mem: 33368 +Test: [ 200/2573] eta: 0:03:26 time: 0.0735 data: 0.0012 max mem: 33368 +Test: [ 300/2573] eta: 0:03:06 time: 0.0752 data: 0.0012 max mem: 33368 +Test: [ 400/2573] eta: 0:02:53 time: 0.0754 data: 0.0011 max mem: 33368 +Test: [ 500/2573] eta: 0:02:43 time: 0.0738 data: 0.0012 max mem: 33368 +Test: [ 600/2573] eta: 0:02:33 time: 0.0740 data: 0.0012 max mem: 33368 +Test: [ 700/2573] eta: 0:02:25 time: 0.0738 data: 0.0011 max mem: 33368 +Test: [ 800/2573] eta: 0:02:17 time: 0.0774 data: 0.0011 max mem: 33368 +Test: [ 900/2573] eta: 0:02:08 time: 0.0738 data: 0.0012 max mem: 33368 +Test: [1000/2573] eta: 0:02:00 time: 0.0739 data: 0.0012 max mem: 33368 +Test: [1100/2573] eta: 0:01:52 time: 0.0741 data: 0.0012 max mem: 33368 +Test: [1200/2573] eta: 0:01:44 time: 0.0742 data: 0.0011 max mem: 33368 +Test: [1300/2573] eta: 0:01:37 time: 0.0740 data: 0.0011 max mem: 33368 +Test: [1400/2573] eta: 0:01:29 time: 0.0724 data: 0.0012 max mem: 33368 +Test: [1500/2573] eta: 0:01:21 time: 0.0741 data: 0.0012 max mem: 33368 +Test: [1600/2573] eta: 0:01:13 time: 0.0777 data: 0.0012 max mem: 33368 +Test: [1700/2573] eta: 0:01:06 time: 0.0727 data: 0.0011 max mem: 33368 +Test: [1800/2573] eta: 0:00:58 time: 0.0758 data: 0.0012 max mem: 33368 +Test: [1900/2573] eta: 0:00:50 time: 0.0726 data: 0.0012 max mem: 33368 +Test: [2000/2573] eta: 0:00:43 time: 0.0742 data: 0.0011 max mem: 33368 +Test: [2100/2573] eta: 0:00:35 time: 0.0759 data: 0.0011 max mem: 33368 +Test: [2200/2573] eta: 0:00:28 time: 0.0761 data: 0.0011 max mem: 33368 +Test: [2300/2573] eta: 0:00:20 time: 0.0760 data: 0.0012 max mem: 33368 +Test: [2400/2573] eta: 0:00:13 time: 0.0708 data: 0.0012 max mem: 33368 +Test: [2500/2573] eta: 0:00:05 time: 0.0742 data: 0.0012 max mem: 33368 +Test: Total time: 0:03:13 +Final results: +Mean IoU is 43.57 + + precision@0.5 = 43.46 + precision@0.6 = 32.25 + precision@0.7 = 23.06 + precision@0.8 = 13.60 + precision@0.9 = 3.51 + overall IoU = 45.70 + +Average object IoU 43.57060302872509 +Overall IoU 45.70063400268555 +Better epoch: 1 + +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [2] [ 0/1319] eta: 1:27:15 lr: 4.774341177520056e-05 loss: 0.0942 (0.0942) time: 3.9696 data: 1.2562 max mem: 33368 +Epoch: [2] [ 10/1319] eta: 1:01:43 lr: 4.773483862237391e-05 loss: 0.1661 (0.1787) time: 2.8291 data: 0.1198 max mem: 33368 +Epoch: [2] [ 20/1319] eta: 0:59:54 lr: 4.772626529846231e-05 loss: 0.1661 (0.1691) time: 2.7066 data: 0.0060 max mem: 33368 +Epoch: [2] [ 30/1319] eta: 0:59:08 lr: 4.771769180342819e-05 loss: 0.1353 (0.1645) time: 2.7106 data: 0.0062 max mem: 33368 +Epoch: [2] [ 40/1319] eta: 0:58:36 lr: 4.7709118137233964e-05 loss: 0.1500 (0.1683) time: 2.7319 data: 0.0065 max mem: 33368 +Epoch: [2] [ 50/1319] eta: 0:58:02 lr: 4.770054429984204e-05 loss: 0.1742 (0.1678) time: 2.7322 data: 0.0065 max mem: 33368 +Epoch: [2] [ 60/1319] eta: 0:57:20 lr: 4.769197029121481e-05 loss: 0.1540 (0.1640) time: 2.6981 data: 0.0066 max mem: 33368 +Epoch: [2] [ 70/1319] eta: 0:56:53 lr: 4.7683396111314645e-05 loss: 0.1655 (0.1697) time: 2.7037 data: 0.0066 max mem: 33368 +Epoch: [2] [ 80/1319] eta: 0:56:21 lr: 4.7674821760103904e-05 loss: 0.1678 (0.1675) time: 2.7168 data: 0.0065 max mem: 33368 +Epoch: [2] [ 90/1319] eta: 0:55:53 lr: 4.766624723754494e-05 loss: 0.1431 (0.1655) time: 2.7129 data: 0.0065 max mem: 33368 +Epoch: [2] [ 100/1319] eta: 0:55:26 lr: 4.7657672543600056e-05 loss: 0.1596 (0.1664) time: 2.7303 data: 0.0066 max mem: 33368 +Epoch: [2] [ 110/1319] eta: 0:55:02 lr: 4.764909767823158e-05 loss: 0.1706 (0.1664) time: 2.7466 data: 0.0067 max mem: 33368 +Epoch: [2] [ 120/1319] eta: 0:54:33 lr: 4.76405226414018e-05 loss: 0.1625 (0.1658) time: 2.7367 data: 0.0065 max mem: 33368 +Epoch: [2] [ 130/1319] eta: 0:54:09 lr: 4.7631947433073e-05 loss: 0.1449 (0.1647) time: 2.7401 data: 0.0065 max mem: 33368 +Epoch: [2] [ 140/1319] eta: 0:53:39 lr: 4.762337205320744e-05 loss: 0.1532 (0.1644) time: 2.7332 data: 0.0065 max mem: 33368 +Epoch: [2] [ 150/1319] eta: 0:53:08 lr: 4.7614796501767376e-05 loss: 0.1532 (0.1638) time: 2.6930 data: 0.0066 max mem: 33368 +Epoch: [2] [ 160/1319] eta: 0:52:39 lr: 4.760622077871502e-05 loss: 0.1609 (0.1640) time: 2.6938 data: 0.0066 max mem: 33368 +Epoch: [2] [ 170/1319] eta: 0:52:11 lr: 4.75976448840126e-05 loss: 0.1487 (0.1634) time: 2.7053 data: 0.0065 max mem: 33368 +Epoch: [2] [ 180/1319] eta: 0:51:41 lr: 4.7589068817622304e-05 loss: 0.1463 (0.1624) time: 2.6941 data: 0.0064 max mem: 33368 +Epoch: [2] [ 190/1319] eta: 0:51:15 lr: 4.758049257950633e-05 loss: 0.1463 (0.1628) time: 2.7161 data: 0.0064 max mem: 33368 +Epoch: [2] [ 200/1319] eta: 0:50:49 lr: 4.757191616962685e-05 loss: 0.1466 (0.1629) time: 2.7484 data: 0.0064 max mem: 33368 +Epoch: [2] [ 210/1319] eta: 0:50:21 lr: 4.756333958794601e-05 loss: 0.1491 (0.1624) time: 2.7257 data: 0.0065 max mem: 33368 +Epoch: [2] [ 220/1319] eta: 0:49:51 lr: 4.7554762834425936e-05 loss: 0.1538 (0.1620) time: 2.6943 data: 0.0064 max mem: 33368 +Epoch: [2] [ 230/1319] eta: 0:49:26 lr: 4.7546185909028754e-05 loss: 0.1549 (0.1635) time: 2.7223 data: 0.0064 max mem: 33368 +Epoch: [2] [ 240/1319] eta: 0:49:02 lr: 4.753760881171657e-05 loss: 0.1786 (0.1636) time: 2.7758 data: 0.0064 max mem: 33368 +Epoch: [2] [ 250/1319] eta: 0:48:33 lr: 4.7529031542451477e-05 loss: 0.1658 (0.1645) time: 2.7361 data: 0.0066 max mem: 33368 +Epoch: [2] [ 260/1319] eta: 0:48:07 lr: 4.7520454101195535e-05 loss: 0.1658 (0.1648) time: 2.7281 data: 0.0067 max mem: 33368 +Epoch: [2] [ 270/1319] eta: 0:47:40 lr: 4.751187648791081e-05 loss: 0.1631 (0.1649) time: 2.7480 data: 0.0065 max mem: 33368 +Epoch: [2] [ 280/1319] eta: 0:47:11 lr: 4.7503298702559326e-05 loss: 0.1584 (0.1647) time: 2.7034 data: 0.0064 max mem: 33368 +Epoch: [2] [ 290/1319] eta: 0:46:42 lr: 4.7494720745103136e-05 loss: 0.1496 (0.1654) time: 2.6784 data: 0.0065 max mem: 33368 +Epoch: [2] [ 300/1319] eta: 0:46:15 lr: 4.748614261550422e-05 loss: 0.1415 (0.1648) time: 2.7075 data: 0.0066 max mem: 33368 +Epoch: [2] [ 310/1319] eta: 0:45:49 lr: 4.7477564313724594e-05 loss: 0.1415 (0.1647) time: 2.7429 data: 0.0064 max mem: 33368 +Epoch: [2] [ 320/1319] eta: 0:45:22 lr: 4.746898583972622e-05 loss: 0.1649 (0.1658) time: 2.7475 data: 0.0064 max mem: 33368 +Epoch: [2] [ 330/1319] eta: 0:44:56 lr: 4.746040719347105e-05 loss: 0.1542 (0.1653) time: 2.7593 data: 0.0063 max mem: 33368 +Epoch: [2] [ 340/1319] eta: 0:44:28 lr: 4.745182837492104e-05 loss: 0.1538 (0.1657) time: 2.7324 data: 0.0064 max mem: 33368 +Epoch: [2] [ 350/1319] eta: 0:44:01 lr: 4.744324938403812e-05 loss: 0.1675 (0.1661) time: 2.7123 data: 0.0064 max mem: 33368 +Epoch: [2] [ 360/1319] eta: 0:43:34 lr: 4.7434670220784206e-05 loss: 0.1564 (0.1655) time: 2.7247 data: 0.0062 max mem: 33368 +Epoch: [2] [ 370/1319] eta: 0:43:05 lr: 4.7426090885121175e-05 loss: 0.1486 (0.1652) time: 2.6968 data: 0.0063 max mem: 33368 +Epoch: [2] [ 380/1319] eta: 0:42:38 lr: 4.741751137701092e-05 loss: 0.1550 (0.1652) time: 2.6949 data: 0.0065 max mem: 33368 +Epoch: [2] [ 390/1319] eta: 0:42:11 lr: 4.74089316964153e-05 loss: 0.1725 (0.1659) time: 2.7282 data: 0.0064 max mem: 33368 +Epoch: [2] [ 400/1319] eta: 0:41:44 lr: 4.740035184329618e-05 loss: 0.1700 (0.1661) time: 2.7521 data: 0.0062 max mem: 33368 +Epoch: [2] [ 410/1319] eta: 0:41:17 lr: 4.739177181761536e-05 loss: 0.1566 (0.1657) time: 2.7344 data: 0.0064 max mem: 33368 +Epoch: [2] [ 420/1319] eta: 0:40:48 lr: 4.738319161933468e-05 loss: 0.1559 (0.1657) time: 2.6855 data: 0.0065 max mem: 33368 +Epoch: [2] [ 430/1319] eta: 0:40:20 lr: 4.737461124841593e-05 loss: 0.1529 (0.1653) time: 2.6629 data: 0.0066 max mem: 33368 +Epoch: [2] [ 440/1319] eta: 0:39:52 lr: 4.736603070482089e-05 loss: 0.1387 (0.1648) time: 2.6785 data: 0.0067 max mem: 33368 +Epoch: [2] [ 450/1319] eta: 0:39:24 lr: 4.735744998851133e-05 loss: 0.1387 (0.1641) time: 2.6867 data: 0.0066 max mem: 33368 +Epoch: [2] [ 460/1319] eta: 0:38:57 lr: 4.734886909944901e-05 loss: 0.1461 (0.1642) time: 2.7030 data: 0.0063 max mem: 33368 +Epoch: [2] [ 470/1319] eta: 0:38:30 lr: 4.734028803759565e-05 loss: 0.1448 (0.1640) time: 2.7508 data: 0.0063 max mem: 33368 +Epoch: [2] [ 480/1319] eta: 0:38:04 lr: 4.733170680291298e-05 loss: 0.1490 (0.1638) time: 2.7604 data: 0.0065 max mem: 33368 +Epoch: [2] [ 490/1319] eta: 0:37:36 lr: 4.7323125395362694e-05 loss: 0.1446 (0.1633) time: 2.7313 data: 0.0064 max mem: 33368 +Epoch: [2] [ 500/1319] eta: 0:37:09 lr: 4.731454381490648e-05 loss: 0.1446 (0.1635) time: 2.7129 data: 0.0064 max mem: 33368 +Epoch: [2] [ 510/1319] eta: 0:36:42 lr: 4.730596206150601e-05 loss: 0.1572 (0.1632) time: 2.7193 data: 0.0065 max mem: 33368 +Epoch: [2] [ 520/1319] eta: 0:36:14 lr: 4.729738013512294e-05 loss: 0.1403 (0.1631) time: 2.7174 data: 0.0065 max mem: 33368 +Epoch: [2] [ 530/1319] eta: 0:35:47 lr: 4.72887980357189e-05 loss: 0.1508 (0.1630) time: 2.7205 data: 0.0065 max mem: 33368 +Epoch: [2] [ 540/1319] eta: 0:35:20 lr: 4.7280215763255517e-05 loss: 0.1527 (0.1630) time: 2.7287 data: 0.0065 max mem: 33368 +Epoch: [2] [ 550/1319] eta: 0:34:53 lr: 4.7271633317694384e-05 loss: 0.1562 (0.1630) time: 2.7361 data: 0.0065 max mem: 33368 +Epoch: [2] [ 560/1319] eta: 0:34:25 lr: 4.726305069899711e-05 loss: 0.1524 (0.1637) time: 2.7094 data: 0.0065 max mem: 33368 +Epoch: [2] [ 570/1319] eta: 0:33:58 lr: 4.725446790712525e-05 loss: 0.1619 (0.1638) time: 2.7085 data: 0.0065 max mem: 33368 +Epoch: [2] [ 580/1319] eta: 0:33:31 lr: 4.7245884942040375e-05 loss: 0.1666 (0.1638) time: 2.7166 data: 0.0064 max mem: 33368 +Epoch: [2] [ 590/1319] eta: 0:33:03 lr: 4.7237301803704005e-05 loss: 0.1622 (0.1637) time: 2.7021 data: 0.0062 max mem: 33368 +Epoch: [2] [ 600/1319] eta: 0:32:36 lr: 4.722871849207768e-05 loss: 0.1412 (0.1633) time: 2.6999 data: 0.0063 max mem: 33368 +Epoch: [2] [ 610/1319] eta: 0:32:09 lr: 4.72201350071229e-05 loss: 0.1475 (0.1634) time: 2.7016 data: 0.0065 max mem: 33368 +Epoch: [2] [ 620/1319] eta: 0:31:42 lr: 4.7211551348801154e-05 loss: 0.1580 (0.1634) time: 2.7296 data: 0.0065 max mem: 33368 +Epoch: [2] [ 630/1319] eta: 0:31:14 lr: 4.7202967517073924e-05 loss: 0.1485 (0.1637) time: 2.7014 data: 0.0065 max mem: 33368 +Epoch: [2] [ 640/1319] eta: 0:30:47 lr: 4.719438351190267e-05 loss: 0.1355 (0.1634) time: 2.7033 data: 0.0067 max mem: 33368 +Epoch: [2] [ 650/1319] eta: 0:30:20 lr: 4.718579933324881e-05 loss: 0.1431 (0.1634) time: 2.7470 data: 0.0065 max mem: 33368 +Epoch: [2] [ 660/1319] eta: 0:29:53 lr: 4.71772149810738e-05 loss: 0.1533 (0.1637) time: 2.7398 data: 0.0062 max mem: 33368 +Epoch: [2] [ 670/1319] eta: 0:29:25 lr: 4.716863045533903e-05 loss: 0.1582 (0.1637) time: 2.7106 data: 0.0064 max mem: 33368 +Epoch: [2] [ 680/1319] eta: 0:28:58 lr: 4.71600457560059e-05 loss: 0.1514 (0.1636) time: 2.6868 data: 0.0067 max mem: 33368 +Epoch: [2] [ 690/1319] eta: 0:28:30 lr: 4.7151460883035786e-05 loss: 0.1514 (0.1640) time: 2.6982 data: 0.0068 max mem: 33368 +Epoch: [2] [ 700/1319] eta: 0:28:03 lr: 4.714287583639004e-05 loss: 0.1498 (0.1636) time: 2.7037 data: 0.0067 max mem: 33368 +Epoch: [2] [ 710/1319] eta: 0:27:36 lr: 4.713429061603002e-05 loss: 0.1350 (0.1637) time: 2.7294 data: 0.0067 max mem: 33368 +Epoch: [2] [ 720/1319] eta: 0:27:09 lr: 4.712570522191704e-05 loss: 0.1478 (0.1634) time: 2.7203 data: 0.0065 max mem: 33368 +Epoch: [2] [ 730/1319] eta: 0:26:41 lr: 4.7117119654012416e-05 loss: 0.1370 (0.1631) time: 2.6671 data: 0.0065 max mem: 33368 +Epoch: [2] [ 740/1319] eta: 0:26:14 lr: 4.7108533912277444e-05 loss: 0.1436 (0.1630) time: 2.6902 data: 0.0069 max mem: 33368 +Epoch: [2] [ 750/1319] eta: 0:25:46 lr: 4.709994799667339e-05 loss: 0.1572 (0.1634) time: 2.7066 data: 0.0068 max mem: 33368 +Epoch: [2] [ 760/1319] eta: 0:25:19 lr: 4.709136190716153e-05 loss: 0.1572 (0.1633) time: 2.6962 data: 0.0067 max mem: 33368 +Epoch: [2] [ 770/1319] eta: 0:24:52 lr: 4.708277564370309e-05 loss: 0.1477 (0.1631) time: 2.6908 data: 0.0067 max mem: 33368 +Epoch: [2] [ 780/1319] eta: 0:24:24 lr: 4.707418920625932e-05 loss: 0.1445 (0.1630) time: 2.6687 data: 0.0068 max mem: 33368 +Epoch: [2] [ 790/1319] eta: 0:23:56 lr: 4.706560259479142e-05 loss: 0.1461 (0.1630) time: 2.6445 data: 0.0069 max mem: 33368 +Epoch: [2] [ 800/1319] eta: 0:23:29 lr: 4.705701580926059e-05 loss: 0.1710 (0.1635) time: 2.6409 data: 0.0068 max mem: 33368 +Epoch: [2] [ 810/1319] eta: 0:23:01 lr: 4.7048428849628004e-05 loss: 0.1810 (0.1638) time: 2.6574 data: 0.0066 max mem: 33368 +Epoch: [2] [ 820/1319] eta: 0:22:34 lr: 4.703984171585482e-05 loss: 0.1406 (0.1636) time: 2.6734 data: 0.0068 max mem: 33368 +Epoch: [2] [ 830/1319] eta: 0:22:06 lr: 4.703125440790219e-05 loss: 0.1390 (0.1637) time: 2.6732 data: 0.0069 max mem: 33368 +Epoch: [2] [ 840/1319] eta: 0:21:39 lr: 4.702266692573125e-05 loss: 0.1747 (0.1638) time: 2.6938 data: 0.0068 max mem: 33368 +Epoch: [2] [ 850/1319] eta: 0:21:12 lr: 4.70140792693031e-05 loss: 0.1468 (0.1638) time: 2.6972 data: 0.0067 max mem: 33368 +Epoch: [2] [ 860/1319] eta: 0:20:45 lr: 4.700549143857884e-05 loss: 0.1613 (0.1640) time: 2.6681 data: 0.0068 max mem: 33368 +Epoch: [2] [ 870/1319] eta: 0:20:17 lr: 4.699690343351954e-05 loss: 0.1630 (0.1640) time: 2.6780 data: 0.0067 max mem: 33368 +Epoch: [2] [ 880/1319] eta: 0:19:50 lr: 4.698831525408628e-05 loss: 0.1536 (0.1641) time: 2.7237 data: 0.0065 max mem: 33368 +Epoch: [2] [ 890/1319] eta: 0:19:23 lr: 4.697972690024009e-05 loss: 0.1532 (0.1642) time: 2.7243 data: 0.0065 max mem: 33368 +Epoch: [2] [ 900/1319] eta: 0:18:56 lr: 4.6971138371942025e-05 loss: 0.1415 (0.1640) time: 2.7098 data: 0.0063 max mem: 33368 +Epoch: [2] [ 910/1319] eta: 0:18:29 lr: 4.696254966915307e-05 loss: 0.1560 (0.1640) time: 2.7238 data: 0.0063 max mem: 33368 +Epoch: [2] [ 920/1319] eta: 0:18:02 lr: 4.695396079183423e-05 loss: 0.1566 (0.1640) time: 2.7392 data: 0.0066 max mem: 33368 +Epoch: [2] [ 930/1319] eta: 0:17:35 lr: 4.694537173994649e-05 loss: 0.1581 (0.1640) time: 2.7285 data: 0.0067 max mem: 33368 +Epoch: [2] [ 940/1319] eta: 0:17:08 lr: 4.69367825134508e-05 loss: 0.1553 (0.1639) time: 2.6965 data: 0.0069 max mem: 33368 +Epoch: [2] [ 950/1319] eta: 0:16:41 lr: 4.692819311230812e-05 loss: 0.1553 (0.1639) time: 2.6929 data: 0.0070 max mem: 33368 +Epoch: [2] [ 960/1319] eta: 0:16:13 lr: 4.6919603536479375e-05 loss: 0.1646 (0.1641) time: 2.6978 data: 0.0068 max mem: 33368 +Epoch: [2] [ 970/1319] eta: 0:15:46 lr: 4.691101378592547e-05 loss: 0.1633 (0.1641) time: 2.7136 data: 0.0067 max mem: 33368 +Epoch: [2] [ 980/1319] eta: 0:15:19 lr: 4.690242386060732e-05 loss: 0.1540 (0.1639) time: 2.7385 data: 0.0065 max mem: 33368 +Epoch: [2] [ 990/1319] eta: 0:14:52 lr: 4.6893833760485775e-05 loss: 0.1353 (0.1637) time: 2.7243 data: 0.0066 max mem: 33368 +Epoch: [2] [1000/1319] eta: 0:14:25 lr: 4.688524348552173e-05 loss: 0.1390 (0.1636) time: 2.7184 data: 0.0066 max mem: 33368 +Epoch: [2] [1010/1319] eta: 0:13:58 lr: 4.6876653035676014e-05 loss: 0.1541 (0.1636) time: 2.7136 data: 0.0067 max mem: 33368 +Epoch: [2] [1020/1319] eta: 0:13:31 lr: 4.6868062410909454e-05 loss: 0.1611 (0.1637) time: 2.7154 data: 0.0065 max mem: 33368 +Epoch: [2] [1030/1319] eta: 0:13:04 lr: 4.685947161118287e-05 loss: 0.1384 (0.1635) time: 2.7243 data: 0.0064 max mem: 33368 +Epoch: [2] [1040/1319] eta: 0:12:37 lr: 4.685088063645705e-05 loss: 0.1384 (0.1634) time: 2.7322 data: 0.0066 max mem: 33368 +Epoch: [2] [1050/1319] eta: 0:12:09 lr: 4.684228948669277e-05 loss: 0.1418 (0.1633) time: 2.7374 data: 0.0069 max mem: 33368 +Epoch: [2] [1060/1319] eta: 0:11:42 lr: 4.683369816185082e-05 loss: 0.1171 (0.1628) time: 2.7119 data: 0.0067 max mem: 33368 +Epoch: [2] [1070/1319] eta: 0:11:15 lr: 4.682510666189191e-05 loss: 0.1065 (0.1626) time: 2.6980 data: 0.0066 max mem: 33368 +Epoch: [2] [1080/1319] eta: 0:10:48 lr: 4.681651498677679e-05 loss: 0.1466 (0.1627) time: 2.7152 data: 0.0067 max mem: 33368 +Epoch: [2] [1090/1319] eta: 0:10:21 lr: 4.680792313646616e-05 loss: 0.1498 (0.1626) time: 2.7319 data: 0.0065 max mem: 33368 +Epoch: [2] [1100/1319] eta: 0:09:54 lr: 4.679933111092072e-05 loss: 0.1498 (0.1626) time: 2.7424 data: 0.0065 max mem: 33368 +Epoch: [2] [1110/1319] eta: 0:09:27 lr: 4.6790738910101147e-05 loss: 0.1739 (0.1628) time: 2.7555 data: 0.0064 max mem: 33368 +Epoch: [2] [1120/1319] eta: 0:09:00 lr: 4.67821465339681e-05 loss: 0.1724 (0.1629) time: 2.7068 data: 0.0065 max mem: 33368 +Epoch: [2] [1130/1319] eta: 0:08:32 lr: 4.677355398248223e-05 loss: 0.1711 (0.1629) time: 2.6966 data: 0.0066 max mem: 33368 +Epoch: [2] [1140/1319] eta: 0:08:05 lr: 4.676496125560416e-05 loss: 0.1711 (0.1630) time: 2.7394 data: 0.0066 max mem: 33368 +Epoch: [2] [1150/1319] eta: 0:07:38 lr: 4.6756368353294506e-05 loss: 0.1235 (0.1627) time: 2.7552 data: 0.0065 max mem: 33368 +Epoch: [2] [1160/1319] eta: 0:07:11 lr: 4.6747775275513856e-05 loss: 0.1157 (0.1625) time: 2.7399 data: 0.0067 max mem: 33368 +Epoch: [2] [1170/1319] eta: 0:06:44 lr: 4.6739182022222775e-05 loss: 0.1333 (0.1624) time: 2.7155 data: 0.0066 max mem: 33368 +Epoch: [2] [1180/1319] eta: 0:06:17 lr: 4.6730588593381847e-05 loss: 0.1539 (0.1626) time: 2.6947 data: 0.0067 max mem: 33368 +Epoch: [2] [1190/1319] eta: 0:05:50 lr: 4.67219949889516e-05 loss: 0.1539 (0.1626) time: 2.6994 data: 0.0067 max mem: 33368 +Epoch: [2] [1200/1319] eta: 0:05:23 lr: 4.6713401208892564e-05 loss: 0.1420 (0.1626) time: 2.7194 data: 0.0066 max mem: 33368 +Epoch: [2] [1210/1319] eta: 0:04:55 lr: 4.6704807253165246e-05 loss: 0.1535 (0.1627) time: 2.7334 data: 0.0066 max mem: 33368 +Epoch: [2] [1220/1319] eta: 0:04:28 lr: 4.6696213121730145e-05 loss: 0.1442 (0.1628) time: 2.7422 data: 0.0063 max mem: 33368 +Epoch: [2] [1230/1319] eta: 0:04:01 lr: 4.668761881454772e-05 loss: 0.1472 (0.1628) time: 2.7373 data: 0.0064 max mem: 33368 +Epoch: [2] [1240/1319] eta: 0:03:34 lr: 4.6679024331578444e-05 loss: 0.1576 (0.1630) time: 2.7049 data: 0.0066 max mem: 33368 +Epoch: [2] [1250/1319] eta: 0:03:07 lr: 4.6670429672782765e-05 loss: 0.1576 (0.1628) time: 2.7091 data: 0.0066 max mem: 33368 +Epoch: [2] [1260/1319] eta: 0:02:40 lr: 4.6661834838121084e-05 loss: 0.1408 (0.1628) time: 2.7376 data: 0.0065 max mem: 33368 +Epoch: [2] [1270/1319] eta: 0:02:13 lr: 4.665323982755382e-05 loss: 0.1471 (0.1627) time: 2.7054 data: 0.0065 max mem: 33368 +Epoch: [2] [1280/1319] eta: 0:01:45 lr: 4.664464464104137e-05 loss: 0.1543 (0.1627) time: 2.6928 data: 0.0066 max mem: 33368 +Epoch: [2] [1290/1319] eta: 0:01:18 lr: 4.6636049278544094e-05 loss: 0.1461 (0.1627) time: 2.7239 data: 0.0064 max mem: 33368 +Epoch: [2] [1300/1319] eta: 0:00:51 lr: 4.662745374002236e-05 loss: 0.1655 (0.1628) time: 2.7468 data: 0.0064 max mem: 33368 +Epoch: [2] [1310/1319] eta: 0:00:24 lr: 4.6618858025436495e-05 loss: 0.1660 (0.1629) time: 2.7488 data: 0.0063 max mem: 33368 +Epoch: [2] Total time: 0:59:42 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 1:47:56 time: 2.5172 data: 2.4087 max mem: 33368 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 100/2573] eta: 0:03:59 time: 0.0722 data: 0.0012 max mem: 33368 +Test: [ 200/2573] eta: 0:03:23 time: 0.0733 data: 0.0011 max mem: 33368 +Test: [ 300/2573] eta: 0:03:04 time: 0.0751 data: 0.0011 max mem: 33368 +Test: [ 400/2573] eta: 0:02:52 time: 0.0753 data: 0.0011 max mem: 33368 +Test: [ 500/2573] eta: 0:02:42 time: 0.0739 data: 0.0012 max mem: 33368 +Test: [ 600/2573] eta: 0:02:33 time: 0.0740 data: 0.0012 max mem: 33368 +Test: [ 700/2573] eta: 0:02:24 time: 0.0739 data: 0.0011 max mem: 33368 +Test: [ 800/2573] eta: 0:02:16 time: 0.0775 data: 0.0011 max mem: 33368 +Test: [ 900/2573] eta: 0:02:08 time: 0.0740 data: 0.0012 max mem: 33368 +Test: [1000/2573] eta: 0:02:00 time: 0.0740 data: 0.0012 max mem: 33368 +Test: [1100/2573] eta: 0:01:52 time: 0.0741 data: 0.0012 max mem: 33368 +Test: [1200/2573] eta: 0:01:44 time: 0.0742 data: 0.0011 max mem: 33368 +Test: [1300/2573] eta: 0:01:36 time: 0.0743 data: 0.0012 max mem: 33368 +Test: [1400/2573] eta: 0:01:29 time: 0.0725 data: 0.0012 max mem: 33368 +Test: [1500/2573] eta: 0:01:21 time: 0.0740 data: 0.0012 max mem: 33368 +Test: [1600/2573] eta: 0:01:13 time: 0.0775 data: 0.0012 max mem: 33368 +Test: [1700/2573] eta: 0:01:06 time: 0.0726 data: 0.0011 max mem: 33368 +Test: [1800/2573] eta: 0:00:58 time: 0.0758 data: 0.0012 max mem: 33368 +Test: [1900/2573] eta: 0:00:50 time: 0.0726 data: 0.0012 max mem: 33368 +Test: [2000/2573] eta: 0:00:43 time: 0.0742 data: 0.0012 max mem: 33368 +Test: [2100/2573] eta: 0:00:35 time: 0.0761 data: 0.0012 max mem: 33368 +Test: [2200/2573] eta: 0:00:28 time: 0.0759 data: 0.0012 max mem: 33368 +Test: [2300/2573] eta: 0:00:20 time: 0.0759 data: 0.0012 max mem: 33368 +Test: [2400/2573] eta: 0:00:12 time: 0.0710 data: 0.0012 max mem: 33368 +Test: [2500/2573] eta: 0:00:05 time: 0.0744 data: 0.0012 max mem: 33368 +Test: Total time: 0:03:13 +Final results: +Mean IoU is 43.98 + + precision@0.5 = 47.20 + precision@0.6 = 38.54 + precision@0.7 = 29.70 + precision@0.8 = 18.53 + precision@0.9 = 5.88 + overall IoU = 47.37 + +Average object IoU 43.97673574291625 +Overall IoU 47.37043762207031 +Better epoch: 2 + +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [3] [ 0/1319] eta: 1:31:50 lr: 4.661112173174161e-05 loss: 0.1019 (0.1019) time: 4.1775 data: 1.4582 max mem: 33368 +Epoch: [3] [ 10/1319] eta: 1:01:36 lr: 4.660252568252458e-05 loss: 0.1338 (0.1314) time: 2.8241 data: 0.1385 max mem: 33368 +Epoch: [3] [ 20/1319] eta: 1:00:17 lr: 4.6593929457128314e-05 loss: 0.1335 (0.1315) time: 2.7151 data: 0.0062 max mem: 33368 +Epoch: [3] [ 30/1319] eta: 0:59:38 lr: 4.6585333055513096e-05 loss: 0.1275 (0.1320) time: 2.7502 data: 0.0060 max mem: 33368 +Epoch: [3] [ 40/1319] eta: 0:58:50 lr: 4.657673647763916e-05 loss: 0.1465 (0.1449) time: 2.7345 data: 0.0063 max mem: 33368 +Epoch: [3] [ 50/1319] eta: 0:58:13 lr: 4.656813972346675e-05 loss: 0.1465 (0.1445) time: 2.7166 data: 0.0066 max mem: 33368 +Epoch: [3] [ 60/1319] eta: 0:57:34 lr: 4.655954279295608e-05 loss: 0.1354 (0.1452) time: 2.7094 data: 0.0066 max mem: 33368 +Epoch: [3] [ 70/1319] eta: 0:57:11 lr: 4.655094568606738e-05 loss: 0.1404 (0.1473) time: 2.7342 data: 0.0063 max mem: 33368 +Epoch: [3] [ 80/1319] eta: 0:56:46 lr: 4.6542348402760813e-05 loss: 0.1293 (0.1469) time: 2.7683 data: 0.0063 max mem: 33368 +Epoch: [3] [ 90/1319] eta: 0:56:16 lr: 4.653375094299656e-05 loss: 0.1445 (0.1478) time: 2.7465 data: 0.0065 max mem: 33368 +Epoch: [3] [ 100/1319] eta: 0:55:49 lr: 4.652515330673476e-05 loss: 0.1347 (0.1467) time: 2.7408 data: 0.0063 max mem: 33368 +Epoch: [3] [ 110/1319] eta: 0:55:17 lr: 4.651655549393556e-05 loss: 0.1199 (0.1460) time: 2.7272 data: 0.0064 max mem: 33368 +Epoch: [3] [ 120/1319] eta: 0:54:47 lr: 4.650795750455908e-05 loss: 0.1387 (0.1465) time: 2.7096 data: 0.0066 max mem: 33368 +Epoch: [3] [ 130/1319] eta: 0:54:20 lr: 4.649935933856541e-05 loss: 0.1387 (0.1465) time: 2.7356 data: 0.0064 max mem: 33368 +Epoch: [3] [ 140/1319] eta: 0:53:50 lr: 4.6490760995914644e-05 loss: 0.1254 (0.1450) time: 2.7330 data: 0.0063 max mem: 33368 +Epoch: [3] [ 150/1319] eta: 0:53:20 lr: 4.648216247656684e-05 loss: 0.1221 (0.1447) time: 2.7086 data: 0.0064 max mem: 33368 +Epoch: [3] [ 160/1319] eta: 0:52:51 lr: 4.647356378048206e-05 loss: 0.1227 (0.1441) time: 2.7091 data: 0.0066 max mem: 33368 +Epoch: [3] [ 170/1319] eta: 0:52:22 lr: 4.646496490762032e-05 loss: 0.1286 (0.1446) time: 2.7152 data: 0.0064 max mem: 33368 +Epoch: [3] [ 180/1319] eta: 0:51:54 lr: 4.645636585794164e-05 loss: 0.1488 (0.1447) time: 2.7184 data: 0.0062 max mem: 33368 +Epoch: [3] [ 190/1319] eta: 0:51:24 lr: 4.644776663140602e-05 loss: 0.1336 (0.1448) time: 2.7003 data: 0.0063 max mem: 33368 +Epoch: [3] [ 200/1319] eta: 0:50:54 lr: 4.6439167227973446e-05 loss: 0.1353 (0.1459) time: 2.6831 data: 0.0065 max mem: 33368 +Epoch: [3] [ 210/1319] eta: 0:50:23 lr: 4.643056764760387e-05 loss: 0.1431 (0.1464) time: 2.6708 data: 0.0066 max mem: 33368 +Epoch: [3] [ 220/1319] eta: 0:49:54 lr: 4.642196789025724e-05 loss: 0.1476 (0.1466) time: 2.6776 data: 0.0065 max mem: 33368 +Epoch: [3] [ 230/1319] eta: 0:49:26 lr: 4.641336795589349e-05 loss: 0.1421 (0.1463) time: 2.7053 data: 0.0065 max mem: 33368 +Epoch: [3] [ 240/1319] eta: 0:48:56 lr: 4.6404767844472526e-05 loss: 0.1375 (0.1460) time: 2.6909 data: 0.0065 max mem: 33368 +Epoch: [3] [ 250/1319] eta: 0:48:30 lr: 4.639616755595424e-05 loss: 0.1363 (0.1461) time: 2.7101 data: 0.0065 max mem: 33368 +Epoch: [3] [ 260/1319] eta: 0:48:03 lr: 4.638756709029851e-05 loss: 0.1405 (0.1466) time: 2.7367 data: 0.0064 max mem: 33368 +Epoch: [3] [ 270/1319] eta: 0:47:37 lr: 4.6378966447465196e-05 loss: 0.1578 (0.1470) time: 2.7358 data: 0.0065 max mem: 33368 +Epoch: [3] [ 280/1319] eta: 0:47:12 lr: 4.637036562741414e-05 loss: 0.1347 (0.1473) time: 2.7612 data: 0.0066 max mem: 33368 +Epoch: [3] [ 290/1319] eta: 0:46:45 lr: 4.636176463010516e-05 loss: 0.1393 (0.1477) time: 2.7554 data: 0.0066 max mem: 33368 +Epoch: [3] [ 300/1319] eta: 0:46:18 lr: 4.635316345549808e-05 loss: 0.1150 (0.1469) time: 2.7412 data: 0.0066 max mem: 33368 +Epoch: [3] [ 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+Epoch: [3] [ 390/1319] eta: 0:42:14 lr: 4.627574489897873e-05 loss: 0.1174 (0.1453) time: 2.7299 data: 0.0064 max mem: 33368 +Epoch: [3] [ 400/1319] eta: 0:41:47 lr: 4.626714194917605e-05 loss: 0.1214 (0.1449) time: 2.7378 data: 0.0062 max mem: 33368 +Epoch: [3] [ 410/1319] eta: 0:41:20 lr: 4.625853882163199e-05 loss: 0.1237 (0.1447) time: 2.7449 data: 0.0064 max mem: 33368 +Epoch: [3] [ 420/1319] eta: 0:40:51 lr: 4.624993551630613e-05 loss: 0.1310 (0.1443) time: 2.6871 data: 0.0067 max mem: 33368 +Epoch: [3] [ 430/1319] eta: 0:40:21 lr: 4.624133203315806e-05 loss: 0.1412 (0.1451) time: 2.6329 data: 0.0069 max mem: 33368 +Epoch: [3] [ 440/1319] eta: 0:39:54 lr: 4.6232728372147346e-05 loss: 0.1415 (0.1450) time: 2.6605 data: 0.0068 max mem: 33368 +Epoch: [3] [ 450/1319] eta: 0:39:25 lr: 4.6224124533233514e-05 loss: 0.1360 (0.1448) time: 2.6704 data: 0.0066 max mem: 33368 +Epoch: [3] [ 460/1319] eta: 0:38:58 lr: 4.621552051637611e-05 loss: 0.1334 (0.1448) time: 2.6970 data: 0.0066 max mem: 33368 +Epoch: [3] [ 470/1319] eta: 0:38:30 lr: 4.620691632153463e-05 loss: 0.1355 (0.1448) time: 2.7056 data: 0.0066 max mem: 33368 +Epoch: [3] [ 480/1319] eta: 0:38:01 lr: 4.619831194866858e-05 loss: 0.1346 (0.1447) time: 2.6592 data: 0.0068 max mem: 33368 +Epoch: [3] [ 490/1319] eta: 0:37:33 lr: 4.618970739773742e-05 loss: 0.1159 (0.1444) time: 2.6393 data: 0.0068 max mem: 33368 +Epoch: [3] [ 500/1319] eta: 0:37:05 lr: 4.618110266870061e-05 loss: 0.1419 (0.1447) time: 2.6540 data: 0.0069 max mem: 33368 +Epoch: [3] [ 510/1319] eta: 0:36:37 lr: 4.6172497761517596e-05 loss: 0.1518 (0.1447) time: 2.6702 data: 0.0068 max mem: 33368 +Epoch: [3] [ 520/1319] eta: 0:36:09 lr: 4.6163892676147796e-05 loss: 0.1455 (0.1451) time: 2.6595 data: 0.0067 max mem: 33368 +Epoch: [3] [ 530/1319] eta: 0:35:40 lr: 4.615528741255061e-05 loss: 0.1455 (0.1451) time: 2.6424 data: 0.0068 max mem: 33368 +Epoch: [3] [ 540/1319] eta: 0:35:13 lr: 4.6146681970685424e-05 loss: 0.1362 (0.1450) time: 2.6551 data: 0.0066 max mem: 33368 +Epoch: [3] [ 550/1319] eta: 0:34:45 lr: 4.613807635051161e-05 loss: 0.1320 (0.1451) time: 2.6767 data: 0.0068 max mem: 33368 +Epoch: [3] [ 560/1319] eta: 0:34:17 lr: 4.612947055198852e-05 loss: 0.1567 (0.1457) time: 2.6621 data: 0.0068 max mem: 33368 +Epoch: [3] [ 570/1319] eta: 0:33:50 lr: 4.612086457507548e-05 loss: 0.1707 (0.1464) time: 2.6903 data: 0.0066 max mem: 33368 +Epoch: [3] [ 580/1319] eta: 0:33:23 lr: 4.611225841973181e-05 loss: 0.1373 (0.1462) time: 2.7328 data: 0.0065 max mem: 33368 +Epoch: [3] [ 590/1319] eta: 0:32:57 lr: 4.610365208591681e-05 loss: 0.1173 (0.1462) time: 2.7558 data: 0.0067 max mem: 33368 +Epoch: [3] [ 600/1319] eta: 0:32:30 lr: 4.609504557358975e-05 loss: 0.1374 (0.1462) time: 2.7426 data: 0.0068 max mem: 33368 +Epoch: [3] [ 610/1319] eta: 0:32:03 lr: 4.60864388827099e-05 loss: 0.1427 (0.1464) time: 2.7090 data: 0.0068 max mem: 33368 +Epoch: [3] [ 620/1319] eta: 0:31:35 lr: 4.6077832013236505e-05 loss: 0.1503 (0.1464) time: 2.6738 data: 0.0073 max mem: 33368 +Epoch: [3] [ 630/1319] eta: 0:31:08 lr: 4.606922496512879e-05 loss: 0.1511 (0.1470) time: 2.6839 data: 0.0070 max mem: 33368 +Epoch: [3] [ 640/1319] eta: 0:30:41 lr: 4.606061773834596e-05 loss: 0.1422 (0.1470) time: 2.7133 data: 0.0067 max mem: 33368 +Epoch: [3] [ 650/1319] eta: 0:30:14 lr: 4.60520103328472e-05 loss: 0.1332 (0.1472) time: 2.7226 data: 0.0067 max mem: 33368 +Epoch: [3] [ 660/1319] eta: 0:29:46 lr: 4.60434027485917e-05 loss: 0.1376 (0.1472) time: 2.6942 data: 0.0067 max mem: 33368 +Epoch: [3] [ 670/1319] eta: 0:29:18 lr: 4.6034794985538615e-05 loss: 0.1374 (0.1471) time: 2.6539 data: 0.0066 max mem: 33368 +Epoch: [3] [ 680/1319] eta: 0:28:52 lr: 4.602618704364706e-05 loss: 0.1397 (0.1472) time: 2.6939 data: 0.0065 max mem: 33368 +Epoch: [3] [ 690/1319] eta: 0:28:24 lr: 4.601757892287618e-05 loss: 0.1516 (0.1474) time: 2.7120 data: 0.0067 max mem: 33368 +Epoch: [3] [ 700/1319] eta: 0:27:57 lr: 4.600897062318506e-05 loss: 0.1434 (0.1477) time: 2.7191 data: 0.0065 max mem: 33368 +Epoch: [3] [ 710/1319] eta: 0:27:30 lr: 4.600036214453279e-05 loss: 0.1440 (0.1478) time: 2.7090 data: 0.0064 max mem: 33368 +Epoch: [3] [ 720/1319] eta: 0:27:02 lr: 4.599175348687844e-05 loss: 0.1433 (0.1476) time: 2.6546 data: 0.0067 max mem: 33368 +Epoch: [3] [ 730/1319] eta: 0:26:35 lr: 4.598314465018106e-05 loss: 0.1340 (0.1476) time: 2.6639 data: 0.0065 max mem: 33368 +Epoch: [3] [ 740/1319] eta: 0:26:08 lr: 4.5974535634399665e-05 loss: 0.1340 (0.1476) time: 2.7186 data: 0.0063 max mem: 33368 +Epoch: [3] [ 750/1319] eta: 0:25:41 lr: 4.596592643949328e-05 loss: 0.1337 (0.1474) time: 2.7403 data: 0.0065 max mem: 33368 +Epoch: [3] [ 760/1319] eta: 0:25:14 lr: 4.595731706542089e-05 loss: 0.1435 (0.1475) time: 2.7054 data: 0.0067 max mem: 33368 +Epoch: [3] [ 770/1319] eta: 0:24:47 lr: 4.5948707512141485e-05 loss: 0.1469 (0.1477) time: 2.6763 data: 0.0068 max mem: 33368 +Epoch: [3] [ 780/1319] eta: 0:24:19 lr: 4.594009777961402e-05 loss: 0.1240 (0.1472) time: 2.6649 data: 0.0067 max mem: 33368 +Epoch: [3] [ 790/1319] eta: 0:23:52 lr: 4.593148786779743e-05 loss: 0.1259 (0.1478) time: 2.6622 data: 0.0064 max mem: 33368 +Epoch: [3] [ 800/1319] eta: 0:23:24 lr: 4.592287777665063e-05 loss: 0.1441 (0.1477) time: 2.6584 data: 0.0065 max mem: 33368 +Epoch: [3] [ 810/1319] eta: 0:22:57 lr: 4.5914267506132555e-05 loss: 0.1419 (0.1478) time: 2.6845 data: 0.0067 max mem: 33368 +Epoch: [3] [ 820/1319] eta: 0:22:30 lr: 4.590565705620206e-05 loss: 0.1424 (0.1476) time: 2.7089 data: 0.0068 max mem: 33368 +Epoch: [3] [ 830/1319] eta: 0:22:03 lr: 4.589704642681802e-05 loss: 0.1249 (0.1476) time: 2.7174 data: 0.0066 max mem: 33368 +Epoch: [3] [ 840/1319] eta: 0:21:36 lr: 4.58884356179393e-05 loss: 0.1473 (0.1479) time: 2.7313 data: 0.0066 max mem: 33368 +Epoch: [3] [ 850/1319] eta: 0:21:10 lr: 4.5879824629524725e-05 loss: 0.1473 (0.1478) time: 2.7425 data: 0.0065 max mem: 33368 +Epoch: [3] [ 860/1319] eta: 0:20:43 lr: 4.5871213461533106e-05 loss: 0.1345 (0.1478) time: 2.7458 data: 0.0064 max mem: 33368 +Epoch: [3] [ 870/1319] eta: 0:20:16 lr: 4.5862602113923244e-05 loss: 0.1362 (0.1476) time: 2.7148 data: 0.0064 max mem: 33368 +Epoch: [3] [ 880/1319] eta: 0:19:48 lr: 4.585399058665391e-05 loss: 0.1311 (0.1474) time: 2.7002 data: 0.0065 max mem: 33368 +Epoch: [3] [ 890/1319] eta: 0:19:21 lr: 4.5845378879683885e-05 loss: 0.1380 (0.1473) time: 2.6849 data: 0.0065 max mem: 33368 +Epoch: [3] [ 900/1319] eta: 0:18:54 lr: 4.583676699297189e-05 loss: 0.1425 (0.1475) time: 2.6839 data: 0.0064 max mem: 33368 +Epoch: [3] [ 910/1319] eta: 0:18:27 lr: 4.582815492647665e-05 loss: 0.1453 (0.1474) time: 2.7041 data: 0.0065 max mem: 33368 +Epoch: [3] [ 920/1319] eta: 0:18:00 lr: 4.5819542680156885e-05 loss: 0.1507 (0.1477) time: 2.7084 data: 0.0065 max mem: 33368 +Epoch: [3] [ 930/1319] eta: 0:17:33 lr: 4.5810930253971277e-05 loss: 0.1469 (0.1477) time: 2.6877 data: 0.0064 max mem: 33368 +Epoch: [3] [ 940/1319] eta: 0:17:06 lr: 4.580231764787849e-05 loss: 0.1549 (0.1478) time: 2.7157 data: 0.0063 max mem: 33368 +Epoch: [3] [ 950/1319] eta: 0:16:39 lr: 4.579370486183719e-05 loss: 0.1559 (0.1477) time: 2.7547 data: 0.0063 max mem: 33368 +Epoch: [3] [ 960/1319] eta: 0:16:12 lr: 4.5785091895806004e-05 loss: 0.1108 (0.1474) time: 2.7421 data: 0.0065 max mem: 33368 +Epoch: [3] [ 970/1319] eta: 0:15:45 lr: 4.577647874974354e-05 loss: 0.1268 (0.1473) time: 2.7059 data: 0.0066 max mem: 33368 +Epoch: [3] [ 980/1319] eta: 0:15:17 lr: 4.57678654236084e-05 loss: 0.1398 (0.1472) time: 2.6708 data: 0.0064 max mem: 33368 +Epoch: [3] [ 990/1319] eta: 0:14:50 lr: 4.575925191735917e-05 loss: 0.1370 (0.1471) time: 2.6822 data: 0.0064 max mem: 33368 +Epoch: [3] [1000/1319] eta: 0:14:23 lr: 4.57506382309544e-05 loss: 0.1380 (0.1472) time: 2.6985 data: 0.0063 max mem: 33368 +Epoch: [3] [1010/1319] eta: 0:13:56 lr: 4.574202436435264e-05 loss: 0.1353 (0.1471) time: 2.7170 data: 0.0065 max mem: 33368 +Epoch: [3] [1020/1319] eta: 0:13:29 lr: 4.573341031751242e-05 loss: 0.1281 (0.1470) time: 2.7597 data: 0.0066 max mem: 33368 +Epoch: [3] [1030/1319] eta: 0:13:02 lr: 4.5724796090392234e-05 loss: 0.1323 (0.1470) time: 2.7678 data: 0.0065 max mem: 33368 +Epoch: [3] [1040/1319] eta: 0:12:35 lr: 4.571618168295058e-05 loss: 0.1281 (0.1468) time: 2.7091 data: 0.0064 max mem: 33368 +Epoch: [3] [1050/1319] eta: 0:12:08 lr: 4.570756709514592e-05 loss: 0.1250 (0.1467) time: 2.7043 data: 0.0063 max mem: 33368 +Epoch: [3] [1060/1319] eta: 0:11:41 lr: 4.569895232693671e-05 loss: 0.1414 (0.1468) time: 2.7385 data: 0.0064 max mem: 33368 +Epoch: [3] [1070/1319] eta: 0:11:14 lr: 4.569033737828139e-05 loss: 0.1464 (0.1468) time: 2.7409 data: 0.0063 max mem: 33368 +Epoch: [3] [1080/1319] eta: 0:10:47 lr: 4.568172224913836e-05 loss: 0.1265 (0.1466) time: 2.7278 data: 0.0063 max mem: 33368 +Epoch: [3] [1090/1319] eta: 0:10:20 lr: 4.567310693946603e-05 loss: 0.1391 (0.1466) time: 2.7120 data: 0.0064 max mem: 33368 +Epoch: [3] [1100/1319] eta: 0:09:53 lr: 4.566449144922278e-05 loss: 0.1391 (0.1465) time: 2.7302 data: 0.0064 max mem: 33368 +Epoch: [3] [1110/1319] eta: 0:09:26 lr: 4.565587577836695e-05 loss: 0.1308 (0.1465) time: 2.7437 data: 0.0066 max mem: 33368 +Epoch: [3] [1120/1319] eta: 0:08:59 lr: 4.5647259926856906e-05 loss: 0.1527 (0.1467) time: 2.7256 data: 0.0066 max mem: 33368 +Epoch: [3] [1130/1319] eta: 0:08:32 lr: 4.563864389465096e-05 loss: 0.1350 (0.1466) time: 2.7102 data: 0.0063 max mem: 33368 +Epoch: [3] [1140/1319] eta: 0:08:05 lr: 4.563002768170741e-05 loss: 0.1193 (0.1467) time: 2.7364 data: 0.0064 max mem: 33368 +Epoch: [3] [1150/1319] eta: 0:07:38 lr: 4.562141128798457e-05 loss: 0.1351 (0.1467) time: 2.7528 data: 0.0063 max mem: 33368 +Epoch: [3] [1160/1319] eta: 0:07:11 lr: 4.561279471344068e-05 loss: 0.1372 (0.1468) time: 2.7468 data: 0.0063 max mem: 33368 +Epoch: [3] [1170/1319] eta: 0:06:44 lr: 4.5604177958034e-05 loss: 0.1339 (0.1469) time: 2.7524 data: 0.0064 max mem: 33368 +Epoch: [3] [1180/1319] eta: 0:06:16 lr: 4.559556102172276e-05 loss: 0.1391 (0.1468) time: 2.7316 data: 0.0064 max mem: 33368 +Epoch: [3] [1190/1319] eta: 0:05:49 lr: 4.5586943904465176e-05 loss: 0.1391 (0.1469) time: 2.7221 data: 0.0064 max mem: 33368 +Epoch: [3] [1200/1319] eta: 0:05:22 lr: 4.557832660621944e-05 loss: 0.1254 (0.1469) time: 2.7241 data: 0.0063 max mem: 33368 +Epoch: [3] [1210/1319] eta: 0:04:55 lr: 4.556970912694373e-05 loss: 0.1265 (0.1468) time: 2.7255 data: 0.0063 max mem: 33368 +Epoch: [3] [1220/1319] eta: 0:04:28 lr: 4.5561091466596205e-05 loss: 0.1481 (0.1469) time: 2.7296 data: 0.0065 max mem: 33368 +Epoch: [3] [1230/1319] eta: 0:04:01 lr: 4.555247362513501e-05 loss: 0.1511 (0.1467) time: 2.7367 data: 0.0066 max mem: 33368 +Epoch: [3] [1240/1319] eta: 0:03:34 lr: 4.5543855602518245e-05 loss: 0.1302 (0.1466) time: 2.7547 data: 0.0064 max mem: 33368 +Epoch: [3] [1250/1319] eta: 0:03:07 lr: 4.553523739870403e-05 loss: 0.1157 (0.1464) time: 2.7341 data: 0.0061 max mem: 33368 +Epoch: [3] [1260/1319] eta: 0:02:40 lr: 4.552661901365045e-05 loss: 0.1356 (0.1463) time: 2.7098 data: 0.0063 max mem: 33368 +Epoch: [3] [1270/1319] eta: 0:02:12 lr: 4.551800044731557e-05 loss: 0.1356 (0.1462) time: 2.7117 data: 0.0064 max mem: 33368 +Epoch: [3] [1280/1319] eta: 0:01:45 lr: 4.550938169965743e-05 loss: 0.1339 (0.1462) time: 2.7178 data: 0.0062 max mem: 33368 +Epoch: [3] [1290/1319] eta: 0:01:18 lr: 4.550076277063406e-05 loss: 0.1355 (0.1461) time: 2.7096 data: 0.0061 max mem: 33368 +Epoch: [3] [1300/1319] eta: 0:00:51 lr: 4.549214366020347e-05 loss: 0.1346 (0.1463) time: 2.6816 data: 0.0062 max mem: 33368 +Epoch: [3] [1310/1319] eta: 0:00:24 lr: 4.5483524368323656e-05 loss: 0.1427 (0.1466) time: 2.6955 data: 0.0062 max mem: 33368 +Epoch: [3] Total time: 0:59:38 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 2:27:43 time: 3.4450 data: 3.3657 max mem: 33368 +Test: [ 100/2573] eta: 0:04:21 time: 0.0718 data: 0.0011 max mem: 33368 +Test: [ 200/2573] eta: 0:03:33 time: 0.0735 data: 0.0012 max mem: 33368 +Test: [ 300/2573] eta: 0:03:10 time: 0.0749 data: 0.0011 max mem: 33368 +Test: [ 400/2573] eta: 0:02:56 time: 0.0749 data: 0.0011 max mem: 33368 +Test: [ 500/2573] eta: 0:02:45 time: 0.0737 data: 0.0012 max mem: 33368 +Test: [ 600/2573] eta: 0:02:35 time: 0.0736 data: 0.0012 max mem: 33368 +Test: [ 700/2573] eta: 0:02:26 time: 0.0737 data: 0.0012 max mem: 33368 +Test: [ 800/2573] eta: 0:02:18 time: 0.0772 data: 0.0011 max mem: 33368 +Test: [ 900/2573] eta: 0:02:09 time: 0.0737 data: 0.0012 max mem: 33368 +Test: [1000/2573] eta: 0:02:01 time: 0.0740 data: 0.0012 max mem: 33368 +Test: [1100/2573] eta: 0:01:53 time: 0.0738 data: 0.0012 max mem: 33368 +Test: [1200/2573] eta: 0:01:45 time: 0.0740 data: 0.0012 max mem: 33368 +Test: [1300/2573] eta: 0:01:37 time: 0.0739 data: 0.0011 max mem: 33368 +Test: [1400/2573] eta: 0:01:29 time: 0.0720 data: 0.0011 max mem: 33368 +Test: [1500/2573] eta: 0:01:21 time: 0.0738 data: 0.0011 max mem: 33368 +Test: [1600/2573] eta: 0:01:14 time: 0.0773 data: 0.0012 max mem: 33368 +Test: [1700/2573] eta: 0:01:06 time: 0.0722 data: 0.0011 max mem: 33368 +Test: [1800/2573] eta: 0:00:58 time: 0.0756 data: 0.0011 max mem: 33368 +Test: [1900/2573] eta: 0:00:50 time: 0.0723 data: 0.0012 max mem: 33368 +Test: [2000/2573] eta: 0:00:43 time: 0.0740 data: 0.0012 max mem: 33368 +Test: [2100/2573] eta: 0:00:35 time: 0.0757 data: 0.0011 max mem: 33368 +Test: [2200/2573] eta: 0:00:28 time: 0.0757 data: 0.0012 max mem: 33368 +Test: [2300/2573] eta: 0:00:20 time: 0.0756 data: 0.0012 max mem: 33368 +Test: [2400/2573] eta: 0:00:13 time: 0.0708 data: 0.0012 max mem: 33368 +Test: [2500/2573] eta: 0:00:05 time: 0.0741 data: 0.0012 max mem: 33368 +Test: Total time: 0:03:13 +Final results: +Mean IoU is 50.46 + + precision@0.5 = 53.98 + precision@0.6 = 45.57 + precision@0.7 = 36.03 + precision@0.8 = 24.33 + precision@0.9 = 8.72 + overall IoU = 51.13 + +Average object IoU 50.456440677786865 +Overall IoU 51.128868103027344 +Better epoch: 3 + +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [4] [ 0/1319] eta: 1:33:05 lr: 4.547576685045799e-05 loss: 0.1178 (0.1178) time: 4.2344 data: 1.4332 max mem: 33368 +Epoch: [4] [ 10/1319] eta: 1:02:27 lr: 4.546714721370884e-05 loss: 0.1507 (0.1447) time: 2.8627 data: 0.1358 max mem: 33368 +Epoch: [4] [ 20/1319] eta: 1:00:24 lr: 4.5458527395388535e-05 loss: 0.1287 (0.1327) time: 2.7182 data: 0.0061 max mem: 33368 +Epoch: [4] [ 30/1319] eta: 0:59:09 lr: 4.544990739545498e-05 loss: 0.1162 (0.1339) time: 2.6941 data: 0.0063 max mem: 33368 +Epoch: [4] [ 40/1319] eta: 0:58:16 lr: 4.544128721386609e-05 loss: 0.1140 (0.1317) time: 2.6739 data: 0.0065 max mem: 33368 +Epoch: [4] [ 50/1319] eta: 0:57:54 lr: 4.543266685057974e-05 loss: 0.1140 (0.1291) time: 2.7136 data: 0.0064 max mem: 33368 +Epoch: [4] [ 60/1319] eta: 0:57:16 lr: 4.54240463055538e-05 loss: 0.1105 (0.1280) time: 2.7203 data: 0.0066 max mem: 33368 +Epoch: [4] [ 70/1319] eta: 0:56:58 lr: 4.541542557874611e-05 loss: 0.1062 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0:45:17 lr: 4.520847349090225e-05 loss: 0.1278 (0.1346) time: 2.7139 data: 0.0064 max mem: 33368 +Epoch: [4] [ 320/1319] eta: 0:44:50 lr: 4.5199848205795306e-05 loss: 0.1139 (0.1344) time: 2.7002 data: 0.0065 max mem: 33368 +Epoch: [4] [ 330/1319] eta: 0:44:24 lr: 4.519122273780396e-05 loss: 0.1139 (0.1337) time: 2.6966 data: 0.0065 max mem: 33368 +Epoch: [4] [ 340/1319] eta: 0:43:55 lr: 4.518259708688556e-05 loss: 0.1155 (0.1335) time: 2.6855 data: 0.0065 max mem: 33368 +Epoch: [4] [ 350/1319] eta: 0:43:29 lr: 4.5173971252997424e-05 loss: 0.1160 (0.1333) time: 2.6869 data: 0.0065 max mem: 33368 +Epoch: [4] [ 360/1319] eta: 0:43:04 lr: 4.5165345236096837e-05 loss: 0.1196 (0.1336) time: 2.7350 data: 0.0064 max mem: 33368 +Epoch: [4] [ 370/1319] eta: 0:42:36 lr: 4.5156719036141086e-05 loss: 0.1289 (0.1339) time: 2.6950 data: 0.0065 max mem: 33368 +Epoch: [4] [ 380/1319] eta: 0:42:08 lr: 4.5148092653087434e-05 loss: 0.1272 (0.1340) time: 2.6529 data: 0.0064 max mem: 33368 +Epoch: [4] [ 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+Epoch: [4] [ 470/1319] eta: 0:38:10 lr: 4.507044695913725e-05 loss: 0.1486 (0.1351) time: 2.7045 data: 0.0066 max mem: 33368 +Epoch: [4] [ 480/1319] eta: 0:37:43 lr: 4.506181874274963e-05 loss: 0.1223 (0.1349) time: 2.6974 data: 0.0066 max mem: 33368 +Epoch: [4] [ 490/1319] eta: 0:37:17 lr: 4.5053190342792706e-05 loss: 0.1176 (0.1347) time: 2.7335 data: 0.0066 max mem: 33368 +Epoch: [4] [ 500/1319] eta: 0:36:51 lr: 4.50445617592235e-05 loss: 0.1319 (0.1348) time: 2.7458 data: 0.0065 max mem: 33368 +Epoch: [4] [ 510/1319] eta: 0:36:24 lr: 4.503593299199903e-05 loss: 0.1277 (0.1348) time: 2.7206 data: 0.0065 max mem: 33368 +Epoch: [4] [ 520/1319] eta: 0:35:57 lr: 4.502730404107628e-05 loss: 0.1204 (0.1346) time: 2.7132 data: 0.0065 max mem: 33368 +Epoch: [4] [ 530/1319] eta: 0:35:31 lr: 4.5018674906412226e-05 loss: 0.1177 (0.1346) time: 2.7319 data: 0.0063 max mem: 33368 +Epoch: [4] [ 540/1319] eta: 0:35:04 lr: 4.5010045587963815e-05 loss: 0.1163 (0.1346) time: 2.7178 data: 0.0064 max 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(0.1341) time: 2.7160 data: 0.0064 max mem: 33368 +Epoch: [4] [ 790/1319] eta: 0:23:50 lr: 4.4794252770532266e-05 loss: 0.1169 (0.1338) time: 2.7337 data: 0.0062 max mem: 33368 +Epoch: [4] [ 800/1319] eta: 0:23:23 lr: 4.4785618658517975e-05 loss: 0.1169 (0.1339) time: 2.7074 data: 0.0064 max mem: 33368 +Epoch: [4] [ 810/1319] eta: 0:22:57 lr: 4.477698436154974e-05 loss: 0.1112 (0.1336) time: 2.7190 data: 0.0066 max mem: 33368 +Epoch: [4] [ 820/1319] eta: 0:22:30 lr: 4.476834987958398e-05 loss: 0.1054 (0.1335) time: 2.7439 data: 0.0065 max mem: 33368 +Epoch: [4] [ 830/1319] eta: 0:22:03 lr: 4.4759715212577086e-05 loss: 0.1159 (0.1336) time: 2.7275 data: 0.0064 max mem: 33368 +Epoch: [4] [ 840/1319] eta: 0:21:36 lr: 4.475108036048542e-05 loss: 0.1345 (0.1336) time: 2.7033 data: 0.0064 max mem: 33368 +Epoch: [4] [ 850/1319] eta: 0:21:09 lr: 4.4742445323265344e-05 loss: 0.1419 (0.1338) time: 2.7129 data: 0.0066 max mem: 33368 +Epoch: [4] [ 860/1319] eta: 0:20:42 lr: 4.473381010087318e-05 loss: 0.1389 (0.1340) time: 2.7301 data: 0.0065 max mem: 33368 +Epoch: [4] [ 870/1319] eta: 0:20:15 lr: 4.4725174693265234e-05 loss: 0.1374 (0.1340) time: 2.7243 data: 0.0064 max mem: 33368 +Epoch: [4] [ 880/1319] eta: 0:19:48 lr: 4.471653910039782e-05 loss: 0.1419 (0.1344) time: 2.7286 data: 0.0063 max mem: 33368 +Epoch: [4] [ 890/1319] eta: 0:19:21 lr: 4.4707903322227184e-05 loss: 0.1274 (0.1343) time: 2.7271 data: 0.0063 max mem: 33368 +Epoch: [4] [ 900/1319] eta: 0:18:54 lr: 4.469926735870959e-05 loss: 0.1137 (0.1343) time: 2.7190 data: 0.0064 max mem: 33368 +Epoch: [4] [ 910/1319] eta: 0:18:26 lr: 4.4690631209801266e-05 loss: 0.1177 (0.1342) time: 2.6882 data: 0.0063 max mem: 33368 +Epoch: [4] [ 920/1319] eta: 0:17:59 lr: 4.4681994875458425e-05 loss: 0.1144 (0.1339) time: 2.6801 data: 0.0066 max mem: 33368 +Epoch: [4] [ 930/1319] eta: 0:17:33 lr: 4.467335835563727e-05 loss: 0.1112 (0.1337) time: 2.7277 data: 0.0065 max mem: 33368 +Epoch: [4] [ 940/1319] eta: 0:17:06 lr: 4.466472165029396e-05 loss: 0.1187 (0.1339) time: 2.7391 data: 0.0062 max mem: 33368 +Epoch: [4] [ 950/1319] eta: 0:16:39 lr: 4.4656084759384645e-05 loss: 0.1265 (0.1339) time: 2.7259 data: 0.0066 max mem: 33368 +Epoch: [4] [ 960/1319] eta: 0:16:12 lr: 4.464744768286547e-05 loss: 0.1290 (0.1340) time: 2.7226 data: 0.0065 max mem: 33368 +Epoch: [4] [ 970/1319] eta: 0:15:45 lr: 4.463881042069255e-05 loss: 0.1425 (0.1341) time: 2.7361 data: 0.0064 max mem: 33368 +Epoch: [4] [ 980/1319] eta: 0:15:18 lr: 4.463017297282197e-05 loss: 0.1344 (0.1339) time: 2.7328 data: 0.0067 max mem: 33368 +Epoch: [4] [ 990/1319] eta: 0:14:51 lr: 4.4621535339209816e-05 loss: 0.1172 (0.1339) time: 2.7528 data: 0.0065 max mem: 33368 +Epoch: [4] [1000/1319] eta: 0:14:24 lr: 4.461289751981212e-05 loss: 0.1237 (0.1338) time: 2.7252 data: 0.0064 max mem: 33368 +Epoch: [4] [1010/1319] eta: 0:13:57 lr: 4.460425951458493e-05 loss: 0.1263 (0.1339) time: 2.7068 data: 0.0063 max mem: 33368 +Epoch: [4] [1020/1319] eta: 0:13:29 lr: 4.459562132348427e-05 loss: 0.1314 (0.1341) time: 2.7321 data: 0.0065 max mem: 33368 +Epoch: [4] [1030/1319] eta: 0:13:02 lr: 4.458698294646612e-05 loss: 0.1190 (0.1339) time: 2.7119 data: 0.0065 max mem: 33368 +Epoch: [4] [1040/1319] eta: 0:12:35 lr: 4.457834438348646e-05 loss: 0.1098 (0.1336) time: 2.6713 data: 0.0065 max mem: 33368 +Epoch: [4] [1050/1319] eta: 0:12:08 lr: 4.456970563450125e-05 loss: 0.1227 (0.1337) time: 2.6605 data: 0.0067 max mem: 33368 +Epoch: [4] [1060/1319] eta: 0:11:41 lr: 4.456106669946641e-05 loss: 0.1305 (0.1337) time: 2.6816 data: 0.0066 max mem: 33368 +Epoch: [4] [1070/1319] eta: 0:11:14 lr: 4.4552427578337865e-05 loss: 0.1181 (0.1335) time: 2.6887 data: 0.0064 max mem: 33368 +Epoch: [4] [1080/1319] eta: 0:10:46 lr: 4.45437882710715e-05 loss: 0.1337 (0.1336) time: 2.6698 data: 0.0064 max mem: 33368 +Epoch: [4] [1090/1319] eta: 0:10:19 lr: 4.453514877762321e-05 loss: 0.1246 (0.1335) time: 2.6568 data: 0.0066 max mem: 33368 +Epoch: [4] [1100/1319] eta: 0:09:52 lr: 4.4526509097948836e-05 loss: 0.1184 (0.1335) time: 2.6897 data: 0.0064 max mem: 33368 +Epoch: [4] [1110/1319] eta: 0:09:25 lr: 4.451786923200421e-05 loss: 0.1228 (0.1336) time: 2.7353 data: 0.0064 max mem: 33368 +Epoch: [4] [1120/1319] eta: 0:08:58 lr: 4.450922917974515e-05 loss: 0.1289 (0.1337) time: 2.7364 data: 0.0065 max mem: 33368 +Epoch: [4] [1130/1319] eta: 0:08:31 lr: 4.4500588941127465e-05 loss: 0.1328 (0.1337) time: 2.7244 data: 0.0064 max mem: 33368 +Epoch: [4] [1140/1319] eta: 0:08:04 lr: 4.449194851610691e-05 loss: 0.1315 (0.1338) time: 2.7587 data: 0.0064 max mem: 33368 +Epoch: [4] [1150/1319] eta: 0:07:37 lr: 4.4483307904639245e-05 loss: 0.1177 (0.1338) time: 2.7695 data: 0.0064 max mem: 33368 +Epoch: [4] [1160/1319] eta: 0:07:10 lr: 4.447466710668021e-05 loss: 0.1232 (0.1339) time: 2.7450 data: 0.0064 max mem: 33368 +Epoch: [4] [1170/1319] eta: 0:06:43 lr: 4.4466026122185514e-05 loss: 0.1277 (0.1337) time: 2.7096 data: 0.0065 max mem: 33368 +Epoch: [4] [1180/1319] eta: 0:06:16 lr: 4.4457384951110855e-05 loss: 0.1196 (0.1341) time: 2.6972 data: 0.0066 max mem: 33368 +Epoch: [4] [1190/1319] eta: 0:05:49 lr: 4.44487435934119e-05 loss: 0.1196 (0.1340) time: 2.6993 data: 0.0065 max mem: 33368 +Epoch: [4] [1200/1319] eta: 0:05:22 lr: 4.4440102049044326e-05 loss: 0.1149 (0.1340) time: 2.6865 data: 0.0066 max mem: 33368 +Epoch: [4] [1210/1319] eta: 0:04:55 lr: 4.443146031796374e-05 loss: 0.1138 (0.1338) time: 2.6840 data: 0.0069 max mem: 33368 +Epoch: [4] [1220/1319] eta: 0:04:28 lr: 4.442281840012577e-05 loss: 0.1173 (0.1340) time: 2.6684 data: 0.0067 max mem: 33368 +Epoch: [4] [1230/1319] eta: 0:04:00 lr: 4.441417629548601e-05 loss: 0.1499 (0.1341) time: 2.6464 data: 0.0067 max mem: 33368 +Epoch: [4] [1240/1319] eta: 0:03:33 lr: 4.4405534004000035e-05 loss: 0.1296 (0.1342) time: 2.6615 data: 0.0070 max mem: 33368 +Epoch: [4] [1250/1319] eta: 0:03:06 lr: 4.439689152562339e-05 loss: 0.1369 (0.1344) time: 2.6696 data: 0.0069 max mem: 33368 +Epoch: [4] [1260/1319] eta: 0:02:39 lr: 4.438824886031161e-05 loss: 0.1520 (0.1344) time: 2.6574 data: 0.0069 max mem: 33368 +Epoch: [4] [1270/1319] eta: 0:02:12 lr: 4.437960600802022e-05 loss: 0.1194 (0.1344) time: 2.6625 data: 0.0069 max mem: 33368 +Epoch: [4] [1280/1319] eta: 0:01:45 lr: 4.4370962968704706e-05 loss: 0.1250 (0.1345) time: 2.6682 data: 0.0068 max mem: 33368 +Epoch: [4] [1290/1319] eta: 0:01:18 lr: 4.436231974232054e-05 loss: 0.1250 (0.1345) time: 2.6616 data: 0.0067 max mem: 33368 +Epoch: [4] [1300/1319] eta: 0:00:51 lr: 4.435367632882316e-05 loss: 0.1185 (0.1343) time: 2.6272 data: 0.0069 max mem: 33368 +Epoch: [4] [1310/1319] eta: 0:00:24 lr: 4.434503272816803e-05 loss: 0.1185 (0.1343) time: 2.6297 data: 0.0069 max mem: 33368 +Epoch: [4] Total time: 0:59:26 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 2:12:39 time: 3.0935 data: 3.0137 max mem: 33368 +Test: [ 100/2573] eta: 0:04:12 time: 0.0719 data: 0.0012 max mem: 33368 +Test: [ 200/2573] eta: 0:03:29 time: 0.0733 data: 0.0012 max mem: 33368 +Test: [ 300/2573] eta: 0:03:08 time: 0.0751 data: 0.0012 max mem: 33368 +Test: [ 400/2573] eta: 0:02:54 time: 0.0751 data: 0.0011 max mem: 33368 +Test: [ 500/2573] eta: 0:02:44 time: 0.0737 data: 0.0012 max mem: 33368 +Test: [ 600/2573] eta: 0:02:34 time: 0.0739 data: 0.0012 max mem: 33368 +Test: [ 700/2573] eta: 0:02:26 time: 0.0738 data: 0.0012 max mem: 33368 +Test: [ 800/2573] eta: 0:02:17 time: 0.0771 data: 0.0011 max mem: 33368 +Test: [ 900/2573] eta: 0:02:09 time: 0.0738 data: 0.0012 max mem: 33368 +Test: [1000/2573] eta: 0:02:01 time: 0.0739 data: 0.0012 max mem: 33368 +Test: [1100/2573] eta: 0:01:52 time: 0.0738 data: 0.0012 max mem: 33368 +Test: [1200/2573] eta: 0:01:45 time: 0.0738 data: 0.0011 max mem: 33368 +Test: [1300/2573] eta: 0:01:37 time: 0.0740 data: 0.0011 max mem: 33368 +Test: [1400/2573] eta: 0:01:29 time: 0.0723 data: 0.0012 max mem: 33368 +Test: [1500/2573] eta: 0:01:21 time: 0.0741 data: 0.0012 max mem: 33368 +Test: [1600/2573] eta: 0:01:13 time: 0.0772 data: 0.0011 max mem: 33368 +Test: [1700/2573] eta: 0:01:06 time: 0.0722 data: 0.0011 max mem: 33368 +Test: [1800/2573] eta: 0:00:58 time: 0.0757 data: 0.0012 max mem: 33368 +Test: [1900/2573] eta: 0:00:50 time: 0.0725 data: 0.0012 max mem: 33368 +Test: [2000/2573] eta: 0:00:43 time: 0.0739 data: 0.0012 max mem: 33368 +Test: [2100/2573] eta: 0:00:35 time: 0.0757 data: 0.0011 max mem: 33368 +Test: [2200/2573] eta: 0:00:28 time: 0.0756 data: 0.0012 max mem: 33368 +Test: [2300/2573] eta: 0:00:20 time: 0.0757 data: 0.0012 max mem: 33368 +Test: [2400/2573] eta: 0:00:12 time: 0.0706 data: 0.0011 max mem: 33368 +Test: [2500/2573] eta: 0:00:05 time: 0.0740 data: 0.0011 max mem: 33368 +Test: Total time: 0:03:13 +Final results: +Mean IoU is 49.58 + + precision@0.5 = 54.31 + precision@0.6 = 47.30 + precision@0.7 = 38.32 + precision@0.8 = 26.96 + precision@0.9 = 10.46 + overall IoU = 51.93 + +Average object IoU 49.58134947781975 +Overall IoU 51.929386138916016 +Better epoch: 4 + +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [5] [ 0/1319] eta: 1:30:02 lr: 4.433725332752167e-05 loss: 0.1931 (0.1931) time: 4.0961 data: 1.3669 max mem: 33368 +Epoch: [5] [ 10/1319] eta: 1:02:17 lr: 4.432860937114392e-05 loss: 0.0949 (0.1287) time: 2.8550 data: 0.1303 max mem: 33368 +Epoch: [5] [ 20/1319] eta: 1:00:16 lr: 4.4319965227479046e-05 loss: 0.1032 (0.1248) time: 2.7184 data: 0.0060 max mem: 33368 +Epoch: [5] [ 30/1319] eta: 0:59:20 lr: 4.43113208964824e-05 loss: 0.1148 (0.1251) time: 2.7106 data: 0.0058 max mem: 33368 +Epoch: [5] [ 40/1319] eta: 0:58:37 lr: 4.43026763781093e-05 loss: 0.1099 (0.1206) time: 2.7155 data: 0.0063 max mem: 33368 +Epoch: [5] [ 50/1319] eta: 0:57:59 lr: 4.429403167231508e-05 loss: 0.1099 (0.1239) time: 2.7109 data: 0.0062 max mem: 33368 +Epoch: [5] [ 60/1319] eta: 0:57:32 lr: 4.428538677905502e-05 loss: 0.1258 (0.1239) time: 2.7255 data: 0.0061 max mem: 33368 +Epoch: [5] [ 70/1319] eta: 0:56:53 lr: 4.4276741698284395e-05 loss: 0.1258 (0.1263) time: 2.7108 data: 0.0062 max mem: 33368 +Epoch: [5] [ 80/1319] eta: 0:56:23 lr: 4.4268096429958464e-05 loss: 0.1182 (0.1259) time: 2.6962 data: 0.0064 max mem: 33368 +Epoch: [5] [ 90/1319] eta: 0:55:58 lr: 4.425945097403244e-05 loss: 0.1073 (0.1245) time: 2.7325 data: 0.0064 max mem: 33368 +Epoch: [5] [ 100/1319] eta: 0:55:28 lr: 4.425080533046155e-05 loss: 0.0945 (0.1216) time: 2.7267 data: 0.0063 max mem: 33368 +Epoch: [5] [ 110/1319] eta: 0:55:01 lr: 4.424215949920098e-05 loss: 0.0973 (0.1242) time: 2.7202 data: 0.0064 max mem: 33368 +Epoch: [5] [ 120/1319] eta: 0:54:31 lr: 4.423351348020589e-05 loss: 0.1276 (0.1281) time: 2.7214 data: 0.0064 max mem: 33368 +Epoch: [5] [ 130/1319] eta: 0:54:01 lr: 4.4224867273431445e-05 loss: 0.1123 (0.1271) time: 2.6991 data: 0.0066 max mem: 33368 +Epoch: [5] [ 140/1319] eta: 0:53:30 lr: 4.421622087883277e-05 loss: 0.1123 (0.1268) time: 2.6904 data: 0.0064 max mem: 33368 +Epoch: [5] [ 150/1319] eta: 0:53:07 lr: 4.4207574296364965e-05 loss: 0.1086 (0.1254) time: 2.7289 data: 0.0062 max mem: 33368 +Epoch: [5] [ 160/1319] eta: 0:52:41 lr: 4.419892752598312e-05 loss: 0.0956 (0.1250) time: 2.7565 data: 0.0062 max mem: 33368 +Epoch: [5] [ 170/1319] eta: 0:52:15 lr: 4.419028056764231e-05 loss: 0.1126 (0.1254) time: 2.7466 data: 0.0060 max mem: 33368 +Epoch: [5] [ 180/1319] eta: 0:51:45 lr: 4.418163342129758e-05 loss: 0.1160 (0.1265) time: 2.7163 data: 0.0061 max mem: 33368 +Epoch: [5] [ 190/1319] eta: 0:51:17 lr: 4.417298608690395e-05 loss: 0.1176 (0.1268) time: 2.7052 data: 0.0063 max mem: 33368 +Epoch: [5] [ 200/1319] eta: 0:50:48 lr: 4.416433856441643e-05 loss: 0.1174 (0.1263) time: 2.7115 data: 0.0063 max mem: 33368 +Epoch: [5] [ 210/1319] eta: 0:50:18 lr: 4.415569085379001e-05 loss: 0.1173 (0.1262) time: 2.6785 data: 0.0065 max mem: 33368 +Epoch: [5] [ 220/1319] eta: 0:49:50 lr: 4.4147042954979643e-05 loss: 0.1173 (0.1259) time: 2.6804 data: 0.0066 max mem: 33368 +Epoch: [5] [ 230/1319] eta: 0:49:25 lr: 4.413839486794028e-05 loss: 0.1172 (0.1263) time: 2.7384 data: 0.0065 max mem: 33368 +Epoch: [5] [ 240/1319] eta: 0:48:55 lr: 4.412974659262685e-05 loss: 0.1166 (0.1266) time: 2.7166 data: 0.0063 max mem: 33368 +Epoch: [5] [ 250/1319] eta: 0:48:27 lr: 4.412109812899424e-05 loss: 0.1166 (0.1260) time: 2.6811 data: 0.0062 max mem: 33368 +Epoch: [5] [ 260/1319] eta: 0:48:00 lr: 4.411244947699735e-05 loss: 0.1048 (0.1257) time: 2.7206 data: 0.0061 max mem: 33368 +Epoch: [5] [ 270/1319] eta: 0:47:30 lr: 4.4103800636591036e-05 loss: 0.1072 (0.1257) time: 2.6916 data: 0.0062 max mem: 33368 +Epoch: [5] [ 280/1319] eta: 0:47:03 lr: 4.409515160773014e-05 loss: 0.1186 (0.1262) time: 2.6741 data: 0.0063 max mem: 33368 +Epoch: [5] [ 290/1319] eta: 0:46:34 lr: 4.408650239036947e-05 loss: 0.1052 (0.1256) time: 2.6913 data: 0.0065 max mem: 33368 +Epoch: [5] [ 300/1319] eta: 0:46:05 lr: 4.407785298446384e-05 loss: 0.1052 (0.1251) time: 2.6768 data: 0.0065 max mem: 33368 +Epoch: [5] [ 310/1319] eta: 0:45:39 lr: 4.406920338996803e-05 loss: 0.1078 (0.1253) time: 2.7076 data: 0.0062 max mem: 33368 +Epoch: [5] [ 320/1319] eta: 0:45:11 lr: 4.406055360683679e-05 loss: 0.1013 (0.1249) time: 2.7160 data: 0.0062 max mem: 33368 +Epoch: [5] [ 330/1319] eta: 0:44:44 lr: 4.4051903635024855e-05 loss: 0.1048 (0.1250) time: 2.7042 data: 0.0062 max mem: 33368 +Epoch: [5] [ 340/1319] eta: 0:44:17 lr: 4.404325347448695e-05 loss: 0.1221 (0.1250) time: 2.7093 data: 0.0062 max mem: 33368 +Epoch: [5] [ 350/1319] eta: 0:43:50 lr: 4.403460312517776e-05 loss: 0.1087 (0.1250) time: 2.7207 data: 0.0063 max mem: 33368 +Epoch: [5] [ 360/1319] eta: 0:43:24 lr: 4.402595258705198e-05 loss: 0.1180 (0.1249) time: 2.7457 data: 0.0063 max mem: 33368 +Epoch: [5] [ 370/1319] eta: 0:42:57 lr: 4.401730186006425e-05 loss: 0.1278 (0.1256) time: 2.7278 data: 0.0064 max mem: 33368 +Epoch: [5] [ 380/1319] eta: 0:42:29 lr: 4.40086509441692e-05 loss: 0.1262 (0.1255) time: 2.6991 data: 0.0066 max mem: 33368 +Epoch: [5] [ 390/1319] eta: 0:42:02 lr: 4.399999983932147e-05 loss: 0.1223 (0.1255) time: 2.7052 data: 0.0064 max mem: 33368 +Epoch: [5] [ 400/1319] eta: 0:41:34 lr: 4.399134854547561e-05 loss: 0.1227 (0.1260) time: 2.7081 data: 0.0062 max mem: 33368 +Epoch: [5] [ 410/1319] eta: 0:41:07 lr: 4.3982697062586214e-05 loss: 0.1187 (0.1257) time: 2.6976 data: 0.0064 max mem: 33368 +Epoch: [5] [ 420/1319] eta: 0:40:40 lr: 4.397404539060784e-05 loss: 0.1005 (0.1256) time: 2.7097 data: 0.0063 max mem: 33368 +Epoch: [5] [ 430/1319] eta: 0:40:11 lr: 4.3965393529495005e-05 loss: 0.1005 (0.1252) time: 2.6857 data: 0.0064 max mem: 33368 +Epoch: [5] [ 440/1319] eta: 0:39:45 lr: 4.3956741479202226e-05 loss: 0.0997 (0.1253) time: 2.7064 data: 0.0063 max mem: 33368 +Epoch: [5] [ 450/1319] eta: 0:39:18 lr: 4.3948089239683975e-05 loss: 0.1105 (0.1256) time: 2.7270 data: 0.0061 max mem: 33368 +Epoch: [5] [ 460/1319] eta: 0:38:50 lr: 4.3939436810894734e-05 loss: 0.1324 (0.1260) time: 2.6979 data: 0.0063 max mem: 33368 +Epoch: [5] [ 470/1319] eta: 0:38:23 lr: 4.393078419278895e-05 loss: 0.1262 (0.1260) time: 2.7085 data: 0.0063 max mem: 33368 +Epoch: [5] [ 480/1319] eta: 0:37:56 lr: 4.3922131385321036e-05 loss: 0.1140 (0.1257) time: 2.7058 data: 0.0062 max mem: 33368 +Epoch: [5] [ 490/1319] eta: 0:37:28 lr: 4.3913478388445405e-05 loss: 0.1181 (0.1259) time: 2.6948 data: 0.0061 max mem: 33368 +Epoch: [5] [ 500/1319] eta: 0:37:02 lr: 4.390482520211644e-05 loss: 0.1218 (0.1255) time: 2.7161 data: 0.0061 max mem: 33368 +Epoch: [5] [ 510/1319] eta: 0:36:34 lr: 4.389617182628851e-05 loss: 0.1218 (0.1256) time: 2.7094 data: 0.0061 max mem: 33368 +Epoch: [5] [ 520/1319] eta: 0:36:07 lr: 4.3887518260915935e-05 loss: 0.1249 (0.1257) time: 2.6936 data: 0.0062 max mem: 33368 +Epoch: [5] [ 530/1319] eta: 0:35:40 lr: 4.3878864505953046e-05 loss: 0.1079 (0.1252) time: 2.7092 data: 0.0063 max mem: 33368 +Epoch: [5] [ 540/1319] eta: 0:35:12 lr: 4.387021056135415e-05 loss: 0.1147 (0.1255) time: 2.7010 data: 0.0061 max mem: 33368 +Epoch: [5] [ 550/1319] eta: 0:34:45 lr: 4.386155642707351e-05 loss: 0.1292 (0.1258) time: 2.6877 data: 0.0062 max mem: 33368 +Epoch: [5] [ 560/1319] eta: 0:34:19 lr: 4.3852902103065404e-05 loss: 0.1167 (0.1258) time: 2.7461 data: 0.0062 max mem: 33368 +Epoch: [5] [ 570/1319] eta: 0:33:52 lr: 4.3844247589284045e-05 loss: 0.1232 (0.1258) time: 2.7565 data: 0.0061 max mem: 33368 +Epoch: [5] [ 580/1319] eta: 0:33:24 lr: 4.383559288568366e-05 loss: 0.1232 (0.1261) time: 2.6809 data: 0.0063 max mem: 33368 +Epoch: [5] [ 590/1319] eta: 0:32:57 lr: 4.382693799221843e-05 loss: 0.1331 (0.1261) time: 2.6802 data: 0.0063 max mem: 33368 +Epoch: [5] [ 600/1319] eta: 0:32:30 lr: 4.381828290884256e-05 loss: 0.1204 (0.1262) time: 2.7303 data: 0.0063 max mem: 33368 +Epoch: [5] [ 610/1319] eta: 0:32:03 lr: 4.380962763551017e-05 loss: 0.1188 (0.1259) time: 2.7235 data: 0.0062 max mem: 33368 +Epoch: [5] [ 620/1319] eta: 0:31:35 lr: 4.38009721721754e-05 loss: 0.1188 (0.1260) time: 2.6842 data: 0.0064 max mem: 33368 +Epoch: [5] [ 630/1319] eta: 0:31:08 lr: 4.3792316518792354e-05 loss: 0.1068 (0.1256) time: 2.7127 data: 0.0064 max mem: 33368 +Epoch: [5] [ 640/1319] eta: 0:30:41 lr: 4.378366067531513e-05 loss: 0.1025 (0.1256) time: 2.7355 data: 0.0061 max mem: 33368 +Epoch: [5] [ 650/1319] eta: 0:30:15 lr: 4.37750046416978e-05 loss: 0.1231 (0.1255) time: 2.7407 data: 0.0061 max mem: 33368 +Epoch: [5] [ 660/1319] eta: 0:29:47 lr: 4.376634841789439e-05 loss: 0.1262 (0.1258) time: 2.7331 data: 0.0063 max mem: 33368 +Epoch: [5] [ 670/1319] eta: 0:29:21 lr: 4.375769200385893e-05 loss: 0.1200 (0.1259) time: 2.7349 data: 0.0062 max mem: 33368 +Epoch: [5] [ 680/1319] eta: 0:28:53 lr: 4.3749035399545434e-05 loss: 0.1152 (0.1261) time: 2.7198 data: 0.0061 max mem: 33368 +Epoch: [5] [ 690/1319] eta: 0:28:26 lr: 4.374037860490788e-05 loss: 0.1122 (0.1260) time: 2.6905 data: 0.0063 max mem: 33368 +Epoch: [5] [ 700/1319] eta: 0:27:59 lr: 4.373172161990022e-05 loss: 0.1249 (0.1264) time: 2.7219 data: 0.0062 max mem: 33368 +Epoch: [5] [ 710/1319] eta: 0:27:32 lr: 4.372306444447641e-05 loss: 0.1280 (0.1265) time: 2.7298 data: 0.0062 max mem: 33368 +Epoch: [5] [ 720/1319] eta: 0:27:05 lr: 4.3714407078590355e-05 loss: 0.1058 (0.1263) time: 2.7034 data: 0.0064 max mem: 33368 +Epoch: [5] [ 730/1319] eta: 0:26:38 lr: 4.370574952219595e-05 loss: 0.1063 (0.1265) time: 2.7211 data: 0.0064 max mem: 33368 +Epoch: [5] [ 740/1319] eta: 0:26:11 lr: 4.369709177524708e-05 loss: 0.1115 (0.1265) time: 2.7251 data: 0.0062 max mem: 33368 +Epoch: [5] [ 750/1319] eta: 0:25:43 lr: 4.36884338376976e-05 loss: 0.1164 (0.1267) time: 2.6782 data: 0.0062 max mem: 33368 +Epoch: [5] [ 760/1319] eta: 0:25:16 lr: 4.3679775709501325e-05 loss: 0.1303 (0.1266) time: 2.6785 data: 0.0065 max mem: 33368 +Epoch: [5] [ 770/1319] eta: 0:24:49 lr: 4.3671117390612085e-05 loss: 0.1252 (0.1266) time: 2.7320 data: 0.0063 max mem: 33368 +Epoch: [5] [ 780/1319] eta: 0:24:22 lr: 4.366245888098367e-05 loss: 0.1142 (0.1270) time: 2.7647 data: 0.0061 max mem: 33368 +Epoch: [5] [ 790/1319] eta: 0:23:55 lr: 4.3653800180569845e-05 loss: 0.1116 (0.1269) time: 2.7424 data: 0.0061 max mem: 33368 +Epoch: [5] [ 800/1319] eta: 0:23:28 lr: 4.364514128932435e-05 loss: 0.1205 (0.1269) time: 2.7119 data: 0.0063 max mem: 33368 +Epoch: [5] [ 810/1319] eta: 0:23:01 lr: 4.363648220720092e-05 loss: 0.1034 (0.1265) time: 2.6962 data: 0.0067 max mem: 33368 +Epoch: [5] [ 820/1319] eta: 0:22:34 lr: 4.3627822934153263e-05 loss: 0.1010 (0.1265) time: 2.7323 data: 0.0065 max mem: 33368 +Epoch: [5] [ 830/1319] eta: 0:22:07 lr: 4.361916347013505e-05 loss: 0.0998 (0.1262) time: 2.7299 data: 0.0063 max mem: 33368 +Epoch: [5] [ 840/1319] eta: 0:21:40 lr: 4.361050381509995e-05 loss: 0.0990 (0.1259) time: 2.7022 data: 0.0063 max mem: 33368 +Epoch: [5] [ 850/1319] eta: 0:21:12 lr: 4.3601843969001596e-05 loss: 0.1159 (0.1261) time: 2.6975 data: 0.0064 max mem: 33368 +Epoch: [5] [ 860/1319] eta: 0:20:45 lr: 4.359318393179363e-05 loss: 0.1332 (0.1263) time: 2.7010 data: 0.0064 max mem: 33368 +Epoch: [5] [ 870/1319] eta: 0:20:18 lr: 4.3584523703429616e-05 loss: 0.1360 (0.1266) time: 2.7157 data: 0.0063 max mem: 33368 +Epoch: [5] [ 880/1319] eta: 0:19:51 lr: 4.357586328386315e-05 loss: 0.1180 (0.1264) time: 2.6994 data: 0.0063 max mem: 33368 +Epoch: [5] [ 890/1319] eta: 0:19:23 lr: 4.356720267304778e-05 loss: 0.0984 (0.1262) time: 2.6725 data: 0.0063 max mem: 33368 +Epoch: [5] [ 900/1319] eta: 0:18:56 lr: 4.3558541870937056e-05 loss: 0.1021 (0.1261) time: 2.6669 data: 0.0064 max mem: 33368 +Epoch: [5] [ 910/1319] eta: 0:18:29 lr: 4.354988087748445e-05 loss: 0.1049 (0.1258) time: 2.6826 data: 0.0064 max mem: 33368 +Epoch: [5] [ 920/1319] eta: 0:18:01 lr: 4.35412196926435e-05 loss: 0.1068 (0.1258) time: 2.6692 data: 0.0064 max mem: 33368 +Epoch: [5] [ 930/1319] eta: 0:17:34 lr: 4.353255831636764e-05 loss: 0.1311 (0.1260) time: 2.6517 data: 0.0066 max mem: 33368 +Epoch: [5] [ 940/1319] eta: 0:17:07 lr: 4.352389674861032e-05 loss: 0.1311 (0.1261) time: 2.6465 data: 0.0065 max mem: 33368 +Epoch: [5] [ 950/1319] eta: 0:16:39 lr: 4.3515234989324975e-05 loss: 0.1165 (0.1261) time: 2.6294 data: 0.0066 max mem: 33368 +Epoch: [5] [ 960/1319] eta: 0:16:12 lr: 4.350657303846501e-05 loss: 0.1165 (0.1261) time: 2.6229 data: 0.0066 max mem: 33368 +Epoch: [5] [ 970/1319] eta: 0:15:45 lr: 4.34979108959838e-05 loss: 0.1048 (0.1259) time: 2.6469 data: 0.0065 max mem: 33368 +Epoch: [5] [ 980/1319] eta: 0:15:17 lr: 4.348924856183469e-05 loss: 0.1163 (0.1261) time: 2.6544 data: 0.0064 max mem: 33368 +Epoch: [5] [ 990/1319] eta: 0:14:50 lr: 4.348058603597104e-05 loss: 0.1343 (0.1262) time: 2.6739 data: 0.0065 max mem: 33368 +Epoch: [5] [1000/1319] eta: 0:14:23 lr: 4.347192331834616e-05 loss: 0.1343 (0.1265) time: 2.6822 data: 0.0065 max mem: 33368 +Epoch: [5] [1010/1319] eta: 0:13:56 lr: 4.346326040891335e-05 loss: 0.1517 (0.1268) time: 2.6771 data: 0.0064 max mem: 33368 +Epoch: [5] [1020/1319] eta: 0:13:29 lr: 4.345459730762588e-05 loss: 0.1487 (0.1268) time: 2.6723 data: 0.0066 max mem: 33368 +Epoch: [5] [1030/1319] eta: 0:13:02 lr: 4.344593401443699e-05 loss: 0.1175 (0.1268) time: 2.6803 data: 0.0066 max mem: 33368 +Epoch: [5] [1040/1319] eta: 0:12:34 lr: 4.343727052929992e-05 loss: 0.1175 (0.1268) time: 2.6897 data: 0.0064 max mem: 33368 +Epoch: [5] [1050/1319] eta: 0:12:07 lr: 4.342860685216788e-05 loss: 0.1177 (0.1267) time: 2.6928 data: 0.0062 max mem: 33368 +Epoch: [5] [1060/1319] eta: 0:11:40 lr: 4.341994298299405e-05 loss: 0.1193 (0.1266) time: 2.6915 data: 0.0064 max mem: 33368 +Epoch: [5] [1070/1319] eta: 0:11:13 lr: 4.341127892173159e-05 loss: 0.1245 (0.1267) time: 2.6974 data: 0.0066 max mem: 33368 +Epoch: [5] [1080/1319] eta: 0:10:46 lr: 4.3402614668333656e-05 loss: 0.1250 (0.1266) time: 2.7252 data: 0.0066 max mem: 33368 +Epoch: [5] [1090/1319] eta: 0:10:19 lr: 4.339395022275336e-05 loss: 0.1238 (0.1266) time: 2.7140 data: 0.0068 max mem: 33368 +Epoch: [5] [1100/1319] eta: 0:09:52 lr: 4.33852855849438e-05 loss: 0.1080 (0.1264) time: 2.7248 data: 0.0067 max mem: 33368 +Epoch: [5] [1110/1319] eta: 0:09:25 lr: 4.337662075485806e-05 loss: 0.0952 (0.1263) time: 2.7354 data: 0.0064 max mem: 33368 +Epoch: [5] [1120/1319] eta: 0:08:58 lr: 4.3367955732449175e-05 loss: 0.1126 (0.1262) time: 2.7264 data: 0.0063 max mem: 33368 +Epoch: [5] [1130/1319] eta: 0:08:31 lr: 4.3359290517670206e-05 loss: 0.1186 (0.1262) time: 2.7127 data: 0.0061 max mem: 33368 +Epoch: [5] [1140/1319] eta: 0:08:04 lr: 4.335062511047415e-05 loss: 0.1282 (0.1261) time: 2.6902 data: 0.0061 max mem: 33368 +Epoch: [5] [1150/1319] eta: 0:07:37 lr: 4.3341959510813994e-05 loss: 0.1190 (0.1260) time: 2.7051 data: 0.0062 max mem: 33368 +Epoch: [5] [1160/1319] eta: 0:07:10 lr: 4.33332937186427e-05 loss: 0.1011 (0.1258) time: 2.7456 data: 0.0063 max mem: 33368 +Epoch: [5] [1170/1319] eta: 0:06:43 lr: 4.332462773391324e-05 loss: 0.1081 (0.1258) time: 2.7305 data: 0.0063 max mem: 33368 +Epoch: [5] [1180/1319] eta: 0:06:16 lr: 4.331596155657851e-05 loss: 0.1318 (0.1259) time: 2.7209 data: 0.0061 max mem: 33368 +Epoch: [5] [1190/1319] eta: 0:05:49 lr: 4.3307295186591415e-05 loss: 0.1359 (0.1260) time: 2.7214 data: 0.0064 max mem: 33368 +Epoch: [5] [1200/1319] eta: 0:05:22 lr: 4.329862862390485e-05 loss: 0.1397 (0.1262) time: 2.6867 data: 0.0066 max mem: 33368 +Epoch: [5] [1210/1319] eta: 0:04:55 lr: 4.328996186847165e-05 loss: 0.1222 (0.1262) time: 2.6795 data: 0.0065 max mem: 33368 +Epoch: [5] [1220/1319] eta: 0:04:27 lr: 4.328129492024467e-05 loss: 0.1096 (0.1261) time: 2.6833 data: 0.0064 max mem: 33368 +Epoch: [5] [1230/1319] eta: 0:04:00 lr: 4.3272627779176715e-05 loss: 0.1098 (0.1261) time: 2.7258 data: 0.0064 max mem: 33368 +Epoch: [5] [1240/1319] eta: 0:03:33 lr: 4.326396044522058e-05 loss: 0.1186 (0.1262) time: 2.7286 data: 0.0063 max mem: 33368 +Epoch: [5] [1250/1319] eta: 0:03:06 lr: 4.3255292918329036e-05 loss: 0.1358 (0.1263) time: 2.7013 data: 0.0063 max mem: 33368 +Epoch: [5] [1260/1319] eta: 0:02:39 lr: 4.324662519845482e-05 loss: 0.1222 (0.1263) time: 2.7061 data: 0.0063 max mem: 33368 +Epoch: [5] [1270/1319] eta: 0:02:12 lr: 4.323795728555066e-05 loss: 0.1181 (0.1263) time: 2.7227 data: 0.0062 max mem: 33368 +Epoch: [5] [1280/1319] eta: 0:01:45 lr: 4.322928917956926e-05 loss: 0.1247 (0.1264) time: 2.7458 data: 0.0062 max mem: 33368 +Epoch: [5] [1290/1319] eta: 0:01:18 lr: 4.322062088046332e-05 loss: 0.1262 (0.1263) time: 2.7227 data: 0.0064 max mem: 33368 +Epoch: [5] [1300/1319] eta: 0:00:51 lr: 4.321195238818547e-05 loss: 0.1262 (0.1264) time: 2.6815 data: 0.0064 max mem: 33368 +Epoch: [5] [1310/1319] eta: 0:00:24 lr: 4.3203283702688355e-05 loss: 0.1043 (0.1262) time: 2.7079 data: 0.0062 max mem: 33368 +Epoch: [5] Total time: 0:59:31 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 2:01:47 time: 2.8402 data: 2.7605 max mem: 33368 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 100/2573] eta: 0:04:06 time: 0.0722 data: 0.0012 max mem: 33368 +Test: [ 200/2573] eta: 0:03:26 time: 0.0737 data: 0.0012 max mem: 33368 +Test: [ 300/2573] eta: 0:03:06 time: 0.0753 data: 0.0012 max mem: 33368 +Test: [ 400/2573] eta: 0:02:53 time: 0.0751 data: 0.0012 max mem: 33368 +Test: [ 500/2573] eta: 0:02:43 time: 0.0736 data: 0.0012 max mem: 33368 +Test: [ 600/2573] eta: 0:02:33 time: 0.0739 data: 0.0012 max mem: 33368 +Test: [ 700/2573] eta: 0:02:25 time: 0.0740 data: 0.0012 max mem: 33368 +Test: [ 800/2573] eta: 0:02:17 time: 0.0772 data: 0.0011 max mem: 33368 +Test: [ 900/2573] eta: 0:02:09 time: 0.0742 data: 0.0011 max mem: 33368 +Test: [1000/2573] eta: 0:02:00 time: 0.0737 data: 0.0012 max mem: 33368 +Test: [1100/2573] eta: 0:01:52 time: 0.0738 data: 0.0012 max mem: 33368 +Test: [1200/2573] eta: 0:01:44 time: 0.0739 data: 0.0011 max mem: 33368 +Test: [1300/2573] eta: 0:01:37 time: 0.0739 data: 0.0012 max mem: 33368 +Test: [1400/2573] eta: 0:01:29 time: 0.0726 data: 0.0012 max mem: 33368 +Test: [1500/2573] eta: 0:01:21 time: 0.0741 data: 0.0012 max mem: 33368 +Test: [1600/2573] eta: 0:01:13 time: 0.0776 data: 0.0012 max mem: 33368 +Test: [1700/2573] eta: 0:01:06 time: 0.0723 data: 0.0011 max mem: 33368 +Test: [1800/2573] eta: 0:00:58 time: 0.0758 data: 0.0012 max mem: 33368 +Test: [1900/2573] eta: 0:00:50 time: 0.0724 data: 0.0012 max mem: 33368 +Test: [2000/2573] eta: 0:00:43 time: 0.0741 data: 0.0012 max mem: 33368 +Test: [2100/2573] eta: 0:00:35 time: 0.0760 data: 0.0012 max mem: 33368 +Test: [2200/2573] eta: 0:00:28 time: 0.0758 data: 0.0011 max mem: 33368 +Test: [2300/2573] eta: 0:00:20 time: 0.0760 data: 0.0012 max mem: 33368 +Test: [2400/2573] eta: 0:00:12 time: 0.0708 data: 0.0012 max mem: 33368 +Test: [2500/2573] eta: 0:00:05 time: 0.0741 data: 0.0012 max mem: 33368 +Test: Total time: 0:03:13 +Final results: +Mean IoU is 53.43 + + precision@0.5 = 59.74 + precision@0.6 = 52.61 + precision@0.7 = 42.69 + precision@0.8 = 30.31 + precision@0.9 = 12.34 + overall IoU = 54.26 + +Average object IoU 53.42531546888537 +Overall IoU 54.262733459472656 +Better epoch: 5 + +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [6] [ 0/1319] eta: 1:33:47 lr: 4.319548172049932e-05 loss: 0.0457 (0.0457) time: 4.2666 data: 1.2737 max mem: 33368 +Epoch: [6] [ 10/1319] eta: 1:02:16 lr: 4.318681266775505e-05 loss: 0.1308 (0.1219) time: 2.8548 data: 0.1215 max mem: 33368 +Epoch: [6] [ 20/1319] eta: 0:59:54 lr: 4.317814342165404e-05 loss: 0.1112 (0.1139) time: 2.6918 data: 0.0059 max mem: 33368 +Epoch: [6] [ 30/1319] eta: 0:58:49 lr: 4.316947398214883e-05 loss: 0.1042 (0.1144) time: 2.6741 data: 0.0060 max mem: 33368 +Epoch: [6] [ 40/1319] eta: 0:57:58 lr: 4.316080434919196e-05 loss: 0.1091 (0.1153) time: 2.6695 data: 0.0065 max mem: 33368 +Epoch: [6] [ 50/1319] eta: 0:57:36 lr: 4.315213452273593e-05 loss: 0.1033 (0.1113) time: 2.7008 data: 0.0066 max mem: 33368 +Epoch: [6] [ 60/1319] eta: 0:57:17 lr: 4.314346450273323e-05 loss: 0.0987 (0.1123) time: 2.7536 data: 0.0066 max mem: 33368 +Epoch: [6] [ 70/1319] eta: 0:56:53 lr: 4.313479428913631e-05 loss: 0.1042 (0.1126) time: 2.7556 data: 0.0064 max mem: 33368 +Epoch: [6] [ 80/1319] eta: 0:56:24 lr: 4.312612388189762e-05 loss: 0.1033 (0.1107) time: 2.7346 data: 0.0064 max mem: 33368 +Epoch: [6] [ 90/1319] eta: 0:55:57 lr: 4.311745328096956e-05 loss: 0.0954 (0.1102) time: 2.7311 data: 0.0062 max mem: 33368 +Epoch: [6] [ 100/1319] eta: 0:55:31 lr: 4.3108782486304546e-05 loss: 0.0940 (0.1085) time: 2.7398 data: 0.0062 max mem: 33368 +Epoch: [6] [ 110/1319] eta: 0:55:00 lr: 4.310011149785494e-05 loss: 0.0916 (0.1080) time: 2.7191 data: 0.0064 max mem: 33368 +Epoch: [6] [ 120/1319] eta: 0:54:33 lr: 4.309144031557308e-05 loss: 0.0933 (0.1075) time: 2.7141 data: 0.0064 max mem: 33368 +Epoch: [6] [ 130/1319] eta: 0:54:02 lr: 4.308276893941131e-05 loss: 0.1066 (0.1082) time: 2.7092 data: 0.0063 max mem: 33368 +Epoch: [6] [ 140/1319] eta: 0:53:36 lr: 4.307409736932192e-05 loss: 0.0993 (0.1081) time: 2.7160 data: 0.0064 max mem: 33368 +Epoch: [6] [ 150/1319] eta: 0:53:12 lr: 4.306542560525721e-05 loss: 0.0999 (0.1095) time: 2.7560 data: 0.0064 max mem: 33368 +Epoch: [6] [ 160/1319] eta: 0:52:41 lr: 4.305675364716942e-05 loss: 0.1056 (0.1094) time: 2.7255 data: 0.0065 max mem: 33368 +Epoch: [6] [ 170/1319] eta: 0:52:10 lr: 4.3048081495010805e-05 loss: 0.1133 (0.1107) time: 2.6785 data: 0.0067 max mem: 33368 +Epoch: [6] [ 180/1319] eta: 0:51:42 lr: 4.303940914873357e-05 loss: 0.1197 (0.1112) time: 2.6911 data: 0.0066 max mem: 33368 +Epoch: [6] [ 190/1319] eta: 0:51:14 lr: 4.30307366082899e-05 loss: 0.1053 (0.1115) time: 2.7143 data: 0.0063 max mem: 33368 +Epoch: [6] [ 200/1319] eta: 0:50:46 lr: 4.302206387363197e-05 loss: 0.1125 (0.1128) time: 2.7123 data: 0.0063 max mem: 33368 +Epoch: [6] [ 210/1319] eta: 0:50:16 lr: 4.301339094471194e-05 loss: 0.1287 (0.1137) time: 2.6852 data: 0.0065 max mem: 33368 +Epoch: [6] [ 220/1319] eta: 0:49:47 lr: 4.300471782148193e-05 loss: 0.1285 (0.1151) time: 2.6771 data: 0.0065 max mem: 33368 +Epoch: [6] [ 230/1319] eta: 0:49:17 lr: 4.299604450389403e-05 loss: 0.1068 (0.1150) time: 2.6719 data: 0.0065 max mem: 33368 +Epoch: [6] [ 240/1319] eta: 0:48:52 lr: 4.298737099190034e-05 loss: 0.1054 (0.1151) time: 2.7071 data: 0.0063 max mem: 33368 +Epoch: [6] [ 250/1319] eta: 0:48:26 lr: 4.297869728545289e-05 loss: 0.1054 (0.1148) time: 2.7519 data: 0.0063 max mem: 33368 +Epoch: [6] [ 260/1319] eta: 0:48:00 lr: 4.2970023384503735e-05 loss: 0.1090 (0.1148) time: 2.7562 data: 0.0063 max mem: 33368 +Epoch: [6] [ 270/1319] eta: 0:47:33 lr: 4.296134928900489e-05 loss: 0.1111 (0.1147) time: 2.7404 data: 0.0062 max mem: 33368 +Epoch: [6] [ 280/1319] eta: 0:47:06 lr: 4.295267499890832e-05 loss: 0.1083 (0.1146) time: 2.7264 data: 0.0064 max mem: 33368 +Epoch: [6] [ 290/1319] eta: 0:46:40 lr: 4.2944000514166015e-05 loss: 0.0970 (0.1149) time: 2.7392 data: 0.0063 max mem: 33368 +Epoch: [6] [ 300/1319] eta: 0:46:13 lr: 4.293532583472992e-05 loss: 0.0937 (0.1143) time: 2.7288 data: 0.0063 max mem: 33368 +Epoch: [6] [ 310/1319] eta: 0:45:45 lr: 4.292665096055194e-05 loss: 0.0898 (0.1139) time: 2.7114 data: 0.0067 max mem: 33368 +Epoch: [6] [ 320/1319] eta: 0:45:18 lr: 4.2917975891583976e-05 loss: 0.0946 (0.1132) time: 2.7198 data: 0.0066 max mem: 33368 +Epoch: [6] [ 330/1319] eta: 0:44:51 lr: 4.2909300627777926e-05 loss: 0.0946 (0.1132) time: 2.7373 data: 0.0064 max mem: 33368 +Epoch: [6] [ 340/1319] eta: 0:44:24 lr: 4.290062516908562e-05 loss: 0.1217 (0.1139) time: 2.7210 data: 0.0062 max mem: 33368 +Epoch: [6] [ 350/1319] eta: 0:43:56 lr: 4.2891949515458894e-05 loss: 0.1253 (0.1138) time: 2.7063 data: 0.0062 max mem: 33369 +Epoch: [6] [ 360/1319] eta: 0:43:29 lr: 4.288327366684957e-05 loss: 0.1100 (0.1142) time: 2.7153 data: 0.0062 max mem: 33369 +Epoch: [6] [ 370/1319] eta: 0:43:01 lr: 4.287459762320942e-05 loss: 0.1027 (0.1135) time: 2.7029 data: 0.0065 max mem: 33369 +Epoch: [6] [ 380/1319] eta: 0:42:32 lr: 4.28659213844902e-05 loss: 0.1034 (0.1136) time: 2.6661 data: 0.0068 max mem: 33369 +Epoch: [6] [ 390/1319] eta: 0:42:04 lr: 4.285724495064366e-05 loss: 0.1244 (0.1140) time: 2.6710 data: 0.0067 max mem: 33369 +Epoch: [6] [ 400/1319] eta: 0:41:37 lr: 4.2848568321621514e-05 loss: 0.1244 (0.1144) time: 2.7129 data: 0.0066 max mem: 33369 +Epoch: [6] [ 410/1319] eta: 0:41:10 lr: 4.283989149737546e-05 loss: 0.1147 (0.1142) time: 2.7282 data: 0.0066 max mem: 33369 +Epoch: [6] [ 420/1319] eta: 0:40:43 lr: 4.283121447785717e-05 loss: 0.1100 (0.1142) time: 2.7221 data: 0.0067 max mem: 33369 +Epoch: [6] [ 430/1319] eta: 0:40:16 lr: 4.2822537263018285e-05 loss: 0.1070 (0.1140) time: 2.7298 data: 0.0064 max mem: 33369 +Epoch: [6] [ 440/1319] eta: 0:39:49 lr: 4.281385985281043e-05 loss: 0.0914 (0.1135) time: 2.7262 data: 0.0063 max mem: 33369 +Epoch: [6] [ 450/1319] eta: 0:39:22 lr: 4.280518224718522e-05 loss: 0.0938 (0.1136) time: 2.7112 data: 0.0064 max mem: 33369 +Epoch: [6] [ 460/1319] eta: 0:38:54 lr: 4.2796504446094225e-05 loss: 0.1009 (0.1136) time: 2.6977 data: 0.0065 max mem: 33369 +Epoch: [6] [ 470/1319] eta: 0:38:26 lr: 4.278782644948901e-05 loss: 0.1046 (0.1136) time: 2.6776 data: 0.0065 max mem: 33369 +Epoch: [6] [ 480/1319] eta: 0:37:59 lr: 4.27791482573211e-05 loss: 0.1046 (0.1135) time: 2.6980 data: 0.0065 max mem: 33369 +Epoch: [6] [ 490/1319] eta: 0:37:31 lr: 4.2770469869541996e-05 loss: 0.0893 (0.1132) time: 2.7027 data: 0.0067 max mem: 33369 +Epoch: [6] [ 500/1319] eta: 0:37:04 lr: 4.276179128610321e-05 loss: 0.0867 (0.1128) time: 2.6917 data: 0.0064 max mem: 33369 +Epoch: [6] [ 510/1319] eta: 0:36:37 lr: 4.2753112506956194e-05 loss: 0.0969 (0.1127) time: 2.7228 data: 0.0063 max mem: 33369 +Epoch: [6] [ 520/1319] eta: 0:36:09 lr: 4.274443353205239e-05 loss: 0.1028 (0.1128) time: 2.7125 data: 0.0064 max mem: 33369 +Epoch: [6] [ 530/1319] eta: 0:35:42 lr: 4.2735754361343224e-05 loss: 0.0953 (0.1125) time: 2.7092 data: 0.0064 max mem: 33369 +Epoch: [6] [ 540/1319] eta: 0:35:15 lr: 4.2727074994780086e-05 loss: 0.0970 (0.1125) time: 2.7284 data: 0.0063 max mem: 33369 +Epoch: [6] [ 550/1319] eta: 0:34:49 lr: 4.271839543231435e-05 loss: 0.1028 (0.1124) time: 2.7337 data: 0.0062 max mem: 33369 +Epoch: [6] [ 560/1319] eta: 0:34:21 lr: 4.270971567389736e-05 loss: 0.1031 (0.1123) time: 2.7221 data: 0.0063 max mem: 33369 +Epoch: [6] [ 570/1319] eta: 0:33:55 lr: 4.270103571948045e-05 loss: 0.1050 (0.1127) time: 2.7290 data: 0.0063 max mem: 33369 +Epoch: [6] [ 580/1319] eta: 0:33:27 lr: 4.2692355569014936e-05 loss: 0.1172 (0.1129) time: 2.7163 data: 0.0064 max mem: 33369 +Epoch: [6] [ 590/1319] eta: 0:32:59 lr: 4.268367522245208e-05 loss: 0.1200 (0.1131) time: 2.6579 data: 0.0066 max mem: 33369 +Epoch: [6] [ 600/1319] eta: 0:32:31 lr: 4.267499467974314e-05 loss: 0.1200 (0.1132) time: 2.6529 data: 0.0066 max mem: 33369 +Epoch: [6] [ 610/1319] eta: 0:32:03 lr: 4.2666313940839357e-05 loss: 0.1128 (0.1134) time: 2.6458 data: 0.0066 max mem: 33369 +Epoch: [6] [ 620/1319] eta: 0:31:35 lr: 4.2657633005691946e-05 loss: 0.1002 (0.1132) time: 2.6344 data: 0.0067 max mem: 33369 +Epoch: [6] [ 630/1319] eta: 0:31:07 lr: 4.264895187425208e-05 loss: 0.1071 (0.1133) time: 2.6396 data: 0.0068 max mem: 33369 +Epoch: [6] [ 640/1319] eta: 0:30:39 lr: 4.264027054647094e-05 loss: 0.1086 (0.1133) time: 2.6521 data: 0.0067 max mem: 33369 +Epoch: [6] [ 650/1319] eta: 0:30:12 lr: 4.263158902229967e-05 loss: 0.1018 (0.1132) time: 2.6523 data: 0.0067 max mem: 33369 +Epoch: [6] [ 660/1319] eta: 0:29:44 lr: 4.262290730168937e-05 loss: 0.1051 (0.1132) time: 2.6341 data: 0.0069 max mem: 33369 +Epoch: [6] [ 670/1319] eta: 0:29:16 lr: 4.261422538459115e-05 loss: 0.1084 (0.1130) time: 2.6441 data: 0.0067 max mem: 33369 +Epoch: [6] [ 680/1319] eta: 0:28:49 lr: 4.260554327095607e-05 loss: 0.1084 (0.1131) time: 2.6622 data: 0.0067 max mem: 33369 +Epoch: [6] [ 690/1319] eta: 0:28:21 lr: 4.2596860960735204e-05 loss: 0.1060 (0.1130) time: 2.6522 data: 0.0068 max mem: 33369 +Epoch: [6] [ 700/1319] eta: 0:27:53 lr: 4.258817845387955e-05 loss: 0.0988 (0.1128) time: 2.6424 data: 0.0067 max mem: 33369 +Epoch: [6] [ 710/1319] eta: 0:27:26 lr: 4.257949575034011e-05 loss: 0.0924 (0.1131) time: 2.6480 data: 0.0067 max mem: 33369 +Epoch: [6] [ 720/1319] eta: 0:26:58 lr: 4.257081285006789e-05 loss: 0.1036 (0.1130) time: 2.6515 data: 0.0066 max mem: 33369 +Epoch: [6] [ 730/1319] eta: 0:26:31 lr: 4.256212975301382e-05 loss: 0.1106 (0.1133) time: 2.6581 data: 0.0067 max mem: 33369 +Epoch: [6] [ 740/1319] eta: 0:26:05 lr: 4.255344645912884e-05 loss: 0.1047 (0.1131) time: 2.7080 data: 0.0066 max mem: 33369 +Epoch: [6] [ 750/1319] eta: 0:25:38 lr: 4.254476296836386e-05 loss: 0.0964 (0.1129) time: 2.7497 data: 0.0066 max mem: 33369 +Epoch: [6] [ 760/1319] eta: 0:25:11 lr: 4.253607928066978e-05 loss: 0.0947 (0.1130) time: 2.7534 data: 0.0069 max mem: 33369 +Epoch: [6] [ 770/1319] eta: 0:24:44 lr: 4.252739539599743e-05 loss: 0.1264 (0.1136) time: 2.7549 data: 0.0068 max mem: 33369 +Epoch: [6] [ 780/1319] eta: 0:24:18 lr: 4.2518711314297674e-05 loss: 0.1264 (0.1138) time: 2.7598 data: 0.0065 max mem: 33369 +Epoch: [6] [ 790/1319] eta: 0:23:51 lr: 4.2510027035521314e-05 loss: 0.1073 (0.1140) time: 2.7492 data: 0.0064 max mem: 33369 +Epoch: [6] [ 800/1319] eta: 0:23:24 lr: 4.250134255961916e-05 loss: 0.1081 (0.1140) time: 2.7408 data: 0.0065 max mem: 33369 +Epoch: [6] [ 810/1319] eta: 0:22:58 lr: 4.2492657886541955e-05 loss: 0.1081 (0.1139) time: 2.7672 data: 0.0064 max mem: 33369 +Epoch: [6] [ 820/1319] eta: 0:22:31 lr: 4.2483973016240455e-05 loss: 0.1090 (0.1139) time: 2.7406 data: 0.0059 max mem: 33369 +Epoch: [6] [ 830/1319] eta: 0:22:03 lr: 4.247528794866539e-05 loss: 0.1072 (0.1141) time: 2.7041 data: 0.0057 max mem: 33369 +Epoch: [6] [ 840/1319] eta: 0:21:36 lr: 4.2466602683767445e-05 loss: 0.0978 (0.1140) time: 2.7128 data: 0.0058 max mem: 33369 +Epoch: [6] [ 850/1319] eta: 0:21:09 lr: 4.24579172214973e-05 loss: 0.1042 (0.1141) time: 2.7162 data: 0.0057 max mem: 33369 +Epoch: [6] [ 860/1319] eta: 0:20:42 lr: 4.244923156180561e-05 loss: 0.1052 (0.1142) time: 2.6990 data: 0.0059 max mem: 33369 +Epoch: [6] [ 870/1319] eta: 0:20:15 lr: 4.2440545704643e-05 loss: 0.0921 (0.1140) time: 2.6781 data: 0.0061 max mem: 33369 +Epoch: [6] [ 880/1319] eta: 0:19:48 lr: 4.243185964996007e-05 loss: 0.0997 (0.1141) time: 2.7167 data: 0.0059 max mem: 33369 +Epoch: [6] [ 890/1319] eta: 0:19:21 lr: 4.24231733977074e-05 loss: 0.1089 (0.1140) time: 2.7406 data: 0.0059 max mem: 33369 +Epoch: [6] [ 900/1319] eta: 0:18:54 lr: 4.2414486947835554e-05 loss: 0.0953 (0.1141) time: 2.7223 data: 0.0059 max mem: 33369 +Epoch: [6] [ 910/1319] eta: 0:18:27 lr: 4.240580030029505e-05 loss: 0.1063 (0.1140) time: 2.7318 data: 0.0058 max mem: 33369 +Epoch: [6] [ 920/1319] eta: 0:18:00 lr: 4.239711345503641e-05 loss: 0.1177 (0.1141) time: 2.7245 data: 0.0059 max mem: 33369 +Epoch: [6] [ 930/1319] eta: 0:17:33 lr: 4.2388426412010114e-05 loss: 0.1140 (0.1141) time: 2.7170 data: 0.0059 max mem: 33369 +Epoch: [6] [ 940/1319] eta: 0:17:06 lr: 4.237973917116662e-05 loss: 0.1001 (0.1140) time: 2.7120 data: 0.0059 max mem: 33369 +Epoch: [6] [ 950/1319] eta: 0:16:39 lr: 4.237105173245638e-05 loss: 0.1096 (0.1142) time: 2.7103 data: 0.0058 max mem: 33369 +Epoch: [6] [ 960/1319] eta: 0:16:12 lr: 4.23623640958298e-05 loss: 0.1098 (0.1141) time: 2.7177 data: 0.0058 max mem: 33369 +Epoch: [6] [ 970/1319] eta: 0:15:45 lr: 4.235367626123727e-05 loss: 0.0956 (0.1140) time: 2.6886 data: 0.0059 max mem: 33369 +Epoch: [6] [ 980/1319] eta: 0:15:17 lr: 4.234498822862916e-05 loss: 0.0979 (0.1140) time: 2.6585 data: 0.0058 max mem: 33369 +Epoch: [6] [ 990/1319] eta: 0:14:50 lr: 4.23362999979558e-05 loss: 0.1021 (0.1139) time: 2.6776 data: 0.0056 max mem: 33369 +Epoch: [6] [1000/1319] eta: 0:14:23 lr: 4.2327611569167524e-05 loss: 0.1041 (0.1140) time: 2.7099 data: 0.0058 max mem: 33369 +Epoch: [6] [1010/1319] eta: 0:13:56 lr: 4.2318922942214635e-05 loss: 0.0920 (0.1138) time: 2.7393 data: 0.0059 max mem: 33369 +Epoch: [6] [1020/1319] eta: 0:13:29 lr: 4.231023411704738e-05 loss: 0.0951 (0.1139) time: 2.7391 data: 0.0057 max mem: 33369 +Epoch: [6] [1030/1319] eta: 0:13:02 lr: 4.230154509361603e-05 loss: 0.1117 (0.1140) time: 2.7160 data: 0.0058 max mem: 33369 +Epoch: [6] [1040/1319] eta: 0:12:35 lr: 4.229285587187079e-05 loss: 0.1097 (0.1139) time: 2.7429 data: 0.0060 max mem: 33369 +Epoch: [6] [1050/1319] eta: 0:12:08 lr: 4.2284166451761876e-05 loss: 0.1033 (0.1141) time: 2.7783 data: 0.0062 max mem: 33369 +Epoch: [6] [1060/1319] eta: 0:11:41 lr: 4.2275476833239456e-05 loss: 0.0977 (0.1139) time: 2.7549 data: 0.0061 max mem: 33369 +Epoch: [6] [1070/1319] eta: 0:11:14 lr: 4.2266787016253686e-05 loss: 0.1050 (0.1138) time: 2.7427 data: 0.0059 max mem: 33369 +Epoch: [6] [1080/1319] eta: 0:10:47 lr: 4.22580970007547e-05 loss: 0.1099 (0.1137) time: 2.7376 data: 0.0059 max mem: 33369 +Epoch: [6] [1090/1319] eta: 0:10:20 lr: 4.224940678669259e-05 loss: 0.1021 (0.1137) time: 2.7073 data: 0.0059 max mem: 33369 +Epoch: [6] [1100/1319] eta: 0:09:53 lr: 4.2240716374017434e-05 loss: 0.1185 (0.1139) time: 2.7203 data: 0.0060 max mem: 33369 +Epoch: [6] [1110/1319] eta: 0:09:26 lr: 4.2232025762679314e-05 loss: 0.1185 (0.1138) time: 2.7357 data: 0.0060 max mem: 33369 +Epoch: [6] [1120/1319] eta: 0:08:59 lr: 4.2223334952628234e-05 loss: 0.0996 (0.1138) time: 2.7264 data: 0.0060 max mem: 33369 +Epoch: [6] [1130/1319] eta: 0:08:32 lr: 4.221464394381422e-05 loss: 0.0977 (0.1138) time: 2.7043 data: 0.0060 max mem: 33369 +Epoch: [6] [1140/1319] eta: 0:08:05 lr: 4.220595273618725e-05 loss: 0.0963 (0.1137) time: 2.7283 data: 0.0062 max mem: 33369 +Epoch: [6] [1150/1319] eta: 0:07:38 lr: 4.2197261329697285e-05 loss: 0.0958 (0.1137) time: 2.7504 data: 0.0061 max mem: 33369 +Epoch: [6] [1160/1319] eta: 0:07:11 lr: 4.218856972429426e-05 loss: 0.1019 (0.1136) time: 2.7027 data: 0.0059 max mem: 33369 +Epoch: [6] [1170/1319] eta: 0:06:43 lr: 4.2179877919928104e-05 loss: 0.1026 (0.1137) time: 2.6612 data: 0.0061 max mem: 33369 +Epoch: [6] [1180/1319] eta: 0:06:16 lr: 4.217118591654868e-05 loss: 0.1098 (0.1138) time: 2.6709 data: 0.0062 max mem: 33369 +Epoch: [6] [1190/1319] eta: 0:05:49 lr: 4.2162493714105874e-05 loss: 0.1091 (0.1138) time: 2.6873 data: 0.0061 max mem: 33369 +Epoch: [6] [1200/1319] eta: 0:05:22 lr: 4.2153801312549505e-05 loss: 0.0928 (0.1138) time: 2.6680 data: 0.0063 max mem: 33369 +Epoch: [6] [1210/1319] eta: 0:04:55 lr: 4.2145108711829405e-05 loss: 0.0828 (0.1136) time: 2.7012 data: 0.0062 max mem: 33369 +Epoch: [6] [1220/1319] eta: 0:04:28 lr: 4.213641591189537e-05 loss: 0.0834 (0.1134) time: 2.7255 data: 0.0061 max mem: 33369 +Epoch: [6] [1230/1319] eta: 0:04:01 lr: 4.212772291269716e-05 loss: 0.1085 (0.1135) time: 2.7078 data: 0.0062 max mem: 33369 +Epoch: [6] [1240/1319] eta: 0:03:34 lr: 4.2119029714184504e-05 loss: 0.1152 (0.1135) time: 2.6978 data: 0.0063 max mem: 33369 +Epoch: [6] [1250/1319] eta: 0:03:06 lr: 4.211033631630714e-05 loss: 0.1181 (0.1137) time: 2.7148 data: 0.0064 max mem: 33369 +Epoch: [6] [1260/1319] eta: 0:02:39 lr: 4.2101642719014764e-05 loss: 0.1184 (0.1136) time: 2.7985 data: 0.0064 max mem: 33369 +Epoch: [6] [1270/1319] eta: 0:02:12 lr: 4.2092948922257045e-05 loss: 0.1149 (0.1139) time: 2.7666 data: 0.0063 max mem: 33369 +Epoch: [6] [1280/1319] eta: 0:01:45 lr: 4.208425492598362e-05 loss: 0.1251 (0.1141) time: 2.6647 data: 0.0062 max mem: 33369 +Epoch: [6] [1290/1319] eta: 0:01:18 lr: 4.207556073014412e-05 loss: 0.1141 (0.1144) time: 2.6836 data: 0.0063 max mem: 33369 +Epoch: [6] [1300/1319] eta: 0:00:51 lr: 4.2066866334688144e-05 loss: 0.1141 (0.1144) time: 2.7034 data: 0.0063 max mem: 33369 +Epoch: [6] [1310/1319] eta: 0:00:24 lr: 4.205817173956526e-05 loss: 0.1153 (0.1145) time: 2.7235 data: 0.0061 max mem: 33369 +Epoch: [6] Total time: 0:59:35 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 2:01:22 time: 2.8305 data: 2.7499 max mem: 33369 +Test: [ 100/2573] eta: 0:04:06 time: 0.0718 data: 0.0012 max mem: 33369 +Test: [ 200/2573] eta: 0:03:26 time: 0.0734 data: 0.0012 max mem: 33369 +Test: [ 300/2573] eta: 0:03:06 time: 0.0748 data: 0.0011 max mem: 33369 +Test: [ 400/2573] eta: 0:02:53 time: 0.0750 data: 0.0011 max mem: 33369 +Test: [ 500/2573] eta: 0:02:42 time: 0.0737 data: 0.0012 max mem: 33369 +Test: [ 600/2573] eta: 0:02:33 time: 0.0737 data: 0.0012 max mem: 33369 +Test: [ 700/2573] eta: 0:02:25 time: 0.0738 data: 0.0012 max mem: 33369 +Test: [ 800/2573] eta: 0:02:16 time: 0.0771 data: 0.0011 max mem: 33369 +Test: [ 900/2573] eta: 0:02:08 time: 0.0737 data: 0.0011 max mem: 33369 +Test: [1000/2573] eta: 0:02:00 time: 0.0738 data: 0.0011 max mem: 33369 +Test: [1100/2573] eta: 0:01:52 time: 0.0738 data: 0.0012 max mem: 33369 +Test: [1200/2573] eta: 0:01:44 time: 0.0739 data: 0.0012 max mem: 33369 +Test: [1300/2573] eta: 0:01:36 time: 0.0736 data: 0.0011 max mem: 33369 +Test: [1400/2573] eta: 0:01:28 time: 0.0722 data: 0.0012 max mem: 33369 +Test: [1500/2573] eta: 0:01:21 time: 0.0740 data: 0.0012 max mem: 33369 +Test: [1600/2573] eta: 0:01:13 time: 0.0772 data: 0.0011 max mem: 33369 +Test: [1700/2573] eta: 0:01:06 time: 0.0722 data: 0.0011 max mem: 33369 +Test: [1800/2573] eta: 0:00:58 time: 0.0757 data: 0.0011 max mem: 33369 +Test: [1900/2573] eta: 0:00:50 time: 0.0723 data: 0.0012 max mem: 33369 +Test: [2000/2573] eta: 0:00:43 time: 0.0741 data: 0.0012 max mem: 33369 +Test: [2100/2573] eta: 0:00:35 time: 0.0756 data: 0.0011 max mem: 33369 +Test: [2200/2573] eta: 0:00:27 time: 0.0757 data: 0.0011 max mem: 33369 +Test: [2300/2573] eta: 0:00:20 time: 0.0755 data: 0.0011 max mem: 33369 +Test: [2400/2573] eta: 0:00:12 time: 0.0705 data: 0.0011 max mem: 33369 +Test: [2500/2573] eta: 0:00:05 time: 0.0739 data: 0.0011 max mem: 33369 +Test: Total time: 0:03:13 +Final results: +Mean IoU is 56.69 + + precision@0.5 = 63.24 + precision@0.6 = 55.94 + precision@0.7 = 46.71 + precision@0.8 = 33.86 + precision@0.9 = 14.28 + overall IoU = 56.41 + +Average object IoU 56.68927322756261 +Overall IoU 56.413028717041016 +Better epoch: 6 + +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [7] [ 0/1319] eta: 1:26:24 lr: 4.205034643319776e-05 loss: 0.0924 (0.0924) time: 3.9307 data: 1.1579 max mem: 33369 +Epoch: [7] [ 10/1319] eta: 1:01:10 lr: 4.204165145856875e-05 loss: 0.0924 (0.0916) time: 2.8041 data: 0.1110 max mem: 33369 +Epoch: [7] [ 20/1319] eta: 0:59:29 lr: 4.203295628412646e-05 loss: 0.0836 (0.0936) time: 2.6887 data: 0.0063 max mem: 33369 +Epoch: [7] [ 30/1319] eta: 0:59:01 lr: 4.202426090982037e-05 loss: 0.0915 (0.0938) time: 2.7169 data: 0.0064 max mem: 33369 +Epoch: [7] [ 40/1319] eta: 0:58:31 lr: 4.201556533559993e-05 loss: 0.0940 (0.0949) time: 2.7426 data: 0.0064 max mem: 33369 +Epoch: [7] [ 50/1319] eta: 0:57:48 lr: 4.2006869561414584e-05 loss: 0.0969 (0.0972) time: 2.7113 data: 0.0063 max mem: 33369 +Epoch: [7] [ 60/1319] eta: 0:57:05 lr: 4.199817358721372e-05 loss: 0.1034 (0.0970) time: 2.6698 data: 0.0065 max mem: 33369 +Epoch: [7] [ 70/1319] eta: 0:56:35 lr: 4.1989477412946735e-05 loss: 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4.1919900810347894e-05 loss: 0.0886 (0.1068) time: 2.6647 data: 0.0066 max mem: 33369 +Epoch: [7] [ 160/1319] eta: 0:52:17 lr: 4.191120283320388e-05 loss: 0.0882 (0.1071) time: 2.6869 data: 0.0068 max mem: 33369 +Epoch: [7] [ 170/1319] eta: 0:51:49 lr: 4.190250465548619e-05 loss: 0.0882 (0.1065) time: 2.6937 data: 0.0068 max mem: 33369 +Epoch: [7] [ 180/1319] eta: 0:51:26 lr: 4.189380627714394e-05 loss: 0.0970 (0.1070) time: 2.7259 data: 0.0066 max mem: 33369 +Epoch: [7] [ 190/1319] eta: 0:50:59 lr: 4.188510769812624e-05 loss: 0.0998 (0.1073) time: 2.7452 data: 0.0065 max mem: 33369 +Epoch: [7] [ 200/1319] eta: 0:50:31 lr: 4.1876408918382123e-05 loss: 0.1019 (0.1072) time: 2.7102 data: 0.0066 max mem: 33369 +Epoch: [7] [ 210/1319] eta: 0:50:04 lr: 4.1867709937860646e-05 loss: 0.0999 (0.1067) time: 2.7053 data: 0.0064 max mem: 33369 +Epoch: [7] [ 220/1319] eta: 0:49:36 lr: 4.185901075651081e-05 loss: 0.0867 (0.1060) time: 2.7017 data: 0.0063 max mem: 33369 +Epoch: [7] [ 230/1319] eta: 0:49:07 lr: 4.185031137428161e-05 loss: 0.0826 (0.1059) time: 2.6712 data: 0.0067 max mem: 33369 +Epoch: [7] [ 240/1319] eta: 0:48:40 lr: 4.1841611791121996e-05 loss: 0.0822 (0.1056) time: 2.6838 data: 0.0067 max mem: 33369 +Epoch: [7] [ 250/1319] eta: 0:48:14 lr: 4.183291200698093e-05 loss: 0.0927 (0.1056) time: 2.7218 data: 0.0066 max mem: 33369 +Epoch: [7] [ 260/1319] eta: 0:47:45 lr: 4.182421202180731e-05 loss: 0.0952 (0.1053) time: 2.6936 data: 0.0065 max mem: 33369 +Epoch: [7] [ 270/1319] eta: 0:47:17 lr: 4.181551183555002e-05 loss: 0.1007 (0.1057) time: 2.6706 data: 0.0065 max mem: 33369 +Epoch: [7] [ 280/1319] eta: 0:46:48 lr: 4.180681144815793e-05 loss: 0.1127 (0.1059) time: 2.6627 data: 0.0064 max mem: 33369 +Epoch: [7] [ 290/1319] eta: 0:46:20 lr: 4.179811085957988e-05 loss: 0.0937 (0.1057) time: 2.6606 data: 0.0067 max mem: 33369 +Epoch: [7] [ 300/1319] eta: 0:45:52 lr: 4.178941006976469e-05 loss: 0.0936 (0.1053) time: 2.6736 data: 0.0068 max mem: 33369 +Epoch: [7] [ 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+Epoch: [7] [ 390/1319] eta: 0:41:38 lr: 4.171109389729833e-05 loss: 0.0956 (0.1058) time: 2.6629 data: 0.0066 max mem: 33369 +Epoch: [7] [ 400/1319] eta: 0:41:09 lr: 4.1702391092290966e-05 loss: 0.0859 (0.1060) time: 2.6416 data: 0.0066 max mem: 33369 +Epoch: [7] [ 410/1319] eta: 0:40:42 lr: 4.169368808548177e-05 loss: 0.1097 (0.1062) time: 2.6258 data: 0.0067 max mem: 33369 +Epoch: [7] [ 420/1319] eta: 0:40:14 lr: 4.168498487681925e-05 loss: 0.1012 (0.1063) time: 2.6465 data: 0.0067 max mem: 33369 +Epoch: [7] [ 430/1319] eta: 0:39:47 lr: 4.1676281466251895e-05 loss: 0.0871 (0.1058) time: 2.6684 data: 0.0066 max mem: 33369 +Epoch: [7] [ 440/1319] eta: 0:39:21 lr: 4.166757785372817e-05 loss: 0.0902 (0.1056) time: 2.7093 data: 0.0065 max mem: 33369 +Epoch: [7] [ 450/1319] eta: 0:38:56 lr: 4.1658874039196515e-05 loss: 0.1036 (0.1058) time: 2.7526 data: 0.0064 max mem: 33369 +Epoch: [7] [ 460/1319] eta: 0:38:29 lr: 4.165017002260535e-05 loss: 0.1024 (0.1059) time: 2.7320 data: 0.0066 max mem: 33369 +Epoch: [7] [ 470/1319] eta: 0:38:02 lr: 4.164146580390306e-05 loss: 0.0993 (0.1060) time: 2.6939 data: 0.0067 max mem: 33369 +Epoch: [7] [ 480/1319] eta: 0:37:37 lr: 4.163276138303801e-05 loss: 0.1003 (0.1061) time: 2.7329 data: 0.0066 max mem: 33369 +Epoch: [7] [ 490/1319] eta: 0:37:10 lr: 4.1624056759958536e-05 loss: 0.1023 (0.1062) time: 2.7366 data: 0.0067 max mem: 33369 +Epoch: [7] [ 500/1319] eta: 0:36:44 lr: 4.161535193461295e-05 loss: 0.1143 (0.1063) time: 2.7120 data: 0.0067 max mem: 33369 +Epoch: [7] [ 510/1319] eta: 0:36:17 lr: 4.1606646906949546e-05 loss: 0.0907 (0.1060) time: 2.7253 data: 0.0068 max mem: 33369 +Epoch: [7] [ 520/1319] eta: 0:35:51 lr: 4.159794167691658e-05 loss: 0.0948 (0.1061) time: 2.7256 data: 0.0066 max mem: 33369 +Epoch: [7] [ 530/1319] eta: 0:35:25 lr: 4.158923624446229e-05 loss: 0.1047 (0.1063) time: 2.7261 data: 0.0066 max mem: 33369 +Epoch: [7] [ 540/1319] eta: 0:34:58 lr: 4.15805306095349e-05 loss: 0.0919 (0.1061) time: 2.7351 data: 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2.7094 data: 0.0064 max mem: 33369 +Epoch: [7] [ 630/1319] eta: 0:30:57 lr: 4.1502170775340975e-05 loss: 0.0970 (0.1062) time: 2.6775 data: 0.0065 max mem: 33369 +Epoch: [7] [ 640/1319] eta: 0:30:31 lr: 4.14934631128286e-05 loss: 0.1037 (0.1064) time: 2.6973 data: 0.0064 max mem: 33369 +Epoch: [7] [ 650/1319] eta: 0:30:04 lr: 4.148475524727178e-05 loss: 0.1087 (0.1064) time: 2.7352 data: 0.0065 max mem: 33369 +Epoch: [7] [ 660/1319] eta: 0:29:37 lr: 4.147604717861842e-05 loss: 0.0985 (0.1063) time: 2.7135 data: 0.0064 max mem: 33369 +Epoch: [7] [ 670/1319] eta: 0:29:11 lr: 4.14673389068164e-05 loss: 0.0966 (0.1063) time: 2.7340 data: 0.0062 max mem: 33369 +Epoch: [7] [ 680/1319] eta: 0:28:44 lr: 4.145863043181359e-05 loss: 0.1122 (0.1064) time: 2.7479 data: 0.0063 max mem: 33369 +Epoch: [7] [ 690/1319] eta: 0:28:17 lr: 4.144992175355781e-05 loss: 0.1022 (0.1062) time: 2.7388 data: 0.0062 max mem: 33369 +Epoch: [7] [ 700/1319] eta: 0:27:50 lr: 4.1441212871996857e-05 loss: 0.0916 (0.1060) time: 2.7022 data: 0.0064 max mem: 33369 +Epoch: [7] [ 710/1319] eta: 0:27:24 lr: 4.143250378707853e-05 loss: 0.1003 (0.1062) time: 2.7079 data: 0.0064 max mem: 33369 +Epoch: [7] [ 720/1319] eta: 0:26:57 lr: 4.142379449875057e-05 loss: 0.1003 (0.1062) time: 2.7347 data: 0.0062 max mem: 33369 +Epoch: [7] [ 730/1319] eta: 0:26:30 lr: 4.141508500696071e-05 loss: 0.0891 (0.1063) time: 2.7158 data: 0.0062 max mem: 33369 +Epoch: [7] [ 740/1319] eta: 0:26:02 lr: 4.140637531165665e-05 loss: 0.0994 (0.1064) time: 2.6799 data: 0.0063 max mem: 33369 +Epoch: [7] [ 750/1319] eta: 0:25:36 lr: 4.139766541278606e-05 loss: 0.1161 (0.1067) time: 2.6866 data: 0.0065 max mem: 33369 +Epoch: [7] [ 760/1319] eta: 0:25:09 lr: 4.138895531029661e-05 loss: 0.1083 (0.1066) time: 2.7200 data: 0.0063 max mem: 33369 +Epoch: [7] [ 770/1319] eta: 0:24:42 lr: 4.138024500413592e-05 loss: 0.1037 (0.1067) time: 2.6901 data: 0.0060 max mem: 33369 +Epoch: [7] [ 780/1319] eta: 0:24:14 lr: 4.137153449425158e-05 loss: 0.0964 (0.1068) time: 2.6497 data: 0.0064 max mem: 33369 +Epoch: [7] [ 790/1319] eta: 0:23:47 lr: 4.136282378059117e-05 loss: 0.0944 (0.1066) time: 2.6638 data: 0.0063 max mem: 33369 +Epoch: [7] [ 800/1319] eta: 0:23:20 lr: 4.1354112863102244e-05 loss: 0.0935 (0.1067) time: 2.6877 data: 0.0062 max mem: 33369 +Epoch: [7] [ 810/1319] eta: 0:22:53 lr: 4.134540174173232e-05 loss: 0.0948 (0.1067) time: 2.6947 data: 0.0063 max mem: 33369 +Epoch: [7] [ 820/1319] eta: 0:22:26 lr: 4.1336690416428894e-05 loss: 0.0836 (0.1065) time: 2.7139 data: 0.0062 max mem: 33369 +Epoch: [7] [ 830/1319] eta: 0:21:59 lr: 4.132797888713944e-05 loss: 0.0904 (0.1064) time: 2.6944 data: 0.0063 max mem: 33369 +Epoch: [7] [ 840/1319] eta: 0:21:32 lr: 4.13192671538114e-05 loss: 0.0993 (0.1065) time: 2.6777 data: 0.0062 max mem: 33369 +Epoch: [7] [ 850/1319] eta: 0:21:05 lr: 4.1310555216392185e-05 loss: 0.1106 (0.1068) time: 2.6617 data: 0.0064 max mem: 33369 +Epoch: [7] [ 860/1319] eta: 0:20:38 lr: 4.130184307482921e-05 loss: 0.1143 (0.1068) time: 2.6797 data: 0.0064 max mem: 33369 +Epoch: [7] [ 870/1319] eta: 0:20:11 lr: 4.1293130729069835e-05 loss: 0.0924 (0.1067) time: 2.7403 data: 0.0064 max mem: 33369 +Epoch: [7] [ 880/1319] eta: 0:19:44 lr: 4.128441817906139e-05 loss: 0.0943 (0.1068) time: 2.7426 data: 0.0064 max mem: 33369 +Epoch: [7] [ 890/1319] eta: 0:19:17 lr: 4.1275705424751206e-05 loss: 0.0943 (0.1067) time: 2.7287 data: 0.0062 max mem: 33369 +Epoch: [7] [ 900/1319] eta: 0:18:50 lr: 4.1266992466086555e-05 loss: 0.0908 (0.1065) time: 2.7075 data: 0.0063 max mem: 33369 +Epoch: [7] [ 910/1319] eta: 0:18:24 lr: 4.125827930301473e-05 loss: 0.0946 (0.1065) time: 2.7326 data: 0.0064 max mem: 33369 +Epoch: [7] [ 920/1319] eta: 0:17:57 lr: 4.124956593548294e-05 loss: 0.1014 (0.1067) time: 2.7921 data: 0.0064 max mem: 33369 +Epoch: [7] [ 930/1319] eta: 0:17:30 lr: 4.124085236343841e-05 loss: 0.1014 (0.1067) time: 2.7843 data: 0.0062 max mem: 33369 +Epoch: [7] [ 940/1319] eta: 0:17:03 lr: 4.123213858682832e-05 loss: 0.0928 (0.1065) time: 2.7366 data: 0.0063 max mem: 33369 +Epoch: [7] [ 950/1319] eta: 0:16:36 lr: 4.122342460559985e-05 loss: 0.0943 (0.1065) time: 2.7051 data: 0.0063 max mem: 33369 +Epoch: [7] [ 960/1319] eta: 0:16:10 lr: 4.12147104197001e-05 loss: 0.0980 (0.1066) time: 2.7128 data: 0.0064 max mem: 33369 +Epoch: [7] [ 970/1319] eta: 0:15:43 lr: 4.12059960290762e-05 loss: 0.0967 (0.1065) time: 2.7280 data: 0.0065 max mem: 33369 +Epoch: [7] [ 980/1319] eta: 0:15:16 lr: 4.119728143367523e-05 loss: 0.0933 (0.1067) time: 2.7422 data: 0.0063 max mem: 33369 +Epoch: [7] [ 990/1319] eta: 0:14:49 lr: 4.1188566633444246e-05 loss: 0.1040 (0.1067) time: 2.7311 data: 0.0062 max mem: 33369 +Epoch: [7] [1000/1319] eta: 0:14:22 lr: 4.1179851628330275e-05 loss: 0.1019 (0.1066) time: 2.7143 data: 0.0064 max mem: 33369 +Epoch: [7] [1010/1319] eta: 0:13:55 lr: 4.117113641828032e-05 loss: 0.1051 (0.1067) time: 2.7153 data: 0.0065 max mem: 33369 +Epoch: [7] [1020/1319] eta: 0:13:28 lr: 4.116242100324135e-05 loss: 0.1051 (0.1066) time: 2.7113 data: 0.0064 max mem: 33369 +Epoch: [7] [1030/1319] eta: 0:13:01 lr: 4.1153705383160326e-05 loss: 0.0844 (0.1064) time: 2.7178 data: 0.0062 max mem: 33369 +Epoch: [7] [1040/1319] eta: 0:12:34 lr: 4.114498955798418e-05 loss: 0.0833 (0.1064) time: 2.7222 data: 0.0062 max mem: 33369 +Epoch: [7] [1050/1319] eta: 0:12:07 lr: 4.113627352765979e-05 loss: 0.1091 (0.1064) time: 2.7224 data: 0.0063 max mem: 33369 +Epoch: [7] [1060/1319] eta: 0:11:40 lr: 4.1127557292134045e-05 loss: 0.0987 (0.1064) time: 2.7527 data: 0.0063 max mem: 33369 +Epoch: [7] [1070/1319] eta: 0:11:13 lr: 4.111884085135378e-05 loss: 0.0953 (0.1064) time: 2.7384 data: 0.0063 max mem: 33369 +Epoch: [7] [1080/1319] eta: 0:10:46 lr: 4.111012420526582e-05 loss: 0.0946 (0.1063) time: 2.7056 data: 0.0064 max mem: 33369 +Epoch: [7] [1090/1319] eta: 0:10:19 lr: 4.110140735381696e-05 loss: 0.0947 (0.1063) time: 2.7181 data: 0.0064 max mem: 33369 +Epoch: [7] [1100/1319] eta: 0:09:52 lr: 4.109269029695397e-05 loss: 0.1050 (0.1064) time: 2.7316 data: 0.0064 max mem: 33369 +Epoch: [7] [1110/1319] eta: 0:09:25 lr: 4.108397303462358e-05 loss: 0.0896 (0.1063) time: 2.7524 data: 0.0065 max mem: 33369 +Epoch: [7] [1120/1319] eta: 0:08:58 lr: 4.1075255566772506e-05 loss: 0.0942 (0.1063) time: 2.7213 data: 0.0064 max mem: 33369 +Epoch: [7] [1130/1319] eta: 0:08:31 lr: 4.106653789334745e-05 loss: 0.1018 (0.1064) time: 2.7090 data: 0.0063 max mem: 33369 +Epoch: [7] [1140/1319] eta: 0:08:04 lr: 4.105782001429505e-05 loss: 0.1144 (0.1066) time: 2.7186 data: 0.0065 max mem: 33369 +Epoch: [7] [1150/1319] eta: 0:07:37 lr: 4.104910192956196e-05 loss: 0.1093 (0.1065) time: 2.7203 data: 0.0064 max mem: 33369 +Epoch: [7] [1160/1319] eta: 0:07:10 lr: 4.104038363909479e-05 loss: 0.0862 (0.1064) time: 2.7352 data: 0.0064 max mem: 33369 +Epoch: [7] [1170/1319] eta: 0:06:43 lr: 4.1031665142840106e-05 loss: 0.0862 (0.1063) time: 2.7179 data: 0.0065 max mem: 33369 +Epoch: [7] [1180/1319] eta: 0:06:16 lr: 4.1022946440744476e-05 loss: 0.0939 (0.1064) time: 2.7209 data: 0.0066 max mem: 33369 +Epoch: [7] [1190/1319] eta: 0:05:49 lr: 4.1014227532754415e-05 loss: 0.1028 (0.1064) time: 2.6958 data: 0.0065 max mem: 33369 +Epoch: [7] [1200/1319] eta: 0:05:21 lr: 4.100550841881645e-05 loss: 0.0995 (0.1065) time: 2.6683 data: 0.0063 max mem: 33369 +Epoch: [7] [1210/1319] eta: 0:04:54 lr: 4.099678909887704e-05 loss: 0.1001 (0.1065) time: 2.6831 data: 0.0065 max mem: 33369 +Epoch: [7] [1220/1319] eta: 0:04:27 lr: 4.098806957288263e-05 loss: 0.1054 (0.1065) time: 2.6907 data: 0.0066 max mem: 33369 +Epoch: [7] [1230/1319] eta: 0:04:00 lr: 4.0979349840779665e-05 loss: 0.0933 (0.1064) time: 2.6961 data: 0.0067 max mem: 33369 +Epoch: [7] [1240/1319] eta: 0:03:33 lr: 4.0970629902514516e-05 loss: 0.0910 (0.1065) time: 2.7170 data: 0.0065 max mem: 33369 +Epoch: [7] [1250/1319] eta: 0:03:06 lr: 4.0961909758033565e-05 loss: 0.1012 (0.1065) time: 2.7159 data: 0.0063 max mem: 33369 +Epoch: [7] [1260/1319] eta: 0:02:39 lr: 4.095318940728316e-05 loss: 0.0957 (0.1065) time: 2.7019 data: 0.0064 max mem: 33369 +Epoch: [7] [1270/1319] eta: 0:02:12 lr: 4.0944468850209605e-05 loss: 0.0966 (0.1065) time: 2.7046 data: 0.0065 max mem: 33369 +Epoch: [7] [1280/1319] eta: 0:01:45 lr: 4.093574808675919e-05 loss: 0.0932 (0.1064) time: 2.6889 data: 0.0063 max mem: 33369 +Epoch: [7] [1290/1319] eta: 0:01:18 lr: 4.09270271168782e-05 loss: 0.0900 (0.1064) time: 2.7094 data: 0.0061 max mem: 33369 +Epoch: [7] [1300/1319] eta: 0:00:51 lr: 4.091830594051285e-05 loss: 0.1041 (0.1065) time: 2.6835 data: 0.0063 max mem: 33369 +Epoch: [7] [1310/1319] eta: 0:00:24 lr: 4.090958455760934e-05 loss: 0.0990 (0.1065) time: 2.6634 data: 0.0063 max mem: 33369 +Epoch: [7] Total time: 0:59:28 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 1:48:22 time: 2.5271 data: 2.4478 max mem: 33369 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 100/2573] eta: 0:04:03 time: 0.0719 data: 0.0012 max mem: 33369 +Test: [ 200/2573] eta: 0:03:25 time: 0.0737 data: 0.0011 max mem: 33369 +Test: [ 300/2573] eta: 0:03:05 time: 0.0752 data: 0.0012 max mem: 33369 +Test: [ 400/2573] eta: 0:02:52 time: 0.0753 data: 0.0011 max mem: 33369 +Test: [ 500/2573] eta: 0:02:42 time: 0.0737 data: 0.0012 max mem: 33369 +Test: [ 600/2573] eta: 0:02:33 time: 0.0738 data: 0.0012 max mem: 33369 +Test: [ 700/2573] eta: 0:02:25 time: 0.0738 data: 0.0011 max mem: 33369 +Test: [ 800/2573] eta: 0:02:16 time: 0.0772 data: 0.0012 max mem: 33369 +Test: [ 900/2573] eta: 0:02:08 time: 0.0738 data: 0.0011 max mem: 33369 +Test: [1000/2573] eta: 0:02:00 time: 0.0738 data: 0.0011 max mem: 33369 +Test: [1100/2573] eta: 0:01:52 time: 0.0740 data: 0.0012 max mem: 33369 +Test: [1200/2573] eta: 0:01:44 time: 0.0741 data: 0.0012 max mem: 33369 +Test: [1300/2573] eta: 0:01:36 time: 0.0742 data: 0.0012 max mem: 33369 +Test: [1400/2573] eta: 0:01:29 time: 0.0725 data: 0.0012 max mem: 33369 +Test: [1500/2573] eta: 0:01:21 time: 0.0742 data: 0.0012 max mem: 33369 +Test: [1600/2573] eta: 0:01:13 time: 0.0775 data: 0.0012 max mem: 33369 +Test: [1700/2573] eta: 0:01:06 time: 0.0724 data: 0.0011 max mem: 33369 +Test: [1800/2573] eta: 0:00:58 time: 0.0759 data: 0.0012 max mem: 33369 +Test: [1900/2573] eta: 0:00:50 time: 0.0728 data: 0.0012 max mem: 33369 +Test: [2000/2573] eta: 0:00:43 time: 0.0743 data: 0.0012 max mem: 33369 +Test: [2100/2573] eta: 0:00:35 time: 0.0760 data: 0.0012 max mem: 33369 +Test: [2200/2573] eta: 0:00:28 time: 0.0758 data: 0.0012 max mem: 33369 +Test: [2300/2573] eta: 0:00:20 time: 0.0762 data: 0.0012 max mem: 33369 +Test: [2400/2573] eta: 0:00:12 time: 0.0711 data: 0.0012 max mem: 33369 +Test: [2500/2573] eta: 0:00:05 time: 0.0744 data: 0.0012 max mem: 33369 +Test: Total time: 0:03:13 +Final results: +Mean IoU is 58.02 + + precision@0.5 = 64.89 + precision@0.6 = 57.88 + precision@0.7 = 48.90 + precision@0.8 = 36.46 + precision@0.9 = 15.42 + overall IoU = 56.92 + +Average object IoU 58.024384291269094 +Overall IoU 56.92463684082031 +Better epoch: 7 + +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [8] [ 0/1319] eta: 1:31:25 lr: 4.09017351363616e-05 loss: 0.0959 (0.0959) time: 4.1591 data: 1.4596 max mem: 33369 +Epoch: [8] [ 10/1319] eta: 1:00:44 lr: 4.089301336088734e-05 loss: 0.0873 (0.0832) time: 2.7842 data: 0.1384 max mem: 33369 +Epoch: [8] [ 20/1319] eta: 0:59:06 lr: 4.088429137871879e-05 loss: 0.0832 (0.0872) time: 2.6583 data: 0.0061 max mem: 33369 +Epoch: [8] [ 30/1319] eta: 0:58:12 lr: 4.087556918980205e-05 loss: 0.0832 (0.0968) time: 2.6684 data: 0.0061 max mem: 33369 +Epoch: [8] [ 40/1319] eta: 0:57:29 lr: 4.0866846794083216e-05 loss: 0.0743 (0.0903) time: 2.6619 data: 0.0065 max mem: 33369 +Epoch: [8] [ 50/1319] eta: 0:56:49 lr: 4.0858124191508315e-05 loss: 0.0694 (0.0899) time: 2.6522 data: 0.0067 max mem: 33369 +Epoch: [8] [ 60/1319] eta: 0:56:12 lr: 4.08494013820234e-05 loss: 0.0820 (0.0935) time: 2.6428 data: 0.0067 max mem: 33369 +Epoch: [8] [ 70/1319] eta: 0:55:42 lr: 4.0840678365574436e-05 loss: 0.0993 (0.0976) time: 2.6483 data: 0.0066 max mem: 33369 +Epoch: [8] [ 80/1319] eta: 0:55:15 lr: 4.083195514210742e-05 loss: 0.0885 (0.0957) time: 2.6652 data: 0.0066 max mem: 33369 +Epoch: [8] [ 90/1319] eta: 0:54:46 lr: 4.0823231711568287e-05 loss: 0.0810 (0.0948) time: 2.6674 data: 0.0066 max mem: 33369 +Epoch: [8] [ 100/1319] eta: 0:54:14 lr: 4.081450807390295e-05 loss: 0.0877 (0.0953) time: 2.6458 data: 0.0065 max mem: 33369 +Epoch: [8] [ 110/1319] eta: 0:53:46 lr: 4.0805784229057304e-05 loss: 0.0811 (0.0939) time: 2.6429 data: 0.0065 max mem: 33369 +Epoch: [8] [ 120/1319] eta: 0:53:18 lr: 4.079706017697721e-05 loss: 0.0779 (0.0946) time: 2.6594 data: 0.0067 max mem: 33369 +Epoch: [8] [ 130/1319] eta: 0:53:00 lr: 4.0788335917608504e-05 loss: 0.0924 (0.0944) time: 2.7119 data: 0.0066 max mem: 33369 +Epoch: [8] [ 140/1319] eta: 0:52:38 lr: 4.077961145089699e-05 loss: 0.0900 (0.0950) time: 2.7426 data: 0.0063 max mem: 33369 +Epoch: [8] [ 150/1319] eta: 0:52:12 lr: 4.0770886776788466e-05 loss: 0.0940 (0.0957) time: 2.7109 data: 0.0063 max mem: 33369 +Epoch: [8] [ 160/1319] eta: 0:51:47 lr: 4.076216189522867e-05 loss: 0.1028 (0.0967) time: 2.7007 data: 0.0062 max mem: 33369 +Epoch: [8] [ 170/1319] eta: 0:51:25 lr: 4.075343680616333e-05 loss: 0.0861 (0.0961) time: 2.7287 data: 0.0062 max mem: 33369 +Epoch: [8] [ 180/1319] eta: 0:50:59 lr: 4.074471150953815e-05 loss: 0.0740 (0.0952) time: 2.7222 data: 0.0063 max mem: 33369 +Epoch: [8] [ 190/1319] eta: 0:50:32 lr: 4.0735986005298814e-05 loss: 0.0709 (0.0949) time: 2.6907 data: 0.0063 max mem: 33369 +Epoch: [8] [ 200/1319] eta: 0:50:09 lr: 4.072726029339096e-05 loss: 0.0809 (0.0946) time: 2.7177 data: 0.0064 max mem: 33369 +Epoch: [8] [ 210/1319] eta: 0:49:45 lr: 4.07185343737602e-05 loss: 0.0814 (0.0947) time: 2.7447 data: 0.0066 max mem: 33369 +Epoch: [8] [ 220/1319] eta: 0:49:21 lr: 4.070980824635213e-05 loss: 0.0814 (0.0943) time: 2.7516 data: 0.0069 max mem: 33369 +Epoch: [8] [ 230/1319] eta: 0:48:56 lr: 4.070108191111232e-05 loss: 0.0700 (0.0937) time: 2.7475 data: 0.0068 max mem: 33369 +Epoch: [8] [ 240/1319] eta: 0:48:27 lr: 4.069235536798631e-05 loss: 0.0700 (0.0936) time: 2.6992 data: 0.0066 max mem: 33369 +Epoch: [8] [ 250/1319] eta: 0:48:02 lr: 4.0683628616919596e-05 loss: 0.0794 (0.0934) time: 2.6986 data: 0.0064 max mem: 33369 +Epoch: [8] [ 260/1319] eta: 0:47:38 lr: 4.0674901657857675e-05 loss: 0.0870 (0.0946) time: 2.7441 data: 0.0062 max mem: 33369 +Epoch: [8] [ 270/1319] eta: 0:47:11 lr: 4.066617449074599e-05 loss: 0.0843 (0.0942) time: 2.7365 data: 0.0064 max mem: 33369 +Epoch: [8] [ 280/1319] eta: 0:46:46 lr: 4.065744711552997e-05 loss: 0.0843 (0.0949) time: 2.7325 data: 0.0064 max mem: 33369 +Epoch: [8] [ 290/1319] eta: 0:46:20 lr: 4.064871953215503e-05 loss: 0.1016 (0.0954) time: 2.7312 data: 0.0062 max mem: 33369 +Epoch: [8] [ 300/1319] eta: 0:45:54 lr: 4.063999174056654e-05 loss: 0.1007 (0.0950) time: 2.7232 data: 0.0063 max mem: 33369 +Epoch: [8] [ 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+Epoch: [8] [ 390/1319] eta: 0:41:57 lr: 4.056143223763321e-05 loss: 0.0887 (0.0946) time: 2.7177 data: 0.0062 max mem: 33369 +Epoch: [8] [ 400/1319] eta: 0:41:29 lr: 4.055270236089869e-05 loss: 0.0893 (0.0949) time: 2.7010 data: 0.0062 max mem: 33369 +Epoch: [8] [ 410/1319] eta: 0:41:02 lr: 4.054397227534791e-05 loss: 0.0889 (0.0948) time: 2.6877 data: 0.0061 max mem: 33369 +Epoch: [8] [ 420/1319] eta: 0:40:36 lr: 4.0535241980925915e-05 loss: 0.0875 (0.0948) time: 2.7366 data: 0.0061 max mem: 33369 +Epoch: [8] [ 430/1319] eta: 0:40:10 lr: 4.0526511477577724e-05 loss: 0.0880 (0.0947) time: 2.7708 data: 0.0061 max mem: 33369 +Epoch: [8] [ 440/1319] eta: 0:39:43 lr: 4.051778076524832e-05 loss: 0.0887 (0.0949) time: 2.7539 data: 0.0063 max mem: 33369 +Epoch: [8] [ 450/1319] eta: 0:39:17 lr: 4.050904984388268e-05 loss: 0.0909 (0.0949) time: 2.7480 data: 0.0063 max mem: 33369 +Epoch: [8] [ 460/1319] eta: 0:38:51 lr: 4.0500318713425716e-05 loss: 0.0775 (0.0950) time: 2.7469 data: 0.0062 max mem: 33369 +Epoch: [8] [ 470/1319] eta: 0:38:24 lr: 4.0491587373822346e-05 loss: 0.0921 (0.0951) time: 2.7404 data: 0.0064 max mem: 33369 +Epoch: [8] [ 480/1319] eta: 0:37:57 lr: 4.048285582501745e-05 loss: 0.0873 (0.0948) time: 2.7248 data: 0.0064 max mem: 33369 +Epoch: [8] [ 490/1319] eta: 0:37:30 lr: 4.047412406695587e-05 loss: 0.0792 (0.0948) time: 2.7329 data: 0.0062 max mem: 33369 +Epoch: [8] [ 500/1319] eta: 0:37:02 lr: 4.046539209958243e-05 loss: 0.0776 (0.0946) time: 2.7124 data: 0.0061 max mem: 33369 +Epoch: [8] [ 510/1319] eta: 0:36:36 lr: 4.0456659922841925e-05 loss: 0.0829 (0.0946) time: 2.7075 data: 0.0062 max mem: 33369 +Epoch: [8] [ 520/1319] eta: 0:36:08 lr: 4.044792753667913e-05 loss: 0.0899 (0.0946) time: 2.7224 data: 0.0063 max mem: 33369 +Epoch: [8] [ 530/1319] eta: 0:35:41 lr: 4.0439194941038765e-05 loss: 0.0920 (0.0946) time: 2.6974 data: 0.0062 max mem: 33369 +Epoch: [8] [ 540/1319] eta: 0:35:14 lr: 4.043046213586556e-05 loss: 0.0979 (0.0948) time: 2.7034 data: 0.0063 max mem: 33369 +Epoch: [8] [ 550/1319] eta: 0:34:47 lr: 4.042172912110419e-05 loss: 0.0786 (0.0946) time: 2.7117 data: 0.0063 max mem: 33369 +Epoch: [8] [ 560/1319] eta: 0:34:19 lr: 4.0412995896699314e-05 loss: 0.0681 (0.0947) time: 2.7153 data: 0.0064 max mem: 33369 +Epoch: [8] [ 570/1319] eta: 0:33:52 lr: 4.040426246259555e-05 loss: 0.0973 (0.0948) time: 2.7077 data: 0.0064 max mem: 33369 +Epoch: [8] [ 580/1319] eta: 0:33:25 lr: 4.03955288187375e-05 loss: 0.0860 (0.0949) time: 2.7058 data: 0.0062 max mem: 33369 +Epoch: [8] [ 590/1319] eta: 0:32:58 lr: 4.038679496506974e-05 loss: 0.0860 (0.0948) time: 2.7080 data: 0.0062 max mem: 33369 +Epoch: [8] [ 600/1319] eta: 0:32:31 lr: 4.0378060901536817e-05 loss: 0.0772 (0.0950) time: 2.7224 data: 0.0062 max mem: 33369 +Epoch: [8] [ 610/1319] eta: 0:32:03 lr: 4.0369326628083236e-05 loss: 0.0880 (0.0950) time: 2.6916 data: 0.0064 max mem: 33369 +Epoch: [8] [ 620/1319] eta: 0:31:35 lr: 4.0360592144653494e-05 loss: 0.0925 (0.0949) time: 2.6546 data: 0.0064 max mem: 33369 +Epoch: [8] [ 630/1319] eta: 0:31:08 lr: 4.0351857451192053e-05 loss: 0.0892 (0.0950) time: 2.6856 data: 0.0063 max mem: 33369 +Epoch: [8] [ 640/1319] eta: 0:30:41 lr: 4.034312254764333e-05 loss: 0.0877 (0.0950) time: 2.7054 data: 0.0064 max mem: 33369 +Epoch: [8] [ 650/1319] eta: 0:30:14 lr: 4.033438743395174e-05 loss: 0.0837 (0.0947) time: 2.7277 data: 0.0063 max mem: 33369 +Epoch: [8] [ 660/1319] eta: 0:29:47 lr: 4.032565211006165e-05 loss: 0.0837 (0.0947) time: 2.7324 data: 0.0060 max mem: 33369 +Epoch: [8] [ 670/1319] eta: 0:29:20 lr: 4.031691657591742e-05 loss: 0.1005 (0.0949) time: 2.7043 data: 0.0060 max mem: 33369 +Epoch: [8] [ 680/1319] eta: 0:28:52 lr: 4.030818083146336e-05 loss: 0.0895 (0.0947) time: 2.6930 data: 0.0061 max mem: 33369 +Epoch: [8] [ 690/1319] eta: 0:28:25 lr: 4.029944487664375e-05 loss: 0.0821 (0.0947) time: 2.6926 data: 0.0061 max mem: 33369 +Epoch: [8] [ 700/1319] eta: 0:27:57 lr: 4.0290708711402866e-05 loss: 0.0757 (0.0946) time: 2.6680 data: 0.0063 max mem: 33369 +Epoch: [8] [ 710/1319] eta: 0:27:30 lr: 4.028197233568494e-05 loss: 0.0771 (0.0944) time: 2.6812 data: 0.0066 max mem: 33369 +Epoch: [8] [ 720/1319] eta: 0:27:03 lr: 4.027323574943419e-05 loss: 0.0892 (0.0946) time: 2.7178 data: 0.0066 max mem: 33369 +Epoch: [8] [ 730/1319] eta: 0:26:36 lr: 4.0264498952594776e-05 loss: 0.0998 (0.0946) time: 2.6901 data: 0.0064 max mem: 33369 +Epoch: [8] [ 740/1319] eta: 0:26:09 lr: 4.0255761945110847e-05 loss: 0.0985 (0.0948) time: 2.7074 data: 0.0062 max mem: 33369 +Epoch: [8] [ 750/1319] eta: 0:25:42 lr: 4.0247024726926543e-05 loss: 0.0985 (0.0950) time: 2.7378 data: 0.0062 max mem: 33369 +Epoch: [8] [ 760/1319] eta: 0:25:15 lr: 4.0238287297985935e-05 loss: 0.0920 (0.0953) time: 2.7071 data: 0.0063 max mem: 33369 +Epoch: [8] [ 770/1319] eta: 0:24:48 lr: 4.022954965823311e-05 loss: 0.0802 (0.0952) time: 2.7183 data: 0.0063 max mem: 33369 +Epoch: [8] [ 780/1319] eta: 0:24:21 lr: 4.0220811807612084e-05 loss: 0.0733 (0.0950) time: 2.7491 data: 0.0063 max mem: 33369 +Epoch: [8] [ 790/1319] eta: 0:23:54 lr: 4.021207374606688e-05 loss: 0.0797 (0.0950) time: 2.7143 data: 0.0063 max mem: 33369 +Epoch: [8] [ 800/1319] eta: 0:23:26 lr: 4.0203335473541464e-05 loss: 0.0914 (0.0952) time: 2.6705 data: 0.0063 max mem: 33369 +Epoch: [8] [ 810/1319] eta: 0:22:59 lr: 4.01945969899798e-05 loss: 0.0874 (0.0951) time: 2.6709 data: 0.0064 max mem: 33369 +Epoch: [8] [ 820/1319] eta: 0:22:32 lr: 4.0185858295325805e-05 loss: 0.0874 (0.0953) time: 2.6982 data: 0.0064 max mem: 33369 +Epoch: [8] [ 830/1319] eta: 0:22:05 lr: 4.017711938952337e-05 loss: 0.0936 (0.0954) time: 2.7043 data: 0.0060 max mem: 33369 +Epoch: [8] [ 840/1319] eta: 0:21:38 lr: 4.0168380272516376e-05 loss: 0.0992 (0.0956) time: 2.6902 data: 0.0062 max mem: 33369 +Epoch: [8] [ 850/1319] eta: 0:21:10 lr: 4.0159640944248643e-05 loss: 0.0911 (0.0956) time: 2.6799 data: 0.0063 max mem: 33369 +Epoch: [8] [ 860/1319] eta: 0:20:43 lr: 4.0150901404663985e-05 loss: 0.0894 (0.0957) time: 2.6889 data: 0.0063 max mem: 33369 +Epoch: [8] [ 870/1319] eta: 0:20:16 lr: 4.0142161653706185e-05 loss: 0.1104 (0.0958) time: 2.6870 data: 0.0063 max mem: 33369 +Epoch: [8] [ 880/1319] eta: 0:19:49 lr: 4.013342169131899e-05 loss: 0.0952 (0.0959) time: 2.7082 data: 0.0066 max mem: 33369 +Epoch: [8] [ 890/1319] eta: 0:19:22 lr: 4.012468151744613e-05 loss: 0.0885 (0.0959) time: 2.7556 data: 0.0067 max mem: 33369 +Epoch: [8] [ 900/1319] eta: 0:18:55 lr: 4.01159411320313e-05 loss: 0.0977 (0.0960) time: 2.7271 data: 0.0063 max mem: 33369 +Epoch: [8] [ 910/1319] eta: 0:18:28 lr: 4.010720053501816e-05 loss: 0.0977 (0.0959) time: 2.6866 data: 0.0064 max mem: 33369 +Epoch: [8] [ 920/1319] eta: 0:18:01 lr: 4.009845972635034e-05 loss: 0.0819 (0.0958) time: 2.6934 data: 0.0066 max mem: 33369 +Epoch: [8] [ 930/1319] eta: 0:17:33 lr: 4.008971870597147e-05 loss: 0.0819 (0.0957) time: 2.6945 data: 0.0065 max mem: 33369 +Epoch: [8] [ 940/1319] eta: 0:17:06 lr: 4.008097747382511e-05 loss: 0.0911 (0.0957) time: 2.7130 data: 0.0063 max mem: 33369 +Epoch: [8] [ 950/1319] eta: 0:16:39 lr: 4.0072236029854826e-05 loss: 0.0959 (0.0959) time: 2.7203 data: 0.0062 max mem: 33369 +Epoch: [8] [ 960/1319] eta: 0:16:12 lr: 4.006349437400413e-05 loss: 0.0976 (0.0960) time: 2.7229 data: 0.0063 max mem: 33369 +Epoch: [8] [ 970/1319] eta: 0:15:45 lr: 4.005475250621652e-05 loss: 0.0828 (0.0957) time: 2.7154 data: 0.0062 max mem: 33369 +Epoch: [8] [ 980/1319] eta: 0:15:18 lr: 4.004601042643546e-05 loss: 0.0656 (0.0955) time: 2.6828 data: 0.0065 max mem: 33369 +Epoch: [8] [ 990/1319] eta: 0:14:51 lr: 4.003726813460439e-05 loss: 0.0857 (0.0956) time: 2.6946 data: 0.0066 max mem: 33369 +Epoch: [8] [1000/1319] eta: 0:14:24 lr: 4.0028525630666715e-05 loss: 0.0907 (0.0955) time: 2.7303 data: 0.0064 max mem: 33369 +Epoch: [8] [1010/1319] eta: 0:13:57 lr: 4.00197829145658e-05 loss: 0.0907 (0.0956) time: 2.7173 data: 0.0064 max mem: 33369 +Epoch: [8] [1020/1319] eta: 0:13:30 lr: 4.001103998624502e-05 loss: 0.0898 (0.0956) time: 2.6937 data: 0.0065 max mem: 33369 +Epoch: [8] [1030/1319] eta: 0:13:02 lr: 4.000229684564768e-05 loss: 0.0898 (0.0956) time: 2.7077 data: 0.0064 max mem: 33369 +Epoch: [8] [1040/1319] eta: 0:12:35 lr: 3.9993553492717074e-05 loss: 0.1003 (0.0957) time: 2.7210 data: 0.0064 max mem: 33369 +Epoch: [8] [1050/1319] eta: 0:12:08 lr: 3.998480992739647e-05 loss: 0.1041 (0.0960) time: 2.7176 data: 0.0065 max mem: 33369 +Epoch: [8] [1060/1319] eta: 0:11:41 lr: 3.9976066149629094e-05 loss: 0.1062 (0.0960) time: 2.7002 data: 0.0065 max mem: 33369 +Epoch: [8] [1070/1319] eta: 0:11:14 lr: 3.9967322159358156e-05 loss: 0.0901 (0.0961) time: 2.6925 data: 0.0066 max mem: 33369 +Epoch: [8] [1080/1319] eta: 0:10:47 lr: 3.995857795652683e-05 loss: 0.0983 (0.0963) time: 2.6568 data: 0.0068 max mem: 33369 +Epoch: [8] [1090/1319] eta: 0:10:20 lr: 3.994983354107826e-05 loss: 0.1008 (0.0963) time: 2.6397 data: 0.0068 max mem: 33369 +Epoch: [8] [1100/1319] eta: 0:09:52 lr: 3.994108891295557e-05 loss: 0.0764 (0.0962) time: 2.6505 data: 0.0067 max mem: 33369 +Epoch: [8] [1110/1319] eta: 0:09:25 lr: 3.9932344072101854e-05 loss: 0.0727 (0.0962) time: 2.6680 data: 0.0066 max mem: 33369 +Epoch: [8] [1120/1319] eta: 0:08:58 lr: 3.9923599018460164e-05 loss: 0.0857 (0.0961) time: 2.6770 data: 0.0066 max mem: 33369 +Epoch: [8] [1130/1319] eta: 0:08:31 lr: 3.991485375197353e-05 loss: 0.0886 (0.0962) time: 2.6753 data: 0.0066 max mem: 33369 +Epoch: [8] [1140/1319] eta: 0:08:04 lr: 3.990610827258495e-05 loss: 0.1035 (0.0962) time: 2.6721 data: 0.0068 max mem: 33369 +Epoch: [8] [1150/1319] eta: 0:07:37 lr: 3.9897362580237394e-05 loss: 0.0704 (0.0960) time: 2.6869 data: 0.0068 max mem: 33369 +Epoch: [8] [1160/1319] eta: 0:07:10 lr: 3.988861667487383e-05 loss: 0.0753 (0.0961) time: 2.6790 data: 0.0066 max mem: 33369 +Epoch: [8] [1170/1319] eta: 0:06:43 lr: 3.987987055643715e-05 loss: 0.0897 (0.0961) time: 2.6613 data: 0.0066 max mem: 33369 +Epoch: [8] [1180/1319] eta: 0:06:16 lr: 3.9871124224870237e-05 loss: 0.0740 (0.0960) time: 2.6903 data: 0.0067 max mem: 33369 +Epoch: [8] [1190/1319] eta: 0:05:48 lr: 3.986237768011596e-05 loss: 0.0743 (0.0962) time: 2.6706 data: 0.0068 max mem: 33369 +Epoch: [8] [1200/1319] eta: 0:05:21 lr: 3.985363092211714e-05 loss: 0.0921 (0.0962) time: 2.6744 data: 0.0067 max mem: 33369 +Epoch: [8] [1210/1319] eta: 0:04:54 lr: 3.984488395081657e-05 loss: 0.0921 (0.0963) time: 2.7232 data: 0.0065 max mem: 33369 +Epoch: [8] [1220/1319] eta: 0:04:27 lr: 3.9836136766157016e-05 loss: 0.0976 (0.0963) time: 2.7363 data: 0.0064 max mem: 33369 +Epoch: [8] [1230/1319] eta: 0:04:00 lr: 3.9827389368081224e-05 loss: 0.0826 (0.0963) time: 2.7380 data: 0.0066 max mem: 33369 +Epoch: [8] [1240/1319] eta: 0:03:33 lr: 3.9818641756531906e-05 loss: 0.0853 (0.0963) time: 2.7109 data: 0.0067 max mem: 33369 +Epoch: [8] [1250/1319] eta: 0:03:06 lr: 3.980989393145173e-05 loss: 0.0931 (0.0964) time: 2.7163 data: 0.0066 max mem: 33369 +Epoch: [8] [1260/1319] eta: 0:02:39 lr: 3.9801145892783356e-05 loss: 0.0887 (0.0964) time: 2.7427 data: 0.0065 max mem: 33369 +Epoch: [8] [1270/1319] eta: 0:02:12 lr: 3.97923976404694e-05 loss: 0.0922 (0.0964) time: 2.6987 data: 0.0067 max mem: 33369 +Epoch: [8] [1280/1319] eta: 0:01:45 lr: 3.978364917445246e-05 loss: 0.1197 (0.0966) time: 2.6729 data: 0.0068 max mem: 33369 +Epoch: [8] [1290/1319] eta: 0:01:18 lr: 3.9774900494675086e-05 loss: 0.0920 (0.0966) time: 2.6914 data: 0.0066 max mem: 33369 +Epoch: [8] [1300/1319] eta: 0:00:51 lr: 3.976615160107982e-05 loss: 0.0916 (0.0967) time: 2.7087 data: 0.0066 max mem: 33369 +Epoch: [8] [1310/1319] eta: 0:00:24 lr: 3.975740249360917e-05 loss: 0.0896 (0.0967) time: 2.7477 data: 0.0065 max mem: 33369 +Epoch: [8] Total time: 0:59:29 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 2:09:52 time: 3.0284 data: 2.9094 max mem: 33369 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 100/2573] eta: 0:04:11 time: 0.0719 data: 0.0011 max mem: 33369 +Test: [ 200/2573] eta: 0:03:28 time: 0.0733 data: 0.0012 max mem: 33369 +Test: [ 300/2573] eta: 0:03:08 time: 0.0751 data: 0.0012 max mem: 33369 +Test: [ 400/2573] eta: 0:02:54 time: 0.0749 data: 0.0011 max mem: 33369 +Test: [ 500/2573] eta: 0:02:43 time: 0.0740 data: 0.0012 max mem: 33369 +Test: [ 600/2573] eta: 0:02:34 time: 0.0737 data: 0.0012 max mem: 33369 +Test: [ 700/2573] eta: 0:02:25 time: 0.0737 data: 0.0011 max mem: 33369 +Test: [ 800/2573] eta: 0:02:17 time: 0.0772 data: 0.0012 max mem: 33369 +Test: [ 900/2573] eta: 0:02:09 time: 0.0738 data: 0.0011 max mem: 33369 +Test: [1000/2573] eta: 0:02:01 time: 0.0737 data: 0.0012 max mem: 33369 +Test: [1100/2573] eta: 0:01:52 time: 0.0738 data: 0.0012 max mem: 33369 +Test: [1200/2573] eta: 0:01:45 time: 0.0740 data: 0.0011 max mem: 33369 +Test: [1300/2573] eta: 0:01:37 time: 0.0739 data: 0.0011 max mem: 33369 +Test: [1400/2573] eta: 0:01:29 time: 0.0722 data: 0.0012 max mem: 33369 +Test: [1500/2573] eta: 0:01:21 time: 0.0740 data: 0.0012 max mem: 33369 +Test: [1600/2573] eta: 0:01:13 time: 0.0772 data: 0.0012 max mem: 33369 +Test: [1700/2573] eta: 0:01:06 time: 0.0723 data: 0.0011 max mem: 33369 +Test: [1800/2573] eta: 0:00:58 time: 0.0756 data: 0.0012 max mem: 33369 +Test: [1900/2573] eta: 0:00:50 time: 0.0724 data: 0.0012 max mem: 33369 +Test: [2000/2573] eta: 0:00:43 time: 0.0741 data: 0.0012 max mem: 33369 +Test: [2100/2573] eta: 0:00:35 time: 0.0756 data: 0.0011 max mem: 33369 +Test: [2200/2573] eta: 0:00:28 time: 0.0756 data: 0.0011 max mem: 33369 +Test: [2300/2573] eta: 0:00:20 time: 0.0757 data: 0.0012 max mem: 33369 +Test: [2400/2573] eta: 0:00:12 time: 0.0707 data: 0.0012 max mem: 33369 +Test: [2500/2573] eta: 0:00:05 time: 0.0742 data: 0.0012 max mem: 33369 +Test: Total time: 0:03:13 +Final results: +Mean IoU is 59.38 + + precision@0.5 = 66.75 + precision@0.6 = 60.09 + precision@0.7 = 52.02 + precision@0.8 = 39.44 + precision@0.9 = 17.20 + overall IoU = 58.64 + +Average object IoU 59.37840437828531 +Overall IoU 58.643306732177734 +Better epoch: 8 + +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [9] [ 0/1319] eta: 1:33:37 lr: 3.974952811397457e-05 loss: 0.1151 (0.1151) time: 4.2591 data: 1.3031 max mem: 33369 +Epoch: [9] [ 10/1319] eta: 1:03:00 lr: 3.974077859998216e-05 loss: 0.0943 (0.1008) time: 2.8883 data: 0.1244 max mem: 33369 +Epoch: [9] [ 20/1319] eta: 1:00:30 lr: 3.9732028871947454e-05 loss: 0.0919 (0.0966) time: 2.7220 data: 0.0061 max mem: 33369 +Epoch: [9] [ 30/1319] eta: 0:59:22 lr: 3.972327892981283e-05 loss: 0.0807 (0.0925) time: 2.6956 data: 0.0058 max mem: 33369 +Epoch: [9] [ 40/1319] eta: 0:58:45 lr: 3.971452877352066e-05 loss: 0.0719 (0.0900) time: 2.7161 data: 0.0061 max mem: 33369 +Epoch: [9] [ 50/1319] eta: 0:57:46 lr: 3.9705778403013264e-05 loss: 0.0749 (0.0932) time: 2.6812 data: 0.0063 max mem: 33369 +Epoch: [9] [ 60/1319] eta: 0:57:19 lr: 3.969702781823294e-05 loss: 0.0891 (0.0926) time: 2.6818 data: 0.0064 max mem: 33369 +Epoch: [9] [ 70/1319] eta: 0:56:46 lr: 3.9688277019121967e-05 loss: 0.0865 (0.0914) time: 2.7156 data: 0.0064 max mem: 33369 +Epoch: [9] [ 80/1319] eta: 0:56:15 lr: 3.967952600562257e-05 loss: 0.0750 (0.0898) time: 2.7003 data: 0.0063 max mem: 33369 +Epoch: [9] [ 90/1319] eta: 0:55:54 lr: 3.967077477767697e-05 loss: 0.0786 (0.0929) time: 2.7388 data: 0.0064 max mem: 33369 +Epoch: [9] [ 100/1319] eta: 0:55:22 lr: 3.966202333522733e-05 loss: 0.0852 (0.0929) time: 2.7315 data: 0.0063 max mem: 33369 +Epoch: [9] [ 110/1319] eta: 0:54:58 lr: 3.965327167821583e-05 loss: 0.0739 (0.0917) time: 2.7203 data: 0.0061 max mem: 33369 +Epoch: [9] [ 120/1319] eta: 0:54:29 lr: 3.9644519806584564e-05 loss: 0.0701 (0.0914) time: 2.7333 data: 0.0062 max mem: 33369 +Epoch: [9] [ 130/1319] eta: 0:54:00 lr: 3.963576772027564e-05 loss: 0.0711 (0.0903) time: 2.7092 data: 0.0064 max mem: 33369 +Epoch: [9] [ 140/1319] eta: 0:53:34 lr: 3.96270154192311e-05 loss: 0.0654 (0.0892) time: 2.7231 data: 0.0064 max mem: 33369 +Epoch: [9] [ 150/1319] eta: 0:53:04 lr: 3.9618262903393e-05 loss: 0.0654 (0.0889) time: 2.7192 data: 0.0063 max mem: 33369 +Epoch: [9] [ 160/1319] eta: 0:52:38 lr: 3.960951017270332e-05 loss: 0.0742 (0.0877) time: 2.7193 data: 0.0064 max mem: 33369 +Epoch: [9] [ 170/1319] eta: 0:52:12 lr: 3.9600757227104046e-05 loss: 0.0776 (0.0878) time: 2.7397 data: 0.0063 max mem: 33369 +Epoch: [9] [ 180/1319] eta: 0:51:42 lr: 3.95920040665371e-05 loss: 0.0871 (0.0882) time: 2.7109 data: 0.0062 max mem: 33369 +Epoch: [9] [ 190/1319] eta: 0:51:15 lr: 3.958325069094442e-05 loss: 0.0838 (0.0881) time: 2.7084 data: 0.0063 max mem: 33369 +Epoch: [9] [ 200/1319] eta: 0:50:48 lr: 3.957449710026786e-05 loss: 0.0791 (0.0876) time: 2.7244 data: 0.0061 max mem: 33369 +Epoch: [9] [ 210/1319] eta: 0:50:19 lr: 3.9565743294449283e-05 loss: 0.0765 (0.0875) time: 2.7089 data: 0.0061 max mem: 33369 +Epoch: [9] [ 220/1319] eta: 0:49:51 lr: 3.955698927343052e-05 loss: 0.0774 (0.0876) time: 2.7026 data: 0.0062 max mem: 33369 +Epoch: [9] [ 230/1319] eta: 0:49:24 lr: 3.954823503715335e-05 loss: 0.0813 (0.0876) time: 2.7170 data: 0.0062 max mem: 33369 +Epoch: [9] [ 240/1319] eta: 0:48:55 lr: 3.953948058555954e-05 loss: 0.0683 (0.0874) time: 2.6996 data: 0.0063 max mem: 33369 +Epoch: [9] [ 250/1319] eta: 0:48:26 lr: 3.9530725918590825e-05 loss: 0.0771 (0.0883) time: 2.6842 data: 0.0063 max mem: 33369 +Epoch: [9] [ 260/1319] eta: 0:47:58 lr: 3.952197103618889e-05 loss: 0.0804 (0.0882) time: 2.6936 data: 0.0062 max mem: 33369 +Epoch: [9] [ 270/1319] eta: 0:47:31 lr: 3.951321593829542e-05 loss: 0.0799 (0.0883) time: 2.7054 data: 0.0063 max mem: 33369 +Epoch: [9] [ 280/1319] eta: 0:47:03 lr: 3.9504460624852056e-05 loss: 0.0918 (0.0883) time: 2.7061 data: 0.0064 max mem: 33369 +Epoch: [9] [ 290/1319] eta: 0:46:35 lr: 3.94957050958004e-05 loss: 0.0779 (0.0886) time: 2.6934 data: 0.0065 max mem: 33369 +Epoch: [9] [ 300/1319] eta: 0:46:07 lr: 3.9486949351082035e-05 loss: 0.0814 (0.0886) time: 2.7039 data: 0.0063 max mem: 33369 +Epoch: [9] [ 310/1319] eta: 0:45:39 lr: 3.9478193390638515e-05 loss: 0.0866 (0.0887) time: 2.6970 data: 0.0063 max mem: 33369 +Epoch: [9] [ 320/1319] eta: 0:45:13 lr: 3.946943721441136e-05 loss: 0.0864 (0.0887) time: 2.7165 data: 0.0065 max mem: 33369 +Epoch: [9] [ 330/1319] eta: 0:44:45 lr: 3.946068082234206e-05 loss: 0.0743 (0.0883) time: 2.7192 data: 0.0064 max mem: 33369 +Epoch: [9] [ 340/1319] eta: 0:44:17 lr: 3.945192421437206e-05 loss: 0.0669 (0.0877) time: 2.6760 data: 0.0064 max mem: 33369 +Epoch: [9] [ 350/1319] eta: 0:43:49 lr: 3.944316739044282e-05 loss: 0.0729 (0.0877) time: 2.6829 data: 0.0063 max mem: 33369 +Epoch: [9] [ 360/1319] eta: 0:43:21 lr: 3.94344103504957e-05 loss: 0.0757 (0.0877) time: 2.6957 data: 0.0063 max mem: 33369 +Epoch: [9] [ 370/1319] eta: 0:42:54 lr: 3.94256530944721e-05 loss: 0.0766 (0.0880) time: 2.7076 data: 0.0064 max mem: 33369 +Epoch: [9] [ 380/1319] eta: 0:42:27 lr: 3.9416895622313336e-05 loss: 0.0876 (0.0882) time: 2.7218 data: 0.0065 max mem: 33369 +Epoch: [9] [ 390/1319] eta: 0:42:01 lr: 3.9408137933960734e-05 loss: 0.0800 (0.0879) time: 2.7326 data: 0.0067 max mem: 33369 +Epoch: [9] [ 400/1319] eta: 0:41:34 lr: 3.939938002935556e-05 loss: 0.0901 (0.0885) time: 2.7400 data: 0.0066 max mem: 33369 +Epoch: [9] [ 410/1319] eta: 0:41:08 lr: 3.9390621908439054e-05 loss: 0.0876 (0.0886) time: 2.7395 data: 0.0066 max mem: 33369 +Epoch: [9] [ 420/1319] eta: 0:40:41 lr: 3.938186357115245e-05 loss: 0.0814 (0.0886) time: 2.7409 data: 0.0064 max mem: 33369 +Epoch: [9] [ 430/1319] eta: 0:40:14 lr: 3.937310501743692e-05 loss: 0.0895 (0.0895) time: 2.7229 data: 0.0062 max mem: 33369 +Epoch: [9] [ 440/1319] eta: 0:39:48 lr: 3.936434624723363e-05 loss: 0.0785 (0.0896) time: 2.7480 data: 0.0061 max mem: 33369 +Epoch: [9] [ 450/1319] eta: 0:39:21 lr: 3.9355587260483696e-05 loss: 0.0785 (0.0896) time: 2.7427 data: 0.0057 max mem: 33369 +Epoch: [9] [ 460/1319] eta: 0:38:55 lr: 3.9346828057128216e-05 loss: 0.0835 (0.0897) time: 2.7432 data: 0.0058 max mem: 33369 +Epoch: [9] [ 470/1319] eta: 0:38:27 lr: 3.9338068637108247e-05 loss: 0.0835 (0.0898) time: 2.7448 data: 0.0062 max mem: 33369 +Epoch: [9] [ 480/1319] eta: 0:37:59 lr: 3.932930900036482e-05 loss: 0.0712 (0.0898) time: 2.6735 data: 0.0063 max mem: 33369 +Epoch: [9] [ 490/1319] eta: 0:37:31 lr: 3.932054914683895e-05 loss: 0.0776 (0.0899) time: 2.6739 data: 0.0063 max mem: 33369 +Epoch: [9] [ 500/1319] eta: 0:37:04 lr: 3.9311789076471614e-05 loss: 0.0859 (0.0897) time: 2.7168 data: 0.0063 max mem: 33369 +Epoch: [9] [ 510/1319] eta: 0:36:37 lr: 3.930302878920372e-05 loss: 0.0752 (0.0898) time: 2.7038 data: 0.0064 max mem: 33369 +Epoch: [9] [ 520/1319] eta: 0:36:09 lr: 3.929426828497621e-05 loss: 0.0891 (0.0902) time: 2.6816 data: 0.0064 max mem: 33369 +Epoch: [9] [ 530/1319] eta: 0:35:43 lr: 3.9285507563729945e-05 loss: 0.0891 (0.0903) time: 2.7266 data: 0.0065 max mem: 33369 +Epoch: [9] [ 540/1319] eta: 0:35:15 lr: 3.927674662540578e-05 loss: 0.0887 (0.0902) time: 2.7364 data: 0.0064 max mem: 33369 +Epoch: [9] [ 550/1319] eta: 0:34:48 lr: 3.926798546994454e-05 loss: 0.0819 (0.0902) time: 2.7064 data: 0.0063 max mem: 33369 +Epoch: [9] [ 560/1319] eta: 0:34:22 lr: 3.9259224097287e-05 loss: 0.0829 (0.0904) time: 2.7331 data: 0.0063 max mem: 33369 +Epoch: [9] [ 570/1319] eta: 0:33:54 lr: 3.925046250737393e-05 loss: 0.0856 (0.0906) time: 2.7398 data: 0.0065 max mem: 33369 +Epoch: [9] [ 580/1319] eta: 0:33:28 lr: 3.924170070014604e-05 loss: 0.0841 (0.0904) time: 2.7312 data: 0.0067 max mem: 33369 +Epoch: [9] [ 590/1319] eta: 0:33:01 lr: 3.923293867554403e-05 loss: 0.0841 (0.0904) time: 2.7364 data: 0.0065 max mem: 33369 +Epoch: [9] [ 600/1319] eta: 0:32:34 lr: 3.9224176433508566e-05 loss: 0.0894 (0.0907) time: 2.7330 data: 0.0063 max mem: 33369 +Epoch: [9] [ 610/1319] eta: 0:32:06 lr: 3.9215413973980275e-05 loss: 0.0826 (0.0906) time: 2.7235 data: 0.0064 max mem: 33369 +Epoch: [9] [ 620/1319] eta: 0:31:40 lr: 3.920665129689976e-05 loss: 0.0793 (0.0905) time: 2.7607 data: 0.0064 max mem: 33369 +Epoch: [9] [ 630/1319] eta: 0:31:13 lr: 3.919788840220759e-05 loss: 0.0816 (0.0906) time: 2.7496 data: 0.0064 max mem: 33369 +Epoch: [9] [ 640/1319] eta: 0:30:45 lr: 3.918912528984432e-05 loss: 0.0857 (0.0906) time: 2.6905 data: 0.0065 max mem: 33369 +Epoch: [9] [ 650/1319] eta: 0:30:18 lr: 3.918036195975044e-05 loss: 0.0821 (0.0907) time: 2.6805 data: 0.0065 max mem: 33369 +Epoch: [9] [ 660/1319] eta: 0:29:50 lr: 3.9171598411866434e-05 loss: 0.0913 (0.0909) time: 2.6717 data: 0.0065 max mem: 33369 +Epoch: [9] [ 670/1319] eta: 0:29:23 lr: 3.9162834646132755e-05 loss: 0.0914 (0.0912) time: 2.6923 data: 0.0066 max mem: 33369 +Epoch: [9] [ 680/1319] eta: 0:28:56 lr: 3.915407066248981e-05 loss: 0.0914 (0.0913) time: 2.7383 data: 0.0067 max mem: 33369 +Epoch: [9] [ 690/1319] eta: 0:28:29 lr: 3.914530646087798e-05 loss: 0.0889 (0.0913) time: 2.7549 data: 0.0067 max mem: 33369 +Epoch: [9] [ 700/1319] eta: 0:28:02 lr: 3.9136542041237625e-05 loss: 0.0790 (0.0912) time: 2.7252 data: 0.0068 max mem: 33369 +Epoch: [9] [ 710/1319] eta: 0:27:35 lr: 3.9127777403509066e-05 loss: 0.0736 (0.0909) time: 2.7243 data: 0.0068 max mem: 33369 +Epoch: [9] [ 720/1319] eta: 0:27:07 lr: 3.9119012547632586e-05 loss: 0.0759 (0.0911) time: 2.7206 data: 0.0066 max mem: 33369 +Epoch: [9] [ 730/1319] eta: 0:26:40 lr: 3.911024747354846e-05 loss: 0.0861 (0.0910) time: 2.7086 data: 0.0067 max mem: 33369 +Epoch: [9] [ 740/1319] eta: 0:26:12 lr: 3.9101482181196904e-05 loss: 0.0780 (0.0909) time: 2.6522 data: 0.0068 max mem: 33369 +Epoch: [9] [ 750/1319] eta: 0:25:45 lr: 3.909271667051812e-05 loss: 0.0729 (0.0908) time: 2.6261 data: 0.0068 max mem: 33369 +Epoch: [9] [ 760/1319] eta: 0:25:17 lr: 3.908395094145227e-05 loss: 0.0646 (0.0908) time: 2.6407 data: 0.0066 max mem: 33369 +Epoch: [9] [ 770/1319] eta: 0:24:49 lr: 3.9075184993939487e-05 loss: 0.0814 (0.0908) time: 2.6239 data: 0.0067 max mem: 33369 +Epoch: [9] [ 780/1319] eta: 0:24:21 lr: 3.906641882791989e-05 loss: 0.0937 (0.0912) time: 2.6279 data: 0.0067 max mem: 33369 +Epoch: [9] [ 790/1319] eta: 0:23:53 lr: 3.9057652443333534e-05 loss: 0.0993 (0.0914) time: 2.6214 data: 0.0065 max mem: 33369 +Epoch: [9] [ 800/1319] eta: 0:23:26 lr: 3.904888584012046e-05 loss: 0.0894 (0.0916) time: 2.6377 data: 0.0063 max mem: 33369 +Epoch: [9] [ 810/1319] eta: 0:22:59 lr: 3.904011901822068e-05 loss: 0.1002 (0.0918) time: 2.6701 data: 0.0063 max mem: 33369 +Epoch: [9] [ 820/1319] eta: 0:22:31 lr: 3.9031351977574175e-05 loss: 0.0878 (0.0918) time: 2.6857 data: 0.0066 max mem: 33369 +Epoch: [9] [ 830/1319] eta: 0:22:04 lr: 3.9022584718120886e-05 loss: 0.0878 (0.0919) time: 2.6854 data: 0.0066 max mem: 33369 +Epoch: [9] [ 840/1319] eta: 0:21:37 lr: 3.901381723980073e-05 loss: 0.0896 (0.0918) time: 2.6545 data: 0.0063 max mem: 33369 +Epoch: [9] [ 850/1319] eta: 0:21:09 lr: 3.900504954255358e-05 loss: 0.0896 (0.0920) time: 2.6248 data: 0.0065 max mem: 33369 +Epoch: [9] [ 860/1319] eta: 0:20:42 lr: 3.899628162631931e-05 loss: 0.0870 (0.0920) time: 2.6308 data: 0.0065 max mem: 33369 +Epoch: [9] [ 870/1319] eta: 0:20:14 lr: 3.898751349103772e-05 loss: 0.0829 (0.0921) time: 2.6316 data: 0.0065 max mem: 33369 +Epoch: [9] [ 880/1319] eta: 0:19:47 lr: 3.8978745136648617e-05 loss: 0.0760 (0.0919) time: 2.6370 data: 0.0065 max mem: 33369 +Epoch: [9] [ 890/1319] eta: 0:19:20 lr: 3.896997656309173e-05 loss: 0.0728 (0.0918) time: 2.6448 data: 0.0064 max mem: 33369 +Epoch: [9] [ 900/1319] eta: 0:18:52 lr: 3.896120777030681e-05 loss: 0.0770 (0.0918) time: 2.6484 data: 0.0064 max mem: 33369 +Epoch: [9] [ 910/1319] eta: 0:18:25 lr: 3.895243875823353e-05 loss: 0.0970 (0.0920) time: 2.6446 data: 0.0063 max mem: 33369 +Epoch: [9] [ 920/1319] eta: 0:17:58 lr: 3.894366952681158e-05 loss: 0.0883 (0.0920) time: 2.6330 data: 0.0063 max mem: 33369 +Epoch: [9] [ 930/1319] eta: 0:17:30 lr: 3.8934900075980555e-05 loss: 0.0839 (0.0922) time: 2.6293 data: 0.0064 max mem: 33369 +Epoch: [9] [ 940/1319] eta: 0:17:03 lr: 3.8926130405680076e-05 loss: 0.0852 (0.0921) time: 2.6536 data: 0.0066 max mem: 33369 +Epoch: [9] [ 950/1319] eta: 0:16:36 lr: 3.8917360515849704e-05 loss: 0.0852 (0.0921) time: 2.6653 data: 0.0067 max mem: 33369 +Epoch: [9] [ 960/1319] eta: 0:16:09 lr: 3.8908590406428975e-05 loss: 0.0784 (0.0919) time: 2.6475 data: 0.0065 max mem: 33369 +Epoch: [9] [ 970/1319] eta: 0:15:42 lr: 3.889982007735738e-05 loss: 0.0739 (0.0917) time: 2.6455 data: 0.0064 max mem: 33369 +Epoch: [9] [ 980/1319] eta: 0:15:14 lr: 3.889104952857442e-05 loss: 0.0734 (0.0917) time: 2.6198 data: 0.0065 max mem: 33369 +Epoch: [9] [ 990/1319] eta: 0:14:47 lr: 3.888227876001951e-05 loss: 0.0970 (0.0919) time: 2.6394 data: 0.0065 max mem: 33369 +Epoch: [9] [1000/1319] eta: 0:14:20 lr: 3.887350777163206e-05 loss: 0.0931 (0.0920) time: 2.6686 data: 0.0064 max mem: 33369 +Epoch: [9] [1010/1319] eta: 0:13:53 lr: 3.886473656335145e-05 loss: 0.0786 (0.0919) time: 2.6400 data: 0.0065 max mem: 33369 +Epoch: [9] [1020/1319] eta: 0:13:26 lr: 3.8855965135117015e-05 loss: 0.0865 (0.0921) time: 2.6219 data: 0.0066 max mem: 33369 +Epoch: [9] [1030/1319] eta: 0:12:58 lr: 3.8847193486868084e-05 loss: 0.0865 (0.0922) time: 2.6022 data: 0.0065 max mem: 33369 +Epoch: [9] [1040/1319] eta: 0:12:31 lr: 3.883842161854392e-05 loss: 0.0659 (0.0920) time: 2.6319 data: 0.0065 max mem: 33369 +Epoch: [9] [1050/1319] eta: 0:12:04 lr: 3.8829649530083775e-05 loss: 0.0804 (0.0921) time: 2.6567 data: 0.0066 max mem: 33369 +Epoch: [9] [1060/1319] eta: 0:11:37 lr: 3.882087722142687e-05 loss: 0.0910 (0.0920) time: 2.6892 data: 0.0065 max mem: 33369 +Epoch: [9] [1070/1319] eta: 0:11:10 lr: 3.8812104692512384e-05 loss: 0.0840 (0.0923) time: 2.6897 data: 0.0064 max mem: 33369 +Epoch: [9] [1080/1319] eta: 0:10:43 lr: 3.880333194327947e-05 loss: 0.0890 (0.0923) time: 2.6284 data: 0.0064 max mem: 33369 +Epoch: [9] [1090/1319] eta: 0:10:16 lr: 3.879455897366725e-05 loss: 0.0794 (0.0921) time: 2.6236 data: 0.0064 max mem: 33369 +Epoch: [9] [1100/1319] eta: 0:09:49 lr: 3.878578578361481e-05 loss: 0.0781 (0.0921) time: 2.6483 data: 0.0064 max mem: 33369 +Epoch: [9] [1110/1319] eta: 0:09:22 lr: 3.87770123730612e-05 loss: 0.0877 (0.0921) time: 2.6603 data: 0.0065 max mem: 33369 +Epoch: [9] [1120/1319] eta: 0:08:55 lr: 3.876823874194545e-05 loss: 0.0814 (0.0921) time: 2.6481 data: 0.0065 max mem: 33369 +Epoch: [9] [1130/1319] eta: 0:08:28 lr: 3.8759464890206544e-05 loss: 0.0706 (0.0920) time: 2.6696 data: 0.0063 max mem: 33369 +Epoch: [9] [1140/1319] eta: 0:08:01 lr: 3.875069081778345e-05 loss: 0.0782 (0.0920) time: 2.6520 data: 0.0063 max mem: 33369 +Epoch: [9] [1150/1319] eta: 0:07:34 lr: 3.874191652461509e-05 loss: 0.0862 (0.0920) time: 2.6589 data: 0.0065 max mem: 33369 +Epoch: [9] [1160/1319] eta: 0:07:07 lr: 3.8733142010640345e-05 loss: 0.0819 (0.0918) time: 2.6890 data: 0.0065 max mem: 33369 +Epoch: [9] [1170/1319] eta: 0:06:40 lr: 3.872436727579809e-05 loss: 0.0835 (0.0918) time: 2.6691 data: 0.0065 max mem: 33369 +Epoch: [9] [1180/1319] eta: 0:06:13 lr: 3.871559232002716e-05 loss: 0.0775 (0.0918) time: 2.6418 data: 0.0064 max mem: 33369 +Epoch: [9] [1190/1319] eta: 0:05:47 lr: 3.870681714326634e-05 loss: 0.0829 (0.0918) time: 2.6383 data: 0.0064 max mem: 33369 +Epoch: [9] [1200/1319] eta: 0:05:20 lr: 3.86980417454544e-05 loss: 0.0861 (0.0917) time: 2.6395 data: 0.0063 max mem: 33369 +Epoch: [9] [1210/1319] eta: 0:04:53 lr: 3.8689266126530076e-05 loss: 0.0755 (0.0917) time: 2.6482 data: 0.0062 max mem: 33369 +Epoch: [9] [1220/1319] eta: 0:04:26 lr: 3.868049028643206e-05 loss: 0.0948 (0.0919) time: 2.6405 data: 0.0063 max mem: 33369 +Epoch: [9] [1230/1319] eta: 0:03:59 lr: 3.867171422509902e-05 loss: 0.0974 (0.0918) time: 2.6234 data: 0.0065 max mem: 33369 +Epoch: [9] [1240/1319] eta: 0:03:32 lr: 3.866293794246959e-05 loss: 0.0911 (0.0920) time: 2.6428 data: 0.0065 max mem: 33369 +Epoch: [9] [1250/1319] eta: 0:03:05 lr: 3.8654161438482394e-05 loss: 0.0966 (0.0920) time: 2.6931 data: 0.0066 max mem: 33369 +Epoch: [9] [1260/1319] eta: 0:02:38 lr: 3.864538471307598e-05 loss: 0.0828 (0.0919) time: 2.7250 data: 0.0067 max mem: 33369 +Epoch: [9] [1270/1319] eta: 0:02:11 lr: 3.863660776618888e-05 loss: 0.0832 (0.0920) time: 2.6778 data: 0.0065 max mem: 33369 +Epoch: [9] [1280/1319] eta: 0:01:44 lr: 3.8627830597759606e-05 loss: 0.0996 (0.0920) time: 2.6551 data: 0.0064 max mem: 33369 +Epoch: [9] [1290/1319] eta: 0:01:17 lr: 3.861905320772664e-05 loss: 0.0996 (0.0922) time: 2.6502 data: 0.0062 max mem: 33369 +Epoch: [9] [1300/1319] eta: 0:00:51 lr: 3.861027559602841e-05 loss: 0.0809 (0.0921) time: 2.6393 data: 0.0062 max mem: 33369 +Epoch: [9] [1310/1319] eta: 0:00:24 lr: 3.860149776260333e-05 loss: 0.0787 (0.0921) time: 2.6248 data: 0.0064 max mem: 33369 +Epoch: [9] Total time: 0:59:03 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 1:59:01 time: 2.7756 data: 2.6967 max mem: 33369 +Test: [ 100/2573] eta: 0:04:03 time: 0.0715 data: 0.0011 max mem: 33369 +Test: [ 200/2573] eta: 0:03:24 time: 0.0732 data: 0.0011 max mem: 33369 +Test: [ 300/2573] eta: 0:03:05 time: 0.0750 data: 0.0011 max mem: 33369 +Test: [ 400/2573] eta: 0:02:52 time: 0.0750 data: 0.0011 max mem: 33369 +Test: [ 500/2573] eta: 0:02:42 time: 0.0736 data: 0.0011 max mem: 33369 +Test: [ 600/2573] eta: 0:02:33 time: 0.0737 data: 0.0011 max mem: 33369 +Test: [ 700/2573] eta: 0:02:24 time: 0.0736 data: 0.0011 max mem: 33369 +Test: [ 800/2573] eta: 0:02:16 time: 0.0768 data: 0.0011 max mem: 33369 +Test: [ 900/2573] eta: 0:02:08 time: 0.0736 data: 0.0011 max mem: 33369 +Test: [1000/2573] eta: 0:02:00 time: 0.0736 data: 0.0011 max mem: 33369 +Test: [1100/2573] eta: 0:01:52 time: 0.0735 data: 0.0011 max mem: 33369 +Test: [1200/2573] eta: 0:01:44 time: 0.0736 data: 0.0011 max mem: 33369 +Test: [1300/2573] eta: 0:01:36 time: 0.0736 data: 0.0011 max mem: 33369 +Test: [1400/2573] eta: 0:01:28 time: 0.0719 data: 0.0011 max mem: 33369 +Test: [1500/2573] eta: 0:01:21 time: 0.0737 data: 0.0011 max mem: 33369 +Test: [1600/2573] eta: 0:01:13 time: 0.0770 data: 0.0011 max mem: 33369 +Test: [1700/2573] eta: 0:01:05 time: 0.0720 data: 0.0011 max mem: 33369 +Test: [1800/2573] eta: 0:00:58 time: 0.0754 data: 0.0011 max mem: 33369 +Test: [1900/2573] eta: 0:00:50 time: 0.0721 data: 0.0011 max mem: 33369 +Test: [2000/2573] eta: 0:00:42 time: 0.0738 data: 0.0011 max mem: 33369 +Test: [2100/2573] eta: 0:00:35 time: 0.0755 data: 0.0011 max mem: 33369 +Test: [2200/2573] eta: 0:00:27 time: 0.0754 data: 0.0011 max mem: 33369 +Test: [2300/2573] eta: 0:00:20 time: 0.0756 data: 0.0011 max mem: 33369 +Test: [2400/2573] eta: 0:00:12 time: 0.0707 data: 0.0011 max mem: 33369 +Test: [2500/2573] eta: 0:00:05 time: 0.0739 data: 0.0011 max mem: 33369 +Test: Total time: 0:03:12 +Final results: +Mean IoU is 58.19 + + precision@0.5 = 65.58 + precision@0.6 = 59.01 + precision@0.7 = 50.92 + precision@0.8 = 39.22 + precision@0.9 = 17.34 + overall IoU = 58.07 + +Average object IoU 58.18772039460918 +Overall IoU 58.06598663330078 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [10] [ 0/1319] eta: 3:00:10 lr: 3.859359752289337e-05 loss: 0.1161 (0.1161) time: 8.1962 data: 2.0172 max mem: 33369 +Epoch: [10] [ 10/1319] eta: 1:09:24 lr: 3.858481926801746e-05 loss: 0.0840 (0.0863) time: 3.1811 data: 0.1890 max mem: 33369 +Epoch: [10] [ 20/1319] eta: 1:03:06 lr: 3.857604079123589e-05 loss: 0.0785 (0.0898) time: 2.6508 data: 0.0060 max mem: 33369 +Epoch: [10] [ 30/1319] eta: 1:00:33 lr: 3.856726209248695e-05 loss: 0.0820 (0.0931) time: 2.6195 data: 0.0061 max mem: 33369 +Epoch: [10] [ 40/1319] eta: 0:59:06 lr: 3.855848317170887e-05 loss: 0.0856 (0.0947) time: 2.6233 data: 0.0065 max mem: 33369 +Epoch: [10] [ 50/1319] eta: 0:58:03 lr: 3.854970402883988e-05 loss: 0.0799 (0.0896) time: 2.6307 data: 0.0067 max mem: 33369 +Epoch: [10] [ 60/1319] eta: 0:57:32 lr: 3.854092466381814e-05 loss: 0.0824 (0.0915) time: 2.6810 data: 0.0066 max mem: 33369 +Epoch: [10] [ 70/1319] eta: 0:56:52 lr: 3.853214507658182e-05 loss: 0.0878 (0.0900) time: 2.7004 data: 0.0063 max mem: 33369 +Epoch: [10] [ 80/1319] eta: 0:56:13 lr: 3.852336526706903e-05 loss: 0.0846 (0.0897) time: 2.6609 data: 0.0063 max mem: 33369 +Epoch: [10] [ 90/1319] eta: 0:55:33 lr: 3.8514585235217835e-05 loss: 0.0774 (0.0911) time: 2.6408 data: 0.0064 max mem: 33369 +Epoch: [10] [ 100/1319] eta: 0:54:55 lr: 3.850580498096631e-05 loss: 0.0774 (0.0919) time: 2.6264 data: 0.0066 max mem: 33369 +Epoch: [10] [ 110/1319] eta: 0:54:22 lr: 3.849702450425245e-05 loss: 0.0846 (0.0915) time: 2.6359 data: 0.0066 max mem: 33369 +Epoch: [10] [ 120/1319] eta: 0:53:53 lr: 3.8488243805014244e-05 loss: 0.0663 (0.0896) time: 2.6650 data: 0.0065 max mem: 33369 +Epoch: [10] [ 130/1319] eta: 0:53:25 lr: 3.8479462883189646e-05 loss: 0.0663 (0.0896) time: 2.6793 data: 0.0068 max mem: 33369 +Epoch: [10] [ 140/1319] eta: 0:53:09 lr: 3.8470681738716575e-05 loss: 0.0819 (0.0884) time: 2.7576 data: 0.0071 max mem: 33369 +Epoch: [10] [ 150/1319] eta: 0:53:08 lr: 3.846190037153291e-05 loss: 0.0743 (0.0877) time: 2.9360 data: 0.0110 max mem: 33369 +Epoch: [10] [ 160/1319] eta: 0:52:48 lr: 3.84531187815765e-05 loss: 0.0743 (0.0873) time: 2.9350 data: 0.0111 max mem: 33369 +Epoch: [10] [ 170/1319] eta: 0:52:32 lr: 3.844433696878517e-05 loss: 0.0726 (0.0881) time: 2.8693 data: 0.0074 max mem: 33369 +Epoch: [10] [ 180/1319] eta: 0:52:15 lr: 3.843555493309671e-05 loss: 0.0723 (0.0869) time: 2.9031 data: 0.0074 max mem: 33369 +Epoch: [10] [ 190/1319] eta: 0:51:54 lr: 3.842677267444885e-05 loss: 0.0823 (0.0874) time: 2.8799 data: 0.0077 max mem: 33369 +Epoch: [10] [ 200/1319] eta: 0:51:31 lr: 3.8417990192779335e-05 loss: 0.0935 (0.0873) time: 2.8532 data: 0.0076 max mem: 33369 +Epoch: [10] [ 210/1319] eta: 0:51:08 lr: 3.8409207488025836e-05 loss: 0.0820 (0.0879) time: 2.8448 data: 0.0076 max mem: 33369 +Epoch: [10] [ 220/1319] eta: 0:50:45 lr: 3.8400424560126e-05 loss: 0.0741 (0.0873) time: 2.8552 data: 0.0079 max mem: 33369 +Epoch: [10] [ 230/1319] eta: 0:50:19 lr: 3.839164140901745e-05 loss: 0.0730 (0.0872) time: 2.8417 data: 0.0081 max mem: 33369 +Epoch: [10] [ 240/1319] eta: 0:49:56 lr: 3.838285803463778e-05 loss: 0.0840 (0.0873) time: 2.8436 data: 0.0080 max mem: 33369 +Epoch: [10] [ 250/1319] eta: 0:49:34 lr: 3.8374074436924536e-05 loss: 0.0858 (0.0874) time: 2.8970 data: 0.0077 max mem: 33369 +Epoch: [10] [ 260/1319] eta: 0:49:10 lr: 3.836529061581523e-05 loss: 0.0784 (0.0868) time: 2.8936 data: 0.0079 max mem: 33369 +Epoch: [10] [ 270/1319] eta: 0:48:44 lr: 3.8356506571247355e-05 loss: 0.0665 (0.0867) time: 2.8546 data: 0.0080 max mem: 33369 +Epoch: [10] [ 280/1319] eta: 0:48:19 lr: 3.834772230315837e-05 loss: 0.0752 (0.0865) time: 2.8496 data: 0.0077 max mem: 33369 +Epoch: [10] [ 290/1319] eta: 0:47:54 lr: 3.833893781148568e-05 loss: 0.0718 (0.0866) time: 2.8602 data: 0.0076 max mem: 33369 +Epoch: [10] [ 300/1319] eta: 0:47:29 lr: 3.833015309616668e-05 loss: 0.0822 (0.0871) time: 2.8729 data: 0.0078 max mem: 33369 +Epoch: [10] [ 310/1319] eta: 0:47:03 lr: 3.832136815713871e-05 loss: 0.0798 (0.0870) time: 2.8713 data: 0.0080 max mem: 33369 +Epoch: [10] [ 320/1319] eta: 0:46:38 lr: 3.83125829943391e-05 loss: 0.0764 (0.0867) time: 2.8796 data: 0.0078 max mem: 33369 +Epoch: [10] [ 330/1319] eta: 0:46:12 lr: 3.830379760770512e-05 loss: 0.0752 (0.0862) time: 2.8792 data: 0.0077 max mem: 33369 +Epoch: [10] [ 340/1319] eta: 0:45:46 lr: 3.829501199717404e-05 loss: 0.0681 (0.0862) time: 2.8790 data: 0.0078 max mem: 33369 +Epoch: [10] [ 350/1319] eta: 0:45:20 lr: 3.828622616268306e-05 loss: 0.0665 (0.0857) time: 2.8901 data: 0.0076 max mem: 33369 +Epoch: [10] [ 360/1319] eta: 0:44:54 lr: 3.8277440104169376e-05 loss: 0.0709 (0.0860) time: 2.8793 data: 0.0077 max mem: 33369 +Epoch: [10] [ 370/1319] eta: 0:44:27 lr: 3.826865382157014e-05 loss: 0.0890 (0.0865) time: 2.8635 data: 0.0079 max mem: 33369 +Epoch: [10] [ 380/1319] eta: 0:43:59 lr: 3.8259867314822454e-05 loss: 0.0890 (0.0865) time: 2.8375 data: 0.0081 max mem: 33369 +Epoch: [10] [ 390/1319] eta: 0:43:33 lr: 3.825108058386341e-05 loss: 0.0802 (0.0865) time: 2.8537 data: 0.0081 max mem: 33369 +Epoch: [10] [ 400/1319] eta: 0:43:05 lr: 3.824229362863006e-05 loss: 0.0750 (0.0866) time: 2.8533 data: 0.0084 max mem: 33369 +Epoch: [10] [ 410/1319] eta: 0:42:38 lr: 3.823350644905941e-05 loss: 0.0715 (0.0865) time: 2.8457 data: 0.0084 max mem: 33369 +Epoch: [10] [ 420/1319] eta: 0:42:11 lr: 3.822471904508845e-05 loss: 0.0772 (0.0864) time: 2.8647 data: 0.0081 max mem: 33369 +Epoch: [10] [ 430/1319] eta: 0:41:45 lr: 3.821593141665413e-05 loss: 0.0699 (0.0861) time: 2.8850 data: 0.0083 max mem: 33369 +Epoch: [10] [ 440/1319] eta: 0:41:18 lr: 3.8207143563693345e-05 loss: 0.0664 (0.0859) time: 2.8921 data: 0.0083 max mem: 33369 +Epoch: [10] [ 450/1319] eta: 0:40:51 lr: 3.819835548614299e-05 loss: 0.0698 (0.0859) time: 2.8767 data: 0.0079 max mem: 33369 +Epoch: [10] [ 460/1319] eta: 0:40:23 lr: 3.8189567183939914e-05 loss: 0.0728 (0.0856) time: 2.8535 data: 0.0080 max mem: 33369 +Epoch: [10] [ 470/1319] eta: 0:39:55 lr: 3.8180778657020925e-05 loss: 0.0728 (0.0860) time: 2.8309 data: 0.0081 max mem: 33369 +Epoch: [10] [ 480/1319] eta: 0:39:28 lr: 3.81719899053228e-05 loss: 0.0843 (0.0862) time: 2.8792 data: 0.0080 max mem: 33369 +Epoch: [10] [ 490/1319] eta: 0:39:01 lr: 3.8163200928782287e-05 loss: 0.0943 (0.0862) time: 2.9123 data: 0.0080 max mem: 33369 +Epoch: [10] [ 500/1319] eta: 0:38:33 lr: 3.8154411727336084e-05 loss: 0.0818 (0.0862) time: 2.8690 data: 0.0082 max mem: 33369 +Epoch: [10] [ 510/1319] eta: 0:38:03 lr: 3.814562230092089e-05 loss: 0.0842 (0.0864) time: 2.7698 data: 0.0082 max mem: 33369 +Epoch: [10] [ 520/1319] eta: 0:37:32 lr: 3.8136832649473325e-05 loss: 0.0771 (0.0862) time: 2.6767 data: 0.0079 max mem: 33369 +Epoch: [10] [ 530/1319] eta: 0:37:01 lr: 3.812804277293001e-05 loss: 0.0685 (0.0862) time: 2.6516 data: 0.0075 max mem: 33369 +Epoch: [10] [ 540/1319] eta: 0:36:31 lr: 3.811925267122751e-05 loss: 0.0778 (0.0862) time: 2.6589 data: 0.0071 max mem: 33369 +Epoch: [10] [ 550/1319] eta: 0:36:01 lr: 3.8110462344302376e-05 loss: 0.0814 (0.0861) time: 2.6729 data: 0.0069 max mem: 33369 +Epoch: [10] [ 560/1319] eta: 0:35:31 lr: 3.8101671792091106e-05 loss: 0.0803 (0.0860) time: 2.6620 data: 0.0070 max mem: 33369 +Epoch: [10] [ 570/1319] eta: 0:35:00 lr: 3.809288101453017e-05 loss: 0.0817 (0.0861) time: 2.6299 data: 0.0069 max mem: 33369 +Epoch: [10] [ 580/1319] eta: 0:34:33 lr: 3.808409001155601e-05 loss: 0.0817 (0.0861) time: 2.7498 data: 0.0069 max mem: 33369 +Epoch: [10] [ 590/1319] eta: 0:34:06 lr: 3.807529878310503e-05 loss: 0.0803 (0.0862) time: 2.8955 data: 0.0075 max mem: 33369 +Epoch: [10] [ 600/1319] eta: 0:33:39 lr: 3.806650732911359e-05 loss: 0.0803 (0.0861) time: 2.9043 data: 0.0076 max mem: 33369 +Epoch: [10] [ 610/1319] eta: 0:33:12 lr: 3.8057715649518045e-05 loss: 0.0644 (0.0860) time: 2.9024 data: 0.0075 max mem: 33369 +Epoch: [10] [ 620/1319] eta: 0:32:45 lr: 3.804892374425468e-05 loss: 0.0733 (0.0861) time: 2.8991 data: 0.0074 max mem: 33369 +Epoch: [10] [ 630/1319] eta: 0:32:18 lr: 3.804013161325975e-05 loss: 0.0767 (0.0860) time: 2.9148 data: 0.0073 max mem: 33369 +Epoch: [10] [ 640/1319] eta: 0:31:51 lr: 3.803133925646951e-05 loss: 0.0784 (0.0860) time: 2.8899 data: 0.0072 max mem: 33369 +Epoch: [10] [ 650/1319] eta: 0:31:24 lr: 3.802254667382014e-05 loss: 0.0758 (0.0859) time: 2.8931 data: 0.0073 max mem: 33369 +Epoch: [10] [ 660/1319] eta: 0:30:56 lr: 3.801375386524781e-05 loss: 0.0711 (0.0858) time: 2.8980 data: 0.0074 max mem: 33369 +Epoch: [10] [ 670/1319] eta: 0:30:28 lr: 3.800496083068865e-05 loss: 0.0728 (0.0858) time: 2.8594 data: 0.0073 max mem: 33369 +Epoch: [10] [ 680/1319] eta: 0:30:00 lr: 3.799616757007876e-05 loss: 0.0730 (0.0856) time: 2.8358 data: 0.0073 max mem: 33369 +Epoch: [10] [ 690/1319] eta: 0:29:32 lr: 3.798737408335417e-05 loss: 0.0764 (0.0860) time: 2.8045 data: 0.0074 max mem: 33369 +Epoch: [10] [ 700/1319] eta: 0:29:04 lr: 3.797858037045094e-05 loss: 0.0655 (0.0858) time: 2.8126 data: 0.0075 max mem: 33369 +Epoch: [10] [ 710/1319] eta: 0:28:36 lr: 3.796978643130504e-05 loss: 0.0602 (0.0857) time: 2.8336 data: 0.0078 max mem: 33369 +Epoch: [10] [ 720/1319] eta: 0:28:07 lr: 3.796099226585244e-05 loss: 0.0700 (0.0858) time: 2.8175 data: 0.0080 max mem: 33369 +Epoch: [10] [ 730/1319] eta: 0:27:39 lr: 3.795219787402904e-05 loss: 0.0719 (0.0859) time: 2.8052 data: 0.0079 max mem: 33369 +Epoch: [10] [ 740/1319] eta: 0:27:11 lr: 3.794340325577075e-05 loss: 0.0806 (0.0858) time: 2.8362 data: 0.0079 max mem: 33369 +Epoch: [10] [ 750/1319] eta: 0:26:43 lr: 3.79346084110134e-05 loss: 0.0823 (0.0858) time: 2.8392 data: 0.0079 max mem: 33369 +Epoch: [10] [ 760/1319] eta: 0:26:15 lr: 3.7925813339692824e-05 loss: 0.0863 (0.0859) time: 2.8016 data: 0.0084 max mem: 33369 +Epoch: [10] [ 770/1319] eta: 0:25:46 lr: 3.79170180417448e-05 loss: 0.0794 (0.0859) time: 2.7870 data: 0.0084 max mem: 33369 +Epoch: [10] [ 780/1319] eta: 0:25:18 lr: 3.790822251710506e-05 loss: 0.0858 (0.0859) time: 2.8095 data: 0.0081 max mem: 33369 +Epoch: [10] [ 790/1319] eta: 0:24:50 lr: 3.789942676570934e-05 loss: 0.0858 (0.0858) time: 2.7950 data: 0.0082 max mem: 33369 +Epoch: [10] [ 800/1319] eta: 0:24:22 lr: 3.7890630787493295e-05 loss: 0.0686 (0.0857) time: 2.8152 data: 0.0084 max mem: 33369 +Epoch: [10] [ 810/1319] eta: 0:23:54 lr: 3.788183458239259e-05 loss: 0.0686 (0.0856) time: 2.8457 data: 0.0083 max mem: 33369 +Epoch: [10] [ 820/1319] eta: 0:23:26 lr: 3.7873038150342824e-05 loss: 0.0689 (0.0854) time: 2.8390 data: 0.0082 max mem: 33369 +Epoch: [10] [ 830/1319] eta: 0:22:57 lr: 3.7864241491279565e-05 loss: 0.0710 (0.0854) time: 2.8267 data: 0.0081 max mem: 33369 +Epoch: [10] [ 840/1319] eta: 0:22:29 lr: 3.785544460513836e-05 loss: 0.0763 (0.0853) time: 2.7991 data: 0.0082 max mem: 33369 +Epoch: [10] [ 850/1319] eta: 0:22:01 lr: 3.784664749185471e-05 loss: 0.0748 (0.0853) time: 2.7799 data: 0.0082 max mem: 33369 +Epoch: [10] [ 860/1319] eta: 0:21:33 lr: 3.7837850151364085e-05 loss: 0.0748 (0.0851) time: 2.7986 data: 0.0082 max mem: 33369 +Epoch: [10] [ 870/1319] eta: 0:21:04 lr: 3.78290525836019e-05 loss: 0.0671 (0.0850) time: 2.8172 data: 0.0083 max mem: 33369 +Epoch: [10] [ 880/1319] eta: 0:20:36 lr: 3.782025478850358e-05 loss: 0.0693 (0.0848) time: 2.8053 data: 0.0083 max mem: 33369 +Epoch: [10] [ 890/1319] eta: 0:20:08 lr: 3.7811456766004476e-05 loss: 0.0693 (0.0849) time: 2.8122 data: 0.0083 max mem: 33369 +Epoch: [10] [ 900/1319] eta: 0:19:40 lr: 3.780265851603992e-05 loss: 0.0737 (0.0849) time: 2.8041 data: 0.0084 max mem: 33369 +Epoch: [10] [ 910/1319] eta: 0:19:11 lr: 3.779386003854519e-05 loss: 0.0792 (0.0853) time: 2.8043 data: 0.0084 max mem: 33369 +Epoch: [10] [ 920/1319] eta: 0:18:43 lr: 3.7785061333455565e-05 loss: 0.0983 (0.0853) time: 2.8230 data: 0.0084 max mem: 33369 +Epoch: [10] [ 930/1319] eta: 0:18:15 lr: 3.7776262400706265e-05 loss: 0.0771 (0.0857) time: 2.7894 data: 0.0084 max mem: 33369 +Epoch: [10] [ 940/1319] eta: 0:17:46 lr: 3.776746324023246e-05 loss: 0.0771 (0.0859) time: 2.7211 data: 0.0084 max mem: 33369 +Epoch: [10] [ 950/1319] eta: 0:17:17 lr: 3.775866385196932e-05 loss: 0.0801 (0.0857) time: 2.6684 data: 0.0082 max mem: 33369 +Epoch: [10] [ 960/1319] eta: 0:16:49 lr: 3.774986423585195e-05 loss: 0.0698 (0.0859) time: 2.6647 data: 0.0074 max mem: 33369 +Epoch: [10] [ 970/1319] eta: 0:16:20 lr: 3.7741064391815444e-05 loss: 0.0771 (0.0860) time: 2.6777 data: 0.0069 max mem: 33369 +Epoch: [10] [ 980/1319] eta: 0:15:52 lr: 3.7732264319794836e-05 loss: 0.0702 (0.0861) time: 2.6657 data: 0.0068 max mem: 33369 +Epoch: [10] [ 990/1319] eta: 0:15:23 lr: 3.772346401972514e-05 loss: 0.0861 (0.0861) time: 2.7337 data: 0.0074 max mem: 33369 +Epoch: [10] [1000/1319] eta: 0:14:56 lr: 3.771466349154134e-05 loss: 0.0861 (0.0861) time: 2.8520 data: 0.0078 max mem: 33369 +Epoch: [10] [1010/1319] eta: 0:14:28 lr: 3.7705862735178374e-05 loss: 0.0716 (0.0861) time: 2.8788 data: 0.0075 max mem: 33369 +Epoch: [10] [1020/1319] eta: 0:14:00 lr: 3.7697061750571136e-05 loss: 0.0740 (0.0861) time: 2.8757 data: 0.0075 max mem: 33369 +Epoch: [10] [1030/1319] eta: 0:13:32 lr: 3.768826053765451e-05 loss: 0.0813 (0.0862) time: 2.9251 data: 0.0075 max mem: 33369 +Epoch: [10] [1040/1319] eta: 0:13:04 lr: 3.767945909636332e-05 loss: 0.0784 (0.0863) time: 2.9035 data: 0.0080 max mem: 33369 +Epoch: [10] [1050/1319] eta: 0:12:36 lr: 3.767065742663237e-05 loss: 0.0685 (0.0861) time: 2.8872 data: 0.0080 max mem: 33369 +Epoch: [10] [1060/1319] eta: 0:12:08 lr: 3.7661855528396415e-05 loss: 0.0685 (0.0861) time: 2.9138 data: 0.0077 max mem: 33369 +Epoch: [10] [1070/1319] eta: 0:11:40 lr: 3.765305340159019e-05 loss: 0.0749 (0.0862) time: 2.8796 data: 0.0076 max mem: 33369 +Epoch: [10] [1080/1319] eta: 0:11:12 lr: 3.764425104614838e-05 loss: 0.0827 (0.0864) time: 2.8593 data: 0.0076 max mem: 33369 +Epoch: [10] [1090/1319] eta: 0:10:44 lr: 3.763544846200565e-05 loss: 0.0876 (0.0863) time: 2.8621 data: 0.0075 max mem: 33369 +Epoch: [10] [1100/1319] eta: 0:10:16 lr: 3.7626645649096614e-05 loss: 0.0779 (0.0864) time: 2.8456 data: 0.0077 max mem: 33369 +Epoch: [10] [1110/1319] eta: 0:09:48 lr: 3.761784260735586e-05 loss: 0.0761 (0.0864) time: 2.8385 data: 0.0079 max mem: 33369 +Epoch: [10] [1120/1319] eta: 0:09:20 lr: 3.760903933671793e-05 loss: 0.0750 (0.0864) time: 2.8145 data: 0.0080 max mem: 33369 +Epoch: [10] [1130/1319] eta: 0:08:52 lr: 3.760023583711735e-05 loss: 0.0718 (0.0864) time: 2.7975 data: 0.0079 max mem: 33369 +Epoch: [10] [1140/1319] eta: 0:08:23 lr: 3.7591432108488584e-05 loss: 0.0701 (0.0864) time: 2.7919 data: 0.0081 max mem: 33369 +Epoch: [10] [1150/1319] eta: 0:07:55 lr: 3.758262815076608e-05 loss: 0.0739 (0.0863) time: 2.7844 data: 0.0082 max mem: 33369 +Epoch: [10] [1160/1319] eta: 0:07:27 lr: 3.7573823963884245e-05 loss: 0.0846 (0.0863) time: 2.8112 data: 0.0081 max mem: 33369 +Epoch: [10] [1170/1319] eta: 0:06:59 lr: 3.756501954777745e-05 loss: 0.0680 (0.0861) time: 2.8214 data: 0.0081 max mem: 33369 +Epoch: [10] [1180/1319] eta: 0:06:31 lr: 3.755621490238003e-05 loss: 0.0780 (0.0862) time: 2.8037 data: 0.0083 max mem: 33369 +Epoch: [10] [1190/1319] eta: 0:06:03 lr: 3.754741002762627e-05 loss: 0.0833 (0.0863) time: 2.7841 data: 0.0084 max mem: 33369 +Epoch: [10] [1200/1319] eta: 0:05:34 lr: 3.753860492345044e-05 loss: 0.0856 (0.0864) time: 2.8022 data: 0.0084 max mem: 33369 +Epoch: [10] [1210/1319] eta: 0:05:06 lr: 3.7529799589786776e-05 loss: 0.0856 (0.0864) time: 2.8191 data: 0.0085 max mem: 33369 +Epoch: [10] [1220/1319] eta: 0:04:38 lr: 3.752099402656945e-05 loss: 0.0880 (0.0864) time: 2.8134 data: 0.0085 max mem: 33369 +Epoch: [10] [1230/1319] eta: 0:04:10 lr: 3.751218823373263e-05 loss: 0.0823 (0.0865) time: 2.7963 data: 0.0087 max mem: 33369 +Epoch: [10] [1240/1319] eta: 0:03:42 lr: 3.750338221121043e-05 loss: 0.0735 (0.0864) time: 2.8032 data: 0.0086 max mem: 33369 +Epoch: [10] [1250/1319] eta: 0:03:14 lr: 3.749457595893693e-05 loss: 0.0652 (0.0865) time: 2.7917 data: 0.0084 max mem: 33369 +Epoch: [10] [1260/1319] eta: 0:02:46 lr: 3.748576947684619e-05 loss: 0.0642 (0.0865) time: 2.7552 data: 0.0081 max mem: 33369 +Epoch: [10] [1270/1319] eta: 0:02:17 lr: 3.74769627648722e-05 loss: 0.0692 (0.0864) time: 2.6938 data: 0.0076 max mem: 33369 +Epoch: [10] [1280/1319] eta: 0:01:49 lr: 3.746815582294894e-05 loss: 0.0777 (0.0864) time: 2.7228 data: 0.0076 max mem: 33369 +Epoch: [10] [1290/1319] eta: 0:01:21 lr: 3.745934865101035e-05 loss: 0.0798 (0.0864) time: 2.8183 data: 0.0078 max mem: 33369 +Epoch: [10] [1300/1319] eta: 0:00:53 lr: 3.7450541248990324e-05 loss: 0.0803 (0.0865) time: 2.8025 data: 0.0080 max mem: 33369 +Epoch: [10] [1310/1319] eta: 0:00:25 lr: 3.7441733616822736e-05 loss: 0.0803 (0.0865) time: 2.7879 data: 0.0083 max mem: 33369 +Epoch: [10] Total time: 1:02:05 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 4:05:10 time: 5.7172 data: 5.5384 max mem: 33369 +Test: [ 100/2573] eta: 0:05:18 time: 0.0727 data: 0.0012 max mem: 33369 +Test: [ 200/2573] eta: 0:04:03 time: 0.0749 data: 0.0013 max mem: 33369 +Test: [ 300/2573] eta: 0:03:31 time: 0.0763 data: 0.0012 max mem: 33369 +Test: [ 400/2573] eta: 0:03:11 time: 0.0766 data: 0.0013 max mem: 33369 +Test: [ 500/2573] eta: 0:02:57 time: 0.0753 data: 0.0013 max mem: 33369 +Test: [ 600/2573] eta: 0:02:45 time: 0.0753 data: 0.0013 max mem: 33369 +Test: [ 700/2573] eta: 0:02:35 time: 0.0752 data: 0.0013 max mem: 33369 +Test: [ 800/2573] eta: 0:02:25 time: 0.0786 data: 0.0013 max mem: 33369 +Test: [ 900/2573] eta: 0:02:16 time: 0.0752 data: 0.0013 max mem: 33369 +Test: [1000/2573] eta: 0:02:07 time: 0.0757 data: 0.0014 max mem: 33369 +Test: [1100/2573] eta: 0:01:58 time: 0.0756 data: 0.0014 max mem: 33369 +Test: [1200/2573] eta: 0:01:50 time: 0.0756 data: 0.0014 max mem: 33369 +Test: [1300/2573] eta: 0:01:41 time: 0.0751 data: 0.0012 max mem: 33369 +Test: [1400/2573] eta: 0:01:33 time: 0.0741 data: 0.0014 max mem: 33369 +Test: [1500/2573] eta: 0:01:25 time: 0.0756 data: 0.0013 max mem: 33369 +Test: [1600/2573] eta: 0:01:16 time: 0.0783 data: 0.0012 max mem: 33369 +Test: [1700/2573] eta: 0:01:08 time: 0.0727 data: 0.0011 max mem: 33369 +Test: [1800/2573] eta: 0:01:00 time: 0.0770 data: 0.0013 max mem: 33369 +Test: [1900/2573] eta: 0:00:52 time: 0.0726 data: 0.0012 max mem: 33369 +Test: [2000/2573] eta: 0:00:44 time: 0.0741 data: 0.0011 max mem: 33369 +Test: [2100/2573] eta: 0:00:36 time: 0.0757 data: 0.0011 max mem: 33369 +Test: [2200/2573] eta: 0:00:28 time: 0.0758 data: 0.0011 max mem: 33369 +Test: [2300/2573] eta: 0:00:21 time: 0.0758 data: 0.0012 max mem: 33369 +Test: [2400/2573] eta: 0:00:13 time: 0.0704 data: 0.0011 max mem: 33369 +Test: [2500/2573] eta: 0:00:05 time: 0.0739 data: 0.0011 max mem: 33369 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: Total time: 0:03:18 +Final results: +Mean IoU is 60.71 + + precision@0.5 = 67.65 + precision@0.6 = 60.72 + precision@0.7 = 52.57 + precision@0.8 = 40.81 + precision@0.9 = 18.53 + overall IoU = 58.85 + +Average object IoU 60.71476583654809 +Overall IoU 58.8515510559082 +Better epoch: 10 + +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [11] [ 0/1319] eta: 1:32:47 lr: 3.743380655104104e-05 loss: 0.0815 (0.0815) time: 4.2208 data: 1.3886 max mem: 33369 +Epoch: [11] [ 10/1319] eta: 1:01:43 lr: 3.742499848141075e-05 loss: 0.0750 (0.0833) time: 2.8294 data: 0.1318 max mem: 33369 +Epoch: [11] [ 20/1319] eta: 0:59:27 lr: 3.741619018144089e-05 loss: 0.0769 (0.0912) time: 2.6722 data: 0.0060 max mem: 33369 +Epoch: [11] [ 30/1319] eta: 0:58:26 lr: 3.7407381651065185e-05 loss: 0.0843 (0.0910) time: 2.6600 data: 0.0062 max mem: 33369 +Epoch: [11] [ 40/1319] eta: 0:57:41 lr: 3.739857289021734e-05 loss: 0.0796 (0.0883) time: 2.6653 data: 0.0066 max mem: 33369 +Epoch: [11] [ 50/1319] eta: 0:57:00 lr: 3.738976389883098e-05 loss: 0.0777 (0.0891) time: 2.6573 data: 0.0066 max mem: 33369 +Epoch: [11] [ 60/1319] eta: 0:56:44 lr: 3.738095467683973e-05 loss: 0.0671 (0.0856) time: 2.6984 data: 0.0068 max mem: 33369 +Epoch: [11] [ 70/1319] eta: 0:56:29 lr: 3.737214522417717e-05 loss: 0.0671 (0.0848) time: 2.7592 data: 0.0069 max mem: 33369 +Epoch: [11] [ 80/1319] eta: 0:56:32 lr: 3.736333554077684e-05 loss: 0.0736 (0.0835) time: 2.8407 data: 0.0074 max mem: 33369 +Epoch: [11] [ 90/1319] eta: 0:56:26 lr: 3.735452562657224e-05 loss: 0.0807 (0.0842) time: 2.9052 data: 0.0077 max mem: 33369 +Epoch: [11] [ 100/1319] eta: 0:56:15 lr: 3.734571548149683e-05 loss: 0.0807 (0.0843) time: 2.8979 data: 0.0077 max mem: 33369 +Epoch: [11] [ 110/1319] eta: 0:56:02 lr: 3.733690510548406e-05 loss: 0.0708 (0.0828) time: 2.8974 data: 0.0078 max mem: 33369 +Epoch: [11] [ 120/1319] eta: 0:55:47 lr: 3.732809449846732e-05 loss: 0.0683 (0.0822) time: 2.9063 data: 0.0077 max mem: 33369 +Epoch: [11] [ 130/1319] eta: 0:55:31 lr: 3.7319283660379954e-05 loss: 0.0628 (0.0804) time: 2.9151 data: 0.0075 max mem: 33369 +Epoch: [11] [ 140/1319] eta: 0:55:12 lr: 3.7310472591155297e-05 loss: 0.0631 (0.0800) time: 2.9146 data: 0.0077 max mem: 33369 +Epoch: [11] [ 150/1319] eta: 0:54:49 lr: 3.7301661290726626e-05 loss: 0.0759 (0.0811) time: 2.8930 data: 0.0077 max mem: 33369 +Epoch: [11] [ 160/1319] eta: 0:54:21 lr: 3.729284975902719e-05 loss: 0.0759 (0.0817) time: 2.8445 data: 0.0077 max mem: 33369 +Epoch: [11] [ 170/1319] eta: 0:53:58 lr: 3.728403799599019e-05 loss: 0.0613 (0.0809) time: 2.8576 data: 0.0079 max mem: 33369 +Epoch: [11] [ 180/1319] eta: 0:53:29 lr: 3.727522600154881e-05 loss: 0.0716 (0.0811) time: 2.8476 data: 0.0080 max mem: 33369 +Epoch: [11] [ 190/1319] eta: 0:53:01 lr: 3.7266413775636196e-05 loss: 0.0809 (0.0820) time: 2.8138 data: 0.0080 max mem: 33369 +Epoch: [11] [ 200/1319] eta: 0:52:32 lr: 3.725760131818543e-05 loss: 0.0666 (0.0810) time: 2.8106 data: 0.0081 max mem: 33369 +Epoch: [11] [ 210/1319] eta: 0:52:01 lr: 3.724878862912958e-05 loss: 0.0610 (0.0808) time: 2.7819 data: 0.0083 max mem: 33369 +Epoch: [11] [ 220/1319] eta: 0:51:30 lr: 3.723997570840168e-05 loss: 0.0684 (0.0806) time: 2.7662 data: 0.0083 max mem: 33369 +Epoch: [11] [ 230/1319] eta: 0:51:01 lr: 3.723116255593471e-05 loss: 0.0684 (0.0803) time: 2.7736 data: 0.0083 max mem: 33369 +Epoch: [11] [ 240/1319] eta: 0:50:32 lr: 3.7222349171661633e-05 loss: 0.0753 (0.0808) time: 2.7873 data: 0.0083 max mem: 33369 +Epoch: [11] [ 250/1319] eta: 0:50:02 lr: 3.721353555551535e-05 loss: 0.0791 (0.0804) time: 2.7770 data: 0.0084 max mem: 33369 +Epoch: [11] [ 260/1319] eta: 0:49:34 lr: 3.720472170742875e-05 loss: 0.0791 (0.0814) time: 2.7921 data: 0.0085 max mem: 33369 +Epoch: [11] [ 270/1319] eta: 0:49:04 lr: 3.719590762733466e-05 loss: 0.0813 (0.0815) time: 2.7913 data: 0.0084 max mem: 33369 +Epoch: [11] [ 280/1319] eta: 0:48:36 lr: 3.718709331516589e-05 loss: 0.0751 (0.0816) time: 2.7827 data: 0.0082 max mem: 33369 +Epoch: [11] [ 290/1319] eta: 0:48:09 lr: 3.7178278770855225e-05 loss: 0.0716 (0.0814) time: 2.8154 data: 0.0082 max mem: 33369 +Epoch: [11] [ 300/1319] eta: 0:47:42 lr: 3.716946399433537e-05 loss: 0.0750 (0.0813) time: 2.8348 data: 0.0085 max mem: 33369 +Epoch: 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mem: 33369 +Epoch: [11] [ 390/1319] eta: 0:43:29 lr: 3.709012054512541e-05 loss: 0.0825 (0.0813) time: 2.8236 data: 0.0087 max mem: 33369 +Epoch: [11] [ 400/1319] eta: 0:43:01 lr: 3.7081303442805645e-05 loss: 0.0765 (0.0815) time: 2.7951 data: 0.0086 max mem: 33369 +Epoch: [11] [ 410/1319] eta: 0:42:32 lr: 3.7072486107534264e-05 loss: 0.0701 (0.0813) time: 2.7771 data: 0.0084 max mem: 33369 +Epoch: [11] [ 420/1319] eta: 0:42:01 lr: 3.706366853924354e-05 loss: 0.0657 (0.0812) time: 2.7328 data: 0.0083 max mem: 33369 +Epoch: [11] [ 430/1319] eta: 0:41:30 lr: 3.705485073786572e-05 loss: 0.0669 (0.0811) time: 2.6754 data: 0.0076 max mem: 33369 +Epoch: [11] [ 440/1319] eta: 0:41:01 lr: 3.704603270333301e-05 loss: 0.0836 (0.0813) time: 2.6919 data: 0.0070 max mem: 33369 +Epoch: [11] [ 450/1319] eta: 0:40:30 lr: 3.703721443557757e-05 loss: 0.0846 (0.0815) time: 2.7048 data: 0.0070 max mem: 33369 +Epoch: [11] [ 460/1319] eta: 0:40:01 lr: 3.702839593453153e-05 loss: 0.0752 (0.0815) time: 2.7104 data: 0.0072 max mem: 33369 +Epoch: [11] [ 470/1319] eta: 0:39:35 lr: 3.7019577200126995e-05 loss: 0.0700 (0.0816) time: 2.8137 data: 0.0078 max mem: 33369 +Epoch: [11] [ 480/1319] eta: 0:39:09 lr: 3.701075823229601e-05 loss: 0.0633 (0.0813) time: 2.8849 data: 0.0081 max mem: 33369 +Epoch: [11] [ 490/1319] eta: 0:38:42 lr: 3.700193903097059e-05 loss: 0.0643 (0.0813) time: 2.9001 data: 0.0077 max mem: 33369 +Epoch: [11] [ 500/1319] eta: 0:38:16 lr: 3.6993119596082715e-05 loss: 0.0758 (0.0813) time: 2.8915 data: 0.0077 max mem: 33369 +Epoch: [11] [ 510/1319] eta: 0:37:49 lr: 3.698429992756433e-05 loss: 0.0805 (0.0812) time: 2.8935 data: 0.0075 max mem: 33369 +Epoch: [11] [ 520/1319] eta: 0:37:23 lr: 3.6975480025347336e-05 loss: 0.0756 (0.0813) time: 2.9055 data: 0.0074 max mem: 33369 +Epoch: [11] [ 530/1319] eta: 0:36:56 lr: 3.69666598893636e-05 loss: 0.0668 (0.0809) time: 2.9133 data: 0.0077 max mem: 33369 +Epoch: [11] [ 540/1319] eta: 0:36:29 lr: 3.695783951954495e-05 loss: 0.0681 (0.0810) time: 2.9027 data: 0.0076 max mem: 33369 +Epoch: [11] [ 550/1319] eta: 0:36:01 lr: 3.694901891582318e-05 loss: 0.0853 (0.0812) time: 2.8502 data: 0.0073 max mem: 33369 +Epoch: [11] [ 560/1319] eta: 0:35:33 lr: 3.694019807813003e-05 loss: 0.0792 (0.0811) time: 2.8251 data: 0.0074 max mem: 33369 +Epoch: [11] [ 570/1319] eta: 0:35:06 lr: 3.6931377006397214e-05 loss: 0.0677 (0.0809) time: 2.8510 data: 0.0077 max mem: 33369 +Epoch: [11] [ 580/1319] eta: 0:34:38 lr: 3.692255570055642e-05 loss: 0.0695 (0.0809) time: 2.8422 data: 0.0079 max mem: 33369 +Epoch: [11] [ 590/1319] eta: 0:34:10 lr: 3.691373416053928e-05 loss: 0.0765 (0.0808) time: 2.8045 data: 0.0082 max mem: 33369 +Epoch: [11] [ 600/1319] eta: 0:33:42 lr: 3.690491238627739e-05 loss: 0.0697 (0.0808) time: 2.8076 data: 0.0083 max mem: 33369 +Epoch: [11] [ 610/1319] eta: 0:33:13 lr: 3.6896090377702305e-05 loss: 0.0823 (0.0811) time: 2.8090 data: 0.0084 max mem: 33369 +Epoch: [11] [ 620/1319] eta: 0:32:45 lr: 3.688726813474555e-05 loss: 0.0823 (0.0810) time: 2.8107 data: 0.0085 max mem: 33369 +Epoch: [11] [ 630/1319] eta: 0:32:16 lr: 3.687844565733862e-05 loss: 0.0696 (0.0810) time: 2.7871 data: 0.0083 max mem: 33369 +Epoch: [11] [ 640/1319] eta: 0:31:49 lr: 3.686962294541296e-05 loss: 0.0696 (0.0808) time: 2.7887 data: 0.0084 max mem: 33369 +Epoch: [11] [ 650/1319] eta: 0:31:21 lr: 3.686079999889997e-05 loss: 0.0778 (0.0814) time: 2.8382 data: 0.0084 max mem: 33369 +Epoch: [11] [ 660/1319] eta: 0:30:53 lr: 3.6851976817731035e-05 loss: 0.0887 (0.0815) time: 2.8634 data: 0.0084 max mem: 33369 +Epoch: [11] [ 670/1319] eta: 0:30:25 lr: 3.684315340183746e-05 loss: 0.0705 (0.0814) time: 2.8510 data: 0.0083 max mem: 33369 +Epoch: [11] [ 680/1319] eta: 0:29:57 lr: 3.683432975115057e-05 loss: 0.0694 (0.0813) time: 2.8037 data: 0.0083 max mem: 33369 +Epoch: [11] [ 690/1319] eta: 0:29:28 lr: 3.682550586560159e-05 loss: 0.0833 (0.0813) time: 2.7808 data: 0.0085 max mem: 33369 +Epoch: [11] [ 700/1319] eta: 0:29:01 lr: 3.6816681745121755e-05 loss: 0.0857 (0.0814) time: 2.8108 data: 0.0085 max mem: 33369 +Epoch: [11] [ 710/1319] eta: 0:28:33 lr: 3.680785738964223e-05 loss: 0.0731 (0.0812) time: 2.8414 data: 0.0085 max mem: 33369 +Epoch: [11] [ 720/1319] eta: 0:28:05 lr: 3.679903279909417e-05 loss: 0.0682 (0.0811) time: 2.8347 data: 0.0084 max mem: 33369 +Epoch: [11] [ 730/1319] eta: 0:27:37 lr: 3.679020797340866e-05 loss: 0.0836 (0.0813) time: 2.8286 data: 0.0085 max mem: 33369 +Epoch: [11] [ 740/1319] eta: 0:27:09 lr: 3.678138291251678e-05 loss: 0.0853 (0.0814) time: 2.8433 data: 0.0085 max mem: 33369 +Epoch: [11] [ 750/1319] eta: 0:26:41 lr: 3.677255761634953e-05 loss: 0.0840 (0.0814) time: 2.8276 data: 0.0086 max mem: 33369 +Epoch: [11] [ 760/1319] eta: 0:26:13 lr: 3.6763732084837915e-05 loss: 0.0913 (0.0817) time: 2.8133 data: 0.0086 max mem: 33369 +Epoch: [11] [ 770/1319] eta: 0:25:44 lr: 3.675490631791288e-05 loss: 0.0988 (0.0818) time: 2.8165 data: 0.0084 max mem: 33369 +Epoch: 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max mem: 33369 +Epoch: [11] [ 860/1319] eta: 0:21:27 lr: 3.667546381057031e-05 loss: 0.0669 (0.0816) time: 2.6281 data: 0.0068 max mem: 33369 +Epoch: [11] [ 870/1319] eta: 0:20:58 lr: 3.666663568570454e-05 loss: 0.0584 (0.0819) time: 2.6604 data: 0.0069 max mem: 33369 +Epoch: [11] [ 880/1319] eta: 0:20:30 lr: 3.665780732466318e-05 loss: 0.0623 (0.0817) time: 2.7758 data: 0.0073 max mem: 33369 +Epoch: [11] [ 890/1319] eta: 0:20:03 lr: 3.6648978727376724e-05 loss: 0.0622 (0.0817) time: 2.8962 data: 0.0077 max mem: 33369 +Epoch: [11] [ 900/1319] eta: 0:19:35 lr: 3.664014989377562e-05 loss: 0.0622 (0.0816) time: 2.9082 data: 0.0078 max mem: 33369 +Epoch: [11] [ 910/1319] eta: 0:19:07 lr: 3.663132082379026e-05 loss: 0.0657 (0.0815) time: 2.9043 data: 0.0077 max mem: 33369 +Epoch: [11] [ 920/1319] eta: 0:18:40 lr: 3.6622491517351006e-05 loss: 0.0758 (0.0815) time: 2.9096 data: 0.0077 max mem: 33369 +Epoch: [11] [ 930/1319] eta: 0:18:13 lr: 3.661366197438818e-05 loss: 0.0745 (0.0814) time: 2.9458 data: 0.0076 max mem: 33369 +Epoch: [11] [ 940/1319] eta: 0:17:45 lr: 3.660483219483207e-05 loss: 0.0745 (0.0814) time: 2.9425 data: 0.0076 max mem: 33369 +Epoch: [11] [ 950/1319] eta: 0:17:17 lr: 3.659600217861292e-05 loss: 0.0726 (0.0814) time: 2.9163 data: 0.0077 max mem: 33369 +Epoch: [11] [ 960/1319] eta: 0:16:49 lr: 3.658717192566094e-05 loss: 0.0726 (0.0815) time: 2.8896 data: 0.0075 max mem: 33369 +Epoch: [11] [ 970/1319] eta: 0:16:21 lr: 3.6578341435906296e-05 loss: 0.0712 (0.0814) time: 2.8486 data: 0.0074 max mem: 33369 +Epoch: [11] [ 980/1319] eta: 0:15:53 lr: 3.656951070927911e-05 loss: 0.0643 (0.0813) time: 2.8354 data: 0.0076 max mem: 33369 +Epoch: [11] [ 990/1319] eta: 0:15:25 lr: 3.656067974570946e-05 loss: 0.0580 (0.0812) time: 2.8130 data: 0.0079 max mem: 33369 +Epoch: [11] [1000/1319] eta: 0:14:57 lr: 3.655184854512743e-05 loss: 0.0595 (0.0812) time: 2.8188 data: 0.0080 max mem: 33369 +Epoch: [11] [1010/1319] eta: 0:14:29 lr: 3.654301710746299e-05 loss: 0.0596 (0.0811) time: 2.8333 data: 0.0080 max mem: 33369 +Epoch: [11] [1020/1319] eta: 0:14:01 lr: 3.653418543264612e-05 loss: 0.0596 (0.0809) time: 2.8177 data: 0.0082 max mem: 33369 +Epoch: [11] [1030/1319] eta: 0:13:32 lr: 3.652535352060675e-05 loss: 0.0731 (0.0810) time: 2.7847 data: 0.0085 max mem: 33369 +Epoch: [11] [1040/1319] eta: 0:13:04 lr: 3.651652137127478e-05 loss: 0.0781 (0.0809) time: 2.7832 data: 0.0085 max mem: 33369 +Epoch: [11] [1050/1319] eta: 0:12:36 lr: 3.6507688984580056e-05 loss: 0.0726 (0.0810) time: 2.8142 data: 0.0086 max mem: 33369 +Epoch: [11] [1060/1319] eta: 0:12:08 lr: 3.649885636045239e-05 loss: 0.0747 (0.0809) time: 2.8353 data: 0.0088 max mem: 33369 +Epoch: [11] [1070/1319] eta: 0:11:40 lr: 3.6490023498821546e-05 loss: 0.0673 (0.0808) time: 2.8268 data: 0.0087 max mem: 33369 +Epoch: [11] [1080/1319] eta: 0:11:12 lr: 3.648119039961727e-05 loss: 0.0661 (0.0807) time: 2.8166 data: 0.0086 max mem: 33369 +Epoch: [11] [1090/1319] eta: 0:10:44 lr: 3.647235706276924e-05 loss: 0.0672 (0.0806) time: 2.8145 data: 0.0086 max mem: 33369 +Epoch: [11] [1100/1319] eta: 0:10:16 lr: 3.646352348820711e-05 loss: 0.0648 (0.0805) time: 2.7979 data: 0.0086 max mem: 33369 +Epoch: [11] [1110/1319] eta: 0:09:47 lr: 3.6454689675860496e-05 loss: 0.0630 (0.0804) time: 2.8052 data: 0.0085 max mem: 33369 +Epoch: [11] [1120/1319] eta: 0:09:19 lr: 3.6445855625658975e-05 loss: 0.0741 (0.0805) time: 2.7947 data: 0.0084 max mem: 33369 +Epoch: [11] [1130/1319] eta: 0:08:51 lr: 3.643702133753208e-05 loss: 0.0748 (0.0805) time: 2.7986 data: 0.0083 max mem: 33369 +Epoch: [11] [1140/1319] eta: 0:08:23 lr: 3.6428186811409296e-05 loss: 0.0669 (0.0805) time: 2.8349 data: 0.0083 max mem: 33369 +Epoch: [11] [1150/1319] eta: 0:07:55 lr: 3.641935204722008e-05 loss: 0.0741 (0.0805) time: 2.8462 data: 0.0085 max mem: 33369 +Epoch: [11] [1160/1319] eta: 0:07:27 lr: 3.6410517044893844e-05 loss: 0.0745 (0.0804) time: 2.8446 data: 0.0085 max mem: 33369 +Epoch: [11] [1170/1319] eta: 0:06:59 lr: 3.6401681804359965e-05 loss: 0.0680 (0.0803) time: 2.8416 data: 0.0083 max mem: 33369 +Epoch: [11] [1180/1319] eta: 0:06:31 lr: 3.6392846325547776e-05 loss: 0.0606 (0.0805) time: 2.8283 data: 0.0084 max mem: 33369 +Epoch: [11] [1190/1319] eta: 0:06:02 lr: 3.638401060838657e-05 loss: 0.0728 (0.0805) time: 2.8267 data: 0.0084 max mem: 33369 +Epoch: [11] [1200/1319] eta: 0:05:34 lr: 3.63751746528056e-05 loss: 0.0699 (0.0806) time: 2.8132 data: 0.0083 max mem: 33369 +Epoch: [11] [1210/1319] eta: 0:05:06 lr: 3.636633845873407e-05 loss: 0.0685 (0.0808) time: 2.8121 data: 0.0086 max mem: 33369 +Epoch: [11] [1220/1319] eta: 0:04:38 lr: 3.6357502026101176e-05 loss: 0.0869 (0.0808) time: 2.7637 data: 0.0084 max mem: 33369 +Epoch: [11] [1230/1319] eta: 0:04:10 lr: 3.6348665354836024e-05 loss: 0.0869 (0.0808) time: 2.6559 data: 0.0082 max mem: 33369 +Epoch: [11] [1240/1319] eta: 0:03:41 lr: 3.6339828444867725e-05 loss: 0.0874 (0.0809) time: 2.6371 data: 0.0079 max mem: 33369 +Epoch: [11] [1250/1319] eta: 0:03:13 lr: 3.6330991296125324e-05 loss: 0.0699 (0.0808) time: 2.6547 data: 0.0072 max mem: 33369 +Epoch: [11] [1260/1319] eta: 0:02:45 lr: 3.632215390853783e-05 loss: 0.0687 (0.0808) time: 2.6753 data: 0.0070 max mem: 33369 +Epoch: [11] [1270/1319] eta: 0:02:17 lr: 3.631331628203422e-05 loss: 0.0783 (0.0809) time: 2.8016 data: 0.0072 max mem: 33369 +Epoch: [11] [1280/1319] eta: 0:01:49 lr: 3.630447841654343e-05 loss: 0.0780 (0.0808) time: 2.8993 data: 0.0076 max mem: 33369 +Epoch: [11] [1290/1319] eta: 0:01:21 lr: 3.629564031199434e-05 loss: 0.0777 (0.0808) time: 2.9012 data: 0.0084 max mem: 33369 +Epoch: [11] [1300/1319] eta: 0:00:53 lr: 3.6286801968315816e-05 loss: 0.0777 (0.0808) time: 2.8776 data: 0.0083 max mem: 33369 +Epoch: [11] [1310/1319] eta: 0:00:25 lr: 3.627796338543665e-05 loss: 0.0776 (0.0808) time: 2.8909 data: 0.0075 max mem: 33369 +Epoch: [11] Total time: 1:01:49 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 2:14:41 time: 3.1408 data: 3.0597 max mem: 33369 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 100/2573] eta: 0:04:16 time: 0.0734 data: 0.0014 max mem: 33369 +Test: [ 200/2573] eta: 0:03:33 time: 0.0752 data: 0.0014 max mem: 33369 +Test: [ 300/2573] eta: 0:03:12 time: 0.0767 data: 0.0013 max mem: 33369 +Test: [ 400/2573] eta: 0:02:58 time: 0.0767 data: 0.0013 max mem: 33369 +Test: [ 500/2573] eta: 0:02:47 time: 0.0753 data: 0.0013 max mem: 33369 +Test: [ 600/2573] eta: 0:02:37 time: 0.0755 data: 0.0013 max mem: 33369 +Test: [ 700/2573] eta: 0:02:29 time: 0.0754 data: 0.0013 max mem: 33369 +Test: [ 800/2573] eta: 0:02:20 time: 0.0788 data: 0.0013 max mem: 33369 +Test: [ 900/2573] eta: 0:02:12 time: 0.0755 data: 0.0014 max mem: 33369 +Test: [1000/2573] eta: 0:02:03 time: 0.0755 data: 0.0013 max mem: 33369 +Test: [1100/2573] eta: 0:01:55 time: 0.0756 data: 0.0013 max mem: 33369 +Test: [1200/2573] eta: 0:01:47 time: 0.0758 data: 0.0013 max mem: 33369 +Test: [1300/2573] eta: 0:01:39 time: 0.0757 data: 0.0013 max mem: 33369 +Test: [1400/2573] eta: 0:01:31 time: 0.0737 data: 0.0013 max mem: 33369 +Test: [1500/2573] eta: 0:01:23 time: 0.0757 data: 0.0013 max mem: 33369 +Test: [1600/2573] eta: 0:01:15 time: 0.0790 data: 0.0013 max mem: 33369 +Test: [1700/2573] eta: 0:01:07 time: 0.0740 data: 0.0013 max mem: 33369 +Test: [1800/2573] eta: 0:00:59 time: 0.0773 data: 0.0013 max mem: 33369 +Test: [1900/2573] eta: 0:00:51 time: 0.0739 data: 0.0013 max mem: 33369 +Test: [2000/2573] eta: 0:00:44 time: 0.0759 data: 0.0013 max mem: 33369 +Test: [2100/2573] eta: 0:00:36 time: 0.0772 data: 0.0013 max mem: 33369 +Test: [2200/2573] eta: 0:00:28 time: 0.0772 data: 0.0013 max mem: 33369 +Test: [2300/2573] eta: 0:00:20 time: 0.0775 data: 0.0013 max mem: 33369 +Test: [2400/2573] eta: 0:00:13 time: 0.0722 data: 0.0014 max mem: 33369 +Test: [2500/2573] eta: 0:00:05 time: 0.0755 data: 0.0013 max mem: 33369 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: Total time: 0:03:17 +Final results: +Mean IoU is 60.78 + + precision@0.5 = 68.38 + precision@0.6 = 62.13 + precision@0.7 = 54.06 + precision@0.8 = 41.99 + precision@0.9 = 17.83 + overall IoU = 59.16 + +Average object IoU 60.778012858543576 +Overall IoU 59.159385681152344 +Better epoch: 11 + +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [12] [ 0/1319] eta: 1:44:17 lr: 3.6270008456269996e-05 loss: 0.0759 (0.0759) time: 4.7442 data: 1.5384 max mem: 33369 +Epoch: [12] [ 10/1319] eta: 1:11:34 lr: 3.6261169418713356e-05 loss: 0.0615 (0.0666) time: 3.2807 data: 0.1468 max mem: 33369 +Epoch: [12] [ 20/1319] eta: 1:09:16 lr: 3.62523301417494e-05 loss: 0.0661 (0.0703) time: 3.1225 data: 0.0077 max mem: 33369 +Epoch: [12] [ 30/1319] eta: 1:07:45 lr: 3.624349062530679e-05 loss: 0.0747 (0.0758) time: 3.0847 data: 0.0079 max mem: 33369 +Epoch: [12] [ 40/1319] eta: 1:06:54 lr: 3.623465086931413e-05 loss: 0.0718 (0.0747) time: 3.0741 data: 0.0082 max mem: 33369 +Epoch: [12] [ 50/1319] eta: 1:06:02 lr: 3.62258108737e-05 loss: 0.0725 (0.0760) time: 3.0724 data: 0.0083 max mem: 33369 +Epoch: [12] [ 60/1319] eta: 1:05:27 lr: 3.621697063839292e-05 loss: 0.0685 (0.0750) time: 3.0813 data: 0.0084 max mem: 33369 +Epoch: [12] [ 70/1319] eta: 1:04:59 lr: 3.6208130163321375e-05 loss: 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3.613739772263389e-05 loss: 0.0719 (0.0750) time: 3.0783 data: 0.0086 max mem: 33369 +Epoch: [12] [ 160/1319] eta: 0:59:56 lr: 3.6128555086457536e-05 loss: 0.0713 (0.0745) time: 3.0888 data: 0.0086 max mem: 33369 +Epoch: [12] [ 170/1319] eta: 0:59:25 lr: 3.6119712209799373e-05 loss: 0.0713 (0.0746) time: 3.1066 data: 0.0084 max mem: 33369 +Epoch: [12] [ 180/1319] eta: 0:58:51 lr: 3.6110869092587446e-05 loss: 0.0736 (0.0751) time: 3.0846 data: 0.0083 max mem: 33369 +Epoch: [12] [ 190/1319] eta: 0:58:19 lr: 3.610202573474975e-05 loss: 0.0639 (0.0745) time: 3.0724 data: 0.0083 max mem: 33369 +Epoch: [12] [ 200/1319] eta: 0:57:41 lr: 3.609318213621424e-05 loss: 0.0630 (0.0743) time: 3.0290 data: 0.0082 max mem: 33369 +Epoch: [12] [ 210/1319] eta: 0:56:58 lr: 3.608433829690883e-05 loss: 0.0681 (0.0747) time: 2.9170 data: 0.0081 max mem: 33369 +Epoch: [12] [ 220/1319] eta: 0:56:09 lr: 3.607549421676141e-05 loss: 0.0681 (0.0746) time: 2.7833 data: 0.0077 max mem: 33369 +Epoch: [12] [ 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(0.0751) time: 2.8386 data: 0.0083 max mem: 33369 +Epoch: [12] [ 470/1319] eta: 0:41:40 lr: 3.585431372760496e-05 loss: 0.0614 (0.0751) time: 2.8403 data: 0.0083 max mem: 33369 +Epoch: [12] [ 480/1319] eta: 0:41:09 lr: 3.5845463360113225e-05 loss: 0.0587 (0.0750) time: 2.8396 data: 0.0084 max mem: 33369 +Epoch: [12] [ 490/1319] eta: 0:40:38 lr: 3.583661274981637e-05 loss: 0.0652 (0.0750) time: 2.8538 data: 0.0085 max mem: 33369 +Epoch: [12] [ 500/1319] eta: 0:40:07 lr: 3.582776189664111e-05 loss: 0.0652 (0.0750) time: 2.8416 data: 0.0087 max mem: 33369 +Epoch: [12] [ 510/1319] eta: 0:39:35 lr: 3.581891080051412e-05 loss: 0.0693 (0.0750) time: 2.7996 data: 0.0088 max mem: 33369 +Epoch: [12] [ 520/1319] eta: 0:39:04 lr: 3.5810059461362006e-05 loss: 0.0590 (0.0749) time: 2.8129 data: 0.0088 max mem: 33369 +Epoch: [12] [ 530/1319] eta: 0:38:33 lr: 3.580120787911136e-05 loss: 0.0590 (0.0746) time: 2.8241 data: 0.0085 max mem: 33369 +Epoch: [12] [ 540/1319] eta: 0:38:02 lr: 3.579235605368871e-05 loss: 0.0640 (0.0748) time: 2.8155 data: 0.0084 max mem: 33369 +Epoch: [12] [ 550/1319] eta: 0:37:30 lr: 3.578350398502055e-05 loss: 0.0826 (0.0750) time: 2.7930 data: 0.0086 max mem: 33369 +Epoch: [12] [ 560/1319] eta: 0:36:59 lr: 3.5774651673033346e-05 loss: 0.0670 (0.0749) time: 2.7852 data: 0.0087 max mem: 33369 +Epoch: [12] [ 570/1319] eta: 0:36:29 lr: 3.57657991176535e-05 loss: 0.0630 (0.0749) time: 2.8016 data: 0.0086 max mem: 33369 +Epoch: [12] [ 580/1319] eta: 0:35:58 lr: 3.5756946318807374e-05 loss: 0.0615 (0.0747) time: 2.8108 data: 0.0084 max mem: 33369 +Epoch: [12] [ 590/1319] eta: 0:35:28 lr: 3.5748093276421306e-05 loss: 0.0625 (0.0750) time: 2.8396 data: 0.0084 max mem: 33369 +Epoch: [12] [ 600/1319] eta: 0:34:58 lr: 3.573923999042157e-05 loss: 0.0691 (0.0750) time: 2.8461 data: 0.0085 max mem: 33369 +Epoch: [12] [ 610/1319] eta: 0:34:26 lr: 3.573038646073439e-05 loss: 0.0665 (0.0752) time: 2.7614 data: 0.0085 max mem: 33369 +Epoch: [12] [ 620/1319] eta: 0:33:54 lr: 3.5721532687286004e-05 loss: 0.0820 (0.0759) time: 2.6635 data: 0.0085 max mem: 33369 +Epoch: [12] [ 630/1319] eta: 0:33:22 lr: 3.571267867000252e-05 loss: 0.0590 (0.0756) time: 2.6449 data: 0.0077 max mem: 33369 +Epoch: [12] [ 640/1319] eta: 0:32:50 lr: 3.570382440881008e-05 loss: 0.0598 (0.0756) time: 2.6661 data: 0.0070 max mem: 33369 +Epoch: [12] [ 650/1319] eta: 0:32:19 lr: 3.5694969903634736e-05 loss: 0.0670 (0.0754) time: 2.6541 data: 0.0072 max mem: 33369 +Epoch: [12] [ 660/1319] eta: 0:31:47 lr: 3.568611515440253e-05 loss: 0.0606 (0.0754) time: 2.6494 data: 0.0073 max mem: 33369 +Epoch: [12] [ 670/1319] eta: 0:31:19 lr: 3.567726016103943e-05 loss: 0.0697 (0.0754) time: 2.7930 data: 0.0077 max mem: 33369 +Epoch: [12] [ 680/1319] eta: 0:30:49 lr: 3.5668404923471386e-05 loss: 0.0570 (0.0753) time: 2.9003 data: 0.0081 max mem: 33369 +Epoch: [12] [ 690/1319] eta: 0:30:21 lr: 3.565954944162429e-05 loss: 0.0676 (0.0757) time: 2.8903 data: 0.0079 max mem: 33369 +Epoch: [12] [ 700/1319] eta: 0:29:51 lr: 3.5650693715424005e-05 loss: 0.0688 (0.0757) time: 2.8928 data: 0.0076 max mem: 33369 +Epoch: [12] [ 710/1319] eta: 0:29:23 lr: 3.564183774479633e-05 loss: 0.0628 (0.0754) time: 2.8983 data: 0.0078 max mem: 33369 +Epoch: [12] [ 720/1319] eta: 0:28:54 lr: 3.563298152966704e-05 loss: 0.0507 (0.0752) time: 2.9173 data: 0.0078 max mem: 33369 +Epoch: [12] [ 730/1319] eta: 0:28:25 lr: 3.562412506996187e-05 loss: 0.0577 (0.0751) time: 2.9344 data: 0.0078 max mem: 33369 +Epoch: [12] [ 740/1319] eta: 0:27:57 lr: 3.561526836560649e-05 loss: 0.0612 (0.0751) time: 2.9390 data: 0.0079 max mem: 33369 +Epoch: [12] [ 750/1319] eta: 0:27:28 lr: 3.560641141652653e-05 loss: 0.0578 (0.0750) time: 2.9223 data: 0.0079 max mem: 33369 +Epoch: [12] [ 760/1319] eta: 0:26:59 lr: 3.5597554222647605e-05 loss: 0.0578 (0.0750) time: 2.8869 data: 0.0079 max mem: 33369 +Epoch: [12] [ 770/1319] eta: 0:26:29 lr: 3.558869678389526e-05 loss: 0.0599 (0.0750) time: 2.8590 data: 0.0078 max mem: 33369 +Epoch: [12] [ 780/1319] eta: 0:26:00 lr: 3.5579839100195013e-05 loss: 0.0715 (0.0749) time: 2.8585 data: 0.0077 max mem: 33369 +Epoch: [12] [ 790/1319] eta: 0:25:31 lr: 3.5570981171472317e-05 loss: 0.0716 (0.0751) time: 2.8493 data: 0.0080 max mem: 33369 +Epoch: [12] [ 800/1319] eta: 0:25:01 lr: 3.55621229976526e-05 loss: 0.0757 (0.0753) time: 2.8325 data: 0.0082 max mem: 33369 +Epoch: [12] [ 810/1319] eta: 0:24:32 lr: 3.555326457866125e-05 loss: 0.0693 (0.0751) time: 2.7967 data: 0.0085 max mem: 33369 +Epoch: [12] [ 820/1319] eta: 0:24:02 lr: 3.554440591442359e-05 loss: 0.0623 (0.0751) time: 2.8044 data: 0.0083 max mem: 33369 +Epoch: [12] [ 830/1319] eta: 0:23:33 lr: 3.5535547004864924e-05 loss: 0.0623 (0.0749) time: 2.8520 data: 0.0080 max mem: 33369 +Epoch: [12] [ 840/1319] eta: 0:23:04 lr: 3.552668784991049e-05 loss: 0.0636 (0.0749) time: 2.8317 data: 0.0081 max mem: 33369 +Epoch: [12] [ 850/1319] eta: 0:22:35 lr: 3.551782844948551e-05 loss: 0.0679 (0.0748) time: 2.8145 data: 0.0083 max mem: 33369 +Epoch: [12] [ 860/1319] eta: 0:22:05 lr: 3.550896880351513e-05 loss: 0.0583 (0.0746) time: 2.8103 data: 0.0084 max mem: 33369 +Epoch: [12] [ 870/1319] eta: 0:21:36 lr: 3.550010891192448e-05 loss: 0.0587 (0.0745) time: 2.8074 data: 0.0082 max mem: 33369 +Epoch: [12] [ 880/1319] eta: 0:21:07 lr: 3.549124877463863e-05 loss: 0.0606 (0.0746) time: 2.8283 data: 0.0082 max mem: 33369 +Epoch: [12] [ 890/1319] eta: 0:20:38 lr: 3.548238839158261e-05 loss: 0.0702 (0.0747) time: 2.8233 data: 0.0084 max mem: 33369 +Epoch: [12] [ 900/1319] eta: 0:20:09 lr: 3.5473527762681414e-05 loss: 0.0790 (0.0747) time: 2.8302 data: 0.0087 max mem: 33369 +Epoch: [12] [ 910/1319] eta: 0:19:40 lr: 3.546466688785999e-05 loss: 0.0723 (0.0748) time: 2.8438 data: 0.0086 max mem: 33369 +Epoch: [12] [ 920/1319] eta: 0:19:10 lr: 3.545580576704322e-05 loss: 0.0656 (0.0747) time: 2.8287 data: 0.0084 max mem: 33369 +Epoch: [12] [ 930/1319] eta: 0:18:42 lr: 3.544694440015598e-05 loss: 0.0706 (0.0747) time: 2.8404 data: 0.0083 max mem: 33369 +Epoch: [12] [ 940/1319] eta: 0:18:12 lr: 3.543808278712307e-05 loss: 0.0730 (0.0749) time: 2.8430 data: 0.0081 max mem: 33369 +Epoch: [12] [ 950/1319] eta: 0:17:43 lr: 3.542922092786927e-05 loss: 0.0718 (0.0750) time: 2.8164 data: 0.0082 max mem: 33369 +Epoch: [12] [ 960/1319] eta: 0:17:14 lr: 3.542035882231929e-05 loss: 0.0670 (0.0750) time: 2.8136 data: 0.0085 max mem: 33369 +Epoch: [12] [ 970/1319] eta: 0:16:45 lr: 3.541149647039783e-05 loss: 0.0709 (0.0751) time: 2.8604 data: 0.0085 max mem: 33369 +Epoch: [12] [ 980/1319] eta: 0:16:16 lr: 3.540263387202951e-05 loss: 0.0738 (0.0751) time: 2.8634 data: 0.0084 max mem: 33369 +Epoch: [12] [ 990/1319] eta: 0:15:47 lr: 3.5393771027138936e-05 loss: 0.0703 (0.0751) time: 2.8111 data: 0.0084 max mem: 33369 +Epoch: [12] [1000/1319] eta: 0:15:18 lr: 3.5384907935650645e-05 loss: 0.0680 (0.0751) time: 2.7991 data: 0.0080 max mem: 33369 +Epoch: [12] [1010/1319] eta: 0:14:49 lr: 3.5376044597489155e-05 loss: 0.0680 (0.0752) time: 2.7589 data: 0.0081 max mem: 33369 +Epoch: [12] [1020/1319] eta: 0:14:20 lr: 3.536718101257892e-05 loss: 0.0782 (0.0752) time: 2.7065 data: 0.0084 max mem: 33369 +Epoch: [12] [1030/1319] eta: 0:13:50 lr: 3.5358317180844356e-05 loss: 0.0728 (0.0752) time: 2.6932 data: 0.0076 max mem: 33369 +Epoch: [12] [1040/1319] eta: 0:13:21 lr: 3.5349453102209835e-05 loss: 0.0617 (0.0754) time: 2.6835 data: 0.0070 max mem: 33369 +Epoch: [12] [1050/1319] eta: 0:12:52 lr: 3.534058877659969e-05 loss: 0.0614 (0.0754) time: 2.6768 data: 0.0072 max mem: 33369 +Epoch: [12] [1060/1319] eta: 0:12:23 lr: 3.5331724203938196e-05 loss: 0.0701 (0.0754) time: 2.7970 data: 0.0076 max mem: 33369 +Epoch: [12] [1070/1319] eta: 0:11:55 lr: 3.53228593841496e-05 loss: 0.0731 (0.0753) time: 2.9024 data: 0.0080 max mem: 33369 +Epoch: [12] [1080/1319] eta: 0:11:26 lr: 3.53139943171581e-05 loss: 0.0738 (0.0754) time: 2.8871 data: 0.0078 max mem: 33369 +Epoch: [12] [1090/1319] eta: 0:10:57 lr: 3.5305129002887835e-05 loss: 0.0782 (0.0754) time: 2.8858 data: 0.0078 max mem: 33369 +Epoch: [12] [1100/1319] eta: 0:10:29 lr: 3.529626344126292e-05 loss: 0.0665 (0.0754) time: 2.9205 data: 0.0079 max mem: 33369 +Epoch: [12] [1110/1319] eta: 0:10:00 lr: 3.5287397632207417e-05 loss: 0.0645 (0.0753) time: 2.9332 data: 0.0076 max mem: 33369 +Epoch: [12] [1120/1319] eta: 0:09:31 lr: 3.527853157564535e-05 loss: 0.0695 (0.0753) time: 2.9380 data: 0.0077 max mem: 33369 +Epoch: [12] [1130/1319] eta: 0:09:03 lr: 3.526966527150067e-05 loss: 0.0703 (0.0754) time: 2.9537 data: 0.0076 max mem: 33369 +Epoch: [12] [1140/1319] eta: 0:08:34 lr: 3.5260798719697326e-05 loss: 0.0841 (0.0755) time: 2.8923 data: 0.0075 max mem: 33369 +Epoch: [12] [1150/1319] eta: 0:08:05 lr: 3.52519319201592e-05 loss: 0.0831 (0.0755) time: 2.8640 data: 0.0077 max mem: 33369 +Epoch: [12] [1160/1319] eta: 0:07:36 lr: 3.524306487281011e-05 loss: 0.0710 (0.0755) time: 2.8474 data: 0.0081 max mem: 33369 +Epoch: [12] [1170/1319] eta: 0:07:08 lr: 3.523419757757387e-05 loss: 0.0691 (0.0755) time: 2.8366 data: 0.0084 max mem: 33369 +Epoch: [12] [1180/1319] eta: 0:06:39 lr: 3.5225330034374235e-05 loss: 0.0683 (0.0755) time: 2.8545 data: 0.0082 max mem: 33369 +Epoch: [12] [1190/1319] eta: 0:06:10 lr: 3.5216462243134885e-05 loss: 0.0680 (0.0754) time: 2.8351 data: 0.0079 max mem: 33369 +Epoch: [12] [1200/1319] eta: 0:05:41 lr: 3.52075942037795e-05 loss: 0.0579 (0.0755) time: 2.8383 data: 0.0081 max mem: 33369 +Epoch: [12] [1210/1319] eta: 0:05:13 lr: 3.519872591623169e-05 loss: 0.0555 (0.0753) time: 2.8544 data: 0.0084 max mem: 33369 +Epoch: [12] [1220/1319] eta: 0:04:44 lr: 3.518985738041502e-05 loss: 0.0666 (0.0754) time: 2.8329 data: 0.0083 max mem: 33369 +Epoch: [12] [1230/1319] eta: 0:04:15 lr: 3.518098859625303e-05 loss: 0.0792 (0.0754) time: 2.8298 data: 0.0081 max mem: 33369 +Epoch: [12] [1240/1319] eta: 0:03:46 lr: 3.517211956366918e-05 loss: 0.0735 (0.0754) time: 2.8468 data: 0.0081 max mem: 33369 +Epoch: [12] [1250/1319] eta: 0:03:18 lr: 3.5163250282586914e-05 loss: 0.0699 (0.0754) time: 2.8382 data: 0.0083 max mem: 33369 +Epoch: [12] [1260/1319] eta: 0:02:49 lr: 3.515438075292963e-05 loss: 0.0695 (0.0754) time: 2.8529 data: 0.0084 max mem: 33369 +Epoch: [12] [1270/1319] eta: 0:02:20 lr: 3.514551097462066e-05 loss: 0.0750 (0.0755) time: 2.8491 data: 0.0084 max mem: 33369 +Epoch: [12] [1280/1319] eta: 0:01:51 lr: 3.513664094758331e-05 loss: 0.0752 (0.0755) time: 2.8337 data: 0.0084 max mem: 33369 +Epoch: [12] [1290/1319] eta: 0:01:23 lr: 3.512777067174083e-05 loss: 0.0732 (0.0755) time: 2.8419 data: 0.0085 max mem: 33369 +Epoch: [12] [1300/1319] eta: 0:00:54 lr: 3.511890014701643e-05 loss: 0.0654 (0.0755) time: 2.8374 data: 0.0085 max mem: 33369 +Epoch: [12] [1310/1319] eta: 0:00:25 lr: 3.511002937333328e-05 loss: 0.0566 (0.0755) time: 2.8335 data: 0.0082 max mem: 33369 +Epoch: [12] Total time: 1:03:06 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 2:12:46 time: 3.0960 data: 2.9938 max mem: 33369 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 100/2573] eta: 0:04:16 time: 0.0730 data: 0.0013 max mem: 33369 +Test: [ 200/2573] eta: 0:03:33 time: 0.0751 data: 0.0014 max mem: 33369 +Test: [ 300/2573] eta: 0:03:11 time: 0.0767 data: 0.0014 max mem: 33369 +Test: [ 400/2573] eta: 0:02:58 time: 0.0769 data: 0.0014 max mem: 33369 +Test: [ 500/2573] eta: 0:02:47 time: 0.0752 data: 0.0013 max mem: 33369 +Test: [ 600/2573] eta: 0:02:37 time: 0.0754 data: 0.0014 max mem: 33369 +Test: [ 700/2573] eta: 0:02:28 time: 0.0752 data: 0.0013 max mem: 33369 +Test: [ 800/2573] eta: 0:02:20 time: 0.0784 data: 0.0013 max mem: 33369 +Test: [ 900/2573] eta: 0:02:11 time: 0.0752 data: 0.0013 max mem: 33369 +Test: [1000/2573] eta: 0:02:03 time: 0.0755 data: 0.0014 max mem: 33369 +Test: [1100/2573] eta: 0:01:55 time: 0.0755 data: 0.0013 max mem: 33369 +Test: [1200/2573] eta: 0:01:47 time: 0.0755 data: 0.0013 max mem: 33369 +Test: [1300/2573] eta: 0:01:39 time: 0.0755 data: 0.0013 max mem: 33369 +Test: [1400/2573] eta: 0:01:31 time: 0.0738 data: 0.0014 max mem: 33369 +Test: [1500/2573] eta: 0:01:23 time: 0.0754 data: 0.0013 max mem: 33369 +Test: [1600/2573] eta: 0:01:15 time: 0.0790 data: 0.0014 max mem: 33369 +Test: [1700/2573] eta: 0:01:07 time: 0.0738 data: 0.0013 max mem: 33369 +Test: [1800/2573] eta: 0:00:59 time: 0.0774 data: 0.0013 max mem: 33369 +Test: [1900/2573] eta: 0:00:51 time: 0.0739 data: 0.0014 max mem: 33369 +Test: [2000/2573] eta: 0:00:44 time: 0.0755 data: 0.0014 max mem: 33369 +Test: [2100/2573] eta: 0:00:36 time: 0.0771 data: 0.0013 max mem: 33369 +Test: [2200/2573] eta: 0:00:28 time: 0.0771 data: 0.0013 max mem: 33369 +Test: [2300/2573] eta: 0:00:20 time: 0.0770 data: 0.0013 max mem: 33369 +Test: [2400/2573] eta: 0:00:13 time: 0.0722 data: 0.0014 max mem: 33369 +Test: [2500/2573] eta: 0:00:05 time: 0.0757 data: 0.0014 max mem: 33369 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: Total time: 0:03:17 +Final results: +Mean IoU is 61.64 + + precision@0.5 = 69.59 + precision@0.6 = 62.72 + precision@0.7 = 54.86 + precision@0.8 = 43.22 + precision@0.9 = 19.36 + overall IoU = 59.99 + +Average object IoU 61.6443689355426 +Overall IoU 59.98695755004883 +Better epoch: 12 + +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [13] [ 0/1319] eta: 1:38:43 lr: 3.510204546409517e-05 loss: 0.0545 (0.0545) time: 4.4906 data: 1.6565 max mem: 33369 +Epoch: [13] [ 10/1319] eta: 1:02:09 lr: 3.509317421717855e-05 loss: 0.0645 (0.0794) time: 2.8492 data: 0.1571 max mem: 33369 +Epoch: [13] [ 20/1319] eta: 0:59:47 lr: 3.50843027210801e-05 loss: 0.0645 (0.0763) time: 2.6751 data: 0.0067 max mem: 33369 +Epoch: [13] [ 30/1319] eta: 0:58:41 lr: 3.5075430975722793e-05 loss: 0.0649 (0.0791) time: 2.6671 data: 0.0067 max mem: 33369 +Epoch: [13] [ 40/1319] eta: 0:58:00 lr: 3.506655898102959e-05 loss: 0.0674 (0.0775) time: 2.6785 data: 0.0069 max mem: 33369 +Epoch: [13] [ 50/1319] eta: 0:57:09 lr: 3.505768673692337e-05 loss: 0.0636 (0.0750) time: 2.6582 data: 0.0067 max mem: 33369 +Epoch: [13] [ 60/1319] eta: 0:56:36 lr: 3.5048814243327e-05 loss: 0.0674 (0.0771) time: 2.6506 data: 0.0069 max mem: 33369 +Epoch: [13] [ 70/1319] eta: 0:56:40 lr: 3.503994150016327e-05 loss: 0.0674 (0.0768) time: 2.7737 data: 0.0075 max mem: 33369 +Epoch: [13] [ 80/1319] eta: 0:56:41 lr: 3.503106850735495e-05 loss: 0.0599 (0.0750) time: 2.8891 data: 0.0077 max mem: 33369 +Epoch: [13] [ 90/1319] eta: 0:56:36 lr: 3.502219526482476e-05 loss: 0.0566 (0.0738) time: 2.9068 data: 0.0074 max mem: 33369 +Epoch: [13] [ 100/1319] eta: 0:56:27 lr: 3.501332177249536e-05 loss: 0.0566 (0.0719) time: 2.9143 data: 0.0075 max mem: 33369 +Epoch: [13] [ 110/1319] eta: 0:56:12 lr: 3.500444803028936e-05 loss: 0.0539 (0.0712) time: 2.9106 data: 0.0075 max mem: 33369 +Epoch: [13] [ 120/1319] eta: 0:55:58 lr: 3.499557403812936e-05 loss: 0.0585 (0.0716) time: 2.9158 data: 0.0074 max mem: 33369 +Epoch: [13] [ 130/1319] eta: 0:55:42 lr: 3.498669979593787e-05 loss: 0.0604 (0.0711) time: 2.9309 data: 0.0076 max mem: 33369 +Epoch: [13] [ 140/1319] eta: 0:55:24 lr: 3.497782530363739e-05 loss: 0.0649 (0.0715) time: 2.9331 data: 0.0075 max mem: 33369 +Epoch: [13] [ 150/1319] eta: 0:55:03 lr: 3.4968950561150356e-05 loss: 0.0631 (0.0708) time: 2.9217 data: 0.0073 max mem: 33369 +Epoch: [13] [ 160/1319] eta: 0:54:36 lr: 3.496007556839915e-05 loss: 0.0590 (0.0714) time: 2.8770 data: 0.0076 max mem: 33369 +Epoch: [13] [ 170/1319] eta: 0:54:07 lr: 3.495120032530614e-05 loss: 0.0521 (0.0704) time: 2.8314 data: 0.0077 max mem: 33369 +Epoch: [13] [ 180/1319] eta: 0:53:41 lr: 3.49423248317936e-05 loss: 0.0535 (0.0704) time: 2.8368 data: 0.0076 max mem: 33369 +Epoch: [13] [ 190/1319] eta: 0:53:15 lr: 3.493344908778381e-05 loss: 0.0540 (0.0704) time: 2.8606 data: 0.0077 max mem: 33369 +Epoch: [13] [ 200/1319] eta: 0:52:48 lr: 3.4924573093198975e-05 loss: 0.0548 (0.0700) time: 2.8629 data: 0.0077 max mem: 33369 +Epoch: [13] [ 210/1319] eta: 0:52:21 lr: 3.491569684796125e-05 loss: 0.0612 (0.0701) time: 2.8612 data: 0.0078 max mem: 33369 +Epoch: [13] [ 220/1319] eta: 0:51:55 lr: 3.490682035199276e-05 loss: 0.0644 (0.0700) time: 2.8673 data: 0.0079 max mem: 33369 +Epoch: [13] [ 230/1319] eta: 0:51:28 lr: 3.4897943605215565e-05 loss: 0.0705 (0.0708) time: 2.8696 data: 0.0079 max mem: 33369 +Epoch: [13] [ 240/1319] eta: 0:51:01 lr: 3.488906660755169e-05 loss: 0.0672 (0.0708) time: 2.8643 data: 0.0080 max mem: 33369 +Epoch: [13] [ 250/1319] eta: 0:50:32 lr: 3.4880189358923125e-05 loss: 0.0567 (0.0703) time: 2.8374 data: 0.0082 max mem: 33369 +Epoch: [13] [ 260/1319] eta: 0:50:05 lr: 3.487131185925179e-05 loss: 0.0618 (0.0704) time: 2.8488 data: 0.0085 max mem: 33369 +Epoch: [13] [ 270/1319] eta: 0:49:39 lr: 3.486243410845958e-05 loss: 0.0572 (0.0699) time: 2.8908 data: 0.0085 max mem: 33369 +Epoch: [13] [ 280/1319] eta: 0:49:12 lr: 3.485355610646832e-05 loss: 0.0538 (0.0701) time: 2.8820 data: 0.0083 max mem: 33369 +Epoch: [13] [ 290/1319] eta: 0:48:44 lr: 3.484467785319982e-05 loss: 0.0524 (0.0696) time: 2.8668 data: 0.0084 max mem: 33369 +Epoch: [13] [ 300/1319] eta: 0:48:16 lr: 3.483579934857581e-05 loss: 0.0539 (0.0698) time: 2.8653 data: 0.0084 max mem: 33369 +Epoch: [13] [ 310/1319] eta: 0:47:47 lr: 3.4826920592518003e-05 loss: 0.0603 (0.0696) time: 2.8427 data: 0.0084 max mem: 33369 +Epoch: [13] [ 320/1319] eta: 0:47:19 lr: 3.481804158494804e-05 loss: 0.0617 (0.0697) time: 2.8288 data: 0.0085 max mem: 33369 +Epoch: [13] [ 330/1319] eta: 0:46:49 lr: 3.4809162325787535e-05 loss: 0.0624 (0.0699) time: 2.8181 data: 0.0082 max mem: 33369 +Epoch: [13] [ 340/1319] eta: 0:46:22 lr: 3.480028281495805e-05 loss: 0.0642 (0.0699) time: 2.8431 data: 0.0080 max mem: 33369 +Epoch: [13] [ 350/1319] eta: 0:45:53 lr: 3.479140305238109e-05 loss: 0.0642 (0.0699) time: 2.8502 data: 0.0081 max mem: 33369 +Epoch: [13] [ 360/1319] eta: 0:45:24 lr: 3.478252303797812e-05 loss: 0.0689 (0.0704) time: 2.8178 data: 0.0083 max mem: 33369 +Epoch: [13] [ 370/1319] eta: 0:44:55 lr: 3.4773642771670566e-05 loss: 0.0621 (0.0703) time: 2.8229 data: 0.0086 max mem: 33369 +Epoch: [13] [ 380/1319] eta: 0:44:27 lr: 3.47647622533798e-05 loss: 0.0567 (0.0702) time: 2.8338 data: 0.0085 max mem: 33369 +Epoch: [13] [ 390/1319] eta: 0:43:58 lr: 3.475588148302715e-05 loss: 0.0597 (0.0701) time: 2.8381 data: 0.0083 max mem: 33369 +Epoch: [13] [ 400/1319] eta: 0:43:29 lr: 3.474700046053388e-05 loss: 0.0611 (0.0699) time: 2.8156 data: 0.0080 max mem: 33369 +Epoch: [13] [ 410/1319] eta: 0:42:57 lr: 3.473811918582123e-05 loss: 0.0631 (0.0699) time: 2.7550 data: 0.0080 max mem: 33369 +Epoch: [13] [ 420/1319] eta: 0:42:25 lr: 3.47292376588104e-05 loss: 0.0693 (0.0699) time: 2.6746 data: 0.0080 max mem: 33369 +Epoch: [13] [ 430/1319] eta: 0:41:53 lr: 3.472035587942251e-05 loss: 0.0693 (0.0703) time: 2.6430 data: 0.0074 max mem: 33369 +Epoch: [13] [ 440/1319] eta: 0:41:22 lr: 3.4711473847578654e-05 loss: 0.0726 (0.0706) time: 2.6777 data: 0.0069 max mem: 33369 +Epoch: [13] [ 450/1319] eta: 0:40:51 lr: 3.470259156319988e-05 loss: 0.0847 (0.0710) time: 2.7008 data: 0.0067 max mem: 33369 +Epoch: [13] [ 460/1319] eta: 0:40:21 lr: 3.469370902620718e-05 loss: 0.0718 (0.0708) time: 2.6908 data: 0.0066 max mem: 33369 +Epoch: [13] [ 470/1319] eta: 0:39:54 lr: 3.4684826236521504e-05 loss: 0.0633 (0.0711) time: 2.7931 data: 0.0072 max mem: 33369 +Epoch: [13] [ 480/1319] eta: 0:39:27 lr: 3.467594319406376e-05 loss: 0.0641 (0.0712) time: 2.8973 data: 0.0080 max mem: 33369 +Epoch: [13] [ 490/1319] eta: 0:38:59 lr: 3.466705989875479e-05 loss: 0.0592 (0.0708) time: 2.8637 data: 0.0079 max mem: 33369 +Epoch: [13] [ 500/1319] eta: 0:38:33 lr: 3.465817635051541e-05 loss: 0.0613 (0.0708) time: 2.8844 data: 0.0077 max mem: 33369 +Epoch: [13] [ 510/1319] eta: 0:38:06 lr: 3.4649292549266374e-05 loss: 0.0709 (0.0707) time: 2.9368 data: 0.0077 max mem: 33369 +Epoch: [13] [ 520/1319] eta: 0:37:40 lr: 3.464040849492841e-05 loss: 0.0656 (0.0706) time: 2.9426 data: 0.0073 max mem: 33369 +Epoch: [13] [ 530/1319] eta: 0:37:12 lr: 3.463152418742217e-05 loss: 0.0656 (0.0706) time: 2.9222 data: 0.0074 max mem: 33369 +Epoch: [13] [ 540/1319] eta: 0:36:45 lr: 3.4622639626668276e-05 loss: 0.0566 (0.0706) time: 2.9072 data: 0.0077 max mem: 33369 +Epoch: [13] [ 550/1319] eta: 0:36:19 lr: 3.461375481258729e-05 loss: 0.0514 (0.0705) time: 2.9260 data: 0.0077 max mem: 33369 +Epoch: [13] [ 560/1319] eta: 0:35:51 lr: 3.460486974509975e-05 loss: 0.0677 (0.0705) time: 2.9207 data: 0.0075 max mem: 33369 +Epoch: [13] [ 570/1319] eta: 0:35:23 lr: 3.4595984424126115e-05 loss: 0.0713 (0.0706) time: 2.8930 data: 0.0077 max mem: 33369 +Epoch: [13] [ 580/1319] eta: 0:34:56 lr: 3.458709884958682e-05 loss: 0.0687 (0.0706) time: 2.8825 data: 0.0078 max mem: 33369 +Epoch: [13] [ 590/1319] eta: 0:34:27 lr: 3.457821302140224e-05 loss: 0.0687 (0.0708) time: 2.8529 data: 0.0079 max mem: 33369 +Epoch: [13] [ 600/1319] eta: 0:33:59 lr: 3.456932693949272e-05 loss: 0.0632 (0.0708) time: 2.8350 data: 0.0081 max mem: 33369 +Epoch: [13] [ 610/1319] eta: 0:33:31 lr: 3.456044060377853e-05 loss: 0.0706 (0.0711) time: 2.8739 data: 0.0079 max mem: 33369 +Epoch: [13] [ 620/1319] eta: 0:33:03 lr: 3.455155401417991e-05 loss: 0.0730 (0.0712) time: 2.8699 data: 0.0079 max mem: 33369 +Epoch: [13] [ 630/1319] eta: 0:32:35 lr: 3.4542667170617054e-05 loss: 0.0659 (0.0713) time: 2.8402 data: 0.0081 max mem: 33369 +Epoch: [13] [ 640/1319] eta: 0:32:06 lr: 3.453378007301009e-05 loss: 0.0599 (0.0711) time: 2.8444 data: 0.0080 max mem: 33369 +Epoch: [13] [ 650/1319] eta: 0:31:38 lr: 3.4524892721279126e-05 loss: 0.0590 (0.0710) time: 2.8247 data: 0.0080 max mem: 33369 +Epoch: [13] [ 660/1319] eta: 0:31:09 lr: 3.4516005115344196e-05 loss: 0.0531 (0.0708) time: 2.8012 data: 0.0082 max mem: 33369 +Epoch: [13] [ 670/1319] eta: 0:30:40 lr: 3.45071172551253e-05 loss: 0.0555 (0.0707) time: 2.8055 data: 0.0083 max mem: 33369 +Epoch: [13] [ 680/1319] eta: 0:30:12 lr: 3.4498229140542384e-05 loss: 0.0629 (0.0707) time: 2.8371 data: 0.0083 max mem: 33369 +Epoch: [13] [ 690/1319] eta: 0:29:44 lr: 3.448934077151535e-05 loss: 0.0710 (0.0707) time: 2.8524 data: 0.0084 max mem: 33369 +Epoch: [13] [ 700/1319] eta: 0:29:16 lr: 3.448045214796405e-05 loss: 0.0639 (0.0708) time: 2.8571 data: 0.0085 max mem: 33369 +Epoch: [13] [ 710/1319] eta: 0:28:47 lr: 3.447156326980829e-05 loss: 0.0639 (0.0707) time: 2.8455 data: 0.0084 max mem: 33369 +Epoch: [13] [ 720/1319] eta: 0:28:19 lr: 3.446267413696782e-05 loss: 0.0643 (0.0706) time: 2.8306 data: 0.0083 max mem: 33369 +Epoch: [13] [ 730/1319] eta: 0:27:51 lr: 3.445378474936235e-05 loss: 0.0580 (0.0705) time: 2.8428 data: 0.0082 max mem: 33369 +Epoch: [13] [ 740/1319] eta: 0:27:22 lr: 3.444489510691154e-05 loss: 0.0586 (0.0704) time: 2.8379 data: 0.0082 max mem: 33369 +Epoch: [13] [ 750/1319] eta: 0:26:54 lr: 3.443600520953501e-05 loss: 0.0738 (0.0706) time: 2.8475 data: 0.0083 max mem: 33369 +Epoch: [13] [ 760/1319] eta: 0:26:26 lr: 3.4427115057152303e-05 loss: 0.0705 (0.0705) time: 2.8538 data: 0.0084 max mem: 33369 +Epoch: [13] [ 770/1319] eta: 0:25:57 lr: 3.441822464968295e-05 loss: 0.0650 (0.0705) time: 2.8383 data: 0.0086 max mem: 33369 +Epoch: [13] [ 780/1319] eta: 0:25:29 lr: 3.44093339870464e-05 loss: 0.0706 (0.0705) time: 2.8287 data: 0.0086 max mem: 33369 +Epoch: [13] [ 790/1319] eta: 0:25:00 lr: 3.4400443069162084e-05 loss: 0.0611 (0.0705) time: 2.8251 data: 0.0084 max mem: 33369 +Epoch: [13] [ 800/1319] eta: 0:24:32 lr: 3.439155189594936e-05 loss: 0.0647 (0.0705) time: 2.8252 data: 0.0085 max mem: 33369 +Epoch: [13] [ 810/1319] eta: 0:24:03 lr: 3.4382660467327555e-05 loss: 0.0661 (0.0705) time: 2.7579 data: 0.0084 max mem: 33369 +Epoch: [13] [ 820/1319] eta: 0:23:33 lr: 3.437376878321594e-05 loss: 0.0615 (0.0707) time: 2.6874 data: 0.0085 max mem: 33369 +Epoch: [13] [ 830/1319] eta: 0:23:04 lr: 3.436487684353372e-05 loss: 0.0662 (0.0708) time: 2.6808 data: 0.0080 max mem: 33369 +Epoch: [13] [ 840/1319] eta: 0:22:35 lr: 3.435598464820009e-05 loss: 0.0662 (0.0707) time: 2.6635 data: 0.0071 max mem: 33369 +Epoch: [13] [ 850/1319] eta: 0:22:06 lr: 3.434709219713417e-05 loss: 0.0605 (0.0705) time: 2.6602 data: 0.0068 max mem: 33369 +Epoch: [13] [ 860/1319] eta: 0:21:37 lr: 3.433819949025503e-05 loss: 0.0585 (0.0705) time: 2.7435 data: 0.0070 max mem: 33369 +Epoch: [13] [ 870/1319] eta: 0:21:09 lr: 3.432930652748169e-05 loss: 0.0630 (0.0704) time: 2.8561 data: 0.0077 max mem: 33369 +Epoch: [13] [ 880/1319] eta: 0:20:41 lr: 3.432041330873315e-05 loss: 0.0626 (0.0706) time: 2.8776 data: 0.0079 max mem: 33369 +Epoch: [13] [ 890/1319] eta: 0:20:13 lr: 3.4311519833928315e-05 loss: 0.0659 (0.0707) time: 2.8713 data: 0.0078 max mem: 33369 +Epoch: [13] [ 900/1319] eta: 0:19:45 lr: 3.430262610298607e-05 loss: 0.0684 (0.0708) time: 2.8966 data: 0.0076 max mem: 33369 +Epoch: [13] [ 910/1319] eta: 0:19:17 lr: 3.429373211582526e-05 loss: 0.0645 (0.0709) time: 2.8996 data: 0.0076 max mem: 33369 +Epoch: [13] [ 920/1319] eta: 0:18:49 lr: 3.428483787236465e-05 loss: 0.0645 (0.0708) time: 2.8969 data: 0.0077 max mem: 33369 +Epoch: [13] [ 930/1319] eta: 0:18:21 lr: 3.4275943372522975e-05 loss: 0.0633 (0.0708) time: 2.9204 data: 0.0079 max mem: 33369 +Epoch: [13] [ 940/1319] eta: 0:17:53 lr: 3.426704861621893e-05 loss: 0.0617 (0.0709) time: 2.9300 data: 0.0077 max mem: 33369 +Epoch: [13] [ 950/1319] eta: 0:17:25 lr: 3.4258153603371135e-05 loss: 0.0566 (0.0709) time: 2.8900 data: 0.0076 max mem: 33369 +Epoch: [13] [ 960/1319] eta: 0:16:57 lr: 3.424925833389819e-05 loss: 0.0558 (0.0709) time: 2.8424 data: 0.0079 max mem: 33369 +Epoch: [13] [ 970/1319] eta: 0:16:28 lr: 3.424036280771861e-05 loss: 0.0558 (0.0708) time: 2.8297 data: 0.0081 max mem: 33369 +Epoch: [13] [ 980/1319] eta: 0:16:00 lr: 3.42314670247509e-05 loss: 0.0619 (0.0710) time: 2.8352 data: 0.0082 max mem: 33369 +Epoch: [13] [ 990/1319] eta: 0:15:32 lr: 3.422257098491348e-05 loss: 0.0799 (0.0711) time: 2.8493 data: 0.0081 max mem: 33369 +Epoch: [13] [1000/1319] eta: 0:15:04 lr: 3.4213674688124745e-05 loss: 0.0589 (0.0711) time: 2.8432 data: 0.0081 max mem: 33369 +Epoch: [13] [1010/1319] eta: 0:14:35 lr: 3.420477813430303e-05 loss: 0.0589 (0.0710) time: 2.8468 data: 0.0082 max mem: 33369 +Epoch: [13] [1020/1319] eta: 0:14:07 lr: 3.419588132336663e-05 loss: 0.0644 (0.0710) time: 2.8337 data: 0.0085 max mem: 33369 +Epoch: [13] [1030/1319] eta: 0:13:39 lr: 3.418698425523378e-05 loss: 0.0535 (0.0709) time: 2.8262 data: 0.0085 max mem: 33369 +Epoch: [13] [1040/1319] eta: 0:13:10 lr: 3.417808692982266e-05 loss: 0.0552 (0.0710) time: 2.8585 data: 0.0082 max mem: 33369 +Epoch: [13] [1050/1319] eta: 0:12:42 lr: 3.4169189347051416e-05 loss: 0.0626 (0.0710) time: 2.8728 data: 0.0083 max mem: 33369 +Epoch: [13] [1060/1319] eta: 0:12:14 lr: 3.416029150683815e-05 loss: 0.0681 (0.0710) time: 2.8540 data: 0.0084 max mem: 33369 +Epoch: [13] [1070/1319] eta: 0:11:45 lr: 3.4151393409100875e-05 loss: 0.0708 (0.0710) time: 2.8323 data: 0.0086 max mem: 33369 +Epoch: [13] [1080/1319] eta: 0:11:17 lr: 3.41424950537576e-05 loss: 0.0729 (0.0712) time: 2.8325 data: 0.0087 max mem: 33369 +Epoch: [13] [1090/1319] eta: 0:10:49 lr: 3.413359644072625e-05 loss: 0.0622 (0.0711) time: 2.8458 data: 0.0087 max mem: 33369 +Epoch: [13] [1100/1319] eta: 0:10:20 lr: 3.412469756992473e-05 loss: 0.0622 (0.0711) time: 2.8526 data: 0.0086 max mem: 33369 +Epoch: [13] [1110/1319] eta: 0:09:52 lr: 3.411579844127087e-05 loss: 0.0752 (0.0711) time: 2.8387 data: 0.0085 max mem: 33369 +Epoch: [13] [1120/1319] eta: 0:09:24 lr: 3.410689905468246e-05 loss: 0.0604 (0.0710) time: 2.8205 data: 0.0083 max mem: 33369 +Epoch: [13] [1130/1319] eta: 0:08:55 lr: 3.409799941007725e-05 loss: 0.0568 (0.0710) time: 2.8399 data: 0.0083 max mem: 33369 +Epoch: [13] [1140/1319] eta: 0:08:27 lr: 3.408909950737292e-05 loss: 0.0554 (0.0710) time: 2.8568 data: 0.0085 max mem: 33369 +Epoch: [13] [1150/1319] eta: 0:07:59 lr: 3.4080199346487104e-05 loss: 0.0641 (0.0711) time: 2.8417 data: 0.0085 max mem: 33369 +Epoch: [13] [1160/1319] eta: 0:07:30 lr: 3.4071298927337405e-05 loss: 0.0651 (0.0713) time: 2.8347 data: 0.0085 max mem: 33369 +Epoch: [13] [1170/1319] eta: 0:07:02 lr: 3.406239824984136e-05 loss: 0.0793 (0.0714) time: 2.8285 data: 0.0084 max mem: 33369 +Epoch: [13] [1180/1319] eta: 0:06:34 lr: 3.405349731391645e-05 loss: 0.0681 (0.0713) time: 2.8231 data: 0.0085 max mem: 33369 +Epoch: [13] [1190/1319] eta: 0:06:05 lr: 3.404459611948011e-05 loss: 0.0632 (0.0713) time: 2.8230 data: 0.0087 max mem: 33369 +Epoch: [13] [1200/1319] eta: 0:05:37 lr: 3.4035694666449745e-05 loss: 0.0700 (0.0713) time: 2.7660 data: 0.0085 max mem: 33369 +Epoch: [13] [1210/1319] eta: 0:05:08 lr: 3.402679295474268e-05 loss: 0.0631 (0.0713) time: 2.6697 data: 0.0086 max mem: 33369 +Epoch: [13] [1220/1319] eta: 0:04:40 lr: 3.401789098427621e-05 loss: 0.0686 (0.0713) time: 2.6295 data: 0.0081 max mem: 33369 +Epoch: [13] [1230/1319] eta: 0:04:11 lr: 3.400898875496756e-05 loss: 0.0669 (0.0712) time: 2.6489 data: 0.0069 max mem: 33369 +Epoch: [13] [1240/1319] eta: 0:03:43 lr: 3.400008626673392e-05 loss: 0.0572 (0.0711) time: 2.6436 data: 0.0065 max mem: 33369 +Epoch: [13] [1250/1319] eta: 0:03:14 lr: 3.399118351949243e-05 loss: 0.0607 (0.0712) time: 2.6219 data: 0.0068 max mem: 33369 +Epoch: [13] [1260/1319] eta: 0:02:46 lr: 3.398228051316017e-05 loss: 0.0680 (0.0712) time: 2.6305 data: 0.0068 max mem: 33369 +Epoch: [13] [1270/1319] eta: 0:02:18 lr: 3.397337724765419e-05 loss: 0.0805 (0.0713) time: 2.6270 data: 0.0067 max mem: 33369 +Epoch: [13] [1280/1319] eta: 0:01:50 lr: 3.396447372289146e-05 loss: 0.0788 (0.0713) time: 2.6309 data: 0.0069 max mem: 33369 +Epoch: [13] [1290/1319] eta: 0:01:21 lr: 3.395556993878891e-05 loss: 0.0604 (0.0712) time: 2.6577 data: 0.0068 max mem: 33369 +Epoch: [13] [1300/1319] eta: 0:00:53 lr: 3.394666589526343e-05 loss: 0.0606 (0.0713) time: 2.7826 data: 0.0071 max mem: 33369 +Epoch: [13] [1310/1319] eta: 0:00:25 lr: 3.393776159223184e-05 loss: 0.0633 (0.0712) time: 2.9068 data: 0.0077 max mem: 33369 +Epoch: [13] Total time: 1:02:02 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 1:55:16 time: 2.6882 data: 2.5755 max mem: 33369 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 100/2573] eta: 0:04:10 time: 0.0735 data: 0.0013 max mem: 33369 +Test: [ 200/2573] eta: 0:03:30 time: 0.0755 data: 0.0013 max mem: 33369 +Test: [ 300/2573] eta: 0:03:10 time: 0.0773 data: 0.0013 max mem: 33369 +Test: [ 400/2573] eta: 0:02:57 time: 0.0771 data: 0.0013 max mem: 33369 +Test: [ 500/2573] eta: 0:02:46 time: 0.0755 data: 0.0014 max mem: 33369 +Test: [ 600/2573] eta: 0:02:37 time: 0.0754 data: 0.0013 max mem: 33369 +Test: [ 700/2573] eta: 0:02:28 time: 0.0754 data: 0.0013 max mem: 33369 +Test: [ 800/2573] eta: 0:02:20 time: 0.0791 data: 0.0013 max mem: 33369 +Test: [ 900/2573] eta: 0:02:11 time: 0.0755 data: 0.0013 max mem: 33369 +Test: [1000/2573] eta: 0:02:03 time: 0.0759 data: 0.0014 max mem: 33369 +Test: [1100/2573] eta: 0:01:55 time: 0.0758 data: 0.0013 max mem: 33369 +Test: [1200/2573] eta: 0:01:47 time: 0.0757 data: 0.0013 max mem: 33369 +Test: [1300/2573] eta: 0:01:39 time: 0.0756 data: 0.0013 max mem: 33369 +Test: [1400/2573] eta: 0:01:31 time: 0.0741 data: 0.0014 max mem: 33369 +Test: [1500/2573] eta: 0:01:23 time: 0.0760 data: 0.0013 max mem: 33369 +Test: [1600/2573] eta: 0:01:15 time: 0.0793 data: 0.0013 max mem: 33369 +Test: [1700/2573] eta: 0:01:07 time: 0.0743 data: 0.0013 max mem: 33369 +Test: [1800/2573] eta: 0:00:59 time: 0.0777 data: 0.0013 max mem: 33369 +Test: [1900/2573] eta: 0:00:52 time: 0.0742 data: 0.0013 max mem: 33369 +Test: [2000/2573] eta: 0:00:44 time: 0.0757 data: 0.0014 max mem: 33369 +Test: [2100/2573] eta: 0:00:36 time: 0.0778 data: 0.0013 max mem: 33369 +Test: [2200/2573] eta: 0:00:28 time: 0.0774 data: 0.0013 max mem: 33369 +Test: [2300/2573] eta: 0:00:21 time: 0.0777 data: 0.0014 max mem: 33369 +Test: [2400/2573] eta: 0:00:13 time: 0.0726 data: 0.0013 max mem: 33369 +Test: [2500/2573] eta: 0:00:05 time: 0.0759 data: 0.0014 max mem: 33369 +Test: Total time: 0:03:18 +Final results: +Mean IoU is 61.52 + + precision@0.5 = 69.69 + precision@0.6 = 63.32 + precision@0.7 = 54.51 + precision@0.8 = 42.99 + precision@0.9 = 19.59 + overall IoU = 60.03 + +Average object IoU 61.52220609903557 +Overall IoU 60.03263854980469 +Better epoch: 13 + +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [14] [ 0/1319] eta: 1:42:17 lr: 3.392974749755691e-05 loss: 0.0484 (0.0484) time: 4.6534 data: 1.5091 max mem: 33369 +Epoch: [14] [ 10/1319] eta: 1:10:03 lr: 3.392084270123441e-05 loss: 0.0484 (0.0499) time: 3.2114 data: 0.1447 max mem: 33369 +Epoch: [14] [ 20/1319] eta: 1:08:01 lr: 3.391193764516433e-05 loss: 0.0546 (0.0602) time: 3.0666 data: 0.0073 max mem: 33369 +Epoch: [14] [ 30/1319] eta: 1:07:35 lr: 3.3903032329263314e-05 loss: 0.0555 (0.0583) time: 3.1109 data: 0.0068 max mem: 33369 +Epoch: [14] [ 40/1319] eta: 1:07:00 lr: 3.389412675344791e-05 loss: 0.0570 (0.0634) time: 3.1451 data: 0.0072 max mem: 33369 +Epoch: [14] [ 50/1319] eta: 1:06:13 lr: 3.388522091763468e-05 loss: 0.0615 (0.0661) time: 3.1072 data: 0.0072 max mem: 33369 +Epoch: [14] [ 60/1319] eta: 1:05:29 lr: 3.387631482174009e-05 loss: 0.0526 (0.0653) time: 3.0756 data: 0.0074 max mem: 33369 +Epoch: [14] [ 70/1319] eta: 1:04:48 lr: 3.386740846568057e-05 loss: 0.0512 (0.0645) time: 3.0679 data: 0.0075 max mem: 33369 +Epoch: [14] [ 80/1319] eta: 1:04:07 lr: 3.385850184937249e-05 loss: 0.0604 (0.0654) time: 3.0569 data: 0.0075 max mem: 33369 +Epoch: [14] [ 90/1319] eta: 1:03:32 lr: 3.3849594972732175e-05 loss: 0.0515 (0.0646) time: 3.0609 data: 0.0076 max mem: 33369 +Epoch: [14] [ 100/1319] eta: 1:02:56 lr: 3.38406878356759e-05 loss: 0.0476 (0.0638) time: 3.0680 data: 0.0077 max mem: 33369 +Epoch: [14] [ 110/1319] eta: 1:02:21 lr: 3.3831780438119907e-05 loss: 0.0509 (0.0641) time: 3.0633 data: 0.0078 max mem: 33369 +Epoch: [14] [ 120/1319] eta: 1:01:47 lr: 3.3822872779980336e-05 loss: 0.0730 (0.0661) time: 3.0619 data: 0.0078 max mem: 33369 +Epoch: [14] [ 130/1319] eta: 1:01:11 lr: 3.381396486117332e-05 loss: 0.0651 (0.0653) time: 3.0503 data: 0.0076 max mem: 33369 +Epoch: [14] [ 140/1319] eta: 1:00:34 lr: 3.380505668161494e-05 loss: 0.0530 (0.0650) time: 3.0278 data: 0.0076 max mem: 33369 +Epoch: [14] [ 150/1319] eta: 1:00:00 lr: 3.3796148241221185e-05 loss: 0.0537 (0.0644) time: 3.0271 data: 0.0078 max mem: 33369 +Epoch: [14] [ 160/1319] eta: 0:59:26 lr: 3.378723953990804e-05 loss: 0.0550 (0.0643) time: 3.0372 data: 0.0080 max mem: 33369 +Epoch: [14] [ 170/1319] eta: 0:58:53 lr: 3.3778330577591404e-05 loss: 0.0629 (0.0648) time: 3.0395 data: 0.0080 max mem: 33369 +Epoch: [14] [ 180/1319] eta: 0:58:18 lr: 3.3769421354187145e-05 loss: 0.0657 (0.0647) time: 3.0264 data: 0.0079 max mem: 33369 +Epoch: [14] [ 190/1319] eta: 0:57:42 lr: 3.376051186961107e-05 loss: 0.0589 (0.0653) time: 2.9914 data: 0.0077 max mem: 33369 +Epoch: [14] [ 200/1319] eta: 0:57:06 lr: 3.375160212377894e-05 loss: 0.0724 (0.0663) time: 2.9778 data: 0.0077 max mem: 33369 +Epoch: [14] [ 210/1319] eta: 0:56:31 lr: 3.374269211660646e-05 loss: 0.0676 (0.0660) time: 2.9786 data: 0.0077 max mem: 33369 +Epoch: [14] [ 220/1319] eta: 0:55:59 lr: 3.373378184800928e-05 loss: 0.0555 (0.0657) time: 3.0040 data: 0.0079 max mem: 33369 +Epoch: [14] [ 230/1319] eta: 0:55:20 lr: 3.372487131790299e-05 loss: 0.0584 (0.0662) time: 2.9538 data: 0.0079 max mem: 33369 +Epoch: [14] [ 240/1319] eta: 0:54:38 lr: 3.371596052620316e-05 loss: 0.0587 (0.0661) time: 2.8313 data: 0.0080 max mem: 33369 +Epoch: [14] [ 250/1319] eta: 0:53:56 lr: 3.370704947282529e-05 loss: 0.0598 (0.0662) time: 2.7814 data: 0.0076 max mem: 33369 +Epoch: [14] [ 260/1319] eta: 0:53:12 lr: 3.3698138157684804e-05 loss: 0.0571 (0.0655) time: 2.7257 data: 0.0069 max mem: 33369 +Epoch: [14] [ 270/1319] eta: 0:52:28 lr: 3.368922658069711e-05 loss: 0.0493 (0.0654) time: 2.6758 data: 0.0069 max mem: 33369 +Epoch: [14] [ 280/1319] eta: 0:51:47 lr: 3.368031474177754e-05 loss: 0.0552 (0.0655) time: 2.6906 data: 0.0071 max mem: 33369 +Epoch: [14] [ 290/1319] eta: 0:51:15 lr: 3.367140264084139e-05 loss: 0.0641 (0.0661) time: 2.8142 data: 0.0076 max mem: 33369 +Epoch: [14] [ 300/1319] eta: 0:50:41 lr: 3.366249027780389e-05 loss: 0.0664 (0.0662) time: 2.8991 data: 0.0078 max mem: 33369 +Epoch: [14] [ 310/1319] eta: 0:50:08 lr: 3.365357765258022e-05 loss: 0.0637 (0.0661) time: 2.8736 data: 0.0078 max mem: 33369 +Epoch: [14] [ 320/1319] eta: 0:49:39 lr: 3.364466476508552e-05 loss: 0.0535 (0.0659) time: 2.9460 data: 0.0076 max mem: 33369 +Epoch: [14] [ 330/1319] eta: 0:49:08 lr: 3.363575161523487e-05 loss: 0.0500 (0.0655) time: 2.9742 data: 0.0076 max mem: 33369 +Epoch: [14] [ 340/1319] eta: 0:48:34 lr: 3.362683820294329e-05 loss: 0.0570 (0.0659) time: 2.8917 data: 0.0077 max mem: 33369 +Epoch: [14] [ 350/1319] eta: 0:48:03 lr: 3.361792452812576e-05 loss: 0.0570 (0.0658) time: 2.8834 data: 0.0077 max mem: 33369 +Epoch: [14] [ 360/1319] eta: 0:47:32 lr: 3.36090105906972e-05 loss: 0.0619 (0.0661) time: 2.9273 data: 0.0077 max mem: 33369 +Epoch: [14] [ 370/1319] eta: 0:47:00 lr: 3.3600096390572475e-05 loss: 0.0638 (0.0660) time: 2.9184 data: 0.0079 max mem: 33369 +Epoch: [14] [ 380/1319] eta: 0:46:27 lr: 3.3591181927666404e-05 loss: 0.0635 (0.0659) time: 2.8597 data: 0.0079 max mem: 33369 +Epoch: [14] [ 390/1319] eta: 0:45:55 lr: 3.358226720189375e-05 loss: 0.0635 (0.0660) time: 2.8524 data: 0.0076 max mem: 33369 +Epoch: [14] [ 400/1319] eta: 0:45:23 lr: 3.357335221316921e-05 loss: 0.0627 (0.0660) time: 2.8726 data: 0.0075 max mem: 33369 +Epoch: [14] [ 410/1319] eta: 0:44:51 lr: 3.3564436961407466e-05 loss: 0.0635 (0.0669) time: 2.8545 data: 0.0078 max mem: 33369 +Epoch: [14] [ 420/1319] eta: 0:44:19 lr: 3.35555214465231e-05 loss: 0.0752 (0.0670) time: 2.8587 data: 0.0080 max mem: 33369 +Epoch: [14] [ 430/1319] eta: 0:43:47 lr: 3.354660566843068e-05 loss: 0.0656 (0.0669) time: 2.8445 data: 0.0079 max mem: 33369 +Epoch: [14] [ 440/1319] eta: 0:43:15 lr: 3.353768962704469e-05 loss: 0.0596 (0.0669) time: 2.8343 data: 0.0079 max mem: 33369 +Epoch: [14] [ 450/1319] eta: 0:42:43 lr: 3.352877332227959e-05 loss: 0.0536 (0.0665) time: 2.8444 data: 0.0080 max mem: 33369 +Epoch: [14] [ 460/1319] eta: 0:42:12 lr: 3.351985675404978e-05 loss: 0.0536 (0.0666) time: 2.8393 data: 0.0082 max mem: 33369 +Epoch: [14] [ 470/1319] eta: 0:41:40 lr: 3.3510939922269576e-05 loss: 0.0585 (0.0666) time: 2.8367 data: 0.0083 max mem: 33369 +Epoch: [14] [ 480/1319] eta: 0:41:08 lr: 3.350202282685327e-05 loss: 0.0667 (0.0667) time: 2.8171 data: 0.0084 max mem: 33369 +Epoch: [14] [ 490/1319] eta: 0:40:37 lr: 3.34931054677151e-05 loss: 0.0658 (0.0666) time: 2.8236 data: 0.0084 max mem: 33369 +Epoch: [14] [ 500/1319] eta: 0:40:06 lr: 3.3484187844769246e-05 loss: 0.0563 (0.0664) time: 2.8412 data: 0.0084 max mem: 33369 +Epoch: [14] [ 510/1319] eta: 0:39:36 lr: 3.347526995792984e-05 loss: 0.0589 (0.0664) time: 2.8632 data: 0.0086 max mem: 33369 +Epoch: [14] [ 520/1319] eta: 0:39:05 lr: 3.346635180711094e-05 loss: 0.0642 (0.0664) time: 2.8633 data: 0.0086 max mem: 33369 +Epoch: [14] [ 530/1319] eta: 0:38:34 lr: 3.3457433392226575e-05 loss: 0.0555 (0.0662) time: 2.8178 data: 0.0083 max mem: 33369 +Epoch: [14] [ 540/1319] eta: 0:38:03 lr: 3.344851471319071e-05 loss: 0.0517 (0.0662) time: 2.8202 data: 0.0081 max mem: 33369 +Epoch: [14] [ 550/1319] eta: 0:37:32 lr: 3.343959576991726e-05 loss: 0.0588 (0.0663) time: 2.8381 data: 0.0083 max mem: 33369 +Epoch: [14] [ 560/1319] eta: 0:37:01 lr: 3.343067656232008e-05 loss: 0.0588 (0.0663) time: 2.8116 data: 0.0085 max mem: 33369 +Epoch: [14] [ 570/1319] eta: 0:36:31 lr: 3.342175709031298e-05 loss: 0.0597 (0.0664) time: 2.8096 data: 0.0083 max mem: 33369 +Epoch: [14] [ 580/1319] eta: 0:36:01 lr: 3.341283735380971e-05 loss: 0.0802 (0.0667) time: 2.8655 data: 0.0082 max mem: 33369 +Epoch: [14] [ 590/1319] eta: 0:35:30 lr: 3.3403917352723954e-05 loss: 0.0724 (0.0668) time: 2.8505 data: 0.0082 max mem: 33369 +Epoch: [14] [ 600/1319] eta: 0:35:00 lr: 3.339499708696938e-05 loss: 0.0596 (0.0668) time: 2.8264 data: 0.0083 max mem: 33369 +Epoch: [14] [ 610/1319] eta: 0:34:30 lr: 3.3386076556459565e-05 loss: 0.0735 (0.0672) time: 2.8426 data: 0.0085 max mem: 33369 +Epoch: [14] [ 620/1319] eta: 0:33:59 lr: 3.337715576110804e-05 loss: 0.0726 (0.0673) time: 2.7910 data: 0.0082 max mem: 33369 +Epoch: [14] [ 630/1319] eta: 0:33:28 lr: 3.336823470082831e-05 loss: 0.0602 (0.0672) time: 2.7528 data: 0.0079 max mem: 33369 +Epoch: [14] [ 640/1319] eta: 0:32:56 lr: 3.335931337553377e-05 loss: 0.0624 (0.0672) time: 2.7150 data: 0.0077 max mem: 33369 +Epoch: [14] [ 650/1319] eta: 0:32:24 lr: 3.3350391785137824e-05 loss: 0.0699 (0.0674) time: 2.6599 data: 0.0070 max mem: 33369 +Epoch: [14] [ 660/1319] eta: 0:31:52 lr: 3.334146992955378e-05 loss: 0.0575 (0.0673) time: 2.6319 data: 0.0067 max mem: 33369 +Epoch: [14] [ 670/1319] eta: 0:31:21 lr: 3.33325478086949e-05 loss: 0.0637 (0.0674) time: 2.6589 data: 0.0067 max mem: 33369 +Epoch: [14] [ 680/1319] eta: 0:30:50 lr: 3.332362542247442e-05 loss: 0.0704 (0.0676) time: 2.6716 data: 0.0066 max mem: 33369 +Epoch: [14] [ 690/1319] eta: 0:30:19 lr: 3.3314702770805464e-05 loss: 0.0751 (0.0677) time: 2.6417 data: 0.0065 max mem: 33369 +Epoch: [14] [ 700/1319] eta: 0:29:48 lr: 3.330577985360116e-05 loss: 0.0686 (0.0677) time: 2.6512 data: 0.0064 max mem: 33369 +Epoch: [14] [ 710/1319] eta: 0:29:17 lr: 3.329685667077455e-05 loss: 0.0590 (0.0676) time: 2.6861 data: 0.0067 max mem: 33369 +Epoch: [14] [ 720/1319] eta: 0:28:48 lr: 3.3287933222238623e-05 loss: 0.0590 (0.0677) time: 2.7757 data: 0.0072 max mem: 33369 +Epoch: [14] [ 730/1319] eta: 0:28:20 lr: 3.327900950790632e-05 loss: 0.0629 (0.0677) time: 2.8815 data: 0.0076 max mem: 33369 +Epoch: [14] [ 740/1319] eta: 0:27:51 lr: 3.327008552769054e-05 loss: 0.0648 (0.0677) time: 2.9097 data: 0.0075 max mem: 33369 +Epoch: [14] [ 750/1319] eta: 0:27:22 lr: 3.32611612815041e-05 loss: 0.0687 (0.0677) time: 2.8866 data: 0.0073 max mem: 33369 +Epoch: [14] [ 760/1319] eta: 0:26:53 lr: 3.325223676925979e-05 loss: 0.0580 (0.0677) time: 2.9050 data: 0.0073 max mem: 33369 +Epoch: [14] [ 770/1319] eta: 0:26:25 lr: 3.324331199087032e-05 loss: 0.0477 (0.0678) time: 2.9167 data: 0.0073 max mem: 33369 +Epoch: [14] [ 780/1319] eta: 0:25:56 lr: 3.323438694624837e-05 loss: 0.0638 (0.0677) time: 2.9240 data: 0.0071 max mem: 33369 +Epoch: [14] [ 790/1319] eta: 0:25:28 lr: 3.322546163530654e-05 loss: 0.0572 (0.0676) time: 2.9455 data: 0.0072 max mem: 33369 +Epoch: [14] [ 800/1319] eta: 0:24:59 lr: 3.32165360579574e-05 loss: 0.0568 (0.0676) time: 2.9019 data: 0.0075 max mem: 33369 +Epoch: [14] [ 810/1319] eta: 0:24:30 lr: 3.320761021411345e-05 loss: 0.0632 (0.0676) time: 2.8716 data: 0.0074 max mem: 33369 +Epoch: [14] [ 820/1319] eta: 0:24:00 lr: 3.3198684103687127e-05 loss: 0.0599 (0.0676) time: 2.8494 data: 0.0073 max mem: 33369 +Epoch: [14] [ 830/1319] eta: 0:23:31 lr: 3.318975772659084e-05 loss: 0.0630 (0.0676) time: 2.8335 data: 0.0078 max mem: 33369 +Epoch: [14] [ 840/1319] eta: 0:23:02 lr: 3.3180831082736915e-05 loss: 0.0537 (0.0674) time: 2.8551 data: 0.0081 max mem: 33369 +Epoch: [14] [ 850/1319] eta: 0:22:33 lr: 3.3171904172037654e-05 loss: 0.0498 (0.0674) time: 2.8362 data: 0.0078 max mem: 33369 +Epoch: [14] [ 860/1319] eta: 0:22:04 lr: 3.3162976994405264e-05 loss: 0.0565 (0.0673) time: 2.8453 data: 0.0078 max mem: 33369 +Epoch: [14] [ 870/1319] eta: 0:21:35 lr: 3.315404954975194e-05 loss: 0.0566 (0.0672) time: 2.8454 data: 0.0079 max mem: 33369 +Epoch: [14] [ 880/1319] eta: 0:21:06 lr: 3.314512183798977e-05 loss: 0.0564 (0.0672) time: 2.8071 data: 0.0082 max mem: 33369 +Epoch: [14] [ 890/1319] eta: 0:20:36 lr: 3.3136193859030854e-05 loss: 0.0560 (0.0672) time: 2.8183 data: 0.0084 max mem: 33369 +Epoch: [14] [ 900/1319] eta: 0:20:07 lr: 3.312726561278717e-05 loss: 0.0547 (0.0671) time: 2.8279 data: 0.0083 max mem: 33369 +Epoch: [14] [ 910/1319] eta: 0:19:38 lr: 3.311833709917069e-05 loss: 0.0565 (0.0672) time: 2.8277 data: 0.0081 max mem: 33369 +Epoch: [14] [ 920/1319] eta: 0:19:09 lr: 3.3109408318093296e-05 loss: 0.0593 (0.0672) time: 2.8139 data: 0.0083 max mem: 33369 +Epoch: [14] [ 930/1319] eta: 0:18:40 lr: 3.310047926946684e-05 loss: 0.0569 (0.0671) time: 2.8028 data: 0.0083 max mem: 33369 +Epoch: [14] [ 940/1319] eta: 0:18:11 lr: 3.309154995320309e-05 loss: 0.0569 (0.0672) time: 2.8112 data: 0.0078 max mem: 33369 +Epoch: [14] [ 950/1319] eta: 0:17:42 lr: 3.308262036921381e-05 loss: 0.0699 (0.0671) time: 2.8030 data: 0.0079 max mem: 33369 +Epoch: [14] [ 960/1319] eta: 0:17:13 lr: 3.307369051741064e-05 loss: 0.0664 (0.0673) time: 2.8120 data: 0.0083 max mem: 33369 +Epoch: [14] [ 970/1319] eta: 0:16:44 lr: 3.306476039770522e-05 loss: 0.0648 (0.0671) time: 2.8379 data: 0.0084 max mem: 33369 +Epoch: [14] [ 980/1319] eta: 0:16:15 lr: 3.30558300100091e-05 loss: 0.0586 (0.0672) time: 2.8639 data: 0.0083 max mem: 33369 +Epoch: [14] [ 990/1319] eta: 0:15:46 lr: 3.30468993542338e-05 loss: 0.0711 (0.0672) time: 2.8566 data: 0.0081 max mem: 33369 +Epoch: [14] [1000/1319] eta: 0:15:17 lr: 3.3037968430290776e-05 loss: 0.0573 (0.0672) time: 2.8326 data: 0.0081 max mem: 33369 +Epoch: [14] [1010/1319] eta: 0:14:48 lr: 3.3029037238091407e-05 loss: 0.0612 (0.0673) time: 2.8355 data: 0.0082 max mem: 33369 +Epoch: [14] [1020/1319] eta: 0:14:20 lr: 3.3020105777547046e-05 loss: 0.0644 (0.0673) time: 2.8361 data: 0.0081 max mem: 33369 +Epoch: [14] [1030/1319] eta: 0:13:51 lr: 3.301117404856897e-05 loss: 0.0607 (0.0673) time: 2.8232 data: 0.0082 max mem: 33369 +Epoch: [14] [1040/1319] eta: 0:13:22 lr: 3.300224205106842e-05 loss: 0.0543 (0.0672) time: 2.8392 data: 0.0083 max mem: 33369 +Epoch: [14] [1050/1319] eta: 0:12:53 lr: 3.2993309784956545e-05 loss: 0.0583 (0.0672) time: 2.8495 data: 0.0082 max mem: 33369 +Epoch: [14] [1060/1319] eta: 0:12:24 lr: 3.298437725014447e-05 loss: 0.0649 (0.0672) time: 2.7741 data: 0.0082 max mem: 33369 +Epoch: [14] [1070/1319] eta: 0:11:55 lr: 3.297544444654327e-05 loss: 0.0544 (0.0671) time: 2.7151 data: 0.0080 max mem: 33369 +Epoch: [14] [1080/1319] eta: 0:11:25 lr: 3.296651137406393e-05 loss: 0.0531 (0.0670) time: 2.6587 data: 0.0074 max mem: 33369 +Epoch: [14] [1090/1319] eta: 0:10:56 lr: 3.2957578032617413e-05 loss: 0.0540 (0.0669) time: 2.6337 data: 0.0070 max mem: 33369 +Epoch: [14] [1100/1319] eta: 0:10:27 lr: 3.29486444221146e-05 loss: 0.0650 (0.0671) time: 2.6574 data: 0.0071 max mem: 33369 +Epoch: [14] [1110/1319] eta: 0:09:58 lr: 3.293971054246633e-05 loss: 0.0619 (0.0671) time: 2.6584 data: 0.0069 max mem: 33369 +Epoch: [14] [1120/1319] eta: 0:09:29 lr: 3.293077639358339e-05 loss: 0.0579 (0.0670) time: 2.7212 data: 0.0070 max mem: 33369 +Epoch: [14] [1130/1319] eta: 0:09:01 lr: 3.2921841975376476e-05 loss: 0.0710 (0.0672) time: 2.8420 data: 0.0074 max mem: 33369 +Epoch: [14] [1140/1319] eta: 0:08:32 lr: 3.291290728775627e-05 loss: 0.0624 (0.0671) time: 2.9125 data: 0.0078 max mem: 33369 +Epoch: [14] [1150/1319] eta: 0:08:04 lr: 3.290397233063338e-05 loss: 0.0566 (0.0671) time: 2.9162 data: 0.0076 max mem: 33369 +Epoch: [14] [1160/1319] eta: 0:07:35 lr: 3.2895037103918356e-05 loss: 0.0576 (0.0671) time: 2.8929 data: 0.0072 max mem: 33369 +Epoch: [14] [1170/1319] eta: 0:07:06 lr: 3.2886101607521696e-05 loss: 0.0597 (0.0671) time: 2.9048 data: 0.0075 max mem: 33369 +Epoch: [14] [1180/1319] eta: 0:06:38 lr: 3.287716584135384e-05 loss: 0.0540 (0.0671) time: 2.9343 data: 0.0076 max mem: 33369 +Epoch: [14] [1190/1319] eta: 0:06:09 lr: 3.286822980532516e-05 loss: 0.0540 (0.0672) time: 2.9254 data: 0.0074 max mem: 33369 +Epoch: [14] [1200/1319] eta: 0:05:41 lr: 3.285929349934599e-05 loss: 0.0664 (0.0671) time: 2.9116 data: 0.0074 max mem: 33369 +Epoch: [14] [1210/1319] eta: 0:05:12 lr: 3.28503569233266e-05 loss: 0.0624 (0.0672) time: 2.8823 data: 0.0073 max mem: 33369 +Epoch: [14] [1220/1319] eta: 0:04:43 lr: 3.284142007717719e-05 loss: 0.0704 (0.0673) time: 2.8442 data: 0.0074 max mem: 33369 +Epoch: [14] [1230/1319] eta: 0:04:15 lr: 3.283248296080793e-05 loss: 0.0683 (0.0673) time: 2.8615 data: 0.0075 max mem: 33369 +Epoch: [14] [1240/1319] eta: 0:03:46 lr: 3.2823545574128904e-05 loss: 0.0626 (0.0673) time: 2.8795 data: 0.0076 max mem: 33369 +Epoch: [14] [1250/1319] eta: 0:03:17 lr: 3.2814607917050156e-05 loss: 0.0611 (0.0673) time: 2.8306 data: 0.0079 max mem: 33369 +Epoch: [14] [1260/1319] eta: 0:02:49 lr: 3.280566998948166e-05 loss: 0.0568 (0.0672) time: 2.8278 data: 0.0080 max mem: 33369 +Epoch: [14] [1270/1319] eta: 0:02:20 lr: 3.2796731791333364e-05 loss: 0.0628 (0.0673) time: 2.8543 data: 0.0080 max mem: 33369 +Epoch: [14] [1280/1319] eta: 0:01:51 lr: 3.278779332251511e-05 loss: 0.0650 (0.0673) time: 2.8504 data: 0.0081 max mem: 33369 +Epoch: [14] [1290/1319] eta: 0:01:23 lr: 3.277885458293673e-05 loss: 0.0594 (0.0674) time: 2.8405 data: 0.0081 max mem: 33369 +Epoch: [14] [1300/1319] eta: 0:00:54 lr: 3.276991557250796e-05 loss: 0.0684 (0.0674) time: 2.8186 data: 0.0080 max mem: 33369 +Epoch: [14] [1310/1319] eta: 0:00:25 lr: 3.276097629113851e-05 loss: 0.0708 (0.0676) time: 2.8252 data: 0.0082 max mem: 33369 +Epoch: [14] Total time: 1:02:58 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 2:07:00 time: 2.9616 data: 2.8280 max mem: 33369 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 100/2573] eta: 0:04:12 time: 0.0730 data: 0.0014 max mem: 33369 +Test: [ 200/2573] eta: 0:03:31 time: 0.0750 data: 0.0014 max mem: 33369 +Test: [ 300/2573] eta: 0:03:10 time: 0.0767 data: 0.0014 max mem: 33369 +Test: [ 400/2573] eta: 0:02:57 time: 0.0770 data: 0.0014 max mem: 33369 +Test: [ 500/2573] eta: 0:02:46 time: 0.0752 data: 0.0014 max mem: 33369 +Test: [ 600/2573] eta: 0:02:37 time: 0.0752 data: 0.0014 max mem: 33369 +Test: [ 700/2573] eta: 0:02:28 time: 0.0753 data: 0.0014 max mem: 33369 +Test: [ 800/2573] eta: 0:02:19 time: 0.0786 data: 0.0013 max mem: 33369 +Test: [ 900/2573] eta: 0:02:11 time: 0.0754 data: 0.0013 max mem: 33369 +Test: [1000/2573] eta: 0:02:03 time: 0.0753 data: 0.0014 max mem: 33369 +Test: [1100/2573] eta: 0:01:55 time: 0.0756 data: 0.0014 max mem: 33369 +Test: [1200/2573] eta: 0:01:47 time: 0.0757 data: 0.0014 max mem: 33369 +Test: [1300/2573] eta: 0:01:39 time: 0.0758 data: 0.0013 max mem: 33369 +Test: [1400/2573] eta: 0:01:31 time: 0.0742 data: 0.0014 max mem: 33369 +Test: [1500/2573] eta: 0:01:23 time: 0.0759 data: 0.0014 max mem: 33369 +Test: [1600/2573] eta: 0:01:15 time: 0.0792 data: 0.0014 max mem: 33369 +Test: [1700/2573] eta: 0:01:07 time: 0.0740 data: 0.0013 max mem: 33369 +Test: [1800/2573] eta: 0:00:59 time: 0.0778 data: 0.0013 max mem: 33369 +Test: [1900/2573] eta: 0:00:51 time: 0.0740 data: 0.0014 max mem: 33369 +Test: [2000/2573] eta: 0:00:44 time: 0.0759 data: 0.0014 max mem: 33369 +Test: [2100/2573] eta: 0:00:36 time: 0.0777 data: 0.0013 max mem: 33369 +Test: [2200/2573] eta: 0:00:28 time: 0.0776 data: 0.0013 max mem: 33369 +Test: [2300/2573] eta: 0:00:20 time: 0.0776 data: 0.0013 max mem: 33369 +Test: [2400/2573] eta: 0:00:13 time: 0.0725 data: 0.0013 max mem: 33369 +Test: [2500/2573] eta: 0:00:05 time: 0.0760 data: 0.0014 max mem: 33369 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: Total time: 0:03:18 +Final results: +Mean IoU is 62.24 + + precision@0.5 = 70.12 + precision@0.6 = 64.07 + precision@0.7 = 55.98 + precision@0.8 = 43.36 + precision@0.9 = 20.73 + overall IoU = 60.09 + +Average object IoU 62.2434876008223 +Overall IoU 60.08503723144531 +Better epoch: 14 + +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [15] [ 0/1319] eta: 1:46:33 lr: 3.275293070617704e-05 loss: 0.1001 (0.1001) time: 4.8469 data: 1.6591 max mem: 33369 +Epoch: [15] [ 10/1319] eta: 1:09:54 lr: 3.274399090977129e-05 loss: 0.0668 (0.0783) time: 3.2045 data: 0.1574 max mem: 33369 +Epoch: [15] [ 20/1319] eta: 1:07:31 lr: 3.2735050842162644e-05 loss: 0.0619 (0.0701) time: 3.0323 data: 0.0070 max mem: 33369 +Epoch: [15] [ 30/1319] eta: 1:06:15 lr: 3.2726110503260586e-05 loss: 0.0511 (0.0648) time: 3.0182 data: 0.0073 max mem: 33369 +Epoch: [15] [ 40/1319] eta: 1:05:21 lr: 3.271716989297451e-05 loss: 0.0481 (0.0602) time: 3.0116 data: 0.0077 max mem: 33369 +Epoch: [15] [ 50/1319] eta: 1:04:35 lr: 3.2708229011213794e-05 loss: 0.0507 (0.0627) time: 3.0067 data: 0.0076 max mem: 33369 +Epoch: [15] [ 60/1319] eta: 1:03:48 lr: 3.269928785788772e-05 loss: 0.0621 (0.0631) time: 2.9876 data: 0.0073 max mem: 33369 +Epoch: [15] [ 70/1319] eta: 1:02:44 lr: 3.2690346432905536e-05 loss: 0.0559 (0.0627) time: 2.9117 data: 0.0075 max mem: 33369 +Epoch: [15] [ 80/1319] eta: 1:01:38 lr: 3.268140473617642e-05 loss: 0.0630 (0.0650) time: 2.8167 data: 0.0073 max mem: 33369 +Epoch: [15] [ 90/1319] eta: 1:00:33 lr: 3.26724627676095e-05 loss: 0.0635 (0.0652) time: 2.7543 data: 0.0068 max mem: 33369 +Epoch: [15] [ 100/1319] eta: 0:59:31 lr: 3.266352052711384e-05 loss: 0.0633 (0.0650) time: 2.7058 data: 0.0070 max mem: 33369 +Epoch: [15] [ 110/1319] eta: 0:58:36 lr: 3.265457801459844e-05 loss: 0.0579 (0.0646) time: 2.6895 data: 0.0072 max mem: 33369 +Epoch: [15] [ 120/1319] eta: 0:57:59 lr: 3.2645635229972264e-05 loss: 0.0605 (0.0643) time: 2.7631 data: 0.0071 max mem: 33369 +Epoch: [15] [ 130/1319] eta: 0:57:23 lr: 3.2636692173144204e-05 loss: 0.0605 (0.0641) time: 2.8258 data: 0.0069 max mem: 33369 +Epoch: [15] [ 140/1319] eta: 0:56:48 lr: 3.2627748844023084e-05 loss: 0.0553 (0.0636) time: 2.8235 data: 0.0070 max mem: 33369 +Epoch: [15] [ 150/1319] eta: 0:56:18 lr: 3.261880524251768e-05 loss: 0.0560 (0.0635) time: 2.8525 data: 0.0075 max mem: 33369 +Epoch: [15] [ 160/1319] eta: 0:55:50 lr: 3.260986136853672e-05 loss: 0.0571 (0.0634) time: 2.8854 data: 0.0079 max mem: 33369 +Epoch: [15] [ 170/1319] eta: 0:55:22 lr: 3.2600917221988844e-05 loss: 0.0594 (0.0638) time: 2.9001 data: 0.0078 max mem: 33369 +Epoch: [15] [ 180/1319] eta: 0:54:56 lr: 3.259197280278268e-05 loss: 0.0589 (0.0632) time: 2.9281 data: 0.0075 max mem: 33369 +Epoch: [15] [ 190/1319] eta: 0:54:30 lr: 3.258302811082674e-05 loss: 0.0538 (0.0624) time: 2.9411 data: 0.0073 max mem: 33369 +Epoch: [15] [ 200/1319] eta: 0:54:03 lr: 3.257408314602953e-05 loss: 0.0526 (0.0623) time: 2.9383 data: 0.0074 max mem: 33369 +Epoch: [15] [ 210/1319] eta: 0:53:34 lr: 3.2565137908299456e-05 loss: 0.0542 (0.0632) time: 2.9159 data: 0.0078 max mem: 33369 +Epoch: [15] [ 220/1319] eta: 0:53:06 lr: 3.25561923975449e-05 loss: 0.0530 (0.0632) time: 2.9031 data: 0.0079 max mem: 33369 +Epoch: [15] [ 230/1319] eta: 0:52:38 lr: 3.2547246613674155e-05 loss: 0.0521 (0.0628) time: 2.9247 data: 0.0079 max mem: 33369 +Epoch: [15] [ 240/1319] eta: 0:52:10 lr: 3.253830055659547e-05 loss: 0.0563 (0.0627) time: 2.9251 data: 0.0079 max mem: 33369 +Epoch: [15] [ 250/1319] eta: 0:51:41 lr: 3.252935422621704e-05 loss: 0.0662 (0.0633) time: 2.9121 data: 0.0076 max mem: 33369 +Epoch: [15] [ 260/1319] eta: 0:51:12 lr: 3.252040762244701e-05 loss: 0.0618 (0.0634) time: 2.8959 data: 0.0076 max mem: 33369 +Epoch: [15] [ 270/1319] eta: 0:50:41 lr: 3.251146074519342e-05 loss: 0.0558 (0.0640) time: 2.8691 data: 0.0079 max mem: 33369 +Epoch: [15] [ 280/1319] eta: 0:50:11 lr: 3.2502513594364305e-05 loss: 0.0582 (0.0638) time: 2.8585 data: 0.0080 max mem: 33369 +Epoch: [15] [ 290/1319] eta: 0:49:42 lr: 3.2493566169867616e-05 loss: 0.0618 (0.0638) time: 2.8896 data: 0.0078 max mem: 33369 +Epoch: [15] [ 300/1319] eta: 0:49:12 lr: 3.248461847161124e-05 loss: 0.0574 (0.0634) time: 2.8871 data: 0.0078 max mem: 33369 +Epoch: [15] [ 310/1319] eta: 0:48:41 lr: 3.247567049950301e-05 loss: 0.0519 (0.0632) time: 2.8578 data: 0.0081 max mem: 33369 +Epoch: [15] [ 320/1319] eta: 0:48:12 lr: 3.246672225345071e-05 loss: 0.0547 (0.0630) time: 2.8587 data: 0.0080 max mem: 33369 +Epoch: [15] [ 330/1319] eta: 0:47:42 lr: 3.245777373336205e-05 loss: 0.0582 (0.0631) time: 2.8648 data: 0.0080 max mem: 33369 +Epoch: [15] [ 340/1319] eta: 0:47:12 lr: 3.244882493914469e-05 loss: 0.0608 (0.0635) time: 2.8583 data: 0.0083 max mem: 33369 +Epoch: [15] [ 350/1319] eta: 0:46:42 lr: 3.243987587070623e-05 loss: 0.0520 (0.0633) time: 2.8538 data: 0.0083 max mem: 33369 +Epoch: [15] [ 360/1319] eta: 0:46:11 lr: 3.24309265279542e-05 loss: 0.0520 (0.0634) time: 2.8408 data: 0.0084 max mem: 33369 +Epoch: [15] [ 370/1319] eta: 0:45:41 lr: 3.2421976910796087e-05 loss: 0.0531 (0.0633) time: 2.8359 data: 0.0086 max mem: 33369 +Epoch: [15] [ 380/1319] eta: 0:45:11 lr: 3.24130270191393e-05 loss: 0.0531 (0.0633) time: 2.8482 data: 0.0084 max mem: 33369 +Epoch: [15] [ 390/1319] eta: 0:44:42 lr: 3.2404076852891215e-05 loss: 0.0521 (0.0633) time: 2.8610 data: 0.0081 max mem: 33369 +Epoch: [15] [ 400/1319] eta: 0:44:13 lr: 3.239512641195912e-05 loss: 0.0513 (0.0632) time: 2.8828 data: 0.0081 max mem: 33369 +Epoch: [15] [ 410/1319] eta: 0:43:44 lr: 3.238617569625025e-05 loss: 0.0513 (0.0631) time: 2.8854 data: 0.0082 max mem: 33369 +Epoch: [15] [ 420/1319] eta: 0:43:15 lr: 3.23772247056718e-05 loss: 0.0511 (0.0629) time: 2.8742 data: 0.0081 max mem: 33369 +Epoch: [15] [ 430/1319] eta: 0:42:44 lr: 3.2368273440130875e-05 loss: 0.0502 (0.0628) time: 2.8385 data: 0.0082 max mem: 33369 +Epoch: [15] [ 440/1319] eta: 0:42:15 lr: 3.235932189953454e-05 loss: 0.0442 (0.0624) time: 2.8457 data: 0.0085 max mem: 33369 +Epoch: [15] [ 450/1319] eta: 0:41:46 lr: 3.23503700837898e-05 loss: 0.0496 (0.0624) time: 2.8595 data: 0.0083 max mem: 33369 +Epoch: [15] [ 460/1319] eta: 0:41:15 lr: 3.234141799280359e-05 loss: 0.0543 (0.0624) time: 2.8029 data: 0.0080 max mem: 33369 +Epoch: [15] [ 470/1319] eta: 0:40:44 lr: 3.2332465626482786e-05 loss: 0.0614 (0.0625) time: 2.7642 data: 0.0078 max mem: 33369 +Epoch: [15] [ 480/1319] eta: 0:40:11 lr: 3.232351298473422e-05 loss: 0.0571 (0.0626) time: 2.7040 data: 0.0073 max mem: 33369 +Epoch: [15] [ 490/1319] eta: 0:39:39 lr: 3.231456006746465e-05 loss: 0.0585 (0.0629) time: 2.6600 data: 0.0068 max mem: 33369 +Epoch: [15] [ 500/1319] eta: 0:39:06 lr: 3.2305606874580764e-05 loss: 0.0585 (0.0628) time: 2.6642 data: 0.0067 max mem: 33369 +Epoch: [15] [ 510/1319] eta: 0:38:36 lr: 3.229665340598921e-05 loss: 0.0573 (0.0628) time: 2.6901 data: 0.0066 max mem: 33369 +Epoch: [15] [ 520/1319] eta: 0:38:03 lr: 3.228769966159657e-05 loss: 0.0587 (0.0631) time: 2.6802 data: 0.0067 max mem: 33369 +Epoch: [15] [ 530/1319] eta: 0:37:33 lr: 3.227874564130935e-05 loss: 0.0572 (0.0629) time: 2.6887 data: 0.0068 max mem: 33369 +Epoch: [15] [ 540/1319] eta: 0:37:04 lr: 3.2269791345034015e-05 loss: 0.0571 (0.0630) time: 2.7726 data: 0.0069 max mem: 33369 +Epoch: [15] [ 550/1319] eta: 0:36:35 lr: 3.226083677267696e-05 loss: 0.0655 (0.0632) time: 2.8334 data: 0.0074 max mem: 33369 +Epoch: [15] [ 560/1319] eta: 0:36:06 lr: 3.225188192414452e-05 loss: 0.0586 (0.0631) time: 2.8381 data: 0.0078 max mem: 33369 +Epoch: [15] [ 570/1319] eta: 0:35:39 lr: 3.224292679934298e-05 loss: 0.0526 (0.0630) time: 2.8676 data: 0.0078 max mem: 33369 +Epoch: [15] [ 580/1319] eta: 0:35:11 lr: 3.2233971398178544e-05 loss: 0.0526 (0.0631) time: 2.9133 data: 0.0077 max mem: 33369 +Epoch: [15] [ 590/1319] eta: 0:34:43 lr: 3.2225015720557374e-05 loss: 0.0556 (0.0631) time: 2.9174 data: 0.0077 max mem: 33369 +Epoch: [15] [ 600/1319] eta: 0:34:15 lr: 3.221605976638556e-05 loss: 0.0558 (0.0632) time: 2.9263 data: 0.0075 max mem: 33369 +Epoch: [15] [ 610/1319] eta: 0:33:47 lr: 3.2207103535569134e-05 loss: 0.0581 (0.0633) time: 2.9151 data: 0.0075 max mem: 33369 +Epoch: [15] [ 620/1319] eta: 0:33:20 lr: 3.219814702801407e-05 loss: 0.0691 (0.0635) time: 2.9319 data: 0.0077 max mem: 33369 +Epoch: [15] [ 630/1319] eta: 0:32:52 lr: 3.218919024362627e-05 loss: 0.0638 (0.0636) time: 2.9566 data: 0.0077 max mem: 33369 +Epoch: [15] [ 640/1319] eta: 0:32:24 lr: 3.21802331823116e-05 loss: 0.0596 (0.0636) time: 2.9250 data: 0.0076 max mem: 33369 +Epoch: [15] [ 650/1319] eta: 0:31:55 lr: 3.2171275843975836e-05 loss: 0.0561 (0.0636) time: 2.8861 data: 0.0076 max mem: 33369 +Epoch: [15] [ 660/1319] eta: 0:31:26 lr: 3.21623182285247e-05 loss: 0.0543 (0.0635) time: 2.8636 data: 0.0078 max mem: 33369 +Epoch: [15] [ 670/1319] eta: 0:30:58 lr: 3.215336033586388e-05 loss: 0.0543 (0.0635) time: 2.8629 data: 0.0079 max mem: 33369 +Epoch: [15] [ 680/1319] eta: 0:30:30 lr: 3.214440216589895e-05 loss: 0.0607 (0.0635) time: 2.8903 data: 0.0078 max mem: 33369 +Epoch: [15] [ 690/1319] eta: 0:30:01 lr: 3.2135443718535476e-05 loss: 0.0520 (0.0634) time: 2.8989 data: 0.0078 max mem: 33369 +Epoch: [15] [ 700/1319] eta: 0:29:32 lr: 3.212648499367893e-05 loss: 0.0616 (0.0635) time: 2.8646 data: 0.0079 max mem: 33369 +Epoch: [15] [ 710/1319] eta: 0:29:04 lr: 3.211752599123473e-05 loss: 0.0640 (0.0635) time: 2.8352 data: 0.0080 max mem: 33369 +Epoch: [15] [ 720/1319] eta: 0:28:35 lr: 3.210856671110825e-05 loss: 0.0515 (0.0635) time: 2.8454 data: 0.0080 max mem: 33369 +Epoch: [15] [ 730/1319] eta: 0:28:06 lr: 3.2099607153204766e-05 loss: 0.0491 (0.0633) time: 2.8511 data: 0.0082 max mem: 33369 +Epoch: [15] [ 740/1319] eta: 0:27:37 lr: 3.209064731742954e-05 loss: 0.0544 (0.0635) time: 2.8547 data: 0.0084 max mem: 33369 +Epoch: [15] [ 750/1319] eta: 0:27:09 lr: 3.208168720368771e-05 loss: 0.0615 (0.0636) time: 2.8584 data: 0.0082 max mem: 33369 +Epoch: [15] [ 760/1319] eta: 0:26:40 lr: 3.2072726811884414e-05 loss: 0.0640 (0.0637) time: 2.8728 data: 0.0083 max mem: 33369 +Epoch: [15] [ 770/1319] eta: 0:26:11 lr: 3.20637661419247e-05 loss: 0.0663 (0.0636) time: 2.8669 data: 0.0084 max mem: 33369 +Epoch: [15] [ 780/1319] eta: 0:25:43 lr: 3.205480519371354e-05 loss: 0.0662 (0.0637) time: 2.8589 data: 0.0083 max mem: 33369 +Epoch: [15] [ 790/1319] eta: 0:25:14 lr: 3.204584396715587e-05 loss: 0.0500 (0.0635) time: 2.8417 data: 0.0085 max mem: 33369 +Epoch: [15] [ 800/1319] eta: 0:24:45 lr: 3.203688246215656e-05 loss: 0.0542 (0.0640) time: 2.8321 data: 0.0084 max mem: 33369 +Epoch: [15] [ 810/1319] eta: 0:24:16 lr: 3.20279206786204e-05 loss: 0.0644 (0.0640) time: 2.8409 data: 0.0082 max mem: 33369 +Epoch: [15] [ 820/1319] eta: 0:23:48 lr: 3.201895861645214e-05 loss: 0.0528 (0.0638) time: 2.8524 data: 0.0082 max mem: 33369 +Epoch: [15] [ 830/1319] eta: 0:23:19 lr: 3.2009996275556456e-05 loss: 0.0535 (0.0638) time: 2.8760 data: 0.0083 max mem: 33369 +Epoch: [15] [ 840/1319] eta: 0:22:51 lr: 3.200103365583796e-05 loss: 0.0611 (0.0638) time: 2.8632 data: 0.0086 max mem: 33369 +Epoch: [15] [ 850/1319] eta: 0:22:22 lr: 3.1992070757201206e-05 loss: 0.0485 (0.0637) time: 2.8686 data: 0.0085 max mem: 33369 +Epoch: [15] [ 860/1319] eta: 0:21:53 lr: 3.198310757955068e-05 loss: 0.0502 (0.0636) time: 2.8470 data: 0.0082 max mem: 33369 +Epoch: [15] [ 870/1319] eta: 0:21:24 lr: 3.197414412279081e-05 loss: 0.0579 (0.0637) time: 2.8067 data: 0.0081 max mem: 33369 +Epoch: [15] [ 880/1319] eta: 0:20:55 lr: 3.196518038682597e-05 loss: 0.0625 (0.0636) time: 2.7758 data: 0.0080 max mem: 33369 +Epoch: [15] [ 890/1319] eta: 0:20:25 lr: 3.1956216371560456e-05 loss: 0.0521 (0.0635) time: 2.6963 data: 0.0074 max mem: 33369 +Epoch: [15] [ 900/1319] eta: 0:19:56 lr: 3.194725207689851e-05 loss: 0.0551 (0.0638) time: 2.6443 data: 0.0071 max mem: 33369 +Epoch: [15] [ 910/1319] eta: 0:19:27 lr: 3.1938287502744314e-05 loss: 0.0589 (0.0637) time: 2.6615 data: 0.0070 max mem: 33369 +Epoch: [15] [ 920/1319] eta: 0:18:58 lr: 3.192932264900198e-05 loss: 0.0542 (0.0638) time: 2.7245 data: 0.0070 max mem: 33369 +Epoch: [15] [ 930/1319] eta: 0:18:29 lr: 3.192035751557555e-05 loss: 0.0531 (0.0637) time: 2.7838 data: 0.0071 max mem: 33369 +Epoch: [15] [ 940/1319] eta: 0:18:00 lr: 3.1911392102369026e-05 loss: 0.0612 (0.0638) time: 2.8301 data: 0.0075 max mem: 33369 +Epoch: [15] [ 950/1319] eta: 0:17:32 lr: 3.1902426409286326e-05 loss: 0.0546 (0.0637) time: 2.8869 data: 0.0077 max mem: 33369 +Epoch: [15] [ 960/1319] eta: 0:17:04 lr: 3.189346043623133e-05 loss: 0.0514 (0.0637) time: 2.8834 data: 0.0077 max mem: 33369 +Epoch: [15] [ 970/1319] eta: 0:16:35 lr: 3.1884494183107815e-05 loss: 0.0523 (0.0637) time: 2.8974 data: 0.0077 max mem: 33369 +Epoch: [15] [ 980/1319] eta: 0:16:07 lr: 3.187552764981953e-05 loss: 0.0588 (0.0637) time: 2.9366 data: 0.0076 max mem: 33369 +Epoch: [15] [ 990/1319] eta: 0:15:39 lr: 3.186656083627014e-05 loss: 0.0551 (0.0637) time: 2.9232 data: 0.0076 max mem: 33369 +Epoch: [15] [1000/1319] eta: 0:15:10 lr: 3.1857593742363276e-05 loss: 0.0525 (0.0636) time: 2.9202 data: 0.0077 max mem: 33369 +Epoch: [15] [1010/1319] eta: 0:14:42 lr: 3.184862636800246e-05 loss: 0.0482 (0.0635) time: 2.9207 data: 0.0079 max mem: 33369 +Epoch: [15] [1020/1319] eta: 0:14:14 lr: 3.183965871309119e-05 loss: 0.0485 (0.0635) time: 2.8781 data: 0.0077 max mem: 33369 +Epoch: [15] [1030/1319] eta: 0:13:45 lr: 3.1830690777532884e-05 loss: 0.0581 (0.0635) time: 2.8530 data: 0.0076 max mem: 33369 +Epoch: [15] [1040/1319] eta: 0:13:16 lr: 3.182172256123091e-05 loss: 0.0568 (0.0636) time: 2.8708 data: 0.0076 max mem: 33369 +Epoch: [15] [1050/1319] eta: 0:12:48 lr: 3.181275406408854e-05 loss: 0.0548 (0.0635) time: 2.8772 data: 0.0077 max mem: 33369 +Epoch: [15] [1060/1319] eta: 0:12:19 lr: 3.180378528600901e-05 loss: 0.0549 (0.0635) time: 2.8739 data: 0.0077 max mem: 33369 +Epoch: [15] [1070/1319] eta: 0:11:51 lr: 3.17948162268955e-05 loss: 0.0597 (0.0636) time: 2.8509 data: 0.0077 max mem: 33369 +Epoch: [15] [1080/1319] eta: 0:11:22 lr: 3.17858468866511e-05 loss: 0.0650 (0.0638) time: 2.8612 data: 0.0077 max mem: 33369 +Epoch: [15] [1090/1319] eta: 0:10:54 lr: 3.177687726517885e-05 loss: 0.0709 (0.0638) time: 2.8573 data: 0.0080 max mem: 33369 +Epoch: [15] [1100/1319] eta: 0:10:25 lr: 3.1767907362381725e-05 loss: 0.0561 (0.0637) time: 2.8407 data: 0.0082 max mem: 33369 +Epoch: [15] [1110/1319] eta: 0:09:57 lr: 3.175893717816263e-05 loss: 0.0488 (0.0636) time: 2.8648 data: 0.0080 max mem: 33369 +Epoch: [15] [1120/1319] eta: 0:09:28 lr: 3.174996671242443e-05 loss: 0.0589 (0.0636) time: 2.8765 data: 0.0080 max mem: 33369 +Epoch: [15] [1130/1319] eta: 0:08:59 lr: 3.1740995965069895e-05 loss: 0.0534 (0.0635) time: 2.8621 data: 0.0080 max mem: 33369 +Epoch: [15] [1140/1319] eta: 0:08:31 lr: 3.173202493600174e-05 loss: 0.0477 (0.0635) time: 2.8469 data: 0.0081 max mem: 33369 +Epoch: [15] [1150/1319] eta: 0:08:02 lr: 3.172305362512263e-05 loss: 0.0638 (0.0637) time: 2.8234 data: 0.0085 max mem: 33369 +Epoch: [15] [1160/1319] eta: 0:07:34 lr: 3.171408203233514e-05 loss: 0.0714 (0.0637) time: 2.8095 data: 0.0085 max mem: 33369 +Epoch: [15] [1170/1319] eta: 0:07:05 lr: 3.170511015754181e-05 loss: 0.0657 (0.0638) time: 2.8362 data: 0.0081 max mem: 33369 +Epoch: [15] [1180/1319] eta: 0:06:36 lr: 3.16961380006451e-05 loss: 0.0550 (0.0637) time: 2.8297 data: 0.0080 max mem: 33369 +Epoch: [15] [1190/1319] eta: 0:06:08 lr: 3.16871655615474e-05 loss: 0.0531 (0.0637) time: 2.8570 data: 0.0083 max mem: 33369 +Epoch: [15] [1200/1319] eta: 0:05:39 lr: 3.1678192840151044e-05 loss: 0.0564 (0.0638) time: 2.8791 data: 0.0085 max mem: 33369 +Epoch: [15] [1210/1319] eta: 0:05:11 lr: 3.16692198363583e-05 loss: 0.0578 (0.0638) time: 2.8529 data: 0.0085 max mem: 33369 +Epoch: [15] [1220/1319] eta: 0:04:42 lr: 3.1660246550071386e-05 loss: 0.0578 (0.0638) time: 2.8491 data: 0.0085 max mem: 33369 +Epoch: [15] [1230/1319] eta: 0:04:14 lr: 3.165127298119242e-05 loss: 0.0699 (0.0641) time: 2.8474 data: 0.0084 max mem: 33369 +Epoch: [15] [1240/1319] eta: 0:03:45 lr: 3.164229912962349e-05 loss: 0.0711 (0.0641) time: 2.8695 data: 0.0085 max mem: 33369 +Epoch: [15] [1250/1319] eta: 0:03:17 lr: 3.163332499526659e-05 loss: 0.0589 (0.0640) time: 2.8470 data: 0.0082 max mem: 33369 +Epoch: [15] [1260/1319] eta: 0:02:48 lr: 3.162435057802369e-05 loss: 0.0532 (0.0639) time: 2.7668 data: 0.0082 max mem: 33369 +Epoch: [15] [1270/1319] eta: 0:02:19 lr: 3.161537587779665e-05 loss: 0.0557 (0.0640) time: 2.6982 data: 0.0080 max mem: 33369 +Epoch: [15] [1280/1319] eta: 0:01:51 lr: 3.1606400894487287e-05 loss: 0.0663 (0.0641) time: 2.6438 data: 0.0073 max mem: 33369 +Epoch: [15] [1290/1319] eta: 0:01:22 lr: 3.159742562799735e-05 loss: 0.0715 (0.0641) time: 2.6522 data: 0.0069 max mem: 33369 +Epoch: [15] [1300/1319] eta: 0:00:54 lr: 3.158845007822852e-05 loss: 0.0634 (0.0641) time: 2.6392 data: 0.0067 max mem: 33369 +Epoch: [15] [1310/1319] eta: 0:00:25 lr: 3.1579474245082424e-05 loss: 0.0634 (0.0641) time: 2.6494 data: 0.0066 max mem: 33369 +Epoch: [15] Total time: 1:02:34 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 2:11:58 time: 3.0776 data: 2.9838 max mem: 33369 +Test: [ 100/2573] eta: 0:04:12 time: 0.0722 data: 0.0012 max mem: 33369 +Test: [ 200/2573] eta: 0:03:30 time: 0.0743 data: 0.0013 max mem: 33369 +Test: [ 300/2573] eta: 0:03:09 time: 0.0760 data: 0.0012 max mem: 33369 +Test: [ 400/2573] eta: 0:02:56 time: 0.0764 data: 0.0012 max mem: 33369 +Test: [ 500/2573] eta: 0:02:45 time: 0.0752 data: 0.0013 max mem: 33369 +Test: [ 600/2573] eta: 0:02:36 time: 0.0748 data: 0.0012 max mem: 33369 +Test: [ 700/2573] eta: 0:02:27 time: 0.0750 data: 0.0013 max mem: 33369 +Test: [ 800/2573] eta: 0:02:19 time: 0.0784 data: 0.0012 max mem: 33369 +Test: [ 900/2573] eta: 0:02:10 time: 0.0749 data: 0.0012 max mem: 33369 +Test: [1000/2573] eta: 0:02:02 time: 0.0756 data: 0.0013 max mem: 33369 +Test: [1100/2573] eta: 0:01:54 time: 0.0755 data: 0.0014 max mem: 33369 +Test: [1200/2573] eta: 0:01:46 time: 0.0758 data: 0.0013 max mem: 33369 +Test: [1300/2573] eta: 0:01:38 time: 0.0760 data: 0.0013 max mem: 33369 +Test: [1400/2573] eta: 0:01:30 time: 0.0741 data: 0.0013 max mem: 33369 +Test: [1500/2573] eta: 0:01:22 time: 0.0758 data: 0.0014 max mem: 33369 +Test: [1600/2573] eta: 0:01:15 time: 0.0790 data: 0.0013 max mem: 33369 +Test: [1700/2573] eta: 0:01:07 time: 0.0740 data: 0.0013 max mem: 33369 +Test: [1800/2573] eta: 0:00:59 time: 0.0772 data: 0.0013 max mem: 33369 +Test: [1900/2573] eta: 0:00:51 time: 0.0741 data: 0.0014 max mem: 33369 +Test: [2000/2573] eta: 0:00:43 time: 0.0759 data: 0.0014 max mem: 33369 +Test: [2100/2573] eta: 0:00:36 time: 0.0772 data: 0.0013 max mem: 33369 +Test: [2200/2573] eta: 0:00:28 time: 0.0773 data: 0.0013 max mem: 33369 +Test: [2300/2573] eta: 0:00:20 time: 0.0774 data: 0.0013 max mem: 33369 +Test: [2400/2573] eta: 0:00:13 time: 0.0722 data: 0.0013 max mem: 33369 +Test: [2500/2573] eta: 0:00:05 time: 0.0756 data: 0.0013 max mem: 33369 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: Total time: 0:03:17 +Final results: +Mean IoU is 62.61 + + precision@0.5 = 70.14 + precision@0.6 = 64.17 + precision@0.7 = 56.05 + precision@0.8 = 44.40 + precision@0.9 = 21.34 + overall IoU = 60.75 + +Average object IoU 62.60913760254518 +Overall IoU 60.75206756591797 +Better epoch: 15 + +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [16] [ 0/1319] eta: 1:34:02 lr: 3.157139575288201e-05 loss: 0.0572 (0.0572) time: 4.2779 data: 1.3203 max mem: 33369 +Epoch: [16] [ 10/1319] eta: 1:06:25 lr: 3.1562419381047834e-05 loss: 0.0509 (0.0583) time: 3.0449 data: 0.1267 max mem: 33369 +Epoch: [16] [ 20/1319] eta: 1:04:30 lr: 3.155344272555071e-05 loss: 0.0509 (0.0556) time: 2.9144 data: 0.0072 max mem: 33369 +Epoch: [16] [ 30/1319] eta: 1:03:25 lr: 3.154446578629201e-05 loss: 0.0570 (0.0590) time: 2.9010 data: 0.0073 max mem: 33369 +Epoch: [16] [ 40/1319] eta: 1:02:55 lr: 3.153548856317304e-05 loss: 0.0560 (0.0583) time: 2.9230 data: 0.0076 max mem: 33369 +Epoch: [16] [ 50/1319] eta: 1:02:15 lr: 3.152651105609501e-05 loss: 0.0427 (0.0544) time: 2.9304 data: 0.0077 max mem: 33369 +Epoch: [16] [ 60/1319] eta: 1:01:31 lr: 3.1517533264959104e-05 loss: 0.0422 (0.0545) time: 2.8920 data: 0.0077 max mem: 33369 +Epoch: [16] [ 70/1319] eta: 1:00:47 lr: 3.150855518966642e-05 loss: 0.0610 (0.0568) time: 2.8624 data: 0.0078 max mem: 33369 +Epoch: [16] [ 80/1319] eta: 1:00:10 lr: 3.1499576830118e-05 loss: 0.0610 (0.0570) time: 2.8591 data: 0.0079 max mem: 33369 +Epoch: [16] [ 90/1319] eta: 0:59:35 lr: 3.14905981862148e-05 loss: 0.0551 (0.0568) time: 2.8702 data: 0.0081 max mem: 33369 +Epoch: [16] [ 100/1319] eta: 0:58:58 lr: 3.1481619257857746e-05 loss: 0.0535 (0.0577) time: 2.8579 data: 0.0081 max mem: 33369 +Epoch: [16] [ 110/1319] eta: 0:58:23 lr: 3.147264004494766e-05 loss: 0.0531 (0.0576) time: 2.8454 data: 0.0079 max mem: 33369 +Epoch: [16] [ 120/1319] eta: 0:57:46 lr: 3.1463660547385324e-05 loss: 0.0439 (0.0580) time: 2.8315 data: 0.0081 max mem: 33369 +Epoch: [16] [ 130/1319] eta: 0:57:10 lr: 3.1454680765071425e-05 loss: 0.0524 (0.0597) time: 2.8137 data: 0.0083 max mem: 33369 +Epoch: [16] [ 140/1319] eta: 0:56:35 lr: 3.1445700697906627e-05 loss: 0.0513 (0.0586) time: 2.8114 data: 0.0084 max mem: 33369 +Epoch: [16] [ 150/1319] eta: 0:56:08 lr: 3.1436720345791495e-05 loss: 0.0479 (0.0586) time: 2.8549 data: 0.0084 max mem: 33369 +Epoch: [16] [ 160/1319] eta: 0:55:37 lr: 3.1427739708626534e-05 loss: 0.0479 (0.0587) time: 2.8767 data: 0.0084 max mem: 33369 +Epoch: [16] [ 170/1319] eta: 0:55:06 lr: 3.141875878631219e-05 loss: 0.0496 (0.0584) time: 2.8533 data: 0.0083 max mem: 33369 +Epoch: [16] [ 180/1319] eta: 0:54:38 lr: 3.140977757874883e-05 loss: 0.0570 (0.0597) time: 2.8668 data: 0.0082 max mem: 33369 +Epoch: [16] [ 190/1319] eta: 0:54:07 lr: 3.140079608583676e-05 loss: 0.0538 (0.0592) time: 2.8651 data: 0.0082 max mem: 33369 +Epoch: [16] [ 200/1319] eta: 0:53:36 lr: 3.1391814307476244e-05 loss: 0.0515 (0.0591) time: 2.8397 data: 0.0084 max mem: 33369 +Epoch: [16] [ 210/1319] eta: 0:53:06 lr: 3.138283224356744e-05 loss: 0.0488 (0.0589) time: 2.8461 data: 0.0085 max mem: 33369 +Epoch: [16] [ 220/1319] eta: 0:52:36 lr: 3.137384989401046e-05 loss: 0.0470 (0.0592) time: 2.8547 data: 0.0085 max mem: 33369 +Epoch: [16] [ 230/1319] eta: 0:52:07 lr: 3.136486725870535e-05 loss: 0.0458 (0.0588) time: 2.8519 data: 0.0089 max mem: 33369 +Epoch: [16] [ 240/1319] eta: 0:51:37 lr: 3.1355884337552074e-05 loss: 0.0517 (0.0591) time: 2.8555 data: 0.0089 max mem: 33369 +Epoch: [16] [ 250/1319] eta: 0:51:08 lr: 3.1346901130450554e-05 loss: 0.0550 (0.0592) time: 2.8547 data: 0.0086 max mem: 33369 +Epoch: [16] [ 260/1319] eta: 0:50:36 lr: 3.133791763730062e-05 loss: 0.0549 (0.0592) time: 2.8274 data: 0.0086 max mem: 33369 +Epoch: [16] [ 270/1319] eta: 0:50:05 lr: 3.132893385800206e-05 loss: 0.0582 (0.0593) time: 2.8007 data: 0.0083 max mem: 33369 +Epoch: [16] [ 280/1319] eta: 0:49:34 lr: 3.131994979245456e-05 loss: 0.0582 (0.0592) time: 2.8002 data: 0.0084 max mem: 33369 +Epoch: [16] [ 290/1319] eta: 0:49:03 lr: 3.131096544055778e-05 loss: 0.0640 (0.0598) time: 2.7926 data: 0.0086 max mem: 33369 +Epoch: [16] [ 300/1319] eta: 0:48:29 lr: 3.130198080221128e-05 loss: 0.0614 (0.0600) time: 2.7414 data: 0.0078 max mem: 33369 +Epoch: [16] [ 310/1319] eta: 0:47:54 lr: 3.129299587731458e-05 loss: 0.0555 (0.0597) time: 2.6882 data: 0.0071 max mem: 33369 +Epoch: [16] [ 320/1319] eta: 0:47:20 lr: 3.1284010665767105e-05 loss: 0.0555 (0.0601) time: 2.6644 data: 0.0070 max mem: 33369 +Epoch: [16] [ 330/1319] eta: 0:46:47 lr: 3.1275025167468235e-05 loss: 0.0604 (0.0601) time: 2.6717 data: 0.0069 max mem: 33369 +Epoch: [16] [ 340/1319] eta: 0:46:18 lr: 3.126603938231727e-05 loss: 0.0532 (0.0600) time: 2.7663 data: 0.0072 max mem: 33369 +Epoch: [16] [ 350/1319] eta: 0:45:50 lr: 3.1257053310213444e-05 loss: 0.0532 (0.0602) time: 2.8316 data: 0.0075 max mem: 33369 +Epoch: [16] [ 360/1319] eta: 0:45:23 lr: 3.124806695105593e-05 loss: 0.0538 (0.0599) time: 2.8569 data: 0.0078 max mem: 33369 +Epoch: [16] [ 370/1319] eta: 0:44:55 lr: 3.1239080304743815e-05 loss: 0.0567 (0.0603) time: 2.8868 data: 0.0080 max mem: 33369 +Epoch: [16] [ 380/1319] eta: 0:44:29 lr: 3.123009337117616e-05 loss: 0.0553 (0.0603) time: 2.8969 data: 0.0079 max mem: 33369 +Epoch: [16] [ 390/1319] eta: 0:44:02 lr: 3.12211061502519e-05 loss: 0.0523 (0.0603) time: 2.9065 data: 0.0078 max mem: 33369 +Epoch: [16] [ 400/1319] eta: 0:43:36 lr: 3.121211864186995e-05 loss: 0.0534 (0.0601) time: 2.9246 data: 0.0078 max mem: 33369 +Epoch: [16] [ 410/1319] eta: 0:43:08 lr: 3.120313084592913e-05 loss: 0.0519 (0.0601) time: 2.9169 data: 0.0078 max mem: 33369 +Epoch: [16] [ 420/1319] eta: 0:42:42 lr: 3.119414276232821e-05 loss: 0.0503 (0.0600) time: 2.9312 data: 0.0077 max mem: 33369 +Epoch: [16] [ 430/1319] eta: 0:42:15 lr: 3.118515439096588e-05 loss: 0.0523 (0.0600) time: 2.9506 data: 0.0077 max mem: 33369 +Epoch: [16] [ 440/1319] eta: 0:41:47 lr: 3.117616573174077e-05 loss: 0.0561 (0.0601) time: 2.8962 data: 0.0078 max mem: 33369 +Epoch: [16] [ 450/1319] eta: 0:41:19 lr: 3.116717678455143e-05 loss: 0.0561 (0.0601) time: 2.8742 data: 0.0078 max mem: 33369 +Epoch: [16] [ 460/1319] eta: 0:40:51 lr: 3.115818754929635e-05 loss: 0.0579 (0.0601) time: 2.8790 data: 0.0079 max mem: 33369 +Epoch: [16] [ 470/1319] eta: 0:40:22 lr: 3.1149198025873954e-05 loss: 0.0569 (0.0603) time: 2.8645 data: 0.0078 max mem: 33369 +Epoch: [16] [ 480/1319] eta: 0:39:54 lr: 3.1140208214182586e-05 loss: 0.0539 (0.0604) time: 2.8611 data: 0.0078 max mem: 33369 +Epoch: [16] [ 490/1319] eta: 0:39:26 lr: 3.113121811412054e-05 loss: 0.0523 (0.0603) time: 2.8789 data: 0.0082 max mem: 33369 +Epoch: [16] [ 500/1319] eta: 0:38:57 lr: 3.1122227725586026e-05 loss: 0.0526 (0.0604) time: 2.8497 data: 0.0081 max mem: 33369 +Epoch: [16] [ 510/1319] eta: 0:38:28 lr: 3.1113237048477186e-05 loss: 0.0551 (0.0603) time: 2.8294 data: 0.0081 max mem: 33369 +Epoch: [16] [ 520/1319] eta: 0:37:59 lr: 3.11042460826921e-05 loss: 0.0531 (0.0604) time: 2.8392 data: 0.0082 max mem: 33369 +Epoch: [16] [ 530/1319] eta: 0:37:31 lr: 3.1095254828128786e-05 loss: 0.0541 (0.0604) time: 2.8333 data: 0.0082 max mem: 33369 +Epoch: [16] [ 540/1319] eta: 0:37:02 lr: 3.108626328468517e-05 loss: 0.0541 (0.0602) time: 2.8446 data: 0.0082 max mem: 33369 +Epoch: [16] [ 550/1319] eta: 0:36:34 lr: 3.107727145225915e-05 loss: 0.0487 (0.0601) time: 2.8659 data: 0.0083 max mem: 33369 +Epoch: [16] [ 560/1319] eta: 0:36:05 lr: 3.106827933074849e-05 loss: 0.0449 (0.0598) time: 2.8370 data: 0.0086 max mem: 33369 +Epoch: [16] [ 570/1319] eta: 0:35:36 lr: 3.105928692005095e-05 loss: 0.0487 (0.0602) time: 2.8315 data: 0.0086 max mem: 33369 +Epoch: [16] [ 580/1319] eta: 0:35:07 lr: 3.105029422006419e-05 loss: 0.0524 (0.0602) time: 2.8398 data: 0.0086 max mem: 33369 +Epoch: [16] [ 590/1319] eta: 0:34:39 lr: 3.104130123068579e-05 loss: 0.0560 (0.0602) time: 2.8382 data: 0.0086 max mem: 33369 +Epoch: [16] [ 600/1319] eta: 0:34:10 lr: 3.10323079518133e-05 loss: 0.0560 (0.0601) time: 2.8415 data: 0.0087 max mem: 33369 +Epoch: [16] [ 610/1319] eta: 0:33:41 lr: 3.102331438334416e-05 loss: 0.0527 (0.0602) time: 2.8311 data: 0.0088 max mem: 33369 +Epoch: [16] [ 620/1319] eta: 0:33:13 lr: 3.1014320525175755e-05 loss: 0.0572 (0.0601) time: 2.8374 data: 0.0087 max mem: 33369 +Epoch: [16] [ 630/1319] eta: 0:32:44 lr: 3.100532637720542e-05 loss: 0.0496 (0.0601) time: 2.8399 data: 0.0086 max mem: 33369 +Epoch: [16] [ 640/1319] eta: 0:32:15 lr: 3.099633193933038e-05 loss: 0.0649 (0.0603) time: 2.8388 data: 0.0087 max mem: 33369 +Epoch: [16] [ 650/1319] eta: 0:31:46 lr: 3.098733721144784e-05 loss: 0.0618 (0.0602) time: 2.8182 data: 0.0087 max mem: 33369 +Epoch: [16] [ 660/1319] eta: 0:31:18 lr: 3.097834219345489e-05 loss: 0.0569 (0.0604) time: 2.8307 data: 0.0085 max mem: 33369 +Epoch: [16] [ 670/1319] eta: 0:30:49 lr: 3.0969346885248574e-05 loss: 0.0518 (0.0603) time: 2.8403 data: 0.0083 max mem: 33369 +Epoch: [16] [ 680/1319] eta: 0:30:20 lr: 3.0960351286725865e-05 loss: 0.0498 (0.0602) time: 2.8155 data: 0.0085 max mem: 33369 +Epoch: [16] [ 690/1319] eta: 0:29:50 lr: 3.0951355397783653e-05 loss: 0.0575 (0.0604) time: 2.7183 data: 0.0084 max mem: 33369 +Epoch: [16] [ 700/1319] eta: 0:29:20 lr: 3.0942359218318776e-05 loss: 0.0615 (0.0604) time: 2.6481 data: 0.0075 max mem: 33369 +Epoch: [16] [ 710/1319] eta: 0:28:50 lr: 3.0933362748228e-05 loss: 0.0602 (0.0603) time: 2.6584 data: 0.0069 max mem: 33369 +Epoch: [16] [ 720/1319] eta: 0:28:19 lr: 3.092436598740799e-05 loss: 0.0486 (0.0603) time: 2.6470 data: 0.0070 max mem: 33369 +Epoch: [16] [ 730/1319] eta: 0:27:50 lr: 3.09153689357554e-05 loss: 0.0485 (0.0604) time: 2.6845 data: 0.0073 max mem: 33369 +Epoch: [16] [ 740/1319] eta: 0:27:21 lr: 3.090637159316675e-05 loss: 0.0470 (0.0603) time: 2.7552 data: 0.0074 max mem: 33369 +Epoch: [16] [ 750/1319] eta: 0:26:53 lr: 3.089737395953854e-05 loss: 0.0525 (0.0605) time: 2.7779 data: 0.0074 max mem: 33369 +Epoch: [16] [ 760/1319] eta: 0:26:25 lr: 3.088837603476717e-05 loss: 0.0631 (0.0607) time: 2.8319 data: 0.0077 max mem: 33369 +Epoch: [16] [ 770/1319] eta: 0:25:57 lr: 3.087937781874897e-05 loss: 0.0631 (0.0609) time: 2.9023 data: 0.0079 max mem: 33369 +Epoch: [16] [ 780/1319] eta: 0:25:29 lr: 3.087037931138022e-05 loss: 0.0582 (0.0610) time: 2.9151 data: 0.0080 max mem: 33369 +Epoch: [16] [ 790/1319] eta: 0:25:01 lr: 3.086138051255712e-05 loss: 0.0569 (0.0610) time: 2.8953 data: 0.0079 max mem: 33369 +Epoch: [16] [ 800/1319] eta: 0:24:33 lr: 3.085238142217579e-05 loss: 0.0523 (0.0609) time: 2.8764 data: 0.0077 max mem: 33369 +Epoch: [16] [ 810/1319] eta: 0:24:05 lr: 3.084338204013227e-05 loss: 0.0488 (0.0608) time: 2.8859 data: 0.0076 max mem: 33369 +Epoch: [16] [ 820/1319] eta: 0:23:37 lr: 3.0834382366322574e-05 loss: 0.0553 (0.0608) time: 2.9044 data: 0.0074 max mem: 33369 +Epoch: [16] [ 830/1319] eta: 0:23:09 lr: 3.08253824006426e-05 loss: 0.0582 (0.0609) time: 2.9117 data: 0.0073 max mem: 33369 +Epoch: [16] [ 840/1319] eta: 0:22:41 lr: 3.08163821429882e-05 loss: 0.0681 (0.0610) time: 2.9211 data: 0.0075 max mem: 33369 +Epoch: [16] [ 850/1319] eta: 0:22:13 lr: 3.0807381593255134e-05 loss: 0.0552 (0.0610) time: 2.9109 data: 0.0074 max mem: 33369 +Epoch: [16] [ 860/1319] eta: 0:21:44 lr: 3.079838075133912e-05 loss: 0.0576 (0.0610) time: 2.8540 data: 0.0074 max mem: 33369 +Epoch: [16] [ 870/1319] eta: 0:21:16 lr: 3.0789379617135774e-05 loss: 0.0610 (0.0612) time: 2.8393 data: 0.0079 max mem: 33369 +Epoch: [16] [ 880/1319] eta: 0:20:48 lr: 3.078037819054066e-05 loss: 0.0564 (0.0612) time: 2.8715 data: 0.0081 max mem: 33369 +Epoch: [16] [ 890/1319] eta: 0:20:19 lr: 3.0771376471449264e-05 loss: 0.0507 (0.0611) time: 2.8654 data: 0.0080 max mem: 33369 +Epoch: [16] [ 900/1319] eta: 0:19:51 lr: 3.076237445975701e-05 loss: 0.0506 (0.0612) time: 2.8672 data: 0.0081 max mem: 33369 +Epoch: [16] [ 910/1319] eta: 0:19:23 lr: 3.075337215535924e-05 loss: 0.0536 (0.0614) time: 2.8849 data: 0.0082 max mem: 33369 +Epoch: [16] [ 920/1319] eta: 0:18:54 lr: 3.074436955815122e-05 loss: 0.0550 (0.0614) time: 2.8638 data: 0.0081 max mem: 33369 +Epoch: [16] [ 930/1319] eta: 0:18:26 lr: 3.073536666802816e-05 loss: 0.0550 (0.0614) time: 2.8406 data: 0.0081 max mem: 33369 +Epoch: [16] [ 940/1319] eta: 0:17:58 lr: 3.0726363484885186e-05 loss: 0.0594 (0.0614) time: 2.8560 data: 0.0082 max mem: 33369 +Epoch: [16] [ 950/1319] eta: 0:17:29 lr: 3.0717360008617356e-05 loss: 0.0594 (0.0613) time: 2.8649 data: 0.0082 max mem: 33369 +Epoch: [16] [ 960/1319] eta: 0:17:01 lr: 3.070835623911966e-05 loss: 0.0644 (0.0614) time: 2.8582 data: 0.0082 max mem: 33369 +Epoch: [16] [ 970/1319] eta: 0:16:32 lr: 3.069935217628702e-05 loss: 0.0631 (0.0613) time: 2.8473 data: 0.0085 max mem: 33369 +Epoch: [16] [ 980/1319] eta: 0:16:04 lr: 3.0690347820014265e-05 loss: 0.0596 (0.0614) time: 2.8575 data: 0.0086 max mem: 33369 +Epoch: [16] [ 990/1319] eta: 0:15:35 lr: 3.068134317019618e-05 loss: 0.0481 (0.0613) time: 2.8451 data: 0.0084 max mem: 33369 +Epoch: [16] [1000/1319] eta: 0:15:07 lr: 3.0672338226727455e-05 loss: 0.0462 (0.0613) time: 2.8232 data: 0.0083 max mem: 33369 +Epoch: [16] [1010/1319] eta: 0:14:38 lr: 3.066333298950271e-05 loss: 0.0571 (0.0613) time: 2.8299 data: 0.0082 max mem: 33369 +Epoch: [16] [1020/1319] eta: 0:14:10 lr: 3.065432745841652e-05 loss: 0.0562 (0.0613) time: 2.8149 data: 0.0082 max mem: 33369 +Epoch: [16] [1030/1319] eta: 0:13:42 lr: 3.064532163336335e-05 loss: 0.0613 (0.0614) time: 2.8490 data: 0.0084 max mem: 33369 +Epoch: [16] [1040/1319] eta: 0:13:13 lr: 3.063631551423762e-05 loss: 0.0607 (0.0614) time: 2.8721 data: 0.0084 max mem: 33369 +Epoch: [16] [1050/1319] eta: 0:12:45 lr: 3.062730910093366e-05 loss: 0.0521 (0.0613) time: 2.8445 data: 0.0083 max mem: 33369 +Epoch: [16] [1060/1319] eta: 0:12:16 lr: 3.061830239334574e-05 loss: 0.0472 (0.0613) time: 2.7882 data: 0.0085 max mem: 33369 +Epoch: [16] [1070/1319] eta: 0:11:47 lr: 3.0609295391368055e-05 loss: 0.0530 (0.0613) time: 2.7611 data: 0.0086 max mem: 33369 +Epoch: [16] [1080/1319] eta: 0:11:19 lr: 3.060028809489473e-05 loss: 0.0538 (0.0613) time: 2.7681 data: 0.0084 max mem: 33369 +Epoch: [16] [1090/1319] eta: 0:10:50 lr: 3.059128050381978e-05 loss: 0.0534 (0.0613) time: 2.7141 data: 0.0077 max mem: 33369 +Epoch: [16] [1100/1319] eta: 0:10:21 lr: 3.058227261803723e-05 loss: 0.0534 (0.0612) time: 2.6477 data: 0.0070 max mem: 33369 +Epoch: [16] [1110/1319] eta: 0:09:52 lr: 3.0573264437440946e-05 loss: 0.0614 (0.0614) time: 2.6364 data: 0.0068 max mem: 33369 +Epoch: [16] [1120/1319] eta: 0:09:24 lr: 3.056425596192476e-05 loss: 0.0704 (0.0614) time: 2.6588 data: 0.0066 max mem: 33369 +Epoch: [16] [1130/1319] eta: 0:08:55 lr: 3.0555247191382436e-05 loss: 0.0631 (0.0614) time: 2.6454 data: 0.0066 max mem: 33369 +Epoch: [16] [1140/1319] eta: 0:08:26 lr: 3.054623812570766e-05 loss: 0.0512 (0.0614) time: 2.6290 data: 0.0067 max mem: 33369 +Epoch: [16] [1150/1319] eta: 0:07:58 lr: 3.053722876479403e-05 loss: 0.0512 (0.0614) time: 2.6475 data: 0.0069 max mem: 33369 +Epoch: [16] [1160/1319] eta: 0:07:29 lr: 3.0528219108535084e-05 loss: 0.0523 (0.0615) time: 2.6729 data: 0.0070 max mem: 33369 +Epoch: [16] [1170/1319] eta: 0:07:01 lr: 3.0519209156824297e-05 loss: 0.0650 (0.0618) time: 2.7524 data: 0.0073 max mem: 33369 +Epoch: [16] [1180/1319] eta: 0:06:33 lr: 3.0510198909555044e-05 loss: 0.0610 (0.0618) time: 2.8569 data: 0.0078 max mem: 33369 +Epoch: [16] [1190/1319] eta: 0:06:05 lr: 3.0501188366620653e-05 loss: 0.0605 (0.0618) time: 2.9056 data: 0.0078 max mem: 33369 +Epoch: [16] [1200/1319] eta: 0:05:36 lr: 3.0492177527914355e-05 loss: 0.0614 (0.0619) time: 2.8924 data: 0.0077 max mem: 33369 +Epoch: [16] [1210/1319] eta: 0:05:08 lr: 3.0483166393329327e-05 loss: 0.0536 (0.0618) time: 2.8823 data: 0.0077 max mem: 33369 +Epoch: [16] [1220/1319] eta: 0:04:40 lr: 3.0474154962758662e-05 loss: 0.0559 (0.0620) time: 2.8765 data: 0.0077 max mem: 33369 +Epoch: [16] [1230/1319] eta: 0:04:12 lr: 3.0465143236095372e-05 loss: 0.0559 (0.0619) time: 2.8920 data: 0.0078 max mem: 33369 +Epoch: [16] [1240/1319] eta: 0:03:43 lr: 3.045613121323242e-05 loss: 0.0473 (0.0619) time: 2.9259 data: 0.0077 max mem: 33369 +Epoch: [16] [1250/1319] eta: 0:03:15 lr: 3.044711889406267e-05 loss: 0.0494 (0.0619) time: 2.9342 data: 0.0077 max mem: 33369 +Epoch: [16] [1260/1319] eta: 0:02:47 lr: 3.0438106278478923e-05 loss: 0.0576 (0.0619) time: 2.9026 data: 0.0080 max mem: 33369 +Epoch: [16] [1270/1319] eta: 0:02:18 lr: 3.0429093366373907e-05 loss: 0.0599 (0.0620) time: 2.8696 data: 0.0081 max mem: 33369 +Epoch: [16] [1280/1319] eta: 0:01:50 lr: 3.0420080157640274e-05 loss: 0.0546 (0.0619) time: 2.8675 data: 0.0078 max mem: 33369 +Epoch: [16] [1290/1319] eta: 0:01:22 lr: 3.0411066652170593e-05 loss: 0.0612 (0.0620) time: 2.8640 data: 0.0078 max mem: 33369 +Epoch: [16] [1300/1319] eta: 0:00:53 lr: 3.040205284985739e-05 loss: 0.0552 (0.0619) time: 2.8842 data: 0.0079 max mem: 33369 +Epoch: [16] [1310/1319] eta: 0:00:25 lr: 3.039303875059306e-05 loss: 0.0512 (0.0619) time: 2.8850 data: 0.0078 max mem: 33369 +Epoch: [16] Total time: 1:02:20 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 2:08:02 time: 2.9858 data: 2.8875 max mem: 33369 +Test: [ 100/2573] eta: 0:04:13 time: 0.0731 data: 0.0013 max mem: 33369 +Test: [ 200/2573] eta: 0:03:31 time: 0.0749 data: 0.0014 max mem: 33369 +Test: [ 300/2573] eta: 0:03:10 time: 0.0765 data: 0.0013 max mem: 33369 +Test: [ 400/2573] eta: 0:02:57 time: 0.0768 data: 0.0013 max mem: 33369 +Test: [ 500/2573] eta: 0:02:46 time: 0.0752 data: 0.0014 max mem: 33369 +Test: [ 600/2573] eta: 0:02:37 time: 0.0754 data: 0.0014 max mem: 33369 +Test: [ 700/2573] eta: 0:02:28 time: 0.0753 data: 0.0014 max mem: 33369 +Test: [ 800/2573] eta: 0:02:20 time: 0.0787 data: 0.0013 max mem: 33369 +Test: [ 900/2573] eta: 0:02:11 time: 0.0757 data: 0.0014 max mem: 33369 +Test: [1000/2573] eta: 0:02:03 time: 0.0755 data: 0.0014 max mem: 33369 +Test: [1100/2573] eta: 0:01:55 time: 0.0755 data: 0.0014 max mem: 33369 +Test: [1200/2573] eta: 0:01:47 time: 0.0756 data: 0.0013 max mem: 33369 +Test: [1300/2573] eta: 0:01:39 time: 0.0757 data: 0.0014 max mem: 33369 +Test: [1400/2573] eta: 0:01:31 time: 0.0739 data: 0.0014 max mem: 33369 +Test: [1500/2573] eta: 0:01:23 time: 0.0758 data: 0.0013 max mem: 33369 +Test: [1600/2573] eta: 0:01:15 time: 0.0790 data: 0.0013 max mem: 33369 +Test: [1700/2573] eta: 0:01:07 time: 0.0741 data: 0.0013 max mem: 33369 +Test: [1800/2573] eta: 0:00:59 time: 0.0772 data: 0.0013 max mem: 33369 +Test: [1900/2573] eta: 0:00:51 time: 0.0742 data: 0.0013 max mem: 33369 +Test: [2000/2573] eta: 0:00:44 time: 0.0755 data: 0.0013 max mem: 33369 +Test: [2100/2573] eta: 0:00:36 time: 0.0776 data: 0.0013 max mem: 33369 +Test: [2200/2573] eta: 0:00:28 time: 0.0773 data: 0.0013 max mem: 33369 +Test: [2300/2573] eta: 0:00:20 time: 0.0772 data: 0.0013 max mem: 33369 +Test: [2400/2573] eta: 0:00:13 time: 0.0725 data: 0.0013 max mem: 33369 +Test: [2500/2573] eta: 0:00:05 time: 0.0757 data: 0.0014 max mem: 33369 +Test: Total time: 0:03:17 +Final results: +Mean IoU is 62.17 + + precision@0.5 = 70.16 + precision@0.6 = 64.34 + precision@0.7 = 55.96 + precision@0.8 = 44.77 + precision@0.9 = 21.34 + overall IoU = 60.42 + +Average object IoU 62.16573539575469 +Overall IoU 60.41587448120117 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [17] [ 0/1319] eta: 3:32:17 lr: 3.0384925807273e-05 loss: 0.0808 (0.0808) time: 9.6567 data: 1.3801 max mem: 33369 +Epoch: [17] [ 10/1319] eta: 1:20:12 lr: 3.0375911143504937e-05 loss: 0.0613 (0.0609) time: 3.6765 data: 0.1324 max mem: 33369 +Epoch: [17] [ 20/1319] eta: 1:13:25 lr: 3.0366896182473385e-05 loss: 0.0580 (0.0673) time: 3.0781 data: 0.0072 max mem: 33369 +Epoch: [17] [ 30/1319] eta: 1:10:25 lr: 3.035788092407048e-05 loss: 0.0570 (0.0621) time: 3.0585 data: 0.0072 max mem: 33369 +Epoch: [17] [ 40/1319] eta: 1:08:40 lr: 3.034886536818829e-05 loss: 0.0527 (0.0606) time: 3.0432 data: 0.0077 max mem: 33369 +Epoch: [17] [ 50/1319] eta: 1:07:31 lr: 3.0339849514718806e-05 loss: 0.0527 (0.0595) time: 3.0614 data: 0.0077 max mem: 33369 +Epoch: [17] [ 60/1319] eta: 1:06:32 lr: 3.033083336355392e-05 loss: 0.0479 (0.0575) time: 3.0677 data: 0.0076 max mem: 33369 +Epoch: [17] [ 70/1319] eta: 1:05:34 lr: 3.03218169145855e-05 loss: 0.0451 (0.0571) time: 3.0411 data: 0.0075 max mem: 33369 +Epoch: [17] [ 80/1319] eta: 1:04:46 lr: 3.0312800167705292e-05 loss: 0.0482 (0.0567) time: 3.0314 data: 0.0077 max mem: 33369 +Epoch: [17] [ 90/1319] eta: 1:04:00 lr: 3.030378312280498e-05 loss: 0.0467 (0.0561) time: 3.0369 data: 0.0076 max mem: 33369 +Epoch: [17] [ 100/1319] eta: 1:03:14 lr: 3.0294765779776184e-05 loss: 0.0459 (0.0561) time: 3.0144 data: 0.0076 max mem: 33369 +Epoch: [17] [ 110/1319] eta: 1:02:18 lr: 3.0285748138510444e-05 loss: 0.0499 (0.0562) time: 2.9434 data: 0.0078 max mem: 33369 +Epoch: [17] [ 120/1319] eta: 1:01:17 lr: 3.0276730198899216e-05 loss: 0.0413 (0.0558) time: 2.8370 data: 0.0078 max mem: 33369 +Epoch: [17] [ 130/1319] eta: 1:00:14 lr: 3.0267711960833896e-05 loss: 0.0472 (0.0579) time: 2.7458 data: 0.0072 max mem: 33369 +Epoch: [17] [ 140/1319] eta: 0:59:14 lr: 3.0258693424205785e-05 loss: 0.0537 (0.0581) time: 2.7029 data: 0.0068 max mem: 33369 +Epoch: [17] [ 150/1319] eta: 0:58:17 lr: 3.024967458890613e-05 loss: 0.0536 (0.0577) time: 2.6808 data: 0.0069 max mem: 33369 +Epoch: [17] [ 160/1319] eta: 0:57:30 lr: 3.0240655454826085e-05 loss: 0.0512 (0.0586) time: 2.7087 data: 0.0072 max mem: 33369 +Epoch: [17] [ 170/1319] eta: 0:56:53 lr: 3.023163602185673e-05 loss: 0.0553 (0.0584) time: 2.8078 data: 0.0077 max mem: 33369 +Epoch: [17] [ 180/1319] eta: 0:56:16 lr: 3.022261628988908e-05 loss: 0.0466 (0.0582) time: 2.8627 data: 0.0080 max mem: 33369 +Epoch: [17] [ 190/1319] eta: 0:55:46 lr: 3.0213596258814065e-05 loss: 0.0509 (0.0585) time: 2.9115 data: 0.0080 max mem: 33369 +Epoch: [17] [ 200/1319] eta: 0:55:12 lr: 3.020457592852254e-05 loss: 0.0548 (0.0584) time: 2.9198 data: 0.0080 max mem: 33369 +Epoch: [17] [ 210/1319] eta: 0:54:39 lr: 3.0195555298905282e-05 loss: 0.0437 (0.0578) time: 2.8905 data: 0.0080 max mem: 33369 +Epoch: [17] [ 220/1319] eta: 0:54:08 lr: 3.0186534369853002e-05 loss: 0.0500 (0.0580) time: 2.9146 data: 0.0078 max mem: 33369 +Epoch: [17] [ 230/1319] eta: 0:53:37 lr: 3.0177513141256336e-05 loss: 0.0534 (0.0576) time: 2.9220 data: 0.0079 max mem: 33369 +Epoch: [17] [ 240/1319] eta: 0:53:06 lr: 3.0168491613005817e-05 loss: 0.0448 (0.0576) time: 2.9231 data: 0.0078 max mem: 33369 +Epoch: [17] [ 250/1319] eta: 0:52:35 lr: 3.0159469784991934e-05 loss: 0.0600 (0.0581) time: 2.9237 data: 0.0076 max mem: 33369 +Epoch: [17] [ 260/1319] eta: 0:52:05 lr: 3.0150447657105084e-05 loss: 0.0462 (0.0580) time: 2.9246 data: 0.0076 max mem: 33369 +Epoch: [17] [ 270/1319] eta: 0:51:33 lr: 3.0141425229235594e-05 loss: 0.0478 (0.0581) time: 2.9189 data: 0.0077 max mem: 33369 +Epoch: [17] [ 280/1319] eta: 0:51:00 lr: 3.01324025012737e-05 loss: 0.0472 (0.0576) time: 2.8755 data: 0.0076 max mem: 33369 +Epoch: [17] [ 290/1319] eta: 0:50:28 lr: 3.012337947310957e-05 loss: 0.0476 (0.0577) time: 2.8561 data: 0.0077 max mem: 33369 +Epoch: [17] [ 300/1319] eta: 0:49:56 lr: 3.0114356144633316e-05 loss: 0.0538 (0.0575) time: 2.8645 data: 0.0078 max mem: 33369 +Epoch: [17] [ 310/1319] eta: 0:49:24 lr: 3.010533251573493e-05 loss: 0.0515 (0.0575) time: 2.8618 data: 0.0077 max mem: 33369 +Epoch: [17] [ 320/1319] eta: 0:48:52 lr: 3.0096308586304355e-05 loss: 0.0518 (0.0575) time: 2.8671 data: 0.0077 max mem: 33369 +Epoch: [17] [ 330/1319] eta: 0:48:21 lr: 3.0087284356231465e-05 loss: 0.0518 (0.0573) time: 2.8735 data: 0.0078 max mem: 33369 +Epoch: [17] [ 340/1319] eta: 0:47:50 lr: 3.0078259825406035e-05 loss: 0.0452 (0.0571) time: 2.8685 data: 0.0079 max mem: 33369 +Epoch: [17] [ 350/1319] eta: 0:47:19 lr: 3.0069234993717783e-05 loss: 0.0451 (0.0571) time: 2.8684 data: 0.0081 max mem: 33369 +Epoch: [17] [ 360/1319] eta: 0:46:47 lr: 3.006020986105632e-05 loss: 0.0519 (0.0570) time: 2.8584 data: 0.0085 max mem: 33369 +Epoch: [17] [ 370/1319] eta: 0:46:15 lr: 3.005118442731122e-05 loss: 0.0604 (0.0571) time: 2.8352 data: 0.0085 max mem: 33369 +Epoch: [17] [ 380/1319] eta: 0:45:45 lr: 3.004215869237195e-05 loss: 0.0465 (0.0569) time: 2.8598 data: 0.0084 max mem: 33369 +Epoch: [17] [ 390/1319] eta: 0:45:14 lr: 3.0033132656127906e-05 loss: 0.0445 (0.0568) time: 2.8671 data: 0.0083 max mem: 33369 +Epoch: [17] [ 400/1319] eta: 0:44:44 lr: 3.002410631846841e-05 loss: 0.0507 (0.0567) time: 2.8665 data: 0.0083 max mem: 33369 +Epoch: [17] [ 410/1319] eta: 0:44:14 lr: 3.0015079679282703e-05 loss: 0.0522 (0.0569) time: 2.8780 data: 0.0082 max mem: 33369 +Epoch: [17] [ 420/1319] eta: 0:43:42 lr: 3.0006052738459948e-05 loss: 0.0594 (0.0568) time: 2.8392 data: 0.0084 max mem: 33369 +Epoch: [17] [ 430/1319] eta: 0:43:11 lr: 2.999702549588924e-05 loss: 0.0481 (0.0568) time: 2.8235 data: 0.0084 max mem: 33369 +Epoch: [17] [ 440/1319] eta: 0:42:42 lr: 2.998799795145959e-05 loss: 0.0465 (0.0565) time: 2.8588 data: 0.0085 max mem: 33369 +Epoch: [17] [ 450/1319] eta: 0:42:12 lr: 2.9978970105059916e-05 loss: 0.0419 (0.0563) time: 2.8848 data: 0.0086 max mem: 33369 +Epoch: [17] [ 460/1319] eta: 0:41:41 lr: 2.9969941956579083e-05 loss: 0.0431 (0.0562) time: 2.8525 data: 0.0087 max mem: 33369 +Epoch: [17] [ 470/1319] eta: 0:41:10 lr: 2.9960913505905863e-05 loss: 0.0555 (0.0563) time: 2.8233 data: 0.0087 max mem: 33369 +Epoch: [17] [ 480/1319] eta: 0:40:40 lr: 2.995188475292896e-05 loss: 0.0595 (0.0563) time: 2.8272 data: 0.0086 max mem: 33369 +Epoch: [17] [ 490/1319] eta: 0:40:10 lr: 2.9942855697536976e-05 loss: 0.0514 (0.0562) time: 2.8357 data: 0.0083 max mem: 33369 +Epoch: [17] [ 500/1319] eta: 0:39:38 lr: 2.9933826339618466e-05 loss: 0.0582 (0.0563) time: 2.8066 data: 0.0081 max mem: 33369 +Epoch: [17] [ 510/1319] eta: 0:39:06 lr: 2.992479667906189e-05 loss: 0.0587 (0.0565) time: 2.7218 data: 0.0084 max mem: 33369 +Epoch: [17] [ 520/1319] eta: 0:38:34 lr: 2.9915766715755623e-05 loss: 0.0592 (0.0566) time: 2.7009 data: 0.0076 max mem: 33369 +Epoch: [17] [ 530/1319] eta: 0:38:01 lr: 2.990673644958798e-05 loss: 0.0528 (0.0567) time: 2.6929 data: 0.0068 max mem: 33369 +Epoch: [17] [ 540/1319] eta: 0:37:29 lr: 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eta: 0:33:37 lr: 2.9825450406848343e-05 loss: 0.0509 (0.0570) time: 2.8932 data: 0.0075 max mem: 33369 +Epoch: [17] [ 630/1319] eta: 0:33:08 lr: 2.981641710590631e-05 loss: 0.0502 (0.0570) time: 2.9051 data: 0.0075 max mem: 33369 +Epoch: [17] [ 640/1319] eta: 0:32:40 lr: 2.9807383500869036e-05 loss: 0.0545 (0.0571) time: 2.9117 data: 0.0074 max mem: 33369 +Epoch: [17] [ 650/1319] eta: 0:32:11 lr: 2.9798349591623877e-05 loss: 0.0622 (0.0572) time: 2.9164 data: 0.0076 max mem: 33369 +Epoch: [17] [ 660/1319] eta: 0:31:43 lr: 2.9789315378058107e-05 loss: 0.0560 (0.0575) time: 2.9278 data: 0.0075 max mem: 33369 +Epoch: [17] [ 670/1319] eta: 0:31:14 lr: 2.978028086005893e-05 loss: 0.0583 (0.0576) time: 2.9195 data: 0.0074 max mem: 33369 +Epoch: [17] [ 680/1319] eta: 0:30:46 lr: 2.977124603751345e-05 loss: 0.0555 (0.0576) time: 2.9170 data: 0.0078 max mem: 33369 +Epoch: [17] [ 690/1319] eta: 0:30:16 lr: 2.9762210910308712e-05 loss: 0.0558 (0.0577) time: 2.8933 data: 0.0078 max mem: 33369 +Epoch: [17] [ 700/1319] eta: 0:29:47 lr: 2.9753175478331675e-05 loss: 0.0597 (0.0577) time: 2.8356 data: 0.0079 max mem: 33369 +Epoch: [17] [ 710/1319] eta: 0:29:17 lr: 2.97441397414692e-05 loss: 0.0523 (0.0576) time: 2.8165 data: 0.0080 max mem: 33369 +Epoch: [17] [ 720/1319] eta: 0:28:49 lr: 2.973510369960809e-05 loss: 0.0488 (0.0577) time: 2.8559 data: 0.0079 max mem: 33369 +Epoch: [17] [ 730/1319] eta: 0:28:19 lr: 2.9726067352635072e-05 loss: 0.0586 (0.0579) time: 2.8560 data: 0.0080 max mem: 33369 +Epoch: [17] [ 740/1319] eta: 0:27:50 lr: 2.971703070043676e-05 loss: 0.0512 (0.0578) time: 2.8255 data: 0.0080 max mem: 33369 +Epoch: [17] [ 750/1319] eta: 0:27:21 lr: 2.970799374289972e-05 loss: 0.0502 (0.0579) time: 2.8229 data: 0.0080 max mem: 33369 +Epoch: [17] [ 760/1319] eta: 0:26:52 lr: 2.9698956479910424e-05 loss: 0.0508 (0.0577) time: 2.8442 data: 0.0079 max mem: 33369 +Epoch: [17] [ 770/1319] eta: 0:26:23 lr: 2.9689918911355265e-05 loss: 0.0508 (0.0580) time: 2.8758 data: 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time: 2.8492 data: 0.0083 max mem: 33369 +Epoch: [17] [ 860/1319] eta: 0:22:02 lr: 2.96085670251099e-05 loss: 0.0540 (0.0582) time: 2.8295 data: 0.0083 max mem: 33369 +Epoch: [17] [ 870/1319] eta: 0:21:32 lr: 2.959952639462995e-05 loss: 0.0534 (0.0582) time: 2.8301 data: 0.0083 max mem: 33369 +Epoch: [17] [ 880/1319] eta: 0:21:03 lr: 2.9590485457329127e-05 loss: 0.0546 (0.0582) time: 2.8334 data: 0.0081 max mem: 33369 +Epoch: [17] [ 890/1319] eta: 0:20:34 lr: 2.9581444213092834e-05 loss: 0.0541 (0.0582) time: 2.8227 data: 0.0082 max mem: 33369 +Epoch: [17] [ 900/1319] eta: 0:20:05 lr: 2.957240266180642e-05 loss: 0.0541 (0.0582) time: 2.7719 data: 0.0081 max mem: 33369 +Epoch: [17] [ 910/1319] eta: 0:19:35 lr: 2.956336080335514e-05 loss: 0.0593 (0.0583) time: 2.7194 data: 0.0073 max mem: 33369 +Epoch: [17] [ 920/1319] eta: 0:19:06 lr: 2.955431863762416e-05 loss: 0.0615 (0.0584) time: 2.6644 data: 0.0069 max mem: 33369 +Epoch: [17] [ 930/1319] eta: 0:18:36 lr: 2.9545276164498587e-05 loss: 0.0543 (0.0585) time: 2.6531 data: 0.0069 max mem: 33369 +Epoch: [17] [ 940/1319] eta: 0:18:06 lr: 2.953623338386342e-05 loss: 0.0562 (0.0585) time: 2.6588 data: 0.0068 max mem: 33369 +Epoch: [17] [ 950/1319] eta: 0:17:37 lr: 2.9527190295603586e-05 loss: 0.0500 (0.0584) time: 2.6418 data: 0.0066 max mem: 33369 +Epoch: [17] [ 960/1319] eta: 0:17:07 lr: 2.9518146899603932e-05 loss: 0.0467 (0.0585) time: 2.6447 data: 0.0066 max mem: 33369 +Epoch: [17] [ 970/1319] eta: 0:16:38 lr: 2.9509103195749226e-05 loss: 0.0467 (0.0584) time: 2.6307 data: 0.0066 max mem: 33369 +Epoch: [17] [ 980/1319] eta: 0:16:09 lr: 2.9500059183924145e-05 loss: 0.0467 (0.0583) time: 2.7175 data: 0.0072 max mem: 33369 +Epoch: [17] [ 990/1319] eta: 0:15:41 lr: 2.9491014864013282e-05 loss: 0.0454 (0.0582) time: 2.8629 data: 0.0078 max mem: 33369 +Epoch: [17] [1000/1319] eta: 0:15:12 lr: 2.9481970235901164e-05 loss: 0.0520 (0.0582) time: 2.9167 data: 0.0076 max mem: 33369 +Epoch: [17] [1010/1319] eta: 0:14:44 lr: 2.9472925299472214e-05 loss: 0.0528 (0.0582) time: 2.8981 data: 0.0076 max mem: 33369 +Epoch: [17] [1020/1319] eta: 0:14:15 lr: 2.9463880054610792e-05 loss: 0.0513 (0.0582) time: 2.8835 data: 0.0076 max mem: 33369 +Epoch: [17] [1030/1319] eta: 0:13:47 lr: 2.9454834501201163e-05 loss: 0.0588 (0.0582) time: 2.9136 data: 0.0075 max mem: 33369 +Epoch: [17] [1040/1319] eta: 0:13:18 lr: 2.9445788639127496e-05 loss: 0.0475 (0.0581) time: 2.9500 data: 0.0074 max mem: 33369 +Epoch: [17] [1050/1319] eta: 0:12:50 lr: 2.943674246827392e-05 loss: 0.0479 (0.0580) time: 2.9362 data: 0.0076 max mem: 33369 +Epoch: [17] [1060/1319] eta: 0:12:21 lr: 2.9427695988524433e-05 loss: 0.0574 (0.0582) time: 2.9056 data: 0.0077 max mem: 33369 +Epoch: [17] [1070/1319] eta: 0:11:53 lr: 2.941864919976297e-05 loss: 0.0577 (0.0581) time: 2.9037 data: 0.0076 max mem: 33369 +Epoch: [17] [1080/1319] eta: 0:11:24 lr: 2.9409602101873397e-05 loss: 0.0471 (0.0583) time: 2.8890 data: 0.0079 max mem: 33369 +Epoch: [17] [1090/1319] eta: 0:10:55 lr: 2.9400554694739468e-05 loss: 0.0569 (0.0584) time: 2.8614 data: 0.0079 max mem: 33369 +Epoch: [17] [1100/1319] eta: 0:10:27 lr: 2.9391506978244877e-05 loss: 0.0564 (0.0585) time: 2.8402 data: 0.0076 max mem: 33369 +Epoch: [17] [1110/1319] eta: 0:09:58 lr: 2.9382458952273217e-05 loss: 0.0551 (0.0585) time: 2.8254 data: 0.0076 max mem: 33369 +Epoch: [17] [1120/1319] eta: 0:09:29 lr: 2.937341061670802e-05 loss: 0.0606 (0.0586) time: 2.8428 data: 0.0079 max mem: 33369 +Epoch: [17] [1130/1319] eta: 0:09:01 lr: 2.9364361971432715e-05 loss: 0.0613 (0.0586) time: 2.8490 data: 0.0081 max mem: 33369 +Epoch: [17] [1140/1319] eta: 0:08:32 lr: 2.9355313016330638e-05 loss: 0.0613 (0.0588) time: 2.8420 data: 0.0080 max mem: 33369 +Epoch: [17] [1150/1319] eta: 0:08:03 lr: 2.934626375128508e-05 loss: 0.0649 (0.0589) time: 2.8579 data: 0.0079 max mem: 33369 +Epoch: [17] [1160/1319] eta: 0:07:35 lr: 2.93372141761792e-05 loss: 0.0569 (0.0588) time: 2.8398 data: 0.0079 max mem: 33369 +Epoch: [17] [1170/1319] eta: 0:07:06 lr: 2.9328164290896108e-05 loss: 0.0458 (0.0589) time: 2.8261 data: 0.0081 max mem: 33369 +Epoch: [17] [1180/1319] eta: 0:06:37 lr: 2.9319114095318817e-05 loss: 0.0525 (0.0589) time: 2.8427 data: 0.0083 max mem: 33369 +Epoch: [17] [1190/1319] eta: 0:06:09 lr: 2.9310063589330256e-05 loss: 0.0562 (0.0589) time: 2.8374 data: 0.0081 max mem: 33369 +Epoch: [17] [1200/1319] eta: 0:05:40 lr: 2.9301012772813273e-05 loss: 0.0584 (0.0590) time: 2.8366 data: 0.0081 max mem: 33369 +Epoch: [17] [1210/1319] eta: 0:05:11 lr: 2.9291961645650624e-05 loss: 0.0571 (0.0590) time: 2.8525 data: 0.0082 max mem: 33369 +Epoch: [17] [1220/1319] eta: 0:04:43 lr: 2.9282910207724996e-05 loss: 0.0558 (0.0589) time: 2.8589 data: 0.0082 max mem: 33369 +Epoch: [17] [1230/1319] eta: 0:04:14 lr: 2.9273858458918974e-05 loss: 0.0558 (0.0590) time: 2.8459 data: 0.0083 max mem: 33369 +Epoch: [17] [1240/1319] eta: 0:03:46 lr: 2.9264806399115058e-05 loss: 0.0528 (0.0589) time: 2.8419 data: 0.0081 max mem: 33369 +Epoch: [17] [1250/1319] eta: 0:03:17 lr: 2.925575402819568e-05 loss: 0.0492 (0.0589) time: 2.8547 data: 0.0081 max mem: 33369 +Epoch: [17] [1260/1319] eta: 0:02:48 lr: 2.9246701346043183e-05 loss: 0.0492 (0.0589) time: 2.8428 data: 0.0082 max mem: 33369 +Epoch: [17] [1270/1319] eta: 0:02:20 lr: 2.9237648352539803e-05 loss: 0.0550 (0.0589) time: 2.8419 data: 0.0081 max mem: 33369 +Epoch: [17] [1280/1319] eta: 0:01:51 lr: 2.9228595047567713e-05 loss: 0.0550 (0.0589) time: 2.8442 data: 0.0081 max mem: 33369 +Epoch: [17] [1290/1319] eta: 0:01:22 lr: 2.9219541431009008e-05 loss: 0.0494 (0.0588) time: 2.8257 data: 0.0082 max mem: 33369 +Epoch: [17] [1300/1319] eta: 0:00:54 lr: 2.921048750274567e-05 loss: 0.0466 (0.0589) time: 2.8341 data: 0.0082 max mem: 33369 +Epoch: [17] [1310/1319] eta: 0:00:25 lr: 2.9201433262659623e-05 loss: 0.0512 (0.0588) time: 2.8347 data: 0.0081 max mem: 33369 +Epoch: [17] Total time: 1:02:52 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 2:16:00 time: 3.1714 data: 3.0908 max mem: 33369 +Test: [ 100/2573] eta: 0:04:14 time: 0.0717 data: 0.0012 max mem: 33369 +Test: [ 200/2573] eta: 0:03:30 time: 0.0734 data: 0.0012 max mem: 33369 +Test: [ 300/2573] eta: 0:03:09 time: 0.0754 data: 0.0011 max mem: 33369 +Test: [ 400/2573] eta: 0:02:55 time: 0.0757 data: 0.0012 max mem: 33369 +Test: [ 500/2573] eta: 0:02:44 time: 0.0736 data: 0.0011 max mem: 33369 +Test: [ 600/2573] eta: 0:02:35 time: 0.0735 data: 0.0011 max mem: 33369 +Test: [ 700/2573] eta: 0:02:26 time: 0.0736 data: 0.0011 max mem: 33369 +Test: [ 800/2573] eta: 0:02:17 time: 0.0772 data: 0.0011 max mem: 33369 +Test: [ 900/2573] eta: 0:02:09 time: 0.0739 data: 0.0012 max mem: 33369 +Test: [1000/2573] eta: 0:02:01 time: 0.0741 data: 0.0012 max mem: 33369 +Test: [1100/2573] eta: 0:01:53 time: 0.0748 data: 0.0013 max mem: 33369 +Test: [1200/2573] eta: 0:01:45 time: 0.0746 data: 0.0012 max mem: 33369 +Test: [1300/2573] eta: 0:01:37 time: 0.0741 data: 0.0011 max mem: 33369 +Test: [1400/2573] eta: 0:01:29 time: 0.0726 data: 0.0012 max mem: 33369 +Test: [1500/2573] eta: 0:01:21 time: 0.0741 data: 0.0012 max mem: 33369 +Test: [1600/2573] eta: 0:01:14 time: 0.0776 data: 0.0012 max mem: 33369 +Test: [1700/2573] eta: 0:01:06 time: 0.0726 data: 0.0011 max mem: 33369 +Test: [1800/2573] eta: 0:00:58 time: 0.0763 data: 0.0012 max mem: 33369 +Test: [1900/2573] eta: 0:00:51 time: 0.0733 data: 0.0013 max mem: 33369 +Test: [2000/2573] eta: 0:00:43 time: 0.0757 data: 0.0014 max mem: 33369 +Test: [2100/2573] eta: 0:00:35 time: 0.0771 data: 0.0013 max mem: 33369 +Test: [2200/2573] eta: 0:00:28 time: 0.0772 data: 0.0013 max mem: 33369 +Test: [2300/2573] eta: 0:00:20 time: 0.0770 data: 0.0013 max mem: 33369 +Test: [2400/2573] eta: 0:00:13 time: 0.0723 data: 0.0014 max mem: 33369 +Test: [2500/2573] eta: 0:00:05 time: 0.0754 data: 0.0014 max mem: 33369 +Test: Total time: 0:03:15 +Final results: +Mean IoU is 62.93 + + precision@0.5 = 70.55 + precision@0.6 = 64.56 + precision@0.7 = 56.90 + precision@0.8 = 45.02 + precision@0.9 = 20.89 + overall IoU = 60.58 + +Average object IoU 62.927746944144324 +Overall IoU 60.5780143737793 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [18] [ 0/1319] eta: 3:48:40 lr: 2.9193284179876086e-05 loss: 0.0504 (0.0504) time: 10.4024 data: 2.4626 max mem: 33369 +Epoch: [18] [ 10/1319] eta: 1:17:38 lr: 2.9184229347001237e-05 loss: 0.0488 (0.0477) time: 3.5586 data: 0.2304 max mem: 33369 +Epoch: [18] [ 20/1319] eta: 1:10:23 lr: 2.9175174201960736e-05 loss: 0.0453 (0.0525) time: 2.8935 data: 0.0072 max mem: 33369 +Epoch: [18] [ 30/1319] eta: 1:07:33 lr: 2.9166118744636155e-05 loss: 0.0563 (0.0566) time: 2.9168 data: 0.0075 max mem: 33369 +Epoch: [18] [ 40/1319] eta: 1:05:31 lr: 2.9157062974908988e-05 loss: 0.0607 (0.0586) time: 2.8883 data: 0.0076 max mem: 33369 +Epoch: [18] [ 50/1319] eta: 1:04:22 lr: 2.9148006892660646e-05 loss: 0.0539 (0.0570) time: 2.8882 data: 0.0075 max mem: 33369 +Epoch: [18] [ 60/1319] eta: 1:03:28 lr: 2.9138950497772444e-05 loss: 0.0498 (0.0574) time: 2.9238 data: 0.0078 max mem: 33369 +Epoch: [18] [ 70/1319] eta: 1:02:45 lr: 2.9129893790125616e-05 loss: 0.0458 (0.0562) time: 2.9411 data: 0.0079 max mem: 33369 +Epoch: [18] [ 80/1319] eta: 1:02:04 lr: 2.9120836769601318e-05 loss: 0.0458 (0.0558) time: 2.9476 data: 0.0078 max mem: 33369 +Epoch: [18] [ 90/1319] eta: 1:01:22 lr: 2.9111779436080605e-05 loss: 0.0487 (0.0564) time: 2.9285 data: 0.0078 max mem: 33369 +Epoch: [18] [ 100/1319] eta: 1:00:38 lr: 2.910272178944446e-05 loss: 0.0524 (0.0567) time: 2.8988 data: 0.0077 max mem: 33369 +Epoch: [18] [ 110/1319] eta: 0:59:57 lr: 2.9093663829573763e-05 loss: 0.0524 (0.0567) time: 2.8841 data: 0.0079 max mem: 33369 +Epoch: [18] [ 120/1319] eta: 0:59:17 lr: 2.9084605556349322e-05 loss: 0.0548 (0.0570) time: 2.8764 data: 0.0081 max mem: 33369 +Epoch: [18] [ 130/1319] eta: 0:58:40 lr: 2.9075546969651845e-05 loss: 0.0465 (0.0563) time: 2.8785 data: 0.0082 max mem: 33369 +Epoch: [18] [ 140/1319] eta: 0:58:05 lr: 2.906648806936197e-05 loss: 0.0471 (0.0566) time: 2.8928 data: 0.0082 max mem: 33369 +Epoch: [18] [ 150/1319] eta: 0:57:31 lr: 2.9057428855360237e-05 loss: 0.0536 (0.0567) time: 2.8957 data: 0.0082 max mem: 33369 +Epoch: [18] [ 160/1319] eta: 0:56:52 lr: 2.9048369327527098e-05 loss: 0.0471 (0.0568) time: 2.8614 data: 0.0081 max mem: 33369 +Epoch: [18] [ 170/1319] eta: 0:56:18 lr: 2.903930948574293e-05 loss: 0.0447 (0.0562) time: 2.8491 data: 0.0080 max mem: 33369 +Epoch: [18] [ 180/1319] eta: 0:55:45 lr: 2.9030249329888e-05 loss: 0.0462 (0.0562) time: 2.8754 data: 0.0082 max mem: 33369 +Epoch: [18] [ 190/1319] eta: 0:55:12 lr: 2.9021188859842518e-05 loss: 0.0511 (0.0557) time: 2.8831 data: 0.0082 max mem: 33369 +Epoch: [18] [ 200/1319] eta: 0:54:39 lr: 2.9012128075486583e-05 loss: 0.0473 (0.0554) time: 2.8745 data: 0.0082 max mem: 33369 +Epoch: [18] [ 210/1319] eta: 0:54:06 lr: 2.900306697670022e-05 loss: 0.0494 (0.0560) time: 2.8645 data: 0.0083 max mem: 33369 +Epoch: [18] [ 220/1319] eta: 0:53:32 lr: 2.8994005563363352e-05 loss: 0.0537 (0.0562) time: 2.8508 data: 0.0084 max mem: 33369 +Epoch: [18] [ 230/1319] eta: 0:53:00 lr: 2.8984943835355838e-05 loss: 0.0564 (0.0562) time: 2.8405 data: 0.0085 max mem: 33369 +Epoch: [18] [ 240/1319] eta: 0:52:27 lr: 2.8975881792557412e-05 loss: 0.0468 (0.0563) time: 2.8422 data: 0.0085 max mem: 33369 +Epoch: [18] [ 250/1319] eta: 0:51:54 lr: 2.8966819434847762e-05 loss: 0.0516 (0.0565) time: 2.8319 data: 0.0085 max mem: 33369 +Epoch: [18] [ 260/1319] eta: 0:51:21 lr: 2.8957756762106468e-05 loss: 0.0516 (0.0563) time: 2.8309 data: 0.0086 max mem: 33369 +Epoch: [18] [ 270/1319] eta: 0:50:51 lr: 2.8948693774213014e-05 loss: 0.0480 (0.0561) time: 2.8582 data: 0.0085 max mem: 33369 +Epoch: [18] [ 280/1319] eta: 0:50:19 lr: 2.8939630471046815e-05 loss: 0.0504 (0.0560) time: 2.8594 data: 0.0086 max mem: 33369 +Epoch: [18] [ 290/1319] eta: 0:49:47 lr: 2.893056685248718e-05 loss: 0.0479 (0.0558) time: 2.8281 data: 0.0085 max mem: 33369 +Epoch: [18] [ 300/1319] eta: 0:49:17 lr: 2.892150291841334e-05 loss: 0.0465 (0.0557) time: 2.8506 data: 0.0085 max mem: 33369 +Epoch: [18] [ 310/1319] eta: 0:48:47 lr: 2.891243866870445e-05 loss: 0.0501 (0.0558) time: 2.8672 data: 0.0084 max mem: 33369 +Epoch: [18] [ 320/1319] eta: 0:48:13 lr: 2.8903374103239537e-05 loss: 0.0494 (0.0557) time: 2.8052 data: 0.0083 max mem: 33369 +Epoch: [18] [ 330/1319] eta: 0:47:37 lr: 2.889430922189758e-05 loss: 0.0461 (0.0554) time: 2.7035 data: 0.0084 max mem: 33369 +Epoch: [18] [ 340/1319] eta: 0:47:02 lr: 2.8885244024557463e-05 loss: 0.0461 (0.0552) time: 2.6682 data: 0.0080 max mem: 33369 +Epoch: [18] [ 350/1319] eta: 0:46:27 lr: 2.8876178511097952e-05 loss: 0.0480 (0.0558) time: 2.6694 data: 0.0072 max mem: 33369 +Epoch: [18] [ 360/1319] eta: 0:45:52 lr: 2.886711268139775e-05 loss: 0.0480 (0.0556) time: 2.6506 data: 0.0069 max mem: 33369 +Epoch: [18] [ 370/1319] eta: 0:45:17 lr: 2.8858046535335475e-05 loss: 0.0490 (0.0554) time: 2.6290 data: 0.0069 max mem: 33369 +Epoch: [18] [ 380/1319] eta: 0:44:50 lr: 2.8848980072789644e-05 loss: 0.0536 (0.0552) time: 2.7693 data: 0.0075 max mem: 33369 +Epoch: [18] [ 390/1319] eta: 0:44:21 lr: 2.8839913293638683e-05 loss: 0.0447 (0.0558) time: 2.8930 data: 0.0081 max mem: 33369 +Epoch: [18] [ 400/1319] eta: 0:43:53 lr: 2.8830846197760937e-05 loss: 0.0600 (0.0559) time: 2.8686 data: 0.0081 max mem: 33369 +Epoch: [18] [ 410/1319] eta: 0:43:24 lr: 2.8821778785034654e-05 loss: 0.0561 (0.0559) time: 2.8835 data: 0.0078 max mem: 33369 +Epoch: [18] [ 420/1319] eta: 0:42:57 lr: 2.8812711055338004e-05 loss: 0.0530 (0.0559) time: 2.9106 data: 0.0078 max mem: 33369 +Epoch: [18] [ 430/1319] eta: 0:42:28 lr: 2.8803643008549054e-05 loss: 0.0495 (0.0559) time: 2.8945 data: 0.0079 max mem: 33369 +Epoch: [18] [ 440/1319] eta: 0:42:01 lr: 2.879457464454579e-05 loss: 0.0495 (0.0558) time: 2.8960 data: 0.0079 max mem: 33369 +Epoch: [18] [ 450/1319] eta: 0:41:33 lr: 2.8785505963206112e-05 loss: 0.0448 (0.0556) time: 2.9202 data: 0.0079 max mem: 33369 +Epoch: [18] [ 460/1319] eta: 0:41:05 lr: 2.877643696440781e-05 loss: 0.0468 (0.0557) time: 2.9140 data: 0.0078 max mem: 33369 +Epoch: [18] [ 470/1319] eta: 0:40:38 lr: 2.876736764802861e-05 loss: 0.0517 (0.0556) time: 2.9361 data: 0.0077 max mem: 33369 +Epoch: [18] [ 480/1319] eta: 0:40:09 lr: 2.8758298013946133e-05 loss: 0.0509 (0.0555) time: 2.9030 data: 0.0079 max mem: 33369 +Epoch: [18] [ 490/1319] eta: 0:39:40 lr: 2.8749228062037915e-05 loss: 0.0582 (0.0557) time: 2.8636 data: 0.0079 max mem: 33369 +Epoch: [18] [ 500/1319] eta: 0:39:11 lr: 2.87401577921814e-05 loss: 0.0593 (0.0557) time: 2.8537 data: 0.0078 max mem: 33369 +Epoch: [18] [ 510/1319] eta: 0:38:43 lr: 2.8731087204253943e-05 loss: 0.0492 (0.0555) time: 2.8646 data: 0.0078 max mem: 33369 +Epoch: [18] [ 520/1319] eta: 0:38:14 lr: 2.8722016298132803e-05 loss: 0.0492 (0.0556) time: 2.8942 data: 0.0078 max mem: 33369 +Epoch: [18] [ 530/1319] eta: 0:37:46 lr: 2.8712945073695164e-05 loss: 0.0512 (0.0556) time: 2.8877 data: 0.0076 max mem: 33369 +Epoch: [18] [ 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data: 0.0082 max mem: 33369 +Epoch: [18] [ 700/1319] eta: 0:29:41 lr: 2.8558685436370514e-05 loss: 0.0438 (0.0562) time: 2.9079 data: 0.0083 max mem: 33369 +Epoch: [18] [ 710/1319] eta: 0:29:12 lr: 2.854960846112869e-05 loss: 0.0450 (0.0562) time: 2.9096 data: 0.0082 max mem: 33369 +Epoch: [18] [ 720/1319] eta: 0:28:42 lr: 2.8540531165219343e-05 loss: 0.0457 (0.0561) time: 2.8078 data: 0.0077 max mem: 33369 +Epoch: [18] [ 730/1319] eta: 0:28:12 lr: 2.8531453548517806e-05 loss: 0.0468 (0.0561) time: 2.7146 data: 0.0074 max mem: 33369 +Epoch: [18] [ 740/1319] eta: 0:27:42 lr: 2.8522375610899337e-05 loss: 0.0468 (0.0561) time: 2.6906 data: 0.0071 max mem: 33369 +Epoch: [18] [ 750/1319] eta: 0:27:11 lr: 2.8513297352239087e-05 loss: 0.0506 (0.0561) time: 2.6641 data: 0.0067 max mem: 33369 +Epoch: [18] [ 760/1319] eta: 0:26:41 lr: 2.850421877241213e-05 loss: 0.0506 (0.0563) time: 2.6490 data: 0.0067 max mem: 33369 +Epoch: [18] [ 770/1319] eta: 0:26:11 lr: 2.8495139871293436e-05 loss: 0.0498 (0.0563) time: 2.6433 data: 0.0068 max mem: 33369 +Epoch: [18] [ 780/1319] eta: 0:25:41 lr: 2.8486060648757875e-05 loss: 0.0481 (0.0563) time: 2.6557 data: 0.0068 max mem: 33369 +Epoch: [18] [ 790/1319] eta: 0:25:12 lr: 2.8476981104680245e-05 loss: 0.0481 (0.0562) time: 2.7148 data: 0.0068 max mem: 33369 +Epoch: [18] [ 800/1319] eta: 0:24:43 lr: 2.846790123893523e-05 loss: 0.0460 (0.0562) time: 2.8057 data: 0.0073 max mem: 33369 +Epoch: [18] [ 810/1319] eta: 0:24:14 lr: 2.8458821051397444e-05 loss: 0.0547 (0.0562) time: 2.8596 data: 0.0077 max mem: 33369 +Epoch: [18] [ 820/1319] eta: 0:23:46 lr: 2.844974054194138e-05 loss: 0.0597 (0.0563) time: 2.9187 data: 0.0078 max mem: 33369 +Epoch: [18] [ 830/1319] eta: 0:23:18 lr: 2.844065971044146e-05 loss: 0.0589 (0.0563) time: 2.9134 data: 0.0079 max mem: 33369 +Epoch: [18] [ 840/1319] eta: 0:22:50 lr: 2.8431578556772e-05 loss: 0.0589 (0.0564) time: 2.8898 data: 0.0078 max mem: 33369 +Epoch: [18] [ 850/1319] eta: 0:22:21 lr: 2.8422497080807237e-05 loss: 0.0519 (0.0564) time: 2.8926 data: 0.0079 max mem: 33369 +Epoch: [18] [ 860/1319] eta: 0:21:53 lr: 2.8413415282421285e-05 loss: 0.0499 (0.0563) time: 2.8880 data: 0.0078 max mem: 33369 +Epoch: [18] [ 870/1319] eta: 0:21:25 lr: 2.840433316148819e-05 loss: 0.0499 (0.0563) time: 2.9368 data: 0.0079 max mem: 33369 +Epoch: [18] [ 880/1319] eta: 0:20:56 lr: 2.8395250717881906e-05 loss: 0.0499 (0.0563) time: 2.9640 data: 0.0078 max mem: 33369 +Epoch: [18] [ 890/1319] eta: 0:20:28 lr: 2.8386167951476273e-05 loss: 0.0504 (0.0563) time: 2.9387 data: 0.0076 max mem: 33369 +Epoch: [18] [ 900/1319] eta: 0:20:00 lr: 2.8377084862145048e-05 loss: 0.0488 (0.0562) time: 2.9366 data: 0.0076 max mem: 33369 +Epoch: [18] [ 910/1319] eta: 0:19:31 lr: 2.8368001449761894e-05 loss: 0.0489 (0.0562) time: 2.9074 data: 0.0079 max mem: 33369 +Epoch: [18] [ 920/1319] eta: 0:19:03 lr: 2.8358917714200377e-05 loss: 0.0519 (0.0561) time: 2.8809 data: 0.0080 max mem: 33369 +Epoch: [18] [ 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33369 +Epoch: [18] [1010/1319] eta: 0:14:46 lr: 2.8277149530212353e-05 loss: 0.0500 (0.0566) time: 2.8922 data: 0.0081 max mem: 33369 +Epoch: [18] [1020/1319] eta: 0:14:17 lr: 2.8268062555892616e-05 loss: 0.0500 (0.0566) time: 2.8884 data: 0.0080 max mem: 33369 +Epoch: [18] [1030/1319] eta: 0:13:48 lr: 2.82589752569975e-05 loss: 0.0433 (0.0565) time: 2.8980 data: 0.0080 max mem: 33369 +Epoch: [18] [1040/1319] eta: 0:13:20 lr: 2.8249887633399437e-05 loss: 0.0441 (0.0565) time: 2.9162 data: 0.0081 max mem: 33369 +Epoch: [18] [1050/1319] eta: 0:12:51 lr: 2.8240799684970753e-05 loss: 0.0441 (0.0564) time: 2.9039 data: 0.0080 max mem: 33369 +Epoch: [18] [1060/1319] eta: 0:12:23 lr: 2.8231711411583693e-05 loss: 0.0440 (0.0564) time: 2.8906 data: 0.0082 max mem: 33369 +Epoch: [18] [1070/1319] eta: 0:11:54 lr: 2.8222622813110382e-05 loss: 0.0511 (0.0564) time: 2.8773 data: 0.0084 max mem: 33369 +Epoch: [18] [1080/1319] eta: 0:11:25 lr: 2.821353388942287e-05 loss: 0.0511 (0.0564) time: 2.8858 data: 0.0083 max mem: 33369 +Epoch: [18] [1090/1319] eta: 0:10:57 lr: 2.820444464039311e-05 loss: 0.0492 (0.0564) time: 2.9085 data: 0.0083 max mem: 33369 +Epoch: [18] [1100/1319] eta: 0:10:28 lr: 2.819535506589294e-05 loss: 0.0495 (0.0564) time: 2.8763 data: 0.0082 max mem: 33369 +Epoch: [18] [1110/1319] eta: 0:09:59 lr: 2.8186265165794125e-05 loss: 0.0513 (0.0564) time: 2.8832 data: 0.0081 max mem: 33369 +Epoch: [18] [1120/1319] eta: 0:09:31 lr: 2.817717493996831e-05 loss: 0.0540 (0.0565) time: 2.9232 data: 0.0080 max mem: 33369 +Epoch: [18] [1130/1319] eta: 0:09:02 lr: 2.816808438828707e-05 loss: 0.0576 (0.0566) time: 2.8132 data: 0.0079 max mem: 33369 +Epoch: [18] [1140/1319] eta: 0:08:33 lr: 2.8158993510621856e-05 loss: 0.0414 (0.0565) time: 2.6885 data: 0.0079 max mem: 33369 +Epoch: [18] [1150/1319] eta: 0:08:04 lr: 2.814990230684405e-05 loss: 0.0414 (0.0564) time: 2.6769 data: 0.0073 max mem: 33369 +Epoch: [18] [1160/1319] eta: 0:07:35 lr: 2.814081077682491e-05 loss: 0.0497 (0.0565) time: 2.6748 data: 0.0068 max mem: 33369 +Epoch: [18] [1170/1319] eta: 0:07:06 lr: 2.8131718920435623e-05 loss: 0.0523 (0.0565) time: 2.6459 data: 0.0069 max mem: 33369 +Epoch: [18] [1180/1319] eta: 0:06:37 lr: 2.812262673754726e-05 loss: 0.0597 (0.0566) time: 2.7121 data: 0.0072 max mem: 33369 +Epoch: [18] [1190/1319] eta: 0:06:09 lr: 2.8113534228030784e-05 loss: 0.0562 (0.0566) time: 2.8279 data: 0.0077 max mem: 33369 +Epoch: [18] [1200/1319] eta: 0:05:40 lr: 2.8104441391757102e-05 loss: 0.0482 (0.0565) time: 2.8875 data: 0.0079 max mem: 33369 +Epoch: [18] [1210/1319] eta: 0:05:11 lr: 2.809534822859698e-05 loss: 0.0543 (0.0567) time: 2.9037 data: 0.0078 max mem: 33369 +Epoch: [18] [1220/1319] eta: 0:04:43 lr: 2.8086254738421114e-05 loss: 0.0546 (0.0566) time: 2.9082 data: 0.0079 max mem: 33369 +Epoch: [18] [1230/1319] eta: 0:04:14 lr: 2.8077160921100087e-05 loss: 0.0480 (0.0566) time: 2.8915 data: 0.0078 max mem: 33369 +Epoch: [18] [1240/1319] eta: 0:03:46 lr: 2.8068066776504393e-05 loss: 0.0464 (0.0566) time: 2.8880 data: 0.0077 max mem: 33369 +Epoch: [18] [1250/1319] eta: 0:03:17 lr: 2.8058972304504428e-05 loss: 0.0580 (0.0566) time: 2.9239 data: 0.0076 max mem: 33369 +Epoch: [18] [1260/1319] eta: 0:02:48 lr: 2.8049877504970483e-05 loss: 0.0500 (0.0566) time: 2.9157 data: 0.0077 max mem: 33369 +Epoch: [18] [1270/1319] eta: 0:02:20 lr: 2.8040782377772763e-05 loss: 0.0493 (0.0565) time: 2.9040 data: 0.0080 max mem: 33369 +Epoch: [18] [1280/1319] eta: 0:01:51 lr: 2.803168692278136e-05 loss: 0.0505 (0.0565) time: 2.9125 data: 0.0078 max mem: 33369 +Epoch: [18] [1290/1319] eta: 0:01:23 lr: 2.8022591139866265e-05 loss: 0.0505 (0.0565) time: 2.9165 data: 0.0079 max mem: 33369 +Epoch: [18] [1300/1319] eta: 0:00:54 lr: 2.80134950288974e-05 loss: 0.0461 (0.0565) time: 2.9102 data: 0.0080 max mem: 33369 +Epoch: [18] [1310/1319] eta: 0:00:25 lr: 2.800439858974456e-05 loss: 0.0520 (0.0566) time: 2.9070 data: 0.0076 max mem: 33369 +Epoch: [18] Total time: 1:03:00 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 2:14:06 time: 3.1274 data: 3.0279 max mem: 33369 +Test: [ 100/2573] eta: 0:04:16 time: 0.0729 data: 0.0013 max mem: 33369 +Test: [ 200/2573] eta: 0:03:33 time: 0.0749 data: 0.0013 max mem: 33369 +Test: [ 300/2573] eta: 0:03:12 time: 0.0767 data: 0.0013 max mem: 33369 +Test: [ 400/2573] eta: 0:02:58 time: 0.0766 data: 0.0012 max mem: 33369 +Test: [ 500/2573] eta: 0:02:47 time: 0.0751 data: 0.0014 max mem: 33369 +Test: [ 600/2573] eta: 0:02:37 time: 0.0754 data: 0.0013 max mem: 33369 +Test: [ 700/2573] eta: 0:02:29 time: 0.0754 data: 0.0014 max mem: 33369 +Test: [ 800/2573] eta: 0:02:20 time: 0.0787 data: 0.0014 max mem: 33369 +Test: [ 900/2573] eta: 0:02:11 time: 0.0753 data: 0.0013 max mem: 33369 +Test: [1000/2573] eta: 0:02:03 time: 0.0752 data: 0.0013 max mem: 33369 +Test: [1100/2573] eta: 0:01:55 time: 0.0755 data: 0.0013 max mem: 33369 +Test: [1200/2573] eta: 0:01:47 time: 0.0755 data: 0.0013 max mem: 33369 +Test: [1300/2573] eta: 0:01:39 time: 0.0757 data: 0.0013 max mem: 33369 +Test: [1400/2573] eta: 0:01:31 time: 0.0737 data: 0.0013 max mem: 33369 +Test: [1500/2573] eta: 0:01:23 time: 0.0754 data: 0.0013 max mem: 33369 +Test: [1600/2573] eta: 0:01:15 time: 0.0787 data: 0.0013 max mem: 33369 +Test: [1700/2573] eta: 0:01:07 time: 0.0740 data: 0.0013 max mem: 33369 +Test: [1800/2573] eta: 0:00:59 time: 0.0772 data: 0.0013 max mem: 33369 +Test: [1900/2573] eta: 0:00:51 time: 0.0737 data: 0.0013 max mem: 33369 +Test: [2000/2573] eta: 0:00:44 time: 0.0755 data: 0.0014 max mem: 33369 +Test: [2100/2573] eta: 0:00:36 time: 0.0772 data: 0.0013 max mem: 33369 +Test: [2200/2573] eta: 0:00:28 time: 0.0772 data: 0.0013 max mem: 33369 +Test: [2300/2573] eta: 0:00:20 time: 0.0773 data: 0.0014 max mem: 33369 +Test: [2400/2573] eta: 0:00:13 time: 0.0721 data: 0.0014 max mem: 33369 +Test: [2500/2573] eta: 0:00:05 time: 0.0758 data: 0.0014 max mem: 33369 +Test: Total time: 0:03:17 +Final results: +Mean IoU is 63.01 + + precision@0.5 = 70.83 + precision@0.6 = 64.89 + precision@0.7 = 57.29 + precision@0.8 = 45.38 + precision@0.9 = 21.69 + overall IoU = 61.01 + +Average object IoU 63.008369429765445 +Overall IoU 61.00839614868164 +Better epoch: 18 + +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [19] [ 0/1319] eta: 1:54:33 lr: 2.7996211513802005e-05 loss: 0.0350 (0.0350) time: 5.2112 data: 2.0221 max mem: 33369 +Epoch: [19] [ 10/1319] eta: 1:11:22 lr: 2.7987114450740563e-05 loss: 0.0629 (0.0672) time: 3.2714 data: 0.1894 max mem: 33369 +Epoch: [19] [ 20/1319] eta: 1:09:12 lr: 2.7978017059117013e-05 loss: 0.0590 (0.0585) time: 3.0959 data: 0.0064 max mem: 33369 +Epoch: [19] [ 30/1319] eta: 1:07:22 lr: 2.7968919338800786e-05 loss: 0.0451 (0.0590) time: 3.0620 data: 0.0073 max mem: 33369 +Epoch: [19] [ 40/1319] eta: 1:06:20 lr: 2.7959821289661182e-05 loss: 0.0554 (0.0593) time: 3.0235 data: 0.0078 max mem: 33369 +Epoch: [19] [ 50/1319] eta: 1:05:27 lr: 2.795072291156743e-05 loss: 0.0536 (0.0590) time: 3.0300 data: 0.0075 max mem: 33369 +Epoch: [19] [ 60/1319] eta: 1:04:41 lr: 2.7941624204388656e-05 loss: 0.0537 (0.0591) time: 3.0230 data: 0.0074 max mem: 33369 +Epoch: [19] [ 70/1319] eta: 1:03:53 lr: 2.7932525167993873e-05 loss: 0.0520 (0.0568) time: 3.0048 data: 0.0076 max mem: 33369 +Epoch: [19] [ 80/1319] eta: 1:03:04 lr: 2.7923425802252002e-05 loss: 0.0434 (0.0566) time: 2.9676 data: 0.0078 max mem: 33369 +Epoch: [19] [ 90/1319] eta: 1:02:14 lr: 2.791432610703186e-05 loss: 0.0461 (0.0559) time: 2.9316 data: 0.0078 max mem: 33369 +Epoch: [19] [ 100/1319] eta: 1:01:39 lr: 2.790522608220219e-05 loss: 0.0417 (0.0548) time: 2.9543 data: 0.0078 max mem: 33369 +Epoch: [19] [ 110/1319] eta: 1:01:01 lr: 2.789612572763159e-05 loss: 0.0453 (0.0552) time: 2.9820 data: 0.0078 max mem: 33369 +Epoch: [19] [ 120/1319] eta: 1:00:14 lr: 2.7887025043188598e-05 loss: 0.0455 (0.0551) time: 2.9121 data: 0.0075 max mem: 33369 +Epoch: [19] [ 130/1319] eta: 0:59:13 lr: 2.7877924028741625e-05 loss: 0.0442 (0.0547) time: 2.7637 data: 0.0076 max mem: 33369 +Epoch: [19] [ 140/1319] eta: 0:58:13 lr: 2.7868822684159008e-05 loss: 0.0457 (0.0543) time: 2.6537 data: 0.0072 max mem: 33369 +Epoch: [19] [ 150/1319] eta: 0:57:21 lr: 2.7859721009308947e-05 loss: 0.0419 (0.0541) time: 2.6531 data: 0.0070 max mem: 33369 +Epoch: [19] [ 160/1319] eta: 0:56:30 lr: 2.7850619004059574e-05 loss: 0.0447 (0.0544) time: 2.6604 data: 0.0070 max mem: 33369 +Epoch: [19] [ 170/1319] eta: 0:55:57 lr: 2.7841516668278917e-05 loss: 0.0447 (0.0546) time: 2.7562 data: 0.0072 max mem: 33369 +Epoch: [19] [ 180/1319] eta: 0:55:25 lr: 2.7832414001834883e-05 loss: 0.0472 (0.0546) time: 2.8759 data: 0.0077 max mem: 33369 +Epoch: [19] [ 190/1319] eta: 0:54:56 lr: 2.782331100459529e-05 loss: 0.0481 (0.0544) time: 2.9037 data: 0.0079 max mem: 33369 +Epoch: [19] [ 200/1319] eta: 0:54:27 lr: 2.781420767642787e-05 loss: 0.0395 (0.0537) time: 2.9176 data: 0.0079 max mem: 33369 +Epoch: [19] [ 210/1319] eta: 0:53:56 lr: 2.7805104017200224e-05 loss: 0.0403 (0.0536) time: 2.9040 data: 0.0079 max mem: 33369 +Epoch: [19] [ 220/1319] eta: 0:53:27 lr: 2.779600002677987e-05 loss: 0.0453 (0.0535) time: 2.9083 data: 0.0078 max mem: 33369 +Epoch: [19] [ 230/1319] eta: 0:52:59 lr: 2.778689570503424e-05 loss: 0.0495 (0.0535) time: 2.9332 data: 0.0076 max mem: 33369 +Epoch: [19] [ 240/1319] eta: 0:52:32 lr: 2.7777791051830626e-05 loss: 0.0500 (0.0534) time: 2.9572 data: 0.0076 max mem: 33369 +Epoch: [19] [ 250/1319] eta: 0:52:04 lr: 2.7768686067036253e-05 loss: 0.0426 (0.0529) time: 2.9550 data: 0.0076 max mem: 33369 +Epoch: [19] [ 260/1319] eta: 0:51:36 lr: 2.775958075051822e-05 loss: 0.0429 (0.0527) time: 2.9525 data: 0.0078 max mem: 33369 +Epoch: [19] [ 270/1319] eta: 0:51:09 lr: 2.7750475102143547e-05 loss: 0.0429 (0.0525) time: 2.9740 data: 0.0078 max mem: 33369 +Epoch: [19] [ 280/1319] eta: 0:50:40 lr: 2.7741369121779126e-05 loss: 0.0445 (0.0526) time: 2.9509 data: 0.0077 max mem: 33369 +Epoch: [19] [ 290/1319] eta: 0:50:11 lr: 2.7732262809291776e-05 loss: 0.0484 (0.0526) time: 2.9262 data: 0.0078 max mem: 33369 +Epoch: [19] [ 300/1319] eta: 0:49:40 lr: 2.7723156164548194e-05 loss: 0.0483 (0.0528) time: 2.9138 data: 0.0078 max mem: 33369 +Epoch: [19] [ 310/1319] eta: 0:49:09 lr: 2.771404918741497e-05 loss: 0.0442 (0.0526) time: 2.8788 data: 0.0078 max mem: 33369 +Epoch: [19] [ 320/1319] eta: 0:48:38 lr: 2.7704941877758615e-05 loss: 0.0456 (0.0526) time: 2.8681 data: 0.0079 max mem: 33369 +Epoch: [19] [ 330/1319] eta: 0:48:09 lr: 2.7695834235445526e-05 loss: 0.0401 (0.0523) time: 2.8893 data: 0.0079 max mem: 33369 +Epoch: [19] [ 340/1319] eta: 0:47:39 lr: 2.7686726260341988e-05 loss: 0.0406 (0.0522) time: 2.8997 data: 0.0080 max mem: 33369 +Epoch: [19] [ 350/1319] eta: 0:47:09 lr: 2.7677617952314193e-05 loss: 0.0459 (0.0520) time: 2.8985 data: 0.0079 max mem: 33369 +Epoch: [19] [ 360/1319] eta: 0:46:38 lr: 2.7668509311228242e-05 loss: 0.0489 (0.0523) time: 2.8796 data: 0.0079 max mem: 33369 +Epoch: [19] [ 370/1319] eta: 0:46:07 lr: 2.7659400336950098e-05 loss: 0.0522 (0.0524) time: 2.8507 data: 0.0081 max mem: 33369 +Epoch: [19] [ 380/1319] eta: 0:45:37 lr: 2.765029102934566e-05 loss: 0.0542 (0.0525) time: 2.8631 data: 0.0082 max mem: 33369 +Epoch: [19] [ 390/1319] eta: 0:45:07 lr: 2.764118138828069e-05 loss: 0.0517 (0.0537) time: 2.8857 data: 0.0082 max mem: 33369 +Epoch: [19] [ 400/1319] eta: 0:44:38 lr: 2.763207141362088e-05 loss: 0.0517 (0.0538) time: 2.8915 data: 0.0082 max mem: 33369 +Epoch: [19] [ 410/1319] eta: 0:44:08 lr: 2.7622961105231792e-05 loss: 0.0494 (0.0537) time: 2.8856 data: 0.0082 max mem: 33369 +Epoch: [19] [ 420/1319] eta: 0:43:39 lr: 2.7613850462978895e-05 loss: 0.0445 (0.0538) time: 2.9137 data: 0.0080 max mem: 33369 +Epoch: [19] [ 430/1319] eta: 0:43:10 lr: 2.7604739486727564e-05 loss: 0.0481 (0.0540) time: 2.9201 data: 0.0081 max mem: 33369 +Epoch: [19] [ 440/1319] eta: 0:42:41 lr: 2.759562817634305e-05 loss: 0.0571 (0.0542) time: 2.9020 data: 0.0081 max mem: 33369 +Epoch: [19] [ 450/1319] eta: 0:42:11 lr: 2.7586516531690514e-05 loss: 0.0538 (0.0541) time: 2.8935 data: 0.0082 max mem: 33369 +Epoch: [19] [ 460/1319] eta: 0:41:42 lr: 2.7577404552635017e-05 loss: 0.0538 (0.0543) time: 2.8930 data: 0.0082 max mem: 33369 +Epoch: [19] [ 470/1319] eta: 0:41:12 lr: 2.7568292239041493e-05 loss: 0.0467 (0.0541) time: 2.9098 data: 0.0079 max mem: 33369 +Epoch: [19] [ 480/1319] eta: 0:40:42 lr: 2.7559179590774802e-05 loss: 0.0438 (0.0542) time: 2.8885 data: 0.0082 max mem: 33369 +Epoch: [19] [ 490/1319] eta: 0:40:12 lr: 2.755006660769968e-05 loss: 0.0592 (0.0545) time: 2.8641 data: 0.0083 max mem: 33369 +Epoch: [19] [ 500/1319] eta: 0:39:39 lr: 2.754095328968076e-05 loss: 0.0592 (0.0547) time: 2.7673 data: 0.0079 max mem: 33369 +Epoch: [19] [ 510/1319] eta: 0:39:07 lr: 2.753183963658258e-05 loss: 0.0425 (0.0546) time: 2.6761 data: 0.0076 max mem: 33369 +Epoch: [19] [ 520/1319] eta: 0:38:34 lr: 2.7522725648269566e-05 loss: 0.0461 (0.0545) time: 2.6510 data: 0.0071 max mem: 33369 +Epoch: [19] [ 530/1319] eta: 0:38:01 lr: 2.7513611324606038e-05 loss: 0.0467 (0.0545) time: 2.6443 data: 0.0067 max mem: 33369 +Epoch: [19] [ 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data: 0.0079 max mem: 33369 +Epoch: [19] [ 700/1319] eta: 0:29:43 lr: 2.735861638171675e-05 loss: 0.0491 (0.0557) time: 2.8605 data: 0.0078 max mem: 33369 +Epoch: [19] [ 710/1319] eta: 0:29:14 lr: 2.7349495998423098e-05 loss: 0.0474 (0.0556) time: 2.8822 data: 0.0080 max mem: 33369 +Epoch: [19] [ 720/1319] eta: 0:28:45 lr: 2.7340375277181003e-05 loss: 0.0476 (0.0554) time: 2.8923 data: 0.0079 max mem: 33369 +Epoch: [19] [ 730/1319] eta: 0:28:16 lr: 2.733125421785267e-05 loss: 0.0498 (0.0555) time: 2.8755 data: 0.0077 max mem: 33369 +Epoch: [19] [ 740/1319] eta: 0:27:48 lr: 2.7322132820300196e-05 loss: 0.0519 (0.0556) time: 2.8800 data: 0.0079 max mem: 33369 +Epoch: [19] [ 750/1319] eta: 0:27:19 lr: 2.731301108438557e-05 loss: 0.0484 (0.0556) time: 2.8946 data: 0.0080 max mem: 33369 +Epoch: [19] [ 760/1319] eta: 0:26:50 lr: 2.7303889009970667e-05 loss: 0.0458 (0.0555) time: 2.8863 data: 0.0081 max mem: 33369 +Epoch: [19] [ 770/1319] eta: 0:26:21 lr: 2.7294766596917266e-05 loss: 0.0473 (0.0556) time: 2.8707 data: 0.0083 max mem: 33369 +Epoch: [19] [ 780/1319] eta: 0:25:52 lr: 2.7285643845087027e-05 loss: 0.0564 (0.0556) time: 2.8736 data: 0.0081 max mem: 33369 +Epoch: [19] [ 790/1319] eta: 0:25:23 lr: 2.7276520754341512e-05 loss: 0.0504 (0.0557) time: 2.8603 data: 0.0082 max mem: 33369 +Epoch: [19] [ 800/1319] eta: 0:24:54 lr: 2.726739732454216e-05 loss: 0.0473 (0.0556) time: 2.8547 data: 0.0083 max mem: 33369 +Epoch: [19] [ 810/1319] eta: 0:24:26 lr: 2.7258273555550322e-05 loss: 0.0448 (0.0555) time: 2.8735 data: 0.0083 max mem: 33369 +Epoch: [19] [ 820/1319] eta: 0:23:57 lr: 2.7249149447227223e-05 loss: 0.0453 (0.0554) time: 2.9003 data: 0.0083 max mem: 33369 +Epoch: [19] [ 830/1319] eta: 0:23:28 lr: 2.7240024999433987e-05 loss: 0.0499 (0.0555) time: 2.8833 data: 0.0082 max mem: 33369 +Epoch: [19] [ 840/1319] eta: 0:22:59 lr: 2.723090021203163e-05 loss: 0.0497 (0.0555) time: 2.8340 data: 0.0084 max mem: 33369 +Epoch: [19] [ 850/1319] eta: 0:22:30 lr: 2.7221775084881062e-05 loss: 0.0472 (0.0555) time: 2.8530 data: 0.0084 max mem: 33369 +Epoch: [19] [ 860/1319] eta: 0:22:01 lr: 2.7212649617843082e-05 loss: 0.0460 (0.0554) time: 2.8544 data: 0.0084 max mem: 33369 +Epoch: [19] [ 870/1319] eta: 0:21:32 lr: 2.7203523810778376e-05 loss: 0.0541 (0.0555) time: 2.8602 data: 0.0083 max mem: 33369 +Epoch: [19] [ 880/1319] eta: 0:21:03 lr: 2.7194397663547522e-05 loss: 0.0548 (0.0557) time: 2.8847 data: 0.0081 max mem: 33369 +Epoch: [19] [ 890/1319] eta: 0:20:35 lr: 2.7185271176010996e-05 loss: 0.0493 (0.0557) time: 2.8800 data: 0.0082 max mem: 33369 +Epoch: [19] [ 900/1319] eta: 0:20:06 lr: 2.7176144348029154e-05 loss: 0.0484 (0.0556) time: 2.8668 data: 0.0082 max mem: 33369 +Epoch: [19] [ 910/1319] eta: 0:19:36 lr: 2.7167017179462245e-05 loss: 0.0496 (0.0557) time: 2.7731 data: 0.0083 max mem: 33369 +Epoch: [19] [ 920/1319] eta: 0:19:06 lr: 2.7157889670170428e-05 loss: 0.0475 (0.0556) time: 2.6674 data: 0.0083 max mem: 33369 +Epoch: [19] [ 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33369 +Epoch: [19] [1010/1319] eta: 0:14:46 lr: 2.7075726730791712e-05 loss: 0.0539 (0.0555) time: 2.9061 data: 0.0075 max mem: 33369 +Epoch: [19] [1020/1319] eta: 0:14:17 lr: 2.706659580653433e-05 loss: 0.0568 (0.0554) time: 2.9123 data: 0.0075 max mem: 33369 +Epoch: [19] [1030/1319] eta: 0:13:49 lr: 2.7057464540006328e-05 loss: 0.0416 (0.0555) time: 2.9331 data: 0.0074 max mem: 33369 +Epoch: [19] [1040/1319] eta: 0:13:20 lr: 2.7048332931066517e-05 loss: 0.0488 (0.0554) time: 2.9020 data: 0.0075 max mem: 33369 +Epoch: [19] [1050/1319] eta: 0:12:51 lr: 2.7039200979573614e-05 loss: 0.0486 (0.0554) time: 2.8715 data: 0.0078 max mem: 33369 +Epoch: [19] [1060/1319] eta: 0:12:23 lr: 2.7030068685386206e-05 loss: 0.0520 (0.0555) time: 2.8775 data: 0.0079 max mem: 33369 +Epoch: [19] [1070/1319] eta: 0:11:54 lr: 2.7020936048362782e-05 loss: 0.0520 (0.0555) time: 2.8895 data: 0.0079 max mem: 33369 +Epoch: [19] [1080/1319] eta: 0:11:25 lr: 2.7011803068361714e-05 loss: 0.0490 (0.0555) time: 2.9094 data: 0.0080 max mem: 33369 +Epoch: [19] [1090/1319] eta: 0:10:57 lr: 2.700266974524126e-05 loss: 0.0490 (0.0555) time: 2.9087 data: 0.0079 max mem: 33369 +Epoch: [19] [1100/1319] eta: 0:10:28 lr: 2.699353607885957e-05 loss: 0.0448 (0.0555) time: 2.8835 data: 0.0078 max mem: 33369 +Epoch: [19] [1110/1319] eta: 0:09:59 lr: 2.6984402069074687e-05 loss: 0.0514 (0.0555) time: 2.8653 data: 0.0080 max mem: 33369 +Epoch: [19] [1120/1319] eta: 0:09:31 lr: 2.6975267715744523e-05 loss: 0.0588 (0.0555) time: 2.8533 data: 0.0081 max mem: 33369 +Epoch: [19] [1130/1319] eta: 0:09:02 lr: 2.6966133018726902e-05 loss: 0.0588 (0.0555) time: 2.8407 data: 0.0082 max mem: 33369 +Epoch: [19] [1140/1319] eta: 0:08:33 lr: 2.6956997977879505e-05 loss: 0.0594 (0.0556) time: 2.8690 data: 0.0080 max mem: 33369 +Epoch: [19] [1150/1319] eta: 0:08:04 lr: 2.6947862593059943e-05 loss: 0.0565 (0.0555) time: 2.8705 data: 0.0080 max mem: 33369 +Epoch: [19] [1160/1319] eta: 0:07:36 lr: 2.6938726864125667e-05 loss: 0.0462 (0.0555) time: 2.8595 data: 0.0082 max mem: 33369 +Epoch: [19] [1170/1319] eta: 0:07:07 lr: 2.6929590790934063e-05 loss: 0.0542 (0.0555) time: 2.8642 data: 0.0081 max mem: 33369 +Epoch: [19] [1180/1319] eta: 0:06:38 lr: 2.6920454373342357e-05 loss: 0.0506 (0.0554) time: 2.8414 data: 0.0083 max mem: 33369 +Epoch: [19] [1190/1319] eta: 0:06:10 lr: 2.6911317611207703e-05 loss: 0.0459 (0.0554) time: 2.8360 data: 0.0085 max mem: 33369 +Epoch: [19] [1200/1319] eta: 0:05:41 lr: 2.6902180504387114e-05 loss: 0.0514 (0.0554) time: 2.8430 data: 0.0085 max mem: 33369 +Epoch: [19] [1210/1319] eta: 0:05:12 lr: 2.689304305273751e-05 loss: 0.0514 (0.0554) time: 2.8489 data: 0.0085 max mem: 33369 +Epoch: [19] [1220/1319] eta: 0:04:44 lr: 2.6883905256115667e-05 loss: 0.0449 (0.0554) time: 2.8681 data: 0.0084 max mem: 33369 +Epoch: [19] [1230/1319] eta: 0:04:15 lr: 2.687476711437828e-05 loss: 0.0450 (0.0555) time: 2.8732 data: 0.0083 max mem: 33369 +Epoch: [19] [1240/1319] eta: 0:03:46 lr: 2.6865628627381928e-05 loss: 0.0525 (0.0555) time: 2.8476 data: 0.0084 max mem: 33369 +Epoch: [19] [1250/1319] eta: 0:03:17 lr: 2.6856489794983043e-05 loss: 0.0469 (0.0555) time: 2.8790 data: 0.0084 max mem: 33369 +Epoch: [19] [1260/1319] eta: 0:02:49 lr: 2.6847350617037976e-05 loss: 0.0469 (0.0555) time: 2.9039 data: 0.0083 max mem: 33369 +Epoch: [19] [1270/1319] eta: 0:02:20 lr: 2.683821109340296e-05 loss: 0.0511 (0.0554) time: 2.8728 data: 0.0082 max mem: 33369 +Epoch: [19] [1280/1319] eta: 0:01:51 lr: 2.68290712239341e-05 loss: 0.0451 (0.0555) time: 2.8798 data: 0.0081 max mem: 33369 +Epoch: [19] [1290/1319] eta: 0:01:23 lr: 2.681993100848739e-05 loss: 0.0509 (0.0555) time: 2.8912 data: 0.0081 max mem: 33369 +Epoch: [19] [1300/1319] eta: 0:00:54 lr: 2.6810790446918727e-05 loss: 0.0580 (0.0557) time: 2.8041 data: 0.0079 max mem: 33369 +Epoch: [19] [1310/1319] eta: 0:00:25 lr: 2.680164953908387e-05 loss: 0.0580 (0.0557) time: 2.6718 data: 0.0079 max mem: 33369 +Epoch: [19] Total time: 1:02:59 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 2:08:09 time: 2.9886 data: 2.9082 max mem: 33369 +Test: [ 100/2573] eta: 0:04:09 time: 0.0721 data: 0.0012 max mem: 33369 +Test: [ 200/2573] eta: 0:03:29 time: 0.0748 data: 0.0013 max mem: 33369 +Test: [ 300/2573] eta: 0:03:08 time: 0.0756 data: 0.0011 max mem: 33369 +Test: [ 400/2573] eta: 0:02:55 time: 0.0758 data: 0.0011 max mem: 33369 +Test: [ 500/2573] eta: 0:02:44 time: 0.0742 data: 0.0012 max mem: 33369 +Test: [ 600/2573] eta: 0:02:35 time: 0.0743 data: 0.0012 max mem: 33369 +Test: [ 700/2573] eta: 0:02:26 time: 0.0743 data: 0.0012 max mem: 33369 +Test: [ 800/2573] eta: 0:02:18 time: 0.0775 data: 0.0012 max mem: 33369 +Test: [ 900/2573] eta: 0:02:10 time: 0.0753 data: 0.0013 max mem: 33369 +Test: [1000/2573] eta: 0:02:02 time: 0.0758 data: 0.0014 max mem: 33369 +Test: [1100/2573] eta: 0:01:54 time: 0.0757 data: 0.0014 max mem: 33369 +Test: [1200/2573] eta: 0:01:46 time: 0.0757 data: 0.0013 max mem: 33369 +Test: [1300/2573] eta: 0:01:38 time: 0.0756 data: 0.0013 max mem: 33369 +Test: [1400/2573] eta: 0:01:30 time: 0.0737 data: 0.0014 max mem: 33369 +Test: [1500/2573] eta: 0:01:22 time: 0.0754 data: 0.0014 max mem: 33369 +Test: [1600/2573] eta: 0:01:14 time: 0.0788 data: 0.0014 max mem: 33369 +Test: [1700/2573] eta: 0:01:07 time: 0.0737 data: 0.0013 max mem: 33369 +Test: [1800/2573] eta: 0:00:59 time: 0.0772 data: 0.0013 max mem: 33369 +Test: [1900/2573] eta: 0:00:51 time: 0.0739 data: 0.0014 max mem: 33369 +Test: [2000/2573] eta: 0:00:43 time: 0.0755 data: 0.0013 max mem: 33369 +Test: [2100/2573] eta: 0:00:36 time: 0.0771 data: 0.0013 max mem: 33369 +Test: [2200/2573] eta: 0:00:28 time: 0.0772 data: 0.0013 max mem: 33369 +Test: [2300/2573] eta: 0:00:20 time: 0.0773 data: 0.0014 max mem: 33369 +Test: [2400/2573] eta: 0:00:13 time: 0.0722 data: 0.0014 max mem: 33369 +Test: [2500/2573] eta: 0:00:05 time: 0.0756 data: 0.0014 max mem: 33369 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: Total time: 0:03:16 +Final results: +Mean IoU is 63.10 + + precision@0.5 = 70.59 + precision@0.6 = 65.05 + precision@0.7 = 58.17 + precision@0.8 = 46.14 + precision@0.9 = 21.85 + overall IoU = 61.42 + +Average object IoU 63.10357534931359 +Overall IoU 61.42414474487305 +Better epoch: 19 + +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [20] [ 0/1319] eta: 2:44:53 lr: 2.6793422425855603e-05 loss: 0.0415 (0.0415) time: 7.5005 data: 4.6116 max mem: 33369 +Epoch: [20] [ 10/1319] eta: 1:12:53 lr: 2.678428085971722e-05 loss: 0.0449 (0.0443) time: 3.3409 data: 0.4258 max mem: 33369 +Epoch: [20] [ 20/1319] eta: 1:08:03 lr: 2.6775138946893718e-05 loss: 0.0464 (0.0487) time: 2.9256 data: 0.0067 max mem: 33369 +Epoch: [20] [ 30/1319] eta: 1:06:11 lr: 2.6765996687240426e-05 loss: 0.0497 (0.0491) time: 2.9387 data: 0.0069 max mem: 33369 +Epoch: [20] [ 40/1319] eta: 1:04:43 lr: 2.675685408061254e-05 loss: 0.0497 (0.0491) time: 2.9236 data: 0.0075 max mem: 33369 +Epoch: [20] [ 50/1319] eta: 1:03:43 lr: 2.6747711126865168e-05 loss: 0.0460 (0.0481) time: 2.9073 data: 0.0074 max mem: 33369 +Epoch: [20] [ 60/1319] eta: 1:02:57 lr: 2.6738567825853273e-05 loss: 0.0547 (0.0508) time: 2.9274 data: 0.0074 max mem: 33369 +Epoch: [20] [ 70/1319] eta: 1:02:07 lr: 2.6729424177431713e-05 loss: 0.0594 (0.0516) time: 2.9122 data: 0.0076 max mem: 33369 +Epoch: [20] [ 80/1319] eta: 1:01:25 lr: 2.6720280181455227e-05 loss: 0.0462 (0.0527) time: 2.8945 data: 0.0079 max mem: 33369 +Epoch: [20] [ 90/1319] eta: 1:00:40 lr: 2.671113583777845e-05 loss: 0.0430 (0.0518) time: 2.8821 data: 0.0078 max mem: 33369 +Epoch: [20] [ 100/1319] eta: 1:00:03 lr: 2.670199114625589e-05 loss: 0.0457 (0.0520) time: 2.8817 data: 0.0077 max mem: 33369 +Epoch: [20] [ 110/1319] eta: 0:59:23 lr: 2.6692846106741932e-05 loss: 0.0454 (0.0519) time: 2.8804 data: 0.0077 max mem: 33369 +Epoch: [20] [ 120/1319] eta: 0:58:47 lr: 2.668370071909087e-05 loss: 0.0438 (0.0515) time: 2.8701 data: 0.0079 max mem: 33369 +Epoch: [20] [ 130/1319] eta: 0:58:15 lr: 2.6674554983156852e-05 loss: 0.0458 (0.0511) time: 2.8983 data: 0.0082 max mem: 33369 +Epoch: [20] [ 140/1319] eta: 0:57:38 lr: 2.666540889879393e-05 loss: 0.0533 (0.0511) time: 2.8801 data: 0.0081 max mem: 33369 +Epoch: [20] [ 150/1319] eta: 0:57:01 lr: 2.6656262465856026e-05 loss: 0.0503 (0.0514) time: 2.8437 data: 0.0081 max mem: 33369 +Epoch: [20] [ 160/1319] eta: 0:56:29 lr: 2.6647115684196954e-05 loss: 0.0503 (0.0513) time: 2.8651 data: 0.0081 max mem: 33369 +Epoch: [20] [ 170/1319] eta: 0:55:57 lr: 2.663796855367041e-05 loss: 0.0541 (0.0513) time: 2.8851 data: 0.0081 max mem: 33369 +Epoch: [20] [ 180/1319] eta: 0:55:28 lr: 2.662882107412996e-05 loss: 0.0519 (0.0511) time: 2.9029 data: 0.0080 max mem: 33369 +Epoch: [20] [ 190/1319] eta: 0:55:00 lr: 2.661967324542908e-05 loss: 0.0449 (0.0513) time: 2.9308 data: 0.0081 max mem: 33369 +Epoch: [20] [ 200/1319] eta: 0:54:28 lr: 2.6610525067421092e-05 loss: 0.0446 (0.0513) time: 2.9121 data: 0.0083 max mem: 33369 +Epoch: [20] [ 210/1319] eta: 0:53:59 lr: 2.6601376539959238e-05 loss: 0.0438 (0.0513) time: 2.8973 data: 0.0083 max mem: 33369 +Epoch: [20] [ 220/1319] eta: 0:53:26 lr: 2.6592227662896617e-05 loss: 0.0445 (0.0515) time: 2.8861 data: 0.0083 max mem: 33369 +Epoch: [20] [ 230/1319] eta: 0:52:55 lr: 2.658307843608621e-05 loss: 0.0427 (0.0513) time: 2.8710 data: 0.0084 max mem: 33369 +Epoch: [20] [ 240/1319] eta: 0:52:24 lr: 2.65739288593809e-05 loss: 0.0458 (0.0521) time: 2.8673 data: 0.0083 max mem: 33369 +Epoch: [20] [ 250/1319] eta: 0:51:52 lr: 2.6564778932633426e-05 loss: 0.0457 (0.0518) time: 2.8619 data: 0.0083 max mem: 33369 +Epoch: [20] [ 260/1319] eta: 0:51:22 lr: 2.655562865569643e-05 loss: 0.0457 (0.0522) time: 2.8788 data: 0.0085 max mem: 33369 +Epoch: [20] [ 270/1319] eta: 0:50:53 lr: 2.654647802842242e-05 loss: 0.0537 (0.0525) time: 2.8901 data: 0.0085 max mem: 33369 +Epoch: [20] [ 280/1319] eta: 0:50:23 lr: 2.6537327050663813e-05 loss: 0.0472 (0.0524) time: 2.8978 data: 0.0083 max mem: 33369 +Epoch: [20] [ 290/1319] eta: 0:49:50 lr: 2.6528175722272857e-05 loss: 0.0472 (0.0524) time: 2.8549 data: 0.0079 max mem: 33369 +Epoch: [20] [ 300/1319] eta: 0:49:13 lr: 2.6519024043101733e-05 loss: 0.0505 (0.0524) time: 2.7318 data: 0.0080 max mem: 33369 +Epoch: [20] [ 310/1319] eta: 0:48:35 lr: 2.6509872013002462e-05 loss: 0.0484 (0.0523) time: 2.6453 data: 0.0078 max mem: 33369 +Epoch: [20] [ 320/1319] eta: 0:47:58 lr: 2.6500719631826982e-05 loss: 0.0446 (0.0520) time: 2.6257 data: 0.0071 max mem: 33369 +Epoch: [20] [ 330/1319] eta: 0:47:22 lr: 2.649156689942709e-05 loss: 0.0427 (0.0519) time: 2.6218 data: 0.0069 max mem: 33369 +Epoch: [20] [ 340/1319] eta: 0:46:47 lr: 2.648241381565446e-05 loss: 0.0427 (0.0517) time: 2.6536 data: 0.0069 max mem: 33369 +Epoch: [20] [ 350/1319] eta: 0:46:13 lr: 2.6473260380360663e-05 loss: 0.0532 (0.0521) time: 2.6714 data: 0.0068 max mem: 33369 +Epoch: [20] [ 360/1319] eta: 0:45:39 lr: 2.6464106593397137e-05 loss: 0.0441 (0.0519) time: 2.6581 data: 0.0068 max mem: 33369 +Epoch: [20] [ 370/1319] eta: 0:45:11 lr: 2.6454952454615202e-05 loss: 0.0441 (0.0517) time: 2.7809 data: 0.0074 max mem: 33369 +Epoch: [20] [ 380/1319] eta: 0:44:43 lr: 2.6445797963866064e-05 loss: 0.0460 (0.0516) time: 2.8894 data: 0.0079 max mem: 33369 +Epoch: [20] [ 390/1319] eta: 0:44:14 lr: 2.643664312100081e-05 loss: 0.0445 (0.0516) time: 2.8565 data: 0.0078 max mem: 33369 +Epoch: [20] [ 400/1319] eta: 0:43:45 lr: 2.6427487925870388e-05 loss: 0.0445 (0.0514) time: 2.8403 data: 0.0078 max mem: 33369 +Epoch: [20] [ 410/1319] eta: 0:43:17 lr: 2.641833237832565e-05 loss: 0.0423 (0.0513) time: 2.8504 data: 0.0078 max mem: 33369 +Epoch: [20] [ 420/1319] eta: 0:42:49 lr: 2.6409176478217318e-05 loss: 0.0396 (0.0512) time: 2.8739 data: 0.0077 max mem: 33369 +Epoch: [20] [ 430/1319] eta: 0:42:22 lr: 2.640002022539598e-05 loss: 0.0419 (0.0512) time: 2.9081 data: 0.0074 max mem: 33369 +Epoch: [20] [ 440/1319] eta: 0:41:54 lr: 2.6390863619712137e-05 loss: 0.0451 (0.0513) time: 2.9150 data: 0.0074 max mem: 33369 +Epoch: [20] [ 450/1319] eta: 0:41:26 lr: 2.6381706661016125e-05 loss: 0.0423 (0.0512) time: 2.9017 data: 0.0073 max mem: 33369 +Epoch: [20] [ 460/1319] eta: 0:40:58 lr: 2.637254934915819e-05 loss: 0.0474 (0.0512) time: 2.8855 data: 0.0073 max mem: 33369 +Epoch: [20] [ 470/1319] eta: 0:40:30 lr: 2.6363391683988447e-05 loss: 0.0442 (0.0510) time: 2.8931 data: 0.0076 max mem: 33369 +Epoch: [20] [ 480/1319] eta: 0:40:02 lr: 2.6354233665356892e-05 loss: 0.0442 (0.0511) time: 2.9149 data: 0.0077 max mem: 33369 +Epoch: [20] [ 490/1319] eta: 0:39:34 lr: 2.6345075293113398e-05 loss: 0.0455 (0.0509) time: 2.9049 data: 0.0075 max mem: 33369 +Epoch: [20] [ 500/1319] eta: 0:39:06 lr: 2.633591656710771e-05 loss: 0.0370 (0.0507) time: 2.8895 data: 0.0075 max mem: 33369 +Epoch: [20] [ 510/1319] eta: 0:38:37 lr: 2.6326757487189457e-05 loss: 0.0377 (0.0506) time: 2.8790 data: 0.0077 max mem: 33369 +Epoch: [20] [ 520/1319] eta: 0:38:09 lr: 2.6317598053208148e-05 loss: 0.0435 (0.0506) time: 2.8850 data: 0.0077 max mem: 33369 +Epoch: [20] [ 530/1319] eta: 0:37:41 lr: 2.6308438265013168e-05 loss: 0.0454 (0.0506) time: 2.8872 data: 0.0077 max mem: 33369 +Epoch: [20] [ 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data: 0.0085 max mem: 33369 +Epoch: [20] [ 700/1319] eta: 0:29:33 lr: 2.615266752446517e-05 loss: 0.0453 (0.0508) time: 2.8110 data: 0.0082 max mem: 33369 +Epoch: [20] [ 710/1319] eta: 0:29:03 lr: 2.614350133452863e-05 loss: 0.0481 (0.0508) time: 2.7386 data: 0.0079 max mem: 33369 +Epoch: [20] [ 720/1319] eta: 0:28:32 lr: 2.6134334787493302e-05 loss: 0.0473 (0.0512) time: 2.6686 data: 0.0078 max mem: 33369 +Epoch: [20] [ 730/1319] eta: 0:28:02 lr: 2.6125167883206104e-05 loss: 0.0487 (0.0511) time: 2.6613 data: 0.0074 max mem: 33369 +Epoch: [20] [ 740/1319] eta: 0:27:33 lr: 2.61160006215138e-05 loss: 0.0505 (0.0512) time: 2.6847 data: 0.0069 max mem: 33369 +Epoch: [20] [ 750/1319] eta: 0:27:02 lr: 2.610683300226307e-05 loss: 0.0525 (0.0512) time: 2.6735 data: 0.0070 max mem: 33369 +Epoch: [20] [ 760/1319] eta: 0:26:34 lr: 2.6097665025300437e-05 loss: 0.0489 (0.0513) time: 2.7543 data: 0.0073 max mem: 33369 +Epoch: [20] [ 770/1319] eta: 0:26:06 lr: 2.608849669047231e-05 loss: 0.0488 (0.0513) time: 2.8973 data: 0.0076 max mem: 33369 +Epoch: [20] [ 780/1319] eta: 0:25:37 lr: 2.6079327997624963e-05 loss: 0.0473 (0.0513) time: 2.8938 data: 0.0079 max mem: 33369 +Epoch: [20] [ 790/1319] eta: 0:25:09 lr: 2.6070158946604555e-05 loss: 0.0447 (0.0513) time: 2.8682 data: 0.0076 max mem: 33369 +Epoch: [20] [ 800/1319] eta: 0:24:41 lr: 2.6060989537257118e-05 loss: 0.0500 (0.0514) time: 2.9176 data: 0.0075 max mem: 33369 +Epoch: [20] [ 810/1319] eta: 0:24:13 lr: 2.6051819769428553e-05 loss: 0.0537 (0.0514) time: 2.9111 data: 0.0077 max mem: 33369 +Epoch: [20] [ 820/1319] eta: 0:23:45 lr: 2.604264964296463e-05 loss: 0.0463 (0.0513) time: 2.8979 data: 0.0076 max mem: 33369 +Epoch: [20] [ 830/1319] eta: 0:23:17 lr: 2.6033479157711e-05 loss: 0.0437 (0.0513) time: 2.9242 data: 0.0075 max mem: 33369 +Epoch: [20] [ 840/1319] eta: 0:22:48 lr: 2.6024308313513185e-05 loss: 0.0443 (0.0514) time: 2.9294 data: 0.0075 max mem: 33369 +Epoch: [20] [ 850/1319] eta: 0:22:20 lr: 2.601513711021658e-05 loss: 0.0471 (0.0513) time: 2.9086 data: 0.0074 max mem: 33369 +Epoch: [20] [ 860/1319] eta: 0:21:52 lr: 2.6005965547666454e-05 loss: 0.0446 (0.0513) time: 2.9005 data: 0.0076 max mem: 33369 +Epoch: [20] [ 870/1319] eta: 0:21:23 lr: 2.599679362570795e-05 loss: 0.0466 (0.0513) time: 2.9099 data: 0.0077 max mem: 33369 +Epoch: [20] [ 880/1319] eta: 0:20:55 lr: 2.598762134418607e-05 loss: 0.0466 (0.0513) time: 2.8917 data: 0.0076 max mem: 33369 +Epoch: [20] [ 890/1319] eta: 0:20:26 lr: 2.5978448702945707e-05 loss: 0.0442 (0.0513) time: 2.8957 data: 0.0079 max mem: 33369 +Epoch: [20] [ 900/1319] eta: 0:19:58 lr: 2.596927570183162e-05 loss: 0.0480 (0.0514) time: 2.8996 data: 0.0080 max mem: 33369 +Epoch: [20] [ 910/1319] eta: 0:19:29 lr: 2.5960102340688436e-05 loss: 0.0480 (0.0513) time: 2.8749 data: 0.0077 max mem: 33369 +Epoch: [20] [ 920/1319] eta: 0:19:01 lr: 2.5950928619360655e-05 loss: 0.0433 (0.0512) time: 2.8657 data: 0.0076 max mem: 33369 +Epoch: [20] [ 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33369 +Epoch: [20] [1010/1319] eta: 0:14:43 lr: 2.586834889338287e-05 loss: 0.0406 (0.0514) time: 2.8480 data: 0.0080 max mem: 33369 +Epoch: [20] [1020/1319] eta: 0:14:14 lr: 2.58591715616284e-05 loss: 0.0482 (0.0515) time: 2.8085 data: 0.0081 max mem: 33369 +Epoch: [20] [1030/1319] eta: 0:13:46 lr: 2.584999386797035e-05 loss: 0.0460 (0.0514) time: 2.8418 data: 0.0081 max mem: 33369 +Epoch: [20] [1040/1319] eta: 0:13:17 lr: 2.5840815812251663e-05 loss: 0.0460 (0.0514) time: 2.8793 data: 0.0081 max mem: 33369 +Epoch: [20] [1050/1319] eta: 0:12:49 lr: 2.583163739431517e-05 loss: 0.0461 (0.0514) time: 2.8660 data: 0.0082 max mem: 33369 +Epoch: [20] [1060/1319] eta: 0:12:20 lr: 2.582245861400355e-05 loss: 0.0451 (0.0514) time: 2.8805 data: 0.0082 max mem: 33369 +Epoch: [20] [1070/1319] eta: 0:11:52 lr: 2.5813279471159375e-05 loss: 0.0386 (0.0513) time: 2.8756 data: 0.0083 max mem: 33369 +Epoch: [20] [1080/1319] eta: 0:11:23 lr: 2.5804099965625085e-05 loss: 0.0456 (0.0513) time: 2.8573 data: 0.0083 max mem: 33369 +Epoch: [20] [1090/1319] eta: 0:10:54 lr: 2.5794920097242954e-05 loss: 0.0499 (0.0513) time: 2.8341 data: 0.0080 max mem: 33369 +Epoch: [20] [1100/1319] eta: 0:10:25 lr: 2.5785739865855164e-05 loss: 0.0407 (0.0513) time: 2.7438 data: 0.0080 max mem: 33369 +Epoch: [20] [1110/1319] eta: 0:09:56 lr: 2.5776559271303753e-05 loss: 0.0416 (0.0512) time: 2.6703 data: 0.0079 max mem: 33369 +Epoch: [20] [1120/1319] eta: 0:09:27 lr: 2.5767378313430623e-05 loss: 0.0417 (0.0514) time: 2.6556 data: 0.0076 max mem: 33369 +Epoch: [20] [1130/1319] eta: 0:08:59 lr: 2.5758196992077554e-05 loss: 0.0481 (0.0516) time: 2.6361 data: 0.0074 max mem: 33369 +Epoch: [20] [1140/1319] eta: 0:08:30 lr: 2.574901530708619e-05 loss: 0.0481 (0.0515) time: 2.6596 data: 0.0072 max mem: 33369 +Epoch: [20] [1150/1319] eta: 0:08:01 lr: 2.573983325829803e-05 loss: 0.0435 (0.0515) time: 2.7871 data: 0.0075 max mem: 33369 +Epoch: [20] [1160/1319] eta: 0:07:33 lr: 2.573065084555446e-05 loss: 0.0480 (0.0515) time: 2.8841 data: 0.0079 max mem: 33369 +Epoch: [20] [1170/1319] eta: 0:07:04 lr: 2.572146806869673e-05 loss: 0.0512 (0.0515) time: 2.9128 data: 0.0079 max mem: 33369 +Epoch: [20] [1180/1319] eta: 0:06:36 lr: 2.5712284927565954e-05 loss: 0.0512 (0.0516) time: 2.9366 data: 0.0079 max mem: 33369 +Epoch: [20] [1190/1319] eta: 0:06:08 lr: 2.5703101422003118e-05 loss: 0.0446 (0.0515) time: 2.9058 data: 0.0077 max mem: 33369 +Epoch: [20] [1200/1319] eta: 0:05:39 lr: 2.569391755184906e-05 loss: 0.0433 (0.0514) time: 2.9018 data: 0.0077 max mem: 33369 +Epoch: [20] [1210/1319] eta: 0:05:11 lr: 2.5684733316944508e-05 loss: 0.0394 (0.0514) time: 2.9254 data: 0.0077 max mem: 33369 +Epoch: [20] [1220/1319] eta: 0:04:42 lr: 2.5675548717130043e-05 loss: 0.0380 (0.0513) time: 2.9146 data: 0.0077 max mem: 33369 +Epoch: [20] [1230/1319] eta: 0:04:14 lr: 2.5666363752246116e-05 loss: 0.0398 (0.0513) time: 2.9141 data: 0.0076 max mem: 33369 +Epoch: [20] [1240/1319] eta: 0:03:45 lr: 2.5657178422133044e-05 loss: 0.0545 (0.0515) time: 2.8814 data: 0.0076 max mem: 33369 +Epoch: [20] [1250/1319] eta: 0:03:16 lr: 2.564799272663101e-05 loss: 0.0570 (0.0515) time: 2.8471 data: 0.0078 max mem: 33369 +Epoch: [20] [1260/1319] eta: 0:02:48 lr: 2.5638806665580068e-05 loss: 0.0494 (0.0515) time: 2.8551 data: 0.0080 max mem: 33369 +Epoch: [20] [1270/1319] eta: 0:02:19 lr: 2.5629620238820134e-05 loss: 0.0489 (0.0516) time: 2.8547 data: 0.0080 max mem: 33369 +Epoch: [20] [1280/1319] eta: 0:01:51 lr: 2.562043344619099e-05 loss: 0.0456 (0.0516) time: 2.8426 data: 0.0079 max mem: 33369 +Epoch: [20] [1290/1319] eta: 0:01:22 lr: 2.5611246287532285e-05 loss: 0.0465 (0.0516) time: 2.8336 data: 0.0080 max mem: 33369 +Epoch: [20] [1300/1319] eta: 0:00:54 lr: 2.560205876268355e-05 loss: 0.0501 (0.0516) time: 2.8359 data: 0.0081 max mem: 33369 +Epoch: [20] [1310/1319] eta: 0:00:25 lr: 2.5592870871484144e-05 loss: 0.0506 (0.0516) time: 2.8590 data: 0.0078 max mem: 33369 +Epoch: [20] Total time: 1:02:45 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 2:12:28 time: 3.0893 data: 2.9398 max mem: 33369 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 100/2573] eta: 0:04:15 time: 0.0732 data: 0.0014 max mem: 33369 +Test: [ 200/2573] eta: 0:03:32 time: 0.0748 data: 0.0013 max mem: 33369 +Test: [ 300/2573] eta: 0:03:11 time: 0.0767 data: 0.0014 max mem: 33369 +Test: [ 400/2573] eta: 0:02:58 time: 0.0768 data: 0.0013 max mem: 33369 +Test: [ 500/2573] eta: 0:02:47 time: 0.0753 data: 0.0014 max mem: 33369 +Test: [ 600/2573] eta: 0:02:37 time: 0.0754 data: 0.0014 max mem: 33369 +Test: [ 700/2573] eta: 0:02:29 time: 0.0754 data: 0.0013 max mem: 33369 +Test: [ 800/2573] eta: 0:02:20 time: 0.0787 data: 0.0013 max mem: 33369 +Test: [ 900/2573] eta: 0:02:11 time: 0.0754 data: 0.0014 max mem: 33369 +Test: [1000/2573] eta: 0:02:03 time: 0.0754 data: 0.0013 max mem: 33369 +Test: [1100/2573] eta: 0:01:55 time: 0.0754 data: 0.0014 max mem: 33369 +Test: [1200/2573] eta: 0:01:47 time: 0.0757 data: 0.0014 max mem: 33369 +Test: [1300/2573] eta: 0:01:39 time: 0.0752 data: 0.0013 max mem: 33369 +Test: [1400/2573] eta: 0:01:31 time: 0.0739 data: 0.0014 max mem: 33369 +Test: [1500/2573] eta: 0:01:23 time: 0.0757 data: 0.0014 max mem: 33369 +Test: [1600/2573] eta: 0:01:15 time: 0.0789 data: 0.0013 max mem: 33369 +Test: [1700/2573] eta: 0:01:07 time: 0.0736 data: 0.0013 max mem: 33369 +Test: [1800/2573] eta: 0:00:59 time: 0.0772 data: 0.0014 max mem: 33369 +Test: [1900/2573] eta: 0:00:51 time: 0.0738 data: 0.0013 max mem: 33369 +Test: [2000/2573] eta: 0:00:44 time: 0.0756 data: 0.0014 max mem: 33369 +Test: [2100/2573] eta: 0:00:36 time: 0.0771 data: 0.0013 max mem: 33369 +Test: [2200/2573] eta: 0:00:28 time: 0.0771 data: 0.0013 max mem: 33369 +Test: [2300/2573] eta: 0:00:20 time: 0.0771 data: 0.0013 max mem: 33369 +Test: [2400/2573] eta: 0:00:13 time: 0.0724 data: 0.0014 max mem: 33369 +Test: [2500/2573] eta: 0:00:05 time: 0.0753 data: 0.0013 max mem: 33369 +Test: Total time: 0:03:17 +Final results: +Mean IoU is 63.71 + + precision@0.5 = 71.49 + precision@0.6 = 66.18 + precision@0.7 = 58.44 + precision@0.8 = 46.14 + precision@0.9 = 22.30 + overall IoU = 61.70 + +Average object IoU 63.70595293786082 +Overall IoU 61.70463180541992 +Better epoch: 20 + +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [21] [ 0/1319] eta: 1:37:17 lr: 2.5584601456041995e-05 loss: 0.0584 (0.0584) time: 4.4255 data: 1.2698 max mem: 33369 +Epoch: [21] [ 10/1319] eta: 1:10:16 lr: 2.5575412868333344e-05 loss: 0.0533 (0.0532) time: 3.2214 data: 0.1226 max mem: 33369 +Epoch: [21] [ 20/1319] eta: 1:07:44 lr: 2.5566223913807464e-05 loss: 0.0412 (0.0585) time: 3.0638 data: 0.0078 max mem: 33369 +Epoch: [21] [ 30/1319] eta: 1:06:26 lr: 2.5557034592303224e-05 loss: 0.0425 (0.0549) time: 3.0219 data: 0.0076 max mem: 33369 +Epoch: [21] [ 40/1319] eta: 1:05:46 lr: 2.5547844903659336e-05 loss: 0.0468 (0.0530) time: 3.0406 data: 0.0076 max mem: 33369 +Epoch: [21] [ 50/1319] eta: 1:04:57 lr: 2.5538654847714393e-05 loss: 0.0457 (0.0526) time: 3.0392 data: 0.0075 max mem: 33369 +Epoch: [21] [ 60/1319] eta: 1:04:08 lr: 2.552946442430683e-05 loss: 0.0399 (0.0509) time: 2.9987 data: 0.0074 max mem: 33369 +Epoch: [21] [ 70/1319] eta: 1:03:27 lr: 2.552027363327497e-05 loss: 0.0448 (0.0510) time: 2.9879 data: 0.0075 max mem: 33369 +Epoch: [21] [ 80/1319] eta: 1:02:43 lr: 2.551108247445699e-05 loss: 0.0459 (0.0502) time: 2.9788 data: 0.0077 max mem: 33369 +Epoch: [21] [ 90/1319] eta: 1:01:43 lr: 2.5501890947690927e-05 loss: 0.0401 (0.0495) time: 2.8905 data: 0.0079 max mem: 33369 +Epoch: [21] [ 100/1319] eta: 1:00:41 lr: 2.5492699052814688e-05 loss: 0.0469 (0.0503) time: 2.7846 data: 0.0076 max mem: 33369 +Epoch: [21] [ 110/1319] eta: 0:59:35 lr: 2.548350678966605e-05 loss: 0.0478 (0.0496) time: 2.7013 data: 0.0074 max mem: 33369 +Epoch: [21] [ 120/1319] eta: 0:58:29 lr: 2.547431415808263e-05 loss: 0.0402 (0.0496) time: 2.6202 data: 0.0070 max mem: 33369 +Epoch: [21] [ 130/1319] eta: 0:57:35 lr: 2.5465121157901932e-05 loss: 0.0414 (0.0489) time: 2.6240 data: 0.0067 max mem: 33369 +Epoch: [21] [ 140/1319] eta: 0:56:41 lr: 2.5455927788961316e-05 loss: 0.0414 (0.0484) time: 2.6303 data: 0.0068 max mem: 33369 +Epoch: [21] [ 150/1319] eta: 0:55:58 lr: 2.5446734051098e-05 loss: 0.0419 (0.0479) time: 2.6520 data: 0.0068 max mem: 33369 +Epoch: [21] [ 160/1319] eta: 0:55:23 lr: 2.5437539944149068e-05 loss: 0.0451 (0.0485) time: 2.7466 data: 0.0072 max mem: 33369 +Epoch: [21] [ 170/1319] eta: 0:54:56 lr: 2.542834546795147e-05 loss: 0.0483 (0.0490) time: 2.8418 data: 0.0077 max mem: 33369 +Epoch: [21] [ 180/1319] eta: 0:54:25 lr: 2.5419150622342014e-05 loss: 0.0509 (0.0495) time: 2.8642 data: 0.0077 max mem: 33369 +Epoch: [21] [ 190/1319] eta: 0:53:58 lr: 2.5409955407157366e-05 loss: 0.0509 (0.0493) time: 2.8605 data: 0.0078 max mem: 33369 +Epoch: [21] [ 200/1319] eta: 0:53:30 lr: 2.5400759822234066e-05 loss: 0.0368 (0.0491) time: 2.8878 data: 0.0078 max mem: 33369 +Epoch: [21] [ 210/1319] eta: 0:53:01 lr: 2.539156386740852e-05 loss: 0.0422 (0.0492) time: 2.8785 data: 0.0078 max mem: 33369 +Epoch: [21] [ 220/1319] eta: 0:52:37 lr: 2.538236754251696e-05 loss: 0.0434 (0.0492) time: 2.9132 data: 0.0078 max mem: 33369 +Epoch: [21] [ 230/1319] eta: 0:52:10 lr: 2.5373170847395516e-05 loss: 0.0434 (0.0489) time: 2.9369 data: 0.0076 max mem: 33369 +Epoch: [21] [ 240/1319] eta: 0:51:41 lr: 2.536397378188018e-05 loss: 0.0407 (0.0487) time: 2.8897 data: 0.0077 max mem: 33369 +Epoch: [21] [ 250/1319] eta: 0:51:19 lr: 2.5354776345806775e-05 loss: 0.0485 (0.0491) time: 2.9437 data: 0.0077 max mem: 33369 +Epoch: [21] [ 260/1319] eta: 0:50:52 lr: 2.534557853901102e-05 loss: 0.0485 (0.0490) time: 2.9791 data: 0.0077 max mem: 33369 +Epoch: [21] [ 270/1319] eta: 0:50:25 lr: 2.5336380361328465e-05 loss: 0.0408 (0.0488) time: 2.9284 data: 0.0078 max mem: 33369 +Epoch: [21] [ 280/1319] eta: 0:49:56 lr: 2.532718181259454e-05 loss: 0.0406 (0.0487) time: 2.8997 data: 0.0079 max mem: 33369 +Epoch: [21] [ 290/1319] eta: 0:49:27 lr: 2.531798289264453e-05 loss: 0.0438 (0.0491) time: 2.8858 data: 0.0078 max mem: 33369 +Epoch: [21] [ 300/1319] eta: 0:49:00 lr: 2.5308783601313586e-05 loss: 0.0476 (0.0491) time: 2.9065 data: 0.0080 max mem: 33369 +Epoch: [21] [ 310/1319] eta: 0:48:31 lr: 2.52995839384367e-05 loss: 0.0396 (0.0488) time: 2.9092 data: 0.0080 max mem: 33369 +Epoch: [21] [ 320/1319] eta: 0:48:03 lr: 2.5290383903848747e-05 loss: 0.0435 (0.0490) time: 2.9055 data: 0.0079 max mem: 33369 +Epoch: [21] [ 330/1319] eta: 0:47:34 lr: 2.5281183497384443e-05 loss: 0.0415 (0.0489) time: 2.8910 data: 0.0079 max mem: 33369 +Epoch: [21] [ 340/1319] eta: 0:47:05 lr: 2.5271982718878386e-05 loss: 0.0434 (0.0491) time: 2.8698 data: 0.0082 max mem: 33369 +Epoch: [21] [ 350/1319] eta: 0:46:36 lr: 2.5262781568165e-05 loss: 0.0477 (0.0490) time: 2.8806 data: 0.0081 max mem: 33369 +Epoch: [21] [ 360/1319] eta: 0:46:07 lr: 2.5253580045078606e-05 loss: 0.0477 (0.0492) time: 2.8935 data: 0.0081 max mem: 33369 +Epoch: [21] [ 370/1319] eta: 0:45:39 lr: 2.5244378149453368e-05 loss: 0.0415 (0.0490) time: 2.8961 data: 0.0082 max mem: 33369 +Epoch: [21] [ 380/1319] eta: 0:45:10 lr: 2.5235175881123296e-05 loss: 0.0398 (0.0489) time: 2.8867 data: 0.0082 max mem: 33369 +Epoch: [21] [ 390/1319] eta: 0:44:42 lr: 2.5225973239922274e-05 loss: 0.0398 (0.0488) time: 2.9000 data: 0.0081 max mem: 33369 +Epoch: [21] [ 400/1319] eta: 0:44:12 lr: 2.5216770225684038e-05 loss: 0.0472 (0.0488) time: 2.8965 data: 0.0081 max mem: 33369 +Epoch: [21] [ 410/1319] eta: 0:43:44 lr: 2.520756683824219e-05 loss: 0.0472 (0.0490) time: 2.8909 data: 0.0080 max mem: 33369 +Epoch: [21] [ 420/1319] eta: 0:43:15 lr: 2.5198363077430187e-05 loss: 0.0580 (0.0493) time: 2.8963 data: 0.0080 max mem: 33369 +Epoch: [21] [ 430/1319] eta: 0:42:46 lr: 2.5189158943081348e-05 loss: 0.0505 (0.0494) time: 2.8773 data: 0.0081 max mem: 33369 +Epoch: [21] [ 440/1319] eta: 0:42:17 lr: 2.5179954435028824e-05 loss: 0.0434 (0.0492) time: 2.8857 data: 0.0081 max mem: 33369 +Epoch: [21] [ 450/1319] eta: 0:41:49 lr: 2.517074955310566e-05 loss: 0.0419 (0.0491) time: 2.9018 data: 0.0081 max mem: 33369 +Epoch: [21] [ 460/1319] eta: 0:41:19 lr: 2.5161544297144735e-05 loss: 0.0444 (0.0495) time: 2.8717 data: 0.0082 max mem: 33369 +Epoch: [21] [ 470/1319] eta: 0:40:51 lr: 2.5152338666978798e-05 loss: 0.0436 (0.0494) time: 2.8889 data: 0.0082 max mem: 33369 +Epoch: [21] [ 480/1319] eta: 0:40:21 lr: 2.5143132662440454e-05 loss: 0.0406 (0.0493) time: 2.8943 data: 0.0080 max mem: 33369 +Epoch: [21] [ 490/1319] eta: 0:39:51 lr: 2.513392628336215e-05 loss: 0.0406 (0.0493) time: 2.8343 data: 0.0078 max mem: 33369 +Epoch: [21] [ 500/1319] eta: 0:39:20 lr: 2.5124719529576212e-05 loss: 0.0474 (0.0494) time: 2.7592 data: 0.0077 max mem: 33369 +Epoch: [21] [ 510/1319] eta: 0:38:48 lr: 2.51155124009148e-05 loss: 0.0457 (0.0494) time: 2.7004 data: 0.0075 max mem: 33369 +Epoch: [21] [ 520/1319] eta: 0:38:17 lr: 2.5106304897209954e-05 loss: 0.0415 (0.0494) time: 2.7075 data: 0.0073 max mem: 33369 +Epoch: [21] [ 530/1319] eta: 0:37:45 lr: 2.5097097018293553e-05 loss: 0.0363 (0.0492) time: 2.6878 data: 0.0072 max mem: 33369 +Epoch: [21] [ 540/1319] eta: 0:37:15 lr: 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data: 0.0082 max mem: 33369 +Epoch: [21] [ 780/1319] eta: 0:25:49 lr: 2.4866777606924187e-05 loss: 0.0454 (0.0494) time: 2.8807 data: 0.0081 max mem: 33369 +Epoch: [21] [ 790/1319] eta: 0:25:21 lr: 2.4857559913023423e-05 loss: 0.0444 (0.0493) time: 2.8804 data: 0.0081 max mem: 33369 +Epoch: [21] [ 800/1319] eta: 0:24:52 lr: 2.4848341839316978e-05 loss: 0.0406 (0.0492) time: 2.8952 data: 0.0081 max mem: 33369 +Epoch: [21] [ 810/1319] eta: 0:24:23 lr: 2.483912338563262e-05 loss: 0.0406 (0.0493) time: 2.8968 data: 0.0082 max mem: 33369 +Epoch: [21] [ 820/1319] eta: 0:23:55 lr: 2.4829904551797996e-05 loss: 0.0602 (0.0495) time: 2.8829 data: 0.0083 max mem: 33369 +Epoch: [21] [ 830/1319] eta: 0:23:26 lr: 2.4820685337640587e-05 loss: 0.0602 (0.0497) time: 2.8612 data: 0.0084 max mem: 33369 +Epoch: [21] [ 840/1319] eta: 0:22:57 lr: 2.481146574298773e-05 loss: 0.0549 (0.0497) time: 2.8572 data: 0.0083 max mem: 33369 +Epoch: [21] [ 850/1319] eta: 0:22:28 lr: 2.480224576766661e-05 loss: 0.0455 (0.0496) time: 2.8701 data: 0.0081 max mem: 33369 +Epoch: [21] [ 860/1319] eta: 0:21:59 lr: 2.4793025411504282e-05 loss: 0.0473 (0.0497) time: 2.8581 data: 0.0083 max mem: 33369 +Epoch: [21] [ 870/1319] eta: 0:21:30 lr: 2.4783804674327604e-05 loss: 0.0458 (0.0496) time: 2.8172 data: 0.0081 max mem: 33369 +Epoch: [21] [ 880/1319] eta: 0:21:01 lr: 2.4774583555963328e-05 loss: 0.0351 (0.0495) time: 2.7715 data: 0.0079 max mem: 33369 +Epoch: [21] [ 890/1319] eta: 0:20:31 lr: 2.4765362056238035e-05 loss: 0.0464 (0.0496) time: 2.7029 data: 0.0077 max mem: 33369 +Epoch: [21] [ 900/1319] eta: 0:20:01 lr: 2.4756140174978167e-05 loss: 0.0504 (0.0497) time: 2.6382 data: 0.0075 max mem: 33369 +Epoch: [21] [ 910/1319] eta: 0:19:31 lr: 2.4746917912010012e-05 loss: 0.0477 (0.0497) time: 2.6456 data: 0.0074 max mem: 33369 +Epoch: [21] [ 920/1319] eta: 0:19:02 lr: 2.4737695267159685e-05 loss: 0.0482 (0.0497) time: 2.7142 data: 0.0073 max mem: 33369 +Epoch: [21] [ 930/1319] eta: 0:18:34 lr: 2.4728472240253183e-05 loss: 0.0482 (0.0497) time: 2.8250 data: 0.0073 max mem: 33369 +Epoch: [21] [ 940/1319] eta: 0:18:05 lr: 2.4719248831116334e-05 loss: 0.0412 (0.0496) time: 2.8755 data: 0.0075 max mem: 33369 +Epoch: [21] [ 950/1319] eta: 0:17:37 lr: 2.4710025039574813e-05 loss: 0.0412 (0.0496) time: 2.8717 data: 0.0077 max mem: 33369 +Epoch: [21] [ 960/1319] eta: 0:17:08 lr: 2.4700800865454158e-05 loss: 0.0395 (0.0496) time: 2.8805 data: 0.0075 max mem: 33369 +Epoch: [21] [ 970/1319] eta: 0:16:39 lr: 2.469157630857973e-05 loss: 0.0471 (0.0497) time: 2.8780 data: 0.0075 max mem: 33369 +Epoch: [21] [ 980/1319] eta: 0:16:11 lr: 2.4682351368776758e-05 loss: 0.0411 (0.0495) time: 2.9186 data: 0.0076 max mem: 33369 +Epoch: [21] [ 990/1319] eta: 0:15:43 lr: 2.467312604587031e-05 loss: 0.0382 (0.0495) time: 2.9471 data: 0.0077 max mem: 33369 +Epoch: [21] [1000/1319] eta: 0:15:14 lr: 2.4663900339685314e-05 loss: 0.0463 (0.0495) time: 2.9259 data: 0.0076 max mem: 33369 +Epoch: [21] [1010/1319] eta: 0:14:46 lr: 2.4654674250046523e-05 loss: 0.0538 (0.0496) time: 2.9139 data: 0.0075 max mem: 33369 +Epoch: [21] [1020/1319] eta: 0:14:17 lr: 2.464544777677856e-05 loss: 0.0517 (0.0497) time: 2.9081 data: 0.0076 max mem: 33369 +Epoch: [21] [1030/1319] eta: 0:13:49 lr: 2.4636220919705875e-05 loss: 0.0447 (0.0497) time: 2.9420 data: 0.0076 max mem: 33369 +Epoch: [21] [1040/1319] eta: 0:13:20 lr: 2.4626993678652773e-05 loss: 0.0467 (0.0499) time: 2.9448 data: 0.0076 max mem: 33369 +Epoch: [21] [1050/1319] eta: 0:12:51 lr: 2.4617766053443412e-05 loss: 0.0439 (0.0499) time: 2.9032 data: 0.0075 max mem: 33369 +Epoch: [21] [1060/1319] eta: 0:12:23 lr: 2.4608538043901786e-05 loss: 0.0415 (0.0499) time: 2.8787 data: 0.0075 max mem: 33369 +Epoch: [21] [1070/1319] eta: 0:11:54 lr: 2.4599309649851742e-05 loss: 0.0403 (0.0498) time: 2.8676 data: 0.0076 max mem: 33369 +Epoch: [21] [1080/1319] eta: 0:11:25 lr: 2.4590080871116966e-05 loss: 0.0468 (0.0498) time: 2.8564 data: 0.0077 max mem: 33369 +Epoch: [21] [1090/1319] eta: 0:10:57 lr: 2.4580851707520996e-05 loss: 0.0453 (0.0498) time: 2.8679 data: 0.0075 max mem: 33369 +Epoch: [21] [1100/1319] eta: 0:10:28 lr: 2.457162215888721e-05 loss: 0.0429 (0.0497) time: 2.8611 data: 0.0077 max mem: 33369 +Epoch: [21] [1110/1319] eta: 0:09:59 lr: 2.456239222503884e-05 loss: 0.0479 (0.0498) time: 2.8632 data: 0.0080 max mem: 33369 +Epoch: [21] [1120/1319] eta: 0:09:31 lr: 2.455316190579896e-05 loss: 0.0485 (0.0498) time: 2.8810 data: 0.0082 max mem: 33369 +Epoch: [21] [1130/1319] eta: 0:09:02 lr: 2.4543931200990468e-05 loss: 0.0461 (0.0498) time: 2.8772 data: 0.0082 max mem: 33369 +Epoch: [21] [1140/1319] eta: 0:08:33 lr: 2.4534700110436136e-05 loss: 0.0442 (0.0497) time: 2.8759 data: 0.0082 max mem: 33369 +Epoch: [21] [1150/1319] eta: 0:08:04 lr: 2.452546863395857e-05 loss: 0.0450 (0.0497) time: 2.8733 data: 0.0081 max mem: 33369 +Epoch: [21] [1160/1319] eta: 0:07:36 lr: 2.451623677138022e-05 loss: 0.0467 (0.0497) time: 2.8740 data: 0.0079 max mem: 33369 +Epoch: [21] [1170/1319] eta: 0:07:07 lr: 2.4507004522523372e-05 loss: 0.0507 (0.0497) time: 2.8530 data: 0.0080 max mem: 33369 +Epoch: [21] [1180/1319] eta: 0:06:38 lr: 2.4497771887210175e-05 loss: 0.0412 (0.0496) time: 2.8462 data: 0.0081 max mem: 33369 +Epoch: [21] [1190/1319] eta: 0:06:10 lr: 2.4488538865262596e-05 loss: 0.0389 (0.0496) time: 2.8554 data: 0.0081 max mem: 33369 +Epoch: [21] [1200/1319] eta: 0:05:41 lr: 2.4479305456502462e-05 loss: 0.0446 (0.0496) time: 2.8528 data: 0.0082 max mem: 33369 +Epoch: [21] [1210/1319] eta: 0:05:12 lr: 2.4470071660751444e-05 loss: 0.0462 (0.0496) time: 2.8435 data: 0.0083 max mem: 33369 +Epoch: [21] [1220/1319] eta: 0:04:44 lr: 2.446083747783105e-05 loss: 0.0416 (0.0496) time: 2.8650 data: 0.0083 max mem: 33369 +Epoch: [21] [1230/1319] eta: 0:04:15 lr: 2.4451602907562637e-05 loss: 0.0405 (0.0496) time: 2.8748 data: 0.0084 max mem: 33369 +Epoch: [21] [1240/1319] eta: 0:03:46 lr: 2.4442367949767393e-05 loss: 0.0391 (0.0496) time: 2.8724 data: 0.0083 max mem: 33369 +Epoch: [21] [1250/1319] eta: 0:03:17 lr: 2.4433132604266355e-05 loss: 0.0391 (0.0495) time: 2.8323 data: 0.0081 max mem: 33369 +Epoch: [21] [1260/1319] eta: 0:02:49 lr: 2.442389687088041e-05 loss: 0.0377 (0.0495) time: 2.7853 data: 0.0082 max mem: 33369 +Epoch: [21] [1270/1319] eta: 0:02:20 lr: 2.441466074943027e-05 loss: 0.0391 (0.0495) time: 2.7386 data: 0.0079 max mem: 33369 +Epoch: [21] [1280/1319] eta: 0:01:51 lr: 2.440542423973651e-05 loss: 0.0415 (0.0495) time: 2.6755 data: 0.0072 max mem: 33369 +Epoch: [21] [1290/1319] eta: 0:01:23 lr: 2.439618734161953e-05 loss: 0.0449 (0.0495) time: 2.6493 data: 0.0069 max mem: 33369 +Epoch: [21] [1300/1319] eta: 0:00:54 lr: 2.4386950054899575e-05 loss: 0.0475 (0.0495) time: 2.6339 data: 0.0067 max mem: 33369 +Epoch: [21] [1310/1319] eta: 0:00:25 lr: 2.4377712379396728e-05 loss: 0.0472 (0.0496) time: 2.6456 data: 0.0066 max mem: 33369 +Epoch: [21] Total time: 1:02:50 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 2:19:10 time: 3.2456 data: 3.1361 max mem: 33369 +Test: [ 100/2573] eta: 0:04:18 time: 0.0728 data: 0.0012 max mem: 33369 +Test: [ 200/2573] eta: 0:03:34 time: 0.0754 data: 0.0014 max mem: 33369 +Test: [ 300/2573] eta: 0:03:12 time: 0.0770 data: 0.0013 max mem: 33369 +Test: [ 400/2573] eta: 0:02:59 time: 0.0769 data: 0.0013 max mem: 33369 +Test: [ 500/2573] eta: 0:02:47 time: 0.0754 data: 0.0013 max mem: 33369 +Test: [ 600/2573] eta: 0:02:38 time: 0.0754 data: 0.0013 max mem: 33369 +Test: [ 700/2573] eta: 0:02:29 time: 0.0753 data: 0.0014 max mem: 33369 +Test: [ 800/2573] eta: 0:02:20 time: 0.0789 data: 0.0014 max mem: 33369 +Test: [ 900/2573] eta: 0:02:12 time: 0.0755 data: 0.0014 max mem: 33369 +Test: [1000/2573] eta: 0:02:03 time: 0.0753 data: 0.0014 max mem: 33369 +Test: [1100/2573] eta: 0:01:55 time: 0.0754 data: 0.0013 max mem: 33369 +Test: [1200/2573] eta: 0:01:47 time: 0.0754 data: 0.0013 max mem: 33369 +Test: [1300/2573] eta: 0:01:39 time: 0.0757 data: 0.0014 max mem: 33369 +Test: [1400/2573] eta: 0:01:31 time: 0.0738 data: 0.0013 max mem: 33369 +Test: [1500/2573] eta: 0:01:23 time: 0.0754 data: 0.0013 max mem: 33369 +Test: [1600/2573] eta: 0:01:15 time: 0.0788 data: 0.0013 max mem: 33369 +Test: [1700/2573] eta: 0:01:07 time: 0.0738 data: 0.0013 max mem: 33369 +Test: [1800/2573] eta: 0:00:59 time: 0.0771 data: 0.0013 max mem: 33369 +Test: [1900/2573] eta: 0:00:51 time: 0.0739 data: 0.0014 max mem: 33369 +Test: [2000/2573] eta: 0:00:44 time: 0.0755 data: 0.0013 max mem: 33369 +Test: [2100/2573] eta: 0:00:36 time: 0.0773 data: 0.0013 max mem: 33369 +Test: [2200/2573] eta: 0:00:28 time: 0.0773 data: 0.0013 max mem: 33369 +Test: [2300/2573] eta: 0:00:20 time: 0.0775 data: 0.0014 max mem: 33369 +Test: [2400/2573] eta: 0:00:13 time: 0.0723 data: 0.0014 max mem: 33369 +Test: [2500/2573] eta: 0:00:05 time: 0.0757 data: 0.0014 max mem: 33369 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: Total time: 0:03:17 +Final results: +Mean IoU is 63.53 + + precision@0.5 = 71.22 + precision@0.6 = 65.67 + precision@0.7 = 57.84 + precision@0.8 = 45.92 + precision@0.9 = 22.43 + overall IoU = 61.25 + +Average object IoU 63.533942318925305 +Overall IoU 61.25382995605469 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [22] [ 0/1319] eta: 3:13:17 lr: 2.4369398138885975e-05 loss: 0.0891 (0.0891) time: 8.7923 data: 1.4226 max mem: 33369 +Epoch: [22] [ 10/1319] eta: 1:16:13 lr: 2.436015972419942e-05 loss: 0.0551 (0.0638) time: 3.4938 data: 0.1366 max mem: 33369 +Epoch: [22] [ 20/1319] eta: 1:09:57 lr: 2.4350920920207323e-05 loss: 0.0504 (0.0588) time: 2.9531 data: 0.0072 max mem: 33369 +Epoch: [22] [ 30/1319] eta: 1:07:23 lr: 2.4341681726729162e-05 loss: 0.0446 (0.0574) time: 2.9401 data: 0.0070 max mem: 33369 +Epoch: [22] [ 40/1319] eta: 1:05:52 lr: 2.4332442143584247e-05 loss: 0.0421 (0.0551) time: 2.9432 data: 0.0076 max mem: 33369 +Epoch: [22] [ 50/1319] eta: 1:04:35 lr: 2.4323202170591704e-05 loss: 0.0447 (0.0540) time: 2.9268 data: 0.0077 max mem: 33369 +Epoch: [22] [ 60/1319] eta: 1:03:34 lr: 2.4313961807570534e-05 loss: 0.0514 (0.0544) time: 2.9044 data: 0.0079 max mem: 33369 +Epoch: [22] [ 70/1319] eta: 1:02:39 lr: 2.430472105433956e-05 loss: 0.0496 (0.0532) time: 2.8973 data: 0.0078 max mem: 33369 +Epoch: [22] [ 80/1319] eta: 1:01:50 lr: 2.4295479910717442e-05 loss: 0.0387 (0.0514) time: 2.8892 data: 0.0077 max mem: 33369 +Epoch: [22] [ 90/1319] eta: 1:01:09 lr: 2.4286238376522685e-05 loss: 0.0410 (0.0515) time: 2.8978 data: 0.0078 max mem: 33369 +Epoch: [22] [ 100/1319] eta: 1:00:27 lr: 2.4276996451573638e-05 loss: 0.0431 (0.0516) time: 2.8999 data: 0.0078 max mem: 33369 +Epoch: [22] [ 110/1319] eta: 0:59:49 lr: 2.426775413568847e-05 loss: 0.0414 (0.0509) time: 2.8960 data: 0.0078 max mem: 33369 +Epoch: [22] [ 120/1319] eta: 0:59:06 lr: 2.4258511428685206e-05 loss: 0.0420 (0.0507) time: 2.8658 data: 0.0083 max mem: 33369 +Epoch: [22] [ 130/1319] eta: 0:58:24 lr: 2.4249268330381702e-05 loss: 0.0359 (0.0501) time: 2.8270 data: 0.0084 max mem: 33369 +Epoch: [22] [ 140/1319] eta: 0:57:49 lr: 2.4240024840595657e-05 loss: 0.0377 (0.0500) time: 2.8496 data: 0.0081 max mem: 33369 +Epoch: [22] [ 150/1319] eta: 0:57:15 lr: 2.4230780959144606e-05 loss: 0.0444 (0.0498) time: 2.8820 data: 0.0080 max mem: 33369 +Epoch: [22] [ 160/1319] eta: 0:56:41 lr: 2.4221536685845908e-05 loss: 0.0444 (0.0501) time: 2.8817 data: 0.0082 max mem: 33369 +Epoch: [22] [ 170/1319] eta: 0:56:07 lr: 2.421229202051678e-05 loss: 0.0413 (0.0495) time: 2.8703 data: 0.0081 max mem: 33369 +Epoch: [22] [ 180/1319] eta: 0:55:33 lr: 2.420304696297427e-05 loss: 0.0391 (0.0493) time: 2.8636 data: 0.0079 max mem: 33369 +Epoch: [22] [ 190/1319] eta: 0:54:59 lr: 2.419380151303525e-05 loss: 0.0396 (0.0490) time: 2.8516 data: 0.0082 max mem: 33369 +Epoch: [22] [ 200/1319] eta: 0:54:29 lr: 2.418455567051645e-05 loss: 0.0427 (0.0489) time: 2.8716 data: 0.0083 max mem: 33369 +Epoch: [22] [ 210/1319] eta: 0:53:58 lr: 2.417530943523442e-05 loss: 0.0454 (0.0488) time: 2.8943 data: 0.0081 max mem: 33369 +Epoch: [22] [ 220/1319] eta: 0:53:24 lr: 2.416606280700555e-05 loss: 0.0377 (0.0482) time: 2.8620 data: 0.0079 max mem: 33369 +Epoch: [22] [ 230/1319] eta: 0:52:56 lr: 2.4156815785646067e-05 loss: 0.0376 (0.0482) time: 2.8888 data: 0.0080 max mem: 33369 +Epoch: [22] [ 240/1319] eta: 0:52:25 lr: 2.414756837097204e-05 loss: 0.0452 (0.0482) time: 2.9074 data: 0.0082 max mem: 33369 +Epoch: [22] [ 250/1319] eta: 0:51:55 lr: 2.4138320562799363e-05 loss: 0.0446 (0.0484) time: 2.8764 data: 0.0084 max mem: 33369 +Epoch: [22] [ 260/1319] eta: 0:51:24 lr: 2.412907236094378e-05 loss: 0.0459 (0.0484) time: 2.8843 data: 0.0082 max mem: 33369 +Epoch: [22] [ 270/1319] eta: 0:50:51 lr: 2.411982376522085e-05 loss: 0.0449 (0.0482) time: 2.8477 data: 0.0078 max mem: 33369 +Epoch: [22] [ 280/1319] eta: 0:50:12 lr: 2.411057477544598e-05 loss: 0.0449 (0.0483) time: 2.7183 data: 0.0078 max mem: 33369 +Epoch: [22] [ 290/1319] eta: 0:49:34 lr: 2.4101325391434414e-05 loss: 0.0446 (0.0483) time: 2.6386 data: 0.0077 max mem: 33369 +Epoch: [22] [ 300/1319] eta: 0:48:59 lr: 2.4092075613001218e-05 loss: 0.0425 (0.0483) time: 2.6767 data: 0.0074 max mem: 33369 +Epoch: [22] [ 310/1319] eta: 0:48:23 lr: 2.4082825439961318e-05 loss: 0.0414 (0.0481) time: 2.6889 data: 0.0072 max mem: 33369 +Epoch: [22] [ 320/1319] eta: 0:47:51 lr: 2.4073574872129434e-05 loss: 0.0400 (0.0479) time: 2.7282 data: 0.0072 max mem: 33369 +Epoch: [22] [ 330/1319] eta: 0:47:25 lr: 2.4064323909320154e-05 loss: 0.0443 (0.0478) time: 2.8664 data: 0.0077 max mem: 33369 +Epoch: [22] [ 340/1319] eta: 0:46:57 lr: 2.405507255134789e-05 loss: 0.0484 (0.0481) time: 2.9278 data: 0.0080 max mem: 33369 +Epoch: [22] [ 350/1319] eta: 0:46:29 lr: 2.404582079802688e-05 loss: 0.0484 (0.0480) time: 2.9085 data: 0.0079 max mem: 33369 +Epoch: [22] [ 360/1319] eta: 0:46:02 lr: 2.4036568649171213e-05 loss: 0.0442 (0.0479) time: 2.9251 data: 0.0078 max mem: 33369 +Epoch: [22] [ 370/1319] eta: 0:45:35 lr: 2.402731610459478e-05 loss: 0.0416 (0.0478) time: 2.9469 data: 0.0077 max mem: 33369 +Epoch: [22] [ 380/1319] eta: 0:45:06 lr: 2.401806316411133e-05 loss: 0.0426 (0.0477) time: 2.9247 data: 0.0076 max mem: 33369 +Epoch: [22] [ 390/1319] eta: 0:44:40 lr: 2.400880982753445e-05 loss: 0.0437 (0.0479) time: 2.9359 data: 0.0075 max mem: 33369 +Epoch: [22] [ 400/1319] eta: 0:44:11 lr: 2.399955609467753e-05 loss: 0.0514 (0.0480) time: 2.9338 data: 0.0075 max mem: 33369 +Epoch: [22] [ 410/1319] eta: 0:43:43 lr: 2.3990301965353823e-05 loss: 0.0481 (0.0479) time: 2.9156 data: 0.0074 max mem: 33369 +Epoch: [22] [ 420/1319] eta: 0:43:16 lr: 2.39810474393764e-05 loss: 0.0387 (0.0478) time: 2.9368 data: 0.0074 max mem: 33369 +Epoch: [22] [ 430/1319] eta: 0:42:48 lr: 2.3971792516558155e-05 loss: 0.0387 (0.0478) time: 2.9342 data: 0.0075 max mem: 33369 +Epoch: [22] [ 440/1319] eta: 0:42:20 lr: 2.3962537196711826e-05 loss: 0.0456 (0.0478) time: 2.9317 data: 0.0077 max mem: 33369 +Epoch: [22] [ 450/1319] eta: 0:41:51 lr: 2.3953281479649982e-05 loss: 0.0490 (0.0478) time: 2.9290 data: 0.0080 max mem: 33369 +Epoch: [22] [ 460/1319] eta: 0:41:23 lr: 2.394402536518502e-05 loss: 0.0425 (0.0477) time: 2.9275 data: 0.0080 max mem: 33369 +Epoch: [22] [ 470/1319] eta: 0:40:55 lr: 2.3934768853129168e-05 loss: 0.0376 (0.0475) time: 2.9169 data: 0.0079 max mem: 33369 +Epoch: [22] [ 480/1319] eta: 0:40:26 lr: 2.3925511943294477e-05 loss: 0.0346 (0.0475) time: 2.9076 data: 0.0078 max mem: 33369 +Epoch: [22] [ 490/1319] eta: 0:39:57 lr: 2.3916254635492843e-05 loss: 0.0420 (0.0476) time: 2.8993 data: 0.0078 max mem: 33369 +Epoch: [22] [ 500/1319] eta: 0:39:27 lr: 2.390699692953598e-05 loss: 0.0421 (0.0475) time: 2.8708 data: 0.0081 max mem: 33369 +Epoch: [22] [ 510/1319] eta: 0:38:58 lr: 2.3897738825235443e-05 loss: 0.0451 (0.0475) time: 2.8671 data: 0.0081 max mem: 33369 +Epoch: [22] [ 520/1319] eta: 0:38:29 lr: 2.3888480322402605e-05 loss: 0.0449 (0.0473) time: 2.8678 data: 0.0080 max mem: 33369 +Epoch: [22] [ 530/1319] eta: 0:38:00 lr: 2.3879221420848673e-05 loss: 0.0418 (0.0474) time: 2.8804 data: 0.0080 max mem: 33369 +Epoch: [22] [ 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data: 0.0067 max mem: 33369 +Epoch: [22] [ 700/1319] eta: 0:29:33 lr: 2.3721758906333604e-05 loss: 0.0437 (0.0473) time: 2.6250 data: 0.0067 max mem: 33369 +Epoch: [22] [ 710/1319] eta: 0:29:02 lr: 2.3712492795320653e-05 loss: 0.0414 (0.0473) time: 2.6471 data: 0.0068 max mem: 33369 +Epoch: [22] [ 720/1319] eta: 0:28:34 lr: 2.3703226281966838e-05 loss: 0.0449 (0.0475) time: 2.7509 data: 0.0074 max mem: 33369 +Epoch: [22] [ 730/1319] eta: 0:28:05 lr: 2.36939593660799e-05 loss: 0.0449 (0.0476) time: 2.8456 data: 0.0078 max mem: 33369 +Epoch: [22] [ 740/1319] eta: 0:27:37 lr: 2.3684692047467423e-05 loss: 0.0469 (0.0477) time: 2.8936 data: 0.0078 max mem: 33369 +Epoch: [22] [ 750/1319] eta: 0:27:08 lr: 2.3675424325936787e-05 loss: 0.0427 (0.0476) time: 2.9042 data: 0.0078 max mem: 33369 +Epoch: [22] [ 760/1319] eta: 0:26:40 lr: 2.3666156201295225e-05 loss: 0.0406 (0.0476) time: 2.8904 data: 0.0077 max mem: 33369 +Epoch: [22] [ 770/1319] eta: 0:26:11 lr: 2.3656887673349775e-05 loss: 0.0410 (0.0475) time: 2.8867 data: 0.0077 max mem: 33369 +Epoch: [22] [ 780/1319] eta: 0:25:43 lr: 2.364761874190731e-05 loss: 0.0445 (0.0475) time: 2.8940 data: 0.0077 max mem: 33369 +Epoch: [22] [ 790/1319] eta: 0:25:15 lr: 2.363834940677452e-05 loss: 0.0461 (0.0476) time: 2.9251 data: 0.0075 max mem: 33369 +Epoch: [22] [ 800/1319] eta: 0:24:47 lr: 2.3629079667757912e-05 loss: 0.0493 (0.0477) time: 2.9214 data: 0.0076 max mem: 33369 +Epoch: [22] [ 810/1319] eta: 0:24:19 lr: 2.361980952466383e-05 loss: 0.0493 (0.0478) time: 2.9382 data: 0.0075 max mem: 33369 +Epoch: [22] [ 820/1319] eta: 0:23:50 lr: 2.3610538977298433e-05 loss: 0.0428 (0.0477) time: 2.9418 data: 0.0076 max mem: 33369 +Epoch: [22] [ 830/1319] eta: 0:23:22 lr: 2.3601268025467702e-05 loss: 0.0416 (0.0477) time: 2.9192 data: 0.0079 max mem: 33369 +Epoch: [22] [ 840/1319] eta: 0:22:53 lr: 2.3591996668977443e-05 loss: 0.0416 (0.0478) time: 2.9137 data: 0.0078 max mem: 33369 +Epoch: [22] [ 850/1319] eta: 0:22:25 lr: 2.3582724907633285e-05 loss: 0.0403 (0.0478) time: 2.8959 data: 0.0078 max mem: 33369 +Epoch: [22] [ 860/1319] eta: 0:21:56 lr: 2.3573452741240666e-05 loss: 0.0399 (0.0477) time: 2.8982 data: 0.0077 max mem: 33369 +Epoch: [22] [ 870/1319] eta: 0:21:28 lr: 2.3564180169604865e-05 loss: 0.0438 (0.0478) time: 2.9225 data: 0.0078 max mem: 33369 +Epoch: [22] [ 880/1319] eta: 0:20:59 lr: 2.3554907192530968e-05 loss: 0.0494 (0.0479) time: 2.9109 data: 0.0080 max mem: 33369 +Epoch: [22] [ 890/1319] eta: 0:20:31 lr: 2.3545633809823888e-05 loss: 0.0448 (0.0480) time: 2.8992 data: 0.0080 max mem: 33369 +Epoch: [22] [ 900/1319] eta: 0:20:03 lr: 2.353636002128836e-05 loss: 0.0430 (0.0479) time: 2.9184 data: 0.0078 max mem: 33369 +Epoch: [22] [ 910/1319] eta: 0:19:34 lr: 2.3527085826728933e-05 loss: 0.0416 (0.0479) time: 2.9015 data: 0.0078 max mem: 33369 +Epoch: [22] [ 920/1319] eta: 0:19:05 lr: 2.351781122594998e-05 loss: 0.0428 (0.0481) time: 2.8828 data: 0.0079 max mem: 33369 +Epoch: [22] [ 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33369 +Epoch: [22] [1010/1319] eta: 0:14:46 lr: 2.3434321506693e-05 loss: 0.0369 (0.0480) time: 2.8621 data: 0.0083 max mem: 33369 +Epoch: [22] [1020/1319] eta: 0:14:18 lr: 2.342504283291958e-05 loss: 0.0383 (0.0479) time: 2.8503 data: 0.0082 max mem: 33369 +Epoch: [22] [1030/1319] eta: 0:13:49 lr: 2.3415763750762803e-05 loss: 0.0336 (0.0480) time: 2.8889 data: 0.0081 max mem: 33369 +Epoch: [22] [1040/1319] eta: 0:13:20 lr: 2.3406484260024864e-05 loss: 0.0404 (0.0480) time: 2.9030 data: 0.0080 max mem: 33369 +Epoch: [22] [1050/1319] eta: 0:12:51 lr: 2.3397204360507778e-05 loss: 0.0478 (0.0480) time: 2.8049 data: 0.0078 max mem: 33369 +Epoch: [22] [1060/1319] eta: 0:12:22 lr: 2.3387924052013375e-05 loss: 0.0426 (0.0480) time: 2.7174 data: 0.0078 max mem: 33369 +Epoch: [22] [1070/1319] eta: 0:11:53 lr: 2.3378643334343302e-05 loss: 0.0384 (0.0479) time: 2.6588 data: 0.0076 max mem: 33369 +Epoch: [22] [1080/1319] eta: 0:11:24 lr: 2.3369362207299018e-05 loss: 0.0462 (0.0480) time: 2.6303 data: 0.0070 max mem: 33369 +Epoch: [22] [1090/1319] eta: 0:10:55 lr: 2.3360080670681804e-05 loss: 0.0464 (0.0480) time: 2.6627 data: 0.0069 max mem: 33369 +Epoch: [22] [1100/1319] eta: 0:10:26 lr: 2.335079872429276e-05 loss: 0.0372 (0.0479) time: 2.7809 data: 0.0072 max mem: 33369 +Epoch: [22] [1110/1319] eta: 0:09:58 lr: 2.334151636793279e-05 loss: 0.0379 (0.0479) time: 2.8858 data: 0.0078 max mem: 33369 +Epoch: [22] [1120/1319] eta: 0:09:29 lr: 2.333223360140262e-05 loss: 0.0445 (0.0479) time: 2.8961 data: 0.0079 max mem: 33369 +Epoch: [22] [1130/1319] eta: 0:09:01 lr: 2.3322950424502793e-05 loss: 0.0472 (0.0479) time: 2.8847 data: 0.0076 max mem: 33369 +Epoch: [22] [1140/1319] eta: 0:08:32 lr: 2.3313666837033663e-05 loss: 0.0468 (0.0479) time: 2.8680 data: 0.0076 max mem: 33369 +Epoch: [22] [1150/1319] eta: 0:08:03 lr: 2.33043828387954e-05 loss: 0.0416 (0.0479) time: 2.8754 data: 0.0078 max mem: 33369 +Epoch: [22] [1160/1319] eta: 0:07:35 lr: 2.3295098429587987e-05 loss: 0.0396 (0.0479) time: 2.9055 data: 0.0076 max mem: 33369 +Epoch: [22] [1170/1319] eta: 0:07:06 lr: 2.328581360921123e-05 loss: 0.0372 (0.0478) time: 2.9177 data: 0.0076 max mem: 33369 +Epoch: [22] [1180/1319] eta: 0:06:38 lr: 2.327652837746473e-05 loss: 0.0380 (0.0478) time: 2.9260 data: 0.0075 max mem: 33369 +Epoch: [22] [1190/1319] eta: 0:06:09 lr: 2.3267242734147912e-05 loss: 0.0401 (0.0477) time: 2.9261 data: 0.0076 max mem: 33369 +Epoch: [22] [1200/1319] eta: 0:05:40 lr: 2.325795667906002e-05 loss: 0.0401 (0.0477) time: 2.8992 data: 0.0078 max mem: 33369 +Epoch: [22] [1210/1319] eta: 0:05:12 lr: 2.3248670212000107e-05 loss: 0.0472 (0.0478) time: 2.9011 data: 0.0076 max mem: 33369 +Epoch: [22] [1220/1319] eta: 0:04:43 lr: 2.3239383332767037e-05 loss: 0.0515 (0.0478) time: 2.9087 data: 0.0075 max mem: 33369 +Epoch: [22] [1230/1319] eta: 0:04:15 lr: 2.323009604115948e-05 loss: 0.0422 (0.0478) time: 2.8955 data: 0.0074 max mem: 33369 +Epoch: [22] [1240/1319] eta: 0:03:46 lr: 2.322080833697593e-05 loss: 0.0420 (0.0478) time: 2.8794 data: 0.0076 max mem: 33369 +Epoch: [22] [1250/1319] eta: 0:03:17 lr: 2.3211520220014678e-05 loss: 0.0434 (0.0478) time: 2.8623 data: 0.0079 max mem: 33369 +Epoch: [22] [1260/1319] eta: 0:02:49 lr: 2.320223169007385e-05 loss: 0.0406 (0.0478) time: 2.8524 data: 0.0078 max mem: 33369 +Epoch: [22] [1270/1319] eta: 0:02:20 lr: 2.319294274695137e-05 loss: 0.0380 (0.0478) time: 2.8850 data: 0.0079 max mem: 33369 +Epoch: [22] [1280/1319] eta: 0:01:51 lr: 2.318365339044496e-05 loss: 0.0426 (0.0479) time: 2.8945 data: 0.0080 max mem: 33369 +Epoch: [22] [1290/1319] eta: 0:01:23 lr: 2.3174363620352174e-05 loss: 0.0476 (0.0479) time: 2.8677 data: 0.0080 max mem: 33369 +Epoch: [22] [1300/1319] eta: 0:00:54 lr: 2.3165073436470368e-05 loss: 0.0478 (0.0479) time: 2.8733 data: 0.0080 max mem: 33369 +Epoch: [22] [1310/1319] eta: 0:00:25 lr: 2.3155782838596706e-05 loss: 0.0491 (0.0480) time: 2.8719 data: 0.0078 max mem: 33369 +Epoch: [22] Total time: 1:03:01 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 2:06:38 time: 2.9531 data: 2.7593 max mem: 33369 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 100/2573] eta: 0:04:14 time: 0.0735 data: 0.0014 max mem: 33369 +Test: [ 200/2573] eta: 0:03:32 time: 0.0748 data: 0.0013 max mem: 33369 +Test: [ 300/2573] eta: 0:03:11 time: 0.0766 data: 0.0013 max mem: 33369 +Test: [ 400/2573] eta: 0:02:57 time: 0.0768 data: 0.0013 max mem: 33369 +Test: [ 500/2573] eta: 0:02:46 time: 0.0753 data: 0.0014 max mem: 33369 +Test: [ 600/2573] eta: 0:02:37 time: 0.0753 data: 0.0013 max mem: 33369 +Test: [ 700/2573] eta: 0:02:28 time: 0.0755 data: 0.0013 max mem: 33369 +Test: [ 800/2573] eta: 0:02:20 time: 0.0787 data: 0.0013 max mem: 33369 +Test: [ 900/2573] eta: 0:02:11 time: 0.0755 data: 0.0013 max mem: 33369 +Test: [1000/2573] eta: 0:02:03 time: 0.0755 data: 0.0014 max mem: 33369 +Test: [1100/2573] eta: 0:01:55 time: 0.0759 data: 0.0014 max mem: 33369 +Test: [1200/2573] eta: 0:01:47 time: 0.0755 data: 0.0013 max mem: 33369 +Test: [1300/2573] eta: 0:01:39 time: 0.0754 data: 0.0013 max mem: 33369 +Test: [1400/2573] eta: 0:01:31 time: 0.0738 data: 0.0014 max mem: 33369 +Test: [1500/2573] eta: 0:01:23 time: 0.0754 data: 0.0013 max mem: 33369 +Test: [1600/2573] eta: 0:01:15 time: 0.0790 data: 0.0014 max mem: 33369 +Test: [1700/2573] eta: 0:01:07 time: 0.0738 data: 0.0013 max mem: 33369 +Test: [1800/2573] eta: 0:00:59 time: 0.0773 data: 0.0014 max mem: 33369 +Test: [1900/2573] eta: 0:00:51 time: 0.0740 data: 0.0013 max mem: 33369 +Test: [2000/2573] eta: 0:00:44 time: 0.0757 data: 0.0014 max mem: 33369 +Test: [2100/2573] eta: 0:00:36 time: 0.0772 data: 0.0013 max mem: 33369 +Test: [2200/2573] eta: 0:00:28 time: 0.0772 data: 0.0013 max mem: 33369 +Test: [2300/2573] eta: 0:00:20 time: 0.0773 data: 0.0013 max mem: 33369 +Test: [2400/2573] eta: 0:00:13 time: 0.0723 data: 0.0014 max mem: 33369 +Test: [2500/2573] eta: 0:00:05 time: 0.0758 data: 0.0014 max mem: 33369 +Test: Total time: 0:03:17 +Final results: +Mean IoU is 63.56 + + precision@0.5 = 71.67 + precision@0.6 = 66.54 + precision@0.7 = 59.09 + precision@0.8 = 46.94 + precision@0.9 = 22.94 + overall IoU = 61.22 + +Average object IoU 63.55848583306876 +Overall IoU 61.215065002441406 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [23] [ 0/1319] eta: 3:30:36 lr: 2.3147420946379584e-05 loss: 0.0661 (0.0661) time: 9.5805 data: 1.9818 max mem: 33369 +Epoch: [23] [ 10/1319] eta: 1:17:22 lr: 2.313812956136191e-05 loss: 0.0353 (0.0415) time: 3.5469 data: 0.1866 max mem: 33369 +Epoch: [23] [ 20/1319] eta: 1:10:40 lr: 2.3128837761763095e-05 loss: 0.0424 (0.0477) time: 2.9488 data: 0.0073 max mem: 33369 +Epoch: [23] [ 30/1319] eta: 1:07:54 lr: 2.3119545547379566e-05 loss: 0.0457 (0.0505) time: 2.9487 data: 0.0076 max mem: 33369 +Epoch: [23] [ 40/1319] eta: 1:05:34 lr: 2.3110252918007542e-05 loss: 0.0400 (0.0492) time: 2.8789 data: 0.0077 max mem: 33369 +Epoch: [23] [ 50/1319] eta: 1:03:40 lr: 2.3100959873443074e-05 loss: 0.0356 (0.0482) time: 2.7773 data: 0.0074 max mem: 33369 +Epoch: [23] [ 60/1319] eta: 1:02:02 lr: 2.3091666413482015e-05 loss: 0.0400 (0.0470) time: 2.7124 data: 0.0070 max mem: 33369 +Epoch: [23] [ 70/1319] eta: 1:00:51 lr: 2.3082372537920018e-05 loss: 0.0415 (0.0476) time: 2.7029 data: 0.0068 max mem: 33369 +Epoch: [23] [ 80/1319] eta: 0:59:51 lr: 2.307307824655256e-05 loss: 0.0496 (0.0478) time: 2.7207 data: 0.0069 max mem: 33369 +Epoch: [23] [ 90/1319] eta: 0:58:45 lr: 2.3063783539174907e-05 loss: 0.0375 (0.0468) time: 2.6722 data: 0.0069 max mem: 33369 +Epoch: [23] [ 100/1319] eta: 0:57:48 lr: 2.3054488415582145e-05 loss: 0.0362 (0.0463) time: 2.6307 data: 0.0069 max mem: 33369 +Epoch: [23] [ 110/1319] eta: 0:57:26 lr: 2.3045192875569164e-05 loss: 0.0385 (0.0459) time: 2.7706 data: 0.0073 max mem: 33369 +Epoch: [23] [ 120/1319] eta: 0:57:01 lr: 2.3035896918930662e-05 loss: 0.0407 (0.0458) time: 2.8950 data: 0.0076 max mem: 33369 +Epoch: [23] [ 130/1319] eta: 0:56:37 lr: 2.3026600545461138e-05 loss: 0.0435 (0.0462) time: 2.8917 data: 0.0075 max mem: 33369 +Epoch: [23] [ 140/1319] eta: 0:56:13 lr: 2.3017303754954915e-05 loss: 0.0446 (0.0465) time: 2.9066 data: 0.0076 max mem: 33369 +Epoch: [23] [ 150/1319] eta: 0:55:50 lr: 2.300800654720609e-05 loss: 0.0372 (0.0457) time: 2.9230 data: 0.0077 max mem: 33369 +Epoch: [23] [ 160/1319] eta: 0:55:28 lr: 2.2998708922008593e-05 loss: 0.0374 (0.0456) time: 2.9453 data: 0.0074 max mem: 33369 +Epoch: [23] [ 170/1319] eta: 0:55:02 lr: 2.2989410879156158e-05 loss: 0.0437 (0.0459) time: 2.9356 data: 0.0075 max mem: 33369 +Epoch: [23] [ 180/1319] eta: 0:54:42 lr: 2.298011241844231e-05 loss: 0.0423 (0.0459) time: 2.9602 data: 0.0078 max mem: 33369 +Epoch: [23] [ 190/1319] eta: 0:54:15 lr: 2.2970813539660394e-05 loss: 0.0361 (0.0453) time: 2.9689 data: 0.0075 max mem: 33369 +Epoch: [23] [ 200/1319] eta: 0:53:50 lr: 2.296151424260354e-05 loss: 0.0361 (0.0453) time: 2.9342 data: 0.0073 max mem: 33369 +Epoch: [23] [ 210/1319] eta: 0:53:24 lr: 2.2952214527064705e-05 loss: 0.0406 (0.0453) time: 2.9456 data: 0.0073 max mem: 33369 +Epoch: [23] [ 220/1319] eta: 0:52:58 lr: 2.294291439283664e-05 loss: 0.0365 (0.0452) time: 2.9431 data: 0.0074 max mem: 33369 +Epoch: [23] [ 230/1319] eta: 0:52:29 lr: 2.2933613839711898e-05 loss: 0.0377 (0.0453) time: 2.9157 data: 0.0074 max mem: 33369 +Epoch: [23] [ 240/1319] eta: 0:52:01 lr: 2.292431286748284e-05 loss: 0.0414 (0.0452) time: 2.9100 data: 0.0076 max mem: 33369 +Epoch: [23] [ 250/1319] eta: 0:51:33 lr: 2.2915011475941626e-05 loss: 0.0386 (0.0449) time: 2.9106 data: 0.0078 max mem: 33369 +Epoch: [23] [ 260/1319] eta: 0:51:03 lr: 2.2905709664880228e-05 loss: 0.0368 (0.0451) time: 2.8864 data: 0.0080 max mem: 33369 +Epoch: [23] [ 270/1319] eta: 0:50:35 lr: 2.28964074340904e-05 loss: 0.0344 (0.0448) time: 2.9000 data: 0.0078 max mem: 33369 +Epoch: [23] [ 280/1319] eta: 0:50:06 lr: 2.2887104783363728e-05 loss: 0.0347 (0.0448) time: 2.9098 data: 0.0078 max mem: 33369 +Epoch: [23] [ 290/1319] eta: 0:49:38 lr: 2.2877801712491578e-05 loss: 0.0428 (0.0449) time: 2.9045 data: 0.0078 max mem: 33369 +Epoch: [23] [ 300/1319] eta: 0:49:08 lr: 2.2868498221265136e-05 loss: 0.0463 (0.0451) time: 2.8872 data: 0.0078 max mem: 33369 +Epoch: [23] [ 310/1319] eta: 0:48:40 lr: 2.2859194309475363e-05 loss: 0.0438 (0.0451) time: 2.8906 data: 0.0079 max mem: 33369 +Epoch: [23] [ 320/1319] eta: 0:48:11 lr: 2.2849889976913045e-05 loss: 0.0411 (0.0451) time: 2.9037 data: 0.0078 max mem: 33369 +Epoch: [23] [ 330/1319] eta: 0:47:42 lr: 2.2840585223368763e-05 loss: 0.0441 (0.0453) time: 2.8940 data: 0.0078 max mem: 33369 +Epoch: [23] [ 340/1319] eta: 0:47:12 lr: 2.2831280048632893e-05 loss: 0.0421 (0.0451) time: 2.8867 data: 0.0081 max mem: 33369 +Epoch: [23] [ 350/1319] eta: 0:46:43 lr: 2.282197445249563e-05 loss: 0.0410 (0.0450) time: 2.8810 data: 0.0081 max mem: 33369 +Epoch: [23] [ 360/1319] eta: 0:46:16 lr: 2.2812668434746943e-05 loss: 0.0377 (0.0448) time: 2.9127 data: 0.0079 max mem: 33369 +Epoch: [23] [ 370/1319] eta: 0:45:47 lr: 2.2803361995176614e-05 loss: 0.0409 (0.0450) time: 2.9176 data: 0.0080 max mem: 33369 +Epoch: [23] [ 380/1319] eta: 0:45:19 lr: 2.279405513357423e-05 loss: 0.0528 (0.0452) time: 2.9171 data: 0.0078 max mem: 33369 +Epoch: [23] [ 390/1319] eta: 0:44:49 lr: 2.278474784972917e-05 loss: 0.0482 (0.0451) time: 2.9039 data: 0.0078 max mem: 33369 +Epoch: [23] [ 400/1319] eta: 0:44:20 lr: 2.277544014343061e-05 loss: 0.0409 (0.0451) time: 2.8741 data: 0.0080 max mem: 33369 +Epoch: [23] [ 410/1319] eta: 0:43:50 lr: 2.2766132014467546e-05 loss: 0.0409 (0.0452) time: 2.8588 data: 0.0080 max mem: 33369 +Epoch: [23] [ 420/1319] eta: 0:43:20 lr: 2.2756823462628737e-05 loss: 0.0365 (0.0451) time: 2.8590 data: 0.0082 max mem: 33369 +Epoch: [23] [ 430/1319] eta: 0:42:51 lr: 2.2747514487702767e-05 loss: 0.0351 (0.0449) time: 2.8708 data: 0.0082 max mem: 33369 +Epoch: [23] [ 440/1319] eta: 0:42:19 lr: 2.2738205089478008e-05 loss: 0.0363 (0.0449) time: 2.7946 data: 0.0080 max mem: 33369 +Epoch: [23] [ 450/1319] eta: 0:41:46 lr: 2.272889526774264e-05 loss: 0.0406 (0.0450) time: 2.7070 data: 0.0080 max mem: 33369 +Epoch: [23] [ 460/1319] eta: 0:41:13 lr: 2.2719585022284628e-05 loss: 0.0415 (0.0449) time: 2.6694 data: 0.0078 max mem: 33369 +Epoch: [23] [ 470/1319] eta: 0:40:40 lr: 2.2710274352891738e-05 loss: 0.0425 (0.0448) time: 2.6561 data: 0.0072 max mem: 33369 +Epoch: [23] [ 480/1319] eta: 0:40:07 lr: 2.2700963259351535e-05 loss: 0.0394 (0.0448) time: 2.6448 data: 0.0070 max mem: 33369 +Epoch: [23] [ 490/1319] eta: 0:39:39 lr: 2.269165174145138e-05 loss: 0.0383 (0.0447) time: 2.7746 data: 0.0071 max mem: 33369 +Epoch: [23] [ 500/1319] eta: 0:39:11 lr: 2.2682339798978432e-05 loss: 0.0444 (0.0449) time: 2.9026 data: 0.0075 max mem: 33369 +Epoch: [23] [ 510/1319] eta: 0:38:42 lr: 2.2673027431719644e-05 loss: 0.0441 (0.0449) time: 2.8706 data: 0.0079 max mem: 33369 +Epoch: [23] [ 520/1319] eta: 0:38:13 lr: 2.266371463946176e-05 loss: 0.0409 (0.0450) time: 2.8781 data: 0.0081 max mem: 33369 +Epoch: [23] [ 530/1319] eta: 0:37:46 lr: 2.2654401421991334e-05 loss: 0.0421 (0.0452) time: 2.9128 data: 0.0078 max mem: 33369 +Epoch: [23] [ 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(0.0453) time: 2.8771 data: 0.0082 max mem: 33369 +Epoch: [23] [ 780/1319] eta: 0:25:52 lr: 2.242143216257503e-05 loss: 0.0405 (0.0454) time: 2.8713 data: 0.0083 max mem: 33369 +Epoch: [23] [ 790/1319] eta: 0:25:23 lr: 2.2412107813978792e-05 loss: 0.0380 (0.0453) time: 2.8748 data: 0.0080 max mem: 33369 +Epoch: [23] [ 800/1319] eta: 0:24:54 lr: 2.240278303432835e-05 loss: 0.0395 (0.0454) time: 2.8628 data: 0.0080 max mem: 33369 +Epoch: [23] [ 810/1319] eta: 0:24:25 lr: 2.2393457823404408e-05 loss: 0.0441 (0.0455) time: 2.8541 data: 0.0083 max mem: 33369 +Epoch: [23] [ 820/1319] eta: 0:23:55 lr: 2.2384132180987457e-05 loss: 0.0375 (0.0454) time: 2.7942 data: 0.0080 max mem: 33369 +Epoch: [23] [ 830/1319] eta: 0:23:25 lr: 2.2374806106857758e-05 loss: 0.0375 (0.0454) time: 2.6958 data: 0.0078 max mem: 33369 +Epoch: [23] [ 840/1319] eta: 0:22:55 lr: 2.2365479600795384e-05 loss: 0.0477 (0.0455) time: 2.6650 data: 0.0076 max mem: 33369 +Epoch: [23] [ 850/1319] eta: 0:22:25 lr: 2.2356152662580173e-05 loss: 0.0446 (0.0454) time: 2.6558 data: 0.0071 max mem: 33369 +Epoch: [23] [ 860/1319] eta: 0:21:55 lr: 2.234682529199176e-05 loss: 0.0360 (0.0453) time: 2.6563 data: 0.0070 max mem: 33369 +Epoch: [23] [ 870/1319] eta: 0:21:26 lr: 2.2337497488809557e-05 loss: 0.0378 (0.0453) time: 2.6833 data: 0.0068 max mem: 33369 +Epoch: [23] [ 880/1319] eta: 0:20:58 lr: 2.232816925281277e-05 loss: 0.0418 (0.0452) time: 2.8052 data: 0.0073 max mem: 33369 +Epoch: [23] [ 890/1319] eta: 0:20:29 lr: 2.2318840583780386e-05 loss: 0.0418 (0.0453) time: 2.9049 data: 0.0079 max mem: 33369 +Epoch: [23] [ 900/1319] eta: 0:20:00 lr: 2.2309511481491173e-05 loss: 0.0475 (0.0453) time: 2.8756 data: 0.0081 max mem: 33369 +Epoch: [23] [ 910/1319] eta: 0:19:32 lr: 2.2300181945723685e-05 loss: 0.0409 (0.0453) time: 2.8957 data: 0.0079 max mem: 33369 +Epoch: [23] [ 920/1319] eta: 0:19:04 lr: 2.2290851976256266e-05 loss: 0.0409 (0.0452) time: 2.9335 data: 0.0075 max mem: 33369 +Epoch: [23] [ 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mem: 33369 +Epoch: [23] [1010/1319] eta: 0:14:47 lr: 2.2206862697871013e-05 loss: 0.0478 (0.0456) time: 2.9107 data: 0.0077 max mem: 33369 +Epoch: [23] [1020/1319] eta: 0:14:19 lr: 2.2197528379165116e-05 loss: 0.0454 (0.0457) time: 2.9131 data: 0.0078 max mem: 33369 +Epoch: [23] [1030/1319] eta: 0:13:50 lr: 2.218819362430666e-05 loss: 0.0368 (0.0456) time: 2.8863 data: 0.0078 max mem: 33369 +Epoch: [23] [1040/1319] eta: 0:13:21 lr: 2.217885843307136e-05 loss: 0.0371 (0.0456) time: 2.8708 data: 0.0077 max mem: 33369 +Epoch: [23] [1050/1319] eta: 0:12:52 lr: 2.2169522805234726e-05 loss: 0.0471 (0.0457) time: 2.8640 data: 0.0079 max mem: 33369 +Epoch: [23] [1060/1319] eta: 0:12:24 lr: 2.2160186740572026e-05 loss: 0.0439 (0.0456) time: 2.8559 data: 0.0080 max mem: 33369 +Epoch: [23] [1070/1319] eta: 0:11:55 lr: 2.215085023885832e-05 loss: 0.0422 (0.0457) time: 2.8949 data: 0.0077 max mem: 33369 +Epoch: [23] [1080/1319] eta: 0:11:26 lr: 2.2141513299868444e-05 loss: 0.0498 (0.0459) time: 2.9223 data: 0.0077 max mem: 33369 +Epoch: [23] [1090/1319] eta: 0:10:58 lr: 2.2132175923377022e-05 loss: 0.0437 (0.0459) time: 2.9091 data: 0.0079 max mem: 33369 +Epoch: [23] [1100/1319] eta: 0:10:29 lr: 2.2122838109158445e-05 loss: 0.0357 (0.0458) time: 2.9088 data: 0.0078 max mem: 33369 +Epoch: [23] [1110/1319] eta: 0:10:00 lr: 2.211349985698688e-05 loss: 0.0426 (0.0458) time: 2.9082 data: 0.0079 max mem: 33369 +Epoch: [23] [1120/1319] eta: 0:09:32 lr: 2.2104161166636274e-05 loss: 0.0408 (0.0458) time: 2.9039 data: 0.0078 max mem: 33369 +Epoch: [23] [1130/1319] eta: 0:09:03 lr: 2.2094822037880365e-05 loss: 0.0352 (0.0457) time: 2.8821 data: 0.0077 max mem: 33369 +Epoch: [23] [1140/1319] eta: 0:08:34 lr: 2.2085482470492644e-05 loss: 0.0413 (0.0458) time: 2.9030 data: 0.0079 max mem: 33369 +Epoch: [23] [1150/1319] eta: 0:08:05 lr: 2.20761424642464e-05 loss: 0.0401 (0.0458) time: 2.9161 data: 0.0081 max mem: 33369 +Epoch: [23] [1160/1319] eta: 0:07:37 lr: 2.2066802018914685e-05 loss: 0.0353 (0.0457) time: 2.9088 data: 0.0081 max mem: 33369 +Epoch: [23] [1170/1319] eta: 0:07:08 lr: 2.2057461134270328e-05 loss: 0.0388 (0.0457) time: 2.9125 data: 0.0081 max mem: 33369 +Epoch: [23] [1180/1319] eta: 0:06:39 lr: 2.2048119810085938e-05 loss: 0.0456 (0.0458) time: 2.9036 data: 0.0083 max mem: 33369 +Epoch: [23] [1190/1319] eta: 0:06:11 lr: 2.2038778046133896e-05 loss: 0.0475 (0.0459) time: 2.8904 data: 0.0080 max mem: 33369 +Epoch: [23] [1200/1319] eta: 0:05:42 lr: 2.2029435842186362e-05 loss: 0.0486 (0.0459) time: 2.8609 data: 0.0077 max mem: 33369 +Epoch: [23] [1210/1319] eta: 0:05:13 lr: 2.2020093198015273e-05 loss: 0.0359 (0.0458) time: 2.7779 data: 0.0076 max mem: 33369 +Epoch: [23] [1220/1319] eta: 0:04:44 lr: 2.2010750113392324e-05 loss: 0.0358 (0.0458) time: 2.6815 data: 0.0074 max mem: 33369 +Epoch: [23] [1230/1319] eta: 0:04:15 lr: 2.2001406588088997e-05 loss: 0.0358 (0.0458) time: 2.6589 data: 0.0071 max mem: 33369 +Epoch: [23] [1240/1319] eta: 0:03:46 lr: 2.199206262187655e-05 loss: 0.0477 (0.0458) time: 2.6655 data: 0.0070 max mem: 33369 +Epoch: [23] [1250/1319] eta: 0:03:17 lr: 2.1982718214526003e-05 loss: 0.0421 (0.0458) time: 2.6670 data: 0.0071 max mem: 33369 +Epoch: [23] [1260/1319] eta: 0:02:49 lr: 2.1973373365808168e-05 loss: 0.0433 (0.0459) time: 2.7958 data: 0.0072 max mem: 33369 +Epoch: [23] [1270/1319] eta: 0:02:20 lr: 2.1964028075493602e-05 loss: 0.0433 (0.0459) time: 2.9209 data: 0.0077 max mem: 33369 +Epoch: [23] [1280/1319] eta: 0:01:51 lr: 2.1954682343352655e-05 loss: 0.0368 (0.0460) time: 2.8981 data: 0.0079 max mem: 33369 +Epoch: [23] [1290/1319] eta: 0:01:23 lr: 2.1945336169155447e-05 loss: 0.0370 (0.0459) time: 2.9037 data: 0.0078 max mem: 33369 +Epoch: [23] [1300/1319] eta: 0:00:54 lr: 2.1935989552671862e-05 loss: 0.0381 (0.0459) time: 2.8884 data: 0.0079 max mem: 33369 +Epoch: [23] [1310/1319] eta: 0:00:25 lr: 2.192664249367156e-05 loss: 0.0399 (0.0459) time: 2.8816 data: 0.0077 max mem: 33369 +Epoch: [23] Total time: 1:03:06 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 2:07:37 time: 2.9760 data: 2.8691 max mem: 33369 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 100/2573] eta: 0:04:14 time: 0.0735 data: 0.0014 max mem: 33369 +Test: [ 200/2573] eta: 0:03:32 time: 0.0752 data: 0.0014 max mem: 33369 +Test: [ 300/2573] eta: 0:03:11 time: 0.0769 data: 0.0014 max mem: 33369 +Test: [ 400/2573] eta: 0:02:58 time: 0.0771 data: 0.0013 max mem: 33369 +Test: [ 500/2573] eta: 0:02:47 time: 0.0754 data: 0.0013 max mem: 33369 +Test: [ 600/2573] eta: 0:02:37 time: 0.0757 data: 0.0014 max mem: 33369 +Test: [ 700/2573] eta: 0:02:29 time: 0.0756 data: 0.0014 max mem: 33369 +Test: [ 800/2573] eta: 0:02:20 time: 0.0788 data: 0.0014 max mem: 33369 +Test: [ 900/2573] eta: 0:02:12 time: 0.0759 data: 0.0013 max mem: 33369 +Test: [1000/2573] eta: 0:02:03 time: 0.0760 data: 0.0014 max mem: 33369 +Test: [1100/2573] eta: 0:01:55 time: 0.0758 data: 0.0014 max mem: 33369 +Test: [1200/2573] eta: 0:01:47 time: 0.0759 data: 0.0014 max mem: 33369 +Test: [1300/2573] eta: 0:01:39 time: 0.0760 data: 0.0013 max mem: 33369 +Test: [1400/2573] eta: 0:01:31 time: 0.0743 data: 0.0014 max mem: 33369 +Test: [1500/2573] eta: 0:01:23 time: 0.0759 data: 0.0014 max mem: 33369 +Test: [1600/2573] eta: 0:01:15 time: 0.0793 data: 0.0014 max mem: 33369 +Test: [1700/2573] eta: 0:01:07 time: 0.0744 data: 0.0013 max mem: 33369 +Test: [1800/2573] eta: 0:00:59 time: 0.0778 data: 0.0013 max mem: 33369 +Test: [1900/2573] eta: 0:00:52 time: 0.0744 data: 0.0014 max mem: 33369 +Test: [2000/2573] eta: 0:00:44 time: 0.0758 data: 0.0014 max mem: 33369 +Test: [2100/2573] eta: 0:00:36 time: 0.0777 data: 0.0013 max mem: 33369 +Test: [2200/2573] eta: 0:00:28 time: 0.0776 data: 0.0013 max mem: 33369 +Test: [2300/2573] eta: 0:00:21 time: 0.0777 data: 0.0013 max mem: 33369 +Test: [2400/2573] eta: 0:00:13 time: 0.0726 data: 0.0014 max mem: 33369 +Test: [2500/2573] eta: 0:00:05 time: 0.0759 data: 0.0014 max mem: 33369 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: Total time: 0:03:18 +Final results: +Mean IoU is 62.95 + + precision@0.5 = 71.45 + precision@0.6 = 65.91 + precision@0.7 = 58.78 + precision@0.8 = 46.57 + precision@0.9 = 22.75 + overall IoU = 61.08 + +Average object IoU 62.95229093556378 +Overall IoU 61.08274841308594 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [24] [ 0/1319] eta: 3:14:43 lr: 2.1918229762028934e-05 loss: 0.0781 (0.0781) time: 8.8576 data: 2.3524 max mem: 33369 +Epoch: [24] [ 10/1319] eta: 1:15:20 lr: 2.1908881861611456e-05 loss: 0.0394 (0.0454) time: 3.4531 data: 0.2200 max mem: 33369 +Epoch: [24] [ 20/1319] eta: 1:09:16 lr: 2.1899533518007982e-05 loss: 0.0416 (0.0477) time: 2.9171 data: 0.0066 max mem: 33369 +Epoch: [24] [ 30/1319] eta: 1:06:45 lr: 2.189018473098726e-05 loss: 0.0367 (0.0445) time: 2.9177 data: 0.0071 max mem: 33369 +Epoch: [24] [ 40/1319] eta: 1:05:14 lr: 2.188083550031783e-05 loss: 0.0338 (0.0441) time: 2.9146 data: 0.0079 max mem: 33369 +Epoch: [24] [ 50/1319] eta: 1:04:05 lr: 2.1871485825767997e-05 loss: 0.0431 (0.0448) time: 2.9094 data: 0.0080 max mem: 33369 +Epoch: [24] [ 60/1319] eta: 1:02:57 lr: 2.1862135707105826e-05 loss: 0.0429 (0.0447) time: 2.8766 data: 0.0081 max mem: 33369 +Epoch: [24] [ 70/1319] eta: 1:02:08 lr: 2.1852785144099174e-05 loss: 0.0340 (0.0434) time: 2.8721 data: 0.0082 max mem: 33369 +Epoch: [24] [ 80/1319] eta: 1:01:21 lr: 2.184343413651562e-05 loss: 0.0340 (0.0431) time: 2.8821 data: 0.0080 max mem: 33369 +Epoch: [24] [ 90/1319] eta: 1:00:41 lr: 2.1834082684122557e-05 loss: 0.0368 (0.0428) time: 2.8830 data: 0.0078 max mem: 33369 +Epoch: [24] [ 100/1319] eta: 1:00:08 lr: 2.1824730786687132e-05 loss: 0.0415 (0.0431) time: 2.9168 data: 0.0077 max mem: 33369 +Epoch: [24] [ 110/1319] eta: 0:59:29 lr: 2.181537844397624e-05 loss: 0.0430 (0.0435) time: 2.9045 data: 0.0080 max mem: 33369 +Epoch: [24] [ 120/1319] eta: 0:58:49 lr: 2.1806025655756576e-05 loss: 0.0387 (0.0434) time: 2.8601 data: 0.0082 max mem: 33369 +Epoch: [24] [ 130/1319] eta: 0:58:12 lr: 2.1796672421794575e-05 loss: 0.0365 (0.0431) time: 2.8534 data: 0.0079 max mem: 33369 +Epoch: [24] [ 140/1319] eta: 0:57:36 lr: 2.1787318741856443e-05 loss: 0.0409 (0.0434) time: 2.8604 data: 0.0078 max mem: 33369 +Epoch: [24] [ 150/1319] eta: 0:57:03 lr: 2.1777964615708157e-05 loss: 0.0449 (0.0439) time: 2.8745 data: 0.0081 max mem: 33369 +Epoch: [24] [ 160/1319] eta: 0:56:34 lr: 2.1768610043115462e-05 loss: 0.0447 (0.0440) time: 2.9073 data: 0.0083 max mem: 33369 +Epoch: [24] [ 170/1319] eta: 0:56:05 lr: 2.1759255023843863e-05 loss: 0.0404 (0.0440) time: 2.9322 data: 0.0082 max mem: 33369 +Epoch: [24] [ 180/1319] eta: 0:55:36 lr: 2.1749899557658636e-05 loss: 0.0384 (0.0441) time: 2.9336 data: 0.0081 max mem: 33369 +Epoch: [24] [ 190/1319] eta: 0:55:08 lr: 2.17405436443248e-05 loss: 0.0425 (0.0444) time: 2.9417 data: 0.0082 max mem: 33369 +Epoch: [24] [ 200/1319] eta: 0:54:29 lr: 2.1731187283607167e-05 loss: 0.0410 (0.0443) time: 2.8548 data: 0.0080 max mem: 33369 +Epoch: [24] [ 210/1319] eta: 0:53:50 lr: 2.17218304752703e-05 loss: 0.0410 (0.0449) time: 2.7406 data: 0.0077 max mem: 33369 +Epoch: [24] [ 220/1319] eta: 0:53:07 lr: 2.171247321907852e-05 loss: 0.0461 (0.0449) time: 2.6777 data: 0.0075 max mem: 33369 +Epoch: [24] [ 230/1319] eta: 0:52:28 lr: 2.1703115514795925e-05 loss: 0.0443 (0.0452) time: 2.6622 data: 0.0071 max mem: 33369 +Epoch: [24] [ 240/1319] eta: 0:51:51 lr: 2.1693757362186356e-05 loss: 0.0400 (0.0450) time: 2.7060 data: 0.0070 max mem: 33369 +Epoch: [24] [ 250/1319] eta: 0:51:10 lr: 2.1684398761013434e-05 loss: 0.0422 (0.0453) time: 2.6614 data: 0.0071 max mem: 33369 +Epoch: [24] [ 260/1319] eta: 0:50:38 lr: 2.1675039711040532e-05 loss: 0.0512 (0.0455) time: 2.6873 data: 0.0073 max mem: 33369 +Epoch: [24] [ 270/1319] eta: 0:50:09 lr: 2.166568021203079e-05 loss: 0.0398 (0.0454) time: 2.8264 data: 0.0077 max mem: 33369 +Epoch: [24] [ 280/1319] eta: 0:49:41 lr: 2.1656320263747106e-05 loss: 0.0398 (0.0453) time: 2.8809 data: 0.0081 max mem: 33369 +Epoch: [24] [ 290/1319] eta: 0:49:13 lr: 2.164695986595215e-05 loss: 0.0419 (0.0452) time: 2.8840 data: 0.0080 max mem: 33369 +Epoch: [24] [ 300/1319] eta: 0:48:44 lr: 2.163759901840832e-05 loss: 0.0404 (0.0450) time: 2.8796 data: 0.0079 max mem: 33369 +Epoch: [24] [ 310/1319] eta: 0:48:17 lr: 2.1628237720877814e-05 loss: 0.0464 (0.0457) time: 2.8979 data: 0.0078 max mem: 33369 +Epoch: [24] [ 320/1319] eta: 0:47:49 lr: 2.161887597312257e-05 loss: 0.0528 (0.0456) time: 2.9003 data: 0.0078 max mem: 33369 +Epoch: [24] [ 330/1319] eta: 0:47:21 lr: 2.160951377490428e-05 loss: 0.0374 (0.0456) time: 2.8896 data: 0.0078 max mem: 33369 +Epoch: [24] [ 340/1319] eta: 0:46:54 lr: 2.160015112598442e-05 loss: 0.0385 (0.0455) time: 2.9126 data: 0.0077 max mem: 33369 +Epoch: [24] [ 350/1319] eta: 0:46:27 lr: 2.1590788026124187e-05 loss: 0.0399 (0.0454) time: 2.9327 data: 0.0079 max mem: 33369 +Epoch: [24] [ 360/1319] eta: 0:45:59 lr: 2.158142447508457e-05 loss: 0.0420 (0.0453) time: 2.9349 data: 0.0080 max mem: 33369 +Epoch: [24] [ 370/1319] eta: 0:45:32 lr: 2.1572060472626296e-05 loss: 0.0431 (0.0453) time: 2.9262 data: 0.0078 max mem: 33369 +Epoch: [24] [ 380/1319] eta: 0:45:04 lr: 2.156269601850986e-05 loss: 0.0417 (0.0453) time: 2.9302 data: 0.0078 max mem: 33369 +Epoch: [24] [ 390/1319] eta: 0:44:38 lr: 2.1553331112495514e-05 loss: 0.0418 (0.0453) time: 2.9480 data: 0.0078 max mem: 33369 +Epoch: [24] [ 400/1319] eta: 0:44:09 lr: 2.1543965754343263e-05 loss: 0.0423 (0.0455) time: 2.9277 data: 0.0078 max mem: 33369 +Epoch: [24] [ 410/1319] eta: 0:43:40 lr: 2.1534599943812868e-05 loss: 0.0423 (0.0460) time: 2.8956 data: 0.0079 max mem: 33369 +Epoch: [24] [ 420/1319] eta: 0:43:13 lr: 2.1525233680663844e-05 loss: 0.0393 (0.0459) time: 2.9238 data: 0.0079 max mem: 33369 +Epoch: [24] [ 430/1319] eta: 0:42:44 lr: 2.151586696465547e-05 loss: 0.0374 (0.0459) time: 2.9194 data: 0.0078 max mem: 33369 +Epoch: [24] [ 440/1319] eta: 0:42:16 lr: 2.1506499795546773e-05 loss: 0.0402 (0.0459) time: 2.8933 data: 0.0079 max mem: 33369 +Epoch: [24] [ 450/1319] eta: 0:41:48 lr: 2.1497132173096545e-05 loss: 0.0404 (0.0463) time: 2.9117 data: 0.0081 max mem: 33369 +Epoch: [24] [ 460/1319] eta: 0:41:19 lr: 2.1487764097063317e-05 loss: 0.0416 (0.0463) time: 2.9113 data: 0.0081 max mem: 33369 +Epoch: [24] [ 470/1319] eta: 0:40:50 lr: 2.1478395567205385e-05 loss: 0.0386 (0.0462) time: 2.8903 data: 0.0081 max mem: 33369 +Epoch: [24] [ 480/1319] eta: 0:40:21 lr: 2.14690265832808e-05 loss: 0.0392 (0.0462) time: 2.8884 data: 0.0082 max mem: 33369 +Epoch: [24] [ 490/1319] eta: 0:39:53 lr: 2.1459657145047365e-05 loss: 0.0459 (0.0462) time: 2.9026 data: 0.0081 max mem: 33369 +Epoch: [24] [ 500/1319] eta: 0:39:24 lr: 2.1450287252262635e-05 loss: 0.0371 (0.0460) time: 2.9048 data: 0.0081 max mem: 33369 +Epoch: [24] [ 510/1319] eta: 0:38:55 lr: 2.144091690468391e-05 loss: 0.0371 (0.0459) time: 2.8776 data: 0.0082 max mem: 33369 +Epoch: [24] [ 520/1319] eta: 0:38:26 lr: 2.1431546102068255e-05 loss: 0.0394 (0.0457) time: 2.8642 data: 0.0083 max mem: 33369 +Epoch: [24] [ 530/1319] eta: 0:37:56 lr: 2.142217484417249e-05 loss: 0.0427 (0.0460) time: 2.8543 data: 0.0080 max mem: 33369 +Epoch: [24] [ 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(0.0458) time: 2.9332 data: 0.0079 max mem: 33369 +Epoch: [24] [ 780/1319] eta: 0:25:49 lr: 2.1187744714297132e-05 loss: 0.0411 (0.0458) time: 2.9192 data: 0.0081 max mem: 33369 +Epoch: [24] [ 790/1319] eta: 0:25:20 lr: 2.117836153293854e-05 loss: 0.0376 (0.0457) time: 2.8777 data: 0.0080 max mem: 33369 +Epoch: [24] [ 800/1319] eta: 0:24:51 lr: 2.1168977889638698e-05 loss: 0.0358 (0.0456) time: 2.8459 data: 0.0078 max mem: 33369 +Epoch: [24] [ 810/1319] eta: 0:24:23 lr: 2.1159593784147318e-05 loss: 0.0364 (0.0456) time: 2.8610 data: 0.0079 max mem: 33369 +Epoch: [24] [ 820/1319] eta: 0:23:54 lr: 2.115020921621386e-05 loss: 0.0376 (0.0456) time: 2.8806 data: 0.0079 max mem: 33369 +Epoch: [24] [ 830/1319] eta: 0:23:25 lr: 2.1140824185587522e-05 loss: 0.0433 (0.0456) time: 2.8750 data: 0.0077 max mem: 33369 +Epoch: [24] [ 840/1319] eta: 0:22:56 lr: 2.113143869201724e-05 loss: 0.0412 (0.0456) time: 2.8614 data: 0.0078 max mem: 33369 +Epoch: [24] [ 850/1319] eta: 0:22:27 lr: 2.11220527352517e-05 loss: 0.0459 (0.0456) time: 2.8621 data: 0.0081 max mem: 33369 +Epoch: [24] [ 860/1319] eta: 0:21:59 lr: 2.111266631503932e-05 loss: 0.0393 (0.0455) time: 2.8734 data: 0.0082 max mem: 33369 +Epoch: [24] [ 870/1319] eta: 0:21:30 lr: 2.1103279431128255e-05 loss: 0.0363 (0.0455) time: 2.8480 data: 0.0080 max mem: 33369 +Epoch: [24] [ 880/1319] eta: 0:21:01 lr: 2.1093892083266405e-05 loss: 0.0406 (0.0455) time: 2.8382 data: 0.0080 max mem: 33369 +Epoch: [24] [ 890/1319] eta: 0:20:32 lr: 2.10845042712014e-05 loss: 0.0413 (0.0455) time: 2.8822 data: 0.0080 max mem: 33369 +Epoch: [24] [ 900/1319] eta: 0:20:04 lr: 2.1075115994680607e-05 loss: 0.0417 (0.0455) time: 2.8849 data: 0.0079 max mem: 33369 +Epoch: [24] [ 910/1319] eta: 0:19:35 lr: 2.106572725345115e-05 loss: 0.0366 (0.0453) time: 2.8684 data: 0.0080 max mem: 33369 +Epoch: [24] [ 920/1319] eta: 0:19:06 lr: 2.105633804725987e-05 loss: 0.0323 (0.0452) time: 2.8528 data: 0.0082 max mem: 33369 +Epoch: [24] [ 930/1319] eta: 0:18:37 lr: 2.104694837585335e-05 loss: 0.0360 (0.0452) time: 2.8530 data: 0.0083 max mem: 33369 +Epoch: [24] [ 940/1319] eta: 0:18:08 lr: 2.1037558238977907e-05 loss: 0.0384 (0.0452) time: 2.8763 data: 0.0084 max mem: 33369 +Epoch: [24] [ 950/1319] eta: 0:17:40 lr: 2.1028167636379597e-05 loss: 0.0333 (0.0451) time: 2.8785 data: 0.0082 max mem: 33369 +Epoch: [24] [ 960/1319] eta: 0:17:11 lr: 2.1018776567804213e-05 loss: 0.0356 (0.0451) time: 2.8677 data: 0.0079 max mem: 33369 +Epoch: [24] [ 970/1319] eta: 0:16:42 lr: 2.1009385032997278e-05 loss: 0.0383 (0.0451) time: 2.8505 data: 0.0081 max mem: 33369 +Epoch: [24] [ 980/1319] eta: 0:16:13 lr: 2.0999993031704057e-05 loss: 0.0394 (0.0451) time: 2.7597 data: 0.0082 max mem: 33369 +Epoch: [24] [ 990/1319] eta: 0:15:43 lr: 2.0990600563669546e-05 loss: 0.0368 (0.0450) time: 2.6797 data: 0.0080 max mem: 33369 +Epoch: [24] [1000/1319] eta: 0:15:14 lr: 2.0981207628638462e-05 loss: 0.0394 (0.0450) time: 2.6564 data: 0.0074 max mem: 33369 +Epoch: [24] [1010/1319] eta: 0:14:45 lr: 2.0971814226355274e-05 loss: 0.0459 (0.0451) time: 2.6645 data: 0.0070 max mem: 33369 +Epoch: [24] [1020/1319] eta: 0:14:15 lr: 2.0962420356564173e-05 loss: 0.0408 (0.0452) time: 2.6741 data: 0.0069 max mem: 33369 +Epoch: [24] [1030/1319] eta: 0:13:46 lr: 2.0953026019009095e-05 loss: 0.0412 (0.0452) time: 2.6614 data: 0.0072 max mem: 33369 +Epoch: [24] [1040/1319] eta: 0:13:18 lr: 2.0943631213433694e-05 loss: 0.0437 (0.0453) time: 2.7467 data: 0.0077 max mem: 33369 +Epoch: [24] [1050/1319] eta: 0:12:49 lr: 2.0934235939581352e-05 loss: 0.0412 (0.0452) time: 2.8629 data: 0.0080 max mem: 33369 +Epoch: [24] [1060/1319] eta: 0:12:20 lr: 2.0924840197195202e-05 loss: 0.0404 (0.0453) time: 2.8810 data: 0.0077 max mem: 33369 +Epoch: [24] [1070/1319] eta: 0:11:52 lr: 2.0915443986018095e-05 loss: 0.0420 (0.0453) time: 2.8619 data: 0.0074 max mem: 33369 +Epoch: [24] [1080/1319] eta: 0:11:23 lr: 2.0906047305792607e-05 loss: 0.0423 (0.0453) time: 2.8909 data: 0.0077 max mem: 33369 +Epoch: [24] [1090/1319] eta: 0:10:55 lr: 2.0896650156261064e-05 loss: 0.0450 (0.0453) time: 2.9090 data: 0.0077 max mem: 33369 +Epoch: [24] [1100/1319] eta: 0:10:26 lr: 2.0887252537165494e-05 loss: 0.0450 (0.0453) time: 2.9087 data: 0.0074 max mem: 33369 +Epoch: [24] [1110/1319] eta: 0:09:58 lr: 2.087785444824768e-05 loss: 0.0440 (0.0455) time: 2.9401 data: 0.0075 max mem: 33369 +Epoch: [24] [1120/1319] eta: 0:09:29 lr: 2.086845588924912e-05 loss: 0.0389 (0.0454) time: 2.9493 data: 0.0078 max mem: 33369 +Epoch: [24] [1130/1319] eta: 0:09:01 lr: 2.0859056859911038e-05 loss: 0.0397 (0.0455) time: 2.9388 data: 0.0075 max mem: 33369 +Epoch: [24] [1140/1319] eta: 0:08:32 lr: 2.0849657359974397e-05 loss: 0.0562 (0.0455) time: 2.9271 data: 0.0073 max mem: 33369 +Epoch: [24] [1150/1319] eta: 0:08:04 lr: 2.084025738917989e-05 loss: 0.0423 (0.0456) time: 2.9062 data: 0.0074 max mem: 33369 +Epoch: [24] [1160/1319] eta: 0:07:35 lr: 2.083085694726791e-05 loss: 0.0416 (0.0456) time: 2.9113 data: 0.0075 max mem: 33369 +Epoch: [24] [1170/1319] eta: 0:07:07 lr: 2.0821456033978605e-05 loss: 0.0431 (0.0456) time: 2.9295 data: 0.0076 max mem: 33369 +Epoch: [24] [1180/1319] eta: 0:06:38 lr: 2.0812054649051834e-05 loss: 0.0475 (0.0456) time: 2.9110 data: 0.0076 max mem: 33369 +Epoch: [24] [1190/1319] eta: 0:06:09 lr: 2.0802652792227197e-05 loss: 0.0403 (0.0456) time: 2.9014 data: 0.0077 max mem: 33369 +Epoch: [24] [1200/1319] eta: 0:05:41 lr: 2.0793250463244006e-05 loss: 0.0455 (0.0457) time: 2.8898 data: 0.0078 max mem: 33369 +Epoch: [24] [1210/1319] eta: 0:05:12 lr: 2.07838476618413e-05 loss: 0.0439 (0.0457) time: 2.8807 data: 0.0079 max mem: 33369 +Epoch: [24] [1220/1319] eta: 0:04:43 lr: 2.077444438775784e-05 loss: 0.0406 (0.0457) time: 2.8682 data: 0.0079 max mem: 33369 +Epoch: [24] [1230/1319] eta: 0:04:15 lr: 2.0765040640732118e-05 loss: 0.0413 (0.0457) time: 2.8400 data: 0.0076 max mem: 33369 +Epoch: [24] [1240/1319] eta: 0:03:46 lr: 2.0755636420502354e-05 loss: 0.0413 (0.0457) time: 2.8444 data: 0.0078 max mem: 33369 +Epoch: [24] [1250/1319] eta: 0:03:17 lr: 2.074623172680648e-05 loss: 0.0421 (0.0457) time: 2.8417 data: 0.0080 max mem: 33369 +Epoch: [24] [1260/1319] eta: 0:02:49 lr: 2.0736826559382146e-05 loss: 0.0466 (0.0457) time: 2.8656 data: 0.0082 max mem: 33369 +Epoch: [24] [1270/1319] eta: 0:02:20 lr: 2.072742091796674e-05 loss: 0.0510 (0.0458) time: 2.9078 data: 0.0083 max mem: 33369 +Epoch: [24] [1280/1319] eta: 0:01:51 lr: 2.071801480229737e-05 loss: 0.0473 (0.0458) time: 2.9012 data: 0.0084 max mem: 33369 +Epoch: [24] [1290/1319] eta: 0:01:23 lr: 2.0708608212110852e-05 loss: 0.0443 (0.0458) time: 2.8848 data: 0.0082 max mem: 33369 +Epoch: [24] [1300/1319] eta: 0:00:54 lr: 2.0699201147143737e-05 loss: 0.0443 (0.0458) time: 2.8726 data: 0.0081 max mem: 33369 +Epoch: [24] [1310/1319] eta: 0:00:25 lr: 2.0689793607132295e-05 loss: 0.0441 (0.0458) time: 2.8689 data: 0.0080 max mem: 33369 +Epoch: [24] Total time: 1:03:02 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 2:11:37 time: 3.0694 data: 2.9620 max mem: 33369 +Test: [ 100/2573] eta: 0:04:14 time: 0.0730 data: 0.0013 max mem: 33369 +Test: [ 200/2573] eta: 0:03:32 time: 0.0750 data: 0.0014 max mem: 33369 +Test: [ 300/2573] eta: 0:03:11 time: 0.0767 data: 0.0014 max mem: 33369 +Test: [ 400/2573] eta: 0:02:57 time: 0.0768 data: 0.0013 max mem: 33369 +Test: [ 500/2573] eta: 0:02:46 time: 0.0752 data: 0.0014 max mem: 33369 +Test: [ 600/2573] eta: 0:02:37 time: 0.0752 data: 0.0014 max mem: 33369 +Test: [ 700/2573] eta: 0:02:28 time: 0.0751 data: 0.0014 max mem: 33369 +Test: [ 800/2573] eta: 0:02:20 time: 0.0786 data: 0.0014 max mem: 33369 +Test: [ 900/2573] eta: 0:02:11 time: 0.0753 data: 0.0014 max mem: 33369 +Test: [1000/2573] eta: 0:02:03 time: 0.0754 data: 0.0013 max mem: 33369 +Test: [1100/2573] eta: 0:01:55 time: 0.0755 data: 0.0013 max mem: 33369 +Test: [1200/2573] eta: 0:01:47 time: 0.0755 data: 0.0014 max mem: 33369 +Test: [1300/2573] eta: 0:01:39 time: 0.0754 data: 0.0013 max mem: 33369 +Test: [1400/2573] eta: 0:01:31 time: 0.0738 data: 0.0013 max mem: 33369 +Test: [1500/2573] eta: 0:01:23 time: 0.0756 data: 0.0014 max mem: 33369 +Test: [1600/2573] eta: 0:01:15 time: 0.0782 data: 0.0013 max mem: 33369 +Test: [1700/2573] eta: 0:01:07 time: 0.0739 data: 0.0012 max mem: 33369 +Test: [1800/2573] eta: 0:00:59 time: 0.0762 data: 0.0012 max mem: 33369 +Test: [1900/2573] eta: 0:00:51 time: 0.0733 data: 0.0013 max mem: 33369 +Test: [2000/2573] eta: 0:00:43 time: 0.0749 data: 0.0012 max mem: 33369 +Test: [2100/2573] eta: 0:00:36 time: 0.0759 data: 0.0011 max mem: 33369 +Test: [2200/2573] eta: 0:00:28 time: 0.0758 data: 0.0011 max mem: 33369 +Test: [2300/2573] eta: 0:00:20 time: 0.0758 data: 0.0011 max mem: 33369 +Test: [2400/2573] eta: 0:00:13 time: 0.0710 data: 0.0012 max mem: 33369 +Test: [2500/2573] eta: 0:00:05 time: 0.0743 data: 0.0012 max mem: 33369 +Test: Total time: 0:03:16 +Final results: +Mean IoU is 63.48 + + precision@0.5 = 71.49 + precision@0.6 = 66.46 + precision@0.7 = 59.44 + precision@0.8 = 47.30 + precision@0.9 = 23.33 + overall IoU = 61.65 + +Average object IoU 63.483712644721614 +Overall IoU 61.65306854248047 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [25] [ 0/1319] eta: 3:18:53 lr: 2.0681326414740886e-05 loss: 0.0341 (0.0341) time: 9.0475 data: 1.7435 max mem: 33369 +Epoch: [25] [ 10/1319] eta: 1:11:25 lr: 2.0671917971417626e-05 loss: 0.0386 (0.0399) time: 3.2739 data: 0.1648 max mem: 33369 +Epoch: [25] [ 20/1319] eta: 1:04:52 lr: 2.0662509052283616e-05 loss: 0.0390 (0.0431) time: 2.6939 data: 0.0068 max mem: 33369 +Epoch: [25] [ 30/1319] eta: 1:03:39 lr: 2.0653099657074033e-05 loss: 0.0302 (0.0399) time: 2.7921 data: 0.0071 max mem: 33369 +Epoch: [25] [ 40/1319] eta: 1:02:45 lr: 2.064368978552377e-05 loss: 0.0347 (0.0395) time: 2.8891 data: 0.0078 max mem: 33369 +Epoch: [25] [ 50/1319] eta: 1:02:01 lr: 2.0634279437367437e-05 loss: 0.0360 (0.0387) time: 2.8864 data: 0.0079 max mem: 33369 +Epoch: [25] [ 60/1319] eta: 1:01:17 lr: 2.0624868612339364e-05 loss: 0.0315 (0.0373) time: 2.8733 data: 0.0078 max mem: 33369 +Epoch: [25] [ 70/1319] eta: 1:00:44 lr: 2.0615457310173584e-05 loss: 0.0365 (0.0381) time: 2.8802 data: 0.0077 max mem: 33369 +Epoch: [25] [ 80/1319] eta: 1:00:08 lr: 2.0606045530603866e-05 loss: 0.0400 (0.0386) time: 2.8862 data: 0.0077 max mem: 33369 +Epoch: [25] [ 90/1319] eta: 0:59:35 lr: 2.059663327336368e-05 loss: 0.0389 (0.0395) time: 2.8780 data: 0.0079 max mem: 33369 +Epoch: [25] [ 100/1319] eta: 0:59:06 lr: 2.058722053818622e-05 loss: 0.0365 (0.0391) time: 2.8956 data: 0.0079 max mem: 33369 +Epoch: [25] [ 110/1319] eta: 0:58:40 lr: 2.0577807324804403e-05 loss: 0.0367 (0.0415) time: 2.9255 data: 0.0079 max mem: 33369 +Epoch: [25] [ 120/1319] eta: 0:58:12 lr: 2.0568393632950847e-05 loss: 0.0402 (0.0415) time: 2.9333 data: 0.0078 max mem: 33369 +Epoch: [25] [ 130/1319] eta: 0:57:44 lr: 2.055897946235788e-05 loss: 0.0413 (0.0417) time: 2.9235 data: 0.0075 max mem: 33369 +Epoch: [25] [ 140/1319] eta: 0:57:14 lr: 2.054956481275756e-05 loss: 0.0367 (0.0417) time: 2.9117 data: 0.0075 max mem: 33369 +Epoch: [25] [ 150/1319] eta: 0:56:44 lr: 2.0540149683881653e-05 loss: 0.0367 (0.0421) time: 2.9001 data: 0.0075 max mem: 33369 +Epoch: [25] [ 160/1319] eta: 0:56:16 lr: 2.0530734075461633e-05 loss: 0.0344 (0.0419) time: 2.9157 data: 0.0073 max mem: 33369 +Epoch: [25] [ 170/1319] eta: 0:55:44 lr: 2.05213179872287e-05 loss: 0.0344 (0.0419) time: 2.9025 data: 0.0076 max mem: 33369 +Epoch: [25] [ 180/1319] eta: 0:55:21 lr: 2.051190141891374e-05 loss: 0.0318 (0.0414) time: 2.9365 data: 0.0078 max mem: 33369 +Epoch: [25] [ 190/1319] eta: 0:54:52 lr: 2.050248437024738e-05 loss: 0.0328 (0.0413) time: 2.9657 data: 0.0078 max mem: 33369 +Epoch: [25] [ 200/1319] eta: 0:54:21 lr: 2.049306684095994e-05 loss: 0.0390 (0.0412) time: 2.9040 data: 0.0077 max mem: 33369 +Epoch: [25] [ 210/1319] eta: 0:53:51 lr: 2.048364883078146e-05 loss: 0.0393 (0.0414) time: 2.8847 data: 0.0076 max mem: 33369 +Epoch: [25] [ 220/1319] eta: 0:53:21 lr: 2.0474230339441687e-05 loss: 0.0404 (0.0416) time: 2.9022 data: 0.0076 max mem: 33369 +Epoch: [25] [ 230/1319] eta: 0:52:52 lr: 2.0464811366670074e-05 loss: 0.0411 (0.0420) time: 2.9128 data: 0.0077 max mem: 33369 +Epoch: [25] [ 240/1319] eta: 0:52:22 lr: 2.0455391912195788e-05 loss: 0.0380 (0.0420) time: 2.9051 data: 0.0079 max mem: 33369 +Epoch: [25] [ 250/1319] eta: 0:51:51 lr: 2.0445971975747706e-05 loss: 0.0380 (0.0420) time: 2.8790 data: 0.0077 max mem: 33369 +Epoch: [25] [ 260/1319] eta: 0:51:20 lr: 2.0436551557054405e-05 loss: 0.0354 (0.0418) time: 2.8635 data: 0.0077 max mem: 33369 +Epoch: [25] [ 270/1319] eta: 0:50:48 lr: 2.0427130655844186e-05 loss: 0.0354 (0.0421) time: 2.8530 data: 0.0080 max mem: 33369 +Epoch: [25] [ 280/1319] eta: 0:50:20 lr: 2.041770927184505e-05 loss: 0.0387 (0.0421) time: 2.8769 data: 0.0080 max mem: 33369 +Epoch: [25] [ 290/1319] eta: 0:49:48 lr: 2.0408287404784693e-05 loss: 0.0368 (0.0420) time: 2.8704 data: 0.0081 max mem: 33369 +Epoch: [25] [ 300/1319] eta: 0:49:18 lr: 2.0398865054390533e-05 loss: 0.0398 (0.0420) time: 2.8504 data: 0.0082 max mem: 33369 +Epoch: [25] [ 310/1319] eta: 0:48:48 lr: 2.038944222038969e-05 loss: 0.0418 (0.0420) time: 2.8795 data: 0.0079 max mem: 33369 +Epoch: [25] [ 320/1319] eta: 0:48:18 lr: 2.0380018902508984e-05 loss: 0.0383 (0.0418) time: 2.8700 data: 0.0079 max mem: 33369 +Epoch: [25] [ 330/1319] eta: 0:47:49 lr: 2.0370595100474957e-05 loss: 0.0365 (0.0417) time: 2.8830 data: 0.0079 max mem: 33369 +Epoch: [25] [ 340/1319] eta: 0:47:19 lr: 2.036117081401383e-05 loss: 0.0365 (0.0416) time: 2.8936 data: 0.0079 max mem: 33369 +Epoch: [25] [ 350/1319] eta: 0:46:50 lr: 2.035174604285155e-05 loss: 0.0387 (0.0417) time: 2.8765 data: 0.0078 max mem: 33369 +Epoch: [25] [ 360/1319] eta: 0:46:21 lr: 2.0342320786713757e-05 loss: 0.0363 (0.0416) time: 2.9053 data: 0.0078 max mem: 33369 +Epoch: [25] [ 370/1319] eta: 0:45:51 lr: 2.03328950453258e-05 loss: 0.0349 (0.0419) time: 2.8885 data: 0.0078 max mem: 33369 +Epoch: [25] [ 380/1319] eta: 0:45:20 lr: 2.0323468818412736e-05 loss: 0.0399 (0.0421) time: 2.8436 data: 0.0078 max mem: 33369 +Epoch: [25] [ 390/1319] eta: 0:44:47 lr: 2.03140421056993e-05 loss: 0.0405 (0.0423) time: 2.7733 data: 0.0076 max mem: 33369 +Epoch: [25] [ 400/1319] eta: 0:44:13 lr: 2.0304614906909954e-05 loss: 0.0477 (0.0424) time: 2.6790 data: 0.0071 max mem: 33369 +Epoch: [25] [ 410/1319] eta: 0:43:39 lr: 2.0295187221768858e-05 loss: 0.0482 (0.0425) time: 2.6684 data: 0.0068 max mem: 33369 +Epoch: [25] [ 420/1319] eta: 0:43:05 lr: 2.028575904999986e-05 loss: 0.0438 (0.0438) time: 2.6534 data: 0.0066 max mem: 33369 +Epoch: [25] [ 430/1319] eta: 0:42:30 lr: 2.0276330391326524e-05 loss: 0.0478 (0.0440) time: 2.6111 data: 0.0066 max mem: 33369 +Epoch: [25] [ 440/1319] eta: 0:41:57 lr: 2.026690124547211e-05 loss: 0.0469 (0.0439) time: 2.6209 data: 0.0066 max mem: 33369 +Epoch: [25] [ 450/1319] eta: 0:41:24 lr: 2.025747161215956e-05 loss: 0.0358 (0.0439) time: 2.6316 data: 0.0066 max mem: 33369 +Epoch: [25] [ 460/1319] eta: 0:40:51 lr: 2.0248041491111535e-05 loss: 0.0358 (0.0438) time: 2.6362 data: 0.0068 max mem: 33369 +Epoch: [25] [ 470/1319] eta: 0:40:19 lr: 2.0238610882050398e-05 loss: 0.0381 (0.0437) time: 2.6428 data: 0.0068 max mem: 33369 +Epoch: [25] [ 480/1319] eta: 0:39:46 lr: 2.0229179784698192e-05 loss: 0.0356 (0.0436) time: 2.6255 data: 0.0070 max mem: 33369 +Epoch: [25] [ 490/1319] eta: 0:39:16 lr: 2.0219748198776674e-05 loss: 0.0307 (0.0436) time: 2.6900 data: 0.0074 max mem: 33369 +Epoch: [25] [ 500/1319] eta: 0:38:50 lr: 2.0210316124007283e-05 loss: 0.0377 (0.0436) time: 2.8732 data: 0.0077 max mem: 33369 +Epoch: [25] [ 510/1319] eta: 0:38:23 lr: 2.020088356011117e-05 loss: 0.0431 (0.0437) time: 2.9479 data: 0.0080 max mem: 33369 +Epoch: [25] [ 520/1319] eta: 0:37:56 lr: 2.019145050680917e-05 loss: 0.0376 (0.0435) time: 2.9189 data: 0.0080 max mem: 33369 +Epoch: [25] [ 530/1319] eta: 0:37:28 lr: 2.0182016963821814e-05 loss: 0.0359 (0.0436) time: 2.9187 data: 0.0081 max mem: 33369 +Epoch: [25] [ 540/1319] eta: 0:37:00 lr: 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data: 0.0081 max mem: 33369 +Epoch: [25] [ 780/1319] eta: 0:25:47 lr: 1.994601841767567e-05 loss: 0.0351 (0.0430) time: 2.9099 data: 0.0082 max mem: 33369 +Epoch: [25] [ 790/1319] eta: 0:25:18 lr: 1.9936572043768427e-05 loss: 0.0410 (0.0430) time: 2.9064 data: 0.0084 max mem: 33369 +Epoch: [25] [ 800/1319] eta: 0:24:50 lr: 1.9927125172513435e-05 loss: 0.0407 (0.0430) time: 2.9005 data: 0.0085 max mem: 33369 +Epoch: [25] [ 810/1319] eta: 0:24:22 lr: 1.991767780362252e-05 loss: 0.0433 (0.0431) time: 2.9149 data: 0.0083 max mem: 33369 +Epoch: [25] [ 820/1319] eta: 0:23:52 lr: 1.990822993680716e-05 loss: 0.0393 (0.0431) time: 2.8170 data: 0.0080 max mem: 33369 +Epoch: [25] [ 830/1319] eta: 0:23:22 lr: 1.9898781571778537e-05 loss: 0.0403 (0.0431) time: 2.7161 data: 0.0078 max mem: 33369 +Epoch: [25] [ 840/1319] eta: 0:22:52 lr: 1.9889332708247497e-05 loss: 0.0446 (0.0432) time: 2.6928 data: 0.0077 max mem: 33369 +Epoch: [25] [ 850/1319] eta: 0:22:23 lr: 1.9879883345924575e-05 loss: 0.0438 (0.0432) time: 2.6651 data: 0.0073 max mem: 33369 +Epoch: [25] [ 860/1319] eta: 0:21:53 lr: 1.987043348451999e-05 loss: 0.0405 (0.0432) time: 2.6443 data: 0.0070 max mem: 33369 +Epoch: [25] [ 870/1319] eta: 0:21:24 lr: 1.9860983123743625e-05 loss: 0.0389 (0.0431) time: 2.6935 data: 0.0072 max mem: 33369 +Epoch: [25] [ 880/1319] eta: 0:20:55 lr: 1.9851532263305046e-05 loss: 0.0444 (0.0432) time: 2.8373 data: 0.0075 max mem: 33369 +Epoch: [25] [ 890/1319] eta: 0:20:27 lr: 1.98420809029135e-05 loss: 0.0475 (0.0432) time: 2.8992 data: 0.0076 max mem: 33369 +Epoch: [25] [ 900/1319] eta: 0:19:58 lr: 1.9832629042277908e-05 loss: 0.0384 (0.0432) time: 2.8881 data: 0.0076 max mem: 33369 +Epoch: [25] [ 910/1319] eta: 0:19:30 lr: 1.982317668110687e-05 loss: 0.0384 (0.0432) time: 2.9179 data: 0.0078 max mem: 33369 +Epoch: [25] [ 920/1319] eta: 0:19:02 lr: 1.981372381910867e-05 loss: 0.0385 (0.0432) time: 2.9169 data: 0.0078 max mem: 33369 +Epoch: [25] [ 930/1319] eta: 0:18:33 lr: 1.980427045599124e-05 loss: 0.0412 (0.0432) time: 2.9060 data: 0.0078 max mem: 33369 +Epoch: [25] [ 940/1319] eta: 0:18:05 lr: 1.9794816591462205e-05 loss: 0.0405 (0.0431) time: 2.9150 data: 0.0078 max mem: 33369 +Epoch: [25] [ 950/1319] eta: 0:17:37 lr: 1.9785362225228878e-05 loss: 0.0343 (0.0431) time: 2.9392 data: 0.0076 max mem: 33369 +Epoch: [25] [ 960/1319] eta: 0:17:08 lr: 1.9775907356998215e-05 loss: 0.0337 (0.0431) time: 2.9720 data: 0.0073 max mem: 33369 +Epoch: [25] [ 970/1319] eta: 0:16:40 lr: 1.976645198647688e-05 loss: 0.0468 (0.0432) time: 2.9745 data: 0.0073 max mem: 33369 +Epoch: [25] [ 980/1319] eta: 0:16:12 lr: 1.9756996113371165e-05 loss: 0.0430 (0.0432) time: 2.9553 data: 0.0075 max mem: 33369 +Epoch: [25] [ 990/1319] eta: 0:15:43 lr: 1.9747539737387077e-05 loss: 0.0434 (0.0433) time: 2.9238 data: 0.0076 max mem: 33369 +Epoch: [25] [1000/1319] eta: 0:15:15 lr: 1.973808285823027e-05 loss: 0.0434 (0.0432) time: 2.9127 data: 0.0079 max mem: 33369 +Epoch: [25] [1010/1319] eta: 0:14:46 lr: 1.972862547560608e-05 loss: 0.0423 (0.0433) time: 2.9105 data: 0.0080 max mem: 33369 +Epoch: [25] [1020/1319] eta: 0:14:18 lr: 1.9719167589219505e-05 loss: 0.0451 (0.0433) time: 2.9296 data: 0.0079 max mem: 33369 +Epoch: [25] [1030/1319] eta: 0:13:49 lr: 1.9709709198775227e-05 loss: 0.0351 (0.0433) time: 2.9205 data: 0.0077 max mem: 33369 +Epoch: [25] [1040/1319] eta: 0:13:20 lr: 1.9700250303977575e-05 loss: 0.0374 (0.0432) time: 2.9027 data: 0.0078 max mem: 33369 +Epoch: [25] [1050/1319] eta: 0:12:52 lr: 1.969079090453056e-05 loss: 0.0401 (0.0432) time: 2.9058 data: 0.0080 max mem: 33369 +Epoch: [25] [1060/1319] eta: 0:12:23 lr: 1.968133100013787e-05 loss: 0.0383 (0.0432) time: 2.8912 data: 0.0079 max mem: 33369 +Epoch: [25] [1070/1319] eta: 0:11:54 lr: 1.967187059050284e-05 loss: 0.0413 (0.0433) time: 2.8881 data: 0.0079 max mem: 33369 +Epoch: [25] [1080/1319] eta: 0:11:26 lr: 1.9662409675328494e-05 loss: 0.0421 (0.0434) time: 2.8653 data: 0.0079 max mem: 33369 +Epoch: [25] [1090/1319] eta: 0:10:57 lr: 1.9652948254317503e-05 loss: 0.0412 (0.0434) time: 2.8561 data: 0.0078 max mem: 33369 +Epoch: [25] [1100/1319] eta: 0:10:28 lr: 1.9643486327172213e-05 loss: 0.0455 (0.0434) time: 2.8757 data: 0.0078 max mem: 33369 +Epoch: [25] [1110/1319] eta: 0:09:59 lr: 1.9634023893594635e-05 loss: 0.0398 (0.0434) time: 2.8669 data: 0.0080 max mem: 33369 +Epoch: [25] [1120/1319] eta: 0:09:31 lr: 1.9624560953286446e-05 loss: 0.0325 (0.0433) time: 2.8787 data: 0.0081 max mem: 33369 +Epoch: [25] [1130/1319] eta: 0:09:02 lr: 1.961509750594899e-05 loss: 0.0342 (0.0434) time: 2.8948 data: 0.0080 max mem: 33369 +Epoch: [25] [1140/1319] eta: 0:08:33 lr: 1.9605633551283273e-05 loss: 0.0409 (0.0433) time: 2.8778 data: 0.0079 max mem: 33369 +Epoch: [25] [1150/1319] eta: 0:08:05 lr: 1.9596169088989948e-05 loss: 0.0365 (0.0434) time: 2.8827 data: 0.0078 max mem: 33369 +Epoch: [25] [1160/1319] eta: 0:07:36 lr: 1.9586704118769358e-05 loss: 0.0367 (0.0433) time: 2.8956 data: 0.0080 max mem: 33369 +Epoch: [25] [1170/1319] eta: 0:07:07 lr: 1.9577238640321492e-05 loss: 0.0367 (0.0433) time: 2.8785 data: 0.0080 max mem: 33369 +Epoch: [25] [1180/1319] eta: 0:06:39 lr: 1.9567772653346e-05 loss: 0.0397 (0.0433) time: 2.8324 data: 0.0080 max mem: 33369 +Epoch: [25] [1190/1319] eta: 0:06:10 lr: 1.9558306157542204e-05 loss: 0.0392 (0.0433) time: 2.8038 data: 0.0079 max mem: 33369 +Epoch: [25] [1200/1319] eta: 0:05:41 lr: 1.9548839152609067e-05 loss: 0.0433 (0.0434) time: 2.8374 data: 0.0079 max mem: 33369 +Epoch: [25] [1210/1319] eta: 0:05:12 lr: 1.9539371638245233e-05 loss: 0.0445 (0.0434) time: 2.8315 data: 0.0079 max mem: 33369 +Epoch: [25] [1220/1319] eta: 0:04:43 lr: 1.952990361414899e-05 loss: 0.0390 (0.0434) time: 2.7367 data: 0.0076 max mem: 33369 +Epoch: [25] [1230/1319] eta: 0:04:15 lr: 1.9520435080018294e-05 loss: 0.0404 (0.0434) time: 2.6703 data: 0.0071 max mem: 33369 +Epoch: [25] [1240/1319] eta: 0:03:46 lr: 1.9510966035550763e-05 loss: 0.0410 (0.0434) time: 2.6527 data: 0.0067 max mem: 33369 +Epoch: [25] [1250/1319] eta: 0:03:17 lr: 1.9501496480443652e-05 loss: 0.0415 (0.0435) time: 2.6194 data: 0.0068 max mem: 33369 +Epoch: [25] [1260/1319] eta: 0:02:48 lr: 1.9492026414393892e-05 loss: 0.0437 (0.0436) time: 2.6048 data: 0.0068 max mem: 33369 +Epoch: [25] [1270/1319] eta: 0:02:20 lr: 1.9482555837098063e-05 loss: 0.0453 (0.0436) time: 2.6293 data: 0.0066 max mem: 33369 +Epoch: [25] [1280/1319] eta: 0:01:51 lr: 1.9473084748252403e-05 loss: 0.0413 (0.0436) time: 2.6403 data: 0.0066 max mem: 33369 +Epoch: [25] [1290/1319] eta: 0:01:22 lr: 1.9463613147552807e-05 loss: 0.0393 (0.0436) time: 2.6161 data: 0.0069 max mem: 33369 +Epoch: [25] [1300/1319] eta: 0:00:54 lr: 1.9454141034694828e-05 loss: 0.0393 (0.0435) time: 2.6268 data: 0.0070 max mem: 33369 +Epoch: [25] [1310/1319] eta: 0:00:25 lr: 1.9444668409373652e-05 loss: 0.0360 (0.0435) time: 2.6394 data: 0.0069 max mem: 33369 +Epoch: [25] Total time: 1:02:40 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 2:16:28 time: 3.1826 data: 3.0337 max mem: 33369 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 100/2573] eta: 0:04:16 time: 0.0723 data: 0.0012 max mem: 33369 +Test: [ 200/2573] eta: 0:03:32 time: 0.0744 data: 0.0013 max mem: 33369 +Test: [ 300/2573] eta: 0:03:11 time: 0.0768 data: 0.0013 max mem: 33369 +Test: [ 400/2573] eta: 0:02:57 time: 0.0771 data: 0.0013 max mem: 33369 +Test: [ 500/2573] eta: 0:02:47 time: 0.0752 data: 0.0013 max mem: 33369 +Test: [ 600/2573] eta: 0:02:37 time: 0.0752 data: 0.0013 max mem: 33369 +Test: [ 700/2573] eta: 0:02:28 time: 0.0754 data: 0.0013 max mem: 33369 +Test: [ 800/2573] eta: 0:02:20 time: 0.0788 data: 0.0013 max mem: 33369 +Test: [ 900/2573] eta: 0:02:11 time: 0.0756 data: 0.0014 max mem: 33369 +Test: [1000/2573] eta: 0:02:03 time: 0.0758 data: 0.0014 max mem: 33369 +Test: [1100/2573] eta: 0:01:55 time: 0.0758 data: 0.0014 max mem: 33369 +Test: [1200/2573] eta: 0:01:47 time: 0.0751 data: 0.0012 max mem: 33369 +Test: [1300/2573] eta: 0:01:39 time: 0.0756 data: 0.0013 max mem: 33369 +Test: [1400/2573] eta: 0:01:31 time: 0.0740 data: 0.0014 max mem: 33369 +Test: [1500/2573] eta: 0:01:23 time: 0.0756 data: 0.0013 max mem: 33369 +Test: [1600/2573] eta: 0:01:15 time: 0.0786 data: 0.0013 max mem: 33369 +Test: [1700/2573] eta: 0:01:07 time: 0.0739 data: 0.0013 max mem: 33369 +Test: [1800/2573] eta: 0:00:59 time: 0.0774 data: 0.0014 max mem: 33369 +Test: [1900/2573] eta: 0:00:51 time: 0.0740 data: 0.0014 max mem: 33369 +Test: [2000/2573] eta: 0:00:44 time: 0.0757 data: 0.0013 max mem: 33369 +Test: [2100/2573] eta: 0:00:36 time: 0.0776 data: 0.0014 max mem: 33369 +Test: [2200/2573] eta: 0:00:28 time: 0.0764 data: 0.0012 max mem: 33369 +Test: [2300/2573] eta: 0:00:20 time: 0.0772 data: 0.0014 max mem: 33369 +Test: [2400/2573] eta: 0:00:13 time: 0.0722 data: 0.0014 max mem: 33369 +Test: [2500/2573] eta: 0:00:05 time: 0.0756 data: 0.0014 max mem: 33369 +Test: Total time: 0:03:17 +Final results: +Mean IoU is 63.65 + + precision@0.5 = 71.59 + precision@0.6 = 66.48 + precision@0.7 = 59.66 + precision@0.8 = 48.10 + precision@0.9 = 23.57 + overall IoU = 62.19 + +Average object IoU 63.65192422372685 +Overall IoU 62.190818786621094 +Better epoch: 25 + +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [26] [ 0/1319] eta: 1:37:59 lr: 1.943614260817638e-05 loss: 0.0799 (0.0799) time: 4.4574 data: 1.3885 max mem: 33369 +Epoch: [26] [ 10/1319] eta: 1:06:57 lr: 1.9426669008334188e-05 loss: 0.0369 (0.0425) time: 3.0692 data: 0.1327 max mem: 33369 +Epoch: [26] [ 20/1319] eta: 1:04:30 lr: 1.941719489514293e-05 loss: 0.0358 (0.0395) time: 2.9058 data: 0.0067 max mem: 33369 +Epoch: [26] [ 30/1319] eta: 1:03:07 lr: 1.9407720268296455e-05 loss: 0.0362 (0.0386) time: 2.8661 data: 0.0071 max mem: 33369 +Epoch: [26] [ 40/1319] eta: 1:01:49 lr: 1.9398245127488253e-05 loss: 0.0378 (0.0379) time: 2.8175 data: 0.0073 max mem: 33369 +Epoch: [26] [ 50/1319] eta: 1:00:21 lr: 1.9388769472411493e-05 loss: 0.0388 (0.0388) time: 2.7239 data: 0.0069 max mem: 33369 +Epoch: [26] [ 60/1319] eta: 0:59:08 lr: 1.9379293302758954e-05 loss: 0.0364 (0.0378) time: 2.6502 data: 0.0068 max mem: 33369 +Epoch: [26] [ 70/1319] eta: 0:58:00 lr: 1.936981661822309e-05 loss: 0.0364 (0.0384) time: 2.6143 data: 0.0068 max mem: 33369 +Epoch: [26] [ 80/1319] eta: 0:57:08 lr: 1.9360339418495996e-05 loss: 0.0388 (0.0385) time: 2.6107 data: 0.0067 max mem: 33369 +Epoch: [26] [ 90/1319] eta: 0:56:26 lr: 1.935086170326942e-05 loss: 0.0381 (0.0385) time: 2.6450 data: 0.0066 max mem: 33369 +Epoch: [26] [ 100/1319] eta: 0:55:42 lr: 1.934138347223476e-05 loss: 0.0430 (0.0408) time: 2.6385 data: 0.0067 max mem: 33369 +Epoch: [26] [ 110/1319] eta: 0:55:03 lr: 1.9331904725083057e-05 loss: 0.0388 (0.0406) time: 2.6274 data: 0.0067 max mem: 33369 +Epoch: [26] [ 120/1319] eta: 0:54:28 lr: 1.9322425461504988e-05 loss: 0.0381 (0.0407) time: 2.6448 data: 0.0066 max mem: 33369 +Epoch: [26] [ 130/1319] eta: 0:53:56 lr: 1.931294568119089e-05 loss: 0.0394 (0.0409) time: 2.6643 data: 0.0068 max mem: 33369 +Epoch: [26] [ 140/1319] eta: 0:53:21 lr: 1.930346538383074e-05 loss: 0.0441 (0.0411) time: 2.6552 data: 0.0067 max mem: 33369 +Epoch: [26] [ 150/1319] eta: 0:52:52 lr: 1.9293984569114164e-05 loss: 0.0417 (0.0411) time: 2.6607 data: 0.0065 max mem: 33369 +Epoch: [26] [ 160/1319] eta: 0:52:18 lr: 1.9284503236730435e-05 loss: 0.0383 (0.0412) time: 2.6568 data: 0.0064 max mem: 33369 +Epoch: [26] [ 170/1319] eta: 0:51:47 lr: 1.927502138636845e-05 loss: 0.0436 (0.0416) time: 2.6327 data: 0.0064 max mem: 33369 +Epoch: [26] [ 180/1319] eta: 0:51:15 lr: 1.9265539017716765e-05 loss: 0.0367 (0.0410) time: 2.6303 data: 0.0066 max mem: 33369 +Epoch: [26] [ 190/1319] eta: 0:50:43 lr: 1.9256056130463582e-05 loss: 0.0344 (0.0413) time: 2.6183 data: 0.0065 max mem: 33369 +Epoch: [26] [ 200/1319] eta: 0:50:12 lr: 1.9246572724296735e-05 loss: 0.0396 (0.0412) time: 2.6227 data: 0.0064 max mem: 33369 +Epoch: [26] [ 210/1319] eta: 0:49:40 lr: 1.9237088798903708e-05 loss: 0.0361 (0.0413) time: 2.6170 data: 0.0064 max mem: 33369 +Epoch: [26] [ 220/1319] eta: 0:49:12 lr: 1.922760435397161e-05 loss: 0.0386 (0.0414) time: 2.6291 data: 0.0064 max mem: 33369 +Epoch: [26] [ 230/1319] eta: 0:48:42 lr: 1.9218119389187204e-05 loss: 0.0378 (0.0415) time: 2.6356 data: 0.0064 max mem: 33369 +Epoch: [26] [ 240/1319] eta: 0:48:10 lr: 1.9208633904236885e-05 loss: 0.0362 (0.0419) time: 2.5973 data: 0.0065 max mem: 33369 +Epoch: [26] [ 250/1319] eta: 0:47:41 lr: 1.9199147898806697e-05 loss: 0.0430 (0.0419) time: 2.6000 data: 0.0068 max mem: 33369 +Epoch: [26] [ 260/1319] eta: 0:47:11 lr: 1.9189661372582306e-05 loss: 0.0396 (0.0416) time: 2.6050 data: 0.0067 max mem: 33369 +Epoch: [26] [ 270/1319] eta: 0:46:41 lr: 1.918017432524904e-05 loss: 0.0348 (0.0415) time: 2.5968 data: 0.0065 max mem: 33369 +Epoch: [26] [ 280/1319] eta: 0:46:14 lr: 1.9170686756491828e-05 loss: 0.0360 (0.0415) time: 2.6320 data: 0.0065 max mem: 33369 +Epoch: [26] [ 290/1319] eta: 0:45:46 lr: 1.916119866599526e-05 loss: 0.0378 (0.0415) time: 2.6435 data: 0.0066 max mem: 33369 +Epoch: [26] [ 300/1319] eta: 0:45:18 lr: 1.9151710053443563e-05 loss: 0.0362 (0.0414) time: 2.6279 data: 0.0066 max mem: 33369 +Epoch: [26] [ 310/1319] eta: 0:44:50 lr: 1.9142220918520593e-05 loss: 0.0358 (0.0411) time: 2.6257 data: 0.0067 max mem: 33369 +Epoch: [26] [ 320/1319] eta: 0:44:22 lr: 1.9132731260909836e-05 loss: 0.0327 (0.0410) time: 2.6294 data: 0.0066 max mem: 33369 +Epoch: [26] [ 330/1319] eta: 0:43:53 lr: 1.9123241080294413e-05 loss: 0.0390 (0.0411) time: 2.6105 data: 0.0065 max mem: 33369 +Epoch: [26] [ 340/1319] eta: 0:43:26 lr: 1.9113750376357084e-05 loss: 0.0416 (0.0414) time: 2.6097 data: 0.0065 max mem: 33369 +Epoch: [26] [ 350/1319] eta: 0:42:59 lr: 1.9104259148780233e-05 loss: 0.0366 (0.0412) time: 2.6464 data: 0.0065 max mem: 33369 +Epoch: [26] [ 360/1319] eta: 0:42:31 lr: 1.909476739724589e-05 loss: 0.0336 (0.0412) time: 2.6438 data: 0.0064 max mem: 33369 +Epoch: [26] [ 370/1319] eta: 0:42:03 lr: 1.9085275121435705e-05 loss: 0.0372 (0.0413) time: 2.6128 data: 0.0066 max mem: 33369 +Epoch: [26] [ 380/1319] eta: 0:41:35 lr: 1.907578232103095e-05 loss: 0.0348 (0.0413) time: 2.6021 data: 0.0068 max mem: 33369 +Epoch: [26] [ 390/1319] eta: 0:41:08 lr: 1.906628899571255e-05 loss: 0.0346 (0.0412) time: 2.6103 data: 0.0068 max mem: 33369 +Epoch: [26] [ 400/1319] eta: 0:40:41 lr: 1.9056795145161037e-05 loss: 0.0346 (0.0411) time: 2.6302 data: 0.0066 max mem: 33369 +Epoch: [26] [ 410/1319] eta: 0:40:13 lr: 1.9047300769056588e-05 loss: 0.0334 (0.0409) time: 2.6153 data: 0.0064 max mem: 33369 +Epoch: [26] [ 420/1319] eta: 0:39:46 lr: 1.9037805867078998e-05 loss: 0.0393 (0.0409) time: 2.6155 data: 0.0065 max mem: 33369 +Epoch: [26] [ 430/1319] eta: 0:39:19 lr: 1.9028310438907695e-05 loss: 0.0357 (0.0409) time: 2.6367 data: 0.0066 max mem: 33369 +Epoch: [26] [ 440/1319] eta: 0:38:51 lr: 1.901881448422173e-05 loss: 0.0334 (0.0409) time: 2.6055 data: 0.0065 max mem: 33369 +Epoch: [26] [ 450/1319] eta: 0:38:23 lr: 1.900931800269978e-05 loss: 0.0373 (0.0408) time: 2.5814 data: 0.0065 max mem: 33369 +Epoch: [26] [ 460/1319] eta: 0:37:56 lr: 1.8999820994020145e-05 loss: 0.0360 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data: 0.0066 max mem: 33369 +Epoch: [26] [ 780/1319] eta: 0:23:42 lr: 1.8695636432127905e-05 loss: 0.0369 (0.0413) time: 2.6236 data: 0.0066 max mem: 33369 +Epoch: [26] [ 790/1319] eta: 0:23:16 lr: 1.8686121844283114e-05 loss: 0.0328 (0.0412) time: 2.6312 data: 0.0066 max mem: 33369 +Epoch: [26] [ 800/1319] eta: 0:22:50 lr: 1.8676606718115407e-05 loss: 0.0312 (0.0412) time: 2.6402 data: 0.0065 max mem: 33369 +Epoch: [26] [ 810/1319] eta: 0:22:23 lr: 1.866709105328956e-05 loss: 0.0332 (0.0414) time: 2.6191 data: 0.0065 max mem: 33369 +Epoch: [26] [ 820/1319] eta: 0:21:57 lr: 1.8657574849469954e-05 loss: 0.0342 (0.0416) time: 2.6205 data: 0.0065 max mem: 33369 +Epoch: [26] [ 830/1319] eta: 0:21:30 lr: 1.864805810632056e-05 loss: 0.0355 (0.0418) time: 2.6387 data: 0.0065 max mem: 33369 +Epoch: [26] [ 840/1319] eta: 0:21:04 lr: 1.8638540823504965e-05 loss: 0.0355 (0.0419) time: 2.6316 data: 0.0066 max mem: 33369 +Epoch: [26] [ 850/1319] eta: 0:20:37 lr: 1.8629023000686338e-05 loss: 0.0351 (0.0418) time: 2.6038 data: 0.0068 max mem: 33369 +Epoch: [26] [ 860/1319] eta: 0:20:10 lr: 1.8619504637527467e-05 loss: 0.0373 (0.0418) time: 2.5979 data: 0.0068 max mem: 33369 +Epoch: [26] [ 870/1319] eta: 0:19:44 lr: 1.8609985733690715e-05 loss: 0.0374 (0.0418) time: 2.6047 data: 0.0066 max mem: 33369 +Epoch: [26] [ 880/1319] eta: 0:19:17 lr: 1.860046628883806e-05 loss: 0.0407 (0.0419) time: 2.6162 data: 0.0065 max mem: 33369 +Epoch: [26] [ 890/1319] eta: 0:18:51 lr: 1.859094630263106e-05 loss: 0.0430 (0.0419) time: 2.6227 data: 0.0064 max mem: 33369 +Epoch: [26] [ 900/1319] eta: 0:18:25 lr: 1.8581425774730882e-05 loss: 0.0386 (0.0419) time: 2.6584 data: 0.0065 max mem: 33369 +Epoch: [26] [ 910/1319] eta: 0:17:58 lr: 1.8571904704798292e-05 loss: 0.0367 (0.0419) time: 2.6466 data: 0.0066 max mem: 33369 +Epoch: [26] [ 920/1319] eta: 0:17:32 lr: 1.856238309249363e-05 loss: 0.0410 (0.0419) time: 2.5987 data: 0.0066 max mem: 33369 +Epoch: [26] [ 930/1319] eta: 0:17:05 lr: 1.855286093747684e-05 loss: 0.0413 (0.0420) time: 2.6162 data: 0.0065 max mem: 33369 +Epoch: [26] [ 940/1319] eta: 0:16:39 lr: 1.854333823940747e-05 loss: 0.0428 (0.0420) time: 2.6390 data: 0.0066 max mem: 33369 +Epoch: [26] [ 950/1319] eta: 0:16:12 lr: 1.853381499794464e-05 loss: 0.0412 (0.0421) time: 2.6093 data: 0.0068 max mem: 33369 +Epoch: [26] [ 960/1319] eta: 0:15:46 lr: 1.8524291212747084e-05 loss: 0.0421 (0.0421) time: 2.6039 data: 0.0066 max mem: 33369 +Epoch: [26] [ 970/1319] eta: 0:15:20 lr: 1.85147668834731e-05 loss: 0.0376 (0.0421) time: 2.6407 data: 0.0064 max mem: 33369 +Epoch: [26] [ 980/1319] eta: 0:14:53 lr: 1.8505242009780593e-05 loss: 0.0347 (0.0421) time: 2.6466 data: 0.0064 max mem: 33369 +Epoch: [26] [ 990/1319] eta: 0:14:27 lr: 1.8495716591327057e-05 loss: 0.0376 (0.0421) time: 2.6361 data: 0.0065 max mem: 33369 +Epoch: [26] [1000/1319] eta: 0:14:01 lr: 1.848619062776957e-05 loss: 0.0357 (0.0421) time: 2.6199 data: 0.0064 max mem: 33369 +Epoch: [26] [1010/1319] eta: 0:13:34 lr: 1.8476664118764797e-05 loss: 0.0295 (0.0420) time: 2.6331 data: 0.0064 max mem: 33369 +Epoch: [26] [1020/1319] eta: 0:13:08 lr: 1.8467137063969e-05 loss: 0.0340 (0.0420) time: 2.6362 data: 0.0065 max mem: 33369 +Epoch: [26] [1030/1319] eta: 0:12:41 lr: 1.8457609463038007e-05 loss: 0.0367 (0.0420) time: 2.6223 data: 0.0066 max mem: 33369 +Epoch: [26] [1040/1319] eta: 0:12:15 lr: 1.8448081315627246e-05 loss: 0.0362 (0.0419) time: 2.6381 data: 0.0067 max mem: 33369 +Epoch: [26] [1050/1319] eta: 0:11:49 lr: 1.843855262139173e-05 loss: 0.0347 (0.0419) time: 2.6333 data: 0.0066 max mem: 33369 +Epoch: [26] [1060/1319] eta: 0:11:22 lr: 1.8429023379986053e-05 loss: 0.0350 (0.0418) time: 2.6267 data: 0.0065 max mem: 33369 +Epoch: [26] [1070/1319] eta: 0:10:56 lr: 1.8419493591064395e-05 loss: 0.0357 (0.0419) time: 2.6165 data: 0.0066 max mem: 33369 +Epoch: [26] [1080/1319] eta: 0:10:30 lr: 1.840996325428051e-05 loss: 0.0367 (0.0419) time: 2.6358 data: 0.0067 max mem: 33369 +Epoch: [26] [1090/1319] eta: 0:10:03 lr: 1.840043236928774e-05 loss: 0.0360 (0.0418) time: 2.6586 data: 0.0068 max mem: 33369 +Epoch: [26] [1100/1319] eta: 0:09:37 lr: 1.839090093573901e-05 loss: 0.0430 (0.0419) time: 2.6192 data: 0.0067 max mem: 33369 +Epoch: [26] [1110/1319] eta: 0:09:10 lr: 1.838136895328682e-05 loss: 0.0420 (0.0419) time: 2.6024 data: 0.0066 max mem: 33369 +Epoch: [26] [1120/1319] eta: 0:08:44 lr: 1.8371836421583257e-05 loss: 0.0387 (0.0419) time: 2.5977 data: 0.0066 max mem: 33369 +Epoch: [26] [1130/1319] eta: 0:08:18 lr: 1.836230334027998e-05 loss: 0.0369 (0.0420) time: 2.6330 data: 0.0066 max mem: 33369 +Epoch: [26] [1140/1319] eta: 0:07:51 lr: 1.8352769709028224e-05 loss: 0.0401 (0.0421) time: 2.6494 data: 0.0065 max mem: 33369 +Epoch: [26] [1150/1319] eta: 0:07:25 lr: 1.8343235527478807e-05 loss: 0.0369 (0.0420) time: 2.6121 data: 0.0064 max mem: 33369 +Epoch: [26] [1160/1319] eta: 0:06:59 lr: 1.8333700795282125e-05 loss: 0.0358 (0.0420) time: 2.6549 data: 0.0065 max mem: 33369 +Epoch: [26] [1170/1319] eta: 0:06:32 lr: 1.832416551208814e-05 loss: 0.0424 (0.0421) time: 2.6726 data: 0.0066 max mem: 33369 +Epoch: [26] [1180/1319] eta: 0:06:06 lr: 1.8314629677546413e-05 loss: 0.0399 (0.0421) time: 2.6139 data: 0.0066 max mem: 33369 +Epoch: [26] [1190/1319] eta: 0:05:39 lr: 1.8305093291306038e-05 loss: 0.0399 (0.0422) time: 2.6162 data: 0.0066 max mem: 33369 +Epoch: [26] [1200/1319] eta: 0:05:13 lr: 1.829555635301572e-05 loss: 0.0360 (0.0421) time: 2.6222 data: 0.0066 max mem: 33369 +Epoch: [26] [1210/1319] eta: 0:04:47 lr: 1.8286018862323718e-05 loss: 0.0368 (0.0422) time: 2.6104 data: 0.0067 max mem: 33369 +Epoch: [26] [1220/1319] eta: 0:04:20 lr: 1.8276480818877866e-05 loss: 0.0442 (0.0423) time: 2.6197 data: 0.0066 max mem: 33369 +Epoch: [26] [1230/1319] eta: 0:03:54 lr: 1.8266942222325584e-05 loss: 0.0399 (0.0423) time: 2.6221 data: 0.0065 max mem: 33369 +Epoch: [26] [1240/1319] eta: 0:03:28 lr: 1.8257403072313833e-05 loss: 0.0339 (0.0423) time: 2.6188 data: 0.0065 max mem: 33369 +Epoch: [26] [1250/1319] eta: 0:03:01 lr: 1.8247863368489165e-05 loss: 0.0397 (0.0423) time: 2.5957 data: 0.0065 max mem: 33369 +Epoch: [26] [1260/1319] eta: 0:02:35 lr: 1.8238323110497695e-05 loss: 0.0407 (0.0423) time: 2.6127 data: 0.0068 max mem: 33369 +Epoch: [26] [1270/1319] eta: 0:02:09 lr: 1.822878229798511e-05 loss: 0.0359 (0.0423) time: 2.6330 data: 0.0068 max mem: 33369 +Epoch: [26] [1280/1319] eta: 0:01:42 lr: 1.821924093059666e-05 loss: 0.0358 (0.0422) time: 2.6157 data: 0.0066 max mem: 33369 +Epoch: [26] [1290/1319] eta: 0:01:16 lr: 1.8209699007977167e-05 loss: 0.0336 (0.0422) time: 2.5991 data: 0.0065 max mem: 33369 +Epoch: [26] [1300/1319] eta: 0:00:50 lr: 1.8200156529771002e-05 loss: 0.0332 (0.0422) time: 2.5897 data: 0.0064 max mem: 33369 +Epoch: [26] [1310/1319] eta: 0:00:23 lr: 1.819061349562212e-05 loss: 0.0415 (0.0422) time: 2.5904 data: 0.0065 max mem: 33369 +Epoch: [26] Total time: 0:57:53 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 2:19:46 time: 3.2596 data: 3.1822 max mem: 33369 +Test: [ 100/2573] eta: 0:04:15 time: 0.0715 data: 0.0011 max mem: 33369 +Test: [ 200/2573] eta: 0:03:30 time: 0.0734 data: 0.0011 max mem: 33369 +Test: [ 300/2573] eta: 0:03:09 time: 0.0752 data: 0.0011 max mem: 33369 +Test: [ 400/2573] eta: 0:02:55 time: 0.0752 data: 0.0011 max mem: 33369 +Test: [ 500/2573] eta: 0:02:44 time: 0.0737 data: 0.0011 max mem: 33369 +Test: [ 600/2573] eta: 0:02:34 time: 0.0736 data: 0.0011 max mem: 33369 +Test: [ 700/2573] eta: 0:02:26 time: 0.0738 data: 0.0011 max mem: 33369 +Test: [ 800/2573] eta: 0:02:17 time: 0.0772 data: 0.0011 max mem: 33369 +Test: [ 900/2573] eta: 0:02:09 time: 0.0737 data: 0.0011 max mem: 33369 +Test: [1000/2573] eta: 0:02:01 time: 0.0738 data: 0.0011 max mem: 33369 +Test: [1100/2573] eta: 0:01:53 time: 0.0739 data: 0.0011 max mem: 33369 +Test: [1200/2573] eta: 0:01:45 time: 0.0739 data: 0.0011 max mem: 33369 +Test: [1300/2573] eta: 0:01:37 time: 0.0738 data: 0.0011 max mem: 33369 +Test: [1400/2573] eta: 0:01:29 time: 0.0722 data: 0.0011 max mem: 33369 +Test: [1500/2573] eta: 0:01:21 time: 0.0738 data: 0.0011 max mem: 33369 +Test: [1600/2573] eta: 0:01:13 time: 0.0771 data: 0.0011 max mem: 33369 +Test: [1700/2573] eta: 0:01:06 time: 0.0720 data: 0.0011 max mem: 33369 +Test: [1800/2573] eta: 0:00:58 time: 0.0755 data: 0.0011 max mem: 33369 +Test: [1900/2573] eta: 0:00:50 time: 0.0721 data: 0.0011 max mem: 33369 +Test: [2000/2573] eta: 0:00:43 time: 0.0737 data: 0.0011 max mem: 33369 +Test: [2100/2573] eta: 0:00:35 time: 0.0753 data: 0.0011 max mem: 33369 +Test: [2200/2573] eta: 0:00:28 time: 0.0753 data: 0.0011 max mem: 33369 +Test: [2300/2573] eta: 0:00:20 time: 0.0755 data: 0.0011 max mem: 33369 +Test: [2400/2573] eta: 0:00:12 time: 0.0705 data: 0.0011 max mem: 33369 +Test: [2500/2573] eta: 0:00:05 time: 0.0738 data: 0.0011 max mem: 33369 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: Total time: 0:03:13 +Final results: +Mean IoU is 64.35 + + precision@0.5 = 71.96 + precision@0.6 = 66.32 + precision@0.7 = 58.84 + precision@0.8 = 47.20 + precision@0.9 = 23.14 + overall IoU = 61.97 + +Average object IoU 64.35138910034924 +Overall IoU 61.97362518310547 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [27] [ 0/1319] eta: 3:10:55 lr: 1.818202428926248e-05 loss: 0.0291 (0.0291) time: 8.6847 data: 2.7922 max mem: 33369 +Epoch: [27] [ 10/1319] eta: 1:09:40 lr: 1.817248019783995e-05 loss: 0.0505 (0.0476) time: 3.1938 data: 0.2595 max mem: 33369 +Epoch: [27] [ 20/1319] eta: 1:03:29 lr: 1.8162935549439682e-05 loss: 0.0409 (0.0441) time: 2.6453 data: 0.0061 max mem: 33369 +Epoch: [27] [ 30/1319] eta: 1:00:52 lr: 1.8153390343703928e-05 loss: 0.0391 (0.0435) time: 2.6359 data: 0.0063 max mem: 33369 +Epoch: [27] [ 40/1319] eta: 0:59:31 lr: 1.8143844580274487e-05 loss: 0.0356 (0.0405) time: 2.6451 data: 0.0065 max mem: 33369 +Epoch: [27] [ 50/1319] eta: 0:58:24 lr: 1.813429825879272e-05 loss: 0.0356 (0.0409) time: 2.6505 data: 0.0065 max mem: 33369 +Epoch: [27] [ 60/1319] eta: 0:57:39 lr: 1.8124751378899558e-05 loss: 0.0417 (0.0407) time: 2.6563 data: 0.0065 max mem: 33369 +Epoch: [27] [ 70/1319] eta: 0:56:55 lr: 1.811520394023548e-05 loss: 0.0361 (0.0403) time: 2.6660 data: 0.0066 max mem: 33369 +Epoch: [27] [ 80/1319] eta: 0:56:12 lr: 1.8105655942440525e-05 loss: 0.0343 (0.0400) time: 2.6427 data: 0.0065 max mem: 33369 +Epoch: [27] [ 90/1319] eta: 0:55:33 lr: 1.8096107385154294e-05 loss: 0.0331 (0.0397) time: 2.6309 data: 0.0065 max mem: 33369 +Epoch: [27] [ 100/1319] eta: 0:55:01 lr: 1.8086558268015952e-05 loss: 0.0341 (0.0402) time: 2.6533 data: 0.0066 max mem: 33369 +Epoch: [27] [ 110/1319] eta: 0:54:28 lr: 1.807700859066419e-05 loss: 0.0387 (0.0404) time: 2.6653 data: 0.0066 max mem: 33369 +Epoch: [27] [ 120/1319] eta: 0:53:52 lr: 1.8067458352737284e-05 loss: 0.0345 (0.0402) time: 2.6343 data: 0.0066 max mem: 33369 +Epoch: [27] [ 130/1319] eta: 0:53:24 lr: 1.8057907553873043e-05 loss: 0.0399 (0.0404) time: 2.6462 data: 0.0067 max mem: 33369 +Epoch: [27] [ 140/1319] eta: 0:52:54 lr: 1.8048356193708847e-05 loss: 0.0389 (0.0399) time: 2.6735 data: 0.0067 max mem: 33369 +Epoch: [27] [ 150/1319] eta: 0:52:20 lr: 1.803880427188162e-05 loss: 0.0310 (0.0396) time: 2.6333 data: 0.0065 max mem: 33369 +Epoch: [27] [ 160/1319] eta: 0:51:53 lr: 1.802925178802783e-05 loss: 0.0344 (0.0399) time: 2.6423 data: 0.0065 max mem: 33369 +Epoch: [27] [ 170/1319] eta: 0:51:23 lr: 1.8019698741783504e-05 loss: 0.0344 (0.0396) time: 2.6605 data: 0.0066 max mem: 33369 +Epoch: [27] [ 180/1319] eta: 0:50:53 lr: 1.8010145132784217e-05 loss: 0.0300 (0.0396) time: 2.6371 data: 0.0066 max mem: 33369 +Epoch: [27] [ 190/1319] eta: 0:50:26 lr: 1.8000590960665095e-05 loss: 0.0319 (0.0393) time: 2.6582 data: 0.0064 max mem: 33369 +Epoch: [27] [ 200/1319] eta: 0:49:56 lr: 1.7991036225060814e-05 loss: 0.0344 (0.0391) time: 2.6497 data: 0.0064 max mem: 33369 +Epoch: [27] [ 210/1319] eta: 0:49:28 lr: 1.7981480925605583e-05 loss: 0.0378 (0.0392) time: 2.6356 data: 0.0066 max mem: 33369 +Epoch: [27] [ 220/1319] eta: 0:49:00 lr: 1.7971925061933174e-05 loss: 0.0382 (0.0392) time: 2.6488 data: 0.0066 max mem: 33369 +Epoch: [27] [ 230/1319] eta: 0:48:29 lr: 1.7962368633676893e-05 loss: 0.0376 (0.0390) time: 2.6241 data: 0.0065 max mem: 33369 +Epoch: [27] [ 240/1319] eta: 0:48:03 lr: 1.7952811640469606e-05 loss: 0.0350 (0.0391) time: 2.6368 data: 0.0066 max mem: 33369 +Epoch: [27] [ 250/1319] eta: 0:47:35 lr: 1.7943254081943704e-05 loss: 0.0324 (0.0391) time: 2.6587 data: 0.0066 max mem: 33369 +Epoch: [27] [ 260/1319] eta: 0:47:05 lr: 1.7933695957731138e-05 loss: 0.0328 (0.0390) time: 2.6240 data: 0.0065 max mem: 33369 +Epoch: [27] [ 270/1319] eta: 0:46:38 lr: 1.7924137267463387e-05 loss: 0.0334 (0.0388) time: 2.6323 data: 0.0065 max mem: 33369 +Epoch: [27] [ 280/1319] eta: 0:46:11 lr: 1.7914578010771477e-05 loss: 0.0341 (0.0387) time: 2.6495 data: 0.0064 max mem: 33369 +Epoch: [27] [ 290/1319] eta: 0:45:43 lr: 1.7905018187285976e-05 loss: 0.0361 (0.0386) time: 2.6368 data: 0.0065 max mem: 33369 +Epoch: [27] [ 300/1319] eta: 0:45:15 lr: 1.7895457796636998e-05 loss: 0.0361 (0.0386) time: 2.6328 data: 0.0066 max mem: 33369 +Epoch: [27] [ 310/1319] eta: 0:44:50 lr: 1.7885896838454187e-05 loss: 0.0363 (0.0386) time: 2.6734 data: 0.0066 max mem: 33369 +Epoch: [27] [ 320/1319] eta: 0:44:23 lr: 1.787633531236672e-05 loss: 0.0360 (0.0385) time: 2.6895 data: 0.0066 max mem: 33369 +Epoch: [27] [ 330/1319] eta: 0:43:57 lr: 1.786677321800332e-05 loss: 0.0365 (0.0386) time: 2.6669 data: 0.0067 max mem: 33369 +Epoch: [27] [ 340/1319] eta: 0:43:30 lr: 1.7857210554992246e-05 loss: 0.0396 (0.0388) time: 2.6607 data: 0.0066 max mem: 33369 +Epoch: [27] [ 350/1319] eta: 0:43:03 lr: 1.7847647322961293e-05 loss: 0.0364 (0.0387) time: 2.6558 data: 0.0068 max mem: 33369 +Epoch: [27] [ 360/1319] eta: 0:42:37 lr: 1.783808352153779e-05 loss: 0.0422 (0.0388) time: 2.6724 data: 0.0070 max mem: 33369 +Epoch: [27] [ 370/1319] eta: 0:42:10 lr: 1.782851915034859e-05 loss: 0.0420 (0.0388) time: 2.6793 data: 0.0070 max mem: 33369 +Epoch: [27] [ 380/1319] eta: 0:41:43 lr: 1.78189542090201e-05 loss: 0.0319 (0.0387) time: 2.6623 data: 0.0069 max mem: 33369 +Epoch: [27] [ 390/1319] eta: 0:41:18 lr: 1.780938869717823e-05 loss: 0.0329 (0.0388) time: 2.6824 data: 0.0068 max mem: 33369 +Epoch: [27] [ 400/1319] eta: 0:40:52 lr: 1.779982261444845e-05 loss: 0.0371 (0.0388) time: 2.7191 data: 0.0069 max mem: 33369 +Epoch: [27] [ 410/1319] eta: 0:40:26 lr: 1.7790255960455746e-05 loss: 0.0368 (0.0387) time: 2.7096 data: 0.0069 max mem: 33369 +Epoch: [27] [ 420/1319] eta: 0:40:00 lr: 1.7780688734824637e-05 loss: 0.0379 (0.0388) time: 2.6966 data: 0.0067 max mem: 33369 +Epoch: [27] [ 430/1319] eta: 0:39:32 lr: 1.777112093717916e-05 loss: 0.0372 (0.0387) time: 2.6629 data: 0.0067 max mem: 33369 +Epoch: [27] [ 440/1319] eta: 0:39:06 lr: 1.7761552567142895e-05 loss: 0.0370 (0.0389) time: 2.6682 data: 0.0068 max mem: 33369 +Epoch: [27] [ 450/1319] eta: 0:38:40 lr: 1.7751983624338938e-05 loss: 0.0366 (0.0387) time: 2.6868 data: 0.0070 max mem: 33369 +Epoch: [27] [ 460/1319] eta: 0:38:12 lr: 1.7742414108389917e-05 loss: 0.0322 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0.0341 (0.0402) time: 2.6961 data: 0.0067 max mem: 33369 +Epoch: [27] [ 860/1319] eta: 0:20:28 lr: 1.7359159099747958e-05 loss: 0.0319 (0.0401) time: 2.6935 data: 0.0066 max mem: 33369 +Epoch: [27] [ 870/1319] eta: 0:20:02 lr: 1.7349565753959942e-05 loss: 0.0342 (0.0401) time: 2.6909 data: 0.0067 max mem: 33369 +Epoch: [27] [ 880/1319] eta: 0:19:35 lr: 1.7339971818737108e-05 loss: 0.0384 (0.0401) time: 2.6971 data: 0.0068 max mem: 33369 +Epoch: [27] [ 890/1319] eta: 0:19:09 lr: 1.733037729368083e-05 loss: 0.0407 (0.0402) time: 2.7380 data: 0.0069 max mem: 33369 +Epoch: [27] [ 900/1319] eta: 0:18:42 lr: 1.7320782178391982e-05 loss: 0.0407 (0.0402) time: 2.7244 data: 0.0069 max mem: 33369 +Epoch: [27] [ 910/1319] eta: 0:18:16 lr: 1.7311186472470895e-05 loss: 0.0332 (0.0401) time: 2.7295 data: 0.0069 max mem: 33369 +Epoch: [27] [ 920/1319] eta: 0:17:49 lr: 1.7301590175517403e-05 loss: 0.0309 (0.0401) time: 2.7525 data: 0.0069 max mem: 33369 +Epoch: [27] [ 930/1319] eta: 0:17:22 lr: 1.7291993287130824e-05 loss: 0.0359 (0.0401) time: 2.7245 data: 0.0068 max mem: 33369 +Epoch: [27] [ 940/1319] eta: 0:16:56 lr: 1.728239580690995e-05 loss: 0.0344 (0.0400) time: 2.7177 data: 0.0070 max mem: 33369 +Epoch: [27] [ 950/1319] eta: 0:16:29 lr: 1.727279773445306e-05 loss: 0.0322 (0.0399) time: 2.7396 data: 0.0071 max mem: 33369 +Epoch: [27] [ 960/1319] eta: 0:16:02 lr: 1.7263199069357895e-05 loss: 0.0307 (0.0399) time: 2.7043 data: 0.0069 max mem: 33369 +Epoch: [27] [ 970/1319] eta: 0:15:35 lr: 1.725359981122169e-05 loss: 0.0315 (0.0398) time: 2.6737 data: 0.0067 max mem: 33369 +Epoch: [27] [ 980/1319] eta: 0:15:09 lr: 1.7243999959641156e-05 loss: 0.0348 (0.0398) time: 2.7308 data: 0.0069 max mem: 33369 +Epoch: [27] [ 990/1319] eta: 0:14:42 lr: 1.7234399514212475e-05 loss: 0.0388 (0.0398) time: 2.7580 data: 0.0069 max mem: 33369 +Epoch: [27] [1000/1319] eta: 0:14:15 lr: 1.7224798474531302e-05 loss: 0.0374 (0.0399) time: 2.6953 data: 0.0067 max mem: 33369 +Epoch: [27] 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mem: 33369 +Epoch: [27] [1090/1319] eta: 0:10:13 lr: 1.7138362309061432e-05 loss: 0.0326 (0.0399) time: 2.6325 data: 0.0065 max mem: 33369 +Epoch: [27] [1100/1319] eta: 0:09:46 lr: 1.7128755304500424e-05 loss: 0.0389 (0.0400) time: 2.6523 data: 0.0066 max mem: 33369 +Epoch: [27] [1110/1319] eta: 0:09:19 lr: 1.7119147701204254e-05 loss: 0.0349 (0.0400) time: 2.6774 data: 0.0065 max mem: 33369 +Epoch: [27] [1120/1319] eta: 0:08:53 lr: 1.710953949876218e-05 loss: 0.0330 (0.0400) time: 2.6707 data: 0.0064 max mem: 33369 +Epoch: [27] [1130/1319] eta: 0:08:26 lr: 1.709993069676296e-05 loss: 0.0322 (0.0400) time: 2.6555 data: 0.0066 max mem: 33369 +Epoch: [27] [1140/1319] eta: 0:07:59 lr: 1.7090321294794796e-05 loss: 0.0362 (0.0400) time: 2.6689 data: 0.0067 max mem: 33369 +Epoch: [27] [1150/1319] eta: 0:07:32 lr: 1.7080711292445346e-05 loss: 0.0367 (0.0400) time: 2.6539 data: 0.0066 max mem: 33369 +Epoch: [27] [1160/1319] eta: 0:07:05 lr: 1.7071100689301735e-05 loss: 0.0370 (0.0400) time: 2.6363 data: 0.0066 max mem: 33369 +Epoch: [27] [1170/1319] eta: 0:06:38 lr: 1.706148948495055e-05 loss: 0.0382 (0.0401) time: 2.6374 data: 0.0066 max mem: 33369 +Epoch: [27] [1180/1319] eta: 0:06:12 lr: 1.705187767897781e-05 loss: 0.0372 (0.0401) time: 2.6197 data: 0.0065 max mem: 33369 +Epoch: [27] [1190/1319] eta: 0:05:45 lr: 1.704226527096902e-05 loss: 0.0372 (0.0401) time: 2.6469 data: 0.0064 max mem: 33369 +Epoch: [27] [1200/1319] eta: 0:05:18 lr: 1.703265226050912e-05 loss: 0.0361 (0.0401) time: 2.6467 data: 0.0065 max mem: 33369 +Epoch: [27] [1210/1319] eta: 0:04:51 lr: 1.702303864718251e-05 loss: 0.0350 (0.0401) time: 2.6190 data: 0.0065 max mem: 33369 +Epoch: [27] [1220/1319] eta: 0:04:24 lr: 1.7013424430573045e-05 loss: 0.0368 (0.0402) time: 2.6485 data: 0.0065 max mem: 33369 +Epoch: [27] [1230/1319] eta: 0:03:58 lr: 1.7003809610264022e-05 loss: 0.0368 (0.0402) time: 2.6570 data: 0.0064 max mem: 33369 +Epoch: [27] [1240/1319] eta: 0:03:31 lr: 1.6994194185838196e-05 loss: 0.0424 (0.0402) time: 2.6549 data: 0.0065 max mem: 33369 +Epoch: [27] [1250/1319] eta: 0:03:04 lr: 1.698457815687777e-05 loss: 0.0381 (0.0402) time: 2.6569 data: 0.0065 max mem: 33369 +Epoch: [27] [1260/1319] eta: 0:02:37 lr: 1.6974961522964392e-05 loss: 0.0358 (0.0402) time: 2.6202 data: 0.0066 max mem: 33369 +Epoch: [27] [1270/1319] eta: 0:02:11 lr: 1.6965344283679166e-05 loss: 0.0358 (0.0402) time: 2.6216 data: 0.0067 max mem: 33369 +Epoch: [27] [1280/1319] eta: 0:01:44 lr: 1.6955726438602627e-05 loss: 0.0370 (0.0403) time: 2.6592 data: 0.0065 max mem: 33369 +Epoch: [27] [1290/1319] eta: 0:01:17 lr: 1.694610798731476e-05 loss: 0.0357 (0.0403) time: 2.6485 data: 0.0065 max mem: 33369 +Epoch: [27] [1300/1319] eta: 0:00:50 lr: 1.6936488929395006e-05 loss: 0.0283 (0.0403) time: 2.6471 data: 0.0065 max mem: 33369 +Epoch: [27] [1310/1319] eta: 0:00:24 lr: 1.6926869264422233e-05 loss: 0.0309 (0.0404) time: 2.6428 data: 0.0066 max mem: 33369 +Epoch: [27] Total time: 0:58:47 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 2:24:05 time: 3.3599 data: 3.2766 max mem: 33369 +Test: [ 100/2573] eta: 0:04:18 time: 0.0716 data: 0.0011 max mem: 33369 +Test: [ 200/2573] eta: 0:03:32 time: 0.0734 data: 0.0011 max mem: 33369 +Test: [ 300/2573] eta: 0:03:10 time: 0.0752 data: 0.0011 max mem: 33369 +Test: [ 400/2573] eta: 0:02:56 time: 0.0754 data: 0.0011 max mem: 33369 +Test: [ 500/2573] eta: 0:02:45 time: 0.0737 data: 0.0011 max mem: 33369 +Test: [ 600/2573] eta: 0:02:35 time: 0.0739 data: 0.0011 max mem: 33369 +Test: [ 700/2573] eta: 0:02:26 time: 0.0740 data: 0.0011 max mem: 33369 +Test: [ 800/2573] eta: 0:02:18 time: 0.0773 data: 0.0011 max mem: 33369 +Test: [ 900/2573] eta: 0:02:09 time: 0.0739 data: 0.0011 max mem: 33369 +Test: [1000/2573] eta: 0:02:01 time: 0.0738 data: 0.0011 max mem: 33369 +Test: [1100/2573] eta: 0:01:53 time: 0.0739 data: 0.0011 max mem: 33369 +Test: [1200/2573] eta: 0:01:45 time: 0.0739 data: 0.0011 max mem: 33369 +Test: [1300/2573] eta: 0:01:37 time: 0.0739 data: 0.0011 max mem: 33369 +Test: [1400/2573] eta: 0:01:29 time: 0.0724 data: 0.0011 max mem: 33369 +Test: [1500/2573] eta: 0:01:21 time: 0.0738 data: 0.0011 max mem: 33369 +Test: [1600/2573] eta: 0:01:14 time: 0.0772 data: 0.0011 max mem: 33369 +Test: [1700/2573] eta: 0:01:06 time: 0.0723 data: 0.0011 max mem: 33369 +Test: [1800/2573] eta: 0:00:58 time: 0.0756 data: 0.0011 max mem: 33369 +Test: [1900/2573] eta: 0:00:50 time: 0.0721 data: 0.0011 max mem: 33369 +Test: [2000/2573] eta: 0:00:43 time: 0.0740 data: 0.0011 max mem: 33369 +Test: [2100/2573] eta: 0:00:35 time: 0.0755 data: 0.0010 max mem: 33369 +Test: [2200/2573] eta: 0:00:28 time: 0.0754 data: 0.0011 max mem: 33369 +Test: [2300/2573] eta: 0:00:20 time: 0.0755 data: 0.0011 max mem: 33369 +Test: [2400/2573] eta: 0:00:13 time: 0.0705 data: 0.0011 max mem: 33369 +Test: [2500/2573] eta: 0:00:05 time: 0.0738 data: 0.0011 max mem: 33369 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: Total time: 0:03:13 +Final results: +Mean IoU is 63.80 + + precision@0.5 = 71.51 + precision@0.6 = 66.48 + precision@0.7 = 59.52 + precision@0.8 = 47.81 + precision@0.9 = 24.18 + overall IoU = 62.10 + +Average object IoU 63.795766677268105 +Overall IoU 62.097206115722656 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [28] [ 0/1319] eta: 3:10:57 lr: 1.69182110465679e-05 loss: 0.0318 (0.0318) time: 8.6866 data: 1.5785 max mem: 33369 +Epoch: [28] [ 10/1319] eta: 1:09:22 lr: 1.690859022703219e-05 loss: 0.0370 (0.0399) time: 3.1800 data: 0.1494 max mem: 33369 +Epoch: [28] [ 20/1319] eta: 1:03:27 lr: 1.6898968799219036e-05 loss: 0.0370 (0.0418) time: 2.6433 data: 0.0062 max mem: 33369 +Epoch: [28] [ 30/1319] eta: 1:00:56 lr: 1.6889346762705132e-05 loss: 0.0357 (0.0415) time: 2.6477 data: 0.0063 max mem: 33369 +Epoch: [28] [ 40/1319] eta: 0:59:25 lr: 1.6879724117066593e-05 loss: 0.0357 (0.0394) time: 2.6372 data: 0.0065 max mem: 33369 +Epoch: [28] [ 50/1319] eta: 0:58:45 lr: 1.6870100861878995e-05 loss: 0.0377 (0.0418) time: 2.6880 data: 0.0065 max mem: 33369 +Epoch: [28] [ 60/1319] eta: 0:57:54 lr: 1.6860476996717327e-05 loss: 0.0397 (0.0409) time: 2.7027 data: 0.0065 max mem: 33369 +Epoch: [28] [ 70/1319] eta: 0:57:04 lr: 1.6850852521156025e-05 loss: 0.0376 (0.0412) time: 2.6478 data: 0.0065 max mem: 33369 +Epoch: [28] [ 80/1319] eta: 0:56:24 lr: 1.684122743476896e-05 loss: 0.0345 (0.0403) time: 2.6462 data: 0.0065 max mem: 33369 +Epoch: [28] [ 90/1319] eta: 0:55:49 lr: 1.6831601737129412e-05 loss: 0.0322 (0.0401) time: 2.6669 data: 0.0066 max mem: 33369 +Epoch: [28] [ 100/1319] eta: 0:55:13 lr: 1.6821975427810122e-05 loss: 0.0322 (0.0393) time: 2.6648 data: 0.0066 max mem: 33369 +Epoch: [28] [ 110/1319] eta: 0:54:38 lr: 1.6812348506383245e-05 loss: 0.0328 (0.0389) time: 2.6513 data: 0.0065 max mem: 33369 +Epoch: [28] [ 120/1319] eta: 0:54:01 lr: 1.680272097242036e-05 loss: 0.0340 (0.0384) time: 2.6291 data: 0.0065 max mem: 33369 +Epoch: [28] [ 130/1319] eta: 0:53:28 lr: 1.6793092825492484e-05 loss: 0.0353 (0.0387) time: 2.6251 data: 0.0066 max mem: 33369 +Epoch: [28] [ 140/1319] eta: 0:52:52 lr: 1.6783464065170062e-05 loss: 0.0364 (0.0392) time: 2.6150 data: 0.0066 max mem: 33369 +Epoch: [28] [ 150/1319] eta: 0:52:21 lr: 1.6773834691022944e-05 loss: 0.0357 (0.0389) time: 2.6156 data: 0.0067 max mem: 33369 +Epoch: [28] [ 160/1319] eta: 0:51:51 lr: 1.6764204702620422e-05 loss: 0.0378 (0.0388) time: 2.6380 data: 0.0065 max mem: 33369 +Epoch: [28] [ 170/1319] eta: 0:51:23 lr: 1.6754574099531206e-05 loss: 0.0347 (0.0385) time: 2.6535 data: 0.0063 max mem: 33369 +Epoch: [28] [ 180/1319] eta: 0:50:52 lr: 1.6744942881323427e-05 loss: 0.0344 (0.0386) time: 2.6423 data: 0.0065 max mem: 33369 +Epoch: [28] [ 190/1319] eta: 0:50:23 lr: 1.6735311047564646e-05 loss: 0.0380 (0.0388) time: 2.6280 data: 0.0066 max mem: 33369 +Epoch: [28] [ 200/1319] eta: 0:49:55 lr: 1.6725678597821815e-05 loss: 0.0369 (0.0386) time: 2.6482 data: 0.0066 max mem: 33369 +Epoch: [28] [ 210/1319] eta: 0:49:26 lr: 1.6716045531661334e-05 loss: 0.0306 (0.0383) time: 2.6495 data: 0.0066 max mem: 33369 +Epoch: [28] [ 220/1319] eta: 0:48:59 lr: 1.6706411848649008e-05 loss: 0.0323 (0.0385) time: 2.6579 data: 0.0066 max mem: 33369 +Epoch: [28] [ 230/1319] eta: 0:48:31 lr: 1.6696777548350058e-05 loss: 0.0398 (0.0384) time: 2.6558 data: 0.0065 max mem: 33369 +Epoch: [28] [ 240/1319] eta: 0:48:03 lr: 1.668714263032912e-05 loss: 0.0353 (0.0385) time: 2.6449 data: 0.0064 max mem: 33369 +Epoch: [28] [ 250/1319] eta: 0:47:35 lr: 1.6677507094150246e-05 loss: 0.0373 (0.0388) time: 2.6439 data: 0.0066 max mem: 33369 +Epoch: [28] [ 260/1319] eta: 0:47:07 lr: 1.6667870939376894e-05 loss: 0.0377 (0.0390) time: 2.6451 data: 0.0066 max mem: 33369 +Epoch: [28] [ 270/1319] eta: 0:46:39 lr: 1.6658234165571935e-05 loss: 0.0395 (0.0390) time: 2.6378 data: 0.0065 max mem: 33369 +Epoch: [28] [ 280/1319] eta: 0:46:10 lr: 1.6648596772297652e-05 loss: 0.0388 (0.0391) time: 2.6099 data: 0.0066 max mem: 33369 +Epoch: [28] [ 290/1319] eta: 0:45:43 lr: 1.6638958759115745e-05 loss: 0.0388 (0.0391) time: 2.6288 data: 0.0066 max mem: 33369 +Epoch: [28] [ 300/1319] eta: 0:45:15 lr: 1.6629320125587307e-05 loss: 0.0381 (0.0392) time: 2.6451 data: 0.0067 max mem: 33369 +Epoch: [28] [ 310/1319] eta: 0:44:50 lr: 1.6619680871272843e-05 loss: 0.0320 (0.0390) time: 2.6724 data: 0.0066 max mem: 33369 +Epoch: [28] [ 320/1319] eta: 0:44:23 lr: 1.6610040995732262e-05 loss: 0.0347 (0.0389) time: 2.6825 data: 0.0065 max mem: 33369 +Epoch: [28] [ 330/1319] eta: 0:43:56 lr: 1.6600400498524878e-05 loss: 0.0350 (0.0389) time: 2.6510 data: 0.0064 max mem: 33369 +Epoch: [28] [ 340/1319] eta: 0:43:28 lr: 1.659075937920942e-05 loss: 0.0359 (0.0390) time: 2.6486 data: 0.0064 max mem: 33369 +Epoch: [28] [ 350/1319] eta: 0:43:01 lr: 1.6581117637343994e-05 loss: 0.0366 (0.0389) time: 2.6446 data: 0.0065 max mem: 33369 +Epoch: [28] [ 360/1319] eta: 0:42:34 lr: 1.657147527248612e-05 loss: 0.0358 (0.0388) time: 2.6515 data: 0.0065 max mem: 33369 +Epoch: [28] [ 370/1319] eta: 0:42:07 lr: 1.6561832284192722e-05 loss: 0.0372 (0.0390) time: 2.6553 data: 0.0066 max mem: 33369 +Epoch: [28] [ 380/1319] eta: 0:41:40 lr: 1.6552188672020112e-05 loss: 0.0346 (0.0388) time: 2.6489 data: 0.0066 max mem: 33369 +Epoch: [28] [ 390/1319] eta: 0:41:13 lr: 1.654254443552401e-05 loss: 0.0326 (0.0388) time: 2.6487 data: 0.0067 max mem: 33369 +Epoch: [28] [ 400/1319] eta: 0:40:47 lr: 1.6532899574259518e-05 loss: 0.0313 (0.0386) time: 2.6540 data: 0.0067 max mem: 33369 +Epoch: [28] [ 410/1319] eta: 0:40:19 lr: 1.6523254087781154e-05 loss: 0.0333 (0.0387) time: 2.6485 data: 0.0066 max mem: 33369 +Epoch: [28] [ 420/1319] eta: 0:39:53 lr: 1.651360797564279e-05 loss: 0.0367 (0.0388) time: 2.6485 data: 0.0067 max mem: 33369 +Epoch: [28] [ 430/1319] eta: 0:39:27 lr: 1.6503961237397734e-05 loss: 0.0367 (0.0387) time: 2.6735 data: 0.0066 max mem: 33369 +Epoch: [28] [ 440/1319] eta: 0:39:00 lr: 1.6494313872598656e-05 loss: 0.0329 (0.0387) time: 2.6714 data: 0.0066 max mem: 33369 +Epoch: [28] [ 450/1319] eta: 0:38:33 lr: 1.6484665880797628e-05 loss: 0.0378 (0.0389) time: 2.6598 data: 0.0065 max mem: 33369 +Epoch: [28] [ 460/1319] eta: 0:38:06 lr: 1.6475017261546112e-05 loss: 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(0.0391) time: 2.6246 data: 0.0066 max mem: 33369 +Epoch: [28] [ 860/1319] eta: 0:20:17 lr: 1.608855275594644e-05 loss: 0.0340 (0.0391) time: 2.6372 data: 0.0067 max mem: 33369 +Epoch: [28] [ 870/1319] eta: 0:19:50 lr: 1.6078878017308325e-05 loss: 0.0381 (0.0392) time: 2.6387 data: 0.0066 max mem: 33369 +Epoch: [28] [ 880/1319] eta: 0:19:24 lr: 1.6069202631811695e-05 loss: 0.0419 (0.0392) time: 2.6242 data: 0.0064 max mem: 33369 +Epoch: [28] [ 890/1319] eta: 0:18:57 lr: 1.6059526598980493e-05 loss: 0.0351 (0.0393) time: 2.6117 data: 0.0065 max mem: 33369 +Epoch: [28] [ 900/1319] eta: 0:18:30 lr: 1.6049849918337977e-05 loss: 0.0372 (0.0393) time: 2.6211 data: 0.0066 max mem: 33369 +Epoch: [28] [ 910/1319] eta: 0:18:03 lr: 1.6040172589406754e-05 loss: 0.0336 (0.0392) time: 2.5936 data: 0.0066 max mem: 33369 +Epoch: [28] [ 920/1319] eta: 0:17:37 lr: 1.603049461170875e-05 loss: 0.0340 (0.0392) time: 2.5913 data: 0.0066 max mem: 33369 +Epoch: [28] [ 930/1319] eta: 0:17:10 lr: 1.602081598476522e-05 loss: 0.0341 (0.0392) time: 2.6362 data: 0.0065 max mem: 33369 +Epoch: [28] [ 940/1319] eta: 0:16:44 lr: 1.6011136708096744e-05 loss: 0.0341 (0.0392) time: 2.6261 data: 0.0064 max mem: 33369 +Epoch: [28] [ 950/1319] eta: 0:16:17 lr: 1.6001456781223216e-05 loss: 0.0350 (0.0392) time: 2.5977 data: 0.0064 max mem: 33369 +Epoch: [28] [ 960/1319] eta: 0:15:50 lr: 1.599177620366387e-05 loss: 0.0350 (0.0393) time: 2.6134 data: 0.0067 max mem: 33369 +Epoch: [28] [ 970/1319] eta: 0:15:24 lr: 1.598209497493724e-05 loss: 0.0372 (0.0394) time: 2.6251 data: 0.0068 max mem: 33369 +Epoch: [28] [ 980/1319] eta: 0:14:57 lr: 1.5972413094561205e-05 loss: 0.0393 (0.0394) time: 2.6223 data: 0.0066 max mem: 33369 +Epoch: [28] [ 990/1319] eta: 0:14:31 lr: 1.5962730562052938e-05 loss: 0.0311 (0.0393) time: 2.6433 data: 0.0066 max mem: 33369 +Epoch: [28] [1000/1319] eta: 0:14:04 lr: 1.5953047376928946e-05 loss: 0.0334 (0.0394) time: 2.6677 data: 0.0066 max mem: 33369 +Epoch: [28] 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mem: 33369 +Epoch: [28] [1090/1319] eta: 0:10:06 lr: 1.5865869262987425e-05 loss: 0.0398 (0.0395) time: 2.6212 data: 0.0067 max mem: 33369 +Epoch: [28] [1100/1319] eta: 0:09:40 lr: 1.5856179524962237e-05 loss: 0.0379 (0.0395) time: 2.6526 data: 0.0064 max mem: 33369 +Epoch: [28] [1110/1319] eta: 0:09:13 lr: 1.5846489128957288e-05 loss: 0.0372 (0.0395) time: 2.6698 data: 0.0064 max mem: 33369 +Epoch: [28] [1120/1319] eta: 0:08:47 lr: 1.5836798074480774e-05 loss: 0.0333 (0.0395) time: 2.6379 data: 0.0065 max mem: 33369 +Epoch: [28] [1130/1319] eta: 0:08:20 lr: 1.582710636104018e-05 loss: 0.0352 (0.0395) time: 2.6330 data: 0.0066 max mem: 33369 +Epoch: [28] [1140/1319] eta: 0:07:53 lr: 1.5817413988142284e-05 loss: 0.0365 (0.0397) time: 2.6178 data: 0.0067 max mem: 33369 +Epoch: [28] [1150/1319] eta: 0:07:27 lr: 1.5807720955293166e-05 loss: 0.0373 (0.0397) time: 2.5983 data: 0.0066 max mem: 33369 +Epoch: [28] [1160/1319] eta: 0:07:00 lr: 1.579802726199819e-05 loss: 0.0349 (0.0397) time: 2.6300 data: 0.0066 max mem: 33369 +Epoch: [28] [1170/1319] eta: 0:06:34 lr: 1.5788332907762015e-05 loss: 0.0348 (0.0398) time: 2.6548 data: 0.0067 max mem: 33369 +Epoch: [28] [1180/1319] eta: 0:06:07 lr: 1.577863789208859e-05 loss: 0.0391 (0.0398) time: 2.6424 data: 0.0065 max mem: 33369 +Epoch: [28] [1190/1319] eta: 0:05:41 lr: 1.576894221448116e-05 loss: 0.0368 (0.0398) time: 2.6232 data: 0.0064 max mem: 33369 +Epoch: [28] [1200/1319] eta: 0:05:14 lr: 1.5759245874442245e-05 loss: 0.0318 (0.0398) time: 2.6110 data: 0.0065 max mem: 33369 +Epoch: [28] [1210/1319] eta: 0:04:48 lr: 1.5749548871473663e-05 loss: 0.0366 (0.0398) time: 2.6198 data: 0.0065 max mem: 33369 +Epoch: [28] [1220/1319] eta: 0:04:22 lr: 1.57398512050765e-05 loss: 0.0357 (0.0398) time: 2.6411 data: 0.0065 max mem: 33369 +Epoch: [28] [1230/1319] eta: 0:03:55 lr: 1.5730152874751144e-05 loss: 0.0331 (0.0397) time: 2.6470 data: 0.0066 max mem: 33369 +Epoch: [28] [1240/1319] eta: 0:03:29 lr: 1.572045387999725e-05 loss: 0.0372 (0.0398) time: 2.6409 data: 0.0065 max mem: 33369 +Epoch: [28] [1250/1319] eta: 0:03:02 lr: 1.5710754220313764e-05 loss: 0.0378 (0.0398) time: 2.6411 data: 0.0065 max mem: 33369 +Epoch: [28] [1260/1319] eta: 0:02:36 lr: 1.5701053895198906e-05 loss: 0.0397 (0.0398) time: 2.6411 data: 0.0066 max mem: 33369 +Epoch: [28] [1270/1319] eta: 0:02:09 lr: 1.5691352904150157e-05 loss: 0.0363 (0.0398) time: 2.6506 data: 0.0066 max mem: 33369 +Epoch: [28] [1280/1319] eta: 0:01:43 lr: 1.5681651246664294e-05 loss: 0.0363 (0.0398) time: 2.6601 data: 0.0065 max mem: 33369 +Epoch: [28] [1290/1319] eta: 0:01:16 lr: 1.5671948922237363e-05 loss: 0.0381 (0.0398) time: 2.6530 data: 0.0065 max mem: 33369 +Epoch: [28] [1300/1319] eta: 0:00:50 lr: 1.5662245930364672e-05 loss: 0.0348 (0.0397) time: 2.6277 data: 0.0065 max mem: 33369 +Epoch: [28] [1310/1319] eta: 0:00:23 lr: 1.5652542270540813e-05 loss: 0.0328 (0.0397) time: 2.6187 data: 0.0066 max mem: 33369 +Epoch: [28] Total time: 0:58:10 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 2:01:18 time: 2.8288 data: 2.7410 max mem: 33369 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 100/2573] eta: 0:04:07 time: 0.0718 data: 0.0011 max mem: 33369 +Test: [ 200/2573] eta: 0:03:27 time: 0.0738 data: 0.0011 max mem: 33369 +Test: [ 300/2573] eta: 0:03:07 time: 0.0755 data: 0.0010 max mem: 33369 +Test: [ 400/2573] eta: 0:02:54 time: 0.0756 data: 0.0011 max mem: 33369 +Test: [ 500/2573] eta: 0:02:43 time: 0.0741 data: 0.0011 max mem: 33369 +Test: [ 600/2573] eta: 0:02:34 time: 0.0740 data: 0.0011 max mem: 33369 +Test: [ 700/2573] eta: 0:02:26 time: 0.0741 data: 0.0011 max mem: 33369 +Test: [ 800/2573] eta: 0:02:17 time: 0.0774 data: 0.0010 max mem: 33369 +Test: [ 900/2573] eta: 0:02:09 time: 0.0741 data: 0.0011 max mem: 33369 +Test: [1000/2573] eta: 0:02:01 time: 0.0740 data: 0.0011 max mem: 33369 +Test: [1100/2573] eta: 0:01:53 time: 0.0741 data: 0.0011 max mem: 33369 +Test: [1200/2573] eta: 0:01:45 time: 0.0740 data: 0.0011 max mem: 33369 +Test: [1300/2573] eta: 0:01:37 time: 0.0742 data: 0.0011 max mem: 33369 +Test: [1400/2573] eta: 0:01:29 time: 0.0723 data: 0.0011 max mem: 33369 +Test: [1500/2573] eta: 0:01:21 time: 0.0741 data: 0.0011 max mem: 33369 +Test: [1600/2573] eta: 0:01:13 time: 0.0774 data: 0.0011 max mem: 33369 +Test: [1700/2573] eta: 0:01:06 time: 0.0724 data: 0.0011 max mem: 33369 +Test: [1800/2573] eta: 0:00:58 time: 0.0757 data: 0.0011 max mem: 33369 +Test: [1900/2573] eta: 0:00:50 time: 0.0725 data: 0.0011 max mem: 33369 +Test: [2000/2573] eta: 0:00:43 time: 0.0741 data: 0.0011 max mem: 33369 +Test: [2100/2573] eta: 0:00:35 time: 0.0757 data: 0.0011 max mem: 33369 +Test: [2200/2573] eta: 0:00:28 time: 0.0755 data: 0.0010 max mem: 33369 +Test: [2300/2573] eta: 0:00:20 time: 0.0756 data: 0.0011 max mem: 33369 +Test: [2400/2573] eta: 0:00:13 time: 0.0707 data: 0.0011 max mem: 33369 +Test: [2500/2573] eta: 0:00:05 time: 0.0740 data: 0.0011 max mem: 33369 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: Total time: 0:03:13 +Final results: +Mean IoU is 64.51 + + precision@0.5 = 72.90 + precision@0.6 = 67.40 + precision@0.7 = 60.13 + precision@0.8 = 48.90 + precision@0.9 = 24.24 + overall IoU = 62.26 + +Average object IoU 64.5100949854171 +Overall IoU 62.26433181762695 +Better epoch: 28 + +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [29] [ 0/1319] eta: 1:28:28 lr: 1.5643808405182777e-05 loss: 0.0193 (0.0193) time: 4.0243 data: 1.1717 max mem: 33369 +Epoch: [29] [ 10/1319] eta: 0:59:41 lr: 1.563410347485666e-05 loss: 0.0328 (0.0376) time: 2.7357 data: 0.1126 max mem: 33369 +Epoch: [29] [ 20/1319] eta: 0:58:08 lr: 1.5624397875109532e-05 loss: 0.0357 (0.0372) time: 2.6188 data: 0.0065 max mem: 33369 +Epoch: [29] [ 30/1319] eta: 0:57:36 lr: 1.5614691605433113e-05 loss: 0.0357 (0.0385) time: 2.6515 data: 0.0065 max mem: 33369 +Epoch: [29] [ 40/1319] eta: 0:57:00 lr: 1.5604984665318397e-05 loss: 0.0350 (0.0388) time: 2.6627 data: 0.0067 max mem: 33369 +Epoch: [29] [ 50/1319] eta: 0:56:31 lr: 1.5595277054255625e-05 loss: 0.0333 (0.0386) time: 2.6584 data: 0.0065 max mem: 33369 +Epoch: [29] [ 60/1319] eta: 0:55:57 lr: 1.558556877173431e-05 loss: 0.0333 (0.0385) time: 2.6509 data: 0.0065 max mem: 33369 +Epoch: [29] [ 70/1319] eta: 0:55:27 lr: 1.557585981724323e-05 loss: 0.0347 (0.0381) time: 2.6443 data: 0.0067 max mem: 33369 +Epoch: [29] [ 80/1319] eta: 0:55:00 lr: 1.5566150190270393e-05 loss: 0.0344 (0.0379) time: 2.6546 data: 0.0067 max mem: 33369 +Epoch: [29] [ 90/1319] eta: 0:54:30 lr: 1.5556439890303075e-05 loss: 0.0319 (0.0374) time: 2.6475 data: 0.0065 max mem: 33369 +Epoch: [29] [ 100/1319] eta: 0:53:58 lr: 1.554672891682782e-05 loss: 0.0337 (0.0390) time: 2.6265 data: 0.0065 max mem: 33369 +Epoch: [29] [ 110/1319] eta: 0:53:31 lr: 1.55370172693304e-05 loss: 0.0340 (0.0387) time: 2.6350 data: 0.0065 max mem: 33369 +Epoch: [29] [ 120/1319] eta: 0:53:01 lr: 1.552730494729585e-05 loss: 0.0342 (0.0387) time: 2.6402 data: 0.0065 max mem: 33369 +Epoch: [29] [ 130/1319] eta: 0:52:35 lr: 1.551759195020846e-05 loss: 0.0310 (0.0384) time: 2.6421 data: 0.0066 max mem: 33369 +Epoch: [29] [ 140/1319] eta: 0:52:09 lr: 1.5507878277551742e-05 loss: 0.0313 (0.0381) time: 2.6559 data: 0.0066 max mem: 33369 +Epoch: [29] [ 150/1319] eta: 0:51:42 lr: 1.5498163928808475e-05 loss: 0.0314 (0.0381) time: 2.6516 data: 0.0066 max mem: 33369 +Epoch: [29] [ 160/1319] eta: 0:51:16 lr: 1.548844890346068e-05 loss: 0.0314 (0.0386) time: 2.6542 data: 0.0065 max mem: 33369 +Epoch: [29] [ 170/1319] eta: 0:50:46 lr: 1.547873320098961e-05 loss: 0.0340 (0.0385) time: 2.6336 data: 0.0065 max mem: 33369 +Epoch: [29] [ 180/1319] eta: 0:50:18 lr: 1.546901682087577e-05 loss: 0.0369 (0.0389) time: 2.6211 data: 0.0065 max mem: 33369 +Epoch: [29] [ 190/1319] eta: 0:49:51 lr: 1.5459299762598884e-05 loss: 0.0370 (0.0387) time: 2.6365 data: 0.0066 max mem: 33369 +Epoch: [29] [ 200/1319] eta: 0:49:24 lr: 1.5449582025637935e-05 loss: 0.0334 (0.0386) time: 2.6361 data: 0.0066 max mem: 33369 +Epoch: [29] [ 210/1319] eta: 0:48:57 lr: 1.543986360947113e-05 loss: 0.0318 (0.0383) time: 2.6377 data: 0.0066 max mem: 33369 +Epoch: [29] [ 220/1319] eta: 0:48:31 lr: 1.543014451357591e-05 loss: 0.0322 (0.0384) time: 2.6488 data: 0.0067 max mem: 33369 +Epoch: [29] [ 230/1319] eta: 0:48:05 lr: 1.5420424737428955e-05 loss: 0.0350 (0.0383) time: 2.6592 data: 0.0066 max mem: 33369 +Epoch: [29] [ 240/1319] eta: 0:47:39 lr: 1.541070428050616e-05 loss: 0.0350 (0.0384) time: 2.6647 data: 0.0065 max mem: 33369 +Epoch: [29] [ 250/1319] eta: 0:47:12 lr: 1.5400983142282667e-05 loss: 0.0357 (0.0383) time: 2.6562 data: 0.0065 max mem: 33369 +Epoch: [29] [ 260/1319] eta: 0:46:45 lr: 1.539126132223283e-05 loss: 0.0357 (0.0384) time: 2.6321 data: 0.0066 max mem: 33369 +Epoch: [29] [ 270/1319] eta: 0:46:17 lr: 1.538153881983024e-05 loss: 0.0395 (0.0385) time: 2.6240 data: 0.0067 max mem: 33369 +Epoch: [29] [ 280/1319] eta: 0:45:50 lr: 1.53718156345477e-05 loss: 0.0365 (0.0384) time: 2.6205 data: 0.0067 max mem: 33369 +Epoch: [29] [ 290/1319] eta: 0:45:21 lr: 1.5362091765857252e-05 loss: 0.0337 (0.0382) time: 2.5943 data: 0.0067 max mem: 33369 +Epoch: [29] [ 300/1319] eta: 0:44:54 lr: 1.5352367213230138e-05 loss: 0.0352 (0.0383) time: 2.6132 data: 0.0067 max mem: 33369 +Epoch: [29] [ 310/1319] eta: 0:44:29 lr: 1.5342641976136825e-05 loss: 0.0367 (0.0384) time: 2.6649 data: 0.0065 max mem: 33369 +Epoch: [29] [ 320/1319] eta: 0:44:02 lr: 1.5332916054047e-05 loss: 0.0321 (0.0385) time: 2.6490 data: 0.0064 max mem: 33369 +Epoch: [29] [ 330/1319] eta: 0:43:35 lr: 1.532318944642957e-05 loss: 0.0365 (0.0386) time: 2.6242 data: 0.0065 max mem: 33369 +Epoch: [29] [ 340/1319] eta: 0:43:08 lr: 1.5313462152752656e-05 loss: 0.0364 (0.0386) time: 2.6287 data: 0.0066 max mem: 33369 +Epoch: [29] [ 350/1319] eta: 0:42:42 lr: 1.5303734172483566e-05 loss: 0.0375 (0.0386) time: 2.6450 data: 0.0066 max mem: 33369 +Epoch: [29] [ 360/1319] eta: 0:42:16 lr: 1.529400550508885e-05 loss: 0.0345 (0.0386) time: 2.6608 data: 0.0064 max mem: 33369 +Epoch: [29] [ 370/1319] eta: 0:41:49 lr: 1.528427615003424e-05 loss: 0.0344 (0.0387) time: 2.6440 data: 0.0064 max mem: 33369 +Epoch: [29] [ 380/1319] eta: 0:41:23 lr: 1.5274546106784702e-05 loss: 0.0377 (0.0386) time: 2.6412 data: 0.0064 max mem: 33369 +Epoch: [29] [ 390/1319] eta: 0:40:56 lr: 1.526481537480438e-05 loss: 0.0333 (0.0386) time: 2.6365 data: 0.0066 max mem: 33369 +Epoch: [29] [ 400/1319] eta: 0:40:28 lr: 1.525508395355664e-05 loss: 0.0343 (0.0386) time: 2.6003 data: 0.0066 max mem: 33369 +Epoch: [29] [ 410/1319] eta: 0:40:01 lr: 1.5245351842504036e-05 loss: 0.0345 (0.0385) time: 2.5943 data: 0.0065 max mem: 33369 +Epoch: [29] [ 420/1319] eta: 0:39:35 lr: 1.5235619041108326e-05 loss: 0.0350 (0.0388) time: 2.6453 data: 0.0066 max mem: 33369 +Epoch: [29] [ 430/1319] eta: 0:39:07 lr: 1.5225885548830468e-05 loss: 0.0350 (0.0387) time: 2.6303 data: 0.0066 max mem: 33369 +Epoch: [29] [ 440/1319] eta: 0:38:40 lr: 1.5216151365130616e-05 loss: 0.0336 (0.0387) time: 2.5914 data: 0.0065 max mem: 33369 +Epoch: [29] [ 450/1319] eta: 0:38:14 lr: 1.520641648946812e-05 loss: 0.0349 (0.0390) time: 2.6133 data: 0.0064 max mem: 33369 +Epoch: [29] [ 460/1319] eta: 0:37:47 lr: 1.519668092130151e-05 loss: 0.0356 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data: 0.0063 max mem: 33369 +Epoch: [29] [ 780/1319] eta: 0:23:42 lr: 1.4884773814725032e-05 loss: 0.0332 (0.0399) time: 2.6447 data: 0.0063 max mem: 33369 +Epoch: [29] [ 790/1319] eta: 0:23:15 lr: 1.4875015084769944e-05 loss: 0.0304 (0.0399) time: 2.6287 data: 0.0063 max mem: 33369 +Epoch: [29] [ 800/1319] eta: 0:22:49 lr: 1.4865255643407467e-05 loss: 0.0341 (0.0399) time: 2.6225 data: 0.0064 max mem: 33369 +Epoch: [29] [ 810/1319] eta: 0:22:22 lr: 1.4855495490066707e-05 loss: 0.0410 (0.0399) time: 2.6409 data: 0.0064 max mem: 33369 +Epoch: [29] [ 820/1319] eta: 0:21:56 lr: 1.4845734624175911e-05 loss: 0.0330 (0.0398) time: 2.6590 data: 0.0065 max mem: 33369 +Epoch: [29] [ 830/1319] eta: 0:21:30 lr: 1.4835973045162419e-05 loss: 0.0354 (0.0398) time: 2.6467 data: 0.0066 max mem: 33369 +Epoch: [29] [ 840/1319] eta: 0:21:03 lr: 1.4826210752452718e-05 loss: 0.0363 (0.0398) time: 2.6378 data: 0.0065 max mem: 33369 +Epoch: [29] [ 850/1319] eta: 0:20:37 lr: 1.48164477454724e-05 loss: 0.0363 (0.0398) time: 2.6336 data: 0.0065 max mem: 33369 +Epoch: [29] [ 860/1319] eta: 0:20:11 lr: 1.4806684023646183e-05 loss: 0.0387 (0.0398) time: 2.6633 data: 0.0064 max mem: 33369 +Epoch: [29] [ 870/1319] eta: 0:19:44 lr: 1.4796919586397895e-05 loss: 0.0411 (0.0398) time: 2.6621 data: 0.0063 max mem: 33369 +Epoch: [29] [ 880/1319] eta: 0:19:18 lr: 1.4787154433150476e-05 loss: 0.0376 (0.0398) time: 2.6353 data: 0.0064 max mem: 33369 +Epoch: [29] [ 890/1319] eta: 0:18:52 lr: 1.4777388563325976e-05 loss: 0.0376 (0.0399) time: 2.6696 data: 0.0064 max mem: 33369 +Epoch: [29] [ 900/1319] eta: 0:18:26 lr: 1.4767621976345552e-05 loss: 0.0371 (0.0398) time: 2.6939 data: 0.0063 max mem: 33369 +Epoch: [29] [ 910/1319] eta: 0:17:59 lr: 1.4757854671629475e-05 loss: 0.0342 (0.0398) time: 2.6730 data: 0.0065 max mem: 33369 +Epoch: [29] [ 920/1319] eta: 0:17:33 lr: 1.4748086648597121e-05 loss: 0.0363 (0.0398) time: 2.6413 data: 0.0066 max mem: 33369 +Epoch: [29] [ 930/1319] eta: 0:17:07 lr: 1.4738317906666963e-05 loss: 0.0342 (0.0398) time: 2.6224 data: 0.0064 max mem: 33369 +Epoch: [29] [ 940/1319] eta: 0:16:40 lr: 1.4728548445256565e-05 loss: 0.0377 (0.0398) time: 2.6264 data: 0.0063 max mem: 33369 +Epoch: [29] [ 950/1319] eta: 0:16:14 lr: 1.471877826378261e-05 loss: 0.0373 (0.0397) time: 2.6528 data: 0.0063 max mem: 33369 +Epoch: [29] [ 960/1319] eta: 0:15:47 lr: 1.4709007361660864e-05 loss: 0.0307 (0.0397) time: 2.6604 data: 0.0066 max mem: 33369 +Epoch: [29] [ 970/1319] eta: 0:15:21 lr: 1.4699235738306196e-05 loss: 0.0362 (0.0396) time: 2.6198 data: 0.0068 max mem: 33369 +Epoch: [29] [ 980/1319] eta: 0:14:54 lr: 1.4689463393132561e-05 loss: 0.0363 (0.0397) time: 2.6190 data: 0.0066 max mem: 33369 +Epoch: [29] [ 990/1319] eta: 0:14:28 lr: 1.4679690325553006e-05 loss: 0.0359 (0.0396) time: 2.6450 data: 0.0065 max mem: 33369 +Epoch: [29] [1000/1319] eta: 0:14:02 lr: 1.466991653497966e-05 loss: 0.0374 (0.0396) time: 2.6304 data: 0.0064 max mem: 33369 +Epoch: [29] 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mem: 33369 +Epoch: [29] [1090/1319] eta: 0:10:04 lr: 1.4581919787647347e-05 loss: 0.0315 (0.0394) time: 2.6878 data: 0.0066 max mem: 33369 +Epoch: [29] [1100/1319] eta: 0:09:38 lr: 1.4572138734601442e-05 loss: 0.0352 (0.0394) time: 2.6767 data: 0.0062 max mem: 33369 +Epoch: [29] [1110/1319] eta: 0:09:12 lr: 1.4562356952034447e-05 loss: 0.0379 (0.0395) time: 2.6485 data: 0.0062 max mem: 33369 +Epoch: [29] [1120/1319] eta: 0:08:45 lr: 1.4552574439347391e-05 loss: 0.0379 (0.0394) time: 2.6199 data: 0.0063 max mem: 33369 +Epoch: [29] [1130/1319] eta: 0:08:19 lr: 1.4542791195940364e-05 loss: 0.0369 (0.0394) time: 2.6199 data: 0.0062 max mem: 33369 +Epoch: [29] [1140/1319] eta: 0:07:52 lr: 1.453300722121251e-05 loss: 0.0389 (0.0394) time: 2.6333 data: 0.0062 max mem: 33369 +Epoch: [29] [1150/1319] eta: 0:07:26 lr: 1.4523222514562035e-05 loss: 0.0323 (0.0394) time: 2.6524 data: 0.0061 max mem: 33369 +Epoch: [29] [1160/1319] eta: 0:06:59 lr: 1.4513437075386188e-05 loss: 0.0295 (0.0393) time: 2.6549 data: 0.0062 max mem: 33369 +Epoch: [29] [1170/1319] eta: 0:06:33 lr: 1.4503650903081281e-05 loss: 0.0334 (0.0393) time: 2.6294 data: 0.0062 max mem: 33369 +Epoch: [29] [1180/1319] eta: 0:06:07 lr: 1.449386399704267e-05 loss: 0.0383 (0.0393) time: 2.6358 data: 0.0063 max mem: 33369 +Epoch: [29] [1190/1319] eta: 0:05:40 lr: 1.4484076356664761e-05 loss: 0.0358 (0.0393) time: 2.6330 data: 0.0064 max mem: 33369 +Epoch: [29] [1200/1319] eta: 0:05:14 lr: 1.447428798134101e-05 loss: 0.0391 (0.0394) time: 2.6227 data: 0.0063 max mem: 33369 +Epoch: [29] [1210/1319] eta: 0:04:47 lr: 1.4464498870463896e-05 loss: 0.0364 (0.0393) time: 2.6335 data: 0.0063 max mem: 33369 +Epoch: [29] [1220/1319] eta: 0:04:21 lr: 1.4454709023424959e-05 loss: 0.0342 (0.0393) time: 2.6417 data: 0.0062 max mem: 33369 +Epoch: [29] [1230/1319] eta: 0:03:55 lr: 1.444491843961477e-05 loss: 0.0366 (0.0393) time: 2.6387 data: 0.0063 max mem: 33369 +Epoch: [29] [1240/1319] eta: 0:03:28 lr: 1.4435127118422938e-05 loss: 0.0374 (0.0393) time: 2.6145 data: 0.0065 max mem: 33369 +Epoch: [29] [1250/1319] eta: 0:03:02 lr: 1.442533505923811e-05 loss: 0.0304 (0.0392) time: 2.6219 data: 0.0064 max mem: 33369 +Epoch: [29] [1260/1319] eta: 0:02:35 lr: 1.4415542261447945e-05 loss: 0.0303 (0.0392) time: 2.6516 data: 0.0062 max mem: 33369 +Epoch: [29] [1270/1319] eta: 0:02:09 lr: 1.4405748724439155e-05 loss: 0.0363 (0.0391) time: 2.6530 data: 0.0062 max mem: 33369 +Epoch: [29] [1280/1319] eta: 0:01:42 lr: 1.4395954447597464e-05 loss: 0.0342 (0.0391) time: 2.6416 data: 0.0062 max mem: 33369 +Epoch: [29] [1290/1319] eta: 0:01:16 lr: 1.4386159430307632e-05 loss: 0.0342 (0.0391) time: 2.6073 data: 0.0062 max mem: 33369 +Epoch: [29] [1300/1319] eta: 0:00:50 lr: 1.4376363671953435e-05 loss: 0.0384 (0.0392) time: 2.6065 data: 0.0062 max mem: 33369 +Epoch: [29] [1310/1319] eta: 0:00:23 lr: 1.4366567171917672e-05 loss: 0.0319 (0.0391) time: 2.6482 data: 0.0062 max mem: 33369 +Epoch: [29] Total time: 0:58:02 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 1:48:53 time: 2.5391 data: 2.2865 max mem: 33369 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 100/2573] eta: 0:04:01 time: 0.0717 data: 0.0011 max mem: 33369 +Test: [ 200/2573] eta: 0:03:24 time: 0.0735 data: 0.0011 max mem: 33369 +Test: [ 300/2573] eta: 0:03:05 time: 0.0753 data: 0.0011 max mem: 33369 +Test: [ 400/2573] eta: 0:02:52 time: 0.0755 data: 0.0011 max mem: 33369 +Test: [ 500/2573] eta: 0:02:42 time: 0.0738 data: 0.0011 max mem: 33369 +Test: [ 600/2573] eta: 0:02:33 time: 0.0739 data: 0.0011 max mem: 33369 +Test: [ 700/2573] eta: 0:02:25 time: 0.0739 data: 0.0011 max mem: 33369 +Test: [ 800/2573] eta: 0:02:16 time: 0.0771 data: 0.0011 max mem: 33369 +Test: [ 900/2573] eta: 0:02:08 time: 0.0739 data: 0.0011 max mem: 33369 +Test: [1000/2573] eta: 0:02:00 time: 0.0739 data: 0.0011 max mem: 33369 +Test: [1100/2573] eta: 0:01:52 time: 0.0741 data: 0.0011 max mem: 33369 +Test: [1200/2573] eta: 0:01:44 time: 0.0740 data: 0.0011 max mem: 33369 +Test: [1300/2573] eta: 0:01:36 time: 0.0739 data: 0.0011 max mem: 33369 +Test: [1400/2573] eta: 0:01:29 time: 0.0722 data: 0.0011 max mem: 33369 +Test: [1500/2573] eta: 0:01:21 time: 0.0740 data: 0.0011 max mem: 33369 +Test: [1600/2573] eta: 0:01:13 time: 0.0772 data: 0.0011 max mem: 33369 +Test: [1700/2573] eta: 0:01:06 time: 0.0722 data: 0.0011 max mem: 33369 +Test: [1800/2573] eta: 0:00:58 time: 0.0756 data: 0.0011 max mem: 33369 +Test: [1900/2573] eta: 0:00:50 time: 0.0724 data: 0.0011 max mem: 33369 +Test: [2000/2573] eta: 0:00:43 time: 0.0742 data: 0.0011 max mem: 33369 +Test: [2100/2573] eta: 0:00:35 time: 0.0757 data: 0.0011 max mem: 33369 +Test: [2200/2573] eta: 0:00:28 time: 0.0757 data: 0.0011 max mem: 33369 +Test: [2300/2573] eta: 0:00:20 time: 0.0757 data: 0.0011 max mem: 33369 +Test: [2400/2573] eta: 0:00:12 time: 0.0707 data: 0.0011 max mem: 33369 +Test: [2500/2573] eta: 0:00:05 time: 0.0740 data: 0.0011 max mem: 33369 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: Total time: 0:03:13 +Final results: +Mean IoU is 64.49 + + precision@0.5 = 72.34 + precision@0.6 = 66.93 + precision@0.7 = 60.11 + precision@0.8 = 48.16 + precision@0.9 = 23.96 + overall IoU = 62.33 + +Average object IoU 64.485956934896 +Overall IoU 62.33256149291992 +Better epoch: 29 + +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [30] [ 0/1319] eta: 1:24:14 lr: 1.4357749687236825e-05 loss: 0.0240 (0.0240) time: 3.8321 data: 1.1779 max mem: 33369 +Epoch: [30] [ 10/1319] eta: 0:59:06 lr: 1.4347951776302166e-05 loss: 0.0341 (0.0353) time: 2.7094 data: 0.1130 max mem: 33369 +Epoch: [30] [ 20/1319] eta: 0:58:27 lr: 1.433815312189048e-05 loss: 0.0391 (0.0389) time: 2.6439 data: 0.0065 max mem: 33369 +Epoch: [30] [ 30/1319] eta: 0:57:46 lr: 1.4328353723380728e-05 loss: 0.0368 (0.0379) time: 2.6781 data: 0.0065 max mem: 33369 +Epoch: [30] [ 40/1319] eta: 0:57:03 lr: 1.431855358015087e-05 loss: 0.0314 (0.0360) time: 2.6525 data: 0.0066 max mem: 33369 +Epoch: [30] [ 50/1319] eta: 0:56:27 lr: 1.4308752691577878e-05 loss: 0.0278 (0.0355) time: 2.6379 data: 0.0067 max mem: 33369 +Epoch: [30] [ 60/1319] eta: 0:55:55 lr: 1.4298951057037729e-05 loss: 0.0300 (0.0353) time: 2.6418 data: 0.0068 max mem: 33369 +Epoch: [30] [ 70/1319] eta: 0:55:29 lr: 1.4289148675905387e-05 loss: 0.0339 (0.0358) time: 2.6577 data: 0.0067 max mem: 33369 +Epoch: [30] [ 80/1319] eta: 0:54:54 lr: 1.4279345547554832e-05 loss: 0.0339 (0.0360) time: 2.6383 data: 0.0065 max mem: 33369 +Epoch: [30] [ 90/1319] eta: 0:54:23 lr: 1.4269541671359036e-05 loss: 0.0293 (0.0356) time: 2.6194 data: 0.0064 max mem: 33369 +Epoch: [30] [ 100/1319] eta: 0:53:57 lr: 1.4259737046689963e-05 loss: 0.0333 (0.0362) time: 2.6443 data: 0.0064 max mem: 33369 +Epoch: [30] [ 110/1319] eta: 0:53:32 lr: 1.424993167291858e-05 loss: 0.0377 (0.0358) time: 2.6627 data: 0.0064 max mem: 33369 +Epoch: [30] [ 120/1319] eta: 0:53:00 lr: 1.4240125549414829e-05 loss: 0.0354 (0.0363) time: 2.6359 data: 0.0065 max mem: 33369 +Epoch: [30] [ 130/1319] eta: 0:52:36 lr: 1.4230318675547643e-05 loss: 0.0353 (0.0366) time: 2.6446 data: 0.0066 max mem: 33369 +Epoch: [30] [ 140/1319] eta: 0:52:10 lr: 1.4220511050684946e-05 loss: 0.0351 (0.0370) time: 2.6737 data: 0.0065 max mem: 33369 +Epoch: [30] [ 150/1319] eta: 0:51:44 lr: 1.4210702674193643e-05 loss: 0.0373 (0.0371) time: 2.6627 data: 0.0064 max mem: 33369 +Epoch: [30] [ 160/1319] eta: 0:51:16 lr: 1.420089354543962e-05 loss: 0.0356 (0.0369) time: 2.6475 data: 0.0063 max mem: 33369 +Epoch: [30] [ 170/1319] eta: 0:50:50 lr: 1.419108366378774e-05 loss: 0.0335 (0.0376) time: 2.6448 data: 0.0063 max mem: 33369 +Epoch: [30] [ 180/1319] eta: 0:50:21 lr: 1.4181273028601838e-05 loss: 0.0328 (0.0374) time: 2.6383 data: 0.0065 max mem: 33369 +Epoch: [30] [ 190/1319] eta: 0:49:55 lr: 1.4171461639244721e-05 loss: 0.0323 (0.0373) time: 2.6428 data: 0.0066 max mem: 33369 +Epoch: [30] [ 200/1319] eta: 0:49:31 lr: 1.4161649495078178e-05 loss: 0.0332 (0.0373) time: 2.6822 data: 0.0065 max mem: 33369 +Epoch: [30] [ 210/1319] eta: 0:49:05 lr: 1.415183659546295e-05 loss: 0.0347 (0.0374) time: 2.6786 data: 0.0064 max mem: 33369 +Epoch: [30] [ 220/1319] eta: 0:48:36 lr: 1.4142022939758767e-05 loss: 0.0332 (0.0372) time: 2.6385 data: 0.0064 max mem: 33369 +Epoch: [30] [ 230/1319] eta: 0:48:10 lr: 1.413220852732429e-05 loss: 0.0316 (0.0371) time: 2.6349 data: 0.0063 max mem: 33369 +Epoch: [30] [ 240/1319] eta: 0:47:42 lr: 1.4122393357517167e-05 loss: 0.0277 (0.0367) time: 2.6432 data: 0.0065 max mem: 33369 +Epoch: [30] [ 250/1319] eta: 0:47:16 lr: 1.4112577429693993e-05 loss: 0.0277 (0.0367) time: 2.6499 data: 0.0065 max mem: 33369 +Epoch: [30] [ 260/1319] eta: 0:46:49 lr: 1.4102760743210322e-05 loss: 0.0319 (0.0366) time: 2.6473 data: 0.0063 max mem: 33369 +Epoch: [30] [ 270/1319] eta: 0:46:23 lr: 1.4092943297420657e-05 loss: 0.0320 (0.0365) time: 2.6464 data: 0.0064 max mem: 33369 +Epoch: [30] [ 280/1319] eta: 0:45:54 lr: 1.4083125091678468e-05 loss: 0.0353 (0.0365) time: 2.6355 data: 0.0065 max mem: 33369 +Epoch: [30] [ 290/1319] eta: 0:45:28 lr: 1.4073306125336142e-05 loss: 0.0353 (0.0365) time: 2.6287 data: 0.0065 max mem: 33369 +Epoch: [30] [ 300/1319] eta: 0:45:00 lr: 1.4063486397745037e-05 loss: 0.0328 (0.0364) time: 2.6286 data: 0.0064 max mem: 33369 +Epoch: [30] [ 310/1319] eta: 0:44:34 lr: 1.4053665908255448e-05 loss: 0.0330 (0.0364) time: 2.6380 data: 0.0064 max mem: 33369 +Epoch: [30] [ 320/1319] eta: 0:44:06 lr: 1.4043844656216607e-05 loss: 0.0341 (0.0364) time: 2.6418 data: 0.0064 max mem: 33369 +Epoch: [30] [ 330/1319] eta: 0:43:39 lr: 1.4034022640976696e-05 loss: 0.0327 (0.0363) time: 2.6103 data: 0.0063 max mem: 33369 +Epoch: [30] [ 340/1319] eta: 0:43:12 lr: 1.4024199861882808e-05 loss: 0.0327 (0.0364) time: 2.6280 data: 0.0061 max mem: 33369 +Epoch: [30] [ 350/1319] eta: 0:42:47 lr: 1.4014376318280992e-05 loss: 0.0309 (0.0362) time: 2.6761 data: 0.0063 max mem: 33369 +Epoch: [30] [ 360/1319] eta: 0:42:20 lr: 1.4004552009516214e-05 loss: 0.0309 (0.0360) time: 2.6676 data: 0.0063 max mem: 33369 +Epoch: [30] [ 370/1319] eta: 0:41:53 lr: 1.3994726934932381e-05 loss: 0.0339 (0.0362) time: 2.6249 data: 0.0063 max mem: 33369 +Epoch: [30] [ 380/1319] eta: 0:41:26 lr: 1.3984901093872316e-05 loss: 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1.3136936515041629e-05 loss: 0.0295 (0.0365) time: 2.6792 data: 0.0062 max mem: 33369 +Epoch: [30] [1250/1319] eta: 0:03:02 lr: 1.3127041345777947e-05 loss: 0.0303 (0.0366) time: 2.6776 data: 0.0063 max mem: 33369 +Epoch: [30] [1260/1319] eta: 0:02:35 lr: 1.3117145347668891e-05 loss: 0.0346 (0.0366) time: 2.6562 data: 0.0063 max mem: 33369 +Epoch: [30] [1270/1319] eta: 0:02:09 lr: 1.3107248519950133e-05 loss: 0.0346 (0.0366) time: 2.6377 data: 0.0063 max mem: 33369 +Epoch: [30] [1280/1319] eta: 0:01:42 lr: 1.3097350861856001e-05 loss: 0.0361 (0.0366) time: 2.6383 data: 0.0063 max mem: 33369 +Epoch: [30] [1290/1319] eta: 0:01:16 lr: 1.3087452372619463e-05 loss: 0.0344 (0.0367) time: 2.6443 data: 0.0063 max mem: 33369 +Epoch: [30] [1300/1319] eta: 0:00:50 lr: 1.3077553051472149e-05 loss: 0.0344 (0.0367) time: 2.6223 data: 0.0063 max mem: 33369 +Epoch: [30] [1310/1319] eta: 0:00:23 lr: 1.3067652897644308e-05 loss: 0.0344 (0.0367) time: 2.6036 data: 0.0063 max mem: 33369 +Epoch: [30] Total time: 0:58:00 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 2:10:30 time: 3.0434 data: 2.9649 max mem: 33369 +Test: [ 100/2573] eta: 0:04:10 time: 0.0715 data: 0.0011 max mem: 33369 +Test: [ 200/2573] eta: 0:03:28 time: 0.0732 data: 0.0011 max mem: 33369 +Test: [ 300/2573] eta: 0:03:07 time: 0.0751 data: 0.0010 max mem: 33369 +Test: [ 400/2573] eta: 0:02:54 time: 0.0751 data: 0.0010 max mem: 33369 +Test: [ 500/2573] eta: 0:02:43 time: 0.0736 data: 0.0011 max mem: 33369 +Test: [ 600/2573] eta: 0:02:34 time: 0.0737 data: 0.0011 max mem: 33369 +Test: [ 700/2573] eta: 0:02:25 time: 0.0737 data: 0.0011 max mem: 33369 +Test: [ 800/2573] eta: 0:02:17 time: 0.0771 data: 0.0011 max mem: 33369 +Test: [ 900/2573] eta: 0:02:09 time: 0.0738 data: 0.0011 max mem: 33369 +Test: [1000/2573] eta: 0:02:00 time: 0.0737 data: 0.0011 max mem: 33369 +Test: [1100/2573] eta: 0:01:52 time: 0.0737 data: 0.0011 max mem: 33369 +Test: [1200/2573] eta: 0:01:44 time: 0.0737 data: 0.0010 max mem: 33369 +Test: [1300/2573] eta: 0:01:37 time: 0.0737 data: 0.0010 max mem: 33369 +Test: [1400/2573] eta: 0:01:29 time: 0.0721 data: 0.0011 max mem: 33369 +Test: [1500/2573] eta: 0:01:21 time: 0.0738 data: 0.0011 max mem: 33369 +Test: [1600/2573] eta: 0:01:13 time: 0.0771 data: 0.0011 max mem: 33369 +Test: [1700/2573] eta: 0:01:06 time: 0.0721 data: 0.0010 max mem: 33369 +Test: [1800/2573] eta: 0:00:58 time: 0.0754 data: 0.0011 max mem: 33369 +Test: [1900/2573] eta: 0:00:50 time: 0.0721 data: 0.0011 max mem: 33369 +Test: [2000/2573] eta: 0:00:43 time: 0.0738 data: 0.0011 max mem: 33369 +Test: [2100/2573] eta: 0:00:35 time: 0.0753 data: 0.0010 max mem: 33369 +Test: [2200/2573] eta: 0:00:27 time: 0.0753 data: 0.0010 max mem: 33369 +Test: [2300/2573] eta: 0:00:20 time: 0.0754 data: 0.0011 max mem: 33369 +Test: [2400/2573] eta: 0:00:12 time: 0.0705 data: 0.0011 max mem: 33369 +Test: [2500/2573] eta: 0:00:05 time: 0.0738 data: 0.0011 max mem: 33369 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: Total time: 0:03:13 +Final results: +Mean IoU is 64.97 + + precision@0.5 = 73.26 + precision@0.6 = 67.77 + precision@0.7 = 60.25 + precision@0.8 = 48.77 + precision@0.9 = 24.51 + overall IoU = 62.46 + +Average object IoU 64.97417801811623 +Overall IoU 62.459564208984375 +Better epoch: 30 + +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [31] [ 0/1319] eta: 1:29:10 lr: 1.3058742046620123e-05 loss: 0.0436 (0.0436) time: 4.0564 data: 1.4479 max mem: 33369 +Epoch: [31] [ 10/1319] eta: 1:01:17 lr: 1.3048840308573793e-05 loss: 0.0345 (0.0343) time: 2.8092 data: 0.1376 max mem: 33369 +Epoch: [31] [ 20/1319] eta: 0:59:01 lr: 1.3038937735606992e-05 loss: 0.0308 (0.0330) time: 2.6597 data: 0.0061 max mem: 33369 +Epoch: [31] [ 30/1319] eta: 0:57:59 lr: 1.3029034326944665e-05 loss: 0.0323 (0.0347) time: 2.6386 data: 0.0062 max mem: 33369 +Epoch: [31] [ 40/1319] eta: 0:57:13 lr: 1.3019130081810363e-05 loss: 0.0330 (0.0350) time: 2.6403 data: 0.0067 max mem: 33369 +Epoch: [31] [ 50/1319] eta: 0:56:45 lr: 1.3009224999426282e-05 loss: 0.0311 (0.0353) time: 2.6600 data: 0.0066 max mem: 33369 +Epoch: [31] [ 60/1319] eta: 0:56:08 lr: 1.2999319079013207e-05 loss: 0.0318 (0.0354) time: 2.6576 data: 0.0065 max mem: 33369 +Epoch: [31] [ 70/1319] eta: 0:55:27 lr: 1.298941231979056e-05 loss: 0.0338 (0.0357) time: 2.6138 data: 0.0065 max mem: 33369 +Epoch: [31] [ 80/1319] eta: 0:55:01 lr: 1.2979504720976363e-05 loss: 0.0318 (0.0352) time: 2.6299 data: 0.0065 max mem: 33369 +Epoch: [31] [ 90/1319] eta: 0:54:35 lr: 1.2969596281787253e-05 loss: 0.0316 (0.0357) time: 2.6686 data: 0.0064 max mem: 33369 +Epoch: [31] [ 100/1319] eta: 0:54:07 lr: 1.2959687001438464e-05 loss: 0.0335 (0.0358) time: 2.6629 data: 0.0065 max mem: 33369 +Epoch: [31] [ 110/1319] eta: 0:53:38 lr: 1.2949776879143838e-05 loss: 0.0335 (0.0358) time: 2.6482 data: 0.0065 max mem: 33369 +Epoch: [31] [ 120/1319] eta: 0:53:08 lr: 1.2939865914115796e-05 loss: 0.0300 (0.0359) time: 2.6339 data: 0.0065 max mem: 33369 +Epoch: [31] [ 130/1319] eta: 0:52:41 lr: 1.2929954105565368e-05 loss: 0.0388 (0.0363) time: 2.6411 data: 0.0066 max mem: 33369 +Epoch: [31] [ 140/1319] eta: 0:52:15 lr: 1.2920041452702167e-05 loss: 0.0338 (0.0361) time: 2.6607 data: 0.0066 max mem: 33369 +Epoch: [31] [ 150/1319] eta: 0:51:49 lr: 1.2910127954734388e-05 loss: 0.0275 (0.0358) time: 2.6690 data: 0.0066 max mem: 33369 +Epoch: [31] [ 160/1319] eta: 0:51:20 lr: 1.2900213610868823e-05 loss: 0.0313 (0.0359) time: 2.6492 data: 0.0064 max mem: 33369 +Epoch: [31] [ 170/1319] eta: 0:50:48 lr: 1.2890298420310808e-05 loss: 0.0324 (0.0357) time: 2.6012 data: 0.0063 max mem: 33369 +Epoch: [31] [ 180/1319] eta: 0:50:21 lr: 1.2880382382264284e-05 loss: 0.0324 (0.0359) time: 2.6074 data: 0.0065 max mem: 33369 +Epoch: [31] [ 190/1319] eta: 0:49:53 lr: 1.2870465495931752e-05 loss: 0.0284 (0.0356) time: 2.6318 data: 0.0066 max mem: 33369 +Epoch: [31] [ 200/1319] eta: 0:49:27 lr: 1.2860547760514275e-05 loss: 0.0293 (0.0356) time: 2.6435 data: 0.0064 max mem: 33369 +Epoch: [31] [ 210/1319] eta: 0:49:00 lr: 1.285062917521149e-05 loss: 0.0319 (0.0358) time: 2.6582 data: 0.0064 max mem: 33369 +Epoch: [31] [ 220/1319] eta: 0:48:33 lr: 1.2840709739221567e-05 loss: 0.0331 (0.0358) time: 2.6437 data: 0.0064 max mem: 33369 +Epoch: [31] [ 230/1319] eta: 0:48:06 lr: 1.2830789451741262e-05 loss: 0.0332 (0.0357) time: 2.6436 data: 0.0064 max mem: 33369 +Epoch: [31] [ 240/1319] eta: 0:47:38 lr: 1.2820868311965862e-05 loss: 0.0315 (0.0356) time: 2.6364 data: 0.0066 max mem: 33369 +Epoch: [31] [ 250/1319] eta: 0:47:12 lr: 1.2810946319089204e-05 loss: 0.0315 (0.0355) time: 2.6292 data: 0.0065 max mem: 33369 +Epoch: [31] [ 260/1319] eta: 0:46:45 lr: 1.2801023472303672e-05 loss: 0.0358 (0.0357) time: 2.6440 data: 0.0064 max mem: 33369 +Epoch: [31] [ 270/1319] eta: 0:46:16 lr: 1.2791099770800195e-05 loss: 0.0383 (0.0356) time: 2.6127 data: 0.0065 max mem: 33369 +Epoch: [31] [ 280/1319] eta: 0:45:49 lr: 1.2781175213768214e-05 loss: 0.0339 (0.0356) time: 2.6119 data: 0.0066 max mem: 33369 +Epoch: [31] [ 290/1319] eta: 0:45:23 lr: 1.277124980039573e-05 loss: 0.0319 (0.0355) time: 2.6428 data: 0.0066 max mem: 33369 +Epoch: [31] [ 300/1319] eta: 0:44:56 lr: 1.2761323529869248e-05 loss: 0.0319 (0.0356) time: 2.6374 data: 0.0064 max mem: 33369 +Epoch: [31] [ 310/1319] eta: 0:44:30 lr: 1.2751396401373813e-05 loss: 0.0398 (0.0359) time: 2.6451 data: 0.0064 max mem: 33369 +Epoch: [31] [ 320/1319] eta: 0:44:04 lr: 1.2741468414092989e-05 loss: 0.0397 (0.0360) time: 2.6641 data: 0.0064 max mem: 33369 +Epoch: [31] [ 330/1319] eta: 0:43:39 lr: 1.2731539567208833e-05 loss: 0.0336 (0.0360) time: 2.6868 data: 0.0063 max mem: 33369 +Epoch: [31] [ 340/1319] eta: 0:43:12 lr: 1.2721609859901942e-05 loss: 0.0335 (0.0360) time: 2.6725 data: 0.0064 max mem: 33369 +Epoch: [31] [ 350/1319] eta: 0:42:46 lr: 1.2711679291351405e-05 loss: 0.0371 (0.0361) time: 2.6408 data: 0.0064 max mem: 33369 +Epoch: [31] [ 360/1319] eta: 0:42:20 lr: 1.2701747860734819e-05 loss: 0.0387 (0.0361) time: 2.6523 data: 0.0063 max mem: 33369 +Epoch: [31] [ 370/1319] eta: 0:41:52 lr: 1.2691815567228285e-05 loss: 0.0368 (0.0362) time: 2.6384 data: 0.0064 max mem: 33369 +Epoch: [31] [ 380/1319] eta: 0:41:26 lr: 1.2681882410006382e-05 loss: 0.0362 (0.0364) time: 2.6334 data: 0.0065 max mem: 33369 +Epoch: [31] [ 390/1319] eta: 0:40:59 lr: 1.26719483882422e-05 loss: 0.0378 (0.0365) time: 2.6481 data: 0.0064 max mem: 33369 +Epoch: [31] [ 400/1319] eta: 0:40:33 lr: 1.2662013501107303e-05 loss: 0.0339 (0.0364) time: 2.6503 data: 0.0063 max mem: 33369 +Epoch: [31] [ 410/1319] eta: 0:40:06 lr: 1.265207774777175e-05 loss: 0.0322 (0.0364) time: 2.6511 data: 0.0065 max mem: 33369 +Epoch: [31] [ 420/1319] eta: 0:39:40 lr: 1.2642141127404073e-05 loss: 0.0343 (0.0364) time: 2.6450 data: 0.0067 max mem: 33369 +Epoch: [31] [ 430/1319] eta: 0:39:14 lr: 1.2632203639171281e-05 loss: 0.0304 (0.0362) time: 2.6538 data: 0.0065 max mem: 33369 +Epoch: [31] [ 440/1319] eta: 0:38:47 lr: 1.2622265282238837e-05 loss: 0.0303 (0.0363) time: 2.6483 data: 0.0063 max mem: 33369 +Epoch: [31] [ 450/1319] eta: 0:38:21 lr: 1.2612326055770701e-05 loss: 0.0306 (0.0361) time: 2.6588 data: 0.0063 max mem: 33369 +Epoch: [31] [ 460/1319] eta: 0:37:54 lr: 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data: 0.0062 max mem: 33369 +Epoch: [31] [ 700/1319] eta: 0:27:17 lr: 1.236356031760655e-05 loss: 0.0334 (0.0368) time: 2.6473 data: 0.0063 max mem: 33369 +Epoch: [31] [ 710/1319] eta: 0:26:51 lr: 1.2353598184630927e-05 loss: 0.0371 (0.0368) time: 2.6585 data: 0.0065 max mem: 33369 +Epoch: [31] [ 720/1319] eta: 0:26:24 lr: 1.2343635158950937e-05 loss: 0.0371 (0.0370) time: 2.6325 data: 0.0064 max mem: 33369 +Epoch: [31] [ 730/1319] eta: 0:25:58 lr: 1.2333671239685849e-05 loss: 0.0350 (0.0369) time: 2.6273 data: 0.0064 max mem: 33369 +Epoch: [31] [ 740/1319] eta: 0:25:32 lr: 1.2323706425953264e-05 loss: 0.0307 (0.0368) time: 2.6599 data: 0.0065 max mem: 33369 +Epoch: [31] [ 750/1319] eta: 0:25:05 lr: 1.2313740716869131e-05 loss: 0.0317 (0.0368) time: 2.6477 data: 0.0063 max mem: 33369 +Epoch: [31] [ 760/1319] eta: 0:24:39 lr: 1.2303774111547706e-05 loss: 0.0300 (0.0367) time: 2.6409 data: 0.0064 max mem: 33369 +Epoch: [31] [ 770/1319] eta: 0:24:12 lr: 1.2293806609101593e-05 loss: 0.0333 (0.0368) time: 2.6485 data: 0.0065 max mem: 33369 +Epoch: [31] [ 780/1319] eta: 0:23:45 lr: 1.2283838208641708e-05 loss: 0.0347 (0.0368) time: 2.6246 data: 0.0063 max mem: 33369 +Epoch: [31] [ 790/1319] eta: 0:23:19 lr: 1.2273868909277286e-05 loss: 0.0347 (0.0369) time: 2.6303 data: 0.0062 max mem: 33369 +Epoch: [31] [ 800/1319] eta: 0:22:52 lr: 1.2263898710115878e-05 loss: 0.0321 (0.0368) time: 2.6400 data: 0.0063 max mem: 33369 +Epoch: [31] [ 810/1319] eta: 0:22:26 lr: 1.2253927610263324e-05 loss: 0.0302 (0.0368) time: 2.6511 data: 0.0065 max mem: 33369 +Epoch: [31] [ 820/1319] eta: 0:22:00 lr: 1.2243955608823781e-05 loss: 0.0322 (0.0368) time: 2.6544 data: 0.0065 max mem: 33369 +Epoch: [31] [ 830/1319] eta: 0:21:33 lr: 1.2233982704899707e-05 loss: 0.0358 (0.0368) time: 2.6312 data: 0.0064 max mem: 33369 +Epoch: [31] [ 840/1319] eta: 0:21:07 lr: 1.2224008897591841e-05 loss: 0.0358 (0.0369) time: 2.6365 data: 0.0066 max mem: 33369 +Epoch: [31] [ 850/1319] eta: 0:20:40 lr: 1.2214034185999218e-05 loss: 0.0319 (0.0369) time: 2.6390 data: 0.0065 max mem: 33369 +Epoch: [31] [ 860/1319] eta: 0:20:13 lr: 1.2204058569219158e-05 loss: 0.0311 (0.0368) time: 2.6245 data: 0.0065 max mem: 33369 +Epoch: [31] [ 870/1319] eta: 0:19:47 lr: 1.2194082046347242e-05 loss: 0.0322 (0.0368) time: 2.6201 data: 0.0066 max mem: 33369 +Epoch: [31] [ 880/1319] eta: 0:19:20 lr: 1.2184104616477345e-05 loss: 0.0394 (0.0369) time: 2.6208 data: 0.0065 max mem: 33369 +Epoch: [31] [ 890/1319] eta: 0:18:54 lr: 1.2174126278701602e-05 loss: 0.0346 (0.0370) time: 2.6168 data: 0.0064 max mem: 33369 +Epoch: [31] [ 900/1319] eta: 0:18:27 lr: 1.2164147032110409e-05 loss: 0.0339 (0.0371) time: 2.6322 data: 0.0063 max mem: 33369 +Epoch: [31] [ 910/1319] eta: 0:18:01 lr: 1.215416687579243e-05 loss: 0.0338 (0.0370) time: 2.6422 data: 0.0064 max mem: 33369 +Epoch: [31] [ 920/1319] eta: 0:17:34 lr: 1.2144185808834565e-05 loss: 0.0309 (0.0370) time: 2.6251 data: 0.0065 max mem: 33369 +Epoch: [31] [ 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33369 +Epoch: [31] [1010/1319] eta: 0:13:36 lr: 1.2054315075888731e-05 loss: 0.0306 (0.0368) time: 2.6457 data: 0.0064 max mem: 33369 +Epoch: [31] [1020/1319] eta: 0:13:10 lr: 1.2044324851924447e-05 loss: 0.0331 (0.0368) time: 2.6669 data: 0.0064 max mem: 33369 +Epoch: [31] [1030/1319] eta: 0:12:44 lr: 1.2034333707159618e-05 loss: 0.0331 (0.0368) time: 2.6643 data: 0.0065 max mem: 33369 +Epoch: [31] [1040/1319] eta: 0:12:17 lr: 1.2024341640659817e-05 loss: 0.0364 (0.0369) time: 2.6454 data: 0.0065 max mem: 33369 +Epoch: [31] [1050/1319] eta: 0:11:51 lr: 1.2014348651488794e-05 loss: 0.0322 (0.0368) time: 2.6611 data: 0.0064 max mem: 33369 +Epoch: [31] [1060/1319] eta: 0:11:24 lr: 1.2004354738708488e-05 loss: 0.0279 (0.0368) time: 2.6606 data: 0.0062 max mem: 33369 +Epoch: [31] [1070/1319] eta: 0:10:58 lr: 1.1994359901379014e-05 loss: 0.0348 (0.0368) time: 2.6504 data: 0.0061 max mem: 33369 +Epoch: [31] [1080/1319] eta: 0:10:32 lr: 1.1984364138558649e-05 loss: 0.0341 (0.0368) time: 2.6353 data: 0.0062 max mem: 33369 +Epoch: [31] [1090/1319] eta: 0:10:05 lr: 1.1974367449303851e-05 loss: 0.0315 (0.0369) time: 2.6352 data: 0.0062 max mem: 33369 +Epoch: [31] [1100/1319] eta: 0:09:39 lr: 1.1964369832669236e-05 loss: 0.0325 (0.0369) time: 2.6600 data: 0.0065 max mem: 33369 +Epoch: [31] [1110/1319] eta: 0:09:12 lr: 1.195437128770757e-05 loss: 0.0321 (0.0368) time: 2.6602 data: 0.0066 max mem: 33369 +Epoch: [31] [1120/1319] eta: 0:08:46 lr: 1.194437181346979e-05 loss: 0.0319 (0.0368) time: 2.6479 data: 0.0063 max mem: 33369 +Epoch: [31] [1130/1319] eta: 0:08:19 lr: 1.1934371409004944e-05 loss: 0.0324 (0.0368) time: 2.6516 data: 0.0063 max mem: 33369 +Epoch: [31] [1140/1319] eta: 0:07:53 lr: 1.192437007336025e-05 loss: 0.0334 (0.0368) time: 2.6501 data: 0.0065 max mem: 33369 +Epoch: [31] [1150/1319] eta: 0:07:26 lr: 1.1914367805581053e-05 loss: 0.0334 (0.0368) time: 2.6374 data: 0.0064 max mem: 33369 +Epoch: [31] [1160/1319] eta: 0:07:00 lr: 1.1904364604710826e-05 loss: 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1.1824305291067328e-05 loss: 0.0335 (0.0368) time: 2.6325 data: 0.0064 max mem: 33369 +Epoch: [31] [1250/1319] eta: 0:03:02 lr: 1.1814293649022872e-05 loss: 0.0297 (0.0367) time: 2.6672 data: 0.0063 max mem: 33369 +Epoch: [31] [1260/1319] eta: 0:02:36 lr: 1.180428106421806e-05 loss: 0.0300 (0.0367) time: 2.6588 data: 0.0062 max mem: 33369 +Epoch: [31] [1270/1319] eta: 0:02:09 lr: 1.1794267535675433e-05 loss: 0.0319 (0.0367) time: 2.6347 data: 0.0062 max mem: 33369 +Epoch: [31] [1280/1319] eta: 0:01:43 lr: 1.1784253062415594e-05 loss: 0.0345 (0.0367) time: 2.6386 data: 0.0063 max mem: 33369 +Epoch: [31] [1290/1319] eta: 0:01:16 lr: 1.1774237643457209e-05 loss: 0.0356 (0.0367) time: 2.6542 data: 0.0062 max mem: 33369 +Epoch: [31] [1300/1319] eta: 0:00:50 lr: 1.1764221277816978e-05 loss: 0.0356 (0.0367) time: 2.6283 data: 0.0062 max mem: 33369 +Epoch: [31] [1310/1319] eta: 0:00:23 lr: 1.1754203964509668e-05 loss: 0.0338 (0.0367) time: 2.6493 data: 0.0063 max mem: 33369 +Epoch: [31] Total time: 0:58:08 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 2:12:26 time: 3.0885 data: 2.9334 max mem: 33369 +Test: [ 100/2573] eta: 0:04:11 time: 0.0715 data: 0.0011 max mem: 33369 +Test: [ 200/2573] eta: 0:03:28 time: 0.0734 data: 0.0011 max mem: 33369 +Test: [ 300/2573] eta: 0:03:08 time: 0.0751 data: 0.0011 max mem: 33369 +Test: [ 400/2573] eta: 0:02:54 time: 0.0753 data: 0.0011 max mem: 33369 +Test: [ 500/2573] eta: 0:02:43 time: 0.0737 data: 0.0011 max mem: 33369 +Test: [ 600/2573] eta: 0:02:34 time: 0.0737 data: 0.0011 max mem: 33369 +Test: [ 700/2573] eta: 0:02:25 time: 0.0737 data: 0.0011 max mem: 33369 +Test: [ 800/2573] eta: 0:02:17 time: 0.0772 data: 0.0011 max mem: 33369 +Test: [ 900/2573] eta: 0:02:09 time: 0.0737 data: 0.0011 max mem: 33369 +Test: [1000/2573] eta: 0:02:01 time: 0.0738 data: 0.0011 max mem: 33369 +Test: [1100/2573] eta: 0:01:52 time: 0.0738 data: 0.0011 max mem: 33369 +Test: [1200/2573] eta: 0:01:45 time: 0.0740 data: 0.0011 max mem: 33369 +Test: [1300/2573] eta: 0:01:37 time: 0.0738 data: 0.0010 max mem: 33369 +Test: [1400/2573] eta: 0:01:29 time: 0.0722 data: 0.0011 max mem: 33369 +Test: [1500/2573] eta: 0:01:21 time: 0.0738 data: 0.0011 max mem: 33369 +Test: [1600/2573] eta: 0:01:13 time: 0.0772 data: 0.0011 max mem: 33369 +Test: [1700/2573] eta: 0:01:06 time: 0.0723 data: 0.0011 max mem: 33369 +Test: [1800/2573] eta: 0:00:58 time: 0.0755 data: 0.0011 max mem: 33369 +Test: [1900/2573] eta: 0:00:50 time: 0.0722 data: 0.0011 max mem: 33369 +Test: [2000/2573] eta: 0:00:43 time: 0.0739 data: 0.0011 max mem: 33369 +Test: [2100/2573] eta: 0:00:35 time: 0.0754 data: 0.0010 max mem: 33369 +Test: [2200/2573] eta: 0:00:28 time: 0.0753 data: 0.0010 max mem: 33369 +Test: [2300/2573] eta: 0:00:20 time: 0.0754 data: 0.0011 max mem: 33369 +Test: [2400/2573] eta: 0:00:12 time: 0.0704 data: 0.0011 max mem: 33369 +Test: [2500/2573] eta: 0:00:05 time: 0.0738 data: 0.0011 max mem: 33369 +Test: Total time: 0:03:13 +Final results: +Mean IoU is 64.79 + + precision@0.5 = 73.00 + precision@0.6 = 67.57 + precision@0.7 = 60.85 + precision@0.8 = 49.41 + precision@0.9 = 24.63 + overall IoU = 62.88 + +Average object IoU 64.79203770049267 +Overall IoU 62.87544631958008 +Better epoch: 31 + +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [32] [ 0/1319] eta: 1:26:43 lr: 1.1745187571461855e-05 loss: 0.0313 (0.0313) time: 3.9452 data: 1.1804 max mem: 33369 +Epoch: [32] [ 10/1319] eta: 1:00:56 lr: 1.1735168454865734e-05 loss: 0.0243 (0.0288) time: 2.7935 data: 0.1128 max mem: 33369 +Epoch: [32] [ 20/1319] eta: 0:58:42 lr: 1.1725148387734231e-05 loss: 0.0276 (0.0322) time: 2.6504 data: 0.0059 max mem: 33369 +Epoch: [32] [ 30/1319] eta: 0:57:47 lr: 1.1715127369074435e-05 loss: 0.0319 (0.0320) time: 2.6338 data: 0.0063 max mem: 33369 +Epoch: [32] [ 40/1319] eta: 0:57:07 lr: 1.1705105397891451e-05 loss: 0.0265 (0.0317) time: 2.6457 data: 0.0066 max mem: 33369 +Epoch: [32] [ 50/1319] eta: 0:56:28 lr: 1.1695082473188386e-05 loss: 0.0311 (0.0326) time: 2.6387 data: 0.0065 max mem: 33369 +Epoch: [32] [ 60/1319] eta: 0:55:52 lr: 1.1685058593966367e-05 loss: 0.0315 (0.0327) time: 2.6275 data: 0.0066 max mem: 33369 +Epoch: [32] [ 70/1319] eta: 0:55:25 lr: 1.1675033759224512e-05 loss: 0.0304 (0.0322) time: 2.6436 data: 0.0067 max mem: 33369 +Epoch: [32] [ 80/1319] eta: 0:54:54 lr: 1.1665007967959945e-05 loss: 0.0313 (0.0327) time: 2.6480 data: 0.0066 max mem: 33369 +Epoch: [32] [ 90/1319] eta: 0:54:30 lr: 1.1654981219167763e-05 loss: 0.0327 (0.0327) time: 2.6551 data: 0.0064 max mem: 33369 +Epoch: [32] [ 100/1319] eta: 0:54:00 lr: 1.1644953511841062e-05 loss: 0.0322 (0.0326) time: 2.6575 data: 0.0064 max mem: 33369 +Epoch: [32] [ 110/1319] eta: 0:53:30 lr: 1.1634924844970898e-05 loss: 0.0316 (0.0325) time: 2.6312 data: 0.0066 max mem: 33369 +Epoch: [32] [ 120/1319] eta: 0:53:06 lr: 1.1624895217546308e-05 loss: 0.0312 (0.0326) time: 2.6547 data: 0.0066 max mem: 33369 +Epoch: [32] [ 130/1319] eta: 0:52:33 lr: 1.1614864628554293e-05 loss: 0.0321 (0.0333) time: 2.6346 data: 0.0066 max mem: 33369 +Epoch: [32] [ 140/1319] eta: 0:52:05 lr: 1.160483307697981e-05 loss: 0.0321 (0.0334) time: 2.6082 data: 0.0065 max mem: 33369 +Epoch: [32] [ 150/1319] eta: 0:51:39 lr: 1.159480056180578e-05 loss: 0.0278 (0.0332) time: 2.6479 data: 0.0065 max mem: 33369 +Epoch: [32] [ 160/1319] eta: 0:51:09 lr: 1.1584767082013038e-05 loss: 0.0303 (0.0334) time: 2.6320 data: 0.0066 max mem: 33369 +Epoch: [32] [ 170/1319] eta: 0:50:41 lr: 1.1574732636580395e-05 loss: 0.0312 (0.0337) time: 2.6130 data: 0.0066 max mem: 33369 +Epoch: [32] [ 180/1319] eta: 0:50:14 lr: 1.1564697224484583e-05 loss: 0.0280 (0.0336) time: 2.6278 data: 0.0064 max mem: 33369 +Epoch: [32] [ 190/1319] eta: 0:49:46 lr: 1.1554660844700256e-05 loss: 0.0297 (0.0337) time: 2.6259 data: 0.0064 max mem: 33369 +Epoch: [32] [ 200/1319] eta: 0:49:20 lr: 1.1544623496200004e-05 loss: 0.0344 (0.0339) time: 2.6388 data: 0.0064 max mem: 33369 +Epoch: [32] [ 210/1319] eta: 0:48:53 lr: 1.153458517795431e-05 loss: 0.0366 (0.0341) time: 2.6462 data: 0.0065 max mem: 33369 +Epoch: [32] [ 220/1319] eta: 0:48:26 lr: 1.1524545888931584e-05 loss: 0.0336 (0.0343) time: 2.6340 data: 0.0065 max mem: 33369 +Epoch: [32] [ 230/1319] eta: 0:48:00 lr: 1.1514505628098139e-05 loss: 0.0321 (0.0343) time: 2.6416 data: 0.0065 max mem: 33369 +Epoch: [32] [ 240/1319] eta: 0:47:33 lr: 1.1504464394418176e-05 loss: 0.0321 (0.0343) time: 2.6408 data: 0.0064 max mem: 33369 +Epoch: [32] [ 250/1319] eta: 0:47:05 lr: 1.149442218685379e-05 loss: 0.0295 (0.0341) time: 2.6282 data: 0.0064 max mem: 33369 +Epoch: [32] [ 260/1319] eta: 0:46:38 lr: 1.1484379004364971e-05 loss: 0.0257 (0.0339) time: 2.6263 data: 0.0066 max mem: 33369 +Epoch: [32] [ 270/1319] eta: 0:46:12 lr: 1.147433484590956e-05 loss: 0.0266 (0.0339) time: 2.6310 data: 0.0066 max mem: 33369 +Epoch: [32] [ 280/1319] eta: 0:45:47 lr: 1.1464289710443295e-05 loss: 0.0300 (0.0338) time: 2.6649 data: 0.0064 max mem: 33369 +Epoch: [32] [ 290/1319] eta: 0:45:21 lr: 1.1454243596919765e-05 loss: 0.0315 (0.0339) time: 2.6720 data: 0.0063 max mem: 33369 +Epoch: [32] [ 300/1319] eta: 0:44:54 lr: 1.144419650429042e-05 loss: 0.0333 (0.0340) time: 2.6393 data: 0.0064 max mem: 33369 +Epoch: [32] [ 310/1319] eta: 0:44:27 lr: 1.1434148431504575e-05 loss: 0.0310 (0.0338) time: 2.6326 data: 0.0063 max mem: 33369 +Epoch: [32] [ 320/1319] eta: 0:44:01 lr: 1.1424099377509363e-05 loss: 0.0290 (0.0337) time: 2.6453 data: 0.0062 max mem: 33369 +Epoch: [32] [ 330/1319] eta: 0:43:34 lr: 1.141404934124978e-05 loss: 0.0325 (0.0337) time: 2.6400 data: 0.0063 max mem: 33369 +Epoch: [32] [ 340/1319] eta: 0:43:06 lr: 1.140399832166864e-05 loss: 0.0293 (0.0336) time: 2.6112 data: 0.0065 max mem: 33369 +Epoch: [32] [ 350/1319] eta: 0:42:41 lr: 1.1393946317706594e-05 loss: 0.0293 (0.0337) time: 2.6347 data: 0.0064 max mem: 33369 +Epoch: [32] [ 360/1319] eta: 0:42:13 lr: 1.138389332830211e-05 loss: 0.0331 (0.0338) time: 2.6425 data: 0.0063 max mem: 33369 +Epoch: [32] [ 370/1319] eta: 0:41:47 lr: 1.1373839352391454e-05 loss: 0.0334 (0.0338) time: 2.6192 data: 0.0063 max mem: 33369 +Epoch: [32] [ 380/1319] eta: 0:41:20 lr: 1.1363784388908714e-05 loss: 0.0334 (0.0343) time: 2.6403 data: 0.0064 max mem: 33369 +Epoch: [32] [ 390/1319] eta: 0:40:55 lr: 1.1353728436785773e-05 loss: 0.0322 (0.0342) time: 2.6671 data: 0.0063 max mem: 33369 +Epoch: [32] [ 400/1319] eta: 0:40:30 lr: 1.1343671494952302e-05 loss: 0.0339 (0.0344) time: 2.6878 data: 0.0063 max mem: 33369 +Epoch: [32] [ 410/1319] eta: 0:40:03 lr: 1.1333613562335765e-05 loss: 0.0337 (0.0343) time: 2.6656 data: 0.0065 max mem: 33369 +Epoch: [32] [ 420/1319] eta: 0:39:36 lr: 1.1323554637861402e-05 loss: 0.0308 (0.0344) time: 2.6208 data: 0.0066 max mem: 33369 +Epoch: [32] [ 430/1319] eta: 0:39:09 lr: 1.1313494720452216e-05 loss: 0.0323 (0.0344) time: 2.6166 data: 0.0065 max mem: 33369 +Epoch: [32] [ 440/1319] eta: 0:38:44 lr: 1.1303433809028986e-05 loss: 0.0339 (0.0345) time: 2.6608 data: 0.0064 max mem: 33369 +Epoch: [32] [ 450/1319] eta: 0:38:16 lr: 1.1293371902510248e-05 loss: 0.0366 (0.0347) time: 2.6450 data: 0.0065 max mem: 33369 +Epoch: [32] [ 460/1319] eta: 0:37:50 lr: 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1.0890066963908222e-05 loss: 0.0313 (0.0344) time: 2.6390 data: 0.0065 max mem: 33369 +Epoch: [32] [ 860/1319] eta: 0:20:12 lr: 1.087996329870281e-05 loss: 0.0291 (0.0344) time: 2.6777 data: 0.0064 max mem: 33369 +Epoch: [32] [ 870/1319] eta: 0:19:46 lr: 1.0869858590861098e-05 loss: 0.0324 (0.0344) time: 2.6934 data: 0.0063 max mem: 33369 +Epoch: [32] [ 880/1319] eta: 0:19:20 lr: 1.085975283919833e-05 loss: 0.0303 (0.0343) time: 2.6710 data: 0.0064 max mem: 33369 +Epoch: [32] [ 890/1319] eta: 0:18:53 lr: 1.0849646042527184e-05 loss: 0.0325 (0.0345) time: 2.6460 data: 0.0064 max mem: 33369 +Epoch: [32] [ 900/1319] eta: 0:18:27 lr: 1.0839538199657755e-05 loss: 0.0331 (0.0344) time: 2.6249 data: 0.0065 max mem: 33369 +Epoch: [32] [ 910/1319] eta: 0:18:00 lr: 1.0829429309397535e-05 loss: 0.0280 (0.0344) time: 2.6340 data: 0.0063 max mem: 33369 +Epoch: [32] [ 920/1319] eta: 0:17:34 lr: 1.0819319370551438e-05 loss: 0.0359 (0.0344) time: 2.6484 data: 0.0063 max mem: 33369 +Epoch: [32] [ 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data: 0.0066 max mem: 33369 +Epoch: [32] [1090/1319] eta: 0:10:05 lr: 1.0647288805724908e-05 loss: 0.0363 (0.0345) time: 2.6413 data: 0.0065 max mem: 33369 +Epoch: [32] [1100/1319] eta: 0:09:38 lr: 1.0637159784959879e-05 loss: 0.0312 (0.0346) time: 2.6149 data: 0.0063 max mem: 33369 +Epoch: [32] [1110/1319] eta: 0:09:12 lr: 1.0627029692397306e-05 loss: 0.0358 (0.0346) time: 2.6286 data: 0.0063 max mem: 33369 +Epoch: [32] [1120/1319] eta: 0:08:45 lr: 1.0616898526788328e-05 loss: 0.0306 (0.0346) time: 2.6627 data: 0.0064 max mem: 33369 +Epoch: [32] [1130/1319] eta: 0:08:19 lr: 1.0606766286881316e-05 loss: 0.0307 (0.0347) time: 2.6474 data: 0.0062 max mem: 33369 +Epoch: [32] [1140/1319] eta: 0:07:52 lr: 1.059663297142185e-05 loss: 0.0311 (0.0347) time: 2.6220 data: 0.0062 max mem: 33369 +Epoch: [32] [1150/1319] eta: 0:07:26 lr: 1.058649857915271e-05 loss: 0.0311 (0.0347) time: 2.6226 data: 0.0062 max mem: 33369 +Epoch: [32] [1160/1319] eta: 0:07:00 lr: 1.0576363108813862e-05 loss: 0.0315 (0.0347) time: 2.6424 data: 0.0062 max mem: 33369 +Epoch: [32] [1170/1319] eta: 0:06:33 lr: 1.0566226559142468e-05 loss: 0.0362 (0.0347) time: 2.6188 data: 0.0063 max mem: 33369 +Epoch: [32] [1180/1319] eta: 0:06:07 lr: 1.0556088928872841e-05 loss: 0.0359 (0.0347) time: 2.6182 data: 0.0063 max mem: 33369 +Epoch: [32] [1190/1319] eta: 0:05:40 lr: 1.0545950216736473e-05 loss: 0.0314 (0.0347) time: 2.6380 data: 0.0063 max mem: 33369 +Epoch: [32] [1200/1319] eta: 0:05:14 lr: 1.0535810421462011e-05 loss: 0.0336 (0.0347) time: 2.6721 data: 0.0062 max mem: 33369 +Epoch: [32] [1210/1319] eta: 0:04:47 lr: 1.0525669541775238e-05 loss: 0.0333 (0.0347) time: 2.6716 data: 0.0063 max mem: 33369 +Epoch: [32] [1220/1319] eta: 0:04:21 lr: 1.0515527576399085e-05 loss: 0.0271 (0.0346) time: 2.6178 data: 0.0063 max mem: 33369 +Epoch: [32] [1230/1319] eta: 0:03:55 lr: 1.050538452405359e-05 loss: 0.0345 (0.0347) time: 2.6193 data: 0.0066 max mem: 33369 +Epoch: [32] [1240/1319] eta: 0:03:28 lr: 1.049524038345592e-05 loss: 0.0342 (0.0347) time: 2.6274 data: 0.0066 max mem: 33369 +Epoch: [32] [1250/1319] eta: 0:03:02 lr: 1.048509515332035e-05 loss: 0.0289 (0.0347) time: 2.6512 data: 0.0064 max mem: 33369 +Epoch: [32] [1260/1319] eta: 0:02:35 lr: 1.0474948832358245e-05 loss: 0.0314 (0.0347) time: 2.6636 data: 0.0063 max mem: 33369 +Epoch: [32] [1270/1319] eta: 0:02:09 lr: 1.0464801419278068e-05 loss: 0.0335 (0.0347) time: 2.6383 data: 0.0063 max mem: 33369 +Epoch: [32] [1280/1319] eta: 0:01:43 lr: 1.0454652912785337e-05 loss: 0.0353 (0.0347) time: 2.6386 data: 0.0062 max mem: 33369 +Epoch: [32] [1290/1319] eta: 0:01:16 lr: 1.0444503311582662e-05 loss: 0.0324 (0.0347) time: 2.6824 data: 0.0062 max mem: 33369 +Epoch: [32] [1300/1319] eta: 0:00:50 lr: 1.0434352614369702e-05 loss: 0.0292 (0.0347) time: 2.6711 data: 0.0063 max mem: 33369 +Epoch: [32] [1310/1319] eta: 0:00:23 lr: 1.0424200819843158e-05 loss: 0.0297 (0.0347) time: 2.6309 data: 0.0063 max mem: 33369 +Epoch: [32] Total time: 0:58:05 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 2:00:57 time: 2.8205 data: 2.6608 max mem: 33369 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 100/2573] eta: 0:04:04 time: 0.0716 data: 0.0011 max mem: 33369 +Test: [ 200/2573] eta: 0:03:25 time: 0.0734 data: 0.0011 max mem: 33369 +Test: [ 300/2573] eta: 0:03:06 time: 0.0753 data: 0.0011 max mem: 33369 +Test: [ 400/2573] eta: 0:02:53 time: 0.0754 data: 0.0011 max mem: 33369 +Test: [ 500/2573] eta: 0:02:42 time: 0.0737 data: 0.0011 max mem: 33369 +Test: [ 600/2573] eta: 0:02:33 time: 0.0738 data: 0.0011 max mem: 33369 +Test: [ 700/2573] eta: 0:02:25 time: 0.0738 data: 0.0011 max mem: 33369 +Test: [ 800/2573] eta: 0:02:17 time: 0.0771 data: 0.0011 max mem: 33369 +Test: [ 900/2573] eta: 0:02:08 time: 0.0738 data: 0.0011 max mem: 33369 +Test: [1000/2573] eta: 0:02:00 time: 0.0739 data: 0.0011 max mem: 33369 +Test: [1100/2573] eta: 0:01:52 time: 0.0738 data: 0.0011 max mem: 33369 +Test: [1200/2573] eta: 0:01:44 time: 0.0737 data: 0.0011 max mem: 33369 +Test: [1300/2573] eta: 0:01:36 time: 0.0738 data: 0.0011 max mem: 33369 +Test: [1400/2573] eta: 0:01:29 time: 0.0721 data: 0.0011 max mem: 33369 +Test: [1500/2573] eta: 0:01:21 time: 0.0739 data: 0.0011 max mem: 33369 +Test: [1600/2573] eta: 0:01:13 time: 0.0772 data: 0.0011 max mem: 33369 +Test: [1700/2573] eta: 0:01:06 time: 0.0722 data: 0.0010 max mem: 33369 +Test: [1800/2573] eta: 0:00:58 time: 0.0754 data: 0.0011 max mem: 33369 +Test: [1900/2573] eta: 0:00:50 time: 0.0721 data: 0.0011 max mem: 33369 +Test: [2000/2573] eta: 0:00:43 time: 0.0739 data: 0.0011 max mem: 33369 +Test: [2100/2573] eta: 0:00:35 time: 0.0755 data: 0.0011 max mem: 33369 +Test: [2200/2573] eta: 0:00:27 time: 0.0755 data: 0.0011 max mem: 33369 +Test: [2300/2573] eta: 0:00:20 time: 0.0756 data: 0.0011 max mem: 33369 +Test: [2400/2573] eta: 0:00:12 time: 0.0705 data: 0.0011 max mem: 33369 +Test: [2500/2573] eta: 0:00:05 time: 0.0738 data: 0.0011 max mem: 33369 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: Total time: 0:03:13 +Final results: +Mean IoU is 64.76 + + precision@0.5 = 72.98 + precision@0.6 = 67.63 + precision@0.7 = 60.50 + precision@0.8 = 49.00 + precision@0.9 = 24.65 + overall IoU = 62.79 + +Average object IoU 64.76215184151638 +Overall IoU 62.789398193359375 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [33] [ 0/1319] eta: 3:03:45 lr: 1.04150632654866e-05 loss: 0.0274 (0.0274) time: 8.3590 data: 1.1657 max mem: 33369 +Epoch: [33] [ 10/1319] eta: 1:08:34 lr: 1.0404909382463066e-05 loss: 0.0274 (0.0274) time: 3.1430 data: 0.1116 max mem: 33369 +Epoch: [33] [ 20/1319] eta: 1:02:28 lr: 1.0394754398329612e-05 loss: 0.0291 (0.0330) time: 2.6117 data: 0.0060 max mem: 33369 +Epoch: [33] [ 30/1319] eta: 1:00:26 lr: 1.0384598311771345e-05 loss: 0.0297 (0.0322) time: 2.6321 data: 0.0062 max mem: 33369 +Epoch: [33] [ 40/1319] eta: 0:59:19 lr: 1.0374441121470351e-05 loss: 0.0296 (0.0326) time: 2.6755 data: 0.0066 max mem: 33369 +Epoch: [33] [ 50/1319] eta: 0:58:20 lr: 1.0364282826105723e-05 loss: 0.0342 (0.0341) time: 2.6744 data: 0.0066 max mem: 33369 +Epoch: [33] [ 60/1319] eta: 0:57:30 lr: 1.0354123424353528e-05 loss: 0.0341 (0.0345) time: 2.6528 data: 0.0065 max mem: 33369 +Epoch: [33] [ 70/1319] eta: 0:56:42 lr: 1.0343962914886797e-05 loss: 0.0347 (0.0355) time: 2.6350 data: 0.0064 max mem: 33369 +Epoch: [33] [ 80/1319] eta: 0:55:56 lr: 1.033380129637553e-05 loss: 0.0322 (0.0352) time: 2.6150 data: 0.0063 max mem: 33369 +Epoch: [33] [ 90/1319] eta: 0:55:17 lr: 1.0323638567486653e-05 loss: 0.0297 (0.0351) time: 2.6124 data: 0.0065 max mem: 33369 +Epoch: [33] [ 100/1319] eta: 0:54:42 lr: 1.0313474726884054e-05 loss: 0.0306 (0.0356) time: 2.6252 data: 0.0065 max mem: 33369 +Epoch: [33] [ 110/1319] eta: 0:54:12 lr: 1.0303309773228537e-05 loss: 0.0320 (0.0355) time: 2.6493 data: 0.0065 max mem: 33369 +Epoch: [33] [ 120/1319] eta: 0:53:43 lr: 1.0293143705177821e-05 loss: 0.0303 (0.0350) time: 2.6664 data: 0.0066 max mem: 33369 +Epoch: [33] [ 130/1319] eta: 0:53:12 lr: 1.0282976521386539e-05 loss: 0.0303 (0.0348) time: 2.6566 data: 0.0066 max mem: 33369 +Epoch: [33] [ 140/1319] eta: 0:52:41 lr: 1.0272808220506222e-05 loss: 0.0315 (0.0349) time: 2.6406 data: 0.0065 max mem: 33369 +Epoch: [33] [ 150/1319] eta: 0:52:08 lr: 1.026263880118526e-05 loss: 0.0330 (0.0351) time: 2.6172 data: 0.0064 max mem: 33369 +Epoch: [33] [ 160/1319] eta: 0:51:41 lr: 1.0252468262068951e-05 loss: 0.0307 (0.0350) time: 2.6352 data: 0.0065 max mem: 33369 +Epoch: [33] [ 170/1319] eta: 0:51:16 lr: 1.024229660179944e-05 loss: 0.0332 (0.0350) time: 2.6897 data: 0.0065 max mem: 33369 +Epoch: [33] [ 180/1319] eta: 0:50:46 lr: 1.023212381901573e-05 loss: 0.0300 (0.0347) time: 2.6636 data: 0.0064 max mem: 33369 +Epoch: [33] [ 190/1319] eta: 0:50:16 lr: 1.0221949912353669e-05 loss: 0.0302 (0.0349) time: 2.6222 data: 0.0065 max mem: 33369 +Epoch: [33] [ 200/1319] eta: 0:49:48 lr: 1.0211774880445919e-05 loss: 0.0327 (0.0350) time: 2.6401 data: 0.0065 max mem: 33369 +Epoch: [33] [ 210/1319] eta: 0:49:19 lr: 1.0201598721921983e-05 loss: 0.0309 (0.0350) time: 2.6389 data: 0.0065 max mem: 33369 +Epoch: [33] [ 220/1319] eta: 0:48:51 lr: 1.0191421435408169e-05 loss: 0.0325 (0.0353) time: 2.6262 data: 0.0066 max mem: 33369 +Epoch: [33] [ 230/1319] eta: 0:48:22 lr: 1.0181243019527578e-05 loss: 0.0284 (0.0350) time: 2.6259 data: 0.0065 max mem: 33369 +Epoch: [33] [ 240/1319] eta: 0:47:54 lr: 1.0171063472900106e-05 loss: 0.0281 (0.0351) time: 2.6277 data: 0.0065 max mem: 33369 +Epoch: [33] [ 250/1319] eta: 0:47:27 lr: 1.0160882794142423e-05 loss: 0.0328 (0.0352) time: 2.6441 data: 0.0065 max mem: 33369 +Epoch: [33] [ 260/1319] eta: 0:46:58 lr: 1.0150700981867957e-05 loss: 0.0283 (0.0350) time: 2.6324 data: 0.0064 max mem: 33369 +Epoch: [33] [ 270/1319] eta: 0:46:29 lr: 1.01405180346869e-05 loss: 0.0278 (0.0349) time: 2.6052 data: 0.0064 max mem: 33369 +Epoch: [33] [ 280/1319] eta: 0:46:02 lr: 1.0130333951206182e-05 loss: 0.0323 (0.0349) time: 2.6212 data: 0.0065 max mem: 33369 +Epoch: [33] [ 290/1319] eta: 0:45:36 lr: 1.0120148730029472e-05 loss: 0.0309 (0.0349) time: 2.6573 data: 0.0066 max mem: 33369 +Epoch: [33] [ 300/1319] eta: 0:45:07 lr: 1.0109962369757157e-05 loss: 0.0298 (0.0349) time: 2.6439 data: 0.0065 max mem: 33369 +Epoch: [33] [ 310/1319] eta: 0:44:40 lr: 1.0099774868986322e-05 loss: 0.0298 (0.0348) time: 2.6209 data: 0.0066 max mem: 33369 +Epoch: [33] [ 320/1319] eta: 0:44:13 lr: 1.008958622631076e-05 loss: 0.0310 (0.0347) time: 2.6395 data: 0.0068 max mem: 33369 +Epoch: [33] [ 330/1319] eta: 0:43:45 lr: 1.0079396440320953e-05 loss: 0.0333 (0.0351) time: 2.6294 data: 0.0065 max mem: 33369 +Epoch: [33] [ 340/1319] eta: 0:43:17 lr: 1.0069205509604051e-05 loss: 0.0353 (0.0353) time: 2.5985 data: 0.0063 max mem: 33369 +Epoch: [33] [ 350/1319] eta: 0:42:49 lr: 1.0059013432743876e-05 loss: 0.0348 (0.0354) time: 2.6072 data: 0.0066 max mem: 33369 +Epoch: [33] [ 360/1319] eta: 0:42:23 lr: 1.0048820208320883e-05 loss: 0.0318 (0.0353) time: 2.6354 data: 0.0066 max mem: 33369 +Epoch: [33] [ 370/1319] eta: 0:41:57 lr: 1.0038625834912186e-05 loss: 0.0306 (0.0352) time: 2.6599 data: 0.0063 max mem: 33369 +Epoch: [33] [ 380/1319] eta: 0:41:31 lr: 1.0028430311091521e-05 loss: 0.0315 (0.0352) time: 2.6693 data: 0.0064 max mem: 33369 +Epoch: [33] [ 390/1319] eta: 0:41:03 lr: 1.0018233635429235e-05 loss: 0.0302 (0.0351) time: 2.6302 data: 0.0063 max mem: 33369 +Epoch: [33] [ 400/1319] eta: 0:40:36 lr: 1.0008035806492287e-05 loss: 0.0280 (0.0351) time: 2.6262 data: 0.0062 max mem: 33369 +Epoch: [33] [ 410/1319] eta: 0:40:10 lr: 9.99783682284423e-06 loss: 0.0309 (0.0352) time: 2.6533 data: 0.0063 max mem: 33369 +Epoch: [33] [ 420/1319] eta: 0:39:43 lr: 9.987636683045179e-06 loss: 0.0309 (0.0350) time: 2.6423 data: 0.0064 max mem: 33369 +Epoch: [33] [ 430/1319] eta: 0:39:15 lr: 9.977435385651839e-06 loss: 0.0284 (0.0350) time: 2.6202 data: 0.0064 max mem: 33369 +Epoch: [33] [ 440/1319] eta: 0:38:49 lr: 9.967232929217462e-06 loss: 0.0277 (0.0350) time: 2.6184 data: 0.0065 max mem: 33369 +Epoch: [33] [ 450/1319] eta: 0:38:22 lr: 9.957029312291845e-06 loss: 0.0337 (0.0352) time: 2.6510 data: 0.0066 max mem: 33369 +Epoch: [33] [ 460/1319] eta: 0:37:56 lr: 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mem: 33369 +Epoch: [33] [ 700/1319] eta: 0:27:17 lr: 9.701557415421759e-06 loss: 0.0323 (0.0350) time: 2.6419 data: 0.0064 max mem: 33369 +Epoch: [33] [ 710/1319] eta: 0:26:51 lr: 9.69132310508487e-06 loss: 0.0339 (0.0349) time: 2.6670 data: 0.0065 max mem: 33369 +Epoch: [33] [ 720/1319] eta: 0:26:25 lr: 9.681087593749006e-06 loss: 0.0288 (0.0349) time: 2.6687 data: 0.0064 max mem: 33369 +Epoch: [33] [ 730/1319] eta: 0:25:58 lr: 9.670850879862032e-06 loss: 0.0288 (0.0349) time: 2.6515 data: 0.0064 max mem: 33369 +Epoch: [33] [ 740/1319] eta: 0:25:32 lr: 9.660612961867972e-06 loss: 0.0298 (0.0348) time: 2.6559 data: 0.0065 max mem: 33369 +Epoch: [33] [ 750/1319] eta: 0:25:05 lr: 9.650373838207014e-06 loss: 0.0299 (0.0348) time: 2.6448 data: 0.0065 max mem: 33369 +Epoch: [33] [ 760/1319] eta: 0:24:38 lr: 9.640133507315477e-06 loss: 0.0314 (0.0348) time: 2.6087 data: 0.0064 max mem: 33369 +Epoch: [33] [ 770/1319] eta: 0:24:12 lr: 9.62989196762581e-06 loss: 0.0322 (0.0348) time: 2.6364 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(0.0347) time: 2.6294 data: 0.0063 max mem: 33369 +Epoch: [33] [ 860/1319] eta: 0:20:14 lr: 9.537663453919165e-06 loss: 0.0338 (0.0347) time: 2.6397 data: 0.0065 max mem: 33369 +Epoch: [33] [ 870/1319] eta: 0:19:48 lr: 9.52740973916964e-06 loss: 0.0315 (0.0347) time: 2.6792 data: 0.0065 max mem: 33369 +Epoch: [33] [ 880/1319] eta: 0:19:22 lr: 9.517154798118936e-06 loss: 0.0291 (0.0346) time: 2.6659 data: 0.0063 max mem: 33369 +Epoch: [33] [ 890/1319] eta: 0:18:55 lr: 9.506898629151863e-06 loss: 0.0341 (0.0347) time: 2.6506 data: 0.0062 max mem: 33369 +Epoch: [33] [ 900/1319] eta: 0:18:29 lr: 9.496641230649144e-06 loss: 0.0343 (0.0346) time: 2.6712 data: 0.0062 max mem: 33369 +Epoch: [33] [ 910/1319] eta: 0:18:02 lr: 9.48638260098744e-06 loss: 0.0307 (0.0346) time: 2.6489 data: 0.0063 max mem: 33369 +Epoch: [33] [ 920/1319] eta: 0:17:36 lr: 9.476122738539313e-06 loss: 0.0301 (0.0345) time: 2.6312 data: 0.0063 max mem: 33369 +Epoch: [33] [ 930/1319] eta: 0:17:09 lr: 9.465861641673206e-06 loss: 0.0310 (0.0345) time: 2.6452 data: 0.0065 max mem: 33369 +Epoch: [33] [ 940/1319] eta: 0:16:43 lr: 9.455599308753445e-06 loss: 0.0306 (0.0345) time: 2.6323 data: 0.0065 max mem: 33369 +Epoch: [33] [ 950/1319] eta: 0:16:16 lr: 9.445335738140192e-06 loss: 0.0294 (0.0345) time: 2.6349 data: 0.0064 max mem: 33369 +Epoch: [33] [ 960/1319] eta: 0:15:50 lr: 9.435070928189476e-06 loss: 0.0306 (0.0345) time: 2.6487 data: 0.0064 max mem: 33369 +Epoch: [33] [ 970/1319] eta: 0:15:23 lr: 9.424804877253139e-06 loss: 0.0320 (0.0345) time: 2.6640 data: 0.0063 max mem: 33369 +Epoch: [33] [ 980/1319] eta: 0:14:57 lr: 9.414537583678836e-06 loss: 0.0337 (0.0345) time: 2.6409 data: 0.0063 max mem: 33369 +Epoch: [33] [ 990/1319] eta: 0:14:31 lr: 9.404269045810016e-06 loss: 0.0294 (0.0345) time: 2.6519 data: 0.0063 max mem: 33369 +Epoch: [33] [1000/1319] eta: 0:14:04 lr: 9.393999261985916e-06 loss: 0.0330 (0.0345) time: 2.6640 data: 0.0065 max mem: 33369 +Epoch: [33] [1010/1319] eta: 0:13:38 lr: 9.383728230541512e-06 loss: 0.0301 (0.0345) time: 2.6500 data: 0.0066 max mem: 33369 +Epoch: [33] [1020/1319] eta: 0:13:11 lr: 9.373455949807552e-06 loss: 0.0313 (0.0345) time: 2.6630 data: 0.0064 max mem: 33369 +Epoch: [33] [1030/1319] eta: 0:12:45 lr: 9.363182418110507e-06 loss: 0.0295 (0.0344) time: 2.6405 data: 0.0063 max mem: 33369 +Epoch: [33] [1040/1319] eta: 0:12:18 lr: 9.352907633772557e-06 loss: 0.0332 (0.0345) time: 2.6264 data: 0.0063 max mem: 33369 +Epoch: [33] [1050/1319] eta: 0:11:52 lr: 9.342631595111597e-06 loss: 0.0347 (0.0344) time: 2.6290 data: 0.0063 max mem: 33369 +Epoch: [33] [1060/1319] eta: 0:11:25 lr: 9.332354300441178e-06 loss: 0.0303 (0.0344) time: 2.5969 data: 0.0064 max mem: 33369 +Epoch: [33] [1070/1319] eta: 0:10:58 lr: 9.322075748070539e-06 loss: 0.0302 (0.0344) time: 2.5864 data: 0.0065 max mem: 33369 +Epoch: [33] [1080/1319] eta: 0:10:32 lr: 9.311795936304561e-06 loss: 0.0308 (0.0344) time: 2.6216 data: 0.0065 max mem: 33369 +Epoch: [33] [1090/1319] eta: 0:10:05 lr: 9.301514863443759e-06 loss: 0.0333 (0.0344) time: 2.6335 data: 0.0064 max mem: 33369 +Epoch: [33] [1100/1319] eta: 0:09:39 lr: 9.291232527784269e-06 loss: 0.0351 (0.0344) time: 2.6558 data: 0.0063 max mem: 33369 +Epoch: [33] [1110/1319] eta: 0:09:12 lr: 9.280948927617811e-06 loss: 0.0361 (0.0344) time: 2.6317 data: 0.0063 max mem: 33369 +Epoch: [33] [1120/1319] eta: 0:08:46 lr: 9.270664061231702e-06 loss: 0.0293 (0.0344) time: 2.6223 data: 0.0063 max mem: 33369 +Epoch: [33] [1130/1319] eta: 0:08:20 lr: 9.260377926908826e-06 loss: 0.0296 (0.0344) time: 2.6652 data: 0.0064 max mem: 33369 +Epoch: [33] [1140/1319] eta: 0:07:53 lr: 9.250090522927605e-06 loss: 0.0331 (0.0344) time: 2.6518 data: 0.0064 max mem: 33369 +Epoch: [33] [1150/1319] eta: 0:07:27 lr: 9.239801847562006e-06 loss: 0.0349 (0.0344) time: 2.6441 data: 0.0063 max mem: 33369 +Epoch: [33] [1160/1319] eta: 0:07:00 lr: 9.229511899081506e-06 loss: 0.0315 (0.0344) time: 2.6438 data: 0.0063 max mem: 33369 +Epoch: [33] [1170/1319] eta: 0:06:34 lr: 9.219220675751069e-06 loss: 0.0265 (0.0343) time: 2.6488 data: 0.0064 max mem: 33369 +Epoch: [33] [1180/1319] eta: 0:06:07 lr: 9.20892817583115e-06 loss: 0.0286 (0.0343) time: 2.6680 data: 0.0063 max mem: 33369 +Epoch: [33] [1190/1319] eta: 0:05:41 lr: 9.19863439757767e-06 loss: 0.0303 (0.0343) time: 2.6390 data: 0.0064 max mem: 33369 +Epoch: [33] [1200/1319] eta: 0:05:14 lr: 9.188339339241987e-06 loss: 0.0333 (0.0343) time: 2.6417 data: 0.0064 max mem: 33369 +Epoch: [33] [1210/1319] eta: 0:04:48 lr: 9.178042999070898e-06 loss: 0.0324 (0.0343) time: 2.6764 data: 0.0064 max mem: 33369 +Epoch: [33] [1220/1319] eta: 0:04:21 lr: 9.16774537530659e-06 loss: 0.0332 (0.0343) time: 2.6471 data: 0.0065 max mem: 33369 +Epoch: [33] [1230/1319] eta: 0:03:55 lr: 9.157446466186662e-06 loss: 0.0342 (0.0344) time: 2.6268 data: 0.0063 max mem: 33369 +Epoch: [33] [1240/1319] eta: 0:03:29 lr: 9.147146269944078e-06 loss: 0.0318 (0.0343) time: 2.6443 data: 0.0064 max mem: 33369 +Epoch: [33] [1250/1319] eta: 0:03:02 lr: 9.136844784807162e-06 loss: 0.0283 (0.0343) time: 2.6360 data: 0.0065 max mem: 33369 +Epoch: [33] [1260/1319] eta: 0:02:36 lr: 9.126542008999582e-06 loss: 0.0327 (0.0343) time: 2.6353 data: 0.0063 max mem: 33369 +Epoch: [33] [1270/1319] eta: 0:02:09 lr: 9.11623794074031e-06 loss: 0.0327 (0.0343) time: 2.6600 data: 0.0061 max mem: 33369 +Epoch: [33] [1280/1319] eta: 0:01:43 lr: 9.105932578243631e-06 loss: 0.0292 (0.0343) time: 2.6629 data: 0.0062 max mem: 33369 +Epoch: [33] [1290/1319] eta: 0:01:16 lr: 9.095625919719118e-06 loss: 0.0318 (0.0343) time: 2.6578 data: 0.0062 max mem: 33369 +Epoch: [33] [1300/1319] eta: 0:00:50 lr: 9.085317963371604e-06 loss: 0.0356 (0.0343) time: 2.6611 data: 0.0061 max mem: 33369 +Epoch: [33] [1310/1319] eta: 0:00:23 lr: 9.075008707401167e-06 loss: 0.0299 (0.0343) time: 2.6584 data: 0.0062 max mem: 33369 +Epoch: [33] Total time: 0:58:10 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 2:10:47 time: 3.0498 data: 2.9700 max mem: 33369 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 100/2573] eta: 0:04:10 time: 0.0715 data: 0.0011 max mem: 33369 +Test: [ 200/2573] eta: 0:03:28 time: 0.0734 data: 0.0011 max mem: 33369 +Test: [ 300/2573] eta: 0:03:07 time: 0.0752 data: 0.0011 max mem: 33369 +Test: [ 400/2573] eta: 0:02:54 time: 0.0752 data: 0.0011 max mem: 33369 +Test: [ 500/2573] eta: 0:02:43 time: 0.0737 data: 0.0011 max mem: 33369 +Test: [ 600/2573] eta: 0:02:34 time: 0.0737 data: 0.0011 max mem: 33369 +Test: [ 700/2573] eta: 0:02:25 time: 0.0738 data: 0.0011 max mem: 33369 +Test: [ 800/2573] eta: 0:02:17 time: 0.0771 data: 0.0011 max mem: 33369 +Test: [ 900/2573] eta: 0:02:09 time: 0.0739 data: 0.0011 max mem: 33369 +Test: [1000/2573] eta: 0:02:00 time: 0.0738 data: 0.0011 max mem: 33369 +Test: [1100/2573] eta: 0:01:52 time: 0.0739 data: 0.0011 max mem: 33369 +Test: [1200/2573] eta: 0:01:44 time: 0.0739 data: 0.0011 max mem: 33369 +Test: [1300/2573] eta: 0:01:37 time: 0.0739 data: 0.0011 max mem: 33369 +Test: [1400/2573] eta: 0:01:29 time: 0.0722 data: 0.0011 max mem: 33369 +Test: [1500/2573] eta: 0:01:21 time: 0.0738 data: 0.0011 max mem: 33369 +Test: [1600/2573] eta: 0:01:13 time: 0.0771 data: 0.0011 max mem: 33369 +Test: [1700/2573] eta: 0:01:06 time: 0.0721 data: 0.0010 max mem: 33369 +Test: [1800/2573] eta: 0:00:58 time: 0.0756 data: 0.0011 max mem: 33369 +Test: [1900/2573] eta: 0:00:50 time: 0.0722 data: 0.0011 max mem: 33369 +Test: [2000/2573] eta: 0:00:43 time: 0.0739 data: 0.0011 max mem: 33369 +Test: [2100/2573] eta: 0:00:35 time: 0.0755 data: 0.0011 max mem: 33369 +Test: [2200/2573] eta: 0:00:28 time: 0.0755 data: 0.0011 max mem: 33369 +Test: [2300/2573] eta: 0:00:20 time: 0.0755 data: 0.0011 max mem: 33369 +Test: [2400/2573] eta: 0:00:12 time: 0.0705 data: 0.0011 max mem: 33369 +Test: [2500/2573] eta: 0:00:05 time: 0.0739 data: 0.0011 max mem: 33369 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: Total time: 0:03:13 +Final results: +Mean IoU is 64.62 + + precision@0.5 = 72.79 + precision@0.6 = 67.36 + precision@0.7 = 60.74 + precision@0.8 = 49.16 + precision@0.9 = 24.86 + overall IoU = 62.73 + +Average object IoU 64.61874665004854 +Overall IoU 62.72834396362305 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [34] [ 0/1319] eta: 3:19:55 lr: 9.065729264358701e-06 loss: 0.0280 (0.0280) time: 9.0943 data: 1.2421 max mem: 33369 +Epoch: [34] [ 10/1319] eta: 1:10:43 lr: 9.05541753412883e-06 loss: 0.0280 (0.0295) time: 3.2421 data: 0.1184 max mem: 33369 +Epoch: [34] [ 20/1319] eta: 1:03:32 lr: 9.045104499029229e-06 loss: 0.0335 (0.0327) time: 2.6272 data: 0.0059 max mem: 33369 +Epoch: [34] [ 30/1319] eta: 1:01:16 lr: 9.03479015724125e-06 loss: 0.0311 (0.0313) time: 2.6383 data: 0.0061 max mem: 33369 +Epoch: [34] [ 40/1319] eta: 0:59:34 lr: 9.024474506941415e-06 loss: 0.0277 (0.0313) time: 2.6474 data: 0.0065 max mem: 33369 +Epoch: [34] [ 50/1319] eta: 0:58:23 lr: 9.014157546301385e-06 loss: 0.0281 (0.0313) time: 2.6182 data: 0.0069 max mem: 33369 +Epoch: [34] [ 60/1319] eta: 0:57:34 lr: 9.003839273487931e-06 loss: 0.0323 (0.0327) time: 2.6400 data: 0.0068 max mem: 33369 +Epoch: [34] [ 70/1319] eta: 0:56:57 lr: 8.99351968666293e-06 loss: 0.0320 (0.0322) time: 2.6731 data: 0.0065 max mem: 33369 +Epoch: [34] [ 80/1319] eta: 0:56:15 lr: 8.983198783983315e-06 loss: 0.0316 (0.0322) time: 2.6639 data: 0.0064 max mem: 33369 +Epoch: [34] [ 90/1319] eta: 0:55:37 lr: 8.972876563601101e-06 loss: 0.0314 (0.0319) time: 2.6433 data: 0.0063 max mem: 33369 +Epoch: [34] [ 100/1319] eta: 0:55:00 lr: 8.962553023663333e-06 loss: 0.0314 (0.0325) time: 2.6408 data: 0.0063 max mem: 33369 +Epoch: [34] [ 110/1319] eta: 0:54:30 lr: 8.952228162312077e-06 loss: 0.0282 (0.0321) time: 2.6589 data: 0.0063 max mem: 33369 +Epoch: [34] [ 120/1319] eta: 0:53:58 lr: 8.941901977684397e-06 loss: 0.0308 (0.0324) time: 2.6696 data: 0.0063 max mem: 33369 +Epoch: [34] [ 130/1319] eta: 0:53:26 lr: 8.93157446791234e-06 loss: 0.0327 (0.0323) time: 2.6509 data: 0.0064 max mem: 33369 +Epoch: [34] [ 140/1319] eta: 0:52:56 lr: 8.9212456311229e-06 loss: 0.0320 (0.0323) time: 2.6504 data: 0.0064 max mem: 33369 +Epoch: [34] [ 150/1319] eta: 0:52:26 lr: 8.910915465438025e-06 loss: 0.0330 (0.0326) time: 2.6573 data: 0.0064 max mem: 33369 +Epoch: [34] [ 160/1319] eta: 0:51:58 lr: 8.900583968974578e-06 loss: 0.0306 (0.0323) time: 2.6630 data: 0.0063 max mem: 33369 +Epoch: [34] [ 170/1319] eta: 0:51:27 lr: 8.89025113984432e-06 loss: 0.0298 (0.0323) time: 2.6522 data: 0.0065 max mem: 33369 +Epoch: [34] [ 180/1319] eta: 0:50:57 lr: 8.879916976153894e-06 loss: 0.0307 (0.0321) time: 2.6362 data: 0.0065 max mem: 33369 +Epoch: [34] [ 190/1319] eta: 0:50:29 lr: 8.869581476004788e-06 loss: 0.0311 (0.0322) time: 2.6476 data: 0.0063 max mem: 33369 +Epoch: [34] [ 200/1319] eta: 0:49:59 lr: 8.859244637493344e-06 loss: 0.0311 (0.0322) time: 2.6466 data: 0.0064 max mem: 33369 +Epoch: [34] [ 210/1319] eta: 0:49:31 lr: 8.84890645871071e-06 loss: 0.0323 (0.0323) time: 2.6444 data: 0.0064 max mem: 33369 +Epoch: [34] [ 220/1319] eta: 0:49:02 lr: 8.838566937742836e-06 loss: 0.0346 (0.0324) time: 2.6504 data: 0.0065 max mem: 33369 +Epoch: [34] [ 230/1319] eta: 0:48:32 lr: 8.828226072670449e-06 loss: 0.0326 (0.0326) time: 2.6270 data: 0.0064 max mem: 33369 +Epoch: [34] [ 240/1319] eta: 0:48:04 lr: 8.817883861569014e-06 loss: 0.0321 (0.0327) time: 2.6277 data: 0.0065 max mem: 33369 +Epoch: [34] [ 250/1319] eta: 0:47:38 lr: 8.807540302508743e-06 loss: 0.0321 (0.0328) time: 2.6669 data: 0.0065 max mem: 33369 +Epoch: [34] [ 260/1319] eta: 0:47:10 lr: 8.797195393554557e-06 loss: 0.0313 (0.0328) time: 2.6581 data: 0.0065 max mem: 33369 +Epoch: [34] [ 270/1319] eta: 0:46:42 lr: 8.786849132766063e-06 loss: 0.0267 (0.0326) time: 2.6452 data: 0.0063 max mem: 33369 +Epoch: [34] [ 280/1319] eta: 0:46:14 lr: 8.776501518197541e-06 loss: 0.0284 (0.0326) time: 2.6376 data: 0.0065 max mem: 33369 +Epoch: [34] [ 290/1319] eta: 0:45:45 lr: 8.76615254789792e-06 loss: 0.0308 (0.0326) time: 2.6166 data: 0.0065 max mem: 33369 +Epoch: [34] [ 300/1319] eta: 0:45:17 lr: 8.755802219910735e-06 loss: 0.0337 (0.0328) time: 2.6199 data: 0.0063 max mem: 33369 +Epoch: [34] [ 310/1319] eta: 0:44:49 lr: 8.745450532274145e-06 loss: 0.0331 (0.0328) time: 2.6264 data: 0.0063 max mem: 33369 +Epoch: [34] [ 320/1319] eta: 0:44:21 lr: 8.735097483020883e-06 loss: 0.0334 (0.0329) time: 2.6205 data: 0.0065 max mem: 33369 +Epoch: [34] [ 330/1319] eta: 0:43:53 lr: 8.724743070178239e-06 loss: 0.0384 (0.0330) time: 2.6255 data: 0.0064 max mem: 33369 +Epoch: [34] [ 340/1319] eta: 0:43:26 lr: 8.714387291768046e-06 loss: 0.0341 (0.0330) time: 2.6419 data: 0.0063 max mem: 33369 +Epoch: [34] [ 350/1319] eta: 0:42:58 lr: 8.704030145806636e-06 loss: 0.0297 (0.0329) time: 2.6329 data: 0.0064 max mem: 33369 +Epoch: [34] [ 360/1319] eta: 0:42:32 lr: 8.693671630304845e-06 loss: 0.0327 (0.0332) time: 2.6468 data: 0.0065 max mem: 33369 +Epoch: [34] [ 370/1319] eta: 0:42:05 lr: 8.683311743267978e-06 loss: 0.0328 (0.0332) time: 2.6546 data: 0.0065 max mem: 33369 +Epoch: [34] [ 380/1319] eta: 0:41:38 lr: 8.672950482695785e-06 loss: 0.0286 (0.0331) time: 2.6464 data: 0.0066 max mem: 33369 +Epoch: [34] [ 390/1319] eta: 0:41:11 lr: 8.662587846582436e-06 loss: 0.0307 (0.0331) time: 2.6489 data: 0.0066 max mem: 33369 +Epoch: [34] [ 400/1319] eta: 0:40:44 lr: 8.65222383291651e-06 loss: 0.0318 (0.0331) time: 2.6387 data: 0.0065 max mem: 33369 +Epoch: [34] [ 410/1319] eta: 0:40:16 lr: 8.641858439680947e-06 loss: 0.0308 (0.0331) time: 2.6159 data: 0.0066 max mem: 33369 +Epoch: [34] [ 420/1319] eta: 0:39:49 lr: 8.631491664853054e-06 loss: 0.0310 (0.0332) time: 2.6239 data: 0.0067 max mem: 33369 +Epoch: [34] [ 430/1319] eta: 0:39:22 lr: 8.621123506404469e-06 loss: 0.0340 (0.0331) time: 2.6398 data: 0.0066 max mem: 33369 +Epoch: [34] [ 440/1319] eta: 0:38:55 lr: 8.610753962301133e-06 loss: 0.0305 (0.0331) time: 2.6255 data: 0.0065 max mem: 33369 +Epoch: [34] [ 450/1319] eta: 0:38:28 lr: 8.600383030503278e-06 loss: 0.0323 (0.0332) time: 2.6330 data: 0.0063 max mem: 33369 +Epoch: [34] [ 460/1319] eta: 0:38:00 lr: 8.590010708965377e-06 loss: 0.0368 (0.0333) time: 2.6221 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0:27:19 lr: 8.340652648571916e-06 loss: 0.0338 (0.0336) time: 2.6546 data: 0.0062 max mem: 33369 +Epoch: [34] [ 710/1319] eta: 0:26:53 lr: 8.330244901449094e-06 loss: 0.0338 (0.0337) time: 2.6424 data: 0.0064 max mem: 33369 +Epoch: [34] [ 720/1319] eta: 0:26:26 lr: 8.319835709307101e-06 loss: 0.0326 (0.0337) time: 2.6269 data: 0.0065 max mem: 33369 +Epoch: [34] [ 730/1319] eta: 0:25:59 lr: 8.309425069935955e-06 loss: 0.0336 (0.0337) time: 2.6288 data: 0.0065 max mem: 33369 +Epoch: [34] [ 740/1319] eta: 0:25:33 lr: 8.299012981119228e-06 loss: 0.0314 (0.0336) time: 2.6611 data: 0.0064 max mem: 33369 +Epoch: [34] [ 750/1319] eta: 0:25:06 lr: 8.288599440633996e-06 loss: 0.0268 (0.0336) time: 2.6499 data: 0.0064 max mem: 33369 +Epoch: [34] [ 760/1319] eta: 0:24:40 lr: 8.278184446250822e-06 loss: 0.0334 (0.0336) time: 2.6234 data: 0.0064 max mem: 33369 +Epoch: [34] [ 770/1319] eta: 0:24:13 lr: 8.267767995733725e-06 loss: 0.0338 (0.0337) time: 2.6395 data: 0.0065 max mem: 33369 +Epoch: [34] [ 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+Epoch: [34] [ 860/1319] eta: 0:20:15 lr: 8.173954042838362e-06 loss: 0.0269 (0.0335) time: 2.6568 data: 0.0064 max mem: 33369 +Epoch: [34] [ 870/1319] eta: 0:19:48 lr: 8.163522906542168e-06 loss: 0.0287 (0.0335) time: 2.6536 data: 0.0064 max mem: 33369 +Epoch: [34] [ 880/1319] eta: 0:19:22 lr: 8.153090289075947e-06 loss: 0.0325 (0.0336) time: 2.6698 data: 0.0065 max mem: 33369 +Epoch: [34] [ 890/1319] eta: 0:18:55 lr: 8.142656188122887e-06 loss: 0.0345 (0.0336) time: 2.6671 data: 0.0064 max mem: 33369 +Epoch: [34] [ 900/1319] eta: 0:18:29 lr: 8.132220601359272e-06 loss: 0.0297 (0.0336) time: 2.6413 data: 0.0063 max mem: 33369 +Epoch: [34] [ 910/1319] eta: 0:18:02 lr: 8.121783526454415e-06 loss: 0.0287 (0.0335) time: 2.6353 data: 0.0063 max mem: 33369 +Epoch: [34] [ 920/1319] eta: 0:17:36 lr: 8.111344961070641e-06 loss: 0.0306 (0.0335) time: 2.6336 data: 0.0065 max mem: 33369 +Epoch: [34] [ 930/1319] eta: 0:17:09 lr: 8.100904902863262e-06 loss: 0.0311 (0.0335) time: 2.6305 data: 0.0065 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2.6448 data: 0.0064 max mem: 33369 +Epoch: [34] [1020/1319] eta: 0:13:11 lr: 8.006876811544029e-06 loss: 0.0256 (0.0334) time: 2.6714 data: 0.0062 max mem: 33369 +Epoch: [34] [1030/1319] eta: 0:12:45 lr: 7.996421694575264e-06 loss: 0.0261 (0.0333) time: 2.6786 data: 0.0063 max mem: 33369 +Epoch: [34] [1040/1319] eta: 0:12:18 lr: 7.985965058518847e-06 loss: 0.0307 (0.0334) time: 2.6411 data: 0.0064 max mem: 33369 +Epoch: [34] [1050/1319] eta: 0:11:52 lr: 7.97550690094334e-06 loss: 0.0341 (0.0334) time: 2.6258 data: 0.0064 max mem: 33369 +Epoch: [34] [1060/1319] eta: 0:11:25 lr: 7.965047219409881e-06 loss: 0.0336 (0.0335) time: 2.6485 data: 0.0063 max mem: 33369 +Epoch: [34] [1070/1319] eta: 0:10:59 lr: 7.95458601147213e-06 loss: 0.0336 (0.0335) time: 2.6810 data: 0.0064 max mem: 33369 +Epoch: [34] [1080/1319] eta: 0:10:32 lr: 7.944123274676236e-06 loss: 0.0301 (0.0335) time: 2.6989 data: 0.0063 max mem: 33369 +Epoch: [34] [1090/1319] eta: 0:10:06 lr: 7.933659006560817e-06 loss: 0.0325 (0.0335) time: 2.6815 data: 0.0062 max mem: 33369 +Epoch: [34] [1100/1319] eta: 0:09:40 lr: 7.923193204656895e-06 loss: 0.0299 (0.0335) time: 2.6647 data: 0.0064 max mem: 33369 +Epoch: [34] [1110/1319] eta: 0:09:13 lr: 7.912725866487896e-06 loss: 0.0269 (0.0334) time: 2.6484 data: 0.0065 max mem: 33369 +Epoch: [34] [1120/1319] eta: 0:08:47 lr: 7.902256989569599e-06 loss: 0.0291 (0.0334) time: 2.6519 data: 0.0064 max mem: 33369 +Epoch: [34] [1130/1319] eta: 0:08:20 lr: 7.891786571410098e-06 loss: 0.0342 (0.0335) time: 2.6694 data: 0.0062 max mem: 33369 +Epoch: [34] [1140/1319] eta: 0:07:54 lr: 7.881314609509776e-06 loss: 0.0327 (0.0334) time: 2.6401 data: 0.0063 max mem: 33369 +Epoch: [34] [1150/1319] eta: 0:07:27 lr: 7.870841101361268e-06 loss: 0.0279 (0.0334) time: 2.6286 data: 0.0065 max mem: 33369 +Epoch: [34] [1160/1319] eta: 0:07:01 lr: 7.860366044449406e-06 loss: 0.0290 (0.0334) time: 2.6400 data: 0.0064 max mem: 33369 +Epoch: [34] [1170/1319] eta: 0:06:34 lr: 7.849889436251218e-06 loss: 0.0280 (0.0334) time: 2.6395 data: 0.0064 max mem: 33369 +Epoch: [34] [1180/1319] eta: 0:06:08 lr: 7.839411274235871e-06 loss: 0.0285 (0.0334) time: 2.6545 data: 0.0064 max mem: 33369 +Epoch: [34] [1190/1319] eta: 0:05:41 lr: 7.82893155586463e-06 loss: 0.0345 (0.0334) time: 2.6745 data: 0.0063 max mem: 33369 +Epoch: [34] [1200/1319] eta: 0:05:15 lr: 7.818450278590844e-06 loss: 0.0345 (0.0334) time: 2.6423 data: 0.0063 max mem: 33369 +Epoch: [34] [1210/1319] eta: 0:04:48 lr: 7.80796743985987e-06 loss: 0.0298 (0.0334) time: 2.6653 data: 0.0062 max mem: 33369 +Epoch: [34] [1220/1319] eta: 0:04:22 lr: 7.797483037109084e-06 loss: 0.0299 (0.0334) time: 2.6658 data: 0.0063 max mem: 33369 +Epoch: [34] [1230/1319] eta: 0:03:55 lr: 7.786997067767811e-06 loss: 0.0311 (0.0333) time: 2.6369 data: 0.0063 max mem: 33369 +Epoch: [34] [1240/1319] eta: 0:03:29 lr: 7.776509529257303e-06 loss: 0.0318 (0.0334) time: 2.6572 data: 0.0061 max mem: 33369 +Epoch: [34] [1250/1319] eta: 0:03:02 lr: 7.766020418990693e-06 loss: 0.0342 (0.0334) time: 2.6247 data: 0.0062 max mem: 33369 +Epoch: [34] [1260/1319] eta: 0:02:36 lr: 7.755529734372952e-06 loss: 0.0317 (0.0334) time: 2.6228 data: 0.0064 max mem: 33369 +Epoch: [34] [1270/1319] eta: 0:02:09 lr: 7.74503747280087e-06 loss: 0.0288 (0.0334) time: 2.6433 data: 0.0063 max mem: 33369 +Epoch: [34] [1280/1319] eta: 0:01:43 lr: 7.734543631663006e-06 loss: 0.0290 (0.0334) time: 2.6564 data: 0.0061 max mem: 33369 +Epoch: [34] [1290/1319] eta: 0:01:16 lr: 7.724048208339646e-06 loss: 0.0327 (0.0334) time: 2.6635 data: 0.0062 max mem: 33369 +Epoch: [34] [1300/1319] eta: 0:00:50 lr: 7.713551200202774e-06 loss: 0.0325 (0.0334) time: 2.6464 data: 0.0064 max mem: 33369 +Epoch: [34] [1310/1319] eta: 0:00:23 lr: 7.703052604616029e-06 loss: 0.0311 (0.0334) time: 2.6507 data: 0.0063 max mem: 33369 +Epoch: [34] Total time: 0:58:14 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 2:02:53 time: 2.8657 data: 2.7871 max mem: 33369 +Test: [ 100/2573] eta: 0:04:05 time: 0.0715 data: 0.0011 max mem: 33369 +Test: [ 200/2573] eta: 0:03:26 time: 0.0733 data: 0.0011 max mem: 33369 +Test: [ 300/2573] eta: 0:03:06 time: 0.0752 data: 0.0011 max mem: 33369 +Test: [ 400/2573] eta: 0:02:53 time: 0.0753 data: 0.0011 max mem: 33369 +Test: [ 500/2573] eta: 0:02:42 time: 0.0737 data: 0.0011 max mem: 33369 +Test: [ 600/2573] eta: 0:02:33 time: 0.0736 data: 0.0011 max mem: 33369 +Test: [ 700/2573] eta: 0:02:25 time: 0.0736 data: 0.0011 max mem: 33369 +Test: [ 800/2573] eta: 0:02:16 time: 0.0770 data: 0.0011 max mem: 33369 +Test: [ 900/2573] eta: 0:02:08 time: 0.0738 data: 0.0011 max mem: 33369 +Test: [1000/2573] eta: 0:02:00 time: 0.0738 data: 0.0012 max mem: 33369 +Test: [1100/2573] eta: 0:01:52 time: 0.0740 data: 0.0011 max mem: 33369 +Test: [1200/2573] eta: 0:01:44 time: 0.0739 data: 0.0011 max mem: 33369 +Test: [1300/2573] eta: 0:01:36 time: 0.0738 data: 0.0011 max mem: 33369 +Test: [1400/2573] eta: 0:01:29 time: 0.0723 data: 0.0011 max mem: 33369 +Test: [1500/2573] eta: 0:01:21 time: 0.0739 data: 0.0011 max mem: 33369 +Test: [1600/2573] eta: 0:01:13 time: 0.0772 data: 0.0011 max mem: 33369 +Test: [1700/2573] eta: 0:01:06 time: 0.0721 data: 0.0011 max mem: 33369 +Test: [1800/2573] eta: 0:00:58 time: 0.0756 data: 0.0011 max mem: 33369 +Test: [1900/2573] eta: 0:00:50 time: 0.0722 data: 0.0011 max mem: 33369 +Test: [2000/2573] eta: 0:00:43 time: 0.0739 data: 0.0011 max mem: 33369 +Test: [2100/2573] eta: 0:00:35 time: 0.0755 data: 0.0011 max mem: 33369 +Test: [2200/2573] eta: 0:00:27 time: 0.0756 data: 0.0011 max mem: 33369 +Test: [2300/2573] eta: 0:00:20 time: 0.0755 data: 0.0011 max mem: 33369 +Test: [2400/2573] eta: 0:00:12 time: 0.0706 data: 0.0011 max mem: 33369 +Test: [2500/2573] eta: 0:00:05 time: 0.0738 data: 0.0011 max mem: 33369 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: Total time: 0:03:13 +Final results: +Mean IoU is 64.67 + + precision@0.5 = 73.06 + precision@0.6 = 67.54 + precision@0.7 = 60.07 + precision@0.8 = 49.31 + precision@0.9 = 25.41 + overall IoU = 62.65 + +Average object IoU 64.66501689748702 +Overall IoU 62.64584732055664 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [35] [ 0/1319] eta: 3:13:13 lr: 7.693602509132593e-06 loss: 0.0398 (0.0398) time: 8.7893 data: 1.3133 max mem: 33369 +Epoch: [35] [ 10/1319] eta: 1:10:24 lr: 7.683100890097833e-06 loss: 0.0331 (0.0326) time: 3.2274 data: 0.1259 max mem: 33369 +Epoch: [35] [ 20/1319] eta: 1:04:01 lr: 7.67259767592017e-06 loss: 0.0328 (0.0325) time: 2.6654 data: 0.0068 max mem: 33369 +Epoch: [35] [ 30/1319] eta: 1:01:04 lr: 7.66209286393032e-06 loss: 0.0334 (0.0332) time: 2.6308 data: 0.0067 max mem: 33369 +Epoch: [35] [ 40/1319] eta: 0:59:21 lr: 7.651586451450453e-06 loss: 0.0343 (0.0354) time: 2.6036 data: 0.0069 max mem: 33369 +Epoch: [35] [ 50/1319] eta: 0:58:13 lr: 7.641078435794154e-06 loss: 0.0340 (0.0350) time: 2.6146 data: 0.0067 max mem: 33369 +Epoch: [35] [ 60/1319] eta: 0:57:34 lr: 7.630568814266394e-06 loss: 0.0315 (0.0345) time: 2.6600 data: 0.0065 max mem: 33369 +Epoch: [35] [ 70/1319] eta: 0:56:45 lr: 7.62005758416347e-06 loss: 0.0299 (0.0349) time: 2.6598 data: 0.0066 max mem: 33369 +Epoch: [35] [ 80/1319] eta: 0:56:04 lr: 7.609544742772985e-06 loss: 0.0285 (0.0347) time: 2.6277 data: 0.0066 max mem: 33369 +Epoch: [35] [ 90/1319] eta: 0:55:21 lr: 7.599030287373793e-06 loss: 0.0330 (0.0351) time: 2.6164 data: 0.0065 max mem: 33369 +Epoch: [35] [ 100/1319] eta: 0:54:42 lr: 7.588514215235963e-06 loss: 0.0360 (0.0349) time: 2.6032 data: 0.0065 max mem: 33369 +Epoch: [35] [ 110/1319] eta: 0:54:11 lr: 7.5779965236207366e-06 loss: 0.0272 (0.0345) time: 2.6297 data: 0.0065 max mem: 33369 +Epoch: [35] [ 120/1319] eta: 0:53:39 lr: 7.5674772097804864e-06 loss: 0.0321 (0.0347) time: 2.6472 data: 0.0068 max mem: 33369 +Epoch: [35] [ 130/1319] eta: 0:53:05 lr: 7.556956270958658e-06 loss: 0.0315 (0.0342) time: 2.6229 data: 0.0068 max mem: 33369 +Epoch: [35] [ 140/1319] eta: 0:52:36 lr: 7.546433704389756e-06 loss: 0.0265 (0.0338) time: 2.6266 data: 0.0067 max mem: 33369 +Epoch: [35] [ 150/1319] eta: 0:52:07 lr: 7.535909507299282e-06 loss: 0.0288 (0.0334) time: 2.6510 data: 0.0067 max mem: 33369 +Epoch: [35] [ 160/1319] eta: 0:51:38 lr: 7.525383676903694e-06 loss: 0.0275 (0.0332) time: 2.6462 data: 0.0065 max mem: 33369 +Epoch: [35] [ 170/1319] eta: 0:51:07 lr: 7.514856210410369e-06 loss: 0.0308 (0.0333) time: 2.6257 data: 0.0066 max mem: 33369 +Epoch: [35] [ 180/1319] eta: 0:50:40 lr: 7.504327105017539e-06 loss: 0.0308 (0.0331) time: 2.6395 data: 0.0066 max mem: 33369 +Epoch: [35] [ 190/1319] eta: 0:50:10 lr: 7.493796357914276e-06 loss: 0.0282 (0.0328) time: 2.6435 data: 0.0065 max mem: 33369 +Epoch: [35] [ 200/1319] eta: 0:49:44 lr: 7.483263966280434e-06 loss: 0.0279 (0.0326) time: 2.6472 data: 0.0064 max mem: 33369 +Epoch: [35] [ 210/1319] eta: 0:49:15 lr: 7.4727299272865964e-06 loss: 0.0330 (0.0331) time: 2.6500 data: 0.0063 max mem: 33369 +Epoch: [35] [ 220/1319] eta: 0:48:47 lr: 7.462194238094052e-06 loss: 0.0333 (0.0331) time: 2.6237 data: 0.0064 max mem: 33369 +Epoch: [35] [ 230/1319] eta: 0:48:20 lr: 7.4516568958547115e-06 loss: 0.0319 (0.0331) time: 2.6404 data: 0.0065 max mem: 33369 +Epoch: [35] [ 240/1319] eta: 0:47:52 lr: 7.4411178977111085e-06 loss: 0.0315 (0.0329) time: 2.6539 data: 0.0066 max mem: 33369 +Epoch: [35] [ 250/1319] eta: 0:47:24 lr: 7.430577240796325e-06 loss: 0.0257 (0.0329) time: 2.6327 data: 0.0065 max mem: 33369 +Epoch: [35] [ 260/1319] eta: 0:46:58 lr: 7.420034922233955e-06 loss: 0.0257 (0.0328) time: 2.6519 data: 0.0066 max mem: 33369 +Epoch: [35] [ 270/1319] eta: 0:46:32 lr: 7.4094909391380505e-06 loss: 0.0338 (0.0330) time: 2.6742 data: 0.0066 max mem: 33369 +Epoch: [35] [ 280/1319] eta: 0:46:05 lr: 7.398945288613088e-06 loss: 0.0346 (0.0329) time: 2.6674 data: 0.0065 max mem: 33369 +Epoch: [35] [ 290/1319] eta: 0:45:37 lr: 7.388397967753893e-06 loss: 0.0346 (0.0333) time: 2.6401 data: 0.0065 max mem: 33369 +Epoch: [35] [ 300/1319] eta: 0:45:10 lr: 7.3778489736456335e-06 loss: 0.0371 (0.0333) time: 2.6335 data: 0.0065 max mem: 33369 +Epoch: [35] [ 310/1319] eta: 0:44:43 lr: 7.367298303363743e-06 loss: 0.0356 (0.0337) time: 2.6496 data: 0.0065 max mem: 33369 +Epoch: [35] [ 320/1319] eta: 0:44:16 lr: 7.35674595397388e-06 loss: 0.0279 (0.0334) time: 2.6361 data: 0.0063 max mem: 33369 +Epoch: [35] [ 330/1319] eta: 0:43:49 lr: 7.34619192253189e-06 loss: 0.0259 (0.0335) time: 2.6538 data: 0.0063 max mem: 33369 +Epoch: [35] [ 340/1319] eta: 0:43:22 lr: 7.335636206083729e-06 loss: 0.0322 (0.0335) time: 2.6575 data: 0.0065 max mem: 33369 +Epoch: [35] [ 350/1319] eta: 0:42:56 lr: 7.325078801665445e-06 loss: 0.0320 (0.0335) time: 2.6593 data: 0.0065 max mem: 33369 +Epoch: [35] [ 360/1319] eta: 0:42:30 lr: 7.31451970630312e-06 loss: 0.0311 (0.0336) time: 2.6660 data: 0.0065 max mem: 33369 +Epoch: [35] [ 370/1319] eta: 0:42:02 lr: 7.303958917012809e-06 loss: 0.0308 (0.0336) time: 2.6421 data: 0.0065 max mem: 33369 +Epoch: [35] [ 380/1319] eta: 0:41:35 lr: 7.293396430800509e-06 loss: 0.0308 (0.0336) time: 2.6367 data: 0.0064 max mem: 33369 +Epoch: [35] [ 390/1319] eta: 0:41:08 lr: 7.282832244662077e-06 loss: 0.0320 (0.0336) time: 2.6439 data: 0.0065 max mem: 33369 +Epoch: [35] [ 400/1319] eta: 0:40:41 lr: 7.272266355583221e-06 loss: 0.0324 (0.0336) time: 2.6431 data: 0.0064 max mem: 33369 +Epoch: [35] [ 410/1319] eta: 0:40:14 lr: 7.261698760539424e-06 loss: 0.0323 (0.0336) time: 2.6356 data: 0.0065 max mem: 33369 +Epoch: [35] [ 420/1319] eta: 0:39:48 lr: 7.2511294564958895e-06 loss: 0.0314 (0.0336) time: 2.6406 data: 0.0066 max mem: 33369 +Epoch: [35] [ 430/1319] eta: 0:39:21 lr: 7.240558440407508e-06 loss: 0.0297 (0.0336) time: 2.6572 data: 0.0065 max mem: 33369 +Epoch: [35] [ 440/1319] eta: 0:38:54 lr: 7.229985709218795e-06 loss: 0.0292 (0.0335) time: 2.6420 data: 0.0064 max mem: 33369 +Epoch: [35] [ 450/1319] eta: 0:38:27 lr: 7.219411259863819e-06 loss: 0.0292 (0.0335) time: 2.6380 data: 0.0064 max mem: 33369 +Epoch: [35] [ 460/1319] eta: 0:38:00 lr: 7.208835089266191e-06 loss: 0.0308 (0.0335) time: 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eta: 0:27:21 lr: 6.954482434226801e-06 loss: 0.0340 (0.0339) time: 2.6412 data: 0.0063 max mem: 33369 +Epoch: [35] [ 710/1319] eta: 0:26:55 lr: 6.9438622009590656e-06 loss: 0.0335 (0.0338) time: 2.6539 data: 0.0063 max mem: 33369 +Epoch: [35] [ 720/1319] eta: 0:26:28 lr: 6.933240162602753e-06 loss: 0.0298 (0.0338) time: 2.6626 data: 0.0062 max mem: 33369 +Epoch: [35] [ 730/1319] eta: 0:26:02 lr: 6.922616315777261e-06 loss: 0.0298 (0.0337) time: 2.6517 data: 0.0063 max mem: 33369 +Epoch: [35] [ 740/1319] eta: 0:25:35 lr: 6.911990657089877e-06 loss: 0.0300 (0.0337) time: 2.6489 data: 0.0063 max mem: 33369 +Epoch: [35] [ 750/1319] eta: 0:25:08 lr: 6.901363183135715e-06 loss: 0.0309 (0.0337) time: 2.6307 data: 0.0064 max mem: 33369 +Epoch: [35] [ 760/1319] eta: 0:24:42 lr: 6.890733890497658e-06 loss: 0.0312 (0.0336) time: 2.6304 data: 0.0064 max mem: 33369 +Epoch: [35] [ 770/1319] eta: 0:24:15 lr: 6.880102775746271e-06 loss: 0.0312 (0.0337) time: 2.6515 data: 0.0065 max mem: 33369 +Epoch: 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mem: 33369 +Epoch: [35] [ 860/1319] eta: 0:20:16 lr: 6.784340175855078e-06 loss: 0.0305 (0.0337) time: 2.6405 data: 0.0064 max mem: 33369 +Epoch: [35] [ 870/1319] eta: 0:19:50 lr: 6.7736906485984466e-06 loss: 0.0275 (0.0337) time: 2.6412 data: 0.0064 max mem: 33369 +Epoch: [35] [ 880/1319] eta: 0:19:23 lr: 6.763039260673876e-06 loss: 0.0268 (0.0337) time: 2.6506 data: 0.0063 max mem: 33369 +Epoch: [35] [ 890/1319] eta: 0:18:57 lr: 6.752386008499089e-06 loss: 0.0268 (0.0336) time: 2.6459 data: 0.0064 max mem: 33369 +Epoch: [35] [ 900/1319] eta: 0:18:30 lr: 6.741730888478615e-06 loss: 0.0280 (0.0336) time: 2.6221 data: 0.0064 max mem: 33369 +Epoch: [35] [ 910/1319] eta: 0:18:03 lr: 6.7310738970037205e-06 loss: 0.0280 (0.0335) time: 2.6237 data: 0.0063 max mem: 33369 +Epoch: [35] [ 920/1319] eta: 0:17:37 lr: 6.7204150304523424e-06 loss: 0.0292 (0.0335) time: 2.6271 data: 0.0062 max mem: 33369 +Epoch: [35] [ 930/1319] eta: 0:17:10 lr: 6.709754285188997e-06 loss: 0.0315 (0.0335) time: 2.6273 data: 0.0063 max mem: 33369 +Epoch: [35] [ 940/1319] eta: 0:16:44 lr: 6.699091657564736e-06 loss: 0.0328 (0.0335) time: 2.6378 data: 0.0063 max mem: 33369 +Epoch: [35] [ 950/1319] eta: 0:16:17 lr: 6.688427143917049e-06 loss: 0.0318 (0.0335) time: 2.6457 data: 0.0063 max mem: 33369 +Epoch: [35] [ 960/1319] eta: 0:15:51 lr: 6.677760740569799e-06 loss: 0.0276 (0.0335) time: 2.6533 data: 0.0063 max mem: 33369 +Epoch: [35] [ 970/1319] eta: 0:15:24 lr: 6.667092443833153e-06 loss: 0.0313 (0.0335) time: 2.6770 data: 0.0063 max mem: 33369 +Epoch: [35] [ 980/1319] eta: 0:14:58 lr: 6.656422250003478e-06 loss: 0.0321 (0.0335) time: 2.6749 data: 0.0063 max mem: 33369 +Epoch: [35] [ 990/1319] eta: 0:14:31 lr: 6.645750155363307e-06 loss: 0.0286 (0.0335) time: 2.6378 data: 0.0063 max mem: 33369 +Epoch: [35] [1000/1319] eta: 0:14:05 lr: 6.635076156181232e-06 loss: 0.0294 (0.0335) time: 2.6190 data: 0.0064 max mem: 33369 +Epoch: [35] [1010/1319] eta: 0:13:38 lr: 6.624400248711836e-06 loss: 0.0354 (0.0336) time: 2.6293 data: 0.0065 max mem: 33369 +Epoch: [35] [1020/1319] eta: 0:13:12 lr: 6.613722429195618e-06 loss: 0.0305 (0.0335) time: 2.6386 data: 0.0063 max mem: 33369 +Epoch: [35] [1030/1319] eta: 0:12:45 lr: 6.603042693858916e-06 loss: 0.0312 (0.0335) time: 2.6350 data: 0.0063 max mem: 33369 +Epoch: [35] [1040/1319] eta: 0:12:18 lr: 6.5923610389138055e-06 loss: 0.0325 (0.0335) time: 2.6322 data: 0.0064 max mem: 33369 +Epoch: [35] [1050/1319] eta: 0:11:52 lr: 6.581677460558057e-06 loss: 0.0278 (0.0334) time: 2.6436 data: 0.0063 max mem: 33369 +Epoch: [35] [1060/1319] eta: 0:11:26 lr: 6.570991954975031e-06 loss: 0.0286 (0.0334) time: 2.6864 data: 0.0063 max mem: 33369 +Epoch: [35] [1070/1319] eta: 0:10:59 lr: 6.560304518333606e-06 loss: 0.0310 (0.0334) time: 2.6951 data: 0.0063 max mem: 33369 +Epoch: [35] [1080/1319] eta: 0:10:33 lr: 6.549615146788095e-06 loss: 0.0315 (0.0334) time: 2.6662 data: 0.0063 max mem: 33369 +Epoch: [35] [1090/1319] eta: 0:10:06 lr: 6.538923836478152e-06 loss: 0.0312 (0.0334) time: 2.6466 data: 0.0063 max mem: 33369 +Epoch: [35] [1100/1319] eta: 0:09:40 lr: 6.528230583528713e-06 loss: 0.0292 (0.0333) time: 2.6297 data: 0.0063 max mem: 33369 +Epoch: [35] [1110/1319] eta: 0:09:13 lr: 6.5175353840499016e-06 loss: 0.0287 (0.0333) time: 2.6237 data: 0.0062 max mem: 33369 +Epoch: [35] [1120/1319] eta: 0:08:47 lr: 6.506838234136938e-06 loss: 0.0287 (0.0333) time: 2.6591 data: 0.0063 max mem: 33369 +Epoch: [35] [1130/1319] eta: 0:08:20 lr: 6.4961391298700616e-06 loss: 0.0272 (0.0333) time: 2.6929 data: 0.0063 max mem: 33369 +Epoch: [35] [1140/1319] eta: 0:07:54 lr: 6.485438067314456e-06 loss: 0.0293 (0.0333) time: 2.6722 data: 0.0062 max mem: 33369 +Epoch: [35] [1150/1319] eta: 0:07:27 lr: 6.4747350425201315e-06 loss: 0.0301 (0.0333) time: 2.6281 data: 0.0062 max mem: 33369 +Epoch: [35] [1160/1319] eta: 0:07:01 lr: 6.464030051521878e-06 loss: 0.0346 (0.0333) time: 2.6360 data: 0.0063 max mem: 33369 +Epoch: [35] [1170/1319] eta: 0:06:34 lr: 6.453323090339156e-06 loss: 0.0269 (0.0333) time: 2.6343 data: 0.0063 max mem: 33369 +Epoch: [35] [1180/1319] eta: 0:06:08 lr: 6.442614154976011e-06 loss: 0.0279 (0.0333) time: 2.6277 data: 0.0061 max mem: 33369 +Epoch: [35] [1190/1319] eta: 0:05:41 lr: 6.431903241420996e-06 loss: 0.0309 (0.0332) time: 2.6427 data: 0.0064 max mem: 33369 +Epoch: [35] [1200/1319] eta: 0:05:15 lr: 6.4211903456470515e-06 loss: 0.0286 (0.0332) time: 2.6271 data: 0.0065 max mem: 33369 +Epoch: [35] [1210/1319] eta: 0:04:48 lr: 6.410475463611462e-06 loss: 0.0291 (0.0332) time: 2.6205 data: 0.0063 max mem: 33369 +Epoch: [35] [1220/1319] eta: 0:04:22 lr: 6.399758591255733e-06 loss: 0.0381 (0.0332) time: 2.6111 data: 0.0063 max mem: 33369 +Epoch: [35] [1230/1319] eta: 0:03:55 lr: 6.389039724505507e-06 loss: 0.0318 (0.0332) time: 2.6110 data: 0.0064 max mem: 33369 +Epoch: [35] [1240/1319] eta: 0:03:29 lr: 6.378318859270487e-06 loss: 0.0345 (0.0333) time: 2.6430 data: 0.0063 max mem: 33369 +Epoch: [35] [1250/1319] eta: 0:03:02 lr: 6.3675959914443046e-06 loss: 0.0348 (0.0333) time: 2.6624 data: 0.0063 max mem: 33369 +Epoch: [35] [1260/1319] eta: 0:02:36 lr: 6.356871116904475e-06 loss: 0.0338 (0.0333) time: 2.6550 data: 0.0064 max mem: 33369 +Epoch: [35] [1270/1319] eta: 0:02:09 lr: 6.34614423151228e-06 loss: 0.0328 (0.0333) time: 2.6635 data: 0.0063 max mem: 33369 +Epoch: [35] [1280/1319] eta: 0:01:43 lr: 6.335415331112665e-06 loss: 0.0304 (0.0332) time: 2.6746 data: 0.0063 max mem: 33369 +Epoch: [35] [1290/1319] eta: 0:01:16 lr: 6.324684411534165e-06 loss: 0.0304 (0.0332) time: 2.6529 data: 0.0063 max mem: 33369 +Epoch: [35] [1300/1319] eta: 0:00:50 lr: 6.313951468588795e-06 loss: 0.0333 (0.0332) time: 2.6449 data: 0.0062 max mem: 33369 +Epoch: [35] [1310/1319] eta: 0:00:23 lr: 6.3032164980719415e-06 loss: 0.0310 (0.0332) time: 2.6455 data: 0.0062 max mem: 33369 +Epoch: [35] Total time: 0:58:14 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 1:55:05 time: 2.6838 data: 2.5430 max mem: 33369 +Test: [ 100/2573] eta: 0:04:01 time: 0.0717 data: 0.0011 max mem: 33369 +Test: [ 200/2573] eta: 0:03:24 time: 0.0735 data: 0.0011 max mem: 33369 +Test: [ 300/2573] eta: 0:03:05 time: 0.0753 data: 0.0011 max mem: 33369 +Test: [ 400/2573] eta: 0:02:52 time: 0.0753 data: 0.0011 max mem: 33369 +Test: [ 500/2573] eta: 0:02:42 time: 0.0738 data: 0.0011 max mem: 33369 +Test: [ 600/2573] eta: 0:02:33 time: 0.0739 data: 0.0011 max mem: 33369 +Test: [ 700/2573] eta: 0:02:25 time: 0.0739 data: 0.0011 max mem: 33369 +Test: [ 800/2573] eta: 0:02:16 time: 0.0773 data: 0.0011 max mem: 33369 +Test: [ 900/2573] eta: 0:02:08 time: 0.0740 data: 0.0011 max mem: 33369 +Test: [1000/2573] eta: 0:02:00 time: 0.0740 data: 0.0011 max mem: 33369 +Test: [1100/2573] eta: 0:01:52 time: 0.0739 data: 0.0011 max mem: 33369 +Test: [1200/2573] eta: 0:01:44 time: 0.0738 data: 0.0011 max mem: 33369 +Test: [1300/2573] eta: 0:01:36 time: 0.0739 data: 0.0011 max mem: 33369 +Test: [1400/2573] eta: 0:01:29 time: 0.0723 data: 0.0011 max mem: 33369 +Test: [1500/2573] eta: 0:01:21 time: 0.0739 data: 0.0011 max mem: 33369 +Test: [1600/2573] eta: 0:01:13 time: 0.0773 data: 0.0011 max mem: 33369 +Test: [1700/2573] eta: 0:01:06 time: 0.0722 data: 0.0011 max mem: 33369 +Test: [1800/2573] eta: 0:00:58 time: 0.0755 data: 0.0011 max mem: 33369 +Test: [1900/2573] eta: 0:00:50 time: 0.0721 data: 0.0011 max mem: 33369 +Test: [2000/2573] eta: 0:00:43 time: 0.0739 data: 0.0011 max mem: 33369 +Test: [2100/2573] eta: 0:00:35 time: 0.0755 data: 0.0011 max mem: 33369 +Test: [2200/2573] eta: 0:00:27 time: 0.0754 data: 0.0010 max mem: 33369 +Test: [2300/2573] eta: 0:00:20 time: 0.0755 data: 0.0011 max mem: 33369 +Test: [2400/2573] eta: 0:00:12 time: 0.0705 data: 0.0011 max mem: 33369 +Test: [2500/2573] eta: 0:00:05 time: 0.0739 data: 0.0011 max mem: 33369 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: Total time: 0:03:13 +Final results: +Mean IoU is 64.87 + + precision@0.5 = 72.96 + precision@0.6 = 67.61 + precision@0.7 = 60.87 + precision@0.8 = 49.69 + precision@0.9 = 25.06 + overall IoU = 62.70 + +Average object IoU 64.86543017877622 +Overall IoU 62.69819641113281 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [36] [ 0/1319] eta: 3:11:47 lr: 6.293553287544593e-06 loss: 0.0554 (0.0554) time: 8.7245 data: 1.6089 max mem: 33369 +Epoch: [36] [ 10/1319] eta: 1:10:03 lr: 6.282814452998321e-06 loss: 0.0366 (0.0358) time: 3.2112 data: 0.1518 max mem: 33369 +Epoch: [36] [ 20/1319] eta: 1:04:01 lr: 6.2720735785923675e-06 loss: 0.0300 (0.0337) time: 2.6690 data: 0.0060 max mem: 33369 +Epoch: [36] [ 30/1319] eta: 1:01:24 lr: 6.261330660056396e-06 loss: 0.0300 (0.0335) time: 2.6649 data: 0.0061 max mem: 33369 +Epoch: [36] [ 40/1319] eta: 1:00:13 lr: 6.250585693102968e-06 loss: 0.0342 (0.0343) time: 2.6873 data: 0.0064 max mem: 33369 +Epoch: [36] [ 50/1319] eta: 0:59:04 lr: 6.2398386734274585e-06 loss: 0.0362 (0.0344) time: 2.6914 data: 0.0065 max mem: 33369 +Epoch: [36] [ 60/1319] eta: 0:58:00 lr: 6.229089596707912e-06 loss: 0.0299 (0.0330) time: 2.6397 data: 0.0066 max mem: 33369 +Epoch: [36] [ 70/1319] eta: 0:57:06 lr: 6.218338458604991e-06 loss: 0.0276 (0.0325) time: 2.6161 data: 0.0066 max mem: 33369 +Epoch: [36] [ 80/1319] eta: 0:56:23 lr: 6.207585254761843e-06 loss: 0.0283 (0.0321) time: 2.6265 data: 0.0064 max mem: 33369 +Epoch: [36] [ 90/1319] eta: 0:55:47 lr: 6.196829980804001e-06 loss: 0.0283 (0.0318) time: 2.6533 data: 0.0066 max mem: 33369 +Epoch: [36] [ 100/1319] eta: 0:55:15 lr: 6.1860726323392754e-06 loss: 0.0293 (0.0320) time: 2.6759 data: 0.0067 max mem: 33369 +Epoch: [36] [ 110/1319] eta: 0:54:41 lr: 6.175313204957665e-06 loss: 0.0327 (0.0324) time: 2.6711 data: 0.0066 max mem: 33369 +Epoch: [36] [ 120/1319] eta: 0:54:08 lr: 6.164551694231212e-06 loss: 0.0339 (0.0323) time: 2.6573 data: 0.0065 max mem: 33369 +Epoch: [36] [ 130/1319] eta: 0:53:36 lr: 6.153788095713938e-06 loss: 0.0367 (0.0330) time: 2.6563 data: 0.0065 max mem: 33369 +Epoch: [36] [ 140/1319] eta: 0:53:01 lr: 6.143022404941713e-06 loss: 0.0367 (0.0329) time: 2.6327 data: 0.0064 max mem: 33369 +Epoch: [36] [ 150/1319] eta: 0:52:31 lr: 6.132254617432146e-06 loss: 0.0271 (0.0327) time: 2.6360 data: 0.0065 max mem: 33369 +Epoch: [36] [ 160/1319] eta: 0:51:59 lr: 6.121484728684484e-06 loss: 0.0305 (0.0327) time: 2.6410 data: 0.0064 max mem: 33369 +Epoch: [36] [ 170/1319] eta: 0:51:27 lr: 6.110712734179475e-06 loss: 0.0305 (0.0325) time: 2.6203 data: 0.0065 max mem: 33369 +Epoch: [36] [ 180/1319] eta: 0:50:58 lr: 6.099938629379293e-06 loss: 0.0256 (0.0325) time: 2.6352 data: 0.0065 max mem: 33369 +Epoch: [36] [ 190/1319] eta: 0:50:28 lr: 6.0891624097274035e-06 loss: 0.0256 (0.0324) time: 2.6432 data: 0.0063 max mem: 33369 +Epoch: [36] [ 200/1319] eta: 0:50:03 lr: 6.07838407064845e-06 loss: 0.0284 (0.0323) time: 2.6729 data: 0.0064 max mem: 33369 +Epoch: [36] [ 210/1319] eta: 0:49:35 lr: 6.067603607548146e-06 loss: 0.0284 (0.0322) time: 2.6867 data: 0.0064 max mem: 33369 +Epoch: [36] [ 220/1319] eta: 0:49:05 lr: 6.05682101581314e-06 loss: 0.0302 (0.0323) time: 2.6387 data: 0.0064 max mem: 33369 +Epoch: [36] [ 230/1319] eta: 0:48:36 lr: 6.0460362908109285e-06 loss: 0.0334 (0.0323) time: 2.6298 data: 0.0064 max mem: 33369 +Epoch: [36] [ 240/1319] eta: 0:48:09 lr: 6.035249427889721e-06 loss: 0.0306 (0.0322) time: 2.6568 data: 0.0066 max mem: 33369 +Epoch: [36] [ 250/1319] eta: 0:47:39 lr: 6.024460422378318e-06 loss: 0.0284 (0.0322) time: 2.6371 data: 0.0066 max mem: 33369 +Epoch: [36] [ 260/1319] eta: 0:47:14 lr: 6.013669269586002e-06 loss: 0.0313 (0.0321) time: 2.6594 data: 0.0064 max mem: 33369 +Epoch: [36] [ 270/1319] eta: 0:46:46 lr: 6.002875964802412e-06 loss: 0.0311 (0.0322) time: 2.6740 data: 0.0064 max mem: 33369 +Epoch: [36] [ 280/1319] eta: 0:46:17 lr: 5.992080503297408e-06 loss: 0.0311 (0.0323) time: 2.6347 data: 0.0066 max mem: 33369 +Epoch: [36] [ 290/1319] eta: 0:45:49 lr: 5.981282880320978e-06 loss: 0.0319 (0.0323) time: 2.6322 data: 0.0066 max mem: 33369 +Epoch: [36] [ 300/1319] eta: 0:45:22 lr: 5.97048309110309e-06 loss: 0.0341 (0.0324) time: 2.6469 data: 0.0065 max mem: 33369 +Epoch: [36] [ 310/1319] eta: 0:44:55 lr: 5.959681130853577e-06 loss: 0.0294 (0.0323) time: 2.6661 data: 0.0064 max mem: 33369 +Epoch: [36] [ 320/1319] eta: 0:44:29 lr: 5.948876994762015e-06 loss: 0.0267 (0.0326) time: 2.6771 data: 0.0065 max mem: 33369 +Epoch: [36] [ 330/1319] eta: 0:44:01 lr: 5.938070677997572e-06 loss: 0.0293 (0.0328) time: 2.6636 data: 0.0065 max mem: 33369 +Epoch: [36] [ 340/1319] eta: 0:43:33 lr: 5.927262175708919e-06 loss: 0.0356 (0.0329) time: 2.6240 data: 0.0067 max mem: 33369 +Epoch: [36] [ 350/1319] eta: 0:43:05 lr: 5.916451483024071e-06 loss: 0.0356 (0.0331) time: 2.6222 data: 0.0066 max mem: 33369 +Epoch: [36] [ 360/1319] eta: 0:42:39 lr: 5.905638595050271e-06 loss: 0.0354 (0.0332) time: 2.6559 data: 0.0064 max mem: 33369 +Epoch: [36] [ 370/1319] eta: 0:42:11 lr: 5.894823506873858e-06 loss: 0.0311 (0.0331) time: 2.6533 data: 0.0065 max mem: 33369 +Epoch: [36] [ 380/1319] eta: 0:41:44 lr: 5.884006213560114e-06 loss: 0.0311 (0.0331) time: 2.6365 data: 0.0066 max mem: 33369 +Epoch: [36] [ 390/1319] eta: 0:41:16 lr: 5.873186710153169e-06 loss: 0.0346 (0.0332) time: 2.6402 data: 0.0066 max mem: 33369 +Epoch: [36] [ 400/1319] eta: 0:40:49 lr: 5.862364991675836e-06 loss: 0.0334 (0.0332) time: 2.6391 data: 0.0067 max mem: 33369 +Epoch: [36] [ 410/1319] eta: 0:40:22 lr: 5.85154105312949e-06 loss: 0.0319 (0.0332) time: 2.6522 data: 0.0065 max mem: 33369 +Epoch: [36] [ 420/1319] eta: 0:39:56 lr: 5.840714889493923e-06 loss: 0.0283 (0.0331) time: 2.6711 data: 0.0065 max mem: 33369 +Epoch: [36] [ 430/1319] eta: 0:39:29 lr: 5.829886495727219e-06 loss: 0.0320 (0.0336) time: 2.6672 data: 0.0066 max mem: 33369 +Epoch: [36] [ 440/1319] eta: 0:39:02 lr: 5.819055866765587e-06 loss: 0.0331 (0.0335) time: 2.6520 data: 0.0065 max mem: 33369 +Epoch: [36] [ 450/1319] eta: 0:38:36 lr: 5.808222997523256e-06 loss: 0.0327 (0.0335) time: 2.6796 data: 0.0063 max mem: 33369 +Epoch: [36] [ 460/1319] eta: 0:38:09 lr: 5.797387882892317e-06 loss: 0.0320 (0.0335) time: 2.6701 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0.0261 (0.0323) time: 2.6400 data: 0.0065 max mem: 33369 +Epoch: [36] [1020/1319] eta: 0:13:13 lr: 5.186869293487148e-06 loss: 0.0320 (0.0324) time: 2.6482 data: 0.0066 max mem: 33369 +Epoch: [36] [1030/1319] eta: 0:12:46 lr: 5.175896951795028e-06 loss: 0.0334 (0.0324) time: 2.6673 data: 0.0065 max mem: 33369 +Epoch: [36] [1040/1319] eta: 0:12:20 lr: 5.164922025027563e-06 loss: 0.0298 (0.0324) time: 2.6653 data: 0.0064 max mem: 33369 +Epoch: [36] [1050/1319] eta: 0:11:53 lr: 5.153944506469468e-06 loss: 0.0324 (0.0324) time: 2.6596 data: 0.0063 max mem: 33369 +Epoch: [36] [1060/1319] eta: 0:11:27 lr: 5.142964389372074e-06 loss: 0.0370 (0.0325) time: 2.6804 data: 0.0064 max mem: 33369 +Epoch: [36] [1070/1319] eta: 0:11:00 lr: 5.13198166695309e-06 loss: 0.0305 (0.0324) time: 2.6354 data: 0.0064 max mem: 33369 +Epoch: [36] [1080/1319] eta: 0:10:33 lr: 5.120996332396334e-06 loss: 0.0286 (0.0324) time: 2.6008 data: 0.0065 max mem: 33369 +Epoch: [36] [1090/1319] eta: 0:10:07 lr: 5.1100083788515145e-06 loss: 0.0325 (0.0324) time: 2.6100 data: 0.0065 max mem: 33369 +Epoch: [36] [1100/1319] eta: 0:09:40 lr: 5.0990177994339575e-06 loss: 0.0325 (0.0324) time: 2.6027 data: 0.0063 max mem: 33369 +Epoch: [36] [1110/1319] eta: 0:09:14 lr: 5.088024587224353e-06 loss: 0.0327 (0.0325) time: 2.6221 data: 0.0065 max mem: 33369 +Epoch: [36] [1120/1319] eta: 0:08:47 lr: 5.077028735268508e-06 loss: 0.0354 (0.0325) time: 2.6308 data: 0.0065 max mem: 33369 +Epoch: [36] [1130/1319] eta: 0:08:20 lr: 5.066030236577056e-06 loss: 0.0307 (0.0325) time: 2.6192 data: 0.0063 max mem: 33369 +Epoch: [36] [1140/1319] eta: 0:07:54 lr: 5.055029084125236e-06 loss: 0.0295 (0.0325) time: 2.6303 data: 0.0063 max mem: 33369 +Epoch: [36] [1150/1319] eta: 0:07:27 lr: 5.044025270852602e-06 loss: 0.0287 (0.0326) time: 2.6657 data: 0.0065 max mem: 33369 +Epoch: [36] [1160/1319] eta: 0:07:01 lr: 5.033018789662757e-06 loss: 0.0269 (0.0326) time: 2.6476 data: 0.0066 max mem: 33369 +Epoch: [36] [1170/1319] eta: 0:06:34 lr: 5.022009633423085e-06 loss: 0.0270 (0.0325) time: 2.6441 data: 0.0065 max mem: 33369 +Epoch: [36] [1180/1319] eta: 0:06:08 lr: 5.0109977949644845e-06 loss: 0.0305 (0.0326) time: 2.6452 data: 0.0064 max mem: 33369 +Epoch: [36] [1190/1319] eta: 0:05:41 lr: 4.999983267081064e-06 loss: 0.0307 (0.0326) time: 2.6428 data: 0.0063 max mem: 33369 +Epoch: [36] [1200/1319] eta: 0:05:15 lr: 4.988966042529905e-06 loss: 0.0279 (0.0326) time: 2.6619 data: 0.0063 max mem: 33369 +Epoch: [36] [1210/1319] eta: 0:04:48 lr: 4.977946114030749e-06 loss: 0.0293 (0.0326) time: 2.6627 data: 0.0062 max mem: 33369 +Epoch: [36] [1220/1319] eta: 0:04:22 lr: 4.966923474265728e-06 loss: 0.0298 (0.0326) time: 2.6583 data: 0.0062 max mem: 33369 +Epoch: [36] [1230/1319] eta: 0:03:55 lr: 4.9558981158790714e-06 loss: 0.0300 (0.0326) time: 2.6610 data: 0.0063 max mem: 33369 +Epoch: [36] [1240/1319] eta: 0:03:29 lr: 4.944870031476802e-06 loss: 0.0298 (0.0325) time: 2.6788 data: 0.0063 max mem: 33369 +Epoch: [36] [1250/1319] eta: 0:03:02 lr: 4.9338392136264714e-06 loss: 0.0296 (0.0325) time: 2.6656 data: 0.0063 max mem: 33369 +Epoch: [36] [1260/1319] eta: 0:02:36 lr: 4.922805654856843e-06 loss: 0.0290 (0.0325) time: 2.6388 data: 0.0063 max mem: 33369 +Epoch: [36] [1270/1319] eta: 0:02:09 lr: 4.9117693476576e-06 loss: 0.0298 (0.0325) time: 2.6553 data: 0.0064 max mem: 33369 +Epoch: [36] [1280/1319] eta: 0:01:43 lr: 4.9007302844790375e-06 loss: 0.0328 (0.0325) time: 2.6592 data: 0.0064 max mem: 33369 +Epoch: [36] [1290/1319] eta: 0:01:16 lr: 4.889688457731768e-06 loss: 0.0309 (0.0325) time: 2.6476 data: 0.0063 max mem: 33369 +Epoch: [36] [1300/1319] eta: 0:00:50 lr: 4.878643859786385e-06 loss: 0.0278 (0.0325) time: 2.6446 data: 0.0062 max mem: 33369 +Epoch: [36] [1310/1319] eta: 0:00:23 lr: 4.867596482973188e-06 loss: 0.0282 (0.0325) time: 2.6502 data: 0.0063 max mem: 33369 +Epoch: [36] Total time: 0:58:16 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 1:56:53 time: 2.7258 data: 2.6025 max mem: 33369 +Test: [ 100/2573] eta: 0:04:02 time: 0.0715 data: 0.0011 max mem: 33369 +Test: [ 200/2573] eta: 0:03:24 time: 0.0734 data: 0.0011 max mem: 33369 +Test: [ 300/2573] eta: 0:03:05 time: 0.0751 data: 0.0010 max mem: 33369 +Test: [ 400/2573] eta: 0:02:52 time: 0.0754 data: 0.0011 max mem: 33369 +Test: [ 500/2573] eta: 0:02:42 time: 0.0737 data: 0.0011 max mem: 33369 +Test: [ 600/2573] eta: 0:02:33 time: 0.0737 data: 0.0011 max mem: 33369 +Test: [ 700/2573] eta: 0:02:25 time: 0.0737 data: 0.0011 max mem: 33369 +Test: [ 800/2573] eta: 0:02:16 time: 0.0771 data: 0.0011 max mem: 33369 +Test: [ 900/2573] eta: 0:02:08 time: 0.0737 data: 0.0011 max mem: 33369 +Test: [1000/2573] eta: 0:02:00 time: 0.0739 data: 0.0011 max mem: 33369 +Test: [1100/2573] eta: 0:01:52 time: 0.0739 data: 0.0011 max mem: 33369 +Test: [1200/2573] eta: 0:01:44 time: 0.0739 data: 0.0011 max mem: 33369 +Test: [1300/2573] eta: 0:01:36 time: 0.0738 data: 0.0011 max mem: 33369 +Test: [1400/2573] eta: 0:01:28 time: 0.0723 data: 0.0011 max mem: 33369 +Test: [1500/2573] eta: 0:01:21 time: 0.0739 data: 0.0011 max mem: 33369 +Test: [1600/2573] eta: 0:01:13 time: 0.0772 data: 0.0011 max mem: 33369 +Test: [1700/2573] eta: 0:01:05 time: 0.0721 data: 0.0011 max mem: 33369 +Test: [1800/2573] eta: 0:00:58 time: 0.0756 data: 0.0011 max mem: 33369 +Test: [1900/2573] eta: 0:00:50 time: 0.0721 data: 0.0011 max mem: 33369 +Test: [2000/2573] eta: 0:00:43 time: 0.0739 data: 0.0011 max mem: 33369 +Test: [2100/2573] eta: 0:00:35 time: 0.0755 data: 0.0011 max mem: 33369 +Test: [2200/2573] eta: 0:00:27 time: 0.0755 data: 0.0010 max mem: 33369 +Test: [2300/2573] eta: 0:00:20 time: 0.0754 data: 0.0011 max mem: 33369 +Test: [2400/2573] eta: 0:00:12 time: 0.0706 data: 0.0011 max mem: 33369 +Test: [2500/2573] eta: 0:00:05 time: 0.0737 data: 0.0011 max mem: 33369 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: Total time: 0:03:13 +Final results: +Mean IoU is 65.01 + + precision@0.5 = 73.16 + precision@0.6 = 67.81 + precision@0.7 = 61.19 + precision@0.8 = 49.45 + precision@0.9 = 25.04 + overall IoU = 62.87 + +Average object IoU 65.0099164243465 +Overall IoU 62.869998931884766 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [37] [ 0/1319] eta: 3:18:17 lr: 4.85765146153759e-06 loss: 0.0250 (0.0250) time: 9.0204 data: 1.3094 max mem: 33369 +Epoch: [37] [ 10/1319] eta: 1:10:38 lr: 4.846598783599751e-06 loss: 0.0257 (0.0265) time: 3.2379 data: 0.1249 max mem: 33369 +Epoch: [37] [ 20/1319] eta: 1:03:51 lr: 4.835543304321068e-06 loss: 0.0285 (0.0317) time: 2.6464 data: 0.0064 max mem: 33369 +Epoch: [37] [ 30/1319] eta: 1:01:30 lr: 4.824485015871577e-06 loss: 0.0285 (0.0307) time: 2.6571 data: 0.0064 max mem: 33369 +Epoch: [37] [ 40/1319] eta: 0:59:45 lr: 4.813423910379438e-06 loss: 0.0285 (0.0319) time: 2.6488 data: 0.0065 max mem: 33369 +Epoch: [37] [ 50/1319] eta: 0:58:44 lr: 4.802359979930566e-06 loss: 0.0326 (0.0316) time: 2.6439 data: 0.0066 max mem: 33369 +Epoch: [37] [ 60/1319] eta: 0:57:54 lr: 4.791293216568347e-06 loss: 0.0244 (0.0305) time: 2.6703 data: 0.0066 max mem: 33369 +Epoch: [37] [ 70/1319] eta: 0:57:04 lr: 4.780223612293264e-06 loss: 0.0258 (0.0307) time: 2.6525 data: 0.0065 max mem: 33369 +Epoch: [37] [ 80/1319] eta: 0:56:30 lr: 4.7691511590625665e-06 loss: 0.0322 (0.0316) time: 2.6650 data: 0.0067 max mem: 33369 +Epoch: [37] [ 90/1319] eta: 0:55:54 lr: 4.75807584878992e-06 loss: 0.0356 (0.0318) time: 2.6835 data: 0.0065 max mem: 33369 +Epoch: [37] [ 100/1319] eta: 0:55:19 lr: 4.7469976733450685e-06 loss: 0.0286 (0.0314) time: 2.6720 data: 0.0062 max mem: 33369 +Epoch: [37] [ 110/1319] eta: 0:54:44 lr: 4.735916624553454e-06 loss: 0.0279 (0.0312) time: 2.6590 data: 0.0063 max mem: 33369 +Epoch: [37] [ 120/1319] eta: 0:54:13 lr: 4.724832694195895e-06 loss: 0.0280 (0.0312) time: 2.6630 data: 0.0065 max mem: 33369 +Epoch: [37] [ 130/1319] eta: 0:53:40 lr: 4.713745874008202e-06 loss: 0.0276 (0.0311) time: 2.6626 data: 0.0064 max mem: 33369 +Epoch: [37] [ 140/1319] eta: 0:53:08 lr: 4.702656155680819e-06 loss: 0.0268 (0.0308) time: 2.6469 data: 0.0065 max mem: 33369 +Epoch: [37] [ 150/1319] eta: 0:52:36 lr: 4.691563530858464e-06 loss: 0.0276 (0.0312) time: 2.6485 data: 0.0066 max mem: 33369 +Epoch: [37] [ 160/1319] eta: 0:52:03 lr: 4.6804679911397265e-06 loss: 0.0316 (0.0312) time: 2.6303 data: 0.0065 max mem: 33369 +Epoch: [37] [ 170/1319] eta: 0:51:33 lr: 4.66936952807673e-06 loss: 0.0298 (0.0311) time: 2.6334 data: 0.0064 max mem: 33369 +Epoch: [37] [ 180/1319] eta: 0:51:01 lr: 4.65826813317473e-06 loss: 0.0267 (0.0309) time: 2.6311 data: 0.0064 max mem: 33369 +Epoch: [37] [ 190/1319] eta: 0:50:31 lr: 4.64716379789173e-06 loss: 0.0278 (0.0308) time: 2.6222 data: 0.0064 max mem: 33369 +Epoch: [37] [ 200/1319] eta: 0:50:02 lr: 4.636056513638103e-06 loss: 0.0293 (0.0306) time: 2.6450 data: 0.0064 max mem: 33369 +Epoch: [37] [ 210/1319] eta: 0:49:35 lr: 4.6249462717761695e-06 loss: 0.0305 (0.0308) time: 2.6650 data: 0.0065 max mem: 33369 +Epoch: [37] [ 220/1319] eta: 0:49:05 lr: 4.6138330636198426e-06 loss: 0.0322 (0.0308) time: 2.6438 data: 0.0065 max mem: 33369 +Epoch: [37] [ 230/1319] eta: 0:48:37 lr: 4.602716880434195e-06 loss: 0.0276 (0.0306) time: 2.6398 data: 0.0066 max mem: 33369 +Epoch: [37] [ 240/1319] eta: 0:48:10 lr: 4.591597713435064e-06 loss: 0.0286 (0.0309) time: 2.6617 data: 0.0066 max mem: 33369 +Epoch: [37] [ 250/1319] eta: 0:47:42 lr: 4.580475553788638e-06 loss: 0.0287 (0.0308) time: 2.6523 data: 0.0067 max mem: 33369 +Epoch: [37] [ 260/1319] eta: 0:47:12 lr: 4.569350392611047e-06 loss: 0.0263 (0.0307) time: 2.6319 data: 0.0068 max mem: 33369 +Epoch: [37] [ 270/1319] eta: 0:46:43 lr: 4.558222220967921e-06 loss: 0.0273 (0.0308) time: 2.6095 data: 0.0067 max mem: 33369 +Epoch: [37] [ 280/1319] eta: 0:46:16 lr: 4.547091029873999e-06 loss: 0.0311 (0.0308) time: 2.6349 data: 0.0066 max mem: 33369 +Epoch: [37] [ 290/1319] eta: 0:45:46 lr: 4.5359568102926745e-06 loss: 0.0306 (0.0308) time: 2.6309 data: 0.0067 max mem: 33369 +Epoch: [37] [ 300/1319] eta: 0:45:17 lr: 4.524819553135574e-06 loss: 0.0289 (0.0307) time: 2.6011 data: 0.0067 max mem: 33369 +Epoch: [37] [ 310/1319] eta: 0:44:50 lr: 4.5136792492621144e-06 loss: 0.0301 (0.0307) time: 2.6174 data: 0.0066 max mem: 33369 +Epoch: [37] [ 320/1319] eta: 0:44:22 lr: 4.502535889479041e-06 loss: 0.0279 (0.0307) time: 2.6248 data: 0.0066 max mem: 33369 +Epoch: [37] [ 330/1319] eta: 0:43:54 lr: 4.491389464540016e-06 loss: 0.0263 (0.0307) time: 2.6304 data: 0.0065 max mem: 33369 +Epoch: [37] [ 340/1319] eta: 0:43:26 lr: 4.480239965145135e-06 loss: 0.0293 (0.0309) time: 2.6321 data: 0.0065 max mem: 33369 +Epoch: [37] [ 350/1319] eta: 0:42:59 lr: 4.469087381940477e-06 loss: 0.0323 (0.0310) time: 2.6224 data: 0.0065 max mem: 33369 +Epoch: [37] [ 360/1319] eta: 0:42:32 lr: 4.457931705517646e-06 loss: 0.0263 (0.0308) time: 2.6343 data: 0.0063 max mem: 33369 +Epoch: [37] [ 370/1319] eta: 0:42:05 lr: 4.446772926413276e-06 loss: 0.0267 (0.0309) time: 2.6557 data: 0.0063 max mem: 33369 +Epoch: [37] [ 380/1319] eta: 0:41:38 lr: 4.435611035108594e-06 loss: 0.0308 (0.0308) time: 2.6602 data: 0.0063 max mem: 33369 +Epoch: [37] [ 390/1319] eta: 0:41:11 lr: 4.424446022028913e-06 loss: 0.0308 (0.0309) time: 2.6514 data: 0.0064 max mem: 33369 +Epoch: [37] [ 400/1319] eta: 0:40:44 lr: 4.413277877543152e-06 loss: 0.0273 (0.0309) time: 2.6380 data: 0.0065 max mem: 33369 +Epoch: [37] [ 410/1319] eta: 0:40:17 lr: 4.40210659196335e-06 loss: 0.0306 (0.0310) time: 2.6333 data: 0.0065 max mem: 33369 +Epoch: [37] [ 420/1319] eta: 0:39:50 lr: 4.390932155544163e-06 loss: 0.0345 (0.0311) time: 2.6464 data: 0.0065 max mem: 33369 +Epoch: [37] [ 430/1319] eta: 0:39:23 lr: 4.379754558482349e-06 loss: 0.0300 (0.0310) time: 2.6378 data: 0.0064 max mem: 33369 +Epoch: [37] [ 440/1319] eta: 0:38:56 lr: 4.368573790916289e-06 loss: 0.0291 (0.0311) time: 2.6212 data: 0.0064 max mem: 33369 +Epoch: [37] [ 450/1319] eta: 0:38:29 lr: 4.357389842925446e-06 loss: 0.0295 (0.0311) time: 2.6437 data: 0.0064 max mem: 33369 +Epoch: [37] [ 460/1319] eta: 0:38:02 lr: 4.346202704529857e-06 loss: 0.0271 (0.0310) time: 2.6428 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4.166766212733477e-06 loss: 0.0286 (0.0313) time: 2.6924 data: 0.0064 max mem: 33369 +Epoch: [37] [ 630/1319] eta: 0:30:27 lr: 4.15552325028145e-06 loss: 0.0274 (0.0312) time: 2.6580 data: 0.0064 max mem: 33369 +Epoch: [37] [ 640/1319] eta: 0:30:00 lr: 4.1442769069903985e-06 loss: 0.0272 (0.0312) time: 2.6113 data: 0.0062 max mem: 33369 +Epoch: [37] [ 650/1319] eta: 0:29:33 lr: 4.133027171643516e-06 loss: 0.0269 (0.0312) time: 2.6143 data: 0.0063 max mem: 33369 +Epoch: [37] [ 660/1319] eta: 0:29:07 lr: 4.121774032952729e-06 loss: 0.0252 (0.0311) time: 2.6470 data: 0.0063 max mem: 33369 +Epoch: [37] [ 670/1319] eta: 0:28:40 lr: 4.110517479558032e-06 loss: 0.0286 (0.0311) time: 2.6508 data: 0.0063 max mem: 33369 +Epoch: [37] [ 680/1319] eta: 0:28:14 lr: 4.099257500026817e-06 loss: 0.0286 (0.0311) time: 2.6339 data: 0.0064 max mem: 33369 +Epoch: [37] [ 690/1319] eta: 0:27:47 lr: 4.087994082853156e-06 loss: 0.0285 (0.0311) time: 2.6467 data: 0.0063 max mem: 33369 +Epoch: [37] [ 700/1319] eta: 0:27:20 lr: 4.076727216457151e-06 loss: 0.0257 (0.0310) time: 2.6484 data: 0.0062 max mem: 33369 +Epoch: [37] [ 710/1319] eta: 0:26:54 lr: 4.065456889184196e-06 loss: 0.0294 (0.0311) time: 2.6468 data: 0.0063 max mem: 33369 +Epoch: [37] [ 720/1319] eta: 0:26:27 lr: 4.054183089304276e-06 loss: 0.0364 (0.0311) time: 2.6485 data: 0.0063 max mem: 33369 +Epoch: [37] [ 730/1319] eta: 0:26:01 lr: 4.0429058050112415e-06 loss: 0.0328 (0.0311) time: 2.6549 data: 0.0063 max mem: 33369 +Epoch: [37] [ 740/1319] eta: 0:25:34 lr: 4.031625024422082e-06 loss: 0.0300 (0.0311) time: 2.6543 data: 0.0063 max mem: 33369 +Epoch: [37] [ 750/1319] eta: 0:25:08 lr: 4.020340735576163e-06 loss: 0.0325 (0.0312) time: 2.6441 data: 0.0065 max mem: 33369 +Epoch: [37] [ 760/1319] eta: 0:24:41 lr: 4.0090529264345135e-06 loss: 0.0313 (0.0312) time: 2.6261 data: 0.0065 max mem: 33369 +Epoch: [37] [ 770/1319] eta: 0:24:15 lr: 3.997761584879033e-06 loss: 0.0296 (0.0312) time: 2.6269 data: 0.0064 max mem: 33369 +Epoch: 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time: 2.6176 data: 0.0064 max mem: 33369 +Epoch: [37] [1020/1319] eta: 0:13:11 lr: 3.714292849713318e-06 loss: 0.0261 (0.0313) time: 2.6289 data: 0.0065 max mem: 33369 +Epoch: [37] [1030/1319] eta: 0:12:45 lr: 3.7029051332087708e-06 loss: 0.0307 (0.0313) time: 2.6403 data: 0.0065 max mem: 33369 +Epoch: [37] [1040/1319] eta: 0:12:18 lr: 3.691513524125288e-06 loss: 0.0269 (0.0313) time: 2.6436 data: 0.0065 max mem: 33369 +Epoch: [37] [1050/1319] eta: 0:11:52 lr: 3.680118007776355e-06 loss: 0.0260 (0.0313) time: 2.6542 data: 0.0063 max mem: 33369 +Epoch: [37] [1060/1319] eta: 0:11:25 lr: 3.6687185693693123e-06 loss: 0.0299 (0.0313) time: 2.6629 data: 0.0063 max mem: 33369 +Epoch: [37] [1070/1319] eta: 0:10:59 lr: 3.657315194004196e-06 loss: 0.0308 (0.0314) time: 2.6544 data: 0.0062 max mem: 33369 +Epoch: [37] [1080/1319] eta: 0:10:32 lr: 3.6459078666726217e-06 loss: 0.0304 (0.0313) time: 2.6387 data: 0.0063 max mem: 33369 +Epoch: [37] [1090/1319] eta: 0:10:06 lr: 3.6344965722565904e-06 loss: 0.0297 (0.0314) time: 2.6630 data: 0.0062 max mem: 33369 +Epoch: [37] [1100/1319] eta: 0:09:40 lr: 3.6230812955273095e-06 loss: 0.0320 (0.0314) time: 2.6784 data: 0.0064 max mem: 33369 +Epoch: [37] [1110/1319] eta: 0:09:13 lr: 3.6116620211439967e-06 loss: 0.0297 (0.0314) time: 2.6578 data: 0.0064 max mem: 33369 +Epoch: [37] [1120/1319] eta: 0:08:47 lr: 3.6002387336526318e-06 loss: 0.0290 (0.0314) time: 2.6510 data: 0.0063 max mem: 33369 +Epoch: [37] [1130/1319] eta: 0:08:20 lr: 3.588811417484761e-06 loss: 0.0326 (0.0314) time: 2.6491 data: 0.0063 max mem: 33369 +Epoch: [37] [1140/1319] eta: 0:07:54 lr: 3.577380056956213e-06 loss: 0.0289 (0.0314) time: 2.6509 data: 0.0062 max mem: 33369 +Epoch: [37] [1150/1319] eta: 0:07:27 lr: 3.5659446362658317e-06 loss: 0.0285 (0.0314) time: 2.6424 data: 0.0062 max mem: 33369 +Epoch: [37] [1160/1319] eta: 0:07:01 lr: 3.5545051394941854e-06 loss: 0.0305 (0.0315) time: 2.6431 data: 0.0062 max mem: 33369 +Epoch: [37] [1170/1319] eta: 0:06:34 lr: 3.5430615506022587e-06 loss: 0.0290 (0.0315) time: 2.6456 data: 0.0063 max mem: 33369 +Epoch: [37] [1180/1319] eta: 0:06:08 lr: 3.531613853430098e-06 loss: 0.0290 (0.0315) time: 2.6408 data: 0.0063 max mem: 33369 +Epoch: [37] [1190/1319] eta: 0:05:41 lr: 3.5201620316954973e-06 loss: 0.0293 (0.0315) time: 2.6640 data: 0.0063 max mem: 33369 +Epoch: [37] [1200/1319] eta: 0:05:15 lr: 3.5087060689926057e-06 loss: 0.0293 (0.0315) time: 2.6907 data: 0.0063 max mem: 33369 +Epoch: [37] [1210/1319] eta: 0:04:48 lr: 3.4972459487905388e-06 loss: 0.0311 (0.0315) time: 2.6615 data: 0.0063 max mem: 33369 +Epoch: [37] [1220/1319] eta: 0:04:22 lr: 3.485781654431977e-06 loss: 0.0295 (0.0315) time: 2.6425 data: 0.0064 max mem: 33369 +Epoch: [37] [1230/1319] eta: 0:03:55 lr: 3.4743131691317023e-06 loss: 0.0311 (0.0315) time: 2.6307 data: 0.0064 max mem: 33369 +Epoch: [37] [1240/1319] eta: 0:03:29 lr: 3.462840475975186e-06 loss: 0.0309 (0.0315) time: 2.6276 data: 0.0063 max mem: 33369 +Epoch: [37] 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+/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 1:59:26 time: 2.7854 data: 2.6323 max mem: 33369 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 100/2573] eta: 0:04:04 time: 0.0716 data: 0.0011 max mem: 33369 +Test: [ 200/2573] eta: 0:03:25 time: 0.0734 data: 0.0011 max mem: 33369 +Test: [ 300/2573] eta: 0:03:05 time: 0.0751 data: 0.0011 max mem: 33369 +Test: [ 400/2573] eta: 0:02:53 time: 0.0753 data: 0.0011 max mem: 33369 +Test: [ 500/2573] eta: 0:02:42 time: 0.0737 data: 0.0011 max mem: 33369 +Test: [ 600/2573] eta: 0:02:33 time: 0.0737 data: 0.0011 max mem: 33369 +Test: [ 700/2573] eta: 0:02:25 time: 0.0737 data: 0.0011 max mem: 33369 +Test: [ 800/2573] eta: 0:02:16 time: 0.0770 data: 0.0011 max mem: 33369 +Test: [ 900/2573] eta: 0:02:08 time: 0.0739 data: 0.0011 max mem: 33369 +Test: [1000/2573] eta: 0:02:00 time: 0.0738 data: 0.0011 max mem: 33369 +Test: [1100/2573] eta: 0:01:52 time: 0.0739 data: 0.0011 max mem: 33369 +Test: [1200/2573] eta: 0:01:44 time: 0.0739 data: 0.0011 max mem: 33369 +Test: [1300/2573] eta: 0:01:36 time: 0.0738 data: 0.0011 max mem: 33369 +Test: [1400/2573] eta: 0:01:28 time: 0.0722 data: 0.0011 max mem: 33369 +Test: [1500/2573] eta: 0:01:21 time: 0.0738 data: 0.0011 max mem: 33369 +Test: [1600/2573] eta: 0:01:13 time: 0.0771 data: 0.0011 max mem: 33369 +Test: [1700/2573] eta: 0:01:05 time: 0.0721 data: 0.0011 max mem: 33369 +Test: [1800/2573] eta: 0:00:58 time: 0.0756 data: 0.0011 max mem: 33369 +Test: [1900/2573] eta: 0:00:50 time: 0.0725 data: 0.0011 max mem: 33369 +Test: [2000/2573] eta: 0:00:43 time: 0.0738 data: 0.0011 max mem: 33369 +Test: [2100/2573] eta: 0:00:35 time: 0.0755 data: 0.0011 max mem: 33369 +Test: [2200/2573] eta: 0:00:27 time: 0.0755 data: 0.0011 max mem: 33369 +Test: [2300/2573] eta: 0:00:20 time: 0.0756 data: 0.0011 max mem: 33369 +Test: [2400/2573] eta: 0:00:12 time: 0.0705 data: 0.0011 max mem: 33369 +Test: [2500/2573] eta: 0:00:05 time: 0.0738 data: 0.0011 max mem: 33369 +Test: Total time: 0:03:12 +Final results: +Mean IoU is 64.86 + + precision@0.5 = 72.90 + precision@0.6 = 67.44 + precision@0.7 = 60.99 + precision@0.8 = 49.31 + precision@0.9 = 25.12 + overall IoU = 62.82 + +Average object IoU 64.85817269651342 +Overall IoU 62.82413101196289 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [38] [ 0/1319] eta: 3:22:03 lr: 3.3720562685558925e-06 loss: 0.0243 (0.0243) time: 9.1917 data: 1.1954 max mem: 33369 +Epoch: [38] [ 10/1319] eta: 1:10:57 lr: 3.3605453588871517e-06 loss: 0.0293 (0.0304) time: 3.2525 data: 0.1145 max mem: 33369 +Epoch: [38] [ 20/1319] eta: 1:04:07 lr: 3.349030066603249e-06 loss: 0.0293 (0.0308) time: 2.6501 data: 0.0063 max mem: 33369 +Epoch: [38] [ 30/1319] eta: 1:01:36 lr: 3.3375103732791936e-06 loss: 0.0312 (0.0318) time: 2.6566 data: 0.0064 max mem: 33369 +Epoch: [38] [ 40/1319] eta: 0:59:45 lr: 3.3259862603415314e-06 loss: 0.0331 (0.0318) time: 2.6369 data: 0.0065 max mem: 33369 +Epoch: [38] [ 50/1319] eta: 0:58:43 lr: 3.314457709066606e-06 loss: 0.0312 (0.0316) time: 2.6346 data: 0.0065 max mem: 33369 +Epoch: [38] [ 60/1319] eta: 0:57:55 lr: 3.302924700578736e-06 loss: 0.0312 (0.0321) time: 2.6721 data: 0.0065 max mem: 33369 +Epoch: [38] [ 70/1319] eta: 0:57:09 lr: 3.2913872158483893e-06 loss: 0.0303 (0.0320) time: 2.6684 data: 0.0064 max mem: 33369 +Epoch: [38] [ 80/1319] eta: 0:56:21 lr: 3.279845235690334e-06 loss: 0.0269 (0.0313) time: 2.6332 data: 0.0064 max mem: 33369 +Epoch: [38] [ 90/1319] eta: 0:55:42 lr: 3.268298740761722e-06 loss: 0.0286 (0.0316) time: 2.6256 data: 0.0064 max mem: 33369 +Epoch: [38] [ 100/1319] eta: 0:55:06 lr: 3.2567477115602124e-06 loss: 0.0298 (0.0323) time: 2.6468 data: 0.0064 max mem: 33369 +Epoch: [38] [ 110/1319] eta: 0:54:25 lr: 3.2451921284219928e-06 loss: 0.0302 (0.0324) time: 2.6154 data: 0.0064 max mem: 33369 +Epoch: [38] [ 120/1319] eta: 0:53:49 lr: 3.233631971519807e-06 loss: 0.0276 (0.0321) time: 2.5994 data: 0.0065 max mem: 33369 +Epoch: [38] [ 130/1319] eta: 0:53:21 lr: 3.2220672208609392e-06 loss: 0.0264 (0.0318) time: 2.6463 data: 0.0065 max mem: 33369 +Epoch: [38] [ 140/1319] eta: 0:52:51 lr: 3.2104978562851772e-06 loss: 0.0250 (0.0315) time: 2.6677 data: 0.0064 max mem: 33369 +Epoch: [38] [ 150/1319] eta: 0:52:19 lr: 3.1989238574627024e-06 loss: 0.0283 (0.0314) time: 2.6379 data: 0.0065 max mem: 33369 +Epoch: [38] [ 160/1319] eta: 0:51:47 lr: 3.18734520389202e-06 loss: 0.0292 (0.0312) time: 2.6172 data: 0.0066 max mem: 33369 +Epoch: [38] [ 170/1319] eta: 0:51:18 lr: 3.175761874897778e-06 loss: 0.0307 (0.0312) time: 2.6359 data: 0.0067 max mem: 33369 +Epoch: [38] [ 180/1319] eta: 0:50:50 lr: 3.1641738496285912e-06 loss: 0.0337 (0.0316) time: 2.6584 data: 0.0065 max mem: 33369 +Epoch: [38] [ 190/1319] eta: 0:50:19 lr: 3.1525811070548283e-06 loss: 0.0337 (0.0316) time: 2.6326 data: 0.0063 max mem: 33369 +Epoch: [38] [ 200/1319] eta: 0:49:52 lr: 3.1409836259663234e-06 loss: 0.0318 (0.0318) time: 2.6349 data: 0.0064 max mem: 33369 +Epoch: [38] [ 210/1319] eta: 0:49:24 lr: 3.1293813849701203e-06 loss: 0.0316 (0.0318) time: 2.6574 data: 0.0064 max mem: 33369 +Epoch: [38] [ 220/1319] eta: 0:48:56 lr: 3.1177743624881108e-06 loss: 0.0301 (0.0318) time: 2.6451 data: 0.0064 max mem: 33369 +Epoch: [38] [ 230/1319] eta: 0:48:27 lr: 3.1061625367546658e-06 loss: 0.0256 (0.0315) time: 2.6348 data: 0.0064 max mem: 33369 +Epoch: [38] [ 240/1319] eta: 0:48:00 lr: 3.0945458858142194e-06 loss: 0.0261 (0.0315) time: 2.6457 data: 0.0064 max mem: 33369 +Epoch: [38] [ 250/1319] eta: 0:47:29 lr: 3.08292438751882e-06 loss: 0.0278 (0.0315) time: 2.6244 data: 0.0064 max mem: 33369 +Epoch: [38] [ 260/1319] eta: 0:47:00 lr: 3.071298019525602e-06 loss: 0.0278 (0.0315) time: 2.5859 data: 0.0066 max mem: 33369 +Epoch: [38] [ 270/1319] eta: 0:46:31 lr: 3.0596667592942867e-06 loss: 0.0302 (0.0315) time: 2.6046 data: 0.0065 max mem: 33369 +Epoch: [38] [ 280/1319] eta: 0:46:03 lr: 3.048030584084566e-06 loss: 0.0318 (0.0318) time: 2.6132 data: 0.0064 max mem: 33369 +Epoch: [38] [ 290/1319] eta: 0:45:36 lr: 3.036389470953479e-06 loss: 0.0310 (0.0318) time: 2.6373 data: 0.0063 max mem: 33369 +Epoch: [38] [ 300/1319] eta: 0:45:10 lr: 3.024743396752744e-06 loss: 0.0275 (0.0317) time: 2.6593 data: 0.0063 max mem: 33369 +Epoch: [38] [ 310/1319] eta: 0:44:42 lr: 3.013092338126003e-06 loss: 0.0271 (0.0317) time: 2.6475 data: 0.0063 max mem: 33369 +Epoch: [38] [ 320/1319] eta: 0:44:16 lr: 3.0014362715060913e-06 loss: 0.0321 (0.0317) time: 2.6531 data: 0.0063 max mem: 33369 +Epoch: [38] [ 330/1319] eta: 0:43:49 lr: 2.9897751731121923e-06 loss: 0.0308 (0.0316) time: 2.6485 data: 0.0065 max mem: 33369 +Epoch: [38] [ 340/1319] eta: 0:43:23 lr: 2.978109018946967e-06 loss: 0.0286 (0.0315) time: 2.6568 data: 0.0066 max mem: 33369 +Epoch: [38] [ 350/1319] eta: 0:42:56 lr: 2.9664377847936435e-06 loss: 0.0257 (0.0314) time: 2.6591 data: 0.0065 max mem: 33369 +Epoch: [38] [ 360/1319] eta: 0:42:29 lr: 2.954761446213011e-06 loss: 0.0267 (0.0314) time: 2.6475 data: 0.0063 max mem: 33369 +Epoch: [38] [ 370/1319] eta: 0:42:01 lr: 2.943079978540434e-06 loss: 0.0267 (0.0313) time: 2.6352 data: 0.0063 max mem: 33369 +Epoch: [38] [ 380/1319] eta: 0:41:34 lr: 2.931393356882739e-06 loss: 0.0287 (0.0313) time: 2.6205 data: 0.0064 max mem: 33369 +Epoch: [38] [ 390/1319] eta: 0:41:07 lr: 2.919701556115084e-06 loss: 0.0287 (0.0313) time: 2.6290 data: 0.0063 max mem: 33369 +Epoch: [38] [ 400/1319] eta: 0:40:40 lr: 2.908004550877762e-06 loss: 0.0284 (0.0312) time: 2.6479 data: 0.0063 max mem: 33369 +Epoch: [38] [ 410/1319] eta: 0:40:13 lr: 2.8963023155729493e-06 loss: 0.0283 (0.0312) time: 2.6452 data: 0.0063 max mem: 33369 +Epoch: [38] [ 420/1319] eta: 0:39:47 lr: 2.884594824361366e-06 loss: 0.0281 (0.0311) time: 2.6432 data: 0.0063 max mem: 33369 +Epoch: [38] [ 430/1319] eta: 0:39:21 lr: 2.8728820511589384e-06 loss: 0.0300 (0.0312) time: 2.6756 data: 0.0064 max mem: 33369 +Epoch: [38] [ 440/1319] eta: 0:38:54 lr: 2.861163969633332e-06 loss: 0.0274 (0.0313) time: 2.6612 data: 0.0063 max mem: 33369 +Epoch: [38] [ 450/1319] eta: 0:38:27 lr: 2.849440553200456e-06 loss: 0.0269 (0.0312) time: 2.6398 data: 0.0065 max mem: 33369 +Epoch: [38] [ 460/1319] eta: 0:38:00 lr: 2.837711775020899e-06 loss: 0.0284 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data: 0.0063 max mem: 33369 +Epoch: [38] [ 780/1319] eta: 0:23:46 lr: 2.4593843748450576e-06 loss: 0.0260 (0.0312) time: 2.5793 data: 0.0063 max mem: 33369 +Epoch: [38] [ 790/1319] eta: 0:23:20 lr: 2.447461687224963e-06 loss: 0.0277 (0.0311) time: 2.6172 data: 0.0064 max mem: 33369 +Epoch: [38] [ 800/1319] eta: 0:22:53 lr: 2.4355325426601037e-06 loss: 0.0301 (0.0311) time: 2.6264 data: 0.0064 max mem: 33369 +Epoch: [38] [ 810/1319] eta: 0:22:27 lr: 2.423596902475233e-06 loss: 0.0303 (0.0312) time: 2.6191 data: 0.0063 max mem: 33369 +Epoch: [38] [ 820/1319] eta: 0:22:00 lr: 2.4116547275504333e-06 loss: 0.0272 (0.0312) time: 2.6378 data: 0.0064 max mem: 33369 +Epoch: [38] [ 830/1319] eta: 0:21:34 lr: 2.3997059783135262e-06 loss: 0.0265 (0.0311) time: 2.6484 data: 0.0065 max mem: 33369 +Epoch: [38] [ 840/1319] eta: 0:21:07 lr: 2.38775061473232e-06 loss: 0.0264 (0.0311) time: 2.6314 data: 0.0064 max mem: 33369 +Epoch: [38] [ 850/1319] eta: 0:20:41 lr: 2.3757885963066428e-06 loss: 0.0291 (0.0311) time: 2.6477 data: 0.0061 max mem: 33369 +Epoch: [38] [ 860/1319] eta: 0:20:14 lr: 2.3638198820602614e-06 loss: 0.0264 (0.0310) time: 2.6501 data: 0.0063 max mem: 33369 +Epoch: [38] [ 870/1319] eta: 0:19:48 lr: 2.351844430532552e-06 loss: 0.0277 (0.0311) time: 2.6308 data: 0.0064 max mem: 33369 +Epoch: [38] [ 880/1319] eta: 0:19:21 lr: 2.339862199770001e-06 loss: 0.0324 (0.0311) time: 2.6341 data: 0.0064 max mem: 33369 +Epoch: [38] [ 890/1319] eta: 0:18:55 lr: 2.327873147317513e-06 loss: 0.0296 (0.0311) time: 2.6503 data: 0.0064 max mem: 33369 +Epoch: [38] [ 900/1319] eta: 0:18:28 lr: 2.315877230209485e-06 loss: 0.0278 (0.0311) time: 2.6727 data: 0.0064 max mem: 33369 +Epoch: [38] [ 910/1319] eta: 0:18:02 lr: 2.303874404960728e-06 loss: 0.0285 (0.0311) time: 2.6326 data: 0.0064 max mem: 33369 +Epoch: [38] [ 920/1319] eta: 0:17:35 lr: 2.291864627557113e-06 loss: 0.0285 (0.0310) time: 2.6482 data: 0.0063 max mem: 33369 +Epoch: [38] [ 930/1319] eta: 0:17:09 lr: 2.2798478534460264e-06 loss: 0.0280 (0.0311) time: 2.6765 data: 0.0062 max mem: 33369 +Epoch: [38] [ 940/1319] eta: 0:16:43 lr: 2.2678240375265906e-06 loss: 0.0280 (0.0311) time: 2.6490 data: 0.0063 max mem: 33369 +Epoch: [38] [ 950/1319] eta: 0:16:16 lr: 2.25579313413962e-06 loss: 0.0291 (0.0311) time: 2.6384 data: 0.0065 max mem: 33369 +Epoch: [38] [ 960/1319] eta: 0:15:50 lr: 2.243755097057401e-06 loss: 0.0269 (0.0311) time: 2.6398 data: 0.0065 max mem: 33369 +Epoch: [38] [ 970/1319] eta: 0:15:23 lr: 2.2317098794731506e-06 loss: 0.0279 (0.0311) time: 2.6240 data: 0.0063 max mem: 33369 +Epoch: [38] [ 980/1319] eta: 0:14:56 lr: 2.2196574339902486e-06 loss: 0.0300 (0.0311) time: 2.6120 data: 0.0062 max mem: 33369 +Epoch: [38] [ 990/1319] eta: 0:14:30 lr: 2.2075977126112046e-06 loss: 0.0336 (0.0311) time: 2.6436 data: 0.0063 max mem: 33369 +Epoch: [38] [1000/1319] eta: 0:14:04 lr: 2.195530666726346e-06 loss: 0.0296 (0.0311) time: 2.6616 data: 0.0064 max mem: 33369 +Epoch: [38] 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mem: 33369 +Epoch: [38] [1090/1319] eta: 0:10:05 lr: 2.086589311928101e-06 loss: 0.0275 (0.0311) time: 2.6372 data: 0.0063 max mem: 33369 +Epoch: [38] [1100/1319] eta: 0:09:39 lr: 2.074446204087186e-06 loss: 0.0289 (0.0312) time: 2.6337 data: 0.0061 max mem: 33369 +Epoch: [38] [1110/1319] eta: 0:09:12 lr: 2.062295193091432e-06 loss: 0.0303 (0.0312) time: 2.6347 data: 0.0063 max mem: 33369 +Epoch: [38] [1120/1319] eta: 0:08:46 lr: 2.050136221989693e-06 loss: 0.0302 (0.0312) time: 2.6094 data: 0.0063 max mem: 33369 +Epoch: [38] [1130/1319] eta: 0:08:19 lr: 2.0379692330421533e-06 loss: 0.0300 (0.0312) time: 2.6385 data: 0.0062 max mem: 33369 +Epoch: [38] [1140/1319] eta: 0:07:53 lr: 2.0257941677041134e-06 loss: 0.0254 (0.0312) time: 2.6694 data: 0.0065 max mem: 33369 +Epoch: [38] [1150/1319] eta: 0:07:27 lr: 2.013610966609312e-06 loss: 0.0279 (0.0312) time: 2.6549 data: 0.0066 max mem: 33369 +Epoch: [38] [1160/1319] eta: 0:07:00 lr: 2.0014195695528014e-06 loss: 0.0312 (0.0312) time: 2.6777 data: 0.0063 max mem: 33369 +Epoch: [38] [1170/1319] eta: 0:06:34 lr: 1.9892199154733075e-06 loss: 0.0277 (0.0312) time: 2.6704 data: 0.0062 max mem: 33369 +Epoch: [38] [1180/1319] eta: 0:06:07 lr: 1.977011942435173e-06 loss: 0.0279 (0.0312) time: 2.6361 data: 0.0062 max mem: 33369 +Epoch: [38] [1190/1319] eta: 0:05:41 lr: 1.964795587609718e-06 loss: 0.0279 (0.0312) time: 2.6398 data: 0.0062 max mem: 33369 +Epoch: [38] [1200/1319] eta: 0:05:14 lr: 1.9525707872561044e-06 loss: 0.0256 (0.0311) time: 2.6462 data: 0.0063 max mem: 33369 +Epoch: [38] [1210/1319] eta: 0:04:48 lr: 1.9403374767016633e-06 loss: 0.0259 (0.0311) time: 2.6163 data: 0.0065 max mem: 33369 +Epoch: [38] [1220/1319] eta: 0:04:21 lr: 1.928095590321611e-06 loss: 0.0315 (0.0311) time: 2.6162 data: 0.0063 max mem: 33369 +Epoch: [38] [1230/1319] eta: 0:03:55 lr: 1.915845061518256e-06 loss: 0.0296 (0.0311) time: 2.6500 data: 0.0061 max mem: 33369 +Epoch: [38] [1240/1319] eta: 0:03:28 lr: 1.9035858226995284e-06 loss: 0.0243 (0.0311) time: 2.6332 data: 0.0061 max mem: 33369 +Epoch: [38] [1250/1319] eta: 0:03:02 lr: 1.8913178052569088e-06 loss: 0.0312 (0.0312) time: 2.6152 data: 0.0062 max mem: 33369 +Epoch: [38] [1260/1319] eta: 0:02:36 lr: 1.8790409395427117e-06 loss: 0.0350 (0.0312) time: 2.6497 data: 0.0062 max mem: 33369 +Epoch: [38] [1270/1319] eta: 0:02:09 lr: 1.8667551548466507e-06 loss: 0.0264 (0.0312) time: 2.6525 data: 0.0062 max mem: 33369 +Epoch: [38] [1280/1319] eta: 0:01:43 lr: 1.8544603793717773e-06 loss: 0.0316 (0.0312) time: 2.6394 data: 0.0062 max mem: 33369 +Epoch: [38] [1290/1319] eta: 0:01:16 lr: 1.8421565402096163e-06 loss: 0.0303 (0.0312) time: 2.6488 data: 0.0062 max mem: 33369 +Epoch: [38] [1300/1319] eta: 0:00:50 lr: 1.8298435633145817e-06 loss: 0.0284 (0.0313) time: 2.6299 data: 0.0064 max mem: 33369 +Epoch: [38] [1310/1319] eta: 0:00:23 lr: 1.8175213734776007e-06 loss: 0.0286 (0.0312) time: 2.6050 data: 0.0064 max mem: 33369 +Epoch: [38] Total time: 0:58:08 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 2:07:31 time: 2.9736 data: 2.8936 max mem: 33369 +Test: [ 100/2573] eta: 0:04:08 time: 0.0717 data: 0.0011 max mem: 33369 +Test: [ 200/2573] eta: 0:03:27 time: 0.0736 data: 0.0011 max mem: 33369 +Test: [ 300/2573] eta: 0:03:07 time: 0.0752 data: 0.0011 max mem: 33369 +Test: [ 400/2573] eta: 0:02:54 time: 0.0754 data: 0.0011 max mem: 33369 +Test: [ 500/2573] eta: 0:02:43 time: 0.0738 data: 0.0011 max mem: 33369 +Test: [ 600/2573] eta: 0:02:34 time: 0.0739 data: 0.0011 max mem: 33369 +Test: [ 700/2573] eta: 0:02:25 time: 0.0739 data: 0.0011 max mem: 33369 +Test: [ 800/2573] eta: 0:02:17 time: 0.0773 data: 0.0011 max mem: 33369 +Test: [ 900/2573] eta: 0:02:09 time: 0.0739 data: 0.0011 max mem: 33369 +Test: [1000/2573] eta: 0:02:01 time: 0.0741 data: 0.0011 max mem: 33369 +Test: [1100/2573] eta: 0:01:52 time: 0.0739 data: 0.0011 max mem: 33369 +Test: [1200/2573] eta: 0:01:45 time: 0.0739 data: 0.0011 max mem: 33369 +Test: [1300/2573] eta: 0:01:37 time: 0.0739 data: 0.0011 max mem: 33369 +Test: [1400/2573] eta: 0:01:29 time: 0.0722 data: 0.0011 max mem: 33369 +Test: [1500/2573] eta: 0:01:21 time: 0.0740 data: 0.0011 max mem: 33369 +Test: [1600/2573] eta: 0:01:13 time: 0.0772 data: 0.0011 max mem: 33369 +Test: [1700/2573] eta: 0:01:06 time: 0.0722 data: 0.0011 max mem: 33369 +Test: [1800/2573] eta: 0:00:58 time: 0.0755 data: 0.0011 max mem: 33369 +Test: [1900/2573] eta: 0:00:50 time: 0.0722 data: 0.0011 max mem: 33369 +Test: [2000/2573] eta: 0:00:43 time: 0.0737 data: 0.0011 max mem: 33369 +Test: [2100/2573] eta: 0:00:35 time: 0.0754 data: 0.0010 max mem: 33369 +Test: [2200/2573] eta: 0:00:28 time: 0.0755 data: 0.0011 max mem: 33369 +Test: [2300/2573] eta: 0:00:20 time: 0.0754 data: 0.0011 max mem: 33369 +Test: [2400/2573] eta: 0:00:12 time: 0.0704 data: 0.0011 max mem: 33369 +Test: [2500/2573] eta: 0:00:05 time: 0.0737 data: 0.0011 max mem: 33369 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: Total time: 0:03:13 +Final results: +Mean IoU is 65.07 + + precision@0.5 = 73.28 + precision@0.6 = 67.81 + precision@0.7 = 61.19 + precision@0.8 = 49.78 + precision@0.9 = 25.37 + overall IoU = 62.83 + +Average object IoU 65.07308059542558 +Overall IoU 62.8302116394043 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [39] [ 0/1319] eta: 3:15:35 lr: 1.8064234624396156e-06 loss: 0.0334 (0.0334) time: 8.8973 data: 1.1370 max mem: 33369 +Epoch: [39] [ 10/1319] eta: 1:10:10 lr: 1.7940835565249508e-06 loss: 0.0248 (0.0264) time: 3.2162 data: 0.1091 max mem: 33369 +Epoch: [39] [ 20/1319] eta: 1:04:25 lr: 1.7817342127276263e-06 loss: 0.0274 (0.0277) time: 2.6798 data: 0.0064 max mem: 33369 +Epoch: [39] [ 30/1319] eta: 1:01:39 lr: 1.7693753510331764e-06 loss: 0.0282 (0.0279) time: 2.6801 data: 0.0065 max mem: 33369 +Epoch: [39] [ 40/1319] eta: 1:00:11 lr: 1.757006890122028e-06 loss: 0.0311 (0.0287) time: 2.6638 data: 0.0067 max mem: 33369 +Epoch: [39] [ 50/1319] eta: 0:59:10 lr: 1.7446287473378005e-06 loss: 0.0305 (0.0297) time: 2.6860 data: 0.0069 max mem: 33369 +Epoch: [39] [ 60/1319] eta: 0:57:58 lr: 1.7322408386546176e-06 loss: 0.0308 (0.0306) time: 2.6389 data: 0.0067 max mem: 33369 +Epoch: [39] [ 70/1319] eta: 0:57:11 lr: 1.7198430786433514e-06 loss: 0.0361 (0.0313) time: 2.6177 data: 0.0063 max mem: 33369 +Epoch: [39] [ 80/1319] eta: 0:56:28 lr: 1.7074353804367206e-06 loss: 0.0279 (0.0308) time: 2.6492 data: 0.0063 max mem: 33369 +Epoch: [39] [ 90/1319] eta: 0:55:51 lr: 1.6950176556933094e-06 loss: 0.0276 (0.0306) time: 2.6556 data: 0.0064 max mem: 33369 +Epoch: [39] [ 100/1319] eta: 0:55:13 lr: 1.682589814560305e-06 loss: 0.0293 (0.0309) time: 2.6500 data: 0.0065 max mem: 33369 +Epoch: [39] [ 110/1319] eta: 0:54:34 lr: 1.6701517656350208e-06 loss: 0.0320 (0.0309) time: 2.6226 data: 0.0066 max mem: 33369 +Epoch: [39] [ 120/1319] eta: 0:53:56 lr: 1.6577034159251048e-06 loss: 0.0269 (0.0311) time: 2.6034 data: 0.0065 max mem: 33369 +Epoch: [39] [ 130/1319] eta: 0:53:26 lr: 1.6452446708073954e-06 loss: 0.0309 (0.0311) time: 2.6332 data: 0.0065 max mem: 33369 +Epoch: [39] [ 140/1319] eta: 0:52:57 lr: 1.632775433985313e-06 loss: 0.0303 (0.0309) time: 2.6696 data: 0.0066 max mem: 33369 +Epoch: [39] [ 150/1319] eta: 0:52:22 lr: 1.62029560744485e-06 loss: 0.0280 (0.0308) time: 2.6322 data: 0.0065 max mem: 33369 +Epoch: [39] [ 160/1319] eta: 0:51:51 lr: 1.6078050914089353e-06 loss: 0.0276 (0.0306) time: 2.6128 data: 0.0065 max mem: 33369 +Epoch: [39] [ 170/1319] eta: 0:51:22 lr: 1.5953037842902214e-06 loss: 0.0280 (0.0308) time: 2.6420 data: 0.0065 max mem: 33369 +Epoch: [39] [ 180/1319] eta: 0:50:53 lr: 1.5827915826421849e-06 loss: 0.0314 (0.0310) time: 2.6514 data: 0.0064 max mem: 33369 +Epoch: [39] [ 190/1319] eta: 0:50:27 lr: 1.5702683811084266e-06 loss: 0.0287 (0.0309) time: 2.6687 data: 0.0064 max mem: 33369 +Epoch: [39] [ 200/1319] eta: 0:49:56 lr: 1.5577340723702017e-06 loss: 0.0275 (0.0310) time: 2.6514 data: 0.0064 max mem: 33369 +Epoch: [39] [ 210/1319] eta: 0:49:27 lr: 1.5451885470919527e-06 loss: 0.0260 (0.0309) time: 2.6189 data: 0.0065 max mem: 33369 +Epoch: [39] [ 220/1319] eta: 0:49:00 lr: 1.5326316938648584e-06 loss: 0.0276 (0.0309) time: 2.6508 data: 0.0064 max mem: 33369 +Epoch: [39] [ 230/1319] eta: 0:48:32 lr: 1.5200633991482792e-06 loss: 0.0300 (0.0309) time: 2.6673 data: 0.0065 max mem: 33369 +Epoch: [39] [ 240/1319] eta: 0:48:06 lr: 1.5074835472089545e-06 loss: 0.0258 (0.0307) time: 2.6736 data: 0.0064 max mem: 33369 +Epoch: [39] [ 250/1319] eta: 0:47:37 lr: 1.4948920200579605e-06 loss: 0.0262 (0.0306) time: 2.6558 data: 0.0063 max mem: 33369 +Epoch: [39] [ 260/1319] eta: 0:47:09 lr: 1.4822886973851744e-06 loss: 0.0275 (0.0306) time: 2.6222 data: 0.0063 max mem: 33369 +Epoch: [39] [ 270/1319] eta: 0:46:41 lr: 1.4696734564912314e-06 loss: 0.0275 (0.0307) time: 2.6394 data: 0.0064 max mem: 33369 +Epoch: [39] [ 280/1319] eta: 0:46:11 lr: 1.457046172216814e-06 loss: 0.0316 (0.0310) time: 2.6204 data: 0.0066 max mem: 33369 +Epoch: [39] [ 290/1319] eta: 0:45:43 lr: 1.444406716869153e-06 loss: 0.0342 (0.0311) time: 2.6043 data: 0.0065 max mem: 33369 +Epoch: [39] [ 300/1319] eta: 0:45:16 lr: 1.4317549601455566e-06 loss: 0.0320 (0.0311) time: 2.6392 data: 0.0064 max mem: 33369 +Epoch: [39] [ 310/1319] eta: 0:44:47 lr: 1.419090769053936e-06 loss: 0.0307 (0.0312) time: 2.6243 data: 0.0064 max mem: 33369 +Epoch: [39] [ 320/1319] eta: 0:44:19 lr: 1.4064140078300187e-06 loss: 0.0319 (0.0313) time: 2.6037 data: 0.0064 max mem: 33369 +Epoch: [39] [ 330/1319] eta: 0:43:51 lr: 1.3937245378511972e-06 loss: 0.0287 (0.0312) time: 2.6209 data: 0.0064 max mem: 33369 +Epoch: [39] [ 340/1319] eta: 0:43:24 lr: 1.3810222175468009e-06 loss: 0.0266 (0.0311) time: 2.6421 data: 0.0065 max mem: 33369 +Epoch: [39] [ 350/1319] eta: 0:42:55 lr: 1.3683069023045655e-06 loss: 0.0270 (0.0312) time: 2.6136 data: 0.0065 max mem: 33369 +Epoch: [39] [ 360/1319] eta: 0:42:29 lr: 1.355578444373217e-06 loss: 0.0266 (0.0311) time: 2.6123 data: 0.0064 max mem: 33369 +Epoch: [39] [ 370/1319] eta: 0:42:02 lr: 1.3428366927608033e-06 loss: 0.0266 (0.0311) time: 2.6541 data: 0.0063 max mem: 33369 +Epoch: [39] [ 380/1319] eta: 0:41:35 lr: 1.330081493128668e-06 loss: 0.0282 (0.0311) time: 2.6578 data: 0.0063 max mem: 33369 +Epoch: [39] [ 390/1319] eta: 0:41:09 lr: 1.3173126876807778e-06 loss: 0.0282 (0.0311) time: 2.6618 data: 0.0064 max mem: 33369 +Epoch: [39] [ 400/1319] eta: 0:40:43 lr: 1.304530115048165e-06 loss: 0.0315 (0.0311) time: 2.6621 data: 0.0065 max mem: 33369 +Epoch: [39] [ 410/1319] eta: 0:40:15 lr: 1.2917336101681678e-06 loss: 0.0275 (0.0311) time: 2.6460 data: 0.0064 max mem: 33369 +Epoch: [39] [ 420/1319] eta: 0:39:49 lr: 1.2789230041582899e-06 loss: 0.0275 (0.0311) time: 2.6461 data: 0.0064 max mem: 33369 +Epoch: [39] [ 430/1319] eta: 0:39:22 lr: 1.2660981241842216e-06 loss: 0.0294 (0.0311) time: 2.6551 data: 0.0065 max mem: 33369 +Epoch: [39] [ 440/1319] eta: 0:38:55 lr: 1.2532587933218004e-06 loss: 0.0280 (0.0312) time: 2.6489 data: 0.0065 max mem: 33369 +Epoch: [39] [ 450/1319] eta: 0:38:27 lr: 1.2404048304125217e-06 loss: 0.0313 (0.0312) time: 2.6200 data: 0.0064 max mem: 33369 +Epoch: [39] [ 460/1319] eta: 0:38:01 lr: 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data: 0.0063 max mem: 33369 +Epoch: [39] [ 700/1319] eta: 0:27:19 lr: 9.136614974653884e-07 loss: 0.0271 (0.0309) time: 2.6374 data: 0.0063 max mem: 33369 +Epoch: [39] [ 710/1319] eta: 0:26:53 lr: 9.003449179133091e-07 loss: 0.0287 (0.0308) time: 2.6595 data: 0.0063 max mem: 33369 +Epoch: [39] [ 720/1319] eta: 0:26:26 lr: 8.870064170319405e-07 loss: 0.0282 (0.0308) time: 2.6606 data: 0.0062 max mem: 33369 +Epoch: [39] [ 730/1319] eta: 0:26:00 lr: 8.736455912114245e-07 loss: 0.0260 (0.0308) time: 2.6410 data: 0.0063 max mem: 33369 +Epoch: [39] [ 740/1319] eta: 0:25:33 lr: 8.602620224130043e-07 loss: 0.0339 (0.0309) time: 2.6447 data: 0.0064 max mem: 33369 +Epoch: [39] [ 750/1319] eta: 0:25:07 lr: 8.468552773943076e-07 loss: 0.0345 (0.0310) time: 2.6484 data: 0.0064 max mem: 33369 +Epoch: [39] [ 760/1319] eta: 0:24:40 lr: 8.334249068786857e-07 loss: 0.0289 (0.0309) time: 2.6439 data: 0.0062 max mem: 33369 +Epoch: [39] [ 770/1319] eta: 0:24:14 lr: 8.199704446634483e-07 loss: 0.0289 (0.0310) time: 2.6548 data: 0.0061 max mem: 33369 +Epoch: [39] [ 780/1319] eta: 0:23:47 lr: 8.064914066612595e-07 loss: 0.0298 (0.0309) time: 2.6380 data: 0.0062 max mem: 33369 +Epoch: [39] [ 790/1319] eta: 0:23:21 lr: 7.92987289868475e-07 loss: 0.0311 (0.0310) time: 2.6411 data: 0.0064 max mem: 33369 +Epoch: [39] [ 800/1319] eta: 0:22:54 lr: 7.79457571253187e-07 loss: 0.0310 (0.0310) time: 2.6414 data: 0.0063 max mem: 33369 +Epoch: [39] [ 810/1319] eta: 0:22:28 lr: 7.659017065551902e-07 loss: 0.0319 (0.0311) time: 2.6365 data: 0.0064 max mem: 33369 +Epoch: [39] [ 820/1319] eta: 0:22:01 lr: 7.523191289889679e-07 loss: 0.0332 (0.0311) time: 2.6633 data: 0.0064 max mem: 33369 +Epoch: [39] [ 830/1319] eta: 0:21:34 lr: 7.387092478397154e-07 loss: 0.0318 (0.0312) time: 2.6321 data: 0.0064 max mem: 33369 +Epoch: [39] [ 840/1319] eta: 0:21:08 lr: 7.250714469413284e-07 loss: 0.0302 (0.0312) time: 2.6376 data: 0.0064 max mem: 33369 +Epoch: [39] [ 850/1319] eta: 0:20:41 lr: 7.114050830235778e-07 loss: 0.0291 (0.0312) time: 2.6264 data: 0.0064 max mem: 33369 +Epoch: [39] [ 860/1319] eta: 0:20:15 lr: 6.977094839143229e-07 loss: 0.0292 (0.0313) time: 2.6113 data: 0.0064 max mem: 33369 +Epoch: [39] [ 870/1319] eta: 0:19:48 lr: 6.839839465805414e-07 loss: 0.0292 (0.0312) time: 2.6289 data: 0.0064 max mem: 33369 +Epoch: [39] [ 880/1319] eta: 0:19:22 lr: 6.702277349898191e-07 loss: 0.0267 (0.0312) time: 2.6283 data: 0.0063 max mem: 33369 +Epoch: [39] [ 890/1319] eta: 0:18:55 lr: 6.564400777713066e-07 loss: 0.0284 (0.0313) time: 2.6318 data: 0.0063 max mem: 33369 +Epoch: [39] [ 900/1319] eta: 0:18:29 lr: 6.426201656523381e-07 loss: 0.0344 (0.0313) time: 2.6514 data: 0.0063 max mem: 33369 +Epoch: [39] [ 910/1319] eta: 0:18:02 lr: 6.287671486431178e-07 loss: 0.0319 (0.0313) time: 2.6376 data: 0.0066 max mem: 33369 +Epoch: [39] [ 920/1319] eta: 0:17:35 lr: 6.148801329380617e-07 loss: 0.0318 (0.0314) time: 2.6137 data: 0.0066 max mem: 33369 +Epoch: [39] [ 930/1319] eta: 0:17:09 lr: 6.009581774973726e-07 loss: 0.0311 (0.0314) time: 2.6264 data: 0.0065 max mem: 33369 +Epoch: [39] [ 940/1319] eta: 0:16:42 lr: 5.870002902666957e-07 loss: 0.0281 (0.0314) time: 2.6162 data: 0.0064 max mem: 33369 +Epoch: [39] [ 950/1319] eta: 0:16:16 lr: 5.7300542398606e-07 loss: 0.0266 (0.0313) time: 2.6253 data: 0.0064 max mem: 33369 +Epoch: [39] [ 960/1319] eta: 0:15:49 lr: 5.589724715308914e-07 loss: 0.0278 (0.0313) time: 2.6507 data: 0.0065 max mem: 33369 +Epoch: [39] [ 970/1319] eta: 0:15:23 lr: 5.449002607184345e-07 loss: 0.0282 (0.0313) time: 2.6466 data: 0.0065 max mem: 33369 +Epoch: [39] [ 980/1319] eta: 0:14:56 lr: 5.307875485010082e-07 loss: 0.0285 (0.0313) time: 2.6236 data: 0.0065 max mem: 33369 +Epoch: [39] [ 990/1319] eta: 0:14:30 lr: 5.166330144533874e-07 loss: 0.0333 (0.0313) time: 2.6152 data: 0.0063 max mem: 33369 +Epoch: [39] [1000/1319] eta: 0:14:03 lr: 5.024352534442401e-07 loss: 0.0331 (0.0313) time: 2.6391 data: 0.0062 max mem: 33369 +Epoch: [39] [1010/1319] eta: 0:13:37 lr: 4.881927673605746e-07 loss: 0.0313 (0.0313) time: 2.6479 data: 0.0063 max mem: 33369 +Epoch: [39] [1020/1319] eta: 0:13:10 lr: 4.7390395572780197e-07 loss: 0.0305 (0.0313) time: 2.6526 data: 0.0063 max mem: 33369 +Epoch: [39] [1030/1319] eta: 0:12:44 lr: 4.595671050360423e-07 loss: 0.0296 (0.0313) time: 2.6561 data: 0.0061 max mem: 33369 +Epoch: [39] [1040/1319] eta: 0:12:18 lr: 4.4518037654287396e-07 loss: 0.0300 (0.0313) time: 2.6349 data: 0.0062 max mem: 33369 +Epoch: [39] [1050/1319] eta: 0:11:51 lr: 4.3074179227215756e-07 loss: 0.0295 (0.0312) time: 2.6279 data: 0.0063 max mem: 33369 +Epoch: [39] [1060/1319] eta: 0:11:25 lr: 4.162492188647174e-07 loss: 0.0305 (0.0313) time: 2.6384 data: 0.0062 max mem: 33369 +Epoch: [39] [1070/1319] eta: 0:10:58 lr: 4.01700348854669e-07 loss: 0.0307 (0.0313) time: 2.6455 data: 0.0062 max mem: 33369 +Epoch: [39] [1080/1319] eta: 0:10:32 lr: 3.8709267884030336e-07 loss: 0.0284 (0.0312) time: 2.6319 data: 0.0062 max mem: 33369 +Epoch: [39] [1090/1319] eta: 0:10:05 lr: 3.724234838815835e-07 loss: 0.0285 (0.0313) time: 2.6269 data: 0.0063 max mem: 33369 +Epoch: [39] [1100/1319] eta: 0:09:39 lr: 3.5768978727688177e-07 loss: 0.0286 (0.0313) time: 2.6512 data: 0.0064 max mem: 33369 +Epoch: [39] [1110/1319] eta: 0:09:12 lr: 3.428883246336122e-07 loss: 0.0271 (0.0312) time: 2.6314 data: 0.0063 max mem: 33369 +Epoch: [39] [1120/1319] eta: 0:08:46 lr: 3.280155008272766e-07 loss: 0.0258 (0.0312) time: 2.6197 data: 0.0062 max mem: 33369 +Epoch: [39] [1130/1319] eta: 0:08:19 lr: 3.1306733800860497e-07 loss: 0.0279 (0.0312) time: 2.6256 data: 0.0062 max mem: 33369 +Epoch: [39] [1140/1319] eta: 0:07:53 lr: 2.9803941221786203e-07 loss: 0.0279 (0.0313) time: 2.6294 data: 0.0062 max mem: 33369 +Epoch: [39] [1150/1319] eta: 0:07:26 lr: 2.829267753240405e-07 loss: 0.0280 (0.0313) time: 2.6135 data: 0.0063 max mem: 33369 +Epoch: [39] [1160/1319] eta: 0:07:00 lr: 2.677238578071334e-07 loss: 0.0293 (0.0313) time: 2.6126 data: 0.0063 max mem: 33369 +Epoch: [39] [1170/1319] eta: 0:06:33 lr: 2.524243461593822e-07 loss: 0.0273 (0.0312) time: 2.6398 data: 0.0062 max mem: 33369 +Epoch: [39] [1180/1319] eta: 0:06:07 lr: 2.370210260957732e-07 loss: 0.0273 (0.0312) time: 2.6233 data: 0.0063 max mem: 33369 +Epoch: [39] [1190/1319] eta: 0:05:40 lr: 2.2150557883672493e-07 loss: 0.0284 (0.0312) time: 2.6267 data: 0.0063 max mem: 33369 +Epoch: [39] [1200/1319] eta: 0:05:14 lr: 2.058683115970694e-07 loss: 0.0281 (0.0312) time: 2.6633 data: 0.0062 max mem: 33369 +Epoch: [39] [1210/1319] eta: 0:04:48 lr: 1.9009779355624344e-07 loss: 0.0262 (0.0311) time: 2.6548 data: 0.0063 max mem: 33369 +Epoch: [39] [1220/1319] eta: 0:04:21 lr: 1.7418035215766808e-07 loss: 0.0262 (0.0311) time: 2.6273 data: 0.0063 max mem: 33369 +Epoch: [39] [1230/1319] eta: 0:03:55 lr: 1.5809935607220197e-07 loss: 0.0257 (0.0310) time: 2.6137 data: 0.0062 max mem: 33369 +Epoch: [39] [1240/1319] eta: 0:03:28 lr: 1.4183415922236583e-07 loss: 0.0257 (0.0310) time: 2.6265 data: 0.0063 max mem: 33369 +Epoch: [39] [1250/1319] eta: 0:03:02 lr: 1.2535848000328487e-07 loss: 0.0301 (0.0310) time: 2.6671 data: 0.0063 max mem: 33369 +Epoch: [39] [1260/1319] eta: 0:02:35 lr: 1.0863778202227116e-07 loss: 0.0301 (0.0310) time: 2.6642 data: 0.0063 max mem: 33369 +Epoch: [39] [1270/1319] eta: 0:02:09 lr: 9.162475150165058e-08 loss: 0.0294 (0.0310) time: 2.6388 data: 0.0063 max mem: 33369 +Epoch: [39] [1280/1319] eta: 0:01:43 lr: 7.425076510067331e-08 loss: 0.0277 (0.0310) time: 2.6441 data: 0.0063 max mem: 33369 +Epoch: [39] [1290/1319] eta: 0:01:16 lr: 5.640763927216541e-08 loss: 0.0316 (0.0310) time: 2.6592 data: 0.0063 max mem: 33369 +Epoch: [39] [1300/1319] eta: 0:00:50 lr: 3.790015191412361e-08 loss: 0.0303 (0.0310) time: 2.6484 data: 0.0064 max mem: 33369 +Epoch: [39] [1310/1319] eta: 0:00:23 lr: 1.8267397722216235e-08 loss: 0.0277 (0.0310) time: 2.6214 data: 0.0064 max mem: 33369 +Epoch: [39] Total time: 0:58:07 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 2:02:02 time: 2.8459 data: 2.6952 max mem: 33369 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 100/2573] eta: 0:04:05 time: 0.0716 data: 0.0011 max mem: 33369 +Test: [ 200/2573] eta: 0:03:26 time: 0.0735 data: 0.0011 max mem: 33369 +Test: [ 300/2573] eta: 0:03:06 time: 0.0753 data: 0.0011 max mem: 33369 +Test: [ 400/2573] eta: 0:02:53 time: 0.0753 data: 0.0011 max mem: 33369 +Test: [ 500/2573] eta: 0:02:43 time: 0.0738 data: 0.0011 max mem: 33369 +Test: [ 600/2573] eta: 0:02:33 time: 0.0737 data: 0.0011 max mem: 33369 +Test: [ 700/2573] eta: 0:02:25 time: 0.0739 data: 0.0011 max mem: 33369 +Test: [ 800/2573] eta: 0:02:17 time: 0.0772 data: 0.0011 max mem: 33369 +Test: [ 900/2573] eta: 0:02:08 time: 0.0737 data: 0.0011 max mem: 33369 +Test: [1000/2573] eta: 0:02:00 time: 0.0739 data: 0.0011 max mem: 33369 +Test: [1100/2573] eta: 0:01:52 time: 0.0739 data: 0.0011 max mem: 33369 +Test: [1200/2573] eta: 0:01:44 time: 0.0739 data: 0.0011 max mem: 33369 +Test: [1300/2573] eta: 0:01:37 time: 0.0740 data: 0.0011 max mem: 33369 +Test: [1400/2573] eta: 0:01:29 time: 0.0723 data: 0.0011 max mem: 33369 +Test: [1500/2573] eta: 0:01:21 time: 0.0739 data: 0.0011 max mem: 33369 +Test: [1600/2573] eta: 0:01:13 time: 0.0772 data: 0.0011 max mem: 33369 +Test: [1700/2573] eta: 0:01:06 time: 0.0723 data: 0.0011 max mem: 33369 +Test: [1800/2573] eta: 0:00:58 time: 0.0756 data: 0.0011 max mem: 33369 +Test: [1900/2573] eta: 0:00:50 time: 0.0722 data: 0.0011 max mem: 33369 +Test: [2000/2573] eta: 0:00:43 time: 0.0740 data: 0.0011 max mem: 33369 +Test: [2100/2573] eta: 0:00:35 time: 0.0757 data: 0.0011 max mem: 33369 +Test: [2200/2573] eta: 0:00:28 time: 0.0755 data: 0.0011 max mem: 33369 +Test: [2300/2573] eta: 0:00:20 time: 0.0756 data: 0.0011 max mem: 33369 +Test: [2400/2573] eta: 0:00:12 time: 0.0708 data: 0.0011 max mem: 33369 +Test: [2500/2573] eta: 0:00:05 time: 0.0740 data: 0.0011 max mem: 33369 +Test: Total time: 0:03:13 +Final results: +Mean IoU is 65.10 + + precision@0.5 = 73.35 + precision@0.6 = 67.91 + precision@0.7 = 61.34 + precision@0.8 = 49.96 + precision@0.9 = 25.25 + overall IoU = 62.90 + +Average object IoU 65.09914819882013 +Overall IoU 62.90497589111328 +Better epoch: 39 + +Training time 1 day, 18:27:42 diff --git a/LAVT-RIS/logs/old/gref_m10_mg12_tmp010_4gpu_bs32_ang.log b/LAVT-RIS/logs/old/gref_m10_mg12_tmp010_4gpu_bs32_ang.log new file mode 100644 index 0000000000000000000000000000000000000000..66f70aa9d83bf6ec500e8394521efc4f4238fad1 --- /dev/null +++ b/LAVT-RIS/logs/old/gref_m10_mg12_tmp010_4gpu_bs32_ang.log @@ -0,0 +1,12099 @@ +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torch/distributed/launch.py:178: FutureWarning: The module torch.distributed.launch is deprecated +and will be removed in future. Use torchrun. +Note that --use_env is set by default in torchrun. +If your script expects `--local_rank` argument to be set, please +change it to read from `os.environ['LOCAL_RANK']` instead. See +https://pytorch.org/docs/stable/distributed.html#launch-utility for +further instructions + + warnings.warn( +WARNING:torch.distributed.run: +***************************************** +Setting OMP_NUM_THREADS environment variable for each process to be 1 in default, to avoid your system being overloaded, please further tune the variable for optimal performance in your application as needed. +***************************************** +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/timm/models/layers/__init__.py:48: FutureWarning: Importing from timm.models.layers is deprecated, please import via timm.layers + warnings.warn(f"Importing from {__name__} is deprecated, please import via timm.layers", FutureWarning) +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/timm/models/layers/__init__.py:48: FutureWarning: Importing from timm.models.layers is deprecated, please import via timm.layers + warnings.warn(f"Importing from {__name__} is deprecated, please import via timm.layers", FutureWarning) +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/timm/models/layers/__init__.py:48: FutureWarning: Importing from timm.models.layers is deprecated, please import via timm.layers + warnings.warn(f"Importing from {__name__} is deprecated, please import via timm.layers", FutureWarning) +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/timm/models/layers/__init__.py:48: FutureWarning: Importing from timm.models.layers is deprecated, please import via timm.layers + warnings.warn(f"Importing from {__name__} is deprecated, please import via timm.layers", FutureWarning) +RANK and WORLD_SIZE in environment: 3/4 +RANK and WORLD_SIZE in environment: 2/4 +RANK and WORLD_SIZE in environment: 0/4 +RANK and WORLD_SIZE in environment: 1/4 +Image size: 480 +loading dataset refcocog into memory... +creating index... +index created. +DONE (t=6.41s) +loading dataset refcocog into memory... +creating index... +index created. +DONE (t=5.29s) +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torch/functional.py:478: UserWarning: torch.meshgrid: in an upcoming release, it will be required to pass the indexing argument. (Triggered internally at ../aten/src/ATen/native/TensorShape.cpp:2894.) + return _VF.meshgrid(tensors, **kwargs) # type: ignore[attr-defined] +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torch/functional.py:478: UserWarning: torch.meshgrid: in an upcoming release, it will be required to pass the indexing argument. (Triggered internally at ../aten/src/ATen/native/TensorShape.cpp:2894.) + return _VF.meshgrid(tensors, **kwargs) # type: ignore[attr-defined] +local rank 0 / global rank 0 successfully built train dataset. +lavt_one +Window size 12! +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torch/functional.py:478: UserWarning: torch.meshgrid: in an upcoming release, it will be required to pass the indexing argument. (Triggered internally at ../aten/src/ATen/native/TensorShape.cpp:2894.) + return _VF.meshgrid(tensors, **kwargs) # type: ignore[attr-defined] +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torch/functional.py:478: UserWarning: torch.meshgrid: in an upcoming release, it will be required to pass the indexing argument. (Triggered internally at ../aten/src/ATen/native/TensorShape.cpp:2894.) + return _VF.meshgrid(tensors, **kwargs) # type: ignore[attr-defined] +Initializing Multi-modal Swin Transformer weights from ./pretrained_weights/swin_base_patch4_window12_384_22k.pth +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [0] [ 0/1319] eta: 5:03:58 lr: 4.9999147080313756e-05 loss: 0.6477 (0.6477) time: 13.8276 data: 3.6496 max mem: 20156 +Epoch: [0] [ 10/1319] eta: 1:21:13 lr: 4.999061779453083e-05 loss: 0.3886 (0.4136) time: 3.7229 data: 0.3370 max mem: 28287 +Epoch: [0] [ 20/1319] eta: 1:10:53 lr: 4.9982088347050674e-05 loss: 0.3494 (0.3695) time: 2.7468 data: 0.0058 max mem: 28287 +Epoch: [0] [ 30/1319] eta: 1:07:06 lr: 4.9973558737839576e-05 loss: 0.3008 (0.3484) time: 2.7945 data: 0.0065 max mem: 28287 +Epoch: [0] [ 40/1319] eta: 1:04:49 lr: 4.9965028966863786e-05 loss: 0.2797 (0.3309) time: 2.7965 data: 0.0067 max mem: 28287 +Epoch: [0] [ 50/1319] eta: 1:03:20 lr: 4.995649903408956e-05 loss: 0.2762 (0.3236) time: 2.7941 data: 0.0063 max mem: 28287 +Epoch: [0] [ 60/1319] eta: 1:01:54 lr: 4.9947968939483133e-05 loss: 0.2915 (0.3254) time: 2.7641 data: 0.0065 max mem: 28287 +Epoch: [0] [ 70/1319] eta: 1:00:53 lr: 4.993943868301072e-05 loss: 0.2915 (0.3183) time: 2.7473 data: 0.0067 max mem: 28287 +Epoch: [0] [ 80/1319] eta: 0:59:54 lr: 4.993090826463852e-05 loss: 0.2467 (0.3092) time: 2.7516 data: 0.0066 max mem: 28288 +Epoch: [0] [ 90/1319] eta: 0:59:05 lr: 4.9922377684332736e-05 loss: 0.2449 (0.3038) time: 2.7437 data: 0.0068 max mem: 28288 +Epoch: [0] [ 100/1319] eta: 0:58:19 lr: 4.991384694205954e-05 loss: 0.2479 (0.2989) time: 2.7463 data: 0.0069 max mem: 28288 +Epoch: [0] [ 110/1319] eta: 0:57:36 lr: 4.990531603778512e-05 loss: 0.2572 (0.2996) time: 2.7409 data: 0.0069 max mem: 28288 +Epoch: [0] [ 120/1319] eta: 0:56:55 lr: 4.98967849714756e-05 loss: 0.2609 (0.2968) time: 2.7369 data: 0.0069 max mem: 29995 +Epoch: [0] [ 130/1319] eta: 0:56:17 lr: 4.988825374309713e-05 loss: 0.2487 (0.2941) time: 2.7395 data: 0.0070 max mem: 29995 +Epoch: [0] [ 140/1319] eta: 0:55:39 lr: 4.987972235261584e-05 loss: 0.2366 (0.2903) time: 2.7377 data: 0.0070 max mem: 29995 +Epoch: [0] [ 150/1319] eta: 0:55:05 lr: 4.987119079999784e-05 loss: 0.2531 (0.2897) time: 2.7420 data: 0.0070 max mem: 29995 +Epoch: [0] [ 160/1319] eta: 0:54:27 lr: 4.986265908520923e-05 loss: 0.2388 (0.2865) time: 2.7236 data: 0.0070 max mem: 29995 +Epoch: [0] [ 170/1319] eta: 0:53:56 lr: 4.985412720821609e-05 loss: 0.2373 (0.2858) time: 2.7365 data: 0.0070 max mem: 29995 +Epoch: [0] [ 180/1319] eta: 0:53:25 lr: 4.984559516898449e-05 loss: 0.2336 (0.2827) time: 2.7748 data: 0.0071 max mem: 29995 +Epoch: [0] [ 190/1319] eta: 0:52:51 lr: 4.98370629674805e-05 loss: 0.2310 (0.2814) time: 2.7450 data: 0.0073 max mem: 29995 +Epoch: [0] [ 200/1319] eta: 0:52:18 lr: 4.982853060367015e-05 loss: 0.2488 (0.2796) time: 2.7218 data: 0.0072 max mem: 29995 +Epoch: [0] [ 210/1319] eta: 0:51:47 lr: 4.9819998077519475e-05 loss: 0.2427 (0.2786) time: 2.7347 data: 0.0071 max mem: 29996 +Epoch: [0] [ 220/1319] eta: 0:51:16 lr: 4.98114653889945e-05 loss: 0.2205 (0.2763) time: 2.7384 data: 0.0071 max mem: 29996 +Epoch: [0] [ 230/1319] eta: 0:50:47 lr: 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mem: 31677 +Epoch: [0] [ 550/1319] eta: 0:35:22 lr: 4.952979535246434e-05 loss: 0.2045 (0.2473) time: 2.7583 data: 0.0071 max mem: 31677 +Epoch: [0] [ 560/1319] eta: 0:34:54 lr: 4.952125712289576e-05 loss: 0.2082 (0.2469) time: 2.7427 data: 0.0069 max mem: 31677 +Epoch: [0] [ 570/1319] eta: 0:34:27 lr: 4.9512718729754866e-05 loss: 0.2200 (0.2467) time: 2.7494 data: 0.0070 max mem: 31677 +Epoch: [0] [ 580/1319] eta: 0:33:59 lr: 4.9504180173007175e-05 loss: 0.2196 (0.2462) time: 2.7576 data: 0.0069 max mem: 31677 +Epoch: [0] [ 590/1319] eta: 0:33:31 lr: 4.9495641452618194e-05 loss: 0.2033 (0.2458) time: 2.7384 data: 0.0070 max mem: 31677 +Epoch: [0] [ 600/1319] eta: 0:33:03 lr: 4.948710256855343e-05 loss: 0.2005 (0.2450) time: 2.7513 data: 0.0070 max mem: 31677 +Epoch: [0] [ 610/1319] eta: 0:32:36 lr: 4.9478563520778356e-05 loss: 0.2189 (0.2456) time: 2.7639 data: 0.0073 max mem: 31677 +Epoch: [0] [ 620/1319] eta: 0:32:08 lr: 4.947002430925844e-05 loss: 0.2665 (0.2458) time: 2.7506 data: 0.0075 max mem: 31677 +Epoch: [0] [ 630/1319] eta: 0:31:40 lr: 4.946148493395914e-05 loss: 0.2302 (0.2457) time: 2.7541 data: 0.0074 max mem: 31677 +Epoch: [0] [ 640/1319] eta: 0:31:13 lr: 4.945294539484589e-05 loss: 0.2196 (0.2452) time: 2.7450 data: 0.0072 max mem: 31677 +Epoch: [0] [ 650/1319] eta: 0:30:44 lr: 4.944440569188412e-05 loss: 0.2053 (0.2445) time: 2.6968 data: 0.0069 max mem: 31677 +Epoch: [0] [ 660/1319] eta: 0:30:15 lr: 4.943586582503924e-05 loss: 0.2070 (0.2443) time: 2.6394 data: 0.0069 max mem: 31677 +Epoch: [0] [ 670/1319] eta: 0:29:46 lr: 4.942732579427665e-05 loss: 0.2216 (0.2442) time: 2.6297 data: 0.0069 max mem: 31677 +Epoch: [0] [ 680/1319] eta: 0:29:18 lr: 4.941878559956172e-05 loss: 0.2149 (0.2436) time: 2.6423 data: 0.0068 max mem: 31677 +Epoch: [0] [ 690/1319] eta: 0:28:49 lr: 4.941024524085985e-05 loss: 0.2149 (0.2436) time: 2.6159 data: 0.0067 max mem: 31677 +Epoch: [0] [ 700/1319] eta: 0:28:20 lr: 4.940170471813637e-05 loss: 0.2114 (0.2433) time: 2.6092 data: 0.0066 max mem: 31677 +Epoch: [0] [ 710/1319] eta: 0:27:53 lr: 4.939316403135663e-05 loss: 0.2088 (0.2433) time: 2.7199 data: 0.0071 max mem: 31677 +Epoch: [0] [ 720/1319] eta: 0:27:27 lr: 4.938462318048596e-05 loss: 0.2179 (0.2430) time: 2.8299 data: 0.0075 max mem: 31677 +Epoch: [0] [ 730/1319] eta: 0:26:59 lr: 4.937608216548967e-05 loss: 0.1907 (0.2422) time: 2.8168 data: 0.0073 max mem: 31677 +Epoch: [0] [ 740/1319] eta: 0:26:32 lr: 4.936754098633307e-05 loss: 0.1922 (0.2422) time: 2.7816 data: 0.0070 max mem: 31677 +Epoch: [0] [ 750/1319] eta: 0:26:05 lr: 4.935899964298143e-05 loss: 0.1922 (0.2414) time: 2.7629 data: 0.0070 max mem: 31677 +Epoch: [0] [ 760/1319] eta: 0:25:37 lr: 4.9350458135400046e-05 loss: 0.1872 (0.2409) time: 2.7715 data: 0.0072 max mem: 31677 +Epoch: [0] [ 770/1319] eta: 0:25:10 lr: 4.934191646355415e-05 loss: 0.1977 (0.2407) time: 2.7619 data: 0.0071 max mem: 31677 +Epoch: [0] [ 780/1319] eta: 0:24:42 lr: 4.9333374627409e-05 loss: 0.2035 (0.2403) time: 2.7362 data: 0.0070 max mem: 31677 +Epoch: [0] [ 790/1319] eta: 0:24:15 lr: 4.932483262692982e-05 loss: 0.2035 (0.2401) time: 2.7293 data: 0.0072 max mem: 31677 +Epoch: [0] [ 800/1319] eta: 0:23:47 lr: 4.931629046208183e-05 loss: 0.2064 (0.2397) time: 2.7427 data: 0.0071 max mem: 31677 +Epoch: [0] [ 810/1319] eta: 0:23:19 lr: 4.9307748132830237e-05 loss: 0.1969 (0.2394) time: 2.7451 data: 0.0068 max mem: 31677 +Epoch: [0] [ 820/1319] eta: 0:22:52 lr: 4.929920563914022e-05 loss: 0.2151 (0.2392) time: 2.7249 data: 0.0068 max mem: 31677 +Epoch: [0] [ 830/1319] eta: 0:22:24 lr: 4.929066298097696e-05 loss: 0.2134 (0.2387) time: 2.7130 data: 0.0069 max mem: 31677 +Epoch: [0] [ 840/1319] eta: 0:21:57 lr: 4.928212015830561e-05 loss: 0.1835 (0.2381) time: 2.7288 data: 0.0069 max mem: 31677 +Epoch: [0] [ 850/1319] eta: 0:21:29 lr: 4.927357717109131e-05 loss: 0.1815 (0.2378) time: 2.7478 data: 0.0069 max mem: 31677 +Epoch: [0] [ 860/1319] eta: 0:21:01 lr: 4.926503401929921e-05 loss: 0.1989 (0.2375) time: 2.7291 data: 0.0070 max mem: 31677 +Epoch: [0] [ 870/1319] eta: 0:20:34 lr: 4.925649070289441e-05 loss: 0.2001 (0.2373) time: 2.7056 data: 0.0072 max mem: 31677 +Epoch: [0] [ 880/1319] eta: 0:20:06 lr: 4.9247947221842024e-05 loss: 0.2137 (0.2371) time: 2.7320 data: 0.0073 max mem: 31677 +Epoch: [0] [ 890/1319] eta: 0:19:39 lr: 4.923940357610714e-05 loss: 0.1880 (0.2366) time: 2.7446 data: 0.0072 max mem: 31677 +Epoch: [0] [ 900/1319] eta: 0:19:11 lr: 4.9230859765654824e-05 loss: 0.1863 (0.2362) time: 2.7410 data: 0.0073 max mem: 31677 +Epoch: [0] [ 910/1319] eta: 0:18:44 lr: 4.922231579045014e-05 loss: 0.1796 (0.2355) time: 2.7488 data: 0.0074 max mem: 31677 +Epoch: [0] [ 920/1319] eta: 0:18:16 lr: 4.921377165045815e-05 loss: 0.1867 (0.2353) time: 2.7457 data: 0.0074 max mem: 31677 +Epoch: [0] [ 930/1319] eta: 0:17:49 lr: 4.9205227345643864e-05 loss: 0.2064 (0.2351) time: 2.7519 data: 0.0073 max mem: 31677 +Epoch: [0] [ 940/1319] eta: 0:17:21 lr: 4.919668287597232e-05 loss: 0.2023 (0.2353) time: 2.7243 data: 0.0073 max mem: 31677 +Epoch: [0] [ 950/1319] eta: 0:16:53 lr: 4.918813824140851e-05 loss: 0.2108 (0.2350) time: 2.7136 data: 0.0072 max mem: 31677 +Epoch: [0] [ 960/1319] eta: 0:16:26 lr: 4.9179593441917424e-05 loss: 0.1934 (0.2347) time: 2.7306 data: 0.0071 max mem: 31677 +Epoch: [0] [ 970/1319] eta: 0:15:58 lr: 4.917104847746404e-05 loss: 0.1947 (0.2343) time: 2.7348 data: 0.0072 max mem: 31677 +Epoch: [0] [ 980/1319] eta: 0:15:31 lr: 4.916250334801333e-05 loss: 0.1947 (0.2341) time: 2.7425 data: 0.0071 max mem: 31677 +Epoch: [0] [ 990/1319] eta: 0:15:03 lr: 4.915395805353022e-05 loss: 0.1819 (0.2336) time: 2.7231 data: 0.0069 max mem: 31677 +Epoch: [0] [1000/1319] eta: 0:14:35 lr: 4.9145412593979664e-05 loss: 0.1844 (0.2333) time: 2.6749 data: 0.0069 max mem: 31677 +Epoch: [0] [1010/1319] eta: 0:14:08 lr: 4.913686696932656e-05 loss: 0.1954 (0.2329) time: 2.6525 data: 0.0069 max mem: 31677 +Epoch: [0] [1020/1319] eta: 0:13:40 lr: 4.9128321179535836e-05 loss: 0.1811 (0.2325) time: 2.6497 data: 0.0066 max mem: 31677 +Epoch: [0] [1030/1319] eta: 0:13:12 lr: 4.911977522457237e-05 loss: 0.1836 (0.2323) time: 2.6636 data: 0.0067 max mem: 31677 +Epoch: [0] [1040/1319] eta: 0:12:45 lr: 4.9111229104401044e-05 loss: 0.1999 (0.2322) time: 2.6682 data: 0.0068 max mem: 31677 +Epoch: [0] [1050/1319] eta: 0:12:17 lr: 4.910268281898671e-05 loss: 0.1999 (0.2320) time: 2.6985 data: 0.0068 max mem: 31677 +Epoch: [0] [1060/1319] eta: 0:11:50 lr: 4.9094136368294215e-05 loss: 0.2007 (0.2318) time: 2.7701 data: 0.0070 max mem: 31677 +Epoch: [0] [1070/1319] eta: 0:11:23 lr: 4.90855897522884e-05 loss: 0.1969 (0.2315) time: 2.8074 data: 0.0072 max mem: 31677 +Epoch: [0] [1080/1319] eta: 0:10:55 lr: 4.907704297093409e-05 loss: 0.1758 (0.2309) time: 2.7657 data: 0.0070 max mem: 31677 +Epoch: [0] [1090/1319] eta: 0:10:28 lr: 4.906849602419608e-05 loss: 0.1770 (0.2309) time: 2.7174 data: 0.0071 max mem: 31677 +Epoch: [0] [1100/1319] eta: 0:10:00 lr: 4.905994891203916e-05 loss: 0.2094 (0.2308) time: 2.7266 data: 0.0072 max mem: 31677 +Epoch: [0] [1110/1319] eta: 0:09:33 lr: 4.905140163442811e-05 loss: 0.2100 (0.2306) time: 2.7582 data: 0.0072 max mem: 31677 +Epoch: [0] [1120/1319] eta: 0:09:05 lr: 4.904285419132769e-05 loss: 0.1831 (0.2302) time: 2.7648 data: 0.0072 max mem: 31677 +Epoch: [0] [1130/1319] eta: 0:08:38 lr: 4.903430658270266e-05 loss: 0.1846 (0.2301) time: 2.7451 data: 0.0070 max mem: 31677 +Epoch: [0] [1140/1319] eta: 0:08:11 lr: 4.902575880851773e-05 loss: 0.1901 (0.2298) time: 2.7160 data: 0.0072 max mem: 31677 +Epoch: [0] [1150/1319] eta: 0:07:43 lr: 4.9017210868737634e-05 loss: 0.1705 (0.2293) time: 2.7042 data: 0.0073 max mem: 31677 +Epoch: [0] [1160/1319] eta: 0:07:16 lr: 4.900866276332707e-05 loss: 0.1730 (0.2290) time: 2.7277 data: 0.0072 max mem: 31677 +Epoch: [0] [1170/1319] eta: 0:06:48 lr: 4.9000114492250734e-05 loss: 0.1838 (0.2286) time: 2.7449 data: 0.0071 max mem: 31677 +Epoch: [0] [1180/1319] eta: 0:06:21 lr: 4.8991566055473306e-05 loss: 0.1838 (0.2283) time: 2.7527 data: 0.0071 max mem: 31677 +Epoch: [0] [1190/1319] eta: 0:05:53 lr: 4.8983017452959435e-05 loss: 0.1777 (0.2280) time: 2.7479 data: 0.0070 max mem: 31677 +Epoch: [0] [1200/1319] eta: 0:05:26 lr: 4.8974468684673776e-05 loss: 0.2064 (0.2281) time: 2.7365 data: 0.0069 max mem: 31677 +Epoch: [0] [1210/1319] eta: 0:04:58 lr: 4.896591975058095e-05 loss: 0.2029 (0.2277) time: 2.7348 data: 0.0072 max mem: 31677 +Epoch: [0] [1220/1319] eta: 0:04:31 lr: 4.89573706506456e-05 loss: 0.1909 (0.2275) time: 2.7362 data: 0.0073 max mem: 31677 +Epoch: [0] [1230/1319] eta: 0:04:04 lr: 4.89488213848323e-05 loss: 0.1909 (0.2274) time: 2.7367 data: 0.0072 max mem: 31677 +Epoch: [0] [1240/1319] eta: 0:03:36 lr: 4.894027195310566e-05 loss: 0.1841 (0.2271) time: 2.7370 data: 0.0071 max mem: 31677 +Epoch: [0] [1250/1319] eta: 0:03:09 lr: 4.893172235543025e-05 loss: 0.1841 (0.2270) time: 2.7319 data: 0.0072 max mem: 31677 +Epoch: [0] [1260/1319] eta: 0:02:41 lr: 4.892317259177062e-05 loss: 0.2006 (0.2269) time: 2.7186 data: 0.0073 max mem: 31677 +Epoch: [0] [1270/1319] eta: 0:02:14 lr: 4.8914622662091334e-05 loss: 0.1943 (0.2267) time: 2.7154 data: 0.0072 max mem: 31677 +Epoch: [0] [1280/1319] eta: 0:01:46 lr: 4.890607256635692e-05 loss: 0.1919 (0.2265) time: 2.7180 data: 0.0071 max mem: 31677 +Epoch: [0] [1290/1319] eta: 0:01:19 lr: 4.8897522304531876e-05 loss: 0.1868 (0.2262) time: 2.7174 data: 0.0070 max mem: 31677 +Epoch: [0] [1300/1319] eta: 0:00:52 lr: 4.888897187658072e-05 loss: 0.1989 (0.2260) time: 2.7051 data: 0.0070 max mem: 31677 +Epoch: [0] [1310/1319] eta: 0:00:24 lr: 4.888042128246795e-05 loss: 0.1989 (0.2258) time: 2.7250 data: 0.0070 max mem: 31677 +Epoch: [0] Total time: 1:00:16 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 2:06:08 time: 2.9414 data: 2.8080 max mem: 31677 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 100/2573] eta: 0:04:13 time: 0.0718 data: 0.0012 max mem: 31677 +Test: [ 200/2573] eta: 0:03:30 time: 0.0733 data: 0.0012 max mem: 31677 +Test: [ 300/2573] eta: 0:03:08 time: 0.0750 data: 0.0012 max mem: 31677 +Test: [ 400/2573] eta: 0:02:55 time: 0.0747 data: 0.0011 max mem: 31677 +Test: [ 500/2573] eta: 0:02:43 time: 0.0732 data: 0.0011 max mem: 31677 +Test: [ 600/2573] eta: 0:02:34 time: 0.0733 data: 0.0011 max mem: 31677 +Test: [ 700/2573] eta: 0:02:25 time: 0.0735 data: 0.0011 max mem: 31677 +Test: [ 800/2573] eta: 0:02:17 time: 0.0765 data: 0.0011 max mem: 31677 +Test: [ 900/2573] eta: 0:02:08 time: 0.0733 data: 0.0011 max mem: 31677 +Test: [1000/2573] eta: 0:02:00 time: 0.0732 data: 0.0011 max mem: 31677 +Test: [1100/2573] eta: 0:01:52 time: 0.0732 data: 0.0011 max mem: 31677 +Test: [1200/2573] eta: 0:01:44 time: 0.0734 data: 0.0011 max mem: 31677 +Test: [1300/2573] eta: 0:01:36 time: 0.0734 data: 0.0011 max mem: 31677 +Test: [1400/2573] eta: 0:01:28 time: 0.0719 data: 0.0011 max mem: 31677 +Test: [1500/2573] eta: 0:01:21 time: 0.0735 data: 0.0011 max mem: 31677 +Test: [1600/2573] eta: 0:01:13 time: 0.0768 data: 0.0011 max mem: 31677 +Test: [1700/2573] eta: 0:01:05 time: 0.0717 data: 0.0011 max mem: 31677 +Test: [1800/2573] eta: 0:00:58 time: 0.0753 data: 0.0011 max mem: 31677 +Test: [1900/2573] eta: 0:00:50 time: 0.0719 data: 0.0011 max mem: 31677 +Test: [2000/2573] eta: 0:00:42 time: 0.0735 data: 0.0011 max mem: 31677 +Test: [2100/2573] eta: 0:00:35 time: 0.0751 data: 0.0010 max mem: 31677 +Test: [2200/2573] eta: 0:00:27 time: 0.0753 data: 0.0011 max mem: 31677 +Test: [2300/2573] eta: 0:00:20 time: 0.0753 data: 0.0011 max mem: 31677 +Test: [2400/2573] eta: 0:00:12 time: 0.0703 data: 0.0011 max mem: 31677 +Test: [2500/2573] eta: 0:00:05 time: 0.0740 data: 0.0011 max mem: 31677 +Test: Total time: 0:03:12 +Final results: +Mean IoU is 29.92 + + precision@0.5 = 28.12 + precision@0.6 = 20.89 + precision@0.7 = 13.58 + precision@0.8 = 7.21 + precision@0.9 = 1.53 + overall IoU = 36.67 + +Average object IoU 29.921293941336312 +Overall IoU 36.66654968261719 +Better epoch: 0 + +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [1] [ 0/1319] eta: 1:41:15 lr: 4.8872725605668895e-05 loss: 0.1753 (0.1753) time: 4.6065 data: 1.6517 max mem: 31677 +Epoch: [1] [ 10/1319] eta: 1:05:47 lr: 4.886417469575114e-05 loss: 0.2014 (0.1996) time: 3.0158 data: 0.1559 max mem: 31677 +Epoch: [1] [ 20/1319] eta: 1:03:09 lr: 4.88556236195687e-05 loss: 0.2014 (0.1919) time: 2.8328 data: 0.0062 max mem: 31677 +Epoch: [1] [ 30/1319] eta: 1:01:41 lr: 4.884707237708599e-05 loss: 0.1697 (0.1875) time: 2.7921 data: 0.0065 max mem: 31677 +Epoch: [1] [ 40/1319] eta: 1:00:18 lr: 4.883852096826744e-05 loss: 0.1791 (0.1944) time: 2.7360 data: 0.0069 max mem: 31677 +Epoch: [1] [ 50/1319] eta: 0:59:22 lr: 4.882996939307746e-05 loss: 0.1975 (0.1938) time: 2.7073 data: 0.0071 max mem: 31677 +Epoch: [1] [ 60/1319] eta: 0:58:41 lr: 4.882141765148041e-05 loss: 0.1802 (0.1936) time: 2.7329 data: 0.0069 max mem: 31677 +Epoch: [1] [ 70/1319] eta: 0:58:07 lr: 4.881286574344069e-05 loss: 0.1732 (0.1925) time: 2.7542 data: 0.0067 max mem: 31677 +Epoch: [1] [ 80/1319] eta: 0:57:28 lr: 4.8804313668922646e-05 loss: 0.1752 (0.1927) time: 2.7394 data: 0.0068 max mem: 31677 +Epoch: [1] [ 90/1319] eta: 0:57:06 lr: 4.879576142789063e-05 loss: 0.1760 (0.1911) time: 2.7740 data: 0.0068 max mem: 31677 +Epoch: [1] [ 100/1319] eta: 0:56:38 lr: 4.878720902030896e-05 loss: 0.1786 (0.1916) time: 2.8058 data: 0.0070 max mem: 31677 +Epoch: [1] [ 110/1319] eta: 0:56:06 lr: 4.877865644614197e-05 loss: 0.1767 (0.1897) time: 2.7661 data: 0.0072 max mem: 31677 +Epoch: [1] [ 120/1319] eta: 0:55:33 lr: 4.877010370535394e-05 loss: 0.1767 (0.1909) time: 2.7435 data: 0.0071 max mem: 31677 +Epoch: [1] [ 130/1319] eta: 0:55:03 lr: 4.8761550797909164e-05 loss: 0.1893 (0.1901) time: 2.7456 data: 0.0070 max mem: 31677 +Epoch: [1] [ 140/1319] eta: 0:54:32 lr: 4.875299772377192e-05 loss: 0.1855 (0.1902) time: 2.7465 data: 0.0069 max mem: 31677 +Epoch: [1] [ 150/1319] eta: 0:54:01 lr: 4.874444448290645e-05 loss: 0.1855 (0.1904) time: 2.7378 data: 0.0068 max mem: 31677 +Epoch: [1] [ 160/1319] eta: 0:53:29 lr: 4.873589107527701e-05 loss: 0.1768 (0.1896) time: 2.7272 data: 0.0069 max mem: 31677 +Epoch: [1] [ 170/1319] eta: 0:52:59 lr: 4.872733750084782e-05 loss: 0.1828 (0.1905) time: 2.7257 data: 0.0072 max mem: 31677 +Epoch: [1] [ 180/1319] eta: 0:52:30 lr: 4.871878375958309e-05 loss: 0.2048 (0.1911) time: 2.7382 data: 0.0071 max mem: 31677 +Epoch: [1] [ 190/1319] eta: 0:52:02 lr: 4.871022985144703e-05 loss: 0.1792 (0.1906) time: 2.7520 data: 0.0068 max mem: 31677 +Epoch: [1] [ 200/1319] eta: 0:51:33 lr: 4.870167577640381e-05 loss: 0.1942 (0.1926) time: 2.7517 data: 0.0068 max mem: 31677 +Epoch: [1] [ 210/1319] eta: 0:51:04 lr: 4.869312153441761e-05 loss: 0.1942 (0.1929) time: 2.7369 data: 0.0070 max mem: 31677 +Epoch: [1] [ 220/1319] eta: 0:50:35 lr: 4.868456712545258e-05 loss: 0.1690 (0.1932) time: 2.7357 data: 0.0071 max mem: 31677 +Epoch: [1] [ 230/1319] eta: 0:50:06 lr: 4.8676012549472854e-05 loss: 0.1796 (0.1926) time: 2.7396 data: 0.0071 max mem: 31677 +Epoch: [1] [ 240/1319] eta: 0:49:38 lr: 4.866745780644256e-05 loss: 0.1714 (0.1914) time: 2.7465 data: 0.0069 max mem: 31677 +Epoch: [1] [ 250/1319] eta: 0:49:11 lr: 4.865890289632581e-05 loss: 0.1733 (0.1912) time: 2.7615 data: 0.0069 max mem: 31677 +Epoch: [1] [ 260/1319] eta: 0:48:43 lr: 4.8650347819086694e-05 loss: 0.1810 (0.1912) time: 2.7610 data: 0.0071 max mem: 31677 +Epoch: [1] [ 270/1319] eta: 0:48:14 lr: 4.864179257468931e-05 loss: 0.1763 (0.1908) time: 2.7411 data: 0.0070 max mem: 31677 +Epoch: [1] [ 280/1319] eta: 0:47:49 lr: 4.8633237163097687e-05 loss: 0.1796 (0.1913) time: 2.7691 data: 0.0070 max mem: 31678 +Epoch: [1] [ 290/1319] eta: 0:47:15 lr: 4.862468158427592e-05 loss: 0.1848 (0.1917) time: 2.7040 data: 0.0070 max mem: 31678 +Epoch: [1] [ 300/1319] eta: 0:46:44 lr: 4.861612583818801e-05 loss: 0.1795 (0.1925) time: 2.6238 data: 0.0068 max mem: 31678 +Epoch: [1] [ 310/1319] eta: 0:46:12 lr: 4.860756992479799e-05 loss: 0.1768 (0.1930) time: 2.6290 data: 0.0068 max mem: 31678 +Epoch: [1] [ 320/1319] eta: 0:45:41 lr: 4.859901384406988e-05 loss: 0.1914 (0.1928) time: 2.6308 data: 0.0069 max mem: 31678 +Epoch: [1] [ 330/1319] eta: 0:45:10 lr: 4.8590457595967656e-05 loss: 0.1914 (0.1934) time: 2.6270 data: 0.0067 max mem: 31678 +Epoch: [1] [ 340/1319] eta: 0:44:39 lr: 4.85819011804553e-05 loss: 0.1698 (0.1924) time: 2.6144 data: 0.0066 max mem: 31678 +Epoch: [1] [ 350/1319] eta: 0:44:11 lr: 4.8573344597496775e-05 loss: 0.1691 (0.1926) time: 2.6627 data: 0.0067 max mem: 31678 +Epoch: [1] [ 360/1319] eta: 0:43:46 lr: 4.856478784705602e-05 loss: 0.1793 (0.1923) time: 2.7695 data: 0.0071 max mem: 31678 +Epoch: [1] [ 370/1319] eta: 0:43:20 lr: 4.8556230929096985e-05 loss: 0.1858 (0.1927) time: 2.8229 data: 0.0074 max mem: 31678 +Epoch: [1] [ 380/1319] eta: 0:42:53 lr: 4.854767384358357e-05 loss: 0.1879 (0.1923) time: 2.7733 data: 0.0074 max mem: 31678 +Epoch: [1] [ 390/1319] eta: 0:42:27 lr: 4.8539116590479686e-05 loss: 0.1863 (0.1925) time: 2.7705 data: 0.0074 max mem: 31678 +Epoch: [1] [ 400/1319] eta: 0:42:00 lr: 4.8530559169749225e-05 loss: 0.1637 (0.1918) time: 2.7728 data: 0.0071 max mem: 31678 +Epoch: [1] [ 410/1319] eta: 0:41:33 lr: 4.852200158135605e-05 loss: 0.1676 (0.1914) time: 2.7644 data: 0.0072 max mem: 31678 +Epoch: [1] [ 420/1319] eta: 0:41:06 lr: 4.851344382526403e-05 loss: 0.1676 (0.1910) time: 2.7632 data: 0.0071 max mem: 31678 +Epoch: [1] [ 430/1319] eta: 0:40:38 lr: 4.850488590143701e-05 loss: 0.1779 (0.1910) time: 2.7490 data: 0.0067 max mem: 31678 +Epoch: [1] [ 440/1319] eta: 0:40:12 lr: 4.84963278098388e-05 loss: 0.1671 (0.1908) time: 2.7686 data: 0.0067 max mem: 31678 +Epoch: [1] [ 450/1319] eta: 0:39:45 lr: 4.8487769550433236e-05 loss: 0.1617 (0.1908) time: 2.7928 data: 0.0067 max mem: 31678 +Epoch: [1] [ 460/1319] eta: 0:39:19 lr: 4.84792111231841e-05 loss: 0.1706 (0.1900) time: 2.7987 data: 0.0068 max mem: 31678 +Epoch: [1] [ 470/1319] eta: 0:38:51 lr: 4.847065252805519e-05 loss: 0.1734 (0.1901) time: 2.7704 data: 0.0069 max mem: 31678 +Epoch: [1] [ 480/1319] eta: 0:38:25 lr: 4.846209376501027e-05 loss: 0.1805 (0.1900) time: 2.7865 data: 0.0067 max mem: 31678 +Epoch: [1] [ 490/1319] eta: 0:37:58 lr: 4.8453534834013074e-05 loss: 0.1805 (0.1904) time: 2.8008 data: 0.0067 max mem: 31678 +Epoch: [1] [ 500/1319] eta: 0:37:31 lr: 4.844497573502737e-05 loss: 0.1821 (0.1906) time: 2.7641 data: 0.0066 max mem: 31678 +Epoch: [1] [ 510/1319] eta: 0:37:04 lr: 4.8436416468016874e-05 loss: 0.1787 (0.1906) time: 2.7694 data: 0.0065 max mem: 31678 +Epoch: [1] [ 520/1319] eta: 0:36:37 lr: 4.8427857032945285e-05 loss: 0.1747 (0.1905) time: 2.7694 data: 0.0066 max mem: 31678 +Epoch: [1] [ 530/1319] eta: 0:36:09 lr: 4.841929742977631e-05 loss: 0.1736 (0.1904) time: 2.7608 data: 0.0066 max mem: 31678 +Epoch: [1] [ 540/1319] eta: 0:35:42 lr: 4.841073765847362e-05 loss: 0.1916 (0.1909) time: 2.7638 data: 0.0067 max mem: 31678 +Epoch: [1] [ 550/1319] eta: 0:35:15 lr: 4.840217771900089e-05 loss: 0.1954 (0.1908) time: 2.7743 data: 0.0069 max mem: 31678 +Epoch: [1] [ 560/1319] eta: 0:34:48 lr: 4.8393617611321754e-05 loss: 0.1893 (0.1908) time: 2.7704 data: 0.0070 max mem: 31678 +Epoch: [1] [ 570/1319] eta: 0:34:21 lr: 4.838505733539985e-05 loss: 0.1708 (0.1912) time: 2.7774 data: 0.0070 max mem: 31678 +Epoch: [1] [ 580/1319] eta: 0:33:53 lr: 4.83764968911988e-05 loss: 0.1708 (0.1909) time: 2.7810 data: 0.0069 max mem: 31678 +Epoch: [1] [ 590/1319] eta: 0:33:26 lr: 4.836793627868222e-05 loss: 0.1714 (0.1906) time: 2.7593 data: 0.0068 max mem: 31678 +Epoch: [1] [ 600/1319] eta: 0:32:58 lr: 4.835937549781368e-05 loss: 0.1739 (0.1905) time: 2.7476 data: 0.0069 max mem: 31678 +Epoch: [1] [ 610/1319] eta: 0:32:30 lr: 4.835081454855677e-05 loss: 0.1691 (0.1902) time: 2.7272 data: 0.0069 max mem: 31678 +Epoch: [1] [ 620/1319] eta: 0:32:03 lr: 4.8342253430875026e-05 loss: 0.1580 (0.1901) time: 2.7486 data: 0.0070 max mem: 31678 +Epoch: [1] [ 630/1319] eta: 0:31:35 lr: 4.833369214473202e-05 loss: 0.1580 (0.1899) time: 2.7646 data: 0.0069 max mem: 31678 +Epoch: [1] [ 640/1319] eta: 0:31:06 lr: 4.832513069009127e-05 loss: 0.1498 (0.1894) time: 2.6784 data: 0.0068 max mem: 31678 +Epoch: [1] [ 650/1319] eta: 0:30:38 lr: 4.8316569066916287e-05 loss: 0.1552 (0.1894) time: 2.6457 data: 0.0067 max mem: 31678 +Epoch: [1] [ 660/1319] eta: 0:30:09 lr: 4.8308007275170564e-05 loss: 0.1793 (0.1894) time: 2.6476 data: 0.0068 max mem: 31678 +Epoch: [1] [ 670/1319] eta: 0:29:41 lr: 4.829944531481759e-05 loss: 0.1773 (0.1890) time: 2.6356 data: 0.0068 max mem: 31678 +Epoch: [1] [ 680/1319] eta: 0:29:12 lr: 4.8290883185820843e-05 loss: 0.1630 (0.1888) time: 2.6361 data: 0.0066 max mem: 31678 +Epoch: [1] [ 690/1319] eta: 0:28:44 lr: 4.828232088814377e-05 loss: 0.1748 (0.1887) time: 2.6080 data: 0.0068 max mem: 31678 +Epoch: [1] [ 700/1319] eta: 0:28:15 lr: 4.827375842174981e-05 loss: 0.1748 (0.1887) time: 2.6142 data: 0.0068 max mem: 31678 +Epoch: [1] [ 710/1319] eta: 0:27:47 lr: 4.826519578660238e-05 loss: 0.1685 (0.1887) time: 2.6447 data: 0.0067 max mem: 31678 +Epoch: [1] [ 720/1319] eta: 0:27:19 lr: 4.825663298266489e-05 loss: 0.1896 (0.1887) time: 2.6342 data: 0.0067 max mem: 31678 +Epoch: [1] [ 730/1319] eta: 0:26:52 lr: 4.824807000990074e-05 loss: 0.1590 (0.1883) time: 2.7080 data: 0.0071 max mem: 31678 +Epoch: [1] [ 740/1319] eta: 0:26:25 lr: 4.82395068682733e-05 loss: 0.1553 (0.1882) time: 2.7910 data: 0.0073 max mem: 31678 +Epoch: [1] [ 750/1319] eta: 0:25:58 lr: 4.823094355774595e-05 loss: 0.1794 (0.1882) time: 2.7764 data: 0.0072 max mem: 31678 +Epoch: [1] [ 760/1319] eta: 0:25:30 lr: 4.822238007828201e-05 loss: 0.1805 (0.1883) time: 2.7646 data: 0.0073 max mem: 31678 +Epoch: [1] [ 770/1319] eta: 0:25:03 lr: 4.8213816429844826e-05 loss: 0.1805 (0.1881) time: 2.7371 data: 0.0071 max mem: 31678 +Epoch: [1] [ 780/1319] eta: 0:24:36 lr: 4.8205252612397726e-05 loss: 0.1594 (0.1877) time: 2.7769 data: 0.0067 max mem: 31678 +Epoch: [1] [ 790/1319] eta: 0:24:09 lr: 4.8196688625903984e-05 loss: 0.1470 (0.1876) time: 2.7918 data: 0.0066 max mem: 31678 +Epoch: [1] [ 800/1319] eta: 0:23:42 lr: 4.8188124470326915e-05 loss: 0.1600 (0.1874) time: 2.7617 data: 0.0067 max mem: 31678 +Epoch: [1] [ 810/1319] eta: 0:23:14 lr: 4.8179560145629784e-05 loss: 0.1692 (0.1878) time: 2.7496 data: 0.0067 max mem: 31678 +Epoch: [1] [ 820/1319] eta: 0:22:47 lr: 4.817099565177583e-05 loss: 0.1867 (0.1879) time: 2.7453 data: 0.0066 max mem: 31678 +Epoch: [1] [ 830/1319] eta: 0:22:20 lr: 4.8162430988728305e-05 loss: 0.1725 (0.1878) time: 2.7472 data: 0.0066 max mem: 31678 +Epoch: [1] [ 840/1319] eta: 0:21:52 lr: 4.815386615645044e-05 loss: 0.1656 (0.1874) time: 2.7426 data: 0.0070 max mem: 31678 +Epoch: [1] [ 850/1319] eta: 0:21:25 lr: 4.814530115490545e-05 loss: 0.1574 (0.1873) time: 2.7526 data: 0.0071 max mem: 31678 +Epoch: [1] [ 860/1319] eta: 0:20:57 lr: 4.813673598405651e-05 loss: 0.1702 (0.1871) time: 2.7327 data: 0.0069 max mem: 31678 +Epoch: [1] [ 870/1319] eta: 0:20:30 lr: 4.812817064386682e-05 loss: 0.1605 (0.1868) time: 2.7402 data: 0.0070 max mem: 31678 +Epoch: [1] [ 880/1319] eta: 0:20:03 lr: 4.8119605134299526e-05 loss: 0.1521 (0.1864) time: 2.7812 data: 0.0070 max mem: 31678 +Epoch: [1] [ 890/1319] eta: 0:19:36 lr: 4.81110394553178e-05 loss: 0.1521 (0.1860) time: 2.7683 data: 0.0069 max mem: 31678 +Epoch: [1] [ 900/1319] eta: 0:19:08 lr: 4.810247360688475e-05 loss: 0.1580 (0.1860) time: 2.7478 data: 0.0070 max mem: 31678 +Epoch: [1] [ 910/1319] eta: 0:18:41 lr: 4.809390758896352e-05 loss: 0.1403 (0.1856) time: 2.7363 data: 0.0069 max mem: 31678 +Epoch: [1] [ 920/1319] eta: 0:18:13 lr: 4.808534140151719e-05 loss: 0.1611 (0.1858) time: 2.7438 data: 0.0070 max mem: 31678 +Epoch: [1] [ 930/1319] eta: 0:17:46 lr: 4.807677504450886e-05 loss: 0.1648 (0.1856) time: 2.7461 data: 0.0071 max mem: 31678 +Epoch: [1] [ 940/1319] eta: 0:17:19 lr: 4.806820851790161e-05 loss: 0.1648 (0.1856) time: 2.7502 data: 0.0071 max mem: 31678 +Epoch: [1] [ 950/1319] eta: 0:16:51 lr: 4.805964182165848e-05 loss: 0.1825 (0.1856) time: 2.7616 data: 0.0072 max mem: 31678 +Epoch: [1] [ 960/1319] eta: 0:16:24 lr: 4.8051074955742525e-05 loss: 0.1677 (0.1853) time: 2.7424 data: 0.0074 max mem: 31678 +Epoch: [1] [ 970/1319] eta: 0:15:56 lr: 4.804250792011677e-05 loss: 0.1702 (0.1855) time: 2.7511 data: 0.0071 max mem: 31678 +Epoch: [1] [ 980/1319] eta: 0:15:29 lr: 4.803394071474422e-05 loss: 0.1916 (0.1856) time: 2.7462 data: 0.0069 max mem: 31678 +Epoch: [1] [ 990/1319] eta: 0:15:02 lr: 4.802537333958788e-05 loss: 0.1786 (0.1856) time: 2.7341 data: 0.0069 max mem: 31678 +Epoch: [1] [1000/1319] eta: 0:14:34 lr: 4.801680579461071e-05 loss: 0.1786 (0.1857) time: 2.7808 data: 0.0069 max mem: 31678 +Epoch: [1] [1010/1319] eta: 0:14:07 lr: 4.80082380797757e-05 loss: 0.1911 (0.1858) time: 2.7395 data: 0.0070 max mem: 31678 +Epoch: [1] [1020/1319] eta: 0:13:39 lr: 4.79996701950458e-05 loss: 0.1923 (0.1860) time: 2.6587 data: 0.0068 max mem: 31678 +Epoch: [1] [1030/1319] eta: 0:13:11 lr: 4.799110214038392e-05 loss: 0.2043 (0.1862) time: 2.6654 data: 0.0067 max mem: 31678 +Epoch: [1] [1040/1319] eta: 0:12:44 lr: 4.7982533915752995e-05 loss: 0.2032 (0.1863) time: 2.6576 data: 0.0066 max mem: 31678 +Epoch: [1] [1050/1319] eta: 0:12:16 lr: 4.797396552111593e-05 loss: 0.1738 (0.1862) time: 2.6423 data: 0.0066 max mem: 31678 +Epoch: [1] [1060/1319] eta: 0:11:48 lr: 4.7965396956435596e-05 loss: 0.1570 (0.1860) time: 2.6362 data: 0.0065 max mem: 31678 +Epoch: [1] [1070/1319] eta: 0:11:21 lr: 4.795682822167489e-05 loss: 0.1641 (0.1861) time: 2.6610 data: 0.0068 max mem: 31678 +Epoch: [1] [1080/1319] eta: 0:10:54 lr: 4.794825931679665e-05 loss: 0.1869 (0.1863) time: 2.7487 data: 0.0071 max mem: 31678 +Epoch: [1] [1090/1319] eta: 0:10:26 lr: 4.7939690241763725e-05 loss: 0.1751 (0.1860) time: 2.7752 data: 0.0072 max mem: 31678 +Epoch: [1] [1100/1319] eta: 0:09:59 lr: 4.793112099653894e-05 loss: 0.1578 (0.1858) time: 2.7817 data: 0.0072 max mem: 31678 +Epoch: [1] [1110/1319] eta: 0:09:32 lr: 4.79225515810851e-05 loss: 0.1540 (0.1858) time: 2.8038 data: 0.0072 max mem: 31678 +Epoch: [1] [1120/1319] eta: 0:09:05 lr: 4.791398199536501e-05 loss: 0.1576 (0.1859) time: 2.7803 data: 0.0072 max mem: 31678 +Epoch: [1] [1130/1319] eta: 0:08:37 lr: 4.790541223934144e-05 loss: 0.1774 (0.1859) time: 2.7555 data: 0.0069 max mem: 31678 +Epoch: [1] [1140/1319] eta: 0:08:10 lr: 4.7896842312977156e-05 loss: 0.1883 (0.1861) time: 2.7345 data: 0.0070 max mem: 31678 +Epoch: [1] [1150/1319] eta: 0:07:42 lr: 4.788827221623491e-05 loss: 0.1732 (0.1860) time: 2.7698 data: 0.0069 max mem: 31678 +Epoch: [1] [1160/1319] eta: 0:07:15 lr: 4.787970194907743e-05 loss: 0.1709 (0.1860) time: 2.7697 data: 0.0067 max mem: 31678 +Epoch: [1] [1170/1319] eta: 0:06:48 lr: 4.787113151146744e-05 loss: 0.1711 (0.1858) time: 2.7255 data: 0.0068 max mem: 31678 +Epoch: [1] [1180/1319] eta: 0:06:20 lr: 4.786256090336764e-05 loss: 0.1773 (0.1858) time: 2.7393 data: 0.0069 max mem: 31678 +Epoch: [1] [1190/1319] eta: 0:05:53 lr: 4.7853990124740705e-05 loss: 0.1839 (0.1857) time: 2.7670 data: 0.0070 max mem: 31678 +Epoch: [1] [1200/1319] eta: 0:05:26 lr: 4.784541917554932e-05 loss: 0.1762 (0.1856) time: 2.7784 data: 0.0068 max mem: 31678 +Epoch: [1] [1210/1319] eta: 0:04:58 lr: 4.783684805575612e-05 loss: 0.1616 (0.1855) time: 2.7600 data: 0.0068 max mem: 31678 +Epoch: [1] [1220/1319] eta: 0:04:31 lr: 4.782827676532376e-05 loss: 0.1667 (0.1855) time: 2.7359 data: 0.0070 max mem: 31678 +Epoch: [1] [1230/1319] eta: 0:04:03 lr: 4.781970530421487e-05 loss: 0.1667 (0.1853) time: 2.7609 data: 0.0072 max mem: 31678 +Epoch: [1] [1240/1319] eta: 0:03:36 lr: 4.7811133672392044e-05 loss: 0.1544 (0.1851) time: 2.7676 data: 0.0074 max mem: 31678 +Epoch: [1] [1250/1319] eta: 0:03:09 lr: 4.780256186981787e-05 loss: 0.1544 (0.1850) time: 2.7515 data: 0.0072 max mem: 31678 +Epoch: [1] [1260/1319] eta: 0:02:41 lr: 4.779398989645494e-05 loss: 0.1750 (0.1850) time: 2.7423 data: 0.0069 max mem: 31678 +Epoch: [1] [1270/1319] eta: 0:02:14 lr: 4.778541775226581e-05 loss: 0.1769 (0.1849) time: 2.7266 data: 0.0070 max mem: 31678 +Epoch: [1] [1280/1319] eta: 0:01:46 lr: 4.777684543721302e-05 loss: 0.1640 (0.1847) time: 2.7290 data: 0.0071 max mem: 31678 +Epoch: [1] [1290/1319] eta: 0:01:19 lr: 4.776827295125911e-05 loss: 0.1455 (0.1845) time: 2.7233 data: 0.0072 max mem: 31678 +Epoch: [1] [1300/1319] eta: 0:00:52 lr: 4.775970029436657e-05 loss: 0.1336 (0.1842) time: 2.7263 data: 0.0069 max mem: 31678 +Epoch: [1] [1310/1319] eta: 0:00:24 lr: 4.7751127466497925e-05 loss: 0.1543 (0.1842) time: 2.7396 data: 0.0069 max mem: 31678 +Epoch: [1] Total time: 1:00:14 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 2:03:01 time: 2.8687 data: 2.7885 max mem: 31678 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 100/2573] eta: 0:04:07 time: 0.0721 data: 0.0011 max mem: 31678 +Test: [ 200/2573] eta: 0:03:27 time: 0.0733 data: 0.0012 max mem: 31678 +Test: [ 300/2573] eta: 0:03:07 time: 0.0749 data: 0.0011 max mem: 31678 +Test: [ 400/2573] eta: 0:02:53 time: 0.0748 data: 0.0011 max mem: 31678 +Test: [ 500/2573] eta: 0:02:43 time: 0.0739 data: 0.0012 max mem: 31678 +Test: [ 600/2573] eta: 0:02:33 time: 0.0739 data: 0.0012 max mem: 31678 +Test: [ 700/2573] eta: 0:02:25 time: 0.0739 data: 0.0012 max mem: 31678 +Test: [ 800/2573] eta: 0:02:17 time: 0.0775 data: 0.0011 max mem: 31678 +Test: [ 900/2573] eta: 0:02:09 time: 0.0743 data: 0.0012 max mem: 31678 +Test: [1000/2573] eta: 0:02:00 time: 0.0741 data: 0.0012 max mem: 31678 +Test: [1100/2573] eta: 0:01:52 time: 0.0736 data: 0.0011 max mem: 31678 +Test: [1200/2573] eta: 0:01:44 time: 0.0733 data: 0.0011 max mem: 31678 +Test: [1300/2573] eta: 0:01:37 time: 0.0741 data: 0.0011 max mem: 31678 +Test: [1400/2573] eta: 0:01:29 time: 0.0720 data: 0.0011 max mem: 31678 +Test: [1500/2573] eta: 0:01:21 time: 0.0737 data: 0.0011 max mem: 31678 +Test: [1600/2573] eta: 0:01:13 time: 0.0769 data: 0.0011 max mem: 31678 +Test: [1700/2573] eta: 0:01:06 time: 0.0719 data: 0.0010 max mem: 31678 +Test: [1800/2573] eta: 0:00:58 time: 0.0752 data: 0.0011 max mem: 31678 +Test: [1900/2573] eta: 0:00:50 time: 0.0719 data: 0.0011 max mem: 31678 +Test: [2000/2573] eta: 0:00:43 time: 0.0737 data: 0.0011 max mem: 31678 +Test: [2100/2573] eta: 0:00:35 time: 0.0753 data: 0.0011 max mem: 31678 +Test: [2200/2573] eta: 0:00:27 time: 0.0753 data: 0.0011 max mem: 31678 +Test: [2300/2573] eta: 0:00:20 time: 0.0753 data: 0.0011 max mem: 31678 +Test: [2400/2573] eta: 0:00:12 time: 0.0703 data: 0.0011 max mem: 31678 +Test: [2500/2573] eta: 0:00:05 time: 0.0736 data: 0.0011 max mem: 31678 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: Total time: 0:03:13 +Final results: +Mean IoU is 40.20 + + precision@0.5 = 40.81 + precision@0.6 = 32.25 + precision@0.7 = 23.37 + precision@0.8 = 14.38 + precision@0.9 = 3.88 + overall IoU = 44.00 + +Average object IoU 40.195143451007596 +Overall IoU 44.00050735473633 +Better epoch: 1 + +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [2] [ 0/1319] eta: 1:32:32 lr: 4.774341177520056e-05 loss: 0.1030 (0.1030) time: 4.2100 data: 1.4626 max mem: 31678 +Epoch: [2] [ 10/1319] eta: 1:00:19 lr: 4.773483862237391e-05 loss: 0.1798 (0.1775) time: 2.7647 data: 0.1383 max mem: 31678 +Epoch: [2] [ 20/1319] eta: 0:59:14 lr: 4.772626529846231e-05 loss: 0.1679 (0.1748) time: 2.6623 data: 0.0061 max mem: 31678 +Epoch: [2] [ 30/1319] eta: 0:59:09 lr: 4.771769180342819e-05 loss: 0.1428 (0.1697) time: 2.7475 data: 0.0068 max mem: 31678 +Epoch: [2] [ 40/1319] eta: 0:58:59 lr: 4.7709118137233964e-05 loss: 0.1426 (0.1645) time: 2.7998 data: 0.0072 max mem: 31678 +Epoch: [2] [ 50/1319] eta: 0:58:46 lr: 4.770054429984204e-05 loss: 0.1488 (0.1634) time: 2.8189 data: 0.0071 max mem: 31678 +Epoch: [2] [ 60/1319] eta: 0:58:19 lr: 4.769197029121481e-05 loss: 0.1466 (0.1621) time: 2.8045 data: 0.0068 max mem: 31678 +Epoch: [2] [ 70/1319] eta: 0:57:51 lr: 4.7683396111314645e-05 loss: 0.1600 (0.1683) time: 2.7803 data: 0.0068 max mem: 31678 +Epoch: [2] [ 80/1319] eta: 0:57:14 lr: 4.7674821760103904e-05 loss: 0.1600 (0.1656) time: 2.7502 data: 0.0069 max mem: 31678 +Epoch: [2] [ 90/1319] eta: 0:56:50 lr: 4.766624723754494e-05 loss: 0.1506 (0.1656) time: 2.7600 data: 0.0069 max mem: 31678 +Epoch: [2] [ 100/1319] eta: 0:56:22 lr: 4.7657672543600056e-05 loss: 0.1594 (0.1666) time: 2.7855 data: 0.0068 max mem: 31678 +Epoch: [2] [ 110/1319] eta: 0:55:55 lr: 4.764909767823158e-05 loss: 0.1593 (0.1663) time: 2.7775 data: 0.0068 max mem: 31678 +Epoch: [2] [ 120/1319] eta: 0:55:23 lr: 4.76405226414018e-05 loss: 0.1593 (0.1663) time: 2.7554 data: 0.0070 max mem: 31678 +Epoch: [2] [ 130/1319] eta: 0:54:55 lr: 4.7631947433073e-05 loss: 0.1532 (0.1652) time: 2.7506 data: 0.0070 max mem: 31678 +Epoch: [2] [ 140/1319] eta: 0:54:27 lr: 4.762337205320744e-05 loss: 0.1427 (0.1645) time: 2.7702 data: 0.0069 max mem: 31678 +Epoch: [2] [ 150/1319] eta: 0:53:57 lr: 4.7614796501767376e-05 loss: 0.1418 (0.1641) time: 2.7567 data: 0.0071 max mem: 31678 +Epoch: [2] [ 160/1319] eta: 0:53:31 lr: 4.760622077871502e-05 loss: 0.1680 (0.1649) time: 2.7644 data: 0.0071 max mem: 31678 +Epoch: [2] [ 170/1319] eta: 0:53:00 lr: 4.75976448840126e-05 loss: 0.1680 (0.1643) time: 2.7568 data: 0.0070 max mem: 31678 +Epoch: [2] [ 180/1319] eta: 0:52:31 lr: 4.7589068817622304e-05 loss: 0.1516 (0.1635) time: 2.7384 data: 0.0071 max mem: 31678 +Epoch: [2] [ 190/1319] eta: 0:52:02 lr: 4.758049257950633e-05 loss: 0.1373 (0.1641) time: 2.7406 data: 0.0070 max mem: 31678 +Epoch: [2] [ 200/1319] eta: 0:51:35 lr: 4.757191616962685e-05 loss: 0.1377 (0.1647) time: 2.7557 data: 0.0069 max mem: 31678 +Epoch: [2] [ 210/1319] eta: 0:51:10 lr: 4.756333958794601e-05 loss: 0.1563 (0.1641) time: 2.8011 data: 0.0071 max mem: 31678 +Epoch: [2] [ 220/1319] eta: 0:50:40 lr: 4.7554762834425936e-05 loss: 0.1498 (0.1639) time: 2.7740 data: 0.0073 max mem: 31678 +Epoch: [2] [ 230/1319] eta: 0:50:13 lr: 4.7546185909028754e-05 loss: 0.1578 (0.1649) time: 2.7524 data: 0.0072 max mem: 31678 +Epoch: [2] [ 240/1319] eta: 0:49:46 lr: 4.753760881171657e-05 loss: 0.1824 (0.1652) time: 2.7764 data: 0.0072 max mem: 31678 +Epoch: [2] [ 250/1319] eta: 0:49:17 lr: 4.7529031542451477e-05 loss: 0.1693 (0.1657) time: 2.7617 data: 0.0073 max mem: 31678 +Epoch: [2] [ 260/1319] eta: 0:48:51 lr: 4.7520454101195535e-05 loss: 0.1557 (0.1666) time: 2.7719 data: 0.0071 max mem: 31678 +Epoch: [2] [ 270/1319] eta: 0:48:24 lr: 4.751187648791081e-05 loss: 0.1526 (0.1661) time: 2.7872 data: 0.0071 max mem: 31678 +Epoch: [2] [ 280/1319] eta: 0:47:55 lr: 4.7503298702559326e-05 loss: 0.1544 (0.1659) time: 2.7717 data: 0.0074 max mem: 31678 +Epoch: [2] [ 290/1319] eta: 0:47:25 lr: 4.7494720745103136e-05 loss: 0.1544 (0.1666) time: 2.7252 data: 0.0073 max mem: 31678 +Epoch: [2] [ 300/1319] eta: 0:46:56 lr: 4.748614261550422e-05 loss: 0.1430 (0.1658) time: 2.7068 data: 0.0071 max mem: 31678 +Epoch: [2] [ 310/1319] eta: 0:46:24 lr: 4.7477564313724594e-05 loss: 0.1513 (0.1663) time: 2.6772 data: 0.0070 max mem: 31678 +Epoch: [2] [ 320/1319] eta: 0:45:54 lr: 4.746898583972622e-05 loss: 0.1742 (0.1669) time: 2.6625 data: 0.0069 max mem: 31678 +Epoch: [2] [ 330/1319] eta: 0:45:25 lr: 4.746040719347105e-05 loss: 0.1664 (0.1671) time: 2.6965 data: 0.0067 max mem: 33369 +Epoch: [2] [ 340/1319] eta: 0:44:54 lr: 4.745182837492104e-05 loss: 0.1664 (0.1671) time: 2.6664 data: 0.0066 max mem: 33369 +Epoch: [2] [ 350/1319] eta: 0:44:23 lr: 4.744324938403812e-05 loss: 0.1703 (0.1674) time: 2.6360 data: 0.0067 max mem: 33369 +Epoch: [2] [ 360/1319] eta: 0:43:53 lr: 4.7434670220784206e-05 loss: 0.1703 (0.1674) time: 2.6469 data: 0.0068 max mem: 33369 +Epoch: [2] [ 370/1319] eta: 0:43:27 lr: 4.7426090885121175e-05 loss: 0.1545 (0.1668) time: 2.7140 data: 0.0070 max mem: 33369 +Epoch: [2] [ 380/1319] eta: 0:43:01 lr: 4.741751137701092e-05 loss: 0.1657 (0.1675) time: 2.7969 data: 0.0074 max mem: 33369 +Epoch: [2] [ 390/1319] eta: 0:42:36 lr: 4.74089316964153e-05 loss: 0.1992 (0.1685) time: 2.8443 data: 0.0072 max mem: 33369 +Epoch: [2] [ 400/1319] eta: 0:42:09 lr: 4.740035184329618e-05 loss: 0.1711 (0.1684) time: 2.8270 data: 0.0072 max mem: 33369 +Epoch: [2] [ 410/1319] eta: 0:41:41 lr: 4.739177181761536e-05 loss: 0.1490 (0.1682) time: 2.7574 data: 0.0072 max mem: 33369 +Epoch: [2] [ 420/1319] eta: 0:41:14 lr: 4.738319161933468e-05 loss: 0.1406 (0.1677) time: 2.7483 data: 0.0070 max mem: 33369 +Epoch: [2] [ 430/1319] eta: 0:40:46 lr: 4.737461124841593e-05 loss: 0.1438 (0.1672) time: 2.7410 data: 0.0071 max mem: 33369 +Epoch: [2] [ 440/1319] eta: 0:40:18 lr: 4.736603070482089e-05 loss: 0.1338 (0.1668) time: 2.7332 data: 0.0070 max mem: 33369 +Epoch: [2] [ 450/1319] eta: 0:39:51 lr: 4.735744998851133e-05 loss: 0.1303 (0.1659) time: 2.7421 data: 0.0068 max mem: 33369 +Epoch: [2] [ 460/1319] eta: 0:39:23 lr: 4.734886909944901e-05 loss: 0.1542 (0.1662) time: 2.7529 data: 0.0067 max mem: 33369 +Epoch: [2] [ 470/1319] eta: 0:38:56 lr: 4.734028803759565e-05 loss: 0.1703 (0.1660) time: 2.7685 data: 0.0067 max mem: 33369 +Epoch: [2] [ 480/1319] eta: 0:38:28 lr: 4.733170680291298e-05 loss: 0.1427 (0.1656) time: 2.7528 data: 0.0068 max mem: 33369 +Epoch: [2] [ 490/1319] eta: 0:38:01 lr: 4.7323125395362694e-05 loss: 0.1427 (0.1651) time: 2.7449 data: 0.0068 max mem: 33369 +Epoch: [2] [ 500/1319] eta: 0:37:34 lr: 4.731454381490648e-05 loss: 0.1429 (0.1654) time: 2.7728 data: 0.0066 max mem: 33369 +Epoch: [2] [ 510/1319] eta: 0:37:06 lr: 4.730596206150601e-05 loss: 0.1407 (0.1650) time: 2.7506 data: 0.0070 max mem: 33369 +Epoch: [2] [ 520/1319] eta: 0:36:38 lr: 4.729738013512294e-05 loss: 0.1347 (0.1647) time: 2.7352 data: 0.0070 max mem: 33369 +Epoch: [2] [ 530/1319] eta: 0:36:11 lr: 4.72887980357189e-05 loss: 0.1500 (0.1650) time: 2.7598 data: 0.0068 max mem: 33369 +Epoch: [2] [ 540/1319] eta: 0:35:44 lr: 4.7280215763255517e-05 loss: 0.1694 (0.1652) time: 2.7595 data: 0.0068 max mem: 33369 +Epoch: [2] [ 550/1319] eta: 0:35:17 lr: 4.7271633317694384e-05 loss: 0.1604 (0.1652) time: 2.7791 data: 0.0068 max mem: 33369 +Epoch: [2] [ 560/1319] eta: 0:34:49 lr: 4.726305069899711e-05 loss: 0.1604 (0.1657) time: 2.7584 data: 0.0069 max mem: 33369 +Epoch: [2] [ 570/1319] eta: 0:34:21 lr: 4.725446790712525e-05 loss: 0.1694 (0.1659) time: 2.7372 data: 0.0072 max mem: 33369 +Epoch: [2] [ 580/1319] eta: 0:33:54 lr: 4.7245884942040375e-05 loss: 0.1689 (0.1660) time: 2.7495 data: 0.0070 max mem: 33369 +Epoch: [2] [ 590/1319] eta: 0:33:26 lr: 4.7237301803704005e-05 loss: 0.1542 (0.1659) time: 2.7518 data: 0.0071 max mem: 33369 +Epoch: [2] [ 600/1319] eta: 0:32:59 lr: 4.722871849207768e-05 loss: 0.1421 (0.1656) time: 2.7506 data: 0.0074 max mem: 33369 +Epoch: [2] [ 610/1319] eta: 0:32:31 lr: 4.72201350071229e-05 loss: 0.1571 (0.1656) time: 2.7557 data: 0.0072 max mem: 33369 +Epoch: [2] [ 620/1319] eta: 0:32:04 lr: 4.7211551348801154e-05 loss: 0.1617 (0.1656) time: 2.7893 data: 0.0068 max mem: 33369 +Epoch: [2] [ 630/1319] eta: 0:31:37 lr: 4.7202967517073924e-05 loss: 0.1441 (0.1655) time: 2.7870 data: 0.0069 max mem: 33369 +Epoch: [2] [ 640/1319] eta: 0:31:09 lr: 4.719438351190267e-05 loss: 0.1360 (0.1655) time: 2.7576 data: 0.0071 max mem: 33369 +Epoch: [2] [ 650/1319] eta: 0:30:41 lr: 4.718579933324881e-05 loss: 0.1469 (0.1655) time: 2.7002 data: 0.0069 max mem: 33369 +Epoch: [2] [ 660/1319] eta: 0:30:12 lr: 4.71772149810738e-05 loss: 0.1665 (0.1661) time: 2.6435 data: 0.0068 max mem: 33369 +Epoch: [2] [ 670/1319] eta: 0:29:43 lr: 4.716863045533903e-05 loss: 0.1640 (0.1662) time: 2.6263 data: 0.0069 max mem: 33369 +Epoch: [2] [ 680/1319] eta: 0:29:14 lr: 4.71600457560059e-05 loss: 0.1609 (0.1661) time: 2.6120 data: 0.0068 max mem: 33369 +Epoch: [2] [ 690/1319] eta: 0:28:46 lr: 4.7151460883035786e-05 loss: 0.1782 (0.1666) time: 2.6460 data: 0.0066 max mem: 33369 +Epoch: [2] [ 700/1319] eta: 0:28:18 lr: 4.714287583639004e-05 loss: 0.1508 (0.1661) time: 2.6614 data: 0.0066 max mem: 33369 +Epoch: [2] [ 710/1319] eta: 0:27:51 lr: 4.713429061603002e-05 loss: 0.1261 (0.1661) time: 2.7084 data: 0.0070 max mem: 33369 +Epoch: [2] [ 720/1319] eta: 0:27:24 lr: 4.712570522191704e-05 loss: 0.1478 (0.1659) time: 2.7944 data: 0.0074 max mem: 33369 +Epoch: [2] [ 730/1319] eta: 0:26:57 lr: 4.7117119654012416e-05 loss: 0.1380 (0.1655) time: 2.8076 data: 0.0074 max mem: 33369 +Epoch: [2] [ 740/1319] eta: 0:26:30 lr: 4.7108533912277444e-05 loss: 0.1380 (0.1653) time: 2.8052 data: 0.0074 max mem: 33369 +Epoch: [2] [ 750/1319] eta: 0:26:03 lr: 4.709994799667339e-05 loss: 0.1733 (0.1657) time: 2.8087 data: 0.0071 max mem: 33369 +Epoch: [2] [ 760/1319] eta: 0:25:36 lr: 4.709136190716153e-05 loss: 0.1784 (0.1657) time: 2.8025 data: 0.0071 max mem: 33369 +Epoch: [2] [ 770/1319] eta: 0:25:08 lr: 4.708277564370309e-05 loss: 0.1514 (0.1656) time: 2.7738 data: 0.0072 max mem: 33369 +Epoch: [2] [ 780/1319] eta: 0:24:41 lr: 4.707418920625932e-05 loss: 0.1502 (0.1657) time: 2.7261 data: 0.0070 max mem: 33369 +Epoch: [2] [ 790/1319] eta: 0:24:13 lr: 4.706560259479142e-05 loss: 0.1621 (0.1656) time: 2.7199 data: 0.0069 max mem: 33369 +Epoch: [2] [ 800/1319] eta: 0:23:46 lr: 4.705701580926059e-05 loss: 0.1652 (0.1660) time: 2.7439 data: 0.0068 max mem: 33369 +Epoch: [2] [ 810/1319] eta: 0:23:18 lr: 4.7048428849628004e-05 loss: 0.1766 (0.1663) time: 2.7399 data: 0.0070 max mem: 33369 +Epoch: [2] [ 820/1319] eta: 0:22:51 lr: 4.703984171585482e-05 loss: 0.1546 (0.1661) time: 2.7617 data: 0.0072 max mem: 33369 +Epoch: [2] [ 830/1319] eta: 0:22:23 lr: 4.703125440790219e-05 loss: 0.1517 (0.1662) time: 2.7786 data: 0.0070 max mem: 33369 +Epoch: [2] [ 840/1319] eta: 0:21:56 lr: 4.702266692573125e-05 loss: 0.1517 (0.1661) time: 2.7649 data: 0.0069 max mem: 33369 +Epoch: [2] [ 850/1319] eta: 0:21:29 lr: 4.70140792693031e-05 loss: 0.1527 (0.1660) time: 2.7662 data: 0.0068 max mem: 33369 +Epoch: [2] [ 860/1319] eta: 0:21:01 lr: 4.700549143857884e-05 loss: 0.1659 (0.1662) time: 2.7536 data: 0.0069 max mem: 33369 +Epoch: [2] [ 870/1319] eta: 0:20:34 lr: 4.699690343351954e-05 loss: 0.1573 (0.1661) time: 2.7556 data: 0.0069 max mem: 33369 +Epoch: [2] [ 880/1319] eta: 0:20:06 lr: 4.698831525408628e-05 loss: 0.1534 (0.1662) time: 2.7769 data: 0.0068 max mem: 33369 +Epoch: [2] [ 890/1319] eta: 0:19:39 lr: 4.697972690024009e-05 loss: 0.1699 (0.1661) time: 2.7553 data: 0.0068 max mem: 33369 +Epoch: [2] [ 900/1319] eta: 0:19:11 lr: 4.6971138371942025e-05 loss: 0.1254 (0.1658) time: 2.7368 data: 0.0068 max mem: 33369 +Epoch: [2] [ 910/1319] eta: 0:18:44 lr: 4.696254966915307e-05 loss: 0.1344 (0.1658) time: 2.7579 data: 0.0066 max mem: 33369 +Epoch: [2] [ 920/1319] eta: 0:18:16 lr: 4.695396079183423e-05 loss: 0.1488 (0.1656) time: 2.7595 data: 0.0065 max mem: 33369 +Epoch: [2] [ 930/1319] eta: 0:17:49 lr: 4.694537173994649e-05 loss: 0.1544 (0.1658) time: 2.7471 data: 0.0069 max mem: 33369 +Epoch: [2] [ 940/1319] eta: 0:17:21 lr: 4.69367825134508e-05 loss: 0.1532 (0.1655) time: 2.7480 data: 0.0070 max mem: 33369 +Epoch: [2] [ 950/1319] eta: 0:16:54 lr: 4.692819311230812e-05 loss: 0.1536 (0.1656) time: 2.7606 data: 0.0070 max mem: 33369 +Epoch: [2] [ 960/1319] eta: 0:16:27 lr: 4.6919603536479375e-05 loss: 0.1571 (0.1656) time: 2.7751 data: 0.0071 max mem: 33369 +Epoch: [2] [ 970/1319] eta: 0:15:59 lr: 4.691101378592547e-05 loss: 0.1503 (0.1657) time: 2.7707 data: 0.0070 max mem: 33369 +Epoch: [2] [ 980/1319] eta: 0:15:32 lr: 4.690242386060732e-05 loss: 0.1498 (0.1656) time: 2.7849 data: 0.0068 max mem: 33369 +Epoch: [2] [ 990/1319] eta: 0:15:04 lr: 4.6893833760485775e-05 loss: 0.1360 (0.1653) time: 2.7462 data: 0.0068 max mem: 33369 +Epoch: [2] [1000/1319] eta: 0:14:36 lr: 4.688524348552173e-05 loss: 0.1413 (0.1652) time: 2.6725 data: 0.0067 max mem: 33369 +Epoch: [2] [1010/1319] eta: 0:14:09 lr: 4.6876653035676014e-05 loss: 0.1541 (0.1652) time: 2.6674 data: 0.0067 max mem: 33369 +Epoch: [2] [1020/1319] eta: 0:13:41 lr: 4.6868062410909454e-05 loss: 0.1772 (0.1652) time: 2.6453 data: 0.0067 max mem: 33369 +Epoch: [2] [1030/1319] eta: 0:13:13 lr: 4.685947161118287e-05 loss: 0.1643 (0.1652) time: 2.6253 data: 0.0067 max mem: 33369 +Epoch: [2] [1040/1319] eta: 0:12:45 lr: 4.685088063645705e-05 loss: 0.1446 (0.1651) time: 2.6318 data: 0.0067 max mem: 33369 +Epoch: [2] [1050/1319] eta: 0:12:18 lr: 4.684228948669277e-05 loss: 0.1528 (0.1651) time: 2.6476 data: 0.0067 max mem: 33369 +Epoch: [2] [1060/1319] eta: 0:11:50 lr: 4.683369816185082e-05 loss: 0.1256 (0.1646) time: 2.6528 data: 0.0068 max mem: 33369 +Epoch: [2] [1070/1319] eta: 0:11:22 lr: 4.682510666189191e-05 loss: 0.1222 (0.1647) time: 2.6378 data: 0.0067 max mem: 33369 +Epoch: [2] [1080/1319] eta: 0:10:55 lr: 4.681651498677679e-05 loss: 0.1498 (0.1647) time: 2.6432 data: 0.0066 max mem: 33369 +Epoch: [2] [1090/1319] eta: 0:10:27 lr: 4.680792313646616e-05 loss: 0.1574 (0.1647) time: 2.6366 data: 0.0065 max mem: 33369 +Epoch: [2] [1100/1319] eta: 0:10:00 lr: 4.679933111092072e-05 loss: 0.1456 (0.1645) time: 2.6944 data: 0.0068 max mem: 33369 +Epoch: [2] [1110/1319] eta: 0:09:32 lr: 4.6790738910101147e-05 loss: 0.1536 (0.1649) time: 2.8013 data: 0.0072 max mem: 33369 +Epoch: [2] [1120/1319] eta: 0:09:05 lr: 4.67821465339681e-05 loss: 0.1808 (0.1648) time: 2.8161 data: 0.0074 max mem: 33369 +Epoch: [2] [1130/1319] eta: 0:08:38 lr: 4.677355398248223e-05 loss: 0.1563 (0.1647) time: 2.7631 data: 0.0077 max mem: 33369 +Epoch: [2] [1140/1319] eta: 0:08:10 lr: 4.676496125560416e-05 loss: 0.1536 (0.1647) time: 2.7585 data: 0.0074 max mem: 33369 +Epoch: [2] [1150/1319] eta: 0:07:43 lr: 4.6756368353294506e-05 loss: 0.1318 (0.1645) time: 2.7940 data: 0.0071 max mem: 33369 +Epoch: [2] [1160/1319] eta: 0:07:16 lr: 4.6747775275513856e-05 loss: 0.1268 (0.1641) time: 2.7840 data: 0.0071 max mem: 33369 +Epoch: [2] [1170/1319] eta: 0:06:48 lr: 4.6739182022222775e-05 loss: 0.1388 (0.1640) time: 2.7641 data: 0.0070 max mem: 33369 +Epoch: [2] [1180/1319] eta: 0:06:21 lr: 4.6730588593381847e-05 loss: 0.1510 (0.1641) time: 2.7631 data: 0.0071 max mem: 33369 +Epoch: [2] [1190/1319] eta: 0:05:53 lr: 4.67219949889516e-05 loss: 0.1665 (0.1643) time: 2.7500 data: 0.0071 max mem: 33369 +Epoch: [2] [1200/1319] eta: 0:05:26 lr: 4.6713401208892564e-05 loss: 0.1665 (0.1643) time: 2.7278 data: 0.0070 max mem: 33369 +Epoch: [2] [1210/1319] eta: 0:04:58 lr: 4.6704807253165246e-05 loss: 0.1644 (0.1643) time: 2.7249 data: 0.0070 max mem: 33369 +Epoch: [2] [1220/1319] eta: 0:04:31 lr: 4.6696213121730145e-05 loss: 0.1678 (0.1643) time: 2.7363 data: 0.0070 max mem: 33369 +Epoch: [2] [1230/1319] eta: 0:04:04 lr: 4.668761881454772e-05 loss: 0.1565 (0.1643) time: 2.7420 data: 0.0071 max mem: 33369 +Epoch: [2] [1240/1319] eta: 0:03:36 lr: 4.6679024331578444e-05 loss: 0.1498 (0.1643) time: 2.6997 data: 0.0070 max mem: 33369 +Epoch: [2] [1250/1319] eta: 0:03:09 lr: 4.6670429672782765e-05 loss: 0.1346 (0.1641) time: 2.6999 data: 0.0074 max mem: 33369 +Epoch: [2] [1260/1319] eta: 0:02:41 lr: 4.6661834838121084e-05 loss: 0.1470 (0.1641) time: 2.7583 data: 0.0073 max mem: 33369 +Epoch: [2] [1270/1319] eta: 0:02:14 lr: 4.665323982755382e-05 loss: 0.1470 (0.1639) time: 2.7477 data: 0.0069 max mem: 33369 +Epoch: [2] [1280/1319] eta: 0:01:46 lr: 4.664464464104137e-05 loss: 0.1337 (0.1639) time: 2.7294 data: 0.0071 max mem: 33369 +Epoch: [2] [1290/1319] eta: 0:01:19 lr: 4.6636049278544094e-05 loss: 0.1525 (0.1639) time: 2.7328 data: 0.0071 max mem: 33369 +Epoch: [2] [1300/1319] eta: 0:00:52 lr: 4.662745374002236e-05 loss: 0.1559 (0.1641) time: 2.7358 data: 0.0071 max mem: 33369 +Epoch: [2] [1310/1319] eta: 0:00:24 lr: 4.6618858025436495e-05 loss: 0.1559 (0.1642) time: 2.7463 data: 0.0069 max mem: 33369 +Epoch: [2] Total time: 1:00:17 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 2:18:46 time: 3.2359 data: 3.1548 max mem: 33369 +Test: [ 100/2573] eta: 0:04:16 time: 0.0723 data: 0.0012 max mem: 33369 +Test: [ 200/2573] eta: 0:03:32 time: 0.0736 data: 0.0012 max mem: 33369 +Test: [ 300/2573] eta: 0:03:10 time: 0.0756 data: 0.0012 max mem: 33369 +Test: [ 400/2573] eta: 0:02:56 time: 0.0756 data: 0.0012 max mem: 33369 +Test: [ 500/2573] eta: 0:02:45 time: 0.0742 data: 0.0012 max mem: 33369 +Test: [ 600/2573] eta: 0:02:35 time: 0.0742 data: 0.0012 max mem: 33369 +Test: [ 700/2573] eta: 0:02:27 time: 0.0743 data: 0.0012 max mem: 33369 +Test: [ 800/2573] eta: 0:02:18 time: 0.0774 data: 0.0012 max mem: 33369 +Test: [ 900/2573] eta: 0:02:10 time: 0.0742 data: 0.0012 max mem: 33369 +Test: [1000/2573] eta: 0:02:01 time: 0.0741 data: 0.0012 max mem: 33369 +Test: [1100/2573] eta: 0:01:53 time: 0.0742 data: 0.0012 max mem: 33369 +Test: [1200/2573] eta: 0:01:45 time: 0.0744 data: 0.0012 max mem: 33369 +Test: [1300/2573] eta: 0:01:37 time: 0.0744 data: 0.0012 max mem: 33369 +Test: [1400/2573] eta: 0:01:29 time: 0.0725 data: 0.0012 max mem: 33369 +Test: [1500/2573] eta: 0:01:22 time: 0.0742 data: 0.0012 max mem: 33369 +Test: [1600/2573] eta: 0:01:14 time: 0.0777 data: 0.0012 max mem: 33369 +Test: [1700/2573] eta: 0:01:06 time: 0.0724 data: 0.0011 max mem: 33369 +Test: [1800/2573] eta: 0:00:58 time: 0.0760 data: 0.0012 max mem: 33369 +Test: [1900/2573] eta: 0:00:51 time: 0.0725 data: 0.0012 max mem: 33369 +Test: [2000/2573] eta: 0:00:43 time: 0.0741 data: 0.0012 max mem: 33369 +Test: [2100/2573] eta: 0:00:35 time: 0.0755 data: 0.0011 max mem: 33369 +Test: [2200/2573] eta: 0:00:28 time: 0.0754 data: 0.0011 max mem: 33369 +Test: [2300/2573] eta: 0:00:20 time: 0.0757 data: 0.0012 max mem: 33369 +Test: [2400/2573] eta: 0:00:13 time: 0.0706 data: 0.0012 max mem: 33369 +Test: [2500/2573] eta: 0:00:05 time: 0.0737 data: 0.0011 max mem: 33369 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: Total time: 0:03:14 +Final results: +Mean IoU is 42.07 + + precision@0.5 = 46.04 + precision@0.6 = 38.77 + precision@0.7 = 30.62 + precision@0.8 = 19.73 + precision@0.9 = 6.99 + overall IoU = 45.41 + +Average object IoU 42.07314858108085 +Overall IoU 45.40886306762695 +Better epoch: 2 + +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [3] [ 0/1319] eta: 1:58:01 lr: 4.661112173174161e-05 loss: 0.0983 (0.0983) time: 5.3689 data: 2.6650 max mem: 33369 +Epoch: [3] [ 10/1319] eta: 1:02:19 lr: 4.660252568252458e-05 loss: 0.1291 (0.1437) time: 2.8566 data: 0.2484 max mem: 33369 +Epoch: [3] [ 20/1319] eta: 0:59:55 lr: 4.6593929457128314e-05 loss: 0.1219 (0.1331) time: 2.6382 data: 0.0061 max mem: 33369 +Epoch: [3] [ 30/1319] eta: 0:58:31 lr: 4.6585333055513096e-05 loss: 0.1184 (0.1335) time: 2.6508 data: 0.0060 max mem: 33369 +Epoch: [3] [ 40/1319] eta: 0:57:44 lr: 4.657673647763916e-05 loss: 0.1539 (0.1455) time: 2.6460 data: 0.0064 max mem: 33369 +Epoch: [3] [ 50/1319] eta: 0:57:06 lr: 4.656813972346675e-05 loss: 0.1409 (0.1430) time: 2.6625 data: 0.0064 max mem: 33369 +Epoch: [3] [ 60/1319] eta: 0:56:57 lr: 4.655954279295608e-05 loss: 0.1236 (0.1438) time: 2.7277 data: 0.0068 max mem: 33369 +Epoch: [3] [ 70/1319] eta: 0:56:42 lr: 4.655094568606738e-05 loss: 0.1435 (0.1435) time: 2.7867 data: 0.0072 max mem: 33369 +Epoch: [3] [ 80/1319] eta: 0:56:27 lr: 4.6542348402760813e-05 loss: 0.1351 (0.1448) time: 2.7923 data: 0.0070 max mem: 33369 +Epoch: [3] [ 90/1319] eta: 0:56:11 lr: 4.653375094299656e-05 loss: 0.1351 (0.1476) time: 2.8094 data: 0.0069 max mem: 33369 +Epoch: [3] [ 100/1319] eta: 0:55:50 lr: 4.652515330673476e-05 loss: 0.1190 (0.1462) time: 2.8084 data: 0.0069 max mem: 33369 +Epoch: [3] [ 110/1319] eta: 0:55:25 lr: 4.651655549393556e-05 loss: 0.1230 (0.1469) time: 2.7856 data: 0.0071 max mem: 33369 +Epoch: [3] [ 120/1319] eta: 0:54:57 lr: 4.650795750455908e-05 loss: 0.1507 (0.1468) time: 2.7587 data: 0.0072 max mem: 33369 +Epoch: [3] [ 130/1319] eta: 0:54:28 lr: 4.649935933856541e-05 loss: 0.1460 (0.1463) time: 2.7369 data: 0.0071 max mem: 33369 +Epoch: [3] [ 140/1319] eta: 0:54:01 lr: 4.6490760995914644e-05 loss: 0.1306 (0.1444) time: 2.7424 data: 0.0068 max mem: 33369 +Epoch: [3] [ 150/1319] eta: 0:53:39 lr: 4.648216247656684e-05 loss: 0.1224 (0.1442) time: 2.7891 data: 0.0065 max mem: 33369 +Epoch: [3] [ 160/1319] eta: 0:53:17 lr: 4.647356378048206e-05 loss: 0.1355 (0.1439) time: 2.8301 data: 0.0065 max mem: 33369 +Epoch: [3] [ 170/1319] eta: 0:52:51 lr: 4.646496490762032e-05 loss: 0.1446 (0.1441) time: 2.8110 data: 0.0065 max mem: 33369 +Epoch: [3] [ 180/1319] eta: 0:52:24 lr: 4.645636585794164e-05 loss: 0.1418 (0.1444) time: 2.7716 data: 0.0068 max mem: 33369 +Epoch: [3] [ 190/1319] eta: 0:51:51 lr: 4.644776663140602e-05 loss: 0.1418 (0.1460) time: 2.7171 data: 0.0073 max mem: 33369 +Epoch: [3] [ 200/1319] eta: 0:51:24 lr: 4.6439167227973446e-05 loss: 0.1475 (0.1469) time: 2.7175 data: 0.0074 max mem: 33369 +Epoch: [3] [ 210/1319] eta: 0:50:54 lr: 4.643056764760387e-05 loss: 0.1465 (0.1472) time: 2.7367 data: 0.0071 max mem: 33369 +Epoch: [3] [ 220/1319] eta: 0:50:27 lr: 4.642196789025724e-05 loss: 0.1453 (0.1475) time: 2.7388 data: 0.0070 max mem: 33369 +Epoch: [3] [ 230/1319] eta: 0:50:01 lr: 4.641336795589349e-05 loss: 0.1453 (0.1472) time: 2.7725 data: 0.0070 max mem: 33369 +Epoch: [3] [ 240/1319] eta: 0:49:34 lr: 4.6404767844472526e-05 loss: 0.1407 (0.1467) time: 2.7732 data: 0.0069 max mem: 33369 +Epoch: [3] [ 250/1319] eta: 0:49:07 lr: 4.639616755595424e-05 loss: 0.1402 (0.1467) time: 2.7719 data: 0.0068 max mem: 33369 +Epoch: [3] [ 260/1319] eta: 0:48:37 lr: 4.638756709029851e-05 loss: 0.1453 (0.1468) time: 2.7338 data: 0.0068 max mem: 33369 +Epoch: [3] [ 270/1319] eta: 0:48:10 lr: 4.6378966447465196e-05 loss: 0.1566 (0.1473) time: 2.7326 data: 0.0068 max mem: 33369 +Epoch: [3] [ 280/1319] eta: 0:47:42 lr: 4.637036562741414e-05 loss: 0.1566 (0.1472) time: 2.7630 data: 0.0071 max mem: 33369 +Epoch: [3] [ 290/1319] eta: 0:47:15 lr: 4.636176463010516e-05 loss: 0.1573 (0.1478) time: 2.7592 data: 0.0071 max mem: 33369 +Epoch: [3] [ 300/1319] eta: 0:46:48 lr: 4.635316345549808e-05 loss: 0.1258 (0.1473) time: 2.7682 data: 0.0069 max mem: 33369 +Epoch: [3] [ 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+Epoch: [3] [ 390/1319] eta: 0:42:25 lr: 4.627574489897873e-05 loss: 0.1203 (0.1463) time: 2.6467 data: 0.0066 max mem: 33369 +Epoch: [3] [ 400/1319] eta: 0:41:59 lr: 4.626714194917605e-05 loss: 0.1297 (0.1461) time: 2.7433 data: 0.0070 max mem: 33369 +Epoch: [3] [ 410/1319] eta: 0:41:34 lr: 4.625853882163199e-05 loss: 0.1405 (0.1460) time: 2.8366 data: 0.0074 max mem: 33369 +Epoch: [3] [ 420/1319] eta: 0:41:07 lr: 4.624993551630613e-05 loss: 0.1405 (0.1459) time: 2.8071 data: 0.0074 max mem: 33369 +Epoch: [3] [ 430/1319] eta: 0:40:40 lr: 4.624133203315806e-05 loss: 0.1443 (0.1459) time: 2.7639 data: 0.0070 max mem: 33369 +Epoch: [3] [ 440/1319] eta: 0:40:14 lr: 4.6232728372147346e-05 loss: 0.1333 (0.1456) time: 2.7925 data: 0.0071 max mem: 33369 +Epoch: [3] [ 450/1319] eta: 0:39:46 lr: 4.6224124533233514e-05 loss: 0.1328 (0.1456) time: 2.7721 data: 0.0072 max mem: 33369 +Epoch: [3] [ 460/1319] eta: 0:39:21 lr: 4.621552051637611e-05 loss: 0.1545 (0.1464) time: 2.7814 data: 0.0068 max mem: 33369 +Epoch: [3] [ 470/1319] eta: 0:38:53 lr: 4.620691632153463e-05 loss: 0.1446 (0.1460) time: 2.7791 data: 0.0067 max mem: 33369 +Epoch: [3] [ 480/1319] eta: 0:38:24 lr: 4.619831194866858e-05 loss: 0.1267 (0.1459) time: 2.7146 data: 0.0068 max mem: 33369 +Epoch: [3] [ 490/1319] eta: 0:37:57 lr: 4.618970739773742e-05 loss: 0.1267 (0.1456) time: 2.7391 data: 0.0069 max mem: 33369 +Epoch: [3] [ 500/1319] eta: 0:37:31 lr: 4.618110266870061e-05 loss: 0.1419 (0.1460) time: 2.7863 data: 0.0067 max mem: 33369 +Epoch: [3] [ 510/1319] eta: 0:37:03 lr: 4.6172497761517596e-05 loss: 0.1540 (0.1461) time: 2.7784 data: 0.0067 max mem: 33369 +Epoch: [3] [ 520/1319] eta: 0:36:36 lr: 4.6163892676147796e-05 loss: 0.1504 (0.1463) time: 2.7521 data: 0.0066 max mem: 33369 +Epoch: [3] [ 530/1319] eta: 0:36:08 lr: 4.615528741255061e-05 loss: 0.1541 (0.1465) time: 2.7247 data: 0.0066 max mem: 33369 +Epoch: [3] [ 540/1319] eta: 0:35:41 lr: 4.6146681970685424e-05 loss: 0.1527 (0.1466) time: 2.7543 data: 0.0068 max mem: 33369 +Epoch: [3] [ 550/1319] eta: 0:35:14 lr: 4.613807635051161e-05 loss: 0.1393 (0.1469) time: 2.7837 data: 0.0070 max mem: 33369 +Epoch: [3] [ 560/1319] eta: 0:34:46 lr: 4.612947055198852e-05 loss: 0.1661 (0.1476) time: 2.7515 data: 0.0070 max mem: 33369 +Epoch: [3] [ 570/1319] eta: 0:34:19 lr: 4.612086457507548e-05 loss: 0.1725 (0.1480) time: 2.7549 data: 0.0072 max mem: 33369 +Epoch: [3] [ 580/1319] eta: 0:33:51 lr: 4.611225841973181e-05 loss: 0.1344 (0.1477) time: 2.7554 data: 0.0072 max mem: 33369 +Epoch: [3] [ 590/1319] eta: 0:33:24 lr: 4.610365208591681e-05 loss: 0.1145 (0.1475) time: 2.7656 data: 0.0071 max mem: 33369 +Epoch: [3] [ 600/1319] eta: 0:32:57 lr: 4.609504557358975e-05 loss: 0.1291 (0.1474) time: 2.7759 data: 0.0071 max mem: 33369 +Epoch: [3] [ 610/1319] eta: 0:32:29 lr: 4.60864388827099e-05 loss: 0.1454 (0.1476) time: 2.7571 data: 0.0070 max mem: 33369 +Epoch: [3] [ 620/1319] eta: 0:32:02 lr: 4.6077832013236505e-05 loss: 0.1695 (0.1480) time: 2.7344 data: 0.0069 max mem: 33369 +Epoch: [3] [ 630/1319] eta: 0:31:35 lr: 4.606922496512879e-05 loss: 0.1455 (0.1482) time: 2.7648 data: 0.0068 max mem: 33369 +Epoch: [3] [ 640/1319] eta: 0:31:07 lr: 4.606061773834596e-05 loss: 0.1334 (0.1482) time: 2.7479 data: 0.0070 max mem: 33369 +Epoch: [3] [ 650/1319] eta: 0:30:39 lr: 4.60520103328472e-05 loss: 0.1390 (0.1483) time: 2.7342 data: 0.0071 max mem: 33369 +Epoch: [3] [ 660/1319] eta: 0:30:11 lr: 4.60434027485917e-05 loss: 0.1558 (0.1484) time: 2.7403 data: 0.0072 max mem: 33369 +Epoch: [3] [ 670/1319] eta: 0:29:43 lr: 4.6034794985538615e-05 loss: 0.1409 (0.1482) time: 2.6730 data: 0.0072 max mem: 33369 +Epoch: [3] [ 680/1319] eta: 0:29:14 lr: 4.602618704364706e-05 loss: 0.1448 (0.1484) time: 2.6442 data: 0.0070 max mem: 33369 +Epoch: [3] [ 690/1319] eta: 0:28:46 lr: 4.601757892287618e-05 loss: 0.1580 (0.1488) time: 2.6382 data: 0.0070 max mem: 33369 +Epoch: [3] [ 700/1319] eta: 0:28:18 lr: 4.600897062318506e-05 loss: 0.1565 (0.1491) time: 2.6323 data: 0.0071 max mem: 33369 +Epoch: [3] [ 710/1319] eta: 0:27:49 lr: 4.600036214453279e-05 loss: 0.1565 (0.1490) time: 2.6124 data: 0.0067 max mem: 33369 +Epoch: [3] [ 720/1319] eta: 0:27:20 lr: 4.599175348687844e-05 loss: 0.1369 (0.1489) time: 2.5970 data: 0.0066 max mem: 33369 +Epoch: [3] [ 730/1319] eta: 0:26:52 lr: 4.598314465018106e-05 loss: 0.1369 (0.1489) time: 2.6168 data: 0.0066 max mem: 33369 +Epoch: [3] [ 740/1319] eta: 0:26:24 lr: 4.5974535634399665e-05 loss: 0.1353 (0.1487) time: 2.6226 data: 0.0066 max mem: 33369 +Epoch: [3] [ 750/1319] eta: 0:25:56 lr: 4.596592643949328e-05 loss: 0.1320 (0.1486) time: 2.6536 data: 0.0067 max mem: 33369 +Epoch: [3] [ 760/1319] eta: 0:25:29 lr: 4.595731706542089e-05 loss: 0.1347 (0.1487) time: 2.7523 data: 0.0069 max mem: 33369 +Epoch: [3] [ 770/1319] eta: 0:25:02 lr: 4.5948707512141485e-05 loss: 0.1470 (0.1487) time: 2.8078 data: 0.0071 max mem: 33369 +Epoch: [3] [ 780/1319] eta: 0:24:35 lr: 4.594009777961402e-05 loss: 0.1312 (0.1484) time: 2.7663 data: 0.0070 max mem: 33369 +Epoch: [3] [ 790/1319] eta: 0:24:08 lr: 4.593148786779743e-05 loss: 0.1312 (0.1488) time: 2.7491 data: 0.0069 max mem: 33369 +Epoch: [3] [ 800/1319] eta: 0:23:40 lr: 4.592287777665063e-05 loss: 0.1285 (0.1486) time: 2.7579 data: 0.0070 max mem: 33369 +Epoch: [3] [ 810/1319] eta: 0:23:13 lr: 4.5914267506132555e-05 loss: 0.1285 (0.1486) time: 2.7541 data: 0.0072 max mem: 33369 +Epoch: [3] [ 820/1319] eta: 0:22:46 lr: 4.590565705620206e-05 loss: 0.1425 (0.1484) time: 2.7541 data: 0.0073 max mem: 33369 +Epoch: [3] [ 830/1319] eta: 0:22:19 lr: 4.589704642681802e-05 loss: 0.1126 (0.1481) time: 2.7685 data: 0.0074 max mem: 33369 +Epoch: [3] [ 840/1319] eta: 0:21:51 lr: 4.58884356179393e-05 loss: 0.1504 (0.1485) time: 2.7591 data: 0.0072 max mem: 33369 +Epoch: [3] [ 850/1319] eta: 0:21:24 lr: 4.5879824629524725e-05 loss: 0.1504 (0.1481) time: 2.7584 data: 0.0071 max mem: 33369 +Epoch: [3] [ 860/1319] eta: 0:20:57 lr: 4.5871213461533106e-05 loss: 0.1326 (0.1483) time: 2.7624 data: 0.0070 max mem: 33369 +Epoch: [3] [ 870/1319] eta: 0:20:29 lr: 4.5862602113923244e-05 loss: 0.1339 (0.1482) time: 2.7257 data: 0.0068 max mem: 33369 +Epoch: [3] [ 880/1319] eta: 0:20:02 lr: 4.585399058665391e-05 loss: 0.1278 (0.1480) time: 2.7361 data: 0.0070 max mem: 33369 +Epoch: [3] [ 890/1319] eta: 0:19:34 lr: 4.5845378879683885e-05 loss: 0.1381 (0.1479) time: 2.7188 data: 0.0071 max mem: 33369 +Epoch: [3] [ 900/1319] eta: 0:19:07 lr: 4.583676699297189e-05 loss: 0.1421 (0.1480) time: 2.6853 data: 0.0070 max mem: 33369 +Epoch: [3] [ 910/1319] eta: 0:18:39 lr: 4.582815492647665e-05 loss: 0.1387 (0.1479) time: 2.7283 data: 0.0069 max mem: 33369 +Epoch: [3] [ 920/1319] eta: 0:18:12 lr: 4.5819542680156885e-05 loss: 0.1556 (0.1484) time: 2.7568 data: 0.0069 max mem: 33369 +Epoch: [3] [ 930/1319] eta: 0:17:45 lr: 4.5810930253971277e-05 loss: 0.1656 (0.1484) time: 2.7357 data: 0.0068 max mem: 33369 +Epoch: [3] [ 940/1319] eta: 0:17:18 lr: 4.580231764787849e-05 loss: 0.1645 (0.1490) time: 2.7672 data: 0.0068 max mem: 33369 +Epoch: [3] [ 950/1319] eta: 0:16:50 lr: 4.579370486183719e-05 loss: 0.1485 (0.1490) time: 2.7773 data: 0.0071 max mem: 33369 +Epoch: [3] [ 960/1319] eta: 0:16:23 lr: 4.5785091895806004e-05 loss: 0.1295 (0.1489) time: 2.7595 data: 0.0071 max mem: 33369 +Epoch: [3] [ 970/1319] eta: 0:15:55 lr: 4.577647874974354e-05 loss: 0.1316 (0.1488) time: 2.7511 data: 0.0069 max mem: 33369 +Epoch: [3] [ 980/1319] eta: 0:15:28 lr: 4.57678654236084e-05 loss: 0.1296 (0.1485) time: 2.7372 data: 0.0071 max mem: 33369 +Epoch: [3] [ 990/1319] eta: 0:15:01 lr: 4.575925191735917e-05 loss: 0.1105 (0.1484) time: 2.7517 data: 0.0072 max mem: 33369 +Epoch: [3] [1000/1319] eta: 0:14:33 lr: 4.57506382309544e-05 loss: 0.1299 (0.1484) time: 2.7583 data: 0.0071 max mem: 33369 +Epoch: [3] [1010/1319] eta: 0:14:06 lr: 4.574202436435264e-05 loss: 0.1465 (0.1484) time: 2.7472 data: 0.0072 max mem: 33369 +Epoch: [3] [1020/1319] eta: 0:13:39 lr: 4.573341031751242e-05 loss: 0.1327 (0.1483) time: 2.7767 data: 0.0071 max mem: 33369 +Epoch: [3] [1030/1319] eta: 0:13:11 lr: 4.5724796090392234e-05 loss: 0.1277 (0.1482) time: 2.7779 data: 0.0070 max mem: 33369 +Epoch: [3] [1040/1319] eta: 0:12:44 lr: 4.571618168295058e-05 loss: 0.1283 (0.1481) time: 2.6793 data: 0.0068 max mem: 33369 +Epoch: [3] [1050/1319] eta: 0:12:16 lr: 4.570756709514592e-05 loss: 0.1283 (0.1479) time: 2.6113 data: 0.0068 max mem: 33369 +Epoch: [3] [1060/1319] eta: 0:11:48 lr: 4.569895232693671e-05 loss: 0.1308 (0.1481) time: 2.6196 data: 0.0069 max mem: 33369 +Epoch: [3] [1070/1319] eta: 0:11:21 lr: 4.569033737828139e-05 loss: 0.1413 (0.1480) time: 2.6463 data: 0.0067 max mem: 33369 +Epoch: [3] [1080/1319] eta: 0:10:53 lr: 4.568172224913836e-05 loss: 0.1279 (0.1478) time: 2.6432 data: 0.0065 max mem: 33369 +Epoch: [3] [1090/1319] eta: 0:10:26 lr: 4.567310693946603e-05 loss: 0.1221 (0.1478) time: 2.6435 data: 0.0065 max mem: 33369 +Epoch: [3] [1100/1319] eta: 0:09:59 lr: 4.566449144922278e-05 loss: 0.1239 (0.1476) time: 2.7335 data: 0.0069 max mem: 33369 +Epoch: [3] [1110/1319] eta: 0:09:31 lr: 4.565587577836695e-05 loss: 0.1323 (0.1477) time: 2.8197 data: 0.0075 max mem: 33369 +Epoch: [3] [1120/1319] eta: 0:09:04 lr: 4.5647259926856906e-05 loss: 0.1437 (0.1478) time: 2.8063 data: 0.0077 max mem: 33369 +Epoch: [3] [1130/1319] eta: 0:08:37 lr: 4.563864389465096e-05 loss: 0.1323 (0.1478) time: 2.7809 data: 0.0072 max mem: 33369 +Epoch: [3] [1140/1319] eta: 0:08:09 lr: 4.563002768170741e-05 loss: 0.1317 (0.1477) time: 2.7712 data: 0.0071 max mem: 33369 +Epoch: [3] [1150/1319] eta: 0:07:42 lr: 4.562141128798457e-05 loss: 0.1387 (0.1479) time: 2.7696 data: 0.0072 max mem: 33369 +Epoch: [3] [1160/1319] eta: 0:07:15 lr: 4.561279471344068e-05 loss: 0.1405 (0.1480) time: 2.7649 data: 0.0070 max mem: 33369 +Epoch: [3] [1170/1319] eta: 0:06:47 lr: 4.5604177958034e-05 loss: 0.1413 (0.1480) time: 2.7544 data: 0.0068 max mem: 33369 +Epoch: [3] [1180/1319] eta: 0:06:20 lr: 4.559556102172276e-05 loss: 0.1489 (0.1480) time: 2.7688 data: 0.0069 max mem: 33369 +Epoch: [3] [1190/1319] eta: 0:05:53 lr: 4.5586943904465176e-05 loss: 0.1377 (0.1481) time: 2.7802 data: 0.0069 max mem: 33369 +Epoch: [3] [1200/1319] eta: 0:05:25 lr: 4.557832660621944e-05 loss: 0.1216 (0.1480) time: 2.7556 data: 0.0069 max mem: 33369 +Epoch: [3] [1210/1319] eta: 0:04:58 lr: 4.556970912694373e-05 loss: 0.1332 (0.1480) time: 2.7412 data: 0.0070 max mem: 33369 +Epoch: [3] [1220/1319] eta: 0:04:31 lr: 4.5561091466596205e-05 loss: 0.1613 (0.1481) time: 2.7414 data: 0.0070 max mem: 33369 +Epoch: [3] [1230/1319] eta: 0:04:03 lr: 4.555247362513501e-05 loss: 0.1319 (0.1480) time: 2.7419 data: 0.0070 max mem: 33369 +Epoch: [3] [1240/1319] eta: 0:03:36 lr: 4.5543855602518245e-05 loss: 0.1208 (0.1479) time: 2.7380 data: 0.0069 max mem: 33369 +Epoch: [3] [1250/1319] eta: 0:03:08 lr: 4.553523739870403e-05 loss: 0.1208 (0.1477) time: 2.7388 data: 0.0070 max mem: 33369 +Epoch: [3] [1260/1319] eta: 0:02:41 lr: 4.552661901365045e-05 loss: 0.1296 (0.1478) time: 2.7656 data: 0.0070 max mem: 33369 +Epoch: [3] [1270/1319] eta: 0:02:14 lr: 4.551800044731557e-05 loss: 0.1296 (0.1478) time: 2.7805 data: 0.0069 max mem: 33369 +Epoch: [3] [1280/1319] eta: 0:01:46 lr: 4.550938169965743e-05 loss: 0.1308 (0.1477) time: 2.7804 data: 0.0070 max mem: 33369 +Epoch: [3] [1290/1319] eta: 0:01:19 lr: 4.550076277063406e-05 loss: 0.1381 (0.1477) time: 2.7561 data: 0.0070 max mem: 33369 +Epoch: [3] [1300/1319] eta: 0:00:52 lr: 4.549214366020347e-05 loss: 0.1346 (0.1479) time: 2.7310 data: 0.0070 max mem: 33369 +Epoch: [3] [1310/1319] eta: 0:00:24 lr: 4.5483524368323656e-05 loss: 0.1428 (0.1481) time: 2.7512 data: 0.0067 max mem: 33369 +Epoch: [3] Total time: 1:00:14 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 2:41:25 time: 3.7642 data: 3.6690 max mem: 33369 +Test: [ 100/2573] eta: 0:04:30 time: 0.0722 data: 0.0012 max mem: 33369 +Test: [ 200/2573] eta: 0:03:38 time: 0.0735 data: 0.0012 max mem: 33369 +Test: [ 300/2573] eta: 0:03:14 time: 0.0752 data: 0.0012 max mem: 33369 +Test: [ 400/2573] eta: 0:02:59 time: 0.0754 data: 0.0011 max mem: 33369 +Test: [ 500/2573] eta: 0:02:47 time: 0.0741 data: 0.0012 max mem: 33369 +Test: [ 600/2573] eta: 0:02:37 time: 0.0748 data: 0.0013 max mem: 33369 +Test: [ 700/2573] eta: 0:02:28 time: 0.0740 data: 0.0012 max mem: 33369 +Test: [ 800/2573] eta: 0:02:19 time: 0.0777 data: 0.0012 max mem: 33369 +Test: [ 900/2573] eta: 0:02:11 time: 0.0746 data: 0.0012 max mem: 33369 +Test: [1000/2573] eta: 0:02:02 time: 0.0742 data: 0.0012 max mem: 33369 +Test: [1100/2573] eta: 0:01:54 time: 0.0743 data: 0.0012 max mem: 33369 +Test: [1200/2573] eta: 0:01:46 time: 0.0742 data: 0.0012 max mem: 33369 +Test: [1300/2573] eta: 0:01:38 time: 0.0742 data: 0.0011 max mem: 33369 +Test: [1400/2573] eta: 0:01:30 time: 0.0727 data: 0.0012 max mem: 33369 +Test: [1500/2573] eta: 0:01:22 time: 0.0741 data: 0.0012 max mem: 33369 +Test: [1600/2573] eta: 0:01:14 time: 0.0778 data: 0.0012 max mem: 33369 +Test: [1700/2573] eta: 0:01:06 time: 0.0728 data: 0.0012 max mem: 33369 +Test: [1800/2573] eta: 0:00:59 time: 0.0761 data: 0.0012 max mem: 33369 +Test: [1900/2573] eta: 0:00:51 time: 0.0720 data: 0.0011 max mem: 33369 +Test: [2000/2573] eta: 0:00:43 time: 0.0739 data: 0.0011 max mem: 33369 +Test: [2100/2573] eta: 0:00:35 time: 0.0756 data: 0.0011 max mem: 33369 +Test: [2200/2573] eta: 0:00:28 time: 0.0755 data: 0.0011 max mem: 33369 +Test: [2300/2573] eta: 0:00:20 time: 0.0753 data: 0.0011 max mem: 33369 +Test: [2400/2573] eta: 0:00:13 time: 0.0704 data: 0.0011 max mem: 33369 +Test: [2500/2573] eta: 0:00:05 time: 0.0737 data: 0.0011 max mem: 33369 +Test: Total time: 0:03:15 +Final results: +Mean IoU is 50.33 + + precision@0.5 = 54.47 + precision@0.6 = 45.87 + precision@0.7 = 37.01 + precision@0.8 = 24.92 + precision@0.9 = 9.15 + overall IoU = 51.13 + +Average object IoU 50.33035416927745 +Overall IoU 51.1298942565918 +Better epoch: 3 + +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [4] [ 0/1319] eta: 1:29:42 lr: 4.547576685045799e-05 loss: 0.1201 (0.1201) time: 4.0808 data: 1.3841 max mem: 33369 +Epoch: [4] [ 10/1319] eta: 1:00:13 lr: 4.546714721370884e-05 loss: 0.1361 (0.1424) time: 2.7602 data: 0.1321 max mem: 33369 +Epoch: [4] [ 20/1319] eta: 0:58:45 lr: 4.5458527395388535e-05 loss: 0.1302 (0.1367) time: 2.6453 data: 0.0066 max mem: 33369 +Epoch: [4] [ 30/1319] eta: 0:57:28 lr: 4.544990739545498e-05 loss: 0.1204 (0.1358) time: 2.6283 data: 0.0064 max mem: 33369 +Epoch: [4] [ 40/1319] eta: 0:56:51 lr: 4.544128721386609e-05 loss: 0.1204 (0.1340) time: 2.6190 data: 0.0067 max mem: 33369 +Epoch: [4] [ 50/1319] eta: 0:57:28 lr: 4.543266685057974e-05 loss: 0.1042 (0.1300) time: 2.7824 data: 0.0072 max mem: 33369 +Epoch: [4] [ 60/1319] eta: 0:57:17 lr: 4.54240463055538e-05 loss: 0.1202 (0.1325) time: 2.8598 data: 0.0075 max mem: 33369 +Epoch: [4] [ 70/1319] eta: 0:57:08 lr: 4.541542557874611e-05 loss: 0.1217 (0.1311) time: 2.8158 data: 0.0075 max mem: 33369 +Epoch: [4] [ 80/1319] eta: 0:56:51 lr: 4.540680467011449e-05 loss: 0.1431 (0.1350) time: 2.8217 data: 0.0072 max mem: 33369 +Epoch: [4] [ 90/1319] eta: 0:56:30 lr: 4.5398183579616753e-05 loss: 0.1424 (0.1370) time: 2.8065 data: 0.0068 max mem: 33369 +Epoch: [4] [ 100/1319] eta: 0:56:03 lr: 4.5389562307210684e-05 loss: 0.1284 (0.1366) time: 2.7834 data: 0.0067 max mem: 33369 +Epoch: [4] [ 110/1319] eta: 0:55:34 lr: 4.5380940852854056e-05 loss: 0.1253 (0.1363) time: 2.7544 data: 0.0067 max mem: 33369 +Epoch: [4] [ 120/1319] eta: 0:55:13 lr: 4.537231921650461e-05 loss: 0.1239 (0.1357) time: 2.7854 data: 0.0066 max mem: 33369 +Epoch: [4] [ 130/1319] eta: 0:54:44 lr: 4.53636973981201e-05 loss: 0.1246 (0.1352) time: 2.7878 data: 0.0067 max mem: 33369 +Epoch: [4] [ 140/1319] eta: 0:54:14 lr: 4.535507539765821e-05 loss: 0.1291 (0.1359) time: 2.7398 data: 0.0069 max mem: 33369 +Epoch: [4] [ 150/1319] eta: 0:53:47 lr: 4.534645321507665e-05 loss: 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4.527746919303318e-05 loss: 0.1246 (0.1351) time: 2.7737 data: 0.0069 max mem: 33369 +Epoch: [4] [ 240/1319] eta: 0:49:38 lr: 4.5268845369467734e-05 loss: 0.1209 (0.1343) time: 2.7779 data: 0.0069 max mem: 33369 +Epoch: [4] [ 250/1319] eta: 0:49:11 lr: 4.526022136335852e-05 loss: 0.1200 (0.1341) time: 2.7624 data: 0.0069 max mem: 33369 +Epoch: [4] [ 260/1319] eta: 0:48:43 lr: 4.525159717466304e-05 loss: 0.1351 (0.1357) time: 2.7573 data: 0.0069 max mem: 33369 +Epoch: [4] [ 270/1319] eta: 0:48:15 lr: 4.524297280333875e-05 loss: 0.1248 (0.1360) time: 2.7535 data: 0.0071 max mem: 33369 +Epoch: [4] [ 280/1319] eta: 0:47:48 lr: 4.5234348249343114e-05 loss: 0.1157 (0.1360) time: 2.7664 data: 0.0070 max mem: 33369 +Epoch: [4] [ 290/1319] eta: 0:47:21 lr: 4.522572351263354e-05 loss: 0.1190 (0.1363) time: 2.7766 data: 0.0068 max mem: 33369 +Epoch: [4] [ 300/1319] eta: 0:46:55 lr: 4.521709859316746e-05 loss: 0.1235 (0.1362) time: 2.7853 data: 0.0070 max mem: 33369 +Epoch: [4] [ 310/1319] eta: 0:46:27 lr: 4.520847349090225e-05 loss: 0.1211 (0.1358) time: 2.7730 data: 0.0071 max mem: 33369 +Epoch: [4] [ 320/1319] eta: 0:45:58 lr: 4.5199848205795306e-05 loss: 0.1222 (0.1359) time: 2.7433 data: 0.0071 max mem: 33369 +Epoch: [4] [ 330/1319] eta: 0:45:27 lr: 4.519122273780396e-05 loss: 0.1222 (0.1352) time: 2.6918 data: 0.0073 max mem: 33369 +Epoch: [4] [ 340/1319] eta: 0:44:55 lr: 4.518259708688556e-05 loss: 0.1244 (0.1353) time: 2.6196 data: 0.0073 max mem: 33369 +Epoch: [4] [ 350/1319] eta: 0:44:25 lr: 4.5173971252997424e-05 loss: 0.1353 (0.1356) time: 2.6334 data: 0.0071 max mem: 33369 +Epoch: [4] [ 360/1319] eta: 0:43:55 lr: 4.5165345236096837e-05 loss: 0.1351 (0.1358) time: 2.6604 data: 0.0070 max mem: 33369 +Epoch: [4] [ 370/1319] eta: 0:43:24 lr: 4.5156719036141086e-05 loss: 0.1319 (0.1357) time: 2.6234 data: 0.0067 max mem: 33369 +Epoch: [4] [ 380/1319] eta: 0:42:53 lr: 4.5148092653087434e-05 loss: 0.1319 (0.1363) time: 2.6165 data: 0.0068 max mem: 33369 +Epoch: [4] [ 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+Epoch: [4] [ 470/1319] eta: 0:38:52 lr: 4.507044695913725e-05 loss: 0.1414 (0.1372) time: 2.7534 data: 0.0068 max mem: 33369 +Epoch: [4] [ 480/1319] eta: 0:38:25 lr: 4.506181874274963e-05 loss: 0.1101 (0.1366) time: 2.7568 data: 0.0069 max mem: 33369 +Epoch: [4] [ 490/1319] eta: 0:37:58 lr: 4.5053190342792706e-05 loss: 0.1098 (0.1366) time: 2.7689 data: 0.0068 max mem: 33369 +Epoch: [4] [ 500/1319] eta: 0:37:31 lr: 4.50445617592235e-05 loss: 0.1098 (0.1366) time: 2.7755 data: 0.0067 max mem: 33369 +Epoch: [4] [ 510/1319] eta: 0:37:04 lr: 4.503593299199903e-05 loss: 0.1164 (0.1366) time: 2.7674 data: 0.0069 max mem: 33369 +Epoch: [4] [ 520/1319] eta: 0:36:37 lr: 4.502730404107628e-05 loss: 0.1348 (0.1365) time: 2.7676 data: 0.0069 max mem: 33369 +Epoch: [4] [ 530/1319] eta: 0:36:10 lr: 4.5018674906412226e-05 loss: 0.1148 (0.1362) time: 2.7837 data: 0.0070 max mem: 33369 +Epoch: [4] [ 540/1319] eta: 0:35:42 lr: 4.5010045587963815e-05 loss: 0.1140 (0.1361) time: 2.7595 data: 0.0068 max 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(0.1348) time: 2.7579 data: 0.0071 max mem: 33369 +Epoch: [4] [ 790/1319] eta: 0:24:11 lr: 4.4794252770532266e-05 loss: 0.1147 (0.1345) time: 2.7651 data: 0.0070 max mem: 33369 +Epoch: [4] [ 800/1319] eta: 0:23:44 lr: 4.4785618658517975e-05 loss: 0.1136 (0.1343) time: 2.7452 data: 0.0069 max mem: 33369 +Epoch: [4] [ 810/1319] eta: 0:23:17 lr: 4.477698436154974e-05 loss: 0.1136 (0.1342) time: 2.7694 data: 0.0069 max mem: 33369 +Epoch: [4] [ 820/1319] eta: 0:22:49 lr: 4.476834987958398e-05 loss: 0.1242 (0.1343) time: 2.7572 data: 0.0068 max mem: 33369 +Epoch: [4] [ 830/1319] eta: 0:22:22 lr: 4.4759715212577086e-05 loss: 0.1369 (0.1345) time: 2.7285 data: 0.0068 max mem: 33369 +Epoch: [4] [ 840/1319] eta: 0:21:54 lr: 4.475108036048542e-05 loss: 0.1325 (0.1347) time: 2.7472 data: 0.0069 max mem: 33369 +Epoch: [4] [ 850/1319] eta: 0:21:27 lr: 4.4742445323265344e-05 loss: 0.1348 (0.1348) time: 2.7615 data: 0.0068 max mem: 33369 +Epoch: [4] [ 860/1319] eta: 0:21:00 lr: 4.473381010087318e-05 loss: 0.1348 (0.1347) time: 2.7881 data: 0.0067 max mem: 33369 +Epoch: [4] [ 870/1319] eta: 0:20:32 lr: 4.4725174693265234e-05 loss: 0.1113 (0.1345) time: 2.7759 data: 0.0067 max mem: 33369 +Epoch: [4] [ 880/1319] eta: 0:20:05 lr: 4.471653910039782e-05 loss: 0.1272 (0.1349) time: 2.7388 data: 0.0067 max mem: 33369 +Epoch: [4] [ 890/1319] eta: 0:19:37 lr: 4.4707903322227184e-05 loss: 0.1398 (0.1348) time: 2.7367 data: 0.0067 max mem: 33369 +Epoch: [4] [ 900/1319] eta: 0:19:10 lr: 4.469926735870959e-05 loss: 0.1267 (0.1348) time: 2.7583 data: 0.0067 max mem: 33369 +Epoch: [4] [ 910/1319] eta: 0:18:43 lr: 4.4690631209801266e-05 loss: 0.1142 (0.1348) time: 2.7537 data: 0.0067 max mem: 33369 +Epoch: [4] [ 920/1319] eta: 0:18:15 lr: 4.4681994875458425e-05 loss: 0.1210 (0.1348) time: 2.7751 data: 0.0066 max mem: 33369 +Epoch: [4] [ 930/1319] eta: 0:17:48 lr: 4.467335835563727e-05 loss: 0.1210 (0.1345) time: 2.7844 data: 0.0069 max mem: 33369 +Epoch: [4] [ 940/1319] eta: 0:17:21 lr: 4.466472165029396e-05 loss: 0.1205 (0.1346) time: 2.7702 data: 0.0068 max mem: 33369 +Epoch: [4] [ 950/1319] eta: 0:16:53 lr: 4.4656084759384645e-05 loss: 0.1221 (0.1346) time: 2.7786 data: 0.0066 max mem: 33369 +Epoch: [4] [ 960/1319] eta: 0:16:26 lr: 4.464744768286547e-05 loss: 0.1305 (0.1346) time: 2.7533 data: 0.0066 max mem: 33369 +Epoch: [4] [ 970/1319] eta: 0:15:58 lr: 4.463881042069255e-05 loss: 0.1252 (0.1346) time: 2.7362 data: 0.0067 max mem: 33369 +Epoch: [4] [ 980/1319] eta: 0:15:31 lr: 4.463017297282197e-05 loss: 0.1182 (0.1344) time: 2.7266 data: 0.0067 max mem: 33369 +Epoch: [4] [ 990/1319] eta: 0:15:03 lr: 4.4621535339209816e-05 loss: 0.1182 (0.1345) time: 2.7595 data: 0.0066 max mem: 33369 +Epoch: [4] [1000/1319] eta: 0:14:36 lr: 4.461289751981212e-05 loss: 0.1221 (0.1344) time: 2.7650 data: 0.0066 max mem: 33369 +Epoch: [4] [1010/1319] eta: 0:14:08 lr: 4.460425951458493e-05 loss: 0.1139 (0.1344) time: 2.7253 data: 0.0066 max mem: 33369 +Epoch: [4] [1020/1319] eta: 0:13:40 lr: 4.459562132348427e-05 loss: 0.1340 (0.1345) time: 2.6743 data: 0.0067 max mem: 33369 +Epoch: [4] [1030/1319] eta: 0:13:13 lr: 4.458698294646612e-05 loss: 0.1247 (0.1343) time: 2.6330 data: 0.0067 max mem: 33369 +Epoch: [4] [1040/1319] eta: 0:12:45 lr: 4.457834438348646e-05 loss: 0.0989 (0.1340) time: 2.6103 data: 0.0066 max mem: 33369 +Epoch: [4] [1050/1319] eta: 0:12:17 lr: 4.456970563450125e-05 loss: 0.1018 (0.1340) time: 2.5868 data: 0.0068 max mem: 33369 +Epoch: [4] [1060/1319] eta: 0:11:49 lr: 4.456106669946641e-05 loss: 0.1188 (0.1339) time: 2.6366 data: 0.0068 max mem: 33369 +Epoch: [4] [1070/1319] eta: 0:11:22 lr: 4.4552427578337865e-05 loss: 0.1188 (0.1337) time: 2.6533 data: 0.0066 max mem: 33369 +Epoch: [4] [1080/1319] eta: 0:10:54 lr: 4.45437882710715e-05 loss: 0.1326 (0.1338) time: 2.6809 data: 0.0070 max mem: 33369 +Epoch: [4] [1090/1319] eta: 0:10:27 lr: 4.453514877762321e-05 loss: 0.1384 (0.1337) time: 2.7561 data: 0.0075 max mem: 33369 +Epoch: [4] [1100/1319] eta: 0:10:00 lr: 4.4526509097948836e-05 loss: 0.1181 (0.1337) time: 2.7889 data: 0.0074 max mem: 33369 +Epoch: [4] [1110/1319] eta: 0:09:32 lr: 4.451786923200421e-05 loss: 0.1261 (0.1337) time: 2.7667 data: 0.0072 max mem: 33369 +Epoch: [4] [1120/1319] eta: 0:09:05 lr: 4.450922917974515e-05 loss: 0.1425 (0.1339) time: 2.7352 data: 0.0070 max mem: 33369 +Epoch: [4] [1130/1319] eta: 0:08:38 lr: 4.4500588941127465e-05 loss: 0.1493 (0.1340) time: 2.7397 data: 0.0069 max mem: 33369 +Epoch: [4] [1140/1319] eta: 0:08:10 lr: 4.449194851610691e-05 loss: 0.1321 (0.1341) time: 2.7771 data: 0.0068 max mem: 33369 +Epoch: [4] [1150/1319] eta: 0:07:43 lr: 4.4483307904639245e-05 loss: 0.1186 (0.1339) time: 2.7681 data: 0.0067 max mem: 33369 +Epoch: [4] [1160/1319] eta: 0:07:15 lr: 4.447466710668021e-05 loss: 0.1186 (0.1340) time: 2.7489 data: 0.0068 max mem: 33369 +Epoch: [4] [1170/1319] eta: 0:06:48 lr: 4.4466026122185514e-05 loss: 0.1235 (0.1339) time: 2.7608 data: 0.0068 max mem: 33369 +Epoch: [4] [1180/1319] eta: 0:06:21 lr: 4.4457384951110855e-05 loss: 0.1192 (0.1340) time: 2.7453 data: 0.0066 max mem: 33369 +Epoch: [4] [1190/1319] eta: 0:05:53 lr: 4.44487435934119e-05 loss: 0.1238 (0.1339) time: 2.7415 data: 0.0066 max mem: 33369 +Epoch: [4] [1200/1319] eta: 0:05:26 lr: 4.4440102049044326e-05 loss: 0.1156 (0.1338) time: 2.7629 data: 0.0065 max mem: 33369 +Epoch: [4] [1210/1319] eta: 0:04:58 lr: 4.443146031796374e-05 loss: 0.1246 (0.1338) time: 2.7697 data: 0.0067 max mem: 33369 +Epoch: [4] [1220/1319] eta: 0:04:31 lr: 4.442281840012577e-05 loss: 0.1351 (0.1341) time: 2.7656 data: 0.0067 max mem: 33369 +Epoch: [4] [1230/1319] eta: 0:04:04 lr: 4.441417629548601e-05 loss: 0.1434 (0.1342) time: 2.7556 data: 0.0066 max mem: 33369 +Epoch: [4] [1240/1319] eta: 0:03:36 lr: 4.4405534004000035e-05 loss: 0.1310 (0.1343) time: 2.7501 data: 0.0068 max mem: 33369 +Epoch: [4] [1250/1319] eta: 0:03:09 lr: 4.439689152562339e-05 loss: 0.1295 (0.1343) time: 2.7400 data: 0.0067 max mem: 33369 +Epoch: [4] [1260/1319] eta: 0:02:41 lr: 4.438824886031161e-05 loss: 0.1325 (0.1344) time: 2.7539 data: 0.0068 max mem: 33369 +Epoch: [4] [1270/1319] eta: 0:02:14 lr: 4.437960600802022e-05 loss: 0.1178 (0.1343) time: 2.7689 data: 0.0068 max mem: 33369 +Epoch: [4] [1280/1319] eta: 0:01:46 lr: 4.4370962968704706e-05 loss: 0.1164 (0.1344) time: 2.7354 data: 0.0066 max mem: 33369 +Epoch: [4] [1290/1319] eta: 0:01:19 lr: 4.436231974232054e-05 loss: 0.1147 (0.1342) time: 2.7082 data: 0.0068 max mem: 33369 +Epoch: [4] [1300/1319] eta: 0:00:52 lr: 4.435367632882316e-05 loss: 0.1078 (0.1342) time: 2.6975 data: 0.0068 max mem: 33369 +Epoch: [4] [1310/1319] eta: 0:00:24 lr: 4.434503272816803e-05 loss: 0.1112 (0.1341) time: 2.7301 data: 0.0065 max mem: 33369 +Epoch: [4] Total time: 1:00:17 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 2:08:42 time: 3.0013 data: 2.9189 max mem: 33369 +Test: [ 100/2573] eta: 0:04:10 time: 0.0717 data: 0.0012 max mem: 33369 +Test: [ 200/2573] eta: 0:03:28 time: 0.0736 data: 0.0012 max mem: 33369 +Test: [ 300/2573] eta: 0:03:08 time: 0.0753 data: 0.0011 max mem: 33369 +Test: [ 400/2573] eta: 0:02:54 time: 0.0757 data: 0.0011 max mem: 33369 +Test: [ 500/2573] eta: 0:02:44 time: 0.0741 data: 0.0012 max mem: 33369 +Test: [ 600/2573] eta: 0:02:34 time: 0.0739 data: 0.0012 max mem: 33369 +Test: [ 700/2573] eta: 0:02:26 time: 0.0741 data: 0.0012 max mem: 33369 +Test: [ 800/2573] eta: 0:02:17 time: 0.0774 data: 0.0011 max mem: 33369 +Test: [ 900/2573] eta: 0:02:09 time: 0.0741 data: 0.0012 max mem: 33369 +Test: [1000/2573] eta: 0:02:01 time: 0.0740 data: 0.0012 max mem: 33369 +Test: [1100/2573] eta: 0:01:53 time: 0.0743 data: 0.0012 max mem: 33369 +Test: [1200/2573] eta: 0:01:45 time: 0.0740 data: 0.0011 max mem: 33369 +Test: [1300/2573] eta: 0:01:37 time: 0.0740 data: 0.0011 max mem: 33369 +Test: [1400/2573] eta: 0:01:29 time: 0.0724 data: 0.0012 max mem: 33369 +Test: [1500/2573] eta: 0:01:21 time: 0.0737 data: 0.0011 max mem: 33369 +Test: [1600/2573] eta: 0:01:13 time: 0.0777 data: 0.0012 max mem: 33369 +Test: [1700/2573] eta: 0:01:06 time: 0.0722 data: 0.0011 max mem: 33369 +Test: [1800/2573] eta: 0:00:58 time: 0.0754 data: 0.0011 max mem: 33369 +Test: [1900/2573] eta: 0:00:50 time: 0.0721 data: 0.0011 max mem: 33369 +Test: [2000/2573] eta: 0:00:43 time: 0.0738 data: 0.0011 max mem: 33369 +Test: [2100/2573] eta: 0:00:35 time: 0.0754 data: 0.0011 max mem: 33369 +Test: [2200/2573] eta: 0:00:28 time: 0.0754 data: 0.0011 max mem: 33369 +Test: [2300/2573] eta: 0:00:20 time: 0.0754 data: 0.0011 max mem: 33369 +Test: [2400/2573] eta: 0:00:12 time: 0.0705 data: 0.0011 max mem: 33369 +Test: [2500/2573] eta: 0:00:05 time: 0.0738 data: 0.0011 max mem: 33369 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: Total time: 0:03:13 +Final results: +Mean IoU is 49.39 + + precision@0.5 = 55.11 + precision@0.6 = 48.75 + precision@0.7 = 39.54 + precision@0.8 = 27.86 + precision@0.9 = 11.17 + overall IoU = 51.36 + +Average object IoU 49.386787569323104 +Overall IoU 51.3555793762207 +Better epoch: 4 + +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [5] [ 0/1319] eta: 2:11:51 lr: 4.433725332752167e-05 loss: 0.1265 (0.1265) time: 5.9979 data: 3.2640 max mem: 33369 +Epoch: [5] [ 10/1319] eta: 1:04:16 lr: 4.432860937114392e-05 loss: 0.0916 (0.1253) time: 2.9463 data: 0.3026 max mem: 33369 +Epoch: [5] [ 20/1319] eta: 1:00:34 lr: 4.4319965227479046e-05 loss: 0.1055 (0.1240) time: 2.6379 data: 0.0063 max mem: 33369 +Epoch: [5] [ 30/1319] eta: 1:00:03 lr: 4.43113208964824e-05 loss: 0.1165 (0.1214) time: 2.7122 data: 0.0067 max mem: 33369 +Epoch: [5] [ 40/1319] eta: 0:59:42 lr: 4.43026763781093e-05 loss: 0.1026 (0.1181) time: 2.8038 data: 0.0072 max mem: 33369 +Epoch: [5] [ 50/1319] eta: 0:59:04 lr: 4.429403167231508e-05 loss: 0.1185 (0.1227) time: 2.7895 data: 0.0073 max mem: 33369 +Epoch: [5] [ 60/1319] eta: 0:58:32 lr: 4.428538677905502e-05 loss: 0.1072 (0.1211) time: 2.7671 data: 0.0071 max mem: 33369 +Epoch: [5] [ 70/1319] eta: 0:58:02 lr: 4.4276741698284395e-05 loss: 0.1280 (0.1235) time: 2.7752 data: 0.0070 max mem: 33369 +Epoch: [5] [ 80/1319] eta: 0:57:29 lr: 4.4268096429958464e-05 loss: 0.1280 (0.1224) time: 2.7661 data: 0.0069 max mem: 33369 +Epoch: [5] [ 90/1319] eta: 0:57:04 lr: 4.425945097403244e-05 loss: 0.0978 (0.1212) time: 2.7807 data: 0.0067 max mem: 33369 +Epoch: [5] [ 100/1319] eta: 0:56:33 lr: 4.425080533046155e-05 loss: 0.1114 (0.1200) time: 2.7825 data: 0.0067 max mem: 33369 +Epoch: [5] [ 110/1319] eta: 0:56:03 lr: 4.424215949920098e-05 loss: 0.1128 (0.1205) time: 2.7617 data: 0.0067 max mem: 33369 +Epoch: [5] [ 120/1319] eta: 0:55:30 lr: 4.423351348020589e-05 loss: 0.1343 (0.1227) time: 2.7470 data: 0.0068 max mem: 33369 +Epoch: [5] [ 130/1319] eta: 0:55:01 lr: 4.4224867273431445e-05 loss: 0.1129 (0.1216) time: 2.7484 data: 0.0067 max mem: 33369 +Epoch: [5] [ 140/1319] eta: 0:54:30 lr: 4.421622087883277e-05 loss: 0.1044 (0.1222) time: 2.7525 data: 0.0067 max mem: 33369 +Epoch: [5] [ 150/1319] eta: 0:54:03 lr: 4.4207574296364965e-05 loss: 0.1076 (0.1221) time: 2.7586 data: 0.0069 max mem: 33369 +Epoch: [5] [ 160/1319] eta: 0:53:31 lr: 4.419892752598312e-05 loss: 0.1062 (0.1223) time: 2.7521 data: 0.0069 max mem: 33369 +Epoch: [5] [ 170/1319] eta: 0:53:04 lr: 4.419028056764231e-05 loss: 0.1091 (0.1234) time: 2.7483 data: 0.0071 max mem: 33369 +Epoch: [5] [ 180/1319] eta: 0:52:34 lr: 4.418163342129758e-05 loss: 0.1279 (0.1231) time: 2.7575 data: 0.0071 max mem: 33369 +Epoch: [5] [ 190/1319] eta: 0:52:04 lr: 4.417298608690395e-05 loss: 0.1247 (0.1240) time: 2.7357 data: 0.0070 max mem: 33369 +Epoch: [5] [ 200/1319] eta: 0:51:36 lr: 4.416433856441643e-05 loss: 0.1132 (0.1236) time: 2.7423 data: 0.0070 max mem: 33369 +Epoch: [5] [ 210/1319] eta: 0:51:07 lr: 4.415569085379001e-05 loss: 0.1091 (0.1234) time: 2.7550 data: 0.0070 max mem: 33369 +Epoch: [5] [ 220/1319] eta: 0:50:38 lr: 4.4147042954979643e-05 loss: 0.1158 (0.1234) time: 2.7467 data: 0.0071 max mem: 33369 +Epoch: [5] [ 230/1319] eta: 0:50:12 lr: 4.413839486794028e-05 loss: 0.1372 (0.1235) time: 2.7700 data: 0.0070 max mem: 33369 +Epoch: [5] [ 240/1319] eta: 0:49:44 lr: 4.412974659262685e-05 loss: 0.1269 (0.1235) time: 2.7739 data: 0.0068 max mem: 33369 +Epoch: [5] [ 250/1319] eta: 0:49:15 lr: 4.412109812899424e-05 loss: 0.1105 (0.1232) time: 2.7420 data: 0.0068 max mem: 33369 +Epoch: [5] [ 260/1319] eta: 0:48:48 lr: 4.411244947699735e-05 loss: 0.0990 (0.1231) time: 2.7535 data: 0.0070 max mem: 33369 +Epoch: [5] [ 270/1319] eta: 0:48:19 lr: 4.4103800636591036e-05 loss: 0.1144 (0.1235) time: 2.7497 data: 0.0071 max mem: 33369 +Epoch: [5] [ 280/1319] eta: 0:47:52 lr: 4.409515160773014e-05 loss: 0.1278 (0.1235) time: 2.7550 data: 0.0070 max mem: 33369 +Epoch: [5] [ 290/1319] eta: 0:47:23 lr: 4.408650239036947e-05 loss: 0.1136 (0.1241) time: 2.7568 data: 0.0072 max mem: 33369 +Epoch: [5] [ 300/1319] eta: 0:46:55 lr: 4.407785298446384e-05 loss: 0.1103 (0.1237) time: 2.7402 data: 0.0071 max mem: 33369 +Epoch: [5] [ 310/1319] eta: 0:46:26 lr: 4.406920338996803e-05 loss: 0.1103 (0.1237) time: 2.7367 data: 0.0068 max mem: 33369 +Epoch: [5] [ 320/1319] eta: 0:45:55 lr: 4.406055360683679e-05 loss: 0.1048 (0.1234) time: 2.6905 data: 0.0067 max mem: 33369 +Epoch: [5] [ 330/1319] eta: 0:45:24 lr: 4.4051903635024855e-05 loss: 0.1152 (0.1238) time: 2.6483 data: 0.0068 max mem: 33369 +Epoch: [5] [ 340/1319] eta: 0:44:52 lr: 4.404325347448695e-05 loss: 0.1181 (0.1234) time: 2.6295 data: 0.0067 max mem: 33369 +Epoch: [5] [ 350/1319] eta: 0:44:23 lr: 4.403460312517776e-05 loss: 0.0973 (0.1227) time: 2.6437 data: 0.0067 max mem: 33369 +Epoch: [5] [ 360/1319] eta: 0:43:53 lr: 4.402595258705198e-05 loss: 0.1168 (0.1231) time: 2.6702 data: 0.0067 max mem: 33369 +Epoch: [5] [ 370/1319] eta: 0:43:28 lr: 4.401730186006425e-05 loss: 0.1278 (0.1237) time: 2.7476 data: 0.0070 max mem: 33369 +Epoch: [5] [ 380/1319] eta: 0:43:01 lr: 4.40086509441692e-05 loss: 0.1271 (0.1238) time: 2.8141 data: 0.0075 max mem: 33369 +Epoch: [5] [ 390/1319] eta: 0:42:35 lr: 4.399999983932147e-05 loss: 0.1289 (0.1238) time: 2.8059 data: 0.0073 max mem: 33369 +Epoch: [5] [ 400/1319] eta: 0:42:09 lr: 4.399134854547561e-05 loss: 0.1304 (0.1240) time: 2.8047 data: 0.0070 max mem: 33369 +Epoch: [5] [ 410/1319] eta: 0:41:42 lr: 4.3982697062586214e-05 loss: 0.1171 (0.1237) time: 2.7941 data: 0.0070 max mem: 33369 +Epoch: [5] [ 420/1319] eta: 0:41:15 lr: 4.397404539060784e-05 loss: 0.1050 (0.1236) time: 2.7831 data: 0.0070 max mem: 33369 +Epoch: [5] [ 430/1319] eta: 0:40:48 lr: 4.3965393529495005e-05 loss: 0.1050 (0.1233) time: 2.7692 data: 0.0070 max mem: 33369 +Epoch: [5] [ 440/1319] eta: 0:40:21 lr: 4.3956741479202226e-05 loss: 0.1043 (0.1231) time: 2.7801 data: 0.0071 max mem: 33369 +Epoch: [5] [ 450/1319] eta: 0:39:54 lr: 4.3948089239683975e-05 loss: 0.1126 (0.1231) time: 2.7762 data: 0.0068 max mem: 33369 +Epoch: [5] [ 460/1319] eta: 0:39:26 lr: 4.3939436810894734e-05 loss: 0.1233 (0.1234) time: 2.7583 data: 0.0065 max mem: 33369 +Epoch: [5] [ 470/1319] eta: 0:38:59 lr: 4.393078419278895e-05 loss: 0.1346 (0.1234) time: 2.7569 data: 0.0068 max mem: 33369 +Epoch: [5] [ 480/1319] eta: 0:38:31 lr: 4.3922131385321036e-05 loss: 0.1291 (0.1234) time: 2.7486 data: 0.0069 max mem: 33369 +Epoch: [5] [ 490/1319] eta: 0:38:03 lr: 4.3913478388445405e-05 loss: 0.1206 (0.1235) time: 2.7339 data: 0.0069 max mem: 33369 +Epoch: [5] [ 500/1319] eta: 0:37:36 lr: 4.390482520211644e-05 loss: 0.1139 (0.1232) time: 2.7558 data: 0.0069 max mem: 33369 +Epoch: [5] [ 510/1319] eta: 0:37:08 lr: 4.389617182628851e-05 loss: 0.1136 (0.1231) time: 2.7519 data: 0.0066 max mem: 33369 +Epoch: [5] [ 520/1319] eta: 0:36:40 lr: 4.3887518260915935e-05 loss: 0.1209 (0.1231) time: 2.7375 data: 0.0066 max mem: 33369 +Epoch: [5] [ 530/1319] eta: 0:36:13 lr: 4.3878864505953046e-05 loss: 0.1057 (0.1228) time: 2.7597 data: 0.0066 max mem: 33369 +Epoch: [5] [ 540/1319] eta: 0:35:44 lr: 4.387021056135415e-05 loss: 0.1212 (0.1233) time: 2.7304 data: 0.0068 max mem: 33369 +Epoch: [5] [ 550/1319] eta: 0:35:17 lr: 4.386155642707351e-05 loss: 0.1511 (0.1236) time: 2.7243 data: 0.0067 max mem: 33369 +Epoch: [5] [ 560/1319] eta: 0:34:49 lr: 4.3852902103065404e-05 loss: 0.1119 (0.1236) time: 2.7464 data: 0.0068 max mem: 33369 +Epoch: [5] [ 570/1319] eta: 0:34:21 lr: 4.3844247589284045e-05 loss: 0.1067 (0.1235) time: 2.7451 data: 0.0070 max mem: 33369 +Epoch: [5] [ 580/1319] eta: 0:33:54 lr: 4.383559288568366e-05 loss: 0.1092 (0.1236) time: 2.7314 data: 0.0071 max mem: 33369 +Epoch: [5] [ 590/1319] eta: 0:33:26 lr: 4.382693799221843e-05 loss: 0.1127 (0.1235) time: 2.7220 data: 0.0069 max mem: 33369 +Epoch: [5] [ 600/1319] eta: 0:32:58 lr: 4.381828290884256e-05 loss: 0.1127 (0.1237) time: 2.7500 data: 0.0068 max mem: 33369 +Epoch: [5] [ 610/1319] eta: 0:32:31 lr: 4.380962763551017e-05 loss: 0.1134 (0.1235) time: 2.7717 data: 0.0072 max mem: 33369 +Epoch: [5] [ 620/1319] eta: 0:32:03 lr: 4.38009721721754e-05 loss: 0.1027 (0.1234) time: 2.7563 data: 0.0071 max mem: 33369 +Epoch: [5] [ 630/1319] eta: 0:31:36 lr: 4.3792316518792354e-05 loss: 0.0908 (0.1229) time: 2.7589 data: 0.0069 max mem: 33369 +Epoch: [5] [ 640/1319] eta: 0:31:08 lr: 4.378366067531513e-05 loss: 0.1016 (0.1230) time: 2.7505 data: 0.0071 max mem: 33369 +Epoch: [5] [ 650/1319] eta: 0:30:40 lr: 4.37750046416978e-05 loss: 0.1133 (0.1230) time: 2.6890 data: 0.0070 max mem: 33369 +Epoch: [5] [ 660/1319] eta: 0:30:11 lr: 4.376634841789439e-05 loss: 0.1203 (0.1235) time: 2.6304 data: 0.0068 max mem: 33369 +Epoch: [5] [ 670/1319] eta: 0:29:43 lr: 4.375769200385893e-05 loss: 0.1214 (0.1235) time: 2.6393 data: 0.0067 max mem: 33369 +Epoch: [5] [ 680/1319] eta: 0:29:14 lr: 4.3749035399545434e-05 loss: 0.1214 (0.1238) time: 2.6354 data: 0.0067 max mem: 33369 +Epoch: [5] [ 690/1319] eta: 0:28:46 lr: 4.374037860490788e-05 loss: 0.1230 (0.1239) time: 2.6366 data: 0.0069 max mem: 33369 +Epoch: [5] [ 700/1319] eta: 0:28:18 lr: 4.373172161990022e-05 loss: 0.1170 (0.1238) time: 2.6731 data: 0.0068 max mem: 33369 +Epoch: [5] [ 710/1319] eta: 0:27:49 lr: 4.372306444447641e-05 loss: 0.1068 (0.1239) time: 2.6668 data: 0.0067 max mem: 33369 +Epoch: [5] [ 720/1319] eta: 0:27:21 lr: 4.3714407078590355e-05 loss: 0.1068 (0.1239) time: 2.6284 data: 0.0067 max mem: 33369 +Epoch: [5] [ 730/1319] eta: 0:26:53 lr: 4.370574952219595e-05 loss: 0.1128 (0.1240) time: 2.6381 data: 0.0067 max mem: 33369 +Epoch: [5] [ 740/1319] eta: 0:26:26 lr: 4.369709177524708e-05 loss: 0.1128 (0.1239) time: 2.7344 data: 0.0070 max mem: 33369 +Epoch: [5] [ 750/1319] eta: 0:25:59 lr: 4.36884338376976e-05 loss: 0.1193 (0.1240) time: 2.7834 data: 0.0075 max mem: 33369 +Epoch: [5] [ 760/1319] eta: 0:25:32 lr: 4.3679775709501325e-05 loss: 0.1255 (0.1241) time: 2.8001 data: 0.0077 max mem: 33369 +Epoch: [5] [ 770/1319] eta: 0:25:05 lr: 4.3671117390612085e-05 loss: 0.1212 (0.1241) time: 2.8166 data: 0.0074 max mem: 33369 +Epoch: [5] [ 780/1319] eta: 0:24:38 lr: 4.366245888098367e-05 loss: 0.1093 (0.1243) time: 2.7990 data: 0.0072 max mem: 33369 +Epoch: [5] [ 790/1319] eta: 0:24:11 lr: 4.3653800180569845e-05 loss: 0.1147 (0.1243) time: 2.7894 data: 0.0070 max mem: 33369 +Epoch: [5] [ 800/1319] eta: 0:23:44 lr: 4.364514128932435e-05 loss: 0.1083 (0.1241) time: 2.7829 data: 0.0069 max mem: 33369 +Epoch: [5] [ 810/1319] eta: 0:23:17 lr: 4.363648220720092e-05 loss: 0.0924 (0.1239) time: 2.7913 data: 0.0070 max mem: 33369 +Epoch: [5] [ 820/1319] eta: 0:22:49 lr: 4.3627822934153263e-05 loss: 0.1061 (0.1242) time: 2.7976 data: 0.0070 max mem: 33369 +Epoch: [5] [ 830/1319] eta: 0:22:22 lr: 4.361916347013505e-05 loss: 0.1180 (0.1241) time: 2.7571 data: 0.0070 max mem: 33369 +Epoch: [5] [ 840/1319] eta: 0:21:55 lr: 4.361050381509995e-05 loss: 0.1180 (0.1242) time: 2.7503 data: 0.0070 max mem: 33369 +Epoch: [5] [ 850/1319] eta: 0:21:27 lr: 4.3601843969001596e-05 loss: 0.1202 (0.1244) time: 2.7679 data: 0.0068 max mem: 33369 +Epoch: [5] [ 860/1319] eta: 0:21:00 lr: 4.359318393179363e-05 loss: 0.1196 (0.1244) time: 2.7598 data: 0.0067 max mem: 33369 +Epoch: [5] [ 870/1319] eta: 0:20:32 lr: 4.3584523703429616e-05 loss: 0.1303 (0.1247) time: 2.7357 data: 0.0070 max mem: 33369 +Epoch: [5] [ 880/1319] eta: 0:20:05 lr: 4.357586328386315e-05 loss: 0.1326 (0.1247) time: 2.7275 data: 0.0072 max mem: 33369 +Epoch: [5] [ 890/1319] eta: 0:19:37 lr: 4.356720267304778e-05 loss: 0.1113 (0.1248) time: 2.7364 data: 0.0069 max mem: 33369 +Epoch: [5] [ 900/1319] eta: 0:19:10 lr: 4.3558541870937056e-05 loss: 0.1105 (0.1247) time: 2.7393 data: 0.0069 max mem: 33369 +Epoch: [5] [ 910/1319] eta: 0:18:42 lr: 4.354988087748445e-05 loss: 0.1142 (0.1245) time: 2.7470 data: 0.0068 max mem: 33369 +Epoch: [5] [ 920/1319] eta: 0:18:15 lr: 4.35412196926435e-05 loss: 0.1146 (0.1247) time: 2.7462 data: 0.0068 max mem: 33369 +Epoch: [5] [ 930/1319] eta: 0:17:48 lr: 4.353255831636764e-05 loss: 0.1361 (0.1250) time: 2.7585 data: 0.0071 max mem: 33369 +Epoch: [5] [ 940/1319] eta: 0:17:20 lr: 4.352389674861032e-05 loss: 0.1382 (0.1251) time: 2.7605 data: 0.0071 max mem: 33369 +Epoch: [5] [ 950/1319] eta: 0:16:52 lr: 4.3515234989324975e-05 loss: 0.1250 (0.1252) time: 2.7251 data: 0.0073 max mem: 33369 +Epoch: [5] [ 960/1319] eta: 0:16:25 lr: 4.350657303846501e-05 loss: 0.1144 (0.1254) time: 2.7088 data: 0.0075 max mem: 33369 +Epoch: [5] [ 970/1319] eta: 0:15:58 lr: 4.34979108959838e-05 loss: 0.1096 (0.1252) time: 2.7461 data: 0.0073 max mem: 33369 +Epoch: [5] [ 980/1319] eta: 0:15:30 lr: 4.348924856183469e-05 loss: 0.1105 (0.1257) time: 2.7448 data: 0.0072 max mem: 33369 +Epoch: [5] [ 990/1319] eta: 0:15:03 lr: 4.348058603597104e-05 loss: 0.1346 (0.1259) time: 2.7566 data: 0.0070 max mem: 33369 +Epoch: [5] [1000/1319] eta: 0:14:35 lr: 4.347192331834616e-05 loss: 0.1139 (0.1260) time: 2.7486 data: 0.0069 max mem: 33369 +Epoch: [5] [1010/1319] eta: 0:14:08 lr: 4.346326040891335e-05 loss: 0.1180 (0.1260) time: 2.7556 data: 0.0070 max mem: 33369 +Epoch: [5] [1020/1319] eta: 0:13:40 lr: 4.345459730762588e-05 loss: 0.1180 (0.1261) time: 2.7432 data: 0.0069 max mem: 33369 +Epoch: [5] [1030/1319] eta: 0:13:12 lr: 4.344593401443699e-05 loss: 0.1326 (0.1262) time: 2.6636 data: 0.0069 max mem: 33369 +Epoch: [5] [1040/1319] eta: 0:12:45 lr: 4.343727052929992e-05 loss: 0.1173 (0.1261) time: 2.6367 data: 0.0069 max mem: 33369 +Epoch: [5] [1050/1319] eta: 0:12:17 lr: 4.342860685216788e-05 loss: 0.1016 (0.1261) time: 2.6364 data: 0.0068 max mem: 33369 +Epoch: [5] [1060/1319] eta: 0:11:49 lr: 4.341994298299405e-05 loss: 0.1115 (0.1263) time: 2.6136 data: 0.0068 max mem: 33369 +Epoch: [5] [1070/1319] eta: 0:11:22 lr: 4.341127892173159e-05 loss: 0.1286 (0.1266) time: 2.6131 data: 0.0069 max mem: 33369 +Epoch: [5] [1080/1319] eta: 0:10:54 lr: 4.3402614668333656e-05 loss: 0.1391 (0.1266) time: 2.6525 data: 0.0067 max mem: 33369 +Epoch: [5] [1090/1319] eta: 0:10:26 lr: 4.339395022275336e-05 loss: 0.1304 (0.1265) time: 2.6531 data: 0.0067 max mem: 33369 +Epoch: [5] [1100/1319] eta: 0:09:59 lr: 4.33852855849438e-05 loss: 0.1126 (0.1264) time: 2.7341 data: 0.0070 max mem: 33369 +Epoch: [5] [1110/1319] eta: 0:09:32 lr: 4.337662075485806e-05 loss: 0.1126 (0.1264) time: 2.8174 data: 0.0073 max mem: 33369 +Epoch: [5] [1120/1319] eta: 0:09:05 lr: 4.3367955732449175e-05 loss: 0.1240 (0.1264) time: 2.7777 data: 0.0073 max mem: 33369 +Epoch: [5] [1130/1319] eta: 0:08:37 lr: 4.3359290517670206e-05 loss: 0.1246 (0.1265) time: 2.7282 data: 0.0072 max mem: 33369 +Epoch: [5] [1140/1319] eta: 0:08:10 lr: 4.335062511047415e-05 loss: 0.1208 (0.1265) time: 2.7296 data: 0.0071 max mem: 33369 +Epoch: [5] [1150/1319] eta: 0:07:42 lr: 4.3341959510813994e-05 loss: 0.1190 (0.1264) time: 2.7420 data: 0.0069 max mem: 33369 +Epoch: [5] [1160/1319] eta: 0:07:15 lr: 4.33332937186427e-05 loss: 0.1070 (0.1262) time: 2.7699 data: 0.0070 max mem: 33369 +Epoch: [5] [1170/1319] eta: 0:06:48 lr: 4.332462773391324e-05 loss: 0.1152 (0.1263) time: 2.7711 data: 0.0070 max mem: 33369 +Epoch: [5] [1180/1319] eta: 0:06:20 lr: 4.331596155657851e-05 loss: 0.1279 (0.1264) time: 2.7495 data: 0.0068 max mem: 33369 +Epoch: [5] [1190/1319] eta: 0:05:53 lr: 4.3307295186591415e-05 loss: 0.1202 (0.1262) time: 2.7476 data: 0.0069 max mem: 33369 +Epoch: [5] [1200/1319] eta: 0:05:26 lr: 4.329862862390485e-05 loss: 0.1160 (0.1262) time: 2.7328 data: 0.0071 max mem: 33369 +Epoch: [5] [1210/1319] eta: 0:04:58 lr: 4.328996186847165e-05 loss: 0.1027 (0.1261) time: 2.7387 data: 0.0071 max mem: 33369 +Epoch: [5] [1220/1319] eta: 0:04:31 lr: 4.328129492024467e-05 loss: 0.1108 (0.1261) time: 2.7328 data: 0.0071 max mem: 33369 +Epoch: [5] [1230/1319] eta: 0:04:03 lr: 4.3272627779176715e-05 loss: 0.1117 (0.1260) time: 2.7439 data: 0.0069 max mem: 33369 +Epoch: [5] [1240/1319] eta: 0:03:36 lr: 4.326396044522058e-05 loss: 0.1138 (0.1260) time: 2.7468 data: 0.0068 max mem: 33369 +Epoch: [5] [1250/1319] eta: 0:03:09 lr: 4.3255292918329036e-05 loss: 0.1277 (0.1260) time: 2.7246 data: 0.0068 max mem: 33369 +Epoch: [5] [1260/1319] eta: 0:02:41 lr: 4.324662519845482e-05 loss: 0.1387 (0.1262) time: 2.7129 data: 0.0071 max mem: 33369 +Epoch: [5] [1270/1319] eta: 0:02:14 lr: 4.323795728555066e-05 loss: 0.1517 (0.1265) time: 2.7452 data: 0.0070 max mem: 33369 +Epoch: [5] [1280/1319] eta: 0:01:46 lr: 4.322928917956926e-05 loss: 0.1206 (0.1266) time: 2.7826 data: 0.0068 max mem: 33369 +Epoch: [5] [1290/1319] eta: 0:01:19 lr: 4.322062088046332e-05 loss: 0.1141 (0.1264) time: 2.7710 data: 0.0070 max mem: 33369 +Epoch: [5] [1300/1319] eta: 0:00:52 lr: 4.321195238818547e-05 loss: 0.1160 (0.1264) time: 2.7500 data: 0.0070 max mem: 33369 +Epoch: [5] [1310/1319] eta: 0:00:24 lr: 4.3203283702688355e-05 loss: 0.1151 (0.1263) time: 2.7525 data: 0.0066 max mem: 33369 +Epoch: [5] Total time: 1:00:15 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 2:12:14 time: 3.0838 data: 3.0014 max mem: 33369 +Test: [ 100/2573] eta: 0:04:12 time: 0.0717 data: 0.0012 max mem: 33369 +Test: [ 200/2573] eta: 0:03:29 time: 0.0735 data: 0.0012 max mem: 33369 +Test: [ 300/2573] eta: 0:03:08 time: 0.0750 data: 0.0012 max mem: 33369 +Test: [ 400/2573] eta: 0:02:55 time: 0.0753 data: 0.0011 max mem: 33369 +Test: [ 500/2573] eta: 0:02:44 time: 0.0743 data: 0.0012 max mem: 33369 +Test: [ 600/2573] eta: 0:02:34 time: 0.0742 data: 0.0012 max mem: 33369 +Test: [ 700/2573] eta: 0:02:26 time: 0.0740 data: 0.0012 max mem: 33369 +Test: [ 800/2573] eta: 0:02:17 time: 0.0773 data: 0.0012 max mem: 33369 +Test: [ 900/2573] eta: 0:02:09 time: 0.0740 data: 0.0012 max mem: 33369 +Test: [1000/2573] eta: 0:02:01 time: 0.0738 data: 0.0012 max mem: 33369 +Test: [1100/2573] eta: 0:01:53 time: 0.0739 data: 0.0012 max mem: 33369 +Test: [1200/2573] eta: 0:01:45 time: 0.0742 data: 0.0012 max mem: 33369 +Test: [1300/2573] eta: 0:01:37 time: 0.0742 data: 0.0012 max mem: 33369 +Test: [1400/2573] eta: 0:01:29 time: 0.0727 data: 0.0012 max mem: 33369 +Test: [1500/2573] eta: 0:01:21 time: 0.0741 data: 0.0012 max mem: 33369 +Test: [1600/2573] eta: 0:01:13 time: 0.0772 data: 0.0011 max mem: 33369 +Test: [1700/2573] eta: 0:01:06 time: 0.0724 data: 0.0012 max mem: 33369 +Test: [1800/2573] eta: 0:00:58 time: 0.0756 data: 0.0012 max mem: 33369 +Test: [1900/2573] eta: 0:00:50 time: 0.0726 data: 0.0012 max mem: 33369 +Test: [2000/2573] eta: 0:00:43 time: 0.0738 data: 0.0011 max mem: 33369 +Test: [2100/2573] eta: 0:00:35 time: 0.0754 data: 0.0011 max mem: 33369 +Test: [2200/2573] eta: 0:00:28 time: 0.0754 data: 0.0011 max mem: 33369 +Test: [2300/2573] eta: 0:00:20 time: 0.0753 data: 0.0011 max mem: 33369 +Test: [2400/2573] eta: 0:00:13 time: 0.0703 data: 0.0011 max mem: 33369 +Test: [2500/2573] eta: 0:00:05 time: 0.0737 data: 0.0011 max mem: 33369 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: Total time: 0:03:13 +Final results: +Mean IoU is 53.60 + + precision@0.5 = 59.64 + precision@0.6 = 52.74 + precision@0.7 = 43.40 + precision@0.8 = 31.56 + precision@0.9 = 12.83 + overall IoU = 53.66 + +Average object IoU 53.596965083730694 +Overall IoU 53.656768798828125 +Better epoch: 5 + +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [6] [ 0/1319] eta: 1:27:26 lr: 4.319548172049932e-05 loss: 0.0746 (0.0746) time: 3.9775 data: 1.1769 max mem: 33369 +Epoch: [6] [ 10/1319] eta: 1:00:19 lr: 4.318681266775505e-05 loss: 0.1001 (0.1175) time: 2.7655 data: 0.1127 max mem: 33369 +Epoch: [6] [ 20/1319] eta: 0:58:24 lr: 4.317814342165404e-05 loss: 0.1063 (0.1161) time: 2.6337 data: 0.0064 max mem: 33369 +Epoch: [6] [ 30/1319] eta: 0:57:34 lr: 4.316947398214883e-05 loss: 0.1063 (0.1125) time: 2.6326 data: 0.0065 max mem: 33369 +Epoch: [6] [ 40/1319] eta: 0:56:49 lr: 4.316080434919196e-05 loss: 0.1043 (0.1096) time: 2.6321 data: 0.0066 max mem: 33369 +Epoch: [6] [ 50/1319] eta: 0:56:29 lr: 4.315213452273593e-05 loss: 0.0917 (0.1106) time: 2.6565 data: 0.0069 max mem: 33369 +Epoch: [6] [ 60/1319] eta: 0:56:46 lr: 4.314346450273323e-05 loss: 0.0956 (0.1147) time: 2.7869 data: 0.0071 max mem: 33369 +Epoch: [6] [ 70/1319] eta: 0:56:39 lr: 4.313479428913631e-05 loss: 0.1174 (0.1143) time: 2.8520 data: 0.0072 max mem: 33369 +Epoch: [6] [ 80/1319] eta: 0:56:24 lr: 4.312612388189762e-05 loss: 0.1050 (0.1126) time: 2.8102 data: 0.0072 max mem: 33369 +Epoch: [6] [ 90/1319] eta: 0:56:05 lr: 4.311745328096956e-05 loss: 0.1019 (0.1123) time: 2.7991 data: 0.0070 max mem: 33369 +Epoch: [6] [ 100/1319] eta: 0:55:41 lr: 4.3108782486304546e-05 loss: 0.1015 (0.1112) time: 2.7830 data: 0.0069 max mem: 33369 +Epoch: [6] [ 110/1319] eta: 0:55:14 lr: 4.310011149785494e-05 loss: 0.1050 (0.1114) time: 2.7555 data: 0.0069 max mem: 33369 +Epoch: [6] [ 120/1319] eta: 0:54:48 lr: 4.309144031557308e-05 loss: 0.0984 (0.1108) time: 2.7481 data: 0.0069 max mem: 33369 +Epoch: [6] [ 130/1319] eta: 0:54:20 lr: 4.308276893941131e-05 loss: 0.1068 (0.1113) time: 2.7449 data: 0.0070 max mem: 33369 +Epoch: [6] [ 140/1319] eta: 0:53:53 lr: 4.307409736932192e-05 loss: 0.1007 (0.1102) time: 2.7404 data: 0.0076 max mem: 33369 +Epoch: [6] [ 150/1319] eta: 0:53:27 lr: 4.306542560525721e-05 loss: 0.0993 (0.1103) time: 2.7538 data: 0.0074 max mem: 33369 +Epoch: [6] [ 160/1319] eta: 0:52:59 lr: 4.305675364716942e-05 loss: 0.1020 (0.1099) time: 2.7513 data: 0.0065 max mem: 33369 +Epoch: [6] [ 170/1319] eta: 0:52:33 lr: 4.3048081495010805e-05 loss: 0.1076 (0.1100) time: 2.7515 data: 0.0067 max mem: 33369 +Epoch: [6] [ 180/1319] eta: 0:52:04 lr: 4.303940914873357e-05 loss: 0.1114 (0.1107) time: 2.7429 data: 0.0068 max mem: 33369 +Epoch: [6] [ 190/1319] eta: 0:51:37 lr: 4.30307366082899e-05 loss: 0.1136 (0.1105) time: 2.7350 data: 0.0066 max mem: 33369 +Epoch: [6] [ 200/1319] eta: 0:51:12 lr: 4.302206387363197e-05 loss: 0.1044 (0.1118) time: 2.7665 data: 0.0066 max mem: 33369 +Epoch: [6] [ 210/1319] eta: 0:50:44 lr: 4.301339094471194e-05 loss: 0.1123 (0.1116) time: 2.7620 data: 0.0068 max mem: 33369 +Epoch: [6] [ 220/1319] eta: 0:50:18 lr: 4.300471782148193e-05 loss: 0.1108 (0.1118) time: 2.7565 data: 0.0068 max mem: 33369 +Epoch: [6] [ 230/1319] eta: 0:49:49 lr: 4.299604450389403e-05 loss: 0.1027 (0.1115) time: 2.7427 data: 0.0068 max mem: 33369 +Epoch: [6] [ 240/1319] eta: 0:49:22 lr: 4.298737099190034e-05 loss: 0.1003 (0.1114) time: 2.7352 data: 0.0068 max mem: 33369 +Epoch: [6] [ 250/1319] eta: 0:48:54 lr: 4.297869728545289e-05 loss: 0.1065 (0.1114) time: 2.7482 data: 0.0071 max mem: 33369 +Epoch: [6] [ 260/1319] eta: 0:48:29 lr: 4.2970023384503735e-05 loss: 0.1096 (0.1111) time: 2.7661 data: 0.0070 max mem: 33369 +Epoch: [6] [ 270/1319] eta: 0:48:02 lr: 4.296134928900489e-05 loss: 0.0980 (0.1114) time: 2.7726 data: 0.0066 max mem: 33369 +Epoch: [6] [ 280/1319] eta: 0:47:35 lr: 4.295267499890832e-05 loss: 0.1020 (0.1121) time: 2.7650 data: 0.0066 max mem: 33369 +Epoch: [6] [ 290/1319] eta: 0:47:08 lr: 4.2944000514166015e-05 loss: 0.1041 (0.1126) time: 2.7741 data: 0.0066 max mem: 33369 +Epoch: [6] [ 300/1319] eta: 0:46:41 lr: 4.293532583472992e-05 loss: 0.1026 (0.1123) time: 2.7658 data: 0.0067 max mem: 33369 +Epoch: [6] [ 310/1319] eta: 0:46:14 lr: 4.292665096055194e-05 loss: 0.0978 (0.1121) time: 2.7595 data: 0.0068 max mem: 33369 +Epoch: [6] [ 320/1319] eta: 0:45:47 lr: 4.2917975891583976e-05 loss: 0.0988 (0.1123) time: 2.7642 data: 0.0069 max mem: 33369 +Epoch: [6] [ 330/1319] eta: 0:45:21 lr: 4.2909300627777926e-05 loss: 0.1055 (0.1120) time: 2.7726 data: 0.0069 max mem: 33369 +Epoch: [6] [ 340/1319] eta: 0:44:49 lr: 4.290062516908562e-05 loss: 0.1077 (0.1123) time: 2.6979 data: 0.0070 max mem: 33369 +Epoch: [6] [ 350/1319] eta: 0:44:19 lr: 4.2891949515458894e-05 loss: 0.1220 (0.1128) time: 2.6321 data: 0.0071 max mem: 33369 +Epoch: [6] [ 360/1319] eta: 0:43:50 lr: 4.288327366684957e-05 loss: 0.1232 (0.1135) time: 2.6608 data: 0.0069 max mem: 33369 +Epoch: [6] [ 370/1319] eta: 0:43:20 lr: 4.287459762320942e-05 loss: 0.1072 (0.1127) time: 2.6645 data: 0.0067 max mem: 33369 +Epoch: [6] [ 380/1319] eta: 0:42:50 lr: 4.28659213844902e-05 loss: 0.0943 (0.1129) time: 2.6406 data: 0.0067 max mem: 33369 +Epoch: [6] [ 390/1319] eta: 0:42:20 lr: 4.285724495064366e-05 loss: 0.1065 (0.1132) time: 2.6253 data: 0.0065 max mem: 33369 +Epoch: [6] [ 400/1319] eta: 0:41:54 lr: 4.2848568321621514e-05 loss: 0.1107 (0.1133) time: 2.7191 data: 0.0069 max mem: 33369 +Epoch: [6] [ 410/1319] eta: 0:41:29 lr: 4.283989149737546e-05 loss: 0.1290 (0.1140) time: 2.8189 data: 0.0072 max mem: 33369 +Epoch: [6] [ 420/1319] eta: 0:41:03 lr: 4.283121447785717e-05 loss: 0.1243 (0.1141) time: 2.8071 data: 0.0071 max mem: 33369 +Epoch: [6] [ 430/1319] eta: 0:40:36 lr: 4.2822537263018285e-05 loss: 0.0993 (0.1139) time: 2.7865 data: 0.0073 max mem: 33369 +Epoch: [6] [ 440/1319] eta: 0:40:09 lr: 4.281385985281043e-05 loss: 0.1082 (0.1138) time: 2.7731 data: 0.0072 max mem: 33369 +Epoch: [6] [ 450/1319] eta: 0:39:42 lr: 4.280518224718522e-05 loss: 0.1082 (0.1137) time: 2.7704 data: 0.0068 max mem: 33369 +Epoch: [6] [ 460/1319] eta: 0:39:16 lr: 4.2796504446094225e-05 loss: 0.1016 (0.1137) time: 2.7815 data: 0.0068 max mem: 33369 +Epoch: [6] [ 470/1319] eta: 0:38:48 lr: 4.278782644948901e-05 loss: 0.0949 (0.1135) time: 2.7678 data: 0.0068 max mem: 33369 +Epoch: [6] [ 480/1319] eta: 0:38:23 lr: 4.27791482573211e-05 loss: 0.0999 (0.1133) time: 2.8161 data: 0.0068 max mem: 33369 +Epoch: [6] [ 490/1319] eta: 0:37:56 lr: 4.2770469869541996e-05 loss: 0.0973 (0.1131) time: 2.8192 data: 0.0068 max mem: 33369 +Epoch: [6] [ 500/1319] eta: 0:37:28 lr: 4.276179128610321e-05 loss: 0.0805 (0.1126) time: 2.7357 data: 0.0069 max mem: 33369 +Epoch: [6] [ 510/1319] eta: 0:37:01 lr: 4.2753112506956194e-05 loss: 0.0829 (0.1127) time: 2.7362 data: 0.0070 max mem: 33369 +Epoch: [6] [ 520/1319] eta: 0:36:33 lr: 4.274443353205239e-05 loss: 0.0923 (0.1125) time: 2.7275 data: 0.0069 max mem: 33369 +Epoch: [6] [ 530/1319] eta: 0:36:06 lr: 4.2735754361343224e-05 loss: 0.0901 (0.1123) time: 2.7399 data: 0.0066 max mem: 33369 +Epoch: [6] [ 540/1319] eta: 0:35:39 lr: 4.2727074994780086e-05 loss: 0.1105 (0.1123) time: 2.7811 data: 0.0065 max mem: 33369 +Epoch: [6] [ 550/1319] eta: 0:35:11 lr: 4.271839543231435e-05 loss: 0.1161 (0.1123) time: 2.7535 data: 0.0065 max mem: 33369 +Epoch: [6] [ 560/1319] eta: 0:34:43 lr: 4.270971567389736e-05 loss: 0.1007 (0.1121) time: 2.7269 data: 0.0065 max mem: 33369 +Epoch: [6] [ 570/1319] eta: 0:34:16 lr: 4.270103571948045e-05 loss: 0.0934 (0.1123) time: 2.7499 data: 0.0068 max mem: 33369 +Epoch: [6] [ 580/1319] eta: 0:33:49 lr: 4.2692355569014936e-05 loss: 0.0997 (0.1122) time: 2.7605 data: 0.0067 max mem: 33369 +Epoch: [6] [ 590/1319] eta: 0:33:21 lr: 4.268367522245208e-05 loss: 0.0997 (0.1122) time: 2.7445 data: 0.0066 max mem: 33369 +Epoch: [6] [ 600/1319] eta: 0:32:54 lr: 4.267499467974314e-05 loss: 0.1047 (0.1124) time: 2.7528 data: 0.0068 max mem: 33369 +Epoch: [6] [ 610/1319] eta: 0:32:26 lr: 4.2666313940839357e-05 loss: 0.1041 (0.1124) time: 2.7342 data: 0.0068 max mem: 33369 +Epoch: [6] [ 620/1319] eta: 0:31:59 lr: 4.2657633005691946e-05 loss: 0.1052 (0.1128) time: 2.7210 data: 0.0068 max mem: 33369 +Epoch: [6] [ 630/1319] eta: 0:31:31 lr: 4.264895187425208e-05 loss: 0.1256 (0.1132) time: 2.7574 data: 0.0067 max mem: 33369 +Epoch: [6] [ 640/1319] eta: 0:31:04 lr: 4.264027054647094e-05 loss: 0.1087 (0.1129) time: 2.7593 data: 0.0065 max mem: 33369 +Epoch: [6] [ 650/1319] eta: 0:30:37 lr: 4.263158902229967e-05 loss: 0.0972 (0.1129) time: 2.7674 data: 0.0065 max mem: 33369 +Epoch: [6] [ 660/1319] eta: 0:30:09 lr: 4.262290730168937e-05 loss: 0.1143 (0.1130) time: 2.7363 data: 0.0066 max mem: 33369 +Epoch: [6] [ 670/1319] eta: 0:29:41 lr: 4.261422538459115e-05 loss: 0.1236 (0.1129) time: 2.6921 data: 0.0066 max mem: 33369 +Epoch: [6] [ 680/1319] eta: 0:29:13 lr: 4.260554327095607e-05 loss: 0.1027 (0.1128) time: 2.6842 data: 0.0066 max mem: 33369 +Epoch: [6] [ 690/1319] eta: 0:28:44 lr: 4.2596860960735204e-05 loss: 0.1027 (0.1130) time: 2.6376 data: 0.0068 max mem: 33369 +Epoch: [6] [ 700/1319] eta: 0:28:16 lr: 4.258817845387955e-05 loss: 0.0943 (0.1128) time: 2.6218 data: 0.0068 max mem: 33369 +Epoch: [6] [ 710/1319] eta: 0:27:47 lr: 4.257949575034011e-05 loss: 0.0943 (0.1126) time: 2.6310 data: 0.0066 max mem: 33369 +Epoch: [6] [ 720/1319] eta: 0:27:19 lr: 4.257081285006789e-05 loss: 0.0989 (0.1127) time: 2.6257 data: 0.0066 max mem: 33369 +Epoch: [6] [ 730/1319] eta: 0:26:51 lr: 4.256212975301382e-05 loss: 0.1127 (0.1129) time: 2.6289 data: 0.0069 max mem: 33369 +Epoch: [6] [ 740/1319] eta: 0:26:24 lr: 4.255344645912884e-05 loss: 0.1182 (0.1130) time: 2.6940 data: 0.0070 max mem: 33369 +Epoch: [6] [ 750/1319] eta: 0:25:56 lr: 4.254476296836386e-05 loss: 0.0988 (0.1128) time: 2.7573 data: 0.0074 max mem: 33369 +Epoch: [6] [ 760/1319] eta: 0:25:29 lr: 4.253607928066978e-05 loss: 0.1089 (0.1132) time: 2.7649 data: 0.0076 max mem: 33369 +Epoch: [6] [ 770/1319] eta: 0:25:02 lr: 4.252739539599743e-05 loss: 0.1274 (0.1136) time: 2.7600 data: 0.0075 max mem: 33369 +Epoch: [6] [ 780/1319] eta: 0:24:35 lr: 4.2518711314297674e-05 loss: 0.1274 (0.1138) time: 2.7347 data: 0.0070 max mem: 33369 +Epoch: [6] [ 790/1319] eta: 0:24:07 lr: 4.2510027035521314e-05 loss: 0.1166 (0.1142) time: 2.7265 data: 0.0068 max mem: 33369 +Epoch: [6] [ 800/1319] eta: 0:23:40 lr: 4.250134255961916e-05 loss: 0.1108 (0.1142) time: 2.7420 data: 0.0067 max mem: 33369 +Epoch: [6] [ 810/1319] eta: 0:23:12 lr: 4.2492657886541955e-05 loss: 0.1076 (0.1142) time: 2.7289 data: 0.0066 max mem: 33369 +Epoch: [6] [ 820/1319] eta: 0:22:45 lr: 4.2483973016240455e-05 loss: 0.1041 (0.1142) time: 2.6980 data: 0.0066 max mem: 33369 +Epoch: [6] [ 830/1319] eta: 0:22:17 lr: 4.247528794866539e-05 loss: 0.1041 (0.1143) time: 2.6924 data: 0.0067 max mem: 33369 +Epoch: [6] [ 840/1319] eta: 0:21:49 lr: 4.2466602683767445e-05 loss: 0.0920 (0.1144) time: 2.6760 data: 0.0069 max mem: 33369 +Epoch: [6] [ 850/1319] eta: 0:21:22 lr: 4.24579172214973e-05 loss: 0.1057 (0.1146) time: 2.6931 data: 0.0069 max mem: 33369 +Epoch: [6] [ 860/1319] eta: 0:20:54 lr: 4.244923156180561e-05 loss: 0.0988 (0.1145) time: 2.7176 data: 0.0066 max mem: 33369 +Epoch: [6] [ 870/1319] eta: 0:20:27 lr: 4.2440545704643e-05 loss: 0.1018 (0.1145) time: 2.7051 data: 0.0065 max mem: 33369 +Epoch: [6] [ 880/1319] eta: 0:20:00 lr: 4.243185964996007e-05 loss: 0.1141 (0.1146) time: 2.7127 data: 0.0064 max mem: 33369 +Epoch: [6] [ 890/1319] eta: 0:19:32 lr: 4.24231733977074e-05 loss: 0.1029 (0.1146) time: 2.6899 data: 0.0066 max mem: 33369 +Epoch: [6] [ 900/1319] eta: 0:19:04 lr: 4.2414486947835554e-05 loss: 0.0927 (0.1145) time: 2.6653 data: 0.0070 max mem: 33369 +Epoch: [6] [ 910/1319] eta: 0:18:37 lr: 4.240580030029505e-05 loss: 0.0923 (0.1143) time: 2.6805 data: 0.0068 max mem: 33369 +Epoch: [6] [ 920/1319] eta: 0:18:09 lr: 4.239711345503641e-05 loss: 0.1093 (0.1146) time: 2.6950 data: 0.0067 max mem: 33369 +Epoch: [6] [ 930/1319] eta: 0:17:42 lr: 4.2388426412010114e-05 loss: 0.1051 (0.1146) time: 2.7086 data: 0.0068 max mem: 33369 +Epoch: [6] [ 940/1319] eta: 0:17:14 lr: 4.237973917116662e-05 loss: 0.0984 (0.1145) time: 2.6987 data: 0.0066 max mem: 33369 +Epoch: [6] [ 950/1319] eta: 0:16:47 lr: 4.237105173245638e-05 loss: 0.1077 (0.1146) time: 2.7034 data: 0.0066 max mem: 33369 +Epoch: [6] [ 960/1319] eta: 0:16:20 lr: 4.23623640958298e-05 loss: 0.1077 (0.1145) time: 2.7086 data: 0.0069 max mem: 33369 +Epoch: [6] [ 970/1319] eta: 0:15:52 lr: 4.235367626123727e-05 loss: 0.1075 (0.1145) time: 2.6843 data: 0.0068 max mem: 33369 +Epoch: [6] [ 980/1319] eta: 0:15:25 lr: 4.234498822862916e-05 loss: 0.0962 (0.1144) time: 2.6872 data: 0.0067 max mem: 33369 +Epoch: [6] [ 990/1319] eta: 0:14:57 lr: 4.23362999979558e-05 loss: 0.1051 (0.1144) time: 2.7142 data: 0.0067 max mem: 33369 +Epoch: [6] [1000/1319] eta: 0:14:30 lr: 4.2327611569167524e-05 loss: 0.1081 (0.1146) time: 2.7038 data: 0.0067 max mem: 33369 +Epoch: [6] [1010/1319] eta: 0:14:03 lr: 4.2318922942214635e-05 loss: 0.1075 (0.1144) time: 2.7375 data: 0.0068 max mem: 33369 +Epoch: [6] [1020/1319] eta: 0:13:35 lr: 4.231023411704738e-05 loss: 0.0990 (0.1144) time: 2.7312 data: 0.0067 max mem: 33369 +Epoch: [6] [1030/1319] eta: 0:13:08 lr: 4.230154509361603e-05 loss: 0.1005 (0.1146) time: 2.6686 data: 0.0065 max mem: 33369 +Epoch: [6] [1040/1319] eta: 0:12:40 lr: 4.229285587187079e-05 loss: 0.1063 (0.1145) time: 2.6632 data: 0.0066 max mem: 33369 +Epoch: [6] [1050/1319] eta: 0:12:13 lr: 4.2284166451761876e-05 loss: 0.1111 (0.1146) time: 2.6409 data: 0.0067 max mem: 33369 +Epoch: [6] [1060/1319] eta: 0:11:45 lr: 4.2275476833239456e-05 loss: 0.1111 (0.1147) time: 2.6187 data: 0.0067 max mem: 33369 +Epoch: [6] [1070/1319] eta: 0:11:18 lr: 4.2266787016253686e-05 loss: 0.0887 (0.1146) time: 2.6207 data: 0.0067 max mem: 33369 +Epoch: [6] [1080/1319] eta: 0:10:51 lr: 4.22580970007547e-05 loss: 0.1047 (0.1146) time: 2.6570 data: 0.0068 max mem: 33369 +Epoch: [6] [1090/1319] eta: 0:10:23 lr: 4.224940678669259e-05 loss: 0.1047 (0.1145) time: 2.7209 data: 0.0071 max mem: 33369 +Epoch: [6] [1100/1319] eta: 0:09:56 lr: 4.2240716374017434e-05 loss: 0.1229 (0.1148) time: 2.7617 data: 0.0070 max mem: 33369 +Epoch: [6] [1110/1319] eta: 0:09:29 lr: 4.2232025762679314e-05 loss: 0.1219 (0.1149) time: 2.7537 data: 0.0069 max mem: 33369 +Epoch: [6] [1120/1319] eta: 0:09:02 lr: 4.2223334952628234e-05 loss: 0.1064 (0.1148) time: 2.7398 data: 0.0070 max mem: 33369 +Epoch: [6] [1130/1319] eta: 0:08:35 lr: 4.221464394381422e-05 loss: 0.0995 (0.1148) time: 2.7266 data: 0.0070 max mem: 33369 +Epoch: [6] [1140/1319] eta: 0:08:07 lr: 4.220595273618725e-05 loss: 0.0935 (0.1146) time: 2.7367 data: 0.0068 max mem: 33369 +Epoch: [6] [1150/1319] eta: 0:07:40 lr: 4.2197261329697285e-05 loss: 0.1039 (0.1145) time: 2.7382 data: 0.0066 max mem: 33369 +Epoch: [6] [1160/1319] eta: 0:07:13 lr: 4.218856972429426e-05 loss: 0.1051 (0.1144) time: 2.7018 data: 0.0066 max mem: 33369 +Epoch: [6] [1170/1319] eta: 0:06:45 lr: 4.2179877919928104e-05 loss: 0.1063 (0.1145) time: 2.6783 data: 0.0067 max mem: 33369 +Epoch: [6] [1180/1319] eta: 0:06:18 lr: 4.217118591654868e-05 loss: 0.1164 (0.1146) time: 2.6815 data: 0.0070 max mem: 33369 +Epoch: [6] [1190/1319] eta: 0:05:51 lr: 4.2162493714105874e-05 loss: 0.1164 (0.1147) time: 2.6909 data: 0.0070 max mem: 33369 +Epoch: [6] [1200/1319] eta: 0:05:24 lr: 4.2153801312549505e-05 loss: 0.1092 (0.1146) time: 2.6654 data: 0.0068 max mem: 33369 +Epoch: [6] [1210/1319] eta: 0:04:56 lr: 4.2145108711829405e-05 loss: 0.0952 (0.1144) time: 2.6812 data: 0.0068 max mem: 33369 +Epoch: [6] [1220/1319] eta: 0:04:29 lr: 4.213641591189537e-05 loss: 0.0952 (0.1144) time: 2.7070 data: 0.0068 max mem: 33369 +Epoch: [6] [1230/1319] eta: 0:04:02 lr: 4.212772291269716e-05 loss: 0.1143 (0.1144) time: 2.6954 data: 0.0066 max mem: 33369 +Epoch: [6] [1240/1319] eta: 0:03:35 lr: 4.2119029714184504e-05 loss: 0.1085 (0.1146) time: 2.6885 data: 0.0067 max mem: 33369 +Epoch: [6] [1250/1319] eta: 0:03:07 lr: 4.211033631630714e-05 loss: 0.1291 (0.1147) time: 2.6919 data: 0.0069 max mem: 33369 +Epoch: [6] [1260/1319] eta: 0:02:40 lr: 4.2101642719014764e-05 loss: 0.1249 (0.1147) time: 2.7546 data: 0.0068 max mem: 33369 +Epoch: [6] [1270/1319] eta: 0:02:13 lr: 4.2092948922257045e-05 loss: 0.1200 (0.1148) time: 2.7449 data: 0.0068 max mem: 33369 +Epoch: [6] [1280/1319] eta: 0:01:46 lr: 4.208425492598362e-05 loss: 0.1200 (0.1149) time: 2.6796 data: 0.0068 max mem: 33369 +Epoch: [6] [1290/1319] eta: 0:01:18 lr: 4.207556073014412e-05 loss: 0.1158 (0.1150) time: 2.6847 data: 0.0067 max mem: 33369 +Epoch: [6] [1300/1319] eta: 0:00:51 lr: 4.2066866334688144e-05 loss: 0.1018 (0.1149) time: 2.6993 data: 0.0070 max mem: 33369 +Epoch: [6] [1310/1319] eta: 0:00:24 lr: 4.205817173956526e-05 loss: 0.1073 (0.1149) time: 2.6975 data: 0.0069 max mem: 33369 +Epoch: [6] Total time: 0:59:49 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 2:10:09 time: 3.0351 data: 2.9554 max mem: 33369 +Test: [ 100/2573] eta: 0:04:10 time: 0.0716 data: 0.0011 max mem: 33369 +Test: [ 200/2573] eta: 0:03:28 time: 0.0736 data: 0.0012 max mem: 33369 +Test: [ 300/2573] eta: 0:03:07 time: 0.0753 data: 0.0011 max mem: 33369 +Test: [ 400/2573] eta: 0:02:54 time: 0.0755 data: 0.0012 max mem: 33369 +Test: [ 500/2573] eta: 0:02:43 time: 0.0736 data: 0.0012 max mem: 33369 +Test: [ 600/2573] eta: 0:02:34 time: 0.0737 data: 0.0012 max mem: 33369 +Test: [ 700/2573] eta: 0:02:25 time: 0.0739 data: 0.0012 max mem: 33369 +Test: [ 800/2573] eta: 0:02:17 time: 0.0772 data: 0.0011 max mem: 33369 +Test: [ 900/2573] eta: 0:02:09 time: 0.0741 data: 0.0012 max mem: 33369 +Test: [1000/2573] eta: 0:02:01 time: 0.0738 data: 0.0011 max mem: 33369 +Test: [1100/2573] eta: 0:01:52 time: 0.0740 data: 0.0012 max mem: 33369 +Test: [1200/2573] eta: 0:01:45 time: 0.0740 data: 0.0011 max mem: 33369 +Test: [1300/2573] eta: 0:01:37 time: 0.0737 data: 0.0011 max mem: 33369 +Test: [1400/2573] eta: 0:01:29 time: 0.0721 data: 0.0011 max mem: 33369 +Test: [1500/2573] eta: 0:01:21 time: 0.0738 data: 0.0011 max mem: 33369 +Test: [1600/2573] eta: 0:01:13 time: 0.0772 data: 0.0012 max mem: 33369 +Test: [1700/2573] eta: 0:01:06 time: 0.0720 data: 0.0011 max mem: 33369 +Test: [1800/2573] eta: 0:00:58 time: 0.0754 data: 0.0011 max mem: 33369 +Test: [1900/2573] eta: 0:00:50 time: 0.0721 data: 0.0011 max mem: 33369 +Test: [2000/2573] eta: 0:00:43 time: 0.0738 data: 0.0011 max mem: 33369 +Test: [2100/2573] eta: 0:00:35 time: 0.0754 data: 0.0011 max mem: 33369 +Test: [2200/2573] eta: 0:00:28 time: 0.0754 data: 0.0011 max mem: 33369 +Test: [2300/2573] eta: 0:00:20 time: 0.0754 data: 0.0011 max mem: 33369 +Test: [2400/2573] eta: 0:00:12 time: 0.0704 data: 0.0011 max mem: 33369 +Test: [2500/2573] eta: 0:00:05 time: 0.0737 data: 0.0011 max mem: 33369 +Test: Total time: 0:03:13 +Final results: +Mean IoU is 57.72 + + precision@0.5 = 64.38 + precision@0.6 = 57.46 + precision@0.7 = 48.18 + precision@0.8 = 35.68 + precision@0.9 = 15.22 + overall IoU = 57.55 + +Average object IoU 57.72105661699104 +Overall IoU 57.546485900878906 +Better epoch: 6 + +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [7] [ 0/1319] eta: 1:29:00 lr: 4.205034643319776e-05 loss: 0.1036 (0.1036) time: 4.0488 data: 1.2702 max mem: 33369 +Epoch: [7] [ 10/1319] eta: 1:01:43 lr: 4.204165145856875e-05 loss: 0.0891 (0.0935) time: 2.8289 data: 0.1216 max mem: 33369 +Epoch: [7] [ 20/1319] eta: 1:00:28 lr: 4.203295628412646e-05 loss: 0.0847 (0.0948) time: 2.7308 data: 0.0068 max mem: 33369 +Epoch: [7] [ 30/1319] eta: 0:59:59 lr: 4.202426090982037e-05 loss: 0.0860 (0.0923) time: 2.7724 data: 0.0069 max mem: 33369 +Epoch: [7] [ 40/1319] eta: 0:59:16 lr: 4.201556533559993e-05 loss: 0.0877 (0.0965) time: 2.7667 data: 0.0068 max mem: 33369 +Epoch: [7] [ 50/1319] eta: 0:58:27 lr: 4.2006869561414584e-05 loss: 0.1020 (0.1010) time: 2.7203 data: 0.0067 max mem: 33369 +Epoch: [7] [ 60/1319] eta: 0:57:44 lr: 4.199817358721372e-05 loss: 0.1056 (0.1034) time: 2.6935 data: 0.0067 max mem: 33369 +Epoch: [7] [ 70/1319] eta: 0:57:15 lr: 4.1989477412946735e-05 loss: 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4.1919900810347894e-05 loss: 0.1103 (0.1089) time: 2.6832 data: 0.0067 max mem: 33369 +Epoch: [7] [ 160/1319] eta: 0:52:26 lr: 4.191120283320388e-05 loss: 0.0959 (0.1097) time: 2.6636 data: 0.0068 max mem: 33369 +Epoch: [7] [ 170/1319] eta: 0:51:56 lr: 4.190250465548619e-05 loss: 0.0947 (0.1085) time: 2.6551 data: 0.0068 max mem: 33369 +Epoch: [7] [ 180/1319] eta: 0:51:31 lr: 4.189380627714394e-05 loss: 0.0889 (0.1084) time: 2.7091 data: 0.0067 max mem: 33369 +Epoch: [7] [ 190/1319] eta: 0:51:02 lr: 4.188510769812624e-05 loss: 0.0912 (0.1081) time: 2.7124 data: 0.0067 max mem: 33369 +Epoch: [7] [ 200/1319] eta: 0:50:36 lr: 4.1876408918382123e-05 loss: 0.0950 (0.1081) time: 2.7059 data: 0.0067 max mem: 33369 +Epoch: [7] [ 210/1319] eta: 0:50:10 lr: 4.1867709937860646e-05 loss: 0.0909 (0.1075) time: 2.7350 data: 0.0067 max mem: 33369 +Epoch: [7] [ 220/1319] eta: 0:49:41 lr: 4.185901075651081e-05 loss: 0.0909 (0.1069) time: 2.7028 data: 0.0067 max mem: 33369 +Epoch: [7] [ 230/1319] eta: 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+Epoch: [7] [ 390/1319] eta: 0:41:45 lr: 4.171109389729833e-05 loss: 0.0859 (0.1058) time: 2.7478 data: 0.0071 max mem: 33369 +Epoch: [7] [ 400/1319] eta: 0:41:19 lr: 4.1702391092290966e-05 loss: 0.1114 (0.1073) time: 2.7740 data: 0.0071 max mem: 33369 +Epoch: [7] [ 410/1319] eta: 0:40:54 lr: 4.169368808548177e-05 loss: 0.1236 (0.1078) time: 2.7600 data: 0.0071 max mem: 33369 +Epoch: [7] [ 420/1319] eta: 0:40:29 lr: 4.168498487681925e-05 loss: 0.1025 (0.1076) time: 2.7805 data: 0.0073 max mem: 33369 +Epoch: [7] [ 430/1319] eta: 0:40:03 lr: 4.1676281466251895e-05 loss: 0.0950 (0.1072) time: 2.7807 data: 0.0070 max mem: 33369 +Epoch: [7] [ 440/1319] eta: 0:39:38 lr: 4.166757785372817e-05 loss: 0.0939 (0.1072) time: 2.7809 data: 0.0067 max mem: 33369 +Epoch: [7] [ 450/1319] eta: 0:39:13 lr: 4.1658874039196515e-05 loss: 0.0982 (0.1071) time: 2.8030 data: 0.0066 max mem: 33369 +Epoch: [7] [ 460/1319] eta: 0:38:48 lr: 4.165017002260535e-05 loss: 0.0979 (0.1073) time: 2.8147 data: 0.0066 max mem: 33369 +Epoch: [7] [ 470/1319] eta: 0:38:21 lr: 4.164146580390306e-05 loss: 0.1029 (0.1077) time: 2.7840 data: 0.0068 max mem: 33369 +Epoch: [7] [ 480/1319] eta: 0:37:55 lr: 4.163276138303801e-05 loss: 0.1029 (0.1076) time: 2.7483 data: 0.0069 max mem: 33369 +Epoch: [7] [ 490/1319] eta: 0:37:30 lr: 4.1624056759958536e-05 loss: 0.0927 (0.1078) time: 2.7892 data: 0.0068 max mem: 33369 +Epoch: [7] [ 500/1319] eta: 0:37:03 lr: 4.161535193461295e-05 loss: 0.1044 (0.1079) time: 2.8005 data: 0.0067 max mem: 33369 +Epoch: [7] [ 510/1319] eta: 0:36:36 lr: 4.1606646906949546e-05 loss: 0.1047 (0.1079) time: 2.7418 data: 0.0067 max mem: 33369 +Epoch: [7] [ 520/1319] eta: 0:36:09 lr: 4.159794167691658e-05 loss: 0.1102 (0.1083) time: 2.7246 data: 0.0067 max mem: 33369 +Epoch: [7] [ 530/1319] eta: 0:35:42 lr: 4.158923624446229e-05 loss: 0.1033 (0.1081) time: 2.7209 data: 0.0068 max mem: 33369 +Epoch: [7] [ 540/1319] eta: 0:35:15 lr: 4.15805306095349e-05 loss: 0.1016 (0.1081) time: 2.7292 data: 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2.7371 data: 0.0072 max mem: 33369 +Epoch: [7] [ 630/1319] eta: 0:31:14 lr: 4.1502170775340975e-05 loss: 0.1059 (0.1088) time: 2.7422 data: 0.0071 max mem: 33369 +Epoch: [7] [ 640/1319] eta: 0:30:47 lr: 4.14934631128286e-05 loss: 0.1045 (0.1087) time: 2.7303 data: 0.0070 max mem: 33369 +Epoch: [7] [ 650/1319] eta: 0:30:19 lr: 4.148475524727178e-05 loss: 0.0964 (0.1086) time: 2.6965 data: 0.0068 max mem: 33369 +Epoch: [7] [ 660/1319] eta: 0:29:52 lr: 4.147604717861842e-05 loss: 0.0918 (0.1087) time: 2.6857 data: 0.0068 max mem: 33369 +Epoch: [7] [ 670/1319] eta: 0:29:24 lr: 4.14673389068164e-05 loss: 0.1025 (0.1089) time: 2.6588 data: 0.0068 max mem: 33369 +Epoch: [7] [ 680/1319] eta: 0:28:56 lr: 4.145863043181359e-05 loss: 0.0998 (0.1089) time: 2.6338 data: 0.0068 max mem: 33369 +Epoch: [7] [ 690/1319] eta: 0:28:28 lr: 4.144992175355781e-05 loss: 0.0886 (0.1085) time: 2.6260 data: 0.0067 max mem: 33369 +Epoch: [7] [ 700/1319] eta: 0:28:00 lr: 4.1441212871996857e-05 loss: 0.0966 (0.1085) time: 2.6260 data: 0.0064 max mem: 33369 +Epoch: [7] [ 710/1319] eta: 0:27:32 lr: 4.143250378707853e-05 loss: 0.1038 (0.1085) time: 2.6447 data: 0.0066 max mem: 33369 +Epoch: [7] [ 720/1319] eta: 0:27:05 lr: 4.142379449875057e-05 loss: 0.1065 (0.1086) time: 2.6896 data: 0.0072 max mem: 33369 +Epoch: [7] [ 730/1319] eta: 0:26:38 lr: 4.141508500696071e-05 loss: 0.0936 (0.1085) time: 2.7458 data: 0.0075 max mem: 33369 +Epoch: [7] [ 740/1319] eta: 0:26:11 lr: 4.140637531165665e-05 loss: 0.0919 (0.1085) time: 2.7449 data: 0.0072 max mem: 33369 +Epoch: [7] [ 750/1319] eta: 0:25:45 lr: 4.139766541278606e-05 loss: 0.1167 (0.1092) time: 2.7389 data: 0.0069 max mem: 33369 +Epoch: [7] [ 760/1319] eta: 0:25:17 lr: 4.138895531029661e-05 loss: 0.1191 (0.1091) time: 2.7279 data: 0.0069 max mem: 33369 +Epoch: [7] [ 770/1319] eta: 0:24:50 lr: 4.138024500413592e-05 loss: 0.0886 (0.1090) time: 2.6922 data: 0.0069 max mem: 33369 +Epoch: [7] [ 780/1319] eta: 0:24:22 lr: 4.137153449425158e-05 loss: 0.0965 (0.1090) time: 2.6734 data: 0.0069 max mem: 33369 +Epoch: [7] [ 790/1319] eta: 0:23:55 lr: 4.136282378059117e-05 loss: 0.1105 (0.1088) time: 2.6941 data: 0.0069 max mem: 33369 +Epoch: [7] [ 800/1319] eta: 0:23:28 lr: 4.1354112863102244e-05 loss: 0.1093 (0.1088) time: 2.7055 data: 0.0069 max mem: 33369 +Epoch: [7] [ 810/1319] eta: 0:23:01 lr: 4.134540174173232e-05 loss: 0.1095 (0.1089) time: 2.7200 data: 0.0069 max mem: 33369 +Epoch: [7] [ 820/1319] eta: 0:22:34 lr: 4.1336690416428894e-05 loss: 0.1056 (0.1088) time: 2.7611 data: 0.0068 max mem: 33369 +Epoch: [7] [ 830/1319] eta: 0:22:07 lr: 4.132797888713944e-05 loss: 0.0868 (0.1086) time: 2.7479 data: 0.0067 max mem: 33369 +Epoch: [7] [ 840/1319] eta: 0:21:40 lr: 4.13192671538114e-05 loss: 0.0991 (0.1086) time: 2.7473 data: 0.0067 max mem: 33369 +Epoch: [7] [ 850/1319] eta: 0:21:13 lr: 4.1310555216392185e-05 loss: 0.1014 (0.1086) time: 2.7475 data: 0.0068 max mem: 33369 +Epoch: [7] [ 860/1319] eta: 0:20:46 lr: 4.130184307482921e-05 loss: 0.1017 (0.1087) time: 2.7581 data: 0.0070 max mem: 33369 +Epoch: [7] [ 870/1319] eta: 0:20:20 lr: 4.1293130729069835e-05 loss: 0.1020 (0.1086) time: 2.7713 data: 0.0070 max mem: 33369 +Epoch: [7] [ 880/1319] eta: 0:19:53 lr: 4.128441817906139e-05 loss: 0.1020 (0.1088) time: 2.7716 data: 0.0067 max mem: 33369 +Epoch: [7] [ 890/1319] eta: 0:19:26 lr: 4.1275705424751206e-05 loss: 0.1010 (0.1087) time: 2.7618 data: 0.0068 max mem: 33369 +Epoch: [7] [ 900/1319] eta: 0:18:58 lr: 4.1266992466086555e-05 loss: 0.0938 (0.1086) time: 2.7244 data: 0.0072 max mem: 33369 +Epoch: [7] [ 910/1319] eta: 0:18:31 lr: 4.125827930301473e-05 loss: 0.0995 (0.1086) time: 2.7368 data: 0.0071 max mem: 33369 +Epoch: [7] [ 920/1319] eta: 0:18:05 lr: 4.124956593548294e-05 loss: 0.1124 (0.1087) time: 2.7767 data: 0.0069 max mem: 33369 +Epoch: [7] [ 930/1319] eta: 0:17:37 lr: 4.124085236343841e-05 loss: 0.1124 (0.1087) time: 2.7566 data: 0.0071 max mem: 33369 +Epoch: [7] [ 940/1319] eta: 0:17:10 lr: 4.123213858682832e-05 loss: 0.0998 (0.1087) time: 2.7337 data: 0.0071 max mem: 33369 +Epoch: [7] [ 950/1319] eta: 0:16:43 lr: 4.122342460559985e-05 loss: 0.1031 (0.1088) time: 2.7451 data: 0.0069 max mem: 33369 +Epoch: [7] [ 960/1319] eta: 0:16:16 lr: 4.12147104197001e-05 loss: 0.1054 (0.1090) time: 2.7525 data: 0.0069 max mem: 33369 +Epoch: [7] [ 970/1319] eta: 0:15:49 lr: 4.12059960290762e-05 loss: 0.1098 (0.1090) time: 2.7619 data: 0.0069 max mem: 33369 +Epoch: [7] [ 980/1319] eta: 0:15:22 lr: 4.119728143367523e-05 loss: 0.0998 (0.1091) time: 2.7526 data: 0.0067 max mem: 33369 +Epoch: [7] [ 990/1319] eta: 0:14:55 lr: 4.1188566633444246e-05 loss: 0.0998 (0.1092) time: 2.7509 data: 0.0066 max mem: 33369 +Epoch: [7] [1000/1319] eta: 0:14:28 lr: 4.1179851628330275e-05 loss: 0.0978 (0.1093) time: 2.7220 data: 0.0065 max mem: 33369 +Epoch: [7] [1010/1319] eta: 0:14:00 lr: 4.117113641828032e-05 loss: 0.0883 (0.1093) time: 2.6659 data: 0.0064 max mem: 33369 +Epoch: [7] [1020/1319] eta: 0:13:33 lr: 4.116242100324135e-05 loss: 0.0970 (0.1094) time: 2.6512 data: 0.0065 max mem: 33369 +Epoch: [7] [1030/1319] eta: 0:13:05 lr: 4.1153705383160326e-05 loss: 0.0869 (0.1092) time: 2.6771 data: 0.0066 max mem: 33369 +Epoch: [7] [1040/1319] eta: 0:12:38 lr: 4.114498955798418e-05 loss: 0.0846 (0.1091) time: 2.6640 data: 0.0067 max mem: 33369 +Epoch: [7] [1050/1319] eta: 0:12:11 lr: 4.113627352765979e-05 loss: 0.0840 (0.1088) time: 2.6300 data: 0.0068 max mem: 33369 +Epoch: [7] [1060/1319] eta: 0:11:44 lr: 4.1127557292134045e-05 loss: 0.0840 (0.1087) time: 2.7031 data: 0.0068 max mem: 33369 +Epoch: [7] [1070/1319] eta: 0:11:17 lr: 4.111884085135378e-05 loss: 0.0859 (0.1087) time: 2.7850 data: 0.0071 max mem: 33369 +Epoch: [7] [1080/1319] eta: 0:10:50 lr: 4.111012420526582e-05 loss: 0.0923 (0.1087) time: 2.7955 data: 0.0071 max mem: 33369 +Epoch: [7] [1090/1319] eta: 0:10:23 lr: 4.110140735381696e-05 loss: 0.0906 (0.1086) time: 2.8636 data: 0.0070 max mem: 33369 +Epoch: [7] [1100/1319] eta: 0:09:56 lr: 4.109269029695397e-05 loss: 0.0906 (0.1086) time: 2.8756 data: 0.0069 max mem: 33369 +Epoch: [7] [1110/1319] eta: 0:09:29 lr: 4.108397303462358e-05 loss: 0.0968 (0.1086) time: 2.7838 data: 0.0069 max mem: 33369 +Epoch: [7] [1120/1319] eta: 0:09:01 lr: 4.1075255566772506e-05 loss: 0.1069 (0.1086) time: 2.7258 data: 0.0069 max mem: 33369 +Epoch: [7] [1130/1319] eta: 0:08:34 lr: 4.106653789334745e-05 loss: 0.1069 (0.1086) time: 2.7111 data: 0.0072 max mem: 33369 +Epoch: [7] [1140/1319] eta: 0:08:07 lr: 4.105782001429505e-05 loss: 0.1067 (0.1093) time: 2.7346 data: 0.0070 max mem: 33369 +Epoch: [7] [1150/1319] eta: 0:07:40 lr: 4.104910192956196e-05 loss: 0.1194 (0.1094) time: 2.7646 data: 0.0069 max mem: 33369 +Epoch: [7] [1160/1319] eta: 0:07:13 lr: 4.104038363909479e-05 loss: 0.1042 (0.1093) time: 2.7997 data: 0.0068 max mem: 33369 +Epoch: [7] [1170/1319] eta: 0:06:45 lr: 4.1031665142840106e-05 loss: 0.0964 (0.1094) time: 2.7722 data: 0.0070 max mem: 33369 +Epoch: [7] [1180/1319] eta: 0:06:18 lr: 4.1022946440744476e-05 loss: 0.0964 (0.1098) time: 2.7457 data: 0.0070 max mem: 33369 +Epoch: [7] [1190/1319] eta: 0:05:51 lr: 4.1014227532754415e-05 loss: 0.1055 (0.1098) time: 2.7529 data: 0.0066 max mem: 33369 +Epoch: [7] [1200/1319] eta: 0:05:24 lr: 4.100550841881645e-05 loss: 0.1084 (0.1098) time: 2.7560 data: 0.0067 max mem: 33369 +Epoch: [7] [1210/1319] eta: 0:04:57 lr: 4.099678909887704e-05 loss: 0.1164 (0.1097) time: 2.7590 data: 0.0067 max mem: 33369 +Epoch: [7] [1220/1319] eta: 0:04:29 lr: 4.098806957288263e-05 loss: 0.1109 (0.1097) time: 2.7415 data: 0.0067 max mem: 33369 +Epoch: [7] [1230/1319] eta: 0:04:02 lr: 4.0979349840779665e-05 loss: 0.0911 (0.1095) time: 2.7481 data: 0.0068 max mem: 33369 +Epoch: [7] [1240/1319] eta: 0:03:35 lr: 4.0970629902514516e-05 loss: 0.0891 (0.1095) time: 2.7608 data: 0.0068 max mem: 33369 +Epoch: [7] [1250/1319] eta: 0:03:08 lr: 4.0961909758033565e-05 loss: 0.0921 (0.1094) time: 2.7465 data: 0.0067 max mem: 33369 +Epoch: [7] [1260/1319] eta: 0:02:40 lr: 4.095318940728316e-05 loss: 0.1148 (0.1094) time: 2.7404 data: 0.0067 max mem: 33369 +Epoch: [7] [1270/1319] eta: 0:02:13 lr: 4.0944468850209605e-05 loss: 0.0939 (0.1094) time: 2.7372 data: 0.0069 max mem: 33369 +Epoch: [7] [1280/1319] eta: 0:01:46 lr: 4.093574808675919e-05 loss: 0.0939 (0.1094) time: 2.7321 data: 0.0069 max mem: 33369 +Epoch: [7] [1290/1319] eta: 0:01:19 lr: 4.09270271168782e-05 loss: 0.1035 (0.1095) time: 2.7465 data: 0.0070 max mem: 33369 +Epoch: [7] [1300/1319] eta: 0:00:51 lr: 4.091830594051285e-05 loss: 0.1057 (0.1094) time: 2.7263 data: 0.0071 max mem: 33369 +Epoch: [7] [1310/1319] eta: 0:00:24 lr: 4.090958455760934e-05 loss: 0.0858 (0.1093) time: 2.7162 data: 0.0068 max mem: 33369 +Epoch: [7] Total time: 0:59:56 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 2:12:00 time: 3.0783 data: 2.9977 max mem: 33369 +Test: [ 100/2573] eta: 0:04:12 time: 0.0722 data: 0.0012 max mem: 33369 +Test: [ 200/2573] eta: 0:03:30 time: 0.0735 data: 0.0012 max mem: 33369 +Test: [ 300/2573] eta: 0:03:09 time: 0.0752 data: 0.0011 max mem: 33369 +Test: [ 400/2573] eta: 0:02:55 time: 0.0755 data: 0.0011 max mem: 33369 +Test: [ 500/2573] eta: 0:02:44 time: 0.0740 data: 0.0012 max mem: 33369 +Test: [ 600/2573] eta: 0:02:35 time: 0.0739 data: 0.0011 max mem: 33369 +Test: [ 700/2573] eta: 0:02:26 time: 0.0738 data: 0.0011 max mem: 33369 +Test: [ 800/2573] eta: 0:02:17 time: 0.0770 data: 0.0011 max mem: 33369 +Test: [ 900/2573] eta: 0:02:09 time: 0.0738 data: 0.0011 max mem: 33369 +Test: [1000/2573] eta: 0:02:01 time: 0.0737 data: 0.0011 max mem: 33369 +Test: [1100/2573] eta: 0:01:53 time: 0.0737 data: 0.0011 max mem: 33369 +Test: [1200/2573] eta: 0:01:45 time: 0.0737 data: 0.0011 max mem: 33369 +Test: [1300/2573] eta: 0:01:37 time: 0.0737 data: 0.0010 max mem: 33369 +Test: [1400/2573] eta: 0:01:29 time: 0.0720 data: 0.0011 max mem: 33369 +Test: [1500/2573] eta: 0:01:21 time: 0.0737 data: 0.0011 max mem: 33369 +Test: [1600/2573] eta: 0:01:13 time: 0.0771 data: 0.0011 max mem: 33369 +Test: [1700/2573] eta: 0:01:06 time: 0.0722 data: 0.0011 max mem: 33369 +Test: [1800/2573] eta: 0:00:58 time: 0.0755 data: 0.0011 max mem: 33369 +Test: [1900/2573] eta: 0:00:50 time: 0.0723 data: 0.0011 max mem: 33369 +Test: [2000/2573] eta: 0:00:43 time: 0.0739 data: 0.0011 max mem: 33369 +Test: [2100/2573] eta: 0:00:35 time: 0.0756 data: 0.0011 max mem: 33369 +Test: [2200/2573] eta: 0:00:28 time: 0.0755 data: 0.0011 max mem: 33369 +Test: [2300/2573] eta: 0:00:20 time: 0.0755 data: 0.0011 max mem: 33369 +Test: [2400/2573] eta: 0:00:12 time: 0.0705 data: 0.0011 max mem: 33369 +Test: [2500/2573] eta: 0:00:05 time: 0.0739 data: 0.0011 max mem: 33369 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: Total time: 0:03:13 +Final results: +Mean IoU is 58.23 + + precision@0.5 = 65.58 + precision@0.6 = 58.50 + precision@0.7 = 49.53 + precision@0.8 = 36.91 + precision@0.9 = 15.34 + overall IoU = 57.71 + +Average object IoU 58.233856533527515 +Overall IoU 57.70948791503906 +Better epoch: 7 + +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [8] [ 0/1319] eta: 1:35:21 lr: 4.09017351363616e-05 loss: 0.1015 (0.1015) time: 4.3376 data: 1.4828 max mem: 33369 +Epoch: [8] [ 10/1319] eta: 1:03:53 lr: 4.089301336088734e-05 loss: 0.0896 (0.0954) time: 2.9283 data: 0.1413 max mem: 33369 +Epoch: [8] [ 20/1319] eta: 1:02:13 lr: 4.088429137871879e-05 loss: 0.0953 (0.1031) time: 2.8007 data: 0.0071 max mem: 33369 +Epoch: [8] [ 30/1319] eta: 1:00:57 lr: 4.087556918980205e-05 loss: 0.0980 (0.1029) time: 2.7870 data: 0.0069 max mem: 33369 +Epoch: [8] [ 40/1319] eta: 1:00:02 lr: 4.0866846794083216e-05 loss: 0.0898 (0.0993) time: 2.7566 data: 0.0070 max mem: 33369 +Epoch: [8] [ 50/1319] eta: 0:59:18 lr: 4.0858124191508315e-05 loss: 0.0886 (0.1030) time: 2.7536 data: 0.0073 max mem: 33369 +Epoch: [8] [ 60/1319] eta: 0:58:41 lr: 4.08494013820234e-05 loss: 0.0944 (0.1041) time: 2.7563 data: 0.0070 max mem: 33369 +Epoch: [8] [ 70/1319] eta: 0:58:07 lr: 4.0840678365574436e-05 loss: 0.1154 (0.1079) time: 2.7604 data: 0.0069 max mem: 33369 +Epoch: [8] [ 80/1319] eta: 0:57:30 lr: 4.083195514210742e-05 loss: 0.0941 (0.1054) time: 2.7482 data: 0.0069 max mem: 33369 +Epoch: [8] [ 90/1319] eta: 0:57:06 lr: 4.0823231711568287e-05 loss: 0.0717 (0.1036) time: 2.7745 data: 0.0069 max mem: 33369 +Epoch: [8] [ 100/1319] eta: 0:56:32 lr: 4.081450807390295e-05 loss: 0.0806 (0.1029) time: 2.7744 data: 0.0069 max mem: 33369 +Epoch: [8] [ 110/1319] eta: 0:55:59 lr: 4.0805784229057304e-05 loss: 0.0796 (0.1008) time: 2.7351 data: 0.0067 max mem: 33369 +Epoch: [8] [ 120/1319] eta: 0:55:27 lr: 4.079706017697721e-05 loss: 0.0778 (0.1007) time: 2.7361 data: 0.0068 max mem: 33369 +Epoch: [8] [ 130/1319] eta: 0:55:01 lr: 4.0788335917608504e-05 loss: 0.0855 (0.1019) time: 2.7649 data: 0.0069 max mem: 33369 +Epoch: [8] [ 140/1319] eta: 0:54:33 lr: 4.077961145089699e-05 loss: 0.0936 (0.1018) time: 2.7826 data: 0.0068 max mem: 33369 +Epoch: [8] [ 150/1319] eta: 0:54:02 lr: 4.0770886776788466e-05 loss: 0.0927 (0.1017) time: 2.7583 data: 0.0068 max mem: 33369 +Epoch: [8] [ 160/1319] eta: 0:53:32 lr: 4.076216189522867e-05 loss: 0.0930 (0.1019) time: 2.7412 data: 0.0069 max mem: 33369 +Epoch: [8] [ 170/1319] eta: 0:53:05 lr: 4.075343680616333e-05 loss: 0.0778 (0.1009) time: 2.7583 data: 0.0070 max mem: 33369 +Epoch: [8] [ 180/1319] eta: 0:52:34 lr: 4.074471150953815e-05 loss: 0.0778 (0.1003) time: 2.7526 data: 0.0070 max mem: 33369 +Epoch: [8] [ 190/1319] eta: 0:52:04 lr: 4.0735986005298814e-05 loss: 0.0829 (0.0998) time: 2.7271 data: 0.0069 max mem: 33369 +Epoch: [8] [ 200/1319] eta: 0:51:36 lr: 4.072726029339096e-05 loss: 0.0894 (0.0993) time: 2.7405 data: 0.0067 max mem: 33369 +Epoch: [8] [ 210/1319] eta: 0:51:08 lr: 4.07185343737602e-05 loss: 0.0899 (0.0992) time: 2.7601 data: 0.0066 max mem: 33369 +Epoch: [8] [ 220/1319] eta: 0:50:41 lr: 4.070980824635213e-05 loss: 0.0699 (0.0985) time: 2.7755 data: 0.0067 max mem: 33369 +Epoch: [8] [ 230/1319] eta: 0:50:13 lr: 4.070108191111232e-05 loss: 0.0786 (0.0996) time: 2.7698 data: 0.0066 max mem: 33369 +Epoch: [8] [ 240/1319] eta: 0:49:44 lr: 4.069235536798631e-05 loss: 0.0926 (0.0996) time: 2.7437 data: 0.0066 max mem: 33369 +Epoch: [8] [ 250/1319] eta: 0:49:15 lr: 4.0683628616919596e-05 loss: 0.0808 (0.0991) time: 2.7413 data: 0.0067 max mem: 33369 +Epoch: [8] [ 260/1319] eta: 0:48:49 lr: 4.0674901657857675e-05 loss: 0.0808 (0.0990) time: 2.7715 data: 0.0069 max mem: 33369 +Epoch: [8] [ 270/1319] eta: 0:48:20 lr: 4.066617449074599e-05 loss: 0.0814 (0.0990) time: 2.7658 data: 0.0071 max mem: 33369 +Epoch: [8] [ 280/1319] eta: 0:47:52 lr: 4.065744711552997e-05 loss: 0.0854 (0.0997) time: 2.7476 data: 0.0068 max mem: 33369 +Epoch: [8] [ 290/1319] eta: 0:47:22 lr: 4.064871953215503e-05 loss: 0.1042 (0.0997) time: 2.7304 data: 0.0064 max mem: 33369 +Epoch: [8] [ 300/1319] eta: 0:46:50 lr: 4.063999174056654e-05 loss: 0.0869 (0.0993) time: 2.6722 data: 0.0065 max mem: 33369 +Epoch: [8] [ 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+Epoch: [8] [ 390/1319] eta: 0:42:38 lr: 4.056143223763321e-05 loss: 0.0839 (0.0980) time: 2.7478 data: 0.0071 max mem: 33369 +Epoch: [8] [ 400/1319] eta: 0:42:10 lr: 4.055270236089869e-05 loss: 0.0934 (0.0986) time: 2.7383 data: 0.0070 max mem: 33369 +Epoch: [8] [ 410/1319] eta: 0:41:42 lr: 4.054397227534791e-05 loss: 0.1059 (0.0985) time: 2.7507 data: 0.0069 max mem: 33369 +Epoch: [8] [ 420/1319] eta: 0:41:15 lr: 4.0535241980925915e-05 loss: 0.1036 (0.0987) time: 2.7542 data: 0.0068 max mem: 33369 +Epoch: [8] [ 430/1319] eta: 0:40:47 lr: 4.0526511477577724e-05 loss: 0.0984 (0.0987) time: 2.7430 data: 0.0066 max mem: 33369 +Epoch: [8] [ 440/1319] eta: 0:40:19 lr: 4.051778076524832e-05 loss: 0.0913 (0.0985) time: 2.7493 data: 0.0067 max mem: 33369 +Epoch: [8] [ 450/1319] eta: 0:39:53 lr: 4.050904984388268e-05 loss: 0.0809 (0.0982) time: 2.7750 data: 0.0070 max mem: 33369 +Epoch: [8] [ 460/1319] eta: 0:39:25 lr: 4.0500318713425716e-05 loss: 0.0775 (0.0982) time: 2.7779 data: 0.0070 max mem: 33369 +Epoch: [8] [ 470/1319] eta: 0:38:58 lr: 4.0491587373822346e-05 loss: 0.0898 (0.0986) time: 2.7696 data: 0.0068 max mem: 33369 +Epoch: [8] [ 480/1319] eta: 0:38:31 lr: 4.048285582501745e-05 loss: 0.1069 (0.0990) time: 2.7703 data: 0.0067 max mem: 33369 +Epoch: [8] [ 490/1319] eta: 0:38:04 lr: 4.047412406695587e-05 loss: 0.1085 (0.0990) time: 2.7792 data: 0.0067 max mem: 33369 +Epoch: [8] [ 500/1319] eta: 0:37:36 lr: 4.046539209958243e-05 loss: 0.1056 (0.0989) time: 2.7685 data: 0.0068 max mem: 33369 +Epoch: [8] [ 510/1319] eta: 0:37:08 lr: 4.0456659922841925e-05 loss: 0.0863 (0.0992) time: 2.7345 data: 0.0068 max mem: 33369 +Epoch: [8] [ 520/1319] eta: 0:36:41 lr: 4.044792753667913e-05 loss: 0.0995 (0.0991) time: 2.7476 data: 0.0065 max mem: 33369 +Epoch: [8] [ 530/1319] eta: 0:36:13 lr: 4.0439194941038765e-05 loss: 0.0898 (0.0989) time: 2.7430 data: 0.0066 max mem: 33369 +Epoch: [8] [ 540/1319] eta: 0:35:45 lr: 4.043046213586556e-05 loss: 0.0898 (0.0989) time: 2.7216 data: 0.0068 max mem: 33369 +Epoch: [8] [ 550/1319] eta: 0:35:18 lr: 4.042172912110419e-05 loss: 0.0862 (0.0984) time: 2.7543 data: 0.0068 max mem: 33369 +Epoch: [8] [ 560/1319] eta: 0:34:50 lr: 4.0412995896699314e-05 loss: 0.0818 (0.0986) time: 2.7621 data: 0.0067 max mem: 33369 +Epoch: [8] [ 570/1319] eta: 0:34:22 lr: 4.040426246259555e-05 loss: 0.0932 (0.0986) time: 2.7355 data: 0.0068 max mem: 33369 +Epoch: [8] [ 580/1319] eta: 0:33:54 lr: 4.03955288187375e-05 loss: 0.0922 (0.0988) time: 2.7385 data: 0.0067 max mem: 33369 +Epoch: [8] [ 590/1319] eta: 0:33:27 lr: 4.038679496506974e-05 loss: 0.0956 (0.0989) time: 2.7481 data: 0.0067 max mem: 33369 +Epoch: [8] [ 600/1319] eta: 0:33:00 lr: 4.0378060901536817e-05 loss: 0.0945 (0.0989) time: 2.7823 data: 0.0067 max mem: 33369 +Epoch: [8] [ 610/1319] eta: 0:32:32 lr: 4.0369326628083236e-05 loss: 0.0828 (0.0986) time: 2.7622 data: 0.0067 max mem: 33369 +Epoch: [8] [ 620/1319] eta: 0:32:05 lr: 4.0360592144653494e-05 loss: 0.0859 (0.0985) time: 2.7381 data: 0.0066 max mem: 33369 +Epoch: [8] [ 630/1319] eta: 0:31:36 lr: 4.0351857451192053e-05 loss: 0.0985 (0.0987) time: 2.7053 data: 0.0068 max mem: 33369 +Epoch: [8] [ 640/1319] eta: 0:31:07 lr: 4.034312254764333e-05 loss: 0.0996 (0.0986) time: 2.6505 data: 0.0067 max mem: 33369 +Epoch: [8] [ 650/1319] eta: 0:30:39 lr: 4.033438743395174e-05 loss: 0.0933 (0.0987) time: 2.6693 data: 0.0065 max mem: 33369 +Epoch: [8] [ 660/1319] eta: 0:30:10 lr: 4.032565211006165e-05 loss: 0.0795 (0.0986) time: 2.6626 data: 0.0065 max mem: 33369 +Epoch: [8] [ 670/1319] eta: 0:29:42 lr: 4.031691657591742e-05 loss: 0.0881 (0.0987) time: 2.6444 data: 0.0065 max mem: 33369 +Epoch: [8] [ 680/1319] eta: 0:29:14 lr: 4.030818083146336e-05 loss: 0.0791 (0.0985) time: 2.6417 data: 0.0066 max mem: 33369 +Epoch: [8] [ 690/1319] eta: 0:28:45 lr: 4.029944487664375e-05 loss: 0.0768 (0.0984) time: 2.6284 data: 0.0067 max mem: 33369 +Epoch: [8] [ 700/1319] eta: 0:28:18 lr: 4.0290708711402866e-05 loss: 0.0816 (0.0983) time: 2.6884 data: 0.0069 max mem: 33369 +Epoch: [8] [ 710/1319] eta: 0:27:51 lr: 4.028197233568494e-05 loss: 0.0978 (0.0985) time: 2.7706 data: 0.0073 max mem: 33369 +Epoch: [8] [ 720/1319] eta: 0:27:24 lr: 4.027323574943419e-05 loss: 0.0978 (0.0986) time: 2.7895 data: 0.0074 max mem: 33369 +Epoch: [8] [ 730/1319] eta: 0:26:56 lr: 4.0264498952594776e-05 loss: 0.0889 (0.0986) time: 2.7747 data: 0.0071 max mem: 33369 +Epoch: [8] [ 740/1319] eta: 0:26:29 lr: 4.0255761945110847e-05 loss: 0.0930 (0.0986) time: 2.7752 data: 0.0069 max mem: 33369 +Epoch: [8] [ 750/1319] eta: 0:26:02 lr: 4.0247024726926543e-05 loss: 0.0962 (0.0989) time: 2.7792 data: 0.0068 max mem: 33369 +Epoch: [8] [ 760/1319] eta: 0:25:34 lr: 4.0238287297985935e-05 loss: 0.1084 (0.0991) time: 2.7579 data: 0.0068 max mem: 33369 +Epoch: [8] [ 770/1319] eta: 0:25:07 lr: 4.022954965823311e-05 loss: 0.0985 (0.0989) time: 2.7656 data: 0.0067 max mem: 33369 +Epoch: [8] [ 780/1319] eta: 0:24:40 lr: 4.0220811807612084e-05 loss: 0.0862 (0.0988) time: 2.7659 data: 0.0068 max mem: 33369 +Epoch: [8] [ 790/1319] eta: 0:24:12 lr: 4.021207374606688e-05 loss: 0.0862 (0.0987) time: 2.7493 data: 0.0068 max mem: 33369 +Epoch: [8] [ 800/1319] eta: 0:23:45 lr: 4.0203335473541464e-05 loss: 0.0900 (0.0987) time: 2.7408 data: 0.0069 max mem: 33369 +Epoch: [8] [ 810/1319] eta: 0:23:17 lr: 4.01945969899798e-05 loss: 0.0903 (0.0987) time: 2.7369 data: 0.0068 max mem: 33369 +Epoch: [8] [ 820/1319] eta: 0:22:50 lr: 4.0185858295325805e-05 loss: 0.0995 (0.0988) time: 2.7524 data: 0.0067 max mem: 33369 +Epoch: [8] [ 830/1319] eta: 0:22:23 lr: 4.017711938952337e-05 loss: 0.1126 (0.0990) time: 2.7637 data: 0.0068 max mem: 33369 +Epoch: [8] [ 840/1319] eta: 0:21:55 lr: 4.0168380272516376e-05 loss: 0.1038 (0.0991) time: 2.7310 data: 0.0069 max mem: 33369 +Epoch: [8] [ 850/1319] eta: 0:21:27 lr: 4.0159640944248643e-05 loss: 0.0882 (0.0991) time: 2.7270 data: 0.0068 max mem: 33369 +Epoch: [8] [ 860/1319] eta: 0:21:00 lr: 4.0150901404663985e-05 loss: 0.0896 (0.0992) time: 2.7446 data: 0.0068 max mem: 33369 +Epoch: [8] [ 870/1319] eta: 0:20:32 lr: 4.0142161653706185e-05 loss: 0.1138 (0.0996) time: 2.7348 data: 0.0067 max mem: 33369 +Epoch: [8] [ 880/1319] eta: 0:20:05 lr: 4.013342169131899e-05 loss: 0.1064 (0.0997) time: 2.7718 data: 0.0066 max mem: 33369 +Epoch: [8] [ 890/1319] eta: 0:19:38 lr: 4.012468151744613e-05 loss: 0.0956 (0.0997) time: 2.7884 data: 0.0067 max mem: 33369 +Epoch: [8] [ 900/1319] eta: 0:19:10 lr: 4.01159411320313e-05 loss: 0.0948 (0.0997) time: 2.7658 data: 0.0071 max mem: 33369 +Epoch: [8] [ 910/1319] eta: 0:18:43 lr: 4.010720053501816e-05 loss: 0.0973 (0.0998) time: 2.7516 data: 0.0071 max mem: 33369 +Epoch: [8] [ 920/1319] eta: 0:18:15 lr: 4.009845972635034e-05 loss: 0.0833 (0.0995) time: 2.7308 data: 0.0069 max mem: 33369 +Epoch: [8] [ 930/1319] eta: 0:17:48 lr: 4.008971870597147e-05 loss: 0.0893 (0.0995) time: 2.7320 data: 0.0070 max mem: 33369 +Epoch: [8] [ 940/1319] eta: 0:17:21 lr: 4.008097747382511e-05 loss: 0.1045 (0.0998) time: 2.7705 data: 0.0069 max mem: 33369 +Epoch: [8] [ 950/1319] eta: 0:16:53 lr: 4.0072236029854826e-05 loss: 0.1161 (0.1000) time: 2.7842 data: 0.0068 max mem: 33369 +Epoch: [8] [ 960/1319] eta: 0:16:26 lr: 4.006349437400413e-05 loss: 0.0950 (0.0999) time: 2.7763 data: 0.0070 max mem: 33369 +Epoch: [8] [ 970/1319] eta: 0:15:58 lr: 4.005475250621652e-05 loss: 0.0925 (0.0999) time: 2.7661 data: 0.0068 max mem: 33369 +Epoch: [8] [ 980/1319] eta: 0:15:31 lr: 4.004601042643546e-05 loss: 0.0879 (0.0998) time: 2.7268 data: 0.0067 max mem: 33369 +Epoch: [8] [ 990/1319] eta: 0:15:03 lr: 4.003726813460439e-05 loss: 0.0876 (0.0998) time: 2.6843 data: 0.0066 max mem: 33369 +Epoch: [8] [1000/1319] eta: 0:14:35 lr: 4.0028525630666715e-05 loss: 0.0902 (0.1000) time: 2.6683 data: 0.0066 max mem: 33369 +Epoch: [8] [1010/1319] eta: 0:14:08 lr: 4.00197829145658e-05 loss: 0.1151 (0.1002) time: 2.6631 data: 0.0067 max mem: 33369 +Epoch: [8] [1020/1319] eta: 0:13:40 lr: 4.001103998624502e-05 loss: 0.1016 (0.1002) time: 2.6629 data: 0.0067 max mem: 33369 +Epoch: [8] [1030/1319] eta: 0:13:12 lr: 4.000229684564768e-05 loss: 0.0940 (0.1001) time: 2.6696 data: 0.0067 max mem: 33369 +Epoch: [8] [1040/1319] eta: 0:12:45 lr: 3.9993553492717074e-05 loss: 0.0888 (0.1000) time: 2.6765 data: 0.0066 max mem: 33369 +Epoch: [8] [1050/1319] eta: 0:12:17 lr: 3.998480992739647e-05 loss: 0.0958 (0.1003) time: 2.6505 data: 0.0066 max mem: 33369 +Epoch: [8] [1060/1319] eta: 0:11:50 lr: 3.9976066149629094e-05 loss: 0.1013 (0.1003) time: 2.7200 data: 0.0069 max mem: 33369 +Epoch: [8] [1070/1319] eta: 0:11:22 lr: 3.9967322159358156e-05 loss: 0.0961 (0.1003) time: 2.8006 data: 0.0071 max mem: 33369 +Epoch: [8] [1080/1319] eta: 0:10:55 lr: 3.995857795652683e-05 loss: 0.1027 (0.1004) time: 2.7633 data: 0.0070 max mem: 33369 +Epoch: [8] [1090/1319] eta: 0:10:28 lr: 3.994983354107826e-05 loss: 0.1010 (0.1003) time: 2.7558 data: 0.0070 max mem: 33369 +Epoch: [8] [1100/1319] eta: 0:10:00 lr: 3.994108891295557e-05 loss: 0.0791 (0.1002) time: 2.7529 data: 0.0072 max mem: 33369 +Epoch: [8] [1110/1319] eta: 0:09:33 lr: 3.9932344072101854e-05 loss: 0.0841 (0.1002) time: 2.7643 data: 0.0071 max mem: 33369 +Epoch: [8] [1120/1319] eta: 0:09:05 lr: 3.9923599018460164e-05 loss: 0.0924 (0.1002) time: 2.7632 data: 0.0069 max mem: 33369 +Epoch: [8] [1130/1319] eta: 0:08:38 lr: 3.991485375197353e-05 loss: 0.0930 (0.1002) time: 2.7522 data: 0.0068 max mem: 33369 +Epoch: [8] [1140/1319] eta: 0:08:11 lr: 3.990610827258495e-05 loss: 0.0879 (0.1002) time: 2.7545 data: 0.0067 max mem: 33369 +Epoch: [8] [1150/1319] eta: 0:07:43 lr: 3.9897362580237394e-05 loss: 0.0864 (0.1001) time: 2.7533 data: 0.0067 max mem: 33369 +Epoch: [8] [1160/1319] eta: 0:07:16 lr: 3.988861667487383e-05 loss: 0.0949 (0.1002) time: 2.7509 data: 0.0069 max mem: 33369 +Epoch: [8] [1170/1319] eta: 0:06:48 lr: 3.987987055643715e-05 loss: 0.1047 (0.1004) time: 2.7777 data: 0.0070 max mem: 33369 +Epoch: [8] [1180/1319] eta: 0:06:21 lr: 3.9871124224870237e-05 loss: 0.0992 (0.1004) time: 2.7872 data: 0.0069 max mem: 33369 +Epoch: [8] [1190/1319] eta: 0:05:54 lr: 3.986237768011596e-05 loss: 0.0894 (0.1005) time: 2.7516 data: 0.0070 max mem: 33369 +Epoch: [8] [1200/1319] eta: 0:05:26 lr: 3.985363092211714e-05 loss: 0.0935 (0.1005) time: 2.7340 data: 0.0069 max mem: 33369 +Epoch: [8] [1210/1319] eta: 0:04:59 lr: 3.984488395081657e-05 loss: 0.0976 (0.1006) time: 2.7235 data: 0.0067 max mem: 33369 +Epoch: [8] [1220/1319] eta: 0:04:31 lr: 3.9836136766157016e-05 loss: 0.1067 (0.1007) time: 2.7308 data: 0.0069 max mem: 33369 +Epoch: [8] [1230/1319] eta: 0:04:04 lr: 3.9827389368081224e-05 loss: 0.1139 (0.1007) time: 2.7483 data: 0.0069 max mem: 33369 +Epoch: [8] [1240/1319] eta: 0:03:36 lr: 3.9818641756531906e-05 loss: 0.1035 (0.1007) time: 2.7437 data: 0.0068 max mem: 33369 +Epoch: [8] [1250/1319] eta: 0:03:09 lr: 3.980989393145173e-05 loss: 0.0941 (0.1007) time: 2.7612 data: 0.0066 max mem: 33369 +Epoch: [8] [1260/1319] eta: 0:02:41 lr: 3.9801145892783356e-05 loss: 0.0941 (0.1007) time: 2.7793 data: 0.0067 max mem: 33369 +Epoch: [8] [1270/1319] eta: 0:02:14 lr: 3.97923976404694e-05 loss: 0.0942 (0.1007) time: 2.7601 data: 0.0067 max mem: 33369 +Epoch: [8] [1280/1319] eta: 0:01:47 lr: 3.978364917445246e-05 loss: 0.0960 (0.1008) time: 2.7465 data: 0.0065 max mem: 33369 +Epoch: [8] [1290/1319] eta: 0:01:19 lr: 3.9774900494675086e-05 loss: 0.0887 (0.1007) time: 2.7634 data: 0.0067 max mem: 33369 +Epoch: [8] [1300/1319] eta: 0:00:52 lr: 3.976615160107982e-05 loss: 0.0962 (0.1008) time: 2.7625 data: 0.0069 max mem: 33369 +Epoch: [8] [1310/1319] eta: 0:00:24 lr: 3.975740249360917e-05 loss: 0.0937 (0.1009) time: 2.7573 data: 0.0068 max mem: 33369 +Epoch: [8] Total time: 1:00:21 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 2:14:19 time: 3.1322 data: 3.0523 max mem: 33369 +Test: [ 100/2573] eta: 0:04:14 time: 0.0722 data: 0.0012 max mem: 33369 +Test: [ 200/2573] eta: 0:03:30 time: 0.0735 data: 0.0011 max mem: 33369 +Test: [ 300/2573] eta: 0:03:09 time: 0.0753 data: 0.0012 max mem: 33369 +Test: [ 400/2573] eta: 0:02:55 time: 0.0755 data: 0.0011 max mem: 33369 +Test: [ 500/2573] eta: 0:02:44 time: 0.0739 data: 0.0012 max mem: 33369 +Test: [ 600/2573] eta: 0:02:35 time: 0.0736 data: 0.0011 max mem: 33369 +Test: [ 700/2573] eta: 0:02:26 time: 0.0743 data: 0.0012 max mem: 33369 +Test: [ 800/2573] eta: 0:02:17 time: 0.0770 data: 0.0011 max mem: 33369 +Test: [ 900/2573] eta: 0:02:09 time: 0.0737 data: 0.0011 max mem: 33369 +Test: [1000/2573] eta: 0:02:01 time: 0.0738 data: 0.0011 max mem: 33369 +Test: [1100/2573] eta: 0:01:53 time: 0.0738 data: 0.0011 max mem: 33369 +Test: [1200/2573] eta: 0:01:45 time: 0.0738 data: 0.0011 max mem: 33369 +Test: [1300/2573] eta: 0:01:37 time: 0.0739 data: 0.0011 max mem: 33369 +Test: [1400/2573] eta: 0:01:29 time: 0.0722 data: 0.0011 max mem: 33369 +Test: [1500/2573] eta: 0:01:21 time: 0.0737 data: 0.0011 max mem: 33369 +Test: [1600/2573] eta: 0:01:13 time: 0.0772 data: 0.0011 max mem: 33369 +Test: [1700/2573] eta: 0:01:06 time: 0.0722 data: 0.0011 max mem: 33369 +Test: [1800/2573] eta: 0:00:58 time: 0.0756 data: 0.0011 max mem: 33369 +Test: [1900/2573] eta: 0:00:50 time: 0.0723 data: 0.0011 max mem: 33369 +Test: [2000/2573] eta: 0:00:43 time: 0.0740 data: 0.0011 max mem: 33369 +Test: [2100/2573] eta: 0:00:35 time: 0.0756 data: 0.0011 max mem: 33369 +Test: [2200/2573] eta: 0:00:28 time: 0.0756 data: 0.0011 max mem: 33369 +Test: [2300/2573] eta: 0:00:20 time: 0.0755 data: 0.0011 max mem: 33369 +Test: [2400/2573] eta: 0:00:12 time: 0.0707 data: 0.0011 max mem: 33369 +Test: [2500/2573] eta: 0:00:05 time: 0.0740 data: 0.0011 max mem: 33369 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: Total time: 0:03:13 +Final results: +Mean IoU is 59.08 + + precision@0.5 = 66.42 + precision@0.6 = 59.46 + precision@0.7 = 50.96 + precision@0.8 = 38.60 + precision@0.9 = 16.52 + overall IoU = 57.92 + +Average object IoU 59.07974701943803 +Overall IoU 57.91716766357422 +Better epoch: 8 + +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [9] [ 0/1319] eta: 1:39:18 lr: 3.974952811397457e-05 loss: 0.1161 (0.1161) time: 4.5176 data: 1.5292 max mem: 33369 +Epoch: [9] [ 10/1319] eta: 1:05:25 lr: 3.974077859998216e-05 loss: 0.1033 (0.1271) time: 2.9991 data: 0.1451 max mem: 33369 +Epoch: [9] [ 20/1319] eta: 1:02:56 lr: 3.9732028871947454e-05 loss: 0.0896 (0.1119) time: 2.8264 data: 0.0067 max mem: 33369 +Epoch: [9] [ 30/1319] eta: 1:01:24 lr: 3.972327892981283e-05 loss: 0.0836 (0.1067) time: 2.7809 data: 0.0069 max mem: 33369 +Epoch: [9] [ 40/1319] eta: 1:00:22 lr: 3.971452877352066e-05 loss: 0.0836 (0.1091) time: 2.7531 data: 0.0071 max mem: 33369 +Epoch: [9] [ 50/1319] eta: 0:59:29 lr: 3.9705778403013264e-05 loss: 0.0863 (0.1117) time: 2.7433 data: 0.0069 max mem: 33369 +Epoch: [9] [ 60/1319] eta: 0:58:54 lr: 3.969702781823294e-05 loss: 0.0875 (0.1078) time: 2.7578 data: 0.0070 max mem: 33369 +Epoch: [9] [ 70/1319] eta: 0:58:11 lr: 3.9688277019121967e-05 loss: 0.1038 (0.1105) time: 2.7488 data: 0.0069 max mem: 33369 +Epoch: [9] [ 80/1319] eta: 0:57:31 lr: 3.967952600562257e-05 loss: 0.1006 (0.1083) time: 2.7178 data: 0.0068 max mem: 33369 +Epoch: [9] [ 90/1319] eta: 0:56:58 lr: 3.967077477767697e-05 loss: 0.0820 (0.1066) time: 2.7344 data: 0.0068 max mem: 33369 +Epoch: [9] [ 100/1319] eta: 0:56:23 lr: 3.966202333522733e-05 loss: 0.0838 (0.1063) time: 2.7351 data: 0.0067 max mem: 33369 +Epoch: [9] [ 110/1319] eta: 0:55:54 lr: 3.965327167821583e-05 loss: 0.0838 (0.1037) time: 2.7405 data: 0.0068 max mem: 33369 +Epoch: [9] [ 120/1319] eta: 0:55:25 lr: 3.9644519806584564e-05 loss: 0.0835 (0.1027) time: 2.7631 data: 0.0068 max mem: 33369 +Epoch: [9] [ 130/1319] eta: 0:54:54 lr: 3.963576772027564e-05 loss: 0.0835 (0.1019) time: 2.7490 data: 0.0069 max mem: 33369 +Epoch: [9] [ 140/1319] eta: 0:54:25 lr: 3.96270154192311e-05 loss: 0.0831 (0.1009) time: 2.7491 data: 0.0070 max mem: 33369 +Epoch: [9] [ 150/1319] eta: 0:53:55 lr: 3.9618262903393e-05 loss: 0.0853 (0.1005) time: 2.7499 data: 0.0069 max mem: 33369 +Epoch: [9] [ 160/1319] eta: 0:53:29 lr: 3.960951017270332e-05 loss: 0.0762 (0.0991) time: 2.7617 data: 0.0068 max mem: 33369 +Epoch: [9] [ 170/1319] eta: 0:53:01 lr: 3.9600757227104046e-05 loss: 0.0777 (0.0994) time: 2.7773 data: 0.0067 max mem: 33369 +Epoch: [9] [ 180/1319] eta: 0:52:32 lr: 3.95920040665371e-05 loss: 0.0880 (0.0988) time: 2.7579 data: 0.0068 max mem: 33369 +Epoch: [9] [ 190/1319] eta: 0:52:03 lr: 3.958325069094442e-05 loss: 0.0772 (0.0983) time: 2.7497 data: 0.0071 max mem: 33369 +Epoch: [9] [ 200/1319] eta: 0:51:35 lr: 3.957449710026786e-05 loss: 0.0856 (0.0982) time: 2.7558 data: 0.0071 max mem: 33369 +Epoch: [9] [ 210/1319] eta: 0:51:07 lr: 3.9565743294449283e-05 loss: 0.0856 (0.0975) time: 2.7602 data: 0.0067 max mem: 33369 +Epoch: [9] [ 220/1319] eta: 0:50:38 lr: 3.955698927343052e-05 loss: 0.0761 (0.0972) time: 2.7501 data: 0.0067 max mem: 33369 +Epoch: [9] [ 230/1319] eta: 0:50:10 lr: 3.954823503715335e-05 loss: 0.0760 (0.0963) time: 2.7488 data: 0.0069 max mem: 33369 +Epoch: [9] [ 240/1319] eta: 0:49:42 lr: 3.953948058555954e-05 loss: 0.0775 (0.0956) time: 2.7562 data: 0.0070 max mem: 33369 +Epoch: [9] [ 250/1319] eta: 0:49:13 lr: 3.9530725918590825e-05 loss: 0.0797 (0.0953) time: 2.7380 data: 0.0070 max mem: 33369 +Epoch: [9] [ 260/1319] eta: 0:48:44 lr: 3.952197103618889e-05 loss: 0.0780 (0.0946) time: 2.7243 data: 0.0069 max mem: 33369 +Epoch: [9] [ 270/1319] eta: 0:48:16 lr: 3.951321593829542e-05 loss: 0.0780 (0.0948) time: 2.7422 data: 0.0069 max mem: 33369 +Epoch: [9] [ 280/1319] eta: 0:47:47 lr: 3.9504460624852056e-05 loss: 0.0774 (0.0942) time: 2.7389 data: 0.0068 max mem: 33369 +Epoch: [9] [ 290/1319] eta: 0:47:15 lr: 3.94957050958004e-05 loss: 0.0676 (0.0938) time: 2.6780 data: 0.0065 max mem: 33369 +Epoch: [9] [ 300/1319] eta: 0:46:44 lr: 3.9486949351082035e-05 loss: 0.0735 (0.0932) time: 2.6507 data: 0.0065 max mem: 33369 +Epoch: [9] [ 310/1319] eta: 0:46:13 lr: 3.9478193390638515e-05 loss: 0.0735 (0.0929) time: 2.6533 data: 0.0065 max mem: 33369 +Epoch: [9] [ 320/1319] eta: 0:45:44 lr: 3.946943721441136e-05 loss: 0.0802 (0.0928) time: 2.6732 data: 0.0066 max mem: 33369 +Epoch: [9] [ 330/1319] eta: 0:45:15 lr: 3.946068082234206e-05 loss: 0.0831 (0.0928) time: 2.6942 data: 0.0066 max mem: 33369 +Epoch: [9] [ 340/1319] eta: 0:44:47 lr: 3.945192421437206e-05 loss: 0.0841 (0.0927) time: 2.7132 data: 0.0068 max mem: 33369 +Epoch: [9] [ 350/1319] eta: 0:44:21 lr: 3.944316739044282e-05 loss: 0.0825 (0.0924) time: 2.7684 data: 0.0073 max mem: 33369 +Epoch: [9] [ 360/1319] eta: 0:43:55 lr: 3.94344103504957e-05 loss: 0.0751 (0.0925) time: 2.7877 data: 0.0074 max mem: 33369 +Epoch: [9] [ 370/1319] eta: 0:43:28 lr: 3.94256530944721e-05 loss: 0.0858 (0.0922) time: 2.7873 data: 0.0072 max mem: 33369 +Epoch: [9] [ 380/1319] eta: 0:43:02 lr: 3.9416895622313336e-05 loss: 0.0893 (0.0926) time: 2.7848 data: 0.0072 max mem: 33369 +Epoch: [9] [ 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+Epoch: [9] [ 470/1319] eta: 0:38:56 lr: 3.9338068637108247e-05 loss: 0.0817 (0.0933) time: 2.7451 data: 0.0069 max mem: 33369 +Epoch: [9] [ 480/1319] eta: 0:38:29 lr: 3.932930900036482e-05 loss: 0.0789 (0.0930) time: 2.7390 data: 0.0067 max mem: 33369 +Epoch: [9] [ 490/1319] eta: 0:38:01 lr: 3.932054914683895e-05 loss: 0.0870 (0.0932) time: 2.7419 data: 0.0067 max mem: 33369 +Epoch: [9] [ 500/1319] eta: 0:37:33 lr: 3.9311789076471614e-05 loss: 0.0870 (0.0932) time: 2.7347 data: 0.0068 max mem: 33369 +Epoch: [9] [ 510/1319] eta: 0:37:05 lr: 3.930302878920372e-05 loss: 0.0820 (0.0931) time: 2.7340 data: 0.0070 max mem: 33369 +Epoch: [9] [ 520/1319] eta: 0:36:37 lr: 3.929426828497621e-05 loss: 0.0806 (0.0929) time: 2.7301 data: 0.0068 max mem: 33369 +Epoch: [9] [ 530/1319] eta: 0:36:10 lr: 3.9285507563729945e-05 loss: 0.0671 (0.0926) time: 2.7320 data: 0.0069 max mem: 33369 +Epoch: [9] [ 540/1319] eta: 0:35:42 lr: 3.927674662540578e-05 loss: 0.0705 (0.0924) time: 2.7399 data: 0.0069 max 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0.0070 max mem: 33369 +Epoch: [9] [ 630/1319] eta: 0:31:34 lr: 3.919788840220759e-05 loss: 0.0881 (0.0930) time: 2.6886 data: 0.0068 max mem: 33369 +Epoch: [9] [ 640/1319] eta: 0:31:06 lr: 3.918912528984432e-05 loss: 0.1080 (0.0930) time: 2.6562 data: 0.0068 max mem: 33369 +Epoch: [9] [ 650/1319] eta: 0:30:37 lr: 3.918036195975044e-05 loss: 0.0839 (0.0934) time: 2.6344 data: 0.0068 max mem: 33369 +Epoch: [9] [ 660/1319] eta: 0:30:09 lr: 3.9171598411866434e-05 loss: 0.0854 (0.0935) time: 2.6459 data: 0.0069 max mem: 33369 +Epoch: [9] [ 670/1319] eta: 0:29:41 lr: 3.9162834646132755e-05 loss: 0.0860 (0.0936) time: 2.6857 data: 0.0068 max mem: 33369 +Epoch: [9] [ 680/1319] eta: 0:29:13 lr: 3.915407066248981e-05 loss: 0.0871 (0.0939) time: 2.7343 data: 0.0072 max mem: 33369 +Epoch: [9] [ 690/1319] eta: 0:28:47 lr: 3.914530646087798e-05 loss: 0.0868 (0.0937) time: 2.7951 data: 0.0075 max mem: 33369 +Epoch: [9] [ 700/1319] eta: 0:28:20 lr: 3.9136542041237625e-05 loss: 0.0749 (0.0936) time: 2.7972 data: 0.0073 max mem: 33369 +Epoch: [9] [ 710/1319] eta: 0:27:52 lr: 3.9127777403509066e-05 loss: 0.0749 (0.0934) time: 2.7717 data: 0.0071 max mem: 33369 +Epoch: [9] [ 720/1319] eta: 0:27:25 lr: 3.9119012547632586e-05 loss: 0.0809 (0.0938) time: 2.7552 data: 0.0072 max mem: 33369 +Epoch: [9] [ 730/1319] eta: 0:26:57 lr: 3.911024747354846e-05 loss: 0.0961 (0.0938) time: 2.7612 data: 0.0071 max mem: 33369 +Epoch: [9] [ 740/1319] eta: 0:26:30 lr: 3.9101482181196904e-05 loss: 0.0912 (0.0937) time: 2.7695 data: 0.0070 max mem: 33369 +Epoch: [9] [ 750/1319] eta: 0:26:03 lr: 3.909271667051812e-05 loss: 0.0886 (0.0938) time: 2.7736 data: 0.0070 max mem: 33369 +Epoch: [9] [ 760/1319] eta: 0:25:35 lr: 3.908395094145227e-05 loss: 0.0876 (0.0940) time: 2.7435 data: 0.0069 max mem: 33369 +Epoch: [9] [ 770/1319] eta: 0:25:08 lr: 3.9075184993939487e-05 loss: 0.0876 (0.0940) time: 2.7391 data: 0.0071 max mem: 33369 +Epoch: [9] [ 780/1319] eta: 0:24:40 lr: 3.906641882791989e-05 loss: 0.0979 (0.0943) time: 2.7568 data: 0.0071 max mem: 33369 +Epoch: [9] [ 790/1319] eta: 0:24:13 lr: 3.9057652443333534e-05 loss: 0.0958 (0.0945) time: 2.7329 data: 0.0069 max mem: 33369 +Epoch: [9] [ 800/1319] eta: 0:23:45 lr: 3.904888584012046e-05 loss: 0.0846 (0.0945) time: 2.7321 data: 0.0070 max mem: 33369 +Epoch: [9] [ 810/1319] eta: 0:23:18 lr: 3.904011901822068e-05 loss: 0.0846 (0.0945) time: 2.7473 data: 0.0071 max mem: 33369 +Epoch: [9] [ 820/1319] eta: 0:22:50 lr: 3.9031351977574175e-05 loss: 0.0825 (0.0946) time: 2.7457 data: 0.0072 max mem: 33369 +Epoch: [9] [ 830/1319] eta: 0:22:23 lr: 3.9022584718120886e-05 loss: 0.0935 (0.0948) time: 2.7564 data: 0.0069 max mem: 33369 +Epoch: [9] [ 840/1319] eta: 0:21:56 lr: 3.901381723980073e-05 loss: 0.0923 (0.0946) time: 2.7758 data: 0.0068 max mem: 33369 +Epoch: [9] [ 850/1319] eta: 0:21:28 lr: 3.900504954255358e-05 loss: 0.0785 (0.0945) time: 2.7690 data: 0.0070 max mem: 33369 +Epoch: [9] [ 860/1319] eta: 0:21:01 lr: 3.899628162631931e-05 loss: 0.0750 (0.0945) time: 2.7417 data: 0.0070 max mem: 33369 +Epoch: [9] [ 870/1319] eta: 0:20:33 lr: 3.898751349103772e-05 loss: 0.0905 (0.0946) time: 2.7301 data: 0.0070 max mem: 33369 +Epoch: [9] [ 880/1319] eta: 0:20:06 lr: 3.8978745136648617e-05 loss: 0.0952 (0.0945) time: 2.7435 data: 0.0070 max mem: 33369 +Epoch: [9] [ 890/1319] eta: 0:19:38 lr: 3.896997656309173e-05 loss: 0.0776 (0.0944) time: 2.7444 data: 0.0071 max mem: 33369 +Epoch: [9] [ 900/1319] eta: 0:19:11 lr: 3.896120777030681e-05 loss: 0.0782 (0.0943) time: 2.7701 data: 0.0072 max mem: 33369 +Epoch: [9] [ 910/1319] eta: 0:18:43 lr: 3.895243875823353e-05 loss: 0.0762 (0.0942) time: 2.7691 data: 0.0072 max mem: 33369 +Epoch: [9] [ 920/1319] eta: 0:18:16 lr: 3.894366952681158e-05 loss: 0.0899 (0.0943) time: 2.7594 data: 0.0070 max mem: 33369 +Epoch: [9] [ 930/1319] eta: 0:17:49 lr: 3.8934900075980555e-05 loss: 0.0980 (0.0944) time: 2.7720 data: 0.0068 max mem: 33369 +Epoch: [9] [ 940/1319] eta: 0:17:21 lr: 3.8926130405680076e-05 loss: 0.0899 (0.0942) time: 2.7553 data: 0.0068 max mem: 33369 +Epoch: [9] [ 950/1319] eta: 0:16:54 lr: 3.8917360515849704e-05 loss: 0.0770 (0.0941) time: 2.7350 data: 0.0069 max mem: 33369 +Epoch: [9] [ 960/1319] eta: 0:16:26 lr: 3.8908590406428975e-05 loss: 0.0720 (0.0939) time: 2.6991 data: 0.0068 max mem: 33369 +Epoch: [9] [ 970/1319] eta: 0:15:58 lr: 3.889982007735738e-05 loss: 0.0701 (0.0937) time: 2.6832 data: 0.0066 max mem: 33369 +Epoch: [9] [ 980/1319] eta: 0:15:30 lr: 3.889104952857442e-05 loss: 0.0701 (0.0936) time: 2.6751 data: 0.0066 max mem: 33369 +Epoch: [9] [ 990/1319] eta: 0:15:03 lr: 3.888227876001951e-05 loss: 0.0905 (0.0937) time: 2.6743 data: 0.0067 max mem: 33369 +Epoch: [9] [1000/1319] eta: 0:14:35 lr: 3.887350777163206e-05 loss: 0.0979 (0.0939) time: 2.6818 data: 0.0067 max mem: 33369 +Epoch: [9] [1010/1319] eta: 0:14:07 lr: 3.886473656335145e-05 loss: 0.0909 (0.0940) time: 2.6684 data: 0.0068 max mem: 33369 +Epoch: [9] [1020/1319] eta: 0:13:40 lr: 3.8855965135117015e-05 loss: 0.0773 (0.0940) time: 2.6512 data: 0.0069 max mem: 33369 +Epoch: [9] [1030/1319] eta: 0:13:12 lr: 3.8847193486868084e-05 loss: 0.0780 (0.0940) time: 2.7024 data: 0.0069 max mem: 33369 +Epoch: [9] [1040/1319] eta: 0:12:45 lr: 3.883842161854392e-05 loss: 0.0724 (0.0939) time: 2.7985 data: 0.0072 max mem: 33369 +Epoch: [9] [1050/1319] eta: 0:12:18 lr: 3.8829649530083775e-05 loss: 0.0729 (0.0939) time: 2.8106 data: 0.0075 max mem: 33369 +Epoch: [9] [1060/1319] eta: 0:11:50 lr: 3.882087722142687e-05 loss: 0.0774 (0.0939) time: 2.7931 data: 0.0073 max mem: 33369 +Epoch: [9] [1070/1319] eta: 0:11:23 lr: 3.8812104692512384e-05 loss: 0.0806 (0.0939) time: 2.8078 data: 0.0070 max mem: 33369 +Epoch: [9] [1080/1319] eta: 0:10:56 lr: 3.880333194327947e-05 loss: 0.0917 (0.0939) time: 2.7972 data: 0.0068 max mem: 33369 +Epoch: [9] [1090/1319] eta: 0:10:28 lr: 3.879455897366725e-05 loss: 0.0945 (0.0939) time: 2.7836 data: 0.0068 max mem: 33369 +Epoch: [9] [1100/1319] eta: 0:10:01 lr: 3.878578578361481e-05 loss: 0.0789 (0.0937) time: 2.7841 data: 0.0068 max mem: 33369 +Epoch: [9] [1110/1319] eta: 0:09:34 lr: 3.87770123730612e-05 loss: 0.0776 (0.0937) time: 2.7969 data: 0.0068 max mem: 33369 +Epoch: [9] [1120/1319] eta: 0:09:06 lr: 3.876823874194545e-05 loss: 0.0867 (0.0937) time: 2.7712 data: 0.0068 max mem: 33369 +Epoch: [9] [1130/1319] eta: 0:08:39 lr: 3.8759464890206544e-05 loss: 0.0817 (0.0936) time: 2.7377 data: 0.0068 max mem: 33369 +Epoch: [9] [1140/1319] eta: 0:08:11 lr: 3.875069081778345e-05 loss: 0.0871 (0.0936) time: 2.7739 data: 0.0069 max mem: 33369 +Epoch: [9] [1150/1319] eta: 0:07:44 lr: 3.874191652461509e-05 loss: 0.0871 (0.0938) time: 2.7677 data: 0.0069 max mem: 33369 +Epoch: [9] [1160/1319] eta: 0:07:16 lr: 3.8733142010640345e-05 loss: 0.0772 (0.0937) time: 2.7506 data: 0.0068 max mem: 33369 +Epoch: [9] [1170/1319] eta: 0:06:49 lr: 3.872436727579809e-05 loss: 0.0791 (0.0936) time: 2.7847 data: 0.0067 max mem: 33369 +Epoch: [9] [1180/1319] eta: 0:06:21 lr: 3.871559232002716e-05 loss: 0.0791 (0.0935) time: 2.7457 data: 0.0067 max mem: 33369 +Epoch: [9] [1190/1319] eta: 0:05:54 lr: 3.870681714326634e-05 loss: 0.0861 (0.0935) time: 2.7051 data: 0.0067 max mem: 33369 +Epoch: [9] [1200/1319] eta: 0:05:26 lr: 3.86980417454544e-05 loss: 0.0817 (0.0934) time: 2.7014 data: 0.0069 max mem: 33369 +Epoch: [9] [1210/1319] eta: 0:04:59 lr: 3.8689266126530076e-05 loss: 0.0780 (0.0934) time: 2.7139 data: 0.0070 max mem: 33369 +Epoch: [9] [1220/1319] eta: 0:04:31 lr: 3.868049028643206e-05 loss: 0.0943 (0.0936) time: 2.6992 data: 0.0070 max mem: 33369 +Epoch: [9] [1230/1319] eta: 0:04:04 lr: 3.867171422509902e-05 loss: 0.0943 (0.0935) time: 2.6939 data: 0.0070 max mem: 33369 +Epoch: [9] [1240/1319] eta: 0:03:36 lr: 3.866293794246959e-05 loss: 0.0932 (0.0937) time: 2.7262 data: 0.0069 max mem: 33369 +Epoch: [9] [1250/1319] eta: 0:03:09 lr: 3.8654161438482394e-05 loss: 0.0899 (0.0938) time: 2.7471 data: 0.0069 max mem: 33369 +Epoch: [9] [1260/1319] eta: 0:02:41 lr: 3.864538471307598e-05 loss: 0.0793 (0.0936) time: 2.7378 data: 0.0068 max mem: 33369 +Epoch: [9] [1270/1319] eta: 0:02:14 lr: 3.863660776618888e-05 loss: 0.0800 (0.0937) time: 2.7119 data: 0.0067 max mem: 33369 +Epoch: [9] [1280/1319] eta: 0:01:47 lr: 3.8627830597759606e-05 loss: 0.0935 (0.0938) time: 2.7070 data: 0.0067 max mem: 33369 +Epoch: [9] [1290/1319] eta: 0:01:19 lr: 3.861905320772664e-05 loss: 0.1038 (0.0939) time: 2.6672 data: 0.0068 max mem: 33369 +Epoch: [9] [1300/1319] eta: 0:00:52 lr: 3.861027559602841e-05 loss: 0.0875 (0.0937) time: 2.6639 data: 0.0069 max mem: 33369 +Epoch: [9] [1310/1319] eta: 0:00:24 lr: 3.860149776260333e-05 loss: 0.0794 (0.0938) time: 2.6700 data: 0.0069 max mem: 33369 +Epoch: [9] Total time: 1:00:17 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 2:05:35 time: 2.9285 data: 2.8500 max mem: 33369 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 100/2573] eta: 0:04:07 time: 0.0715 data: 0.0011 max mem: 33369 +Test: [ 200/2573] eta: 0:03:26 time: 0.0735 data: 0.0012 max mem: 33369 +Test: [ 300/2573] eta: 0:03:06 time: 0.0751 data: 0.0011 max mem: 33369 +Test: [ 400/2573] eta: 0:02:53 time: 0.0752 data: 0.0011 max mem: 33369 +Test: [ 500/2573] eta: 0:02:43 time: 0.0736 data: 0.0011 max mem: 33369 +Test: [ 600/2573] eta: 0:02:33 time: 0.0735 data: 0.0011 max mem: 33369 +Test: [ 700/2573] eta: 0:02:25 time: 0.0736 data: 0.0011 max mem: 33369 +Test: [ 800/2573] eta: 0:02:16 time: 0.0770 data: 0.0011 max mem: 33369 +Test: [ 900/2573] eta: 0:02:08 time: 0.0737 data: 0.0011 max mem: 33369 +Test: [1000/2573] eta: 0:02:00 time: 0.0738 data: 0.0011 max mem: 33369 +Test: [1100/2573] eta: 0:01:52 time: 0.0738 data: 0.0011 max mem: 33369 +Test: [1200/2573] eta: 0:01:44 time: 0.0738 data: 0.0011 max mem: 33369 +Test: [1300/2573] eta: 0:01:36 time: 0.0737 data: 0.0011 max mem: 33369 +Test: [1400/2573] eta: 0:01:28 time: 0.0722 data: 0.0011 max mem: 33369 +Test: [1500/2573] eta: 0:01:21 time: 0.0741 data: 0.0012 max mem: 33369 +Test: [1600/2573] eta: 0:01:13 time: 0.0772 data: 0.0012 max mem: 33369 +Test: [1700/2573] eta: 0:01:05 time: 0.0721 data: 0.0011 max mem: 33369 +Test: [1800/2573] eta: 0:00:58 time: 0.0755 data: 0.0011 max mem: 33369 +Test: [1900/2573] eta: 0:00:50 time: 0.0722 data: 0.0011 max mem: 33369 +Test: [2000/2573] eta: 0:00:43 time: 0.0738 data: 0.0012 max mem: 33369 +Test: [2100/2573] eta: 0:00:35 time: 0.0754 data: 0.0011 max mem: 33369 +Test: [2200/2573] eta: 0:00:27 time: 0.0753 data: 0.0011 max mem: 33369 +Test: [2300/2573] eta: 0:00:20 time: 0.0754 data: 0.0011 max mem: 33369 +Test: [2400/2573] eta: 0:00:12 time: 0.0706 data: 0.0011 max mem: 33369 +Test: [2500/2573] eta: 0:00:05 time: 0.0737 data: 0.0011 max mem: 33369 +Test: Total time: 0:03:12 +Final results: +Mean IoU is 59.67 + + precision@0.5 = 66.99 + precision@0.6 = 60.80 + precision@0.7 = 52.78 + precision@0.8 = 40.24 + precision@0.9 = 18.44 + overall IoU = 59.07 + +Average object IoU 59.66971492280479 +Overall IoU 59.06611633300781 +Better epoch: 9 + +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [10] [ 0/1319] eta: 1:24:07 lr: 3.859359752289337e-05 loss: 0.1402 (0.1402) time: 3.8265 data: 1.1401 max mem: 33369 +Epoch: [10] [ 10/1319] eta: 1:00:15 lr: 3.858481926801746e-05 loss: 0.0910 (0.0899) time: 2.7619 data: 0.1092 max mem: 33369 +Epoch: [10] [ 20/1319] eta: 0:58:29 lr: 3.857604079123589e-05 loss: 0.0839 (0.0832) time: 2.6456 data: 0.0063 max mem: 33369 +Epoch: [10] [ 30/1319] eta: 0:57:19 lr: 3.856726209248695e-05 loss: 0.0855 (0.0881) time: 2.6170 data: 0.0064 max mem: 33369 +Epoch: [10] [ 40/1319] eta: 0:56:41 lr: 3.855848317170887e-05 loss: 0.0872 (0.0902) time: 2.6153 data: 0.0065 max mem: 33369 +Epoch: [10] [ 50/1319] eta: 0:56:10 lr: 3.854970402883988e-05 loss: 0.0800 (0.0867) time: 2.6372 data: 0.0065 max mem: 33369 +Epoch: [10] [ 60/1319] eta: 0:55:42 lr: 3.854092466381814e-05 loss: 0.0664 (0.0858) time: 2.6451 data: 0.0064 max mem: 33369 +Epoch: [10] [ 70/1319] eta: 0:55:12 lr: 3.853214507658182e-05 loss: 0.0831 (0.0863) time: 2.6420 data: 0.0064 max mem: 33369 +Epoch: [10] [ 80/1319] eta: 0:54:45 lr: 3.852336526706903e-05 loss: 0.0932 (0.0875) time: 2.6406 data: 0.0065 max mem: 33369 +Epoch: [10] [ 90/1319] eta: 0:54:19 lr: 3.8514585235217835e-05 loss: 0.0891 (0.0874) time: 2.6515 data: 0.0065 max mem: 33369 +Epoch: [10] [ 100/1319] eta: 0:53:54 lr: 3.850580498096631e-05 loss: 0.0717 (0.0863) time: 2.6627 data: 0.0066 max mem: 33369 +Epoch: [10] [ 110/1319] eta: 0:53:28 lr: 3.849702450425245e-05 loss: 0.0775 (0.0869) time: 2.6612 data: 0.0067 max mem: 33369 +Epoch: [10] [ 120/1319] eta: 0:53:03 lr: 3.8488243805014244e-05 loss: 0.0674 (0.0856) time: 2.6650 data: 0.0066 max mem: 33369 +Epoch: [10] [ 130/1319] eta: 0:52:35 lr: 3.8479462883189646e-05 loss: 0.0755 (0.0853) time: 2.6574 data: 0.0065 max mem: 33369 +Epoch: [10] [ 140/1319] eta: 0:52:11 lr: 3.8470681738716575e-05 loss: 0.0819 (0.0855) time: 2.6588 data: 0.0065 max mem: 33369 +Epoch: [10] [ 150/1319] eta: 0:51:38 lr: 3.846190037153291e-05 loss: 0.0856 (0.0850) time: 2.6283 data: 0.0066 max mem: 33369 +Epoch: [10] [ 160/1319] eta: 0:51:10 lr: 3.84531187815765e-05 loss: 0.0737 (0.0849) time: 2.6031 data: 0.0066 max mem: 33369 +Epoch: [10] [ 170/1319] eta: 0:50:43 lr: 3.844433696878517e-05 loss: 0.0740 (0.0864) time: 2.6306 data: 0.0065 max mem: 33369 +Epoch: [10] [ 180/1319] eta: 0:50:16 lr: 3.843555493309671e-05 loss: 0.0709 (0.0854) time: 2.6387 data: 0.0064 max mem: 33369 +Epoch: [10] [ 190/1319] eta: 0:49:50 lr: 3.842677267444885e-05 loss: 0.0692 (0.0855) time: 2.6529 data: 0.0063 max mem: 33369 +Epoch: [10] [ 200/1319] eta: 0:49:22 lr: 3.8417990192779335e-05 loss: 0.0797 (0.0858) time: 2.6428 data: 0.0065 max mem: 33369 +Epoch: [10] [ 210/1319] eta: 0:48:54 lr: 3.8409207488025836e-05 loss: 0.0797 (0.0861) time: 2.6236 data: 0.0065 max mem: 33369 +Epoch: [10] [ 220/1319] eta: 0:48:30 lr: 3.8400424560126e-05 loss: 0.0813 (0.0858) time: 2.6540 data: 0.0066 max mem: 33369 +Epoch: [10] [ 230/1319] eta: 0:48:02 lr: 3.839164140901745e-05 loss: 0.0820 (0.0859) time: 2.6536 data: 0.0067 max mem: 33369 +Epoch: [10] [ 240/1319] eta: 0:47:33 lr: 3.838285803463778e-05 loss: 0.0806 (0.0858) time: 2.6045 data: 0.0067 max mem: 33369 +Epoch: [10] [ 250/1319] eta: 0:47:09 lr: 3.8374074436924536e-05 loss: 0.0843 (0.0859) time: 2.6418 data: 0.0065 max mem: 33369 +Epoch: [10] [ 260/1319] eta: 0:46:42 lr: 3.836529061581523e-05 loss: 0.0893 (0.0862) time: 2.6657 data: 0.0064 max mem: 33369 +Epoch: [10] [ 270/1319] eta: 0:46:15 lr: 3.8356506571247355e-05 loss: 0.0809 (0.0865) time: 2.6382 data: 0.0064 max mem: 33369 +Epoch: [10] [ 280/1319] eta: 0:45:48 lr: 3.834772230315837e-05 loss: 0.0771 (0.0862) time: 2.6339 data: 0.0068 max mem: 33369 +Epoch: [10] [ 290/1319] eta: 0:45:21 lr: 3.833893781148568e-05 loss: 0.0765 (0.0862) time: 2.6336 data: 0.0069 max mem: 33369 +Epoch: [10] [ 300/1319] eta: 0:44:54 lr: 3.833015309616668e-05 loss: 0.0872 (0.0870) time: 2.6279 data: 0.0066 max mem: 33369 +Epoch: [10] [ 310/1319] eta: 0:44:29 lr: 3.832136815713871e-05 loss: 0.0866 (0.0868) time: 2.6470 data: 0.0065 max mem: 33369 +Epoch: [10] [ 320/1319] eta: 0:44:02 lr: 3.83125829943391e-05 loss: 0.0870 (0.0869) time: 2.6596 data: 0.0064 max mem: 33369 +Epoch: [10] [ 330/1319] eta: 0:43:36 lr: 3.830379760770512e-05 loss: 0.0870 (0.0867) time: 2.6461 data: 0.0065 max mem: 33369 +Epoch: [10] [ 340/1319] eta: 0:43:10 lr: 3.829501199717404e-05 loss: 0.0912 (0.0873) time: 2.6650 data: 0.0063 max mem: 33369 +Epoch: [10] [ 350/1319] eta: 0:42:44 lr: 3.828622616268306e-05 loss: 0.0856 (0.0872) time: 2.6695 data: 0.0063 max mem: 33369 +Epoch: [10] [ 360/1319] eta: 0:42:18 lr: 3.8277440104169376e-05 loss: 0.0785 (0.0871) time: 2.6576 data: 0.0064 max mem: 33369 +Epoch: [10] [ 370/1319] eta: 0:41:51 lr: 3.826865382157014e-05 loss: 0.0837 (0.0875) time: 2.6320 data: 0.0064 max mem: 33369 +Epoch: [10] [ 380/1319] eta: 0:41:24 lr: 3.8259867314822454e-05 loss: 0.0825 (0.0872) time: 2.6185 data: 0.0066 max mem: 33369 +Epoch: [10] [ 390/1319] eta: 0:40:57 lr: 3.825108058386341e-05 loss: 0.0777 (0.0869) time: 2.6325 data: 0.0067 max mem: 33369 +Epoch: [10] [ 400/1319] eta: 0:40:30 lr: 3.824229362863006e-05 loss: 0.0830 (0.0869) time: 2.6384 data: 0.0067 max mem: 33369 +Epoch: [10] [ 410/1319] eta: 0:40:04 lr: 3.823350644905941e-05 loss: 0.0906 (0.0872) time: 2.6434 data: 0.0065 max mem: 33369 +Epoch: [10] [ 420/1319] eta: 0:39:37 lr: 3.822471904508845e-05 loss: 0.0896 (0.0873) time: 2.6350 data: 0.0064 max mem: 33369 +Epoch: [10] [ 430/1319] eta: 0:39:11 lr: 3.821593141665413e-05 loss: 0.0823 (0.0872) time: 2.6524 data: 0.0065 max mem: 33369 +Epoch: [10] [ 440/1319] eta: 0:38:45 lr: 3.8207143563693345e-05 loss: 0.0770 (0.0870) time: 2.6635 data: 0.0065 max mem: 33369 +Epoch: [10] [ 450/1319] eta: 0:38:18 lr: 3.819835548614299e-05 loss: 0.0770 (0.0871) time: 2.6386 data: 0.0065 max mem: 33369 +Epoch: [10] [ 460/1319] eta: 0:37:52 lr: 3.8189567183939914e-05 loss: 0.0816 (0.0870) time: 2.6345 data: 0.0064 max mem: 33369 +Epoch: [10] [ 470/1319] eta: 0:37:24 lr: 3.8180778657020925e-05 loss: 0.0702 (0.0867) time: 2.6002 data: 0.0066 max mem: 33369 +Epoch: [10] [ 480/1319] eta: 0:36:57 lr: 3.81719899053228e-05 loss: 0.0663 (0.0869) time: 2.5976 data: 0.0066 max mem: 33369 +Epoch: [10] [ 490/1319] eta: 0:36:31 lr: 3.8163200928782287e-05 loss: 0.0889 (0.0869) time: 2.6392 data: 0.0066 max mem: 33369 +Epoch: [10] [ 500/1319] eta: 0:36:04 lr: 3.8154411727336084e-05 loss: 0.0844 (0.0870) time: 2.6346 data: 0.0066 max mem: 33369 +Epoch: [10] [ 510/1319] eta: 0:35:37 lr: 3.814562230092089e-05 loss: 0.0785 (0.0869) time: 2.6100 data: 0.0066 max mem: 33369 +Epoch: [10] [ 520/1319] eta: 0:35:10 lr: 3.8136832649473325e-05 loss: 0.0740 (0.0869) time: 2.6121 data: 0.0066 max mem: 33369 +Epoch: [10] [ 530/1319] eta: 0:34:44 lr: 3.812804277293001e-05 loss: 0.0740 (0.0868) time: 2.6335 data: 0.0065 max mem: 33369 +Epoch: [10] [ 540/1319] eta: 0:34:17 lr: 3.811925267122751e-05 loss: 0.0843 (0.0870) time: 2.6364 data: 0.0063 max mem: 33369 +Epoch: [10] [ 550/1319] eta: 0:33:51 lr: 3.8110462344302376e-05 loss: 0.0843 (0.0871) time: 2.6501 data: 0.0063 max mem: 33369 +Epoch: [10] [ 560/1319] eta: 0:33:25 lr: 3.8101671792091106e-05 loss: 0.0847 (0.0872) time: 2.6609 data: 0.0063 max mem: 33369 +Epoch: [10] [ 570/1319] eta: 0:32:58 lr: 3.809288101453017e-05 loss: 0.0874 (0.0873) time: 2.6371 data: 0.0064 max mem: 33369 +Epoch: [10] [ 580/1319] eta: 0:32:32 lr: 3.808409001155601e-05 loss: 0.0748 (0.0873) time: 2.6380 data: 0.0065 max mem: 33369 +Epoch: [10] [ 590/1319] eta: 0:32:06 lr: 3.807529878310503e-05 loss: 0.0772 (0.0873) time: 2.6550 data: 0.0064 max mem: 33369 +Epoch: [10] [ 600/1319] eta: 0:31:39 lr: 3.806650732911359e-05 loss: 0.0759 (0.0871) time: 2.6512 data: 0.0064 max mem: 33369 +Epoch: [10] [ 610/1319] eta: 0:31:13 lr: 3.8057715649518045e-05 loss: 0.0694 (0.0871) time: 2.6409 data: 0.0064 max mem: 33369 +Epoch: [10] [ 620/1319] eta: 0:30:46 lr: 3.804892374425468e-05 loss: 0.0878 (0.0872) time: 2.6265 data: 0.0065 max mem: 33369 +Epoch: [10] [ 630/1319] eta: 0:30:20 lr: 3.804013161325975e-05 loss: 0.0873 (0.0871) time: 2.6345 data: 0.0065 max mem: 33369 +Epoch: [10] [ 640/1319] eta: 0:29:53 lr: 3.803133925646951e-05 loss: 0.0851 (0.0873) time: 2.6196 data: 0.0064 max mem: 33369 +Epoch: [10] [ 650/1319] eta: 0:29:26 lr: 3.802254667382014e-05 loss: 0.0827 (0.0873) time: 2.6058 data: 0.0064 max mem: 33369 +Epoch: [10] [ 660/1319] eta: 0:29:00 lr: 3.801375386524781e-05 loss: 0.0733 (0.0872) time: 2.6358 data: 0.0066 max mem: 33369 +Epoch: [10] [ 670/1319] eta: 0:28:33 lr: 3.800496083068865e-05 loss: 0.0799 (0.0871) time: 2.6453 data: 0.0066 max mem: 33369 +Epoch: [10] [ 680/1319] eta: 0:28:07 lr: 3.799616757007876e-05 loss: 0.0719 (0.0870) time: 2.6245 data: 0.0065 max mem: 33369 +Epoch: [10] [ 690/1319] eta: 0:27:40 lr: 3.798737408335417e-05 loss: 0.0681 (0.0868) time: 2.6062 data: 0.0064 max mem: 33369 +Epoch: [10] [ 700/1319] eta: 0:27:14 lr: 3.797858037045094e-05 loss: 0.0681 (0.0866) time: 2.6349 data: 0.0063 max mem: 33369 +Epoch: [10] [ 710/1319] eta: 0:26:47 lr: 3.796978643130504e-05 loss: 0.0743 (0.0866) time: 2.6476 data: 0.0065 max mem: 33369 +Epoch: [10] [ 720/1319] eta: 0:26:21 lr: 3.796099226585244e-05 loss: 0.0761 (0.0866) time: 2.6370 data: 0.0065 max mem: 33369 +Epoch: [10] [ 730/1319] eta: 0:25:55 lr: 3.795219787402904e-05 loss: 0.0815 (0.0866) time: 2.6447 data: 0.0064 max mem: 33369 +Epoch: [10] [ 740/1319] eta: 0:25:28 lr: 3.794340325577075e-05 loss: 0.0834 (0.0867) time: 2.6549 data: 0.0064 max mem: 33369 +Epoch: [10] [ 750/1319] eta: 0:25:02 lr: 3.79346084110134e-05 loss: 0.0899 (0.0868) time: 2.6643 data: 0.0066 max mem: 33369 +Epoch: [10] [ 760/1319] eta: 0:24:36 lr: 3.7925813339692824e-05 loss: 0.0899 (0.0869) time: 2.6441 data: 0.0067 max mem: 33369 +Epoch: [10] [ 770/1319] eta: 0:24:09 lr: 3.79170180417448e-05 loss: 0.0749 (0.0870) time: 2.6404 data: 0.0064 max mem: 33369 +Epoch: [10] [ 780/1319] eta: 0:23:43 lr: 3.790822251710506e-05 loss: 0.0804 (0.0871) time: 2.6603 data: 0.0064 max mem: 33369 +Epoch: [10] [ 790/1319] eta: 0:23:16 lr: 3.789942676570934e-05 loss: 0.0749 (0.0870) time: 2.6360 data: 0.0065 max mem: 33369 +Epoch: [10] [ 800/1319] eta: 0:22:50 lr: 3.7890630787493295e-05 loss: 0.0747 (0.0869) time: 2.6248 data: 0.0063 max mem: 33369 +Epoch: [10] [ 810/1319] eta: 0:22:24 lr: 3.788183458239259e-05 loss: 0.0808 (0.0871) time: 2.6454 data: 0.0063 max mem: 33369 +Epoch: [10] [ 820/1319] eta: 0:21:57 lr: 3.7873038150342824e-05 loss: 0.0843 (0.0869) time: 2.6407 data: 0.0064 max mem: 33369 +Epoch: [10] [ 830/1319] eta: 0:21:31 lr: 3.7864241491279565e-05 loss: 0.0688 (0.0870) time: 2.6694 data: 0.0066 max mem: 33369 +Epoch: [10] [ 840/1319] eta: 0:21:05 lr: 3.785544460513836e-05 loss: 0.0767 (0.0870) time: 2.7080 data: 0.0068 max mem: 33369 +Epoch: [10] [ 850/1319] eta: 0:20:39 lr: 3.784664749185471e-05 loss: 0.0809 (0.0871) time: 2.6696 data: 0.0065 max mem: 33369 +Epoch: [10] [ 860/1319] eta: 0:20:13 lr: 3.7837850151364085e-05 loss: 0.0660 (0.0868) time: 2.7036 data: 0.0065 max mem: 33369 +Epoch: [10] [ 870/1319] eta: 0:19:48 lr: 3.78290525836019e-05 loss: 0.0731 (0.0870) time: 2.8195 data: 0.0066 max mem: 33369 +Epoch: [10] [ 880/1319] eta: 0:19:22 lr: 3.782025478850358e-05 loss: 0.0752 (0.0869) time: 2.8598 data: 0.0067 max mem: 33369 +Epoch: [10] [ 890/1319] eta: 0:18:57 lr: 3.7811456766004476e-05 loss: 0.0752 (0.0868) time: 2.8675 data: 0.0068 max mem: 33369 +Epoch: [10] [ 900/1319] eta: 0:18:31 lr: 3.780265851603992e-05 loss: 0.0737 (0.0867) time: 2.8837 data: 0.0066 max mem: 33369 +Epoch: [10] [ 910/1319] eta: 0:18:06 lr: 3.779386003854519e-05 loss: 0.0810 (0.0868) time: 2.8940 data: 0.0065 max mem: 33369 +Epoch: [10] [ 920/1319] eta: 0:17:40 lr: 3.7785061333455565e-05 loss: 0.0892 (0.0869) time: 2.8975 data: 0.0067 max mem: 33369 +Epoch: [10] [ 930/1319] eta: 0:17:15 lr: 3.7776262400706265e-05 loss: 0.0777 (0.0870) time: 2.8812 data: 0.0068 max mem: 33369 +Epoch: [10] [ 940/1319] eta: 0:16:49 lr: 3.776746324023246e-05 loss: 0.0766 (0.0869) time: 2.8803 data: 0.0068 max mem: 33369 +Epoch: [10] [ 950/1319] eta: 0:16:23 lr: 3.775866385196932e-05 loss: 0.0796 (0.0869) time: 2.8932 data: 0.0069 max mem: 33369 +Epoch: [10] [ 960/1319] eta: 0:15:58 lr: 3.774986423585195e-05 loss: 0.0800 (0.0870) time: 2.9055 data: 0.0068 max mem: 33369 +Epoch: [10] [ 970/1319] eta: 0:15:32 lr: 3.7741064391815444e-05 loss: 0.0834 (0.0870) time: 2.8943 data: 0.0067 max mem: 33369 +Epoch: [10] [ 980/1319] eta: 0:15:06 lr: 3.7732264319794836e-05 loss: 0.0757 (0.0870) time: 2.8818 data: 0.0066 max mem: 33369 +Epoch: [10] [ 990/1319] eta: 0:14:40 lr: 3.772346401972514e-05 loss: 0.0757 (0.0870) time: 2.8746 data: 0.0067 max mem: 33369 +Epoch: [10] [1000/1319] eta: 0:14:13 lr: 3.771466349154134e-05 loss: 0.0700 (0.0869) time: 2.8046 data: 0.0068 max mem: 33369 +Epoch: [10] [1010/1319] eta: 0:13:47 lr: 3.7705862735178374e-05 loss: 0.0714 (0.0869) time: 2.8172 data: 0.0072 max mem: 33369 +Epoch: [10] [1020/1319] eta: 0:13:21 lr: 3.7697061750571136e-05 loss: 0.0816 (0.0869) time: 2.8737 data: 0.0076 max mem: 33369 +Epoch: [10] [1030/1319] eta: 0:12:55 lr: 3.768826053765451e-05 loss: 0.0905 (0.0869) time: 2.8752 data: 0.0072 max mem: 33369 +Epoch: [10] [1040/1319] eta: 0:12:28 lr: 3.767945909636332e-05 loss: 0.0797 (0.0869) time: 2.8582 data: 0.0070 max mem: 33369 +Epoch: [10] [1050/1319] eta: 0:12:02 lr: 3.767065742663237e-05 loss: 0.0725 (0.0868) time: 2.8490 data: 0.0072 max mem: 33369 +Epoch: [10] [1060/1319] eta: 0:11:35 lr: 3.7661855528396415e-05 loss: 0.0687 (0.0867) time: 2.8511 data: 0.0076 max mem: 33369 +Epoch: [10] [1070/1319] eta: 0:11:09 lr: 3.765305340159019e-05 loss: 0.0698 (0.0868) time: 2.8340 data: 0.0078 max mem: 33369 +Epoch: [10] [1080/1319] eta: 0:10:42 lr: 3.764425104614838e-05 loss: 0.0822 (0.0870) time: 2.8050 data: 0.0072 max mem: 33369 +Epoch: [10] [1090/1319] eta: 0:10:16 lr: 3.763544846200565e-05 loss: 0.0983 (0.0870) time: 2.9014 data: 0.0068 max mem: 33369 +Epoch: [10] [1100/1319] eta: 0:09:49 lr: 3.7626645649096614e-05 loss: 0.0750 (0.0869) time: 2.9156 data: 0.0071 max mem: 33369 +Epoch: [10] [1110/1319] eta: 0:09:23 lr: 3.761784260735586e-05 loss: 0.0731 (0.0868) time: 2.8456 data: 0.0071 max mem: 33369 +Epoch: [10] [1120/1319] eta: 0:08:56 lr: 3.760903933671793e-05 loss: 0.0791 (0.0868) time: 2.8598 data: 0.0071 max mem: 33369 +Epoch: [10] [1130/1319] eta: 0:08:29 lr: 3.760023583711735e-05 loss: 0.0824 (0.0868) time: 2.8480 data: 0.0076 max mem: 33369 +Epoch: [10] [1140/1319] eta: 0:08:03 lr: 3.7591432108488584e-05 loss: 0.0818 (0.0868) time: 2.8506 data: 0.0080 max mem: 33369 +Epoch: [10] [1150/1319] eta: 0:07:36 lr: 3.758262815076608e-05 loss: 0.0790 (0.0869) time: 2.8018 data: 0.0075 max mem: 33369 +Epoch: [10] [1160/1319] eta: 0:07:09 lr: 3.7573823963884245e-05 loss: 0.0847 (0.0869) time: 2.8260 data: 0.0070 max mem: 33369 +Epoch: [10] [1170/1319] eta: 0:06:42 lr: 3.756501954777745e-05 loss: 0.0725 (0.0868) time: 2.8592 data: 0.0077 max mem: 33369 +Epoch: [10] [1180/1319] eta: 0:06:15 lr: 3.755621490238003e-05 loss: 0.0762 (0.0868) time: 2.8282 data: 0.0083 max mem: 33369 +Epoch: [10] [1190/1319] eta: 0:05:48 lr: 3.754741002762627e-05 loss: 0.0822 (0.0869) time: 2.8358 data: 0.0082 max mem: 33369 +Epoch: [10] [1200/1319] eta: 0:05:21 lr: 3.753860492345044e-05 loss: 0.0813 (0.0869) time: 2.8501 data: 0.0079 max mem: 33369 +Epoch: [10] [1210/1319] eta: 0:04:54 lr: 3.7529799589786776e-05 loss: 0.0758 (0.0869) time: 2.8369 data: 0.0073 max mem: 33369 +Epoch: [10] [1220/1319] eta: 0:04:27 lr: 3.752099402656945e-05 loss: 0.0836 (0.0869) time: 2.8225 data: 0.0077 max mem: 33369 +Epoch: [10] [1230/1319] eta: 0:04:00 lr: 3.751218823373263e-05 loss: 0.0935 (0.0870) time: 2.7810 data: 0.0076 max mem: 33369 +Epoch: [10] [1240/1319] eta: 0:03:34 lr: 3.750338221121043e-05 loss: 0.0865 (0.0870) time: 2.8485 data: 0.0070 max mem: 33369 +Epoch: [10] [1250/1319] eta: 0:03:06 lr: 3.749457595893693e-05 loss: 0.0865 (0.0870) time: 2.8839 data: 0.0076 max mem: 33369 +Epoch: [10] [1260/1319] eta: 0:02:39 lr: 3.748576947684619e-05 loss: 0.0856 (0.0870) time: 2.8457 data: 0.0077 max mem: 33369 +Epoch: [10] [1270/1319] eta: 0:02:12 lr: 3.74769627648722e-05 loss: 0.0827 (0.0870) time: 2.8568 data: 0.0075 max mem: 33369 +Epoch: [10] [1280/1319] eta: 0:01:45 lr: 3.746815582294894e-05 loss: 0.0757 (0.0870) time: 2.8207 data: 0.0079 max mem: 33369 +Epoch: [10] [1290/1319] eta: 0:01:18 lr: 3.745934865101035e-05 loss: 0.0735 (0.0871) time: 2.8433 data: 0.0078 max mem: 33369 +Epoch: [10] [1300/1319] eta: 0:00:51 lr: 3.7450541248990324e-05 loss: 0.0785 (0.0871) time: 2.8513 data: 0.0070 max mem: 33369 +Epoch: [10] [1310/1319] eta: 0:00:24 lr: 3.7441733616822736e-05 loss: 0.0857 (0.0872) time: 2.8459 data: 0.0067 max mem: 33369 +Epoch: [10] Total time: 0:59:44 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 2:21:45 time: 3.3056 data: 3.2261 max mem: 33369 +Test: [ 100/2573] eta: 0:04:20 time: 0.0729 data: 0.0013 max mem: 33369 +Test: [ 200/2573] eta: 0:03:34 time: 0.0740 data: 0.0012 max mem: 33369 +Test: [ 300/2573] eta: 0:03:12 time: 0.0758 data: 0.0013 max mem: 33369 +Test: [ 400/2573] eta: 0:02:58 time: 0.0761 data: 0.0012 max mem: 33369 +Test: [ 500/2573] eta: 0:02:46 time: 0.0748 data: 0.0013 max mem: 33369 +Test: [ 600/2573] eta: 0:02:37 time: 0.0745 data: 0.0013 max mem: 33369 +Test: [ 700/2573] eta: 0:02:28 time: 0.0748 data: 0.0013 max mem: 33369 +Test: [ 800/2573] eta: 0:02:19 time: 0.0780 data: 0.0012 max mem: 33369 +Test: [ 900/2573] eta: 0:02:11 time: 0.0746 data: 0.0012 max mem: 33369 +Test: [1000/2573] eta: 0:02:02 time: 0.0749 data: 0.0013 max mem: 33369 +Test: [1100/2573] eta: 0:01:54 time: 0.0747 data: 0.0012 max mem: 33369 +Test: [1200/2573] eta: 0:01:46 time: 0.0746 data: 0.0012 max mem: 33369 +Test: [1300/2573] eta: 0:01:38 time: 0.0749 data: 0.0012 max mem: 33369 +Test: [1400/2573] eta: 0:01:30 time: 0.0733 data: 0.0013 max mem: 33369 +Test: [1500/2573] eta: 0:01:22 time: 0.0750 data: 0.0013 max mem: 33369 +Test: [1600/2573] eta: 0:01:14 time: 0.0784 data: 0.0013 max mem: 33369 +Test: [1700/2573] eta: 0:01:07 time: 0.0733 data: 0.0012 max mem: 33369 +Test: [1800/2573] eta: 0:00:59 time: 0.0764 data: 0.0012 max mem: 33369 +Test: [1900/2573] eta: 0:00:51 time: 0.0732 data: 0.0013 max mem: 33369 +Test: [2000/2573] eta: 0:00:43 time: 0.0750 data: 0.0013 max mem: 33369 +Test: [2100/2573] eta: 0:00:36 time: 0.0759 data: 0.0011 max mem: 33369 +Test: [2200/2573] eta: 0:00:28 time: 0.0760 data: 0.0011 max mem: 33369 +Test: [2300/2573] eta: 0:00:20 time: 0.0758 data: 0.0011 max mem: 33369 +Test: [2400/2573] eta: 0:00:13 time: 0.0709 data: 0.0012 max mem: 33369 +Test: [2500/2573] eta: 0:00:05 time: 0.0765 data: 0.0015 max mem: 33369 +Test: Total time: 0:03:15 +Final results: +Mean IoU is 60.79 + + precision@0.5 = 68.48 + precision@0.6 = 62.15 + precision@0.7 = 54.11 + precision@0.8 = 41.12 + precision@0.9 = 18.77 + overall IoU = 59.49 + +Average object IoU 60.78795373096612 +Overall IoU 59.49290084838867 +Better epoch: 10 + +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [11] [ 0/1319] eta: 1:34:59 lr: 3.743380655104104e-05 loss: 0.0307 (0.0307) time: 4.3207 data: 1.3563 max mem: 33369 +Epoch: [11] [ 10/1319] eta: 1:06:07 lr: 3.742499848141075e-05 loss: 0.0672 (0.0658) time: 3.0306 data: 0.1295 max mem: 33369 +Epoch: [11] [ 20/1319] eta: 1:03:45 lr: 3.741619018144089e-05 loss: 0.0688 (0.0715) time: 2.8759 data: 0.0067 max mem: 33369 +Epoch: [11] [ 30/1319] eta: 1:03:02 lr: 3.7407381651065185e-05 loss: 0.0780 (0.0769) time: 2.8814 data: 0.0067 max mem: 33369 +Epoch: [11] [ 40/1319] eta: 1:02:17 lr: 3.739857289021734e-05 loss: 0.0795 (0.0788) time: 2.8979 data: 0.0068 max mem: 33369 +Epoch: [11] [ 50/1319] eta: 1:01:43 lr: 3.738976389883098e-05 loss: 0.0740 (0.0852) time: 2.8947 data: 0.0067 max mem: 33369 +Epoch: [11] [ 60/1319] eta: 1:01:04 lr: 3.738095467683973e-05 loss: 0.0642 (0.0837) time: 2.8889 data: 0.0070 max mem: 33369 +Epoch: [11] [ 70/1319] eta: 1:00:34 lr: 3.737214522417717e-05 loss: 0.0773 (0.0833) time: 2.8872 data: 0.0071 max mem: 33369 +Epoch: [11] [ 80/1319] eta: 0:59:58 lr: 3.736333554077684e-05 loss: 0.0717 (0.0821) time: 2.8852 data: 0.0069 max mem: 33369 +Epoch: [11] [ 90/1319] eta: 0:59:29 lr: 3.735452562657224e-05 loss: 0.0739 (0.0831) time: 2.8855 data: 0.0073 max mem: 33369 +Epoch: [11] [ 100/1319] eta: 0:58:56 lr: 3.734571548149683e-05 loss: 0.0781 (0.0827) time: 2.8864 data: 0.0072 max mem: 33369 +Epoch: [11] [ 110/1319] eta: 0:58:23 lr: 3.733690510548406e-05 loss: 0.0686 (0.0821) time: 2.8657 data: 0.0069 max mem: 33369 +Epoch: [11] [ 120/1319] eta: 0:57:54 lr: 3.732809449846732e-05 loss: 0.0698 (0.0828) time: 2.8818 data: 0.0070 max mem: 33369 +Epoch: [11] [ 130/1319] eta: 0:57:21 lr: 3.7319283660379954e-05 loss: 0.0676 (0.0822) time: 2.8760 data: 0.0069 max mem: 33369 +Epoch: [11] [ 140/1319] eta: 0:56:41 lr: 3.7310472591155297e-05 loss: 0.0643 (0.0813) time: 2.8102 data: 0.0072 max mem: 33369 +Epoch: [11] [ 150/1319] eta: 0:56:12 lr: 3.7301661290726626e-05 loss: 0.0744 (0.0829) time: 2.8231 data: 0.0073 max mem: 33369 +Epoch: [11] [ 160/1319] eta: 0:55:39 lr: 3.729284975902719e-05 loss: 0.0962 (0.0843) time: 2.8494 data: 0.0071 max mem: 33369 +Epoch: [11] [ 170/1319] eta: 0:55:13 lr: 3.728403799599019e-05 loss: 0.0820 (0.0848) time: 2.8754 data: 0.0069 max mem: 33369 +Epoch: [11] [ 180/1319] eta: 0:54:45 lr: 3.727522600154881e-05 loss: 0.0784 (0.0844) time: 2.9129 data: 0.0067 max mem: 33369 +Epoch: [11] [ 190/1319] eta: 0:54:19 lr: 3.7266413775636196e-05 loss: 0.0793 (0.0847) time: 2.9160 data: 0.0067 max mem: 33369 +Epoch: [11] [ 200/1319] eta: 0:53:45 lr: 3.725760131818543e-05 loss: 0.0730 (0.0842) time: 2.8685 data: 0.0074 max mem: 33369 +Epoch: [11] [ 210/1319] eta: 0:53:10 lr: 3.724878862912958e-05 loss: 0.0614 (0.0836) time: 2.7837 data: 0.0080 max mem: 33369 +Epoch: [11] [ 220/1319] eta: 0:52:35 lr: 3.723997570840168e-05 loss: 0.0668 (0.0830) time: 2.7590 data: 0.0075 max mem: 33369 +Epoch: [11] [ 230/1319] eta: 0:52:10 lr: 3.723116255593471e-05 loss: 0.0703 (0.0826) time: 2.8476 data: 0.0072 max mem: 33369 +Epoch: [11] [ 240/1319] eta: 0:51:40 lr: 3.7222349171661633e-05 loss: 0.0800 (0.0839) time: 2.8969 data: 0.0077 max mem: 33369 +Epoch: [11] [ 250/1319] eta: 0:51:09 lr: 3.721353555551535e-05 loss: 0.0769 (0.0833) time: 2.8369 data: 0.0079 max mem: 33369 +Epoch: [11] [ 260/1319] eta: 0:50:40 lr: 3.720472170742875e-05 loss: 0.0717 (0.0835) time: 2.8350 data: 0.0079 max mem: 33369 +Epoch: [11] [ 270/1319] eta: 0:50:11 lr: 3.719590762733466e-05 loss: 0.0748 (0.0834) time: 2.8572 data: 0.0080 max mem: 33369 +Epoch: [11] [ 280/1319] eta: 0:49:41 lr: 3.718709331516589e-05 loss: 0.0714 (0.0832) time: 2.8539 data: 0.0077 max mem: 33369 +Epoch: [11] [ 290/1319] eta: 0:49:10 lr: 3.7178278770855225e-05 loss: 0.0732 (0.0830) time: 2.8171 data: 0.0073 max mem: 33369 +Epoch: [11] [ 300/1319] eta: 0:48:42 lr: 3.716946399433537e-05 loss: 0.0769 (0.0828) time: 2.8494 data: 0.0070 max mem: 33369 +Epoch: [11] [ 310/1319] eta: 0:48:13 lr: 3.716064898553902e-05 loss: 0.0737 (0.0827) time: 2.8847 data: 0.0068 max mem: 33369 +Epoch: [11] [ 320/1319] eta: 0:47:45 lr: 3.715183374439884e-05 loss: 0.0777 (0.0824) time: 2.8743 data: 0.0067 max mem: 33369 +Epoch: [11] [ 330/1319] eta: 0:47:16 lr: 3.7143018270847454e-05 loss: 0.0723 (0.0824) time: 2.8716 data: 0.0068 max mem: 33369 +Epoch: [11] [ 340/1319] eta: 0:46:47 lr: 3.713420256481742e-05 loss: 0.0674 (0.0822) time: 2.8568 data: 0.0070 max mem: 33369 +Epoch: [11] [ 350/1319] eta: 0:46:17 lr: 3.712538662624129e-05 loss: 0.0614 (0.0817) time: 2.8335 data: 0.0071 max mem: 33369 +Epoch: [11] [ 360/1319] eta: 0:45:48 lr: 3.7116570455051586e-05 loss: 0.0639 (0.0818) time: 2.8283 data: 0.0073 max mem: 33369 +Epoch: [11] [ 370/1319] eta: 0:45:15 lr: 3.710775405118075e-05 loss: 0.0740 (0.0818) time: 2.7788 data: 0.0072 max mem: 33369 +Epoch: [11] [ 380/1319] eta: 0:44:49 lr: 3.709893741456123e-05 loss: 0.0740 (0.0818) time: 2.8285 data: 0.0071 max mem: 33369 +Epoch: [11] [ 390/1319] eta: 0:44:20 lr: 3.709012054512541e-05 loss: 0.0734 (0.0819) time: 2.8946 data: 0.0073 max mem: 33369 +Epoch: [11] [ 400/1319] eta: 0:43:50 lr: 3.7081303442805645e-05 loss: 0.0744 (0.0822) time: 2.8386 data: 0.0076 max mem: 33369 +Epoch: [11] [ 410/1319] eta: 0:43:20 lr: 3.7072486107534264e-05 loss: 0.0871 (0.0826) time: 2.8192 data: 0.0079 max mem: 33369 +Epoch: [11] [ 420/1319] eta: 0:42:52 lr: 3.706366853924354e-05 loss: 0.0871 (0.0827) time: 2.8321 data: 0.0077 max mem: 33369 +Epoch: [11] [ 430/1319] eta: 0:42:23 lr: 3.705485073786572e-05 loss: 0.0644 (0.0826) time: 2.8600 data: 0.0073 max mem: 33369 +Epoch: [11] [ 440/1319] eta: 0:41:54 lr: 3.704603270333301e-05 loss: 0.0595 (0.0821) time: 2.8556 data: 0.0069 max mem: 33369 +Epoch: [11] [ 450/1319] eta: 0:41:25 lr: 3.703721443557757e-05 loss: 0.0682 (0.0824) time: 2.8520 data: 0.0068 max mem: 33369 +Epoch: [11] [ 460/1319] eta: 0:40:56 lr: 3.702839593453153e-05 loss: 0.0775 (0.0824) time: 2.8469 data: 0.0071 max mem: 33369 +Epoch: [11] [ 470/1319] eta: 0:40:27 lr: 3.7019577200126995e-05 loss: 0.0697 (0.0824) time: 2.8384 data: 0.0071 max mem: 33369 +Epoch: [11] [ 480/1319] eta: 0:39:58 lr: 3.701075823229601e-05 loss: 0.0809 (0.0826) time: 2.8378 data: 0.0075 max mem: 33369 +Epoch: [11] [ 490/1319] eta: 0:39:29 lr: 3.700193903097059e-05 loss: 0.0904 (0.0828) time: 2.8243 data: 0.0076 max mem: 33369 +Epoch: [11] [ 500/1319] eta: 0:39:00 lr: 3.6993119596082715e-05 loss: 0.0837 (0.0829) time: 2.8179 data: 0.0077 max mem: 33369 +Epoch: [11] [ 510/1319] eta: 0:38:32 lr: 3.698429992756433e-05 loss: 0.0796 (0.0830) time: 2.8488 data: 0.0078 max mem: 33369 +Epoch: [11] [ 520/1319] eta: 0:38:01 lr: 3.6975480025347336e-05 loss: 0.0796 (0.0830) time: 2.8090 data: 0.0070 max mem: 33369 +Epoch: [11] [ 530/1319] eta: 0:37:34 lr: 3.69666598893636e-05 loss: 0.0859 (0.0836) time: 2.8369 data: 0.0070 max mem: 33369 +Epoch: [11] [ 540/1319] eta: 0:37:06 lr: 3.695783951954495e-05 loss: 0.0859 (0.0837) time: 2.9065 data: 0.0073 max mem: 33369 +Epoch: [11] [ 550/1319] eta: 0:36:37 lr: 3.694901891582318e-05 loss: 0.0913 (0.0839) time: 2.8536 data: 0.0072 max mem: 33369 +Epoch: [11] [ 560/1319] eta: 0:36:08 lr: 3.694019807813003e-05 loss: 0.0811 (0.0838) time: 2.8228 data: 0.0080 max mem: 33369 +Epoch: [11] [ 570/1319] eta: 0:35:39 lr: 3.6931377006397214e-05 loss: 0.0793 (0.0838) time: 2.8541 data: 0.0078 max mem: 33369 +Epoch: [11] [ 580/1319] eta: 0:35:11 lr: 3.692255570055642e-05 loss: 0.0725 (0.0839) time: 2.8698 data: 0.0073 max mem: 33369 +Epoch: [11] [ 590/1319] eta: 0:34:42 lr: 3.691373416053928e-05 loss: 0.0725 (0.0838) time: 2.8535 data: 0.0073 max mem: 33369 +Epoch: [11] [ 600/1319] eta: 0:34:13 lr: 3.690491238627739e-05 loss: 0.0680 (0.0836) time: 2.8353 data: 0.0067 max mem: 33369 +Epoch: [11] [ 610/1319] eta: 0:33:45 lr: 3.6896090377702305e-05 loss: 0.0795 (0.0838) time: 2.8596 data: 0.0073 max mem: 33369 +Epoch: [11] [ 620/1319] eta: 0:33:16 lr: 3.688726813474555e-05 loss: 0.0795 (0.0838) time: 2.8536 data: 0.0083 max mem: 33369 +Epoch: [11] [ 630/1319] eta: 0:32:47 lr: 3.687844565733862e-05 loss: 0.0750 (0.0839) time: 2.8134 data: 0.0084 max mem: 33369 +Epoch: [11] [ 640/1319] eta: 0:32:18 lr: 3.686962294541296e-05 loss: 0.0721 (0.0838) time: 2.8315 data: 0.0078 max mem: 33369 +Epoch: [11] [ 650/1319] eta: 0:31:51 lr: 3.686079999889997e-05 loss: 0.0715 (0.0842) time: 2.8904 data: 0.0071 max mem: 33369 +Epoch: [11] [ 660/1319] eta: 0:31:22 lr: 3.6851976817731035e-05 loss: 0.0733 (0.0844) time: 2.9210 data: 0.0071 max mem: 33369 +Epoch: [11] [ 670/1319] eta: 0:30:53 lr: 3.684315340183746e-05 loss: 0.0747 (0.0844) time: 2.8414 data: 0.0073 max mem: 33369 +Epoch: [11] [ 680/1319] eta: 0:30:25 lr: 3.683432975115057e-05 loss: 0.0739 (0.0843) time: 2.8474 data: 0.0069 max mem: 33369 +Epoch: [11] [ 690/1319] eta: 0:29:57 lr: 3.682550586560159e-05 loss: 0.0731 (0.0844) time: 2.8924 data: 0.0067 max mem: 33369 +Epoch: [11] [ 700/1319] eta: 0:29:28 lr: 3.6816681745121755e-05 loss: 0.0715 (0.0845) time: 2.8745 data: 0.0068 max mem: 33369 +Epoch: [11] [ 710/1319] eta: 0:29:00 lr: 3.680785738964223e-05 loss: 0.0682 (0.0844) time: 2.8815 data: 0.0069 max mem: 33369 +Epoch: [11] [ 720/1319] eta: 0:28:32 lr: 3.679903279909417e-05 loss: 0.0674 (0.0843) time: 2.8801 data: 0.0068 max mem: 33369 +Epoch: [11] [ 730/1319] eta: 0:28:03 lr: 3.679020797340866e-05 loss: 0.0753 (0.0843) time: 2.8988 data: 0.0069 max mem: 33369 +Epoch: [11] [ 740/1319] eta: 0:27:35 lr: 3.678138291251678e-05 loss: 0.0753 (0.0843) time: 2.8883 data: 0.0075 max mem: 33369 +Epoch: [11] [ 750/1319] eta: 0:27:06 lr: 3.677255761634953e-05 loss: 0.0652 (0.0842) time: 2.8388 data: 0.0072 max mem: 33369 +Epoch: [11] [ 760/1319] eta: 0:26:38 lr: 3.6763732084837915e-05 loss: 0.0627 (0.0841) time: 2.8646 data: 0.0074 max mem: 33369 +Epoch: [11] [ 770/1319] eta: 0:26:09 lr: 3.675490631791288e-05 loss: 0.0729 (0.0842) time: 2.8679 data: 0.0081 max mem: 33369 +Epoch: 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max mem: 33369 +Epoch: [11] [ 860/1319] eta: 0:21:52 lr: 3.667546381057031e-05 loss: 0.0720 (0.0840) time: 2.9034 data: 0.0068 max mem: 33369 +Epoch: [11] [ 870/1319] eta: 0:21:24 lr: 3.666663568570454e-05 loss: 0.0769 (0.0839) time: 2.8674 data: 0.0074 max mem: 33369 +Epoch: [11] [ 880/1319] eta: 0:20:55 lr: 3.665780732466318e-05 loss: 0.0659 (0.0837) time: 2.8482 data: 0.0077 max mem: 33369 +Epoch: [11] [ 890/1319] eta: 0:20:26 lr: 3.6648978727376724e-05 loss: 0.0659 (0.0836) time: 2.8325 data: 0.0072 max mem: 33369 +Epoch: [11] [ 900/1319] eta: 0:19:57 lr: 3.664014989377562e-05 loss: 0.0734 (0.0836) time: 2.7831 data: 0.0068 max mem: 33369 +Epoch: [11] [ 910/1319] eta: 0:19:29 lr: 3.663132082379026e-05 loss: 0.0711 (0.0835) time: 2.8609 data: 0.0068 max mem: 33369 +Epoch: [11] [ 920/1319] eta: 0:19:00 lr: 3.6622491517351006e-05 loss: 0.0724 (0.0837) time: 2.9100 data: 0.0069 max mem: 33369 +Epoch: [11] [ 930/1319] eta: 0:18:32 lr: 3.661366197438818e-05 loss: 0.0744 (0.0836) time: 2.9001 data: 0.0069 max mem: 33369 +Epoch: [11] [ 940/1319] eta: 0:18:04 lr: 3.660483219483207e-05 loss: 0.0744 (0.0836) time: 2.8911 data: 0.0076 max mem: 33369 +Epoch: [11] [ 950/1319] eta: 0:17:35 lr: 3.659600217861292e-05 loss: 0.0738 (0.0835) time: 2.8469 data: 0.0077 max mem: 33369 +Epoch: [11] [ 960/1319] eta: 0:17:07 lr: 3.658717192566094e-05 loss: 0.0691 (0.0834) time: 2.8869 data: 0.0071 max mem: 33369 +Epoch: [11] [ 970/1319] eta: 0:16:38 lr: 3.6578341435906296e-05 loss: 0.0636 (0.0833) time: 2.8565 data: 0.0068 max mem: 33369 +Epoch: [11] [ 980/1319] eta: 0:16:09 lr: 3.656951070927911e-05 loss: 0.0688 (0.0832) time: 2.8476 data: 0.0070 max mem: 33369 +Epoch: [11] [ 990/1319] eta: 0:15:41 lr: 3.656067974570946e-05 loss: 0.0638 (0.0831) time: 2.8877 data: 0.0074 max mem: 33369 +Epoch: [11] [1000/1319] eta: 0:15:12 lr: 3.655184854512743e-05 loss: 0.0653 (0.0831) time: 2.8583 data: 0.0072 max mem: 33369 +Epoch: [11] [1010/1319] eta: 0:14:43 lr: 3.654301710746299e-05 loss: 0.0805 (0.0832) time: 2.8580 data: 0.0070 max mem: 33369 +Epoch: [11] [1020/1319] eta: 0:14:15 lr: 3.653418543264612e-05 loss: 0.0716 (0.0830) time: 2.8754 data: 0.0069 max mem: 33369 +Epoch: [11] [1030/1319] eta: 0:13:46 lr: 3.652535352060675e-05 loss: 0.0704 (0.0831) time: 2.8378 data: 0.0074 max mem: 33369 +Epoch: [11] [1040/1319] eta: 0:13:17 lr: 3.651652137127478e-05 loss: 0.0722 (0.0829) time: 2.8082 data: 0.0080 max mem: 33369 +Epoch: [11] [1050/1319] eta: 0:12:49 lr: 3.6507688984580056e-05 loss: 0.0728 (0.0831) time: 2.8049 data: 0.0076 max mem: 33369 +Epoch: [11] [1060/1319] eta: 0:12:20 lr: 3.649885636045239e-05 loss: 0.0743 (0.0831) time: 2.8809 data: 0.0075 max mem: 33369 +Epoch: [11] [1070/1319] eta: 0:11:52 lr: 3.6490023498821546e-05 loss: 0.0683 (0.0829) time: 2.9086 data: 0.0075 max mem: 33369 +Epoch: [11] [1080/1319] eta: 0:11:23 lr: 3.648119039961727e-05 loss: 0.0637 (0.0828) time: 2.8537 data: 0.0072 max mem: 33369 +Epoch: [11] [1090/1319] eta: 0:10:54 lr: 3.647235706276924e-05 loss: 0.0793 (0.0829) time: 2.8385 data: 0.0076 max mem: 33369 +Epoch: [11] [1100/1319] eta: 0:10:26 lr: 3.646352348820711e-05 loss: 0.0646 (0.0829) time: 2.8251 data: 0.0076 max mem: 33369 +Epoch: [11] [1110/1319] eta: 0:09:57 lr: 3.6454689675860496e-05 loss: 0.0650 (0.0830) time: 2.8299 data: 0.0073 max mem: 33369 +Epoch: [11] [1120/1319] eta: 0:09:28 lr: 3.6445855625658975e-05 loss: 0.0907 (0.0833) time: 2.7982 data: 0.0074 max mem: 33369 +Epoch: [11] [1130/1319] eta: 0:09:00 lr: 3.643702133753208e-05 loss: 0.0866 (0.0833) time: 2.8572 data: 0.0072 max mem: 33369 +Epoch: [11] [1140/1319] eta: 0:08:31 lr: 3.6428186811409296e-05 loss: 0.0774 (0.0834) time: 2.9086 data: 0.0072 max mem: 33369 +Epoch: [11] [1150/1319] eta: 0:08:03 lr: 3.641935204722008e-05 loss: 0.0948 (0.0835) time: 2.8820 data: 0.0076 max mem: 33369 +Epoch: [11] [1160/1319] eta: 0:07:34 lr: 3.6410517044893844e-05 loss: 0.0881 (0.0835) time: 2.8999 data: 0.0072 max mem: 33369 +Epoch: [11] [1170/1319] eta: 0:07:06 lr: 3.6401681804359965e-05 loss: 0.0762 (0.0836) time: 2.8892 data: 0.0069 max mem: 33369 +Epoch: [11] [1180/1319] eta: 0:06:37 lr: 3.6392846325547776e-05 loss: 0.0786 (0.0836) time: 2.8674 data: 0.0070 max mem: 33369 +Epoch: [11] [1190/1319] eta: 0:06:08 lr: 3.638401060838657e-05 loss: 0.0872 (0.0838) time: 2.8708 data: 0.0070 max mem: 33369 +Epoch: [11] [1200/1319] eta: 0:05:40 lr: 3.63751746528056e-05 loss: 0.0730 (0.0837) time: 2.8373 data: 0.0070 max mem: 33369 +Epoch: [11] [1210/1319] eta: 0:05:11 lr: 3.636633845873407e-05 loss: 0.0793 (0.0839) time: 2.8496 data: 0.0074 max mem: 33369 +Epoch: [11] [1220/1319] eta: 0:04:43 lr: 3.6357502026101176e-05 loss: 0.0949 (0.0840) time: 2.8879 data: 0.0077 max mem: 33369 +Epoch: [11] [1230/1319] eta: 0:04:14 lr: 3.6348665354836024e-05 loss: 0.0827 (0.0839) time: 2.8540 data: 0.0071 max mem: 33369 +Epoch: [11] [1240/1319] eta: 0:03:45 lr: 3.6339828444867725e-05 loss: 0.0729 (0.0838) time: 2.8619 data: 0.0069 max mem: 33369 +Epoch: [11] [1250/1319] eta: 0:03:17 lr: 3.6330991296125324e-05 loss: 0.0667 (0.0838) time: 2.8833 data: 0.0068 max mem: 33369 +Epoch: [11] [1260/1319] eta: 0:02:48 lr: 3.632215390853783e-05 loss: 0.0667 (0.0836) time: 2.8842 data: 0.0068 max mem: 33369 +Epoch: [11] [1270/1319] eta: 0:02:20 lr: 3.631331628203422e-05 loss: 0.0741 (0.0837) time: 2.8840 data: 0.0067 max mem: 33369 +Epoch: [11] [1280/1319] eta: 0:01:51 lr: 3.630447841654343e-05 loss: 0.0831 (0.0837) time: 2.8858 data: 0.0068 max mem: 33369 +Epoch: [11] [1290/1319] eta: 0:01:22 lr: 3.629564031199434e-05 loss: 0.0831 (0.0838) time: 2.8786 data: 0.0074 max mem: 33369 +Epoch: [11] [1300/1319] eta: 0:00:54 lr: 3.6286801968315816e-05 loss: 0.0941 (0.0838) time: 2.8302 data: 0.0077 max mem: 33369 +Epoch: [11] [1310/1319] eta: 0:00:25 lr: 3.627796338543665e-05 loss: 0.0850 (0.0838) time: 2.8341 data: 0.0075 max mem: 33369 +Epoch: [11] Total time: 1:02:53 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 2:36:29 time: 3.6491 data: 3.5684 max mem: 33369 +Test: [ 100/2573] eta: 0:04:28 time: 0.0729 data: 0.0012 max mem: 33369 +Test: [ 200/2573] eta: 0:03:38 time: 0.0744 data: 0.0012 max mem: 33369 +Test: [ 300/2573] eta: 0:03:14 time: 0.0757 data: 0.0012 max mem: 33369 +Test: [ 400/2573] eta: 0:02:59 time: 0.0760 data: 0.0012 max mem: 33369 +Test: [ 500/2573] eta: 0:02:48 time: 0.0743 data: 0.0012 max mem: 33369 +Test: [ 600/2573] eta: 0:02:38 time: 0.0747 data: 0.0013 max mem: 33369 +Test: [ 700/2573] eta: 0:02:29 time: 0.0746 data: 0.0012 max mem: 33369 +Test: [ 800/2573] eta: 0:02:20 time: 0.0781 data: 0.0012 max mem: 33369 +Test: [ 900/2573] eta: 0:02:11 time: 0.0740 data: 0.0011 max mem: 33369 +Test: [1000/2573] eta: 0:02:03 time: 0.0742 data: 0.0012 max mem: 33369 +Test: [1100/2573] eta: 0:01:54 time: 0.0741 data: 0.0012 max mem: 33369 +Test: [1200/2573] eta: 0:01:46 time: 0.0741 data: 0.0011 max mem: 33369 +Test: [1300/2573] eta: 0:01:38 time: 0.0764 data: 0.0015 max mem: 33369 +Test: [1400/2573] eta: 0:01:30 time: 0.0731 data: 0.0013 max mem: 33369 +Test: [1500/2573] eta: 0:01:22 time: 0.0749 data: 0.0013 max mem: 33369 +Test: [1600/2573] eta: 0:01:14 time: 0.0784 data: 0.0013 max mem: 33369 +Test: [1700/2573] eta: 0:01:07 time: 0.0732 data: 0.0012 max mem: 33369 +Test: [1800/2573] eta: 0:00:59 time: 0.0768 data: 0.0013 max mem: 33369 +Test: [1900/2573] eta: 0:00:51 time: 0.0733 data: 0.0013 max mem: 33369 +Test: [2000/2573] eta: 0:00:43 time: 0.0754 data: 0.0013 max mem: 33369 +Test: [2100/2573] eta: 0:00:36 time: 0.0767 data: 0.0012 max mem: 33369 +Test: [2200/2573] eta: 0:00:28 time: 0.0767 data: 0.0012 max mem: 33369 +Test: [2300/2573] eta: 0:00:20 time: 0.0767 data: 0.0012 max mem: 33369 +Test: [2400/2573] eta: 0:00:13 time: 0.0716 data: 0.0012 max mem: 33369 +Test: [2500/2573] eta: 0:00:05 time: 0.0749 data: 0.0013 max mem: 33369 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: Total time: 0:03:16 +Final results: +Mean IoU is 60.92 + + precision@0.5 = 68.44 + precision@0.6 = 62.93 + precision@0.7 = 54.74 + precision@0.8 = 41.95 + precision@0.9 = 19.59 + overall IoU = 59.98 + +Average object IoU 60.919401040122715 +Overall IoU 59.976219177246094 +Better epoch: 11 + +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [12] [ 0/1319] eta: 1:34:08 lr: 3.6270008456269996e-05 loss: 0.0733 (0.0733) time: 4.2824 data: 1.3452 max mem: 33369 +Epoch: [12] [ 10/1319] eta: 1:06:01 lr: 3.6261169418713356e-05 loss: 0.0560 (0.0635) time: 3.0262 data: 0.1289 max mem: 33369 +Epoch: [12] [ 20/1319] eta: 1:03:52 lr: 3.62523301417494e-05 loss: 0.0640 (0.0740) time: 2.8835 data: 0.0074 max mem: 33369 +Epoch: [12] [ 30/1319] eta: 1:02:14 lr: 3.624349062530679e-05 loss: 0.0679 (0.0740) time: 2.8259 data: 0.0075 max mem: 33369 +Epoch: [12] [ 40/1319] eta: 1:01:56 lr: 3.623465086931413e-05 loss: 0.0662 (0.0733) time: 2.8594 data: 0.0074 max mem: 33369 +Epoch: [12] [ 50/1319] eta: 1:01:11 lr: 3.62258108737e-05 loss: 0.0641 (0.0742) time: 2.8865 data: 0.0076 max mem: 33369 +Epoch: [12] [ 60/1319] eta: 1:00:40 lr: 3.621697063839292e-05 loss: 0.0670 (0.0756) time: 2.8629 data: 0.0078 max mem: 33369 +Epoch: [12] [ 70/1319] eta: 1:00:21 lr: 3.6208130163321375e-05 loss: 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3.613739772263389e-05 loss: 0.0719 (0.0748) time: 2.8373 data: 0.0076 max mem: 33369 +Epoch: [12] [ 160/1319] eta: 0:55:40 lr: 3.6128555086457536e-05 loss: 0.0605 (0.0739) time: 2.8539 data: 0.0074 max mem: 33369 +Epoch: [12] [ 170/1319] eta: 0:55:11 lr: 3.6119712209799373e-05 loss: 0.0612 (0.0750) time: 2.8669 data: 0.0072 max mem: 33369 +Epoch: [12] [ 180/1319] eta: 0:54:34 lr: 3.6110869092587446e-05 loss: 0.0747 (0.0752) time: 2.8145 data: 0.0069 max mem: 33369 +Epoch: [12] [ 190/1319] eta: 0:54:13 lr: 3.610202573474975e-05 loss: 0.0674 (0.0748) time: 2.8774 data: 0.0068 max mem: 33369 +Epoch: [12] [ 200/1319] eta: 0:53:44 lr: 3.609318213621424e-05 loss: 0.0638 (0.0744) time: 2.9387 data: 0.0068 max mem: 33369 +Epoch: [12] [ 210/1319] eta: 0:53:15 lr: 3.608433829690883e-05 loss: 0.0700 (0.0753) time: 2.8827 data: 0.0069 max mem: 33369 +Epoch: [12] [ 220/1319] eta: 0:52:49 lr: 3.607549421676141e-05 loss: 0.0702 (0.0755) time: 2.9106 data: 0.0071 max mem: 33369 +Epoch: [12] [ 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data: 0.0068 max mem: 33369 +Epoch: [12] [ 390/1319] eta: 0:44:02 lr: 3.5925107935336354e-05 loss: 0.0685 (0.0779) time: 2.6436 data: 0.0068 max mem: 33369 +Epoch: [12] [ 400/1319] eta: 0:43:30 lr: 3.5916259507651966e-05 loss: 0.0641 (0.0777) time: 2.6528 data: 0.0067 max mem: 33369 +Epoch: [12] [ 410/1319] eta: 0:42:57 lr: 3.59074108377473e-05 loss: 0.0528 (0.0773) time: 2.6469 data: 0.0065 max mem: 33369 +Epoch: [12] [ 420/1319] eta: 0:42:27 lr: 3.58985619255494e-05 loss: 0.0528 (0.0773) time: 2.7055 data: 0.0066 max mem: 33369 +Epoch: [12] [ 430/1319] eta: 0:41:58 lr: 3.588971277098527e-05 loss: 0.0699 (0.0773) time: 2.7772 data: 0.0071 max mem: 33369 +Epoch: [12] [ 440/1319] eta: 0:41:26 lr: 3.588086337398186e-05 loss: 0.0690 (0.0773) time: 2.7281 data: 0.0068 max mem: 33369 +Epoch: [12] [ 450/1319] eta: 0:40:55 lr: 3.58720137344661e-05 loss: 0.0605 (0.0774) time: 2.6708 data: 0.0063 max mem: 33369 +Epoch: [12] [ 460/1319] eta: 0:40:28 lr: 3.5863163852364855e-05 loss: 0.0679 (0.0773) time: 2.7904 data: 0.0066 max mem: 33369 +Epoch: [12] [ 470/1319] eta: 0:40:01 lr: 3.585431372760496e-05 loss: 0.0679 (0.0771) time: 2.8962 data: 0.0071 max mem: 33369 +Epoch: [12] [ 480/1319] eta: 0:39:33 lr: 3.5845463360113225e-05 loss: 0.0629 (0.0770) time: 2.8662 data: 0.0074 max mem: 33369 +Epoch: [12] [ 490/1319] eta: 0:39:06 lr: 3.583661274981637e-05 loss: 0.0641 (0.0769) time: 2.8699 data: 0.0070 max mem: 33369 +Epoch: [12] [ 500/1319] eta: 0:38:38 lr: 3.582776189664111e-05 loss: 0.0769 (0.0770) time: 2.8736 data: 0.0066 max mem: 33369 +Epoch: [12] [ 510/1319] eta: 0:38:10 lr: 3.581891080051412e-05 loss: 0.0722 (0.0769) time: 2.8646 data: 0.0067 max mem: 33369 +Epoch: [12] [ 520/1319] eta: 0:37:42 lr: 3.5810059461362006e-05 loss: 0.0665 (0.0768) time: 2.8658 data: 0.0067 max mem: 33369 +Epoch: [12] [ 530/1319] eta: 0:37:14 lr: 3.580120787911136e-05 loss: 0.0665 (0.0767) time: 2.8391 data: 0.0068 max mem: 33369 +Epoch: [12] [ 540/1319] eta: 0:36:47 lr: 3.579235605368871e-05 loss: 0.0762 (0.0771) time: 2.8641 data: 0.0068 max mem: 33369 +Epoch: [12] [ 550/1319] eta: 0:36:18 lr: 3.578350398502055e-05 loss: 0.0883 (0.0772) time: 2.8596 data: 0.0068 max mem: 33369 +Epoch: [12] [ 560/1319] eta: 0:35:50 lr: 3.5774651673033346e-05 loss: 0.0689 (0.0771) time: 2.8345 data: 0.0068 max mem: 33369 +Epoch: [12] [ 570/1319] eta: 0:35:22 lr: 3.57657991176535e-05 loss: 0.0637 (0.0773) time: 2.8652 data: 0.0067 max mem: 33369 +Epoch: [12] [ 580/1319] eta: 0:34:55 lr: 3.5756946318807374e-05 loss: 0.0642 (0.0775) time: 2.8960 data: 0.0069 max mem: 33369 +Epoch: [12] [ 590/1319] eta: 0:34:27 lr: 3.5748093276421306e-05 loss: 0.0868 (0.0781) time: 2.8990 data: 0.0069 max mem: 33369 +Epoch: [12] [ 600/1319] eta: 0:33:58 lr: 3.573923999042157e-05 loss: 0.0772 (0.0781) time: 2.8479 data: 0.0067 max mem: 33369 +Epoch: [12] [ 610/1319] eta: 0:33:31 lr: 3.573038646073439e-05 loss: 0.0762 (0.0783) time: 2.8590 data: 0.0071 max mem: 33369 +Epoch: [12] [ 620/1319] eta: 0:33:02 lr: 3.5721532687286004e-05 loss: 0.0718 (0.0783) time: 2.8645 data: 0.0072 max mem: 33369 +Epoch: [12] [ 630/1319] eta: 0:32:34 lr: 3.571267867000252e-05 loss: 0.0640 (0.0782) time: 2.8300 data: 0.0074 max mem: 33369 +Epoch: [12] [ 640/1319] eta: 0:32:06 lr: 3.570382440881008e-05 loss: 0.0646 (0.0781) time: 2.8418 data: 0.0075 max mem: 33369 +Epoch: [12] [ 650/1319] eta: 0:31:37 lr: 3.5694969903634736e-05 loss: 0.0700 (0.0782) time: 2.8320 data: 0.0075 max mem: 33369 +Epoch: [12] [ 660/1319] eta: 0:31:09 lr: 3.568611515440253e-05 loss: 0.0670 (0.0781) time: 2.8347 data: 0.0078 max mem: 33369 +Epoch: [12] [ 670/1319] eta: 0:30:40 lr: 3.567726016103943e-05 loss: 0.0663 (0.0781) time: 2.8388 data: 0.0076 max mem: 33369 +Epoch: [12] [ 680/1319] eta: 0:30:11 lr: 3.5668404923471386e-05 loss: 0.0633 (0.0780) time: 2.7821 data: 0.0070 max mem: 33369 +Epoch: [12] [ 690/1319] eta: 0:29:44 lr: 3.565954944162429e-05 loss: 0.0653 (0.0782) time: 2.8305 data: 0.0072 max mem: 33369 +Epoch: [12] [ 700/1319] eta: 0:29:16 lr: 3.5650693715424005e-05 loss: 0.0692 (0.0781) time: 2.8967 data: 0.0076 max mem: 33369 +Epoch: [12] [ 710/1319] eta: 0:28:48 lr: 3.564183774479633e-05 loss: 0.0649 (0.0779) time: 2.8958 data: 0.0074 max mem: 33369 +Epoch: [12] [ 720/1319] eta: 0:28:20 lr: 3.563298152966704e-05 loss: 0.0591 (0.0778) time: 2.8921 data: 0.0070 max mem: 33369 +Epoch: [12] [ 730/1319] eta: 0:27:52 lr: 3.562412506996187e-05 loss: 0.0609 (0.0779) time: 2.8901 data: 0.0071 max mem: 33369 +Epoch: [12] [ 740/1319] eta: 0:27:24 lr: 3.561526836560649e-05 loss: 0.0799 (0.0779) time: 2.8896 data: 0.0074 max mem: 33369 +Epoch: [12] [ 750/1319] eta: 0:26:55 lr: 3.560641141652653e-05 loss: 0.0638 (0.0778) time: 2.8513 data: 0.0072 max mem: 33369 +Epoch: [12] [ 760/1319] eta: 0:26:27 lr: 3.5597554222647605e-05 loss: 0.0591 (0.0778) time: 2.8577 data: 0.0071 max mem: 33369 +Epoch: [12] [ 770/1319] eta: 0:25:59 lr: 3.558869678389526e-05 loss: 0.0712 (0.0779) time: 2.8889 data: 0.0071 max mem: 33369 +Epoch: [12] [ 780/1319] eta: 0:25:31 lr: 3.5579839100195013e-05 loss: 0.0712 (0.0778) time: 2.8861 data: 0.0073 max mem: 33369 +Epoch: [12] [ 790/1319] eta: 0:25:03 lr: 3.5570981171472317e-05 loss: 0.0825 (0.0780) time: 2.8688 data: 0.0077 max mem: 33369 +Epoch: [12] [ 800/1319] eta: 0:24:34 lr: 3.55621229976526e-05 loss: 0.0885 (0.0782) time: 2.8510 data: 0.0078 max mem: 33369 +Epoch: [12] [ 810/1319] eta: 0:24:06 lr: 3.555326457866125e-05 loss: 0.0845 (0.0782) time: 2.8233 data: 0.0082 max mem: 33369 +Epoch: [12] [ 820/1319] eta: 0:23:37 lr: 3.554440591442359e-05 loss: 0.0700 (0.0783) time: 2.8345 data: 0.0081 max mem: 33369 +Epoch: [12] [ 830/1319] eta: 0:23:08 lr: 3.5535547004864924e-05 loss: 0.0728 (0.0782) time: 2.7921 data: 0.0072 max mem: 33369 +Epoch: [12] [ 840/1319] eta: 0:22:40 lr: 3.552668784991049e-05 loss: 0.0681 (0.0782) time: 2.8192 data: 0.0071 max mem: 33369 +Epoch: [12] [ 850/1319] eta: 0:22:12 lr: 3.551782844948551e-05 loss: 0.0618 (0.0781) time: 2.8835 data: 0.0072 max mem: 33369 +Epoch: [12] [ 860/1319] eta: 0:21:44 lr: 3.550896880351513e-05 loss: 0.0618 (0.0780) time: 2.8569 data: 0.0070 max mem: 33369 +Epoch: [12] [ 870/1319] eta: 0:21:15 lr: 3.550010891192448e-05 loss: 0.0709 (0.0780) time: 2.8400 data: 0.0075 max mem: 33369 +Epoch: [12] [ 880/1319] eta: 0:20:47 lr: 3.549124877463863e-05 loss: 0.0736 (0.0780) time: 2.8360 data: 0.0076 max mem: 33369 +Epoch: [12] [ 890/1319] eta: 0:20:18 lr: 3.548238839158261e-05 loss: 0.0647 (0.0779) time: 2.8255 data: 0.0075 max mem: 33369 +Epoch: [12] [ 900/1319] eta: 0:19:50 lr: 3.5473527762681414e-05 loss: 0.0655 (0.0781) time: 2.8101 data: 0.0077 max mem: 33369 +Epoch: [12] [ 910/1319] eta: 0:19:22 lr: 3.546466688785999e-05 loss: 0.0714 (0.0781) time: 2.8643 data: 0.0073 max mem: 33369 +Epoch: [12] [ 920/1319] eta: 0:18:53 lr: 3.545580576704322e-05 loss: 0.0693 (0.0780) time: 2.8847 data: 0.0075 max mem: 33369 +Epoch: [12] [ 930/1319] eta: 0:18:25 lr: 3.544694440015598e-05 loss: 0.0693 (0.0781) time: 2.8705 data: 0.0074 max mem: 33369 +Epoch: [12] [ 940/1319] eta: 0:17:57 lr: 3.543808278712307e-05 loss: 0.0735 (0.0782) time: 2.8780 data: 0.0067 max mem: 33369 +Epoch: [12] [ 950/1319] eta: 0:17:28 lr: 3.542922092786927e-05 loss: 0.0797 (0.0783) time: 2.8646 data: 0.0071 max mem: 33369 +Epoch: [12] [ 960/1319] eta: 0:17:00 lr: 3.542035882231929e-05 loss: 0.0797 (0.0784) time: 2.8314 data: 0.0072 max mem: 33369 +Epoch: [12] [ 970/1319] eta: 0:16:32 lr: 3.541149647039783e-05 loss: 0.0741 (0.0784) time: 2.8438 data: 0.0071 max mem: 33369 +Epoch: [12] [ 980/1319] eta: 0:16:03 lr: 3.540263387202951e-05 loss: 0.0741 (0.0785) time: 2.8361 data: 0.0072 max mem: 33369 +Epoch: [12] [ 990/1319] eta: 0:15:35 lr: 3.5393771027138936e-05 loss: 0.0731 (0.0787) time: 2.8486 data: 0.0073 max mem: 33369 +Epoch: [12] [1000/1319] eta: 0:15:06 lr: 3.5384907935650645e-05 loss: 0.0692 (0.0786) time: 2.8643 data: 0.0076 max mem: 33369 +Epoch: [12] [1010/1319] eta: 0:14:38 lr: 3.5376044597489155e-05 loss: 0.0623 (0.0787) time: 2.8265 data: 0.0076 max mem: 33369 +Epoch: [12] [1020/1319] eta: 0:14:09 lr: 3.536718101257892e-05 loss: 0.0714 (0.0788) time: 2.8601 data: 0.0073 max mem: 33369 +Epoch: [12] [1030/1319] eta: 0:13:41 lr: 3.5358317180844356e-05 loss: 0.0815 (0.0790) time: 2.8987 data: 0.0070 max mem: 33369 +Epoch: [12] [1040/1319] eta: 0:13:13 lr: 3.5349453102209835e-05 loss: 0.0644 (0.0788) time: 2.9043 data: 0.0071 max mem: 33369 +Epoch: [12] [1050/1319] eta: 0:12:44 lr: 3.534058877659969e-05 loss: 0.0623 (0.0788) time: 2.8661 data: 0.0075 max mem: 33369 +Epoch: [12] [1060/1319] eta: 0:12:16 lr: 3.5331724203938196e-05 loss: 0.0664 (0.0788) time: 2.8237 data: 0.0073 max mem: 33369 +Epoch: [12] [1070/1319] eta: 0:11:48 lr: 3.53228593841496e-05 loss: 0.0641 (0.0787) time: 2.8609 data: 0.0072 max mem: 33369 +Epoch: [12] [1080/1319] eta: 0:11:19 lr: 3.53139943171581e-05 loss: 0.0682 (0.0788) time: 2.8785 data: 0.0072 max mem: 33369 +Epoch: [12] [1090/1319] eta: 0:10:51 lr: 3.5305129002887835e-05 loss: 0.0698 (0.0788) time: 2.8455 data: 0.0071 max mem: 33369 +Epoch: [12] [1100/1319] eta: 0:10:23 lr: 3.529626344126292e-05 loss: 0.0698 (0.0788) time: 2.8837 data: 0.0071 max mem: 33369 +Epoch: [12] [1110/1319] eta: 0:09:54 lr: 3.5287397632207417e-05 loss: 0.0768 (0.0791) time: 2.9011 data: 0.0072 max mem: 33369 +Epoch: [12] [1120/1319] eta: 0:09:26 lr: 3.527853157564535e-05 loss: 0.0841 (0.0791) time: 2.8732 data: 0.0076 max mem: 33369 +Epoch: [12] [1130/1319] eta: 0:08:57 lr: 3.526966527150067e-05 loss: 0.0713 (0.0793) time: 2.8612 data: 0.0071 max mem: 33369 +Epoch: [12] [1140/1319] eta: 0:08:29 lr: 3.5260798719697326e-05 loss: 0.0737 (0.0794) time: 2.8529 data: 0.0071 max mem: 33369 +Epoch: [12] [1150/1319] eta: 0:08:00 lr: 3.52519319201592e-05 loss: 0.0737 (0.0793) time: 2.8816 data: 0.0074 max mem: 33369 +Epoch: [12] [1160/1319] eta: 0:07:32 lr: 3.524306487281011e-05 loss: 0.0648 (0.0792) time: 2.8638 data: 0.0074 max mem: 33369 +Epoch: [12] [1170/1319] eta: 0:07:04 lr: 3.523419757757387e-05 loss: 0.0527 (0.0791) time: 2.8471 data: 0.0076 max mem: 33369 +Epoch: [12] [1180/1319] eta: 0:06:35 lr: 3.5225330034374235e-05 loss: 0.0592 (0.0791) time: 2.8644 data: 0.0076 max mem: 33369 +Epoch: [12] [1190/1319] eta: 0:06:07 lr: 3.5216462243134885e-05 loss: 0.0651 (0.0790) time: 2.8456 data: 0.0077 max mem: 33369 +Epoch: [12] [1200/1319] eta: 0:05:38 lr: 3.52075942037795e-05 loss: 0.0583 (0.0790) time: 2.8671 data: 0.0073 max mem: 33369 +Epoch: [12] [1210/1319] eta: 0:05:10 lr: 3.519872591623169e-05 loss: 0.0602 (0.0788) time: 2.8880 data: 0.0069 max mem: 33369 +Epoch: [12] [1220/1319] eta: 0:04:41 lr: 3.518985738041502e-05 loss: 0.0693 (0.0789) time: 2.8896 data: 0.0075 max mem: 33369 +Epoch: [12] [1230/1319] eta: 0:04:13 lr: 3.518098859625303e-05 loss: 0.0703 (0.0789) time: 2.9042 data: 0.0076 max mem: 33369 +Epoch: [12] [1240/1319] eta: 0:03:45 lr: 3.517211956366918e-05 loss: 0.0621 (0.0789) time: 2.9023 data: 0.0069 max mem: 33369 +Epoch: [12] [1250/1319] eta: 0:03:16 lr: 3.5163250282586914e-05 loss: 0.0621 (0.0789) time: 2.9104 data: 0.0070 max mem: 33369 +Epoch: [12] [1260/1319] eta: 0:02:48 lr: 3.515438075292963e-05 loss: 0.0633 (0.0788) time: 2.9023 data: 0.0072 max mem: 33369 +Epoch: [12] [1270/1319] eta: 0:02:19 lr: 3.514551097462066e-05 loss: 0.0760 (0.0788) time: 2.8610 data: 0.0071 max mem: 33369 +Epoch: [12] [1280/1319] eta: 0:01:51 lr: 3.513664094758331e-05 loss: 0.0800 (0.0789) time: 2.8261 data: 0.0070 max mem: 33369 +Epoch: [12] [1290/1319] eta: 0:01:22 lr: 3.512777067174083e-05 loss: 0.0751 (0.0788) time: 2.8673 data: 0.0071 max mem: 33369 +Epoch: [12] [1300/1319] eta: 0:00:54 lr: 3.511890014701643e-05 loss: 0.0644 (0.0787) time: 2.8842 data: 0.0075 max mem: 33369 +Epoch: [12] [1310/1319] eta: 0:00:25 lr: 3.511002937333328e-05 loss: 0.0667 (0.0788) time: 2.8731 data: 0.0074 max mem: 33369 +Epoch: [12] Total time: 1:02:38 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 2:11:01 time: 3.0555 data: 2.9748 max mem: 33369 +Test: [ 100/2573] eta: 0:04:13 time: 0.0728 data: 0.0012 max mem: 33369 +Test: [ 200/2573] eta: 0:03:31 time: 0.0743 data: 0.0013 max mem: 33369 +Test: [ 300/2573] eta: 0:03:10 time: 0.0757 data: 0.0012 max mem: 33369 +Test: [ 400/2573] eta: 0:02:56 time: 0.0757 data: 0.0012 max mem: 33369 +Test: [ 500/2573] eta: 0:02:45 time: 0.0746 data: 0.0012 max mem: 33369 +Test: [ 600/2573] eta: 0:02:35 time: 0.0746 data: 0.0012 max mem: 33369 +Test: [ 700/2573] eta: 0:02:27 time: 0.0746 data: 0.0012 max mem: 33369 +Test: [ 800/2573] eta: 0:02:18 time: 0.0779 data: 0.0012 max mem: 33369 +Test: [ 900/2573] eta: 0:02:10 time: 0.0745 data: 0.0012 max mem: 33369 +Test: [1000/2573] eta: 0:02:02 time: 0.0748 data: 0.0013 max mem: 33369 +Test: [1100/2573] eta: 0:01:54 time: 0.0745 data: 0.0012 max mem: 33369 +Test: [1200/2573] eta: 0:01:46 time: 0.0739 data: 0.0011 max mem: 33369 +Test: [1300/2573] eta: 0:01:38 time: 0.0739 data: 0.0011 max mem: 33369 +Test: [1400/2573] eta: 0:01:30 time: 0.0723 data: 0.0011 max mem: 33369 +Test: [1500/2573] eta: 0:01:22 time: 0.0741 data: 0.0012 max mem: 33369 +Test: [1600/2573] eta: 0:01:14 time: 0.0788 data: 0.0014 max mem: 33369 +Test: [1700/2573] eta: 0:01:06 time: 0.0733 data: 0.0012 max mem: 33369 +Test: [1800/2573] eta: 0:00:59 time: 0.0769 data: 0.0013 max mem: 33369 +Test: [1900/2573] eta: 0:00:51 time: 0.0734 data: 0.0012 max mem: 33369 +Test: [2000/2573] eta: 0:00:43 time: 0.0748 data: 0.0012 max mem: 33369 +Test: [2100/2573] eta: 0:00:35 time: 0.0765 data: 0.0012 max mem: 33369 +Test: [2200/2573] eta: 0:00:28 time: 0.0768 data: 0.0012 max mem: 33369 +Test: [2300/2573] eta: 0:00:20 time: 0.0765 data: 0.0012 max mem: 33369 +Test: [2400/2573] eta: 0:00:13 time: 0.0717 data: 0.0012 max mem: 33369 +Test: [2500/2573] eta: 0:00:05 time: 0.0750 data: 0.0013 max mem: 33369 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: Total time: 0:03:15 +Final results: +Mean IoU is 61.02 + + precision@0.5 = 67.99 + precision@0.6 = 62.36 + precision@0.7 = 54.33 + precision@0.8 = 43.20 + precision@0.9 = 20.63 + overall IoU = 60.19 + +Average object IoU 61.023421088369986 +Overall IoU 60.192020416259766 +Better epoch: 12 + +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [13] [ 0/1319] eta: 1:39:53 lr: 3.510204546409517e-05 loss: 0.0821 (0.0821) time: 4.5443 data: 1.3647 max mem: 33369 +Epoch: [13] [ 10/1319] eta: 1:05:36 lr: 3.509317421717855e-05 loss: 0.0821 (0.0755) time: 3.0074 data: 0.1309 max mem: 33369 +Epoch: [13] [ 20/1319] eta: 1:03:50 lr: 3.50843027210801e-05 loss: 0.0624 (0.0712) time: 2.8688 data: 0.0075 max mem: 33369 +Epoch: [13] [ 30/1319] eta: 1:02:51 lr: 3.5075430975722793e-05 loss: 0.0637 (0.0726) time: 2.8813 data: 0.0073 max mem: 33369 +Epoch: [13] [ 40/1319] eta: 1:01:42 lr: 3.506655898102959e-05 loss: 0.0654 (0.0742) time: 2.8381 data: 0.0069 max mem: 33369 +Epoch: [13] [ 50/1319] eta: 1:01:10 lr: 3.505768673692337e-05 loss: 0.0535 (0.0695) time: 2.8396 data: 0.0071 max mem: 33369 +Epoch: [13] [ 60/1319] eta: 1:00:41 lr: 3.5048814243327e-05 loss: 0.0502 (0.0706) time: 2.8881 data: 0.0071 max mem: 33369 +Epoch: [13] [ 70/1319] eta: 1:00:03 lr: 3.503994150016327e-05 loss: 0.0502 (0.0691) time: 2.8684 data: 0.0068 max mem: 33369 +Epoch: [13] [ 80/1319] eta: 0:59:34 lr: 3.503106850735495e-05 loss: 0.0497 (0.0677) time: 2.8622 data: 0.0067 max mem: 33369 +Epoch: [13] [ 90/1319] eta: 0:59:05 lr: 3.502219526482476e-05 loss: 0.0588 (0.0673) time: 2.8843 data: 0.0071 max mem: 33369 +Epoch: [13] [ 100/1319] eta: 0:58:33 lr: 3.501332177249536e-05 loss: 0.0588 (0.0684) time: 2.8694 data: 0.0073 max mem: 33369 +Epoch: [13] [ 110/1319] eta: 0:57:57 lr: 3.500444803028936e-05 loss: 0.0649 (0.0686) time: 2.8370 data: 0.0073 max mem: 33369 +Epoch: [13] [ 120/1319] eta: 0:57:22 lr: 3.499557403812936e-05 loss: 0.0649 (0.0689) time: 2.8190 data: 0.0072 max mem: 33369 +Epoch: [13] [ 130/1319] eta: 0:56:53 lr: 3.498669979593787e-05 loss: 0.0601 (0.0688) time: 2.8372 data: 0.0070 max mem: 33369 +Epoch: [13] [ 140/1319] eta: 0:56:26 lr: 3.497782530363739e-05 loss: 0.0656 (0.0688) time: 2.8777 data: 0.0068 max mem: 33369 +Epoch: [13] [ 150/1319] eta: 0:55:56 lr: 3.4968950561150356e-05 loss: 0.0595 (0.0679) time: 2.8782 data: 0.0069 max mem: 33369 +Epoch: [13] [ 160/1319] eta: 0:55:29 lr: 3.496007556839915e-05 loss: 0.0603 (0.0699) time: 2.8745 data: 0.0071 max mem: 33369 +Epoch: [13] [ 170/1319] eta: 0:54:59 lr: 3.495120032530614e-05 loss: 0.0617 (0.0692) time: 2.8746 data: 0.0069 max mem: 33369 +Epoch: [13] [ 180/1319] eta: 0:54:31 lr: 3.49423248317936e-05 loss: 0.0576 (0.0698) time: 2.8704 data: 0.0072 max mem: 33369 +Epoch: [13] [ 190/1319] eta: 0:53:56 lr: 3.493344908778381e-05 loss: 0.0671 (0.0701) time: 2.8253 data: 0.0075 max mem: 33369 +Epoch: [13] [ 200/1319] eta: 0:53:27 lr: 3.4924573093198975e-05 loss: 0.0668 (0.0698) time: 2.8097 data: 0.0076 max mem: 33369 +Epoch: [13] [ 210/1319] eta: 0:52:58 lr: 3.491569684796125e-05 loss: 0.0601 (0.0697) time: 2.8545 data: 0.0077 max mem: 33369 +Epoch: [13] [ 220/1319] eta: 0:52:28 lr: 3.490682035199276e-05 loss: 0.0601 (0.0696) time: 2.8473 data: 0.0075 max mem: 33369 +Epoch: [13] [ 230/1319] eta: 0:52:00 lr: 3.4897943605215565e-05 loss: 0.0631 (0.0701) time: 2.8578 data: 0.0073 max mem: 33369 +Epoch: [13] [ 240/1319] eta: 0:51:30 lr: 3.488906660755169e-05 loss: 0.0610 (0.0695) time: 2.8647 data: 0.0073 max mem: 33369 +Epoch: [13] [ 250/1319] eta: 0:51:01 lr: 3.4880189358923125e-05 loss: 0.0486 (0.0692) time: 2.8507 data: 0.0076 max mem: 33369 +Epoch: [13] [ 260/1319] eta: 0:50:33 lr: 3.487131185925179e-05 loss: 0.0615 (0.0693) time: 2.8608 data: 0.0075 max mem: 33369 +Epoch: [13] [ 270/1319] eta: 0:50:00 lr: 3.486243410845958e-05 loss: 0.0552 (0.0692) time: 2.8134 data: 0.0071 max mem: 33369 +Epoch: [13] [ 280/1319] eta: 0:49:36 lr: 3.485355610646832e-05 loss: 0.0603 (0.0697) time: 2.8656 data: 0.0072 max mem: 33369 +Epoch: [13] [ 290/1319] eta: 0:49:07 lr: 3.484467785319982e-05 loss: 0.0583 (0.0693) time: 2.9275 data: 0.0074 max mem: 33369 +Epoch: [13] [ 300/1319] eta: 0:48:40 lr: 3.483579934857581e-05 loss: 0.0583 (0.0695) time: 2.8908 data: 0.0070 max mem: 33369 +Epoch: [13] [ 310/1319] eta: 0:48:10 lr: 3.4826920592518003e-05 loss: 0.0645 (0.0695) time: 2.8690 data: 0.0068 max mem: 33369 +Epoch: [13] [ 320/1319] eta: 0:47:41 lr: 3.481804158494804e-05 loss: 0.0660 (0.0699) time: 2.8452 data: 0.0071 max mem: 33369 +Epoch: [13] [ 330/1319] eta: 0:47:11 lr: 3.4809162325787535e-05 loss: 0.0770 (0.0709) time: 2.8332 data: 0.0077 max mem: 33369 +Epoch: [13] [ 340/1319] eta: 0:46:41 lr: 3.480028281495805e-05 loss: 0.0697 (0.0711) time: 2.8108 data: 0.0076 max mem: 33369 +Epoch: [13] [ 350/1319] eta: 0:46:13 lr: 3.479140305238109e-05 loss: 0.0777 (0.0718) time: 2.8393 data: 0.0070 max mem: 33369 +Epoch: [13] [ 360/1319] eta: 0:45:44 lr: 3.478252303797812e-05 loss: 0.0725 (0.0717) time: 2.8627 data: 0.0068 max mem: 33369 +Epoch: [13] [ 370/1319] eta: 0:45:15 lr: 3.4773642771670566e-05 loss: 0.0585 (0.0720) time: 2.8628 data: 0.0067 max mem: 33369 +Epoch: [13] [ 380/1319] eta: 0:44:46 lr: 3.47647622533798e-05 loss: 0.0497 (0.0716) time: 2.8427 data: 0.0067 max mem: 33369 +Epoch: [13] [ 390/1319] eta: 0:44:17 lr: 3.475588148302715e-05 loss: 0.0537 (0.0714) time: 2.8266 data: 0.0075 max mem: 33369 +Epoch: [13] [ 400/1319] eta: 0:43:48 lr: 3.474700046053388e-05 loss: 0.0605 (0.0714) time: 2.8615 data: 0.0077 max mem: 33369 +Epoch: [13] [ 410/1319] eta: 0:43:20 lr: 3.473811918582123e-05 loss: 0.0612 (0.0714) time: 2.8822 data: 0.0069 max mem: 33369 +Epoch: [13] [ 420/1319] eta: 0:42:49 lr: 3.47292376588104e-05 loss: 0.0610 (0.0713) time: 2.8044 data: 0.0067 max mem: 33369 +Epoch: [13] [ 430/1319] eta: 0:42:22 lr: 3.472035587942251e-05 loss: 0.0696 (0.0716) time: 2.8377 data: 0.0068 max mem: 33369 +Epoch: [13] [ 440/1319] eta: 0:41:54 lr: 3.4711473847578654e-05 loss: 0.0845 (0.0719) time: 2.9039 data: 0.0069 max mem: 33369 +Epoch: [13] [ 450/1319] eta: 0:41:25 lr: 3.470259156319988e-05 loss: 0.0845 (0.0725) time: 2.8726 data: 0.0068 max mem: 33369 +Epoch: [13] [ 460/1319] eta: 0:40:58 lr: 3.469370902620718e-05 loss: 0.0742 (0.0722) time: 2.8934 data: 0.0067 max mem: 33369 +Epoch: [13] [ 470/1319] eta: 0:40:30 lr: 3.4684826236521504e-05 loss: 0.0596 (0.0722) time: 2.9098 data: 0.0073 max mem: 33369 +Epoch: [13] [ 480/1319] eta: 0:40:02 lr: 3.467594319406376e-05 loss: 0.0596 (0.0720) time: 2.8949 data: 0.0073 max mem: 33369 +Epoch: [13] [ 490/1319] eta: 0:39:31 lr: 3.466705989875479e-05 loss: 0.0545 (0.0719) time: 2.8119 data: 0.0072 max mem: 33369 +Epoch: [13] [ 500/1319] eta: 0:39:03 lr: 3.465817635051541e-05 loss: 0.0513 (0.0719) time: 2.8101 data: 0.0076 max mem: 33369 +Epoch: [13] [ 510/1319] eta: 0:38:34 lr: 3.4649292549266374e-05 loss: 0.0649 (0.0718) time: 2.8798 data: 0.0074 max mem: 33369 +Epoch: [13] [ 520/1319] eta: 0:38:06 lr: 3.464040849492841e-05 loss: 0.0665 (0.0721) time: 2.8819 data: 0.0071 max mem: 33369 +Epoch: [13] [ 530/1319] eta: 0:37:37 lr: 3.463152418742217e-05 loss: 0.0729 (0.0723) time: 2.8557 data: 0.0071 max mem: 33369 +Epoch: [13] [ 540/1319] eta: 0:37:09 lr: 3.4622639626668276e-05 loss: 0.0717 (0.0726) time: 2.8608 data: 0.0072 max mem: 33369 +Epoch: [13] [ 550/1319] eta: 0:36:41 lr: 3.461375481258729e-05 loss: 0.0831 (0.0732) time: 2.8938 data: 0.0070 max mem: 33369 +Epoch: [13] [ 560/1319] eta: 0:36:13 lr: 3.460486974509975e-05 loss: 0.0777 (0.0731) time: 2.9092 data: 0.0070 max mem: 33369 +Epoch: [13] [ 570/1319] eta: 0:35:43 lr: 3.4595984424126115e-05 loss: 0.0652 (0.0730) time: 2.8472 data: 0.0069 max mem: 33369 +Epoch: [13] [ 580/1319] eta: 0:35:16 lr: 3.458709884958682e-05 loss: 0.0619 (0.0729) time: 2.8722 data: 0.0071 max mem: 33369 +Epoch: [13] [ 590/1319] eta: 0:34:47 lr: 3.457821302140224e-05 loss: 0.0671 (0.0732) time: 2.9131 data: 0.0070 max mem: 33369 +Epoch: [13] [ 600/1319] eta: 0:34:18 lr: 3.456932693949272e-05 loss: 0.0671 (0.0735) time: 2.8403 data: 0.0074 max mem: 33369 +Epoch: [13] [ 610/1319] eta: 0:33:49 lr: 3.456044060377853e-05 loss: 0.0835 (0.0738) time: 2.8400 data: 0.0076 max mem: 33369 +Epoch: [13] [ 620/1319] eta: 0:33:21 lr: 3.455155401417991e-05 loss: 0.0850 (0.0737) time: 2.8596 data: 0.0070 max mem: 33369 +Epoch: [13] [ 630/1319] eta: 0:32:52 lr: 3.4542667170617054e-05 loss: 0.0611 (0.0736) time: 2.8615 data: 0.0071 max mem: 33369 +Epoch: [13] [ 640/1319] eta: 0:32:23 lr: 3.453378007301009e-05 loss: 0.0536 (0.0736) time: 2.8566 data: 0.0071 max mem: 33369 +Epoch: [13] [ 650/1319] eta: 0:31:54 lr: 3.4524892721279126e-05 loss: 0.0537 (0.0735) time: 2.8091 data: 0.0067 max mem: 33369 +Epoch: [13] [ 660/1319] eta: 0:31:25 lr: 3.4516005115344196e-05 loss: 0.0557 (0.0735) time: 2.8202 data: 0.0069 max mem: 33369 +Epoch: [13] [ 670/1319] eta: 0:30:57 lr: 3.45071172551253e-05 loss: 0.0578 (0.0733) time: 2.8748 data: 0.0069 max mem: 33369 +Epoch: [13] [ 680/1319] eta: 0:30:29 lr: 3.4498229140542384e-05 loss: 0.0662 (0.0733) time: 2.9027 data: 0.0070 max mem: 33369 +Epoch: [13] [ 690/1319] eta: 0:30:00 lr: 3.448934077151535e-05 loss: 0.0743 (0.0734) time: 2.8743 data: 0.0074 max mem: 33369 +Epoch: [13] [ 700/1319] eta: 0:29:31 lr: 3.448045214796405e-05 loss: 0.0817 (0.0735) time: 2.8409 data: 0.0073 max mem: 33369 +Epoch: [13] [ 710/1319] eta: 0:29:02 lr: 3.447156326980829e-05 loss: 0.0648 (0.0736) time: 2.8342 data: 0.0074 max mem: 33369 +Epoch: [13] [ 720/1319] eta: 0:28:33 lr: 3.446267413696782e-05 loss: 0.0634 (0.0735) time: 2.7883 data: 0.0074 max mem: 33369 +Epoch: [13] [ 730/1319] eta: 0:28:05 lr: 3.445378474936235e-05 loss: 0.0638 (0.0736) time: 2.8515 data: 0.0071 max mem: 33369 +Epoch: [13] [ 740/1319] eta: 0:27:36 lr: 3.444489510691154e-05 loss: 0.0704 (0.0735) time: 2.8958 data: 0.0073 max mem: 33369 +Epoch: [13] [ 750/1319] eta: 0:27:07 lr: 3.443600520953501e-05 loss: 0.0707 (0.0735) time: 2.8594 data: 0.0071 max mem: 33369 +Epoch: [13] [ 760/1319] eta: 0:26:38 lr: 3.4427115057152303e-05 loss: 0.0715 (0.0736) time: 2.8480 data: 0.0071 max mem: 33369 +Epoch: [13] [ 770/1319] eta: 0:26:10 lr: 3.441822464968295e-05 loss: 0.0756 (0.0736) time: 2.8236 data: 0.0075 max mem: 33369 +Epoch: [13] [ 780/1319] eta: 0:25:41 lr: 3.44093339870464e-05 loss: 0.0756 (0.0736) time: 2.8297 data: 0.0076 max mem: 33369 +Epoch: [13] [ 790/1319] eta: 0:25:12 lr: 3.4400443069162084e-05 loss: 0.0640 (0.0735) time: 2.8360 data: 0.0072 max mem: 33369 +Epoch: [13] [ 800/1319] eta: 0:24:43 lr: 3.439155189594936e-05 loss: 0.0698 (0.0736) time: 2.7888 data: 0.0068 max mem: 33369 +Epoch: [13] [ 810/1319] eta: 0:24:15 lr: 3.4382660467327555e-05 loss: 0.0698 (0.0735) time: 2.8533 data: 0.0069 max mem: 33369 +Epoch: [13] [ 820/1319] eta: 0:23:46 lr: 3.437376878321594e-05 loss: 0.0641 (0.0734) time: 2.9033 data: 0.0069 max mem: 33369 +Epoch: [13] [ 830/1319] eta: 0:23:18 lr: 3.436487684353372e-05 loss: 0.0641 (0.0734) time: 2.8833 data: 0.0068 max mem: 33369 +Epoch: [13] [ 840/1319] eta: 0:22:49 lr: 3.435598464820009e-05 loss: 0.0650 (0.0734) time: 2.8911 data: 0.0072 max mem: 33369 +Epoch: [13] [ 850/1319] eta: 0:22:21 lr: 3.434709219713417e-05 loss: 0.0605 (0.0733) time: 2.8930 data: 0.0075 max mem: 33369 +Epoch: [13] [ 860/1319] eta: 0:21:52 lr: 3.433819949025503e-05 loss: 0.0629 (0.0733) time: 2.8855 data: 0.0078 max mem: 33369 +Epoch: [13] [ 870/1319] eta: 0:21:24 lr: 3.432930652748169e-05 loss: 0.0726 (0.0734) time: 2.8340 data: 0.0077 max mem: 33369 +Epoch: [13] [ 880/1319] eta: 0:20:55 lr: 3.432041330873315e-05 loss: 0.0680 (0.0734) time: 2.8505 data: 0.0074 max mem: 33369 +Epoch: [13] [ 890/1319] eta: 0:20:26 lr: 3.4311519833928315e-05 loss: 0.0606 (0.0734) time: 2.8683 data: 0.0074 max mem: 33369 +Epoch: [13] [ 900/1319] eta: 0:19:58 lr: 3.430262610298607e-05 loss: 0.0644 (0.0734) time: 2.8828 data: 0.0071 max mem: 33369 +Epoch: [13] [ 910/1319] eta: 0:19:29 lr: 3.429373211582526e-05 loss: 0.0646 (0.0734) time: 2.8827 data: 0.0073 max mem: 33369 +Epoch: [13] [ 920/1319] eta: 0:19:01 lr: 3.428483787236465e-05 loss: 0.0646 (0.0734) time: 2.8619 data: 0.0080 max mem: 33369 +Epoch: [13] [ 930/1319] eta: 0:18:32 lr: 3.4275943372522975e-05 loss: 0.0713 (0.0734) time: 2.8660 data: 0.0081 max mem: 33369 +Epoch: [13] [ 940/1319] eta: 0:18:04 lr: 3.426704861621893e-05 loss: 0.0777 (0.0735) time: 2.8615 data: 0.0078 max mem: 33369 +Epoch: [13] [ 950/1319] eta: 0:17:35 lr: 3.4258153603371135e-05 loss: 0.0701 (0.0736) time: 2.8095 data: 0.0074 max mem: 33369 +Epoch: [13] [ 960/1319] eta: 0:17:06 lr: 3.424925833389819e-05 loss: 0.0666 (0.0737) time: 2.8105 data: 0.0076 max mem: 33369 +Epoch: [13] [ 970/1319] eta: 0:16:37 lr: 3.424036280771861e-05 loss: 0.0701 (0.0737) time: 2.8444 data: 0.0080 max mem: 33369 +Epoch: [13] [ 980/1319] eta: 0:16:09 lr: 3.42314670247509e-05 loss: 0.0727 (0.0739) time: 2.8201 data: 0.0079 max mem: 33369 +Epoch: [13] [ 990/1319] eta: 0:15:40 lr: 3.422257098491348e-05 loss: 0.0752 (0.0739) time: 2.8193 data: 0.0080 max mem: 33369 +Epoch: [13] [1000/1319] eta: 0:15:11 lr: 3.4213674688124745e-05 loss: 0.0744 (0.0739) time: 2.8398 data: 0.0076 max mem: 33369 +Epoch: [13] [1010/1319] eta: 0:14:43 lr: 3.420477813430303e-05 loss: 0.0629 (0.0739) time: 2.8619 data: 0.0072 max mem: 33369 +Epoch: [13] [1020/1319] eta: 0:14:14 lr: 3.419588132336663e-05 loss: 0.0571 (0.0739) time: 2.8296 data: 0.0074 max mem: 33369 +Epoch: [13] [1030/1319] eta: 0:13:46 lr: 3.418698425523378e-05 loss: 0.0686 (0.0738) time: 2.8525 data: 0.0072 max mem: 33369 +Epoch: [13] [1040/1319] eta: 0:13:17 lr: 3.417808692982266e-05 loss: 0.0639 (0.0738) time: 2.8832 data: 0.0069 max mem: 33369 +Epoch: [13] [1050/1319] eta: 0:12:49 lr: 3.4169189347051416e-05 loss: 0.0607 (0.0739) time: 2.8883 data: 0.0074 max mem: 33369 +Epoch: [13] [1060/1319] eta: 0:12:20 lr: 3.416029150683815e-05 loss: 0.0780 (0.0741) time: 2.9118 data: 0.0074 max mem: 33369 +Epoch: [13] [1070/1319] eta: 0:11:51 lr: 3.4151393409100875e-05 loss: 0.0775 (0.0743) time: 2.8596 data: 0.0073 max mem: 33369 +Epoch: [13] [1080/1319] eta: 0:11:23 lr: 3.41424950537576e-05 loss: 0.0837 (0.0746) time: 2.8245 data: 0.0077 max mem: 33369 +Epoch: [13] [1090/1319] eta: 0:10:54 lr: 3.413359644072625e-05 loss: 0.0728 (0.0746) time: 2.8535 data: 0.0077 max mem: 33369 +Epoch: [13] [1100/1319] eta: 0:10:26 lr: 3.412469756992473e-05 loss: 0.0637 (0.0745) time: 2.8428 data: 0.0073 max mem: 33369 +Epoch: [13] [1110/1319] eta: 0:09:57 lr: 3.411579844127087e-05 loss: 0.0707 (0.0745) time: 2.8476 data: 0.0070 max mem: 33369 +Epoch: [13] [1120/1319] eta: 0:09:28 lr: 3.410689905468246e-05 loss: 0.0650 (0.0744) time: 2.8869 data: 0.0070 max mem: 33369 +Epoch: [13] [1130/1319] eta: 0:09:00 lr: 3.409799941007725e-05 loss: 0.0581 (0.0744) time: 2.8984 data: 0.0073 max mem: 33369 +Epoch: [13] [1140/1319] eta: 0:08:31 lr: 3.408909950737292e-05 loss: 0.0608 (0.0743) time: 2.8735 data: 0.0080 max mem: 33369 +Epoch: [13] [1150/1319] eta: 0:08:03 lr: 3.4080199346487104e-05 loss: 0.0651 (0.0743) time: 2.8549 data: 0.0077 max mem: 33369 +Epoch: [13] [1160/1319] eta: 0:07:34 lr: 3.4071298927337405e-05 loss: 0.0697 (0.0743) time: 2.8389 data: 0.0073 max mem: 33369 +Epoch: [13] [1170/1319] eta: 0:07:05 lr: 3.406239824984136e-05 loss: 0.0755 (0.0744) time: 2.8175 data: 0.0079 max mem: 33369 +Epoch: [13] [1180/1319] eta: 0:06:37 lr: 3.405349731391645e-05 loss: 0.0755 (0.0745) time: 2.8010 data: 0.0074 max mem: 33369 +Epoch: [13] [1190/1319] eta: 0:06:08 lr: 3.404459611948011e-05 loss: 0.0667 (0.0744) time: 2.8437 data: 0.0070 max mem: 33369 +Epoch: [13] [1200/1319] eta: 0:05:40 lr: 3.4035694666449745e-05 loss: 0.0514 (0.0744) time: 2.8943 data: 0.0072 max mem: 33369 +Epoch: [13] [1210/1319] eta: 0:05:11 lr: 3.402679295474268e-05 loss: 0.0633 (0.0743) time: 2.8470 data: 0.0070 max mem: 33369 +Epoch: [13] [1220/1319] eta: 0:04:42 lr: 3.401789098427621e-05 loss: 0.0657 (0.0743) time: 2.8154 data: 0.0077 max mem: 33369 +Epoch: [13] [1230/1319] eta: 0:04:14 lr: 3.400898875496756e-05 loss: 0.0687 (0.0743) time: 2.8368 data: 0.0076 max mem: 33369 +Epoch: [13] [1240/1319] eta: 0:03:45 lr: 3.400008626673392e-05 loss: 0.0627 (0.0743) time: 2.8372 data: 0.0076 max mem: 33369 +Epoch: [13] [1250/1319] eta: 0:03:17 lr: 3.399118351949243e-05 loss: 0.0627 (0.0743) time: 2.7985 data: 0.0078 max mem: 33369 +Epoch: [13] [1260/1319] eta: 0:02:48 lr: 3.398228051316017e-05 loss: 0.0642 (0.0744) time: 2.8196 data: 0.0074 max mem: 33369 +Epoch: [13] [1270/1319] eta: 0:02:19 lr: 3.397337724765419e-05 loss: 0.0792 (0.0745) time: 2.8304 data: 0.0077 max mem: 33369 +Epoch: [13] [1280/1319] eta: 0:01:51 lr: 3.396447372289146e-05 loss: 0.0729 (0.0745) time: 2.8268 data: 0.0078 max mem: 33369 +Epoch: [13] [1290/1319] eta: 0:01:22 lr: 3.395556993878891e-05 loss: 0.0655 (0.0746) time: 2.8482 data: 0.0079 max mem: 33369 +Epoch: [13] [1300/1319] eta: 0:00:54 lr: 3.394666589526343e-05 loss: 0.0713 (0.0746) time: 2.8678 data: 0.0075 max mem: 33369 +Epoch: [13] [1310/1319] eta: 0:00:25 lr: 3.393776159223184e-05 loss: 0.0713 (0.0745) time: 2.8898 data: 0.0069 max mem: 33369 +Epoch: [13] Total time: 1:02:48 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 2:10:42 time: 3.0481 data: 2.9390 max mem: 33369 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 100/2573] eta: 0:04:13 time: 0.0722 data: 0.0012 max mem: 33369 +Test: [ 200/2573] eta: 0:03:30 time: 0.0735 data: 0.0012 max mem: 33369 +Test: [ 300/2573] eta: 0:03:09 time: 0.0752 data: 0.0011 max mem: 33369 +Test: [ 400/2573] eta: 0:02:55 time: 0.0754 data: 0.0011 max mem: 33369 +Test: [ 500/2573] eta: 0:02:44 time: 0.0763 data: 0.0015 max mem: 33369 +Test: [ 600/2573] eta: 0:02:35 time: 0.0757 data: 0.0014 max mem: 33369 +Test: [ 700/2573] eta: 0:02:27 time: 0.0755 data: 0.0014 max mem: 33369 +Test: [ 800/2573] eta: 0:02:18 time: 0.0769 data: 0.0011 max mem: 33369 +Test: [ 900/2573] eta: 0:02:10 time: 0.0736 data: 0.0011 max mem: 33369 +Test: [1000/2573] eta: 0:02:01 time: 0.0737 data: 0.0011 max mem: 33369 +Test: [1100/2573] eta: 0:01:53 time: 0.0737 data: 0.0011 max mem: 33369 +Test: [1200/2573] eta: 0:01:45 time: 0.0737 data: 0.0011 max mem: 33369 +Test: [1300/2573] eta: 0:01:37 time: 0.0742 data: 0.0011 max mem: 33369 +Test: [1400/2573] eta: 0:01:29 time: 0.0721 data: 0.0011 max mem: 33369 +Test: [1500/2573] eta: 0:01:21 time: 0.0738 data: 0.0011 max mem: 33369 +Test: [1600/2573] eta: 0:01:14 time: 0.0770 data: 0.0011 max mem: 33369 +Test: [1700/2573] eta: 0:01:06 time: 0.0751 data: 0.0015 max mem: 33369 +Test: [1800/2573] eta: 0:00:58 time: 0.0766 data: 0.0013 max mem: 33369 +Test: [1900/2573] eta: 0:00:51 time: 0.0732 data: 0.0013 max mem: 33369 +Test: [2000/2573] eta: 0:00:43 time: 0.0751 data: 0.0013 max mem: 33369 +Test: [2100/2573] eta: 0:00:35 time: 0.0767 data: 0.0012 max mem: 33369 +Test: [2200/2573] eta: 0:00:28 time: 0.0767 data: 0.0012 max mem: 33369 +Test: [2300/2573] eta: 0:00:20 time: 0.0767 data: 0.0013 max mem: 33369 +Test: [2400/2573] eta: 0:00:13 time: 0.0717 data: 0.0013 max mem: 33369 +Test: [2500/2573] eta: 0:00:05 time: 0.0750 data: 0.0013 max mem: 33369 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: Total time: 0:03:15 +Final results: +Mean IoU is 61.79 + + precision@0.5 = 69.32 + precision@0.6 = 63.50 + precision@0.7 = 55.68 + precision@0.8 = 44.14 + precision@0.9 = 20.18 + overall IoU = 59.43 + +Average object IoU 61.79051204904985 +Overall IoU 59.430397033691406 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [14] [ 0/1319] eta: 3:25:41 lr: 3.392974749755691e-05 loss: 0.0534 (0.0534) time: 9.3567 data: 1.4785 max mem: 33369 +Epoch: [14] [ 10/1319] eta: 1:14:34 lr: 3.392084270123441e-05 loss: 0.0595 (0.0637) time: 3.4183 data: 0.1411 max mem: 33369 +Epoch: [14] [ 20/1319] eta: 1:08:11 lr: 3.391193764516433e-05 loss: 0.0601 (0.0663) time: 2.8391 data: 0.0073 max mem: 33369 +Epoch: [14] [ 30/1319] eta: 1:05:52 lr: 3.3903032329263314e-05 loss: 0.0599 (0.0658) time: 2.8732 data: 0.0073 max mem: 33369 +Epoch: [14] [ 40/1319] eta: 1:04:22 lr: 3.389412675344791e-05 loss: 0.0601 (0.0665) time: 2.8837 data: 0.0073 max mem: 33369 +Epoch: [14] [ 50/1319] eta: 1:03:18 lr: 3.388522091763468e-05 loss: 0.0689 (0.0669) time: 2.8790 data: 0.0073 max mem: 33369 +Epoch: [14] [ 60/1319] eta: 1:02:14 lr: 3.387631482174009e-05 loss: 0.0596 (0.0672) time: 2.8575 data: 0.0078 max mem: 33369 +Epoch: [14] [ 70/1319] eta: 1:01:21 lr: 3.386740846568057e-05 loss: 0.0569 (0.0661) time: 2.8322 data: 0.0084 max mem: 33369 +Epoch: [14] [ 80/1319] eta: 1:00:39 lr: 3.385850184937249e-05 loss: 0.0558 (0.0661) time: 2.8478 data: 0.0081 max mem: 33369 +Epoch: [14] [ 90/1319] eta: 0:59:58 lr: 3.3849594972732175e-05 loss: 0.0601 (0.0653) time: 2.8572 data: 0.0075 max mem: 33369 +Epoch: [14] [ 100/1319] eta: 0:59:19 lr: 3.38406878356759e-05 loss: 0.0506 (0.0645) time: 2.8482 data: 0.0074 max mem: 33369 +Epoch: [14] [ 110/1319] eta: 0:58:36 lr: 3.3831780438119907e-05 loss: 0.0506 (0.0638) time: 2.8222 data: 0.0077 max mem: 33369 +Epoch: [14] [ 120/1319] eta: 0:57:52 lr: 3.3822872779980336e-05 loss: 0.0668 (0.0652) time: 2.7781 data: 0.0074 max mem: 33369 +Epoch: [14] [ 130/1319] eta: 0:57:25 lr: 3.381396486117332e-05 loss: 0.0734 (0.0658) time: 2.8376 data: 0.0073 max mem: 33369 +Epoch: [14] [ 140/1319] eta: 0:56:55 lr: 3.380505668161494e-05 loss: 0.0624 (0.0662) time: 2.9002 data: 0.0072 max mem: 33369 +Epoch: [14] [ 150/1319] eta: 0:56:21 lr: 3.3796148241221185e-05 loss: 0.0624 (0.0663) time: 2.8567 data: 0.0070 max mem: 33369 +Epoch: [14] [ 160/1319] eta: 0:55:46 lr: 3.378723953990804e-05 loss: 0.0582 (0.0658) time: 2.8194 data: 0.0075 max mem: 33369 +Epoch: [14] [ 170/1319] eta: 0:55:15 lr: 3.3778330577591404e-05 loss: 0.0582 (0.0666) time: 2.8349 data: 0.0077 max mem: 33369 +Epoch: [14] [ 180/1319] eta: 0:54:42 lr: 3.3769421354187145e-05 loss: 0.0670 (0.0670) time: 2.8413 data: 0.0076 max mem: 33369 +Epoch: [14] [ 190/1319] eta: 0:54:07 lr: 3.376051186961107e-05 loss: 0.0637 (0.0672) time: 2.7989 data: 0.0080 max mem: 33369 +Epoch: [14] [ 200/1319] eta: 0:53:38 lr: 3.375160212377894e-05 loss: 0.0613 (0.0674) time: 2.8194 data: 0.0077 max mem: 33369 +Epoch: [14] [ 210/1319] eta: 0:53:08 lr: 3.374269211660646e-05 loss: 0.0639 (0.0673) time: 2.8557 data: 0.0073 max mem: 33369 +Epoch: [14] [ 220/1319] eta: 0:52:40 lr: 3.373378184800928e-05 loss: 0.0600 (0.0672) time: 2.8748 data: 0.0072 max mem: 33369 +Epoch: [14] [ 230/1319] eta: 0:52:09 lr: 3.372487131790299e-05 loss: 0.0671 (0.0673) time: 2.8634 data: 0.0073 max mem: 33369 +Epoch: [14] [ 240/1319] eta: 0:51:40 lr: 3.371596052620316e-05 loss: 0.0606 (0.0683) time: 2.8435 data: 0.0075 max mem: 33369 +Epoch: [14] [ 250/1319] eta: 0:51:12 lr: 3.370704947282529e-05 loss: 0.0643 (0.0684) time: 2.8788 data: 0.0073 max mem: 33369 +Epoch: [14] [ 260/1319] eta: 0:50:44 lr: 3.3698138157684804e-05 loss: 0.0643 (0.0680) time: 2.8999 data: 0.0071 max mem: 33369 +Epoch: [14] [ 270/1319] eta: 0:50:15 lr: 3.368922658069711e-05 loss: 0.0520 (0.0678) time: 2.8771 data: 0.0070 max mem: 33369 +Epoch: [14] [ 280/1319] eta: 0:49:48 lr: 3.368031474177754e-05 loss: 0.0608 (0.0680) time: 2.8968 data: 0.0070 max mem: 33369 +Epoch: [14] [ 290/1319] eta: 0:49:21 lr: 3.367140264084139e-05 loss: 0.0568 (0.0680) time: 2.9232 data: 0.0070 max mem: 33369 +Epoch: [14] [ 300/1319] eta: 0:48:52 lr: 3.366249027780389e-05 loss: 0.0559 (0.0677) time: 2.8889 data: 0.0070 max mem: 33369 +Epoch: [14] [ 310/1319] eta: 0:48:21 lr: 3.365357765258022e-05 loss: 0.0565 (0.0675) time: 2.8486 data: 0.0071 max mem: 33369 +Epoch: [14] [ 320/1319] eta: 0:47:55 lr: 3.364466476508552e-05 loss: 0.0597 (0.0673) time: 2.8875 data: 0.0070 max mem: 33369 +Epoch: [14] [ 330/1319] eta: 0:47:26 lr: 3.363575161523487e-05 loss: 0.0511 (0.0667) time: 2.9069 data: 0.0076 max mem: 33369 +Epoch: [14] [ 340/1319] eta: 0:46:54 lr: 3.362683820294329e-05 loss: 0.0511 (0.0668) time: 2.8291 data: 0.0080 max mem: 33369 +Epoch: [14] [ 350/1319] eta: 0:46:22 lr: 3.361792452812576e-05 loss: 0.0517 (0.0668) time: 2.7781 data: 0.0073 max mem: 33369 +Epoch: [14] [ 360/1319] eta: 0:45:56 lr: 3.36090105906972e-05 loss: 0.0654 (0.0669) time: 2.8531 data: 0.0072 max mem: 33369 +Epoch: [14] [ 370/1319] eta: 0:45:27 lr: 3.3600096390572475e-05 loss: 0.0693 (0.0673) time: 2.9131 data: 0.0073 max mem: 33369 +Epoch: [14] [ 380/1319] eta: 0:44:57 lr: 3.3591181927666404e-05 loss: 0.0557 (0.0670) time: 2.8503 data: 0.0074 max mem: 33369 +Epoch: [14] [ 390/1319] eta: 0:44:28 lr: 3.358226720189375e-05 loss: 0.0512 (0.0669) time: 2.8369 data: 0.0077 max mem: 33369 +Epoch: [14] [ 400/1319] eta: 0:44:00 lr: 3.357335221316921e-05 loss: 0.0512 (0.0668) time: 2.8736 data: 0.0073 max mem: 33369 +Epoch: [14] [ 410/1319] eta: 0:43:30 lr: 3.3564436961407466e-05 loss: 0.0648 (0.0672) time: 2.8542 data: 0.0072 max mem: 33369 +Epoch: [14] [ 420/1319] eta: 0:43:00 lr: 3.35555214465231e-05 loss: 0.0815 (0.0677) time: 2.8115 data: 0.0071 max mem: 33369 +Epoch: [14] [ 430/1319] eta: 0:42:32 lr: 3.354660566843068e-05 loss: 0.0805 (0.0678) time: 2.8607 data: 0.0072 max mem: 33369 +Epoch: [14] [ 440/1319] eta: 0:42:03 lr: 3.353768962704469e-05 loss: 0.0706 (0.0678) time: 2.8972 data: 0.0077 max mem: 33369 +Epoch: [14] [ 450/1319] eta: 0:41:34 lr: 3.352877332227959e-05 loss: 0.0662 (0.0676) time: 2.8630 data: 0.0080 max mem: 33369 +Epoch: [14] [ 460/1319] eta: 0:41:05 lr: 3.351985675404978e-05 loss: 0.0545 (0.0674) time: 2.8489 data: 0.0078 max mem: 33369 +Epoch: [14] [ 470/1319] eta: 0:40:36 lr: 3.3510939922269576e-05 loss: 0.0624 (0.0674) time: 2.8456 data: 0.0078 max mem: 33369 +Epoch: [14] [ 480/1319] eta: 0:40:07 lr: 3.350202282685327e-05 loss: 0.0681 (0.0677) time: 2.8464 data: 0.0080 max mem: 33369 +Epoch: [14] [ 490/1319] eta: 0:39:38 lr: 3.34931054677151e-05 loss: 0.0675 (0.0677) time: 2.8500 data: 0.0078 max mem: 33369 +Epoch: [14] [ 500/1319] eta: 0:39:07 lr: 3.3484187844769246e-05 loss: 0.0632 (0.0676) time: 2.7926 data: 0.0071 max mem: 33369 +Epoch: [14] [ 510/1319] eta: 0:38:40 lr: 3.347526995792984e-05 loss: 0.0632 (0.0675) time: 2.8690 data: 0.0072 max mem: 33369 +Epoch: [14] [ 520/1319] eta: 0:38:12 lr: 3.346635180711094e-05 loss: 0.0628 (0.0675) time: 2.9356 data: 0.0079 max mem: 33369 +Epoch: [14] [ 530/1319] eta: 0:37:42 lr: 3.3457433392226575e-05 loss: 0.0578 (0.0673) time: 2.8509 data: 0.0078 max mem: 33369 +Epoch: [14] [ 540/1319] eta: 0:37:14 lr: 3.344851471319071e-05 loss: 0.0632 (0.0676) time: 2.8604 data: 0.0071 max mem: 33369 +Epoch: [14] [ 550/1319] eta: 0:36:46 lr: 3.343959576991726e-05 loss: 0.0694 (0.0678) time: 2.8887 data: 0.0073 max mem: 33369 +Epoch: [14] [ 560/1319] eta: 0:36:17 lr: 3.343067656232008e-05 loss: 0.0595 (0.0680) time: 2.8649 data: 0.0079 max mem: 33369 +Epoch: [14] [ 570/1319] eta: 0:35:47 lr: 3.342175709031298e-05 loss: 0.0550 (0.0684) time: 2.8205 data: 0.0077 max mem: 33369 +Epoch: [14] [ 580/1319] eta: 0:35:19 lr: 3.341283735380971e-05 loss: 0.0675 (0.0685) time: 2.8722 data: 0.0072 max mem: 33369 +Epoch: [14] [ 590/1319] eta: 0:34:50 lr: 3.3403917352723954e-05 loss: 0.0630 (0.0685) time: 2.8953 data: 0.0073 max mem: 33369 +Epoch: [14] [ 600/1319] eta: 0:34:22 lr: 3.339499708696938e-05 loss: 0.0707 (0.0686) time: 2.8723 data: 0.0074 max mem: 33369 +Epoch: [14] [ 610/1319] eta: 0:33:53 lr: 3.3386076556459565e-05 loss: 0.0784 (0.0689) time: 2.8713 data: 0.0076 max mem: 33369 +Epoch: [14] [ 620/1319] eta: 0:33:24 lr: 3.337715576110804e-05 loss: 0.0649 (0.0688) time: 2.8496 data: 0.0077 max mem: 33369 +Epoch: [14] [ 630/1319] eta: 0:32:56 lr: 3.336823470082831e-05 loss: 0.0598 (0.0687) time: 2.8751 data: 0.0072 max mem: 33369 +Epoch: [14] [ 640/1319] eta: 0:32:27 lr: 3.335931337553377e-05 loss: 0.0598 (0.0687) time: 2.8823 data: 0.0076 max mem: 33369 +Epoch: [14] [ 650/1319] eta: 0:31:58 lr: 3.3350391785137824e-05 loss: 0.0704 (0.0691) time: 2.8235 data: 0.0075 max mem: 33369 +Epoch: [14] [ 660/1319] eta: 0:31:29 lr: 3.334146992955378e-05 loss: 0.0707 (0.0690) time: 2.8400 data: 0.0070 max mem: 33369 +Epoch: [14] [ 670/1319] eta: 0:31:01 lr: 3.33325478086949e-05 loss: 0.0703 (0.0692) time: 2.9139 data: 0.0070 max mem: 33369 +Epoch: [14] [ 680/1319] eta: 0:30:32 lr: 3.332362542247442e-05 loss: 0.0586 (0.0692) time: 2.8943 data: 0.0072 max mem: 33369 +Epoch: [14] [ 690/1319] eta: 0:30:04 lr: 3.3314702770805464e-05 loss: 0.0574 (0.0691) time: 2.8690 data: 0.0076 max mem: 33369 +Epoch: [14] [ 700/1319] eta: 0:29:35 lr: 3.330577985360116e-05 loss: 0.0539 (0.0690) time: 2.8644 data: 0.0080 max mem: 33369 +Epoch: [14] [ 710/1319] eta: 0:29:06 lr: 3.329685667077455e-05 loss: 0.0605 (0.0689) time: 2.8474 data: 0.0079 max mem: 33369 +Epoch: [14] [ 720/1319] eta: 0:28:37 lr: 3.3287933222238623e-05 loss: 0.0679 (0.0690) time: 2.8120 data: 0.0078 max mem: 33369 +Epoch: [14] [ 730/1319] eta: 0:28:08 lr: 3.327900950790632e-05 loss: 0.0699 (0.0690) time: 2.8188 data: 0.0076 max mem: 33369 +Epoch: [14] [ 740/1319] eta: 0:27:39 lr: 3.327008552769054e-05 loss: 0.0606 (0.0691) time: 2.8352 data: 0.0079 max mem: 33369 +Epoch: [14] [ 750/1319] eta: 0:27:10 lr: 3.32611612815041e-05 loss: 0.0701 (0.0691) time: 2.8285 data: 0.0085 max mem: 33369 +Epoch: [14] [ 760/1319] eta: 0:26:41 lr: 3.325223676925979e-05 loss: 0.0642 (0.0690) time: 2.8445 data: 0.0079 max mem: 33369 +Epoch: [14] [ 770/1319] eta: 0:26:12 lr: 3.324331199087032e-05 loss: 0.0540 (0.0690) time: 2.8204 data: 0.0076 max mem: 33369 +Epoch: [14] [ 780/1319] eta: 0:25:43 lr: 3.323438694624837e-05 loss: 0.0608 (0.0689) time: 2.8206 data: 0.0080 max mem: 33369 +Epoch: [14] [ 790/1319] eta: 0:25:14 lr: 3.322546163530654e-05 loss: 0.0550 (0.0689) time: 2.8319 data: 0.0081 max mem: 33369 +Epoch: [14] [ 800/1319] eta: 0:24:45 lr: 3.32165360579574e-05 loss: 0.0551 (0.0690) time: 2.7887 data: 0.0075 max mem: 33369 +Epoch: [14] [ 810/1319] eta: 0:24:17 lr: 3.320761021411345e-05 loss: 0.0644 (0.0691) time: 2.8305 data: 0.0075 max mem: 33369 +Epoch: [14] [ 820/1319] eta: 0:23:48 lr: 3.3198684103687127e-05 loss: 0.0646 (0.0693) time: 2.8508 data: 0.0080 max mem: 33369 +Epoch: [14] [ 830/1319] eta: 0:23:19 lr: 3.318975772659084e-05 loss: 0.0781 (0.0694) time: 2.8149 data: 0.0077 max mem: 33369 +Epoch: [14] [ 840/1319] eta: 0:22:50 lr: 3.3180831082736915e-05 loss: 0.0662 (0.0693) time: 2.8301 data: 0.0076 max mem: 33369 +Epoch: [14] [ 850/1319] eta: 0:22:21 lr: 3.3171904172037654e-05 loss: 0.0608 (0.0693) time: 2.8446 data: 0.0076 max mem: 33369 +Epoch: [14] [ 860/1319] eta: 0:21:53 lr: 3.3162976994405264e-05 loss: 0.0600 (0.0692) time: 2.8531 data: 0.0075 max mem: 33369 +Epoch: [14] [ 870/1319] eta: 0:21:24 lr: 3.315404954975194e-05 loss: 0.0641 (0.0693) time: 2.8479 data: 0.0072 max mem: 33369 +Epoch: [14] [ 880/1319] eta: 0:20:55 lr: 3.314512183798977e-05 loss: 0.0649 (0.0694) time: 2.8041 data: 0.0066 max mem: 33369 +Epoch: [14] [ 890/1319] eta: 0:20:27 lr: 3.3136193859030854e-05 loss: 0.0649 (0.0694) time: 2.8601 data: 0.0071 max mem: 33369 +Epoch: [14] [ 900/1319] eta: 0:19:58 lr: 3.312726561278717e-05 loss: 0.0714 (0.0694) time: 2.9200 data: 0.0075 max mem: 33369 +Epoch: [14] [ 910/1319] eta: 0:19:30 lr: 3.311833709917069e-05 loss: 0.0724 (0.0695) time: 2.8838 data: 0.0072 max mem: 33369 +Epoch: [14] [ 920/1319] eta: 0:19:01 lr: 3.3109408318093296e-05 loss: 0.0639 (0.0694) time: 2.8723 data: 0.0075 max mem: 33369 +Epoch: [14] [ 930/1319] eta: 0:18:32 lr: 3.310047926946684e-05 loss: 0.0589 (0.0694) time: 2.8508 data: 0.0077 max mem: 33369 +Epoch: [14] [ 940/1319] eta: 0:18:04 lr: 3.309154995320309e-05 loss: 0.0658 (0.0695) time: 2.8484 data: 0.0071 max mem: 33369 +Epoch: [14] [ 950/1319] eta: 0:17:35 lr: 3.308262036921381e-05 loss: 0.0679 (0.0695) time: 2.8176 data: 0.0071 max mem: 33369 +Epoch: [14] [ 960/1319] eta: 0:17:06 lr: 3.307369051741064e-05 loss: 0.0689 (0.0696) time: 2.8316 data: 0.0075 max mem: 33369 +Epoch: [14] [ 970/1319] eta: 0:16:38 lr: 3.306476039770522e-05 loss: 0.0691 (0.0696) time: 2.8762 data: 0.0070 max mem: 33369 +Epoch: [14] [ 980/1319] eta: 0:16:09 lr: 3.30558300100091e-05 loss: 0.0691 (0.0697) time: 2.8589 data: 0.0068 max mem: 33369 +Epoch: [14] [ 990/1319] eta: 0:15:41 lr: 3.30468993542338e-05 loss: 0.0697 (0.0697) time: 2.8650 data: 0.0069 max mem: 33369 +Epoch: [14] [1000/1319] eta: 0:15:12 lr: 3.3037968430290776e-05 loss: 0.0619 (0.0696) time: 2.8995 data: 0.0068 max mem: 33369 +Epoch: [14] [1010/1319] eta: 0:14:44 lr: 3.3029037238091407e-05 loss: 0.0626 (0.0697) time: 2.8895 data: 0.0068 max mem: 33369 +Epoch: [14] [1020/1319] eta: 0:14:15 lr: 3.3020105777547046e-05 loss: 0.0759 (0.0698) time: 2.8812 data: 0.0070 max mem: 33369 +Epoch: [14] [1030/1319] eta: 0:13:46 lr: 3.301117404856897e-05 loss: 0.0655 (0.0698) time: 2.8350 data: 0.0070 max mem: 33369 +Epoch: [14] [1040/1319] eta: 0:13:18 lr: 3.300224205106842e-05 loss: 0.0671 (0.0698) time: 2.8515 data: 0.0074 max mem: 33369 +Epoch: [14] [1050/1319] eta: 0:12:49 lr: 3.2993309784956545e-05 loss: 0.0618 (0.0698) time: 2.9076 data: 0.0080 max mem: 33369 +Epoch: [14] [1060/1319] eta: 0:12:21 lr: 3.298437725014447e-05 loss: 0.0627 (0.0699) time: 2.8883 data: 0.0077 max mem: 33369 +Epoch: [14] [1070/1319] eta: 0:11:52 lr: 3.297544444654327e-05 loss: 0.0592 (0.0699) time: 2.9124 data: 0.0071 max mem: 33369 +Epoch: [14] [1080/1319] eta: 0:11:24 lr: 3.296651137406393e-05 loss: 0.0619 (0.0700) time: 2.8692 data: 0.0074 max mem: 33369 +Epoch: [14] [1090/1319] eta: 0:10:55 lr: 3.2957578032617413e-05 loss: 0.0619 (0.0699) time: 2.8382 data: 0.0072 max mem: 33369 +Epoch: [14] [1100/1319] eta: 0:10:26 lr: 3.29486444221146e-05 loss: 0.0692 (0.0700) time: 2.8498 data: 0.0070 max mem: 33369 +Epoch: [14] [1110/1319] eta: 0:09:58 lr: 3.293971054246633e-05 loss: 0.0740 (0.0700) time: 2.8622 data: 0.0074 max mem: 33369 +Epoch: [14] [1120/1319] eta: 0:09:29 lr: 3.293077639358339e-05 loss: 0.0656 (0.0700) time: 2.8580 data: 0.0080 max mem: 33369 +Epoch: [14] [1130/1319] eta: 0:09:00 lr: 3.2921841975376476e-05 loss: 0.0656 (0.0700) time: 2.8304 data: 0.0083 max mem: 33369 +Epoch: [14] [1140/1319] eta: 0:08:32 lr: 3.291290728775627e-05 loss: 0.0601 (0.0700) time: 2.8600 data: 0.0076 max mem: 33369 +Epoch: [14] [1150/1319] eta: 0:08:03 lr: 3.290397233063338e-05 loss: 0.0586 (0.0700) time: 2.9023 data: 0.0072 max mem: 33369 +Epoch: [14] [1160/1319] eta: 0:07:35 lr: 3.2895037103918356e-05 loss: 0.0583 (0.0699) time: 2.8918 data: 0.0076 max mem: 33369 +Epoch: [14] [1170/1319] eta: 0:07:06 lr: 3.2886101607521696e-05 loss: 0.0633 (0.0699) time: 2.8686 data: 0.0078 max mem: 33369 +Epoch: [14] [1180/1319] eta: 0:06:37 lr: 3.287716584135384e-05 loss: 0.0585 (0.0699) time: 2.8259 data: 0.0076 max mem: 33369 +Epoch: [14] [1190/1319] eta: 0:06:09 lr: 3.286822980532516e-05 loss: 0.0585 (0.0698) time: 2.8628 data: 0.0074 max mem: 33369 +Epoch: [14] [1200/1319] eta: 0:05:40 lr: 3.285929349934599e-05 loss: 0.0633 (0.0698) time: 2.8952 data: 0.0074 max mem: 33369 +Epoch: [14] [1210/1319] eta: 0:05:11 lr: 3.28503569233266e-05 loss: 0.0584 (0.0697) time: 2.8632 data: 0.0072 max mem: 33369 +Epoch: [14] [1220/1319] eta: 0:04:43 lr: 3.284142007717719e-05 loss: 0.0601 (0.0698) time: 2.8834 data: 0.0070 max mem: 33369 +Epoch: [14] [1230/1319] eta: 0:04:14 lr: 3.283248296080793e-05 loss: 0.0604 (0.0698) time: 2.8879 data: 0.0070 max mem: 33369 +Epoch: [14] [1240/1319] eta: 0:03:46 lr: 3.2823545574128904e-05 loss: 0.0645 (0.0698) time: 2.8851 data: 0.0069 max mem: 33369 +Epoch: [14] [1250/1319] eta: 0:03:17 lr: 3.2814607917050156e-05 loss: 0.0625 (0.0698) time: 2.8581 data: 0.0068 max mem: 33369 +Epoch: [14] [1260/1319] eta: 0:02:48 lr: 3.280566998948166e-05 loss: 0.0625 (0.0698) time: 2.8833 data: 0.0071 max mem: 33369 +Epoch: [14] [1270/1319] eta: 0:02:20 lr: 3.2796731791333364e-05 loss: 0.0618 (0.0698) time: 2.9111 data: 0.0070 max mem: 33369 +Epoch: [14] [1280/1319] eta: 0:01:51 lr: 3.278779332251511e-05 loss: 0.0618 (0.0697) time: 2.8924 data: 0.0070 max mem: 33369 +Epoch: [14] [1290/1319] eta: 0:01:23 lr: 3.277885458293673e-05 loss: 0.0659 (0.0698) time: 2.8789 data: 0.0070 max mem: 33369 +Epoch: [14] [1300/1319] eta: 0:00:54 lr: 3.276991557250796e-05 loss: 0.0711 (0.0698) time: 2.8779 data: 0.0070 max mem: 33369 +Epoch: [14] [1310/1319] eta: 0:00:25 lr: 3.276097629113851e-05 loss: 0.0822 (0.0699) time: 2.8913 data: 0.0070 max mem: 33369 +Epoch: [14] Total time: 1:02:58 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 2:02:34 time: 2.8583 data: 2.6531 max mem: 33369 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 100/2573] eta: 0:04:10 time: 0.0727 data: 0.0012 max mem: 33369 +Test: [ 200/2573] eta: 0:03:29 time: 0.0734 data: 0.0011 max mem: 33369 +Test: [ 300/2573] eta: 0:03:08 time: 0.0750 data: 0.0011 max mem: 33369 +Test: [ 400/2573] eta: 0:02:54 time: 0.0752 data: 0.0011 max mem: 33369 +Test: [ 500/2573] eta: 0:02:43 time: 0.0737 data: 0.0011 max mem: 33369 +Test: [ 600/2573] eta: 0:02:35 time: 0.0744 data: 0.0012 max mem: 33369 +Test: [ 700/2573] eta: 0:02:26 time: 0.0749 data: 0.0013 max mem: 33369 +Test: [ 800/2573] eta: 0:02:18 time: 0.0781 data: 0.0013 max mem: 33369 +Test: [ 900/2573] eta: 0:02:10 time: 0.0747 data: 0.0012 max mem: 33369 +Test: [1000/2573] eta: 0:02:01 time: 0.0746 data: 0.0012 max mem: 33369 +Test: [1100/2573] eta: 0:01:53 time: 0.0749 data: 0.0013 max mem: 33369 +Test: [1200/2573] eta: 0:01:45 time: 0.0747 data: 0.0013 max mem: 33369 +Test: [1300/2573] eta: 0:01:37 time: 0.0750 data: 0.0012 max mem: 33369 +Test: [1400/2573] eta: 0:01:30 time: 0.0731 data: 0.0012 max mem: 33369 +Test: [1500/2573] eta: 0:01:22 time: 0.0748 data: 0.0012 max mem: 33369 +Test: [1600/2573] eta: 0:01:14 time: 0.0784 data: 0.0013 max mem: 33369 +Test: [1700/2573] eta: 0:01:06 time: 0.0732 data: 0.0012 max mem: 33369 +Test: [1800/2573] eta: 0:00:59 time: 0.0767 data: 0.0012 max mem: 33369 +Test: [1900/2573] eta: 0:00:51 time: 0.0735 data: 0.0013 max mem: 33369 +Test: [2000/2573] eta: 0:00:43 time: 0.0749 data: 0.0013 max mem: 33369 +Test: [2100/2573] eta: 0:00:35 time: 0.0765 data: 0.0012 max mem: 33369 +Test: [2200/2573] eta: 0:00:28 time: 0.0767 data: 0.0013 max mem: 33369 +Test: [2300/2573] eta: 0:00:20 time: 0.0766 data: 0.0012 max mem: 33369 +Test: [2400/2573] eta: 0:00:13 time: 0.0717 data: 0.0013 max mem: 33369 +Test: [2500/2573] eta: 0:00:05 time: 0.0751 data: 0.0013 max mem: 33369 +Test: Total time: 0:03:15 +Final results: +Mean IoU is 61.47 + + precision@0.5 = 68.81 + precision@0.6 = 63.26 + precision@0.7 = 55.37 + precision@0.8 = 44.00 + precision@0.9 = 20.94 + overall IoU = 59.19 + +Average object IoU 61.46716881783928 +Overall IoU 59.19031524658203 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [15] [ 0/1319] eta: 3:23:13 lr: 3.275293070617704e-05 loss: 0.0811 (0.0811) time: 9.2447 data: 1.7404 max mem: 33369 +Epoch: [15] [ 10/1319] eta: 1:15:18 lr: 3.274399090977129e-05 loss: 0.0674 (0.0714) time: 3.4516 data: 0.1643 max mem: 33369 +Epoch: [15] [ 20/1319] eta: 1:08:28 lr: 3.2735050842162644e-05 loss: 0.0606 (0.0667) time: 2.8586 data: 0.0067 max mem: 33369 +Epoch: [15] [ 30/1319] eta: 1:05:36 lr: 3.2726110503260586e-05 loss: 0.0565 (0.0654) time: 2.8357 data: 0.0071 max mem: 33369 +Epoch: [15] [ 40/1319] eta: 1:04:11 lr: 3.271716989297451e-05 loss: 0.0539 (0.0611) time: 2.8526 data: 0.0075 max mem: 33369 +Epoch: [15] [ 50/1319] eta: 1:03:05 lr: 3.2708229011213794e-05 loss: 0.0540 (0.0628) time: 2.8718 data: 0.0080 max mem: 33369 +Epoch: [15] [ 60/1319] eta: 1:02:02 lr: 3.269928785788772e-05 loss: 0.0660 (0.0656) time: 2.8439 data: 0.0079 max mem: 33369 +Epoch: [15] [ 70/1319] eta: 1:01:20 lr: 3.2690346432905536e-05 loss: 0.0689 (0.0664) time: 2.8540 data: 0.0076 max mem: 33369 +Epoch: [15] [ 80/1319] eta: 1:00:37 lr: 3.268140473617642e-05 loss: 0.0619 (0.0654) time: 2.8718 data: 0.0082 max mem: 33369 +Epoch: [15] [ 90/1319] eta: 0:59:40 lr: 3.26724627676095e-05 loss: 0.0588 (0.0651) time: 2.7970 data: 0.0078 max mem: 33369 +Epoch: [15] [ 100/1319] eta: 0:59:11 lr: 3.266352052711384e-05 loss: 0.0649 (0.0662) time: 2.8240 data: 0.0072 max mem: 33369 +Epoch: [15] [ 110/1319] eta: 0:58:37 lr: 3.265457801459844e-05 loss: 0.0649 (0.0662) time: 2.8909 data: 0.0073 max mem: 33369 +Epoch: [15] [ 120/1319] eta: 0:58:04 lr: 3.2645635229972264e-05 loss: 0.0661 (0.0666) time: 2.8690 data: 0.0074 max mem: 33369 +Epoch: [15] [ 130/1319] eta: 0:57:30 lr: 3.2636692173144204e-05 loss: 0.0666 (0.0668) time: 2.8609 data: 0.0074 max mem: 33369 +Epoch: [15] [ 140/1319] eta: 0:56:59 lr: 3.2627748844023084e-05 loss: 0.0525 (0.0655) time: 2.8666 data: 0.0077 max mem: 33369 +Epoch: [15] [ 150/1319] eta: 0:56:26 lr: 3.261880524251768e-05 loss: 0.0525 (0.0652) time: 2.8633 data: 0.0074 max mem: 33369 +Epoch: [15] [ 160/1319] eta: 0:55:52 lr: 3.260986136853672e-05 loss: 0.0651 (0.0652) time: 2.8343 data: 0.0073 max mem: 33369 +Epoch: [15] [ 170/1319] eta: 0:55:20 lr: 3.2600917221988844e-05 loss: 0.0708 (0.0657) time: 2.8373 data: 0.0075 max mem: 33369 +Epoch: [15] [ 180/1319] eta: 0:54:51 lr: 3.259197280278268e-05 loss: 0.0733 (0.0656) time: 2.8706 data: 0.0073 max mem: 33369 +Epoch: [15] [ 190/1319] eta: 0:54:18 lr: 3.258302811082674e-05 loss: 0.0609 (0.0655) time: 2.8555 data: 0.0077 max mem: 33369 +Epoch: [15] [ 200/1319] eta: 0:53:47 lr: 3.257408314602953e-05 loss: 0.0584 (0.0654) time: 2.8331 data: 0.0077 max mem: 33369 +Epoch: [15] [ 210/1319] eta: 0:53:16 lr: 3.2565137908299456e-05 loss: 0.0620 (0.0663) time: 2.8399 data: 0.0071 max mem: 33369 +Epoch: [15] [ 220/1319] eta: 0:52:45 lr: 3.25561923975449e-05 loss: 0.0620 (0.0662) time: 2.8372 data: 0.0069 max mem: 33369 +Epoch: [15] [ 230/1319] eta: 0:52:15 lr: 3.2547246613674155e-05 loss: 0.0596 (0.0664) time: 2.8513 data: 0.0069 max mem: 33369 +Epoch: [15] [ 240/1319] eta: 0:51:42 lr: 3.253830055659547e-05 loss: 0.0585 (0.0668) time: 2.8224 data: 0.0069 max mem: 33369 +Epoch: [15] [ 250/1319] eta: 0:51:13 lr: 3.252935422621704e-05 loss: 0.0581 (0.0669) time: 2.8317 data: 0.0070 max mem: 33369 +Epoch: [15] [ 260/1319] eta: 0:50:44 lr: 3.252040762244701e-05 loss: 0.0614 (0.0672) time: 2.8769 data: 0.0071 max mem: 33369 +Epoch: [15] [ 270/1319] eta: 0:50:14 lr: 3.251146074519342e-05 loss: 0.0594 (0.0672) time: 2.8553 data: 0.0071 max mem: 33369 +Epoch: [15] [ 280/1319] eta: 0:49:44 lr: 3.2502513594364305e-05 loss: 0.0556 (0.0670) time: 2.8326 data: 0.0073 max mem: 33369 +Epoch: [15] [ 290/1319] eta: 0:49:16 lr: 3.2493566169867616e-05 loss: 0.0640 (0.0678) time: 2.8608 data: 0.0075 max mem: 33369 +Epoch: [15] [ 300/1319] eta: 0:48:46 lr: 3.248461847161124e-05 loss: 0.0634 (0.0675) time: 2.8658 data: 0.0070 max mem: 33369 +Epoch: [15] [ 310/1319] eta: 0:48:15 lr: 3.247567049950301e-05 loss: 0.0538 (0.0673) time: 2.8140 data: 0.0073 max mem: 33369 +Epoch: [15] [ 320/1319] eta: 0:47:43 lr: 3.246672225345071e-05 loss: 0.0579 (0.0671) time: 2.7854 data: 0.0075 max mem: 33369 +Epoch: [15] [ 330/1319] eta: 0:47:17 lr: 3.245777373336205e-05 loss: 0.0579 (0.0670) time: 2.8588 data: 0.0070 max mem: 33369 +Epoch: [15] [ 340/1319] eta: 0:46:48 lr: 3.244882493914469e-05 loss: 0.0641 (0.0671) time: 2.9111 data: 0.0070 max mem: 33369 +Epoch: [15] [ 350/1319] eta: 0:46:19 lr: 3.243987587070623e-05 loss: 0.0539 (0.0668) time: 2.8635 data: 0.0069 max mem: 33369 +Epoch: [15] [ 360/1319] eta: 0:45:49 lr: 3.24309265279542e-05 loss: 0.0505 (0.0666) time: 2.8392 data: 0.0072 max mem: 33369 +Epoch: [15] [ 370/1319] eta: 0:45:20 lr: 3.2421976910796087e-05 loss: 0.0509 (0.0664) time: 2.8383 data: 0.0077 max mem: 33369 +Epoch: [15] [ 380/1319] eta: 0:44:50 lr: 3.24130270191393e-05 loss: 0.0604 (0.0668) time: 2.8356 data: 0.0076 max mem: 33369 +Epoch: [15] [ 390/1319] eta: 0:44:20 lr: 3.2404076852891215e-05 loss: 0.0681 (0.0675) time: 2.8155 data: 0.0076 max mem: 33369 +Epoch: [15] [ 400/1319] eta: 0:43:53 lr: 3.239512641195912e-05 loss: 0.0703 (0.0675) time: 2.8569 data: 0.0076 max mem: 33369 +Epoch: [15] [ 410/1319] eta: 0:43:24 lr: 3.238617569625025e-05 loss: 0.0575 (0.0673) time: 2.8814 data: 0.0073 max mem: 33369 +Epoch: [15] [ 420/1319] eta: 0:42:55 lr: 3.23772247056718e-05 loss: 0.0512 (0.0670) time: 2.8555 data: 0.0072 max mem: 33369 +Epoch: [15] [ 430/1319] eta: 0:42:25 lr: 3.2368273440130875e-05 loss: 0.0530 (0.0673) time: 2.8280 data: 0.0076 max mem: 33369 +Epoch: [15] [ 440/1319] eta: 0:41:56 lr: 3.235932189953454e-05 loss: 0.0577 (0.0670) time: 2.8163 data: 0.0079 max mem: 33369 +Epoch: [15] [ 450/1319] eta: 0:41:26 lr: 3.23503700837898e-05 loss: 0.0581 (0.0671) time: 2.8235 data: 0.0080 max mem: 33369 +Epoch: [15] [ 460/1319] eta: 0:40:57 lr: 3.234141799280359e-05 loss: 0.0643 (0.0672) time: 2.8293 data: 0.0079 max mem: 33369 +Epoch: [15] [ 470/1319] eta: 0:40:27 lr: 3.2332465626482786e-05 loss: 0.0677 (0.0672) time: 2.7951 data: 0.0075 max mem: 33369 +Epoch: [15] [ 480/1319] eta: 0:39:59 lr: 3.232351298473422e-05 loss: 0.0680 (0.0674) time: 2.8306 data: 0.0073 max mem: 33369 +Epoch: [15] [ 490/1319] eta: 0:39:30 lr: 3.231456006746465e-05 loss: 0.0664 (0.0674) time: 2.8803 data: 0.0074 max mem: 33369 +Epoch: [15] [ 500/1319] eta: 0:39:02 lr: 3.2305606874580764e-05 loss: 0.0616 (0.0674) time: 2.8668 data: 0.0073 max mem: 33369 +Epoch: [15] [ 510/1319] eta: 0:38:34 lr: 3.229665340598921e-05 loss: 0.0599 (0.0672) time: 2.9039 data: 0.0068 max mem: 33369 +Epoch: [15] [ 520/1319] eta: 0:38:05 lr: 3.228769966159657e-05 loss: 0.0684 (0.0673) time: 2.8751 data: 0.0068 max mem: 33369 +Epoch: [15] [ 530/1319] eta: 0:37:37 lr: 3.227874564130935e-05 loss: 0.0675 (0.0671) time: 2.8558 data: 0.0069 max mem: 33369 +Epoch: [15] [ 540/1319] eta: 0:37:08 lr: 3.2269791345034015e-05 loss: 0.0526 (0.0669) time: 2.8633 data: 0.0071 max mem: 33369 +Epoch: [15] [ 550/1319] eta: 0:36:39 lr: 3.226083677267696e-05 loss: 0.0535 (0.0670) time: 2.8253 data: 0.0071 max mem: 33369 +Epoch: [15] [ 560/1319] eta: 0:36:10 lr: 3.225188192414452e-05 loss: 0.0630 (0.0669) time: 2.8369 data: 0.0072 max mem: 33369 +Epoch: [15] [ 570/1319] eta: 0:35:42 lr: 3.224292679934298e-05 loss: 0.0599 (0.0667) time: 2.8679 data: 0.0075 max mem: 33369 +Epoch: [15] [ 580/1319] eta: 0:35:13 lr: 3.2233971398178544e-05 loss: 0.0490 (0.0665) time: 2.8654 data: 0.0074 max mem: 33369 +Epoch: [15] [ 590/1319] eta: 0:34:45 lr: 3.2225015720557374e-05 loss: 0.0508 (0.0663) time: 2.9005 data: 0.0071 max mem: 33369 +Epoch: [15] [ 600/1319] eta: 0:34:17 lr: 3.221605976638556e-05 loss: 0.0604 (0.0664) time: 2.9113 data: 0.0075 max mem: 33369 +Epoch: [15] [ 610/1319] eta: 0:33:48 lr: 3.2207103535569134e-05 loss: 0.0614 (0.0665) time: 2.8651 data: 0.0080 max mem: 33369 +Epoch: [15] [ 620/1319] eta: 0:33:19 lr: 3.219814702801407e-05 loss: 0.0711 (0.0668) time: 2.8361 data: 0.0076 max mem: 33369 +Epoch: [15] [ 630/1319] eta: 0:32:51 lr: 3.218919024362627e-05 loss: 0.0761 (0.0669) time: 2.8742 data: 0.0075 max mem: 33369 +Epoch: [15] [ 640/1319] eta: 0:32:22 lr: 3.21802331823116e-05 loss: 0.0601 (0.0668) time: 2.8683 data: 0.0080 max mem: 33369 +Epoch: [15] [ 650/1319] eta: 0:31:53 lr: 3.2171275843975836e-05 loss: 0.0597 (0.0668) time: 2.8240 data: 0.0081 max mem: 33369 +Epoch: [15] [ 660/1319] eta: 0:31:24 lr: 3.21623182285247e-05 loss: 0.0669 (0.0669) time: 2.8267 data: 0.0080 max mem: 33369 +Epoch: [15] [ 670/1319] eta: 0:30:56 lr: 3.215336033586388e-05 loss: 0.0669 (0.0670) time: 2.8409 data: 0.0076 max mem: 33369 +Epoch: [15] [ 680/1319] eta: 0:30:27 lr: 3.214440216589895e-05 loss: 0.0603 (0.0670) time: 2.8488 data: 0.0072 max mem: 33369 +Epoch: [15] [ 690/1319] eta: 0:29:58 lr: 3.2135443718535476e-05 loss: 0.0549 (0.0669) time: 2.8524 data: 0.0078 max mem: 33369 +Epoch: [15] [ 700/1319] eta: 0:29:29 lr: 3.212648499367893e-05 loss: 0.0620 (0.0671) time: 2.8092 data: 0.0078 max mem: 33369 +Epoch: [15] [ 710/1319] eta: 0:29:01 lr: 3.211752599123473e-05 loss: 0.0591 (0.0669) time: 2.8549 data: 0.0071 max mem: 33369 +Epoch: [15] [ 720/1319] eta: 0:28:33 lr: 3.210856671110825e-05 loss: 0.0515 (0.0669) time: 2.9174 data: 0.0068 max mem: 33369 +Epoch: [15] [ 730/1319] eta: 0:28:04 lr: 3.2099607153204766e-05 loss: 0.0611 (0.0668) time: 2.8683 data: 0.0067 max mem: 33369 +Epoch: [15] [ 740/1319] eta: 0:27:36 lr: 3.209064731742954e-05 loss: 0.0597 (0.0667) time: 2.8647 data: 0.0068 max mem: 33369 +Epoch: [15] [ 750/1319] eta: 0:27:07 lr: 3.208168720368771e-05 loss: 0.0536 (0.0667) time: 2.8742 data: 0.0068 max mem: 33369 +Epoch: [15] [ 760/1319] eta: 0:26:39 lr: 3.2072726811884414e-05 loss: 0.0605 (0.0667) time: 2.8932 data: 0.0068 max mem: 33369 +Epoch: [15] [ 770/1319] eta: 0:26:10 lr: 3.20637661419247e-05 loss: 0.0601 (0.0665) time: 2.8589 data: 0.0072 max mem: 33369 +Epoch: [15] [ 780/1319] eta: 0:25:41 lr: 3.205480519371354e-05 loss: 0.0577 (0.0667) time: 2.8377 data: 0.0076 max mem: 33369 +Epoch: [15] [ 790/1319] eta: 0:25:12 lr: 3.204584396715587e-05 loss: 0.0415 (0.0664) time: 2.8455 data: 0.0080 max mem: 33369 +Epoch: [15] [ 800/1319] eta: 0:24:44 lr: 3.203688246215656e-05 loss: 0.0473 (0.0665) time: 2.8186 data: 0.0082 max mem: 33369 +Epoch: [15] [ 810/1319] eta: 0:24:15 lr: 3.20279206786204e-05 loss: 0.0609 (0.0665) time: 2.8277 data: 0.0081 max mem: 33369 +Epoch: [15] [ 820/1319] eta: 0:23:46 lr: 3.201895861645214e-05 loss: 0.0466 (0.0663) time: 2.8521 data: 0.0079 max mem: 33369 +Epoch: [15] [ 830/1319] eta: 0:23:18 lr: 3.2009996275556456e-05 loss: 0.0572 (0.0663) time: 2.8466 data: 0.0076 max mem: 33369 +Epoch: [15] [ 840/1319] eta: 0:22:49 lr: 3.200103365583796e-05 loss: 0.0594 (0.0666) time: 2.8431 data: 0.0074 max mem: 33369 +Epoch: [15] [ 850/1319] eta: 0:22:20 lr: 3.1992070757201206e-05 loss: 0.0566 (0.0666) time: 2.8158 data: 0.0069 max mem: 33369 +Epoch: [15] [ 860/1319] eta: 0:21:52 lr: 3.198310757955068e-05 loss: 0.0550 (0.0665) time: 2.8790 data: 0.0072 max mem: 33369 +Epoch: [15] [ 870/1319] eta: 0:21:22 lr: 3.197414412279081e-05 loss: 0.0622 (0.0665) time: 2.8141 data: 0.0074 max mem: 33369 +Epoch: [15] [ 880/1319] eta: 0:20:53 lr: 3.196518038682597e-05 loss: 0.0625 (0.0666) time: 2.6669 data: 0.0068 max mem: 33369 +Epoch: [15] [ 890/1319] eta: 0:20:24 lr: 3.1956216371560456e-05 loss: 0.0609 (0.0666) time: 2.7885 data: 0.0071 max mem: 33369 +Epoch: [15] [ 900/1319] eta: 0:19:56 lr: 3.194725207689851e-05 loss: 0.0601 (0.0665) time: 2.8437 data: 0.0079 max mem: 33369 +Epoch: [15] [ 910/1319] eta: 0:19:27 lr: 3.1938287502744314e-05 loss: 0.0613 (0.0665) time: 2.8381 data: 0.0077 max mem: 33369 +Epoch: [15] [ 920/1319] eta: 0:18:58 lr: 3.192932264900198e-05 loss: 0.0646 (0.0665) time: 2.8485 data: 0.0076 max mem: 33369 +Epoch: [15] [ 930/1319] eta: 0:18:30 lr: 3.192035751557555e-05 loss: 0.0641 (0.0665) time: 2.8165 data: 0.0080 max mem: 33369 +Epoch: [15] [ 940/1319] eta: 0:18:01 lr: 3.1911392102369026e-05 loss: 0.0615 (0.0666) time: 2.8121 data: 0.0081 max mem: 33369 +Epoch: [15] [ 950/1319] eta: 0:17:32 lr: 3.1902426409286326e-05 loss: 0.0614 (0.0666) time: 2.7971 data: 0.0079 max mem: 33369 +Epoch: [15] [ 960/1319] eta: 0:17:04 lr: 3.189346043623133e-05 loss: 0.0554 (0.0665) time: 2.8124 data: 0.0076 max mem: 33369 +Epoch: [15] [ 970/1319] eta: 0:16:35 lr: 3.1884494183107815e-05 loss: 0.0614 (0.0667) time: 2.8549 data: 0.0076 max mem: 33369 +Epoch: [15] [ 980/1319] eta: 0:16:07 lr: 3.187552764981953e-05 loss: 0.0630 (0.0667) time: 2.8766 data: 0.0079 max mem: 33369 +Epoch: [15] [ 990/1319] eta: 0:15:38 lr: 3.186656083627014e-05 loss: 0.0570 (0.0667) time: 2.8867 data: 0.0075 max mem: 33369 +Epoch: [15] [1000/1319] eta: 0:15:10 lr: 3.1857593742363276e-05 loss: 0.0660 (0.0669) time: 2.8594 data: 0.0073 max mem: 33369 +Epoch: [15] [1010/1319] eta: 0:14:41 lr: 3.184862636800246e-05 loss: 0.0552 (0.0668) time: 2.8105 data: 0.0078 max mem: 33369 +Epoch: [15] [1020/1319] eta: 0:14:12 lr: 3.183965871309119e-05 loss: 0.0548 (0.0668) time: 2.7956 data: 0.0084 max mem: 33369 +Epoch: [15] [1030/1319] eta: 0:13:44 lr: 3.1830690777532884e-05 loss: 0.0612 (0.0667) time: 2.7995 data: 0.0080 max mem: 33369 +Epoch: [15] [1040/1319] eta: 0:13:15 lr: 3.182172256123091e-05 loss: 0.0628 (0.0668) time: 2.8473 data: 0.0075 max mem: 33369 +Epoch: [15] [1050/1319] eta: 0:12:47 lr: 3.181275406408854e-05 loss: 0.0539 (0.0666) time: 2.8815 data: 0.0074 max mem: 33369 +Epoch: [15] [1060/1319] eta: 0:12:18 lr: 3.180378528600901e-05 loss: 0.0553 (0.0667) time: 2.8725 data: 0.0071 max mem: 33369 +Epoch: [15] [1070/1319] eta: 0:11:50 lr: 3.17948162268955e-05 loss: 0.0691 (0.0669) time: 2.8366 data: 0.0075 max mem: 33369 +Epoch: [15] [1080/1319] eta: 0:11:21 lr: 3.17858468866511e-05 loss: 0.0612 (0.0670) time: 2.8716 data: 0.0075 max mem: 33369 +Epoch: [15] [1090/1319] eta: 0:10:53 lr: 3.177687726517885e-05 loss: 0.0656 (0.0670) time: 2.8916 data: 0.0071 max mem: 33369 +Epoch: [15] [1100/1319] eta: 0:10:24 lr: 3.1767907362381725e-05 loss: 0.0627 (0.0670) time: 2.8330 data: 0.0072 max mem: 33369 +Epoch: [15] [1110/1319] eta: 0:09:56 lr: 3.175893717816263e-05 loss: 0.0604 (0.0670) time: 2.8042 data: 0.0070 max mem: 33369 +Epoch: [15] [1120/1319] eta: 0:09:27 lr: 3.174996671242443e-05 loss: 0.0598 (0.0670) time: 2.8457 data: 0.0071 max mem: 33369 +Epoch: [15] [1130/1319] eta: 0:08:59 lr: 3.1740995965069895e-05 loss: 0.0571 (0.0669) time: 2.8956 data: 0.0071 max mem: 33369 +Epoch: [15] [1140/1319] eta: 0:08:30 lr: 3.173202493600174e-05 loss: 0.0606 (0.0670) time: 2.8911 data: 0.0067 max mem: 33369 +Epoch: [15] [1150/1319] eta: 0:08:02 lr: 3.172305362512263e-05 loss: 0.0776 (0.0671) time: 2.8791 data: 0.0068 max mem: 33369 +Epoch: [15] [1160/1319] eta: 0:07:33 lr: 3.171408203233514e-05 loss: 0.0787 (0.0673) time: 2.8670 data: 0.0071 max mem: 33369 +Epoch: [15] [1170/1319] eta: 0:07:05 lr: 3.170511015754181e-05 loss: 0.0744 (0.0674) time: 2.8732 data: 0.0070 max mem: 33369 +Epoch: [15] [1180/1319] eta: 0:06:36 lr: 3.16961380006451e-05 loss: 0.0654 (0.0673) time: 2.8323 data: 0.0069 max mem: 33369 +Epoch: [15] [1190/1319] eta: 0:06:08 lr: 3.16871655615474e-05 loss: 0.0636 (0.0674) time: 2.8863 data: 0.0072 max mem: 33369 +Epoch: [15] [1200/1319] eta: 0:05:39 lr: 3.1678192840151044e-05 loss: 0.0593 (0.0674) time: 2.9170 data: 0.0075 max mem: 33369 +Epoch: [15] [1210/1319] eta: 0:05:11 lr: 3.16692198363583e-05 loss: 0.0580 (0.0674) time: 2.8532 data: 0.0076 max mem: 33369 +Epoch: [15] [1220/1319] eta: 0:04:42 lr: 3.1660246550071386e-05 loss: 0.0501 (0.0674) time: 2.8305 data: 0.0077 max mem: 33369 +Epoch: [15] [1230/1319] eta: 0:04:14 lr: 3.165127298119242e-05 loss: 0.0742 (0.0676) time: 2.8504 data: 0.0075 max mem: 33369 +Epoch: [15] [1240/1319] eta: 0:03:45 lr: 3.164229912962349e-05 loss: 0.0742 (0.0676) time: 2.8832 data: 0.0073 max mem: 33369 +Epoch: [15] [1250/1319] eta: 0:03:16 lr: 3.163332499526659e-05 loss: 0.0578 (0.0676) time: 2.8688 data: 0.0072 max mem: 33369 +Epoch: [15] [1260/1319] eta: 0:02:48 lr: 3.162435057802369e-05 loss: 0.0578 (0.0676) time: 2.7961 data: 0.0069 max mem: 33369 +Epoch: [15] [1270/1319] eta: 0:02:19 lr: 3.161537587779665e-05 loss: 0.0557 (0.0675) time: 2.8219 data: 0.0070 max mem: 33369 +Epoch: [15] [1280/1319] eta: 0:01:51 lr: 3.1606400894487287e-05 loss: 0.0658 (0.0676) time: 2.8801 data: 0.0077 max mem: 33369 +Epoch: [15] [1290/1319] eta: 0:01:22 lr: 3.159742562799735e-05 loss: 0.0756 (0.0677) time: 2.8593 data: 0.0077 max mem: 33369 +Epoch: [15] [1300/1319] eta: 0:00:54 lr: 3.158845007822852e-05 loss: 0.0756 (0.0678) time: 2.8206 data: 0.0074 max mem: 33369 +Epoch: [15] [1310/1319] eta: 0:00:25 lr: 3.1579474245082424e-05 loss: 0.0631 (0.0678) time: 2.8156 data: 0.0079 max mem: 33369 +Epoch: [15] Total time: 1:02:44 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 2:02:14 time: 2.8506 data: 2.7083 max mem: 33369 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 100/2573] eta: 0:04:09 time: 0.0728 data: 0.0012 max mem: 33369 +Test: [ 200/2573] eta: 0:03:29 time: 0.0741 data: 0.0012 max mem: 33369 +Test: [ 300/2573] eta: 0:03:08 time: 0.0751 data: 0.0011 max mem: 33369 +Test: [ 400/2573] eta: 0:02:55 time: 0.0753 data: 0.0011 max mem: 33369 +Test: [ 500/2573] eta: 0:02:44 time: 0.0740 data: 0.0012 max mem: 33369 +Test: [ 600/2573] eta: 0:02:34 time: 0.0738 data: 0.0012 max mem: 33369 +Test: [ 700/2573] eta: 0:02:26 time: 0.0763 data: 0.0015 max mem: 33369 +Test: [ 800/2573] eta: 0:02:18 time: 0.0780 data: 0.0012 max mem: 33369 +Test: [ 900/2573] eta: 0:02:10 time: 0.0748 data: 0.0013 max mem: 33369 +Test: [1000/2573] eta: 0:02:01 time: 0.0747 data: 0.0013 max mem: 33369 +Test: [1100/2573] eta: 0:01:53 time: 0.0748 data: 0.0012 max mem: 33369 +Test: [1200/2573] eta: 0:01:45 time: 0.0747 data: 0.0012 max mem: 33369 +Test: [1300/2573] eta: 0:01:37 time: 0.0749 data: 0.0012 max mem: 33369 +Test: [1400/2573] eta: 0:01:29 time: 0.0731 data: 0.0012 max mem: 33369 +Test: [1500/2573] eta: 0:01:22 time: 0.0748 data: 0.0012 max mem: 33369 +Test: [1600/2573] eta: 0:01:14 time: 0.0784 data: 0.0013 max mem: 33369 +Test: [1700/2573] eta: 0:01:06 time: 0.0733 data: 0.0012 max mem: 33369 +Test: [1800/2573] eta: 0:00:59 time: 0.0766 data: 0.0013 max mem: 33369 +Test: [1900/2573] eta: 0:00:51 time: 0.0734 data: 0.0012 max mem: 33369 +Test: [2000/2573] eta: 0:00:43 time: 0.0751 data: 0.0013 max mem: 33369 +Test: [2100/2573] eta: 0:00:35 time: 0.0766 data: 0.0012 max mem: 33369 +Test: [2200/2573] eta: 0:00:28 time: 0.0767 data: 0.0012 max mem: 33369 +Test: [2300/2573] eta: 0:00:20 time: 0.0767 data: 0.0012 max mem: 33369 +Test: [2400/2573] eta: 0:00:13 time: 0.0719 data: 0.0013 max mem: 33369 +Test: [2500/2573] eta: 0:00:05 time: 0.0752 data: 0.0013 max mem: 33369 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: Total time: 0:03:15 +Final results: +Mean IoU is 61.83 + + precision@0.5 = 69.34 + precision@0.6 = 63.81 + precision@0.7 = 56.37 + precision@0.8 = 44.30 + precision@0.9 = 21.00 + overall IoU = 59.77 + +Average object IoU 61.83041364498949 +Overall IoU 59.76832962036133 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [16] [ 0/1319] eta: 3:19:07 lr: 3.157139575288201e-05 loss: 0.0568 (0.0568) time: 9.0582 data: 1.4332 max mem: 33369 +Epoch: [16] [ 10/1319] eta: 1:14:43 lr: 3.1562419381047834e-05 loss: 0.0568 (0.0575) time: 3.4251 data: 0.1363 max mem: 33369 +Epoch: [16] [ 20/1319] eta: 1:07:16 lr: 3.155344272555071e-05 loss: 0.0616 (0.0632) time: 2.8098 data: 0.0065 max mem: 33369 +Epoch: [16] [ 30/1319] eta: 1:05:13 lr: 3.154446578629201e-05 loss: 0.0626 (0.0632) time: 2.8217 data: 0.0069 max mem: 33369 +Epoch: [16] [ 40/1319] eta: 1:03:37 lr: 3.153548856317304e-05 loss: 0.0559 (0.0607) time: 2.8565 data: 0.0072 max mem: 33369 +Epoch: [16] [ 50/1319] eta: 1:02:29 lr: 3.152651105609501e-05 loss: 0.0413 (0.0574) time: 2.8280 data: 0.0075 max mem: 33369 +Epoch: [16] [ 60/1319] eta: 1:01:34 lr: 3.1517533264959104e-05 loss: 0.0470 (0.0571) time: 2.8315 data: 0.0076 max mem: 33369 +Epoch: [16] [ 70/1319] eta: 1:00:48 lr: 3.150855518966642e-05 loss: 0.0564 (0.0598) time: 2.8354 data: 0.0074 max mem: 33369 +Epoch: [16] [ 80/1319] eta: 1:00:05 lr: 3.1499576830118e-05 loss: 0.0660 (0.0604) time: 2.8362 data: 0.0077 max mem: 33369 +Epoch: [16] [ 90/1319] eta: 0:59:33 lr: 3.14905981862148e-05 loss: 0.0563 (0.0596) time: 2.8591 data: 0.0074 max mem: 33369 +Epoch: [16] [ 100/1319] eta: 0:58:54 lr: 3.1481619257857746e-05 loss: 0.0587 (0.0610) time: 2.8556 data: 0.0069 max mem: 33369 +Epoch: [16] [ 110/1319] eta: 0:58:22 lr: 3.147264004494766e-05 loss: 0.0612 (0.0606) time: 2.8515 data: 0.0069 max mem: 33369 +Epoch: [16] [ 120/1319] eta: 0:57:47 lr: 3.1463660547385324e-05 loss: 0.0512 (0.0609) time: 2.8563 data: 0.0072 max mem: 33369 +Epoch: [16] [ 130/1319] eta: 0:57:19 lr: 3.1454680765071425e-05 loss: 0.0551 (0.0614) time: 2.8679 data: 0.0072 max mem: 33369 +Epoch: [16] [ 140/1319] eta: 0:56:44 lr: 3.1445700697906627e-05 loss: 0.0463 (0.0604) time: 2.8589 data: 0.0071 max mem: 33369 +Epoch: [16] [ 150/1319] eta: 0:56:15 lr: 3.1436720345791495e-05 loss: 0.0475 (0.0611) time: 2.8547 data: 0.0076 max mem: 33369 +Epoch: [16] [ 160/1319] eta: 0:55:48 lr: 3.1427739708626534e-05 loss: 0.0483 (0.0607) time: 2.8984 data: 0.0075 max mem: 33369 +Epoch: [16] [ 170/1319] eta: 0:55:13 lr: 3.141875878631219e-05 loss: 0.0526 (0.0604) time: 2.8541 data: 0.0068 max mem: 33369 +Epoch: [16] [ 180/1319] eta: 0:54:46 lr: 3.140977757874883e-05 loss: 0.0526 (0.0603) time: 2.8605 data: 0.0073 max mem: 33369 +Epoch: [16] [ 190/1319] eta: 0:54:15 lr: 3.140079608583676e-05 loss: 0.0585 (0.0608) time: 2.8782 data: 0.0081 max mem: 33369 +Epoch: [16] [ 200/1319] eta: 0:53:44 lr: 3.1391814307476244e-05 loss: 0.0585 (0.0604) time: 2.8404 data: 0.0083 max mem: 33369 +Epoch: [16] [ 210/1319] eta: 0:53:12 lr: 3.138283224356744e-05 loss: 0.0467 (0.0603) time: 2.8372 data: 0.0083 max mem: 33369 +Epoch: [16] [ 220/1319] eta: 0:52:42 lr: 3.137384989401046e-05 loss: 0.0547 (0.0615) time: 2.8433 data: 0.0076 max mem: 33369 +Epoch: [16] [ 230/1319] eta: 0:52:10 lr: 3.136486725870535e-05 loss: 0.0531 (0.0616) time: 2.8319 data: 0.0072 max mem: 33369 +Epoch: [16] [ 240/1319] eta: 0:51:40 lr: 3.1355884337552074e-05 loss: 0.0556 (0.0614) time: 2.8222 data: 0.0076 max mem: 33369 +Epoch: [16] [ 250/1319] eta: 0:51:07 lr: 3.1346901130450554e-05 loss: 0.0556 (0.0611) time: 2.8058 data: 0.0073 max mem: 33369 +Epoch: [16] [ 260/1319] eta: 0:50:39 lr: 3.133791763730062e-05 loss: 0.0587 (0.0624) time: 2.8309 data: 0.0071 max mem: 33369 +Epoch: [16] [ 270/1319] eta: 0:50:08 lr: 3.132893385800206e-05 loss: 0.0647 (0.0625) time: 2.8470 data: 0.0080 max mem: 33369 +Epoch: [16] [ 280/1319] eta: 0:49:41 lr: 3.131994979245456e-05 loss: 0.0593 (0.0625) time: 2.8642 data: 0.0078 max mem: 33369 +Epoch: [16] [ 290/1319] eta: 0:49:14 lr: 3.131096544055778e-05 loss: 0.0584 (0.0629) time: 2.9225 data: 0.0071 max mem: 33369 +Epoch: [16] [ 300/1319] eta: 0:48:46 lr: 3.130198080221128e-05 loss: 0.0606 (0.0628) time: 2.9064 data: 0.0074 max mem: 33369 +Epoch: [16] [ 310/1319] eta: 0:48:16 lr: 3.129299587731458e-05 loss: 0.0555 (0.0626) time: 2.8671 data: 0.0075 max mem: 33369 +Epoch: [16] [ 320/1319] eta: 0:47:45 lr: 3.1284010665767105e-05 loss: 0.0601 (0.0628) time: 2.8170 data: 0.0072 max mem: 33369 +Epoch: [16] [ 330/1319] eta: 0:47:18 lr: 3.1275025167468235e-05 loss: 0.0585 (0.0626) time: 2.8515 data: 0.0072 max mem: 33369 +Epoch: [16] [ 340/1319] eta: 0:46:50 lr: 3.126603938231727e-05 loss: 0.0485 (0.0629) time: 2.8998 data: 0.0073 max mem: 33369 +Epoch: [16] [ 350/1319] eta: 0:46:20 lr: 3.1257053310213444e-05 loss: 0.0560 (0.0629) time: 2.8665 data: 0.0077 max mem: 33369 +Epoch: [16] [ 360/1319] eta: 0:45:51 lr: 3.124806695105593e-05 loss: 0.0560 (0.0626) time: 2.8537 data: 0.0079 max mem: 33369 +Epoch: [16] [ 370/1319] eta: 0:45:22 lr: 3.1239080304743815e-05 loss: 0.0560 (0.0625) time: 2.8550 data: 0.0076 max mem: 33369 +Epoch: [16] [ 380/1319] eta: 0:44:53 lr: 3.123009337117616e-05 loss: 0.0555 (0.0624) time: 2.8483 data: 0.0072 max mem: 33369 +Epoch: [16] [ 390/1319] eta: 0:44:24 lr: 3.12211061502519e-05 loss: 0.0555 (0.0627) time: 2.8540 data: 0.0069 max mem: 33369 +Epoch: [16] [ 400/1319] eta: 0:43:53 lr: 3.121211864186995e-05 loss: 0.0585 (0.0626) time: 2.8024 data: 0.0070 max mem: 33369 +Epoch: [16] [ 410/1319] eta: 0:43:26 lr: 3.120313084592913e-05 loss: 0.0673 (0.0629) time: 2.8512 data: 0.0071 max mem: 33369 +Epoch: [16] [ 420/1319] eta: 0:42:58 lr: 3.119414276232821e-05 loss: 0.0569 (0.0628) time: 2.9256 data: 0.0071 max mem: 33369 +Epoch: [16] [ 430/1319] eta: 0:42:28 lr: 3.118515439096588e-05 loss: 0.0526 (0.0630) time: 2.8581 data: 0.0069 max mem: 33369 +Epoch: [16] [ 440/1319] eta: 0:42:00 lr: 3.117616573174077e-05 loss: 0.0571 (0.0632) time: 2.8597 data: 0.0068 max mem: 33369 +Epoch: [16] [ 450/1319] eta: 0:41:31 lr: 3.116717678455143e-05 loss: 0.0515 (0.0632) time: 2.8712 data: 0.0069 max mem: 33369 +Epoch: [16] [ 460/1319] eta: 0:41:02 lr: 3.115818754929635e-05 loss: 0.0597 (0.0631) time: 2.8341 data: 0.0073 max mem: 33369 +Epoch: [16] [ 470/1319] eta: 0:40:32 lr: 3.1149198025873954e-05 loss: 0.0583 (0.0630) time: 2.8130 data: 0.0073 max mem: 33369 +Epoch: [16] [ 480/1319] eta: 0:40:04 lr: 3.1140208214182586e-05 loss: 0.0527 (0.0629) time: 2.8638 data: 0.0071 max mem: 33369 +Epoch: [16] [ 490/1319] eta: 0:39:36 lr: 3.113121811412054e-05 loss: 0.0527 (0.0629) time: 2.9136 data: 0.0073 max mem: 33369 +Epoch: [16] [ 500/1319] eta: 0:39:07 lr: 3.1122227725586026e-05 loss: 0.0525 (0.0627) time: 2.8677 data: 0.0078 max mem: 33369 +Epoch: [16] [ 510/1319] eta: 0:38:38 lr: 3.1113237048477186e-05 loss: 0.0570 (0.0628) time: 2.8418 data: 0.0079 max mem: 33369 +Epoch: [16] [ 520/1319] eta: 0:38:09 lr: 3.11042460826921e-05 loss: 0.0587 (0.0627) time: 2.8467 data: 0.0075 max mem: 33369 +Epoch: [16] [ 530/1319] eta: 0:37:39 lr: 3.1095254828128786e-05 loss: 0.0566 (0.0626) time: 2.8276 data: 0.0078 max mem: 33369 +Epoch: [16] [ 540/1319] eta: 0:37:10 lr: 3.108626328468517e-05 loss: 0.0548 (0.0625) time: 2.8228 data: 0.0081 max mem: 33369 +Epoch: [16] [ 550/1319] eta: 0:36:41 lr: 3.107727145225915e-05 loss: 0.0545 (0.0626) time: 2.8129 data: 0.0076 max mem: 33369 +Epoch: [16] [ 560/1319] eta: 0:36:13 lr: 3.106827933074849e-05 loss: 0.0484 (0.0623) time: 2.8507 data: 0.0073 max mem: 33369 +Epoch: [16] [ 570/1319] eta: 0:35:45 lr: 3.105928692005095e-05 loss: 0.0537 (0.0624) time: 2.9029 data: 0.0071 max mem: 33369 +Epoch: [16] [ 580/1319] eta: 0:35:16 lr: 3.105029422006419e-05 loss: 0.0537 (0.0623) time: 2.8855 data: 0.0069 max mem: 33369 +Epoch: [16] [ 590/1319] eta: 0:34:48 lr: 3.104130123068579e-05 loss: 0.0576 (0.0625) time: 2.8914 data: 0.0071 max mem: 33369 +Epoch: [16] [ 600/1319] eta: 0:34:19 lr: 3.10323079518133e-05 loss: 0.0576 (0.0625) time: 2.8814 data: 0.0074 max mem: 33369 +Epoch: [16] [ 610/1319] eta: 0:33:50 lr: 3.102331438334416e-05 loss: 0.0647 (0.0627) time: 2.8390 data: 0.0079 max mem: 33369 +Epoch: [16] [ 620/1319] eta: 0:33:21 lr: 3.1014320525175755e-05 loss: 0.0687 (0.0626) time: 2.8192 data: 0.0078 max mem: 33369 +Epoch: [16] [ 630/1319] eta: 0:32:53 lr: 3.100532637720542e-05 loss: 0.0569 (0.0626) time: 2.8649 data: 0.0073 max mem: 33369 +Epoch: [16] [ 640/1319] eta: 0:32:24 lr: 3.099633193933038e-05 loss: 0.0584 (0.0626) time: 2.8725 data: 0.0075 max mem: 33369 +Epoch: [16] [ 650/1319] eta: 0:31:55 lr: 3.098733721144784e-05 loss: 0.0578 (0.0626) time: 2.8247 data: 0.0079 max mem: 33369 +Epoch: [16] [ 660/1319] eta: 0:31:26 lr: 3.097834219345489e-05 loss: 0.0660 (0.0628) time: 2.8329 data: 0.0082 max mem: 33369 +Epoch: [16] [ 670/1319] eta: 0:30:57 lr: 3.0969346885248574e-05 loss: 0.0600 (0.0627) time: 2.8423 data: 0.0079 max mem: 33369 +Epoch: [16] [ 680/1319] eta: 0:30:29 lr: 3.0960351286725865e-05 loss: 0.0497 (0.0629) time: 2.8635 data: 0.0074 max mem: 33369 +Epoch: [16] [ 690/1319] eta: 0:30:00 lr: 3.0951355397783653e-05 loss: 0.0574 (0.0631) time: 2.8844 data: 0.0072 max mem: 33369 +Epoch: [16] [ 700/1319] eta: 0:29:31 lr: 3.0942359218318776e-05 loss: 0.0584 (0.0629) time: 2.8193 data: 0.0069 max mem: 33369 +Epoch: [16] [ 710/1319] eta: 0:29:02 lr: 3.0933362748228e-05 loss: 0.0560 (0.0631) time: 2.8218 data: 0.0070 max mem: 33369 +Epoch: [16] [ 720/1319] eta: 0:28:34 lr: 3.092436598740799e-05 loss: 0.0566 (0.0631) time: 2.8646 data: 0.0072 max mem: 33369 +Epoch: [16] [ 730/1319] eta: 0:28:05 lr: 3.09153689357554e-05 loss: 0.0566 (0.0631) time: 2.8281 data: 0.0077 max mem: 33369 +Epoch: [16] [ 740/1319] eta: 0:27:36 lr: 3.090637159316675e-05 loss: 0.0528 (0.0630) time: 2.8360 data: 0.0077 max mem: 33369 +Epoch: [16] [ 750/1319] eta: 0:27:07 lr: 3.089737395953854e-05 loss: 0.0545 (0.0631) time: 2.8385 data: 0.0077 max mem: 33369 +Epoch: [16] [ 760/1319] eta: 0:26:38 lr: 3.088837603476717e-05 loss: 0.0545 (0.0633) time: 2.8443 data: 0.0079 max mem: 33369 +Epoch: [16] [ 770/1319] eta: 0:26:10 lr: 3.087937781874897e-05 loss: 0.0503 (0.0632) time: 2.8479 data: 0.0075 max mem: 33369 +Epoch: [16] [ 780/1319] eta: 0:25:41 lr: 3.087037931138022e-05 loss: 0.0528 (0.0633) time: 2.8279 data: 0.0068 max mem: 33369 +Epoch: [16] [ 790/1319] eta: 0:25:12 lr: 3.086138051255712e-05 loss: 0.0536 (0.0632) time: 2.8501 data: 0.0069 max mem: 33369 +Epoch: [16] [ 800/1319] eta: 0:24:44 lr: 3.085238142217579e-05 loss: 0.0478 (0.0630) time: 2.8718 data: 0.0072 max mem: 33369 +Epoch: [16] [ 810/1319] eta: 0:24:15 lr: 3.084338204013227e-05 loss: 0.0466 (0.0631) time: 2.8728 data: 0.0071 max mem: 33369 +Epoch: [16] [ 820/1319] eta: 0:23:47 lr: 3.0834382366322574e-05 loss: 0.0511 (0.0630) time: 2.8776 data: 0.0070 max mem: 33369 +Epoch: [16] [ 830/1319] eta: 0:23:18 lr: 3.08253824006426e-05 loss: 0.0580 (0.0631) time: 2.8655 data: 0.0071 max mem: 33369 +Epoch: [16] [ 840/1319] eta: 0:22:50 lr: 3.08163821429882e-05 loss: 0.0614 (0.0630) time: 2.8610 data: 0.0072 max mem: 33369 +Epoch: [16] [ 850/1319] eta: 0:22:21 lr: 3.0807381593255134e-05 loss: 0.0510 (0.0630) time: 2.8505 data: 0.0070 max mem: 33369 +Epoch: [16] [ 860/1319] eta: 0:21:52 lr: 3.079838075133912e-05 loss: 0.0521 (0.0631) time: 2.8513 data: 0.0071 max mem: 33369 +Epoch: [16] [ 870/1319] eta: 0:21:24 lr: 3.0789379617135774e-05 loss: 0.0538 (0.0632) time: 2.8870 data: 0.0072 max mem: 33369 +Epoch: [16] [ 880/1319] eta: 0:20:55 lr: 3.078037819054066e-05 loss: 0.0662 (0.0632) time: 2.8883 data: 0.0072 max mem: 33369 +Epoch: [16] [ 890/1319] eta: 0:20:27 lr: 3.0771376471449264e-05 loss: 0.0573 (0.0631) time: 2.8783 data: 0.0071 max mem: 33369 +Epoch: [16] [ 900/1319] eta: 0:19:58 lr: 3.076237445975701e-05 loss: 0.0516 (0.0632) time: 2.8911 data: 0.0073 max mem: 33369 +Epoch: [16] [ 910/1319] eta: 0:19:30 lr: 3.075337215535924e-05 loss: 0.0516 (0.0631) time: 2.8916 data: 0.0075 max mem: 33369 +Epoch: [16] [ 920/1319] eta: 0:19:01 lr: 3.074436955815122e-05 loss: 0.0451 (0.0630) time: 2.8587 data: 0.0073 max mem: 33369 +Epoch: [16] [ 930/1319] eta: 0:18:32 lr: 3.073536666802816e-05 loss: 0.0489 (0.0630) time: 2.7894 data: 0.0071 max mem: 33369 +Epoch: [16] [ 940/1319] eta: 0:18:04 lr: 3.0726363484885186e-05 loss: 0.0540 (0.0630) time: 2.8526 data: 0.0075 max mem: 33369 +Epoch: [16] [ 950/1319] eta: 0:17:35 lr: 3.0717360008617356e-05 loss: 0.0534 (0.0629) time: 2.8987 data: 0.0079 max mem: 33369 +Epoch: [16] [ 960/1319] eta: 0:17:06 lr: 3.070835623911966e-05 loss: 0.0548 (0.0629) time: 2.8376 data: 0.0076 max mem: 33369 +Epoch: [16] [ 970/1319] eta: 0:16:38 lr: 3.069935217628702e-05 loss: 0.0544 (0.0628) time: 2.8247 data: 0.0075 max mem: 33369 +Epoch: [16] [ 980/1319] eta: 0:16:09 lr: 3.0690347820014265e-05 loss: 0.0544 (0.0628) time: 2.8439 data: 0.0076 max mem: 33369 +Epoch: [16] [ 990/1319] eta: 0:15:41 lr: 3.068134317019618e-05 loss: 0.0524 (0.0627) time: 2.8660 data: 0.0076 max mem: 33369 +Epoch: [16] [1000/1319] eta: 0:15:12 lr: 3.0672338226727455e-05 loss: 0.0523 (0.0627) time: 2.9059 data: 0.0071 max mem: 33369 +Epoch: [16] [1010/1319] eta: 0:14:44 lr: 3.066333298950271e-05 loss: 0.0531 (0.0626) time: 2.9053 data: 0.0069 max mem: 33369 +Epoch: [16] [1020/1319] eta: 0:14:15 lr: 3.065432745841652e-05 loss: 0.0501 (0.0625) time: 2.8517 data: 0.0070 max mem: 33369 +Epoch: [16] [1030/1319] eta: 0:13:46 lr: 3.064532163336335e-05 loss: 0.0548 (0.0626) time: 2.8560 data: 0.0071 max mem: 33369 +Epoch: [16] [1040/1319] eta: 0:13:18 lr: 3.063631551423762e-05 loss: 0.0575 (0.0625) time: 2.8886 data: 0.0071 max mem: 33369 +Epoch: [16] [1050/1319] eta: 0:12:49 lr: 3.062730910093366e-05 loss: 0.0442 (0.0624) time: 2.9072 data: 0.0071 max mem: 33369 +Epoch: [16] [1060/1319] eta: 0:12:21 lr: 3.061830239334574e-05 loss: 0.0430 (0.0623) time: 2.8756 data: 0.0076 max mem: 33369 +Epoch: [16] [1070/1319] eta: 0:11:52 lr: 3.0609295391368055e-05 loss: 0.0498 (0.0624) time: 2.8462 data: 0.0079 max mem: 33369 +Epoch: [16] [1080/1319] eta: 0:11:23 lr: 3.060028809489473e-05 loss: 0.0511 (0.0623) time: 2.8144 data: 0.0072 max mem: 33369 +Epoch: [16] [1090/1319] eta: 0:10:55 lr: 3.059128050381978e-05 loss: 0.0496 (0.0622) time: 2.8462 data: 0.0074 max mem: 33369 +Epoch: [16] [1100/1319] eta: 0:10:26 lr: 3.058227261803723e-05 loss: 0.0466 (0.0622) time: 2.8797 data: 0.0082 max mem: 33369 +Epoch: [16] [1110/1319] eta: 0:09:57 lr: 3.0573264437440946e-05 loss: 0.0661 (0.0623) time: 2.8401 data: 0.0081 max mem: 33369 +Epoch: [16] [1120/1319] eta: 0:09:29 lr: 3.056425596192476e-05 loss: 0.0640 (0.0623) time: 2.8313 data: 0.0080 max mem: 33369 +Epoch: [16] [1130/1319] eta: 0:09:00 lr: 3.0555247191382436e-05 loss: 0.0537 (0.0623) time: 2.8500 data: 0.0075 max mem: 33369 +Epoch: [16] [1140/1319] eta: 0:08:32 lr: 3.054623812570766e-05 loss: 0.0482 (0.0622) time: 2.8726 data: 0.0073 max mem: 33369 +Epoch: [16] [1150/1319] eta: 0:08:03 lr: 3.053722876479403e-05 loss: 0.0554 (0.0622) time: 2.8641 data: 0.0077 max mem: 33369 +Epoch: [16] [1160/1319] eta: 0:07:34 lr: 3.0528219108535084e-05 loss: 0.0561 (0.0623) time: 2.8474 data: 0.0077 max mem: 33369 +Epoch: [16] [1170/1319] eta: 0:07:06 lr: 3.0519209156824297e-05 loss: 0.0581 (0.0624) time: 2.8458 data: 0.0079 max mem: 33369 +Epoch: [16] [1180/1319] eta: 0:06:37 lr: 3.0510198909555044e-05 loss: 0.0581 (0.0624) time: 2.8398 data: 0.0080 max mem: 33369 +Epoch: [16] [1190/1319] eta: 0:06:08 lr: 3.0501188366620653e-05 loss: 0.0632 (0.0625) time: 2.8492 data: 0.0078 max mem: 33369 +Epoch: [16] [1200/1319] eta: 0:05:40 lr: 3.0492177527914355e-05 loss: 0.0616 (0.0626) time: 2.8637 data: 0.0076 max mem: 33369 +Epoch: [16] [1210/1319] eta: 0:05:11 lr: 3.0483166393329327e-05 loss: 0.0616 (0.0626) time: 2.8682 data: 0.0071 max mem: 33369 +Epoch: [16] [1220/1319] eta: 0:04:43 lr: 3.0474154962758662e-05 loss: 0.0674 (0.0627) time: 2.8686 data: 0.0072 max mem: 33369 +Epoch: [16] [1230/1319] eta: 0:04:14 lr: 3.0465143236095372e-05 loss: 0.0641 (0.0627) time: 2.8406 data: 0.0075 max mem: 33369 +Epoch: [16] [1240/1319] eta: 0:03:45 lr: 3.045613121323242e-05 loss: 0.0528 (0.0626) time: 2.8487 data: 0.0077 max mem: 33369 +Epoch: [16] [1250/1319] eta: 0:03:17 lr: 3.044711889406267e-05 loss: 0.0534 (0.0626) time: 2.8786 data: 0.0080 max mem: 33369 +Epoch: [16] [1260/1319] eta: 0:02:48 lr: 3.0438106278478923e-05 loss: 0.0581 (0.0626) time: 2.8438 data: 0.0080 max mem: 33369 +Epoch: [16] [1270/1319] eta: 0:02:20 lr: 3.0429093366373907e-05 loss: 0.0581 (0.0628) time: 2.8295 data: 0.0078 max mem: 33369 +Epoch: [16] [1280/1319] eta: 0:01:51 lr: 3.0420080157640274e-05 loss: 0.0516 (0.0627) time: 2.8483 data: 0.0074 max mem: 33369 +Epoch: [16] [1290/1319] eta: 0:01:22 lr: 3.0411066652170593e-05 loss: 0.0529 (0.0627) time: 2.8618 data: 0.0072 max mem: 33369 +Epoch: [16] [1300/1319] eta: 0:00:54 lr: 3.040205284985739e-05 loss: 0.0529 (0.0626) time: 2.8836 data: 0.0072 max mem: 33369 +Epoch: [16] [1310/1319] eta: 0:00:25 lr: 3.039303875059306e-05 loss: 0.0509 (0.0627) time: 2.8623 data: 0.0070 max mem: 33369 +Epoch: [16] Total time: 1:02:53 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 2:00:01 time: 2.7989 data: 2.7055 max mem: 33369 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 100/2573] eta: 0:04:10 time: 0.0729 data: 0.0012 max mem: 33369 +Test: [ 200/2573] eta: 0:03:29 time: 0.0748 data: 0.0013 max mem: 33369 +Test: [ 300/2573] eta: 0:03:09 time: 0.0763 data: 0.0012 max mem: 33369 +Test: [ 400/2573] eta: 0:02:56 time: 0.0766 data: 0.0012 max mem: 33369 +Test: [ 500/2573] eta: 0:02:45 time: 0.0751 data: 0.0012 max mem: 33369 +Test: [ 600/2573] eta: 0:02:36 time: 0.0750 data: 0.0013 max mem: 33369 +Test: [ 700/2573] eta: 0:02:27 time: 0.0754 data: 0.0013 max mem: 33369 +Test: [ 800/2573] eta: 0:02:19 time: 0.0785 data: 0.0012 max mem: 33369 +Test: [ 900/2573] eta: 0:02:11 time: 0.0750 data: 0.0012 max mem: 33369 +Test: [1000/2573] eta: 0:02:02 time: 0.0753 data: 0.0013 max mem: 33369 +Test: [1100/2573] eta: 0:01:54 time: 0.0753 data: 0.0013 max mem: 33369 +Test: [1200/2573] eta: 0:01:46 time: 0.0753 data: 0.0012 max mem: 33369 +Test: [1300/2573] eta: 0:01:38 time: 0.0752 data: 0.0012 max mem: 33369 +Test: [1400/2573] eta: 0:01:30 time: 0.0738 data: 0.0013 max mem: 33369 +Test: [1500/2573] eta: 0:01:22 time: 0.0753 data: 0.0013 max mem: 33369 +Test: [1600/2573] eta: 0:01:15 time: 0.0788 data: 0.0013 max mem: 33369 +Test: [1700/2573] eta: 0:01:07 time: 0.0737 data: 0.0012 max mem: 33369 +Test: [1800/2573] eta: 0:00:59 time: 0.0771 data: 0.0013 max mem: 33369 +Test: [1900/2573] eta: 0:00:51 time: 0.0738 data: 0.0013 max mem: 33369 +Test: [2000/2573] eta: 0:00:43 time: 0.0749 data: 0.0013 max mem: 33369 +Test: [2100/2573] eta: 0:00:36 time: 0.0764 data: 0.0012 max mem: 33369 +Test: [2200/2573] eta: 0:00:28 time: 0.0761 data: 0.0011 max mem: 33369 +Test: [2300/2573] eta: 0:00:20 time: 0.0759 data: 0.0012 max mem: 33369 +Test: [2400/2573] eta: 0:00:13 time: 0.0709 data: 0.0011 max mem: 33369 +Test: [2500/2573] eta: 0:00:05 time: 0.0767 data: 0.0015 max mem: 33369 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: Total time: 0:03:16 +Final results: +Mean IoU is 62.07 + + precision@0.5 = 69.98 + precision@0.6 = 64.73 + precision@0.7 = 56.96 + precision@0.8 = 44.98 + precision@0.9 = 21.71 + overall IoU = 60.68 + +Average object IoU 62.072775674312844 +Overall IoU 60.6794548034668 +Better epoch: 16 + +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [17] [ 0/1319] eta: 1:31:06 lr: 3.0384925807273e-05 loss: 0.0469 (0.0469) time: 4.1444 data: 1.2149 max mem: 33369 +Epoch: [17] [ 10/1319] eta: 1:05:10 lr: 3.0375911143504937e-05 loss: 0.0598 (0.0579) time: 2.9875 data: 0.1168 max mem: 33369 +Epoch: [17] [ 20/1319] eta: 1:03:50 lr: 3.0366896182473385e-05 loss: 0.0603 (0.0603) time: 2.8891 data: 0.0067 max mem: 33369 +Epoch: [17] [ 30/1319] eta: 1:02:44 lr: 3.035788092407048e-05 loss: 0.0570 (0.0573) time: 2.8830 data: 0.0071 max mem: 33369 +Epoch: [17] [ 40/1319] eta: 1:01:58 lr: 3.034886536818829e-05 loss: 0.0516 (0.0577) time: 2.8642 data: 0.0076 max mem: 33369 +Epoch: [17] [ 50/1319] eta: 1:01:15 lr: 3.0339849514718806e-05 loss: 0.0544 (0.0591) time: 2.8602 data: 0.0079 max mem: 33369 +Epoch: [17] [ 60/1319] eta: 1:00:37 lr: 3.033083336355392e-05 loss: 0.0517 (0.0573) time: 2.8505 data: 0.0077 max mem: 33369 +Epoch: [17] [ 70/1319] eta: 1:00:04 lr: 3.03218169145855e-05 loss: 0.0493 (0.0566) time: 2.8586 data: 0.0072 max mem: 33369 +Epoch: [17] [ 80/1319] eta: 0:59:31 lr: 3.0312800167705292e-05 loss: 0.0507 (0.0572) time: 2.8628 data: 0.0074 max mem: 33369 +Epoch: [17] [ 90/1319] eta: 0:59:01 lr: 3.030378312280498e-05 loss: 0.0548 (0.0570) time: 2.8658 data: 0.0072 max mem: 33369 +Epoch: [17] [ 100/1319] eta: 0:58:33 lr: 3.0294765779776184e-05 loss: 0.0540 (0.0570) time: 2.8816 data: 0.0071 max mem: 33369 +Epoch: [17] [ 110/1319] eta: 0:58:00 lr: 3.0285748138510444e-05 loss: 0.0481 (0.0566) time: 2.8655 data: 0.0079 max mem: 33369 +Epoch: [17] [ 120/1319] eta: 0:57:27 lr: 3.0276730198899216e-05 loss: 0.0459 (0.0564) time: 2.8417 data: 0.0078 max mem: 33369 +Epoch: [17] [ 130/1319] eta: 0:56:54 lr: 3.0267711960833896e-05 loss: 0.0459 (0.0566) time: 2.8352 data: 0.0069 max mem: 33369 +Epoch: [17] [ 140/1319] eta: 0:56:16 lr: 3.0258693424205785e-05 loss: 0.0608 (0.0575) time: 2.7940 data: 0.0069 max mem: 33369 +Epoch: [17] [ 150/1319] eta: 0:55:50 lr: 3.024967458890613e-05 loss: 0.0564 (0.0566) time: 2.8270 data: 0.0071 max mem: 33369 +Epoch: [17] [ 160/1319] eta: 0:55:20 lr: 3.0240655454826085e-05 loss: 0.0476 (0.0574) time: 2.8687 data: 0.0072 max mem: 33369 +Epoch: [17] [ 170/1319] eta: 0:54:51 lr: 3.023163602185673e-05 loss: 0.0573 (0.0572) time: 2.8517 data: 0.0071 max mem: 33369 +Epoch: [17] [ 180/1319] eta: 0:54:20 lr: 3.022261628988908e-05 loss: 0.0570 (0.0580) time: 2.8457 data: 0.0073 max mem: 33369 +Epoch: [17] [ 190/1319] eta: 0:53:54 lr: 3.0213596258814065e-05 loss: 0.0570 (0.0582) time: 2.8712 data: 0.0073 max mem: 33369 +Epoch: [17] [ 200/1319] eta: 0:53:25 lr: 3.020457592852254e-05 loss: 0.0528 (0.0583) time: 2.8832 data: 0.0070 max mem: 33369 +Epoch: [17] [ 210/1319] eta: 0:52:56 lr: 3.0195555298905282e-05 loss: 0.0511 (0.0579) time: 2.8538 data: 0.0070 max mem: 33369 +Epoch: [17] [ 220/1319] eta: 0:52:21 lr: 3.0186534369853002e-05 loss: 0.0489 (0.0575) time: 2.8006 data: 0.0069 max mem: 33369 +Epoch: [17] [ 230/1319] eta: 0:51:59 lr: 3.0177513141256336e-05 loss: 0.0424 (0.0570) time: 2.8740 data: 0.0071 max mem: 33369 +Epoch: [17] [ 240/1319] eta: 0:51:31 lr: 3.0168491613005817e-05 loss: 0.0522 (0.0577) time: 2.9371 data: 0.0072 max mem: 33369 +Epoch: [17] [ 250/1319] eta: 0:51:03 lr: 3.0159469784991934e-05 loss: 0.0552 (0.0579) time: 2.8767 data: 0.0070 max mem: 33369 +Epoch: [17] [ 260/1319] eta: 0:50:36 lr: 3.0150447657105084e-05 loss: 0.0530 (0.0575) time: 2.8888 data: 0.0071 max mem: 33369 +Epoch: [17] [ 270/1319] eta: 0:50:06 lr: 3.0141425229235594e-05 loss: 0.0447 (0.0574) time: 2.8724 data: 0.0076 max mem: 33369 +Epoch: [17] [ 280/1319] eta: 0:49:37 lr: 3.01324025012737e-05 loss: 0.0474 (0.0573) time: 2.8437 data: 0.0080 max mem: 33369 +Epoch: [17] [ 290/1319] eta: 0:49:05 lr: 3.012337947310957e-05 loss: 0.0508 (0.0574) time: 2.8167 data: 0.0079 max mem: 33369 +Epoch: [17] [ 300/1319] eta: 0:48:39 lr: 3.0114356144633316e-05 loss: 0.0548 (0.0573) time: 2.8586 data: 0.0073 max mem: 33369 +Epoch: [17] [ 310/1319] eta: 0:48:10 lr: 3.010533251573493e-05 loss: 0.0539 (0.0572) time: 2.8933 data: 0.0073 max mem: 33369 +Epoch: [17] [ 320/1319] eta: 0:47:41 lr: 3.0096308586304355e-05 loss: 0.0538 (0.0572) time: 2.8545 data: 0.0083 max mem: 33369 +Epoch: [17] [ 330/1319] eta: 0:47:13 lr: 3.0087284356231465e-05 loss: 0.0583 (0.0573) time: 2.8745 data: 0.0084 max mem: 33369 +Epoch: [17] [ 340/1319] eta: 0:46:45 lr: 3.0078259825406035e-05 loss: 0.0531 (0.0571) time: 2.8908 data: 0.0075 max mem: 33369 +Epoch: [17] [ 350/1319] eta: 0:46:17 lr: 3.0069234993717783e-05 loss: 0.0495 (0.0573) time: 2.8904 data: 0.0070 max mem: 33369 +Epoch: [17] [ 360/1319] eta: 0:45:50 lr: 3.006020986105632e-05 loss: 0.0525 (0.0572) time: 2.9008 data: 0.0069 max mem: 33369 +Epoch: [17] [ 370/1319] eta: 0:45:18 lr: 3.005118442731122e-05 loss: 0.0546 (0.0573) time: 2.8294 data: 0.0072 max mem: 33369 +Epoch: [17] [ 380/1319] eta: 0:44:52 lr: 3.004215869237195e-05 loss: 0.0520 (0.0572) time: 2.8599 data: 0.0078 max mem: 33369 +Epoch: [17] [ 390/1319] eta: 0:44:18 lr: 3.0033132656127906e-05 loss: 0.0455 (0.0574) time: 2.7973 data: 0.0074 max mem: 33369 +Epoch: [17] [ 400/1319] eta: 0:43:44 lr: 3.002410631846841e-05 loss: 0.0571 (0.0576) time: 2.6347 data: 0.0066 max mem: 33369 +Epoch: [17] [ 410/1319] eta: 0:43:17 lr: 3.0015079679282703e-05 loss: 0.0573 (0.0576) time: 2.7871 data: 0.0067 max mem: 33369 +Epoch: [17] [ 420/1319] eta: 0:42:49 lr: 3.0006052738459948e-05 loss: 0.0524 (0.0576) time: 2.9037 data: 0.0068 max mem: 33369 +Epoch: [17] [ 430/1319] eta: 0:42:21 lr: 2.999702549588924e-05 loss: 0.0477 (0.0575) time: 2.8733 data: 0.0069 max mem: 33369 +Epoch: [17] [ 440/1319] eta: 0:41:53 lr: 2.998799795145959e-05 loss: 0.0522 (0.0575) time: 2.8850 data: 0.0069 max mem: 33369 +Epoch: [17] [ 450/1319] eta: 0:41:25 lr: 2.9978970105059916e-05 loss: 0.0522 (0.0575) time: 2.8847 data: 0.0073 max mem: 33369 +Epoch: [17] [ 460/1319] eta: 0:40:55 lr: 2.9969941956579083e-05 loss: 0.0468 (0.0573) time: 2.8536 data: 0.0080 max mem: 33369 +Epoch: [17] [ 470/1319] eta: 0:40:27 lr: 2.9960913505905863e-05 loss: 0.0514 (0.0575) time: 2.8377 data: 0.0077 max mem: 33369 +Epoch: [17] [ 480/1319] eta: 0:39:58 lr: 2.995188475292896e-05 loss: 0.0658 (0.0577) time: 2.8417 data: 0.0071 max mem: 33369 +Epoch: [17] [ 490/1319] eta: 0:39:30 lr: 2.9942855697536976e-05 loss: 0.0611 (0.0580) time: 2.8625 data: 0.0073 max mem: 33369 +Epoch: [17] [ 500/1319] eta: 0:39:00 lr: 2.9933826339618466e-05 loss: 0.0519 (0.0578) time: 2.8489 data: 0.0077 max mem: 33369 +Epoch: [17] [ 510/1319] eta: 0:38:32 lr: 2.992479667906189e-05 loss: 0.0473 (0.0581) time: 2.8401 data: 0.0078 max mem: 33369 +Epoch: [17] [ 520/1319] eta: 0:38:04 lr: 2.9915766715755623e-05 loss: 0.0590 (0.0582) time: 2.8965 data: 0.0076 max mem: 33369 +Epoch: [17] [ 530/1319] eta: 0:37:35 lr: 2.990673644958798e-05 loss: 0.0532 (0.0584) time: 2.8794 data: 0.0076 max mem: 33369 +Epoch: [17] [ 540/1319] eta: 0:37:06 lr: 2.989770588044718e-05 loss: 0.0536 (0.0585) time: 2.8189 data: 0.0077 max mem: 33369 +Epoch: [17] [ 550/1319] eta: 0:36:37 lr: 2.9888675008221372e-05 loss: 0.0608 (0.0586) time: 2.8091 data: 0.0078 max mem: 33369 +Epoch: [17] [ 560/1319] eta: 0:36:08 lr: 2.9879643832798625e-05 loss: 0.0565 (0.0586) time: 2.8179 data: 0.0078 max mem: 33369 +Epoch: [17] [ 570/1319] eta: 0:35:39 lr: 2.987061235406693e-05 loss: 0.0501 (0.0585) time: 2.8429 data: 0.0076 max mem: 33369 +Epoch: [17] [ 580/1319] eta: 0:35:11 lr: 2.98615805719142e-05 loss: 0.0499 (0.0584) time: 2.8794 data: 0.0074 max mem: 33369 +Epoch: [17] [ 590/1319] eta: 0:34:42 lr: 2.9852548486228266e-05 loss: 0.0533 (0.0584) time: 2.8753 data: 0.0079 max mem: 33369 +Epoch: [17] [ 600/1319] eta: 0:34:14 lr: 2.9843516096896873e-05 loss: 0.0621 (0.0584) time: 2.8659 data: 0.0077 max mem: 33369 +Epoch: [17] [ 610/1319] eta: 0:33:45 lr: 2.98344834038077e-05 loss: 0.0559 (0.0585) time: 2.8620 data: 0.0072 max mem: 33369 +Epoch: [17] [ 620/1319] eta: 0:33:17 lr: 2.9825450406848343e-05 loss: 0.0514 (0.0584) time: 2.8454 data: 0.0072 max mem: 33369 +Epoch: [17] [ 630/1319] eta: 0:32:48 lr: 2.981641710590631e-05 loss: 0.0514 (0.0586) time: 2.8354 data: 0.0070 max mem: 33369 +Epoch: [17] [ 640/1319] eta: 0:32:20 lr: 2.9807383500869036e-05 loss: 0.0591 (0.0588) time: 2.8743 data: 0.0073 max mem: 33369 +Epoch: [17] [ 650/1319] eta: 0:31:51 lr: 2.9798349591623877e-05 loss: 0.0591 (0.0588) time: 2.8707 data: 0.0076 max mem: 33369 +Epoch: [17] [ 660/1319] eta: 0:31:22 lr: 2.9789315378058107e-05 loss: 0.0627 (0.0589) time: 2.8365 data: 0.0078 max mem: 33369 +Epoch: [17] [ 670/1319] eta: 0:30:54 lr: 2.978028086005893e-05 loss: 0.0595 (0.0588) time: 2.8688 data: 0.0075 max mem: 33369 +Epoch: [17] [ 680/1319] eta: 0:30:26 lr: 2.977124603751345e-05 loss: 0.0467 (0.0586) time: 2.9038 data: 0.0071 max mem: 33369 +Epoch: [17] [ 690/1319] eta: 0:29:58 lr: 2.9762210910308712e-05 loss: 0.0482 (0.0586) time: 2.9160 data: 0.0074 max mem: 33369 +Epoch: [17] [ 700/1319] eta: 0:29:28 lr: 2.9753175478331675e-05 loss: 0.0526 (0.0586) time: 2.8181 data: 0.0074 max mem: 33369 +Epoch: [17] [ 710/1319] eta: 0:29:00 lr: 2.97441397414692e-05 loss: 0.0561 (0.0586) time: 2.7970 data: 0.0074 max mem: 33369 +Epoch: [17] [ 720/1319] eta: 0:28:31 lr: 2.973510369960809e-05 loss: 0.0523 (0.0586) time: 2.8668 data: 0.0075 max mem: 33369 +Epoch: [17] [ 730/1319] eta: 0:28:02 lr: 2.9726067352635072e-05 loss: 0.0523 (0.0586) time: 2.8346 data: 0.0079 max mem: 33369 +Epoch: [17] [ 740/1319] eta: 0:27:33 lr: 2.971703070043676e-05 loss: 0.0523 (0.0586) time: 2.8170 data: 0.0080 max mem: 33369 +Epoch: [17] [ 750/1319] eta: 0:27:05 lr: 2.970799374289972e-05 loss: 0.0619 (0.0587) time: 2.8246 data: 0.0079 max mem: 33369 +Epoch: [17] [ 760/1319] eta: 0:26:36 lr: 2.9698956479910424e-05 loss: 0.0507 (0.0586) time: 2.8453 data: 0.0076 max mem: 33369 +Epoch: [17] [ 770/1319] eta: 0:26:08 lr: 2.9689918911355265e-05 loss: 0.0454 (0.0587) time: 2.8850 data: 0.0069 max mem: 33369 +Epoch: [17] [ 780/1319] eta: 0:25:39 lr: 2.9680881037120552e-05 loss: 0.0641 (0.0590) time: 2.8352 data: 0.0067 max mem: 33369 +Epoch: [17] [ 790/1319] eta: 0:25:11 lr: 2.9671842857092525e-05 loss: 0.0605 (0.0592) time: 2.8848 data: 0.0071 max mem: 33369 +Epoch: [17] [ 800/1319] eta: 0:24:43 lr: 2.9662804371157326e-05 loss: 0.0605 (0.0594) time: 2.9747 data: 0.0072 max mem: 33369 +Epoch: [17] [ 810/1319] eta: 0:24:15 lr: 2.9653765579201043e-05 loss: 0.0639 (0.0596) time: 2.9041 data: 0.0073 max mem: 33369 +Epoch: [17] [ 820/1319] eta: 0:23:46 lr: 2.964472648110964e-05 loss: 0.0580 (0.0597) time: 2.8513 data: 0.0079 max mem: 33369 +Epoch: [17] [ 830/1319] eta: 0:23:17 lr: 2.963568707676905e-05 loss: 0.0536 (0.0597) time: 2.8526 data: 0.0078 max mem: 33369 +Epoch: [17] [ 840/1319] eta: 0:22:49 lr: 2.962664736606507e-05 loss: 0.0428 (0.0595) time: 2.8501 data: 0.0074 max mem: 33369 +Epoch: [17] [ 850/1319] eta: 0:22:20 lr: 2.961760734888347e-05 loss: 0.0358 (0.0594) time: 2.8229 data: 0.0073 max mem: 33369 +Epoch: [17] [ 860/1319] eta: 0:21:51 lr: 2.96085670251099e-05 loss: 0.0505 (0.0594) time: 2.8598 data: 0.0074 max mem: 33369 +Epoch: [17] [ 870/1319] eta: 0:21:23 lr: 2.959952639462995e-05 loss: 0.0534 (0.0594) time: 2.8969 data: 0.0075 max mem: 33369 +Epoch: [17] [ 880/1319] eta: 0:20:55 lr: 2.9590485457329127e-05 loss: 0.0548 (0.0596) time: 2.8952 data: 0.0073 max mem: 33369 +Epoch: [17] [ 890/1319] eta: 0:20:26 lr: 2.9581444213092834e-05 loss: 0.0562 (0.0595) time: 2.8882 data: 0.0069 max mem: 33369 +Epoch: [17] [ 900/1319] eta: 0:19:57 lr: 2.957240266180642e-05 loss: 0.0547 (0.0596) time: 2.8591 data: 0.0067 max mem: 33369 +Epoch: [17] [ 910/1319] eta: 0:19:29 lr: 2.956336080335514e-05 loss: 0.0600 (0.0598) time: 2.8506 data: 0.0071 max mem: 33369 +Epoch: [17] [ 920/1319] eta: 0:19:00 lr: 2.955431863762416e-05 loss: 0.0643 (0.0599) time: 2.8549 data: 0.0071 max mem: 33369 +Epoch: [17] [ 930/1319] eta: 0:18:31 lr: 2.9545276164498587e-05 loss: 0.0571 (0.0599) time: 2.8201 data: 0.0070 max mem: 33369 +Epoch: [17] [ 940/1319] eta: 0:18:03 lr: 2.953623338386342e-05 loss: 0.0571 (0.0599) time: 2.8491 data: 0.0072 max mem: 33369 +Epoch: [17] [ 950/1319] eta: 0:17:34 lr: 2.9527190295603586e-05 loss: 0.0631 (0.0600) time: 2.8919 data: 0.0075 max mem: 33369 +Epoch: [17] [ 960/1319] eta: 0:17:06 lr: 2.9518146899603932e-05 loss: 0.0558 (0.0601) time: 2.8680 data: 0.0077 max mem: 33369 +Epoch: [17] [ 970/1319] eta: 0:16:37 lr: 2.9509103195749226e-05 loss: 0.0522 (0.0601) time: 2.8461 data: 0.0081 max mem: 33369 +Epoch: [17] [ 980/1319] eta: 0:16:09 lr: 2.9500059183924145e-05 loss: 0.0545 (0.0602) time: 2.8501 data: 0.0078 max mem: 33369 +Epoch: [17] [ 990/1319] eta: 0:15:40 lr: 2.9491014864013282e-05 loss: 0.0556 (0.0602) time: 2.8650 data: 0.0072 max mem: 33369 +Epoch: [17] [1000/1319] eta: 0:15:11 lr: 2.9481970235901164e-05 loss: 0.0570 (0.0602) time: 2.8458 data: 0.0068 max mem: 33369 +Epoch: [17] [1010/1319] eta: 0:14:43 lr: 2.9472925299472214e-05 loss: 0.0574 (0.0603) time: 2.8587 data: 0.0070 max mem: 33369 +Epoch: [17] [1020/1319] eta: 0:14:14 lr: 2.9463880054610792e-05 loss: 0.0589 (0.0603) time: 2.8815 data: 0.0072 max mem: 33369 +Epoch: [17] [1030/1319] eta: 0:13:46 lr: 2.9454834501201163e-05 loss: 0.0541 (0.0603) time: 2.8864 data: 0.0075 max mem: 33369 +Epoch: [17] [1040/1319] eta: 0:13:17 lr: 2.9445788639127496e-05 loss: 0.0511 (0.0604) time: 2.8911 data: 0.0077 max mem: 33369 +Epoch: [17] [1050/1319] eta: 0:12:49 lr: 2.943674246827392e-05 loss: 0.0551 (0.0603) time: 2.8789 data: 0.0072 max mem: 33369 +Epoch: [17] [1060/1319] eta: 0:12:20 lr: 2.9427695988524433e-05 loss: 0.0562 (0.0604) time: 2.8553 data: 0.0070 max mem: 33369 +Epoch: [17] [1070/1319] eta: 0:11:52 lr: 2.941864919976297e-05 loss: 0.0558 (0.0604) time: 2.8803 data: 0.0069 max mem: 33369 +Epoch: [17] [1080/1319] eta: 0:11:23 lr: 2.9409602101873397e-05 loss: 0.0524 (0.0604) time: 2.8370 data: 0.0070 max mem: 33369 +Epoch: [17] [1090/1319] eta: 0:10:54 lr: 2.9400554694739468e-05 loss: 0.0524 (0.0604) time: 2.8382 data: 0.0074 max mem: 33369 +Epoch: [17] [1100/1319] eta: 0:10:26 lr: 2.9391506978244877e-05 loss: 0.0500 (0.0604) time: 2.9081 data: 0.0076 max mem: 33369 +Epoch: [17] [1110/1319] eta: 0:09:57 lr: 2.9382458952273217e-05 loss: 0.0501 (0.0603) time: 2.8582 data: 0.0078 max mem: 33369 +Epoch: [17] [1120/1319] eta: 0:09:29 lr: 2.937341061670802e-05 loss: 0.0578 (0.0604) time: 2.8311 data: 0.0079 max mem: 33369 +Epoch: [17] [1130/1319] eta: 0:09:00 lr: 2.9364361971432715e-05 loss: 0.0668 (0.0605) time: 2.8183 data: 0.0080 max mem: 33369 +Epoch: [17] [1140/1319] eta: 0:08:31 lr: 2.9355313016330638e-05 loss: 0.0596 (0.0606) time: 2.8066 data: 0.0084 max mem: 33369 +Epoch: [17] [1150/1319] eta: 0:08:03 lr: 2.934626375128508e-05 loss: 0.0597 (0.0605) time: 2.8145 data: 0.0083 max mem: 33369 +Epoch: [17] [1160/1319] eta: 0:07:34 lr: 2.93372141761792e-05 loss: 0.0571 (0.0605) time: 2.8292 data: 0.0078 max mem: 33369 +Epoch: [17] [1170/1319] eta: 0:07:05 lr: 2.9328164290896108e-05 loss: 0.0560 (0.0606) time: 2.8430 data: 0.0071 max mem: 33369 +Epoch: [17] [1180/1319] eta: 0:06:37 lr: 2.9319114095318817e-05 loss: 0.0569 (0.0606) time: 2.8207 data: 0.0073 max mem: 33369 +Epoch: [17] [1190/1319] eta: 0:06:08 lr: 2.9310063589330256e-05 loss: 0.0591 (0.0607) time: 2.8167 data: 0.0076 max mem: 33369 +Epoch: [17] [1200/1319] eta: 0:05:40 lr: 2.9301012772813273e-05 loss: 0.0627 (0.0608) time: 2.8725 data: 0.0074 max mem: 33369 +Epoch: [17] [1210/1319] eta: 0:05:11 lr: 2.9291961645650624e-05 loss: 0.0553 (0.0607) time: 2.9079 data: 0.0072 max mem: 33369 +Epoch: [17] [1220/1319] eta: 0:04:42 lr: 2.9282910207724996e-05 loss: 0.0510 (0.0607) time: 2.8628 data: 0.0078 max mem: 33369 +Epoch: [17] [1230/1319] eta: 0:04:14 lr: 2.9273858458918974e-05 loss: 0.0608 (0.0608) time: 2.8241 data: 0.0077 max mem: 33369 +Epoch: [17] [1240/1319] eta: 0:03:45 lr: 2.9264806399115058e-05 loss: 0.0628 (0.0609) time: 2.8868 data: 0.0070 max mem: 33369 +Epoch: [17] [1250/1319] eta: 0:03:17 lr: 2.925575402819568e-05 loss: 0.0573 (0.0609) time: 2.9325 data: 0.0071 max mem: 33369 +Epoch: [17] [1260/1319] eta: 0:02:48 lr: 2.9246701346043183e-05 loss: 0.0523 (0.0609) time: 2.8587 data: 0.0075 max mem: 33369 +Epoch: [17] [1270/1319] eta: 0:02:20 lr: 2.9237648352539803e-05 loss: 0.0500 (0.0609) time: 2.8323 data: 0.0079 max mem: 33369 +Epoch: [17] [1280/1319] eta: 0:01:51 lr: 2.9228595047567713e-05 loss: 0.0604 (0.0609) time: 2.8728 data: 0.0073 max mem: 33369 +Epoch: [17] [1290/1319] eta: 0:01:22 lr: 2.9219541431009008e-05 loss: 0.0554 (0.0609) time: 2.8816 data: 0.0066 max mem: 33369 +Epoch: [17] [1300/1319] eta: 0:00:54 lr: 2.921048750274567e-05 loss: 0.0550 (0.0609) time: 2.8629 data: 0.0068 max mem: 33369 +Epoch: [17] [1310/1319] eta: 0:00:25 lr: 2.9201433262659623e-05 loss: 0.0550 (0.0608) time: 2.8741 data: 0.0069 max mem: 33369 +Epoch: [17] Total time: 1:02:50 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 2:27:25 time: 3.4378 data: 3.3514 max mem: 33369 +Test: [ 100/2573] eta: 0:04:23 time: 0.0729 data: 0.0012 max mem: 33369 +Test: [ 200/2573] eta: 0:03:35 time: 0.0741 data: 0.0012 max mem: 33369 +Test: [ 300/2573] eta: 0:03:13 time: 0.0758 data: 0.0012 max mem: 33369 +Test: [ 400/2573] eta: 0:02:58 time: 0.0760 data: 0.0012 max mem: 33369 +Test: [ 500/2573] eta: 0:02:47 time: 0.0745 data: 0.0013 max mem: 33369 +Test: [ 600/2573] eta: 0:02:37 time: 0.0746 data: 0.0012 max mem: 33369 +Test: [ 700/2573] eta: 0:02:28 time: 0.0750 data: 0.0013 max mem: 33369 +Test: [ 800/2573] eta: 0:02:19 time: 0.0779 data: 0.0012 max mem: 33369 +Test: [ 900/2573] eta: 0:02:11 time: 0.0747 data: 0.0013 max mem: 33369 +Test: [1000/2573] eta: 0:02:03 time: 0.0748 data: 0.0012 max mem: 33369 +Test: [1100/2573] eta: 0:01:54 time: 0.0749 data: 0.0013 max mem: 33369 +Test: [1200/2573] eta: 0:01:46 time: 0.0752 data: 0.0013 max mem: 33369 +Test: [1300/2573] eta: 0:01:38 time: 0.0748 data: 0.0012 max mem: 33369 +Test: [1400/2573] eta: 0:01:30 time: 0.0733 data: 0.0012 max mem: 33369 +Test: [1500/2573] eta: 0:01:22 time: 0.0750 data: 0.0012 max mem: 33369 +Test: [1600/2573] eta: 0:01:14 time: 0.0783 data: 0.0013 max mem: 33369 +Test: [1700/2573] eta: 0:01:07 time: 0.0733 data: 0.0012 max mem: 33369 +Test: [1800/2573] eta: 0:00:59 time: 0.0767 data: 0.0013 max mem: 33369 +Test: [1900/2573] eta: 0:00:51 time: 0.0736 data: 0.0013 max mem: 33369 +Test: [2000/2573] eta: 0:00:43 time: 0.0754 data: 0.0014 max mem: 33369 +Test: [2100/2573] eta: 0:00:36 time: 0.0762 data: 0.0012 max mem: 33369 +Test: [2200/2573] eta: 0:00:28 time: 0.0762 data: 0.0011 max mem: 33369 +Test: [2300/2573] eta: 0:00:20 time: 0.0763 data: 0.0012 max mem: 33369 +Test: [2400/2573] eta: 0:00:13 time: 0.0712 data: 0.0012 max mem: 33369 +Test: [2500/2573] eta: 0:00:05 time: 0.0755 data: 0.0013 max mem: 33369 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: Total time: 0:03:16 +Final results: +Mean IoU is 62.95 + + precision@0.5 = 70.59 + precision@0.6 = 64.79 + precision@0.7 = 58.15 + precision@0.8 = 46.08 + precision@0.9 = 22.32 + overall IoU = 60.39 + +Average object IoU 62.94949297292563 +Overall IoU 60.386932373046875 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [18] [ 0/1319] eta: 3:23:54 lr: 2.9193284179876086e-05 loss: 0.0500 (0.0500) time: 9.2753 data: 1.5849 max mem: 33369 +Epoch: [18] [ 10/1319] eta: 1:16:11 lr: 2.9184229347001237e-05 loss: 0.0535 (0.0561) time: 3.4926 data: 0.1509 max mem: 33369 +Epoch: [18] [ 20/1319] eta: 1:09:05 lr: 2.9175174201960736e-05 loss: 0.0535 (0.0596) time: 2.8871 data: 0.0070 max mem: 33369 +Epoch: [18] [ 30/1319] eta: 1:06:22 lr: 2.9166118744636155e-05 loss: 0.0534 (0.0587) time: 2.8685 data: 0.0068 max mem: 33369 +Epoch: [18] [ 40/1319] eta: 1:04:35 lr: 2.9157062974908988e-05 loss: 0.0534 (0.0576) time: 2.8611 data: 0.0070 max mem: 33369 +Epoch: [18] [ 50/1319] eta: 1:03:25 lr: 2.9148006892660646e-05 loss: 0.0519 (0.0622) time: 2.8569 data: 0.0069 max mem: 33369 +Epoch: [18] [ 60/1319] eta: 1:02:24 lr: 2.9138950497772444e-05 loss: 0.0503 (0.0617) time: 2.8582 data: 0.0070 max mem: 33369 +Epoch: [18] [ 70/1319] eta: 1:01:46 lr: 2.9129893790125616e-05 loss: 0.0499 (0.0605) time: 2.8877 data: 0.0070 max mem: 33369 +Epoch: [18] [ 80/1319] eta: 1:00:58 lr: 2.9120836769601318e-05 loss: 0.0514 (0.0599) time: 2.8892 data: 0.0074 max mem: 33369 +Epoch: [18] [ 90/1319] eta: 1:00:25 lr: 2.9111779436080605e-05 loss: 0.0519 (0.0597) time: 2.8900 data: 0.0072 max mem: 33369 +Epoch: [18] [ 100/1319] eta: 0:59:46 lr: 2.910272178944446e-05 loss: 0.0488 (0.0591) time: 2.8973 data: 0.0068 max mem: 33369 +Epoch: [18] [ 110/1319] eta: 0:59:08 lr: 2.9093663829573763e-05 loss: 0.0488 (0.0591) time: 2.8661 data: 0.0068 max mem: 33369 +Epoch: [18] [ 120/1319] eta: 0:58:37 lr: 2.9084605556349322e-05 loss: 0.0604 (0.0600) time: 2.8916 data: 0.0069 max mem: 33369 +Epoch: [18] [ 130/1319] eta: 0:58:02 lr: 2.9075546969651845e-05 loss: 0.0584 (0.0595) time: 2.8942 data: 0.0075 max mem: 33369 +Epoch: [18] [ 140/1319] eta: 0:57:20 lr: 2.906648806936197e-05 loss: 0.0559 (0.0598) time: 2.8239 data: 0.0077 max mem: 33369 +Epoch: [18] [ 150/1319] eta: 0:56:54 lr: 2.9057428855360237e-05 loss: 0.0554 (0.0593) time: 2.8705 data: 0.0073 max mem: 33369 +Epoch: [18] [ 160/1319] eta: 0:56:20 lr: 2.9048369327527098e-05 loss: 0.0468 (0.0591) time: 2.9097 data: 0.0077 max mem: 33369 +Epoch: [18] [ 170/1319] eta: 0:55:45 lr: 2.903930948574293e-05 loss: 0.0468 (0.0582) time: 2.8422 data: 0.0083 max mem: 33369 +Epoch: [18] [ 180/1319] eta: 0:55:11 lr: 2.9030249329888e-05 loss: 0.0485 (0.0593) time: 2.8321 data: 0.0080 max mem: 33369 +Epoch: [18] [ 190/1319] eta: 0:54:40 lr: 2.9021188859842518e-05 loss: 0.0422 (0.0583) time: 2.8539 data: 0.0075 max mem: 33369 +Epoch: [18] [ 200/1319] eta: 0:54:12 lr: 2.9012128075486583e-05 loss: 0.0429 (0.0576) time: 2.8948 data: 0.0076 max mem: 33369 +Epoch: [18] [ 210/1319] eta: 0:53:41 lr: 2.900306697670022e-05 loss: 0.0435 (0.0572) time: 2.8919 data: 0.0072 max mem: 33369 +Epoch: [18] [ 220/1319] eta: 0:53:08 lr: 2.8994005563363352e-05 loss: 0.0521 (0.0575) time: 2.8489 data: 0.0071 max mem: 33369 +Epoch: [18] [ 230/1319] eta: 0:52:37 lr: 2.8984943835355838e-05 loss: 0.0512 (0.0575) time: 2.8453 data: 0.0078 max mem: 33369 +Epoch: [18] [ 240/1319] eta: 0:52:04 lr: 2.8975881792557412e-05 loss: 0.0488 (0.0575) time: 2.8407 data: 0.0078 max mem: 33369 +Epoch: [18] [ 250/1319] eta: 0:51:32 lr: 2.8966819434847762e-05 loss: 0.0503 (0.0575) time: 2.8167 data: 0.0073 max mem: 33369 +Epoch: [18] [ 260/1319] eta: 0:51:02 lr: 2.8957756762106468e-05 loss: 0.0511 (0.0575) time: 2.8444 data: 0.0073 max mem: 33369 +Epoch: [18] [ 270/1319] eta: 0:50:33 lr: 2.8948693774213014e-05 loss: 0.0550 (0.0576) time: 2.8823 data: 0.0071 max mem: 33369 +Epoch: [18] [ 280/1319] eta: 0:50:04 lr: 2.8939630471046815e-05 loss: 0.0514 (0.0575) time: 2.8902 data: 0.0070 max mem: 33369 +Epoch: [18] [ 290/1319] eta: 0:49:31 lr: 2.893056685248718e-05 loss: 0.0459 (0.0571) time: 2.8296 data: 0.0070 max mem: 33369 +Epoch: [18] [ 300/1319] eta: 0:49:03 lr: 2.892150291841334e-05 loss: 0.0415 (0.0569) time: 2.8441 data: 0.0074 max mem: 33369 +Epoch: [18] [ 310/1319] eta: 0:48:34 lr: 2.891243866870445e-05 loss: 0.0514 (0.0569) time: 2.8925 data: 0.0078 max mem: 33369 +Epoch: [18] [ 320/1319] eta: 0:48:04 lr: 2.8903374103239537e-05 loss: 0.0558 (0.0572) time: 2.8724 data: 0.0075 max mem: 33369 +Epoch: [18] [ 330/1319] eta: 0:47:34 lr: 2.889430922189758e-05 loss: 0.0544 (0.0571) time: 2.8577 data: 0.0071 max mem: 33369 +Epoch: [18] [ 340/1319] eta: 0:47:05 lr: 2.8885244024557463e-05 loss: 0.0534 (0.0571) time: 2.8533 data: 0.0070 max mem: 33369 +Epoch: [18] [ 350/1319] eta: 0:46:34 lr: 2.8876178511097952e-05 loss: 0.0534 (0.0572) time: 2.8499 data: 0.0072 max mem: 33369 +Epoch: [18] [ 360/1319] eta: 0:46:04 lr: 2.886711268139775e-05 loss: 0.0473 (0.0570) time: 2.8279 data: 0.0076 max mem: 33369 +Epoch: [18] [ 370/1319] eta: 0:45:31 lr: 2.8858046535335475e-05 loss: 0.0495 (0.0572) time: 2.7833 data: 0.0072 max mem: 33369 +Epoch: [18] [ 380/1319] eta: 0:45:05 lr: 2.8848980072789644e-05 loss: 0.0521 (0.0571) time: 2.8576 data: 0.0070 max mem: 33369 +Epoch: [18] [ 390/1319] eta: 0:44:37 lr: 2.8839913293638683e-05 loss: 0.0526 (0.0570) time: 2.9357 data: 0.0072 max mem: 33369 +Epoch: [18] [ 400/1319] eta: 0:44:08 lr: 2.8830846197760937e-05 loss: 0.0540 (0.0571) time: 2.8877 data: 0.0069 max mem: 33369 +Epoch: [18] [ 410/1319] eta: 0:43:39 lr: 2.8821778785034654e-05 loss: 0.0528 (0.0570) time: 2.8846 data: 0.0068 max mem: 33369 +Epoch: [18] [ 420/1319] eta: 0:43:10 lr: 2.8812711055338004e-05 loss: 0.0497 (0.0570) time: 2.8821 data: 0.0069 max mem: 33369 +Epoch: [18] [ 430/1319] eta: 0:42:41 lr: 2.8803643008549054e-05 loss: 0.0497 (0.0573) time: 2.8626 data: 0.0068 max mem: 33369 +Epoch: [18] [ 440/1319] eta: 0:42:11 lr: 2.879457464454579e-05 loss: 0.0507 (0.0572) time: 2.8525 data: 0.0068 max mem: 33369 +Epoch: [18] [ 450/1319] eta: 0:41:43 lr: 2.8785505963206112e-05 loss: 0.0483 (0.0569) time: 2.8800 data: 0.0072 max mem: 33369 +Epoch: [18] [ 460/1319] eta: 0:41:14 lr: 2.877643696440781e-05 loss: 0.0548 (0.0572) time: 2.8967 data: 0.0074 max mem: 33369 +Epoch: [18] [ 470/1319] eta: 0:40:45 lr: 2.876736764802861e-05 loss: 0.0607 (0.0572) time: 2.8839 data: 0.0073 max mem: 33369 +Epoch: [18] [ 480/1319] eta: 0:40:16 lr: 2.8758298013946133e-05 loss: 0.0524 (0.0573) time: 2.8678 data: 0.0072 max mem: 33369 +Epoch: [18] [ 490/1319] eta: 0:39:47 lr: 2.8749228062037915e-05 loss: 0.0543 (0.0575) time: 2.8609 data: 0.0070 max mem: 33369 +Epoch: [18] [ 500/1319] eta: 0:39:17 lr: 2.87401577921814e-05 loss: 0.0565 (0.0577) time: 2.8353 data: 0.0074 max mem: 33369 +Epoch: [18] [ 510/1319] eta: 0:38:48 lr: 2.8731087204253943e-05 loss: 0.0442 (0.0574) time: 2.8203 data: 0.0080 max mem: 33369 +Epoch: [18] [ 520/1319] eta: 0:38:17 lr: 2.8722016298132803e-05 loss: 0.0476 (0.0574) time: 2.7932 data: 0.0079 max mem: 33369 +Epoch: [18] [ 530/1319] eta: 0:37:49 lr: 2.8712945073695164e-05 loss: 0.0572 (0.0575) time: 2.8353 data: 0.0074 max mem: 33369 +Epoch: [18] [ 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data: 0.0070 max mem: 33369 +Epoch: [18] [ 700/1319] eta: 0:29:37 lr: 2.8558685436370514e-05 loss: 0.0475 (0.0581) time: 2.8670 data: 0.0071 max mem: 33369 +Epoch: [18] [ 710/1319] eta: 0:29:08 lr: 2.854960846112869e-05 loss: 0.0527 (0.0580) time: 2.8863 data: 0.0071 max mem: 33369 +Epoch: [18] [ 720/1319] eta: 0:28:39 lr: 2.8540531165219343e-05 loss: 0.0473 (0.0579) time: 2.8856 data: 0.0071 max mem: 33369 +Epoch: [18] [ 730/1319] eta: 0:28:11 lr: 2.8531453548517806e-05 loss: 0.0475 (0.0579) time: 2.8870 data: 0.0070 max mem: 33369 +Epoch: [18] [ 740/1319] eta: 0:27:42 lr: 2.8522375610899337e-05 loss: 0.0542 (0.0578) time: 2.8749 data: 0.0070 max mem: 33369 +Epoch: [18] [ 750/1319] eta: 0:27:13 lr: 2.8513297352239087e-05 loss: 0.0551 (0.0578) time: 2.8245 data: 0.0069 max mem: 33369 +Epoch: [18] [ 760/1319] eta: 0:26:44 lr: 2.850421877241213e-05 loss: 0.0563 (0.0580) time: 2.8458 data: 0.0075 max mem: 33369 +Epoch: [18] [ 770/1319] eta: 0:26:16 lr: 2.8495139871293436e-05 loss: 0.0565 (0.0581) time: 2.8826 data: 0.0082 max mem: 33369 +Epoch: [18] [ 780/1319] eta: 0:25:47 lr: 2.8486060648757875e-05 loss: 0.0518 (0.0581) time: 2.8848 data: 0.0079 max mem: 33369 +Epoch: [18] [ 790/1319] eta: 0:25:18 lr: 2.8476981104680245e-05 loss: 0.0479 (0.0581) time: 2.8976 data: 0.0075 max mem: 33369 +Epoch: [18] [ 800/1319] eta: 0:24:50 lr: 2.846790123893523e-05 loss: 0.0488 (0.0581) time: 2.8840 data: 0.0071 max mem: 33369 +Epoch: [18] [ 810/1319] eta: 0:24:21 lr: 2.8458821051397444e-05 loss: 0.0543 (0.0583) time: 2.8594 data: 0.0071 max mem: 33369 +Epoch: [18] [ 820/1319] eta: 0:23:52 lr: 2.844974054194138e-05 loss: 0.0543 (0.0582) time: 2.8357 data: 0.0070 max mem: 33369 +Epoch: [18] [ 830/1319] eta: 0:23:24 lr: 2.844065971044146e-05 loss: 0.0495 (0.0582) time: 2.8753 data: 0.0071 max mem: 33369 +Epoch: [18] [ 840/1319] eta: 0:22:55 lr: 2.8431578556772e-05 loss: 0.0622 (0.0584) time: 2.8861 data: 0.0073 max mem: 33369 +Epoch: [18] [ 850/1319] eta: 0:22:26 lr: 2.8422497080807237e-05 loss: 0.0561 (0.0583) time: 2.8364 data: 0.0076 max mem: 33369 +Epoch: [18] [ 860/1319] eta: 0:21:57 lr: 2.8413415282421285e-05 loss: 0.0529 (0.0584) time: 2.8832 data: 0.0077 max mem: 33369 +Epoch: [18] [ 870/1319] eta: 0:21:29 lr: 2.840433316148819e-05 loss: 0.0561 (0.0584) time: 2.9184 data: 0.0079 max mem: 33369 +Epoch: [18] [ 880/1319] eta: 0:21:00 lr: 2.8395250717881906e-05 loss: 0.0487 (0.0585) time: 2.9111 data: 0.0076 max mem: 33369 +Epoch: [18] [ 890/1319] eta: 0:20:32 lr: 2.8386167951476273e-05 loss: 0.0557 (0.0586) time: 2.8967 data: 0.0071 max mem: 33369 +Epoch: [18] [ 900/1319] eta: 0:20:02 lr: 2.8377084862145048e-05 loss: 0.0584 (0.0588) time: 2.8193 data: 0.0070 max mem: 33369 +Epoch: [18] [ 910/1319] eta: 0:19:34 lr: 2.8368001449761894e-05 loss: 0.0626 (0.0590) time: 2.8729 data: 0.0073 max mem: 33369 +Epoch: [18] [ 920/1319] eta: 0:19:06 lr: 2.8358917714200377e-05 loss: 0.0559 (0.0589) time: 2.9359 data: 0.0072 max mem: 33369 +Epoch: [18] [ 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33369 +Epoch: [18] [1010/1319] eta: 0:14:47 lr: 2.8277149530212353e-05 loss: 0.0492 (0.0590) time: 2.8570 data: 0.0079 max mem: 33369 +Epoch: [18] [1020/1319] eta: 0:14:18 lr: 2.8268062555892616e-05 loss: 0.0504 (0.0590) time: 2.8814 data: 0.0075 max mem: 33369 +Epoch: [18] [1030/1319] eta: 0:13:49 lr: 2.82589752569975e-05 loss: 0.0563 (0.0590) time: 2.8911 data: 0.0071 max mem: 33369 +Epoch: [18] [1040/1319] eta: 0:13:21 lr: 2.8249887633399437e-05 loss: 0.0538 (0.0590) time: 2.8966 data: 0.0072 max mem: 33369 +Epoch: [18] [1050/1319] eta: 0:12:52 lr: 2.8240799684970753e-05 loss: 0.0525 (0.0590) time: 2.8482 data: 0.0071 max mem: 33369 +Epoch: [18] [1060/1319] eta: 0:12:23 lr: 2.8231711411583693e-05 loss: 0.0525 (0.0590) time: 2.8711 data: 0.0076 max mem: 33369 +Epoch: [18] [1070/1319] eta: 0:11:55 lr: 2.8222622813110382e-05 loss: 0.0585 (0.0591) time: 2.9017 data: 0.0077 max mem: 33369 +Epoch: [18] [1080/1319] eta: 0:11:26 lr: 2.821353388942287e-05 loss: 0.0531 (0.0590) time: 2.8593 data: 0.0073 max mem: 33369 +Epoch: [18] [1090/1319] eta: 0:10:57 lr: 2.820444464039311e-05 loss: 0.0514 (0.0590) time: 2.8743 data: 0.0073 max mem: 33369 +Epoch: [18] [1100/1319] eta: 0:10:28 lr: 2.819535506589294e-05 loss: 0.0533 (0.0590) time: 2.8494 data: 0.0077 max mem: 33369 +Epoch: [18] [1110/1319] eta: 0:10:00 lr: 2.8186265165794125e-05 loss: 0.0555 (0.0590) time: 2.8479 data: 0.0077 max mem: 33369 +Epoch: [18] [1120/1319] eta: 0:09:31 lr: 2.817717493996831e-05 loss: 0.0603 (0.0591) time: 2.9016 data: 0.0073 max mem: 33369 +Epoch: [18] [1130/1319] eta: 0:09:02 lr: 2.816808438828707e-05 loss: 0.0691 (0.0592) time: 2.8873 data: 0.0072 max mem: 33369 +Epoch: [18] [1140/1319] eta: 0:08:33 lr: 2.8158993510621856e-05 loss: 0.0488 (0.0590) time: 2.8622 data: 0.0076 max mem: 33369 +Epoch: [18] [1150/1319] eta: 0:08:05 lr: 2.814990230684405e-05 loss: 0.0408 (0.0590) time: 2.8599 data: 0.0077 max mem: 33369 +Epoch: [18] [1160/1319] eta: 0:07:36 lr: 2.814081077682491e-05 loss: 0.0540 (0.0591) time: 2.8779 data: 0.0073 max mem: 33369 +Epoch: [18] [1170/1319] eta: 0:07:07 lr: 2.8131718920435623e-05 loss: 0.0568 (0.0591) time: 2.8743 data: 0.0070 max mem: 33369 +Epoch: [18] [1180/1319] eta: 0:06:39 lr: 2.812262673754726e-05 loss: 0.0488 (0.0590) time: 2.8512 data: 0.0072 max mem: 33369 +Epoch: [18] [1190/1319] eta: 0:06:10 lr: 2.8113534228030784e-05 loss: 0.0466 (0.0590) time: 2.8371 data: 0.0075 max mem: 33369 +Epoch: [18] [1200/1319] eta: 0:05:41 lr: 2.8104441391757102e-05 loss: 0.0456 (0.0589) time: 2.7974 data: 0.0075 max mem: 33369 +Epoch: [18] [1210/1319] eta: 0:05:12 lr: 2.809534822859698e-05 loss: 0.0515 (0.0589) time: 2.8923 data: 0.0073 max mem: 33369 +Epoch: [18] [1220/1319] eta: 0:04:44 lr: 2.8086254738421114e-05 loss: 0.0515 (0.0591) time: 2.9586 data: 0.0072 max mem: 33369 +Epoch: [18] [1230/1319] eta: 0:04:15 lr: 2.8077160921100087e-05 loss: 0.0495 (0.0590) time: 2.8893 data: 0.0068 max mem: 33369 +Epoch: [18] [1240/1319] eta: 0:03:46 lr: 2.8068066776504393e-05 loss: 0.0472 (0.0590) time: 2.8830 data: 0.0069 max mem: 33369 +Epoch: [18] [1250/1319] eta: 0:03:18 lr: 2.8058972304504428e-05 loss: 0.0493 (0.0590) time: 2.8913 data: 0.0076 max mem: 33369 +Epoch: [18] [1260/1319] eta: 0:02:49 lr: 2.8049877504970483e-05 loss: 0.0587 (0.0590) time: 2.8609 data: 0.0083 max mem: 33369 +Epoch: [18] [1270/1319] eta: 0:02:20 lr: 2.8040782377772763e-05 loss: 0.0463 (0.0589) time: 2.8264 data: 0.0082 max mem: 33369 +Epoch: [18] [1280/1319] eta: 0:01:51 lr: 2.803168692278136e-05 loss: 0.0479 (0.0589) time: 2.8613 data: 0.0077 max mem: 33369 +Epoch: [18] [1290/1319] eta: 0:01:23 lr: 2.8022591139866265e-05 loss: 0.0533 (0.0589) time: 2.8147 data: 0.0074 max mem: 33369 +Epoch: [18] [1300/1319] eta: 0:00:54 lr: 2.80134950288974e-05 loss: 0.0500 (0.0589) time: 2.6861 data: 0.0069 max mem: 33369 +Epoch: [18] [1310/1319] eta: 0:00:25 lr: 2.800439858974456e-05 loss: 0.0674 (0.0590) time: 2.6598 data: 0.0066 max mem: 33369 +Epoch: [18] Total time: 1:03:02 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 2:12:59 time: 3.1013 data: 3.0131 max mem: 33369 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 100/2573] eta: 0:04:14 time: 0.0727 data: 0.0013 max mem: 33369 +Test: [ 200/2573] eta: 0:03:31 time: 0.0747 data: 0.0013 max mem: 33369 +Test: [ 300/2573] eta: 0:03:10 time: 0.0762 data: 0.0012 max mem: 33369 +Test: [ 400/2573] eta: 0:02:57 time: 0.0763 data: 0.0012 max mem: 33369 +Test: [ 500/2573] eta: 0:02:46 time: 0.0746 data: 0.0012 max mem: 33369 +Test: [ 600/2573] eta: 0:02:36 time: 0.0746 data: 0.0012 max mem: 33369 +Test: [ 700/2573] eta: 0:02:28 time: 0.0750 data: 0.0013 max mem: 33369 +Test: [ 800/2573] eta: 0:02:19 time: 0.0785 data: 0.0012 max mem: 33369 +Test: [ 900/2573] eta: 0:02:11 time: 0.0749 data: 0.0012 max mem: 33369 +Test: [1000/2573] eta: 0:02:02 time: 0.0753 data: 0.0013 max mem: 33369 +Test: [1100/2573] eta: 0:01:54 time: 0.0750 data: 0.0012 max mem: 33369 +Test: [1200/2573] eta: 0:01:46 time: 0.0751 data: 0.0012 max mem: 33369 +Test: [1300/2573] eta: 0:01:38 time: 0.0752 data: 0.0012 max mem: 33369 +Test: [1400/2573] eta: 0:01:30 time: 0.0735 data: 0.0012 max mem: 33369 +Test: [1500/2573] eta: 0:01:22 time: 0.0753 data: 0.0013 max mem: 33369 +Test: [1600/2573] eta: 0:01:14 time: 0.0786 data: 0.0013 max mem: 33369 +Test: [1700/2573] eta: 0:01:07 time: 0.0735 data: 0.0012 max mem: 33369 +Test: [1800/2573] eta: 0:00:59 time: 0.0771 data: 0.0013 max mem: 33369 +Test: [1900/2573] eta: 0:00:51 time: 0.0736 data: 0.0012 max mem: 33369 +Test: [2000/2573] eta: 0:00:43 time: 0.0753 data: 0.0012 max mem: 33369 +Test: [2100/2573] eta: 0:00:36 time: 0.0760 data: 0.0011 max mem: 33369 +Test: [2200/2573] eta: 0:00:28 time: 0.0762 data: 0.0011 max mem: 33369 +Test: [2300/2573] eta: 0:00:20 time: 0.0761 data: 0.0012 max mem: 33369 +Test: [2400/2573] eta: 0:00:13 time: 0.0710 data: 0.0011 max mem: 33369 +Test: [2500/2573] eta: 0:00:05 time: 0.0771 data: 0.0015 max mem: 33369 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: Total time: 0:03:16 +Final results: +Mean IoU is 62.80 + + precision@0.5 = 70.32 + precision@0.6 = 64.95 + precision@0.7 = 57.99 + precision@0.8 = 45.89 + precision@0.9 = 22.12 + overall IoU = 60.31 + +Average object IoU 62.80083021613409 +Overall IoU 60.31056213378906 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [19] [ 0/1319] eta: 3:38:15 lr: 2.7996211513802005e-05 loss: 0.0362 (0.0362) time: 9.9280 data: 1.4078 max mem: 33369 +Epoch: [19] [ 10/1319] eta: 1:16:20 lr: 2.7987114450740563e-05 loss: 0.0522 (0.0518) time: 3.4995 data: 0.1344 max mem: 33369 +Epoch: [19] [ 20/1319] eta: 1:09:56 lr: 2.7978017059117013e-05 loss: 0.0522 (0.0540) time: 2.8958 data: 0.0069 max mem: 33369 +Epoch: [19] [ 30/1319] eta: 1:06:50 lr: 2.7968919338800786e-05 loss: 0.0485 (0.0567) time: 2.8977 data: 0.0072 max mem: 33369 +Epoch: [19] [ 40/1319] eta: 1:05:14 lr: 2.7959821289661182e-05 loss: 0.0461 (0.0556) time: 2.8826 data: 0.0073 max mem: 33369 +Epoch: [19] [ 50/1319] eta: 1:03:59 lr: 2.795072291156743e-05 loss: 0.0468 (0.0554) time: 2.8939 data: 0.0068 max mem: 33369 +Epoch: [19] [ 60/1319] eta: 1:02:55 lr: 2.7941624204388656e-05 loss: 0.0504 (0.0554) time: 2.8708 data: 0.0067 max mem: 33369 +Epoch: [19] [ 70/1319] eta: 1:02:00 lr: 2.7932525167993873e-05 loss: 0.0470 (0.0542) time: 2.8595 data: 0.0069 max mem: 33369 +Epoch: [19] [ 80/1319] eta: 1:01:06 lr: 2.7923425802252002e-05 loss: 0.0538 (0.0570) time: 2.8383 data: 0.0072 max mem: 33369 +Epoch: [19] [ 90/1319] eta: 1:00:22 lr: 2.791432610703186e-05 loss: 0.0566 (0.0575) time: 2.8355 data: 0.0072 max mem: 33369 +Epoch: [19] [ 100/1319] eta: 0:59:40 lr: 2.790522608220219e-05 loss: 0.0528 (0.0573) time: 2.8505 data: 0.0071 max mem: 33369 +Epoch: [19] [ 110/1319] eta: 0:59:05 lr: 2.789612572763159e-05 loss: 0.0546 (0.0573) time: 2.8624 data: 0.0069 max mem: 33369 +Epoch: [19] [ 120/1319] eta: 0:58:35 lr: 2.7887025043188598e-05 loss: 0.0497 (0.0561) time: 2.9025 data: 0.0069 max mem: 33369 +Epoch: [19] [ 130/1319] eta: 0:58:00 lr: 2.7877924028741625e-05 loss: 0.0421 (0.0555) time: 2.9003 data: 0.0073 max mem: 33369 +Epoch: [19] [ 140/1319] eta: 0:57:22 lr: 2.7868822684159008e-05 loss: 0.0454 (0.0549) time: 2.8474 data: 0.0073 max mem: 33369 +Epoch: [19] [ 150/1319] eta: 0:56:50 lr: 2.7859721009308947e-05 loss: 0.0454 (0.0547) time: 2.8515 data: 0.0075 max mem: 33369 +Epoch: [19] [ 160/1319] eta: 0:56:15 lr: 2.7850619004059574e-05 loss: 0.0509 (0.0558) time: 2.8637 data: 0.0078 max mem: 33369 +Epoch: [19] [ 170/1319] eta: 0:55:40 lr: 2.7841516668278917e-05 loss: 0.0490 (0.0555) time: 2.8336 data: 0.0077 max mem: 33369 +Epoch: [19] [ 180/1319] eta: 0:55:08 lr: 2.7832414001834883e-05 loss: 0.0509 (0.0556) time: 2.8417 data: 0.0074 max mem: 33369 +Epoch: [19] [ 190/1319] eta: 0:54:36 lr: 2.782331100459529e-05 loss: 0.0554 (0.0566) time: 2.8569 data: 0.0071 max mem: 33369 +Epoch: [19] [ 200/1319] eta: 0:54:05 lr: 2.781420767642787e-05 loss: 0.0551 (0.0561) time: 2.8545 data: 0.0072 max mem: 33369 +Epoch: [19] [ 210/1319] eta: 0:53:36 lr: 2.7805104017200224e-05 loss: 0.0490 (0.0559) time: 2.8858 data: 0.0072 max mem: 33369 +Epoch: [19] [ 220/1319] eta: 0:53:01 lr: 2.779600002677987e-05 loss: 0.0522 (0.0559) time: 2.8466 data: 0.0070 max mem: 33369 +Epoch: [19] [ 230/1319] eta: 0:52:36 lr: 2.778689570503424e-05 loss: 0.0522 (0.0555) time: 2.8787 data: 0.0076 max mem: 33369 +Epoch: [19] [ 240/1319] eta: 0:52:07 lr: 2.7777791051830626e-05 loss: 0.0523 (0.0556) time: 2.9399 data: 0.0075 max mem: 33369 +Epoch: [19] [ 250/1319] eta: 0:51:37 lr: 2.7768686067036253e-05 loss: 0.0550 (0.0555) time: 2.8815 data: 0.0068 max mem: 33369 +Epoch: [19] [ 260/1319] eta: 0:51:08 lr: 2.775958075051822e-05 loss: 0.0462 (0.0554) time: 2.8874 data: 0.0070 max mem: 33369 +Epoch: [19] [ 270/1319] eta: 0:50:38 lr: 2.7750475102143547e-05 loss: 0.0441 (0.0551) time: 2.8822 data: 0.0077 max mem: 33369 +Epoch: [19] [ 280/1319] eta: 0:50:06 lr: 2.7741369121779126e-05 loss: 0.0453 (0.0551) time: 2.8430 data: 0.0079 max mem: 33369 +Epoch: [19] [ 290/1319] eta: 0:49:34 lr: 2.7732262809291776e-05 loss: 0.0488 (0.0550) time: 2.8211 data: 0.0073 max mem: 33369 +Epoch: [19] [ 300/1319] eta: 0:49:07 lr: 2.7723156164548194e-05 loss: 0.0483 (0.0549) time: 2.8682 data: 0.0073 max mem: 33369 +Epoch: [19] [ 310/1319] eta: 0:48:36 lr: 2.771404918741497e-05 loss: 0.0434 (0.0547) time: 2.8811 data: 0.0074 max mem: 33369 +Epoch: [19] [ 320/1319] eta: 0:48:05 lr: 2.7704941877758615e-05 loss: 0.0538 (0.0546) time: 2.8342 data: 0.0074 max mem: 33369 +Epoch: [19] [ 330/1319] eta: 0:47:35 lr: 2.7695834235445526e-05 loss: 0.0507 (0.0545) time: 2.8387 data: 0.0073 max mem: 33369 +Epoch: [19] [ 340/1319] eta: 0:47:05 lr: 2.7686726260341988e-05 loss: 0.0444 (0.0543) time: 2.8438 data: 0.0077 max mem: 33369 +Epoch: [19] [ 350/1319] eta: 0:46:35 lr: 2.7677617952314193e-05 loss: 0.0462 (0.0544) time: 2.8488 data: 0.0076 max mem: 33369 +Epoch: [19] [ 360/1319] eta: 0:46:06 lr: 2.7668509311228242e-05 loss: 0.0549 (0.0544) time: 2.8591 data: 0.0069 max mem: 33369 +Epoch: [19] [ 370/1319] eta: 0:45:34 lr: 2.7659400336950098e-05 loss: 0.0502 (0.0544) time: 2.8117 data: 0.0070 max mem: 33369 +Epoch: [19] [ 380/1319] eta: 0:45:07 lr: 2.765029102934566e-05 loss: 0.0486 (0.0547) time: 2.8678 data: 0.0073 max mem: 33369 +Epoch: [19] [ 390/1319] eta: 0:44:37 lr: 2.764118138828069e-05 loss: 0.0531 (0.0547) time: 2.9088 data: 0.0081 max mem: 33369 +Epoch: [19] [ 400/1319] eta: 0:44:09 lr: 2.763207141362088e-05 loss: 0.0531 (0.0549) time: 2.8682 data: 0.0079 max mem: 33369 +Epoch: [19] [ 410/1319] eta: 0:43:40 lr: 2.7622961105231792e-05 loss: 0.0559 (0.0552) time: 2.8827 data: 0.0072 max mem: 33369 +Epoch: [19] [ 420/1319] eta: 0:43:12 lr: 2.7613850462978895e-05 loss: 0.0515 (0.0551) time: 2.9043 data: 0.0071 max mem: 33369 +Epoch: [19] [ 430/1319] eta: 0:42:42 lr: 2.7604739486727564e-05 loss: 0.0515 (0.0554) time: 2.8907 data: 0.0076 max mem: 33369 +Epoch: [19] [ 440/1319] eta: 0:42:12 lr: 2.759562817634305e-05 loss: 0.0578 (0.0555) time: 2.8289 data: 0.0078 max mem: 33369 +Epoch: [19] [ 450/1319] eta: 0:41:44 lr: 2.7586516531690514e-05 loss: 0.0550 (0.0555) time: 2.8540 data: 0.0074 max mem: 33369 +Epoch: [19] [ 460/1319] eta: 0:41:15 lr: 2.7577404552635017e-05 loss: 0.0503 (0.0555) time: 2.8915 data: 0.0072 max mem: 33369 +Epoch: [19] [ 470/1319] eta: 0:40:46 lr: 2.7568292239041493e-05 loss: 0.0479 (0.0554) time: 2.8724 data: 0.0076 max mem: 33369 +Epoch: [19] [ 480/1319] eta: 0:40:17 lr: 2.7559179590774802e-05 loss: 0.0448 (0.0552) time: 2.8565 data: 0.0076 max mem: 33369 +Epoch: [19] [ 490/1319] eta: 0:39:48 lr: 2.755006660769968e-05 loss: 0.0519 (0.0555) time: 2.8761 data: 0.0073 max mem: 33369 +Epoch: [19] [ 500/1319] eta: 0:39:19 lr: 2.754095328968076e-05 loss: 0.0527 (0.0555) time: 2.8968 data: 0.0071 max mem: 33369 +Epoch: [19] [ 510/1319] eta: 0:38:51 lr: 2.753183963658258e-05 loss: 0.0508 (0.0556) time: 2.8881 data: 0.0071 max mem: 33369 +Epoch: [19] [ 520/1319] eta: 0:38:21 lr: 2.7522725648269566e-05 loss: 0.0427 (0.0555) time: 2.8531 data: 0.0069 max mem: 33369 +Epoch: [19] [ 530/1319] eta: 0:37:54 lr: 2.7513611324606038e-05 loss: 0.0450 (0.0554) time: 2.9169 data: 0.0070 max mem: 33369 +Epoch: [19] [ 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(0.0553) time: 2.8795 data: 0.0071 max mem: 33369 +Epoch: [19] [ 780/1319] eta: 0:25:49 lr: 2.7285643845087027e-05 loss: 0.0472 (0.0552) time: 2.8741 data: 0.0072 max mem: 33369 +Epoch: [19] [ 790/1319] eta: 0:25:20 lr: 2.7276520754341512e-05 loss: 0.0461 (0.0550) time: 2.8750 data: 0.0079 max mem: 33369 +Epoch: [19] [ 800/1319] eta: 0:24:52 lr: 2.726739732454216e-05 loss: 0.0434 (0.0549) time: 2.8447 data: 0.0083 max mem: 33369 +Epoch: [19] [ 810/1319] eta: 0:24:23 lr: 2.7258273555550322e-05 loss: 0.0415 (0.0550) time: 2.8739 data: 0.0072 max mem: 33369 +Epoch: [19] [ 820/1319] eta: 0:23:54 lr: 2.7249149447227223e-05 loss: 0.0460 (0.0549) time: 2.8655 data: 0.0067 max mem: 33369 +Epoch: [19] [ 830/1319] eta: 0:23:26 lr: 2.7240024999433987e-05 loss: 0.0477 (0.0549) time: 2.8867 data: 0.0074 max mem: 33369 +Epoch: [19] [ 840/1319] eta: 0:22:56 lr: 2.723090021203163e-05 loss: 0.0486 (0.0549) time: 2.8717 data: 0.0075 max mem: 33369 +Epoch: [19] [ 850/1319] eta: 0:22:28 lr: 2.7221775084881062e-05 loss: 0.0501 (0.0548) time: 2.8392 data: 0.0071 max mem: 33369 +Epoch: [19] [ 860/1319] eta: 0:21:59 lr: 2.7212649617843082e-05 loss: 0.0501 (0.0548) time: 2.8838 data: 0.0073 max mem: 33369 +Epoch: [19] [ 870/1319] eta: 0:21:30 lr: 2.7203523810778376e-05 loss: 0.0476 (0.0548) time: 2.8878 data: 0.0073 max mem: 33369 +Epoch: [19] [ 880/1319] eta: 0:21:02 lr: 2.7194397663547522e-05 loss: 0.0522 (0.0549) time: 2.8813 data: 0.0076 max mem: 33369 +Epoch: [19] [ 890/1319] eta: 0:20:33 lr: 2.7185271176010996e-05 loss: 0.0531 (0.0549) time: 2.8551 data: 0.0079 max mem: 33369 +Epoch: [19] [ 900/1319] eta: 0:20:04 lr: 2.7176144348029154e-05 loss: 0.0458 (0.0548) time: 2.8493 data: 0.0077 max mem: 33369 +Epoch: [19] [ 910/1319] eta: 0:19:35 lr: 2.7167017179462245e-05 loss: 0.0492 (0.0547) time: 2.8635 data: 0.0074 max mem: 33369 +Epoch: [19] [ 920/1319] eta: 0:19:06 lr: 2.7157889670170428e-05 loss: 0.0440 (0.0546) time: 2.8728 data: 0.0074 max mem: 33369 +Epoch: [19] [ 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33369 +Epoch: [19] [1010/1319] eta: 0:14:48 lr: 2.7075726730791712e-05 loss: 0.0503 (0.0546) time: 2.8755 data: 0.0075 max mem: 33369 +Epoch: [19] [1020/1319] eta: 0:14:19 lr: 2.706659580653433e-05 loss: 0.0470 (0.0546) time: 2.8996 data: 0.0073 max mem: 33369 +Epoch: [19] [1030/1319] eta: 0:13:50 lr: 2.7057464540006328e-05 loss: 0.0470 (0.0548) time: 2.9075 data: 0.0071 max mem: 33369 +Epoch: [19] [1040/1319] eta: 0:13:21 lr: 2.7048332931066517e-05 loss: 0.0587 (0.0548) time: 2.8571 data: 0.0077 max mem: 33369 +Epoch: [19] [1050/1319] eta: 0:12:53 lr: 2.7039200979573614e-05 loss: 0.0518 (0.0548) time: 2.8412 data: 0.0079 max mem: 33369 +Epoch: [19] [1060/1319] eta: 0:12:24 lr: 2.7030068685386206e-05 loss: 0.0518 (0.0548) time: 2.8418 data: 0.0075 max mem: 33369 +Epoch: [19] [1070/1319] eta: 0:11:55 lr: 2.7020936048362782e-05 loss: 0.0474 (0.0548) time: 2.8531 data: 0.0073 max mem: 33369 +Epoch: [19] [1080/1319] eta: 0:11:26 lr: 2.7011803068361714e-05 loss: 0.0445 (0.0547) time: 2.8801 data: 0.0074 max mem: 33369 +Epoch: [19] [1090/1319] eta: 0:10:58 lr: 2.700266974524126e-05 loss: 0.0541 (0.0548) time: 2.8841 data: 0.0073 max mem: 33369 +Epoch: [19] [1100/1319] eta: 0:10:29 lr: 2.699353607885957e-05 loss: 0.0510 (0.0548) time: 2.8746 data: 0.0071 max mem: 33369 +Epoch: [19] [1110/1319] eta: 0:10:00 lr: 2.6984402069074687e-05 loss: 0.0494 (0.0548) time: 2.8774 data: 0.0074 max mem: 33369 +Epoch: [19] [1120/1319] eta: 0:09:31 lr: 2.6975267715744523e-05 loss: 0.0506 (0.0548) time: 2.8691 data: 0.0076 max mem: 33369 +Epoch: [19] [1130/1319] eta: 0:09:03 lr: 2.6966133018726902e-05 loss: 0.0506 (0.0549) time: 2.9200 data: 0.0076 max mem: 33369 +Epoch: [19] [1140/1319] eta: 0:08:34 lr: 2.6956997977879505e-05 loss: 0.0534 (0.0550) time: 2.9514 data: 0.0072 max mem: 33369 +Epoch: [19] [1150/1319] eta: 0:08:05 lr: 2.6947862593059943e-05 loss: 0.0548 (0.0550) time: 2.8813 data: 0.0070 max mem: 33369 +Epoch: [19] [1160/1319] eta: 0:07:37 lr: 2.6938726864125667e-05 loss: 0.0506 (0.0550) time: 2.8671 data: 0.0075 max mem: 33369 +Epoch: [19] [1170/1319] eta: 0:07:08 lr: 2.6929590790934063e-05 loss: 0.0506 (0.0549) time: 2.8532 data: 0.0081 max mem: 33369 +Epoch: [19] [1180/1319] eta: 0:06:39 lr: 2.6920454373342357e-05 loss: 0.0498 (0.0550) time: 2.8238 data: 0.0075 max mem: 33369 +Epoch: [19] [1190/1319] eta: 0:06:10 lr: 2.6911317611207703e-05 loss: 0.0487 (0.0551) time: 2.8527 data: 0.0070 max mem: 33369 +Epoch: [19] [1200/1319] eta: 0:05:41 lr: 2.6902180504387114e-05 loss: 0.0576 (0.0551) time: 2.8687 data: 0.0070 max mem: 33369 +Epoch: [19] [1210/1319] eta: 0:05:13 lr: 2.689304305273751e-05 loss: 0.0600 (0.0551) time: 2.8618 data: 0.0075 max mem: 33369 +Epoch: [19] [1220/1319] eta: 0:04:44 lr: 2.6883905256115667e-05 loss: 0.0606 (0.0552) time: 2.8819 data: 0.0077 max mem: 33369 +Epoch: [19] [1230/1319] eta: 0:04:15 lr: 2.687476711437828e-05 loss: 0.0535 (0.0552) time: 2.9139 data: 0.0073 max mem: 33369 +Epoch: [19] [1240/1319] eta: 0:03:47 lr: 2.6865628627381928e-05 loss: 0.0519 (0.0552) time: 2.8927 data: 0.0071 max mem: 33369 +Epoch: [19] [1250/1319] eta: 0:03:18 lr: 2.6856489794983043e-05 loss: 0.0510 (0.0552) time: 2.8845 data: 0.0071 max mem: 33369 +Epoch: [19] [1260/1319] eta: 0:02:49 lr: 2.6847350617037976e-05 loss: 0.0510 (0.0552) time: 2.8948 data: 0.0073 max mem: 33369 +Epoch: [19] [1270/1319] eta: 0:02:20 lr: 2.683821109340296e-05 loss: 0.0436 (0.0552) time: 2.8559 data: 0.0071 max mem: 33369 +Epoch: [19] [1280/1319] eta: 0:01:52 lr: 2.68290712239341e-05 loss: 0.0452 (0.0552) time: 2.9033 data: 0.0072 max mem: 33369 +Epoch: [19] [1290/1319] eta: 0:01:23 lr: 2.681993100848739e-05 loss: 0.0548 (0.0552) time: 2.9371 data: 0.0074 max mem: 33369 +Epoch: [19] [1300/1319] eta: 0:00:54 lr: 2.6810790446918727e-05 loss: 0.0512 (0.0552) time: 2.8943 data: 0.0074 max mem: 33369 +Epoch: [19] [1310/1319] eta: 0:00:25 lr: 2.680164953908387e-05 loss: 0.0539 (0.0555) time: 2.8609 data: 0.0076 max mem: 33369 +Epoch: [19] Total time: 1:03:12 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 2:15:21 time: 3.1565 data: 3.0564 max mem: 33369 +Test: [ 100/2573] eta: 0:04:16 time: 0.0727 data: 0.0013 max mem: 33369 +Test: [ 200/2573] eta: 0:03:32 time: 0.0742 data: 0.0012 max mem: 33369 +Test: [ 300/2573] eta: 0:03:12 time: 0.0762 data: 0.0012 max mem: 33369 +Test: [ 400/2573] eta: 0:02:57 time: 0.0760 data: 0.0012 max mem: 33369 +Test: [ 500/2573] eta: 0:02:46 time: 0.0749 data: 0.0013 max mem: 33369 +Test: [ 600/2573] eta: 0:02:37 time: 0.0746 data: 0.0012 max mem: 33369 +Test: [ 700/2573] eta: 0:02:28 time: 0.0749 data: 0.0012 max mem: 33369 +Test: [ 800/2573] eta: 0:02:19 time: 0.0776 data: 0.0011 max mem: 33369 +Test: [ 900/2573] eta: 0:02:11 time: 0.0744 data: 0.0011 max mem: 33369 +Test: [1000/2573] eta: 0:02:02 time: 0.0743 data: 0.0011 max mem: 33369 +Test: [1100/2573] eta: 0:01:54 time: 0.0744 data: 0.0012 max mem: 33369 +Test: [1200/2573] eta: 0:01:46 time: 0.0750 data: 0.0012 max mem: 33369 +Test: [1300/2573] eta: 0:01:38 time: 0.0750 data: 0.0012 max mem: 33369 +Test: [1400/2573] eta: 0:01:30 time: 0.0735 data: 0.0013 max mem: 33369 +Test: [1500/2573] eta: 0:01:22 time: 0.0749 data: 0.0013 max mem: 33369 +Test: [1600/2573] eta: 0:01:14 time: 0.0784 data: 0.0012 max mem: 33369 +Test: [1700/2573] eta: 0:01:07 time: 0.0735 data: 0.0012 max mem: 33369 +Test: [1800/2573] eta: 0:00:59 time: 0.0767 data: 0.0012 max mem: 33369 +Test: [1900/2573] eta: 0:00:51 time: 0.0736 data: 0.0013 max mem: 33369 +Test: [2000/2573] eta: 0:00:43 time: 0.0753 data: 0.0013 max mem: 33369 +Test: [2100/2573] eta: 0:00:36 time: 0.0769 data: 0.0012 max mem: 33369 +Test: [2200/2573] eta: 0:00:28 time: 0.0768 data: 0.0013 max mem: 33369 +Test: [2300/2573] eta: 0:00:20 time: 0.0769 data: 0.0013 max mem: 33369 +Test: [2400/2573] eta: 0:00:13 time: 0.0723 data: 0.0013 max mem: 33369 +Test: [2500/2573] eta: 0:00:05 time: 0.0751 data: 0.0013 max mem: 33369 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: Total time: 0:03:16 +Final results: +Mean IoU is 62.82 + + precision@0.5 = 70.67 + precision@0.6 = 65.48 + precision@0.7 = 58.23 + precision@0.8 = 46.71 + precision@0.9 = 22.08 + overall IoU = 60.60 + +Average object IoU 62.82298524574295 +Overall IoU 60.60129165649414 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [20] [ 0/1319] eta: 3:01:10 lr: 2.6793422425855603e-05 loss: 0.0417 (0.0417) time: 8.2415 data: 2.0433 max mem: 33369 +Epoch: [20] [ 10/1319] eta: 1:13:04 lr: 2.678428085971722e-05 loss: 0.0461 (0.0463) time: 3.3495 data: 0.1927 max mem: 33369 +Epoch: [20] [ 20/1319] eta: 1:07:11 lr: 2.6775138946893718e-05 loss: 0.0404 (0.0455) time: 2.8467 data: 0.0075 max mem: 33369 +Epoch: [20] [ 30/1319] eta: 1:04:46 lr: 2.6765996687240426e-05 loss: 0.0450 (0.0479) time: 2.8314 data: 0.0072 max mem: 33369 +Epoch: [20] [ 40/1319] eta: 1:03:56 lr: 2.675685408061254e-05 loss: 0.0499 (0.0479) time: 2.8899 data: 0.0073 max mem: 33369 +Epoch: [20] [ 50/1319] eta: 1:02:53 lr: 2.6747711126865168e-05 loss: 0.0501 (0.0485) time: 2.9096 data: 0.0077 max mem: 33369 +Epoch: [20] [ 60/1319] eta: 1:02:14 lr: 2.6738567825853273e-05 loss: 0.0501 (0.0495) time: 2.8980 data: 0.0077 max mem: 33369 +Epoch: [20] [ 70/1319] eta: 1:01:19 lr: 2.6729424177431713e-05 loss: 0.0500 (0.0505) time: 2.8745 data: 0.0075 max mem: 33369 +Epoch: [20] [ 80/1319] eta: 1:00:34 lr: 2.6720280181455227e-05 loss: 0.0472 (0.0500) time: 2.8348 data: 0.0074 max mem: 33369 +Epoch: [20] [ 90/1319] eta: 0:59:55 lr: 2.671113583777845e-05 loss: 0.0429 (0.0499) time: 2.8549 data: 0.0071 max mem: 33369 +Epoch: [20] [ 100/1319] eta: 0:59:18 lr: 2.670199114625589e-05 loss: 0.0429 (0.0495) time: 2.8602 data: 0.0072 max mem: 33369 +Epoch: [20] [ 110/1319] eta: 0:58:36 lr: 2.6692846106741932e-05 loss: 0.0429 (0.0497) time: 2.8302 data: 0.0073 max mem: 33369 +Epoch: [20] [ 120/1319] eta: 0:58:08 lr: 2.668370071909087e-05 loss: 0.0458 (0.0502) time: 2.8598 data: 0.0072 max mem: 33369 +Epoch: [20] [ 130/1319] eta: 0:57:37 lr: 2.6674554983156852e-05 loss: 0.0436 (0.0504) time: 2.9066 data: 0.0074 max mem: 33369 +Epoch: [20] [ 140/1319] eta: 0:57:03 lr: 2.666540889879393e-05 loss: 0.0454 (0.0513) time: 2.8678 data: 0.0079 max mem: 33369 +Epoch: [20] [ 150/1319] eta: 0:56:30 lr: 2.6656262465856026e-05 loss: 0.0467 (0.0520) time: 2.8495 data: 0.0078 max mem: 33369 +Epoch: [20] [ 160/1319] eta: 0:55:59 lr: 2.6647115684196954e-05 loss: 0.0550 (0.0521) time: 2.8627 data: 0.0074 max mem: 33369 +Epoch: [20] [ 170/1319] eta: 0:55:30 lr: 2.663796855367041e-05 loss: 0.0460 (0.0522) time: 2.8872 data: 0.0074 max mem: 33369 +Epoch: [20] [ 180/1319] eta: 0:54:59 lr: 2.662882107412996e-05 loss: 0.0460 (0.0520) time: 2.8844 data: 0.0074 max mem: 33369 +Epoch: [20] [ 190/1319] eta: 0:54:34 lr: 2.661967324542908e-05 loss: 0.0537 (0.0525) time: 2.9131 data: 0.0071 max mem: 33369 +Epoch: [20] [ 200/1319] eta: 0:54:03 lr: 2.6610525067421092e-05 loss: 0.0476 (0.0518) time: 2.9099 data: 0.0072 max mem: 33369 +Epoch: [20] [ 210/1319] eta: 0:53:35 lr: 2.6601376539959238e-05 loss: 0.0401 (0.0519) time: 2.8862 data: 0.0073 max mem: 33369 +Epoch: [20] [ 220/1319] eta: 0:53:06 lr: 2.6592227662896617e-05 loss: 0.0462 (0.0521) time: 2.9119 data: 0.0071 max mem: 33369 +Epoch: [20] [ 230/1319] eta: 0:52:35 lr: 2.658307843608621e-05 loss: 0.0551 (0.0522) time: 2.8767 data: 0.0075 max mem: 33369 +Epoch: [20] [ 240/1319] eta: 0:52:05 lr: 2.65739288593809e-05 loss: 0.0551 (0.0530) time: 2.8663 data: 0.0077 max mem: 33369 +Epoch: [20] [ 250/1319] eta: 0:51:35 lr: 2.6564778932633426e-05 loss: 0.0565 (0.0530) time: 2.8789 data: 0.0078 max mem: 33369 +Epoch: [20] [ 260/1319] eta: 0:51:03 lr: 2.655562865569643e-05 loss: 0.0481 (0.0531) time: 2.8520 data: 0.0076 max mem: 33369 +Epoch: [20] [ 270/1319] eta: 0:50:36 lr: 2.654647802842242e-05 loss: 0.0519 (0.0531) time: 2.8825 data: 0.0076 max mem: 33369 +Epoch: [20] [ 280/1319] eta: 0:50:07 lr: 2.6537327050663813e-05 loss: 0.0473 (0.0532) time: 2.9188 data: 0.0076 max mem: 33369 +Epoch: [20] [ 290/1319] eta: 0:49:39 lr: 2.6528175722272857e-05 loss: 0.0482 (0.0531) time: 2.9110 data: 0.0071 max mem: 33369 +Epoch: [20] [ 300/1319] eta: 0:49:09 lr: 2.6519024043101733e-05 loss: 0.0536 (0.0538) time: 2.8818 data: 0.0073 max mem: 33369 +Epoch: [20] [ 310/1319] eta: 0:48:39 lr: 2.6509872013002462e-05 loss: 0.0501 (0.0537) time: 2.8604 data: 0.0075 max mem: 33369 +Epoch: [20] [ 320/1319] eta: 0:48:10 lr: 2.6500719631826982e-05 loss: 0.0408 (0.0534) time: 2.8748 data: 0.0073 max mem: 33369 +Epoch: [20] [ 330/1319] eta: 0:47:38 lr: 2.649156689942709e-05 loss: 0.0439 (0.0532) time: 2.8403 data: 0.0071 max mem: 33369 +Epoch: [20] [ 340/1319] eta: 0:47:11 lr: 2.648241381565446e-05 loss: 0.0467 (0.0531) time: 2.8756 data: 0.0074 max mem: 33369 +Epoch: [20] [ 350/1319] eta: 0:46:42 lr: 2.6473260380360663e-05 loss: 0.0555 (0.0534) time: 2.9263 data: 0.0076 max mem: 33369 +Epoch: [20] [ 360/1319] eta: 0:46:13 lr: 2.6464106593397137e-05 loss: 0.0572 (0.0534) time: 2.8895 data: 0.0071 max mem: 33369 +Epoch: [20] [ 370/1319] eta: 0:45:43 lr: 2.6454952454615202e-05 loss: 0.0498 (0.0533) time: 2.8602 data: 0.0069 max mem: 33369 +Epoch: [20] [ 380/1319] eta: 0:45:14 lr: 2.6445797963866064e-05 loss: 0.0495 (0.0534) time: 2.8778 data: 0.0071 max mem: 33369 +Epoch: [20] [ 390/1319] eta: 0:44:45 lr: 2.643664312100081e-05 loss: 0.0436 (0.0533) time: 2.8818 data: 0.0071 max mem: 33369 +Epoch: [20] [ 400/1319] eta: 0:44:15 lr: 2.6427487925870388e-05 loss: 0.0460 (0.0532) time: 2.8510 data: 0.0068 max mem: 33369 +Epoch: [20] [ 410/1319] eta: 0:43:43 lr: 2.641833237832565e-05 loss: 0.0430 (0.0533) time: 2.8001 data: 0.0069 max mem: 33369 +Epoch: [20] [ 420/1319] eta: 0:43:15 lr: 2.6409176478217318e-05 loss: 0.0429 (0.0532) time: 2.8526 data: 0.0076 max mem: 33369 +Epoch: [20] [ 430/1319] eta: 0:42:46 lr: 2.640002022539598e-05 loss: 0.0486 (0.0533) time: 2.9082 data: 0.0079 max mem: 33369 +Epoch: [20] [ 440/1319] eta: 0:42:17 lr: 2.6390863619712137e-05 loss: 0.0492 (0.0532) time: 2.8688 data: 0.0074 max mem: 33369 +Epoch: [20] [ 450/1319] eta: 0:41:48 lr: 2.6381706661016125e-05 loss: 0.0516 (0.0535) time: 2.8883 data: 0.0072 max mem: 33369 +Epoch: [20] [ 460/1319] eta: 0:41:19 lr: 2.637254934915819e-05 loss: 0.0556 (0.0533) time: 2.8943 data: 0.0070 max mem: 33369 +Epoch: [20] [ 470/1319] eta: 0:40:50 lr: 2.6363391683988447e-05 loss: 0.0466 (0.0533) time: 2.8843 data: 0.0073 max mem: 33369 +Epoch: [20] [ 480/1319] eta: 0:40:20 lr: 2.6354233665356892e-05 loss: 0.0503 (0.0533) time: 2.8460 data: 0.0076 max mem: 33369 +Epoch: [20] [ 490/1319] eta: 0:39:52 lr: 2.6345075293113398e-05 loss: 0.0468 (0.0531) time: 2.8640 data: 0.0072 max mem: 33369 +Epoch: [20] [ 500/1319] eta: 0:39:23 lr: 2.633591656710771e-05 loss: 0.0345 (0.0530) time: 2.8890 data: 0.0077 max mem: 33369 +Epoch: [20] [ 510/1319] eta: 0:38:54 lr: 2.6326757487189457e-05 loss: 0.0394 (0.0528) time: 2.8819 data: 0.0082 max mem: 33369 +Epoch: [20] [ 520/1319] eta: 0:38:25 lr: 2.6317598053208148e-05 loss: 0.0402 (0.0528) time: 2.8883 data: 0.0074 max mem: 33369 +Epoch: [20] [ 530/1319] eta: 0:37:56 lr: 2.6308438265013168e-05 loss: 0.0469 (0.0528) time: 2.8780 data: 0.0069 max mem: 33369 +Epoch: [20] [ 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(0.0523) time: 2.8778 data: 0.0077 max mem: 33369 +Epoch: [20] [ 780/1319] eta: 0:25:53 lr: 2.6079327997624963e-05 loss: 0.0439 (0.0522) time: 2.8457 data: 0.0071 max mem: 33369 +Epoch: [20] [ 790/1319] eta: 0:25:25 lr: 2.6070158946604555e-05 loss: 0.0459 (0.0524) time: 2.8885 data: 0.0072 max mem: 33369 +Epoch: [20] [ 800/1319] eta: 0:24:54 lr: 2.6060989537257118e-05 loss: 0.0517 (0.0524) time: 2.8397 data: 0.0073 max mem: 33369 +Epoch: [20] [ 810/1319] eta: 0:24:24 lr: 2.6051819769428553e-05 loss: 0.0477 (0.0523) time: 2.6694 data: 0.0069 max mem: 33369 +Epoch: [20] [ 820/1319] eta: 0:23:55 lr: 2.604264964296463e-05 loss: 0.0498 (0.0524) time: 2.7420 data: 0.0071 max mem: 33369 +Epoch: [20] [ 830/1319] eta: 0:23:26 lr: 2.6033479157711e-05 loss: 0.0498 (0.0524) time: 2.8544 data: 0.0073 max mem: 33369 +Epoch: [20] [ 840/1319] eta: 0:22:58 lr: 2.6024308313513185e-05 loss: 0.0440 (0.0524) time: 2.9022 data: 0.0070 max mem: 33369 +Epoch: [20] [ 850/1319] eta: 0:22:29 lr: 2.601513711021658e-05 loss: 0.0481 (0.0524) time: 2.9161 data: 0.0071 max mem: 33369 +Epoch: [20] [ 860/1319] eta: 0:22:01 lr: 2.6005965547666454e-05 loss: 0.0460 (0.0524) time: 2.8994 data: 0.0073 max mem: 33369 +Epoch: [20] [ 870/1319] eta: 0:21:32 lr: 2.599679362570795e-05 loss: 0.0443 (0.0523) time: 2.8939 data: 0.0072 max mem: 33369 +Epoch: [20] [ 880/1319] eta: 0:21:03 lr: 2.598762134418607e-05 loss: 0.0400 (0.0523) time: 2.8804 data: 0.0071 max mem: 33369 +Epoch: [20] [ 890/1319] eta: 0:20:34 lr: 2.5978448702945707e-05 loss: 0.0386 (0.0521) time: 2.8393 data: 0.0070 max mem: 33369 +Epoch: [20] [ 900/1319] eta: 0:20:06 lr: 2.596927570183162e-05 loss: 0.0406 (0.0521) time: 2.8972 data: 0.0072 max mem: 33369 +Epoch: [20] [ 910/1319] eta: 0:19:37 lr: 2.5960102340688436e-05 loss: 0.0522 (0.0522) time: 2.9348 data: 0.0076 max mem: 33369 +Epoch: [20] [ 920/1319] eta: 0:19:08 lr: 2.5950928619360655e-05 loss: 0.0528 (0.0522) time: 2.8706 data: 0.0079 max mem: 33369 +Epoch: [20] [ 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33369 +Epoch: [20] [1010/1319] eta: 0:14:49 lr: 2.586834889338287e-05 loss: 0.0454 (0.0522) time: 2.8924 data: 0.0073 max mem: 33369 +Epoch: [20] [1020/1319] eta: 0:14:20 lr: 2.58591715616284e-05 loss: 0.0475 (0.0522) time: 2.8529 data: 0.0071 max mem: 33369 +Epoch: [20] [1030/1319] eta: 0:13:51 lr: 2.584999386797035e-05 loss: 0.0466 (0.0521) time: 2.8662 data: 0.0070 max mem: 33369 +Epoch: [20] [1040/1319] eta: 0:13:22 lr: 2.5840815812251663e-05 loss: 0.0393 (0.0520) time: 2.8329 data: 0.0069 max mem: 33369 +Epoch: [20] [1050/1319] eta: 0:12:54 lr: 2.583163739431517e-05 loss: 0.0443 (0.0520) time: 2.8784 data: 0.0073 max mem: 33369 +Epoch: [20] [1060/1319] eta: 0:12:25 lr: 2.582245861400355e-05 loss: 0.0441 (0.0519) time: 2.9376 data: 0.0074 max mem: 33369 +Epoch: [20] [1070/1319] eta: 0:11:56 lr: 2.5813279471159375e-05 loss: 0.0426 (0.0519) time: 2.8968 data: 0.0073 max mem: 33369 +Epoch: [20] [1080/1319] eta: 0:11:27 lr: 2.5804099965625085e-05 loss: 0.0482 (0.0519) time: 2.8707 data: 0.0080 max mem: 33369 +Epoch: [20] [1090/1319] eta: 0:10:59 lr: 2.5794920097242954e-05 loss: 0.0493 (0.0519) time: 2.8568 data: 0.0083 max mem: 33369 +Epoch: [20] [1100/1319] eta: 0:10:30 lr: 2.5785739865855164e-05 loss: 0.0388 (0.0518) time: 2.8618 data: 0.0082 max mem: 33369 +Epoch: [20] [1110/1319] eta: 0:10:01 lr: 2.5776559271303753e-05 loss: 0.0496 (0.0518) time: 2.8156 data: 0.0075 max mem: 33369 +Epoch: [20] [1120/1319] eta: 0:09:32 lr: 2.5767378313430623e-05 loss: 0.0496 (0.0518) time: 2.8498 data: 0.0071 max mem: 33369 +Epoch: [20] [1130/1319] eta: 0:09:03 lr: 2.5758196992077554e-05 loss: 0.0528 (0.0520) time: 2.8924 data: 0.0072 max mem: 33369 +Epoch: [20] [1140/1319] eta: 0:08:34 lr: 2.574901530708619e-05 loss: 0.0530 (0.0520) time: 2.8577 data: 0.0071 max mem: 33369 +Epoch: [20] [1150/1319] eta: 0:08:06 lr: 2.573983325829803e-05 loss: 0.0528 (0.0521) time: 2.8740 data: 0.0071 max mem: 33369 +Epoch: [20] [1160/1319] eta: 0:07:37 lr: 2.573065084555446e-05 loss: 0.0532 (0.0522) time: 2.8857 data: 0.0077 max mem: 33369 +Epoch: [20] [1170/1319] eta: 0:07:08 lr: 2.572146806869673e-05 loss: 0.0529 (0.0522) time: 2.9012 data: 0.0077 max mem: 33369 +Epoch: [20] [1180/1319] eta: 0:06:39 lr: 2.5712284927565954e-05 loss: 0.0500 (0.0522) time: 2.9010 data: 0.0072 max mem: 33369 +Epoch: [20] [1190/1319] eta: 0:06:11 lr: 2.5703101422003118e-05 loss: 0.0480 (0.0522) time: 2.8145 data: 0.0072 max mem: 33369 +Epoch: [20] [1200/1319] eta: 0:05:42 lr: 2.569391755184906e-05 loss: 0.0455 (0.0522) time: 2.8497 data: 0.0075 max mem: 33369 +Epoch: [20] [1210/1319] eta: 0:05:13 lr: 2.5684733316944508e-05 loss: 0.0401 (0.0522) time: 2.9088 data: 0.0075 max mem: 33369 +Epoch: [20] [1220/1319] eta: 0:04:44 lr: 2.5675548717130043e-05 loss: 0.0395 (0.0522) time: 2.8798 data: 0.0071 max mem: 33369 +Epoch: [20] [1230/1319] eta: 0:04:16 lr: 2.5666363752246116e-05 loss: 0.0446 (0.0522) time: 2.8867 data: 0.0070 max mem: 33369 +Epoch: [20] [1240/1319] eta: 0:03:47 lr: 2.5657178422133044e-05 loss: 0.0493 (0.0523) time: 2.8776 data: 0.0071 max mem: 33369 +Epoch: [20] [1250/1319] eta: 0:03:18 lr: 2.564799272663101e-05 loss: 0.0513 (0.0523) time: 2.8658 data: 0.0077 max mem: 33369 +Epoch: [20] [1260/1319] eta: 0:02:49 lr: 2.5638806665580068e-05 loss: 0.0499 (0.0524) time: 2.8302 data: 0.0079 max mem: 33369 +Epoch: [20] [1270/1319] eta: 0:02:20 lr: 2.5629620238820134e-05 loss: 0.0549 (0.0525) time: 2.8796 data: 0.0076 max mem: 33369 +Epoch: [20] [1280/1319] eta: 0:01:52 lr: 2.562043344619099e-05 loss: 0.0509 (0.0524) time: 2.9053 data: 0.0078 max mem: 33369 +Epoch: [20] [1290/1319] eta: 0:01:23 lr: 2.5611246287532285e-05 loss: 0.0476 (0.0524) time: 2.8575 data: 0.0079 max mem: 33369 +Epoch: [20] [1300/1319] eta: 0:00:54 lr: 2.560205876268355e-05 loss: 0.0513 (0.0524) time: 2.8864 data: 0.0074 max mem: 33369 +Epoch: [20] [1310/1319] eta: 0:00:25 lr: 2.5592870871484144e-05 loss: 0.0513 (0.0524) time: 2.9046 data: 0.0073 max mem: 33369 +Epoch: [20] Total time: 1:03:15 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 2:03:33 time: 2.8813 data: 2.6168 max mem: 33369 +Test: [ 100/2573] eta: 0:04:09 time: 0.0728 data: 0.0012 max mem: 33369 +Test: [ 200/2573] eta: 0:03:29 time: 0.0743 data: 0.0013 max mem: 33369 +Test: [ 300/2573] eta: 0:03:08 time: 0.0760 data: 0.0012 max mem: 33369 +Test: [ 400/2573] eta: 0:02:55 time: 0.0762 data: 0.0012 max mem: 33369 +Test: [ 500/2573] eta: 0:02:44 time: 0.0736 data: 0.0011 max mem: 33369 +Test: [ 600/2573] eta: 0:02:35 time: 0.0737 data: 0.0011 max mem: 33369 +Test: [ 700/2573] eta: 0:02:26 time: 0.0738 data: 0.0011 max mem: 33369 +Test: [ 800/2573] eta: 0:02:18 time: 0.0782 data: 0.0012 max mem: 33369 +Test: [ 900/2573] eta: 0:02:10 time: 0.0750 data: 0.0012 max mem: 33369 +Test: [1000/2573] eta: 0:02:01 time: 0.0748 data: 0.0012 max mem: 33369 +Test: [1100/2573] eta: 0:01:53 time: 0.0745 data: 0.0012 max mem: 33369 +Test: [1200/2573] eta: 0:01:45 time: 0.0748 data: 0.0012 max mem: 33369 +Test: [1300/2573] eta: 0:01:37 time: 0.0746 data: 0.0012 max mem: 33369 +Test: [1400/2573] eta: 0:01:29 time: 0.0729 data: 0.0012 max mem: 33369 +Test: [1500/2573] eta: 0:01:22 time: 0.0748 data: 0.0012 max mem: 33369 +Test: [1600/2573] eta: 0:01:14 time: 0.0780 data: 0.0012 max mem: 33369 +Test: [1700/2573] eta: 0:01:06 time: 0.0731 data: 0.0012 max mem: 33369 +Test: [1800/2573] eta: 0:00:59 time: 0.0765 data: 0.0012 max mem: 33369 +Test: [1900/2573] eta: 0:00:51 time: 0.0732 data: 0.0013 max mem: 33369 +Test: [2000/2573] eta: 0:00:43 time: 0.0747 data: 0.0012 max mem: 33369 +Test: [2100/2573] eta: 0:00:35 time: 0.0765 data: 0.0012 max mem: 33369 +Test: [2200/2573] eta: 0:00:28 time: 0.0763 data: 0.0012 max mem: 33369 +Test: [2300/2573] eta: 0:00:20 time: 0.0764 data: 0.0012 max mem: 33369 +Test: [2400/2573] eta: 0:00:13 time: 0.0715 data: 0.0012 max mem: 33369 +Test: [2500/2573] eta: 0:00:05 time: 0.0747 data: 0.0012 max mem: 33369 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: Total time: 0:03:15 +Final results: +Mean IoU is 63.02 + + precision@0.5 = 70.81 + precision@0.6 = 65.30 + precision@0.7 = 58.23 + precision@0.8 = 46.96 + precision@0.9 = 22.43 + overall IoU = 60.54 + +Average object IoU 63.01935359270907 +Overall IoU 60.542484283447266 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [21] [ 0/1319] eta: 3:17:26 lr: 2.5584601456041995e-05 loss: 0.0651 (0.0651) time: 8.9816 data: 1.3628 max mem: 33369 +Epoch: [21] [ 10/1319] eta: 1:15:15 lr: 2.5575412868333344e-05 loss: 0.0535 (0.0554) time: 3.4494 data: 0.1305 max mem: 33369 +Epoch: [21] [ 20/1319] eta: 1:08:23 lr: 2.5566223913807464e-05 loss: 0.0471 (0.0520) time: 2.8680 data: 0.0068 max mem: 33369 +Epoch: [21] [ 30/1319] eta: 1:05:58 lr: 2.5557034592303224e-05 loss: 0.0467 (0.0511) time: 2.8634 data: 0.0069 max mem: 33369 +Epoch: [21] [ 40/1319] eta: 1:04:34 lr: 2.5547844903659336e-05 loss: 0.0460 (0.0506) time: 2.8922 data: 0.0078 max mem: 33369 +Epoch: [21] [ 50/1319] eta: 1:03:19 lr: 2.5538654847714393e-05 loss: 0.0478 (0.0513) time: 2.8743 data: 0.0078 max mem: 33369 +Epoch: [21] [ 60/1319] eta: 1:02:22 lr: 2.552946442430683e-05 loss: 0.0459 (0.0508) time: 2.8579 data: 0.0073 max mem: 33369 +Epoch: [21] [ 70/1319] eta: 1:01:39 lr: 2.552027363327497e-05 loss: 0.0460 (0.0519) time: 2.8813 data: 0.0073 max mem: 33369 +Epoch: [21] [ 80/1319] eta: 1:01:00 lr: 2.551108247445699e-05 loss: 0.0452 (0.0509) time: 2.8980 data: 0.0074 max mem: 33369 +Epoch: [21] [ 90/1319] eta: 1:00:15 lr: 2.5501890947690927e-05 loss: 0.0465 (0.0512) time: 2.8700 data: 0.0073 max mem: 33369 +Epoch: [21] [ 100/1319] eta: 0:59:23 lr: 2.5492699052814688e-05 loss: 0.0496 (0.0515) time: 2.7971 data: 0.0070 max mem: 33369 +Epoch: [21] [ 110/1319] eta: 0:59:01 lr: 2.548350678966605e-05 loss: 0.0404 (0.0501) time: 2.8702 data: 0.0071 max mem: 33369 +Epoch: [21] [ 120/1319] eta: 0:58:27 lr: 2.547431415808263e-05 loss: 0.0399 (0.0496) time: 2.9355 data: 0.0074 max mem: 33369 +Epoch: [21] [ 130/1319] eta: 0:57:53 lr: 2.5465121157901932e-05 loss: 0.0428 (0.0500) time: 2.8790 data: 0.0074 max mem: 33369 +Epoch: [21] [ 140/1319] eta: 0:57:18 lr: 2.5455927788961316e-05 loss: 0.0441 (0.0497) time: 2.8612 data: 0.0074 max mem: 33369 +Epoch: [21] [ 150/1319] eta: 0:56:48 lr: 2.5446734051098e-05 loss: 0.0418 (0.0491) time: 2.8797 data: 0.0072 max mem: 33369 +Epoch: [21] [ 160/1319] eta: 0:56:17 lr: 2.5437539944149068e-05 loss: 0.0445 (0.0493) time: 2.8966 data: 0.0071 max mem: 33369 +Epoch: [21] [ 170/1319] eta: 0:55:41 lr: 2.542834546795147e-05 loss: 0.0519 (0.0497) time: 2.8491 data: 0.0072 max mem: 33369 +Epoch: [21] [ 180/1319] eta: 0:55:08 lr: 2.5419150622342014e-05 loss: 0.0537 (0.0505) time: 2.8313 data: 0.0073 max mem: 33369 +Epoch: [21] [ 190/1319] eta: 0:54:35 lr: 2.5409955407157366e-05 loss: 0.0452 (0.0502) time: 2.8423 data: 0.0073 max mem: 33369 +Epoch: [21] [ 200/1319] eta: 0:54:05 lr: 2.5400759822234066e-05 loss: 0.0431 (0.0500) time: 2.8642 data: 0.0069 max mem: 33369 +Epoch: [21] [ 210/1319] eta: 0:53:33 lr: 2.539156386740852e-05 loss: 0.0430 (0.0500) time: 2.8624 data: 0.0071 max mem: 33369 +Epoch: [21] [ 220/1319] eta: 0:53:04 lr: 2.538236754251696e-05 loss: 0.0456 (0.0502) time: 2.8706 data: 0.0071 max mem: 33369 +Epoch: [21] [ 230/1319] eta: 0:52:33 lr: 2.5373170847395516e-05 loss: 0.0471 (0.0500) time: 2.8815 data: 0.0069 max mem: 33369 +Epoch: [21] [ 240/1319] eta: 0:52:02 lr: 2.536397378188018e-05 loss: 0.0475 (0.0501) time: 2.8491 data: 0.0070 max mem: 33369 +Epoch: [21] [ 250/1319] eta: 0:51:27 lr: 2.5354776345806775e-05 loss: 0.0498 (0.0501) time: 2.7931 data: 0.0070 max mem: 33369 +Epoch: [21] [ 260/1319] eta: 0:51:00 lr: 2.534557853901102e-05 loss: 0.0429 (0.0501) time: 2.8484 data: 0.0071 max mem: 33369 +Epoch: [21] [ 270/1319] eta: 0:50:32 lr: 2.5336380361328465e-05 loss: 0.0379 (0.0498) time: 2.9219 data: 0.0072 max mem: 33369 +Epoch: [21] [ 280/1319] eta: 0:50:01 lr: 2.532718181259454e-05 loss: 0.0398 (0.0494) time: 2.8744 data: 0.0072 max mem: 33369 +Epoch: [21] [ 290/1319] eta: 0:49:32 lr: 2.531798289264453e-05 loss: 0.0418 (0.0500) time: 2.8682 data: 0.0072 max mem: 33369 +Epoch: [21] [ 300/1319] eta: 0:49:02 lr: 2.5308783601313586e-05 loss: 0.0501 (0.0500) time: 2.8707 data: 0.0076 max mem: 33369 +Epoch: [21] [ 310/1319] eta: 0:48:31 lr: 2.52995839384367e-05 loss: 0.0423 (0.0499) time: 2.8364 data: 0.0079 max mem: 33369 +Epoch: [21] [ 320/1319] eta: 0:48:00 lr: 2.5290383903848747e-05 loss: 0.0447 (0.0500) time: 2.8081 data: 0.0075 max mem: 33369 +Epoch: [21] [ 330/1319] eta: 0:47:31 lr: 2.5281183497384443e-05 loss: 0.0447 (0.0501) time: 2.8438 data: 0.0072 max mem: 33369 +Epoch: [21] [ 340/1319] eta: 0:47:02 lr: 2.5271982718878386e-05 loss: 0.0477 (0.0502) time: 2.8806 data: 0.0072 max mem: 33369 +Epoch: [21] [ 350/1319] eta: 0:46:32 lr: 2.5262781568165e-05 loss: 0.0468 (0.0504) time: 2.8687 data: 0.0078 max mem: 33369 +Epoch: [21] [ 360/1319] eta: 0:46:02 lr: 2.5253580045078606e-05 loss: 0.0465 (0.0504) time: 2.8455 data: 0.0078 max mem: 33369 +Epoch: [21] [ 370/1319] eta: 0:45:34 lr: 2.5244378149453368e-05 loss: 0.0463 (0.0502) time: 2.8712 data: 0.0075 max mem: 33369 +Epoch: [21] [ 380/1319] eta: 0:45:05 lr: 2.5235175881123296e-05 loss: 0.0411 (0.0500) time: 2.8818 data: 0.0080 max mem: 33369 +Epoch: [21] [ 390/1319] eta: 0:44:36 lr: 2.5225973239922274e-05 loss: 0.0392 (0.0498) time: 2.8814 data: 0.0078 max mem: 33369 +Epoch: [21] [ 400/1319] eta: 0:44:06 lr: 2.5216770225684038e-05 loss: 0.0425 (0.0496) time: 2.8515 data: 0.0071 max mem: 33369 +Epoch: [21] [ 410/1319] eta: 0:43:38 lr: 2.520756683824219e-05 loss: 0.0450 (0.0500) time: 2.8598 data: 0.0074 max mem: 33369 +Epoch: [21] [ 420/1319] eta: 0:43:09 lr: 2.5198363077430187e-05 loss: 0.0493 (0.0501) time: 2.8893 data: 0.0077 max mem: 33369 +Epoch: [21] [ 430/1319] eta: 0:42:39 lr: 2.5189158943081348e-05 loss: 0.0425 (0.0500) time: 2.8448 data: 0.0073 max mem: 33369 +Epoch: [21] [ 440/1319] eta: 0:42:09 lr: 2.5179954435028824e-05 loss: 0.0425 (0.0500) time: 2.8308 data: 0.0074 max mem: 33369 +Epoch: [21] [ 450/1319] eta: 0:41:40 lr: 2.517074955310566e-05 loss: 0.0467 (0.0500) time: 2.8428 data: 0.0075 max mem: 33369 +Epoch: [21] [ 460/1319] eta: 0:41:11 lr: 2.5161544297144735e-05 loss: 0.0467 (0.0500) time: 2.8658 data: 0.0070 max mem: 33369 +Epoch: [21] [ 470/1319] eta: 0:40:42 lr: 2.5152338666978798e-05 loss: 0.0426 (0.0499) time: 2.8814 data: 0.0069 max mem: 33369 +Epoch: [21] [ 480/1319] eta: 0:40:15 lr: 2.5143132662440454e-05 loss: 0.0452 (0.0500) time: 2.9105 data: 0.0073 max mem: 33369 +Epoch: [21] [ 490/1319] eta: 0:39:46 lr: 2.513392628336215e-05 loss: 0.0535 (0.0502) time: 2.9185 data: 0.0073 max mem: 33369 +Epoch: [21] [ 500/1319] eta: 0:39:17 lr: 2.5124719529576212e-05 loss: 0.0450 (0.0501) time: 2.8909 data: 0.0070 max mem: 33369 +Epoch: [21] [ 510/1319] eta: 0:38:49 lr: 2.51155124009148e-05 loss: 0.0378 (0.0500) time: 2.8908 data: 0.0074 max mem: 33369 +Epoch: [21] [ 520/1319] eta: 0:38:20 lr: 2.5106304897209954e-05 loss: 0.0422 (0.0502) time: 2.8891 data: 0.0075 max mem: 33369 +Epoch: [21] [ 530/1319] eta: 0:37:51 lr: 2.5097097018293553e-05 loss: 0.0431 (0.0500) time: 2.8531 data: 0.0072 max mem: 33369 +Epoch: [21] [ 540/1319] eta: 0:37:21 lr: 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(0.0508) time: 2.7910 data: 0.0073 max mem: 33369 +Epoch: [21] [ 860/1319] eta: 0:21:59 lr: 2.4793025411504282e-05 loss: 0.0443 (0.0508) time: 2.8054 data: 0.0075 max mem: 33369 +Epoch: [21] [ 870/1319] eta: 0:21:30 lr: 2.4783804674327604e-05 loss: 0.0464 (0.0508) time: 2.8396 data: 0.0082 max mem: 33369 +Epoch: [21] [ 880/1319] eta: 0:21:02 lr: 2.4774583555963328e-05 loss: 0.0450 (0.0508) time: 2.8617 data: 0.0078 max mem: 33369 +Epoch: [21] [ 890/1319] eta: 0:20:33 lr: 2.4765362056238035e-05 loss: 0.0445 (0.0508) time: 2.8920 data: 0.0071 max mem: 33369 +Epoch: [21] [ 900/1319] eta: 0:20:04 lr: 2.4756140174978167e-05 loss: 0.0482 (0.0511) time: 2.8748 data: 0.0072 max mem: 33369 +Epoch: [21] [ 910/1319] eta: 0:19:35 lr: 2.4746917912010012e-05 loss: 0.0537 (0.0511) time: 2.8824 data: 0.0072 max mem: 33369 +Epoch: [21] [ 920/1319] eta: 0:19:06 lr: 2.4737695267159685e-05 loss: 0.0514 (0.0513) time: 2.8647 data: 0.0076 max mem: 33369 +Epoch: [21] [ 930/1319] eta: 0:18:38 lr: 2.4728472240253183e-05 loss: 0.0445 (0.0512) time: 2.8412 data: 0.0076 max mem: 33369 +Epoch: [21] [ 940/1319] eta: 0:18:09 lr: 2.4719248831116334e-05 loss: 0.0445 (0.0512) time: 2.8872 data: 0.0074 max mem: 33369 +Epoch: [21] [ 950/1319] eta: 0:17:40 lr: 2.4710025039574813e-05 loss: 0.0479 (0.0514) time: 2.9171 data: 0.0074 max mem: 33369 +Epoch: [21] [ 960/1319] eta: 0:17:12 lr: 2.4700800865454158e-05 loss: 0.0470 (0.0513) time: 2.9041 data: 0.0071 max mem: 33369 +Epoch: [21] [ 970/1319] eta: 0:16:43 lr: 2.469157630857973e-05 loss: 0.0499 (0.0514) time: 2.8851 data: 0.0079 max mem: 33369 +Epoch: [21] [ 980/1319] eta: 0:16:14 lr: 2.4682351368776758e-05 loss: 0.0525 (0.0513) time: 2.8706 data: 0.0082 max mem: 33369 +Epoch: [21] [ 990/1319] eta: 0:15:46 lr: 2.467312604587031e-05 loss: 0.0393 (0.0513) time: 2.8868 data: 0.0073 max mem: 33369 +Epoch: [21] [1000/1319] eta: 0:15:17 lr: 2.4663900339685314e-05 loss: 0.0505 (0.0515) time: 2.8799 data: 0.0070 max mem: 33369 +Epoch: [21] 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mem: 33369 +Epoch: [21] [1090/1319] eta: 0:10:58 lr: 2.4580851707520996e-05 loss: 0.0420 (0.0515) time: 2.8780 data: 0.0078 max mem: 33369 +Epoch: [21] [1100/1319] eta: 0:10:29 lr: 2.457162215888721e-05 loss: 0.0420 (0.0514) time: 2.9269 data: 0.0083 max mem: 33369 +Epoch: [21] [1110/1319] eta: 0:10:00 lr: 2.456239222503884e-05 loss: 0.0454 (0.0515) time: 2.8676 data: 0.0074 max mem: 33369 +Epoch: [21] [1120/1319] eta: 0:09:31 lr: 2.455316190579896e-05 loss: 0.0543 (0.0515) time: 2.8894 data: 0.0071 max mem: 33369 +Epoch: [21] [1130/1319] eta: 0:09:03 lr: 2.4543931200990468e-05 loss: 0.0451 (0.0515) time: 2.8928 data: 0.0071 max mem: 33369 +Epoch: [21] [1140/1319] eta: 0:08:34 lr: 2.4534700110436136e-05 loss: 0.0477 (0.0515) time: 2.8540 data: 0.0069 max mem: 33369 +Epoch: [21] [1150/1319] eta: 0:08:05 lr: 2.452546863395857e-05 loss: 0.0526 (0.0516) time: 2.8217 data: 0.0070 max mem: 33369 +Epoch: [21] [1160/1319] eta: 0:07:36 lr: 2.451623677138022e-05 loss: 0.0526 (0.0517) time: 2.8485 data: 0.0072 max mem: 33369 +Epoch: [21] [1170/1319] eta: 0:07:08 lr: 2.4507004522523372e-05 loss: 0.0516 (0.0517) time: 2.8478 data: 0.0076 max mem: 33369 +Epoch: [21] [1180/1319] eta: 0:06:39 lr: 2.4497771887210175e-05 loss: 0.0405 (0.0516) time: 2.8361 data: 0.0079 max mem: 33369 +Epoch: [21] [1190/1319] eta: 0:06:10 lr: 2.4488538865262596e-05 loss: 0.0410 (0.0516) time: 2.8553 data: 0.0075 max mem: 33369 +Epoch: [21] [1200/1319] eta: 0:05:41 lr: 2.4479305456502462e-05 loss: 0.0475 (0.0515) time: 2.8567 data: 0.0073 max mem: 33369 +Epoch: [21] [1210/1319] eta: 0:05:13 lr: 2.4470071660751444e-05 loss: 0.0473 (0.0515) time: 2.8456 data: 0.0074 max mem: 33369 +Epoch: [21] [1220/1319] eta: 0:04:44 lr: 2.446083747783105e-05 loss: 0.0473 (0.0517) time: 2.8660 data: 0.0073 max mem: 33369 +Epoch: [21] [1230/1319] eta: 0:04:15 lr: 2.4451602907562637e-05 loss: 0.0425 (0.0516) time: 2.8072 data: 0.0072 max mem: 33369 +Epoch: [21] [1240/1319] eta: 0:03:46 lr: 2.4442367949767393e-05 loss: 0.0416 (0.0516) time: 2.8544 data: 0.0073 max mem: 33369 +Epoch: [21] [1250/1319] eta: 0:03:18 lr: 2.4433132604266355e-05 loss: 0.0433 (0.0516) time: 2.9247 data: 0.0077 max mem: 33369 +Epoch: [21] [1260/1319] eta: 0:02:49 lr: 2.442389687088041e-05 loss: 0.0426 (0.0516) time: 2.8566 data: 0.0075 max mem: 33369 +Epoch: [21] [1270/1319] eta: 0:02:20 lr: 2.441466074943027e-05 loss: 0.0427 (0.0516) time: 2.8751 data: 0.0069 max mem: 33369 +Epoch: [21] [1280/1319] eta: 0:01:52 lr: 2.440542423973651e-05 loss: 0.0432 (0.0516) time: 2.8974 data: 0.0070 max mem: 33369 +Epoch: [21] [1290/1319] eta: 0:01:23 lr: 2.439618734161953e-05 loss: 0.0450 (0.0516) time: 2.8856 data: 0.0075 max mem: 33369 +Epoch: [21] [1300/1319] eta: 0:00:54 lr: 2.4386950054899575e-05 loss: 0.0453 (0.0515) time: 2.8503 data: 0.0076 max mem: 33369 +Epoch: [21] [1310/1319] eta: 0:00:25 lr: 2.4377712379396728e-05 loss: 0.0459 (0.0515) time: 2.8518 data: 0.0074 max mem: 33369 +Epoch: [21] Total time: 1:03:08 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 2:03:01 time: 2.8689 data: 2.7489 max mem: 33369 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 100/2573] eta: 0:04:12 time: 0.0735 data: 0.0013 max mem: 33369 +Test: [ 200/2573] eta: 0:03:30 time: 0.0740 data: 0.0012 max mem: 33369 +Test: [ 300/2573] eta: 0:03:09 time: 0.0757 data: 0.0012 max mem: 33369 +Test: [ 400/2573] eta: 0:02:56 time: 0.0760 data: 0.0012 max mem: 33369 +Test: [ 500/2573] eta: 0:02:45 time: 0.0742 data: 0.0013 max mem: 33369 +Test: [ 600/2573] eta: 0:02:35 time: 0.0741 data: 0.0012 max mem: 33369 +Test: [ 700/2573] eta: 0:02:27 time: 0.0744 data: 0.0012 max mem: 33369 +Test: [ 800/2573] eta: 0:02:18 time: 0.0777 data: 0.0012 max mem: 33369 +Test: [ 900/2573] eta: 0:02:10 time: 0.0744 data: 0.0012 max mem: 33369 +Test: [1000/2573] eta: 0:02:02 time: 0.0748 data: 0.0013 max mem: 33369 +Test: [1100/2573] eta: 0:01:53 time: 0.0747 data: 0.0012 max mem: 33369 +Test: [1200/2573] eta: 0:01:45 time: 0.0747 data: 0.0012 max mem: 33369 +Test: [1300/2573] eta: 0:01:38 time: 0.0748 data: 0.0012 max mem: 33369 +Test: [1400/2573] eta: 0:01:30 time: 0.0733 data: 0.0012 max mem: 33369 +Test: [1500/2573] eta: 0:01:22 time: 0.0752 data: 0.0013 max mem: 33369 +Test: [1600/2573] eta: 0:01:14 time: 0.0781 data: 0.0013 max mem: 33369 +Test: [1700/2573] eta: 0:01:06 time: 0.0731 data: 0.0012 max mem: 33369 +Test: [1800/2573] eta: 0:00:59 time: 0.0767 data: 0.0013 max mem: 33369 +Test: [1900/2573] eta: 0:00:51 time: 0.0734 data: 0.0013 max mem: 33369 +Test: [2000/2573] eta: 0:00:43 time: 0.0747 data: 0.0011 max mem: 33369 +Test: [2100/2573] eta: 0:00:36 time: 0.0761 data: 0.0011 max mem: 33369 +Test: [2200/2573] eta: 0:00:28 time: 0.0763 data: 0.0011 max mem: 33369 +Test: [2300/2573] eta: 0:00:20 time: 0.0762 data: 0.0011 max mem: 33369 +Test: [2400/2573] eta: 0:00:13 time: 0.0739 data: 0.0016 max mem: 33369 +Test: [2500/2573] eta: 0:00:05 time: 0.0753 data: 0.0013 max mem: 33369 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: Total time: 0:03:15 +Final results: +Mean IoU is 63.48 + + precision@0.5 = 71.38 + precision@0.6 = 66.26 + precision@0.7 = 59.38 + precision@0.8 = 47.30 + precision@0.9 = 23.47 + overall IoU = 61.10 + +Average object IoU 63.483395002204404 +Overall IoU 61.09871292114258 +Better epoch: 21 + +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [22] [ 0/1319] eta: 1:34:42 lr: 2.4369398138885975e-05 loss: 0.0379 (0.0379) time: 4.3081 data: 1.3445 max mem: 33369 +Epoch: [22] [ 10/1319] eta: 1:05:48 lr: 2.436015972419942e-05 loss: 0.0457 (0.0493) time: 3.0165 data: 0.1294 max mem: 33369 +Epoch: [22] [ 20/1319] eta: 1:04:37 lr: 2.4350920920207323e-05 loss: 0.0424 (0.0507) time: 2.9189 data: 0.0072 max mem: 33369 +Epoch: [22] [ 30/1319] eta: 1:03:04 lr: 2.4341681726729162e-05 loss: 0.0385 (0.0507) time: 2.8916 data: 0.0072 max mem: 33369 +Epoch: [22] [ 40/1319] eta: 1:02:21 lr: 2.4332442143584247e-05 loss: 0.0486 (0.0510) time: 2.8623 data: 0.0077 max mem: 33369 +Epoch: [22] [ 50/1319] eta: 1:01:25 lr: 2.4323202170591704e-05 loss: 0.0486 (0.0509) time: 2.8555 data: 0.0072 max mem: 33369 +Epoch: [22] [ 60/1319] eta: 1:00:34 lr: 2.4313961807570534e-05 loss: 0.0455 (0.0506) time: 2.8084 data: 0.0070 max mem: 33369 +Epoch: [22] [ 70/1319] eta: 1:00:04 lr: 2.430472105433956e-05 loss: 0.0380 (0.0504) time: 2.8394 data: 0.0073 max mem: 33369 +Epoch: [22] [ 80/1319] eta: 0:59:36 lr: 2.4295479910717442e-05 loss: 0.0380 (0.0494) time: 2.8856 data: 0.0076 max mem: 33369 +Epoch: [22] [ 90/1319] eta: 0:59:05 lr: 2.4286238376522685e-05 loss: 0.0420 (0.0489) time: 2.8790 data: 0.0076 max mem: 33369 +Epoch: [22] [ 100/1319] eta: 0:58:34 lr: 2.4276996451573638e-05 loss: 0.0434 (0.0490) time: 2.8678 data: 0.0072 max mem: 33369 +Epoch: [22] [ 110/1319] eta: 0:58:09 lr: 2.426775413568847e-05 loss: 0.0434 (0.0486) time: 2.8925 data: 0.0068 max mem: 33369 +Epoch: [22] [ 120/1319] eta: 0:57:34 lr: 2.4258511428685206e-05 loss: 0.0394 (0.0487) time: 2.8722 data: 0.0070 max mem: 33369 +Epoch: [22] [ 130/1319] eta: 0:57:04 lr: 2.4249268330381702e-05 loss: 0.0376 (0.0478) time: 2.8464 data: 0.0071 max mem: 33369 +Epoch: [22] [ 140/1319] eta: 0:56:24 lr: 2.4240024840595657e-05 loss: 0.0453 (0.0478) time: 2.8070 data: 0.0070 max mem: 33369 +Epoch: [22] [ 150/1319] eta: 0:56:05 lr: 2.4230780959144606e-05 loss: 0.0472 (0.0474) time: 2.8718 data: 0.0074 max mem: 33369 +Epoch: [22] [ 160/1319] eta: 0:55:30 lr: 2.4221536685845908e-05 loss: 0.0456 (0.0480) time: 2.8946 data: 0.0082 max mem: 33369 +Epoch: [22] [ 170/1319] eta: 0:54:59 lr: 2.421229202051678e-05 loss: 0.0455 (0.0476) time: 2.8199 data: 0.0078 max mem: 33369 +Epoch: [22] [ 180/1319] eta: 0:54:31 lr: 2.420304696297427e-05 loss: 0.0381 (0.0473) time: 2.8648 data: 0.0072 max mem: 33369 +Epoch: [22] [ 190/1319] eta: 0:54:04 lr: 2.419380151303525e-05 loss: 0.0431 (0.0476) time: 2.8911 data: 0.0072 max mem: 33369 +Epoch: [22] [ 200/1319] eta: 0:53:38 lr: 2.418455567051645e-05 loss: 0.0489 (0.0476) time: 2.9072 data: 0.0073 max mem: 33369 +Epoch: [22] [ 210/1319] eta: 0:53:09 lr: 2.417530943523442e-05 loss: 0.0469 (0.0479) time: 2.8915 data: 0.0074 max mem: 33369 +Epoch: [22] [ 220/1319] eta: 0:52:41 lr: 2.416606280700555e-05 loss: 0.0416 (0.0476) time: 2.8868 data: 0.0074 max mem: 33369 +Epoch: [22] [ 230/1319] eta: 0:52:13 lr: 2.4156815785646067e-05 loss: 0.0388 (0.0475) time: 2.9008 data: 0.0073 max mem: 33369 +Epoch: [22] [ 240/1319] eta: 0:51:47 lr: 2.414756837097204e-05 loss: 0.0453 (0.0478) time: 2.9085 data: 0.0071 max mem: 33369 +Epoch: [22] [ 250/1319] eta: 0:51:17 lr: 2.4138320562799363e-05 loss: 0.0522 (0.0480) time: 2.8876 data: 0.0076 max mem: 33369 +Epoch: [22] [ 260/1319] eta: 0:50:48 lr: 2.412907236094378e-05 loss: 0.0501 (0.0484) time: 2.8619 data: 0.0079 max mem: 33369 +Epoch: [22] [ 270/1319] eta: 0:50:20 lr: 2.411982376522085e-05 loss: 0.0496 (0.0482) time: 2.8868 data: 0.0073 max mem: 33369 +Epoch: [22] [ 280/1319] eta: 0:49:51 lr: 2.411057477544598e-05 loss: 0.0405 (0.0484) time: 2.8936 data: 0.0070 max mem: 33369 +Epoch: [22] [ 290/1319] eta: 0:49:19 lr: 2.4101325391434414e-05 loss: 0.0439 (0.0483) time: 2.8400 data: 0.0070 max mem: 33369 +Epoch: [22] [ 300/1319] eta: 0:48:55 lr: 2.4092075613001218e-05 loss: 0.0467 (0.0484) time: 2.8965 data: 0.0073 max mem: 33369 +Epoch: [22] [ 310/1319] eta: 0:48:19 lr: 2.4082825439961318e-05 loss: 0.0423 (0.0493) time: 2.8267 data: 0.0073 max mem: 33369 +Epoch: [22] [ 320/1319] eta: 0:47:45 lr: 2.4073574872129434e-05 loss: 0.0483 (0.0492) time: 2.6854 data: 0.0067 max mem: 33369 +Epoch: [22] [ 330/1319] eta: 0:47:19 lr: 2.4064323909320154e-05 loss: 0.0502 (0.0493) time: 2.8421 data: 0.0076 max mem: 33369 +Epoch: [22] [ 340/1319] eta: 0:46:52 lr: 2.405507255134789e-05 loss: 0.0533 (0.0496) time: 2.9366 data: 0.0079 max mem: 33369 +Epoch: [22] [ 350/1319] eta: 0:46:24 lr: 2.404582079802688e-05 loss: 0.0518 (0.0496) time: 2.9027 data: 0.0077 max mem: 33369 +Epoch: [22] [ 360/1319] eta: 0:45:56 lr: 2.4036568649171213e-05 loss: 0.0411 (0.0494) time: 2.9075 data: 0.0076 max mem: 33370 +Epoch: [22] [ 370/1319] eta: 0:45:28 lr: 2.402731610459478e-05 loss: 0.0436 (0.0494) time: 2.9100 data: 0.0072 max mem: 33370 +Epoch: [22] [ 380/1319] eta: 0:44:59 lr: 2.401806316411133e-05 loss: 0.0431 (0.0493) time: 2.8751 data: 0.0076 max mem: 33370 +Epoch: [22] [ 390/1319] eta: 0:44:29 lr: 2.400880982753445e-05 loss: 0.0392 (0.0493) time: 2.8357 data: 0.0076 max mem: 33370 +Epoch: [22] [ 400/1319] eta: 0:44:00 lr: 2.399955609467753e-05 loss: 0.0446 (0.0493) time: 2.8542 data: 0.0075 max mem: 33370 +Epoch: [22] [ 410/1319] eta: 0:43:31 lr: 2.3990301965353823e-05 loss: 0.0423 (0.0491) time: 2.8745 data: 0.0072 max mem: 33370 +Epoch: [22] [ 420/1319] eta: 0:43:03 lr: 2.39810474393764e-05 loss: 0.0392 (0.0488) time: 2.8843 data: 0.0070 max mem: 33370 +Epoch: [22] [ 430/1319] eta: 0:42:34 lr: 2.3971792516558155e-05 loss: 0.0396 (0.0489) time: 2.8870 data: 0.0076 max mem: 33370 +Epoch: [22] [ 440/1319] eta: 0:42:05 lr: 2.3962537196711826e-05 loss: 0.0494 (0.0490) time: 2.8656 data: 0.0076 max mem: 33370 +Epoch: [22] [ 450/1319] eta: 0:41:36 lr: 2.3953281479649982e-05 loss: 0.0499 (0.0491) time: 2.8409 data: 0.0072 max mem: 33370 +Epoch: [22] [ 460/1319] eta: 0:41:08 lr: 2.394402536518502e-05 loss: 0.0401 (0.0490) time: 2.8727 data: 0.0070 max mem: 33370 +Epoch: [22] [ 470/1319] eta: 0:40:39 lr: 2.3934768853129168e-05 loss: 0.0364 (0.0488) time: 2.8904 data: 0.0069 max mem: 33370 +Epoch: [22] [ 480/1319] eta: 0:40:11 lr: 2.3925511943294477e-05 loss: 0.0423 (0.0489) time: 2.8908 data: 0.0071 max mem: 33370 +Epoch: [22] [ 490/1319] eta: 0:39:42 lr: 2.3916254635492843e-05 loss: 0.0468 (0.0491) time: 2.9033 data: 0.0071 max mem: 33370 +Epoch: [22] [ 500/1319] eta: 0:39:14 lr: 2.390699692953598e-05 loss: 0.0486 (0.0491) time: 2.8940 data: 0.0070 max mem: 33370 +Epoch: [22] [ 510/1319] eta: 0:38:45 lr: 2.3897738825235443e-05 loss: 0.0496 (0.0491) time: 2.8863 data: 0.0071 max mem: 33370 +Epoch: [22] [ 520/1319] eta: 0:38:17 lr: 2.3888480322402605e-05 loss: 0.0460 (0.0491) time: 2.8744 data: 0.0074 max mem: 33370 +Epoch: [22] [ 530/1319] eta: 0:37:48 lr: 2.3879221420848673e-05 loss: 0.0460 (0.0491) time: 2.8822 data: 0.0079 max mem: 33370 +Epoch: [22] [ 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data: 0.0071 max mem: 33370 +Epoch: [22] [1090/1319] eta: 0:10:57 lr: 2.3360080670681804e-05 loss: 0.0421 (0.0496) time: 2.9147 data: 0.0077 max mem: 33370 +Epoch: [22] [1100/1319] eta: 0:10:28 lr: 2.335079872429276e-05 loss: 0.0421 (0.0497) time: 2.8894 data: 0.0075 max mem: 33370 +Epoch: [22] [1110/1319] eta: 0:09:59 lr: 2.334151636793279e-05 loss: 0.0407 (0.0496) time: 2.9027 data: 0.0072 max mem: 33370 +Epoch: [22] [1120/1319] eta: 0:09:31 lr: 2.333223360140262e-05 loss: 0.0407 (0.0496) time: 2.8966 data: 0.0074 max mem: 33370 +Epoch: [22] [1130/1319] eta: 0:09:02 lr: 2.3322950424502793e-05 loss: 0.0483 (0.0496) time: 2.8846 data: 0.0079 max mem: 33370 +Epoch: [22] [1140/1319] eta: 0:08:33 lr: 2.3313666837033663e-05 loss: 0.0466 (0.0496) time: 2.8386 data: 0.0081 max mem: 33370 +Epoch: [22] [1150/1319] eta: 0:08:05 lr: 2.33043828387954e-05 loss: 0.0402 (0.0495) time: 2.8614 data: 0.0078 max mem: 33370 +Epoch: [22] [1160/1319] eta: 0:07:36 lr: 2.3295098429587987e-05 loss: 0.0387 (0.0495) time: 2.8833 data: 0.0079 max mem: 33370 +Epoch: [22] [1170/1319] eta: 0:07:07 lr: 2.328581360921123e-05 loss: 0.0401 (0.0494) time: 2.8574 data: 0.0078 max mem: 33370 +Epoch: [22] [1180/1319] eta: 0:06:38 lr: 2.327652837746473e-05 loss: 0.0401 (0.0495) time: 2.8793 data: 0.0073 max mem: 33370 +Epoch: [22] [1190/1319] eta: 0:06:10 lr: 2.3267242734147912e-05 loss: 0.0363 (0.0494) time: 2.8835 data: 0.0072 max mem: 33370 +Epoch: [22] [1200/1319] eta: 0:05:41 lr: 2.325795667906002e-05 loss: 0.0403 (0.0494) time: 2.8806 data: 0.0074 max mem: 33370 +Epoch: [22] [1210/1319] eta: 0:05:12 lr: 2.3248670212000107e-05 loss: 0.0531 (0.0495) time: 2.8972 data: 0.0077 max mem: 33370 +Epoch: [22] [1220/1319] eta: 0:04:44 lr: 2.3239383332767037e-05 loss: 0.0524 (0.0494) time: 2.8510 data: 0.0075 max mem: 33370 +Epoch: [22] [1230/1319] eta: 0:04:15 lr: 2.323009604115948e-05 loss: 0.0489 (0.0495) time: 2.9043 data: 0.0072 max mem: 33370 +Epoch: [22] [1240/1319] eta: 0:03:46 lr: 2.322080833697593e-05 loss: 0.0506 (0.0496) time: 2.9493 data: 0.0071 max mem: 33370 +Epoch: [22] [1250/1319] eta: 0:03:18 lr: 2.3211520220014678e-05 loss: 0.0478 (0.0496) time: 2.8889 data: 0.0069 max mem: 33370 +Epoch: [22] [1260/1319] eta: 0:02:49 lr: 2.320223169007385e-05 loss: 0.0460 (0.0496) time: 2.8909 data: 0.0073 max mem: 33370 +Epoch: [22] [1270/1319] eta: 0:02:20 lr: 2.319294274695137e-05 loss: 0.0396 (0.0497) time: 2.9098 data: 0.0073 max mem: 33370 +Epoch: [22] [1280/1319] eta: 0:01:52 lr: 2.318365339044496e-05 loss: 0.0444 (0.0497) time: 2.9075 data: 0.0069 max mem: 33370 +Epoch: [22] [1290/1319] eta: 0:01:23 lr: 2.3174363620352174e-05 loss: 0.0491 (0.0497) time: 2.8562 data: 0.0071 max mem: 33370 +Epoch: [22] [1300/1319] eta: 0:00:54 lr: 2.3165073436470368e-05 loss: 0.0491 (0.0498) time: 2.8844 data: 0.0072 max mem: 33370 +Epoch: [22] [1310/1319] eta: 0:00:25 lr: 2.3155782838596706e-05 loss: 0.0646 (0.0500) time: 2.9137 data: 0.0071 max mem: 33370 +Epoch: [22] Total time: 1:03:09 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 2:05:52 time: 2.9354 data: 2.7859 max mem: 33370 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 100/2573] eta: 0:04:11 time: 0.0731 data: 0.0013 max mem: 33370 +Test: [ 200/2573] eta: 0:03:30 time: 0.0742 data: 0.0013 max mem: 33370 +Test: [ 300/2573] eta: 0:03:09 time: 0.0756 data: 0.0012 max mem: 33370 +Test: [ 400/2573] eta: 0:02:55 time: 0.0760 data: 0.0012 max mem: 33370 +Test: [ 500/2573] eta: 0:02:45 time: 0.0741 data: 0.0012 max mem: 33370 +Test: [ 600/2573] eta: 0:02:35 time: 0.0743 data: 0.0013 max mem: 33370 +Test: [ 700/2573] eta: 0:02:27 time: 0.0744 data: 0.0013 max mem: 33370 +Test: [ 800/2573] eta: 0:02:18 time: 0.0777 data: 0.0012 max mem: 33370 +Test: [ 900/2573] eta: 0:02:10 time: 0.0745 data: 0.0013 max mem: 33370 +Test: [1000/2573] eta: 0:02:01 time: 0.0744 data: 0.0012 max mem: 33370 +Test: [1100/2573] eta: 0:01:53 time: 0.0744 data: 0.0012 max mem: 33370 +Test: [1200/2573] eta: 0:01:45 time: 0.0746 data: 0.0012 max mem: 33370 +Test: [1300/2573] eta: 0:01:37 time: 0.0748 data: 0.0012 max mem: 33370 +Test: [1400/2573] eta: 0:01:29 time: 0.0730 data: 0.0013 max mem: 33370 +Test: [1500/2573] eta: 0:01:22 time: 0.0748 data: 0.0013 max mem: 33370 +Test: [1600/2573] eta: 0:01:14 time: 0.0781 data: 0.0012 max mem: 33370 +Test: [1700/2573] eta: 0:01:06 time: 0.0725 data: 0.0011 max mem: 33370 +Test: [1800/2573] eta: 0:00:58 time: 0.0761 data: 0.0012 max mem: 33370 +Test: [1900/2573] eta: 0:00:51 time: 0.0725 data: 0.0012 max mem: 33370 +Test: [2000/2573] eta: 0:00:43 time: 0.0742 data: 0.0012 max mem: 33370 +Test: [2100/2573] eta: 0:00:35 time: 0.0766 data: 0.0012 max mem: 33370 +Test: [2200/2573] eta: 0:00:28 time: 0.0764 data: 0.0012 max mem: 33370 +Test: [2300/2573] eta: 0:00:20 time: 0.0765 data: 0.0013 max mem: 33370 +Test: [2400/2573] eta: 0:00:13 time: 0.0715 data: 0.0013 max mem: 33370 +Test: [2500/2573] eta: 0:00:05 time: 0.0750 data: 0.0012 max mem: 33370 +Test: Total time: 0:03:15 +Final results: +Mean IoU is 63.27 + + precision@0.5 = 71.28 + precision@0.6 = 65.93 + precision@0.7 = 59.01 + precision@0.8 = 46.81 + precision@0.9 = 22.96 + overall IoU = 60.84 + +Average object IoU 63.26596251597112 +Overall IoU 60.843753814697266 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [23] [ 0/1319] eta: 3:21:16 lr: 2.3147420946379584e-05 loss: 0.0646 (0.0646) time: 9.1554 data: 1.8201 max mem: 33370 +Epoch: [23] [ 10/1319] eta: 1:14:47 lr: 2.313812956136191e-05 loss: 0.0365 (0.0461) time: 3.4281 data: 0.1723 max mem: 33370 +Epoch: [23] [ 20/1319] eta: 1:08:24 lr: 2.3128837761763095e-05 loss: 0.0430 (0.0505) time: 2.8602 data: 0.0072 max mem: 33370 +Epoch: [23] [ 30/1319] eta: 1:06:21 lr: 2.3119545547379566e-05 loss: 0.0457 (0.0494) time: 2.9017 data: 0.0073 max mem: 33370 +Epoch: [23] [ 40/1319] eta: 1:04:52 lr: 2.3110252918007542e-05 loss: 0.0402 (0.0478) time: 2.9209 data: 0.0077 max mem: 33370 +Epoch: [23] [ 50/1319] eta: 1:03:39 lr: 2.3100959873443074e-05 loss: 0.0435 (0.0479) time: 2.8876 data: 0.0073 max mem: 33370 +Epoch: [23] [ 60/1319] eta: 1:02:42 lr: 2.3091666413482015e-05 loss: 0.0468 (0.0494) time: 2.8760 data: 0.0072 max mem: 33370 +Epoch: [23] [ 70/1319] eta: 1:01:49 lr: 2.3082372537920018e-05 loss: 0.0423 (0.0495) time: 2.8674 data: 0.0077 max mem: 33370 +Epoch: [23] [ 80/1319] eta: 1:01:15 lr: 2.307307824655256e-05 loss: 0.0423 (0.0487) time: 2.8987 data: 0.0075 max mem: 33370 +Epoch: [23] [ 90/1319] eta: 1:00:33 lr: 2.3063783539174907e-05 loss: 0.0387 (0.0475) time: 2.9097 data: 0.0073 max mem: 33370 +Epoch: [23] [ 100/1319] eta: 0:59:46 lr: 2.3054488415582145e-05 loss: 0.0366 (0.0469) time: 2.8462 data: 0.0077 max mem: 33370 +Epoch: [23] [ 110/1319] eta: 0:59:13 lr: 2.3045192875569164e-05 loss: 0.0389 (0.0467) time: 2.8595 data: 0.0077 max mem: 33370 +Epoch: [23] [ 120/1319] eta: 0:58:35 lr: 2.3035896918930662e-05 loss: 0.0389 (0.0466) time: 2.8801 data: 0.0080 max mem: 33370 +Epoch: [23] [ 130/1319] eta: 0:57:50 lr: 2.3026600545461138e-05 loss: 0.0388 (0.0469) time: 2.8088 data: 0.0077 max mem: 33370 +Epoch: [23] [ 140/1319] eta: 0:57:27 lr: 2.3017303754954915e-05 loss: 0.0383 (0.0463) time: 2.8776 data: 0.0073 max mem: 33370 +Epoch: [23] [ 150/1319] eta: 0:56:53 lr: 2.300800654720609e-05 loss: 0.0367 (0.0458) time: 2.9248 data: 0.0076 max mem: 33370 +Epoch: [23] [ 160/1319] eta: 0:56:19 lr: 2.2998708922008593e-05 loss: 0.0374 (0.0456) time: 2.8529 data: 0.0071 max mem: 33370 +Epoch: [23] [ 170/1319] eta: 0:55:43 lr: 2.2989410879156158e-05 loss: 0.0465 (0.0458) time: 2.8342 data: 0.0075 max mem: 33370 +Epoch: [23] [ 180/1319] eta: 0:55:14 lr: 2.298011241844231e-05 loss: 0.0465 (0.0460) time: 2.8646 data: 0.0076 max mem: 33370 +Epoch: [23] [ 190/1319] eta: 0:54:43 lr: 2.2970813539660394e-05 loss: 0.0398 (0.0457) time: 2.8922 data: 0.0070 max mem: 33370 +Epoch: [23] [ 200/1319] eta: 0:54:11 lr: 2.296151424260354e-05 loss: 0.0388 (0.0455) time: 2.8639 data: 0.0072 max mem: 33370 +Epoch: [23] [ 210/1319] eta: 0:53:41 lr: 2.2952214527064705e-05 loss: 0.0433 (0.0457) time: 2.8761 data: 0.0076 max mem: 33370 +Epoch: [23] [ 220/1319] eta: 0:53:11 lr: 2.294291439283664e-05 loss: 0.0402 (0.0456) time: 2.8889 data: 0.0077 max mem: 33370 +Epoch: [23] [ 230/1319] eta: 0:52:38 lr: 2.2933613839711898e-05 loss: 0.0414 (0.0461) time: 2.8468 data: 0.0077 max mem: 33370 +Epoch: [23] [ 240/1319] eta: 0:52:05 lr: 2.292431286748284e-05 loss: 0.0471 (0.0461) time: 2.8136 data: 0.0080 max mem: 33370 +Epoch: [23] [ 250/1319] eta: 0:51:33 lr: 2.2915011475941626e-05 loss: 0.0444 (0.0461) time: 2.8285 data: 0.0081 max mem: 33370 +Epoch: [23] [ 260/1319] eta: 0:51:01 lr: 2.2905709664880228e-05 loss: 0.0410 (0.0459) time: 2.8230 data: 0.0082 max mem: 33370 +Epoch: [23] [ 270/1319] eta: 0:50:32 lr: 2.28964074340904e-05 loss: 0.0379 (0.0470) time: 2.8506 data: 0.0078 max mem: 33370 +Epoch: [23] [ 280/1319] eta: 0:49:59 lr: 2.2887104783363728e-05 loss: 0.0474 (0.0470) time: 2.8385 data: 0.0071 max mem: 33370 +Epoch: [23] [ 290/1319] eta: 0:49:32 lr: 2.2877801712491578e-05 loss: 0.0462 (0.0470) time: 2.8508 data: 0.0073 max mem: 33370 +Epoch: [23] [ 300/1319] eta: 0:49:02 lr: 2.2868498221265136e-05 loss: 0.0462 (0.0471) time: 2.8939 data: 0.0073 max mem: 33370 +Epoch: [23] [ 310/1319] eta: 0:48:33 lr: 2.2859194309475363e-05 loss: 0.0496 (0.0474) time: 2.8828 data: 0.0076 max mem: 33370 +Epoch: [23] [ 320/1319] eta: 0:48:03 lr: 2.2849889976913045e-05 loss: 0.0496 (0.0475) time: 2.8705 data: 0.0079 max mem: 33370 +Epoch: [23] [ 330/1319] eta: 0:47:33 lr: 2.2840585223368763e-05 loss: 0.0422 (0.0476) time: 2.8478 data: 0.0075 max mem: 33370 +Epoch: [23] [ 340/1319] eta: 0:47:03 lr: 2.2831280048632893e-05 loss: 0.0398 (0.0474) time: 2.8412 data: 0.0072 max mem: 33370 +Epoch: [23] [ 350/1319] eta: 0:46:33 lr: 2.282197445249563e-05 loss: 0.0364 (0.0472) time: 2.8467 data: 0.0072 max mem: 33370 +Epoch: [23] [ 360/1319] eta: 0:46:05 lr: 2.2812668434746943e-05 loss: 0.0377 (0.0474) time: 2.8832 data: 0.0072 max mem: 33370 +Epoch: [23] [ 370/1319] eta: 0:45:36 lr: 2.2803361995176614e-05 loss: 0.0445 (0.0476) time: 2.8792 data: 0.0074 max mem: 33370 +Epoch: [23] [ 380/1319] eta: 0:45:07 lr: 2.279405513357423e-05 loss: 0.0499 (0.0475) time: 2.8685 data: 0.0079 max mem: 33370 +Epoch: [23] [ 390/1319] eta: 0:44:37 lr: 2.278474784972917e-05 loss: 0.0389 (0.0476) time: 2.8687 data: 0.0078 max mem: 33370 +Epoch: [23] [ 400/1319] eta: 0:44:08 lr: 2.277544014343061e-05 loss: 0.0491 (0.0478) time: 2.8632 data: 0.0072 max mem: 33370 +Epoch: [23] [ 410/1319] eta: 0:43:39 lr: 2.2766132014467546e-05 loss: 0.0400 (0.0475) time: 2.8755 data: 0.0072 max mem: 33370 +Epoch: [23] [ 420/1319] eta: 0:43:10 lr: 2.2756823462628737e-05 loss: 0.0396 (0.0475) time: 2.8757 data: 0.0072 max mem: 33370 +Epoch: [23] [ 430/1319] eta: 0:42:40 lr: 2.2747514487702767e-05 loss: 0.0435 (0.0473) time: 2.8459 data: 0.0071 max mem: 33370 +Epoch: [23] [ 440/1319] eta: 0:42:12 lr: 2.2738205089478008e-05 loss: 0.0392 (0.0475) time: 2.8597 data: 0.0074 max mem: 33370 +Epoch: [23] [ 450/1319] eta: 0:41:43 lr: 2.272889526774264e-05 loss: 0.0485 (0.0478) time: 2.9038 data: 0.0077 max mem: 33370 +Epoch: [23] [ 460/1319] eta: 0:41:14 lr: 2.2719585022284628e-05 loss: 0.0469 (0.0478) time: 2.8927 data: 0.0074 max mem: 33370 +Epoch: [23] [ 470/1319] eta: 0:40:45 lr: 2.2710274352891738e-05 loss: 0.0484 (0.0479) time: 2.8576 data: 0.0073 max mem: 33370 +Epoch: [23] [ 480/1319] eta: 0:40:16 lr: 2.2700963259351535e-05 loss: 0.0449 (0.0478) time: 2.8642 data: 0.0072 max mem: 33370 +Epoch: [23] [ 490/1319] eta: 0:39:48 lr: 2.269165174145138e-05 loss: 0.0368 (0.0477) time: 2.9017 data: 0.0073 max mem: 33370 +Epoch: [23] [ 500/1319] eta: 0:39:19 lr: 2.2682339798978432e-05 loss: 0.0397 (0.0479) time: 2.8907 data: 0.0077 max mem: 33370 +Epoch: [23] [ 510/1319] eta: 0:38:49 lr: 2.2673027431719644e-05 loss: 0.0465 (0.0479) time: 2.8284 data: 0.0073 max mem: 33370 +Epoch: [23] [ 520/1319] eta: 0:38:21 lr: 2.266371463946176e-05 loss: 0.0456 (0.0478) time: 2.8701 data: 0.0077 max mem: 33370 +Epoch: [23] [ 530/1319] eta: 0:37:51 lr: 2.2654401421991334e-05 loss: 0.0406 (0.0477) time: 2.8842 data: 0.0085 max mem: 33370 +Epoch: [23] [ 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2.2356152662580173e-05 loss: 0.0471 (0.0479) time: 2.9012 data: 0.0074 max mem: 33370 +Epoch: [23] [ 860/1319] eta: 0:22:00 lr: 2.234682529199176e-05 loss: 0.0345 (0.0478) time: 2.8859 data: 0.0072 max mem: 33370 +Epoch: [23] [ 870/1319] eta: 0:21:31 lr: 2.2337497488809557e-05 loss: 0.0401 (0.0478) time: 2.8978 data: 0.0073 max mem: 33370 +Epoch: [23] [ 880/1319] eta: 0:21:02 lr: 2.232816925281277e-05 loss: 0.0477 (0.0478) time: 2.8575 data: 0.0071 max mem: 33370 +Epoch: [23] [ 890/1319] eta: 0:20:34 lr: 2.2318840583780386e-05 loss: 0.0495 (0.0480) time: 2.8847 data: 0.0072 max mem: 33370 +Epoch: [23] [ 900/1319] eta: 0:20:05 lr: 2.2309511481491173e-05 loss: 0.0497 (0.0480) time: 2.9124 data: 0.0073 max mem: 33370 +Epoch: [23] [ 910/1319] eta: 0:19:36 lr: 2.2300181945723685e-05 loss: 0.0436 (0.0479) time: 2.8852 data: 0.0071 max mem: 33370 +Epoch: [23] [ 920/1319] eta: 0:19:08 lr: 2.2290851976256266e-05 loss: 0.0443 (0.0480) time: 2.9034 data: 0.0074 max mem: 33370 +Epoch: [23] [ 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mem: 33370 +Epoch: [23] [1010/1319] eta: 0:14:48 lr: 2.2206862697871013e-05 loss: 0.0514 (0.0483) time: 2.8405 data: 0.0073 max mem: 33370 +Epoch: [23] [1020/1319] eta: 0:14:19 lr: 2.2197528379165116e-05 loss: 0.0503 (0.0483) time: 2.8289 data: 0.0073 max mem: 33370 +Epoch: [23] [1030/1319] eta: 0:13:50 lr: 2.218819362430666e-05 loss: 0.0419 (0.0482) time: 2.8560 data: 0.0073 max mem: 33370 +Epoch: [23] [1040/1319] eta: 0:13:22 lr: 2.217885843307136e-05 loss: 0.0373 (0.0482) time: 2.9055 data: 0.0073 max mem: 33370 +Epoch: [23] [1050/1319] eta: 0:12:53 lr: 2.2169522805234726e-05 loss: 0.0458 (0.0482) time: 2.9001 data: 0.0074 max mem: 33370 +Epoch: [23] [1060/1319] eta: 0:12:24 lr: 2.2160186740572026e-05 loss: 0.0448 (0.0482) time: 2.8394 data: 0.0078 max mem: 33370 +Epoch: [23] [1070/1319] eta: 0:11:55 lr: 2.215085023885832e-05 loss: 0.0452 (0.0482) time: 2.8394 data: 0.0080 max mem: 33370 +Epoch: [23] [1080/1319] eta: 0:11:27 lr: 2.2141513299868444e-05 loss: 0.0476 (0.0483) time: 2.8768 data: 0.0075 max mem: 33370 +Epoch: [23] [1090/1319] eta: 0:10:58 lr: 2.2132175923377022e-05 loss: 0.0458 (0.0483) time: 2.8882 data: 0.0071 max mem: 33370 +Epoch: [23] [1100/1319] eta: 0:10:29 lr: 2.2122838109158445e-05 loss: 0.0423 (0.0484) time: 2.9001 data: 0.0074 max mem: 33370 +Epoch: [23] [1110/1319] eta: 0:10:00 lr: 2.211349985698688e-05 loss: 0.0487 (0.0485) time: 2.8351 data: 0.0078 max mem: 33370 +Epoch: [23] [1120/1319] eta: 0:09:32 lr: 2.2104161166636274e-05 loss: 0.0391 (0.0484) time: 2.8735 data: 0.0077 max mem: 33370 +Epoch: [23] [1130/1319] eta: 0:09:03 lr: 2.2094822037880365e-05 loss: 0.0391 (0.0484) time: 2.9248 data: 0.0075 max mem: 33370 +Epoch: [23] [1140/1319] eta: 0:08:34 lr: 2.2085482470492644e-05 loss: 0.0455 (0.0485) time: 2.8896 data: 0.0074 max mem: 33370 +Epoch: [23] [1150/1319] eta: 0:08:05 lr: 2.20761424642464e-05 loss: 0.0417 (0.0484) time: 2.8728 data: 0.0076 max mem: 33370 +Epoch: [23] [1160/1319] eta: 0:07:37 lr: 2.2066802018914685e-05 loss: 0.0366 (0.0484) time: 2.8532 data: 0.0074 max mem: 33370 +Epoch: [23] [1170/1319] eta: 0:07:08 lr: 2.2057461134270328e-05 loss: 0.0379 (0.0484) time: 2.8644 data: 0.0071 max mem: 33370 +Epoch: [23] [1180/1319] eta: 0:06:39 lr: 2.2048119810085938e-05 loss: 0.0416 (0.0483) time: 2.8639 data: 0.0069 max mem: 33370 +Epoch: [23] [1190/1319] eta: 0:06:10 lr: 2.2038778046133896e-05 loss: 0.0470 (0.0485) time: 2.8762 data: 0.0071 max mem: 33370 +Epoch: [23] [1200/1319] eta: 0:05:41 lr: 2.2029435842186362e-05 loss: 0.0480 (0.0485) time: 2.8250 data: 0.0074 max mem: 33370 +Epoch: [23] [1210/1319] eta: 0:05:13 lr: 2.2020093198015273e-05 loss: 0.0446 (0.0484) time: 2.7014 data: 0.0071 max mem: 33370 +Epoch: [23] [1220/1319] eta: 0:04:44 lr: 2.2010750113392324e-05 loss: 0.0397 (0.0483) time: 2.7200 data: 0.0068 max mem: 33370 +Epoch: [23] [1230/1319] eta: 0:04:15 lr: 2.2001406588088997e-05 loss: 0.0397 (0.0483) time: 2.8391 data: 0.0070 max mem: 33370 +Epoch: [23] [1240/1319] eta: 0:03:46 lr: 2.199206262187655e-05 loss: 0.0439 (0.0484) time: 2.8881 data: 0.0070 max mem: 33370 +Epoch: [23] [1250/1319] eta: 0:03:18 lr: 2.1982718214526003e-05 loss: 0.0464 (0.0484) time: 2.8745 data: 0.0075 max mem: 33370 +Epoch: [23] [1260/1319] eta: 0:02:49 lr: 2.1973373365808168e-05 loss: 0.0440 (0.0484) time: 2.8766 data: 0.0074 max mem: 33370 +Epoch: [23] [1270/1319] eta: 0:02:20 lr: 2.1964028075493602e-05 loss: 0.0463 (0.0485) time: 2.9470 data: 0.0069 max mem: 33370 +Epoch: [23] [1280/1319] eta: 0:01:52 lr: 2.1954682343352655e-05 loss: 0.0492 (0.0485) time: 2.9256 data: 0.0071 max mem: 33370 +Epoch: [23] [1290/1319] eta: 0:01:23 lr: 2.1945336169155447e-05 loss: 0.0459 (0.0485) time: 2.8547 data: 0.0070 max mem: 33370 +Epoch: [23] [1300/1319] eta: 0:00:54 lr: 2.1935989552671862e-05 loss: 0.0414 (0.0484) time: 2.8705 data: 0.0075 max mem: 33370 +Epoch: [23] [1310/1319] eta: 0:00:25 lr: 2.192664249367156e-05 loss: 0.0477 (0.0485) time: 2.8737 data: 0.0079 max mem: 33370 +Epoch: [23] Total time: 1:03:08 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 2:15:57 time: 3.1704 data: 3.0521 max mem: 33370 +Test: [ 100/2573] eta: 0:04:16 time: 0.0730 data: 0.0013 max mem: 33370 +Test: [ 200/2573] eta: 0:03:32 time: 0.0742 data: 0.0012 max mem: 33370 +Test: [ 300/2573] eta: 0:03:11 time: 0.0757 data: 0.0012 max mem: 33370 +Test: [ 400/2573] eta: 0:02:57 time: 0.0761 data: 0.0012 max mem: 33370 +Test: [ 500/2573] eta: 0:02:46 time: 0.0747 data: 0.0013 max mem: 33370 +Test: [ 600/2573] eta: 0:02:36 time: 0.0745 data: 0.0012 max mem: 33370 +Test: [ 700/2573] eta: 0:02:27 time: 0.0744 data: 0.0012 max mem: 33370 +Test: [ 800/2573] eta: 0:02:19 time: 0.0778 data: 0.0012 max mem: 33370 +Test: [ 900/2573] eta: 0:02:10 time: 0.0749 data: 0.0013 max mem: 33370 +Test: [1000/2573] eta: 0:02:02 time: 0.0747 data: 0.0012 max mem: 33370 +Test: [1100/2573] eta: 0:01:54 time: 0.0749 data: 0.0012 max mem: 33370 +Test: [1200/2573] eta: 0:01:46 time: 0.0749 data: 0.0012 max mem: 33370 +Test: [1300/2573] eta: 0:01:38 time: 0.0748 data: 0.0012 max mem: 33370 +Test: [1400/2573] eta: 0:01:30 time: 0.0734 data: 0.0012 max mem: 33370 +Test: [1500/2573] eta: 0:01:22 time: 0.0743 data: 0.0012 max mem: 33370 +Test: [1600/2573] eta: 0:01:14 time: 0.0777 data: 0.0012 max mem: 33370 +Test: [1700/2573] eta: 0:01:06 time: 0.0727 data: 0.0011 max mem: 33370 +Test: [1800/2573] eta: 0:00:59 time: 0.0760 data: 0.0012 max mem: 33370 +Test: [1900/2573] eta: 0:00:51 time: 0.0735 data: 0.0013 max mem: 33370 +Test: [2000/2573] eta: 0:00:43 time: 0.0751 data: 0.0013 max mem: 33370 +Test: [2100/2573] eta: 0:00:36 time: 0.0766 data: 0.0012 max mem: 33370 +Test: [2200/2573] eta: 0:00:28 time: 0.0769 data: 0.0012 max mem: 33370 +Test: [2300/2573] eta: 0:00:20 time: 0.0770 data: 0.0013 max mem: 33370 +Test: [2400/2573] eta: 0:00:13 time: 0.0720 data: 0.0013 max mem: 33370 +Test: [2500/2573] eta: 0:00:05 time: 0.0751 data: 0.0012 max mem: 33370 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: Total time: 0:03:16 +Final results: +Mean IoU is 63.70 + + precision@0.5 = 71.85 + precision@0.6 = 66.14 + precision@0.7 = 59.74 + precision@0.8 = 48.12 + precision@0.9 = 24.14 + overall IoU = 61.26 + +Average object IoU 63.702373384345414 +Overall IoU 61.25926208496094 +Better epoch: 23 + +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [24] [ 0/1319] eta: 1:36:12 lr: 2.1918229762028934e-05 loss: 0.0682 (0.0682) time: 4.3767 data: 1.3187 max mem: 33370 +Epoch: [24] [ 10/1319] eta: 1:05:06 lr: 2.1908881861611456e-05 loss: 0.0446 (0.0503) time: 2.9847 data: 0.1262 max mem: 33370 +Epoch: [24] [ 20/1319] eta: 1:03:40 lr: 2.1899533518007982e-05 loss: 0.0420 (0.0656) time: 2.8696 data: 0.0071 max mem: 33370 +Epoch: [24] [ 30/1319] eta: 1:02:45 lr: 2.189018473098726e-05 loss: 0.0382 (0.0585) time: 2.8869 data: 0.0075 max mem: 33370 +Epoch: [24] [ 40/1319] eta: 1:01:48 lr: 2.188083550031783e-05 loss: 0.0382 (0.0553) time: 2.8558 data: 0.0080 max mem: 33370 +Epoch: [24] [ 50/1319] eta: 1:00:47 lr: 2.1871485825767997e-05 loss: 0.0392 (0.0541) time: 2.8014 data: 0.0075 max mem: 33370 +Epoch: [24] [ 60/1319] eta: 1:00:40 lr: 2.1862135707105826e-05 loss: 0.0388 (0.0514) time: 2.8739 data: 0.0073 max mem: 33370 +Epoch: [24] [ 70/1319] eta: 1:00:02 lr: 2.1852785144099174e-05 loss: 0.0376 (0.0501) time: 2.9092 data: 0.0078 max mem: 33370 +Epoch: [24] [ 80/1319] eta: 0:59:34 lr: 2.184343413651562e-05 loss: 0.0404 (0.0500) time: 2.8662 data: 0.0073 max mem: 33370 +Epoch: [24] [ 90/1319] eta: 0:59:04 lr: 2.1834082684122557e-05 loss: 0.0404 (0.0497) time: 2.8821 data: 0.0072 max mem: 33370 +Epoch: [24] [ 100/1319] eta: 0:58:36 lr: 2.1824730786687132e-05 loss: 0.0421 (0.0490) time: 2.8825 data: 0.0074 max mem: 33370 +Epoch: [24] [ 110/1319] eta: 0:58:10 lr: 2.181537844397624e-05 loss: 0.0427 (0.0489) time: 2.9024 data: 0.0073 max mem: 33370 +Epoch: [24] [ 120/1319] eta: 0:57:33 lr: 2.1806025655756576e-05 loss: 0.0398 (0.0489) time: 2.8583 data: 0.0075 max mem: 33370 +Epoch: [24] [ 130/1319] eta: 0:57:02 lr: 2.1796672421794575e-05 loss: 0.0398 (0.0482) time: 2.8304 data: 0.0080 max mem: 33370 +Epoch: [24] [ 140/1319] eta: 0:56:31 lr: 2.1787318741856443e-05 loss: 0.0395 (0.0478) time: 2.8526 data: 0.0079 max mem: 33370 +Epoch: [24] [ 150/1319] eta: 0:56:04 lr: 2.1777964615708157e-05 loss: 0.0395 (0.0475) time: 2.8777 data: 0.0073 max mem: 33370 +Epoch: [24] [ 160/1319] eta: 0:55:38 lr: 2.1768610043115462e-05 loss: 0.0438 (0.0475) time: 2.9135 data: 0.0072 max mem: 33370 +Epoch: [24] [ 170/1319] eta: 0:55:11 lr: 2.1759255023843863e-05 loss: 0.0421 (0.0474) time: 2.9111 data: 0.0074 max mem: 33370 +Epoch: [24] [ 180/1319] eta: 0:54:44 lr: 2.1749899557658636e-05 loss: 0.0398 (0.0472) time: 2.9074 data: 0.0074 max mem: 33370 +Epoch: [24] [ 190/1319] eta: 0:54:16 lr: 2.17405436443248e-05 loss: 0.0436 (0.0471) time: 2.9019 data: 0.0073 max mem: 33370 +Epoch: [24] [ 200/1319] eta: 0:53:41 lr: 2.1731187283607167e-05 loss: 0.0386 (0.0468) time: 2.8332 data: 0.0072 max mem: 33370 +Epoch: [24] [ 210/1319] eta: 0:53:21 lr: 2.17218304752703e-05 loss: 0.0449 (0.0471) time: 2.9081 data: 0.0074 max mem: 33370 +Epoch: [24] [ 220/1319] eta: 0:52:49 lr: 2.171247321907852e-05 loss: 0.0463 (0.0469) time: 2.9404 data: 0.0078 max mem: 33370 +Epoch: [24] [ 230/1319] eta: 0:52:21 lr: 2.1703115514795925e-05 loss: 0.0493 (0.0473) time: 2.8690 data: 0.0074 max mem: 33370 +Epoch: [24] [ 240/1319] eta: 0:51:54 lr: 2.1693757362186356e-05 loss: 0.0408 (0.0471) time: 2.9066 data: 0.0072 max mem: 33370 +Epoch: [24] [ 250/1319] eta: 0:51:24 lr: 2.1684398761013434e-05 loss: 0.0411 (0.0473) time: 2.8949 data: 0.0073 max mem: 33370 +Epoch: [24] [ 260/1319] eta: 0:50:54 lr: 2.1675039711040532e-05 loss: 0.0478 (0.0471) time: 2.8571 data: 0.0077 max mem: 33370 +Epoch: [24] [ 270/1319] eta: 0:50:24 lr: 2.166568021203079e-05 loss: 0.0380 (0.0472) time: 2.8447 data: 0.0076 max mem: 33370 +Epoch: [24] [ 280/1319] eta: 0:49:56 lr: 2.1656320263747106e-05 loss: 0.0380 (0.0468) time: 2.8796 data: 0.0075 max mem: 33370 +Epoch: [24] [ 290/1319] eta: 0:49:28 lr: 2.164695986595215e-05 loss: 0.0383 (0.0466) time: 2.9163 data: 0.0076 max mem: 33370 +Epoch: [24] [ 300/1319] eta: 0:48:59 lr: 2.163759901840832e-05 loss: 0.0383 (0.0465) time: 2.8938 data: 0.0072 max mem: 33370 +Epoch: [24] [ 310/1319] eta: 0:48:30 lr: 2.1628237720877814e-05 loss: 0.0441 (0.0464) time: 2.8843 data: 0.0072 max mem: 33370 +Epoch: [24] [ 320/1319] eta: 0:48:01 lr: 2.161887597312257e-05 loss: 0.0446 (0.0463) time: 2.8786 data: 0.0072 max mem: 33370 +Epoch: [24] [ 330/1319] eta: 0:47:32 lr: 2.160951377490428e-05 loss: 0.0408 (0.0463) time: 2.8650 data: 0.0069 max mem: 33370 +Epoch: [24] [ 340/1319] eta: 0:47:03 lr: 2.160015112598442e-05 loss: 0.0408 (0.0462) time: 2.8804 data: 0.0072 max mem: 33370 +Epoch: [24] [ 350/1319] eta: 0:46:31 lr: 2.1590788026124187e-05 loss: 0.0414 (0.0461) time: 2.8291 data: 0.0074 max mem: 33370 +Epoch: [24] [ 360/1319] eta: 0:46:05 lr: 2.158142447508457e-05 loss: 0.0416 (0.0460) time: 2.8899 data: 0.0075 max mem: 33370 +Epoch: [24] [ 370/1319] eta: 0:45:36 lr: 2.1572060472626296e-05 loss: 0.0424 (0.0460) time: 2.9401 data: 0.0079 max mem: 33370 +Epoch: [24] [ 380/1319] eta: 0:45:07 lr: 2.156269601850986e-05 loss: 0.0394 (0.0459) time: 2.8627 data: 0.0075 max mem: 33370 +Epoch: [24] [ 390/1319] eta: 0:44:37 lr: 2.1553331112495514e-05 loss: 0.0379 (0.0458) time: 2.8521 data: 0.0072 max mem: 33370 +Epoch: [24] [ 400/1319] eta: 0:44:08 lr: 2.1543965754343263e-05 loss: 0.0416 (0.0460) time: 2.8691 data: 0.0072 max mem: 33370 +Epoch: [24] [ 410/1319] eta: 0:43:39 lr: 2.1534599943812868e-05 loss: 0.0432 (0.0459) time: 2.8742 data: 0.0070 max mem: 33370 +Epoch: [24] [ 420/1319] eta: 0:43:10 lr: 2.1525233680663844e-05 loss: 0.0400 (0.0458) time: 2.8669 data: 0.0070 max mem: 33370 +Epoch: [24] [ 430/1319] eta: 0:42:41 lr: 2.151586696465547e-05 loss: 0.0388 (0.0457) time: 2.8665 data: 0.0073 max mem: 33370 +Epoch: [24] [ 440/1319] eta: 0:42:11 lr: 2.1506499795546773e-05 loss: 0.0365 (0.0455) time: 2.8463 data: 0.0082 max mem: 33370 +Epoch: [24] [ 450/1319] eta: 0:41:43 lr: 2.1497132173096545e-05 loss: 0.0420 (0.0454) time: 2.8793 data: 0.0078 max mem: 33370 +Epoch: [24] [ 460/1319] eta: 0:41:14 lr: 2.1487764097063317e-05 loss: 0.0441 (0.0455) time: 2.9000 data: 0.0072 max mem: 33370 +Epoch: [24] [ 470/1319] eta: 0:40:46 lr: 2.1478395567205385e-05 loss: 0.0431 (0.0455) time: 2.8991 data: 0.0075 max mem: 33370 +Epoch: [24] [ 480/1319] eta: 0:40:18 lr: 2.14690265832808e-05 loss: 0.0451 (0.0457) time: 2.9205 data: 0.0073 max mem: 33370 +Epoch: [24] [ 490/1319] eta: 0:39:49 lr: 2.1459657145047365e-05 loss: 0.0458 (0.0457) time: 2.9040 data: 0.0069 max mem: 33370 +Epoch: [24] [ 500/1319] eta: 0:39:19 lr: 2.1450287252262635e-05 loss: 0.0374 (0.0456) time: 2.8512 data: 0.0069 max mem: 33370 +Epoch: [24] [ 510/1319] eta: 0:38:51 lr: 2.144091690468391e-05 loss: 0.0407 (0.0457) time: 2.8600 data: 0.0074 max mem: 33370 +Epoch: [24] [ 520/1319] eta: 0:38:22 lr: 2.1431546102068255e-05 loss: 0.0381 (0.0455) time: 2.8830 data: 0.0076 max mem: 33370 +Epoch: [24] [ 530/1319] eta: 0:37:52 lr: 2.142217484417249e-05 loss: 0.0373 (0.0455) time: 2.8363 data: 0.0076 max mem: 33370 +Epoch: [24] [ 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eta: 0:18:38 lr: 2.104694837585335e-05 loss: 0.0406 (0.0456) time: 2.8816 data: 0.0079 max mem: 33370 +Epoch: [24] [ 940/1319] eta: 0:18:09 lr: 2.1037558238977907e-05 loss: 0.0363 (0.0456) time: 2.8996 data: 0.0071 max mem: 33370 +Epoch: [24] [ 950/1319] eta: 0:17:40 lr: 2.1028167636379597e-05 loss: 0.0368 (0.0455) time: 2.8630 data: 0.0069 max mem: 33370 +Epoch: [24] [ 960/1319] eta: 0:17:12 lr: 2.1018776567804213e-05 loss: 0.0374 (0.0455) time: 2.8938 data: 0.0071 max mem: 33370 +Epoch: [24] [ 970/1319] eta: 0:16:43 lr: 2.1009385032997278e-05 loss: 0.0358 (0.0455) time: 2.9390 data: 0.0073 max mem: 33370 +Epoch: [24] [ 980/1319] eta: 0:16:15 lr: 2.0999993031704057e-05 loss: 0.0348 (0.0454) time: 2.8942 data: 0.0073 max mem: 33370 +Epoch: [24] [ 990/1319] eta: 0:15:46 lr: 2.0990600563669546e-05 loss: 0.0358 (0.0454) time: 2.8839 data: 0.0075 max mem: 33370 +Epoch: [24] [1000/1319] eta: 0:15:17 lr: 2.0981207628638462e-05 loss: 0.0444 (0.0454) time: 2.9089 data: 0.0074 max mem: 33370 +Epoch: [24] [1010/1319] eta: 0:14:49 lr: 2.0971814226355274e-05 loss: 0.0444 (0.0455) time: 2.9153 data: 0.0074 max mem: 33370 +Epoch: [24] [1020/1319] eta: 0:14:20 lr: 2.0962420356564173e-05 loss: 0.0415 (0.0454) time: 2.8640 data: 0.0078 max mem: 33370 +Epoch: [24] [1030/1319] eta: 0:13:51 lr: 2.0953026019009095e-05 loss: 0.0409 (0.0455) time: 2.8266 data: 0.0074 max mem: 33370 +Epoch: [24] [1040/1319] eta: 0:13:22 lr: 2.0943631213433694e-05 loss: 0.0443 (0.0455) time: 2.8600 data: 0.0074 max mem: 33370 +Epoch: [24] [1050/1319] eta: 0:12:53 lr: 2.0934235939581352e-05 loss: 0.0443 (0.0455) time: 2.8793 data: 0.0079 max mem: 33370 +Epoch: [24] [1060/1319] eta: 0:12:24 lr: 2.0924840197195202e-05 loss: 0.0376 (0.0454) time: 2.8530 data: 0.0076 max mem: 33370 +Epoch: [24] [1070/1319] eta: 0:11:56 lr: 2.0915443986018095e-05 loss: 0.0412 (0.0455) time: 2.8344 data: 0.0077 max mem: 33370 +Epoch: [24] [1080/1319] eta: 0:11:27 lr: 2.0906047305792607e-05 loss: 0.0421 (0.0455) time: 2.8494 data: 0.0078 max mem: 33370 +Epoch: [24] [1090/1319] eta: 0:10:58 lr: 2.0896650156261064e-05 loss: 0.0421 (0.0455) time: 2.8713 data: 0.0072 max mem: 33370 +Epoch: [24] [1100/1319] eta: 0:10:29 lr: 2.0887252537165494e-05 loss: 0.0496 (0.0455) time: 2.8437 data: 0.0069 max mem: 33370 +Epoch: [24] [1110/1319] eta: 0:10:01 lr: 2.087785444824768e-05 loss: 0.0459 (0.0457) time: 2.8864 data: 0.0072 max mem: 33370 +Epoch: [24] [1120/1319] eta: 0:09:32 lr: 2.086845588924912e-05 loss: 0.0442 (0.0456) time: 2.9317 data: 0.0071 max mem: 33370 +Epoch: [24] [1130/1319] eta: 0:09:03 lr: 2.0859056859911038e-05 loss: 0.0323 (0.0456) time: 2.8855 data: 0.0068 max mem: 33370 +Epoch: [24] [1140/1319] eta: 0:08:34 lr: 2.0849657359974397e-05 loss: 0.0441 (0.0457) time: 2.8863 data: 0.0070 max mem: 33370 +Epoch: [24] [1150/1319] eta: 0:08:06 lr: 2.084025738917989e-05 loss: 0.0424 (0.0457) time: 2.8829 data: 0.0076 max mem: 33370 +Epoch: [24] [1160/1319] eta: 0:07:37 lr: 2.083085694726791e-05 loss: 0.0412 (0.0457) time: 2.8462 data: 0.0081 max mem: 33370 +Epoch: [24] [1170/1319] eta: 0:07:08 lr: 2.0821456033978605e-05 loss: 0.0440 (0.0457) time: 2.8293 data: 0.0082 max mem: 33370 +Epoch: [24] [1180/1319] eta: 0:06:39 lr: 2.0812054649051834e-05 loss: 0.0442 (0.0458) time: 2.8170 data: 0.0076 max mem: 33370 +Epoch: [24] [1190/1319] eta: 0:06:10 lr: 2.0802652792227197e-05 loss: 0.0453 (0.0458) time: 2.8969 data: 0.0074 max mem: 33370 +Epoch: [24] [1200/1319] eta: 0:05:42 lr: 2.0793250463244006e-05 loss: 0.0483 (0.0459) time: 2.9174 data: 0.0074 max mem: 33370 +Epoch: [24] [1210/1319] eta: 0:05:13 lr: 2.07838476618413e-05 loss: 0.0485 (0.0459) time: 2.8698 data: 0.0071 max mem: 33370 +Epoch: [24] [1220/1319] eta: 0:04:44 lr: 2.077444438775784e-05 loss: 0.0485 (0.0460) time: 2.9192 data: 0.0073 max mem: 33370 +Epoch: [24] [1230/1319] eta: 0:04:15 lr: 2.0765040640732118e-05 loss: 0.0439 (0.0459) time: 2.8886 data: 0.0081 max mem: 33370 +Epoch: [24] [1240/1319] eta: 0:03:47 lr: 2.0755636420502354e-05 loss: 0.0429 (0.0459) time: 2.8512 data: 0.0084 max mem: 33370 +Epoch: [24] [1250/1319] eta: 0:03:18 lr: 2.074623172680648e-05 loss: 0.0434 (0.0460) time: 2.8178 data: 0.0079 max mem: 33370 +Epoch: [24] [1260/1319] eta: 0:02:49 lr: 2.0736826559382146e-05 loss: 0.0544 (0.0461) time: 2.8551 data: 0.0074 max mem: 33370 +Epoch: [24] [1270/1319] eta: 0:02:20 lr: 2.072742091796674e-05 loss: 0.0553 (0.0461) time: 2.9206 data: 0.0076 max mem: 33370 +Epoch: [24] [1280/1319] eta: 0:01:52 lr: 2.071801480229737e-05 loss: 0.0466 (0.0461) time: 2.8925 data: 0.0078 max mem: 33370 +Epoch: [24] [1290/1319] eta: 0:01:23 lr: 2.0708608212110852e-05 loss: 0.0417 (0.0461) time: 2.9055 data: 0.0073 max mem: 33370 +Epoch: [24] [1300/1319] eta: 0:00:54 lr: 2.0699201147143737e-05 loss: 0.0417 (0.0461) time: 2.8930 data: 0.0074 max mem: 33370 +Epoch: [24] [1310/1319] eta: 0:00:25 lr: 2.0689793607132295e-05 loss: 0.0430 (0.0462) time: 2.8595 data: 0.0074 max mem: 33370 +Epoch: [24] Total time: 1:03:13 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 2:09:27 time: 3.0187 data: 2.7584 max mem: 33370 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 100/2573] eta: 0:04:12 time: 0.0721 data: 0.0012 max mem: 33370 +Test: [ 200/2573] eta: 0:03:30 time: 0.0740 data: 0.0012 max mem: 33370 +Test: [ 300/2573] eta: 0:03:09 time: 0.0753 data: 0.0012 max mem: 33370 +Test: [ 400/2573] eta: 0:02:55 time: 0.0755 data: 0.0012 max mem: 33370 +Test: [ 500/2573] eta: 0:02:45 time: 0.0745 data: 0.0012 max mem: 33370 +Test: [ 600/2573] eta: 0:02:36 time: 0.0741 data: 0.0012 max mem: 33370 +Test: [ 700/2573] eta: 0:02:27 time: 0.0744 data: 0.0013 max mem: 33370 +Test: [ 800/2573] eta: 0:02:18 time: 0.0778 data: 0.0012 max mem: 33370 +Test: [ 900/2573] eta: 0:02:10 time: 0.0742 data: 0.0012 max mem: 33370 +Test: [1000/2573] eta: 0:02:02 time: 0.0746 data: 0.0013 max mem: 33370 +Test: [1100/2573] eta: 0:01:54 time: 0.0748 data: 0.0013 max mem: 33370 +Test: [1200/2573] eta: 0:01:46 time: 0.0748 data: 0.0012 max mem: 33370 +Test: [1300/2573] eta: 0:01:38 time: 0.0747 data: 0.0012 max mem: 33370 +Test: [1400/2573] eta: 0:01:30 time: 0.0732 data: 0.0012 max mem: 33370 +Test: [1500/2573] eta: 0:01:22 time: 0.0749 data: 0.0013 max mem: 33370 +Test: [1600/2573] eta: 0:01:14 time: 0.0781 data: 0.0012 max mem: 33370 +Test: [1700/2573] eta: 0:01:06 time: 0.0730 data: 0.0012 max mem: 33370 +Test: [1800/2573] eta: 0:00:59 time: 0.0765 data: 0.0013 max mem: 33370 +Test: [1900/2573] eta: 0:00:51 time: 0.0736 data: 0.0013 max mem: 33370 +Test: [2000/2573] eta: 0:00:43 time: 0.0748 data: 0.0012 max mem: 33370 +Test: [2100/2573] eta: 0:00:36 time: 0.0766 data: 0.0012 max mem: 33370 +Test: [2200/2573] eta: 0:00:28 time: 0.0771 data: 0.0013 max mem: 33370 +Test: [2300/2573] eta: 0:00:20 time: 0.0766 data: 0.0013 max mem: 33370 +Test: [2400/2573] eta: 0:00:13 time: 0.0716 data: 0.0013 max mem: 33370 +Test: [2500/2573] eta: 0:00:05 time: 0.0751 data: 0.0012 max mem: 33370 +Test: Total time: 0:03:15 +Final results: +Mean IoU is 63.40 + + precision@0.5 = 71.77 + precision@0.6 = 66.40 + precision@0.7 = 59.07 + precision@0.8 = 47.22 + precision@0.9 = 23.98 + overall IoU = 61.27 + +Average object IoU 63.40226846507476 +Overall IoU 61.272857666015625 +Better epoch: 24 + +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [25] [ 0/1319] eta: 1:34:25 lr: 2.0681326414740886e-05 loss: 0.0349 (0.0349) time: 4.2953 data: 1.3593 max mem: 33370 +Epoch: [25] [ 10/1319] eta: 1:04:42 lr: 2.0671917971417626e-05 loss: 0.0361 (0.0439) time: 2.9656 data: 0.1297 max mem: 33370 +Epoch: [25] [ 20/1319] eta: 1:04:30 lr: 2.0662509052283616e-05 loss: 0.0412 (0.0443) time: 2.9137 data: 0.0067 max mem: 33370 +Epoch: [25] [ 30/1319] eta: 1:03:39 lr: 2.0653099657074033e-05 loss: 0.0355 (0.0408) time: 2.9622 data: 0.0069 max mem: 33370 +Epoch: [25] [ 40/1319] eta: 1:02:41 lr: 2.064368978552377e-05 loss: 0.0342 (0.0423) time: 2.9012 data: 0.0074 max mem: 33370 +Epoch: [25] [ 50/1319] eta: 1:02:05 lr: 2.0634279437367437e-05 loss: 0.0373 (0.0414) time: 2.8935 data: 0.0072 max mem: 33370 +Epoch: [25] [ 60/1319] eta: 1:01:14 lr: 2.0624868612339364e-05 loss: 0.0368 (0.0414) time: 2.8727 data: 0.0068 max mem: 33370 +Epoch: [25] [ 70/1319] eta: 1:00:31 lr: 2.0615457310173584e-05 loss: 0.0342 (0.0405) time: 2.8356 data: 0.0069 max mem: 33370 +Epoch: [25] [ 80/1319] eta: 0:59:48 lr: 2.0606045530603866e-05 loss: 0.0423 (0.0415) time: 2.8285 data: 0.0072 max mem: 33370 +Epoch: [25] [ 90/1319] eta: 0:59:01 lr: 2.059663327336368e-05 loss: 0.0432 (0.0414) time: 2.7900 data: 0.0072 max mem: 33370 +Epoch: [25] [ 100/1319] eta: 0:58:44 lr: 2.058722053818622e-05 loss: 0.0417 (0.0431) time: 2.8684 data: 0.0070 max mem: 33370 +Epoch: [25] [ 110/1319] eta: 0:58:13 lr: 2.0577807324804403e-05 loss: 0.0426 (0.0437) time: 2.9232 data: 0.0070 max mem: 33370 +Epoch: [25] [ 120/1319] eta: 0:57:45 lr: 2.0568393632950847e-05 loss: 0.0426 (0.0440) time: 2.8859 data: 0.0071 max mem: 33370 +Epoch: [25] [ 130/1319] eta: 0:57:14 lr: 2.055897946235788e-05 loss: 0.0426 (0.0448) time: 2.8864 data: 0.0078 max mem: 33370 +Epoch: [25] [ 140/1319] eta: 0:56:41 lr: 2.054956481275756e-05 loss: 0.0394 (0.0445) time: 2.8519 data: 0.0077 max mem: 33370 +Epoch: [25] [ 150/1319] eta: 0:56:09 lr: 2.0540149683881653e-05 loss: 0.0377 (0.0446) time: 2.8384 data: 0.0071 max mem: 33370 +Epoch: [25] [ 160/1319] eta: 0:55:34 lr: 2.0530734075461633e-05 loss: 0.0358 (0.0441) time: 2.8241 data: 0.0071 max mem: 33370 +Epoch: [25] [ 170/1319] eta: 0:55:07 lr: 2.05213179872287e-05 loss: 0.0340 (0.0440) time: 2.8531 data: 0.0073 max mem: 33370 +Epoch: [25] [ 180/1319] eta: 0:54:41 lr: 2.051190141891374e-05 loss: 0.0311 (0.0437) time: 2.9145 data: 0.0075 max mem: 33370 +Epoch: [25] [ 190/1319] eta: 0:54:12 lr: 2.050248437024738e-05 loss: 0.0348 (0.0434) time: 2.8987 data: 0.0074 max mem: 33370 +Epoch: [25] [ 200/1319] eta: 0:53:44 lr: 2.049306684095994e-05 loss: 0.0401 (0.0439) time: 2.8859 data: 0.0071 max mem: 33370 +Epoch: [25] [ 210/1319] eta: 0:53:16 lr: 2.048364883078146e-05 loss: 0.0416 (0.0439) time: 2.8963 data: 0.0070 max mem: 33370 +Epoch: [25] [ 220/1319] eta: 0:52:48 lr: 2.0474230339441687e-05 loss: 0.0356 (0.0437) time: 2.8945 data: 0.0076 max mem: 33370 +Epoch: [25] [ 230/1319] eta: 0:52:20 lr: 2.0464811366670074e-05 loss: 0.0349 (0.0437) time: 2.9004 data: 0.0079 max mem: 33370 +Epoch: [25] [ 240/1319] eta: 0:51:46 lr: 2.0455391912195788e-05 loss: 0.0400 (0.0436) time: 2.8362 data: 0.0072 max mem: 33370 +Epoch: [25] [ 250/1319] eta: 0:51:20 lr: 2.0445971975747706e-05 loss: 0.0400 (0.0436) time: 2.8605 data: 0.0078 max mem: 33370 +Epoch: [25] [ 260/1319] eta: 0:50:51 lr: 2.0436551557054405e-05 loss: 0.0417 (0.0437) time: 2.9122 data: 0.0078 max mem: 33370 +Epoch: [25] [ 270/1319] eta: 0:50:21 lr: 2.0427130655844186e-05 loss: 0.0417 (0.0437) time: 2.8556 data: 0.0074 max mem: 33370 +Epoch: [25] [ 280/1319] eta: 0:49:52 lr: 2.041770927184505e-05 loss: 0.0416 (0.0435) time: 2.8616 data: 0.0079 max mem: 33370 +Epoch: [25] [ 290/1319] eta: 0:49:21 lr: 2.0408287404784693e-05 loss: 0.0411 (0.0433) time: 2.8490 data: 0.0081 max mem: 33370 +Epoch: [25] [ 300/1319] eta: 0:48:51 lr: 2.0398865054390533e-05 loss: 0.0374 (0.0432) time: 2.8313 data: 0.0079 max mem: 33370 +Epoch: [25] [ 310/1319] eta: 0:48:22 lr: 2.038944222038969e-05 loss: 0.0428 (0.0432) time: 2.8505 data: 0.0075 max mem: 33370 +Epoch: [25] [ 320/1319] eta: 0:47:53 lr: 2.0380018902508984e-05 loss: 0.0396 (0.0430) time: 2.8724 data: 0.0073 max mem: 33370 +Epoch: [25] [ 330/1319] eta: 0:47:24 lr: 2.0370595100474957e-05 loss: 0.0363 (0.0431) time: 2.8720 data: 0.0077 max mem: 33370 +Epoch: [25] [ 340/1319] eta: 0:46:54 lr: 2.036117081401383e-05 loss: 0.0363 (0.0429) time: 2.8488 data: 0.0075 max mem: 33370 +Epoch: [25] [ 350/1319] eta: 0:46:24 lr: 2.035174604285155e-05 loss: 0.0415 (0.0431) time: 2.8377 data: 0.0073 max mem: 33370 +Epoch: [25] [ 360/1319] eta: 0:45:58 lr: 2.0342320786713757e-05 loss: 0.0415 (0.0432) time: 2.8979 data: 0.0075 max mem: 33370 +Epoch: [25] [ 370/1319] eta: 0:45:28 lr: 2.03328950453258e-05 loss: 0.0360 (0.0436) time: 2.9051 data: 0.0075 max mem: 33370 +Epoch: [25] [ 380/1319] eta: 0:45:00 lr: 2.0323468818412736e-05 loss: 0.0408 (0.0435) time: 2.8617 data: 0.0074 max mem: 33370 +Epoch: [25] [ 390/1319] eta: 0:44:28 lr: 2.03140421056993e-05 loss: 0.0371 (0.0434) time: 2.8206 data: 0.0071 max mem: 33370 +Epoch: [25] [ 400/1319] eta: 0:44:02 lr: 2.0304614906909954e-05 loss: 0.0353 (0.0435) time: 2.8667 data: 0.0076 max mem: 33370 +Epoch: [25] [ 410/1319] eta: 0:43:33 lr: 2.0295187221768858e-05 loss: 0.0451 (0.0436) time: 2.9163 data: 0.0077 max mem: 33370 +Epoch: [25] [ 420/1319] eta: 0:43:04 lr: 2.028575904999986e-05 loss: 0.0455 (0.0436) time: 2.8770 data: 0.0076 max mem: 33370 +Epoch: [25] [ 430/1319] eta: 0:42:36 lr: 2.0276330391326524e-05 loss: 0.0379 (0.0437) time: 2.8917 data: 0.0076 max mem: 33370 +Epoch: [25] [ 440/1319] eta: 0:42:07 lr: 2.026690124547211e-05 loss: 0.0461 (0.0439) time: 2.8890 data: 0.0072 max mem: 33370 +Epoch: [25] [ 450/1319] eta: 0:41:38 lr: 2.025747161215956e-05 loss: 0.0426 (0.0438) time: 2.8709 data: 0.0072 max mem: 33370 +Epoch: [25] [ 460/1319] eta: 0:41:09 lr: 2.0248041491111535e-05 loss: 0.0426 (0.0442) time: 2.8414 data: 0.0072 max mem: 33370 +Epoch: [25] [ 470/1319] eta: 0:40:42 lr: 2.0238610882050398e-05 loss: 0.0404 (0.0441) time: 2.9232 data: 0.0072 max mem: 33370 +Epoch: [25] [ 480/1319] eta: 0:40:13 lr: 2.0229179784698192e-05 loss: 0.0372 (0.0439) time: 2.9167 data: 0.0072 max mem: 33370 +Epoch: [25] [ 490/1319] eta: 0:39:43 lr: 2.0219748198776674e-05 loss: 0.0361 (0.0438) time: 2.8318 data: 0.0071 max mem: 33370 +Epoch: [25] [ 500/1319] eta: 0:39:15 lr: 2.0210316124007283e-05 loss: 0.0388 (0.0440) time: 2.8697 data: 0.0071 max mem: 33370 +Epoch: [25] [ 510/1319] eta: 0:38:46 lr: 2.020088356011117e-05 loss: 0.0440 (0.0441) time: 2.8920 data: 0.0072 max mem: 33370 +Epoch: [25] [ 520/1319] eta: 0:38:18 lr: 2.019145050680917e-05 loss: 0.0436 (0.0443) time: 2.9033 data: 0.0074 max mem: 33370 +Epoch: [25] [ 530/1319] eta: 0:37:49 lr: 2.0182016963821814e-05 loss: 0.0412 (0.0442) time: 2.8858 data: 0.0074 max mem: 33370 +Epoch: [25] [ 540/1319] eta: 0:37:18 lr: 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(0.0448) time: 2.8971 data: 0.0070 max mem: 33370 +Epoch: [25] [ 860/1319] eta: 0:21:57 lr: 1.987043348451999e-05 loss: 0.0406 (0.0447) time: 2.8757 data: 0.0073 max mem: 33370 +Epoch: [25] [ 870/1319] eta: 0:21:28 lr: 1.9860983123743625e-05 loss: 0.0377 (0.0446) time: 2.8059 data: 0.0076 max mem: 33370 +Epoch: [25] [ 880/1319] eta: 0:21:00 lr: 1.9851532263305046e-05 loss: 0.0373 (0.0447) time: 2.8606 data: 0.0072 max mem: 33370 +Epoch: [25] [ 890/1319] eta: 0:20:31 lr: 1.98420809029135e-05 loss: 0.0474 (0.0448) time: 2.9121 data: 0.0071 max mem: 33370 +Epoch: [25] [ 900/1319] eta: 0:20:02 lr: 1.9832629042277908e-05 loss: 0.0396 (0.0448) time: 2.8622 data: 0.0072 max mem: 33370 +Epoch: [25] [ 910/1319] eta: 0:19:34 lr: 1.982317668110687e-05 loss: 0.0388 (0.0451) time: 2.8981 data: 0.0073 max mem: 33370 +Epoch: [25] [ 920/1319] eta: 0:19:05 lr: 1.981372381910867e-05 loss: 0.0445 (0.0451) time: 2.8905 data: 0.0078 max mem: 33370 +Epoch: [25] [ 930/1319] eta: 0:18:36 lr: 1.980427045599124e-05 loss: 0.0443 (0.0451) time: 2.8628 data: 0.0081 max mem: 33370 +Epoch: [25] [ 940/1319] eta: 0:18:07 lr: 1.9794816591462205e-05 loss: 0.0443 (0.0451) time: 2.8538 data: 0.0076 max mem: 33370 +Epoch: [25] [ 950/1319] eta: 0:17:39 lr: 1.9785362225228878e-05 loss: 0.0364 (0.0450) time: 2.8790 data: 0.0070 max mem: 33370 +Epoch: [25] [ 960/1319] eta: 0:17:10 lr: 1.9775907356998215e-05 loss: 0.0360 (0.0449) time: 2.9156 data: 0.0072 max mem: 33370 +Epoch: [25] [ 970/1319] eta: 0:16:42 lr: 1.976645198647688e-05 loss: 0.0396 (0.0449) time: 2.9275 data: 0.0073 max mem: 33370 +Epoch: [25] [ 980/1319] eta: 0:16:13 lr: 1.9756996113371165e-05 loss: 0.0366 (0.0449) time: 2.9021 data: 0.0071 max mem: 33370 +Epoch: [25] [ 990/1319] eta: 0:15:45 lr: 1.9747539737387077e-05 loss: 0.0392 (0.0450) time: 2.8953 data: 0.0071 max mem: 33370 +Epoch: [25] [1000/1319] eta: 0:15:16 lr: 1.973808285823027e-05 loss: 0.0392 (0.0449) time: 2.9157 data: 0.0072 max mem: 33370 +Epoch: [25] [1010/1319] eta: 0:14:47 lr: 1.972862547560608e-05 loss: 0.0369 (0.0450) time: 2.8763 data: 0.0075 max mem: 33370 +Epoch: [25] [1020/1319] eta: 0:14:18 lr: 1.9719167589219505e-05 loss: 0.0494 (0.0451) time: 2.8116 data: 0.0071 max mem: 33370 +Epoch: [25] [1030/1319] eta: 0:13:50 lr: 1.9709709198775227e-05 loss: 0.0426 (0.0452) time: 2.8493 data: 0.0068 max mem: 33370 +Epoch: [25] [1040/1319] eta: 0:13:21 lr: 1.9700250303977575e-05 loss: 0.0413 (0.0452) time: 2.9120 data: 0.0070 max mem: 33370 +Epoch: [25] [1050/1319] eta: 0:12:52 lr: 1.969079090453056e-05 loss: 0.0375 (0.0452) time: 2.8775 data: 0.0071 max mem: 33370 +Epoch: [25] [1060/1319] eta: 0:12:23 lr: 1.968133100013787e-05 loss: 0.0329 (0.0451) time: 2.8814 data: 0.0076 max mem: 33370 +Epoch: [25] [1070/1319] eta: 0:11:55 lr: 1.967187059050284e-05 loss: 0.0374 (0.0451) time: 2.8624 data: 0.0080 max mem: 33370 +Epoch: [25] [1080/1319] eta: 0:11:26 lr: 1.9662409675328494e-05 loss: 0.0375 (0.0451) time: 2.8307 data: 0.0081 max mem: 33370 +Epoch: [25] [1090/1319] eta: 0:10:57 lr: 1.9652948254317503e-05 loss: 0.0381 (0.0452) time: 2.8485 data: 0.0077 max mem: 33370 +Epoch: [25] [1100/1319] eta: 0:10:28 lr: 1.9643486327172213e-05 loss: 0.0458 (0.0452) time: 2.8906 data: 0.0072 max mem: 33370 +Epoch: [25] [1110/1319] eta: 0:10:00 lr: 1.9634023893594635e-05 loss: 0.0369 (0.0451) time: 2.8781 data: 0.0075 max mem: 33370 +Epoch: [25] [1120/1319] eta: 0:09:31 lr: 1.9624560953286446e-05 loss: 0.0349 (0.0451) time: 2.8473 data: 0.0075 max mem: 33370 +Epoch: [25] [1130/1319] eta: 0:09:02 lr: 1.961509750594899e-05 loss: 0.0442 (0.0451) time: 2.8908 data: 0.0072 max mem: 33370 +Epoch: [25] [1140/1319] eta: 0:08:34 lr: 1.9605633551283273e-05 loss: 0.0361 (0.0451) time: 2.9053 data: 0.0074 max mem: 33370 +Epoch: [25] [1150/1319] eta: 0:08:05 lr: 1.9596169088989948e-05 loss: 0.0399 (0.0451) time: 2.8733 data: 0.0079 max mem: 33370 +Epoch: [25] [1160/1319] eta: 0:07:36 lr: 1.9586704118769358e-05 loss: 0.0396 (0.0450) time: 2.8729 data: 0.0075 max mem: 33370 +Epoch: [25] [1170/1319] eta: 0:07:07 lr: 1.9577238640321492e-05 loss: 0.0383 (0.0451) time: 2.8259 data: 0.0072 max mem: 33370 +Epoch: [25] [1180/1319] eta: 0:06:39 lr: 1.9567772653346e-05 loss: 0.0360 (0.0451) time: 2.8722 data: 0.0074 max mem: 33370 +Epoch: [25] [1190/1319] eta: 0:06:10 lr: 1.9558306157542204e-05 loss: 0.0358 (0.0451) time: 2.9460 data: 0.0076 max mem: 33370 +Epoch: [25] [1200/1319] eta: 0:05:41 lr: 1.9548839152609067e-05 loss: 0.0365 (0.0451) time: 2.8819 data: 0.0074 max mem: 33370 +Epoch: [25] [1210/1319] eta: 0:05:13 lr: 1.9539371638245233e-05 loss: 0.0374 (0.0451) time: 2.8838 data: 0.0070 max mem: 33370 +Epoch: [25] [1220/1319] eta: 0:04:44 lr: 1.952990361414899e-05 loss: 0.0398 (0.0451) time: 2.9199 data: 0.0073 max mem: 33370 +Epoch: [25] [1230/1319] eta: 0:04:15 lr: 1.9520435080018294e-05 loss: 0.0414 (0.0451) time: 2.9093 data: 0.0072 max mem: 33370 +Epoch: [25] [1240/1319] eta: 0:03:46 lr: 1.9510966035550763e-05 loss: 0.0391 (0.0451) time: 2.8842 data: 0.0069 max mem: 33370 +Epoch: [25] [1250/1319] eta: 0:03:18 lr: 1.9501496480443652e-05 loss: 0.0415 (0.0451) time: 2.8946 data: 0.0073 max mem: 33370 +Epoch: [25] [1260/1319] eta: 0:02:49 lr: 1.9492026414393892e-05 loss: 0.0422 (0.0451) time: 2.8444 data: 0.0075 max mem: 33370 +Epoch: [25] [1270/1319] eta: 0:02:20 lr: 1.9482555837098063e-05 loss: 0.0470 (0.0452) time: 2.8182 data: 0.0075 max mem: 33370 +Epoch: [25] [1280/1319] eta: 0:01:52 lr: 1.9473084748252403e-05 loss: 0.0468 (0.0452) time: 2.8676 data: 0.0072 max mem: 33370 +Epoch: [25] [1290/1319] eta: 0:01:23 lr: 1.9463613147552807e-05 loss: 0.0411 (0.0452) time: 2.8388 data: 0.0071 max mem: 33370 +Epoch: [25] [1300/1319] eta: 0:00:54 lr: 1.9454141034694828e-05 loss: 0.0401 (0.0452) time: 2.8083 data: 0.0074 max mem: 33370 +Epoch: [25] [1310/1319] eta: 0:00:25 lr: 1.9444668409373652e-05 loss: 0.0399 (0.0452) time: 2.8160 data: 0.0076 max mem: 33370 +Epoch: [25] Total time: 1:03:06 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 1:56:53 time: 2.7259 data: 2.3630 max mem: 33370 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 100/2573] eta: 0:04:04 time: 0.0721 data: 0.0012 max mem: 33370 +Test: [ 200/2573] eta: 0:03:26 time: 0.0756 data: 0.0015 max mem: 33370 +Test: [ 300/2573] eta: 0:03:08 time: 0.0761 data: 0.0012 max mem: 33370 +Test: [ 400/2573] eta: 0:02:55 time: 0.0759 data: 0.0012 max mem: 33370 +Test: [ 500/2573] eta: 0:02:44 time: 0.0743 data: 0.0012 max mem: 33370 +Test: [ 600/2573] eta: 0:02:35 time: 0.0747 data: 0.0013 max mem: 33370 +Test: [ 700/2573] eta: 0:02:26 time: 0.0746 data: 0.0012 max mem: 33370 +Test: [ 800/2573] eta: 0:02:18 time: 0.0781 data: 0.0012 max mem: 33370 +Test: [ 900/2573] eta: 0:02:10 time: 0.0748 data: 0.0012 max mem: 33370 +Test: [1000/2573] eta: 0:02:01 time: 0.0747 data: 0.0013 max mem: 33370 +Test: [1100/2573] eta: 0:01:53 time: 0.0749 data: 0.0013 max mem: 33370 +Test: [1200/2573] eta: 0:01:45 time: 0.0749 data: 0.0012 max mem: 33370 +Test: [1300/2573] eta: 0:01:38 time: 0.0749 data: 0.0012 max mem: 33370 +Test: [1400/2573] eta: 0:01:30 time: 0.0734 data: 0.0013 max mem: 33370 +Test: [1500/2573] eta: 0:01:22 time: 0.0749 data: 0.0013 max mem: 33370 +Test: [1600/2573] eta: 0:01:14 time: 0.0782 data: 0.0012 max mem: 33370 +Test: [1700/2573] eta: 0:01:06 time: 0.0733 data: 0.0012 max mem: 33370 +Test: [1800/2573] eta: 0:00:59 time: 0.0765 data: 0.0012 max mem: 33370 +Test: [1900/2573] eta: 0:00:51 time: 0.0732 data: 0.0012 max mem: 33370 +Test: [2000/2573] eta: 0:00:43 time: 0.0751 data: 0.0012 max mem: 33370 +Test: [2100/2573] eta: 0:00:36 time: 0.0767 data: 0.0012 max mem: 33370 +Test: [2200/2573] eta: 0:00:28 time: 0.0768 data: 0.0012 max mem: 33370 +Test: [2300/2573] eta: 0:00:20 time: 0.0766 data: 0.0013 max mem: 33370 +Test: [2400/2573] eta: 0:00:13 time: 0.0717 data: 0.0012 max mem: 33370 +Test: [2500/2573] eta: 0:00:05 time: 0.0748 data: 0.0012 max mem: 33370 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: Total time: 0:03:15 +Final results: +Mean IoU is 63.63 + + precision@0.5 = 71.43 + precision@0.6 = 66.44 + precision@0.7 = 59.82 + precision@0.8 = 48.30 + precision@0.9 = 24.98 + overall IoU = 61.42 + +Average object IoU 63.6313863908993 +Overall IoU 61.416290283203125 +Better epoch: 25 + +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [26] [ 0/1319] eta: 1:31:03 lr: 1.943614260817638e-05 loss: 0.0382 (0.0382) time: 4.1425 data: 1.1323 max mem: 33370 +Epoch: [26] [ 10/1319] eta: 1:06:54 lr: 1.9426669008334188e-05 loss: 0.0387 (0.0488) time: 3.0668 data: 0.1095 max mem: 33370 +Epoch: [26] [ 20/1319] eta: 1:04:13 lr: 1.941719489514293e-05 loss: 0.0379 (0.0429) time: 2.9080 data: 0.0070 max mem: 33370 +Epoch: [26] [ 30/1319] eta: 1:02:58 lr: 1.9407720268296455e-05 loss: 0.0352 (0.0409) time: 2.8574 data: 0.0072 max mem: 33370 +Epoch: [26] [ 40/1319] eta: 1:02:22 lr: 1.9398245127488253e-05 loss: 0.0395 (0.0408) time: 2.8838 data: 0.0074 max mem: 33370 +Epoch: [26] [ 50/1319] eta: 1:01:43 lr: 1.9388769472411493e-05 loss: 0.0397 (0.0421) time: 2.8981 data: 0.0072 max mem: 33370 +Epoch: [26] [ 60/1319] eta: 1:01:12 lr: 1.9379293302758954e-05 loss: 0.0343 (0.0410) time: 2.8991 data: 0.0073 max mem: 33370 +Epoch: [26] [ 70/1319] eta: 1:00:23 lr: 1.936981661822309e-05 loss: 0.0384 (0.0424) time: 2.8579 data: 0.0079 max mem: 33370 +Epoch: [26] [ 80/1319] eta: 0:59:41 lr: 1.9360339418495996e-05 loss: 0.0384 (0.0422) time: 2.8094 data: 0.0080 max mem: 33370 +Epoch: [26] [ 90/1319] eta: 0:59:35 lr: 1.935086170326942e-05 loss: 0.0347 (0.0417) time: 2.9382 data: 0.0074 max mem: 33370 +Epoch: [26] [ 100/1319] eta: 0:59:06 lr: 1.934138347223476e-05 loss: 0.0374 (0.0419) time: 2.9865 data: 0.0074 max mem: 33370 +Epoch: [26] [ 110/1319] eta: 0:58:34 lr: 1.9331904725083057e-05 loss: 0.0382 (0.0418) time: 2.8929 data: 0.0074 max mem: 33370 +Epoch: [26] [ 120/1319] eta: 0:58:01 lr: 1.9322425461504988e-05 loss: 0.0382 (0.0418) time: 2.8758 data: 0.0072 max mem: 33370 +Epoch: [26] [ 130/1319] eta: 0:57:37 lr: 1.931294568119089e-05 loss: 0.0408 (0.0420) time: 2.9139 data: 0.0073 max mem: 33370 +Epoch: [26] [ 140/1319] eta: 0:56:44 lr: 1.930346538383074e-05 loss: 0.0447 (0.0424) time: 2.7909 data: 0.0072 max mem: 33370 +Epoch: [26] [ 150/1319] eta: 0:56:01 lr: 1.9293984569114164e-05 loss: 0.0461 (0.0433) time: 2.6631 data: 0.0068 max mem: 33370 +Epoch: [26] [ 160/1319] eta: 0:55:17 lr: 1.9284503236730435e-05 loss: 0.0405 (0.0432) time: 2.6807 data: 0.0067 max mem: 33370 +Epoch: [26] [ 170/1319] eta: 0:54:36 lr: 1.927502138636845e-05 loss: 0.0405 (0.0436) time: 2.6736 data: 0.0067 max mem: 33370 +Epoch: [26] [ 180/1319] eta: 0:53:54 lr: 1.9265539017716765e-05 loss: 0.0351 (0.0431) time: 2.6577 data: 0.0068 max mem: 33370 +Epoch: [26] [ 190/1319] eta: 0:53:14 lr: 1.9256056130463582e-05 loss: 0.0383 (0.0435) time: 2.6360 data: 0.0069 max mem: 33370 +Epoch: [26] [ 200/1319] eta: 0:52:34 lr: 1.9246572724296735e-05 loss: 0.0375 (0.0430) time: 2.6353 data: 0.0067 max mem: 33370 +Epoch: [26] [ 210/1319] eta: 0:51:56 lr: 1.9237088798903708e-05 loss: 0.0364 (0.0429) time: 2.6305 data: 0.0067 max mem: 33370 +Epoch: [26] [ 220/1319] eta: 0:51:17 lr: 1.922760435397161e-05 loss: 0.0380 (0.0431) time: 2.6097 data: 0.0068 max mem: 33370 +Epoch: [26] [ 230/1319] eta: 0:50:42 lr: 1.9218119389187204e-05 loss: 0.0352 (0.0430) time: 2.6201 data: 0.0066 max mem: 33370 +Epoch: [26] [ 240/1319] eta: 0:50:05 lr: 1.9208633904236885e-05 loss: 0.0352 (0.0428) time: 2.6258 data: 0.0067 max mem: 33370 +Epoch: [26] [ 250/1319] eta: 0:49:30 lr: 1.9199147898806697e-05 loss: 0.0375 (0.0426) time: 2.6103 data: 0.0068 max mem: 33370 +Epoch: [26] [ 260/1319] eta: 0:48:55 lr: 1.9189661372582306e-05 loss: 0.0356 (0.0423) time: 2.6090 data: 0.0067 max mem: 33370 +Epoch: [26] [ 270/1319] eta: 0:48:22 lr: 1.918017432524904e-05 loss: 0.0356 (0.0423) time: 2.6077 data: 0.0067 max mem: 33370 +Epoch: [26] [ 280/1319] eta: 0:47:49 lr: 1.9170686756491828e-05 loss: 0.0431 (0.0424) time: 2.6252 data: 0.0066 max mem: 33370 +Epoch: [26] [ 290/1319] eta: 0:47:17 lr: 1.916119866599526e-05 loss: 0.0439 (0.0425) time: 2.6425 data: 0.0067 max mem: 33370 +Epoch: [26] [ 300/1319] eta: 0:46:46 lr: 1.9151710053443563e-05 loss: 0.0411 (0.0429) time: 2.6501 data: 0.0066 max mem: 33370 +Epoch: [26] [ 310/1319] eta: 0:46:15 lr: 1.9142220918520593e-05 loss: 0.0391 (0.0429) time: 2.6516 data: 0.0066 max mem: 33370 +Epoch: [26] [ 320/1319] eta: 0:45:45 lr: 1.9132731260909836e-05 loss: 0.0444 (0.0434) time: 2.6493 data: 0.0067 max mem: 33370 +Epoch: [26] [ 330/1319] eta: 0:45:13 lr: 1.9123241080294413e-05 loss: 0.0470 (0.0436) time: 2.6326 data: 0.0068 max mem: 33370 +Epoch: [26] [ 340/1319] eta: 0:44:41 lr: 1.9113750376357084e-05 loss: 0.0428 (0.0435) time: 2.6025 data: 0.0069 max mem: 33370 +Epoch: [26] [ 350/1319] eta: 0:44:11 lr: 1.9104259148780233e-05 loss: 0.0356 (0.0433) time: 2.6180 data: 0.0067 max mem: 33370 +Epoch: [26] [ 360/1319] eta: 0:43:42 lr: 1.909476739724589e-05 loss: 0.0350 (0.0432) time: 2.6478 data: 0.0066 max mem: 33370 +Epoch: [26] [ 370/1319] eta: 0:43:11 lr: 1.9085275121435705e-05 loss: 0.0379 (0.0431) time: 2.6185 data: 0.0067 max mem: 33370 +Epoch: [26] [ 380/1319] eta: 0:42:41 lr: 1.907578232103095e-05 loss: 0.0379 (0.0430) time: 2.6038 data: 0.0068 max mem: 33370 +Epoch: [26] [ 390/1319] eta: 0:42:11 lr: 1.906628899571255e-05 loss: 0.0376 (0.0429) time: 2.6179 data: 0.0067 max mem: 33370 +Epoch: [26] [ 400/1319] eta: 0:41:41 lr: 1.9056795145161037e-05 loss: 0.0370 (0.0428) time: 2.6194 data: 0.0066 max mem: 33370 +Epoch: [26] [ 410/1319] eta: 0:41:11 lr: 1.9047300769056588e-05 loss: 0.0330 (0.0426) time: 2.6086 data: 0.0067 max mem: 33370 +Epoch: [26] [ 420/1319] eta: 0:40:43 lr: 1.9037805867078998e-05 loss: 0.0352 (0.0428) time: 2.6296 data: 0.0067 max mem: 33370 +Epoch: [26] [ 430/1319] eta: 0:40:14 lr: 1.9028310438907695e-05 loss: 0.0370 (0.0427) time: 2.6414 data: 0.0067 max mem: 33370 +Epoch: [26] [ 440/1319] eta: 0:39:44 lr: 1.901881448422173e-05 loss: 0.0317 (0.0428) time: 2.6008 data: 0.0066 max mem: 33370 +Epoch: [26] [ 450/1319] eta: 0:39:14 lr: 1.900931800269978e-05 loss: 0.0334 (0.0429) time: 2.5876 data: 0.0067 max mem: 33370 +Epoch: [26] [ 460/1319] eta: 0:38:46 lr: 1.8999820994020145e-05 loss: 0.0414 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data: 0.0068 max mem: 33370 +Epoch: [26] [ 780/1319] eta: 0:24:01 lr: 1.8695636432127905e-05 loss: 0.0362 (0.0424) time: 2.6267 data: 0.0067 max mem: 33370 +Epoch: [26] [ 790/1319] eta: 0:23:34 lr: 1.8686121844283114e-05 loss: 0.0351 (0.0423) time: 2.6486 data: 0.0066 max mem: 33370 +Epoch: [26] [ 800/1319] eta: 0:23:07 lr: 1.8676606718115407e-05 loss: 0.0351 (0.0423) time: 2.6704 data: 0.0068 max mem: 33370 +Epoch: [26] [ 810/1319] eta: 0:22:41 lr: 1.866709105328956e-05 loss: 0.0347 (0.0423) time: 2.6519 data: 0.0068 max mem: 33370 +Epoch: [26] [ 820/1319] eta: 0:22:14 lr: 1.8657574849469954e-05 loss: 0.0347 (0.0422) time: 2.6552 data: 0.0067 max mem: 33370 +Epoch: [26] [ 830/1319] eta: 0:21:47 lr: 1.864805810632056e-05 loss: 0.0353 (0.0422) time: 2.6564 data: 0.0067 max mem: 33370 +Epoch: [26] [ 840/1319] eta: 0:21:20 lr: 1.8638540823504965e-05 loss: 0.0359 (0.0422) time: 2.6065 data: 0.0067 max mem: 33370 +Epoch: [26] [ 850/1319] eta: 0:20:52 lr: 1.8629023000686338e-05 loss: 0.0364 (0.0422) time: 2.5877 data: 0.0069 max mem: 33370 +Epoch: [26] [ 860/1319] eta: 0:20:25 lr: 1.8619504637527467e-05 loss: 0.0369 (0.0422) time: 2.6135 data: 0.0070 max mem: 33370 +Epoch: [26] [ 870/1319] eta: 0:19:59 lr: 1.8609985733690715e-05 loss: 0.0393 (0.0423) time: 2.6243 data: 0.0068 max mem: 33370 +Epoch: [26] [ 880/1319] eta: 0:19:31 lr: 1.860046628883806e-05 loss: 0.0411 (0.0423) time: 2.6150 data: 0.0066 max mem: 33370 +Epoch: [26] [ 890/1319] eta: 0:19:05 lr: 1.859094630263106e-05 loss: 0.0408 (0.0423) time: 2.6185 data: 0.0066 max mem: 33370 +Epoch: [26] [ 900/1319] eta: 0:18:38 lr: 1.8581425774730882e-05 loss: 0.0377 (0.0422) time: 2.6187 data: 0.0068 max mem: 33370 +Epoch: [26] [ 910/1319] eta: 0:18:11 lr: 1.8571904704798292e-05 loss: 0.0371 (0.0422) time: 2.6107 data: 0.0067 max mem: 33370 +Epoch: [26] [ 920/1319] eta: 0:17:44 lr: 1.856238309249363e-05 loss: 0.0369 (0.0422) time: 2.6464 data: 0.0067 max mem: 33370 +Epoch: [26] [ 930/1319] eta: 0:17:17 lr: 1.855286093747684e-05 loss: 0.0369 (0.0422) time: 2.6573 data: 0.0067 max mem: 33370 +Epoch: [26] [ 940/1319] eta: 0:16:51 lr: 1.854333823940747e-05 loss: 0.0405 (0.0421) time: 2.6538 data: 0.0067 max mem: 33370 +Epoch: [26] [ 950/1319] eta: 0:16:24 lr: 1.853381499794464e-05 loss: 0.0370 (0.0421) time: 2.6385 data: 0.0067 max mem: 33370 +Epoch: [26] [ 960/1319] eta: 0:15:57 lr: 1.8524291212747084e-05 loss: 0.0395 (0.0421) time: 2.6130 data: 0.0068 max mem: 33370 +Epoch: [26] [ 970/1319] eta: 0:15:30 lr: 1.85147668834731e-05 loss: 0.0388 (0.0422) time: 2.6210 data: 0.0069 max mem: 33370 +Epoch: [26] [ 980/1319] eta: 0:15:03 lr: 1.8505242009780593e-05 loss: 0.0365 (0.0422) time: 2.6325 data: 0.0066 max mem: 33370 +Epoch: [26] [ 990/1319] eta: 0:14:36 lr: 1.8495716591327057e-05 loss: 0.0377 (0.0422) time: 2.6388 data: 0.0068 max mem: 33370 +Epoch: [26] [1000/1319] eta: 0:14:10 lr: 1.848619062776957e-05 loss: 0.0388 (0.0422) time: 2.6223 data: 0.0070 max mem: 33370 +Epoch: [26] [1010/1319] eta: 0:13:43 lr: 1.8476664118764797e-05 loss: 0.0312 (0.0421) time: 2.6408 data: 0.0067 max mem: 33370 +Epoch: [26] [1020/1319] eta: 0:13:16 lr: 1.8467137063969e-05 loss: 0.0329 (0.0422) time: 2.6569 data: 0.0067 max mem: 33370 +Epoch: [26] [1030/1319] eta: 0:12:50 lr: 1.8457609463038007e-05 loss: 0.0360 (0.0421) time: 2.6402 data: 0.0066 max mem: 33370 +Epoch: [26] [1040/1319] eta: 0:12:23 lr: 1.8448081315627246e-05 loss: 0.0356 (0.0421) time: 2.6391 data: 0.0068 max mem: 33370 +Epoch: [26] [1050/1319] eta: 0:11:56 lr: 1.843855262139173e-05 loss: 0.0344 (0.0420) time: 2.6184 data: 0.0067 max mem: 33370 +Epoch: [26] [1060/1319] eta: 0:11:29 lr: 1.8429023379986053e-05 loss: 0.0394 (0.0421) time: 2.6223 data: 0.0066 max mem: 33370 +Epoch: [26] [1070/1319] eta: 0:11:03 lr: 1.8419493591064395e-05 loss: 0.0447 (0.0421) time: 2.6246 data: 0.0068 max mem: 33370 +Epoch: [26] [1080/1319] eta: 0:10:36 lr: 1.840996325428051e-05 loss: 0.0368 (0.0421) time: 2.6270 data: 0.0068 max mem: 33370 +Epoch: [26] [1090/1319] eta: 0:10:09 lr: 1.840043236928774e-05 loss: 0.0365 (0.0421) time: 2.6456 data: 0.0067 max mem: 33370 +Epoch: [26] [1100/1319] eta: 0:09:43 lr: 1.839090093573901e-05 loss: 0.0382 (0.0421) time: 2.6354 data: 0.0068 max mem: 33370 +Epoch: [26] [1110/1319] eta: 0:09:16 lr: 1.838136895328682e-05 loss: 0.0385 (0.0421) time: 2.6192 data: 0.0069 max mem: 33370 +Epoch: [26] [1120/1319] eta: 0:08:49 lr: 1.8371836421583257e-05 loss: 0.0372 (0.0421) time: 2.6357 data: 0.0068 max mem: 33370 +Epoch: [26] [1130/1319] eta: 0:08:23 lr: 1.836230334027998e-05 loss: 0.0363 (0.0421) time: 2.6657 data: 0.0067 max mem: 33370 +Epoch: [26] [1140/1319] eta: 0:07:56 lr: 1.8352769709028224e-05 loss: 0.0439 (0.0422) time: 2.6279 data: 0.0066 max mem: 33370 +Epoch: [26] [1150/1319] eta: 0:07:29 lr: 1.8343235527478807e-05 loss: 0.0421 (0.0421) time: 2.6098 data: 0.0066 max mem: 33370 +Epoch: [26] [1160/1319] eta: 0:07:03 lr: 1.8333700795282125e-05 loss: 0.0414 (0.0422) time: 2.6508 data: 0.0066 max mem: 33370 +Epoch: [26] [1170/1319] eta: 0:06:36 lr: 1.832416551208814e-05 loss: 0.0421 (0.0422) time: 2.6474 data: 0.0066 max mem: 33370 +Epoch: [26] [1180/1319] eta: 0:06:09 lr: 1.8314629677546413e-05 loss: 0.0397 (0.0421) time: 2.6225 data: 0.0066 max mem: 33370 +Epoch: [26] [1190/1319] eta: 0:05:43 lr: 1.8305093291306038e-05 loss: 0.0397 (0.0422) time: 2.6250 data: 0.0066 max mem: 33370 +Epoch: [26] [1200/1319] eta: 0:05:16 lr: 1.829555635301572e-05 loss: 0.0400 (0.0423) time: 2.6219 data: 0.0066 max mem: 33370 +Epoch: [26] [1210/1319] eta: 0:04:49 lr: 1.8286018862323718e-05 loss: 0.0394 (0.0423) time: 2.6193 data: 0.0068 max mem: 33370 +Epoch: [26] [1220/1319] eta: 0:04:23 lr: 1.8276480818877866e-05 loss: 0.0390 (0.0422) time: 2.6316 data: 0.0067 max mem: 33370 +Epoch: [26] [1230/1319] eta: 0:03:56 lr: 1.8266942222325584e-05 loss: 0.0338 (0.0422) time: 2.6217 data: 0.0065 max mem: 33370 +Epoch: [26] [1240/1319] eta: 0:03:30 lr: 1.8257403072313833e-05 loss: 0.0338 (0.0421) time: 2.6100 data: 0.0066 max mem: 33370 +Epoch: [26] [1250/1319] eta: 0:03:03 lr: 1.8247863368489165e-05 loss: 0.0363 (0.0422) time: 2.6039 data: 0.0065 max mem: 33370 +Epoch: [26] [1260/1319] eta: 0:02:36 lr: 1.8238323110497695e-05 loss: 0.0363 (0.0422) time: 2.6019 data: 0.0065 max mem: 33370 +Epoch: [26] [1270/1319] eta: 0:02:10 lr: 1.822878229798511e-05 loss: 0.0339 (0.0422) time: 2.6343 data: 0.0065 max mem: 33370 +Epoch: [26] [1280/1319] eta: 0:01:43 lr: 1.821924093059666e-05 loss: 0.0336 (0.0421) time: 2.6622 data: 0.0068 max mem: 33370 +Epoch: [26] [1290/1319] eta: 0:01:17 lr: 1.8209699007977167e-05 loss: 0.0318 (0.0421) time: 2.6398 data: 0.0070 max mem: 33370 +Epoch: [26] [1300/1319] eta: 0:00:50 lr: 1.8200156529771002e-05 loss: 0.0325 (0.0420) time: 2.6363 data: 0.0067 max mem: 33370 +Epoch: [26] [1310/1319] eta: 0:00:23 lr: 1.819061349562212e-05 loss: 0.0393 (0.0421) time: 2.6471 data: 0.0065 max mem: 33370 +Epoch: [26] Total time: 0:58:25 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 2:05:18 time: 2.9220 data: 2.8420 max mem: 33370 +Test: [ 100/2573] eta: 0:04:07 time: 0.0717 data: 0.0011 max mem: 33370 +Test: [ 200/2573] eta: 0:03:26 time: 0.0734 data: 0.0011 max mem: 33370 +Test: [ 300/2573] eta: 0:03:06 time: 0.0752 data: 0.0011 max mem: 33370 +Test: [ 400/2573] eta: 0:02:53 time: 0.0749 data: 0.0010 max mem: 33370 +Test: [ 500/2573] eta: 0:02:43 time: 0.0736 data: 0.0011 max mem: 33370 +Test: [ 600/2573] eta: 0:02:33 time: 0.0736 data: 0.0011 max mem: 33370 +Test: [ 700/2573] eta: 0:02:25 time: 0.0737 data: 0.0011 max mem: 33370 +Test: [ 800/2573] eta: 0:02:17 time: 0.0771 data: 0.0011 max mem: 33370 +Test: [ 900/2573] eta: 0:02:08 time: 0.0738 data: 0.0011 max mem: 33370 +Test: [1000/2573] eta: 0:02:00 time: 0.0739 data: 0.0011 max mem: 33370 +Test: [1100/2573] eta: 0:01:52 time: 0.0739 data: 0.0011 max mem: 33370 +Test: [1200/2573] eta: 0:01:44 time: 0.0739 data: 0.0011 max mem: 33370 +Test: [1300/2573] eta: 0:01:36 time: 0.0738 data: 0.0011 max mem: 33370 +Test: [1400/2573] eta: 0:01:29 time: 0.0722 data: 0.0011 max mem: 33370 +Test: [1500/2573] eta: 0:01:21 time: 0.0739 data: 0.0011 max mem: 33370 +Test: [1600/2573] eta: 0:01:13 time: 0.0772 data: 0.0011 max mem: 33370 +Test: [1700/2573] eta: 0:01:06 time: 0.0722 data: 0.0011 max mem: 33370 +Test: [1800/2573] eta: 0:00:58 time: 0.0757 data: 0.0011 max mem: 33370 +Test: [1900/2573] eta: 0:00:50 time: 0.0722 data: 0.0011 max mem: 33370 +Test: [2000/2573] eta: 0:00:43 time: 0.0740 data: 0.0011 max mem: 33370 +Test: [2100/2573] eta: 0:00:35 time: 0.0755 data: 0.0011 max mem: 33370 +Test: [2200/2573] eta: 0:00:28 time: 0.0754 data: 0.0011 max mem: 33370 +Test: [2300/2573] eta: 0:00:20 time: 0.0756 data: 0.0011 max mem: 33370 +Test: [2400/2573] eta: 0:00:12 time: 0.0705 data: 0.0011 max mem: 33370 +Test: [2500/2573] eta: 0:00:05 time: 0.0736 data: 0.0010 max mem: 33370 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: Total time: 0:03:13 +Final results: +Mean IoU is 63.77 + + precision@0.5 = 71.81 + precision@0.6 = 66.44 + precision@0.7 = 59.31 + precision@0.8 = 48.45 + precision@0.9 = 24.43 + overall IoU = 61.53 + +Average object IoU 63.770830258543796 +Overall IoU 61.528297424316406 +Better epoch: 26 + +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [27] [ 0/1319] eta: 1:24:50 lr: 1.818202428926248e-05 loss: 0.0331 (0.0331) time: 3.8597 data: 1.1295 max mem: 33370 +Epoch: [27] [ 10/1319] eta: 1:00:35 lr: 1.817248019783995e-05 loss: 0.0366 (0.0423) time: 2.7775 data: 0.1080 max mem: 33370 +Epoch: [27] [ 20/1319] eta: 0:58:24 lr: 1.8162935549439682e-05 loss: 0.0366 (0.0424) time: 2.6401 data: 0.0062 max mem: 33370 +Epoch: [27] [ 30/1319] eta: 0:57:08 lr: 1.8153390343703928e-05 loss: 0.0407 (0.0425) time: 2.5950 data: 0.0065 max mem: 33370 +Epoch: [27] [ 40/1319] eta: 0:56:34 lr: 1.8143844580274487e-05 loss: 0.0406 (0.0409) time: 2.6084 data: 0.0066 max mem: 33370 +Epoch: [27] [ 50/1319] eta: 0:56:03 lr: 1.813429825879272e-05 loss: 0.0409 (0.0423) time: 2.6357 data: 0.0068 max mem: 33370 +Epoch: [27] [ 60/1319] eta: 0:55:37 lr: 1.8124751378899558e-05 loss: 0.0434 (0.0422) time: 2.6427 data: 0.0067 max mem: 33370 +Epoch: [27] [ 70/1319] eta: 0:55:10 lr: 1.811520394023548e-05 loss: 0.0377 (0.0436) time: 2.6497 data: 0.0065 max mem: 33370 +Epoch: [27] [ 80/1319] eta: 0:54:41 lr: 1.8105655942440525e-05 loss: 0.0368 (0.0430) time: 2.6410 data: 0.0065 max mem: 33370 +Epoch: [27] [ 90/1319] eta: 0:54:11 lr: 1.8096107385154294e-05 loss: 0.0359 (0.0427) time: 2.6290 data: 0.0067 max mem: 33370 +Epoch: [27] [ 100/1319] eta: 0:53:47 lr: 1.8086558268015952e-05 loss: 0.0366 (0.0425) time: 2.6475 data: 0.0067 max mem: 33370 +Epoch: [27] [ 110/1319] eta: 0:53:20 lr: 1.807700859066419e-05 loss: 0.0349 (0.0421) time: 2.6565 data: 0.0066 max mem: 33370 +Epoch: [27] [ 120/1319] eta: 0:52:50 lr: 1.8067458352737284e-05 loss: 0.0346 (0.0415) time: 2.6260 data: 0.0066 max mem: 33370 +Epoch: [27] [ 130/1319] eta: 0:52:22 lr: 1.8057907553873043e-05 loss: 0.0363 (0.0412) time: 2.6197 data: 0.0066 max mem: 33370 +Epoch: [27] [ 140/1319] eta: 0:51:57 lr: 1.8048356193708847e-05 loss: 0.0370 (0.0414) time: 2.6419 data: 0.0065 max mem: 33370 +Epoch: [27] [ 150/1319] eta: 0:51:28 lr: 1.803880427188162e-05 loss: 0.0361 (0.0412) time: 2.6349 data: 0.0065 max mem: 33370 +Epoch: [27] [ 160/1319] eta: 0:51:01 lr: 1.802925178802783e-05 loss: 0.0401 (0.0413) time: 2.6258 data: 0.0067 max mem: 33370 +Epoch: [27] [ 170/1319] eta: 0:50:32 lr: 1.8019698741783504e-05 loss: 0.0370 (0.0408) time: 2.6202 data: 0.0066 max mem: 33370 +Epoch: [27] [ 180/1319] eta: 0:50:04 lr: 1.8010145132784217e-05 loss: 0.0304 (0.0410) time: 2.6031 data: 0.0064 max mem: 33370 +Epoch: [27] [ 190/1319] eta: 0:49:40 lr: 1.8000590960665095e-05 loss: 0.0316 (0.0417) time: 2.6435 data: 0.0065 max mem: 33370 +Epoch: [27] [ 200/1319] eta: 0:49:14 lr: 1.7991036225060814e-05 loss: 0.0359 (0.0415) time: 2.6667 data: 0.0066 max mem: 33370 +Epoch: [27] [ 210/1319] eta: 0:48:46 lr: 1.7981480925605583e-05 loss: 0.0386 (0.0416) time: 2.6290 data: 0.0064 max mem: 33370 +Epoch: [27] [ 220/1319] eta: 0:48:21 lr: 1.7971925061933174e-05 loss: 0.0396 (0.0416) time: 2.6412 data: 0.0065 max mem: 33370 +Epoch: [27] [ 230/1319] eta: 0:47:54 lr: 1.7962368633676893e-05 loss: 0.0321 (0.0413) time: 2.6472 data: 0.0066 max mem: 33370 +Epoch: [27] [ 240/1319] eta: 0:47:28 lr: 1.7952811640469606e-05 loss: 0.0342 (0.0411) time: 2.6304 data: 0.0065 max mem: 33370 +Epoch: [27] [ 250/1319] eta: 0:47:01 lr: 1.7943254081943704e-05 loss: 0.0364 (0.0412) time: 2.6390 data: 0.0065 max mem: 33370 +Epoch: [27] [ 260/1319] eta: 0:46:35 lr: 1.7933695957731138e-05 loss: 0.0378 (0.0413) time: 2.6355 data: 0.0064 max mem: 33370 +Epoch: [27] [ 270/1319] eta: 0:46:07 lr: 1.7924137267463387e-05 loss: 0.0378 (0.0410) time: 2.6227 data: 0.0065 max mem: 33370 +Epoch: [27] [ 280/1319] eta: 0:45:40 lr: 1.7914578010771477e-05 loss: 0.0364 (0.0410) time: 2.6209 data: 0.0065 max mem: 33370 +Epoch: [27] [ 290/1319] eta: 0:45:13 lr: 1.7905018187285976e-05 loss: 0.0375 (0.0410) time: 2.6189 data: 0.0065 max mem: 33370 +Epoch: [27] [ 300/1319] eta: 0:44:46 lr: 1.7895457796636998e-05 loss: 0.0433 (0.0411) time: 2.6141 data: 0.0066 max mem: 33370 +Epoch: [27] [ 310/1319] eta: 0:44:20 lr: 1.7885896838454187e-05 loss: 0.0388 (0.0412) time: 2.6259 data: 0.0064 max mem: 33370 +Epoch: [27] [ 320/1319] eta: 0:43:52 lr: 1.787633531236672e-05 loss: 0.0362 (0.0410) time: 2.6201 data: 0.0063 max mem: 33370 +Epoch: [27] [ 330/1319] eta: 0:43:26 lr: 1.786677321800332e-05 loss: 0.0345 (0.0409) time: 2.6298 data: 0.0065 max mem: 33370 +Epoch: [27] [ 340/1319] eta: 0:43:01 lr: 1.7857210554992246e-05 loss: 0.0364 (0.0409) time: 2.6616 data: 0.0066 max mem: 33370 +Epoch: [27] [ 350/1319] eta: 0:42:34 lr: 1.7847647322961293e-05 loss: 0.0369 (0.0407) time: 2.6466 data: 0.0065 max mem: 33370 +Epoch: [27] [ 360/1319] eta: 0:42:08 lr: 1.783808352153779e-05 loss: 0.0346 (0.0409) time: 2.6303 data: 0.0067 max mem: 33370 +Epoch: [27] [ 370/1319] eta: 0:41:40 lr: 1.782851915034859e-05 loss: 0.0374 (0.0409) time: 2.6151 data: 0.0067 max mem: 33370 +Epoch: [27] [ 380/1319] eta: 0:41:14 lr: 1.78189542090201e-05 loss: 0.0338 (0.0407) time: 2.6138 data: 0.0065 max mem: 33370 +Epoch: [27] [ 390/1319] eta: 0:40:48 lr: 1.780938869717823e-05 loss: 0.0386 (0.0408) time: 2.6392 data: 0.0066 max mem: 33370 +Epoch: [27] [ 400/1319] eta: 0:40:22 lr: 1.779982261444845e-05 loss: 0.0406 (0.0407) time: 2.6447 data: 0.0067 max mem: 33370 +Epoch: [27] [ 410/1319] eta: 0:39:56 lr: 1.7790255960455746e-05 loss: 0.0356 (0.0409) time: 2.6421 data: 0.0066 max mem: 33370 +Epoch: [27] [ 420/1319] eta: 0:39:30 lr: 1.7780688734824637e-05 loss: 0.0378 (0.0408) time: 2.6482 data: 0.0066 max mem: 33370 +Epoch: [27] [ 430/1319] eta: 0:39:03 lr: 1.777112093717916e-05 loss: 0.0378 (0.0409) time: 2.6368 data: 0.0064 max mem: 33370 +Epoch: [27] [ 440/1319] eta: 0:38:37 lr: 1.7761552567142895e-05 loss: 0.0358 (0.0409) time: 2.6310 data: 0.0063 max mem: 33370 +Epoch: [27] [ 450/1319] eta: 0:38:11 lr: 1.7751983624338938e-05 loss: 0.0374 (0.0409) time: 2.6480 data: 0.0062 max mem: 33370 +Epoch: [27] [ 460/1319] eta: 0:37:43 lr: 1.7742414108389917e-05 loss: 0.0370 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1.7291993287130824e-05 loss: 0.0353 (0.0410) time: 2.6367 data: 0.0063 max mem: 33370 +Epoch: [27] [ 940/1319] eta: 0:16:37 lr: 1.728239580690995e-05 loss: 0.0327 (0.0409) time: 2.6514 data: 0.0063 max mem: 33370 +Epoch: [27] [ 950/1319] eta: 0:16:10 lr: 1.727279773445306e-05 loss: 0.0355 (0.0409) time: 2.6317 data: 0.0064 max mem: 33370 +Epoch: [27] [ 960/1319] eta: 0:15:44 lr: 1.7263199069357895e-05 loss: 0.0350 (0.0409) time: 2.6247 data: 0.0065 max mem: 33370 +Epoch: [27] [ 970/1319] eta: 0:15:18 lr: 1.725359981122169e-05 loss: 0.0338 (0.0408) time: 2.6251 data: 0.0065 max mem: 33370 +Epoch: [27] [ 980/1319] eta: 0:14:52 lr: 1.7243999959641156e-05 loss: 0.0376 (0.0409) time: 2.6368 data: 0.0064 max mem: 33370 +Epoch: [27] [ 990/1319] eta: 0:14:25 lr: 1.7234399514212475e-05 loss: 0.0359 (0.0408) time: 2.6473 data: 0.0063 max mem: 33370 +Epoch: [27] [1000/1319] eta: 0:13:59 lr: 1.7224798474531302e-05 loss: 0.0349 (0.0408) time: 2.6300 data: 0.0062 max mem: 33370 +Epoch: [27] 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mem: 33370 +Epoch: [27] [1090/1319] eta: 0:10:02 lr: 1.7138362309061432e-05 loss: 0.0367 (0.0408) time: 2.6231 data: 0.0063 max mem: 33370 +Epoch: [27] [1100/1319] eta: 0:09:36 lr: 1.7128755304500424e-05 loss: 0.0362 (0.0408) time: 2.6216 data: 0.0062 max mem: 33370 +Epoch: [27] [1110/1319] eta: 0:09:09 lr: 1.7119147701204254e-05 loss: 0.0394 (0.0409) time: 2.6412 data: 0.0061 max mem: 33370 +Epoch: [27] [1120/1319] eta: 0:08:43 lr: 1.710953949876218e-05 loss: 0.0394 (0.0409) time: 2.6606 data: 0.0061 max mem: 33370 +Epoch: [27] [1130/1319] eta: 0:08:17 lr: 1.709993069676296e-05 loss: 0.0361 (0.0409) time: 2.6513 data: 0.0063 max mem: 33370 +Epoch: [27] [1140/1319] eta: 0:07:51 lr: 1.7090321294794796e-05 loss: 0.0397 (0.0409) time: 2.6272 data: 0.0065 max mem: 33370 +Epoch: [27] [1150/1319] eta: 0:07:24 lr: 1.7080711292445346e-05 loss: 0.0395 (0.0410) time: 2.6081 data: 0.0066 max mem: 33370 +Epoch: [27] [1160/1319] eta: 0:06:58 lr: 1.7071100689301735e-05 loss: 0.0356 (0.0410) time: 2.6459 data: 0.0065 max mem: 33370 +Epoch: [27] [1170/1319] eta: 0:06:32 lr: 1.706148948495055e-05 loss: 0.0462 (0.0411) time: 2.6475 data: 0.0064 max mem: 33370 +Epoch: [27] [1180/1319] eta: 0:06:05 lr: 1.705187767897781e-05 loss: 0.0393 (0.0411) time: 2.6076 data: 0.0063 max mem: 33370 +Epoch: [27] [1190/1319] eta: 0:05:39 lr: 1.704226527096902e-05 loss: 0.0364 (0.0411) time: 2.6233 data: 0.0065 max mem: 33370 +Epoch: [27] [1200/1319] eta: 0:05:13 lr: 1.703265226050912e-05 loss: 0.0333 (0.0411) time: 2.6324 data: 0.0065 max mem: 33370 +Epoch: [27] [1210/1319] eta: 0:04:46 lr: 1.702303864718251e-05 loss: 0.0344 (0.0411) time: 2.6273 data: 0.0065 max mem: 33370 +Epoch: [27] [1220/1319] eta: 0:04:20 lr: 1.7013424430573045e-05 loss: 0.0412 (0.0411) time: 2.6376 data: 0.0066 max mem: 33370 +Epoch: [27] [1230/1319] eta: 0:03:54 lr: 1.7003809610264022e-05 loss: 0.0412 (0.0412) time: 2.6414 data: 0.0066 max mem: 33370 +Epoch: [27] [1240/1319] eta: 0:03:27 lr: 1.6994194185838196e-05 loss: 0.0357 (0.0411) time: 2.6474 data: 0.0065 max mem: 33370 +Epoch: [27] [1250/1319] eta: 0:03:01 lr: 1.698457815687777e-05 loss: 0.0356 (0.0411) time: 2.6418 data: 0.0066 max mem: 33370 +Epoch: [27] [1260/1319] eta: 0:02:35 lr: 1.6974961522964392e-05 loss: 0.0356 (0.0411) time: 2.6086 data: 0.0066 max mem: 33370 +Epoch: [27] [1270/1319] eta: 0:02:08 lr: 1.6965344283679166e-05 loss: 0.0354 (0.0412) time: 2.6061 data: 0.0063 max mem: 33370 +Epoch: [27] [1280/1319] eta: 0:01:42 lr: 1.6955726438602627e-05 loss: 0.0336 (0.0412) time: 2.6401 data: 0.0063 max mem: 33370 +Epoch: [27] [1290/1319] eta: 0:01:16 lr: 1.694610798731476e-05 loss: 0.0336 (0.0411) time: 2.6261 data: 0.0064 max mem: 33370 +Epoch: [27] [1300/1319] eta: 0:00:49 lr: 1.6936488929395006e-05 loss: 0.0324 (0.0411) time: 2.6337 data: 0.0064 max mem: 33370 +Epoch: [27] [1310/1319] eta: 0:00:23 lr: 1.6926869264422233e-05 loss: 0.0365 (0.0411) time: 2.6429 data: 0.0064 max mem: 33370 +Epoch: [27] Total time: 0:57:51 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 1:53:33 time: 2.6480 data: 2.4553 max mem: 33370 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 100/2573] eta: 0:04:02 time: 0.0716 data: 0.0011 max mem: 33370 +Test: [ 200/2573] eta: 0:03:24 time: 0.0733 data: 0.0011 max mem: 33370 +Test: [ 300/2573] eta: 0:03:05 time: 0.0752 data: 0.0011 max mem: 33370 +Test: [ 400/2573] eta: 0:02:52 time: 0.0752 data: 0.0011 max mem: 33370 +Test: [ 500/2573] eta: 0:02:42 time: 0.0737 data: 0.0011 max mem: 33370 +Test: [ 600/2573] eta: 0:02:33 time: 0.0738 data: 0.0011 max mem: 33370 +Test: [ 700/2573] eta: 0:02:25 time: 0.0737 data: 0.0011 max mem: 33370 +Test: [ 800/2573] eta: 0:02:16 time: 0.0771 data: 0.0011 max mem: 33370 +Test: [ 900/2573] eta: 0:02:08 time: 0.0737 data: 0.0011 max mem: 33370 +Test: [1000/2573] eta: 0:02:00 time: 0.0738 data: 0.0011 max mem: 33370 +Test: [1100/2573] eta: 0:01:52 time: 0.0738 data: 0.0011 max mem: 33370 +Test: [1200/2573] eta: 0:01:44 time: 0.0736 data: 0.0010 max mem: 33370 +Test: [1300/2573] eta: 0:01:36 time: 0.0737 data: 0.0011 max mem: 33370 +Test: [1400/2573] eta: 0:01:28 time: 0.0721 data: 0.0011 max mem: 33370 +Test: [1500/2573] eta: 0:01:21 time: 0.0737 data: 0.0011 max mem: 33370 +Test: [1600/2573] eta: 0:01:13 time: 0.0770 data: 0.0011 max mem: 33370 +Test: [1700/2573] eta: 0:01:05 time: 0.0720 data: 0.0011 max mem: 33370 +Test: [1800/2573] eta: 0:00:58 time: 0.0754 data: 0.0011 max mem: 33370 +Test: [1900/2573] eta: 0:00:50 time: 0.0721 data: 0.0011 max mem: 33370 +Test: [2000/2573] eta: 0:00:43 time: 0.0737 data: 0.0011 max mem: 33370 +Test: [2100/2573] eta: 0:00:35 time: 0.0753 data: 0.0011 max mem: 33370 +Test: [2200/2573] eta: 0:00:27 time: 0.0754 data: 0.0010 max mem: 33370 +Test: [2300/2573] eta: 0:00:20 time: 0.0754 data: 0.0011 max mem: 33370 +Test: [2400/2573] eta: 0:00:12 time: 0.0704 data: 0.0011 max mem: 33370 +Test: [2500/2573] eta: 0:00:05 time: 0.0737 data: 0.0011 max mem: 33370 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: Total time: 0:03:12 +Final results: +Mean IoU is 64.02 + + precision@0.5 = 72.18 + precision@0.6 = 67.14 + precision@0.7 = 59.84 + precision@0.8 = 48.45 + precision@0.9 = 24.67 + overall IoU = 61.84 + +Average object IoU 64.0239742115972 +Overall IoU 61.83786392211914 +Better epoch: 27 + +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [28] [ 0/1319] eta: 1:25:13 lr: 1.69182110465679e-05 loss: 0.0442 (0.0442) time: 3.8771 data: 1.1180 max mem: 33370 +Epoch: [28] [ 10/1319] eta: 1:00:11 lr: 1.690859022703219e-05 loss: 0.0334 (0.0363) time: 2.7592 data: 0.1077 max mem: 33370 +Epoch: [28] [ 20/1319] eta: 0:58:27 lr: 1.6898968799219036e-05 loss: 0.0343 (0.0371) time: 2.6417 data: 0.0066 max mem: 33370 +Epoch: [28] [ 30/1319] eta: 0:57:26 lr: 1.6889346762705132e-05 loss: 0.0369 (0.0386) time: 2.6265 data: 0.0065 max mem: 33370 +Epoch: [28] [ 40/1319] eta: 0:57:02 lr: 1.6879724117066593e-05 loss: 0.0383 (0.0388) time: 2.6507 data: 0.0065 max mem: 33370 +Epoch: [28] [ 50/1319] eta: 0:56:36 lr: 1.6870100861878995e-05 loss: 0.0407 (0.0399) time: 2.6810 data: 0.0065 max mem: 33370 +Epoch: [28] [ 60/1319] eta: 0:56:12 lr: 1.6860476996717327e-05 loss: 0.0417 (0.0398) time: 2.6829 data: 0.0065 max mem: 33370 +Epoch: [28] [ 70/1319] eta: 0:55:35 lr: 1.6850852521156025e-05 loss: 0.0417 (0.0417) time: 2.6550 data: 0.0066 max mem: 33370 +Epoch: [28] [ 80/1319] eta: 0:55:05 lr: 1.684122743476896e-05 loss: 0.0358 (0.0411) time: 2.6351 data: 0.0066 max mem: 33370 +Epoch: [28] [ 90/1319] eta: 0:54:34 lr: 1.6831601737129412e-05 loss: 0.0376 (0.0413) time: 2.6437 data: 0.0065 max mem: 33370 +Epoch: [28] [ 100/1319] eta: 0:53:59 lr: 1.6821975427810122e-05 loss: 0.0376 (0.0406) time: 2.6171 data: 0.0066 max mem: 33370 +Epoch: [28] [ 110/1319] eta: 0:53:26 lr: 1.6812348506383245e-05 loss: 0.0302 (0.0403) time: 2.5951 data: 0.0067 max mem: 33370 +Epoch: [28] [ 120/1319] eta: 0:52:58 lr: 1.680272097242036e-05 loss: 0.0329 (0.0399) time: 2.6154 data: 0.0067 max mem: 33370 +Epoch: [28] [ 130/1319] eta: 0:52:30 lr: 1.6793092825492484e-05 loss: 0.0355 (0.0401) time: 2.6357 data: 0.0066 max mem: 33370 +Epoch: [28] [ 140/1319] eta: 0:51:59 lr: 1.6783464065170062e-05 loss: 0.0370 (0.0398) time: 2.6173 data: 0.0066 max mem: 33370 +Epoch: [28] [ 150/1319] eta: 0:51:31 lr: 1.6773834691022944e-05 loss: 0.0371 (0.0398) time: 2.6118 data: 0.0064 max mem: 33370 +Epoch: [28] [ 160/1319] eta: 0:51:04 lr: 1.6764204702620422e-05 loss: 0.0384 (0.0400) time: 2.6293 data: 0.0067 max mem: 33370 +Epoch: [28] [ 170/1319] eta: 0:50:39 lr: 1.6754574099531206e-05 loss: 0.0343 (0.0398) time: 2.6497 data: 0.0067 max mem: 33370 +Epoch: [28] [ 180/1319] eta: 0:50:09 lr: 1.6744942881323427e-05 loss: 0.0315 (0.0395) time: 2.6272 data: 0.0065 max mem: 33370 +Epoch: [28] [ 190/1319] eta: 0:49:41 lr: 1.6735311047564646e-05 loss: 0.0352 (0.0397) time: 2.6065 data: 0.0064 max mem: 33370 +Epoch: [28] [ 200/1319] eta: 0:49:14 lr: 1.6725678597821815e-05 loss: 0.0355 (0.0394) time: 2.6250 data: 0.0065 max mem: 33370 +Epoch: [28] [ 210/1319] eta: 0:48:47 lr: 1.6716045531661334e-05 loss: 0.0333 (0.0395) time: 2.6304 data: 0.0067 max mem: 33370 +Epoch: [28] [ 220/1319] eta: 0:48:24 lr: 1.6706411848649008e-05 loss: 0.0367 (0.0398) time: 2.6645 data: 0.0066 max mem: 33370 +Epoch: [28] [ 230/1319] eta: 0:47:57 lr: 1.6696777548350058e-05 loss: 0.0365 (0.0396) time: 2.6679 data: 0.0064 max mem: 33370 +Epoch: [28] [ 240/1319] eta: 0:47:31 lr: 1.668714263032912e-05 loss: 0.0355 (0.0401) time: 2.6423 data: 0.0065 max mem: 33370 +Epoch: [28] [ 250/1319] eta: 0:47:04 lr: 1.6677507094150246e-05 loss: 0.0372 (0.0406) time: 2.6332 data: 0.0064 max mem: 33370 +Epoch: [28] [ 260/1319] eta: 0:46:37 lr: 1.6667870939376894e-05 loss: 0.0393 (0.0410) time: 2.6293 data: 0.0063 max mem: 33370 +Epoch: [28] [ 270/1319] eta: 0:46:09 lr: 1.6658234165571935e-05 loss: 0.0412 (0.0411) time: 2.6153 data: 0.0064 max mem: 33370 +Epoch: [28] [ 280/1319] eta: 0:45:41 lr: 1.6648596772297652e-05 loss: 0.0352 (0.0409) time: 2.5951 data: 0.0064 max mem: 33370 +Epoch: [28] [ 290/1319] eta: 0:45:16 lr: 1.6638958759115745e-05 loss: 0.0338 (0.0408) time: 2.6411 data: 0.0066 max mem: 33370 +Epoch: [28] [ 300/1319] eta: 0:44:49 lr: 1.6629320125587307e-05 loss: 0.0353 (0.0407) time: 2.6585 data: 0.0064 max mem: 33370 +Epoch: [28] [ 310/1319] eta: 0:44:23 lr: 1.6619680871272843e-05 loss: 0.0374 (0.0408) time: 2.6372 data: 0.0066 max mem: 33370 +Epoch: [28] [ 320/1319] eta: 0:43:57 lr: 1.6610040995732262e-05 loss: 0.0415 (0.0409) time: 2.6461 data: 0.0066 max mem: 33370 +Epoch: [28] [ 330/1319] eta: 0:43:30 lr: 1.6600400498524878e-05 loss: 0.0415 (0.0411) time: 2.6396 data: 0.0063 max mem: 33370 +Epoch: [28] [ 340/1319] eta: 0:43:04 lr: 1.659075937920942e-05 loss: 0.0390 (0.0411) time: 2.6475 data: 0.0065 max mem: 33370 +Epoch: [28] [ 350/1319] eta: 0:42:38 lr: 1.6581117637343994e-05 loss: 0.0348 (0.0409) time: 2.6515 data: 0.0065 max mem: 33370 +Epoch: [28] [ 360/1319] eta: 0:42:11 lr: 1.657147527248612e-05 loss: 0.0334 (0.0408) time: 2.6372 data: 0.0064 max mem: 33370 +Epoch: [28] [ 370/1319] eta: 0:41:45 lr: 1.6561832284192722e-05 loss: 0.0358 (0.0409) time: 2.6275 data: 0.0066 max mem: 33370 +Epoch: [28] [ 380/1319] eta: 0:41:18 lr: 1.6552188672020112e-05 loss: 0.0327 (0.0407) time: 2.6318 data: 0.0065 max mem: 33370 +Epoch: [28] [ 390/1319] eta: 0:40:52 lr: 1.654254443552401e-05 loss: 0.0326 (0.0407) time: 2.6384 data: 0.0064 max mem: 33370 +Epoch: [28] [ 400/1319] eta: 0:40:25 lr: 1.6532899574259518e-05 loss: 0.0329 (0.0405) time: 2.6398 data: 0.0065 max mem: 33370 +Epoch: [28] [ 410/1319] eta: 0:39:58 lr: 1.6523254087781154e-05 loss: 0.0334 (0.0406) time: 2.6251 data: 0.0065 max mem: 33370 +Epoch: [28] [ 420/1319] eta: 0:39:32 lr: 1.651360797564279e-05 loss: 0.0415 (0.0408) time: 2.6218 data: 0.0067 max mem: 33370 +Epoch: [28] [ 430/1319] eta: 0:39:06 lr: 1.6503961237397734e-05 loss: 0.0373 (0.0406) time: 2.6499 data: 0.0066 max mem: 33370 +Epoch: [28] [ 440/1319] eta: 0:38:40 lr: 1.6494313872598656e-05 loss: 0.0320 (0.0404) time: 2.6597 data: 0.0064 max mem: 33370 +Epoch: [28] [ 450/1319] eta: 0:38:13 lr: 1.6484665880797628e-05 loss: 0.0366 (0.0405) time: 2.6444 data: 0.0066 max mem: 33370 +Epoch: [28] [ 460/1319] eta: 0:37:47 lr: 1.6475017261546112e-05 loss: 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data: 0.0064 max mem: 33370 +Epoch: [28] [ 780/1319] eta: 0:23:40 lr: 1.6165927435052318e-05 loss: 0.0385 (0.0403) time: 2.6342 data: 0.0064 max mem: 33370 +Epoch: [28] [ 790/1319] eta: 0:23:14 lr: 1.6156257854223998e-05 loss: 0.0385 (0.0404) time: 2.6244 data: 0.0064 max mem: 33370 +Epoch: [28] [ 800/1319] eta: 0:22:47 lr: 1.614658763032172e-05 loss: 0.0341 (0.0404) time: 2.6048 data: 0.0063 max mem: 33370 +Epoch: [28] [ 810/1319] eta: 0:22:22 lr: 1.6136916762874727e-05 loss: 0.0360 (0.0404) time: 2.6727 data: 0.0063 max mem: 33370 +Epoch: [28] [ 820/1319] eta: 0:21:55 lr: 1.6127245251411607e-05 loss: 0.0391 (0.0404) time: 2.6907 data: 0.0062 max mem: 33370 +Epoch: [28] [ 830/1319] eta: 0:21:29 lr: 1.6117573095460284e-05 loss: 0.0391 (0.0405) time: 2.6427 data: 0.0064 max mem: 33370 +Epoch: [28] [ 840/1319] eta: 0:21:02 lr: 1.610790029454803e-05 loss: 0.0396 (0.0405) time: 2.6293 data: 0.0065 max mem: 33370 +Epoch: [28] [ 850/1319] eta: 0:20:36 lr: 1.609822684820143e-05 loss: 0.0388 (0.0407) time: 2.6186 data: 0.0064 max mem: 33370 +Epoch: [28] [ 860/1319] eta: 0:20:09 lr: 1.608855275594644e-05 loss: 0.0383 (0.0408) time: 2.6173 data: 0.0064 max mem: 33370 +Epoch: [28] [ 870/1319] eta: 0:19:43 lr: 1.6078878017308325e-05 loss: 0.0383 (0.0408) time: 2.6255 data: 0.0064 max mem: 33370 +Epoch: [28] [ 880/1319] eta: 0:19:17 lr: 1.6069202631811695e-05 loss: 0.0357 (0.0407) time: 2.6365 data: 0.0063 max mem: 33370 +Epoch: [28] [ 890/1319] eta: 0:18:50 lr: 1.6059526598980493e-05 loss: 0.0372 (0.0407) time: 2.6251 data: 0.0065 max mem: 33370 +Epoch: [28] [ 900/1319] eta: 0:18:24 lr: 1.6049849918337977e-05 loss: 0.0392 (0.0407) time: 2.6145 data: 0.0066 max mem: 33370 +Epoch: [28] [ 910/1319] eta: 0:17:57 lr: 1.6040172589406754e-05 loss: 0.0392 (0.0408) time: 2.5936 data: 0.0066 max mem: 33370 +Epoch: [28] [ 920/1319] eta: 0:17:31 lr: 1.603049461170875e-05 loss: 0.0392 (0.0408) time: 2.5927 data: 0.0066 max mem: 33370 +Epoch: [28] [ 930/1319] eta: 0:17:04 lr: 1.602081598476522e-05 loss: 0.0366 (0.0408) time: 2.6219 data: 0.0064 max mem: 33370 +Epoch: [28] [ 940/1319] eta: 0:16:38 lr: 1.6011136708096744e-05 loss: 0.0307 (0.0408) time: 2.6253 data: 0.0063 max mem: 33370 +Epoch: [28] [ 950/1319] eta: 0:16:12 lr: 1.6001456781223216e-05 loss: 0.0331 (0.0407) time: 2.6075 data: 0.0066 max mem: 33370 +Epoch: [28] [ 960/1319] eta: 0:15:45 lr: 1.599177620366387e-05 loss: 0.0331 (0.0406) time: 2.5974 data: 0.0066 max mem: 33370 +Epoch: [28] [ 970/1319] eta: 0:15:19 lr: 1.598209497493724e-05 loss: 0.0361 (0.0406) time: 2.6084 data: 0.0065 max mem: 33370 +Epoch: [28] [ 980/1319] eta: 0:14:52 lr: 1.5972413094561205e-05 loss: 0.0374 (0.0406) time: 2.6255 data: 0.0065 max mem: 33370 +Epoch: [28] [ 990/1319] eta: 0:14:26 lr: 1.5962730562052938e-05 loss: 0.0341 (0.0405) time: 2.6437 data: 0.0064 max mem: 33370 +Epoch: [28] [1000/1319] eta: 0:14:00 lr: 1.5953047376928946e-05 loss: 0.0403 (0.0406) time: 2.6684 data: 0.0064 max mem: 33370 +Epoch: [28] 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mem: 33370 +Epoch: [28] [1090/1319] eta: 0:10:03 lr: 1.5865869262987425e-05 loss: 0.0377 (0.0409) time: 2.6319 data: 0.0063 max mem: 33370 +Epoch: [28] [1100/1319] eta: 0:09:36 lr: 1.5856179524962237e-05 loss: 0.0352 (0.0410) time: 2.6439 data: 0.0064 max mem: 33370 +Epoch: [28] [1110/1319] eta: 0:09:10 lr: 1.5846489128957288e-05 loss: 0.0404 (0.0412) time: 2.6612 data: 0.0067 max mem: 33370 +Epoch: [28] [1120/1319] eta: 0:08:44 lr: 1.5836798074480774e-05 loss: 0.0462 (0.0413) time: 2.6433 data: 0.0067 max mem: 33370 +Epoch: [28] [1130/1319] eta: 0:08:18 lr: 1.582710636104018e-05 loss: 0.0414 (0.0413) time: 2.6548 data: 0.0064 max mem: 33370 +Epoch: [28] [1140/1319] eta: 0:07:51 lr: 1.5817413988142284e-05 loss: 0.0393 (0.0413) time: 2.6478 data: 0.0065 max mem: 33370 +Epoch: [28] [1150/1319] eta: 0:07:25 lr: 1.5807720955293166e-05 loss: 0.0362 (0.0413) time: 2.6240 data: 0.0065 max mem: 33370 +Epoch: [28] [1160/1319] eta: 0:06:59 lr: 1.579802726199819e-05 loss: 0.0351 (0.0413) time: 2.6482 data: 0.0064 max mem: 33370 +Epoch: [28] [1170/1319] eta: 0:06:32 lr: 1.5788332907762015e-05 loss: 0.0335 (0.0412) time: 2.6768 data: 0.0063 max mem: 33370 +Epoch: [28] [1180/1319] eta: 0:06:06 lr: 1.577863789208859e-05 loss: 0.0360 (0.0413) time: 2.6492 data: 0.0062 max mem: 33370 +Epoch: [28] [1190/1319] eta: 0:05:39 lr: 1.576894221448116e-05 loss: 0.0336 (0.0412) time: 2.6307 data: 0.0062 max mem: 33370 +Epoch: [28] [1200/1319] eta: 0:05:13 lr: 1.5759245874442245e-05 loss: 0.0341 (0.0412) time: 2.6404 data: 0.0064 max mem: 33370 +Epoch: [28] [1210/1319] eta: 0:04:47 lr: 1.5749548871473663e-05 loss: 0.0400 (0.0412) time: 2.6193 data: 0.0063 max mem: 33370 +Epoch: [28] [1220/1319] eta: 0:04:20 lr: 1.57398512050765e-05 loss: 0.0400 (0.0412) time: 2.6137 data: 0.0063 max mem: 33370 +Epoch: [28] [1230/1319] eta: 0:03:54 lr: 1.5730152874751144e-05 loss: 0.0366 (0.0412) time: 2.6428 data: 0.0064 max mem: 33370 +Epoch: [28] [1240/1319] eta: 0:03:28 lr: 1.572045387999725e-05 loss: 0.0375 (0.0412) time: 2.6577 data: 0.0064 max mem: 33370 +Epoch: [28] [1250/1319] eta: 0:03:01 lr: 1.5710754220313764e-05 loss: 0.0369 (0.0412) time: 2.6614 data: 0.0063 max mem: 33370 +Epoch: [28] [1260/1319] eta: 0:02:35 lr: 1.5701053895198906e-05 loss: 0.0357 (0.0412) time: 2.6478 data: 0.0063 max mem: 33370 +Epoch: [28] [1270/1319] eta: 0:02:09 lr: 1.5691352904150157e-05 loss: 0.0387 (0.0414) time: 2.6591 data: 0.0064 max mem: 33370 +Epoch: [28] [1280/1319] eta: 0:01:42 lr: 1.5681651246664294e-05 loss: 0.0395 (0.0413) time: 2.6633 data: 0.0065 max mem: 33370 +Epoch: [28] [1290/1319] eta: 0:01:16 lr: 1.5671948922237363e-05 loss: 0.0379 (0.0414) time: 2.6600 data: 0.0064 max mem: 33370 +Epoch: [28] [1300/1319] eta: 0:00:50 lr: 1.5662245930364672e-05 loss: 0.0379 (0.0414) time: 2.6595 data: 0.0063 max mem: 33370 +Epoch: [28] [1310/1319] eta: 0:00:23 lr: 1.5652542270540813e-05 loss: 0.0384 (0.0415) time: 2.6449 data: 0.0063 max mem: 33370 +Epoch: [28] Total time: 0:57:58 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 1:38:23 time: 2.2945 data: 2.1418 max mem: 33370 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 100/2573] eta: 0:03:57 time: 0.0717 data: 0.0011 max mem: 33370 +Test: [ 200/2573] eta: 0:03:22 time: 0.0737 data: 0.0011 max mem: 33370 +Test: [ 300/2573] eta: 0:03:04 time: 0.0752 data: 0.0011 max mem: 33370 +Test: [ 400/2573] eta: 0:02:51 time: 0.0755 data: 0.0011 max mem: 33370 +Test: [ 500/2573] eta: 0:02:41 time: 0.0739 data: 0.0011 max mem: 33370 +Test: [ 600/2573] eta: 0:02:32 time: 0.0738 data: 0.0011 max mem: 33370 +Test: [ 700/2573] eta: 0:02:24 time: 0.0739 data: 0.0011 max mem: 33370 +Test: [ 800/2573] eta: 0:02:16 time: 0.0772 data: 0.0011 max mem: 33370 +Test: [ 900/2573] eta: 0:02:08 time: 0.0739 data: 0.0011 max mem: 33370 +Test: [1000/2573] eta: 0:02:00 time: 0.0740 data: 0.0011 max mem: 33370 +Test: [1100/2573] eta: 0:01:53 time: 0.0737 data: 0.0011 max mem: 33370 +Test: [1200/2573] eta: 0:01:45 time: 0.0738 data: 0.0011 max mem: 33370 +Test: [1300/2573] eta: 0:01:37 time: 0.0738 data: 0.0011 max mem: 33370 +Test: [1400/2573] eta: 0:01:29 time: 0.0721 data: 0.0011 max mem: 33370 +Test: [1500/2573] eta: 0:01:21 time: 0.0741 data: 0.0011 max mem: 33370 +Test: [1600/2573] eta: 0:01:13 time: 0.0773 data: 0.0011 max mem: 33370 +Test: [1700/2573] eta: 0:01:06 time: 0.0723 data: 0.0011 max mem: 33370 +Test: [1800/2573] eta: 0:00:58 time: 0.0758 data: 0.0011 max mem: 33370 +Test: [1900/2573] eta: 0:00:50 time: 0.0724 data: 0.0011 max mem: 33370 +Test: [2000/2573] eta: 0:00:43 time: 0.0740 data: 0.0011 max mem: 33370 +Test: [2100/2573] eta: 0:00:35 time: 0.0756 data: 0.0011 max mem: 33370 +Test: [2200/2573] eta: 0:00:28 time: 0.0759 data: 0.0011 max mem: 33370 +Test: [2300/2573] eta: 0:00:20 time: 0.0759 data: 0.0011 max mem: 33370 +Test: [2400/2573] eta: 0:00:13 time: 0.0708 data: 0.0011 max mem: 33370 +Test: [2500/2573] eta: 0:00:05 time: 0.0741 data: 0.0011 max mem: 33370 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: Total time: 0:03:13 +Final results: +Mean IoU is 63.83 + + precision@0.5 = 71.98 + precision@0.6 = 67.22 + precision@0.7 = 60.09 + precision@0.8 = 48.37 + precision@0.9 = 24.24 + overall IoU = 61.65 + +Average object IoU 63.82977858962673 +Overall IoU 61.647090911865234 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [29] [ 0/1319] eta: 3:05:51 lr: 1.5643808405182777e-05 loss: 0.0199 (0.0199) time: 8.4544 data: 1.3722 max mem: 33370 +Epoch: [29] [ 10/1319] eta: 1:08:44 lr: 1.563410347485666e-05 loss: 0.0397 (0.0409) time: 3.1507 data: 0.1309 max mem: 33370 +Epoch: [29] [ 20/1319] eta: 1:02:48 lr: 1.5624397875109532e-05 loss: 0.0410 (0.0414) time: 2.6235 data: 0.0065 max mem: 33370 +Epoch: [29] [ 30/1319] eta: 1:00:56 lr: 1.5614691605433113e-05 loss: 0.0410 (0.0408) time: 2.6638 data: 0.0066 max mem: 33370 +Epoch: [29] [ 40/1319] eta: 0:59:27 lr: 1.5604984665318397e-05 loss: 0.0375 (0.0413) time: 2.6723 data: 0.0067 max mem: 33370 +Epoch: [29] [ 50/1319] eta: 0:58:20 lr: 1.5595277054255625e-05 loss: 0.0342 (0.0401) time: 2.6381 data: 0.0067 max mem: 33370 +Epoch: [29] [ 60/1319] eta: 0:57:27 lr: 1.558556877173431e-05 loss: 0.0322 (0.0409) time: 2.6327 data: 0.0065 max mem: 33370 +Epoch: [29] [ 70/1319] eta: 0:56:46 lr: 1.557585981724323e-05 loss: 0.0327 (0.0401) time: 2.6477 data: 0.0064 max mem: 33370 +Epoch: [29] [ 80/1319] eta: 0:56:14 lr: 1.5566150190270393e-05 loss: 0.0347 (0.0402) time: 2.6779 data: 0.0064 max mem: 33370 +Epoch: [29] [ 90/1319] eta: 0:55:30 lr: 1.5556439890303075e-05 loss: 0.0358 (0.0398) time: 2.6481 data: 0.0068 max mem: 33370 +Epoch: [29] [ 100/1319] eta: 0:54:53 lr: 1.554672891682782e-05 loss: 0.0344 (0.0389) time: 2.6160 data: 0.0067 max mem: 33370 +Epoch: [29] [ 110/1319] eta: 0:54:21 lr: 1.55370172693304e-05 loss: 0.0340 (0.0387) time: 2.6421 data: 0.0066 max mem: 33370 +Epoch: [29] [ 120/1319] eta: 0:53:48 lr: 1.552730494729585e-05 loss: 0.0347 (0.0382) time: 2.6437 data: 0.0069 max mem: 33370 +Epoch: [29] [ 130/1319] eta: 0:53:16 lr: 1.551759195020846e-05 loss: 0.0339 (0.0390) time: 2.6375 data: 0.0071 max mem: 33370 +Epoch: [29] [ 140/1319] eta: 0:52:49 lr: 1.5507878277551742e-05 loss: 0.0342 (0.0386) time: 2.6618 data: 0.0068 max mem: 33370 +Epoch: [29] [ 150/1319] eta: 0:52:18 lr: 1.5498163928808475e-05 loss: 0.0357 (0.0387) time: 2.6581 data: 0.0066 max mem: 33370 +Epoch: [29] [ 160/1319] eta: 0:51:48 lr: 1.548844890346068e-05 loss: 0.0358 (0.0386) time: 2.6371 data: 0.0065 max mem: 33370 +Epoch: [29] [ 170/1319] eta: 0:51:16 lr: 1.547873320098961e-05 loss: 0.0356 (0.0386) time: 2.6274 data: 0.0066 max mem: 33370 +Epoch: [29] [ 180/1319] eta: 0:50:47 lr: 1.546901682087577e-05 loss: 0.0382 (0.0392) time: 2.6229 data: 0.0067 max mem: 33370 +Epoch: [29] [ 190/1319] eta: 0:50:15 lr: 1.5459299762598884e-05 loss: 0.0402 (0.0396) time: 2.6130 data: 0.0065 max mem: 33370 +Epoch: [29] [ 200/1319] eta: 0:49:45 lr: 1.5449582025637935e-05 loss: 0.0402 (0.0397) time: 2.6002 data: 0.0065 max mem: 33370 +Epoch: [29] [ 210/1319] eta: 0:49:17 lr: 1.543986360947113e-05 loss: 0.0334 (0.0394) time: 2.6253 data: 0.0068 max mem: 33370 +Epoch: [29] [ 220/1319] eta: 0:48:48 lr: 1.543014451357591e-05 loss: 0.0312 (0.0397) time: 2.6382 data: 0.0067 max mem: 33370 +Epoch: [29] [ 230/1319] eta: 0:48:20 lr: 1.5420424737428955e-05 loss: 0.0356 (0.0396) time: 2.6242 data: 0.0067 max mem: 33370 +Epoch: [29] [ 240/1319] eta: 0:47:53 lr: 1.541070428050616e-05 loss: 0.0389 (0.0400) time: 2.6362 data: 0.0067 max mem: 33370 +Epoch: [29] [ 250/1319] eta: 0:47:25 lr: 1.5400983142282667e-05 loss: 0.0418 (0.0400) time: 2.6522 data: 0.0066 max mem: 33370 +Epoch: [29] [ 260/1319] eta: 0:46:58 lr: 1.539126132223283e-05 loss: 0.0387 (0.0400) time: 2.6431 data: 0.0066 max mem: 33370 +Epoch: [29] [ 270/1319] eta: 0:46:28 lr: 1.538153881983024e-05 loss: 0.0406 (0.0402) time: 2.6138 data: 0.0067 max mem: 33370 +Epoch: [29] [ 280/1319] eta: 0:45:59 lr: 1.53718156345477e-05 loss: 0.0406 (0.0402) time: 2.5938 data: 0.0068 max mem: 33370 +Epoch: [29] [ 290/1319] eta: 0:45:31 lr: 1.5362091765857252e-05 loss: 0.0327 (0.0402) time: 2.5944 data: 0.0068 max mem: 33370 +Epoch: [29] [ 300/1319] eta: 0:45:03 lr: 1.5352367213230138e-05 loss: 0.0374 (0.0402) time: 2.6043 data: 0.0066 max mem: 33370 +Epoch: [29] [ 310/1319] eta: 0:44:37 lr: 1.5342641976136825e-05 loss: 0.0360 (0.0401) time: 2.6426 data: 0.0066 max mem: 33370 +Epoch: [29] [ 320/1319] eta: 0:44:09 lr: 1.5332916054047e-05 loss: 0.0340 (0.0400) time: 2.6377 data: 0.0067 max mem: 33370 +Epoch: [29] [ 330/1319] eta: 0:43:43 lr: 1.532318944642957e-05 loss: 0.0340 (0.0401) time: 2.6372 data: 0.0065 max mem: 33370 +Epoch: [29] [ 340/1319] eta: 0:43:15 lr: 1.5313462152752656e-05 loss: 0.0323 (0.0400) time: 2.6459 data: 0.0066 max mem: 33370 +Epoch: [29] [ 350/1319] eta: 0:42:48 lr: 1.5303734172483566e-05 loss: 0.0350 (0.0400) time: 2.6180 data: 0.0066 max mem: 33370 +Epoch: [29] [ 360/1319] eta: 0:42:21 lr: 1.529400550508885e-05 loss: 0.0333 (0.0399) time: 2.6205 data: 0.0065 max mem: 33370 +Epoch: [29] [ 370/1319] eta: 0:41:54 lr: 1.528427615003424e-05 loss: 0.0319 (0.0399) time: 2.6298 data: 0.0065 max mem: 33370 +Epoch: [29] [ 380/1319] eta: 0:41:26 lr: 1.5274546106784702e-05 loss: 0.0329 (0.0397) time: 2.6225 data: 0.0066 max mem: 33370 +Epoch: [29] [ 390/1319] eta: 0:40:59 lr: 1.526481537480438e-05 loss: 0.0311 (0.0396) time: 2.6128 data: 0.0065 max mem: 33370 +Epoch: [29] [ 400/1319] eta: 0:40:31 lr: 1.525508395355664e-05 loss: 0.0352 (0.0396) time: 2.6059 data: 0.0065 max mem: 33370 +Epoch: [29] [ 410/1319] eta: 0:40:04 lr: 1.5245351842504036e-05 loss: 0.0375 (0.0396) time: 2.6034 data: 0.0065 max mem: 33370 +Epoch: [29] [ 420/1319] eta: 0:39:39 lr: 1.5235619041108326e-05 loss: 0.0374 (0.0397) time: 2.6510 data: 0.0064 max mem: 33370 +Epoch: [29] [ 430/1319] eta: 0:39:11 lr: 1.5225885548830468e-05 loss: 0.0375 (0.0397) time: 2.6491 data: 0.0064 max mem: 33370 +Epoch: [29] [ 440/1319] eta: 0:38:44 lr: 1.5216151365130616e-05 loss: 0.0338 (0.0395) time: 2.6118 data: 0.0065 max mem: 33370 +Epoch: [29] [ 450/1319] eta: 0:38:18 lr: 1.520641648946812e-05 loss: 0.0387 (0.0398) time: 2.6229 data: 0.0065 max mem: 33370 +Epoch: [29] [ 460/1319] eta: 0:37:51 lr: 1.519668092130151e-05 loss: 0.0400 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1.4738317906666963e-05 loss: 0.0430 (0.0398) time: 2.6280 data: 0.0065 max mem: 33370 +Epoch: [29] [ 940/1319] eta: 0:16:40 lr: 1.4728548445256565e-05 loss: 0.0389 (0.0399) time: 2.6295 data: 0.0065 max mem: 33370 +Epoch: [29] [ 950/1319] eta: 0:16:14 lr: 1.471877826378261e-05 loss: 0.0404 (0.0399) time: 2.6150 data: 0.0065 max mem: 33370 +Epoch: [29] [ 960/1319] eta: 0:15:48 lr: 1.4709007361660864e-05 loss: 0.0381 (0.0399) time: 2.6234 data: 0.0063 max mem: 33370 +Epoch: [29] [ 970/1319] eta: 0:15:21 lr: 1.4699235738306196e-05 loss: 0.0374 (0.0399) time: 2.6358 data: 0.0063 max mem: 33370 +Epoch: [29] [ 980/1319] eta: 0:14:55 lr: 1.4689463393132561e-05 loss: 0.0336 (0.0399) time: 2.6251 data: 0.0063 max mem: 33370 +Epoch: [29] [ 990/1319] eta: 0:14:28 lr: 1.4679690325553006e-05 loss: 0.0312 (0.0398) time: 2.6405 data: 0.0063 max mem: 33370 +Epoch: [29] [1000/1319] eta: 0:14:02 lr: 1.466991653497966e-05 loss: 0.0392 (0.0398) time: 2.6364 data: 0.0062 max mem: 33370 +Epoch: [29] 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mem: 33370 +Epoch: [29] [1090/1319] eta: 0:10:04 lr: 1.4581919787647347e-05 loss: 0.0355 (0.0396) time: 2.6383 data: 0.0065 max mem: 33370 +Epoch: [29] [1100/1319] eta: 0:09:38 lr: 1.4572138734601442e-05 loss: 0.0359 (0.0396) time: 2.6462 data: 0.0064 max mem: 33370 +Epoch: [29] [1110/1319] eta: 0:09:11 lr: 1.4562356952034447e-05 loss: 0.0350 (0.0396) time: 2.6333 data: 0.0064 max mem: 33370 +Epoch: [29] [1120/1319] eta: 0:08:45 lr: 1.4552574439347391e-05 loss: 0.0328 (0.0395) time: 2.6292 data: 0.0065 max mem: 33370 +Epoch: [29] [1130/1319] eta: 0:08:18 lr: 1.4542791195940364e-05 loss: 0.0332 (0.0395) time: 2.6264 data: 0.0065 max mem: 33370 +Epoch: [29] [1140/1319] eta: 0:07:52 lr: 1.453300722121251e-05 loss: 0.0404 (0.0395) time: 2.6343 data: 0.0065 max mem: 33370 +Epoch: [29] [1150/1319] eta: 0:07:26 lr: 1.4523222514562035e-05 loss: 0.0378 (0.0395) time: 2.6525 data: 0.0063 max mem: 33370 +Epoch: [29] [1160/1319] eta: 0:06:59 lr: 1.4513437075386188e-05 loss: 0.0294 (0.0394) time: 2.6467 data: 0.0061 max mem: 33370 +Epoch: [29] [1170/1319] eta: 0:06:33 lr: 1.4503650903081281e-05 loss: 0.0334 (0.0394) time: 2.6245 data: 0.0063 max mem: 33370 +Epoch: [29] [1180/1319] eta: 0:06:06 lr: 1.449386399704267e-05 loss: 0.0335 (0.0394) time: 2.6153 data: 0.0064 max mem: 33370 +Epoch: [29] [1190/1319] eta: 0:05:40 lr: 1.4484076356664761e-05 loss: 0.0337 (0.0393) time: 2.6210 data: 0.0064 max mem: 33370 +Epoch: [29] [1200/1319] eta: 0:05:14 lr: 1.447428798134101e-05 loss: 0.0343 (0.0393) time: 2.6263 data: 0.0064 max mem: 33370 +Epoch: [29] [1210/1319] eta: 0:04:47 lr: 1.4464498870463896e-05 loss: 0.0358 (0.0393) time: 2.6252 data: 0.0064 max mem: 33370 +Epoch: [29] [1220/1319] eta: 0:04:21 lr: 1.4454709023424959e-05 loss: 0.0344 (0.0393) time: 2.6245 data: 0.0065 max mem: 33370 +Epoch: [29] [1230/1319] eta: 0:03:54 lr: 1.444491843961477e-05 loss: 0.0344 (0.0393) time: 2.6451 data: 0.0063 max mem: 33370 +Epoch: [29] [1240/1319] eta: 0:03:28 lr: 1.4435127118422938e-05 loss: 0.0387 (0.0393) time: 2.6367 data: 0.0062 max mem: 33370 +Epoch: [29] [1250/1319] eta: 0:03:02 lr: 1.442533505923811e-05 loss: 0.0402 (0.0393) time: 2.6071 data: 0.0064 max mem: 33370 +Epoch: [29] [1260/1319] eta: 0:02:35 lr: 1.4415542261447945e-05 loss: 0.0330 (0.0393) time: 2.6077 data: 0.0063 max mem: 33370 +Epoch: [29] [1270/1319] eta: 0:02:09 lr: 1.4405748724439155e-05 loss: 0.0330 (0.0393) time: 2.6261 data: 0.0064 max mem: 33370 +Epoch: [29] [1280/1319] eta: 0:01:42 lr: 1.4395954447597464e-05 loss: 0.0355 (0.0393) time: 2.6325 data: 0.0064 max mem: 33370 +Epoch: [29] [1290/1319] eta: 0:01:16 lr: 1.4386159430307632e-05 loss: 0.0384 (0.0394) time: 2.5963 data: 0.0063 max mem: 33370 +Epoch: [29] [1300/1319] eta: 0:00:50 lr: 1.4376363671953435e-05 loss: 0.0419 (0.0394) time: 2.5917 data: 0.0065 max mem: 33370 +Epoch: [29] [1310/1319] eta: 0:00:23 lr: 1.4366567171917672e-05 loss: 0.0387 (0.0394) time: 2.6368 data: 0.0065 max mem: 33370 +Epoch: [29] Total time: 0:57:59 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 2:10:43 time: 3.0482 data: 2.9601 max mem: 33370 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 100/2573] eta: 0:04:11 time: 0.0714 data: 0.0011 max mem: 33370 +Test: [ 200/2573] eta: 0:03:28 time: 0.0732 data: 0.0011 max mem: 33370 +Test: [ 300/2573] eta: 0:03:07 time: 0.0750 data: 0.0011 max mem: 33370 +Test: [ 400/2573] eta: 0:02:54 time: 0.0752 data: 0.0011 max mem: 33370 +Test: [ 500/2573] eta: 0:02:43 time: 0.0735 data: 0.0011 max mem: 33370 +Test: [ 600/2573] eta: 0:02:34 time: 0.0735 data: 0.0011 max mem: 33370 +Test: [ 700/2573] eta: 0:02:25 time: 0.0736 data: 0.0011 max mem: 33370 +Test: [ 800/2573] eta: 0:02:17 time: 0.0770 data: 0.0011 max mem: 33370 +Test: [ 900/2573] eta: 0:02:09 time: 0.0737 data: 0.0011 max mem: 33370 +Test: [1000/2573] eta: 0:02:00 time: 0.0737 data: 0.0011 max mem: 33370 +Test: [1100/2573] eta: 0:01:52 time: 0.0738 data: 0.0011 max mem: 33370 +Test: [1200/2573] eta: 0:01:44 time: 0.0736 data: 0.0011 max mem: 33370 +Test: [1300/2573] eta: 0:01:37 time: 0.0737 data: 0.0010 max mem: 33370 +Test: [1400/2573] eta: 0:01:29 time: 0.0721 data: 0.0011 max mem: 33370 +Test: [1500/2573] eta: 0:01:21 time: 0.0737 data: 0.0011 max mem: 33370 +Test: [1600/2573] eta: 0:01:13 time: 0.0769 data: 0.0011 max mem: 33370 +Test: [1700/2573] eta: 0:01:06 time: 0.0720 data: 0.0011 max mem: 33370 +Test: [1800/2573] eta: 0:00:58 time: 0.0754 data: 0.0011 max mem: 33370 +Test: [1900/2573] eta: 0:00:50 time: 0.0721 data: 0.0011 max mem: 33370 +Test: [2000/2573] eta: 0:00:43 time: 0.0738 data: 0.0011 max mem: 33370 +Test: [2100/2573] eta: 0:00:35 time: 0.0754 data: 0.0011 max mem: 33370 +Test: [2200/2573] eta: 0:00:27 time: 0.0754 data: 0.0011 max mem: 33370 +Test: [2300/2573] eta: 0:00:20 time: 0.0754 data: 0.0011 max mem: 33370 +Test: [2400/2573] eta: 0:00:12 time: 0.0705 data: 0.0011 max mem: 33370 +Test: [2500/2573] eta: 0:00:05 time: 0.0739 data: 0.0011 max mem: 33370 +Test: Total time: 0:03:13 +Final results: +Mean IoU is 63.76 + + precision@0.5 = 71.69 + precision@0.6 = 66.77 + precision@0.7 = 59.97 + precision@0.8 = 48.77 + precision@0.9 = 24.90 + overall IoU = 61.23 + +Average object IoU 63.75873771153691 +Overall IoU 61.22686004638672 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [30] [ 0/1319] eta: 3:13:52 lr: 1.4357749687236825e-05 loss: 0.0283 (0.0283) time: 8.8190 data: 1.5586 max mem: 33370 +Epoch: [30] [ 10/1319] eta: 1:09:10 lr: 1.4347951776302166e-05 loss: 0.0344 (0.0365) time: 3.1710 data: 0.1481 max mem: 33370 +Epoch: [30] [ 20/1319] eta: 1:03:28 lr: 1.433815312189048e-05 loss: 0.0383 (0.0375) time: 2.6379 data: 0.0064 max mem: 33370 +Epoch: [30] [ 30/1319] eta: 1:00:51 lr: 1.4328353723380728e-05 loss: 0.0365 (0.0357) time: 2.6468 data: 0.0062 max mem: 33370 +Epoch: [30] [ 40/1319] eta: 0:59:20 lr: 1.431855358015087e-05 loss: 0.0305 (0.0344) time: 2.6284 data: 0.0066 max mem: 33370 +Epoch: [30] [ 50/1319] eta: 0:58:09 lr: 1.4308752691577878e-05 loss: 0.0310 (0.0342) time: 2.6214 data: 0.0066 max mem: 33370 +Epoch: [30] [ 60/1319] eta: 0:57:12 lr: 1.4298951057037729e-05 loss: 0.0332 (0.0348) time: 2.6089 data: 0.0066 max mem: 33370 +Epoch: [30] [ 70/1319] eta: 0:56:36 lr: 1.4289148675905387e-05 loss: 0.0354 (0.0353) time: 2.6402 data: 0.0066 max mem: 33370 +Epoch: [30] [ 80/1319] eta: 0:55:48 lr: 1.4279345547554832e-05 loss: 0.0354 (0.0371) time: 2.6309 data: 0.0066 max mem: 33370 +Epoch: [30] [ 90/1319] eta: 0:55:13 lr: 1.4269541671359036e-05 loss: 0.0340 (0.0367) time: 2.6135 data: 0.0066 max mem: 33370 +Epoch: [30] [ 100/1319] eta: 0:54:40 lr: 1.4259737046689963e-05 loss: 0.0354 (0.0371) time: 2.6442 data: 0.0066 max mem: 33370 +Epoch: [30] [ 110/1319] eta: 0:54:11 lr: 1.424993167291858e-05 loss: 0.0388 (0.0369) time: 2.6613 data: 0.0066 max mem: 33370 +Epoch: [30] [ 120/1319] eta: 0:53:38 lr: 1.4240125549414829e-05 loss: 0.0319 (0.0368) time: 2.6479 data: 0.0066 max mem: 33370 +Epoch: [30] [ 130/1319] eta: 0:53:10 lr: 1.4230318675547643e-05 loss: 0.0322 (0.0368) time: 2.6509 data: 0.0067 max mem: 33370 +Epoch: [30] [ 140/1319] eta: 0:52:39 lr: 1.4220511050684946e-05 loss: 0.0322 (0.0367) time: 2.6551 data: 0.0067 max mem: 33370 +Epoch: [30] [ 150/1319] eta: 0:52:07 lr: 1.4210702674193643e-05 loss: 0.0333 (0.0370) time: 2.6233 data: 0.0067 max mem: 33370 +Epoch: [30] [ 160/1319] eta: 0:51:36 lr: 1.420089354543962e-05 loss: 0.0333 (0.0370) time: 2.6132 data: 0.0066 max mem: 33370 +Epoch: [30] [ 170/1319] eta: 0:51:06 lr: 1.419108366378774e-05 loss: 0.0322 (0.0367) time: 2.6200 data: 0.0066 max mem: 33370 +Epoch: [30] [ 180/1319] eta: 0:50:38 lr: 1.4181273028601838e-05 loss: 0.0311 (0.0364) time: 2.6334 data: 0.0068 max mem: 33370 +Epoch: [30] [ 190/1319] eta: 0:50:09 lr: 1.4171461639244721e-05 loss: 0.0348 (0.0367) time: 2.6385 data: 0.0065 max mem: 33370 +Epoch: [30] [ 200/1319] eta: 0:49:42 lr: 1.4161649495078178e-05 loss: 0.0383 (0.0366) time: 2.6502 data: 0.0064 max mem: 33370 +Epoch: [30] [ 210/1319] eta: 0:49:15 lr: 1.415183659546295e-05 loss: 0.0329 (0.0367) time: 2.6513 data: 0.0065 max mem: 33370 +Epoch: [30] [ 220/1319] eta: 0:48:47 lr: 1.4142022939758767e-05 loss: 0.0345 (0.0369) time: 2.6428 data: 0.0065 max mem: 33370 +Epoch: [30] [ 230/1319] eta: 0:48:19 lr: 1.413220852732429e-05 loss: 0.0343 (0.0367) time: 2.6364 data: 0.0065 max mem: 33370 +Epoch: [30] [ 240/1319] eta: 0:47:51 lr: 1.4122393357517167e-05 loss: 0.0305 (0.0367) time: 2.6296 data: 0.0067 max mem: 33370 +Epoch: [30] [ 250/1319] eta: 0:47:22 lr: 1.4112577429693993e-05 loss: 0.0334 (0.0368) time: 2.6238 data: 0.0066 max mem: 33370 +Epoch: [30] [ 260/1319] eta: 0:46:54 lr: 1.4102760743210322e-05 loss: 0.0305 (0.0370) time: 2.6160 data: 0.0065 max mem: 33370 +Epoch: [30] [ 270/1319] eta: 0:46:27 lr: 1.4092943297420657e-05 loss: 0.0378 (0.0369) time: 2.6357 data: 0.0065 max mem: 33370 +Epoch: [30] [ 280/1319] eta: 0:46:00 lr: 1.4083125091678468e-05 loss: 0.0378 (0.0371) time: 2.6542 data: 0.0066 max mem: 33370 +Epoch: [30] [ 290/1319] eta: 0:45:33 lr: 1.4073306125336142e-05 loss: 0.0372 (0.0373) time: 2.6469 data: 0.0065 max mem: 33370 +Epoch: [30] [ 300/1319] eta: 0:45:05 lr: 1.4063486397745037e-05 loss: 0.0343 (0.0371) time: 2.6272 data: 0.0063 max mem: 33370 +Epoch: [30] [ 310/1319] eta: 0:44:39 lr: 1.4053665908255448e-05 loss: 0.0338 (0.0371) time: 2.6344 data: 0.0064 max mem: 33370 +Epoch: [30] [ 320/1319] eta: 0:44:11 lr: 1.4043844656216607e-05 loss: 0.0360 (0.0371) time: 2.6340 data: 0.0066 max mem: 33370 +Epoch: [30] [ 330/1319] eta: 0:43:43 lr: 1.4034022640976696e-05 loss: 0.0360 (0.0371) time: 2.6167 data: 0.0065 max mem: 33370 +Epoch: [30] [ 340/1319] eta: 0:43:16 lr: 1.4024199861882808e-05 loss: 0.0348 (0.0374) time: 2.6268 data: 0.0064 max mem: 33370 +Epoch: [30] [ 350/1319] eta: 0:42:50 lr: 1.4014376318280992e-05 loss: 0.0317 (0.0373) time: 2.6544 data: 0.0066 max mem: 33370 +Epoch: [30] [ 360/1319] eta: 0:42:23 lr: 1.4004552009516214e-05 loss: 0.0286 (0.0372) time: 2.6580 data: 0.0066 max mem: 33370 +Epoch: [30] [ 370/1319] eta: 0:41:56 lr: 1.3994726934932381e-05 loss: 0.0284 (0.0371) time: 2.6307 data: 0.0065 max mem: 33370 +Epoch: [30] [ 380/1319] eta: 0:41:29 lr: 1.3984901093872316e-05 loss: 0.0336 (0.0371) time: 2.6282 data: 0.0067 max mem: 33370 +Epoch: [30] [ 390/1319] eta: 0:41:02 lr: 1.3975074485677755e-05 loss: 0.0341 (0.0370) time: 2.6318 data: 0.0066 max mem: 33370 +Epoch: [30] [ 400/1319] eta: 0:40:36 lr: 1.3965247109689372e-05 loss: 0.0341 (0.0369) time: 2.6420 data: 0.0064 max mem: 33370 +Epoch: [30] [ 410/1319] eta: 0:40:09 lr: 1.3955418965246752e-05 loss: 0.0300 (0.0368) time: 2.6407 data: 0.0064 max mem: 33370 +Epoch: [30] [ 420/1319] eta: 0:39:43 lr: 1.394559005168839e-05 loss: 0.0312 (0.0367) time: 2.6550 data: 0.0063 max mem: 33370 +Epoch: [30] [ 430/1319] eta: 0:39:16 lr: 1.39357603683517e-05 loss: 0.0362 (0.0367) time: 2.6631 data: 0.0063 max mem: 33370 +Epoch: [30] [ 440/1319] eta: 0:38:49 lr: 1.3925929914573002e-05 loss: 0.0387 (0.0368) time: 2.6361 data: 0.0063 max mem: 33370 +Epoch: [30] [ 450/1319] eta: 0:38:23 lr: 1.3916098689687517e-05 loss: 0.0347 (0.0368) time: 2.6507 data: 0.0064 max mem: 33370 +Epoch: [30] [ 460/1319] eta: 0:37:56 lr: 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1.3136936515041629e-05 loss: 0.0314 (0.0379) time: 2.6455 data: 0.0064 max mem: 33370 +Epoch: [30] [1250/1319] eta: 0:03:01 lr: 1.3127041345777947e-05 loss: 0.0311 (0.0379) time: 2.6386 data: 0.0066 max mem: 33370 +Epoch: [30] [1260/1319] eta: 0:02:35 lr: 1.3117145347668891e-05 loss: 0.0356 (0.0379) time: 2.6271 data: 0.0067 max mem: 33370 +Epoch: [30] [1270/1319] eta: 0:02:09 lr: 1.3107248519950133e-05 loss: 0.0394 (0.0379) time: 2.6085 data: 0.0067 max mem: 33370 +Epoch: [30] [1280/1319] eta: 0:01:42 lr: 1.3097350861856001e-05 loss: 0.0394 (0.0379) time: 2.6413 data: 0.0065 max mem: 33370 +Epoch: [30] [1290/1319] eta: 0:01:16 lr: 1.3087452372619463e-05 loss: 0.0340 (0.0379) time: 2.6378 data: 0.0065 max mem: 33370 +Epoch: [30] [1300/1319] eta: 0:00:50 lr: 1.3077553051472149e-05 loss: 0.0340 (0.0379) time: 2.6224 data: 0.0065 max mem: 33370 +Epoch: [30] [1310/1319] eta: 0:00:23 lr: 1.3067652897644308e-05 loss: 0.0365 (0.0379) time: 2.6259 data: 0.0065 max mem: 33370 +Epoch: [30] Total time: 0:57:57 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 1:45:47 time: 2.4671 data: 2.3172 max mem: 33370 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 100/2573] eta: 0:04:00 time: 0.0715 data: 0.0011 max mem: 33370 +Test: [ 200/2573] eta: 0:03:23 time: 0.0733 data: 0.0011 max mem: 33370 +Test: [ 300/2573] eta: 0:03:04 time: 0.0750 data: 0.0011 max mem: 33370 +Test: [ 400/2573] eta: 0:02:52 time: 0.0753 data: 0.0011 max mem: 33370 +Test: [ 500/2573] eta: 0:02:42 time: 0.0737 data: 0.0011 max mem: 33370 +Test: [ 600/2573] eta: 0:02:32 time: 0.0738 data: 0.0011 max mem: 33370 +Test: [ 700/2573] eta: 0:02:24 time: 0.0739 data: 0.0011 max mem: 33370 +Test: [ 800/2573] eta: 0:02:16 time: 0.0770 data: 0.0011 max mem: 33370 +Test: [ 900/2573] eta: 0:02:08 time: 0.0738 data: 0.0011 max mem: 33370 +Test: [1000/2573] eta: 0:02:00 time: 0.0738 data: 0.0011 max mem: 33370 +Test: [1100/2573] eta: 0:01:52 time: 0.0739 data: 0.0011 max mem: 33370 +Test: [1200/2573] eta: 0:01:44 time: 0.0737 data: 0.0011 max mem: 33370 +Test: [1300/2573] eta: 0:01:36 time: 0.0739 data: 0.0011 max mem: 33370 +Test: [1400/2573] eta: 0:01:28 time: 0.0721 data: 0.0011 max mem: 33370 +Test: [1500/2573] eta: 0:01:21 time: 0.0737 data: 0.0011 max mem: 33370 +Test: [1600/2573] eta: 0:01:13 time: 0.0771 data: 0.0011 max mem: 33370 +Test: [1700/2573] eta: 0:01:05 time: 0.0721 data: 0.0011 max mem: 33370 +Test: [1800/2573] eta: 0:00:58 time: 0.0754 data: 0.0011 max mem: 33370 +Test: [1900/2573] eta: 0:00:50 time: 0.0720 data: 0.0011 max mem: 33370 +Test: [2000/2573] eta: 0:00:42 time: 0.0737 data: 0.0011 max mem: 33370 +Test: [2100/2573] eta: 0:00:35 time: 0.0753 data: 0.0011 max mem: 33370 +Test: [2200/2573] eta: 0:00:27 time: 0.0755 data: 0.0010 max mem: 33370 +Test: [2300/2573] eta: 0:00:20 time: 0.0755 data: 0.0011 max mem: 33370 +Test: [2400/2573] eta: 0:00:12 time: 0.0704 data: 0.0011 max mem: 33370 +Test: [2500/2573] eta: 0:00:05 time: 0.0737 data: 0.0011 max mem: 33370 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: Total time: 0:03:12 +Final results: +Mean IoU is 64.39 + + precision@0.5 = 72.28 + precision@0.6 = 67.34 + precision@0.7 = 60.62 + precision@0.8 = 49.47 + precision@0.9 = 24.65 + overall IoU = 61.77 + +Average object IoU 64.38505135406383 +Overall IoU 61.77479934692383 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [31] [ 0/1319] eta: 3:01:25 lr: 1.3058742046620123e-05 loss: 0.0377 (0.0377) time: 8.2531 data: 1.0719 max mem: 33370 +Epoch: [31] [ 10/1319] eta: 1:09:31 lr: 1.3048840308573793e-05 loss: 0.0345 (0.0346) time: 3.1865 data: 0.1031 max mem: 33370 +Epoch: [31] [ 20/1319] eta: 1:03:16 lr: 1.3038937735606992e-05 loss: 0.0315 (0.0343) time: 2.6561 data: 0.0064 max mem: 33370 +Epoch: [31] [ 30/1319] eta: 1:00:51 lr: 1.3029034326944665e-05 loss: 0.0332 (0.0357) time: 2.6378 data: 0.0070 max mem: 33370 +Epoch: [31] [ 40/1319] eta: 0:59:25 lr: 1.3019130081810363e-05 loss: 0.0314 (0.0355) time: 2.6454 data: 0.0069 max mem: 33370 +Epoch: [31] [ 50/1319] eta: 0:58:30 lr: 1.3009224999426282e-05 loss: 0.0320 (0.0364) time: 2.6643 data: 0.0065 max mem: 33370 +Epoch: [31] [ 60/1319] eta: 0:57:34 lr: 1.2999319079013207e-05 loss: 0.0320 (0.0361) time: 2.6552 data: 0.0068 max mem: 33370 +Epoch: [31] [ 70/1319] eta: 0:56:45 lr: 1.298941231979056e-05 loss: 0.0315 (0.0359) time: 2.6260 data: 0.0068 max mem: 33370 +Epoch: [31] [ 80/1319] eta: 0:56:06 lr: 1.2979504720976363e-05 loss: 0.0317 (0.0351) time: 2.6362 data: 0.0067 max mem: 33370 +Epoch: [31] [ 90/1319] eta: 0:55:32 lr: 1.2969596281787253e-05 loss: 0.0318 (0.0357) time: 2.6576 data: 0.0066 max mem: 33370 +Epoch: [31] [ 100/1319] eta: 0:54:55 lr: 1.2959687001438464e-05 loss: 0.0331 (0.0359) time: 2.6464 data: 0.0065 max mem: 33370 +Epoch: [31] [ 110/1319] eta: 0:54:20 lr: 1.2949776879143838e-05 loss: 0.0339 (0.0357) time: 2.6312 data: 0.0067 max mem: 33370 +Epoch: [31] [ 120/1319] eta: 0:53:46 lr: 1.2939865914115796e-05 loss: 0.0326 (0.0358) time: 2.6262 data: 0.0068 max mem: 33370 +Epoch: [31] [ 130/1319] eta: 0:53:13 lr: 1.2929954105565368e-05 loss: 0.0363 (0.0362) time: 2.6248 data: 0.0066 max mem: 33370 +Epoch: [31] [ 140/1319] eta: 0:52:45 lr: 1.2920041452702167e-05 loss: 0.0334 (0.0361) time: 2.6496 data: 0.0066 max mem: 33370 +Epoch: [31] [ 150/1319] eta: 0:52:12 lr: 1.2910127954734388e-05 loss: 0.0298 (0.0358) time: 2.6346 data: 0.0068 max mem: 33370 +Epoch: [31] [ 160/1319] eta: 0:51:44 lr: 1.2900213610868823e-05 loss: 0.0321 (0.0364) time: 2.6367 data: 0.0067 max mem: 33370 +Epoch: [31] [ 170/1319] eta: 0:51:11 lr: 1.2890298420310808e-05 loss: 0.0342 (0.0363) time: 2.6258 data: 0.0064 max mem: 33370 +Epoch: [31] [ 180/1319] eta: 0:50:43 lr: 1.2880382382264284e-05 loss: 0.0288 (0.0364) time: 2.6157 data: 0.0064 max mem: 33370 +Epoch: [31] [ 190/1319] eta: 0:50:15 lr: 1.2870465495931752e-05 loss: 0.0269 (0.0363) time: 2.6490 data: 0.0066 max mem: 33370 +Epoch: [31] [ 200/1319] eta: 0:49:46 lr: 1.2860547760514275e-05 loss: 0.0292 (0.0364) time: 2.6388 data: 0.0066 max mem: 33370 +Epoch: [31] [ 210/1319] eta: 0:49:18 lr: 1.285062917521149e-05 loss: 0.0326 (0.0363) time: 2.6433 data: 0.0065 max mem: 33370 +Epoch: [31] [ 220/1319] eta: 0:48:50 lr: 1.2840709739221567e-05 loss: 0.0308 (0.0362) time: 2.6419 data: 0.0064 max mem: 33370 +Epoch: [31] [ 230/1319] eta: 0:48:21 lr: 1.2830789451741262e-05 loss: 0.0284 (0.0364) time: 2.6272 data: 0.0065 max mem: 33370 +Epoch: [31] [ 240/1319] eta: 0:47:52 lr: 1.2820868311965862e-05 loss: 0.0289 (0.0361) time: 2.6191 data: 0.0067 max mem: 33370 +Epoch: [31] [ 250/1319] eta: 0:47:23 lr: 1.2810946319089204e-05 loss: 0.0328 (0.0361) time: 2.6090 data: 0.0067 max mem: 33370 +Epoch: [31] [ 260/1319] eta: 0:46:55 lr: 1.2801023472303672e-05 loss: 0.0389 (0.0363) time: 2.6136 data: 0.0067 max mem: 33370 +Epoch: [31] [ 270/1319] eta: 0:46:26 lr: 1.2791099770800195e-05 loss: 0.0369 (0.0365) time: 2.6040 data: 0.0067 max mem: 33370 +Epoch: [31] [ 280/1319] eta: 0:45:57 lr: 1.2781175213768214e-05 loss: 0.0351 (0.0365) time: 2.6000 data: 0.0065 max mem: 33370 +Epoch: [31] [ 290/1319] eta: 0:45:31 lr: 1.277124980039573e-05 loss: 0.0340 (0.0364) time: 2.6305 data: 0.0065 max mem: 33370 +Epoch: [31] [ 300/1319] eta: 0:45:02 lr: 1.2761323529869248e-05 loss: 0.0344 (0.0366) time: 2.6251 data: 0.0066 max mem: 33370 +Epoch: [31] [ 310/1319] eta: 0:44:35 lr: 1.2751396401373813e-05 loss: 0.0358 (0.0366) time: 2.6196 data: 0.0066 max mem: 33370 +Epoch: [31] [ 320/1319] eta: 0:44:09 lr: 1.2741468414092989e-05 loss: 0.0331 (0.0366) time: 2.6424 data: 0.0065 max mem: 33370 +Epoch: [31] [ 330/1319] eta: 0:43:42 lr: 1.2731539567208833e-05 loss: 0.0324 (0.0366) time: 2.6518 data: 0.0065 max mem: 33370 +Epoch: [31] [ 340/1319] eta: 0:43:16 lr: 1.2721609859901942e-05 loss: 0.0320 (0.0366) time: 2.6524 data: 0.0065 max mem: 33370 +Epoch: [31] [ 350/1319] eta: 0:42:48 lr: 1.2711679291351405e-05 loss: 0.0364 (0.0367) time: 2.6224 data: 0.0064 max mem: 33370 +Epoch: [31] [ 360/1319] eta: 0:42:21 lr: 1.2701747860734819e-05 loss: 0.0364 (0.0367) time: 2.6200 data: 0.0064 max mem: 33370 +Epoch: [31] [ 370/1319] eta: 0:41:53 lr: 1.2691815567228285e-05 loss: 0.0353 (0.0368) time: 2.6159 data: 0.0064 max mem: 33370 +Epoch: [31] [ 380/1319] eta: 0:41:26 lr: 1.2681882410006382e-05 loss: 0.0351 (0.0368) time: 2.6049 data: 0.0064 max mem: 33370 +Epoch: [31] [ 390/1319] eta: 0:40:57 lr: 1.26719483882422e-05 loss: 0.0360 (0.0368) time: 2.5959 data: 0.0064 max mem: 33370 +Epoch: [31] [ 400/1319] eta: 0:40:31 lr: 1.2662013501107303e-05 loss: 0.0357 (0.0369) time: 2.6016 data: 0.0064 max mem: 33370 +Epoch: [31] [ 410/1319] eta: 0:40:04 lr: 1.265207774777175e-05 loss: 0.0311 (0.0368) time: 2.6363 data: 0.0063 max mem: 33370 +Epoch: [31] [ 420/1319] eta: 0:39:37 lr: 1.2642141127404073e-05 loss: 0.0335 (0.0368) time: 2.6333 data: 0.0064 max mem: 33370 +Epoch: [31] [ 430/1319] eta: 0:39:11 lr: 1.2632203639171281e-05 loss: 0.0331 (0.0366) time: 2.6430 data: 0.0065 max mem: 33370 +Epoch: [31] [ 440/1319] eta: 0:38:45 lr: 1.2622265282238837e-05 loss: 0.0350 (0.0366) time: 2.6543 data: 0.0066 max mem: 33370 +Epoch: [31] [ 450/1319] eta: 0:38:19 lr: 1.2612326055770701e-05 loss: 0.0350 (0.0365) time: 2.6573 data: 0.0067 max mem: 33370 +Epoch: [31] [ 460/1319] eta: 0:37:52 lr: 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1.1824305291067328e-05 loss: 0.0361 (0.0375) time: 2.6328 data: 0.0064 max mem: 33370 +Epoch: [31] [1250/1319] eta: 0:03:02 lr: 1.1814293649022872e-05 loss: 0.0352 (0.0374) time: 2.6659 data: 0.0064 max mem: 33370 +Epoch: [31] [1260/1319] eta: 0:02:35 lr: 1.180428106421806e-05 loss: 0.0298 (0.0374) time: 2.6616 data: 0.0063 max mem: 33370 +Epoch: [31] [1270/1319] eta: 0:02:09 lr: 1.1794267535675433e-05 loss: 0.0322 (0.0375) time: 2.6499 data: 0.0063 max mem: 33370 +Epoch: [31] [1280/1319] eta: 0:01:42 lr: 1.1784253062415594e-05 loss: 0.0327 (0.0375) time: 2.6449 data: 0.0064 max mem: 33370 +Epoch: [31] [1290/1319] eta: 0:01:16 lr: 1.1774237643457209e-05 loss: 0.0333 (0.0375) time: 2.6573 data: 0.0065 max mem: 33370 +Epoch: [31] [1300/1319] eta: 0:00:50 lr: 1.1764221277816978e-05 loss: 0.0333 (0.0375) time: 2.6475 data: 0.0064 max mem: 33370 +Epoch: [31] [1310/1319] eta: 0:00:23 lr: 1.1754203964509668e-05 loss: 0.0333 (0.0375) time: 2.6584 data: 0.0063 max mem: 33370 +Epoch: [31] Total time: 0:58:02 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 2:01:40 time: 2.8372 data: 2.7243 max mem: 33370 +Test: [ 100/2573] eta: 0:04:04 time: 0.0713 data: 0.0011 max mem: 33370 +Test: [ 200/2573] eta: 0:03:25 time: 0.0732 data: 0.0011 max mem: 33370 +Test: [ 300/2573] eta: 0:03:05 time: 0.0750 data: 0.0011 max mem: 33370 +Test: [ 400/2573] eta: 0:02:52 time: 0.0751 data: 0.0010 max mem: 33370 +Test: [ 500/2573] eta: 0:02:42 time: 0.0736 data: 0.0011 max mem: 33370 +Test: [ 600/2573] eta: 0:02:33 time: 0.0737 data: 0.0011 max mem: 33370 +Test: [ 700/2573] eta: 0:02:25 time: 0.0736 data: 0.0011 max mem: 33370 +Test: [ 800/2573] eta: 0:02:16 time: 0.0772 data: 0.0011 max mem: 33370 +Test: [ 900/2573] eta: 0:02:08 time: 0.0737 data: 0.0011 max mem: 33370 +Test: [1000/2573] eta: 0:02:00 time: 0.0738 data: 0.0011 max mem: 33370 +Test: [1100/2573] eta: 0:01:52 time: 0.0739 data: 0.0011 max mem: 33370 +Test: [1200/2573] eta: 0:01:44 time: 0.0737 data: 0.0010 max mem: 33370 +Test: [1300/2573] eta: 0:01:36 time: 0.0738 data: 0.0011 max mem: 33370 +Test: [1400/2573] eta: 0:01:28 time: 0.0720 data: 0.0011 max mem: 33370 +Test: [1500/2573] eta: 0:01:21 time: 0.0737 data: 0.0011 max mem: 33370 +Test: [1600/2573] eta: 0:01:13 time: 0.0771 data: 0.0011 max mem: 33370 +Test: [1700/2573] eta: 0:01:05 time: 0.0723 data: 0.0011 max mem: 33370 +Test: [1800/2573] eta: 0:00:58 time: 0.0753 data: 0.0011 max mem: 33370 +Test: [1900/2573] eta: 0:00:50 time: 0.0721 data: 0.0011 max mem: 33370 +Test: [2000/2573] eta: 0:00:43 time: 0.0739 data: 0.0011 max mem: 33370 +Test: [2100/2573] eta: 0:00:35 time: 0.0756 data: 0.0011 max mem: 33370 +Test: [2200/2573] eta: 0:00:27 time: 0.0754 data: 0.0011 max mem: 33370 +Test: [2300/2573] eta: 0:00:20 time: 0.0755 data: 0.0011 max mem: 33370 +Test: [2400/2573] eta: 0:00:12 time: 0.0704 data: 0.0011 max mem: 33370 +Test: [2500/2573] eta: 0:00:05 time: 0.0740 data: 0.0012 max mem: 33370 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: Total time: 0:03:12 +Final results: +Mean IoU is 64.51 + + precision@0.5 = 72.73 + precision@0.6 = 68.12 + precision@0.7 = 60.72 + precision@0.8 = 49.57 + precision@0.9 = 25.08 + overall IoU = 61.98 + +Average object IoU 64.51224507985683 +Overall IoU 61.980445861816406 +Better epoch: 31 + +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [32] [ 0/1319] eta: 1:25:26 lr: 1.1745187571461855e-05 loss: 0.0265 (0.0265) time: 3.8866 data: 1.1962 max mem: 33370 +Epoch: [32] [ 10/1319] eta: 1:00:40 lr: 1.1735168454865734e-05 loss: 0.0276 (0.0336) time: 2.7812 data: 0.1144 max mem: 33370 +Epoch: [32] [ 20/1319] eta: 0:58:46 lr: 1.1725148387734231e-05 loss: 0.0343 (0.0362) time: 2.6564 data: 0.0062 max mem: 33370 +Epoch: [32] [ 30/1319] eta: 0:57:44 lr: 1.1715127369074435e-05 loss: 0.0343 (0.0353) time: 2.6359 data: 0.0064 max mem: 33370 +Epoch: [32] [ 40/1319] eta: 0:57:04 lr: 1.1705105397891451e-05 loss: 0.0331 (0.0347) time: 2.6386 data: 0.0066 max mem: 33370 +Epoch: [32] [ 50/1319] eta: 0:56:25 lr: 1.1695082473188386e-05 loss: 0.0328 (0.0352) time: 2.6383 data: 0.0065 max mem: 33370 +Epoch: [32] [ 60/1319] eta: 0:55:49 lr: 1.1685058593966367e-05 loss: 0.0317 (0.0344) time: 2.6245 data: 0.0067 max mem: 33370 +Epoch: [32] [ 70/1319] eta: 0:55:15 lr: 1.1675033759224512e-05 loss: 0.0281 (0.0337) time: 2.6207 data: 0.0067 max mem: 33370 +Epoch: [32] [ 80/1319] eta: 0:54:44 lr: 1.1665007967959945e-05 loss: 0.0318 (0.0349) time: 2.6220 data: 0.0065 max mem: 33370 +Epoch: [32] [ 90/1319] eta: 0:54:19 lr: 1.1654981219167763e-05 loss: 0.0397 (0.0354) time: 2.6441 data: 0.0066 max mem: 33370 +Epoch: [32] [ 100/1319] eta: 0:53:49 lr: 1.1644953511841062e-05 loss: 0.0347 (0.0352) time: 2.6449 data: 0.0067 max mem: 33370 +Epoch: [32] [ 110/1319] eta: 0:53:19 lr: 1.1634924844970898e-05 loss: 0.0319 (0.0348) time: 2.6183 data: 0.0066 max mem: 33370 +Epoch: [32] [ 120/1319] eta: 0:52:53 lr: 1.1624895217546308e-05 loss: 0.0327 (0.0349) time: 2.6338 data: 0.0065 max mem: 33370 +Epoch: [32] [ 130/1319] eta: 0:52:22 lr: 1.1614864628554293e-05 loss: 0.0345 (0.0357) time: 2.6257 data: 0.0063 max mem: 33370 +Epoch: [32] [ 140/1319] eta: 0:51:55 lr: 1.160483307697981e-05 loss: 0.0357 (0.0357) time: 2.6140 data: 0.0064 max mem: 33370 +Epoch: [32] [ 150/1319] eta: 0:51:30 lr: 1.159480056180578e-05 loss: 0.0309 (0.0355) time: 2.6461 data: 0.0065 max mem: 33370 +Epoch: [32] [ 160/1319] eta: 0:51:01 lr: 1.1584767082013038e-05 loss: 0.0322 (0.0358) time: 2.6321 data: 0.0064 max mem: 33370 +Epoch: [32] [ 170/1319] eta: 0:50:33 lr: 1.1574732636580395e-05 loss: 0.0322 (0.0357) time: 2.6109 data: 0.0063 max mem: 33370 +Epoch: [32] [ 180/1319] eta: 0:50:06 lr: 1.1564697224484583e-05 loss: 0.0302 (0.0355) time: 2.6251 data: 0.0063 max mem: 33370 +Epoch: [32] [ 190/1319] eta: 0:49:39 lr: 1.1554660844700256e-05 loss: 0.0302 (0.0357) time: 2.6299 data: 0.0063 max mem: 33370 +Epoch: [32] [ 200/1319] eta: 0:49:12 lr: 1.1544623496200004e-05 loss: 0.0326 (0.0358) time: 2.6345 data: 0.0064 max mem: 33370 +Epoch: [32] [ 210/1319] eta: 0:48:45 lr: 1.153458517795431e-05 loss: 0.0366 (0.0358) time: 2.6267 data: 0.0066 max mem: 33370 +Epoch: [32] [ 220/1319] eta: 0:48:18 lr: 1.1524545888931584e-05 loss: 0.0357 (0.0360) time: 2.6246 data: 0.0067 max mem: 33370 +Epoch: [32] [ 230/1319] eta: 0:47:50 lr: 1.1514505628098139e-05 loss: 0.0324 (0.0359) time: 2.6172 data: 0.0065 max mem: 33370 +Epoch: [32] [ 240/1319] eta: 0:47:22 lr: 1.1504464394418176e-05 loss: 0.0359 (0.0359) time: 2.6048 data: 0.0064 max mem: 33370 +Epoch: [32] [ 250/1319] eta: 0:46:56 lr: 1.149442218685379e-05 loss: 0.0339 (0.0360) time: 2.6212 data: 0.0064 max mem: 33370 +Epoch: [32] [ 260/1319] eta: 0:46:28 lr: 1.1484379004364971e-05 loss: 0.0272 (0.0356) time: 2.6109 data: 0.0063 max mem: 33370 +Epoch: [32] [ 270/1319] eta: 0:46:01 lr: 1.147433484590956e-05 loss: 0.0278 (0.0356) time: 2.6083 data: 0.0065 max mem: 33370 +Epoch: [32] [ 280/1319] eta: 0:45:36 lr: 1.1464289710443295e-05 loss: 0.0299 (0.0354) time: 2.6500 data: 0.0066 max mem: 33370 +Epoch: [32] [ 290/1319] eta: 0:45:11 lr: 1.1454243596919765e-05 loss: 0.0299 (0.0357) time: 2.6636 data: 0.0064 max mem: 33370 +Epoch: [32] [ 300/1319] eta: 0:44:44 lr: 1.144419650429042e-05 loss: 0.0324 (0.0357) time: 2.6444 data: 0.0064 max mem: 33370 +Epoch: [32] [ 310/1319] eta: 0:44:19 lr: 1.1434148431504575e-05 loss: 0.0323 (0.0357) time: 2.6496 data: 0.0064 max mem: 33370 +Epoch: [32] [ 320/1319] eta: 0:43:52 lr: 1.1424099377509363e-05 loss: 0.0323 (0.0357) time: 2.6420 data: 0.0065 max mem: 33370 +Epoch: [32] [ 330/1319] eta: 0:43:26 lr: 1.141404934124978e-05 loss: 0.0335 (0.0355) time: 2.6235 data: 0.0066 max mem: 33370 +Epoch: [32] [ 340/1319] eta: 0:42:58 lr: 1.140399832166864e-05 loss: 0.0335 (0.0355) time: 2.6096 data: 0.0066 max mem: 33370 +Epoch: [32] [ 350/1319] eta: 0:42:33 lr: 1.1393946317706594e-05 loss: 0.0328 (0.0355) time: 2.6335 data: 0.0066 max mem: 33370 +Epoch: [32] [ 360/1319] eta: 0:42:07 lr: 1.138389332830211e-05 loss: 0.0319 (0.0354) time: 2.6639 data: 0.0065 max mem: 33370 +Epoch: [32] [ 370/1319] eta: 0:41:40 lr: 1.1373839352391454e-05 loss: 0.0316 (0.0353) time: 2.6395 data: 0.0065 max mem: 33370 +Epoch: [32] [ 380/1319] eta: 0:41:14 lr: 1.1363784388908714e-05 loss: 0.0324 (0.0358) time: 2.6266 data: 0.0066 max mem: 33370 +Epoch: [32] [ 390/1319] eta: 0:40:48 lr: 1.1353728436785773e-05 loss: 0.0332 (0.0358) time: 2.6378 data: 0.0067 max mem: 33370 +Epoch: [32] [ 400/1319] eta: 0:40:22 lr: 1.1343671494952302e-05 loss: 0.0332 (0.0358) time: 2.6571 data: 0.0068 max mem: 33370 +Epoch: [32] [ 410/1319] eta: 0:39:55 lr: 1.1333613562335765e-05 loss: 0.0381 (0.0360) time: 2.6427 data: 0.0067 max mem: 33370 +Epoch: [32] [ 420/1319] eta: 0:39:28 lr: 1.1323554637861402e-05 loss: 0.0379 (0.0361) time: 2.6028 data: 0.0065 max mem: 33370 +Epoch: [32] [ 430/1319] eta: 0:39:02 lr: 1.1313494720452216e-05 loss: 0.0351 (0.0361) time: 2.6118 data: 0.0065 max mem: 33370 +Epoch: [32] [ 440/1319] eta: 0:38:35 lr: 1.1303433809028986e-05 loss: 0.0324 (0.0360) time: 2.6200 data: 0.0065 max mem: 33370 +Epoch: [32] [ 450/1319] eta: 0:38:07 lr: 1.1293371902510248e-05 loss: 0.0327 (0.0361) time: 2.5912 data: 0.0066 max mem: 33370 +Epoch: [32] [ 460/1319] eta: 0:37:40 lr: 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1.049524038345592e-05 loss: 0.0332 (0.0363) time: 2.6457 data: 0.0062 max mem: 33370 +Epoch: [32] [1250/1319] eta: 0:03:01 lr: 1.048509515332035e-05 loss: 0.0307 (0.0363) time: 2.6285 data: 0.0063 max mem: 33370 +Epoch: [32] [1260/1319] eta: 0:02:35 lr: 1.0474948832358245e-05 loss: 0.0326 (0.0363) time: 2.6177 data: 0.0064 max mem: 33370 +Epoch: [32] [1270/1319] eta: 0:02:08 lr: 1.0464801419278068e-05 loss: 0.0346 (0.0363) time: 2.6067 data: 0.0062 max mem: 33370 +Epoch: [32] [1280/1319] eta: 0:01:42 lr: 1.0454652912785337e-05 loss: 0.0327 (0.0363) time: 2.6296 data: 0.0062 max mem: 33370 +Epoch: [32] [1290/1319] eta: 0:01:16 lr: 1.0444503311582662e-05 loss: 0.0325 (0.0363) time: 2.6597 data: 0.0065 max mem: 33370 +Epoch: [32] [1300/1319] eta: 0:00:50 lr: 1.0434352614369702e-05 loss: 0.0324 (0.0363) time: 2.6425 data: 0.0064 max mem: 33370 +Epoch: [32] [1310/1319] eta: 0:00:23 lr: 1.0424200819843158e-05 loss: 0.0325 (0.0363) time: 2.6219 data: 0.0062 max mem: 33370 +Epoch: [32] Total time: 0:57:52 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 2:01:48 time: 2.8404 data: 2.6635 max mem: 33370 +Test: [ 100/2573] eta: 0:04:05 time: 0.0713 data: 0.0011 max mem: 33370 +Test: [ 200/2573] eta: 0:03:25 time: 0.0732 data: 0.0011 max mem: 33370 +Test: [ 300/2573] eta: 0:03:05 time: 0.0749 data: 0.0011 max mem: 33370 +Test: [ 400/2573] eta: 0:02:52 time: 0.0752 data: 0.0010 max mem: 33370 +Test: [ 500/2573] eta: 0:02:42 time: 0.0735 data: 0.0011 max mem: 33370 +Test: [ 600/2573] eta: 0:02:33 time: 0.0736 data: 0.0011 max mem: 33370 +Test: [ 700/2573] eta: 0:02:25 time: 0.0737 data: 0.0011 max mem: 33370 +Test: [ 800/2573] eta: 0:02:16 time: 0.0770 data: 0.0011 max mem: 33370 +Test: [ 900/2573] eta: 0:02:08 time: 0.0737 data: 0.0011 max mem: 33370 +Test: [1000/2573] eta: 0:02:00 time: 0.0738 data: 0.0011 max mem: 33370 +Test: [1100/2573] eta: 0:01:52 time: 0.0738 data: 0.0011 max mem: 33370 +Test: [1200/2573] eta: 0:01:44 time: 0.0737 data: 0.0011 max mem: 33370 +Test: [1300/2573] eta: 0:01:36 time: 0.0739 data: 0.0011 max mem: 33370 +Test: [1400/2573] eta: 0:01:28 time: 0.0722 data: 0.0011 max mem: 33370 +Test: [1500/2573] eta: 0:01:21 time: 0.0738 data: 0.0011 max mem: 33370 +Test: [1600/2573] eta: 0:01:13 time: 0.0771 data: 0.0011 max mem: 33370 +Test: [1700/2573] eta: 0:01:05 time: 0.0722 data: 0.0011 max mem: 33370 +Test: [1800/2573] eta: 0:00:58 time: 0.0755 data: 0.0011 max mem: 33370 +Test: [1900/2573] eta: 0:00:50 time: 0.0721 data: 0.0011 max mem: 33370 +Test: [2000/2573] eta: 0:00:43 time: 0.0737 data: 0.0011 max mem: 33370 +Test: [2100/2573] eta: 0:00:35 time: 0.0754 data: 0.0011 max mem: 33370 +Test: [2200/2573] eta: 0:00:27 time: 0.0753 data: 0.0011 max mem: 33370 +Test: [2300/2573] eta: 0:00:20 time: 0.0754 data: 0.0011 max mem: 33370 +Test: [2400/2573] eta: 0:00:12 time: 0.0705 data: 0.0011 max mem: 33370 +Test: [2500/2573] eta: 0:00:05 time: 0.0738 data: 0.0011 max mem: 33370 +Test: Total time: 0:03:12 +Final results: +Mean IoU is 64.61 + + precision@0.5 = 72.96 + precision@0.6 = 67.73 + precision@0.7 = 61.07 + precision@0.8 = 49.80 + precision@0.9 = 25.27 + overall IoU = 62.29 + +Average object IoU 64.60860288366864 +Overall IoU 62.29314041137695 +Better epoch: 32 + +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [33] [ 0/1319] eta: 1:22:47 lr: 1.04150632654866e-05 loss: 0.0262 (0.0262) time: 3.7658 data: 1.1421 max mem: 33370 +Epoch: [33] [ 10/1319] eta: 0:58:59 lr: 1.0404909382463066e-05 loss: 0.0289 (0.0322) time: 2.7037 data: 0.1096 max mem: 33370 +Epoch: [33] [ 20/1319] eta: 0:57:28 lr: 1.0394754398329612e-05 loss: 0.0342 (0.0363) time: 2.5989 data: 0.0063 max mem: 33370 +Epoch: [33] [ 30/1319] eta: 0:56:53 lr: 1.0384598311771345e-05 loss: 0.0349 (0.0346) time: 2.6178 data: 0.0064 max mem: 33370 +Epoch: [33] [ 40/1319] eta: 0:56:33 lr: 1.0374441121470351e-05 loss: 0.0341 (0.0344) time: 2.6525 data: 0.0065 max mem: 33370 +Epoch: [33] [ 50/1319] eta: 0:56:02 lr: 1.0364282826105723e-05 loss: 0.0323 (0.0353) time: 2.6528 data: 0.0067 max mem: 33370 +Epoch: [33] [ 60/1319] eta: 0:55:28 lr: 1.0354123424353528e-05 loss: 0.0326 (0.0358) time: 2.6235 data: 0.0068 max mem: 33370 +Epoch: [33] [ 70/1319] eta: 0:55:03 lr: 1.0343962914886797e-05 loss: 0.0344 (0.0362) time: 2.6332 data: 0.0065 max mem: 33370 +Epoch: [33] [ 80/1319] eta: 0:54:34 lr: 1.033380129637553e-05 loss: 0.0334 (0.0359) time: 2.6394 data: 0.0065 max mem: 33370 +Epoch: [33] [ 90/1319] eta: 0:54:06 lr: 1.0323638567486653e-05 loss: 0.0308 (0.0357) time: 2.6267 data: 0.0066 max mem: 33370 +Epoch: [33] [ 100/1319] eta: 0:53:42 lr: 1.0313474726884054e-05 loss: 0.0331 (0.0361) time: 2.6461 data: 0.0065 max mem: 33370 +Epoch: [33] [ 110/1319] eta: 0:53:14 lr: 1.0303309773228537e-05 loss: 0.0345 (0.0373) time: 2.6469 data: 0.0064 max mem: 33370 +Epoch: [33] [ 120/1319] eta: 0:52:45 lr: 1.0293143705177821e-05 loss: 0.0319 (0.0374) time: 2.6254 data: 0.0064 max mem: 33370 +Epoch: [33] [ 130/1319] eta: 0:52:14 lr: 1.0282976521386539e-05 loss: 0.0305 (0.0373) time: 2.6004 data: 0.0065 max mem: 33370 +Epoch: [33] [ 140/1319] eta: 0:51:46 lr: 1.0272808220506222e-05 loss: 0.0305 (0.0370) time: 2.6043 data: 0.0065 max mem: 33370 +Epoch: [33] [ 150/1319] eta: 0:51:17 lr: 1.026263880118526e-05 loss: 0.0317 (0.0368) time: 2.6115 data: 0.0066 max mem: 33370 +Epoch: [33] [ 160/1319] eta: 0:50:54 lr: 1.0252468262068951e-05 loss: 0.0317 (0.0366) time: 2.6395 data: 0.0066 max mem: 33370 +Epoch: [33] [ 170/1319] eta: 0:50:30 lr: 1.024229660179944e-05 loss: 0.0325 (0.0368) time: 2.6781 data: 0.0064 max mem: 33370 +Epoch: [33] [ 180/1319] eta: 0:50:03 lr: 1.023212381901573e-05 loss: 0.0335 (0.0365) time: 2.6427 data: 0.0064 max mem: 33370 +Epoch: [33] [ 190/1319] eta: 0:49:37 lr: 1.0221949912353669e-05 loss: 0.0375 (0.0366) time: 2.6285 data: 0.0064 max mem: 33370 +Epoch: [33] [ 200/1319] eta: 0:49:09 lr: 1.0211774880445919e-05 loss: 0.0321 (0.0365) time: 2.6339 data: 0.0064 max mem: 33370 +Epoch: [33] [ 210/1319] eta: 0:48:44 lr: 1.0201598721921983e-05 loss: 0.0321 (0.0365) time: 2.6344 data: 0.0064 max mem: 33370 +Epoch: [33] [ 220/1319] eta: 0:48:18 lr: 1.0191421435408169e-05 loss: 0.0353 (0.0366) time: 2.6490 data: 0.0065 max mem: 33370 +Epoch: [33] [ 230/1319] eta: 0:47:50 lr: 1.0181243019527578e-05 loss: 0.0320 (0.0366) time: 2.6230 data: 0.0065 max mem: 33370 +Epoch: [33] [ 240/1319] eta: 0:47:23 lr: 1.0171063472900106e-05 loss: 0.0287 (0.0364) time: 2.6085 data: 0.0063 max mem: 33370 +Epoch: [33] [ 250/1319] eta: 0:46:57 lr: 1.0160882794142423e-05 loss: 0.0287 (0.0364) time: 2.6407 data: 0.0063 max mem: 33370 +Epoch: [33] [ 260/1319] eta: 0:46:29 lr: 1.0150700981867957e-05 loss: 0.0330 (0.0368) time: 2.6272 data: 0.0065 max mem: 33370 +Epoch: [33] [ 270/1319] eta: 0:46:03 lr: 1.01405180346869e-05 loss: 0.0337 (0.0367) time: 2.6132 data: 0.0065 max mem: 33370 +Epoch: [33] [ 280/1319] eta: 0:45:36 lr: 1.0130333951206182e-05 loss: 0.0303 (0.0365) time: 2.6287 data: 0.0064 max mem: 33370 +Epoch: [33] [ 290/1319] eta: 0:45:11 lr: 1.0120148730029472e-05 loss: 0.0296 (0.0363) time: 2.6444 data: 0.0065 max mem: 33370 +Epoch: [33] [ 300/1319] eta: 0:44:42 lr: 1.0109962369757157e-05 loss: 0.0300 (0.0362) time: 2.6117 data: 0.0068 max mem: 33370 +Epoch: [33] [ 310/1319] eta: 0:44:16 lr: 1.0099774868986322e-05 loss: 0.0305 (0.0360) time: 2.6073 data: 0.0067 max mem: 33370 +Epoch: [33] [ 320/1319] eta: 0:43:48 lr: 1.008958622631076e-05 loss: 0.0262 (0.0359) time: 2.6126 data: 0.0065 max mem: 33370 +Epoch: [33] [ 330/1319] eta: 0:43:22 lr: 1.0079396440320953e-05 loss: 0.0339 (0.0361) time: 2.5977 data: 0.0065 max mem: 33370 +Epoch: [33] [ 340/1319] eta: 0:42:54 lr: 1.0069205509604051e-05 loss: 0.0380 (0.0360) time: 2.5972 data: 0.0066 max mem: 33370 +Epoch: [33] [ 350/1319] eta: 0:42:27 lr: 1.0059013432743876e-05 loss: 0.0320 (0.0359) time: 2.5863 data: 0.0066 max mem: 33370 +Epoch: [33] [ 360/1319] eta: 0:42:01 lr: 1.0048820208320883e-05 loss: 0.0320 (0.0358) time: 2.6244 data: 0.0064 max mem: 33370 +Epoch: [33] [ 370/1319] eta: 0:41:35 lr: 1.0038625834912186e-05 loss: 0.0318 (0.0357) time: 2.6548 data: 0.0063 max mem: 33370 +Epoch: [33] [ 380/1319] eta: 0:41:10 lr: 1.0028430311091521e-05 loss: 0.0322 (0.0356) time: 2.6702 data: 0.0063 max mem: 33370 +Epoch: [33] [ 390/1319] eta: 0:40:44 lr: 1.0018233635429235e-05 loss: 0.0331 (0.0357) time: 2.6515 data: 0.0065 max mem: 33370 +Epoch: [33] [ 400/1319] eta: 0:40:18 lr: 1.0008035806492287e-05 loss: 0.0316 (0.0356) time: 2.6360 data: 0.0065 max mem: 33370 +Epoch: [33] [ 410/1319] eta: 0:39:52 lr: 9.99783682284423e-06 loss: 0.0324 (0.0356) time: 2.6530 data: 0.0065 max mem: 33370 +Epoch: [33] [ 420/1319] eta: 0:39:25 lr: 9.987636683045179e-06 loss: 0.0341 (0.0355) time: 2.6335 data: 0.0065 max mem: 33370 +Epoch: [33] [ 430/1319] eta: 0:38:59 lr: 9.977435385651839e-06 loss: 0.0329 (0.0354) time: 2.6223 data: 0.0066 max mem: 33370 +Epoch: [33] [ 440/1319] eta: 0:38:33 lr: 9.967232929217462e-06 loss: 0.0293 (0.0353) time: 2.6424 data: 0.0067 max mem: 33370 +Epoch: [33] [ 450/1319] eta: 0:38:07 lr: 9.957029312291845e-06 loss: 0.0293 (0.0355) time: 2.6509 data: 0.0065 max mem: 33370 +Epoch: [33] [ 460/1319] eta: 0:37:41 lr: 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eta: 0:34:10 lr: 9.865144296845656e-06 loss: 0.0334 (0.0358) time: 2.6786 data: 0.0064 max mem: 33370 +Epoch: [33] [ 550/1319] eta: 0:33:44 lr: 9.85492899447742e-06 loss: 0.0352 (0.0359) time: 2.6626 data: 0.0064 max mem: 33370 +Epoch: [33] [ 560/1319] eta: 0:33:18 lr: 9.844712515434104e-06 loss: 0.0302 (0.0358) time: 2.6237 data: 0.0064 max mem: 33370 +Epoch: [33] [ 570/1319] eta: 0:32:52 lr: 9.83449485822307e-06 loss: 0.0306 (0.0358) time: 2.6622 data: 0.0064 max mem: 33370 +Epoch: [33] [ 580/1319] eta: 0:32:26 lr: 9.824276021348049e-06 loss: 0.0330 (0.0357) time: 2.6753 data: 0.0063 max mem: 33370 +Epoch: [33] [ 590/1319] eta: 0:32:00 lr: 9.814056003309152e-06 loss: 0.0313 (0.0358) time: 2.6403 data: 0.0064 max mem: 33370 +Epoch: [33] [ 600/1319] eta: 0:31:33 lr: 9.803834802602848e-06 loss: 0.0316 (0.0357) time: 2.6385 data: 0.0065 max mem: 33370 +Epoch: [33] [ 610/1319] eta: 0:31:07 lr: 9.793612417721937e-06 loss: 0.0322 (0.0358) time: 2.6265 data: 0.0065 max mem: 33370 +Epoch: 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mem: 33370 +Epoch: [33] [ 700/1319] eta: 0:27:10 lr: 9.701557415421759e-06 loss: 0.0320 (0.0355) time: 2.6345 data: 0.0064 max mem: 33370 +Epoch: [33] [ 710/1319] eta: 0:26:44 lr: 9.69132310508487e-06 loss: 0.0341 (0.0356) time: 2.6713 data: 0.0063 max mem: 33370 +Epoch: [33] [ 720/1319] eta: 0:26:18 lr: 9.681087593749006e-06 loss: 0.0335 (0.0356) time: 2.6707 data: 0.0062 max mem: 33370 +Epoch: [33] [ 730/1319] eta: 0:25:52 lr: 9.670850879862032e-06 loss: 0.0313 (0.0356) time: 2.6665 data: 0.0063 max mem: 33370 +Epoch: [33] [ 740/1319] eta: 0:25:26 lr: 9.660612961867972e-06 loss: 0.0307 (0.0355) time: 2.6976 data: 0.0064 max mem: 33370 +Epoch: [33] [ 750/1319] eta: 0:25:00 lr: 9.650373838207014e-06 loss: 0.0307 (0.0356) time: 2.6706 data: 0.0063 max mem: 33370 +Epoch: [33] [ 760/1319] eta: 0:24:33 lr: 9.640133507315477e-06 loss: 0.0333 (0.0356) time: 2.6326 data: 0.0063 max mem: 33370 +Epoch: [33] [ 770/1319] eta: 0:24:07 lr: 9.62989196762581e-06 loss: 0.0356 (0.0356) time: 2.6296 data: 0.0066 max mem: 33370 +Epoch: [33] [ 780/1319] eta: 0:23:41 lr: 9.61964921756657e-06 loss: 0.0337 (0.0356) time: 2.6458 data: 0.0066 max mem: 33370 +Epoch: [33] [ 790/1319] eta: 0:23:15 lr: 9.609405255562397e-06 loss: 0.0298 (0.0355) time: 2.6700 data: 0.0065 max mem: 33370 +Epoch: [33] [ 800/1319] eta: 0:22:49 lr: 9.599160080034027e-06 loss: 0.0294 (0.0355) time: 2.6795 data: 0.0064 max mem: 33370 +Epoch: [33] [ 810/1319] eta: 0:22:22 lr: 9.588913689398257e-06 loss: 0.0287 (0.0354) time: 2.6449 data: 0.0063 max mem: 33370 +Epoch: [33] [ 820/1319] eta: 0:21:56 lr: 9.578666082067937e-06 loss: 0.0259 (0.0354) time: 2.6312 data: 0.0063 max mem: 33370 +Epoch: [33] [ 830/1319] eta: 0:21:29 lr: 9.568417256451955e-06 loss: 0.0328 (0.0354) time: 2.6422 data: 0.0065 max mem: 33370 +Epoch: [33] [ 840/1319] eta: 0:21:03 lr: 9.558167210955227e-06 loss: 0.0360 (0.0354) time: 2.6479 data: 0.0065 max mem: 33370 +Epoch: [33] [ 850/1319] eta: 0:20:36 lr: 9.547915943978656e-06 loss: 0.0371 (0.0354) time: 2.6123 data: 0.0064 max mem: 33370 +Epoch: [33] [ 860/1319] eta: 0:20:10 lr: 9.537663453919165e-06 loss: 0.0375 (0.0354) time: 2.6344 data: 0.0064 max mem: 33370 +Epoch: [33] [ 870/1319] eta: 0:19:44 lr: 9.52740973916964e-06 loss: 0.0350 (0.0354) time: 2.6578 data: 0.0064 max mem: 33370 +Epoch: [33] [ 880/1319] eta: 0:19:18 lr: 9.517154798118936e-06 loss: 0.0295 (0.0353) time: 2.6452 data: 0.0063 max mem: 33370 +Epoch: [33] [ 890/1319] eta: 0:18:51 lr: 9.506898629151863e-06 loss: 0.0338 (0.0356) time: 2.6429 data: 0.0063 max mem: 33370 +Epoch: [33] [ 900/1319] eta: 0:18:25 lr: 9.496641230649144e-06 loss: 0.0371 (0.0356) time: 2.6579 data: 0.0063 max mem: 33370 +Epoch: [33] [ 910/1319] eta: 0:17:58 lr: 9.48638260098744e-06 loss: 0.0323 (0.0355) time: 2.6433 data: 0.0065 max mem: 33370 +Epoch: [33] [ 920/1319] eta: 0:17:32 lr: 9.476122738539313e-06 loss: 0.0286 (0.0354) time: 2.6143 data: 0.0065 max mem: 33370 +Epoch: [33] [ 930/1319] eta: 0:17:06 lr: 9.465861641673206e-06 loss: 0.0288 (0.0354) time: 2.6565 data: 0.0064 max mem: 33370 +Epoch: [33] [ 940/1319] eta: 0:16:40 lr: 9.455599308753445e-06 loss: 0.0306 (0.0354) time: 2.6668 data: 0.0065 max mem: 33370 +Epoch: [33] [ 950/1319] eta: 0:16:13 lr: 9.445335738140192e-06 loss: 0.0349 (0.0354) time: 2.6532 data: 0.0065 max mem: 33370 +Epoch: [33] [ 960/1319] eta: 0:15:47 lr: 9.435070928189476e-06 loss: 0.0349 (0.0354) time: 2.6616 data: 0.0065 max mem: 33370 +Epoch: [33] [ 970/1319] eta: 0:15:21 lr: 9.424804877253139e-06 loss: 0.0326 (0.0353) time: 2.6588 data: 0.0064 max mem: 33370 +Epoch: [33] [ 980/1319] eta: 0:14:54 lr: 9.414537583678836e-06 loss: 0.0330 (0.0354) time: 2.6285 data: 0.0065 max mem: 33370 +Epoch: [33] [ 990/1319] eta: 0:14:28 lr: 9.404269045810016e-06 loss: 0.0345 (0.0354) time: 2.6218 data: 0.0066 max mem: 33370 +Epoch: [33] [1000/1319] eta: 0:14:01 lr: 9.393999261985916e-06 loss: 0.0358 (0.0354) time: 2.6483 data: 0.0065 max mem: 33370 +Epoch: [33] [1010/1319] eta: 0:13:35 lr: 9.383728230541512e-06 loss: 0.0316 (0.0354) time: 2.6564 data: 0.0066 max mem: 33370 +Epoch: [33] [1020/1319] eta: 0:13:09 lr: 9.373455949807552e-06 loss: 0.0298 (0.0353) time: 2.6610 data: 0.0065 max mem: 33370 +Epoch: [33] [1030/1319] eta: 0:12:42 lr: 9.363182418110507e-06 loss: 0.0288 (0.0353) time: 2.6554 data: 0.0064 max mem: 33370 +Epoch: [33] [1040/1319] eta: 0:12:16 lr: 9.352907633772557e-06 loss: 0.0274 (0.0353) time: 2.6305 data: 0.0063 max mem: 33370 +Epoch: [33] [1050/1319] eta: 0:11:50 lr: 9.342631595111597e-06 loss: 0.0342 (0.0353) time: 2.6404 data: 0.0063 max mem: 33370 +Epoch: [33] [1060/1319] eta: 0:11:23 lr: 9.332354300441178e-06 loss: 0.0371 (0.0354) time: 2.6250 data: 0.0064 max mem: 33370 +Epoch: [33] [1070/1319] eta: 0:10:57 lr: 9.322075748070539e-06 loss: 0.0311 (0.0354) time: 2.6103 data: 0.0064 max mem: 33370 +Epoch: [33] [1080/1319] eta: 0:10:30 lr: 9.311795936304561e-06 loss: 0.0290 (0.0353) time: 2.6266 data: 0.0064 max mem: 33370 +Epoch: [33] [1090/1319] eta: 0:10:04 lr: 9.301514863443759e-06 loss: 0.0354 (0.0354) time: 2.6227 data: 0.0063 max mem: 33370 +Epoch: [33] [1100/1319] eta: 0:09:37 lr: 9.291232527784269e-06 loss: 0.0365 (0.0355) time: 2.6310 data: 0.0063 max mem: 33370 +Epoch: [33] [1110/1319] eta: 0:09:11 lr: 9.280948927617811e-06 loss: 0.0376 (0.0355) time: 2.6189 data: 0.0063 max mem: 33370 +Epoch: [33] [1120/1319] eta: 0:08:44 lr: 9.270664061231702e-06 loss: 0.0376 (0.0355) time: 2.6062 data: 0.0064 max mem: 33370 +Epoch: [33] [1130/1319] eta: 0:08:18 lr: 9.260377926908826e-06 loss: 0.0326 (0.0355) time: 2.6600 data: 0.0064 max mem: 33370 +Epoch: [33] [1140/1319] eta: 0:07:52 lr: 9.250090522927605e-06 loss: 0.0326 (0.0356) time: 2.6822 data: 0.0065 max mem: 33370 +Epoch: [33] [1150/1319] eta: 0:07:25 lr: 9.239801847562006e-06 loss: 0.0332 (0.0356) time: 2.6517 data: 0.0065 max mem: 33370 +Epoch: [33] [1160/1319] eta: 0:06:59 lr: 9.229511899081506e-06 loss: 0.0297 (0.0355) time: 2.6352 data: 0.0064 max mem: 33370 +Epoch: [33] [1170/1319] eta: 0:06:33 lr: 9.219220675751069e-06 loss: 0.0286 (0.0355) time: 2.6220 data: 0.0064 max mem: 33370 +Epoch: [33] [1180/1319] eta: 0:06:06 lr: 9.20892817583115e-06 loss: 0.0298 (0.0354) time: 2.6270 data: 0.0064 max mem: 33370 +Epoch: [33] [1190/1319] eta: 0:05:40 lr: 9.19863439757767e-06 loss: 0.0314 (0.0354) time: 2.6347 data: 0.0065 max mem: 33370 +Epoch: [33] [1200/1319] eta: 0:05:13 lr: 9.188339339241987e-06 loss: 0.0328 (0.0354) time: 2.6413 data: 0.0066 max mem: 33370 +Epoch: [33] [1210/1319] eta: 0:04:47 lr: 9.178042999070898e-06 loss: 0.0324 (0.0354) time: 2.6368 data: 0.0065 max mem: 33370 +Epoch: [33] [1220/1319] eta: 0:04:21 lr: 9.16774537530659e-06 loss: 0.0334 (0.0354) time: 2.6161 data: 0.0064 max mem: 33370 +Epoch: [33] [1230/1319] eta: 0:03:54 lr: 9.157446466186662e-06 loss: 0.0338 (0.0354) time: 2.6112 data: 0.0064 max mem: 33370 +Epoch: [33] [1240/1319] eta: 0:03:28 lr: 9.147146269944078e-06 loss: 0.0336 (0.0354) time: 2.6299 data: 0.0064 max mem: 33370 +Epoch: [33] [1250/1319] eta: 0:03:02 lr: 9.136844784807162e-06 loss: 0.0323 (0.0354) time: 2.6251 data: 0.0065 max mem: 33370 +Epoch: [33] [1260/1319] eta: 0:02:35 lr: 9.126542008999582e-06 loss: 0.0327 (0.0354) time: 2.6277 data: 0.0065 max mem: 33370 +Epoch: [33] [1270/1319] eta: 0:02:09 lr: 9.11623794074031e-06 loss: 0.0308 (0.0353) time: 2.6526 data: 0.0064 max mem: 33370 +Epoch: [33] [1280/1319] eta: 0:01:42 lr: 9.105932578243631e-06 loss: 0.0299 (0.0353) time: 2.6520 data: 0.0064 max mem: 33370 +Epoch: [33] [1290/1319] eta: 0:01:16 lr: 9.095625919719118e-06 loss: 0.0335 (0.0354) time: 2.6482 data: 0.0065 max mem: 33370 +Epoch: [33] [1300/1319] eta: 0:00:50 lr: 9.085317963371604e-06 loss: 0.0383 (0.0354) time: 2.6613 data: 0.0065 max mem: 33370 +Epoch: [33] [1310/1319] eta: 0:00:23 lr: 9.075008707401167e-06 loss: 0.0352 (0.0354) time: 2.6771 data: 0.0063 max mem: 33370 +Epoch: [33] Total time: 0:58:00 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 2:02:02 time: 2.8460 data: 2.6899 max mem: 33370 +Test: [ 100/2573] eta: 0:04:05 time: 0.0714 data: 0.0011 max mem: 33370 +Test: [ 200/2573] eta: 0:03:25 time: 0.0732 data: 0.0011 max mem: 33370 +Test: [ 300/2573] eta: 0:03:05 time: 0.0750 data: 0.0011 max mem: 33370 +Test: [ 400/2573] eta: 0:02:53 time: 0.0751 data: 0.0011 max mem: 33370 +Test: [ 500/2573] eta: 0:02:42 time: 0.0735 data: 0.0011 max mem: 33370 +Test: [ 600/2573] eta: 0:02:33 time: 0.0736 data: 0.0011 max mem: 33370 +Test: [ 700/2573] eta: 0:02:25 time: 0.0738 data: 0.0011 max mem: 33370 +Test: [ 800/2573] eta: 0:02:16 time: 0.0770 data: 0.0011 max mem: 33370 +Test: [ 900/2573] eta: 0:02:08 time: 0.0737 data: 0.0011 max mem: 33370 +Test: [1000/2573] eta: 0:02:00 time: 0.0737 data: 0.0011 max mem: 33370 +Test: [1100/2573] eta: 0:01:52 time: 0.0739 data: 0.0011 max mem: 33370 +Test: [1200/2573] eta: 0:01:44 time: 0.0737 data: 0.0011 max mem: 33370 +Test: [1300/2573] eta: 0:01:36 time: 0.0736 data: 0.0011 max mem: 33370 +Test: [1400/2573] eta: 0:01:28 time: 0.0720 data: 0.0011 max mem: 33370 +Test: [1500/2573] eta: 0:01:21 time: 0.0736 data: 0.0011 max mem: 33370 +Test: [1600/2573] eta: 0:01:13 time: 0.0769 data: 0.0011 max mem: 33370 +Test: [1700/2573] eta: 0:01:05 time: 0.0720 data: 0.0011 max mem: 33370 +Test: [1800/2573] eta: 0:00:58 time: 0.0754 data: 0.0011 max mem: 33370 +Test: [1900/2573] eta: 0:00:50 time: 0.0722 data: 0.0011 max mem: 33370 +Test: [2000/2573] eta: 0:00:43 time: 0.0737 data: 0.0011 max mem: 33370 +Test: [2100/2573] eta: 0:00:35 time: 0.0753 data: 0.0011 max mem: 33370 +Test: [2200/2573] eta: 0:00:27 time: 0.0754 data: 0.0011 max mem: 33370 +Test: [2300/2573] eta: 0:00:20 time: 0.0753 data: 0.0011 max mem: 33370 +Test: [2400/2573] eta: 0:00:12 time: 0.0705 data: 0.0011 max mem: 33370 +Test: [2500/2573] eta: 0:00:05 time: 0.0738 data: 0.0011 max mem: 33370 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: Total time: 0:03:12 +Final results: +Mean IoU is 64.76 + + precision@0.5 = 72.94 + precision@0.6 = 67.83 + precision@0.7 = 61.19 + precision@0.8 = 49.84 + precision@0.9 = 25.35 + overall IoU = 62.44 + +Average object IoU 64.75586913204879 +Overall IoU 62.43680953979492 +Better epoch: 33 + +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [34] [ 0/1319] eta: 1:25:03 lr: 9.065729264358701e-06 loss: 0.0238 (0.0238) time: 3.8692 data: 1.2339 max mem: 33370 +Epoch: [34] [ 10/1319] eta: 0:59:54 lr: 9.05541753412883e-06 loss: 0.0253 (0.0312) time: 2.7459 data: 0.1182 max mem: 33370 +Epoch: [34] [ 20/1319] eta: 0:58:00 lr: 9.045104499029229e-06 loss: 0.0346 (0.0338) time: 2.6200 data: 0.0064 max mem: 33370 +Epoch: [34] [ 30/1319] eta: 0:57:35 lr: 9.03479015724125e-06 loss: 0.0346 (0.0342) time: 2.6451 data: 0.0063 max mem: 33370 +Epoch: [34] [ 40/1319] eta: 0:56:44 lr: 9.024474506941415e-06 loss: 0.0306 (0.0333) time: 2.6435 data: 0.0064 max mem: 33370 +Epoch: [34] [ 50/1319] eta: 0:56:03 lr: 9.014157546301385e-06 loss: 0.0301 (0.0336) time: 2.6037 data: 0.0065 max mem: 33370 +Epoch: [34] [ 60/1319] eta: 0:55:40 lr: 9.003839273487931e-06 loss: 0.0334 (0.0335) time: 2.6345 data: 0.0066 max mem: 33370 +Epoch: [34] [ 70/1319] eta: 0:55:14 lr: 8.99351968666293e-06 loss: 0.0334 (0.0340) time: 2.6625 data: 0.0065 max mem: 33370 +Epoch: [34] [ 80/1319] eta: 0:54:45 lr: 8.983198783983315e-06 loss: 0.0350 (0.0342) time: 2.6474 data: 0.0066 max mem: 33370 +Epoch: [34] [ 90/1319] eta: 0:54:12 lr: 8.972876563601101e-06 loss: 0.0347 (0.0340) time: 2.6199 data: 0.0066 max mem: 33370 +Epoch: [34] [ 100/1319] eta: 0:53:43 lr: 8.962553023663333e-06 loss: 0.0304 (0.0343) time: 2.6172 data: 0.0066 max mem: 33370 +Epoch: [34] [ 110/1319] eta: 0:53:19 lr: 8.952228162312077e-06 loss: 0.0312 (0.0349) time: 2.6455 data: 0.0066 max mem: 33370 +Epoch: [34] [ 120/1319] eta: 0:52:49 lr: 8.941901977684397e-06 loss: 0.0338 (0.0352) time: 2.6360 data: 0.0066 max mem: 33370 +Epoch: [34] [ 130/1319] eta: 0:52:20 lr: 8.93157446791234e-06 loss: 0.0360 (0.0359) time: 2.6114 data: 0.0068 max mem: 33370 +Epoch: [34] [ 140/1319] eta: 0:51:53 lr: 8.9212456311229e-06 loss: 0.0360 (0.0358) time: 2.6239 data: 0.0068 max mem: 33370 +Epoch: [34] [ 150/1319] eta: 0:51:26 lr: 8.910915465438025e-06 loss: 0.0333 (0.0360) time: 2.6339 data: 0.0066 max mem: 33370 +Epoch: [34] [ 160/1319] eta: 0:50:59 lr: 8.900583968974578e-06 loss: 0.0318 (0.0356) time: 2.6376 data: 0.0065 max mem: 33370 +Epoch: [34] [ 170/1319] eta: 0:50:33 lr: 8.89025113984432e-06 loss: 0.0303 (0.0353) time: 2.6405 data: 0.0065 max mem: 33370 +Epoch: [34] [ 180/1319] eta: 0:50:06 lr: 8.879916976153894e-06 loss: 0.0313 (0.0354) time: 2.6376 data: 0.0064 max mem: 33370 +Epoch: [34] [ 190/1319] eta: 0:49:38 lr: 8.869581476004788e-06 loss: 0.0325 (0.0355) time: 2.6190 data: 0.0066 max mem: 33370 +Epoch: [34] [ 200/1319] eta: 0:49:10 lr: 8.859244637493344e-06 loss: 0.0305 (0.0353) time: 2.6113 data: 0.0066 max mem: 33370 +Epoch: [34] [ 210/1319] eta: 0:48:44 lr: 8.84890645871071e-06 loss: 0.0305 (0.0354) time: 2.6281 data: 0.0065 max mem: 33370 +Epoch: [34] [ 220/1319] eta: 0:48:17 lr: 8.838566937742836e-06 loss: 0.0342 (0.0353) time: 2.6303 data: 0.0065 max mem: 33370 +Epoch: [34] [ 230/1319] eta: 0:47:48 lr: 8.828226072670449e-06 loss: 0.0289 (0.0351) time: 2.6034 data: 0.0066 max mem: 33370 +Epoch: [34] [ 240/1319] eta: 0:47:21 lr: 8.817883861569014e-06 loss: 0.0289 (0.0352) time: 2.6039 data: 0.0068 max mem: 33370 +Epoch: [34] [ 250/1319] eta: 0:46:57 lr: 8.807540302508743e-06 loss: 0.0333 (0.0353) time: 2.6525 data: 0.0067 max mem: 33370 +Epoch: [34] [ 260/1319] eta: 0:46:29 lr: 8.797195393554557e-06 loss: 0.0303 (0.0352) time: 2.6379 data: 0.0066 max mem: 33370 +Epoch: [34] [ 270/1319] eta: 0:46:03 lr: 8.786849132766063e-06 loss: 0.0300 (0.0350) time: 2.6157 data: 0.0067 max mem: 33370 +Epoch: [34] [ 280/1319] eta: 0:45:37 lr: 8.776501518197541e-06 loss: 0.0303 (0.0349) time: 2.6409 data: 0.0066 max mem: 33370 +Epoch: [34] [ 290/1319] eta: 0:45:09 lr: 8.76615254789792e-06 loss: 0.0325 (0.0351) time: 2.6219 data: 0.0067 max mem: 33370 +Epoch: [34] [ 300/1319] eta: 0:44:41 lr: 8.755802219910735e-06 loss: 0.0334 (0.0350) time: 2.5875 data: 0.0066 max mem: 33370 +Epoch: [34] [ 310/1319] eta: 0:44:14 lr: 8.745450532274145e-06 loss: 0.0330 (0.0351) time: 2.5995 data: 0.0064 max mem: 33370 +Epoch: [34] [ 320/1319] eta: 0:43:47 lr: 8.735097483020883e-06 loss: 0.0330 (0.0351) time: 2.6082 data: 0.0064 max mem: 33370 +Epoch: [34] [ 330/1319] eta: 0:43:21 lr: 8.724743070178239e-06 loss: 0.0353 (0.0356) time: 2.6237 data: 0.0066 max mem: 33370 +Epoch: [34] [ 340/1319] eta: 0:42:53 lr: 8.714387291768046e-06 loss: 0.0327 (0.0354) time: 2.6147 data: 0.0067 max mem: 33370 +Epoch: [34] [ 350/1319] eta: 0:42:27 lr: 8.704030145806636e-06 loss: 0.0277 (0.0353) time: 2.5948 data: 0.0066 max mem: 33370 +Epoch: [34] [ 360/1319] eta: 0:42:00 lr: 8.693671630304845e-06 loss: 0.0319 (0.0353) time: 2.6116 data: 0.0065 max mem: 33370 +Epoch: [34] [ 370/1319] eta: 0:41:35 lr: 8.683311743267978e-06 loss: 0.0316 (0.0351) time: 2.6528 data: 0.0065 max mem: 33370 +Epoch: [34] [ 380/1319] eta: 0:41:09 lr: 8.672950482695785e-06 loss: 0.0284 (0.0351) time: 2.6685 data: 0.0065 max mem: 33370 +Epoch: [34] [ 390/1319] eta: 0:40:43 lr: 8.662587846582436e-06 loss: 0.0295 (0.0351) time: 2.6417 data: 0.0065 max mem: 33370 +Epoch: [34] [ 400/1319] eta: 0:40:17 lr: 8.65222383291651e-06 loss: 0.0298 (0.0351) time: 2.6412 data: 0.0065 max mem: 33370 +Epoch: [34] [ 410/1319] eta: 0:39:51 lr: 8.641858439680947e-06 loss: 0.0307 (0.0351) time: 2.6472 data: 0.0065 max mem: 33370 +Epoch: [34] [ 420/1319] eta: 0:39:26 lr: 8.631491664853054e-06 loss: 0.0311 (0.0351) time: 2.6525 data: 0.0064 max mem: 33370 +Epoch: [34] [ 430/1319] eta: 0:38:59 lr: 8.621123506404469e-06 loss: 0.0311 (0.0351) time: 2.6364 data: 0.0063 max mem: 33370 +Epoch: [34] [ 440/1319] eta: 0:38:33 lr: 8.610753962301133e-06 loss: 0.0300 (0.0349) time: 2.6229 data: 0.0064 max mem: 33370 +Epoch: [34] [ 450/1319] eta: 0:38:06 lr: 8.600383030503278e-06 loss: 0.0318 (0.0352) time: 2.6202 data: 0.0065 max mem: 33370 +Epoch: [34] [ 460/1319] eta: 0:37:40 lr: 8.590010708965377e-06 loss: 0.0401 (0.0353) time: 2.6215 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0:27:07 lr: 8.340652648571916e-06 loss: 0.0327 (0.0345) time: 2.6362 data: 0.0063 max mem: 33370 +Epoch: [34] [ 710/1319] eta: 0:26:40 lr: 8.330244901449094e-06 loss: 0.0395 (0.0347) time: 2.6228 data: 0.0064 max mem: 33370 +Epoch: [34] [ 720/1319] eta: 0:26:15 lr: 8.319835709307101e-06 loss: 0.0353 (0.0346) time: 2.6350 data: 0.0065 max mem: 33370 +Epoch: [34] [ 730/1319] eta: 0:25:48 lr: 8.309425069935955e-06 loss: 0.0339 (0.0346) time: 2.6574 data: 0.0065 max mem: 33370 +Epoch: [34] [ 740/1319] eta: 0:25:22 lr: 8.299012981119228e-06 loss: 0.0337 (0.0346) time: 2.6470 data: 0.0064 max mem: 33370 +Epoch: [34] [ 750/1319] eta: 0:24:56 lr: 8.288599440633996e-06 loss: 0.0329 (0.0346) time: 2.6213 data: 0.0066 max mem: 33370 +Epoch: [34] [ 760/1319] eta: 0:24:29 lr: 8.278184446250822e-06 loss: 0.0296 (0.0346) time: 2.6167 data: 0.0065 max mem: 33370 +Epoch: [34] [ 770/1319] eta: 0:24:03 lr: 8.267767995733725e-06 loss: 0.0306 (0.0345) time: 2.6371 data: 0.0063 max mem: 33370 +Epoch: [34] [ 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+Epoch: [34] [ 860/1319] eta: 0:20:06 lr: 8.173954042838362e-06 loss: 0.0317 (0.0346) time: 2.5930 data: 0.0065 max mem: 33370 +Epoch: [34] [ 870/1319] eta: 0:19:39 lr: 8.163522906542168e-06 loss: 0.0317 (0.0346) time: 2.5987 data: 0.0065 max mem: 33370 +Epoch: [34] [ 880/1319] eta: 0:19:13 lr: 8.153090289075947e-06 loss: 0.0323 (0.0346) time: 2.6428 data: 0.0064 max mem: 33370 +Epoch: [34] [ 890/1319] eta: 0:18:47 lr: 8.142656188122887e-06 loss: 0.0323 (0.0345) time: 2.6654 data: 0.0065 max mem: 33370 +Epoch: [34] [ 900/1319] eta: 0:18:21 lr: 8.132220601359272e-06 loss: 0.0317 (0.0345) time: 2.6417 data: 0.0067 max mem: 33370 +Epoch: [34] [ 910/1319] eta: 0:17:55 lr: 8.121783526454415e-06 loss: 0.0301 (0.0346) time: 2.6214 data: 0.0065 max mem: 33370 +Epoch: [34] [ 920/1319] eta: 0:17:28 lr: 8.111344961070641e-06 loss: 0.0313 (0.0346) time: 2.6195 data: 0.0064 max mem: 33370 +Epoch: [34] [ 930/1319] eta: 0:17:02 lr: 8.100904902863262e-06 loss: 0.0307 (0.0345) time: 2.6168 data: 0.0066 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2.6399 data: 0.0064 max mem: 33370 +Epoch: [34] [1020/1319] eta: 0:13:06 lr: 8.006876811544029e-06 loss: 0.0280 (0.0344) time: 2.6547 data: 0.0064 max mem: 33370 +Epoch: [34] [1030/1319] eta: 0:12:39 lr: 7.996421694575264e-06 loss: 0.0277 (0.0344) time: 2.6736 data: 0.0064 max mem: 33370 +Epoch: [34] [1040/1319] eta: 0:12:13 lr: 7.985965058518847e-06 loss: 0.0320 (0.0344) time: 2.6560 data: 0.0063 max mem: 33370 +Epoch: [34] [1050/1319] eta: 0:11:47 lr: 7.97550690094334e-06 loss: 0.0349 (0.0345) time: 2.6352 data: 0.0063 max mem: 33370 +Epoch: [34] [1060/1319] eta: 0:11:21 lr: 7.965047219409881e-06 loss: 0.0342 (0.0345) time: 2.6469 data: 0.0065 max mem: 33370 +Epoch: [34] [1070/1319] eta: 0:10:54 lr: 7.95458601147213e-06 loss: 0.0319 (0.0344) time: 2.6692 data: 0.0064 max mem: 33370 +Epoch: [34] [1080/1319] eta: 0:10:28 lr: 7.944123274676236e-06 loss: 0.0345 (0.0345) time: 2.6858 data: 0.0062 max mem: 33370 +Epoch: [34] [1090/1319] eta: 0:10:02 lr: 7.933659006560817e-06 loss: 0.0342 (0.0345) time: 2.6777 data: 0.0064 max mem: 33370 +Epoch: [34] [1100/1319] eta: 0:09:36 lr: 7.923193204656895e-06 loss: 0.0324 (0.0345) time: 2.6443 data: 0.0064 max mem: 33370 +Epoch: [34] [1110/1319] eta: 0:09:09 lr: 7.912725866487896e-06 loss: 0.0310 (0.0345) time: 2.6166 data: 0.0065 max mem: 33370 +Epoch: [34] [1120/1319] eta: 0:08:43 lr: 7.902256989569599e-06 loss: 0.0296 (0.0345) time: 2.6199 data: 0.0065 max mem: 33370 +Epoch: [34] [1130/1319] eta: 0:08:17 lr: 7.891786571410098e-06 loss: 0.0336 (0.0345) time: 2.6495 data: 0.0064 max mem: 33370 +Epoch: [34] [1140/1319] eta: 0:07:50 lr: 7.881314609509776e-06 loss: 0.0294 (0.0344) time: 2.6449 data: 0.0063 max mem: 33370 +Epoch: [34] [1150/1319] eta: 0:07:24 lr: 7.870841101361268e-06 loss: 0.0258 (0.0344) time: 2.6174 data: 0.0064 max mem: 33370 +Epoch: [34] [1160/1319] eta: 0:06:58 lr: 7.860366044449406e-06 loss: 0.0310 (0.0344) time: 2.6122 data: 0.0067 max mem: 33370 +Epoch: [34] [1170/1319] eta: 0:06:32 lr: 7.849889436251218e-06 loss: 0.0310 (0.0344) time: 2.6293 data: 0.0066 max mem: 33370 +Epoch: [34] [1180/1319] eta: 0:06:05 lr: 7.839411274235871e-06 loss: 0.0314 (0.0344) time: 2.6297 data: 0.0064 max mem: 33370 +Epoch: [34] [1190/1319] eta: 0:05:39 lr: 7.82893155586463e-06 loss: 0.0348 (0.0344) time: 2.6360 data: 0.0064 max mem: 33370 +Epoch: [34] [1200/1319] eta: 0:05:13 lr: 7.818450278590844e-06 loss: 0.0361 (0.0344) time: 2.6335 data: 0.0065 max mem: 33370 +Epoch: [34] [1210/1319] eta: 0:04:46 lr: 7.80796743985987e-06 loss: 0.0348 (0.0344) time: 2.6473 data: 0.0065 max mem: 33370 +Epoch: [34] [1220/1319] eta: 0:04:20 lr: 7.797483037109084e-06 loss: 0.0279 (0.0344) time: 2.6590 data: 0.0065 max mem: 33370 +Epoch: [34] [1230/1319] eta: 0:03:54 lr: 7.786997067767811e-06 loss: 0.0263 (0.0343) time: 2.6343 data: 0.0064 max mem: 33370 +Epoch: [34] [1240/1319] eta: 0:03:27 lr: 7.776509529257303e-06 loss: 0.0299 (0.0343) time: 2.6321 data: 0.0064 max mem: 33370 +Epoch: [34] [1250/1319] eta: 0:03:01 lr: 7.766020418990693e-06 loss: 0.0319 (0.0343) time: 2.6310 data: 0.0066 max mem: 33370 +Epoch: [34] [1260/1319] eta: 0:02:35 lr: 7.755529734372952e-06 loss: 0.0310 (0.0343) time: 2.6393 data: 0.0064 max mem: 33370 +Epoch: [34] [1270/1319] eta: 0:02:08 lr: 7.74503747280087e-06 loss: 0.0307 (0.0343) time: 2.6191 data: 0.0064 max mem: 33370 +Epoch: [34] [1280/1319] eta: 0:01:42 lr: 7.734543631663006e-06 loss: 0.0312 (0.0343) time: 2.6006 data: 0.0065 max mem: 33370 +Epoch: [34] [1290/1319] eta: 0:01:16 lr: 7.724048208339646e-06 loss: 0.0312 (0.0343) time: 2.6187 data: 0.0065 max mem: 33370 +Epoch: [34] [1300/1319] eta: 0:00:49 lr: 7.713551200202774e-06 loss: 0.0297 (0.0342) time: 2.6199 data: 0.0066 max mem: 33370 +Epoch: [34] [1310/1319] eta: 0:00:23 lr: 7.703052604616029e-06 loss: 0.0297 (0.0343) time: 2.6495 data: 0.0065 max mem: 33370 +Epoch: [34] Total time: 0:57:51 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 1:47:25 time: 2.5049 data: 2.1963 max mem: 33370 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 100/2573] eta: 0:03:57 time: 0.0714 data: 0.0011 max mem: 33370 +Test: [ 200/2573] eta: 0:03:22 time: 0.0733 data: 0.0011 max mem: 33370 +Test: [ 300/2573] eta: 0:03:03 time: 0.0751 data: 0.0011 max mem: 33370 +Test: [ 400/2573] eta: 0:02:51 time: 0.0753 data: 0.0011 max mem: 33370 +Test: [ 500/2573] eta: 0:02:41 time: 0.0736 data: 0.0011 max mem: 33370 +Test: [ 600/2573] eta: 0:02:32 time: 0.0737 data: 0.0011 max mem: 33370 +Test: [ 700/2573] eta: 0:02:24 time: 0.0737 data: 0.0011 max mem: 33370 +Test: [ 800/2573] eta: 0:02:16 time: 0.0770 data: 0.0011 max mem: 33370 +Test: [ 900/2573] eta: 0:02:08 time: 0.0737 data: 0.0011 max mem: 33370 +Test: [1000/2573] eta: 0:02:00 time: 0.0737 data: 0.0011 max mem: 33370 +Test: [1100/2573] eta: 0:01:52 time: 0.0738 data: 0.0011 max mem: 33370 +Test: [1200/2573] eta: 0:01:44 time: 0.0738 data: 0.0011 max mem: 33370 +Test: [1300/2573] eta: 0:01:36 time: 0.0739 data: 0.0011 max mem: 33370 +Test: [1400/2573] eta: 0:01:28 time: 0.0721 data: 0.0011 max mem: 33370 +Test: [1500/2573] eta: 0:01:21 time: 0.0738 data: 0.0011 max mem: 33370 +Test: [1600/2573] eta: 0:01:13 time: 0.0770 data: 0.0011 max mem: 33370 +Test: [1700/2573] eta: 0:01:05 time: 0.0720 data: 0.0011 max mem: 33370 +Test: [1800/2573] eta: 0:00:58 time: 0.0753 data: 0.0011 max mem: 33370 +Test: [1900/2573] eta: 0:00:50 time: 0.0721 data: 0.0011 max mem: 33370 +Test: [2000/2573] eta: 0:00:42 time: 0.0738 data: 0.0011 max mem: 33370 +Test: [2100/2573] eta: 0:00:35 time: 0.0754 data: 0.0011 max mem: 33370 +Test: [2200/2573] eta: 0:00:27 time: 0.0754 data: 0.0011 max mem: 33370 +Test: [2300/2573] eta: 0:00:20 time: 0.0754 data: 0.0011 max mem: 33370 +Test: [2400/2573] eta: 0:00:12 time: 0.0705 data: 0.0011 max mem: 33370 +Test: [2500/2573] eta: 0:00:05 time: 0.0737 data: 0.0011 max mem: 33370 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: Total time: 0:03:12 +Final results: +Mean IoU is 64.88 + + precision@0.5 = 73.00 + precision@0.6 = 68.08 + precision@0.7 = 61.68 + precision@0.8 = 49.92 + precision@0.9 = 25.82 + overall IoU = 62.35 + +Average object IoU 64.87939974723001 +Overall IoU 62.35488510131836 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [35] [ 0/1319] eta: 3:15:57 lr: 7.693602509132593e-06 loss: 0.0370 (0.0370) time: 8.9140 data: 1.1980 max mem: 33370 +Epoch: [35] [ 10/1319] eta: 1:09:37 lr: 7.683100890097833e-06 loss: 0.0309 (0.0339) time: 3.1917 data: 0.1148 max mem: 33370 +Epoch: [35] [ 20/1319] eta: 1:03:54 lr: 7.67259767592017e-06 loss: 0.0309 (0.0330) time: 2.6538 data: 0.0064 max mem: 33370 +Epoch: [35] [ 30/1319] eta: 1:00:58 lr: 7.66209286393032e-06 loss: 0.0340 (0.0357) time: 2.6444 data: 0.0065 max mem: 33370 +Epoch: [35] [ 40/1319] eta: 0:59:37 lr: 7.651586451450453e-06 loss: 0.0366 (0.0357) time: 2.6349 data: 0.0067 max mem: 33370 +Epoch: [35] [ 50/1319] eta: 0:58:28 lr: 7.641078435794154e-06 loss: 0.0311 (0.0347) time: 2.6496 data: 0.0066 max mem: 33370 +Epoch: [35] [ 60/1319] eta: 0:57:36 lr: 7.630568814266394e-06 loss: 0.0290 (0.0340) time: 2.6391 data: 0.0065 max mem: 33370 +Epoch: [35] [ 70/1319] eta: 0:56:38 lr: 7.62005758416347e-06 loss: 0.0317 (0.0342) time: 2.6107 data: 0.0065 max mem: 33370 +Epoch: [35] [ 80/1319] eta: 0:56:00 lr: 7.609544742772985e-06 loss: 0.0328 (0.0341) time: 2.6100 data: 0.0067 max mem: 33370 +Epoch: [35] [ 90/1319] eta: 0:55:16 lr: 7.599030287373793e-06 loss: 0.0328 (0.0340) time: 2.6186 data: 0.0067 max mem: 33370 +Epoch: [35] [ 100/1319] eta: 0:54:43 lr: 7.588514215235963e-06 loss: 0.0285 (0.0335) time: 2.6201 data: 0.0066 max mem: 33370 +Epoch: [35] [ 110/1319] eta: 0:54:10 lr: 7.5779965236207366e-06 loss: 0.0275 (0.0332) time: 2.6433 data: 0.0066 max mem: 33370 +Epoch: [35] [ 120/1319] eta: 0:53:35 lr: 7.5674772097804864e-06 loss: 0.0310 (0.0331) time: 2.6192 data: 0.0067 max mem: 33370 +Epoch: [35] [ 130/1319] eta: 0:53:03 lr: 7.556956270958658e-06 loss: 0.0287 (0.0326) time: 2.6162 data: 0.0066 max mem: 33370 +Epoch: [35] [ 140/1319] eta: 0:52:29 lr: 7.546433704389756e-06 loss: 0.0258 (0.0323) time: 2.6086 data: 0.0065 max mem: 33370 +Epoch: [35] [ 150/1319] eta: 0:52:03 lr: 7.535909507299282e-06 loss: 0.0282 (0.0323) time: 2.6330 data: 0.0065 max mem: 33370 +Epoch: [35] [ 160/1319] eta: 0:51:33 lr: 7.525383676903694e-06 loss: 0.0311 (0.0322) time: 2.6524 data: 0.0065 max mem: 33370 +Epoch: [35] [ 170/1319] eta: 0:51:03 lr: 7.514856210410369e-06 loss: 0.0338 (0.0324) time: 2.6229 data: 0.0067 max mem: 33370 +Epoch: [35] [ 180/1319] eta: 0:50:37 lr: 7.504327105017539e-06 loss: 0.0338 (0.0329) time: 2.6540 data: 0.0067 max mem: 33370 +Epoch: [35] [ 190/1319] eta: 0:50:09 lr: 7.493796357914276e-06 loss: 0.0316 (0.0326) time: 2.6616 data: 0.0065 max mem: 33370 +Epoch: [35] [ 200/1319] eta: 0:49:41 lr: 7.483263966280434e-06 loss: 0.0287 (0.0328) time: 2.6369 data: 0.0066 max mem: 33370 +Epoch: [35] [ 210/1319] eta: 0:49:10 lr: 7.4727299272865964e-06 loss: 0.0338 (0.0329) time: 2.6090 data: 0.0066 max mem: 33370 +Epoch: [35] [ 220/1319] eta: 0:48:41 lr: 7.462194238094052e-06 loss: 0.0354 (0.0330) time: 2.6022 data: 0.0066 max mem: 33370 +Epoch: [35] [ 230/1319] eta: 0:48:16 lr: 7.4516568958547115e-06 loss: 0.0324 (0.0329) time: 2.6565 data: 0.0066 max mem: 33370 +Epoch: [35] [ 240/1319] eta: 0:47:49 lr: 7.4411178977111085e-06 loss: 0.0293 (0.0327) time: 2.6645 data: 0.0064 max mem: 33370 +Epoch: [35] [ 250/1319] eta: 0:47:20 lr: 7.430577240796325e-06 loss: 0.0258 (0.0328) time: 2.6242 data: 0.0065 max mem: 33370 +Epoch: [35] [ 260/1319] eta: 0:46:53 lr: 7.420034922233955e-06 loss: 0.0258 (0.0326) time: 2.6242 data: 0.0066 max mem: 33370 +Epoch: [35] [ 270/1319] eta: 0:46:25 lr: 7.4094909391380505e-06 loss: 0.0313 (0.0327) time: 2.6308 data: 0.0065 max mem: 33370 +Epoch: [35] [ 280/1319] eta: 0:45:58 lr: 7.398945288613088e-06 loss: 0.0323 (0.0327) time: 2.6333 data: 0.0065 max mem: 33370 +Epoch: [35] [ 290/1319] eta: 0:45:30 lr: 7.388397967753893e-06 loss: 0.0323 (0.0329) time: 2.6368 data: 0.0066 max mem: 33370 +Epoch: [35] [ 300/1319] eta: 0:45:04 lr: 7.3778489736456335e-06 loss: 0.0312 (0.0328) time: 2.6412 data: 0.0066 max mem: 33370 +Epoch: [35] [ 310/1319] eta: 0:44:36 lr: 7.367298303363743e-06 loss: 0.0312 (0.0329) time: 2.6364 data: 0.0066 max mem: 33370 +Epoch: [35] [ 320/1319] eta: 0:44:09 lr: 7.35674595397388e-06 loss: 0.0312 (0.0328) time: 2.6199 data: 0.0065 max mem: 33370 +Epoch: [35] [ 330/1319] eta: 0:43:42 lr: 7.34619192253189e-06 loss: 0.0301 (0.0328) time: 2.6287 data: 0.0064 max mem: 33370 +Epoch: [35] [ 340/1319] eta: 0:43:15 lr: 7.335636206083729e-06 loss: 0.0321 (0.0329) time: 2.6506 data: 0.0064 max mem: 33370 +Epoch: [35] [ 350/1319] eta: 0:42:50 lr: 7.325078801665445e-06 loss: 0.0308 (0.0329) time: 2.6794 data: 0.0064 max mem: 33370 +Epoch: [35] [ 360/1319] eta: 0:42:23 lr: 7.31451970630312e-06 loss: 0.0315 (0.0336) time: 2.6665 data: 0.0065 max mem: 33370 +Epoch: [35] [ 370/1319] eta: 0:41:57 lr: 7.303958917012809e-06 loss: 0.0333 (0.0336) time: 2.6475 data: 0.0066 max mem: 33370 +Epoch: [35] [ 380/1319] eta: 0:41:30 lr: 7.293396430800509e-06 loss: 0.0306 (0.0347) time: 2.6456 data: 0.0066 max mem: 33370 +Epoch: [35] [ 390/1319] eta: 0:41:03 lr: 7.282832244662077e-06 loss: 0.0356 (0.0346) time: 2.6431 data: 0.0064 max mem: 33370 +Epoch: [35] [ 400/1319] eta: 0:40:37 lr: 7.272266355583221e-06 loss: 0.0356 (0.0346) time: 2.6503 data: 0.0064 max mem: 33370 +Epoch: [35] [ 410/1319] eta: 0:40:10 lr: 7.261698760539424e-06 loss: 0.0318 (0.0346) time: 2.6445 data: 0.0063 max mem: 33370 +Epoch: [35] [ 420/1319] eta: 0:39:44 lr: 7.2511294564958895e-06 loss: 0.0318 (0.0346) time: 2.6637 data: 0.0064 max mem: 33370 +Epoch: [35] [ 430/1319] eta: 0:39:17 lr: 7.240558440407508e-06 loss: 0.0347 (0.0347) time: 2.6636 data: 0.0064 max mem: 33370 +Epoch: [35] [ 440/1319] eta: 0:38:51 lr: 7.229985709218795e-06 loss: 0.0348 (0.0347) time: 2.6498 data: 0.0064 max mem: 33370 +Epoch: [35] [ 450/1319] eta: 0:38:24 lr: 7.219411259863819e-06 loss: 0.0348 (0.0347) time: 2.6425 data: 0.0065 max mem: 33370 +Epoch: [35] [ 460/1319] eta: 0:37:56 lr: 7.208835089266191e-06 loss: 0.0323 (0.0348) time: 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eta: 0:27:20 lr: 6.954482434226801e-06 loss: 0.0347 (0.0347) time: 2.6503 data: 0.0063 max mem: 33370 +Epoch: [35] [ 710/1319] eta: 0:26:54 lr: 6.9438622009590656e-06 loss: 0.0331 (0.0348) time: 2.6602 data: 0.0063 max mem: 33370 +Epoch: [35] [ 720/1319] eta: 0:26:27 lr: 6.933240162602753e-06 loss: 0.0298 (0.0347) time: 2.6456 data: 0.0065 max mem: 33370 +Epoch: [35] [ 730/1319] eta: 0:26:01 lr: 6.922616315777261e-06 loss: 0.0271 (0.0347) time: 2.6480 data: 0.0065 max mem: 33370 +Epoch: [35] [ 740/1319] eta: 0:25:35 lr: 6.911990657089877e-06 loss: 0.0286 (0.0346) time: 2.6719 data: 0.0064 max mem: 33370 +Epoch: [35] [ 750/1319] eta: 0:25:08 lr: 6.901363183135715e-06 loss: 0.0316 (0.0346) time: 2.6403 data: 0.0065 max mem: 33370 +Epoch: [35] [ 760/1319] eta: 0:24:41 lr: 6.890733890497658e-06 loss: 0.0347 (0.0346) time: 2.6336 data: 0.0065 max mem: 33370 +Epoch: [35] [ 770/1319] eta: 0:24:15 lr: 6.880102775746271e-06 loss: 0.0368 (0.0346) time: 2.6561 data: 0.0065 max mem: 33370 +Epoch: 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mem: 33370 +Epoch: [35] [ 860/1319] eta: 0:20:15 lr: 6.784340175855078e-06 loss: 0.0318 (0.0347) time: 2.6162 data: 0.0066 max mem: 33370 +Epoch: [35] [ 870/1319] eta: 0:19:49 lr: 6.7736906485984466e-06 loss: 0.0305 (0.0346) time: 2.6141 data: 0.0065 max mem: 33370 +Epoch: [35] [ 880/1319] eta: 0:19:22 lr: 6.763039260673876e-06 loss: 0.0287 (0.0346) time: 2.6225 data: 0.0063 max mem: 33370 +Epoch: [35] [ 890/1319] eta: 0:18:56 lr: 6.752386008499089e-06 loss: 0.0280 (0.0345) time: 2.6341 data: 0.0065 max mem: 33370 +Epoch: [35] [ 900/1319] eta: 0:18:29 lr: 6.741730888478615e-06 loss: 0.0319 (0.0345) time: 2.6149 data: 0.0065 max mem: 33370 +Epoch: [35] [ 910/1319] eta: 0:18:02 lr: 6.7310738970037205e-06 loss: 0.0320 (0.0345) time: 2.6215 data: 0.0064 max mem: 33370 +Epoch: [35] [ 920/1319] eta: 0:17:36 lr: 6.7204150304523424e-06 loss: 0.0295 (0.0345) time: 2.6222 data: 0.0065 max mem: 33370 +Epoch: [35] [ 930/1319] eta: 0:17:09 lr: 6.709754285188997e-06 loss: 0.0320 (0.0346) time: 2.6258 data: 0.0066 max mem: 33370 +Epoch: [35] [ 940/1319] eta: 0:16:43 lr: 6.699091657564736e-06 loss: 0.0361 (0.0346) time: 2.6492 data: 0.0064 max mem: 33370 +Epoch: [35] [ 950/1319] eta: 0:16:16 lr: 6.688427143917049e-06 loss: 0.0357 (0.0346) time: 2.6556 data: 0.0063 max mem: 33370 +Epoch: [35] [ 960/1319] eta: 0:15:50 lr: 6.677760740569799e-06 loss: 0.0293 (0.0346) time: 2.6519 data: 0.0063 max mem: 33370 +Epoch: [35] [ 970/1319] eta: 0:15:24 lr: 6.667092443833153e-06 loss: 0.0305 (0.0346) time: 2.6645 data: 0.0064 max mem: 33370 +Epoch: [35] [ 980/1319] eta: 0:14:57 lr: 6.656422250003478e-06 loss: 0.0310 (0.0346) time: 2.6614 data: 0.0065 max mem: 33370 +Epoch: [35] [ 990/1319] eta: 0:14:30 lr: 6.645750155363307e-06 loss: 0.0325 (0.0346) time: 2.6304 data: 0.0065 max mem: 33370 +Epoch: [35] [1000/1319] eta: 0:14:04 lr: 6.635076156181232e-06 loss: 0.0352 (0.0346) time: 2.6047 data: 0.0065 max mem: 33370 +Epoch: [35] [1010/1319] eta: 0:13:37 lr: 6.624400248711836e-06 loss: 0.0385 (0.0347) time: 2.6226 data: 0.0064 max mem: 33370 +Epoch: [35] [1020/1319] eta: 0:13:11 lr: 6.613722429195618e-06 loss: 0.0323 (0.0346) time: 2.6539 data: 0.0064 max mem: 33370 +Epoch: [35] [1030/1319] eta: 0:12:44 lr: 6.603042693858916e-06 loss: 0.0327 (0.0346) time: 2.6439 data: 0.0065 max mem: 33370 +Epoch: [35] [1040/1319] eta: 0:12:18 lr: 6.5923610389138055e-06 loss: 0.0328 (0.0346) time: 2.6317 data: 0.0065 max mem: 33370 +Epoch: [35] [1050/1319] eta: 0:11:51 lr: 6.581677460558057e-06 loss: 0.0279 (0.0346) time: 2.6385 data: 0.0064 max mem: 33370 +Epoch: [35] [1060/1319] eta: 0:11:25 lr: 6.570991954975031e-06 loss: 0.0292 (0.0346) time: 2.6480 data: 0.0064 max mem: 33370 +Epoch: [35] [1070/1319] eta: 0:10:59 lr: 6.560304518333606e-06 loss: 0.0294 (0.0346) time: 2.6558 data: 0.0063 max mem: 33370 +Epoch: [35] [1080/1319] eta: 0:10:32 lr: 6.549615146788095e-06 loss: 0.0343 (0.0346) time: 2.6472 data: 0.0062 max mem: 33370 +Epoch: [35] [1090/1319] eta: 0:10:06 lr: 6.538923836478152e-06 loss: 0.0301 (0.0345) time: 2.6337 data: 0.0063 max mem: 33370 +Epoch: [35] [1100/1319] eta: 0:09:39 lr: 6.528230583528713e-06 loss: 0.0301 (0.0345) time: 2.6493 data: 0.0065 max mem: 33370 +Epoch: [35] [1110/1319] eta: 0:09:13 lr: 6.5175353840499016e-06 loss: 0.0337 (0.0345) time: 2.6466 data: 0.0066 max mem: 33370 +Epoch: [35] [1120/1319] eta: 0:08:46 lr: 6.506838234136938e-06 loss: 0.0306 (0.0345) time: 2.6526 data: 0.0065 max mem: 33370 +Epoch: [35] [1130/1319] eta: 0:08:20 lr: 6.4961391298700616e-06 loss: 0.0274 (0.0345) time: 2.6912 data: 0.0064 max mem: 33370 +Epoch: [35] [1140/1319] eta: 0:07:53 lr: 6.485438067314456e-06 loss: 0.0270 (0.0345) time: 2.6822 data: 0.0063 max mem: 33370 +Epoch: [35] [1150/1319] eta: 0:07:27 lr: 6.4747350425201315e-06 loss: 0.0322 (0.0344) time: 2.6218 data: 0.0064 max mem: 33370 +Epoch: [35] [1160/1319] eta: 0:07:00 lr: 6.464030051521878e-06 loss: 0.0317 (0.0345) time: 2.6180 data: 0.0064 max mem: 33370 +Epoch: [35] 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33370 +Epoch: [35] [1250/1319] eta: 0:03:02 lr: 6.3675959914443046e-06 loss: 0.0328 (0.0343) time: 2.6630 data: 0.0065 max mem: 33370 +Epoch: [35] [1260/1319] eta: 0:02:36 lr: 6.356871116904475e-06 loss: 0.0353 (0.0345) time: 2.6554 data: 0.0065 max mem: 33370 +Epoch: [35] [1270/1319] eta: 0:02:09 lr: 6.34614423151228e-06 loss: 0.0353 (0.0345) time: 2.6405 data: 0.0063 max mem: 33370 +Epoch: [35] [1280/1319] eta: 0:01:43 lr: 6.335415331112665e-06 loss: 0.0343 (0.0344) time: 2.6303 data: 0.0063 max mem: 33370 +Epoch: [35] [1290/1319] eta: 0:01:16 lr: 6.324684411534165e-06 loss: 0.0340 (0.0345) time: 2.6322 data: 0.0063 max mem: 33370 +Epoch: [35] [1300/1319] eta: 0:00:50 lr: 6.313951468588795e-06 loss: 0.0324 (0.0345) time: 2.6371 data: 0.0065 max mem: 33370 +Epoch: [35] [1310/1319] eta: 0:00:23 lr: 6.3032164980719415e-06 loss: 0.0309 (0.0344) time: 2.6415 data: 0.0064 max mem: 33370 +Epoch: [35] Total time: 0:58:09 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 2:06:30 time: 2.9499 data: 2.6079 max mem: 33370 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 100/2573] eta: 0:04:09 time: 0.0716 data: 0.0011 max mem: 33370 +Test: [ 200/2573] eta: 0:03:28 time: 0.0734 data: 0.0011 max mem: 33370 +Test: [ 300/2573] eta: 0:03:07 time: 0.0751 data: 0.0011 max mem: 33370 +Test: [ 400/2573] eta: 0:02:54 time: 0.0752 data: 0.0011 max mem: 33370 +Test: [ 500/2573] eta: 0:02:43 time: 0.0738 data: 0.0011 max mem: 33370 +Test: [ 600/2573] eta: 0:02:34 time: 0.0738 data: 0.0011 max mem: 33370 +Test: [ 700/2573] eta: 0:02:25 time: 0.0738 data: 0.0011 max mem: 33370 +Test: [ 800/2573] eta: 0:02:17 time: 0.0771 data: 0.0010 max mem: 33370 +Test: [ 900/2573] eta: 0:02:09 time: 0.0737 data: 0.0011 max mem: 33370 +Test: [1000/2573] eta: 0:02:00 time: 0.0738 data: 0.0011 max mem: 33370 +Test: [1100/2573] eta: 0:01:52 time: 0.0738 data: 0.0011 max mem: 33370 +Test: [1200/2573] eta: 0:01:44 time: 0.0738 data: 0.0011 max mem: 33370 +Test: [1300/2573] eta: 0:01:37 time: 0.0737 data: 0.0011 max mem: 33370 +Test: [1400/2573] eta: 0:01:29 time: 0.0721 data: 0.0011 max mem: 33370 +Test: [1500/2573] eta: 0:01:21 time: 0.0739 data: 0.0011 max mem: 33370 +Test: [1600/2573] eta: 0:01:13 time: 0.0771 data: 0.0011 max mem: 33370 +Test: [1700/2573] eta: 0:01:06 time: 0.0721 data: 0.0011 max mem: 33370 +Test: [1800/2573] eta: 0:00:58 time: 0.0753 data: 0.0011 max mem: 33370 +Test: [1900/2573] eta: 0:00:50 time: 0.0721 data: 0.0011 max mem: 33370 +Test: [2000/2573] eta: 0:00:43 time: 0.0738 data: 0.0011 max mem: 33370 +Test: [2100/2573] eta: 0:00:35 time: 0.0753 data: 0.0011 max mem: 33370 +Test: [2200/2573] eta: 0:00:27 time: 0.0753 data: 0.0011 max mem: 33370 +Test: [2300/2573] eta: 0:00:20 time: 0.0753 data: 0.0011 max mem: 33370 +Test: [2400/2573] eta: 0:00:12 time: 0.0705 data: 0.0011 max mem: 33370 +Test: [2500/2573] eta: 0:00:05 time: 0.0737 data: 0.0011 max mem: 33370 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: Total time: 0:03:13 +Final results: +Mean IoU is 64.98 + + precision@0.5 = 73.18 + precision@0.6 = 68.30 + precision@0.7 = 61.70 + precision@0.8 = 50.14 + precision@0.9 = 25.71 + overall IoU = 62.38 + +Average object IoU 64.9836239533139 +Overall IoU 62.378868103027344 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [36] [ 0/1319] eta: 3:00:31 lr: 6.293553287544593e-06 loss: 0.0338 (0.0338) time: 8.2121 data: 1.1560 max mem: 33370 +Epoch: [36] [ 10/1319] eta: 1:08:34 lr: 6.282814452998321e-06 loss: 0.0338 (0.0352) time: 3.1429 data: 0.1111 max mem: 33370 +Epoch: [36] [ 20/1319] eta: 1:03:17 lr: 6.2720735785923675e-06 loss: 0.0302 (0.0333) time: 2.6591 data: 0.0064 max mem: 33370 +Epoch: [36] [ 30/1319] eta: 1:01:05 lr: 6.261330660056396e-06 loss: 0.0312 (0.0329) time: 2.6794 data: 0.0064 max mem: 33370 +Epoch: [36] [ 40/1319] eta: 0:59:43 lr: 6.250585693102968e-06 loss: 0.0345 (0.0340) time: 2.6735 data: 0.0067 max mem: 33370 +Epoch: [36] [ 50/1319] eta: 0:58:29 lr: 6.2398386734274585e-06 loss: 0.0354 (0.0350) time: 2.6447 data: 0.0068 max mem: 33370 +Epoch: [36] [ 60/1319] eta: 0:57:36 lr: 6.229089596707912e-06 loss: 0.0322 (0.0341) time: 2.6307 data: 0.0066 max mem: 33370 +Epoch: [36] [ 70/1319] eta: 0:56:37 lr: 6.218338458604991e-06 loss: 0.0275 (0.0343) time: 2.6042 data: 0.0066 max mem: 33370 +Epoch: [36] [ 80/1319] eta: 0:55:53 lr: 6.207585254761843e-06 loss: 0.0310 (0.0341) time: 2.5884 data: 0.0066 max mem: 33370 +Epoch: [36] [ 90/1319] eta: 0:55:18 lr: 6.196829980804001e-06 loss: 0.0317 (0.0336) time: 2.6287 data: 0.0066 max mem: 33370 +Epoch: [36] [ 100/1319] eta: 0:54:49 lr: 6.1860726323392754e-06 loss: 0.0316 (0.0337) time: 2.6639 data: 0.0067 max mem: 33370 +Epoch: [36] [ 110/1319] eta: 0:54:13 lr: 6.175313204957665e-06 loss: 0.0345 (0.0339) time: 2.6519 data: 0.0067 max mem: 33370 +Epoch: [36] [ 120/1319] eta: 0:53:41 lr: 6.164551694231212e-06 loss: 0.0345 (0.0336) time: 2.6303 data: 0.0066 max mem: 33370 +Epoch: [36] [ 130/1319] eta: 0:53:09 lr: 6.153788095713938e-06 loss: 0.0356 (0.0343) time: 2.6353 data: 0.0067 max mem: 33370 +Epoch: [36] [ 140/1319] eta: 0:52:36 lr: 6.143022404941713e-06 loss: 0.0356 (0.0341) time: 2.6161 data: 0.0066 max mem: 33370 +Epoch: [36] [ 150/1319] eta: 0:52:04 lr: 6.132254617432146e-06 loss: 0.0293 (0.0338) time: 2.6069 data: 0.0065 max mem: 33370 +Epoch: [36] [ 160/1319] eta: 0:51:33 lr: 6.121484728684484e-06 loss: 0.0295 (0.0337) time: 2.6146 data: 0.0065 max mem: 33370 +Epoch: [36] [ 170/1319] eta: 0:51:03 lr: 6.110712734179475e-06 loss: 0.0295 (0.0334) time: 2.6188 data: 0.0065 max mem: 33370 +Epoch: [36] [ 180/1319] eta: 0:50:32 lr: 6.099938629379293e-06 loss: 0.0287 (0.0335) time: 2.6094 data: 0.0065 max mem: 33370 +Epoch: [36] [ 190/1319] eta: 0:50:01 lr: 6.0891624097274035e-06 loss: 0.0287 (0.0335) time: 2.5946 data: 0.0065 max mem: 33370 +Epoch: [36] [ 200/1319] eta: 0:49:37 lr: 6.07838407064845e-06 loss: 0.0298 (0.0336) time: 2.6489 data: 0.0064 max mem: 33370 +Epoch: [36] [ 210/1319] eta: 0:49:10 lr: 6.067603607548146e-06 loss: 0.0327 (0.0334) time: 2.6766 data: 0.0066 max mem: 33370 +Epoch: [36] [ 220/1319] eta: 0:48:41 lr: 6.05682101581314e-06 loss: 0.0327 (0.0336) time: 2.6302 data: 0.0064 max mem: 33370 +Epoch: [36] [ 230/1319] eta: 0:48:14 lr: 6.0460362908109285e-06 loss: 0.0331 (0.0336) time: 2.6299 data: 0.0063 max mem: 33370 +Epoch: [36] [ 240/1319] eta: 0:47:46 lr: 6.035249427889721e-06 loss: 0.0292 (0.0334) time: 2.6411 data: 0.0065 max mem: 33370 +Epoch: [36] [ 250/1319] eta: 0:47:17 lr: 6.024460422378318e-06 loss: 0.0288 (0.0333) time: 2.6168 data: 0.0066 max mem: 33370 +Epoch: [36] [ 260/1319] eta: 0:46:51 lr: 6.013669269586002e-06 loss: 0.0315 (0.0336) time: 2.6323 data: 0.0065 max mem: 33370 +Epoch: [36] [ 270/1319] eta: 0:46:24 lr: 6.002875964802412e-06 loss: 0.0319 (0.0335) time: 2.6504 data: 0.0065 max mem: 33370 +Epoch: [36] [ 280/1319] eta: 0:45:56 lr: 5.992080503297408e-06 loss: 0.0319 (0.0336) time: 2.6223 data: 0.0066 max mem: 33370 +Epoch: [36] [ 290/1319] eta: 0:45:27 lr: 5.981282880320978e-06 loss: 0.0310 (0.0335) time: 2.5999 data: 0.0065 max mem: 33370 +Epoch: [36] [ 300/1319] eta: 0:44:59 lr: 5.97048309110309e-06 loss: 0.0284 (0.0334) time: 2.5933 data: 0.0064 max mem: 33370 +Epoch: [36] [ 310/1319] eta: 0:44:33 lr: 5.959681130853577e-06 loss: 0.0284 (0.0334) time: 2.6289 data: 0.0064 max mem: 33370 +Epoch: [36] [ 320/1319] eta: 0:44:05 lr: 5.948876994762015e-06 loss: 0.0272 (0.0334) time: 2.6450 data: 0.0064 max mem: 33370 +Epoch: [36] [ 330/1319] eta: 0:43:38 lr: 5.938070677997572e-06 loss: 0.0282 (0.0334) time: 2.6296 data: 0.0067 max mem: 33370 +Epoch: [36] [ 340/1319] eta: 0:43:10 lr: 5.927262175708919e-06 loss: 0.0301 (0.0335) time: 2.6141 data: 0.0068 max mem: 33370 +Epoch: [36] [ 350/1319] eta: 0:42:44 lr: 5.916451483024071e-06 loss: 0.0301 (0.0335) time: 2.6205 data: 0.0068 max mem: 33370 +Epoch: [36] [ 360/1319] eta: 0:42:17 lr: 5.905638595050271e-06 loss: 0.0323 (0.0335) time: 2.6393 data: 0.0067 max mem: 33370 +Epoch: [36] [ 370/1319] eta: 0:41:50 lr: 5.894823506873858e-06 loss: 0.0329 (0.0335) time: 2.6183 data: 0.0067 max mem: 33370 +Epoch: [36] [ 380/1319] eta: 0:41:23 lr: 5.884006213560114e-06 loss: 0.0327 (0.0336) time: 2.6286 data: 0.0065 max mem: 33370 +Epoch: [36] [ 390/1319] eta: 0:40:56 lr: 5.873186710153169e-06 loss: 0.0327 (0.0336) time: 2.6269 data: 0.0064 max mem: 33370 +Epoch: [36] [ 400/1319] eta: 0:40:29 lr: 5.862364991675836e-06 loss: 0.0323 (0.0341) time: 2.6222 data: 0.0066 max mem: 33370 +Epoch: [36] [ 410/1319] eta: 0:40:03 lr: 5.85154105312949e-06 loss: 0.0305 (0.0341) time: 2.6401 data: 0.0065 max mem: 33370 +Epoch: [36] [ 420/1319] eta: 0:39:36 lr: 5.840714889493923e-06 loss: 0.0305 (0.0340) time: 2.6362 data: 0.0064 max mem: 33370 +Epoch: [36] [ 430/1319] eta: 0:39:10 lr: 5.829886495727219e-06 loss: 0.0329 (0.0341) time: 2.6348 data: 0.0064 max mem: 33370 +Epoch: [36] [ 440/1319] eta: 0:38:42 lr: 5.819055866765587e-06 loss: 0.0340 (0.0340) time: 2.6037 data: 0.0066 max mem: 33370 +Epoch: [36] [ 450/1319] eta: 0:38:15 lr: 5.808222997523256e-06 loss: 0.0297 (0.0340) time: 2.6104 data: 0.0066 max mem: 33370 +Epoch: [36] [ 460/1319] eta: 0:37:49 lr: 5.797387882892317e-06 loss: 0.0323 (0.0340) time: 2.6331 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5.1100083788515145e-06 loss: 0.0339 (0.0334) time: 2.6345 data: 0.0065 max mem: 33370 +Epoch: [36] [1100/1319] eta: 0:09:38 lr: 5.0990177994339575e-06 loss: 0.0315 (0.0334) time: 2.6170 data: 0.0068 max mem: 33370 +Epoch: [36] [1110/1319] eta: 0:09:11 lr: 5.088024587224353e-06 loss: 0.0333 (0.0334) time: 2.6328 data: 0.0066 max mem: 33370 +Epoch: [36] [1120/1319] eta: 0:08:45 lr: 5.077028735268508e-06 loss: 0.0346 (0.0334) time: 2.6316 data: 0.0063 max mem: 33370 +Epoch: [36] [1130/1319] eta: 0:08:18 lr: 5.066030236577056e-06 loss: 0.0366 (0.0335) time: 2.6051 data: 0.0063 max mem: 33370 +Epoch: [36] [1140/1319] eta: 0:07:52 lr: 5.055029084125236e-06 loss: 0.0313 (0.0335) time: 2.6283 data: 0.0064 max mem: 33370 +Epoch: [36] [1150/1319] eta: 0:07:26 lr: 5.044025270852602e-06 loss: 0.0307 (0.0335) time: 2.6510 data: 0.0064 max mem: 33370 +Epoch: [36] [1160/1319] eta: 0:06:59 lr: 5.033018789662757e-06 loss: 0.0301 (0.0334) time: 2.6192 data: 0.0065 max mem: 33370 +Epoch: [36] [1170/1319] eta: 0:06:33 lr: 5.022009633423085e-06 loss: 0.0278 (0.0334) time: 2.6486 data: 0.0064 max mem: 33370 +Epoch: [36] [1180/1319] eta: 0:06:06 lr: 5.0109977949644845e-06 loss: 0.0290 (0.0334) time: 2.6511 data: 0.0063 max mem: 33370 +Epoch: [36] [1190/1319] eta: 0:05:40 lr: 4.999983267081064e-06 loss: 0.0336 (0.0334) time: 2.6097 data: 0.0064 max mem: 33370 +Epoch: [36] [1200/1319] eta: 0:05:14 lr: 4.988966042529905e-06 loss: 0.0335 (0.0334) time: 2.6382 data: 0.0065 max mem: 33370 +Epoch: [36] [1210/1319] eta: 0:04:47 lr: 4.977946114030749e-06 loss: 0.0322 (0.0335) time: 2.6390 data: 0.0063 max mem: 33370 +Epoch: [36] [1220/1319] eta: 0:04:21 lr: 4.966923474265728e-06 loss: 0.0322 (0.0334) time: 2.6046 data: 0.0065 max mem: 33370 +Epoch: [36] [1230/1319] eta: 0:03:54 lr: 4.9558981158790714e-06 loss: 0.0324 (0.0335) time: 2.6121 data: 0.0065 max mem: 33370 +Epoch: [36] [1240/1319] eta: 0:03:28 lr: 4.944870031476802e-06 loss: 0.0328 (0.0335) time: 2.6456 data: 0.0062 max mem: 33370 +Epoch: [36] [1250/1319] eta: 0:03:02 lr: 4.9338392136264714e-06 loss: 0.0326 (0.0335) time: 2.6365 data: 0.0062 max mem: 33370 +Epoch: [36] [1260/1319] eta: 0:02:35 lr: 4.922805654856843e-06 loss: 0.0291 (0.0335) time: 2.6395 data: 0.0064 max mem: 33370 +Epoch: [36] [1270/1319] eta: 0:02:09 lr: 4.9117693476576e-06 loss: 0.0299 (0.0335) time: 2.6476 data: 0.0064 max mem: 33370 +Epoch: [36] [1280/1319] eta: 0:01:42 lr: 4.9007302844790375e-06 loss: 0.0299 (0.0335) time: 2.6396 data: 0.0062 max mem: 33370 +Epoch: [36] [1290/1319] eta: 0:01:16 lr: 4.889688457731768e-06 loss: 0.0301 (0.0335) time: 2.6553 data: 0.0064 max mem: 33370 +Epoch: [36] [1300/1319] eta: 0:00:50 lr: 4.878643859786385e-06 loss: 0.0287 (0.0335) time: 2.6332 data: 0.0065 max mem: 33370 +Epoch: [36] [1310/1319] eta: 0:00:23 lr: 4.867596482973188e-06 loss: 0.0287 (0.0334) time: 2.6401 data: 0.0062 max mem: 33370 +Epoch: [36] Total time: 0:58:00 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 2:01:16 time: 2.8281 data: 2.7341 max mem: 33370 +Test: [ 100/2573] eta: 0:04:04 time: 0.0715 data: 0.0011 max mem: 33370 +Test: [ 200/2573] eta: 0:03:25 time: 0.0731 data: 0.0011 max mem: 33370 +Test: [ 300/2573] eta: 0:03:05 time: 0.0751 data: 0.0011 max mem: 33370 +Test: [ 400/2573] eta: 0:02:52 time: 0.0752 data: 0.0011 max mem: 33370 +Test: [ 500/2573] eta: 0:02:42 time: 0.0735 data: 0.0011 max mem: 33370 +Test: [ 600/2573] eta: 0:02:33 time: 0.0737 data: 0.0011 max mem: 33370 +Test: [ 700/2573] eta: 0:02:25 time: 0.0737 data: 0.0011 max mem: 33370 +Test: [ 800/2573] eta: 0:02:16 time: 0.0770 data: 0.0011 max mem: 33370 +Test: [ 900/2573] eta: 0:02:08 time: 0.0738 data: 0.0011 max mem: 33370 +Test: [1000/2573] eta: 0:02:00 time: 0.0737 data: 0.0011 max mem: 33370 +Test: [1100/2573] eta: 0:01:52 time: 0.0737 data: 0.0011 max mem: 33370 +Test: [1200/2573] eta: 0:01:44 time: 0.0737 data: 0.0011 max mem: 33370 +Test: [1300/2573] eta: 0:01:36 time: 0.0737 data: 0.0011 max mem: 33370 +Test: [1400/2573] eta: 0:01:28 time: 0.0721 data: 0.0011 max mem: 33370 +Test: [1500/2573] eta: 0:01:21 time: 0.0737 data: 0.0011 max mem: 33370 +Test: [1600/2573] eta: 0:01:13 time: 0.0770 data: 0.0011 max mem: 33370 +Test: [1700/2573] eta: 0:01:05 time: 0.0719 data: 0.0011 max mem: 33370 +Test: [1800/2573] eta: 0:00:58 time: 0.0754 data: 0.0011 max mem: 33370 +Test: [1900/2573] eta: 0:00:50 time: 0.0721 data: 0.0011 max mem: 33370 +Test: [2000/2573] eta: 0:00:43 time: 0.0736 data: 0.0011 max mem: 33370 +Test: [2100/2573] eta: 0:00:35 time: 0.0754 data: 0.0011 max mem: 33370 +Test: [2200/2573] eta: 0:00:27 time: 0.0753 data: 0.0011 max mem: 33370 +Test: [2300/2573] eta: 0:00:20 time: 0.0753 data: 0.0011 max mem: 33370 +Test: [2400/2573] eta: 0:00:12 time: 0.0704 data: 0.0011 max mem: 33370 +Test: [2500/2573] eta: 0:00:05 time: 0.0737 data: 0.0011 max mem: 33370 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: Total time: 0:03:12 +Final results: +Mean IoU is 64.98 + + precision@0.5 = 73.33 + precision@0.6 = 68.50 + precision@0.7 = 61.79 + precision@0.8 = 50.16 + precision@0.9 = 26.04 + overall IoU = 62.36 + +Average object IoU 64.97856090078247 +Overall IoU 62.35845184326172 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [37] [ 0/1319] eta: 3:09:16 lr: 4.85765146153759e-06 loss: 0.0196 (0.0196) time: 8.6096 data: 1.0727 max mem: 33370 +Epoch: [37] [ 10/1319] eta: 1:09:33 lr: 4.846598783599751e-06 loss: 0.0237 (0.0241) time: 3.1887 data: 0.1037 max mem: 33370 +Epoch: [37] [ 20/1319] eta: 1:03:10 lr: 4.835543304321068e-06 loss: 0.0257 (0.0307) time: 2.6338 data: 0.0065 max mem: 33370 +Epoch: [37] [ 30/1319] eta: 1:00:57 lr: 4.824485015871577e-06 loss: 0.0299 (0.0312) time: 2.6441 data: 0.0064 max mem: 33370 +Epoch: [37] [ 40/1319] eta: 0:59:11 lr: 4.813423910379438e-06 loss: 0.0320 (0.0314) time: 2.6274 data: 0.0066 max mem: 33370 +Epoch: [37] [ 50/1319] eta: 0:58:18 lr: 4.802359979930566e-06 loss: 0.0303 (0.0311) time: 2.6328 data: 0.0068 max mem: 33370 +Epoch: [37] [ 60/1319] eta: 0:57:30 lr: 4.791293216568347e-06 loss: 0.0253 (0.0305) time: 2.6685 data: 0.0068 max mem: 33370 +Epoch: [37] [ 70/1319] eta: 0:56:43 lr: 4.780223612293264e-06 loss: 0.0279 (0.0311) time: 2.6421 data: 0.0068 max mem: 33370 +Epoch: [37] [ 80/1319] eta: 0:56:05 lr: 4.7691511590625665e-06 loss: 0.0324 (0.0319) time: 2.6424 data: 0.0067 max mem: 33370 +Epoch: [37] [ 90/1319] eta: 0:55:26 lr: 4.75807584878992e-06 loss: 0.0324 (0.0324) time: 2.6416 data: 0.0066 max mem: 33370 +Epoch: [37] [ 100/1319] eta: 0:54:51 lr: 4.7469976733450685e-06 loss: 0.0315 (0.0331) time: 2.6326 data: 0.0065 max mem: 33370 +Epoch: [37] [ 110/1319] eta: 0:54:17 lr: 4.735916624553454e-06 loss: 0.0281 (0.0326) time: 2.6411 data: 0.0067 max mem: 33370 +Epoch: [37] [ 120/1319] eta: 0:53:47 lr: 4.724832694195895e-06 loss: 0.0274 (0.0326) time: 2.6506 data: 0.0068 max mem: 33370 +Epoch: [37] [ 130/1319] eta: 0:53:13 lr: 4.713745874008202e-06 loss: 0.0274 (0.0322) time: 2.6373 data: 0.0066 max mem: 33370 +Epoch: [37] [ 140/1319] eta: 0:52:46 lr: 4.702656155680819e-06 loss: 0.0260 (0.0322) time: 2.6459 data: 0.0066 max mem: 33370 +Epoch: [37] [ 150/1319] eta: 0:52:18 lr: 4.691563530858464e-06 loss: 0.0308 (0.0323) time: 2.6743 data: 0.0067 max mem: 33370 +Epoch: [37] [ 160/1319] eta: 0:51:46 lr: 4.6804679911397265e-06 loss: 0.0319 (0.0322) time: 2.6443 data: 0.0066 max mem: 33370 +Epoch: [37] [ 170/1319] eta: 0:51:18 lr: 4.66936952807673e-06 loss: 0.0289 (0.0321) time: 2.6408 data: 0.0065 max mem: 33370 +Epoch: [37] [ 180/1319] eta: 0:50:48 lr: 4.65826813317473e-06 loss: 0.0278 (0.0320) time: 2.6475 data: 0.0065 max mem: 33370 +Epoch: [37] [ 190/1319] eta: 0:50:20 lr: 4.64716379789173e-06 loss: 0.0309 (0.0321) time: 2.6424 data: 0.0064 max mem: 33370 +Epoch: [37] [ 200/1319] eta: 0:49:51 lr: 4.636056513638103e-06 loss: 0.0312 (0.0322) time: 2.6418 data: 0.0065 max mem: 33370 +Epoch: [37] [ 210/1319] eta: 0:49:24 lr: 4.6249462717761695e-06 loss: 0.0344 (0.0326) time: 2.6522 data: 0.0066 max mem: 33370 +Epoch: [37] [ 220/1319] eta: 0:48:54 lr: 4.6138330636198426e-06 loss: 0.0325 (0.0325) time: 2.6429 data: 0.0067 max mem: 33370 +Epoch: [37] [ 230/1319] eta: 0:48:26 lr: 4.602716880434195e-06 loss: 0.0304 (0.0323) time: 2.6255 data: 0.0068 max mem: 33370 +Epoch: [37] [ 240/1319] eta: 0:47:59 lr: 4.591597713435064e-06 loss: 0.0319 (0.0326) time: 2.6483 data: 0.0066 max mem: 33370 +Epoch: [37] [ 250/1319] eta: 0:47:32 lr: 4.580475553788638e-06 loss: 0.0313 (0.0325) time: 2.6543 data: 0.0065 max mem: 33370 +Epoch: [37] [ 260/1319] eta: 0:47:02 lr: 4.569350392611047e-06 loss: 0.0279 (0.0326) time: 2.6270 data: 0.0066 max mem: 33370 +Epoch: [37] [ 270/1319] eta: 0:46:33 lr: 4.558222220967921e-06 loss: 0.0319 (0.0328) time: 2.5960 data: 0.0066 max mem: 33370 +Epoch: [37] [ 280/1319] eta: 0:46:05 lr: 4.547091029873999e-06 loss: 0.0319 (0.0327) time: 2.6121 data: 0.0066 max mem: 33370 +Epoch: [37] [ 290/1319] eta: 0:45:37 lr: 4.5359568102926745e-06 loss: 0.0289 (0.0327) time: 2.6227 data: 0.0066 max mem: 33370 +Epoch: [37] [ 300/1319] eta: 0:45:10 lr: 4.524819553135574e-06 loss: 0.0302 (0.0326) time: 2.6367 data: 0.0066 max mem: 33370 +Epoch: [37] [ 310/1319] eta: 0:44:42 lr: 4.5136792492621144e-06 loss: 0.0303 (0.0326) time: 2.6389 data: 0.0064 max mem: 33370 +Epoch: [37] [ 320/1319] eta: 0:44:14 lr: 4.502535889479041e-06 loss: 0.0280 (0.0325) time: 2.6202 data: 0.0063 max mem: 33370 +Epoch: [37] [ 330/1319] eta: 0:43:48 lr: 4.491389464540016e-06 loss: 0.0274 (0.0324) time: 2.6411 data: 0.0065 max mem: 33370 +Epoch: [37] [ 340/1319] eta: 0:43:19 lr: 4.480239965145135e-06 loss: 0.0286 (0.0325) time: 2.6279 data: 0.0065 max mem: 33370 +Epoch: [37] [ 350/1319] eta: 0:42:52 lr: 4.469087381940477e-06 loss: 0.0300 (0.0324) time: 2.6021 data: 0.0065 max mem: 33370 +Epoch: [37] [ 360/1319] eta: 0:42:24 lr: 4.457931705517646e-06 loss: 0.0267 (0.0323) time: 2.6092 data: 0.0065 max mem: 33370 +Epoch: [37] [ 370/1319] eta: 0:41:57 lr: 4.446772926413276e-06 loss: 0.0270 (0.0324) time: 2.6338 data: 0.0066 max mem: 33370 +Epoch: [37] [ 380/1319] eta: 0:41:31 lr: 4.435611035108594e-06 loss: 0.0283 (0.0322) time: 2.6482 data: 0.0064 max mem: 33370 +Epoch: [37] [ 390/1319] eta: 0:41:03 lr: 4.424446022028913e-06 loss: 0.0307 (0.0323) time: 2.6217 data: 0.0065 max mem: 33370 +Epoch: [37] [ 400/1319] eta: 0:40:36 lr: 4.413277877543152e-06 loss: 0.0321 (0.0322) time: 2.6186 data: 0.0066 max mem: 33370 +Epoch: [37] [ 410/1319] eta: 0:40:09 lr: 4.40210659196335e-06 loss: 0.0305 (0.0323) time: 2.6245 data: 0.0064 max mem: 33370 +Epoch: [37] [ 420/1319] eta: 0:39:42 lr: 4.390932155544163e-06 loss: 0.0331 (0.0324) time: 2.6307 data: 0.0064 max mem: 33370 +Epoch: [37] [ 430/1319] eta: 0:39:15 lr: 4.379754558482349e-06 loss: 0.0295 (0.0323) time: 2.6280 data: 0.0065 max mem: 33370 +Epoch: [37] [ 440/1319] eta: 0:38:47 lr: 4.368573790916289e-06 loss: 0.0269 (0.0323) time: 2.6051 data: 0.0065 max mem: 33370 +Epoch: [37] [ 450/1319] eta: 0:38:21 lr: 4.357389842925446e-06 loss: 0.0274 (0.0323) time: 2.6196 data: 0.0063 max mem: 33370 +Epoch: [37] [ 460/1319] eta: 0:37:54 lr: 4.346202704529857e-06 loss: 0.0306 (0.0323) time: 2.6361 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eta: 0:27:16 lr: 4.076727216457151e-06 loss: 0.0296 (0.0325) time: 2.6335 data: 0.0064 max mem: 33370 +Epoch: [37] [ 710/1319] eta: 0:26:49 lr: 4.065456889184196e-06 loss: 0.0333 (0.0325) time: 2.6133 data: 0.0063 max mem: 33370 +Epoch: [37] [ 720/1319] eta: 0:26:23 lr: 4.054183089304276e-06 loss: 0.0335 (0.0325) time: 2.6197 data: 0.0063 max mem: 33370 +Epoch: [37] [ 730/1319] eta: 0:25:56 lr: 4.0429058050112415e-06 loss: 0.0317 (0.0325) time: 2.6336 data: 0.0065 max mem: 33370 +Epoch: [37] [ 740/1319] eta: 0:25:30 lr: 4.031625024422082e-06 loss: 0.0317 (0.0325) time: 2.6246 data: 0.0065 max mem: 33370 +Epoch: [37] [ 750/1319] eta: 0:25:03 lr: 4.020340735576163e-06 loss: 0.0334 (0.0325) time: 2.6285 data: 0.0066 max mem: 33370 +Epoch: [37] [ 760/1319] eta: 0:24:37 lr: 4.0090529264345135e-06 loss: 0.0321 (0.0325) time: 2.6388 data: 0.0066 max mem: 33370 +Epoch: [37] [ 770/1319] eta: 0:24:10 lr: 3.997761584879033e-06 loss: 0.0296 (0.0325) time: 2.6163 data: 0.0065 max mem: 33370 +Epoch: 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time: 2.6160 data: 0.0063 max mem: 33370 +Epoch: [37] [1020/1319] eta: 0:13:09 lr: 3.714292849713318e-06 loss: 0.0286 (0.0327) time: 2.6193 data: 0.0062 max mem: 33370 +Epoch: [37] [1030/1319] eta: 0:12:42 lr: 3.7029051332087708e-06 loss: 0.0313 (0.0327) time: 2.6439 data: 0.0063 max mem: 33370 +Epoch: [37] [1040/1319] eta: 0:12:16 lr: 3.691513524125288e-06 loss: 0.0277 (0.0326) time: 2.6409 data: 0.0065 max mem: 33370 +Epoch: [37] [1050/1319] eta: 0:11:49 lr: 3.680118007776355e-06 loss: 0.0290 (0.0327) time: 2.6331 data: 0.0067 max mem: 33370 +Epoch: [37] [1060/1319] eta: 0:11:23 lr: 3.6687185693693123e-06 loss: 0.0329 (0.0326) time: 2.6432 data: 0.0067 max mem: 33370 +Epoch: [37] [1070/1319] eta: 0:10:57 lr: 3.657315194004196e-06 loss: 0.0300 (0.0326) time: 2.6414 data: 0.0066 max mem: 33370 +Epoch: [37] [1080/1319] eta: 0:10:30 lr: 3.6459078666726217e-06 loss: 0.0288 (0.0327) time: 2.6333 data: 0.0065 max mem: 33370 +Epoch: [37] [1090/1319] eta: 0:10:04 lr: 3.6344965722565904e-06 loss: 0.0288 (0.0327) time: 2.6673 data: 0.0063 max mem: 33370 +Epoch: [37] [1100/1319] eta: 0:09:38 lr: 3.6230812955273095e-06 loss: 0.0299 (0.0327) time: 2.6748 data: 0.0064 max mem: 33370 +Epoch: [37] [1110/1319] eta: 0:09:11 lr: 3.6116620211439967e-06 loss: 0.0300 (0.0327) time: 2.6377 data: 0.0064 max mem: 33370 +Epoch: [37] [1120/1319] eta: 0:08:45 lr: 3.6002387336526318e-06 loss: 0.0300 (0.0327) time: 2.6211 data: 0.0064 max mem: 33370 +Epoch: [37] [1130/1319] eta: 0:08:18 lr: 3.588811417484761e-06 loss: 0.0319 (0.0327) time: 2.6374 data: 0.0064 max mem: 33370 +Epoch: [37] [1140/1319] eta: 0:07:52 lr: 3.577380056956213e-06 loss: 0.0288 (0.0327) time: 2.6443 data: 0.0064 max mem: 33370 +Epoch: [37] [1150/1319] eta: 0:07:26 lr: 3.5659446362658317e-06 loss: 0.0274 (0.0327) time: 2.6390 data: 0.0065 max mem: 33370 +Epoch: [37] [1160/1319] eta: 0:06:59 lr: 3.5545051394941854e-06 loss: 0.0323 (0.0327) time: 2.6675 data: 0.0066 max mem: 33370 +Epoch: [37] [1170/1319] eta: 0:06:33 lr: 3.5430615506022587e-06 loss: 0.0341 (0.0327) time: 2.6650 data: 0.0065 max mem: 33370 +Epoch: [37] [1180/1319] eta: 0:06:06 lr: 3.531613853430098e-06 loss: 0.0321 (0.0327) time: 2.6272 data: 0.0065 max mem: 33370 +Epoch: [37] [1190/1319] eta: 0:05:40 lr: 3.5201620316954973e-06 loss: 0.0290 (0.0326) time: 2.6436 data: 0.0065 max mem: 33370 +Epoch: [37] [1200/1319] eta: 0:05:14 lr: 3.5087060689926057e-06 loss: 0.0278 (0.0326) time: 2.6667 data: 0.0063 max mem: 33370 +Epoch: [37] [1210/1319] eta: 0:04:47 lr: 3.4972459487905388e-06 loss: 0.0292 (0.0326) time: 2.6420 data: 0.0063 max mem: 33370 +Epoch: [37] [1220/1319] eta: 0:04:21 lr: 3.485781654431977e-06 loss: 0.0292 (0.0326) time: 2.6431 data: 0.0064 max mem: 33370 +Epoch: [37] [1230/1319] eta: 0:03:54 lr: 3.4743131691317023e-06 loss: 0.0326 (0.0327) time: 2.6247 data: 0.0063 max mem: 33370 +Epoch: [37] [1240/1319] eta: 0:03:28 lr: 3.462840475975186e-06 loss: 0.0379 (0.0327) time: 2.5986 data: 0.0063 max mem: 33370 +Epoch: [37] 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+/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 1:56:55 time: 2.7265 data: 2.6063 max mem: 33370 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 100/2573] eta: 0:04:03 time: 0.0715 data: 0.0011 max mem: 33370 +Test: [ 200/2573] eta: 0:03:25 time: 0.0733 data: 0.0011 max mem: 33370 +Test: [ 300/2573] eta: 0:03:05 time: 0.0749 data: 0.0011 max mem: 33370 +Test: [ 400/2573] eta: 0:02:52 time: 0.0751 data: 0.0011 max mem: 33370 +Test: [ 500/2573] eta: 0:02:42 time: 0.0735 data: 0.0011 max mem: 33370 +Test: [ 600/2573] eta: 0:02:33 time: 0.0737 data: 0.0011 max mem: 33370 +Test: [ 700/2573] eta: 0:02:25 time: 0.0737 data: 0.0011 max mem: 33370 +Test: [ 800/2573] eta: 0:02:16 time: 0.0769 data: 0.0011 max mem: 33370 +Test: [ 900/2573] eta: 0:02:08 time: 0.0738 data: 0.0011 max mem: 33370 +Test: [1000/2573] eta: 0:02:00 time: 0.0738 data: 0.0011 max mem: 33370 +Test: [1100/2573] eta: 0:01:52 time: 0.0738 data: 0.0011 max mem: 33370 +Test: [1200/2573] eta: 0:01:44 time: 0.0738 data: 0.0011 max mem: 33370 +Test: [1300/2573] eta: 0:01:36 time: 0.0739 data: 0.0011 max mem: 33370 +Test: [1400/2573] eta: 0:01:28 time: 0.0720 data: 0.0011 max mem: 33370 +Test: [1500/2573] eta: 0:01:21 time: 0.0738 data: 0.0011 max mem: 33370 +Test: [1600/2573] eta: 0:01:13 time: 0.0771 data: 0.0011 max mem: 33370 +Test: [1700/2573] eta: 0:01:05 time: 0.0721 data: 0.0011 max mem: 33370 +Test: [1800/2573] eta: 0:00:58 time: 0.0754 data: 0.0011 max mem: 33370 +Test: [1900/2573] eta: 0:00:50 time: 0.0720 data: 0.0011 max mem: 33370 +Test: [2000/2573] eta: 0:00:43 time: 0.0738 data: 0.0011 max mem: 33370 +Test: [2100/2573] eta: 0:00:35 time: 0.0755 data: 0.0011 max mem: 33370 +Test: [2200/2573] eta: 0:00:27 time: 0.0754 data: 0.0011 max mem: 33370 +Test: [2300/2573] eta: 0:00:20 time: 0.0755 data: 0.0011 max mem: 33370 +Test: [2400/2573] eta: 0:00:12 time: 0.0704 data: 0.0011 max mem: 33370 +Test: [2500/2573] eta: 0:00:05 time: 0.0738 data: 0.0011 max mem: 33370 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: Total time: 0:03:12 +Final results: +Mean IoU is 65.15 + + precision@0.5 = 73.33 + precision@0.6 = 68.32 + precision@0.7 = 61.62 + precision@0.8 = 50.20 + precision@0.9 = 26.10 + overall IoU = 62.52 + +Average object IoU 65.15217030910529 +Overall IoU 62.517478942871094 +Better epoch: 37 + +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [38] [ 0/1319] eta: 1:23:28 lr: 3.3720562685558925e-06 loss: 0.0269 (0.0269) time: 3.7969 data: 1.1459 max mem: 33370 +Epoch: [38] [ 10/1319] eta: 1:00:16 lr: 3.3605453588871517e-06 loss: 0.0322 (0.0325) time: 2.7630 data: 0.1099 max mem: 33370 +Epoch: [38] [ 20/1319] eta: 0:58:52 lr: 3.349030066603249e-06 loss: 0.0309 (0.0316) time: 2.6654 data: 0.0061 max mem: 33370 +Epoch: [38] [ 30/1319] eta: 0:58:08 lr: 3.3375103732791936e-06 loss: 0.0309 (0.0329) time: 2.6750 data: 0.0064 max mem: 33370 +Epoch: [38] [ 40/1319] eta: 0:57:11 lr: 3.3259862603415314e-06 loss: 0.0327 (0.0331) time: 2.6451 data: 0.0067 max mem: 33370 +Epoch: [38] [ 50/1319] eta: 0:56:40 lr: 3.314457709066606e-06 loss: 0.0334 (0.0332) time: 2.6377 data: 0.0065 max mem: 33370 +Epoch: [38] [ 60/1319] eta: 0:56:09 lr: 3.302924700578736e-06 loss: 0.0319 (0.0332) time: 2.6631 data: 0.0064 max mem: 33370 +Epoch: [38] [ 70/1319] eta: 0:55:44 lr: 3.2913872158483893e-06 loss: 0.0303 (0.0333) time: 2.6750 data: 0.0065 max mem: 33370 +Epoch: [38] [ 80/1319] eta: 0:55:06 lr: 3.279845235690334e-06 loss: 0.0274 (0.0325) time: 2.6431 data: 0.0066 max mem: 33370 +Epoch: [38] [ 90/1319] eta: 0:54:31 lr: 3.268298740761722e-06 loss: 0.0282 (0.0329) time: 2.6055 data: 0.0067 max mem: 33370 +Epoch: [38] [ 100/1319] eta: 0:54:02 lr: 3.2567477115602124e-06 loss: 0.0304 (0.0326) time: 2.6273 data: 0.0067 max mem: 33370 +Epoch: [38] [ 110/1319] eta: 0:53:31 lr: 3.2451921284219928e-06 loss: 0.0304 (0.0327) time: 2.6291 data: 0.0066 max mem: 33370 +Epoch: [38] [ 120/1319] eta: 0:52:57 lr: 3.233631971519807e-06 loss: 0.0331 (0.0328) time: 2.6005 data: 0.0065 max mem: 33370 +Epoch: [38] [ 130/1319] eta: 0:52:30 lr: 3.2220672208609392e-06 loss: 0.0284 (0.0324) time: 2.6157 data: 0.0065 max mem: 33370 +Epoch: [38] [ 140/1319] eta: 0:52:00 lr: 3.2104978562851772e-06 loss: 0.0264 (0.0320) time: 2.6244 data: 0.0068 max mem: 33370 +Epoch: [38] [ 150/1319] eta: 0:51:31 lr: 3.1989238574627024e-06 loss: 0.0281 (0.0321) time: 2.6094 data: 0.0067 max mem: 33370 +Epoch: [38] [ 160/1319] eta: 0:51:04 lr: 3.18734520389202e-06 loss: 0.0286 (0.0318) time: 2.6291 data: 0.0066 max mem: 33370 +Epoch: [38] [ 170/1319] eta: 0:50:38 lr: 3.175761874897778e-06 loss: 0.0286 (0.0317) time: 2.6460 data: 0.0065 max mem: 33370 +Epoch: [38] [ 180/1319] eta: 0:50:13 lr: 3.1641738496285912e-06 loss: 0.0299 (0.0317) time: 2.6578 data: 0.0064 max mem: 33370 +Epoch: [38] [ 190/1319] eta: 0:49:48 lr: 3.1525811070548283e-06 loss: 0.0293 (0.0320) time: 2.6665 data: 0.0065 max mem: 33370 +Epoch: [38] [ 200/1319] eta: 0:49:24 lr: 3.1409836259663234e-06 loss: 0.0294 (0.0320) time: 2.6768 data: 0.0064 max mem: 33370 +Epoch: [38] [ 210/1319] eta: 0:48:56 lr: 3.1293813849701203e-06 loss: 0.0298 (0.0320) time: 2.6558 data: 0.0066 max mem: 33370 +Epoch: [38] [ 220/1319] eta: 0:48:29 lr: 3.1177743624881108e-06 loss: 0.0316 (0.0320) time: 2.6334 data: 0.0066 max mem: 33370 +Epoch: [38] [ 230/1319] eta: 0:48:02 lr: 3.1061625367546658e-06 loss: 0.0287 (0.0317) time: 2.6357 data: 0.0066 max mem: 33370 +Epoch: [38] [ 240/1319] eta: 0:47:37 lr: 3.0945458858142194e-06 loss: 0.0279 (0.0317) time: 2.6593 data: 0.0067 max mem: 33370 +Epoch: [38] [ 250/1319] eta: 0:47:10 lr: 3.08292438751882e-06 loss: 0.0290 (0.0318) time: 2.6630 data: 0.0068 max mem: 33370 +Epoch: [38] [ 260/1319] eta: 0:46:43 lr: 3.071298019525602e-06 loss: 0.0324 (0.0318) time: 2.6380 data: 0.0070 max mem: 33370 +Epoch: [38] [ 270/1319] eta: 0:46:27 lr: 3.0596667592942867e-06 loss: 0.0337 (0.0320) time: 2.7690 data: 0.0076 max mem: 33370 +Epoch: [38] [ 280/1319] eta: 0:46:02 lr: 3.048030584084566e-06 loss: 0.0337 (0.0322) time: 2.8082 data: 0.0077 max mem: 33370 +Epoch: [38] [ 290/1319] eta: 0:45:37 lr: 3.036389470953479e-06 loss: 0.0320 (0.0322) time: 2.7088 data: 0.0074 max mem: 33370 +Epoch: [38] [ 300/1319] eta: 0:45:10 lr: 3.024743396752744e-06 loss: 0.0292 (0.0321) time: 2.6732 data: 0.0070 max mem: 33370 +Epoch: [38] [ 310/1319] eta: 0:44:42 lr: 3.013092338126003e-06 loss: 0.0289 (0.0321) time: 2.6351 data: 0.0065 max mem: 33370 +Epoch: [38] [ 320/1319] eta: 0:44:15 lr: 3.0014362715060913e-06 loss: 0.0318 (0.0321) time: 2.6232 data: 0.0068 max mem: 33370 +Epoch: [38] [ 330/1319] eta: 0:43:46 lr: 2.9897751731121923e-06 loss: 0.0313 (0.0321) time: 2.6051 data: 0.0068 max mem: 33370 +Epoch: [38] [ 340/1319] eta: 0:43:21 lr: 2.978109018946967e-06 loss: 0.0283 (0.0320) time: 2.6446 data: 0.0066 max mem: 33370 +Epoch: [38] [ 350/1319] eta: 0:42:54 lr: 2.9664377847936435e-06 loss: 0.0261 (0.0319) time: 2.6712 data: 0.0064 max mem: 33370 +Epoch: [38] [ 360/1319] eta: 0:42:27 lr: 2.954761446213011e-06 loss: 0.0261 (0.0319) time: 2.6469 data: 0.0064 max mem: 33370 +Epoch: [38] [ 370/1319] eta: 0:41:59 lr: 2.943079978540434e-06 loss: 0.0285 (0.0319) time: 2.6305 data: 0.0066 max mem: 33370 +Epoch: [38] [ 380/1319] eta: 0:41:32 lr: 2.931393356882739e-06 loss: 0.0297 (0.0319) time: 2.6207 data: 0.0068 max mem: 33370 +Epoch: [38] [ 390/1319] eta: 0:41:05 lr: 2.919701556115084e-06 loss: 0.0297 (0.0319) time: 2.6230 data: 0.0067 max mem: 33370 +Epoch: [38] [ 400/1319] eta: 0:40:38 lr: 2.908004550877762e-06 loss: 0.0309 (0.0319) time: 2.6287 data: 0.0065 max mem: 33370 +Epoch: [38] [ 410/1319] eta: 0:40:10 lr: 2.8963023155729493e-06 loss: 0.0313 (0.0320) time: 2.6224 data: 0.0065 max mem: 33370 +Epoch: [38] [ 420/1319] eta: 0:39:44 lr: 2.884594824361366e-06 loss: 0.0301 (0.0320) time: 2.6326 data: 0.0066 max mem: 33370 +Epoch: [38] [ 430/1319] eta: 0:39:18 lr: 2.8728820511589384e-06 loss: 0.0296 (0.0320) time: 2.6725 data: 0.0066 max mem: 33370 +Epoch: [38] [ 440/1319] eta: 0:38:51 lr: 2.861163969633332e-06 loss: 0.0300 (0.0319) time: 2.6547 data: 0.0066 max mem: 33370 +Epoch: [38] [ 450/1319] eta: 0:38:24 lr: 2.849440553200456e-06 loss: 0.0285 (0.0319) time: 2.6344 data: 0.0067 max mem: 33370 +Epoch: [38] [ 460/1319] eta: 0:37:58 lr: 2.837711775020899e-06 loss: 0.0292 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(0.0317) time: 2.6231 data: 0.0064 max mem: 33370 +Epoch: [38] [ 860/1319] eta: 0:20:13 lr: 2.3638198820602614e-06 loss: 0.0297 (0.0316) time: 2.6386 data: 0.0064 max mem: 33370 +Epoch: [38] [ 870/1319] eta: 0:19:47 lr: 2.351844430532552e-06 loss: 0.0300 (0.0317) time: 2.6454 data: 0.0064 max mem: 33370 +Epoch: [38] [ 880/1319] eta: 0:19:20 lr: 2.339862199770001e-06 loss: 0.0328 (0.0317) time: 2.6444 data: 0.0064 max mem: 33370 +Epoch: [38] [ 890/1319] eta: 0:18:54 lr: 2.327873147317513e-06 loss: 0.0311 (0.0317) time: 2.6425 data: 0.0064 max mem: 33370 +Epoch: [38] [ 900/1319] eta: 0:18:27 lr: 2.315877230209485e-06 loss: 0.0292 (0.0316) time: 2.6407 data: 0.0064 max mem: 33370 +Epoch: [38] [ 910/1319] eta: 0:18:01 lr: 2.303874404960728e-06 loss: 0.0285 (0.0316) time: 2.6114 data: 0.0066 max mem: 33370 +Epoch: [38] [ 920/1319] eta: 0:17:34 lr: 2.291864627557113e-06 loss: 0.0285 (0.0316) time: 2.6335 data: 0.0066 max mem: 33370 +Epoch: [38] [ 930/1319] eta: 0:17:08 lr: 2.2798478534460264e-06 loss: 0.0315 (0.0316) time: 2.6656 data: 0.0064 max mem: 33370 +Epoch: [38] [ 940/1319] eta: 0:16:41 lr: 2.2678240375265906e-06 loss: 0.0274 (0.0316) time: 2.6562 data: 0.0063 max mem: 33370 +Epoch: [38] [ 950/1319] eta: 0:16:15 lr: 2.25579313413962e-06 loss: 0.0268 (0.0316) time: 2.6525 data: 0.0063 max mem: 33370 +Epoch: [38] [ 960/1319] eta: 0:15:49 lr: 2.243755097057401e-06 loss: 0.0273 (0.0316) time: 2.6509 data: 0.0064 max mem: 33370 +Epoch: [38] [ 970/1319] eta: 0:15:22 lr: 2.2317098794731506e-06 loss: 0.0274 (0.0316) time: 2.6383 data: 0.0063 max mem: 33370 +Epoch: [38] [ 980/1319] eta: 0:14:56 lr: 2.2196574339902486e-06 loss: 0.0278 (0.0316) time: 2.6138 data: 0.0063 max mem: 33370 +Epoch: [38] [ 990/1319] eta: 0:14:29 lr: 2.2075977126112046e-06 loss: 0.0347 (0.0316) time: 2.6254 data: 0.0065 max mem: 33370 +Epoch: [38] [1000/1319] eta: 0:14:03 lr: 2.195530666726346e-06 loss: 0.0324 (0.0316) time: 2.6480 data: 0.0066 max mem: 33370 +Epoch: [38] 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mem: 33370 +Epoch: [38] [1090/1319] eta: 0:10:05 lr: 2.086589311928101e-06 loss: 0.0303 (0.0317) time: 2.6641 data: 0.0063 max mem: 33370 +Epoch: [38] [1100/1319] eta: 0:09:38 lr: 2.074446204087186e-06 loss: 0.0330 (0.0318) time: 2.6262 data: 0.0064 max mem: 33370 +Epoch: [38] [1110/1319] eta: 0:09:12 lr: 2.062295193091432e-06 loss: 0.0341 (0.0318) time: 2.6335 data: 0.0063 max mem: 33370 +Epoch: [38] [1120/1319] eta: 0:08:45 lr: 2.050136221989693e-06 loss: 0.0306 (0.0318) time: 2.6205 data: 0.0063 max mem: 33370 +Epoch: [38] [1130/1319] eta: 0:08:19 lr: 2.0379692330421533e-06 loss: 0.0335 (0.0318) time: 2.6175 data: 0.0064 max mem: 33370 +Epoch: [38] [1140/1319] eta: 0:07:53 lr: 2.0257941677041134e-06 loss: 0.0318 (0.0318) time: 2.6557 data: 0.0064 max mem: 33370 +Epoch: [38] [1150/1319] eta: 0:07:26 lr: 2.013610966609312e-06 loss: 0.0311 (0.0318) time: 2.6545 data: 0.0063 max mem: 33370 +Epoch: [38] [1160/1319] eta: 0:07:00 lr: 2.0014195695528014e-06 loss: 0.0311 (0.0318) time: 2.6617 data: 0.0065 max mem: 33370 +Epoch: [38] [1170/1319] eta: 0:06:33 lr: 1.9892199154733075e-06 loss: 0.0299 (0.0318) time: 2.6406 data: 0.0064 max mem: 33370 +Epoch: [38] [1180/1319] eta: 0:06:07 lr: 1.977011942435173e-06 loss: 0.0290 (0.0318) time: 2.6337 data: 0.0063 max mem: 33370 +Epoch: [38] [1190/1319] eta: 0:05:40 lr: 1.964795587609718e-06 loss: 0.0278 (0.0318) time: 2.6425 data: 0.0064 max mem: 33370 +Epoch: [38] [1200/1319] eta: 0:05:14 lr: 1.9525707872561044e-06 loss: 0.0271 (0.0318) time: 2.6406 data: 0.0063 max mem: 33370 +Epoch: [38] [1210/1319] eta: 0:04:48 lr: 1.9403374767016633e-06 loss: 0.0288 (0.0319) time: 2.6406 data: 0.0063 max mem: 33370 +Epoch: [38] [1220/1319] eta: 0:04:21 lr: 1.928095590321611e-06 loss: 0.0315 (0.0319) time: 2.6348 data: 0.0062 max mem: 33370 +Epoch: [38] [1230/1319] eta: 0:03:55 lr: 1.915845061518256e-06 loss: 0.0298 (0.0318) time: 2.6321 data: 0.0064 max mem: 33370 +Epoch: [38] [1240/1319] eta: 0:03:28 lr: 1.9035858226995284e-06 loss: 0.0258 (0.0318) time: 2.6260 data: 0.0064 max mem: 33370 +Epoch: [38] [1250/1319] eta: 0:03:02 lr: 1.8913178052569088e-06 loss: 0.0342 (0.0319) time: 2.6433 data: 0.0063 max mem: 33370 +Epoch: [38] [1260/1319] eta: 0:02:35 lr: 1.8790409395427117e-06 loss: 0.0353 (0.0319) time: 2.6449 data: 0.0065 max mem: 33370 +Epoch: [38] [1270/1319] eta: 0:02:09 lr: 1.8667551548466507e-06 loss: 0.0325 (0.0319) time: 2.6219 data: 0.0066 max mem: 33370 +Epoch: [38] [1280/1319] eta: 0:01:43 lr: 1.8544603793717773e-06 loss: 0.0319 (0.0320) time: 2.6372 data: 0.0065 max mem: 33370 +Epoch: [38] [1290/1319] eta: 0:01:16 lr: 1.8421565402096163e-06 loss: 0.0300 (0.0320) time: 2.6504 data: 0.0065 max mem: 33370 +Epoch: [38] [1300/1319] eta: 0:00:50 lr: 1.8298435633145817e-06 loss: 0.0274 (0.0320) time: 2.6328 data: 0.0064 max mem: 33370 +Epoch: [38] [1310/1319] eta: 0:00:23 lr: 1.8175213734776007e-06 loss: 0.0285 (0.0320) time: 2.6010 data: 0.0064 max mem: 33370 +Epoch: [38] Total time: 0:58:04 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 1:39:46 time: 2.3266 data: 2.1497 max mem: 33370 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 100/2573] eta: 0:03:58 time: 0.0717 data: 0.0011 max mem: 33370 +Test: [ 200/2573] eta: 0:03:22 time: 0.0736 data: 0.0011 max mem: 33370 +Test: [ 300/2573] eta: 0:03:04 time: 0.0752 data: 0.0011 max mem: 33370 +Test: [ 400/2573] eta: 0:02:52 time: 0.0754 data: 0.0011 max mem: 33370 +Test: [ 500/2573] eta: 0:02:41 time: 0.0739 data: 0.0011 max mem: 33370 +Test: [ 600/2573] eta: 0:02:32 time: 0.0739 data: 0.0011 max mem: 33370 +Test: [ 700/2573] eta: 0:02:24 time: 0.0740 data: 0.0011 max mem: 33370 +Test: [ 800/2573] eta: 0:02:16 time: 0.0773 data: 0.0011 max mem: 33370 +Test: [ 900/2573] eta: 0:02:08 time: 0.0740 data: 0.0011 max mem: 33370 +Test: [1000/2573] eta: 0:02:00 time: 0.0737 data: 0.0011 max mem: 33370 +Test: [1100/2573] eta: 0:01:52 time: 0.0738 data: 0.0011 max mem: 33370 +Test: [1200/2573] eta: 0:01:44 time: 0.0738 data: 0.0011 max mem: 33370 +Test: [1300/2573] eta: 0:01:36 time: 0.0738 data: 0.0011 max mem: 33370 +Test: [1400/2573] eta: 0:01:28 time: 0.0720 data: 0.0011 max mem: 33370 +Test: [1500/2573] eta: 0:01:21 time: 0.0737 data: 0.0011 max mem: 33370 +Test: [1600/2573] eta: 0:01:13 time: 0.0770 data: 0.0011 max mem: 33370 +Test: [1700/2573] eta: 0:01:05 time: 0.0721 data: 0.0011 max mem: 33370 +Test: [1800/2573] eta: 0:00:58 time: 0.0753 data: 0.0011 max mem: 33370 +Test: [1900/2573] eta: 0:00:50 time: 0.0720 data: 0.0011 max mem: 33370 +Test: [2000/2573] eta: 0:00:43 time: 0.0737 data: 0.0011 max mem: 33370 +Test: [2100/2573] eta: 0:00:35 time: 0.0753 data: 0.0011 max mem: 33370 +Test: [2200/2573] eta: 0:00:27 time: 0.0754 data: 0.0011 max mem: 33370 +Test: [2300/2573] eta: 0:00:20 time: 0.0754 data: 0.0011 max mem: 33370 +Test: [2400/2573] eta: 0:00:12 time: 0.0704 data: 0.0011 max mem: 33370 +Test: [2500/2573] eta: 0:00:05 time: 0.0738 data: 0.0011 max mem: 33370 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: Total time: 0:03:12 +Final results: +Mean IoU is 65.19 + + precision@0.5 = 73.51 + precision@0.6 = 68.38 + precision@0.7 = 61.87 + precision@0.8 = 50.53 + precision@0.9 = 26.08 + overall IoU = 62.56 + +Average object IoU 65.19486269817727 +Overall IoU 62.55509567260742 +Better epoch: 38 + +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [39] [ 0/1319] eta: 1:24:47 lr: 1.8064234624396156e-06 loss: 0.0371 (0.0371) time: 3.8572 data: 1.0875 max mem: 33370 +Epoch: [39] [ 10/1319] eta: 1:00:07 lr: 1.7940835565249508e-06 loss: 0.0328 (0.0309) time: 2.7557 data: 0.1048 max mem: 33370 +Epoch: [39] [ 20/1319] eta: 0:58:47 lr: 1.7817342127276263e-06 loss: 0.0299 (0.0333) time: 2.6584 data: 0.0064 max mem: 33370 +Epoch: [39] [ 30/1319] eta: 0:57:51 lr: 1.7693753510331764e-06 loss: 0.0292 (0.0315) time: 2.6591 data: 0.0064 max mem: 33370 +Epoch: [39] [ 40/1319] eta: 0:57:09 lr: 1.757006890122028e-06 loss: 0.0299 (0.0328) time: 2.6464 data: 0.0065 max mem: 33370 +Epoch: [39] [ 50/1319] eta: 0:56:28 lr: 1.7446287473378005e-06 loss: 0.0315 (0.0328) time: 2.6351 data: 0.0066 max mem: 33370 +Epoch: [39] [ 60/1319] eta: 0:55:52 lr: 1.7322408386546176e-06 loss: 0.0312 (0.0321) time: 2.6230 data: 0.0068 max mem: 33370 +Epoch: [39] [ 70/1319] eta: 0:55:21 lr: 1.7198430786433514e-06 loss: 0.0312 (0.0320) time: 2.6322 data: 0.0067 max mem: 33370 +Epoch: [39] [ 80/1319] eta: 0:54:48 lr: 1.7074353804367206e-06 loss: 0.0314 (0.0322) time: 2.6301 data: 0.0067 max mem: 33370 +Epoch: [39] [ 90/1319] eta: 0:54:21 lr: 1.6950176556933094e-06 loss: 0.0333 (0.0321) time: 2.6324 data: 0.0066 max mem: 33370 +Epoch: [39] [ 100/1319] eta: 0:53:51 lr: 1.682589814560305e-06 loss: 0.0343 (0.0329) time: 2.6349 data: 0.0066 max mem: 33370 +Epoch: [39] [ 110/1319] eta: 0:53:24 lr: 1.6701517656350208e-06 loss: 0.0338 (0.0329) time: 2.6362 data: 0.0066 max mem: 33370 +Epoch: [39] [ 120/1319] eta: 0:52:53 lr: 1.6577034159251048e-06 loss: 0.0310 (0.0324) time: 2.6288 data: 0.0067 max mem: 33370 +Epoch: [39] [ 130/1319] eta: 0:52:26 lr: 1.6452446708073954e-06 loss: 0.0283 (0.0323) time: 2.6234 data: 0.0066 max mem: 33370 +Epoch: [39] [ 140/1319] eta: 0:52:01 lr: 1.632775433985313e-06 loss: 0.0283 (0.0321) time: 2.6526 data: 0.0065 max mem: 33370 +Epoch: [39] [ 150/1319] eta: 0:51:29 lr: 1.62029560744485e-06 loss: 0.0274 (0.0317) time: 2.6205 data: 0.0068 max mem: 33370 +Epoch: [39] [ 160/1319] eta: 0:51:03 lr: 1.6078050914089353e-06 loss: 0.0299 (0.0319) time: 2.6127 data: 0.0068 max mem: 33370 +Epoch: [39] [ 170/1319] eta: 0:50:35 lr: 1.5953037842902214e-06 loss: 0.0309 (0.0321) time: 2.6349 data: 0.0067 max mem: 33370 +Epoch: [39] [ 180/1319] eta: 0:50:10 lr: 1.5827915826421849e-06 loss: 0.0332 (0.0323) time: 2.6404 data: 0.0065 max mem: 33370 +Epoch: [39] [ 190/1319] eta: 0:49:44 lr: 1.5702683811084266e-06 loss: 0.0333 (0.0323) time: 2.6519 data: 0.0065 max mem: 33370 +Epoch: [39] [ 200/1319] eta: 0:49:14 lr: 1.5577340723702017e-06 loss: 0.0319 (0.0323) time: 2.6168 data: 0.0066 max mem: 33370 +Epoch: [39] [ 210/1319] eta: 0:48:46 lr: 1.5451885470919527e-06 loss: 0.0256 (0.0323) time: 2.6029 data: 0.0067 max mem: 33370 +Epoch: [39] [ 220/1319] eta: 0:48:20 lr: 1.5326316938648584e-06 loss: 0.0283 (0.0325) time: 2.6265 data: 0.0067 max mem: 33370 +Epoch: [39] [ 230/1319] eta: 0:47:53 lr: 1.5200633991482792e-06 loss: 0.0289 (0.0322) time: 2.6357 data: 0.0065 max mem: 33370 +Epoch: [39] [ 240/1319] eta: 0:47:27 lr: 1.5074835472089545e-06 loss: 0.0264 (0.0321) time: 2.6350 data: 0.0065 max mem: 33370 +Epoch: [39] [ 250/1319] eta: 0:46:59 lr: 1.4948920200579605e-06 loss: 0.0274 (0.0320) time: 2.6226 data: 0.0064 max mem: 33370 +Epoch: [39] [ 260/1319] eta: 0:46:32 lr: 1.4822886973851744e-06 loss: 0.0272 (0.0319) time: 2.6152 data: 0.0065 max mem: 33370 +Epoch: [39] [ 270/1319] eta: 0:46:06 lr: 1.4696734564912314e-06 loss: 0.0292 (0.0321) time: 2.6362 data: 0.0065 max mem: 33370 +Epoch: [39] [ 280/1319] eta: 0:45:39 lr: 1.457046172216814e-06 loss: 0.0319 (0.0322) time: 2.6340 data: 0.0065 max mem: 33370 +Epoch: [39] [ 290/1319] eta: 0:45:12 lr: 1.444406716869153e-06 loss: 0.0375 (0.0324) time: 2.6190 data: 0.0064 max mem: 33370 +Epoch: [39] [ 300/1319] eta: 0:44:47 lr: 1.4317549601455566e-06 loss: 0.0366 (0.0324) time: 2.6386 data: 0.0064 max mem: 33370 +Epoch: [39] [ 310/1319] eta: 0:44:19 lr: 1.419090769053936e-06 loss: 0.0323 (0.0325) time: 2.6296 data: 0.0065 max mem: 33370 +Epoch: [39] [ 320/1319] eta: 0:43:52 lr: 1.4064140078300187e-06 loss: 0.0323 (0.0325) time: 2.6045 data: 0.0066 max mem: 33370 +Epoch: [39] [ 330/1319] eta: 0:43:26 lr: 1.3937245378511972e-06 loss: 0.0300 (0.0324) time: 2.6275 data: 0.0066 max mem: 33370 +Epoch: [39] [ 340/1319] eta: 0:43:00 lr: 1.3810222175468009e-06 loss: 0.0279 (0.0323) time: 2.6486 data: 0.0066 max mem: 33370 +Epoch: [39] [ 350/1319] eta: 0:42:32 lr: 1.3683069023045655e-06 loss: 0.0291 (0.0323) time: 2.6218 data: 0.0065 max mem: 33370 +Epoch: [39] [ 360/1319] eta: 0:42:07 lr: 1.355578444373217e-06 loss: 0.0287 (0.0321) time: 2.6396 data: 0.0064 max mem: 33370 +Epoch: [39] [ 370/1319] eta: 0:41:41 lr: 1.3428366927608033e-06 loss: 0.0262 (0.0320) time: 2.6607 data: 0.0064 max mem: 33370 +Epoch: [39] [ 380/1319] eta: 0:41:15 lr: 1.330081493128668e-06 loss: 0.0281 (0.0320) time: 2.6433 data: 0.0064 max mem: 33370 +Epoch: [39] [ 390/1319] eta: 0:40:49 lr: 1.3173126876807778e-06 loss: 0.0281 (0.0319) time: 2.6442 data: 0.0064 max mem: 33370 +Epoch: [39] [ 400/1319] eta: 0:40:23 lr: 1.304530115048165e-06 loss: 0.0271 (0.0318) time: 2.6470 data: 0.0064 max mem: 33370 +Epoch: [39] [ 410/1319] eta: 0:39:57 lr: 1.2917336101681678e-06 loss: 0.0262 (0.0318) time: 2.6543 data: 0.0064 max mem: 33370 +Epoch: [39] [ 420/1319] eta: 0:39:31 lr: 1.2789230041582899e-06 loss: 0.0279 (0.0318) time: 2.6598 data: 0.0063 max mem: 33370 +Epoch: [39] [ 430/1319] eta: 0:39:05 lr: 1.2660981241842216e-06 loss: 0.0282 (0.0317) time: 2.6575 data: 0.0064 max mem: 33370 +Epoch: [39] [ 440/1319] eta: 0:38:38 lr: 1.2532587933218004e-06 loss: 0.0282 (0.0317) time: 2.6403 data: 0.0064 max mem: 33370 +Epoch: [39] [ 450/1319] eta: 0:38:11 lr: 1.2404048304125217e-06 loss: 0.0328 (0.0318) time: 2.6016 data: 0.0063 max mem: 33370 +Epoch: [39] [ 460/1319] eta: 0:37:45 lr: 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data: 0.0067 max mem: 33370 +Epoch: [39] [ 700/1319] eta: 0:27:12 lr: 9.136614974653884e-07 loss: 0.0272 (0.0316) time: 2.6443 data: 0.0065 max mem: 33370 +Epoch: [39] [ 710/1319] eta: 0:26:46 lr: 9.003449179133091e-07 loss: 0.0284 (0.0315) time: 2.6490 data: 0.0064 max mem: 33370 +Epoch: [39] [ 720/1319] eta: 0:26:19 lr: 8.870064170319405e-07 loss: 0.0284 (0.0315) time: 2.6443 data: 0.0063 max mem: 33370 +Epoch: [39] [ 730/1319] eta: 0:25:53 lr: 8.736455912114245e-07 loss: 0.0268 (0.0315) time: 2.6201 data: 0.0063 max mem: 33370 +Epoch: [39] [ 740/1319] eta: 0:25:26 lr: 8.602620224130043e-07 loss: 0.0295 (0.0315) time: 2.6151 data: 0.0064 max mem: 33370 +Epoch: [39] [ 750/1319] eta: 0:25:00 lr: 8.468552773943076e-07 loss: 0.0337 (0.0315) time: 2.6266 data: 0.0064 max mem: 33370 +Epoch: [39] [ 760/1319] eta: 0:24:33 lr: 8.334249068786857e-07 loss: 0.0289 (0.0315) time: 2.6366 data: 0.0064 max mem: 33370 +Epoch: [39] [ 770/1319] eta: 0:24:07 lr: 8.199704446634483e-07 loss: 0.0266 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loss: 0.0296 (0.0316) time: 2.6115 data: 0.0064 max mem: 33370 +Epoch: [39] [ 860/1319] eta: 0:20:09 lr: 6.977094839143229e-07 loss: 0.0296 (0.0316) time: 2.6372 data: 0.0065 max mem: 33370 +Epoch: [39] [ 870/1319] eta: 0:19:43 lr: 6.839839465805414e-07 loss: 0.0300 (0.0316) time: 2.6471 data: 0.0065 max mem: 33370 +Epoch: [39] [ 880/1319] eta: 0:19:17 lr: 6.702277349898191e-07 loss: 0.0300 (0.0316) time: 2.6500 data: 0.0064 max mem: 33370 +Epoch: [39] [ 890/1319] eta: 0:18:50 lr: 6.564400777713066e-07 loss: 0.0350 (0.0317) time: 2.6483 data: 0.0064 max mem: 33370 +Epoch: [39] [ 900/1319] eta: 0:18:24 lr: 6.426201656523381e-07 loss: 0.0350 (0.0317) time: 2.6280 data: 0.0064 max mem: 33370 +Epoch: [39] [ 910/1319] eta: 0:17:58 lr: 6.287671486431178e-07 loss: 0.0315 (0.0318) time: 2.6169 data: 0.0064 max mem: 33370 +Epoch: [39] [ 920/1319] eta: 0:17:31 lr: 6.148801329380617e-07 loss: 0.0319 (0.0318) time: 2.6142 data: 0.0063 max mem: 33370 +Epoch: [39] [ 930/1319] eta: 0:17:05 lr: 6.009581774973726e-07 loss: 0.0307 (0.0318) time: 2.6138 data: 0.0065 max mem: 33370 +Epoch: [39] [ 940/1319] eta: 0:16:38 lr: 5.870002902666957e-07 loss: 0.0278 (0.0318) time: 2.6296 data: 0.0066 max mem: 33370 +Epoch: [39] [ 950/1319] eta: 0:16:12 lr: 5.7300542398606e-07 loss: 0.0270 (0.0317) time: 2.6249 data: 0.0065 max mem: 33370 +Epoch: [39] [ 960/1319] eta: 0:15:46 lr: 5.589724715308914e-07 loss: 0.0274 (0.0317) time: 2.6284 data: 0.0066 max mem: 33370 +Epoch: [39] [ 970/1319] eta: 0:15:19 lr: 5.449002607184345e-07 loss: 0.0268 (0.0317) time: 2.6399 data: 0.0065 max mem: 33370 +Epoch: [39] [ 980/1319] eta: 0:14:53 lr: 5.307875485010082e-07 loss: 0.0260 (0.0316) time: 2.6259 data: 0.0065 max mem: 33370 +Epoch: [39] [ 990/1319] eta: 0:14:26 lr: 5.166330144533874e-07 loss: 0.0322 (0.0317) time: 2.6304 data: 0.0066 max mem: 33370 +Epoch: [39] [1000/1319] eta: 0:14:00 lr: 5.024352534442401e-07 loss: 0.0321 (0.0317) time: 2.6379 data: 0.0066 max mem: 33370 +Epoch: [39] [1010/1319] eta: 0:13:34 lr: 4.881927673605746e-07 loss: 0.0311 (0.0317) time: 2.6302 data: 0.0065 max mem: 33370 +Epoch: [39] [1020/1319] eta: 0:13:07 lr: 4.7390395572780197e-07 loss: 0.0301 (0.0317) time: 2.6462 data: 0.0064 max mem: 33370 +Epoch: [39] [1030/1319] eta: 0:12:41 lr: 4.595671050360423e-07 loss: 0.0301 (0.0317) time: 2.6508 data: 0.0066 max mem: 33370 +Epoch: [39] [1040/1319] eta: 0:12:15 lr: 4.4518037654287396e-07 loss: 0.0302 (0.0317) time: 2.6451 data: 0.0065 max mem: 33370 +Epoch: [39] [1050/1319] eta: 0:11:48 lr: 4.3074179227215756e-07 loss: 0.0305 (0.0317) time: 2.6396 data: 0.0066 max mem: 33370 +Epoch: [39] [1060/1319] eta: 0:11:22 lr: 4.162492188647174e-07 loss: 0.0314 (0.0317) time: 2.6443 data: 0.0065 max mem: 33370 +Epoch: [39] [1070/1319] eta: 0:10:56 lr: 4.01700348854669e-07 loss: 0.0286 (0.0316) time: 2.6727 data: 0.0064 max mem: 33370 +Epoch: [39] [1080/1319] eta: 0:10:30 lr: 3.8709267884030336e-07 loss: 0.0284 (0.0316) time: 2.6497 data: 0.0065 max mem: 33370 +Epoch: [39] [1090/1319] eta: 0:10:03 lr: 3.724234838815835e-07 loss: 0.0297 (0.0316) time: 2.6275 data: 0.0065 max mem: 33370 +Epoch: [39] [1100/1319] eta: 0:09:37 lr: 3.5768978727688177e-07 loss: 0.0329 (0.0316) time: 2.6165 data: 0.0066 max mem: 33370 +Epoch: [39] [1110/1319] eta: 0:09:10 lr: 3.428883246336122e-07 loss: 0.0326 (0.0317) time: 2.5883 data: 0.0066 max mem: 33370 +Epoch: [39] [1120/1319] eta: 0:08:44 lr: 3.280155008272766e-07 loss: 0.0302 (0.0317) time: 2.6156 data: 0.0064 max mem: 33370 +Epoch: [39] [1130/1319] eta: 0:08:18 lr: 3.1306733800860497e-07 loss: 0.0302 (0.0316) time: 2.6387 data: 0.0066 max mem: 33370 +Epoch: [39] [1140/1319] eta: 0:07:51 lr: 2.9803941221786203e-07 loss: 0.0301 (0.0317) time: 2.6267 data: 0.0066 max mem: 33370 +Epoch: [39] [1150/1319] eta: 0:07:25 lr: 2.829267753240405e-07 loss: 0.0301 (0.0317) time: 2.6062 data: 0.0065 max mem: 33370 +Epoch: [39] [1160/1319] eta: 0:06:58 lr: 2.677238578071334e-07 loss: 0.0274 (0.0316) time: 2.6045 data: 0.0065 max mem: 33370 +Epoch: [39] [1170/1319] eta: 0:06:32 lr: 2.524243461593822e-07 loss: 0.0274 (0.0316) time: 2.6273 data: 0.0063 max mem: 33370 +Epoch: [39] [1180/1319] eta: 0:06:06 lr: 2.370210260957732e-07 loss: 0.0299 (0.0316) time: 2.6126 data: 0.0063 max mem: 33370 +Epoch: [39] [1190/1319] eta: 0:05:39 lr: 2.2150557883672493e-07 loss: 0.0299 (0.0316) time: 2.6233 data: 0.0064 max mem: 33370 +Epoch: [39] [1200/1319] eta: 0:05:13 lr: 2.058683115970694e-07 loss: 0.0287 (0.0316) time: 2.6623 data: 0.0063 max mem: 33370 +Epoch: [39] [1210/1319] eta: 0:04:47 lr: 1.9009779355624344e-07 loss: 0.0281 (0.0316) time: 2.6571 data: 0.0063 max mem: 33370 +Epoch: [39] [1220/1319] eta: 0:04:20 lr: 1.7418035215766808e-07 loss: 0.0282 (0.0315) time: 2.6321 data: 0.0064 max mem: 33370 +Epoch: [39] [1230/1319] eta: 0:03:54 lr: 1.5809935607220197e-07 loss: 0.0262 (0.0315) time: 2.6150 data: 0.0064 max mem: 33370 +Epoch: [39] [1240/1319] eta: 0:03:28 lr: 1.4183415922236583e-07 loss: 0.0303 (0.0315) time: 2.6226 data: 0.0064 max mem: 33370 +Epoch: [39] [1250/1319] eta: 0:03:01 lr: 1.2535848000328487e-07 loss: 0.0285 (0.0315) time: 2.6483 data: 0.0064 max mem: 33370 +Epoch: [39] [1260/1319] eta: 0:02:35 lr: 1.0863778202227116e-07 loss: 0.0286 (0.0315) time: 2.6430 data: 0.0064 max mem: 33370 +Epoch: [39] [1270/1319] eta: 0:02:09 lr: 9.162475150165058e-08 loss: 0.0319 (0.0315) time: 2.6593 data: 0.0063 max mem: 33370 +Epoch: [39] [1280/1319] eta: 0:01:42 lr: 7.425076510067331e-08 loss: 0.0308 (0.0315) time: 2.6773 data: 0.0062 max mem: 33370 +Epoch: [39] [1290/1319] eta: 0:01:16 lr: 5.640763927216541e-08 loss: 0.0308 (0.0315) time: 2.6581 data: 0.0062 max mem: 33370 +Epoch: [39] [1300/1319] eta: 0:00:50 lr: 3.790015191412361e-08 loss: 0.0309 (0.0316) time: 2.6369 data: 0.0064 max mem: 33370 +Epoch: [39] [1310/1319] eta: 0:00:23 lr: 1.8267397722216235e-08 loss: 0.0301 (0.0316) time: 2.6321 data: 0.0063 max mem: 33370 +Epoch: [39] Total time: 0:57:56 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 1:54:55 time: 2.6798 data: 2.5126 max mem: 33370 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 100/2573] eta: 0:04:01 time: 0.0715 data: 0.0011 max mem: 33370 +Test: [ 200/2573] eta: 0:03:24 time: 0.0734 data: 0.0011 max mem: 33370 +Test: [ 300/2573] eta: 0:03:05 time: 0.0752 data: 0.0011 max mem: 33370 +Test: [ 400/2573] eta: 0:02:52 time: 0.0752 data: 0.0010 max mem: 33370 +Test: [ 500/2573] eta: 0:02:42 time: 0.0737 data: 0.0011 max mem: 33370 +Test: [ 600/2573] eta: 0:02:33 time: 0.0739 data: 0.0011 max mem: 33370 +Test: [ 700/2573] eta: 0:02:24 time: 0.0738 data: 0.0011 max mem: 33370 +Test: [ 800/2573] eta: 0:02:16 time: 0.0770 data: 0.0011 max mem: 33370 +Test: [ 900/2573] eta: 0:02:08 time: 0.0737 data: 0.0011 max mem: 33370 +Test: [1000/2573] eta: 0:02:00 time: 0.0737 data: 0.0011 max mem: 33370 +Test: [1100/2573] eta: 0:01:52 time: 0.0737 data: 0.0011 max mem: 33370 +Test: [1200/2573] eta: 0:01:44 time: 0.0737 data: 0.0011 max mem: 33370 +Test: [1300/2573] eta: 0:01:36 time: 0.0737 data: 0.0011 max mem: 33370 +Test: [1400/2573] eta: 0:01:28 time: 0.0721 data: 0.0011 max mem: 33370 +Test: [1500/2573] eta: 0:01:21 time: 0.0738 data: 0.0011 max mem: 33370 +Test: [1600/2573] eta: 0:01:13 time: 0.0770 data: 0.0011 max mem: 33370 +Test: [1700/2573] eta: 0:01:05 time: 0.0721 data: 0.0011 max mem: 33370 +Test: [1800/2573] eta: 0:00:58 time: 0.0756 data: 0.0011 max mem: 33370 +Test: [1900/2573] eta: 0:00:50 time: 0.0722 data: 0.0011 max mem: 33370 +Test: [2000/2573] eta: 0:00:43 time: 0.0739 data: 0.0011 max mem: 33370 +Test: [2100/2573] eta: 0:00:35 time: 0.0755 data: 0.0011 max mem: 33370 +Test: [2200/2573] eta: 0:00:27 time: 0.0754 data: 0.0011 max mem: 33370 +Test: [2300/2573] eta: 0:00:20 time: 0.0755 data: 0.0011 max mem: 33370 +Test: [2400/2573] eta: 0:00:12 time: 0.0706 data: 0.0011 max mem: 33370 +Test: [2500/2573] eta: 0:00:05 time: 0.0739 data: 0.0011 max mem: 33370 +Test: Total time: 0:03:12 +Final results: +Mean IoU is 65.07 + + precision@0.5 = 73.47 + precision@0.6 = 68.24 + precision@0.7 = 61.87 + precision@0.8 = 50.65 + precision@0.9 = 26.33 + overall IoU = 62.56 + +Average object IoU 65.06565732558522 +Overall IoU 62.56327438354492 +Better epoch: 39 + +Training time 1 day, 18:32:21 diff --git a/LAVT-RIS/logs/old/gref_m10_mg15_tmp007_2gpu_bs16_ang.log b/LAVT-RIS/logs/old/gref_m10_mg15_tmp007_2gpu_bs16_ang.log new file mode 100644 index 0000000000000000000000000000000000000000..1ee5a2fa389efc721c88e1baaf33dfbbb33b926f --- /dev/null +++ b/LAVT-RIS/logs/old/gref_m10_mg15_tmp007_2gpu_bs16_ang.log @@ -0,0 +1,14839 @@ +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torch/distributed/launch.py:178: FutureWarning: The module torch.distributed.launch is deprecated +and will be removed in future. Use torchrun. +Note that --use_env is set by default in torchrun. +If your script expects `--local_rank` argument to be set, please +change it to read from `os.environ['LOCAL_RANK']` instead. See +https://pytorch.org/docs/stable/distributed.html#launch-utility for +further instructions + + warnings.warn( +WARNING:torch.distributed.run: +***************************************** +Setting OMP_NUM_THREADS environment variable for each process to be 1 in default, to avoid your system being overloaded, please further tune the variable for optimal performance in your application as needed. +***************************************** +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/timm/models/layers/__init__.py:48: FutureWarning: Importing from timm.models.layers is deprecated, please import via timm.layers + warnings.warn(f"Importing from {__name__} is deprecated, please import via timm.layers", FutureWarning) +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/timm/models/layers/__init__.py:48: FutureWarning: Importing from timm.models.layers is deprecated, please import via timm.layers + warnings.warn(f"Importing from {__name__} is deprecated, please import via timm.layers", FutureWarning) +RANK and WORLD_SIZE in environment: 1/2RANK and WORLD_SIZE in environment: 0/2 + +Image size: 480 +loading dataset refcocog into memory... +creating index... +index created. +DONE (t=6.63s) +loading dataset refcocog into memory... +creating index... +index created. +DONE (t=6.49s) +local rank 0 / global rank 0 successfully built train dataset. +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torch/utils/data/dataloader.py:557: UserWarning: This DataLoader will create 8 worker processes in total. Our suggested max number of worker in current system is 6, which is smaller than what this DataLoader is going to create. Please be aware that excessive worker creation might get DataLoader running slow or even freeze, lower the worker number to avoid potential slowness/freeze if necessary. + warnings.warn(_create_warning_msg( +lavt_one +Window size 12! +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torch/functional.py:478: UserWarning: torch.meshgrid: in an upcoming release, it will be required to pass the indexing argument. (Triggered internally at ../aten/src/ATen/native/TensorShape.cpp:2894.) + return _VF.meshgrid(tensors, **kwargs) # type: ignore[attr-defined] +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torch/utils/data/dataloader.py:557: UserWarning: This DataLoader will create 8 worker processes in total. Our suggested max number of worker in current system is 6, which is smaller than what this DataLoader is going to create. Please be aware that excessive worker creation might get DataLoader running slow or even freeze, lower the worker number to avoid potential slowness/freeze if necessary. + warnings.warn(_create_warning_msg( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torch/functional.py:478: UserWarning: torch.meshgrid: in an upcoming release, it will be required to pass the indexing argument. (Triggered internally at ../aten/src/ATen/native/TensorShape.cpp:2894.) + return _VF.meshgrid(tensors, **kwargs) # type: ignore[attr-defined] +Initializing Multi-modal Swin Transformer weights from ./pretrained_weights/swin_base_patch4_window12_384_22k.pth +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [0] [ 0/2639] eta: 6:47:04 lr: 4.999957370195798e-05 loss: 0.8235 (0.8235) time: 9.2553 data: 2.8436 max mem: 20156 +Epoch: [0] [ 10/2639] eta: 2:31:04 lr: 4.99953106993255e-05 loss: 0.4739 (0.5141) time: 3.4479 data: 0.2655 max mem: 28287 +Epoch: [0] [ 20/2639] eta: 2:19:15 lr: 4.999104765630397e-05 loss: 0.3239 (0.4164) time: 2.8871 data: 0.0075 max mem: 29995 +Epoch: [0] [ 30/2639] eta: 2:14:39 lr: 4.998678457288919e-05 loss: 0.3103 (0.3871) time: 2.9036 data: 0.0076 max mem: 29995 +Epoch: [0] [ 40/2639] eta: 2:11:45 lr: 4.998252144907695e-05 loss: 0.3009 (0.3643) time: 2.8861 data: 0.0078 max mem: 29995 +Epoch: [0] [ 50/2639] eta: 2:10:03 lr: 4.9978258284863036e-05 loss: 0.2909 (0.3489) time: 2.8863 data: 0.0081 max mem: 29996 +Epoch: [0] [ 60/2639] eta: 2:08:53 lr: 4.997399508024324e-05 loss: 0.2909 (0.3409) time: 2.9100 data: 0.0080 max mem: 31677 +Epoch: [0] [ 70/2639] eta: 2:07:41 lr: 4.996973183521335e-05 loss: 0.2914 (0.3404) time: 2.9012 data: 0.0076 max mem: 31677 +Epoch: [0] [ 80/2639] eta: 2:06:53 lr: 4.996546854976915e-05 loss: 0.2890 (0.3321) time: 2.9042 data: 0.0078 max mem: 31677 +Epoch: [0] [ 90/2639] eta: 2:06:06 lr: 4.9961205223906416e-05 loss: 0.2706 (0.3266) time: 2.9197 data: 0.0080 max mem: 31677 +Epoch: [0] [ 100/2639] eta: 2:05:35 lr: 4.995694185762094e-05 loss: 0.2820 (0.3257) time: 2.9372 data: 0.0078 max mem: 31677 +Epoch: [0] [ 110/2639] eta: 2:04:42 lr: 4.9952678450908516e-05 loss: 0.2677 (0.3246) time: 2.9138 data: 0.0076 max mem: 31677 +Epoch: [0] [ 120/2639] eta: 2:03:54 lr: 4.994841500376492e-05 loss: 0.2530 (0.3199) time: 2.8676 data: 0.0073 max mem: 31677 +Epoch: [0] [ 130/2639] eta: 2:03:06 lr: 4.9944151516185925e-05 loss: 0.2678 (0.3183) time: 2.8633 data: 0.0073 max mem: 31677 +Epoch: [0] [ 140/2639] eta: 2:02:26 lr: 4.993988798816731e-05 loss: 0.2911 (0.3162) time: 2.8701 data: 0.0074 max mem: 31677 +Epoch: [0] [ 150/2639] eta: 2:01:40 lr: 4.9935624419704875e-05 loss: 0.2895 (0.3137) time: 2.8606 data: 0.0078 max mem: 31677 +Epoch: [0] [ 160/2639] eta: 2:00:59 lr: 4.993136081079439e-05 loss: 0.2438 (0.3095) time: 2.8478 data: 0.0082 max mem: 31677 +Epoch: [0] [ 170/2639] eta: 2:00:26 lr: 4.992709716143162e-05 loss: 0.2514 (0.3065) time: 2.8799 data: 0.0080 max mem: 31677 +Epoch: [0] [ 180/2639] eta: 1:59:49 lr: 4.9922833471612366e-05 loss: 0.2525 (0.3032) time: 2.8867 data: 0.0079 max mem: 31677 +Epoch: [0] [ 190/2639] eta: 1:59:13 lr: 4.9918569741332385e-05 loss: 0.2711 (0.3024) time: 2.8720 data: 0.0078 max mem: 31677 +Epoch: [0] [ 200/2639] eta: 1:58:42 lr: 4.9914305970587466e-05 loss: 0.2737 (0.3005) time: 2.8908 data: 0.0073 max mem: 31677 +Epoch: [0] [ 210/2639] eta: 1:58:01 lr: 4.9910042159373386e-05 loss: 0.2419 (0.2981) time: 2.8614 data: 0.0072 max mem: 31677 +Epoch: [0] [ 220/2639] eta: 1:57:34 lr: 4.9905778307685896e-05 loss: 0.2419 (0.2982) time: 2.8738 data: 0.0079 max mem: 31677 +Epoch: [0] [ 230/2639] eta: 1:57:00 lr: 4.99015144155208e-05 loss: 0.2340 (0.2950) time: 2.9028 data: 0.0083 max mem: 31677 +Epoch: [0] [ 240/2639] eta: 1:56:28 lr: 4.989725048287385e-05 loss: 0.2327 (0.2955) time: 2.8779 data: 0.0078 max mem: 31677 +Epoch: [0] [ 250/2639] eta: 1:55:59 lr: 4.989298650974083e-05 loss: 0.2379 (0.2930) time: 2.9009 data: 0.0076 max mem: 31677 +Epoch: [0] [ 260/2639] eta: 1:55:33 lr: 4.988872249611751e-05 loss: 0.2433 (0.2927) time: 2.9310 data: 0.0078 max mem: 31677 +Epoch: [0] [ 270/2639] eta: 1:55:05 lr: 4.988445844199965e-05 loss: 0.2433 (0.2901) time: 2.9362 data: 0.0080 max mem: 31677 +Epoch: [0] [ 280/2639] eta: 1:54:37 lr: 4.988019434738304e-05 loss: 0.2346 (0.2892) time: 2.9303 data: 0.0077 max mem: 31677 +Epoch: [0] [ 290/2639] eta: 1:54:10 lr: 4.987593021226342e-05 loss: 0.2526 (0.2890) time: 2.9349 data: 0.0071 max mem: 31677 +Epoch: [0] [ 300/2639] eta: 1:53:38 lr: 4.987166603663657e-05 loss: 0.2630 (0.2877) time: 2.9095 data: 0.0073 max mem: 31677 +Epoch: [0] [ 310/2639] eta: 1:53:04 lr: 4.9867401820498264e-05 loss: 0.2482 (0.2867) time: 2.8643 data: 0.0075 max mem: 31677 +Epoch: [0] [ 320/2639] eta: 1:52:30 lr: 4.986313756384427e-05 loss: 0.2422 (0.2851) time: 2.8486 data: 0.0074 max mem: 31677 +Epoch: [0] [ 330/2639] eta: 1:52:00 lr: 4.985887326667033e-05 loss: 0.2422 (0.2848) time: 2.8700 data: 0.0077 max mem: 31677 +Epoch: [0] [ 340/2639] eta: 1:51:33 lr: 4.9854608928972235e-05 loss: 0.2559 (0.2838) time: 2.9217 data: 0.0078 max mem: 31677 +Epoch: [0] [ 350/2639] eta: 1:51:06 lr: 4.9850344550745735e-05 loss: 0.2217 (0.2820) time: 2.9419 data: 0.0076 max mem: 31677 +Epoch: [0] [ 360/2639] eta: 1:50:36 lr: 4.98460801319866e-05 loss: 0.2072 (0.2803) time: 2.9205 data: 0.0077 max mem: 31677 +Epoch: [0] [ 370/2639] eta: 1:50:05 lr: 4.984181567269058e-05 loss: 0.2262 (0.2799) time: 2.8923 data: 0.0079 max mem: 31677 +Epoch: [0] [ 380/2639] eta: 1:49:36 lr: 4.983755117285345e-05 loss: 0.2422 (0.2798) time: 2.8993 data: 0.0075 max mem: 31677 +Epoch: [0] [ 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31677 +Epoch: [0] [ 550/2639] eta: 1:41:26 lr: 4.976504846871943e-05 loss: 0.2432 (0.2683) time: 2.9591 data: 0.0081 max mem: 33367 +Epoch: [0] [ 560/2639] eta: 1:40:57 lr: 4.9760783238416335e-05 loss: 0.2344 (0.2676) time: 2.9438 data: 0.0079 max mem: 33367 +Epoch: [0] [ 570/2639] eta: 1:40:29 lr: 4.975651796749142e-05 loss: 0.2028 (0.2670) time: 2.9199 data: 0.0076 max mem: 33367 +Epoch: [0] [ 580/2639] eta: 1:39:59 lr: 4.975225265594042e-05 loss: 0.2028 (0.2663) time: 2.9149 data: 0.0076 max mem: 33367 +Epoch: [0] [ 590/2639] eta: 1:39:32 lr: 4.974798730375909e-05 loss: 0.2146 (0.2657) time: 2.9357 data: 0.0080 max mem: 33367 +Epoch: [0] [ 600/2639] eta: 1:39:01 lr: 4.974372191094317e-05 loss: 0.2525 (0.2660) time: 2.9116 data: 0.0081 max mem: 33367 +Epoch: [0] [ 610/2639] eta: 1:38:32 lr: 4.97394564774884e-05 loss: 0.2655 (0.2662) time: 2.8959 data: 0.0077 max mem: 33367 +Epoch: [0] [ 620/2639] eta: 1:38:02 lr: 4.973519100339051e-05 loss: 0.2229 (0.2656) time: 2.9131 data: 0.0073 max mem: 33367 +Epoch: [0] [ 630/2639] eta: 1:37:33 lr: 4.973092548864526e-05 loss: 0.2121 (0.2650) time: 2.8953 data: 0.0075 max mem: 33367 +Epoch: [0] [ 640/2639] eta: 1:37:03 lr: 4.972665993324837e-05 loss: 0.2210 (0.2647) time: 2.8969 data: 0.0075 max mem: 33367 +Epoch: [0] [ 650/2639] eta: 1:36:33 lr: 4.972239433719559e-05 loss: 0.2418 (0.2643) time: 2.8891 data: 0.0075 max mem: 33367 +Epoch: [0] [ 660/2639] eta: 1:36:02 lr: 4.971812870048265e-05 loss: 0.2147 (0.2635) time: 2.8628 data: 0.0077 max mem: 33367 +Epoch: [0] [ 670/2639] eta: 1:35:33 lr: 4.97138630231053e-05 loss: 0.2303 (0.2637) time: 2.8770 data: 0.0077 max mem: 33367 +Epoch: [0] [ 680/2639] eta: 1:35:02 lr: 4.970959730505925e-05 loss: 0.2555 (0.2634) time: 2.8821 data: 0.0078 max mem: 33367 +Epoch: [0] [ 690/2639] eta: 1:34:32 lr: 4.970533154634026e-05 loss: 0.2341 (0.2632) time: 2.8730 data: 0.0084 max mem: 33367 +Epoch: [0] [ 700/2639] eta: 1:34:04 lr: 4.9701065746944046e-05 loss: 0.2216 (0.2625) time: 2.9107 data: 0.0086 max mem: 33367 +Epoch: [0] [ 710/2639] eta: 1:33:36 lr: 4.969679990686636e-05 loss: 0.2216 (0.2622) time: 2.9485 data: 0.0080 max mem: 33367 +Epoch: [0] [ 720/2639] eta: 1:33:07 lr: 4.969253402610291e-05 loss: 0.2122 (0.2617) time: 2.9472 data: 0.0077 max mem: 33367 +Epoch: [0] [ 730/2639] eta: 1:32:39 lr: 4.968826810464944e-05 loss: 0.2098 (0.2612) time: 2.9272 data: 0.0074 max mem: 33368 +Epoch: [0] [ 740/2639] eta: 1:32:10 lr: 4.9684002142501685e-05 loss: 0.2184 (0.2609) time: 2.9329 data: 0.0081 max mem: 33368 +Epoch: [0] [ 750/2639] eta: 1:31:42 lr: 4.967973613965537e-05 loss: 0.2184 (0.2603) time: 2.9467 data: 0.0085 max mem: 33368 +Epoch: [0] [ 760/2639] eta: 1:31:12 lr: 4.9675470096106215e-05 loss: 0.2082 (0.2599) time: 2.9178 data: 0.0079 max mem: 33368 +Epoch: [0] [ 770/2639] eta: 1:30:44 lr: 4.9671204011849954e-05 loss: 0.1981 (0.2599) time: 2.9227 data: 0.0073 max mem: 33368 +Epoch: [0] [ 780/2639] eta: 1:30:17 lr: 4.966693788688232e-05 loss: 0.2057 (0.2595) time: 2.9801 data: 0.0073 max mem: 33368 +Epoch: [0] [ 790/2639] eta: 1:29:48 lr: 4.966267172119903e-05 loss: 0.2101 (0.2595) time: 2.9575 data: 0.0074 max mem: 33368 +Epoch: [0] [ 800/2639] eta: 1:29:19 lr: 4.965840551479581e-05 loss: 0.2247 (0.2592) time: 2.9250 data: 0.0075 max mem: 33368 +Epoch: [0] [ 810/2639] eta: 1:28:50 lr: 4.965413926766839e-05 loss: 0.2032 (0.2588) time: 2.9212 data: 0.0077 max mem: 33368 +Epoch: [0] [ 820/2639] eta: 1:28:22 lr: 4.96498729798125e-05 loss: 0.2008 (0.2584) time: 2.9356 data: 0.0074 max mem: 33368 +Epoch: [0] [ 830/2639] eta: 1:27:53 lr: 4.964560665122384e-05 loss: 0.2230 (0.2580) time: 2.9486 data: 0.0072 max mem: 33368 +Epoch: [0] [ 840/2639] eta: 1:27:24 lr: 4.964134028189815e-05 loss: 0.2204 (0.2577) time: 2.9219 data: 0.0072 max mem: 33368 +Epoch: [0] [ 850/2639] eta: 1:26:55 lr: 4.9637073871831144e-05 loss: 0.2227 (0.2581) time: 2.9100 data: 0.0073 max mem: 33368 +Epoch: [0] [ 860/2639] eta: 1:26:26 lr: 4.963280742101855e-05 loss: 0.2227 (0.2578) time: 2.9315 data: 0.0072 max mem: 33368 +Epoch: [0] [ 870/2639] eta: 1:25:57 lr: 4.9628540929456074e-05 loss: 0.2159 (0.2576) time: 2.9287 data: 0.0075 max mem: 33368 +Epoch: [0] [ 880/2639] eta: 1:25:28 lr: 4.962427439713945e-05 loss: 0.2201 (0.2574) time: 2.9108 data: 0.0079 max mem: 33368 +Epoch: [0] [ 890/2639] eta: 1:25:00 lr: 4.962000782406438e-05 loss: 0.2412 (0.2573) time: 2.9499 data: 0.0076 max mem: 33368 +Epoch: [0] [ 900/2639] eta: 1:24:32 lr: 4.961574121022658e-05 loss: 0.2176 (0.2569) time: 2.9731 data: 0.0075 max mem: 33368 +Epoch: [0] [ 910/2639] eta: 1:24:02 lr: 4.961147455562178e-05 loss: 0.2083 (0.2568) time: 2.9253 data: 0.0074 max mem: 33368 +Epoch: [0] [ 920/2639] eta: 1:23:32 lr: 4.9607207860245686e-05 loss: 0.2216 (0.2567) time: 2.8780 data: 0.0071 max mem: 33368 +Epoch: [0] [ 930/2639] eta: 1:23:02 lr: 4.960294112409401e-05 loss: 0.2290 (0.2564) time: 2.8578 data: 0.0071 max mem: 33368 +Epoch: [0] [ 940/2639] eta: 1:22:31 lr: 4.9598674347162476e-05 loss: 0.2148 (0.2560) time: 2.8466 data: 0.0073 max mem: 33368 +Epoch: [0] [ 950/2639] eta: 1:22:03 lr: 4.9594407529446787e-05 loss: 0.2148 (0.2558) time: 2.9076 data: 0.0075 max mem: 33368 +Epoch: [0] [ 960/2639] eta: 1:21:34 lr: 4.959014067094265e-05 loss: 0.2243 (0.2558) time: 2.9418 data: 0.0079 max mem: 33368 +Epoch: [0] [ 970/2639] eta: 1:21:06 lr: 4.9585873771645784e-05 loss: 0.2205 (0.2555) time: 2.9495 data: 0.0085 max mem: 33368 +Epoch: [0] [ 980/2639] eta: 1:20:37 lr: 4.95816068315519e-05 loss: 0.2231 (0.2554) time: 2.9501 data: 0.0086 max mem: 33368 +Epoch: [0] [ 990/2639] eta: 1:20:08 lr: 4.95773398506567e-05 loss: 0.2409 (0.2552) time: 2.9243 data: 0.0079 max mem: 33368 +Epoch: [0] [1000/2639] eta: 1:19:38 lr: 4.9573072828955893e-05 loss: 0.2268 (0.2548) time: 2.9095 data: 0.0075 max mem: 33368 +Epoch: [0] [1010/2639] eta: 1:19:10 lr: 4.9568805766445195e-05 loss: 0.2161 (0.2544) time: 2.9205 data: 0.0075 max mem: 33368 +Epoch: [0] [1020/2639] eta: 1:18:41 lr: 4.95645386631203e-05 loss: 0.2127 (0.2544) time: 2.9474 data: 0.0075 max mem: 33368 +Epoch: [0] [1030/2639] eta: 1:18:12 lr: 4.9560271518976925e-05 loss: 0.2022 (0.2539) time: 2.9249 data: 0.0074 max mem: 33368 +Epoch: [0] [1040/2639] eta: 1:17:43 lr: 4.9556004334010755e-05 loss: 0.2098 (0.2540) time: 2.9144 data: 0.0075 max mem: 33368 +Epoch: [0] [1050/2639] eta: 1:17:13 lr: 4.955173710821752e-05 loss: 0.2391 (0.2538) time: 2.8970 data: 0.0077 max mem: 33368 +Epoch: [0] [1060/2639] eta: 1:16:44 lr: 4.95474698415929e-05 loss: 0.2114 (0.2533) time: 2.9150 data: 0.0078 max mem: 33368 +Epoch: [0] [1070/2639] eta: 1:16:16 lr: 4.9543202534132616e-05 loss: 0.2015 (0.2530) time: 2.9644 data: 0.0080 max mem: 33368 +Epoch: [0] [1080/2639] eta: 1:15:47 lr: 4.953893518583235e-05 loss: 0.2064 (0.2527) time: 2.9523 data: 0.0078 max mem: 33368 +Epoch: [0] [1090/2639] eta: 1:15:17 lr: 4.9534667796687825e-05 loss: 0.2098 (0.2527) time: 2.8972 data: 0.0075 max mem: 33368 +Epoch: [0] [1100/2639] eta: 1:14:48 lr: 4.9530400366694714e-05 loss: 0.1998 (0.2524) time: 2.9048 data: 0.0073 max mem: 33368 +Epoch: [0] [1110/2639] eta: 1:14:18 lr: 4.952613289584874e-05 loss: 0.2227 (0.2522) time: 2.8928 data: 0.0073 max mem: 33368 +Epoch: [0] [1120/2639] eta: 1:13:49 lr: 4.952186538414557e-05 loss: 0.2227 (0.2522) time: 2.8762 data: 0.0076 max mem: 33368 +Epoch: [0] [1130/2639] eta: 1:13:21 lr: 4.951759783158094e-05 loss: 0.2093 (0.2523) time: 2.9622 data: 0.0075 max mem: 33368 +Epoch: [0] [1140/2639] eta: 1:12:51 lr: 4.951333023815051e-05 loss: 0.2212 (0.2521) time: 2.9469 data: 0.0079 max mem: 33368 +Epoch: [0] [1150/2639] eta: 1:12:22 lr: 4.9509062603850004e-05 loss: 0.2212 (0.2518) time: 2.8881 data: 0.0082 max mem: 33368 +Epoch: [0] [1160/2639] eta: 1:11:52 lr: 4.950479492867509e-05 loss: 0.2131 (0.2518) time: 2.8894 data: 0.0078 max mem: 33368 +Epoch: [0] [1170/2639] eta: 1:11:23 lr: 4.9500527212621484e-05 loss: 0.2186 (0.2516) time: 2.9038 data: 0.0072 max mem: 33368 +Epoch: [0] [1180/2639] eta: 1:10:54 lr: 4.9496259455684864e-05 loss: 0.2186 (0.2514) time: 2.9258 data: 0.0071 max mem: 33368 +Epoch: [0] [1190/2639] eta: 1:10:24 lr: 4.949199165786093e-05 loss: 0.2065 (0.2510) time: 2.8988 data: 0.0072 max mem: 33368 +Epoch: [0] [1200/2639] eta: 1:09:56 lr: 4.9487723819145357e-05 loss: 0.2131 (0.2510) time: 2.9143 data: 0.0072 max mem: 33368 +Epoch: [0] [1210/2639] eta: 1:09:27 lr: 4.9483455939533856e-05 loss: 0.2145 (0.2509) time: 2.9694 data: 0.0073 max mem: 33368 +Epoch: [0] [1220/2639] eta: 1:08:58 lr: 4.94791880190221e-05 loss: 0.2264 (0.2510) time: 2.9576 data: 0.0072 max mem: 33368 +Epoch: [0] [1230/2639] eta: 1:08:29 lr: 4.947492005760579e-05 loss: 0.2265 (0.2509) time: 2.8950 data: 0.0075 max mem: 33368 +Epoch: [0] [1240/2639] eta: 1:08:00 lr: 4.9470652055280605e-05 loss: 0.2213 (0.2510) time: 2.8910 data: 0.0076 max mem: 33368 +Epoch: [0] [1250/2639] eta: 1:07:31 lr: 4.946638401204223e-05 loss: 0.2377 (0.2511) time: 2.9285 data: 0.0078 max mem: 33368 +Epoch: [0] [1260/2639] eta: 1:07:01 lr: 4.946211592788635e-05 loss: 0.2322 (0.2508) time: 2.9056 data: 0.0078 max mem: 33368 +Epoch: [0] [1270/2639] eta: 1:06:31 lr: 4.945784780280866e-05 loss: 0.2304 (0.2506) time: 2.8758 data: 0.0073 max mem: 33368 +Epoch: [0] [1280/2639] eta: 1:06:02 lr: 4.945357963680484e-05 loss: 0.2273 (0.2505) time: 2.8647 data: 0.0078 max mem: 33368 +Epoch: [0] [1290/2639] eta: 1:05:33 lr: 4.9449311429870553e-05 loss: 0.2085 (0.2503) time: 2.9021 data: 0.0077 max mem: 33368 +Epoch: [0] [1300/2639] eta: 1:05:04 lr: 4.944504318200151e-05 loss: 0.2071 (0.2500) time: 2.9308 data: 0.0073 max mem: 33368 +Epoch: [0] [1310/2639] eta: 1:04:34 lr: 4.9440774893193375e-05 loss: 0.2136 (0.2499) time: 2.9006 data: 0.0072 max mem: 33368 +Epoch: [0] [1320/2639] eta: 1:04:05 lr: 4.9436506563441834e-05 loss: 0.2149 (0.2495) time: 2.8941 data: 0.0069 max mem: 33368 +Epoch: [0] [1330/2639] eta: 1:03:36 lr: 4.9432238192742565e-05 loss: 0.2152 (0.2496) time: 2.9025 data: 0.0071 max mem: 33368 +Epoch: [0] [1340/2639] eta: 1:03:07 lr: 4.9427969781091246e-05 loss: 0.2242 (0.2494) time: 2.9198 data: 0.0077 max mem: 33368 +Epoch: [0] [1350/2639] eta: 1:02:37 lr: 4.942370132848356e-05 loss: 0.2032 (0.2490) time: 2.9280 data: 0.0074 max mem: 33368 +Epoch: [0] [1360/2639] eta: 1:02:08 lr: 4.941943283491517e-05 loss: 0.1994 (0.2488) time: 2.9112 data: 0.0071 max mem: 33368 +Epoch: [0] [1370/2639] eta: 1:01:38 lr: 4.941516430038176e-05 loss: 0.2083 (0.2486) time: 2.8711 data: 0.0072 max mem: 33368 +Epoch: [0] [1380/2639] eta: 1:01:08 lr: 4.941089572487902e-05 loss: 0.2079 (0.2485) time: 2.8298 data: 0.0071 max mem: 33368 +Epoch: [0] [1390/2639] eta: 1:00:39 lr: 4.9406627108402595e-05 loss: 0.2187 (0.2484) time: 2.8669 data: 0.0075 max mem: 33368 +Epoch: [0] [1400/2639] eta: 1:00:10 lr: 4.9402358450948176e-05 loss: 0.2178 (0.2481) time: 2.8995 data: 0.0078 max mem: 33368 +Epoch: [0] [1410/2639] eta: 0:59:41 lr: 4.939808975251144e-05 loss: 0.2083 (0.2482) time: 2.9388 data: 0.0077 max mem: 33368 +Epoch: [0] [1420/2639] eta: 0:59:12 lr: 4.939382101308804e-05 loss: 0.2126 (0.2480) time: 2.9384 data: 0.0077 max mem: 33368 +Epoch: [0] [1430/2639] eta: 0:58:43 lr: 4.9389552232673656e-05 loss: 0.2112 (0.2479) time: 2.8883 data: 0.0078 max mem: 33368 +Epoch: [0] [1440/2639] eta: 0:58:14 lr: 4.938528341126397e-05 loss: 0.2112 (0.2477) time: 2.9088 data: 0.0078 max mem: 33368 +Epoch: [0] [1450/2639] eta: 0:57:44 lr: 4.9381014548854634e-05 loss: 0.2182 (0.2474) time: 2.8932 data: 0.0079 max mem: 33368 +Epoch: [0] [1460/2639] eta: 0:57:15 lr: 4.9376745645441316e-05 loss: 0.2069 (0.2471) time: 2.8699 data: 0.0078 max mem: 33368 +Epoch: [0] [1470/2639] eta: 0:56:45 lr: 4.93724767010197e-05 loss: 0.2027 (0.2471) time: 2.8947 data: 0.0074 max mem: 33368 +Epoch: [0] [1480/2639] eta: 0:56:16 lr: 4.936820771558544e-05 loss: 0.2068 (0.2470) time: 2.9121 data: 0.0077 max mem: 33368 +Epoch: [0] [1490/2639] eta: 0:55:47 lr: 4.93639386891342e-05 loss: 0.2068 (0.2468) time: 2.9206 data: 0.0078 max mem: 33368 +Epoch: [0] [1500/2639] eta: 0:55:18 lr: 4.9359669621661654e-05 loss: 0.1900 (0.2464) time: 2.9069 data: 0.0078 max mem: 33368 +Epoch: [0] [1510/2639] eta: 0:54:48 lr: 4.935540051316345e-05 loss: 0.1910 (0.2463) time: 2.8746 data: 0.0077 max mem: 33368 +Epoch: [0] [1520/2639] eta: 0:54:19 lr: 4.935113136363527e-05 loss: 0.2191 (0.2461) time: 2.8742 data: 0.0074 max mem: 33368 +Epoch: [0] [1530/2639] eta: 0:53:50 lr: 4.934686217307276e-05 loss: 0.2191 (0.2459) time: 2.9092 data: 0.0074 max mem: 33368 +Epoch: [0] [1540/2639] eta: 0:53:21 lr: 4.934259294147158e-05 loss: 0.2111 (0.2459) time: 2.8968 data: 0.0076 max mem: 33368 +Epoch: [0] [1550/2639] eta: 0:52:51 lr: 4.9338323668827404e-05 loss: 0.2111 (0.2458) time: 2.8768 data: 0.0077 max mem: 33368 +Epoch: [0] [1560/2639] eta: 0:52:22 lr: 4.933405435513589e-05 loss: 0.2045 (0.2455) time: 2.8782 data: 0.0078 max mem: 33368 +Epoch: [0] [1570/2639] eta: 0:51:52 lr: 4.932978500039269e-05 loss: 0.2045 (0.2454) time: 2.8456 data: 0.0076 max mem: 33368 +Epoch: [0] [1580/2639] eta: 0:51:23 lr: 4.932551560459345e-05 loss: 0.2180 (0.2452) time: 2.8576 data: 0.0073 max mem: 33368 +Epoch: [0] [1590/2639] eta: 0:50:53 lr: 4.9321246167733846e-05 loss: 0.2001 (0.2450) time: 2.8717 data: 0.0073 max mem: 33368 +Epoch: [0] [1600/2639] eta: 0:50:25 lr: 4.931697668980953e-05 loss: 0.2001 (0.2448) time: 2.9164 data: 0.0078 max mem: 33368 +Epoch: [0] [1610/2639] eta: 0:49:56 lr: 4.9312707170816146e-05 loss: 0.2070 (0.2447) time: 2.9565 data: 0.0077 max mem: 33368 +Epoch: [0] [1620/2639] eta: 0:49:26 lr: 4.930843761074936e-05 loss: 0.2081 (0.2444) time: 2.9090 data: 0.0076 max mem: 33368 +Epoch: [0] [1630/2639] eta: 0:48:57 lr: 4.9304168009604826e-05 loss: 0.2022 (0.2443) time: 2.8879 data: 0.0075 max mem: 33368 +Epoch: [0] [1640/2639] eta: 0:48:29 lr: 4.929989836737818e-05 loss: 0.1911 (0.2441) time: 2.9434 data: 0.0073 max mem: 33368 +Epoch: [0] [1650/2639] eta: 0:47:59 lr: 4.929562868406509e-05 loss: 0.1976 (0.2441) time: 2.9488 data: 0.0077 max mem: 33368 +Epoch: [0] [1660/2639] eta: 0:47:30 lr: 4.9291358959661196e-05 loss: 0.2280 (0.2441) time: 2.8692 data: 0.0079 max mem: 33368 +Epoch: [0] [1670/2639] eta: 0:47:01 lr: 4.928708919416216e-05 loss: 0.2278 (0.2439) time: 2.8565 data: 0.0077 max mem: 33368 +Epoch: [0] [1680/2639] eta: 0:46:31 lr: 4.928281938756362e-05 loss: 0.2044 (0.2437) time: 2.8714 data: 0.0074 max mem: 33368 +Epoch: [0] [1690/2639] eta: 0:46:02 lr: 4.9278549539861226e-05 loss: 0.2010 (0.2436) time: 2.8757 data: 0.0072 max mem: 33368 +Epoch: [0] [1700/2639] eta: 0:45:33 lr: 4.927427965105062e-05 loss: 0.2010 (0.2434) time: 2.8960 data: 0.0074 max mem: 33368 +Epoch: [0] [1710/2639] eta: 0:45:04 lr: 4.9270009721127455e-05 loss: 0.2058 (0.2433) time: 2.8930 data: 0.0073 max mem: 33368 +Epoch: [0] [1720/2639] eta: 0:44:34 lr: 4.926573975008739e-05 loss: 0.2058 (0.2431) time: 2.8796 data: 0.0075 max mem: 33368 +Epoch: [0] [1730/2639] eta: 0:44:05 lr: 4.9261469737926035e-05 loss: 0.1950 (0.2429) time: 2.8712 data: 0.0078 max mem: 33368 +Epoch: [0] [1740/2639] eta: 0:43:36 lr: 4.925719968463906e-05 loss: 0.1961 (0.2428) time: 2.8894 data: 0.0077 max mem: 33368 +Epoch: [0] [1750/2639] eta: 0:43:06 lr: 4.925292959022211e-05 loss: 0.2263 (0.2428) time: 2.8834 data: 0.0072 max mem: 33368 +Epoch: [0] [1760/2639] eta: 0:42:37 lr: 4.924865945467081e-05 loss: 0.2015 (0.2426) time: 2.8793 data: 0.0072 max mem: 33368 +Epoch: [0] [1770/2639] eta: 0:42:08 lr: 4.9244389277980806e-05 loss: 0.1891 (0.2425) time: 2.9063 data: 0.0083 max mem: 33368 +Epoch: [0] [1780/2639] eta: 0:41:39 lr: 4.9240119060147744e-05 loss: 0.1880 (0.2422) time: 2.9297 data: 0.0082 max mem: 33368 +Epoch: [0] [1790/2639] eta: 0:41:10 lr: 4.923584880116726e-05 loss: 0.1952 (0.2419) time: 2.9379 data: 0.0075 max mem: 33368 +Epoch: [0] [1800/2639] eta: 0:40:42 lr: 4.923157850103499e-05 loss: 0.1913 (0.2417) time: 2.9583 data: 0.0079 max mem: 33368 +Epoch: [0] [1810/2639] eta: 0:40:12 lr: 4.922730815974657e-05 loss: 0.1806 (0.2415) time: 2.9503 data: 0.0078 max mem: 33368 +Epoch: [0] [1820/2639] eta: 0:39:43 lr: 4.922303777729764e-05 loss: 0.1809 (0.2412) time: 2.8998 data: 0.0076 max mem: 33368 +Epoch: [0] [1830/2639] eta: 0:39:14 lr: 4.9218767353683825e-05 loss: 0.1911 (0.2411) time: 2.9123 data: 0.0078 max mem: 33368 +Epoch: [0] [1840/2639] eta: 0:38:45 lr: 4.921449688890078e-05 loss: 0.2118 (0.2409) time: 2.9205 data: 0.0080 max mem: 33368 +Epoch: [0] [1850/2639] eta: 0:38:16 lr: 4.921022638294413e-05 loss: 0.1988 (0.2408) time: 2.9092 data: 0.0078 max mem: 33368 +Epoch: [0] [1860/2639] eta: 0:37:47 lr: 4.9205955835809496e-05 loss: 0.2063 (0.2407) time: 2.8877 data: 0.0075 max mem: 33368 +Epoch: [0] [1870/2639] eta: 0:37:18 lr: 4.920168524749252e-05 loss: 0.2070 (0.2407) time: 2.8886 data: 0.0077 max mem: 33368 +Epoch: [0] [1880/2639] eta: 0:36:48 lr: 4.919741461798884e-05 loss: 0.2077 (0.2407) time: 2.8662 data: 0.0078 max mem: 33368 +Epoch: [0] [1890/2639] eta: 0:36:19 lr: 4.9193143947294075e-05 loss: 0.2108 (0.2406) time: 2.8485 data: 0.0077 max mem: 33368 +Epoch: [0] [1900/2639] eta: 0:35:50 lr: 4.9188873235403865e-05 loss: 0.2154 (0.2405) time: 2.8712 data: 0.0074 max mem: 33368 +Epoch: [0] [1910/2639] eta: 0:35:20 lr: 4.918460248231382e-05 loss: 0.2029 (0.2403) time: 2.8777 data: 0.0075 max mem: 33368 +Epoch: [0] [1920/2639] eta: 0:34:51 lr: 4.9180331688019586e-05 loss: 0.1957 (0.2400) time: 2.9144 data: 0.0081 max mem: 33368 +Epoch: [0] [1930/2639] eta: 0:34:22 lr: 4.917606085251678e-05 loss: 0.1971 (0.2399) time: 2.9101 data: 0.0079 max mem: 33368 +Epoch: [0] [1940/2639] eta: 0:33:53 lr: 4.917178997580103e-05 loss: 0.2076 (0.2400) time: 2.9253 data: 0.0073 max mem: 33368 +Epoch: [0] [1950/2639] eta: 0:33:24 lr: 4.916751905786797e-05 loss: 0.1916 (0.2397) time: 2.9247 data: 0.0074 max mem: 33368 +Epoch: [0] [1960/2639] eta: 0:32:55 lr: 4.916324809871321e-05 loss: 0.1901 (0.2396) time: 2.9085 data: 0.0080 max mem: 33368 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mem: 33368 +Epoch: [0] [2050/2639] eta: 0:28:34 lr: 4.912480761062162e-05 loss: 0.1977 (0.2387) time: 2.9586 data: 0.0079 max mem: 33368 +Epoch: [0] [2060/2639] eta: 0:28:05 lr: 4.912053623900903e-05 loss: 0.2182 (0.2385) time: 2.9392 data: 0.0074 max mem: 33368 +Epoch: [0] [2070/2639] eta: 0:27:36 lr: 4.9116264826126566e-05 loss: 0.1932 (0.2384) time: 2.9509 data: 0.0072 max mem: 33368 +Epoch: [0] [2080/2639] eta: 0:27:06 lr: 4.911199337196982e-05 loss: 0.1932 (0.2383) time: 2.9305 data: 0.0074 max mem: 33368 +Epoch: [0] [2090/2639] eta: 0:26:37 lr: 4.9107721876534415e-05 loss: 0.2148 (0.2384) time: 2.9014 data: 0.0075 max mem: 33368 +Epoch: [0] [2100/2639] eta: 0:26:08 lr: 4.910345033981595e-05 loss: 0.2113 (0.2383) time: 2.9380 data: 0.0074 max mem: 33368 +Epoch: [0] [2110/2639] eta: 0:25:39 lr: 4.909917876181004e-05 loss: 0.2007 (0.2382) time: 2.9423 data: 0.0074 max mem: 33368 +Epoch: [0] [2120/2639] eta: 0:25:10 lr: 4.9094907142512306e-05 loss: 0.1924 (0.2381) time: 2.8938 data: 0.0075 max mem: 33368 +Epoch: [0] [2130/2639] eta: 0:24:41 lr: 4.9090635481918355e-05 loss: 0.2006 (0.2380) time: 2.8774 data: 0.0076 max mem: 33368 +Epoch: [0] [2140/2639] eta: 0:24:12 lr: 4.908636378002378e-05 loss: 0.2039 (0.2379) time: 2.9297 data: 0.0077 max mem: 33368 +Epoch: [0] [2150/2639] eta: 0:23:43 lr: 4.908209203682421e-05 loss: 0.1856 (0.2376) time: 2.9570 data: 0.0075 max mem: 33368 +Epoch: [0] [2160/2639] eta: 0:23:14 lr: 4.907782025231522e-05 loss: 0.1797 (0.2374) time: 2.8815 data: 0.0076 max mem: 33368 +Epoch: [0] [2170/2639] eta: 0:22:44 lr: 4.907354842649245e-05 loss: 0.1873 (0.2374) time: 2.8619 data: 0.0076 max mem: 33368 +Epoch: [0] [2180/2639] eta: 0:22:15 lr: 4.906927655935148e-05 loss: 0.1957 (0.2372) time: 2.8825 data: 0.0076 max mem: 33368 +Epoch: [0] [2190/2639] eta: 0:21:46 lr: 4.906500465088792e-05 loss: 0.1945 (0.2371) time: 2.8698 data: 0.0077 max mem: 33368 +Epoch: [0] [2200/2639] eta: 0:21:17 lr: 4.906073270109739e-05 loss: 0.1945 (0.2369) time: 2.9265 data: 0.0075 max mem: 33368 +Epoch: [0] [2210/2639] eta: 0:20:48 lr: 4.905646070997546e-05 loss: 0.2063 (0.2368) time: 2.9639 data: 0.0074 max mem: 33368 +Epoch: [0] [2220/2639] eta: 0:20:19 lr: 4.905218867751776e-05 loss: 0.1877 (0.2366) time: 2.9470 data: 0.0075 max mem: 33368 +Epoch: [0] [2230/2639] eta: 0:19:50 lr: 4.9047916603719866e-05 loss: 0.1814 (0.2366) time: 2.9195 data: 0.0074 max mem: 33368 +Epoch: [0] [2240/2639] eta: 0:19:21 lr: 4.904364448857739e-05 loss: 0.1810 (0.2364) time: 2.9075 data: 0.0073 max mem: 33368 +Epoch: [0] [2250/2639] eta: 0:18:52 lr: 4.9039372332085935e-05 loss: 0.1842 (0.2362) time: 2.9194 data: 0.0074 max mem: 33368 +Epoch: [0] [2260/2639] eta: 0:18:23 lr: 4.903510013424109e-05 loss: 0.2224 (0.2362) time: 2.9131 data: 0.0074 max mem: 33368 +Epoch: [0] [2270/2639] eta: 0:17:54 lr: 4.903082789503846e-05 loss: 0.2153 (0.2359) time: 2.9187 data: 0.0076 max mem: 33368 +Epoch: [0] [2280/2639] eta: 0:17:25 lr: 4.902655561447363e-05 loss: 0.1901 (0.2359) time: 2.9485 data: 0.0077 max mem: 33368 +Epoch: [0] [2290/2639] eta: 0:16:55 lr: 4.902228329254219e-05 loss: 0.1965 (0.2358) time: 2.9125 data: 0.0074 max mem: 33368 +Epoch: [0] [2300/2639] eta: 0:16:26 lr: 4.901801092923974e-05 loss: 0.1923 (0.2356) time: 2.8971 data: 0.0075 max mem: 33368 +Epoch: [0] [2310/2639] eta: 0:15:57 lr: 4.901373852456188e-05 loss: 0.1821 (0.2355) time: 2.9185 data: 0.0075 max mem: 33368 +Epoch: [0] [2320/2639] eta: 0:15:28 lr: 4.90094660785042e-05 loss: 0.1821 (0.2354) time: 2.8805 data: 0.0077 max mem: 33368 +Epoch: [0] [2330/2639] eta: 0:14:59 lr: 4.9005193591062285e-05 loss: 0.1710 (0.2351) time: 2.8793 data: 0.0075 max mem: 33368 +Epoch: [0] [2340/2639] eta: 0:14:30 lr: 4.900092106223173e-05 loss: 0.1976 (0.2350) time: 2.8965 data: 0.0070 max mem: 33368 +Epoch: [0] [2350/2639] eta: 0:14:01 lr: 4.8996648492008116e-05 loss: 0.2114 (0.2349) time: 2.9130 data: 0.0078 max mem: 33368 +Epoch: [0] [2360/2639] eta: 0:13:32 lr: 4.8992375880387045e-05 loss: 0.2040 (0.2348) time: 2.9269 data: 0.0078 max mem: 33368 +Epoch: [0] [2370/2639] eta: 0:13:02 lr: 4.8988103227364095e-05 loss: 0.1980 (0.2346) time: 2.9162 data: 0.0072 max mem: 33368 +Epoch: [0] [2380/2639] eta: 0:12:33 lr: 4.8983830532934854e-05 loss: 0.2242 (0.2346) time: 2.8939 data: 0.0076 max mem: 33368 +Epoch: [0] [2390/2639] eta: 0:12:04 lr: 4.8979557797094904e-05 loss: 0.2139 (0.2345) time: 2.8827 data: 0.0076 max mem: 33368 +Epoch: [0] [2400/2639] eta: 0:11:35 lr: 4.897528501983984e-05 loss: 0.2058 (0.2344) time: 2.8991 data: 0.0075 max mem: 33368 +Epoch: [0] [2410/2639] eta: 0:11:06 lr: 4.897101220116523e-05 loss: 0.1729 (0.2341) time: 2.8950 data: 0.0076 max mem: 33368 +Epoch: [0] [2420/2639] eta: 0:10:37 lr: 4.896673934106668e-05 loss: 0.1729 (0.2342) time: 2.8816 data: 0.0075 max mem: 33368 +Epoch: [0] [2430/2639] eta: 0:10:08 lr: 4.896246643953975e-05 loss: 0.1889 (0.2340) time: 2.8843 data: 0.0080 max mem: 33368 +Epoch: [0] [2440/2639] eta: 0:09:39 lr: 4.895819349658003e-05 loss: 0.1729 (0.2339) time: 2.8640 data: 0.0084 max mem: 33368 +Epoch: [0] [2450/2639] eta: 0:09:09 lr: 4.89539205121831e-05 loss: 0.1926 (0.2338) time: 2.8893 data: 0.0088 max mem: 33368 +Epoch: [0] [2460/2639] eta: 0:08:40 lr: 4.894964748634454e-05 loss: 0.2063 (0.2337) time: 2.9131 data: 0.0087 max mem: 33368 +Epoch: [0] [2470/2639] eta: 0:08:11 lr: 4.8945374419059924e-05 loss: 0.2063 (0.2336) time: 2.8708 data: 0.0080 max mem: 33368 +Epoch: [0] [2480/2639] eta: 0:07:42 lr: 4.894110131032483e-05 loss: 0.1723 (0.2333) time: 2.8525 data: 0.0081 max mem: 33368 +Epoch: [0] [2490/2639] eta: 0:07:13 lr: 4.893682816013485e-05 loss: 0.1843 (0.2333) time: 2.8813 data: 0.0082 max mem: 33368 +Epoch: [0] [2500/2639] eta: 0:06:44 lr: 4.893255496848554e-05 loss: 0.1955 (0.2334) time: 2.9040 data: 0.0084 max mem: 33368 +Epoch: [0] [2510/2639] eta: 0:06:15 lr: 4.892828173537248e-05 loss: 0.1828 (0.2331) time: 2.9016 data: 0.0087 max mem: 33368 +Epoch: [0] [2520/2639] eta: 0:05:46 lr: 4.8924008460791246e-05 loss: 0.1828 (0.2332) time: 2.8866 data: 0.0085 max mem: 33368 +Epoch: [0] [2530/2639] eta: 0:05:17 lr: 4.891973514473742e-05 loss: 0.1969 (0.2331) time: 2.8614 data: 0.0082 max mem: 33368 +Epoch: [0] [2540/2639] eta: 0:04:47 lr: 4.891546178720656e-05 loss: 0.1890 (0.2330) time: 2.8659 data: 0.0080 max mem: 33368 +Epoch: [0] [2550/2639] eta: 0:04:18 lr: 4.891118838819424e-05 loss: 0.1973 (0.2329) time: 2.8476 data: 0.0077 max mem: 33368 +Epoch: [0] [2560/2639] eta: 0:03:49 lr: 4.890691494769603e-05 loss: 0.1918 (0.2327) time: 2.8587 data: 0.0078 max mem: 33368 +Epoch: [0] [2570/2639] eta: 0:03:20 lr: 4.890264146570751e-05 loss: 0.1754 (0.2326) time: 2.8883 data: 0.0078 max mem: 33368 +Epoch: [0] [2580/2639] eta: 0:02:51 lr: 4.8898367942224233e-05 loss: 0.1779 (0.2325) time: 2.9037 data: 0.0076 max mem: 33368 +Epoch: [0] [2590/2639] eta: 0:02:22 lr: 4.889409437724178e-05 loss: 0.2003 (0.2324) time: 2.8900 data: 0.0076 max mem: 33368 +Epoch: [0] [2600/2639] eta: 0:01:53 lr: 4.8889820770755715e-05 loss: 0.2004 (0.2322) time: 2.8882 data: 0.0079 max mem: 33368 +Epoch: [0] [2610/2639] eta: 0:01:24 lr: 4.8885547122761596e-05 loss: 0.1896 (0.2321) time: 2.9108 data: 0.0081 max mem: 33368 +Epoch: [0] [2620/2639] eta: 0:00:55 lr: 4.888127343325499e-05 loss: 0.2070 (0.2320) time: 2.8524 data: 0.0081 max mem: 33368 +Epoch: [0] [2630/2639] eta: 0:00:26 lr: 4.887699970223147e-05 loss: 0.2138 (0.2320) time: 2.8519 data: 0.0076 max mem: 33368 +Epoch: [0] Total time: 2:07:53 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 2:17:46 time: 3.2129 data: 3.1179 max mem: 33368 +Test: [ 100/2573] eta: 0:04:29 time: 0.0780 data: 0.0014 max mem: 33368 +Test: [ 200/2573] eta: 0:03:44 time: 0.0802 data: 0.0015 max mem: 33368 +Test: [ 300/2573] eta: 0:03:22 time: 0.0810 data: 0.0015 max mem: 33368 +Test: [ 400/2573] eta: 0:03:08 time: 0.0808 data: 0.0014 max mem: 33368 +Test: [ 500/2573] eta: 0:02:56 time: 0.0802 data: 0.0014 max mem: 33368 +Test: [ 600/2573] eta: 0:02:46 time: 0.0791 data: 0.0013 max mem: 33368 +Test: [ 700/2573] eta: 0:02:37 time: 0.0812 data: 0.0015 max mem: 33368 +Test: [ 800/2573] eta: 0:02:28 time: 0.0839 data: 0.0015 max mem: 33368 +Test: [ 900/2573] eta: 0:02:19 time: 0.0805 data: 0.0014 max mem: 33368 +Test: [1000/2573] eta: 0:02:10 time: 0.0799 data: 0.0015 max mem: 33368 +Test: [1100/2573] eta: 0:02:02 time: 0.0803 data: 0.0013 max mem: 33368 +Test: [1200/2573] eta: 0:01:53 time: 0.0800 data: 0.0015 max mem: 33368 +Test: [1300/2573] eta: 0:01:45 time: 0.0793 data: 0.0014 max mem: 33368 +Test: [1400/2573] eta: 0:01:36 time: 0.0787 data: 0.0015 max mem: 33368 +Test: [1500/2573] eta: 0:01:28 time: 0.0818 data: 0.0015 max mem: 33368 +Test: [1600/2573] eta: 0:01:19 time: 0.0825 data: 0.0015 max mem: 33368 +Test: [1700/2573] eta: 0:01:11 time: 0.0786 data: 0.0014 max mem: 33368 +Test: [1800/2573] eta: 0:01:03 time: 0.0811 data: 0.0015 max mem: 33368 +Test: [1900/2573] eta: 0:00:55 time: 0.0789 data: 0.0015 max mem: 33368 +Test: [2000/2573] eta: 0:00:46 time: 0.0805 data: 0.0014 max mem: 33368 +Test: [2100/2573] eta: 0:00:38 time: 0.0819 data: 0.0014 max mem: 33368 +Test: [2200/2573] eta: 0:00:30 time: 0.0820 data: 0.0014 max mem: 33368 +Test: [2300/2573] eta: 0:00:22 time: 0.0815 data: 0.0014 max mem: 33368 +Test: [2400/2573] eta: 0:00:14 time: 0.0762 data: 0.0014 max mem: 33368 +Test: [2500/2573] eta: 0:00:05 time: 0.0807 data: 0.0014 max mem: 33368 +Test: Total time: 0:03:30 +Final results: +Mean IoU is 25.56 + + precision@0.5 = 24.18 + precision@0.6 = 17.91 + precision@0.7 = 11.64 + precision@0.8 = 5.31 + precision@0.9 = 0.96 + overall IoU = 31.28 + +Average object IoU 25.55985288139443 +Overall IoU 31.28200912475586 +Better epoch: 0 + +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [1] [ 0/2639] eta: 4:01:12 lr: 4.887315330880966e-05 loss: 0.1739 (0.1739) time: 5.4840 data: 2.5509 max mem: 33368 +Epoch: [1] [ 10/2639] eta: 2:15:04 lr: 4.8868879498891765e-05 loss: 0.1626 (0.1676) time: 3.0828 data: 0.2386 max mem: 33368 +Epoch: [1] [ 20/2639] eta: 2:10:19 lr: 4.886460564744408e-05 loss: 0.1633 (0.1712) time: 2.8609 data: 0.0074 max mem: 33368 +Epoch: [1] [ 30/2639] eta: 2:08:05 lr: 4.8860331754462155e-05 loss: 0.1644 (0.1694) time: 2.8704 data: 0.0080 max mem: 33368 +Epoch: [1] [ 40/2639] eta: 2:07:11 lr: 4.885605781994157e-05 loss: 0.1699 (0.1728) time: 2.8840 data: 0.0082 max mem: 33368 +Epoch: [1] [ 50/2639] eta: 2:06:39 lr: 4.885178384387788e-05 loss: 0.1699 (0.1735) time: 2.9194 data: 0.0081 max mem: 33368 +Epoch: [1] [ 60/2639] eta: 2:05:44 lr: 4.884750982626663e-05 loss: 0.1709 (0.1751) time: 2.9033 data: 0.0082 max mem: 33368 +Epoch: [1] [ 70/2639] eta: 2:04:53 lr: 4.884323576710337e-05 loss: 0.1769 (0.1781) time: 2.8704 data: 0.0084 max mem: 33368 +Epoch: [1] [ 80/2639] eta: 2:03:54 lr: 4.883896166638368e-05 loss: 0.1769 (0.1791) time: 2.8442 data: 0.0085 max mem: 33368 +Epoch: [1] [ 90/2639] eta: 2:03:26 lr: 4.8834687524103106e-05 loss: 0.1804 (0.1802) time: 2.8645 data: 0.0082 max mem: 33368 +Epoch: [1] [ 100/2639] eta: 2:02:40 lr: 4.8830413340257195e-05 loss: 0.1868 (0.1820) time: 2.8725 data: 0.0084 max mem: 33368 +Epoch: [1] [ 110/2639] eta: 2:02:09 lr: 4.882613911484151e-05 loss: 0.2073 (0.1856) time: 2.8657 data: 0.0085 max mem: 33368 +Epoch: [1] [ 120/2639] eta: 2:01:47 lr: 4.88218648478516e-05 loss: 0.2024 (0.1865) time: 2.9108 data: 0.0081 max mem: 33368 +Epoch: [1] [ 130/2639] eta: 2:01:07 lr: 4.881759053928301e-05 loss: 0.1633 (0.1848) time: 2.8865 data: 0.0079 max mem: 33368 +Epoch: [1] [ 140/2639] eta: 2:00:39 lr: 4.8813316189131296e-05 loss: 0.1682 (0.1858) time: 2.8742 data: 0.0078 max mem: 33368 +Epoch: [1] [ 150/2639] eta: 2:00:09 lr: 4.880904179739201e-05 loss: 0.1666 (0.1839) time: 2.8952 data: 0.0079 max mem: 33368 +Epoch: [1] [ 160/2639] eta: 1:59:42 lr: 4.88047673640607e-05 loss: 0.1651 (0.1852) time: 2.8983 data: 0.0080 max mem: 33368 +Epoch: [1] [ 170/2639] eta: 1:59:17 lr: 4.880049288913291e-05 loss: 0.1808 (0.1854) time: 2.9173 data: 0.0079 max mem: 33368 +Epoch: [1] [ 180/2639] eta: 1:58:48 lr: 4.8796218372604184e-05 loss: 0.1897 (0.1864) time: 2.9123 data: 0.0082 max mem: 33368 +Epoch: [1] [ 190/2639] eta: 1:58:17 lr: 4.8791943814470074e-05 loss: 0.1831 (0.1862) time: 2.8925 data: 0.0079 max mem: 33368 +Epoch: [1] [ 200/2639] eta: 1:57:50 lr: 4.878766921472612e-05 loss: 0.1664 (0.1851) time: 2.8986 data: 0.0080 max mem: 33368 +Epoch: [1] [ 210/2639] eta: 1:57:22 lr: 4.878339457336788e-05 loss: 0.1515 (0.1838) time: 2.9095 data: 0.0080 max mem: 33368 +Epoch: [1] [ 220/2639] eta: 1:56:47 lr: 4.877911989039088e-05 loss: 0.1702 (0.1841) time: 2.8759 data: 0.0081 max mem: 33368 +Epoch: [1] [ 230/2639] eta: 1:56:18 lr: 4.877484516579067e-05 loss: 0.1770 (0.1843) time: 2.8725 data: 0.0082 max mem: 33368 +Epoch: [1] [ 240/2639] eta: 1:55:48 lr: 4.877057039956279e-05 loss: 0.1778 (0.1847) time: 2.8916 data: 0.0079 max mem: 33368 +Epoch: [1] [ 250/2639] eta: 1:55:23 lr: 4.8766295591702774e-05 loss: 0.1649 (0.1842) time: 2.9141 data: 0.0078 max mem: 33368 +Epoch: [1] [ 260/2639] eta: 1:54:58 lr: 4.876202074220617e-05 loss: 0.1659 (0.1851) time: 2.9391 data: 0.0080 max mem: 33368 +Epoch: [1] [ 270/2639] eta: 1:54:23 lr: 4.875774585106852e-05 loss: 0.1924 (0.1856) time: 2.8830 data: 0.0081 max mem: 33368 +Epoch: [1] [ 280/2639] eta: 1:53:54 lr: 4.875347091828536e-05 loss: 0.2129 (0.1872) time: 2.8688 data: 0.0077 max mem: 33368 +Epoch: [1] [ 290/2639] eta: 1:53:28 lr: 4.874919594385222e-05 loss: 0.1780 (0.1874) time: 2.9149 data: 0.0076 max mem: 33368 +Epoch: [1] [ 300/2639] eta: 1:52:59 lr: 4.874492092776463e-05 loss: 0.1663 (0.1872) time: 2.9130 data: 0.0075 max mem: 33368 +Epoch: [1] [ 310/2639] eta: 1:52:27 lr: 4.8740645870018144e-05 loss: 0.1661 (0.1872) time: 2.8816 data: 0.0077 max mem: 33368 +Epoch: [1] [ 320/2639] eta: 1:51:56 lr: 4.873637077060828e-05 loss: 0.1661 (0.1870) time: 2.8613 data: 0.0080 max mem: 33368 +Epoch: [1] [ 330/2639] eta: 1:51:22 lr: 4.873209562953058e-05 loss: 0.1654 (0.1863) time: 2.8438 data: 0.0081 max mem: 33368 +Epoch: [1] [ 340/2639] eta: 1:50:51 lr: 4.872782044678058e-05 loss: 0.1858 (0.1883) time: 2.8495 data: 0.0079 max mem: 33368 +Epoch: [1] [ 350/2639] eta: 1:50:23 lr: 4.872354522235379e-05 loss: 0.1903 (0.1878) time: 2.8901 data: 0.0079 max mem: 33368 +Epoch: [1] [ 360/2639] eta: 1:49:52 lr: 4.8719269956245765e-05 loss: 0.1609 (0.1881) time: 2.8811 data: 0.0077 max mem: 33368 +Epoch: [1] [ 370/2639] eta: 1:49:27 lr: 4.871499464845202e-05 loss: 0.1609 (0.1877) time: 2.9015 data: 0.0073 max mem: 33368 +Epoch: [1] [ 380/2639] eta: 1:48:59 lr: 4.87107192989681e-05 loss: 0.1848 (0.1880) time: 2.9322 data: 0.0073 max mem: 33368 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mem: 33368 +Epoch: [1] [ 470/2639] eta: 1:44:38 lr: 4.86722392768161e-05 loss: 0.1648 (0.1901) time: 2.8520 data: 0.0077 max mem: 33368 +Epoch: [1] [ 480/2639] eta: 1:44:08 lr: 4.866796351018418e-05 loss: 0.1648 (0.1901) time: 2.8640 data: 0.0076 max mem: 33368 +Epoch: [1] [ 490/2639] eta: 1:43:40 lr: 4.866368770181282e-05 loss: 0.1993 (0.1913) time: 2.8959 data: 0.0077 max mem: 33368 +Epoch: [1] [ 500/2639] eta: 1:43:13 lr: 4.865941185169755e-05 loss: 0.1907 (0.1915) time: 2.9299 data: 0.0076 max mem: 33368 +Epoch: [1] [ 510/2639] eta: 1:42:43 lr: 4.865513595983387e-05 loss: 0.1734 (0.1913) time: 2.9054 data: 0.0074 max mem: 33368 +Epoch: [1] [ 520/2639] eta: 1:42:15 lr: 4.865086002621732e-05 loss: 0.1749 (0.1911) time: 2.9006 data: 0.0075 max mem: 33368 +Epoch: [1] [ 530/2639] eta: 1:41:47 lr: 4.8646584050843396e-05 loss: 0.1592 (0.1912) time: 2.9134 data: 0.0080 max mem: 33368 +Epoch: [1] [ 540/2639] eta: 1:41:19 lr: 4.8642308033707624e-05 loss: 0.1755 (0.1912) time: 2.9165 data: 0.0077 max mem: 33368 +Epoch: [1] [ 550/2639] eta: 1:40:52 lr: 4.86380319748055e-05 loss: 0.1965 (0.1914) time: 2.9415 data: 0.0074 max mem: 33368 +Epoch: [1] [ 560/2639] eta: 1:40:25 lr: 4.863375587413255e-05 loss: 0.1999 (0.1913) time: 2.9506 data: 0.0076 max mem: 33368 +Epoch: [1] [ 570/2639] eta: 1:40:00 lr: 4.862947973168429e-05 loss: 0.1794 (0.1907) time: 2.9704 data: 0.0074 max mem: 33368 +Epoch: [1] [ 580/2639] eta: 1:39:28 lr: 4.86252035474562e-05 loss: 0.1794 (0.1909) time: 2.9148 data: 0.0075 max mem: 33368 +Epoch: [1] [ 590/2639] eta: 1:38:59 lr: 4.8620927321443834e-05 loss: 0.2016 (0.1913) time: 2.8580 data: 0.0078 max mem: 33368 +Epoch: [1] [ 600/2639] eta: 1:38:30 lr: 4.861665105364267e-05 loss: 0.1920 (0.1913) time: 2.8941 data: 0.0081 max mem: 33368 +Epoch: [1] [ 610/2639] eta: 1:38:00 lr: 4.8612374744048226e-05 loss: 0.2026 (0.1921) time: 2.8881 data: 0.0080 max mem: 33368 +Epoch: [1] [ 620/2639] eta: 1:37:31 lr: 4.8608098392656e-05 loss: 0.2081 (0.1921) time: 2.8850 data: 0.0078 max mem: 33368 +Epoch: [1] [ 630/2639] eta: 1:37:02 lr: 4.8603821999461515e-05 loss: 0.1717 (0.1920) time: 2.8881 data: 0.0077 max mem: 33368 +Epoch: [1] [ 640/2639] eta: 1:36:34 lr: 4.8599545564460246e-05 loss: 0.1654 (0.1916) time: 2.9152 data: 0.0077 max mem: 33368 +Epoch: [1] [ 650/2639] eta: 1:36:03 lr: 4.8595269087647724e-05 loss: 0.1683 (0.1915) time: 2.8838 data: 0.0079 max mem: 33368 +Epoch: [1] [ 660/2639] eta: 1:35:34 lr: 4.859099256901944e-05 loss: 0.1689 (0.1914) time: 2.8525 data: 0.0079 max mem: 33368 +Epoch: [1] [ 670/2639] eta: 1:35:07 lr: 4.858671600857091e-05 loss: 0.1880 (0.1916) time: 2.9321 data: 0.0079 max mem: 33368 +Epoch: [1] [ 680/2639] eta: 1:34:39 lr: 4.8582439406297606e-05 loss: 0.1867 (0.1916) time: 2.9549 data: 0.0077 max mem: 33368 +Epoch: [1] [ 690/2639] eta: 1:34:10 lr: 4.857816276219506e-05 loss: 0.1648 (0.1913) time: 2.9254 data: 0.0078 max mem: 33368 +Epoch: [1] [ 700/2639] eta: 1:33:41 lr: 4.857388607625875e-05 loss: 0.1707 (0.1916) time: 2.8933 data: 0.0077 max mem: 33368 +Epoch: [1] [ 710/2639] eta: 1:33:12 lr: 4.856960934848418e-05 loss: 0.1749 (0.1916) time: 2.8877 data: 0.0075 max mem: 33368 +Epoch: [1] [ 720/2639] eta: 1:32:43 lr: 4.8565332578866844e-05 loss: 0.1743 (0.1915) time: 2.9083 data: 0.0077 max mem: 33368 +Epoch: [1] [ 730/2639] eta: 1:32:14 lr: 4.856105576740225e-05 loss: 0.1910 (0.1918) time: 2.9025 data: 0.0075 max mem: 33368 +Epoch: [1] [ 740/2639] eta: 1:31:45 lr: 4.855677891408588e-05 loss: 0.1910 (0.1920) time: 2.8976 data: 0.0071 max mem: 33368 +Epoch: [1] [ 750/2639] eta: 1:31:15 lr: 4.855250201891324e-05 loss: 0.1781 (0.1922) time: 2.8815 data: 0.0077 max mem: 33368 +Epoch: [1] [ 760/2639] eta: 1:30:44 lr: 4.8548225081879814e-05 loss: 0.1781 (0.1921) time: 2.8359 data: 0.0081 max mem: 33368 +Epoch: [1] [ 770/2639] eta: 1:30:15 lr: 4.8543948102981106e-05 loss: 0.1772 (0.1921) time: 2.8658 data: 0.0080 max mem: 33368 +Epoch: [1] [ 780/2639] eta: 1:29:47 lr: 4.853967108221259e-05 loss: 0.1773 (0.1923) time: 2.9155 data: 0.0081 max mem: 33368 +Epoch: [1] [ 790/2639] eta: 1:29:19 lr: 4.8535394019569774e-05 loss: 0.1725 (0.1920) time: 2.9358 data: 0.0077 max mem: 33368 +Epoch: [1] [ 800/2639] eta: 1:28:51 lr: 4.853111691504814e-05 loss: 0.1593 (0.1916) time: 2.9352 data: 0.0077 max mem: 33368 +Epoch: [1] [ 810/2639] eta: 1:28:21 lr: 4.8526839768643176e-05 loss: 0.1593 (0.1914) time: 2.8921 data: 0.0079 max mem: 33368 +Epoch: [1] [ 820/2639] eta: 1:27:53 lr: 4.852256258035037e-05 loss: 0.1658 (0.1914) time: 2.9132 data: 0.0074 max mem: 33368 +Epoch: [1] [ 830/2639] eta: 1:27:24 lr: 4.851828535016521e-05 loss: 0.1698 (0.1913) time: 2.9127 data: 0.0077 max mem: 33368 +Epoch: [1] [ 840/2639] eta: 1:26:54 lr: 4.851400807808318e-05 loss: 0.1722 (0.1911) time: 2.8684 data: 0.0079 max mem: 33368 +Epoch: [1] [ 850/2639] eta: 1:26:26 lr: 4.850973076409978e-05 loss: 0.1718 (0.1908) time: 2.9096 data: 0.0079 max mem: 33368 +Epoch: [1] [ 860/2639] eta: 1:25:56 lr: 4.8505453408210476e-05 loss: 0.1773 (0.1910) time: 2.9068 data: 0.0082 max mem: 33368 +Epoch: [1] [ 870/2639] eta: 1:25:28 lr: 4.850117601041076e-05 loss: 0.1911 (0.1910) time: 2.8922 data: 0.0079 max mem: 33368 +Epoch: [1] [ 880/2639] eta: 1:24:58 lr: 4.8496898570696106e-05 loss: 0.1911 (0.1909) time: 2.8890 data: 0.0081 max mem: 33368 +Epoch: [1] [ 890/2639] eta: 1:24:30 lr: 4.8492621089062006e-05 loss: 0.1716 (0.1906) time: 2.9066 data: 0.0077 max mem: 33368 +Epoch: [1] [ 900/2639] eta: 1:24:00 lr: 4.848834356550394e-05 loss: 0.1792 (0.1910) time: 2.9011 data: 0.0071 max mem: 33368 +Epoch: [1] [ 910/2639] eta: 1:23:32 lr: 4.848406600001738e-05 loss: 0.1706 (0.1908) time: 2.8947 data: 0.0075 max mem: 33368 +Epoch: [1] [ 920/2639] eta: 1:23:04 lr: 4.8479788392597816e-05 loss: 0.1691 (0.1908) time: 2.9580 data: 0.0078 max mem: 33368 +Epoch: [1] [ 930/2639] eta: 1:22:36 lr: 4.847551074324071e-05 loss: 0.1777 (0.1906) time: 2.9428 data: 0.0078 max mem: 33368 +Epoch: [1] [ 940/2639] eta: 1:22:05 lr: 4.847123305194156e-05 loss: 0.1844 (0.1909) time: 2.8720 data: 0.0077 max mem: 33368 +Epoch: [1] [ 950/2639] eta: 1:21:37 lr: 4.846695531869581e-05 loss: 0.1867 (0.1906) time: 2.8863 data: 0.0077 max mem: 33368 +Epoch: [1] [ 960/2639] eta: 1:21:07 lr: 4.846267754349897e-05 loss: 0.1873 (0.1907) time: 2.8954 data: 0.0078 max mem: 33368 +Epoch: [1] [ 970/2639] eta: 1:20:38 lr: 4.8458399726346494e-05 loss: 0.1902 (0.1908) time: 2.8723 data: 0.0074 max mem: 33368 +Epoch: [1] [ 980/2639] eta: 1:20:09 lr: 4.845412186723386e-05 loss: 0.1902 (0.1910) time: 2.8905 data: 0.0074 max mem: 33368 +Epoch: [1] [ 990/2639] eta: 1:19:40 lr: 4.844984396615654e-05 loss: 0.1804 (0.1909) time: 2.8939 data: 0.0077 max mem: 33368 +Epoch: [1] [1000/2639] eta: 1:19:11 lr: 4.844556602311e-05 loss: 0.1785 (0.1908) time: 2.8926 data: 0.0077 max mem: 33368 +Epoch: [1] [1010/2639] eta: 1:18:43 lr: 4.8441288038089724e-05 loss: 0.1785 (0.1908) time: 2.9196 data: 0.0077 max mem: 33368 +Epoch: [1] [1020/2639] eta: 1:18:14 lr: 4.843701001109117e-05 loss: 0.1780 (0.1907) time: 2.9379 data: 0.0076 max mem: 33368 +Epoch: [1] [1030/2639] eta: 1:17:45 lr: 4.8432731942109806e-05 loss: 0.1772 (0.1905) time: 2.9161 data: 0.0076 max mem: 33368 +Epoch: [1] [1040/2639] eta: 1:17:16 lr: 4.84284538311411e-05 loss: 0.1772 (0.1905) time: 2.9043 data: 0.0077 max mem: 33368 +Epoch: [1] [1050/2639] eta: 1:16:47 lr: 4.842417567818053e-05 loss: 0.1697 (0.1903) time: 2.8843 data: 0.0076 max mem: 33368 +Epoch: [1] [1060/2639] eta: 1:16:18 lr: 4.8419897483223554e-05 loss: 0.1643 (0.1902) time: 2.8940 data: 0.0074 max mem: 33368 +Epoch: [1] [1070/2639] eta: 1:15:49 lr: 4.8415619246265624e-05 loss: 0.1713 (0.1902) time: 2.9122 data: 0.0074 max mem: 33368 +Epoch: [1] [1080/2639] eta: 1:15:20 lr: 4.841134096730222e-05 loss: 0.1783 (0.1903) time: 2.8852 data: 0.0077 max mem: 33368 +Epoch: [1] [1090/2639] eta: 1:14:50 lr: 4.840706264632881e-05 loss: 0.1949 (0.1904) time: 2.8623 data: 0.0075 max mem: 33368 +Epoch: [1] [1100/2639] eta: 1:14:21 lr: 4.8402784283340835e-05 loss: 0.1765 (0.1903) time: 2.8800 data: 0.0075 max mem: 33368 +Epoch: [1] [1110/2639] eta: 1:13:53 lr: 4.839850587833378e-05 loss: 0.1636 (0.1902) time: 2.9122 data: 0.0076 max mem: 33368 +Epoch: [1] [1120/2639] eta: 1:13:24 lr: 4.839422743130308e-05 loss: 0.1802 (0.1901) time: 2.9172 data: 0.0077 max mem: 33368 +Epoch: [1] [1130/2639] eta: 1:12:56 lr: 4.8389948942244215e-05 loss: 0.1813 (0.1900) time: 2.9415 data: 0.0076 max mem: 33368 +Epoch: [1] [1140/2639] eta: 1:12:27 lr: 4.838567041115263e-05 loss: 0.1845 (0.1904) time: 2.9384 data: 0.0074 max mem: 33368 +Epoch: [1] [1150/2639] eta: 1:11:58 lr: 4.838139183802379e-05 loss: 0.1805 (0.1902) time: 2.9071 data: 0.0075 max mem: 33368 +Epoch: [1] [1160/2639] eta: 1:11:29 lr: 4.8377113222853146e-05 loss: 0.1735 (0.1901) time: 2.9029 data: 0.0074 max mem: 33368 +Epoch: [1] [1170/2639] eta: 1:11:00 lr: 4.837283456563615e-05 loss: 0.1591 (0.1899) time: 2.9216 data: 0.0074 max mem: 33368 +Epoch: [1] [1180/2639] eta: 1:10:31 lr: 4.836855586636827e-05 loss: 0.1591 (0.1898) time: 2.9284 data: 0.0072 max mem: 33368 +Epoch: [1] [1190/2639] eta: 1:10:02 lr: 4.836427712504496e-05 loss: 0.1777 (0.1896) time: 2.8871 data: 0.0073 max mem: 33368 +Epoch: [1] [1200/2639] eta: 1:09:33 lr: 4.835999834166164e-05 loss: 0.1609 (0.1895) time: 2.8727 data: 0.0077 max mem: 33368 +Epoch: [1] [1210/2639] eta: 1:09:04 lr: 4.835571951621381e-05 loss: 0.1653 (0.1895) time: 2.8979 data: 0.0073 max mem: 33368 +Epoch: [1] [1220/2639] eta: 1:08:34 lr: 4.8351440648696885e-05 loss: 0.1671 (0.1892) time: 2.8726 data: 0.0073 max mem: 33368 +Epoch: [1] [1230/2639] eta: 1:08:05 lr: 4.834716173910633e-05 loss: 0.1561 (0.1890) time: 2.8651 data: 0.0077 max mem: 33368 +Epoch: [1] [1240/2639] eta: 1:07:36 lr: 4.8342882787437584e-05 loss: 0.1561 (0.1889) time: 2.8932 data: 0.0077 max mem: 33368 +Epoch: [1] [1250/2639] eta: 1:07:07 lr: 4.833860379368611e-05 loss: 0.1650 (0.1890) time: 2.8778 data: 0.0077 max mem: 33368 +Epoch: [1] [1260/2639] eta: 1:06:38 lr: 4.833432475784733e-05 loss: 0.1669 (0.1890) time: 2.9087 data: 0.0076 max mem: 33368 +Epoch: [1] [1270/2639] eta: 1:06:09 lr: 4.8330045679916724e-05 loss: 0.1523 (0.1887) time: 2.9152 data: 0.0074 max mem: 33368 +Epoch: [1] [1280/2639] eta: 1:05:40 lr: 4.8325766559889704e-05 loss: 0.1573 (0.1886) time: 2.8697 data: 0.0073 max mem: 33368 +Epoch: [1] [1290/2639] eta: 1:05:10 lr: 4.832148739776174e-05 loss: 0.1648 (0.1886) time: 2.8603 data: 0.0074 max mem: 33368 +Epoch: [1] [1300/2639] eta: 1:04:42 lr: 4.831720819352826e-05 loss: 0.1670 (0.1886) time: 2.9038 data: 0.0076 max mem: 33368 +Epoch: [1] [1310/2639] eta: 1:04:12 lr: 4.831292894718471e-05 loss: 0.1737 (0.1887) time: 2.8976 data: 0.0075 max mem: 33368 +Epoch: [1] [1320/2639] eta: 1:03:43 lr: 4.8308649658726526e-05 loss: 0.1846 (0.1888) time: 2.8625 data: 0.0073 max mem: 33368 +Epoch: [1] [1330/2639] eta: 1:03:13 lr: 4.830437032814916e-05 loss: 0.1846 (0.1887) time: 2.8549 data: 0.0073 max mem: 33368 +Epoch: [1] [1340/2639] eta: 1:02:44 lr: 4.830009095544805e-05 loss: 0.1705 (0.1886) time: 2.8349 data: 0.0073 max mem: 33368 +Epoch: [1] [1350/2639] eta: 1:02:14 lr: 4.829581154061861e-05 loss: 0.1683 (0.1885) time: 2.8453 data: 0.0073 max mem: 33368 +Epoch: [1] [1360/2639] eta: 1:01:45 lr: 4.829153208365632e-05 loss: 0.1727 (0.1885) time: 2.8717 data: 0.0073 max mem: 33368 +Epoch: [1] [1370/2639] eta: 1:01:16 lr: 4.828725258455658e-05 loss: 0.1834 (0.1884) time: 2.8695 data: 0.0074 max mem: 33368 +Epoch: [1] [1380/2639] eta: 1:00:47 lr: 4.8282973043314844e-05 loss: 0.1728 (0.1885) time: 2.8634 data: 0.0072 max mem: 33368 +Epoch: [1] [1390/2639] eta: 1:00:18 lr: 4.827869345992654e-05 loss: 0.1750 (0.1884) time: 2.8752 data: 0.0071 max mem: 33368 +Epoch: [1] [1400/2639] eta: 0:59:48 lr: 4.8274413834387107e-05 loss: 0.1610 (0.1883) time: 2.8693 data: 0.0070 max mem: 33368 +Epoch: [1] [1410/2639] eta: 0:59:19 lr: 4.8270134166691974e-05 loss: 0.1550 (0.1883) time: 2.8494 data: 0.0073 max mem: 33368 +Epoch: [1] [1420/2639] eta: 0:58:50 lr: 4.826585445683657e-05 loss: 0.1550 (0.1881) time: 2.8797 data: 0.0076 max mem: 33368 +Epoch: [1] [1430/2639] eta: 0:58:21 lr: 4.826157470481633e-05 loss: 0.1527 (0.1880) time: 2.8744 data: 0.0075 max mem: 33368 +Epoch: [1] [1440/2639] eta: 0:57:51 lr: 4.825729491062669e-05 loss: 0.1799 (0.1881) time: 2.8281 data: 0.0073 max mem: 33368 +Epoch: [1] [1450/2639] eta: 0:57:22 lr: 4.825301507426306e-05 loss: 0.1679 (0.1881) time: 2.8648 data: 0.0074 max mem: 33368 +Epoch: [1] [1460/2639] eta: 0:56:53 lr: 4.824873519572088e-05 loss: 0.1678 (0.1880) time: 2.8804 data: 0.0074 max mem: 33368 +Epoch: [1] [1470/2639] eta: 0:56:24 lr: 4.824445527499559e-05 loss: 0.1733 (0.1881) time: 2.9061 data: 0.0071 max mem: 33368 +Epoch: [1] [1480/2639] eta: 0:55:55 lr: 4.82401753120826e-05 loss: 0.1639 (0.1881) time: 2.9016 data: 0.0076 max mem: 33368 +Epoch: [1] [1490/2639] eta: 0:55:26 lr: 4.823589530697733e-05 loss: 0.1665 (0.1881) time: 2.8740 data: 0.0078 max mem: 33368 +Epoch: [1] [1500/2639] eta: 0:54:57 lr: 4.823161525967522e-05 loss: 0.1808 (0.1881) time: 2.8563 data: 0.0075 max mem: 33368 +Epoch: [1] [1510/2639] eta: 0:54:27 lr: 4.822733517017168e-05 loss: 0.1512 (0.1881) time: 2.8426 data: 0.0074 max mem: 33368 +Epoch: [1] [1520/2639] eta: 0:53:58 lr: 4.8223055038462146e-05 loss: 0.1761 (0.1881) time: 2.8691 data: 0.0075 max mem: 33368 +Epoch: [1] [1530/2639] eta: 0:53:29 lr: 4.821877486454203e-05 loss: 0.1949 (0.1882) time: 2.8547 data: 0.0074 max mem: 33368 +Epoch: [1] [1540/2639] eta: 0:53:00 lr: 4.8214494648406744e-05 loss: 0.1887 (0.1886) time: 2.8514 data: 0.0075 max mem: 33368 +Epoch: [1] [1550/2639] eta: 0:52:31 lr: 4.8210214390051726e-05 loss: 0.1788 (0.1885) time: 2.9022 data: 0.0078 max mem: 33368 +Epoch: [1] [1560/2639] eta: 0:52:02 lr: 4.8205934089472394e-05 loss: 0.1669 (0.1884) time: 2.9231 data: 0.0076 max mem: 33368 +Epoch: [1] [1570/2639] eta: 0:51:33 lr: 4.820165374666415e-05 loss: 0.1622 (0.1885) time: 2.8944 data: 0.0074 max mem: 33368 +Epoch: [1] [1580/2639] eta: 0:51:04 lr: 4.8197373361622414e-05 loss: 0.1433 (0.1882) time: 2.8912 data: 0.0073 max mem: 33368 +Epoch: [1] [1590/2639] eta: 0:50:35 lr: 4.819309293434261e-05 loss: 0.1605 (0.1882) time: 2.8876 data: 0.0073 max mem: 33368 +Epoch: [1] [1600/2639] eta: 0:50:07 lr: 4.818881246482015e-05 loss: 0.1605 (0.1880) time: 2.9180 data: 0.0072 max mem: 33368 +Epoch: [1] [1610/2639] eta: 0:49:38 lr: 4.8184531953050455e-05 loss: 0.1762 (0.1880) time: 2.9125 data: 0.0072 max mem: 33368 +Epoch: [1] [1620/2639] eta: 0:49:09 lr: 4.8180251399028917e-05 loss: 0.1783 (0.1879) time: 2.8901 data: 0.0073 max mem: 33368 +Epoch: [1] [1630/2639] eta: 0:48:40 lr: 4.817597080275097e-05 loss: 0.1581 (0.1878) time: 2.9095 data: 0.0072 max mem: 33368 +Epoch: [1] [1640/2639] eta: 0:48:11 lr: 4.817169016421201e-05 loss: 0.1581 (0.1879) time: 2.9188 data: 0.0073 max mem: 33368 +Epoch: [1] [1650/2639] eta: 0:47:43 lr: 4.816740948340746e-05 loss: 0.1825 (0.1879) time: 2.9512 data: 0.0073 max mem: 33368 +Epoch: [1] [1660/2639] eta: 0:47:14 lr: 4.816312876033272e-05 loss: 0.1825 (0.1878) time: 2.9306 data: 0.0073 max mem: 33368 +Epoch: [1] [1670/2639] eta: 0:46:45 lr: 4.8158847994983195e-05 loss: 0.1749 (0.1877) time: 2.9121 data: 0.0071 max mem: 33368 +Epoch: [1] [1680/2639] eta: 0:46:16 lr: 4.815456718735431e-05 loss: 0.1681 (0.1876) time: 2.9325 data: 0.0069 max mem: 33368 +Epoch: [1] [1690/2639] eta: 0:45:47 lr: 4.815028633744144e-05 loss: 0.1665 (0.1874) time: 2.8576 data: 0.0071 max mem: 33368 +Epoch: [1] [1700/2639] eta: 0:45:18 lr: 4.814600544524002e-05 loss: 0.1645 (0.1876) time: 2.8373 data: 0.0076 max mem: 33368 +Epoch: [1] [1710/2639] eta: 0:44:49 lr: 4.814172451074544e-05 loss: 0.1602 (0.1875) time: 2.8636 data: 0.0077 max mem: 33368 +Epoch: [1] [1720/2639] eta: 0:44:20 lr: 4.8137443533953106e-05 loss: 0.1602 (0.1874) time: 2.8613 data: 0.0078 max mem: 33368 +Epoch: [1] [1730/2639] eta: 0:43:51 lr: 4.8133162514858424e-05 loss: 0.1597 (0.1874) time: 2.9080 data: 0.0076 max mem: 33368 +Epoch: [1] [1740/2639] eta: 0:43:22 lr: 4.8128881453456785e-05 loss: 0.1597 (0.1872) time: 2.8999 data: 0.0072 max mem: 33368 +Epoch: [1] [1750/2639] eta: 0:42:53 lr: 4.812460034974361e-05 loss: 0.1600 (0.1872) time: 2.8800 data: 0.0071 max mem: 33368 +Epoch: [1] [1760/2639] eta: 0:42:24 lr: 4.812031920371427e-05 loss: 0.1489 (0.1871) time: 2.9228 data: 0.0072 max mem: 33368 +Epoch: [1] [1770/2639] eta: 0:41:55 lr: 4.8116038015364184e-05 loss: 0.1460 (0.1870) time: 2.9018 data: 0.0077 max mem: 33368 +Epoch: [1] [1780/2639] eta: 0:41:26 lr: 4.811175678468874e-05 loss: 0.1581 (0.1869) time: 2.8465 data: 0.0077 max mem: 33368 +Epoch: [1] [1790/2639] eta: 0:40:57 lr: 4.8107475511683345e-05 loss: 0.1608 (0.1868) time: 2.8449 data: 0.0077 max mem: 33368 +Epoch: [1] [1800/2639] eta: 0:40:28 lr: 4.810319419634339e-05 loss: 0.1595 (0.1866) time: 2.8757 data: 0.0076 max mem: 33368 +Epoch: [1] [1810/2639] eta: 0:39:59 lr: 4.8098912838664276e-05 loss: 0.1452 (0.1866) time: 2.8832 data: 0.0072 max mem: 33368 +Epoch: [1] [1820/2639] eta: 0:39:30 lr: 4.8094631438641375e-05 loss: 0.1487 (0.1865) time: 2.8644 data: 0.0073 max mem: 33368 +Epoch: [1] [1830/2639] eta: 0:39:01 lr: 4.809034999627009e-05 loss: 0.1633 (0.1865) time: 2.8885 data: 0.0073 max mem: 33368 +Epoch: [1] [1840/2639] eta: 0:38:32 lr: 4.8086068511545836e-05 loss: 0.1640 (0.1865) time: 2.9054 data: 0.0075 max mem: 33368 +Epoch: [1] [1850/2639] eta: 0:38:03 lr: 4.808178698446397e-05 loss: 0.1710 (0.1864) time: 2.9056 data: 0.0075 max mem: 33368 +Epoch: [1] [1860/2639] eta: 0:37:34 lr: 4.80775054150199e-05 loss: 0.1764 (0.1865) time: 2.8990 data: 0.0071 max mem: 33368 +Epoch: [1] [1870/2639] eta: 0:37:05 lr: 4.8073223803209016e-05 loss: 0.1733 (0.1864) time: 2.9161 data: 0.0070 max mem: 33368 +Epoch: [1] [1880/2639] eta: 0:36:36 lr: 4.8068942149026704e-05 loss: 0.1716 (0.1864) time: 2.9075 data: 0.0073 max mem: 33368 +Epoch: [1] [1890/2639] eta: 0:36:07 lr: 4.806466045246834e-05 loss: 0.1966 (0.1866) time: 2.9018 data: 0.0077 max mem: 33368 +Epoch: [1] [1900/2639] eta: 0:35:39 lr: 4.8060378713529324e-05 loss: 0.1932 (0.1865) time: 2.9305 data: 0.0076 max mem: 33368 +Epoch: [1] [1910/2639] eta: 0:35:09 lr: 4.8056096932205035e-05 loss: 0.1695 (0.1864) time: 2.8765 data: 0.0076 max mem: 33368 +Epoch: [1] [1920/2639] eta: 0:34:40 lr: 4.805181510849086e-05 loss: 0.1553 (0.1863) time: 2.8293 data: 0.0077 max mem: 33368 +Epoch: [1] [1930/2639] eta: 0:34:11 lr: 4.804753324238218e-05 loss: 0.1770 (0.1863) time: 2.8533 data: 0.0076 max mem: 33368 +Epoch: [1] [1940/2639] eta: 0:33:42 lr: 4.804325133387438e-05 loss: 0.1904 (0.1864) time: 2.8486 data: 0.0073 max mem: 33368 +Epoch: [1] [1950/2639] eta: 0:33:13 lr: 4.803896938296284e-05 loss: 0.1579 (0.1863) time: 2.8341 data: 0.0072 max mem: 33368 +Epoch: [1] [1960/2639] eta: 0:32:44 lr: 4.803468738964294e-05 loss: 0.1568 (0.1864) time: 2.8727 data: 0.0073 max mem: 33368 +Epoch: [1] [1970/2639] eta: 0:32:15 lr: 4.803040535391006e-05 loss: 0.1733 (0.1864) time: 2.8687 data: 0.0076 max mem: 33368 +Epoch: [1] [1980/2639] eta: 0:31:46 lr: 4.802612327575957e-05 loss: 0.1828 (0.1863) time: 2.8563 data: 0.0080 max mem: 33368 +Epoch: [1] [1990/2639] eta: 0:31:17 lr: 4.802184115518686e-05 loss: 0.1828 (0.1864) time: 2.8741 data: 0.0079 max mem: 33368 +Epoch: [1] [2000/2639] eta: 0:30:48 lr: 4.801755899218731e-05 loss: 0.1938 (0.1865) time: 2.9004 data: 0.0075 max mem: 33368 +Epoch: [1] [2010/2639] eta: 0:30:19 lr: 4.801327678675627e-05 loss: 0.1912 (0.1865) time: 2.9112 data: 0.0074 max mem: 33368 +Epoch: [1] [2020/2639] eta: 0:29:50 lr: 4.800899453888915e-05 loss: 0.1639 (0.1864) time: 2.8757 data: 0.0075 max mem: 33368 +Epoch: [1] [2030/2639] eta: 0:29:21 lr: 4.800471224858129e-05 loss: 0.1552 (0.1864) time: 2.8458 data: 0.0072 max mem: 33368 +Epoch: [1] [2040/2639] eta: 0:28:52 lr: 4.8000429915828084e-05 loss: 0.1692 (0.1864) time: 2.8556 data: 0.0070 max mem: 33368 +Epoch: [1] [2050/2639] eta: 0:28:23 lr: 4.7996147540624906e-05 loss: 0.1736 (0.1865) time: 2.9001 data: 0.0074 max mem: 33368 +Epoch: [1] [2060/2639] eta: 0:27:54 lr: 4.799186512296711e-05 loss: 0.1730 (0.1864) time: 2.9156 data: 0.0075 max mem: 33368 +Epoch: [1] [2070/2639] eta: 0:27:25 lr: 4.798758266285008e-05 loss: 0.1730 (0.1865) time: 2.9103 data: 0.0075 max mem: 33368 +Epoch: [1] [2080/2639] eta: 0:26:57 lr: 4.798330016026917e-05 loss: 0.1966 (0.1866) time: 2.9063 data: 0.0074 max mem: 33368 +Epoch: [1] [2090/2639] eta: 0:26:28 lr: 4.7979017615219765e-05 loss: 0.1861 (0.1865) time: 2.8840 data: 0.0075 max mem: 33368 +Epoch: [1] [2100/2639] eta: 0:25:59 lr: 4.797473502769722e-05 loss: 0.1566 (0.1864) time: 2.8869 data: 0.0074 max mem: 33368 +Epoch: [1] [2110/2639] eta: 0:25:30 lr: 4.797045239769691e-05 loss: 0.1589 (0.1864) time: 2.9257 data: 0.0072 max mem: 33368 +Epoch: [1] [2120/2639] eta: 0:25:01 lr: 4.796616972521419e-05 loss: 0.1628 (0.1862) time: 2.8890 data: 0.0073 max mem: 33368 +Epoch: [1] [2130/2639] eta: 0:24:32 lr: 4.796188701024443e-05 loss: 0.1628 (0.1862) time: 2.8545 data: 0.0071 max mem: 33368 +Epoch: [1] [2140/2639] eta: 0:24:03 lr: 4.7957604252783e-05 loss: 0.1658 (0.1861) time: 2.8919 data: 0.0076 max mem: 33368 +Epoch: [1] [2150/2639] eta: 0:23:34 lr: 4.795332145282525e-05 loss: 0.1702 (0.1862) time: 2.8600 data: 0.0079 max mem: 33368 +Epoch: [1] [2160/2639] eta: 0:23:05 lr: 4.794903861036653e-05 loss: 0.1832 (0.1862) time: 2.8630 data: 0.0074 max mem: 33368 +Epoch: [1] [2170/2639] eta: 0:22:36 lr: 4.7944755725402234e-05 loss: 0.1832 (0.1862) time: 2.8902 data: 0.0075 max mem: 33368 +Epoch: [1] [2180/2639] eta: 0:22:07 lr: 4.794047279792769e-05 loss: 0.1838 (0.1862) time: 2.8482 data: 0.0074 max mem: 33368 +Epoch: [1] [2190/2639] eta: 0:21:38 lr: 4.7936189827938284e-05 loss: 0.1621 (0.1861) time: 2.8602 data: 0.0071 max mem: 33368 +Epoch: [1] [2200/2639] eta: 0:21:09 lr: 4.7931906815429346e-05 loss: 0.1458 (0.1860) time: 2.9305 data: 0.0075 max mem: 33368 +Epoch: [1] [2210/2639] eta: 0:20:40 lr: 4.7927623760396244e-05 loss: 0.1683 (0.1859) time: 2.9257 data: 0.0078 max mem: 33368 +Epoch: [1] [2220/2639] eta: 0:20:11 lr: 4.7923340662834335e-05 loss: 0.1793 (0.1860) time: 2.8946 data: 0.0073 max mem: 33368 +Epoch: [1] [2230/2639] eta: 0:19:43 lr: 4.791905752273898e-05 loss: 0.1794 (0.1860) time: 2.9196 data: 0.0070 max mem: 33368 +Epoch: [1] [2240/2639] eta: 0:19:14 lr: 4.791477434010552e-05 loss: 0.1742 (0.1861) time: 2.8900 data: 0.0074 max mem: 33368 +Epoch: [1] [2250/2639] eta: 0:18:45 lr: 4.791049111492931e-05 loss: 0.1688 (0.1861) time: 2.8786 data: 0.0078 max mem: 33368 +Epoch: [1] [2260/2639] eta: 0:18:16 lr: 4.79062078472057e-05 loss: 0.1688 (0.1860) time: 2.9036 data: 0.0078 max mem: 33368 +Epoch: [1] [2270/2639] eta: 0:17:47 lr: 4.790192453693004e-05 loss: 0.1938 (0.1862) time: 2.8607 data: 0.0079 max mem: 33368 +Epoch: [1] [2280/2639] eta: 0:17:18 lr: 4.789764118409769e-05 loss: 0.1928 (0.1862) time: 2.8504 data: 0.0081 max mem: 33368 +Epoch: [1] [2290/2639] eta: 0:16:49 lr: 4.789335778870399e-05 loss: 0.1768 (0.1861) time: 2.8489 data: 0.0077 max mem: 33368 +Epoch: [1] [2300/2639] eta: 0:16:20 lr: 4.788907435074429e-05 loss: 0.1351 (0.1860) time: 2.8620 data: 0.0075 max mem: 33368 +Epoch: [1] [2310/2639] eta: 0:15:51 lr: 4.788479087021393e-05 loss: 0.1389 (0.1859) time: 2.8830 data: 0.0076 max mem: 33368 +Epoch: [1] [2320/2639] eta: 0:15:22 lr: 4.788050734710827e-05 loss: 0.1610 (0.1859) time: 2.8612 data: 0.0076 max mem: 33368 +Epoch: [1] [2330/2639] eta: 0:14:53 lr: 4.787622378142264e-05 loss: 0.1700 (0.1859) time: 2.8457 data: 0.0079 max mem: 33368 +Epoch: [1] [2340/2639] eta: 0:14:24 lr: 4.7871940173152394e-05 loss: 0.1713 (0.1858) time: 2.8339 data: 0.0077 max mem: 33368 +Epoch: [1] [2350/2639] eta: 0:13:55 lr: 4.7867656522292864e-05 loss: 0.1633 (0.1858) time: 2.8891 data: 0.0075 max mem: 33368 +Epoch: [1] [2360/2639] eta: 0:13:26 lr: 4.78633728288394e-05 loss: 0.1800 (0.1857) time: 2.9125 data: 0.0078 max mem: 33368 +Epoch: [1] [2370/2639] eta: 0:12:57 lr: 4.785908909278734e-05 loss: 0.1590 (0.1856) time: 2.8804 data: 0.0074 max mem: 33368 +Epoch: [1] [2380/2639] eta: 0:12:28 lr: 4.785480531413203e-05 loss: 0.1333 (0.1855) time: 2.9453 data: 0.0072 max mem: 33368 +Epoch: [1] [2390/2639] eta: 0:11:59 lr: 4.7850521492868797e-05 loss: 0.1485 (0.1853) time: 2.9343 data: 0.0075 max mem: 33368 +Epoch: [1] [2400/2639] eta: 0:11:31 lr: 4.784623762899298e-05 loss: 0.1624 (0.1853) time: 2.8991 data: 0.0075 max mem: 33368 +Epoch: [1] [2410/2639] eta: 0:11:02 lr: 4.784195372249993e-05 loss: 0.1631 (0.1853) time: 2.9555 data: 0.0077 max mem: 33368 +Epoch: [1] [2420/2639] eta: 0:10:33 lr: 4.783766977338498e-05 loss: 0.1596 (0.1853) time: 2.9700 data: 0.0082 max mem: 33368 +Epoch: [1] [2430/2639] eta: 0:10:04 lr: 4.783338578164344e-05 loss: 0.1746 (0.1853) time: 2.9408 data: 0.0080 max mem: 33368 +Epoch: [1] [2440/2639] eta: 0:09:35 lr: 4.7829101747270676e-05 loss: 0.1653 (0.1852) time: 2.8844 data: 0.0078 max mem: 33368 +Epoch: [1] [2450/2639] eta: 0:09:06 lr: 4.7824817670262e-05 loss: 0.1637 (0.1851) time: 2.8687 data: 0.0076 max mem: 33368 +Epoch: [1] [2460/2639] eta: 0:08:37 lr: 4.7820533550612755e-05 loss: 0.1674 (0.1851) time: 2.8881 data: 0.0073 max mem: 33368 +Epoch: [1] [2470/2639] eta: 0:08:08 lr: 4.781624938831827e-05 loss: 0.1647 (0.1851) time: 2.9200 data: 0.0074 max mem: 33368 +Epoch: [1] [2480/2639] eta: 0:07:39 lr: 4.781196518337387e-05 loss: 0.1533 (0.1849) time: 2.9047 data: 0.0075 max mem: 33368 +Epoch: [1] [2490/2639] eta: 0:07:10 lr: 4.780768093577489e-05 loss: 0.1549 (0.1848) time: 2.8884 data: 0.0075 max mem: 33368 +Epoch: [1] [2500/2639] eta: 0:06:42 lr: 4.780339664551666e-05 loss: 0.1643 (0.1848) time: 2.8807 data: 0.0074 max mem: 33368 +Epoch: [1] [2510/2639] eta: 0:06:13 lr: 4.779911231259449e-05 loss: 0.1679 (0.1848) time: 2.8513 data: 0.0075 max mem: 33368 +Epoch: [1] [2520/2639] eta: 0:05:44 lr: 4.779482793700373e-05 loss: 0.1739 (0.1847) time: 2.8628 data: 0.0077 max mem: 33368 +Epoch: [1] [2530/2639] eta: 0:05:15 lr: 4.779054351873968e-05 loss: 0.1553 (0.1846) time: 2.8695 data: 0.0075 max mem: 33368 +Epoch: [1] [2540/2639] eta: 0:04:46 lr: 4.778625905779769e-05 loss: 0.1703 (0.1847) time: 2.8682 data: 0.0074 max mem: 33368 +Epoch: [1] [2550/2639] eta: 0:04:17 lr: 4.778197455417307e-05 loss: 0.1846 (0.1846) time: 2.8588 data: 0.0076 max mem: 33368 +Epoch: [1] [2560/2639] eta: 0:03:48 lr: 4.777769000786114e-05 loss: 0.1635 (0.1845) time: 2.8598 data: 0.0080 max mem: 33368 +Epoch: [1] [2570/2639] eta: 0:03:19 lr: 4.777340541885722e-05 loss: 0.1570 (0.1845) time: 2.9039 data: 0.0082 max mem: 33368 +Epoch: [1] [2580/2639] eta: 0:02:50 lr: 4.776912078715664e-05 loss: 0.1591 (0.1844) time: 2.9066 data: 0.0079 max mem: 33368 +Epoch: [1] [2590/2639] eta: 0:02:21 lr: 4.776483611275472e-05 loss: 0.1584 (0.1844) time: 2.8788 data: 0.0079 max mem: 33368 +Epoch: [1] [2600/2639] eta: 0:01:52 lr: 4.776055139564676e-05 loss: 0.1489 (0.1843) time: 2.9119 data: 0.0080 max mem: 33368 +Epoch: [1] [2610/2639] eta: 0:01:23 lr: 4.77562666358281e-05 loss: 0.1489 (0.1842) time: 2.9156 data: 0.0080 max mem: 33368 +Epoch: [1] [2620/2639] eta: 0:00:54 lr: 4.775198183329404e-05 loss: 0.1777 (0.1843) time: 2.8941 data: 0.0079 max mem: 33368 +Epoch: [1] [2630/2639] eta: 0:00:26 lr: 4.774769698803991e-05 loss: 0.1875 (0.1843) time: 2.8937 data: 0.0078 max mem: 33368 +Epoch: [1] Total time: 2:07:12 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 2:37:25 time: 3.6711 data: 3.5462 max mem: 33368 +Test: [ 100/2573] eta: 0:04:39 time: 0.0778 data: 0.0014 max mem: 33368 +Test: [ 200/2573] eta: 0:03:49 time: 0.0793 data: 0.0014 max mem: 33368 +Test: [ 300/2573] eta: 0:03:25 time: 0.0801 data: 0.0014 max mem: 33368 +Test: [ 400/2573] eta: 0:03:10 time: 0.0813 data: 0.0015 max mem: 33368 +Test: [ 500/2573] eta: 0:02:58 time: 0.0800 data: 0.0015 max mem: 33368 +Test: [ 600/2573] eta: 0:02:47 time: 0.0798 data: 0.0014 max mem: 33368 +Test: [ 700/2573] eta: 0:02:38 time: 0.0799 data: 0.0014 max mem: 33368 +Test: [ 800/2573] eta: 0:02:28 time: 0.0821 data: 0.0014 max mem: 33368 +Test: [ 900/2573] eta: 0:02:19 time: 0.0805 data: 0.0016 max mem: 33368 +Test: [1000/2573] eta: 0:02:10 time: 0.0793 data: 0.0015 max mem: 33368 +Test: [1100/2573] eta: 0:02:02 time: 0.0797 data: 0.0015 max mem: 33368 +Test: [1200/2573] eta: 0:01:53 time: 0.0805 data: 0.0015 max mem: 33368 +Test: [1300/2573] eta: 0:01:45 time: 0.0803 data: 0.0014 max mem: 33368 +Test: [1400/2573] eta: 0:01:36 time: 0.0791 data: 0.0014 max mem: 33368 +Test: [1500/2573] eta: 0:01:28 time: 0.0802 data: 0.0014 max mem: 33368 +Test: [1600/2573] eta: 0:01:19 time: 0.0830 data: 0.0014 max mem: 33368 +Test: [1700/2573] eta: 0:01:11 time: 0.0780 data: 0.0014 max mem: 33368 +Test: [1800/2573] eta: 0:01:03 time: 0.0816 data: 0.0014 max mem: 33368 +Test: [1900/2573] eta: 0:00:55 time: 0.0784 data: 0.0013 max mem: 33368 +Test: [2000/2573] eta: 0:00:46 time: 0.0799 data: 0.0015 max mem: 33368 +Test: [2100/2573] eta: 0:00:38 time: 0.0814 data: 0.0014 max mem: 33368 +Test: [2200/2573] eta: 0:00:30 time: 0.0820 data: 0.0014 max mem: 33368 +Test: [2300/2573] eta: 0:00:22 time: 0.0818 data: 0.0015 max mem: 33368 +Test: [2400/2573] eta: 0:00:14 time: 0.0777 data: 0.0014 max mem: 33368 +Test: [2500/2573] eta: 0:00:05 time: 0.0802 data: 0.0014 max mem: 33368 +Test: Total time: 0:03:30 +Final results: +Mean IoU is 40.66 + + precision@0.5 = 42.44 + precision@0.6 = 33.74 + precision@0.7 = 24.94 + precision@0.8 = 14.99 + precision@0.9 = 4.17 + overall IoU = 44.21 + +Average object IoU 40.661710867246136 +Overall IoU 44.2130241394043 +Better epoch: 1 + +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [2] [ 0/2639] eta: 3:53:19 lr: 4.7743840590781646e-05 loss: 0.1305 (0.1305) time: 5.3047 data: 2.2997 max mem: 33368 +Epoch: [2] [ 10/2639] eta: 2:15:34 lr: 4.773955566434645e-05 loss: 0.1637 (0.1683) time: 3.0940 data: 0.2160 max mem: 33368 +Epoch: [2] [ 20/2639] eta: 2:10:22 lr: 4.773527069517758e-05 loss: 0.1648 (0.1739) time: 2.8710 data: 0.0082 max mem: 33368 +Epoch: [2] [ 30/2639] eta: 2:08:36 lr: 4.7730985683270355e-05 loss: 0.1648 (0.1754) time: 2.8826 data: 0.0083 max mem: 33368 +Epoch: [2] [ 40/2639] eta: 2:06:39 lr: 4.7726700628620086e-05 loss: 0.1656 (0.1721) time: 2.8583 data: 0.0079 max mem: 33368 +Epoch: [2] [ 50/2639] eta: 2:05:21 lr: 4.7722415531222076e-05 loss: 0.1493 (0.1708) time: 2.8236 data: 0.0079 max mem: 33368 +Epoch: [2] [ 60/2639] eta: 2:04:38 lr: 4.771813039107164e-05 loss: 0.1285 (0.1657) time: 2.8492 data: 0.0079 max mem: 33368 +Epoch: [2] [ 70/2639] eta: 2:04:02 lr: 4.771384520816407e-05 loss: 0.1315 (0.1630) time: 2.8772 data: 0.0079 max mem: 33368 +Epoch: [2] [ 80/2639] eta: 2:03:09 lr: 4.7709559982494694e-05 loss: 0.1589 (0.1699) time: 2.8510 data: 0.0078 max mem: 33368 +Epoch: [2] [ 90/2639] eta: 2:02:49 lr: 4.7705274714058804e-05 loss: 0.1589 (0.1689) time: 2.8695 data: 0.0076 max mem: 33368 +Epoch: [2] [ 100/2639] eta: 2:02:37 lr: 4.7700989402851715e-05 loss: 0.1341 (0.1669) time: 2.9392 data: 0.0076 max mem: 33368 +Epoch: [2] [ 110/2639] eta: 2:02:08 lr: 4.769670404886872e-05 loss: 0.1335 (0.1648) time: 2.9275 data: 0.0078 max mem: 33368 +Epoch: [2] [ 120/2639] eta: 2:01:42 lr: 4.7692418652105127e-05 loss: 0.1471 (0.1637) time: 2.9039 data: 0.0084 max mem: 33368 +Epoch: [2] [ 130/2639] eta: 2:00:57 lr: 4.7688133212556235e-05 loss: 0.1867 (0.1695) time: 2.8646 data: 0.0083 max mem: 33368 +Epoch: [2] [ 140/2639] eta: 2:00:36 lr: 4.7683847730217354e-05 loss: 0.2024 (0.1709) time: 2.8779 data: 0.0083 max mem: 33368 +Epoch: [2] [ 150/2639] eta: 2:00:01 lr: 4.767956220508376e-05 loss: 0.1715 (0.1701) time: 2.8996 data: 0.0093 max mem: 33368 +Epoch: [2] [ 160/2639] eta: 1:59:40 lr: 4.767527663715078e-05 loss: 0.1516 (0.1690) time: 2.9028 data: 0.0092 max mem: 33368 +Epoch: [2] [ 170/2639] eta: 1:59:13 lr: 4.76709910264137e-05 loss: 0.1516 (0.1691) time: 2.9274 data: 0.0084 max mem: 33368 +Epoch: [2] [ 180/2639] eta: 1:58:47 lr: 4.766670537286781e-05 loss: 0.1388 (0.1675) time: 2.9143 data: 0.0082 max mem: 33368 +Epoch: [2] [ 190/2639] eta: 1:58:16 lr: 4.7662419676508415e-05 loss: 0.1331 (0.1664) time: 2.8989 data: 0.0083 max mem: 33368 +Epoch: [2] [ 200/2639] eta: 1:57:51 lr: 4.765813393733081e-05 loss: 0.1540 (0.1663) time: 2.9059 data: 0.0081 max mem: 33368 +Epoch: [2] [ 210/2639] eta: 1:57:25 lr: 4.7653848155330276e-05 loss: 0.1622 (0.1661) time: 2.9267 data: 0.0078 max mem: 33368 +Epoch: [2] [ 220/2639] eta: 1:57:02 lr: 4.764956233050212e-05 loss: 0.1588 (0.1658) time: 2.9397 data: 0.0078 max mem: 33368 +Epoch: [2] [ 230/2639] eta: 1:56:32 lr: 4.7645276462841635e-05 loss: 0.1519 (0.1651) time: 2.9269 data: 0.0078 max mem: 33368 +Epoch: [2] [ 240/2639] eta: 1:56:03 lr: 4.76409905523441e-05 loss: 0.1558 (0.1657) time: 2.8983 data: 0.0079 max mem: 33368 +Epoch: [2] [ 250/2639] eta: 1:55:30 lr: 4.7636704599004816e-05 loss: 0.1559 (0.1654) time: 2.8815 data: 0.0082 max mem: 33368 +Epoch: [2] [ 260/2639] eta: 1:55:01 lr: 4.763241860281906e-05 loss: 0.1612 (0.1657) time: 2.8799 data: 0.0080 max mem: 33368 +Epoch: [2] [ 270/2639] eta: 1:54:32 lr: 4.7628132563782134e-05 loss: 0.1758 (0.1667) time: 2.8988 data: 0.0078 max mem: 33368 +Epoch: [2] [ 280/2639] eta: 1:54:03 lr: 4.762384648188931e-05 loss: 0.1517 (0.1663) time: 2.9015 data: 0.0076 max mem: 33368 +Epoch: [2] [ 290/2639] eta: 1:53:35 lr: 4.761956035713589e-05 loss: 0.1407 (0.1665) time: 2.9096 data: 0.0076 max mem: 33368 +Epoch: [2] [ 300/2639] eta: 1:53:07 lr: 4.7615274189517144e-05 loss: 0.1487 (0.1659) time: 2.9128 data: 0.0078 max mem: 33368 +Epoch: [2] [ 310/2639] eta: 1:52:43 lr: 4.761098797902837e-05 loss: 0.1508 (0.1660) time: 2.9394 data: 0.0079 max mem: 33368 +Epoch: [2] [ 320/2639] eta: 1:52:16 lr: 4.760670172566483e-05 loss: 0.1599 (0.1659) time: 2.9558 data: 0.0082 max mem: 33368 +Epoch: [2] [ 330/2639] eta: 1:51:45 lr: 4.760241542942183e-05 loss: 0.1507 (0.1652) time: 2.9078 data: 0.0081 max mem: 33368 +Epoch: [2] [ 340/2639] eta: 1:51:18 lr: 4.759812909029463e-05 loss: 0.1524 (0.1652) time: 2.9005 data: 0.0079 max mem: 33368 +Epoch: [2] [ 350/2639] eta: 1:50:43 lr: 4.759384270827853e-05 loss: 0.1500 (0.1649) time: 2.8749 data: 0.0079 max mem: 33368 +Epoch: [2] [ 360/2639] eta: 1:50:14 lr: 4.758955628336879e-05 loss: 0.1352 (0.1643) time: 2.8643 data: 0.0079 max mem: 33368 +Epoch: [2] [ 370/2639] eta: 1:49:45 lr: 4.75852698155607e-05 loss: 0.1352 (0.1643) time: 2.9016 data: 0.0077 max mem: 33368 +Epoch: [2] [ 380/2639] eta: 1:49:16 lr: 4.758098330484953e-05 loss: 0.1701 (0.1650) time: 2.8970 data: 0.0075 max mem: 33368 +Epoch: [2] [ 390/2639] eta: 1:48:45 lr: 4.757669675123057e-05 loss: 0.1830 (0.1653) time: 2.8850 data: 0.0076 max mem: 33368 +Epoch: [2] [ 400/2639] eta: 1:48:15 lr: 4.7572410154699075e-05 loss: 0.1525 (0.1650) time: 2.8780 data: 0.0078 max mem: 33368 +Epoch: [2] [ 410/2639] eta: 1:47:44 lr: 4.756812351525034e-05 loss: 0.1420 (0.1647) time: 2.8776 data: 0.0079 max mem: 33368 +Epoch: [2] [ 420/2639] eta: 1:47:16 lr: 4.756383683287961e-05 loss: 0.1612 (0.1647) time: 2.8872 data: 0.0076 max mem: 33368 +Epoch: [2] [ 430/2639] eta: 1:46:44 lr: 4.755955010758218e-05 loss: 0.1656 (0.1646) time: 2.8812 data: 0.0075 max mem: 33368 +Epoch: [2] [ 440/2639] eta: 1:46:12 lr: 4.7555263339353316e-05 loss: 0.1452 (0.1643) time: 2.8472 data: 0.0076 max mem: 33368 +Epoch: [2] [ 450/2639] eta: 1:45:42 lr: 4.7550976528188286e-05 loss: 0.1691 (0.1649) time: 2.8558 data: 0.0077 max mem: 33368 +Epoch: [2] [ 460/2639] eta: 1:45:15 lr: 4.7546689674082365e-05 loss: 0.1749 (0.1649) time: 2.9017 data: 0.0075 max mem: 33368 +Epoch: [2] [ 470/2639] eta: 1:44:49 lr: 4.75424027770308e-05 loss: 0.1533 (0.1648) time: 2.9483 data: 0.0076 max mem: 33368 +Epoch: [2] [ 480/2639] eta: 1:44:20 lr: 4.753811583702889e-05 loss: 0.1397 (0.1645) time: 2.9357 data: 0.0078 max mem: 33368 +Epoch: [2] [ 490/2639] eta: 1:43:54 lr: 4.753382885407187e-05 loss: 0.1424 (0.1645) time: 2.9343 data: 0.0076 max mem: 33368 +Epoch: [2] [ 500/2639] eta: 1:43:22 lr: 4.7529541828155034e-05 loss: 0.1596 (0.1643) time: 2.9045 data: 0.0078 max mem: 33368 +Epoch: [2] [ 510/2639] eta: 1:42:54 lr: 4.752525475927362e-05 loss: 0.1475 (0.1642) time: 2.8768 data: 0.0079 max mem: 33368 +Epoch: [2] [ 520/2639] eta: 1:42:26 lr: 4.7520967647422916e-05 loss: 0.1429 (0.1644) time: 2.9162 data: 0.0079 max mem: 33368 +Epoch: [2] [ 530/2639] eta: 1:41:58 lr: 4.751668049259816e-05 loss: 0.1555 (0.1645) time: 2.9214 data: 0.0081 max mem: 33368 +Epoch: [2] [ 540/2639] eta: 1:41:30 lr: 4.751239329479463e-05 loss: 0.1564 (0.1643) time: 2.9297 data: 0.0080 max mem: 33368 +Epoch: [2] [ 550/2639] eta: 1:41:01 lr: 4.750810605400757e-05 loss: 0.1287 (0.1637) time: 2.9155 data: 0.0078 max mem: 33368 +Epoch: [2] [ 560/2639] eta: 1:40:30 lr: 4.750381877023225e-05 loss: 0.1395 (0.1643) time: 2.8759 data: 0.0081 max mem: 33368 +Epoch: [2] [ 570/2639] eta: 1:40:00 lr: 4.7499531443463937e-05 loss: 0.1507 (0.1643) time: 2.8634 data: 0.0084 max mem: 33368 +Epoch: [2] [ 580/2639] eta: 1:39:30 lr: 4.749524407369787e-05 loss: 0.1719 (0.1649) time: 2.8781 data: 0.0079 max mem: 33368 +Epoch: [2] [ 590/2639] eta: 1:39:02 lr: 4.7490956660929315e-05 loss: 0.1652 (0.1646) time: 2.8961 data: 0.0080 max mem: 33368 +Epoch: [2] [ 600/2639] eta: 1:38:34 lr: 4.7486669205153524e-05 loss: 0.1515 (0.1643) time: 2.9160 data: 0.0080 max mem: 33368 +Epoch: [2] [ 610/2639] eta: 1:38:02 lr: 4.748238170636575e-05 loss: 0.1530 (0.1649) time: 2.8704 data: 0.0075 max mem: 33368 +Epoch: [2] [ 620/2639] eta: 1:37:33 lr: 4.7478094164561255e-05 loss: 0.1640 (0.1653) time: 2.8641 data: 0.0077 max mem: 33368 +Epoch: [2] [ 630/2639] eta: 1:37:06 lr: 4.747380657973528e-05 loss: 0.1900 (0.1656) time: 2.9393 data: 0.0076 max mem: 33368 +Epoch: [2] [ 640/2639] eta: 1:36:38 lr: 4.7469518951883076e-05 loss: 0.1694 (0.1659) time: 2.9454 data: 0.0074 max mem: 33368 +Epoch: [2] [ 650/2639] eta: 1:36:12 lr: 4.74652312809999e-05 loss: 0.1616 (0.1657) time: 2.9579 data: 0.0074 max mem: 33368 +Epoch: [2] [ 660/2639] eta: 1:35:43 lr: 4.7460943567081e-05 loss: 0.1532 (0.1658) time: 2.9558 data: 0.0075 max mem: 33368 +Epoch: [2] [ 670/2639] eta: 1:35:13 lr: 4.7456655810121616e-05 loss: 0.1677 (0.1658) time: 2.8943 data: 0.0075 max mem: 33368 +Epoch: [2] [ 680/2639] eta: 1:34:44 lr: 4.7452368010117e-05 loss: 0.1556 (0.1658) time: 2.8756 data: 0.0074 max mem: 33368 +Epoch: [2] [ 690/2639] eta: 1:34:13 lr: 4.744808016706241e-05 loss: 0.1621 (0.1662) time: 2.8577 data: 0.0075 max mem: 33368 +Epoch: [2] [ 700/2639] eta: 1:33:46 lr: 4.7443792280953076e-05 loss: 0.1788 (0.1661) time: 2.9072 data: 0.0075 max mem: 33368 +Epoch: [2] [ 710/2639] eta: 1:33:18 lr: 4.7439504351784245e-05 loss: 0.1775 (0.1662) time: 2.9674 data: 0.0074 max mem: 33368 +Epoch: [2] [ 720/2639] eta: 1:32:48 lr: 4.743521637955116e-05 loss: 0.1775 (0.1662) time: 2.8996 data: 0.0076 max mem: 33368 +Epoch: [2] [ 730/2639] eta: 1:32:18 lr: 4.743092836424907e-05 loss: 0.1728 (0.1664) time: 2.8532 data: 0.0078 max mem: 33368 +Epoch: [2] [ 740/2639] eta: 1:31:49 lr: 4.74266403058732e-05 loss: 0.1446 (0.1659) time: 2.8867 data: 0.0077 max mem: 33368 +Epoch: [2] [ 750/2639] eta: 1:31:20 lr: 4.7422352204418815e-05 loss: 0.1517 (0.1661) time: 2.9100 data: 0.0076 max mem: 33368 +Epoch: [2] [ 760/2639] eta: 1:30:51 lr: 4.7418064059881124e-05 loss: 0.1645 (0.1664) time: 2.8911 data: 0.0076 max mem: 33368 +Epoch: [2] [ 770/2639] eta: 1:30:23 lr: 4.741377587225539e-05 loss: 0.1510 (0.1666) time: 2.9129 data: 0.0077 max mem: 33368 +Epoch: [2] [ 780/2639] eta: 1:29:54 lr: 4.740948764153683e-05 loss: 0.1510 (0.1667) time: 2.9240 data: 0.0079 max mem: 33368 +Epoch: [2] [ 790/2639] eta: 1:29:24 lr: 4.74051993677207e-05 loss: 0.1479 (0.1666) time: 2.8835 data: 0.0081 max mem: 33368 +Epoch: [2] [ 800/2639] eta: 1:28:55 lr: 4.740091105080223e-05 loss: 0.1440 (0.1664) time: 2.8812 data: 0.0080 max mem: 33368 +Epoch: [2] [ 810/2639] eta: 1:28:25 lr: 4.739662269077664e-05 loss: 0.1454 (0.1663) time: 2.8804 data: 0.0082 max mem: 33368 +Epoch: [2] [ 820/2639] eta: 1:27:54 lr: 4.739233428763917e-05 loss: 0.1596 (0.1662) time: 2.8494 data: 0.0081 max mem: 33368 +Epoch: [2] [ 830/2639] eta: 1:27:24 lr: 4.7388045841385064e-05 loss: 0.1571 (0.1660) time: 2.8421 data: 0.0079 max mem: 33368 +Epoch: [2] [ 840/2639] eta: 1:26:54 lr: 4.738375735200953e-05 loss: 0.1441 (0.1658) time: 2.8472 data: 0.0080 max mem: 33368 +Epoch: [2] [ 850/2639] eta: 1:26:25 lr: 4.737946881950783e-05 loss: 0.1418 (0.1656) time: 2.8661 data: 0.0078 max mem: 33368 +Epoch: [2] [ 860/2639] eta: 1:25:57 lr: 4.7375180243875157e-05 loss: 0.1423 (0.1654) time: 2.9243 data: 0.0081 max mem: 33368 +Epoch: [2] [ 870/2639] eta: 1:25:29 lr: 4.7370891625106764e-05 loss: 0.1399 (0.1651) time: 2.9492 data: 0.0078 max mem: 33368 +Epoch: [2] [ 880/2639] eta: 1:24:59 lr: 4.736660296319787e-05 loss: 0.1423 (0.1649) time: 2.8987 data: 0.0076 max mem: 33368 +Epoch: [2] [ 890/2639] eta: 1:24:30 lr: 4.7362314258143696e-05 loss: 0.1468 (0.1649) time: 2.8648 data: 0.0077 max mem: 33368 +Epoch: [2] [ 900/2639] eta: 1:23:59 lr: 4.7358025509939474e-05 loss: 0.1550 (0.1648) time: 2.8546 data: 0.0074 max mem: 33368 +Epoch: [2] [ 910/2639] eta: 1:23:30 lr: 4.7353736718580433e-05 loss: 0.1587 (0.1647) time: 2.8567 data: 0.0078 max mem: 33368 +Epoch: [2] [ 920/2639] eta: 1:23:01 lr: 4.7349447884061785e-05 loss: 0.1629 (0.1647) time: 2.8737 data: 0.0080 max mem: 33368 +Epoch: [2] [ 930/2639] eta: 1:22:31 lr: 4.7345159006378744e-05 loss: 0.1613 (0.1648) time: 2.8685 data: 0.0080 max mem: 33368 +Epoch: [2] [ 940/2639] eta: 1:22:03 lr: 4.7340870085526554e-05 loss: 0.1469 (0.1646) time: 2.8992 data: 0.0084 max mem: 33368 +Epoch: [2] [ 950/2639] eta: 1:21:34 lr: 4.7336581121500417e-05 loss: 0.1352 (0.1647) time: 2.9131 data: 0.0080 max mem: 33368 +Epoch: [2] [ 960/2639] eta: 1:21:06 lr: 4.733229211429557e-05 loss: 0.1536 (0.1646) time: 2.9437 data: 0.0074 max mem: 33368 +Epoch: [2] [ 970/2639] eta: 1:20:38 lr: 4.7328003063907206e-05 loss: 0.1512 (0.1645) time: 2.9777 data: 0.0077 max mem: 33368 +Epoch: [2] [ 980/2639] eta: 1:20:10 lr: 4.7323713970330564e-05 loss: 0.1427 (0.1645) time: 2.9471 data: 0.0079 max mem: 33368 +Epoch: [2] [ 990/2639] eta: 1:19:41 lr: 4.731942483356084e-05 loss: 0.1452 (0.1645) time: 2.9047 data: 0.0079 max mem: 33368 +Epoch: [2] [1000/2639] eta: 1:19:12 lr: 4.731513565359327e-05 loss: 0.1582 (0.1645) time: 2.8915 data: 0.0076 max mem: 33368 +Epoch: [2] [1010/2639] eta: 1:18:43 lr: 4.731084643042305e-05 loss: 0.1492 (0.1646) time: 2.9120 data: 0.0080 max mem: 33368 +Epoch: [2] [1020/2639] eta: 1:18:13 lr: 4.730655716404541e-05 loss: 0.1473 (0.1645) time: 2.8866 data: 0.0080 max mem: 33368 +Epoch: [2] [1030/2639] eta: 1:17:44 lr: 4.730226785445554e-05 loss: 0.1559 (0.1646) time: 2.8668 data: 0.0079 max mem: 33368 +Epoch: [2] [1040/2639] eta: 1:17:16 lr: 4.729797850164866e-05 loss: 0.1418 (0.1643) time: 2.9344 data: 0.0080 max mem: 33368 +Epoch: [2] [1050/2639] eta: 1:16:47 lr: 4.7293689105619995e-05 loss: 0.1395 (0.1643) time: 2.9453 data: 0.0080 max mem: 33368 +Epoch: [2] [1060/2639] eta: 1:16:19 lr: 4.7289399666364735e-05 loss: 0.1664 (0.1645) time: 2.9080 data: 0.0080 max mem: 33368 +Epoch: [2] [1070/2639] eta: 1:15:49 lr: 4.728511018387809e-05 loss: 0.1505 (0.1643) time: 2.8992 data: 0.0080 max mem: 33368 +Epoch: [2] [1080/2639] eta: 1:15:21 lr: 4.728082065815528e-05 loss: 0.1364 (0.1641) time: 2.8964 data: 0.0082 max mem: 33368 +Epoch: [2] [1090/2639] eta: 1:14:52 lr: 4.72765310891915e-05 loss: 0.1448 (0.1640) time: 2.9314 data: 0.0079 max mem: 33368 +Epoch: [2] [1100/2639] eta: 1:14:23 lr: 4.727224147698195e-05 loss: 0.1448 (0.1640) time: 2.9224 data: 0.0083 max mem: 33368 +Epoch: [2] [1110/2639] eta: 1:13:54 lr: 4.726795182152184e-05 loss: 0.1455 (0.1639) time: 2.8796 data: 0.0080 max mem: 33368 +Epoch: [2] [1120/2639] eta: 1:13:24 lr: 4.7263662122806376e-05 loss: 0.1462 (0.1641) time: 2.8420 data: 0.0076 max mem: 33368 +Epoch: [2] [1130/2639] eta: 1:12:54 lr: 4.725937238083074e-05 loss: 0.1502 (0.1641) time: 2.8425 data: 0.0077 max mem: 33368 +Epoch: [2] [1140/2639] eta: 1:12:25 lr: 4.725508259559017e-05 loss: 0.1502 (0.1641) time: 2.8731 data: 0.0075 max mem: 33368 +Epoch: [2] [1150/2639] eta: 1:11:56 lr: 4.725079276707984e-05 loss: 0.1502 (0.1641) time: 2.8927 data: 0.0077 max mem: 33368 +Epoch: [2] [1160/2639] eta: 1:11:27 lr: 4.724650289529495e-05 loss: 0.1415 (0.1643) time: 2.8971 data: 0.0074 max mem: 33368 +Epoch: [2] [1170/2639] eta: 1:10:58 lr: 4.7242212980230693e-05 loss: 0.1415 (0.1645) time: 2.9048 data: 0.0074 max mem: 33368 +Epoch: [2] [1180/2639] eta: 1:10:30 lr: 4.7237923021882276e-05 loss: 0.1376 (0.1642) time: 2.9231 data: 0.0075 max mem: 33368 +Epoch: [2] [1190/2639] eta: 1:10:00 lr: 4.723363302024489e-05 loss: 0.1322 (0.1640) time: 2.8949 data: 0.0075 max mem: 33368 +Epoch: [2] [1200/2639] eta: 1:09:32 lr: 4.7229342975313736e-05 loss: 0.1327 (0.1638) time: 2.9095 data: 0.0076 max mem: 33368 +Epoch: [2] [1210/2639] eta: 1:09:03 lr: 4.7225052887084e-05 loss: 0.1338 (0.1638) time: 2.9373 data: 0.0074 max mem: 33368 +Epoch: [2] [1220/2639] eta: 1:08:34 lr: 4.722076275555087e-05 loss: 0.1587 (0.1639) time: 2.9036 data: 0.0078 max mem: 33368 +Epoch: [2] [1230/2639] eta: 1:08:05 lr: 4.721647258070956e-05 loss: 0.1567 (0.1639) time: 2.9100 data: 0.0079 max mem: 33368 +Epoch: [2] [1240/2639] eta: 1:07:36 lr: 4.721218236255523e-05 loss: 0.1462 (0.1638) time: 2.9066 data: 0.0078 max mem: 33368 +Epoch: [2] [1250/2639] eta: 1:07:07 lr: 4.720789210108309e-05 loss: 0.1462 (0.1639) time: 2.8715 data: 0.0082 max mem: 33368 +Epoch: [2] [1260/2639] eta: 1:06:38 lr: 4.720360179628832e-05 loss: 0.1675 (0.1640) time: 2.8751 data: 0.0083 max mem: 33368 +Epoch: [2] [1270/2639] eta: 1:06:08 lr: 4.719931144816612e-05 loss: 0.1594 (0.1639) time: 2.8726 data: 0.0082 max mem: 33368 +Epoch: [2] [1280/2639] eta: 1:05:39 lr: 4.719502105671165e-05 loss: 0.1457 (0.1640) time: 2.8660 data: 0.0083 max mem: 33368 +Epoch: [2] [1290/2639] eta: 1:05:10 lr: 4.719073062192012e-05 loss: 0.1722 (0.1642) time: 2.8765 data: 0.0081 max mem: 33368 +Epoch: [2] [1300/2639] eta: 1:04:41 lr: 4.7186440143786705e-05 loss: 0.1613 (0.1640) time: 2.9065 data: 0.0081 max mem: 33368 +Epoch: [2] [1310/2639] eta: 1:04:12 lr: 4.7182149622306586e-05 loss: 0.1547 (0.1640) time: 2.9236 data: 0.0078 max mem: 33368 +Epoch: [2] [1320/2639] eta: 1:03:43 lr: 4.717785905747495e-05 loss: 0.1637 (0.1644) time: 2.9091 data: 0.0075 max mem: 33368 +Epoch: [2] [1330/2639] eta: 1:03:14 lr: 4.717356844928698e-05 loss: 0.1692 (0.1644) time: 2.9062 data: 0.0073 max mem: 33368 +Epoch: [2] [1340/2639] eta: 1:02:45 lr: 4.7169277797737845e-05 loss: 0.1529 (0.1644) time: 2.8648 data: 0.0071 max mem: 33368 +Epoch: [2] [1350/2639] eta: 1:02:16 lr: 4.7164987102822737e-05 loss: 0.1500 (0.1644) time: 2.8756 data: 0.0072 max mem: 33368 +Epoch: [2] [1360/2639] eta: 1:01:47 lr: 4.7160696364536824e-05 loss: 0.1448 (0.1642) time: 2.9118 data: 0.0072 max mem: 33368 +Epoch: [2] [1370/2639] eta: 1:01:18 lr: 4.71564055828753e-05 loss: 0.1630 (0.1645) time: 2.8812 data: 0.0075 max mem: 33368 +Epoch: [2] [1380/2639] eta: 1:00:48 lr: 4.715211475783332e-05 loss: 0.1674 (0.1644) time: 2.8655 data: 0.0076 max mem: 33368 +Epoch: [2] [1390/2639] eta: 1:00:19 lr: 4.714782388940607e-05 loss: 0.1400 (0.1642) time: 2.8690 data: 0.0076 max mem: 33368 +Epoch: [2] [1400/2639] eta: 0:59:50 lr: 4.7143532977588725e-05 loss: 0.1362 (0.1639) time: 2.8995 data: 0.0075 max mem: 33368 +Epoch: [2] [1410/2639] eta: 0:59:22 lr: 4.7139242022376455e-05 loss: 0.1383 (0.1638) time: 2.9380 data: 0.0072 max mem: 33368 +Epoch: [2] [1420/2639] eta: 0:58:53 lr: 4.713495102376443e-05 loss: 0.1501 (0.1639) time: 2.9368 data: 0.0077 max mem: 33369 +Epoch: [2] [1430/2639] eta: 0:58:24 lr: 4.713065998174782e-05 loss: 0.1490 (0.1638) time: 2.9066 data: 0.0080 max mem: 33369 +Epoch: [2] [1440/2639] eta: 0:57:55 lr: 4.7126368896321804e-05 loss: 0.1498 (0.1636) time: 2.9212 data: 0.0080 max mem: 33369 +Epoch: [2] [1450/2639] eta: 0:57:26 lr: 4.712207776748154e-05 loss: 0.1472 (0.1635) time: 2.8917 data: 0.0076 max mem: 33369 +Epoch: [2] [1460/2639] eta: 0:56:57 lr: 4.7117786595222215e-05 loss: 0.1469 (0.1634) time: 2.8680 data: 0.0073 max mem: 33369 +Epoch: [2] [1470/2639] eta: 0:56:28 lr: 4.711349537953897e-05 loss: 0.1465 (0.1636) time: 2.9048 data: 0.0076 max mem: 33369 +Epoch: [2] [1480/2639] eta: 0:56:00 lr: 4.710920412042699e-05 loss: 0.1510 (0.1636) time: 2.9355 data: 0.0074 max mem: 33369 +Epoch: [2] [1490/2639] eta: 0:55:31 lr: 4.7104912817881424e-05 loss: 0.1582 (0.1637) time: 2.9632 data: 0.0073 max mem: 33369 +Epoch: [2] [1500/2639] eta: 0:55:02 lr: 4.7100621471897456e-05 loss: 0.1657 (0.1638) time: 2.9327 data: 0.0076 max mem: 33369 +Epoch: [2] [1510/2639] eta: 0:54:33 lr: 4.709633008247023e-05 loss: 0.1505 (0.1636) time: 2.9107 data: 0.0075 max mem: 33369 +Epoch: [2] [1520/2639] eta: 0:54:05 lr: 4.709203864959492e-05 loss: 0.1426 (0.1635) time: 2.9474 data: 0.0074 max mem: 33369 +Epoch: [2] [1530/2639] eta: 0:53:36 lr: 4.7087747173266676e-05 loss: 0.1444 (0.1635) time: 2.9464 data: 0.0079 max mem: 33369 +Epoch: [2] [1540/2639] eta: 0:53:07 lr: 4.7083455653480675e-05 loss: 0.1480 (0.1634) time: 2.9081 data: 0.0081 max mem: 33369 +Epoch: [2] [1550/2639] eta: 0:52:38 lr: 4.707916409023205e-05 loss: 0.1519 (0.1635) time: 2.8792 data: 0.0079 max mem: 33369 +Epoch: [2] [1560/2639] eta: 0:52:08 lr: 4.707487248351599e-05 loss: 0.1683 (0.1635) time: 2.8554 data: 0.0078 max mem: 33369 +Epoch: [2] [1570/2639] eta: 0:51:39 lr: 4.707058083332762e-05 loss: 0.1295 (0.1634) time: 2.8550 data: 0.0076 max mem: 33369 +Epoch: [2] [1580/2639] eta: 0:51:10 lr: 4.7066289139662116e-05 loss: 0.1338 (0.1634) time: 2.8718 data: 0.0076 max mem: 33369 +Epoch: [2] [1590/2639] eta: 0:50:41 lr: 4.7061997402514627e-05 loss: 0.1487 (0.1636) time: 2.8945 data: 0.0077 max mem: 33369 +Epoch: [2] [1600/2639] eta: 0:50:12 lr: 4.70577056218803e-05 loss: 0.1567 (0.1636) time: 2.8976 data: 0.0074 max mem: 33369 +Epoch: [2] [1610/2639] eta: 0:49:43 lr: 4.7053413797754307e-05 loss: 0.1736 (0.1638) time: 2.9061 data: 0.0078 max mem: 33369 +Epoch: [2] [1620/2639] eta: 0:49:13 lr: 4.704912193013177e-05 loss: 0.1771 (0.1639) time: 2.8623 data: 0.0078 max mem: 33369 +Epoch: [2] [1630/2639] eta: 0:48:45 lr: 4.704483001900787e-05 loss: 0.1495 (0.1638) time: 2.8587 data: 0.0076 max mem: 33369 +Epoch: [2] [1640/2639] eta: 0:48:16 lr: 4.704053806437773e-05 loss: 0.1381 (0.1637) time: 2.9282 data: 0.0078 max mem: 33369 +Epoch: [2] [1650/2639] eta: 0:47:46 lr: 4.703624606623652e-05 loss: 0.1405 (0.1637) time: 2.8826 data: 0.0076 max mem: 33369 +Epoch: [2] [1660/2639] eta: 0:47:18 lr: 4.703195402457938e-05 loss: 0.1538 (0.1637) time: 2.8984 data: 0.0074 max mem: 33369 +Epoch: [2] [1670/2639] eta: 0:46:49 lr: 4.702766193940145e-05 loss: 0.1573 (0.1637) time: 2.9863 data: 0.0077 max mem: 33369 +Epoch: [2] [1680/2639] eta: 0:46:21 lr: 4.702336981069787e-05 loss: 0.1446 (0.1635) time: 2.9566 data: 0.0082 max mem: 33369 +Epoch: [2] [1690/2639] eta: 0:45:51 lr: 4.701907763846381e-05 loss: 0.1587 (0.1636) time: 2.9001 data: 0.0083 max mem: 33369 +Epoch: [2] [1700/2639] eta: 0:45:22 lr: 4.7014785422694386e-05 loss: 0.1316 (0.1633) time: 2.8913 data: 0.0078 max mem: 33369 +Epoch: [2] [1710/2639] eta: 0:44:53 lr: 4.7010493163384755e-05 loss: 0.1296 (0.1633) time: 2.9038 data: 0.0073 max mem: 33369 +Epoch: [2] [1720/2639] eta: 0:44:25 lr: 4.700620086053005e-05 loss: 0.1513 (0.1633) time: 2.9111 data: 0.0072 max mem: 33369 +Epoch: [2] [1730/2639] eta: 0:43:56 lr: 4.700190851412542e-05 loss: 0.1643 (0.1634) time: 2.9211 data: 0.0072 max mem: 33369 +Epoch: [2] [1740/2639] eta: 0:43:27 lr: 4.699761612416599e-05 loss: 0.1621 (0.1635) time: 2.9580 data: 0.0076 max mem: 33369 +Epoch: [2] [1750/2639] eta: 0:42:58 lr: 4.699332369064692e-05 loss: 0.1643 (0.1636) time: 2.9746 data: 0.0079 max mem: 33369 +Epoch: [2] [1760/2639] eta: 0:42:30 lr: 4.698903121356333e-05 loss: 0.1924 (0.1638) time: 2.9379 data: 0.0079 max mem: 33369 +Epoch: [2] [1770/2639] eta: 0:42:01 lr: 4.698473869291036e-05 loss: 0.1560 (0.1637) time: 2.9236 data: 0.0076 max mem: 33369 +Epoch: [2] [1780/2639] eta: 0:41:31 lr: 4.6980446128683144e-05 loss: 0.1398 (0.1636) time: 2.8714 data: 0.0073 max mem: 33369 +Epoch: [2] [1790/2639] eta: 0:41:02 lr: 4.6976153520876816e-05 loss: 0.1389 (0.1635) time: 2.8490 data: 0.0073 max mem: 33369 +Epoch: [2] [1800/2639] eta: 0:40:33 lr: 4.6971860869486504e-05 loss: 0.1400 (0.1634) time: 2.8416 data: 0.0073 max mem: 33369 +Epoch: [2] [1810/2639] eta: 0:40:04 lr: 4.696756817450736e-05 loss: 0.1450 (0.1635) time: 2.8583 data: 0.0073 max mem: 33369 +Epoch: [2] [1820/2639] eta: 0:39:35 lr: 4.696327543593449e-05 loss: 0.1433 (0.1634) time: 2.8855 data: 0.0073 max mem: 33369 +Epoch: [2] [1830/2639] eta: 0:39:06 lr: 4.695898265376304e-05 loss: 0.1414 (0.1634) time: 2.8752 data: 0.0076 max mem: 33369 +Epoch: [2] [1840/2639] eta: 0:38:36 lr: 4.6954689827988126e-05 loss: 0.1461 (0.1634) time: 2.8855 data: 0.0076 max mem: 33369 +Epoch: [2] [1850/2639] eta: 0:38:07 lr: 4.6950396958604885e-05 loss: 0.1513 (0.1634) time: 2.8711 data: 0.0072 max mem: 33369 +Epoch: [2] [1860/2639] eta: 0:37:38 lr: 4.6946104045608433e-05 loss: 0.1549 (0.1634) time: 2.8879 data: 0.0073 max mem: 33369 +Epoch: [2] [1870/2639] eta: 0:37:09 lr: 4.694181108899392e-05 loss: 0.1479 (0.1633) time: 2.8825 data: 0.0077 max mem: 33369 +Epoch: [2] [1880/2639] eta: 0:36:40 lr: 4.693751808875644e-05 loss: 0.1557 (0.1635) time: 2.8966 data: 0.0075 max mem: 33369 +Epoch: [2] [1890/2639] eta: 0:36:12 lr: 4.6933225044891135e-05 loss: 0.1486 (0.1635) time: 2.9427 data: 0.0072 max mem: 33369 +Epoch: [2] [1900/2639] eta: 0:35:42 lr: 4.692893195739312e-05 loss: 0.1460 (0.1636) time: 2.8918 data: 0.0072 max mem: 33369 +Epoch: [2] [1910/2639] eta: 0:35:13 lr: 4.692463882625753e-05 loss: 0.1460 (0.1635) time: 2.8543 data: 0.0075 max mem: 33369 +Epoch: [2] [1920/2639] eta: 0:34:44 lr: 4.692034565147946e-05 loss: 0.1565 (0.1637) time: 2.8965 data: 0.0077 max mem: 33369 +Epoch: [2] [1930/2639] eta: 0:34:15 lr: 4.6916052433054056e-05 loss: 0.1668 (0.1636) time: 2.8876 data: 0.0078 max mem: 33369 +Epoch: [2] [1940/2639] eta: 0:33:46 lr: 4.691175917097642e-05 loss: 0.1356 (0.1635) time: 2.8799 data: 0.0076 max mem: 33369 +Epoch: [2] [1950/2639] eta: 0:33:17 lr: 4.690746586524167e-05 loss: 0.1390 (0.1634) time: 2.9483 data: 0.0077 max mem: 33369 +Epoch: [2] [1960/2639] eta: 0:32:49 lr: 4.6903172515844934e-05 loss: 0.1469 (0.1634) time: 2.9892 data: 0.0078 max mem: 33369 +Epoch: [2] [1970/2639] eta: 0:32:20 lr: 4.689887912278131e-05 loss: 0.1216 (0.1633) time: 2.9343 data: 0.0074 max mem: 33369 +Epoch: [2] [1980/2639] eta: 0:31:51 lr: 4.689458568604593e-05 loss: 0.1461 (0.1633) time: 2.9226 data: 0.0074 max mem: 33369 +Epoch: [2] [1990/2639] eta: 0:31:22 lr: 4.689029220563388e-05 loss: 0.1645 (0.1635) time: 2.9114 data: 0.0071 max mem: 33369 +Epoch: [2] [2000/2639] eta: 0:30:53 lr: 4.688599868154031e-05 loss: 0.1645 (0.1636) time: 2.8842 data: 0.0074 max mem: 33369 +Epoch: [2] [2010/2639] eta: 0:30:24 lr: 4.68817051137603e-05 loss: 0.1498 (0.1635) time: 2.8985 data: 0.0077 max mem: 33369 +Epoch: [2] [2020/2639] eta: 0:29:55 lr: 4.6877411502288975e-05 loss: 0.1498 (0.1635) time: 2.8887 data: 0.0075 max mem: 33369 +Epoch: [2] [2030/2639] eta: 0:29:26 lr: 4.6873117847121435e-05 loss: 0.1457 (0.1635) time: 2.9028 data: 0.0076 max mem: 33369 +Epoch: [2] [2040/2639] eta: 0:28:57 lr: 4.68688241482528e-05 loss: 0.1451 (0.1635) time: 2.9066 data: 0.0075 max mem: 33369 +Epoch: [2] [2050/2639] eta: 0:28:28 lr: 4.686453040567816e-05 loss: 0.1489 (0.1634) time: 2.8630 data: 0.0073 max mem: 33369 +Epoch: [2] [2060/2639] eta: 0:27:58 lr: 4.686023661939264e-05 loss: 0.1501 (0.1634) time: 2.8546 data: 0.0071 max mem: 33369 +Epoch: [2] [2070/2639] eta: 0:27:29 lr: 4.685594278939132e-05 loss: 0.1452 (0.1633) time: 2.8619 data: 0.0071 max mem: 33369 +Epoch: [2] [2080/2639] eta: 0:27:00 lr: 4.685164891566933e-05 loss: 0.1357 (0.1631) time: 2.8458 data: 0.0073 max mem: 33369 +Epoch: [2] [2090/2639] eta: 0:26:31 lr: 4.684735499822176e-05 loss: 0.1316 (0.1630) time: 2.8915 data: 0.0073 max mem: 33369 +Epoch: [2] [2100/2639] eta: 0:26:02 lr: 4.684306103704371e-05 loss: 0.1487 (0.1630) time: 2.9199 data: 0.0073 max mem: 33369 +Epoch: [2] [2110/2639] eta: 0:25:33 lr: 4.683876703213028e-05 loss: 0.1344 (0.1629) time: 2.8954 data: 0.0073 max mem: 33369 +Epoch: [2] [2120/2639] eta: 0:25:04 lr: 4.683447298347658e-05 loss: 0.1330 (0.1628) time: 2.9114 data: 0.0071 max mem: 33369 +Epoch: [2] [2130/2639] eta: 0:24:35 lr: 4.6830178891077696e-05 loss: 0.1435 (0.1627) time: 2.8897 data: 0.0074 max mem: 33369 +Epoch: [2] [2140/2639] eta: 0:24:06 lr: 4.682588475492873e-05 loss: 0.1441 (0.1627) time: 2.8894 data: 0.0076 max mem: 33369 +Epoch: [2] [2150/2639] eta: 0:23:37 lr: 4.682159057502478e-05 loss: 0.1408 (0.1627) time: 2.8949 data: 0.0074 max mem: 33369 +Epoch: [2] [2160/2639] eta: 0:23:08 lr: 4.681729635136095e-05 loss: 0.1408 (0.1627) time: 2.8887 data: 0.0075 max mem: 33369 +Epoch: [2] [2170/2639] eta: 0:22:39 lr: 4.6813002083932304e-05 loss: 0.1709 (0.1628) time: 2.8776 data: 0.0076 max mem: 33369 +Epoch: [2] [2180/2639] eta: 0:22:10 lr: 4.680870777273396e-05 loss: 0.1709 (0.1627) time: 2.8468 data: 0.0076 max mem: 33369 +Epoch: [2] [2190/2639] eta: 0:21:41 lr: 4.680441341776102e-05 loss: 0.1405 (0.1627) time: 2.8838 data: 0.0076 max mem: 33369 +Epoch: [2] [2200/2639] eta: 0:21:12 lr: 4.680011901900854e-05 loss: 0.1536 (0.1628) time: 2.9010 data: 0.0075 max mem: 33369 +Epoch: [2] [2210/2639] eta: 0:20:43 lr: 4.6795824576471646e-05 loss: 0.1577 (0.1628) time: 2.8811 data: 0.0076 max mem: 33369 +Epoch: [2] [2220/2639] eta: 0:20:14 lr: 4.67915300901454e-05 loss: 0.1577 (0.1628) time: 2.9166 data: 0.0078 max mem: 33369 +Epoch: [2] [2230/2639] eta: 0:19:45 lr: 4.6787235560024914e-05 loss: 0.1582 (0.1628) time: 2.9323 data: 0.0077 max mem: 33369 +Epoch: [2] [2240/2639] eta: 0:19:16 lr: 4.678294098610525e-05 loss: 0.1424 (0.1627) time: 2.9283 data: 0.0076 max mem: 33369 +Epoch: [2] [2250/2639] eta: 0:18:47 lr: 4.677864636838151e-05 loss: 0.1509 (0.1628) time: 2.9464 data: 0.0076 max mem: 33369 +Epoch: [2] [2260/2639] eta: 0:18:18 lr: 4.6774351706848774e-05 loss: 0.1821 (0.1629) time: 2.9119 data: 0.0078 max mem: 33369 +Epoch: [2] [2270/2639] eta: 0:17:49 lr: 4.677005700150213e-05 loss: 0.1770 (0.1630) time: 2.8901 data: 0.0076 max mem: 33369 +Epoch: [2] [2280/2639] eta: 0:17:20 lr: 4.676576225233665e-05 loss: 0.1582 (0.1629) time: 2.8911 data: 0.0079 max mem: 33369 +Epoch: [2] [2290/2639] eta: 0:16:51 lr: 4.676146745934743e-05 loss: 0.1439 (0.1630) time: 2.8799 data: 0.0083 max mem: 33369 +Epoch: [2] [2300/2639] eta: 0:16:22 lr: 4.675717262252954e-05 loss: 0.1402 (0.1629) time: 2.9006 data: 0.0078 max mem: 33369 +Epoch: [2] [2310/2639] eta: 0:15:53 lr: 4.675287774187806e-05 loss: 0.1310 (0.1629) time: 2.9290 data: 0.0076 max mem: 33369 +Epoch: [2] [2320/2639] eta: 0:15:24 lr: 4.674858281738807e-05 loss: 0.1310 (0.1629) time: 2.9121 data: 0.0078 max mem: 33369 +Epoch: [2] [2330/2639] eta: 0:14:55 lr: 4.6744287849054656e-05 loss: 0.1453 (0.1628) time: 2.9061 data: 0.0073 max mem: 33369 +Epoch: [2] [2340/2639] eta: 0:14:26 lr: 4.6739992836872876e-05 loss: 0.1453 (0.1628) time: 2.9195 data: 0.0076 max mem: 33369 +Epoch: [2] [2350/2639] eta: 0:13:58 lr: 4.673569778083783e-05 loss: 0.1454 (0.1627) time: 2.9123 data: 0.0079 max mem: 33369 +Epoch: [2] [2360/2639] eta: 0:13:29 lr: 4.673140268094456e-05 loss: 0.1365 (0.1627) time: 2.9286 data: 0.0076 max mem: 33369 +Epoch: [2] [2370/2639] eta: 0:13:00 lr: 4.672710753718817e-05 loss: 0.1468 (0.1627) time: 2.9421 data: 0.0078 max mem: 33369 +Epoch: [2] [2380/2639] eta: 0:12:31 lr: 4.672281234956371e-05 loss: 0.1528 (0.1626) time: 2.9004 data: 0.0080 max mem: 33369 +Epoch: [2] [2390/2639] eta: 0:12:02 lr: 4.6718517118066266e-05 loss: 0.1528 (0.1627) time: 2.8808 data: 0.0082 max mem: 33369 +Epoch: [2] [2400/2639] eta: 0:11:33 lr: 4.6714221842690905e-05 loss: 0.1549 (0.1627) time: 2.8782 data: 0.0080 max mem: 33369 +Epoch: [2] [2410/2639] eta: 0:11:04 lr: 4.670992652343269e-05 loss: 0.1474 (0.1626) time: 2.8899 data: 0.0077 max mem: 33369 +Epoch: [2] [2420/2639] eta: 0:10:35 lr: 4.6705631160286694e-05 loss: 0.1390 (0.1626) time: 2.9067 data: 0.0079 max mem: 33369 +Epoch: [2] [2430/2639] eta: 0:10:06 lr: 4.670133575324798e-05 loss: 0.1476 (0.1626) time: 2.8986 data: 0.0075 max mem: 33369 +Epoch: [2] [2440/2639] eta: 0:09:37 lr: 4.6697040302311615e-05 loss: 0.1685 (0.1627) time: 2.8783 data: 0.0074 max mem: 33369 +Epoch: [2] [2450/2639] eta: 0:09:08 lr: 4.669274480747266e-05 loss: 0.1579 (0.1626) time: 2.8880 data: 0.0075 max mem: 33369 +Epoch: [2] [2460/2639] eta: 0:08:39 lr: 4.668844926872619e-05 loss: 0.1598 (0.1626) time: 2.9077 data: 0.0075 max mem: 33369 +Epoch: [2] [2470/2639] eta: 0:08:10 lr: 4.668415368606726e-05 loss: 0.1745 (0.1627) time: 2.8896 data: 0.0079 max mem: 33369 +Epoch: [2] [2480/2639] eta: 0:07:41 lr: 4.667985805949093e-05 loss: 0.1675 (0.1627) time: 2.8766 data: 0.0078 max mem: 33369 +Epoch: [2] [2490/2639] eta: 0:07:12 lr: 4.667556238899226e-05 loss: 0.1403 (0.1626) time: 2.8726 data: 0.0074 max mem: 33369 +Epoch: [2] [2500/2639] eta: 0:06:43 lr: 4.6671266674566314e-05 loss: 0.1284 (0.1625) time: 2.8982 data: 0.0080 max mem: 33369 +Epoch: [2] [2510/2639] eta: 0:06:14 lr: 4.6666970916208146e-05 loss: 0.1452 (0.1626) time: 2.8816 data: 0.0081 max mem: 33369 +Epoch: [2] [2520/2639] eta: 0:05:45 lr: 4.666267511391282e-05 loss: 0.1425 (0.1626) time: 2.8792 data: 0.0074 max mem: 33369 +Epoch: [2] [2530/2639] eta: 0:05:16 lr: 4.6658379267675384e-05 loss: 0.1319 (0.1625) time: 2.8948 data: 0.0074 max mem: 33369 +Epoch: [2] [2540/2639] eta: 0:04:47 lr: 4.66540833774909e-05 loss: 0.1334 (0.1625) time: 2.8988 data: 0.0076 max mem: 33369 +Epoch: [2] [2550/2639] eta: 0:04:18 lr: 4.664978744335441e-05 loss: 0.1616 (0.1625) time: 2.9119 data: 0.0078 max mem: 33369 +Epoch: [2] [2560/2639] eta: 0:03:49 lr: 4.664549146526099e-05 loss: 0.1565 (0.1625) time: 2.8949 data: 0.0079 max mem: 33369 +Epoch: [2] [2570/2639] eta: 0:03:20 lr: 4.664119544320566e-05 loss: 0.1650 (0.1626) time: 2.9071 data: 0.0077 max mem: 33369 +Epoch: [2] [2580/2639] eta: 0:02:51 lr: 4.6636899377183505e-05 loss: 0.1527 (0.1625) time: 2.9002 data: 0.0077 max mem: 33369 +Epoch: [2] [2590/2639] eta: 0:02:22 lr: 4.663260326718955e-05 loss: 0.1520 (0.1625) time: 2.9129 data: 0.0081 max mem: 33369 +Epoch: [2] [2600/2639] eta: 0:01:53 lr: 4.662830711321886e-05 loss: 0.1572 (0.1626) time: 2.9233 data: 0.0079 max mem: 33369 +Epoch: [2] [2610/2639] eta: 0:01:24 lr: 4.6624010915266466e-05 loss: 0.1383 (0.1625) time: 2.9170 data: 0.0077 max mem: 33369 +Epoch: [2] [2620/2639] eta: 0:00:55 lr: 4.6619714673327424e-05 loss: 0.1587 (0.1626) time: 2.9419 data: 0.0077 max mem: 33369 +Epoch: [2] [2630/2639] eta: 0:00:26 lr: 4.6615418387396776e-05 loss: 0.1721 (0.1627) time: 2.9319 data: 0.0072 max mem: 33369 +Epoch: [2] Total time: 2:07:33 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 3:33:13 time: 4.9721 data: 4.8795 max mem: 33369 +Test: [ 100/2573] eta: 0:05:11 time: 0.0777 data: 0.0015 max mem: 33369 +Test: [ 200/2573] eta: 0:04:03 time: 0.0776 data: 0.0015 max mem: 33369 +Test: [ 300/2573] eta: 0:03:34 time: 0.0805 data: 0.0014 max mem: 33369 +Test: [ 400/2573] eta: 0:03:16 time: 0.0807 data: 0.0014 max mem: 33369 +Test: [ 500/2573] eta: 0:03:02 time: 0.0784 data: 0.0013 max mem: 33369 +Test: [ 600/2573] eta: 0:02:50 time: 0.0797 data: 0.0014 max mem: 33369 +Test: [ 700/2573] eta: 0:02:40 time: 0.0793 data: 0.0014 max mem: 33369 +Test: [ 800/2573] eta: 0:02:31 time: 0.0822 data: 0.0014 max mem: 33369 +Test: [ 900/2573] eta: 0:02:21 time: 0.0787 data: 0.0014 max mem: 33369 +Test: [1000/2573] eta: 0:02:12 time: 0.0800 data: 0.0014 max mem: 33369 +Test: [1100/2573] eta: 0:02:03 time: 0.0801 data: 0.0014 max mem: 33369 +Test: [1200/2573] eta: 0:01:54 time: 0.0795 data: 0.0015 max mem: 33369 +Test: [1300/2573] eta: 0:01:46 time: 0.0804 data: 0.0014 max mem: 33369 +Test: [1400/2573] eta: 0:01:37 time: 0.0787 data: 0.0014 max mem: 33369 +Test: [1500/2573] eta: 0:01:28 time: 0.0799 data: 0.0015 max mem: 33369 +Test: [1600/2573] eta: 0:01:20 time: 0.0829 data: 0.0014 max mem: 33369 +Test: [1700/2573] eta: 0:01:12 time: 0.0791 data: 0.0014 max mem: 33369 +Test: [1800/2573] eta: 0:01:03 time: 0.0816 data: 0.0014 max mem: 33369 +Test: [1900/2573] eta: 0:00:55 time: 0.0789 data: 0.0015 max mem: 33369 +Test: [2000/2573] eta: 0:00:47 time: 0.0804 data: 0.0014 max mem: 33369 +Test: [2100/2573] eta: 0:00:38 time: 0.0825 data: 0.0015 max mem: 33369 +Test: [2200/2573] eta: 0:00:30 time: 0.0819 data: 0.0014 max mem: 33369 +Test: [2300/2573] eta: 0:00:22 time: 0.0818 data: 0.0015 max mem: 33369 +Test: [2400/2573] eta: 0:00:14 time: 0.0783 data: 0.0015 max mem: 33369 +Test: [2500/2573] eta: 0:00:05 time: 0.0805 data: 0.0014 max mem: 33369 +Test: Total time: 0:03:31 +Final results: +Mean IoU is 47.32 + + precision@0.5 = 50.51 + precision@0.6 = 42.34 + precision@0.7 = 32.84 + precision@0.8 = 21.51 + precision@0.9 = 7.43 + overall IoU = 48.67 + +Average object IoU 47.3214674615884 +Overall IoU 48.666629791259766 +Better epoch: 2 + +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [3] [ 0/2639] eta: 4:01:13 lr: 4.6611551692442284e-05 loss: 0.1006 (0.1006) time: 5.4846 data: 2.3712 max mem: 33369 +Epoch: [3] [ 10/2639] eta: 2:15:38 lr: 4.660725532291394e-05 loss: 0.1153 (0.1340) time: 3.0957 data: 0.2237 max mem: 33369 +Epoch: [3] [ 20/2639] eta: 2:10:33 lr: 4.660295890937962e-05 loss: 0.1368 (0.1346) time: 2.8662 data: 0.0082 max mem: 33369 +Epoch: [3] [ 30/2639] eta: 2:08:48 lr: 4.6598662451834365e-05 loss: 0.1184 (0.1331) time: 2.8888 data: 0.0075 max mem: 33369 +Epoch: [3] [ 40/2639] eta: 2:08:06 lr: 4.659436595027322e-05 loss: 0.1422 (0.1357) time: 2.9225 data: 0.0077 max mem: 33369 +Epoch: [3] [ 50/2639] eta: 2:07:01 lr: 4.659006940469121e-05 loss: 0.1422 (0.1389) time: 2.9148 data: 0.0076 max mem: 33369 +Epoch: [3] [ 60/2639] eta: 2:05:37 lr: 4.658577281508339e-05 loss: 0.1124 (0.1384) time: 2.8516 data: 0.0079 max mem: 33369 +Epoch: [3] [ 70/2639] eta: 2:04:53 lr: 4.658147618144478e-05 loss: 0.1260 (0.1393) time: 2.8490 data: 0.0080 max mem: 33369 +Epoch: [3] [ 80/2639] eta: 2:04:22 lr: 4.6577179503770434e-05 loss: 0.1368 (0.1417) time: 2.8958 data: 0.0077 max mem: 33369 +Epoch: [3] [ 90/2639] eta: 2:03:48 lr: 4.657288278205537e-05 loss: 0.1500 (0.1418) time: 2.9044 data: 0.0078 max mem: 33369 +Epoch: [3] [ 100/2639] eta: 2:03:05 lr: 4.656858601629464e-05 loss: 0.1267 (0.1416) time: 2.8798 data: 0.0080 max mem: 33369 +Epoch: [3] [ 110/2639] eta: 2:02:29 lr: 4.656428920648326e-05 loss: 0.1381 (0.1423) time: 2.8682 data: 0.0081 max mem: 33369 +Epoch: [3] [ 120/2639] eta: 2:01:41 lr: 4.655999235261628e-05 loss: 0.1287 (0.1417) time: 2.8455 data: 0.0081 max mem: 33369 +Epoch: [3] [ 130/2639] eta: 2:01:22 lr: 4.655569545468871e-05 loss: 0.1387 (0.1431) time: 2.8848 data: 0.0084 max mem: 33369 +Epoch: [3] [ 140/2639] eta: 2:01:04 lr: 4.6551398512695596e-05 loss: 0.1435 (0.1429) time: 2.9579 data: 0.0082 max mem: 33369 +Epoch: [3] [ 150/2639] eta: 2:00:30 lr: 4.654710152663195e-05 loss: 0.1362 (0.1419) time: 2.9196 data: 0.0078 max mem: 33369 +Epoch: [3] [ 160/2639] eta: 2:00:14 lr: 4.6542804496492816e-05 loss: 0.1438 (0.1423) time: 2.9342 data: 0.0079 max mem: 33369 +Epoch: [3] [ 170/2639] eta: 1:59:54 lr: 4.6538507422273206e-05 loss: 0.1419 (0.1425) time: 2.9811 data: 0.0080 max mem: 33369 +Epoch: [3] [ 180/2639] eta: 1:59:28 lr: 4.653421030396817e-05 loss: 0.1339 (0.1437) time: 2.9552 data: 0.0083 max mem: 33369 +Epoch: [3] [ 190/2639] eta: 1:59:03 lr: 4.65299131415727e-05 loss: 0.1336 (0.1451) time: 2.9434 data: 0.0085 max mem: 33369 +Epoch: [3] [ 200/2639] eta: 1:58:35 lr: 4.652561593508185e-05 loss: 0.1370 (0.1449) time: 2.9368 data: 0.0079 max mem: 33369 +Epoch: [3] [ 210/2639] eta: 1:58:10 lr: 4.652131868449061e-05 loss: 0.1371 (0.1452) time: 2.9398 data: 0.0076 max mem: 33369 +Epoch: [3] [ 220/2639] eta: 1:57:44 lr: 4.651702138979403e-05 loss: 0.1225 (0.1446) time: 2.9488 data: 0.0076 max mem: 33369 +Epoch: [3] [ 230/2639] eta: 1:57:11 lr: 4.651272405098711e-05 loss: 0.1283 (0.1446) time: 2.9169 data: 0.0073 max mem: 33369 +Epoch: [3] [ 240/2639] eta: 1:56:40 lr: 4.6508426668064875e-05 loss: 0.1403 (0.1447) time: 2.8954 data: 0.0074 max mem: 33369 +Epoch: [3] [ 250/2639] eta: 1:56:03 lr: 4.650412924102235e-05 loss: 0.1372 (0.1445) time: 2.8687 data: 0.0076 max mem: 33369 +Epoch: [3] [ 260/2639] eta: 1:55:26 lr: 4.6499831769854554e-05 loss: 0.1372 (0.1443) time: 2.8328 data: 0.0077 max mem: 33369 +Epoch: [3] [ 270/2639] eta: 1:54:53 lr: 4.649553425455649e-05 loss: 0.1461 (0.1444) time: 2.8450 data: 0.0077 max mem: 33369 +Epoch: [3] [ 280/2639] eta: 1:54:24 lr: 4.649123669512317e-05 loss: 0.1431 (0.1444) time: 2.8873 data: 0.0077 max mem: 33369 +Epoch: [3] [ 290/2639] eta: 1:53:55 lr: 4.648693909154962e-05 loss: 0.1328 (0.1449) time: 2.9110 data: 0.0079 max mem: 33369 +Epoch: [3] [ 300/2639] eta: 1:53:29 lr: 4.648264144383086e-05 loss: 0.1208 (0.1448) time: 2.9286 data: 0.0079 max mem: 33369 +Epoch: [3] [ 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+Epoch: [3] [ 390/2639] eta: 1:49:01 lr: 4.644396062700346e-05 loss: 0.1370 (0.1441) time: 2.8864 data: 0.0080 max mem: 33369 +Epoch: [3] [ 400/2639] eta: 1:48:28 lr: 4.643966253755792e-05 loss: 0.1426 (0.1443) time: 2.8710 data: 0.0079 max mem: 33369 +Epoch: [3] [ 410/2639] eta: 1:47:56 lr: 4.643536440391222e-05 loss: 0.1576 (0.1453) time: 2.8508 data: 0.0080 max mem: 33369 +Epoch: [3] [ 420/2639] eta: 1:47:25 lr: 4.643106622606137e-05 loss: 0.1496 (0.1452) time: 2.8569 data: 0.0080 max mem: 33369 +Epoch: [3] [ 430/2639] eta: 1:46:56 lr: 4.642676800400036e-05 loss: 0.1409 (0.1457) time: 2.8830 data: 0.0079 max mem: 33369 +Epoch: [3] [ 440/2639] eta: 1:46:27 lr: 4.6422469737724186e-05 loss: 0.1336 (0.1457) time: 2.9052 data: 0.0076 max mem: 33369 +Epoch: [3] [ 450/2639] eta: 1:45:53 lr: 4.641817142722785e-05 loss: 0.1212 (0.1452) time: 2.8617 data: 0.0078 max mem: 33369 +Epoch: [3] [ 460/2639] eta: 1:45:27 lr: 4.6413873072506345e-05 loss: 0.1212 (0.1449) time: 2.8873 data: 0.0087 max mem: 33369 +Epoch: [3] [ 470/2639] eta: 1:44:56 lr: 4.6409574673554676e-05 loss: 0.1223 (0.1448) time: 2.9093 data: 0.0084 max mem: 33369 +Epoch: [3] [ 480/2639] eta: 1:44:27 lr: 4.6405276230367803e-05 loss: 0.1373 (0.1447) time: 2.8818 data: 0.0081 max mem: 33369 +Epoch: [3] [ 490/2639] eta: 1:43:57 lr: 4.640097774294075e-05 loss: 0.1318 (0.1446) time: 2.8882 data: 0.0080 max mem: 33369 +Epoch: [3] [ 500/2639] eta: 1:43:29 lr: 4.639667921126851e-05 loss: 0.1318 (0.1445) time: 2.9100 data: 0.0074 max mem: 33369 +Epoch: [3] [ 510/2639] eta: 1:42:59 lr: 4.639238063534605e-05 loss: 0.1254 (0.1447) time: 2.9060 data: 0.0073 max mem: 33369 +Epoch: [3] [ 520/2639] eta: 1:42:30 lr: 4.638808201516837e-05 loss: 0.1312 (0.1448) time: 2.8903 data: 0.0073 max mem: 33369 +Epoch: [3] [ 530/2639] eta: 1:42:00 lr: 4.638378335073046e-05 loss: 0.1357 (0.1450) time: 2.8884 data: 0.0078 max mem: 33369 +Epoch: [3] [ 540/2639] eta: 1:41:32 lr: 4.6379484642027306e-05 loss: 0.1570 (0.1451) time: 2.8977 data: 0.0079 max mem: 33369 +Epoch: [3] [ 550/2639] eta: 1:41:04 lr: 4.637518588905389e-05 loss: 0.1379 (0.1449) time: 2.9315 data: 0.0075 max mem: 33369 +Epoch: [3] [ 560/2639] eta: 1:40:38 lr: 4.6370887091805196e-05 loss: 0.1232 (0.1451) time: 2.9563 data: 0.0081 max mem: 33369 +Epoch: [3] [ 570/2639] eta: 1:40:09 lr: 4.63665882502762e-05 loss: 0.1682 (0.1455) time: 2.9392 data: 0.0082 max mem: 33369 +Epoch: [3] [ 580/2639] eta: 1:39:40 lr: 4.636228936446191e-05 loss: 0.1665 (0.1457) time: 2.9040 data: 0.0079 max mem: 33369 +Epoch: [3] [ 590/2639] eta: 1:39:12 lr: 4.635799043435728e-05 loss: 0.1342 (0.1455) time: 2.9274 data: 0.0081 max mem: 33369 +Epoch: [3] [ 600/2639] eta: 1:38:41 lr: 4.635369145995731e-05 loss: 0.1290 (0.1454) time: 2.8962 data: 0.0081 max mem: 33369 +Epoch: [3] [ 610/2639] eta: 1:38:12 lr: 4.634939244125695e-05 loss: 0.1378 (0.1455) time: 2.8808 data: 0.0080 max mem: 33369 +Epoch: [3] [ 620/2639] eta: 1:37:45 lr: 4.6345093378251215e-05 loss: 0.1414 (0.1454) time: 2.9355 data: 0.0076 max mem: 33369 +Epoch: [3] [ 630/2639] eta: 1:37:15 lr: 4.6340794270935054e-05 loss: 0.1414 (0.1458) time: 2.9089 data: 0.0080 max mem: 33369 +Epoch: [3] [ 640/2639] eta: 1:36:46 lr: 4.6336495119303465e-05 loss: 0.1572 (0.1459) time: 2.8949 data: 0.0079 max mem: 33369 +Epoch: [3] [ 650/2639] eta: 1:36:16 lr: 4.63321959233514e-05 loss: 0.1326 (0.1459) time: 2.9023 data: 0.0075 max mem: 33369 +Epoch: [3] [ 660/2639] eta: 1:35:46 lr: 4.632789668307385e-05 loss: 0.1297 (0.1459) time: 2.8727 data: 0.0075 max mem: 33369 +Epoch: [3] [ 670/2639] eta: 1:35:18 lr: 4.6323597398465776e-05 loss: 0.1328 (0.1463) time: 2.8927 data: 0.0077 max mem: 33369 +Epoch: [3] [ 680/2639] eta: 1:34:48 lr: 4.631929806952216e-05 loss: 0.1399 (0.1462) time: 2.8932 data: 0.0076 max mem: 33369 +Epoch: [3] [ 690/2639] eta: 1:34:17 lr: 4.631499869623795e-05 loss: 0.1399 (0.1463) time: 2.8593 data: 0.0074 max mem: 33369 +Epoch: [3] [ 700/2639] eta: 1:33:47 lr: 4.6310699278608145e-05 loss: 0.1406 (0.1463) time: 2.8542 data: 0.0074 max mem: 33369 +Epoch: [3] [ 710/2639] eta: 1:33:17 lr: 4.6306399816627695e-05 loss: 0.1406 (0.1466) time: 2.8684 data: 0.0078 max mem: 33369 +Epoch: [3] [ 720/2639] eta: 1:32:49 lr: 4.630210031029157e-05 loss: 0.1566 (0.1467) time: 2.9033 data: 0.0079 max mem: 33369 +Epoch: [3] [ 730/2639] eta: 1:32:17 lr: 4.629780075959474e-05 loss: 0.1452 (0.1465) time: 2.8667 data: 0.0075 max mem: 33369 +Epoch: [3] [ 740/2639] eta: 1:31:48 lr: 4.629350116453217e-05 loss: 0.1357 (0.1465) time: 2.8475 data: 0.0077 max mem: 33369 +Epoch: [3] [ 750/2639] eta: 1:31:19 lr: 4.628920152509881e-05 loss: 0.1399 (0.1465) time: 2.8942 data: 0.0074 max mem: 33369 +Epoch: [3] [ 760/2639] eta: 1:30:49 lr: 4.628490184128965e-05 loss: 0.1476 (0.1466) time: 2.8822 data: 0.0077 max mem: 33369 +Epoch: [3] [ 770/2639] eta: 1:30:20 lr: 4.628060211309962e-05 loss: 0.1467 (0.1466) time: 2.8802 data: 0.0078 max mem: 33369 +Epoch: [3] [ 780/2639] eta: 1:29:49 lr: 4.62763023405237e-05 loss: 0.1467 (0.1465) time: 2.8691 data: 0.0077 max mem: 33369 +Epoch: [3] [ 790/2639] eta: 1:29:20 lr: 4.6272002523556844e-05 loss: 0.1331 (0.1465) time: 2.8601 data: 0.0076 max mem: 33369 +Epoch: [3] [ 800/2639] eta: 1:28:49 lr: 4.626770266219401e-05 loss: 0.1382 (0.1467) time: 2.8497 data: 0.0074 max mem: 33369 +Epoch: [3] [ 810/2639] eta: 1:28:20 lr: 4.626340275643016e-05 loss: 0.1382 (0.1465) time: 2.8589 data: 0.0073 max mem: 33369 +Epoch: [3] [ 820/2639] eta: 1:27:51 lr: 4.625910280626025e-05 loss: 0.1287 (0.1463) time: 2.8927 data: 0.0073 max mem: 33369 +Epoch: [3] [ 830/2639] eta: 1:27:22 lr: 4.6254802811679224e-05 loss: 0.1287 (0.1463) time: 2.8844 data: 0.0073 max mem: 33369 +Epoch: [3] [ 840/2639] eta: 1:26:52 lr: 4.625050277268204e-05 loss: 0.1357 (0.1461) time: 2.8758 data: 0.0073 max mem: 33369 +Epoch: [3] [ 850/2639] eta: 1:26:22 lr: 4.6246202689263665e-05 loss: 0.1125 (0.1458) time: 2.8554 data: 0.0072 max mem: 33369 +Epoch: [3] [ 860/2639] eta: 1:25:53 lr: 4.624190256141903e-05 loss: 0.1280 (0.1459) time: 2.8607 data: 0.0073 max mem: 33369 +Epoch: [3] [ 870/2639] eta: 1:25:24 lr: 4.6237602389143095e-05 loss: 0.1365 (0.1460) time: 2.8952 data: 0.0073 max mem: 33369 +Epoch: [3] [ 880/2639] eta: 1:24:54 lr: 4.623330217243082e-05 loss: 0.1260 (0.1458) time: 2.8885 data: 0.0073 max mem: 33369 +Epoch: [3] [ 890/2639] eta: 1:24:25 lr: 4.6229001911277134e-05 loss: 0.1260 (0.1458) time: 2.8640 data: 0.0074 max mem: 33369 +Epoch: [3] [ 900/2639] eta: 1:23:54 lr: 4.622470160567699e-05 loss: 0.1445 (0.1459) time: 2.8440 data: 0.0076 max mem: 33369 +Epoch: [3] [ 910/2639] eta: 1:23:26 lr: 4.6220401255625346e-05 loss: 0.1525 (0.1462) time: 2.8706 data: 0.0074 max mem: 33369 +Epoch: [3] [ 920/2639] eta: 1:22:58 lr: 4.6216100861117126e-05 loss: 0.1447 (0.1462) time: 2.9389 data: 0.0073 max mem: 33369 +Epoch: [3] [ 930/2639] eta: 1:22:28 lr: 4.6211800422147306e-05 loss: 0.1183 (0.1461) time: 2.8894 data: 0.0074 max mem: 33369 +Epoch: [3] [ 940/2639] eta: 1:21:59 lr: 4.62074999387108e-05 loss: 0.1361 (0.1461) time: 2.8590 data: 0.0074 max mem: 33369 +Epoch: [3] [ 950/2639] eta: 1:21:29 lr: 4.620319941080256e-05 loss: 0.1364 (0.1459) time: 2.8827 data: 0.0072 max mem: 33369 +Epoch: [3] [ 960/2639] eta: 1:21:00 lr: 4.619889883841752e-05 loss: 0.1336 (0.1459) time: 2.8770 data: 0.0073 max mem: 33369 +Epoch: [3] [ 970/2639] eta: 1:20:30 lr: 4.619459822155063e-05 loss: 0.1296 (0.1457) time: 2.8619 data: 0.0075 max mem: 33369 +Epoch: [3] [ 980/2639] eta: 1:20:01 lr: 4.619029756019682e-05 loss: 0.1319 (0.1457) time: 2.8474 data: 0.0078 max mem: 33369 +Epoch: [3] [ 990/2639] eta: 1:19:31 lr: 4.618599685435104e-05 loss: 0.1343 (0.1458) time: 2.8657 data: 0.0078 max mem: 33369 +Epoch: [3] [1000/2639] eta: 1:19:03 lr: 4.6181696104008213e-05 loss: 0.1560 (0.1461) time: 2.9062 data: 0.0077 max mem: 33369 +Epoch: [3] [1010/2639] eta: 1:18:35 lr: 4.617739530916329e-05 loss: 0.1547 (0.1461) time: 2.9385 data: 0.0077 max mem: 33369 +Epoch: [3] [1020/2639] eta: 1:18:05 lr: 4.617309446981118e-05 loss: 0.1519 (0.1464) time: 2.8741 data: 0.0080 max mem: 33369 +Epoch: [3] [1030/2639] eta: 1:17:36 lr: 4.616879358594683e-05 loss: 0.1454 (0.1465) time: 2.8646 data: 0.0082 max mem: 33369 +Epoch: [3] [1040/2639] eta: 1:17:06 lr: 4.6164492657565175e-05 loss: 0.1353 (0.1466) time: 2.8591 data: 0.0078 max mem: 33369 +Epoch: [3] [1050/2639] eta: 1:16:37 lr: 4.616019168466115e-05 loss: 0.1353 (0.1466) time: 2.8444 data: 0.0080 max mem: 33369 +Epoch: [3] [1060/2639] eta: 1:16:08 lr: 4.6155890667229674e-05 loss: 0.1359 (0.1467) time: 2.8853 data: 0.0079 max mem: 33369 +Epoch: [3] [1070/2639] eta: 1:15:40 lr: 4.615158960526568e-05 loss: 0.1409 (0.1468) time: 2.9160 data: 0.0076 max mem: 33369 +Epoch: [3] [1080/2639] eta: 1:15:11 lr: 4.6147288498764094e-05 loss: 0.1409 (0.1470) time: 2.9377 data: 0.0076 max mem: 33369 +Epoch: [3] [1090/2639] eta: 1:14:43 lr: 4.614298734771984e-05 loss: 0.1339 (0.1468) time: 2.9379 data: 0.0074 max mem: 33369 +Epoch: [3] [1100/2639] eta: 1:14:13 lr: 4.613868615212785e-05 loss: 0.1318 (0.1470) time: 2.8993 data: 0.0074 max mem: 33369 +Epoch: [3] [1110/2639] eta: 1:13:44 lr: 4.613438491198305e-05 loss: 0.1662 (0.1472) time: 2.8547 data: 0.0079 max mem: 33369 +Epoch: [3] [1120/2639] eta: 1:13:15 lr: 4.613008362728035e-05 loss: 0.1662 (0.1473) time: 2.8710 data: 0.0079 max mem: 33369 +Epoch: [3] [1130/2639] eta: 1:12:46 lr: 4.612578229801468e-05 loss: 0.1360 (0.1471) time: 2.8792 data: 0.0078 max mem: 33369 +Epoch: [3] [1140/2639] eta: 1:12:17 lr: 4.6121480924180966e-05 loss: 0.1360 (0.1473) time: 2.8765 data: 0.0075 max mem: 33369 +Epoch: [3] [1150/2639] eta: 1:11:49 lr: 4.611717950577412e-05 loss: 0.1451 (0.1474) time: 2.9287 data: 0.0074 max mem: 33369 +Epoch: [3] [1160/2639] eta: 1:11:20 lr: 4.6112878042789065e-05 loss: 0.1101 (0.1473) time: 2.9358 data: 0.0075 max mem: 33369 +Epoch: [3] [1170/2639] eta: 1:10:52 lr: 4.6108576535220714e-05 loss: 0.1394 (0.1473) time: 2.9216 data: 0.0076 max mem: 33369 +Epoch: [3] [1180/2639] eta: 1:10:24 lr: 4.6104274983063986e-05 loss: 0.1393 (0.1474) time: 2.9613 data: 0.0074 max mem: 33369 +Epoch: [3] [1190/2639] eta: 1:09:54 lr: 4.60999733863138e-05 loss: 0.1337 (0.1473) time: 2.9282 data: 0.0075 max mem: 33369 +Epoch: [3] [1200/2639] eta: 1:09:26 lr: 4.609567174496507e-05 loss: 0.1335 (0.1473) time: 2.8875 data: 0.0074 max mem: 33369 +Epoch: [3] [1210/2639] eta: 1:08:57 lr: 4.60913700590127e-05 loss: 0.1267 (0.1474) time: 2.8950 data: 0.0074 max mem: 33369 +Epoch: [3] [1220/2639] eta: 1:08:28 lr: 4.608706832845161e-05 loss: 0.1405 (0.1474) time: 2.8937 data: 0.0074 max mem: 33369 +Epoch: [3] [1230/2639] eta: 1:07:59 lr: 4.608276655327671e-05 loss: 0.1435 (0.1476) time: 2.8950 data: 0.0073 max mem: 33369 +Epoch: [3] [1240/2639] eta: 1:07:29 lr: 4.6078464733482906e-05 loss: 0.1435 (0.1476) time: 2.8857 data: 0.0074 max mem: 33369 +Epoch: [3] [1250/2639] eta: 1:07:00 lr: 4.607416286906511e-05 loss: 0.1459 (0.1476) time: 2.8818 data: 0.0074 max mem: 33369 +Epoch: [3] [1260/2639] eta: 1:06:32 lr: 4.606986096001823e-05 loss: 0.1493 (0.1477) time: 2.9049 data: 0.0076 max mem: 33369 +Epoch: [3] [1270/2639] eta: 1:06:03 lr: 4.606555900633718e-05 loss: 0.1488 (0.1478) time: 2.9051 data: 0.0077 max mem: 33369 +Epoch: [3] [1280/2639] eta: 1:05:34 lr: 4.606125700801684e-05 loss: 0.1488 (0.1478) time: 2.8781 data: 0.0074 max mem: 33369 +Epoch: [3] [1290/2639] eta: 1:05:05 lr: 4.6056954965052146e-05 loss: 0.1571 (0.1480) time: 2.8827 data: 0.0073 max mem: 33369 +Epoch: [3] [1300/2639] eta: 1:04:36 lr: 4.605265287743798e-05 loss: 0.1635 (0.1480) time: 2.9142 data: 0.0073 max mem: 33369 +Epoch: [3] [1310/2639] eta: 1:04:06 lr: 4.6048350745169254e-05 loss: 0.1678 (0.1483) time: 2.8789 data: 0.0073 max mem: 33369 +Epoch: [3] [1320/2639] eta: 1:03:37 lr: 4.604404856824086e-05 loss: 0.1523 (0.1483) time: 2.8395 data: 0.0072 max mem: 33369 +Epoch: [3] [1330/2639] eta: 1:03:08 lr: 4.603974634664771e-05 loss: 0.1284 (0.1483) time: 2.8557 data: 0.0075 max mem: 33369 +Epoch: [3] [1340/2639] eta: 1:02:39 lr: 4.603544408038469e-05 loss: 0.1284 (0.1483) time: 2.8736 data: 0.0079 max mem: 33369 +Epoch: [3] [1350/2639] eta: 1:02:10 lr: 4.6031141769446714e-05 loss: 0.1300 (0.1483) time: 2.8780 data: 0.0078 max mem: 33369 +Epoch: [3] [1360/2639] eta: 1:01:41 lr: 4.602683941382865e-05 loss: 0.1322 (0.1482) time: 2.8840 data: 0.0075 max mem: 33369 +Epoch: [3] [1370/2639] eta: 1:01:12 lr: 4.602253701352543e-05 loss: 0.1253 (0.1483) time: 2.8992 data: 0.0074 max mem: 33369 +Epoch: [3] [1380/2639] eta: 1:00:43 lr: 4.601823456853192e-05 loss: 0.1299 (0.1484) time: 2.9170 data: 0.0074 max mem: 33369 +Epoch: [3] [1390/2639] eta: 1:00:14 lr: 4.601393207884303e-05 loss: 0.1421 (0.1484) time: 2.9243 data: 0.0076 max mem: 33369 +Epoch: [3] [1400/2639] eta: 0:59:45 lr: 4.6009629544453636e-05 loss: 0.1550 (0.1484) time: 2.8982 data: 0.0079 max mem: 33369 +Epoch: [3] [1410/2639] eta: 0:59:17 lr: 4.600532696535864e-05 loss: 0.1550 (0.1484) time: 2.8964 data: 0.0078 max mem: 33369 +Epoch: [3] [1420/2639] eta: 0:58:47 lr: 4.600102434155293e-05 loss: 0.1369 (0.1484) time: 2.8750 data: 0.0077 max mem: 33369 +Epoch: [3] [1430/2639] eta: 0:58:18 lr: 4.5996721673031404e-05 loss: 0.1478 (0.1485) time: 2.8389 data: 0.0078 max mem: 33369 +Epoch: [3] [1440/2639] eta: 0:57:49 lr: 4.599241895978893e-05 loss: 0.1478 (0.1485) time: 2.8871 data: 0.0074 max mem: 33369 +Epoch: [3] [1450/2639] eta: 0:57:20 lr: 4.598811620182041e-05 loss: 0.1401 (0.1486) time: 2.9183 data: 0.0077 max mem: 33369 +Epoch: [3] [1460/2639] eta: 0:56:52 lr: 4.598381339912071e-05 loss: 0.1416 (0.1487) time: 2.9167 data: 0.0080 max mem: 33369 +Epoch: [3] [1470/2639] eta: 0:56:23 lr: 4.5979510551684745e-05 loss: 0.1392 (0.1487) time: 2.9191 data: 0.0076 max mem: 33369 +Epoch: [3] [1480/2639] eta: 0:55:54 lr: 4.597520765950737e-05 loss: 0.1284 (0.1487) time: 2.9104 data: 0.0075 max mem: 33369 +Epoch: [3] [1490/2639] eta: 0:55:25 lr: 4.597090472258348e-05 loss: 0.1497 (0.1488) time: 2.8742 data: 0.0075 max mem: 33369 +Epoch: [3] [1500/2639] eta: 0:54:56 lr: 4.596660174090796e-05 loss: 0.1398 (0.1486) time: 2.8964 data: 0.0074 max mem: 33369 +Epoch: [3] [1510/2639] eta: 0:54:27 lr: 4.596229871447568e-05 loss: 0.1184 (0.1487) time: 2.9264 data: 0.0080 max mem: 33369 +Epoch: [3] [1520/2639] eta: 0:53:58 lr: 4.5957995643281526e-05 loss: 0.1256 (0.1488) time: 2.8808 data: 0.0079 max mem: 33369 +Epoch: [3] [1530/2639] eta: 0:53:29 lr: 4.5953692527320366e-05 loss: 0.1256 (0.1486) time: 2.8762 data: 0.0073 max mem: 33369 +Epoch: [3] [1540/2639] eta: 0:53:00 lr: 4.5949389366587085e-05 loss: 0.1278 (0.1487) time: 2.8963 data: 0.0073 max mem: 33369 +Epoch: [3] [1550/2639] eta: 0:52:31 lr: 4.594508616107655e-05 loss: 0.1322 (0.1486) time: 2.8995 data: 0.0075 max mem: 33369 +Epoch: [3] [1560/2639] eta: 0:52:02 lr: 4.594078291078365e-05 loss: 0.1206 (0.1487) time: 2.8890 data: 0.0074 max mem: 33369 +Epoch: [3] [1570/2639] eta: 0:51:34 lr: 4.593647961570324e-05 loss: 0.1355 (0.1487) time: 2.9163 data: 0.0073 max mem: 33369 +Epoch: [3] [1580/2639] eta: 0:51:05 lr: 4.5932176275830216e-05 loss: 0.1409 (0.1489) time: 2.9173 data: 0.0073 max mem: 33369 +Epoch: [3] [1590/2639] eta: 0:50:36 lr: 4.592787289115942e-05 loss: 0.1578 (0.1490) time: 2.9220 data: 0.0070 max mem: 33369 +Epoch: [3] [1600/2639] eta: 0:50:07 lr: 4.5923569461685734e-05 loss: 0.1489 (0.1490) time: 2.9195 data: 0.0071 max mem: 33369 +Epoch: [3] [1610/2639] eta: 0:49:38 lr: 4.591926598740403e-05 loss: 0.1458 (0.1489) time: 2.8732 data: 0.0073 max mem: 33369 +Epoch: [3] [1620/2639] eta: 0:49:09 lr: 4.591496246830918e-05 loss: 0.1395 (0.1490) time: 2.9069 data: 0.0075 max mem: 33369 +Epoch: [3] [1630/2639] eta: 0:48:41 lr: 4.591065890439604e-05 loss: 0.1178 (0.1489) time: 2.9495 data: 0.0078 max mem: 33369 +Epoch: [3] [1640/2639] eta: 0:48:12 lr: 4.5906355295659474e-05 loss: 0.1180 (0.1488) time: 2.9121 data: 0.0076 max mem: 33369 +Epoch: [3] [1650/2639] eta: 0:47:43 lr: 4.590205164209435e-05 loss: 0.1300 (0.1489) time: 2.8992 data: 0.0074 max mem: 33369 +Epoch: [3] [1660/2639] eta: 0:47:14 lr: 4.589774794369554e-05 loss: 0.1300 (0.1489) time: 2.9319 data: 0.0075 max mem: 33369 +Epoch: [3] [1670/2639] eta: 0:46:46 lr: 4.589344420045789e-05 loss: 0.1603 (0.1492) time: 2.9416 data: 0.0075 max mem: 33369 +Epoch: [3] [1680/2639] eta: 0:46:17 lr: 4.588914041237627e-05 loss: 0.1491 (0.1492) time: 2.9194 data: 0.0072 max mem: 33369 +Epoch: [3] [1690/2639] eta: 0:45:48 lr: 4.588483657944554e-05 loss: 0.1408 (0.1491) time: 2.9031 data: 0.0074 max mem: 33369 +Epoch: [3] [1700/2639] eta: 0:45:19 lr: 4.5880532701660555e-05 loss: 0.1196 (0.1489) time: 2.9015 data: 0.0074 max mem: 33369 +Epoch: [3] [1710/2639] eta: 0:44:50 lr: 4.587622877901617e-05 loss: 0.1066 (0.1488) time: 2.8854 data: 0.0077 max mem: 33369 +Epoch: [3] [1720/2639] eta: 0:44:21 lr: 4.587192481150725e-05 loss: 0.1301 (0.1489) time: 2.8679 data: 0.0078 max mem: 33369 +Epoch: [3] [1730/2639] eta: 0:43:52 lr: 4.586762079912864e-05 loss: 0.1041 (0.1487) time: 2.8742 data: 0.0078 max mem: 33369 +Epoch: [3] [1740/2639] eta: 0:43:22 lr: 4.58633167418752e-05 loss: 0.0983 (0.1486) time: 2.8792 data: 0.0080 max mem: 33369 +Epoch: [3] [1750/2639] eta: 0:42:54 lr: 4.585901263974178e-05 loss: 0.1379 (0.1486) time: 2.9100 data: 0.0076 max mem: 33369 +Epoch: [3] [1760/2639] eta: 0:42:25 lr: 4.585470849272324e-05 loss: 0.1271 (0.1485) time: 2.9155 data: 0.0078 max mem: 33369 +Epoch: [3] [1770/2639] eta: 0:41:56 lr: 4.585040430081442e-05 loss: 0.1408 (0.1486) time: 2.8849 data: 0.0077 max mem: 33369 +Epoch: [3] [1780/2639] eta: 0:41:27 lr: 4.584610006401017e-05 loss: 0.1408 (0.1486) time: 2.8610 data: 0.0075 max mem: 33369 +Epoch: [3] [1790/2639] eta: 0:40:58 lr: 4.5841795782305344e-05 loss: 0.1362 (0.1486) time: 2.8600 data: 0.0076 max mem: 33369 +Epoch: [3] [1800/2639] eta: 0:40:28 lr: 4.5837491455694786e-05 loss: 0.1323 (0.1486) time: 2.8825 data: 0.0073 max mem: 33369 +Epoch: [3] [1810/2639] eta: 0:39:59 lr: 4.583318708417335e-05 loss: 0.1344 (0.1485) time: 2.8771 data: 0.0074 max mem: 33369 +Epoch: [3] [1820/2639] eta: 0:39:31 lr: 4.582888266773586e-05 loss: 0.1344 (0.1485) time: 2.8988 data: 0.0076 max mem: 33369 +Epoch: [3] [1830/2639] eta: 0:39:01 lr: 4.582457820637718e-05 loss: 0.1498 (0.1486) time: 2.8870 data: 0.0077 max mem: 33369 +Epoch: [3] [1840/2639] eta: 0:38:32 lr: 4.582027370009215e-05 loss: 0.1519 (0.1486) time: 2.8419 data: 0.0076 max mem: 33369 +Epoch: [3] [1850/2639] eta: 0:38:03 lr: 4.581596914887561e-05 loss: 0.1452 (0.1487) time: 2.8309 data: 0.0076 max mem: 33369 +Epoch: [3] [1860/2639] eta: 0:37:34 lr: 4.581166455272238e-05 loss: 0.1401 (0.1486) time: 2.8559 data: 0.0076 max mem: 33369 +Epoch: [3] [1870/2639] eta: 0:37:05 lr: 4.580735991162733e-05 loss: 0.1301 (0.1487) time: 2.8673 data: 0.0073 max mem: 33369 +Epoch: [3] [1880/2639] eta: 0:36:36 lr: 4.580305522558528e-05 loss: 0.1389 (0.1489) time: 2.8787 data: 0.0075 max mem: 33369 +Epoch: [3] [1890/2639] eta: 0:36:07 lr: 4.5798750494591085e-05 loss: 0.1466 (0.1489) time: 2.9151 data: 0.0078 max mem: 33369 +Epoch: [3] [1900/2639] eta: 0:35:38 lr: 4.579444571863956e-05 loss: 0.1575 (0.1489) time: 2.9089 data: 0.0075 max mem: 33369 +Epoch: [3] [1910/2639] eta: 0:35:10 lr: 4.579014089772555e-05 loss: 0.1502 (0.1489) time: 2.9157 data: 0.0075 max mem: 33369 +Epoch: [3] [1920/2639] eta: 0:34:40 lr: 4.5785836031843875e-05 loss: 0.1373 (0.1489) time: 2.9061 data: 0.0074 max mem: 33369 +Epoch: [3] [1930/2639] eta: 0:34:12 lr: 4.5781531120989394e-05 loss: 0.1294 (0.1489) time: 2.8880 data: 0.0076 max mem: 33369 +Epoch: [3] [1940/2639] eta: 0:33:42 lr: 4.5777226165156914e-05 loss: 0.1393 (0.1489) time: 2.8678 data: 0.0075 max mem: 33369 +Epoch: [3] [1950/2639] eta: 0:33:13 lr: 4.577292116434128e-05 loss: 0.1352 (0.1488) time: 2.8472 data: 0.0070 max mem: 33369 +Epoch: [3] [1960/2639] eta: 0:32:44 lr: 4.576861611853731e-05 loss: 0.1352 (0.1488) time: 2.8743 data: 0.0074 max mem: 33369 +Epoch: [3] [1970/2639] eta: 0:32:15 lr: 4.576431102773984e-05 loss: 0.1422 (0.1487) time: 2.8921 data: 0.0078 max mem: 33369 +Epoch: [3] [1980/2639] eta: 0:31:47 lr: 4.5760005891943694e-05 loss: 0.1324 (0.1486) time: 2.9046 data: 0.0080 max mem: 33369 +Epoch: [3] [1990/2639] eta: 0:31:18 lr: 4.5755700711143695e-05 loss: 0.1199 (0.1487) time: 2.9103 data: 0.0075 max mem: 33369 +Epoch: [3] [2000/2639] eta: 0:30:49 lr: 4.575139548533468e-05 loss: 0.1246 (0.1486) time: 2.9129 data: 0.0073 max mem: 33369 +Epoch: [3] [2010/2639] eta: 0:30:20 lr: 4.5747090214511453e-05 loss: 0.1291 (0.1485) time: 2.9171 data: 0.0073 max mem: 33369 +Epoch: [3] [2020/2639] eta: 0:29:51 lr: 4.574278489866885e-05 loss: 0.1328 (0.1485) time: 2.9135 data: 0.0072 max mem: 33369 +Epoch: [3] [2030/2639] eta: 0:29:22 lr: 4.573847953780169e-05 loss: 0.1297 (0.1484) time: 2.9312 data: 0.0073 max mem: 33369 +Epoch: [3] [2040/2639] eta: 0:28:53 lr: 4.573417413190479e-05 loss: 0.1245 (0.1483) time: 2.9464 data: 0.0075 max mem: 33369 +Epoch: [3] [2050/2639] eta: 0:28:25 lr: 4.572986868097297e-05 loss: 0.1396 (0.1484) time: 2.9334 data: 0.0077 max mem: 33369 +Epoch: [3] [2060/2639] eta: 0:27:56 lr: 4.572556318500105e-05 loss: 0.1479 (0.1484) time: 2.9357 data: 0.0076 max mem: 33369 +Epoch: [3] [2070/2639] eta: 0:27:27 lr: 4.572125764398384e-05 loss: 0.1435 (0.1484) time: 2.9116 data: 0.0075 max mem: 33369 +Epoch: [3] [2080/2639] eta: 0:26:58 lr: 4.5716952057916154e-05 loss: 0.1435 (0.1483) time: 2.8710 data: 0.0076 max mem: 33369 +Epoch: [3] [2090/2639] eta: 0:26:29 lr: 4.571264642679282e-05 loss: 0.1071 (0.1482) time: 2.8697 data: 0.0078 max mem: 33369 +Epoch: [3] [2100/2639] eta: 0:26:00 lr: 4.570834075060865e-05 loss: 0.1269 (0.1482) time: 2.9012 data: 0.0079 max mem: 33369 +Epoch: [3] [2110/2639] eta: 0:25:31 lr: 4.570403502935843e-05 loss: 0.1413 (0.1482) time: 2.8790 data: 0.0078 max mem: 33369 +Epoch: [3] [2120/2639] eta: 0:25:02 lr: 4.569972926303701e-05 loss: 0.1432 (0.1482) time: 2.8611 data: 0.0082 max mem: 33369 +Epoch: [3] [2130/2639] eta: 0:24:33 lr: 4.5695423451639166e-05 loss: 0.1407 (0.1481) time: 2.8962 data: 0.0085 max mem: 33369 +Epoch: [3] [2140/2639] eta: 0:24:04 lr: 4.5691117595159725e-05 loss: 0.1483 (0.1481) time: 2.9068 data: 0.0082 max mem: 33369 +Epoch: [3] [2150/2639] eta: 0:23:35 lr: 4.568681169359349e-05 loss: 0.1364 (0.1481) time: 2.9263 data: 0.0079 max mem: 33369 +Epoch: [3] [2160/2639] eta: 0:23:06 lr: 4.568250574693527e-05 loss: 0.1355 (0.1480) time: 2.9368 data: 0.0076 max mem: 33369 +Epoch: [3] [2170/2639] eta: 0:22:37 lr: 4.5678199755179864e-05 loss: 0.1355 (0.1481) time: 2.9446 data: 0.0075 max mem: 33369 +Epoch: [3] [2180/2639] eta: 0:22:09 lr: 4.567389371832208e-05 loss: 0.1334 (0.1481) time: 2.9240 data: 0.0078 max mem: 33369 +Epoch: [3] [2190/2639] eta: 0:21:40 lr: 4.5669587636356715e-05 loss: 0.1309 (0.1481) time: 2.9060 data: 0.0080 max mem: 33369 +Epoch: [3] [2200/2639] eta: 0:21:11 lr: 4.5665281509278586e-05 loss: 0.1230 (0.1479) time: 2.9456 data: 0.0076 max mem: 33369 +Epoch: [3] [2210/2639] eta: 0:20:42 lr: 4.5660975337082474e-05 loss: 0.1216 (0.1479) time: 2.9588 data: 0.0075 max mem: 33369 +Epoch: [3] [2220/2639] eta: 0:20:13 lr: 4.565666911976319e-05 loss: 0.1295 (0.1478) time: 2.9585 data: 0.0076 max mem: 33369 +Epoch: [3] [2230/2639] eta: 0:19:44 lr: 4.565236285731553e-05 loss: 0.1521 (0.1479) time: 2.9588 data: 0.0076 max mem: 33369 +Epoch: [3] [2240/2639] eta: 0:19:15 lr: 4.5648056549734283e-05 loss: 0.1664 (0.1481) time: 2.9546 data: 0.0075 max mem: 33369 +Epoch: [3] [2250/2639] eta: 0:18:46 lr: 4.564375019701427e-05 loss: 0.1803 (0.1482) time: 2.9378 data: 0.0074 max mem: 33369 +Epoch: [3] [2260/2639] eta: 0:18:18 lr: 4.563944379915026e-05 loss: 0.1459 (0.1482) time: 2.9328 data: 0.0073 max mem: 33369 +Epoch: [3] [2270/2639] eta: 0:17:49 lr: 4.563513735613706e-05 loss: 0.1467 (0.1483) time: 2.9007 data: 0.0074 max mem: 33369 +Epoch: [3] [2280/2639] eta: 0:17:19 lr: 4.5630830867969446e-05 loss: 0.1540 (0.1483) time: 2.8512 data: 0.0076 max mem: 33369 +Epoch: [3] [2290/2639] eta: 0:16:51 lr: 4.562652433464224e-05 loss: 0.1237 (0.1483) time: 2.8968 data: 0.0073 max mem: 33369 +Epoch: [3] [2300/2639] eta: 0:16:22 lr: 4.56222177561502e-05 loss: 0.1194 (0.1483) time: 2.9322 data: 0.0072 max mem: 33369 +Epoch: [3] [2310/2639] eta: 0:15:53 lr: 4.5617911132488136e-05 loss: 0.1343 (0.1483) time: 2.9347 data: 0.0073 max mem: 33369 +Epoch: [3] [2320/2639] eta: 0:15:24 lr: 4.561360446365083e-05 loss: 0.1343 (0.1483) time: 2.9069 data: 0.0072 max mem: 33369 +Epoch: [3] [2330/2639] eta: 0:14:55 lr: 4.5609297749633065e-05 loss: 0.1294 (0.1483) time: 2.8753 data: 0.0075 max mem: 33369 +Epoch: [3] [2340/2639] eta: 0:14:26 lr: 4.560499099042962e-05 loss: 0.1248 (0.1483) time: 2.9223 data: 0.0074 max mem: 33369 +Epoch: [3] [2350/2639] eta: 0:13:57 lr: 4.560068418603531e-05 loss: 0.1248 (0.1483) time: 2.8990 data: 0.0075 max mem: 33369 +Epoch: [3] [2360/2639] eta: 0:13:28 lr: 4.559637733644488e-05 loss: 0.1439 (0.1483) time: 2.8503 data: 0.0081 max mem: 33369 +Epoch: [3] [2370/2639] eta: 0:12:59 lr: 4.559207044165314e-05 loss: 0.1463 (0.1483) time: 2.8672 data: 0.0076 max mem: 33369 +Epoch: [3] [2380/2639] eta: 0:12:30 lr: 4.558776350165485e-05 loss: 0.1568 (0.1483) time: 2.8826 data: 0.0072 max mem: 33369 +Epoch: [3] [2390/2639] eta: 0:12:01 lr: 4.558345651644481e-05 loss: 0.1429 (0.1484) time: 2.8792 data: 0.0071 max mem: 33369 +Epoch: [3] [2400/2639] eta: 0:11:32 lr: 4.557914948601779e-05 loss: 0.1403 (0.1484) time: 2.8795 data: 0.0073 max mem: 33369 +Epoch: [3] [2410/2639] eta: 0:11:03 lr: 4.557484241036856e-05 loss: 0.1439 (0.1484) time: 2.9067 data: 0.0075 max mem: 33369 +Epoch: [3] [2420/2639] eta: 0:10:34 lr: 4.55705352894919e-05 loss: 0.1556 (0.1485) time: 2.9429 data: 0.0074 max mem: 33369 +Epoch: [3] [2430/2639] eta: 0:10:05 lr: 4.556622812338261e-05 loss: 0.1556 (0.1484) time: 2.9206 data: 0.0078 max mem: 33369 +Epoch: [3] [2440/2639] eta: 0:09:36 lr: 4.5561920912035424e-05 loss: 0.1541 (0.1485) time: 2.9232 data: 0.0080 max mem: 33369 +Epoch: [3] [2450/2639] eta: 0:09:07 lr: 4.555761365544514e-05 loss: 0.1509 (0.1485) time: 2.9596 data: 0.0080 max mem: 33369 +Epoch: [3] [2460/2639] eta: 0:08:38 lr: 4.555330635360652e-05 loss: 0.1483 (0.1486) time: 2.9100 data: 0.0082 max mem: 33369 +Epoch: [3] [2470/2639] eta: 0:08:09 lr: 4.5548999006514345e-05 loss: 0.1470 (0.1485) time: 2.9057 data: 0.0078 max mem: 33369 +Epoch: [3] [2480/2639] eta: 0:07:40 lr: 4.5544691614163376e-05 loss: 0.1466 (0.1485) time: 2.9060 data: 0.0076 max mem: 33369 +Epoch: [3] [2490/2639] eta: 0:07:11 lr: 4.5540384176548376e-05 loss: 0.1336 (0.1484) time: 2.8784 data: 0.0077 max mem: 33369 +Epoch: [3] [2500/2639] eta: 0:06:42 lr: 4.5536076693664134e-05 loss: 0.1336 (0.1485) time: 2.8939 data: 0.0077 max mem: 33369 +Epoch: [3] [2510/2639] eta: 0:06:13 lr: 4.55317691655054e-05 loss: 0.1497 (0.1486) time: 2.9043 data: 0.0078 max mem: 33369 +Epoch: [3] [2520/2639] eta: 0:05:44 lr: 4.552746159206693e-05 loss: 0.1410 (0.1486) time: 2.9063 data: 0.0078 max mem: 33369 +Epoch: [3] [2530/2639] eta: 0:05:15 lr: 4.55231539733435e-05 loss: 0.1303 (0.1486) time: 2.9318 data: 0.0075 max mem: 33369 +Epoch: [3] [2540/2639] eta: 0:04:46 lr: 4.551884630932988e-05 loss: 0.1264 (0.1486) time: 2.9526 data: 0.0077 max mem: 33369 +Epoch: [3] [2550/2639] eta: 0:04:17 lr: 4.5514538600020816e-05 loss: 0.1354 (0.1486) time: 2.9388 data: 0.0081 max mem: 33369 +Epoch: [3] [2560/2639] eta: 0:03:48 lr: 4.551023084541108e-05 loss: 0.1643 (0.1486) time: 2.9326 data: 0.0076 max mem: 33369 +Epoch: [3] [2570/2639] eta: 0:03:19 lr: 4.5505923045495424e-05 loss: 0.1393 (0.1486) time: 2.9096 data: 0.0071 max mem: 33369 +Epoch: [3] [2580/2639] eta: 0:02:50 lr: 4.5501615200268614e-05 loss: 0.1337 (0.1487) time: 2.8565 data: 0.0079 max mem: 33369 +Epoch: [3] [2590/2639] eta: 0:02:21 lr: 4.549730730972539e-05 loss: 0.1612 (0.1488) time: 2.8404 data: 0.0084 max mem: 33369 +Epoch: [3] [2600/2639] eta: 0:01:53 lr: 4.5492999373860526e-05 loss: 0.1612 (0.1488) time: 2.8805 data: 0.0081 max mem: 33369 +Epoch: [3] [2610/2639] eta: 0:01:24 lr: 4.548869139266877e-05 loss: 0.1360 (0.1488) time: 2.9026 data: 0.0079 max mem: 33369 +Epoch: [3] [2620/2639] eta: 0:00:55 lr: 4.5484383366144873e-05 loss: 0.1300 (0.1488) time: 2.9213 data: 0.0076 max mem: 33369 +Epoch: [3] [2630/2639] eta: 0:00:26 lr: 4.548007529428358e-05 loss: 0.1300 (0.1488) time: 2.9225 data: 0.0071 max mem: 33369 +Epoch: [3] Total time: 2:07:28 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 2:13:50 time: 3.1209 data: 3.0135 max mem: 33369 +Test: [ 100/2573] eta: 0:04:26 time: 0.0783 data: 0.0014 max mem: 33369 +Test: [ 200/2573] eta: 0:03:43 time: 0.0792 data: 0.0013 max mem: 33369 +Test: [ 300/2573] eta: 0:03:22 time: 0.0810 data: 0.0013 max mem: 33369 +Test: [ 400/2573] eta: 0:03:07 time: 0.0818 data: 0.0014 max mem: 33369 +Test: [ 500/2573] eta: 0:02:56 time: 0.0801 data: 0.0015 max mem: 33369 +Test: [ 600/2573] eta: 0:02:46 time: 0.0796 data: 0.0014 max mem: 33369 +Test: [ 700/2573] eta: 0:02:37 time: 0.0800 data: 0.0014 max mem: 33369 +Test: [ 800/2573] eta: 0:02:28 time: 0.0836 data: 0.0014 max mem: 33369 +Test: [ 900/2573] eta: 0:02:19 time: 0.0800 data: 0.0015 max mem: 33369 +Test: [1000/2573] eta: 0:02:10 time: 0.0803 data: 0.0015 max mem: 33369 +Test: [1100/2573] eta: 0:02:02 time: 0.0800 data: 0.0014 max mem: 33369 +Test: [1200/2573] eta: 0:01:53 time: 0.0807 data: 0.0014 max mem: 33369 +Test: [1300/2573] eta: 0:01:45 time: 0.0810 data: 0.0014 max mem: 33369 +Test: [1400/2573] eta: 0:01:36 time: 0.0791 data: 0.0015 max mem: 33369 +Test: [1500/2573] eta: 0:01:28 time: 0.0807 data: 0.0015 max mem: 33369 +Test: [1600/2573] eta: 0:01:20 time: 0.0840 data: 0.0015 max mem: 33369 +Test: [1700/2573] eta: 0:01:11 time: 0.0793 data: 0.0013 max mem: 33369 +Test: [1800/2573] eta: 0:01:03 time: 0.0823 data: 0.0015 max mem: 33369 +Test: [1900/2573] eta: 0:00:55 time: 0.0780 data: 0.0015 max mem: 33369 +Test: [2000/2573] eta: 0:00:46 time: 0.0805 data: 0.0015 max mem: 33369 +Test: [2100/2573] eta: 0:00:38 time: 0.0819 data: 0.0014 max mem: 33369 +Test: [2200/2573] eta: 0:00:30 time: 0.0816 data: 0.0014 max mem: 33369 +Test: [2300/2573] eta: 0:00:22 time: 0.0824 data: 0.0015 max mem: 33369 +Test: [2400/2573] eta: 0:00:14 time: 0.0769 data: 0.0014 max mem: 33369 +Test: [2500/2573] eta: 0:00:05 time: 0.0807 data: 0.0014 max mem: 33369 +Test: Total time: 0:03:30 +Final results: +Mean IoU is 48.78 + + precision@0.5 = 53.08 + precision@0.6 = 45.79 + precision@0.7 = 37.09 + precision@0.8 = 25.80 + precision@0.9 = 10.25 + overall IoU = 50.15 + +Average object IoU 48.77594711808622 +Overall IoU 50.150753021240234 +Better epoch: 3 + +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [4] [ 0/2639] eta: 3:49:52 lr: 4.5476197990840624e-05 loss: 0.1268 (0.1268) time: 5.2265 data: 2.2587 max mem: 33369 +Epoch: [4] [ 10/2639] eta: 2:15:32 lr: 4.5471889832823845e-05 loss: 0.1237 (0.1318) time: 3.0934 data: 0.2117 max mem: 33369 +Epoch: [4] [ 20/2639] eta: 2:10:50 lr: 4.546758162945445e-05 loss: 0.1155 (0.1275) time: 2.8861 data: 0.0076 max mem: 33369 +Epoch: [4] [ 30/2639] eta: 2:08:49 lr: 4.546327338072719e-05 loss: 0.1247 (0.1321) time: 2.8905 data: 0.0084 max mem: 33369 +Epoch: [4] [ 40/2639] eta: 2:07:31 lr: 4.545896508663681e-05 loss: 0.1200 (0.1273) time: 2.8881 data: 0.0081 max mem: 33369 +Epoch: [4] [ 50/2639] eta: 2:06:26 lr: 4.5454656747178066e-05 loss: 0.1074 (0.1264) time: 2.8799 data: 0.0077 max mem: 33369 +Epoch: [4] [ 60/2639] eta: 2:05:36 lr: 4.545034836234568e-05 loss: 0.1193 (0.1272) time: 2.8775 data: 0.0076 max mem: 33369 +Epoch: [4] [ 70/2639] eta: 2:05:05 lr: 4.544603993213442e-05 loss: 0.1271 (0.1288) time: 2.8996 data: 0.0077 max mem: 33369 +Epoch: [4] [ 80/2639] eta: 2:04:15 lr: 4.544173145653901e-05 loss: 0.1152 (0.1278) time: 2.8864 data: 0.0078 max mem: 33369 +Epoch: [4] [ 90/2639] eta: 2:03:49 lr: 4.5437422935554206e-05 loss: 0.1137 (0.1261) time: 2.8903 data: 0.0079 max mem: 33369 +Epoch: [4] [ 100/2639] eta: 2:03:13 lr: 4.5433114369174725e-05 loss: 0.1041 (0.1243) time: 2.9068 data: 0.0080 max mem: 33369 +Epoch: [4] [ 110/2639] eta: 2:02:41 lr: 4.542880575739533e-05 loss: 0.1179 (0.1254) time: 2.8946 data: 0.0079 max mem: 33369 +Epoch: [4] [ 120/2639] eta: 2:02:10 lr: 4.542449710021074e-05 loss: 0.1241 (0.1252) time: 2.8997 data: 0.0082 max mem: 33369 +Epoch: [4] [ 130/2639] eta: 2:01:33 lr: 4.54201883976157e-05 loss: 0.1213 (0.1254) time: 2.8856 data: 0.0081 max mem: 33369 +Epoch: [4] [ 140/2639] eta: 2:01:11 lr: 4.5415879649604945e-05 loss: 0.1280 (0.1273) time: 2.9078 data: 0.0076 max mem: 33369 +Epoch: [4] [ 150/2639] eta: 2:00:44 lr: 4.541157085617321e-05 loss: 0.1447 (0.1282) time: 2.9347 data: 0.0078 max mem: 33369 +Epoch: [4] [ 160/2639] eta: 2:00:17 lr: 4.540726201731521e-05 loss: 0.1388 (0.1297) time: 2.9229 data: 0.0077 max mem: 33369 +Epoch: [4] [ 170/2639] eta: 1:59:44 lr: 4.54029531330257e-05 loss: 0.1219 (0.1298) time: 2.9022 data: 0.0078 max mem: 33369 +Epoch: [4] [ 180/2639] eta: 1:59:12 lr: 4.539864420329941e-05 loss: 0.1182 (0.1305) time: 2.8855 data: 0.0082 max mem: 33369 +Epoch: [4] [ 190/2639] eta: 1:58:44 lr: 4.539433522813105e-05 loss: 0.1162 (0.1301) time: 2.9040 data: 0.0080 max mem: 33369 +Epoch: [4] [ 200/2639] eta: 1:58:04 lr: 4.5390026207515356e-05 loss: 0.1256 (0.1305) time: 2.8683 data: 0.0078 max mem: 33369 +Epoch: [4] [ 210/2639] eta: 1:57:29 lr: 4.5385717141447056e-05 loss: 0.1342 (0.1313) time: 2.8359 data: 0.0079 max mem: 33369 +Epoch: [4] [ 220/2639] eta: 1:56:59 lr: 4.5381408029920884e-05 loss: 0.1342 (0.1313) time: 2.8726 data: 0.0076 max mem: 33369 +Epoch: [4] [ 230/2639] eta: 1:56:37 lr: 4.537709887293155e-05 loss: 0.1462 (0.1324) time: 2.9335 data: 0.0077 max mem: 33369 +Epoch: [4] [ 240/2639] eta: 1:56:20 lr: 4.537278967047379e-05 loss: 0.1214 (0.1315) time: 2.9999 data: 0.0080 max mem: 33369 +Epoch: [4] [ 250/2639] eta: 1:55:45 lr: 4.5368480422542314e-05 loss: 0.1071 (0.1314) time: 2.9369 data: 0.0083 max mem: 33369 +Epoch: [4] [ 260/2639] eta: 1:55:19 lr: 4.5364171129131856e-05 loss: 0.1311 (0.1317) time: 2.8948 data: 0.0080 max mem: 33369 +Epoch: [4] [ 270/2639] eta: 1:54:48 lr: 4.535986179023712e-05 loss: 0.1264 (0.1316) time: 2.9129 data: 0.0077 max mem: 33369 +Epoch: [4] [ 280/2639] eta: 1:54:20 lr: 4.535555240585284e-05 loss: 0.1260 (0.1317) time: 2.9058 data: 0.0082 max mem: 33369 +Epoch: [4] [ 290/2639] eta: 1:53:49 lr: 4.535124297597372e-05 loss: 0.1260 (0.1317) time: 2.9022 data: 0.0082 max mem: 33369 +Epoch: [4] [ 300/2639] eta: 1:53:21 lr: 4.534693350059449e-05 loss: 0.1225 (0.1316) time: 2.9006 data: 0.0080 max mem: 33369 +Epoch: [4] [ 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+Epoch: [4] [ 390/2639] eta: 1:48:59 lr: 4.5308146173803666e-05 loss: 0.1221 (0.1334) time: 2.8745 data: 0.0078 max mem: 33369 +Epoch: [4] [ 400/2639] eta: 1:48:30 lr: 4.530383624313239e-05 loss: 0.1163 (0.1330) time: 2.8969 data: 0.0079 max mem: 33369 +Epoch: [4] [ 410/2639] eta: 1:48:01 lr: 4.529952626690279e-05 loss: 0.1087 (0.1329) time: 2.9093 data: 0.0080 max mem: 33369 +Epoch: [4] [ 420/2639] eta: 1:47:33 lr: 4.529521624510958e-05 loss: 0.1172 (0.1326) time: 2.9210 data: 0.0077 max mem: 33369 +Epoch: [4] [ 430/2639] eta: 1:47:04 lr: 4.529090617774746e-05 loss: 0.1122 (0.1324) time: 2.9144 data: 0.0079 max mem: 33369 +Epoch: [4] [ 440/2639] eta: 1:46:35 lr: 4.5286596064811116e-05 loss: 0.1296 (0.1326) time: 2.9104 data: 0.0076 max mem: 33369 +Epoch: [4] [ 450/2639] eta: 1:46:09 lr: 4.5282285906295266e-05 loss: 0.1460 (0.1327) time: 2.9418 data: 0.0074 max mem: 33369 +Epoch: [4] [ 460/2639] eta: 1:45:41 lr: 4.527797570219459e-05 loss: 0.1284 (0.1326) time: 2.9464 data: 0.0079 max mem: 33369 +Epoch: [4] [ 470/2639] eta: 1:45:09 lr: 4.52736654525038e-05 loss: 0.1113 (0.1323) time: 2.8933 data: 0.0078 max mem: 33369 +Epoch: [4] [ 480/2639] eta: 1:44:40 lr: 4.5269355157217576e-05 loss: 0.1218 (0.1325) time: 2.8794 data: 0.0075 max mem: 33369 +Epoch: [4] [ 490/2639] eta: 1:44:09 lr: 4.526504481633062e-05 loss: 0.1309 (0.1325) time: 2.8883 data: 0.0079 max mem: 33369 +Epoch: [4] [ 500/2639] eta: 1:43:39 lr: 4.526073442983763e-05 loss: 0.1273 (0.1323) time: 2.8782 data: 0.0081 max mem: 33369 +Epoch: [4] [ 510/2639] eta: 1:43:08 lr: 4.525642399773328e-05 loss: 0.1270 (0.1326) time: 2.8744 data: 0.0083 max mem: 33369 +Epoch: [4] [ 520/2639] eta: 1:42:38 lr: 4.525211352001228e-05 loss: 0.1296 (0.1327) time: 2.8711 data: 0.0081 max mem: 33369 +Epoch: [4] [ 530/2639] eta: 1:42:09 lr: 4.524780299666931e-05 loss: 0.1296 (0.1327) time: 2.8916 data: 0.0076 max mem: 33369 +Epoch: [4] [ 540/2639] eta: 1:41:39 lr: 4.5243492427699054e-05 loss: 0.1195 (0.1325) time: 2.8926 data: 0.0075 max mem: 33369 +Epoch: [4] [ 550/2639] eta: 1:41:09 lr: 4.5239181813096206e-05 loss: 0.1142 (0.1321) time: 2.8880 data: 0.0080 max mem: 33369 +Epoch: [4] [ 560/2639] eta: 1:40:41 lr: 4.5234871152855454e-05 loss: 0.1273 (0.1323) time: 2.9149 data: 0.0082 max mem: 33369 +Epoch: [4] [ 570/2639] eta: 1:40:11 lr: 4.523056044697147e-05 loss: 0.1285 (0.1323) time: 2.9116 data: 0.0079 max mem: 33369 +Epoch: [4] [ 580/2639] eta: 1:39:42 lr: 4.5226249695438944e-05 loss: 0.1419 (0.1328) time: 2.8925 data: 0.0078 max mem: 33369 +Epoch: [4] [ 590/2639] eta: 1:39:12 lr: 4.522193889825256e-05 loss: 0.1551 (0.1328) time: 2.8816 data: 0.0076 max mem: 33369 +Epoch: [4] [ 600/2639] eta: 1:38:42 lr: 4.5217628055407e-05 loss: 0.1449 (0.1329) time: 2.8815 data: 0.0075 max mem: 33369 +Epoch: [4] [ 610/2639] eta: 1:38:14 lr: 4.521331716689694e-05 loss: 0.1311 (0.1328) time: 2.9081 data: 0.0076 max mem: 33369 +Epoch: [4] [ 620/2639] eta: 1:37:45 lr: 4.520900623271706e-05 loss: 0.1212 (0.1329) time: 2.9116 data: 0.0078 max mem: 33369 +Epoch: [4] [ 630/2639] eta: 1:37:15 lr: 4.520469525286203e-05 loss: 0.1379 (0.1331) time: 2.8926 data: 0.0077 max mem: 33369 +Epoch: [4] [ 640/2639] eta: 1:36:44 lr: 4.5200384227326544e-05 loss: 0.1305 (0.1332) time: 2.8616 data: 0.0077 max mem: 33369 +Epoch: [4] [ 650/2639] eta: 1:36:14 lr: 4.5196073156105264e-05 loss: 0.1265 (0.1332) time: 2.8662 data: 0.0078 max mem: 33369 +Epoch: [4] [ 660/2639] eta: 1:35:46 lr: 4.5191762039192864e-05 loss: 0.1135 (0.1328) time: 2.9002 data: 0.0079 max mem: 33369 +Epoch: [4] [ 670/2639] eta: 1:35:17 lr: 4.518745087658401e-05 loss: 0.1048 (0.1329) time: 2.9088 data: 0.0076 max mem: 33369 +Epoch: [4] [ 680/2639] eta: 1:34:49 lr: 4.51831396682734e-05 loss: 0.1350 (0.1332) time: 2.9307 data: 0.0076 max mem: 33369 +Epoch: [4] [ 690/2639] eta: 1:34:19 lr: 4.517882841425567e-05 loss: 0.1270 (0.1331) time: 2.9144 data: 0.0079 max mem: 33369 +Epoch: [4] [ 700/2639] eta: 1:33:49 lr: 4.517451711452551e-05 loss: 0.1163 (0.1331) time: 2.8764 data: 0.0080 max mem: 33369 +Epoch: [4] [ 710/2639] eta: 1:33:19 lr: 4.517020576907758e-05 loss: 0.1156 (0.1330) time: 2.8725 data: 0.0078 max mem: 33369 +Epoch: [4] [ 720/2639] eta: 1:32:49 lr: 4.516589437790656e-05 loss: 0.1129 (0.1334) time: 2.8685 data: 0.0078 max mem: 33369 +Epoch: [4] [ 730/2639] eta: 1:32:20 lr: 4.5161582941007094e-05 loss: 0.1240 (0.1336) time: 2.8673 data: 0.0077 max mem: 33369 +Epoch: [4] [ 740/2639] eta: 1:31:50 lr: 4.515727145837386e-05 loss: 0.1352 (0.1336) time: 2.8663 data: 0.0078 max mem: 33369 +Epoch: [4] [ 750/2639] eta: 1:31:18 lr: 4.515295993000152e-05 loss: 0.1348 (0.1338) time: 2.8403 data: 0.0083 max mem: 33369 +Epoch: [4] [ 760/2639] eta: 1:30:48 lr: 4.514864835588473e-05 loss: 0.1461 (0.1339) time: 2.8356 data: 0.0081 max mem: 33369 +Epoch: [4] [ 770/2639] eta: 1:30:20 lr: 4.514433673601816e-05 loss: 0.1194 (0.1340) time: 2.8889 data: 0.0079 max mem: 33369 +Epoch: [4] [ 780/2639] eta: 1:29:51 lr: 4.514002507039646e-05 loss: 0.1226 (0.1339) time: 2.9074 data: 0.0077 max mem: 33369 +Epoch: [4] [ 790/2639] eta: 1:29:22 lr: 4.5135713359014296e-05 loss: 0.1408 (0.1340) time: 2.8946 data: 0.0075 max mem: 33369 +Epoch: [4] [ 800/2639] eta: 1:28:51 lr: 4.5131401601866324e-05 loss: 0.1507 (0.1343) time: 2.8677 data: 0.0077 max mem: 33369 +Epoch: [4] [ 810/2639] eta: 1:28:22 lr: 4.512708979894719e-05 loss: 0.1208 (0.1342) time: 2.8630 data: 0.0079 max mem: 33369 +Epoch: [4] [ 820/2639] eta: 1:27:53 lr: 4.512277795025157e-05 loss: 0.1047 (0.1342) time: 2.8886 data: 0.0080 max mem: 33369 +Epoch: [4] [ 830/2639] eta: 1:27:23 lr: 4.511846605577409e-05 loss: 0.1413 (0.1344) time: 2.8858 data: 0.0080 max mem: 33369 +Epoch: [4] [ 840/2639] eta: 1:26:53 lr: 4.511415411550942e-05 loss: 0.1234 (0.1342) time: 2.8670 data: 0.0084 max mem: 33369 +Epoch: [4] [ 850/2639] eta: 1:26:23 lr: 4.510984212945221e-05 loss: 0.1137 (0.1343) time: 2.8518 data: 0.0081 max mem: 33369 +Epoch: [4] [ 860/2639] eta: 1:25:53 lr: 4.510553009759711e-05 loss: 0.1485 (0.1346) time: 2.8440 data: 0.0079 max mem: 33369 +Epoch: [4] [ 870/2639] eta: 1:25:26 lr: 4.510121801993876e-05 loss: 0.1302 (0.1345) time: 2.9105 data: 0.0082 max mem: 33369 +Epoch: [4] [ 880/2639] eta: 1:24:59 lr: 4.509690589647182e-05 loss: 0.1310 (0.1347) time: 2.9872 data: 0.0080 max mem: 33369 +Epoch: [4] [ 890/2639] eta: 1:24:31 lr: 4.509259372719093e-05 loss: 0.1399 (0.1348) time: 2.9648 data: 0.0075 max mem: 33369 +Epoch: [4] [ 900/2639] eta: 1:24:02 lr: 4.508828151209073e-05 loss: 0.1183 (0.1347) time: 2.9395 data: 0.0075 max mem: 33369 +Epoch: [4] [ 910/2639] eta: 1:23:36 lr: 4.5083969251165875e-05 loss: 0.1209 (0.1348) time: 2.9754 data: 0.0079 max mem: 33369 +Epoch: [4] [ 920/2639] eta: 1:23:07 lr: 4.5079656944411e-05 loss: 0.1363 (0.1349) time: 2.9645 data: 0.0078 max mem: 33369 +Epoch: [4] [ 930/2639] eta: 1:22:39 lr: 4.507534459182075e-05 loss: 0.1536 (0.1350) time: 2.9390 data: 0.0076 max mem: 33369 +Epoch: [4] [ 940/2639] eta: 1:22:09 lr: 4.5071032193389755e-05 loss: 0.1227 (0.1349) time: 2.9107 data: 0.0075 max mem: 33369 +Epoch: [4] [ 950/2639] eta: 1:21:41 lr: 4.506671974911268e-05 loss: 0.1093 (0.1346) time: 2.9115 data: 0.0075 max mem: 33369 +Epoch: [4] [ 960/2639] eta: 1:21:12 lr: 4.5062407258984135e-05 loss: 0.1194 (0.1347) time: 2.9319 data: 0.0077 max mem: 33369 +Epoch: [4] [ 970/2639] eta: 1:20:43 lr: 4.5058094722998774e-05 loss: 0.1163 (0.1344) time: 2.8880 data: 0.0077 max mem: 33369 +Epoch: [4] [ 980/2639] eta: 1:20:14 lr: 4.505378214115123e-05 loss: 0.1048 (0.1344) time: 2.8869 data: 0.0078 max mem: 33369 +Epoch: [4] [ 990/2639] eta: 1:19:45 lr: 4.504946951343613e-05 loss: 0.1308 (0.1344) time: 2.9022 data: 0.0081 max mem: 33369 +Epoch: [4] [1000/2639] eta: 1:19:16 lr: 4.504515683984811e-05 loss: 0.1371 (0.1348) time: 2.9282 data: 0.0082 max mem: 33369 +Epoch: [4] [1010/2639] eta: 1:18:46 lr: 4.5040844120381804e-05 loss: 0.1413 (0.1349) time: 2.8844 data: 0.0080 max mem: 33369 +Epoch: [4] [1020/2639] eta: 1:18:17 lr: 4.503653135503184e-05 loss: 0.1321 (0.1353) time: 2.8591 data: 0.0081 max mem: 33369 +Epoch: [4] [1030/2639] eta: 1:17:49 lr: 4.5032218543792856e-05 loss: 0.1291 (0.1353) time: 2.9184 data: 0.0080 max mem: 33369 +Epoch: [4] [1040/2639] eta: 1:17:20 lr: 4.502790568665947e-05 loss: 0.1230 (0.1353) time: 2.9484 data: 0.0077 max mem: 33369 +Epoch: [4] [1050/2639] eta: 1:16:51 lr: 4.502359278362632e-05 loss: 0.1121 (0.1351) time: 2.9299 data: 0.0079 max mem: 33369 +Epoch: [4] [1060/2639] eta: 1:16:22 lr: 4.5019279834688025e-05 loss: 0.1215 (0.1355) time: 2.9051 data: 0.0081 max mem: 33369 +Epoch: [4] [1070/2639] eta: 1:15:53 lr: 4.5014966839839214e-05 loss: 0.1532 (0.1359) time: 2.8970 data: 0.0082 max mem: 33369 +Epoch: [4] [1080/2639] eta: 1:15:25 lr: 4.50106537990745e-05 loss: 0.1522 (0.1358) time: 2.9102 data: 0.0082 max mem: 33369 +Epoch: [4] [1090/2639] eta: 1:14:55 lr: 4.5006340712388515e-05 loss: 0.1128 (0.1356) time: 2.9020 data: 0.0078 max mem: 33369 +Epoch: [4] [1100/2639] eta: 1:14:26 lr: 4.500202757977588e-05 loss: 0.1123 (0.1355) time: 2.8848 data: 0.0078 max mem: 33369 +Epoch: [4] [1110/2639] eta: 1:13:57 lr: 4.499771440123121e-05 loss: 0.1158 (0.1355) time: 2.9045 data: 0.0082 max mem: 33369 +Epoch: [4] [1120/2639] eta: 1:13:28 lr: 4.499340117674913e-05 loss: 0.1209 (0.1353) time: 2.9163 data: 0.0084 max mem: 33369 +Epoch: [4] [1130/2639] eta: 1:13:00 lr: 4.498908790632425e-05 loss: 0.1239 (0.1353) time: 2.9210 data: 0.0082 max mem: 33369 +Epoch: [4] [1140/2639] eta: 1:12:32 lr: 4.4984774589951196e-05 loss: 0.1406 (0.1356) time: 2.9523 data: 0.0078 max mem: 33369 +Epoch: [4] [1150/2639] eta: 1:12:03 lr: 4.4980461227624574e-05 loss: 0.1330 (0.1356) time: 2.9503 data: 0.0079 max mem: 33369 +Epoch: [4] [1160/2639] eta: 1:11:34 lr: 4.497614781933901e-05 loss: 0.1225 (0.1356) time: 2.9128 data: 0.0078 max mem: 33369 +Epoch: [4] [1170/2639] eta: 1:11:05 lr: 4.49718343650891e-05 loss: 0.1232 (0.1357) time: 2.9329 data: 0.0073 max mem: 33369 +Epoch: [4] [1180/2639] eta: 1:10:36 lr: 4.496752086486947e-05 loss: 0.1233 (0.1356) time: 2.9275 data: 0.0078 max mem: 33369 +Epoch: [4] [1190/2639] eta: 1:10:07 lr: 4.496320731867472e-05 loss: 0.1189 (0.1357) time: 2.8816 data: 0.0079 max mem: 33369 +Epoch: [4] [1200/2639] eta: 1:09:37 lr: 4.495889372649947e-05 loss: 0.1211 (0.1356) time: 2.8607 data: 0.0075 max mem: 33369 +Epoch: [4] [1210/2639] eta: 1:09:08 lr: 4.4954580088338316e-05 loss: 0.1272 (0.1357) time: 2.8830 data: 0.0074 max mem: 33369 +Epoch: [4] [1220/2639] eta: 1:08:39 lr: 4.4950266404185877e-05 loss: 0.1104 (0.1355) time: 2.8927 data: 0.0074 max mem: 33369 +Epoch: [4] [1230/2639] eta: 1:08:10 lr: 4.494595267403675e-05 loss: 0.1125 (0.1356) time: 2.8850 data: 0.0080 max mem: 33369 +Epoch: [4] [1240/2639] eta: 1:07:40 lr: 4.494163889788554e-05 loss: 0.1383 (0.1356) time: 2.8645 data: 0.0079 max mem: 33369 +Epoch: [4] [1250/2639] eta: 1:07:11 lr: 4.4937325075726856e-05 loss: 0.1319 (0.1356) time: 2.8759 data: 0.0077 max mem: 33369 +Epoch: [4] [1260/2639] eta: 1:06:42 lr: 4.4933011207555295e-05 loss: 0.1171 (0.1355) time: 2.9193 data: 0.0078 max mem: 33369 +Epoch: [4] [1270/2639] eta: 1:06:13 lr: 4.492869729336546e-05 loss: 0.1171 (0.1354) time: 2.9014 data: 0.0077 max mem: 33369 +Epoch: [4] [1280/2639] eta: 1:05:43 lr: 4.492438333315194e-05 loss: 0.1245 (0.1355) time: 2.8545 data: 0.0079 max mem: 33369 +Epoch: [4] [1290/2639] eta: 1:05:14 lr: 4.492006932690935e-05 loss: 0.1368 (0.1355) time: 2.8638 data: 0.0080 max mem: 33369 +Epoch: [4] [1300/2639] eta: 1:04:45 lr: 4.4915755274632284e-05 loss: 0.1368 (0.1357) time: 2.9141 data: 0.0076 max mem: 33369 +Epoch: [4] [1310/2639] eta: 1:04:17 lr: 4.491144117631532e-05 loss: 0.1306 (0.1357) time: 2.9247 data: 0.0075 max mem: 33369 +Epoch: [4] [1320/2639] eta: 1:03:48 lr: 4.490712703195308e-05 loss: 0.1277 (0.1355) time: 2.9157 data: 0.0076 max mem: 33369 +Epoch: [4] [1330/2639] eta: 1:03:18 lr: 4.4902812841540134e-05 loss: 0.1241 (0.1357) time: 2.8985 data: 0.0074 max mem: 33369 +Epoch: [4] [1340/2639] eta: 1:02:49 lr: 4.489849860507108e-05 loss: 0.1232 (0.1357) time: 2.8847 data: 0.0078 max mem: 33369 +Epoch: [4] [1350/2639] eta: 1:02:20 lr: 4.489418432254053e-05 loss: 0.1198 (0.1356) time: 2.8876 data: 0.0079 max mem: 33369 +Epoch: [4] [1360/2639] eta: 1:01:51 lr: 4.488986999394305e-05 loss: 0.1374 (0.1356) time: 2.8691 data: 0.0078 max mem: 33369 +Epoch: [4] [1370/2639] eta: 1:01:22 lr: 4.488555561927323e-05 loss: 0.1343 (0.1357) time: 2.8849 data: 0.0076 max mem: 33369 +Epoch: [4] [1380/2639] eta: 1:00:53 lr: 4.4881241198525656e-05 loss: 0.1549 (0.1360) time: 2.8993 data: 0.0080 max mem: 33369 +Epoch: [4] [1390/2639] eta: 1:00:24 lr: 4.487692673169493e-05 loss: 0.1236 (0.1358) time: 2.9058 data: 0.0081 max mem: 33369 +Epoch: [4] [1400/2639] eta: 0:59:55 lr: 4.487261221877563e-05 loss: 0.1005 (0.1360) time: 2.9294 data: 0.0076 max mem: 33369 +Epoch: [4] [1410/2639] eta: 0:59:26 lr: 4.4868297659762335e-05 loss: 0.1158 (0.1359) time: 2.9177 data: 0.0079 max mem: 33369 +Epoch: [4] [1420/2639] eta: 0:58:57 lr: 4.486398305464963e-05 loss: 0.1158 (0.1358) time: 2.9076 data: 0.0078 max mem: 33369 +Epoch: [4] [1430/2639] eta: 0:58:28 lr: 4.4859668403432095e-05 loss: 0.1012 (0.1357) time: 2.8978 data: 0.0076 max mem: 33369 +Epoch: [4] [1440/2639] eta: 0:57:59 lr: 4.485535370610431e-05 loss: 0.1049 (0.1357) time: 2.9032 data: 0.0081 max mem: 33369 +Epoch: [4] [1450/2639] eta: 0:57:30 lr: 4.4851038962660865e-05 loss: 0.1200 (0.1357) time: 2.9064 data: 0.0080 max mem: 33369 +Epoch: [4] [1460/2639] eta: 0:57:02 lr: 4.484672417309632e-05 loss: 0.1177 (0.1356) time: 2.9316 data: 0.0078 max mem: 33369 +Epoch: [4] [1470/2639] eta: 0:56:32 lr: 4.484240933740526e-05 loss: 0.1177 (0.1355) time: 2.9250 data: 0.0082 max mem: 33369 +Epoch: [4] [1480/2639] eta: 0:56:03 lr: 4.483809445558226e-05 loss: 0.1290 (0.1355) time: 2.8966 data: 0.0078 max mem: 33369 +Epoch: [4] [1490/2639] eta: 0:55:34 lr: 4.483377952762189e-05 loss: 0.1334 (0.1355) time: 2.9104 data: 0.0074 max mem: 33369 +Epoch: [4] [1500/2639] eta: 0:55:05 lr: 4.4829464553518734e-05 loss: 0.1148 (0.1354) time: 2.8794 data: 0.0076 max mem: 33369 +Epoch: [4] [1510/2639] eta: 0:54:36 lr: 4.482514953326736e-05 loss: 0.1321 (0.1355) time: 2.8743 data: 0.0079 max mem: 33369 +Epoch: [4] [1520/2639] eta: 0:54:06 lr: 4.4820834466862323e-05 loss: 0.1417 (0.1355) time: 2.8661 data: 0.0077 max mem: 33369 +Epoch: [4] [1530/2639] eta: 0:53:37 lr: 4.481651935429821e-05 loss: 0.1403 (0.1356) time: 2.8638 data: 0.0076 max mem: 33369 +Epoch: [4] [1540/2639] eta: 0:53:08 lr: 4.481220419556958e-05 loss: 0.1147 (0.1355) time: 2.8817 data: 0.0076 max mem: 33369 +Epoch: [4] [1550/2639] eta: 0:52:39 lr: 4.4807888990671e-05 loss: 0.1248 (0.1355) time: 2.8894 data: 0.0075 max mem: 33369 +Epoch: [4] [1560/2639] eta: 0:52:10 lr: 4.480357373959704e-05 loss: 0.1243 (0.1355) time: 2.9155 data: 0.0075 max mem: 33369 +Epoch: [4] [1570/2639] eta: 0:51:41 lr: 4.479925844234227e-05 loss: 0.1285 (0.1356) time: 2.8874 data: 0.0076 max mem: 33369 +Epoch: [4] [1580/2639] eta: 0:51:12 lr: 4.479494309890123e-05 loss: 0.1338 (0.1355) time: 2.8715 data: 0.0076 max mem: 33369 +Epoch: [4] [1590/2639] eta: 0:50:43 lr: 4.4790627709268505e-05 loss: 0.1237 (0.1355) time: 2.8817 data: 0.0075 max mem: 33369 +Epoch: [4] [1600/2639] eta: 0:50:14 lr: 4.478631227343865e-05 loss: 0.1312 (0.1356) time: 2.8812 data: 0.0076 max mem: 33369 +Epoch: [4] [1610/2639] eta: 0:49:45 lr: 4.478199679140622e-05 loss: 0.1339 (0.1355) time: 2.9081 data: 0.0076 max mem: 33369 +Epoch: [4] [1620/2639] eta: 0:49:15 lr: 4.4777681263165776e-05 loss: 0.1209 (0.1354) time: 2.8900 data: 0.0075 max mem: 33369 +Epoch: [4] [1630/2639] eta: 0:48:46 lr: 4.477336568871187e-05 loss: 0.1155 (0.1353) time: 2.8671 data: 0.0073 max mem: 33369 +Epoch: [4] [1640/2639] eta: 0:48:17 lr: 4.476905006803906e-05 loss: 0.1154 (0.1353) time: 2.9061 data: 0.0073 max mem: 33369 +Epoch: [4] [1650/2639] eta: 0:47:48 lr: 4.476473440114191e-05 loss: 0.1264 (0.1355) time: 2.9183 data: 0.0076 max mem: 33369 +Epoch: [4] [1660/2639] eta: 0:47:20 lr: 4.476041868801497e-05 loss: 0.1329 (0.1354) time: 2.9470 data: 0.0074 max mem: 33369 +Epoch: [4] [1670/2639] eta: 0:46:51 lr: 4.475610292865277e-05 loss: 0.1279 (0.1355) time: 2.9098 data: 0.0072 max mem: 33369 +Epoch: [4] [1680/2639] eta: 0:46:22 lr: 4.4751787123049884e-05 loss: 0.1178 (0.1353) time: 2.9027 data: 0.0074 max mem: 33369 +Epoch: [4] [1690/2639] eta: 0:45:53 lr: 4.4747471271200866e-05 loss: 0.1272 (0.1354) time: 2.9587 data: 0.0073 max mem: 33369 +Epoch: [4] [1700/2639] eta: 0:45:24 lr: 4.4743155373100245e-05 loss: 0.1333 (0.1354) time: 2.9236 data: 0.0072 max mem: 33369 +Epoch: [4] [1710/2639] eta: 0:44:56 lr: 4.473883942874257e-05 loss: 0.1343 (0.1355) time: 2.9356 data: 0.0073 max mem: 33369 +Epoch: [4] [1720/2639] eta: 0:44:27 lr: 4.473452343812241e-05 loss: 0.1343 (0.1355) time: 2.9482 data: 0.0077 max mem: 33369 +Epoch: [4] [1730/2639] eta: 0:43:58 lr: 4.473020740123429e-05 loss: 0.1254 (0.1355) time: 2.9365 data: 0.0076 max mem: 33369 +Epoch: [4] [1740/2639] eta: 0:43:29 lr: 4.472589131807276e-05 loss: 0.1182 (0.1355) time: 2.9529 data: 0.0073 max mem: 33369 +Epoch: [4] [1750/2639] eta: 0:43:00 lr: 4.472157518863234e-05 loss: 0.1306 (0.1355) time: 2.9094 data: 0.0079 max mem: 33369 +Epoch: [4] [1760/2639] eta: 0:42:31 lr: 4.471725901290761e-05 loss: 0.1326 (0.1357) time: 2.8983 data: 0.0080 max mem: 33369 +Epoch: [4] [1770/2639] eta: 0:42:02 lr: 4.471294279089308e-05 loss: 0.1386 (0.1357) time: 2.9215 data: 0.0077 max mem: 33369 +Epoch: [4] [1780/2639] eta: 0:41:33 lr: 4.470862652258331e-05 loss: 0.1155 (0.1356) time: 2.9047 data: 0.0076 max mem: 33369 +Epoch: [4] [1790/2639] eta: 0:41:04 lr: 4.470431020797281e-05 loss: 0.1181 (0.1355) time: 2.9035 data: 0.0079 max mem: 33369 +Epoch: [4] [1800/2639] eta: 0:40:35 lr: 4.4699993847056146e-05 loss: 0.1277 (0.1356) time: 2.9148 data: 0.0081 max mem: 33369 +Epoch: [4] [1810/2639] eta: 0:40:06 lr: 4.4695677439827824e-05 loss: 0.1225 (0.1355) time: 2.9329 data: 0.0076 max mem: 33369 +Epoch: [4] [1820/2639] eta: 0:39:37 lr: 4.469136098628241e-05 loss: 0.1302 (0.1355) time: 2.9442 data: 0.0079 max mem: 33369 +Epoch: [4] [1830/2639] eta: 0:39:09 lr: 4.468704448641441e-05 loss: 0.1302 (0.1355) time: 2.9599 data: 0.0077 max mem: 33369 +Epoch: [4] [1840/2639] eta: 0:38:40 lr: 4.468272794021836e-05 loss: 0.1298 (0.1355) time: 2.9505 data: 0.0076 max mem: 33369 +Epoch: [4] [1850/2639] eta: 0:38:11 lr: 4.4678411347688796e-05 loss: 0.1312 (0.1356) time: 2.9572 data: 0.0081 max mem: 33369 +Epoch: [4] [1860/2639] eta: 0:37:42 lr: 4.4674094708820254e-05 loss: 0.1092 (0.1354) time: 2.9681 data: 0.0079 max mem: 33369 +Epoch: [4] [1870/2639] eta: 0:37:13 lr: 4.466977802360724e-05 loss: 0.1092 (0.1354) time: 2.9447 data: 0.0077 max mem: 33369 +Epoch: [4] [1880/2639] eta: 0:36:44 lr: 4.466546129204429e-05 loss: 0.1318 (0.1354) time: 2.9265 data: 0.0076 max mem: 33369 +Epoch: [4] [1890/2639] eta: 0:36:15 lr: 4.466114451412594e-05 loss: 0.1391 (0.1354) time: 2.9119 data: 0.0076 max mem: 33369 +Epoch: [4] [1900/2639] eta: 0:35:46 lr: 4.46568276898467e-05 loss: 0.1384 (0.1354) time: 2.9087 data: 0.0074 max mem: 33369 +Epoch: [4] [1910/2639] eta: 0:35:17 lr: 4.4652510819201105e-05 loss: 0.1231 (0.1355) time: 2.9005 data: 0.0073 max mem: 33369 +Epoch: [4] [1920/2639] eta: 0:34:48 lr: 4.464819390218366e-05 loss: 0.1274 (0.1354) time: 2.8907 data: 0.0076 max mem: 33369 +Epoch: [4] [1930/2639] eta: 0:34:19 lr: 4.46438769387889e-05 loss: 0.1274 (0.1354) time: 2.8870 data: 0.0075 max mem: 33369 +Epoch: [4] [1940/2639] eta: 0:33:50 lr: 4.463955992901133e-05 loss: 0.1323 (0.1354) time: 2.8715 data: 0.0073 max mem: 33369 +Epoch: [4] [1950/2639] eta: 0:33:21 lr: 4.463524287284548e-05 loss: 0.1331 (0.1354) time: 2.9152 data: 0.0077 max mem: 33369 +Epoch: [4] [1960/2639] eta: 0:32:52 lr: 4.463092577028586e-05 loss: 0.1231 (0.1354) time: 2.9406 data: 0.0077 max mem: 33369 +Epoch: [4] [1970/2639] eta: 0:32:23 lr: 4.462660862132699e-05 loss: 0.1293 (0.1355) time: 2.9154 data: 0.0075 max mem: 33369 +Epoch: [4] [1980/2639] eta: 0:31:54 lr: 4.462229142596337e-05 loss: 0.1415 (0.1356) time: 2.9479 data: 0.0075 max mem: 33369 +Epoch: [4] [1990/2639] eta: 0:31:25 lr: 4.461797418418953e-05 loss: 0.1227 (0.1355) time: 2.9338 data: 0.0076 max mem: 33369 +Epoch: [4] [2000/2639] eta: 0:30:56 lr: 4.461365689599997e-05 loss: 0.1135 (0.1354) time: 2.8971 data: 0.0075 max mem: 33369 +Epoch: [4] [2010/2639] eta: 0:30:27 lr: 4.460933956138921e-05 loss: 0.1249 (0.1354) time: 2.9085 data: 0.0075 max mem: 33369 +Epoch: [4] [2020/2639] eta: 0:29:58 lr: 4.460502218035175e-05 loss: 0.1249 (0.1354) time: 2.8993 data: 0.0076 max mem: 33369 +Epoch: [4] [2030/2639] eta: 0:29:29 lr: 4.4600704752882104e-05 loss: 0.1218 (0.1355) time: 2.8910 data: 0.0080 max mem: 33369 +Epoch: [4] [2040/2639] eta: 0:29:00 lr: 4.459638727897476e-05 loss: 0.1218 (0.1355) time: 2.9175 data: 0.0086 max mem: 33369 +Epoch: [4] [2050/2639] eta: 0:28:31 lr: 4.459206975862426e-05 loss: 0.1126 (0.1353) time: 2.9452 data: 0.0083 max mem: 33369 +Epoch: [4] [2060/2639] eta: 0:28:02 lr: 4.4587752191825074e-05 loss: 0.1119 (0.1353) time: 2.9151 data: 0.0079 max mem: 33369 +Epoch: [4] [2070/2639] eta: 0:27:32 lr: 4.458343457857172e-05 loss: 0.1256 (0.1353) time: 2.8536 data: 0.0078 max mem: 33369 +Epoch: [4] [2080/2639] eta: 0:27:03 lr: 4.457911691885869e-05 loss: 0.1093 (0.1352) time: 2.8481 data: 0.0079 max mem: 33369 +Epoch: [4] [2090/2639] eta: 0:26:34 lr: 4.4574799212680496e-05 loss: 0.1093 (0.1352) time: 2.8671 data: 0.0080 max mem: 33369 +Epoch: [4] [2100/2639] eta: 0:26:05 lr: 4.4570481460031635e-05 loss: 0.1156 (0.1352) time: 2.8736 data: 0.0080 max mem: 33369 +Epoch: [4] [2110/2639] eta: 0:25:36 lr: 4.45661636609066e-05 loss: 0.1167 (0.1352) time: 2.8859 data: 0.0078 max mem: 33369 +Epoch: [4] [2120/2639] eta: 0:25:07 lr: 4.456184581529988e-05 loss: 0.1288 (0.1352) time: 2.8770 data: 0.0072 max mem: 33369 +Epoch: [4] [2130/2639] eta: 0:24:38 lr: 4.4557527923205985e-05 loss: 0.1141 (0.1351) time: 2.8838 data: 0.0073 max mem: 33369 +Epoch: [4] [2140/2639] eta: 0:24:09 lr: 4.45532099846194e-05 loss: 0.1112 (0.1350) time: 2.9051 data: 0.0075 max mem: 33369 +Epoch: [4] [2150/2639] eta: 0:23:40 lr: 4.454889199953462e-05 loss: 0.1247 (0.1351) time: 2.8968 data: 0.0076 max mem: 33369 +Epoch: [4] [2160/2639] eta: 0:23:11 lr: 4.454457396794614e-05 loss: 0.1304 (0.1350) time: 2.8996 data: 0.0077 max mem: 33369 +Epoch: [4] [2170/2639] eta: 0:22:41 lr: 4.4540255889848445e-05 loss: 0.1147 (0.1351) time: 2.8736 data: 0.0079 max mem: 33369 +Epoch: [4] [2180/2639] eta: 0:22:12 lr: 4.453593776523603e-05 loss: 0.1243 (0.1351) time: 2.8695 data: 0.0081 max mem: 33369 +Epoch: [4] [2190/2639] eta: 0:21:43 lr: 4.453161959410338e-05 loss: 0.1243 (0.1351) time: 2.8812 data: 0.0085 max mem: 33369 +Epoch: [4] [2200/2639] eta: 0:21:14 lr: 4.4527301376444975e-05 loss: 0.1104 (0.1350) time: 2.9106 data: 0.0086 max mem: 33369 +Epoch: [4] [2210/2639] eta: 0:20:45 lr: 4.45229831122553e-05 loss: 0.1241 (0.1350) time: 2.9154 data: 0.0081 max mem: 33369 +Epoch: [4] [2220/2639] eta: 0:20:16 lr: 4.451866480152885e-05 loss: 0.1256 (0.1350) time: 2.8715 data: 0.0080 max mem: 33369 +Epoch: [4] [2230/2639] eta: 0:19:47 lr: 4.451434644426011e-05 loss: 0.1369 (0.1350) time: 2.8700 data: 0.0084 max mem: 33369 +Epoch: [4] [2240/2639] eta: 0:19:18 lr: 4.451002804044355e-05 loss: 0.1373 (0.1351) time: 2.8553 data: 0.0082 max mem: 33369 +Epoch: [4] [2250/2639] eta: 0:18:49 lr: 4.4505709590073645e-05 loss: 0.1394 (0.1351) time: 2.8407 data: 0.0075 max mem: 33369 +Epoch: [4] [2260/2639] eta: 0:18:20 lr: 4.4501391093144895e-05 loss: 0.1304 (0.1351) time: 2.8601 data: 0.0074 max mem: 33369 +Epoch: [4] [2270/2639] eta: 0:17:51 lr: 4.4497072549651756e-05 loss: 0.1297 (0.1351) time: 2.9164 data: 0.0074 max mem: 33369 +Epoch: [4] [2280/2639] eta: 0:17:22 lr: 4.4492753959588725e-05 loss: 0.1295 (0.1351) time: 2.9465 data: 0.0074 max mem: 33369 +Epoch: [4] [2290/2639] eta: 0:16:53 lr: 4.448843532295026e-05 loss: 0.1295 (0.1351) time: 2.9311 data: 0.0073 max mem: 33369 +Epoch: [4] [2300/2639] eta: 0:16:24 lr: 4.4484116639730836e-05 loss: 0.1289 (0.1351) time: 2.8921 data: 0.0073 max mem: 33369 +Epoch: [4] [2310/2639] eta: 0:15:55 lr: 4.447979790992494e-05 loss: 0.1251 (0.1351) time: 2.8632 data: 0.0071 max mem: 33369 +Epoch: [4] [2320/2639] eta: 0:15:26 lr: 4.447547913352703e-05 loss: 0.1303 (0.1351) time: 2.8807 data: 0.0071 max mem: 33369 +Epoch: [4] [2330/2639] eta: 0:14:56 lr: 4.447116031053158e-05 loss: 0.1272 (0.1351) time: 2.8740 data: 0.0075 max mem: 33369 +Epoch: [4] [2340/2639] eta: 0:14:27 lr: 4.446684144093306e-05 loss: 0.1150 (0.1350) time: 2.8831 data: 0.0074 max mem: 33369 +Epoch: [4] [2350/2639] eta: 0:13:58 lr: 4.4462522524725944e-05 loss: 0.1191 (0.1350) time: 2.8663 data: 0.0076 max mem: 33369 +Epoch: [4] [2360/2639] eta: 0:13:29 lr: 4.445820356190469e-05 loss: 0.1334 (0.1351) time: 2.8338 data: 0.0078 max mem: 33369 +Epoch: [4] [2370/2639] eta: 0:13:00 lr: 4.445388455246376e-05 loss: 0.1156 (0.1350) time: 2.8885 data: 0.0073 max mem: 33369 +Epoch: [4] [2380/2639] eta: 0:12:31 lr: 4.4449565496397634e-05 loss: 0.1136 (0.1350) time: 2.8655 data: 0.0072 max mem: 33369 +Epoch: [4] [2390/2639] eta: 0:12:02 lr: 4.4445246393700756e-05 loss: 0.1233 (0.1350) time: 2.8755 data: 0.0078 max mem: 33369 +Epoch: [4] [2400/2639] eta: 0:11:33 lr: 4.44409272443676e-05 loss: 0.1268 (0.1351) time: 2.9133 data: 0.0080 max mem: 33369 +Epoch: [4] [2410/2639] eta: 0:11:04 lr: 4.443660804839262e-05 loss: 0.1253 (0.1350) time: 2.8937 data: 0.0076 max mem: 33369 +Epoch: [4] [2420/2639] eta: 0:10:35 lr: 4.443228880577027e-05 loss: 0.1157 (0.1350) time: 2.9006 data: 0.0078 max mem: 33369 +Epoch: [4] [2430/2639] eta: 0:10:06 lr: 4.442796951649503e-05 loss: 0.1155 (0.1351) time: 2.8883 data: 0.0079 max mem: 33369 +Epoch: [4] [2440/2639] eta: 0:09:37 lr: 4.442365018056132e-05 loss: 0.1473 (0.1352) time: 2.8937 data: 0.0077 max mem: 33369 +Epoch: [4] [2450/2639] eta: 0:09:08 lr: 4.441933079796363e-05 loss: 0.1360 (0.1352) time: 2.8929 data: 0.0074 max mem: 33369 +Epoch: [4] [2460/2639] eta: 0:08:39 lr: 4.44150113686964e-05 loss: 0.1212 (0.1353) time: 2.8838 data: 0.0077 max mem: 33369 +Epoch: [4] [2470/2639] eta: 0:08:10 lr: 4.441069189275408e-05 loss: 0.1212 (0.1353) time: 2.9044 data: 0.0079 max mem: 33369 +Epoch: [4] [2480/2639] eta: 0:07:41 lr: 4.440637237013112e-05 loss: 0.1354 (0.1354) time: 2.9194 data: 0.0081 max mem: 33369 +Epoch: [4] [2490/2639] eta: 0:07:12 lr: 4.440205280082198e-05 loss: 0.1441 (0.1354) time: 2.8938 data: 0.0079 max mem: 33369 +Epoch: [4] [2500/2639] eta: 0:06:43 lr: 4.43977331848211e-05 loss: 0.1393 (0.1354) time: 2.8617 data: 0.0079 max mem: 33369 +Epoch: [4] [2510/2639] eta: 0:06:14 lr: 4.4393413522122936e-05 loss: 0.1210 (0.1353) time: 2.8863 data: 0.0081 max mem: 33369 +Epoch: [4] [2520/2639] eta: 0:05:45 lr: 4.438909381272192e-05 loss: 0.1301 (0.1354) time: 2.9311 data: 0.0077 max mem: 33369 +Epoch: [4] [2530/2639] eta: 0:05:16 lr: 4.4384774056612516e-05 loss: 0.1271 (0.1353) time: 2.9133 data: 0.0078 max mem: 33369 +Epoch: [4] [2540/2639] eta: 0:04:47 lr: 4.438045425378915e-05 loss: 0.1275 (0.1354) time: 2.8788 data: 0.0078 max mem: 33369 +Epoch: [4] [2550/2639] eta: 0:04:18 lr: 4.437613440424628e-05 loss: 0.1424 (0.1354) time: 2.8912 data: 0.0076 max mem: 33369 +Epoch: [4] [2560/2639] eta: 0:03:49 lr: 4.437181450797833e-05 loss: 0.1228 (0.1353) time: 2.8904 data: 0.0077 max mem: 33369 +Epoch: [4] [2570/2639] eta: 0:03:20 lr: 4.436749456497975e-05 loss: 0.1316 (0.1353) time: 2.8813 data: 0.0075 max mem: 33369 +Epoch: [4] [2580/2639] eta: 0:02:51 lr: 4.436317457524499e-05 loss: 0.1156 (0.1353) time: 2.8783 data: 0.0078 max mem: 33369 +Epoch: [4] [2590/2639] eta: 0:02:22 lr: 4.4358854538768466e-05 loss: 0.1116 (0.1352) time: 2.8629 data: 0.0078 max mem: 33369 +Epoch: [4] [2600/2639] eta: 0:01:53 lr: 4.435453445554463e-05 loss: 0.1044 (0.1351) time: 2.8428 data: 0.0072 max mem: 33369 +Epoch: [4] [2610/2639] eta: 0:01:24 lr: 4.435021432556791e-05 loss: 0.0994 (0.1350) time: 2.8894 data: 0.0074 max mem: 33369 +Epoch: [4] [2620/2639] eta: 0:00:55 lr: 4.434589414883274e-05 loss: 0.1160 (0.1350) time: 2.9234 data: 0.0078 max mem: 33369 +Epoch: [4] [2630/2639] eta: 0:00:26 lr: 4.434157392533355e-05 loss: 0.1161 (0.1350) time: 2.9080 data: 0.0075 max mem: 33369 +Epoch: [4] Total time: 2:07:36 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 2:31:54 time: 3.5424 data: 3.4509 max mem: 33369 +Test: [ 100/2573] eta: 0:04:36 time: 0.0779 data: 0.0014 max mem: 33369 +Test: [ 200/2573] eta: 0:03:48 time: 0.0794 data: 0.0015 max mem: 33369 +Test: [ 300/2573] eta: 0:03:25 time: 0.0814 data: 0.0015 max mem: 33369 +Test: [ 400/2573] eta: 0:03:10 time: 0.0820 data: 0.0014 max mem: 33369 +Test: [ 500/2573] eta: 0:02:58 time: 0.0804 data: 0.0015 max mem: 33369 +Test: [ 600/2573] eta: 0:02:48 time: 0.0805 data: 0.0014 max mem: 33369 +Test: [ 700/2573] eta: 0:02:39 time: 0.0804 data: 0.0015 max mem: 33369 +Test: [ 800/2573] eta: 0:02:29 time: 0.0828 data: 0.0014 max mem: 33369 +Test: [ 900/2573] eta: 0:02:20 time: 0.0813 data: 0.0015 max mem: 33369 +Test: [1000/2573] eta: 0:02:11 time: 0.0798 data: 0.0015 max mem: 33369 +Test: [1100/2573] eta: 0:02:02 time: 0.0801 data: 0.0014 max mem: 33369 +Test: [1200/2573] eta: 0:01:54 time: 0.0799 data: 0.0016 max mem: 33369 +Test: [1300/2573] eta: 0:01:45 time: 0.0808 data: 0.0014 max mem: 33369 +Test: [1400/2573] eta: 0:01:37 time: 0.0790 data: 0.0015 max mem: 33369 +Test: [1500/2573] eta: 0:01:28 time: 0.0808 data: 0.0014 max mem: 33369 +Test: [1600/2573] eta: 0:01:20 time: 0.0835 data: 0.0014 max mem: 33369 +Test: [1700/2573] eta: 0:01:12 time: 0.0794 data: 0.0014 max mem: 33369 +Test: [1800/2573] eta: 0:01:03 time: 0.0828 data: 0.0015 max mem: 33369 +Test: [1900/2573] eta: 0:00:55 time: 0.0790 data: 0.0014 max mem: 33369 +Test: [2000/2573] eta: 0:00:47 time: 0.0799 data: 0.0014 max mem: 33369 +Test: [2100/2573] eta: 0:00:38 time: 0.0821 data: 0.0014 max mem: 33369 +Test: [2200/2573] eta: 0:00:30 time: 0.0827 data: 0.0014 max mem: 33369 +Test: [2300/2573] eta: 0:00:22 time: 0.0829 data: 0.0014 max mem: 33369 +Test: [2400/2573] eta: 0:00:14 time: 0.0788 data: 0.0014 max mem: 33369 +Test: [2500/2573] eta: 0:00:05 time: 0.0811 data: 0.0014 max mem: 33369 +Test: Total time: 0:03:31 +Final results: +Mean IoU is 48.80 + + precision@0.5 = 54.15 + precision@0.6 = 47.49 + precision@0.7 = 39.71 + precision@0.8 = 28.76 + precision@0.9 = 11.07 + overall IoU = 50.87 + +Average object IoU 48.796783067743256 +Overall IoU 50.8708381652832 +Better epoch: 4 + +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [5] [ 0/2639] eta: 3:52:24 lr: 4.433768568419645e-05 loss: 0.1288 (0.1288) time: 5.2842 data: 2.1862 max mem: 33369 +Epoch: [5] [ 10/2639] eta: 2:16:51 lr: 4.433336537183029e-05 loss: 0.1084 (0.1205) time: 3.1233 data: 0.2062 max mem: 33369 +Epoch: [5] [ 20/2639] eta: 2:12:22 lr: 4.432904501268396e-05 loss: 0.1084 (0.1206) time: 2.9200 data: 0.0077 max mem: 33369 +Epoch: [5] [ 30/2639] eta: 2:10:21 lr: 4.432472460675189e-05 loss: 0.1039 (0.1176) time: 2.9287 data: 0.0074 max mem: 33369 +Epoch: [5] [ 40/2639] eta: 2:08:09 lr: 4.43204041540285e-05 loss: 0.1026 (0.1208) time: 2.8811 data: 0.0084 max mem: 33369 +Epoch: [5] [ 50/2639] eta: 2:07:12 lr: 4.431608365450822e-05 loss: 0.1109 (0.1227) time: 2.8713 data: 0.0083 max mem: 33369 +Epoch: [5] [ 60/2639] eta: 2:06:11 lr: 4.431176310818548e-05 loss: 0.1190 (0.1214) time: 2.8889 data: 0.0077 max mem: 33369 +Epoch: [5] [ 70/2639] eta: 2:05:51 lr: 4.4307442515054684e-05 loss: 0.1069 (0.1185) time: 2.9170 data: 0.0077 max mem: 33369 +Epoch: [5] [ 80/2639] eta: 2:04:55 lr: 4.430312187511028e-05 loss: 0.1089 (0.1182) time: 2.9080 data: 0.0078 max mem: 33369 +Epoch: [5] [ 90/2639] eta: 2:03:57 lr: 4.429880118834666e-05 loss: 0.1316 (0.1202) time: 2.8410 data: 0.0079 max mem: 33369 +Epoch: [5] [ 100/2639] eta: 2:03:42 lr: 4.429448045475826e-05 loss: 0.1226 (0.1190) time: 2.9004 data: 0.0078 max mem: 33369 +Epoch: [5] [ 110/2639] eta: 2:03:00 lr: 4.429015967433949e-05 loss: 0.1108 (0.1197) time: 2.9216 data: 0.0076 max mem: 33369 +Epoch: [5] [ 120/2639] eta: 2:02:47 lr: 4.428583884708477e-05 loss: 0.1051 (0.1184) time: 2.9316 data: 0.0076 max mem: 33369 +Epoch: [5] [ 130/2639] eta: 2:02:29 lr: 4.4281517972988514e-05 loss: 0.1006 (0.1184) time: 2.9891 data: 0.0076 max mem: 33369 +Epoch: [5] [ 140/2639] eta: 2:01:46 lr: 4.4277197052045135e-05 loss: 0.1135 (0.1188) time: 2.9178 data: 0.0078 max mem: 33369 +Epoch: [5] [ 150/2639] eta: 2:01:16 lr: 4.427287608424906e-05 loss: 0.1137 (0.1192) time: 2.8865 data: 0.0083 max mem: 33369 +Epoch: [5] [ 160/2639] eta: 2:00:42 lr: 4.426855506959466e-05 loss: 0.1209 (0.1199) time: 2.9058 data: 0.0083 max mem: 33369 +Epoch: [5] [ 170/2639] eta: 2:00:00 lr: 4.4264234008076386e-05 loss: 0.1223 (0.1197) time: 2.8624 data: 0.0079 max mem: 33369 +Epoch: [5] [ 180/2639] eta: 1:59:33 lr: 4.425991289968863e-05 loss: 0.1067 (0.1193) time: 2.8819 data: 0.0077 max mem: 33369 +Epoch: [5] [ 190/2639] eta: 1:58:58 lr: 4.425559174442579e-05 loss: 0.1057 (0.1189) time: 2.9007 data: 0.0078 max mem: 33369 +Epoch: [5] [ 200/2639] eta: 1:58:26 lr: 4.425127054228229e-05 loss: 0.1072 (0.1198) time: 2.8825 data: 0.0080 max mem: 33369 +Epoch: [5] [ 210/2639] eta: 1:57:58 lr: 4.424694929325253e-05 loss: 0.1171 (0.1203) time: 2.9070 data: 0.0084 max mem: 33369 +Epoch: [5] [ 220/2639] eta: 1:57:31 lr: 4.4242627997330896e-05 loss: 0.1369 (0.1207) time: 2.9283 data: 0.0081 max mem: 33369 +Epoch: [5] [ 230/2639] eta: 1:57:02 lr: 4.4238306654511814e-05 loss: 0.1303 (0.1211) time: 2.9263 data: 0.0076 max mem: 33369 +Epoch: [5] [ 240/2639] eta: 1:56:26 lr: 4.423398526478967e-05 loss: 0.1304 (0.1225) time: 2.8837 data: 0.0077 max mem: 33369 +Epoch: [5] [ 250/2639] eta: 1:55:58 lr: 4.422966382815888e-05 loss: 0.1240 (0.1222) time: 2.8846 data: 0.0078 max mem: 33369 +Epoch: [5] [ 260/2639] eta: 1:55:23 lr: 4.4225342344613816e-05 loss: 0.1062 (0.1217) time: 2.8871 data: 0.0081 max mem: 33369 +Epoch: [5] [ 270/2639] eta: 1:54:51 lr: 4.4221020814148896e-05 loss: 0.0986 (0.1220) time: 2.8638 data: 0.0083 max mem: 33369 +Epoch: [5] [ 280/2639] eta: 1:54:16 lr: 4.4216699236758506e-05 loss: 0.1134 (0.1225) time: 2.8574 data: 0.0081 max mem: 33369 +Epoch: [5] [ 290/2639] eta: 1:53:53 lr: 4.421237761243704e-05 loss: 0.1134 (0.1220) time: 2.9082 data: 0.0080 max mem: 33369 +Epoch: [5] [ 300/2639] eta: 1:53:26 lr: 4.420805594117891e-05 loss: 0.1123 (0.1222) time: 2.9540 data: 0.0082 max mem: 33369 +Epoch: [5] [ 310/2639] eta: 1:52:55 lr: 4.420373422297848e-05 loss: 0.1177 (0.1220) time: 2.9153 data: 0.0081 max mem: 33369 +Epoch: [5] [ 320/2639] eta: 1:52:23 lr: 4.4199412457830166e-05 loss: 0.1122 (0.1217) time: 2.8798 data: 0.0078 max mem: 33369 +Epoch: [5] [ 330/2639] eta: 1:51:51 lr: 4.419509064572833e-05 loss: 0.1178 (0.1220) time: 2.8662 data: 0.0078 max mem: 33369 +Epoch: [5] [ 340/2639] eta: 1:51:22 lr: 4.419076878666738e-05 loss: 0.1268 (0.1241) time: 2.8831 data: 0.0077 max mem: 33369 +Epoch: [5] [ 350/2639] eta: 1:50:57 lr: 4.41864468806417e-05 loss: 0.1387 (0.1242) time: 2.9330 data: 0.0078 max mem: 33369 +Epoch: [5] [ 360/2639] eta: 1:50:26 lr: 4.4182124927645666e-05 loss: 0.1387 (0.1250) time: 2.9263 data: 0.0079 max mem: 33369 +Epoch: [5] [ 370/2639] eta: 1:49:55 lr: 4.417780292767368e-05 loss: 0.1286 (0.1253) time: 2.8809 data: 0.0077 max mem: 33369 +Epoch: [5] [ 380/2639] eta: 1:49:25 lr: 4.417348088072011e-05 loss: 0.1162 (0.1256) time: 2.8823 data: 0.0080 max mem: 33369 +Epoch: [5] [ 390/2639] eta: 1:48:55 lr: 4.4169158786779335e-05 loss: 0.1250 (0.1258) time: 2.8919 data: 0.0081 max mem: 33369 +Epoch: [5] [ 400/2639] eta: 1:48:25 lr: 4.416483664584575e-05 loss: 0.1107 (0.1253) time: 2.8955 data: 0.0080 max mem: 33369 +Epoch: [5] [ 410/2639] eta: 1:47:57 lr: 4.416051445791371e-05 loss: 0.1189 (0.1257) time: 2.9077 data: 0.0079 max mem: 33369 +Epoch: [5] [ 420/2639] eta: 1:47:27 lr: 4.415619222297763e-05 loss: 0.1131 (0.1253) time: 2.8985 data: 0.0083 max mem: 33369 +Epoch: [5] [ 430/2639] eta: 1:46:58 lr: 4.4151869941031854e-05 loss: 0.1125 (0.1259) time: 2.8976 data: 0.0090 max mem: 33369 +Epoch: [5] [ 440/2639] eta: 1:46:28 lr: 4.4147547612070764e-05 loss: 0.1343 (0.1258) time: 2.9036 data: 0.0086 max mem: 33369 +Epoch: [5] [ 450/2639] eta: 1:46:01 lr: 4.414322523608875e-05 loss: 0.1262 (0.1257) time: 2.9142 data: 0.0082 max mem: 33369 +Epoch: [5] [ 460/2639] eta: 1:45:35 lr: 4.413890281308017e-05 loss: 0.1181 (0.1256) time: 2.9560 data: 0.0082 max mem: 33369 +Epoch: [5] [ 470/2639] eta: 1:45:03 lr: 4.41345803430394e-05 loss: 0.1294 (0.1257) time: 2.9029 data: 0.0082 max mem: 33369 +Epoch: [5] [ 480/2639] eta: 1:44:34 lr: 4.41302578259608e-05 loss: 0.1056 (0.1252) time: 2.8791 data: 0.0081 max mem: 33369 +Epoch: [5] [ 490/2639] eta: 1:44:03 lr: 4.4125935261838754e-05 loss: 0.1100 (0.1254) time: 2.8863 data: 0.0081 max mem: 33369 +Epoch: [5] [ 500/2639] eta: 1:43:32 lr: 4.4121612650667624e-05 loss: 0.1118 (0.1251) time: 2.8528 data: 0.0080 max mem: 33369 +Epoch: [5] [ 510/2639] eta: 1:43:02 lr: 4.4117289992441774e-05 loss: 0.1016 (0.1250) time: 2.8696 data: 0.0076 max mem: 33369 +Epoch: [5] [ 520/2639] eta: 1:42:35 lr: 4.4112967287155566e-05 loss: 0.0985 (0.1247) time: 2.9276 data: 0.0077 max mem: 33369 +Epoch: [5] [ 530/2639] eta: 1:42:05 lr: 4.4108644534803376e-05 loss: 0.0960 (0.1245) time: 2.9166 data: 0.0080 max mem: 33369 +Epoch: [5] [ 540/2639] eta: 1:41:37 lr: 4.4104321735379546e-05 loss: 0.1066 (0.1247) time: 2.8979 data: 0.0080 max mem: 33369 +Epoch: [5] [ 550/2639] eta: 1:41:08 lr: 4.409999888887846e-05 loss: 0.1288 (0.1251) time: 2.9242 data: 0.0078 max mem: 33369 +Epoch: [5] [ 560/2639] eta: 1:40:38 lr: 4.4095675995294454e-05 loss: 0.1287 (0.1249) time: 2.8912 data: 0.0079 max mem: 33369 +Epoch: [5] [ 570/2639] eta: 1:40:07 lr: 4.409135305462191e-05 loss: 0.1202 (0.1261) time: 2.8681 data: 0.0078 max mem: 33369 +Epoch: [5] [ 580/2639] eta: 1:39:39 lr: 4.408703006685517e-05 loss: 0.1070 (0.1255) time: 2.8911 data: 0.0080 max mem: 33369 +Epoch: [5] [ 590/2639] eta: 1:39:09 lr: 4.4082707031988595e-05 loss: 0.0976 (0.1256) time: 2.9001 data: 0.0083 max mem: 33369 +Epoch: [5] [ 600/2639] eta: 1:38:39 lr: 4.4078383950016536e-05 loss: 0.1225 (0.1253) time: 2.8868 data: 0.0081 max mem: 33369 +Epoch: [5] [ 610/2639] eta: 1:38:12 lr: 4.407406082093336e-05 loss: 0.1053 (0.1251) time: 2.9222 data: 0.0076 max mem: 33369 +Epoch: [5] [ 620/2639] eta: 1:37:45 lr: 4.4069737644733396e-05 loss: 0.1053 (0.1254) time: 2.9534 data: 0.0071 max mem: 33369 +Epoch: [5] [ 630/2639] eta: 1:37:18 lr: 4.406541442141101e-05 loss: 0.1258 (0.1252) time: 2.9603 data: 0.0072 max mem: 33369 +Epoch: [5] [ 640/2639] eta: 1:36:47 lr: 4.406109115096055e-05 loss: 0.1342 (0.1255) time: 2.9183 data: 0.0073 max mem: 33369 +Epoch: [5] [ 650/2639] eta: 1:36:17 lr: 4.405676783337636e-05 loss: 0.1316 (0.1256) time: 2.8702 data: 0.0078 max mem: 33369 +Epoch: [5] [ 660/2639] eta: 1:35:48 lr: 4.405244446865279e-05 loss: 0.1235 (0.1258) time: 2.8864 data: 0.0083 max mem: 33369 +Epoch: [5] [ 670/2639] eta: 1:35:18 lr: 4.4048121056784194e-05 loss: 0.1046 (0.1254) time: 2.8821 data: 0.0082 max mem: 33369 +Epoch: [5] [ 680/2639] eta: 1:34:48 lr: 4.404379759776489e-05 loss: 0.1009 (0.1254) time: 2.8690 data: 0.0080 max mem: 33369 +Epoch: [5] [ 690/2639] eta: 1:34:17 lr: 4.403947409158925e-05 loss: 0.1314 (0.1255) time: 2.8612 data: 0.0077 max mem: 33369 +Epoch: [5] [ 700/2639] eta: 1:33:48 lr: 4.4035150538251604e-05 loss: 0.0965 (0.1250) time: 2.8673 data: 0.0080 max mem: 33369 +Epoch: [5] [ 710/2639] eta: 1:33:19 lr: 4.403082693774629e-05 loss: 0.0944 (0.1248) time: 2.8972 data: 0.0084 max mem: 33369 +Epoch: [5] [ 720/2639] eta: 1:32:49 lr: 4.402650329006764e-05 loss: 0.1216 (0.1250) time: 2.8877 data: 0.0081 max mem: 33369 +Epoch: [5] [ 730/2639] eta: 1:32:19 lr: 4.4022179595210014e-05 loss: 0.1323 (0.1250) time: 2.8701 data: 0.0076 max mem: 33369 +Epoch: [5] [ 740/2639] eta: 1:31:50 lr: 4.401785585316773e-05 loss: 0.1047 (0.1249) time: 2.8845 data: 0.0075 max mem: 33369 +Epoch: [5] [ 750/2639] eta: 1:31:20 lr: 4.401353206393513e-05 loss: 0.1027 (0.1247) time: 2.8856 data: 0.0077 max mem: 33369 +Epoch: [5] [ 760/2639] eta: 1:30:51 lr: 4.4009208227506545e-05 loss: 0.1140 (0.1249) time: 2.8800 data: 0.0074 max mem: 33369 +Epoch: [5] [ 770/2639] eta: 1:30:22 lr: 4.400488434387631e-05 loss: 0.1205 (0.1250) time: 2.8969 data: 0.0072 max mem: 33369 +Epoch: [5] [ 780/2639] eta: 1:29:53 lr: 4.4000560413038755e-05 loss: 0.1372 (0.1251) time: 2.8993 data: 0.0073 max mem: 33369 +Epoch: [5] [ 790/2639] eta: 1:29:24 lr: 4.399623643498821e-05 loss: 0.1042 (0.1249) time: 2.8936 data: 0.0073 max mem: 33369 +Epoch: [5] [ 800/2639] eta: 1:28:55 lr: 4.3991912409719006e-05 loss: 0.0998 (0.1247) time: 2.8981 data: 0.0076 max mem: 33369 +Epoch: [5] [ 810/2639] eta: 1:28:26 lr: 4.398758833722546e-05 loss: 0.0985 (0.1245) time: 2.9136 data: 0.0079 max mem: 33369 +Epoch: [5] [ 820/2639] eta: 1:27:57 lr: 4.398326421750191e-05 loss: 0.1190 (0.1248) time: 2.9092 data: 0.0078 max mem: 33369 +Epoch: [5] [ 830/2639] eta: 1:27:28 lr: 4.397894005054268e-05 loss: 0.1291 (0.1248) time: 2.8869 data: 0.0075 max mem: 33369 +Epoch: [5] [ 840/2639] eta: 1:26:58 lr: 4.3974615836342096e-05 loss: 0.1002 (0.1248) time: 2.8829 data: 0.0076 max mem: 33369 +Epoch: [5] [ 850/2639] eta: 1:26:29 lr: 4.3970291574894465e-05 loss: 0.1110 (0.1248) time: 2.8975 data: 0.0080 max mem: 33369 +Epoch: [5] [ 860/2639] eta: 1:25:59 lr: 4.3965967266194126e-05 loss: 0.1080 (0.1248) time: 2.8849 data: 0.0078 max mem: 33369 +Epoch: [5] [ 870/2639] eta: 1:25:31 lr: 4.3961642910235386e-05 loss: 0.1075 (0.1248) time: 2.9012 data: 0.0075 max mem: 33369 +Epoch: [5] [ 880/2639] eta: 1:25:03 lr: 4.3957318507012566e-05 loss: 0.1099 (0.1246) time: 2.9350 data: 0.0076 max mem: 33369 +Epoch: [5] [ 890/2639] eta: 1:24:34 lr: 4.395299405651999e-05 loss: 0.1005 (0.1245) time: 2.9150 data: 0.0079 max mem: 33369 +Epoch: [5] [ 900/2639] eta: 1:24:07 lr: 4.3948669558751955e-05 loss: 0.1102 (0.1245) time: 2.9568 data: 0.0078 max mem: 33369 +Epoch: [5] [ 910/2639] eta: 1:23:40 lr: 4.39443450137028e-05 loss: 0.1174 (0.1248) time: 3.0018 data: 0.0075 max mem: 33369 +Epoch: [5] [ 920/2639] eta: 1:23:10 lr: 4.394002042136683e-05 loss: 0.1304 (0.1251) time: 2.9241 data: 0.0076 max mem: 33369 +Epoch: [5] [ 930/2639] eta: 1:22:41 lr: 4.393569578173834e-05 loss: 0.1358 (0.1251) time: 2.8944 data: 0.0079 max mem: 33369 +Epoch: [5] [ 940/2639] eta: 1:22:12 lr: 4.3931371094811655e-05 loss: 0.1075 (0.1251) time: 2.9064 data: 0.0080 max mem: 33369 +Epoch: [5] [ 950/2639] eta: 1:21:42 lr: 4.39270463605811e-05 loss: 0.1075 (0.1249) time: 2.8662 data: 0.0077 max mem: 33369 +Epoch: [5] [ 960/2639] eta: 1:21:12 lr: 4.3922721579040955e-05 loss: 0.1067 (0.1247) time: 2.8671 data: 0.0075 max mem: 33369 +Epoch: [5] [ 970/2639] eta: 1:20:44 lr: 4.391839675018553e-05 loss: 0.1115 (0.1246) time: 2.9063 data: 0.0075 max mem: 33369 +Epoch: [5] [ 980/2639] eta: 1:20:15 lr: 4.3914071874009145e-05 loss: 0.1200 (0.1247) time: 2.9081 data: 0.0076 max mem: 33369 +Epoch: [5] [ 990/2639] eta: 1:19:45 lr: 4.390974695050609e-05 loss: 0.1036 (0.1244) time: 2.8784 data: 0.0079 max mem: 33369 +Epoch: [5] [1000/2639] eta: 1:19:16 lr: 4.390542197967068e-05 loss: 0.0921 (0.1242) time: 2.8803 data: 0.0081 max mem: 33369 +Epoch: [5] [1010/2639] eta: 1:18:47 lr: 4.3901096961497213e-05 loss: 0.0949 (0.1242) time: 2.8908 data: 0.0080 max mem: 33369 +Epoch: [5] [1020/2639] eta: 1:18:17 lr: 4.3896771895979976e-05 loss: 0.1218 (0.1242) time: 2.8749 data: 0.0080 max mem: 33369 +Epoch: [5] [1030/2639] eta: 1:17:48 lr: 4.3892446783113286e-05 loss: 0.1239 (0.1243) time: 2.8647 data: 0.0085 max mem: 33369 +Epoch: [5] [1040/2639] eta: 1:17:18 lr: 4.388812162289143e-05 loss: 0.1129 (0.1242) time: 2.8871 data: 0.0082 max mem: 33369 +Epoch: [5] [1050/2639] eta: 1:16:49 lr: 4.38837964153087e-05 loss: 0.1064 (0.1242) time: 2.8930 data: 0.0077 max mem: 33369 +Epoch: [5] [1060/2639] eta: 1:16:21 lr: 4.38794711603594e-05 loss: 0.1095 (0.1242) time: 2.9117 data: 0.0081 max mem: 33369 +Epoch: [5] [1070/2639] eta: 1:15:52 lr: 4.387514585803782e-05 loss: 0.1217 (0.1243) time: 2.9209 data: 0.0078 max mem: 33369 +Epoch: [5] [1080/2639] eta: 1:15:22 lr: 4.387082050833825e-05 loss: 0.1229 (0.1244) time: 2.8832 data: 0.0075 max mem: 33369 +Epoch: [5] [1090/2639] eta: 1:14:53 lr: 4.3866495111254997e-05 loss: 0.1130 (0.1242) time: 2.8846 data: 0.0078 max mem: 33369 +Epoch: [5] [1100/2639] eta: 1:14:24 lr: 4.386216966678232e-05 loss: 0.1111 (0.1244) time: 2.9105 data: 0.0083 max mem: 33369 +Epoch: [5] [1110/2639] eta: 1:13:56 lr: 4.385784417491454e-05 loss: 0.1262 (0.1243) time: 2.9356 data: 0.0081 max mem: 33369 +Epoch: [5] [1120/2639] eta: 1:13:27 lr: 4.3853518635645906e-05 loss: 0.1114 (0.1246) time: 2.9353 data: 0.0078 max mem: 33369 +Epoch: [5] [1130/2639] eta: 1:12:58 lr: 4.384919304897074e-05 loss: 0.1077 (0.1246) time: 2.8770 data: 0.0079 max mem: 33369 +Epoch: [5] [1140/2639] eta: 1:12:28 lr: 4.3844867414883304e-05 loss: 0.1009 (0.1243) time: 2.8430 data: 0.0078 max mem: 33369 +Epoch: [5] [1150/2639] eta: 1:11:59 lr: 4.384054173337789e-05 loss: 0.0892 (0.1241) time: 2.8691 data: 0.0076 max mem: 33369 +Epoch: [5] [1160/2639] eta: 1:11:29 lr: 4.383621600444878e-05 loss: 0.1114 (0.1242) time: 2.8889 data: 0.0075 max mem: 33369 +Epoch: [5] [1170/2639] eta: 1:11:01 lr: 4.3831890228090254e-05 loss: 0.1184 (0.1242) time: 2.9052 data: 0.0078 max mem: 33369 +Epoch: [5] [1180/2639] eta: 1:10:32 lr: 4.3827564404296586e-05 loss: 0.1114 (0.1241) time: 2.9228 data: 0.0080 max mem: 33369 +Epoch: [5] [1190/2639] eta: 1:10:03 lr: 4.382323853306205e-05 loss: 0.0954 (0.1239) time: 2.9126 data: 0.0079 max mem: 33369 +Epoch: [5] [1200/2639] eta: 1:09:35 lr: 4.381891261438094e-05 loss: 0.1060 (0.1239) time: 2.9422 data: 0.0078 max mem: 33369 +Epoch: [5] [1210/2639] eta: 1:09:06 lr: 4.3814586648247515e-05 loss: 0.1104 (0.1239) time: 2.9497 data: 0.0078 max mem: 33369 +Epoch: [5] [1220/2639] eta: 1:08:37 lr: 4.381026063465605e-05 loss: 0.1348 (0.1241) time: 2.8941 data: 0.0077 max mem: 33369 +Epoch: [5] [1230/2639] eta: 1:08:09 lr: 4.380593457360082e-05 loss: 0.1305 (0.1241) time: 2.9294 data: 0.0077 max mem: 33369 +Epoch: [5] [1240/2639] eta: 1:07:40 lr: 4.3801608465076104e-05 loss: 0.1095 (0.1240) time: 2.9407 data: 0.0078 max mem: 33369 +Epoch: [5] [1250/2639] eta: 1:07:11 lr: 4.379728230907617e-05 loss: 0.1061 (0.1243) time: 2.8998 data: 0.0078 max mem: 33369 +Epoch: [5] [1260/2639] eta: 1:06:42 lr: 4.379295610559526e-05 loss: 0.1134 (0.1243) time: 2.9206 data: 0.0073 max mem: 33369 +Epoch: [5] [1270/2639] eta: 1:06:13 lr: 4.378862985462767e-05 loss: 0.1046 (0.1242) time: 2.9019 data: 0.0074 max mem: 33369 +Epoch: [5] [1280/2639] eta: 1:05:44 lr: 4.378430355616767e-05 loss: 0.1079 (0.1244) time: 2.9192 data: 0.0076 max mem: 33369 +Epoch: [5] [1290/2639] eta: 1:05:15 lr: 4.37799772102095e-05 loss: 0.1256 (0.1244) time: 2.9212 data: 0.0078 max mem: 33369 +Epoch: [5] [1300/2639] eta: 1:04:46 lr: 4.377565081674744e-05 loss: 0.1112 (0.1244) time: 2.8787 data: 0.0077 max mem: 33369 +Epoch: [5] [1310/2639] eta: 1:04:17 lr: 4.377132437577574e-05 loss: 0.1072 (0.1244) time: 2.8952 data: 0.0077 max mem: 33369 +Epoch: [5] [1320/2639] eta: 1:03:47 lr: 4.376699788728868e-05 loss: 0.1105 (0.1245) time: 2.8710 data: 0.0080 max mem: 33369 +Epoch: [5] [1330/2639] eta: 1:03:18 lr: 4.3762671351280495e-05 loss: 0.1154 (0.1245) time: 2.8879 data: 0.0078 max mem: 33369 +Epoch: [5] [1340/2639] eta: 1:02:49 lr: 4.375834476774546e-05 loss: 0.1361 (0.1248) time: 2.9227 data: 0.0076 max mem: 33369 +Epoch: [5] [1350/2639] eta: 1:02:20 lr: 4.375401813667782e-05 loss: 0.1330 (0.1248) time: 2.8794 data: 0.0080 max mem: 33369 +Epoch: [5] [1360/2639] eta: 1:01:50 lr: 4.374969145807184e-05 loss: 0.1250 (0.1250) time: 2.8489 data: 0.0080 max mem: 33369 +Epoch: [5] [1370/2639] eta: 1:01:22 lr: 4.374536473192177e-05 loss: 0.1091 (0.1248) time: 2.8921 data: 0.0078 max mem: 33369 +Epoch: [5] [1380/2639] eta: 1:00:53 lr: 4.3741037958221866e-05 loss: 0.1044 (0.1247) time: 2.9144 data: 0.0078 max mem: 33369 +Epoch: [5] [1390/2639] eta: 1:00:24 lr: 4.373671113696637e-05 loss: 0.1267 (0.1250) time: 2.8968 data: 0.0078 max mem: 33369 +Epoch: [5] [1400/2639] eta: 0:59:55 lr: 4.3732384268149534e-05 loss: 0.1245 (0.1248) time: 2.9130 data: 0.0079 max mem: 33369 +Epoch: [5] [1410/2639] eta: 0:59:25 lr: 4.3728057351765615e-05 loss: 0.1172 (0.1248) time: 2.8675 data: 0.0077 max mem: 33369 +Epoch: [5] [1420/2639] eta: 0:58:57 lr: 4.3723730387808856e-05 loss: 0.1211 (0.1248) time: 2.8914 data: 0.0078 max mem: 33369 +Epoch: [5] [1430/2639] eta: 0:58:28 lr: 4.37194033762735e-05 loss: 0.1094 (0.1246) time: 2.9376 data: 0.0080 max mem: 33369 +Epoch: [5] [1440/2639] eta: 0:57:58 lr: 4.371507631715379e-05 loss: 0.1055 (0.1247) time: 2.9005 data: 0.0078 max mem: 33369 +Epoch: [5] [1450/2639] eta: 0:57:30 lr: 4.371074921044398e-05 loss: 0.1293 (0.1249) time: 2.9098 data: 0.0078 max mem: 33369 +Epoch: [5] [1460/2639] eta: 0:57:00 lr: 4.37064220561383e-05 loss: 0.1292 (0.1249) time: 2.8996 data: 0.0079 max mem: 33369 +Epoch: [5] [1470/2639] eta: 0:56:32 lr: 4.3702094854231e-05 loss: 0.1154 (0.1250) time: 2.9176 data: 0.0077 max mem: 33369 +Epoch: [5] [1480/2639] eta: 0:56:03 lr: 4.3697767604716306e-05 loss: 0.1154 (0.1249) time: 2.9491 data: 0.0076 max mem: 33369 +Epoch: [5] [1490/2639] eta: 0:55:33 lr: 4.369344030758847e-05 loss: 0.1170 (0.1250) time: 2.8696 data: 0.0075 max mem: 33369 +Epoch: [5] [1500/2639] eta: 0:55:04 lr: 4.368911296284172e-05 loss: 0.1195 (0.1251) time: 2.8433 data: 0.0073 max mem: 33369 +Epoch: [5] [1510/2639] eta: 0:54:35 lr: 4.368478557047029e-05 loss: 0.1195 (0.1251) time: 2.8772 data: 0.0078 max mem: 33369 +Epoch: [5] [1520/2639] eta: 0:54:05 lr: 4.3680458130468425e-05 loss: 0.1180 (0.1251) time: 2.8505 data: 0.0079 max mem: 33369 +Epoch: [5] [1530/2639] eta: 0:53:36 lr: 4.367613064283035e-05 loss: 0.1121 (0.1249) time: 2.8605 data: 0.0076 max mem: 33369 +Epoch: [5] [1540/2639] eta: 0:53:07 lr: 4.367180310755029e-05 loss: 0.1024 (0.1249) time: 2.8855 data: 0.0080 max mem: 33369 +Epoch: [5] [1550/2639] eta: 0:52:39 lr: 4.3667475524622493e-05 loss: 0.1133 (0.1251) time: 2.9188 data: 0.0084 max mem: 33369 +Epoch: [5] [1560/2639] eta: 0:52:10 lr: 4.366314789404117e-05 loss: 0.1259 (0.1251) time: 2.9242 data: 0.0086 max mem: 33369 +Epoch: [5] [1570/2639] eta: 0:51:41 lr: 4.3658820215800547e-05 loss: 0.1073 (0.1250) time: 2.8953 data: 0.0085 max mem: 33369 +Epoch: [5] [1580/2639] eta: 0:51:11 lr: 4.3654492489894866e-05 loss: 0.1126 (0.1249) time: 2.8564 data: 0.0080 max mem: 33369 +Epoch: [5] [1590/2639] eta: 0:50:42 lr: 4.365016471631834e-05 loss: 0.1095 (0.1249) time: 2.8848 data: 0.0077 max mem: 33369 +Epoch: [5] [1600/2639] eta: 0:50:14 lr: 4.36458368950652e-05 loss: 0.1095 (0.1249) time: 2.9579 data: 0.0077 max mem: 33369 +Epoch: [5] [1610/2639] eta: 0:49:44 lr: 4.3641509026129655e-05 loss: 0.1077 (0.1249) time: 2.8980 data: 0.0079 max mem: 33369 +Epoch: [5] [1620/2639] eta: 0:49:16 lr: 4.3637181109505935e-05 loss: 0.0988 (0.1248) time: 2.9237 data: 0.0078 max mem: 33369 +Epoch: [5] [1630/2639] eta: 0:48:47 lr: 4.363285314518826e-05 loss: 0.1016 (0.1247) time: 2.9668 data: 0.0078 max mem: 33369 +Epoch: [5] [1640/2639] eta: 0:48:18 lr: 4.3628525133170844e-05 loss: 0.1042 (0.1247) time: 2.9076 data: 0.0083 max mem: 33369 +Epoch: [5] [1650/2639] eta: 0:47:49 lr: 4.36241970734479e-05 loss: 0.0911 (0.1245) time: 2.8707 data: 0.0081 max mem: 33369 +Epoch: [5] [1660/2639] eta: 0:47:19 lr: 4.361986896601366e-05 loss: 0.1131 (0.1247) time: 2.8625 data: 0.0079 max mem: 33369 +Epoch: [5] [1670/2639] eta: 0:46:51 lr: 4.3615540810862315e-05 loss: 0.1100 (0.1245) time: 2.9198 data: 0.0080 max mem: 33369 +Epoch: [5] [1680/2639] eta: 0:46:22 lr: 4.361121260798809e-05 loss: 0.1046 (0.1246) time: 2.9246 data: 0.0079 max mem: 33369 +Epoch: [5] [1690/2639] eta: 0:45:53 lr: 4.36068843573852e-05 loss: 0.1125 (0.1246) time: 2.8825 data: 0.0079 max mem: 33369 +Epoch: [5] [1700/2639] eta: 0:45:24 lr: 4.360255605904785e-05 loss: 0.1125 (0.1246) time: 2.8964 data: 0.0080 max mem: 33369 +Epoch: [5] [1710/2639] eta: 0:44:54 lr: 4.359822771297024e-05 loss: 0.1112 (0.1245) time: 2.8678 data: 0.0084 max mem: 33369 +Epoch: [5] [1720/2639] eta: 0:44:25 lr: 4.3593899319146585e-05 loss: 0.1091 (0.1245) time: 2.8575 data: 0.0085 max mem: 33369 +Epoch: [5] [1730/2639] eta: 0:43:56 lr: 4.35895708775711e-05 loss: 0.1091 (0.1245) time: 2.8891 data: 0.0084 max mem: 33369 +Epoch: [5] [1740/2639] eta: 0:43:27 lr: 4.358524238823797e-05 loss: 0.1209 (0.1245) time: 2.8810 data: 0.0081 max mem: 33369 +Epoch: [5] [1750/2639] eta: 0:42:58 lr: 4.358091385114142e-05 loss: 0.1246 (0.1246) time: 2.8619 data: 0.0076 max mem: 33369 +Epoch: [5] [1760/2639] eta: 0:42:28 lr: 4.357658526627563e-05 loss: 0.1132 (0.1245) time: 2.8358 data: 0.0076 max mem: 33369 +Epoch: [5] [1770/2639] eta: 0:41:59 lr: 4.357225663363481e-05 loss: 0.1113 (0.1244) time: 2.8556 data: 0.0076 max mem: 33369 +Epoch: [5] [1780/2639] eta: 0:41:30 lr: 4.356792795321317e-05 loss: 0.1200 (0.1246) time: 2.8727 data: 0.0079 max mem: 33369 +Epoch: [5] [1790/2639] eta: 0:41:01 lr: 4.356359922500489e-05 loss: 0.1174 (0.1245) time: 2.8813 data: 0.0079 max mem: 33369 +Epoch: [5] [1800/2639] eta: 0:40:32 lr: 4.355927044900418e-05 loss: 0.1090 (0.1245) time: 2.8958 data: 0.0075 max mem: 33369 +Epoch: [5] [1810/2639] eta: 0:40:03 lr: 4.355494162520522e-05 loss: 0.1085 (0.1244) time: 2.8786 data: 0.0079 max mem: 33369 +Epoch: [5] [1820/2639] eta: 0:39:34 lr: 4.355061275360222e-05 loss: 0.1066 (0.1244) time: 2.8888 data: 0.0079 max mem: 33369 +Epoch: [5] [1830/2639] eta: 0:39:05 lr: 4.354628383418936e-05 loss: 0.1035 (0.1243) time: 2.9010 data: 0.0077 max mem: 33369 +Epoch: [5] [1840/2639] eta: 0:38:36 lr: 4.354195486696084e-05 loss: 0.1046 (0.1243) time: 2.8941 data: 0.0076 max mem: 33369 +Epoch: [5] [1850/2639] eta: 0:38:07 lr: 4.3537625851910844e-05 loss: 0.1046 (0.1243) time: 2.9306 data: 0.0075 max mem: 33369 +Epoch: [5] [1860/2639] eta: 0:37:38 lr: 4.353329678903356e-05 loss: 0.0937 (0.1241) time: 2.9299 data: 0.0077 max mem: 33369 +Epoch: [5] [1870/2639] eta: 0:37:09 lr: 4.3528967678323174e-05 loss: 0.0986 (0.1241) time: 2.8819 data: 0.0078 max mem: 33369 +Epoch: [5] [1880/2639] eta: 0:36:40 lr: 4.352463851977388e-05 loss: 0.1229 (0.1242) time: 2.8983 data: 0.0081 max mem: 33369 +Epoch: [5] [1890/2639] eta: 0:36:11 lr: 4.352030931337985e-05 loss: 0.1237 (0.1242) time: 2.9435 data: 0.0082 max mem: 33369 +Epoch: [5] [1900/2639] eta: 0:35:42 lr: 4.351598005913528e-05 loss: 0.1225 (0.1242) time: 2.9254 data: 0.0078 max mem: 33369 +Epoch: [5] [1910/2639] eta: 0:35:13 lr: 4.351165075703435e-05 loss: 0.1197 (0.1242) time: 2.8918 data: 0.0077 max mem: 33369 +Epoch: [5] [1920/2639] eta: 0:34:44 lr: 4.3507321407071234e-05 loss: 0.1025 (0.1242) time: 2.8681 data: 0.0078 max mem: 33369 +Epoch: [5] [1930/2639] eta: 0:34:15 lr: 4.3502992009240104e-05 loss: 0.1097 (0.1242) time: 2.8831 data: 0.0079 max mem: 33369 +Epoch: [5] [1940/2639] eta: 0:33:46 lr: 4.349866256353515e-05 loss: 0.1269 (0.1242) time: 2.9418 data: 0.0077 max mem: 33369 +Epoch: [5] [1950/2639] eta: 0:33:17 lr: 4.349433306995054e-05 loss: 0.1213 (0.1243) time: 2.9008 data: 0.0075 max mem: 33369 +Epoch: [5] [1960/2639] eta: 0:32:48 lr: 4.349000352848046e-05 loss: 0.1331 (0.1244) time: 2.8894 data: 0.0073 max mem: 33369 +Epoch: [5] [1970/2639] eta: 0:32:20 lr: 4.348567393911908e-05 loss: 0.1240 (0.1243) time: 2.9397 data: 0.0071 max mem: 33369 +Epoch: [5] [1980/2639] eta: 0:31:51 lr: 4.348134430186055e-05 loss: 0.1240 (0.1244) time: 2.9551 data: 0.0071 max mem: 33369 +Epoch: [5] [1990/2639] eta: 0:31:22 lr: 4.347701461669908e-05 loss: 0.1296 (0.1244) time: 2.9440 data: 0.0072 max mem: 33369 +Epoch: [5] [2000/2639] eta: 0:30:53 lr: 4.347268488362881e-05 loss: 0.1296 (0.1244) time: 2.9139 data: 0.0072 max mem: 33369 +Epoch: [5] [2010/2639] eta: 0:30:24 lr: 4.346835510264391e-05 loss: 0.1107 (0.1244) time: 2.9383 data: 0.0072 max mem: 33369 +Epoch: [5] [2020/2639] eta: 0:29:55 lr: 4.3464025273738556e-05 loss: 0.1165 (0.1244) time: 2.8905 data: 0.0074 max mem: 33369 +Epoch: [5] [2030/2639] eta: 0:29:26 lr: 4.345969539690691e-05 loss: 0.1220 (0.1245) time: 2.8651 data: 0.0075 max mem: 33369 +Epoch: [5] [2040/2639] eta: 0:28:57 lr: 4.3455365472143146e-05 loss: 0.1355 (0.1246) time: 2.8918 data: 0.0076 max mem: 33369 +Epoch: [5] [2050/2639] eta: 0:28:28 lr: 4.3451035499441414e-05 loss: 0.1355 (0.1246) time: 2.9103 data: 0.0076 max mem: 33369 +Epoch: [5] [2060/2639] eta: 0:27:59 lr: 4.344670547879587e-05 loss: 0.1236 (0.1246) time: 2.9640 data: 0.0077 max mem: 33369 +Epoch: [5] [2070/2639] eta: 0:27:30 lr: 4.344237541020068e-05 loss: 0.1249 (0.1246) time: 2.9624 data: 0.0083 max mem: 33369 +Epoch: [5] [2080/2639] eta: 0:27:01 lr: 4.3438045293650015e-05 loss: 0.1207 (0.1246) time: 2.9084 data: 0.0083 max mem: 33369 +Epoch: [5] [2090/2639] eta: 0:26:32 lr: 4.3433715129138025e-05 loss: 0.1125 (0.1246) time: 2.8817 data: 0.0081 max mem: 33369 +Epoch: [5] [2100/2639] eta: 0:26:03 lr: 4.3429384916658856e-05 loss: 0.1360 (0.1247) time: 2.8969 data: 0.0076 max mem: 33369 +Epoch: [5] [2110/2639] eta: 0:25:34 lr: 4.342505465620667e-05 loss: 0.1365 (0.1248) time: 2.8764 data: 0.0073 max mem: 33369 +Epoch: [5] [2120/2639] eta: 0:25:05 lr: 4.3420724347775616e-05 loss: 0.1077 (0.1248) time: 2.8828 data: 0.0075 max mem: 33369 +Epoch: [5] [2130/2639] eta: 0:24:36 lr: 4.3416393991359854e-05 loss: 0.1101 (0.1248) time: 2.9254 data: 0.0074 max mem: 33369 +Epoch: [5] [2140/2639] eta: 0:24:07 lr: 4.341206358695353e-05 loss: 0.1299 (0.1249) time: 2.9389 data: 0.0074 max mem: 33369 +Epoch: [5] [2150/2639] eta: 0:23:38 lr: 4.340773313455079e-05 loss: 0.1487 (0.1250) time: 2.9276 data: 0.0077 max mem: 33369 +Epoch: [5] [2160/2639] eta: 0:23:09 lr: 4.340340263414578e-05 loss: 0.1159 (0.1250) time: 2.8965 data: 0.0077 max mem: 33369 +Epoch: [5] [2170/2639] eta: 0:22:40 lr: 4.339907208573266e-05 loss: 0.1096 (0.1250) time: 2.8969 data: 0.0078 max mem: 33369 +Epoch: [5] [2180/2639] eta: 0:22:11 lr: 4.3394741489305555e-05 loss: 0.1125 (0.1250) time: 2.8968 data: 0.0079 max mem: 33369 +Epoch: [5] [2190/2639] eta: 0:21:42 lr: 4.3390410844858625e-05 loss: 0.1070 (0.1249) time: 2.8599 data: 0.0076 max mem: 33369 +Epoch: [5] [2200/2639] eta: 0:21:13 lr: 4.3386080152386004e-05 loss: 0.1016 (0.1249) time: 2.8446 data: 0.0077 max mem: 33369 +Epoch: [5] [2210/2639] eta: 0:20:44 lr: 4.3381749411881845e-05 loss: 0.1231 (0.1250) time: 2.8532 data: 0.0080 max mem: 33369 +Epoch: [5] [2220/2639] eta: 0:20:15 lr: 4.3377418623340265e-05 loss: 0.1345 (0.1251) time: 2.8997 data: 0.0079 max mem: 33369 +Epoch: [5] [2230/2639] eta: 0:19:46 lr: 4.337308778675541e-05 loss: 0.1313 (0.1251) time: 2.8969 data: 0.0076 max mem: 33369 +Epoch: [5] [2240/2639] eta: 0:19:17 lr: 4.336875690212144e-05 loss: 0.1185 (0.1251) time: 2.8758 data: 0.0076 max mem: 33369 +Epoch: [5] [2250/2639] eta: 0:18:48 lr: 4.336442596943246e-05 loss: 0.1128 (0.1251) time: 2.8846 data: 0.0077 max mem: 33369 +Epoch: [5] [2260/2639] eta: 0:18:19 lr: 4.3360094988682615e-05 loss: 0.1053 (0.1251) time: 2.8837 data: 0.0076 max mem: 33369 +Epoch: [5] [2270/2639] eta: 0:17:50 lr: 4.335576395986604e-05 loss: 0.1418 (0.1252) time: 2.8860 data: 0.0074 max mem: 33369 +Epoch: [5] [2280/2639] eta: 0:17:21 lr: 4.3351432882976865e-05 loss: 0.1229 (0.1252) time: 2.8604 data: 0.0075 max mem: 33369 +Epoch: [5] [2290/2639] eta: 0:16:52 lr: 4.3347101758009215e-05 loss: 0.1067 (0.1252) time: 2.8690 data: 0.0076 max mem: 33369 +Epoch: [5] [2300/2639] eta: 0:16:22 lr: 4.334277058495723e-05 loss: 0.0999 (0.1252) time: 2.8782 data: 0.0078 max mem: 33369 +Epoch: [5] [2310/2639] eta: 0:15:53 lr: 4.333843936381503e-05 loss: 0.0972 (0.1251) time: 2.8826 data: 0.0081 max mem: 33369 +Epoch: [5] [2320/2639] eta: 0:15:25 lr: 4.3334108094576735e-05 loss: 0.0907 (0.1250) time: 2.9260 data: 0.0086 max mem: 33369 +Epoch: [5] [2330/2639] eta: 0:14:55 lr: 4.332977677723648e-05 loss: 0.0964 (0.1250) time: 2.9041 data: 0.0084 max mem: 33369 +Epoch: [5] [2340/2639] eta: 0:14:26 lr: 4.332544541178839e-05 loss: 0.1214 (0.1250) time: 2.8801 data: 0.0076 max mem: 33369 +Epoch: [5] [2350/2639] eta: 0:13:57 lr: 4.332111399822656e-05 loss: 0.1210 (0.1250) time: 2.8746 data: 0.0074 max mem: 33369 +Epoch: [5] [2360/2639] eta: 0:13:28 lr: 4.331678253654515e-05 loss: 0.1210 (0.1250) time: 2.8869 data: 0.0075 max mem: 33369 +Epoch: [5] [2370/2639] eta: 0:12:59 lr: 4.331245102673825e-05 loss: 0.1296 (0.1251) time: 2.8958 data: 0.0075 max mem: 33369 +Epoch: [5] [2380/2639] eta: 0:12:30 lr: 4.330811946879999e-05 loss: 0.1191 (0.1250) time: 2.8947 data: 0.0073 max mem: 33369 +Epoch: [5] [2390/2639] eta: 0:12:01 lr: 4.3303787862724485e-05 loss: 0.1117 (0.1251) time: 2.9018 data: 0.0075 max mem: 33369 +Epoch: [5] [2400/2639] eta: 0:11:32 lr: 4.329945620850584e-05 loss: 0.1118 (0.1251) time: 2.8800 data: 0.0081 max mem: 33369 +Epoch: [5] [2410/2639] eta: 0:11:03 lr: 4.3295124506138185e-05 loss: 0.1168 (0.1251) time: 2.8637 data: 0.0081 max mem: 33369 +Epoch: [5] [2420/2639] eta: 0:10:34 lr: 4.329079275561562e-05 loss: 0.1442 (0.1252) time: 2.8772 data: 0.0078 max mem: 33369 +Epoch: [5] [2430/2639] eta: 0:10:05 lr: 4.3286460956932264e-05 loss: 0.1198 (0.1252) time: 2.9255 data: 0.0073 max mem: 33369 +Epoch: [5] [2440/2639] eta: 0:09:36 lr: 4.328212911008221e-05 loss: 0.1162 (0.1253) time: 2.9176 data: 0.0071 max mem: 33369 +Epoch: [5] [2450/2639] eta: 0:09:07 lr: 4.327779721505959e-05 loss: 0.1241 (0.1253) time: 2.8953 data: 0.0074 max mem: 33369 +Epoch: [5] [2460/2639] eta: 0:08:39 lr: 4.327346527185849e-05 loss: 0.1207 (0.1253) time: 2.9469 data: 0.0074 max mem: 33369 +Epoch: [5] [2470/2639] eta: 0:08:10 lr: 4.326913328047303e-05 loss: 0.1207 (0.1253) time: 2.9361 data: 0.0073 max mem: 33369 +Epoch: [5] [2480/2639] eta: 0:07:41 lr: 4.3264801240897304e-05 loss: 0.1242 (0.1253) time: 2.8912 data: 0.0075 max mem: 33369 +Epoch: [5] [2490/2639] eta: 0:07:12 lr: 4.3260469153125416e-05 loss: 0.1165 (0.1253) time: 2.8926 data: 0.0077 max mem: 33369 +Epoch: [5] [2500/2639] eta: 0:06:43 lr: 4.325613701715147e-05 loss: 0.1291 (0.1253) time: 2.8798 data: 0.0078 max mem: 33369 +Epoch: [5] [2510/2639] eta: 0:06:14 lr: 4.325180483296956e-05 loss: 0.1214 (0.1253) time: 2.8944 data: 0.0077 max mem: 33369 +Epoch: [5] [2520/2639] eta: 0:05:45 lr: 4.3247472600573796e-05 loss: 0.1100 (0.1253) time: 2.9114 data: 0.0076 max mem: 33369 +Epoch: [5] [2530/2639] eta: 0:05:16 lr: 4.324314031995826e-05 loss: 0.1051 (0.1253) time: 2.9368 data: 0.0080 max mem: 33369 +Epoch: [5] [2540/2639] eta: 0:04:47 lr: 4.323880799111706e-05 loss: 0.1080 (0.1254) time: 2.9639 data: 0.0078 max mem: 33369 +Epoch: [5] [2550/2639] eta: 0:04:18 lr: 4.323447561404429e-05 loss: 0.1012 (0.1253) time: 2.9168 data: 0.0075 max mem: 33369 +Epoch: [5] [2560/2639] eta: 0:03:49 lr: 4.323014318873403e-05 loss: 0.1053 (0.1253) time: 2.8600 data: 0.0079 max mem: 33369 +Epoch: [5] [2570/2639] eta: 0:03:20 lr: 4.3225810715180386e-05 loss: 0.1275 (0.1253) time: 2.8779 data: 0.0080 max mem: 33369 +Epoch: [5] [2580/2639] eta: 0:02:51 lr: 4.322147819337744e-05 loss: 0.1176 (0.1253) time: 2.9000 data: 0.0078 max mem: 33369 +Epoch: [5] [2590/2639] eta: 0:02:22 lr: 4.321714562331928e-05 loss: 0.1130 (0.1253) time: 2.8957 data: 0.0076 max mem: 33369 +Epoch: [5] [2600/2639] eta: 0:01:53 lr: 4.321281300499999e-05 loss: 0.1235 (0.1253) time: 2.8749 data: 0.0078 max mem: 33369 +Epoch: [5] [2610/2639] eta: 0:01:24 lr: 4.320848033841367e-05 loss: 0.1122 (0.1253) time: 2.8828 data: 0.0078 max mem: 33369 +Epoch: [5] [2620/2639] eta: 0:00:55 lr: 4.3204147623554394e-05 loss: 0.1073 (0.1252) time: 2.9066 data: 0.0077 max mem: 33369 +Epoch: [5] [2630/2639] eta: 0:00:26 lr: 4.319981486041624e-05 loss: 0.1045 (0.1251) time: 2.9155 data: 0.0074 max mem: 33369 +Epoch: [5] Total time: 2:07:45 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 2:12:09 time: 3.0817 data: 2.9899 max mem: 33369 +Test: [ 100/2573] eta: 0:04:25 time: 0.0777 data: 0.0015 max mem: 33369 +Test: [ 200/2573] eta: 0:03:42 time: 0.0789 data: 0.0016 max mem: 33369 +Test: [ 300/2573] eta: 0:03:21 time: 0.0808 data: 0.0013 max mem: 33369 +Test: [ 400/2573] eta: 0:03:07 time: 0.0807 data: 0.0014 max mem: 33369 +Test: [ 500/2573] eta: 0:02:55 time: 0.0797 data: 0.0015 max mem: 33369 +Test: [ 600/2573] eta: 0:02:45 time: 0.0797 data: 0.0015 max mem: 33369 +Test: [ 700/2573] eta: 0:02:36 time: 0.0797 data: 0.0015 max mem: 33369 +Test: [ 800/2573] eta: 0:02:27 time: 0.0826 data: 0.0014 max mem: 33369 +Test: [ 900/2573] eta: 0:02:18 time: 0.0802 data: 0.0014 max mem: 33369 +Test: [1000/2573] eta: 0:02:10 time: 0.0807 data: 0.0015 max mem: 33369 +Test: [1100/2573] eta: 0:02:01 time: 0.0802 data: 0.0014 max mem: 33369 +Test: [1200/2573] eta: 0:01:53 time: 0.0799 data: 0.0014 max mem: 33369 +Test: [1300/2573] eta: 0:01:44 time: 0.0801 data: 0.0013 max mem: 33369 +Test: [1400/2573] eta: 0:01:36 time: 0.0792 data: 0.0014 max mem: 33369 +Test: [1500/2573] eta: 0:01:27 time: 0.0805 data: 0.0016 max mem: 33369 +Test: [1600/2573] eta: 0:01:19 time: 0.0829 data: 0.0014 max mem: 33369 +Test: [1700/2573] eta: 0:01:11 time: 0.0782 data: 0.0014 max mem: 33369 +Test: [1800/2573] eta: 0:01:03 time: 0.0828 data: 0.0014 max mem: 33369 +Test: [1900/2573] eta: 0:00:54 time: 0.0782 data: 0.0014 max mem: 33369 +Test: [2000/2573] eta: 0:00:46 time: 0.0805 data: 0.0016 max mem: 33369 +Test: [2100/2573] eta: 0:00:38 time: 0.0822 data: 0.0014 max mem: 33369 +Test: [2200/2573] eta: 0:00:30 time: 0.0817 data: 0.0015 max mem: 33369 +Test: [2300/2573] eta: 0:00:22 time: 0.0815 data: 0.0014 max mem: 33369 +Test: [2400/2573] eta: 0:00:14 time: 0.0773 data: 0.0015 max mem: 33369 +Test: [2500/2573] eta: 0:00:05 time: 0.0795 data: 0.0014 max mem: 33369 +Test: Total time: 0:03:29 +Final results: +Mean IoU is 52.87 + + precision@0.5 = 58.82 + precision@0.6 = 51.78 + precision@0.7 = 43.40 + precision@0.8 = 31.43 + precision@0.9 = 13.34 + overall IoU = 53.63 + +Average object IoU 52.87464219863166 +Overall IoU 53.63386535644531 +Better epoch: 5 + +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [6] [ 0/2639] eta: 4:08:31 lr: 4.319591533230858e-05 loss: 0.0745 (0.0745) time: 5.6505 data: 2.6658 max mem: 33369 +Epoch: [6] [ 10/2639] eta: 2:18:32 lr: 4.319158247742427e-05 loss: 0.0950 (0.1115) time: 3.1620 data: 0.2491 max mem: 33369 +Epoch: [6] [ 20/2639] eta: 2:12:48 lr: 4.3187249574243926e-05 loss: 0.1088 (0.1215) time: 2.9123 data: 0.0071 max mem: 33369 +Epoch: [6] [ 30/2639] eta: 2:10:21 lr: 4.3182916622761615e-05 loss: 0.1088 (0.1195) time: 2.9073 data: 0.0075 max mem: 33369 +Epoch: [6] [ 40/2639] eta: 2:08:12 lr: 4.317858362297142e-05 loss: 0.1095 (0.1191) time: 2.8727 data: 0.0082 max mem: 33369 +Epoch: [6] [ 50/2639] eta: 2:06:49 lr: 4.3174250574867425e-05 loss: 0.1074 (0.1171) time: 2.8487 data: 0.0079 max mem: 33369 +Epoch: [6] [ 60/2639] eta: 2:05:51 lr: 4.316991747844369e-05 loss: 0.0937 (0.1123) time: 2.8632 data: 0.0079 max mem: 33369 +Epoch: [6] [ 70/2639] eta: 2:05:07 lr: 4.316558433369429e-05 loss: 0.0937 (0.1113) time: 2.8792 data: 0.0081 max mem: 33369 +Epoch: [6] [ 80/2639] eta: 2:04:37 lr: 4.31612511406133e-05 loss: 0.0923 (0.1114) time: 2.9030 data: 0.0080 max mem: 33369 +Epoch: [6] [ 90/2639] eta: 2:04:20 lr: 4.315691789919478e-05 loss: 0.0899 (0.1096) time: 2.9420 data: 0.0078 max mem: 33369 +Epoch: [6] [ 100/2639] eta: 2:04:05 lr: 4.315258460943282e-05 loss: 0.0944 (0.1109) time: 2.9746 data: 0.0082 max mem: 33369 +Epoch: [6] [ 110/2639] eta: 2:03:51 lr: 4.314825127132145e-05 loss: 0.1027 (0.1135) time: 2.9922 data: 0.0082 max mem: 33369 +Epoch: [6] [ 120/2639] eta: 2:03:16 lr: 4.314391788485477e-05 loss: 0.1335 (0.1158) time: 2.9559 data: 0.0080 max mem: 33369 +Epoch: [6] [ 130/2639] eta: 2:02:47 lr: 4.3139584450026835e-05 loss: 0.1171 (0.1157) time: 2.9239 data: 0.0077 max mem: 33369 +Epoch: [6] [ 140/2639] eta: 2:02:15 lr: 4.3135250966831694e-05 loss: 0.0998 (0.1139) time: 2.9292 data: 0.0075 max mem: 33369 +Epoch: [6] [ 150/2639] eta: 2:01:35 lr: 4.3130917435263415e-05 loss: 0.0950 (0.1141) time: 2.8990 data: 0.0077 max mem: 33369 +Epoch: [6] [ 160/2639] eta: 2:01:01 lr: 4.3126583855316064e-05 loss: 0.0950 (0.1128) time: 2.8859 data: 0.0075 max mem: 33369 +Epoch: [6] [ 170/2639] eta: 2:00:26 lr: 4.3122250226983704e-05 loss: 0.0993 (0.1126) time: 2.8942 data: 0.0076 max mem: 33369 +Epoch: [6] [ 180/2639] eta: 1:59:50 lr: 4.3117916550260365e-05 loss: 0.1015 (0.1122) time: 2.8860 data: 0.0080 max mem: 33369 +Epoch: [6] [ 190/2639] eta: 1:59:18 lr: 4.311358282514013e-05 loss: 0.0900 (0.1108) time: 2.8883 data: 0.0080 max mem: 33369 +Epoch: [6] [ 200/2639] eta: 1:58:46 lr: 4.310924905161705e-05 loss: 0.0847 (0.1103) time: 2.8987 data: 0.0081 max mem: 33369 +Epoch: [6] [ 210/2639] eta: 1:58:12 lr: 4.310491522968516e-05 loss: 0.1029 (0.1111) time: 2.8923 data: 0.0082 max mem: 33369 +Epoch: [6] [ 220/2639] eta: 1:57:36 lr: 4.310058135933852e-05 loss: 0.1141 (0.1119) time: 2.8682 data: 0.0083 max mem: 33369 +Epoch: [6] [ 230/2639] eta: 1:56:58 lr: 4.309624744057119e-05 loss: 0.1145 (0.1122) time: 2.8462 data: 0.0081 max mem: 33369 +Epoch: [6] [ 240/2639] eta: 1:56:33 lr: 4.3091913473377206e-05 loss: 0.1069 (0.1121) time: 2.8943 data: 0.0075 max mem: 33369 +Epoch: [6] [ 250/2639] eta: 1:55:57 lr: 4.3087579457750625e-05 loss: 0.1062 (0.1124) time: 2.8986 data: 0.0078 max mem: 33369 +Epoch: [6] [ 260/2639] eta: 1:55:24 lr: 4.308324539368548e-05 loss: 0.1062 (0.1120) time: 2.8578 data: 0.0079 max mem: 33369 +Epoch: [6] [ 270/2639] eta: 1:54:56 lr: 4.3078911281175835e-05 loss: 0.0895 (0.1111) time: 2.8941 data: 0.0080 max mem: 33369 +Epoch: [6] [ 280/2639] eta: 1:54:30 lr: 4.3074577120215706e-05 loss: 0.0874 (0.1107) time: 2.9329 data: 0.0079 max mem: 33369 +Epoch: [6] [ 290/2639] eta: 1:54:02 lr: 4.3070242910799154e-05 loss: 0.0920 (0.1107) time: 2.9372 data: 0.0079 max mem: 33369 +Epoch: [6] [ 300/2639] eta: 1:53:33 lr: 4.3065908652920215e-05 loss: 0.1138 (0.1110) time: 2.9211 data: 0.0084 max mem: 33369 +Epoch: [6] [ 310/2639] eta: 1:53:01 lr: 4.306157434657293e-05 loss: 0.1126 (0.1110) time: 2.8975 data: 0.0084 max mem: 33369 +Epoch: [6] [ 320/2639] eta: 1:52:27 lr: 4.305723999175133e-05 loss: 0.1074 (0.1116) time: 2.8627 data: 0.0081 max mem: 33369 +Epoch: [6] [ 330/2639] eta: 1:51:50 lr: 4.305290558844946e-05 loss: 0.1191 (0.1123) time: 2.8189 data: 0.0084 max mem: 33369 +Epoch: [6] [ 340/2639] eta: 1:51:18 lr: 4.304857113666134e-05 loss: 0.1156 (0.1122) time: 2.8309 data: 0.0084 max mem: 33369 +Epoch: [6] [ 350/2639] eta: 1:50:48 lr: 4.304423663638101e-05 loss: 0.1185 (0.1126) time: 2.8771 data: 0.0082 max mem: 33369 +Epoch: [6] [ 360/2639] eta: 1:50:13 lr: 4.303990208760251e-05 loss: 0.1156 (0.1123) time: 2.8478 data: 0.0080 max mem: 33369 +Epoch: [6] [ 370/2639] eta: 1:49:43 lr: 4.303556749031986e-05 loss: 0.1084 (0.1127) time: 2.8452 data: 0.0079 max mem: 33369 +Epoch: [6] [ 380/2639] eta: 1:49:15 lr: 4.3031232844527095e-05 loss: 0.1238 (0.1129) time: 2.9013 data: 0.0079 max mem: 33369 +Epoch: [6] [ 390/2639] eta: 1:48:50 lr: 4.302689815021824e-05 loss: 0.1134 (0.1127) time: 2.9501 data: 0.0080 max mem: 33369 +Epoch: [6] [ 400/2639] eta: 1:48:22 lr: 4.302256340738732e-05 loss: 0.1158 (0.1131) time: 2.9497 data: 0.0081 max mem: 33369 +Epoch: [6] [ 410/2639] eta: 1:47:53 lr: 4.3018228616028364e-05 loss: 0.1172 (0.1140) time: 2.9128 data: 0.0080 max mem: 33369 +Epoch: [6] [ 420/2639] eta: 1:47:21 lr: 4.301389377613539e-05 loss: 0.1087 (0.1138) time: 2.8743 data: 0.0078 max mem: 33369 +Epoch: [6] [ 430/2639] eta: 1:46:52 lr: 4.3009558887702415e-05 loss: 0.0993 (0.1136) time: 2.8714 data: 0.0079 max mem: 33369 +Epoch: [6] [ 440/2639] eta: 1:46:21 lr: 4.300522395072348e-05 loss: 0.0961 (0.1133) time: 2.8858 data: 0.0080 max mem: 33369 +Epoch: [6] [ 450/2639] eta: 1:45:51 lr: 4.300088896519258e-05 loss: 0.0924 (0.1130) time: 2.8768 data: 0.0081 max mem: 33369 +Epoch: [6] [ 460/2639] eta: 1:45:21 lr: 4.2996553931103745e-05 loss: 0.0889 (0.1131) time: 2.8779 data: 0.0082 max mem: 33369 +Epoch: [6] [ 470/2639] eta: 1:44:49 lr: 4.299221884845099e-05 loss: 0.1071 (0.1130) time: 2.8610 data: 0.0085 max mem: 33369 +Epoch: [6] [ 480/2639] eta: 1:44:23 lr: 4.298788371722833e-05 loss: 0.1071 (0.1134) time: 2.9062 data: 0.0089 max mem: 33369 +Epoch: [6] [ 490/2639] eta: 1:43:54 lr: 4.298354853742977e-05 loss: 0.1042 (0.1132) time: 2.9271 data: 0.0084 max mem: 33369 +Epoch: [6] [ 500/2639] eta: 1:43:26 lr: 4.297921330904934e-05 loss: 0.1159 (0.1137) time: 2.9121 data: 0.0077 max mem: 33369 +Epoch: [6] [ 510/2639] eta: 1:43:00 lr: 4.297487803208104e-05 loss: 0.1190 (0.1139) time: 2.9458 data: 0.0076 max mem: 33369 +Epoch: [6] [ 520/2639] eta: 1:42:30 lr: 4.297054270651888e-05 loss: 0.1025 (0.1135) time: 2.9204 data: 0.0077 max mem: 33369 +Epoch: [6] [ 530/2639] eta: 1:42:03 lr: 4.296620733235686e-05 loss: 0.0956 (0.1134) time: 2.9214 data: 0.0078 max mem: 33369 +Epoch: [6] [ 540/2639] eta: 1:41:32 lr: 4.2961871909588994e-05 loss: 0.1160 (0.1138) time: 2.9096 data: 0.0078 max mem: 33369 +Epoch: [6] [ 550/2639] eta: 1:41:03 lr: 4.295753643820929e-05 loss: 0.1160 (0.1138) time: 2.8777 data: 0.0077 max mem: 33369 +Epoch: [6] [ 560/2639] eta: 1:40:34 lr: 4.295320091821175e-05 loss: 0.1078 (0.1139) time: 2.8969 data: 0.0077 max mem: 33369 +Epoch: [6] [ 570/2639] eta: 1:40:04 lr: 4.294886534959037e-05 loss: 0.1075 (0.1138) time: 2.8906 data: 0.0081 max mem: 33369 +Epoch: [6] [ 580/2639] eta: 1:39:32 lr: 4.294452973233916e-05 loss: 0.1173 (0.1140) time: 2.8578 data: 0.0080 max mem: 33369 +Epoch: [6] [ 590/2639] eta: 1:39:03 lr: 4.29401940664521e-05 loss: 0.1193 (0.1141) time: 2.8602 data: 0.0078 max mem: 33369 +Epoch: [6] [ 600/2639] eta: 1:38:33 lr: 4.2935858351923225e-05 loss: 0.1094 (0.1142) time: 2.8796 data: 0.0080 max mem: 33369 +Epoch: [6] [ 610/2639] eta: 1:38:03 lr: 4.2931522588746493e-05 loss: 0.0940 (0.1138) time: 2.8678 data: 0.0083 max mem: 33369 +Epoch: [6] [ 620/2639] eta: 1:37:33 lr: 4.292718677691591e-05 loss: 0.0834 (0.1137) time: 2.8722 data: 0.0083 max mem: 33369 +Epoch: [6] [ 630/2639] eta: 1:37:06 lr: 4.292285091642549e-05 loss: 0.0911 (0.1135) time: 2.9149 data: 0.0080 max mem: 33369 +Epoch: [6] [ 640/2639] eta: 1:36:36 lr: 4.29185150072692e-05 loss: 0.0942 (0.1135) time: 2.9151 data: 0.0081 max mem: 33369 +Epoch: [6] [ 650/2639] eta: 1:36:06 lr: 4.291417904944104e-05 loss: 0.1025 (0.1133) time: 2.8718 data: 0.0080 max mem: 33369 +Epoch: [6] [ 660/2639] eta: 1:35:38 lr: 4.290984304293501e-05 loss: 0.1076 (0.1135) time: 2.9020 data: 0.0085 max mem: 33369 +Epoch: [6] [ 670/2639] eta: 1:35:10 lr: 4.290550698774508e-05 loss: 0.0930 (0.1133) time: 2.9388 data: 0.0087 max mem: 33369 +Epoch: [6] [ 680/2639] eta: 1:34:40 lr: 4.290117088386524e-05 loss: 0.1133 (0.1139) time: 2.8878 data: 0.0082 max mem: 33369 +Epoch: [6] [ 690/2639] eta: 1:34:12 lr: 4.2896834731289485e-05 loss: 0.1355 (0.1139) time: 2.8897 data: 0.0085 max mem: 33369 +Epoch: [6] [ 700/2639] eta: 1:33:42 lr: 4.2892498530011796e-05 loss: 0.1161 (0.1142) time: 2.9042 data: 0.0090 max mem: 33369 +Epoch: [6] [ 710/2639] eta: 1:33:13 lr: 4.288816228002615e-05 loss: 0.1168 (0.1144) time: 2.8872 data: 0.0086 max mem: 33369 +Epoch: [6] [ 720/2639] eta: 1:32:44 lr: 4.2883825981326524e-05 loss: 0.1238 (0.1146) time: 2.9102 data: 0.0084 max mem: 33369 +Epoch: [6] [ 730/2639] eta: 1:32:16 lr: 4.287948963390691e-05 loss: 0.1004 (0.1144) time: 2.9132 data: 0.0079 max mem: 33369 +Epoch: [6] [ 740/2639] eta: 1:31:48 lr: 4.287515323776128e-05 loss: 0.0822 (0.1141) time: 2.9354 data: 0.0073 max mem: 33369 +Epoch: [6] [ 750/2639] eta: 1:31:19 lr: 4.287081679288361e-05 loss: 0.0888 (0.1140) time: 2.9209 data: 0.0076 max mem: 33369 +Epoch: [6] [ 760/2639] eta: 1:30:50 lr: 4.286648029926787e-05 loss: 0.1143 (0.1141) time: 2.8923 data: 0.0078 max mem: 33369 +Epoch: [6] [ 770/2639] eta: 1:30:20 lr: 4.2862143756908054e-05 loss: 0.1058 (0.1141) time: 2.8865 data: 0.0081 max mem: 33369 +Epoch: [6] [ 780/2639] eta: 1:29:52 lr: 4.285780716579811e-05 loss: 0.1071 (0.1141) time: 2.9108 data: 0.0082 max mem: 33369 +Epoch: [6] [ 790/2639] eta: 1:29:23 lr: 4.285347052593202e-05 loss: 0.1128 (0.1141) time: 2.9184 data: 0.0079 max mem: 33369 +Epoch: [6] [ 800/2639] eta: 1:28:54 lr: 4.284913383730375e-05 loss: 0.1224 (0.1141) time: 2.8997 data: 0.0078 max mem: 33369 +Epoch: [6] [ 810/2639] eta: 1:28:27 lr: 4.284479709990728e-05 loss: 0.0993 (0.1141) time: 2.9435 data: 0.0077 max mem: 33369 +Epoch: [6] [ 820/2639] eta: 1:27:59 lr: 4.284046031373656e-05 loss: 0.0951 (0.1139) time: 2.9608 data: 0.0076 max mem: 33369 +Epoch: [6] [ 830/2639] eta: 1:27:29 lr: 4.2836123478785554e-05 loss: 0.0863 (0.1136) time: 2.9107 data: 0.0080 max mem: 33369 +Epoch: [6] [ 840/2639] eta: 1:27:01 lr: 4.283178659504825e-05 loss: 0.0959 (0.1136) time: 2.9116 data: 0.0082 max mem: 33369 +Epoch: [6] [ 850/2639] eta: 1:26:32 lr: 4.2827449662518593e-05 loss: 0.1096 (0.1136) time: 2.9308 data: 0.0080 max mem: 33369 +Epoch: [6] [ 860/2639] eta: 1:26:03 lr: 4.2823112681190536e-05 loss: 0.1109 (0.1139) time: 2.8932 data: 0.0080 max mem: 33369 +Epoch: [6] [ 870/2639] eta: 1:25:34 lr: 4.2818775651058054e-05 loss: 0.1127 (0.1139) time: 2.9029 data: 0.0082 max mem: 33369 +Epoch: [6] [ 880/2639] eta: 1:25:06 lr: 4.28144385721151e-05 loss: 0.1127 (0.1141) time: 2.9247 data: 0.0083 max mem: 33369 +Epoch: [6] [ 890/2639] eta: 1:24:37 lr: 4.281010144435563e-05 loss: 0.1218 (0.1142) time: 2.9082 data: 0.0080 max mem: 33369 +Epoch: [6] [ 900/2639] eta: 1:24:09 lr: 4.2805764267773594e-05 loss: 0.1109 (0.1140) time: 2.9332 data: 0.0077 max mem: 33369 +Epoch: [6] [ 910/2639] eta: 1:23:40 lr: 4.280142704236296e-05 loss: 0.0930 (0.1139) time: 2.9405 data: 0.0076 max mem: 33369 +Epoch: [6] [ 920/2639] eta: 1:23:10 lr: 4.2797089768117666e-05 loss: 0.1018 (0.1139) time: 2.8967 data: 0.0076 max mem: 33369 +Epoch: [6] [ 930/2639] eta: 1:22:42 lr: 4.279275244503166e-05 loss: 0.1039 (0.1139) time: 2.9003 data: 0.0076 max mem: 33369 +Epoch: [6] [ 940/2639] eta: 1:22:13 lr: 4.278841507309892e-05 loss: 0.0972 (0.1138) time: 2.9190 data: 0.0076 max mem: 33369 +Epoch: [6] [ 950/2639] eta: 1:21:45 lr: 4.278407765231336e-05 loss: 0.0942 (0.1137) time: 2.9332 data: 0.0077 max mem: 33369 +Epoch: [6] [ 960/2639] eta: 1:21:17 lr: 4.2779740182668946e-05 loss: 0.0975 (0.1137) time: 2.9685 data: 0.0077 max mem: 33369 +Epoch: [6] [ 970/2639] eta: 1:20:48 lr: 4.2775402664159614e-05 loss: 0.1021 (0.1135) time: 2.9577 data: 0.0077 max mem: 33369 +Epoch: [6] [ 980/2639] eta: 1:20:20 lr: 4.277106509677932e-05 loss: 0.0994 (0.1134) time: 2.9283 data: 0.0080 max mem: 33369 +Epoch: [6] [ 990/2639] eta: 1:19:50 lr: 4.276672748052199e-05 loss: 0.0986 (0.1133) time: 2.8972 data: 0.0080 max mem: 33369 +Epoch: [6] [1000/2639] eta: 1:19:21 lr: 4.276238981538157e-05 loss: 0.0994 (0.1131) time: 2.8753 data: 0.0081 max mem: 33369 +Epoch: [6] [1010/2639] eta: 1:18:51 lr: 4.2758052101352014e-05 loss: 0.0990 (0.1129) time: 2.8870 data: 0.0083 max mem: 33369 +Epoch: [6] [1020/2639] eta: 1:18:22 lr: 4.275371433842724e-05 loss: 0.0964 (0.1129) time: 2.8841 data: 0.0082 max mem: 33369 +Epoch: [6] [1030/2639] eta: 1:17:52 lr: 4.27493765266012e-05 loss: 0.1162 (0.1136) time: 2.8602 data: 0.0083 max mem: 33369 +Epoch: [6] [1040/2639] eta: 1:17:23 lr: 4.2745038665867815e-05 loss: 0.1100 (0.1136) time: 2.8802 data: 0.0083 max mem: 33369 +Epoch: [6] [1050/2639] eta: 1:16:53 lr: 4.274070075622103e-05 loss: 0.1010 (0.1136) time: 2.8872 data: 0.0080 max mem: 33369 +Epoch: [6] [1060/2639] eta: 1:16:24 lr: 4.273636279765478e-05 loss: 0.1112 (0.1136) time: 2.8636 data: 0.0080 max mem: 33369 +Epoch: [6] [1070/2639] eta: 1:15:55 lr: 4.2732024790162975e-05 loss: 0.1208 (0.1137) time: 2.8951 data: 0.0081 max mem: 33369 +Epoch: [6] [1080/2639] eta: 1:15:27 lr: 4.272768673373957e-05 loss: 0.1150 (0.1138) time: 2.9429 data: 0.0082 max mem: 33369 +Epoch: [6] [1090/2639] eta: 1:14:58 lr: 4.272334862837848e-05 loss: 0.1084 (0.1137) time: 2.9238 data: 0.0083 max mem: 33369 +Epoch: [6] [1100/2639] eta: 1:14:28 lr: 4.271901047407364e-05 loss: 0.1173 (0.1139) time: 2.8677 data: 0.0087 max mem: 33369 +Epoch: [6] [1110/2639] eta: 1:13:59 lr: 4.271467227081896e-05 loss: 0.1178 (0.1139) time: 2.8730 data: 0.0086 max mem: 33369 +Epoch: [6] [1120/2639] eta: 1:13:30 lr: 4.2710334018608375e-05 loss: 0.1060 (0.1139) time: 2.8972 data: 0.0081 max mem: 33369 +Epoch: [6] [1130/2639] eta: 1:13:01 lr: 4.27059957174358e-05 loss: 0.0908 (0.1137) time: 2.9350 data: 0.0077 max mem: 33369 +Epoch: [6] [1140/2639] eta: 1:12:34 lr: 4.2701657367295164e-05 loss: 0.0943 (0.1136) time: 2.9869 data: 0.0077 max mem: 33369 +Epoch: [6] [1150/2639] eta: 1:12:04 lr: 4.269731896818039e-05 loss: 0.0958 (0.1136) time: 2.9191 data: 0.0084 max mem: 33369 +Epoch: [6] [1160/2639] eta: 1:11:35 lr: 4.2692980520085377e-05 loss: 0.1078 (0.1135) time: 2.8676 data: 0.0082 max mem: 33369 +Epoch: [6] [1170/2639] eta: 1:11:05 lr: 4.2688642023004064e-05 loss: 0.1011 (0.1135) time: 2.8932 data: 0.0079 max mem: 33369 +Epoch: [6] [1180/2639] eta: 1:10:36 lr: 4.2684303476930346e-05 loss: 0.1103 (0.1135) time: 2.8877 data: 0.0082 max mem: 33369 +Epoch: [6] [1190/2639] eta: 1:10:07 lr: 4.267996488185816e-05 loss: 0.1071 (0.1135) time: 2.9064 data: 0.0080 max mem: 33369 +Epoch: [6] [1200/2639] eta: 1:09:38 lr: 4.267562623778139e-05 loss: 0.1071 (0.1135) time: 2.9053 data: 0.0077 max mem: 33369 +Epoch: [6] [1210/2639] eta: 1:09:09 lr: 4.267128754469397e-05 loss: 0.1147 (0.1135) time: 2.8952 data: 0.0076 max mem: 33369 +Epoch: [6] [1220/2639] eta: 1:08:40 lr: 4.2666948802589794e-05 loss: 0.0903 (0.1136) time: 2.8889 data: 0.0074 max mem: 33369 +Epoch: [6] [1230/2639] eta: 1:08:10 lr: 4.266261001146278e-05 loss: 0.0950 (0.1135) time: 2.8636 data: 0.0076 max mem: 33369 +Epoch: [6] [1240/2639] eta: 1:07:42 lr: 4.265827117130683e-05 loss: 0.1118 (0.1136) time: 2.9018 data: 0.0075 max mem: 33369 +Epoch: [6] [1250/2639] eta: 1:07:13 lr: 4.2653932282115845e-05 loss: 0.0999 (0.1136) time: 2.9353 data: 0.0074 max mem: 33369 +Epoch: [6] [1260/2639] eta: 1:06:43 lr: 4.2649593343883735e-05 loss: 0.0999 (0.1137) time: 2.8949 data: 0.0074 max mem: 33369 +Epoch: [6] [1270/2639] eta: 1:06:14 lr: 4.2645254356604405e-05 loss: 0.1088 (0.1136) time: 2.8774 data: 0.0074 max mem: 33369 +Epoch: [6] [1280/2639] eta: 1:05:45 lr: 4.2640915320271744e-05 loss: 0.1055 (0.1136) time: 2.9110 data: 0.0075 max mem: 33369 +Epoch: [6] [1290/2639] eta: 1:05:16 lr: 4.263657623487966e-05 loss: 0.0967 (0.1135) time: 2.9066 data: 0.0077 max mem: 33369 +Epoch: [6] [1300/2639] eta: 1:04:46 lr: 4.2632237100422054e-05 loss: 0.0943 (0.1135) time: 2.8604 data: 0.0078 max mem: 33369 +Epoch: [6] [1310/2639] eta: 1:04:17 lr: 4.2627897916892814e-05 loss: 0.1031 (0.1136) time: 2.8708 data: 0.0079 max mem: 33369 +Epoch: [6] [1320/2639] eta: 1:03:49 lr: 4.262355868428583e-05 loss: 0.1108 (0.1137) time: 2.9084 data: 0.0079 max mem: 33369 +Epoch: [6] [1330/2639] eta: 1:03:19 lr: 4.261921940259501e-05 loss: 0.1104 (0.1137) time: 2.8811 data: 0.0078 max mem: 33369 +Epoch: [6] [1340/2639] eta: 1:02:50 lr: 4.2614880071814234e-05 loss: 0.1145 (0.1137) time: 2.8807 data: 0.0077 max mem: 33369 +Epoch: [6] [1350/2639] eta: 1:02:21 lr: 4.2610540691937404e-05 loss: 0.1145 (0.1137) time: 2.8974 data: 0.0081 max mem: 33369 +Epoch: [6] [1360/2639] eta: 1:01:51 lr: 4.26062012629584e-05 loss: 0.1126 (0.1137) time: 2.8584 data: 0.0083 max mem: 33369 +Epoch: [6] [1370/2639] eta: 1:01:22 lr: 4.26018617848711e-05 loss: 0.1059 (0.1137) time: 2.8560 data: 0.0079 max mem: 33369 +Epoch: [6] [1380/2639] eta: 1:00:52 lr: 4.2597522257669415e-05 loss: 0.1059 (0.1136) time: 2.8577 data: 0.0080 max mem: 33369 +Epoch: [6] [1390/2639] eta: 1:00:23 lr: 4.259318268134721e-05 loss: 0.1059 (0.1137) time: 2.8699 data: 0.0078 max mem: 33369 +Epoch: [6] [1400/2639] eta: 0:59:54 lr: 4.258884305589838e-05 loss: 0.1067 (0.1136) time: 2.8807 data: 0.0077 max mem: 33369 +Epoch: [6] [1410/2639] eta: 0:59:25 lr: 4.25845033813168e-05 loss: 0.1018 (0.1135) time: 2.8790 data: 0.0076 max mem: 33369 +Epoch: [6] [1420/2639] eta: 0:58:56 lr: 4.258016365759635e-05 loss: 0.1004 (0.1134) time: 2.9043 data: 0.0076 max mem: 33369 +Epoch: [6] [1430/2639] eta: 0:58:27 lr: 4.257582388473091e-05 loss: 0.1004 (0.1133) time: 2.8933 data: 0.0078 max mem: 33369 +Epoch: [6] [1440/2639] eta: 0:57:58 lr: 4.257148406271436e-05 loss: 0.0958 (0.1132) time: 2.8827 data: 0.0079 max mem: 33369 +Epoch: [6] [1450/2639] eta: 0:57:29 lr: 4.256714419154057e-05 loss: 0.0979 (0.1132) time: 2.8959 data: 0.0079 max mem: 33369 +Epoch: [6] [1460/2639] eta: 0:56:59 lr: 4.256280427120342e-05 loss: 0.1094 (0.1133) time: 2.8949 data: 0.0078 max mem: 33369 +Epoch: [6] [1470/2639] eta: 0:56:30 lr: 4.255846430169678e-05 loss: 0.1241 (0.1134) time: 2.8883 data: 0.0080 max mem: 33369 +Epoch: [6] [1480/2639] eta: 0:56:02 lr: 4.255412428301453e-05 loss: 0.1128 (0.1133) time: 2.9113 data: 0.0079 max mem: 33369 +Epoch: [6] [1490/2639] eta: 0:55:33 lr: 4.254978421515052e-05 loss: 0.1019 (0.1133) time: 2.9468 data: 0.0076 max mem: 33369 +Epoch: [6] [1500/2639] eta: 0:55:04 lr: 4.254544409809864e-05 loss: 0.0911 (0.1133) time: 2.9442 data: 0.0075 max mem: 33369 +Epoch: [6] [1510/2639] eta: 0:54:36 lr: 4.2541103931852746e-05 loss: 0.1054 (0.1132) time: 2.9575 data: 0.0071 max mem: 33369 +Epoch: [6] [1520/2639] eta: 0:54:07 lr: 4.253676371640671e-05 loss: 0.0949 (0.1132) time: 2.9569 data: 0.0071 max mem: 33369 +Epoch: [6] [1530/2639] eta: 0:53:38 lr: 4.2532423451754386e-05 loss: 0.1060 (0.1132) time: 2.9502 data: 0.0075 max mem: 33369 +Epoch: [6] [1540/2639] eta: 0:53:09 lr: 4.252808313788965e-05 loss: 0.1193 (0.1135) time: 2.9345 data: 0.0075 max mem: 33369 +Epoch: [6] [1550/2639] eta: 0:52:41 lr: 4.2523742774806355e-05 loss: 0.1223 (0.1136) time: 2.9323 data: 0.0075 max mem: 33369 +Epoch: [6] [1560/2639] eta: 0:52:12 lr: 4.251940236249836e-05 loss: 0.1155 (0.1137) time: 2.9530 data: 0.0078 max mem: 33369 +Epoch: [6] [1570/2639] eta: 0:51:43 lr: 4.251506190095953e-05 loss: 0.1098 (0.1138) time: 2.9288 data: 0.0081 max mem: 33369 +Epoch: [6] [1580/2639] eta: 0:51:14 lr: 4.251072139018371e-05 loss: 0.1079 (0.1139) time: 2.9062 data: 0.0076 max mem: 33369 +Epoch: [6] [1590/2639] eta: 0:50:45 lr: 4.250638083016477e-05 loss: 0.0988 (0.1138) time: 2.9206 data: 0.0077 max mem: 33369 +Epoch: [6] [1600/2639] eta: 0:50:16 lr: 4.250204022089656e-05 loss: 0.1075 (0.1139) time: 2.9047 data: 0.0079 max mem: 33369 +Epoch: [6] [1610/2639] eta: 0:49:47 lr: 4.2497699562372924e-05 loss: 0.1187 (0.1139) time: 2.9055 data: 0.0079 max mem: 33369 +Epoch: [6] [1620/2639] eta: 0:49:18 lr: 4.2493358854587716e-05 loss: 0.1119 (0.1139) time: 2.8909 data: 0.0081 max mem: 33369 +Epoch: [6] [1630/2639] eta: 0:48:48 lr: 4.2489018097534795e-05 loss: 0.1078 (0.1138) time: 2.8343 data: 0.0079 max mem: 33369 +Epoch: [6] [1640/2639] eta: 0:48:19 lr: 4.2484677291207996e-05 loss: 0.0920 (0.1139) time: 2.8615 data: 0.0078 max mem: 33369 +Epoch: [6] [1650/2639] eta: 0:47:50 lr: 4.248033643560118e-05 loss: 0.0920 (0.1139) time: 2.8870 data: 0.0075 max mem: 33369 +Epoch: [6] [1660/2639] eta: 0:47:21 lr: 4.247599553070818e-05 loss: 0.1079 (0.1140) time: 2.8810 data: 0.0075 max mem: 33369 +Epoch: [6] [1670/2639] eta: 0:46:52 lr: 4.247165457652285e-05 loss: 0.1131 (0.1141) time: 2.8894 data: 0.0079 max mem: 33369 +Epoch: [6] [1680/2639] eta: 0:46:23 lr: 4.2467313573039013e-05 loss: 0.1131 (0.1142) time: 2.8785 data: 0.0085 max mem: 33369 +Epoch: [6] [1690/2639] eta: 0:45:54 lr: 4.2462972520250536e-05 loss: 0.1139 (0.1143) time: 2.8832 data: 0.0084 max mem: 33369 +Epoch: [6] [1700/2639] eta: 0:45:24 lr: 4.2458631418151243e-05 loss: 0.1113 (0.1144) time: 2.8895 data: 0.0082 max mem: 33369 +Epoch: [6] [1710/2639] eta: 0:44:56 lr: 4.2454290266734975e-05 loss: 0.1113 (0.1144) time: 2.9226 data: 0.0085 max mem: 33369 +Epoch: [6] [1720/2639] eta: 0:44:27 lr: 4.2449949065995565e-05 loss: 0.1088 (0.1145) time: 2.9368 data: 0.0081 max mem: 33369 +Epoch: [6] [1730/2639] eta: 0:43:58 lr: 4.244560781592685e-05 loss: 0.1376 (0.1147) time: 2.9087 data: 0.0075 max mem: 33369 +Epoch: [6] [1740/2639] eta: 0:43:29 lr: 4.2441266516522667e-05 loss: 0.1144 (0.1147) time: 2.9199 data: 0.0077 max mem: 33369 +Epoch: [6] [1750/2639] eta: 0:43:00 lr: 4.243692516777684e-05 loss: 0.1070 (0.1148) time: 2.8879 data: 0.0076 max mem: 33369 +Epoch: [6] [1760/2639] eta: 0:42:31 lr: 4.243258376968321e-05 loss: 0.1307 (0.1150) time: 2.9076 data: 0.0077 max mem: 33369 +Epoch: [6] [1770/2639] eta: 0:42:02 lr: 4.242824232223561e-05 loss: 0.1120 (0.1149) time: 2.9416 data: 0.0078 max mem: 33369 +Epoch: [6] [1780/2639] eta: 0:41:33 lr: 4.242390082542784e-05 loss: 0.0974 (0.1149) time: 2.8896 data: 0.0078 max mem: 33369 +Epoch: [6] [1790/2639] eta: 0:41:04 lr: 4.241955927925375e-05 loss: 0.0973 (0.1148) time: 2.8692 data: 0.0079 max mem: 33369 +Epoch: [6] [1800/2639] eta: 0:40:34 lr: 4.2415217683707167e-05 loss: 0.0994 (0.1148) time: 2.8625 data: 0.0079 max mem: 33369 +Epoch: [6] [1810/2639] eta: 0:40:05 lr: 4.2410876038781897e-05 loss: 0.1133 (0.1148) time: 2.8653 data: 0.0080 max mem: 33369 +Epoch: [6] [1820/2639] eta: 0:39:36 lr: 4.240653434447177e-05 loss: 0.1217 (0.1148) time: 2.8830 data: 0.0080 max mem: 33369 +Epoch: [6] [1830/2639] eta: 0:39:07 lr: 4.240219260077062e-05 loss: 0.1175 (0.1150) time: 2.8972 data: 0.0081 max mem: 33369 +Epoch: [6] [1840/2639] eta: 0:38:38 lr: 4.239785080767225e-05 loss: 0.1175 (0.1150) time: 2.9193 data: 0.0081 max mem: 33369 +Epoch: [6] [1850/2639] eta: 0:38:09 lr: 4.239350896517047e-05 loss: 0.0962 (0.1149) time: 2.9282 data: 0.0080 max mem: 33369 +Epoch: [6] [1860/2639] eta: 0:37:40 lr: 4.2389167073259114e-05 loss: 0.1068 (0.1150) time: 2.9328 data: 0.0079 max mem: 33369 +Epoch: [6] [1870/2639] eta: 0:37:11 lr: 4.238482513193198e-05 loss: 0.1068 (0.1150) time: 2.9045 data: 0.0076 max mem: 33369 +Epoch: [6] [1880/2639] eta: 0:36:42 lr: 4.2380483141182895e-05 loss: 0.1047 (0.1149) time: 2.8973 data: 0.0075 max mem: 33369 +Epoch: [6] [1890/2639] eta: 0:36:13 lr: 4.237614110100566e-05 loss: 0.1168 (0.1151) time: 2.9091 data: 0.0076 max mem: 33369 +Epoch: [6] [1900/2639] eta: 0:35:44 lr: 4.2371799011394094e-05 loss: 0.1079 (0.1151) time: 2.9105 data: 0.0076 max mem: 33369 +Epoch: [6] [1910/2639] eta: 0:35:15 lr: 4.236745687234199e-05 loss: 0.1001 (0.1151) time: 2.9105 data: 0.0077 max mem: 33369 +Epoch: [6] [1920/2639] eta: 0:34:46 lr: 4.236311468384318e-05 loss: 0.1266 (0.1152) time: 2.8961 data: 0.0076 max mem: 33369 +Epoch: [6] [1930/2639] eta: 0:34:17 lr: 4.235877244589144e-05 loss: 0.1019 (0.1152) time: 2.8868 data: 0.0075 max mem: 33369 +Epoch: [6] [1940/2639] eta: 0:33:48 lr: 4.23544301584806e-05 loss: 0.1066 (0.1152) time: 2.8574 data: 0.0075 max mem: 33369 +Epoch: [6] [1950/2639] eta: 0:33:19 lr: 4.2350087821604446e-05 loss: 0.1020 (0.1151) time: 2.8728 data: 0.0078 max mem: 33369 +Epoch: [6] [1960/2639] eta: 0:32:50 lr: 4.234574543525679e-05 loss: 0.1020 (0.1151) time: 2.9124 data: 0.0081 max mem: 33369 +Epoch: [6] [1970/2639] eta: 0:32:21 lr: 4.234140299943142e-05 loss: 0.1110 (0.1151) time: 2.9134 data: 0.0080 max mem: 33369 +Epoch: [6] [1980/2639] eta: 0:31:52 lr: 4.233706051412214e-05 loss: 0.0956 (0.1150) time: 2.9327 data: 0.0079 max mem: 33369 +Epoch: [6] [1990/2639] eta: 0:31:23 lr: 4.2332717979322745e-05 loss: 0.1070 (0.1150) time: 2.9351 data: 0.0078 max mem: 33369 +Epoch: [6] [2000/2639] eta: 0:30:54 lr: 4.2328375395027026e-05 loss: 0.1083 (0.1150) time: 2.8819 data: 0.0075 max mem: 33369 +Epoch: [6] [2010/2639] eta: 0:30:25 lr: 4.2324032761228785e-05 loss: 0.1133 (0.1151) time: 2.8913 data: 0.0075 max mem: 33369 +Epoch: [6] [2020/2639] eta: 0:29:56 lr: 4.231969007792182e-05 loss: 0.1112 (0.1151) time: 2.9100 data: 0.0075 max mem: 33369 +Epoch: [6] [2030/2639] eta: 0:29:27 lr: 4.2315347345099905e-05 loss: 0.1103 (0.1151) time: 2.9042 data: 0.0080 max mem: 33369 +Epoch: [6] [2040/2639] eta: 0:28:58 lr: 4.231100456275683e-05 loss: 0.1195 (0.1152) time: 2.8967 data: 0.0082 max mem: 33369 +Epoch: [6] [2050/2639] eta: 0:28:29 lr: 4.23066617308864e-05 loss: 0.0964 (0.1151) time: 2.8878 data: 0.0077 max mem: 33369 +Epoch: [6] [2060/2639] eta: 0:28:00 lr: 4.230231884948238e-05 loss: 0.0984 (0.1151) time: 2.9030 data: 0.0075 max mem: 33369 +Epoch: [6] [2070/2639] eta: 0:27:31 lr: 4.2297975918538566e-05 loss: 0.1098 (0.1151) time: 2.9100 data: 0.0076 max mem: 33369 +Epoch: [6] [2080/2639] eta: 0:27:02 lr: 4.2293632938048743e-05 loss: 0.0958 (0.1150) time: 2.9448 data: 0.0075 max mem: 33369 +Epoch: [6] [2090/2639] eta: 0:26:33 lr: 4.2289289908006694e-05 loss: 0.0932 (0.1150) time: 2.9491 data: 0.0075 max mem: 33369 +Epoch: [6] [2100/2639] eta: 0:26:04 lr: 4.228494682840618e-05 loss: 0.1050 (0.1150) time: 2.9161 data: 0.0078 max mem: 33369 +Epoch: [6] [2110/2639] eta: 0:25:35 lr: 4.2280603699241003e-05 loss: 0.1065 (0.1150) time: 2.9054 data: 0.0079 max mem: 33369 +Epoch: [6] [2120/2639] eta: 0:25:06 lr: 4.227626052050493e-05 loss: 0.0989 (0.1149) time: 2.8813 data: 0.0076 max mem: 33369 +Epoch: [6] [2130/2639] eta: 0:24:37 lr: 4.2271917292191744e-05 loss: 0.1029 (0.1150) time: 2.9011 data: 0.0075 max mem: 33369 +Epoch: [6] [2140/2639] eta: 0:24:08 lr: 4.22675740142952e-05 loss: 0.1026 (0.1150) time: 2.9118 data: 0.0075 max mem: 33369 +Epoch: [6] [2150/2639] eta: 0:23:39 lr: 4.22632306868091e-05 loss: 0.0924 (0.1149) time: 2.8756 data: 0.0075 max mem: 33369 +Epoch: [6] [2160/2639] eta: 0:23:10 lr: 4.225888730972718e-05 loss: 0.1015 (0.1150) time: 2.8864 data: 0.0074 max mem: 33369 +Epoch: [6] [2170/2639] eta: 0:22:41 lr: 4.225454388304324e-05 loss: 0.1163 (0.1150) time: 2.8809 data: 0.0073 max mem: 33369 +Epoch: [6] [2180/2639] eta: 0:22:12 lr: 4.225020040675103e-05 loss: 0.1163 (0.1151) time: 2.8757 data: 0.0074 max mem: 33369 +Epoch: [6] [2190/2639] eta: 0:21:42 lr: 4.224585688084433e-05 loss: 0.1142 (0.1151) time: 2.8561 data: 0.0078 max mem: 33369 +Epoch: [6] [2200/2639] eta: 0:21:13 lr: 4.2241513305316896e-05 loss: 0.1165 (0.1151) time: 2.8496 data: 0.0079 max mem: 33369 +Epoch: [6] [2210/2639] eta: 0:20:44 lr: 4.2237169680162494e-05 loss: 0.1155 (0.1151) time: 2.8798 data: 0.0080 max mem: 33369 +Epoch: [6] [2220/2639] eta: 0:20:15 lr: 4.223282600537489e-05 loss: 0.1123 (0.1152) time: 2.8530 data: 0.0084 max mem: 33369 +Epoch: [6] [2230/2639] eta: 0:19:46 lr: 4.222848228094784e-05 loss: 0.1174 (0.1152) time: 2.8876 data: 0.0080 max mem: 33369 +Epoch: [6] [2240/2639] eta: 0:19:17 lr: 4.22241385068751e-05 loss: 0.0994 (0.1152) time: 2.9642 data: 0.0076 max mem: 33369 +Epoch: [6] [2250/2639] eta: 0:18:48 lr: 4.221979468315043e-05 loss: 0.0920 (0.1152) time: 2.9588 data: 0.0078 max mem: 33369 +Epoch: [6] [2260/2639] eta: 0:18:19 lr: 4.2215450809767596e-05 loss: 0.1045 (0.1152) time: 2.9561 data: 0.0078 max mem: 33369 +Epoch: [6] [2270/2639] eta: 0:17:51 lr: 4.221110688672034e-05 loss: 0.1219 (0.1152) time: 2.9633 data: 0.0074 max mem: 33369 +Epoch: [6] [2280/2639] eta: 0:17:22 lr: 4.220676291400242e-05 loss: 0.1214 (0.1151) time: 2.9580 data: 0.0072 max mem: 33369 +Epoch: [6] [2290/2639] eta: 0:16:53 lr: 4.220241889160759e-05 loss: 0.1011 (0.1151) time: 2.9480 data: 0.0073 max mem: 33369 +Epoch: [6] [2300/2639] eta: 0:16:24 lr: 4.2198074819529605e-05 loss: 0.0977 (0.1150) time: 2.9310 data: 0.0074 max mem: 33369 +Epoch: [6] [2310/2639] eta: 0:15:55 lr: 4.21937306977622e-05 loss: 0.1044 (0.1150) time: 2.9151 data: 0.0076 max mem: 33369 +Epoch: [6] [2320/2639] eta: 0:15:26 lr: 4.218938652629913e-05 loss: 0.1161 (0.1150) time: 2.8860 data: 0.0080 max mem: 33369 +Epoch: [6] [2330/2639] eta: 0:14:56 lr: 4.218504230513414e-05 loss: 0.1206 (0.1151) time: 2.8516 data: 0.0082 max mem: 33369 +Epoch: [6] [2340/2639] eta: 0:14:27 lr: 4.2180698034260974e-05 loss: 0.1256 (0.1152) time: 2.8606 data: 0.0079 max mem: 33369 +Epoch: [6] [2350/2639] eta: 0:13:58 lr: 4.217635371367338e-05 loss: 0.0993 (0.1151) time: 2.9030 data: 0.0075 max mem: 33369 +Epoch: [6] [2360/2639] eta: 0:13:29 lr: 4.217200934336508e-05 loss: 0.0971 (0.1151) time: 2.8870 data: 0.0075 max mem: 33369 +Epoch: [6] [2370/2639] eta: 0:13:00 lr: 4.2167664923329834e-05 loss: 0.1057 (0.1151) time: 2.8552 data: 0.0076 max mem: 33369 +Epoch: [6] [2380/2639] eta: 0:12:31 lr: 4.216332045356138e-05 loss: 0.1060 (0.1151) time: 2.8501 data: 0.0078 max mem: 33369 +Epoch: [6] [2390/2639] eta: 0:12:02 lr: 4.2158975934053445e-05 loss: 0.1146 (0.1151) time: 2.8481 data: 0.0078 max mem: 33369 +Epoch: [6] [2400/2639] eta: 0:11:33 lr: 4.2154631364799766e-05 loss: 0.0910 (0.1151) time: 2.8700 data: 0.0075 max mem: 33369 +Epoch: [6] [2410/2639] eta: 0:11:04 lr: 4.215028674579408e-05 loss: 0.0911 (0.1151) time: 2.8613 data: 0.0075 max mem: 33369 +Epoch: [6] [2420/2639] eta: 0:10:35 lr: 4.214594207703012e-05 loss: 0.0911 (0.1150) time: 2.8830 data: 0.0080 max mem: 33369 +Epoch: [6] [2430/2639] eta: 0:10:06 lr: 4.2141597358501614e-05 loss: 0.0970 (0.1150) time: 2.8836 data: 0.0079 max mem: 33369 +Epoch: [6] [2440/2639] eta: 0:09:37 lr: 4.2137252590202294e-05 loss: 0.0985 (0.1149) time: 2.8902 data: 0.0076 max mem: 33369 +Epoch: [6] [2450/2639] eta: 0:09:08 lr: 4.213290777212588e-05 loss: 0.0985 (0.1149) time: 2.9389 data: 0.0079 max mem: 33369 +Epoch: [6] [2460/2639] eta: 0:08:39 lr: 4.212856290426611e-05 loss: 0.1021 (0.1149) time: 2.9407 data: 0.0082 max mem: 33369 +Epoch: [6] [2470/2639] eta: 0:08:10 lr: 4.2124217986616684e-05 loss: 0.1154 (0.1150) time: 2.9195 data: 0.0083 max mem: 33369 +Epoch: [6] [2480/2639] eta: 0:07:41 lr: 4.211987301917136e-05 loss: 0.1136 (0.1150) time: 2.8733 data: 0.0079 max mem: 33369 +Epoch: [6] [2490/2639] eta: 0:07:12 lr: 4.211552800192384e-05 loss: 0.1189 (0.1150) time: 2.8962 data: 0.0075 max mem: 33369 +Epoch: [6] [2500/2639] eta: 0:06:43 lr: 4.2111182934867846e-05 loss: 0.1236 (0.1151) time: 2.8787 data: 0.0074 max mem: 33369 +Epoch: [6] [2510/2639] eta: 0:06:14 lr: 4.2106837817997094e-05 loss: 0.1111 (0.1150) time: 2.8671 data: 0.0075 max mem: 33369 +Epoch: [6] [2520/2639] eta: 0:05:45 lr: 4.210249265130531e-05 loss: 0.0851 (0.1150) time: 2.8973 data: 0.0076 max mem: 33369 +Epoch: [6] [2530/2639] eta: 0:05:16 lr: 4.20981474347862e-05 loss: 0.0954 (0.1151) time: 2.8898 data: 0.0079 max mem: 33369 +Epoch: [6] [2540/2639] eta: 0:04:47 lr: 4.2093802168433476e-05 loss: 0.1228 (0.1151) time: 2.9075 data: 0.0080 max mem: 33369 +Epoch: [6] [2550/2639] eta: 0:04:18 lr: 4.208945685224087e-05 loss: 0.1178 (0.1151) time: 2.9153 data: 0.0076 max mem: 33369 +Epoch: [6] [2560/2639] eta: 0:03:49 lr: 4.208511148620208e-05 loss: 0.1056 (0.1151) time: 2.8693 data: 0.0076 max mem: 33369 +Epoch: [6] [2570/2639] eta: 0:03:20 lr: 4.20807660703108e-05 loss: 0.1056 (0.1151) time: 2.8526 data: 0.0077 max mem: 33369 +Epoch: [6] [2580/2639] eta: 0:02:51 lr: 4.2076420604560764e-05 loss: 0.1032 (0.1150) time: 2.9044 data: 0.0076 max mem: 33369 +Epoch: [6] [2590/2639] eta: 0:02:22 lr: 4.207207508894566e-05 loss: 0.0956 (0.1151) time: 2.9383 data: 0.0074 max mem: 33369 +Epoch: [6] [2600/2639] eta: 0:01:53 lr: 4.206772952345921e-05 loss: 0.1166 (0.1152) time: 2.9532 data: 0.0079 max mem: 33369 +Epoch: [6] [2610/2639] eta: 0:01:24 lr: 4.20633839080951e-05 loss: 0.1234 (0.1152) time: 2.9227 data: 0.0084 max mem: 33369 +Epoch: [6] [2620/2639] eta: 0:00:55 lr: 4.2059038242847045e-05 loss: 0.1234 (0.1153) time: 2.9051 data: 0.0081 max mem: 33369 +Epoch: [6] [2630/2639] eta: 0:00:26 lr: 4.2054692527708737e-05 loss: 0.1103 (0.1152) time: 2.9246 data: 0.0073 max mem: 33369 +Epoch: [6] Total time: 2:07:38 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 2:25:11 time: 3.3857 data: 3.2933 max mem: 33369 +Test: [ 100/2573] eta: 0:04:35 time: 0.0787 data: 0.0014 max mem: 33369 +Test: [ 200/2573] eta: 0:03:47 time: 0.0798 data: 0.0015 max mem: 33369 +Test: [ 300/2573] eta: 0:03:25 time: 0.0817 data: 0.0014 max mem: 33369 +Test: [ 400/2573] eta: 0:03:10 time: 0.0815 data: 0.0014 max mem: 33369 +Test: [ 500/2573] eta: 0:02:58 time: 0.0810 data: 0.0014 max mem: 33369 +Test: [ 600/2573] eta: 0:02:48 time: 0.0807 data: 0.0014 max mem: 33369 +Test: [ 700/2573] eta: 0:02:39 time: 0.0813 data: 0.0016 max mem: 33369 +Test: [ 800/2573] eta: 0:02:30 time: 0.0844 data: 0.0014 max mem: 33369 +Test: [ 900/2573] eta: 0:02:21 time: 0.0805 data: 0.0014 max mem: 33369 +Test: [1000/2573] eta: 0:02:12 time: 0.0803 data: 0.0015 max mem: 33369 +Test: [1100/2573] eta: 0:02:03 time: 0.0798 data: 0.0014 max mem: 33369 +Test: [1200/2573] eta: 0:01:54 time: 0.0807 data: 0.0013 max mem: 33369 +Test: [1300/2573] eta: 0:01:46 time: 0.0822 data: 0.0014 max mem: 33369 +Test: [1400/2573] eta: 0:01:37 time: 0.0789 data: 0.0015 max mem: 33369 +Test: [1500/2573] eta: 0:01:29 time: 0.0805 data: 0.0014 max mem: 33369 +Test: [1600/2573] eta: 0:01:20 time: 0.0837 data: 0.0014 max mem: 33369 +Test: [1700/2573] eta: 0:01:12 time: 0.0817 data: 0.0015 max mem: 33369 +Test: [1800/2573] eta: 0:01:04 time: 0.0839 data: 0.0014 max mem: 33369 +Test: [1900/2573] eta: 0:00:55 time: 0.0798 data: 0.0014 max mem: 33369 +Test: [2000/2573] eta: 0:00:47 time: 0.0826 data: 0.0015 max mem: 33369 +Test: [2100/2573] eta: 0:00:39 time: 0.0830 data: 0.0014 max mem: 33369 +Test: [2200/2573] eta: 0:00:30 time: 0.0839 data: 0.0014 max mem: 33369 +Test: [2300/2573] eta: 0:00:22 time: 0.0833 data: 0.0015 max mem: 33369 +Test: [2400/2573] eta: 0:00:14 time: 0.0782 data: 0.0015 max mem: 33369 +Test: [2500/2573] eta: 0:00:06 time: 0.0800 data: 0.0014 max mem: 33369 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: Total time: 0:03:33 +Final results: +Mean IoU is 56.65 + + precision@0.5 = 62.79 + precision@0.6 = 55.72 + precision@0.7 = 46.88 + precision@0.8 = 34.95 + precision@0.9 = 15.87 + overall IoU = 56.44 + +Average object IoU 56.65142382218852 +Overall IoU 56.435691833496094 +Better epoch: 6 + +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [7] [ 0/2639] eta: 3:59:47 lr: 4.205078134142289e-05 loss: 0.0822 (0.0822) time: 5.4517 data: 2.3143 max mem: 33369 +Epoch: [7] [ 10/2639] eta: 2:17:17 lr: 4.204643553147575e-05 loss: 0.0999 (0.1017) time: 3.1335 data: 0.2172 max mem: 33369 +Epoch: [7] [ 20/2639] eta: 2:12:20 lr: 4.2042089671620086e-05 loss: 0.0866 (0.0942) time: 2.9107 data: 0.0073 max mem: 33369 +Epoch: [7] [ 30/2639] eta: 2:10:20 lr: 4.203774376184958e-05 loss: 0.0798 (0.0923) time: 2.9226 data: 0.0075 max mem: 33369 +Epoch: [7] [ 40/2639] eta: 2:08:02 lr: 4.2033397802157936e-05 loss: 0.0817 (0.0954) time: 2.8766 data: 0.0077 max mem: 33369 +Epoch: [7] [ 50/2639] eta: 2:07:16 lr: 4.2029051792538845e-05 loss: 0.0791 (0.0928) time: 2.8758 data: 0.0078 max mem: 33369 +Epoch: [7] [ 60/2639] eta: 2:06:14 lr: 4.2024705732986e-05 loss: 0.0766 (0.0918) time: 2.8983 data: 0.0077 max mem: 33369 +Epoch: [7] [ 70/2639] eta: 2:05:11 lr: 4.2020359623493075e-05 loss: 0.0785 (0.0915) time: 2.8574 data: 0.0073 max mem: 33369 +Epoch: [7] [ 80/2639] eta: 2:04:54 lr: 4.2016013464053784e-05 loss: 0.0854 (0.0936) time: 2.9036 data: 0.0076 max mem: 33369 +Epoch: [7] [ 90/2639] eta: 2:04:14 lr: 4.2011667254661776e-05 loss: 0.1032 (0.0958) time: 2.9263 data: 0.0083 max mem: 33369 +Epoch: [7] [ 100/2639] eta: 2:03:44 lr: 4.200732099531077e-05 loss: 0.1032 (0.0966) time: 2.9046 data: 0.0081 max mem: 33369 +Epoch: [7] [ 110/2639] eta: 2:03:03 lr: 4.200297468599442e-05 loss: 0.1104 (0.0990) time: 2.8979 data: 0.0078 max mem: 33369 +Epoch: [7] [ 120/2639] eta: 2:02:31 lr: 4.1998628326706426e-05 loss: 0.1027 (0.0995) time: 2.8892 data: 0.0084 max mem: 33369 +Epoch: [7] [ 130/2639] eta: 2:02:02 lr: 4.199428191744046e-05 loss: 0.1038 (0.1023) time: 2.9119 data: 0.0084 max mem: 33369 +Epoch: [7] [ 140/2639] eta: 2:01:34 lr: 4.198993545819019e-05 loss: 0.1229 (0.1031) time: 2.9245 data: 0.0081 max mem: 33369 +Epoch: [7] [ 150/2639] eta: 2:01:04 lr: 4.1985588948949314e-05 loss: 0.0951 (0.1031) time: 2.9216 data: 0.0083 max mem: 33369 +Epoch: [7] [ 160/2639] eta: 2:00:24 lr: 4.19812423897115e-05 loss: 0.0749 (0.1020) time: 2.8808 data: 0.0080 max mem: 33369 +Epoch: [7] [ 170/2639] eta: 1:59:55 lr: 4.19768957804704e-05 loss: 0.0767 (0.1016) time: 2.8820 data: 0.0081 max mem: 33369 +Epoch: [7] [ 180/2639] eta: 1:59:16 lr: 4.197254912121971e-05 loss: 0.0851 (0.1007) time: 2.8763 data: 0.0081 max mem: 33369 +Epoch: [7] [ 190/2639] eta: 1:58:52 lr: 4.196820241195309e-05 loss: 0.0860 (0.1008) time: 2.8929 data: 0.0077 max mem: 33369 +Epoch: [7] [ 200/2639] eta: 1:58:31 lr: 4.196385565266422e-05 loss: 0.1006 (0.1016) time: 2.9656 data: 0.0080 max mem: 33369 +Epoch: [7] [ 210/2639] eta: 1:58:06 lr: 4.195950884334675e-05 loss: 0.0982 (0.1011) time: 2.9687 data: 0.0080 max mem: 33369 +Epoch: [7] [ 220/2639] eta: 1:57:34 lr: 4.195516198399434e-05 loss: 0.0918 (0.1011) time: 2.9223 data: 0.0080 max mem: 33369 +Epoch: [7] [ 230/2639] eta: 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+Epoch: [7] [ 390/2639] eta: 1:49:02 lr: 4.18812577135141e-05 loss: 0.0999 (0.1012) time: 2.9149 data: 0.0085 max mem: 33369 +Epoch: [7] [ 400/2639] eta: 1:48:33 lr: 4.1876909952448065e-05 loss: 0.0891 (0.1009) time: 2.9100 data: 0.0081 max mem: 33369 +Epoch: [7] [ 410/2639] eta: 1:48:02 lr: 4.1872562141226446e-05 loss: 0.0825 (0.1006) time: 2.8900 data: 0.0083 max mem: 33369 +Epoch: [7] [ 420/2639] eta: 1:47:32 lr: 4.1868214279842886e-05 loss: 0.0826 (0.1003) time: 2.8785 data: 0.0085 max mem: 33369 +Epoch: [7] [ 430/2639] eta: 1:47:01 lr: 4.186386636829102e-05 loss: 0.0882 (0.1004) time: 2.8842 data: 0.0081 max mem: 33369 +Epoch: [7] [ 440/2639] eta: 1:46:30 lr: 4.185951840656448e-05 loss: 0.1056 (0.1006) time: 2.8752 data: 0.0082 max mem: 33369 +Epoch: [7] [ 450/2639] eta: 1:46:00 lr: 4.1855170394656906e-05 loss: 0.1016 (0.1004) time: 2.8764 data: 0.0087 max mem: 33369 +Epoch: [7] [ 460/2639] eta: 1:45:27 lr: 4.18508223325619e-05 loss: 0.0833 (0.1001) time: 2.8496 data: 0.0086 max mem: 33369 +Epoch: [7] [ 470/2639] eta: 1:44:57 lr: 4.1846474220273116e-05 loss: 0.0914 (0.1003) time: 2.8530 data: 0.0082 max mem: 33369 +Epoch: [7] [ 480/2639] eta: 1:44:25 lr: 4.184212605778416e-05 loss: 0.1118 (0.1008) time: 2.8616 data: 0.0083 max mem: 33369 +Epoch: [7] [ 490/2639] eta: 1:43:55 lr: 4.1837777845088666e-05 loss: 0.0916 (0.1007) time: 2.8612 data: 0.0080 max mem: 33369 +Epoch: [7] [ 500/2639] eta: 1:43:29 lr: 4.183342958218026e-05 loss: 0.0805 (0.1005) time: 2.9273 data: 0.0077 max mem: 33369 +Epoch: [7] [ 510/2639] eta: 1:43:00 lr: 4.1829081269052545e-05 loss: 0.0912 (0.1008) time: 2.9342 data: 0.0082 max mem: 33369 +Epoch: [7] [ 520/2639] eta: 1:42:29 lr: 4.182473290569917e-05 loss: 0.1033 (0.1009) time: 2.8804 data: 0.0084 max mem: 33369 +Epoch: [7] [ 530/2639] eta: 1:42:00 lr: 4.1820384492113715e-05 loss: 0.0970 (0.1008) time: 2.8729 data: 0.0078 max mem: 33369 +Epoch: [7] [ 540/2639] eta: 1:41:30 lr: 4.181603602828983e-05 loss: 0.0945 (0.1006) time: 2.8826 data: 0.0077 max mem: 33369 +Epoch: [7] [ 550/2639] eta: 1:40:59 lr: 4.181168751422111e-05 loss: 0.0948 (0.1007) time: 2.8679 data: 0.0077 max mem: 33369 +Epoch: [7] [ 560/2639] eta: 1:40:32 lr: 4.180733894990118e-05 loss: 0.1047 (0.1008) time: 2.8996 data: 0.0079 max mem: 33369 +Epoch: [7] [ 570/2639] eta: 1:40:03 lr: 4.180299033532364e-05 loss: 0.1004 (0.1006) time: 2.9208 data: 0.0089 max mem: 33369 +Epoch: [7] [ 580/2639] eta: 1:39:33 lr: 4.179864167048211e-05 loss: 0.0810 (0.1003) time: 2.8966 data: 0.0090 max mem: 33369 +Epoch: [7] [ 590/2639] eta: 1:39:05 lr: 4.179429295537019e-05 loss: 0.0850 (0.1005) time: 2.9018 data: 0.0082 max mem: 33369 +Epoch: [7] [ 600/2639] eta: 1:38:36 lr: 4.17899441899815e-05 loss: 0.0975 (0.1010) time: 2.9106 data: 0.0081 max mem: 33369 +Epoch: [7] [ 610/2639] eta: 1:38:07 lr: 4.178559537430963e-05 loss: 0.0979 (0.1010) time: 2.9155 data: 0.0081 max mem: 33369 +Epoch: [7] [ 620/2639] eta: 1:37:39 lr: 4.178124650834819e-05 loss: 0.0962 (0.1010) time: 2.9211 data: 0.0081 max mem: 33369 +Epoch: [7] [ 630/2639] eta: 1:37:09 lr: 4.177689759209078e-05 loss: 0.0941 (0.1009) time: 2.8917 data: 0.0082 max mem: 33369 +Epoch: [7] [ 640/2639] eta: 1:36:39 lr: 4.1772548625531004e-05 loss: 0.1015 (0.1012) time: 2.8707 data: 0.0081 max mem: 33369 +Epoch: [7] [ 650/2639] eta: 1:36:10 lr: 4.176819960866247e-05 loss: 0.0955 (0.1013) time: 2.8841 data: 0.0084 max mem: 33369 +Epoch: [7] [ 660/2639] eta: 1:35:39 lr: 4.176385054147876e-05 loss: 0.0915 (0.1012) time: 2.8750 data: 0.0083 max mem: 33369 +Epoch: [7] [ 670/2639] eta: 1:35:11 lr: 4.175950142397347e-05 loss: 0.0970 (0.1015) time: 2.8871 data: 0.0081 max mem: 33369 +Epoch: [7] [ 680/2639] eta: 1:34:42 lr: 4.175515225614021e-05 loss: 0.1028 (0.1020) time: 2.9137 data: 0.0087 max mem: 33369 +Epoch: [7] [ 690/2639] eta: 1:34:13 lr: 4.1750803037972556e-05 loss: 0.1019 (0.1018) time: 2.9118 data: 0.0087 max mem: 33369 +Epoch: [7] [ 700/2639] eta: 1:33:45 lr: 4.174645376946412e-05 loss: 0.0926 (0.1017) time: 2.9168 data: 0.0080 max mem: 33369 +Epoch: [7] [ 710/2639] eta: 1:33:14 lr: 4.174210445060846e-05 loss: 0.0899 (0.1017) time: 2.8837 data: 0.0078 max mem: 33369 +Epoch: [7] [ 720/2639] eta: 1:32:46 lr: 4.173775508139919e-05 loss: 0.0808 (0.1014) time: 2.8776 data: 0.0083 max mem: 33369 +Epoch: [7] [ 730/2639] eta: 1:32:15 lr: 4.1733405661829894e-05 loss: 0.0806 (0.1013) time: 2.8738 data: 0.0087 max mem: 33369 +Epoch: [7] [ 740/2639] eta: 1:31:44 lr: 4.172905619189414e-05 loss: 0.0859 (0.1013) time: 2.8223 data: 0.0084 max mem: 33369 +Epoch: [7] [ 750/2639] eta: 1:31:15 lr: 4.172470667158554e-05 loss: 0.0859 (0.1011) time: 2.8528 data: 0.0082 max mem: 33369 +Epoch: [7] [ 760/2639] eta: 1:30:45 lr: 4.1720357100897654e-05 loss: 0.0927 (0.1014) time: 2.8761 data: 0.0082 max mem: 33369 +Epoch: [7] [ 770/2639] eta: 1:30:15 lr: 4.171600747982407e-05 loss: 0.0881 (0.1012) time: 2.8728 data: 0.0082 max mem: 33369 +Epoch: [7] [ 780/2639] eta: 1:29:46 lr: 4.1711657808358356e-05 loss: 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4.167685862174531e-05 loss: 0.0860 (0.1017) time: 2.8662 data: 0.0081 max mem: 33369 +Epoch: [7] [ 870/2639] eta: 1:25:20 lr: 4.167250849646132e-05 loss: 0.0954 (0.1016) time: 2.8946 data: 0.0083 max mem: 33369 +Epoch: [7] [ 880/2639] eta: 1:24:52 lr: 4.1668158320720894e-05 loss: 0.0947 (0.1015) time: 2.9200 data: 0.0084 max mem: 33369 +Epoch: [7] [ 890/2639] eta: 1:24:22 lr: 4.166380809451762e-05 loss: 0.0909 (0.1015) time: 2.8907 data: 0.0085 max mem: 33369 +Epoch: [7] [ 900/2639] eta: 1:23:54 lr: 4.165945781784505e-05 loss: 0.1010 (0.1016) time: 2.8896 data: 0.0081 max mem: 33369 +Epoch: [7] [ 910/2639] eta: 1:23:27 lr: 4.165510749069674e-05 loss: 0.1015 (0.1018) time: 2.9474 data: 0.0076 max mem: 33369 +Epoch: [7] [ 920/2639] eta: 1:22:59 lr: 4.1650757113066254e-05 loss: 0.0881 (0.1017) time: 2.9815 data: 0.0077 max mem: 33369 +Epoch: [7] [ 930/2639] eta: 1:22:30 lr: 4.164640668494714e-05 loss: 0.0881 (0.1017) time: 2.9317 data: 0.0079 max mem: 33369 +Epoch: [7] [ 940/2639] eta: 1:22:01 lr: 4.1642056206332955e-05 loss: 0.1002 (0.1017) time: 2.9071 data: 0.0080 max mem: 33369 +Epoch: [7] [ 950/2639] eta: 1:21:33 lr: 4.163770567721725e-05 loss: 0.0973 (0.1018) time: 2.9144 data: 0.0083 max mem: 33369 +Epoch: [7] [ 960/2639] eta: 1:21:04 lr: 4.1633355097593575e-05 loss: 0.0933 (0.1017) time: 2.9008 data: 0.0081 max mem: 33369 +Epoch: [7] [ 970/2639] eta: 1:20:36 lr: 4.1629004467455476e-05 loss: 0.0795 (0.1016) time: 2.9322 data: 0.0078 max mem: 33369 +Epoch: [7] [ 980/2639] eta: 1:20:07 lr: 4.162465378679652e-05 loss: 0.1025 (0.1018) time: 2.9362 data: 0.0083 max mem: 33369 +Epoch: [7] [ 990/2639] eta: 1:19:38 lr: 4.162030305561022e-05 loss: 0.1183 (0.1021) time: 2.9027 data: 0.0082 max mem: 33369 +Epoch: [7] [1000/2639] eta: 1:19:09 lr: 4.1615952273890155e-05 loss: 0.1008 (0.1021) time: 2.9005 data: 0.0080 max mem: 33369 +Epoch: [7] [1010/2639] eta: 1:18:41 lr: 4.1611601441629835e-05 loss: 0.0900 (0.1021) time: 2.9106 data: 0.0079 max mem: 33369 +Epoch: [7] 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+Epoch: [7] [1100/2639] eta: 1:14:21 lr: 4.1572441675910067e-05 loss: 0.0915 (0.1022) time: 2.8960 data: 0.0084 max mem: 33369 +Epoch: [7] [1110/2639] eta: 1:13:53 lr: 4.156809033789188e-05 loss: 0.0992 (0.1023) time: 2.9071 data: 0.0081 max mem: 33369 +Epoch: [7] [1120/2639] eta: 1:13:23 lr: 4.1563738949262316e-05 loss: 0.0992 (0.1022) time: 2.9125 data: 0.0086 max mem: 33369 +Epoch: [7] [1130/2639] eta: 1:12:55 lr: 4.15593875100149e-05 loss: 0.0932 (0.1021) time: 2.9052 data: 0.0086 max mem: 33369 +Epoch: [7] [1140/2639] eta: 1:12:26 lr: 4.155503602014316e-05 loss: 0.0940 (0.1021) time: 2.9181 data: 0.0083 max mem: 33369 +Epoch: [7] [1150/2639] eta: 1:11:58 lr: 4.155068447964062e-05 loss: 0.1005 (0.1021) time: 2.9325 data: 0.0083 max mem: 33369 +Epoch: [7] [1160/2639] eta: 1:11:29 lr: 4.154633288850079e-05 loss: 0.0979 (0.1021) time: 2.9339 data: 0.0081 max mem: 33369 +Epoch: [7] [1170/2639] eta: 1:11:01 lr: 4.154198124671719e-05 loss: 0.0946 (0.1020) time: 2.9509 data: 0.0079 max mem: 33369 +Epoch: [7] [1180/2639] eta: 1:10:32 lr: 4.153762955428333e-05 loss: 0.1031 (0.1020) time: 2.9601 data: 0.0080 max mem: 33369 +Epoch: [7] [1190/2639] eta: 1:10:03 lr: 4.153327781119274e-05 loss: 0.1184 (0.1024) time: 2.9181 data: 0.0081 max mem: 33369 +Epoch: [7] [1200/2639] eta: 1:09:34 lr: 4.152892601743893e-05 loss: 0.1199 (0.1025) time: 2.8939 data: 0.0081 max mem: 33369 +Epoch: [7] [1210/2639] eta: 1:09:05 lr: 4.15245741730154e-05 loss: 0.1141 (0.1025) time: 2.8824 data: 0.0079 max mem: 33369 +Epoch: [7] [1220/2639] eta: 1:08:35 lr: 4.152022227791565e-05 loss: 0.1161 (0.1027) time: 2.8622 data: 0.0077 max mem: 33369 +Epoch: [7] [1230/2639] eta: 1:08:06 lr: 4.1515870332133224e-05 loss: 0.0991 (0.1026) time: 2.8771 data: 0.0080 max mem: 33369 +Epoch: [7] [1240/2639] eta: 1:07:37 lr: 4.1511518335661606e-05 loss: 0.0991 (0.1026) time: 2.8897 data: 0.0079 max mem: 33369 +Epoch: [7] [1250/2639] eta: 1:07:08 lr: 4.1507166288494294e-05 loss: 0.1084 (0.1027) time: 2.8931 data: 0.0077 max mem: 33369 +Epoch: [7] [1260/2639] eta: 1:06:39 lr: 4.15028141906248e-05 loss: 0.0994 (0.1026) time: 2.8974 data: 0.0076 max mem: 33369 +Epoch: [7] [1270/2639] eta: 1:06:10 lr: 4.149846204204663e-05 loss: 0.1011 (0.1028) time: 2.8979 data: 0.0077 max mem: 33369 +Epoch: [7] [1280/2639] eta: 1:05:41 lr: 4.1494109842753274e-05 loss: 0.1109 (0.1028) time: 2.8997 data: 0.0076 max mem: 33369 +Epoch: [7] [1290/2639] eta: 1:05:13 lr: 4.148975759273824e-05 loss: 0.0864 (0.1030) time: 2.9334 data: 0.0078 max mem: 33369 +Epoch: [7] [1300/2639] eta: 1:04:43 lr: 4.148540529199502e-05 loss: 0.1010 (0.1031) time: 2.9258 data: 0.0081 max mem: 33369 +Epoch: [7] [1310/2639] eta: 1:04:15 lr: 4.1481052940517114e-05 loss: 0.0966 (0.1031) time: 2.9076 data: 0.0084 max mem: 33369 +Epoch: [7] [1320/2639] eta: 1:03:46 lr: 4.1476700538298005e-05 loss: 0.1024 (0.1033) time: 2.9196 data: 0.0082 max mem: 33369 +Epoch: [7] [1330/2639] eta: 1:03:16 lr: 4.1472348085331194e-05 loss: 0.1047 (0.1033) time: 2.8798 data: 0.0076 max mem: 33369 +Epoch: [7] [1340/2639] eta: 1:02:47 lr: 4.146799558161017e-05 loss: 0.0908 (0.1032) time: 2.8488 data: 0.0076 max mem: 33369 +Epoch: [7] [1350/2639] eta: 1:02:18 lr: 4.146364302712842e-05 loss: 0.0921 (0.1032) time: 2.8577 data: 0.0079 max mem: 33369 +Epoch: [7] [1360/2639] eta: 1:01:48 lr: 4.1459290421879434e-05 loss: 0.0983 (0.1032) time: 2.8705 data: 0.0082 max mem: 33369 +Epoch: [7] [1370/2639] eta: 1:01:19 lr: 4.1454937765856694e-05 loss: 0.0891 (0.1033) time: 2.8657 data: 0.0080 max mem: 33369 +Epoch: [7] [1380/2639] eta: 1:00:49 lr: 4.1450585059053685e-05 loss: 0.0913 (0.1032) time: 2.8412 data: 0.0077 max mem: 33369 +Epoch: [7] [1390/2639] eta: 1:00:20 lr: 4.144623230146389e-05 loss: 0.0939 (0.1034) time: 2.8381 data: 0.0073 max mem: 33369 +Epoch: [7] [1400/2639] eta: 0:59:51 lr: 4.14418794930808e-05 loss: 0.1202 (0.1034) time: 2.8975 data: 0.0075 max mem: 33369 +Epoch: [7] [1410/2639] eta: 0:59:23 lr: 4.143752663389788e-05 loss: 0.0917 (0.1034) time: 2.9473 data: 0.0078 max mem: 33369 +Epoch: [7] [1420/2639] eta: 0:58:54 lr: 4.1433173723908605e-05 loss: 0.0919 (0.1034) time: 2.9291 data: 0.0076 max mem: 33369 +Epoch: [7] [1430/2639] eta: 0:58:25 lr: 4.142882076310647e-05 loss: 0.0919 (0.1034) time: 2.9196 data: 0.0074 max mem: 33369 +Epoch: [7] [1440/2639] eta: 0:57:56 lr: 4.142446775148493e-05 loss: 0.0778 (0.1035) time: 2.9171 data: 0.0078 max mem: 33369 +Epoch: [7] [1450/2639] eta: 0:57:27 lr: 4.142011468903748e-05 loss: 0.0790 (0.1036) time: 2.8844 data: 0.0081 max mem: 33369 +Epoch: [7] [1460/2639] eta: 0:56:58 lr: 4.1415761575757565e-05 loss: 0.0875 (0.1036) time: 2.8788 data: 0.0077 max mem: 33369 +Epoch: [7] [1470/2639] eta: 0:56:28 lr: 4.141140841163867e-05 loss: 0.0997 (0.1035) time: 2.8743 data: 0.0076 max mem: 33369 +Epoch: [7] [1480/2639] eta: 0:56:00 lr: 4.140705519667426e-05 loss: 0.0997 (0.1036) time: 2.8961 data: 0.0080 max mem: 33369 +Epoch: [7] [1490/2639] eta: 0:55:31 lr: 4.1402701930857806e-05 loss: 0.0938 (0.1035) time: 2.9485 data: 0.0081 max mem: 33369 +Epoch: [7] [1500/2639] eta: 0:55:02 lr: 4.139834861418277e-05 loss: 0.1080 (0.1038) time: 2.9419 data: 0.0081 max mem: 33369 +Epoch: [7] [1510/2639] eta: 0:54:33 lr: 4.139399524664261e-05 loss: 0.1185 (0.1040) time: 2.9185 data: 0.0082 max mem: 33369 +Epoch: [7] [1520/2639] eta: 0:54:04 lr: 4.1389641828230794e-05 loss: 0.1089 (0.1041) time: 2.8848 data: 0.0080 max mem: 33369 +Epoch: [7] [1530/2639] eta: 0:53:34 lr: 4.138528835894078e-05 loss: 0.1060 (0.1039) time: 2.8211 data: 0.0081 max mem: 33369 +Epoch: [7] [1540/2639] eta: 0:53:05 lr: 4.1380934838766036e-05 loss: 0.0843 (0.1039) time: 2.8372 data: 0.0079 max mem: 33369 +Epoch: [7] [1550/2639] eta: 0:52:36 lr: 4.1376581267699993e-05 loss: 0.0843 (0.1038) time: 2.8609 data: 0.0076 max mem: 33369 +Epoch: [7] [1560/2639] eta: 0:52:07 lr: 4.1372227645736134e-05 loss: 0.0910 (0.1039) time: 2.8664 data: 0.0074 max mem: 33369 +Epoch: [7] [1570/2639] eta: 0:51:38 lr: 4.13678739728679e-05 loss: 0.1153 (0.1041) time: 2.8817 data: 0.0076 max mem: 33369 +Epoch: [7] [1580/2639] eta: 0:51:08 lr: 4.136352024908875e-05 loss: 0.1066 (0.1041) time: 2.8524 data: 0.0075 max mem: 33369 +Epoch: [7] [1590/2639] eta: 0:50:39 lr: 4.1359166474392114e-05 loss: 0.0971 (0.1041) time: 2.8750 data: 0.0078 max mem: 33369 +Epoch: [7] [1600/2639] eta: 0:50:10 lr: 4.135481264877146e-05 loss: 0.1001 (0.1041) time: 2.8993 data: 0.0083 max mem: 33369 +Epoch: [7] [1610/2639] eta: 0:49:41 lr: 4.135045877222024e-05 loss: 0.0932 (0.1042) time: 2.8847 data: 0.0085 max mem: 33369 +Epoch: [7] [1620/2639] eta: 0:49:12 lr: 4.1346104844731896e-05 loss: 0.0883 (0.1042) time: 2.8926 data: 0.0084 max mem: 33369 +Epoch: [7] [1630/2639] eta: 0:48:44 lr: 4.134175086629986e-05 loss: 0.0883 (0.1042) time: 2.9151 data: 0.0079 max mem: 33369 +Epoch: [7] [1640/2639] eta: 0:48:15 lr: 4.1337396836917575e-05 loss: 0.0909 (0.1042) time: 2.9291 data: 0.0078 max mem: 33369 +Epoch: [7] [1650/2639] eta: 0:47:46 lr: 4.1333042756578496e-05 loss: 0.0908 (0.1042) time: 2.9065 data: 0.0076 max mem: 33369 +Epoch: [7] [1660/2639] eta: 0:47:17 lr: 4.132868862527605e-05 loss: 0.0908 (0.1042) time: 2.9055 data: 0.0080 max mem: 33369 +Epoch: [7] [1670/2639] eta: 0:46:48 lr: 4.132433444300368e-05 loss: 0.0948 (0.1043) time: 2.8813 data: 0.0084 max mem: 33369 +Epoch: [7] [1680/2639] eta: 0:46:18 lr: 4.1319980209754824e-05 loss: 0.0941 (0.1043) time: 2.8631 data: 0.0079 max mem: 33369 +Epoch: [7] [1690/2639] eta: 0:45:49 lr: 4.131562592552291e-05 loss: 0.1060 (0.1043) time: 2.8615 data: 0.0080 max mem: 33369 +Epoch: [7] [1700/2639] eta: 0:45:20 lr: 4.131127159030138e-05 loss: 0.1052 (0.1044) time: 2.8390 data: 0.0081 max mem: 33369 +Epoch: [7] [1710/2639] eta: 0:44:51 lr: 4.130691720408365e-05 loss: 0.0953 (0.1044) time: 2.9228 data: 0.0080 max mem: 33369 +Epoch: [7] [1720/2639] eta: 0:44:23 lr: 4.1302562766863165e-05 loss: 0.0949 (0.1044) time: 2.9649 data: 0.0078 max mem: 33369 +Epoch: [7] [1730/2639] eta: 0:43:54 lr: 4.129820827863336e-05 loss: 0.0949 (0.1046) time: 2.9507 data: 0.0076 max mem: 33369 +Epoch: [7] [1740/2639] eta: 0:43:25 lr: 4.129385373938763e-05 loss: 0.0995 (0.1046) time: 2.9682 data: 0.0078 max mem: 33369 +Epoch: [7] [1750/2639] eta: 0:42:57 lr: 4.128949914911942e-05 loss: 0.1250 (0.1047) time: 2.9399 data: 0.0075 max mem: 33369 +Epoch: [7] [1760/2639] eta: 0:42:28 lr: 4.128514450782215e-05 loss: 0.1199 (0.1047) time: 2.9100 data: 0.0076 max mem: 33369 +Epoch: [7] [1770/2639] eta: 0:41:59 lr: 4.1280789815489253e-05 loss: 0.1100 (0.1047) time: 2.9185 data: 0.0081 max mem: 33369 +Epoch: [7] [1780/2639] eta: 0:41:30 lr: 4.127643507211413e-05 loss: 0.0975 (0.1047) time: 2.9495 data: 0.0081 max mem: 33369 +Epoch: [7] [1790/2639] eta: 0:41:01 lr: 4.1272080277690203e-05 loss: 0.0911 (0.1046) time: 2.9164 data: 0.0079 max mem: 33369 +Epoch: [7] [1800/2639] eta: 0:40:32 lr: 4.12677254322109e-05 loss: 0.0913 (0.1046) time: 2.8896 data: 0.0076 max mem: 33369 +Epoch: [7] [1810/2639] eta: 0:40:03 lr: 4.126337053566963e-05 loss: 0.0956 (0.1046) time: 2.9017 data: 0.0074 max mem: 33369 +Epoch: [7] [1820/2639] eta: 0:39:34 lr: 4.12590155880598e-05 loss: 0.1012 (0.1047) time: 2.9305 data: 0.0076 max mem: 33369 +Epoch: [7] [1830/2639] eta: 0:39:06 lr: 4.1254660589374836e-05 loss: 0.1017 (0.1048) time: 2.9619 data: 0.0079 max mem: 33369 +Epoch: [7] [1840/2639] eta: 0:38:37 lr: 4.125030553960813e-05 loss: 0.1085 (0.1049) time: 2.9282 data: 0.0078 max mem: 33369 +Epoch: [7] [1850/2639] eta: 0:38:08 lr: 4.124595043875309e-05 loss: 0.0954 (0.1048) time: 2.9091 data: 0.0079 max mem: 33369 +Epoch: [7] [1860/2639] eta: 0:37:39 lr: 4.124159528680315e-05 loss: 0.0880 (0.1047) time: 2.9233 data: 0.0079 max mem: 33369 +Epoch: [7] [1870/2639] eta: 0:37:10 lr: 4.123724008375169e-05 loss: 0.0880 (0.1047) time: 2.9038 data: 0.0077 max mem: 33369 +Epoch: [7] [1880/2639] eta: 0:36:41 lr: 4.1232884829592125e-05 loss: 0.0907 (0.1046) time: 2.9203 data: 0.0077 max mem: 33369 +Epoch: [7] [1890/2639] eta: 0:36:12 lr: 4.1228529524317846e-05 loss: 0.0885 (0.1045) time: 2.9660 data: 0.0074 max mem: 33369 +Epoch: [7] [1900/2639] eta: 0:35:43 lr: 4.122417416792226e-05 loss: 0.0973 (0.1045) time: 2.9296 data: 0.0074 max mem: 33369 +Epoch: [7] [1910/2639] eta: 0:35:14 lr: 4.1219818760398774e-05 loss: 0.1031 (0.1047) time: 2.8849 data: 0.0077 max mem: 33369 +Epoch: [7] [1920/2639] eta: 0:34:45 lr: 4.1215463301740774e-05 loss: 0.0997 (0.1048) time: 2.8960 data: 0.0077 max mem: 33369 +Epoch: [7] [1930/2639] eta: 0:34:16 lr: 4.1211107791941655e-05 loss: 0.0947 (0.1049) time: 2.9183 data: 0.0074 max mem: 33369 +Epoch: [7] [1940/2639] eta: 0:33:47 lr: 4.1206752230994825e-05 loss: 0.1069 (0.1049) time: 2.9135 data: 0.0076 max mem: 33369 +Epoch: [7] [1950/2639] eta: 0:33:18 lr: 4.1202396618893655e-05 loss: 0.1172 (0.1050) time: 2.8900 data: 0.0081 max mem: 33369 +Epoch: [7] [1960/2639] eta: 0:32:49 lr: 4.119804095563155e-05 loss: 0.1028 (0.1050) time: 2.9023 data: 0.0078 max mem: 33369 +Epoch: [7] [1970/2639] eta: 0:32:20 lr: 4.119368524120189e-05 loss: 0.0986 (0.1050) time: 2.9296 data: 0.0079 max mem: 33369 +Epoch: [7] [1980/2639] eta: 0:31:51 lr: 4.118932947559807e-05 loss: 0.0991 (0.1050) time: 2.8963 data: 0.0083 max mem: 33369 +Epoch: [7] [1990/2639] eta: 0:31:22 lr: 4.118497365881348e-05 loss: 0.1085 (0.1051) time: 2.8812 data: 0.0077 max mem: 33369 +Epoch: [7] [2000/2639] eta: 0:30:53 lr: 4.118061779084148e-05 loss: 0.0989 (0.1050) time: 2.8927 data: 0.0074 max mem: 33369 +Epoch: [7] [2010/2639] eta: 0:30:24 lr: 4.117626187167549e-05 loss: 0.0852 (0.1050) time: 2.8854 data: 0.0082 max mem: 33369 +Epoch: [7] [2020/2639] eta: 0:29:55 lr: 4.117190590130886e-05 loss: 0.0885 (0.1050) time: 2.9123 data: 0.0084 max mem: 33369 +Epoch: [7] [2030/2639] eta: 0:29:26 lr: 4.116754987973498e-05 loss: 0.0865 (0.1049) time: 2.9296 data: 0.0084 max mem: 33369 +Epoch: [7] [2040/2639] eta: 0:28:57 lr: 4.116319380694723e-05 loss: 0.0983 (0.1049) time: 2.9092 data: 0.0082 max mem: 33369 +Epoch: [7] [2050/2639] eta: 0:28:28 lr: 4.115883768293897e-05 loss: 0.0963 (0.1049) time: 2.9005 data: 0.0082 max mem: 33369 +Epoch: [7] [2060/2639] eta: 0:27:59 lr: 4.11544815077036e-05 loss: 0.0963 (0.1050) time: 2.8990 data: 0.0084 max mem: 33369 +Epoch: [7] [2070/2639] eta: 0:27:30 lr: 4.1150125281234474e-05 loss: 0.1050 (0.1050) time: 2.8716 data: 0.0079 max mem: 33369 +Epoch: [7] [2080/2639] eta: 0:27:01 lr: 4.1145769003524975e-05 loss: 0.0878 (0.1049) time: 2.8870 data: 0.0080 max mem: 33369 +Epoch: [7] [2090/2639] eta: 0:26:32 lr: 4.1141412674568466e-05 loss: 0.0922 (0.1049) time: 2.8999 data: 0.0080 max mem: 33369 +Epoch: [7] [2100/2639] eta: 0:26:03 lr: 4.1137056294358304e-05 loss: 0.0952 (0.1049) time: 2.8665 data: 0.0078 max mem: 33369 +Epoch: [7] [2110/2639] eta: 0:25:34 lr: 4.113269986288788e-05 loss: 0.0877 (0.1049) time: 2.8774 data: 0.0078 max mem: 33369 +Epoch: [7] [2120/2639] eta: 0:25:05 lr: 4.1128343380150536e-05 loss: 0.0959 (0.1050) time: 2.8826 data: 0.0079 max mem: 33369 +Epoch: [7] [2130/2639] eta: 0:24:36 lr: 4.112398684613964e-05 loss: 0.0959 (0.1050) time: 2.8731 data: 0.0079 max mem: 33369 +Epoch: [7] [2140/2639] eta: 0:24:07 lr: 4.1119630260848554e-05 loss: 0.0904 (0.1049) time: 2.8827 data: 0.0074 max mem: 33369 +Epoch: [7] [2150/2639] eta: 0:23:38 lr: 4.111527362427064e-05 loss: 0.0894 (0.1049) time: 2.8958 data: 0.0074 max mem: 33369 +Epoch: [7] [2160/2639] eta: 0:23:09 lr: 4.111091693639927e-05 loss: 0.0862 (0.1049) time: 2.8813 data: 0.0075 max mem: 33369 +Epoch: [7] [2170/2639] eta: 0:22:39 lr: 4.1106560197227774e-05 loss: 0.0924 (0.1049) time: 2.8339 data: 0.0076 max mem: 33369 +Epoch: [7] [2180/2639] eta: 0:22:10 lr: 4.110220340674951e-05 loss: 0.1025 (0.1049) time: 2.8727 data: 0.0077 max mem: 33369 +Epoch: [7] [2190/2639] eta: 0:21:41 lr: 4.1097846564957854e-05 loss: 0.0884 (0.1049) time: 2.9265 data: 0.0075 max mem: 33369 +Epoch: [7] [2200/2639] eta: 0:21:12 lr: 4.1093489671846136e-05 loss: 0.0884 (0.1048) time: 2.9053 data: 0.0075 max mem: 33369 +Epoch: [7] [2210/2639] eta: 0:20:43 lr: 4.108913272740771e-05 loss: 0.0952 (0.1048) time: 2.8881 data: 0.0076 max mem: 33369 +Epoch: [7] [2220/2639] eta: 0:20:14 lr: 4.1084775731635925e-05 loss: 0.0968 (0.1048) time: 2.8807 data: 0.0076 max mem: 33369 +Epoch: [7] [2230/2639] eta: 0:19:45 lr: 4.1080418684524137e-05 loss: 0.0986 (0.1049) time: 2.8704 data: 0.0077 max mem: 33369 +Epoch: [7] [2240/2639] eta: 0:19:16 lr: 4.1076061586065665e-05 loss: 0.1015 (0.1049) time: 2.8676 data: 0.0078 max mem: 33369 +Epoch: [7] [2250/2639] eta: 0:18:47 lr: 4.1071704436253883e-05 loss: 0.1179 (0.1051) time: 2.8709 data: 0.0079 max mem: 33369 +Epoch: [7] [2260/2639] eta: 0:18:18 lr: 4.106734723508212e-05 loss: 0.1084 (0.1051) time: 2.8913 data: 0.0076 max mem: 33369 +Epoch: [7] [2270/2639] eta: 0:17:49 lr: 4.1062989982543704e-05 loss: 0.0916 (0.1051) time: 2.9017 data: 0.0078 max mem: 33369 +Epoch: [7] [2280/2639] eta: 0:17:20 lr: 4.1058632678631984e-05 loss: 0.1036 (0.1052) time: 2.8816 data: 0.0082 max mem: 33369 +Epoch: [7] [2290/2639] eta: 0:16:51 lr: 4.10542753233403e-05 loss: 0.1036 (0.1052) time: 2.8862 data: 0.0082 max mem: 33369 +Epoch: [7] [2300/2639] eta: 0:16:22 lr: 4.104991791666198e-05 loss: 0.0908 (0.1051) time: 2.9006 data: 0.0085 max mem: 33369 +Epoch: [7] [2310/2639] eta: 0:15:53 lr: 4.104556045859036e-05 loss: 0.0838 (0.1051) time: 2.8987 data: 0.0083 max mem: 33369 +Epoch: [7] [2320/2639] eta: 0:15:24 lr: 4.1041202949118776e-05 loss: 0.0825 (0.1050) time: 2.9113 data: 0.0078 max mem: 33369 +Epoch: [7] [2330/2639] eta: 0:14:55 lr: 4.103684538824055e-05 loss: 0.0897 (0.1049) time: 2.8824 data: 0.0083 max mem: 33369 +Epoch: [7] [2340/2639] eta: 0:14:26 lr: 4.1032487775949e-05 loss: 0.0922 (0.1049) time: 2.8616 data: 0.0083 max mem: 33369 +Epoch: [7] [2350/2639] eta: 0:13:57 lr: 4.102813011223748e-05 loss: 0.0953 (0.1050) time: 2.9158 data: 0.0081 max mem: 33369 +Epoch: [7] [2360/2639] eta: 0:13:28 lr: 4.10237723970993e-05 loss: 0.1047 (0.1051) time: 2.9474 data: 0.0077 max mem: 33369 +Epoch: [7] [2370/2639] eta: 0:12:59 lr: 4.101941463052778e-05 loss: 0.1047 (0.1052) time: 2.9445 data: 0.0075 max mem: 33369 +Epoch: [7] [2380/2639] eta: 0:12:30 lr: 4.101505681251624e-05 loss: 0.1123 (0.1053) time: 2.8813 data: 0.0074 max mem: 33369 +Epoch: [7] [2390/2639] eta: 0:12:01 lr: 4.101069894305801e-05 loss: 0.1024 (0.1053) time: 2.8549 data: 0.0072 max mem: 33369 +Epoch: [7] [2400/2639] eta: 0:11:32 lr: 4.100634102214641e-05 loss: 0.0956 (0.1053) time: 2.8839 data: 0.0071 max mem: 33369 +Epoch: [7] [2410/2639] eta: 0:11:03 lr: 4.100198304977474e-05 loss: 0.0873 (0.1052) time: 2.8831 data: 0.0071 max mem: 33369 +Epoch: [7] [2420/2639] eta: 0:10:34 lr: 4.099762502593633e-05 loss: 0.0896 (0.1052) time: 2.8879 data: 0.0073 max mem: 33369 +Epoch: [7] [2430/2639] eta: 0:10:05 lr: 4.099326695062448e-05 loss: 0.0962 (0.1054) time: 2.8976 data: 0.0075 max mem: 33369 +Epoch: [7] [2440/2639] eta: 0:09:36 lr: 4.098890882383252e-05 loss: 0.0942 (0.1054) time: 2.8935 data: 0.0076 max mem: 33369 +Epoch: [7] [2450/2639] eta: 0:09:07 lr: 4.0984550645553744e-05 loss: 0.0936 (0.1053) time: 2.8790 data: 0.0074 max mem: 33369 +Epoch: [7] [2460/2639] eta: 0:08:38 lr: 4.0980192415781466e-05 loss: 0.0825 (0.1053) time: 2.8710 data: 0.0076 max mem: 33369 +Epoch: [7] [2470/2639] eta: 0:08:09 lr: 4.097583413450899e-05 loss: 0.0975 (0.1054) time: 2.8889 data: 0.0075 max mem: 33369 +Epoch: [7] [2480/2639] eta: 0:07:40 lr: 4.097147580172963e-05 loss: 0.0966 (0.1054) time: 2.9051 data: 0.0074 max mem: 33369 +Epoch: [7] [2490/2639] eta: 0:07:11 lr: 4.096711741743668e-05 loss: 0.0847 (0.1053) time: 2.8956 data: 0.0077 max mem: 33369 +Epoch: [7] [2500/2639] eta: 0:06:42 lr: 4.096275898162345e-05 loss: 0.0894 (0.1053) time: 2.9228 data: 0.0079 max mem: 33369 +Epoch: [7] [2510/2639] eta: 0:06:13 lr: 4.095840049428323e-05 loss: 0.1002 (0.1053) time: 2.9204 data: 0.0078 max mem: 33369 +Epoch: [7] [2520/2639] eta: 0:05:44 lr: 4.095404195540932e-05 loss: 0.0953 (0.1052) time: 2.9053 data: 0.0075 max mem: 33369 +Epoch: [7] [2530/2639] eta: 0:05:15 lr: 4.094968336499502e-05 loss: 0.0889 (0.1052) time: 2.9256 data: 0.0076 max mem: 33369 +Epoch: [7] [2540/2639] eta: 0:04:46 lr: 4.094532472303363e-05 loss: 0.0962 (0.1053) time: 2.8925 data: 0.0079 max mem: 33369 +Epoch: [7] [2550/2639] eta: 0:04:17 lr: 4.0940966029518434e-05 loss: 0.1020 (0.1053) time: 2.8344 data: 0.0085 max mem: 33369 +Epoch: [7] [2560/2639] eta: 0:03:48 lr: 4.0936607284442726e-05 loss: 0.1022 (0.1054) time: 2.8648 data: 0.0081 max mem: 33369 +Epoch: [7] [2570/2639] eta: 0:03:20 lr: 4.09322484877998e-05 loss: 0.1235 (0.1054) time: 2.9260 data: 0.0076 max mem: 33369 +Epoch: [7] [2580/2639] eta: 0:02:51 lr: 4.0927889639582945e-05 loss: 0.1060 (0.1054) time: 2.8910 data: 0.0082 max mem: 33369 +Epoch: [7] [2590/2639] eta: 0:02:22 lr: 4.0923530739785434e-05 loss: 0.1037 (0.1054) time: 2.8533 data: 0.0080 max mem: 33369 +Epoch: [7] [2600/2639] eta: 0:01:53 lr: 4.0919171788400575e-05 loss: 0.1037 (0.1055) time: 2.8413 data: 0.0077 max mem: 33369 +Epoch: [7] [2610/2639] eta: 0:01:24 lr: 4.091481278542164e-05 loss: 0.1052 (0.1055) time: 2.8267 data: 0.0082 max mem: 33369 +Epoch: [7] [2620/2639] eta: 0:00:55 lr: 4.09104537308419e-05 loss: 0.1046 (0.1055) time: 2.8669 data: 0.0085 max mem: 33369 +Epoch: [7] [2630/2639] eta: 0:00:26 lr: 4.0906094624654654e-05 loss: 0.1076 (0.1056) time: 2.8674 data: 0.0079 max mem: 33369 +Epoch: [7] Total time: 2:07:27 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 2:12:49 time: 3.0973 data: 3.0037 max mem: 33369 +Test: [ 100/2573] eta: 0:04:28 time: 0.0783 data: 0.0014 max mem: 33369 +Test: [ 200/2573] eta: 0:03:44 time: 0.0791 data: 0.0015 max mem: 33369 +Test: [ 300/2573] eta: 0:03:22 time: 0.0811 data: 0.0014 max mem: 33369 +Test: [ 400/2573] eta: 0:03:08 time: 0.0809 data: 0.0015 max mem: 33369 +Test: [ 500/2573] eta: 0:02:56 time: 0.0800 data: 0.0016 max mem: 33369 +Test: [ 600/2573] eta: 0:02:46 time: 0.0799 data: 0.0014 max mem: 33369 +Test: [ 700/2573] eta: 0:02:37 time: 0.0792 data: 0.0014 max mem: 33369 +Test: [ 800/2573] eta: 0:02:28 time: 0.0829 data: 0.0014 max mem: 33369 +Test: [ 900/2573] eta: 0:02:19 time: 0.0801 data: 0.0015 max mem: 33369 +Test: [1000/2573] eta: 0:02:10 time: 0.0801 data: 0.0015 max mem: 33369 +Test: [1100/2573] eta: 0:02:02 time: 0.0793 data: 0.0014 max mem: 33369 +Test: [1200/2573] eta: 0:01:53 time: 0.0798 data: 0.0015 max mem: 33369 +Test: [1300/2573] eta: 0:01:45 time: 0.0799 data: 0.0014 max mem: 33369 +Test: [1400/2573] eta: 0:01:36 time: 0.0793 data: 0.0014 max mem: 33369 +Test: [1500/2573] eta: 0:01:28 time: 0.0823 data: 0.0015 max mem: 33369 +Test: [1600/2573] eta: 0:01:19 time: 0.0844 data: 0.0015 max mem: 33369 +Test: [1700/2573] eta: 0:01:11 time: 0.0792 data: 0.0014 max mem: 33369 +Test: [1800/2573] eta: 0:01:03 time: 0.0814 data: 0.0015 max mem: 33369 +Test: [1900/2573] eta: 0:00:55 time: 0.0800 data: 0.0015 max mem: 33369 +Test: [2000/2573] eta: 0:00:46 time: 0.0812 data: 0.0014 max mem: 33369 +Test: [2100/2573] eta: 0:00:38 time: 0.0826 data: 0.0014 max mem: 33369 +Test: [2200/2573] eta: 0:00:30 time: 0.0827 data: 0.0014 max mem: 33369 +Test: [2300/2573] eta: 0:00:22 time: 0.0827 data: 0.0015 max mem: 33369 +Test: [2400/2573] eta: 0:00:14 time: 0.0781 data: 0.0015 max mem: 33369 +Test: [2500/2573] eta: 0:00:05 time: 0.0807 data: 0.0014 max mem: 33369 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: Total time: 0:03:31 +Final results: +Mean IoU is 57.60 + + precision@0.5 = 64.50 + precision@0.6 = 57.41 + precision@0.7 = 49.31 + precision@0.8 = 37.23 + precision@0.9 = 16.12 + overall IoU = 57.47 + +Average object IoU 57.59784286532066 +Overall IoU 57.46712112426758 +Better epoch: 7 + +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [8] [ 0/2639] eta: 3:46:47 lr: 4.090217138495614e-05 loss: 0.1087 (0.1087) time: 5.1564 data: 2.1476 max mem: 33369 +Epoch: [8] [ 10/2639] eta: 2:14:07 lr: 4.0897812180696095e-05 loss: 0.0836 (0.0784) time: 3.0612 data: 0.2026 max mem: 33369 +Epoch: [8] [ 20/2639] eta: 2:09:51 lr: 4.089345292480903e-05 loss: 0.0843 (0.0890) time: 2.8660 data: 0.0077 max mem: 33369 +Epoch: [8] [ 30/2639] eta: 2:09:23 lr: 4.088909361728822e-05 loss: 0.0823 (0.0847) time: 2.9284 data: 0.0080 max mem: 33369 +Epoch: [8] [ 40/2639] eta: 2:08:20 lr: 4.088473425812695e-05 loss: 0.0973 (0.0921) time: 2.9498 data: 0.0080 max mem: 33369 +Epoch: [8] [ 50/2639] eta: 2:07:08 lr: 4.088037484731849e-05 loss: 0.1018 (0.0939) time: 2.9015 data: 0.0076 max mem: 33369 +Epoch: [8] [ 60/2639] eta: 2:06:48 lr: 4.0876015384856095e-05 loss: 0.0896 (0.0955) time: 2.9242 data: 0.0076 max mem: 33369 +Epoch: [8] [ 70/2639] eta: 2:05:55 lr: 4.0871655870733025e-05 loss: 0.0833 (0.0942) time: 2.9264 data: 0.0078 max mem: 33369 +Epoch: [8] [ 80/2639] eta: 2:05:15 lr: 4.086729630494258e-05 loss: 0.0809 (0.0945) time: 2.8973 data: 0.0084 max mem: 33369 +Epoch: [8] [ 90/2639] eta: 2:04:28 lr: 4.0862936687477984e-05 loss: 0.0948 (0.0962) time: 2.8915 data: 0.0079 max mem: 33369 +Epoch: [8] [ 100/2639] eta: 2:03:39 lr: 4.085857701833252e-05 loss: 0.0948 (0.0956) time: 2.8628 data: 0.0074 max mem: 33369 +Epoch: [8] [ 110/2639] eta: 2:03:00 lr: 4.0854217297499444e-05 loss: 0.0819 (0.0950) time: 2.8654 data: 0.0076 max mem: 33369 +Epoch: [8] [ 120/2639] eta: 2:02:33 lr: 4.0849857524972026e-05 loss: 0.0955 (0.0966) time: 2.9031 data: 0.0077 max mem: 33369 +Epoch: [8] [ 130/2639] eta: 2:02:13 lr: 4.08454977007435e-05 loss: 0.0964 (0.0963) time: 2.9472 data: 0.0076 max mem: 33369 +Epoch: [8] [ 140/2639] eta: 2:01:38 lr: 4.0841137824807134e-05 loss: 0.0828 (0.0952) time: 2.9278 data: 0.0075 max mem: 33369 +Epoch: [8] [ 150/2639] eta: 2:01:08 lr: 4.083677789715618e-05 loss: 0.0771 (0.0944) time: 2.9032 data: 0.0076 max mem: 33369 +Epoch: [8] [ 160/2639] eta: 2:00:32 lr: 4.083241791778389e-05 loss: 0.0677 (0.0949) time: 2.8982 data: 0.0077 max mem: 33369 +Epoch: [8] [ 170/2639] eta: 2:00:02 lr: 4.0828057886683514e-05 loss: 0.0889 (0.0952) time: 2.8937 data: 0.0075 max mem: 33369 +Epoch: [8] [ 180/2639] eta: 1:59:31 lr: 4.08236978038483e-05 loss: 0.0917 (0.0950) time: 2.9066 data: 0.0074 max mem: 33369 +Epoch: [8] [ 190/2639] eta: 1:59:01 lr: 4.081933766927149e-05 loss: 0.0825 (0.0949) time: 2.9059 data: 0.0075 max mem: 33369 +Epoch: [8] [ 200/2639] eta: 1:58:22 lr: 4.0814977482946337e-05 loss: 0.0768 (0.0937) time: 2.8728 data: 0.0075 max mem: 33369 +Epoch: [8] [ 210/2639] eta: 1:57:54 lr: 4.081061724486607e-05 loss: 0.0671 (0.0929) time: 2.8804 data: 0.0075 max mem: 33369 +Epoch: [8] [ 220/2639] eta: 1:57:20 lr: 4.080625695502396e-05 loss: 0.0703 (0.0926) time: 2.8951 data: 0.0075 max mem: 33369 +Epoch: [8] [ 230/2639] eta: 1:56:41 lr: 4.080189661341321e-05 loss: 0.0759 (0.0917) time: 2.8422 data: 0.0077 max mem: 33369 +Epoch: [8] [ 240/2639] eta: 1:56:05 lr: 4.079753622002708e-05 loss: 0.0752 (0.0922) time: 2.8259 data: 0.0080 max mem: 33369 +Epoch: [8] [ 250/2639] eta: 1:55:31 lr: 4.079317577485881e-05 loss: 0.0927 (0.0927) time: 2.8449 data: 0.0081 max mem: 33369 +Epoch: [8] [ 260/2639] eta: 1:54:56 lr: 4.078881527790163e-05 loss: 0.0928 (0.0936) time: 2.8414 data: 0.0081 max mem: 33369 +Epoch: [8] [ 270/2639] eta: 1:54:24 lr: 4.0784454729148766e-05 loss: 0.0927 (0.0933) time: 2.8486 data: 0.0078 max mem: 33369 +Epoch: [8] [ 280/2639] eta: 1:53:54 lr: 4.078009412859344e-05 loss: 0.0742 (0.0931) time: 2.8748 data: 0.0075 max mem: 33369 +Epoch: [8] [ 290/2639] eta: 1:53:28 lr: 4.077573347622892e-05 loss: 0.0759 (0.0933) time: 2.9086 data: 0.0077 max mem: 33369 +Epoch: [8] [ 300/2639] eta: 1:52:56 lr: 4.077137277204839e-05 loss: 0.0842 (0.0933) time: 2.9020 data: 0.0077 max mem: 33369 +Epoch: [8] [ 310/2639] eta: 1:52:28 lr: 4.0767012016045105e-05 loss: 0.0774 (0.0931) time: 2.8836 data: 0.0077 max mem: 33369 +Epoch: [8] [ 320/2639] eta: 1:51:59 lr: 4.076265120821228e-05 loss: 0.0777 (0.0937) time: 2.8992 data: 0.0083 max mem: 33369 +Epoch: [8] [ 330/2639] eta: 1:51:31 lr: 4.0758290348543146e-05 loss: 0.0830 (0.0934) time: 2.9052 data: 0.0081 max mem: 33369 +Epoch: [8] [ 340/2639] eta: 1:51:03 lr: 4.07539294370309e-05 loss: 0.0751 (0.0931) time: 2.9133 data: 0.0077 max mem: 33369 +Epoch: [8] [ 350/2639] eta: 1:50:39 lr: 4.07495684736688e-05 loss: 0.0733 (0.0929) time: 2.9460 data: 0.0079 max mem: 33369 +Epoch: [8] [ 360/2639] eta: 1:50:17 lr: 4.074520745845003e-05 loss: 0.0883 (0.0930) time: 2.9951 data: 0.0078 max mem: 33369 +Epoch: [8] [ 370/2639] eta: 1:49:55 lr: 4.074084639136782e-05 loss: 0.0929 (0.0936) time: 3.0163 data: 0.0079 max mem: 33369 +Epoch: [8] [ 380/2639] eta: 1:49:24 lr: 4.073648527241538e-05 loss: 0.0827 (0.0932) time: 2.9486 data: 0.0084 max mem: 33369 +Epoch: [8] [ 390/2639] eta: 1:48:54 lr: 4.073212410158593e-05 loss: 0.0808 (0.0932) time: 2.8773 data: 0.0087 max mem: 33369 +Epoch: [8] [ 400/2639] eta: 1:48:24 lr: 4.072776287887268e-05 loss: 0.0925 (0.0938) time: 2.8856 data: 0.0087 max mem: 33369 +Epoch: [8] [ 410/2639] eta: 1:47:55 lr: 4.072340160426884e-05 loss: 0.0879 (0.0937) time: 2.8986 data: 0.0084 max mem: 33369 +Epoch: [8] [ 420/2639] eta: 1:47:29 lr: 4.0719040277767606e-05 loss: 0.0703 (0.0938) time: 2.9379 data: 0.0086 max mem: 33369 +Epoch: [8] [ 430/2639] eta: 1:47:02 lr: 4.07146788993622e-05 loss: 0.0781 (0.0935) time: 2.9574 data: 0.0090 max mem: 33369 +Epoch: [8] [ 440/2639] eta: 1:46:31 lr: 4.071031746904581e-05 loss: 0.0697 (0.0930) time: 2.8996 data: 0.0085 max mem: 33369 +Epoch: [8] [ 450/2639] eta: 1:46:02 lr: 4.070595598681166e-05 loss: 0.0843 (0.0936) time: 2.8838 data: 0.0080 max mem: 33369 +Epoch: [8] [ 460/2639] eta: 1:45:31 lr: 4.070159445265293e-05 loss: 0.0907 (0.0933) time: 2.8960 data: 0.0079 max mem: 33369 +Epoch: [8] [ 470/2639] eta: 1:44:59 lr: 4.069723286656283e-05 loss: 0.0732 (0.0936) time: 2.8549 data: 0.0081 max mem: 33369 +Epoch: [8] [ 480/2639] eta: 1:44:31 lr: 4.0692871228534556e-05 loss: 0.0874 (0.0937) time: 2.8785 data: 0.0082 max mem: 33369 +Epoch: [8] [ 490/2639] eta: 1:44:01 lr: 4.06885095385613e-05 loss: 0.0737 (0.0933) time: 2.9114 data: 0.0087 max mem: 33369 +Epoch: [8] [ 500/2639] eta: 1:43:31 lr: 4.068414779663627e-05 loss: 0.0671 (0.0928) time: 2.8817 data: 0.0085 max mem: 33369 +Epoch: [8] [ 510/2639] eta: 1:42:59 lr: 4.0679786002752645e-05 loss: 0.0671 (0.0924) time: 2.8591 data: 0.0078 max mem: 33369 +Epoch: [8] [ 520/2639] eta: 1:42:29 lr: 4.067542415690361e-05 loss: 0.0796 (0.0924) time: 2.8555 data: 0.0078 max mem: 33369 +Epoch: [8] [ 530/2639] eta: 1:41:58 lr: 4.067106225908237e-05 loss: 0.0862 (0.0925) time: 2.8571 data: 0.0081 max mem: 33369 +Epoch: [8] [ 540/2639] eta: 1:41:31 lr: 4.066670030928211e-05 loss: 0.0745 (0.0926) time: 2.8987 data: 0.0084 max mem: 33369 +Epoch: [8] [ 550/2639] eta: 1:41:03 lr: 4.0662338307496e-05 loss: 0.0771 (0.0924) time: 2.9421 data: 0.0087 max mem: 33369 +Epoch: [8] [ 560/2639] eta: 1:40:34 lr: 4.065797625371724e-05 loss: 0.0921 (0.0928) time: 2.9226 data: 0.0087 max mem: 33369 +Epoch: [8] [ 570/2639] eta: 1:40:07 lr: 4.0653614147939e-05 loss: 0.1010 (0.0928) time: 2.9360 data: 0.0083 max mem: 33369 +Epoch: [8] [ 580/2639] eta: 1:39:37 lr: 4.064925199015448e-05 loss: 0.0865 (0.0928) time: 2.9113 data: 0.0082 max mem: 33369 +Epoch: [8] [ 590/2639] eta: 1:39:07 lr: 4.0644889780356836e-05 loss: 0.0876 (0.0931) time: 2.8669 data: 0.0082 max mem: 33369 +Epoch: [8] [ 600/2639] eta: 1:38:37 lr: 4.0640527518539264e-05 loss: 0.1125 (0.0935) time: 2.8878 data: 0.0081 max mem: 33369 +Epoch: [8] [ 610/2639] eta: 1:38:10 lr: 4.0636165204694924e-05 loss: 0.0969 (0.0935) time: 2.9274 data: 0.0079 max mem: 33369 +Epoch: [8] [ 620/2639] eta: 1:37:40 lr: 4.0631802838817004e-05 loss: 0.0919 (0.0936) time: 2.9087 data: 0.0079 max mem: 33369 +Epoch: [8] [ 630/2639] eta: 1:37:10 lr: 4.062744042089866e-05 loss: 0.0877 (0.0936) time: 2.8769 data: 0.0082 max mem: 33369 +Epoch: [8] [ 640/2639] eta: 1:36:44 lr: 4.0623077950933076e-05 loss: 0.0852 (0.0934) time: 2.9368 data: 0.0081 max mem: 33369 +Epoch: [8] [ 650/2639] eta: 1:36:14 lr: 4.0618715428913414e-05 loss: 0.0711 (0.0930) time: 2.9333 data: 0.0081 max mem: 33369 +Epoch: [8] [ 660/2639] eta: 1:35:47 lr: 4.0614352854832844e-05 loss: 0.0718 (0.0933) time: 2.9154 data: 0.0078 max mem: 33369 +Epoch: [8] [ 670/2639] eta: 1:35:17 lr: 4.060999022868452e-05 loss: 0.1037 (0.0938) time: 2.9224 data: 0.0077 max mem: 33369 +Epoch: [8] [ 680/2639] eta: 1:34:51 lr: 4.060562755046163e-05 loss: 0.0843 (0.0936) time: 2.9433 data: 0.0079 max mem: 33369 +Epoch: [8] [ 690/2639] eta: 1:34:22 lr: 4.060126482015731e-05 loss: 0.0937 (0.0938) time: 2.9499 data: 0.0080 max mem: 33369 +Epoch: [8] [ 700/2639] eta: 1:33:52 lr: 4.059690203776474e-05 loss: 0.1022 (0.0939) time: 2.8892 data: 0.0079 max mem: 33369 +Epoch: [8] [ 710/2639] eta: 1:33:23 lr: 4.059253920327705e-05 loss: 0.0776 (0.0938) time: 2.8916 data: 0.0078 max mem: 33369 +Epoch: [8] [ 720/2639] eta: 1:32:54 lr: 4.058817631668743e-05 loss: 0.0796 (0.0943) time: 2.9072 data: 0.0078 max mem: 33369 +Epoch: [8] [ 730/2639] eta: 1:32:25 lr: 4.058381337798901e-05 loss: 0.0864 (0.0942) time: 2.9070 data: 0.0076 max mem: 33369 +Epoch: [8] [ 740/2639] eta: 1:31:56 lr: 4.057945038717496e-05 loss: 0.0849 (0.0941) time: 2.9077 data: 0.0077 max mem: 33369 +Epoch: [8] [ 750/2639] eta: 1:31:27 lr: 4.057508734423843e-05 loss: 0.0832 (0.0943) time: 2.8962 data: 0.0078 max mem: 33369 +Epoch: [8] [ 760/2639] eta: 1:30:58 lr: 4.057072424917256e-05 loss: 0.0704 (0.0941) time: 2.9017 data: 0.0079 max mem: 33369 +Epoch: [8] [ 770/2639] eta: 1:30:29 lr: 4.05663611019705e-05 loss: 0.0704 (0.0942) time: 2.9071 data: 0.0079 max mem: 33369 +Epoch: [8] [ 780/2639] eta: 1:29:59 lr: 4.05619979026254e-05 loss: 0.0889 (0.0944) time: 2.8924 data: 0.0081 max mem: 33369 +Epoch: [8] [ 790/2639] eta: 1:29:30 lr: 4.055763465113041e-05 loss: 0.0978 (0.0944) time: 2.8965 data: 0.0080 max mem: 33369 +Epoch: [8] [ 800/2639] eta: 1:29:01 lr: 4.0553271347478655e-05 loss: 0.1018 (0.0946) time: 2.9127 data: 0.0076 max mem: 33369 +Epoch: [8] [ 810/2639] eta: 1:28:31 lr: 4.054890799166329e-05 loss: 0.1009 (0.0946) time: 2.8832 data: 0.0077 max mem: 33369 +Epoch: [8] [ 820/2639] eta: 1:28:02 lr: 4.0544544583677446e-05 loss: 0.0942 (0.0948) time: 2.8874 data: 0.0078 max mem: 33369 +Epoch: [8] [ 830/2639] eta: 1:27:34 lr: 4.054018112351427e-05 loss: 0.0852 (0.0948) time: 2.9353 data: 0.0079 max mem: 33369 +Epoch: [8] [ 840/2639] eta: 1:27:04 lr: 4.05358176111669e-05 loss: 0.0946 (0.0949) time: 2.9087 data: 0.0081 max mem: 33369 +Epoch: [8] [ 850/2639] eta: 1:26:35 lr: 4.0531454046628456e-05 loss: 0.0946 (0.0948) time: 2.8800 data: 0.0079 max mem: 33369 +Epoch: [8] [ 860/2639] eta: 1:26:08 lr: 4.0527090429892083e-05 loss: 0.0747 (0.0947) time: 2.9536 data: 0.0078 max mem: 33369 +Epoch: [8] [ 870/2639] eta: 1:25:40 lr: 4.052272676095091e-05 loss: 0.0784 (0.0947) time: 2.9769 data: 0.0080 max mem: 33369 +Epoch: [8] [ 880/2639] eta: 1:25:11 lr: 4.0518363039798053e-05 loss: 0.0979 (0.0951) time: 2.9223 data: 0.0079 max mem: 33369 +Epoch: [8] [ 890/2639] eta: 1:24:40 lr: 4.051399926642666e-05 loss: 0.0950 (0.0950) time: 2.8609 data: 0.0083 max mem: 33369 +Epoch: [8] [ 900/2639] eta: 1:24:12 lr: 4.050963544082984e-05 loss: 0.0950 (0.0953) time: 2.8722 data: 0.0083 max mem: 33369 +Epoch: [8] [ 910/2639] eta: 1:23:42 lr: 4.0505271563000724e-05 loss: 0.0862 (0.0951) time: 2.9091 data: 0.0078 max mem: 33369 +Epoch: [8] [ 920/2639] eta: 1:23:13 lr: 4.050090763293243e-05 loss: 0.0792 (0.0950) time: 2.8945 data: 0.0080 max mem: 33369 +Epoch: [8] [ 930/2639] eta: 1:22:43 lr: 4.049654365061809e-05 loss: 0.0849 (0.0951) time: 2.8860 data: 0.0079 max mem: 33369 +Epoch: [8] [ 940/2639] eta: 1:22:15 lr: 4.0492179616050804e-05 loss: 0.0860 (0.0951) time: 2.9090 data: 0.0075 max mem: 33369 +Epoch: [8] [ 950/2639] eta: 1:21:46 lr: 4.04878155292237e-05 loss: 0.0887 (0.0953) time: 2.9255 data: 0.0080 max mem: 33369 +Epoch: [8] [ 960/2639] eta: 1:21:17 lr: 4.04834513901299e-05 loss: 0.0904 (0.0953) time: 2.8999 data: 0.0080 max mem: 33369 +Epoch: [8] [ 970/2639] eta: 1:20:48 lr: 4.0479087198762516e-05 loss: 0.0871 (0.0952) time: 2.9070 data: 0.0079 max mem: 33369 +Epoch: [8] [ 980/2639] eta: 1:20:19 lr: 4.0474722955114643e-05 loss: 0.0779 (0.0953) time: 2.9043 data: 0.0085 max mem: 33369 +Epoch: [8] [ 990/2639] eta: 1:19:49 lr: 4.04703586591794e-05 loss: 0.0757 (0.0952) time: 2.8828 data: 0.0083 max mem: 33369 +Epoch: [8] [1000/2639] eta: 1:19:20 lr: 4.046599431094989e-05 loss: 0.0887 (0.0955) time: 2.8740 data: 0.0080 max mem: 33369 +Epoch: [8] [1010/2639] eta: 1:18:50 lr: 4.046162991041924e-05 loss: 0.1166 (0.0954) time: 2.8710 data: 0.0082 max mem: 33369 +Epoch: [8] [1020/2639] eta: 1:18:21 lr: 4.0457265457580534e-05 loss: 0.0966 (0.0955) time: 2.8751 data: 0.0081 max mem: 33369 +Epoch: [8] [1030/2639] eta: 1:17:53 lr: 4.045290095242688e-05 loss: 0.1001 (0.0958) time: 2.9289 data: 0.0077 max mem: 33369 +Epoch: [8] [1040/2639] eta: 1:17:23 lr: 4.0448536394951395e-05 loss: 0.1046 (0.0960) time: 2.9147 data: 0.0076 max mem: 33369 +Epoch: [8] [1050/2639] eta: 1:16:54 lr: 4.044417178514715e-05 loss: 0.1026 (0.0960) time: 2.8700 data: 0.0080 max mem: 33369 +Epoch: [8] [1060/2639] eta: 1:16:24 lr: 4.043980712300726e-05 loss: 0.0957 (0.0962) time: 2.8705 data: 0.0084 max mem: 33369 +Epoch: [8] [1070/2639] eta: 1:15:55 lr: 4.043544240852482e-05 loss: 0.0887 (0.0963) time: 2.8815 data: 0.0082 max mem: 33369 +Epoch: [8] [1080/2639] eta: 1:15:25 lr: 4.043107764169292e-05 loss: 0.0870 (0.0963) time: 2.8867 data: 0.0078 max mem: 33369 +Epoch: [8] [1090/2639] eta: 1:14:56 lr: 4.042671282250466e-05 loss: 0.0949 (0.0962) time: 2.8784 data: 0.0078 max mem: 33369 +Epoch: [8] [1100/2639] eta: 1:14:28 lr: 4.042234795095313e-05 loss: 0.0839 (0.0961) time: 2.9306 data: 0.0080 max mem: 33369 +Epoch: [8] [1110/2639] eta: 1:13:59 lr: 4.041798302703141e-05 loss: 0.0730 (0.0960) time: 2.9539 data: 0.0080 max mem: 33369 +Epoch: [8] [1120/2639] eta: 1:13:31 lr: 4.0413618050732596e-05 loss: 0.0953 (0.0961) time: 2.9476 data: 0.0078 max mem: 33369 +Epoch: [8] [1130/2639] eta: 1:13:03 lr: 4.040925302204976e-05 loss: 0.0953 (0.0961) time: 2.9654 data: 0.0079 max mem: 33369 +Epoch: [8] [1140/2639] eta: 1:12:34 lr: 4.040488794097602e-05 loss: 0.0856 (0.0962) time: 2.9333 data: 0.0078 max mem: 33369 +Epoch: [8] [1150/2639] eta: 1:12:05 lr: 4.0400522807504414e-05 loss: 0.0861 (0.0962) time: 2.9253 data: 0.0078 max mem: 33369 +Epoch: [8] [1160/2639] eta: 1:11:36 lr: 4.0396157621628055e-05 loss: 0.0857 (0.0964) time: 2.9158 data: 0.0079 max mem: 33369 +Epoch: [8] [1170/2639] eta: 1:11:07 lr: 4.039179238334e-05 loss: 0.0849 (0.0963) time: 2.8744 data: 0.0076 max mem: 33369 +Epoch: [8] [1180/2639] eta: 1:10:38 lr: 4.0387427092633345e-05 loss: 0.0790 (0.0962) time: 2.9147 data: 0.0076 max mem: 33369 +Epoch: [8] [1190/2639] eta: 1:10:09 lr: 4.038306174950115e-05 loss: 0.0790 (0.0960) time: 2.9187 data: 0.0078 max mem: 33369 +Epoch: [8] [1200/2639] eta: 1:09:40 lr: 4.0378696353936494e-05 loss: 0.0799 (0.0961) time: 2.8929 data: 0.0079 max mem: 33369 +Epoch: [8] [1210/2639] eta: 1:09:10 lr: 4.037433090593245e-05 loss: 0.0778 (0.0959) time: 2.8962 data: 0.0078 max mem: 33369 +Epoch: [8] [1220/2639] eta: 1:08:41 lr: 4.03699654054821e-05 loss: 0.0782 (0.0960) time: 2.8865 data: 0.0078 max mem: 33369 +Epoch: [8] [1230/2639] eta: 1:08:12 lr: 4.036559985257848e-05 loss: 0.0813 (0.0960) time: 2.9000 data: 0.0079 max mem: 33369 +Epoch: [8] [1240/2639] eta: 1:07:43 lr: 4.0361234247214686e-05 loss: 0.0809 (0.0959) time: 2.8936 data: 0.0080 max mem: 33369 +Epoch: [8] [1250/2639] eta: 1:07:13 lr: 4.035686858938377e-05 loss: 0.0873 (0.0958) time: 2.8528 data: 0.0080 max mem: 33369 +Epoch: [8] [1260/2639] eta: 1:06:43 lr: 4.035250287907881e-05 loss: 0.0805 (0.0957) time: 2.8470 data: 0.0077 max mem: 33369 +Epoch: [8] [1270/2639] eta: 1:06:15 lr: 4.034813711629284e-05 loss: 0.0801 (0.0957) time: 2.8843 data: 0.0079 max mem: 33369 +Epoch: [8] [1280/2639] eta: 1:05:45 lr: 4.0343771301018934e-05 loss: 0.1081 (0.0958) time: 2.8935 data: 0.0080 max mem: 33369 +Epoch: [8] [1290/2639] eta: 1:05:16 lr: 4.033940543325015e-05 loss: 0.1073 (0.0958) time: 2.8613 data: 0.0078 max mem: 33369 +Epoch: [8] [1300/2639] eta: 1:04:47 lr: 4.033503951297956e-05 loss: 0.1026 (0.0959) time: 2.8825 data: 0.0077 max mem: 33369 +Epoch: [8] [1310/2639] eta: 1:04:17 lr: 4.0330673540200184e-05 loss: 0.1000 (0.0958) time: 2.8906 data: 0.0075 max mem: 33369 +Epoch: [8] [1320/2639] eta: 1:03:47 lr: 4.0326307514905094e-05 loss: 0.0881 (0.0959) time: 2.8475 data: 0.0080 max mem: 33369 +Epoch: [8] [1330/2639] eta: 1:03:18 lr: 4.032194143708734e-05 loss: 0.0953 (0.0961) time: 2.8642 data: 0.0083 max mem: 33369 +Epoch: [8] [1340/2639] eta: 1:02:49 lr: 4.031757530673997e-05 loss: 0.0958 (0.0961) time: 2.8720 data: 0.0080 max mem: 33369 +Epoch: [8] [1350/2639] eta: 1:02:20 lr: 4.031320912385604e-05 loss: 0.0939 (0.0962) time: 2.8558 data: 0.0079 max mem: 33369 +Epoch: [8] [1360/2639] eta: 1:01:50 lr: 4.0308842888428577e-05 loss: 0.0862 (0.0961) time: 2.8781 data: 0.0081 max mem: 33369 +Epoch: [8] [1370/2639] eta: 1:01:21 lr: 4.030447660045064e-05 loss: 0.0834 (0.0960) time: 2.8792 data: 0.0077 max mem: 33369 +Epoch: [8] [1380/2639] eta: 1:00:52 lr: 4.030011025991526e-05 loss: 0.0728 (0.0960) time: 2.8763 data: 0.0074 max mem: 33369 +Epoch: [8] [1390/2639] eta: 1:00:23 lr: 4.029574386681549e-05 loss: 0.0803 (0.0959) time: 2.9084 data: 0.0079 max mem: 33369 +Epoch: [8] [1400/2639] eta: 0:59:54 lr: 4.029137742114435e-05 loss: 0.0807 (0.0958) time: 2.9166 data: 0.0079 max mem: 33369 +Epoch: [8] [1410/2639] eta: 0:59:26 lr: 4.0287010922894895e-05 loss: 0.0910 (0.0960) time: 2.9391 data: 0.0079 max mem: 33369 +Epoch: [8] [1420/2639] eta: 0:58:57 lr: 4.0282644372060144e-05 loss: 0.1028 (0.0960) time: 2.9476 data: 0.0083 max mem: 33369 +Epoch: [8] [1430/2639] eta: 0:58:28 lr: 4.027827776863315e-05 loss: 0.0930 (0.0961) time: 2.9032 data: 0.0080 max mem: 33369 +Epoch: [8] [1440/2639] eta: 0:57:59 lr: 4.027391111260693e-05 loss: 0.0941 (0.0962) time: 2.8999 data: 0.0078 max mem: 33369 +Epoch: [8] [1450/2639] eta: 0:57:30 lr: 4.026954440397451e-05 loss: 0.0968 (0.0964) time: 2.9042 data: 0.0077 max mem: 33369 +Epoch: [8] [1460/2639] eta: 0:57:00 lr: 4.0265177642728925e-05 loss: 0.0890 (0.0963) time: 2.8653 data: 0.0081 max mem: 33369 +Epoch: [8] [1470/2639] eta: 0:56:31 lr: 4.02608108288632e-05 loss: 0.0897 (0.0964) time: 2.8556 data: 0.0085 max mem: 33369 +Epoch: [8] [1480/2639] eta: 0:56:02 lr: 4.025644396237036e-05 loss: 0.0801 (0.0964) time: 2.8956 data: 0.0079 max mem: 33369 +Epoch: [8] [1490/2639] eta: 0:55:33 lr: 4.025207704324342e-05 loss: 0.0778 (0.0964) time: 2.8774 data: 0.0074 max mem: 33369 +Epoch: [8] [1500/2639] eta: 0:55:04 lr: 4.024771007147542e-05 loss: 0.0968 (0.0966) time: 2.8997 data: 0.0075 max mem: 33369 +Epoch: [8] [1510/2639] eta: 0:54:35 lr: 4.024334304705937e-05 loss: 0.1003 (0.0965) time: 2.8996 data: 0.0077 max mem: 33369 +Epoch: [8] [1520/2639] eta: 0:54:06 lr: 4.023897596998827e-05 loss: 0.1003 (0.0966) time: 2.8850 data: 0.0076 max mem: 33369 +Epoch: [8] [1530/2639] eta: 0:53:37 lr: 4.023460884025515e-05 loss: 0.1022 (0.0966) time: 2.9123 data: 0.0076 max mem: 33369 +Epoch: [8] [1540/2639] eta: 0:53:08 lr: 4.023024165785303e-05 loss: 0.1027 (0.0968) time: 2.8952 data: 0.0078 max mem: 33369 +Epoch: [8] [1550/2639] eta: 0:52:39 lr: 4.022587442277491e-05 loss: 0.0966 (0.0967) time: 2.8983 data: 0.0085 max mem: 33369 +Epoch: [8] [1560/2639] eta: 0:52:10 lr: 4.0221507135013806e-05 loss: 0.0909 (0.0968) time: 2.8943 data: 0.0087 max mem: 33369 +Epoch: [8] [1570/2639] eta: 0:51:41 lr: 4.0217139794562724e-05 loss: 0.0888 (0.0967) time: 2.9121 data: 0.0079 max mem: 33369 +Epoch: [8] [1580/2639] eta: 0:51:11 lr: 4.021277240141467e-05 loss: 0.0888 (0.0967) time: 2.8820 data: 0.0079 max mem: 33369 +Epoch: [8] [1590/2639] eta: 0:50:42 lr: 4.020840495556265e-05 loss: 0.0932 (0.0966) time: 2.8575 data: 0.0079 max mem: 33369 +Epoch: [8] [1600/2639] eta: 0:50:13 lr: 4.020403745699968e-05 loss: 0.0955 (0.0967) time: 2.8543 data: 0.0080 max mem: 33369 +Epoch: [8] [1610/2639] eta: 0:49:44 lr: 4.019966990571873e-05 loss: 0.0898 (0.0967) time: 2.8620 data: 0.0081 max mem: 33369 +Epoch: [8] [1620/2639] eta: 0:49:15 lr: 4.0195302301712834e-05 loss: 0.0836 (0.0967) time: 2.8971 data: 0.0083 max mem: 33369 +Epoch: [8] [1630/2639] eta: 0:48:46 lr: 4.019093464497497e-05 loss: 0.0841 (0.0967) time: 2.8849 data: 0.0086 max mem: 33369 +Epoch: [8] [1640/2639] eta: 0:48:16 lr: 4.018656693549813e-05 loss: 0.0841 (0.0967) time: 2.8798 data: 0.0081 max mem: 33369 +Epoch: [8] [1650/2639] eta: 0:47:47 lr: 4.018219917327532e-05 loss: 0.0928 (0.0968) time: 2.8963 data: 0.0080 max mem: 33369 +Epoch: [8] [1660/2639] eta: 0:47:18 lr: 4.0177831358299536e-05 loss: 0.0928 (0.0968) time: 2.8883 data: 0.0082 max mem: 33369 +Epoch: [8] [1670/2639] eta: 0:46:49 lr: 4.017346349056375e-05 loss: 0.0852 (0.0968) time: 2.8790 data: 0.0078 max mem: 33369 +Epoch: [8] [1680/2639] eta: 0:46:20 lr: 4.0169095570060974e-05 loss: 0.0947 (0.0970) time: 2.8698 data: 0.0077 max mem: 33369 +Epoch: [8] [1690/2639] eta: 0:45:51 lr: 4.016472759678417e-05 loss: 0.0993 (0.0970) time: 2.8875 data: 0.0076 max mem: 33369 +Epoch: [8] [1700/2639] eta: 0:45:22 lr: 4.016035957072634e-05 loss: 0.0993 (0.0970) time: 2.9171 data: 0.0074 max mem: 33369 +Epoch: [8] [1710/2639] eta: 0:44:53 lr: 4.015599149188047e-05 loss: 0.1058 (0.0971) time: 2.9063 data: 0.0078 max mem: 33369 +Epoch: [8] [1720/2639] eta: 0:44:24 lr: 4.0151623360239534e-05 loss: 0.0894 (0.0971) time: 2.8989 data: 0.0081 max mem: 33369 +Epoch: [8] [1730/2639] eta: 0:43:55 lr: 4.01472551757965e-05 loss: 0.0878 (0.0971) time: 2.8779 data: 0.0082 max mem: 33369 +Epoch: [8] [1740/2639] eta: 0:43:26 lr: 4.0142886938544374e-05 loss: 0.0878 (0.0971) time: 2.8608 data: 0.0080 max mem: 33369 +Epoch: [8] [1750/2639] eta: 0:42:57 lr: 4.0138518648476117e-05 loss: 0.0863 (0.0972) time: 2.9153 data: 0.0076 max mem: 33369 +Epoch: [8] [1760/2639] eta: 0:42:28 lr: 4.01341503055847e-05 loss: 0.0863 (0.0974) time: 2.9422 data: 0.0075 max mem: 33369 +Epoch: [8] [1770/2639] eta: 0:41:59 lr: 4.01297819098631e-05 loss: 0.0860 (0.0974) time: 2.8942 data: 0.0079 max mem: 33369 +Epoch: [8] [1780/2639] eta: 0:41:30 lr: 4.012541346130429e-05 loss: 0.0952 (0.0974) time: 2.8952 data: 0.0079 max mem: 33369 +Epoch: [8] [1790/2639] eta: 0:41:01 lr: 4.012104495990124e-05 loss: 0.0975 (0.0975) time: 2.9119 data: 0.0078 max mem: 33369 +Epoch: [8] [1800/2639] eta: 0:40:32 lr: 4.011667640564692e-05 loss: 0.0961 (0.0976) time: 2.8971 data: 0.0081 max mem: 33369 +Epoch: [8] [1810/2639] eta: 0:40:03 lr: 4.011230779853428e-05 loss: 0.1002 (0.0976) time: 2.9004 data: 0.0083 max mem: 33369 +Epoch: [8] [1820/2639] eta: 0:39:34 lr: 4.01079391385563e-05 loss: 0.1032 (0.0977) time: 2.9242 data: 0.0076 max mem: 33369 +Epoch: [8] [1830/2639] eta: 0:39:06 lr: 4.010357042570593e-05 loss: 0.0854 (0.0976) time: 2.9508 data: 0.0071 max mem: 33369 +Epoch: [8] [1840/2639] eta: 0:38:37 lr: 4.0099201659976136e-05 loss: 0.0798 (0.0975) time: 2.9593 data: 0.0076 max mem: 33369 +Epoch: [8] [1850/2639] eta: 0:38:08 lr: 4.009483284135989e-05 loss: 0.0788 (0.0975) time: 2.9470 data: 0.0077 max mem: 33369 +Epoch: [8] [1860/2639] eta: 0:37:39 lr: 4.009046396985012e-05 loss: 0.0795 (0.0974) time: 2.9399 data: 0.0074 max mem: 33369 +Epoch: [8] [1870/2639] eta: 0:37:10 lr: 4.0086095045439816e-05 loss: 0.0857 (0.0974) time: 2.9486 data: 0.0072 max mem: 33369 +Epoch: [8] [1880/2639] eta: 0:36:41 lr: 4.00817260681219e-05 loss: 0.0858 (0.0974) time: 2.9076 data: 0.0073 max mem: 33369 +Epoch: [8] [1890/2639] eta: 0:36:12 lr: 4.0077357037889335e-05 loss: 0.0859 (0.0973) time: 2.8621 data: 0.0078 max mem: 33369 +Epoch: [8] [1900/2639] eta: 0:35:43 lr: 4.0072987954735076e-05 loss: 0.0928 (0.0974) time: 2.8551 data: 0.0079 max mem: 33369 +Epoch: [8] [1910/2639] eta: 0:35:14 lr: 4.006861881865206e-05 loss: 0.1015 (0.0974) time: 2.8613 data: 0.0078 max mem: 33369 +Epoch: [8] [1920/2639] eta: 0:34:45 lr: 4.006424962963324e-05 loss: 0.1041 (0.0975) time: 2.9055 data: 0.0077 max mem: 33369 +Epoch: [8] [1930/2639] eta: 0:34:16 lr: 4.005988038767157e-05 loss: 0.0881 (0.0975) time: 2.8991 data: 0.0076 max mem: 33369 +Epoch: [8] [1940/2639] eta: 0:33:47 lr: 4.005551109275996e-05 loss: 0.0772 (0.0974) time: 2.8938 data: 0.0077 max mem: 33369 +Epoch: [8] [1950/2639] eta: 0:33:18 lr: 4.0051141744891384e-05 loss: 0.0795 (0.0974) time: 2.8786 data: 0.0077 max mem: 33369 +Epoch: [8] [1960/2639] eta: 0:32:49 lr: 4.004677234405877e-05 loss: 0.0884 (0.0974) time: 2.8791 data: 0.0076 max mem: 33369 +Epoch: [8] [1970/2639] eta: 0:32:20 lr: 4.004240289025505e-05 loss: 0.0935 (0.0975) time: 2.8987 data: 0.0078 max mem: 33369 +Epoch: [8] [1980/2639] eta: 0:31:51 lr: 4.003803338347317e-05 loss: 0.0918 (0.0975) time: 2.9020 data: 0.0080 max mem: 33369 +Epoch: [8] [1990/2639] eta: 0:31:22 lr: 4.003366382370605e-05 loss: 0.0906 (0.0976) time: 2.9394 data: 0.0079 max mem: 33369 +Epoch: [8] [2000/2639] eta: 0:30:53 lr: 4.002929421094663e-05 loss: 0.1029 (0.0976) time: 2.9448 data: 0.0079 max mem: 33369 +Epoch: [8] [2010/2639] eta: 0:30:24 lr: 4.002492454518784e-05 loss: 0.1043 (0.0976) time: 2.9379 data: 0.0077 max mem: 33369 +Epoch: [8] [2020/2639] eta: 0:29:55 lr: 4.00205548264226e-05 loss: 0.0857 (0.0977) time: 2.9447 data: 0.0073 max mem: 33369 +Epoch: [8] [2030/2639] eta: 0:29:26 lr: 4.0016185054643834e-05 loss: 0.0945 (0.0977) time: 2.9308 data: 0.0074 max mem: 33369 +Epoch: [8] [2040/2639] eta: 0:28:57 lr: 4.001181522984449e-05 loss: 0.0984 (0.0977) time: 2.8994 data: 0.0074 max mem: 33369 +Epoch: [8] [2050/2639] eta: 0:28:28 lr: 4.000744535201746e-05 loss: 0.0984 (0.0978) time: 2.8984 data: 0.0076 max mem: 33369 +Epoch: [8] [2060/2639] eta: 0:27:59 lr: 4.0003075421155686e-05 loss: 0.0909 (0.0978) time: 2.8829 data: 0.0078 max mem: 33369 +Epoch: [8] [2070/2639] eta: 0:27:30 lr: 3.999870543725208e-05 loss: 0.0947 (0.0979) time: 2.8736 data: 0.0076 max mem: 33369 +Epoch: [8] [2080/2639] eta: 0:27:01 lr: 3.9994335400299565e-05 loss: 0.0962 (0.0978) time: 2.8862 data: 0.0078 max mem: 33369 +Epoch: [8] [2090/2639] eta: 0:26:32 lr: 3.9989965310291044e-05 loss: 0.0852 (0.0979) time: 2.9034 data: 0.0077 max mem: 33369 +Epoch: [8] [2100/2639] eta: 0:26:03 lr: 3.998559516721944e-05 loss: 0.0967 (0.0979) time: 2.9052 data: 0.0074 max mem: 33369 +Epoch: [8] [2110/2639] eta: 0:25:34 lr: 3.998122497107766e-05 loss: 0.0946 (0.0979) time: 2.8874 data: 0.0079 max mem: 33369 +Epoch: [8] [2120/2639] eta: 0:25:05 lr: 3.997685472185862e-05 loss: 0.0861 (0.0979) time: 2.9030 data: 0.0077 max mem: 33369 +Epoch: [8] [2130/2639] eta: 0:24:36 lr: 3.997248441955522e-05 loss: 0.0850 (0.0980) time: 2.8931 data: 0.0078 max mem: 33369 +Epoch: [8] [2140/2639] eta: 0:24:07 lr: 3.9968114064160373e-05 loss: 0.0996 (0.0980) time: 2.8549 data: 0.0078 max mem: 33369 +Epoch: [8] [2150/2639] eta: 0:23:38 lr: 3.996374365566698e-05 loss: 0.1009 (0.0980) time: 2.8465 data: 0.0078 max mem: 33369 +Epoch: [8] [2160/2639] eta: 0:23:09 lr: 3.995937319406794e-05 loss: 0.1035 (0.0981) time: 2.8658 data: 0.0078 max mem: 33369 +Epoch: [8] [2170/2639] eta: 0:22:39 lr: 3.995500267935616e-05 loss: 0.0959 (0.0980) time: 2.8451 data: 0.0076 max mem: 33369 +Epoch: [8] [2180/2639] eta: 0:22:10 lr: 3.995063211152454e-05 loss: 0.0959 (0.0981) time: 2.8578 data: 0.0075 max mem: 33369 +Epoch: [8] [2190/2639] eta: 0:21:41 lr: 3.994626149056597e-05 loss: 0.0876 (0.0981) time: 2.8951 data: 0.0073 max mem: 33369 +Epoch: [8] [2200/2639] eta: 0:21:12 lr: 3.994189081647335e-05 loss: 0.0877 (0.0982) time: 2.9012 data: 0.0077 max mem: 33369 +Epoch: [8] [2210/2639] eta: 0:20:44 lr: 3.9937520089239586e-05 loss: 0.0843 (0.0981) time: 2.9409 data: 0.0077 max mem: 33369 +Epoch: [8] [2220/2639] eta: 0:20:15 lr: 3.9933149308857553e-05 loss: 0.0820 (0.0982) time: 2.9535 data: 0.0074 max mem: 33369 +Epoch: [8] [2230/2639] eta: 0:19:46 lr: 3.992877847532014e-05 loss: 0.0820 (0.0981) time: 2.9178 data: 0.0077 max mem: 33369 +Epoch: [8] [2240/2639] eta: 0:19:17 lr: 3.9924407588620243e-05 loss: 0.0789 (0.0980) time: 2.9235 data: 0.0082 max mem: 33369 +Epoch: [8] [2250/2639] eta: 0:18:48 lr: 3.992003664875075e-05 loss: 0.0893 (0.0981) time: 2.9319 data: 0.0085 max mem: 33369 +Epoch: [8] [2260/2639] eta: 0:18:19 lr: 3.9915665655704534e-05 loss: 0.0899 (0.0980) time: 2.9182 data: 0.0087 max mem: 33369 +Epoch: [8] [2270/2639] eta: 0:17:50 lr: 3.991129460947449e-05 loss: 0.0900 (0.0980) time: 2.9148 data: 0.0085 max mem: 33369 +Epoch: [8] [2280/2639] eta: 0:17:21 lr: 3.990692351005349e-05 loss: 0.0902 (0.0980) time: 2.8777 data: 0.0078 max mem: 33369 +Epoch: [8] [2290/2639] eta: 0:16:52 lr: 3.990255235743443e-05 loss: 0.0871 (0.0980) time: 2.8656 data: 0.0073 max mem: 33369 +Epoch: [8] [2300/2639] eta: 0:16:23 lr: 3.989818115161016e-05 loss: 0.0773 (0.0979) time: 2.9410 data: 0.0073 max mem: 33369 +Epoch: [8] [2310/2639] eta: 0:15:54 lr: 3.989380989257358e-05 loss: 0.0849 (0.0980) time: 2.9450 data: 0.0075 max mem: 33369 +Epoch: [8] [2320/2639] eta: 0:15:25 lr: 3.988943858031755e-05 loss: 0.1024 (0.0980) time: 2.9317 data: 0.0076 max mem: 33369 +Epoch: [8] [2330/2639] eta: 0:14:56 lr: 3.9885067214834943e-05 loss: 0.1024 (0.0981) time: 2.9639 data: 0.0077 max mem: 33369 +Epoch: [8] [2340/2639] eta: 0:14:27 lr: 3.9880695796118636e-05 loss: 0.0788 (0.0981) time: 2.9204 data: 0.0079 max mem: 33369 +Epoch: [8] [2350/2639] eta: 0:13:58 lr: 3.987632432416149e-05 loss: 0.0718 (0.0980) time: 2.8615 data: 0.0077 max mem: 33369 +Epoch: [8] [2360/2639] eta: 0:13:29 lr: 3.987195279895637e-05 loss: 0.0817 (0.0980) time: 2.8562 data: 0.0079 max mem: 33369 +Epoch: [8] [2370/2639] eta: 0:13:00 lr: 3.986758122049615e-05 loss: 0.0987 (0.0981) time: 2.8823 data: 0.0081 max mem: 33369 +Epoch: [8] [2380/2639] eta: 0:12:31 lr: 3.9863209588773685e-05 loss: 0.0937 (0.0981) time: 2.8919 data: 0.0078 max mem: 33369 +Epoch: [8] [2390/2639] eta: 0:12:02 lr: 3.9858837903781844e-05 loss: 0.0862 (0.0981) time: 2.8628 data: 0.0075 max mem: 33369 +Epoch: [8] [2400/2639] eta: 0:11:33 lr: 3.985446616551347e-05 loss: 0.0958 (0.0981) time: 2.8640 data: 0.0075 max mem: 33369 +Epoch: [8] [2410/2639] eta: 0:11:04 lr: 3.985009437396144e-05 loss: 0.0858 (0.0981) time: 2.8826 data: 0.0079 max mem: 33369 +Epoch: [8] [2420/2639] eta: 0:10:35 lr: 3.9845722529118596e-05 loss: 0.1032 (0.0981) time: 2.8931 data: 0.0079 max mem: 33369 +Epoch: [8] [2430/2639] eta: 0:10:06 lr: 3.984135063097779e-05 loss: 0.0963 (0.0981) time: 2.8729 data: 0.0078 max mem: 33369 +Epoch: [8] [2440/2639] eta: 0:09:37 lr: 3.983697867953188e-05 loss: 0.0811 (0.0981) time: 2.8520 data: 0.0077 max mem: 33369 +Epoch: [8] [2450/2639] eta: 0:09:08 lr: 3.983260667477372e-05 loss: 0.0846 (0.0981) time: 2.8851 data: 0.0082 max mem: 33369 +Epoch: [8] [2460/2639] eta: 0:08:39 lr: 3.982823461669615e-05 loss: 0.0903 (0.0981) time: 2.8957 data: 0.0083 max mem: 33369 +Epoch: [8] [2470/2639] eta: 0:08:10 lr: 3.982386250529203e-05 loss: 0.1010 (0.0982) time: 2.8832 data: 0.0083 max mem: 33369 +Epoch: [8] [2480/2639] eta: 0:07:41 lr: 3.981949034055418e-05 loss: 0.1072 (0.0982) time: 2.8808 data: 0.0078 max mem: 33369 +Epoch: [8] [2490/2639] eta: 0:07:12 lr: 3.9815118122475455e-05 loss: 0.0856 (0.0982) time: 2.8863 data: 0.0071 max mem: 33369 +Epoch: [8] [2500/2639] eta: 0:06:43 lr: 3.98107458510487e-05 loss: 0.0856 (0.0982) time: 2.8772 data: 0.0073 max mem: 33369 +Epoch: [8] [2510/2639] eta: 0:06:14 lr: 3.980637352626676e-05 loss: 0.0854 (0.0982) time: 2.9201 data: 0.0075 max mem: 33369 +Epoch: [8] [2520/2639] eta: 0:05:45 lr: 3.9802001148122446e-05 loss: 0.0817 (0.0982) time: 2.9251 data: 0.0074 max mem: 33369 +Epoch: [8] [2530/2639] eta: 0:05:16 lr: 3.979762871660862e-05 loss: 0.0973 (0.0983) time: 2.8846 data: 0.0073 max mem: 33369 +Epoch: [8] [2540/2639] eta: 0:04:47 lr: 3.9793256231718104e-05 loss: 0.1047 (0.0984) time: 2.8897 data: 0.0073 max mem: 33369 +Epoch: [8] [2550/2639] eta: 0:04:18 lr: 3.978888369344374e-05 loss: 0.1172 (0.0984) time: 2.9176 data: 0.0075 max mem: 33369 +Epoch: [8] [2560/2639] eta: 0:03:49 lr: 3.9784511101778336e-05 loss: 0.1044 (0.0984) time: 2.9296 data: 0.0079 max mem: 33369 +Epoch: [8] [2570/2639] eta: 0:03:20 lr: 3.978013845671473e-05 loss: 0.0871 (0.0984) time: 2.9237 data: 0.0078 max mem: 33369 +Epoch: [8] [2580/2639] eta: 0:02:51 lr: 3.977576575824575e-05 loss: 0.0999 (0.0985) time: 2.9547 data: 0.0081 max mem: 33369 +Epoch: [8] [2590/2639] eta: 0:02:22 lr: 3.977139300636423e-05 loss: 0.0994 (0.0984) time: 2.9481 data: 0.0082 max mem: 33369 +Epoch: [8] [2600/2639] eta: 0:01:53 lr: 3.9767020201062984e-05 loss: 0.0929 (0.0985) time: 2.9054 data: 0.0074 max mem: 33369 +Epoch: [8] [2610/2639] eta: 0:01:24 lr: 3.9762647342334816e-05 loss: 0.1081 (0.0985) time: 2.9010 data: 0.0076 max mem: 33369 +Epoch: [8] [2620/2639] eta: 0:00:55 lr: 3.975827443017258e-05 loss: 0.0944 (0.0986) time: 2.9498 data: 0.0078 max mem: 33369 +Epoch: [8] [2630/2639] eta: 0:00:26 lr: 3.975390146456906e-05 loss: 0.0997 (0.0987) time: 2.9315 data: 0.0072 max mem: 33369 +Epoch: [8] Total time: 2:07:36 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 2:15:17 time: 3.1547 data: 3.0274 max mem: 33369 +Test: [ 100/2573] eta: 0:04:28 time: 0.0795 data: 0.0015 max mem: 33369 +Test: [ 200/2573] eta: 0:03:44 time: 0.0793 data: 0.0014 max mem: 33369 +Test: [ 300/2573] eta: 0:03:22 time: 0.0812 data: 0.0014 max mem: 33369 +Test: [ 400/2573] eta: 0:03:09 time: 0.0815 data: 0.0015 max mem: 33369 +Test: [ 500/2573] eta: 0:02:57 time: 0.0804 data: 0.0014 max mem: 33369 +Test: [ 600/2573] eta: 0:02:47 time: 0.0805 data: 0.0015 max mem: 33369 +Test: [ 700/2573] eta: 0:02:38 time: 0.0804 data: 0.0014 max mem: 33369 +Test: [ 800/2573] eta: 0:02:29 time: 0.0836 data: 0.0014 max mem: 33369 +Test: [ 900/2573] eta: 0:02:20 time: 0.0806 data: 0.0014 max mem: 33369 +Test: [1000/2573] eta: 0:02:11 time: 0.0810 data: 0.0014 max mem: 33369 +Test: [1100/2573] eta: 0:02:02 time: 0.0817 data: 0.0014 max mem: 33369 +Test: [1200/2573] eta: 0:01:54 time: 0.0805 data: 0.0014 max mem: 33369 +Test: [1300/2573] eta: 0:01:45 time: 0.0809 data: 0.0014 max mem: 33369 +Test: [1400/2573] eta: 0:01:37 time: 0.0797 data: 0.0015 max mem: 33369 +Test: [1500/2573] eta: 0:01:28 time: 0.0799 data: 0.0015 max mem: 33369 +Test: [1600/2573] eta: 0:01:20 time: 0.0842 data: 0.0014 max mem: 33369 +Test: [1700/2573] eta: 0:01:12 time: 0.0785 data: 0.0014 max mem: 33369 +Test: [1800/2573] eta: 0:01:03 time: 0.0824 data: 0.0014 max mem: 33369 +Test: [1900/2573] eta: 0:00:55 time: 0.0801 data: 0.0013 max mem: 33369 +Test: [2000/2573] eta: 0:00:47 time: 0.0809 data: 0.0016 max mem: 33369 +Test: [2100/2573] eta: 0:00:38 time: 0.0824 data: 0.0014 max mem: 33369 +Test: [2200/2573] eta: 0:00:30 time: 0.0826 data: 0.0014 max mem: 33369 +Test: [2300/2573] eta: 0:00:22 time: 0.0823 data: 0.0014 max mem: 33369 +Test: [2400/2573] eta: 0:00:14 time: 0.0933 data: 0.0162 max mem: 33369 +Test: [2500/2573] eta: 0:00:05 time: 0.0797 data: 0.0013 max mem: 33369 +Test: Total time: 0:03:31 +Final results: +Mean IoU is 58.50 + + precision@0.5 = 65.73 + precision@0.6 = 58.88 + precision@0.7 = 50.22 + precision@0.8 = 37.72 + precision@0.9 = 16.14 + overall IoU = 57.35 + +Average object IoU 58.4990080038846 +Overall IoU 57.350563049316406 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [9] [ 0/2639] eta: 5:05:54 lr: 3.9749965749827665e-05 loss: 0.0900 (0.0900) time: 6.9550 data: 3.2960 max mem: 33369 +Epoch: [9] [ 10/2639] eta: 2:27:12 lr: 3.9745592682665946e-05 loss: 0.0948 (0.0953) time: 3.3596 data: 0.3079 max mem: 33369 +Epoch: [9] [ 20/2639] eta: 2:17:31 lr: 3.9741219562042095e-05 loss: 0.0948 (0.0948) time: 2.9606 data: 0.0079 max mem: 33369 +Epoch: [9] [ 30/2639] eta: 2:13:40 lr: 3.973684638794896e-05 loss: 0.0830 (0.0941) time: 2.9172 data: 0.0074 max mem: 33369 +Epoch: [9] [ 40/2639] eta: 2:11:41 lr: 3.973247316037931e-05 loss: 0.0711 (0.0905) time: 2.9244 data: 0.0078 max mem: 33369 +Epoch: [9] [ 50/2639] eta: 2:09:40 lr: 3.9728099879325984e-05 loss: 0.0711 (0.0905) time: 2.8982 data: 0.0076 max mem: 33369 +Epoch: [9] [ 60/2639] eta: 2:08:12 lr: 3.972372654478177e-05 loss: 0.0872 (0.0888) time: 2.8652 data: 0.0081 max mem: 33369 +Epoch: [9] [ 70/2639] eta: 2:06:53 lr: 3.971935315673947e-05 loss: 0.0879 (0.0922) time: 2.8573 data: 0.0082 max mem: 33369 +Epoch: [9] [ 80/2639] eta: 2:06:17 lr: 3.9714979715191894e-05 loss: 0.0759 (0.0895) time: 2.8939 data: 0.0080 max mem: 33369 +Epoch: [9] [ 90/2639] eta: 2:05:26 lr: 3.9710606220131824e-05 loss: 0.0731 (0.0913) time: 2.9153 data: 0.0079 max mem: 33369 +Epoch: [9] [ 100/2639] eta: 2:04:33 lr: 3.970623267155207e-05 loss: 0.0777 (0.0919) time: 2.8736 data: 0.0079 max mem: 33369 +Epoch: [9] [ 110/2639] eta: 2:04:05 lr: 3.970185906944543e-05 loss: 0.0845 (0.0915) time: 2.9037 data: 0.0080 max mem: 33369 +Epoch: [9] [ 120/2639] eta: 2:03:04 lr: 3.969748541380469e-05 loss: 0.0845 (0.0906) time: 2.8713 data: 0.0079 max mem: 33369 +Epoch: [9] [ 130/2639] eta: 2:02:24 lr: 3.9693111704622624e-05 loss: 0.0749 (0.0918) time: 2.8334 data: 0.0081 max mem: 33369 +Epoch: [9] [ 140/2639] eta: 2:01:42 lr: 3.968873794189206e-05 loss: 0.0887 (0.0921) time: 2.8654 data: 0.0078 max mem: 33369 +Epoch: [9] [ 150/2639] eta: 2:01:05 lr: 3.9684364125605754e-05 loss: 0.0886 (0.0915) time: 2.8660 data: 0.0077 max mem: 33369 +Epoch: [9] [ 160/2639] eta: 2:00:29 lr: 3.96799902557565e-05 loss: 0.0857 (0.0917) time: 2.8729 data: 0.0077 max mem: 33369 +Epoch: [9] [ 170/2639] eta: 1:59:51 lr: 3.9675616332337084e-05 loss: 0.0817 (0.0912) time: 2.8660 data: 0.0076 max mem: 33369 +Epoch: [9] [ 180/2639] eta: 1:59:25 lr: 3.967124235534029e-05 loss: 0.0817 (0.0913) time: 2.8968 data: 0.0078 max mem: 33369 +Epoch: [9] [ 190/2639] eta: 1:58:58 lr: 3.9666868324758894e-05 loss: 0.0948 (0.0917) time: 2.9305 data: 0.0080 max mem: 33369 +Epoch: [9] [ 200/2639] eta: 1:58:33 lr: 3.966249424058568e-05 loss: 0.0920 (0.0913) time: 2.9391 data: 0.0084 max mem: 33369 +Epoch: [9] [ 210/2639] eta: 1:57:58 lr: 3.9658120102813415e-05 loss: 0.0827 (0.0912) time: 2.9085 data: 0.0084 max mem: 33369 +Epoch: [9] [ 220/2639] eta: 1:57:40 lr: 3.9653745911434874e-05 loss: 0.0680 (0.0905) time: 2.9424 data: 0.0079 max mem: 33369 +Epoch: [9] [ 230/2639] eta: 1:57:09 lr: 3.9649371666442834e-05 loss: 0.0683 (0.0903) time: 2.9613 data: 0.0083 max mem: 33369 +Epoch: [9] [ 240/2639] eta: 1:56:37 lr: 3.964499736783007e-05 loss: 0.0714 (0.0901) time: 2.8968 data: 0.0086 max mem: 33369 +Epoch: [9] [ 250/2639] eta: 1:56:14 lr: 3.964062301558935e-05 loss: 0.0714 (0.0898) time: 2.9347 data: 0.0085 max mem: 33369 +Epoch: [9] [ 260/2639] eta: 1:55:44 lr: 3.963624860971343e-05 loss: 0.0688 (0.0890) time: 2.9440 data: 0.0084 max mem: 33369 +Epoch: [9] [ 270/2639] eta: 1:55:18 lr: 3.963187415019508e-05 loss: 0.0689 (0.0891) time: 2.9296 data: 0.0082 max mem: 33369 +Epoch: [9] [ 280/2639] eta: 1:54:49 lr: 3.962749963702707e-05 loss: 0.0782 (0.0887) time: 2.9409 data: 0.0081 max mem: 33369 +Epoch: [9] [ 290/2639] eta: 1:54:16 lr: 3.962312507020216e-05 loss: 0.0832 (0.0889) time: 2.9014 data: 0.0084 max mem: 33369 +Epoch: [9] [ 300/2639] eta: 1:53:44 lr: 3.96187504497131e-05 loss: 0.0822 (0.0893) time: 2.8781 data: 0.0083 max mem: 33369 +Epoch: [9] [ 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+Epoch: [9] [ 390/2639] eta: 1:49:16 lr: 3.9579376449229504e-05 loss: 0.0784 (0.0886) time: 2.9465 data: 0.0083 max mem: 33369 +Epoch: [9] [ 400/2639] eta: 1:48:44 lr: 3.9575001291700375e-05 loss: 0.0837 (0.0889) time: 2.9293 data: 0.0085 max mem: 33369 +Epoch: [9] [ 410/2639] eta: 1:48:15 lr: 3.9570626080427325e-05 loss: 0.1018 (0.0890) time: 2.8885 data: 0.0079 max mem: 33369 +Epoch: [9] [ 420/2639] eta: 1:47:45 lr: 3.956625081540311e-05 loss: 0.0787 (0.0887) time: 2.9045 data: 0.0080 max mem: 33369 +Epoch: [9] [ 430/2639] eta: 1:47:12 lr: 3.956187549662044e-05 loss: 0.0722 (0.0894) time: 2.8755 data: 0.0080 max mem: 33369 +Epoch: [9] [ 440/2639] eta: 1:46:42 lr: 3.955750012407208e-05 loss: 0.0737 (0.0891) time: 2.8684 data: 0.0078 max mem: 33369 +Epoch: [9] [ 450/2639] eta: 1:46:13 lr: 3.955312469775074e-05 loss: 0.0758 (0.0892) time: 2.9024 data: 0.0080 max mem: 33369 +Epoch: [9] [ 460/2639] eta: 1:45:45 lr: 3.9548749217649145e-05 loss: 0.0812 (0.0890) time: 2.9248 data: 0.0079 max mem: 33369 +Epoch: [9] [ 470/2639] eta: 1:45:17 lr: 3.954437368376004e-05 loss: 0.0740 (0.0888) time: 2.9314 data: 0.0076 max mem: 33369 +Epoch: [9] [ 480/2639] eta: 1:44:46 lr: 3.953999809607614e-05 loss: 0.0770 (0.0890) time: 2.9018 data: 0.0079 max mem: 33369 +Epoch: [9] [ 490/2639] eta: 1:44:17 lr: 3.9535622454590184e-05 loss: 0.0893 (0.0891) time: 2.8951 data: 0.0081 max mem: 33369 +Epoch: [9] [ 500/2639] eta: 1:43:46 lr: 3.953124675929487e-05 loss: 0.0773 (0.0889) time: 2.8925 data: 0.0079 max mem: 33369 +Epoch: [9] [ 510/2639] eta: 1:43:14 lr: 3.952687101018293e-05 loss: 0.0789 (0.0888) time: 2.8534 data: 0.0080 max mem: 33369 +Epoch: [9] [ 520/2639] eta: 1:42:42 lr: 3.952249520724708e-05 loss: 0.0789 (0.0885) time: 2.8384 data: 0.0082 max mem: 33369 +Epoch: [9] [ 530/2639] eta: 1:42:11 lr: 3.951811935048005e-05 loss: 0.0814 (0.0890) time: 2.8554 data: 0.0082 max mem: 33369 +Epoch: [9] [ 540/2639] eta: 1:41:40 lr: 3.9513743439874535e-05 loss: 0.0809 (0.0888) time: 2.8606 data: 0.0078 max mem: 33369 +Epoch: [9] [ 550/2639] eta: 1:41:09 lr: 3.950936747542326e-05 loss: 0.0714 (0.0887) time: 2.8551 data: 0.0078 max mem: 33369 +Epoch: [9] [ 560/2639] eta: 1:40:39 lr: 3.9504991457118925e-05 loss: 0.0796 (0.0887) time: 2.8722 data: 0.0077 max mem: 33369 +Epoch: [9] [ 570/2639] eta: 1:40:11 lr: 3.950061538495426e-05 loss: 0.0830 (0.0889) time: 2.9102 data: 0.0077 max mem: 33369 +Epoch: [9] [ 580/2639] eta: 1:39:40 lr: 3.949623925892194e-05 loss: 0.0829 (0.0888) time: 2.8930 data: 0.0079 max mem: 33369 +Epoch: [9] [ 590/2639] eta: 1:39:12 lr: 3.9491863079014695e-05 loss: 0.0776 (0.0886) time: 2.8881 data: 0.0081 max mem: 33369 +Epoch: [9] [ 600/2639] eta: 1:38:42 lr: 3.948748684522523e-05 loss: 0.0792 (0.0885) time: 2.8950 data: 0.0082 max mem: 33369 +Epoch: [9] [ 610/2639] eta: 1:38:11 lr: 3.948311055754623e-05 loss: 0.0843 (0.0885) time: 2.8644 data: 0.0081 max mem: 33369 +Epoch: [9] [ 620/2639] eta: 1:37:42 lr: 3.94787342159704e-05 loss: 0.0885 (0.0886) time: 2.8783 data: 0.0079 max mem: 33369 +Epoch: [9] [ 630/2639] eta: 1:37:15 lr: 3.947435782049044e-05 loss: 0.0889 (0.0885) time: 2.9321 data: 0.0077 max mem: 33369 +Epoch: [9] [ 640/2639] eta: 1:36:49 lr: 3.9469981371099054e-05 loss: 0.0870 (0.0886) time: 2.9806 data: 0.0078 max mem: 33369 +Epoch: [9] [ 650/2639] eta: 1:36:20 lr: 3.946560486778892e-05 loss: 0.0870 (0.0888) time: 2.9539 data: 0.0081 max mem: 33369 +Epoch: [9] [ 660/2639] eta: 1:35:49 lr: 3.9461228310552735e-05 loss: 0.0777 (0.0890) time: 2.8764 data: 0.0081 max mem: 33369 +Epoch: [9] [ 670/2639] eta: 1:35:18 lr: 3.945685169938319e-05 loss: 0.0728 (0.0888) time: 2.8428 data: 0.0084 max mem: 33369 +Epoch: [9] [ 680/2639] eta: 1:34:49 lr: 3.945247503427298e-05 loss: 0.0751 (0.0890) time: 2.8710 data: 0.0089 max mem: 33369 +Epoch: [9] [ 690/2639] eta: 1:34:18 lr: 3.944809831521478e-05 loss: 0.0809 (0.0888) time: 2.8693 data: 0.0086 max mem: 33369 +Epoch: [9] [ 700/2639] eta: 1:33:49 lr: 3.944372154220129e-05 loss: 0.0838 (0.0888) time: 2.8670 data: 0.0082 max mem: 33369 +Epoch: [9] [ 710/2639] eta: 1:33:18 lr: 3.943934471522517e-05 loss: 0.0875 (0.0888) time: 2.8622 data: 0.0085 max mem: 33369 +Epoch: [9] [ 720/2639] eta: 1:32:49 lr: 3.943496783427912e-05 loss: 0.0741 (0.0885) time: 2.8763 data: 0.0086 max mem: 33369 +Epoch: [9] [ 730/2639] eta: 1:32:21 lr: 3.9430590899355806e-05 loss: 0.0672 (0.0884) time: 2.9326 data: 0.0083 max mem: 33369 +Epoch: [9] [ 740/2639] eta: 1:31:52 lr: 3.942621391044792e-05 loss: 0.0801 (0.0885) time: 2.9297 data: 0.0084 max mem: 33369 +Epoch: [9] [ 750/2639] eta: 1:31:21 lr: 3.9421836867548113e-05 loss: 0.0860 (0.0885) time: 2.8549 data: 0.0083 max mem: 33369 +Epoch: [9] [ 760/2639] eta: 1:30:51 lr: 3.941745977064908e-05 loss: 0.0856 (0.0888) time: 2.8342 data: 0.0078 max mem: 33369 +Epoch: [9] [ 770/2639] eta: 1:30:22 lr: 3.941308261974349e-05 loss: 0.0828 (0.0889) time: 2.8937 data: 0.0079 max mem: 33369 +Epoch: [9] [ 780/2639] eta: 1:29:54 lr: 3.940870541482399e-05 loss: 0.0796 (0.0888) time: 2.9311 data: 0.0086 max mem: 33369 +Epoch: [9] [ 790/2639] eta: 1:29:27 lr: 3.9404328155883276e-05 loss: 0.0862 (0.0893) time: 2.9481 data: 0.0086 max mem: 33369 +Epoch: [9] [ 800/2639] eta: 1:28:58 lr: 3.9399950842914e-05 loss: 0.0904 (0.0893) time: 2.9409 data: 0.0080 max mem: 33369 +Epoch: [9] [ 810/2639] eta: 1:28:29 lr: 3.939557347590882e-05 loss: 0.0751 (0.0893) time: 2.9197 data: 0.0081 max mem: 33369 +Epoch: [9] [ 820/2639] eta: 1:28:00 lr: 3.939119605486041e-05 loss: 0.0703 (0.0890) time: 2.8916 data: 0.0086 max mem: 33369 +Epoch: [9] [ 830/2639] eta: 1:27:30 lr: 3.938681857976142e-05 loss: 0.0762 (0.0891) time: 2.8844 data: 0.0084 max mem: 33369 +Epoch: [9] [ 840/2639] eta: 1:27:01 lr: 3.9382441050604516e-05 loss: 0.0896 (0.0892) time: 2.8853 data: 0.0081 max mem: 33369 +Epoch: [9] [ 850/2639] eta: 1:26:32 lr: 3.9378063467382345e-05 loss: 0.0781 (0.0891) time: 2.8835 data: 0.0084 max mem: 33369 +Epoch: [9] [ 860/2639] eta: 1:26:02 lr: 3.937368583008757e-05 loss: 0.0751 (0.0893) time: 2.8931 data: 0.0085 max mem: 33369 +Epoch: [9] [ 870/2639] eta: 1:25:33 lr: 3.936930813871283e-05 loss: 0.0898 (0.0896) time: 2.8794 data: 0.0086 max mem: 33369 +Epoch: [9] [ 880/2639] eta: 1:25:04 lr: 3.936493039325079e-05 loss: 0.0867 (0.0898) time: 2.9031 data: 0.0086 max mem: 33369 +Epoch: [9] [ 890/2639] eta: 1:24:34 lr: 3.9360552593694086e-05 loss: 0.0873 (0.0898) time: 2.8952 data: 0.0086 max mem: 33369 +Epoch: [9] [ 900/2639] eta: 1:24:05 lr: 3.9356174740035376e-05 loss: 0.0873 (0.0898) time: 2.8730 data: 0.0082 max mem: 33369 +Epoch: [9] [ 910/2639] eta: 1:23:36 lr: 3.935179683226729e-05 loss: 0.0792 (0.0898) time: 2.9068 data: 0.0077 max mem: 33369 +Epoch: [9] [ 920/2639] eta: 1:23:08 lr: 3.9347418870382486e-05 loss: 0.0858 (0.0898) time: 2.9216 data: 0.0076 max mem: 33369 +Epoch: [9] [ 930/2639] eta: 1:22:39 lr: 3.9343040854373594e-05 loss: 0.0853 (0.0897) time: 2.9129 data: 0.0079 max mem: 33369 +Epoch: [9] [ 940/2639] eta: 1:22:09 lr: 3.933866278423326e-05 loss: 0.0752 (0.0897) time: 2.8838 data: 0.0083 max mem: 33369 +Epoch: [9] [ 950/2639] eta: 1:21:40 lr: 3.933428465995411e-05 loss: 0.0752 (0.0895) time: 2.8669 data: 0.0086 max mem: 33369 +Epoch: [9] [ 960/2639] eta: 1:21:10 lr: 3.932990648152879e-05 loss: 0.0822 (0.0896) time: 2.8682 data: 0.0083 max mem: 33369 +Epoch: [9] [ 970/2639] eta: 1:20:41 lr: 3.9325528248949934e-05 loss: 0.0794 (0.0895) time: 2.8993 data: 0.0081 max mem: 33369 +Epoch: [9] [ 980/2639] eta: 1:20:12 lr: 3.9321149962210156e-05 loss: 0.0785 (0.0895) time: 2.9161 data: 0.0082 max mem: 33369 +Epoch: [9] [ 990/2639] eta: 1:19:43 lr: 3.9316771621302106e-05 loss: 0.0746 (0.0894) time: 2.8998 data: 0.0079 max mem: 33369 +Epoch: [9] [1000/2639] eta: 1:19:13 lr: 3.93123932262184e-05 loss: 0.0736 (0.0894) time: 2.8675 data: 0.0083 max mem: 33369 +Epoch: [9] [1010/2639] eta: 1:18:44 lr: 3.9308014776951666e-05 loss: 0.0788 (0.0895) time: 2.8696 data: 0.0083 max mem: 33369 +Epoch: [9] [1020/2639] eta: 1:18:14 lr: 3.9303636273494524e-05 loss: 0.0788 (0.0894) time: 2.8640 data: 0.0080 max mem: 33369 +Epoch: [9] [1030/2639] eta: 1:17:44 lr: 3.92992577158396e-05 loss: 0.0741 (0.0894) time: 2.8369 data: 0.0081 max mem: 33369 +Epoch: [9] [1040/2639] eta: 1:17:16 lr: 3.9294879103979506e-05 loss: 0.0842 (0.0895) time: 2.8875 data: 0.0083 max mem: 33369 +Epoch: [9] [1050/2639] eta: 1:16:47 lr: 3.929050043790687e-05 loss: 0.0886 (0.0897) time: 2.9230 data: 0.0085 max mem: 33369 +Epoch: [9] [1060/2639] eta: 1:16:17 lr: 3.92861217176143e-05 loss: 0.0670 (0.0896) time: 2.8796 data: 0.0083 max mem: 33369 +Epoch: [9] [1070/2639] eta: 1:15:48 lr: 3.928174294309443e-05 loss: 0.0752 (0.0897) time: 2.8768 data: 0.0085 max mem: 33369 +Epoch: [9] [1080/2639] eta: 1:15:19 lr: 3.9277364114339825e-05 loss: 0.0759 (0.0896) time: 2.8976 data: 0.0085 max mem: 33369 +Epoch: [9] [1090/2639] eta: 1:14:51 lr: 3.9272985231343143e-05 loss: 0.0655 (0.0895) time: 2.9248 data: 0.0084 max mem: 33369 +Epoch: [9] [1100/2639] eta: 1:14:22 lr: 3.926860629409697e-05 loss: 0.0737 (0.0897) time: 2.9187 data: 0.0083 max mem: 33369 +Epoch: [9] [1110/2639] eta: 1:13:53 lr: 3.926422730259392e-05 loss: 0.0764 (0.0896) time: 2.9068 data: 0.0087 max mem: 33369 +Epoch: [9] [1120/2639] eta: 1:13:24 lr: 3.925984825682658e-05 loss: 0.0764 (0.0898) time: 2.9022 data: 0.0090 max mem: 33369 +Epoch: [9] [1130/2639] eta: 1:12:55 lr: 3.925546915678757e-05 loss: 0.0914 (0.0898) time: 2.8788 data: 0.0086 max mem: 33369 +Epoch: [9] [1140/2639] eta: 1:12:27 lr: 3.9251090002469494e-05 loss: 0.0678 (0.0897) time: 2.9322 data: 0.0082 max mem: 33369 +Epoch: [9] [1150/2639] eta: 1:11:58 lr: 3.924671079386494e-05 loss: 0.0714 (0.0896) time: 2.9282 data: 0.0089 max mem: 33369 +Epoch: [9] [1160/2639] eta: 1:11:29 lr: 3.92423315309665e-05 loss: 0.0662 (0.0896) time: 2.8996 data: 0.0090 max mem: 33369 +Epoch: [9] [1170/2639] eta: 1:10:59 lr: 3.923795221376677e-05 loss: 0.0874 (0.0898) time: 2.8826 data: 0.0086 max mem: 33369 +Epoch: [9] [1180/2639] eta: 1:10:30 lr: 3.923357284225836e-05 loss: 0.0951 (0.0899) time: 2.8617 data: 0.0085 max mem: 33369 +Epoch: [9] [1190/2639] eta: 1:10:01 lr: 3.922919341643384e-05 loss: 0.0945 (0.0900) time: 2.8870 data: 0.0080 max mem: 33369 +Epoch: [9] [1200/2639] eta: 1:09:32 lr: 3.922481393628581e-05 loss: 0.0837 (0.0900) time: 2.9081 data: 0.0083 max mem: 33369 +Epoch: [9] [1210/2639] eta: 1:09:03 lr: 3.922043440180685e-05 loss: 0.0840 (0.0900) time: 2.9022 data: 0.0085 max mem: 33369 +Epoch: [9] [1220/2639] eta: 1:08:34 lr: 3.9216054812989554e-05 loss: 0.0771 (0.0900) time: 2.9065 data: 0.0080 max mem: 33369 +Epoch: [9] [1230/2639] eta: 1:08:05 lr: 3.9211675169826495e-05 loss: 0.0771 (0.0900) time: 2.9140 data: 0.0081 max mem: 33369 +Epoch: [9] [1240/2639] eta: 1:07:36 lr: 3.920729547231026e-05 loss: 0.0757 (0.0901) time: 2.8901 data: 0.0083 max mem: 33369 +Epoch: [9] [1250/2639] eta: 1:07:07 lr: 3.920291572043342e-05 loss: 0.0716 (0.0900) time: 2.8660 data: 0.0083 max mem: 33369 +Epoch: [9] [1260/2639] eta: 1:06:37 lr: 3.919853591418857e-05 loss: 0.0725 (0.0900) time: 2.8433 data: 0.0082 max mem: 33369 +Epoch: [9] [1270/2639] eta: 1:06:07 lr: 3.9194156053568266e-05 loss: 0.0798 (0.0899) time: 2.8188 data: 0.0085 max mem: 33369 +Epoch: [9] [1280/2639] eta: 1:05:38 lr: 3.918977613856509e-05 loss: 0.0796 (0.0901) time: 2.8465 data: 0.0094 max mem: 33369 +Epoch: [9] [1290/2639] eta: 1:05:09 lr: 3.918539616917161e-05 loss: 0.0796 (0.0900) time: 2.8839 data: 0.0091 max mem: 33369 +Epoch: [9] [1300/2639] eta: 1:04:39 lr: 3.91810161453804e-05 loss: 0.0822 (0.0900) time: 2.8807 data: 0.0088 max mem: 33369 +Epoch: [9] [1310/2639] eta: 1:04:10 lr: 3.917663606718403e-05 loss: 0.0711 (0.0900) time: 2.8685 data: 0.0086 max mem: 33369 +Epoch: [9] [1320/2639] eta: 1:03:41 lr: 3.917225593457506e-05 loss: 0.0786 (0.0902) time: 2.8655 data: 0.0083 max mem: 33369 +Epoch: [9] [1330/2639] eta: 1:03:11 lr: 3.916787574754605e-05 loss: 0.0833 (0.0903) time: 2.8620 data: 0.0080 max mem: 33369 +Epoch: [9] [1340/2639] eta: 1:02:43 lr: 3.916349550608957e-05 loss: 0.0904 (0.0904) time: 2.8968 data: 0.0077 max mem: 33369 +Epoch: [9] [1350/2639] eta: 1:02:13 lr: 3.915911521019817e-05 loss: 0.0995 (0.0906) time: 2.8958 data: 0.0079 max mem: 33369 +Epoch: [9] [1360/2639] eta: 1:01:45 lr: 3.915473485986442e-05 loss: 0.0852 (0.0906) time: 2.8823 data: 0.0082 max mem: 33369 +Epoch: [9] [1370/2639] eta: 1:01:16 lr: 3.915035445508086e-05 loss: 0.0794 (0.0906) time: 2.9093 data: 0.0081 max mem: 33369 +Epoch: [9] [1380/2639] eta: 1:00:47 lr: 3.9145973995840055e-05 loss: 0.0851 (0.0906) time: 2.8999 data: 0.0079 max mem: 33369 +Epoch: [9] [1390/2639] eta: 1:00:18 lr: 3.914159348213456e-05 loss: 0.0931 (0.0907) time: 2.9021 data: 0.0080 max mem: 33369 +Epoch: [9] [1400/2639] eta: 0:59:49 lr: 3.913721291395692e-05 loss: 0.0863 (0.0907) time: 2.8878 data: 0.0083 max mem: 33369 +Epoch: [9] [1410/2639] eta: 0:59:20 lr: 3.913283229129968e-05 loss: 0.0745 (0.0907) time: 2.9078 data: 0.0085 max mem: 33369 +Epoch: [9] [1420/2639] eta: 0:58:52 lr: 3.912845161415539e-05 loss: 0.0801 (0.0908) time: 2.9603 data: 0.0085 max mem: 33369 +Epoch: [9] [1430/2639] eta: 0:58:23 lr: 3.91240708825166e-05 loss: 0.0785 (0.0907) time: 2.9520 data: 0.0088 max mem: 33369 +Epoch: [9] [1440/2639] eta: 0:57:54 lr: 3.911969009637584e-05 loss: 0.0798 (0.0908) time: 2.9095 data: 0.0088 max mem: 33369 +Epoch: [9] [1450/2639] eta: 0:57:25 lr: 3.9115309255725656e-05 loss: 0.0874 (0.0908) time: 2.9143 data: 0.0080 max mem: 33369 +Epoch: [9] [1460/2639] eta: 0:56:56 lr: 3.9110928360558576e-05 loss: 0.0874 (0.0910) time: 2.8920 data: 0.0078 max mem: 33369 +Epoch: [9] [1470/2639] eta: 0:56:27 lr: 3.9106547410867166e-05 loss: 0.1022 (0.0911) time: 2.8681 data: 0.0082 max mem: 33369 +Epoch: [9] [1480/2639] eta: 0:55:58 lr: 3.910216640664392e-05 loss: 0.0897 (0.0911) time: 2.8842 data: 0.0083 max mem: 33369 +Epoch: [9] [1490/2639] eta: 0:55:29 lr: 3.909778534788141e-05 loss: 0.0861 (0.0911) time: 2.8831 data: 0.0081 max mem: 33369 +Epoch: [9] [1500/2639] eta: 0:55:01 lr: 3.909340423457214e-05 loss: 0.0951 (0.0914) time: 2.9430 data: 0.0081 max mem: 33369 +Epoch: [9] [1510/2639] eta: 0:54:31 lr: 3.908902306670865e-05 loss: 0.0847 (0.0914) time: 2.9270 data: 0.0083 max mem: 33369 +Epoch: [9] [1520/2639] eta: 0:54:02 lr: 3.908464184428345e-05 loss: 0.0954 (0.0914) time: 2.8490 data: 0.0081 max mem: 33369 +Epoch: [9] [1530/2639] eta: 0:53:33 lr: 3.90802605672891e-05 loss: 0.1030 (0.0915) time: 2.8897 data: 0.0080 max mem: 33369 +Epoch: [9] [1540/2639] eta: 0:53:04 lr: 3.9075879235718074e-05 loss: 0.0877 (0.0915) time: 2.9260 data: 0.0079 max mem: 33369 +Epoch: [9] [1550/2639] eta: 0:52:35 lr: 3.907149784956293e-05 loss: 0.0916 (0.0916) time: 2.8623 data: 0.0079 max mem: 33369 +Epoch: [9] [1560/2639] eta: 0:52:06 lr: 3.9067116408816184e-05 loss: 0.0897 (0.0917) time: 2.8910 data: 0.0081 max mem: 33369 +Epoch: [9] [1570/2639] eta: 0:51:37 lr: 3.9062734913470337e-05 loss: 0.0821 (0.0916) time: 2.9112 data: 0.0082 max mem: 33369 +Epoch: [9] [1580/2639] eta: 0:51:08 lr: 3.9058353363517915e-05 loss: 0.0821 (0.0916) time: 2.8613 data: 0.0079 max mem: 33369 +Epoch: [9] [1590/2639] eta: 0:50:39 lr: 3.905397175895142e-05 loss: 0.0754 (0.0915) time: 2.8932 data: 0.0079 max mem: 33369 +Epoch: [9] [1600/2639] eta: 0:50:10 lr: 3.904959009976338e-05 loss: 0.0787 (0.0916) time: 2.9140 data: 0.0077 max mem: 33369 +Epoch: [9] [1610/2639] eta: 0:49:41 lr: 3.9045208385946285e-05 loss: 0.0711 (0.0915) time: 2.9130 data: 0.0079 max mem: 33369 +Epoch: [9] [1620/2639] eta: 0:49:12 lr: 3.9040826617492655e-05 loss: 0.0733 (0.0917) time: 2.9098 data: 0.0078 max mem: 33369 +Epoch: [9] [1630/2639] eta: 0:48:43 lr: 3.903644479439499e-05 loss: 0.0831 (0.0915) time: 2.8913 data: 0.0075 max mem: 33369 +Epoch: [9] [1640/2639] eta: 0:48:14 lr: 3.903206291664579e-05 loss: 0.0712 (0.0915) time: 2.8847 data: 0.0075 max mem: 33369 +Epoch: [9] [1650/2639] eta: 0:47:45 lr: 3.902768098423758e-05 loss: 0.0966 (0.0917) time: 2.8889 data: 0.0079 max mem: 33369 +Epoch: [9] [1660/2639] eta: 0:47:16 lr: 3.902329899716282e-05 loss: 0.0966 (0.0917) time: 2.8820 data: 0.0083 max mem: 33369 +Epoch: [9] [1670/2639] eta: 0:46:47 lr: 3.901891695541403e-05 loss: 0.0877 (0.0917) time: 2.8651 data: 0.0081 max mem: 33369 +Epoch: [9] [1680/2639] eta: 0:46:18 lr: 3.90145348589837e-05 loss: 0.0807 (0.0917) time: 2.8926 data: 0.0081 max mem: 33369 +Epoch: [9] [1690/2639] eta: 0:45:49 lr: 3.9010152707864326e-05 loss: 0.0768 (0.0917) time: 2.8922 data: 0.0081 max mem: 33369 +Epoch: [9] [1700/2639] eta: 0:45:20 lr: 3.9005770502048405e-05 loss: 0.0840 (0.0917) time: 2.8892 data: 0.0077 max mem: 33369 +Epoch: [9] [1710/2639] eta: 0:44:51 lr: 3.900138824152841e-05 loss: 0.0816 (0.0916) time: 2.9117 data: 0.0075 max mem: 33369 +Epoch: [9] [1720/2639] eta: 0:44:22 lr: 3.899700592629685e-05 loss: 0.0703 (0.0916) time: 2.9302 data: 0.0075 max mem: 33369 +Epoch: [9] [1730/2639] eta: 0:43:54 lr: 3.899262355634619e-05 loss: 0.0912 (0.0917) time: 2.9378 data: 0.0074 max mem: 33369 +Epoch: [9] [1740/2639] eta: 0:43:25 lr: 3.8988241131668926e-05 loss: 0.0895 (0.0917) time: 2.9134 data: 0.0073 max mem: 33369 +Epoch: [9] [1750/2639] eta: 0:42:56 lr: 3.898385865225753e-05 loss: 0.0741 (0.0917) time: 2.9043 data: 0.0076 max mem: 33369 +Epoch: [9] [1760/2639] eta: 0:42:27 lr: 3.897947611810449e-05 loss: 0.0694 (0.0915) time: 2.8901 data: 0.0076 max mem: 33369 +Epoch: [9] [1770/2639] eta: 0:41:57 lr: 3.897509352920228e-05 loss: 0.0687 (0.0915) time: 2.8793 data: 0.0075 max mem: 33369 +Epoch: [9] [1780/2639] eta: 0:41:29 lr: 3.897071088554338e-05 loss: 0.0731 (0.0915) time: 2.8937 data: 0.0077 max mem: 33369 +Epoch: [9] [1790/2639] eta: 0:40:59 lr: 3.896632818712025e-05 loss: 0.0727 (0.0915) time: 2.8904 data: 0.0077 max mem: 33369 +Epoch: [9] [1800/2639] eta: 0:40:31 lr: 3.896194543392537e-05 loss: 0.0861 (0.0916) time: 2.9026 data: 0.0078 max mem: 33369 +Epoch: [9] [1810/2639] eta: 0:40:02 lr: 3.895756262595122e-05 loss: 0.0939 (0.0917) time: 2.9117 data: 0.0079 max mem: 33369 +Epoch: [9] [1820/2639] eta: 0:39:33 lr: 3.895317976319026e-05 loss: 0.0886 (0.0917) time: 2.9124 data: 0.0077 max mem: 33369 +Epoch: [9] [1830/2639] eta: 0:39:04 lr: 3.894879684563495e-05 loss: 0.0871 (0.0918) time: 2.9197 data: 0.0078 max mem: 33369 +Epoch: [9] [1840/2639] eta: 0:38:35 lr: 3.894441387327775e-05 loss: 0.0890 (0.0918) time: 2.9170 data: 0.0075 max mem: 33369 +Epoch: [9] [1850/2639] eta: 0:38:06 lr: 3.894003084611114e-05 loss: 0.0802 (0.0918) time: 2.9161 data: 0.0075 max mem: 33369 +Epoch: [9] [1860/2639] eta: 0:37:37 lr: 3.893564776412757e-05 loss: 0.0802 (0.0918) time: 2.8749 data: 0.0080 max mem: 33369 +Epoch: [9] [1870/2639] eta: 0:37:08 lr: 3.893126462731948e-05 loss: 0.0804 (0.0918) time: 2.8616 data: 0.0076 max mem: 33369 +Epoch: [9] [1880/2639] eta: 0:36:39 lr: 3.8926881435679355e-05 loss: 0.0770 (0.0918) time: 2.8622 data: 0.0074 max mem: 33369 +Epoch: [9] [1890/2639] eta: 0:36:10 lr: 3.8922498189199635e-05 loss: 0.0770 (0.0918) time: 2.8717 data: 0.0077 max mem: 33369 +Epoch: [9] [1900/2639] eta: 0:35:41 lr: 3.891811488787277e-05 loss: 0.0879 (0.0919) time: 2.8879 data: 0.0080 max mem: 33369 +Epoch: [9] [1910/2639] eta: 0:35:12 lr: 3.891373153169121e-05 loss: 0.0773 (0.0918) time: 2.9056 data: 0.0078 max mem: 33369 +Epoch: [9] [1920/2639] eta: 0:34:43 lr: 3.890934812064741e-05 loss: 0.0710 (0.0917) time: 2.8849 data: 0.0075 max mem: 33369 +Epoch: [9] [1930/2639] eta: 0:34:14 lr: 3.890496465473381e-05 loss: 0.0746 (0.0917) time: 2.8612 data: 0.0078 max mem: 33369 +Epoch: [9] [1940/2639] eta: 0:33:45 lr: 3.890058113394285e-05 loss: 0.0810 (0.0917) time: 2.8971 data: 0.0079 max mem: 33369 +Epoch: [9] [1950/2639] eta: 0:33:15 lr: 3.889619755826699e-05 loss: 0.0793 (0.0916) time: 2.8800 data: 0.0078 max mem: 33369 +Epoch: [9] [1960/2639] eta: 0:32:47 lr: 3.889181392769865e-05 loss: 0.0893 (0.0917) time: 2.8931 data: 0.0075 max mem: 33369 +Epoch: [9] [1970/2639] eta: 0:32:18 lr: 3.888743024223027e-05 loss: 0.1085 (0.0919) time: 2.9203 data: 0.0074 max mem: 33369 +Epoch: [9] [1980/2639] eta: 0:31:49 lr: 3.8883046501854295e-05 loss: 0.1028 (0.0920) time: 2.9307 data: 0.0076 max mem: 33369 +Epoch: [9] [1990/2639] eta: 0:31:20 lr: 3.887866270656315e-05 loss: 0.0956 (0.0920) time: 2.9507 data: 0.0077 max mem: 33369 +Epoch: [9] [2000/2639] eta: 0:30:51 lr: 3.887427885634928e-05 loss: 0.0955 (0.0920) time: 2.9330 data: 0.0080 max mem: 33369 +Epoch: [9] [2010/2639] eta: 0:30:22 lr: 3.88698949512051e-05 loss: 0.0797 (0.0920) time: 2.9466 data: 0.0082 max mem: 33369 +Epoch: [9] [2020/2639] eta: 0:29:53 lr: 3.886551099112304e-05 loss: 0.0720 (0.0919) time: 2.9202 data: 0.0080 max mem: 33369 +Epoch: [9] [2030/2639] eta: 0:29:25 lr: 3.886112697609554e-05 loss: 0.0728 (0.0919) time: 2.9081 data: 0.0077 max mem: 33369 +Epoch: [9] [2040/2639] eta: 0:28:55 lr: 3.8856742906115e-05 loss: 0.0766 (0.0918) time: 2.9049 data: 0.0077 max mem: 33369 +Epoch: [9] [2050/2639] eta: 0:28:26 lr: 3.8852358781173865e-05 loss: 0.0862 (0.0918) time: 2.8681 data: 0.0078 max mem: 33369 +Epoch: [9] [2060/2639] eta: 0:27:57 lr: 3.884797460126455e-05 loss: 0.0924 (0.0918) time: 2.8753 data: 0.0080 max mem: 33369 +Epoch: [9] [2070/2639] eta: 0:27:28 lr: 3.884359036637946e-05 loss: 0.0823 (0.0919) time: 2.8704 data: 0.0083 max mem: 33369 +Epoch: [9] [2080/2639] eta: 0:26:59 lr: 3.8839206076511025e-05 loss: 0.0823 (0.0918) time: 2.8790 data: 0.0080 max mem: 33369 +Epoch: [9] [2090/2639] eta: 0:26:30 lr: 3.883482173165165e-05 loss: 0.0784 (0.0918) time: 2.9116 data: 0.0078 max mem: 33369 +Epoch: [9] [2100/2639] eta: 0:26:01 lr: 3.883043733179376e-05 loss: 0.0784 (0.0918) time: 2.8672 data: 0.0076 max mem: 33369 +Epoch: [9] [2110/2639] eta: 0:25:32 lr: 3.882605287692974e-05 loss: 0.0705 (0.0918) time: 2.8516 data: 0.0073 max mem: 33369 +Epoch: [9] [2120/2639] eta: 0:25:03 lr: 3.8821668367052025e-05 loss: 0.0696 (0.0918) time: 2.8821 data: 0.0075 max mem: 33369 +Epoch: [9] [2130/2639] eta: 0:24:34 lr: 3.881728380215301e-05 loss: 0.0793 (0.0918) time: 2.9128 data: 0.0075 max mem: 33369 +Epoch: [9] [2140/2639] eta: 0:24:05 lr: 3.8812899182225084e-05 loss: 0.0862 (0.0919) time: 2.9484 data: 0.0077 max mem: 33369 +Epoch: [9] [2150/2639] eta: 0:23:37 lr: 3.880851450726068e-05 loss: 0.0737 (0.0917) time: 2.9328 data: 0.0083 max mem: 33369 +Epoch: [9] [2160/2639] eta: 0:23:08 lr: 3.8804129777252174e-05 loss: 0.0737 (0.0917) time: 2.9009 data: 0.0082 max mem: 33369 +Epoch: [9] [2170/2639] eta: 0:22:39 lr: 3.8799744992191966e-05 loss: 0.0812 (0.0917) time: 2.8851 data: 0.0080 max mem: 33369 +Epoch: [9] [2180/2639] eta: 0:22:10 lr: 3.879536015207247e-05 loss: 0.0845 (0.0917) time: 2.8987 data: 0.0081 max mem: 33369 +Epoch: [9] [2190/2639] eta: 0:21:41 lr: 3.879097525688606e-05 loss: 0.0895 (0.0917) time: 2.9041 data: 0.0078 max mem: 33369 +Epoch: [9] [2200/2639] eta: 0:21:12 lr: 3.878659030662513e-05 loss: 0.0822 (0.0917) time: 2.9065 data: 0.0074 max mem: 33369 +Epoch: [9] [2210/2639] eta: 0:20:43 lr: 3.878220530128208e-05 loss: 0.0819 (0.0917) time: 2.9248 data: 0.0074 max mem: 33369 +Epoch: [9] [2220/2639] eta: 0:20:14 lr: 3.87778202408493e-05 loss: 0.0799 (0.0917) time: 2.9481 data: 0.0075 max mem: 33369 +Epoch: [9] [2230/2639] eta: 0:19:45 lr: 3.8773435125319154e-05 loss: 0.0675 (0.0916) time: 2.9038 data: 0.0076 max mem: 33369 +Epoch: [9] [2240/2639] eta: 0:19:16 lr: 3.8769049954684054e-05 loss: 0.0654 (0.0916) time: 2.8853 data: 0.0083 max mem: 33369 +Epoch: [9] [2250/2639] eta: 0:18:47 lr: 3.876466472893636e-05 loss: 0.0742 (0.0916) time: 2.8860 data: 0.0082 max mem: 33369 +Epoch: [9] [2260/2639] eta: 0:18:18 lr: 3.876027944806847e-05 loss: 0.0686 (0.0915) time: 2.8632 data: 0.0083 max mem: 33369 +Epoch: [9] [2270/2639] eta: 0:17:49 lr: 3.8755894112072735e-05 loss: 0.0723 (0.0915) time: 2.9056 data: 0.0084 max mem: 33369 +Epoch: [9] [2280/2639] eta: 0:17:20 lr: 3.875150872094157e-05 loss: 0.0864 (0.0915) time: 2.9183 data: 0.0080 max mem: 33369 +Epoch: [9] [2290/2639] eta: 0:16:51 lr: 3.874712327466731e-05 loss: 0.0864 (0.0914) time: 2.9329 data: 0.0080 max mem: 33369 +Epoch: [9] [2300/2639] eta: 0:16:22 lr: 3.874273777324234e-05 loss: 0.0742 (0.0914) time: 2.9331 data: 0.0083 max mem: 33369 +Epoch: [9] [2310/2639] eta: 0:15:53 lr: 3.8738352216659044e-05 loss: 0.0823 (0.0914) time: 2.8805 data: 0.0082 max mem: 33369 +Epoch: [9] [2320/2639] eta: 0:15:24 lr: 3.8733966604909785e-05 loss: 0.0821 (0.0913) time: 2.9008 data: 0.0077 max mem: 33369 +Epoch: [9] [2330/2639] eta: 0:14:55 lr: 3.872958093798691e-05 loss: 0.0793 (0.0913) time: 2.9061 data: 0.0078 max mem: 33369 +Epoch: [9] [2340/2639] eta: 0:14:26 lr: 3.8725195215882806e-05 loss: 0.0747 (0.0912) time: 2.8918 data: 0.0079 max mem: 33369 +Epoch: [9] [2350/2639] eta: 0:13:57 lr: 3.872080943858982e-05 loss: 0.0709 (0.0912) time: 2.9225 data: 0.0078 max mem: 33369 +Epoch: [9] [2360/2639] eta: 0:13:28 lr: 3.8716423606100325e-05 loss: 0.0883 (0.0912) time: 2.9001 data: 0.0075 max mem: 33369 +Epoch: [9] [2370/2639] eta: 0:12:59 lr: 3.871203771840665e-05 loss: 0.0883 (0.0912) time: 2.8694 data: 0.0080 max mem: 33369 +Epoch: [9] [2380/2639] eta: 0:12:30 lr: 3.8707651775501186e-05 loss: 0.0728 (0.0913) time: 2.8865 data: 0.0082 max mem: 33369 +Epoch: [9] [2390/2639] eta: 0:12:01 lr: 3.870326577737627e-05 loss: 0.0797 (0.0912) time: 2.8910 data: 0.0079 max mem: 33369 +Epoch: [9] [2400/2639] eta: 0:11:32 lr: 3.8698879724024253e-05 loss: 0.0797 (0.0912) time: 2.8970 data: 0.0078 max mem: 33369 +Epoch: [9] [2410/2639] eta: 0:11:03 lr: 3.8694493615437485e-05 loss: 0.0901 (0.0912) time: 2.9237 data: 0.0079 max mem: 33369 +Epoch: [9] [2420/2639] eta: 0:10:34 lr: 3.869010745160832e-05 loss: 0.0901 (0.0912) time: 2.9496 data: 0.0081 max mem: 33369 +Epoch: [9] [2430/2639] eta: 0:10:05 lr: 3.8685721232529096e-05 loss: 0.0846 (0.0912) time: 2.8933 data: 0.0077 max mem: 33369 +Epoch: [9] [2440/2639] eta: 0:09:36 lr: 3.868133495819215e-05 loss: 0.0846 (0.0912) time: 2.8553 data: 0.0079 max mem: 33369 +Epoch: [9] [2450/2639] eta: 0:09:07 lr: 3.8676948628589845e-05 loss: 0.0775 (0.0912) time: 2.8800 data: 0.0078 max mem: 33369 +Epoch: [9] [2460/2639] eta: 0:08:38 lr: 3.86725622437145e-05 loss: 0.0775 (0.0912) time: 2.8874 data: 0.0074 max mem: 33369 +Epoch: [9] [2470/2639] eta: 0:08:09 lr: 3.866817580355847e-05 loss: 0.0918 (0.0912) time: 2.9286 data: 0.0074 max mem: 33369 +Epoch: [9] [2480/2639] eta: 0:07:40 lr: 3.866378930811407e-05 loss: 0.0883 (0.0913) time: 2.9234 data: 0.0074 max mem: 33369 +Epoch: [9] [2490/2639] eta: 0:07:11 lr: 3.865940275737366e-05 loss: 0.0883 (0.0913) time: 2.9153 data: 0.0075 max mem: 33369 +Epoch: [9] [2500/2639] eta: 0:06:42 lr: 3.865501615132954e-05 loss: 0.0744 (0.0913) time: 2.9234 data: 0.0075 max mem: 33369 +Epoch: [9] [2510/2639] eta: 0:06:13 lr: 3.865062948997407e-05 loss: 0.0716 (0.0913) time: 2.8731 data: 0.0072 max mem: 33369 +Epoch: [9] [2520/2639] eta: 0:05:44 lr: 3.8646242773299553e-05 loss: 0.0743 (0.0912) time: 2.8824 data: 0.0073 max mem: 33369 +Epoch: [9] [2530/2639] eta: 0:05:15 lr: 3.8641856001298325e-05 loss: 0.0742 (0.0912) time: 2.9063 data: 0.0073 max mem: 33369 +Epoch: [9] [2540/2639] eta: 0:04:46 lr: 3.863746917396271e-05 loss: 0.0835 (0.0913) time: 2.8907 data: 0.0075 max mem: 33369 +Epoch: [9] [2550/2639] eta: 0:04:17 lr: 3.863308229128502e-05 loss: 0.0945 (0.0914) time: 2.9390 data: 0.0077 max mem: 33370 +Epoch: [9] [2560/2639] eta: 0:03:49 lr: 3.8628695353257596e-05 loss: 0.0978 (0.0914) time: 2.9615 data: 0.0077 max mem: 33370 +Epoch: [9] [2570/2639] eta: 0:03:20 lr: 3.862430835987273e-05 loss: 0.1003 (0.0914) time: 2.8823 data: 0.0074 max mem: 33370 +Epoch: [9] [2580/2639] eta: 0:02:51 lr: 3.861992131112275e-05 loss: 0.1003 (0.0915) time: 2.8819 data: 0.0075 max mem: 33370 +Epoch: [9] [2590/2639] eta: 0:02:22 lr: 3.861553420699997e-05 loss: 0.0784 (0.0914) time: 2.9310 data: 0.0080 max mem: 33370 +Epoch: [9] [2600/2639] eta: 0:01:53 lr: 3.861114704749669e-05 loss: 0.0783 (0.0914) time: 2.9246 data: 0.0077 max mem: 33370 +Epoch: [9] [2610/2639] eta: 0:01:24 lr: 3.860675983260523e-05 loss: 0.0870 (0.0915) time: 2.9398 data: 0.0075 max mem: 33370 +Epoch: [9] [2620/2639] eta: 0:00:55 lr: 3.86023725623179e-05 loss: 0.0953 (0.0916) time: 2.9224 data: 0.0080 max mem: 33370 +Epoch: [9] [2630/2639] eta: 0:00:26 lr: 3.8597985236626986e-05 loss: 0.0833 (0.0915) time: 2.8863 data: 0.0077 max mem: 33370 +Epoch: [9] Total time: 2:07:31 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 2:38:51 time: 3.7044 data: 3.6010 max mem: 33370 +Test: [ 100/2573] eta: 0:04:40 time: 0.0777 data: 0.0014 max mem: 33370 +Test: [ 200/2573] eta: 0:03:50 time: 0.0799 data: 0.0014 max mem: 33370 +Test: [ 300/2573] eta: 0:03:27 time: 0.0818 data: 0.0013 max mem: 33370 +Test: [ 400/2573] eta: 0:03:12 time: 0.0825 data: 0.0015 max mem: 33370 +Test: [ 500/2573] eta: 0:02:59 time: 0.0811 data: 0.0014 max mem: 33370 +Test: [ 600/2573] eta: 0:02:49 time: 0.0817 data: 0.0014 max mem: 33370 +Test: [ 700/2573] eta: 0:02:40 time: 0.0800 data: 0.0014 max mem: 33370 +Test: [ 800/2573] eta: 0:02:30 time: 0.0836 data: 0.0014 max mem: 33370 +Test: [ 900/2573] eta: 0:02:21 time: 0.0795 data: 0.0015 max mem: 33370 +Test: [1000/2573] eta: 0:02:12 time: 0.0798 data: 0.0014 max mem: 33370 +Test: [1100/2573] eta: 0:02:03 time: 0.0814 data: 0.0016 max mem: 33370 +Test: [1200/2573] eta: 0:01:54 time: 0.0799 data: 0.0012 max mem: 33370 +Test: [1300/2573] eta: 0:01:46 time: 0.0805 data: 0.0015 max mem: 33370 +Test: [1400/2573] eta: 0:01:37 time: 0.0792 data: 0.0014 max mem: 33370 +Test: [1500/2573] eta: 0:01:29 time: 0.0798 data: 0.0014 max mem: 33370 +Test: [1600/2573] eta: 0:01:20 time: 0.0835 data: 0.0014 max mem: 33370 +Test: [1700/2573] eta: 0:01:12 time: 0.0785 data: 0.0015 max mem: 33370 +Test: [1800/2573] eta: 0:01:03 time: 0.0814 data: 0.0014 max mem: 33370 +Test: [1900/2573] eta: 0:00:55 time: 0.0795 data: 0.0015 max mem: 33370 +Test: [2000/2573] eta: 0:00:47 time: 0.0802 data: 0.0015 max mem: 33370 +Test: [2100/2573] eta: 0:00:38 time: 0.0820 data: 0.0014 max mem: 33370 +Test: [2200/2573] eta: 0:00:30 time: 0.0826 data: 0.0014 max mem: 33370 +Test: [2300/2573] eta: 0:00:22 time: 0.0822 data: 0.0015 max mem: 33370 +Test: [2400/2573] eta: 0:00:14 time: 0.0778 data: 0.0014 max mem: 33370 +Test: [2500/2573] eta: 0:00:05 time: 0.0809 data: 0.0014 max mem: 33370 +Test: Total time: 0:03:31 +Final results: +Mean IoU is 59.98 + + precision@0.5 = 67.46 + precision@0.6 = 61.11 + precision@0.7 = 52.78 + precision@0.8 = 40.48 + precision@0.9 = 18.18 + overall IoU = 58.23 + +Average object IoU 59.978333808599196 +Overall IoU 58.23492431640625 +Better epoch: 9 + +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [10] [ 0/2639] eta: 3:51:37 lr: 3.8594036596128766e-05 loss: 0.1141 (0.1141) time: 5.2663 data: 2.2655 max mem: 33370 +Epoch: [10] [ 10/2639] eta: 2:19:16 lr: 3.8589649165149864e-05 loss: 0.0850 (0.0972) time: 3.1787 data: 0.2127 max mem: 33370 +Epoch: [10] [ 20/2639] eta: 2:14:26 lr: 3.858526167874506e-05 loss: 0.0739 (0.0938) time: 2.9706 data: 0.0073 max mem: 33370 +Epoch: [10] [ 30/2639] eta: 2:10:52 lr: 3.858087413690667e-05 loss: 0.0812 (0.0883) time: 2.9171 data: 0.0076 max mem: 33370 +Epoch: [10] [ 40/2639] eta: 2:08:51 lr: 3.8576486539626965e-05 loss: 0.0812 (0.0880) time: 2.8640 data: 0.0083 max mem: 33370 +Epoch: [10] [ 50/2639] eta: 2:07:28 lr: 3.8572098886898245e-05 loss: 0.0810 (0.0868) time: 2.8682 data: 0.0083 max mem: 33370 +Epoch: [10] [ 60/2639] eta: 2:06:03 lr: 3.85677111787128e-05 loss: 0.0743 (0.0853) time: 2.8465 data: 0.0082 max mem: 33370 +Epoch: [10] [ 70/2639] eta: 2:05:07 lr: 3.856332341506292e-05 loss: 0.0799 (0.0869) time: 2.8410 data: 0.0082 max mem: 33370 +Epoch: [10] [ 80/2639] eta: 2:04:23 lr: 3.85589355959409e-05 loss: 0.0799 (0.0861) time: 2.8671 data: 0.0080 max mem: 33370 +Epoch: [10] [ 90/2639] eta: 2:03:47 lr: 3.855454772133902e-05 loss: 0.0657 (0.0832) time: 2.8835 data: 0.0080 max mem: 33370 +Epoch: [10] [ 100/2639] eta: 2:03:13 lr: 3.855015979124954e-05 loss: 0.0576 (0.0823) time: 2.8935 data: 0.0078 max mem: 33370 +Epoch: [10] [ 110/2639] eta: 2:02:46 lr: 3.854577180566478e-05 loss: 0.0652 (0.0829) time: 2.9072 data: 0.0080 max mem: 33370 +Epoch: [10] [ 120/2639] eta: 2:02:14 lr: 3.8541383764577e-05 loss: 0.0680 (0.0820) time: 2.9118 data: 0.0078 max mem: 33370 +Epoch: [10] [ 130/2639] eta: 2:01:41 lr: 3.853699566797846e-05 loss: 0.0703 (0.0820) time: 2.8967 data: 0.0075 max mem: 33370 +Epoch: [10] [ 140/2639] eta: 2:01:17 lr: 3.853260751586146e-05 loss: 0.0720 (0.0823) time: 2.9135 data: 0.0076 max mem: 33370 +Epoch: [10] [ 150/2639] eta: 2:00:45 lr: 3.8528219308218254e-05 loss: 0.0692 (0.0838) time: 2.9165 data: 0.0079 max mem: 33370 +Epoch: [10] [ 160/2639] eta: 2:00:12 lr: 3.852383104504113e-05 loss: 0.0746 (0.0837) time: 2.8917 data: 0.0085 max mem: 33370 +Epoch: [10] [ 170/2639] eta: 1:59:40 lr: 3.851944272632235e-05 loss: 0.0746 (0.0839) time: 2.8873 data: 0.0086 max mem: 33370 +Epoch: [10] [ 180/2639] eta: 1:59:15 lr: 3.851505435205416e-05 loss: 0.0726 (0.0835) time: 2.9121 data: 0.0083 max mem: 33370 +Epoch: [10] [ 190/2639] eta: 1:58:52 lr: 3.851066592222885e-05 loss: 0.0677 (0.0840) time: 2.9479 data: 0.0083 max mem: 33370 +Epoch: [10] [ 200/2639] eta: 1:58:13 lr: 3.850627743683868e-05 loss: 0.0804 (0.0848) time: 2.8937 data: 0.0084 max mem: 33370 +Epoch: [10] [ 210/2639] eta: 1:57:43 lr: 3.8501888895875895e-05 loss: 0.0922 (0.0861) time: 2.8663 data: 0.0081 max mem: 33370 +Epoch: [10] [ 220/2639] eta: 1:57:14 lr: 3.849750029933276e-05 loss: 0.0884 (0.0867) time: 2.9038 data: 0.0081 max mem: 33370 +Epoch: [10] [ 230/2639] eta: 1:56:43 lr: 3.849311164720153e-05 loss: 0.0720 (0.0867) time: 2.8996 data: 0.0081 max mem: 33370 +Epoch: [10] [ 240/2639] eta: 1:56:16 lr: 3.848872293947447e-05 loss: 0.0753 (0.0868) time: 2.9133 data: 0.0080 max mem: 33370 +Epoch: [10] [ 250/2639] eta: 1:55:46 lr: 3.848433417614382e-05 loss: 0.0716 (0.0865) time: 2.9140 data: 0.0081 max mem: 33370 +Epoch: [10] [ 260/2639] eta: 1:55:19 lr: 3.847994535720183e-05 loss: 0.0663 (0.0863) time: 2.9145 data: 0.0081 max mem: 33370 +Epoch: [10] [ 270/2639] eta: 1:54:53 lr: 3.847555648264075e-05 loss: 0.0677 (0.0859) time: 2.9368 data: 0.0080 max mem: 33370 +Epoch: [10] [ 280/2639] eta: 1:54:24 lr: 3.847116755245283e-05 loss: 0.0697 (0.0859) time: 2.9243 data: 0.0080 max mem: 33370 +Epoch: [10] [ 290/2639] eta: 1:53:54 lr: 3.846677856663031e-05 loss: 0.0799 (0.0856) time: 2.9030 data: 0.0081 max mem: 33370 +Epoch: [10] [ 300/2639] eta: 1:53:19 lr: 3.8462389525165424e-05 loss: 0.0799 (0.0858) time: 2.8650 data: 0.0081 max mem: 33370 +Epoch: [10] [ 310/2639] eta: 1:52:44 lr: 3.8458000428050414e-05 loss: 0.0798 (0.0855) time: 2.8335 data: 0.0082 max mem: 33370 +Epoch: [10] [ 320/2639] eta: 1:52:08 lr: 3.845361127527753e-05 loss: 0.0680 (0.0856) time: 2.8209 data: 0.0085 max mem: 33370 +Epoch: [10] [ 330/2639] eta: 1:51:38 lr: 3.844922206683901e-05 loss: 0.0656 (0.0853) time: 2.8420 data: 0.0081 max mem: 33370 +Epoch: [10] [ 340/2639] eta: 1:51:06 lr: 3.8444832802727055e-05 loss: 0.0744 (0.0854) time: 2.8729 data: 0.0078 max mem: 33370 +Epoch: [10] [ 350/2639] eta: 1:50:37 lr: 3.844044348293393e-05 loss: 0.0739 (0.0850) time: 2.8803 data: 0.0082 max mem: 33370 +Epoch: [10] [ 360/2639] eta: 1:50:11 lr: 3.843605410745184e-05 loss: 0.0716 (0.0848) time: 2.9185 data: 0.0081 max mem: 33370 +Epoch: [10] [ 370/2639] eta: 1:49:41 lr: 3.843166467627303e-05 loss: 0.0764 (0.0856) time: 2.9195 data: 0.0079 max mem: 33370 +Epoch: [10] [ 380/2639] eta: 1:49:10 lr: 3.8427275189389725e-05 loss: 0.0819 (0.0855) time: 2.8799 data: 0.0082 max mem: 33370 +Epoch: [10] [ 390/2639] eta: 1:48:42 lr: 3.842288564679413e-05 loss: 0.0813 (0.0855) time: 2.8940 data: 0.0084 max mem: 33370 +Epoch: [10] [ 400/2639] eta: 1:48:16 lr: 3.8418496048478474e-05 loss: 0.0681 (0.0853) time: 2.9359 data: 0.0083 max mem: 33370 +Epoch: [10] [ 410/2639] eta: 1:47:45 lr: 3.841410639443499e-05 loss: 0.0740 (0.0851) time: 2.9034 data: 0.0080 max mem: 33370 +Epoch: [10] [ 420/2639] eta: 1:47:15 lr: 3.840971668465588e-05 loss: 0.0845 (0.0854) time: 2.8721 data: 0.0077 max mem: 33370 +Epoch: [10] [ 430/2639] eta: 1:46:44 lr: 3.840532691913336e-05 loss: 0.0778 (0.0850) time: 2.8721 data: 0.0080 max mem: 33370 +Epoch: [10] [ 440/2639] eta: 1:46:16 lr: 3.840093709785964e-05 loss: 0.0686 (0.0848) time: 2.8864 data: 0.0083 max mem: 33370 +Epoch: [10] [ 450/2639] eta: 1:45:46 lr: 3.839654722082694e-05 loss: 0.0841 (0.0848) time: 2.8992 data: 0.0082 max mem: 33370 +Epoch: [10] [ 460/2639] eta: 1:45:17 lr: 3.8392157288027466e-05 loss: 0.0847 (0.0848) time: 2.8915 data: 0.0085 max mem: 33370 +Epoch: [10] [ 470/2639] eta: 1:44:47 lr: 3.8387767299453416e-05 loss: 0.0793 (0.0849) time: 2.8857 data: 0.0085 max mem: 33370 +Epoch: [10] [ 480/2639] eta: 1:44:18 lr: 3.8383377255096996e-05 loss: 0.0755 (0.0847) time: 2.8840 data: 0.0078 max mem: 33370 +Epoch: [10] [ 490/2639] eta: 1:43:48 lr: 3.837898715495042e-05 loss: 0.0728 (0.0850) time: 2.8962 data: 0.0077 max mem: 33370 +Epoch: [10] [ 500/2639] eta: 1:43:21 lr: 3.837459699900588e-05 loss: 0.0747 (0.0850) time: 2.9145 data: 0.0080 max mem: 33370 +Epoch: [10] [ 510/2639] eta: 1:42:50 lr: 3.837020678725556e-05 loss: 0.0772 (0.0849) time: 2.8949 data: 0.0080 max mem: 33370 +Epoch: [10] [ 520/2639] eta: 1:42:20 lr: 3.836581651969168e-05 loss: 0.0645 (0.0848) time: 2.8639 data: 0.0080 max mem: 33370 +Epoch: [10] [ 530/2639] eta: 1:41:50 lr: 3.836142619630642e-05 loss: 0.0749 (0.0853) time: 2.8716 data: 0.0079 max mem: 33370 +Epoch: [10] [ 540/2639] eta: 1:41:19 lr: 3.8357035817091974e-05 loss: 0.0837 (0.0855) time: 2.8623 data: 0.0080 max mem: 33370 +Epoch: [10] [ 550/2639] eta: 1:40:49 lr: 3.835264538204053e-05 loss: 0.0661 (0.0852) time: 2.8544 data: 0.0083 max mem: 33370 +Epoch: [10] [ 560/2639] eta: 1:40:22 lr: 3.834825489114428e-05 loss: 0.0642 (0.0849) time: 2.8999 data: 0.0084 max mem: 33370 +Epoch: [10] [ 570/2639] eta: 1:39:56 lr: 3.834386434439541e-05 loss: 0.0674 (0.0852) time: 2.9598 data: 0.0084 max mem: 33370 +Epoch: [10] [ 580/2639] eta: 1:39:27 lr: 3.83394737417861e-05 loss: 0.0749 (0.0853) time: 2.9398 data: 0.0084 max mem: 33370 +Epoch: [10] [ 590/2639] eta: 1:38:58 lr: 3.833508308330853e-05 loss: 0.0844 (0.0854) time: 2.9030 data: 0.0082 max mem: 33370 +Epoch: [10] [ 600/2639] eta: 1:38:29 lr: 3.8330692368954874e-05 loss: 0.0844 (0.0855) time: 2.9038 data: 0.0078 max mem: 33370 +Epoch: [10] [ 610/2639] eta: 1:38:00 lr: 3.8326301598717326e-05 loss: 0.0829 (0.0856) time: 2.8985 data: 0.0078 max mem: 33370 +Epoch: [10] [ 620/2639] eta: 1:37:31 lr: 3.8321910772588045e-05 loss: 0.0771 (0.0856) time: 2.8951 data: 0.0079 max mem: 33370 +Epoch: [10] [ 630/2639] eta: 1:37:05 lr: 3.831751989055922e-05 loss: 0.0769 (0.0856) time: 2.9400 data: 0.0078 max mem: 33370 +Epoch: [10] [ 640/2639] eta: 1:36:37 lr: 3.8313128952623e-05 loss: 0.0832 (0.0858) time: 2.9583 data: 0.0080 max mem: 33370 +Epoch: [10] [ 650/2639] eta: 1:36:09 lr: 3.8308737958771564e-05 loss: 0.0882 (0.0858) time: 2.9419 data: 0.0080 max mem: 33370 +Epoch: [10] [ 660/2639] eta: 1:35:41 lr: 3.8304346908997084e-05 loss: 0.0713 (0.0857) time: 2.9391 data: 0.0079 max mem: 33370 +Epoch: [10] [ 670/2639] eta: 1:35:11 lr: 3.829995580329172e-05 loss: 0.0703 (0.0855) time: 2.8914 data: 0.0081 max mem: 33370 +Epoch: [10] [ 680/2639] eta: 1:34:41 lr: 3.829556464164764e-05 loss: 0.0620 (0.0852) time: 2.8580 data: 0.0078 max mem: 33370 +Epoch: [10] [ 690/2639] eta: 1:34:12 lr: 3.8291173424056985e-05 loss: 0.0635 (0.0850) time: 2.8809 data: 0.0079 max mem: 33370 +Epoch: [10] [ 700/2639] eta: 1:33:42 lr: 3.828678215051194e-05 loss: 0.0650 (0.0847) time: 2.8798 data: 0.0081 max mem: 33370 +Epoch: [10] [ 710/2639] eta: 1:33:13 lr: 3.828239082100465e-05 loss: 0.0703 (0.0847) time: 2.8859 data: 0.0083 max mem: 33370 +Epoch: [10] [ 720/2639] eta: 1:32:44 lr: 3.827799943552726e-05 loss: 0.0735 (0.0845) time: 2.9039 data: 0.0084 max mem: 33370 +Epoch: [10] [ 730/2639] eta: 1:32:15 lr: 3.827360799407192e-05 loss: 0.0810 (0.0847) time: 2.8988 data: 0.0083 max mem: 33370 +Epoch: [10] [ 740/2639] eta: 1:31:45 lr: 3.826921649663081e-05 loss: 0.0771 (0.0847) time: 2.8940 data: 0.0084 max mem: 33370 +Epoch: [10] [ 750/2639] eta: 1:31:16 lr: 3.826482494319605e-05 loss: 0.0745 (0.0848) time: 2.8728 data: 0.0082 max mem: 33370 +Epoch: [10] [ 760/2639] eta: 1:30:47 lr: 3.826043333375978e-05 loss: 0.0675 (0.0845) time: 2.8920 data: 0.0081 max mem: 33370 +Epoch: [10] [ 770/2639] eta: 1:30:18 lr: 3.8256041668314165e-05 loss: 0.0661 (0.0845) time: 2.9092 data: 0.0080 max mem: 33370 +Epoch: [10] [ 780/2639] eta: 1:29:49 lr: 3.825164994685134e-05 loss: 0.0737 (0.0847) time: 2.9051 data: 0.0076 max mem: 33370 +Epoch: [10] [ 790/2639] eta: 1:29:22 lr: 3.8247258169363446e-05 loss: 0.0813 (0.0847) time: 2.9376 data: 0.0077 max mem: 33370 +Epoch: [10] [ 800/2639] eta: 1:28:53 lr: 3.82428663358426e-05 loss: 0.0813 (0.0846) time: 2.9402 data: 0.0076 max mem: 33370 +Epoch: [10] [ 810/2639] eta: 1:28:25 lr: 3.823847444628096e-05 loss: 0.0776 (0.0846) time: 2.9153 data: 0.0075 max mem: 33370 +Epoch: [10] [ 820/2639] eta: 1:27:55 lr: 3.8234082500670656e-05 loss: 0.0783 (0.0847) time: 2.9008 data: 0.0078 max mem: 33370 +Epoch: [10] [ 830/2639] eta: 1:27:26 lr: 3.822969049900381e-05 loss: 0.0884 (0.0850) time: 2.8919 data: 0.0082 max mem: 33370 +Epoch: [10] [ 840/2639] eta: 1:26:58 lr: 3.822529844127256e-05 loss: 0.0853 (0.0849) time: 2.9144 data: 0.0081 max mem: 33370 +Epoch: [10] [ 850/2639] eta: 1:26:30 lr: 3.822090632746902e-05 loss: 0.0642 (0.0848) time: 2.9400 data: 0.0080 max mem: 33370 +Epoch: [10] [ 860/2639] eta: 1:26:02 lr: 3.8216514157585324e-05 loss: 0.0745 (0.0848) time: 2.9588 data: 0.0083 max mem: 33370 +Epoch: [10] [ 870/2639] eta: 1:25:33 lr: 3.8212121931613595e-05 loss: 0.0629 (0.0846) time: 2.9339 data: 0.0081 max mem: 33370 +Epoch: [10] [ 880/2639] eta: 1:25:06 lr: 3.820772964954596e-05 loss: 0.0628 (0.0844) time: 2.9445 data: 0.0079 max mem: 33370 +Epoch: [10] [ 890/2639] eta: 1:24:37 lr: 3.820333731137452e-05 loss: 0.0775 (0.0844) time: 2.9578 data: 0.0081 max mem: 33370 +Epoch: [10] [ 900/2639] eta: 1:24:07 lr: 3.819894491709139e-05 loss: 0.0893 (0.0845) time: 2.8881 data: 0.0082 max mem: 33370 +Epoch: [10] [ 910/2639] eta: 1:23:38 lr: 3.819455246668871e-05 loss: 0.0738 (0.0844) time: 2.8594 data: 0.0082 max mem: 33370 +Epoch: [10] [ 920/2639] eta: 1:23:09 lr: 3.8190159960158575e-05 loss: 0.0738 (0.0844) time: 2.8908 data: 0.0080 max mem: 33370 +Epoch: [10] [ 930/2639] eta: 1:22:39 lr: 3.818576739749308e-05 loss: 0.0849 (0.0845) time: 2.8760 data: 0.0082 max mem: 33370 +Epoch: [10] [ 940/2639] eta: 1:22:09 lr: 3.818137477868436e-05 loss: 0.0780 (0.0844) time: 2.8447 data: 0.0082 max mem: 33370 +Epoch: [10] [ 950/2639] eta: 1:21:39 lr: 3.81769821037245e-05 loss: 0.0665 (0.0845) time: 2.8655 data: 0.0078 max mem: 33370 +Epoch: [10] [ 960/2639] eta: 1:21:10 lr: 3.8172589372605624e-05 loss: 0.0670 (0.0844) time: 2.8926 data: 0.0083 max mem: 33370 +Epoch: [10] [ 970/2639] eta: 1:20:41 lr: 3.8168196585319805e-05 loss: 0.0699 (0.0843) time: 2.9062 data: 0.0082 max mem: 33370 +Epoch: [10] [ 980/2639] eta: 1:20:12 lr: 3.816380374185917e-05 loss: 0.0675 (0.0843) time: 2.8983 data: 0.0079 max mem: 33370 +Epoch: [10] [ 990/2639] eta: 1:19:44 lr: 3.8159410842215796e-05 loss: 0.0740 (0.0844) time: 2.9237 data: 0.0082 max mem: 33370 +Epoch: [10] [1000/2639] eta: 1:19:15 lr: 3.815501788638179e-05 loss: 0.0751 (0.0844) time: 2.9352 data: 0.0080 max mem: 33370 +Epoch: [10] [1010/2639] eta: 1:18:45 lr: 3.815062487434924e-05 loss: 0.0883 (0.0846) time: 2.8838 data: 0.0079 max mem: 33370 +Epoch: [10] [1020/2639] eta: 1:18:16 lr: 3.814623180611023e-05 loss: 0.0933 (0.0847) time: 2.8743 data: 0.0080 max mem: 33370 +Epoch: [10] [1030/2639] eta: 1:17:48 lr: 3.8141838681656864e-05 loss: 0.0804 (0.0847) time: 2.9332 data: 0.0082 max mem: 33370 +Epoch: [10] [1040/2639] eta: 1:17:20 lr: 3.813744550098122e-05 loss: 0.0781 (0.0847) time: 2.9412 data: 0.0085 max mem: 33370 +Epoch: [10] [1050/2639] eta: 1:16:50 lr: 3.813305226407538e-05 loss: 0.0717 (0.0846) time: 2.8835 data: 0.0087 max mem: 33370 +Epoch: [10] [1060/2639] eta: 1:16:21 lr: 3.812865897093143e-05 loss: 0.0694 (0.0847) time: 2.8749 data: 0.0081 max mem: 33370 +Epoch: [10] [1070/2639] eta: 1:15:53 lr: 3.812426562154145e-05 loss: 0.0740 (0.0848) time: 2.9272 data: 0.0078 max mem: 33370 +Epoch: [10] [1080/2639] eta: 1:15:23 lr: 3.8119872215897515e-05 loss: 0.0723 (0.0847) time: 2.9164 data: 0.0081 max mem: 33370 +Epoch: [10] [1090/2639] eta: 1:14:55 lr: 3.81154787539917e-05 loss: 0.0741 (0.0846) time: 2.9238 data: 0.0085 max mem: 33370 +Epoch: [10] [1100/2639] eta: 1:14:26 lr: 3.811108523581608e-05 loss: 0.0744 (0.0847) time: 2.9191 data: 0.0083 max mem: 33370 +Epoch: [10] [1110/2639] eta: 1:13:57 lr: 3.810669166136272e-05 loss: 0.0805 (0.0848) time: 2.9032 data: 0.0078 max mem: 33370 +Epoch: [10] [1120/2639] eta: 1:13:28 lr: 3.8102298030623714e-05 loss: 0.0855 (0.0848) time: 2.9076 data: 0.0077 max mem: 33370 +Epoch: [10] [1130/2639] eta: 1:12:59 lr: 3.8097904343591106e-05 loss: 0.0739 (0.0848) time: 2.8885 data: 0.0078 max mem: 33370 +Epoch: [10] [1140/2639] eta: 1:12:29 lr: 3.809351060025696e-05 loss: 0.0739 (0.0848) time: 2.8931 data: 0.0083 max mem: 33370 +Epoch: [10] [1150/2639] eta: 1:12:00 lr: 3.8089116800613344e-05 loss: 0.0902 (0.0849) time: 2.8691 data: 0.0085 max mem: 33370 +Epoch: [10] [1160/2639] eta: 1:11:30 lr: 3.808472294465233e-05 loss: 0.0902 (0.0850) time: 2.8595 data: 0.0086 max mem: 33370 +Epoch: [10] [1170/2639] eta: 1:11:02 lr: 3.808032903236597e-05 loss: 0.0764 (0.0850) time: 2.9202 data: 0.0085 max mem: 33370 +Epoch: [10] [1180/2639] eta: 1:10:35 lr: 3.8075935063746305e-05 loss: 0.0759 (0.0850) time: 3.0115 data: 0.0083 max mem: 33370 +Epoch: [10] [1190/2639] eta: 1:10:06 lr: 3.807154103878541e-05 loss: 0.0768 (0.0851) time: 2.9926 data: 0.0083 max mem: 33370 +Epoch: [10] [1200/2639] eta: 1:09:38 lr: 3.806714695747532e-05 loss: 0.0783 (0.0851) time: 2.9249 data: 0.0083 max mem: 33370 +Epoch: [10] [1210/2639] eta: 1:09:08 lr: 3.806275281980811e-05 loss: 0.0783 (0.0852) time: 2.8954 data: 0.0083 max mem: 33370 +Epoch: [10] [1220/2639] eta: 1:08:40 lr: 3.8058358625775805e-05 loss: 0.0755 (0.0852) time: 2.9181 data: 0.0083 max mem: 33370 +Epoch: [10] [1230/2639] eta: 1:08:10 lr: 3.805396437537045e-05 loss: 0.0739 (0.0852) time: 2.8958 data: 0.0084 max mem: 33370 +Epoch: [10] [1240/2639] eta: 1:07:41 lr: 3.804957006858411e-05 loss: 0.0682 (0.0851) time: 2.8818 data: 0.0080 max mem: 33370 +Epoch: [10] [1250/2639] eta: 1:07:12 lr: 3.8045175705408806e-05 loss: 0.0673 (0.0850) time: 2.8924 data: 0.0080 max mem: 33370 +Epoch: [10] [1260/2639] eta: 1:06:43 lr: 3.8040781285836585e-05 loss: 0.0725 (0.0849) time: 2.8889 data: 0.0081 max mem: 33370 +Epoch: [10] [1270/2639] eta: 1:06:14 lr: 3.8036386809859486e-05 loss: 0.0715 (0.0849) time: 2.9023 data: 0.0081 max mem: 33370 +Epoch: [10] [1280/2639] eta: 1:05:45 lr: 3.8031992277469544e-05 loss: 0.0733 (0.0849) time: 2.8998 data: 0.0085 max mem: 33370 +Epoch: [10] [1290/2639] eta: 1:05:16 lr: 3.802759768865879e-05 loss: 0.0829 (0.0850) time: 2.9176 data: 0.0085 max mem: 33370 +Epoch: [10] [1300/2639] eta: 1:04:48 lr: 3.8023203043419255e-05 loss: 0.0783 (0.0849) time: 2.9514 data: 0.0083 max mem: 33370 +Epoch: [10] [1310/2639] eta: 1:04:19 lr: 3.8018808341742955e-05 loss: 0.0685 (0.0849) time: 2.9744 data: 0.0083 max mem: 33370 +Epoch: [10] [1320/2639] eta: 1:03:50 lr: 3.8014413583621945e-05 loss: 0.0759 (0.0851) time: 2.9341 data: 0.0080 max mem: 33370 +Epoch: [10] [1330/2639] eta: 1:03:21 lr: 3.8010018769048236e-05 loss: 0.0715 (0.0849) time: 2.9067 data: 0.0079 max mem: 33370 +Epoch: [10] [1340/2639] eta: 1:02:52 lr: 3.800562389801383e-05 loss: 0.0782 (0.0850) time: 2.9024 data: 0.0080 max mem: 33370 +Epoch: [10] [1350/2639] eta: 1:02:23 lr: 3.8001228970510776e-05 loss: 0.0782 (0.0849) time: 2.8763 data: 0.0082 max mem: 33370 +Epoch: [10] [1360/2639] eta: 1:01:53 lr: 3.799683398653108e-05 loss: 0.0625 (0.0848) time: 2.8638 data: 0.0082 max mem: 33370 +Epoch: [10] [1370/2639] eta: 1:01:24 lr: 3.7992438946066755e-05 loss: 0.0718 (0.0849) time: 2.8620 data: 0.0078 max mem: 33370 +Epoch: [10] [1380/2639] eta: 1:00:54 lr: 3.7988043849109825e-05 loss: 0.0748 (0.0849) time: 2.8480 data: 0.0081 max mem: 33370 +Epoch: [10] [1390/2639] eta: 1:00:26 lr: 3.798364869565229e-05 loss: 0.0738 (0.0848) time: 2.9016 data: 0.0086 max mem: 33370 +Epoch: [10] [1400/2639] eta: 0:59:56 lr: 3.797925348568616e-05 loss: 0.0685 (0.0848) time: 2.9072 data: 0.0085 max mem: 33370 +Epoch: [10] [1410/2639] eta: 0:59:28 lr: 3.797485821920345e-05 loss: 0.0685 (0.0850) time: 2.9000 data: 0.0080 max mem: 33370 +Epoch: [10] [1420/2639] eta: 0:58:59 lr: 3.7970462896196164e-05 loss: 0.0682 (0.0849) time: 2.9523 data: 0.0080 max mem: 33370 +Epoch: [10] [1430/2639] eta: 0:58:30 lr: 3.7966067516656296e-05 loss: 0.0704 (0.0849) time: 2.9471 data: 0.0081 max mem: 33370 +Epoch: [10] [1440/2639] eta: 0:58:01 lr: 3.796167208057585e-05 loss: 0.0714 (0.0849) time: 2.9325 data: 0.0084 max mem: 33370 +Epoch: [10] [1450/2639] eta: 0:57:32 lr: 3.795727658794683e-05 loss: 0.0774 (0.0849) time: 2.9056 data: 0.0087 max mem: 33370 +Epoch: [10] [1460/2639] eta: 0:57:03 lr: 3.795288103876124e-05 loss: 0.0774 (0.0848) time: 2.8980 data: 0.0082 max mem: 33370 +Epoch: [10] [1470/2639] eta: 0:56:34 lr: 3.794848543301105e-05 loss: 0.0725 (0.0850) time: 2.9007 data: 0.0080 max mem: 33370 +Epoch: [10] [1480/2639] eta: 0:56:05 lr: 3.794408977068826e-05 loss: 0.0899 (0.0851) time: 2.9135 data: 0.0081 max mem: 33370 +Epoch: [10] [1490/2639] eta: 0:55:36 lr: 3.793969405178488e-05 loss: 0.0800 (0.0851) time: 2.9128 data: 0.0085 max mem: 33370 +Epoch: [10] [1500/2639] eta: 0:55:07 lr: 3.7935298276292874e-05 loss: 0.0753 (0.0851) time: 2.8691 data: 0.0084 max mem: 33370 +Epoch: [10] [1510/2639] eta: 0:54:37 lr: 3.7930902444204235e-05 loss: 0.0740 (0.0851) time: 2.8487 data: 0.0081 max mem: 33370 +Epoch: [10] [1520/2639] eta: 0:54:08 lr: 3.7926506555510946e-05 loss: 0.0977 (0.0852) time: 2.8947 data: 0.0081 max mem: 33370 +Epoch: [10] [1530/2639] eta: 0:53:39 lr: 3.7922110610205e-05 loss: 0.0847 (0.0851) time: 2.9166 data: 0.0080 max mem: 33370 +Epoch: [10] [1540/2639] eta: 0:53:10 lr: 3.7917714608278364e-05 loss: 0.0789 (0.0852) time: 2.8870 data: 0.0077 max mem: 33370 +Epoch: [10] [1550/2639] eta: 0:52:41 lr: 3.791331854972301e-05 loss: 0.0763 (0.0852) time: 2.9139 data: 0.0074 max mem: 33370 +Epoch: [10] [1560/2639] eta: 0:52:12 lr: 3.7908922434530916e-05 loss: 0.0763 (0.0853) time: 2.9194 data: 0.0076 max mem: 33370 +Epoch: [10] [1570/2639] eta: 0:51:43 lr: 3.790452626269407e-05 loss: 0.0878 (0.0852) time: 2.8808 data: 0.0075 max mem: 33370 +Epoch: [10] [1580/2639] eta: 0:51:14 lr: 3.790013003420442e-05 loss: 0.0773 (0.0852) time: 2.8487 data: 0.0075 max mem: 33370 +Epoch: [10] [1590/2639] eta: 0:50:44 lr: 3.789573374905394e-05 loss: 0.0742 (0.0852) time: 2.8510 data: 0.0077 max mem: 33370 +Epoch: [10] [1600/2639] eta: 0:50:15 lr: 3.7891337407234605e-05 loss: 0.0683 (0.0852) time: 2.8738 data: 0.0077 max mem: 33370 +Epoch: [10] [1610/2639] eta: 0:49:46 lr: 3.7886941008738375e-05 loss: 0.0678 (0.0852) time: 2.8742 data: 0.0076 max mem: 33370 +Epoch: [10] [1620/2639] eta: 0:49:17 lr: 3.788254455355721e-05 loss: 0.0867 (0.0852) time: 2.9011 data: 0.0075 max mem: 33370 +Epoch: [10] [1630/2639] eta: 0:48:48 lr: 3.787814804168308e-05 loss: 0.0723 (0.0851) time: 2.9062 data: 0.0075 max mem: 33370 +Epoch: [10] [1640/2639] eta: 0:48:19 lr: 3.787375147310791e-05 loss: 0.0685 (0.0851) time: 2.9026 data: 0.0078 max mem: 33370 +Epoch: [10] [1650/2639] eta: 0:47:50 lr: 3.786935484782369e-05 loss: 0.0800 (0.0852) time: 2.9132 data: 0.0077 max mem: 33370 +Epoch: [10] [1660/2639] eta: 0:47:20 lr: 3.786495816582236e-05 loss: 0.0883 (0.0852) time: 2.8585 data: 0.0074 max mem: 33370 +Epoch: [10] [1670/2639] eta: 0:46:51 lr: 3.786056142709587e-05 loss: 0.0815 (0.0853) time: 2.8590 data: 0.0077 max mem: 33370 +Epoch: [10] [1680/2639] eta: 0:46:22 lr: 3.785616463163616e-05 loss: 0.0686 (0.0853) time: 2.8640 data: 0.0082 max mem: 33370 +Epoch: [10] [1690/2639] eta: 0:45:53 lr: 3.78517677794352e-05 loss: 0.0653 (0.0853) time: 2.8506 data: 0.0084 max mem: 33370 +Epoch: [10] [1700/2639] eta: 0:45:24 lr: 3.7847370870484915e-05 loss: 0.0745 (0.0852) time: 2.8667 data: 0.0082 max mem: 33370 +Epoch: [10] [1710/2639] eta: 0:44:54 lr: 3.784297390477725e-05 loss: 0.0844 (0.0853) time: 2.8656 data: 0.0081 max mem: 33370 +Epoch: [10] [1720/2639] eta: 0:44:25 lr: 3.7838576882304146e-05 loss: 0.0809 (0.0853) time: 2.8764 data: 0.0081 max mem: 33370 +Epoch: [10] [1730/2639] eta: 0:43:56 lr: 3.783417980305754e-05 loss: 0.0794 (0.0853) time: 2.9055 data: 0.0076 max mem: 33370 +Epoch: [10] [1740/2639] eta: 0:43:27 lr: 3.782978266702937e-05 loss: 0.0838 (0.0853) time: 2.9081 data: 0.0074 max mem: 33370 +Epoch: [10] [1750/2639] eta: 0:42:58 lr: 3.782538547421157e-05 loss: 0.0827 (0.0852) time: 2.8679 data: 0.0074 max mem: 33370 +Epoch: [10] [1760/2639] eta: 0:42:29 lr: 3.782098822459607e-05 loss: 0.0808 (0.0852) time: 2.8692 data: 0.0071 max mem: 33370 +Epoch: [10] [1770/2639] eta: 0:42:00 lr: 3.781659091817479e-05 loss: 0.0768 (0.0853) time: 2.8941 data: 0.0072 max mem: 33370 +Epoch: [10] [1780/2639] eta: 0:41:31 lr: 3.781219355493967e-05 loss: 0.0768 (0.0854) time: 2.8753 data: 0.0074 max mem: 33370 +Epoch: [10] [1790/2639] eta: 0:41:01 lr: 3.780779613488263e-05 loss: 0.0663 (0.0854) time: 2.8480 data: 0.0077 max mem: 33370 +Epoch: [10] [1800/2639] eta: 0:40:33 lr: 3.780339865799559e-05 loss: 0.0659 (0.0853) time: 2.8853 data: 0.0077 max mem: 33370 +Epoch: [10] [1810/2639] eta: 0:40:04 lr: 3.7799001124270465e-05 loss: 0.0763 (0.0853) time: 2.9191 data: 0.0078 max mem: 33370 +Epoch: [10] [1820/2639] eta: 0:39:35 lr: 3.7794603533699184e-05 loss: 0.0857 (0.0854) time: 2.9171 data: 0.0080 max mem: 33370 +Epoch: [10] [1830/2639] eta: 0:39:06 lr: 3.7790205886273656e-05 loss: 0.0840 (0.0854) time: 2.9240 data: 0.0079 max mem: 33370 +Epoch: [10] [1840/2639] eta: 0:38:37 lr: 3.77858081819858e-05 loss: 0.0832 (0.0855) time: 2.9545 data: 0.0080 max mem: 33370 +Epoch: [10] [1850/2639] eta: 0:38:08 lr: 3.778141042082752e-05 loss: 0.0665 (0.0854) time: 2.9295 data: 0.0082 max mem: 33370 +Epoch: [10] [1860/2639] eta: 0:37:39 lr: 3.7777012602790726e-05 loss: 0.0624 (0.0856) time: 2.8843 data: 0.0079 max mem: 33370 +Epoch: [10] [1870/2639] eta: 0:37:10 lr: 3.777261472786734e-05 loss: 0.0778 (0.0857) time: 2.8778 data: 0.0076 max mem: 33370 +Epoch: [10] [1880/2639] eta: 0:36:41 lr: 3.776821679604925e-05 loss: 0.0758 (0.0856) time: 2.8788 data: 0.0078 max mem: 33370 +Epoch: [10] [1890/2639] eta: 0:36:12 lr: 3.7763818807328354e-05 loss: 0.0765 (0.0856) time: 2.8794 data: 0.0081 max mem: 33370 +Epoch: [10] [1900/2639] eta: 0:35:43 lr: 3.7759420761696564e-05 loss: 0.0835 (0.0856) time: 2.8952 data: 0.0077 max mem: 33370 +Epoch: [10] [1910/2639] eta: 0:35:14 lr: 3.7755022659145787e-05 loss: 0.0910 (0.0856) time: 2.8938 data: 0.0080 max mem: 33370 +Epoch: [10] [1920/2639] eta: 0:34:45 lr: 3.7750624499667896e-05 loss: 0.0795 (0.0856) time: 2.8592 data: 0.0086 max mem: 33370 +Epoch: [10] [1930/2639] eta: 0:34:16 lr: 3.7746226283254796e-05 loss: 0.0754 (0.0856) time: 2.8910 data: 0.0079 max mem: 33370 +Epoch: [10] [1940/2639] eta: 0:33:47 lr: 3.7741828009898374e-05 loss: 0.0754 (0.0856) time: 2.9206 data: 0.0075 max mem: 33370 +Epoch: [10] [1950/2639] eta: 0:33:18 lr: 3.7737429679590534e-05 loss: 0.0706 (0.0856) time: 2.9255 data: 0.0079 max mem: 33370 +Epoch: [10] [1960/2639] eta: 0:32:49 lr: 3.7733031292323156e-05 loss: 0.0644 (0.0857) time: 2.8959 data: 0.0080 max mem: 33370 +Epoch: [10] [1970/2639] eta: 0:32:20 lr: 3.772863284808811e-05 loss: 0.0813 (0.0858) time: 2.8688 data: 0.0078 max mem: 33370 +Epoch: [10] [1980/2639] eta: 0:31:50 lr: 3.77242343468773e-05 loss: 0.0778 (0.0857) time: 2.8694 data: 0.0078 max mem: 33370 +Epoch: [10] [1990/2639] eta: 0:31:21 lr: 3.7719835788682596e-05 loss: 0.0735 (0.0857) time: 2.8739 data: 0.0076 max mem: 33370 +Epoch: [10] [2000/2639] eta: 0:30:52 lr: 3.771543717349587e-05 loss: 0.0790 (0.0858) time: 2.8712 data: 0.0074 max mem: 33370 +Epoch: [10] [2010/2639] eta: 0:30:23 lr: 3.771103850130901e-05 loss: 0.0685 (0.0857) time: 2.8699 data: 0.0074 max mem: 33370 +Epoch: [10] [2020/2639] eta: 0:29:54 lr: 3.770663977211388e-05 loss: 0.0779 (0.0858) time: 2.8688 data: 0.0075 max mem: 33370 +Epoch: [10] [2030/2639] eta: 0:29:25 lr: 3.770224098590237e-05 loss: 0.0803 (0.0857) time: 2.8657 data: 0.0073 max mem: 33370 +Epoch: [10] [2040/2639] eta: 0:28:56 lr: 3.769784214266633e-05 loss: 0.0744 (0.0857) time: 2.8917 data: 0.0074 max mem: 33370 +Epoch: [10] [2050/2639] eta: 0:28:27 lr: 3.769344324239763e-05 loss: 0.0775 (0.0857) time: 2.9127 data: 0.0075 max mem: 33370 +Epoch: [10] [2060/2639] eta: 0:27:58 lr: 3.768904428508814e-05 loss: 0.0775 (0.0857) time: 2.9184 data: 0.0076 max mem: 33370 +Epoch: [10] [2070/2639] eta: 0:27:29 lr: 3.768464527072972e-05 loss: 0.0730 (0.0857) time: 2.9265 data: 0.0081 max mem: 33370 +Epoch: [10] [2080/2639] eta: 0:27:00 lr: 3.768024619931423e-05 loss: 0.0734 (0.0857) time: 2.9096 data: 0.0082 max mem: 33370 +Epoch: [10] [2090/2639] eta: 0:26:32 lr: 3.7675847070833535e-05 loss: 0.0641 (0.0856) time: 2.9481 data: 0.0082 max mem: 33370 +Epoch: [10] [2100/2639] eta: 0:26:02 lr: 3.767144788527948e-05 loss: 0.0610 (0.0856) time: 2.9314 data: 0.0086 max mem: 33370 +Epoch: [10] [2110/2639] eta: 0:25:33 lr: 3.766704864264393e-05 loss: 0.0809 (0.0856) time: 2.8396 data: 0.0090 max mem: 33370 +Epoch: [10] [2120/2639] eta: 0:25:04 lr: 3.7662649342918736e-05 loss: 0.0838 (0.0856) time: 2.8600 data: 0.0085 max mem: 33370 +Epoch: [10] [2130/2639] eta: 0:24:35 lr: 3.765824998609574e-05 loss: 0.0859 (0.0857) time: 2.9463 data: 0.0077 max mem: 33370 +Epoch: [10] [2140/2639] eta: 0:24:06 lr: 3.765385057216679e-05 loss: 0.0847 (0.0857) time: 2.9322 data: 0.0079 max mem: 33370 +Epoch: [10] [2150/2639] eta: 0:23:37 lr: 3.764945110112373e-05 loss: 0.0930 (0.0858) time: 2.8571 data: 0.0081 max mem: 33370 +Epoch: [10] [2160/2639] eta: 0:23:08 lr: 3.764505157295842e-05 loss: 0.0997 (0.0859) time: 2.8815 data: 0.0075 max mem: 33370 +Epoch: [10] [2170/2639] eta: 0:22:39 lr: 3.7640651987662676e-05 loss: 0.0791 (0.0859) time: 2.9194 data: 0.0077 max mem: 33370 +Epoch: [10] [2180/2639] eta: 0:22:10 lr: 3.763625234522835e-05 loss: 0.0851 (0.0860) time: 2.8812 data: 0.0078 max mem: 33370 +Epoch: [10] [2190/2639] eta: 0:21:41 lr: 3.7631852645647276e-05 loss: 0.0848 (0.0860) time: 2.8468 data: 0.0075 max mem: 33370 +Epoch: [10] [2200/2639] eta: 0:21:12 lr: 3.762745288891129e-05 loss: 0.0667 (0.0859) time: 2.8855 data: 0.0075 max mem: 33370 +Epoch: [10] [2210/2639] eta: 0:20:43 lr: 3.7623053075012215e-05 loss: 0.0638 (0.0859) time: 2.9180 data: 0.0077 max mem: 33370 +Epoch: [10] [2220/2639] eta: 0:20:14 lr: 3.761865320394189e-05 loss: 0.0770 (0.0859) time: 2.9413 data: 0.0076 max mem: 33370 +Epoch: [10] [2230/2639] eta: 0:19:45 lr: 3.7614253275692136e-05 loss: 0.0696 (0.0859) time: 2.9186 data: 0.0075 max mem: 33370 +Epoch: [10] [2240/2639] eta: 0:19:16 lr: 3.7609853290254784e-05 loss: 0.0696 (0.0859) time: 2.8584 data: 0.0080 max mem: 33370 +Epoch: [10] [2250/2639] eta: 0:18:47 lr: 3.7605453247621655e-05 loss: 0.0761 (0.0859) time: 2.8720 data: 0.0078 max mem: 33370 +Epoch: [10] [2260/2639] eta: 0:18:18 lr: 3.760105314778456e-05 loss: 0.0778 (0.0859) time: 2.9372 data: 0.0078 max mem: 33370 +Epoch: [10] [2270/2639] eta: 0:17:49 lr: 3.759665299073533e-05 loss: 0.0685 (0.0858) time: 2.9601 data: 0.0084 max mem: 33370 +Epoch: [10] [2280/2639] eta: 0:17:21 lr: 3.759225277646578e-05 loss: 0.0715 (0.0858) time: 2.9683 data: 0.0081 max mem: 33370 +Epoch: [10] [2290/2639] eta: 0:16:52 lr: 3.7587852504967726e-05 loss: 0.0795 (0.0858) time: 2.9647 data: 0.0076 max mem: 33370 +Epoch: [10] [2300/2639] eta: 0:16:23 lr: 3.7583452176232956e-05 loss: 0.0795 (0.0858) time: 2.8972 data: 0.0077 max mem: 33370 +Epoch: [10] [2310/2639] eta: 0:15:54 lr: 3.757905179025331e-05 loss: 0.0719 (0.0858) time: 2.9053 data: 0.0075 max mem: 33370 +Epoch: [10] [2320/2639] eta: 0:15:25 lr: 3.757465134702057e-05 loss: 0.0681 (0.0858) time: 2.9393 data: 0.0072 max mem: 33370 +Epoch: [10] [2330/2639] eta: 0:14:56 lr: 3.757025084652657e-05 loss: 0.0652 (0.0857) time: 2.9090 data: 0.0075 max mem: 33370 +Epoch: [10] [2340/2639] eta: 0:14:27 lr: 3.756585028876308e-05 loss: 0.0659 (0.0857) time: 2.8877 data: 0.0078 max mem: 33370 +Epoch: [10] [2350/2639] eta: 0:13:58 lr: 3.7561449673721925e-05 loss: 0.0734 (0.0857) time: 2.8963 data: 0.0076 max mem: 33370 +Epoch: [10] [2360/2639] eta: 0:13:29 lr: 3.755704900139489e-05 loss: 0.0768 (0.0857) time: 2.9142 data: 0.0077 max mem: 33370 +Epoch: [10] [2370/2639] eta: 0:13:00 lr: 3.7552648271773775e-05 loss: 0.0797 (0.0856) time: 2.9142 data: 0.0080 max mem: 33370 +Epoch: [10] [2380/2639] eta: 0:12:31 lr: 3.754824748485038e-05 loss: 0.0721 (0.0856) time: 2.8872 data: 0.0075 max mem: 33370 +Epoch: [10] [2390/2639] eta: 0:12:02 lr: 3.7543846640616483e-05 loss: 0.0677 (0.0856) time: 2.8395 data: 0.0077 max mem: 33370 +Epoch: [10] [2400/2639] eta: 0:11:33 lr: 3.7539445739063885e-05 loss: 0.0641 (0.0856) time: 2.8567 data: 0.0079 max mem: 33370 +Epoch: [10] [2410/2639] eta: 0:11:04 lr: 3.753504478018436e-05 loss: 0.0703 (0.0856) time: 2.8772 data: 0.0078 max mem: 33370 +Epoch: [10] [2420/2639] eta: 0:10:35 lr: 3.753064376396971e-05 loss: 0.0874 (0.0856) time: 2.8564 data: 0.0076 max mem: 33370 +Epoch: [10] [2430/2639] eta: 0:10:06 lr: 3.7526242690411705e-05 loss: 0.0810 (0.0857) time: 2.8876 data: 0.0074 max mem: 33370 +Epoch: [10] [2440/2639] eta: 0:09:37 lr: 3.752184155950213e-05 loss: 0.0761 (0.0857) time: 2.9095 data: 0.0080 max mem: 33370 +Epoch: [10] [2450/2639] eta: 0:09:07 lr: 3.7517440371232766e-05 loss: 0.0761 (0.0857) time: 2.8680 data: 0.0077 max mem: 33370 +Epoch: [10] [2460/2639] eta: 0:08:39 lr: 3.751303912559538e-05 loss: 0.0794 (0.0857) time: 2.8959 data: 0.0075 max mem: 33370 +Epoch: [10] [2470/2639] eta: 0:08:10 lr: 3.7508637822581745e-05 loss: 0.0738 (0.0857) time: 2.9271 data: 0.0077 max mem: 33370 +Epoch: [10] [2480/2639] eta: 0:07:41 lr: 3.7504236462183634e-05 loss: 0.0800 (0.0857) time: 2.9037 data: 0.0075 max mem: 33370 +Epoch: [10] [2490/2639] eta: 0:07:12 lr: 3.7499835044392826e-05 loss: 0.0830 (0.0857) time: 2.8911 data: 0.0082 max mem: 33370 +Epoch: [10] [2500/2639] eta: 0:06:43 lr: 3.749543356920108e-05 loss: 0.0870 (0.0857) time: 2.8585 data: 0.0083 max mem: 33370 +Epoch: [10] [2510/2639] eta: 0:06:14 lr: 3.749103203660016e-05 loss: 0.0859 (0.0857) time: 2.8769 data: 0.0075 max mem: 33370 +Epoch: [10] [2520/2639] eta: 0:05:45 lr: 3.748663044658182e-05 loss: 0.0787 (0.0858) time: 2.9037 data: 0.0080 max mem: 33370 +Epoch: [10] [2530/2639] eta: 0:05:16 lr: 3.7482228799137844e-05 loss: 0.0762 (0.0858) time: 2.9126 data: 0.0081 max mem: 33370 +Epoch: [10] [2540/2639] eta: 0:04:47 lr: 3.747782709425997e-05 loss: 0.0795 (0.0858) time: 2.9124 data: 0.0079 max mem: 33370 +Epoch: [10] [2550/2639] eta: 0:04:18 lr: 3.747342533193995e-05 loss: 0.0734 (0.0858) time: 2.8934 data: 0.0082 max mem: 33370 +Epoch: [10] [2560/2639] eta: 0:03:49 lr: 3.746902351216955e-05 loss: 0.0809 (0.0860) time: 2.8991 data: 0.0081 max mem: 33370 +Epoch: [10] [2570/2639] eta: 0:03:20 lr: 3.746462163494051e-05 loss: 0.0809 (0.0859) time: 2.9260 data: 0.0078 max mem: 33370 +Epoch: [10] [2580/2639] eta: 0:02:51 lr: 3.7460219700244593e-05 loss: 0.0683 (0.0859) time: 2.9164 data: 0.0079 max mem: 33370 +Epoch: [10] [2590/2639] eta: 0:02:22 lr: 3.7455817708073534e-05 loss: 0.0713 (0.0858) time: 2.9269 data: 0.0085 max mem: 33370 +Epoch: [10] [2600/2639] eta: 0:01:53 lr: 3.745141565841908e-05 loss: 0.0868 (0.0859) time: 2.9401 data: 0.0080 max mem: 33370 +Epoch: [10] [2610/2639] eta: 0:01:24 lr: 3.744701355127297e-05 loss: 0.0964 (0.0859) time: 2.9156 data: 0.0077 max mem: 33370 +Epoch: [10] [2620/2639] eta: 0:00:55 lr: 3.7442611386626945e-05 loss: 0.0885 (0.0859) time: 2.9166 data: 0.0081 max mem: 33370 +Epoch: [10] [2630/2639] eta: 0:00:26 lr: 3.743820916447275e-05 loss: 0.0782 (0.0859) time: 2.9079 data: 0.0076 max mem: 33370 +Epoch: [10] Total time: 2:07:33 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 2:30:10 time: 3.5021 data: 3.4111 max mem: 33370 +Test: [ 100/2573] eta: 0:04:36 time: 0.0784 data: 0.0014 max mem: 33370 +Test: [ 200/2573] eta: 0:03:48 time: 0.0799 data: 0.0014 max mem: 33370 +Test: [ 300/2573] eta: 0:03:25 time: 0.0819 data: 0.0015 max mem: 33370 +Test: [ 400/2573] eta: 0:03:10 time: 0.0821 data: 0.0014 max mem: 33370 +Test: [ 500/2573] eta: 0:02:58 time: 0.0795 data: 0.0015 max mem: 33370 +Test: [ 600/2573] eta: 0:02:48 time: 0.0812 data: 0.0015 max mem: 33370 +Test: [ 700/2573] eta: 0:02:38 time: 0.0789 data: 0.0013 max mem: 33370 +Test: [ 800/2573] eta: 0:02:29 time: 0.0836 data: 0.0014 max mem: 33370 +Test: [ 900/2573] eta: 0:02:20 time: 0.0794 data: 0.0014 max mem: 33370 +Test: [1000/2573] eta: 0:02:11 time: 0.0799 data: 0.0014 max mem: 33370 +Test: [1100/2573] eta: 0:02:02 time: 0.0801 data: 0.0015 max mem: 33370 +Test: [1200/2573] eta: 0:01:54 time: 0.0805 data: 0.0014 max mem: 33370 +Test: [1300/2573] eta: 0:01:45 time: 0.0816 data: 0.0016 max mem: 33370 +Test: [1400/2573] eta: 0:01:37 time: 0.0800 data: 0.0013 max mem: 33370 +Test: [1500/2573] eta: 0:01:28 time: 0.0818 data: 0.0015 max mem: 33370 +Test: [1600/2573] eta: 0:01:20 time: 0.0844 data: 0.0014 max mem: 33370 +Test: [1700/2573] eta: 0:01:12 time: 0.0796 data: 0.0015 max mem: 33370 +Test: [1800/2573] eta: 0:01:03 time: 0.0813 data: 0.0014 max mem: 33370 +Test: [1900/2573] eta: 0:00:55 time: 0.0785 data: 0.0014 max mem: 33370 +Test: [2000/2573] eta: 0:00:47 time: 0.0809 data: 0.0014 max mem: 33370 +Test: [2100/2573] eta: 0:00:38 time: 0.0815 data: 0.0013 max mem: 33370 +Test: [2200/2573] eta: 0:00:30 time: 0.0821 data: 0.0014 max mem: 33370 +Test: [2300/2573] eta: 0:00:22 time: 0.0827 data: 0.0015 max mem: 33370 +Test: [2400/2573] eta: 0:00:14 time: 0.0779 data: 0.0014 max mem: 33370 +Test: [2500/2573] eta: 0:00:05 time: 0.0810 data: 0.0014 max mem: 33370 +Test: Total time: 0:03:31 +Final results: +Mean IoU is 59.90 + + precision@0.5 = 66.87 + precision@0.6 = 60.36 + precision@0.7 = 51.86 + precision@0.8 = 40.40 + precision@0.9 = 18.77 + overall IoU = 58.35 + +Average object IoU 59.90360629616605 +Overall IoU 58.35196304321289 +Better epoch: 10 + +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [11] [ 0/2639] eta: 3:48:04 lr: 3.7434247115357644e-05 loss: 0.0505 (0.0505) time: 5.1855 data: 2.1965 max mem: 33370 +Epoch: [11] [ 10/2639] eta: 2:20:56 lr: 3.742984478391514e-05 loss: 0.0565 (0.0870) time: 3.2167 data: 0.2073 max mem: 33370 +Epoch: [11] [ 20/2639] eta: 2:14:59 lr: 3.7425442394940486e-05 loss: 0.0638 (0.0842) time: 2.9878 data: 0.0077 max mem: 33370 +Epoch: [11] [ 30/2639] eta: 2:11:46 lr: 3.74210399484254e-05 loss: 0.0672 (0.0810) time: 2.9280 data: 0.0076 max mem: 33370 +Epoch: [11] [ 40/2639] eta: 2:10:33 lr: 3.741663744436163e-05 loss: 0.0671 (0.0789) time: 2.9320 data: 0.0083 max mem: 33370 +Epoch: [11] [ 50/2639] eta: 2:09:08 lr: 3.7412234882740875e-05 loss: 0.0671 (0.0783) time: 2.9346 data: 0.0081 max mem: 33370 +Epoch: [11] [ 60/2639] eta: 2:08:13 lr: 3.7407832263554876e-05 loss: 0.0643 (0.0776) time: 2.9196 data: 0.0082 max mem: 33370 +Epoch: [11] [ 70/2639] eta: 2:06:54 lr: 3.740342958679534e-05 loss: 0.0707 (0.0777) time: 2.8908 data: 0.0082 max mem: 33370 +Epoch: [11] [ 80/2639] eta: 2:06:14 lr: 3.739902685245399e-05 loss: 0.0707 (0.0764) time: 2.8892 data: 0.0080 max mem: 33370 +Epoch: [11] [ 90/2639] eta: 2:05:18 lr: 3.7394624060522545e-05 loss: 0.0576 (0.0758) time: 2.8985 data: 0.0086 max mem: 33370 +Epoch: [11] [ 100/2639] eta: 2:04:46 lr: 3.739022121099271e-05 loss: 0.0653 (0.0783) time: 2.9019 data: 0.0085 max mem: 33370 +Epoch: [11] [ 110/2639] eta: 2:04:30 lr: 3.7385818303856197e-05 loss: 0.0837 (0.0786) time: 2.9724 data: 0.0078 max mem: 33370 +Epoch: [11] [ 120/2639] eta: 2:04:05 lr: 3.738141533910471e-05 loss: 0.0645 (0.0768) time: 2.9923 data: 0.0077 max mem: 33370 +Epoch: [11] [ 130/2639] eta: 2:03:22 lr: 3.7377012316729964e-05 loss: 0.0699 (0.0770) time: 2.9316 data: 0.0075 max mem: 33370 +Epoch: [11] [ 140/2639] eta: 2:02:39 lr: 3.737260923672366e-05 loss: 0.0732 (0.0771) time: 2.8794 data: 0.0075 max mem: 33370 +Epoch: [11] [ 150/2639] eta: 2:02:08 lr: 3.7368206099077493e-05 loss: 0.0699 (0.0773) time: 2.9046 data: 0.0074 max mem: 33370 +Epoch: [11] [ 160/2639] eta: 2:01:38 lr: 3.736380290378316e-05 loss: 0.0674 (0.0763) time: 2.9404 data: 0.0075 max mem: 33370 +Epoch: [11] [ 170/2639] eta: 2:01:07 lr: 3.735939965083238e-05 loss: 0.0661 (0.0772) time: 2.9363 data: 0.0077 max mem: 33370 +Epoch: [11] [ 180/2639] eta: 2:00:33 lr: 3.735499634021682e-05 loss: 0.0787 (0.0776) time: 2.9208 data: 0.0079 max mem: 33370 +Epoch: [11] [ 190/2639] eta: 1:59:53 lr: 3.735059297192818e-05 loss: 0.0745 (0.0772) time: 2.8865 data: 0.0080 max mem: 33370 +Epoch: [11] [ 200/2639] eta: 1:59:19 lr: 3.734618954595816e-05 loss: 0.0652 (0.0773) time: 2.8783 data: 0.0080 max mem: 33370 +Epoch: [11] [ 210/2639] eta: 1:58:42 lr: 3.734178606229843e-05 loss: 0.0699 (0.0775) time: 2.8850 data: 0.0081 max mem: 33370 +Epoch: [11] [ 220/2639] eta: 1:58:11 lr: 3.733738252094069e-05 loss: 0.0634 (0.0772) time: 2.8911 data: 0.0079 max mem: 33370 +Epoch: [11] [ 230/2639] eta: 1:57:36 lr: 3.733297892187662e-05 loss: 0.0653 (0.0779) time: 2.8934 data: 0.0078 max mem: 33370 +Epoch: [11] [ 240/2639] eta: 1:57:08 lr: 3.732857526509789e-05 loss: 0.0722 (0.0776) time: 2.9133 data: 0.0079 max mem: 33370 +Epoch: [11] [ 250/2639] eta: 1:56:37 lr: 3.7324171550596195e-05 loss: 0.0670 (0.0770) time: 2.9283 data: 0.0082 max mem: 33370 +Epoch: [11] [ 260/2639] eta: 1:56:05 lr: 3.73197677783632e-05 loss: 0.0634 (0.0766) time: 2.9045 data: 0.0082 max mem: 33370 +Epoch: [11] [ 270/2639] eta: 1:55:31 lr: 3.731536394839058e-05 loss: 0.0656 (0.0766) time: 2.8855 data: 0.0082 max mem: 33370 +Epoch: [11] [ 280/2639] eta: 1:55:02 lr: 3.731096006067001e-05 loss: 0.0720 (0.0763) time: 2.9023 data: 0.0079 max mem: 33370 +Epoch: [11] [ 290/2639] eta: 1:54:29 lr: 3.7306556115193146e-05 loss: 0.0686 (0.0763) time: 2.9061 data: 0.0075 max mem: 33370 +Epoch: [11] [ 300/2639] eta: 1:53:58 lr: 3.730215211195168e-05 loss: 0.0665 (0.0760) time: 2.8890 data: 0.0077 max mem: 33370 +Epoch: [11] [ 310/2639] eta: 1:53:24 lr: 3.729774805093726e-05 loss: 0.0665 (0.0761) time: 2.8778 data: 0.0079 max mem: 33370 +Epoch: [11] [ 320/2639] eta: 1:52:51 lr: 3.7293343932141546e-05 loss: 0.0732 (0.0762) time: 2.8656 data: 0.0081 max mem: 33370 +Epoch: [11] [ 330/2639] eta: 1:52:25 lr: 3.7288939755556196e-05 loss: 0.0768 (0.0767) time: 2.9210 data: 0.0084 max mem: 33370 +Epoch: [11] [ 340/2639] eta: 1:52:01 lr: 3.728453552117288e-05 loss: 0.0605 (0.0766) time: 2.9819 data: 0.0081 max mem: 33370 +Epoch: [11] [ 350/2639] eta: 1:51:29 lr: 3.728013122898325e-05 loss: 0.0608 (0.0769) time: 2.9394 data: 0.0078 max mem: 33370 +Epoch: [11] [ 360/2639] eta: 1:50:57 lr: 3.727572687897895e-05 loss: 0.0626 (0.0767) time: 2.8768 data: 0.0080 max mem: 33370 +Epoch: [11] [ 370/2639] eta: 1:50:25 lr: 3.727132247115164e-05 loss: 0.0656 (0.0767) time: 2.8740 data: 0.0080 max mem: 33370 +Epoch: [11] [ 380/2639] eta: 1:49:58 lr: 3.7266918005492964e-05 loss: 0.0772 (0.0774) time: 2.9198 data: 0.0079 max mem: 33370 +Epoch: [11] [ 390/2639] eta: 1:49:27 lr: 3.726251348199457e-05 loss: 0.0778 (0.0776) time: 2.9277 data: 0.0083 max mem: 33370 +Epoch: [11] [ 400/2639] eta: 1:48:56 lr: 3.72581089006481e-05 loss: 0.0698 (0.0775) time: 2.8922 data: 0.0086 max mem: 33370 +Epoch: [11] [ 410/2639] eta: 1:48:22 lr: 3.725370426144519e-05 loss: 0.0665 (0.0772) time: 2.8548 data: 0.0086 max mem: 33370 +Epoch: [11] [ 420/2639] eta: 1:47:50 lr: 3.72492995643775e-05 loss: 0.0662 (0.0771) time: 2.8391 data: 0.0082 max mem: 33370 +Epoch: [11] [ 430/2639] eta: 1:47:21 lr: 3.724489480943665e-05 loss: 0.0673 (0.0772) time: 2.8914 data: 0.0081 max mem: 33370 +Epoch: [11] [ 440/2639] eta: 1:46:49 lr: 3.724048999661426e-05 loss: 0.0749 (0.0776) time: 2.8934 data: 0.0083 max mem: 33370 +Epoch: [11] [ 450/2639] eta: 1:46:20 lr: 3.7236085125901994e-05 loss: 0.0676 (0.0777) time: 2.8941 data: 0.0083 max mem: 33370 +Epoch: [11] [ 460/2639] eta: 1:45:52 lr: 3.7231680197291466e-05 loss: 0.0772 (0.0776) time: 2.9284 data: 0.0082 max mem: 33370 +Epoch: [11] [ 470/2639] eta: 1:45:22 lr: 3.7227275210774296e-05 loss: 0.0799 (0.0778) time: 2.9177 data: 0.0086 max mem: 33370 +Epoch: [11] [ 480/2639] eta: 1:44:51 lr: 3.7222870166342136e-05 loss: 0.0850 (0.0779) time: 2.8843 data: 0.0084 max mem: 33370 +Epoch: [11] [ 490/2639] eta: 1:44:20 lr: 3.721846506398658e-05 loss: 0.0717 (0.0784) time: 2.8687 data: 0.0081 max mem: 33370 +Epoch: [11] [ 500/2639] eta: 1:43:49 lr: 3.7214059903699256e-05 loss: 0.0643 (0.0781) time: 2.8700 data: 0.0081 max mem: 33370 +Epoch: [11] [ 510/2639] eta: 1:43:18 lr: 3.720965468547179e-05 loss: 0.0695 (0.0781) time: 2.8713 data: 0.0077 max mem: 33370 +Epoch: [11] [ 520/2639] eta: 1:42:50 lr: 3.72052494092958e-05 loss: 0.0714 (0.0781) time: 2.9069 data: 0.0080 max mem: 33370 +Epoch: [11] [ 530/2639] eta: 1:42:19 lr: 3.720084407516289e-05 loss: 0.0834 (0.0781) time: 2.8963 data: 0.0082 max mem: 33370 +Epoch: [11] [ 540/2639] eta: 1:41:48 lr: 3.7196438683064674e-05 loss: 0.0834 (0.0787) time: 2.8578 data: 0.0084 max mem: 33370 +Epoch: [11] [ 550/2639] eta: 1:41:22 lr: 3.719203323299276e-05 loss: 0.0771 (0.0790) time: 2.9277 data: 0.0087 max mem: 33370 +Epoch: [11] [ 560/2639] eta: 1:40:54 lr: 3.718762772493877e-05 loss: 0.0716 (0.0791) time: 2.9700 data: 0.0084 max mem: 33370 +Epoch: [11] [ 570/2639] eta: 1:40:24 lr: 3.718322215889428e-05 loss: 0.0615 (0.0788) time: 2.9193 data: 0.0082 max mem: 33370 +Epoch: [11] [ 580/2639] eta: 1:39:54 lr: 3.717881653485092e-05 loss: 0.0681 (0.0790) time: 2.8874 data: 0.0078 max mem: 33370 +Epoch: [11] [ 590/2639] eta: 1:39:26 lr: 3.7174410852800274e-05 loss: 0.0755 (0.0791) time: 2.9102 data: 0.0077 max mem: 33370 +Epoch: [11] [ 600/2639] eta: 1:38:56 lr: 3.7170005112733945e-05 loss: 0.0755 (0.0790) time: 2.9168 data: 0.0078 max mem: 33370 +Epoch: [11] [ 610/2639] eta: 1:38:25 lr: 3.716559931464352e-05 loss: 0.0636 (0.0790) time: 2.8702 data: 0.0080 max mem: 33370 +Epoch: [11] [ 620/2639] eta: 1:37:54 lr: 3.7161193458520605e-05 loss: 0.0615 (0.0791) time: 2.8566 data: 0.0081 max mem: 33370 +Epoch: [11] [ 630/2639] eta: 1:37:24 lr: 3.715678754435678e-05 loss: 0.0656 (0.0792) time: 2.8780 data: 0.0077 max mem: 33370 +Epoch: [11] [ 640/2639] eta: 1:36:54 lr: 3.715238157214365e-05 loss: 0.0746 (0.0792) time: 2.8753 data: 0.0079 max mem: 33370 +Epoch: [11] [ 650/2639] eta: 1:36:24 lr: 3.714797554187278e-05 loss: 0.0688 (0.0792) time: 2.8735 data: 0.0081 max mem: 33370 +Epoch: [11] [ 660/2639] eta: 1:35:56 lr: 3.714356945353576e-05 loss: 0.0662 (0.0792) time: 2.9095 data: 0.0086 max mem: 33370 +Epoch: [11] [ 670/2639] eta: 1:35:27 lr: 3.7139163307124176e-05 loss: 0.0663 (0.0789) time: 2.9269 data: 0.0089 max mem: 33370 +Epoch: [11] [ 680/2639] eta: 1:34:57 lr: 3.71347571026296e-05 loss: 0.0688 (0.0789) time: 2.9030 data: 0.0087 max mem: 33370 +Epoch: [11] [ 690/2639] eta: 1:34:26 lr: 3.7130350840043614e-05 loss: 0.0781 (0.0790) time: 2.8562 data: 0.0084 max mem: 33370 +Epoch: [11] [ 700/2639] eta: 1:33:56 lr: 3.7125944519357794e-05 loss: 0.0686 (0.0791) time: 2.8569 data: 0.0080 max mem: 33370 +Epoch: [11] [ 710/2639] eta: 1:33:26 lr: 3.7121538140563706e-05 loss: 0.0668 (0.0790) time: 2.8794 data: 0.0079 max mem: 33370 +Epoch: [11] [ 720/2639] eta: 1:32:58 lr: 3.7117131703652925e-05 loss: 0.0693 (0.0790) time: 2.9087 data: 0.0080 max mem: 33370 +Epoch: [11] [ 730/2639] eta: 1:32:29 lr: 3.7112725208617015e-05 loss: 0.0699 (0.0791) time: 2.9324 data: 0.0082 max mem: 33370 +Epoch: [11] [ 740/2639] eta: 1:32:00 lr: 3.710831865544754e-05 loss: 0.0623 (0.0789) time: 2.8963 data: 0.0082 max mem: 33370 +Epoch: [11] [ 750/2639] eta: 1:31:30 lr: 3.7103912044136056e-05 loss: 0.0674 (0.0791) time: 2.8876 data: 0.0083 max mem: 33370 +Epoch: [11] [ 760/2639] eta: 1:31:01 lr: 3.709950537467415e-05 loss: 0.0679 (0.0791) time: 2.8941 data: 0.0079 max mem: 33370 +Epoch: [11] [ 770/2639] eta: 1:30:32 lr: 3.709509864705335e-05 loss: 0.0694 (0.0791) time: 2.8988 data: 0.0075 max mem: 33370 +Epoch: [11] [ 780/2639] eta: 1:30:03 lr: 3.709069186126522e-05 loss: 0.0648 (0.0790) time: 2.9126 data: 0.0079 max mem: 33370 +Epoch: [11] [ 790/2639] eta: 1:29:34 lr: 3.7086285017301315e-05 loss: 0.0648 (0.0789) time: 2.9048 data: 0.0079 max mem: 33370 +Epoch: [11] [ 800/2639] eta: 1:29:04 lr: 3.7081878115153195e-05 loss: 0.0731 (0.0789) time: 2.8977 data: 0.0079 max mem: 33370 +Epoch: [11] [ 810/2639] eta: 1:28:36 lr: 3.70774711548124e-05 loss: 0.0689 (0.0788) time: 2.9109 data: 0.0081 max mem: 33370 +Epoch: [11] [ 820/2639] eta: 1:28:06 lr: 3.707306413627047e-05 loss: 0.0656 (0.0787) time: 2.8917 data: 0.0079 max mem: 33370 +Epoch: [11] [ 830/2639] eta: 1:27:37 lr: 3.7068657059518954e-05 loss: 0.0656 (0.0788) time: 2.8993 data: 0.0079 max mem: 33370 +Epoch: [11] [ 840/2639] eta: 1:27:08 lr: 3.70642499245494e-05 loss: 0.0613 (0.0787) time: 2.9178 data: 0.0081 max mem: 33370 +Epoch: [11] [ 850/2639] eta: 1:26:39 lr: 3.705984273135335e-05 loss: 0.0628 (0.0788) time: 2.9054 data: 0.0081 max mem: 33370 +Epoch: [11] [ 860/2639] eta: 1:26:10 lr: 3.7055435479922315e-05 loss: 0.0756 (0.0788) time: 2.9110 data: 0.0080 max mem: 33370 +Epoch: [11] [ 870/2639] eta: 1:25:41 lr: 3.7051028170247854e-05 loss: 0.0708 (0.0788) time: 2.9172 data: 0.0076 max mem: 33370 +Epoch: [11] [ 880/2639] eta: 1:25:13 lr: 3.70466208023215e-05 loss: 0.0677 (0.0785) time: 2.9304 data: 0.0079 max mem: 33370 +Epoch: [11] [ 890/2639] eta: 1:24:43 lr: 3.704221337613476e-05 loss: 0.0658 (0.0786) time: 2.9052 data: 0.0088 max mem: 33370 +Epoch: [11] [ 900/2639] eta: 1:24:13 lr: 3.7037805891679187e-05 loss: 0.0682 (0.0785) time: 2.8701 data: 0.0089 max mem: 33370 +Epoch: [11] [ 910/2639] eta: 1:23:44 lr: 3.703339834894629e-05 loss: 0.0642 (0.0784) time: 2.8905 data: 0.0086 max mem: 33370 +Epoch: [11] [ 920/2639] eta: 1:23:15 lr: 3.7028990747927606e-05 loss: 0.0661 (0.0784) time: 2.8901 data: 0.0083 max mem: 33370 +Epoch: [11] [ 930/2639] eta: 1:22:45 lr: 3.702458308861465e-05 loss: 0.0689 (0.0784) time: 2.8751 data: 0.0080 max mem: 33370 +Epoch: [11] [ 940/2639] eta: 1:22:17 lr: 3.702017537099891e-05 loss: 0.0745 (0.0785) time: 2.9073 data: 0.0082 max mem: 33370 +Epoch: [11] [ 950/2639] eta: 1:21:48 lr: 3.701576759507195e-05 loss: 0.0743 (0.0785) time: 2.9239 data: 0.0082 max mem: 33370 +Epoch: [11] [ 960/2639] eta: 1:21:20 lr: 3.701135976082525e-05 loss: 0.0726 (0.0785) time: 2.9397 data: 0.0080 max mem: 33370 +Epoch: [11] [ 970/2639] eta: 1:20:50 lr: 3.700695186825034e-05 loss: 0.0764 (0.0787) time: 2.9235 data: 0.0079 max mem: 33370 +Epoch: [11] [ 980/2639] eta: 1:20:21 lr: 3.700254391733873e-05 loss: 0.0826 (0.0786) time: 2.8942 data: 0.0080 max mem: 33370 +Epoch: [11] [ 990/2639] eta: 1:19:53 lr: 3.69981359080819e-05 loss: 0.0645 (0.0785) time: 2.9496 data: 0.0080 max mem: 33370 +Epoch: [11] [1000/2639] eta: 1:19:24 lr: 3.6993727840471374e-05 loss: 0.0710 (0.0785) time: 2.9468 data: 0.0084 max mem: 33370 +Epoch: [11] [1010/2639] eta: 1:18:55 lr: 3.698931971449866e-05 loss: 0.0802 (0.0788) time: 2.9119 data: 0.0084 max mem: 33370 +Epoch: [11] [1020/2639] eta: 1:18:26 lr: 3.6984911530155234e-05 loss: 0.0868 (0.0789) time: 2.9124 data: 0.0080 max mem: 33370 +Epoch: [11] [1030/2639] eta: 1:17:57 lr: 3.698050328743262e-05 loss: 0.0736 (0.0789) time: 2.9025 data: 0.0080 max mem: 33370 +Epoch: [11] [1040/2639] eta: 1:17:28 lr: 3.697609498632228e-05 loss: 0.0597 (0.0788) time: 2.9002 data: 0.0081 max mem: 33370 +Epoch: [11] [1050/2639] eta: 1:17:00 lr: 3.697168662681574e-05 loss: 0.0603 (0.0788) time: 2.9337 data: 0.0082 max mem: 33370 +Epoch: [11] [1060/2639] eta: 1:16:32 lr: 3.696727820890447e-05 loss: 0.0699 (0.0790) time: 2.9691 data: 0.0082 max mem: 33370 +Epoch: [11] [1070/2639] eta: 1:16:03 lr: 3.696286973257996e-05 loss: 0.0727 (0.0789) time: 2.9597 data: 0.0084 max mem: 33370 +Epoch: [11] [1080/2639] eta: 1:15:33 lr: 3.695846119783369e-05 loss: 0.0727 (0.0790) time: 2.9061 data: 0.0083 max mem: 33370 +Epoch: [11] [1090/2639] eta: 1:15:04 lr: 3.695405260465716e-05 loss: 0.0703 (0.0789) time: 2.8897 data: 0.0080 max mem: 33370 +Epoch: [11] [1100/2639] eta: 1:14:35 lr: 3.694964395304183e-05 loss: 0.0707 (0.0790) time: 2.9012 data: 0.0081 max mem: 33370 +Epoch: [11] [1110/2639] eta: 1:14:06 lr: 3.694523524297919e-05 loss: 0.0707 (0.0790) time: 2.8809 data: 0.0081 max mem: 33370 +Epoch: [11] [1120/2639] eta: 1:13:36 lr: 3.694082647446071e-05 loss: 0.0665 (0.0789) time: 2.8847 data: 0.0079 max mem: 33370 +Epoch: [11] [1130/2639] eta: 1:13:08 lr: 3.693641764747787e-05 loss: 0.0612 (0.0788) time: 2.9164 data: 0.0078 max mem: 33370 +Epoch: [11] [1140/2639] eta: 1:12:39 lr: 3.693200876202214e-05 loss: 0.0637 (0.0788) time: 2.9484 data: 0.0077 max mem: 33370 +Epoch: [11] [1150/2639] eta: 1:12:10 lr: 3.6927599818084965e-05 loss: 0.0685 (0.0788) time: 2.9351 data: 0.0081 max mem: 33370 +Epoch: [11] [1160/2639] eta: 1:11:41 lr: 3.692319081565784e-05 loss: 0.0645 (0.0787) time: 2.9193 data: 0.0081 max mem: 33370 +Epoch: [11] [1170/2639] eta: 1:11:12 lr: 3.6918781754732225e-05 loss: 0.0701 (0.0788) time: 2.9261 data: 0.0076 max mem: 33370 +Epoch: [11] [1180/2639] eta: 1:10:44 lr: 3.691437263529957e-05 loss: 0.0760 (0.0788) time: 2.9400 data: 0.0078 max mem: 33370 +Epoch: [11] [1190/2639] eta: 1:10:14 lr: 3.6909963457351336e-05 loss: 0.0849 (0.0789) time: 2.8969 data: 0.0080 max mem: 33370 +Epoch: [11] [1200/2639] eta: 1:09:45 lr: 3.690555422087898e-05 loss: 0.0729 (0.0788) time: 2.8790 data: 0.0079 max mem: 33370 +Epoch: [11] [1210/2639] eta: 1:09:16 lr: 3.690114492587396e-05 loss: 0.0617 (0.0788) time: 2.9313 data: 0.0082 max mem: 33370 +Epoch: [11] [1220/2639] eta: 1:08:47 lr: 3.6896735572327726e-05 loss: 0.0805 (0.0790) time: 2.9328 data: 0.0086 max mem: 33370 +Epoch: [11] [1230/2639] eta: 1:08:17 lr: 3.6892326160231736e-05 loss: 0.0729 (0.0789) time: 2.8707 data: 0.0084 max mem: 33370 +Epoch: [11] [1240/2639] eta: 1:07:48 lr: 3.688791668957741e-05 loss: 0.0660 (0.0789) time: 2.8403 data: 0.0079 max mem: 33370 +Epoch: [11] [1250/2639] eta: 1:07:18 lr: 3.688350716035622e-05 loss: 0.0766 (0.0793) time: 2.8603 data: 0.0078 max mem: 33370 +Epoch: [11] [1260/2639] eta: 1:06:49 lr: 3.6879097572559594e-05 loss: 0.0766 (0.0793) time: 2.8716 data: 0.0085 max mem: 33370 +Epoch: [11] [1270/2639] eta: 1:06:19 lr: 3.687468792617898e-05 loss: 0.0744 (0.0793) time: 2.8753 data: 0.0083 max mem: 33370 +Epoch: [11] [1280/2639] eta: 1:05:50 lr: 3.68702782212058e-05 loss: 0.0745 (0.0792) time: 2.8726 data: 0.0076 max mem: 33370 +Epoch: [11] [1290/2639] eta: 1:05:21 lr: 3.686586845763151e-05 loss: 0.0746 (0.0793) time: 2.8832 data: 0.0077 max mem: 33370 +Epoch: [11] [1300/2639] eta: 1:04:52 lr: 3.686145863544754e-05 loss: 0.0746 (0.0794) time: 2.9086 data: 0.0078 max mem: 33370 +Epoch: [11] [1310/2639] eta: 1:04:23 lr: 3.68570487546453e-05 loss: 0.0788 (0.0794) time: 2.9179 data: 0.0079 max mem: 33370 +Epoch: [11] [1320/2639] eta: 1:03:54 lr: 3.685263881521623e-05 loss: 0.0724 (0.0793) time: 2.9158 data: 0.0083 max mem: 33370 +Epoch: [11] [1330/2639] eta: 1:03:25 lr: 3.684822881715176e-05 loss: 0.0654 (0.0794) time: 2.9076 data: 0.0084 max mem: 33370 +Epoch: [11] [1340/2639] eta: 1:02:56 lr: 3.684381876044331e-05 loss: 0.0749 (0.0794) time: 2.9051 data: 0.0079 max mem: 33370 +Epoch: [11] [1350/2639] eta: 1:02:26 lr: 3.68394086450823e-05 loss: 0.0676 (0.0795) time: 2.8899 data: 0.0085 max mem: 33370 +Epoch: [11] [1360/2639] eta: 1:01:56 lr: 3.6834998471060145e-05 loss: 0.0676 (0.0795) time: 2.8553 data: 0.0087 max mem: 33370 +Epoch: [11] [1370/2639] eta: 1:01:27 lr: 3.683058823836826e-05 loss: 0.0851 (0.0797) time: 2.8537 data: 0.0078 max mem: 33370 +Epoch: [11] [1380/2639] eta: 1:00:57 lr: 3.682617794699806e-05 loss: 0.0914 (0.0797) time: 2.8573 data: 0.0079 max mem: 33370 +Epoch: [11] [1390/2639] eta: 1:00:29 lr: 3.682176759694097e-05 loss: 0.0700 (0.0798) time: 2.8868 data: 0.0083 max mem: 33370 +Epoch: [11] [1400/2639] eta: 0:59:59 lr: 3.681735718818838e-05 loss: 0.0700 (0.0798) time: 2.9055 data: 0.0087 max mem: 33370 +Epoch: [11] [1410/2639] eta: 0:59:30 lr: 3.6812946720731695e-05 loss: 0.0837 (0.0798) time: 2.8889 data: 0.0086 max mem: 33370 +Epoch: [11] [1420/2639] eta: 0:59:01 lr: 3.680853619456233e-05 loss: 0.0636 (0.0797) time: 2.9016 data: 0.0078 max mem: 33370 +Epoch: [11] [1430/2639] eta: 0:58:32 lr: 3.680412560967168e-05 loss: 0.0477 (0.0796) time: 2.8904 data: 0.0080 max mem: 33370 +Epoch: [11] [1440/2639] eta: 0:58:02 lr: 3.679971496605115e-05 loss: 0.0613 (0.0795) time: 2.8503 data: 0.0080 max mem: 33370 +Epoch: [11] [1450/2639] eta: 0:57:33 lr: 3.679530426369213e-05 loss: 0.0692 (0.0795) time: 2.8510 data: 0.0076 max mem: 33370 +Epoch: [11] [1460/2639] eta: 0:57:04 lr: 3.679089350258602e-05 loss: 0.0723 (0.0795) time: 2.9129 data: 0.0079 max mem: 33370 +Epoch: [11] [1470/2639] eta: 0:56:35 lr: 3.678648268272421e-05 loss: 0.0772 (0.0796) time: 2.9094 data: 0.0080 max mem: 33370 +Epoch: [11] [1480/2639] eta: 0:56:06 lr: 3.678207180409809e-05 loss: 0.0763 (0.0795) time: 2.9268 data: 0.0081 max mem: 33370 +Epoch: [11] [1490/2639] eta: 0:55:38 lr: 3.6777660866699036e-05 loss: 0.0652 (0.0795) time: 2.9794 data: 0.0085 max mem: 33370 +Epoch: [11] [1500/2639] eta: 0:55:09 lr: 3.677324987051844e-05 loss: 0.0745 (0.0796) time: 2.9455 data: 0.0084 max mem: 33370 +Epoch: [11] [1510/2639] eta: 0:54:39 lr: 3.67688388155477e-05 loss: 0.0824 (0.0797) time: 2.8794 data: 0.0078 max mem: 33370 +Epoch: [11] [1520/2639] eta: 0:54:11 lr: 3.676442770177818e-05 loss: 0.0801 (0.0797) time: 2.8918 data: 0.0078 max mem: 33370 +Epoch: [11] [1530/2639] eta: 0:53:41 lr: 3.6760016529201246e-05 loss: 0.0702 (0.0796) time: 2.9097 data: 0.0080 max mem: 33370 +Epoch: [11] [1540/2639] eta: 0:53:13 lr: 3.6755605297808285e-05 loss: 0.0702 (0.0796) time: 2.9175 data: 0.0077 max mem: 33370 +Epoch: [11] [1550/2639] eta: 0:52:44 lr: 3.675119400759068e-05 loss: 0.0739 (0.0797) time: 2.9532 data: 0.0079 max mem: 33370 +Epoch: [11] [1560/2639] eta: 0:52:15 lr: 3.6746782658539794e-05 loss: 0.0792 (0.0798) time: 2.9245 data: 0.0085 max mem: 33370 +Epoch: [11] [1570/2639] eta: 0:51:45 lr: 3.674237125064698e-05 loss: 0.0753 (0.0799) time: 2.8821 data: 0.0083 max mem: 33370 +Epoch: [11] [1580/2639] eta: 0:51:16 lr: 3.6737959783903616e-05 loss: 0.0791 (0.0799) time: 2.8722 data: 0.0084 max mem: 33370 +Epoch: [11] [1590/2639] eta: 0:50:47 lr: 3.6733548258301065e-05 loss: 0.0791 (0.0799) time: 2.8791 data: 0.0086 max mem: 33370 +Epoch: [11] [1600/2639] eta: 0:50:18 lr: 3.672913667383069e-05 loss: 0.0782 (0.0800) time: 2.8734 data: 0.0085 max mem: 33370 +Epoch: [11] [1610/2639] eta: 0:49:49 lr: 3.6724725030483834e-05 loss: 0.0765 (0.0799) time: 2.8767 data: 0.0083 max mem: 33370 +Epoch: [11] [1620/2639] eta: 0:49:19 lr: 3.672031332825187e-05 loss: 0.0757 (0.0800) time: 2.8839 data: 0.0078 max mem: 33370 +Epoch: [11] [1630/2639] eta: 0:48:50 lr: 3.671590156712615e-05 loss: 0.0798 (0.0800) time: 2.9072 data: 0.0082 max mem: 33370 +Epoch: [11] [1640/2639] eta: 0:48:21 lr: 3.6711489747098014e-05 loss: 0.0789 (0.0800) time: 2.9007 data: 0.0082 max mem: 33370 +Epoch: [11] [1650/2639] eta: 0:47:52 lr: 3.670707786815881e-05 loss: 0.0790 (0.0801) time: 2.8864 data: 0.0079 max mem: 33370 +Epoch: [11] [1660/2639] eta: 0:47:23 lr: 3.67026659302999e-05 loss: 0.0790 (0.0801) time: 2.8788 data: 0.0077 max mem: 33370 +Epoch: [11] [1670/2639] eta: 0:46:54 lr: 3.669825393351261e-05 loss: 0.0703 (0.0800) time: 2.8944 data: 0.0080 max mem: 33370 +Epoch: [11] [1680/2639] eta: 0:46:25 lr: 3.669384187778828e-05 loss: 0.0700 (0.0799) time: 2.9115 data: 0.0086 max mem: 33370 +Epoch: [11] [1690/2639] eta: 0:45:56 lr: 3.668942976311827e-05 loss: 0.0672 (0.0799) time: 2.8980 data: 0.0085 max mem: 33370 +Epoch: [11] [1700/2639] eta: 0:45:27 lr: 3.668501758949389e-05 loss: 0.0788 (0.0801) time: 2.8983 data: 0.0089 max mem: 33370 +Epoch: [11] [1710/2639] eta: 0:44:58 lr: 3.668060535690649e-05 loss: 0.0770 (0.0800) time: 2.8925 data: 0.0088 max mem: 33370 +Epoch: [11] [1720/2639] eta: 0:44:29 lr: 3.66761930653474e-05 loss: 0.0705 (0.0802) time: 2.9288 data: 0.0081 max mem: 33370 +Epoch: [11] [1730/2639] eta: 0:44:00 lr: 3.667178071480795e-05 loss: 0.0639 (0.0801) time: 2.9231 data: 0.0079 max mem: 33370 +Epoch: [11] [1740/2639] eta: 0:43:31 lr: 3.666736830527945e-05 loss: 0.0690 (0.0801) time: 2.8786 data: 0.0083 max mem: 33370 +Epoch: [11] [1750/2639] eta: 0:43:02 lr: 3.6662955836753235e-05 loss: 0.0731 (0.0800) time: 2.9342 data: 0.0083 max mem: 33370 +Epoch: [11] [1760/2639] eta: 0:42:33 lr: 3.665854330922063e-05 loss: 0.0616 (0.0800) time: 2.9551 data: 0.0083 max mem: 33370 +Epoch: [11] [1770/2639] eta: 0:42:04 lr: 3.6654130722672967e-05 loss: 0.0614 (0.0799) time: 2.9046 data: 0.0082 max mem: 33370 +Epoch: [11] [1780/2639] eta: 0:41:35 lr: 3.664971807710153e-05 loss: 0.0686 (0.0800) time: 2.9082 data: 0.0076 max mem: 33370 +Epoch: [11] [1790/2639] eta: 0:41:06 lr: 3.664530537249765e-05 loss: 0.0825 (0.0799) time: 2.9093 data: 0.0076 max mem: 33370 +Epoch: [11] [1800/2639] eta: 0:40:36 lr: 3.6640892608852644e-05 loss: 0.0778 (0.0799) time: 2.8746 data: 0.0077 max mem: 33370 +Epoch: [11] [1810/2639] eta: 0:40:07 lr: 3.663647978615782e-05 loss: 0.0705 (0.0799) time: 2.8889 data: 0.0077 max mem: 33370 +Epoch: [11] [1820/2639] eta: 0:39:39 lr: 3.663206690440447e-05 loss: 0.0709 (0.0800) time: 2.9370 data: 0.0074 max mem: 33370 +Epoch: [11] [1830/2639] eta: 0:39:10 lr: 3.662765396358392e-05 loss: 0.0818 (0.0800) time: 2.9284 data: 0.0072 max mem: 33370 +Epoch: [11] [1840/2639] eta: 0:38:40 lr: 3.662324096368746e-05 loss: 0.0851 (0.0801) time: 2.8875 data: 0.0079 max mem: 33370 +Epoch: [11] [1850/2639] eta: 0:38:11 lr: 3.661882790470639e-05 loss: 0.0851 (0.0801) time: 2.8880 data: 0.0081 max mem: 33370 +Epoch: [11] [1860/2639] eta: 0:37:42 lr: 3.6614414786632e-05 loss: 0.0740 (0.0801) time: 2.9045 data: 0.0076 max mem: 33370 +Epoch: [11] [1870/2639] eta: 0:37:13 lr: 3.66100016094556e-05 loss: 0.0738 (0.0801) time: 2.9184 data: 0.0077 max mem: 33370 +Epoch: [11] [1880/2639] eta: 0:36:44 lr: 3.660558837316848e-05 loss: 0.0715 (0.0801) time: 2.9111 data: 0.0078 max mem: 33370 +Epoch: [11] [1890/2639] eta: 0:36:15 lr: 3.660117507776192e-05 loss: 0.0696 (0.0801) time: 2.8893 data: 0.0075 max mem: 33370 +Epoch: [11] [1900/2639] eta: 0:35:46 lr: 3.6596761723227205e-05 loss: 0.0741 (0.0801) time: 2.8922 data: 0.0079 max mem: 33370 +Epoch: [11] [1910/2639] eta: 0:35:17 lr: 3.659234830955563e-05 loss: 0.0721 (0.0801) time: 2.9052 data: 0.0080 max mem: 33370 +Epoch: [11] [1920/2639] eta: 0:34:48 lr: 3.658793483673848e-05 loss: 0.0712 (0.0801) time: 2.9193 data: 0.0082 max mem: 33370 +Epoch: [11] [1930/2639] eta: 0:34:19 lr: 3.658352130476702e-05 loss: 0.0682 (0.0800) time: 2.9112 data: 0.0083 max mem: 33370 +Epoch: [11] [1940/2639] eta: 0:33:50 lr: 3.6579107713632545e-05 loss: 0.0791 (0.0802) time: 2.9079 data: 0.0076 max mem: 33370 +Epoch: [11] [1950/2639] eta: 0:33:21 lr: 3.6574694063326315e-05 loss: 0.0796 (0.0801) time: 2.9292 data: 0.0078 max mem: 33370 +Epoch: [11] [1960/2639] eta: 0:32:52 lr: 3.65702803538396e-05 loss: 0.0708 (0.0801) time: 2.9091 data: 0.0081 max mem: 33370 +Epoch: [11] [1970/2639] eta: 0:32:23 lr: 3.65658665851637e-05 loss: 0.0584 (0.0800) time: 2.8661 data: 0.0078 max mem: 33370 +Epoch: [11] [1980/2639] eta: 0:31:54 lr: 3.6561452757289855e-05 loss: 0.0604 (0.0800) time: 2.8887 data: 0.0078 max mem: 33370 +Epoch: [11] [1990/2639] eta: 0:31:25 lr: 3.655703887020933e-05 loss: 0.0644 (0.0799) time: 2.9293 data: 0.0080 max mem: 33370 +Epoch: [11] [2000/2639] eta: 0:30:56 lr: 3.655262492391339e-05 loss: 0.0677 (0.0799) time: 2.8958 data: 0.0079 max mem: 33370 +Epoch: [11] [2010/2639] eta: 0:30:26 lr: 3.654821091839331e-05 loss: 0.0655 (0.0799) time: 2.8680 data: 0.0080 max mem: 33370 +Epoch: [11] [2020/2639] eta: 0:29:57 lr: 3.6543796853640336e-05 loss: 0.0655 (0.0799) time: 2.8964 data: 0.0080 max mem: 33370 +Epoch: [11] [2030/2639] eta: 0:29:29 lr: 3.653938272964573e-05 loss: 0.0648 (0.0798) time: 2.9350 data: 0.0076 max mem: 33370 +Epoch: [11] [2040/2639] eta: 0:29:00 lr: 3.653496854640073e-05 loss: 0.0638 (0.0799) time: 2.9518 data: 0.0077 max mem: 33370 +Epoch: [11] [2050/2639] eta: 0:28:30 lr: 3.65305543038966e-05 loss: 0.0853 (0.0799) time: 2.9089 data: 0.0086 max mem: 33370 +Epoch: [11] [2060/2639] eta: 0:28:01 lr: 3.652614000212459e-05 loss: 0.0768 (0.0800) time: 2.8921 data: 0.0085 max mem: 33370 +Epoch: [11] [2070/2639] eta: 0:27:32 lr: 3.6521725641075925e-05 loss: 0.0771 (0.0800) time: 2.8782 data: 0.0081 max mem: 33370 +Epoch: [11] [2080/2639] eta: 0:27:03 lr: 3.651731122074187e-05 loss: 0.0839 (0.0800) time: 2.8494 data: 0.0080 max mem: 33370 +Epoch: [11] [2090/2639] eta: 0:26:34 lr: 3.651289674111366e-05 loss: 0.0770 (0.0800) time: 2.8785 data: 0.0074 max mem: 33370 +Epoch: [11] [2100/2639] eta: 0:26:05 lr: 3.650848220218253e-05 loss: 0.0624 (0.0799) time: 2.8971 data: 0.0074 max mem: 33370 +Epoch: [11] [2110/2639] eta: 0:25:36 lr: 3.6504067603939714e-05 loss: 0.0596 (0.0798) time: 2.9201 data: 0.0075 max mem: 33370 +Epoch: [11] [2120/2639] eta: 0:25:07 lr: 3.649965294637644e-05 loss: 0.0623 (0.0798) time: 2.9345 data: 0.0075 max mem: 33370 +Epoch: [11] [2130/2639] eta: 0:24:38 lr: 3.6495238229483966e-05 loss: 0.0562 (0.0797) time: 2.8928 data: 0.0075 max mem: 33370 +Epoch: [11] [2140/2639] eta: 0:24:09 lr: 3.649082345325349e-05 loss: 0.0584 (0.0797) time: 2.8851 data: 0.0076 max mem: 33370 +Epoch: [11] [2150/2639] eta: 0:23:40 lr: 3.648640861767625e-05 loss: 0.0627 (0.0797) time: 2.8919 data: 0.0078 max mem: 33370 +Epoch: [11] [2160/2639] eta: 0:23:11 lr: 3.6481993722743454e-05 loss: 0.0637 (0.0797) time: 2.9081 data: 0.0079 max mem: 33370 +Epoch: [11] [2170/2639] eta: 0:22:42 lr: 3.6477578768446346e-05 loss: 0.0754 (0.0798) time: 2.9046 data: 0.0077 max mem: 33370 +Epoch: [11] [2180/2639] eta: 0:22:13 lr: 3.647316375477614e-05 loss: 0.0821 (0.0798) time: 2.8790 data: 0.0073 max mem: 33370 +Epoch: [11] [2190/2639] eta: 0:21:43 lr: 3.646874868172405e-05 loss: 0.0769 (0.0798) time: 2.8867 data: 0.0076 max mem: 33370 +Epoch: [11] [2200/2639] eta: 0:21:15 lr: 3.646433354928127e-05 loss: 0.0724 (0.0798) time: 2.9251 data: 0.0079 max mem: 33370 +Epoch: [11] [2210/2639] eta: 0:20:46 lr: 3.645991835743903e-05 loss: 0.0735 (0.0798) time: 2.9429 data: 0.0074 max mem: 33370 +Epoch: [11] [2220/2639] eta: 0:20:16 lr: 3.6455503106188535e-05 loss: 0.0669 (0.0797) time: 2.8875 data: 0.0075 max mem: 33370 +Epoch: [11] [2230/2639] eta: 0:19:47 lr: 3.6451087795520996e-05 loss: 0.0806 (0.0798) time: 2.9001 data: 0.0079 max mem: 33370 +Epoch: [11] [2240/2639] eta: 0:19:18 lr: 3.6446672425427605e-05 loss: 0.0825 (0.0798) time: 2.9550 data: 0.0074 max mem: 33370 +Epoch: [11] [2250/2639] eta: 0:18:49 lr: 3.644225699589957e-05 loss: 0.0667 (0.0797) time: 2.9159 data: 0.0074 max mem: 33370 +Epoch: [11] [2260/2639] eta: 0:18:20 lr: 3.643784150692809e-05 loss: 0.0569 (0.0797) time: 2.9001 data: 0.0081 max mem: 33370 +Epoch: [11] [2270/2639] eta: 0:17:51 lr: 3.643342595850436e-05 loss: 0.0693 (0.0797) time: 2.9193 data: 0.0083 max mem: 33370 +Epoch: [11] [2280/2639] eta: 0:17:22 lr: 3.6429010350619565e-05 loss: 0.0701 (0.0797) time: 2.9037 data: 0.0080 max mem: 33370 +Epoch: [11] [2290/2639] eta: 0:16:53 lr: 3.64245946832649e-05 loss: 0.0654 (0.0797) time: 2.8982 data: 0.0078 max mem: 33370 +Epoch: [11] [2300/2639] eta: 0:16:24 lr: 3.642017895643157e-05 loss: 0.0683 (0.0797) time: 2.8985 data: 0.0074 max mem: 33370 +Epoch: [11] [2310/2639] eta: 0:15:55 lr: 3.641576317011074e-05 loss: 0.0691 (0.0797) time: 2.8954 data: 0.0076 max mem: 33370 +Epoch: [11] [2320/2639] eta: 0:15:26 lr: 3.64113473242936e-05 loss: 0.0677 (0.0797) time: 2.8973 data: 0.0077 max mem: 33370 +Epoch: [11] [2330/2639] eta: 0:14:57 lr: 3.640693141897133e-05 loss: 0.0677 (0.0797) time: 2.9114 data: 0.0080 max mem: 33370 +Epoch: [11] [2340/2639] eta: 0:14:28 lr: 3.640251545413511e-05 loss: 0.0832 (0.0797) time: 2.9206 data: 0.0080 max mem: 33370 +Epoch: [11] [2350/2639] eta: 0:13:59 lr: 3.6398099429776125e-05 loss: 0.0792 (0.0798) time: 2.8911 data: 0.0075 max mem: 33370 +Epoch: [11] [2360/2639] eta: 0:13:30 lr: 3.639368334588553e-05 loss: 0.0757 (0.0798) time: 2.8589 data: 0.0077 max mem: 33370 +Epoch: [11] [2370/2639] eta: 0:13:01 lr: 3.6389267202454505e-05 loss: 0.0687 (0.0798) time: 2.8777 data: 0.0075 max mem: 33370 +Epoch: [11] [2380/2639] eta: 0:12:32 lr: 3.638485099947422e-05 loss: 0.0710 (0.0798) time: 2.8761 data: 0.0073 max mem: 33370 +Epoch: [11] [2390/2639] eta: 0:12:03 lr: 3.638043473693584e-05 loss: 0.0703 (0.0798) time: 2.8856 data: 0.0073 max mem: 33370 +Epoch: [11] [2400/2639] eta: 0:11:34 lr: 3.637601841483053e-05 loss: 0.0703 (0.0799) time: 2.8805 data: 0.0076 max mem: 33370 +Epoch: [11] [2410/2639] eta: 0:11:05 lr: 3.637160203314944e-05 loss: 0.0783 (0.0799) time: 2.9011 data: 0.0081 max mem: 33370 +Epoch: [11] [2420/2639] eta: 0:10:35 lr: 3.6367185591883746e-05 loss: 0.0716 (0.0800) time: 2.9042 data: 0.0077 max mem: 33370 +Epoch: [11] [2430/2639] eta: 0:10:06 lr: 3.63627690910246e-05 loss: 0.0828 (0.0801) time: 2.9049 data: 0.0072 max mem: 33370 +Epoch: [11] [2440/2639] eta: 0:09:37 lr: 3.6358352530563145e-05 loss: 0.0861 (0.0801) time: 2.9365 data: 0.0076 max mem: 33370 +Epoch: [11] [2450/2639] eta: 0:09:08 lr: 3.6353935910490535e-05 loss: 0.0716 (0.0801) time: 2.9091 data: 0.0079 max mem: 33370 +Epoch: [11] [2460/2639] eta: 0:08:39 lr: 3.634951923079792e-05 loss: 0.0710 (0.0801) time: 2.8975 data: 0.0078 max mem: 33370 +Epoch: [11] [2470/2639] eta: 0:08:10 lr: 3.634510249147645e-05 loss: 0.0916 (0.0802) time: 2.9139 data: 0.0077 max mem: 33370 +Epoch: [11] [2480/2639] eta: 0:07:41 lr: 3.634068569251727e-05 loss: 0.0808 (0.0802) time: 2.8813 data: 0.0078 max mem: 33370 +Epoch: [11] [2490/2639] eta: 0:07:12 lr: 3.633626883391151e-05 loss: 0.0686 (0.0802) time: 2.8580 data: 0.0081 max mem: 33370 +Epoch: [11] [2500/2639] eta: 0:06:43 lr: 3.633185191565032e-05 loss: 0.0624 (0.0802) time: 2.9022 data: 0.0078 max mem: 33370 +Epoch: [11] [2510/2639] eta: 0:06:14 lr: 3.6327434937724826e-05 loss: 0.0698 (0.0801) time: 2.9334 data: 0.0075 max mem: 33370 +Epoch: [11] [2520/2639] eta: 0:05:45 lr: 3.632301790012617e-05 loss: 0.0703 (0.0801) time: 2.9273 data: 0.0076 max mem: 33370 +Epoch: [11] [2530/2639] eta: 0:05:16 lr: 3.631860080284547e-05 loss: 0.0698 (0.0801) time: 2.9136 data: 0.0076 max mem: 33370 +Epoch: [11] [2540/2639] eta: 0:04:47 lr: 3.631418364587386e-05 loss: 0.0698 (0.0800) time: 2.9324 data: 0.0074 max mem: 33370 +Epoch: [11] [2550/2639] eta: 0:04:18 lr: 3.630976642920248e-05 loss: 0.0623 (0.0800) time: 2.9324 data: 0.0076 max mem: 33370 +Epoch: [11] [2560/2639] eta: 0:03:49 lr: 3.6305349152822443e-05 loss: 0.0623 (0.0800) time: 2.8902 data: 0.0081 max mem: 33370 +Epoch: [11] [2570/2639] eta: 0:03:20 lr: 3.6300931816724856e-05 loss: 0.0640 (0.0799) time: 2.8818 data: 0.0075 max mem: 33370 +Epoch: [11] [2580/2639] eta: 0:02:51 lr: 3.6296514420900855e-05 loss: 0.0672 (0.0800) time: 2.9286 data: 0.0073 max mem: 33370 +Epoch: [11] [2590/2639] eta: 0:02:22 lr: 3.6292096965341556e-05 loss: 0.0756 (0.0801) time: 2.8736 data: 0.0077 max mem: 33370 +Epoch: [11] [2600/2639] eta: 0:01:53 lr: 3.628767945003806e-05 loss: 0.0793 (0.0802) time: 2.8168 data: 0.0080 max mem: 33370 +Epoch: [11] [2610/2639] eta: 0:01:24 lr: 3.628326187498149e-05 loss: 0.0787 (0.0802) time: 2.8590 data: 0.0078 max mem: 33370 +Epoch: [11] [2620/2639] eta: 0:00:55 lr: 3.627884424016294e-05 loss: 0.0772 (0.0802) time: 2.8691 data: 0.0074 max mem: 33370 +Epoch: [11] [2630/2639] eta: 0:00:26 lr: 3.627442654557353e-05 loss: 0.0793 (0.0802) time: 2.8889 data: 0.0076 max mem: 33370 +Epoch: [11] Total time: 2:07:43 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 2:29:06 time: 3.4773 data: 3.3851 max mem: 33370 +Test: [ 100/2573] eta: 0:04:35 time: 0.0777 data: 0.0014 max mem: 33370 +Test: [ 200/2573] eta: 0:03:48 time: 0.0799 data: 0.0015 max mem: 33370 +Test: [ 300/2573] eta: 0:03:25 time: 0.0816 data: 0.0015 max mem: 33370 +Test: [ 400/2573] eta: 0:03:11 time: 0.0814 data: 0.0013 max mem: 33370 +Test: [ 500/2573] eta: 0:02:59 time: 0.0802 data: 0.0014 max mem: 33370 +Test: [ 600/2573] eta: 0:02:48 time: 0.0802 data: 0.0015 max mem: 33370 +Test: [ 700/2573] eta: 0:02:39 time: 0.0799 data: 0.0014 max mem: 33370 +Test: [ 800/2573] eta: 0:02:30 time: 0.0835 data: 0.0014 max mem: 33370 +Test: [ 900/2573] eta: 0:02:21 time: 0.0808 data: 0.0015 max mem: 33370 +Test: [1000/2573] eta: 0:02:12 time: 0.0809 data: 0.0015 max mem: 33370 +Test: [1100/2573] eta: 0:02:03 time: 0.0815 data: 0.0016 max mem: 33370 +Test: [1200/2573] eta: 0:01:54 time: 0.0807 data: 0.0014 max mem: 33370 +Test: [1300/2573] eta: 0:01:46 time: 0.0801 data: 0.0015 max mem: 33370 +Test: [1400/2573] eta: 0:01:37 time: 0.0790 data: 0.0014 max mem: 33370 +Test: [1500/2573] eta: 0:01:29 time: 0.0815 data: 0.0014 max mem: 33370 +Test: [1600/2573] eta: 0:01:20 time: 0.0843 data: 0.0014 max mem: 33370 +Test: [1700/2573] eta: 0:01:12 time: 0.0791 data: 0.0016 max mem: 33370 +Test: [1800/2573] eta: 0:01:03 time: 0.0819 data: 0.0015 max mem: 33370 +Test: [1900/2573] eta: 0:00:55 time: 0.0791 data: 0.0015 max mem: 33370 +Test: [2000/2573] eta: 0:00:47 time: 0.0809 data: 0.0015 max mem: 33370 +Test: [2100/2573] eta: 0:00:38 time: 0.0835 data: 0.0014 max mem: 33370 +Test: [2200/2573] eta: 0:00:30 time: 0.0823 data: 0.0014 max mem: 33370 +Test: [2300/2573] eta: 0:00:22 time: 0.0815 data: 0.0014 max mem: 33370 +Test: [2400/2573] eta: 0:00:14 time: 0.0777 data: 0.0014 max mem: 33370 +Test: [2500/2573] eta: 0:00:05 time: 0.0833 data: 0.0015 max mem: 33370 +Test: Total time: 0:03:31 +Final results: +Mean IoU is 60.91 + + precision@0.5 = 68.59 + precision@0.6 = 62.25 + precision@0.7 = 54.58 + precision@0.8 = 42.67 + precision@0.9 = 20.08 + overall IoU = 58.82 + +Average object IoU 60.90551407767092 +Overall IoU 58.81847381591797 +Better epoch: 11 + +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [12] [ 0/2639] eta: 4:00:41 lr: 3.627045056933162e-05 loss: 0.0645 (0.0645) time: 5.4723 data: 2.2870 max mem: 33370 +Epoch: [12] [ 10/2639] eta: 2:20:55 lr: 3.6266032761153045e-05 loss: 0.0645 (0.0641) time: 3.2164 data: 0.2154 max mem: 33370 +Epoch: [12] [ 20/2639] eta: 2:14:14 lr: 3.62616148931778e-05 loss: 0.0657 (0.0737) time: 2.9556 data: 0.0077 max mem: 33370 +Epoch: [12] [ 30/2639] eta: 2:11:08 lr: 3.6257196965396984e-05 loss: 0.0641 (0.0728) time: 2.9054 data: 0.0079 max mem: 33370 +Epoch: [12] [ 40/2639] eta: 2:09:16 lr: 3.6252778977801674e-05 loss: 0.0641 (0.0812) time: 2.8893 data: 0.0083 max mem: 33370 +Epoch: [12] [ 50/2639] eta: 2:07:43 lr: 3.624836093038296e-05 loss: 0.0698 (0.0792) time: 2.8737 data: 0.0082 max mem: 33370 +Epoch: [12] [ 60/2639] eta: 2:06:22 lr: 3.6243942823131956e-05 loss: 0.0637 (0.0772) time: 2.8494 data: 0.0082 max mem: 33370 +Epoch: [12] [ 70/2639] eta: 2:05:39 lr: 3.6239524656039726e-05 loss: 0.0711 (0.0791) time: 2.8710 data: 0.0083 max mem: 33370 +Epoch: [12] [ 80/2639] eta: 2:04:50 lr: 3.623510642909736e-05 loss: 0.0633 (0.0765) time: 2.8872 data: 0.0082 max mem: 33370 +Epoch: [12] [ 90/2639] eta: 2:03:55 lr: 3.623068814229593e-05 loss: 0.0583 (0.0783) time: 2.8542 data: 0.0079 max mem: 33370 +Epoch: [12] [ 100/2639] eta: 2:03:15 lr: 3.622626979562652e-05 loss: 0.0664 (0.0783) time: 2.8544 data: 0.0080 max mem: 33370 +Epoch: [12] [ 110/2639] eta: 2:02:42 lr: 3.622185138908021e-05 loss: 0.0752 (0.0776) time: 2.8830 data: 0.0079 max mem: 33370 +Epoch: [12] [ 120/2639] eta: 2:02:14 lr: 3.621743292264808e-05 loss: 0.0701 (0.0768) time: 2.9055 data: 0.0079 max mem: 33370 +Epoch: [12] [ 130/2639] eta: 2:01:44 lr: 3.621301439632118e-05 loss: 0.0683 (0.0766) time: 2.9134 data: 0.0077 max mem: 33370 +Epoch: [12] [ 140/2639] eta: 2:01:09 lr: 3.620859581009058e-05 loss: 0.0559 (0.0752) time: 2.8934 data: 0.0077 max mem: 33370 +Epoch: [12] [ 150/2639] eta: 2:00:34 lr: 3.620417716394736e-05 loss: 0.0549 (0.0750) time: 2.8743 data: 0.0081 max mem: 33370 +Epoch: [12] [ 160/2639] eta: 2:00:00 lr: 3.6199758457882576e-05 loss: 0.0549 (0.0740) time: 2.8741 data: 0.0085 max mem: 33370 +Epoch: [12] [ 170/2639] eta: 1:59:30 lr: 3.619533969188728e-05 loss: 0.0601 (0.0739) time: 2.8863 data: 0.0082 max mem: 33370 +Epoch: [12] [ 180/2639] eta: 1:59:02 lr: 3.619092086595254e-05 loss: 0.0678 (0.0744) time: 2.9059 data: 0.0081 max mem: 33370 +Epoch: [12] [ 190/2639] eta: 1:58:39 lr: 3.618650198006941e-05 loss: 0.0674 (0.0741) time: 2.9308 data: 0.0080 max mem: 33370 +Epoch: [12] [ 200/2639] eta: 1:58:18 lr: 3.618208303422894e-05 loss: 0.0658 (0.0740) time: 2.9628 data: 0.0081 max mem: 33370 +Epoch: [12] [ 210/2639] eta: 1:57:49 lr: 3.617766402842218e-05 loss: 0.0614 (0.0732) time: 2.9439 data: 0.0083 max mem: 33370 +Epoch: [12] [ 220/2639] eta: 1:57:14 lr: 3.617324496264018e-05 loss: 0.0614 (0.0731) time: 2.8817 data: 0.0078 max mem: 33370 +Epoch: [12] [ 230/2639] eta: 1:56:41 lr: 3.616882583687398e-05 loss: 0.0597 (0.0723) time: 2.8633 data: 0.0075 max mem: 33370 +Epoch: [12] [ 240/2639] eta: 1:56:07 lr: 3.616440665111463e-05 loss: 0.0568 (0.0724) time: 2.8658 data: 0.0076 max mem: 33370 +Epoch: [12] [ 250/2639] eta: 1:55:34 lr: 3.615998740535316e-05 loss: 0.0588 (0.0718) time: 2.8580 data: 0.0075 max mem: 33370 +Epoch: [12] [ 260/2639] eta: 1:55:10 lr: 3.615556809958061e-05 loss: 0.0605 (0.0728) time: 2.9108 data: 0.0077 max mem: 33370 +Epoch: [12] [ 270/2639] eta: 1:54:42 lr: 3.615114873378803e-05 loss: 0.0762 (0.0725) time: 2.9381 data: 0.0082 max mem: 33370 +Epoch: [12] [ 280/2639] eta: 1:54:13 lr: 3.6146729307966424e-05 loss: 0.0677 (0.0728) time: 2.9078 data: 0.0078 max mem: 33370 +Epoch: [12] [ 290/2639] eta: 1:53:41 lr: 3.614230982210684e-05 loss: 0.0677 (0.0724) time: 2.8879 data: 0.0080 max mem: 33370 +Epoch: [12] [ 300/2639] eta: 1:53:07 lr: 3.6137890276200305e-05 loss: 0.0698 (0.0725) time: 2.8590 data: 0.0081 max mem: 33370 +Epoch: [12] [ 310/2639] eta: 1:52:40 lr: 3.613347067023783e-05 loss: 0.0685 (0.0723) time: 2.8833 data: 0.0079 max mem: 33370 +Epoch: [12] [ 320/2639] eta: 1:52:09 lr: 3.6129051004210464e-05 loss: 0.0602 (0.0721) time: 2.8961 data: 0.0082 max mem: 33370 +Epoch: [12] [ 330/2639] eta: 1:51:44 lr: 3.61246312781092e-05 loss: 0.0632 (0.0720) time: 2.9193 data: 0.0082 max mem: 33370 +Epoch: [12] [ 340/2639] eta: 1:51:19 lr: 3.612021149192506e-05 loss: 0.0685 (0.0720) time: 2.9660 data: 0.0082 max mem: 33370 +Epoch: [12] [ 350/2639] eta: 1:50:49 lr: 3.611579164564907e-05 loss: 0.0755 (0.0725) time: 2.9237 data: 0.0084 max mem: 33370 +Epoch: [12] [ 360/2639] eta: 1:50:18 lr: 3.6111371739272225e-05 loss: 0.0732 (0.0726) time: 2.8786 data: 0.0084 max mem: 33370 +Epoch: [12] [ 370/2639] eta: 1:49:50 lr: 3.6106951772785554e-05 loss: 0.0654 (0.0729) time: 2.9010 data: 0.0089 max mem: 33370 +Epoch: [12] [ 380/2639] eta: 1:49:21 lr: 3.610253174618004e-05 loss: 0.0654 (0.0729) time: 2.9146 data: 0.0084 max mem: 33370 +Epoch: [12] [ 390/2639] eta: 1:48:49 lr: 3.60981116594467e-05 loss: 0.0648 (0.0729) time: 2.8821 data: 0.0076 max mem: 33370 +Epoch: [12] [ 400/2639] eta: 1:48:16 lr: 3.609369151257655e-05 loss: 0.0563 (0.0726) time: 2.8465 data: 0.0077 max mem: 33370 +Epoch: [12] [ 410/2639] eta: 1:47:46 lr: 3.6089271305560564e-05 loss: 0.0563 (0.0725) time: 2.8524 data: 0.0078 max mem: 33370 +Epoch: [12] [ 420/2639] eta: 1:47:13 lr: 3.6084851038389746e-05 loss: 0.0704 (0.0726) time: 2.8551 data: 0.0081 max mem: 33370 +Epoch: [12] [ 430/2639] eta: 1:46:45 lr: 3.6080430711055085e-05 loss: 0.0704 (0.0726) time: 2.8715 data: 0.0084 max mem: 33370 +Epoch: [12] [ 440/2639] eta: 1:46:16 lr: 3.607601032354759e-05 loss: 0.0577 (0.0726) time: 2.9079 data: 0.0082 max mem: 33370 +Epoch: [12] [ 450/2639] eta: 1:45:48 lr: 3.607158987585823e-05 loss: 0.0617 (0.0726) time: 2.9106 data: 0.0079 max mem: 33370 +Epoch: [12] [ 460/2639] eta: 1:45:19 lr: 3.6067169367978e-05 loss: 0.0603 (0.0724) time: 2.9048 data: 0.0082 max mem: 33370 +Epoch: [12] [ 470/2639] eta: 1:44:52 lr: 3.6062748799897875e-05 loss: 0.0583 (0.0728) time: 2.9232 data: 0.0079 max mem: 33370 +Epoch: [12] [ 480/2639] eta: 1:44:19 lr: 3.605832817160885e-05 loss: 0.0702 (0.0729) time: 2.8864 data: 0.0077 max mem: 33370 +Epoch: [12] [ 490/2639] eta: 1:43:51 lr: 3.6053907483101904e-05 loss: 0.0788 (0.0733) time: 2.8641 data: 0.0080 max mem: 33370 +Epoch: [12] [ 500/2639] eta: 1:43:21 lr: 3.6049486734367986e-05 loss: 0.0897 (0.0735) time: 2.8937 data: 0.0082 max mem: 33370 +Epoch: [12] [ 510/2639] eta: 1:42:50 lr: 3.60450659253981e-05 loss: 0.0770 (0.0734) time: 2.8721 data: 0.0082 max mem: 33370 +Epoch: [12] [ 520/2639] eta: 1:42:19 lr: 3.6040645056183206e-05 loss: 0.0591 (0.0733) time: 2.8503 data: 0.0083 max mem: 33370 +Epoch: [12] [ 530/2639] eta: 1:41:50 lr: 3.603622412671426e-05 loss: 0.0587 (0.0733) time: 2.8696 data: 0.0085 max mem: 33370 +Epoch: [12] [ 540/2639] eta: 1:41:25 lr: 3.603180313698224e-05 loss: 0.0724 (0.0735) time: 2.9472 data: 0.0082 max mem: 33370 +Epoch: [12] [ 550/2639] eta: 1:40:58 lr: 3.6027382086978104e-05 loss: 0.0664 (0.0735) time: 2.9785 data: 0.0080 max mem: 33370 +Epoch: [12] [ 560/2639] eta: 1:40:28 lr: 3.602296097669281e-05 loss: 0.0649 (0.0737) time: 2.9118 data: 0.0081 max mem: 33370 +Epoch: [12] [ 570/2639] eta: 1:39:58 lr: 3.6018539806117327e-05 loss: 0.0804 (0.0739) time: 2.8651 data: 0.0080 max mem: 33370 +Epoch: [12] [ 580/2639] eta: 1:39:30 lr: 3.60141185752426e-05 loss: 0.0691 (0.0738) time: 2.9072 data: 0.0080 max mem: 33370 +Epoch: [12] [ 590/2639] eta: 1:39:01 lr: 3.600969728405958e-05 loss: 0.0585 (0.0739) time: 2.9224 data: 0.0080 max mem: 33370 +Epoch: [12] [ 600/2639] eta: 1:38:32 lr: 3.6005275932559216e-05 loss: 0.0650 (0.0739) time: 2.8961 data: 0.0087 max mem: 33370 +Epoch: [12] [ 610/2639] eta: 1:38:02 lr: 3.600085452073247e-05 loss: 0.0650 (0.0739) time: 2.8824 data: 0.0086 max mem: 33370 +Epoch: [12] [ 620/2639] eta: 1:37:34 lr: 3.599643304857027e-05 loss: 0.0594 (0.0739) time: 2.8983 data: 0.0078 max mem: 33370 +Epoch: [12] [ 630/2639] eta: 1:37:05 lr: 3.5992011516063565e-05 loss: 0.0634 (0.0740) time: 2.9082 data: 0.0078 max mem: 33370 +Epoch: [12] [ 640/2639] eta: 1:36:37 lr: 3.5987589923203284e-05 loss: 0.0814 (0.0742) time: 2.9072 data: 0.0081 max mem: 33370 +Epoch: [12] [ 650/2639] eta: 1:36:08 lr: 3.5983168269980385e-05 loss: 0.0700 (0.0743) time: 2.9117 data: 0.0083 max mem: 33370 +Epoch: [12] [ 660/2639] eta: 1:35:39 lr: 3.597874655638578e-05 loss: 0.0676 (0.0743) time: 2.9104 data: 0.0083 max mem: 33370 +Epoch: [12] [ 670/2639] eta: 1:35:10 lr: 3.597432478241041e-05 loss: 0.0575 (0.0742) time: 2.9043 data: 0.0083 max mem: 33370 +Epoch: [12] [ 680/2639] eta: 1:34:40 lr: 3.5969902948045206e-05 loss: 0.0538 (0.0740) time: 2.8889 data: 0.0083 max mem: 33370 +Epoch: [12] [ 690/2639] eta: 1:34:12 lr: 3.59654810532811e-05 loss: 0.0699 (0.0742) time: 2.9128 data: 0.0082 max mem: 33370 +Epoch: [12] [ 700/2639] eta: 1:33:43 lr: 3.5961059098109e-05 loss: 0.0699 (0.0740) time: 2.9070 data: 0.0082 max mem: 33370 +Epoch: [12] [ 710/2639] eta: 1:33:14 lr: 3.595663708251984e-05 loss: 0.0599 (0.0739) time: 2.8983 data: 0.0080 max mem: 33370 +Epoch: [12] [ 720/2639] eta: 1:32:45 lr: 3.595221500650453e-05 loss: 0.0620 (0.0738) time: 2.9012 data: 0.0079 max mem: 33370 +Epoch: [12] [ 730/2639] eta: 1:32:16 lr: 3.594779287005399e-05 loss: 0.0681 (0.0738) time: 2.8862 data: 0.0081 max mem: 33370 +Epoch: [12] [ 740/2639] eta: 1:31:47 lr: 3.594337067315913e-05 loss: 0.0589 (0.0739) time: 2.9043 data: 0.0084 max mem: 33370 +Epoch: [12] [ 750/2639] eta: 1:31:18 lr: 3.5938948415810866e-05 loss: 0.0662 (0.0741) time: 2.9060 data: 0.0079 max mem: 33370 +Epoch: [12] [ 760/2639] eta: 1:30:51 lr: 3.59345260980001e-05 loss: 0.0679 (0.0743) time: 2.9410 data: 0.0081 max mem: 33370 +Epoch: [12] [ 770/2639] eta: 1:30:24 lr: 3.593010371971775e-05 loss: 0.0654 (0.0743) time: 2.9946 data: 0.0083 max mem: 33370 +Epoch: [12] [ 780/2639] eta: 1:29:55 lr: 3.592568128095471e-05 loss: 0.0673 (0.0743) time: 2.9481 data: 0.0078 max mem: 33370 +Epoch: [12] [ 790/2639] eta: 1:29:25 lr: 3.5921258781701875e-05 loss: 0.0723 (0.0748) time: 2.8828 data: 0.0080 max mem: 33370 +Epoch: [12] [ 800/2639] eta: 1:28:55 lr: 3.591683622195014e-05 loss: 0.0729 (0.0748) time: 2.8569 data: 0.0085 max mem: 33370 +Epoch: [12] [ 810/2639] eta: 1:28:25 lr: 3.591241360169042e-05 loss: 0.0659 (0.0748) time: 2.8576 data: 0.0084 max mem: 33370 +Epoch: [12] [ 820/2639] eta: 1:27:57 lr: 3.590799092091359e-05 loss: 0.0659 (0.0747) time: 2.8950 data: 0.0082 max mem: 33370 +Epoch: [12] [ 830/2639] eta: 1:27:28 lr: 3.590356817961055e-05 loss: 0.0602 (0.0745) time: 2.9154 data: 0.0084 max mem: 33370 +Epoch: [12] [ 840/2639] eta: 1:26:59 lr: 3.5899145377772174e-05 loss: 0.0607 (0.0744) time: 2.9073 data: 0.0080 max mem: 33370 +Epoch: [12] [ 850/2639] eta: 1:26:29 lr: 3.5894722515389354e-05 loss: 0.0613 (0.0743) time: 2.8829 data: 0.0080 max mem: 33370 +Epoch: [12] [ 860/2639] eta: 1:25:59 lr: 3.589029959245299e-05 loss: 0.0638 (0.0742) time: 2.8560 data: 0.0082 max mem: 33370 +Epoch: [12] [ 870/2639] eta: 1:25:30 lr: 3.588587660895393e-05 loss: 0.0564 (0.0741) time: 2.8622 data: 0.0079 max mem: 33370 +Epoch: [12] [ 880/2639] eta: 1:25:02 lr: 3.5881453564883064e-05 loss: 0.0568 (0.0741) time: 2.9293 data: 0.0081 max mem: 33370 +Epoch: [12] [ 890/2639] eta: 1:24:35 lr: 3.587703046023126e-05 loss: 0.0596 (0.0741) time: 2.9926 data: 0.0081 max mem: 33370 +Epoch: [12] [ 900/2639] eta: 1:24:08 lr: 3.5872607294989414e-05 loss: 0.0618 (0.0740) time: 2.9862 data: 0.0083 max mem: 33370 +Epoch: [12] [ 910/2639] eta: 1:23:39 lr: 3.586818406914837e-05 loss: 0.0609 (0.0740) time: 2.9551 data: 0.0085 max mem: 33370 +Epoch: [12] [ 920/2639] eta: 1:23:11 lr: 3.5863760782699e-05 loss: 0.0653 (0.0739) time: 2.9490 data: 0.0080 max mem: 33370 +Epoch: [12] [ 930/2639] eta: 1:22:43 lr: 3.585933743563216e-05 loss: 0.0652 (0.0738) time: 2.9611 data: 0.0084 max mem: 33370 +Epoch: [12] [ 940/2639] eta: 1:22:15 lr: 3.585491402793873e-05 loss: 0.0610 (0.0736) time: 2.9442 data: 0.0082 max mem: 33370 +Epoch: [12] [ 950/2639] eta: 1:21:46 lr: 3.585049055960955e-05 loss: 0.0610 (0.0737) time: 2.9181 data: 0.0077 max mem: 33370 +Epoch: [12] [ 960/2639] eta: 1:21:16 lr: 3.584606703063549e-05 loss: 0.0754 (0.0737) time: 2.8952 data: 0.0078 max mem: 33370 +Epoch: [12] [ 970/2639] eta: 1:20:47 lr: 3.58416434410074e-05 loss: 0.0640 (0.0736) time: 2.8908 data: 0.0075 max mem: 33370 +Epoch: [12] [ 980/2639] eta: 1:20:19 lr: 3.583721979071613e-05 loss: 0.0640 (0.0737) time: 2.9246 data: 0.0075 max mem: 33370 +Epoch: [12] [ 990/2639] eta: 1:19:49 lr: 3.583279607975251e-05 loss: 0.0643 (0.0738) time: 2.8974 data: 0.0077 max mem: 33370 +Epoch: [12] [1000/2639] eta: 1:19:20 lr: 3.58283723081074e-05 loss: 0.0584 (0.0737) time: 2.8772 data: 0.0081 max mem: 33370 +Epoch: [12] [1010/2639] eta: 1:18:51 lr: 3.582394847577165e-05 loss: 0.0587 (0.0738) time: 2.9045 data: 0.0084 max mem: 33370 +Epoch: [12] [1020/2639] eta: 1:18:21 lr: 3.58195245827361e-05 loss: 0.0786 (0.0738) time: 2.8698 data: 0.0082 max mem: 33370 +Epoch: [12] [1030/2639] eta: 1:17:52 lr: 3.581510062899157e-05 loss: 0.0766 (0.0738) time: 2.8731 data: 0.0080 max mem: 33370 +Epoch: [12] [1040/2639] eta: 1:17:22 lr: 3.58106766145289e-05 loss: 0.0709 (0.0738) time: 2.9012 data: 0.0079 max mem: 33370 +Epoch: [12] [1050/2639] eta: 1:16:53 lr: 3.580625253933893e-05 loss: 0.0635 (0.0737) time: 2.8818 data: 0.0078 max mem: 33370 +Epoch: [12] [1060/2639] eta: 1:16:23 lr: 3.580182840341248e-05 loss: 0.0628 (0.0738) time: 2.8614 data: 0.0079 max mem: 33370 +Epoch: [12] [1070/2639] eta: 1:15:54 lr: 3.5797404206740395e-05 loss: 0.0629 (0.0738) time: 2.8767 data: 0.0079 max mem: 33370 +Epoch: [12] [1080/2639] eta: 1:15:24 lr: 3.5792979949313474e-05 loss: 0.0637 (0.0738) time: 2.8603 data: 0.0078 max mem: 33370 +Epoch: [12] [1090/2639] eta: 1:14:54 lr: 3.578855563112255e-05 loss: 0.0685 (0.0739) time: 2.8419 data: 0.0081 max mem: 33370 +Epoch: [12] [1100/2639] eta: 1:14:25 lr: 3.578413125215844e-05 loss: 0.0729 (0.0739) time: 2.8717 data: 0.0084 max mem: 33370 +Epoch: [12] [1110/2639] eta: 1:13:56 lr: 3.5779706812411975e-05 loss: 0.0703 (0.0738) time: 2.8849 data: 0.0082 max mem: 33370 +Epoch: [12] [1120/2639] eta: 1:13:27 lr: 3.577528231187395e-05 loss: 0.0596 (0.0737) time: 2.8992 data: 0.0078 max mem: 33370 +Epoch: [12] [1130/2639] eta: 1:12:57 lr: 3.5770857750535175e-05 loss: 0.0651 (0.0737) time: 2.8787 data: 0.0077 max mem: 33370 +Epoch: [12] [1140/2639] eta: 1:12:29 lr: 3.5766433128386465e-05 loss: 0.0656 (0.0736) time: 2.8947 data: 0.0080 max mem: 33370 +Epoch: [12] [1150/2639] eta: 1:11:59 lr: 3.576200844541863e-05 loss: 0.0656 (0.0736) time: 2.9132 data: 0.0083 max mem: 33370 +Epoch: [12] [1160/2639] eta: 1:11:30 lr: 3.575758370162246e-05 loss: 0.0627 (0.0735) time: 2.8787 data: 0.0080 max mem: 33370 +Epoch: [12] [1170/2639] eta: 1:11:02 lr: 3.575315889698876e-05 loss: 0.0754 (0.0736) time: 2.9129 data: 0.0078 max mem: 33370 +Epoch: [12] [1180/2639] eta: 1:10:33 lr: 3.5748734031508337e-05 loss: 0.0665 (0.0737) time: 2.9433 data: 0.0079 max mem: 33370 +Epoch: [12] [1190/2639] eta: 1:10:04 lr: 3.574430910517198e-05 loss: 0.0539 (0.0736) time: 2.9171 data: 0.0078 max mem: 33370 +Epoch: [12] [1200/2639] eta: 1:09:36 lr: 3.5739884117970476e-05 loss: 0.0539 (0.0735) time: 2.9308 data: 0.0075 max mem: 33370 +Epoch: [12] [1210/2639] eta: 1:09:07 lr: 3.5735459069894616e-05 loss: 0.0624 (0.0736) time: 2.9328 data: 0.0075 max mem: 33370 +Epoch: [12] [1220/2639] eta: 1:08:38 lr: 3.5731033960935186e-05 loss: 0.0759 (0.0738) time: 2.9027 data: 0.0076 max mem: 33370 +Epoch: [12] [1230/2639] eta: 1:08:08 lr: 3.5726608791082985e-05 loss: 0.0759 (0.0738) time: 2.8907 data: 0.0078 max mem: 33370 +Epoch: [12] [1240/2639] eta: 1:07:40 lr: 3.572218356032878e-05 loss: 0.0685 (0.0741) time: 2.8944 data: 0.0082 max mem: 33370 +Epoch: [12] [1250/2639] eta: 1:07:10 lr: 3.571775826866335e-05 loss: 0.0740 (0.0742) time: 2.8989 data: 0.0081 max mem: 33370 +Epoch: [12] [1260/2639] eta: 1:06:41 lr: 3.5713332916077466e-05 loss: 0.0688 (0.0741) time: 2.8972 data: 0.0077 max mem: 33370 +Epoch: [12] [1270/2639] eta: 1:06:12 lr: 3.570890750256192e-05 loss: 0.0679 (0.0741) time: 2.8941 data: 0.0078 max mem: 33370 +Epoch: [12] [1280/2639] eta: 1:05:43 lr: 3.570448202810747e-05 loss: 0.0663 (0.0740) time: 2.8640 data: 0.0080 max mem: 33370 +Epoch: [12] [1290/2639] eta: 1:05:13 lr: 3.570005649270488e-05 loss: 0.0714 (0.0740) time: 2.8543 data: 0.0079 max mem: 33370 +Epoch: [12] [1300/2639] eta: 1:04:44 lr: 3.569563089634492e-05 loss: 0.0714 (0.0740) time: 2.8743 data: 0.0079 max mem: 33370 +Epoch: [12] [1310/2639] eta: 1:04:15 lr: 3.569120523901836e-05 loss: 0.0711 (0.0740) time: 2.8909 data: 0.0082 max mem: 33370 +Epoch: [12] [1320/2639] eta: 1:03:46 lr: 3.568677952071596e-05 loss: 0.0680 (0.0742) time: 2.8872 data: 0.0081 max mem: 33370 +Epoch: [12] [1330/2639] eta: 1:03:16 lr: 3.568235374142847e-05 loss: 0.0658 (0.0741) time: 2.8637 data: 0.0079 max mem: 33370 +Epoch: [12] [1340/2639] eta: 1:02:47 lr: 3.567792790114664e-05 loss: 0.0671 (0.0741) time: 2.8640 data: 0.0078 max mem: 33370 +Epoch: [12] [1350/2639] eta: 1:02:18 lr: 3.567350199986123e-05 loss: 0.0604 (0.0740) time: 2.8727 data: 0.0075 max mem: 33370 +Epoch: [12] [1360/2639] eta: 1:01:48 lr: 3.566907603756299e-05 loss: 0.0604 (0.0740) time: 2.8661 data: 0.0083 max mem: 33370 +Epoch: [12] [1370/2639] eta: 1:01:19 lr: 3.566465001424267e-05 loss: 0.0689 (0.0740) time: 2.8709 data: 0.0084 max mem: 33370 +Epoch: [12] [1380/2639] eta: 1:00:50 lr: 3.566022392989101e-05 loss: 0.0689 (0.0740) time: 2.9037 data: 0.0077 max mem: 33370 +Epoch: [12] [1390/2639] eta: 1:00:20 lr: 3.5655797784498744e-05 loss: 0.0631 (0.0739) time: 2.8670 data: 0.0078 max mem: 33370 +Epoch: [12] [1400/2639] eta: 0:59:51 lr: 3.565137157805663e-05 loss: 0.0602 (0.0739) time: 2.8238 data: 0.0081 max mem: 33370 +Epoch: [12] [1410/2639] eta: 0:59:22 lr: 3.564694531055538e-05 loss: 0.0645 (0.0738) time: 2.8853 data: 0.0081 max mem: 33370 +Epoch: [12] [1420/2639] eta: 0:58:53 lr: 3.564251898198573e-05 loss: 0.0615 (0.0737) time: 2.9096 data: 0.0078 max mem: 33370 +Epoch: [12] [1430/2639] eta: 0:58:24 lr: 3.563809259233843e-05 loss: 0.0510 (0.0737) time: 2.8735 data: 0.0078 max mem: 33370 +Epoch: [12] [1440/2639] eta: 0:57:54 lr: 3.563366614160421e-05 loss: 0.0583 (0.0736) time: 2.8541 data: 0.0083 max mem: 33370 +Epoch: [12] [1450/2639] eta: 0:57:25 lr: 3.562923962977377e-05 loss: 0.0663 (0.0736) time: 2.8546 data: 0.0084 max mem: 33370 +Epoch: [12] [1460/2639] eta: 0:56:56 lr: 3.562481305683785e-05 loss: 0.0711 (0.0736) time: 2.8810 data: 0.0081 max mem: 33370 +Epoch: [12] [1470/2639] eta: 0:56:27 lr: 3.5620386422787155e-05 loss: 0.0511 (0.0735) time: 2.9097 data: 0.0077 max mem: 33370 +Epoch: [12] [1480/2639] eta: 0:55:58 lr: 3.561595972761242e-05 loss: 0.0568 (0.0736) time: 2.8957 data: 0.0075 max mem: 33370 +Epoch: [12] [1490/2639] eta: 0:55:29 lr: 3.561153297130436e-05 loss: 0.0647 (0.0735) time: 2.8914 data: 0.0076 max mem: 33370 +Epoch: [12] [1500/2639] eta: 0:55:00 lr: 3.560710615385367e-05 loss: 0.0682 (0.0736) time: 2.9034 data: 0.0076 max mem: 33370 +Epoch: [12] [1510/2639] eta: 0:54:32 lr: 3.560267927525107e-05 loss: 0.0768 (0.0736) time: 2.9161 data: 0.0079 max mem: 33370 +Epoch: [12] [1520/2639] eta: 0:54:03 lr: 3.559825233548726e-05 loss: 0.0660 (0.0736) time: 2.9376 data: 0.0077 max mem: 33370 +Epoch: [12] [1530/2639] eta: 0:53:34 lr: 3.5593825334552955e-05 loss: 0.0678 (0.0737) time: 2.9447 data: 0.0079 max mem: 33370 +Epoch: [12] [1540/2639] eta: 0:53:05 lr: 3.5589398272438853e-05 loss: 0.0694 (0.0736) time: 2.9089 data: 0.0083 max mem: 33370 +Epoch: [12] [1550/2639] eta: 0:52:36 lr: 3.558497114913564e-05 loss: 0.0635 (0.0737) time: 2.8986 data: 0.0081 max mem: 33370 +Epoch: [12] [1560/2639] eta: 0:52:07 lr: 3.558054396463402e-05 loss: 0.0710 (0.0737) time: 2.8764 data: 0.0082 max mem: 33370 +Epoch: [12] [1570/2639] eta: 0:51:38 lr: 3.557611671892469e-05 loss: 0.0710 (0.0738) time: 2.8880 data: 0.0079 max mem: 33370 +Epoch: [12] [1580/2639] eta: 0:51:09 lr: 3.5571689411998344e-05 loss: 0.0730 (0.0738) time: 2.9300 data: 0.0078 max mem: 33370 +Epoch: [12] [1590/2639] eta: 0:50:41 lr: 3.556726204384565e-05 loss: 0.0686 (0.0738) time: 2.9286 data: 0.0076 max mem: 33370 +Epoch: [12] [1600/2639] eta: 0:50:12 lr: 3.5562834614457315e-05 loss: 0.0658 (0.0739) time: 2.9366 data: 0.0078 max mem: 33370 +Epoch: [12] [1610/2639] eta: 0:49:43 lr: 3.555840712382401e-05 loss: 0.0626 (0.0739) time: 2.8870 data: 0.0082 max mem: 33370 +Epoch: [12] [1620/2639] eta: 0:49:13 lr: 3.5553979571936414e-05 loss: 0.0598 (0.0738) time: 2.8570 data: 0.0080 max mem: 33370 +Epoch: [12] [1630/2639] eta: 0:48:44 lr: 3.5549551958785204e-05 loss: 0.0598 (0.0739) time: 2.8672 data: 0.0077 max mem: 33370 +Epoch: [12] [1640/2639] eta: 0:48:15 lr: 3.5545124284361055e-05 loss: 0.0625 (0.0739) time: 2.8814 data: 0.0079 max mem: 33370 +Epoch: [12] [1650/2639] eta: 0:47:46 lr: 3.554069654865464e-05 loss: 0.0606 (0.0739) time: 2.8749 data: 0.0083 max mem: 33370 +Epoch: [12] [1660/2639] eta: 0:47:17 lr: 3.553626875165663e-05 loss: 0.0650 (0.0739) time: 2.8782 data: 0.0078 max mem: 33370 +Epoch: [12] [1670/2639] eta: 0:46:48 lr: 3.553184089335768e-05 loss: 0.0680 (0.0738) time: 2.8901 data: 0.0073 max mem: 33370 +Epoch: [12] [1680/2639] eta: 0:46:19 lr: 3.552741297374847e-05 loss: 0.0680 (0.0739) time: 2.8801 data: 0.0077 max mem: 33370 +Epoch: [12] [1690/2639] eta: 0:45:50 lr: 3.5522984992819645e-05 loss: 0.0584 (0.0738) time: 2.8951 data: 0.0079 max mem: 33370 +Epoch: [12] [1700/2639] eta: 0:45:21 lr: 3.551855695056187e-05 loss: 0.0584 (0.0737) time: 2.8926 data: 0.0079 max mem: 33370 +Epoch: [12] [1710/2639] eta: 0:44:52 lr: 3.55141288469658e-05 loss: 0.0690 (0.0737) time: 2.8925 data: 0.0080 max mem: 33370 +Epoch: [12] [1720/2639] eta: 0:44:23 lr: 3.5509700682022076e-05 loss: 0.0678 (0.0737) time: 2.8759 data: 0.0080 max mem: 33370 +Epoch: [12] [1730/2639] eta: 0:43:53 lr: 3.5505272455721375e-05 loss: 0.0634 (0.0737) time: 2.8631 data: 0.0079 max mem: 33370 +Epoch: [12] [1740/2639] eta: 0:43:24 lr: 3.550084416805432e-05 loss: 0.0607 (0.0736) time: 2.8766 data: 0.0077 max mem: 33370 +Epoch: [12] [1750/2639] eta: 0:42:56 lr: 3.549641581901156e-05 loss: 0.0567 (0.0736) time: 2.9186 data: 0.0078 max mem: 33370 +Epoch: [12] [1760/2639] eta: 0:42:27 lr: 3.549198740858373e-05 loss: 0.0633 (0.0736) time: 2.9217 data: 0.0077 max mem: 33370 +Epoch: [12] [1770/2639] eta: 0:41:58 lr: 3.5487558936761486e-05 loss: 0.0690 (0.0736) time: 2.9013 data: 0.0074 max mem: 33370 +Epoch: [12] [1780/2639] eta: 0:41:29 lr: 3.5483130403535456e-05 loss: 0.0721 (0.0737) time: 2.9036 data: 0.0078 max mem: 33370 +Epoch: [12] [1790/2639] eta: 0:41:00 lr: 3.547870180889627e-05 loss: 0.0746 (0.0737) time: 2.8990 data: 0.0078 max mem: 33370 +Epoch: [12] [1800/2639] eta: 0:40:31 lr: 3.547427315283456e-05 loss: 0.0644 (0.0737) time: 2.9149 data: 0.0075 max mem: 33370 +Epoch: [12] [1810/2639] eta: 0:40:02 lr: 3.546984443534095e-05 loss: 0.0664 (0.0739) time: 2.9296 data: 0.0079 max mem: 33370 +Epoch: [12] [1820/2639] eta: 0:39:33 lr: 3.546541565640608e-05 loss: 0.0754 (0.0739) time: 2.9395 data: 0.0083 max mem: 33370 +Epoch: [12] [1830/2639] eta: 0:39:04 lr: 3.546098681602055e-05 loss: 0.0754 (0.0740) time: 2.9279 data: 0.0083 max mem: 33370 +Epoch: [12] [1840/2639] eta: 0:38:36 lr: 3.5456557914175e-05 loss: 0.0783 (0.0740) time: 2.9351 data: 0.0082 max mem: 33370 +Epoch: [12] [1850/2639] eta: 0:38:07 lr: 3.545212895086003e-05 loss: 0.0713 (0.0740) time: 2.9565 data: 0.0081 max mem: 33370 +Epoch: [12] [1860/2639] eta: 0:37:38 lr: 3.544769992606627e-05 loss: 0.0821 (0.0740) time: 2.9544 data: 0.0079 max mem: 33370 +Epoch: [12] [1870/2639] eta: 0:37:09 lr: 3.544327083978433e-05 loss: 0.0805 (0.0741) time: 2.9555 data: 0.0079 max mem: 33370 +Epoch: [12] [1880/2639] eta: 0:36:40 lr: 3.543884169200479e-05 loss: 0.0707 (0.0740) time: 2.9063 data: 0.0080 max mem: 33370 +Epoch: [12] [1890/2639] eta: 0:36:11 lr: 3.543441248271829e-05 loss: 0.0707 (0.0741) time: 2.8779 data: 0.0078 max mem: 33370 +Epoch: [12] [1900/2639] eta: 0:35:42 lr: 3.542998321191543e-05 loss: 0.0740 (0.0741) time: 2.8851 data: 0.0077 max mem: 33370 +Epoch: [12] [1910/2639] eta: 0:35:13 lr: 3.5425553879586795e-05 loss: 0.0740 (0.0741) time: 2.8979 data: 0.0078 max mem: 33370 +Epoch: [12] [1920/2639] eta: 0:34:44 lr: 3.5421124485722984e-05 loss: 0.0703 (0.0741) time: 2.9312 data: 0.0076 max mem: 33370 +Epoch: [12] [1930/2639] eta: 0:34:16 lr: 3.54166950303146e-05 loss: 0.0703 (0.0742) time: 2.9431 data: 0.0076 max mem: 33370 +Epoch: [12] [1940/2639] eta: 0:33:46 lr: 3.5412265513352236e-05 loss: 0.0672 (0.0742) time: 2.9002 data: 0.0077 max mem: 33370 +Epoch: [12] [1950/2639] eta: 0:33:17 lr: 3.540783593482648e-05 loss: 0.0646 (0.0741) time: 2.8521 data: 0.0078 max mem: 33370 +Epoch: [12] [1960/2639] eta: 0:32:48 lr: 3.5403406294727916e-05 loss: 0.0622 (0.0741) time: 2.8929 data: 0.0077 max mem: 33370 +Epoch: [12] [1970/2639] eta: 0:32:19 lr: 3.5398976593047115e-05 loss: 0.0660 (0.0741) time: 2.8966 data: 0.0079 max mem: 33370 +Epoch: [12] [1980/2639] eta: 0:31:50 lr: 3.5394546829774685e-05 loss: 0.0764 (0.0742) time: 2.8681 data: 0.0082 max mem: 33370 +Epoch: [12] [1990/2639] eta: 0:31:21 lr: 3.5390117004901195e-05 loss: 0.0825 (0.0743) time: 2.8913 data: 0.0078 max mem: 33370 +Epoch: [12] [2000/2639] eta: 0:30:52 lr: 3.538568711841721e-05 loss: 0.0705 (0.0742) time: 2.9185 data: 0.0076 max mem: 33370 +Epoch: [12] [2010/2639] eta: 0:30:23 lr: 3.538125717031331e-05 loss: 0.0650 (0.0742) time: 2.9107 data: 0.0080 max mem: 33370 +Epoch: [12] [2020/2639] eta: 0:29:54 lr: 3.537682716058007e-05 loss: 0.0809 (0.0742) time: 2.9103 data: 0.0081 max mem: 33370 +Epoch: [12] [2030/2639] eta: 0:29:25 lr: 3.5372397089208045e-05 loss: 0.0943 (0.0744) time: 2.9023 data: 0.0079 max mem: 33370 +Epoch: [12] [2040/2639] eta: 0:28:56 lr: 3.536796695618782e-05 loss: 0.0786 (0.0744) time: 2.9082 data: 0.0079 max mem: 33370 +Epoch: [12] [2050/2639] eta: 0:28:28 lr: 3.536353676150993e-05 loss: 0.0657 (0.0746) time: 2.9374 data: 0.0077 max mem: 33370 +Epoch: [12] [2060/2639] eta: 0:27:59 lr: 3.535910650516495e-05 loss: 0.0719 (0.0747) time: 2.9353 data: 0.0077 max mem: 33370 +Epoch: [12] [2070/2639] eta: 0:27:30 lr: 3.535467618714344e-05 loss: 0.0591 (0.0746) time: 2.9356 data: 0.0079 max mem: 33370 +Epoch: [12] [2080/2639] eta: 0:27:01 lr: 3.535024580743595e-05 loss: 0.0614 (0.0746) time: 2.9272 data: 0.0084 max mem: 33370 +Epoch: [12] [2090/2639] eta: 0:26:32 lr: 3.534581536603303e-05 loss: 0.0626 (0.0745) time: 2.9073 data: 0.0083 max mem: 33370 +Epoch: [12] [2100/2639] eta: 0:26:03 lr: 3.534138486292522e-05 loss: 0.0555 (0.0745) time: 2.9018 data: 0.0079 max mem: 33370 +Epoch: [12] [2110/2639] eta: 0:25:34 lr: 3.533695429810307e-05 loss: 0.0620 (0.0744) time: 2.9084 data: 0.0077 max mem: 33370 +Epoch: [12] [2120/2639] eta: 0:25:05 lr: 3.533252367155715e-05 loss: 0.0675 (0.0744) time: 2.9042 data: 0.0076 max mem: 33370 +Epoch: [12] [2130/2639] eta: 0:24:36 lr: 3.532809298327795e-05 loss: 0.0819 (0.0745) time: 2.8863 data: 0.0076 max mem: 33370 +Epoch: [12] [2140/2639] eta: 0:24:07 lr: 3.532366223325603e-05 loss: 0.0790 (0.0745) time: 2.8749 data: 0.0076 max mem: 33370 +Epoch: [12] [2150/2639] eta: 0:23:38 lr: 3.5319231421481945e-05 loss: 0.0737 (0.0746) time: 2.8645 data: 0.0075 max mem: 33370 +Epoch: [12] [2160/2639] eta: 0:23:09 lr: 3.5314800547946206e-05 loss: 0.0705 (0.0746) time: 2.8677 data: 0.0076 max mem: 33370 +Epoch: [12] [2170/2639] eta: 0:22:40 lr: 3.5310369612639336e-05 loss: 0.0728 (0.0746) time: 2.8824 data: 0.0074 max mem: 33370 +Epoch: [12] [2180/2639] eta: 0:22:10 lr: 3.530593861555187e-05 loss: 0.0726 (0.0746) time: 2.8482 data: 0.0073 max mem: 33370 +Epoch: [12] [2190/2639] eta: 0:21:41 lr: 3.530150755667432e-05 loss: 0.0665 (0.0745) time: 2.8655 data: 0.0074 max mem: 33370 +Epoch: [12] [2200/2639] eta: 0:21:13 lr: 3.529707643599723e-05 loss: 0.0635 (0.0745) time: 2.9489 data: 0.0076 max mem: 33370 +Epoch: [12] [2210/2639] eta: 0:20:44 lr: 3.5292645253511104e-05 loss: 0.0700 (0.0746) time: 2.9425 data: 0.0073 max mem: 33370 +Epoch: [12] [2220/2639] eta: 0:20:15 lr: 3.528821400920645e-05 loss: 0.0728 (0.0746) time: 2.9056 data: 0.0071 max mem: 33370 +Epoch: [12] [2230/2639] eta: 0:19:46 lr: 3.528378270307379e-05 loss: 0.0622 (0.0746) time: 2.9104 data: 0.0076 max mem: 33370 +Epoch: [12] [2240/2639] eta: 0:19:16 lr: 3.527935133510364e-05 loss: 0.0622 (0.0746) time: 2.8789 data: 0.0080 max mem: 33370 +Epoch: [12] [2250/2639] eta: 0:18:47 lr: 3.527491990528649e-05 loss: 0.0599 (0.0747) time: 2.8725 data: 0.0082 max mem: 33370 +Epoch: [12] [2260/2639] eta: 0:18:18 lr: 3.527048841361284e-05 loss: 0.0704 (0.0748) time: 2.8934 data: 0.0081 max mem: 33370 +Epoch: [12] [2270/2639] eta: 0:17:49 lr: 3.5266056860073207e-05 loss: 0.0674 (0.0748) time: 2.8931 data: 0.0078 max mem: 33370 +Epoch: [12] [2280/2639] eta: 0:17:20 lr: 3.5261625244658084e-05 loss: 0.0736 (0.0748) time: 2.8829 data: 0.0077 max mem: 33370 +Epoch: [12] [2290/2639] eta: 0:16:51 lr: 3.5257193567357975e-05 loss: 0.0702 (0.0747) time: 2.8905 data: 0.0079 max mem: 33370 +Epoch: [12] [2300/2639] eta: 0:16:23 lr: 3.525276182816335e-05 loss: 0.0591 (0.0747) time: 2.9475 data: 0.0080 max mem: 33370 +Epoch: [12] [2310/2639] eta: 0:15:53 lr: 3.524833002706472e-05 loss: 0.0591 (0.0747) time: 2.8957 data: 0.0078 max mem: 33370 +Epoch: [12] [2320/2639] eta: 0:15:24 lr: 3.5243898164052566e-05 loss: 0.0597 (0.0747) time: 2.8196 data: 0.0076 max mem: 33370 +Epoch: [12] [2330/2639] eta: 0:14:55 lr: 3.5239466239117375e-05 loss: 0.0637 (0.0747) time: 2.8419 data: 0.0073 max mem: 33370 +Epoch: [12] [2340/2639] eta: 0:14:26 lr: 3.5235034252249614e-05 loss: 0.0675 (0.0747) time: 2.8674 data: 0.0074 max mem: 33370 +Epoch: [12] [2350/2639] eta: 0:13:57 lr: 3.523060220343978e-05 loss: 0.0673 (0.0747) time: 2.8977 data: 0.0076 max mem: 33370 +Epoch: [12] [2360/2639] eta: 0:13:28 lr: 3.5226170092678336e-05 loss: 0.0711 (0.0747) time: 2.9068 data: 0.0075 max mem: 33370 +Epoch: [12] [2370/2639] eta: 0:12:59 lr: 3.522173791995576e-05 loss: 0.0599 (0.0747) time: 2.8949 data: 0.0075 max mem: 33370 +Epoch: [12] [2380/2639] eta: 0:12:30 lr: 3.521730568526252e-05 loss: 0.0573 (0.0746) time: 2.8890 data: 0.0074 max mem: 33370 +Epoch: [12] [2390/2639] eta: 0:12:01 lr: 3.5212873388589086e-05 loss: 0.0668 (0.0746) time: 2.8885 data: 0.0079 max mem: 33370 +Epoch: [12] [2400/2639] eta: 0:11:32 lr: 3.5208441029925923e-05 loss: 0.0753 (0.0746) time: 2.8981 data: 0.0079 max mem: 33370 +Epoch: [12] [2410/2639] eta: 0:11:03 lr: 3.52040086092635e-05 loss: 0.0615 (0.0746) time: 2.9287 data: 0.0072 max mem: 33370 +Epoch: [12] [2420/2639] eta: 0:10:34 lr: 3.5199576126592254e-05 loss: 0.0654 (0.0746) time: 2.9170 data: 0.0072 max mem: 33370 +Epoch: [12] [2430/2639] eta: 0:10:05 lr: 3.5195143581902665e-05 loss: 0.0878 (0.0747) time: 2.8769 data: 0.0072 max mem: 33370 +Epoch: [12] [2440/2639] eta: 0:09:36 lr: 3.519071097518517e-05 loss: 0.0877 (0.0748) time: 2.8428 data: 0.0072 max mem: 33370 +Epoch: [12] [2450/2639] eta: 0:09:07 lr: 3.5186278306430234e-05 loss: 0.0811 (0.0748) time: 2.8606 data: 0.0074 max mem: 33370 +Epoch: [12] [2460/2639] eta: 0:08:38 lr: 3.518184557562829e-05 loss: 0.0746 (0.0748) time: 2.9017 data: 0.0075 max mem: 33370 +Epoch: [12] [2470/2639] eta: 0:08:09 lr: 3.517741278276978e-05 loss: 0.0746 (0.0748) time: 2.9166 data: 0.0074 max mem: 33370 +Epoch: [12] [2480/2639] eta: 0:07:40 lr: 3.517297992784518e-05 loss: 0.0677 (0.0749) time: 2.9183 data: 0.0074 max mem: 33370 +Epoch: [12] [2490/2639] eta: 0:07:11 lr: 3.51685470108449e-05 loss: 0.0677 (0.0749) time: 2.9093 data: 0.0075 max mem: 33370 +Epoch: [12] [2500/2639] eta: 0:06:42 lr: 3.5164114031759374e-05 loss: 0.0704 (0.0749) time: 2.8889 data: 0.0074 max mem: 33370 +Epoch: [12] [2510/2639] eta: 0:06:13 lr: 3.515968099057904e-05 loss: 0.0728 (0.0749) time: 2.8735 data: 0.0076 max mem: 33370 +Epoch: [12] [2520/2639] eta: 0:05:44 lr: 3.515524788729434e-05 loss: 0.0669 (0.0749) time: 2.8908 data: 0.0075 max mem: 33370 +Epoch: [12] [2530/2639] eta: 0:05:15 lr: 3.5150814721895695e-05 loss: 0.0720 (0.0749) time: 2.8628 data: 0.0074 max mem: 33370 +Epoch: [12] [2540/2639] eta: 0:04:46 lr: 3.514638149437353e-05 loss: 0.0739 (0.0749) time: 2.8637 data: 0.0075 max mem: 33370 +Epoch: [12] [2550/2639] eta: 0:04:17 lr: 3.514194820471827e-05 loss: 0.0768 (0.0749) time: 2.8808 data: 0.0074 max mem: 33370 +Epoch: [12] [2560/2639] eta: 0:03:48 lr: 3.5137514852920326e-05 loss: 0.0703 (0.0749) time: 2.8849 data: 0.0076 max mem: 33370 +Epoch: [12] [2570/2639] eta: 0:03:19 lr: 3.5133081438970135e-05 loss: 0.0631 (0.0749) time: 2.8776 data: 0.0078 max mem: 33370 +Epoch: [12] [2580/2639] eta: 0:02:50 lr: 3.512864796285809e-05 loss: 0.0714 (0.0749) time: 2.8880 data: 0.0077 max mem: 33370 +Epoch: [12] [2590/2639] eta: 0:02:22 lr: 3.5124214424574604e-05 loss: 0.0670 (0.0749) time: 2.8999 data: 0.0073 max mem: 33370 +Epoch: [12] [2600/2639] eta: 0:01:53 lr: 3.5119780824110095e-05 loss: 0.0633 (0.0749) time: 2.9107 data: 0.0076 max mem: 33370 +Epoch: [12] [2610/2639] eta: 0:01:24 lr: 3.511534716145497e-05 loss: 0.0639 (0.0749) time: 2.9312 data: 0.0080 max mem: 33370 +Epoch: [12] [2620/2639] eta: 0:00:55 lr: 3.511091343659962e-05 loss: 0.0661 (0.0748) time: 2.9422 data: 0.0077 max mem: 33370 +Epoch: [12] [2630/2639] eta: 0:00:26 lr: 3.510647964953446e-05 loss: 0.0752 (0.0749) time: 2.9465 data: 0.0074 max mem: 33370 +Epoch: [12] Total time: 2:07:30 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 2:25:10 time: 3.3853 data: 3.2510 max mem: 33370 +Test: [ 100/2573] eta: 0:04:33 time: 0.0786 data: 0.0014 max mem: 33370 +Test: [ 200/2573] eta: 0:03:45 time: 0.0793 data: 0.0015 max mem: 33370 +Test: [ 300/2573] eta: 0:03:23 time: 0.0810 data: 0.0014 max mem: 33370 +Test: [ 400/2573] eta: 0:03:09 time: 0.0806 data: 0.0015 max mem: 33370 +Test: [ 500/2573] eta: 0:02:57 time: 0.0798 data: 0.0015 max mem: 33370 +Test: [ 600/2573] eta: 0:02:47 time: 0.0794 data: 0.0014 max mem: 33370 +Test: [ 700/2573] eta: 0:02:37 time: 0.0807 data: 0.0015 max mem: 33370 +Test: [ 800/2573] eta: 0:02:28 time: 0.0821 data: 0.0013 max mem: 33370 +Test: [ 900/2573] eta: 0:02:19 time: 0.0801 data: 0.0015 max mem: 33370 +Test: [1000/2573] eta: 0:02:10 time: 0.0798 data: 0.0014 max mem: 33370 +Test: [1100/2573] eta: 0:02:02 time: 0.0799 data: 0.0015 max mem: 33370 +Test: [1200/2573] eta: 0:01:53 time: 0.0796 data: 0.0013 max mem: 33370 +Test: [1300/2573] eta: 0:01:45 time: 0.0802 data: 0.0014 max mem: 33370 +Test: [1400/2573] eta: 0:01:36 time: 0.0779 data: 0.0015 max mem: 33370 +Test: [1500/2573] eta: 0:01:28 time: 0.0802 data: 0.0014 max mem: 33370 +Test: [1600/2573] eta: 0:01:19 time: 0.0831 data: 0.0014 max mem: 33370 +Test: [1700/2573] eta: 0:01:11 time: 0.0786 data: 0.0014 max mem: 33370 +Test: [1800/2573] eta: 0:01:03 time: 0.0820 data: 0.0014 max mem: 33370 +Test: [1900/2573] eta: 0:00:54 time: 0.0783 data: 0.0016 max mem: 33370 +Test: [2000/2573] eta: 0:00:46 time: 0.0807 data: 0.0015 max mem: 33370 +Test: [2100/2573] eta: 0:00:38 time: 0.0819 data: 0.0015 max mem: 33370 +Test: [2200/2573] eta: 0:00:30 time: 0.0829 data: 0.0015 max mem: 33370 +Test: [2300/2573] eta: 0:00:22 time: 0.0821 data: 0.0014 max mem: 33370 +Test: [2400/2573] eta: 0:00:14 time: 0.0773 data: 0.0014 max mem: 33370 +Test: [2500/2573] eta: 0:00:05 time: 0.0797 data: 0.0014 max mem: 33370 +Test: Total time: 0:03:29 +Final results: +Mean IoU is 60.32 + + precision@0.5 = 67.30 + precision@0.6 = 62.01 + precision@0.7 = 54.23 + precision@0.8 = 41.97 + precision@0.9 = 20.00 + overall IoU = 58.53 + +Average object IoU 60.32129297602907 +Overall IoU 58.525230407714844 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [13] [ 0/2639] eta: 4:59:45 lr: 3.510248918797848e-05 loss: 0.0796 (0.0796) time: 6.8153 data: 3.4691 max mem: 33370 +Epoch: [13] [ 10/2639] eta: 2:22:00 lr: 3.50980552826882e-05 loss: 0.0781 (0.0759) time: 3.2408 data: 0.3213 max mem: 33370 +Epoch: [13] [ 20/2639] eta: 2:15:08 lr: 3.509362131516024e-05 loss: 0.0677 (0.0725) time: 2.9099 data: 0.0073 max mem: 33370 +Epoch: [13] [ 30/2639] eta: 2:11:44 lr: 3.5089187285385e-05 loss: 0.0663 (0.0730) time: 2.9138 data: 0.0079 max mem: 33370 +Epoch: [13] [ 40/2639] eta: 2:09:51 lr: 3.508475319335286e-05 loss: 0.0687 (0.0740) time: 2.8947 data: 0.0080 max mem: 33370 +Epoch: [13] [ 50/2639] eta: 2:08:41 lr: 3.508031903905421e-05 loss: 0.0654 (0.0720) time: 2.9091 data: 0.0078 max mem: 33370 +Epoch: [13] [ 60/2639] eta: 2:07:42 lr: 3.507588482247941e-05 loss: 0.0614 (0.0725) time: 2.9162 data: 0.0079 max mem: 33370 +Epoch: [13] [ 70/2639] eta: 2:06:56 lr: 3.507145054361886e-05 loss: 0.0620 (0.0720) time: 2.9204 data: 0.0079 max mem: 33370 +Epoch: [13] [ 80/2639] eta: 2:06:10 lr: 3.506701620246293e-05 loss: 0.0603 (0.0705) time: 2.9191 data: 0.0076 max mem: 33370 +Epoch: [13] [ 90/2639] eta: 2:05:17 lr: 3.506258179900198e-05 loss: 0.0576 (0.0690) time: 2.8925 data: 0.0076 max mem: 33370 +Epoch: [13] [ 100/2639] eta: 2:04:26 lr: 3.505814733322639e-05 loss: 0.0624 (0.0698) time: 2.8703 data: 0.0074 max mem: 33370 +Epoch: [13] [ 110/2639] eta: 2:03:49 lr: 3.505371280512652e-05 loss: 0.0633 (0.0721) time: 2.8873 data: 0.0076 max mem: 33370 +Epoch: [13] [ 120/2639] eta: 2:03:17 lr: 3.5049278214692735e-05 loss: 0.0633 (0.0720) time: 2.9151 data: 0.0077 max mem: 33370 +Epoch: [13] [ 130/2639] eta: 2:02:38 lr: 3.504484356191541e-05 loss: 0.0571 (0.0715) time: 2.9055 data: 0.0077 max mem: 33370 +Epoch: [13] [ 140/2639] eta: 2:01:54 lr: 3.504040884678488e-05 loss: 0.0575 (0.0713) time: 2.8700 data: 0.0076 max mem: 33370 +Epoch: [13] [ 150/2639] eta: 2:01:08 lr: 3.503597406929151e-05 loss: 0.0612 (0.0716) time: 2.8369 data: 0.0076 max mem: 33370 +Epoch: [13] [ 160/2639] eta: 2:00:47 lr: 3.503153922942564e-05 loss: 0.0570 (0.0705) time: 2.8975 data: 0.0078 max mem: 33370 +Epoch: [13] [ 170/2639] eta: 2:00:10 lr: 3.502710432717764e-05 loss: 0.0517 (0.0696) time: 2.9222 data: 0.0082 max mem: 33370 +Epoch: [13] [ 180/2639] eta: 1:59:44 lr: 3.5022669362537855e-05 loss: 0.0559 (0.0694) time: 2.9091 data: 0.0083 max mem: 33370 +Epoch: [13] [ 190/2639] eta: 1:59:17 lr: 3.5018234335496614e-05 loss: 0.0560 (0.0691) time: 2.9424 data: 0.0081 max mem: 33370 +Epoch: [13] [ 200/2639] eta: 1:58:49 lr: 3.501379924604426e-05 loss: 0.0556 (0.0686) time: 2.9331 data: 0.0080 max mem: 33370 +Epoch: [13] [ 210/2639] eta: 1:58:14 lr: 3.5009364094171136e-05 loss: 0.0723 (0.0696) time: 2.9017 data: 0.0079 max mem: 33370 +Epoch: [13] [ 220/2639] eta: 1:57:36 lr: 3.5004928879867574e-05 loss: 0.0675 (0.0692) time: 2.8574 data: 0.0078 max mem: 33370 +Epoch: [13] [ 230/2639] eta: 1:57:05 lr: 3.5000493603123914e-05 loss: 0.0545 (0.0689) time: 2.8705 data: 0.0080 max mem: 33370 +Epoch: [13] [ 240/2639] eta: 1:56:33 lr: 3.4996058263930466e-05 loss: 0.0576 (0.0686) time: 2.8923 data: 0.0079 max mem: 33370 +Epoch: [13] [ 250/2639] eta: 1:56:01 lr: 3.499162286227758e-05 loss: 0.0631 (0.0687) time: 2.8855 data: 0.0080 max mem: 33370 +Epoch: [13] [ 260/2639] eta: 1:55:34 lr: 3.498718739815556e-05 loss: 0.0608 (0.0692) time: 2.9128 data: 0.0078 max mem: 33370 +Epoch: [13] [ 270/2639] eta: 1:55:08 lr: 3.498275187155473e-05 loss: 0.0621 (0.0691) time: 2.9450 data: 0.0074 max mem: 33370 +Epoch: [13] [ 280/2639] eta: 1:54:37 lr: 3.4978316282465424e-05 loss: 0.0700 (0.0695) time: 2.9234 data: 0.0076 max mem: 33370 +Epoch: [13] [ 290/2639] eta: 1:54:09 lr: 3.4973880630877945e-05 loss: 0.0602 (0.0694) time: 2.9090 data: 0.0077 max mem: 33370 +Epoch: [13] [ 300/2639] eta: 1:53:31 lr: 3.49694449167826e-05 loss: 0.0588 (0.0693) time: 2.8651 data: 0.0076 max mem: 33370 +Epoch: [13] [ 310/2639] eta: 1:52:57 lr: 3.4965009140169695e-05 loss: 0.0626 (0.0695) time: 2.8255 data: 0.0077 max mem: 33370 +Epoch: [13] [ 320/2639] eta: 1:52:26 lr: 3.496057330102955e-05 loss: 0.0641 (0.0693) time: 2.8677 data: 0.0079 max mem: 33370 +Epoch: [13] [ 330/2639] eta: 1:51:56 lr: 3.495613739935247e-05 loss: 0.0614 (0.0696) time: 2.8942 data: 0.0076 max mem: 33370 +Epoch: [13] [ 340/2639] eta: 1:51:26 lr: 3.495170143512874e-05 loss: 0.0596 (0.0693) time: 2.8927 data: 0.0075 max mem: 33370 +Epoch: [13] [ 350/2639] eta: 1:51:03 lr: 3.494726540834867e-05 loss: 0.0619 (0.0695) time: 2.9429 data: 0.0078 max mem: 33370 +Epoch: [13] [ 360/2639] eta: 1:50:35 lr: 3.494282931900254e-05 loss: 0.0709 (0.0696) time: 2.9682 data: 0.0078 max mem: 33370 +Epoch: [13] [ 370/2639] eta: 1:50:03 lr: 3.4938393167080656e-05 loss: 0.0770 (0.0702) time: 2.8986 data: 0.0079 max mem: 33370 +Epoch: [13] [ 380/2639] eta: 1:49:32 lr: 3.493395695257331e-05 loss: 0.0823 (0.0705) time: 2.8735 data: 0.0086 max mem: 33370 +Epoch: [13] [ 390/2639] eta: 1:49:01 lr: 3.4929520675470774e-05 loss: 0.0727 (0.0707) time: 2.8824 data: 0.0083 max mem: 33370 +Epoch: [13] [ 400/2639] eta: 1:48:30 lr: 3.492508433576334e-05 loss: 0.0669 (0.0705) time: 2.8721 data: 0.0078 max mem: 33370 +Epoch: [13] [ 410/2639] eta: 1:48:02 lr: 3.492064793344128e-05 loss: 0.0546 (0.0702) time: 2.8927 data: 0.0079 max mem: 33370 +Epoch: [13] [ 420/2639] eta: 1:47:30 lr: 3.4916211468494885e-05 loss: 0.0560 (0.0703) time: 2.8933 data: 0.0077 max mem: 33370 +Epoch: [13] [ 430/2639] eta: 1:47:01 lr: 3.491177494091443e-05 loss: 0.0593 (0.0701) time: 2.8803 data: 0.0077 max mem: 33370 +Epoch: [13] [ 440/2639] eta: 1:46:30 lr: 3.490733835069016e-05 loss: 0.0594 (0.0703) time: 2.8827 data: 0.0081 max mem: 33370 +Epoch: [13] [ 450/2639] eta: 1:46:00 lr: 3.4902901697812376e-05 loss: 0.0640 (0.0703) time: 2.8778 data: 0.0083 max mem: 33370 +Epoch: [13] [ 460/2639] eta: 1:45:31 lr: 3.489846498227133e-05 loss: 0.0640 (0.0704) time: 2.8975 data: 0.0083 max mem: 33370 +Epoch: [13] [ 470/2639] eta: 1:45:00 lr: 3.489402820405728e-05 loss: 0.0653 (0.0702) time: 2.8941 data: 0.0085 max mem: 33370 +Epoch: [13] [ 480/2639] eta: 1:44:32 lr: 3.48895913631605e-05 loss: 0.0626 (0.0701) time: 2.8930 data: 0.0081 max mem: 33370 +Epoch: [13] [ 490/2639] eta: 1:44:00 lr: 3.488515445957123e-05 loss: 0.0586 (0.0701) time: 2.8773 data: 0.0081 max mem: 33370 +Epoch: [13] [ 500/2639] eta: 1:43:32 lr: 3.488071749327973e-05 loss: 0.0583 (0.0699) time: 2.8893 data: 0.0081 max mem: 33370 +Epoch: [13] [ 510/2639] eta: 1:43:03 lr: 3.487628046427627e-05 loss: 0.0571 (0.0698) time: 2.9237 data: 0.0079 max mem: 33370 +Epoch: [13] [ 520/2639] eta: 1:42:36 lr: 3.4871843372551075e-05 loss: 0.0607 (0.0698) time: 2.9279 data: 0.0080 max mem: 33370 +Epoch: [13] [ 530/2639] eta: 1:42:08 lr: 3.48674062180944e-05 loss: 0.0608 (0.0701) time: 2.9405 data: 0.0078 max mem: 33370 +Epoch: [13] [ 540/2639] eta: 1:41:42 lr: 3.486296900089649e-05 loss: 0.0757 (0.0703) time: 2.9572 data: 0.0076 max mem: 33370 +Epoch: [13] [ 550/2639] eta: 1:41:14 lr: 3.4858531720947577e-05 loss: 0.0621 (0.0703) time: 2.9602 data: 0.0077 max mem: 33370 +Epoch: [13] [ 560/2639] eta: 1:40:45 lr: 3.4854094378237906e-05 loss: 0.0604 (0.0703) time: 2.9286 data: 0.0078 max mem: 33370 +Epoch: [13] [ 570/2639] eta: 1:40:17 lr: 3.484965697275771e-05 loss: 0.0688 (0.0702) time: 2.9281 data: 0.0079 max mem: 33370 +Epoch: [13] [ 580/2639] eta: 1:39:49 lr: 3.484521950449721e-05 loss: 0.0490 (0.0698) time: 2.9348 data: 0.0081 max mem: 33370 +Epoch: [13] [ 590/2639] eta: 1:39:20 lr: 3.484078197344665e-05 loss: 0.0565 (0.0699) time: 2.9225 data: 0.0081 max mem: 33370 +Epoch: [13] [ 600/2639] eta: 1:38:49 lr: 3.483634437959624e-05 loss: 0.0576 (0.0697) time: 2.8877 data: 0.0078 max mem: 33370 +Epoch: [13] [ 610/2639] eta: 1:38:20 lr: 3.4831906722936214e-05 loss: 0.0507 (0.0694) time: 2.8800 data: 0.0076 max mem: 33370 +Epoch: [13] [ 620/2639] eta: 1:37:51 lr: 3.482746900345679e-05 loss: 0.0564 (0.0692) time: 2.9097 data: 0.0080 max mem: 33370 +Epoch: [13] [ 630/2639] eta: 1:37:23 lr: 3.4823031221148187e-05 loss: 0.0605 (0.0691) time: 2.9184 data: 0.0081 max mem: 33370 +Epoch: [13] [ 640/2639] eta: 1:36:55 lr: 3.4818593376000595e-05 loss: 0.0614 (0.0693) time: 2.9354 data: 0.0079 max mem: 33370 +Epoch: [13] [ 650/2639] eta: 1:36:27 lr: 3.4814155468004256e-05 loss: 0.0622 (0.0694) time: 2.9481 data: 0.0077 max mem: 33370 +Epoch: [13] [ 660/2639] eta: 1:35:57 lr: 3.4809717497149366e-05 loss: 0.0641 (0.0697) time: 2.9119 data: 0.0074 max mem: 33370 +Epoch: [13] [ 670/2639] eta: 1:35:29 lr: 3.4805279463426125e-05 loss: 0.0641 (0.0697) time: 2.9095 data: 0.0073 max mem: 33370 +Epoch: [13] [ 680/2639] eta: 1:35:01 lr: 3.480084136682475e-05 loss: 0.0744 (0.0700) time: 2.9434 data: 0.0077 max mem: 33370 +Epoch: [13] [ 690/2639] eta: 1:34:32 lr: 3.479640320733542e-05 loss: 0.0636 (0.0700) time: 2.9412 data: 0.0083 max mem: 33370 +Epoch: [13] [ 700/2639] eta: 1:34:04 lr: 3.4791964984948346e-05 loss: 0.0636 (0.0701) time: 2.9430 data: 0.0082 max mem: 33370 +Epoch: [13] [ 710/2639] eta: 1:33:36 lr: 3.478752669965372e-05 loss: 0.0632 (0.0700) time: 2.9369 data: 0.0077 max mem: 33370 +Epoch: [13] [ 720/2639] eta: 1:33:07 lr: 3.4783088351441725e-05 loss: 0.0508 (0.0699) time: 2.9287 data: 0.0079 max mem: 33370 +Epoch: [13] [ 730/2639] eta: 1:32:38 lr: 3.477864994030255e-05 loss: 0.0520 (0.0697) time: 2.9334 data: 0.0081 max mem: 33370 +Epoch: [13] [ 740/2639] eta: 1:32:09 lr: 3.4774211466226375e-05 loss: 0.0553 (0.0697) time: 2.9122 data: 0.0084 max mem: 33370 +Epoch: [13] [ 750/2639] eta: 1:31:38 lr: 3.47697729292034e-05 loss: 0.0610 (0.0695) time: 2.8664 data: 0.0088 max mem: 33370 +Epoch: [13] [ 760/2639] eta: 1:31:09 lr: 3.4765334329223794e-05 loss: 0.0658 (0.0697) time: 2.8713 data: 0.0081 max mem: 33370 +Epoch: [13] [ 770/2639] eta: 1:30:39 lr: 3.476089566627772e-05 loss: 0.0663 (0.0697) time: 2.8983 data: 0.0075 max mem: 33370 +Epoch: [13] [ 780/2639] eta: 1:30:10 lr: 3.475645694035537e-05 loss: 0.0618 (0.0696) time: 2.9079 data: 0.0081 max mem: 33370 +Epoch: [13] [ 790/2639] eta: 1:29:44 lr: 3.475201815144691e-05 loss: 0.0586 (0.0695) time: 2.9744 data: 0.0082 max mem: 33370 +Epoch: [13] [ 800/2639] eta: 1:29:14 lr: 3.47475792995425e-05 loss: 0.0586 (0.0695) time: 2.9616 data: 0.0077 max mem: 33370 +Epoch: [13] [ 810/2639] eta: 1:28:45 lr: 3.47431403846323e-05 loss: 0.0607 (0.0694) time: 2.9068 data: 0.0076 max mem: 33370 +Epoch: [13] [ 820/2639] eta: 1:28:16 lr: 3.4738701406706484e-05 loss: 0.0593 (0.0692) time: 2.9075 data: 0.0075 max mem: 33370 +Epoch: [13] [ 830/2639] eta: 1:27:47 lr: 3.4734262365755196e-05 loss: 0.0584 (0.0693) time: 2.9067 data: 0.0079 max mem: 33370 +Epoch: [13] [ 840/2639] eta: 1:27:16 lr: 3.472982326176861e-05 loss: 0.0659 (0.0693) time: 2.8771 data: 0.0082 max mem: 33370 +Epoch: [13] [ 850/2639] eta: 1:26:46 lr: 3.472538409473687e-05 loss: 0.0707 (0.0694) time: 2.8571 data: 0.0082 max mem: 33370 +Epoch: [13] [ 860/2639] eta: 1:26:17 lr: 3.472094486465011e-05 loss: 0.0741 (0.0695) time: 2.8770 data: 0.0086 max mem: 33370 +Epoch: [13] [ 870/2639] eta: 1:25:48 lr: 3.47165055714985e-05 loss: 0.0764 (0.0697) time: 2.9066 data: 0.0085 max mem: 33370 +Epoch: [13] [ 880/2639] eta: 1:25:19 lr: 3.471206621527218e-05 loss: 0.0767 (0.0698) time: 2.9226 data: 0.0083 max mem: 33370 +Epoch: [13] [ 890/2639] eta: 1:24:50 lr: 3.470762679596127e-05 loss: 0.0724 (0.0699) time: 2.9279 data: 0.0085 max mem: 33370 +Epoch: [13] [ 900/2639] eta: 1:24:22 lr: 3.4703187313555925e-05 loss: 0.0679 (0.0698) time: 2.9452 data: 0.0083 max mem: 33370 +Epoch: [13] [ 910/2639] eta: 1:23:53 lr: 3.4698747768046273e-05 loss: 0.0662 (0.0699) time: 2.9331 data: 0.0079 max mem: 33370 +Epoch: [13] [ 920/2639] eta: 1:23:24 lr: 3.4694308159422456e-05 loss: 0.0778 (0.0700) time: 2.9105 data: 0.0079 max mem: 33370 +Epoch: [13] [ 930/2639] eta: 1:22:54 lr: 3.46898684876746e-05 loss: 0.0679 (0.0699) time: 2.8966 data: 0.0079 max mem: 33370 +Epoch: [13] [ 940/2639] eta: 1:22:24 lr: 3.4685428752792815e-05 loss: 0.0656 (0.0699) time: 2.8791 data: 0.0076 max mem: 33370 +Epoch: [13] [ 950/2639] eta: 1:21:55 lr: 3.468098895476724e-05 loss: 0.0622 (0.0700) time: 2.8707 data: 0.0075 max mem: 33370 +Epoch: [13] [ 960/2639] eta: 1:21:26 lr: 3.467654909358799e-05 loss: 0.0558 (0.0700) time: 2.8977 data: 0.0076 max mem: 33370 +Epoch: [13] [ 970/2639] eta: 1:20:56 lr: 3.467210916924519e-05 loss: 0.0582 (0.0701) time: 2.9061 data: 0.0083 max mem: 33370 +Epoch: [13] [ 980/2639] eta: 1:20:26 lr: 3.466766918172894e-05 loss: 0.0634 (0.0701) time: 2.8761 data: 0.0085 max mem: 33370 +Epoch: [13] [ 990/2639] eta: 1:19:57 lr: 3.466322913102936e-05 loss: 0.0653 (0.0701) time: 2.8727 data: 0.0079 max mem: 33370 +Epoch: [13] [1000/2639] eta: 1:19:28 lr: 3.465878901713656e-05 loss: 0.0669 (0.0702) time: 2.9187 data: 0.0080 max mem: 33370 +Epoch: [13] [1010/2639] eta: 1:19:00 lr: 3.465434884004063e-05 loss: 0.0653 (0.0702) time: 2.9399 data: 0.0082 max mem: 33370 +Epoch: [13] [1020/2639] eta: 1:18:30 lr: 3.464990859973169e-05 loss: 0.0584 (0.0700) time: 2.9074 data: 0.0078 max mem: 33370 +Epoch: [13] [1030/2639] eta: 1:18:01 lr: 3.464546829619983e-05 loss: 0.0584 (0.0701) time: 2.8838 data: 0.0073 max mem: 33370 +Epoch: [13] [1040/2639] eta: 1:17:31 lr: 3.4641027929435155e-05 loss: 0.0650 (0.0701) time: 2.8819 data: 0.0076 max mem: 33370 +Epoch: [13] [1050/2639] eta: 1:17:01 lr: 3.463658749942775e-05 loss: 0.0584 (0.0701) time: 2.8571 data: 0.0080 max mem: 33370 +Epoch: [13] [1060/2639] eta: 1:16:32 lr: 3.4632147006167706e-05 loss: 0.0598 (0.0701) time: 2.8791 data: 0.0082 max mem: 33370 +Epoch: [13] [1070/2639] eta: 1:16:04 lr: 3.4627706449645106e-05 loss: 0.0598 (0.0702) time: 2.9337 data: 0.0082 max mem: 33370 +Epoch: [13] [1080/2639] eta: 1:15:34 lr: 3.4623265829850046e-05 loss: 0.0578 (0.0702) time: 2.8985 data: 0.0082 max mem: 33370 +Epoch: [13] [1090/2639] eta: 1:15:05 lr: 3.4618825146772605e-05 loss: 0.0614 (0.0703) time: 2.8858 data: 0.0076 max mem: 33370 +Epoch: [13] [1100/2639] eta: 1:14:36 lr: 3.461438440040286e-05 loss: 0.0679 (0.0704) time: 2.9330 data: 0.0078 max mem: 33370 +Epoch: [13] [1110/2639] eta: 1:14:07 lr: 3.4609943590730874e-05 loss: 0.0672 (0.0703) time: 2.9325 data: 0.0080 max mem: 33370 +Epoch: [13] [1120/2639] eta: 1:13:39 lr: 3.460550271774674e-05 loss: 0.0565 (0.0702) time: 2.9347 data: 0.0076 max mem: 33370 +Epoch: [13] [1130/2639] eta: 1:13:10 lr: 3.460106178144052e-05 loss: 0.0593 (0.0703) time: 2.9646 data: 0.0077 max mem: 33370 +Epoch: [13] [1140/2639] eta: 1:12:41 lr: 3.459662078180227e-05 loss: 0.0724 (0.0703) time: 2.9351 data: 0.0077 max mem: 33370 +Epoch: [13] [1150/2639] eta: 1:12:11 lr: 3.459217971882206e-05 loss: 0.0665 (0.0703) time: 2.8725 data: 0.0077 max mem: 33370 +Epoch: [13] [1160/2639] eta: 1:11:43 lr: 3.458773859248996e-05 loss: 0.0652 (0.0703) time: 2.9066 data: 0.0081 max mem: 33370 +Epoch: [13] [1170/2639] eta: 1:11:14 lr: 3.4583297402796025e-05 loss: 0.0591 (0.0703) time: 2.9368 data: 0.0083 max mem: 33370 +Epoch: [13] [1180/2639] eta: 1:10:44 lr: 3.457885614973031e-05 loss: 0.0668 (0.0703) time: 2.8948 data: 0.0083 max mem: 33370 +Epoch: [13] [1190/2639] eta: 1:10:15 lr: 3.457441483328284e-05 loss: 0.0658 (0.0703) time: 2.8959 data: 0.0082 max mem: 33370 +Epoch: [13] [1200/2639] eta: 1:09:47 lr: 3.45699734534437e-05 loss: 0.0654 (0.0704) time: 2.9243 data: 0.0083 max mem: 33370 +Epoch: [13] [1210/2639] eta: 1:09:17 lr: 3.4565532010202926e-05 loss: 0.0740 (0.0706) time: 2.9195 data: 0.0083 max mem: 33370 +Epoch: [13] [1220/2639] eta: 1:08:48 lr: 3.456109050355055e-05 loss: 0.0715 (0.0706) time: 2.9160 data: 0.0081 max mem: 33370 +Epoch: [13] [1230/2639] eta: 1:08:19 lr: 3.455664893347662e-05 loss: 0.0655 (0.0707) time: 2.9156 data: 0.0081 max mem: 33370 +Epoch: [13] [1240/2639] eta: 1:07:49 lr: 3.455220729997117e-05 loss: 0.0687 (0.0706) time: 2.8747 data: 0.0079 max mem: 33370 +Epoch: [13] [1250/2639] eta: 1:07:20 lr: 3.454776560302424e-05 loss: 0.0639 (0.0706) time: 2.8584 data: 0.0076 max mem: 33370 +Epoch: [13] [1260/2639] eta: 1:06:51 lr: 3.4543323842625857e-05 loss: 0.0637 (0.0707) time: 2.8818 data: 0.0081 max mem: 33370 +Epoch: [13] [1270/2639] eta: 1:06:21 lr: 3.453888201876604e-05 loss: 0.0640 (0.0706) time: 2.8800 data: 0.0081 max mem: 33370 +Epoch: [13] [1280/2639] eta: 1:05:52 lr: 3.453444013143482e-05 loss: 0.0584 (0.0705) time: 2.8843 data: 0.0077 max mem: 33370 +Epoch: [13] [1290/2639] eta: 1:05:22 lr: 3.452999818062224e-05 loss: 0.0563 (0.0705) time: 2.8669 data: 0.0076 max mem: 33370 +Epoch: [13] [1300/2639] eta: 1:04:53 lr: 3.452555616631828e-05 loss: 0.0665 (0.0705) time: 2.8456 data: 0.0077 max mem: 33370 +Epoch: [13] [1310/2639] eta: 1:04:24 lr: 3.452111408851298e-05 loss: 0.0631 (0.0705) time: 2.8880 data: 0.0078 max mem: 33370 +Epoch: [13] [1320/2639] eta: 1:03:55 lr: 3.451667194719634e-05 loss: 0.0591 (0.0705) time: 2.9185 data: 0.0078 max mem: 33370 +Epoch: [13] [1330/2639] eta: 1:03:25 lr: 3.4512229742358395e-05 loss: 0.0592 (0.0705) time: 2.9021 data: 0.0078 max mem: 33370 +Epoch: [13] [1340/2639] eta: 1:02:56 lr: 3.450778747398913e-05 loss: 0.0592 (0.0704) time: 2.9014 data: 0.0079 max mem: 33370 +Epoch: [13] [1350/2639] eta: 1:02:28 lr: 3.4503345142078544e-05 loss: 0.0593 (0.0706) time: 2.9281 data: 0.0081 max mem: 33370 +Epoch: [13] [1360/2639] eta: 1:01:59 lr: 3.449890274661665e-05 loss: 0.0590 (0.0705) time: 2.9274 data: 0.0082 max mem: 33370 +Epoch: [13] [1370/2639] eta: 1:01:30 lr: 3.449446028759345e-05 loss: 0.0555 (0.0705) time: 2.9136 data: 0.0080 max mem: 33370 +Epoch: [13] [1380/2639] eta: 1:01:00 lr: 3.4490017764998935e-05 loss: 0.0555 (0.0705) time: 2.8871 data: 0.0077 max mem: 33370 +Epoch: [13] [1390/2639] eta: 1:00:31 lr: 3.448557517882309e-05 loss: 0.0625 (0.0704) time: 2.8677 data: 0.0077 max mem: 33370 +Epoch: [13] [1400/2639] eta: 1:00:01 lr: 3.4481132529055896e-05 loss: 0.0704 (0.0705) time: 2.8837 data: 0.0076 max mem: 33370 +Epoch: [13] [1410/2639] eta: 0:59:32 lr: 3.4476689815687366e-05 loss: 0.0732 (0.0706) time: 2.8984 data: 0.0076 max mem: 33370 +Epoch: [13] [1420/2639] eta: 0:59:03 lr: 3.447224703870746e-05 loss: 0.0672 (0.0707) time: 2.8984 data: 0.0077 max mem: 33370 +Epoch: [13] [1430/2639] eta: 0:58:34 lr: 3.446780419810617e-05 loss: 0.0661 (0.0707) time: 2.9064 data: 0.0076 max mem: 33370 +Epoch: [13] [1440/2639] eta: 0:58:05 lr: 3.4463361293873466e-05 loss: 0.0728 (0.0708) time: 2.8874 data: 0.0081 max mem: 33370 +Epoch: [13] [1450/2639] eta: 0:57:36 lr: 3.4458918325999324e-05 loss: 0.0714 (0.0708) time: 2.8944 data: 0.0083 max mem: 33370 +Epoch: [13] [1460/2639] eta: 0:57:06 lr: 3.445447529447371e-05 loss: 0.0664 (0.0708) time: 2.9011 data: 0.0084 max mem: 33370 +Epoch: [13] [1470/2639] eta: 0:56:37 lr: 3.445003219928661e-05 loss: 0.0720 (0.0709) time: 2.8757 data: 0.0082 max mem: 33370 +Epoch: [13] [1480/2639] eta: 0:56:08 lr: 3.4445589040427965e-05 loss: 0.0753 (0.0709) time: 2.8701 data: 0.0080 max mem: 33370 +Epoch: [13] [1490/2639] eta: 0:55:39 lr: 3.4441145817887744e-05 loss: 0.0753 (0.0710) time: 2.9155 data: 0.0080 max mem: 33370 +Epoch: [13] [1500/2639] eta: 0:55:10 lr: 3.443670253165592e-05 loss: 0.0659 (0.0709) time: 2.9603 data: 0.0079 max mem: 33370 +Epoch: [13] [1510/2639] eta: 0:54:41 lr: 3.443225918172243e-05 loss: 0.0624 (0.0710) time: 2.9276 data: 0.0080 max mem: 33370 +Epoch: [13] [1520/2639] eta: 0:54:12 lr: 3.442781576807723e-05 loss: 0.0634 (0.0710) time: 2.8853 data: 0.0078 max mem: 33370 +Epoch: [13] [1530/2639] eta: 0:53:42 lr: 3.442337229071028e-05 loss: 0.0634 (0.0710) time: 2.8480 data: 0.0075 max mem: 33370 +Epoch: [13] [1540/2639] eta: 0:53:13 lr: 3.441892874961152e-05 loss: 0.0596 (0.0710) time: 2.8389 data: 0.0074 max mem: 33370 +Epoch: [13] [1550/2639] eta: 0:52:44 lr: 3.44144851447709e-05 loss: 0.0528 (0.0709) time: 2.8728 data: 0.0077 max mem: 33370 +Epoch: [13] [1560/2639] eta: 0:52:15 lr: 3.441004147617834e-05 loss: 0.0570 (0.0710) time: 2.9218 data: 0.0077 max mem: 33370 +Epoch: [13] [1570/2639] eta: 0:51:46 lr: 3.440559774382379e-05 loss: 0.0717 (0.0711) time: 2.9060 data: 0.0076 max mem: 33370 +Epoch: [13] [1580/2639] eta: 0:51:17 lr: 3.44011539476972e-05 loss: 0.0635 (0.0710) time: 2.8820 data: 0.0076 max mem: 33370 +Epoch: [13] [1590/2639] eta: 0:50:47 lr: 3.439671008778848e-05 loss: 0.0656 (0.0711) time: 2.8928 data: 0.0078 max mem: 33370 +Epoch: [13] [1600/2639] eta: 0:50:18 lr: 3.4392266164087575e-05 loss: 0.0626 (0.0710) time: 2.9000 data: 0.0078 max mem: 33370 +Epoch: [13] [1610/2639] eta: 0:49:49 lr: 3.438782217658439e-05 loss: 0.0582 (0.0710) time: 2.9007 data: 0.0076 max mem: 33370 +Epoch: [13] [1620/2639] eta: 0:49:20 lr: 3.438337812526886e-05 loss: 0.0585 (0.0710) time: 2.8730 data: 0.0077 max mem: 33370 +Epoch: [13] [1630/2639] eta: 0:48:51 lr: 3.4378934010130904e-05 loss: 0.0563 (0.0709) time: 2.8622 data: 0.0081 max mem: 33370 +Epoch: [13] [1640/2639] eta: 0:48:21 lr: 3.437448983116044e-05 loss: 0.0581 (0.0710) time: 2.8691 data: 0.0082 max mem: 33370 +Epoch: [13] [1650/2639] eta: 0:47:52 lr: 3.437004558834738e-05 loss: 0.0663 (0.0709) time: 2.8731 data: 0.0083 max mem: 33370 +Epoch: [13] [1660/2639] eta: 0:47:23 lr: 3.4365601281681624e-05 loss: 0.0647 (0.0709) time: 2.9062 data: 0.0088 max mem: 33370 +Epoch: [13] [1670/2639] eta: 0:46:54 lr: 3.4361156911153096e-05 loss: 0.0597 (0.0709) time: 2.9043 data: 0.0086 max mem: 33370 +Epoch: [13] [1680/2639] eta: 0:46:25 lr: 3.435671247675169e-05 loss: 0.0592 (0.0708) time: 2.8750 data: 0.0082 max mem: 33370 +Epoch: [13] [1690/2639] eta: 0:45:55 lr: 3.43522679784673e-05 loss: 0.0660 (0.0709) time: 2.8531 data: 0.0079 max mem: 33370 +Epoch: [13] [1700/2639] eta: 0:45:27 lr: 3.4347823416289846e-05 loss: 0.0646 (0.0709) time: 2.8885 data: 0.0074 max mem: 33370 +Epoch: [13] [1710/2639] eta: 0:44:58 lr: 3.43433787902092e-05 loss: 0.0597 (0.0709) time: 2.9409 data: 0.0074 max mem: 33370 +Epoch: [13] [1720/2639] eta: 0:44:28 lr: 3.433893410021528e-05 loss: 0.0639 (0.0708) time: 2.8775 data: 0.0080 max mem: 33370 +Epoch: [13] [1730/2639] eta: 0:43:59 lr: 3.433448934629794e-05 loss: 0.0637 (0.0709) time: 2.8678 data: 0.0083 max mem: 33370 +Epoch: [13] [1740/2639] eta: 0:43:30 lr: 3.433004452844708e-05 loss: 0.0594 (0.0708) time: 2.9061 data: 0.0079 max mem: 33370 +Epoch: [13] [1750/2639] eta: 0:43:01 lr: 3.43255996466526e-05 loss: 0.0612 (0.0709) time: 2.8978 data: 0.0077 max mem: 33370 +Epoch: [13] [1760/2639] eta: 0:42:32 lr: 3.432115470090437e-05 loss: 0.0580 (0.0708) time: 2.8802 data: 0.0076 max mem: 33370 +Epoch: [13] [1770/2639] eta: 0:42:03 lr: 3.431670969119225e-05 loss: 0.0543 (0.0708) time: 2.8891 data: 0.0076 max mem: 33370 +Epoch: [13] [1780/2639] eta: 0:41:34 lr: 3.431226461750613e-05 loss: 0.0650 (0.0708) time: 2.9075 data: 0.0077 max mem: 33370 +Epoch: [13] [1790/2639] eta: 0:41:05 lr: 3.430781947983588e-05 loss: 0.0650 (0.0709) time: 2.8774 data: 0.0077 max mem: 33370 +Epoch: [13] [1800/2639] eta: 0:40:36 lr: 3.430337427817137e-05 loss: 0.0695 (0.0709) time: 2.8991 data: 0.0078 max mem: 33370 +Epoch: [13] [1810/2639] eta: 0:40:07 lr: 3.429892901250245e-05 loss: 0.0695 (0.0710) time: 2.9621 data: 0.0085 max mem: 33370 +Epoch: [13] [1820/2639] eta: 0:39:38 lr: 3.429448368281898e-05 loss: 0.0624 (0.0710) time: 2.9225 data: 0.0086 max mem: 33370 +Epoch: [13] [1830/2639] eta: 0:39:09 lr: 3.429003828911085e-05 loss: 0.0612 (0.0710) time: 2.8688 data: 0.0084 max mem: 33370 +Epoch: [13] [1840/2639] eta: 0:38:39 lr: 3.428559283136788e-05 loss: 0.0686 (0.0711) time: 2.8780 data: 0.0087 max mem: 33370 +Epoch: [13] [1850/2639] eta: 0:38:10 lr: 3.428114730957994e-05 loss: 0.0762 (0.0711) time: 2.8814 data: 0.0084 max mem: 33370 +Epoch: [13] [1860/2639] eta: 0:37:41 lr: 3.427670172373687e-05 loss: 0.0588 (0.0711) time: 2.8819 data: 0.0080 max mem: 33370 +Epoch: [13] [1870/2639] eta: 0:37:12 lr: 3.4272256073828523e-05 loss: 0.0585 (0.0710) time: 2.9223 data: 0.0081 max mem: 33370 +Epoch: [13] [1880/2639] eta: 0:36:43 lr: 3.426781035984474e-05 loss: 0.0631 (0.0711) time: 2.9142 data: 0.0079 max mem: 33370 +Epoch: [13] [1890/2639] eta: 0:36:14 lr: 3.426336458177536e-05 loss: 0.0650 (0.0711) time: 2.8955 data: 0.0081 max mem: 33370 +Epoch: [13] [1900/2639] eta: 0:35:45 lr: 3.425891873961021e-05 loss: 0.0649 (0.0711) time: 2.9205 data: 0.0085 max mem: 33370 +Epoch: [13] [1910/2639] eta: 0:35:16 lr: 3.425447283333914e-05 loss: 0.0597 (0.0711) time: 2.9146 data: 0.0081 max mem: 33370 +Epoch: [13] [1920/2639] eta: 0:34:47 lr: 3.4250026862951986e-05 loss: 0.0591 (0.0711) time: 2.8860 data: 0.0078 max mem: 33370 +Epoch: [13] [1930/2639] eta: 0:34:18 lr: 3.424558082843855e-05 loss: 0.0625 (0.0711) time: 2.8689 data: 0.0076 max mem: 33370 +Epoch: [13] [1940/2639] eta: 0:33:49 lr: 3.424113472978867e-05 loss: 0.0604 (0.0710) time: 2.8426 data: 0.0076 max mem: 33370 +Epoch: [13] [1950/2639] eta: 0:33:20 lr: 3.423668856699216e-05 loss: 0.0649 (0.0711) time: 2.8629 data: 0.0081 max mem: 33370 +Epoch: [13] [1960/2639] eta: 0:32:50 lr: 3.423224234003886e-05 loss: 0.0748 (0.0712) time: 2.8896 data: 0.0080 max mem: 33370 +Epoch: [13] [1970/2639] eta: 0:32:21 lr: 3.422779604891857e-05 loss: 0.0655 (0.0711) time: 2.8908 data: 0.0074 max mem: 33370 +Epoch: [13] [1980/2639] eta: 0:31:52 lr: 3.422334969362109e-05 loss: 0.0640 (0.0712) time: 2.8995 data: 0.0078 max mem: 33370 +Epoch: [13] [1990/2639] eta: 0:31:23 lr: 3.421890327413625e-05 loss: 0.0649 (0.0711) time: 2.8801 data: 0.0079 max mem: 33370 +Epoch: [13] [2000/2639] eta: 0:30:54 lr: 3.4214456790453845e-05 loss: 0.0649 (0.0711) time: 2.8669 data: 0.0077 max mem: 33370 +Epoch: [13] [2010/2639] eta: 0:30:25 lr: 3.421001024256369e-05 loss: 0.0603 (0.0711) time: 2.8870 data: 0.0079 max mem: 33370 +Epoch: [13] [2020/2639] eta: 0:29:56 lr: 3.420556363045556e-05 loss: 0.0603 (0.0712) time: 2.8873 data: 0.0084 max mem: 33370 +Epoch: [13] [2030/2639] eta: 0:29:27 lr: 3.420111695411927e-05 loss: 0.0632 (0.0712) time: 2.8838 data: 0.0079 max mem: 33370 +Epoch: [13] [2040/2639] eta: 0:28:58 lr: 3.419667021354461e-05 loss: 0.0624 (0.0712) time: 2.8943 data: 0.0075 max mem: 33370 +Epoch: [13] [2050/2639] eta: 0:28:29 lr: 3.4192223408721373e-05 loss: 0.0624 (0.0712) time: 2.8956 data: 0.0079 max mem: 33370 +Epoch: [13] [2060/2639] eta: 0:28:00 lr: 3.418777653963934e-05 loss: 0.0642 (0.0712) time: 2.9002 data: 0.0083 max mem: 33370 +Epoch: [13] [2070/2639] eta: 0:27:31 lr: 3.4183329606288295e-05 loss: 0.0646 (0.0712) time: 2.8601 data: 0.0083 max mem: 33370 +Epoch: [13] [2080/2639] eta: 0:27:02 lr: 3.417888260865803e-05 loss: 0.0640 (0.0711) time: 2.8808 data: 0.0077 max mem: 33370 +Epoch: [13] [2090/2639] eta: 0:26:33 lr: 3.417443554673831e-05 loss: 0.0690 (0.0711) time: 2.9185 data: 0.0074 max mem: 33370 +Epoch: [13] [2100/2639] eta: 0:26:04 lr: 3.416998842051892e-05 loss: 0.0704 (0.0711) time: 2.8958 data: 0.0077 max mem: 33370 +Epoch: [13] [2110/2639] eta: 0:25:35 lr: 3.416554122998962e-05 loss: 0.0607 (0.0711) time: 2.8918 data: 0.0077 max mem: 33370 +Epoch: [13] [2120/2639] eta: 0:25:06 lr: 3.4161093975140204e-05 loss: 0.0607 (0.0711) time: 2.9021 data: 0.0075 max mem: 33370 +Epoch: [13] [2130/2639] eta: 0:24:36 lr: 3.4156646655960404e-05 loss: 0.0684 (0.0711) time: 2.8725 data: 0.0072 max mem: 33370 +Epoch: [13] [2140/2639] eta: 0:24:07 lr: 3.415219927244e-05 loss: 0.0684 (0.0711) time: 2.8228 data: 0.0075 max mem: 33370 +Epoch: [13] [2150/2639] eta: 0:23:38 lr: 3.4147751824568744e-05 loss: 0.0668 (0.0712) time: 2.8354 data: 0.0078 max mem: 33370 +Epoch: [13] [2160/2639] eta: 0:23:09 lr: 3.4143304312336406e-05 loss: 0.0737 (0.0712) time: 2.9045 data: 0.0076 max mem: 33370 +Epoch: [13] [2170/2639] eta: 0:22:40 lr: 3.4138856735732736e-05 loss: 0.0739 (0.0712) time: 2.9057 data: 0.0075 max mem: 33370 +Epoch: [13] [2180/2639] eta: 0:22:11 lr: 3.413440909474747e-05 loss: 0.0698 (0.0712) time: 2.8939 data: 0.0077 max mem: 33370 +Epoch: [13] [2190/2639] eta: 0:21:42 lr: 3.412996138937036e-05 loss: 0.0617 (0.0712) time: 2.9132 data: 0.0078 max mem: 33370 +Epoch: [13] [2200/2639] eta: 0:21:13 lr: 3.412551361959116e-05 loss: 0.0692 (0.0712) time: 2.9291 data: 0.0077 max mem: 33370 +Epoch: [13] [2210/2639] eta: 0:20:44 lr: 3.41210657853996e-05 loss: 0.0600 (0.0712) time: 2.9163 data: 0.0078 max mem: 33370 +Epoch: [13] [2220/2639] eta: 0:20:15 lr: 3.411661788678543e-05 loss: 0.0600 (0.0713) time: 2.8763 data: 0.0080 max mem: 33370 +Epoch: [13] [2230/2639] eta: 0:19:46 lr: 3.411216992373837e-05 loss: 0.0610 (0.0712) time: 2.8916 data: 0.0079 max mem: 33370 +Epoch: [13] [2240/2639] eta: 0:19:17 lr: 3.410772189624815e-05 loss: 0.0586 (0.0712) time: 2.9094 data: 0.0079 max mem: 33370 +Epoch: [13] [2250/2639] eta: 0:18:48 lr: 3.410327380430452e-05 loss: 0.0585 (0.0713) time: 2.9185 data: 0.0080 max mem: 33370 +Epoch: [13] [2260/2639] eta: 0:18:19 lr: 3.409882564789719e-05 loss: 0.0553 (0.0713) time: 2.9181 data: 0.0080 max mem: 33370 +Epoch: [13] [2270/2639] eta: 0:17:50 lr: 3.409437742701587e-05 loss: 0.0644 (0.0713) time: 2.8784 data: 0.0080 max mem: 33370 +Epoch: [13] [2280/2639] eta: 0:17:21 lr: 3.4089929141650295e-05 loss: 0.0644 (0.0713) time: 2.8633 data: 0.0077 max mem: 33370 +Epoch: [13] [2290/2639] eta: 0:16:52 lr: 3.408548079179018e-05 loss: 0.0646 (0.0713) time: 2.8950 data: 0.0078 max mem: 33370 +Epoch: [13] [2300/2639] eta: 0:16:23 lr: 3.408103237742524e-05 loss: 0.0617 (0.0713) time: 2.9004 data: 0.0078 max mem: 33370 +Epoch: [13] [2310/2639] eta: 0:15:54 lr: 3.4076583898545166e-05 loss: 0.0617 (0.0713) time: 2.8943 data: 0.0077 max mem: 33370 +Epoch: [13] [2320/2639] eta: 0:15:25 lr: 3.407213535513968e-05 loss: 0.0654 (0.0714) time: 2.8808 data: 0.0077 max mem: 33370 +Epoch: [13] [2330/2639] eta: 0:14:56 lr: 3.4067686747198494e-05 loss: 0.0698 (0.0714) time: 2.8820 data: 0.0081 max mem: 33370 +Epoch: [13] [2340/2639] eta: 0:14:27 lr: 3.406323807471129e-05 loss: 0.0690 (0.0714) time: 2.8836 data: 0.0081 max mem: 33370 +Epoch: [13] [2350/2639] eta: 0:13:58 lr: 3.405878933766776e-05 loss: 0.0602 (0.0714) time: 2.8561 data: 0.0079 max mem: 33370 +Epoch: [13] [2360/2639] eta: 0:13:29 lr: 3.4054340536057614e-05 loss: 0.0634 (0.0714) time: 2.8776 data: 0.0080 max mem: 33370 +Epoch: [13] [2370/2639] eta: 0:13:00 lr: 3.404989166987054e-05 loss: 0.0634 (0.0714) time: 2.8900 data: 0.0077 max mem: 33370 +Epoch: [13] [2380/2639] eta: 0:12:31 lr: 3.404544273909623e-05 loss: 0.0641 (0.0713) time: 2.9169 data: 0.0080 max mem: 33370 +Epoch: [13] [2390/2639] eta: 0:12:02 lr: 3.404099374372435e-05 loss: 0.0641 (0.0714) time: 2.8953 data: 0.0082 max mem: 33370 +Epoch: [13] [2400/2639] eta: 0:11:33 lr: 3.40365446837446e-05 loss: 0.0583 (0.0713) time: 2.8832 data: 0.0079 max mem: 33370 +Epoch: [13] [2410/2639] eta: 0:11:04 lr: 3.4032095559146644e-05 loss: 0.0580 (0.0712) time: 2.9147 data: 0.0078 max mem: 33370 +Epoch: [13] [2420/2639] eta: 0:10:35 lr: 3.402764636992017e-05 loss: 0.0604 (0.0712) time: 2.9030 data: 0.0079 max mem: 33370 +Epoch: [13] [2430/2639] eta: 0:10:06 lr: 3.402319711605483e-05 loss: 0.0604 (0.0712) time: 2.9325 data: 0.0077 max mem: 33370 +Epoch: [13] [2440/2639] eta: 0:09:37 lr: 3.401874779754032e-05 loss: 0.0700 (0.0714) time: 2.9135 data: 0.0076 max mem: 33370 +Epoch: [13] [2450/2639] eta: 0:09:08 lr: 3.401429841436627e-05 loss: 0.0700 (0.0714) time: 2.8901 data: 0.0074 max mem: 33370 +Epoch: [13] [2460/2639] eta: 0:08:39 lr: 3.4009848966522386e-05 loss: 0.0646 (0.0714) time: 2.9124 data: 0.0078 max mem: 33370 +Epoch: [13] [2470/2639] eta: 0:08:10 lr: 3.400539945399829e-05 loss: 0.0679 (0.0714) time: 2.9305 data: 0.0079 max mem: 33370 +Epoch: [13] [2480/2639] eta: 0:07:41 lr: 3.4000949876783654e-05 loss: 0.0644 (0.0713) time: 2.9197 data: 0.0077 max mem: 33370 +Epoch: [13] [2490/2639] eta: 0:07:12 lr: 3.399650023486813e-05 loss: 0.0591 (0.0713) time: 2.8820 data: 0.0081 max mem: 33370 +Epoch: [13] [2500/2639] eta: 0:06:43 lr: 3.399205052824137e-05 loss: 0.0646 (0.0713) time: 2.8643 data: 0.0079 max mem: 33370 +Epoch: [13] [2510/2639] eta: 0:06:14 lr: 3.3987600756893015e-05 loss: 0.0659 (0.0713) time: 2.8504 data: 0.0074 max mem: 33370 +Epoch: [13] [2520/2639] eta: 0:05:45 lr: 3.39831509208127e-05 loss: 0.0710 (0.0714) time: 2.8388 data: 0.0072 max mem: 33370 +Epoch: [13] [2530/2639] eta: 0:05:16 lr: 3.3978701019990076e-05 loss: 0.0630 (0.0714) time: 2.8599 data: 0.0073 max mem: 33370 +Epoch: [13] [2540/2639] eta: 0:04:47 lr: 3.397425105441479e-05 loss: 0.0602 (0.0714) time: 2.8909 data: 0.0073 max mem: 33370 +Epoch: [13] [2550/2639] eta: 0:04:18 lr: 3.396980102407646e-05 loss: 0.0691 (0.0714) time: 2.8912 data: 0.0072 max mem: 33370 +Epoch: [13] [2560/2639] eta: 0:03:49 lr: 3.396535092896472e-05 loss: 0.0600 (0.0714) time: 2.9224 data: 0.0076 max mem: 33370 +Epoch: [13] [2570/2639] eta: 0:03:20 lr: 3.396090076906919e-05 loss: 0.0793 (0.0715) time: 2.8977 data: 0.0076 max mem: 33370 +Epoch: [13] [2580/2639] eta: 0:02:51 lr: 3.395645054437951e-05 loss: 0.0754 (0.0715) time: 2.8739 data: 0.0075 max mem: 33370 +Epoch: [13] [2590/2639] eta: 0:02:22 lr: 3.39520002548853e-05 loss: 0.0572 (0.0715) time: 2.9001 data: 0.0079 max mem: 33370 +Epoch: [13] [2600/2639] eta: 0:01:53 lr: 3.394754990057617e-05 loss: 0.0602 (0.0715) time: 2.8637 data: 0.0078 max mem: 33370 +Epoch: [13] [2610/2639] eta: 0:01:24 lr: 3.3943099481441724e-05 loss: 0.0668 (0.0715) time: 2.8544 data: 0.0075 max mem: 33370 +Epoch: [13] [2620/2639] eta: 0:00:55 lr: 3.3938648997471594e-05 loss: 0.0683 (0.0717) time: 2.9059 data: 0.0074 max mem: 33370 +Epoch: [13] [2630/2639] eta: 0:00:26 lr: 3.393419844865539e-05 loss: 0.0688 (0.0717) time: 2.9094 data: 0.0072 max mem: 33370 +Epoch: [13] Total time: 2:07:32 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 2:25:25 time: 3.3910 data: 3.2692 max mem: 33370 +Test: [ 100/2573] eta: 0:04:35 time: 0.0777 data: 0.0015 max mem: 33370 +Test: [ 200/2573] eta: 0:03:47 time: 0.0795 data: 0.0014 max mem: 33370 +Test: [ 300/2573] eta: 0:03:24 time: 0.0811 data: 0.0014 max mem: 33370 +Test: [ 400/2573] eta: 0:03:09 time: 0.0811 data: 0.0013 max mem: 33370 +Test: [ 500/2573] eta: 0:02:57 time: 0.0798 data: 0.0015 max mem: 33370 +Test: [ 600/2573] eta: 0:02:47 time: 0.0812 data: 0.0016 max mem: 33370 +Test: [ 700/2573] eta: 0:02:38 time: 0.0795 data: 0.0015 max mem: 33370 +Test: [ 800/2573] eta: 0:02:29 time: 0.0841 data: 0.0015 max mem: 33370 +Test: [ 900/2573] eta: 0:02:20 time: 0.0815 data: 0.0015 max mem: 33370 +Test: [1000/2573] eta: 0:02:11 time: 0.0814 data: 0.0015 max mem: 33370 +Test: [1100/2573] eta: 0:02:03 time: 0.0812 data: 0.0014 max mem: 33370 +Test: [1200/2573] eta: 0:01:54 time: 0.0810 data: 0.0013 max mem: 33370 +Test: [1300/2573] eta: 0:01:46 time: 0.0805 data: 0.0014 max mem: 33370 +Test: [1400/2573] eta: 0:01:37 time: 0.0785 data: 0.0016 max mem: 33370 +Test: [1500/2573] eta: 0:01:29 time: 0.0819 data: 0.0015 max mem: 33370 +Test: [1600/2573] eta: 0:01:20 time: 0.0840 data: 0.0015 max mem: 33370 +Test: [1700/2573] eta: 0:01:12 time: 0.0794 data: 0.0014 max mem: 33370 +Test: [1800/2573] eta: 0:01:03 time: 0.0817 data: 0.0014 max mem: 33370 +Test: [1900/2573] eta: 0:00:55 time: 0.0792 data: 0.0014 max mem: 33370 +Test: [2000/2573] eta: 0:00:47 time: 0.0810 data: 0.0015 max mem: 33370 +Test: [2100/2573] eta: 0:00:38 time: 0.0832 data: 0.0014 max mem: 33370 +Test: [2200/2573] eta: 0:00:30 time: 0.0822 data: 0.0013 max mem: 33370 +Test: [2300/2573] eta: 0:00:22 time: 0.0828 data: 0.0014 max mem: 33370 +Test: [2400/2573] eta: 0:00:14 time: 0.0778 data: 0.0014 max mem: 33370 +Test: [2500/2573] eta: 0:00:05 time: 0.0800 data: 0.0014 max mem: 33370 +Test: Total time: 0:03:31 +Final results: +Mean IoU is 59.67 + + precision@0.5 = 67.18 + precision@0.6 = 61.50 + precision@0.7 = 54.43 + precision@0.8 = 42.61 + precision@0.9 = 20.02 + overall IoU = 58.33 + +Average object IoU 59.67273502557124 +Overall IoU 58.327728271484375 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [14] [ 0/2639] eta: 4:52:20 lr: 3.3930192899268806e-05 loss: 0.0449 (0.0449) time: 6.6465 data: 3.5252 max mem: 33370 +Epoch: [14] [ 10/2639] eta: 2:22:42 lr: 3.3925742227216386e-05 loss: 0.0526 (0.0882) time: 3.2568 data: 0.3282 max mem: 33370 +Epoch: [14] [ 20/2639] eta: 2:14:58 lr: 3.392129149028774e-05 loss: 0.0540 (0.0747) time: 2.9144 data: 0.0082 max mem: 33370 +Epoch: [14] [ 30/2639] eta: 2:11:48 lr: 3.391684068847245e-05 loss: 0.0560 (0.0703) time: 2.9074 data: 0.0081 max mem: 33370 +Epoch: [14] [ 40/2639] eta: 2:10:19 lr: 3.391238982176011e-05 loss: 0.0524 (0.0695) time: 2.9207 data: 0.0078 max mem: 33370 +Epoch: [14] [ 50/2639] eta: 2:08:44 lr: 3.390793889014031e-05 loss: 0.0524 (0.0670) time: 2.9100 data: 0.0076 max mem: 33370 +Epoch: [14] [ 60/2639] eta: 2:07:35 lr: 3.3903487893602645e-05 loss: 0.0556 (0.0678) time: 2.8863 data: 0.0080 max mem: 33370 +Epoch: [14] [ 70/2639] eta: 2:06:40 lr: 3.389903683213668e-05 loss: 0.0580 (0.0686) time: 2.8947 data: 0.0082 max mem: 33370 +Epoch: [14] [ 80/2639] eta: 2:05:50 lr: 3.3894585705732013e-05 loss: 0.0580 (0.0676) time: 2.8965 data: 0.0080 max mem: 33370 +Epoch: [14] [ 90/2639] eta: 2:05:00 lr: 3.389013451437821e-05 loss: 0.0643 (0.0686) time: 2.8851 data: 0.0078 max mem: 33370 +Epoch: [14] [ 100/2639] eta: 2:04:20 lr: 3.388568325806485e-05 loss: 0.0633 (0.0681) time: 2.8877 data: 0.0078 max mem: 33370 +Epoch: [14] [ 110/2639] eta: 2:03:45 lr: 3.3881231936781504e-05 loss: 0.0589 (0.0682) time: 2.9071 data: 0.0076 max mem: 33370 +Epoch: [14] [ 120/2639] eta: 2:03:07 lr: 3.387678055051773e-05 loss: 0.0643 (0.0684) time: 2.9040 data: 0.0077 max mem: 33370 +Epoch: [14] [ 130/2639] eta: 2:02:30 lr: 3.3872329099263104e-05 loss: 0.0643 (0.0693) time: 2.8931 data: 0.0079 max mem: 33370 +Epoch: [14] [ 140/2639] eta: 2:02:08 lr: 3.386787758300718e-05 loss: 0.0537 (0.0682) time: 2.9337 data: 0.0082 max mem: 33370 +Epoch: [14] [ 150/2639] eta: 2:01:41 lr: 3.386342600173952e-05 loss: 0.0575 (0.0682) time: 2.9608 data: 0.0081 max mem: 33370 +Epoch: [14] [ 160/2639] eta: 2:01:14 lr: 3.385897435544967e-05 loss: 0.0628 (0.0679) time: 2.9465 data: 0.0078 max mem: 33370 +Epoch: [14] [ 170/2639] eta: 2:00:39 lr: 3.3854522644127193e-05 loss: 0.0538 (0.0684) time: 2.9218 data: 0.0082 max mem: 33370 +Epoch: [14] [ 180/2639] eta: 2:00:03 lr: 3.385007086776163e-05 loss: 0.0570 (0.0682) time: 2.8911 data: 0.0083 max mem: 33370 +Epoch: [14] [ 190/2639] eta: 1:59:32 lr: 3.384561902634252e-05 loss: 0.0614 (0.0683) time: 2.8991 data: 0.0080 max mem: 33370 +Epoch: [14] [ 200/2639] eta: 1:58:58 lr: 3.384116711985942e-05 loss: 0.0617 (0.0680) time: 2.9028 data: 0.0081 max mem: 33370 +Epoch: [14] [ 210/2639] eta: 1:58:31 lr: 3.383671514830185e-05 loss: 0.0539 (0.0677) time: 2.9180 data: 0.0082 max mem: 33370 +Epoch: [14] [ 220/2639] eta: 1:57:58 lr: 3.383226311165937e-05 loss: 0.0515 (0.0670) time: 2.9174 data: 0.0082 max mem: 33370 +Epoch: [14] [ 230/2639] eta: 1:57:25 lr: 3.382781100992149e-05 loss: 0.0478 (0.0667) time: 2.8920 data: 0.0086 max mem: 33370 +Epoch: [14] [ 240/2639] eta: 1:56:52 lr: 3.382335884307774e-05 loss: 0.0586 (0.0665) time: 2.8881 data: 0.0084 max mem: 33370 +Epoch: [14] [ 250/2639] eta: 1:56:20 lr: 3.3818906611117655e-05 loss: 0.0596 (0.0664) time: 2.8918 data: 0.0079 max mem: 33370 +Epoch: [14] [ 260/2639] eta: 1:55:51 lr: 3.381445431403075e-05 loss: 0.0609 (0.0666) time: 2.9135 data: 0.0074 max mem: 33370 +Epoch: [14] [ 270/2639] eta: 1:55:26 lr: 3.381000195180656e-05 loss: 0.0656 (0.0669) time: 2.9466 data: 0.0075 max mem: 33370 +Epoch: [14] [ 280/2639] eta: 1:55:01 lr: 3.380554952443458e-05 loss: 0.0644 (0.0666) time: 2.9683 data: 0.0078 max mem: 33370 +Epoch: [14] [ 290/2639] eta: 1:54:33 lr: 3.380109703190433e-05 loss: 0.0591 (0.0663) time: 2.9538 data: 0.0077 max mem: 33370 +Epoch: [14] [ 300/2639] eta: 1:54:03 lr: 3.3796644474205325e-05 loss: 0.0621 (0.0663) time: 2.9320 data: 0.0075 max mem: 33370 +Epoch: [14] [ 310/2639] eta: 1:53:33 lr: 3.379219185132707e-05 loss: 0.0532 (0.0660) time: 2.9212 data: 0.0077 max mem: 33370 +Epoch: [14] [ 320/2639] eta: 1:53:08 lr: 3.378773916325906e-05 loss: 0.0478 (0.0657) time: 2.9459 data: 0.0077 max mem: 33370 +Epoch: [14] [ 330/2639] eta: 1:52:37 lr: 3.378328640999081e-05 loss: 0.0511 (0.0659) time: 2.9420 data: 0.0076 max mem: 33370 +Epoch: [14] [ 340/2639] eta: 1:52:03 lr: 3.377883359151179e-05 loss: 0.0511 (0.0657) time: 2.8835 data: 0.0079 max mem: 33370 +Epoch: [14] [ 350/2639] eta: 1:51:28 lr: 3.377438070781152e-05 loss: 0.0545 (0.0654) time: 2.8448 data: 0.0082 max mem: 33370 +Epoch: [14] [ 360/2639] eta: 1:50:58 lr: 3.3769927758879474e-05 loss: 0.0582 (0.0659) time: 2.8749 data: 0.0083 max mem: 33370 +Epoch: [14] [ 370/2639] eta: 1:50:31 lr: 3.376547474470515e-05 loss: 0.0670 (0.0663) time: 2.9324 data: 0.0081 max mem: 33370 +Epoch: [14] [ 380/2639] eta: 1:50:00 lr: 3.376102166527802e-05 loss: 0.0607 (0.0660) time: 2.9229 data: 0.0079 max mem: 33370 +Epoch: [14] [ 390/2639] eta: 1:49:31 lr: 3.375656852058758e-05 loss: 0.0633 (0.0662) time: 2.9123 data: 0.0077 max mem: 33370 +Epoch: [14] [ 400/2639] eta: 1:49:06 lr: 3.375211531062329e-05 loss: 0.0708 (0.0664) time: 2.9628 data: 0.0076 max mem: 33370 +Epoch: [14] [ 410/2639] eta: 1:48:35 lr: 3.3747662035374635e-05 loss: 0.0603 (0.0663) time: 2.9463 data: 0.0078 max mem: 33370 +Epoch: [14] [ 420/2639] eta: 1:48:00 lr: 3.3743208694831075e-05 loss: 0.0571 (0.0663) time: 2.8526 data: 0.0080 max mem: 33370 +Epoch: [14] [ 430/2639] eta: 1:47:28 lr: 3.3738755288982095e-05 loss: 0.0566 (0.0662) time: 2.8366 data: 0.0079 max mem: 33370 +Epoch: [14] [ 440/2639] eta: 1:47:00 lr: 3.3734301817817144e-05 loss: 0.0622 (0.0668) time: 2.8985 data: 0.0081 max mem: 33370 +Epoch: [14] [ 450/2639] eta: 1:46:27 lr: 3.3729848281325684e-05 loss: 0.0557 (0.0669) time: 2.8943 data: 0.0080 max mem: 33370 +Epoch: [14] [ 460/2639] eta: 1:45:57 lr: 3.372539467949718e-05 loss: 0.0529 (0.0668) time: 2.8764 data: 0.0075 max mem: 33370 +Epoch: [14] [ 470/2639] eta: 1:45:23 lr: 3.372094101232109e-05 loss: 0.0535 (0.0665) time: 2.8555 data: 0.0080 max mem: 33370 +Epoch: [14] [ 480/2639] eta: 1:44:54 lr: 3.3716487279786854e-05 loss: 0.0512 (0.0664) time: 2.8661 data: 0.0082 max mem: 33370 +Epoch: [14] [ 490/2639] eta: 1:44:21 lr: 3.371203348188392e-05 loss: 0.0562 (0.0665) time: 2.8674 data: 0.0080 max mem: 33370 +Epoch: [14] [ 500/2639] eta: 1:43:49 lr: 3.370757961860173e-05 loss: 0.0567 (0.0662) time: 2.8400 data: 0.0080 max mem: 33370 +Epoch: [14] [ 510/2639] eta: 1:43:20 lr: 3.3703125689929736e-05 loss: 0.0509 (0.0663) time: 2.8900 data: 0.0081 max mem: 33370 +Epoch: [14] [ 520/2639] eta: 1:42:49 lr: 3.369867169585738e-05 loss: 0.0585 (0.0663) time: 2.8848 data: 0.0083 max mem: 33370 +Epoch: [14] [ 530/2639] eta: 1:42:19 lr: 3.3694217636374085e-05 loss: 0.0640 (0.0663) time: 2.8773 data: 0.0083 max mem: 33370 +Epoch: [14] [ 540/2639] eta: 1:41:51 lr: 3.368976351146929e-05 loss: 0.0651 (0.0663) time: 2.9154 data: 0.0081 max mem: 33370 +Epoch: [14] [ 550/2639] eta: 1:41:23 lr: 3.368530932113241e-05 loss: 0.0655 (0.0663) time: 2.9340 data: 0.0085 max mem: 33370 +Epoch: [14] [ 560/2639] eta: 1:40:56 lr: 3.368085506535289e-05 loss: 0.0598 (0.0661) time: 2.9524 data: 0.0085 max mem: 33370 +Epoch: [14] [ 570/2639] eta: 1:40:28 lr: 3.367640074412014e-05 loss: 0.0597 (0.0663) time: 2.9595 data: 0.0079 max mem: 33370 +Epoch: [14] [ 580/2639] eta: 1:39:58 lr: 3.3671946357423575e-05 loss: 0.0601 (0.0662) time: 2.9204 data: 0.0080 max mem: 33370 +Epoch: [14] [ 590/2639] eta: 1:39:27 lr: 3.3667491905252616e-05 loss: 0.0532 (0.0659) time: 2.8687 data: 0.0081 max mem: 33370 +Epoch: [14] [ 600/2639] eta: 1:38:57 lr: 3.366303738759669e-05 loss: 0.0487 (0.0661) time: 2.8768 data: 0.0081 max mem: 33370 +Epoch: [14] [ 610/2639] eta: 1:38:26 lr: 3.3658582804445175e-05 loss: 0.0603 (0.0660) time: 2.8707 data: 0.0079 max mem: 33370 +Epoch: [14] [ 620/2639] eta: 1:37:55 lr: 3.3654128155787496e-05 loss: 0.0622 (0.0659) time: 2.8570 data: 0.0076 max mem: 33370 +Epoch: [14] [ 630/2639] eta: 1:37:29 lr: 3.364967344161305e-05 loss: 0.0629 (0.0658) time: 2.9383 data: 0.0078 max mem: 33370 +Epoch: [14] [ 640/2639] eta: 1:36:59 lr: 3.3645218661911244e-05 loss: 0.0563 (0.0657) time: 2.9364 data: 0.0082 max mem: 33370 +Epoch: [14] [ 650/2639] eta: 1:36:31 lr: 3.364076381667147e-05 loss: 0.0550 (0.0656) time: 2.9132 data: 0.0081 max mem: 33370 +Epoch: [14] [ 660/2639] eta: 1:36:03 lr: 3.36363089058831e-05 loss: 0.0604 (0.0657) time: 2.9477 data: 0.0078 max mem: 33370 +Epoch: [14] [ 670/2639] eta: 1:35:33 lr: 3.363185392953556e-05 loss: 0.0638 (0.0658) time: 2.9133 data: 0.0080 max mem: 33370 +Epoch: [14] [ 680/2639] eta: 1:35:02 lr: 3.36273988876182e-05 loss: 0.0613 (0.0656) time: 2.8587 data: 0.0083 max mem: 33370 +Epoch: [14] [ 690/2639] eta: 1:34:32 lr: 3.362294378012044e-05 loss: 0.0519 (0.0656) time: 2.8663 data: 0.0080 max mem: 33370 +Epoch: [14] [ 700/2639] eta: 1:34:02 lr: 3.361848860703162e-05 loss: 0.0519 (0.0655) time: 2.8823 data: 0.0079 max mem: 33370 +Epoch: [14] [ 710/2639] eta: 1:33:34 lr: 3.361403336834114e-05 loss: 0.0482 (0.0653) time: 2.9110 data: 0.0077 max mem: 33370 +Epoch: [14] [ 720/2639] eta: 1:33:04 lr: 3.3609578064038365e-05 loss: 0.0538 (0.0653) time: 2.9171 data: 0.0077 max mem: 33370 +Epoch: [14] [ 730/2639] eta: 1:32:36 lr: 3.3605122694112676e-05 loss: 0.0604 (0.0652) time: 2.9177 data: 0.0079 max mem: 33370 +Epoch: [14] [ 740/2639] eta: 1:32:08 lr: 3.360066725855342e-05 loss: 0.0599 (0.0651) time: 2.9541 data: 0.0079 max mem: 33370 +Epoch: [14] [ 750/2639] eta: 1:31:37 lr: 3.359621175734997e-05 loss: 0.0522 (0.0650) time: 2.9022 data: 0.0085 max mem: 33370 +Epoch: [14] [ 760/2639] eta: 1:31:07 lr: 3.359175619049169e-05 loss: 0.0581 (0.0650) time: 2.8577 data: 0.0083 max mem: 33370 +Epoch: [14] [ 770/2639] eta: 1:30:38 lr: 3.3587300557967934e-05 loss: 0.0567 (0.0652) time: 2.8800 data: 0.0078 max mem: 33370 +Epoch: [14] [ 780/2639] eta: 1:30:08 lr: 3.358284485976805e-05 loss: 0.0524 (0.0651) time: 2.8930 data: 0.0081 max mem: 33370 +Epoch: [14] [ 790/2639] eta: 1:29:40 lr: 3.3578389095881385e-05 loss: 0.0614 (0.0651) time: 2.9127 data: 0.0084 max mem: 33370 +Epoch: [14] [ 800/2639] eta: 1:29:10 lr: 3.357393326629729e-05 loss: 0.0623 (0.0651) time: 2.9108 data: 0.0082 max mem: 33370 +Epoch: [14] [ 810/2639] eta: 1:28:40 lr: 3.356947737100512e-05 loss: 0.0519 (0.0650) time: 2.8702 data: 0.0079 max mem: 33370 +Epoch: [14] [ 820/2639] eta: 1:28:09 lr: 3.35650214099942e-05 loss: 0.0528 (0.0650) time: 2.8572 data: 0.0074 max mem: 33370 +Epoch: [14] [ 830/2639] eta: 1:27:41 lr: 3.356056538325386e-05 loss: 0.0602 (0.0651) time: 2.9083 data: 0.0076 max mem: 33370 +Epoch: [14] [ 840/2639] eta: 1:27:13 lr: 3.3556109290773455e-05 loss: 0.0647 (0.0651) time: 2.9520 data: 0.0081 max mem: 33370 +Epoch: [14] [ 850/2639] eta: 1:26:44 lr: 3.35516531325423e-05 loss: 0.0648 (0.0651) time: 2.9369 data: 0.0077 max mem: 33370 +Epoch: [14] [ 860/2639] eta: 1:26:17 lr: 3.354719690854972e-05 loss: 0.0628 (0.0653) time: 2.9514 data: 0.0076 max mem: 33370 +Epoch: [14] [ 870/2639] eta: 1:25:49 lr: 3.354274061878505e-05 loss: 0.0561 (0.0654) time: 2.9706 data: 0.0077 max mem: 33370 +Epoch: [14] [ 880/2639] eta: 1:25:21 lr: 3.353828426323759e-05 loss: 0.0562 (0.0654) time: 2.9733 data: 0.0081 max mem: 33370 +Epoch: [14] [ 890/2639] eta: 1:24:53 lr: 3.353382784189668e-05 loss: 0.0562 (0.0653) time: 2.9664 data: 0.0086 max mem: 33370 +Epoch: [14] [ 900/2639] eta: 1:24:24 lr: 3.352937135475163e-05 loss: 0.0595 (0.0654) time: 2.9440 data: 0.0081 max mem: 33370 +Epoch: [14] [ 910/2639] eta: 1:23:55 lr: 3.352491480179173e-05 loss: 0.0510 (0.0652) time: 2.9152 data: 0.0077 max mem: 33370 +Epoch: [14] [ 920/2639] eta: 1:23:25 lr: 3.35204581830063e-05 loss: 0.0495 (0.0652) time: 2.8964 data: 0.0083 max mem: 33370 +Epoch: [14] [ 930/2639] eta: 1:22:57 lr: 3.351600149838465e-05 loss: 0.0646 (0.0652) time: 2.9385 data: 0.0082 max mem: 33370 +Epoch: [14] [ 940/2639] eta: 1:22:27 lr: 3.3511544747916065e-05 loss: 0.0580 (0.0651) time: 2.9205 data: 0.0078 max mem: 33370 +Epoch: [14] [ 950/2639] eta: 1:21:58 lr: 3.3507087931589855e-05 loss: 0.0576 (0.0651) time: 2.8951 data: 0.0077 max mem: 33370 +Epoch: [14] [ 960/2639] eta: 1:21:28 lr: 3.350263104939531e-05 loss: 0.0585 (0.0652) time: 2.8784 data: 0.0078 max mem: 33370 +Epoch: [14] [ 970/2639] eta: 1:20:58 lr: 3.349817410132171e-05 loss: 0.0566 (0.0650) time: 2.8535 data: 0.0080 max mem: 33370 +Epoch: [14] [ 980/2639] eta: 1:20:30 lr: 3.3493717087358364e-05 loss: 0.0547 (0.0651) time: 2.9124 data: 0.0077 max mem: 33370 +Epoch: [14] [ 990/2639] eta: 1:20:00 lr: 3.348926000749453e-05 loss: 0.0690 (0.0652) time: 2.9028 data: 0.0078 max mem: 33370 +Epoch: [14] [1000/2639] eta: 1:19:31 lr: 3.3484802861719496e-05 loss: 0.0737 (0.0653) time: 2.8856 data: 0.0078 max mem: 33370 +Epoch: [14] [1010/2639] eta: 1:19:01 lr: 3.3480345650022545e-05 loss: 0.0599 (0.0652) time: 2.8904 data: 0.0079 max mem: 33370 +Epoch: [14] [1020/2639] eta: 1:18:32 lr: 3.3475888372392956e-05 loss: 0.0511 (0.0651) time: 2.9008 data: 0.0077 max mem: 33370 +Epoch: [14] [1030/2639] eta: 1:18:02 lr: 3.347143102881999e-05 loss: 0.0493 (0.0650) time: 2.8997 data: 0.0076 max mem: 33370 +Epoch: [14] [1040/2639] eta: 1:17:32 lr: 3.346697361929291e-05 loss: 0.0567 (0.0652) time: 2.8640 data: 0.0079 max mem: 33370 +Epoch: [14] [1050/2639] eta: 1:17:02 lr: 3.3462516143800984e-05 loss: 0.0669 (0.0652) time: 2.8466 data: 0.0077 max mem: 33370 +Epoch: [14] [1060/2639] eta: 1:16:33 lr: 3.345805860233347e-05 loss: 0.0535 (0.0652) time: 2.8578 data: 0.0076 max mem: 33370 +Epoch: [14] [1070/2639] eta: 1:16:03 lr: 3.3453600994879635e-05 loss: 0.0564 (0.0653) time: 2.8824 data: 0.0076 max mem: 33370 +Epoch: [14] [1080/2639] eta: 1:15:34 lr: 3.344914332142872e-05 loss: 0.0687 (0.0653) time: 2.8915 data: 0.0076 max mem: 33370 +Epoch: [14] [1090/2639] eta: 1:15:05 lr: 3.344468558196997e-05 loss: 0.0635 (0.0653) time: 2.9039 data: 0.0076 max mem: 33370 +Epoch: [14] [1100/2639] eta: 1:14:36 lr: 3.344022777649266e-05 loss: 0.0582 (0.0654) time: 2.9073 data: 0.0077 max mem: 33370 +Epoch: [14] [1110/2639] eta: 1:14:06 lr: 3.343576990498601e-05 loss: 0.0593 (0.0654) time: 2.9007 data: 0.0077 max mem: 33370 +Epoch: [14] [1120/2639] eta: 1:13:36 lr: 3.343131196743925e-05 loss: 0.0592 (0.0654) time: 2.8616 data: 0.0079 max mem: 33370 +Epoch: [14] [1130/2639] eta: 1:13:07 lr: 3.3426853963841645e-05 loss: 0.0552 (0.0654) time: 2.8504 data: 0.0085 max mem: 33370 +Epoch: [14] [1140/2639] eta: 1:12:38 lr: 3.342239589418241e-05 loss: 0.0607 (0.0655) time: 2.8884 data: 0.0082 max mem: 33370 +Epoch: [14] [1150/2639] eta: 1:12:09 lr: 3.341793775845079e-05 loss: 0.0603 (0.0654) time: 2.9241 data: 0.0078 max mem: 33370 +Epoch: [14] [1160/2639] eta: 1:11:41 lr: 3.341347955663599e-05 loss: 0.0557 (0.0655) time: 2.9648 data: 0.0080 max mem: 33370 +Epoch: [14] [1170/2639] eta: 1:11:12 lr: 3.340902128872725e-05 loss: 0.0630 (0.0655) time: 2.9713 data: 0.0077 max mem: 33370 +Epoch: [14] [1180/2639] eta: 1:10:43 lr: 3.340456295471378e-05 loss: 0.0705 (0.0656) time: 2.9275 data: 0.0081 max mem: 33370 +Epoch: [14] [1190/2639] eta: 1:10:13 lr: 3.340010455458481e-05 loss: 0.0627 (0.0656) time: 2.8765 data: 0.0085 max mem: 33370 +Epoch: [14] [1200/2639] eta: 1:09:44 lr: 3.339564608832953e-05 loss: 0.0570 (0.0656) time: 2.8732 data: 0.0082 max mem: 33370 +Epoch: [14] [1210/2639] eta: 1:09:16 lr: 3.3391187555937184e-05 loss: 0.0640 (0.0657) time: 2.9186 data: 0.0080 max mem: 33370 +Epoch: [14] [1220/2639] eta: 1:08:46 lr: 3.338672895739694e-05 loss: 0.0630 (0.0656) time: 2.8981 data: 0.0080 max mem: 33370 +Epoch: [14] [1230/2639] eta: 1:08:17 lr: 3.3382270292698034e-05 loss: 0.0584 (0.0655) time: 2.8793 data: 0.0081 max mem: 33370 +Epoch: [14] [1240/2639] eta: 1:07:48 lr: 3.337781156182965e-05 loss: 0.0591 (0.0655) time: 2.9118 data: 0.0079 max mem: 33370 +Epoch: [14] [1250/2639] eta: 1:07:19 lr: 3.337335276478098e-05 loss: 0.0621 (0.0656) time: 2.9085 data: 0.0079 max mem: 33370 +Epoch: [14] [1260/2639] eta: 1:06:50 lr: 3.3368893901541224e-05 loss: 0.0566 (0.0656) time: 2.9066 data: 0.0081 max mem: 33370 +Epoch: [14] [1270/2639] eta: 1:06:21 lr: 3.336443497209958e-05 loss: 0.0637 (0.0659) time: 2.9114 data: 0.0080 max mem: 33370 +Epoch: [14] [1280/2639] eta: 1:05:52 lr: 3.335997597644523e-05 loss: 0.0655 (0.0659) time: 2.9203 data: 0.0079 max mem: 33370 +Epoch: [14] [1290/2639] eta: 1:05:22 lr: 3.335551691456733e-05 loss: 0.0655 (0.0660) time: 2.9069 data: 0.0081 max mem: 33370 +Epoch: [14] [1300/2639] eta: 1:04:53 lr: 3.335105778645509e-05 loss: 0.0712 (0.0660) time: 2.9049 data: 0.0082 max mem: 33370 +Epoch: [14] [1310/2639] eta: 1:04:24 lr: 3.334659859209769e-05 loss: 0.0644 (0.0660) time: 2.8900 data: 0.0080 max mem: 33370 +Epoch: [14] [1320/2639] eta: 1:03:54 lr: 3.3342139331484284e-05 loss: 0.0573 (0.0660) time: 2.8457 data: 0.0081 max mem: 33370 +Epoch: [14] [1330/2639] eta: 1:03:24 lr: 3.333768000460405e-05 loss: 0.0508 (0.0660) time: 2.8471 data: 0.0083 max mem: 33370 +Epoch: [14] [1340/2639] eta: 1:02:55 lr: 3.3333220611446145e-05 loss: 0.0537 (0.0659) time: 2.8624 data: 0.0081 max mem: 33370 +Epoch: [14] [1350/2639] eta: 1:02:26 lr: 3.332876115199975e-05 loss: 0.0607 (0.0660) time: 2.8689 data: 0.0084 max mem: 33370 +Epoch: [14] [1360/2639] eta: 1:01:56 lr: 3.3324301626254004e-05 loss: 0.0612 (0.0660) time: 2.8807 data: 0.0087 max mem: 33370 +Epoch: [14] [1370/2639] eta: 1:01:28 lr: 3.331984203419808e-05 loss: 0.0539 (0.0661) time: 2.9274 data: 0.0080 max mem: 33370 +Epoch: [14] [1380/2639] eta: 1:00:59 lr: 3.331538237582111e-05 loss: 0.0601 (0.0662) time: 2.9524 data: 0.0076 max mem: 33370 +Epoch: [14] [1390/2639] eta: 1:00:31 lr: 3.331092265111227e-05 loss: 0.0632 (0.0662) time: 2.9766 data: 0.0077 max mem: 33370 +Epoch: [14] [1400/2639] eta: 1:00:02 lr: 3.3306462860060686e-05 loss: 0.0632 (0.0661) time: 2.9792 data: 0.0084 max mem: 33370 +Epoch: [14] [1410/2639] eta: 0:59:34 lr: 3.3302003002655505e-05 loss: 0.0650 (0.0662) time: 2.9632 data: 0.0087 max mem: 33370 +Epoch: [14] [1420/2639] eta: 0:59:04 lr: 3.329754307888587e-05 loss: 0.0730 (0.0663) time: 2.9114 data: 0.0080 max mem: 33370 +Epoch: [14] [1430/2639] eta: 0:58:35 lr: 3.329308308874091e-05 loss: 0.0801 (0.0664) time: 2.8743 data: 0.0082 max mem: 33370 +Epoch: [14] [1440/2639] eta: 0:58:06 lr: 3.328862303220977e-05 loss: 0.0780 (0.0666) time: 2.8812 data: 0.0087 max mem: 33370 +Epoch: [14] [1450/2639] eta: 0:57:37 lr: 3.328416290928156e-05 loss: 0.0692 (0.0666) time: 2.8956 data: 0.0081 max mem: 33370 +Epoch: [14] [1460/2639] eta: 0:57:08 lr: 3.3279702719945416e-05 loss: 0.0558 (0.0665) time: 2.9548 data: 0.0076 max mem: 33370 +Epoch: [14] [1470/2639] eta: 0:56:39 lr: 3.327524246419046e-05 loss: 0.0536 (0.0667) time: 2.9517 data: 0.0080 max mem: 33370 +Epoch: [14] [1480/2639] eta: 0:56:10 lr: 3.327078214200581e-05 loss: 0.0693 (0.0666) time: 2.8994 data: 0.0080 max mem: 33370 +Epoch: [14] [1490/2639] eta: 0:55:41 lr: 3.326632175338058e-05 loss: 0.0693 (0.0667) time: 2.8876 data: 0.0077 max mem: 33370 +Epoch: [14] [1500/2639] eta: 0:55:11 lr: 3.326186129830388e-05 loss: 0.0696 (0.0667) time: 2.8874 data: 0.0076 max mem: 33370 +Epoch: [14] [1510/2639] eta: 0:54:42 lr: 3.325740077676482e-05 loss: 0.0562 (0.0666) time: 2.8900 data: 0.0075 max mem: 33370 +Epoch: [14] [1520/2639] eta: 0:54:13 lr: 3.3252940188752514e-05 loss: 0.0505 (0.0665) time: 2.8919 data: 0.0084 max mem: 33370 +Epoch: [14] [1530/2639] eta: 0:53:43 lr: 3.324847953425605e-05 loss: 0.0553 (0.0666) time: 2.8581 data: 0.0088 max mem: 33370 +Epoch: [14] [1540/2639] eta: 0:53:14 lr: 3.324401881326453e-05 loss: 0.0578 (0.0666) time: 2.8476 data: 0.0086 max mem: 33370 +Epoch: [14] [1550/2639] eta: 0:52:45 lr: 3.3239558025767045e-05 loss: 0.0578 (0.0665) time: 2.8886 data: 0.0084 max mem: 33370 +Epoch: [14] [1560/2639] eta: 0:52:16 lr: 3.3235097171752696e-05 loss: 0.0672 (0.0666) time: 2.9058 data: 0.0080 max mem: 33370 +Epoch: [14] [1570/2639] eta: 0:51:46 lr: 3.323063625121057e-05 loss: 0.0558 (0.0665) time: 2.8725 data: 0.0079 max mem: 33370 +Epoch: [14] [1580/2639] eta: 0:51:18 lr: 3.3226175264129744e-05 loss: 0.0513 (0.0665) time: 2.9066 data: 0.0076 max mem: 33370 +Epoch: [14] [1590/2639] eta: 0:50:49 lr: 3.322171421049931e-05 loss: 0.0539 (0.0665) time: 2.9549 data: 0.0078 max mem: 33370 +Epoch: [14] [1600/2639] eta: 0:50:20 lr: 3.3217253090308325e-05 loss: 0.0540 (0.0664) time: 2.9083 data: 0.0085 max mem: 33370 +Epoch: [14] [1610/2639] eta: 0:49:50 lr: 3.3212791903545885e-05 loss: 0.0558 (0.0664) time: 2.8553 data: 0.0085 max mem: 33370 +Epoch: [14] [1620/2639] eta: 0:49:21 lr: 3.3208330650201044e-05 loss: 0.0593 (0.0664) time: 2.8434 data: 0.0083 max mem: 33370 +Epoch: [14] [1630/2639] eta: 0:48:52 lr: 3.320386933026288e-05 loss: 0.0609 (0.0664) time: 2.8654 data: 0.0080 max mem: 33370 +Epoch: [14] [1640/2639] eta: 0:48:23 lr: 3.319940794372046e-05 loss: 0.0574 (0.0663) time: 2.9000 data: 0.0074 max mem: 33370 +Epoch: [14] [1650/2639] eta: 0:47:53 lr: 3.319494649056285e-05 loss: 0.0620 (0.0664) time: 2.8821 data: 0.0077 max mem: 33370 +Epoch: [14] [1660/2639] eta: 0:47:24 lr: 3.319048497077907e-05 loss: 0.0698 (0.0664) time: 2.8779 data: 0.0079 max mem: 33370 +Epoch: [14] [1670/2639] eta: 0:46:55 lr: 3.318602338435821e-05 loss: 0.0590 (0.0664) time: 2.8825 data: 0.0078 max mem: 33370 +Epoch: [14] [1680/2639] eta: 0:46:26 lr: 3.318156173128932e-05 loss: 0.0529 (0.0663) time: 2.8714 data: 0.0077 max mem: 33370 +Epoch: [14] [1690/2639] eta: 0:45:56 lr: 3.317710001156142e-05 loss: 0.0515 (0.0662) time: 2.8661 data: 0.0079 max mem: 33370 +Epoch: [14] [1700/2639] eta: 0:45:27 lr: 3.317263822516358e-05 loss: 0.0549 (0.0662) time: 2.8884 data: 0.0085 max mem: 33370 +Epoch: [14] [1710/2639] eta: 0:44:58 lr: 3.316817637208482e-05 loss: 0.0603 (0.0662) time: 2.9207 data: 0.0083 max mem: 33370 +Epoch: [14] [1720/2639] eta: 0:44:29 lr: 3.3163714452314205e-05 loss: 0.0558 (0.0662) time: 2.9151 data: 0.0080 max mem: 33370 +Epoch: [14] [1730/2639] eta: 0:44:00 lr: 3.3159252465840726e-05 loss: 0.0605 (0.0662) time: 2.9083 data: 0.0083 max mem: 33370 +Epoch: [14] [1740/2639] eta: 0:43:31 lr: 3.3154790412653455e-05 loss: 0.0570 (0.0662) time: 2.9016 data: 0.0082 max mem: 33370 +Epoch: [14] [1750/2639] eta: 0:43:02 lr: 3.3150328292741387e-05 loss: 0.0531 (0.0663) time: 2.9079 data: 0.0082 max mem: 33370 +Epoch: [14] [1760/2639] eta: 0:42:33 lr: 3.314586610609356e-05 loss: 0.0599 (0.0663) time: 2.8914 data: 0.0085 max mem: 33370 +Epoch: [14] [1770/2639] eta: 0:42:04 lr: 3.314140385269899e-05 loss: 0.0622 (0.0663) time: 2.8859 data: 0.0082 max mem: 33370 +Epoch: [14] [1780/2639] eta: 0:41:35 lr: 3.3136941532546693e-05 loss: 0.0627 (0.0664) time: 2.9014 data: 0.0081 max mem: 33370 +Epoch: [14] [1790/2639] eta: 0:41:06 lr: 3.3132479145625676e-05 loss: 0.0612 (0.0664) time: 2.9340 data: 0.0082 max mem: 33370 +Epoch: [14] [1800/2639] eta: 0:40:37 lr: 3.3128016691924954e-05 loss: 0.0509 (0.0663) time: 2.9625 data: 0.0082 max mem: 33370 +Epoch: [14] [1810/2639] eta: 0:40:08 lr: 3.3123554171433536e-05 loss: 0.0509 (0.0663) time: 2.9306 data: 0.0080 max mem: 33370 +Epoch: [14] [1820/2639] eta: 0:39:39 lr: 3.3119091584140424e-05 loss: 0.0510 (0.0663) time: 2.9373 data: 0.0076 max mem: 33370 +Epoch: [14] [1830/2639] eta: 0:39:10 lr: 3.31146289300346e-05 loss: 0.0543 (0.0663) time: 2.9231 data: 0.0079 max mem: 33370 +Epoch: [14] [1840/2639] eta: 0:38:41 lr: 3.3110166209105066e-05 loss: 0.0573 (0.0663) time: 2.8739 data: 0.0078 max mem: 33370 +Epoch: [14] [1850/2639] eta: 0:38:12 lr: 3.310570342134083e-05 loss: 0.0573 (0.0663) time: 2.8840 data: 0.0078 max mem: 33370 +Epoch: [14] [1860/2639] eta: 0:37:43 lr: 3.310124056673086e-05 loss: 0.0546 (0.0662) time: 2.8826 data: 0.0077 max mem: 33370 +Epoch: [14] [1870/2639] eta: 0:37:14 lr: 3.309677764526415e-05 loss: 0.0546 (0.0662) time: 2.9262 data: 0.0076 max mem: 33370 +Epoch: [14] [1880/2639] eta: 0:36:45 lr: 3.309231465692968e-05 loss: 0.0557 (0.0664) time: 2.9401 data: 0.0081 max mem: 33370 +Epoch: [14] [1890/2639] eta: 0:36:16 lr: 3.3087851601716435e-05 loss: 0.0638 (0.0664) time: 2.8920 data: 0.0083 max mem: 33370 +Epoch: [14] [1900/2639] eta: 0:35:47 lr: 3.3083388479613375e-05 loss: 0.0621 (0.0664) time: 2.8940 data: 0.0083 max mem: 33370 +Epoch: [14] [1910/2639] eta: 0:35:17 lr: 3.3078925290609484e-05 loss: 0.0650 (0.0666) time: 2.8728 data: 0.0083 max mem: 33370 +Epoch: [14] [1920/2639] eta: 0:34:48 lr: 3.307446203469371e-05 loss: 0.0733 (0.0666) time: 2.8432 data: 0.0080 max mem: 33370 +Epoch: [14] [1930/2639] eta: 0:34:19 lr: 3.3069998711855035e-05 loss: 0.0532 (0.0666) time: 2.8735 data: 0.0076 max mem: 33370 +Epoch: [14] [1940/2639] eta: 0:33:50 lr: 3.306553532208242e-05 loss: 0.0516 (0.0665) time: 2.9133 data: 0.0077 max mem: 33370 +Epoch: [14] [1950/2639] eta: 0:33:21 lr: 3.3061071865364815e-05 loss: 0.0575 (0.0665) time: 2.9300 data: 0.0078 max mem: 33370 +Epoch: [14] [1960/2639] eta: 0:32:52 lr: 3.3056608341691166e-05 loss: 0.0656 (0.0666) time: 2.9197 data: 0.0078 max mem: 33370 +Epoch: [14] [1970/2639] eta: 0:32:23 lr: 3.3052144751050435e-05 loss: 0.0716 (0.0666) time: 2.8925 data: 0.0079 max mem: 33370 +Epoch: [14] [1980/2639] eta: 0:31:54 lr: 3.304768109343156e-05 loss: 0.0709 (0.0666) time: 2.8705 data: 0.0078 max mem: 33370 +Epoch: [14] [1990/2639] eta: 0:31:25 lr: 3.3043217368823504e-05 loss: 0.0616 (0.0666) time: 2.9127 data: 0.0078 max mem: 33370 +Epoch: [14] [2000/2639] eta: 0:30:56 lr: 3.3038753577215173e-05 loss: 0.0552 (0.0666) time: 2.9346 data: 0.0080 max mem: 33370 +Epoch: [14] [2010/2639] eta: 0:30:27 lr: 3.303428971859553e-05 loss: 0.0633 (0.0667) time: 2.9230 data: 0.0077 max mem: 33370 +Epoch: [14] [2020/2639] eta: 0:29:58 lr: 3.30298257929535e-05 loss: 0.0735 (0.0667) time: 2.8881 data: 0.0073 max mem: 33370 +Epoch: [14] [2030/2639] eta: 0:29:29 lr: 3.3025361800278007e-05 loss: 0.0645 (0.0667) time: 2.8577 data: 0.0075 max mem: 33370 +Epoch: [14] [2040/2639] eta: 0:28:59 lr: 3.3020897740557985e-05 loss: 0.0619 (0.0667) time: 2.8799 data: 0.0077 max mem: 33370 +Epoch: [14] [2050/2639] eta: 0:28:30 lr: 3.3016433613782335e-05 loss: 0.0586 (0.0667) time: 2.9072 data: 0.0076 max mem: 33370 +Epoch: [14] [2060/2639] eta: 0:28:01 lr: 3.3011969419940006e-05 loss: 0.0614 (0.0667) time: 2.9166 data: 0.0074 max mem: 33370 +Epoch: [14] [2070/2639] eta: 0:27:32 lr: 3.3007505159019905e-05 loss: 0.0568 (0.0667) time: 2.9331 data: 0.0077 max mem: 33370 +Epoch: [14] [2080/2639] eta: 0:27:03 lr: 3.3003040831010924e-05 loss: 0.0596 (0.0667) time: 2.9254 data: 0.0079 max mem: 33370 +Epoch: [14] [2090/2639] eta: 0:26:34 lr: 3.2998576435901986e-05 loss: 0.0659 (0.0668) time: 2.8939 data: 0.0077 max mem: 33370 +Epoch: [14] [2100/2639] eta: 0:26:05 lr: 3.299411197368199e-05 loss: 0.0703 (0.0668) time: 2.8971 data: 0.0077 max mem: 33370 +Epoch: [14] [2110/2639] eta: 0:25:36 lr: 3.298964744433985e-05 loss: 0.0563 (0.0668) time: 2.9096 data: 0.0076 max mem: 33370 +Epoch: [14] [2120/2639] eta: 0:25:07 lr: 3.298518284786445e-05 loss: 0.0566 (0.0668) time: 2.8985 data: 0.0080 max mem: 33370 +Epoch: [14] [2130/2639] eta: 0:24:38 lr: 3.298071818424468e-05 loss: 0.0528 (0.0668) time: 2.8850 data: 0.0082 max mem: 33370 +Epoch: [14] [2140/2639] eta: 0:24:09 lr: 3.297625345346945e-05 loss: 0.0527 (0.0668) time: 2.9035 data: 0.0081 max mem: 33370 +Epoch: [14] [2150/2639] eta: 0:23:40 lr: 3.2971788655527636e-05 loss: 0.0626 (0.0668) time: 2.8991 data: 0.0080 max mem: 33370 +Epoch: [14] [2160/2639] eta: 0:23:11 lr: 3.296732379040811e-05 loss: 0.0626 (0.0667) time: 2.9219 data: 0.0078 max mem: 33370 +Epoch: [14] [2170/2639] eta: 0:22:42 lr: 3.2962858858099766e-05 loss: 0.0538 (0.0667) time: 2.9403 data: 0.0077 max mem: 33370 +Epoch: [14] [2180/2639] eta: 0:22:13 lr: 3.2958393858591485e-05 loss: 0.0548 (0.0667) time: 2.9261 data: 0.0078 max mem: 33370 +Epoch: [14] [2190/2639] eta: 0:21:44 lr: 3.295392879187213e-05 loss: 0.0548 (0.0667) time: 2.9536 data: 0.0077 max mem: 33370 +Epoch: [14] [2200/2639] eta: 0:21:15 lr: 3.2949463657930564e-05 loss: 0.0669 (0.0668) time: 2.9455 data: 0.0079 max mem: 33370 +Epoch: [14] [2210/2639] eta: 0:20:46 lr: 3.2944998456755664e-05 loss: 0.0669 (0.0668) time: 2.8741 data: 0.0085 max mem: 33370 +Epoch: [14] [2220/2639] eta: 0:20:17 lr: 3.294053318833629e-05 loss: 0.0582 (0.0668) time: 2.8570 data: 0.0081 max mem: 33370 +Epoch: [14] [2230/2639] eta: 0:19:48 lr: 3.2936067852661306e-05 loss: 0.0619 (0.0668) time: 2.8646 data: 0.0076 max mem: 33370 +Epoch: [14] [2240/2639] eta: 0:19:19 lr: 3.293160244971956e-05 loss: 0.0691 (0.0668) time: 2.8850 data: 0.0076 max mem: 33370 +Epoch: [14] [2250/2639] eta: 0:18:50 lr: 3.2927136979499905e-05 loss: 0.0611 (0.0668) time: 2.9175 data: 0.0075 max mem: 33370 +Epoch: [14] [2260/2639] eta: 0:18:20 lr: 3.2922671441991194e-05 loss: 0.0573 (0.0668) time: 2.9119 data: 0.0076 max mem: 33370 +Epoch: [14] [2270/2639] eta: 0:17:51 lr: 3.2918205837182265e-05 loss: 0.0524 (0.0668) time: 2.8903 data: 0.0073 max mem: 33370 +Epoch: [14] [2280/2639] eta: 0:17:22 lr: 3.291374016506196e-05 loss: 0.0585 (0.0668) time: 2.9057 data: 0.0073 max mem: 33370 +Epoch: [14] [2290/2639] eta: 0:16:53 lr: 3.2909274425619124e-05 loss: 0.0585 (0.0667) time: 2.9105 data: 0.0077 max mem: 33370 +Epoch: [14] [2300/2639] eta: 0:16:24 lr: 3.2904808618842575e-05 loss: 0.0473 (0.0667) time: 2.9053 data: 0.0078 max mem: 33370 +Epoch: [14] [2310/2639] eta: 0:15:55 lr: 3.290034274472117e-05 loss: 0.0521 (0.0666) time: 2.9123 data: 0.0080 max mem: 33370 +Epoch: [14] [2320/2639] eta: 0:15:26 lr: 3.2895876803243714e-05 loss: 0.0521 (0.0666) time: 2.8999 data: 0.0081 max mem: 33370 +Epoch: [14] [2330/2639] eta: 0:14:57 lr: 3.289141079439903e-05 loss: 0.0484 (0.0666) time: 2.8998 data: 0.0078 max mem: 33370 +Epoch: [14] [2340/2639] eta: 0:14:28 lr: 3.288694471817595e-05 loss: 0.0500 (0.0666) time: 2.8999 data: 0.0078 max mem: 33370 +Epoch: [14] [2350/2639] eta: 0:13:59 lr: 3.288247857456329e-05 loss: 0.0605 (0.0666) time: 2.8617 data: 0.0081 max mem: 33370 +Epoch: [14] [2360/2639] eta: 0:13:30 lr: 3.287801236354985e-05 loss: 0.0605 (0.0666) time: 2.8740 data: 0.0077 max mem: 33370 +Epoch: [14] [2370/2639] eta: 0:13:01 lr: 3.287354608512445e-05 loss: 0.0611 (0.0666) time: 2.9021 data: 0.0076 max mem: 33370 +Epoch: [14] [2380/2639] eta: 0:12:32 lr: 3.286907973927589e-05 loss: 0.0729 (0.0666) time: 2.9011 data: 0.0080 max mem: 33370 +Epoch: [14] [2390/2639] eta: 0:12:03 lr: 3.286461332599299e-05 loss: 0.0632 (0.0666) time: 2.9123 data: 0.0080 max mem: 33370 +Epoch: [14] [2400/2639] eta: 0:11:34 lr: 3.2860146845264525e-05 loss: 0.0587 (0.0666) time: 2.9154 data: 0.0078 max mem: 33370 +Epoch: [14] [2410/2639] eta: 0:11:05 lr: 3.28556802970793e-05 loss: 0.0521 (0.0666) time: 2.8872 data: 0.0078 max mem: 33370 +Epoch: [14] [2420/2639] eta: 0:10:36 lr: 3.2851213681426104e-05 loss: 0.0613 (0.0667) time: 2.8551 data: 0.0077 max mem: 33370 +Epoch: [14] [2430/2639] eta: 0:10:06 lr: 3.284674699829373e-05 loss: 0.0629 (0.0667) time: 2.8507 data: 0.0077 max mem: 33370 +Epoch: [14] [2440/2639] eta: 0:09:37 lr: 3.2842280247670964e-05 loss: 0.0639 (0.0668) time: 2.8597 data: 0.0077 max mem: 33370 +Epoch: [14] [2450/2639] eta: 0:09:08 lr: 3.283781342954658e-05 loss: 0.0599 (0.0667) time: 2.9101 data: 0.0076 max mem: 33370 +Epoch: [14] [2460/2639] eta: 0:08:39 lr: 3.283334654390935e-05 loss: 0.0586 (0.0667) time: 2.9227 data: 0.0074 max mem: 33370 +Epoch: [14] [2470/2639] eta: 0:08:10 lr: 3.2828879590748055e-05 loss: 0.0586 (0.0667) time: 2.8748 data: 0.0077 max mem: 33370 +Epoch: [14] [2480/2639] eta: 0:07:41 lr: 3.282441257005148e-05 loss: 0.0618 (0.0668) time: 2.8662 data: 0.0077 max mem: 33370 +Epoch: [14] [2490/2639] eta: 0:07:12 lr: 3.281994548180837e-05 loss: 0.0660 (0.0668) time: 2.8684 data: 0.0074 max mem: 33370 +Epoch: [14] [2500/2639] eta: 0:06:43 lr: 3.2815478326007495e-05 loss: 0.0641 (0.0668) time: 2.8658 data: 0.0080 max mem: 33370 +Epoch: [14] [2510/2639] eta: 0:06:14 lr: 3.2811011102637616e-05 loss: 0.0610 (0.0668) time: 2.8840 data: 0.0079 max mem: 33370 +Epoch: [14] [2520/2639] eta: 0:05:45 lr: 3.28065438116875e-05 loss: 0.0610 (0.0668) time: 2.8818 data: 0.0078 max mem: 33370 +Epoch: [14] [2530/2639] eta: 0:05:16 lr: 3.280207645314587e-05 loss: 0.0624 (0.0668) time: 2.8674 data: 0.0081 max mem: 33370 +Epoch: [14] [2540/2639] eta: 0:04:47 lr: 3.27976090270015e-05 loss: 0.0624 (0.0668) time: 2.8892 data: 0.0078 max mem: 33370 +Epoch: [14] [2550/2639] eta: 0:04:18 lr: 3.279314153324313e-05 loss: 0.0606 (0.0668) time: 2.8810 data: 0.0077 max mem: 33370 +Epoch: [14] [2560/2639] eta: 0:03:49 lr: 3.2788673971859494e-05 loss: 0.0649 (0.0668) time: 2.8643 data: 0.0078 max mem: 33370 +Epoch: [14] [2570/2639] eta: 0:03:20 lr: 3.278420634283934e-05 loss: 0.0695 (0.0668) time: 2.8886 data: 0.0077 max mem: 33370 +Epoch: [14] [2580/2639] eta: 0:02:51 lr: 3.2779738646171394e-05 loss: 0.0669 (0.0669) time: 2.8876 data: 0.0079 max mem: 33370 +Epoch: [14] [2590/2639] eta: 0:02:22 lr: 3.277527088184439e-05 loss: 0.0608 (0.0669) time: 2.8983 data: 0.0079 max mem: 33370 +Epoch: [14] [2600/2639] eta: 0:01:53 lr: 3.2770803049847065e-05 loss: 0.0665 (0.0669) time: 2.9026 data: 0.0075 max mem: 33370 +Epoch: [14] [2610/2639] eta: 0:01:24 lr: 3.2766335150168134e-05 loss: 0.0665 (0.0670) time: 2.9368 data: 0.0076 max mem: 33370 +Epoch: [14] [2620/2639] eta: 0:00:55 lr: 3.276186718279631e-05 loss: 0.0655 (0.0671) time: 2.9556 data: 0.0075 max mem: 33370 +Epoch: [14] [2630/2639] eta: 0:00:26 lr: 3.275739914772031e-05 loss: 0.0724 (0.0671) time: 2.9513 data: 0.0073 max mem: 33370 +Epoch: [14] Total time: 2:07:42 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 2:17:54 time: 3.2158 data: 3.1268 max mem: 33370 +Test: [ 100/2573] eta: 0:04:31 time: 0.0779 data: 0.0014 max mem: 33370 +Test: [ 200/2573] eta: 0:03:45 time: 0.0790 data: 0.0013 max mem: 33370 +Test: [ 300/2573] eta: 0:03:24 time: 0.0818 data: 0.0014 max mem: 33370 +Test: [ 400/2573] eta: 0:03:09 time: 0.0811 data: 0.0014 max mem: 33370 +Test: [ 500/2573] eta: 0:02:58 time: 0.0812 data: 0.0015 max mem: 33370 +Test: [ 600/2573] eta: 0:02:48 time: 0.0799 data: 0.0015 max mem: 33370 +Test: [ 700/2573] eta: 0:02:39 time: 0.0815 data: 0.0015 max mem: 33370 +Test: [ 800/2573] eta: 0:02:29 time: 0.0832 data: 0.0013 max mem: 33370 +Test: [ 900/2573] eta: 0:02:20 time: 0.0824 data: 0.0014 max mem: 33370 +Test: [1000/2573] eta: 0:02:12 time: 0.0824 data: 0.0014 max mem: 33370 +Test: [1100/2573] eta: 0:02:03 time: 0.0807 data: 0.0014 max mem: 33370 +Test: [1200/2573] eta: 0:01:54 time: 0.0814 data: 0.0014 max mem: 33370 +Test: [1300/2573] eta: 0:01:46 time: 0.0813 data: 0.0014 max mem: 33370 +Test: [1400/2573] eta: 0:01:37 time: 0.0790 data: 0.0014 max mem: 33370 +Test: [1500/2573] eta: 0:01:29 time: 0.0814 data: 0.0015 max mem: 33370 +Test: [1600/2573] eta: 0:01:20 time: 0.0851 data: 0.0014 max mem: 33370 +Test: [1700/2573] eta: 0:01:12 time: 0.0788 data: 0.0015 max mem: 33370 +Test: [1800/2573] eta: 0:01:04 time: 0.0835 data: 0.0015 max mem: 33370 +Test: [1900/2573] eta: 0:00:55 time: 0.0797 data: 0.0016 max mem: 33370 +Test: [2000/2573] eta: 0:00:47 time: 0.0811 data: 0.0014 max mem: 33370 +Test: [2100/2573] eta: 0:00:39 time: 0.0827 data: 0.0014 max mem: 33370 +Test: [2200/2573] eta: 0:00:30 time: 0.0824 data: 0.0014 max mem: 33370 +Test: [2300/2573] eta: 0:00:22 time: 0.0833 data: 0.0014 max mem: 33370 +Test: [2400/2573] eta: 0:00:14 time: 0.0787 data: 0.0014 max mem: 33370 +Test: [2500/2573] eta: 0:00:06 time: 0.0812 data: 0.0014 max mem: 33370 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: Total time: 0:03:33 +Final results: +Mean IoU is 60.81 + + precision@0.5 = 67.83 + precision@0.6 = 62.42 + precision@0.7 = 55.49 + precision@0.8 = 43.97 + precision@0.9 = 20.42 + overall IoU = 58.99 + +Average object IoU 60.81400327601909 +Overall IoU 58.99366760253906 +Better epoch: 14 + +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [15] [ 0/2639] eta: 4:00:19 lr: 3.275337785825553e-05 loss: 0.0603 (0.0603) time: 5.4640 data: 2.3111 max mem: 33370 +Epoch: [15] [ 10/2639] eta: 2:16:35 lr: 3.2748909694510515e-05 loss: 0.0561 (0.0663) time: 3.1172 data: 0.2172 max mem: 33370 +Epoch: [15] [ 20/2639] eta: 2:11:55 lr: 3.274444146302859e-05 loss: 0.0561 (0.0633) time: 2.9003 data: 0.0073 max mem: 33370 +Epoch: [15] [ 30/2639] eta: 2:09:23 lr: 3.273997316379846e-05 loss: 0.0592 (0.0666) time: 2.8979 data: 0.0076 max mem: 33370 +Epoch: [15] [ 40/2639] eta: 2:07:32 lr: 3.2735504796808816e-05 loss: 0.0539 (0.0659) time: 2.8623 data: 0.0084 max mem: 33370 +Epoch: [15] [ 50/2639] eta: 2:06:25 lr: 3.2731036362048364e-05 loss: 0.0633 (0.0656) time: 2.8588 data: 0.0081 max mem: 33370 +Epoch: [15] [ 60/2639] eta: 2:05:46 lr: 3.272656785950578e-05 loss: 0.0565 (0.0645) time: 2.8884 data: 0.0075 max mem: 33370 +Epoch: [15] [ 70/2639] eta: 2:05:27 lr: 3.2722099289169764e-05 loss: 0.0527 (0.0638) time: 2.9302 data: 0.0079 max mem: 33370 +Epoch: [15] [ 80/2639] eta: 2:04:42 lr: 3.271763065102901e-05 loss: 0.0558 (0.0619) time: 2.9179 data: 0.0083 max mem: 33370 +Epoch: [15] [ 90/2639] eta: 2:04:21 lr: 3.271316194507217e-05 loss: 0.0497 (0.0617) time: 2.9179 data: 0.0083 max mem: 33370 +Epoch: [15] [ 100/2639] eta: 2:03:37 lr: 3.270869317128794e-05 loss: 0.0509 (0.0606) time: 2.9121 data: 0.0084 max mem: 33370 +Epoch: [15] [ 110/2639] eta: 2:02:48 lr: 3.2704224329664996e-05 loss: 0.0566 (0.0617) time: 2.8520 data: 0.0080 max mem: 33370 +Epoch: [15] [ 120/2639] eta: 2:02:15 lr: 3.2699755420192e-05 loss: 0.0573 (0.0616) time: 2.8648 data: 0.0077 max mem: 33370 +Epoch: [15] [ 130/2639] eta: 2:01:41 lr: 3.269528644285763e-05 loss: 0.0504 (0.0604) time: 2.8888 data: 0.0079 max mem: 33370 +Epoch: [15] [ 140/2639] eta: 2:01:14 lr: 3.2690817397650536e-05 loss: 0.0518 (0.0611) time: 2.9032 data: 0.0081 max mem: 33370 +Epoch: [15] [ 150/2639] eta: 2:00:40 lr: 3.268634828455938e-05 loss: 0.0543 (0.0608) time: 2.9032 data: 0.0082 max mem: 33370 +Epoch: [15] [ 160/2639] eta: 2:00:14 lr: 3.268187910357283e-05 loss: 0.0525 (0.0612) time: 2.9065 data: 0.0089 max mem: 33370 +Epoch: [15] [ 170/2639] eta: 1:59:38 lr: 3.2677409854679525e-05 loss: 0.0534 (0.0610) time: 2.8958 data: 0.0084 max mem: 33370 +Epoch: [15] [ 180/2639] eta: 1:59:11 lr: 3.267294053786811e-05 loss: 0.0570 (0.0610) time: 2.8923 data: 0.0078 max mem: 33370 +Epoch: [15] [ 190/2639] eta: 1:58:43 lr: 3.266847115312724e-05 loss: 0.0506 (0.0612) time: 2.9176 data: 0.0078 max mem: 33370 +Epoch: [15] [ 200/2639] eta: 1:58:09 lr: 3.2664001700445555e-05 loss: 0.0506 (0.0612) time: 2.8911 data: 0.0078 max mem: 33370 +Epoch: [15] [ 210/2639] eta: 1:57:36 lr: 3.2659532179811693e-05 loss: 0.0618 (0.0622) time: 2.8707 data: 0.0083 max mem: 33370 +Epoch: [15] [ 220/2639] eta: 1:57:07 lr: 3.265506259121428e-05 loss: 0.0644 (0.0626) time: 2.8899 data: 0.0082 max mem: 33370 +Epoch: [15] [ 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(0.0617) time: 2.8988 data: 0.0079 max mem: 33370 +Epoch: [15] [ 470/2639] eta: 1:45:02 lr: 3.2543300754806235e-05 loss: 0.0594 (0.0618) time: 2.9173 data: 0.0077 max mem: 33370 +Epoch: [15] [ 480/2639] eta: 1:44:33 lr: 3.25388293951552e-05 loss: 0.0607 (0.0618) time: 2.9004 data: 0.0082 max mem: 33370 +Epoch: [15] [ 490/2639] eta: 1:44:05 lr: 3.2534357967232364e-05 loss: 0.0568 (0.0616) time: 2.9139 data: 0.0085 max mem: 33370 +Epoch: [15] [ 500/2639] eta: 1:43:35 lr: 3.252988647102625e-05 loss: 0.0568 (0.0615) time: 2.9170 data: 0.0084 max mem: 33370 +Epoch: [15] [ 510/2639] eta: 1:43:05 lr: 3.252541490652539e-05 loss: 0.0562 (0.0615) time: 2.8862 data: 0.0082 max mem: 33370 +Epoch: [15] [ 520/2639] eta: 1:42:33 lr: 3.252094327371829e-05 loss: 0.0507 (0.0615) time: 2.8521 data: 0.0086 max mem: 33370 +Epoch: [15] [ 530/2639] eta: 1:42:01 lr: 3.251647157259351e-05 loss: 0.0482 (0.0613) time: 2.8320 data: 0.0086 max mem: 33370 +Epoch: [15] [ 540/2639] eta: 1:41:30 lr: 3.2511999803139524e-05 loss: 0.0490 (0.0614) time: 2.8393 data: 0.0084 max mem: 33370 +Epoch: [15] [ 550/2639] eta: 1:40:59 lr: 3.250752796534487e-05 loss: 0.0559 (0.0615) time: 2.8484 data: 0.0083 max mem: 33370 +Epoch: [15] [ 560/2639] eta: 1:40:29 lr: 3.250305605919805e-05 loss: 0.0545 (0.0614) time: 2.8655 data: 0.0083 max mem: 33370 +Epoch: [15] [ 570/2639] eta: 1:40:02 lr: 3.249858408468758e-05 loss: 0.0528 (0.0614) time: 2.9137 data: 0.0082 max mem: 33370 +Epoch: [15] [ 580/2639] eta: 1:39:32 lr: 3.249411204180195e-05 loss: 0.0554 (0.0614) time: 2.9172 data: 0.0083 max mem: 33370 +Epoch: [15] [ 590/2639] eta: 1:39:03 lr: 3.2489639930529655e-05 loss: 0.0574 (0.0615) time: 2.8952 data: 0.0084 max mem: 33370 +Epoch: [15] [ 600/2639] eta: 1:38:34 lr: 3.2485167750859195e-05 loss: 0.0483 (0.0615) time: 2.9007 data: 0.0079 max mem: 33370 +Epoch: [15] [ 610/2639] eta: 1:38:05 lr: 3.248069550277907e-05 loss: 0.0553 (0.0614) time: 2.8973 data: 0.0076 max mem: 33370 +Epoch: [15] [ 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data: 0.0079 max mem: 33370 +Epoch: [15] [ 780/2639] eta: 1:29:51 lr: 3.240465680756704e-05 loss: 0.0534 (0.0624) time: 2.8715 data: 0.0082 max mem: 33370 +Epoch: [15] [ 790/2639] eta: 1:29:21 lr: 3.2400183326140565e-05 loss: 0.0562 (0.0624) time: 2.9031 data: 0.0082 max mem: 33370 +Epoch: [15] [ 800/2639] eta: 1:28:54 lr: 3.2395709776085044e-05 loss: 0.0556 (0.0625) time: 2.9270 data: 0.0079 max mem: 33370 +Epoch: [15] [ 810/2639] eta: 1:28:24 lr: 3.2391236157388894e-05 loss: 0.0571 (0.0625) time: 2.9128 data: 0.0077 max mem: 33370 +Epoch: [15] [ 820/2639] eta: 1:27:56 lr: 3.2386762470040526e-05 loss: 0.0466 (0.0624) time: 2.9121 data: 0.0084 max mem: 33370 +Epoch: [15] [ 830/2639] eta: 1:27:29 lr: 3.238228871402836e-05 loss: 0.0490 (0.0624) time: 2.9718 data: 0.0084 max mem: 33370 +Epoch: [15] [ 840/2639] eta: 1:26:59 lr: 3.237781488934078e-05 loss: 0.0557 (0.0624) time: 2.9245 data: 0.0080 max mem: 33370 +Epoch: [15] [ 850/2639] eta: 1:26:30 lr: 3.237334099596621e-05 loss: 0.0576 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3.23375473748446e-05 loss: 0.0494 (0.0624) time: 2.8583 data: 0.0078 max mem: 33370 +Epoch: [15] [ 940/2639] eta: 1:22:07 lr: 3.233307286276449e-05 loss: 0.0493 (0.0626) time: 2.8803 data: 0.0075 max mem: 33370 +Epoch: [15] [ 950/2639] eta: 1:21:38 lr: 3.2328598281881196e-05 loss: 0.0528 (0.0627) time: 2.8907 data: 0.0078 max mem: 33370 +Epoch: [15] [ 960/2639] eta: 1:21:08 lr: 3.232412363218308e-05 loss: 0.0528 (0.0628) time: 2.8646 data: 0.0081 max mem: 33370 +Epoch: [15] [ 970/2639] eta: 1:20:38 lr: 3.231964891365848e-05 loss: 0.0521 (0.0628) time: 2.8534 data: 0.0082 max mem: 33370 +Epoch: [15] [ 980/2639] eta: 1:20:09 lr: 3.2315174126295764e-05 loss: 0.0605 (0.0629) time: 2.8713 data: 0.0082 max mem: 33370 +Epoch: [15] [ 990/2639] eta: 1:19:40 lr: 3.231069927008329e-05 loss: 0.0579 (0.0628) time: 2.9100 data: 0.0083 max mem: 33370 +Epoch: [15] [1000/2639] eta: 1:19:12 lr: 3.230622434500939e-05 loss: 0.0532 (0.0628) time: 2.9272 data: 0.0085 max mem: 33370 +Epoch: [15] [1010/2639] eta: 1:18:43 lr: 3.230174935106241e-05 loss: 0.0542 (0.0628) time: 2.9274 data: 0.0083 max mem: 33370 +Epoch: [15] [1020/2639] eta: 1:18:15 lr: 3.229727428823069e-05 loss: 0.0481 (0.0628) time: 2.9530 data: 0.0083 max mem: 33370 +Epoch: [15] [1030/2639] eta: 1:17:46 lr: 3.229279915650256e-05 loss: 0.0500 (0.0628) time: 2.9295 data: 0.0083 max mem: 33370 +Epoch: [15] [1040/2639] eta: 1:17:17 lr: 3.228832395586635e-05 loss: 0.0573 (0.0627) time: 2.8937 data: 0.0085 max mem: 33370 +Epoch: [15] [1050/2639] eta: 1:16:48 lr: 3.228384868631039e-05 loss: 0.0552 (0.0628) time: 2.8824 data: 0.0088 max mem: 33370 +Epoch: [15] [1060/2639] eta: 1:16:19 lr: 3.2279373347823e-05 loss: 0.0517 (0.0627) time: 2.8868 data: 0.0083 max mem: 33370 +Epoch: [15] [1070/2639] eta: 1:15:49 lr: 3.227489794039251e-05 loss: 0.0503 (0.0626) time: 2.8840 data: 0.0080 max mem: 33370 +Epoch: [15] [1080/2639] eta: 1:15:20 lr: 3.227042246400722e-05 loss: 0.0535 (0.0627) time: 2.8654 data: 0.0078 max mem: 33370 +Epoch: [15] [1090/2639] eta: 1:14:51 lr: 3.226594691865544e-05 loss: 0.0582 (0.0627) time: 2.8930 data: 0.0076 max mem: 33370 +Epoch: [15] [1100/2639] eta: 1:14:21 lr: 3.226147130432549e-05 loss: 0.0569 (0.0628) time: 2.8841 data: 0.0076 max mem: 33370 +Epoch: [15] [1110/2639] eta: 1:13:52 lr: 3.225699562100567e-05 loss: 0.0550 (0.0627) time: 2.8729 data: 0.0074 max mem: 33370 +Epoch: [15] [1120/2639] eta: 1:13:22 lr: 3.225251986868429e-05 loss: 0.0466 (0.0627) time: 2.8566 data: 0.0076 max mem: 33370 +Epoch: [15] [1130/2639] eta: 1:12:53 lr: 3.224804404734963e-05 loss: 0.0490 (0.0627) time: 2.8461 data: 0.0078 max mem: 33370 +Epoch: [15] [1140/2639] eta: 1:12:24 lr: 3.2243568156989984e-05 loss: 0.0505 (0.0627) time: 2.8712 data: 0.0078 max mem: 33370 +Epoch: [15] [1150/2639] eta: 1:11:55 lr: 3.223909219759364e-05 loss: 0.0608 (0.0628) time: 2.9018 data: 0.0080 max mem: 33370 +Epoch: [15] [1160/2639] eta: 1:11:25 lr: 3.2234616169148903e-05 loss: 0.0521 (0.0627) time: 2.8900 data: 0.0077 max mem: 33370 +Epoch: [15] [1170/2639] eta: 1:10:56 lr: 3.223014007164404e-05 loss: 0.0521 (0.0627) time: 2.8611 data: 0.0074 max mem: 33370 +Epoch: [15] [1180/2639] eta: 1:10:27 lr: 3.2225663905067326e-05 loss: 0.0600 (0.0628) time: 2.8900 data: 0.0079 max mem: 33370 +Epoch: [15] [1190/2639] eta: 1:09:57 lr: 3.2221187669407035e-05 loss: 0.0600 (0.0628) time: 2.8668 data: 0.0083 max mem: 33370 +Epoch: [15] [1200/2639] eta: 1:09:29 lr: 3.221671136465144e-05 loss: 0.0602 (0.0628) time: 2.8851 data: 0.0082 max mem: 33370 +Epoch: [15] [1210/2639] eta: 1:09:00 lr: 3.2212234990788814e-05 loss: 0.0602 (0.0629) time: 2.9404 data: 0.0080 max mem: 33370 +Epoch: [15] [1220/2639] eta: 1:08:31 lr: 3.22077585478074e-05 loss: 0.0547 (0.0630) time: 2.8939 data: 0.0079 max mem: 33370 +Epoch: [15] [1230/2639] eta: 1:08:02 lr: 3.220328203569547e-05 loss: 0.0530 (0.0630) time: 2.8799 data: 0.0079 max mem: 33370 +Epoch: [15] [1240/2639] eta: 1:07:33 lr: 3.2198805454441275e-05 loss: 0.0509 (0.0630) time: 2.9111 data: 0.0082 max mem: 33370 +Epoch: [15] [1250/2639] eta: 1:07:05 lr: 3.2194328804033084e-05 loss: 0.0624 (0.0631) time: 2.9218 data: 0.0085 max mem: 33370 +Epoch: [15] [1260/2639] eta: 1:06:36 lr: 3.21898520844591e-05 loss: 0.0678 (0.0632) time: 2.9333 data: 0.0082 max mem: 33370 +Epoch: [15] [1270/2639] eta: 1:06:07 lr: 3.218537529570761e-05 loss: 0.0617 (0.0632) time: 2.9243 data: 0.0083 max mem: 33370 +Epoch: [15] [1280/2639] eta: 1:05:39 lr: 3.218089843776684e-05 loss: 0.0599 (0.0632) time: 2.9292 data: 0.0080 max mem: 33370 +Epoch: [15] [1290/2639] eta: 1:05:10 lr: 3.217642151062502e-05 loss: 0.0520 (0.0633) time: 2.9222 data: 0.0082 max mem: 33370 +Epoch: [15] [1300/2639] eta: 1:04:41 lr: 3.217194451427038e-05 loss: 0.0590 (0.0633) time: 2.9254 data: 0.0089 max mem: 33370 +Epoch: [15] [1310/2639] eta: 1:04:12 lr: 3.216746744869115e-05 loss: 0.0587 (0.0633) time: 2.8864 data: 0.0087 max mem: 33370 +Epoch: [15] [1320/2639] eta: 1:03:43 lr: 3.216299031387556e-05 loss: 0.0527 (0.0633) time: 2.8718 data: 0.0082 max mem: 33370 +Epoch: [15] [1330/2639] eta: 1:03:14 lr: 3.2158513109811834e-05 loss: 0.0608 (0.0633) time: 2.9267 data: 0.0081 max mem: 33370 +Epoch: [15] [1340/2639] eta: 1:02:45 lr: 3.215403583648817e-05 loss: 0.0608 (0.0633) time: 2.8935 data: 0.0077 max mem: 33370 +Epoch: [15] [1350/2639] eta: 1:02:16 lr: 3.2149558493892795e-05 loss: 0.0496 (0.0632) time: 2.8975 data: 0.0078 max mem: 33370 +Epoch: [15] [1360/2639] eta: 1:01:47 lr: 3.214508108201392e-05 loss: 0.0496 (0.0632) time: 2.9287 data: 0.0080 max mem: 33370 +Epoch: [15] [1370/2639] eta: 1:01:18 lr: 3.214060360083974e-05 loss: 0.0575 (0.0632) time: 2.8947 data: 0.0081 max mem: 33370 +Epoch: [15] [1380/2639] eta: 1:00:49 lr: 3.2136126050358463e-05 loss: 0.0491 (0.0631) time: 2.8757 data: 0.0082 max mem: 33370 +Epoch: [15] [1390/2639] eta: 1:00:20 lr: 3.213164843055828e-05 loss: 0.0516 (0.0631) time: 2.8904 data: 0.0081 max mem: 33370 +Epoch: [15] [1400/2639] eta: 0:59:50 lr: 3.2127170741427384e-05 loss: 0.0581 (0.0632) time: 2.8689 data: 0.0080 max mem: 33370 +Epoch: [15] [1410/2639] eta: 0:59:22 lr: 3.212269298295398e-05 loss: 0.0600 (0.0631) time: 2.8760 data: 0.0080 max mem: 33370 +Epoch: [15] [1420/2639] eta: 0:58:52 lr: 3.211821515512624e-05 loss: 0.0550 (0.0630) time: 2.8808 data: 0.0078 max mem: 33370 +Epoch: [15] [1430/2639] eta: 0:58:23 lr: 3.2113737257932346e-05 loss: 0.0563 (0.0630) time: 2.8605 data: 0.0078 max mem: 33370 +Epoch: [15] [1440/2639] eta: 0:57:54 lr: 3.210925929136048e-05 loss: 0.0585 (0.0632) time: 2.8867 data: 0.0081 max mem: 33370 +Epoch: [15] [1450/2639] eta: 0:57:25 lr: 3.210478125539882e-05 loss: 0.0585 (0.0631) time: 2.8742 data: 0.0085 max mem: 33370 +Epoch: [15] [1460/2639] eta: 0:56:55 lr: 3.2100303150035525e-05 loss: 0.0517 (0.0631) time: 2.8610 data: 0.0086 max mem: 33370 +Epoch: [15] [1470/2639] eta: 0:56:26 lr: 3.2095824975258764e-05 loss: 0.0480 (0.0631) time: 2.8488 data: 0.0085 max mem: 33370 +Epoch: [15] [1480/2639] eta: 0:55:57 lr: 3.209134673105671e-05 loss: 0.0506 (0.0630) time: 2.8743 data: 0.0083 max mem: 33370 +Epoch: [15] [1490/2639] eta: 0:55:28 lr: 3.2086868417417516e-05 loss: 0.0530 (0.0631) time: 2.8883 data: 0.0081 max mem: 33370 +Epoch: [15] [1500/2639] eta: 0:54:59 lr: 3.208239003432933e-05 loss: 0.0635 (0.0631) time: 2.8722 data: 0.0081 max mem: 33370 +Epoch: [15] [1510/2639] eta: 0:54:30 lr: 3.207791158178032e-05 loss: 0.0513 (0.0631) time: 2.9091 data: 0.0079 max mem: 33370 +Epoch: [15] [1520/2639] eta: 0:54:01 lr: 3.207343305975861e-05 loss: 0.0527 (0.0631) time: 2.9032 data: 0.0082 max mem: 33370 +Epoch: [15] [1530/2639] eta: 0:53:32 lr: 3.206895446825237e-05 loss: 0.0538 (0.0631) time: 2.8971 data: 0.0081 max mem: 33370 +Epoch: [15] [1540/2639] eta: 0:53:03 lr: 3.206447580724972e-05 loss: 0.0538 (0.0631) time: 2.9054 data: 0.0080 max mem: 33370 +Epoch: [15] [1550/2639] eta: 0:52:34 lr: 3.20599970767388e-05 loss: 0.0614 (0.0631) time: 2.9124 data: 0.0081 max mem: 33370 +Epoch: [15] [1560/2639] eta: 0:52:06 lr: 3.205551827670774e-05 loss: 0.0561 (0.0631) time: 2.9339 data: 0.0082 max mem: 33370 +Epoch: [15] [1570/2639] eta: 0:51:37 lr: 3.205103940714468e-05 loss: 0.0497 (0.0631) time: 2.9028 data: 0.0081 max mem: 33370 +Epoch: [15] [1580/2639] eta: 0:51:08 lr: 3.204656046803773e-05 loss: 0.0505 (0.0630) time: 2.8792 data: 0.0081 max mem: 33370 +Epoch: [15] [1590/2639] eta: 0:50:38 lr: 3.2042081459375015e-05 loss: 0.0562 (0.0631) time: 2.8847 data: 0.0082 max mem: 33370 +Epoch: [15] [1600/2639] eta: 0:50:09 lr: 3.203760238114465e-05 loss: 0.0585 (0.0631) time: 2.8771 data: 0.0080 max mem: 33370 +Epoch: [15] [1610/2639] eta: 0:49:40 lr: 3.203312323333475e-05 loss: 0.0483 (0.0631) time: 2.8914 data: 0.0077 max mem: 33370 +Epoch: [15] [1620/2639] eta: 0:49:11 lr: 3.202864401593343e-05 loss: 0.0483 (0.0631) time: 2.8997 data: 0.0078 max mem: 33370 +Epoch: [15] [1630/2639] eta: 0:48:43 lr: 3.2024164728928784e-05 loss: 0.0519 (0.0630) time: 2.9022 data: 0.0080 max mem: 33370 +Epoch: [15] [1640/2639] eta: 0:48:14 lr: 3.2019685372308914e-05 loss: 0.0446 (0.0629) time: 2.9131 data: 0.0083 max mem: 33370 +Epoch: [15] [1650/2639] eta: 0:47:45 lr: 3.201520594606192e-05 loss: 0.0446 (0.0629) time: 2.9041 data: 0.0087 max mem: 33370 +Epoch: [15] [1660/2639] eta: 0:47:16 lr: 3.2010726450175886e-05 loss: 0.0507 (0.0629) time: 2.8821 data: 0.0084 max mem: 33370 +Epoch: [15] [1670/2639] eta: 0:46:47 lr: 3.2006246884638924e-05 loss: 0.0502 (0.0628) time: 2.8819 data: 0.0082 max mem: 33370 +Epoch: [15] [1680/2639] eta: 0:46:18 lr: 3.20017672494391e-05 loss: 0.0487 (0.0629) time: 2.9011 data: 0.0081 max mem: 33370 +Epoch: [15] [1690/2639] eta: 0:45:49 lr: 3.199728754456449e-05 loss: 0.0634 (0.0629) time: 2.9022 data: 0.0078 max mem: 33370 +Epoch: [15] [1700/2639] eta: 0:45:20 lr: 3.199280777000319e-05 loss: 0.0607 (0.0630) time: 2.9167 data: 0.0079 max mem: 33370 +Epoch: [15] [1710/2639] eta: 0:44:51 lr: 3.198832792574327e-05 loss: 0.0607 (0.0631) time: 2.9421 data: 0.0079 max mem: 33370 +Epoch: [15] [1720/2639] eta: 0:44:22 lr: 3.1983848011772784e-05 loss: 0.0537 (0.0630) time: 2.9074 data: 0.0077 max mem: 33370 +Epoch: [15] [1730/2639] eta: 0:43:53 lr: 3.1979368028079806e-05 loss: 0.0558 (0.0631) time: 2.8633 data: 0.0078 max mem: 33370 +Epoch: [15] [1740/2639] eta: 0:43:24 lr: 3.1974887974652415e-05 loss: 0.0609 (0.0631) time: 2.8470 data: 0.0081 max mem: 33370 +Epoch: [15] [1750/2639] eta: 0:42:55 lr: 3.1970407851478644e-05 loss: 0.0557 (0.0631) time: 2.9049 data: 0.0080 max mem: 33370 +Epoch: [15] [1760/2639] eta: 0:42:26 lr: 3.196592765854656e-05 loss: 0.0666 (0.0632) time: 2.9631 data: 0.0082 max mem: 33370 +Epoch: [15] [1770/2639] eta: 0:41:57 lr: 3.19614473958442e-05 loss: 0.0562 (0.0632) time: 2.9075 data: 0.0081 max mem: 33370 +Epoch: [15] [1780/2639] eta: 0:41:28 lr: 3.195696706335963e-05 loss: 0.0534 (0.0633) time: 2.8458 data: 0.0080 max mem: 33370 +Epoch: [15] [1790/2639] eta: 0:40:59 lr: 3.1952486661080895e-05 loss: 0.0554 (0.0633) time: 2.8574 data: 0.0081 max mem: 33370 +Epoch: [15] [1800/2639] eta: 0:40:30 lr: 3.1948006188996005e-05 loss: 0.0545 (0.0632) time: 2.9123 data: 0.0079 max mem: 33370 +Epoch: [15] [1810/2639] eta: 0:40:01 lr: 3.194352564709301e-05 loss: 0.0490 (0.0632) time: 2.9130 data: 0.0081 max mem: 33370 +Epoch: [15] [1820/2639] eta: 0:39:33 lr: 3.193904503535995e-05 loss: 0.0509 (0.0631) time: 2.9394 data: 0.0083 max mem: 33370 +Epoch: [15] [1830/2639] eta: 0:39:04 lr: 3.193456435378484e-05 loss: 0.0551 (0.0632) time: 2.9310 data: 0.0083 max mem: 33370 +Epoch: [15] [1840/2639] eta: 0:38:35 lr: 3.1930083602355705e-05 loss: 0.0679 (0.0632) time: 2.8800 data: 0.0083 max mem: 33370 +Epoch: [15] [1850/2639] eta: 0:38:06 lr: 3.192560278106056e-05 loss: 0.0563 (0.0632) time: 2.8902 data: 0.0080 max mem: 33370 +Epoch: [15] [1860/2639] eta: 0:37:36 lr: 3.1921121889887426e-05 loss: 0.0477 (0.0632) time: 2.8817 data: 0.0081 max mem: 33370 +Epoch: [15] [1870/2639] eta: 0:37:08 lr: 3.191664092882433e-05 loss: 0.0507 (0.0632) time: 2.8951 data: 0.0083 max mem: 33370 +Epoch: [15] [1880/2639] eta: 0:36:39 lr: 3.1912159897859244e-05 loss: 0.0596 (0.0632) time: 2.9348 data: 0.0083 max mem: 33370 +Epoch: [15] [1890/2639] eta: 0:36:10 lr: 3.19076787969802e-05 loss: 0.0510 (0.0631) time: 2.9485 data: 0.0077 max mem: 33370 +Epoch: [15] [1900/2639] eta: 0:35:41 lr: 3.1903197626175166e-05 loss: 0.0510 (0.0632) time: 2.9035 data: 0.0074 max mem: 33370 +Epoch: [15] [1910/2639] eta: 0:35:12 lr: 3.1898716385432175e-05 loss: 0.0631 (0.0631) time: 2.8691 data: 0.0078 max mem: 33370 +Epoch: [15] [1920/2639] eta: 0:34:43 lr: 3.18942350747392e-05 loss: 0.0600 (0.0631) time: 2.8907 data: 0.0079 max mem: 33370 +Epoch: [15] [1930/2639] eta: 0:34:14 lr: 3.188975369408422e-05 loss: 0.0557 (0.0631) time: 2.8864 data: 0.0083 max mem: 33370 +Epoch: [15] [1940/2639] eta: 0:33:45 lr: 3.1885272243455234e-05 loss: 0.0492 (0.0632) time: 2.9052 data: 0.0087 max mem: 33370 +Epoch: [15] [1950/2639] eta: 0:33:16 lr: 3.188079072284021e-05 loss: 0.0605 (0.0632) time: 2.9482 data: 0.0084 max mem: 33370 +Epoch: [15] [1960/2639] eta: 0:32:47 lr: 3.187630913222714e-05 loss: 0.0520 (0.0631) time: 2.9271 data: 0.0083 max mem: 33370 +Epoch: [15] [1970/2639] eta: 0:32:18 lr: 3.187182747160397e-05 loss: 0.0499 (0.0631) time: 2.8904 data: 0.0085 max mem: 33370 +Epoch: [15] [1980/2639] eta: 0:31:49 lr: 3.186734574095869e-05 loss: 0.0593 (0.0631) time: 2.9017 data: 0.0080 max mem: 33370 +Epoch: [15] [1990/2639] eta: 0:31:20 lr: 3.1862863940279255e-05 loss: 0.0647 (0.0632) time: 2.8987 data: 0.0076 max mem: 33370 +Epoch: [15] [2000/2639] eta: 0:30:51 lr: 3.1858382069553627e-05 loss: 0.0647 (0.0632) time: 2.8697 data: 0.0080 max mem: 33370 +Epoch: [15] [2010/2639] eta: 0:30:22 lr: 3.1853900128769754e-05 loss: 0.0574 (0.0632) time: 2.8707 data: 0.0085 max mem: 33370 +Epoch: [15] [2020/2639] eta: 0:29:53 lr: 3.184941811791559e-05 loss: 0.0557 (0.0632) time: 2.8528 data: 0.0085 max mem: 33370 +Epoch: [15] [2030/2639] eta: 0:29:24 lr: 3.18449360369791e-05 loss: 0.0557 (0.0632) time: 2.8530 data: 0.0081 max mem: 33370 +Epoch: [15] [2040/2639] eta: 0:28:55 lr: 3.1840453885948215e-05 loss: 0.0627 (0.0632) time: 2.8320 data: 0.0077 max mem: 33370 +Epoch: [15] [2050/2639] eta: 0:28:26 lr: 3.183597166481086e-05 loss: 0.0612 (0.0632) time: 2.8710 data: 0.0075 max mem: 33370 +Epoch: [15] [2060/2639] eta: 0:27:57 lr: 3.183148937355499e-05 loss: 0.0585 (0.0632) time: 2.9172 data: 0.0076 max mem: 33370 +Epoch: [15] [2070/2639] eta: 0:27:28 lr: 3.182700701216855e-05 loss: 0.0603 (0.0632) time: 2.8902 data: 0.0076 max mem: 33370 +Epoch: [15] [2080/2639] eta: 0:26:59 lr: 3.1822524580639426e-05 loss: 0.0610 (0.0632) time: 2.8868 data: 0.0075 max mem: 33370 +Epoch: [15] [2090/2639] eta: 0:26:30 lr: 3.181804207895559e-05 loss: 0.0563 (0.0632) time: 2.8474 data: 0.0078 max mem: 33370 +Epoch: [15] [2100/2639] eta: 0:26:01 lr: 3.181355950710492e-05 loss: 0.0509 (0.0632) time: 2.8906 data: 0.0083 max mem: 33370 +Epoch: [15] [2110/2639] eta: 0:25:32 lr: 3.180907686507536e-05 loss: 0.0605 (0.0632) time: 2.8984 data: 0.0080 max mem: 33370 +Epoch: [15] [2120/2639] eta: 0:25:03 lr: 3.1804594152854814e-05 loss: 0.0605 (0.0632) time: 2.8542 data: 0.0078 max mem: 33370 +Epoch: [15] [2130/2639] eta: 0:24:34 lr: 3.1800111370431195e-05 loss: 0.0565 (0.0632) time: 2.8984 data: 0.0077 max mem: 33370 +Epoch: [15] [2140/2639] eta: 0:24:05 lr: 3.17956285177924e-05 loss: 0.0565 (0.0633) time: 2.9195 data: 0.0075 max mem: 33370 +Epoch: [15] [2150/2639] eta: 0:23:36 lr: 3.179114559492633e-05 loss: 0.0609 (0.0632) time: 2.9172 data: 0.0080 max mem: 33370 +Epoch: [15] [2160/2639] eta: 0:23:07 lr: 3.1786662601820874e-05 loss: 0.0633 (0.0633) time: 2.9033 data: 0.0080 max mem: 33370 +Epoch: [15] [2170/2639] eta: 0:22:38 lr: 3.1782179538463945e-05 loss: 0.0570 (0.0633) time: 2.8859 data: 0.0078 max mem: 33370 +Epoch: [15] [2180/2639] eta: 0:22:09 lr: 3.177769640484342e-05 loss: 0.0558 (0.0632) time: 2.8547 data: 0.0083 max mem: 33370 +Epoch: [15] [2190/2639] eta: 0:21:40 lr: 3.1773213200947174e-05 loss: 0.0558 (0.0633) time: 2.8649 data: 0.0085 max mem: 33370 +Epoch: [15] [2200/2639] eta: 0:21:11 lr: 3.17687299267631e-05 loss: 0.0554 (0.0633) time: 2.9029 data: 0.0082 max mem: 33370 +Epoch: [15] [2210/2639] eta: 0:20:42 lr: 3.176424658227908e-05 loss: 0.0712 (0.0633) time: 2.9064 data: 0.0078 max mem: 33370 +Epoch: [15] [2220/2639] eta: 0:20:13 lr: 3.175976316748296e-05 loss: 0.0581 (0.0633) time: 2.9212 data: 0.0079 max mem: 33370 +Epoch: [15] [2230/2639] eta: 0:19:44 lr: 3.1755279682362634e-05 loss: 0.0492 (0.0632) time: 2.9303 data: 0.0080 max mem: 33370 +Epoch: [15] [2240/2639] eta: 0:19:15 lr: 3.175079612690596e-05 loss: 0.0502 (0.0632) time: 2.9692 data: 0.0075 max mem: 33370 +Epoch: [15] [2250/2639] eta: 0:18:47 lr: 3.17463125011008e-05 loss: 0.0571 (0.0633) time: 2.9765 data: 0.0075 max mem: 33370 +Epoch: [15] [2260/2639] eta: 0:18:18 lr: 3.1741828804934995e-05 loss: 0.0574 (0.0633) time: 2.9014 data: 0.0079 max mem: 33370 +Epoch: [15] [2270/2639] eta: 0:17:48 lr: 3.173734503839642e-05 loss: 0.0540 (0.0633) time: 2.8411 data: 0.0082 max mem: 33370 +Epoch: [15] [2280/2639] eta: 0:17:19 lr: 3.17328612014729e-05 loss: 0.0580 (0.0633) time: 2.8676 data: 0.0082 max mem: 33370 +Epoch: [15] [2290/2639] eta: 0:16:51 lr: 3.1728377294152306e-05 loss: 0.0593 (0.0633) time: 2.9240 data: 0.0081 max mem: 33370 +Epoch: [15] [2300/2639] eta: 0:16:22 lr: 3.1723893316422456e-05 loss: 0.0578 (0.0633) time: 2.9200 data: 0.0080 max mem: 33370 +Epoch: [15] [2310/2639] eta: 0:15:53 lr: 3.171940926827119e-05 loss: 0.0546 (0.0633) time: 2.8832 data: 0.0077 max mem: 33370 +Epoch: [15] [2320/2639] eta: 0:15:24 lr: 3.1714925149686346e-05 loss: 0.0606 (0.0634) time: 2.8680 data: 0.0079 max mem: 33370 +Epoch: [15] [2330/2639] eta: 0:14:55 lr: 3.171044096065576e-05 loss: 0.0697 (0.0634) time: 2.9040 data: 0.0080 max mem: 33370 +Epoch: [15] [2340/2639] eta: 0:14:26 lr: 3.1705956701167244e-05 loss: 0.0623 (0.0635) time: 2.9041 data: 0.0077 max mem: 33370 +Epoch: [15] [2350/2639] eta: 0:13:57 lr: 3.1701472371208616e-05 loss: 0.0545 (0.0634) time: 2.8919 data: 0.0078 max mem: 33370 +Epoch: [15] [2360/2639] eta: 0:13:28 lr: 3.16969879707677e-05 loss: 0.0514 (0.0634) time: 2.8947 data: 0.0081 max mem: 33370 +Epoch: [15] [2370/2639] eta: 0:12:59 lr: 3.169250349983231e-05 loss: 0.0494 (0.0634) time: 2.9309 data: 0.0081 max mem: 33370 +Epoch: [15] [2380/2639] eta: 0:12:30 lr: 3.1688018958390256e-05 loss: 0.0431 (0.0633) time: 2.9423 data: 0.0081 max mem: 33370 +Epoch: [15] [2390/2639] eta: 0:12:01 lr: 3.168353434642932e-05 loss: 0.0563 (0.0633) time: 2.9039 data: 0.0079 max mem: 33370 +Epoch: [15] [2400/2639] eta: 0:11:32 lr: 3.167904966393733e-05 loss: 0.0588 (0.0634) time: 2.9051 data: 0.0080 max mem: 33370 +Epoch: [15] [2410/2639] eta: 0:11:03 lr: 3.167456491090207e-05 loss: 0.0552 (0.0633) time: 2.8785 data: 0.0079 max mem: 33370 +Epoch: [15] [2420/2639] eta: 0:10:34 lr: 3.1670080087311335e-05 loss: 0.0504 (0.0634) time: 2.8666 data: 0.0077 max mem: 33370 +Epoch: [15] [2430/2639] eta: 0:10:05 lr: 3.166559519315291e-05 loss: 0.0489 (0.0633) time: 2.8882 data: 0.0080 max mem: 33370 +Epoch: [15] [2440/2639] eta: 0:09:36 lr: 3.166111022841458e-05 loss: 0.0489 (0.0633) time: 2.9054 data: 0.0082 max mem: 33370 +Epoch: [15] [2450/2639] eta: 0:09:07 lr: 3.165662519308412e-05 loss: 0.0586 (0.0634) time: 2.8961 data: 0.0079 max mem: 33370 +Epoch: [15] [2460/2639] eta: 0:08:38 lr: 3.165214008714932e-05 loss: 0.0568 (0.0634) time: 2.8835 data: 0.0074 max mem: 33370 +Epoch: [15] [2470/2639] eta: 0:08:09 lr: 3.164765491059794e-05 loss: 0.0558 (0.0634) time: 2.8942 data: 0.0073 max mem: 33370 +Epoch: [15] [2480/2639] eta: 0:07:40 lr: 3.1643169663417743e-05 loss: 0.0552 (0.0635) time: 2.9376 data: 0.0074 max mem: 33370 +Epoch: [15] [2490/2639] eta: 0:07:11 lr: 3.1638684345596505e-05 loss: 0.0552 (0.0635) time: 2.9599 data: 0.0073 max mem: 33370 +Epoch: [15] [2500/2639] eta: 0:06:42 lr: 3.163419895712199e-05 loss: 0.0550 (0.0636) time: 2.9281 data: 0.0073 max mem: 33370 +Epoch: [15] [2510/2639] eta: 0:06:13 lr: 3.162971349798194e-05 loss: 0.0549 (0.0635) time: 2.9276 data: 0.0075 max mem: 33370 +Epoch: [15] [2520/2639] eta: 0:05:44 lr: 3.1625227968164104e-05 loss: 0.0527 (0.0636) time: 2.8780 data: 0.0077 max mem: 33370 +Epoch: [15] [2530/2639] eta: 0:05:15 lr: 3.162074236765625e-05 loss: 0.0583 (0.0636) time: 2.8760 data: 0.0080 max mem: 33370 +Epoch: [15] [2540/2639] eta: 0:04:46 lr: 3.161625669644611e-05 loss: 0.0583 (0.0636) time: 2.8833 data: 0.0079 max mem: 33370 +Epoch: [15] [2550/2639] eta: 0:04:17 lr: 3.1611770954521414e-05 loss: 0.0602 (0.0636) time: 2.8090 data: 0.0079 max mem: 33370 +Epoch: [15] [2560/2639] eta: 0:03:48 lr: 3.1607285141869904e-05 loss: 0.0594 (0.0636) time: 2.8544 data: 0.0080 max mem: 33370 +Epoch: [15] [2570/2639] eta: 0:03:19 lr: 3.160279925847932e-05 loss: 0.0616 (0.0637) time: 2.9030 data: 0.0077 max mem: 33370 +Epoch: [15] [2580/2639] eta: 0:02:50 lr: 3.159831330433739e-05 loss: 0.0573 (0.0636) time: 2.8788 data: 0.0074 max mem: 33370 +Epoch: [15] [2590/2639] eta: 0:02:21 lr: 3.159382727943182e-05 loss: 0.0517 (0.0636) time: 2.8562 data: 0.0077 max mem: 33370 +Epoch: [15] [2600/2639] eta: 0:01:52 lr: 3.158934118375034e-05 loss: 0.0686 (0.0637) time: 2.8645 data: 0.0079 max mem: 33370 +Epoch: [15] [2610/2639] eta: 0:01:24 lr: 3.1584855017280665e-05 loss: 0.0686 (0.0637) time: 2.9183 data: 0.0079 max mem: 33370 +Epoch: [15] [2620/2639] eta: 0:00:55 lr: 3.158036878001051e-05 loss: 0.0530 (0.0637) time: 2.9401 data: 0.0079 max mem: 33370 +Epoch: [15] [2630/2639] eta: 0:00:26 lr: 3.157588247192758e-05 loss: 0.0527 (0.0636) time: 2.9160 data: 0.0077 max mem: 33370 +Epoch: [15] Total time: 2:07:26 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 2:28:22 time: 3.4599 data: 3.3715 max mem: 33370 +Test: [ 100/2573] eta: 0:04:36 time: 0.0784 data: 0.0014 max mem: 33370 +Test: [ 200/2573] eta: 0:03:49 time: 0.0797 data: 0.0014 max mem: 33370 +Test: [ 300/2573] eta: 0:03:25 time: 0.0817 data: 0.0013 max mem: 33370 +Test: [ 400/2573] eta: 0:03:11 time: 0.0826 data: 0.0015 max mem: 33370 +Test: [ 500/2573] eta: 0:02:59 time: 0.0809 data: 0.0015 max mem: 33370 +Test: [ 600/2573] eta: 0:02:48 time: 0.0806 data: 0.0016 max mem: 33370 +Test: [ 700/2573] eta: 0:02:39 time: 0.0805 data: 0.0014 max mem: 33370 +Test: [ 800/2573] eta: 0:02:30 time: 0.0831 data: 0.0014 max mem: 33370 +Test: [ 900/2573] eta: 0:02:21 time: 0.0810 data: 0.0016 max mem: 33370 +Test: [1000/2573] eta: 0:02:12 time: 0.0812 data: 0.0014 max mem: 33370 +Test: [1100/2573] eta: 0:02:03 time: 0.0811 data: 0.0014 max mem: 33370 +Test: [1200/2573] eta: 0:01:54 time: 0.0810 data: 0.0014 max mem: 33370 +Test: [1300/2573] eta: 0:01:46 time: 0.0816 data: 0.0015 max mem: 33370 +Test: [1400/2573] eta: 0:01:37 time: 0.0799 data: 0.0015 max mem: 33370 +Test: [1500/2573] eta: 0:01:29 time: 0.0810 data: 0.0016 max mem: 33370 +Test: [1600/2573] eta: 0:01:20 time: 0.0839 data: 0.0014 max mem: 33370 +Test: [1700/2573] eta: 0:01:12 time: 0.0800 data: 0.0015 max mem: 33370 +Test: [1800/2573] eta: 0:01:04 time: 0.0821 data: 0.0014 max mem: 33370 +Test: [1900/2573] eta: 0:00:55 time: 0.0793 data: 0.0014 max mem: 33370 +Test: [2000/2573] eta: 0:00:47 time: 0.0813 data: 0.0014 max mem: 33370 +Test: [2100/2573] eta: 0:00:39 time: 0.0829 data: 0.0014 max mem: 33370 +Test: [2200/2573] eta: 0:00:30 time: 0.0829 data: 0.0014 max mem: 33370 +Test: [2300/2573] eta: 0:00:22 time: 0.0829 data: 0.0015 max mem: 33370 +Test: [2400/2573] eta: 0:00:14 time: 0.0781 data: 0.0014 max mem: 33370 +Test: [2500/2573] eta: 0:00:06 time: 0.0805 data: 0.0014 max mem: 33370 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: Total time: 0:03:32 +Final results: +Mean IoU is 61.52 + + precision@0.5 = 68.97 + precision@0.6 = 63.17 + precision@0.7 = 55.78 + precision@0.8 = 44.40 + precision@0.9 = 20.73 + overall IoU = 59.73 + +Average object IoU 61.517566605705774 +Overall IoU 59.73097229003906 +Better epoch: 15 + +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [16] [ 0/2639] eta: 3:57:00 lr: 3.157184473409784e-05 loss: 0.0715 (0.0715) time: 5.3886 data: 2.3501 max mem: 33370 +Epoch: [16] [ 10/2639] eta: 2:16:50 lr: 3.1567358291436746e-05 loss: 0.0715 (0.0613) time: 3.1232 data: 0.2207 max mem: 33370 +Epoch: [16] [ 20/2639] eta: 2:11:27 lr: 3.156287177792721e-05 loss: 0.0522 (0.0641) time: 2.8927 data: 0.0079 max mem: 33370 +Epoch: [16] [ 30/2639] eta: 2:09:28 lr: 3.1558385193556906e-05 loss: 0.0503 (0.0601) time: 2.8973 data: 0.0077 max mem: 33370 +Epoch: [16] [ 40/2639] eta: 2:07:36 lr: 3.1553898538313525e-05 loss: 0.0471 (0.0576) time: 2.8770 data: 0.0079 max mem: 33370 +Epoch: [16] [ 50/2639] eta: 2:07:02 lr: 3.154941181218476e-05 loss: 0.0471 (0.0562) time: 2.8926 data: 0.0078 max mem: 33370 +Epoch: [16] [ 60/2639] eta: 2:06:04 lr: 3.15449250151583e-05 loss: 0.0481 (0.0558) time: 2.9071 data: 0.0075 max mem: 33370 +Epoch: [16] [ 70/2639] eta: 2:05:20 lr: 3.154043814722178e-05 loss: 0.0517 (0.0555) time: 2.8851 data: 0.0075 max mem: 33370 +Epoch: [16] [ 80/2639] eta: 2:04:21 lr: 3.15359512083629e-05 loss: 0.0524 (0.0559) time: 2.8627 data: 0.0076 max mem: 33370 +Epoch: [16] [ 90/2639] eta: 2:04:01 lr: 3.1531464198569334e-05 loss: 0.0548 (0.0551) time: 2.8908 data: 0.0078 max mem: 33370 +Epoch: [16] [ 100/2639] eta: 2:03:30 lr: 3.152697711782873e-05 loss: 0.0376 (0.0541) time: 2.9305 data: 0.0076 max mem: 33370 +Epoch: [16] [ 110/2639] eta: 2:03:13 lr: 3.152248996612874e-05 loss: 0.0376 (0.0542) time: 2.9424 data: 0.0077 max mem: 33370 +Epoch: [16] [ 120/2639] eta: 2:02:39 lr: 3.1518002743457024e-05 loss: 0.0499 (0.0543) time: 2.9353 data: 0.0081 max mem: 33370 +Epoch: [16] [ 130/2639] eta: 2:01:58 lr: 3.1513515449801244e-05 loss: 0.0499 (0.0543) time: 2.8809 data: 0.0083 max mem: 33370 +Epoch: [16] [ 140/2639] eta: 2:01:17 lr: 3.150902808514903e-05 loss: 0.0464 (0.0540) time: 2.8556 data: 0.0081 max mem: 33370 +Epoch: [16] [ 150/2639] eta: 2:00:42 lr: 3.150454064948804e-05 loss: 0.0468 (0.0547) time: 2.8629 data: 0.0077 max mem: 33370 +Epoch: [16] [ 160/2639] eta: 2:00:13 lr: 3.150005314280589e-05 loss: 0.0547 (0.0549) time: 2.8950 data: 0.0077 max mem: 33370 +Epoch: [16] [ 170/2639] eta: 1:59:41 lr: 3.149556556509024e-05 loss: 0.0577 (0.0551) time: 2.8999 data: 0.0079 max mem: 33370 +Epoch: [16] [ 180/2639] eta: 1:59:11 lr: 3.14910779163287e-05 loss: 0.0550 (0.0555) time: 2.8956 data: 0.0081 max mem: 33370 +Epoch: [16] [ 190/2639] eta: 1:58:51 lr: 3.1486590196508896e-05 loss: 0.0531 (0.0558) time: 2.9392 data: 0.0084 max mem: 33370 +Epoch: [16] [ 200/2639] eta: 1:58:21 lr: 3.1482102405618464e-05 loss: 0.0681 (0.0576) time: 2.9424 data: 0.0087 max mem: 33370 +Epoch: [16] [ 210/2639] eta: 1:57:49 lr: 3.1477614543645e-05 loss: 0.0661 (0.0580) time: 2.8949 data: 0.0086 max mem: 33370 +Epoch: [16] [ 220/2639] eta: 1:57:23 lr: 3.1473126610576144e-05 loss: 0.0527 (0.0578) time: 2.9096 data: 0.0084 max mem: 33370 +Epoch: [16] [ 230/2639] eta: 1:56:49 lr: 3.146863860639949e-05 loss: 0.0471 (0.0579) time: 2.9018 data: 0.0081 max mem: 33370 +Epoch: [16] [ 240/2639] eta: 1:56:18 lr: 3.1464150531102634e-05 loss: 0.0574 (0.0583) time: 2.8801 data: 0.0077 max mem: 33370 +Epoch: [16] [ 250/2639] eta: 1:55:43 lr: 3.1459662384673185e-05 loss: 0.0676 (0.0592) time: 2.8688 data: 0.0078 max mem: 33370 +Epoch: [16] [ 260/2639] eta: 1:55:11 lr: 3.145517416709875e-05 loss: 0.0585 (0.0593) time: 2.8603 data: 0.0080 max mem: 33370 +Epoch: [16] [ 270/2639] eta: 1:54:39 lr: 3.145068587836691e-05 loss: 0.0523 (0.0590) time: 2.8741 data: 0.0084 max mem: 33370 +Epoch: [16] [ 280/2639] eta: 1:54:09 lr: 3.144619751846525e-05 loss: 0.0500 (0.0587) time: 2.8810 data: 0.0081 max mem: 33370 +Epoch: [16] [ 290/2639] eta: 1:53:42 lr: 3.144170908738136e-05 loss: 0.0500 (0.0586) time: 2.9098 data: 0.0083 max mem: 33370 +Epoch: [16] [ 300/2639] eta: 1:53:17 lr: 3.143722058510283e-05 loss: 0.0484 (0.0581) time: 2.9420 data: 0.0083 max mem: 33370 +Epoch: 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data: 0.0081 max mem: 33370 +Epoch: [16] [ 470/2639] eta: 1:44:55 lr: 3.136090514153135e-05 loss: 0.0579 (0.0580) time: 2.8685 data: 0.0080 max mem: 33370 +Epoch: [16] [ 480/2639] eta: 1:44:25 lr: 3.1356415355620594e-05 loss: 0.0590 (0.0579) time: 2.8774 data: 0.0075 max mem: 33370 +Epoch: [16] [ 490/2639] eta: 1:43:55 lr: 3.1351925498278416e-05 loss: 0.0503 (0.0581) time: 2.8842 data: 0.0074 max mem: 33370 +Epoch: [16] [ 500/2639] eta: 1:43:27 lr: 3.134743556949232e-05 loss: 0.0476 (0.0578) time: 2.9084 data: 0.0076 max mem: 33370 +Epoch: [16] [ 510/2639] eta: 1:42:57 lr: 3.134294556924981e-05 loss: 0.0524 (0.0580) time: 2.8966 data: 0.0077 max mem: 33370 +Epoch: [16] [ 520/2639] eta: 1:42:27 lr: 3.133845549753835e-05 loss: 0.0588 (0.0580) time: 2.8754 data: 0.0079 max mem: 33370 +Epoch: [16] [ 530/2639] eta: 1:41:56 lr: 3.133396535434544e-05 loss: 0.0539 (0.0580) time: 2.8685 data: 0.0083 max mem: 33370 +Epoch: [16] [ 540/2639] eta: 1:41:25 lr: 3.132947513965855e-05 loss: 0.0581 (0.0581) time: 2.8534 data: 0.0082 max mem: 33370 +Epoch: [16] [ 550/2639] eta: 1:40:56 lr: 3.132498485346518e-05 loss: 0.0679 (0.0584) time: 2.8785 data: 0.0081 max mem: 33370 +Epoch: [16] [ 560/2639] eta: 1:40:26 lr: 3.132049449575278e-05 loss: 0.0569 (0.0583) time: 2.8858 data: 0.0081 max mem: 33370 +Epoch: [16] [ 570/2639] eta: 1:39:57 lr: 3.131600406650881e-05 loss: 0.0543 (0.0586) time: 2.8878 data: 0.0081 max mem: 33370 +Epoch: [16] [ 580/2639] eta: 1:39:28 lr: 3.131151356572076e-05 loss: 0.0544 (0.0585) time: 2.8918 data: 0.0080 max mem: 33370 +Epoch: [16] [ 590/2639] eta: 1:38:57 lr: 3.1307022993376073e-05 loss: 0.0576 (0.0587) time: 2.8621 data: 0.0083 max mem: 33370 +Epoch: [16] [ 600/2639] eta: 1:38:28 lr: 3.130253234946221e-05 loss: 0.0678 (0.0588) time: 2.8711 data: 0.0083 max mem: 33370 +Epoch: [16] [ 610/2639] eta: 1:38:01 lr: 3.129804163396661e-05 loss: 0.0643 (0.0589) time: 2.9217 data: 0.0079 max mem: 33370 +Epoch: [16] [ 620/2639] eta: 1:37:31 lr: 3.1293550846876725e-05 loss: 0.0631 (0.0590) time: 2.9060 data: 0.0080 max mem: 33370 +Epoch: [16] [ 630/2639] eta: 1:37:01 lr: 3.128905998818001e-05 loss: 0.0598 (0.0591) time: 2.8735 data: 0.0081 max mem: 33370 +Epoch: [16] [ 640/2639] eta: 1:36:32 lr: 3.1284569057863894e-05 loss: 0.0596 (0.0591) time: 2.8909 data: 0.0081 max mem: 33370 +Epoch: [16] [ 650/2639] eta: 1:36:03 lr: 3.128007805591581e-05 loss: 0.0592 (0.0591) time: 2.8983 data: 0.0081 max mem: 33370 +Epoch: [16] [ 660/2639] eta: 1:35:34 lr: 3.127558698232319e-05 loss: 0.0549 (0.0594) time: 2.8934 data: 0.0079 max mem: 33370 +Epoch: [16] [ 670/2639] eta: 1:35:04 lr: 3.127109583707346e-05 loss: 0.0549 (0.0596) time: 2.8809 data: 0.0079 max mem: 33370 +Epoch: [16] [ 680/2639] eta: 1:34:35 lr: 3.1266604620154035e-05 loss: 0.0568 (0.0596) time: 2.8842 data: 0.0085 max mem: 33370 +Epoch: [16] [ 690/2639] eta: 1:34:06 lr: 3.1262113331552334e-05 loss: 0.0586 (0.0597) time: 2.8926 data: 0.0085 max mem: 33370 +Epoch: [16] [ 700/2639] eta: 1:33:36 lr: 3.125762197125578e-05 loss: 0.0609 (0.0597) time: 2.8655 data: 0.0081 max mem: 33370 +Epoch: [16] [ 710/2639] eta: 1:33:06 lr: 3.125313053925177e-05 loss: 0.0532 (0.0596) time: 2.8609 data: 0.0079 max mem: 33370 +Epoch: [16] [ 720/2639] eta: 1:32:39 lr: 3.1248639035527724e-05 loss: 0.0496 (0.0594) time: 2.9154 data: 0.0079 max mem: 33370 +Epoch: [16] [ 730/2639] eta: 1:32:10 lr: 3.1244147460071024e-05 loss: 0.0518 (0.0594) time: 2.9287 data: 0.0084 max mem: 33370 +Epoch: [16] [ 740/2639] eta: 1:31:43 lr: 3.123965581286908e-05 loss: 0.0518 (0.0594) time: 2.9471 data: 0.0086 max mem: 33370 +Epoch: [16] [ 750/2639] eta: 1:31:13 lr: 3.123516409390927e-05 loss: 0.0493 (0.0594) time: 2.9256 data: 0.0081 max mem: 33370 +Epoch: [16] [ 760/2639] eta: 1:30:44 lr: 3.123067230317901e-05 loss: 0.0513 (0.0596) time: 2.8629 data: 0.0081 max mem: 33370 +Epoch: [16] [ 770/2639] eta: 1:30:13 lr: 3.1226180440665646e-05 loss: 0.0571 (0.0597) time: 2.8562 data: 0.0082 max mem: 33370 +Epoch: [16] [ 780/2639] eta: 1:29:44 lr: 3.1221688506356574e-05 loss: 0.0656 (0.0598) time: 2.8659 data: 0.0082 max mem: 33370 +Epoch: [16] [ 790/2639] eta: 1:29:15 lr: 3.121719650023917e-05 loss: 0.0506 (0.0597) time: 2.8981 data: 0.0079 max mem: 33370 +Epoch: [16] [ 800/2639] eta: 1:28:46 lr: 3.1212704422300816e-05 loss: 0.0573 (0.0597) time: 2.9001 data: 0.0075 max mem: 33370 +Epoch: [16] [ 810/2639] eta: 1:28:18 lr: 3.1208212272528856e-05 loss: 0.0584 (0.0597) time: 2.8988 data: 0.0081 max mem: 33370 +Epoch: [16] [ 820/2639] eta: 1:27:47 lr: 3.120372005091067e-05 loss: 0.0543 (0.0597) time: 2.8710 data: 0.0082 max mem: 33370 +Epoch: [16] [ 830/2639] eta: 1:27:20 lr: 3.11992277574336e-05 loss: 0.0460 (0.0595) time: 2.9029 data: 0.0082 max mem: 33370 +Epoch: [16] [ 840/2639] eta: 1:26:51 lr: 3.1194735392085016e-05 loss: 0.0470 (0.0594) time: 2.9418 data: 0.0084 max mem: 33370 +Epoch: [16] [ 850/2639] eta: 1:26:22 lr: 3.119024295485226e-05 loss: 0.0472 (0.0593) time: 2.8966 data: 0.0084 max mem: 33370 +Epoch: [16] [ 860/2639] eta: 1:25:53 lr: 3.1185750445722674e-05 loss: 0.0488 (0.0593) time: 2.8906 data: 0.0087 max mem: 33370 +Epoch: [16] [ 870/2639] eta: 1:25:24 lr: 3.11812578646836e-05 loss: 0.0568 (0.0593) time: 2.8938 data: 0.0084 max mem: 33370 +Epoch: [16] [ 880/2639] eta: 1:24:56 lr: 3.1176765211722384e-05 loss: 0.0487 (0.0592) time: 2.9051 data: 0.0078 max mem: 33370 +Epoch: [16] [ 890/2639] eta: 1:24:29 lr: 3.1172272486826355e-05 loss: 0.0492 (0.0591) time: 2.9624 data: 0.0079 max mem: 33370 +Epoch: [16] [ 900/2639] eta: 1:23:59 lr: 3.1167779689982826e-05 loss: 0.0487 (0.0591) time: 2.9392 data: 0.0086 max mem: 33370 +Epoch: [16] [ 910/2639] eta: 1:23:30 lr: 3.116328682117914e-05 loss: 0.0499 (0.0591) time: 2.8805 data: 0.0087 max mem: 33370 +Epoch: [16] [ 920/2639] eta: 1:23:01 lr: 3.115879388040261e-05 loss: 0.0499 (0.0590) time: 2.8793 data: 0.0084 max mem: 33370 +Epoch: [16] [ 930/2639] eta: 1:22:33 lr: 3.115430086764055e-05 loss: 0.0489 (0.0589) time: 2.9286 data: 0.0083 max mem: 33370 +Epoch: [16] [ 940/2639] eta: 1:22:04 lr: 3.114980778288027e-05 loss: 0.0490 (0.0589) time: 2.9240 data: 0.0082 max mem: 33370 +Epoch: [16] [ 950/2639] eta: 1:21:34 lr: 3.114531462610908e-05 loss: 0.0524 (0.0590) time: 2.8786 data: 0.0081 max mem: 33370 +Epoch: [16] [ 960/2639] eta: 1:21:06 lr: 3.114082139731428e-05 loss: 0.0536 (0.0589) time: 2.9053 data: 0.0082 max mem: 33370 +Epoch: [16] [ 970/2639] eta: 1:20:37 lr: 3.113632809648318e-05 loss: 0.0538 (0.0590) time: 2.9226 data: 0.0082 max mem: 33370 +Epoch: [16] [ 980/2639] eta: 1:20:09 lr: 3.1131834723603054e-05 loss: 0.0541 (0.0591) time: 2.9222 data: 0.0082 max mem: 33370 +Epoch: [16] [ 990/2639] eta: 1:19:39 lr: 3.11273412786612e-05 loss: 0.0531 (0.0591) time: 2.8823 data: 0.0082 max mem: 33370 +Epoch: [16] [1000/2639] eta: 1:19:10 lr: 3.112284776164491e-05 loss: 0.0490 (0.0590) time: 2.8828 data: 0.0081 max mem: 33370 +Epoch: [16] [1010/2639] eta: 1:18:40 lr: 3.111835417254146e-05 loss: 0.0512 (0.0590) time: 2.8803 data: 0.0080 max mem: 33370 +Epoch: [16] [1020/2639] eta: 1:18:11 lr: 3.1113860511338135e-05 loss: 0.0541 (0.0590) time: 2.8637 data: 0.0076 max mem: 33370 +Epoch: [16] [1030/2639] eta: 1:17:42 lr: 3.110936677802219e-05 loss: 0.0552 (0.0590) time: 2.8963 data: 0.0076 max mem: 33370 +Epoch: [16] [1040/2639] eta: 1:17:12 lr: 3.110487297258091e-05 loss: 0.0529 (0.0592) time: 2.8739 data: 0.0076 max mem: 33370 +Epoch: [16] [1050/2639] eta: 1:16:42 lr: 3.110037909500155e-05 loss: 0.0580 (0.0593) time: 2.8277 data: 0.0079 max mem: 33370 +Epoch: [16] [1060/2639] eta: 1:16:13 lr: 3.1095885145271375e-05 loss: 0.0550 (0.0592) time: 2.8366 data: 0.0081 max mem: 33370 +Epoch: [16] [1070/2639] eta: 1:15:43 lr: 3.1091391123377634e-05 loss: 0.0481 (0.0592) time: 2.8558 data: 0.0080 max mem: 33370 +Epoch: [16] [1080/2639] eta: 1:15:14 lr: 3.108689702930758e-05 loss: 0.0481 (0.0592) time: 2.8636 data: 0.0079 max mem: 33370 +Epoch: [16] [1090/2639] eta: 1:14:45 lr: 3.108240286304847e-05 loss: 0.0550 (0.0592) time: 2.8862 data: 0.0079 max mem: 33370 +Epoch: [16] [1100/2639] eta: 1:14:17 lr: 3.107790862458753e-05 loss: 0.0557 (0.0593) time: 2.9282 data: 0.0080 max mem: 33370 +Epoch: [16] [1110/2639] eta: 1:13:48 lr: 3.107341431391201e-05 loss: 0.0563 (0.0594) time: 2.9235 data: 0.0083 max mem: 33370 +Epoch: [16] [1120/2639] eta: 1:13:18 lr: 3.106891993100914e-05 loss: 0.0551 (0.0593) time: 2.8796 data: 0.0081 max mem: 33370 +Epoch: [16] [1130/2639] eta: 1:12:48 lr: 3.106442547586615e-05 loss: 0.0497 (0.0592) time: 2.8378 data: 0.0075 max mem: 33370 +Epoch: [16] [1140/2639] eta: 1:12:20 lr: 3.105993094847027e-05 loss: 0.0535 (0.0595) time: 2.8611 data: 0.0076 max mem: 33370 +Epoch: [16] [1150/2639] eta: 1:11:50 lr: 3.1055436348808716e-05 loss: 0.0789 (0.0596) time: 2.8802 data: 0.0083 max mem: 33370 +Epoch: [16] [1160/2639] eta: 1:11:20 lr: 3.1050941676868694e-05 loss: 0.0600 (0.0596) time: 2.8488 data: 0.0086 max mem: 33370 +Epoch: [16] [1170/2639] eta: 1:10:51 lr: 3.104644693263744e-05 loss: 0.0562 (0.0596) time: 2.8647 data: 0.0081 max mem: 33370 +Epoch: [16] [1180/2639] eta: 1:10:22 lr: 3.104195211610215e-05 loss: 0.0571 (0.0597) time: 2.8616 data: 0.0077 max mem: 33370 +Epoch: [16] [1190/2639] eta: 1:09:53 lr: 3.103745722725002e-05 loss: 0.0571 (0.0597) time: 2.8664 data: 0.0076 max mem: 33370 +Epoch: [16] [1200/2639] eta: 1:09:24 lr: 3.103296226606826e-05 loss: 0.0532 (0.0597) time: 2.9077 data: 0.0076 max mem: 33370 +Epoch: [16] [1210/2639] eta: 1:08:55 lr: 3.1028467232544065e-05 loss: 0.0512 (0.0597) time: 2.9191 data: 0.0080 max mem: 33370 +Epoch: [16] [1220/2639] eta: 1:08:26 lr: 3.1023972126664626e-05 loss: 0.0592 (0.0596) time: 2.9003 data: 0.0084 max mem: 33370 +Epoch: [16] [1230/2639] eta: 1:07:58 lr: 3.1019476948417124e-05 loss: 0.0559 (0.0596) time: 2.9054 data: 0.0084 max mem: 33370 +Epoch: [16] [1240/2639] eta: 1:07:30 lr: 3.101498169778874e-05 loss: 0.0559 (0.0597) time: 2.9469 data: 0.0081 max mem: 33370 +Epoch: [16] [1250/2639] eta: 1:07:01 lr: 3.101048637476665e-05 loss: 0.0581 (0.0597) time: 2.9639 data: 0.0083 max mem: 33370 +Epoch: [16] [1260/2639] eta: 1:06:33 lr: 3.1005990979338044e-05 loss: 0.0565 (0.0597) time: 2.9538 data: 0.0081 max mem: 33370 +Epoch: [16] [1270/2639] eta: 1:06:05 lr: 3.100149551149008e-05 loss: 0.0459 (0.0597) time: 2.9596 data: 0.0076 max mem: 33370 +Epoch: [16] [1280/2639] eta: 1:05:36 lr: 3.0996999971209914e-05 loss: 0.0553 (0.0597) time: 2.9088 data: 0.0081 max mem: 33370 +Epoch: [16] [1290/2639] eta: 1:05:07 lr: 3.099250435848472e-05 loss: 0.0586 (0.0597) time: 2.8815 data: 0.0081 max mem: 33370 +Epoch: [16] [1300/2639] eta: 1:04:37 lr: 3.098800867330165e-05 loss: 0.0562 (0.0597) time: 2.8671 data: 0.0076 max mem: 33370 +Epoch: [16] [1310/2639] eta: 1:04:08 lr: 3.098351291564785e-05 loss: 0.0529 (0.0598) time: 2.8570 data: 0.0075 max mem: 33370 +Epoch: [16] [1320/2639] eta: 1:03:39 lr: 3.097901708551047e-05 loss: 0.0529 (0.0598) time: 2.8793 data: 0.0076 max mem: 33370 +Epoch: [16] [1330/2639] eta: 1:03:10 lr: 3.097452118287667e-05 loss: 0.0518 (0.0597) time: 2.9171 data: 0.0079 max mem: 33370 +Epoch: [16] [1340/2639] eta: 1:02:42 lr: 3.097002520773356e-05 loss: 0.0497 (0.0597) time: 2.9507 data: 0.0080 max mem: 33370 +Epoch: [16] [1350/2639] eta: 1:02:14 lr: 3.0965529160068295e-05 loss: 0.0530 (0.0597) time: 2.9530 data: 0.0082 max mem: 33370 +Epoch: [16] [1360/2639] eta: 1:01:45 lr: 3.096103303986799e-05 loss: 0.0507 (0.0596) time: 2.9370 data: 0.0082 max mem: 33370 +Epoch: [16] [1370/2639] eta: 1:01:16 lr: 3.095653684711979e-05 loss: 0.0501 (0.0597) time: 2.8984 data: 0.0079 max mem: 33370 +Epoch: [16] [1380/2639] eta: 1:00:47 lr: 3.09520405818108e-05 loss: 0.0612 (0.0597) time: 2.8862 data: 0.0080 max mem: 33370 +Epoch: [16] [1390/2639] eta: 1:00:17 lr: 3.0947544243928137e-05 loss: 0.0556 (0.0597) time: 2.8782 data: 0.0080 max mem: 33370 +Epoch: [16] [1400/2639] eta: 0:59:49 lr: 3.094304783345892e-05 loss: 0.0593 (0.0597) time: 2.9113 data: 0.0080 max mem: 33370 +Epoch: [16] [1410/2639] eta: 0:59:20 lr: 3.093855135039026e-05 loss: 0.0570 (0.0597) time: 2.9108 data: 0.0084 max mem: 33370 +Epoch: [16] [1420/2639] eta: 0:58:51 lr: 3.0934054794709256e-05 loss: 0.0545 (0.0598) time: 2.8873 data: 0.0083 max mem: 33370 +Epoch: [16] [1430/2639] eta: 0:58:22 lr: 3.0929558166403e-05 loss: 0.0509 (0.0597) time: 2.8817 data: 0.0081 max mem: 33370 +Epoch: [16] [1440/2639] eta: 0:57:53 lr: 3.0925061465458604e-05 loss: 0.0519 (0.0597) time: 2.8759 data: 0.0078 max mem: 33370 +Epoch: [16] [1450/2639] eta: 0:57:23 lr: 3.0920564691863143e-05 loss: 0.0492 (0.0597) time: 2.8707 data: 0.0078 max mem: 33370 +Epoch: [16] [1460/2639] eta: 0:56:54 lr: 3.091606784560371e-05 loss: 0.0602 (0.0598) time: 2.8800 data: 0.0084 max mem: 33370 +Epoch: [16] [1470/2639] eta: 0:56:25 lr: 3.091157092666739e-05 loss: 0.0602 (0.0598) time: 2.8827 data: 0.0083 max mem: 33370 +Epoch: [16] [1480/2639] eta: 0:55:56 lr: 3.090707393504125e-05 loss: 0.0473 (0.0598) time: 2.8546 data: 0.0078 max mem: 33370 +Epoch: [16] [1490/2639] eta: 0:55:26 lr: 3.0902576870712376e-05 loss: 0.0522 (0.0599) time: 2.8517 data: 0.0081 max mem: 33370 +Epoch: [16] [1500/2639] eta: 0:54:58 lr: 3.0898079733667824e-05 loss: 0.0618 (0.0599) time: 2.9021 data: 0.0089 max mem: 33370 +Epoch: [16] [1510/2639] eta: 0:54:29 lr: 3.089358252389467e-05 loss: 0.0535 (0.0599) time: 2.9254 data: 0.0082 max mem: 33370 +Epoch: [16] [1520/2639] eta: 0:54:01 lr: 3.088908524137997e-05 loss: 0.0489 (0.0599) time: 2.9424 data: 0.0079 max mem: 33370 +Epoch: [16] [1530/2639] eta: 0:53:32 lr: 3.0884587886110775e-05 loss: 0.0513 (0.0599) time: 2.9569 data: 0.0085 max mem: 33370 +Epoch: [16] [1540/2639] eta: 0:53:03 lr: 3.088009045807413e-05 loss: 0.0572 (0.0599) time: 2.9286 data: 0.0082 max mem: 33370 +Epoch: [16] [1550/2639] eta: 0:52:35 lr: 3.087559295725711e-05 loss: 0.0629 (0.0600) time: 2.9417 data: 0.0079 max mem: 33370 +Epoch: [16] [1560/2639] eta: 0:52:06 lr: 3.087109538364673e-05 loss: 0.0566 (0.0600) time: 2.9173 data: 0.0080 max mem: 33370 +Epoch: [16] [1570/2639] eta: 0:51:36 lr: 3.086659773723003e-05 loss: 0.0536 (0.0600) time: 2.8818 data: 0.0079 max mem: 33370 +Epoch: [16] [1580/2639] eta: 0:51:08 lr: 3.086210001799405e-05 loss: 0.0500 (0.0599) time: 2.8899 data: 0.0077 max mem: 33370 +Epoch: [16] [1590/2639] eta: 0:50:38 lr: 3.085760222592583e-05 loss: 0.0495 (0.0598) time: 2.8789 data: 0.0082 max mem: 33370 +Epoch: [16] [1600/2639] eta: 0:50:09 lr: 3.085310436101238e-05 loss: 0.0498 (0.0598) time: 2.8695 data: 0.0080 max mem: 33370 +Epoch: [16] [1610/2639] eta: 0:49:40 lr: 3.0848606423240725e-05 loss: 0.0499 (0.0597) time: 2.8691 data: 0.0079 max mem: 33370 +Epoch: [16] [1620/2639] eta: 0:49:11 lr: 3.0844108412597874e-05 loss: 0.0562 (0.0599) time: 2.8616 data: 0.0081 max mem: 33370 +Epoch: [16] [1630/2639] eta: 0:48:42 lr: 3.0839610329070846e-05 loss: 0.0562 (0.0599) time: 2.8932 data: 0.0080 max mem: 33370 +Epoch: [16] [1640/2639] eta: 0:48:14 lr: 3.0835112172646645e-05 loss: 0.0544 (0.0598) time: 2.9457 data: 0.0082 max mem: 33370 +Epoch: [16] [1650/2639] eta: 0:47:44 lr: 3.0830613943312273e-05 loss: 0.0550 (0.0599) time: 2.9076 data: 0.0085 max mem: 33370 +Epoch: [16] [1660/2639] eta: 0:47:15 lr: 3.082611564105473e-05 loss: 0.0557 (0.0599) time: 2.8665 data: 0.0084 max mem: 33370 +Epoch: [16] [1670/2639] eta: 0:46:46 lr: 3.082161726586101e-05 loss: 0.0522 (0.0598) time: 2.8825 data: 0.0081 max mem: 33370 +Epoch: [16] [1680/2639] eta: 0:46:17 lr: 3.08171188177181e-05 loss: 0.0546 (0.0599) time: 2.8709 data: 0.0079 max mem: 33370 +Epoch: [16] [1690/2639] eta: 0:45:48 lr: 3.0812620296613e-05 loss: 0.0576 (0.0598) time: 2.9084 data: 0.0080 max mem: 33370 +Epoch: [16] [1700/2639] eta: 0:45:20 lr: 3.080812170253266e-05 loss: 0.0471 (0.0598) time: 2.9347 data: 0.0082 max mem: 33370 +Epoch: [16] [1710/2639] eta: 0:44:50 lr: 3.080362303546408e-05 loss: 0.0492 (0.0598) time: 2.8891 data: 0.0082 max mem: 33370 +Epoch: [16] [1720/2639] eta: 0:44:21 lr: 3.079912429539423e-05 loss: 0.0557 (0.0598) time: 2.8586 data: 0.0082 max mem: 33370 +Epoch: [16] [1730/2639] eta: 0:43:52 lr: 3.079462548231007e-05 loss: 0.0585 (0.0599) time: 2.8787 data: 0.0080 max mem: 33370 +Epoch: [16] [1740/2639] eta: 0:43:23 lr: 3.079012659619856e-05 loss: 0.0648 (0.0599) time: 2.8733 data: 0.0079 max mem: 33370 +Epoch: [16] [1750/2639] eta: 0:42:54 lr: 3.078562763704666e-05 loss: 0.0573 (0.0599) time: 2.8929 data: 0.0080 max mem: 33370 +Epoch: [16] [1760/2639] eta: 0:42:26 lr: 3.078112860484133e-05 loss: 0.0447 (0.0599) time: 2.9706 data: 0.0080 max mem: 33370 +Epoch: [16] [1770/2639] eta: 0:41:57 lr: 3.077662949956952e-05 loss: 0.0510 (0.0599) time: 2.9596 data: 0.0080 max mem: 33370 +Epoch: [16] [1780/2639] eta: 0:41:28 lr: 3.077213032121817e-05 loss: 0.0531 (0.0599) time: 2.8872 data: 0.0081 max mem: 33370 +Epoch: [16] [1790/2639] eta: 0:40:59 lr: 3.076763106977421e-05 loss: 0.0594 (0.0599) time: 2.8568 data: 0.0085 max mem: 33370 +Epoch: [16] [1800/2639] eta: 0:40:30 lr: 3.0763131745224596e-05 loss: 0.0559 (0.0599) time: 2.8718 data: 0.0083 max mem: 33370 +Epoch: [16] [1810/2639] eta: 0:40:01 lr: 3.075863234755626e-05 loss: 0.0493 (0.0599) time: 2.8996 data: 0.0082 max mem: 33370 +Epoch: [16] [1820/2639] eta: 0:39:32 lr: 3.075413287675611e-05 loss: 0.0563 (0.0598) time: 2.9040 data: 0.0081 max mem: 33370 +Epoch: [16] [1830/2639] eta: 0:39:03 lr: 3.0749633332811074e-05 loss: 0.0403 (0.0597) time: 2.9034 data: 0.0080 max mem: 33370 +Epoch: [16] [1840/2639] eta: 0:38:34 lr: 3.074513371570808e-05 loss: 0.0403 (0.0598) time: 2.8721 data: 0.0083 max mem: 33370 +Epoch: [16] [1850/2639] eta: 0:38:05 lr: 3.074063402543404e-05 loss: 0.0468 (0.0598) time: 2.8542 data: 0.0085 max mem: 33370 +Epoch: [16] [1860/2639] eta: 0:37:35 lr: 3.073613426197585e-05 loss: 0.0494 (0.0597) time: 2.8547 data: 0.0082 max mem: 33370 +Epoch: [16] [1870/2639] eta: 0:37:07 lr: 3.0731634425320425e-05 loss: 0.0546 (0.0597) time: 2.8814 data: 0.0080 max mem: 33370 +Epoch: [16] [1880/2639] eta: 0:36:38 lr: 3.0727134515454675e-05 loss: 0.0523 (0.0597) time: 2.9310 data: 0.0083 max mem: 33370 +Epoch: [16] [1890/2639] eta: 0:36:09 lr: 3.072263453236548e-05 loss: 0.0523 (0.0597) time: 2.9008 data: 0.0085 max mem: 33370 +Epoch: [16] [1900/2639] eta: 0:35:40 lr: 3.071813447603973e-05 loss: 0.0511 (0.0598) time: 2.9132 data: 0.0083 max mem: 33370 +Epoch: [16] [1910/2639] eta: 0:35:11 lr: 3.071363434646432e-05 loss: 0.0478 (0.0597) time: 2.9025 data: 0.0082 max mem: 33370 +Epoch: [16] [1920/2639] eta: 0:34:42 lr: 3.070913414362614e-05 loss: 0.0554 (0.0599) time: 2.8877 data: 0.0080 max mem: 33370 +Epoch: [16] [1930/2639] eta: 0:34:13 lr: 3.070463386751205e-05 loss: 0.0731 (0.0600) time: 2.9025 data: 0.0079 max mem: 33370 +Epoch: [16] [1940/2639] eta: 0:33:44 lr: 3.070013351810894e-05 loss: 0.0665 (0.0599) time: 2.8738 data: 0.0082 max mem: 33370 +Epoch: [16] [1950/2639] eta: 0:33:15 lr: 3.0695633095403654e-05 loss: 0.0548 (0.0600) time: 2.9447 data: 0.0082 max mem: 33370 +Epoch: [16] [1960/2639] eta: 0:32:46 lr: 3.069113259938308e-05 loss: 0.0608 (0.0600) time: 2.9539 data: 0.0078 max mem: 33370 +Epoch: [16] [1970/2639] eta: 0:32:17 lr: 3.068663203003408e-05 loss: 0.0608 (0.0600) time: 2.8695 data: 0.0081 max mem: 33370 +Epoch: [16] [1980/2639] eta: 0:31:48 lr: 3.06821313873435e-05 loss: 0.0592 (0.0601) time: 2.8577 data: 0.0083 max mem: 33370 +Epoch: [16] [1990/2639] eta: 0:31:19 lr: 3.067763067129818e-05 loss: 0.0583 (0.0602) time: 2.8986 data: 0.0081 max mem: 33370 +Epoch: [16] [2000/2639] eta: 0:30:50 lr: 3.067312988188498e-05 loss: 0.0522 (0.0602) time: 2.9163 data: 0.0080 max mem: 33370 +Epoch: [16] [2010/2639] eta: 0:30:21 lr: 3.0668629019090746e-05 loss: 0.0496 (0.0602) time: 2.8852 data: 0.0077 max mem: 33370 +Epoch: [16] [2020/2639] eta: 0:29:52 lr: 3.0664128082902306e-05 loss: 0.0532 (0.0602) time: 2.8444 data: 0.0078 max mem: 33370 +Epoch: [16] [2030/2639] eta: 0:29:23 lr: 3.0659627073306494e-05 loss: 0.0648 (0.0603) time: 2.8181 data: 0.0079 max mem: 33370 +Epoch: [16] [2040/2639] eta: 0:28:54 lr: 3.065512599029014e-05 loss: 0.0630 (0.0603) time: 2.8567 data: 0.0078 max mem: 33370 +Epoch: [16] [2050/2639] eta: 0:28:25 lr: 3.065062483384007e-05 loss: 0.0579 (0.0603) time: 2.8853 data: 0.0078 max mem: 33370 +Epoch: [16] [2060/2639] eta: 0:27:56 lr: 3.06461236039431e-05 loss: 0.0596 (0.0603) time: 2.8884 data: 0.0081 max mem: 33370 +Epoch: [16] [2070/2639] eta: 0:27:27 lr: 3.064162230058605e-05 loss: 0.0559 (0.0603) time: 2.9237 data: 0.0082 max mem: 33370 +Epoch: [16] [2080/2639] eta: 0:26:58 lr: 3.0637120923755714e-05 loss: 0.0559 (0.0604) time: 2.9255 data: 0.0080 max mem: 33370 +Epoch: [16] [2090/2639] eta: 0:26:29 lr: 3.063261947343892e-05 loss: 0.0570 (0.0604) time: 2.8895 data: 0.0081 max mem: 33370 +Epoch: [16] [2100/2639] eta: 0:26:00 lr: 3.0628117949622466e-05 loss: 0.0451 (0.0603) time: 2.9079 data: 0.0082 max mem: 33370 +Epoch: [16] [2110/2639] eta: 0:25:31 lr: 3.0623616352293125e-05 loss: 0.0506 (0.0604) time: 2.8953 data: 0.0081 max mem: 33370 +Epoch: [16] [2120/2639] eta: 0:25:02 lr: 3.061911468143772e-05 loss: 0.0571 (0.0604) time: 2.8545 data: 0.0081 max mem: 33370 +Epoch: [16] [2130/2639] eta: 0:24:33 lr: 3.061461293704302e-05 loss: 0.0524 (0.0604) time: 2.8765 data: 0.0082 max mem: 33370 +Epoch: [16] [2140/2639] eta: 0:24:04 lr: 3.061011111909581e-05 loss: 0.0508 (0.0603) time: 2.8897 data: 0.0079 max mem: 33370 +Epoch: [16] [2150/2639] eta: 0:23:35 lr: 3.0605609227582874e-05 loss: 0.0484 (0.0603) time: 2.8849 data: 0.0077 max mem: 33370 +Epoch: [16] [2160/2639] eta: 0:23:06 lr: 3.060110726249098e-05 loss: 0.0490 (0.0603) time: 2.8709 data: 0.0079 max mem: 33370 +Epoch: [16] [2170/2639] eta: 0:22:37 lr: 3.05966052238069e-05 loss: 0.0519 (0.0604) time: 2.8750 data: 0.0079 max mem: 33370 +Epoch: [16] [2180/2639] eta: 0:22:08 lr: 3.059210311151741e-05 loss: 0.0545 (0.0603) time: 2.8669 data: 0.0076 max mem: 33370 +Epoch: [16] [2190/2639] eta: 0:21:39 lr: 3.058760092560926e-05 loss: 0.0545 (0.0604) time: 2.8707 data: 0.0081 max mem: 33370 +Epoch: [16] [2200/2639] eta: 0:21:10 lr: 3.05830986660692e-05 loss: 0.0527 (0.0604) time: 2.8837 data: 0.0081 max mem: 33370 +Epoch: [16] [2210/2639] eta: 0:20:41 lr: 3.0578596332883983e-05 loss: 0.0470 (0.0604) time: 2.8649 data: 0.0081 max mem: 33370 +Epoch: [16] [2220/2639] eta: 0:20:12 lr: 3.0574093926040376e-05 loss: 0.0477 (0.0604) time: 2.8644 data: 0.0083 max mem: 33370 +Epoch: [16] [2230/2639] eta: 0:19:43 lr: 3.0569591445525095e-05 loss: 0.0507 (0.0605) time: 2.8975 data: 0.0080 max mem: 33370 +Epoch: [16] [2240/2639] eta: 0:19:14 lr: 3.0565088891324887e-05 loss: 0.0543 (0.0605) time: 2.8822 data: 0.0080 max mem: 33370 +Epoch: [16] [2250/2639] eta: 0:18:46 lr: 3.056058626342649e-05 loss: 0.0571 (0.0605) time: 2.8797 data: 0.0077 max mem: 33370 +Epoch: [16] [2260/2639] eta: 0:18:16 lr: 3.0556083561816636e-05 loss: 0.0532 (0.0605) time: 2.8875 data: 0.0075 max mem: 33370 +Epoch: [16] [2270/2639] eta: 0:17:48 lr: 3.055158078648203e-05 loss: 0.0535 (0.0605) time: 2.8790 data: 0.0076 max mem: 33370 +Epoch: [16] [2280/2639] eta: 0:17:19 lr: 3.0547077937409406e-05 loss: 0.0523 (0.0605) time: 2.8796 data: 0.0078 max mem: 33370 +Epoch: [16] [2290/2639] eta: 0:16:50 lr: 3.054257501458548e-05 loss: 0.0499 (0.0605) time: 2.8946 data: 0.0083 max mem: 33370 +Epoch: [16] [2300/2639] eta: 0:16:21 lr: 3.053807201799696e-05 loss: 0.0590 (0.0605) time: 2.9325 data: 0.0082 max mem: 33370 +Epoch: [16] [2310/2639] eta: 0:15:52 lr: 3.0533568947630545e-05 loss: 0.0557 (0.0605) time: 2.9394 data: 0.0080 max mem: 33370 +Epoch: [16] [2320/2639] eta: 0:15:23 lr: 3.0529065803472946e-05 loss: 0.0476 (0.0605) time: 2.9309 data: 0.0086 max mem: 33370 +Epoch: [16] [2330/2639] eta: 0:14:54 lr: 3.052456258551085e-05 loss: 0.0559 (0.0605) time: 2.9349 data: 0.0083 max mem: 33370 +Epoch: [16] [2340/2639] eta: 0:14:25 lr: 3.052005929373096e-05 loss: 0.0559 (0.0605) time: 2.9370 data: 0.0074 max mem: 33370 +Epoch: [16] [2350/2639] eta: 0:13:56 lr: 3.051555592811996e-05 loss: 0.0558 (0.0605) time: 2.9028 data: 0.0079 max mem: 33370 +Epoch: [16] [2360/2639] eta: 0:13:27 lr: 3.051105248866452e-05 loss: 0.0528 (0.0605) time: 2.8983 data: 0.0080 max mem: 33370 +Epoch: [16] [2370/2639] eta: 0:12:58 lr: 3.050654897535133e-05 loss: 0.0515 (0.0605) time: 2.9478 data: 0.0080 max mem: 33370 +Epoch: [16] [2380/2639] eta: 0:12:29 lr: 3.0502045388167065e-05 loss: 0.0646 (0.0605) time: 2.9422 data: 0.0084 max mem: 33370 +Epoch: [16] [2390/2639] eta: 0:12:01 lr: 3.0497541727098394e-05 loss: 0.0628 (0.0606) time: 2.9096 data: 0.0088 max mem: 33370 +Epoch: [16] [2400/2639] eta: 0:11:32 lr: 3.0493037992131974e-05 loss: 0.0628 (0.0606) time: 2.9050 data: 0.0087 max mem: 33370 +Epoch: [16] [2410/2639] eta: 0:11:03 lr: 3.0488534183254468e-05 loss: 0.0589 (0.0606) time: 2.8968 data: 0.0080 max mem: 33370 +Epoch: [16] [2420/2639] eta: 0:10:34 lr: 3.048403030045253e-05 loss: 0.0558 (0.0606) time: 2.8888 data: 0.0078 max mem: 33370 +Epoch: [16] [2430/2639] eta: 0:10:05 lr: 3.0479526343712827e-05 loss: 0.0592 (0.0607) time: 2.8475 data: 0.0079 max mem: 33370 +Epoch: [16] [2440/2639] eta: 0:09:36 lr: 3.0475022313021983e-05 loss: 0.0592 (0.0607) time: 2.8420 data: 0.0080 max mem: 33370 +Epoch: [16] [2450/2639] eta: 0:09:07 lr: 3.0470518208366644e-05 loss: 0.0541 (0.0607) time: 2.8926 data: 0.0080 max mem: 33370 +Epoch: [16] [2460/2639] eta: 0:08:38 lr: 3.0466014029733453e-05 loss: 0.0515 (0.0607) time: 2.9715 data: 0.0082 max mem: 33370 +Epoch: [16] [2470/2639] eta: 0:08:09 lr: 3.0461509777109043e-05 loss: 0.0534 (0.0607) time: 2.9780 data: 0.0081 max mem: 33370 +Epoch: [16] [2480/2639] eta: 0:07:40 lr: 3.0457005450480043e-05 loss: 0.0572 (0.0607) time: 2.9330 data: 0.0078 max mem: 33370 +Epoch: [16] [2490/2639] eta: 0:07:11 lr: 3.045250104983306e-05 loss: 0.0529 (0.0607) time: 2.9448 data: 0.0077 max mem: 33370 +Epoch: [16] [2500/2639] eta: 0:06:42 lr: 3.0447996575154724e-05 loss: 0.0572 (0.0607) time: 2.9468 data: 0.0079 max mem: 33370 +Epoch: [16] [2510/2639] eta: 0:06:13 lr: 3.044349202643166e-05 loss: 0.0572 (0.0607) time: 2.8838 data: 0.0076 max mem: 33370 +Epoch: [16] [2520/2639] eta: 0:05:44 lr: 3.043898740365046e-05 loss: 0.0506 (0.0607) time: 2.8333 data: 0.0073 max mem: 33370 +Epoch: [16] [2530/2639] eta: 0:05:15 lr: 3.0434482706797727e-05 loss: 0.0470 (0.0607) time: 2.8960 data: 0.0078 max mem: 33370 +Epoch: [16] [2540/2639] eta: 0:04:46 lr: 3.0429977935860078e-05 loss: 0.0485 (0.0607) time: 2.9183 data: 0.0078 max mem: 33370 +Epoch: [16] [2550/2639] eta: 0:04:17 lr: 3.04254730908241e-05 loss: 0.0506 (0.0608) time: 2.8701 data: 0.0081 max mem: 33370 +Epoch: [16] [2560/2639] eta: 0:03:48 lr: 3.042096817167637e-05 loss: 0.0487 (0.0607) time: 2.8671 data: 0.0080 max mem: 33370 +Epoch: [16] [2570/2639] eta: 0:03:19 lr: 3.0416463178403497e-05 loss: 0.0513 (0.0607) time: 2.9130 data: 0.0074 max mem: 33370 +Epoch: [16] [2580/2639] eta: 0:02:50 lr: 3.0411958110992044e-05 loss: 0.0624 (0.0608) time: 2.9131 data: 0.0074 max mem: 33370 +Epoch: [16] [2590/2639] eta: 0:02:21 lr: 3.04074529694286e-05 loss: 0.0545 (0.0607) time: 2.8885 data: 0.0079 max mem: 33370 +Epoch: [16] [2600/2639] eta: 0:01:52 lr: 3.0402947753699734e-05 loss: 0.0529 (0.0608) time: 2.9190 data: 0.0081 max mem: 33370 +Epoch: [16] [2610/2639] eta: 0:01:24 lr: 3.0398442463792004e-05 loss: 0.0549 (0.0608) time: 2.9387 data: 0.0078 max mem: 33370 +Epoch: [16] [2620/2639] eta: 0:00:55 lr: 3.039393709969198e-05 loss: 0.0562 (0.0609) time: 2.9364 data: 0.0080 max mem: 33370 +Epoch: [16] [2630/2639] eta: 0:00:26 lr: 3.038943166138623e-05 loss: 0.0562 (0.0609) time: 2.9321 data: 0.0076 max mem: 33370 +Epoch: [16] Total time: 2:07:25 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 2:27:32 time: 3.4407 data: 3.3513 max mem: 33370 +Test: [ 100/2573] eta: 0:04:33 time: 0.0771 data: 0.0015 max mem: 33370 +Test: [ 200/2573] eta: 0:03:45 time: 0.0788 data: 0.0015 max mem: 33370 +Test: [ 300/2573] eta: 0:03:23 time: 0.0799 data: 0.0013 max mem: 33370 +Test: [ 400/2573] eta: 0:03:08 time: 0.0813 data: 0.0015 max mem: 33370 +Test: [ 500/2573] eta: 0:02:56 time: 0.0795 data: 0.0015 max mem: 33370 +Test: [ 600/2573] eta: 0:02:46 time: 0.0806 data: 0.0015 max mem: 33370 +Test: [ 700/2573] eta: 0:02:37 time: 0.0806 data: 0.0015 max mem: 33370 +Test: [ 800/2573] eta: 0:02:28 time: 0.0834 data: 0.0014 max mem: 33370 +Test: [ 900/2573] eta: 0:02:20 time: 0.0813 data: 0.0014 max mem: 33370 +Test: [1000/2573] eta: 0:02:11 time: 0.0814 data: 0.0016 max mem: 33370 +Test: [1100/2573] eta: 0:02:02 time: 0.0808 data: 0.0015 max mem: 33370 +Test: [1200/2573] eta: 0:01:54 time: 0.0805 data: 0.0014 max mem: 33370 +Test: [1300/2573] eta: 0:01:45 time: 0.0818 data: 0.0015 max mem: 33370 +Test: [1400/2573] eta: 0:01:37 time: 0.0788 data: 0.0014 max mem: 33370 +Test: [1500/2573] eta: 0:01:28 time: 0.0809 data: 0.0015 max mem: 33370 +Test: [1600/2573] eta: 0:01:20 time: 0.0849 data: 0.0014 max mem: 33370 +Test: [1700/2573] eta: 0:01:12 time: 0.0790 data: 0.0014 max mem: 33370 +Test: [1800/2573] eta: 0:01:03 time: 0.0823 data: 0.0015 max mem: 33370 +Test: [1900/2573] eta: 0:00:55 time: 0.0796 data: 0.0014 max mem: 33370 +Test: [2000/2573] eta: 0:00:47 time: 0.0812 data: 0.0014 max mem: 33370 +Test: [2100/2573] eta: 0:00:38 time: 0.0820 data: 0.0015 max mem: 33370 +Test: [2200/2573] eta: 0:00:30 time: 0.0817 data: 0.0014 max mem: 33370 +Test: [2300/2573] eta: 0:00:22 time: 0.0818 data: 0.0014 max mem: 33370 +Test: [2400/2573] eta: 0:00:14 time: 0.0769 data: 0.0014 max mem: 33370 +Test: [2500/2573] eta: 0:00:05 time: 0.0796 data: 0.0014 max mem: 33370 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: Total time: 0:03:31 +Final results: +Mean IoU is 60.73 + + precision@0.5 = 68.46 + precision@0.6 = 62.95 + precision@0.7 = 55.76 + precision@0.8 = 44.20 + precision@0.9 = 20.81 + overall IoU = 59.05 + +Average object IoU 60.73256453156765 +Overall IoU 59.04522705078125 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [17] [ 0/2639] eta: 4:00:40 lr: 3.038537670345404e-05 loss: 0.0338 (0.0338) time: 5.4721 data: 2.5116 max mem: 33370 +Epoch: [17] [ 10/2639] eta: 2:15:39 lr: 3.0380871124120335e-05 loss: 0.0487 (0.0497) time: 3.0960 data: 0.2354 max mem: 33370 +Epoch: [17] [ 20/2639] eta: 2:11:28 lr: 3.037636547054189e-05 loss: 0.0498 (0.0555) time: 2.8889 data: 0.0079 max mem: 33370 +Epoch: [17] [ 30/2639] eta: 2:10:04 lr: 3.037185974270525e-05 loss: 0.0579 (0.0574) time: 2.9339 data: 0.0081 max mem: 33370 +Epoch: [17] [ 40/2639] eta: 2:08:10 lr: 3.0367353940596933e-05 loss: 0.0506 (0.0555) time: 2.9034 data: 0.0079 max mem: 33370 +Epoch: [17] [ 50/2639] eta: 2:06:58 lr: 3.0362848064203476e-05 loss: 0.0496 (0.0565) time: 2.8669 data: 0.0079 max mem: 33370 +Epoch: [17] [ 60/2639] eta: 2:05:41 lr: 3.0358342113511412e-05 loss: 0.0517 (0.0553) time: 2.8532 data: 0.0082 max mem: 33370 +Epoch: [17] [ 70/2639] eta: 2:05:18 lr: 3.0353836088507265e-05 loss: 0.0485 (0.0574) time: 2.8856 data: 0.0082 max mem: 33370 +Epoch: [17] [ 80/2639] eta: 2:04:23 lr: 3.0349329989177538e-05 loss: 0.0539 (0.0572) time: 2.8924 data: 0.0080 max mem: 33370 +Epoch: [17] [ 90/2639] eta: 2:03:47 lr: 3.034482381550875e-05 loss: 0.0577 (0.0582) time: 2.8684 data: 0.0077 max mem: 33370 +Epoch: [17] [ 100/2639] eta: 2:03:06 lr: 3.0340317567487407e-05 loss: 0.0503 (0.0573) time: 2.8803 data: 0.0077 max mem: 33370 +Epoch: [17] [ 110/2639] eta: 2:02:40 lr: 3.033581124510002e-05 loss: 0.0477 (0.0578) time: 2.8949 data: 0.0077 max mem: 33370 +Epoch: [17] [ 120/2639] eta: 2:02:28 lr: 3.033130484833308e-05 loss: 0.0455 (0.0575) time: 2.9568 data: 0.0080 max mem: 33370 +Epoch: [17] [ 130/2639] eta: 2:02:02 lr: 3.0326798377173072e-05 loss: 0.0535 (0.0581) time: 2.9638 data: 0.0082 max mem: 33370 +Epoch: [17] [ 140/2639] eta: 2:01:39 lr: 3.0322291831606497e-05 loss: 0.0535 (0.0577) time: 2.9455 data: 0.0086 max mem: 33370 +Epoch: [17] [ 150/2639] eta: 2:01:19 lr: 3.0317785211619837e-05 loss: 0.0620 (0.0600) time: 2.9659 data: 0.0086 max mem: 33370 +Epoch: [17] [ 160/2639] eta: 2:00:56 lr: 3.031327851719957e-05 loss: 0.0634 (0.0597) time: 2.9682 data: 0.0084 max mem: 33370 +Epoch: [17] [ 170/2639] eta: 2:00:29 lr: 3.0308771748332166e-05 loss: 0.0607 (0.0602) time: 2.9534 data: 0.0085 max mem: 33370 +Epoch: [17] [ 180/2639] eta: 1:59:54 lr: 3.0304264905004098e-05 loss: 0.0547 (0.0599) time: 2.9157 data: 0.0081 max mem: 33370 +Epoch: [17] [ 190/2639] eta: 1:59:29 lr: 3.0299757987201833e-05 loss: 0.0466 (0.0597) time: 2.9218 data: 0.0079 max mem: 33370 +Epoch: [17] [ 200/2639] eta: 1:58:55 lr: 3.0295250994911833e-05 loss: 0.0552 (0.0603) time: 2.9231 data: 0.0079 max mem: 33370 +Epoch: [17] [ 210/2639] eta: 1:58:15 lr: 3.0290743928120545e-05 loss: 0.0532 (0.0597) time: 2.8607 data: 0.0079 max mem: 33370 +Epoch: [17] [ 220/2639] eta: 1:57:39 lr: 3.0286236786814427e-05 loss: 0.0532 (0.0606) time: 2.8488 data: 0.0079 max mem: 33370 +Epoch: [17] [ 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mem: 33370 +Epoch: [17] [1090/2639] eta: 1:14:59 lr: 2.989382869960906e-05 loss: 0.0526 (0.0582) time: 2.8381 data: 0.0083 max mem: 33370 +Epoch: [17] [1100/2639] eta: 1:14:30 lr: 2.9889314947381225e-05 loss: 0.0527 (0.0582) time: 2.8706 data: 0.0080 max mem: 33370 +Epoch: [17] [1110/2639] eta: 1:14:00 lr: 2.9884801119413568e-05 loss: 0.0557 (0.0583) time: 2.8607 data: 0.0078 max mem: 33370 +Epoch: [17] [1120/2639] eta: 1:13:29 lr: 2.9880287215692122e-05 loss: 0.0550 (0.0583) time: 2.7986 data: 0.0077 max mem: 33370 +Epoch: [17] [1130/2639] eta: 1:12:59 lr: 2.9875773236202875e-05 loss: 0.0484 (0.0582) time: 2.8082 data: 0.0080 max mem: 33370 +Epoch: [17] [1140/2639] eta: 1:12:30 lr: 2.987125918093186e-05 loss: 0.0491 (0.0583) time: 2.8669 data: 0.0083 max mem: 33370 +Epoch: [17] [1150/2639] eta: 1:12:01 lr: 2.986674504986507e-05 loss: 0.0575 (0.0583) time: 2.8862 data: 0.0084 max mem: 33370 +Epoch: [17] [1160/2639] eta: 1:11:32 lr: 2.98622308429885e-05 loss: 0.0580 (0.0583) time: 2.9052 data: 0.0081 max mem: 33370 +Epoch: [17] [1170/2639] eta: 1:11:03 lr: 2.985771656028814e-05 loss: 0.0576 (0.0582) time: 2.9035 data: 0.0079 max mem: 33370 +Epoch: [17] [1180/2639] eta: 1:10:34 lr: 2.985320220174999e-05 loss: 0.0499 (0.0583) time: 2.9145 data: 0.0080 max mem: 33370 +Epoch: [17] [1190/2639] eta: 1:10:05 lr: 2.9848687767360028e-05 loss: 0.0447 (0.0582) time: 2.9248 data: 0.0079 max mem: 33370 +Epoch: [17] [1200/2639] eta: 1:09:37 lr: 2.9844173257104235e-05 loss: 0.0513 (0.0582) time: 2.9414 data: 0.0079 max mem: 33370 +Epoch: [17] [1210/2639] eta: 1:09:08 lr: 2.9839658670968574e-05 loss: 0.0548 (0.0583) time: 2.9119 data: 0.0082 max mem: 33370 +Epoch: [17] [1220/2639] eta: 1:08:39 lr: 2.983514400893902e-05 loss: 0.0575 (0.0583) time: 2.8925 data: 0.0080 max mem: 33370 +Epoch: [17] [1230/2639] eta: 1:08:09 lr: 2.9830629271001535e-05 loss: 0.0490 (0.0582) time: 2.8874 data: 0.0078 max mem: 33370 +Epoch: [17] [1240/2639] eta: 1:07:41 lr: 2.982611445714209e-05 loss: 0.0490 (0.0582) time: 2.8852 data: 0.0079 max mem: 33370 +Epoch: [17] [1250/2639] eta: 1:07:13 lr: 2.982159956734662e-05 loss: 0.0582 (0.0582) time: 2.9724 data: 0.0077 max mem: 33370 +Epoch: [17] [1260/2639] eta: 1:06:44 lr: 2.9817084601601074e-05 loss: 0.0555 (0.0583) time: 2.9561 data: 0.0080 max mem: 33370 +Epoch: [17] [1270/2639] eta: 1:06:15 lr: 2.981256955989142e-05 loss: 0.0555 (0.0583) time: 2.9005 data: 0.0081 max mem: 33370 +Epoch: [17] [1280/2639] eta: 1:05:46 lr: 2.980805444220357e-05 loss: 0.0632 (0.0583) time: 2.9034 data: 0.0080 max mem: 33370 +Epoch: [17] [1290/2639] eta: 1:05:17 lr: 2.9803539248523465e-05 loss: 0.0510 (0.0582) time: 2.9344 data: 0.0081 max mem: 33370 +Epoch: [17] [1300/2639] eta: 1:04:48 lr: 2.979902397883703e-05 loss: 0.0520 (0.0584) time: 2.9216 data: 0.0079 max mem: 33370 +Epoch: [17] [1310/2639] eta: 1:04:19 lr: 2.9794508633130202e-05 loss: 0.0629 (0.0584) time: 2.8991 data: 0.0080 max mem: 33370 +Epoch: [17] [1320/2639] eta: 1:03:51 lr: 2.9789993211388895e-05 loss: 0.0453 (0.0583) time: 2.9513 data: 0.0084 max mem: 33370 +Epoch: [17] [1330/2639] eta: 1:03:21 lr: 2.978547771359902e-05 loss: 0.0460 (0.0583) time: 2.9151 data: 0.0082 max mem: 33370 +Epoch: [17] [1340/2639] eta: 1:02:52 lr: 2.978096213974648e-05 loss: 0.0533 (0.0582) time: 2.8840 data: 0.0081 max mem: 33370 +Epoch: [17] [1350/2639] eta: 1:02:23 lr: 2.9776446489817182e-05 loss: 0.0510 (0.0583) time: 2.9097 data: 0.0083 max mem: 33370 +Epoch: [17] [1360/2639] eta: 1:01:54 lr: 2.9771930763797036e-05 loss: 0.0412 (0.0584) time: 2.9124 data: 0.0082 max mem: 33370 +Epoch: [17] [1370/2639] eta: 1:01:25 lr: 2.9767414961671925e-05 loss: 0.0560 (0.0585) time: 2.9087 data: 0.0079 max mem: 33370 +Epoch: [17] [1380/2639] eta: 1:00:57 lr: 2.9762899083427738e-05 loss: 0.0578 (0.0585) time: 2.9239 data: 0.0080 max mem: 33370 +Epoch: [17] [1390/2639] eta: 1:00:27 lr: 2.9758383129050355e-05 loss: 0.0559 (0.0587) time: 2.8938 data: 0.0087 max mem: 33370 +Epoch: [17] 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33370 +Epoch: [17] [1480/2639] eta: 0:56:06 lr: 2.971773611132872e-05 loss: 0.0459 (0.0587) time: 2.8829 data: 0.0082 max mem: 33370 +Epoch: [17] [1490/2639] eta: 0:55:36 lr: 2.9713219394841946e-05 loss: 0.0459 (0.0586) time: 2.8412 data: 0.0080 max mem: 33370 +Epoch: [17] [1500/2639] eta: 0:55:07 lr: 2.9708702602066368e-05 loss: 0.0508 (0.0587) time: 2.8443 data: 0.0079 max mem: 33370 +Epoch: [17] [1510/2639] eta: 0:54:38 lr: 2.9704185732987816e-05 loss: 0.0572 (0.0587) time: 2.9044 data: 0.0078 max mem: 33370 +Epoch: [17] [1520/2639] eta: 0:54:09 lr: 2.969966878759211e-05 loss: 0.0547 (0.0587) time: 2.9477 data: 0.0078 max mem: 33370 +Epoch: [17] [1530/2639] eta: 0:53:40 lr: 2.9695151765865052e-05 loss: 0.0558 (0.0587) time: 2.9121 data: 0.0081 max mem: 33370 +Epoch: [17] [1540/2639] eta: 0:53:11 lr: 2.9690634667792468e-05 loss: 0.0598 (0.0587) time: 2.8877 data: 0.0084 max mem: 33370 +Epoch: [17] [1550/2639] eta: 0:52:42 lr: 2.968611749336015e-05 loss: 0.0595 (0.0588) time: 2.9006 data: 0.0083 max mem: 33370 +Epoch: [17] [1560/2639] eta: 0:52:13 lr: 2.9681600242553892e-05 loss: 0.0648 (0.0589) time: 2.8976 data: 0.0081 max mem: 33370 +Epoch: [17] [1570/2639] eta: 0:51:43 lr: 2.9677082915359505e-05 loss: 0.0612 (0.0589) time: 2.8860 data: 0.0081 max mem: 33370 +Epoch: [17] [1580/2639] eta: 0:51:14 lr: 2.9672565511762764e-05 loss: 0.0513 (0.0589) time: 2.8632 data: 0.0078 max mem: 33370 +Epoch: [17] [1590/2639] eta: 0:50:45 lr: 2.966804803174945e-05 loss: 0.0491 (0.0589) time: 2.8908 data: 0.0079 max mem: 33370 +Epoch: [17] [1600/2639] eta: 0:50:16 lr: 2.9663530475305346e-05 loss: 0.0517 (0.0590) time: 2.9298 data: 0.0080 max mem: 33370 +Epoch: [17] [1610/2639] eta: 0:49:47 lr: 2.9659012842416233e-05 loss: 0.0514 (0.0589) time: 2.8904 data: 0.0078 max mem: 33370 +Epoch: [17] [1620/2639] eta: 0:49:18 lr: 2.965449513306787e-05 loss: 0.0480 (0.0589) time: 2.8732 data: 0.0080 max mem: 33370 +Epoch: [17] [1630/2639] eta: 0:48:49 lr: 2.9649977347246015e-05 loss: 0.0539 (0.0589) time: 2.8829 data: 0.0080 max mem: 33370 +Epoch: [17] [1640/2639] eta: 0:48:20 lr: 2.964545948493644e-05 loss: 0.0555 (0.0588) time: 2.9012 data: 0.0079 max mem: 33370 +Epoch: [17] [1650/2639] eta: 0:47:51 lr: 2.964094154612489e-05 loss: 0.0425 (0.0588) time: 2.9147 data: 0.0082 max mem: 33370 +Epoch: [17] [1660/2639] eta: 0:47:22 lr: 2.9636423530797112e-05 loss: 0.0530 (0.0588) time: 2.9100 data: 0.0085 max mem: 33370 +Epoch: [17] [1670/2639] eta: 0:46:53 lr: 2.963190543893885e-05 loss: 0.0510 (0.0587) time: 2.9102 data: 0.0084 max mem: 33370 +Epoch: [17] [1680/2639] eta: 0:46:24 lr: 2.9627387270535843e-05 loss: 0.0463 (0.0587) time: 2.9093 data: 0.0080 max mem: 33370 +Epoch: [17] [1690/2639] eta: 0:45:55 lr: 2.9622869025573828e-05 loss: 0.0463 (0.0586) time: 2.9137 data: 0.0077 max mem: 33370 +Epoch: [17] [1700/2639] eta: 0:45:26 lr: 2.9618350704038523e-05 loss: 0.0479 (0.0587) time: 2.9013 data: 0.0081 max mem: 33370 +Epoch: [17] [1710/2639] eta: 0:44:56 lr: 2.9613832305915658e-05 loss: 0.0479 (0.0587) time: 2.8758 data: 0.0084 max mem: 33370 +Epoch: [17] [1720/2639] eta: 0:44:27 lr: 2.9609313831190938e-05 loss: 0.0470 (0.0587) time: 2.8592 data: 0.0082 max mem: 33370 +Epoch: [17] [1730/2639] eta: 0:43:58 lr: 2.9604795279850095e-05 loss: 0.0510 (0.0587) time: 2.8705 data: 0.0080 max mem: 33370 +Epoch: [17] [1740/2639] eta: 0:43:29 lr: 2.960027665187883e-05 loss: 0.0510 (0.0587) time: 2.8843 data: 0.0081 max mem: 33370 +Epoch: [17] [1750/2639] eta: 0:43:00 lr: 2.959575794726283e-05 loss: 0.0494 (0.0587) time: 2.8827 data: 0.0080 max mem: 33370 +Epoch: [17] [1760/2639] eta: 0:42:31 lr: 2.9591239165987804e-05 loss: 0.0512 (0.0587) time: 2.8790 data: 0.0079 max mem: 33370 +Epoch: [17] [1770/2639] eta: 0:42:02 lr: 2.9586720308039456e-05 loss: 0.0535 (0.0586) time: 2.8813 data: 0.0081 max mem: 33370 +Epoch: [17] [1780/2639] eta: 0:41:32 lr: 2.9582201373403452e-05 loss: 0.0550 (0.0586) time: 2.8856 data: 0.0079 max mem: 33370 +Epoch: [17] 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mem: 33370 +Epoch: [17] [1870/2639] eta: 0:37:12 lr: 2.95415275083711e-05 loss: 0.0540 (0.0589) time: 2.8825 data: 0.0082 max mem: 33370 +Epoch: [17] [1880/2639] eta: 0:36:43 lr: 2.9537007806070276e-05 loss: 0.0572 (0.0589) time: 2.8802 data: 0.0080 max mem: 33370 +Epoch: [17] [1890/2639] eta: 0:36:13 lr: 2.9532488026924022e-05 loss: 0.0498 (0.0588) time: 2.8732 data: 0.0083 max mem: 33370 +Epoch: [17] [1900/2639] eta: 0:35:44 lr: 2.9527968170917976e-05 loss: 0.0426 (0.0588) time: 2.8758 data: 0.0085 max mem: 33370 +Epoch: [17] [1910/2639] eta: 0:35:15 lr: 2.9523448238037736e-05 loss: 0.0445 (0.0588) time: 2.8941 data: 0.0081 max mem: 33370 +Epoch: [17] [1920/2639] eta: 0:34:46 lr: 2.951892822826893e-05 loss: 0.0491 (0.0588) time: 2.9252 data: 0.0078 max mem: 33370 +Epoch: [17] [1930/2639] eta: 0:34:18 lr: 2.9514408141597165e-05 loss: 0.0551 (0.0587) time: 2.9575 data: 0.0083 max mem: 33370 +Epoch: [17] [1940/2639] eta: 0:33:49 lr: 2.950988797800805e-05 loss: 0.0472 (0.0587) time: 2.9209 data: 0.0085 max mem: 33370 +Epoch: [17] [1950/2639] eta: 0:33:19 lr: 2.950536773748719e-05 loss: 0.0436 (0.0587) time: 2.8953 data: 0.0079 max mem: 33370 +Epoch: [17] [1960/2639] eta: 0:32:50 lr: 2.9500847420020154e-05 loss: 0.0474 (0.0587) time: 2.8752 data: 0.0080 max mem: 33370 +Epoch: [17] [1970/2639] eta: 0:32:21 lr: 2.9496327025592556e-05 loss: 0.0451 (0.0586) time: 2.8652 data: 0.0082 max mem: 33370 +Epoch: [17] [1980/2639] eta: 0:31:52 lr: 2.9491806554189982e-05 loss: 0.0471 (0.0586) time: 2.8897 data: 0.0080 max mem: 33370 +Epoch: [17] [1990/2639] eta: 0:31:23 lr: 2.9487286005797998e-05 loss: 0.0670 (0.0587) time: 2.9223 data: 0.0077 max mem: 33370 +Epoch: [17] [2000/2639] eta: 0:30:54 lr: 2.9482765380402177e-05 loss: 0.0563 (0.0587) time: 2.9099 data: 0.0078 max mem: 33370 +Epoch: [17] [2010/2639] eta: 0:30:25 lr: 2.9478244677988097e-05 loss: 0.0460 (0.0586) time: 2.8625 data: 0.0087 max mem: 33370 +Epoch: [17] [2020/2639] eta: 0:29:56 lr: 2.947372389854132e-05 loss: 0.0455 (0.0586) time: 2.9210 data: 0.0087 max mem: 33370 +Epoch: [17] [2030/2639] eta: 0:29:27 lr: 2.94692030420474e-05 loss: 0.0526 (0.0585) time: 2.9457 data: 0.0085 max mem: 33370 +Epoch: [17] [2040/2639] eta: 0:28:58 lr: 2.9464682108491897e-05 loss: 0.0557 (0.0585) time: 2.9106 data: 0.0082 max mem: 33370 +Epoch: [17] [2050/2639] eta: 0:28:29 lr: 2.9460161097860355e-05 loss: 0.0602 (0.0586) time: 2.8903 data: 0.0080 max mem: 33370 +Epoch: [17] [2060/2639] eta: 0:28:00 lr: 2.9455640010138313e-05 loss: 0.0506 (0.0585) time: 2.8791 data: 0.0078 max mem: 33370 +Epoch: [17] [2070/2639] eta: 0:27:31 lr: 2.945111884531132e-05 loss: 0.0466 (0.0585) time: 2.8859 data: 0.0079 max mem: 33370 +Epoch: [17] [2080/2639] eta: 0:27:02 lr: 2.94465976033649e-05 loss: 0.0499 (0.0585) time: 2.9045 data: 0.0081 max mem: 33370 +Epoch: [17] [2090/2639] eta: 0:26:33 lr: 2.944207628428458e-05 loss: 0.0499 (0.0585) time: 2.9091 data: 0.0079 max mem: 33370 +Epoch: [17] [2100/2639] eta: 0:26:04 lr: 2.9437554888055886e-05 loss: 0.0504 (0.0585) time: 2.8722 data: 0.0079 max mem: 33370 +Epoch: [17] [2110/2639] eta: 0:25:35 lr: 2.9433033414664333e-05 loss: 0.0543 (0.0585) time: 2.8689 data: 0.0078 max mem: 33370 +Epoch: [17] [2120/2639] eta: 0:25:06 lr: 2.9428511864095438e-05 loss: 0.0549 (0.0586) time: 2.8567 data: 0.0081 max mem: 33370 +Epoch: [17] [2130/2639] eta: 0:24:37 lr: 2.94239902363347e-05 loss: 0.0566 (0.0586) time: 2.8960 data: 0.0083 max mem: 33370 +Epoch: [17] [2140/2639] eta: 0:24:08 lr: 2.941946853136762e-05 loss: 0.0544 (0.0587) time: 2.9080 data: 0.0085 max mem: 33370 +Epoch: [17] [2150/2639] eta: 0:23:38 lr: 2.9414946749179704e-05 loss: 0.0527 (0.0587) time: 2.8777 data: 0.0084 max mem: 33370 +Epoch: [17] [2160/2639] eta: 0:23:09 lr: 2.9410424889756443e-05 loss: 0.0480 (0.0588) time: 2.8808 data: 0.0084 max mem: 33370 +Epoch: [17] [2170/2639] eta: 0:22:40 lr: 2.940590295308331e-05 loss: 0.0485 (0.0587) time: 2.8593 data: 0.0086 max mem: 33370 +Epoch: [17] [2180/2639] eta: 0:22:11 lr: 2.940138093914579e-05 loss: 0.0571 (0.0588) time: 2.8824 data: 0.0082 max mem: 33370 +Epoch: [17] [2190/2639] eta: 0:21:42 lr: 2.9396858847929364e-05 loss: 0.0541 (0.0588) time: 2.9011 data: 0.0078 max mem: 33370 +Epoch: [17] [2200/2639] eta: 0:21:13 lr: 2.9392336679419508e-05 loss: 0.0541 (0.0587) time: 2.9003 data: 0.0081 max mem: 33370 +Epoch: [17] [2210/2639] eta: 0:20:44 lr: 2.938781443360167e-05 loss: 0.0539 (0.0587) time: 2.8948 data: 0.0081 max mem: 33370 +Epoch: [17] [2220/2639] eta: 0:20:15 lr: 2.9383292110461318e-05 loss: 0.0539 (0.0587) time: 2.8693 data: 0.0081 max mem: 33370 +Epoch: [17] [2230/2639] eta: 0:19:46 lr: 2.937876970998391e-05 loss: 0.0542 (0.0588) time: 2.8870 data: 0.0078 max mem: 33370 +Epoch: [17] [2240/2639] eta: 0:19:17 lr: 2.93742472321549e-05 loss: 0.0587 (0.0588) time: 2.9137 data: 0.0075 max mem: 33370 +Epoch: [17] [2250/2639] eta: 0:18:48 lr: 2.9369724676959716e-05 loss: 0.0586 (0.0588) time: 2.9121 data: 0.0076 max mem: 33370 +Epoch: [17] [2260/2639] eta: 0:18:19 lr: 2.9365202044383805e-05 loss: 0.0590 (0.0588) time: 2.8973 data: 0.0075 max mem: 33370 +Epoch: [17] [2270/2639] eta: 0:17:50 lr: 2.9360679334412606e-05 loss: 0.0590 (0.0589) time: 2.9241 data: 0.0080 max mem: 33370 +Epoch: [17] [2280/2639] eta: 0:17:21 lr: 2.9356156547031545e-05 loss: 0.0631 (0.0590) time: 2.9161 data: 0.0083 max mem: 33370 +Epoch: [17] [2290/2639] eta: 0:16:52 lr: 2.9351633682226044e-05 loss: 0.0545 (0.0589) time: 2.8850 data: 0.0080 max mem: 33370 +Epoch: [17] [2300/2639] eta: 0:16:23 lr: 2.9347110739981515e-05 loss: 0.0576 (0.0590) time: 2.9143 data: 0.0080 max mem: 33370 +Epoch: [17] [2310/2639] eta: 0:15:54 lr: 2.9342587720283378e-05 loss: 0.0576 (0.0590) time: 2.9071 data: 0.0081 max mem: 33370 +Epoch: [17] [2320/2639] eta: 0:15:25 lr: 2.9338064623117044e-05 loss: 0.0533 (0.0591) time: 2.8996 data: 0.0082 max mem: 33370 +Epoch: [17] [2330/2639] eta: 0:14:56 lr: 2.9333541448467904e-05 loss: 0.0598 (0.0591) time: 2.9126 data: 0.0082 max mem: 33370 +Epoch: [17] [2340/2639] eta: 0:14:27 lr: 2.9329018196321362e-05 loss: 0.0517 (0.0591) time: 2.9070 data: 0.0078 max mem: 33370 +Epoch: [17] [2350/2639] eta: 0:13:58 lr: 2.932449486666281e-05 loss: 0.0495 (0.0591) time: 2.8794 data: 0.0083 max mem: 33370 +Epoch: [17] [2360/2639] eta: 0:13:29 lr: 2.9319971459477635e-05 loss: 0.0549 (0.0591) time: 2.8850 data: 0.0084 max mem: 33370 +Epoch: [17] [2370/2639] eta: 0:13:00 lr: 2.931544797475122e-05 loss: 0.0560 (0.0591) time: 2.9476 data: 0.0078 max mem: 33370 +Epoch: [17] [2380/2639] eta: 0:12:31 lr: 2.9310924412468928e-05 loss: 0.0551 (0.0591) time: 2.9455 data: 0.0077 max mem: 33370 +Epoch: [17] [2390/2639] eta: 0:12:02 lr: 2.9306400772616144e-05 loss: 0.0598 (0.0592) time: 2.9118 data: 0.0078 max mem: 33370 +Epoch: [17] [2400/2639] eta: 0:11:33 lr: 2.930187705517823e-05 loss: 0.0526 (0.0591) time: 2.9216 data: 0.0079 max mem: 33370 +Epoch: [17] [2410/2639] eta: 0:11:04 lr: 2.9297353260140542e-05 loss: 0.0467 (0.0591) time: 2.9048 data: 0.0076 max mem: 33370 +Epoch: [17] [2420/2639] eta: 0:10:35 lr: 2.929282938748844e-05 loss: 0.0549 (0.0591) time: 2.8935 data: 0.0076 max mem: 33370 +Epoch: [17] [2430/2639] eta: 0:10:06 lr: 2.9288305437207263e-05 loss: 0.0577 (0.0591) time: 2.8969 data: 0.0081 max mem: 33370 +Epoch: [17] [2440/2639] eta: 0:09:37 lr: 2.9283781409282373e-05 loss: 0.0543 (0.0592) time: 2.8783 data: 0.0081 max mem: 33370 +Epoch: [17] [2450/2639] eta: 0:09:08 lr: 2.9279257303699105e-05 loss: 0.0517 (0.0592) time: 2.8975 data: 0.0080 max mem: 33370 +Epoch: [17] [2460/2639] eta: 0:08:39 lr: 2.9274733120442776e-05 loss: 0.0625 (0.0592) time: 2.9026 data: 0.0080 max mem: 33370 +Epoch: [17] [2470/2639] eta: 0:08:10 lr: 2.9270208859498726e-05 loss: 0.0585 (0.0592) time: 2.8695 data: 0.0077 max mem: 33370 +Epoch: [17] [2480/2639] eta: 0:07:41 lr: 2.926568452085229e-05 loss: 0.0477 (0.0592) time: 2.8732 data: 0.0077 max mem: 33370 +Epoch: [17] [2490/2639] eta: 0:07:12 lr: 2.9261160104488766e-05 loss: 0.0484 (0.0591) time: 2.9300 data: 0.0077 max mem: 33370 +Epoch: [17] [2500/2639] eta: 0:06:43 lr: 2.925663561039347e-05 loss: 0.0396 (0.0591) time: 2.9541 data: 0.0076 max mem: 33370 +Epoch: [17] [2510/2639] eta: 0:06:14 lr: 2.9252111038551716e-05 loss: 0.0396 (0.0591) time: 2.9460 data: 0.0076 max mem: 33370 +Epoch: [17] [2520/2639] eta: 0:05:45 lr: 2.9247586388948804e-05 loss: 0.0454 (0.0591) time: 2.9660 data: 0.0076 max mem: 33370 +Epoch: [17] [2530/2639] eta: 0:05:16 lr: 2.9243061661570036e-05 loss: 0.0525 (0.0590) time: 2.9394 data: 0.0080 max mem: 33370 +Epoch: [17] [2540/2639] eta: 0:04:47 lr: 2.92385368564007e-05 loss: 0.0525 (0.0591) time: 2.9174 data: 0.0080 max mem: 33370 +Epoch: [17] [2550/2639] eta: 0:04:18 lr: 2.9234011973426067e-05 loss: 0.0490 (0.0590) time: 2.9256 data: 0.0081 max mem: 33370 +Epoch: [17] [2560/2639] eta: 0:03:49 lr: 2.922948701263144e-05 loss: 0.0484 (0.0590) time: 2.8979 data: 0.0081 max mem: 33370 +Epoch: [17] [2570/2639] eta: 0:03:20 lr: 2.9224961974002084e-05 loss: 0.0504 (0.0590) time: 2.9111 data: 0.0078 max mem: 33370 +Epoch: [17] [2580/2639] eta: 0:02:51 lr: 2.9220436857523275e-05 loss: 0.0521 (0.0590) time: 2.9278 data: 0.0077 max mem: 33370 +Epoch: [17] [2590/2639] eta: 0:02:22 lr: 2.9215911663180268e-05 loss: 0.0500 (0.0590) time: 2.9083 data: 0.0080 max mem: 33370 +Epoch: [17] [2600/2639] eta: 0:01:53 lr: 2.9211386390958324e-05 loss: 0.0500 (0.0590) time: 2.9001 data: 0.0081 max mem: 33370 +Epoch: [17] [2610/2639] eta: 0:01:24 lr: 2.9206861040842702e-05 loss: 0.0565 (0.0590) time: 2.8860 data: 0.0078 max mem: 33370 +Epoch: [17] [2620/2639] eta: 0:00:55 lr: 2.920233561281866e-05 loss: 0.0565 (0.0592) time: 2.8673 data: 0.0077 max mem: 33370 +Epoch: [17] [2630/2639] eta: 0:00:26 lr: 2.9197810106871422e-05 loss: 0.0496 (0.0592) time: 2.8585 data: 0.0075 max mem: 33370 +Epoch: [17] Total time: 2:07:39 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 2:16:55 time: 3.1928 data: 3.0725 max mem: 33370 +Test: [ 100/2573] eta: 0:04:29 time: 0.0774 data: 0.0014 max mem: 33370 +Test: [ 200/2573] eta: 0:03:44 time: 0.0796 data: 0.0015 max mem: 33370 +Test: [ 300/2573] eta: 0:03:22 time: 0.0807 data: 0.0015 max mem: 33370 +Test: [ 400/2573] eta: 0:03:08 time: 0.0815 data: 0.0014 max mem: 33370 +Test: [ 500/2573] eta: 0:02:57 time: 0.0813 data: 0.0014 max mem: 33370 +Test: [ 600/2573] eta: 0:02:47 time: 0.0811 data: 0.0015 max mem: 33370 +Test: [ 700/2573] eta: 0:02:38 time: 0.0804 data: 0.0015 max mem: 33370 +Test: [ 800/2573] eta: 0:02:29 time: 0.0839 data: 0.0014 max mem: 33370 +Test: [ 900/2573] eta: 0:02:20 time: 0.0803 data: 0.0015 max mem: 33370 +Test: [1000/2573] eta: 0:02:11 time: 0.0807 data: 0.0014 max mem: 33370 +Test: [1100/2573] eta: 0:02:02 time: 0.0811 data: 0.0016 max mem: 33370 +Test: [1200/2573] eta: 0:01:54 time: 0.0795 data: 0.0014 max mem: 33370 +Test: [1300/2573] eta: 0:01:45 time: 0.0808 data: 0.0014 max mem: 33370 +Test: [1400/2573] eta: 0:01:37 time: 0.0796 data: 0.0015 max mem: 33370 +Test: [1500/2573] eta: 0:01:28 time: 0.0814 data: 0.0016 max mem: 33370 +Test: [1600/2573] eta: 0:01:20 time: 0.0837 data: 0.0015 max mem: 33370 +Test: [1700/2573] eta: 0:01:11 time: 0.0789 data: 0.0014 max mem: 33370 +Test: [1800/2573] eta: 0:01:03 time: 0.0820 data: 0.0015 max mem: 33370 +Test: [1900/2573] eta: 0:00:55 time: 0.0788 data: 0.0015 max mem: 33370 +Test: [2000/2573] eta: 0:00:47 time: 0.0804 data: 0.0015 max mem: 33370 +Test: [2100/2573] eta: 0:00:38 time: 0.0830 data: 0.0014 max mem: 33370 +Test: [2200/2573] eta: 0:00:30 time: 0.0826 data: 0.0014 max mem: 33370 +Test: [2300/2573] eta: 0:00:22 time: 0.0818 data: 0.0014 max mem: 33370 +Test: [2400/2573] eta: 0:00:14 time: 0.0782 data: 0.0014 max mem: 33370 +Test: [2500/2573] eta: 0:00:05 time: 0.0803 data: 0.0016 max mem: 33370 +Test: Total time: 0:03:31 +Final results: +Mean IoU is 62.19 + + precision@0.5 = 69.89 + precision@0.6 = 64.11 + precision@0.7 = 57.13 + precision@0.8 = 44.75 + precision@0.9 = 21.65 + overall IoU = 59.39 + +Average object IoU 62.18683526828291 +Overall IoU 59.39411163330078 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [18] [ 0/2639] eta: 4:38:57 lr: 2.9193737084882377e-05 loss: 0.0318 (0.0318) time: 6.3423 data: 3.3800 max mem: 33370 +Epoch: [18] [ 10/2639] eta: 2:25:39 lr: 2.9189211430840417e-05 loss: 0.0433 (0.0456) time: 3.3244 data: 0.3149 max mem: 33370 +Epoch: [18] [ 20/2639] eta: 2:16:22 lr: 2.918468569883244e-05 loss: 0.0433 (0.0455) time: 2.9633 data: 0.0082 max mem: 33370 +Epoch: [18] [ 30/2639] eta: 2:12:29 lr: 2.9180159888843673e-05 loss: 0.0499 (0.0491) time: 2.8946 data: 0.0077 max mem: 33370 +Epoch: [18] [ 40/2639] eta: 2:11:14 lr: 2.9175634000859337e-05 loss: 0.0607 (0.0528) time: 2.9311 data: 0.0077 max mem: 33370 +Epoch: [18] [ 50/2639] eta: 2:10:05 lr: 2.9171108034864643e-05 loss: 0.0613 (0.0541) time: 2.9647 data: 0.0083 max mem: 33370 +Epoch: [18] [ 60/2639] eta: 2:09:14 lr: 2.9166581990844794e-05 loss: 0.0513 (0.0544) time: 2.9595 data: 0.0084 max mem: 33370 +Epoch: [18] [ 70/2639] eta: 2:08:06 lr: 2.9162055868784994e-05 loss: 0.0514 (0.0555) time: 2.9344 data: 0.0080 max mem: 33370 +Epoch: [18] [ 80/2639] eta: 2:07:09 lr: 2.9157529668670437e-05 loss: 0.0485 (0.0542) time: 2.9038 data: 0.0083 max mem: 33370 +Epoch: [18] [ 90/2639] eta: 2:06:06 lr: 2.915300339048632e-05 loss: 0.0448 (0.0538) time: 2.8840 data: 0.0086 max mem: 33370 +Epoch: [18] [ 100/2639] eta: 2:05:41 lr: 2.9148477034217818e-05 loss: 0.0429 (0.0536) time: 2.9241 data: 0.0082 max mem: 33370 +Epoch: [18] [ 110/2639] eta: 2:05:00 lr: 2.9143950599850116e-05 loss: 0.0436 (0.0532) time: 2.9533 data: 0.0080 max mem: 33370 +Epoch: [18] [ 120/2639] eta: 2:04:13 lr: 2.913942408736839e-05 loss: 0.0465 (0.0535) time: 2.9022 data: 0.0081 max mem: 33370 +Epoch: [18] [ 130/2639] eta: 2:03:30 lr: 2.9134897496757813e-05 loss: 0.0432 (0.0535) time: 2.8856 data: 0.0083 max mem: 33370 +Epoch: [18] [ 140/2639] eta: 2:02:59 lr: 2.9130370828003535e-05 loss: 0.0432 (0.0542) time: 2.9172 data: 0.0084 max mem: 33370 +Epoch: [18] [ 150/2639] eta: 2:02:35 lr: 2.9125844081090718e-05 loss: 0.0495 (0.0535) time: 2.9663 data: 0.0081 max mem: 33370 +Epoch: [18] [ 160/2639] eta: 2:02:07 lr: 2.9121317256004526e-05 loss: 0.0439 (0.0533) time: 2.9778 data: 0.0083 max mem: 33370 +Epoch: [18] [ 170/2639] eta: 2:01:36 lr: 2.91167903527301e-05 loss: 0.0411 (0.0534) time: 2.9557 data: 0.0081 max mem: 33370 +Epoch: [18] [ 180/2639] eta: 2:00:53 lr: 2.9112263371252584e-05 loss: 0.0396 (0.0530) time: 2.8987 data: 0.0079 max mem: 33370 +Epoch: [18] [ 190/2639] eta: 2:00:20 lr: 2.910773631155711e-05 loss: 0.0432 (0.0527) time: 2.8910 data: 0.0082 max mem: 33370 +Epoch: [18] [ 200/2639] eta: 1:59:43 lr: 2.9103209173628802e-05 loss: 0.0467 (0.0527) time: 2.9033 data: 0.0081 max mem: 33370 +Epoch: [18] [ 210/2639] eta: 1:59:06 lr: 2.909868195745281e-05 loss: 0.0467 (0.0531) time: 2.8806 data: 0.0079 max mem: 33370 +Epoch: [18] [ 220/2639] eta: 1:58:30 lr: 2.909415466301424e-05 loss: 0.0471 (0.0538) time: 2.8816 data: 0.0083 max mem: 33370 +Epoch: [18] [ 230/2639] eta: 1:57:55 lr: 2.90896272902982e-05 loss: 0.0437 (0.0537) time: 2.8851 data: 0.0084 max mem: 33370 +Epoch: [18] [ 240/2639] eta: 1:57:23 lr: 2.908509983928981e-05 loss: 0.0435 (0.0536) time: 2.9008 data: 0.0081 max mem: 33370 +Epoch: [18] [ 250/2639] eta: 1:56:48 lr: 2.9080572309974174e-05 loss: 0.0423 (0.0532) time: 2.8948 data: 0.0079 max mem: 33370 +Epoch: [18] [ 260/2639] eta: 1:56:20 lr: 2.9076044702336387e-05 loss: 0.0506 (0.0537) time: 2.9133 data: 0.0079 max mem: 33370 +Epoch: [18] [ 270/2639] eta: 1:55:54 lr: 2.9071517016361537e-05 loss: 0.0588 (0.0537) time: 2.9580 data: 0.0080 max mem: 33370 +Epoch: [18] [ 280/2639] eta: 1:55:22 lr: 2.9066989252034726e-05 loss: 0.0495 (0.0542) time: 2.9377 data: 0.0079 max mem: 33370 +Epoch: [18] [ 290/2639] eta: 1:54:55 lr: 2.906246140934103e-05 loss: 0.0477 (0.0541) time: 2.9359 data: 0.0079 max mem: 33370 +Epoch: [18] [ 300/2639] eta: 1:54:28 lr: 2.9057933488265527e-05 loss: 0.0477 (0.0541) time: 2.9608 data: 0.0081 max mem: 33370 +Epoch: [18] [ 310/2639] eta: 1:53:54 lr: 2.9053405488793284e-05 loss: 0.0421 (0.0538) time: 2.9188 data: 0.0084 max mem: 33370 +Epoch: [18] [ 320/2639] eta: 1:53:22 lr: 2.904887741090937e-05 loss: 0.0391 (0.0536) time: 2.8908 data: 0.0082 max mem: 33370 +Epoch: [18] [ 330/2639] eta: 1:52:54 lr: 2.9044349254598852e-05 loss: 0.0496 (0.0538) time: 2.9264 data: 0.0080 max mem: 33370 +Epoch: [18] [ 340/2639] eta: 1:52:23 lr: 2.903982101984678e-05 loss: 0.0443 (0.0534) time: 2.9301 data: 0.0078 max mem: 33370 +Epoch: [18] [ 350/2639] eta: 1:51:49 lr: 2.90352927066382e-05 loss: 0.0482 (0.0539) time: 2.8880 data: 0.0081 max mem: 33370 +Epoch: [18] [ 360/2639] eta: 1:51:15 lr: 2.9030764314958164e-05 loss: 0.0579 (0.0541) time: 2.8613 data: 0.0086 max mem: 33370 +Epoch: [18] [ 370/2639] eta: 1:50:42 lr: 2.902623584479171e-05 loss: 0.0443 (0.0538) time: 2.8588 data: 0.0085 max mem: 33370 +Epoch: [18] [ 380/2639] eta: 1:50:12 lr: 2.9021707296123873e-05 loss: 0.0403 (0.0536) time: 2.8865 data: 0.0085 max mem: 33370 +Epoch: [18] [ 390/2639] eta: 1:49:43 lr: 2.901717866893967e-05 loss: 0.0410 (0.0535) time: 2.9261 data: 0.0090 max mem: 33370 +Epoch: [18] [ 400/2639] eta: 1:49:12 lr: 2.9012649963224138e-05 loss: 0.0458 (0.0535) time: 2.9134 data: 0.0088 max mem: 33370 +Epoch: [18] [ 410/2639] eta: 1:48:40 lr: 2.900812117896228e-05 loss: 0.0458 (0.0534) time: 2.8817 data: 0.0083 max mem: 33370 +Epoch: [18] [ 420/2639] eta: 1:48:11 lr: 2.9003592316139126e-05 loss: 0.0461 (0.0533) time: 2.9029 data: 0.0080 max mem: 33370 +Epoch: [18] [ 430/2639] eta: 1:47:40 lr: 2.8999063374739675e-05 loss: 0.0445 (0.0532) time: 2.9148 data: 0.0077 max mem: 33370 +Epoch: [18] [ 440/2639] eta: 1:47:09 lr: 2.899453435474892e-05 loss: 0.0515 (0.0532) time: 2.8893 data: 0.0078 max mem: 33370 +Epoch: [18] [ 450/2639] eta: 1:46:35 lr: 2.8990005256151863e-05 loss: 0.0518 (0.0533) time: 2.8602 data: 0.0080 max mem: 33370 +Epoch: [18] [ 460/2639] eta: 1:46:04 lr: 2.89854760789335e-05 loss: 0.0515 (0.0536) time: 2.8538 data: 0.0081 max mem: 33370 +Epoch: [18] [ 470/2639] eta: 1:45:32 lr: 2.898094682307881e-05 loss: 0.0519 (0.0538) time: 2.8736 data: 0.0079 max mem: 33370 +Epoch: [18] [ 480/2639] eta: 1:45:02 lr: 2.897641748857276e-05 loss: 0.0545 (0.0539) time: 2.8866 data: 0.0078 max mem: 33370 +Epoch: [18] [ 490/2639] eta: 1:44:30 lr: 2.897188807540034e-05 loss: 0.0503 (0.0539) time: 2.8783 data: 0.0078 max mem: 33370 +Epoch: [18] [ 500/2639] eta: 1:44:00 lr: 2.8967358583546515e-05 loss: 0.0467 (0.0540) time: 2.8783 data: 0.0077 max mem: 33370 +Epoch: [18] [ 510/2639] eta: 1:43:30 lr: 2.896282901299625e-05 loss: 0.0526 (0.0541) time: 2.8950 data: 0.0079 max mem: 33370 +Epoch: [18] [ 520/2639] eta: 1:43:03 lr: 2.895829936373449e-05 loss: 0.0526 (0.0543) time: 2.9340 data: 0.0079 max mem: 33370 +Epoch: [18] [ 530/2639] eta: 1:42:31 lr: 2.8953769635746202e-05 loss: 0.0565 (0.0546) time: 2.9022 data: 0.0077 max mem: 33370 +Epoch: [18] [ 540/2639] eta: 1:42:00 lr: 2.8949239829016327e-05 loss: 0.0539 (0.0545) time: 2.8574 data: 0.0076 max mem: 33370 +Epoch: [18] [ 550/2639] eta: 1:41:30 lr: 2.8944709943529802e-05 loss: 0.0442 (0.0544) time: 2.8833 data: 0.0076 max mem: 33370 +Epoch: [18] [ 560/2639] eta: 1:40:59 lr: 2.894017997927156e-05 loss: 0.0450 (0.0544) time: 2.8771 data: 0.0080 max mem: 33370 +Epoch: [18] [ 570/2639] eta: 1:40:27 lr: 2.893564993622653e-05 loss: 0.0474 (0.0543) time: 2.8534 data: 0.0086 max mem: 33370 +Epoch: [18] [ 580/2639] eta: 1:39:56 lr: 2.8931119814379655e-05 loss: 0.0450 (0.0542) time: 2.8451 data: 0.0088 max mem: 33370 +Epoch: [18] [ 590/2639] eta: 1:39:26 lr: 2.8926589613715833e-05 loss: 0.0485 (0.0544) time: 2.8803 data: 0.0083 max mem: 33370 +Epoch: [18] [ 600/2639] eta: 1:39:02 lr: 2.892205933421998e-05 loss: 0.0517 (0.0545) time: 2.9746 data: 0.0079 max mem: 33370 +Epoch: [18] [ 610/2639] eta: 1:38:32 lr: 2.8917528975877005e-05 loss: 0.0511 (0.0545) time: 2.9681 data: 0.0079 max mem: 33370 +Epoch: [18] [ 620/2639] eta: 1:38:01 lr: 2.891299853867182e-05 loss: 0.0508 (0.0544) time: 2.8839 data: 0.0081 max mem: 33370 +Epoch: [18] [ 630/2639] eta: 1:37:31 lr: 2.890846802258932e-05 loss: 0.0541 (0.0546) time: 2.8781 data: 0.0080 max mem: 33370 +Epoch: [18] [ 640/2639] eta: 1:37:03 lr: 2.890393742761438e-05 loss: 0.0541 (0.0546) time: 2.9065 data: 0.0078 max mem: 33370 +Epoch: [18] [ 650/2639] eta: 1:36:33 lr: 2.8899406753731895e-05 loss: 0.0484 (0.0544) time: 2.9048 data: 0.0081 max mem: 33370 +Epoch: [18] [ 660/2639] eta: 1:36:02 lr: 2.8894876000926747e-05 loss: 0.0484 (0.0543) time: 2.8698 data: 0.0085 max mem: 33370 +Epoch: [18] [ 670/2639] eta: 1:35:32 lr: 2.8890345169183813e-05 loss: 0.0491 (0.0544) time: 2.8737 data: 0.0081 max mem: 33370 +Epoch: [18] [ 680/2639] eta: 1:35:02 lr: 2.8885814258487966e-05 loss: 0.0468 (0.0542) time: 2.8877 data: 0.0077 max mem: 33370 +Epoch: [18] [ 690/2639] eta: 1:34:31 lr: 2.888128326882405e-05 loss: 0.0493 (0.0545) time: 2.8672 data: 0.0080 max mem: 33370 +Epoch: [18] [ 700/2639] eta: 1:34:01 lr: 2.8876752200176938e-05 loss: 0.0503 (0.0544) time: 2.8484 data: 0.0081 max mem: 33370 +Epoch: [18] [ 710/2639] eta: 1:33:31 lr: 2.8872221052531478e-05 loss: 0.0503 (0.0544) time: 2.8700 data: 0.0082 max mem: 33370 +Epoch: [18] [ 720/2639] eta: 1:33:02 lr: 2.8867689825872524e-05 loss: 0.0505 (0.0544) time: 2.9007 data: 0.0083 max mem: 33370 +Epoch: [18] [ 730/2639] eta: 1:32:32 lr: 2.886315852018491e-05 loss: 0.0452 (0.0543) time: 2.8996 data: 0.0085 max mem: 33370 +Epoch: [18] [ 740/2639] eta: 1:32:04 lr: 2.8858627135453466e-05 loss: 0.0459 (0.0545) time: 2.9132 data: 0.0087 max mem: 33370 +Epoch: [18] [ 750/2639] eta: 1:31:35 lr: 2.885409567166304e-05 loss: 0.0459 (0.0545) time: 2.9199 data: 0.0086 max mem: 33370 +Epoch: [18] [ 760/2639] eta: 1:31:05 lr: 2.884956412879844e-05 loss: 0.0386 (0.0543) time: 2.8929 data: 0.0083 max mem: 33370 +Epoch: [18] [ 770/2639] eta: 1:30:36 lr: 2.884503250684449e-05 loss: 0.0381 (0.0542) time: 2.8976 data: 0.0084 max mem: 33370 +Epoch: [18] [ 780/2639] eta: 1:30:06 lr: 2.8840500805786003e-05 loss: 0.0407 (0.0542) time: 2.8869 data: 0.0086 max mem: 33370 +Epoch: [18] [ 790/2639] eta: 1:29:36 lr: 2.8835969025607796e-05 loss: 0.0521 (0.0541) time: 2.8803 data: 0.0084 max mem: 33370 +Epoch: [18] [ 800/2639] eta: 1:29:07 lr: 2.8831437166294656e-05 loss: 0.0521 (0.0542) time: 2.9057 data: 0.0081 max mem: 33370 +Epoch: [18] [ 810/2639] eta: 1:28:40 lr: 2.8826905227831392e-05 loss: 0.0518 (0.0542) time: 2.9521 data: 0.0083 max mem: 33370 +Epoch: [18] [ 820/2639] eta: 1:28:12 lr: 2.8822373210202786e-05 loss: 0.0475 (0.0541) time: 2.9624 data: 0.0087 max mem: 33370 +Epoch: [18] [ 830/2639] eta: 1:27:43 lr: 2.8817841113393628e-05 loss: 0.0459 (0.0541) time: 2.9276 data: 0.0086 max mem: 33370 +Epoch: [18] [ 840/2639] eta: 1:27:13 lr: 2.8813308937388706e-05 loss: 0.0466 (0.0541) time: 2.9078 data: 0.0088 max mem: 33370 +Epoch: [18] [ 850/2639] eta: 1:26:43 lr: 2.8808776682172782e-05 loss: 0.0491 (0.0543) time: 2.8674 data: 0.0084 max mem: 33370 +Epoch: [18] [ 860/2639] eta: 1:26:13 lr: 2.8804244347730625e-05 loss: 0.0575 (0.0544) time: 2.8540 data: 0.0077 max mem: 33370 +Epoch: [18] [ 870/2639] eta: 1:25:44 lr: 2.8799711934047007e-05 loss: 0.0532 (0.0544) time: 2.8895 data: 0.0084 max mem: 33370 +Epoch: [18] [ 880/2639] eta: 1:25:15 lr: 2.879517944110669e-05 loss: 0.0490 (0.0543) time: 2.9233 data: 0.0085 max mem: 33370 +Epoch: [18] [ 890/2639] eta: 1:24:47 lr: 2.8790646868894404e-05 loss: 0.0410 (0.0543) time: 2.9392 data: 0.0083 max mem: 33370 +Epoch: [18] [ 900/2639] eta: 1:24:18 lr: 2.878611421739491e-05 loss: 0.0429 (0.0542) time: 2.9181 data: 0.0086 max mem: 33370 +Epoch: [18] [ 910/2639] eta: 1:23:48 lr: 2.878158148659295e-05 loss: 0.0524 (0.0543) time: 2.8791 data: 0.0084 max mem: 33370 +Epoch: [18] [ 920/2639] eta: 1:23:19 lr: 2.8777048676473262e-05 loss: 0.0575 (0.0544) time: 2.8934 data: 0.0083 max mem: 33370 +Epoch: [18] [ 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mem: 33370 +Epoch: [18] [1010/2639] eta: 1:18:53 lr: 2.8736249813576598e-05 loss: 0.0460 (0.0545) time: 2.8582 data: 0.0080 max mem: 33370 +Epoch: [18] [1020/2639] eta: 1:18:24 lr: 2.8731716209438774e-05 loss: 0.0492 (0.0545) time: 2.8839 data: 0.0080 max mem: 33370 +Epoch: [18] [1030/2639] eta: 1:17:54 lr: 2.872718252581494e-05 loss: 0.0439 (0.0545) time: 2.8974 data: 0.0083 max mem: 33370 +Epoch: [18] [1040/2639] eta: 1:17:24 lr: 2.8722648762689763e-05 loss: 0.0439 (0.0545) time: 2.8423 data: 0.0082 max mem: 33370 +Epoch: [18] [1050/2639] eta: 1:16:54 lr: 2.8718114920047896e-05 loss: 0.0510 (0.0546) time: 2.8409 data: 0.0081 max mem: 33370 +Epoch: [18] [1060/2639] eta: 1:16:26 lr: 2.8713580997873995e-05 loss: 0.0538 (0.0548) time: 2.9052 data: 0.0086 max mem: 33370 +Epoch: [18] [1070/2639] eta: 1:15:57 lr: 2.870904699615271e-05 loss: 0.0489 (0.0548) time: 2.9282 data: 0.0086 max mem: 33370 +Epoch: [18] [1080/2639] eta: 1:15:27 lr: 2.8704512914868705e-05 loss: 0.0412 (0.0548) time: 2.8940 data: 0.0087 max mem: 33370 +Epoch: [18] [1090/2639] eta: 1:14:59 lr: 2.86999787540066e-05 loss: 0.0491 (0.0548) time: 2.8956 data: 0.0088 max mem: 33370 +Epoch: [18] [1100/2639] eta: 1:14:30 lr: 2.8695444513551028e-05 loss: 0.0547 (0.0549) time: 2.9313 data: 0.0089 max mem: 33370 +Epoch: [18] [1110/2639] eta: 1:14:00 lr: 2.8690910193486626e-05 loss: 0.0544 (0.0549) time: 2.9017 data: 0.0086 max mem: 33370 +Epoch: [18] [1120/2639] eta: 1:13:31 lr: 2.868637579379802e-05 loss: 0.0465 (0.0548) time: 2.8669 data: 0.0079 max mem: 33370 +Epoch: [18] [1130/2639] eta: 1:13:02 lr: 2.8681841314469814e-05 loss: 0.0465 (0.0548) time: 2.8900 data: 0.0080 max mem: 33370 +Epoch: [18] [1140/2639] eta: 1:12:34 lr: 2.8677306755486626e-05 loss: 0.0525 (0.0548) time: 2.9506 data: 0.0079 max mem: 33370 +Epoch: [18] [1150/2639] eta: 1:12:05 lr: 2.8672772116833065e-05 loss: 0.0525 (0.0547) time: 2.9315 data: 0.0080 max mem: 33370 +Epoch: [18] [1160/2639] eta: 1:11:35 lr: 2.866823739849372e-05 loss: 0.0426 (0.0547) time: 2.8837 data: 0.0085 max mem: 33370 +Epoch: [18] [1170/2639] eta: 1:11:06 lr: 2.8663702600453196e-05 loss: 0.0455 (0.0546) time: 2.9025 data: 0.0087 max mem: 33370 +Epoch: [18] [1180/2639] eta: 1:10:37 lr: 2.8659167722696084e-05 loss: 0.0499 (0.0546) time: 2.8997 data: 0.0085 max mem: 33370 +Epoch: [18] [1190/2639] eta: 1:10:08 lr: 2.865463276520695e-05 loss: 0.0475 (0.0546) time: 2.8793 data: 0.0080 max mem: 33370 +Epoch: [18] [1200/2639] eta: 1:09:38 lr: 2.865009772797038e-05 loss: 0.0464 (0.0549) time: 2.8517 data: 0.0078 max mem: 33370 +Epoch: [18] [1210/2639] eta: 1:09:09 lr: 2.8645562610970955e-05 loss: 0.0721 (0.0551) time: 2.8598 data: 0.0075 max mem: 33370 +Epoch: [18] [1220/2639] eta: 1:08:39 lr: 2.8641027414193232e-05 loss: 0.0669 (0.0551) time: 2.8927 data: 0.0074 max mem: 33370 +Epoch: [18] [1230/2639] eta: 1:08:11 lr: 2.8636492137621764e-05 loss: 0.0545 (0.0551) time: 2.9160 data: 0.0074 max mem: 33370 +Epoch: [18] [1240/2639] eta: 1:07:42 lr: 2.863195678124111e-05 loss: 0.0518 (0.0551) time: 2.9491 data: 0.0079 max mem: 33370 +Epoch: [18] [1250/2639] eta: 1:07:13 lr: 2.8627421345035832e-05 loss: 0.0519 (0.0553) time: 2.9222 data: 0.0085 max mem: 33370 +Epoch: [18] [1260/2639] eta: 1:06:43 lr: 2.8622885828990453e-05 loss: 0.0519 (0.0553) time: 2.8560 data: 0.0082 max mem: 33370 +Epoch: [18] [1270/2639] eta: 1:06:15 lr: 2.861835023308952e-05 loss: 0.0494 (0.0553) time: 2.8844 data: 0.0079 max mem: 33370 +Epoch: [18] [1280/2639] eta: 1:05:45 lr: 2.8613814557317557e-05 loss: 0.0444 (0.0552) time: 2.9011 data: 0.0079 max mem: 33370 +Epoch: [18] [1290/2639] eta: 1:05:16 lr: 2.8609278801659107e-05 loss: 0.0469 (0.0553) time: 2.8952 data: 0.0078 max mem: 33370 +Epoch: [18] [1300/2639] eta: 1:04:47 lr: 2.8604742966098674e-05 loss: 0.0529 (0.0553) time: 2.8931 data: 0.0080 max mem: 33370 +Epoch: [18] [1310/2639] eta: 1:04:18 lr: 2.860020705062077e-05 loss: 0.0501 (0.0553) time: 2.8926 data: 0.0078 max mem: 33370 +Epoch: [18] [1320/2639] eta: 1:03:48 lr: 2.859567105520991e-05 loss: 0.0463 (0.0553) time: 2.8747 data: 0.0077 max mem: 33370 +Epoch: [18] [1330/2639] eta: 1:03:19 lr: 2.8591134979850605e-05 loss: 0.0574 (0.0553) time: 2.8603 data: 0.0080 max mem: 33370 +Epoch: [18] [1340/2639] eta: 1:02:50 lr: 2.858659882452734e-05 loss: 0.0596 (0.0554) time: 2.8844 data: 0.0079 max mem: 33370 +Epoch: [18] [1350/2639] eta: 1:02:21 lr: 2.8582062589224607e-05 loss: 0.0540 (0.0554) time: 2.8839 data: 0.0078 max mem: 33370 +Epoch: [18] [1360/2639] eta: 1:01:52 lr: 2.857752627392689e-05 loss: 0.0494 (0.0554) time: 2.9078 data: 0.0077 max mem: 33370 +Epoch: [18] [1370/2639] eta: 1:01:23 lr: 2.8572989878618683e-05 loss: 0.0391 (0.0554) time: 2.9019 data: 0.0082 max mem: 33370 +Epoch: [18] [1380/2639] eta: 1:00:53 lr: 2.8568453403284445e-05 loss: 0.0391 (0.0554) time: 2.8709 data: 0.0084 max mem: 33370 +Epoch: [18] [1390/2639] eta: 1:00:24 lr: 2.8563916847908644e-05 loss: 0.0499 (0.0553) time: 2.8590 data: 0.0081 max mem: 33370 +Epoch: [18] [1400/2639] eta: 0:59:55 lr: 2.8559380212475757e-05 loss: 0.0505 (0.0553) time: 2.8683 data: 0.0080 max mem: 33370 +Epoch: [18] [1410/2639] eta: 0:59:26 lr: 2.855484349697022e-05 loss: 0.0493 (0.0553) time: 2.9027 data: 0.0077 max mem: 33370 +Epoch: [18] [1420/2639] eta: 0:58:57 lr: 2.8550306701376504e-05 loss: 0.0493 (0.0553) time: 2.9106 data: 0.0079 max mem: 33370 +Epoch: [18] [1430/2639] eta: 0:58:27 lr: 2.854576982567905e-05 loss: 0.0559 (0.0553) time: 2.8743 data: 0.0081 max mem: 33370 +Epoch: [18] [1440/2639] eta: 0:57:58 lr: 2.8541232869862282e-05 loss: 0.0527 (0.0553) time: 2.8704 data: 0.0078 max mem: 33370 +Epoch: [18] [1450/2639] eta: 0:57:29 lr: 2.8536695833910642e-05 loss: 0.0505 (0.0553) time: 2.8761 data: 0.0076 max mem: 33370 +Epoch: [18] [1460/2639] eta: 0:57:00 lr: 2.853215871780857e-05 loss: 0.0553 (0.0554) time: 2.9051 data: 0.0079 max mem: 33370 +Epoch: [18] [1470/2639] eta: 0:56:31 lr: 2.852762152154048e-05 loss: 0.0553 (0.0554) time: 2.9294 data: 0.0081 max mem: 33370 +Epoch: [18] [1480/2639] eta: 0:56:03 lr: 2.852308424509078e-05 loss: 0.0492 (0.0555) time: 2.9336 data: 0.0081 max mem: 33370 +Epoch: [18] [1490/2639] eta: 0:55:34 lr: 2.8518546888443887e-05 loss: 0.0448 (0.0554) time: 2.9354 data: 0.0080 max mem: 33370 +Epoch: [18] [1500/2639] eta: 0:55:05 lr: 2.851400945158421e-05 loss: 0.0468 (0.0554) time: 2.9483 data: 0.0078 max mem: 33370 +Epoch: [18] [1510/2639] eta: 0:54:37 lr: 2.8509471934496146e-05 loss: 0.0559 (0.0554) time: 2.9576 data: 0.0083 max mem: 33370 +Epoch: [18] [1520/2639] eta: 0:54:07 lr: 2.850493433716408e-05 loss: 0.0579 (0.0555) time: 2.8759 data: 0.0083 max mem: 33370 +Epoch: [18] [1530/2639] eta: 0:53:38 lr: 2.8500396659572404e-05 loss: 0.0558 (0.0555) time: 2.8467 data: 0.0083 max mem: 33370 +Epoch: [18] [1540/2639] eta: 0:53:08 lr: 2.8495858901705507e-05 loss: 0.0558 (0.0556) time: 2.8615 data: 0.0084 max mem: 33370 +Epoch: [18] [1550/2639] eta: 0:52:39 lr: 2.849132106354776e-05 loss: 0.0504 (0.0555) time: 2.8854 data: 0.0085 max mem: 33370 +Epoch: [18] [1560/2639] eta: 0:52:11 lr: 2.848678314508353e-05 loss: 0.0528 (0.0556) time: 2.9184 data: 0.0086 max mem: 33370 +Epoch: [18] [1570/2639] eta: 0:51:42 lr: 2.8482245146297175e-05 loss: 0.0472 (0.0555) time: 2.9254 data: 0.0085 max mem: 33370 +Epoch: [18] [1580/2639] eta: 0:51:13 lr: 2.847770706717307e-05 loss: 0.0457 (0.0555) time: 2.9469 data: 0.0082 max mem: 33370 +Epoch: [18] [1590/2639] eta: 0:50:45 lr: 2.8473168907695563e-05 loss: 0.0496 (0.0555) time: 2.9661 data: 0.0074 max mem: 33370 +Epoch: [18] [1600/2639] eta: 0:50:15 lr: 2.8468630667848985e-05 loss: 0.0563 (0.0556) time: 2.9257 data: 0.0075 max mem: 33370 +Epoch: [18] [1610/2639] eta: 0:49:46 lr: 2.8464092347617692e-05 loss: 0.0589 (0.0556) time: 2.8720 data: 0.0077 max mem: 33370 +Epoch: [18] [1620/2639] eta: 0:49:17 lr: 2.8459553946986016e-05 loss: 0.0566 (0.0556) time: 2.8808 data: 0.0081 max mem: 33370 +Epoch: [18] [1630/2639] eta: 0:48:48 lr: 2.8455015465938285e-05 loss: 0.0468 (0.0556) time: 2.9082 data: 0.0083 max mem: 33370 +Epoch: [18] [1640/2639] eta: 0:48:19 lr: 2.845047690445883e-05 loss: 0.0416 (0.0556) time: 2.9104 data: 0.0077 max mem: 33370 +Epoch: [18] [1650/2639] eta: 0:47:50 lr: 2.8445938262531952e-05 loss: 0.0519 (0.0556) time: 2.8797 data: 0.0072 max mem: 33370 +Epoch: [18] [1660/2639] eta: 0:47:21 lr: 2.8441399540141973e-05 loss: 0.0519 (0.0555) time: 2.8758 data: 0.0077 max mem: 33370 +Epoch: [18] [1670/2639] eta: 0:46:52 lr: 2.84368607372732e-05 loss: 0.0490 (0.0556) time: 2.8872 data: 0.0081 max mem: 33370 +Epoch: [18] [1680/2639] eta: 0:46:22 lr: 2.8432321853909936e-05 loss: 0.0446 (0.0555) time: 2.8614 data: 0.0080 max mem: 33370 +Epoch: [18] [1690/2639] eta: 0:45:53 lr: 2.8427782890036464e-05 loss: 0.0441 (0.0555) time: 2.8510 data: 0.0080 max mem: 33370 +Epoch: [18] [1700/2639] eta: 0:45:24 lr: 2.8423243845637078e-05 loss: 0.0514 (0.0555) time: 2.8943 data: 0.0079 max mem: 33370 +Epoch: [18] [1710/2639] eta: 0:44:55 lr: 2.8418704720696066e-05 loss: 0.0507 (0.0556) time: 2.9104 data: 0.0079 max mem: 33370 +Epoch: [18] [1720/2639] eta: 0:44:26 lr: 2.8414165515197698e-05 loss: 0.0528 (0.0555) time: 2.9110 data: 0.0083 max mem: 33370 +Epoch: [18] [1730/2639] eta: 0:43:57 lr: 2.8409626229126245e-05 loss: 0.0401 (0.0555) time: 2.9298 data: 0.0084 max mem: 33370 +Epoch: [18] [1740/2639] eta: 0:43:29 lr: 2.8405086862465974e-05 loss: 0.0505 (0.0555) time: 2.9393 data: 0.0083 max mem: 33370 +Epoch: [18] [1750/2639] eta: 0:43:00 lr: 2.8400547415201147e-05 loss: 0.0521 (0.0555) time: 2.9310 data: 0.0086 max mem: 33370 +Epoch: [18] [1760/2639] eta: 0:42:31 lr: 2.839600788731601e-05 loss: 0.0500 (0.0555) time: 2.9144 data: 0.0082 max mem: 33370 +Epoch: [18] [1770/2639] eta: 0:42:02 lr: 2.8391468278794813e-05 loss: 0.0534 (0.0556) time: 2.9140 data: 0.0084 max mem: 33370 +Epoch: [18] [1780/2639] eta: 0:41:32 lr: 2.8386928589621797e-05 loss: 0.0559 (0.0556) time: 2.8937 data: 0.0086 max mem: 33370 +Epoch: [18] [1790/2639] eta: 0:41:03 lr: 2.8382388819781202e-05 loss: 0.0474 (0.0557) time: 2.8842 data: 0.0079 max mem: 33370 +Epoch: [18] [1800/2639] eta: 0:40:34 lr: 2.8377848969257253e-05 loss: 0.0481 (0.0557) time: 2.8775 data: 0.0080 max mem: 33370 +Epoch: [18] [1810/2639] eta: 0:40:05 lr: 2.8373309038034174e-05 loss: 0.0534 (0.0556) time: 2.8743 data: 0.0081 max mem: 33370 +Epoch: [18] [1820/2639] eta: 0:39:36 lr: 2.836876902609618e-05 loss: 0.0550 (0.0557) time: 2.8751 data: 0.0082 max mem: 33370 +Epoch: [18] [1830/2639] eta: 0:39:07 lr: 2.8364228933427494e-05 loss: 0.0435 (0.0557) time: 2.8601 data: 0.0081 max mem: 33370 +Epoch: [18] [1840/2639] eta: 0:38:38 lr: 2.8359688760012322e-05 loss: 0.0433 (0.0557) time: 2.8672 data: 0.0076 max mem: 33370 +Epoch: [18] [1850/2639] eta: 0:38:09 lr: 2.835514850583484e-05 loss: 0.0537 (0.0557) time: 2.8835 data: 0.0073 max mem: 33370 +Epoch: [18] [1860/2639] eta: 0:37:39 lr: 2.8350608170879266e-05 loss: 0.0513 (0.0557) time: 2.8816 data: 0.0075 max mem: 33370 +Epoch: [18] [1870/2639] eta: 0:37:10 lr: 2.8346067755129784e-05 loss: 0.0513 (0.0557) time: 2.8887 data: 0.0079 max mem: 33370 +Epoch: [18] [1880/2639] eta: 0:36:41 lr: 2.834152725857057e-05 loss: 0.0444 (0.0557) time: 2.8750 data: 0.0077 max mem: 33370 +Epoch: [18] [1890/2639] eta: 0:36:12 lr: 2.8336986681185812e-05 loss: 0.0418 (0.0556) time: 2.8518 data: 0.0073 max mem: 33370 +Epoch: [18] [1900/2639] eta: 0:35:43 lr: 2.8332446022959664e-05 loss: 0.0563 (0.0557) time: 2.8579 data: 0.0074 max mem: 33370 +Epoch: [18] [1910/2639] eta: 0:35:14 lr: 2.8327905283876306e-05 loss: 0.0582 (0.0557) time: 2.8629 data: 0.0074 max mem: 33370 +Epoch: [18] [1920/2639] eta: 0:34:45 lr: 2.832336446391989e-05 loss: 0.0472 (0.0557) time: 2.9084 data: 0.0077 max mem: 33370 +Epoch: [18] [1930/2639] eta: 0:34:16 lr: 2.831882356307457e-05 loss: 0.0506 (0.0557) time: 2.9300 data: 0.0077 max mem: 33370 +Epoch: [18] [1940/2639] eta: 0:33:47 lr: 2.831428258132449e-05 loss: 0.0492 (0.0557) time: 2.8784 data: 0.0074 max mem: 33370 +Epoch: [18] [1950/2639] eta: 0:33:17 lr: 2.8309741518653794e-05 loss: 0.0470 (0.0557) time: 2.8359 data: 0.0077 max mem: 33370 +Epoch: [18] [1960/2639] eta: 0:32:48 lr: 2.830520037504662e-05 loss: 0.0450 (0.0557) time: 2.8065 data: 0.0082 max mem: 33370 +Epoch: [18] [1970/2639] eta: 0:32:19 lr: 2.830065915048709e-05 loss: 0.0505 (0.0558) time: 2.8055 data: 0.0079 max mem: 33370 +Epoch: [18] [1980/2639] eta: 0:31:50 lr: 2.829611784495933e-05 loss: 0.0534 (0.0558) time: 2.8464 data: 0.0074 max mem: 33370 +Epoch: [18] [1990/2639] eta: 0:31:21 lr: 2.829157645844746e-05 loss: 0.0524 (0.0557) time: 2.8643 data: 0.0074 max mem: 33370 +Epoch: [18] [2000/2639] eta: 0:30:51 lr: 2.828703499093559e-05 loss: 0.0467 (0.0557) time: 2.8585 data: 0.0073 max mem: 33370 +Epoch: [18] [2010/2639] eta: 0:30:22 lr: 2.8282493442407826e-05 loss: 0.0427 (0.0556) time: 2.8541 data: 0.0077 max mem: 33370 +Epoch: [18] [2020/2639] eta: 0:29:53 lr: 2.8277951812848265e-05 loss: 0.0519 (0.0557) time: 2.8736 data: 0.0083 max mem: 33370 +Epoch: [18] [2030/2639] eta: 0:29:24 lr: 2.8273410102241e-05 loss: 0.0564 (0.0557) time: 2.8934 data: 0.0083 max mem: 33370 +Epoch: [18] [2040/2639] eta: 0:28:55 lr: 2.8268868310570118e-05 loss: 0.0535 (0.0557) time: 2.8962 data: 0.0083 max mem: 33370 +Epoch: [18] [2050/2639] eta: 0:28:26 lr: 2.826432643781971e-05 loss: 0.0632 (0.0558) time: 2.8947 data: 0.0083 max mem: 33370 +Epoch: [18] [2060/2639] eta: 0:27:57 lr: 2.8259784483973833e-05 loss: 0.0465 (0.0558) time: 2.8766 data: 0.0080 max mem: 33370 +Epoch: [18] [2070/2639] eta: 0:27:28 lr: 2.825524244901657e-05 loss: 0.0473 (0.0557) time: 2.8580 data: 0.0078 max mem: 33370 +Epoch: [18] [2080/2639] eta: 0:26:59 lr: 2.825070033293199e-05 loss: 0.0544 (0.0559) time: 2.8625 data: 0.0077 max mem: 33370 +Epoch: [18] [2090/2639] eta: 0:26:30 lr: 2.8246158135704144e-05 loss: 0.0429 (0.0558) time: 2.8706 data: 0.0076 max mem: 33370 +Epoch: [18] [2100/2639] eta: 0:26:01 lr: 2.824161585731707e-05 loss: 0.0437 (0.0558) time: 2.8962 data: 0.0078 max mem: 33370 +Epoch: [18] [2110/2639] eta: 0:25:32 lr: 2.823707349775483e-05 loss: 0.0480 (0.0558) time: 2.9051 data: 0.0078 max mem: 33370 +Epoch: [18] [2120/2639] eta: 0:25:03 lr: 2.8232531057001464e-05 loss: 0.0516 (0.0558) time: 2.8781 data: 0.0075 max mem: 33370 +Epoch: [18] [2130/2639] eta: 0:24:34 lr: 2.8227988535040994e-05 loss: 0.0551 (0.0559) time: 2.8447 data: 0.0077 max mem: 33370 +Epoch: [18] [2140/2639] eta: 0:24:05 lr: 2.822344593185746e-05 loss: 0.0501 (0.0559) time: 2.8035 data: 0.0079 max mem: 33370 +Epoch: [18] [2150/2639] eta: 0:23:36 lr: 2.8218903247434875e-05 loss: 0.0497 (0.0558) time: 2.8072 data: 0.0077 max mem: 33370 +Epoch: [18] [2160/2639] eta: 0:23:07 lr: 2.8214360481757256e-05 loss: 0.0510 (0.0559) time: 2.8360 data: 0.0074 max mem: 33370 +Epoch: [18] [2170/2639] eta: 0:22:38 lr: 2.8209817634808628e-05 loss: 0.0551 (0.0559) time: 2.8671 data: 0.0076 max mem: 33370 +Epoch: [18] [2180/2639] eta: 0:22:09 lr: 2.820527470657297e-05 loss: 0.0493 (0.0559) time: 2.8811 data: 0.0076 max mem: 33370 +Epoch: [18] [2190/2639] eta: 0:21:40 lr: 2.8200731697034292e-05 loss: 0.0460 (0.0559) time: 2.8603 data: 0.0075 max mem: 33370 +Epoch: [18] [2200/2639] eta: 0:21:11 lr: 2.819618860617658e-05 loss: 0.0519 (0.0559) time: 2.8632 data: 0.0077 max mem: 33370 +Epoch: [18] [2210/2639] eta: 0:20:42 lr: 2.819164543398383e-05 loss: 0.0519 (0.0559) time: 2.8977 data: 0.0077 max mem: 33370 +Epoch: [18] [2220/2639] eta: 0:20:13 lr: 2.8187102180440022e-05 loss: 0.0439 (0.0559) time: 2.9011 data: 0.0075 max mem: 33370 +Epoch: [18] [2230/2639] eta: 0:19:44 lr: 2.818255884552911e-05 loss: 0.0559 (0.0559) time: 2.9122 data: 0.0076 max mem: 33370 +Epoch: [18] [2240/2639] eta: 0:19:15 lr: 2.8178015429235082e-05 loss: 0.0564 (0.0559) time: 2.9284 data: 0.0079 max mem: 33370 +Epoch: [18] [2250/2639] eta: 0:18:46 lr: 2.8173471931541897e-05 loss: 0.0499 (0.0559) time: 2.9006 data: 0.0077 max mem: 33370 +Epoch: [18] [2260/2639] eta: 0:18:17 lr: 2.81689283524335e-05 loss: 0.0538 (0.0560) time: 2.8738 data: 0.0074 max mem: 33370 +Epoch: [18] [2270/2639] eta: 0:17:48 lr: 2.8164384691893842e-05 loss: 0.0435 (0.0559) time: 2.8642 data: 0.0074 max mem: 33370 +Epoch: [18] [2280/2639] eta: 0:17:19 lr: 2.8159840949906868e-05 loss: 0.0397 (0.0559) time: 2.8772 data: 0.0075 max mem: 33370 +Epoch: [18] [2290/2639] eta: 0:16:50 lr: 2.8155297126456527e-05 loss: 0.0500 (0.0559) time: 2.8532 data: 0.0075 max mem: 33370 +Epoch: [18] [2300/2639] eta: 0:16:21 lr: 2.8150753221526742e-05 loss: 0.0539 (0.0559) time: 2.8547 data: 0.0076 max mem: 33370 +Epoch: [18] [2310/2639] eta: 0:15:52 lr: 2.8146209235101428e-05 loss: 0.0510 (0.0558) time: 2.8665 data: 0.0079 max mem: 33370 +Epoch: [18] [2320/2639] eta: 0:15:23 lr: 2.8141665167164516e-05 loss: 0.0358 (0.0558) time: 2.8514 data: 0.0077 max mem: 33370 +Epoch: [18] [2330/2639] eta: 0:14:54 lr: 2.813712101769992e-05 loss: 0.0410 (0.0558) time: 2.8250 data: 0.0076 max mem: 33370 +Epoch: [18] [2340/2639] eta: 0:14:25 lr: 2.8132576786691543e-05 loss: 0.0539 (0.0557) time: 2.8217 data: 0.0075 max mem: 33370 +Epoch: [18] [2350/2639] eta: 0:13:56 lr: 2.8128032474123284e-05 loss: 0.0489 (0.0557) time: 2.8246 data: 0.0077 max mem: 33370 +Epoch: [18] [2360/2639] eta: 0:13:27 lr: 2.812348807997904e-05 loss: 0.0456 (0.0557) time: 2.8529 data: 0.0080 max mem: 33370 +Epoch: [18] [2370/2639] eta: 0:12:58 lr: 2.8118943604242697e-05 loss: 0.0518 (0.0557) time: 2.8533 data: 0.0079 max mem: 33370 +Epoch: [18] [2380/2639] eta: 0:12:29 lr: 2.8114399046898144e-05 loss: 0.0481 (0.0557) time: 2.8155 data: 0.0080 max mem: 33370 +Epoch: [18] [2390/2639] eta: 0:12:00 lr: 2.810985440792926e-05 loss: 0.0445 (0.0556) time: 2.8495 data: 0.0077 max mem: 33370 +Epoch: [18] [2400/2639] eta: 0:11:31 lr: 2.8105309687319902e-05 loss: 0.0460 (0.0556) time: 2.8455 data: 0.0076 max mem: 33370 +Epoch: [18] [2410/2639] eta: 0:11:02 lr: 2.8100764885053944e-05 loss: 0.0469 (0.0556) time: 2.8442 data: 0.0078 max mem: 33370 +Epoch: [18] [2420/2639] eta: 0:10:33 lr: 2.8096220001115246e-05 loss: 0.0485 (0.0557) time: 2.8479 data: 0.0083 max mem: 33370 +Epoch: [18] [2430/2639] eta: 0:10:04 lr: 2.8091675035487664e-05 loss: 0.0517 (0.0557) time: 2.8434 data: 0.0081 max mem: 33370 +Epoch: [18] [2440/2639] eta: 0:09:35 lr: 2.8087129988155026e-05 loss: 0.0448 (0.0556) time: 2.8836 data: 0.0074 max mem: 33370 +Epoch: [18] [2450/2639] eta: 0:09:06 lr: 2.8082584859101185e-05 loss: 0.0366 (0.0556) time: 2.8855 data: 0.0076 max mem: 33370 +Epoch: [18] [2460/2639] eta: 0:08:37 lr: 2.807803964830998e-05 loss: 0.0466 (0.0556) time: 2.8560 data: 0.0079 max mem: 33370 +Epoch: [18] [2470/2639] eta: 0:08:08 lr: 2.8073494355765227e-05 loss: 0.0497 (0.0556) time: 2.8826 data: 0.0077 max mem: 33370 +Epoch: [18] [2480/2639] eta: 0:07:39 lr: 2.8068948981450753e-05 loss: 0.0499 (0.0556) time: 2.8700 data: 0.0075 max mem: 33370 +Epoch: [18] [2490/2639] eta: 0:07:10 lr: 2.8064403525350376e-05 loss: 0.0445 (0.0556) time: 2.8180 data: 0.0076 max mem: 33370 +Epoch: [18] [2500/2639] eta: 0:06:41 lr: 2.8059857987447907e-05 loss: 0.0484 (0.0556) time: 2.8226 data: 0.0079 max mem: 33370 +Epoch: [18] [2510/2639] eta: 0:06:12 lr: 2.805531236772715e-05 loss: 0.0506 (0.0556) time: 2.8559 data: 0.0081 max mem: 33370 +Epoch: [18] [2520/2639] eta: 0:05:44 lr: 2.8050766666171883e-05 loss: 0.0493 (0.0556) time: 2.8495 data: 0.0083 max mem: 33370 +Epoch: [18] [2530/2639] eta: 0:05:15 lr: 2.8046220882765924e-05 loss: 0.0462 (0.0556) time: 2.8546 data: 0.0082 max mem: 33370 +Epoch: [18] [2540/2639] eta: 0:04:46 lr: 2.8041675017493048e-05 loss: 0.0479 (0.0556) time: 2.8803 data: 0.0080 max mem: 33370 +Epoch: [18] [2550/2639] eta: 0:04:17 lr: 2.8037129070337032e-05 loss: 0.0578 (0.0556) time: 2.8774 data: 0.0079 max mem: 33370 +Epoch: [18] [2560/2639] eta: 0:03:48 lr: 2.8032583041281645e-05 loss: 0.0554 (0.0556) time: 2.8779 data: 0.0077 max mem: 33370 +Epoch: [18] [2570/2639] eta: 0:03:19 lr: 2.8028036930310657e-05 loss: 0.0519 (0.0556) time: 2.8614 data: 0.0078 max mem: 33370 +Epoch: [18] [2580/2639] eta: 0:02:50 lr: 2.8023490737407835e-05 loss: 0.0591 (0.0556) time: 2.8609 data: 0.0083 max mem: 33370 +Epoch: [18] [2590/2639] eta: 0:02:21 lr: 2.8018944462556928e-05 loss: 0.0517 (0.0555) time: 2.8714 data: 0.0081 max mem: 33370 +Epoch: [18] [2600/2639] eta: 0:01:52 lr: 2.801439810574168e-05 loss: 0.0457 (0.0555) time: 2.8688 data: 0.0082 max mem: 33370 +Epoch: [18] [2610/2639] eta: 0:01:23 lr: 2.8009851666945842e-05 loss: 0.0460 (0.0555) time: 2.8686 data: 0.0083 max mem: 33370 +Epoch: [18] [2620/2639] eta: 0:00:54 lr: 2.8005305146153138e-05 loss: 0.0519 (0.0555) time: 2.8793 data: 0.0077 max mem: 33370 +Epoch: [18] [2630/2639] eta: 0:00:26 lr: 2.8000758543347315e-05 loss: 0.0483 (0.0555) time: 2.8663 data: 0.0074 max mem: 33370 +Epoch: [18] Total time: 2:07:07 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 2:06:25 time: 2.9480 data: 2.8354 max mem: 33370 +Test: [ 100/2573] eta: 0:04:19 time: 0.0760 data: 0.0014 max mem: 33370 +Test: [ 200/2573] eta: 0:03:37 time: 0.0777 data: 0.0014 max mem: 33370 +Test: [ 300/2573] eta: 0:03:17 time: 0.0794 data: 0.0013 max mem: 33370 +Test: [ 400/2573] eta: 0:03:03 time: 0.0797 data: 0.0014 max mem: 33370 +Test: [ 500/2573] eta: 0:02:52 time: 0.0799 data: 0.0014 max mem: 33370 +Test: [ 600/2573] eta: 0:02:43 time: 0.0816 data: 0.0013 max mem: 33370 +Test: [ 700/2573] eta: 0:02:34 time: 0.0794 data: 0.0014 max mem: 33370 +Test: [ 800/2573] eta: 0:02:25 time: 0.0815 data: 0.0013 max mem: 33370 +Test: [ 900/2573] eta: 0:02:17 time: 0.0794 data: 0.0015 max mem: 33370 +Test: [1000/2573] eta: 0:02:08 time: 0.0798 data: 0.0014 max mem: 33370 +Test: [1100/2573] eta: 0:01:59 time: 0.0791 data: 0.0014 max mem: 33370 +Test: [1200/2573] eta: 0:01:51 time: 0.0788 data: 0.0013 max mem: 33370 +Test: [1300/2573] eta: 0:01:43 time: 0.0794 data: 0.0014 max mem: 33370 +Test: [1400/2573] eta: 0:01:34 time: 0.0773 data: 0.0013 max mem: 33370 +Test: [1500/2573] eta: 0:01:26 time: 0.0802 data: 0.0014 max mem: 33370 +Test: [1600/2573] eta: 0:01:18 time: 0.0824 data: 0.0013 max mem: 33370 +Test: [1700/2573] eta: 0:01:10 time: 0.0776 data: 0.0013 max mem: 33370 +Test: [1800/2573] eta: 0:01:02 time: 0.0808 data: 0.0013 max mem: 33370 +Test: [1900/2573] eta: 0:00:54 time: 0.0775 data: 0.0014 max mem: 33370 +Test: [2000/2573] eta: 0:00:46 time: 0.0796 data: 0.0014 max mem: 33370 +Test: [2100/2573] eta: 0:00:38 time: 0.0812 data: 0.0013 max mem: 33370 +Test: [2200/2573] eta: 0:00:29 time: 0.0814 data: 0.0014 max mem: 33370 +Test: [2300/2573] eta: 0:00:21 time: 0.0819 data: 0.0014 max mem: 33370 +Test: [2400/2573] eta: 0:00:13 time: 0.0761 data: 0.0014 max mem: 33370 +Test: [2500/2573] eta: 0:00:05 time: 0.0796 data: 0.0013 max mem: 33370 +Test: Total time: 0:03:26 +Final results: +Mean IoU is 63.04 + + precision@0.5 = 70.96 + precision@0.6 = 65.38 + precision@0.7 = 58.37 + precision@0.8 = 46.22 + precision@0.9 = 22.86 + overall IoU = 61.16 + +Average object IoU 63.0447299971689 +Overall IoU 61.15937805175781 +Better epoch: 18 + +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [19] [ 0/2639] eta: 4:03:15 lr: 2.7996666530687395e-05 loss: 0.0455 (0.0455) time: 5.5308 data: 2.2409 max mem: 33370 +Epoch: [19] [ 10/2639] eta: 2:17:54 lr: 2.7992119772011772e-05 loss: 0.0455 (0.0528) time: 3.1473 data: 0.2107 max mem: 33370 +Epoch: [19] [ 20/2639] eta: 2:11:40 lr: 2.7987572931275808e-05 loss: 0.0499 (0.0611) time: 2.8910 data: 0.0074 max mem: 33370 +Epoch: [19] [ 30/2639] eta: 2:09:25 lr: 2.7983026008463205e-05 loss: 0.0439 (0.0553) time: 2.8825 data: 0.0077 max mem: 33370 +Epoch: [19] [ 40/2639] eta: 2:07:47 lr: 2.797847900355765e-05 loss: 0.0445 (0.0540) time: 2.8803 data: 0.0078 max mem: 33370 +Epoch: [19] [ 50/2639] eta: 2:06:38 lr: 2.7973931916542844e-05 loss: 0.0494 (0.0550) time: 2.8707 data: 0.0075 max mem: 33370 +Epoch: [19] [ 60/2639] eta: 2:05:19 lr: 2.796938474740249e-05 loss: 0.0477 (0.0536) time: 2.8451 data: 0.0078 max mem: 33370 +Epoch: [19] [ 70/2639] eta: 2:04:30 lr: 2.796483749612025e-05 loss: 0.0469 (0.0526) time: 2.8387 data: 0.0077 max mem: 33370 +Epoch: [19] [ 80/2639] eta: 2:03:36 lr: 2.7960290162679796e-05 loss: 0.0472 (0.0521) time: 2.8451 data: 0.0077 max mem: 33370 +Epoch: [19] [ 90/2639] eta: 2:02:49 lr: 2.795574274706481e-05 loss: 0.0474 (0.0526) time: 2.8315 data: 0.0077 max mem: 33370 +Epoch: [19] [ 100/2639] eta: 2:02:05 lr: 2.7951195249258954e-05 loss: 0.0480 (0.0529) time: 2.8318 data: 0.0077 max mem: 33370 +Epoch: [19] [ 110/2639] eta: 2:01:25 lr: 2.7946647669245878e-05 loss: 0.0517 (0.0529) time: 2.8329 data: 0.0077 max mem: 33370 +Epoch: [19] [ 120/2639] eta: 2:00:51 lr: 2.7942100007009226e-05 loss: 0.0508 (0.0528) time: 2.8452 data: 0.0072 max mem: 33370 +Epoch: [19] [ 130/2639] eta: 2:00:25 lr: 2.793755226253265e-05 loss: 0.0466 (0.0540) time: 2.8762 data: 0.0076 max mem: 33370 +Epoch: [19] [ 140/2639] eta: 1:59:51 lr: 2.7933004435799792e-05 loss: 0.0426 (0.0531) time: 2.8741 data: 0.0081 max mem: 33370 +Epoch: [19] [ 150/2639] eta: 1:59:18 lr: 2.7928456526794278e-05 loss: 0.0426 (0.0538) time: 2.8504 data: 0.0080 max mem: 33370 +Epoch: [19] [ 160/2639] eta: 1:58:40 lr: 2.7923908535499725e-05 loss: 0.0459 (0.0534) time: 2.8320 data: 0.0078 max mem: 33370 +Epoch: [19] [ 170/2639] eta: 1:58:09 lr: 2.7919360461899764e-05 loss: 0.0417 (0.0532) time: 2.8361 data: 0.0079 max mem: 33370 +Epoch: [19] [ 180/2639] eta: 1:57:40 lr: 2.7914812305978006e-05 loss: 0.0552 (0.0544) time: 2.8628 data: 0.0081 max mem: 33370 +Epoch: [19] [ 190/2639] eta: 1:57:10 lr: 2.7910264067718056e-05 loss: 0.0591 (0.0542) time: 2.8654 data: 0.0080 max mem: 33370 +Epoch: [19] [ 200/2639] eta: 1:56:36 lr: 2.7905715747103507e-05 loss: 0.0447 (0.0545) time: 2.8442 data: 0.0080 max mem: 33370 +Epoch: [19] [ 210/2639] eta: 1:56:02 lr: 2.7901167344117963e-05 loss: 0.0447 (0.0552) time: 2.8235 data: 0.0081 max mem: 33370 +Epoch: [19] [ 220/2639] eta: 1:55:31 lr: 2.7896618858745006e-05 loss: 0.0423 (0.0546) time: 2.8339 data: 0.0079 max mem: 33370 +Epoch: [19] [ 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mem: 33370 +Epoch: [19] [1090/2639] eta: 1:14:08 lr: 2.750058337233225e-05 loss: 0.0480 (0.0530) time: 2.8400 data: 0.0075 max mem: 33370 +Epoch: [19] [1100/2639] eta: 1:13:39 lr: 2.7496027571853972e-05 loss: 0.0480 (0.0530) time: 2.8925 data: 0.0073 max mem: 33370 +Epoch: [19] [1110/2639] eta: 1:13:10 lr: 2.7491471687502162e-05 loss: 0.0474 (0.0530) time: 2.8675 data: 0.0072 max mem: 33370 +Epoch: [19] [1120/2639] eta: 1:12:42 lr: 2.748691571925983e-05 loss: 0.0491 (0.0529) time: 2.8733 data: 0.0075 max mem: 33370 +Epoch: [19] [1130/2639] eta: 1:12:14 lr: 2.7482359667109987e-05 loss: 0.0532 (0.0529) time: 2.9218 data: 0.0080 max mem: 33370 +Epoch: [19] [1140/2639] eta: 1:11:45 lr: 2.747780353103563e-05 loss: 0.0447 (0.0528) time: 2.9110 data: 0.0078 max mem: 33370 +Epoch: [19] [1150/2639] eta: 1:11:17 lr: 2.7473247311019746e-05 loss: 0.0440 (0.0529) time: 2.8907 data: 0.0073 max mem: 33370 +Epoch: [19] [1160/2639] eta: 1:10:49 lr: 2.7468691007045317e-05 loss: 0.0423 (0.0528) time: 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0.0437 (0.0530) time: 2.8225 data: 0.0080 max mem: 33370 +Epoch: [19] [1250/2639] eta: 1:06:29 lr: 2.742768049033048e-05 loss: 0.0409 (0.0530) time: 2.8556 data: 0.0081 max mem: 33370 +Epoch: [19] [1260/2639] eta: 1:06:00 lr: 2.742312334583339e-05 loss: 0.0419 (0.0529) time: 2.8573 data: 0.0078 max mem: 33370 +Epoch: [19] [1270/2639] eta: 1:05:32 lr: 2.7418566117190165e-05 loss: 0.0506 (0.0530) time: 2.8727 data: 0.0075 max mem: 33370 +Epoch: [19] [1280/2639] eta: 1:05:03 lr: 2.74140088043837e-05 loss: 0.0440 (0.0529) time: 2.8771 data: 0.0076 max mem: 33370 +Epoch: [19] [1290/2639] eta: 1:04:34 lr: 2.7409451407396903e-05 loss: 0.0422 (0.0529) time: 2.8526 data: 0.0074 max mem: 33370 +Epoch: [19] [1300/2639] eta: 1:04:05 lr: 2.740489392621266e-05 loss: 0.0436 (0.0529) time: 2.8434 data: 0.0075 max mem: 33370 +Epoch: [19] [1310/2639] eta: 1:03:36 lr: 2.7400336360813868e-05 loss: 0.0453 (0.0529) time: 2.8450 data: 0.0076 max mem: 33370 +Epoch: [19] [1320/2639] eta: 1:03:07 lr: 2.73957787111834e-05 loss: 0.0536 (0.0529) time: 2.8685 data: 0.0078 max mem: 33370 +Epoch: [19] [1330/2639] eta: 1:02:39 lr: 2.7391220977304122e-05 loss: 0.0465 (0.0528) time: 2.8729 data: 0.0082 max mem: 33370 +Epoch: [19] [1340/2639] eta: 1:02:10 lr: 2.738666315915891e-05 loss: 0.0480 (0.0529) time: 2.8717 data: 0.0081 max mem: 33370 +Epoch: [19] [1350/2639] eta: 1:01:41 lr: 2.738210525673062e-05 loss: 0.0511 (0.0530) time: 2.8835 data: 0.0077 max mem: 33370 +Epoch: [19] [1360/2639] eta: 1:01:13 lr: 2.7377547270002108e-05 loss: 0.0460 (0.0529) time: 2.9105 data: 0.0077 max mem: 33370 +Epoch: [19] [1370/2639] eta: 1:00:45 lr: 2.7372989198956205e-05 loss: 0.0486 (0.0529) time: 2.9054 data: 0.0077 max mem: 33370 +Epoch: [19] [1380/2639] eta: 1:00:16 lr: 2.736843104357577e-05 loss: 0.0484 (0.0529) time: 2.8619 data: 0.0078 max mem: 33370 +Epoch: [19] [1390/2639] eta: 0:59:47 lr: 2.7363872803843626e-05 loss: 0.0484 (0.0529) time: 2.8778 data: 0.0077 max mem: 33370 +Epoch: [19] [1400/2639] eta: 0:59:18 lr: 2.7359314479742604e-05 loss: 0.0524 (0.0529) time: 2.8839 data: 0.0073 max mem: 33370 +Epoch: [19] [1410/2639] eta: 0:58:50 lr: 2.735475607125551e-05 loss: 0.0435 (0.0529) time: 2.8627 data: 0.0075 max mem: 33370 +Epoch: [19] [1420/2639] eta: 0:58:21 lr: 2.7350197578365172e-05 loss: 0.0489 (0.0529) time: 2.8638 data: 0.0082 max mem: 33370 +Epoch: [19] [1430/2639] eta: 0:57:52 lr: 2.734563900105439e-05 loss: 0.0517 (0.0530) time: 2.8784 data: 0.0081 max mem: 33370 +Epoch: [19] [1440/2639] eta: 0:57:23 lr: 2.734108033930597e-05 loss: 0.0507 (0.0531) time: 2.8776 data: 0.0074 max mem: 33370 +Epoch: [19] [1450/2639] eta: 0:56:54 lr: 2.7336521593102687e-05 loss: 0.0507 (0.0531) time: 2.8525 data: 0.0075 max mem: 33370 +Epoch: [19] [1460/2639] eta: 0:56:26 lr: 2.7331962762427337e-05 loss: 0.0540 (0.0533) time: 2.8916 data: 0.0078 max mem: 33370 +Epoch: [19] [1470/2639] eta: 0:55:58 lr: 2.732740384726271e-05 loss: 0.0516 (0.0532) time: 2.9263 data: 0.0078 max mem: 33370 +Epoch: [19] [1480/2639] eta: 0:55:30 lr: 2.732284484759156e-05 loss: 0.0510 (0.0533) time: 2.9151 data: 0.0081 max mem: 33370 +Epoch: [19] [1490/2639] eta: 0:55:01 lr: 2.7318285763396668e-05 loss: 0.0510 (0.0533) time: 2.8855 data: 0.0082 max mem: 33370 +Epoch: [19] [1500/2639] eta: 0:54:32 lr: 2.7313726594660782e-05 loss: 0.0520 (0.0533) time: 2.8560 data: 0.0078 max mem: 33370 +Epoch: [19] [1510/2639] eta: 0:54:03 lr: 2.7309167341366654e-05 loss: 0.0507 (0.0533) time: 2.8305 data: 0.0075 max mem: 33370 +Epoch: [19] [1520/2639] eta: 0:53:34 lr: 2.7304608003497045e-05 loss: 0.0413 (0.0532) time: 2.8457 data: 0.0076 max mem: 33370 +Epoch: [19] [1530/2639] eta: 0:53:05 lr: 2.7300048581034682e-05 loss: 0.0411 (0.0533) time: 2.8486 data: 0.0076 max mem: 33370 +Epoch: [19] [1540/2639] eta: 0:52:36 lr: 2.7295489073962286e-05 loss: 0.0510 (0.0533) time: 2.8479 data: 0.0073 max mem: 33370 +Epoch: [19] [1550/2639] eta: 0:52:08 lr: 2.7290929482262606e-05 loss: 0.0541 (0.0534) time: 2.8973 data: 0.0073 max mem: 33370 +Epoch: [19] [1560/2639] eta: 0:51:39 lr: 2.728636980591835e-05 loss: 0.0541 (0.0533) time: 2.8732 data: 0.0077 max mem: 33370 +Epoch: [19] [1570/2639] eta: 0:51:10 lr: 2.7281810044912226e-05 loss: 0.0484 (0.0533) time: 2.8703 data: 0.0078 max mem: 33370 +Epoch: [19] [1580/2639] eta: 0:50:42 lr: 2.727725019922694e-05 loss: 0.0423 (0.0533) time: 2.8949 data: 0.0074 max mem: 33370 +Epoch: [19] [1590/2639] eta: 0:50:13 lr: 2.727269026884519e-05 loss: 0.0423 (0.0533) time: 2.8613 data: 0.0075 max mem: 33370 +Epoch: [19] [1600/2639] eta: 0:49:44 lr: 2.7268130253749685e-05 loss: 0.0468 (0.0533) time: 2.8868 data: 0.0078 max mem: 33370 +Epoch: [19] [1610/2639] eta: 0:49:16 lr: 2.726357015392309e-05 loss: 0.0433 (0.0533) time: 2.9401 data: 0.0077 max mem: 33370 +Epoch: [19] [1620/2639] eta: 0:48:47 lr: 2.7259009969348082e-05 loss: 0.0414 (0.0533) time: 2.9263 data: 0.0076 max mem: 33370 +Epoch: [19] [1630/2639] eta: 0:48:19 lr: 2.725444970000734e-05 loss: 0.0408 (0.0533) time: 2.9186 data: 0.0074 max mem: 33370 +Epoch: [19] [1640/2639] eta: 0:47:50 lr: 2.7249889345883534e-05 loss: 0.0460 (0.0533) time: 2.9110 data: 0.0077 max mem: 33370 +Epoch: [19] [1650/2639] eta: 0:47:22 lr: 2.7245328906959317e-05 loss: 0.0493 (0.0533) time: 2.8947 data: 0.0077 max mem: 33370 +Epoch: [19] [1660/2639] eta: 0:46:53 lr: 2.7240768383217337e-05 loss: 0.0467 (0.0532) time: 2.8865 data: 0.0073 max mem: 33370 +Epoch: [19] [1670/2639] eta: 0:46:24 lr: 2.7236207774640237e-05 loss: 0.0465 (0.0532) time: 2.8680 data: 0.0073 max mem: 33370 +Epoch: [19] [1680/2639] eta: 0:45:56 lr: 2.7231647081210663e-05 loss: 0.0441 (0.0532) time: 2.8814 data: 0.0074 max mem: 33370 +Epoch: [19] [1690/2639] eta: 0:45:27 lr: 2.722708630291124e-05 loss: 0.0410 (0.0532) time: 2.8958 data: 0.0079 max mem: 33370 +Epoch: [19] [1700/2639] eta: 0:44:59 lr: 2.7222525439724595e-05 loss: 0.0409 (0.0531) time: 2.9012 data: 0.0083 max mem: 33370 +Epoch: [19] [1710/2639] eta: 0:44:30 lr: 2.7217964491633336e-05 loss: 0.0474 (0.0531) time: 2.8946 data: 0.0081 max mem: 33370 +Epoch: [19] [1720/2639] eta: 0:44:01 lr: 2.7213403458620085e-05 loss: 0.0485 (0.0531) time: 2.8906 data: 0.0079 max mem: 33370 +Epoch: [19] [1730/2639] eta: 0:43:33 lr: 2.720884234066744e-05 loss: 0.0487 (0.0531) time: 2.9098 data: 0.0081 max mem: 33370 +Epoch: [19] [1740/2639] eta: 0:43:04 lr: 2.7204281137758004e-05 loss: 0.0506 (0.0531) time: 2.8825 data: 0.0082 max mem: 33370 +Epoch: [19] [1750/2639] eta: 0:42:35 lr: 2.7199719849874355e-05 loss: 0.0506 (0.0531) time: 2.8952 data: 0.0079 max mem: 33370 +Epoch: [19] [1760/2639] eta: 0:42:07 lr: 2.7195158476999085e-05 loss: 0.0461 (0.0531) time: 2.9290 data: 0.0078 max mem: 33370 +Epoch: [19] [1770/2639] eta: 0:41:38 lr: 2.719059701911477e-05 loss: 0.0414 (0.0531) time: 2.9299 data: 0.0076 max mem: 33370 +Epoch: [19] [1780/2639] eta: 0:41:10 lr: 2.7186035476203986e-05 loss: 0.0418 (0.0530) time: 2.9371 data: 0.0076 max mem: 33370 +Epoch: [19] [1790/2639] eta: 0:40:41 lr: 2.7181473848249276e-05 loss: 0.0439 (0.0530) time: 2.9180 data: 0.0078 max mem: 33370 +Epoch: [19] [1800/2639] eta: 0:40:12 lr: 2.717691213523321e-05 loss: 0.0413 (0.0530) time: 2.8785 data: 0.0076 max mem: 33370 +Epoch: [19] [1810/2639] eta: 0:39:44 lr: 2.717235033713834e-05 loss: 0.0421 (0.0529) time: 2.8575 data: 0.0075 max mem: 33370 +Epoch: [19] [1820/2639] eta: 0:39:15 lr: 2.7167788453947208e-05 loss: 0.0476 (0.0530) time: 2.8426 data: 0.0075 max mem: 33370 +Epoch: [19] [1830/2639] eta: 0:38:46 lr: 2.7163226485642328e-05 loss: 0.0558 (0.0530) time: 2.8468 data: 0.0075 max mem: 33370 +Epoch: [19] [1840/2639] eta: 0:38:17 lr: 2.7158664432206255e-05 loss: 0.0489 (0.0531) time: 2.8784 data: 0.0077 max mem: 33370 +Epoch: [19] [1850/2639] eta: 0:37:48 lr: 2.71541022936215e-05 loss: 0.0451 (0.0531) time: 2.8836 data: 0.0080 max mem: 33370 +Epoch: [19] [1860/2639] eta: 0:37:20 lr: 2.7149540069870587e-05 loss: 0.0505 (0.0531) time: 2.8577 data: 0.0080 max mem: 33370 +Epoch: [19] [1870/2639] eta: 0:36:51 lr: 2.7144977760936e-05 loss: 0.0416 (0.0530) time: 2.8367 data: 0.0081 max mem: 33370 +Epoch: [19] [1880/2639] eta: 0:36:22 lr: 2.7140415366800265e-05 loss: 0.0416 (0.0530) time: 2.8231 data: 0.0082 max mem: 33370 +Epoch: [19] [1890/2639] eta: 0:35:53 lr: 2.7135852887445866e-05 loss: 0.0403 (0.0530) time: 2.8093 data: 0.0080 max mem: 33370 +Epoch: [19] [1900/2639] eta: 0:35:24 lr: 2.7131290322855297e-05 loss: 0.0384 (0.0529) time: 2.8377 data: 0.0077 max mem: 33370 +Epoch: [19] [1910/2639] eta: 0:34:55 lr: 2.7126727673011027e-05 loss: 0.0384 (0.0529) time: 2.9037 data: 0.0078 max mem: 33370 +Epoch: [19] [1920/2639] eta: 0:34:27 lr: 2.7122164937895534e-05 loss: 0.0384 (0.0529) time: 2.9101 data: 0.0078 max mem: 33370 +Epoch: [19] [1930/2639] eta: 0:33:58 lr: 2.7117602117491288e-05 loss: 0.0483 (0.0529) time: 2.8887 data: 0.0074 max mem: 33370 +Epoch: [19] [1940/2639] eta: 0:33:29 lr: 2.711303921178075e-05 loss: 0.0477 (0.0529) time: 2.9001 data: 0.0072 max mem: 33370 +Epoch: [19] [1950/2639] eta: 0:33:01 lr: 2.7108476220746365e-05 loss: 0.0440 (0.0529) time: 2.9252 data: 0.0075 max mem: 33370 +Epoch: [19] [1960/2639] eta: 0:32:32 lr: 2.710391314437059e-05 loss: 0.0513 (0.0530) time: 2.8909 data: 0.0078 max mem: 33370 +Epoch: [19] [1970/2639] eta: 0:32:03 lr: 2.709934998263586e-05 loss: 0.0565 (0.0530) time: 2.8835 data: 0.0077 max mem: 33370 +Epoch: [19] [1980/2639] eta: 0:31:34 lr: 2.7094786735524595e-05 loss: 0.0530 (0.0530) time: 2.8808 data: 0.0076 max mem: 33370 +Epoch: [19] [1990/2639] eta: 0:31:06 lr: 2.7090223403019245e-05 loss: 0.0467 (0.0530) time: 2.8946 data: 0.0076 max mem: 33370 +Epoch: [19] [2000/2639] eta: 0:30:37 lr: 2.7085659985102206e-05 loss: 0.0449 (0.0530) time: 2.9180 data: 0.0074 max mem: 33370 +Epoch: [19] [2010/2639] eta: 0:30:09 lr: 2.70810964817559e-05 loss: 0.0458 (0.0530) time: 2.8988 data: 0.0075 max mem: 33370 +Epoch: [19] [2020/2639] eta: 0:29:40 lr: 2.7076532892962734e-05 loss: 0.0469 (0.0530) time: 2.9035 data: 0.0079 max mem: 33370 +Epoch: [19] [2030/2639] eta: 0:29:11 lr: 2.7071969218705106e-05 loss: 0.0469 (0.0530) time: 2.9053 data: 0.0080 max mem: 33370 +Epoch: [19] [2040/2639] eta: 0:28:42 lr: 2.7067405458965393e-05 loss: 0.0445 (0.0530) time: 2.9020 data: 0.0078 max mem: 33370 +Epoch: [19] [2050/2639] eta: 0:28:14 lr: 2.7062841613725992e-05 loss: 0.0480 (0.0531) time: 2.8808 data: 0.0074 max mem: 33370 +Epoch: [19] [2060/2639] eta: 0:27:45 lr: 2.705827768296928e-05 loss: 0.0536 (0.0531) time: 2.8783 data: 0.0074 max mem: 33370 +Epoch: [19] [2070/2639] eta: 0:27:16 lr: 2.705371366667762e-05 loss: 0.0521 (0.0532) time: 2.8775 data: 0.0081 max mem: 33370 +Epoch: [19] [2080/2639] eta: 0:26:47 lr: 2.7049149564833383e-05 loss: 0.0495 (0.0532) time: 2.8780 data: 0.0081 max mem: 33370 +Epoch: [19] [2090/2639] eta: 0:26:18 lr: 2.7044585377418912e-05 loss: 0.0504 (0.0531) time: 2.8488 data: 0.0077 max mem: 33370 +Epoch: [19] [2100/2639] eta: 0:25:50 lr: 2.7040021104416573e-05 loss: 0.0485 (0.0531) time: 2.8235 data: 0.0075 max mem: 33370 +Epoch: [19] [2110/2639] eta: 0:25:21 lr: 2.7035456745808707e-05 loss: 0.0515 (0.0532) time: 2.8143 data: 0.0076 max mem: 33370 +Epoch: [19] [2120/2639] eta: 0:24:52 lr: 2.703089230157763e-05 loss: 0.0468 (0.0531) time: 2.8061 data: 0.0076 max mem: 33370 +Epoch: [19] [2130/2639] eta: 0:24:23 lr: 2.702632777170569e-05 loss: 0.0423 (0.0531) time: 2.8430 data: 0.0072 max mem: 33370 +Epoch: [19] [2140/2639] eta: 0:23:54 lr: 2.70217631561752e-05 loss: 0.0406 (0.0531) time: 2.9033 data: 0.0072 max mem: 33370 +Epoch: [19] [2150/2639] eta: 0:23:26 lr: 2.7017198454968478e-05 loss: 0.0434 (0.0531) time: 2.9113 data: 0.0076 max mem: 33370 +Epoch: [19] [2160/2639] eta: 0:22:57 lr: 2.7012633668067828e-05 loss: 0.0486 (0.0531) time: 2.9037 data: 0.0078 max mem: 33370 +Epoch: [19] [2170/2639] eta: 0:22:28 lr: 2.7008068795455545e-05 loss: 0.0619 (0.0533) time: 2.9068 data: 0.0076 max mem: 33370 +Epoch: [19] [2180/2639] eta: 0:22:00 lr: 2.7003503837113942e-05 loss: 0.0619 (0.0533) time: 2.8861 data: 0.0077 max mem: 33370 +Epoch: [19] [2190/2639] eta: 0:21:31 lr: 2.6998938793025287e-05 loss: 0.0495 (0.0533) time: 2.8679 data: 0.0075 max mem: 33370 +Epoch: [19] [2200/2639] eta: 0:21:02 lr: 2.6994373663171862e-05 loss: 0.0448 (0.0533) time: 2.9036 data: 0.0071 max mem: 33370 +Epoch: [19] [2210/2639] eta: 0:20:33 lr: 2.698980844753594e-05 loss: 0.0576 (0.0534) time: 2.9132 data: 0.0075 max mem: 33370 +Epoch: [19] [2220/2639] eta: 0:20:05 lr: 2.698524314609979e-05 loss: 0.0492 (0.0534) time: 2.8597 data: 0.0082 max mem: 33370 +Epoch: [19] [2230/2639] eta: 0:19:36 lr: 2.698067775884568e-05 loss: 0.0425 (0.0534) time: 2.8533 data: 0.0084 max mem: 33370 +Epoch: [19] [2240/2639] eta: 0:19:07 lr: 2.697611228575585e-05 loss: 0.0476 (0.0534) time: 2.8773 data: 0.0080 max mem: 33370 +Epoch: [19] [2250/2639] eta: 0:18:38 lr: 2.697154672681254e-05 loss: 0.0487 (0.0535) time: 2.9091 data: 0.0077 max mem: 33370 +Epoch: [19] [2260/2639] eta: 0:18:10 lr: 2.6966981081997993e-05 loss: 0.0530 (0.0535) time: 2.9003 data: 0.0080 max mem: 33370 +Epoch: [19] [2270/2639] eta: 0:17:41 lr: 2.6962415351294445e-05 loss: 0.0530 (0.0535) time: 2.8759 data: 0.0083 max mem: 33370 +Epoch: [19] [2280/2639] eta: 0:17:12 lr: 2.6957849534684115e-05 loss: 0.0558 (0.0536) time: 2.9141 data: 0.0079 max mem: 33370 +Epoch: [19] [2290/2639] eta: 0:16:43 lr: 2.695328363214921e-05 loss: 0.0585 (0.0536) time: 2.9124 data: 0.0076 max mem: 33370 +Epoch: [19] [2300/2639] eta: 0:16:15 lr: 2.6948717643671956e-05 loss: 0.0461 (0.0536) time: 2.8801 data: 0.0076 max mem: 33370 +Epoch: [19] [2310/2639] eta: 0:15:46 lr: 2.6944151569234548e-05 loss: 0.0443 (0.0535) time: 2.8701 data: 0.0075 max mem: 33370 +Epoch: [19] [2320/2639] eta: 0:15:17 lr: 2.693958540881918e-05 loss: 0.0500 (0.0536) time: 2.8573 data: 0.0075 max mem: 33370 +Epoch: [19] [2330/2639] eta: 0:14:48 lr: 2.6935019162408038e-05 loss: 0.0493 (0.0536) time: 2.8747 data: 0.0075 max mem: 33370 +Epoch: [19] [2340/2639] eta: 0:14:20 lr: 2.6930452829983303e-05 loss: 0.0423 (0.0535) time: 2.9042 data: 0.0080 max mem: 33370 +Epoch: [19] [2350/2639] eta: 0:13:51 lr: 2.6925886411527164e-05 loss: 0.0432 (0.0535) time: 2.8848 data: 0.0082 max mem: 33370 +Epoch: [19] [2360/2639] eta: 0:13:22 lr: 2.692131990702177e-05 loss: 0.0470 (0.0536) time: 2.8724 data: 0.0081 max mem: 33370 +Epoch: [19] [2370/2639] eta: 0:12:53 lr: 2.6916753316449284e-05 loss: 0.0458 (0.0536) time: 2.8874 data: 0.0079 max mem: 33370 +Epoch: [19] [2380/2639] eta: 0:12:25 lr: 2.6912186639791864e-05 loss: 0.0453 (0.0536) time: 2.8625 data: 0.0078 max mem: 33370 +Epoch: [19] [2390/2639] eta: 0:11:56 lr: 2.6907619877031658e-05 loss: 0.0453 (0.0536) time: 2.8568 data: 0.0078 max mem: 33370 +Epoch: [19] [2400/2639] eta: 0:11:27 lr: 2.6903053028150803e-05 loss: 0.0456 (0.0536) time: 2.8543 data: 0.0077 max mem: 33370 +Epoch: [19] [2410/2639] eta: 0:10:58 lr: 2.6898486093131427e-05 loss: 0.0427 (0.0535) time: 2.8486 data: 0.0076 max mem: 33370 +Epoch: [19] [2420/2639] eta: 0:10:29 lr: 2.6893919071955654e-05 loss: 0.0428 (0.0535) time: 2.8482 data: 0.0075 max mem: 33370 +Epoch: [19] [2430/2639] eta: 0:10:01 lr: 2.6889351964605613e-05 loss: 0.0477 (0.0535) time: 2.8508 data: 0.0079 max mem: 33370 +Epoch: [19] [2440/2639] eta: 0:09:32 lr: 2.6884784771063403e-05 loss: 0.0572 (0.0535) time: 2.8578 data: 0.0082 max mem: 33370 +Epoch: [19] [2450/2639] eta: 0:09:03 lr: 2.6880217491311128e-05 loss: 0.0545 (0.0535) time: 2.8312 data: 0.0081 max mem: 33370 +Epoch: [19] [2460/2639] eta: 0:08:34 lr: 2.6875650125330885e-05 loss: 0.0480 (0.0536) time: 2.8333 data: 0.0078 max mem: 33370 +Epoch: [19] [2470/2639] eta: 0:08:05 lr: 2.6871082673104762e-05 loss: 0.0481 (0.0536) time: 2.8436 data: 0.0075 max mem: 33370 +Epoch: [19] [2480/2639] eta: 0:07:37 lr: 2.6866515134614856e-05 loss: 0.0465 (0.0536) time: 2.8317 data: 0.0076 max mem: 33370 +Epoch: [19] [2490/2639] eta: 0:07:08 lr: 2.6861947509843232e-05 loss: 0.0468 (0.0536) time: 2.8646 data: 0.0082 max mem: 33370 +Epoch: [19] [2500/2639] eta: 0:06:39 lr: 2.6857379798771948e-05 loss: 0.0589 (0.0537) time: 2.8980 data: 0.0080 max mem: 33370 +Epoch: [19] [2510/2639] eta: 0:06:10 lr: 2.685281200138307e-05 loss: 0.0544 (0.0537) time: 2.8863 data: 0.0073 max mem: 33370 +Epoch: [19] [2520/2639] eta: 0:05:42 lr: 2.6848244117658665e-05 loss: 0.0501 (0.0538) time: 2.8622 data: 0.0075 max mem: 33370 +Epoch: [19] [2530/2639] eta: 0:05:13 lr: 2.684367614758077e-05 loss: 0.0497 (0.0538) time: 2.8527 data: 0.0079 max mem: 33370 +Epoch: [19] [2540/2639] eta: 0:04:44 lr: 2.6839108091131415e-05 loss: 0.0492 (0.0538) time: 2.8808 data: 0.0080 max mem: 33370 +Epoch: [19] [2550/2639] eta: 0:04:15 lr: 2.6834539948292648e-05 loss: 0.0454 (0.0538) time: 2.9094 data: 0.0078 max mem: 33370 +Epoch: [19] [2560/2639] eta: 0:03:47 lr: 2.682997171904649e-05 loss: 0.0465 (0.0538) time: 2.9036 data: 0.0077 max mem: 33370 +Epoch: [19] [2570/2639] eta: 0:03:18 lr: 2.6825403403374956e-05 loss: 0.0526 (0.0538) time: 2.8894 data: 0.0078 max mem: 33370 +Epoch: [19] [2580/2639] eta: 0:02:49 lr: 2.6820835001260048e-05 loss: 0.0494 (0.0538) time: 2.8917 data: 0.0079 max mem: 33370 +Epoch: [19] [2590/2639] eta: 0:02:20 lr: 2.6816266512683784e-05 loss: 0.0500 (0.0539) time: 2.8887 data: 0.0076 max mem: 33370 +Epoch: [19] [2600/2639] eta: 0:01:52 lr: 2.681169793762816e-05 loss: 0.0475 (0.0538) time: 2.8996 data: 0.0074 max mem: 33370 +Epoch: [19] [2610/2639] eta: 0:01:23 lr: 2.6807129276075162e-05 loss: 0.0474 (0.0538) time: 2.8891 data: 0.0076 max mem: 33370 +Epoch: [19] [2620/2639] eta: 0:00:54 lr: 2.6802560528006763e-05 loss: 0.0474 (0.0538) time: 2.8475 data: 0.0075 max mem: 33370 +Epoch: [19] [2630/2639] eta: 0:00:25 lr: 2.6797991693404957e-05 loss: 0.0467 (0.0538) time: 2.8679 data: 0.0075 max mem: 33370 +Epoch: [19] Total time: 2:06:30 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 2:09:53 time: 3.0290 data: 2.9340 max mem: 33370 +Test: [ 100/2573] eta: 0:04:21 time: 0.0765 data: 0.0014 max mem: 33370 +Test: [ 200/2573] eta: 0:03:39 time: 0.0778 data: 0.0013 max mem: 33370 +Test: [ 300/2573] eta: 0:03:18 time: 0.0798 data: 0.0013 max mem: 33370 +Test: [ 400/2573] eta: 0:03:05 time: 0.0799 data: 0.0014 max mem: 33370 +Test: [ 500/2573] eta: 0:02:53 time: 0.0793 data: 0.0015 max mem: 33370 +Test: [ 600/2573] eta: 0:02:43 time: 0.0787 data: 0.0014 max mem: 33370 +Test: [ 700/2573] eta: 0:02:35 time: 0.0797 data: 0.0014 max mem: 33370 +Test: [ 800/2573] eta: 0:02:26 time: 0.0825 data: 0.0013 max mem: 33370 +Test: [ 900/2573] eta: 0:02:17 time: 0.0791 data: 0.0014 max mem: 33370 +Test: [1000/2573] eta: 0:02:09 time: 0.0795 data: 0.0014 max mem: 33370 +Test: [1100/2573] eta: 0:02:00 time: 0.0786 data: 0.0014 max mem: 33370 +Test: [1200/2573] eta: 0:01:52 time: 0.0790 data: 0.0014 max mem: 33370 +Test: [1300/2573] eta: 0:01:43 time: 0.0780 data: 0.0013 max mem: 33370 +Test: [1400/2573] eta: 0:01:35 time: 0.0780 data: 0.0014 max mem: 33370 +Test: [1500/2573] eta: 0:01:26 time: 0.0787 data: 0.0014 max mem: 33370 +Test: [1600/2573] eta: 0:01:18 time: 0.0819 data: 0.0013 max mem: 33370 +Test: [1700/2573] eta: 0:01:10 time: 0.0774 data: 0.0013 max mem: 33370 +Test: [1800/2573] eta: 0:01:02 time: 0.0807 data: 0.0013 max mem: 33370 +Test: [1900/2573] eta: 0:00:54 time: 0.0782 data: 0.0014 max mem: 33370 +Test: [2000/2573] eta: 0:00:46 time: 0.0797 data: 0.0014 max mem: 33370 +Test: [2100/2573] eta: 0:00:38 time: 0.0814 data: 0.0013 max mem: 33370 +Test: [2200/2573] eta: 0:00:29 time: 0.0808 data: 0.0014 max mem: 33370 +Test: [2300/2573] eta: 0:00:21 time: 0.0815 data: 0.0015 max mem: 33370 +Test: [2400/2573] eta: 0:00:13 time: 0.0760 data: 0.0014 max mem: 33370 +Test: [2500/2573] eta: 0:00:05 time: 0.0806 data: 0.0014 max mem: 33370 +Test: Total time: 0:03:27 +Final results: +Mean IoU is 63.29 + + precision@0.5 = 71.45 + precision@0.6 = 65.97 + precision@0.7 = 58.23 + precision@0.8 = 46.36 + precision@0.9 = 22.63 + overall IoU = 60.93 + +Average object IoU 63.292784566870296 +Overall IoU 60.92517852783203 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [20] [ 0/2639] eta: 4:04:43 lr: 2.679387966826235e-05 loss: 0.0498 (0.0498) time: 5.5641 data: 2.5357 max mem: 33370 +Epoch: [20] [ 10/2639] eta: 2:19:03 lr: 2.6789310669197365e-05 loss: 0.0391 (0.0441) time: 3.1738 data: 0.2376 max mem: 33370 +Epoch: [20] [ 20/2639] eta: 2:13:37 lr: 2.6784741583546646e-05 loss: 0.0430 (0.0455) time: 2.9363 data: 0.0075 max mem: 33370 +Epoch: [20] [ 30/2639] eta: 2:10:47 lr: 2.6780172411292147e-05 loss: 0.0460 (0.0446) time: 2.9164 data: 0.0073 max mem: 33370 +Epoch: [20] [ 40/2639] eta: 2:08:58 lr: 2.6775603152415803e-05 loss: 0.0395 (0.0500) time: 2.8891 data: 0.0077 max mem: 33370 +Epoch: [20] [ 50/2639] eta: 2:07:35 lr: 2.677103380689955e-05 loss: 0.0392 (0.0497) time: 2.8782 data: 0.0082 max mem: 33370 +Epoch: [20] [ 60/2639] eta: 2:06:36 lr: 2.676646437472531e-05 loss: 0.0500 (0.0507) time: 2.8804 data: 0.0079 max mem: 33370 +Epoch: [20] [ 70/2639] eta: 2:05:43 lr: 2.6761894855875008e-05 loss: 0.0511 (0.0504) time: 2.8836 data: 0.0076 max mem: 33370 +Epoch: [20] [ 80/2639] eta: 2:04:39 lr: 2.6757325250330546e-05 loss: 0.0469 (0.0503) time: 2.8531 data: 0.0079 max mem: 33370 +Epoch: [20] [ 90/2639] eta: 2:03:45 lr: 2.675275555807384e-05 loss: 0.0427 (0.0498) time: 2.8304 data: 0.0079 max mem: 33370 +Epoch: [20] [ 100/2639] eta: 2:03:13 lr: 2.674818577908677e-05 loss: 0.0454 (0.0501) time: 2.8686 data: 0.0077 max mem: 33370 +Epoch: [20] [ 110/2639] eta: 2:02:40 lr: 2.674361591335124e-05 loss: 0.0505 (0.0506) time: 2.8993 data: 0.0076 max mem: 33370 +Epoch: [20] [ 120/2639] eta: 2:02:03 lr: 2.6739045960849123e-05 loss: 0.0505 (0.0507) time: 2.8842 data: 0.0077 max mem: 33370 +Epoch: [20] [ 130/2639] eta: 2:01:26 lr: 2.6734475921562307e-05 loss: 0.0447 (0.0504) time: 2.8675 data: 0.0079 max mem: 33370 +Epoch: [20] [ 140/2639] eta: 2:00:53 lr: 2.6729905795472642e-05 loss: 0.0467 (0.0504) time: 2.8723 data: 0.0075 max mem: 33370 +Epoch: [20] [ 150/2639] eta: 2:00:14 lr: 2.6725335582562006e-05 loss: 0.0551 (0.0514) time: 2.8633 data: 0.0073 max mem: 33370 +Epoch: [20] [ 160/2639] eta: 1:59:38 lr: 2.6720765282812237e-05 loss: 0.0477 (0.0508) time: 2.8472 data: 0.0074 max mem: 33370 +Epoch: [20] [ 170/2639] eta: 1:59:09 lr: 2.6716194896205192e-05 loss: 0.0436 (0.0509) time: 2.8741 data: 0.0076 max mem: 33370 +Epoch: [20] [ 180/2639] eta: 1:58:28 lr: 2.6711624422722705e-05 loss: 0.0450 (0.0507) time: 2.8540 data: 0.0081 max mem: 33370 +Epoch: [20] [ 190/2639] eta: 1:57:53 lr: 2.670705386234661e-05 loss: 0.0450 (0.0507) time: 2.8236 data: 0.0079 max mem: 33370 +Epoch: [20] [ 200/2639] eta: 1:57:18 lr: 2.6702483215058725e-05 loss: 0.0460 (0.0506) time: 2.8380 data: 0.0077 max mem: 33370 +Epoch: [20] [ 210/2639] eta: 1:56:42 lr: 2.6697912480840882e-05 loss: 0.0440 (0.0503) time: 2.8310 data: 0.0076 max mem: 33370 +Epoch: [20] [ 220/2639] eta: 1:56:10 lr: 2.669334165967487e-05 loss: 0.0462 (0.0502) time: 2.8413 data: 0.0076 max mem: 33370 +Epoch: [20] [ 230/2639] eta: 1:55:37 lr: 2.6688770751542507e-05 loss: 0.0490 (0.0503) time: 2.8508 data: 0.0078 max mem: 33370 +Epoch: [20] [ 240/2639] eta: 1:55:09 lr: 2.6684199756425587e-05 loss: 0.0517 (0.0512) time: 2.8655 data: 0.0080 max mem: 33370 +Epoch: [20] [ 250/2639] eta: 1:54:41 lr: 2.667962867430589e-05 loss: 0.0498 (0.0512) time: 2.8862 data: 0.0081 max mem: 33370 +Epoch: [20] [ 260/2639] eta: 1:54:14 lr: 2.667505750516521e-05 loss: 0.0467 (0.0510) time: 2.8918 data: 0.0081 max mem: 33370 +Epoch: [20] [ 270/2639] eta: 1:53:41 lr: 2.6670486248985297e-05 loss: 0.0435 (0.0510) time: 2.8662 data: 0.0081 max mem: 33370 +Epoch: [20] [ 280/2639] eta: 1:53:12 lr: 2.6665914905747946e-05 loss: 0.0435 (0.0510) time: 2.8548 data: 0.0081 max mem: 33370 +Epoch: [20] [ 290/2639] eta: 1:52:47 lr: 2.666134347543489e-05 loss: 0.0475 (0.0512) time: 2.9000 data: 0.0083 max mem: 33370 +Epoch: [20] [ 300/2639] eta: 1:52:15 lr: 2.6656771958027903e-05 loss: 0.0368 (0.0509) time: 2.8843 data: 0.0083 max mem: 33370 +Epoch: [20] [ 310/2639] eta: 1:51:47 lr: 2.6652200353508715e-05 loss: 0.0421 (0.0508) time: 2.8662 data: 0.0085 max mem: 33370 +Epoch: [20] [ 320/2639] eta: 1:51:20 lr: 2.664762866185907e-05 loss: 0.0470 (0.0515) time: 2.9007 data: 0.0083 max mem: 33370 +Epoch: [20] [ 330/2639] eta: 1:50:52 lr: 2.664305688306069e-05 loss: 0.0495 (0.0513) time: 2.8981 data: 0.0079 max mem: 33370 +Epoch: [20] [ 340/2639] eta: 1:50:25 lr: 2.6638485017095305e-05 loss: 0.0495 (0.0513) time: 2.9002 data: 0.0080 max mem: 33370 +Epoch: [20] [ 350/2639] eta: 1:50:00 lr: 2.6633913063944623e-05 loss: 0.0513 (0.0514) time: 2.9282 data: 0.0079 max mem: 33370 +Epoch: [20] [ 360/2639] eta: 1:49:31 lr: 2.662934102359036e-05 loss: 0.0473 (0.0512) time: 2.9036 data: 0.0075 max mem: 33370 +Epoch: [20] [ 370/2639] eta: 1:48:58 lr: 2.662476889601421e-05 loss: 0.0354 (0.0511) time: 2.8464 data: 0.0074 max mem: 33370 +Epoch: [20] [ 380/2639] eta: 1:48:30 lr: 2.6620196681197868e-05 loss: 0.0429 (0.0510) time: 2.8617 data: 0.0073 max mem: 33370 +Epoch: [20] [ 390/2639] eta: 1:47:58 lr: 2.6615624379123015e-05 loss: 0.0414 (0.0507) time: 2.8569 data: 0.0073 max mem: 33370 +Epoch: [20] [ 400/2639] eta: 1:47:28 lr: 2.661105198977134e-05 loss: 0.0413 (0.0508) time: 2.8429 data: 0.0073 max mem: 33370 +Epoch: [20] [ 410/2639] eta: 1:47:00 lr: 2.6606479513124505e-05 loss: 0.0461 (0.0509) time: 2.8800 data: 0.0075 max mem: 33370 +Epoch: [20] [ 420/2639] eta: 1:46:32 lr: 2.6601906949164185e-05 loss: 0.0443 (0.0508) time: 2.8958 data: 0.0075 max mem: 33370 +Epoch: [20] [ 430/2639] eta: 1:46:03 lr: 2.6597334297872018e-05 loss: 0.0443 (0.0509) time: 2.8862 data: 0.0073 max mem: 33370 +Epoch: [20] [ 440/2639] eta: 1:45:30 lr: 2.659276155922967e-05 loss: 0.0448 (0.0508) time: 2.8328 data: 0.0076 max mem: 33370 +Epoch: [20] [ 450/2639] eta: 1:45:01 lr: 2.6588188733218768e-05 loss: 0.0448 (0.0507) time: 2.8387 data: 0.0077 max mem: 33370 +Epoch: [20] [ 460/2639] eta: 1:44:32 lr: 2.6583615819820955e-05 loss: 0.0454 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data: 0.0076 max mem: 33370 +Epoch: [20] [ 780/2639] eta: 1:29:03 lr: 2.6437236340513045e-05 loss: 0.0517 (0.0499) time: 2.8468 data: 0.0077 max mem: 33370 +Epoch: [20] [ 790/2639] eta: 1:28:32 lr: 2.643266053299544e-05 loss: 0.0568 (0.0502) time: 2.7975 data: 0.0078 max mem: 33370 +Epoch: [20] [ 800/2639] eta: 1:28:02 lr: 2.6428084637462076e-05 loss: 0.0503 (0.0503) time: 2.8104 data: 0.0081 max mem: 33370 +Epoch: [20] [ 810/2639] eta: 1:27:31 lr: 2.6423508653894318e-05 loss: 0.0434 (0.0502) time: 2.8017 data: 0.0079 max mem: 33370 +Epoch: [20] [ 820/2639] eta: 1:27:04 lr: 2.641893258227354e-05 loss: 0.0410 (0.0503) time: 2.8480 data: 0.0073 max mem: 33370 +Epoch: [20] [ 830/2639] eta: 1:26:35 lr: 2.6414356422581094e-05 loss: 0.0388 (0.0502) time: 2.8987 data: 0.0072 max mem: 33370 +Epoch: [20] [ 840/2639] eta: 1:26:07 lr: 2.6409780174798338e-05 loss: 0.0360 (0.0502) time: 2.8918 data: 0.0074 max mem: 33370 +Epoch: [20] [ 850/2639] eta: 1:25:37 lr: 2.6405203838906605e-05 loss: 0.0431 (0.0502) time: 2.8584 data: 0.0075 max mem: 33370 +Epoch: [20] [ 860/2639] eta: 1:25:09 lr: 2.640062741488724e-05 loss: 0.0449 (0.0502) time: 2.8505 data: 0.0075 max mem: 33370 +Epoch: [20] [ 870/2639] eta: 1:24:40 lr: 2.6396050902721565e-05 loss: 0.0509 (0.0503) time: 2.8989 data: 0.0079 max mem: 33370 +Epoch: [20] [ 880/2639] eta: 1:24:11 lr: 2.6391474302390906e-05 loss: 0.0528 (0.0504) time: 2.8777 data: 0.0078 max mem: 33370 +Epoch: [20] [ 890/2639] eta: 1:23:43 lr: 2.6386897613876566e-05 loss: 0.0490 (0.0504) time: 2.8618 data: 0.0079 max mem: 33370 +Epoch: [20] [ 900/2639] eta: 1:23:14 lr: 2.6382320837159868e-05 loss: 0.0501 (0.0506) time: 2.8754 data: 0.0081 max mem: 33370 +Epoch: [20] [ 910/2639] eta: 1:22:45 lr: 2.6377743972222097e-05 loss: 0.0459 (0.0505) time: 2.8782 data: 0.0084 max mem: 33370 +Epoch: [20] [ 920/2639] eta: 1:22:18 lr: 2.6373167019044546e-05 loss: 0.0453 (0.0505) time: 2.8950 data: 0.0090 max mem: 33370 +Epoch: [20] [ 930/2639] eta: 1:21:48 lr: 2.6368589977608497e-05 loss: 0.0463 (0.0505) time: 2.8827 data: 0.0086 max mem: 33370 +Epoch: [20] [ 940/2639] eta: 1:21:20 lr: 2.6364012847895237e-05 loss: 0.0436 (0.0505) time: 2.8675 data: 0.0078 max mem: 33370 +Epoch: [20] [ 950/2639] eta: 1:20:52 lr: 2.6359435629886015e-05 loss: 0.0461 (0.0508) time: 2.8945 data: 0.0078 max mem: 33370 +Epoch: [20] [ 960/2639] eta: 1:20:23 lr: 2.635485832356211e-05 loss: 0.0533 (0.0508) time: 2.8913 data: 0.0080 max mem: 33370 +Epoch: [20] [ 970/2639] eta: 1:19:54 lr: 2.635028092890476e-05 loss: 0.0464 (0.0507) time: 2.8707 data: 0.0079 max mem: 33370 +Epoch: [20] [ 980/2639] eta: 1:19:26 lr: 2.634570344589521e-05 loss: 0.0411 (0.0506) time: 2.8756 data: 0.0079 max mem: 33370 +Epoch: [20] [ 990/2639] eta: 1:18:57 lr: 2.6341125874514704e-05 loss: 0.0477 (0.0509) time: 2.8879 data: 0.0077 max mem: 33370 +Epoch: [20] [1000/2639] eta: 1:18:27 lr: 2.633654821474447e-05 loss: 0.0483 (0.0509) time: 2.8337 data: 0.0076 max mem: 33370 +Epoch: [20] 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mem: 33370 +Epoch: [20] [1090/2639] eta: 1:14:13 lr: 2.62953452961738e-05 loss: 0.0466 (0.0514) time: 2.8966 data: 0.0077 max mem: 33370 +Epoch: [20] [1100/2639] eta: 1:13:44 lr: 2.629076675147225e-05 loss: 0.0430 (0.0513) time: 2.8533 data: 0.0077 max mem: 33370 +Epoch: [20] [1110/2639] eta: 1:13:16 lr: 2.6286188118174005e-05 loss: 0.0406 (0.0512) time: 2.8772 data: 0.0077 max mem: 33370 +Epoch: [20] [1120/2639] eta: 1:12:47 lr: 2.6281609396260194e-05 loss: 0.0416 (0.0512) time: 2.8989 data: 0.0080 max mem: 33370 +Epoch: [20] [1130/2639] eta: 1:12:17 lr: 2.627703058571194e-05 loss: 0.0416 (0.0513) time: 2.8502 data: 0.0078 max mem: 33370 +Epoch: [20] [1140/2639] eta: 1:11:48 lr: 2.627245168651038e-05 loss: 0.0385 (0.0512) time: 2.8223 data: 0.0077 max mem: 33370 +Epoch: [20] [1150/2639] eta: 1:11:19 lr: 2.6267872698636624e-05 loss: 0.0317 (0.0510) time: 2.8477 data: 0.0084 max mem: 33370 +Epoch: [20] [1160/2639] eta: 1:10:50 lr: 2.6263293622071778e-05 loss: 0.0354 (0.0510) time: 2.8711 data: 0.0087 max mem: 33370 +Epoch: [20] [1170/2639] eta: 1:10:21 lr: 2.6258714456796945e-05 loss: 0.0454 (0.0510) time: 2.8535 data: 0.0081 max mem: 33370 +Epoch: [20] [1180/2639] eta: 1:09:52 lr: 2.6254135202793212e-05 loss: 0.0454 (0.0510) time: 2.8382 data: 0.0076 max mem: 33370 +Epoch: [20] [1190/2639] eta: 1:09:23 lr: 2.6249555860041663e-05 loss: 0.0436 (0.0510) time: 2.8569 data: 0.0078 max mem: 33370 +Epoch: [20] [1200/2639] eta: 1:08:54 lr: 2.624497642852338e-05 loss: 0.0419 (0.0509) time: 2.8484 data: 0.0079 max mem: 33370 +Epoch: [20] [1210/2639] eta: 1:08:25 lr: 2.624039690821943e-05 loss: 0.0384 (0.0508) time: 2.8581 data: 0.0077 max mem: 33370 +Epoch: [20] [1220/2639] eta: 1:07:57 lr: 2.6235817299110875e-05 loss: 0.0375 (0.0507) time: 2.8901 data: 0.0075 max mem: 33370 +Epoch: [20] [1230/2639] eta: 1:07:28 lr: 2.623123760117876e-05 loss: 0.0383 (0.0508) time: 2.8848 data: 0.0077 max mem: 33370 +Epoch: [20] [1240/2639] eta: 1:07:00 lr: 2.6226657814404147e-05 loss: 0.0400 (0.0507) time: 2.8960 data: 0.0079 max mem: 33370 +Epoch: [20] [1250/2639] eta: 1:06:31 lr: 2.6222077938768063e-05 loss: 0.0417 (0.0507) time: 2.8922 data: 0.0078 max mem: 33370 +Epoch: [20] [1260/2639] eta: 1:06:02 lr: 2.6217497974251542e-05 loss: 0.0391 (0.0506) time: 2.8732 data: 0.0080 max mem: 33370 +Epoch: [20] [1270/2639] eta: 1:05:34 lr: 2.62129179208356e-05 loss: 0.0484 (0.0508) time: 2.8822 data: 0.0081 max mem: 33370 +Epoch: [20] [1280/2639] eta: 1:05:05 lr: 2.6208337778501262e-05 loss: 0.0550 (0.0508) time: 2.8955 data: 0.0076 max mem: 33370 +Epoch: [20] [1290/2639] eta: 1:04:37 lr: 2.620375754722953e-05 loss: 0.0483 (0.0508) time: 2.9022 data: 0.0075 max mem: 33370 +Epoch: [20] [1300/2639] eta: 1:04:08 lr: 2.6199177227001403e-05 loss: 0.0504 (0.0509) time: 2.8849 data: 0.0076 max mem: 33370 +Epoch: [20] [1310/2639] eta: 1:03:40 lr: 2.6194596817797873e-05 loss: 0.0493 (0.0508) time: 2.8755 data: 0.0081 max mem: 33370 +Epoch: [20] [1320/2639] eta: 1:03:11 lr: 2.6190016319599926e-05 loss: 0.0455 (0.0508) time: 2.8810 data: 0.0080 max mem: 33370 +Epoch: [20] [1330/2639] eta: 1:02:42 lr: 2.618543573238853e-05 loss: 0.0484 (0.0508) time: 2.8687 data: 0.0079 max mem: 33370 +Epoch: [20] [1340/2639] eta: 1:02:14 lr: 2.618085505614467e-05 loss: 0.0484 (0.0508) time: 2.8958 data: 0.0083 max mem: 33370 +Epoch: [20] [1350/2639] eta: 1:01:45 lr: 2.617627429084929e-05 loss: 0.0566 (0.0509) time: 2.8849 data: 0.0082 max mem: 33370 +Epoch: [20] [1360/2639] eta: 1:01:16 lr: 2.6171693436483352e-05 loss: 0.0441 (0.0509) time: 2.8882 data: 0.0079 max mem: 33370 +Epoch: [20] [1370/2639] eta: 1:00:48 lr: 2.6167112493027797e-05 loss: 0.0415 (0.0509) time: 2.9013 data: 0.0077 max mem: 33370 +Epoch: [20] [1380/2639] eta: 1:00:19 lr: 2.616253146046357e-05 loss: 0.0403 (0.0508) time: 2.8686 data: 0.0081 max mem: 33370 +Epoch: [20] [1390/2639] eta: 0:59:50 lr: 2.6157950338771582e-05 loss: 0.0403 (0.0508) time: 2.8517 data: 0.0084 max mem: 33370 +Epoch: [20] [1400/2639] eta: 0:59:21 lr: 2.6153369127932774e-05 loss: 0.0401 (0.0507) time: 2.8465 data: 0.0085 max mem: 33370 +Epoch: [20] [1410/2639] eta: 0:58:52 lr: 2.6148787827928052e-05 loss: 0.0466 (0.0507) time: 2.8453 data: 0.0082 max mem: 33370 +Epoch: [20] [1420/2639] eta: 0:58:22 lr: 2.614420643873833e-05 loss: 0.0478 (0.0507) time: 2.8139 data: 0.0077 max mem: 33370 +Epoch: [20] [1430/2639] eta: 0:57:53 lr: 2.613962496034449e-05 loss: 0.0432 (0.0507) time: 2.7943 data: 0.0077 max mem: 33370 +Epoch: [20] [1440/2639] eta: 0:57:25 lr: 2.6135043392727433e-05 loss: 0.0402 (0.0506) time: 2.8547 data: 0.0075 max mem: 33370 +Epoch: [20] [1450/2639] eta: 0:56:55 lr: 2.6130461735868038e-05 loss: 0.0402 (0.0506) time: 2.8571 data: 0.0075 max mem: 33370 +Epoch: [20] [1460/2639] eta: 0:56:27 lr: 2.6125879989747187e-05 loss: 0.0486 (0.0506) time: 2.8484 data: 0.0075 max mem: 33370 +Epoch: [20] [1470/2639] eta: 0:55:58 lr: 2.6121298154345742e-05 loss: 0.0486 (0.0506) time: 2.8970 data: 0.0073 max mem: 33370 +Epoch: [20] [1480/2639] eta: 0:55:29 lr: 2.611671622964456e-05 loss: 0.0487 (0.0507) time: 2.8705 data: 0.0073 max mem: 33370 +Epoch: [20] [1490/2639] eta: 0:55:00 lr: 2.61121342156245e-05 loss: 0.0511 (0.0507) time: 2.8416 data: 0.0076 max mem: 33370 +Epoch: [20] [1500/2639] eta: 0:54:31 lr: 2.6107552112266393e-05 loss: 0.0479 (0.0506) time: 2.8232 data: 0.0079 max mem: 33370 +Epoch: [20] [1510/2639] eta: 0:54:03 lr: 2.6102969919551086e-05 loss: 0.0453 (0.0506) time: 2.8728 data: 0.0082 max mem: 33370 +Epoch: [20] [1520/2639] eta: 0:53:34 lr: 2.60983876374594e-05 loss: 0.0472 (0.0506) time: 2.8910 data: 0.0080 max mem: 33370 +Epoch: [20] [1530/2639] eta: 0:53:05 lr: 2.6093805265972165e-05 loss: 0.0382 (0.0505) time: 2.8532 data: 0.0078 max mem: 33370 +Epoch: [20] [1540/2639] eta: 0:52:37 lr: 2.608922280507018e-05 loss: 0.0380 (0.0505) time: 2.8852 data: 0.0078 max mem: 33370 +Epoch: [20] [1550/2639] eta: 0:52:08 lr: 2.6084640254734256e-05 loss: 0.0398 (0.0505) time: 2.8713 data: 0.0074 max mem: 33370 +Epoch: [20] [1560/2639] eta: 0:51:39 lr: 2.6080057614945185e-05 loss: 0.0398 (0.0505) time: 2.8350 data: 0.0074 max mem: 33370 +Epoch: [20] [1570/2639] eta: 0:51:10 lr: 2.6075474885683766e-05 loss: 0.0445 (0.0505) time: 2.8543 data: 0.0074 max mem: 33370 +Epoch: [20] [1580/2639] eta: 0:50:41 lr: 2.6070892066930764e-05 loss: 0.0442 (0.0504) time: 2.8687 data: 0.0072 max mem: 33370 +Epoch: [20] [1590/2639] eta: 0:50:13 lr: 2.6066309158666967e-05 loss: 0.0419 (0.0504) time: 2.8881 data: 0.0076 max mem: 33370 +Epoch: [20] [1600/2639] eta: 0:49:44 lr: 2.6061726160873128e-05 loss: 0.0390 (0.0504) time: 2.8905 data: 0.0076 max mem: 33370 +Epoch: [20] [1610/2639] eta: 0:49:15 lr: 2.6057143073530015e-05 loss: 0.0476 (0.0505) time: 2.8570 data: 0.0074 max mem: 33370 +Epoch: [20] [1620/2639] eta: 0:48:46 lr: 2.6052559896618368e-05 loss: 0.0467 (0.0505) time: 2.8683 data: 0.0073 max mem: 33370 +Epoch: [20] [1630/2639] eta: 0:48:18 lr: 2.6047976630118936e-05 loss: 0.0467 (0.0505) time: 2.9118 data: 0.0072 max mem: 33370 +Epoch: [20] [1640/2639] eta: 0:47:49 lr: 2.604339327401244e-05 loss: 0.0467 (0.0505) time: 2.9137 data: 0.0076 max mem: 33370 +Epoch: [20] [1650/2639] eta: 0:47:21 lr: 2.6038809828279614e-05 loss: 0.0479 (0.0504) time: 2.9013 data: 0.0078 max mem: 33370 +Epoch: [20] [1660/2639] eta: 0:46:52 lr: 2.6034226292901178e-05 loss: 0.0501 (0.0505) time: 2.8842 data: 0.0075 max mem: 33370 +Epoch: [20] [1670/2639] eta: 0:46:23 lr: 2.6029642667857836e-05 loss: 0.0487 (0.0505) time: 2.8756 data: 0.0072 max mem: 33370 +Epoch: [20] [1680/2639] eta: 0:45:54 lr: 2.602505895313029e-05 loss: 0.0433 (0.0504) time: 2.8540 data: 0.0074 max mem: 33370 +Epoch: [20] [1690/2639] eta: 0:45:26 lr: 2.6020475148699237e-05 loss: 0.0423 (0.0504) time: 2.8298 data: 0.0074 max mem: 33370 +Epoch: [20] [1700/2639] eta: 0:44:57 lr: 2.601589125454536e-05 loss: 0.0423 (0.0504) time: 2.8616 data: 0.0072 max mem: 33370 +Epoch: [20] [1710/2639] eta: 0:44:28 lr: 2.6011307270649333e-05 loss: 0.0425 (0.0504) time: 2.8303 data: 0.0077 max mem: 33370 +Epoch: [20] [1720/2639] eta: 0:43:59 lr: 2.6006723196991833e-05 loss: 0.0430 (0.0504) time: 2.7986 data: 0.0082 max mem: 33370 +Epoch: [20] [1730/2639] eta: 0:43:30 lr: 2.600213903355352e-05 loss: 0.0430 (0.0504) time: 2.8343 data: 0.0080 max mem: 33370 +Epoch: [20] [1740/2639] eta: 0:43:01 lr: 2.5997554780315053e-05 loss: 0.0438 (0.0504) time: 2.8526 data: 0.0079 max mem: 33370 +Epoch: [20] [1750/2639] eta: 0:42:32 lr: 2.5992970437257064e-05 loss: 0.0438 (0.0504) time: 2.8672 data: 0.0082 max mem: 33370 +Epoch: [20] [1760/2639] eta: 0:42:04 lr: 2.59883860043602e-05 loss: 0.0395 (0.0504) time: 2.8865 data: 0.0083 max mem: 33370 +Epoch: [20] [1770/2639] eta: 0:41:35 lr: 2.598380148160509e-05 loss: 0.0479 (0.0504) time: 2.8877 data: 0.0080 max mem: 33370 +Epoch: [20] [1780/2639] eta: 0:41:06 lr: 2.597921686897236e-05 loss: 0.0396 (0.0503) time: 2.8887 data: 0.0079 max mem: 33370 +Epoch: [20] [1790/2639] eta: 0:40:38 lr: 2.5974632166442616e-05 loss: 0.0350 (0.0503) time: 2.9157 data: 0.0082 max mem: 33370 +Epoch: [20] [1800/2639] eta: 0:40:09 lr: 2.597004737399647e-05 loss: 0.0413 (0.0503) time: 2.8846 data: 0.0083 max mem: 33370 +Epoch: [20] [1810/2639] eta: 0:39:41 lr: 2.596546249161451e-05 loss: 0.0464 (0.0503) time: 2.8683 data: 0.0078 max mem: 33370 +Epoch: [20] [1820/2639] eta: 0:39:12 lr: 2.5960877519277348e-05 loss: 0.0457 (0.0503) time: 2.8587 data: 0.0074 max mem: 33370 +Epoch: [20] [1830/2639] eta: 0:38:43 lr: 2.5956292456965543e-05 loss: 0.0466 (0.0503) time: 2.8308 data: 0.0076 max mem: 33370 +Epoch: [20] [1840/2639] eta: 0:38:14 lr: 2.5951707304659682e-05 loss: 0.0514 (0.0503) time: 2.8639 data: 0.0076 max mem: 33370 +Epoch: [20] [1850/2639] eta: 0:37:45 lr: 2.594712206234033e-05 loss: 0.0415 (0.0504) time: 2.8803 data: 0.0072 max mem: 33370 +Epoch: [20] [1860/2639] eta: 0:37:17 lr: 2.5942536729988037e-05 loss: 0.0405 (0.0504) time: 2.8702 data: 0.0075 max mem: 33370 +Epoch: [20] [1870/2639] eta: 0:36:48 lr: 2.593795130758336e-05 loss: 0.0500 (0.0505) time: 2.8474 data: 0.0076 max mem: 33370 +Epoch: [20] [1880/2639] eta: 0:36:19 lr: 2.5933365795106845e-05 loss: 0.0464 (0.0504) time: 2.8413 data: 0.0074 max mem: 33370 +Epoch: [20] [1890/2639] eta: 0:35:50 lr: 2.5928780192539015e-05 loss: 0.0477 (0.0505) time: 2.8454 data: 0.0074 max mem: 33370 +Epoch: [20] [1900/2639] eta: 0:35:21 lr: 2.5924194499860405e-05 loss: 0.0512 (0.0504) time: 2.8611 data: 0.0076 max mem: 33370 +Epoch: [20] [1910/2639] eta: 0:34:53 lr: 2.5919608717051523e-05 loss: 0.0384 (0.0504) time: 2.8737 data: 0.0077 max mem: 33370 +Epoch: [20] [1920/2639] eta: 0:34:24 lr: 2.5915022844092894e-05 loss: 0.0405 (0.0504) time: 2.8516 data: 0.0080 max mem: 33370 +Epoch: [20] [1930/2639] eta: 0:33:55 lr: 2.5910436880965006e-05 loss: 0.0443 (0.0504) time: 2.8291 data: 0.0080 max mem: 33370 +Epoch: [20] [1940/2639] eta: 0:33:26 lr: 2.590585082764836e-05 loss: 0.0426 (0.0504) time: 2.8051 data: 0.0080 max mem: 33370 +Epoch: [20] [1950/2639] eta: 0:32:57 lr: 2.590126468412344e-05 loss: 0.0351 (0.0504) time: 2.8268 data: 0.0080 max mem: 33370 +Epoch: [20] [1960/2639] eta: 0:32:28 lr: 2.5896678450370713e-05 loss: 0.0434 (0.0504) time: 2.8540 data: 0.0076 max mem: 33370 +Epoch: [20] [1970/2639] eta: 0:32:00 lr: 2.5892092126370675e-05 loss: 0.0567 (0.0504) time: 2.8412 data: 0.0077 max mem: 33370 +Epoch: [20] [1980/2639] eta: 0:31:31 lr: 2.5887505712103766e-05 loss: 0.0544 (0.0504) time: 2.8675 data: 0.0075 max mem: 33370 +Epoch: [20] [1990/2639] eta: 0:31:02 lr: 2.5882919207550443e-05 loss: 0.0421 (0.0504) time: 2.8965 data: 0.0074 max mem: 33370 +Epoch: [20] [2000/2639] eta: 0:30:34 lr: 2.5878332612691152e-05 loss: 0.0418 (0.0504) time: 2.8877 data: 0.0079 max mem: 33370 +Epoch: [20] [2010/2639] eta: 0:30:05 lr: 2.5873745927506338e-05 loss: 0.0443 (0.0505) time: 2.8911 data: 0.0079 max mem: 33370 +Epoch: [20] [2020/2639] eta: 0:29:36 lr: 2.5869159151976417e-05 loss: 0.0511 (0.0505) time: 2.8763 data: 0.0075 max mem: 33370 +Epoch: [20] [2030/2639] eta: 0:29:08 lr: 2.5864572286081827e-05 loss: 0.0516 (0.0506) time: 2.8499 data: 0.0076 max mem: 33370 +Epoch: [20] [2040/2639] eta: 0:28:39 lr: 2.585998532980296e-05 loss: 0.0535 (0.0505) time: 2.8697 data: 0.0082 max mem: 33370 +Epoch: [20] [2050/2639] eta: 0:28:10 lr: 2.5855398283120242e-05 loss: 0.0391 (0.0505) time: 2.8814 data: 0.0080 max mem: 33370 +Epoch: [20] [2060/2639] eta: 0:27:42 lr: 2.5850811146014047e-05 loss: 0.0387 (0.0505) time: 2.8742 data: 0.0077 max mem: 33370 +Epoch: [20] [2070/2639] eta: 0:27:13 lr: 2.584622391846479e-05 loss: 0.0466 (0.0505) time: 2.8829 data: 0.0077 max mem: 33370 +Epoch: [20] [2080/2639] eta: 0:26:44 lr: 2.584163660045283e-05 loss: 0.0454 (0.0504) time: 2.8807 data: 0.0079 max mem: 33370 +Epoch: [20] [2090/2639] eta: 0:26:16 lr: 2.5837049191958544e-05 loss: 0.0413 (0.0504) time: 2.8782 data: 0.0078 max mem: 33370 +Epoch: [20] [2100/2639] eta: 0:25:47 lr: 2.5832461692962306e-05 loss: 0.0425 (0.0504) time: 2.8555 data: 0.0079 max mem: 33370 +Epoch: [20] [2110/2639] eta: 0:25:18 lr: 2.5827874103444467e-05 loss: 0.0439 (0.0504) time: 2.8267 data: 0.0082 max mem: 33370 +Epoch: [20] [2120/2639] eta: 0:24:49 lr: 2.5823286423385362e-05 loss: 0.0430 (0.0504) time: 2.8416 data: 0.0078 max mem: 33370 +Epoch: [20] [2130/2639] eta: 0:24:20 lr: 2.5818698652765357e-05 loss: 0.0411 (0.0504) time: 2.8519 data: 0.0073 max mem: 33370 +Epoch: [20] [2140/2639] eta: 0:23:52 lr: 2.5814110791564756e-05 loss: 0.0441 (0.0504) time: 2.8524 data: 0.0074 max mem: 33370 +Epoch: [20] [2150/2639] eta: 0:23:23 lr: 2.5809522839763905e-05 loss: 0.0497 (0.0504) time: 2.8390 data: 0.0075 max mem: 33370 +Epoch: [20] [2160/2639] eta: 0:22:54 lr: 2.5804934797343105e-05 loss: 0.0501 (0.0504) time: 2.8302 data: 0.0078 max mem: 33370 +Epoch: [20] [2170/2639] eta: 0:22:25 lr: 2.5800346664282675e-05 loss: 0.0427 (0.0504) time: 2.8775 data: 0.0079 max mem: 33370 +Epoch: [20] [2180/2639] eta: 0:21:57 lr: 2.57957584405629e-05 loss: 0.0379 (0.0504) time: 2.9280 data: 0.0077 max mem: 33370 +Epoch: [20] [2190/2639] eta: 0:21:28 lr: 2.5791170126164083e-05 loss: 0.0403 (0.0504) time: 2.9137 data: 0.0081 max mem: 33370 +Epoch: [20] [2200/2639] eta: 0:21:00 lr: 2.5786581721066493e-05 loss: 0.0399 (0.0503) time: 2.8757 data: 0.0083 max mem: 33370 +Epoch: [20] [2210/2639] eta: 0:20:31 lr: 2.5781993225250424e-05 loss: 0.0401 (0.0504) time: 2.8885 data: 0.0076 max mem: 33370 +Epoch: [20] [2220/2639] eta: 0:20:02 lr: 2.577740463869613e-05 loss: 0.0471 (0.0504) time: 2.8847 data: 0.0075 max mem: 33370 +Epoch: [20] [2230/2639] eta: 0:19:34 lr: 2.577281596138386e-05 loss: 0.0462 (0.0504) time: 2.8796 data: 0.0076 max mem: 33370 +Epoch: [20] [2240/2639] eta: 0:19:05 lr: 2.5768227193293886e-05 loss: 0.0444 (0.0504) time: 2.8978 data: 0.0072 max mem: 33370 +Epoch: [20] [2250/2639] eta: 0:18:36 lr: 2.5763638334406438e-05 loss: 0.0457 (0.0504) time: 2.8697 data: 0.0073 max mem: 33370 +Epoch: [20] [2260/2639] eta: 0:18:07 lr: 2.575904938470175e-05 loss: 0.0470 (0.0504) time: 2.8762 data: 0.0078 max mem: 33370 +Epoch: [20] [2270/2639] eta: 0:17:39 lr: 2.5754460344160043e-05 loss: 0.0470 (0.0503) time: 2.8543 data: 0.0078 max mem: 33370 +Epoch: [20] [2280/2639] eta: 0:17:10 lr: 2.574987121276154e-05 loss: 0.0451 (0.0503) time: 2.8426 data: 0.0078 max mem: 33370 +Epoch: [20] [2290/2639] eta: 0:16:41 lr: 2.574528199048644e-05 loss: 0.0451 (0.0503) time: 2.8906 data: 0.0079 max mem: 33370 +Epoch: [20] [2300/2639] eta: 0:16:13 lr: 2.5740692677314965e-05 loss: 0.0425 (0.0503) time: 2.8901 data: 0.0078 max mem: 33370 +Epoch: [20] [2310/2639] eta: 0:15:44 lr: 2.5736103273227286e-05 loss: 0.0389 (0.0503) time: 2.8488 data: 0.0078 max mem: 33370 +Epoch: [20] [2320/2639] eta: 0:15:15 lr: 2.5731513778203597e-05 loss: 0.0410 (0.0503) time: 2.8591 data: 0.0077 max mem: 33370 +Epoch: [20] [2330/2639] eta: 0:14:46 lr: 2.5726924192224073e-05 loss: 0.0443 (0.0503) time: 2.8841 data: 0.0078 max mem: 33370 +Epoch: [20] [2340/2639] eta: 0:14:18 lr: 2.572233451526888e-05 loss: 0.0455 (0.0503) time: 2.8576 data: 0.0079 max mem: 33370 +Epoch: [20] [2350/2639] eta: 0:13:49 lr: 2.571774474731818e-05 loss: 0.0436 (0.0504) time: 2.8747 data: 0.0077 max mem: 33370 +Epoch: [20] [2360/2639] eta: 0:13:20 lr: 2.571315488835212e-05 loss: 0.0407 (0.0504) time: 2.9049 data: 0.0074 max mem: 33370 +Epoch: [20] [2370/2639] eta: 0:12:52 lr: 2.570856493835084e-05 loss: 0.0470 (0.0504) time: 2.8949 data: 0.0074 max mem: 33370 +Epoch: [20] [2380/2639] eta: 0:12:23 lr: 2.5703974897294485e-05 loss: 0.0477 (0.0504) time: 2.8816 data: 0.0077 max mem: 33370 +Epoch: [20] [2390/2639] eta: 0:11:54 lr: 2.569938476516317e-05 loss: 0.0391 (0.0504) time: 2.8587 data: 0.0079 max mem: 33370 +Epoch: [20] [2400/2639] eta: 0:11:26 lr: 2.569479454193703e-05 loss: 0.0440 (0.0504) time: 2.8262 data: 0.0080 max mem: 33370 +Epoch: [20] [2410/2639] eta: 0:10:57 lr: 2.5690204227596155e-05 loss: 0.0414 (0.0504) time: 2.8226 data: 0.0080 max mem: 33370 +Epoch: [20] [2420/2639] eta: 0:10:28 lr: 2.5685613822120657e-05 loss: 0.0386 (0.0504) time: 2.8583 data: 0.0081 max mem: 33370 +Epoch: [20] [2430/2639] eta: 0:09:59 lr: 2.568102332549062e-05 loss: 0.0466 (0.0504) time: 2.8336 data: 0.0079 max mem: 33370 +Epoch: [20] [2440/2639] eta: 0:09:31 lr: 2.5676432737686145e-05 loss: 0.0412 (0.0504) time: 2.7921 data: 0.0074 max mem: 33370 +Epoch: [20] [2450/2639] eta: 0:09:02 lr: 2.5671842058687296e-05 loss: 0.0456 (0.0504) time: 2.8020 data: 0.0073 max mem: 33370 +Epoch: [20] [2460/2639] eta: 0:08:33 lr: 2.5667251288474143e-05 loss: 0.0464 (0.0504) time: 2.8280 data: 0.0077 max mem: 33370 +Epoch: [20] [2470/2639] eta: 0:08:04 lr: 2.5662660427026746e-05 loss: 0.0469 (0.0504) time: 2.8814 data: 0.0079 max mem: 33370 +Epoch: [20] [2480/2639] eta: 0:07:36 lr: 2.5658069474325158e-05 loss: 0.0511 (0.0505) time: 2.8493 data: 0.0079 max mem: 33370 +Epoch: [20] [2490/2639] eta: 0:07:07 lr: 2.5653478430349425e-05 loss: 0.0504 (0.0505) time: 2.8293 data: 0.0077 max mem: 33370 +Epoch: [20] [2500/2639] eta: 0:06:38 lr: 2.5648887295079576e-05 loss: 0.0552 (0.0505) time: 2.8541 data: 0.0078 max mem: 33370 +Epoch: [20] [2510/2639] eta: 0:06:10 lr: 2.5644296068495648e-05 loss: 0.0473 (0.0505) time: 2.8721 data: 0.0080 max mem: 33370 +Epoch: [20] [2520/2639] eta: 0:05:41 lr: 2.5639704750577642e-05 loss: 0.0414 (0.0505) time: 2.9229 data: 0.0080 max mem: 33370 +Epoch: [20] [2530/2639] eta: 0:05:12 lr: 2.5635113341305584e-05 loss: 0.0478 (0.0505) time: 2.9008 data: 0.0078 max mem: 33370 +Epoch: [20] [2540/2639] eta: 0:04:44 lr: 2.5630521840659467e-05 loss: 0.0523 (0.0505) time: 2.8589 data: 0.0075 max mem: 33370 +Epoch: [20] [2550/2639] eta: 0:04:15 lr: 2.5625930248619285e-05 loss: 0.0446 (0.0505) time: 2.8392 data: 0.0077 max mem: 33370 +Epoch: [20] [2560/2639] eta: 0:03:46 lr: 2.562133856516502e-05 loss: 0.0467 (0.0505) time: 2.8445 data: 0.0083 max mem: 33370 +Epoch: [20] [2570/2639] eta: 0:03:17 lr: 2.5616746790276662e-05 loss: 0.0432 (0.0505) time: 2.8637 data: 0.0077 max mem: 33370 +Epoch: [20] [2580/2639] eta: 0:02:49 lr: 2.5612154923934163e-05 loss: 0.0416 (0.0505) time: 2.8655 data: 0.0074 max mem: 33370 +Epoch: [20] [2590/2639] eta: 0:02:20 lr: 2.5607562966117494e-05 loss: 0.0455 (0.0505) time: 2.8786 data: 0.0080 max mem: 33370 +Epoch: [20] [2600/2639] eta: 0:01:51 lr: 2.560297091680659e-05 loss: 0.0478 (0.0505) time: 2.8808 data: 0.0080 max mem: 33370 +Epoch: [20] [2610/2639] eta: 0:01:23 lr: 2.559837877598142e-05 loss: 0.0488 (0.0505) time: 2.8856 data: 0.0076 max mem: 33370 +Epoch: [20] [2620/2639] eta: 0:00:54 lr: 2.559378654362189e-05 loss: 0.0489 (0.0505) time: 2.8945 data: 0.0074 max mem: 33370 +Epoch: [20] [2630/2639] eta: 0:00:25 lr: 2.5589194219707952e-05 loss: 0.0408 (0.0505) time: 2.8921 data: 0.0073 max mem: 33370 +Epoch: [20] Total time: 2:06:13 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 2:18:49 time: 3.2373 data: 3.1487 max mem: 33370 +Test: [ 100/2573] eta: 0:04:27 time: 0.0773 data: 0.0015 max mem: 33370 +Test: [ 200/2573] eta: 0:03:42 time: 0.0781 data: 0.0013 max mem: 33370 +Test: [ 300/2573] eta: 0:03:20 time: 0.0795 data: 0.0014 max mem: 33370 +Test: [ 400/2573] eta: 0:03:06 time: 0.0802 data: 0.0013 max mem: 33370 +Test: [ 500/2573] eta: 0:02:54 time: 0.0783 data: 0.0014 max mem: 33370 +Test: [ 600/2573] eta: 0:02:44 time: 0.0794 data: 0.0015 max mem: 33370 +Test: [ 700/2573] eta: 0:02:35 time: 0.0787 data: 0.0014 max mem: 33370 +Test: [ 800/2573] eta: 0:02:26 time: 0.0817 data: 0.0013 max mem: 33370 +Test: [ 900/2573] eta: 0:02:17 time: 0.0788 data: 0.0013 max mem: 33370 +Test: [1000/2573] eta: 0:02:08 time: 0.0785 data: 0.0013 max mem: 33370 +Test: [1100/2573] eta: 0:02:00 time: 0.0784 data: 0.0013 max mem: 33370 +Test: [1200/2573] eta: 0:01:51 time: 0.0788 data: 0.0014 max mem: 33370 +Test: [1300/2573] eta: 0:01:43 time: 0.0787 data: 0.0014 max mem: 33370 +Test: [1400/2573] eta: 0:01:35 time: 0.0768 data: 0.0014 max mem: 33370 +Test: [1500/2573] eta: 0:01:26 time: 0.0795 data: 0.0014 max mem: 33370 +Test: [1600/2573] eta: 0:01:18 time: 0.0815 data: 0.0013 max mem: 33370 +Test: [1700/2573] eta: 0:01:10 time: 0.0771 data: 0.0014 max mem: 33370 +Test: [1800/2573] eta: 0:01:02 time: 0.0811 data: 0.0014 max mem: 33370 +Test: [1900/2573] eta: 0:00:54 time: 0.0786 data: 0.0014 max mem: 33370 +Test: [2000/2573] eta: 0:00:46 time: 0.0802 data: 0.0014 max mem: 33370 +Test: [2100/2573] eta: 0:00:38 time: 0.0811 data: 0.0013 max mem: 33370 +Test: [2200/2573] eta: 0:00:29 time: 0.0820 data: 0.0014 max mem: 33370 +Test: [2300/2573] eta: 0:00:21 time: 0.0813 data: 0.0014 max mem: 33370 +Test: [2400/2573] eta: 0:00:13 time: 0.0763 data: 0.0014 max mem: 33370 +Test: [2500/2573] eta: 0:00:05 time: 0.0800 data: 0.0013 max mem: 33370 +Test: Total time: 0:03:27 +Final results: +Mean IoU is 63.50 + + precision@0.5 = 71.75 + precision@0.6 = 66.03 + precision@0.7 = 58.97 + precision@0.8 = 46.83 + precision@0.9 = 23.06 + overall IoU = 61.45 + +Average object IoU 63.500738322900595 +Overall IoU 61.44724655151367 +Better epoch: 20 + +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [21] [ 0/2639] eta: 3:41:56 lr: 2.558506104988977e-05 loss: 0.0305 (0.0305) time: 5.0461 data: 2.2222 max mem: 33370 +Epoch: [21] [ 10/2639] eta: 2:14:16 lr: 2.558046855196709e-05 loss: 0.0422 (0.0478) time: 3.0643 data: 0.2091 max mem: 33370 +Epoch: [21] [ 20/2639] eta: 2:09:40 lr: 2.557587596243174e-05 loss: 0.0422 (0.0498) time: 2.8669 data: 0.0075 max mem: 33370 +Epoch: [21] [ 30/2639] eta: 2:07:28 lr: 2.5571283281263586e-05 loss: 0.0400 (0.0486) time: 2.8589 data: 0.0075 max mem: 33370 +Epoch: [21] [ 40/2639] eta: 2:05:46 lr: 2.5566690508442538e-05 loss: 0.0396 (0.0470) time: 2.8332 data: 0.0079 max mem: 33370 +Epoch: [21] [ 50/2639] eta: 2:04:36 lr: 2.556209764394846e-05 loss: 0.0370 (0.0466) time: 2.8192 data: 0.0076 max mem: 33370 +Epoch: [21] [ 60/2639] eta: 2:03:41 lr: 2.555750468776122e-05 loss: 0.0361 (0.0465) time: 2.8242 data: 0.0072 max mem: 33370 +Epoch: [21] [ 70/2639] eta: 2:03:09 lr: 2.5552911639860676e-05 loss: 0.0382 (0.0461) time: 2.8481 data: 0.0072 max mem: 33370 +Epoch: [21] [ 80/2639] eta: 2:02:50 lr: 2.5548318500226688e-05 loss: 0.0460 (0.0463) time: 2.8882 data: 0.0072 max mem: 33370 +Epoch: [21] [ 90/2639] eta: 2:02:20 lr: 2.554372526883909e-05 loss: 0.0433 (0.0460) time: 2.8919 data: 0.0073 max mem: 33370 +Epoch: [21] [ 100/2639] eta: 2:02:08 lr: 2.553913194567772e-05 loss: 0.0431 (0.0468) time: 2.9121 data: 0.0074 max mem: 33370 +Epoch: [21] [ 110/2639] eta: 2:01:35 lr: 2.5534538530722406e-05 loss: 0.0438 (0.0487) time: 2.9074 data: 0.0076 max mem: 33370 +Epoch: [21] [ 120/2639] eta: 2:00:53 lr: 2.552994502395296e-05 loss: 0.0390 (0.0478) time: 2.8440 data: 0.0080 max mem: 33370 +Epoch: [21] [ 130/2639] eta: 2:00:38 lr: 2.5525351425349203e-05 loss: 0.0360 (0.0478) time: 2.8852 data: 0.0082 max mem: 33370 +Epoch: [21] [ 140/2639] eta: 1:59:57 lr: 2.5520757734890915e-05 loss: 0.0450 (0.0480) time: 2.8842 data: 0.0080 max mem: 33370 +Epoch: [21] [ 150/2639] eta: 1:59:26 lr: 2.5516163952557904e-05 loss: 0.0448 (0.0475) time: 2.8435 data: 0.0077 max mem: 33370 +Epoch: [21] [ 160/2639] eta: 1:58:59 lr: 2.5511570078329944e-05 loss: 0.0454 (0.0493) time: 2.8798 data: 0.0075 max mem: 33370 +Epoch: [21] [ 170/2639] eta: 1:58:15 lr: 2.5506976112186816e-05 loss: 0.0471 (0.0492) time: 2.8314 data: 0.0076 max mem: 33370 +Epoch: [21] [ 180/2639] eta: 1:57:42 lr: 2.550238205410828e-05 loss: 0.0442 (0.0492) time: 2.8065 data: 0.0076 max mem: 33370 +Epoch: [21] [ 190/2639] eta: 1:57:02 lr: 2.5497787904074104e-05 loss: 0.0409 (0.0492) time: 2.8141 data: 0.0078 max mem: 33370 +Epoch: [21] [ 200/2639] eta: 1:56:32 lr: 2.5493193662064024e-05 loss: 0.0405 (0.0493) time: 2.8194 data: 0.0083 max mem: 33370 +Epoch: [21] [ 210/2639] eta: 1:56:04 lr: 2.5488599328057794e-05 loss: 0.0381 (0.0486) time: 2.8636 data: 0.0081 max mem: 33370 +Epoch: [21] [ 220/2639] eta: 1:55:37 lr: 2.5484004902035136e-05 loss: 0.0390 (0.0485) time: 2.8784 data: 0.0076 max mem: 33370 +Epoch: [21] [ 230/2639] eta: 1:55:04 lr: 2.5479410383975782e-05 loss: 0.0424 (0.0484) time: 2.8529 data: 0.0079 max mem: 33370 +Epoch: [21] [ 240/2639] eta: 1:54:29 lr: 2.547481577385944e-05 loss: 0.0412 (0.0483) time: 2.8150 data: 0.0081 max mem: 33370 +Epoch: [21] [ 250/2639] eta: 1:53:52 lr: 2.5470221071665824e-05 loss: 0.0400 (0.0479) time: 2.7929 data: 0.0079 max mem: 33370 +Epoch: [21] [ 260/2639] eta: 1:53:23 lr: 2.5465626277374617e-05 loss: 0.0427 (0.0479) time: 2.8164 data: 0.0078 max mem: 33370 +Epoch: [21] [ 270/2639] eta: 1:52:54 lr: 2.546103139096553e-05 loss: 0.0394 (0.0477) time: 2.8527 data: 0.0078 max mem: 33370 +Epoch: [21] [ 280/2639] eta: 1:52:21 lr: 2.545643641241823e-05 loss: 0.0389 (0.0475) time: 2.8340 data: 0.0074 max mem: 33370 +Epoch: [21] [ 290/2639] eta: 1:51:54 lr: 2.545184134171239e-05 loss: 0.0424 (0.0478) time: 2.8448 data: 0.0073 max mem: 33370 +Epoch: [21] [ 300/2639] eta: 1:51:23 lr: 2.5447246178827678e-05 loss: 0.0373 (0.0474) time: 2.8520 data: 0.0073 max mem: 33370 +Epoch: [21] [ 310/2639] eta: 1:50:55 lr: 2.5442650923743754e-05 loss: 0.0355 (0.0471) time: 2.8456 data: 0.0072 max mem: 33370 +Epoch: [21] [ 320/2639] eta: 1:50:28 lr: 2.543805557644025e-05 loss: 0.0446 (0.0474) time: 2.8679 data: 0.0076 max mem: 33370 +Epoch: [21] [ 330/2639] eta: 1:50:01 lr: 2.5433460136896818e-05 loss: 0.0518 (0.0477) time: 2.8798 data: 0.0078 max mem: 33370 +Epoch: [21] [ 340/2639] eta: 1:49:35 lr: 2.5428864605093085e-05 loss: 0.0446 (0.0482) time: 2.8929 data: 0.0075 max mem: 33370 +Epoch: [21] [ 350/2639] eta: 1:49:04 lr: 2.5424268981008666e-05 loss: 0.0443 (0.0483) time: 2.8569 data: 0.0072 max mem: 33370 +Epoch: [21] [ 360/2639] eta: 1:48:39 lr: 2.541967326462318e-05 loss: 0.0430 (0.0482) time: 2.8645 data: 0.0078 max mem: 33370 +Epoch: [21] [ 370/2639] eta: 1:48:12 lr: 2.541507745591622e-05 loss: 0.0385 (0.0479) time: 2.9034 data: 0.0081 max mem: 33370 +Epoch: [21] [ 380/2639] eta: 1:47:40 lr: 2.54104815548674e-05 loss: 0.0473 (0.0482) time: 2.8485 data: 0.0082 max mem: 33370 +Epoch: [21] [ 390/2639] eta: 1:47:12 lr: 2.540588556145629e-05 loss: 0.0473 (0.0480) time: 2.8364 data: 0.0082 max mem: 33370 +Epoch: [21] [ 400/2639] eta: 1:46:42 lr: 2.5401289475662475e-05 loss: 0.0375 (0.0479) time: 2.8558 data: 0.0079 max mem: 33370 +Epoch: [21] [ 410/2639] eta: 1:46:13 lr: 2.5396693297465524e-05 loss: 0.0368 (0.0478) time: 2.8424 data: 0.0085 max mem: 33370 +Epoch: [21] [ 420/2639] eta: 1:45:45 lr: 2.5392097026844997e-05 loss: 0.0461 (0.0480) time: 2.8545 data: 0.0081 max mem: 33370 +Epoch: [21] [ 430/2639] eta: 1:45:18 lr: 2.5387500663780446e-05 loss: 0.0537 (0.0480) time: 2.8835 data: 0.0079 max mem: 33370 +Epoch: [21] [ 440/2639] eta: 1:44:49 lr: 2.5382904208251413e-05 loss: 0.0445 (0.0480) time: 2.8789 data: 0.0082 max mem: 33370 +Epoch: [21] [ 450/2639] eta: 1:44:21 lr: 2.5378307660237432e-05 loss: 0.0397 (0.0479) time: 2.8610 data: 0.0079 max mem: 33370 +Epoch: [21] [ 460/2639] eta: 1:43:52 lr: 2.5373711019718037e-05 loss: 0.0398 (0.0479) time: 2.8588 data: 0.0076 max mem: 33370 +Epoch: [21] [ 470/2639] eta: 1:43:21 lr: 2.5369114286672733e-05 loss: 0.0398 (0.0477) time: 2.8339 data: 0.0079 max mem: 33370 +Epoch: [21] [ 480/2639] eta: 1:42:50 lr: 2.5364517461081044e-05 loss: 0.0418 (0.0477) time: 2.8128 data: 0.0082 max mem: 33370 +Epoch: [21] [ 490/2639] eta: 1:42:19 lr: 2.5359920542922456e-05 loss: 0.0539 (0.0479) time: 2.8060 data: 0.0076 max mem: 33370 +Epoch: [21] [ 500/2639] eta: 1:41:51 lr: 2.5355323532176473e-05 loss: 0.0544 (0.0480) time: 2.8261 data: 0.0075 max mem: 33370 +Epoch: [21] [ 510/2639] eta: 1:41:17 lr: 2.5350726428822565e-05 loss: 0.0426 (0.0479) time: 2.7999 data: 0.0078 max mem: 33370 +Epoch: [21] [ 520/2639] eta: 1:40:49 lr: 2.5346129232840216e-05 loss: 0.0407 (0.0477) time: 2.8081 data: 0.0078 max mem: 33370 +Epoch: [21] [ 530/2639] eta: 1:40:21 lr: 2.534153194420888e-05 loss: 0.0378 (0.0477) time: 2.8628 data: 0.0076 max mem: 33370 +Epoch: [21] [ 540/2639] eta: 1:39:54 lr: 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eta: 1:17:44 lr: 2.5120752730043935e-05 loss: 0.0397 (0.0482) time: 2.9060 data: 0.0078 max mem: 33370 +Epoch: [21] [1020/2639] eta: 1:17:15 lr: 2.511615087627545e-05 loss: 0.0401 (0.0481) time: 2.8685 data: 0.0076 max mem: 33370 +Epoch: [21] [1030/2639] eta: 1:16:47 lr: 2.5111548928820066e-05 loss: 0.0446 (0.0483) time: 2.8575 data: 0.0075 max mem: 33370 +Epoch: [21] [1040/2639] eta: 1:16:20 lr: 2.5106946887656797e-05 loss: 0.0455 (0.0483) time: 2.9098 data: 0.0078 max mem: 33370 +Epoch: [21] [1050/2639] eta: 1:15:52 lr: 2.510234475276464e-05 loss: 0.0384 (0.0482) time: 2.9335 data: 0.0082 max mem: 33370 +Epoch: [21] [1060/2639] eta: 1:15:23 lr: 2.50977425241226e-05 loss: 0.0379 (0.0481) time: 2.8989 data: 0.0088 max mem: 33370 +Epoch: [21] [1070/2639] eta: 1:14:54 lr: 2.5093140201709663e-05 loss: 0.0430 (0.0481) time: 2.8361 data: 0.0083 max mem: 33370 +Epoch: [21] [1080/2639] eta: 1:14:25 lr: 2.5088537785504813e-05 loss: 0.0451 (0.0481) time: 2.8383 data: 0.0078 max mem: 33370 +Epoch: [21] [1090/2639] eta: 1:13:56 lr: 2.508393527548702e-05 loss: 0.0431 (0.0481) time: 2.8447 data: 0.0078 max mem: 33370 +Epoch: [21] [1100/2639] eta: 1:13:26 lr: 2.5079332671635236e-05 loss: 0.0387 (0.0480) time: 2.8028 data: 0.0074 max mem: 33370 +Epoch: [21] [1110/2639] eta: 1:12:58 lr: 2.5074729973928425e-05 loss: 0.0397 (0.0479) time: 2.8332 data: 0.0072 max mem: 33370 +Epoch: [21] [1120/2639] eta: 1:12:30 lr: 2.5070127182345515e-05 loss: 0.0422 (0.0480) time: 2.8906 data: 0.0074 max mem: 33370 +Epoch: [21] [1130/2639] eta: 1:12:02 lr: 2.5065524296865456e-05 loss: 0.0449 (0.0480) time: 2.9135 data: 0.0077 max mem: 33370 +Epoch: [21] [1140/2639] eta: 1:11:32 lr: 2.5060921317467166e-05 loss: 0.0426 (0.0480) time: 2.8433 data: 0.0078 max mem: 33370 +Epoch: [21] [1150/2639] eta: 1:11:02 lr: 2.505631824412956e-05 loss: 0.0416 (0.0480) time: 2.7812 data: 0.0078 max mem: 33370 +Epoch: [21] [1160/2639] eta: 1:10:33 lr: 2.505171507683155e-05 loss: 0.0442 (0.0480) time: 2.7987 data: 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(0.0478) time: 2.9034 data: 0.0079 max mem: 33370 +Epoch: [21] [1250/2639] eta: 1:06:16 lr: 2.5010282339446306e-05 loss: 0.0395 (0.0479) time: 2.8930 data: 0.0079 max mem: 33370 +Epoch: [21] [1260/2639] eta: 1:05:47 lr: 2.5005678231382113e-05 loss: 0.0470 (0.0480) time: 2.8503 data: 0.0075 max mem: 33370 +Epoch: [21] [1270/2639] eta: 1:05:19 lr: 2.50010740291249e-05 loss: 0.0478 (0.0479) time: 2.8762 data: 0.0075 max mem: 33370 +Epoch: [21] [1280/2639] eta: 1:04:50 lr: 2.4996469732653452e-05 loss: 0.0429 (0.0479) time: 2.9113 data: 0.0077 max mem: 33370 +Epoch: [21] [1290/2639] eta: 1:04:21 lr: 2.499186534194657e-05 loss: 0.0399 (0.0479) time: 2.8484 data: 0.0077 max mem: 33370 +Epoch: [21] [1300/2639] eta: 1:03:52 lr: 2.498726085698302e-05 loss: 0.0424 (0.0479) time: 2.8076 data: 0.0080 max mem: 33370 +Epoch: [21] [1310/2639] eta: 1:03:23 lr: 2.498265627774158e-05 loss: 0.0452 (0.0480) time: 2.8221 data: 0.0080 max mem: 33370 +Epoch: [21] [1320/2639] eta: 1:02:54 lr: 2.4978051604201015e-05 loss: 0.0503 (0.0480) time: 2.8285 data: 0.0075 max mem: 33370 +Epoch: [21] [1330/2639] eta: 1:02:25 lr: 2.4973446836340074e-05 loss: 0.0451 (0.0481) time: 2.8468 data: 0.0075 max mem: 33370 +Epoch: [21] [1340/2639] eta: 1:01:57 lr: 2.4968841974137504e-05 loss: 0.0483 (0.0481) time: 2.8558 data: 0.0076 max mem: 33370 +Epoch: [21] [1350/2639] eta: 1:01:29 lr: 2.4964237017572032e-05 loss: 0.0453 (0.0481) time: 2.8891 data: 0.0075 max mem: 33370 +Epoch: [21] [1360/2639] eta: 1:01:00 lr: 2.4959631966622394e-05 loss: 0.0455 (0.0482) time: 2.8833 data: 0.0072 max mem: 33370 +Epoch: [21] [1370/2639] eta: 1:00:31 lr: 2.495502682126729e-05 loss: 0.0463 (0.0482) time: 2.8427 data: 0.0071 max mem: 33370 +Epoch: [21] [1380/2639] eta: 1:00:03 lr: 2.4950421581485443e-05 loss: 0.0455 (0.0482) time: 2.8729 data: 0.0074 max mem: 33370 +Epoch: [21] [1390/2639] eta: 0:59:34 lr: 2.494581624725554e-05 loss: 0.0477 (0.0482) time: 2.8634 data: 0.0079 max mem: 33370 +Epoch: [21] 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mem: 33370 +Epoch: [21] [1480/2639] eta: 0:55:19 lr: 2.4904363985504613e-05 loss: 0.0465 (0.0484) time: 2.9105 data: 0.0083 max mem: 33370 +Epoch: [21] [1490/2639] eta: 0:54:50 lr: 2.489975770562053e-05 loss: 0.0404 (0.0484) time: 2.8891 data: 0.0080 max mem: 33370 +Epoch: [21] [1500/2639] eta: 0:54:21 lr: 2.4895151331053467e-05 loss: 0.0391 (0.0484) time: 2.8112 data: 0.0075 max mem: 33370 +Epoch: [21] [1510/2639] eta: 0:53:52 lr: 2.4890544861782e-05 loss: 0.0443 (0.0484) time: 2.7989 data: 0.0075 max mem: 33370 +Epoch: [21] [1520/2639] eta: 0:53:24 lr: 2.4885938297784718e-05 loss: 0.0449 (0.0484) time: 2.8546 data: 0.0077 max mem: 33370 +Epoch: [21] [1530/2639] eta: 0:52:55 lr: 2.488133163904017e-05 loss: 0.0528 (0.0484) time: 2.8646 data: 0.0081 max mem: 33370 +Epoch: [21] [1540/2639] eta: 0:52:26 lr: 2.4876724885526943e-05 loss: 0.0490 (0.0484) time: 2.8521 data: 0.0078 max mem: 33370 +Epoch: [21] [1550/2639] eta: 0:51:58 lr: 2.487211803722357e-05 loss: 0.0490 (0.0485) time: 2.8767 data: 0.0076 max mem: 33370 +Epoch: [21] [1560/2639] eta: 0:51:29 lr: 2.4867511094108588e-05 loss: 0.0423 (0.0484) time: 2.8669 data: 0.0076 max mem: 33370 +Epoch: [21] [1570/2639] eta: 0:51:01 lr: 2.4862904056160547e-05 loss: 0.0407 (0.0484) time: 2.8653 data: 0.0074 max mem: 33370 +Epoch: [21] [1580/2639] eta: 0:50:32 lr: 2.4858296923357946e-05 loss: 0.0451 (0.0485) time: 2.8875 data: 0.0079 max mem: 33370 +Epoch: [21] [1590/2639] eta: 0:50:04 lr: 2.485368969567932e-05 loss: 0.0480 (0.0485) time: 2.9041 data: 0.0078 max mem: 33370 +Epoch: [21] [1600/2639] eta: 0:49:36 lr: 2.4849082373103156e-05 loss: 0.0474 (0.0484) time: 2.9254 data: 0.0076 max mem: 33370 +Epoch: [21] [1610/2639] eta: 0:49:07 lr: 2.4844474955607956e-05 loss: 0.0474 (0.0484) time: 2.8979 data: 0.0080 max mem: 33370 +Epoch: [21] [1620/2639] eta: 0:48:39 lr: 2.4839867443172204e-05 loss: 0.0450 (0.0484) time: 2.8913 data: 0.0077 max mem: 33370 +Epoch: [21] [1630/2639] eta: 0:48:10 lr: 2.483525983577438e-05 loss: 0.0408 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data: 0.0076 max mem: 33370 +Epoch: [21] [1950/2639] eta: 0:32:53 lr: 2.468776612977652e-05 loss: 0.0457 (0.0487) time: 2.8877 data: 0.0077 max mem: 33370 +Epoch: [21] [1960/2639] eta: 0:32:25 lr: 2.4683155376493766e-05 loss: 0.0460 (0.0487) time: 2.9230 data: 0.0077 max mem: 33370 +Epoch: [21] [1970/2639] eta: 0:31:56 lr: 2.467854452751152e-05 loss: 0.0405 (0.0487) time: 2.8805 data: 0.0074 max mem: 33370 +Epoch: [21] [1980/2639] eta: 0:31:28 lr: 2.4673933582807943e-05 loss: 0.0380 (0.0487) time: 2.8670 data: 0.0075 max mem: 33370 +Epoch: [21] [1990/2639] eta: 0:30:59 lr: 2.4669322542361157e-05 loss: 0.0461 (0.0487) time: 2.9006 data: 0.0077 max mem: 33370 +Epoch: [21] [2000/2639] eta: 0:30:30 lr: 2.4664711406149298e-05 loss: 0.0429 (0.0487) time: 2.8762 data: 0.0077 max mem: 33370 +Epoch: [21] [2010/2639] eta: 0:30:02 lr: 2.466010017415048e-05 loss: 0.0404 (0.0487) time: 2.8724 data: 0.0082 max mem: 33370 +Epoch: [21] [2020/2639] eta: 0:29:33 lr: 2.4655488846342817e-05 loss: 0.0475 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2.4618594772132682e-05 loss: 0.0446 (0.0488) time: 2.8611 data: 0.0079 max mem: 33370 +Epoch: [21] [2110/2639] eta: 0:25:15 lr: 2.4613982581058648e-05 loss: 0.0427 (0.0488) time: 2.8354 data: 0.0080 max mem: 33370 +Epoch: [21] [2120/2639] eta: 0:24:47 lr: 2.460937029395631e-05 loss: 0.0431 (0.0488) time: 2.8666 data: 0.0080 max mem: 33370 +Epoch: [21] [2130/2639] eta: 0:24:18 lr: 2.4604757910803684e-05 loss: 0.0428 (0.0487) time: 2.8988 data: 0.0078 max mem: 33370 +Epoch: [21] [2140/2639] eta: 0:23:49 lr: 2.4600145431578748e-05 loss: 0.0395 (0.0487) time: 2.8632 data: 0.0075 max mem: 33370 +Epoch: [21] [2150/2639] eta: 0:23:21 lr: 2.45955328562595e-05 loss: 0.0468 (0.0487) time: 2.8499 data: 0.0074 max mem: 33370 +Epoch: [21] [2160/2639] eta: 0:22:52 lr: 2.45909201848239e-05 loss: 0.0455 (0.0487) time: 2.8626 data: 0.0073 max mem: 33370 +Epoch: [21] [2170/2639] eta: 0:22:23 lr: 2.458630741724993e-05 loss: 0.0385 (0.0487) time: 2.8999 data: 0.0073 max mem: 33370 +Epoch: [21] [2180/2639] eta: 0:21:55 lr: 2.4581694553515522e-05 loss: 0.0459 (0.0487) time: 2.9103 data: 0.0073 max mem: 33370 +Epoch: [21] [2190/2639] eta: 0:21:26 lr: 2.4577081593598636e-05 loss: 0.0439 (0.0487) time: 2.8684 data: 0.0076 max mem: 33370 +Epoch: [21] [2200/2639] eta: 0:20:58 lr: 2.45724685374772e-05 loss: 0.0385 (0.0486) time: 2.8780 data: 0.0075 max mem: 33370 +Epoch: [21] [2210/2639] eta: 0:20:29 lr: 2.4567855385129146e-05 loss: 0.0432 (0.0487) time: 2.8973 data: 0.0073 max mem: 33370 +Epoch: [21] [2220/2639] eta: 0:20:00 lr: 2.456324213653238e-05 loss: 0.0440 (0.0487) time: 2.8909 data: 0.0077 max mem: 33370 +Epoch: [21] [2230/2639] eta: 0:19:32 lr: 2.4558628791664818e-05 loss: 0.0406 (0.0486) time: 2.8561 data: 0.0078 max mem: 33370 +Epoch: [21] [2240/2639] eta: 0:19:03 lr: 2.4554015350504348e-05 loss: 0.0406 (0.0486) time: 2.8672 data: 0.0078 max mem: 33370 +Epoch: [21] [2250/2639] eta: 0:18:34 lr: 2.4549401813028862e-05 loss: 0.0411 (0.0486) time: 2.8779 data: 0.0079 max mem: 33370 +Epoch: [21] [2260/2639] eta: 0:18:06 lr: 2.4544788179216234e-05 loss: 0.0449 (0.0487) time: 2.8787 data: 0.0078 max mem: 33370 +Epoch: [21] [2270/2639] eta: 0:17:37 lr: 2.4540174449044334e-05 loss: 0.0471 (0.0486) time: 2.8559 data: 0.0081 max mem: 33370 +Epoch: [21] [2280/2639] eta: 0:17:08 lr: 2.4535560622491015e-05 loss: 0.0422 (0.0486) time: 2.8331 data: 0.0083 max mem: 33370 +Epoch: [21] [2290/2639] eta: 0:16:40 lr: 2.453094669953413e-05 loss: 0.0423 (0.0486) time: 2.8703 data: 0.0081 max mem: 33370 +Epoch: [21] [2300/2639] eta: 0:16:11 lr: 2.4526332680151516e-05 loss: 0.0438 (0.0486) time: 2.9004 data: 0.0081 max mem: 33370 +Epoch: [21] [2310/2639] eta: 0:15:42 lr: 2.4521718564320992e-05 loss: 0.0438 (0.0486) time: 2.9194 data: 0.0079 max mem: 33370 +Epoch: [21] [2320/2639] eta: 0:15:14 lr: 2.451710435202039e-05 loss: 0.0511 (0.0487) time: 2.8926 data: 0.0078 max mem: 33370 +Epoch: [21] [2330/2639] eta: 0:14:45 lr: 2.4512490043227512e-05 loss: 0.0454 (0.0487) time: 2.9007 data: 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[2570/2639] eta: 0:03:17 lr: 2.440171762664739e-05 loss: 0.0418 (0.0489) time: 2.8632 data: 0.0077 max mem: 33370 +Epoch: [21] [2580/2639] eta: 0:02:49 lr: 2.4397100898306885e-05 loss: 0.0391 (0.0488) time: 2.8966 data: 0.0076 max mem: 33370 +Epoch: [21] [2590/2639] eta: 0:02:20 lr: 2.4392484072893697e-05 loss: 0.0451 (0.0489) time: 2.8991 data: 0.0075 max mem: 33370 +Epoch: [21] [2600/2639] eta: 0:01:51 lr: 2.4387867150385367e-05 loss: 0.0474 (0.0489) time: 2.8721 data: 0.0079 max mem: 33370 +Epoch: [21] [2610/2639] eta: 0:01:23 lr: 2.4383250130759435e-05 loss: 0.0424 (0.0489) time: 2.8463 data: 0.0079 max mem: 33370 +Epoch: [21] [2620/2639] eta: 0:00:54 lr: 2.437863301399341e-05 loss: 0.0424 (0.0489) time: 2.8456 data: 0.0079 max mem: 33370 +Epoch: [21] [2630/2639] eta: 0:00:25 lr: 2.4374015800064816e-05 loss: 0.0410 (0.0489) time: 2.8385 data: 0.0077 max mem: 33370 +Epoch: [21] Total time: 2:06:04 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 2:10:07 time: 3.0345 data: 2.9420 max mem: 33370 +Test: [ 100/2573] eta: 0:04:22 time: 0.0771 data: 0.0013 max mem: 33370 +Test: [ 200/2573] eta: 0:03:40 time: 0.0776 data: 0.0014 max mem: 33370 +Test: [ 300/2573] eta: 0:03:18 time: 0.0794 data: 0.0013 max mem: 33370 +Test: [ 400/2573] eta: 0:03:04 time: 0.0794 data: 0.0013 max mem: 33370 +Test: [ 500/2573] eta: 0:02:53 time: 0.0781 data: 0.0014 max mem: 33370 +Test: [ 600/2573] eta: 0:02:43 time: 0.0786 data: 0.0014 max mem: 33370 +Test: [ 700/2573] eta: 0:02:34 time: 0.0788 data: 0.0014 max mem: 33370 +Test: [ 800/2573] eta: 0:02:25 time: 0.0821 data: 0.0013 max mem: 33370 +Test: [ 900/2573] eta: 0:02:17 time: 0.0789 data: 0.0013 max mem: 33370 +Test: [1000/2573] eta: 0:02:08 time: 0.0795 data: 0.0013 max mem: 33370 +Test: [1100/2573] eta: 0:02:00 time: 0.0799 data: 0.0015 max mem: 33370 +Test: [1200/2573] eta: 0:01:51 time: 0.0794 data: 0.0014 max mem: 33370 +Test: [1300/2573] eta: 0:01:43 time: 0.0798 data: 0.0014 max mem: 33370 +Test: [1400/2573] eta: 0:01:35 time: 0.0784 data: 0.0014 max mem: 33370 +Test: [1500/2573] eta: 0:01:27 time: 0.0793 data: 0.0014 max mem: 33370 +Test: [1600/2573] eta: 0:01:18 time: 0.0830 data: 0.0013 max mem: 33370 +Test: [1700/2573] eta: 0:01:10 time: 0.0784 data: 0.0014 max mem: 33370 +Test: [1800/2573] eta: 0:01:02 time: 0.0811 data: 0.0013 max mem: 33370 +Test: [1900/2573] eta: 0:00:54 time: 0.0781 data: 0.0014 max mem: 33370 +Test: [2000/2573] eta: 0:00:46 time: 0.0799 data: 0.0013 max mem: 33370 +Test: [2100/2573] eta: 0:00:38 time: 0.0811 data: 0.0013 max mem: 33370 +Test: [2200/2573] eta: 0:00:30 time: 0.0811 data: 0.0013 max mem: 33370 +Test: [2300/2573] eta: 0:00:21 time: 0.0809 data: 0.0013 max mem: 33370 +Test: [2400/2573] eta: 0:00:13 time: 0.0766 data: 0.0014 max mem: 33370 +Test: [2500/2573] eta: 0:00:05 time: 0.0794 data: 0.0014 max mem: 33370 +Test: Total time: 0:03:27 +Final results: +Mean IoU is 63.06 + + precision@0.5 = 70.59 + precision@0.6 = 65.28 + precision@0.7 = 58.27 + precision@0.8 = 47.18 + precision@0.9 = 23.02 + overall IoU = 60.95 + +Average object IoU 63.06371552216278 +Overall IoU 60.948944091796875 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [22] [ 0/2639] eta: 5:18:01 lr: 2.4369860224436493e-05 loss: 0.0613 (0.0613) time: 7.2306 data: 3.5849 max mem: 33370 +Epoch: [22] [ 10/2639] eta: 2:23:54 lr: 2.4365242825837025e-05 loss: 0.0456 (0.0485) time: 3.2842 data: 0.3336 max mem: 33370 +Epoch: [22] [ 20/2639] eta: 2:15:27 lr: 2.4360625330009725e-05 loss: 0.0432 (0.0472) time: 2.8970 data: 0.0084 max mem: 33370 +Epoch: [22] [ 30/2639] eta: 2:12:49 lr: 2.435600773693206e-05 loss: 0.0396 (0.0469) time: 2.9283 data: 0.0086 max mem: 33370 +Epoch: [22] [ 40/2639] eta: 2:11:01 lr: 2.4351390046581497e-05 loss: 0.0443 (0.0492) time: 2.9425 data: 0.0086 max mem: 33370 +Epoch: [22] [ 50/2639] eta: 2:09:05 lr: 2.4346772258935487e-05 loss: 0.0542 (0.0501) time: 2.8945 data: 0.0085 max mem: 33370 +Epoch: [22] [ 60/2639] eta: 2:08:08 lr: 2.4342154373971483e-05 loss: 0.0398 (0.0475) time: 2.8912 data: 0.0080 max mem: 33370 +Epoch: [22] [ 70/2639] eta: 2:06:52 lr: 2.4337536391666914e-05 loss: 0.0408 (0.0499) time: 2.8900 data: 0.0075 max mem: 33370 +Epoch: [22] [ 80/2639] eta: 2:05:56 lr: 2.4332918311999207e-05 loss: 0.0512 (0.0505) time: 2.8666 data: 0.0077 max mem: 33370 +Epoch: [22] [ 90/2639] eta: 2:05:01 lr: 2.4328300134945778e-05 loss: 0.0452 (0.0507) time: 2.8719 data: 0.0074 max mem: 33370 +Epoch: [22] [ 100/2639] eta: 2:04:12 lr: 2.432368186048403e-05 loss: 0.0426 (0.0499) time: 2.8639 data: 0.0078 max mem: 33370 +Epoch: [22] [ 110/2639] eta: 2:03:21 lr: 2.4319063488591353e-05 loss: 0.0436 (0.0495) time: 2.8512 data: 0.0081 max mem: 33370 +Epoch: [22] [ 120/2639] eta: 2:02:46 lr: 2.4314445019245146e-05 loss: 0.0451 (0.0497) time: 2.8698 data: 0.0080 max mem: 33370 +Epoch: [22] [ 130/2639] eta: 2:02:13 lr: 2.4309826452422767e-05 loss: 0.0421 (0.0489) time: 2.9030 data: 0.0081 max mem: 33370 +Epoch: [22] [ 140/2639] eta: 2:01:29 lr: 2.4305207788101597e-05 loss: 0.0422 (0.0486) time: 2.8720 data: 0.0076 max mem: 33370 +Epoch: [22] [ 150/2639] eta: 2:00:49 lr: 2.4300589026258976e-05 loss: 0.0422 (0.0482) time: 2.8464 data: 0.0077 max mem: 33370 +Epoch: [22] [ 160/2639] eta: 2:00:05 lr: 2.429597016687226e-05 loss: 0.0426 (0.0484) time: 2.8328 data: 0.0080 max mem: 33370 +Epoch: [22] [ 170/2639] eta: 1:59:39 lr: 2.4291351209918775e-05 loss: 0.0419 (0.0482) time: 2.8700 data: 0.0081 max mem: 33370 +Epoch: [22] [ 180/2639] eta: 1:59:02 lr: 2.4286732155375848e-05 loss: 0.0348 (0.0475) time: 2.8898 data: 0.0079 max mem: 33370 +Epoch: [22] [ 190/2639] eta: 1:58:32 lr: 2.4282113003220804e-05 loss: 0.0402 (0.0486) time: 2.8731 data: 0.0077 max mem: 33370 +Epoch: [22] [ 200/2639] eta: 1:58:06 lr: 2.427749375343093e-05 loss: 0.0435 (0.0483) time: 2.9120 data: 0.0082 max mem: 33370 +Epoch: [22] [ 210/2639] eta: 1:57:41 lr: 2.427287440598354e-05 loss: 0.0422 (0.0481) time: 2.9361 data: 0.0085 max mem: 33370 +Epoch: [22] [ 220/2639] eta: 1:57:07 lr: 2.42682549608559e-05 loss: 0.0444 (0.0480) time: 2.9042 data: 0.0082 max mem: 33370 +Epoch: [22] [ 230/2639] eta: 1:56:30 lr: 2.42636354180253e-05 loss: 0.0452 (0.0480) time: 2.8433 data: 0.0081 max mem: 33370 +Epoch: [22] [ 240/2639] eta: 1:55:54 lr: 2.4259015777468988e-05 loss: 0.0430 (0.0484) time: 2.8269 data: 0.0076 max mem: 33370 +Epoch: [22] [ 250/2639] eta: 1:55:19 lr: 2.425439603916423e-05 loss: 0.0426 (0.0482) time: 2.8347 data: 0.0073 max mem: 33370 +Epoch: [22] [ 260/2639] eta: 1:54:46 lr: 2.4249776203088266e-05 loss: 0.0421 (0.0482) time: 2.8462 data: 0.0082 max mem: 33370 +Epoch: [22] [ 270/2639] eta: 1:54:10 lr: 2.4245156269218332e-05 loss: 0.0436 (0.0482) time: 2.8352 data: 0.0086 max mem: 33370 +Epoch: [22] [ 280/2639] eta: 1:53:36 lr: 2.4240536237531648e-05 loss: 0.0436 (0.0481) time: 2.8233 data: 0.0083 max mem: 33370 +Epoch: [22] [ 290/2639] eta: 1:53:06 lr: 2.4235916108005435e-05 loss: 0.0406 (0.0479) time: 2.8499 data: 0.0083 max mem: 33370 +Epoch: [22] [ 300/2639] eta: 1:52:31 lr: 2.4231295880616885e-05 loss: 0.0373 (0.0478) time: 2.8404 data: 0.0079 max mem: 33370 +Epoch: [22] [ 310/2639] eta: 1:52:00 lr: 2.4226675555343204e-05 loss: 0.0434 (0.0479) time: 2.8356 data: 0.0075 max mem: 33370 +Epoch: [22] [ 320/2639] eta: 1:51:30 lr: 2.422205513216156e-05 loss: 0.0443 (0.0478) time: 2.8690 data: 0.0077 max mem: 33370 +Epoch: [22] [ 330/2639] eta: 1:50:57 lr: 2.4217434611049144e-05 loss: 0.0406 (0.0475) time: 2.8510 data: 0.0079 max mem: 33370 +Epoch: [22] [ 340/2639] eta: 1:50:25 lr: 2.4212813991983106e-05 loss: 0.0362 (0.0472) time: 2.8254 data: 0.0076 max mem: 33370 +Epoch: [22] [ 350/2639] eta: 1:49:55 lr: 2.4208193274940604e-05 loss: 0.0370 (0.0471) time: 2.8447 data: 0.0081 max mem: 33370 +Epoch: [22] [ 360/2639] eta: 1:49:23 lr: 2.4203572459898775e-05 loss: 0.0417 (0.0469) time: 2.8492 data: 0.0084 max mem: 33370 +Epoch: [22] [ 370/2639] eta: 1:48:54 lr: 2.419895154683476e-05 loss: 0.0436 (0.0469) time: 2.8584 data: 0.0079 max mem: 33370 +Epoch: [22] [ 380/2639] eta: 1:48:22 lr: 2.419433053572567e-05 loss: 0.0395 (0.0467) time: 2.8481 data: 0.0079 max mem: 33370 +Epoch: [22] [ 390/2639] eta: 1:47:50 lr: 2.4189709426548632e-05 loss: 0.0420 (0.0468) time: 2.8238 data: 0.0078 max mem: 33370 +Epoch: [22] [ 400/2639] eta: 1:47:24 lr: 2.4185088219280733e-05 loss: 0.0430 (0.0467) time: 2.8744 data: 0.0074 max mem: 33370 +Epoch: [22] [ 410/2639] eta: 1:46:57 lr: 2.4180466913899074e-05 loss: 0.0456 (0.0467) time: 2.9145 data: 0.0076 max mem: 33370 +Epoch: [22] [ 420/2639] eta: 1:46:28 lr: 2.417584551038073e-05 loss: 0.0498 (0.0468) time: 2.9013 data: 0.0079 max mem: 33370 +Epoch: [22] [ 430/2639] eta: 1:45:58 lr: 2.417122400870277e-05 loss: 0.0399 (0.0465) time: 2.8713 data: 0.0076 max mem: 33370 +Epoch: [22] [ 440/2639] eta: 1:45:32 lr: 2.4166602408842274e-05 loss: 0.0399 (0.0465) time: 2.8919 data: 0.0078 max mem: 33370 +Epoch: [22] [ 450/2639] eta: 1:45:02 lr: 2.4161980710776268e-05 loss: 0.0375 (0.0462) time: 2.8903 data: 0.0080 max mem: 33370 +Epoch: [22] [ 460/2639] eta: 1:44:33 lr: 2.4157358914481813e-05 loss: 0.0432 (0.0466) time: 2.8645 data: 0.0079 max mem: 33370 +Epoch: [22] [ 470/2639] eta: 1:44:04 lr: 2.415273701993592e-05 loss: 0.0448 (0.0466) time: 2.8805 data: 0.0076 max mem: 33370 +Epoch: [22] [ 480/2639] eta: 1:43:37 lr: 2.4148115027115623e-05 loss: 0.0395 (0.0464) time: 2.8903 data: 0.0076 max mem: 33370 +Epoch: [22] [ 490/2639] eta: 1:43:07 lr: 2.414349293599792e-05 loss: 0.0393 (0.0464) time: 2.8850 data: 0.0078 max mem: 33370 +Epoch: [22] [ 500/2639] eta: 1:42:39 lr: 2.413887074655983e-05 loss: 0.0395 (0.0463) time: 2.8754 data: 0.0082 max mem: 33370 +Epoch: [22] [ 510/2639] eta: 1:42:12 lr: 2.4134248458778318e-05 loss: 0.0414 (0.0463) time: 2.9018 data: 0.0082 max mem: 33370 +Epoch: [22] [ 520/2639] eta: 1:41:42 lr: 2.4129626072630383e-05 loss: 0.0399 (0.0462) time: 2.8942 data: 0.0076 max mem: 33370 +Epoch: [22] [ 530/2639] eta: 1:41:14 lr: 2.4125003588092975e-05 loss: 0.0371 (0.0460) time: 2.8752 data: 0.0076 max mem: 33370 +Epoch: [22] [ 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33370 +Epoch: [22] [ 620/2639] eta: 1:36:51 lr: 2.40833967959252e-05 loss: 0.0395 (0.0459) time: 2.8966 data: 0.0076 max mem: 33370 +Epoch: [22] [ 630/2639] eta: 1:36:23 lr: 2.407877332622416e-05 loss: 0.0348 (0.0460) time: 2.9087 data: 0.0076 max mem: 33370 +Epoch: [22] [ 640/2639] eta: 1:35:54 lr: 2.4074149757879634e-05 loss: 0.0429 (0.0460) time: 2.8820 data: 0.0078 max mem: 33370 +Epoch: [22] [ 650/2639] eta: 1:35:25 lr: 2.4069526090868456e-05 loss: 0.0456 (0.0461) time: 2.8752 data: 0.0078 max mem: 33370 +Epoch: [22] [ 660/2639] eta: 1:34:55 lr: 2.406490232516747e-05 loss: 0.0444 (0.0460) time: 2.8558 data: 0.0074 max mem: 33370 +Epoch: [22] [ 670/2639] eta: 1:34:25 lr: 2.4060278460753493e-05 loss: 0.0388 (0.0460) time: 2.8453 data: 0.0076 max mem: 33370 +Epoch: [22] [ 680/2639] eta: 1:33:56 lr: 2.405565449760334e-05 loss: 0.0427 (0.0463) time: 2.8473 data: 0.0079 max mem: 33370 +Epoch: [22] [ 690/2639] eta: 1:33:26 lr: 2.405103043569382e-05 loss: 0.0461 (0.0463) time: 2.8398 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data: 0.0077 max mem: 33370 +Epoch: [22] [1090/2639] eta: 1:14:14 lr: 2.3865986709034485e-05 loss: 0.0384 (0.0463) time: 2.9032 data: 0.0079 max mem: 33370 +Epoch: [22] [1100/2639] eta: 1:13:46 lr: 2.386135857788875e-05 loss: 0.0365 (0.0463) time: 2.8831 data: 0.0079 max mem: 33370 +Epoch: [22] [1110/2639] eta: 1:13:17 lr: 2.385673034699988e-05 loss: 0.0422 (0.0463) time: 2.8724 data: 0.0076 max mem: 33370 +Epoch: [22] [1120/2639] eta: 1:12:48 lr: 2.3852102016344233e-05 loss: 0.0463 (0.0464) time: 2.8866 data: 0.0075 max mem: 33370 +Epoch: [22] [1130/2639] eta: 1:12:20 lr: 2.3847473585898132e-05 loss: 0.0460 (0.0463) time: 2.9131 data: 0.0074 max mem: 33370 +Epoch: [22] [1140/2639] eta: 1:11:51 lr: 2.3842845055637926e-05 loss: 0.0434 (0.0464) time: 2.9004 data: 0.0074 max mem: 33370 +Epoch: [22] [1150/2639] eta: 1:11:23 lr: 2.3838216425539912e-05 loss: 0.0443 (0.0463) time: 2.8823 data: 0.0077 max mem: 33370 +Epoch: [22] [1160/2639] eta: 1:10:54 lr: 2.3833587695580406e-05 loss: 0.0443 (0.0464) time: 2.8856 data: 0.0079 max mem: 33370 +Epoch: [22] [1170/2639] eta: 1:10:24 lr: 2.3828958865735706e-05 loss: 0.0438 (0.0464) time: 2.8281 data: 0.0085 max mem: 33370 +Epoch: [22] [1180/2639] eta: 1:09:55 lr: 2.382432993598209e-05 loss: 0.0410 (0.0464) time: 2.7969 data: 0.0088 max mem: 33370 +Epoch: [22] [1190/2639] eta: 1:09:26 lr: 2.381970090629584e-05 loss: 0.0394 (0.0464) time: 2.8395 data: 0.0078 max mem: 33370 +Epoch: [22] [1200/2639] eta: 1:08:57 lr: 2.381507177665321e-05 loss: 0.0439 (0.0464) time: 2.8749 data: 0.0073 max mem: 33370 +Epoch: [22] [1210/2639] eta: 1:08:28 lr: 2.381044254703046e-05 loss: 0.0429 (0.0464) time: 2.8818 data: 0.0082 max mem: 33370 +Epoch: [22] [1220/2639] eta: 1:08:00 lr: 2.3805813217403824e-05 loss: 0.0405 (0.0464) time: 2.8702 data: 0.0079 max mem: 33370 +Epoch: [22] [1230/2639] eta: 1:07:30 lr: 2.3801183787749547e-05 loss: 0.0373 (0.0463) time: 2.8533 data: 0.0072 max mem: 33370 +Epoch: [22] [1240/2639] eta: 1:07:02 lr: 2.379655425804383e-05 loss: 0.0363 (0.0462) time: 2.8612 data: 0.0076 max mem: 33370 +Epoch: [22] [1250/2639] eta: 1:06:33 lr: 2.3791924628262898e-05 loss: 0.0332 (0.0462) time: 2.8785 data: 0.0077 max mem: 33370 +Epoch: [22] [1260/2639] eta: 1:06:04 lr: 2.3787294898382943e-05 loss: 0.0456 (0.0462) time: 2.8488 data: 0.0077 max mem: 33370 +Epoch: [22] [1270/2639] eta: 1:05:35 lr: 2.3782665068380156e-05 loss: 0.0456 (0.0462) time: 2.8698 data: 0.0078 max mem: 33370 +Epoch: [22] [1280/2639] eta: 1:05:07 lr: 2.3778035138230706e-05 loss: 0.0388 (0.0462) time: 2.9216 data: 0.0077 max mem: 33370 +Epoch: [22] [1290/2639] eta: 1:04:38 lr: 2.377340510791077e-05 loss: 0.0420 (0.0462) time: 2.8735 data: 0.0078 max mem: 33370 +Epoch: [22] [1300/2639] eta: 1:04:09 lr: 2.3768774977396492e-05 loss: 0.0416 (0.0461) time: 2.8561 data: 0.0080 max mem: 33370 +Epoch: [22] [1310/2639] eta: 1:03:40 lr: 2.376414474666403e-05 loss: 0.0416 (0.0461) time: 2.8818 data: 0.0086 max mem: 33370 +Epoch: [22] [1320/2639] eta: 1:03:12 lr: 2.3759514415689503e-05 loss: 0.0351 (0.0461) time: 2.8687 data: 0.0086 max mem: 33370 +Epoch: [22] [1330/2639] eta: 1:02:43 lr: 2.375488398444905e-05 loss: 0.0447 (0.0461) time: 2.8523 data: 0.0082 max mem: 33370 +Epoch: [22] [1340/2639] eta: 1:02:14 lr: 2.3750253452918766e-05 loss: 0.0459 (0.0461) time: 2.8692 data: 0.0078 max mem: 33370 +Epoch: [22] [1350/2639] eta: 1:01:45 lr: 2.3745622821074764e-05 loss: 0.0382 (0.0461) time: 2.8857 data: 0.0074 max mem: 33370 +Epoch: [22] [1360/2639] eta: 1:01:17 lr: 2.3740992088893126e-05 loss: 0.0408 (0.0461) time: 2.8747 data: 0.0077 max mem: 33370 +Epoch: [22] [1370/2639] eta: 1:00:48 lr: 2.3736361256349943e-05 loss: 0.0408 (0.0462) time: 2.8684 data: 0.0079 max mem: 33370 +Epoch: [22] [1380/2639] eta: 1:00:18 lr: 2.3731730323421266e-05 loss: 0.0384 (0.0462) time: 2.8436 data: 0.0076 max mem: 33370 +Epoch: [22] [1390/2639] eta: 0:59:50 lr: 2.3727099290083173e-05 loss: 0.0398 (0.0461) time: 2.8421 data: 0.0080 max mem: 33370 +Epoch: [22] [1400/2639] eta: 0:59:21 lr: 2.3722468156311688e-05 loss: 0.0428 (0.0461) time: 2.8502 data: 0.0085 max mem: 33370 +Epoch: [22] [1410/2639] eta: 0:58:51 lr: 2.3717836922082865e-05 loss: 0.0461 (0.0462) time: 2.8290 data: 0.0083 max mem: 33370 +Epoch: [22] [1420/2639] eta: 0:58:23 lr: 2.3713205587372723e-05 loss: 0.0407 (0.0462) time: 2.8706 data: 0.0081 max mem: 33370 +Epoch: [22] [1430/2639] eta: 0:57:54 lr: 2.370857415215727e-05 loss: 0.0409 (0.0462) time: 2.8957 data: 0.0078 max mem: 33370 +Epoch: [22] [1440/2639] eta: 0:57:25 lr: 2.3703942616412523e-05 loss: 0.0469 (0.0462) time: 2.8575 data: 0.0075 max mem: 33370 +Epoch: [22] [1450/2639] eta: 0:56:57 lr: 2.3699310980114457e-05 loss: 0.0433 (0.0462) time: 2.8743 data: 0.0077 max mem: 33370 +Epoch: [22] [1460/2639] eta: 0:56:28 lr: 2.3694679243239065e-05 loss: 0.0430 (0.0462) time: 2.9006 data: 0.0078 max mem: 33370 +Epoch: [22] [1470/2639] eta: 0:56:00 lr: 2.3690047405762308e-05 loss: 0.0392 (0.0462) time: 2.9282 data: 0.0076 max mem: 33370 +Epoch: [22] [1480/2639] eta: 0:55:32 lr: 2.3685415467660158e-05 loss: 0.0412 (0.0463) time: 2.9597 data: 0.0075 max mem: 33370 +Epoch: [22] [1490/2639] eta: 0:55:03 lr: 2.368078342890855e-05 loss: 0.0412 (0.0463) time: 2.9125 data: 0.0076 max mem: 33370 +Epoch: [22] [1500/2639] eta: 0:54:34 lr: 2.3676151289483428e-05 loss: 0.0420 (0.0463) time: 2.8672 data: 0.0076 max mem: 33370 +Epoch: [22] [1510/2639] eta: 0:54:05 lr: 2.3671519049360717e-05 loss: 0.0415 (0.0462) time: 2.8489 data: 0.0077 max mem: 33370 +Epoch: [22] [1520/2639] eta: 0:53:36 lr: 2.3666886708516332e-05 loss: 0.0411 (0.0463) time: 2.8395 data: 0.0077 max mem: 33370 +Epoch: [22] [1530/2639] eta: 0:53:07 lr: 2.3662254266926173e-05 loss: 0.0408 (0.0462) time: 2.8426 data: 0.0073 max mem: 33370 +Epoch: [22] [1540/2639] eta: 0:52:38 lr: 2.365762172456614e-05 loss: 0.0382 (0.0462) time: 2.8212 data: 0.0072 max mem: 33370 +Epoch: [22] [1550/2639] eta: 0:52:09 lr: 2.365298908141211e-05 loss: 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2.361592430469829e-05 loss: 0.0424 (0.0463) time: 2.8990 data: 0.0078 max mem: 33370 +Epoch: [22] [1640/2639] eta: 0:47:51 lr: 2.361129075331119e-05 loss: 0.0422 (0.0463) time: 2.9277 data: 0.0076 max mem: 33370 +Epoch: [22] [1650/2639] eta: 0:47:23 lr: 2.36066571008883e-05 loss: 0.0423 (0.0463) time: 2.9040 data: 0.0078 max mem: 33370 +Epoch: [22] [1660/2639] eta: 0:46:54 lr: 2.360202334740539e-05 loss: 0.0401 (0.0462) time: 2.8834 data: 0.0079 max mem: 33370 +Epoch: [22] [1670/2639] eta: 0:46:25 lr: 2.3597389492838214e-05 loss: 0.0384 (0.0463) time: 2.8886 data: 0.0079 max mem: 33370 +Epoch: [22] [1680/2639] eta: 0:45:57 lr: 2.3592755537162504e-05 loss: 0.0412 (0.0462) time: 2.8832 data: 0.0078 max mem: 33370 +Epoch: [22] [1690/2639] eta: 0:45:28 lr: 2.358812148035399e-05 loss: 0.0411 (0.0462) time: 2.8751 data: 0.0079 max mem: 33370 +Epoch: [22] [1700/2639] eta: 0:44:59 lr: 2.358348732238838e-05 loss: 0.0395 (0.0462) time: 2.8651 data: 0.0082 max mem: 33370 +Epoch: [22] [1710/2639] eta: 0:44:30 lr: 2.3578853063241394e-05 loss: 0.0397 (0.0462) time: 2.8423 data: 0.0083 max mem: 33370 +Epoch: [22] [1720/2639] eta: 0:44:01 lr: 2.357421870288871e-05 loss: 0.0485 (0.0462) time: 2.8219 data: 0.0078 max mem: 33370 +Epoch: [22] [1730/2639] eta: 0:43:32 lr: 2.3569584241306024e-05 loss: 0.0503 (0.0462) time: 2.8630 data: 0.0075 max mem: 33370 +Epoch: [22] [1740/2639] eta: 0:43:03 lr: 2.3564949678468996e-05 loss: 0.0484 (0.0462) time: 2.8625 data: 0.0076 max mem: 33370 +Epoch: [22] [1750/2639] eta: 0:42:34 lr: 2.3560315014353295e-05 loss: 0.0475 (0.0462) time: 2.8377 data: 0.0076 max mem: 33370 +Epoch: [22] [1760/2639] eta: 0:42:06 lr: 2.3555680248934564e-05 loss: 0.0473 (0.0463) time: 2.8540 data: 0.0078 max mem: 33370 +Epoch: [22] [1770/2639] eta: 0:41:37 lr: 2.3551045382188447e-05 loss: 0.0554 (0.0464) time: 2.8516 data: 0.0078 max mem: 33370 +Epoch: [22] [1780/2639] eta: 0:41:08 lr: 2.354641041409056e-05 loss: 0.0488 (0.0464) time: 2.8527 data: 0.0080 max mem: 33370 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(0.0468) time: 2.8788 data: 0.0085 max mem: 33370 +Epoch: [22] [1950/2639] eta: 0:32:58 lr: 2.346760042593483e-05 loss: 0.0407 (0.0468) time: 2.8423 data: 0.0087 max mem: 33370 +Epoch: [22] [1960/2639] eta: 0:32:30 lr: 2.3462963629324593e-05 loss: 0.0482 (0.0468) time: 2.8173 data: 0.0084 max mem: 33370 +Epoch: [22] [1970/2639] eta: 0:32:01 lr: 2.3458326730897364e-05 loss: 0.0426 (0.0468) time: 2.8635 data: 0.0082 max mem: 33370 +Epoch: [22] [1980/2639] eta: 0:31:32 lr: 2.345368973062855e-05 loss: 0.0426 (0.0468) time: 2.8888 data: 0.0080 max mem: 33370 +Epoch: [22] [1990/2639] eta: 0:31:03 lr: 2.3449052628493535e-05 loss: 0.0433 (0.0468) time: 2.8407 data: 0.0077 max mem: 33370 +Epoch: [22] [2000/2639] eta: 0:30:35 lr: 2.34444154244677e-05 loss: 0.0360 (0.0467) time: 2.8952 data: 0.0076 max mem: 33370 +Epoch: [22] [2010/2639] eta: 0:30:06 lr: 2.343977811852641e-05 loss: 0.0379 (0.0467) time: 2.9237 data: 0.0075 max mem: 33370 +Epoch: [22] [2020/2639] eta: 0:29:37 lr: 2.3435140710645025e-05 loss: 0.0420 (0.0467) time: 2.8698 data: 0.0074 max mem: 33370 +Epoch: [22] [2030/2639] eta: 0:29:09 lr: 2.3430503200798888e-05 loss: 0.0410 (0.0467) time: 2.8493 data: 0.0076 max mem: 33370 +Epoch: [22] [2040/2639] eta: 0:28:40 lr: 2.3425865588963333e-05 loss: 0.0410 (0.0467) time: 2.8749 data: 0.0077 max mem: 33370 +Epoch: [22] [2050/2639] eta: 0:28:11 lr: 2.3421227875113674e-05 loss: 0.0414 (0.0466) time: 2.8731 data: 0.0074 max mem: 33370 +Epoch: [22] [2060/2639] eta: 0:27:43 lr: 2.341659005922524e-05 loss: 0.0376 (0.0466) time: 2.8661 data: 0.0074 max mem: 33370 +Epoch: [22] [2070/2639] eta: 0:27:14 lr: 2.3411952141273306e-05 loss: 0.0362 (0.0466) time: 2.8724 data: 0.0076 max mem: 33370 +Epoch: [22] [2080/2639] eta: 0:26:45 lr: 2.340731412123318e-05 loss: 0.0403 (0.0466) time: 2.8481 data: 0.0078 max mem: 33370 +Epoch: [22] [2090/2639] eta: 0:26:16 lr: 2.3402675999080122e-05 loss: 0.0445 (0.0466) time: 2.8546 data: 0.0077 max mem: 33370 +Epoch: [22] [2100/2639] eta: 0:25:48 lr: 2.3398037774789412e-05 loss: 0.0463 (0.0467) time: 2.8779 data: 0.0077 max mem: 33370 +Epoch: [22] [2110/2639] eta: 0:25:19 lr: 2.3393399448336287e-05 loss: 0.0477 (0.0466) time: 2.8976 data: 0.0077 max mem: 33370 +Epoch: [22] [2120/2639] eta: 0:24:50 lr: 2.3388761019696005e-05 loss: 0.0377 (0.0466) time: 2.8746 data: 0.0075 max mem: 33370 +Epoch: [22] [2130/2639] eta: 0:24:21 lr: 2.3384122488843783e-05 loss: 0.0415 (0.0467) time: 2.8518 data: 0.0075 max mem: 33370 +Epoch: [22] [2140/2639] eta: 0:23:53 lr: 2.337948385575485e-05 loss: 0.0462 (0.0467) time: 2.8393 data: 0.0076 max mem: 33370 +Epoch: [22] [2150/2639] eta: 0:23:24 lr: 2.3374845120404407e-05 loss: 0.0419 (0.0467) time: 2.7988 data: 0.0076 max mem: 33370 +Epoch: [22] [2160/2639] eta: 0:22:55 lr: 2.337020628276765e-05 loss: 0.0406 (0.0468) time: 2.7929 data: 0.0076 max mem: 33370 +Epoch: [22] [2170/2639] eta: 0:22:26 lr: 2.3365567342819772e-05 loss: 0.0415 (0.0468) time: 2.8312 data: 0.0072 max mem: 33370 +Epoch: [22] [2180/2639] eta: 0:21:57 lr: 2.3360928300535935e-05 loss: 0.0418 (0.0468) time: 2.8831 data: 0.0072 max mem: 33370 +Epoch: [22] [2190/2639] eta: 0:21:29 lr: 2.335628915589131e-05 loss: 0.0436 (0.0468) time: 2.8956 data: 0.0078 max mem: 33370 +Epoch: [22] [2200/2639] eta: 0:21:00 lr: 2.3351649908861032e-05 loss: 0.0410 (0.0468) time: 2.8780 data: 0.0081 max mem: 33370 +Epoch: [22] [2210/2639] eta: 0:20:31 lr: 2.334701055942026e-05 loss: 0.0421 (0.0468) time: 2.8559 data: 0.0080 max mem: 33370 +Epoch: [22] [2220/2639] eta: 0:20:03 lr: 2.33423711075441e-05 loss: 0.0471 (0.0468) time: 2.8574 data: 0.0077 max mem: 33370 +Epoch: [22] [2230/2639] eta: 0:19:34 lr: 2.3337731553207687e-05 loss: 0.0409 (0.0468) time: 2.8659 data: 0.0077 max mem: 33370 +Epoch: [22] [2240/2639] eta: 0:19:05 lr: 2.333309189638611e-05 loss: 0.0409 (0.0468) time: 2.8691 data: 0.0079 max mem: 33370 +Epoch: [22] [2250/2639] eta: 0:18:36 lr: 2.3328452137054468e-05 loss: 0.0398 (0.0468) time: 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0.0388 (0.0468) time: 2.8403 data: 0.0075 max mem: 33370 +Epoch: [22] [2340/2639] eta: 0:14:18 lr: 2.328668968600119e-05 loss: 0.0388 (0.0468) time: 2.8669 data: 0.0078 max mem: 33370 +Epoch: [22] [2350/2639] eta: 0:13:49 lr: 2.3282048900196414e-05 loss: 0.0402 (0.0468) time: 2.9082 data: 0.0079 max mem: 33370 +Epoch: [22] [2360/2639] eta: 0:13:21 lr: 2.3277408011606815e-05 loss: 0.0427 (0.0468) time: 2.8699 data: 0.0077 max mem: 33370 +Epoch: [22] [2370/2639] eta: 0:12:52 lr: 2.327276702020736e-05 loss: 0.0426 (0.0467) time: 2.8468 data: 0.0074 max mem: 33370 +Epoch: [22] [2380/2639] eta: 0:12:23 lr: 2.326812592597298e-05 loss: 0.0389 (0.0467) time: 2.8394 data: 0.0076 max mem: 33370 +Epoch: [22] [2390/2639] eta: 0:11:54 lr: 2.326348472887861e-05 loss: 0.0389 (0.0467) time: 2.8364 data: 0.0075 max mem: 33370 +Epoch: [22] [2400/2639] eta: 0:11:26 lr: 2.3258843428899157e-05 loss: 0.0410 (0.0467) time: 2.8534 data: 0.0073 max mem: 33370 +Epoch: [22] [2410/2639] eta: 0:10:57 lr: 2.3254202026009543e-05 loss: 0.0458 (0.0467) time: 2.8605 data: 0.0072 max mem: 33370 +Epoch: [22] [2420/2639] eta: 0:10:28 lr: 2.3249560520184657e-05 loss: 0.0495 (0.0468) time: 2.8913 data: 0.0074 max mem: 33370 +Epoch: [22] [2430/2639] eta: 0:10:00 lr: 2.3244918911399378e-05 loss: 0.0497 (0.0468) time: 2.8827 data: 0.0078 max mem: 33370 +Epoch: [22] [2440/2639] eta: 0:09:31 lr: 2.324027719962858e-05 loss: 0.0474 (0.0468) time: 2.9028 data: 0.0081 max mem: 33370 +Epoch: [22] [2450/2639] eta: 0:09:02 lr: 2.3235635384847123e-05 loss: 0.0426 (0.0468) time: 2.9225 data: 0.0077 max mem: 33370 +Epoch: [22] [2460/2639] eta: 0:08:34 lr: 2.323099346702986e-05 loss: 0.0432 (0.0468) time: 2.9100 data: 0.0079 max mem: 33370 +Epoch: [22] [2470/2639] eta: 0:08:05 lr: 2.3226351446151618e-05 loss: 0.0432 (0.0468) time: 2.9084 data: 0.0078 max mem: 33370 +Epoch: [22] [2480/2639] eta: 0:07:36 lr: 2.3221709322187226e-05 loss: 0.0447 (0.0469) time: 2.8840 data: 0.0071 max mem: 33370 +Epoch: [22] [2490/2639] eta: 0:07:07 lr: 2.321706709511149e-05 loss: 0.0523 (0.0469) time: 2.8663 data: 0.0073 max mem: 33370 +Epoch: [22] [2500/2639] eta: 0:06:39 lr: 2.3212424764899226e-05 loss: 0.0453 (0.0469) time: 2.8246 data: 0.0076 max mem: 33370 +Epoch: [22] [2510/2639] eta: 0:06:10 lr: 2.3207782331525208e-05 loss: 0.0421 (0.0469) time: 2.8221 data: 0.0076 max mem: 33370 +Epoch: [22] [2520/2639] eta: 0:05:41 lr: 2.320313979496422e-05 loss: 0.0423 (0.0469) time: 2.8393 data: 0.0080 max mem: 33370 +Epoch: [22] [2530/2639] eta: 0:05:12 lr: 2.3198497155191025e-05 loss: 0.0399 (0.0468) time: 2.8304 data: 0.0082 max mem: 33370 +Epoch: [22] [2540/2639] eta: 0:04:44 lr: 2.3193854412180383e-05 loss: 0.0398 (0.0468) time: 2.8425 data: 0.0076 max mem: 33370 +Epoch: [22] [2550/2639] eta: 0:04:15 lr: 2.3189211565907027e-05 loss: 0.0434 (0.0469) time: 2.8499 data: 0.0075 max mem: 33370 +Epoch: [22] [2560/2639] eta: 0:03:46 lr: 2.3184568616345693e-05 loss: 0.0437 (0.0469) time: 2.8422 data: 0.0076 max mem: 33370 +Epoch: [22] [2570/2639] eta: 0:03:18 lr: 2.31799255634711e-05 loss: 0.0440 (0.0469) time: 2.8696 data: 0.0076 max mem: 33370 +Epoch: [22] [2580/2639] eta: 0:02:49 lr: 2.3175282407257953e-05 loss: 0.0440 (0.0469) time: 2.8795 data: 0.0074 max mem: 33370 +Epoch: [22] [2590/2639] eta: 0:02:20 lr: 2.317063914768094e-05 loss: 0.0420 (0.0469) time: 2.9095 data: 0.0075 max mem: 33370 +Epoch: [22] [2600/2639] eta: 0:01:51 lr: 2.3165995784714763e-05 loss: 0.0420 (0.0469) time: 2.8995 data: 0.0078 max mem: 33370 +Epoch: [22] [2610/2639] eta: 0:01:23 lr: 2.3161352318334067e-05 loss: 0.0452 (0.0469) time: 2.8609 data: 0.0077 max mem: 33370 +Epoch: [22] [2620/2639] eta: 0:00:54 lr: 2.3156708748513532e-05 loss: 0.0421 (0.0469) time: 2.8662 data: 0.0075 max mem: 33370 +Epoch: [22] [2630/2639] eta: 0:00:25 lr: 2.3152065075227794e-05 loss: 0.0371 (0.0469) time: 2.8625 data: 0.0072 max mem: 33370 +Epoch: [22] Total time: 2:06:17 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 2:13:34 time: 3.1147 data: 3.0243 max mem: 33370 +Test: [ 100/2573] eta: 0:04:24 time: 0.0767 data: 0.0014 max mem: 33370 +Test: [ 200/2573] eta: 0:03:41 time: 0.0793 data: 0.0015 max mem: 33370 +Test: [ 300/2573] eta: 0:03:19 time: 0.0798 data: 0.0013 max mem: 33370 +Test: [ 400/2573] eta: 0:03:05 time: 0.0800 data: 0.0013 max mem: 33370 +Test: [ 500/2573] eta: 0:02:54 time: 0.0785 data: 0.0014 max mem: 33370 +Test: [ 600/2573] eta: 0:02:44 time: 0.0801 data: 0.0014 max mem: 33370 +Test: [ 700/2573] eta: 0:02:35 time: 0.0793 data: 0.0015 max mem: 33370 +Test: [ 800/2573] eta: 0:02:26 time: 0.0829 data: 0.0013 max mem: 33370 +Test: [ 900/2573] eta: 0:02:18 time: 0.0786 data: 0.0014 max mem: 33370 +Test: [1000/2573] eta: 0:02:09 time: 0.0785 data: 0.0013 max mem: 33370 +Test: [1100/2573] eta: 0:02:00 time: 0.0790 data: 0.0015 max mem: 33370 +Test: [1200/2573] eta: 0:01:52 time: 0.0789 data: 0.0013 max mem: 33370 +Test: [1300/2573] eta: 0:01:43 time: 0.0787 data: 0.0013 max mem: 33370 +Test: [1400/2573] eta: 0:01:35 time: 0.0772 data: 0.0013 max mem: 33370 +Test: [1500/2573] eta: 0:01:27 time: 0.0801 data: 0.0015 max mem: 33370 +Test: [1600/2573] eta: 0:01:18 time: 0.0823 data: 0.0013 max mem: 33370 +Test: [1700/2573] eta: 0:01:10 time: 0.0781 data: 0.0014 max mem: 33370 +Test: [1800/2573] eta: 0:01:02 time: 0.0812 data: 0.0015 max mem: 33370 +Test: [1900/2573] eta: 0:00:54 time: 0.0789 data: 0.0015 max mem: 33370 +Test: [2000/2573] eta: 0:00:46 time: 0.0797 data: 0.0014 max mem: 33370 +Test: [2100/2573] eta: 0:00:38 time: 0.0810 data: 0.0013 max mem: 33370 +Test: [2200/2573] eta: 0:00:30 time: 0.0819 data: 0.0013 max mem: 33370 +Test: [2300/2573] eta: 0:00:21 time: 0.0813 data: 0.0013 max mem: 33370 +Test: [2400/2573] eta: 0:00:13 time: 0.0759 data: 0.0015 max mem: 33370 +Test: [2500/2573] eta: 0:00:05 time: 0.0800 data: 0.0014 max mem: 33370 +Test: Total time: 0:03:27 +Final results: +Mean IoU is 63.33 + + precision@0.5 = 70.96 + precision@0.6 = 65.46 + precision@0.7 = 58.50 + precision@0.8 = 47.67 + precision@0.9 = 23.59 + overall IoU = 60.82 + +Average object IoU 63.33049065821723 +Overall IoU 60.8167839050293 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [23] [ 0/2639] eta: 4:37:38 lr: 2.3147885680786924e-05 loss: 0.0628 (0.0628) time: 6.3124 data: 3.1087 max mem: 33370 +Epoch: [23] [ 10/2639] eta: 2:17:17 lr: 2.3143241810847423e-05 loss: 0.0433 (0.0467) time: 3.1333 data: 0.2895 max mem: 33370 +Epoch: [23] [ 20/2639] eta: 2:10:06 lr: 2.313859783736913e-05 loss: 0.0421 (0.0533) time: 2.8140 data: 0.0073 max mem: 33370 +Epoch: [23] [ 30/2639] eta: 2:07:49 lr: 2.3133953760326647e-05 loss: 0.0446 (0.0534) time: 2.8330 data: 0.0071 max mem: 33370 +Epoch: [23] [ 40/2639] eta: 2:06:19 lr: 2.3129309579694574e-05 loss: 0.0494 (0.0524) time: 2.8488 data: 0.0072 max mem: 33370 +Epoch: [23] [ 50/2639] eta: 2:05:08 lr: 2.3124665295447474e-05 loss: 0.0478 (0.0528) time: 2.8388 data: 0.0074 max mem: 33370 +Epoch: [23] [ 60/2639] eta: 2:04:19 lr: 2.3120020907559923e-05 loss: 0.0378 (0.0508) time: 2.8438 data: 0.0075 max mem: 33370 +Epoch: [23] [ 70/2639] eta: 2:04:02 lr: 2.3115376416006463e-05 loss: 0.0370 (0.0490) time: 2.8898 data: 0.0074 max mem: 33370 +Epoch: [23] [ 80/2639] eta: 2:03:35 lr: 2.3110731820761648e-05 loss: 0.0383 (0.0499) time: 2.9133 data: 0.0072 max mem: 33370 +Epoch: [23] [ 90/2639] eta: 2:03:16 lr: 2.3106087121799994e-05 loss: 0.0392 (0.0493) time: 2.9171 data: 0.0074 max mem: 33370 +Epoch: [23] [ 100/2639] eta: 2:02:38 lr: 2.3101442319096034e-05 loss: 0.0392 (0.0487) time: 2.9004 data: 0.0076 max mem: 33370 +Epoch: [23] [ 110/2639] eta: 2:02:12 lr: 2.309679741262426e-05 loss: 0.0384 (0.0482) time: 2.8885 data: 0.0074 max mem: 33370 +Epoch: [23] [ 120/2639] eta: 2:01:42 lr: 2.309215240235918e-05 loss: 0.0458 (0.0477) time: 2.9022 data: 0.0075 max mem: 33370 +Epoch: [23] [ 130/2639] eta: 2:01:08 lr: 2.3087507288275258e-05 loss: 0.0458 (0.0475) time: 2.8857 data: 0.0074 max mem: 33370 +Epoch: [23] [ 140/2639] eta: 2:00:41 lr: 2.308286207034698e-05 loss: 0.0372 (0.0466) time: 2.8907 data: 0.0073 max mem: 33370 +Epoch: [23] [ 150/2639] eta: 2:00:18 lr: 2.3078216748548788e-05 loss: 0.0354 (0.0459) time: 2.9211 data: 0.0074 max mem: 33370 +Epoch: [23] [ 160/2639] eta: 2:00:00 lr: 2.3073571322855145e-05 loss: 0.0362 (0.0463) time: 2.9521 data: 0.0078 max mem: 33370 +Epoch: [23] [ 170/2639] eta: 1:59:26 lr: 2.3068925793240474e-05 loss: 0.0370 (0.0460) time: 2.9184 data: 0.0079 max mem: 33370 +Epoch: [23] [ 180/2639] eta: 1:58:54 lr: 2.30642801596792e-05 loss: 0.0368 (0.0455) time: 2.8775 data: 0.0078 max mem: 33370 +Epoch: [23] [ 190/2639] eta: 1:58:27 lr: 2.3059634422145725e-05 loss: 0.0346 (0.0450) time: 2.9005 data: 0.0076 max mem: 33370 +Epoch: [23] [ 200/2639] eta: 1:57:56 lr: 2.305498858061446e-05 loss: 0.0406 (0.0462) time: 2.8997 data: 0.0076 max mem: 33370 +Epoch: [23] [ 210/2639] eta: 1:57:23 lr: 2.305034263505978e-05 loss: 0.0406 (0.0461) time: 2.8751 data: 0.0077 max mem: 33370 +Epoch: [23] [ 220/2639] eta: 1:56:54 lr: 2.3045696585456065e-05 loss: 0.0393 (0.0459) time: 2.8865 data: 0.0075 max mem: 33370 +Epoch: [23] [ 230/2639] eta: 1:56:22 lr: 2.3041050431777676e-05 loss: 0.0362 (0.0456) time: 2.8880 data: 0.0075 max mem: 33370 +Epoch: [23] [ 240/2639] eta: 1:55:52 lr: 2.303640417399896e-05 loss: 0.0364 (0.0455) time: 2.8774 data: 0.0072 max mem: 33370 +Epoch: [23] [ 250/2639] eta: 1:55:18 lr: 2.303175781209425e-05 loss: 0.0444 (0.0456) time: 2.8632 data: 0.0074 max mem: 33370 +Epoch: [23] [ 260/2639] eta: 1:54:50 lr: 2.3027111346037884e-05 loss: 0.0406 (0.0455) time: 2.8771 data: 0.0079 max mem: 33370 +Epoch: [23] [ 270/2639] eta: 1:54:22 lr: 2.3022464775804158e-05 loss: 0.0350 (0.0454) time: 2.9100 data: 0.0079 max mem: 33370 +Epoch: [23] [ 280/2639] eta: 1:53:48 lr: 2.3017818101367385e-05 loss: 0.0337 (0.0453) time: 2.8728 data: 0.0078 max mem: 33370 +Epoch: [23] [ 290/2639] eta: 1:53:24 lr: 2.3013171322701856e-05 loss: 0.0342 (0.0452) time: 2.8932 data: 0.0077 max mem: 33370 +Epoch: [23] [ 300/2639] eta: 1:52:54 lr: 2.3008524439781838e-05 loss: 0.0365 (0.0450) time: 2.9209 data: 0.0081 max mem: 33370 +Epoch: [23] [ 310/2639] eta: 1:52:27 lr: 2.300387745258161e-05 loss: 0.0383 (0.0450) time: 2.9052 data: 0.0081 max mem: 33370 +Epoch: [23] [ 320/2639] eta: 1:51:58 lr: 2.299923036107541e-05 loss: 0.0441 (0.0450) time: 2.9038 data: 0.0076 max mem: 33370 +Epoch: [23] [ 330/2639] eta: 1:51:24 lr: 2.299458316523749e-05 loss: 0.0476 (0.0453) time: 2.8574 data: 0.0079 max mem: 33370 +Epoch: [23] [ 340/2639] eta: 1:50:54 lr: 2.2989935865042064e-05 loss: 0.0429 (0.0453) time: 2.8539 data: 0.0080 max mem: 33370 +Epoch: [23] [ 350/2639] eta: 1:50:27 lr: 2.2985288460463365e-05 loss: 0.0383 (0.0453) time: 2.9045 data: 0.0076 max mem: 33370 +Epoch: [23] [ 360/2639] eta: 1:49:59 lr: 2.2980640951475583e-05 loss: 0.0393 (0.0451) time: 2.9176 data: 0.0074 max mem: 33370 +Epoch: [23] [ 370/2639] eta: 1:49:33 lr: 2.2975993338052922e-05 loss: 0.0403 (0.0452) time: 2.9287 data: 0.0073 max mem: 33370 +Epoch: [23] [ 380/2639] eta: 1:49:03 lr: 2.2971345620169553e-05 loss: 0.0406 (0.0451) time: 2.9128 data: 0.0074 max mem: 33370 +Epoch: [23] [ 390/2639] eta: 1:48:33 lr: 2.296669779779965e-05 loss: 0.0406 (0.0450) time: 2.8772 data: 0.0076 max mem: 33370 +Epoch: [23] [ 400/2639] eta: 1:48:03 lr: 2.2962049870917357e-05 loss: 0.0386 (0.0448) time: 2.8806 data: 0.0076 max mem: 33370 +Epoch: [23] [ 410/2639] eta: 1:47:33 lr: 2.2957401839496835e-05 loss: 0.0376 (0.0449) time: 2.8809 data: 0.0076 max mem: 33370 +Epoch: [23] [ 420/2639] eta: 1:47:03 lr: 2.2952753703512196e-05 loss: 0.0336 (0.0448) time: 2.8748 data: 0.0076 max mem: 33370 +Epoch: [23] [ 430/2639] eta: 1:46:33 lr: 2.2948105462937572e-05 loss: 0.0358 (0.0447) time: 2.8753 data: 0.0076 max mem: 33370 +Epoch: [23] [ 440/2639] eta: 1:46:05 lr: 2.294345711774706e-05 loss: 0.0428 (0.0447) time: 2.8911 data: 0.0078 max mem: 33370 +Epoch: [23] [ 450/2639] eta: 1:45:33 lr: 2.2938808667914766e-05 loss: 0.0428 (0.0448) time: 2.8708 data: 0.0080 max mem: 33370 +Epoch: [23] [ 460/2639] eta: 1:45:06 lr: 2.2934160113414756e-05 loss: 0.0446 (0.0447) time: 2.8817 data: 0.0076 max mem: 33370 +Epoch: [23] [ 470/2639] eta: 1:44:34 lr: 2.2929511454221118e-05 loss: 0.0467 (0.0449) time: 2.8800 data: 0.0074 max mem: 33370 +Epoch: [23] [ 480/2639] eta: 1:44:02 lr: 2.2924862690307892e-05 loss: 0.0505 (0.0449) time: 2.8341 data: 0.0075 max mem: 33370 +Epoch: [23] [ 490/2639] eta: 1:43:32 lr: 2.292021382164914e-05 loss: 0.0439 (0.0451) time: 2.8481 data: 0.0078 max mem: 33370 +Epoch: [23] [ 500/2639] eta: 1:43:01 lr: 2.2915564848218878e-05 loss: 0.0405 (0.0450) time: 2.8486 data: 0.0081 max mem: 33370 +Epoch: [23] [ 510/2639] eta: 1:42:28 lr: 2.2910915769991136e-05 loss: 0.0385 (0.0448) time: 2.8113 data: 0.0079 max mem: 33370 +Epoch: [23] [ 520/2639] eta: 1:41:56 lr: 2.2906266586939922e-05 loss: 0.0340 (0.0448) time: 2.7969 data: 0.0079 max mem: 33370 +Epoch: [23] [ 530/2639] eta: 1:41:26 lr: 2.2901617299039227e-05 loss: 0.0350 (0.0448) time: 2.8391 data: 0.0078 max mem: 33370 +Epoch: [23] [ 540/2639] eta: 1:40:57 lr: 2.2896967906263045e-05 loss: 0.0354 (0.0447) time: 2.8776 data: 0.0074 max mem: 33370 +Epoch: [23] [ 550/2639] eta: 1:40:26 lr: 2.2892318408585336e-05 loss: 0.0374 (0.0447) time: 2.8544 data: 0.0072 max mem: 33370 +Epoch: [23] [ 560/2639] eta: 1:39:54 lr: 2.288766880598007e-05 loss: 0.0421 (0.0447) time: 2.8099 data: 0.0075 max mem: 33370 +Epoch: [23] [ 570/2639] eta: 1:39:24 lr: 2.288301909842118e-05 loss: 0.0455 (0.0447) time: 2.8212 data: 0.0079 max mem: 33370 +Epoch: [23] [ 580/2639] eta: 1:38:54 lr: 2.2878369285882615e-05 loss: 0.0381 (0.0446) time: 2.8585 data: 0.0080 max mem: 33370 +Epoch: [23] [ 590/2639] eta: 1:38:25 lr: 2.287371936833828e-05 loss: 0.0392 (0.0446) time: 2.8719 data: 0.0078 max mem: 33370 +Epoch: [23] [ 600/2639] eta: 1:37:56 lr: 2.2869069345762105e-05 loss: 0.0421 (0.0446) time: 2.8649 data: 0.0079 max mem: 33370 +Epoch: [23] [ 610/2639] eta: 1:37:28 lr: 2.2864419218127968e-05 loss: 0.0388 (0.0446) time: 2.8818 data: 0.0077 max mem: 33370 +Epoch: [23] [ 620/2639] eta: 1:37:00 lr: 2.285976898540977e-05 loss: 0.0362 (0.0446) time: 2.9063 data: 0.0072 max mem: 33370 +Epoch: [23] [ 630/2639] eta: 1:36:28 lr: 2.2855118647581367e-05 loss: 0.0370 (0.0446) time: 2.8565 data: 0.0072 max mem: 33370 +Epoch: [23] [ 640/2639] eta: 1:35:59 lr: 2.285046820461663e-05 loss: 0.0385 (0.0445) time: 2.8350 data: 0.0072 max mem: 33370 +Epoch: [23] [ 650/2639] eta: 1:35:28 lr: 2.2845817656489403e-05 loss: 0.0431 (0.0446) time: 2.8442 data: 0.0075 max mem: 33370 +Epoch: [23] [ 660/2639] eta: 1:35:00 lr: 2.284116700317353e-05 loss: 0.0429 (0.0447) time: 2.8665 data: 0.0076 max mem: 33370 +Epoch: [23] [ 670/2639] eta: 1:34:33 lr: 2.2836516244642818e-05 loss: 0.0416 (0.0448) time: 2.9114 data: 0.0078 max mem: 33370 +Epoch: [23] [ 680/2639] eta: 1:34:05 lr: 2.283186538087109e-05 loss: 0.0464 (0.0448) time: 2.9141 data: 0.0077 max mem: 33370 +Epoch: [23] [ 690/2639] eta: 1:33:35 lr: 2.282721441183213e-05 loss: 0.0489 (0.0449) time: 2.8759 data: 0.0071 max mem: 33370 +Epoch: [23] [ 700/2639] eta: 1:33:05 lr: 2.2822563337499745e-05 loss: 0.0423 (0.0449) time: 2.8446 data: 0.0075 max mem: 33370 +Epoch: [23] [ 710/2639] eta: 1:32:34 lr: 2.2817912157847683e-05 loss: 0.0426 (0.0450) time: 2.8256 data: 0.0082 max mem: 33370 +Epoch: [23] [ 720/2639] eta: 1:32:03 lr: 2.281326087284973e-05 loss: 0.0393 (0.0449) time: 2.8022 data: 0.0082 max mem: 33370 +Epoch: [23] [ 730/2639] eta: 1:31:34 lr: 2.2808609482479608e-05 loss: 0.0390 (0.0449) time: 2.8294 data: 0.0077 max mem: 33370 +Epoch: [23] [ 740/2639] eta: 1:31:04 lr: 2.2803957986711075e-05 loss: 0.0457 (0.0450) time: 2.8553 data: 0.0076 max mem: 33370 +Epoch: [23] [ 750/2639] eta: 1:30:35 lr: 2.2799306385517834e-05 loss: 0.0419 (0.0449) time: 2.8494 data: 0.0075 max mem: 33370 +Epoch: [23] [ 760/2639] eta: 1:30:06 lr: 2.2794654678873615e-05 loss: 0.0419 (0.0451) time: 2.8620 data: 0.0076 max mem: 33370 +Epoch: [23] [ 770/2639] eta: 1:29:37 lr: 2.27900028667521e-05 loss: 0.0542 (0.0453) time: 2.8627 data: 0.0076 max mem: 33370 +Epoch: [23] [ 780/2639] eta: 1:29:07 lr: 2.278535094912698e-05 loss: 0.0440 (0.0453) time: 2.8482 data: 0.0073 max mem: 33370 +Epoch: [23] [ 790/2639] eta: 1:28:39 lr: 2.2780698925971937e-05 loss: 0.0440 (0.0454) time: 2.8674 data: 0.0072 max mem: 33370 +Epoch: [23] [ 800/2639] eta: 1:28:10 lr: 2.2776046797260613e-05 loss: 0.0448 (0.0454) time: 2.8726 data: 0.0076 max mem: 33370 +Epoch: [23] [ 810/2639] eta: 1:27:41 lr: 2.2771394562966676e-05 loss: 0.0423 (0.0454) time: 2.8635 data: 0.0082 max mem: 33370 +Epoch: [23] [ 820/2639] eta: 1:27:12 lr: 2.2766742223063743e-05 loss: 0.0342 (0.0453) time: 2.8852 data: 0.0080 max mem: 33370 +Epoch: [23] [ 830/2639] eta: 1:26:43 lr: 2.2762089777525447e-05 loss: 0.0352 (0.0452) time: 2.8881 data: 0.0079 max mem: 33370 +Epoch: [23] [ 840/2639] eta: 1:26:13 lr: 2.2757437226325395e-05 loss: 0.0363 (0.0452) time: 2.8396 data: 0.0079 max mem: 33370 +Epoch: [23] [ 850/2639] eta: 1:25:44 lr: 2.2752784569437187e-05 loss: 0.0365 (0.0451) time: 2.8203 data: 0.0077 max mem: 33370 +Epoch: [23] [ 860/2639] eta: 1:25:15 lr: 2.2748131806834405e-05 loss: 0.0417 (0.0452) time: 2.8491 data: 0.0073 max mem: 33370 +Epoch: [23] [ 870/2639] eta: 1:24:46 lr: 2.2743478938490625e-05 loss: 0.0458 (0.0453) time: 2.8686 data: 0.0073 max mem: 33370 +Epoch: [23] [ 880/2639] eta: 1:24:17 lr: 2.27388259643794e-05 loss: 0.0430 (0.0453) time: 2.8650 data: 0.0074 max mem: 33370 +Epoch: [23] [ 890/2639] eta: 1:23:49 lr: 2.2734172884474284e-05 loss: 0.0387 (0.0453) time: 2.8866 data: 0.0073 max mem: 33370 +Epoch: [23] [ 900/2639] eta: 1:23:20 lr: 2.2729519698748803e-05 loss: 0.0412 (0.0454) time: 2.8951 data: 0.0074 max mem: 33370 +Epoch: [23] [ 910/2639] eta: 1:22:51 lr: 2.272486640717649e-05 loss: 0.0473 (0.0455) time: 2.8819 data: 0.0077 max mem: 33370 +Epoch: [23] [ 920/2639] eta: 1:22:23 lr: 2.2720213009730842e-05 loss: 0.0481 (0.0455) time: 2.8795 data: 0.0077 max mem: 33370 +Epoch: [23] [ 930/2639] eta: 1:21:54 lr: 2.271555950638537e-05 loss: 0.0406 (0.0455) time: 2.8768 data: 0.0077 max mem: 33370 +Epoch: [23] [ 940/2639] eta: 1:21:24 lr: 2.271090589711354e-05 loss: 0.0401 (0.0454) time: 2.8541 data: 0.0077 max mem: 33370 +Epoch: [23] [ 950/2639] eta: 1:20:55 lr: 2.270625218188884e-05 loss: 0.0419 (0.0455) time: 2.8257 data: 0.0077 max mem: 33370 +Epoch: [23] [ 960/2639] eta: 1:20:25 lr: 2.2701598360684716e-05 loss: 0.0422 (0.0455) time: 2.8208 data: 0.0077 max mem: 33370 +Epoch: [23] [ 970/2639] eta: 1:19:56 lr: 2.2696944433474623e-05 loss: 0.0388 (0.0454) time: 2.8392 data: 0.0075 max mem: 33370 +Epoch: [23] [ 980/2639] eta: 1:19:27 lr: 2.2692290400231984e-05 loss: 0.0378 (0.0454) time: 2.8615 data: 0.0075 max mem: 33370 +Epoch: [23] [ 990/2639] eta: 1:18:57 lr: 2.268763626093023e-05 loss: 0.0396 (0.0454) time: 2.8236 data: 0.0075 max mem: 33370 +Epoch: [23] [1000/2639] eta: 1:18:28 lr: 2.2682982015542757e-05 loss: 0.0396 (0.0454) time: 2.8240 data: 0.0077 max mem: 33370 +Epoch: [23] [1010/2639] eta: 1:17:59 lr: 2.267832766404297e-05 loss: 0.0470 (0.0455) time: 2.8676 data: 0.0077 max mem: 33370 +Epoch: [23] [1020/2639] eta: 1:17:30 lr: 2.267367320640425e-05 loss: 0.0434 (0.0454) time: 2.8541 data: 0.0076 max mem: 33370 +Epoch: [23] [1030/2639] eta: 1:17:02 lr: 2.2669018642599955e-05 loss: 0.0379 (0.0454) time: 2.8721 data: 0.0076 max mem: 33370 +Epoch: [23] [1040/2639] eta: 1:16:32 lr: 2.266436397260346e-05 loss: 0.0379 (0.0454) time: 2.8748 data: 0.0076 max mem: 33370 +Epoch: [23] [1050/2639] eta: 1:16:04 lr: 2.265970919638809e-05 loss: 0.0427 (0.0454) time: 2.8684 data: 0.0077 max mem: 33370 +Epoch: [23] [1060/2639] eta: 1:15:36 lr: 2.2655054313927192e-05 loss: 0.0438 (0.0454) time: 2.8881 data: 0.0075 max mem: 33370 +Epoch: [23] [1070/2639] eta: 1:15:07 lr: 2.2650399325194075e-05 loss: 0.0400 (0.0454) time: 2.8685 data: 0.0074 max mem: 33370 +Epoch: [23] [1080/2639] eta: 1:14:38 lr: 2.2645744230162046e-05 loss: 0.0381 (0.0454) time: 2.8747 data: 0.0075 max mem: 33370 +Epoch: [23] [1090/2639] eta: 1:14:09 lr: 2.2641089028804398e-05 loss: 0.0380 (0.0453) time: 2.8593 data: 0.0076 max mem: 33370 +Epoch: [23] [1100/2639] eta: 1:13:40 lr: 2.2636433721094418e-05 loss: 0.0376 (0.0454) time: 2.8381 data: 0.0078 max mem: 33370 +Epoch: [23] [1110/2639] eta: 1:13:10 lr: 2.2631778307005356e-05 loss: 0.0364 (0.0453) time: 2.8338 data: 0.0082 max mem: 33370 +Epoch: [23] [1120/2639] eta: 1:12:41 lr: 2.2627122786510484e-05 loss: 0.0324 (0.0453) time: 2.8178 data: 0.0080 max mem: 33370 +Epoch: [23] [1130/2639] eta: 1:12:11 lr: 2.262246715958303e-05 loss: 0.0381 (0.0453) time: 2.8203 data: 0.0079 max mem: 33370 +Epoch: [23] [1140/2639] eta: 1:11:43 lr: 2.261781142619623e-05 loss: 0.0443 (0.0455) time: 2.8542 data: 0.0079 max mem: 33370 +Epoch: [23] [1150/2639] eta: 1:11:14 lr: 2.2613155586323297e-05 loss: 0.0468 (0.0455) time: 2.8866 data: 0.0079 max mem: 33370 +Epoch: [23] [1160/2639] eta: 1:10:46 lr: 2.260849963993744e-05 loss: 0.0400 (0.0454) time: 2.9017 data: 0.0076 max mem: 33370 +Epoch: [23] [1170/2639] eta: 1:10:18 lr: 2.2603843587011833e-05 loss: 0.0400 (0.0454) time: 2.8963 data: 0.0075 max mem: 33370 +Epoch: [23] [1180/2639] eta: 1:09:49 lr: 2.2599187427519673e-05 loss: 0.0372 (0.0453) time: 2.8724 data: 0.0081 max mem: 33370 +Epoch: [23] [1190/2639] eta: 1:09:21 lr: 2.259453116143411e-05 loss: 0.0393 (0.0453) time: 2.8945 data: 0.0080 max mem: 33370 +Epoch: [23] [1200/2639] eta: 1:08:53 lr: 2.2589874788728303e-05 loss: 0.0397 (0.0454) time: 2.9328 data: 0.0073 max mem: 33370 +Epoch: [23] [1210/2639] eta: 1:08:24 lr: 2.2585218309375383e-05 loss: 0.0397 (0.0453) time: 2.9049 data: 0.0073 max mem: 33370 +Epoch: [23] [1220/2639] eta: 1:07:56 lr: 2.2580561723348483e-05 loss: 0.0392 (0.0453) time: 2.8888 data: 0.0073 max mem: 33370 +Epoch: [23] [1230/2639] eta: 1:07:28 lr: 2.2575905030620707e-05 loss: 0.0379 (0.0453) time: 2.9220 data: 0.0072 max mem: 33370 +Epoch: [23] [1240/2639] eta: 1:06:59 lr: 2.2571248231165164e-05 loss: 0.0377 (0.0452) time: 2.9010 data: 0.0076 max mem: 33370 +Epoch: [23] [1250/2639] eta: 1:06:31 lr: 2.2566591324954934e-05 loss: 0.0401 (0.0452) time: 2.8969 data: 0.0081 max mem: 33370 +Epoch: [23] [1260/2639] eta: 1:06:02 lr: 2.256193431196309e-05 loss: 0.0401 (0.0451) time: 2.8792 data: 0.0078 max mem: 33370 +Epoch: [23] [1270/2639] eta: 1:05:33 lr: 2.25572771921627e-05 loss: 0.0413 (0.0453) time: 2.8661 data: 0.0078 max mem: 33370 +Epoch: [23] [1280/2639] eta: 1:05:04 lr: 2.2552619965526802e-05 loss: 0.0485 (0.0453) time: 2.8760 data: 0.0078 max mem: 33370 +Epoch: [23] [1290/2639] eta: 1:04:35 lr: 2.254796263202844e-05 loss: 0.0389 (0.0453) time: 2.8391 data: 0.0071 max mem: 33370 +Epoch: [23] [1300/2639] eta: 1:04:06 lr: 2.2543305191640627e-05 loss: 0.0418 (0.0452) time: 2.8415 data: 0.0072 max mem: 33370 +Epoch: [23] [1310/2639] eta: 1:03:37 lr: 2.253864764433638e-05 loss: 0.0429 (0.0453) time: 2.8598 data: 0.0072 max mem: 33370 +Epoch: [23] [1320/2639] eta: 1:03:08 lr: 2.2533989990088685e-05 loss: 0.0426 (0.0452) time: 2.8462 data: 0.0073 max mem: 33370 +Epoch: [23] [1330/2639] eta: 1:02:40 lr: 2.2529332228870534e-05 loss: 0.0426 (0.0452) time: 2.8605 data: 0.0077 max mem: 33370 +Epoch: [23] [1340/2639] eta: 1:02:11 lr: 2.252467436065489e-05 loss: 0.0405 (0.0452) time: 2.9017 data: 0.0077 max mem: 33370 +Epoch: [23] [1350/2639] eta: 1:01:43 lr: 2.2520016385414717e-05 loss: 0.0405 (0.0452) time: 2.8902 data: 0.0077 max mem: 33370 +Epoch: [23] [1360/2639] eta: 1:01:13 lr: 2.2515358303122944e-05 loss: 0.0383 (0.0452) time: 2.8303 data: 0.0076 max mem: 33370 +Epoch: [23] [1370/2639] eta: 1:00:44 lr: 2.251070011375252e-05 loss: 0.0402 (0.0452) time: 2.8104 data: 0.0076 max mem: 33370 +Epoch: [23] [1380/2639] eta: 1:00:14 lr: 2.2506041817276348e-05 loss: 0.0403 (0.0452) time: 2.8000 data: 0.0076 max mem: 33370 +Epoch: [23] [1390/2639] eta: 0:59:45 lr: 2.2501383413667342e-05 loss: 0.0377 (0.0451) time: 2.7895 data: 0.0075 max mem: 33370 +Epoch: [23] [1400/2639] eta: 0:59:16 lr: 2.2496724902898382e-05 loss: 0.0348 (0.0452) time: 2.8204 data: 0.0074 max mem: 33370 +Epoch: [23] [1410/2639] eta: 0:58:47 lr: 2.2492066284942356e-05 loss: 0.0390 (0.0453) time: 2.8515 data: 0.0077 max mem: 33370 +Epoch: [23] [1420/2639] eta: 0:58:18 lr: 2.2487407559772125e-05 loss: 0.0426 (0.0452) time: 2.8569 data: 0.0076 max mem: 33370 +Epoch: [23] [1430/2639] eta: 0:57:50 lr: 2.2482748727360543e-05 loss: 0.0405 (0.0452) time: 2.8711 data: 0.0075 max mem: 33370 +Epoch: [23] [1440/2639] eta: 0:57:21 lr: 2.2478089787680445e-05 loss: 0.0426 (0.0452) time: 2.8712 data: 0.0076 max mem: 33370 +Epoch: [23] [1450/2639] eta: 0:56:52 lr: 2.2473430740704664e-05 loss: 0.0437 (0.0452) time: 2.8580 data: 0.0075 max mem: 33370 +Epoch: [23] [1460/2639] eta: 0:56:24 lr: 2.2468771586406e-05 loss: 0.0421 (0.0452) time: 2.8926 data: 0.0076 max mem: 33370 +Epoch: [23] [1470/2639] eta: 0:55:55 lr: 2.2464112324757267e-05 loss: 0.0377 (0.0452) time: 2.8976 data: 0.0075 max mem: 33370 +Epoch: [23] [1480/2639] eta: 0:55:27 lr: 2.2459452955731238e-05 loss: 0.0377 (0.0452) time: 2.9055 data: 0.0072 max mem: 33370 +Epoch: [23] [1490/2639] eta: 0:54:58 lr: 2.2454793479300696e-05 loss: 0.0400 (0.0451) time: 2.8751 data: 0.0072 max mem: 33370 +Epoch: [23] [1500/2639] eta: 0:54:29 lr: 2.245013389543839e-05 loss: 0.0368 (0.0451) time: 2.8630 data: 0.0071 max mem: 33370 +Epoch: [23] [1510/2639] eta: 0:54:01 lr: 2.2445474204117074e-05 loss: 0.0370 (0.0450) time: 2.8762 data: 0.0071 max mem: 33370 +Epoch: [23] [1520/2639] eta: 0:53:32 lr: 2.244081440530949e-05 loss: 0.0386 (0.0451) time: 2.8525 data: 0.0072 max mem: 33370 +Epoch: [23] [1530/2639] eta: 0:53:03 lr: 2.2436154498988337e-05 loss: 0.0489 (0.0452) time: 2.8725 data: 0.0072 max mem: 33370 +Epoch: [23] [1540/2639] eta: 0:52:35 lr: 2.243149448512634e-05 loss: 0.0465 (0.0451) time: 2.8911 data: 0.0074 max mem: 33370 +Epoch: [23] [1550/2639] eta: 0:52:06 lr: 2.2426834363696184e-05 loss: 0.0415 (0.0451) time: 2.8760 data: 0.0075 max mem: 33370 +Epoch: [23] [1560/2639] eta: 0:51:37 lr: 2.2422174134670557e-05 loss: 0.0391 (0.0451) time: 2.8841 data: 0.0073 max mem: 33370 +Epoch: [23] [1570/2639] eta: 0:51:09 lr: 2.2417513798022112e-05 loss: 0.0394 (0.0452) time: 2.8885 data: 0.0071 max mem: 33370 +Epoch: [23] [1580/2639] eta: 0:50:40 lr: 2.241285335372352e-05 loss: 0.0502 (0.0452) time: 2.8661 data: 0.0073 max mem: 33370 +Epoch: [23] [1590/2639] eta: 0:50:11 lr: 2.2408192801747406e-05 loss: 0.0399 (0.0452) time: 2.8443 data: 0.0076 max mem: 33370 +Epoch: [23] [1600/2639] eta: 0:49:42 lr: 2.240353214206641e-05 loss: 0.0398 (0.0452) time: 2.8142 data: 0.0076 max mem: 33370 +Epoch: [23] [1610/2639] eta: 0:49:13 lr: 2.239887137465314e-05 loss: 0.0428 (0.0452) time: 2.8459 data: 0.0076 max mem: 33370 +Epoch: [23] [1620/2639] eta: 0:48:44 lr: 2.2394210499480198e-05 loss: 0.0428 (0.0452) time: 2.8777 data: 0.0075 max mem: 33370 +Epoch: [23] [1630/2639] eta: 0:48:16 lr: 2.238954951652017e-05 loss: 0.0374 (0.0452) time: 2.8527 data: 0.0074 max mem: 33370 +Epoch: [23] [1640/2639] eta: 0:47:47 lr: 2.2384888425745634e-05 loss: 0.0523 (0.0452) time: 2.8797 data: 0.0076 max mem: 33370 +Epoch: [23] [1650/2639] eta: 0:47:18 lr: 2.2380227227129144e-05 loss: 0.0465 (0.0452) time: 2.8943 data: 0.0075 max mem: 33370 +Epoch: [23] [1660/2639] eta: 0:46:50 lr: 2.237556592064326e-05 loss: 0.0420 (0.0452) time: 2.8670 data: 0.0077 max mem: 33370 +Epoch: [23] [1670/2639] eta: 0:46:21 lr: 2.23709045062605e-05 loss: 0.0404 (0.0452) time: 2.9073 data: 0.0076 max mem: 33370 +Epoch: [23] [1680/2639] eta: 0:45:53 lr: 2.23662429839534e-05 loss: 0.0456 (0.0454) time: 2.9218 data: 0.0072 max mem: 33370 +Epoch: [23] [1690/2639] eta: 0:45:25 lr: 2.2361581353694454e-05 loss: 0.0472 (0.0454) time: 2.9206 data: 0.0072 max mem: 33370 +Epoch: [23] [1700/2639] eta: 0:44:56 lr: 2.235691961545617e-05 loss: 0.0424 (0.0453) time: 2.9021 data: 0.0073 max mem: 33370 +Epoch: [23] [1710/2639] eta: 0:44:27 lr: 2.2352257769211014e-05 loss: 0.0383 (0.0453) time: 2.8906 data: 0.0073 max mem: 33370 +Epoch: [23] [1720/2639] eta: 0:43:59 lr: 2.2347595814931468e-05 loss: 0.0438 (0.0454) time: 2.9320 data: 0.0071 max mem: 33370 +Epoch: [23] [1730/2639] eta: 0:43:30 lr: 2.2342933752589972e-05 loss: 0.0423 (0.0454) time: 2.8958 data: 0.0073 max mem: 33370 +Epoch: [23] [1740/2639] eta: 0:43:01 lr: 2.2338271582158982e-05 loss: 0.0415 (0.0455) time: 2.8626 data: 0.0076 max mem: 33370 +Epoch: [23] [1750/2639] eta: 0:42:33 lr: 2.2333609303610907e-05 loss: 0.0422 (0.0454) time: 2.8868 data: 0.0073 max mem: 33370 +Epoch: [23] [1760/2639] eta: 0:42:04 lr: 2.232894691691817e-05 loss: 0.0422 (0.0454) time: 2.8735 data: 0.0074 max mem: 33370 +Epoch: [23] [1770/2639] eta: 0:41:35 lr: 2.232428442205318e-05 loss: 0.0423 (0.0454) time: 2.8641 data: 0.0076 max mem: 33370 +Epoch: [23] [1780/2639] eta: 0:41:07 lr: 2.231962181898831e-05 loss: 0.0410 (0.0454) time: 2.8910 data: 0.0075 max mem: 33370 +Epoch: [23] [1790/2639] eta: 0:40:38 lr: 2.231495910769594e-05 loss: 0.0410 (0.0455) time: 2.8728 data: 0.0072 max mem: 33370 +Epoch: [23] [1800/2639] eta: 0:40:09 lr: 2.2310296288148426e-05 loss: 0.0498 (0.0455) time: 2.8618 data: 0.0072 max mem: 33370 +Epoch: [23] [1810/2639] eta: 0:39:41 lr: 2.230563336031812e-05 loss: 0.0457 (0.0455) time: 2.8864 data: 0.0072 max mem: 33370 +Epoch: [23] [1820/2639] eta: 0:39:12 lr: 2.2300970324177347e-05 loss: 0.0388 (0.0454) time: 2.8976 data: 0.0075 max mem: 33370 +Epoch: [23] [1830/2639] eta: 0:38:44 lr: 2.2296307179698437e-05 loss: 0.0361 (0.0454) time: 2.9181 data: 0.0075 max mem: 33370 +Epoch: [23] [1840/2639] eta: 0:38:15 lr: 2.2291643926853683e-05 loss: 0.0383 (0.0454) time: 2.9145 data: 0.0072 max mem: 33370 +Epoch: [23] [1850/2639] eta: 0:37:46 lr: 2.228698056561539e-05 loss: 0.0401 (0.0454) time: 2.8769 data: 0.0073 max mem: 33370 +Epoch: [23] [1860/2639] eta: 0:37:17 lr: 2.2282317095955828e-05 loss: 0.0401 (0.0454) time: 2.8580 data: 0.0074 max mem: 33370 +Epoch: [23] [1870/2639] eta: 0:36:49 lr: 2.2277653517847267e-05 loss: 0.0380 (0.0454) time: 2.8654 data: 0.0074 max mem: 33370 +Epoch: [23] [1880/2639] eta: 0:36:20 lr: 2.2272989831261954e-05 loss: 0.0380 (0.0454) time: 2.8691 data: 0.0073 max mem: 33370 +Epoch: [23] [1890/2639] eta: 0:35:51 lr: 2.2268326036172135e-05 loss: 0.0485 (0.0454) time: 2.8930 data: 0.0073 max mem: 33370 +Epoch: [23] [1900/2639] eta: 0:35:23 lr: 2.2263662132550022e-05 loss: 0.0461 (0.0455) time: 2.9029 data: 0.0077 max mem: 33370 +Epoch: [23] [1910/2639] eta: 0:34:54 lr: 2.2258998120367843e-05 loss: 0.0435 (0.0455) time: 2.8721 data: 0.0076 max mem: 33370 +Epoch: [23] [1920/2639] eta: 0:34:25 lr: 2.225433399959778e-05 loss: 0.0398 (0.0455) time: 2.8703 data: 0.0072 max mem: 33370 +Epoch: [23] [1930/2639] eta: 0:33:56 lr: 2.224966977021203e-05 loss: 0.0412 (0.0455) time: 2.8431 data: 0.0074 max mem: 33370 +Epoch: [23] [1940/2639] eta: 0:33:28 lr: 2.2245005432182747e-05 loss: 0.0441 (0.0455) time: 2.8514 data: 0.0075 max mem: 33370 +Epoch: [23] [1950/2639] eta: 0:32:59 lr: 2.2240340985482106e-05 loss: 0.0379 (0.0454) time: 2.8764 data: 0.0075 max mem: 33370 +Epoch: [23] [1960/2639] eta: 0:32:30 lr: 2.2235676430082235e-05 loss: 0.0400 (0.0455) time: 2.8582 data: 0.0075 max mem: 33370 +Epoch: [23] [1970/2639] eta: 0:32:01 lr: 2.2231011765955273e-05 loss: 0.0380 (0.0454) time: 2.8589 data: 0.0073 max mem: 33370 +Epoch: [23] [1980/2639] eta: 0:31:33 lr: 2.222634699307333e-05 loss: 0.0399 (0.0454) time: 2.8796 data: 0.0073 max mem: 33370 +Epoch: [23] [1990/2639] eta: 0:31:04 lr: 2.2221682111408514e-05 loss: 0.0399 (0.0454) time: 2.8704 data: 0.0075 max mem: 33370 +Epoch: [23] [2000/2639] eta: 0:30:35 lr: 2.2217017120932904e-05 loss: 0.0352 (0.0454) time: 2.8614 data: 0.0075 max mem: 33370 +Epoch: [23] [2010/2639] eta: 0:30:06 lr: 2.221235202161858e-05 loss: 0.0352 (0.0454) time: 2.8923 data: 0.0073 max mem: 33370 +Epoch: [23] [2020/2639] eta: 0:29:38 lr: 2.220768681343761e-05 loss: 0.0416 (0.0454) time: 2.8764 data: 0.0075 max mem: 33370 +Epoch: [23] [2030/2639] eta: 0:29:09 lr: 2.220302149636203e-05 loss: 0.0413 (0.0454) time: 2.8615 data: 0.0076 max mem: 33370 +Epoch: [23] [2040/2639] eta: 0:28:40 lr: 2.2198356070363885e-05 loss: 0.0398 (0.0454) time: 2.8402 data: 0.0073 max mem: 33370 +Epoch: [23] [2050/2639] eta: 0:28:11 lr: 2.219369053541518e-05 loss: 0.0395 (0.0454) time: 2.8339 data: 0.0072 max mem: 33370 +Epoch: [23] [2060/2639] eta: 0:27:42 lr: 2.2189024891487936e-05 loss: 0.0321 (0.0453) time: 2.8491 data: 0.0073 max mem: 33370 +Epoch: [23] [2070/2639] eta: 0:27:14 lr: 2.2184359138554134e-05 loss: 0.0321 (0.0453) time: 2.8782 data: 0.0072 max mem: 33370 +Epoch: [23] [2080/2639] eta: 0:26:45 lr: 2.2179693276585762e-05 loss: 0.0390 (0.0453) time: 2.8994 data: 0.0070 max mem: 33370 +Epoch: [23] [2090/2639] eta: 0:26:16 lr: 2.217502730555478e-05 loss: 0.0390 (0.0453) time: 2.8693 data: 0.0071 max mem: 33370 +Epoch: [23] [2100/2639] eta: 0:25:48 lr: 2.2170361225433144e-05 loss: 0.0421 (0.0453) time: 2.8588 data: 0.0072 max mem: 33370 +Epoch: [23] [2110/2639] eta: 0:25:19 lr: 2.2165695036192776e-05 loss: 0.0430 (0.0453) time: 2.8529 data: 0.0075 max mem: 33370 +Epoch: [23] [2120/2639] eta: 0:24:50 lr: 2.2161028737805623e-05 loss: 0.0386 (0.0453) time: 2.8361 data: 0.0077 max mem: 33370 +Epoch: [23] [2130/2639] eta: 0:24:21 lr: 2.2156362330243577e-05 loss: 0.0399 (0.0454) time: 2.8643 data: 0.0077 max mem: 33370 +Epoch: [23] [2140/2639] eta: 0:23:53 lr: 2.2151695813478543e-05 loss: 0.0425 (0.0454) time: 2.8777 data: 0.0073 max mem: 33370 +Epoch: [23] [2150/2639] eta: 0:23:24 lr: 2.2147029187482397e-05 loss: 0.0425 (0.0454) time: 2.8480 data: 0.0072 max mem: 33370 +Epoch: [23] [2160/2639] eta: 0:22:55 lr: 2.2142362452227014e-05 loss: 0.0417 (0.0454) time: 2.8894 data: 0.0074 max mem: 33370 +Epoch: [23] [2170/2639] eta: 0:22:27 lr: 2.213769560768424e-05 loss: 0.0417 (0.0454) time: 2.9151 data: 0.0073 max mem: 33370 +Epoch: [23] [2180/2639] eta: 0:21:58 lr: 2.213302865382593e-05 loss: 0.0399 (0.0454) time: 2.8824 data: 0.0073 max mem: 33370 +Epoch: [23] [2190/2639] eta: 0:21:29 lr: 2.2128361590623894e-05 loss: 0.0340 (0.0454) time: 2.9036 data: 0.0075 max mem: 33370 +Epoch: [23] [2200/2639] eta: 0:21:01 lr: 2.212369441804996e-05 loss: 0.0387 (0.0454) time: 2.9181 data: 0.0073 max mem: 33370 +Epoch: [23] [2210/2639] eta: 0:20:32 lr: 2.211902713607591e-05 loss: 0.0469 (0.0454) time: 2.8697 data: 0.0071 max mem: 33370 +Epoch: [23] [2220/2639] eta: 0:20:03 lr: 2.211435974467355e-05 loss: 0.0400 (0.0454) time: 2.8542 data: 0.0072 max mem: 33370 +Epoch: [23] [2230/2639] eta: 0:19:34 lr: 2.210969224381463e-05 loss: 0.0437 (0.0454) time: 2.8768 data: 0.0072 max mem: 33370 +Epoch: [23] [2240/2639] eta: 0:19:06 lr: 2.2105024633470928e-05 loss: 0.0449 (0.0454) time: 2.8722 data: 0.0069 max mem: 33370 +Epoch: [23] [2250/2639] eta: 0:18:37 lr: 2.2100356913614174e-05 loss: 0.0378 (0.0454) time: 2.8510 data: 0.0073 max mem: 33370 +Epoch: [23] [2260/2639] eta: 0:18:08 lr: 2.2095689084216094e-05 loss: 0.0392 (0.0454) time: 2.8439 data: 0.0076 max mem: 33370 +Epoch: [23] [2270/2639] eta: 0:17:39 lr: 2.2091021145248424e-05 loss: 0.0398 (0.0454) time: 2.8769 data: 0.0072 max mem: 33370 +Epoch: [23] [2280/2639] eta: 0:17:11 lr: 2.2086353096682845e-05 loss: 0.0398 (0.0454) time: 2.8653 data: 0.0071 max mem: 33370 +Epoch: [23] [2290/2639] eta: 0:16:42 lr: 2.2081684938491054e-05 loss: 0.0403 (0.0454) time: 2.8471 data: 0.0072 max mem: 33370 +Epoch: [23] [2300/2639] eta: 0:16:13 lr: 2.2077016670644722e-05 loss: 0.0427 (0.0454) time: 2.8487 data: 0.0076 max mem: 33370 +Epoch: [23] [2310/2639] eta: 0:15:44 lr: 2.2072348293115514e-05 loss: 0.0430 (0.0454) time: 2.8485 data: 0.0075 max mem: 33370 +Epoch: [23] [2320/2639] eta: 0:15:16 lr: 2.2067679805875065e-05 loss: 0.0397 (0.0453) time: 2.9004 data: 0.0071 max mem: 33370 +Epoch: [23] [2330/2639] eta: 0:14:47 lr: 2.2063011208895024e-05 loss: 0.0397 (0.0453) time: 2.8923 data: 0.0072 max mem: 33370 +Epoch: [23] [2340/2639] eta: 0:14:18 lr: 2.205834250214699e-05 loss: 0.0399 (0.0453) time: 2.8658 data: 0.0072 max mem: 33370 +Epoch: [23] [2350/2639] eta: 0:13:50 lr: 2.205367368560258e-05 loss: 0.0441 (0.0454) time: 2.8785 data: 0.0097 max mem: 33370 +Epoch: [23] [2360/2639] eta: 0:13:21 lr: 2.2049004759233377e-05 loss: 0.0467 (0.0453) time: 2.9164 data: 0.0255 max mem: 33370 +Epoch: [23] [2370/2639] eta: 0:12:52 lr: 2.204433572301096e-05 loss: 0.0470 (0.0454) time: 2.8992 data: 0.0228 max mem: 33370 +Epoch: [23] [2380/2639] eta: 0:12:23 lr: 2.203966657690689e-05 loss: 0.0476 (0.0455) time: 2.8649 data: 0.0072 max mem: 33370 +Epoch: [23] [2390/2639] eta: 0:11:55 lr: 2.2034997320892716e-05 loss: 0.0426 (0.0454) time: 2.8914 data: 0.0074 max mem: 33370 +Epoch: [23] [2400/2639] eta: 0:11:26 lr: 2.2030327954939966e-05 loss: 0.0426 (0.0455) time: 2.8628 data: 0.0072 max mem: 33370 +Epoch: [23] [2410/2639] eta: 0:10:57 lr: 2.202565847902017e-05 loss: 0.0340 (0.0454) time: 2.8184 data: 0.0070 max mem: 33370 +Epoch: [23] [2420/2639] eta: 0:10:31 lr: 2.202098889310482e-05 loss: 0.0374 (0.0455) time: 4.1151 data: 0.0070 max mem: 33370 +Epoch: [23] [2430/2639] eta: 0:10:02 lr: 2.2016319197165418e-05 loss: 0.0426 (0.0455) time: 4.1555 data: 0.0070 max mem: 33370 +Epoch: [23] [2440/2639] eta: 0:09:33 lr: 2.2011649391173434e-05 loss: 0.0370 (0.0455) time: 2.9940 data: 0.0229 max mem: 33370 +Epoch: [23] [2450/2639] eta: 0:09:04 lr: 2.200697947510034e-05 loss: 0.0365 (0.0455) time: 2.9868 data: 0.0226 max mem: 33370 +Epoch: [23] [2460/2639] eta: 0:08:36 lr: 2.2002309448917574e-05 loss: 0.0408 (0.0454) time: 2.8795 data: 0.0067 max mem: 33370 +Epoch: [23] [2470/2639] eta: 0:08:07 lr: 2.1997639312596582e-05 loss: 0.0395 (0.0454) time: 2.8702 data: 0.0069 max mem: 33370 +Epoch: [23] [2480/2639] eta: 0:07:38 lr: 2.1992969066108773e-05 loss: 0.0404 (0.0454) time: 2.8918 data: 0.0069 max mem: 33370 +Epoch: [23] [2490/2639] eta: 0:07:09 lr: 2.1988298709425566e-05 loss: 0.0428 (0.0455) time: 2.8972 data: 0.0068 max mem: 33370 +Epoch: [23] [2500/2639] eta: 0:06:40 lr: 2.198362824251834e-05 loss: 0.0428 (0.0454) time: 2.8701 data: 0.0071 max mem: 33370 +Epoch: [23] [2510/2639] eta: 0:06:11 lr: 2.197895766535848e-05 loss: 0.0471 (0.0455) time: 2.8934 data: 0.0069 max mem: 33370 +Epoch: [23] [2520/2639] eta: 0:05:43 lr: 2.197428697791736e-05 loss: 0.0475 (0.0455) time: 2.9186 data: 0.0067 max mem: 33370 +Epoch: [23] [2530/2639] eta: 0:05:14 lr: 2.196961618016631e-05 loss: 0.0464 (0.0455) time: 2.8827 data: 0.0072 max mem: 33370 +Epoch: [23] [2540/2639] eta: 0:04:45 lr: 2.196494527207668e-05 loss: 0.0447 (0.0455) time: 2.8492 data: 0.0074 max mem: 33370 +Epoch: [23] [2550/2639] eta: 0:04:16 lr: 2.1960274253619783e-05 loss: 0.0404 (0.0455) time: 2.8771 data: 0.0072 max mem: 33370 +Epoch: [23] [2560/2639] eta: 0:03:47 lr: 2.195560312476694e-05 loss: 0.0383 (0.0455) time: 2.9027 data: 0.0071 max mem: 33370 +Epoch: [23] [2570/2639] eta: 0:03:18 lr: 2.195093188548942e-05 loss: 0.0458 (0.0455) time: 2.9170 data: 0.0074 max mem: 33370 +Epoch: [23] [2580/2639] eta: 0:02:50 lr: 2.194626053575852e-05 loss: 0.0434 (0.0456) time: 2.9232 data: 0.0076 max mem: 33370 +Epoch: [23] [2590/2639] eta: 0:02:21 lr: 2.1941589075545503e-05 loss: 0.0454 (0.0456) time: 2.8921 data: 0.0072 max mem: 33370 +Epoch: [23] [2600/2639] eta: 0:01:52 lr: 2.1936917504821614e-05 loss: 0.0452 (0.0456) time: 2.8374 data: 0.0071 max mem: 33370 +Epoch: [23] [2610/2639] eta: 0:01:23 lr: 2.1932245823558086e-05 loss: 0.0420 (0.0456) time: 2.8113 data: 0.0073 max mem: 33370 +Epoch: [23] [2620/2639] eta: 0:00:54 lr: 2.1927574031726153e-05 loss: 0.0441 (0.0456) time: 2.8463 data: 0.0075 max mem: 33370 +Epoch: [23] [2630/2639] eta: 0:00:25 lr: 2.1922902129297006e-05 loss: 0.0448 (0.0456) time: 2.8277 data: 0.0073 max mem: 33370 +Epoch: [23] Total time: 2:06:48 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 3:41:47 time: 5.1719 data: 5.0624 max mem: 33370 +Test: [ 100/2573] eta: 0:05:12 time: 0.0760 data: 0.0014 max mem: 33370 +Test: [ 200/2573] eta: 0:04:03 time: 0.0784 data: 0.0014 max mem: 33370 +Test: [ 300/2573] eta: 0:03:34 time: 0.0798 data: 0.0014 max mem: 33370 +Test: [ 400/2573] eta: 0:03:16 time: 0.0797 data: 0.0013 max mem: 33370 +Test: [ 500/2573] eta: 0:03:02 time: 0.0785 data: 0.0013 max mem: 33370 +Test: [ 600/2573] eta: 0:02:50 time: 0.0788 data: 0.0014 max mem: 33370 +Test: [ 700/2573] eta: 0:02:40 time: 0.0792 data: 0.0014 max mem: 33370 +Test: [ 800/2573] eta: 0:02:30 time: 0.0833 data: 0.0014 max mem: 33370 +Test: [ 900/2573] eta: 0:02:21 time: 0.0787 data: 0.0014 max mem: 33370 +Test: [1000/2573] eta: 0:02:12 time: 0.0793 data: 0.0014 max mem: 33370 +Test: [1100/2573] eta: 0:02:03 time: 0.0787 data: 0.0013 max mem: 33370 +Test: [1200/2573] eta: 0:01:54 time: 0.0803 data: 0.0013 max mem: 33370 +Test: [1300/2573] eta: 0:01:45 time: 0.0796 data: 0.0015 max mem: 33370 +Test: [1400/2573] eta: 0:01:37 time: 0.0794 data: 0.0015 max mem: 33370 +Test: [1500/2573] eta: 0:01:28 time: 0.0795 data: 0.0014 max mem: 33370 +Test: [1600/2573] eta: 0:01:20 time: 0.0831 data: 0.0013 max mem: 33370 +Test: [1700/2573] eta: 0:01:11 time: 0.0784 data: 0.0014 max mem: 33370 +Test: [1800/2573] eta: 0:01:03 time: 0.0815 data: 0.0014 max mem: 33370 +Test: [1900/2573] eta: 0:00:55 time: 0.0785 data: 0.0021 max mem: 33370 +Test: [2000/2573] eta: 0:00:46 time: 0.0799 data: 0.0013 max mem: 33370 +Test: [2100/2573] eta: 0:00:38 time: 0.0814 data: 0.0013 max mem: 33370 +Test: [2200/2573] eta: 0:00:30 time: 0.0810 data: 0.0014 max mem: 33370 +Test: [2300/2573] eta: 0:00:22 time: 0.0811 data: 0.0013 max mem: 33370 +Test: [2400/2573] eta: 0:00:14 time: 0.0762 data: 0.0014 max mem: 33370 +Test: [2500/2573] eta: 0:00:05 time: 0.0798 data: 0.0014 max mem: 33370 +Test: Total time: 0:03:30 +Final results: +Mean IoU is 63.67 + + precision@0.5 = 71.61 + precision@0.6 = 66.40 + precision@0.7 = 59.58 + precision@0.8 = 47.18 + precision@0.9 = 22.92 + overall IoU = 61.42 + +Average object IoU 63.66838572839939 +Overall IoU 61.415260314941406 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [24] [ 0/2639] eta: 4:14:23 lr: 2.1918697322526357e-05 loss: 0.0619 (0.0619) time: 5.7839 data: 2.7643 max mem: 33370 +Epoch: [24] [ 10/2639] eta: 2:17:43 lr: 2.191402520988315e-05 loss: 0.0412 (0.0473) time: 3.1433 data: 0.2583 max mem: 33370 +Epoch: [24] [ 20/2639] eta: 2:09:41 lr: 2.190935298655915e-05 loss: 0.0386 (0.0479) time: 2.8306 data: 0.0074 max mem: 33370 +Epoch: [24] [ 30/2639] eta: 2:08:36 lr: 2.190468065252552e-05 loss: 0.0366 (0.0440) time: 2.8558 data: 0.0073 max mem: 33370 +Epoch: [24] [ 40/2639] eta: 2:07:37 lr: 2.190000820775339e-05 loss: 0.0387 (0.0430) time: 2.9199 data: 0.0078 max mem: 33370 +Epoch: [24] [ 50/2639] eta: 2:06:10 lr: 2.1895335652213885e-05 loss: 0.0387 (0.0415) time: 2.8717 data: 0.0076 max mem: 33370 +Epoch: [24] [ 60/2639] eta: 2:05:38 lr: 2.189066298587811e-05 loss: 0.0358 (0.0412) time: 2.8755 data: 0.0072 max mem: 33370 +Epoch: [24] [ 70/2639] eta: 2:04:38 lr: 2.1885990208717168e-05 loss: 0.0366 (0.0408) time: 2.8773 data: 0.0075 max mem: 33370 +Epoch: [24] [ 80/2639] eta: 2:04:05 lr: 2.1881317320702124e-05 loss: 0.0366 (0.0402) time: 2.8688 data: 0.0075 max mem: 33370 +Epoch: [24] [ 90/2639] eta: 2:03:27 lr: 2.1876644321804056e-05 loss: 0.0370 (0.0400) time: 2.8890 data: 0.0073 max mem: 33370 +Epoch: [24] [ 100/2639] eta: 2:02:49 lr: 2.1871971211994004e-05 loss: 0.0379 (0.0405) time: 2.8744 data: 0.0074 max mem: 33370 +Epoch: [24] [ 110/2639] eta: 2:02:08 lr: 2.186729799124302e-05 loss: 0.0380 (0.0406) time: 2.8601 data: 0.0074 max mem: 33370 +Epoch: [24] [ 120/2639] eta: 2:01:31 lr: 2.18626246595221e-05 loss: 0.0380 (0.0405) time: 2.8533 data: 0.0074 max mem: 33370 +Epoch: [24] [ 130/2639] eta: 2:00:53 lr: 2.1857951216802276e-05 loss: 0.0380 (0.0416) time: 2.8533 data: 0.0074 max mem: 33370 +Epoch: [24] [ 140/2639] eta: 2:00:06 lr: 2.185327766305453e-05 loss: 0.0384 (0.0416) time: 2.8193 data: 0.0075 max mem: 33370 +Epoch: [24] [ 150/2639] eta: 1:59:30 lr: 2.184860399824984e-05 loss: 0.0378 (0.0416) time: 2.8155 data: 0.0074 max mem: 33370 +Epoch: [24] [ 160/2639] eta: 1:58:56 lr: 2.184393022235917e-05 loss: 0.0378 (0.0417) time: 2.8420 data: 0.0075 max mem: 33370 +Epoch: [24] [ 170/2639] eta: 1:58:30 lr: 2.1839256335353472e-05 loss: 0.0306 (0.0411) time: 2.8714 data: 0.0077 max mem: 33370 +Epoch: [24] [ 180/2639] eta: 1:58:03 lr: 2.183458233720368e-05 loss: 0.0328 (0.0414) time: 2.8985 data: 0.0074 max mem: 33370 +Epoch: [24] [ 190/2639] eta: 1:57:29 lr: 2.182990822788071e-05 loss: 0.0412 (0.0418) time: 2.8664 data: 0.0075 max mem: 33370 +Epoch: [24] [ 200/2639] eta: 1:56:58 lr: 2.1825234007355477e-05 loss: 0.0394 (0.0415) time: 2.8480 data: 0.0077 max mem: 33370 +Epoch: [24] [ 210/2639] eta: 1:56:27 lr: 2.182055967559886e-05 loss: 0.0396 (0.0415) time: 2.8604 data: 0.0078 max mem: 33370 +Epoch: [24] [ 220/2639] eta: 1:55:56 lr: 2.1815885232581747e-05 loss: 0.0407 (0.0413) time: 2.8585 data: 0.0078 max mem: 33370 +Epoch: [24] [ 230/2639] eta: 1:55:18 lr: 2.1811210678274988e-05 loss: 0.0383 (0.0412) time: 2.8205 data: 0.0076 max mem: 33370 +Epoch: [24] [ 240/2639] eta: 1:54:46 lr: 2.1806536012649445e-05 loss: 0.0383 (0.0412) time: 2.8139 data: 0.0074 max mem: 33370 +Epoch: [24] [ 250/2639] eta: 1:54:15 lr: 2.180186123567594e-05 loss: 0.0415 (0.0414) time: 2.8430 data: 0.0072 max mem: 33370 +Epoch: [24] [ 260/2639] eta: 1:53:41 lr: 2.1797186347325298e-05 loss: 0.0354 (0.0415) time: 2.8263 data: 0.0077 max mem: 33370 +Epoch: [24] [ 270/2639] eta: 1:53:09 lr: 2.1792511347568313e-05 loss: 0.0350 (0.0414) time: 2.8219 data: 0.0076 max mem: 33370 +Epoch: [24] [ 280/2639] eta: 1:52:39 lr: 2.1787836236375786e-05 loss: 0.0390 (0.0414) time: 2.8423 data: 0.0073 max mem: 33370 +Epoch: [24] [ 290/2639] eta: 1:52:08 lr: 2.178316101371848e-05 loss: 0.0385 (0.0414) time: 2.8438 data: 0.0073 max mem: 33370 +Epoch: [24] [ 300/2639] eta: 1:51:46 lr: 2.177848567956717e-05 loss: 0.0371 (0.0414) time: 2.8920 data: 0.0074 max mem: 33370 +Epoch: [24] [ 310/2639] eta: 1:51:22 lr: 2.1773810233892582e-05 loss: 0.0370 (0.0414) time: 2.9385 data: 0.0074 max mem: 33370 +Epoch: [24] [ 320/2639] eta: 1:50:57 lr: 2.1769134676665464e-05 loss: 0.0404 (0.0415) time: 2.9220 data: 0.0075 max mem: 33370 +Epoch: [24] [ 330/2639] eta: 1:50:32 lr: 2.1764459007856518e-05 loss: 0.0460 (0.0415) time: 2.9226 data: 0.0078 max mem: 33370 +Epoch: [24] [ 340/2639] eta: 1:50:09 lr: 2.1759783227436462e-05 loss: 0.0387 (0.0415) time: 2.9462 data: 0.0080 max mem: 33370 +Epoch: [24] [ 350/2639] eta: 1:49:47 lr: 2.1755107335375964e-05 loss: 0.0385 (0.0417) time: 2.9663 data: 0.0076 max mem: 33370 +Epoch: [24] [ 360/2639] eta: 1:49:20 lr: 2.1750431331645707e-05 loss: 0.0437 (0.0419) time: 2.9423 data: 0.0073 max mem: 33370 +Epoch: [24] [ 370/2639] eta: 1:48:50 lr: 2.1745755216216342e-05 loss: 0.0354 (0.0417) time: 2.8819 data: 0.0074 max mem: 33370 +Epoch: [24] [ 380/2639] eta: 1:48:21 lr: 2.1741078989058513e-05 loss: 0.0385 (0.0419) time: 2.8634 data: 0.0073 max mem: 33370 +Epoch: [24] [ 390/2639] eta: 1:47:54 lr: 2.173640265014286e-05 loss: 0.0412 (0.0420) time: 2.8894 data: 0.0071 max mem: 33370 +Epoch: [24] [ 400/2639] eta: 1:47:30 lr: 2.1731726199439974e-05 loss: 0.0356 (0.0420) time: 2.9344 data: 0.0071 max mem: 33370 +Epoch: [24] [ 410/2639] eta: 1:47:02 lr: 2.172704963692047e-05 loss: 0.0379 (0.0419) time: 2.9366 data: 0.0073 max mem: 33370 +Epoch: [24] [ 420/2639] eta: 1:46:37 lr: 2.172237296255492e-05 loss: 0.0395 (0.0421) time: 2.9274 data: 0.0076 max mem: 33370 +Epoch: [24] [ 430/2639] eta: 1:46:06 lr: 2.1717696176313905e-05 loss: 0.0414 (0.0421) time: 2.8965 data: 0.0076 max mem: 33370 +Epoch: [24] [ 440/2639] eta: 1:45:37 lr: 2.1713019278167967e-05 loss: 0.0393 (0.0419) time: 2.8593 data: 0.0074 max mem: 33370 +Epoch: [24] [ 450/2639] eta: 1:45:09 lr: 2.1708342268087654e-05 loss: 0.0354 (0.0420) time: 2.8834 data: 0.0074 max mem: 33370 +Epoch: [24] [ 460/2639] eta: 1:44:43 lr: 2.1703665146043484e-05 loss: 0.0373 (0.0423) time: 2.9263 data: 0.0074 max mem: 33370 +Epoch: [24] [ 470/2639] eta: 1:44:18 lr: 2.1698987912005973e-05 loss: 0.0417 (0.0424) time: 2.9525 data: 0.0076 max mem: 33370 +Epoch: [24] [ 480/2639] eta: 1:43:48 lr: 2.1694310565945603e-05 loss: 0.0373 (0.0423) time: 2.9028 data: 0.0077 max mem: 33370 +Epoch: [24] [ 490/2639] eta: 1:43:18 lr: 2.1689633107832864e-05 loss: 0.0373 (0.0423) time: 2.8639 data: 0.0075 max mem: 33370 +Epoch: [24] [ 500/2639] eta: 1:42:51 lr: 2.1684955537638222e-05 loss: 0.0384 (0.0425) time: 2.9004 data: 0.0073 max mem: 33370 +Epoch: [24] [ 510/2639] eta: 1:42:25 lr: 2.1680277855332122e-05 loss: 0.0405 (0.0425) time: 2.9374 data: 0.0073 max mem: 33370 +Epoch: [24] [ 520/2639] eta: 1:41:55 lr: 2.1675600060885e-05 loss: 0.0401 (0.0426) time: 2.9040 data: 0.0075 max mem: 33370 +Epoch: [24] [ 530/2639] eta: 1:41:24 lr: 2.1670922154267278e-05 loss: 0.0384 (0.0427) time: 2.8547 data: 0.0075 max mem: 33370 +Epoch: [24] [ 540/2639] eta: 1:40:56 lr: 2.1666244135449357e-05 loss: 0.0421 (0.0428) time: 2.8763 data: 0.0075 max mem: 33370 +Epoch: [24] [ 550/2639] eta: 1:40:28 lr: 2.1661566004401634e-05 loss: 0.0353 (0.0427) time: 2.9063 data: 0.0075 max mem: 33370 +Epoch: [24] [ 560/2639] eta: 1:39:57 lr: 2.165688776109448e-05 loss: 0.0332 (0.0426) time: 2.8601 data: 0.0076 max mem: 33370 +Epoch: [24] [ 570/2639] eta: 1:39:27 lr: 2.1652209405498257e-05 loss: 0.0365 (0.0426) time: 2.8375 data: 0.0075 max mem: 33370 +Epoch: [24] [ 580/2639] eta: 1:38:58 lr: 2.1647530937583308e-05 loss: 0.0365 (0.0425) time: 2.8690 data: 0.0075 max mem: 33370 +Epoch: [24] [ 590/2639] eta: 1:38:28 lr: 2.164285235731997e-05 loss: 0.0351 (0.0426) time: 2.8644 data: 0.0077 max mem: 33370 +Epoch: [24] [ 600/2639] eta: 1:37:58 lr: 2.163817366467855e-05 loss: 0.0384 (0.0426) time: 2.8550 data: 0.0078 max mem: 33370 +Epoch: [24] [ 610/2639] eta: 1:37:32 lr: 2.163349485962936e-05 loss: 0.0402 (0.0426) time: 2.9049 data: 0.0078 max mem: 33370 +Epoch: [24] [ 620/2639] eta: 1:37:04 lr: 2.1628815942142668e-05 loss: 0.0396 (0.0425) time: 2.9274 data: 0.0075 max mem: 33370 +Epoch: [24] [ 630/2639] eta: 1:36:35 lr: 2.162413691218876e-05 loss: 0.0376 (0.0426) time: 2.8926 data: 0.0076 max mem: 33370 +Epoch: [24] [ 640/2639] eta: 1:36:04 lr: 2.1619457769737892e-05 loss: 0.0462 (0.0426) time: 2.8524 data: 0.0075 max mem: 33370 +Epoch: [24] [ 650/2639] eta: 1:35:36 lr: 2.1614778514760294e-05 loss: 0.0456 (0.0429) time: 2.8701 data: 0.0076 max mem: 33370 +Epoch: [24] [ 660/2639] eta: 1:35:06 lr: 2.1610099147226204e-05 loss: 0.0426 (0.0428) time: 2.8870 data: 0.0077 max mem: 33370 +Epoch: [24] [ 670/2639] eta: 1:34:39 lr: 2.1605419667105823e-05 loss: 0.0418 (0.0429) time: 2.8988 data: 0.0077 max mem: 33370 +Epoch: [24] [ 680/2639] eta: 1:34:10 lr: 2.160074007436935e-05 loss: 0.0401 (0.0429) time: 2.8992 data: 0.0077 max mem: 33370 +Epoch: [24] [ 690/2639] eta: 1:33:41 lr: 2.1596060368986965e-05 loss: 0.0409 (0.0429) time: 2.8725 data: 0.0073 max mem: 33370 +Epoch: [24] [ 700/2639] eta: 1:33:11 lr: 2.1591380550928836e-05 loss: 0.0409 (0.0430) time: 2.8697 data: 0.0072 max mem: 33370 +Epoch: [24] [ 710/2639] eta: 1:32:42 lr: 2.1586700620165108e-05 loss: 0.0410 (0.0431) time: 2.8555 data: 0.0074 max mem: 33370 +Epoch: [24] [ 720/2639] eta: 1:32:13 lr: 2.1582020576665925e-05 loss: 0.0415 (0.0431) time: 2.8721 data: 0.0076 max mem: 33370 +Epoch: [24] [ 730/2639] eta: 1:31:42 lr: 2.1577340420401392e-05 loss: 0.0419 (0.0431) time: 2.8494 data: 0.0076 max mem: 33370 +Epoch: [24] [ 740/2639] eta: 1:31:13 lr: 2.1572660151341635e-05 loss: 0.0416 (0.0431) time: 2.8350 data: 0.0076 max mem: 33370 +Epoch: [24] [ 750/2639] eta: 1:30:43 lr: 2.156797976945672e-05 loss: 0.0360 (0.0431) time: 2.8597 data: 0.0077 max mem: 33370 +Epoch: [24] [ 760/2639] eta: 1:30:12 lr: 2.1563299274716744e-05 loss: 0.0409 (0.0433) time: 2.8208 data: 0.0076 max mem: 33370 +Epoch: [24] [ 770/2639] eta: 1:29:45 lr: 2.1558618667091748e-05 loss: 0.0419 (0.0433) time: 2.8570 data: 0.0075 max mem: 33370 +Epoch: [24] [ 780/2639] eta: 1:29:16 lr: 2.1553937946551795e-05 loss: 0.0408 (0.0433) time: 2.9100 data: 0.0075 max mem: 33370 +Epoch: [24] [ 790/2639] eta: 1:28:48 lr: 2.1549257113066894e-05 loss: 0.0396 (0.0433) time: 2.8975 data: 0.0078 max mem: 33370 +Epoch: [24] [ 800/2639] eta: 1:28:19 lr: 2.154457616660708e-05 loss: 0.0369 (0.0433) time: 2.8985 data: 0.0078 max mem: 33370 +Epoch: [24] [ 810/2639] eta: 1:27:49 lr: 2.153989510714233e-05 loss: 0.0429 (0.0434) time: 2.8593 data: 0.0074 max mem: 33370 +Epoch: [24] [ 820/2639] eta: 1:27:21 lr: 2.1535213934642645e-05 loss: 0.0447 (0.0434) time: 2.8817 data: 0.0075 max mem: 33370 +Epoch: [24] [ 830/2639] eta: 1:26:54 lr: 2.1530532649077984e-05 loss: 0.0399 (0.0433) time: 2.9471 data: 0.0077 max mem: 33370 +Epoch: [24] [ 840/2639] eta: 1:26:27 lr: 2.1525851250418304e-05 loss: 0.0413 (0.0434) time: 2.9483 data: 0.0078 max mem: 33370 +Epoch: [24] [ 850/2639] eta: 1:25:59 lr: 2.152116973863354e-05 loss: 0.0376 (0.0434) time: 2.9482 data: 0.0077 max mem: 33370 +Epoch: [24] [ 860/2639] eta: 1:25:30 lr: 2.151648811369362e-05 loss: 0.0376 (0.0434) time: 2.9208 data: 0.0075 max mem: 33370 +Epoch: [24] [ 870/2639] eta: 1:25:02 lr: 2.151180637556845e-05 loss: 0.0355 (0.0433) time: 2.8971 data: 0.0075 max mem: 33370 +Epoch: [24] [ 880/2639] eta: 1:24:34 lr: 2.150712452422791e-05 loss: 0.0374 (0.0434) time: 2.9163 data: 0.0073 max mem: 33370 +Epoch: [24] [ 890/2639] eta: 1:24:05 lr: 2.15024425596419e-05 loss: 0.0396 (0.0434) time: 2.9026 data: 0.0075 max mem: 33370 +Epoch: [24] [ 900/2639] eta: 1:23:36 lr: 2.1497760481780258e-05 loss: 0.0372 (0.0433) time: 2.8843 data: 0.0079 max mem: 33370 +Epoch: [24] [ 910/2639] eta: 1:23:08 lr: 2.1493078290612846e-05 loss: 0.0393 (0.0435) time: 2.9069 data: 0.0078 max mem: 33370 +Epoch: [24] [ 920/2639] eta: 1:22:40 lr: 2.1488395986109485e-05 loss: 0.0463 (0.0435) time: 2.9152 data: 0.0077 max mem: 33370 +Epoch: [24] [ 930/2639] eta: 1:22:12 lr: 2.1483713568240002e-05 loss: 0.0389 (0.0434) time: 2.9239 data: 0.0075 max mem: 33370 +Epoch: [24] [ 940/2639] eta: 1:21:44 lr: 2.147903103697418e-05 loss: 0.0440 (0.0435) time: 2.9503 data: 0.0076 max mem: 33370 +Epoch: [24] [ 950/2639] eta: 1:21:16 lr: 2.1474348392281822e-05 loss: 0.0445 (0.0435) time: 2.9319 data: 0.0080 max mem: 33370 +Epoch: [24] [ 960/2639] eta: 1:20:47 lr: 2.1469665634132686e-05 loss: 0.0425 (0.0436) time: 2.8891 data: 0.0078 max mem: 33370 +Epoch: [24] [ 970/2639] eta: 1:20:17 lr: 2.1464982762496534e-05 loss: 0.0384 (0.0436) time: 2.8542 data: 0.0075 max mem: 33370 +Epoch: [24] [ 980/2639] eta: 1:19:49 lr: 2.146029977734309e-05 loss: 0.0438 (0.0437) time: 2.8761 data: 0.0080 max mem: 33370 +Epoch: [24] [ 990/2639] eta: 1:19:20 lr: 2.1455616678642095e-05 loss: 0.0441 (0.0438) time: 2.8978 data: 0.0082 max mem: 33370 +Epoch: [24] [1000/2639] eta: 1:18:50 lr: 2.1450933466363247e-05 loss: 0.0354 (0.0439) time: 2.8723 data: 0.0076 max mem: 33370 +Epoch: [24] 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mem: 33370 +Epoch: [24] [1090/2639] eta: 1:14:31 lr: 2.1408779439844446e-05 loss: 0.0408 (0.0440) time: 2.9079 data: 0.0076 max mem: 33370 +Epoch: [24] [1100/2639] eta: 1:14:02 lr: 2.140409509011761e-05 loss: 0.0398 (0.0439) time: 2.8510 data: 0.0076 max mem: 33370 +Epoch: [24] [1110/2639] eta: 1:13:33 lr: 2.1399410626478688e-05 loss: 0.0376 (0.0439) time: 2.8639 data: 0.0077 max mem: 33370 +Epoch: [24] [1120/2639] eta: 1:13:03 lr: 2.1394726048897208e-05 loss: 0.0333 (0.0439) time: 2.8683 data: 0.0076 max mem: 33370 +Epoch: [24] [1130/2639] eta: 1:12:33 lr: 2.1390041357342664e-05 loss: 0.0405 (0.0441) time: 2.8328 data: 0.0077 max mem: 33370 +Epoch: [24] [1140/2639] eta: 1:12:05 lr: 2.1385356551784557e-05 loss: 0.0463 (0.0442) time: 2.8462 data: 0.0076 max mem: 33370 +Epoch: [24] [1150/2639] eta: 1:11:36 lr: 2.1380671632192355e-05 loss: 0.0425 (0.0442) time: 2.8806 data: 0.0075 max mem: 33370 +Epoch: [24] [1160/2639] eta: 1:11:07 lr: 2.137598659853552e-05 loss: 0.0388 (0.0442) time: 2.9050 data: 0.0078 max mem: 33370 +Epoch: [24] [1170/2639] eta: 1:10:38 lr: 2.1371301450783493e-05 loss: 0.0382 (0.0442) time: 2.8902 data: 0.0082 max mem: 33370 +Epoch: [24] [1180/2639] eta: 1:10:10 lr: 2.136661618890571e-05 loss: 0.0402 (0.0442) time: 2.8944 data: 0.0085 max mem: 33370 +Epoch: [24] [1190/2639] eta: 1:09:42 lr: 2.1361930812871575e-05 loss: 0.0402 (0.0443) time: 2.9352 data: 0.0081 max mem: 33370 +Epoch: [24] [1200/2639] eta: 1:09:12 lr: 2.1357245322650492e-05 loss: 0.0414 (0.0442) time: 2.8991 data: 0.0075 max mem: 33370 +Epoch: [24] [1210/2639] eta: 1:08:44 lr: 2.1352559718211834e-05 loss: 0.0475 (0.0443) time: 2.8734 data: 0.0076 max mem: 33370 +Epoch: [24] [1220/2639] eta: 1:08:15 lr: 2.134787399952498e-05 loss: 0.0438 (0.0443) time: 2.8900 data: 0.0077 max mem: 33370 +Epoch: [24] [1230/2639] eta: 1:07:46 lr: 2.134318816655926e-05 loss: 0.0380 (0.0443) time: 2.8792 data: 0.0078 max mem: 33370 +Epoch: [24] [1240/2639] eta: 1:07:17 lr: 2.1338502219284028e-05 loss: 0.0374 (0.0443) time: 2.8757 data: 0.0079 max mem: 33370 +Epoch: [24] [1250/2639] eta: 1:06:48 lr: 2.133381615766859e-05 loss: 0.0376 (0.0443) time: 2.8652 data: 0.0076 max mem: 33370 +Epoch: [24] [1260/2639] eta: 1:06:18 lr: 2.132912998168226e-05 loss: 0.0376 (0.0442) time: 2.8519 data: 0.0073 max mem: 33370 +Epoch: [24] [1270/2639] eta: 1:05:50 lr: 2.1324443691294308e-05 loss: 0.0361 (0.0442) time: 2.8746 data: 0.0073 max mem: 33370 +Epoch: [24] [1280/2639] eta: 1:05:20 lr: 2.1319757286474025e-05 loss: 0.0416 (0.0443) time: 2.8711 data: 0.0076 max mem: 33370 +Epoch: [24] [1290/2639] eta: 1:04:52 lr: 2.131507076719065e-05 loss: 0.0416 (0.0443) time: 2.8871 data: 0.0077 max mem: 33370 +Epoch: [24] [1300/2639] eta: 1:04:24 lr: 2.131038413341343e-05 loss: 0.0374 (0.0443) time: 2.9347 data: 0.0074 max mem: 33370 +Epoch: [24] [1310/2639] eta: 1:03:55 lr: 2.1305697385111587e-05 loss: 0.0387 (0.0442) time: 2.9105 data: 0.0073 max mem: 33370 +Epoch: [24] [1320/2639] eta: 1:03:26 lr: 2.1301010522254337e-05 loss: 0.0340 (0.0442) time: 2.8957 data: 0.0072 max mem: 33370 +Epoch: [24] [1330/2639] eta: 1:02:58 lr: 2.1296323544810857e-05 loss: 0.0340 (0.0442) time: 2.9586 data: 0.0074 max mem: 33370 +Epoch: [24] [1340/2639] eta: 1:02:30 lr: 2.129163645275034e-05 loss: 0.0342 (0.0442) time: 2.9755 data: 0.0078 max mem: 33370 +Epoch: [24] [1350/2639] eta: 1:02:02 lr: 2.1286949246041934e-05 loss: 0.0340 (0.0441) time: 2.9311 data: 0.0076 max mem: 33370 +Epoch: [24] [1360/2639] eta: 1:01:33 lr: 2.128226192465479e-05 loss: 0.0402 (0.0441) time: 2.9093 data: 0.0073 max mem: 33370 +Epoch: [24] [1370/2639] eta: 1:01:04 lr: 2.127757448855804e-05 loss: 0.0442 (0.0441) time: 2.9009 data: 0.0073 max mem: 33370 +Epoch: [24] [1380/2639] eta: 1:00:34 lr: 2.127288693772079e-05 loss: 0.0436 (0.0441) time: 2.8476 data: 0.0075 max mem: 33370 +Epoch: [24] [1390/2639] eta: 1:00:05 lr: 2.1268199272112144e-05 loss: 0.0440 (0.0441) time: 2.8227 data: 0.0074 max mem: 33370 +Epoch: [24] [1400/2639] eta: 0:59:36 lr: 2.1263511491701173e-05 loss: 0.0411 (0.0441) time: 2.8497 data: 0.0072 max mem: 33370 +Epoch: [24] [1410/2639] eta: 0:59:08 lr: 2.1258823596456956e-05 loss: 0.0375 (0.0441) time: 2.8975 data: 0.0072 max mem: 33370 +Epoch: [24] [1420/2639] eta: 0:58:39 lr: 2.125413558634853e-05 loss: 0.0375 (0.0442) time: 2.9398 data: 0.0072 max mem: 33370 +Epoch: [24] [1430/2639] eta: 0:58:11 lr: 2.1249447461344943e-05 loss: 0.0364 (0.0442) time: 2.9419 data: 0.0072 max mem: 33370 +Epoch: [24] [1440/2639] eta: 0:57:42 lr: 2.1244759221415193e-05 loss: 0.0377 (0.0442) time: 2.9197 data: 0.0071 max mem: 33370 +Epoch: [24] [1450/2639] eta: 0:57:13 lr: 2.1240070866528303e-05 loss: 0.0432 (0.0442) time: 2.9166 data: 0.0074 max mem: 33370 +Epoch: [24] [1460/2639] eta: 0:56:45 lr: 2.123538239665324e-05 loss: 0.0418 (0.0442) time: 2.9147 data: 0.0074 max mem: 33370 +Epoch: [24] [1470/2639] eta: 0:56:16 lr: 2.1230693811758993e-05 loss: 0.0376 (0.0442) time: 2.9074 data: 0.0074 max mem: 33370 +Epoch: [24] [1480/2639] eta: 0:55:48 lr: 2.1226005111814492e-05 loss: 0.0363 (0.0441) time: 2.9619 data: 0.0075 max mem: 33370 +Epoch: [24] [1490/2639] eta: 0:55:19 lr: 2.12213162967887e-05 loss: 0.0342 (0.0441) time: 2.9554 data: 0.0076 max mem: 33370 +Epoch: [24] [1500/2639] eta: 0:54:50 lr: 2.1216627366650517e-05 loss: 0.0379 (0.0441) time: 2.8777 data: 0.0081 max mem: 33370 +Epoch: [24] [1510/2639] eta: 0:54:22 lr: 2.1211938321368864e-05 loss: 0.0375 (0.0440) time: 2.9172 data: 0.0085 max mem: 33370 +Epoch: [24] [1520/2639] eta: 0:53:53 lr: 2.120724916091262e-05 loss: 0.0360 (0.0440) time: 2.9591 data: 0.0082 max mem: 33370 +Epoch: [24] [1530/2639] eta: 0:53:24 lr: 2.120255988525067e-05 loss: 0.0339 (0.0440) time: 2.9084 data: 0.0076 max mem: 33370 +Epoch: [24] [1540/2639] eta: 0:52:56 lr: 2.119787049435186e-05 loss: 0.0349 (0.0439) time: 2.9131 data: 0.0075 max mem: 33370 +Epoch: [24] [1550/2639] eta: 0:52:27 lr: 2.1193180988185043e-05 loss: 0.0338 (0.0439) time: 2.9302 data: 0.0076 max mem: 33370 +Epoch: [24] [1560/2639] eta: 0:51:59 lr: 2.1188491366719033e-05 loss: 0.0352 (0.0439) time: 2.9254 data: 0.0080 max mem: 33370 +Epoch: [24] [1570/2639] eta: 0:51:30 lr: 2.1183801629922646e-05 loss: 0.0360 (0.0439) time: 2.9201 data: 0.0081 max mem: 33370 +Epoch: [24] [1580/2639] eta: 0:51:01 lr: 2.1179111777764672e-05 loss: 0.0427 (0.0440) time: 2.8818 data: 0.0078 max mem: 33370 +Epoch: [24] [1590/2639] eta: 0:50:32 lr: 2.1174421810213895e-05 loss: 0.0389 (0.0439) time: 2.8709 data: 0.0077 max mem: 33370 +Epoch: [24] [1600/2639] eta: 0:50:03 lr: 2.1169731727239063e-05 loss: 0.0343 (0.0439) time: 2.8827 data: 0.0079 max mem: 33370 +Epoch: [24] [1610/2639] eta: 0:49:34 lr: 2.116504152880893e-05 loss: 0.0352 (0.0438) time: 2.8959 data: 0.0080 max mem: 33370 +Epoch: [24] [1620/2639] eta: 0:49:05 lr: 2.1160351214892226e-05 loss: 0.0352 (0.0438) time: 2.9052 data: 0.0077 max mem: 33370 +Epoch: [24] [1630/2639] eta: 0:48:36 lr: 2.115566078545766e-05 loss: 0.0332 (0.0441) time: 2.9178 data: 0.0075 max mem: 33370 +Epoch: [24] [1640/2639] eta: 0:48:08 lr: 2.115097024047393e-05 loss: 0.0419 (0.0441) time: 2.9301 data: 0.0076 max mem: 33370 +Epoch: [24] [1650/2639] eta: 0:47:39 lr: 2.114627957990971e-05 loss: 0.0428 (0.0441) time: 2.9082 data: 0.0076 max mem: 33370 +Epoch: [24] [1660/2639] eta: 0:47:10 lr: 2.1141588803733678e-05 loss: 0.0420 (0.0441) time: 2.8996 data: 0.0075 max mem: 33370 +Epoch: [24] [1670/2639] eta: 0:46:41 lr: 2.1136897911914468e-05 loss: 0.0392 (0.0441) time: 2.8643 data: 0.0076 max mem: 33370 +Epoch: [24] [1680/2639] eta: 0:46:12 lr: 2.1132206904420714e-05 loss: 0.0335 (0.0440) time: 2.8789 data: 0.0077 max mem: 33370 +Epoch: [24] [1690/2639] eta: 0:45:43 lr: 2.1127515781221033e-05 loss: 0.0363 (0.0440) time: 2.8918 data: 0.0077 max mem: 33370 +Epoch: [24] [1700/2639] eta: 0:45:14 lr: 2.1122824542284028e-05 loss: 0.0393 (0.0441) time: 2.8686 data: 0.0077 max mem: 33370 +Epoch: [24] [1710/2639] eta: 0:44:45 lr: 2.1118133187578272e-05 loss: 0.0341 (0.0440) time: 2.8642 data: 0.0075 max mem: 33370 +Epoch: [24] [1720/2639] eta: 0:44:16 lr: 2.1113441717072342e-05 loss: 0.0341 (0.0440) time: 2.8318 data: 0.0075 max mem: 33370 +Epoch: [24] [1730/2639] eta: 0:43:46 lr: 2.110875013073478e-05 loss: 0.0432 (0.0440) time: 2.8376 data: 0.0076 max mem: 33370 +Epoch: [24] [1740/2639] eta: 0:43:17 lr: 2.1104058428534126e-05 loss: 0.0452 (0.0440) time: 2.8355 data: 0.0075 max mem: 33370 +Epoch: [24] [1750/2639] eta: 0:42:48 lr: 2.1099366610438888e-05 loss: 0.0372 (0.0439) time: 2.8626 data: 0.0077 max mem: 33370 +Epoch: [24] [1760/2639] eta: 0:42:20 lr: 2.109467467641758e-05 loss: 0.0372 (0.0439) time: 2.9238 data: 0.0078 max mem: 33370 +Epoch: [24] [1770/2639] eta: 0:41:51 lr: 2.1089982626438673e-05 loss: 0.0372 (0.0439) time: 2.9129 data: 0.0078 max mem: 33370 +Epoch: [24] [1780/2639] eta: 0:41:22 lr: 2.108529046047065e-05 loss: 0.0352 (0.0439) time: 2.8702 data: 0.0081 max mem: 33370 +Epoch: [24] [1790/2639] eta: 0:40:53 lr: 2.108059817848195e-05 loss: 0.0376 (0.0439) time: 2.8458 data: 0.0078 max mem: 33370 +Epoch: [24] [1800/2639] eta: 0:40:23 lr: 2.1075905780441016e-05 loss: 0.0438 (0.0439) time: 2.8347 data: 0.0072 max mem: 33370 +Epoch: [24] [1810/2639] eta: 0:39:54 lr: 2.107121326631626e-05 loss: 0.0456 (0.0440) time: 2.8376 data: 0.0072 max mem: 33370 +Epoch: [24] [1820/2639] eta: 0:39:25 lr: 2.10665206360761e-05 loss: 0.0375 (0.0439) time: 2.8639 data: 0.0074 max mem: 33370 +Epoch: [24] [1830/2639] eta: 0:38:56 lr: 2.1061827889688902e-05 loss: 0.0346 (0.0439) time: 2.8685 data: 0.0075 max mem: 33370 +Epoch: [24] [1840/2639] eta: 0:38:27 lr: 2.105713502712305e-05 loss: 0.0340 (0.0439) time: 2.8507 data: 0.0078 max mem: 33370 +Epoch: [24] [1850/2639] eta: 0:37:59 lr: 2.1052442048346892e-05 loss: 0.0366 (0.0439) time: 2.8810 data: 0.0081 max mem: 33370 +Epoch: [24] [1860/2639] eta: 0:37:30 lr: 2.1047748953328765e-05 loss: 0.0383 (0.0439) time: 2.8918 data: 0.0080 max mem: 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data: 0.0071 max mem: 33370 +Epoch: [24] [1950/2639] eta: 0:33:22 lr: 2.100550586204457e-05 loss: 0.0359 (0.0439) time: 4.6194 data: 1.7014 max mem: 33370 +Epoch: [24] [1960/2639] eta: 0:32:52 lr: 2.1000811602861677e-05 loss: 0.0379 (0.0439) time: 4.5593 data: 1.7018 max mem: 33370 +Epoch: [24] [1970/2639] eta: 0:32:23 lr: 2.099611722708744e-05 loss: 0.0362 (0.0439) time: 2.8601 data: 0.0080 max mem: 33370 +Epoch: [24] [1980/2639] eta: 0:31:54 lr: 2.0991422734689982e-05 loss: 0.0362 (0.0439) time: 2.8969 data: 0.0077 max mem: 33370 +Epoch: [24] [1990/2639] eta: 0:31:25 lr: 2.0986728125637446e-05 loss: 0.0386 (0.0439) time: 2.9246 data: 0.0073 max mem: 33370 +Epoch: [24] [2000/2639] eta: 0:30:56 lr: 2.0982033399897916e-05 loss: 0.0391 (0.0441) time: 2.9382 data: 0.0079 max mem: 33370 +Epoch: [24] [2010/2639] eta: 0:30:27 lr: 2.0977338557439495e-05 loss: 0.0381 (0.0442) time: 2.9206 data: 0.0080 max mem: 33370 +Epoch: [24] [2020/2639] eta: 0:29:58 lr: 2.0972643598230247e-05 loss: 0.0441 (0.0442) time: 2.9351 data: 0.0077 max mem: 33370 +Epoch: [24] [2030/2639] eta: 0:29:29 lr: 2.0967948522238232e-05 loss: 0.0441 (0.0443) time: 2.9194 data: 0.0076 max mem: 33370 +Epoch: [24] [2040/2639] eta: 0:29:01 lr: 2.0963253329431484e-05 loss: 0.0390 (0.0442) time: 2.9455 data: 0.0072 max mem: 33370 +Epoch: [24] [2050/2639] eta: 0:28:31 lr: 2.095855801977803e-05 loss: 0.0398 (0.0443) time: 2.9410 data: 0.0076 max mem: 33370 +Epoch: [24] [2060/2639] eta: 0:28:02 lr: 2.0953862593245873e-05 loss: 0.0398 (0.0443) time: 2.8937 data: 0.0080 max mem: 33370 +Epoch: [24] [2070/2639] eta: 0:27:33 lr: 2.0949167049803002e-05 loss: 0.0394 (0.0443) time: 2.8746 data: 0.0079 max mem: 33370 +Epoch: [24] [2080/2639] eta: 0:27:04 lr: 2.0944471389417387e-05 loss: 0.0402 (0.0443) time: 2.8601 data: 0.0080 max mem: 33370 +Epoch: [24] [2090/2639] eta: 0:26:35 lr: 2.0939775612056986e-05 loss: 0.0376 (0.0443) time: 2.9234 data: 0.0083 max mem: 33370 +Epoch: [24] [2100/2639] eta: 0:26:06 lr: 2.093507971768973e-05 loss: 0.0375 (0.0443) time: 2.9522 data: 0.0081 max mem: 33370 +Epoch: [24] [2110/2639] eta: 0:25:37 lr: 2.0930383706283545e-05 loss: 0.0422 (0.0443) time: 2.9260 data: 0.0075 max mem: 33370 +Epoch: [24] [2120/2639] eta: 0:25:08 lr: 2.092568757780634e-05 loss: 0.0398 (0.0442) time: 2.8911 data: 0.0078 max mem: 33370 +Epoch: [24] [2130/2639] eta: 0:24:39 lr: 2.0920991332225997e-05 loss: 0.0382 (0.0442) time: 2.8749 data: 0.0081 max mem: 33370 +Epoch: [24] [2140/2639] eta: 0:24:10 lr: 2.0916294969510393e-05 loss: 0.0373 (0.0442) time: 2.8938 data: 0.0076 max mem: 33370 +Epoch: [24] [2150/2639] eta: 0:23:41 lr: 2.0911598489627367e-05 loss: 0.0355 (0.0442) time: 2.9012 data: 0.0076 max mem: 33370 +Epoch: [24] [2160/2639] eta: 0:23:12 lr: 2.0906901892544777e-05 loss: 0.0412 (0.0442) time: 2.9003 data: 0.0076 max mem: 33370 +Epoch: [24] [2170/2639] eta: 0:22:42 lr: 2.0902205178230428e-05 loss: 0.0380 (0.0442) time: 2.8940 data: 0.0075 max mem: 33370 +Epoch: [24] [2180/2639] eta: 0:22:13 lr: 2.0897508346652133e-05 loss: 0.0378 (0.0442) time: 2.8717 data: 0.0075 max mem: 33370 +Epoch: [24] [2190/2639] eta: 0:21:44 lr: 2.089281139777767e-05 loss: 0.0419 (0.0442) time: 2.8394 data: 0.0077 max mem: 33370 +Epoch: [24] [2200/2639] eta: 0:21:15 lr: 2.0888114331574817e-05 loss: 0.0388 (0.0442) time: 2.8306 data: 0.0076 max mem: 33370 +Epoch: [24] [2210/2639] eta: 0:20:46 lr: 2.088341714801132e-05 loss: 0.0426 (0.0442) time: 2.8527 data: 0.0075 max mem: 33370 +Epoch: [24] [2220/2639] eta: 0:20:17 lr: 2.087871984705492e-05 loss: 0.0458 (0.0442) time: 2.8792 data: 0.0078 max mem: 33370 +Epoch: [24] [2230/2639] eta: 0:19:48 lr: 2.087402242867333e-05 loss: 0.0414 (0.0442) time: 2.9072 data: 0.0077 max mem: 33370 +Epoch: [24] [2240/2639] eta: 0:19:19 lr: 2.086932489283426e-05 loss: 0.0324 (0.0442) time: 2.9523 data: 0.0076 max mem: 33370 +Epoch: [24] [2250/2639] eta: 0:18:50 lr: 2.0864627239505387e-05 loss: 0.0321 (0.0442) time: 2.9472 data: 0.0076 max mem: 33370 +Epoch: [24] [2260/2639] eta: 0:18:21 lr: 2.085992946865439e-05 loss: 0.0335 (0.0442) time: 2.8983 data: 0.0075 max mem: 33370 +Epoch: [24] [2270/2639] eta: 0:17:52 lr: 2.0855231580248907e-05 loss: 0.0398 (0.0442) time: 2.8950 data: 0.0077 max mem: 33370 +Epoch: [24] [2280/2639] eta: 0:17:23 lr: 2.085053357425658e-05 loss: 0.0456 (0.0442) time: 2.9477 data: 0.0078 max mem: 33370 +Epoch: [24] [2290/2639] eta: 0:16:54 lr: 2.0845835450645023e-05 loss: 0.0450 (0.0442) time: 2.9579 data: 0.0077 max mem: 33370 +Epoch: [24] [2300/2639] eta: 0:16:25 lr: 2.0841137209381842e-05 loss: 0.0378 (0.0442) time: 2.9229 data: 0.0075 max mem: 33370 +Epoch: [24] [2310/2639] eta: 0:15:55 lr: 2.0836438850434608e-05 loss: 0.0395 (0.0442) time: 2.8986 data: 0.0081 max mem: 33370 +Epoch: [24] [2320/2639] eta: 0:15:26 lr: 2.08317403737709e-05 loss: 0.0426 (0.0442) time: 2.9203 data: 0.0082 max mem: 33370 +Epoch: [24] [2330/2639] eta: 0:14:57 lr: 2.082704177935826e-05 loss: 0.0418 (0.0441) time: 2.9488 data: 0.0079 max mem: 33370 +Epoch: [24] [2340/2639] eta: 0:14:28 lr: 2.082234306716422e-05 loss: 0.0414 (0.0442) time: 2.9313 data: 0.0081 max mem: 33370 +Epoch: [24] [2350/2639] eta: 0:13:59 lr: 2.0817644237156295e-05 loss: 0.0418 (0.0442) time: 2.9235 data: 0.0080 max mem: 33370 +Epoch: [24] [2360/2639] eta: 0:13:30 lr: 2.081294528930198e-05 loss: 0.0460 (0.0442) time: 2.8806 data: 0.0079 max mem: 33370 +Epoch: [24] [2370/2639] eta: 0:13:01 lr: 2.0808246223568767e-05 loss: 0.0430 (0.0442) time: 2.8489 data: 0.0077 max mem: 33370 +Epoch: [24] [2380/2639] eta: 0:12:32 lr: 2.0803547039924105e-05 loss: 0.0397 (0.0442) time: 2.9035 data: 0.0077 max mem: 33370 +Epoch: [24] [2390/2639] eta: 0:12:03 lr: 2.079884773833545e-05 loss: 0.0397 (0.0442) time: 2.9065 data: 0.0077 max mem: 33370 +Epoch: [24] [2400/2639] eta: 0:11:34 lr: 2.079414831877022e-05 loss: 0.0372 (0.0442) time: 2.8714 data: 0.0079 max mem: 33370 +Epoch: [24] [2410/2639] eta: 0:11:05 lr: 2.078944878119584e-05 loss: 0.0412 (0.0442) time: 2.8520 data: 0.0080 max mem: 33370 +Epoch: [24] [2420/2639] eta: 0:10:36 lr: 2.0784749125579697e-05 loss: 0.0389 (0.0442) time: 2.8518 data: 0.0075 max mem: 33370 +Epoch: [24] [2430/2639] eta: 0:10:07 lr: 2.078004935188917e-05 loss: 0.0360 (0.0442) time: 2.8784 data: 0.0074 max mem: 33370 +Epoch: [24] [2440/2639] eta: 0:09:38 lr: 2.077534946009162e-05 loss: 0.0428 (0.0442) time: 2.8962 data: 0.0075 max mem: 33370 +Epoch: [24] [2450/2639] eta: 0:09:09 lr: 2.077064945015439e-05 loss: 0.0399 (0.0442) time: 2.8852 data: 0.0074 max mem: 33370 +Epoch: [24] [2460/2639] eta: 0:08:39 lr: 2.07659493220448e-05 loss: 0.0367 (0.0441) time: 2.8902 data: 0.0072 max mem: 33370 +Epoch: [24] [2470/2639] eta: 0:08:10 lr: 2.076124907573017e-05 loss: 0.0342 (0.0441) time: 2.9234 data: 0.0073 max mem: 33370 +Epoch: [24] [2480/2639] eta: 0:07:41 lr: 2.075654871117778e-05 loss: 0.0386 (0.0441) time: 2.9121 data: 0.0074 max mem: 33370 +Epoch: [24] [2490/2639] eta: 0:07:12 lr: 2.0751848228354914e-05 loss: 0.0379 (0.0442) time: 2.9055 data: 0.0075 max mem: 33370 +Epoch: [24] [2500/2639] eta: 0:06:43 lr: 2.0747147627228818e-05 loss: 0.0414 (0.0442) time: 2.9031 data: 0.0075 max mem: 33370 +Epoch: [24] [2510/2639] eta: 0:06:14 lr: 2.074244690776674e-05 loss: 0.0404 (0.0442) time: 2.8900 data: 0.0075 max mem: 33370 +Epoch: [24] [2520/2639] eta: 0:05:45 lr: 2.0737746069935894e-05 loss: 0.0404 (0.0442) time: 2.8937 data: 0.0078 max mem: 33370 +Epoch: [24] [2530/2639] eta: 0:05:16 lr: 2.0733045113703496e-05 loss: 0.0425 (0.0442) time: 2.8684 data: 0.0079 max mem: 33370 +Epoch: [24] [2540/2639] eta: 0:04:47 lr: 2.072834403903672e-05 loss: 0.0383 (0.0442) time: 2.8510 data: 0.0075 max mem: 33370 +Epoch: [24] [2550/2639] eta: 0:04:18 lr: 2.072364284590275e-05 loss: 0.0364 (0.0442) time: 2.9059 data: 0.0075 max mem: 33370 +Epoch: [24] [2560/2639] eta: 0:03:49 lr: 2.0718941534268723e-05 loss: 0.0349 (0.0442) time: 2.9032 data: 0.0076 max mem: 33370 +Epoch: [24] [2570/2639] eta: 0:03:20 lr: 2.071424010410179e-05 loss: 0.0380 (0.0442) time: 2.8504 data: 0.0073 max mem: 33370 +Epoch: [24] [2580/2639] eta: 0:02:51 lr: 2.0709538555369057e-05 loss: 0.0393 (0.0442) time: 2.8632 data: 0.0074 max mem: 33370 +Epoch: [24] [2590/2639] eta: 0:02:22 lr: 2.0704836888037626e-05 loss: 0.0374 (0.0442) time: 2.8669 data: 0.0076 max mem: 33370 +Epoch: [24] [2600/2639] eta: 0:01:53 lr: 2.070013510207459e-05 loss: 0.0397 (0.0442) time: 2.8695 data: 0.0075 max mem: 33370 +Epoch: [24] [2610/2639] eta: 0:01:24 lr: 2.0695433197446997e-05 loss: 0.0386 (0.0442) time: 2.9151 data: 0.0077 max mem: 33370 +Epoch: [24] [2620/2639] eta: 0:00:55 lr: 2.0690731174121913e-05 loss: 0.0372 (0.0442) time: 2.9037 data: 0.0078 max mem: 33370 +Epoch: [24] [2630/2639] eta: 0:00:26 lr: 2.0686029032066358e-05 loss: 0.0364 (0.0442) time: 2.8844 data: 0.0076 max mem: 33370 +Epoch: [24] Total time: 2:07:45 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 2:39:28 time: 3.7189 data: 3.5872 max mem: 33370 +Test: [ 100/2573] eta: 0:04:42 time: 0.0782 data: 0.0014 max mem: 33370 +Test: [ 200/2573] eta: 0:03:51 time: 0.0798 data: 0.0015 max mem: 33370 +Test: [ 300/2573] eta: 0:03:28 time: 0.0828 data: 0.0015 max mem: 33370 +Test: [ 400/2573] eta: 0:03:12 time: 0.0812 data: 0.0015 max mem: 33370 +Test: [ 500/2573] eta: 0:02:59 time: 0.0796 data: 0.0014 max mem: 33370 +Test: [ 600/2573] eta: 0:02:48 time: 0.0795 data: 0.0014 max mem: 33370 +Test: [ 700/2573] eta: 0:02:39 time: 0.0795 data: 0.0013 max mem: 33370 +Test: [ 800/2573] eta: 0:02:29 time: 0.0825 data: 0.0013 max mem: 33370 +Test: [ 900/2573] eta: 0:02:20 time: 0.0809 data: 0.0016 max mem: 33370 +Test: [1000/2573] eta: 0:02:11 time: 0.0798 data: 0.0015 max mem: 33370 +Test: [1100/2573] eta: 0:02:02 time: 0.0796 data: 0.0014 max mem: 33370 +Test: [1200/2573] eta: 0:01:54 time: 0.0805 data: 0.0014 max mem: 33370 +Test: [1300/2573] eta: 0:01:45 time: 0.0800 data: 0.0015 max mem: 33370 +Test: [1400/2573] eta: 0:01:36 time: 0.0790 data: 0.0015 max mem: 33370 +Test: [1500/2573] eta: 0:01:28 time: 0.0799 data: 0.0014 max mem: 33370 +Test: [1600/2573] eta: 0:01:20 time: 0.0835 data: 0.0014 max mem: 33370 +Test: [1700/2573] eta: 0:01:11 time: 0.0790 data: 0.0014 max mem: 33370 +Test: [1800/2573] eta: 0:01:03 time: 0.0832 data: 0.0024 max mem: 33370 +Test: [1900/2573] eta: 0:00:55 time: 0.0792 data: 0.0015 max mem: 33370 +Test: [2000/2573] eta: 0:00:46 time: 0.0816 data: 0.0015 max mem: 33370 +Test: [2100/2573] eta: 0:00:38 time: 0.0831 data: 0.0015 max mem: 33370 +Test: [2200/2573] eta: 0:00:30 time: 0.0828 data: 0.0015 max mem: 33370 +Test: [2300/2573] eta: 0:00:22 time: 0.0820 data: 0.0014 max mem: 33370 +Test: [2400/2573] eta: 0:00:14 time: 0.0780 data: 0.0015 max mem: 33370 +Test: [2500/2573] eta: 0:00:05 time: 0.0805 data: 0.0015 max mem: 33370 +Test: Total time: 0:03:31 +Final results: +Mean IoU is 63.30 + + precision@0.5 = 70.94 + precision@0.6 = 66.22 + precision@0.7 = 59.50 + precision@0.8 = 48.20 + precision@0.9 = 23.88 + overall IoU = 61.27 + +Average object IoU 63.29876045036276 +Overall IoU 61.267982482910156 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [25] [ 0/2639] eta: 4:20:38 lr: 2.0681797002674545e-05 loss: 0.0348 (0.0348) time: 5.9259 data: 2.8813 max mem: 33370 +Epoch: [25] [ 10/2639] eta: 2:19:52 lr: 2.067709463494021e-05 loss: 0.0342 (0.0351) time: 3.1922 data: 0.2688 max mem: 33370 +Epoch: [25] [ 20/2639] eta: 2:13:40 lr: 2.0672392148379688e-05 loss: 0.0354 (0.0376) time: 2.9192 data: 0.0072 max mem: 33370 +Epoch: [25] [ 30/2639] eta: 2:10:36 lr: 2.0667689542959956e-05 loss: 0.0398 (0.0379) time: 2.9001 data: 0.0073 max mem: 33370 +Epoch: [25] [ 40/2639] eta: 2:08:55 lr: 2.066298681864795e-05 loss: 0.0377 (0.0370) time: 2.8857 data: 0.0075 max mem: 33370 +Epoch: [25] [ 50/2639] eta: 2:08:08 lr: 2.0658283975410604e-05 loss: 0.0367 (0.0383) time: 2.9166 data: 0.0073 max mem: 33370 +Epoch: [25] [ 60/2639] eta: 2:07:21 lr: 2.0653581013214815e-05 loss: 0.0349 (0.0377) time: 2.9364 data: 0.0074 max mem: 33370 +Epoch: [25] [ 70/2639] eta: 2:06:13 lr: 2.0648877932027488e-05 loss: 0.0349 (0.0393) time: 2.8930 data: 0.0076 max mem: 33370 +Epoch: [25] [ 80/2639] eta: 2:05:49 lr: 2.0644174731815487e-05 loss: 0.0342 (0.0392) time: 2.9106 data: 0.0077 max mem: 33370 +Epoch: [25] [ 90/2639] eta: 2:05:14 lr: 2.0639471412545684e-05 loss: 0.0340 (0.0399) time: 2.9474 data: 0.0074 max mem: 33370 +Epoch: [25] [ 100/2639] eta: 2:04:35 lr: 2.0634767974184902e-05 loss: 0.0363 (0.0402) time: 2.9193 data: 0.0075 max mem: 33370 +Epoch: [25] [ 110/2639] eta: 2:03:45 lr: 2.063006441669997e-05 loss: 0.0363 (0.0398) time: 2.8818 data: 0.0076 max mem: 33370 +Epoch: [25] [ 120/2639] eta: 2:03:04 lr: 2.0625360740057688e-05 loss: 0.0363 (0.0398) time: 2.8672 data: 0.0074 max mem: 33370 +Epoch: [25] [ 130/2639] eta: 2:02:22 lr: 2.0620656944224852e-05 loss: 0.0368 (0.0395) time: 2.8738 data: 0.0077 max mem: 33370 +Epoch: [25] [ 140/2639] eta: 2:01:41 lr: 2.061595302916822e-05 loss: 0.0362 (0.0396) time: 2.8624 data: 0.0079 max mem: 33370 +Epoch: [25] [ 150/2639] eta: 2:01:02 lr: 2.0611248994854547e-05 loss: 0.0362 (0.0394) time: 2.8603 data: 0.0077 max mem: 33370 +Epoch: [25] [ 160/2639] eta: 2:00:32 lr: 2.0606544841250562e-05 loss: 0.0358 (0.0394) time: 2.8902 data: 0.0075 max mem: 33370 +Epoch: [25] [ 170/2639] eta: 1:59:54 lr: 2.0601840568322993e-05 loss: 0.0388 (0.0396) time: 2.8841 data: 0.0077 max mem: 33370 +Epoch: [25] [ 180/2639] eta: 1:59:11 lr: 2.0597136176038524e-05 loss: 0.0388 (0.0395) time: 2.8338 data: 0.0080 max mem: 33370 +Epoch: [25] [ 190/2639] eta: 1:58:35 lr: 2.059243166436384e-05 loss: 0.0384 (0.0393) time: 2.8358 data: 0.0078 max mem: 33370 +Epoch: [25] [ 200/2639] eta: 1:58:04 lr: 2.0587727033265603e-05 loss: 0.0377 (0.0394) time: 2.8691 data: 0.0076 max mem: 33370 +Epoch: [25] [ 210/2639] eta: 1:57:34 lr: 2.058302228271046e-05 loss: 0.0348 (0.0392) time: 2.8897 data: 0.0077 max mem: 33370 +Epoch: [25] [ 220/2639] eta: 1:57:10 lr: 2.057831741266503e-05 loss: 0.0348 (0.0396) time: 2.9273 data: 0.0082 max mem: 33370 +Epoch: [25] [ 230/2639] eta: 1:56:45 lr: 2.0573612423095927e-05 loss: 0.0430 (0.0399) time: 2.9509 data: 0.0079 max mem: 33370 +Epoch: [25] [ 240/2639] eta: 1:56:19 lr: 2.0568907313969748e-05 loss: 0.0417 (0.0399) time: 2.9391 data: 0.0074 max mem: 33370 +Epoch: [25] [ 250/2639] eta: 1:55:48 lr: 2.0564202085253057e-05 loss: 0.0404 (0.0403) time: 2.9115 data: 0.0077 max mem: 33370 +Epoch: [25] [ 260/2639] eta: 1:55:14 lr: 2.0559496736912414e-05 loss: 0.0451 (0.0406) time: 2.8721 data: 0.0078 max mem: 33370 +Epoch: [25] [ 270/2639] eta: 1:54:45 lr: 2.0554791268914354e-05 loss: 0.0405 (0.0410) time: 2.8853 data: 0.0076 max mem: 33370 +Epoch: [25] [ 280/2639] eta: 1:54:14 lr: 2.05500856812254e-05 loss: 0.0359 (0.0409) time: 2.8947 data: 0.0074 max mem: 33370 +Epoch: [25] [ 290/2639] eta: 1:53:45 lr: 2.0545379973812045e-05 loss: 0.0408 (0.0411) time: 2.8934 data: 0.0076 max mem: 33370 +Epoch: [25] [ 300/2639] eta: 1:53:13 lr: 2.054067414664079e-05 loss: 0.0419 (0.0413) time: 2.8861 data: 0.0079 max mem: 33370 +Epoch: [25] [ 310/2639] eta: 1:52:39 lr: 2.053596819967808e-05 loss: 0.0415 (0.0413) time: 2.8546 data: 0.0077 max mem: 33370 +Epoch: [25] [ 320/2639] eta: 1:52:09 lr: 2.053126213289038e-05 loss: 0.0337 (0.0412) time: 2.8634 data: 0.0075 max mem: 33370 +Epoch: [25] [ 330/2639] eta: 1:51:42 lr: 2.052655594624411e-05 loss: 0.0358 (0.0411) time: 2.9081 data: 0.0077 max mem: 33370 +Epoch: [25] [ 340/2639] eta: 1:51:14 lr: 2.0521849639705683e-05 loss: 0.0430 (0.0415) time: 2.9271 data: 0.0076 max mem: 33370 +Epoch: [25] [ 350/2639] eta: 1:50:45 lr: 2.0517143213241498e-05 loss: 0.0418 (0.0419) time: 2.9075 data: 0.0075 max mem: 33370 +Epoch: [25] [ 360/2639] eta: 1:50:17 lr: 2.051243666681793e-05 loss: 0.0358 (0.0418) time: 2.9132 data: 0.0077 max mem: 33370 +Epoch: [25] [ 370/2639] eta: 1:49:48 lr: 2.0507730000401333e-05 loss: 0.0405 (0.0419) time: 2.9151 data: 0.0075 max mem: 33370 +Epoch: [25] [ 380/2639] eta: 1:49:18 lr: 2.050302321395805e-05 loss: 0.0445 (0.0421) time: 2.8979 data: 0.0074 max mem: 33370 +Epoch: [25] [ 390/2639] eta: 1:48:47 lr: 2.04983163074544e-05 loss: 0.0410 (0.0421) time: 2.8807 data: 0.0074 max mem: 33370 +Epoch: [25] [ 400/2639] eta: 1:48:16 lr: 2.0493609280856695e-05 loss: 0.0356 (0.0419) time: 2.8682 data: 0.0074 max mem: 33370 +Epoch: [25] [ 410/2639] eta: 1:47:47 lr: 2.048890213413121e-05 loss: 0.0389 (0.0420) time: 2.8844 data: 0.0075 max mem: 33370 +Epoch: [25] [ 420/2639] eta: 1:47:16 lr: 2.0484194867244224e-05 loss: 0.0389 (0.0418) time: 2.8790 data: 0.0076 max mem: 33370 +Epoch: [25] [ 430/2639] eta: 1:46:46 lr: 2.0479487480161975e-05 loss: 0.0327 (0.0417) time: 2.8679 data: 0.0076 max mem: 33370 +Epoch: [25] [ 440/2639] eta: 1:46:16 lr: 2.0474779972850708e-05 loss: 0.0347 (0.0417) time: 2.8793 data: 0.0078 max mem: 33370 +Epoch: [25] [ 450/2639] eta: 1:45:46 lr: 2.0470072345276622e-05 loss: 0.0359 (0.0416) time: 2.8856 data: 0.0080 max mem: 33370 +Epoch: [25] [ 460/2639] eta: 1:45:16 lr: 2.0465364597405924e-05 loss: 0.0359 (0.0417) time: 2.8778 data: 0.0078 max mem: 33370 +Epoch: [25] [ 470/2639] eta: 1:44:49 lr: 2.0460656729204784e-05 loss: 0.0403 (0.0418) time: 2.9001 data: 0.0075 max mem: 33370 +Epoch: [25] [ 480/2639] eta: 1:44:16 lr: 2.0455948740639368e-05 loss: 0.0403 (0.0421) time: 2.8811 data: 0.0074 max mem: 33370 +Epoch: [25] [ 490/2639] eta: 1:43:46 lr: 2.0451240631675814e-05 loss: 0.0388 (0.0422) time: 2.8454 data: 0.0077 max mem: 33370 +Epoch: [25] [ 500/2639] eta: 1:43:15 lr: 2.044653240228024e-05 loss: 0.0370 (0.0420) time: 2.8563 data: 0.0079 max mem: 33370 +Epoch: [25] [ 510/2639] eta: 1:42:41 lr: 2.044182405241876e-05 loss: 0.0371 (0.0422) time: 2.8146 data: 0.0075 max mem: 33370 +Epoch: [25] [ 520/2639] eta: 1:42:09 lr: 2.043711558205745e-05 loss: 0.0405 (0.0422) time: 2.7979 data: 0.0072 max mem: 33370 +Epoch: [25] [ 530/2639] eta: 1:41:41 lr: 2.0432406991162384e-05 loss: 0.0382 (0.0421) time: 2.8676 data: 0.0073 max mem: 33370 +Epoch: [25] [ 540/2639] eta: 1:41:08 lr: 2.042769827969961e-05 loss: 0.0392 (0.0421) time: 2.8589 data: 0.0074 max mem: 33370 +Epoch: [25] [ 550/2639] eta: 1:40:42 lr: 2.0422989447635165e-05 loss: 0.0365 (0.0420) time: 2.8739 data: 0.0076 max mem: 33370 +Epoch: [25] [ 560/2639] eta: 1:40:10 lr: 2.0418280494935052e-05 loss: 0.0329 (0.0418) time: 2.8819 data: 0.0075 max mem: 33370 +Epoch: [25] [ 570/2639] eta: 1:39:44 lr: 2.0413571421565277e-05 loss: 0.0344 (0.0418) time: 2.8920 data: 0.0074 max mem: 33370 +Epoch: [25] [ 580/2639] eta: 1:39:12 lr: 2.0408862227491806e-05 loss: 0.0343 (0.0418) time: 2.8959 data: 0.0077 max mem: 33370 +Epoch: [25] [ 590/2639] eta: 1:38:43 lr: 2.0404152912680612e-05 loss: 0.0343 (0.0424) time: 2.8483 data: 0.0079 max mem: 33370 +Epoch: [25] [ 600/2639] eta: 1:38:11 lr: 2.0399443477097617e-05 loss: 0.0354 (0.0424) time: 2.8345 data: 0.0077 max mem: 33370 +Epoch: [25] [ 610/2639] eta: 1:37:40 lr: 2.0394733920708757e-05 loss: 0.0339 (0.0422) time: 2.8222 data: 0.0076 max mem: 33370 +Epoch: [25] [ 620/2639] eta: 1:37:12 lr: 2.0390024243479928e-05 loss: 0.0339 (0.0421) time: 2.8704 data: 0.0075 max mem: 33370 +Epoch: [25] [ 630/2639] eta: 1:36:40 lr: 2.038531444537702e-05 loss: 0.0312 (0.0421) time: 2.8506 data: 0.0075 max mem: 33370 +Epoch: [25] [ 640/2639] eta: 1:36:11 lr: 2.0380604526365894e-05 loss: 0.0316 (0.0419) time: 2.8341 data: 0.0076 max mem: 33370 +Epoch: [25] [ 650/2639] eta: 1:35:42 lr: 2.0375894486412403e-05 loss: 0.0334 (0.0418) time: 2.8861 data: 0.0079 max mem: 33370 +Epoch: [25] [ 660/2639] eta: 1:35:13 lr: 2.037118432548237e-05 loss: 0.0369 (0.0418) time: 2.8880 data: 0.0081 max mem: 33370 +Epoch: [25] [ 670/2639] eta: 1:34:42 lr: 2.0366474043541618e-05 loss: 0.0320 (0.0416) time: 2.8493 data: 0.0078 max mem: 33370 +Epoch: [25] [ 680/2639] eta: 1:34:12 lr: 2.0361763640555928e-05 loss: 0.0320 (0.0416) time: 2.8388 data: 0.0076 max mem: 33370 +Epoch: [25] [ 690/2639] eta: 1:33:43 lr: 2.0357053116491086e-05 loss: 0.0338 (0.0415) time: 2.8634 data: 0.0076 max mem: 33370 +Epoch: [25] [ 700/2639] eta: 1:33:13 lr: 2.0352342471312835e-05 loss: 0.0379 (0.0415) time: 2.8558 data: 0.0077 max mem: 33370 +Epoch: [25] [ 710/2639] eta: 1:32:44 lr: 2.0347631704986924e-05 loss: 0.0385 (0.0414) time: 2.8592 data: 0.0075 max mem: 33370 +Epoch: [25] [ 720/2639] eta: 1:32:17 lr: 2.0342920817479062e-05 loss: 0.0326 (0.0413) time: 2.9175 data: 0.0074 max mem: 33370 +Epoch: [25] [ 730/2639] eta: 1:31:47 lr: 2.0338209808754955e-05 loss: 0.0381 (0.0413) time: 2.8848 data: 0.0075 max mem: 33370 +Epoch: [25] [ 740/2639] eta: 1:31:17 lr: 2.033349867878029e-05 loss: 0.0390 (0.0413) time: 2.8362 data: 0.0074 max mem: 33370 +Epoch: [25] [ 750/2639] eta: 1:30:47 lr: 2.0328787427520716e-05 loss: 0.0361 (0.0413) time: 2.8473 data: 0.0072 max mem: 33370 +Epoch: [25] [ 760/2639] eta: 1:30:17 lr: 2.0324076054941893e-05 loss: 0.0352 (0.0413) time: 2.8468 data: 0.0073 max mem: 33370 +Epoch: [25] [ 770/2639] eta: 1:29:48 lr: 2.0319364561009435e-05 loss: 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2.028166823668814e-05 loss: 0.0375 (0.0416) time: 2.9215 data: 0.0075 max mem: 33370 +Epoch: [25] [ 860/2639] eta: 1:25:34 lr: 2.027695564902313e-05 loss: 0.0414 (0.0416) time: 2.9134 data: 0.0075 max mem: 33370 +Epoch: [25] [ 870/2639] eta: 1:25:05 lr: 2.0272242939659717e-05 loss: 0.0380 (0.0416) time: 2.9001 data: 0.0074 max mem: 33370 +Epoch: [25] [ 880/2639] eta: 1:24:36 lr: 2.026753010856334e-05 loss: 0.0380 (0.0415) time: 2.8874 data: 0.0074 max mem: 33370 +Epoch: [25] [ 890/2639] eta: 1:24:07 lr: 2.0262817155699386e-05 loss: 0.0392 (0.0415) time: 2.8708 data: 0.0075 max mem: 33370 +Epoch: [25] [ 900/2639] eta: 1:23:36 lr: 2.0258104081033253e-05 loss: 0.0400 (0.0417) time: 2.8224 data: 0.0076 max mem: 33370 +Epoch: [25] [ 910/2639] eta: 1:23:08 lr: 2.025339088453029e-05 loss: 0.0306 (0.0417) time: 2.8506 data: 0.0076 max mem: 33370 +Epoch: [25] [ 920/2639] eta: 1:22:38 lr: 2.0248677566155858e-05 loss: 0.0325 (0.0417) time: 2.8762 data: 0.0076 max mem: 33370 +Epoch: [25] [ 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33370 +Epoch: [25] [1010/2639] eta: 1:18:18 lr: 2.0206252210842176e-05 loss: 0.0407 (0.0417) time: 2.9060 data: 0.0075 max mem: 33370 +Epoch: [25] [1020/2639] eta: 1:17:50 lr: 2.0201537671842828e-05 loss: 0.0345 (0.0417) time: 2.9274 data: 0.0076 max mem: 33370 +Epoch: [25] [1030/2639] eta: 1:17:21 lr: 2.019682301058957e-05 loss: 0.0403 (0.0418) time: 2.9006 data: 0.0075 max mem: 33370 +Epoch: [25] [1040/2639] eta: 1:16:52 lr: 2.0192108227047505e-05 loss: 0.0427 (0.0417) time: 2.8699 data: 0.0075 max mem: 33370 +Epoch: [25] [1050/2639] eta: 1:16:23 lr: 2.018739332118174e-05 loss: 0.0382 (0.0418) time: 2.8963 data: 0.0075 max mem: 33370 +Epoch: [25] [1060/2639] eta: 1:15:55 lr: 2.0182678292957352e-05 loss: 0.0399 (0.0418) time: 2.9226 data: 0.0077 max mem: 33370 +Epoch: [25] [1070/2639] eta: 1:15:25 lr: 2.017796314233941e-05 loss: 0.0379 (0.0417) time: 2.8799 data: 0.0077 max mem: 33370 +Epoch: [25] [1080/2639] eta: 1:14:57 lr: 2.0173247869292943e-05 loss: 0.0361 (0.0417) time: 2.8806 data: 0.0077 max mem: 33370 +Epoch: [25] [1090/2639] eta: 1:14:30 lr: 2.0168532473782993e-05 loss: 0.0367 (0.0417) time: 2.9490 data: 0.0077 max mem: 33370 +Epoch: [25] [1100/2639] eta: 1:14:01 lr: 2.0163816955774544e-05 loss: 0.0367 (0.0417) time: 2.9229 data: 0.0076 max mem: 33370 +Epoch: [25] [1110/2639] eta: 1:13:32 lr: 2.0159101315232602e-05 loss: 0.0374 (0.0417) time: 2.8819 data: 0.0077 max mem: 33370 +Epoch: [25] [1120/2639] eta: 1:13:03 lr: 2.0154385552122117e-05 loss: 0.0389 (0.0417) time: 2.9010 data: 0.0075 max mem: 33370 +Epoch: [25] [1130/2639] eta: 1:12:34 lr: 2.0149669666408043e-05 loss: 0.0389 (0.0417) time: 2.8710 data: 0.0074 max mem: 33370 +Epoch: [25] [1140/2639] eta: 1:12:04 lr: 2.014495365805531e-05 loss: 0.0430 (0.0418) time: 2.8452 data: 0.0075 max mem: 33370 +Epoch: [25] [1150/2639] eta: 1:11:35 lr: 2.0140237527028825e-05 loss: 0.0491 (0.0418) time: 2.8462 data: 0.0073 max mem: 33370 +Epoch: [25] [1160/2639] eta: 1:11:06 lr: 2.013552127329347e-05 loss: 0.0412 (0.0418) time: 2.8410 data: 0.0072 max mem: 33370 +Epoch: [25] [1170/2639] eta: 1:10:38 lr: 2.0130804896814132e-05 loss: 0.0366 (0.0418) time: 2.9001 data: 0.0072 max mem: 33370 +Epoch: [25] [1180/2639] eta: 1:10:08 lr: 2.0126088397555646e-05 loss: 0.0356 (0.0417) time: 2.9048 data: 0.0074 max mem: 33370 +Epoch: [25] [1190/2639] eta: 1:09:40 lr: 2.0121371775482855e-05 loss: 0.0355 (0.0418) time: 2.8750 data: 0.0074 max mem: 33370 +Epoch: [25] [1200/2639] eta: 1:09:10 lr: 2.0116655030560563e-05 loss: 0.0369 (0.0418) time: 2.8734 data: 0.0074 max mem: 33370 +Epoch: [25] [1210/2639] eta: 1:08:42 lr: 2.0111938162753573e-05 loss: 0.0383 (0.0418) time: 2.9062 data: 0.0073 max mem: 33370 +Epoch: [25] [1220/2639] eta: 1:08:13 lr: 2.0107221172026656e-05 loss: 0.0465 (0.0418) time: 2.9084 data: 0.0074 max mem: 33370 +Epoch: [25] [1230/2639] eta: 1:07:44 lr: 2.0102504058344558e-05 loss: 0.0428 (0.0418) time: 2.8697 data: 0.0075 max mem: 33370 +Epoch: [25] [1240/2639] eta: 1:07:16 lr: 2.0097786821672033e-05 loss: 0.0399 (0.0418) time: 2.8810 data: 0.0073 max mem: 33370 +Epoch: [25] [1250/2639] eta: 1:06:46 lr: 2.009306946197378e-05 loss: 0.0427 (0.0418) time: 2.8604 data: 0.0072 max mem: 33370 +Epoch: [25] [1260/2639] eta: 1:06:18 lr: 2.008835197921451e-05 loss: 0.0458 (0.0419) time: 2.8878 data: 0.0074 max mem: 33370 +Epoch: [25] [1270/2639] eta: 1:05:49 lr: 2.0083634373358887e-05 loss: 0.0456 (0.0421) time: 2.9135 data: 0.0081 max mem: 33370 +Epoch: [25] [1280/2639] eta: 1:05:21 lr: 2.0078916644371582e-05 loss: 0.0409 (0.0421) time: 2.9345 data: 0.0081 max mem: 33370 +Epoch: [25] [1290/2639] eta: 1:04:52 lr: 2.0074198792217223e-05 loss: 0.0409 (0.0421) time: 2.9317 data: 0.0078 max mem: 33370 +Epoch: [25] [1300/2639] eta: 1:04:24 lr: 2.0069480816860438e-05 loss: 0.0429 (0.0422) time: 2.8916 data: 0.0076 max mem: 33370 +Epoch: [25] [1310/2639] eta: 1:03:55 lr: 2.0064762718265824e-05 loss: 0.0420 (0.0422) time: 2.8985 data: 0.0075 max mem: 33370 +Epoch: [25] [1320/2639] eta: 1:03:26 lr: 2.0060044496397965e-05 loss: 0.0366 (0.0422) time: 2.8832 data: 0.0075 max mem: 33370 +Epoch: [25] [1330/2639] eta: 1:02:57 lr: 2.005532615122141e-05 loss: 0.0366 (0.0421) time: 2.8896 data: 0.0077 max mem: 33370 +Epoch: [25] [1340/2639] eta: 1:02:29 lr: 2.0050607682700722e-05 loss: 0.0366 (0.0422) time: 2.9115 data: 0.0079 max mem: 33370 +Epoch: [25] [1350/2639] eta: 1:02:00 lr: 2.0045889090800408e-05 loss: 0.0427 (0.0422) time: 2.9140 data: 0.0077 max mem: 33370 +Epoch: [25] [1360/2639] eta: 1:01:31 lr: 2.0041170375484974e-05 loss: 0.0435 (0.0422) time: 2.8881 data: 0.0073 max mem: 33370 +Epoch: [25] [1370/2639] eta: 1:01:02 lr: 2.0036451536718903e-05 loss: 0.0369 (0.0422) time: 2.8805 data: 0.0074 max mem: 33370 +Epoch: [25] [1380/2639] eta: 1:00:33 lr: 2.0031732574466667e-05 loss: 0.0345 (0.0422) time: 2.8782 data: 0.0075 max mem: 33370 +Epoch: [25] [1390/2639] eta: 1:00:04 lr: 2.0027013488692693e-05 loss: 0.0343 (0.0422) time: 2.8553 data: 0.0075 max mem: 33370 +Epoch: [25] [1400/2639] eta: 0:59:35 lr: 2.0022294279361427e-05 loss: 0.0344 (0.0421) time: 2.8894 data: 0.0080 max mem: 33370 +Epoch: [25] [1410/2639] eta: 0:59:06 lr: 2.0017574946437256e-05 loss: 0.0344 (0.0421) time: 2.8999 data: 0.0080 max mem: 33370 +Epoch: [25] [1420/2639] eta: 0:58:37 lr: 2.001285548988458e-05 loss: 0.0340 (0.0421) time: 2.8585 data: 0.0074 max mem: 33370 +Epoch: [25] [1430/2639] eta: 0:58:09 lr: 2.0008135909667752e-05 loss: 0.0327 (0.0421) time: 2.8769 data: 0.0075 max mem: 33370 +Epoch: [25] [1440/2639] eta: 0:57:40 lr: 2.000341620575113e-05 loss: 0.0343 (0.0421) time: 2.8908 data: 0.0076 max mem: 33370 +Epoch: [25] [1450/2639] eta: 0:57:11 lr: 1.9998696378099032e-05 loss: 0.0418 (0.0421) time: 2.8787 data: 0.0076 max mem: 33370 +Epoch: [25] [1460/2639] eta: 0:56:42 lr: 1.999397642667577e-05 loss: 0.0384 (0.0422) time: 2.8875 data: 0.0074 max mem: 33370 +Epoch: [25] [1470/2639] eta: 0:56:13 lr: 1.9989256351445633e-05 loss: 0.0367 (0.0421) time: 2.8979 data: 0.0075 max mem: 33370 +Epoch: [25] [1480/2639] eta: 0:55:45 lr: 1.998453615237289e-05 loss: 0.0370 (0.0421) time: 2.9066 data: 0.0077 max mem: 33370 +Epoch: [25] [1490/2639] eta: 0:55:15 lr: 1.997981582942178e-05 loss: 0.0370 (0.0421) time: 2.8764 data: 0.0073 max mem: 33370 +Epoch: [25] [1500/2639] eta: 0:54:46 lr: 1.997509538255654e-05 loss: 0.0392 (0.0421) time: 2.8634 data: 0.0073 max mem: 33370 +Epoch: [25] [1510/2639] eta: 0:54:17 lr: 1.9970374811741377e-05 loss: 0.0397 (0.0420) time: 2.8626 data: 0.0076 max mem: 33370 +Epoch: [25] [1520/2639] eta: 0:53:48 lr: 1.9965654116940476e-05 loss: 0.0406 (0.0420) time: 2.8249 data: 0.0074 max mem: 33370 +Epoch: [25] [1530/2639] eta: 0:53:19 lr: 1.9960933298118014e-05 loss: 0.0387 (0.0420) time: 2.8296 data: 0.0075 max mem: 33370 +Epoch: [25] [1540/2639] eta: 0:52:50 lr: 1.9956212355238134e-05 loss: 0.0387 (0.0420) time: 2.8817 data: 0.0075 max mem: 33370 +Epoch: [25] [1550/2639] eta: 0:52:21 lr: 1.995149128826497e-05 loss: 0.0407 (0.0422) time: 2.9083 data: 0.0075 max mem: 33370 +Epoch: [25] [1560/2639] eta: 0:51:53 lr: 1.9946770097162622e-05 loss: 0.0393 (0.0422) time: 2.9143 data: 0.0074 max mem: 33370 +Epoch: [25] [1570/2639] eta: 0:51:24 lr: 1.9942048781895197e-05 loss: 0.0419 (0.0422) time: 2.9112 data: 0.0074 max mem: 33370 +Epoch: [25] [1580/2639] eta: 0:50:56 lr: 1.993732734242675e-05 loss: 0.0454 (0.0422) time: 2.9158 data: 0.0074 max mem: 33370 +Epoch: [25] [1590/2639] eta: 0:50:27 lr: 1.9932605778721343e-05 loss: 0.0432 (0.0422) time: 2.9127 data: 0.0073 max mem: 33370 +Epoch: [25] [1600/2639] eta: 0:49:58 lr: 1.9927884090742994e-05 loss: 0.0408 (0.0422) time: 2.8819 data: 0.0074 max mem: 33370 +Epoch: [25] [1610/2639] eta: 0:49:29 lr: 1.9923162278455727e-05 loss: 0.0411 (0.0423) time: 2.8880 data: 0.0073 max mem: 33370 +Epoch: [25] [1620/2639] eta: 0:49:00 lr: 1.991844034182352e-05 loss: 0.0396 (0.0423) time: 2.8772 data: 0.0073 max mem: 33370 +Epoch: [25] [1630/2639] eta: 0:48:31 lr: 1.9913718280810353e-05 loss: 0.0346 (0.0423) time: 2.8593 data: 0.0079 max mem: 33370 +Epoch: [25] [1640/2639] eta: 0:48:02 lr: 1.9908996095380173e-05 loss: 0.0362 (0.0423) time: 2.8625 data: 0.0080 max mem: 33370 +Epoch: [25] [1650/2639] eta: 0:47:33 lr: 1.9904273785496916e-05 loss: 0.0390 (0.0423) time: 2.8634 data: 0.0077 max mem: 33370 +Epoch: [25] [1660/2639] eta: 0:47:04 lr: 1.9899551351124482e-05 loss: 0.0372 (0.0424) time: 2.8857 data: 0.0076 max mem: 33370 +Epoch: [25] [1670/2639] eta: 0:46:35 lr: 1.9894828792226776e-05 loss: 0.0399 (0.0424) time: 2.8827 data: 0.0076 max mem: 33370 +Epoch: [25] [1680/2639] eta: 0:46:06 lr: 1.9890106108767654e-05 loss: 0.0405 (0.0424) time: 2.8780 data: 0.0075 max mem: 33370 +Epoch: [25] [1690/2639] eta: 0:45:38 lr: 1.9885383300710982e-05 loss: 0.0389 (0.0424) time: 2.8856 data: 0.0074 max mem: 33370 +Epoch: [25] [1700/2639] eta: 0:45:09 lr: 1.9880660368020574e-05 loss: 0.0379 (0.0424) time: 2.8691 data: 0.0081 max mem: 33370 +Epoch: [25] [1710/2639] eta: 0:44:40 lr: 1.9875937310660252e-05 loss: 0.0356 (0.0424) time: 2.8901 data: 0.0083 max mem: 33370 +Epoch: [25] [1720/2639] eta: 0:44:11 lr: 1.9871214128593817e-05 loss: 0.0343 (0.0423) time: 2.8995 data: 0.0080 max mem: 33370 +Epoch: [25] [1730/2639] eta: 0:43:42 lr: 1.9866490821785012e-05 loss: 0.0348 (0.0424) time: 2.8851 data: 0.0077 max mem: 33370 +Epoch: [25] [1740/2639] eta: 0:43:14 lr: 1.9861767390197616e-05 loss: 0.0348 (0.0423) time: 2.9203 data: 0.0076 max mem: 33370 +Epoch: [25] [1750/2639] eta: 0:42:45 lr: 1.985704383379534e-05 loss: 0.0339 (0.0423) time: 2.9262 data: 0.0079 max mem: 33370 +Epoch: [25] [1760/2639] eta: 0:42:16 lr: 1.985232015254191e-05 loss: 0.0378 (0.0423) time: 2.8887 data: 0.0078 max mem: 33370 +Epoch: [25] [1770/2639] eta: 0:41:47 lr: 1.9847596346400997e-05 loss: 0.0430 (0.0424) time: 2.8846 data: 0.0076 max mem: 33370 +Epoch: [25] [1780/2639] eta: 0:41:18 lr: 1.984287241533629e-05 loss: 0.0438 (0.0424) time: 2.8888 data: 0.0080 max mem: 33370 +Epoch: [25] [1790/2639] eta: 0:40:49 lr: 1.9838148359311424e-05 loss: 0.0418 (0.0424) time: 2.8591 data: 0.0086 max mem: 33370 +Epoch: [25] [1800/2639] eta: 0:40:20 lr: 1.9833424178290042e-05 loss: 0.0357 (0.0424) time: 2.8249 data: 0.0081 max mem: 33370 +Epoch: [25] [1810/2639] eta: 0:39:51 lr: 1.982869987223574e-05 loss: 0.0357 (0.0424) time: 2.8021 data: 0.0072 max mem: 33370 +Epoch: [25] [1820/2639] eta: 0:39:27 lr: 1.982397544111212e-05 loss: 0.0366 (0.0424) time: 3.3689 data: 0.5179 max mem: 33370 +Epoch: [25] [1830/2639] eta: 0:38:58 lr: 1.9819250884882738e-05 loss: 0.0389 (0.0424) time: 3.3992 data: 0.5178 max mem: 33370 +Epoch: [25] [1840/2639] eta: 0:38:29 lr: 1.9814526203511154e-05 loss: 0.0392 (0.0424) time: 2.8616 data: 0.0073 max mem: 33370 +Epoch: [25] [1850/2639] eta: 0:38:00 lr: 1.980980139696089e-05 loss: 0.0392 (0.0424) time: 2.9148 data: 0.0074 max mem: 33370 +Epoch: [25] [1860/2639] eta: 0:37:31 lr: 1.9805076465195464e-05 loss: 0.0424 (0.0424) time: 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1.972946049782917e-05 loss: 0.0383 (0.0423) time: 2.9089 data: 0.0076 max mem: 33370 +Epoch: [25] [2030/2639] eta: 0:29:20 lr: 1.972473343180285e-05 loss: 0.0398 (0.0423) time: 2.9074 data: 0.0076 max mem: 33370 +Epoch: [25] [2040/2639] eta: 0:28:51 lr: 1.9720006239901012e-05 loss: 0.0407 (0.0423) time: 2.9157 data: 0.0075 max mem: 33370 +Epoch: [25] [2050/2639] eta: 0:28:22 lr: 1.9715278922086786e-05 loss: 0.0400 (0.0423) time: 2.9095 data: 0.0075 max mem: 33370 +Epoch: [25] [2060/2639] eta: 0:27:53 lr: 1.971055147832326e-05 loss: 0.0420 (0.0423) time: 2.9058 data: 0.0076 max mem: 33370 +Epoch: [25] [2070/2639] eta: 0:27:24 lr: 1.970582390857352e-05 loss: 0.0404 (0.0423) time: 2.8855 data: 0.0074 max mem: 33370 +Epoch: [25] [2080/2639] eta: 0:26:55 lr: 1.9701096212800615e-05 loss: 0.0337 (0.0423) time: 2.8961 data: 0.0072 max mem: 33370 +Epoch: [25] [2090/2639] eta: 0:26:27 lr: 1.9696368390967595e-05 loss: 0.0321 (0.0423) time: 2.9189 data: 0.0073 max mem: 33370 +Epoch: [25] [2100/2639] eta: 0:25:58 lr: 1.969164044303746e-05 loss: 0.0328 (0.0423) time: 2.8932 data: 0.0076 max mem: 33370 +Epoch: [25] [2110/2639] eta: 0:25:29 lr: 1.968691236897322e-05 loss: 0.0339 (0.0423) time: 2.8961 data: 0.0077 max mem: 33370 +Epoch: [25] [2120/2639] eta: 0:25:00 lr: 1.9682184168737836e-05 loss: 0.0339 (0.0422) time: 2.9082 data: 0.0073 max mem: 33370 +Epoch: [25] [2130/2639] eta: 0:24:31 lr: 1.9677455842294275e-05 loss: 0.0366 (0.0422) time: 2.9115 data: 0.0073 max mem: 33370 +Epoch: [25] [2140/2639] eta: 0:24:02 lr: 1.9672727389605455e-05 loss: 0.0374 (0.0422) time: 2.9034 data: 0.0076 max mem: 33370 +Epoch: [25] [2150/2639] eta: 0:23:33 lr: 1.96679988106343e-05 loss: 0.0358 (0.0422) time: 2.8494 data: 0.0079 max mem: 33370 +Epoch: [25] [2160/2639] eta: 0:23:04 lr: 1.9663270105343702e-05 loss: 0.0377 (0.0422) time: 2.8502 data: 0.0076 max mem: 33370 +Epoch: [25] [2170/2639] eta: 0:22:35 lr: 1.9658541273696522e-05 loss: 0.0435 (0.0423) time: 2.9111 data: 0.0077 max mem: 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data: 0.0073 max mem: 33370 +Epoch: [25] [2260/2639] eta: 0:18:16 lr: 1.9615976096689273e-05 loss: 0.0454 (0.0423) time: 2.9658 data: 0.0073 max mem: 33370 +Epoch: [25] [2270/2639] eta: 0:17:47 lr: 1.961124599942961e-05 loss: 0.0384 (0.0422) time: 2.9285 data: 0.0073 max mem: 33370 +Epoch: [25] [2280/2639] eta: 0:17:18 lr: 1.9606515775403576e-05 loss: 0.0384 (0.0422) time: 2.8715 data: 0.0076 max mem: 33370 +Epoch: [25] [2290/2639] eta: 0:16:49 lr: 1.9601785424573772e-05 loss: 0.0396 (0.0422) time: 2.8817 data: 0.0079 max mem: 33370 +Epoch: [25] [2300/2639] eta: 0:16:20 lr: 1.9597054946902814e-05 loss: 0.0388 (0.0422) time: 2.8812 data: 0.0078 max mem: 33370 +Epoch: [25] [2310/2639] eta: 0:15:51 lr: 1.9592324342353263e-05 loss: 0.0388 (0.0422) time: 2.8580 data: 0.0077 max mem: 33370 +Epoch: [25] [2320/2639] eta: 0:15:22 lr: 1.958759361088769e-05 loss: 0.0375 (0.0422) time: 2.8503 data: 0.0075 max mem: 33370 +Epoch: [25] [2330/2639] eta: 0:14:53 lr: 1.9582862752468618e-05 loss: 0.0378 (0.0423) time: 2.8790 data: 0.0075 max mem: 33370 +Epoch: [25] [2340/2639] eta: 0:14:24 lr: 1.957813176705857e-05 loss: 0.0404 (0.0423) time: 2.8719 data: 0.0075 max mem: 33370 +Epoch: [25] [2350/2639] eta: 0:13:55 lr: 1.9573400654620026e-05 loss: 0.0415 (0.0423) time: 2.8385 data: 0.0073 max mem: 33370 +Epoch: [25] [2360/2639] eta: 0:13:26 lr: 1.956866941511548e-05 loss: 0.0394 (0.0423) time: 2.8587 data: 0.0074 max mem: 33370 +Epoch: [25] [2370/2639] eta: 0:12:57 lr: 1.956393804850736e-05 loss: 0.0380 (0.0423) time: 2.8380 data: 0.0075 max mem: 33370 +Epoch: [25] [2380/2639] eta: 0:12:28 lr: 1.9559206554758104e-05 loss: 0.0398 (0.0423) time: 2.8408 data: 0.0077 max mem: 33370 +Epoch: [25] [2390/2639] eta: 0:11:59 lr: 1.955447493383012e-05 loss: 0.0376 (0.0423) time: 2.8921 data: 0.0076 max mem: 33370 +Epoch: [25] [2400/2639] eta: 0:11:30 lr: 1.9549743185685798e-05 loss: 0.0407 (0.0423) time: 2.8984 data: 0.0074 max mem: 33370 +Epoch: [25] [2410/2639] eta: 0:11:01 lr: 1.9545011310287495e-05 loss: 0.0350 (0.0423) time: 2.8935 data: 0.0076 max mem: 33370 +Epoch: [25] [2420/2639] eta: 0:10:33 lr: 1.9540279307597568e-05 loss: 0.0350 (0.0423) time: 2.9019 data: 0.0076 max mem: 33370 +Epoch: [25] [2430/2639] eta: 0:10:04 lr: 1.9535547177578324e-05 loss: 0.0375 (0.0423) time: 2.9003 data: 0.0076 max mem: 33370 +Epoch: [25] [2440/2639] eta: 0:09:35 lr: 1.9530814920192082e-05 loss: 0.0396 (0.0423) time: 2.9275 data: 0.0075 max mem: 33370 +Epoch: [25] [2450/2639] eta: 0:09:06 lr: 1.9526082535401107e-05 loss: 0.0396 (0.0423) time: 2.9433 data: 0.0077 max mem: 33370 +Epoch: [25] [2460/2639] eta: 0:08:37 lr: 1.9521350023167665e-05 loss: 0.0363 (0.0423) time: 2.9382 data: 0.0076 max mem: 33370 +Epoch: [25] [2470/2639] eta: 0:08:08 lr: 1.9516617383453996e-05 loss: 0.0355 (0.0423) time: 2.9456 data: 0.0074 max mem: 33370 +Epoch: [25] [2480/2639] eta: 0:07:39 lr: 1.9511884616222312e-05 loss: 0.0410 (0.0423) time: 2.9060 data: 0.0076 max mem: 33370 +Epoch: [25] 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mem: 33370 +Epoch: [25] [2570/2639] eta: 0:03:19 lr: 1.94692839665817e-05 loss: 0.0409 (0.0424) time: 2.8771 data: 0.0077 max mem: 33370 +Epoch: [25] [2580/2639] eta: 0:02:50 lr: 1.9464549922087073e-05 loss: 0.0426 (0.0425) time: 2.8986 data: 0.0079 max mem: 33370 +Epoch: [25] [2590/2639] eta: 0:02:21 lr: 1.9459815749657403e-05 loss: 0.0441 (0.0425) time: 2.9032 data: 0.0083 max mem: 33370 +Epoch: [25] [2600/2639] eta: 0:01:52 lr: 1.9455081449254638e-05 loss: 0.0444 (0.0425) time: 2.9058 data: 0.0080 max mem: 33370 +Epoch: [25] [2610/2639] eta: 0:01:23 lr: 1.9450347020840728e-05 loss: 0.0428 (0.0425) time: 2.8888 data: 0.0078 max mem: 33370 +Epoch: [25] [2620/2639] eta: 0:00:54 lr: 1.9445612464377575e-05 loss: 0.0368 (0.0425) time: 2.8907 data: 0.0077 max mem: 33370 +Epoch: [25] [2630/2639] eta: 0:00:26 lr: 1.9440877779827082e-05 loss: 0.0342 (0.0425) time: 2.9274 data: 0.0075 max mem: 33370 +Epoch: [25] Total time: 2:07:11 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 2:55:11 time: 4.0851 data: 3.9948 max mem: 33370 +Test: [ 100/2573] eta: 0:04:50 time: 0.0769 data: 0.0014 max mem: 33370 +Test: [ 200/2573] eta: 0:03:54 time: 0.0797 data: 0.0015 max mem: 33370 +Test: [ 300/2573] eta: 0:03:29 time: 0.0877 data: 0.0083 max mem: 33370 +Test: [ 400/2573] eta: 0:03:22 time: 0.1741 data: 0.0953 max mem: 33370 +Test: [ 500/2573] eta: 0:03:11 time: 0.1263 data: 0.0497 max mem: 33370 +Test: [ 600/2573] eta: 0:03:01 time: 0.0783 data: 0.0013 max mem: 33370 +Test: [ 700/2573] eta: 0:02:49 time: 0.0795 data: 0.0015 max mem: 33370 +Test: [ 800/2573] eta: 0:02:38 time: 0.0824 data: 0.0012 max mem: 33370 +Test: [ 900/2573] eta: 0:02:30 time: 0.0824 data: 0.0012 max mem: 33370 +Test: [1000/2573] eta: 0:02:21 time: 0.0776 data: 0.0010 max mem: 33370 +Test: [1100/2573] eta: 0:02:13 time: 0.0799 data: 0.0015 max mem: 33370 +Test: [1200/2573] eta: 0:02:03 time: 0.0793 data: 0.0014 max mem: 33370 +Test: [1300/2573] eta: 0:01:53 time: 0.0794 data: 0.0014 max mem: 33370 +Test: [1400/2573] eta: 0:01:44 time: 0.0789 data: 0.0014 max mem: 33370 +Test: [1500/2573] eta: 0:01:34 time: 0.0792 data: 0.0013 max mem: 33370 +Test: [1600/2573] eta: 0:01:25 time: 0.0836 data: 0.0014 max mem: 33370 +Test: [1700/2573] eta: 0:01:16 time: 0.0782 data: 0.0014 max mem: 33370 +Test: [1800/2573] eta: 0:01:07 time: 0.0815 data: 0.0014 max mem: 33370 +Test: [1900/2573] eta: 0:00:58 time: 0.0789 data: 0.0016 max mem: 33370 +Test: [2000/2573] eta: 0:00:49 time: 0.0805 data: 0.0014 max mem: 33370 +Test: [2100/2573] eta: 0:00:40 time: 0.0816 data: 0.0014 max mem: 33370 +Test: [2200/2573] eta: 0:00:31 time: 0.0819 data: 0.0015 max mem: 33370 +Test: [2300/2573] eta: 0:00:23 time: 0.0816 data: 0.0014 max mem: 33370 +Test: [2400/2573] eta: 0:00:14 time: 0.0776 data: 0.0014 max mem: 33370 +Test: [2500/2573] eta: 0:00:06 time: 0.0797 data: 0.0014 max mem: 33370 +Test: Total time: 0:03:38 +Final results: +Mean IoU is 63.15 + + precision@0.5 = 71.00 + precision@0.6 = 65.87 + precision@0.7 = 58.97 + precision@0.8 = 47.69 + precision@0.9 = 23.45 + overall IoU = 60.77 + +Average object IoU 63.15225470784236 +Overall IoU 60.77189254760742 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [26] [ 0/2639] eta: 5:09:10 lr: 1.9436616454185443e-05 loss: 0.0244 (0.0244) time: 7.0294 data: 3.7300 max mem: 33370 +Epoch: [26] [ 10/2639] eta: 2:23:25 lr: 1.9431881526163935e-05 loss: 0.0431 (0.0406) time: 3.2732 data: 0.3457 max mem: 33370 +Epoch: [26] [ 20/2639] eta: 2:15:02 lr: 1.9427146469944455e-05 loss: 0.0413 (0.0427) time: 2.8968 data: 0.0071 max mem: 33370 +Epoch: [26] [ 30/2639] eta: 2:12:01 lr: 1.9422411285488805e-05 loss: 0.0351 (0.0409) time: 2.9057 data: 0.0072 max mem: 33370 +Epoch: [26] [ 40/2639] eta: 2:10:48 lr: 1.941767597275878e-05 loss: 0.0356 (0.0406) time: 2.9427 data: 0.0074 max mem: 33370 +Epoch: [26] [ 50/2639] eta: 2:09:02 lr: 1.9412940531716138e-05 loss: 0.0367 (0.0397) time: 2.9204 data: 0.0079 max mem: 33370 +Epoch: [26] [ 60/2639] eta: 2:07:57 lr: 1.9408204962322638e-05 loss: 0.0367 (0.0402) time: 2.8892 data: 0.0081 max mem: 33370 +Epoch: [26] [ 70/2639] eta: 2:07:06 lr: 1.9403469264539984e-05 loss: 0.0362 (0.0402) time: 2.9125 data: 0.0077 max mem: 33370 +Epoch: [26] [ 80/2639] eta: 2:06:10 lr: 1.9398733438329882e-05 loss: 0.0371 (0.0397) time: 2.9020 data: 0.0081 max mem: 33370 +Epoch: [26] [ 90/2639] eta: 2:05:10 lr: 1.9393997483654023e-05 loss: 0.0337 (0.0395) time: 2.8678 data: 0.0081 max mem: 33370 +Epoch: [26] [ 100/2639] eta: 2:04:22 lr: 1.9389261400474044e-05 loss: 0.0337 (0.0395) time: 2.8611 data: 0.0076 max mem: 33370 +Epoch: [26] [ 110/2639] eta: 2:03:34 lr: 1.9384525188751594e-05 loss: 0.0331 (0.0389) time: 2.8640 data: 0.0075 max mem: 33370 +Epoch: [26] [ 120/2639] eta: 2:02:50 lr: 1.937978884844828e-05 loss: 0.0350 (0.0394) time: 2.8594 data: 0.0076 max mem: 33370 +Epoch: [26] [ 130/2639] eta: 2:02:08 lr: 1.9375052379525698e-05 loss: 0.0386 (0.0397) time: 2.8624 data: 0.0080 max mem: 33370 +Epoch: [26] [ 140/2639] eta: 2:01:26 lr: 1.937031578194541e-05 loss: 0.0382 (0.0395) time: 2.8535 data: 0.0079 max mem: 33370 +Epoch: [26] [ 150/2639] eta: 2:00:47 lr: 1.936557905566897e-05 loss: 0.0330 (0.0392) time: 2.8509 data: 0.0075 max mem: 33370 +Epoch: [26] [ 160/2639] eta: 2:00:13 lr: 1.9360842200657898e-05 loss: 0.0330 (0.0387) time: 2.8692 data: 0.0075 max mem: 33370 +Epoch: [26] [ 170/2639] eta: 1:59:39 lr: 1.9356105216873702e-05 loss: 0.0341 (0.0390) time: 2.8796 data: 0.0077 max mem: 33370 +Epoch: [26] [ 180/2639] eta: 1:59:20 lr: 1.935136810427785e-05 loss: 0.0346 (0.0387) time: 2.9267 data: 0.0077 max mem: 33370 +Epoch: [26] [ 190/2639] eta: 1:58:51 lr: 1.9346630862831827e-05 loss: 0.0346 (0.0388) time: 2.9454 data: 0.0073 max mem: 33370 +Epoch: [26] [ 200/2639] eta: 1:58:14 lr: 1.9341893492497047e-05 loss: 0.0381 (0.0389) time: 2.8805 data: 0.0075 max mem: 33370 +Epoch: [26] [ 210/2639] eta: 1:57:40 lr: 1.933715599323494e-05 loss: 0.0381 (0.0388) time: 2.8564 data: 0.0080 max mem: 33370 +Epoch: [26] [ 220/2639] eta: 1:57:05 lr: 1.9332418365006884e-05 loss: 0.0381 (0.0388) time: 2.8608 data: 0.0081 max mem: 33370 +Epoch: [26] [ 230/2639] eta: 1:56:28 lr: 1.9327680607774268e-05 loss: 0.0375 (0.0390) time: 2.8429 data: 0.0078 max mem: 33370 +Epoch: [26] [ 240/2639] eta: 1:55:58 lr: 1.932294272149843e-05 loss: 0.0478 (0.0398) time: 2.8589 data: 0.0079 max mem: 33370 +Epoch: [26] [ 250/2639] eta: 1:55:27 lr: 1.9318204706140697e-05 loss: 0.0505 (0.0400) time: 2.8811 data: 0.0079 max mem: 33370 +Epoch: [26] [ 260/2639] eta: 1:54:53 lr: 1.9313466561662375e-05 loss: 0.0375 (0.0399) time: 2.8627 data: 0.0076 max mem: 33370 +Epoch: [26] [ 270/2639] eta: 1:54:26 lr: 1.9308728288024748e-05 loss: 0.0374 (0.0400) time: 2.8836 data: 0.0075 max mem: 33370 +Epoch: [26] [ 280/2639] eta: 1:53:52 lr: 1.9303989885189078e-05 loss: 0.0379 (0.0400) time: 2.8775 data: 0.0074 max mem: 33370 +Epoch: [26] [ 290/2639] eta: 1:53:31 lr: 1.92992513531166e-05 loss: 0.0331 (0.0404) time: 2.9212 data: 0.0075 max mem: 33370 +Epoch: [26] [ 300/2639] eta: 1:53:05 lr: 1.929451269176853e-05 loss: 0.0331 (0.0404) time: 2.9666 data: 0.0077 max mem: 33370 +Epoch: [26] [ 310/2639] eta: 1:52:40 lr: 1.928977390110607e-05 loss: 0.0350 (0.0402) time: 2.9461 data: 0.0079 max mem: 33370 +Epoch: [26] [ 320/2639] eta: 1:52:15 lr: 1.9285034981090377e-05 loss: 0.0327 (0.0401) time: 2.9556 data: 0.0076 max mem: 33370 +Epoch: [26] [ 330/2639] eta: 1:51:48 lr: 1.9280295931682607e-05 loss: 0.0336 (0.0401) time: 2.9459 data: 0.0074 max mem: 33370 +Epoch: [26] [ 340/2639] eta: 1:51:21 lr: 1.9275556752843895e-05 loss: 0.0392 (0.0402) time: 2.9359 data: 0.0079 max mem: 33370 +Epoch: [26] [ 350/2639] eta: 1:50:53 lr: 1.9270817444535337e-05 loss: 0.0336 (0.0400) time: 2.9240 data: 0.0083 max mem: 33370 +Epoch: [26] [ 360/2639] eta: 1:50:24 lr: 1.926607800671802e-05 loss: 0.0332 (0.0401) time: 2.9194 data: 0.0080 max mem: 33370 +Epoch: [26] [ 370/2639] eta: 1:49:57 lr: 1.9261338439352993e-05 loss: 0.0413 (0.0402) time: 2.9293 data: 0.0077 max mem: 33370 +Epoch: [26] [ 380/2639] eta: 1:49:27 lr: 1.9256598742401314e-05 loss: 0.0429 (0.0403) time: 2.9141 data: 0.0076 max mem: 33370 +Epoch: [26] [ 390/2639] eta: 1:48:59 lr: 1.925185891582398e-05 loss: 0.0372 (0.0402) time: 2.9107 data: 0.0075 max mem: 33370 +Epoch: [26] [ 400/2639] eta: 1:48:28 lr: 1.9247118959581993e-05 loss: 0.0353 (0.0407) time: 2.9023 data: 0.0072 max mem: 33370 +Epoch: [26] [ 410/2639] eta: 1:47:57 lr: 1.9242378873636318e-05 loss: 0.0395 (0.0410) time: 2.8671 data: 0.0076 max mem: 33370 +Epoch: [26] [ 420/2639] eta: 1:47:25 lr: 1.9237638657947913e-05 loss: 0.0371 (0.0412) time: 2.8538 data: 0.0077 max mem: 33370 +Epoch: [26] [ 430/2639] eta: 1:46:54 lr: 1.9232898312477686e-05 loss: 0.0358 (0.0411) time: 2.8607 data: 0.0074 max mem: 33370 +Epoch: [26] [ 440/2639] eta: 1:46:20 lr: 1.9228157837186564e-05 loss: 0.0369 (0.0410) time: 2.8433 data: 0.0075 max mem: 33370 +Epoch: [26] [ 450/2639] eta: 1:45:49 lr: 1.9223417232035405e-05 loss: 0.0371 (0.0409) time: 2.8349 data: 0.0075 max mem: 33370 +Epoch: [26] [ 460/2639] eta: 1:45:20 lr: 1.9218676496985086e-05 loss: 0.0368 (0.0409) time: 2.8718 data: 0.0075 max mem: 33370 +Epoch: [26] [ 470/2639] eta: 1:44:47 lr: 1.9213935631996427e-05 loss: 0.0423 (0.0411) time: 2.8542 data: 0.0075 max mem: 33370 +Epoch: [26] [ 480/2639] eta: 1:44:16 lr: 1.9209194637030253e-05 loss: 0.0428 (0.0412) time: 2.8382 data: 0.0074 max mem: 33370 +Epoch: [26] [ 490/2639] eta: 1:43:48 lr: 1.9204453512047348e-05 loss: 0.0413 (0.0412) time: 2.8828 data: 0.0077 max mem: 33370 +Epoch: [26] [ 500/2639] eta: 1:43:20 lr: 1.9199712257008483e-05 loss: 0.0402 (0.0412) time: 2.9194 data: 0.0076 max mem: 33370 +Epoch: [26] [ 510/2639] eta: 1:42:51 lr: 1.9194970871874397e-05 loss: 0.0307 (0.0412) time: 2.9189 data: 0.0073 max mem: 33370 +Epoch: [26] [ 520/2639] eta: 1:42:21 lr: 1.919022935660582e-05 loss: 0.0343 (0.0412) time: 2.8846 data: 0.0076 max mem: 33370 +Epoch: [26] [ 530/2639] eta: 1:41:49 lr: 1.918548771116345e-05 loss: 0.0376 (0.0412) time: 2.8420 data: 0.0077 max mem: 33370 +Epoch: [26] [ 540/2639] eta: 1:41:17 lr: 1.918074593550797e-05 loss: 0.0361 (0.0411) time: 2.8188 data: 0.0077 max mem: 33370 +Epoch: [26] [ 550/2639] eta: 1:40:48 lr: 1.917600402960002e-05 loss: 0.0350 (0.0410) time: 2.8624 data: 0.0077 max mem: 33370 +Epoch: [26] [ 560/2639] eta: 1:40:22 lr: 1.9171261993400248e-05 loss: 0.0350 (0.0410) time: 2.9356 data: 0.0078 max mem: 33370 +Epoch: [26] [ 570/2639] eta: 1:39:54 lr: 1.916651982686925e-05 loss: 0.0364 (0.0410) time: 2.9395 data: 0.0077 max mem: 33370 +Epoch: [26] [ 580/2639] eta: 1:39:24 lr: 1.9161777529967618e-05 loss: 0.0401 (0.0411) time: 2.9008 data: 0.0076 max mem: 33370 +Epoch: [26] [ 590/2639] eta: 1:38:55 lr: 1.9157035102655923e-05 loss: 0.0390 (0.0411) time: 2.8875 data: 0.0079 max mem: 33370 +Epoch: [26] [ 600/2639] eta: 1:38:27 lr: 1.9152292544894697e-05 loss: 0.0354 (0.0410) time: 2.9128 data: 0.0082 max mem: 33370 +Epoch: [26] [ 610/2639] eta: 1:37:56 lr: 1.914754985664446e-05 loss: 0.0343 (0.0410) time: 2.8758 data: 0.0080 max mem: 33370 +Epoch: [26] [ 620/2639] eta: 1:37:30 lr: 1.9142807037865708e-05 loss: 0.0302 (0.0409) time: 2.9150 data: 0.0076 max mem: 33370 +Epoch: [26] [ 630/2639] eta: 1:37:02 lr: 1.913806408851892e-05 loss: 0.0307 (0.0409) time: 2.9695 data: 0.0078 max mem: 33370 +Epoch: [26] [ 640/2639] eta: 1:36:34 lr: 1.9133321008564532e-05 loss: 0.0326 (0.0408) time: 2.9271 data: 0.0077 max mem: 33370 +Epoch: [26] [ 650/2639] eta: 1:36:05 lr: 1.9128577797962986e-05 loss: 0.0332 (0.0408) time: 2.9088 data: 0.0074 max mem: 33370 +Epoch: [26] [ 660/2639] eta: 1:35:35 lr: 1.912383445667467e-05 loss: 0.0397 (0.0407) time: 2.8834 data: 0.0071 max mem: 33370 +Epoch: [26] [ 670/2639] eta: 1:35:06 lr: 1.9119090984659983e-05 loss: 0.0417 (0.0409) time: 2.8876 data: 0.0073 max mem: 33370 +Epoch: [26] [ 680/2639] eta: 1:34:37 lr: 1.9114347381879268e-05 loss: 0.0420 (0.0409) time: 2.8979 data: 0.0077 max mem: 33370 +Epoch: [26] [ 690/2639] eta: 1:34:09 lr: 1.9109603648292867e-05 loss: 0.0355 (0.0407) time: 2.8997 data: 0.0077 max mem: 33370 +Epoch: [26] [ 700/2639] eta: 1:33:41 lr: 1.9104859783861086e-05 loss: 0.0358 (0.0408) time: 2.9230 data: 0.0076 max mem: 33370 +Epoch: [26] [ 710/2639] eta: 1:33:12 lr: 1.910011578854423e-05 loss: 0.0403 (0.0408) time: 2.9229 data: 0.0078 max mem: 33370 +Epoch: [26] [ 720/2639] eta: 1:32:43 lr: 1.9095371662302543e-05 loss: 0.0398 (0.0408) time: 2.9071 data: 0.0084 max mem: 33370 +Epoch: [26] [ 730/2639] eta: 1:32:13 lr: 1.9090627405096286e-05 loss: 0.0391 (0.0409) time: 2.8757 data: 0.0083 max mem: 33370 +Epoch: [26] [ 740/2639] eta: 1:31:43 lr: 1.908588301688567e-05 loss: 0.0321 (0.0409) time: 2.8521 data: 0.0077 max mem: 33370 +Epoch: [26] [ 750/2639] eta: 1:31:12 lr: 1.9081138497630898e-05 loss: 0.0352 (0.0409) time: 2.8482 data: 0.0078 max mem: 33370 +Epoch: [26] [ 760/2639] eta: 1:30:42 lr: 1.9076393847292136e-05 loss: 0.0352 (0.0408) time: 2.8458 data: 0.0077 max mem: 33370 +Epoch: [26] [ 770/2639] eta: 1:30:13 lr: 1.907164906582954e-05 loss: 0.0351 (0.0407) time: 2.8726 data: 0.0074 max mem: 33370 +Epoch: [26] [ 780/2639] eta: 1:29:43 lr: 1.906690415320324e-05 loss: 0.0351 (0.0407) time: 2.8718 data: 0.0077 max mem: 33370 +Epoch: [26] [ 790/2639] eta: 1:29:13 lr: 1.9062159109373336e-05 loss: 0.0350 (0.0407) time: 2.8407 data: 0.0078 max mem: 33370 +Epoch: [26] [ 800/2639] eta: 1:28:44 lr: 1.9057413934299906e-05 loss: 0.0377 (0.0406) time: 2.8714 data: 0.0076 max mem: 33370 +Epoch: [26] [ 810/2639] eta: 1:28:14 lr: 1.905266862794302e-05 loss: 0.0329 (0.0405) time: 2.8861 data: 0.0074 max mem: 33370 +Epoch: [26] [ 820/2639] eta: 1:27:46 lr: 1.90479231902627e-05 loss: 0.0318 (0.0405) time: 2.8906 data: 0.0075 max mem: 33370 +Epoch: [26] [ 830/2639] eta: 1:27:18 lr: 1.9043177621218962e-05 loss: 0.0374 (0.0406) time: 2.9332 data: 0.0078 max mem: 33370 +Epoch: [26] [ 840/2639] eta: 1:26:51 lr: 1.9038431920771802e-05 loss: 0.0401 (0.0407) time: 2.9701 data: 0.0076 max mem: 33370 +Epoch: [26] [ 850/2639] eta: 1:26:22 lr: 1.9033686088881175e-05 loss: 0.0364 (0.0406) time: 2.9443 data: 0.0073 max mem: 33370 +Epoch: [26] [ 860/2639] eta: 1:25:53 lr: 1.902894012550703e-05 loss: 0.0328 (0.0405) time: 2.8873 data: 0.0072 max mem: 33370 +Epoch: [26] [ 870/2639] eta: 1:25:24 lr: 1.9024194030609277e-05 loss: 0.0309 (0.0405) time: 2.8847 data: 0.0074 max mem: 33370 +Epoch: [26] [ 880/2639] eta: 1:24:54 lr: 1.9019447804147823e-05 loss: 0.0370 (0.0405) time: 2.8598 data: 0.0074 max mem: 33370 +Epoch: [26] [ 890/2639] eta: 1:24:24 lr: 1.9014701446082528e-05 loss: 0.0379 (0.0406) time: 2.8452 data: 0.0075 max mem: 33370 +Epoch: [26] [ 900/2639] eta: 1:23:55 lr: 1.9009954956373252e-05 loss: 0.0483 (0.0407) time: 2.8746 data: 0.0077 max mem: 33370 +Epoch: [26] [ 910/2639] eta: 1:23:27 lr: 1.9005208334979807e-05 loss: 0.0437 (0.0407) time: 2.9140 data: 0.0077 max mem: 33370 +Epoch: [26] [ 920/2639] eta: 1:22:58 lr: 1.900046158186201e-05 loss: 0.0358 (0.0406) time: 2.9269 data: 0.0075 max mem: 33370 +Epoch: [26] [ 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33370 +Epoch: [26] [1010/2639] eta: 1:18:37 lr: 1.895773486956125e-05 loss: 0.0377 (0.0405) time: 2.9048 data: 0.0077 max mem: 33370 +Epoch: [26] [1020/2639] eta: 1:18:08 lr: 1.895298679698378e-05 loss: 0.0374 (0.0405) time: 2.8951 data: 0.0078 max mem: 33370 +Epoch: [26] [1030/2639] eta: 1:17:39 lr: 1.894823859223821e-05 loss: 0.0413 (0.0407) time: 2.8836 data: 0.0080 max mem: 33370 +Epoch: [26] [1040/2639] eta: 1:17:09 lr: 1.894349025528407e-05 loss: 0.0379 (0.0407) time: 2.8701 data: 0.0076 max mem: 33370 +Epoch: [26] [1050/2639] eta: 1:16:40 lr: 1.893874178608085e-05 loss: 0.0350 (0.0406) time: 2.8719 data: 0.0075 max mem: 33370 +Epoch: [26] [1060/2639] eta: 1:16:11 lr: 1.8933993184588018e-05 loss: 0.0340 (0.0406) time: 2.8844 data: 0.0077 max mem: 33370 +Epoch: [26] [1070/2639] eta: 1:15:42 lr: 1.892924445076504e-05 loss: 0.0352 (0.0405) time: 2.8955 data: 0.0083 max mem: 33370 +Epoch: [26] [1080/2639] eta: 1:15:13 lr: 1.892449558457132e-05 loss: 0.0314 (0.0405) time: 2.9029 data: 0.0081 max mem: 33370 +Epoch: [26] [1090/2639] eta: 1:14:43 lr: 1.8919746585966273e-05 loss: 0.0310 (0.0404) time: 2.8586 data: 0.0076 max mem: 33370 +Epoch: [26] [1100/2639] eta: 1:14:15 lr: 1.8914997454909262e-05 loss: 0.0358 (0.0404) time: 2.8712 data: 0.0074 max mem: 33370 +Epoch: [26] [1110/2639] eta: 1:13:45 lr: 1.8910248191359656e-05 loss: 0.0358 (0.0403) time: 2.8804 data: 0.0072 max mem: 33370 +Epoch: [26] [1120/2639] eta: 1:13:19 lr: 1.890549879527677e-05 loss: 0.0351 (0.0404) time: 2.9746 data: 0.0930 max mem: 33370 +Epoch: [26] [1130/2639] eta: 1:12:50 lr: 1.8900749266619918e-05 loss: 0.0384 (0.0403) time: 3.0080 data: 0.0929 max mem: 33370 +Epoch: [26] [1140/2639] eta: 1:12:21 lr: 1.8895999605348376e-05 loss: 0.0384 (0.0403) time: 2.9042 data: 0.0070 max mem: 33370 +Epoch: [26] [1150/2639] eta: 1:12:44 lr: 1.889124981142141e-05 loss: 0.0368 (0.0403) time: 4.8760 data: 1.8563 max mem: 33370 +Epoch: [26] [1160/2639] eta: 1:12:18 lr: 1.888649988479824e-05 loss: 0.0373 (0.0403) time: 5.0256 data: 1.8560 max mem: 33370 +Epoch: [26] [1170/2639] eta: 1:11:59 lr: 1.8881749825438093e-05 loss: 0.0373 (0.0402) time: 3.4902 data: 0.4260 max mem: 33370 +Epoch: [26] [1180/2639] eta: 1:11:29 lr: 1.8876999633300134e-05 loss: 0.0420 (0.0403) time: 3.3209 data: 0.4264 max mem: 33370 +Epoch: [26] [1190/2639] eta: 1:10:59 lr: 1.8872249308343546e-05 loss: 0.0463 (0.0404) time: 2.8757 data: 0.0074 max mem: 33370 +Epoch: [26] [1200/2639] eta: 1:10:29 lr: 1.8867498850527453e-05 loss: 0.0470 (0.0404) time: 2.9146 data: 0.0072 max mem: 33370 +Epoch: [26] [1210/2639] eta: 1:10:00 lr: 1.886274825981097e-05 loss: 0.0378 (0.0405) time: 2.9336 data: 0.0074 max mem: 33370 +Epoch: [26] [1220/2639] eta: 1:09:29 lr: 1.8857997536153194e-05 loss: 0.0371 (0.0405) time: 2.8818 data: 0.0073 max mem: 33370 +Epoch: [26] [1230/2639] eta: 1:08:58 lr: 1.8853246679513188e-05 loss: 0.0380 (0.0405) time: 2.8286 data: 0.0069 max mem: 33370 +Epoch: [26] [1240/2639] eta: 1:08:29 lr: 1.884849568984999e-05 loss: 0.0426 (0.0405) time: 2.8907 data: 0.0075 max mem: 33370 +Epoch: [26] [1250/2639] eta: 1:08:00 lr: 1.8843744567122623e-05 loss: 0.0426 (0.0406) time: 2.9521 data: 0.0077 max mem: 33370 +Epoch: [26] [1260/2639] eta: 1:07:30 lr: 1.883899331129007e-05 loss: 0.0370 (0.0406) time: 2.9376 data: 0.0073 max mem: 33370 +Epoch: [26] [1270/2639] eta: 1:07:00 lr: 1.8834241922311315e-05 loss: 0.0384 (0.0406) time: 2.9017 data: 0.0076 max mem: 33370 +Epoch: [26] [1280/2639] eta: 1:06:30 lr: 1.8829490400145296e-05 loss: 0.0373 (0.0405) time: 2.8791 data: 0.0082 max mem: 33370 +Epoch: [26] [1290/2639] eta: 1:06:00 lr: 1.8824738744750934e-05 loss: 0.0357 (0.0405) time: 2.8694 data: 0.0078 max mem: 33370 +Epoch: [26] [1300/2639] eta: 1:05:31 lr: 1.8819986956087122e-05 loss: 0.0357 (0.0406) time: 2.8804 data: 0.0076 max mem: 33370 +Epoch: [26] [1310/2639] eta: 1:05:00 lr: 1.8815235034112736e-05 loss: 0.0367 (0.0406) time: 2.8856 data: 0.0080 max mem: 33370 +Epoch: [26] [1320/2639] eta: 1:04:30 lr: 1.881048297878663e-05 loss: 0.0439 (0.0407) time: 2.8354 data: 0.0078 max mem: 33370 +Epoch: [26] [1330/2639] eta: 1:04:00 lr: 1.8805730790067617e-05 loss: 0.0352 (0.0406) time: 2.8368 data: 0.0077 max mem: 33370 +Epoch: [26] [1340/2639] eta: 1:03:31 lr: 1.8800978467914514e-05 loss: 0.0337 (0.0406) time: 2.8990 data: 0.0076 max mem: 33370 +Epoch: [26] [1350/2639] eta: 1:03:00 lr: 1.8796226012286077e-05 loss: 0.0375 (0.0406) time: 2.8682 data: 0.0075 max mem: 33370 +Epoch: [26] [1360/2639] eta: 1:02:30 lr: 1.879147342314107e-05 loss: 0.0375 (0.0406) time: 2.8587 data: 0.0079 max mem: 33370 +Epoch: [26] [1370/2639] eta: 1:02:00 lr: 1.878672070043821e-05 loss: 0.0342 (0.0405) time: 2.8838 data: 0.0082 max mem: 33370 +Epoch: [26] [1380/2639] eta: 1:01:30 lr: 1.8781967844136214e-05 loss: 0.0295 (0.0405) time: 2.8582 data: 0.0082 max mem: 33370 +Epoch: [26] [1390/2639] eta: 1:01:00 lr: 1.8777214854193746e-05 loss: 0.0376 (0.0405) time: 2.8594 data: 0.0079 max mem: 33370 +Epoch: [26] [1400/2639] eta: 1:00:31 lr: 1.8772461730569468e-05 loss: 0.0409 (0.0406) time: 2.8821 data: 0.0075 max mem: 33370 +Epoch: [26] [1410/2639] eta: 1:00:01 lr: 1.8767708473222005e-05 loss: 0.0390 (0.0406) time: 2.8926 data: 0.0074 max mem: 33370 +Epoch: [26] [1420/2639] eta: 0:59:31 lr: 1.8762955082109964e-05 loss: 0.0403 (0.0406) time: 2.8800 data: 0.0074 max mem: 33370 +Epoch: [26] [1430/2639] eta: 0:59:01 lr: 1.8758201557191922e-05 loss: 0.0390 (0.0406) time: 2.8697 data: 0.0075 max mem: 33370 +Epoch: [26] [1440/2639] eta: 0:58:31 lr: 1.8753447898426442e-05 loss: 0.0337 (0.0406) time: 2.8439 data: 0.0078 max mem: 33370 +Epoch: [26] [1450/2639] eta: 0:58:02 lr: 1.874869410577205e-05 loss: 0.0318 (0.0406) time: 2.8727 data: 0.0078 max mem: 33370 +Epoch: [26] [1460/2639] eta: 0:57:33 lr: 1.8743940179187257e-05 loss: 0.0343 (0.0406) time: 2.9351 data: 0.0072 max mem: 33370 +Epoch: [26] [1470/2639] eta: 0:57:03 lr: 1.8739186118630535e-05 loss: 0.0346 (0.0405) time: 2.9196 data: 0.0073 max mem: 33370 +Epoch: [26] [1480/2639] eta: 0:56:34 lr: 1.8734431924060358e-05 loss: 0.0346 (0.0405) time: 2.8911 data: 0.0074 max mem: 33370 +Epoch: [26] [1490/2639] eta: 0:56:04 lr: 1.8729677595435144e-05 loss: 0.0356 (0.0405) time: 2.8934 data: 0.0072 max mem: 33370 +Epoch: [26] [1500/2639] eta: 0:55:35 lr: 1.8724923132713312e-05 loss: 0.0370 (0.0405) time: 2.9153 data: 0.0072 max mem: 33370 +Epoch: [26] [1510/2639] eta: 0:55:05 lr: 1.8720168535853236e-05 loss: 0.0360 (0.0405) time: 2.9110 data: 0.0077 max mem: 33370 +Epoch: [26] [1520/2639] eta: 0:54:36 lr: 1.871541380481329e-05 loss: 0.0374 (0.0405) time: 2.8871 data: 0.0077 max mem: 33370 +Epoch: [26] [1530/2639] eta: 0:54:06 lr: 1.871065893955179e-05 loss: 0.0420 (0.0406) time: 2.8878 data: 0.0076 max mem: 33370 +Epoch: [26] [1540/2639] eta: 0:53:37 lr: 1.8705903940027063e-05 loss: 0.0384 (0.0405) time: 2.8956 data: 0.0076 max mem: 33370 +Epoch: [26] [1550/2639] eta: 0:53:07 lr: 1.8701148806197378e-05 loss: 0.0384 (0.0405) time: 2.8946 data: 0.0074 max mem: 33370 +Epoch: [26] [1560/2639] eta: 0:52:37 lr: 1.8696393538021007e-05 loss: 0.0352 (0.0405) time: 2.8564 data: 0.0078 max mem: 33370 +Epoch: [26] [1570/2639] eta: 0:52:07 lr: 1.8691638135456184e-05 loss: 0.0335 (0.0405) time: 2.8386 data: 0.0079 max mem: 33370 +Epoch: [26] [1580/2639] eta: 0:51:38 lr: 1.8686882598461117e-05 loss: 0.0352 (0.0405) time: 2.9030 data: 0.0077 max mem: 33370 +Epoch: [26] [1590/2639] eta: 0:51:09 lr: 1.8682126926993996e-05 loss: 0.0417 (0.0405) time: 2.9071 data: 0.0077 max mem: 33370 +Epoch: [26] [1600/2639] eta: 0:50:39 lr: 1.8677371121012974e-05 loss: 0.0371 (0.0405) time: 2.8728 data: 0.0075 max mem: 33370 +Epoch: [26] [1610/2639] eta: 0:50:10 lr: 1.8672615180476198e-05 loss: 0.0330 (0.0405) time: 2.8974 data: 0.0076 max mem: 33370 +Epoch: [26] [1620/2639] eta: 0:49:40 lr: 1.8667859105341763e-05 loss: 0.0349 (0.0405) time: 2.8977 data: 0.0079 max mem: 33370 +Epoch: [26] [1630/2639] eta: 0:49:11 lr: 1.866310289556778e-05 loss: 0.0348 (0.0405) time: 2.8891 data: 0.0078 max mem: 33370 +Epoch: [26] [1640/2639] eta: 0:48:41 lr: 1.8658346551112287e-05 loss: 0.0319 (0.0405) time: 2.8973 data: 0.0075 max mem: 33370 +Epoch: [26] [1650/2639] eta: 0:48:12 lr: 1.8653590071933334e-05 loss: 0.0341 (0.0404) time: 2.8818 data: 0.0076 max mem: 33370 +Epoch: [26] [1660/2639] eta: 0:47:42 lr: 1.864883345798893e-05 loss: 0.0346 (0.0404) time: 2.8682 data: 0.0077 max mem: 33370 +Epoch: [26] [1670/2639] eta: 0:47:12 lr: 1.864407670923706e-05 loss: 0.0346 (0.0404) time: 2.8341 data: 0.0080 max mem: 33370 +Epoch: [26] [1680/2639] eta: 0:46:43 lr: 1.8639319825635684e-05 loss: 0.0344 (0.0404) time: 2.8110 data: 0.0083 max mem: 33370 +Epoch: [26] [1690/2639] eta: 0:46:13 lr: 1.8634562807142743e-05 loss: 0.0274 (0.0404) time: 2.8417 data: 0.0079 max mem: 33370 +Epoch: [26] [1700/2639] eta: 0:45:43 lr: 1.8629805653716145e-05 loss: 0.0265 (0.0403) time: 2.8470 data: 0.0074 max mem: 33370 +Epoch: [26] [1710/2639] eta: 0:45:14 lr: 1.8625048365313784e-05 loss: 0.0287 (0.0403) time: 2.8488 data: 0.0076 max mem: 33370 +Epoch: [26] [1720/2639] eta: 0:44:44 lr: 1.8620290941893507e-05 loss: 0.0324 (0.0403) time: 2.8687 data: 0.0076 max mem: 33370 +Epoch: [26] [1730/2639] eta: 0:44:15 lr: 1.8615533383413165e-05 loss: 0.0319 (0.0403) time: 2.9104 data: 0.0076 max mem: 33370 +Epoch: [26] [1740/2639] eta: 0:43:46 lr: 1.8610775689830557e-05 loss: 0.0346 (0.0402) time: 2.9090 data: 0.0074 max mem: 33370 +Epoch: [26] [1750/2639] eta: 0:43:16 lr: 1.8606017861103477e-05 loss: 0.0349 (0.0402) time: 2.8668 data: 0.0071 max mem: 33370 +Epoch: [26] [1760/2639] eta: 0:42:47 lr: 1.8601259897189684e-05 loss: 0.0380 (0.0402) time: 2.8616 data: 0.0072 max mem: 33370 +Epoch: [26] [1770/2639] eta: 0:42:17 lr: 1.8596501798046914e-05 loss: 0.0366 (0.0402) time: 2.8702 data: 0.0073 max mem: 33370 +Epoch: [26] [1780/2639] eta: 0:41:48 lr: 1.859174356363287e-05 loss: 0.0368 (0.0402) time: 2.8463 data: 0.0074 max 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1.8477505245917345e-05 loss: 0.0342 (0.0402) time: 2.8705 data: 0.0070 max mem: 33370 +Epoch: [26] [2030/2639] eta: 0:29:48 lr: 1.8472743615903193e-05 loss: 0.0395 (0.0402) time: 2.8434 data: 0.0071 max mem: 33370 +Epoch: [26] [2040/2639] eta: 0:29:19 lr: 1.8467981849509317e-05 loss: 0.0431 (0.0402) time: 2.8600 data: 0.0072 max mem: 33370 +Epoch: [26] [2050/2639] eta: 0:28:49 lr: 1.8463219946692725e-05 loss: 0.0399 (0.0402) time: 2.8639 data: 0.0077 max mem: 33370 +Epoch: [26] [2060/2639] eta: 0:28:19 lr: 1.845845790741042e-05 loss: 0.0359 (0.0402) time: 2.8562 data: 0.0074 max mem: 33370 +Epoch: [26] [2070/2639] eta: 0:27:50 lr: 1.845369573161937e-05 loss: 0.0359 (0.0403) time: 2.9067 data: 0.0070 max mem: 33370 +Epoch: [26] [2080/2639] eta: 0:27:21 lr: 1.8448933419276517e-05 loss: 0.0439 (0.0403) time: 2.9231 data: 0.0073 max mem: 33370 +Epoch: [26] [2090/2639] eta: 0:26:51 lr: 1.8444170970338783e-05 loss: 0.0414 (0.0403) time: 2.8966 data: 0.0074 max mem: 33370 +Epoch: [26] 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mem: 33370 +Epoch: [26] [2180/2639] eta: 0:22:26 lr: 1.8401302776007674e-05 loss: 0.0348 (0.0402) time: 2.8135 data: 0.0073 max mem: 33370 +Epoch: [26] [2190/2639] eta: 0:21:56 lr: 1.8396538958745785e-05 loss: 0.0367 (0.0403) time: 2.8265 data: 0.0074 max mem: 33370 +Epoch: [26] [2200/2639] eta: 0:21:27 lr: 1.839177500441337e-05 loss: 0.0362 (0.0402) time: 2.8728 data: 0.0072 max mem: 33370 +Epoch: [26] [2210/2639] eta: 0:20:57 lr: 1.8387010912967048e-05 loss: 0.0362 (0.0403) time: 2.8687 data: 0.0069 max mem: 33370 +Epoch: [26] [2220/2639] eta: 0:20:28 lr: 1.8382246684363384e-05 loss: 0.0397 (0.0403) time: 2.8502 data: 0.0070 max mem: 33370 +Epoch: [26] [2230/2639] eta: 0:19:58 lr: 1.837748231855894e-05 loss: 0.0405 (0.0403) time: 2.8941 data: 0.0071 max mem: 33370 +Epoch: [26] [2240/2639] eta: 0:19:29 lr: 1.837271781551023e-05 loss: 0.0357 (0.0403) time: 2.8953 data: 0.0072 max mem: 33370 +Epoch: [26] [2250/2639] eta: 0:19:00 lr: 1.8367953175173765e-05 loss: 0.0334 (0.0403) time: 2.8643 data: 0.0071 max mem: 33370 +Epoch: [26] [2260/2639] eta: 0:18:30 lr: 1.8363188397506e-05 loss: 0.0388 (0.0403) time: 2.8735 data: 0.0070 max mem: 33370 +Epoch: [26] [2270/2639] eta: 0:18:01 lr: 1.8358423482463404e-05 loss: 0.0425 (0.0403) time: 2.8621 data: 0.0070 max mem: 33370 +Epoch: [26] [2280/2639] eta: 0:17:31 lr: 1.8353658430002376e-05 loss: 0.0425 (0.0403) time: 2.8603 data: 0.0071 max mem: 33370 +Epoch: [26] [2290/2639] eta: 0:17:02 lr: 1.8348893240079326e-05 loss: 0.0337 (0.0403) time: 2.8938 data: 0.0072 max mem: 33370 +Epoch: [26] [2300/2639] eta: 0:16:33 lr: 1.8344127912650604e-05 loss: 0.0321 (0.0403) time: 2.8920 data: 0.0071 max mem: 33370 +Epoch: [26] [2310/2639] eta: 0:16:03 lr: 1.8339362447672564e-05 loss: 0.0350 (0.0403) time: 2.8732 data: 0.0075 max mem: 33370 +Epoch: [26] [2320/2639] eta: 0:15:34 lr: 1.8334596845101517e-05 loss: 0.0346 (0.0403) time: 2.8866 data: 0.0076 max mem: 33370 +Epoch: [26] [2330/2639] eta: 0:15:05 lr: 1.8329831104893748e-05 loss: 0.0346 (0.0403) time: 2.9098 data: 0.0073 max mem: 33370 +Epoch: [26] [2340/2639] eta: 0:14:35 lr: 1.8325065227005524e-05 loss: 0.0397 (0.0403) time: 2.9175 data: 0.0074 max mem: 33370 +Epoch: [26] [2350/2639] eta: 0:14:06 lr: 1.8320299211393066e-05 loss: 0.0375 (0.0403) time: 2.8716 data: 0.0078 max mem: 33370 +Epoch: [26] [2360/2639] eta: 0:13:37 lr: 1.83155330580126e-05 loss: 0.0364 (0.0403) time: 2.8324 data: 0.0075 max mem: 33370 +Epoch: [26] [2370/2639] eta: 0:13:07 lr: 1.831076676682029e-05 loss: 0.0376 (0.0403) time: 2.8262 data: 0.0071 max mem: 33370 +Epoch: [26] [2380/2639] eta: 0:12:38 lr: 1.83060003377723e-05 loss: 0.0384 (0.0403) time: 2.8296 data: 0.0073 max mem: 33370 +Epoch: [26] [2390/2639] eta: 0:12:08 lr: 1.8301233770824757e-05 loss: 0.0373 (0.0403) time: 2.8259 data: 0.0073 max mem: 33370 +Epoch: [26] [2400/2639] eta: 0:11:39 lr: 1.8296467065933766e-05 loss: 0.0366 (0.0404) time: 2.8505 data: 0.0072 max mem: 33370 +Epoch: [26] [2410/2639] eta: 0:11:10 lr: 1.8291700223055393e-05 loss: 0.0412 (0.0404) time: 2.8621 data: 0.0070 max mem: 33370 +Epoch: [26] [2420/2639] eta: 0:10:40 lr: 1.8286933242145693e-05 loss: 0.0327 (0.0404) time: 2.8631 data: 0.0072 max mem: 33370 +Epoch: [26] [2430/2639] eta: 0:10:11 lr: 1.828216612316068e-05 loss: 0.0316 (0.0404) time: 2.8865 data: 0.0077 max mem: 33370 +Epoch: [26] [2440/2639] eta: 0:09:42 lr: 1.8277398866056362e-05 loss: 0.0346 (0.0404) time: 2.8780 data: 0.0075 max mem: 33370 +Epoch: [26] [2450/2639] eta: 0:09:12 lr: 1.8272631470788688e-05 loss: 0.0336 (0.0403) time: 2.8837 data: 0.0071 max mem: 33370 +Epoch: [26] [2460/2639] eta: 0:08:43 lr: 1.826786393731362e-05 loss: 0.0303 (0.0403) time: 2.8687 data: 0.0071 max mem: 33370 +Epoch: [26] [2470/2639] eta: 0:08:14 lr: 1.826309626558705e-05 loss: 0.0326 (0.0403) time: 2.8252 data: 0.0072 max mem: 33370 +Epoch: [26] [2480/2639] eta: 0:07:45 lr: 1.825832845556488e-05 loss: 0.0332 (0.0404) time: 2.8318 data: 0.0074 max mem: 33370 +Epoch: [26] [2490/2639] eta: 0:07:15 lr: 1.8253560507202964e-05 loss: 0.0392 (0.0404) time: 2.8663 data: 0.0075 max mem: 33370 +Epoch: [26] [2500/2639] eta: 0:06:46 lr: 1.8248792420457145e-05 loss: 0.0392 (0.0404) time: 2.8659 data: 0.0074 max mem: 33370 +Epoch: [26] [2510/2639] eta: 0:06:17 lr: 1.8244024195283215e-05 loss: 0.0378 (0.0404) time: 2.8508 data: 0.0073 max mem: 33370 +Epoch: [26] [2520/2639] eta: 0:05:47 lr: 1.823925583163697e-05 loss: 0.0362 (0.0404) time: 2.8257 data: 0.0074 max mem: 33370 +Epoch: [26] [2530/2639] eta: 0:05:18 lr: 1.8234487329474143e-05 loss: 0.0368 (0.0404) time: 2.8397 data: 0.0076 max mem: 33370 +Epoch: [26] [2540/2639] eta: 0:04:49 lr: 1.822971868875047e-05 loss: 0.0354 (0.0404) time: 2.8863 data: 0.0076 max mem: 33370 +Epoch: [26] [2550/2639] eta: 0:04:20 lr: 1.8224949909421657e-05 loss: 0.0353 (0.0404) time: 2.9034 data: 0.0074 max mem: 33370 +Epoch: [26] [2560/2639] eta: 0:03:50 lr: 1.8220180991443365e-05 loss: 0.0365 (0.0404) time: 2.8745 data: 0.0073 max mem: 33370 +Epoch: [26] [2570/2639] eta: 0:03:21 lr: 1.8215411934771244e-05 loss: 0.0363 (0.0405) time: 2.8387 data: 0.0073 max mem: 33370 +Epoch: [26] [2580/2639] eta: 0:02:52 lr: 1.8210642739360904e-05 loss: 0.0363 (0.0405) time: 2.8259 data: 0.0075 max mem: 33370 +Epoch: [26] [2590/2639] eta: 0:02:23 lr: 1.8205873405167945e-05 loss: 0.0358 (0.0405) time: 2.8280 data: 0.0074 max mem: 33370 +Epoch: [26] [2600/2639] eta: 0:01:53 lr: 1.820110393214792e-05 loss: 0.0349 (0.0405) time: 2.8729 data: 0.0072 max mem: 33370 +Epoch: [26] [2610/2639] eta: 0:01:24 lr: 1.8196334320256375e-05 loss: 0.0364 (0.0405) time: 2.9042 data: 0.0071 max mem: 33370 +Epoch: [26] [2620/2639] eta: 0:00:55 lr: 1.8191564569448807e-05 loss: 0.0411 (0.0405) time: 2.8743 data: 0.0070 max mem: 33370 +Epoch: [26] [2630/2639] eta: 0:00:26 lr: 1.8186794679680715e-05 loss: 0.0411 (0.0405) time: 2.8946 data: 0.0069 max mem: 33370 +Epoch: [26] Total time: 2:08:30 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 4:46:02 time: 6.6703 data: 6.5887 max mem: 33370 +Test: [ 100/2573] eta: 0:05:48 time: 0.0753 data: 0.0013 max mem: 33370 +Test: [ 200/2573] eta: 0:04:27 time: 0.0820 data: 0.0054 max mem: 33370 +Test: [ 300/2573] eta: 0:03:48 time: 0.0796 data: 0.0014 max mem: 33370 +Test: [ 400/2573] eta: 0:03:26 time: 0.0796 data: 0.0013 max mem: 33370 +Test: [ 500/2573] eta: 0:03:09 time: 0.0782 data: 0.0014 max mem: 33370 +Test: [ 600/2573] eta: 0:02:56 time: 0.0778 data: 0.0013 max mem: 33370 +Test: [ 700/2573] eta: 0:02:45 time: 0.0793 data: 0.0014 max mem: 33370 +Test: [ 800/2573] eta: 0:02:34 time: 0.0821 data: 0.0014 max mem: 33370 +Test: [ 900/2573] eta: 0:02:24 time: 0.0798 data: 0.0014 max mem: 33370 +Test: [1000/2573] eta: 0:02:14 time: 0.0789 data: 0.0014 max mem: 33370 +Test: [1100/2573] eta: 0:02:05 time: 0.0799 data: 0.0015 max mem: 33370 +Test: [1200/2573] eta: 0:01:56 time: 0.0786 data: 0.0014 max mem: 33370 +Test: [1300/2573] eta: 0:01:47 time: 0.0786 data: 0.0014 max mem: 33370 +Test: [1400/2573] eta: 0:01:38 time: 0.0771 data: 0.0013 max mem: 33370 +Test: [1500/2573] eta: 0:01:29 time: 0.0787 data: 0.0014 max mem: 33370 +Test: [1600/2573] eta: 0:01:20 time: 0.0814 data: 0.0014 max mem: 33370 +Test: [1700/2573] eta: 0:01:12 time: 0.0770 data: 0.0013 max mem: 33370 +Test: [1800/2573] eta: 0:01:03 time: 0.0802 data: 0.0014 max mem: 33370 +Test: [1900/2573] eta: 0:00:55 time: 0.0774 data: 0.0013 max mem: 33370 +Test: [2000/2573] eta: 0:00:47 time: 0.0788 data: 0.0014 max mem: 33370 +Test: [2100/2573] eta: 0:00:38 time: 0.0807 data: 0.0014 max mem: 33370 +Test: [2200/2573] eta: 0:00:30 time: 0.0810 data: 0.0014 max mem: 33370 +Test: [2300/2573] eta: 0:00:22 time: 0.0808 data: 0.0013 max mem: 33370 +Test: [2400/2573] eta: 0:00:14 time: 0.0756 data: 0.0013 max mem: 33370 +Test: [2500/2573] eta: 0:00:05 time: 0.0788 data: 0.0013 max mem: 33370 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: Total time: 0:03:30 +Final results: +Mean IoU is 64.01 + + precision@0.5 = 72.02 + precision@0.6 = 66.44 + precision@0.7 = 59.40 + precision@0.8 = 47.81 + precision@0.9 = 24.45 + overall IoU = 61.28 + +Average object IoU 64.00589738678268 +Overall IoU 61.28402328491211 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [27] [ 0/2639] eta: 4:08:58 lr: 1.818250166004135e-05 loss: 0.0400 (0.0400) time: 5.6608 data: 2.5600 max mem: 33370 +Epoch: [27] [ 10/2639] eta: 2:17:04 lr: 1.8177731506125488e-05 loss: 0.0426 (0.0398) time: 3.1284 data: 0.2398 max mem: 33370 +Epoch: [27] [ 20/2639] eta: 2:11:51 lr: 1.8172961213119836e-05 loss: 0.0375 (0.0379) time: 2.8887 data: 0.0076 max mem: 33370 +Epoch: [27] [ 30/2639] eta: 2:08:53 lr: 1.8168190780979762e-05 loss: 0.0359 (0.0386) time: 2.8736 data: 0.0077 max mem: 33370 +Epoch: [27] [ 40/2639] eta: 2:07:44 lr: 1.8163420209660625e-05 loss: 0.0404 (0.0389) time: 2.8737 data: 0.0076 max mem: 33370 +Epoch: [27] [ 50/2639] eta: 2:06:38 lr: 1.8158649499117732e-05 loss: 0.0360 (0.0380) time: 2.8902 data: 0.0073 max mem: 33370 +Epoch: [27] [ 60/2639] eta: 2:05:44 lr: 1.8153878649306386e-05 loss: 0.0350 (0.0381) time: 2.8766 data: 0.0074 max mem: 33370 +Epoch: [27] [ 70/2639] eta: 2:04:51 lr: 1.8149107660181848e-05 loss: 0.0360 (0.0385) time: 2.8672 data: 0.0076 max mem: 33370 +Epoch: [27] [ 80/2639] eta: 2:03:49 lr: 1.8144336531699356e-05 loss: 0.0421 (0.0388) time: 2.8360 data: 0.0074 max mem: 33370 +Epoch: [27] [ 90/2639] eta: 2:03:06 lr: 1.813956526381412e-05 loss: 0.0441 (0.0394) time: 2.8329 data: 0.0076 max mem: 33370 +Epoch: [27] [ 100/2639] eta: 2:02:31 lr: 1.8134793856481334e-05 loss: 0.0436 (0.0400) time: 2.8636 data: 0.0079 max mem: 33370 +Epoch: [27] [ 110/2639] eta: 2:01:50 lr: 1.8130022309656134e-05 loss: 0.0408 (0.0400) time: 2.8588 data: 0.0077 max mem: 33370 +Epoch: [27] [ 120/2639] eta: 2:01:10 lr: 1.8125250623293667e-05 loss: 0.0390 (0.0400) time: 2.8414 data: 0.0076 max mem: 33370 +Epoch: [27] [ 130/2639] eta: 2:00:43 lr: 1.8120478797349017e-05 loss: 0.0368 (0.0397) time: 2.8658 data: 0.0078 max mem: 33370 +Epoch: [27] [ 140/2639] eta: 2:00:11 lr: 1.8115706831777274e-05 loss: 0.0340 (0.0394) time: 2.8824 data: 0.0077 max mem: 33370 +Epoch: [27] [ 150/2639] eta: 1:59:44 lr: 1.8110934726533467e-05 loss: 0.0343 (0.0390) time: 2.8849 data: 0.0076 max mem: 33370 +Epoch: [27] [ 160/2639] eta: 1:59:17 lr: 1.810616248157263e-05 loss: 0.0345 (0.0398) time: 2.8956 data: 0.0076 max mem: 33370 +Epoch: [27] [ 170/2639] eta: 1:58:53 lr: 1.8101390096849732e-05 loss: 0.0397 (0.0398) time: 2.9075 data: 0.0074 max mem: 33370 +Epoch: [27] [ 180/2639] eta: 1:58:20 lr: 1.8096617572319754e-05 loss: 0.0376 (0.0399) time: 2.8914 data: 0.0073 max mem: 33370 +Epoch: [27] [ 190/2639] eta: 1:57:46 lr: 1.8091844907937627e-05 loss: 0.0376 (0.0406) time: 2.8557 data: 0.0072 max mem: 33370 +Epoch: [27] [ 200/2639] eta: 1:57:19 lr: 1.808707210365825e-05 loss: 0.0397 (0.0408) time: 2.8752 data: 0.0074 max mem: 33370 +Epoch: [27] [ 210/2639] eta: 1:56:47 lr: 1.8082299159436512e-05 loss: 0.0413 (0.0408) time: 2.8783 data: 0.0073 max mem: 33370 +Epoch: [27] [ 220/2639] eta: 1:56:18 lr: 1.8077526075227258e-05 loss: 0.0374 (0.0406) time: 2.8691 data: 0.0071 max mem: 33370 +Epoch: [27] [ 230/2639] eta: 1:55:48 lr: 1.8072752850985318e-05 loss: 0.0326 (0.0405) time: 2.8781 data: 0.0075 max mem: 33370 +Epoch: [27] [ 240/2639] eta: 1:55:13 lr: 1.8067979486665473e-05 loss: 0.0326 (0.0402) time: 2.8469 data: 0.0075 max mem: 33370 +Epoch: [27] [ 250/2639] eta: 1:54:41 lr: 1.806320598222251e-05 loss: 0.0328 (0.0399) time: 2.8348 data: 0.0073 max mem: 33370 +Epoch: [27] [ 260/2639] eta: 1:54:12 lr: 1.8058432337611152e-05 loss: 0.0351 (0.0398) time: 2.8640 data: 0.0073 max mem: 33370 +Epoch: [27] [ 270/2639] eta: 1:53:45 lr: 1.8053658552786127e-05 loss: 0.0365 (0.0400) time: 2.8924 data: 0.0076 max mem: 33370 +Epoch: [27] [ 280/2639] eta: 1:53:19 lr: 1.8048884627702103e-05 loss: 0.0336 (0.0399) time: 2.9083 data: 0.0075 max mem: 33370 +Epoch: [27] [ 290/2639] eta: 1:52:54 lr: 1.804411056231375e-05 loss: 0.0353 (0.0399) time: 2.9185 data: 0.0073 max mem: 33370 +Epoch: [27] [ 300/2639] eta: 1:52:21 lr: 1.8039336356575684e-05 loss: 0.0352 (0.0397) time: 2.8800 data: 0.0073 max mem: 33370 +Epoch: [27] [ 310/2639] eta: 1:51:55 lr: 1.8034562010442518e-05 loss: 0.0326 (0.0397) time: 2.8800 data: 0.0070 max mem: 33370 +Epoch: [27] [ 320/2639] eta: 1:51:27 lr: 1.802978752386881e-05 loss: 0.0347 (0.0397) time: 2.9061 data: 0.0069 max mem: 33370 +Epoch: [27] [ 330/2639] eta: 1:50:59 lr: 1.8025012896809117e-05 loss: 0.0306 (0.0394) time: 2.8901 data: 0.0074 max mem: 33370 +Epoch: [27] [ 340/2639] eta: 1:50:25 lr: 1.8020238129217944e-05 loss: 0.0285 (0.0394) time: 2.8516 data: 0.0076 max mem: 33370 +Epoch: [27] [ 350/2639] eta: 1:49:54 lr: 1.8015463221049788e-05 loss: 0.0338 (0.0393) time: 2.8337 data: 0.0077 max mem: 33370 +Epoch: [27] [ 360/2639] eta: 1:49:22 lr: 1.80106881722591e-05 loss: 0.0351 (0.0393) time: 2.8390 data: 0.0077 max mem: 33370 +Epoch: [27] [ 370/2639] eta: 1:48:49 lr: 1.8005912982800317e-05 loss: 0.0380 (0.0396) time: 2.8203 data: 0.0074 max mem: 33370 +Epoch: [27] [ 380/2639] eta: 1:48:23 lr: 1.800113765262784e-05 loss: 0.0359 (0.0394) time: 2.8741 data: 0.0073 max mem: 33370 +Epoch: [27] [ 390/2639] eta: 1:47:56 lr: 1.7996362181696054e-05 loss: 0.0365 (0.0395) time: 2.9144 data: 0.0073 max mem: 33370 +Epoch: [27] [ 400/2639] eta: 1:47:25 lr: 1.7991586569959286e-05 loss: 0.0398 (0.0394) time: 2.8763 data: 0.0074 max mem: 33370 +Epoch: [27] [ 410/2639] eta: 1:46:57 lr: 1.798681081737187e-05 loss: 0.0342 (0.0393) time: 2.8689 data: 0.0076 max mem: 33370 +Epoch: [27] [ 420/2639] eta: 1:46:26 lr: 1.7982034923888087e-05 loss: 0.0392 (0.0395) time: 2.8606 data: 0.0075 max mem: 33370 +Epoch: [27] [ 430/2639] eta: 1:45:58 lr: 1.7977258889462203e-05 loss: 0.0349 (0.0393) time: 2.8592 data: 0.0078 max mem: 33370 +Epoch: [27] [ 440/2639] eta: 1:45:27 lr: 1.7972482714048458e-05 loss: 0.0336 (0.0394) time: 2.8675 data: 0.0077 max mem: 33370 +Epoch: [27] [ 450/2639] eta: 1:44:57 lr: 1.7967706397601044e-05 loss: 0.0396 (0.0394) time: 2.8494 data: 0.0075 max mem: 33370 +Epoch: [27] [ 460/2639] eta: 1:44:25 lr: 1.7962929940074153e-05 loss: 0.0341 (0.0393) time: 2.8231 data: 0.0075 max mem: 33370 +Epoch: [27] [ 470/2639] eta: 1:43:54 lr: 1.7958153341421917e-05 loss: 0.0335 (0.0394) time: 2.8163 data: 0.0076 max mem: 33370 +Epoch: [27] [ 480/2639] eta: 1:43:27 lr: 1.7953376601598467e-05 loss: 0.0326 (0.0394) time: 2.8705 data: 0.0074 max mem: 33370 +Epoch: [27] [ 490/2639] eta: 1:42:56 lr: 1.794859972055789e-05 loss: 0.0326 (0.0394) time: 2.8630 data: 0.0074 max mem: 33370 +Epoch: [27] [ 500/2639] eta: 1:42:27 lr: 1.7943822698254252e-05 loss: 0.0448 (0.0397) time: 2.8437 data: 0.0074 max mem: 33370 +Epoch: [27] [ 510/2639] eta: 1:41:58 lr: 1.7939045534641584e-05 loss: 0.0448 (0.0398) time: 2.8717 data: 0.0074 max mem: 33370 +Epoch: [27] [ 520/2639] eta: 1:41:26 lr: 1.7934268229673893e-05 loss: 0.0432 (0.0399) time: 2.8332 data: 0.0076 max mem: 33370 +Epoch: [27] [ 530/2639] eta: 1:40:54 lr: 1.7929490783305154e-05 loss: 0.0401 (0.0399) time: 2.7995 data: 0.0076 max mem: 33370 +Epoch: [27] [ 540/2639] eta: 1:40:24 lr: 1.792471319548932e-05 loss: 0.0351 (0.0398) time: 2.8124 data: 0.0074 max mem: 33370 +Epoch: [27] [ 550/2639] eta: 1:39:52 lr: 1.7919935466180304e-05 loss: 0.0321 (0.0398) time: 2.8046 data: 0.0072 max mem: 33370 +Epoch: [27] [ 560/2639] eta: 1:39:24 lr: 1.7915157595332008e-05 loss: 0.0368 (0.0400) time: 2.8376 data: 0.0071 max mem: 33370 +Epoch: [27] [ 570/2639] eta: 1:38:56 lr: 1.7910379582898286e-05 loss: 0.0368 (0.0400) time: 2.8833 data: 0.0072 max mem: 33370 +Epoch: [27] [ 580/2639] eta: 1:38:28 lr: 1.7905601428832974e-05 loss: 0.0345 (0.0400) time: 2.8888 data: 0.0072 max mem: 33370 +Epoch: [27] [ 590/2639] eta: 1:37:58 lr: 1.790082313308987e-05 loss: 0.0344 (0.0399) time: 2.8659 data: 0.0074 max mem: 33370 +Epoch: [27] [ 600/2639] eta: 1:37:31 lr: 1.789604469562277e-05 loss: 0.0368 (0.0399) time: 2.8701 data: 0.0075 max mem: 33370 +Epoch: [27] [ 610/2639] eta: 1:37:03 lr: 1.7891266116385396e-05 loss: 0.0336 (0.0399) time: 2.9036 data: 0.0072 max mem: 33370 +Epoch: [27] [ 620/2639] eta: 1:36:35 lr: 1.788648739533149e-05 loss: 0.0325 (0.0398) time: 2.8997 data: 0.0073 max mem: 33370 +Epoch: [27] [ 630/2639] eta: 1:36:07 lr: 1.7881708532414723e-05 loss: 0.0324 (0.0398) time: 2.8843 data: 0.0073 max mem: 33370 +Epoch: [27] [ 640/2639] eta: 1:35:39 lr: 1.787692952758877e-05 loss: 0.0378 (0.0398) time: 2.8942 data: 0.0072 max mem: 33370 +Epoch: [27] [ 650/2639] eta: 1:35:13 lr: 1.7872150380807254e-05 loss: 0.0314 (0.0397) time: 2.9332 data: 0.0073 max mem: 33370 +Epoch: [27] [ 660/2639] eta: 1:34:44 lr: 1.7867371092023786e-05 loss: 0.0314 (0.0398) time: 2.9122 data: 0.0072 max mem: 33370 +Epoch: [27] [ 670/2639] eta: 1:34:18 lr: 1.7862591661191926e-05 loss: 0.0382 (0.0397) time: 2.9143 data: 0.0070 max mem: 33370 +Epoch: [27] [ 680/2639] eta: 1:33:50 lr: 1.7857812088265234e-05 loss: 0.0382 (0.0399) time: 2.9288 data: 0.0070 max mem: 33370 +Epoch: [27] [ 690/2639] eta: 1:33:21 lr: 1.7853032373197222e-05 loss: 0.0402 (0.0400) time: 2.8888 data: 0.0072 max mem: 33370 +Epoch: [27] [ 700/2639] eta: 1:32:53 lr: 1.784825251594137e-05 loss: 0.0317 (0.0399) time: 2.8811 data: 0.0072 max mem: 33370 +Epoch: [27] [ 710/2639] eta: 1:32:26 lr: 1.7843472516451153e-05 loss: 0.0347 (0.0400) time: 2.9089 data: 0.0074 max mem: 33370 +Epoch: [27] [ 720/2639] eta: 1:31:55 lr: 1.7838692374679977e-05 loss: 0.0367 (0.0399) time: 2.8718 data: 0.0077 max mem: 33370 +Epoch: [27] [ 730/2639] eta: 1:31:25 lr: 1.783391209058126e-05 loss: 0.0383 (0.0400) time: 2.8184 data: 0.0076 max mem: 33370 +Epoch: [27] [ 740/2639] eta: 1:30:55 lr: 1.7829131664108366e-05 loss: 0.0383 (0.0399) time: 2.8284 data: 0.0079 max mem: 33370 +Epoch: [27] [ 750/2639] eta: 1:30:27 lr: 1.7824351095214636e-05 loss: 0.0386 (0.0400) time: 2.8521 data: 0.0078 max mem: 33370 +Epoch: [27] [ 760/2639] eta: 1:29:56 lr: 1.781957038385338e-05 loss: 0.0399 (0.0399) time: 2.8317 data: 0.0076 max mem: 33370 +Epoch: [27] [ 770/2639] eta: 1:29:27 lr: 1.781478952997789e-05 loss: 0.0398 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1.7776537562845607e-05 loss: 0.0351 (0.0401) time: 2.8918 data: 0.0074 max mem: 33370 +Epoch: [27] [ 860/2639] eta: 1:25:07 lr: 1.7771755424234854e-05 loss: 0.0404 (0.0401) time: 2.8613 data: 0.0075 max mem: 33370 +Epoch: [27] [ 870/2639] eta: 1:24:39 lr: 1.7766973142641084e-05 loss: 0.0404 (0.0402) time: 2.8861 data: 0.0076 max mem: 33370 +Epoch: [27] [ 880/2639] eta: 1:24:11 lr: 1.7762190718017246e-05 loss: 0.0362 (0.0401) time: 2.8930 data: 0.0076 max mem: 33370 +Epoch: [27] [ 890/2639] eta: 1:23:42 lr: 1.775740815031628e-05 loss: 0.0361 (0.0401) time: 2.8793 data: 0.0075 max mem: 33370 +Epoch: [27] [ 900/2639] eta: 1:23:14 lr: 1.7752625439491076e-05 loss: 0.0293 (0.0400) time: 2.8831 data: 0.0074 max mem: 33370 +Epoch: [27] [ 910/2639] eta: 1:22:44 lr: 1.7747842585494518e-05 loss: 0.0287 (0.0400) time: 2.8631 data: 0.0073 max mem: 33370 +Epoch: [27] [ 920/2639] eta: 1:22:13 lr: 1.7743059588279433e-05 loss: 0.0392 (0.0400) time: 2.7924 data: 0.0074 max mem: 33370 +Epoch: [27] [ 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33370 +Epoch: [27] [1010/2639] eta: 1:17:52 lr: 1.7700006160714445e-05 loss: 0.0410 (0.0399) time: 2.9061 data: 0.0078 max mem: 33370 +Epoch: [27] [1020/2639] eta: 1:17:23 lr: 1.7695221728713907e-05 loss: 0.0385 (0.0400) time: 2.8721 data: 0.0075 max mem: 33370 +Epoch: [27] [1030/2639] eta: 1:16:55 lr: 1.7690437152974134e-05 loss: 0.0377 (0.0399) time: 2.8670 data: 0.0075 max mem: 33370 +Epoch: [27] [1040/2639] eta: 1:16:27 lr: 1.7685652433447624e-05 loss: 0.0340 (0.0399) time: 2.8908 data: 0.0076 max mem: 33370 +Epoch: [27] [1050/2639] eta: 1:15:59 lr: 1.768086757008682e-05 loss: 0.0324 (0.0399) time: 2.9347 data: 0.0074 max mem: 33370 +Epoch: [27] [1060/2639] eta: 1:15:30 lr: 1.767608256284415e-05 loss: 0.0324 (0.0398) time: 2.9017 data: 0.0072 max mem: 33370 +Epoch: [27] [1070/2639] eta: 1:15:02 lr: 1.7671297411672005e-05 loss: 0.0368 (0.0398) time: 2.8618 data: 0.0072 max mem: 33370 +Epoch: [27] [1080/2639] eta: 1:14:33 lr: 1.7666512116522755e-05 loss: 0.0398 (0.0400) time: 2.8879 data: 0.0072 max mem: 33370 +Epoch: [27] [1090/2639] eta: 1:14:05 lr: 1.766172667734872e-05 loss: 0.0377 (0.0399) time: 2.8805 data: 0.0072 max mem: 33370 +Epoch: [27] [1100/2639] eta: 1:13:36 lr: 1.7656941094102215e-05 loss: 0.0329 (0.0399) time: 2.8642 data: 0.0074 max mem: 33370 +Epoch: [27] [1110/2639] eta: 1:13:06 lr: 1.765215536673551e-05 loss: 0.0313 (0.0399) time: 2.8387 data: 0.0074 max mem: 33370 +Epoch: [27] [1120/2639] eta: 1:12:37 lr: 1.7647369495200847e-05 loss: 0.0347 (0.0399) time: 2.8077 data: 0.0073 max mem: 33370 +Epoch: [27] [1130/2639] eta: 1:12:08 lr: 1.7642583479450436e-05 loss: 0.0397 (0.0399) time: 2.8206 data: 0.0073 max mem: 33370 +Epoch: [27] [1140/2639] eta: 1:11:39 lr: 1.7637797319436468e-05 loss: 0.0398 (0.0399) time: 2.8431 data: 0.0073 max mem: 33370 +Epoch: [27] [1150/2639] eta: 1:11:11 lr: 1.7633011015111084e-05 loss: 0.0350 (0.0398) time: 2.8780 data: 0.0073 max mem: 33370 +Epoch: [27] [1160/2639] eta: 1:10:42 lr: 1.762822456642641e-05 loss: 0.0338 (0.0398) time: 2.8921 data: 0.0073 max mem: 33370 +Epoch: [27] [1170/2639] eta: 1:10:13 lr: 1.7623437973334544e-05 loss: 0.0348 (0.0399) time: 2.8404 data: 0.0072 max mem: 33370 +Epoch: [27] [1180/2639] eta: 1:09:44 lr: 1.7618651235787535e-05 loss: 0.0422 (0.0399) time: 2.8260 data: 0.0074 max mem: 33370 +Epoch: [27] [1190/2639] eta: 1:09:15 lr: 1.761386435373743e-05 loss: 0.0309 (0.0398) time: 2.8665 data: 0.0076 max mem: 33370 +Epoch: [27] [1200/2639] eta: 1:08:46 lr: 1.760907732713621e-05 loss: 0.0334 (0.0398) time: 2.8630 data: 0.0073 max mem: 33370 +Epoch: [27] [1210/2639] eta: 1:08:17 lr: 1.760429015593586e-05 loss: 0.0368 (0.0399) time: 2.8530 data: 0.0073 max mem: 33370 +Epoch: [27] [1220/2639] eta: 1:07:49 lr: 1.7599502840088312e-05 loss: 0.0436 (0.0402) time: 2.8818 data: 0.0076 max mem: 33370 +Epoch: [27] [1230/2639] eta: 1:07:21 lr: 1.7594715379545483e-05 loss: 0.0444 (0.0402) time: 2.9190 data: 0.0075 max mem: 33370 +Epoch: [27] [1240/2639] eta: 1:06:53 lr: 1.7589927774259237e-05 loss: 0.0369 (0.0402) time: 2.9060 data: 0.0074 max mem: 33370 +Epoch: [27] [1250/2639] eta: 1:06:23 lr: 1.7585140024181437e-05 loss: 0.0369 (0.0402) time: 2.8397 data: 0.0077 max mem: 33370 +Epoch: [27] [1260/2639] eta: 1:05:54 lr: 1.7580352129263886e-05 loss: 0.0372 (0.0402) time: 2.8293 data: 0.0077 max mem: 33370 +Epoch: [27] [1270/2639] eta: 1:05:25 lr: 1.7575564089458385e-05 loss: 0.0390 (0.0402) time: 2.8407 data: 0.0074 max mem: 33370 +Epoch: [27] [1280/2639] eta: 1:04:57 lr: 1.7570775904716673e-05 loss: 0.0374 (0.0402) time: 2.8690 data: 0.0074 max mem: 33370 +Epoch: [27] [1290/2639] eta: 1:04:29 lr: 1.7565987574990493e-05 loss: 0.0407 (0.0403) time: 2.9120 data: 0.0073 max mem: 33370 +Epoch: [27] [1300/2639] eta: 1:04:00 lr: 1.7561199100231527e-05 loss: 0.0366 (0.0403) time: 2.8799 data: 0.0073 max mem: 33370 +Epoch: [27] [1310/2639] eta: 1:03:31 lr: 1.755641048039145e-05 loss: 0.0304 (0.0403) time: 2.8187 data: 0.0075 max mem: 33370 +Epoch: [27] [1320/2639] eta: 1:03:02 lr: 1.755162171542188e-05 loss: 0.0354 (0.0403) time: 2.8343 data: 0.0074 max mem: 33370 +Epoch: [27] [1330/2639] eta: 1:02:33 lr: 1.7546832805274433e-05 loss: 0.0351 (0.0403) time: 2.8625 data: 0.0074 max mem: 33370 +Epoch: [27] [1340/2639] eta: 1:02:05 lr: 1.754204374990067e-05 loss: 0.0378 (0.0403) time: 2.8862 data: 0.0075 max mem: 33370 +Epoch: [27] [1350/2639] eta: 1:01:36 lr: 1.753725454925214e-05 loss: 0.0428 (0.0403) time: 2.8996 data: 0.0074 max mem: 33370 +Epoch: [27] [1360/2639] eta: 1:01:08 lr: 1.7532465203280345e-05 loss: 0.0379 (0.0404) time: 2.8846 data: 0.0074 max mem: 33370 +Epoch: [27] [1370/2639] eta: 1:00:40 lr: 1.7527675711936772e-05 loss: 0.0332 (0.0403) time: 2.9130 data: 0.0073 max mem: 33370 +Epoch: [27] [1380/2639] eta: 1:00:11 lr: 1.7522886075172862e-05 loss: 0.0359 (0.0404) time: 2.8888 data: 0.0073 max mem: 33370 +Epoch: [27] [1390/2639] eta: 0:59:42 lr: 1.751809629294004e-05 loss: 0.0369 (0.0404) time: 2.8331 data: 0.0076 max mem: 33370 +Epoch: [27] [1400/2639] eta: 0:59:13 lr: 1.7513306365189677e-05 loss: 0.0320 (0.0403) time: 2.8362 data: 0.0076 max mem: 33370 +Epoch: [27] [1410/2639] eta: 0:58:44 lr: 1.750851629187314e-05 loss: 0.0320 (0.0403) time: 2.8484 data: 0.0075 max mem: 33370 +Epoch: [27] [1420/2639] eta: 0:58:15 lr: 1.7503726072941755e-05 loss: 0.0387 (0.0403) time: 2.8515 data: 0.0074 max mem: 33370 +Epoch: [27] [1430/2639] eta: 0:57:47 lr: 1.7498935708346805e-05 loss: 0.0393 (0.0403) time: 2.8869 data: 0.0074 max mem: 33370 +Epoch: [27] [1440/2639] eta: 0:57:18 lr: 1.7494145198039565e-05 loss: 0.0378 (0.0403) time: 2.8941 data: 0.0075 max mem: 33370 +Epoch: [27] [1450/2639] eta: 0:56:50 lr: 1.7489354541971246e-05 loss: 0.0333 (0.0403) time: 2.8959 data: 0.0076 max mem: 33370 +Epoch: [27] [1460/2639] eta: 0:56:22 lr: 1.7484563740093067e-05 loss: 0.0309 (0.0402) time: 2.9265 data: 0.0077 max mem: 33370 +Epoch: [27] [1470/2639] eta: 0:55:53 lr: 1.747977279235618e-05 loss: 0.0363 (0.0402) time: 2.9123 data: 0.0076 max mem: 33370 +Epoch: [27] [1480/2639] eta: 0:55:25 lr: 1.7474981698711735e-05 loss: 0.0360 (0.0402) time: 2.8892 data: 0.0074 max mem: 33370 +Epoch: [27] [1490/2639] eta: 0:54:56 lr: 1.7470190459110824e-05 loss: 0.0349 (0.0402) time: 2.8675 data: 0.0074 max mem: 33370 +Epoch: [27] [1500/2639] eta: 0:54:27 lr: 1.7465399073504538e-05 loss: 0.0372 (0.0402) time: 2.8235 data: 0.0073 max mem: 33370 +Epoch: [27] [1510/2639] eta: 0:53:58 lr: 1.7460607541843903e-05 loss: 0.0386 (0.0402) time: 2.8109 data: 0.0073 max mem: 33370 +Epoch: [27] [1520/2639] eta: 0:53:29 lr: 1.7455815864079947e-05 loss: 0.0325 (0.0402) time: 2.8562 data: 0.0073 max mem: 33370 +Epoch: [27] [1530/2639] eta: 0:53:00 lr: 1.7451024040163634e-05 loss: 0.0345 (0.0401) time: 2.8407 data: 0.0072 max mem: 33370 +Epoch: [27] [1540/2639] eta: 0:52:32 lr: 1.7446232070045928e-05 loss: 0.0329 (0.0401) time: 2.8430 data: 0.0074 max mem: 33370 +Epoch: [27] [1550/2639] eta: 0:52:03 lr: 1.744143995367773e-05 loss: 0.0357 (0.0401) time: 2.8666 data: 0.0076 max mem: 33370 +Epoch: [27] [1560/2639] eta: 0:51:34 lr: 1.7436647691009946e-05 loss: 0.0379 (0.0401) time: 2.8713 data: 0.0077 max mem: 33370 +Epoch: [27] [1570/2639] eta: 0:51:05 lr: 1.743185528199341e-05 loss: 0.0372 (0.0401) time: 2.8720 data: 0.0075 max mem: 33370 +Epoch: [27] [1580/2639] eta: 0:50:37 lr: 1.7427062726578964e-05 loss: 0.0299 (0.0401) time: 2.8556 data: 0.0074 max mem: 33370 +Epoch: [27] [1590/2639] eta: 0:50:08 lr: 1.742227002471738e-05 loss: 0.0306 (0.0400) time: 2.8595 data: 0.0074 max mem: 33370 +Epoch: [27] [1600/2639] eta: 0:49:39 lr: 1.7417477176359437e-05 loss: 0.0344 (0.0400) time: 2.8768 data: 0.0072 max mem: 33370 +Epoch: [27] [1610/2639] eta: 0:49:10 lr: 1.7412684181455843e-05 loss: 0.0375 (0.0400) time: 2.8567 data: 0.0075 max mem: 33370 +Epoch: [27] [1620/2639] eta: 0:48:42 lr: 1.7407891039957318e-05 loss: 0.0367 (0.0400) time: 2.8663 data: 0.0075 max mem: 33370 +Epoch: [27] [1630/2639] eta: 0:48:13 lr: 1.7403097751814502e-05 loss: 0.0357 (0.0400) time: 2.8952 data: 0.0070 max mem: 33370 +Epoch: [27] [1640/2639] eta: 0:47:45 lr: 1.739830431697805e-05 loss: 0.0357 (0.0400) time: 2.8680 data: 0.0068 max mem: 33370 +Epoch: [27] [1650/2639] eta: 0:47:20 lr: 1.7393510735398544e-05 loss: 0.0376 (0.0400) time: 3.1682 data: 0.3196 max mem: 33370 +Epoch: [27] [1660/2639] eta: 0:47:04 lr: 1.7388717007026567e-05 loss: 0.0391 (0.0400) time: 4.3114 data: 1.4463 max mem: 33370 +Epoch: [27] [1670/2639] eta: 0:46:35 lr: 1.7383923131812656e-05 loss: 0.0419 (0.0401) time: 3.9941 data: 1.1338 max mem: 33370 +Epoch: [27] [1680/2639] eta: 0:46:06 lr: 1.737912910970731e-05 loss: 0.0407 (0.0401) time: 2.8512 data: 0.0071 max mem: 33370 +Epoch: [27] [1690/2639] eta: 0:45:37 lr: 1.7374334940661012e-05 loss: 0.0349 (0.0400) time: 2.8360 data: 0.0070 max mem: 33370 +Epoch: [27] [1700/2639] eta: 0:45:08 lr: 1.73695406246242e-05 loss: 0.0366 (0.0401) time: 2.8222 data: 0.0075 max mem: 33370 +Epoch: [27] [1710/2639] eta: 0:44:39 lr: 1.736474616154728e-05 loss: 0.0379 (0.0401) time: 2.8458 data: 0.0077 max mem: 33370 +Epoch: [27] [1720/2639] eta: 0:44:10 lr: 1.7359951551380636e-05 loss: 0.0348 (0.0400) time: 2.8547 data: 0.0076 max mem: 33370 +Epoch: [27] [1730/2639] eta: 0:43:41 lr: 1.7355156794074613e-05 loss: 0.0347 (0.0400) time: 2.8458 data: 0.0074 max mem: 33370 +Epoch: [27] [1740/2639] eta: 0:43:12 lr: 1.7350361889579523e-05 loss: 0.0365 (0.0400) time: 2.8451 data: 0.0076 max mem: 33370 +Epoch: [27] [1750/2639] eta: 0:42:43 lr: 1.7345566837845654e-05 loss: 0.0365 (0.0400) time: 2.8657 data: 0.0074 max mem: 33370 +Epoch: [27] [1760/2639] eta: 0:42:14 lr: 1.7340771638823246e-05 loss: 0.0321 (0.0400) time: 2.9041 data: 0.0069 max mem: 33370 +Epoch: [27] [1770/2639] eta: 0:41:45 lr: 1.7335976292462532e-05 loss: 0.0312 (0.0400) time: 2.8965 data: 0.0072 max mem: 33370 +Epoch: [27] [1780/2639] eta: 0:41:16 lr: 1.7331180798713685e-05 loss: 0.0349 (0.0400) time: 2.8615 data: 0.0074 max mem: 33370 +Epoch: [27] [1790/2639] eta: 0:40:47 lr: 1.7326385157526867e-05 loss: 0.0368 (0.0401) time: 2.8553 data: 0.0074 max mem: 33370 +Epoch: [27] [1800/2639] eta: 0:40:18 lr: 1.7321589368852193e-05 loss: 0.0385 (0.0400) time: 2.8545 data: 0.0072 max mem: 33370 +Epoch: [27] [1810/2639] eta: 0:39:49 lr: 1.731679343263976e-05 loss: 0.0331 (0.0400) time: 2.8426 data: 0.0070 max mem: 33370 +Epoch: [27] [1820/2639] eta: 0:39:21 lr: 1.7311997348839618e-05 loss: 0.0298 (0.0400) time: 2.8973 data: 0.0071 max mem: 33370 +Epoch: [27] [1830/2639] eta: 0:38:52 lr: 1.7307201117401797e-05 loss: 0.0325 (0.0400) time: 2.9300 data: 0.0074 max mem: 33370 +Epoch: [27] [1840/2639] eta: 0:38:23 lr: 1.730240473827629e-05 loss: 0.0350 (0.0399) time: 2.8756 data: 0.0077 max mem: 33370 +Epoch: [27] [1850/2639] eta: 0:37:54 lr: 1.729760821141305e-05 loss: 0.0350 (0.0399) time: 2.8862 data: 0.0076 max mem: 33370 +Epoch: [27] [1860/2639] eta: 0:37:26 lr: 1.729281153676201e-05 loss: 0.0346 (0.0399) time: 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0.0342 (0.0398) time: 2.8588 data: 0.0072 max mem: 33370 +Epoch: [27] [1950/2639] eta: 0:33:05 lr: 1.7249634806173706e-05 loss: 0.0294 (0.0398) time: 2.8610 data: 0.0069 max mem: 33370 +Epoch: [27] [1960/2639] eta: 0:32:36 lr: 1.7244836650883562e-05 loss: 0.0332 (0.0398) time: 2.8799 data: 0.0069 max mem: 33370 +Epoch: [27] [1970/2639] eta: 0:32:07 lr: 1.724003834725267e-05 loss: 0.0302 (0.0397) time: 2.9011 data: 0.0073 max mem: 33370 +Epoch: [27] [1980/2639] eta: 0:31:38 lr: 1.7235239895230583e-05 loss: 0.0264 (0.0397) time: 2.8701 data: 0.0070 max mem: 33370 +Epoch: [27] [1990/2639] eta: 0:31:10 lr: 1.7230441294766794e-05 loss: 0.0320 (0.0398) time: 2.8651 data: 0.0068 max mem: 33370 +Epoch: [27] [2000/2639] eta: 0:30:41 lr: 1.7225642545810787e-05 loss: 0.0344 (0.0398) time: 2.8706 data: 0.0073 max mem: 33370 +Epoch: [27] [2010/2639] eta: 0:30:12 lr: 1.722084364831198e-05 loss: 0.0380 (0.0398) time: 2.8646 data: 0.0074 max mem: 33370 +Epoch: [27] [2020/2639] eta: 0:29:43 lr: 1.7216044602219798e-05 loss: 0.0411 (0.0398) time: 2.8851 data: 0.0070 max mem: 33370 +Epoch: [27] [2030/2639] eta: 0:29:15 lr: 1.7211245407483602e-05 loss: 0.0345 (0.0398) time: 2.9187 data: 0.0070 max mem: 33370 +Epoch: [27] [2040/2639] eta: 0:28:46 lr: 1.720644606405274e-05 loss: 0.0304 (0.0398) time: 2.9272 data: 0.0072 max mem: 33370 +Epoch: [27] [2050/2639] eta: 0:28:17 lr: 1.7201646571876514e-05 loss: 0.0295 (0.0398) time: 2.9178 data: 0.0071 max mem: 33370 +Epoch: [27] [2060/2639] eta: 0:27:48 lr: 1.7196846930904202e-05 loss: 0.0320 (0.0398) time: 2.8786 data: 0.0069 max mem: 33370 +Epoch: [27] [2070/2639] eta: 0:27:19 lr: 1.7192047141085036e-05 loss: 0.0402 (0.0398) time: 2.8748 data: 0.0070 max mem: 33370 +Epoch: [27] [2080/2639] eta: 0:26:51 lr: 1.7187247202368235e-05 loss: 0.0380 (0.0397) time: 2.8913 data: 0.0073 max mem: 33370 +Epoch: [27] [2090/2639] eta: 0:26:22 lr: 1.718244711470296e-05 loss: 0.0285 (0.0397) time: 2.8851 data: 0.0072 max mem: 33370 +Epoch: [27] [2100/2639] eta: 0:25:53 lr: 1.7177646878038367e-05 loss: 0.0289 (0.0397) time: 2.9105 data: 0.0072 max mem: 33370 +Epoch: [27] [2110/2639] eta: 0:25:24 lr: 1.7172846492323554e-05 loss: 0.0380 (0.0397) time: 2.9122 data: 0.0073 max mem: 33370 +Epoch: [27] [2120/2639] eta: 0:24:55 lr: 1.71680459575076e-05 loss: 0.0380 (0.0397) time: 2.8988 data: 0.0074 max mem: 33370 +Epoch: [27] [2130/2639] eta: 0:24:27 lr: 1.7163245273539548e-05 loss: 0.0361 (0.0397) time: 2.8995 data: 0.0073 max mem: 33370 +Epoch: [27] [2140/2639] eta: 0:23:58 lr: 1.7158444440368403e-05 loss: 0.0409 (0.0397) time: 2.8791 data: 0.0070 max mem: 33370 +Epoch: [27] [2150/2639] eta: 0:23:29 lr: 1.7153643457943144e-05 loss: 0.0414 (0.0398) time: 2.8444 data: 0.0073 max mem: 33370 +Epoch: [27] [2160/2639] eta: 0:23:00 lr: 1.714884232621271e-05 loss: 0.0355 (0.0397) time: 2.8537 data: 0.0073 max mem: 33370 +Epoch: [27] [2170/2639] eta: 0:22:31 lr: 1.7144041045126015e-05 loss: 0.0339 (0.0397) time: 2.8589 data: 0.0071 max mem: 33370 +Epoch: [27] [2180/2639] eta: 0:22:02 lr: 1.7139239614631925e-05 loss: 0.0308 (0.0397) time: 2.8551 data: 0.0074 max mem: 33370 +Epoch: [27] [2190/2639] eta: 0:21:33 lr: 1.713443803467929e-05 loss: 0.0309 (0.0397) time: 2.8537 data: 0.0074 max mem: 33370 +Epoch: [27] [2200/2639] eta: 0:21:04 lr: 1.7129636305216916e-05 loss: 0.0309 (0.0397) time: 2.8412 data: 0.0071 max mem: 33370 +Epoch: [27] [2210/2639] eta: 0:20:36 lr: 1.7124834426193578e-05 loss: 0.0336 (0.0397) time: 2.8601 data: 0.0070 max mem: 33370 +Epoch: [27] [2220/2639] eta: 0:20:07 lr: 1.7120032397558014e-05 loss: 0.0374 (0.0397) time: 2.8849 data: 0.0072 max mem: 33370 +Epoch: [27] [2230/2639] eta: 0:19:38 lr: 1.711523021925894e-05 loss: 0.0368 (0.0397) time: 2.8912 data: 0.0072 max mem: 33370 +Epoch: [27] [2240/2639] eta: 0:19:09 lr: 1.711042789124502e-05 loss: 0.0368 (0.0397) time: 2.8951 data: 0.0072 max mem: 33370 +Epoch: [27] [2250/2639] eta: 0:18:40 lr: 1.7105625413464902e-05 loss: 0.0387 (0.0397) time: 2.8857 data: 0.0072 max mem: 33370 +Epoch: [27] [2260/2639] eta: 0:18:12 lr: 1.710082278586719e-05 loss: 0.0383 (0.0397) time: 2.8951 data: 0.0069 max mem: 33370 +Epoch: [27] [2270/2639] eta: 0:17:43 lr: 1.709602000840046e-05 loss: 0.0374 (0.0397) time: 2.9321 data: 0.0072 max mem: 33370 +Epoch: [27] [2280/2639] eta: 0:17:14 lr: 1.7091217081013246e-05 loss: 0.0366 (0.0397) time: 2.9056 data: 0.0074 max mem: 33370 +Epoch: [27] [2290/2639] eta: 0:16:45 lr: 1.7086414003654064e-05 loss: 0.0335 (0.0397) time: 2.8715 data: 0.0074 max mem: 33370 +Epoch: [27] [2300/2639] eta: 0:16:17 lr: 1.7081610776271374e-05 loss: 0.0327 (0.0396) time: 2.8824 data: 0.0075 max mem: 33370 +Epoch: [27] [2310/2639] eta: 0:15:48 lr: 1.7076807398813623e-05 loss: 0.0388 (0.0397) time: 2.8980 data: 0.0073 max mem: 33370 +Epoch: [27] [2320/2639] eta: 0:15:19 lr: 1.707200387122921e-05 loss: 0.0382 (0.0397) time: 2.8883 data: 0.0070 max mem: 33370 +Epoch: [27] [2330/2639] eta: 0:14:50 lr: 1.706720019346651e-05 loss: 0.0347 (0.0397) time: 2.9536 data: 0.0718 max mem: 33370 +Epoch: [27] [2340/2639] eta: 0:14:21 lr: 1.7062396365473853e-05 loss: 0.0398 (0.0397) time: 2.9774 data: 0.0720 max mem: 33370 +Epoch: [27] [2350/2639] eta: 0:13:53 lr: 1.7057592387199552e-05 loss: 0.0398 (0.0397) time: 2.8831 data: 0.0072 max mem: 33370 +Epoch: [27] [2360/2639] eta: 0:13:24 lr: 1.7052788258591865e-05 loss: 0.0393 (0.0397) time: 2.8688 data: 0.0071 max mem: 33370 +Epoch: [27] [2370/2639] eta: 0:12:55 lr: 1.704798397959904e-05 loss: 0.0366 (0.0397) time: 2.8965 data: 0.0071 max mem: 33370 +Epoch: [27] [2380/2639] eta: 0:12:26 lr: 1.7043179550169257e-05 loss: 0.0397 (0.0397) time: 2.8788 data: 0.0069 max mem: 33370 +Epoch: [27] [2390/2639] eta: 0:11:57 lr: 1.7038374970250706e-05 loss: 0.0362 (0.0397) time: 2.8693 data: 0.0070 max mem: 33370 +Epoch: [27] [2400/2639] eta: 0:11:28 lr: 1.70335702397915e-05 loss: 0.0362 (0.0397) time: 2.8720 data: 0.0072 max mem: 33370 +Epoch: [27] [2410/2639] eta: 0:11:00 lr: 1.7028765358739747e-05 loss: 0.0389 (0.0397) time: 2.9017 data: 0.0071 max mem: 33370 +Epoch: [27] [2420/2639] eta: 0:10:31 lr: 1.702396032704352e-05 loss: 0.0346 (0.0397) time: 2.9194 data: 0.0068 max mem: 33370 +Epoch: [27] [2430/2639] eta: 0:10:02 lr: 1.7019155144650827e-05 loss: 0.0323 (0.0397) time: 2.8880 data: 0.0068 max mem: 33370 +Epoch: [27] [2440/2639] eta: 0:09:33 lr: 1.7014349811509685e-05 loss: 0.0367 (0.0397) time: 2.9091 data: 0.0069 max mem: 33370 +Epoch: [27] [2450/2639] eta: 0:09:04 lr: 1.700954432756804e-05 loss: 0.0364 (0.0397) time: 2.9005 data: 0.0072 max mem: 33370 +Epoch: [27] [2460/2639] eta: 0:08:36 lr: 1.700473869277383e-05 loss: 0.0356 (0.0397) time: 2.8858 data: 0.0074 max mem: 33370 +Epoch: [27] [2470/2639] eta: 0:08:07 lr: 1.6999932907074943e-05 loss: 0.0408 (0.0397) time: 2.9078 data: 0.0071 max mem: 33370 +Epoch: [27] [2480/2639] eta: 0:07:38 lr: 1.699512697041924e-05 loss: 0.0409 (0.0397) time: 2.8880 data: 0.0070 max mem: 33370 +Epoch: [27] [2490/2639] eta: 0:07:09 lr: 1.6990320882754536e-05 loss: 0.0375 (0.0398) time: 2.8578 data: 0.0069 max mem: 33370 +Epoch: [27] [2500/2639] eta: 0:06:40 lr: 1.6985514644028637e-05 loss: 0.0376 (0.0398) time: 2.8472 data: 0.0069 max mem: 33370 +Epoch: [27] [2510/2639] eta: 0:06:11 lr: 1.698070825418928e-05 loss: 0.0376 (0.0398) time: 2.8632 data: 0.0071 max mem: 33370 +Epoch: [27] [2520/2639] eta: 0:05:43 lr: 1.6975901713184202e-05 loss: 0.0412 (0.0398) time: 2.8728 data: 0.0073 max mem: 33370 +Epoch: [27] [2530/2639] eta: 0:05:14 lr: 1.697109502096107e-05 loss: 0.0356 (0.0398) time: 2.8934 data: 0.0075 max mem: 33370 +Epoch: [27] [2540/2639] eta: 0:04:45 lr: 1.696628817746756e-05 loss: 0.0315 (0.0397) time: 2.9160 data: 0.0073 max mem: 33370 +Epoch: [27] [2550/2639] eta: 0:04:16 lr: 1.696148118265127e-05 loss: 0.0310 (0.0397) time: 2.8865 data: 0.0071 max mem: 33370 +Epoch: [27] [2560/2639] eta: 0:03:47 lr: 1.6956674036459786e-05 loss: 0.0372 (0.0398) time: 2.8905 data: 0.0072 max mem: 33370 +Epoch: [27] [2570/2639] eta: 0:03:18 lr: 1.695186673884066e-05 loss: 0.0364 (0.0397) time: 2.8968 data: 0.0075 max mem: 33370 +Epoch: [27] [2580/2639] eta: 0:02:50 lr: 1.6947059289741406e-05 loss: 0.0354 (0.0397) time: 2.9088 data: 0.0074 max mem: 33370 +Epoch: [27] [2590/2639] eta: 0:02:21 lr: 1.6942251689109497e-05 loss: 0.0347 (0.0398) time: 2.9285 data: 0.0072 max mem: 33370 +Epoch: [27] [2600/2639] eta: 0:01:52 lr: 1.693744393689238e-05 loss: 0.0347 (0.0397) time: 2.9205 data: 0.0072 max mem: 33370 +Epoch: [27] [2610/2639] eta: 0:01:23 lr: 1.693263603303746e-05 loss: 0.0357 (0.0397) time: 2.8988 data: 0.0073 max mem: 33370 +Epoch: [27] [2620/2639] eta: 0:00:54 lr: 1.6927827977492113e-05 loss: 0.0386 (0.0397) time: 2.8509 data: 0.0072 max mem: 33370 +Epoch: [27] [2630/2639] eta: 0:00:25 lr: 1.6923019770203673e-05 loss: 0.0402 (0.0398) time: 2.8675 data: 0.0071 max mem: 33370 +Epoch: [27] Total time: 2:06:50 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 2:19:39 time: 3.2566 data: 3.1584 max mem: 33370 +Test: [ 100/2573] eta: 0:04:26 time: 0.0764 data: 0.0014 max mem: 33370 +Test: [ 200/2573] eta: 0:03:41 time: 0.0783 data: 0.0014 max mem: 33370 +Test: [ 300/2573] eta: 0:03:19 time: 0.0794 data: 0.0013 max mem: 33370 +Test: [ 400/2573] eta: 0:03:05 time: 0.0805 data: 0.0014 max mem: 33370 +Test: [ 500/2573] eta: 0:02:54 time: 0.0790 data: 0.0014 max mem: 33370 +Test: [ 600/2573] eta: 0:02:43 time: 0.0780 data: 0.0013 max mem: 33370 +Test: [ 700/2573] eta: 0:02:35 time: 0.0794 data: 0.0014 max mem: 33370 +Test: [ 800/2573] eta: 0:02:26 time: 0.0818 data: 0.0013 max mem: 33370 +Test: [ 900/2573] eta: 0:02:17 time: 0.0792 data: 0.0014 max mem: 33370 +Test: [1000/2573] eta: 0:02:08 time: 0.0793 data: 0.0014 max mem: 33370 +Test: [1100/2573] eta: 0:02:00 time: 0.0787 data: 0.0012 max mem: 33370 +Test: [1200/2573] eta: 0:01:53 time: 0.1613 data: 0.0836 max mem: 33370 +Test: [1300/2573] eta: 0:01:47 time: 0.0884 data: 0.0106 max mem: 33370 +Test: [1400/2573] eta: 0:01:38 time: 0.0775 data: 0.0013 max mem: 33370 +Test: [1500/2573] eta: 0:01:29 time: 0.0786 data: 0.0013 max mem: 33370 +Test: [1600/2573] eta: 0:01:21 time: 0.0823 data: 0.0013 max mem: 33370 +Test: [1700/2573] eta: 0:01:12 time: 0.0770 data: 0.0014 max mem: 33370 +Test: [1800/2573] eta: 0:01:04 time: 0.0802 data: 0.0013 max mem: 33370 +Test: [1900/2573] eta: 0:00:55 time: 0.0779 data: 0.0012 max mem: 33370 +Test: [2000/2573] eta: 0:00:47 time: 0.0804 data: 0.0015 max mem: 33370 +Test: [2100/2573] eta: 0:00:39 time: 0.1248 data: 0.0455 max mem: 33370 +Test: [2200/2573] eta: 0:00:31 time: 0.0844 data: 0.0050 max mem: 33370 +Test: [2300/2573] eta: 0:00:23 time: 0.2875 data: 0.2086 max mem: 33370 +Test: [2400/2573] eta: 0:00:15 time: 0.0854 data: 0.0101 max mem: 33370 +Test: [2500/2573] eta: 0:00:06 time: 0.0784 data: 0.0014 max mem: 33370 +Test: Total time: 0:03:53 +Final results: +Mean IoU is 63.37 + + precision@0.5 = 71.16 + precision@0.6 = 66.07 + precision@0.7 = 59.78 + precision@0.8 = 48.45 + precision@0.9 = 24.22 + overall IoU = 60.93 + +Average object IoU 63.37297692403029 +Overall IoU 60.92753982543945 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [28] [ 0/2639] eta: 5:03:43 lr: 1.6918692253860188e-05 loss: 0.0387 (0.0387) time: 6.9054 data: 3.7887 max mem: 33370 +Epoch: [28] [ 10/2639] eta: 2:21:36 lr: 1.6913883758114682e-05 loss: 0.0365 (0.0348) time: 3.2319 data: 0.3518 max mem: 33370 +Epoch: [28] [ 20/2639] eta: 2:13:29 lr: 1.6909075110473163e-05 loss: 0.0327 (0.0352) time: 2.8660 data: 0.0071 max mem: 33370 +Epoch: [28] [ 30/2639] eta: 2:10:25 lr: 1.6904266310882847e-05 loss: 0.0353 (0.0353) time: 2.8717 data: 0.0066 max mem: 33370 +Epoch: [28] [ 40/2639] eta: 2:08:42 lr: 1.68994573592909e-05 loss: 0.0379 (0.0363) time: 2.8801 data: 0.0071 max mem: 33370 +Epoch: [28] [ 50/2639] eta: 2:07:00 lr: 1.689464825564445e-05 loss: 0.0379 (0.0376) time: 2.8569 data: 0.0071 max mem: 33370 +Epoch: [28] [ 60/2639] eta: 2:06:15 lr: 1.68898389998906e-05 loss: 0.0357 (0.0384) time: 2.8682 data: 0.0071 max mem: 33370 +Epoch: [28] [ 70/2639] eta: 2:05:20 lr: 1.6885029591976403e-05 loss: 0.0325 (0.0378) time: 2.8861 data: 0.0072 max mem: 33370 +Epoch: [28] [ 80/2639] eta: 2:04:43 lr: 1.68802200318489e-05 loss: 0.0328 (0.0377) time: 2.8846 data: 0.0075 max mem: 33370 +Epoch: [28] [ 90/2639] eta: 2:04:12 lr: 1.6875410319455066e-05 loss: 0.0331 (0.0384) time: 2.9109 data: 0.0075 max mem: 33370 +Epoch: [28] [ 100/2639] eta: 2:03:43 lr: 1.687060045474187e-05 loss: 0.0364 (0.0392) time: 2.9216 data: 0.0076 max mem: 33370 +Epoch: [28] [ 110/2639] eta: 2:03:13 lr: 1.6865790437656225e-05 loss: 0.0367 (0.0391) time: 2.9223 data: 0.0075 max mem: 33370 +Epoch: [28] [ 120/2639] eta: 2:02:20 lr: 1.6860980268145022e-05 loss: 0.0341 (0.0387) time: 2.8650 data: 0.0073 max mem: 33370 +Epoch: [28] [ 130/2639] eta: 2:01:45 lr: 1.6856169946155106e-05 loss: 0.0328 (0.0383) time: 2.8466 data: 0.0074 max mem: 33370 +Epoch: [28] [ 140/2639] eta: 2:01:05 lr: 1.6851359471633302e-05 loss: 0.0335 (0.0385) time: 2.8647 data: 0.0075 max mem: 33370 +Epoch: [28] [ 150/2639] eta: 2:00:27 lr: 1.684654884452638e-05 loss: 0.0335 (0.0383) time: 2.8502 data: 0.0074 max mem: 33370 +Epoch: [28] [ 160/2639] eta: 1:59:57 lr: 1.6841738064781092e-05 loss: 0.0327 (0.0382) time: 2.8760 data: 0.0073 max mem: 33370 +Epoch: [28] [ 170/2639] eta: 1:59:28 lr: 1.683692713234414e-05 loss: 0.0360 (0.0388) time: 2.9021 data: 0.0073 max mem: 33370 +Epoch: [28] [ 180/2639] eta: 1:59:01 lr: 1.68321160471622e-05 loss: 0.0344 (0.0385) time: 2.9134 data: 0.0076 max mem: 33370 +Epoch: [28] [ 190/2639] eta: 1:58:24 lr: 1.6827304809181906e-05 loss: 0.0325 (0.0382) time: 2.8806 data: 0.0074 max mem: 33370 +Epoch: [28] [ 200/2639] eta: 1:57:54 lr: 1.682249341834987e-05 loss: 0.0323 (0.0381) time: 2.8673 data: 0.0073 max mem: 33370 +Epoch: [28] [ 210/2639] eta: 1:57:24 lr: 1.6817681874612646e-05 loss: 0.0331 (0.0379) time: 2.8928 data: 0.0074 max mem: 33370 +Epoch: [28] [ 220/2639] eta: 1:56:48 lr: 1.6812870177916774e-05 loss: 0.0331 (0.0379) time: 2.8617 data: 0.0073 max mem: 33370 +Epoch: [28] [ 230/2639] eta: 1:58:35 lr: 1.680805832820874e-05 loss: 0.0331 (0.0385) time: 3.5174 data: 0.6764 max mem: 33370 +Epoch: [28] [ 240/2639] eta: 1:58:35 lr: 1.680324632543502e-05 loss: 0.0351 (0.0388) time: 3.7244 data: 0.8820 max mem: 33370 +Epoch: [28] [ 250/2639] eta: 1:57:59 lr: 1.6798434169542014e-05 loss: 0.0368 (0.0386) time: 3.0733 data: 0.2130 max mem: 33370 +Epoch: [28] [ 260/2639] eta: 1:57:12 lr: 1.679362186047613e-05 loss: 0.0368 (0.0387) time: 2.8382 data: 0.0077 max mem: 33370 +Epoch: [28] [ 270/2639] eta: 1:56:35 lr: 1.6788809398183706e-05 loss: 0.0389 (0.0387) time: 2.8228 data: 0.0074 max mem: 33370 +Epoch: [28] [ 280/2639] eta: 1:55:58 lr: 1.678399678261106e-05 loss: 0.0338 (0.0386) time: 2.8701 data: 0.0073 max mem: 33370 +Epoch: [28] [ 290/2639] eta: 1:55:22 lr: 1.6779184013704488e-05 loss: 0.0350 (0.0388) time: 2.8659 data: 0.0072 max mem: 33370 +Epoch: [28] [ 300/2639] eta: 1:54:43 lr: 1.6774371091410214e-05 loss: 0.0354 (0.0390) time: 2.8456 data: 0.0071 max mem: 33370 +Epoch: [28] [ 310/2639] eta: 1:54:04 lr: 1.6769558015674454e-05 loss: 0.0341 (0.0389) time: 2.8207 data: 0.0074 max mem: 33370 +Epoch: [28] [ 320/2639] eta: 1:53:30 lr: 1.676474478644338e-05 loss: 0.0356 (0.0389) time: 2.8455 data: 0.0076 max mem: 33370 +Epoch: [28] [ 330/2639] eta: 1:52:56 lr: 1.6759931403663133e-05 loss: 0.0344 (0.0389) time: 2.8764 data: 0.0077 max mem: 33370 +Epoch: [28] [ 340/2639] eta: 1:52:22 lr: 1.6755117867279797e-05 loss: 0.0317 (0.0386) time: 2.8694 data: 0.0079 max mem: 33370 +Epoch: [28] [ 350/2639] eta: 1:51:44 lr: 1.6750304177239458e-05 loss: 0.0317 (0.0386) time: 2.8269 data: 0.0078 max mem: 33370 +Epoch: [28] [ 360/2639] eta: 1:51:07 lr: 1.6745490333488123e-05 loss: 0.0345 (0.0385) time: 2.8017 data: 0.0074 max mem: 33370 +Epoch: [28] [ 370/2639] eta: 1:50:35 lr: 1.6740676335971798e-05 loss: 0.0331 (0.0384) time: 2.8496 data: 0.0072 max mem: 33370 +Epoch: [28] [ 380/2639] eta: 1:49:58 lr: 1.6735862184636428e-05 loss: 0.0325 (0.0382) time: 2.8401 data: 0.0073 max mem: 33370 +Epoch: [28] [ 390/2639] eta: 1:49:25 lr: 1.673104787942794e-05 loss: 0.0314 (0.0382) time: 2.8189 data: 0.0073 max mem: 33370 +Epoch: [28] [ 400/2639] eta: 1:48:54 lr: 1.6726233420292212e-05 loss: 0.0345 (0.0381) time: 2.8666 data: 0.0072 max mem: 33370 +Epoch: [28] [ 410/2639] eta: 1:48:22 lr: 1.6721418807175092e-05 loss: 0.0342 (0.0381) time: 2.8769 data: 0.0073 max mem: 33370 +Epoch: [28] [ 420/2639] eta: 1:47:53 lr: 1.6716604040022384e-05 loss: 0.0321 (0.0381) time: 2.8938 data: 0.0073 max mem: 33370 +Epoch: [28] [ 430/2639] eta: 1:47:22 lr: 1.6711789118779875e-05 loss: 0.0324 (0.0381) time: 2.8993 data: 0.0075 max mem: 33370 +Epoch: [28] [ 440/2639] eta: 1:46:50 lr: 1.6706974043393284e-05 loss: 0.0347 (0.0382) time: 2.8707 data: 0.0075 max mem: 33370 +Epoch: [28] [ 450/2639] eta: 1:46:17 lr: 1.6702158813808326e-05 loss: 0.0365 (0.0383) time: 2.8502 data: 0.0075 max mem: 33370 +Epoch: [28] [ 460/2639] eta: 1:45:45 lr: 1.669734342997066e-05 loss: 0.0366 (0.0382) time: 2.8420 data: 0.0077 max mem: 33370 +Epoch: [28] [ 470/2639] eta: 1:45:13 lr: 1.6692527891825913e-05 loss: 0.0376 (0.0381) time: 2.8534 data: 0.0073 max mem: 33370 +Epoch: [28] [ 480/2639] eta: 1:44:41 lr: 1.668771219931967e-05 loss: 0.0376 (0.0382) time: 2.8545 data: 0.0075 max mem: 33370 +Epoch: [28] [ 490/2639] eta: 1:44:10 lr: 1.66828963523975e-05 loss: 0.0391 (0.0383) time: 2.8598 data: 0.0077 max mem: 33370 +Epoch: [28] [ 500/2639] eta: 1:43:41 lr: 1.66780803510049e-05 loss: 0.0391 (0.0384) time: 2.8843 data: 0.0073 max mem: 33370 +Epoch: [28] [ 510/2639] eta: 1:43:12 lr: 1.6673264195087375e-05 loss: 0.0354 (0.0384) time: 2.9063 data: 0.0073 max mem: 33370 +Epoch: [28] [ 520/2639] eta: 1:42:43 lr: 1.6668447884590344e-05 loss: 0.0349 (0.0384) time: 2.9052 data: 0.0073 max mem: 33370 +Epoch: [28] [ 530/2639] eta: 1:42:11 lr: 1.666363141945923e-05 loss: 0.0372 (0.0384) time: 2.8734 data: 0.0072 max mem: 33370 +Epoch: [28] [ 540/2639] eta: 1:41:39 lr: 1.6658814799639403e-05 loss: 0.0372 (0.0383) time: 2.8385 data: 0.0074 max mem: 33370 +Epoch: [28] [ 550/2639] eta: 1:41:08 lr: 1.6653998025076188e-05 loss: 0.0353 (0.0383) time: 2.8435 data: 0.0076 max mem: 33370 +Epoch: [28] [ 560/2639] eta: 1:40:35 lr: 1.6649181095714894e-05 loss: 0.0355 (0.0383) time: 2.8313 data: 0.0075 max mem: 33370 +Epoch: [28] [ 570/2639] eta: 1:40:06 lr: 1.6644364011500767e-05 loss: 0.0357 (0.0383) time: 2.8487 data: 0.0075 max mem: 33370 +Epoch: [28] [ 580/2639] eta: 1:39:35 lr: 1.6639546772379043e-05 loss: 0.0329 (0.0382) time: 2.8725 data: 0.0075 max mem: 33370 +Epoch: [28] [ 590/2639] eta: 1:39:05 lr: 1.663472937829489e-05 loss: 0.0373 (0.0382) time: 2.8633 data: 0.0073 max mem: 33370 +Epoch: [28] [ 600/2639] eta: 1:38:35 lr: 1.662991182919348e-05 loss: 0.0382 (0.0382) time: 2.8755 data: 0.0075 max mem: 33370 +Epoch: [28] [ 610/2639] eta: 1:38:08 lr: 1.6625094125019906e-05 loss: 0.0386 (0.0384) time: 2.9131 data: 0.0075 max mem: 33370 +Epoch: [28] [ 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33370 +Epoch: [28] [ 700/2639] eta: 1:33:42 lr: 1.6581727800135665e-05 loss: 0.0321 (0.0386) time: 2.8998 data: 0.0076 max mem: 33370 +Epoch: [28] [ 710/2639] eta: 1:33:13 lr: 1.6576908542213466e-05 loss: 0.0340 (0.0386) time: 2.9183 data: 0.0076 max mem: 33370 +Epoch: [28] [ 720/2639] eta: 1:32:43 lr: 1.6572089128612886e-05 loss: 0.0354 (0.0385) time: 2.8852 data: 0.0073 max mem: 33370 +Epoch: [28] [ 730/2639] eta: 1:32:14 lr: 1.6567269559278574e-05 loss: 0.0339 (0.0385) time: 2.8740 data: 0.0072 max mem: 33370 +Epoch: [28] [ 740/2639] eta: 1:31:44 lr: 1.6562449834155173e-05 loss: 0.0400 (0.0385) time: 2.8699 data: 0.0071 max mem: 33370 +Epoch: [28] [ 750/2639] eta: 1:31:14 lr: 1.6557629953187258e-05 loss: 0.0355 (0.0385) time: 2.8697 data: 0.0071 max mem: 33370 +Epoch: [28] [ 760/2639] eta: 1:30:44 lr: 1.6552809916319388e-05 loss: 0.0318 (0.0384) time: 2.8537 data: 0.0071 max mem: 33370 +Epoch: [28] [ 770/2639] eta: 1:30:13 lr: 1.654798972349607e-05 loss: 0.0319 (0.0385) time: 2.8353 data: 0.0071 max mem: 33370 +Epoch: [28] [ 780/2639] eta: 1:29:42 lr: 1.6543169374661778e-05 loss: 0.0319 (0.0384) time: 2.8175 data: 0.0071 max mem: 33370 +Epoch: [28] [ 790/2639] eta: 1:29:12 lr: 1.6538348869760964e-05 loss: 0.0304 (0.0384) time: 2.8194 data: 0.0073 max mem: 33370 +Epoch: [28] [ 800/2639] eta: 1:28:42 lr: 1.6533528208738012e-05 loss: 0.0338 (0.0384) time: 2.8454 data: 0.0075 max mem: 33370 +Epoch: [28] [ 810/2639] eta: 1:28:11 lr: 1.65287073915373e-05 loss: 0.0364 (0.0384) time: 2.8373 data: 0.0076 max mem: 33370 +Epoch: [28] [ 820/2639] eta: 1:27:41 lr: 1.652388641810313e-05 loss: 0.0351 (0.0384) time: 2.8386 data: 0.0074 max mem: 33370 +Epoch: [28] [ 830/2639] eta: 1:27:12 lr: 1.6519065288379814e-05 loss: 0.0352 (0.0384) time: 2.8642 data: 0.0075 max mem: 33370 +Epoch: [28] [ 840/2639] eta: 1:26:42 lr: 1.651424400231158e-05 loss: 0.0345 (0.0384) time: 2.8574 data: 0.0076 max mem: 33370 +Epoch: [28] [ 850/2639] eta: 1:26:14 lr: 1.6509422559842654e-05 loss: 0.0338 (0.0384) time: 2.8793 data: 0.0077 max mem: 33370 +Epoch: [28] [ 860/2639] eta: 1:25:43 lr: 1.6504600960917192e-05 loss: 0.0340 (0.0384) time: 2.8663 data: 0.0079 max mem: 33370 +Epoch: [28] [ 870/2639] eta: 1:25:13 lr: 1.6499779205479348e-05 loss: 0.0333 (0.0384) time: 2.8257 data: 0.0079 max mem: 33370 +Epoch: [28] [ 880/2639] eta: 1:24:44 lr: 1.64949572934732e-05 loss: 0.0310 (0.0383) time: 2.8621 data: 0.0077 max mem: 33370 +Epoch: [28] [ 890/2639] eta: 1:24:15 lr: 1.6490135224842818e-05 loss: 0.0310 (0.0383) time: 2.8860 data: 0.0076 max mem: 33370 +Epoch: [28] [ 900/2639] eta: 1:23:47 lr: 1.6485312999532216e-05 loss: 0.0351 (0.0383) time: 2.8934 data: 0.0075 max mem: 33370 +Epoch: [28] [ 910/2639] eta: 1:23:18 lr: 1.648049061748538e-05 loss: 0.0324 (0.0381) time: 2.9156 data: 0.0074 max mem: 33370 +Epoch: [28] [ 920/2639] eta: 1:22:49 lr: 1.6475668078646248e-05 loss: 0.0324 (0.0382) time: 2.8946 data: 0.0073 max mem: 33370 +Epoch: [28] [ 930/2639] eta: 1:22:21 lr: 1.6470845382958735e-05 loss: 0.0361 (0.0382) time: 2.9089 data: 0.0071 max mem: 33370 +Epoch: [28] [ 940/2639] eta: 1:21:53 lr: 1.64660225303667e-05 loss: 0.0395 (0.0383) time: 2.9345 data: 0.0072 max mem: 33370 +Epoch: [28] [ 950/2639] eta: 1:21:23 lr: 1.6461199520813974e-05 loss: 0.0336 (0.0383) time: 2.8940 data: 0.0074 max mem: 33370 +Epoch: [28] [ 960/2639] eta: 1:20:54 lr: 1.6456376354244342e-05 loss: 0.0336 (0.0383) time: 2.8772 data: 0.0075 max mem: 33370 +Epoch: [28] [ 970/2639] eta: 1:20:24 lr: 1.6451553030601567e-05 loss: 0.0342 (0.0382) time: 2.8589 data: 0.0074 max mem: 33370 +Epoch: [28] [ 980/2639] eta: 1:19:55 lr: 1.6446729549829353e-05 loss: 0.0346 (0.0382) time: 2.8600 data: 0.0077 max mem: 33370 +Epoch: [28] [ 990/2639] eta: 1:19:26 lr: 1.644190591187138e-05 loss: 0.0401 (0.0382) time: 2.8853 data: 0.0077 max mem: 33370 +Epoch: [28] [1000/2639] eta: 1:18:57 lr: 1.643708211667128e-05 loss: 0.0370 (0.0382) time: 2.8881 data: 0.0074 max mem: 33370 +Epoch: [28] 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mem: 33370 +Epoch: [28] [1090/2639] eta: 1:14:33 lr: 1.6393660874655595e-05 loss: 0.0354 (0.0382) time: 2.8685 data: 0.0075 max mem: 33370 +Epoch: [28] [1100/2639] eta: 1:14:04 lr: 1.6388835503925732e-05 loss: 0.0328 (0.0382) time: 2.8717 data: 0.0075 max mem: 33370 +Epoch: [28] [1110/2639] eta: 1:13:34 lr: 1.6384009975331177e-05 loss: 0.0328 (0.0382) time: 2.8628 data: 0.0075 max mem: 33370 +Epoch: [28] [1120/2639] eta: 1:13:05 lr: 1.6379184288815118e-05 loss: 0.0317 (0.0381) time: 2.8489 data: 0.0074 max mem: 33370 +Epoch: [28] [1130/2639] eta: 1:12:36 lr: 1.6374358444320672e-05 loss: 0.0268 (0.0380) time: 2.8759 data: 0.0075 max mem: 33370 +Epoch: [28] [1140/2639] eta: 1:12:07 lr: 1.6369532441790942e-05 loss: 0.0309 (0.0380) time: 2.8832 data: 0.0074 max mem: 33370 +Epoch: [28] [1150/2639] eta: 1:11:38 lr: 1.6364706281168974e-05 loss: 0.0304 (0.0380) time: 2.8550 data: 0.0075 max mem: 33370 +Epoch: [28] [1160/2639] eta: 1:11:08 lr: 1.635987996239779e-05 loss: 0.0304 (0.0379) time: 2.8221 data: 0.0076 max mem: 33370 +Epoch: [28] [1170/2639] eta: 1:10:39 lr: 1.6355053485420352e-05 loss: 0.0332 (0.0381) time: 2.8409 data: 0.0074 max mem: 33370 +Epoch: [28] [1180/2639] eta: 1:10:10 lr: 1.6350226850179606e-05 loss: 0.0358 (0.0381) time: 2.8718 data: 0.0074 max mem: 33370 +Epoch: [28] [1190/2639] eta: 1:09:42 lr: 1.634540005661844e-05 loss: 0.0358 (0.0381) time: 2.9059 data: 0.0073 max mem: 33370 +Epoch: [28] [1200/2639] eta: 1:09:13 lr: 1.6340573104679727e-05 loss: 0.0356 (0.0381) time: 2.9053 data: 0.0072 max mem: 33370 +Epoch: [28] [1210/2639] eta: 1:08:44 lr: 1.6335745994306264e-05 loss: 0.0356 (0.0381) time: 2.8994 data: 0.0076 max mem: 33370 +Epoch: [28] [1220/2639] eta: 1:08:16 lr: 1.6330918725440845e-05 loss: 0.0361 (0.0381) time: 2.9170 data: 0.0075 max mem: 33370 +Epoch: [28] [1230/2639] eta: 1:07:46 lr: 1.6326091298026193e-05 loss: 0.0361 (0.0381) time: 2.8895 data: 0.0072 max mem: 33370 +Epoch: [28] [1240/2639] eta: 1:07:17 lr: 1.6321263712005024e-05 loss: 0.0328 (0.0381) time: 2.8291 data: 0.0073 max mem: 33370 +Epoch: [28] [1250/2639] eta: 1:06:47 lr: 1.6316435967319985e-05 loss: 0.0319 (0.0381) time: 2.8038 data: 0.0074 max mem: 33370 +Epoch: [28] [1260/2639] eta: 1:06:18 lr: 1.63116080639137e-05 loss: 0.0332 (0.0381) time: 2.8354 data: 0.0076 max mem: 33370 +Epoch: [28] [1270/2639] eta: 1:05:49 lr: 1.6306780001728753e-05 loss: 0.0353 (0.0381) time: 2.8561 data: 0.0076 max mem: 33370 +Epoch: [28] [1280/2639] eta: 1:05:19 lr: 1.6301951780707676e-05 loss: 0.0387 (0.0381) time: 2.8494 data: 0.0077 max mem: 33370 +Epoch: [28] [1290/2639] eta: 1:04:50 lr: 1.6297123400792978e-05 loss: 0.0402 (0.0382) time: 2.8352 data: 0.0079 max mem: 33370 +Epoch: [28] [1300/2639] eta: 1:04:20 lr: 1.6292294861927114e-05 loss: 0.0346 (0.0381) time: 2.8236 data: 0.0076 max mem: 33370 +Epoch: [28] [1310/2639] eta: 1:03:51 lr: 1.6287466164052514e-05 loss: 0.0304 (0.0381) time: 2.8414 data: 0.0073 max mem: 33370 +Epoch: [28] [1320/2639] eta: 1:03:23 lr: 1.6282637307111548e-05 loss: 0.0284 (0.0381) time: 2.8725 data: 0.0075 max mem: 33370 +Epoch: [28] [1330/2639] eta: 1:02:53 lr: 1.627780829104657e-05 loss: 0.0329 (0.0380) time: 2.8721 data: 0.0073 max mem: 33370 +Epoch: [28] [1340/2639] eta: 1:02:25 lr: 1.6272979115799864e-05 loss: 0.0344 (0.0380) time: 2.8761 data: 0.0072 max mem: 33370 +Epoch: [28] [1350/2639] eta: 1:01:57 lr: 1.6268149781313712e-05 loss: 0.0334 (0.0380) time: 2.9293 data: 0.0075 max mem: 33370 +Epoch: [28] [1360/2639] eta: 1:01:28 lr: 1.6263320287530323e-05 loss: 0.0334 (0.0380) time: 2.9433 data: 0.0075 max mem: 33370 +Epoch: [28] [1370/2639] eta: 1:01:00 lr: 1.6258490634391885e-05 loss: 0.0345 (0.0380) time: 2.9153 data: 0.0073 max mem: 33370 +Epoch: [28] [1380/2639] eta: 1:00:30 lr: 1.6253660821840534e-05 loss: 0.0322 (0.0379) time: 2.8679 data: 0.0077 max mem: 33370 +Epoch: [28] [1390/2639] eta: 1:00:01 lr: 1.624883084981838e-05 loss: 0.0322 (0.0379) time: 2.8545 data: 0.0076 max mem: 33370 +Epoch: [28] [1400/2639] eta: 0:59:32 lr: 1.624400071826747e-05 loss: 0.0323 (0.0379) time: 2.8662 data: 0.0070 max mem: 33370 +Epoch: [28] [1410/2639] eta: 0:59:03 lr: 1.6239170427129838e-05 loss: 0.0356 (0.0379) time: 2.8161 data: 0.0072 max mem: 33370 +Epoch: [28] [1420/2639] eta: 0:58:33 lr: 1.623433997634746e-05 loss: 0.0326 (0.0379) time: 2.7877 data: 0.0076 max mem: 33370 +Epoch: [28] [1430/2639] eta: 0:58:04 lr: 1.622950936586228e-05 loss: 0.0304 (0.0379) time: 2.8128 data: 0.0074 max mem: 33370 +Epoch: [28] [1440/2639] eta: 0:57:35 lr: 1.6224678595616195e-05 loss: 0.0306 (0.0379) time: 2.8379 data: 0.0072 max mem: 33370 +Epoch: [28] [1450/2639] eta: 0:57:06 lr: 1.6219847665551065e-05 loss: 0.0351 (0.0379) time: 2.8717 data: 0.0073 max mem: 33370 +Epoch: [28] [1460/2639] eta: 0:56:37 lr: 1.621501657560871e-05 loss: 0.0360 (0.0381) time: 2.9060 data: 0.0075 max mem: 33370 +Epoch: [28] [1470/2639] eta: 0:56:08 lr: 1.6210185325730913e-05 loss: 0.0338 (0.0381) time: 2.8886 data: 0.0072 max mem: 33370 +Epoch: [28] [1480/2639] eta: 0:55:40 lr: 1.6205353915859403e-05 loss: 0.0315 (0.0380) time: 2.9091 data: 0.0071 max mem: 33370 +Epoch: [28] [1490/2639] eta: 0:55:11 lr: 1.620052234593589e-05 loss: 0.0308 (0.0380) time: 2.9158 data: 0.0071 max mem: 33370 +Epoch: [28] [1500/2639] eta: 0:54:43 lr: 1.619569061590202e-05 loss: 0.0308 (0.0380) time: 2.9105 data: 0.0070 max mem: 33370 +Epoch: [28] [1510/2639] eta: 0:54:14 lr: 1.6190858725699417e-05 loss: 0.0360 (0.0380) time: 2.8941 data: 0.0071 max mem: 33370 +Epoch: [28] [1520/2639] eta: 0:53:45 lr: 1.618602667526966e-05 loss: 0.0325 (0.0380) time: 2.8614 data: 0.0070 max mem: 33370 +Epoch: [28] [1530/2639] eta: 0:53:16 lr: 1.618119446455428e-05 loss: 0.0325 (0.0380) time: 2.8869 data: 0.0070 max mem: 33370 +Epoch: [28] [1540/2639] eta: 0:52:47 lr: 1.617636209349477e-05 loss: 0.0316 (0.0380) time: 2.8944 data: 0.0070 max mem: 33370 +Epoch: [28] [1550/2639] eta: 0:52:19 lr: 1.6171529562032583e-05 loss: 0.0330 (0.0380) time: 2.9457 data: 0.0656 max mem: 33370 +Epoch: [28] [1560/2639] eta: 0:51:51 lr: 1.6166696870109145e-05 loss: 0.0330 (0.0379) time: 2.9368 data: 0.0660 max mem: 33370 +Epoch: [28] [1570/2639] eta: 0:51:21 lr: 1.616186401766581e-05 loss: 0.0330 (0.0379) time: 2.8329 data: 0.0073 max mem: 33370 +Epoch: [28] [1580/2639] eta: 0:50:52 lr: 1.6157031004643922e-05 loss: 0.0337 (0.0379) time: 2.7948 data: 0.0075 max mem: 33370 +Epoch: [28] [1590/2639] eta: 0:50:23 lr: 1.6152197830984762e-05 loss: 0.0380 (0.0379) time: 2.8237 data: 0.0076 max mem: 33370 +Epoch: [28] [1600/2639] eta: 0:49:54 lr: 1.6147364496629595e-05 loss: 0.0368 (0.0379) time: 2.9144 data: 0.0072 max mem: 33370 +Epoch: [28] [1610/2639] eta: 0:49:26 lr: 1.614253100151961e-05 loss: 0.0374 (0.0379) time: 2.9358 data: 0.0072 max mem: 33370 +Epoch: [28] [1620/2639] eta: 0:48:57 lr: 1.6137697345595993e-05 loss: 0.0367 (0.0379) time: 2.8981 data: 0.0073 max mem: 33370 +Epoch: [28] [1630/2639] eta: 0:48:28 lr: 1.613286352879985e-05 loss: 0.0319 (0.0379) time: 2.9048 data: 0.0073 max mem: 33370 +Epoch: [28] [1640/2639] eta: 0:47:59 lr: 1.6128029551072288e-05 loss: 0.0337 (0.0379) time: 2.8745 data: 0.0071 max mem: 33370 +Epoch: [28] [1650/2639] eta: 0:47:31 lr: 1.6123195412354332e-05 loss: 0.0351 (0.0380) time: 2.8830 data: 0.0070 max mem: 33370 +Epoch: [28] [1660/2639] eta: 0:47:02 lr: 1.6118361112587e-05 loss: 0.0400 (0.0380) time: 2.8798 data: 0.0073 max mem: 33370 +Epoch: [28] [1670/2639] eta: 0:46:32 lr: 1.6113526651711238e-05 loss: 0.0422 (0.0380) time: 2.8310 data: 0.0074 max mem: 33370 +Epoch: [28] [1680/2639] eta: 0:46:04 lr: 1.6108692029667985e-05 loss: 0.0415 (0.0380) time: 2.8656 data: 0.0072 max mem: 33370 +Epoch: [28] [1690/2639] eta: 0:45:35 lr: 1.61038572463981e-05 loss: 0.0323 (0.0380) time: 2.9239 data: 0.0074 max mem: 33370 +Epoch: [28] [1700/2639] eta: 0:45:06 lr: 1.6099022301842433e-05 loss: 0.0316 (0.0380) time: 2.9205 data: 0.0074 max mem: 33370 +Epoch: [28] [1710/2639] eta: 0:44:38 lr: 1.609418719594177e-05 loss: 0.0326 (0.0381) time: 2.9129 data: 0.0071 max mem: 33370 +Epoch: [28] [1720/2639] eta: 0:44:09 lr: 1.608935192863688e-05 loss: 0.0323 (0.0381) time: 2.9009 data: 0.0073 max mem: 33370 +Epoch: [28] [1730/2639] eta: 0:43:40 lr: 1.608451649986846e-05 loss: 0.0329 (0.0381) time: 2.8928 data: 0.0072 max mem: 33370 +Epoch: [28] [1740/2639] eta: 0:43:11 lr: 1.6079680909577192e-05 loss: 0.0347 (0.0381) time: 2.8933 data: 0.0072 max mem: 33370 +Epoch: [28] [1750/2639] eta: 0:42:42 lr: 1.6074845157703698e-05 loss: 0.0303 (0.0381) time: 2.8584 data: 0.0075 max mem: 33370 +Epoch: [28] [1760/2639] eta: 0:42:13 lr: 1.6070009244188565e-05 loss: 0.0304 (0.0381) time: 2.8132 data: 0.0075 max mem: 33370 +Epoch: [28] [1770/2639] eta: 0:41:44 lr: 1.6065173168972352e-05 loss: 0.0338 (0.0381) time: 2.8385 data: 0.0072 max mem: 33370 +Epoch: [28] [1780/2639] eta: 0:41:15 lr: 1.6060336931995547e-05 loss: 0.0309 (0.0380) time: 2.8631 data: 0.0072 max mem: 33370 +Epoch: [28] [1790/2639] eta: 0:40:46 lr: 1.605550053319863e-05 loss: 0.0287 (0.0381) time: 2.8356 data: 0.0075 max mem: 33370 +Epoch: [28] [1800/2639] eta: 0:40:17 lr: 1.6050663972522004e-05 loss: 0.0301 (0.0381) time: 2.8350 data: 0.0078 max mem: 33370 +Epoch: [28] [1810/2639] eta: 0:39:48 lr: 1.6045827249906058e-05 loss: 0.0322 (0.0381) time: 2.8149 data: 0.0074 max mem: 33370 +Epoch: [28] [1820/2639] eta: 0:39:19 lr: 1.6040990365291124e-05 loss: 0.0354 (0.0381) time: 2.8032 data: 0.0071 max mem: 33370 +Epoch: [28] [1830/2639] eta: 0:38:50 lr: 1.603615331861751e-05 loss: 0.0354 (0.0381) time: 2.8751 data: 0.0071 max mem: 33370 +Epoch: [28] [1840/2639] eta: 0:38:22 lr: 1.6031316109825445e-05 loss: 0.0322 (0.0381) time: 2.9187 data: 0.0070 max mem: 33370 +Epoch: [28] [1850/2639] eta: 0:37:53 lr: 1.602647873885516e-05 loss: 0.0359 (0.0381) time: 2.9226 data: 0.0072 max mem: 33370 +Epoch: [28] [1860/2639] eta: 0:37:24 lr: 1.602164120564681e-05 loss: 0.0359 (0.0381) time: 2.9301 data: 0.0073 max mem: 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data: 0.0070 max mem: 33370 +Epoch: [28] [1950/2639] eta: 0:33:05 lr: 1.597809609616602e-05 loss: 0.0339 (0.0382) time: 2.8637 data: 0.0071 max mem: 33370 +Epoch: [28] [1960/2639] eta: 0:32:36 lr: 1.597325693727707e-05 loss: 0.0322 (0.0382) time: 2.8557 data: 0.0071 max mem: 33370 +Epoch: [28] [1970/2639] eta: 0:32:07 lr: 1.596841761548913e-05 loss: 0.0326 (0.0382) time: 2.8476 data: 0.0071 max mem: 33370 +Epoch: [28] [1980/2639] eta: 0:32:00 lr: 1.5963578130741853e-05 loss: 0.0339 (0.0381) time: 6.2340 data: 3.3721 max mem: 33370 +Epoch: [28] [1990/2639] eta: 0:31:31 lr: 1.5958738482974864e-05 loss: 0.0384 (0.0381) time: 6.2562 data: 3.3724 max mem: 33370 +Epoch: [28] [2000/2639] eta: 0:31:02 lr: 1.5953898672127726e-05 loss: 0.0316 (0.0381) time: 2.8862 data: 0.0074 max mem: 33370 +Epoch: [28] [2010/2639] eta: 0:30:33 lr: 1.5949058698139976e-05 loss: 0.0283 (0.0381) time: 2.8952 data: 0.0069 max mem: 33370 +Epoch: [28] [2020/2639] eta: 0:30:04 lr: 1.594421856095111e-05 loss: 0.0318 (0.0381) time: 2.9067 data: 0.0071 max mem: 33370 +Epoch: [28] [2030/2639] eta: 0:29:34 lr: 1.593937826050056e-05 loss: 0.0361 (0.0381) time: 2.8881 data: 0.0075 max mem: 33370 +Epoch: [28] [2040/2639] eta: 0:29:05 lr: 1.5934537796727744e-05 loss: 0.0360 (0.0381) time: 2.8913 data: 0.0070 max mem: 33370 +Epoch: [28] [2050/2639] eta: 0:28:36 lr: 1.592969716957201e-05 loss: 0.0343 (0.0381) time: 2.9102 data: 0.0067 max mem: 33370 +Epoch: [28] [2060/2639] eta: 0:28:13 lr: 1.5924856378972685e-05 loss: 0.0368 (0.0381) time: 3.9828 data: 1.1159 max mem: 33370 +Epoch: [28] [2070/2639] eta: 0:28:04 lr: 1.5920015424869034e-05 loss: 0.0370 (0.0382) time: 7.6252 data: 2.3316 max mem: 33370 +Epoch: [28] [2080/2639] eta: 0:27:34 lr: 1.59151743072003e-05 loss: 0.0379 (0.0382) time: 6.5452 data: 1.2228 max mem: 33370 +Epoch: [28] [2090/2639] eta: 0:27:04 lr: 1.591033302590565e-05 loss: 0.0320 (0.0382) time: 2.9034 data: 0.0069 max mem: 33370 +Epoch: [28] [2100/2639] eta: 0:26:34 lr: 1.5905491580924256e-05 loss: 0.0368 (0.0382) time: 2.9066 data: 0.0071 max mem: 33370 +Epoch: [28] [2110/2639] eta: 0:26:05 lr: 1.5900649972195196e-05 loss: 0.0391 (0.0382) time: 2.8789 data: 0.0071 max mem: 33370 +Epoch: [28] [2120/2639] eta: 0:25:35 lr: 1.5895808199657548e-05 loss: 0.0314 (0.0382) time: 2.8432 data: 0.0069 max mem: 33370 +Epoch: [28] [2130/2639] eta: 0:25:05 lr: 1.5890966263250306e-05 loss: 0.0314 (0.0382) time: 2.8118 data: 0.0070 max mem: 33370 +Epoch: [28] [2140/2639] eta: 0:24:35 lr: 1.588612416291246e-05 loss: 0.0364 (0.0383) time: 2.8338 data: 0.0071 max mem: 33370 +Epoch: [28] [2150/2639] eta: 0:24:05 lr: 1.5881281898582926e-05 loss: 0.0373 (0.0383) time: 2.8874 data: 0.0071 max mem: 33370 +Epoch: [28] [2160/2639] eta: 0:23:35 lr: 1.58764394702006e-05 loss: 0.0385 (0.0383) time: 2.8935 data: 0.0073 max mem: 33370 +Epoch: [28] [2170/2639] eta: 0:23:06 lr: 1.587159687770431e-05 loss: 0.0375 (0.0383) time: 2.8685 data: 0.0075 max mem: 33370 +Epoch: [28] [2180/2639] eta: 0:22:36 lr: 1.5866754121032866e-05 loss: 0.0331 (0.0383) time: 2.8678 data: 0.0070 max mem: 33370 +Epoch: [28] [2190/2639] eta: 0:22:06 lr: 1.586191120012501e-05 loss: 0.0326 (0.0383) time: 2.8986 data: 0.0068 max mem: 33370 +Epoch: [28] [2200/2639] eta: 0:21:37 lr: 1.5857068114919464e-05 loss: 0.0386 (0.0383) time: 2.9124 data: 0.0069 max mem: 33370 +Epoch: [28] [2210/2639] eta: 0:21:07 lr: 1.585222486535489e-05 loss: 0.0388 (0.0383) time: 2.9004 data: 0.0072 max mem: 33370 +Epoch: [28] [2220/2639] eta: 0:20:37 lr: 1.584738145136991e-05 loss: 0.0365 (0.0384) time: 2.8882 data: 0.0077 max mem: 33370 +Epoch: [28] [2230/2639] eta: 0:20:08 lr: 1.5842537872903103e-05 loss: 0.0365 (0.0384) time: 2.8479 data: 0.0079 max mem: 33370 +Epoch: [28] [2240/2639] eta: 0:19:38 lr: 1.5837694129893007e-05 loss: 0.0355 (0.0384) time: 2.8149 data: 0.0075 max mem: 33370 +Epoch: [28] [2250/2639] eta: 0:19:08 lr: 1.583285022227811e-05 loss: 0.0348 (0.0384) time: 2.8412 data: 0.0074 max mem: 33370 +Epoch: [28] [2260/2639] eta: 0:18:38 lr: 1.582800614999686e-05 loss: 0.0373 (0.0384) time: 2.8217 data: 0.0073 max mem: 33370 +Epoch: [28] [2270/2639] eta: 0:18:08 lr: 1.582316191298767e-05 loss: 0.0426 (0.0384) time: 2.7831 data: 0.0073 max mem: 33370 +Epoch: [28] [2280/2639] eta: 0:17:39 lr: 1.5818317511188887e-05 loss: 0.0398 (0.0384) time: 2.8206 data: 0.0073 max mem: 33370 +Epoch: [28] [2290/2639] eta: 0:17:09 lr: 1.581347294453884e-05 loss: 0.0372 (0.0384) time: 2.8249 data: 0.0071 max mem: 33370 +Epoch: [28] [2300/2639] eta: 0:16:39 lr: 1.5808628212975785e-05 loss: 0.0345 (0.0384) time: 2.8175 data: 0.0073 max mem: 33370 +Epoch: [28] [2310/2639] eta: 0:16:10 lr: 1.5803783316437963e-05 loss: 0.0345 (0.0384) time: 2.8508 data: 0.0074 max mem: 33370 +Epoch: [28] [2320/2639] eta: 0:15:40 lr: 1.5798938254863543e-05 loss: 0.0349 (0.0384) time: 2.8775 data: 0.0072 max mem: 33370 +Epoch: [28] [2330/2639] eta: 0:15:11 lr: 1.5794093028190682e-05 loss: 0.0324 (0.0384) time: 2.8740 data: 0.0071 max mem: 33370 +Epoch: [28] [2340/2639] eta: 0:14:41 lr: 1.578924763635746e-05 loss: 0.0324 (0.0384) time: 2.8809 data: 0.0072 max mem: 33370 +Epoch: [28] [2350/2639] eta: 0:14:11 lr: 1.5784402079301938e-05 loss: 0.0315 (0.0384) time: 2.8912 data: 0.0071 max mem: 33370 +Epoch: [28] [2360/2639] eta: 0:13:42 lr: 1.577955635696211e-05 loss: 0.0327 (0.0384) time: 2.8891 data: 0.0071 max mem: 33370 +Epoch: [28] [2370/2639] eta: 0:13:12 lr: 1.577471046927595e-05 loss: 0.0306 (0.0384) time: 2.8609 data: 0.0073 max mem: 33370 +Epoch: [28] [2380/2639] eta: 0:12:43 lr: 1.5769864416181366e-05 loss: 0.0285 (0.0384) time: 2.8521 data: 0.0076 max mem: 33370 +Epoch: [28] [2390/2639] eta: 0:12:13 lr: 1.5765018197616237e-05 loss: 0.0335 (0.0384) time: 2.8747 data: 0.0077 max mem: 33370 +Epoch: [28] [2400/2639] eta: 0:11:44 lr: 1.5760171813518387e-05 loss: 0.0343 (0.0384) time: 2.8438 data: 0.0079 max mem: 33370 +Epoch: [28] [2410/2639] eta: 0:11:14 lr: 1.5755325263825606e-05 loss: 0.0321 (0.0384) time: 2.8181 data: 0.0080 max mem: 33370 +Epoch: [28] [2420/2639] eta: 0:10:45 lr: 1.575047854847562e-05 loss: 0.0329 (0.0384) time: 2.8350 data: 0.0076 max mem: 33370 +Epoch: [28] [2430/2639] eta: 0:10:15 lr: 1.5745631667406135e-05 loss: 0.0364 (0.0384) time: 2.8399 data: 0.0076 max mem: 33370 +Epoch: [28] [2440/2639] eta: 0:09:45 lr: 1.5740784620554795e-05 loss: 0.0382 (0.0384) time: 2.8293 data: 0.0073 max mem: 33370 +Epoch: [28] [2450/2639] eta: 0:09:16 lr: 1.573593740785921e-05 loss: 0.0375 (0.0384) time: 2.8427 data: 0.0071 max mem: 33370 +Epoch: [28] [2460/2639] eta: 0:08:46 lr: 1.5731090029256926e-05 loss: 0.0334 (0.0384) time: 2.9104 data: 0.0074 max mem: 33370 +Epoch: [28] [2470/2639] eta: 0:08:17 lr: 1.5726242484685476e-05 loss: 0.0311 (0.0384) time: 2.9275 data: 0.0073 max mem: 33370 +Epoch: [28] [2480/2639] eta: 0:07:47 lr: 1.5721394774082314e-05 loss: 0.0336 (0.0384) time: 2.8365 data: 0.0072 max mem: 33370 +Epoch: [28] [2490/2639] eta: 0:07:18 lr: 1.5716546897384882e-05 loss: 0.0345 (0.0385) time: 2.8106 data: 0.0074 max mem: 33370 +Epoch: [28] [2500/2639] eta: 0:06:48 lr: 1.571169885453054e-05 loss: 0.0414 (0.0385) time: 2.8520 data: 0.0074 max mem: 33370 +Epoch: [28] [2510/2639] eta: 0:06:19 lr: 1.5706850645456633e-05 loss: 0.0407 (0.0385) time: 2.8790 data: 0.0075 max mem: 33370 +Epoch: [28] [2520/2639] eta: 0:05:50 lr: 1.570200227010046e-05 loss: 0.0364 (0.0385) time: 2.8958 data: 0.0075 max mem: 33370 +Epoch: [28] [2530/2639] eta: 0:05:20 lr: 1.5697153728399245e-05 loss: 0.0371 (0.0386) time: 2.8943 data: 0.0077 max mem: 33370 +Epoch: [28] [2540/2639] eta: 0:04:51 lr: 1.5692305020290206e-05 loss: 0.0371 (0.0386) time: 2.8739 data: 0.0076 max mem: 33370 +Epoch: [28] [2550/2639] eta: 0:04:21 lr: 1.5687456145710482e-05 loss: 0.0334 (0.0385) time: 2.8574 data: 0.0073 max mem: 33370 +Epoch: [28] [2560/2639] eta: 0:03:52 lr: 1.5682607104597195e-05 loss: 0.0317 (0.0385) time: 2.8748 data: 0.0072 max mem: 33370 +Epoch: [28] [2570/2639] eta: 0:03:22 lr: 1.5677757896887392e-05 loss: 0.0350 (0.0385) time: 2.9106 data: 0.0070 max mem: 33370 +Epoch: [28] [2580/2639] eta: 0:02:53 lr: 1.5672908522518114e-05 loss: 0.0405 (0.0386) time: 2.9003 data: 0.0071 max mem: 33370 +Epoch: [28] [2590/2639] eta: 0:02:24 lr: 1.5668058981426307e-05 loss: 0.0335 (0.0385) time: 2.8485 data: 0.0072 max mem: 33370 +Epoch: [28] [2600/2639] eta: 0:01:54 lr: 1.566320927354892e-05 loss: 0.0332 (0.0385) time: 2.8474 data: 0.0073 max mem: 33370 +Epoch: [28] [2610/2639] eta: 0:01:25 lr: 1.5658359398822817e-05 loss: 0.0381 (0.0385) time: 2.8674 data: 0.0072 max mem: 33370 +Epoch: [28] [2620/2639] eta: 0:00:55 lr: 1.565350935718485e-05 loss: 0.0345 (0.0385) time: 2.8460 data: 0.0070 max mem: 33370 +Epoch: [28] [2630/2639] eta: 0:00:26 lr: 1.564865914857179e-05 loss: 0.0335 (0.0385) time: 2.8452 data: 0.0072 max mem: 33370 +Epoch: [28] Total time: 2:09:24 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 16:33:32 time: 23.1684 data: 23.0633 max mem: 33370 +Test: [ 100/2573] eta: 0:13:38 time: 0.0750 data: 0.0013 max mem: 33370 +Test: [ 200/2573] eta: 0:08:06 time: 0.0771 data: 0.0014 max mem: 33370 +Test: [ 300/2573] eta: 0:06:09 time: 0.0795 data: 0.0013 max mem: 33370 +Test: [ 400/2573] eta: 0:05:06 time: 0.0787 data: 0.0013 max mem: 33370 +Test: [ 500/2573] eta: 0:04:26 time: 0.0783 data: 0.0013 max mem: 33370 +Test: [ 600/2573] eta: 0:03:57 time: 0.0781 data: 0.0014 max mem: 33370 +Test: [ 700/2573] eta: 0:03:34 time: 0.0777 data: 0.0014 max mem: 33370 +Test: [ 800/2573] eta: 0:03:15 time: 0.0815 data: 0.0014 max mem: 33370 +Test: [ 900/2573] eta: 0:02:58 time: 0.0785 data: 0.0013 max mem: 33370 +Test: [1000/2573] eta: 0:02:43 time: 0.0791 data: 0.0013 max mem: 33370 +Test: [1100/2573] eta: 0:02:29 time: 0.0804 data: 0.0015 max mem: 33370 +Test: [1200/2573] eta: 0:02:17 time: 0.0789 data: 0.0014 max mem: 33370 +Test: [1300/2573] eta: 0:02:05 time: 0.0788 data: 0.0014 max mem: 33370 +Test: [1400/2573] eta: 0:01:53 time: 0.0768 data: 0.0014 max mem: 33370 +Test: [1500/2573] eta: 0:01:42 time: 0.0789 data: 0.0013 max mem: 33370 +Test: [1600/2573] eta: 0:01:32 time: 0.0824 data: 0.0014 max mem: 33370 +Test: [1700/2573] eta: 0:01:21 time: 0.0771 data: 0.0013 max mem: 33370 +Test: [1800/2573] eta: 0:01:11 time: 0.0802 data: 0.0014 max mem: 33370 +Test: [1900/2573] eta: 0:01:01 time: 0.0773 data: 0.0014 max mem: 33370 +Test: [2000/2573] eta: 0:00:52 time: 0.0786 data: 0.0013 max mem: 33370 +Test: [2100/2573] eta: 0:00:42 time: 0.0792 data: 0.0012 max mem: 33370 +Test: [2200/2573] eta: 0:00:33 time: 0.0814 data: 0.0015 max mem: 33370 +Test: [2300/2573] eta: 0:00:24 time: 0.0811 data: 0.0013 max mem: 33370 +Test: [2400/2573] eta: 0:00:15 time: 0.0761 data: 0.0014 max mem: 33370 +Test: [2500/2573] eta: 0:00:06 time: 0.0792 data: 0.0013 max mem: 33370 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: Total time: 0:03:51 +Final results: +Mean IoU is 63.74 + + precision@0.5 = 71.81 + precision@0.6 = 66.56 + precision@0.7 = 60.07 + precision@0.8 = 48.61 + precision@0.9 = 24.65 + overall IoU = 61.48 + +Average object IoU 63.73815528256532 +Overall IoU 61.483734130859375 +Better epoch: 28 + +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [29] [ 0/2639] eta: 4:00:49 lr: 1.5644293818004067e-05 loss: 0.0296 (0.0296) time: 5.4755 data: 2.3017 max mem: 33370 +Epoch: [29] [ 10/2639] eta: 2:12:19 lr: 1.563944329196405e-05 loss: 0.0295 (0.0321) time: 3.0198 data: 0.2156 max mem: 33370 +Epoch: [29] [ 20/2639] eta: 2:08:31 lr: 1.5634592598765377e-05 loss: 0.0364 (0.0391) time: 2.8177 data: 0.0071 max mem: 33370 +Epoch: [29] [ 30/2639] eta: 2:07:49 lr: 1.562974173834467e-05 loss: 0.0378 (0.0393) time: 2.8952 data: 0.0073 max mem: 33370 +Epoch: [29] [ 40/2639] eta: 2:06:30 lr: 1.5624890710638484e-05 loss: 0.0339 (0.0379) time: 2.8956 data: 0.0073 max mem: 33370 +Epoch: [29] [ 50/2639] eta: 2:05:59 lr: 1.562003951558335e-05 loss: 0.0355 (0.0388) time: 2.8890 data: 0.0073 max mem: 33370 +Epoch: [29] [ 60/2639] eta: 2:05:27 lr: 1.561518815311573e-05 loss: 0.0353 (0.0376) time: 2.9150 data: 0.0073 max mem: 33370 +Epoch: [29] [ 70/2639] eta: 2:04:44 lr: 1.5610336623172064e-05 loss: 0.0309 (0.0374) time: 2.8980 data: 0.0073 max mem: 33370 +Epoch: [29] [ 80/2639] eta: 2:04:11 lr: 1.560548492568872e-05 loss: 0.0341 (0.0374) time: 2.8915 data: 0.0074 max mem: 33370 +Epoch: [29] [ 90/2639] eta: 2:03:27 lr: 1.5600633060602048e-05 loss: 0.0427 (0.0384) time: 2.8796 data: 0.0074 max mem: 33370 +Epoch: [29] [ 100/2639] eta: 2:03:04 lr: 1.5595781027848318e-05 loss: 0.0437 (0.0386) time: 2.8941 data: 0.0076 max mem: 33370 +Epoch: [29] [ 110/2639] eta: 2:02:33 lr: 1.5590928827363792e-05 loss: 0.0372 (0.0387) time: 2.9142 data: 0.0077 max mem: 33370 +Epoch: [29] [ 120/2639] eta: 2:01:51 lr: 1.5586076459084648e-05 loss: 0.0340 (0.0383) time: 2.8719 data: 0.0077 max mem: 33370 +Epoch: [29] [ 130/2639] eta: 2:01:03 lr: 1.5581223922947047e-05 loss: 0.0332 (0.0380) time: 2.8249 data: 0.0079 max mem: 33370 +Epoch: [29] [ 140/2639] eta: 2:00:21 lr: 1.55763712188871e-05 loss: 0.0332 (0.0379) time: 2.8145 data: 0.0079 max mem: 33370 +Epoch: [29] [ 150/2639] eta: 1:59:55 lr: 1.5571518346840846e-05 loss: 0.0309 (0.0375) time: 2.8649 data: 0.0077 max mem: 33370 +Epoch: [29] [ 160/2639] eta: 1:59:20 lr: 1.5566665306744317e-05 loss: 0.0328 (0.0374) time: 2.8783 data: 0.0072 max mem: 33370 +Epoch: [29] [ 170/2639] eta: 1:58:51 lr: 1.5561812098533456e-05 loss: 0.0359 (0.0375) time: 2.8695 data: 0.0069 max mem: 33370 +Epoch: [29] [ 180/2639] eta: 1:58:28 lr: 1.5556958722144196e-05 loss: 0.0364 (0.0372) time: 2.9085 data: 0.0070 max mem: 33370 +Epoch: [29] [ 190/2639] eta: 1:57:55 lr: 1.5552105177512397e-05 loss: 0.0295 (0.0371) time: 2.8960 data: 0.0072 max mem: 33370 +Epoch: [29] [ 200/2639] eta: 1:57:21 lr: 1.5547251464573894e-05 loss: 0.0295 (0.0368) time: 2.8531 data: 0.0075 max mem: 33370 +Epoch: [29] [ 210/2639] eta: 1:56:56 lr: 1.5542397583264452e-05 loss: 0.0321 (0.0367) time: 2.8830 data: 0.0075 max mem: 33370 +Epoch: [29] [ 220/2639] eta: 1:56:27 lr: 1.553754353351982e-05 loss: 0.0307 (0.0365) time: 2.9056 data: 0.0074 max mem: 33370 +Epoch: [29] [ 230/2639] eta: 1:55:55 lr: 1.5532689315275662e-05 loss: 0.0316 (0.0365) time: 2.8742 data: 0.0075 max mem: 33370 +Epoch: [29] [ 240/2639] eta: 1:55:26 lr: 1.5527834928467627e-05 loss: 0.0346 (0.0364) time: 2.8707 data: 0.0078 max mem: 33370 +Epoch: [29] [ 250/2639] eta: 1:54:51 lr: 1.55229803730313e-05 loss: 0.0341 (0.0364) time: 2.8547 data: 0.0079 max mem: 33370 +Epoch: [29] [ 260/2639] eta: 1:54:20 lr: 1.5518125648902225e-05 loss: 0.0328 (0.0364) time: 2.8449 data: 0.0079 max mem: 33370 +Epoch: [29] [ 270/2639] eta: 1:53:55 lr: 1.55132707560159e-05 loss: 0.0342 (0.0364) time: 2.8942 data: 0.0079 max mem: 33370 +Epoch: [29] [ 280/2639] eta: 1:53:29 lr: 1.5508415694307774e-05 loss: 0.0329 (0.0362) time: 2.9226 data: 0.0075 max mem: 33370 +Epoch: [29] [ 290/2639] eta: 1:52:59 lr: 1.550356046371324e-05 loss: 0.0317 (0.0361) time: 2.8941 data: 0.0070 max mem: 33370 +Epoch: [29] [ 300/2639] eta: 1:52:29 lr: 1.5498705064167667e-05 loss: 0.0319 (0.0361) time: 2.8744 data: 0.0071 max mem: 33370 +Epoch: [29] [ 310/2639] eta: 1:51:57 lr: 1.549384949560635e-05 loss: 0.0370 (0.0363) time: 2.8581 data: 0.0075 max mem: 33370 +Epoch: [29] [ 320/2639] eta: 1:51:28 lr: 1.548899375796456e-05 loss: 0.0331 (0.0361) time: 2.8579 data: 0.0074 max mem: 33370 +Epoch: [29] [ 330/2639] eta: 1:50:57 lr: 1.5484137851177497e-05 loss: 0.0289 (0.0359) time: 2.8688 data: 0.0072 max mem: 33370 +Epoch: [29] [ 340/2639] eta: 1:50:26 lr: 1.547928177518034e-05 loss: 0.0331 (0.0359) time: 2.8526 data: 0.0073 max mem: 33370 +Epoch: [29] [ 350/2639] eta: 1:49:54 lr: 1.5474425529908186e-05 loss: 0.0352 (0.0361) time: 2.8436 data: 0.0075 max mem: 33370 +Epoch: [29] [ 360/2639] eta: 1:49:21 lr: 1.5469569115296133e-05 loss: 0.0346 (0.0360) time: 2.8286 data: 0.0076 max mem: 33370 +Epoch: [29] [ 370/2639] eta: 1:48:51 lr: 1.5464712531279177e-05 loss: 0.0343 (0.0362) time: 2.8362 data: 0.0075 max mem: 33370 +Epoch: [29] [ 380/2639] eta: 1:48:19 lr: 1.5459855777792308e-05 loss: 0.0339 (0.0361) time: 2.8350 data: 0.0074 max mem: 33370 +Epoch: [29] [ 390/2639] eta: 1:47:45 lr: 1.5454998854770456e-05 loss: 0.0300 (0.0359) time: 2.8045 data: 0.0074 max mem: 33370 +Epoch: [29] [ 400/2639] eta: 1:47:13 lr: 1.5450141762148488e-05 loss: 0.0341 (0.0362) time: 2.8092 data: 0.0071 max mem: 33370 +Epoch: [29] [ 410/2639] eta: 1:46:44 lr: 1.544528449986125e-05 loss: 0.0413 (0.0362) time: 2.8442 data: 0.0073 max mem: 33370 +Epoch: [29] [ 420/2639] eta: 1:46:12 lr: 1.544042706784351e-05 loss: 0.0290 (0.0360) time: 2.8369 data: 0.0075 max mem: 33370 +Epoch: [29] [ 430/2639] eta: 1:45:43 lr: 1.543556946603002e-05 loss: 0.0302 (0.0361) time: 2.8365 data: 0.0073 max mem: 33370 +Epoch: [29] [ 440/2639] eta: 1:45:13 lr: 1.5430711694355456e-05 loss: 0.0332 (0.0360) time: 2.8572 data: 0.0074 max mem: 33370 +Epoch: [29] [ 450/2639] eta: 1:44:41 lr: 1.5425853752754473e-05 loss: 0.0277 (0.0359) time: 2.8263 data: 0.0072 max mem: 33370 +Epoch: [29] [ 460/2639] eta: 1:44:13 lr: 1.542099564116164e-05 loss: 0.0314 (0.0360) time: 2.8431 data: 0.0075 max mem: 33370 +Epoch: [29] [ 470/2639] eta: 1:43:48 lr: 1.5416137359511528e-05 loss: 0.0315 (0.0360) time: 2.9190 data: 0.0074 max mem: 33370 +Epoch: [29] [ 480/2639] eta: 1:43:21 lr: 1.541127890773861e-05 loss: 0.0328 (0.0360) time: 2.9288 data: 0.0073 max mem: 33370 +Epoch: [29] [ 490/2639] eta: 1:42:53 lr: 1.540642028577735e-05 loss: 0.0333 (0.0360) time: 2.8968 data: 0.0074 max mem: 33370 +Epoch: [29] [ 500/2639] eta: 1:42:26 lr: 1.5401561493562133e-05 loss: 0.0351 (0.0363) time: 2.8997 data: 0.0070 max mem: 33370 +Epoch: [29] [ 510/2639] eta: 1:42:00 lr: 1.5396702531027326e-05 loss: 0.0413 (0.0363) time: 2.9231 data: 0.0070 max mem: 33370 +Epoch: [29] [ 520/2639] eta: 1:41:30 lr: 1.5391843398107218e-05 loss: 0.0352 (0.0363) time: 2.8977 data: 0.0070 max mem: 33370 +Epoch: [29] [ 530/2639] eta: 1:41:03 lr: 1.5386984094736075e-05 loss: 0.0336 (0.0362) time: 2.8846 data: 0.0071 max mem: 33370 +Epoch: [29] [ 540/2639] eta: 1:40:35 lr: 1.5382124620848095e-05 loss: 0.0352 (0.0363) time: 2.8971 data: 0.0074 max mem: 33370 +Epoch: [29] [ 550/2639] eta: 1:40:06 lr: 1.5377264976377444e-05 loss: 0.0369 (0.0363) time: 2.8750 data: 0.0075 max mem: 33370 +Epoch: [29] [ 560/2639] eta: 1:39:34 lr: 1.537240516125822e-05 loss: 0.0336 (0.0362) time: 2.8327 data: 0.0072 max mem: 33370 +Epoch: [29] [ 570/2639] eta: 1:39:07 lr: 1.5367545175424496e-05 loss: 0.0336 (0.0363) time: 2.8606 data: 0.0070 max mem: 33370 +Epoch: [29] [ 580/2639] eta: 1:38:39 lr: 1.5362685018810267e-05 loss: 0.0319 (0.0361) time: 2.9097 data: 0.0071 max mem: 33370 +Epoch: [29] [ 590/2639] eta: 1:38:12 lr: 1.5357824691349514e-05 loss: 0.0312 (0.0362) time: 2.9066 data: 0.0071 max mem: 33370 +Epoch: [29] [ 600/2639] eta: 1:37:44 lr: 1.5352964192976137e-05 loss: 0.0346 (0.0362) time: 2.9119 data: 0.0075 max mem: 33370 +Epoch: [29] [ 610/2639] eta: 1:37:17 lr: 1.5348103523624016e-05 loss: 0.0298 (0.0361) time: 2.9144 data: 0.0079 max mem: 33370 +Epoch: [29] [ 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data: 0.0073 max mem: 33370 +Epoch: [29] [ 780/2639] eta: 1:29:02 lr: 1.5265445920566833e-05 loss: 0.0336 (0.0360) time: 2.8554 data: 0.0075 max mem: 33370 +Epoch: [29] [ 790/2639] eta: 1:28:32 lr: 1.5260582162232188e-05 loss: 0.0329 (0.0360) time: 2.8321 data: 0.0077 max mem: 33370 +Epoch: [29] [ 800/2639] eta: 1:28:01 lr: 1.5255718231652896e-05 loss: 0.0288 (0.0359) time: 2.7996 data: 0.0078 max mem: 33370 +Epoch: [29] [ 810/2639] eta: 1:27:33 lr: 1.5250854128761821e-05 loss: 0.0334 (0.0360) time: 2.8329 data: 0.0075 max mem: 33370 +Epoch: [29] [ 820/2639] eta: 1:27:03 lr: 1.5245989853491801e-05 loss: 0.0353 (0.0361) time: 2.8559 data: 0.0076 max mem: 33370 +Epoch: [29] [ 830/2639] eta: 1:26:34 lr: 1.5241125405775605e-05 loss: 0.0351 (0.0361) time: 2.8590 data: 0.0076 max mem: 33370 +Epoch: [29] [ 840/2639] eta: 1:26:05 lr: 1.5236260785545973e-05 loss: 0.0362 (0.0362) time: 2.8650 data: 0.0074 max mem: 33370 +Epoch: [29] [ 850/2639] eta: 1:25:36 lr: 1.5231395992735566e-05 loss: 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1.5192471429249516e-05 loss: 0.0348 (0.0365) time: 2.8726 data: 0.0074 max mem: 33370 +Epoch: [29] [ 940/2639] eta: 1:21:19 lr: 1.5187605080174418e-05 loss: 0.0350 (0.0365) time: 2.8690 data: 0.0074 max mem: 33370 +Epoch: [29] [ 950/2639] eta: 1:20:50 lr: 1.5182738557842569e-05 loss: 0.0348 (0.0365) time: 2.8636 data: 0.0074 max mem: 33370 +Epoch: [29] [ 960/2639] eta: 1:20:21 lr: 1.5177871862186075e-05 loss: 0.0404 (0.0366) time: 2.8646 data: 0.0074 max mem: 33370 +Epoch: [29] [ 970/2639] eta: 1:19:51 lr: 1.5173004993137028e-05 loss: 0.0361 (0.0365) time: 2.8317 data: 0.0074 max mem: 33370 +Epoch: [29] [ 980/2639] eta: 1:19:21 lr: 1.5168137950627429e-05 loss: 0.0276 (0.0365) time: 2.7920 data: 0.0074 max mem: 33370 +Epoch: [29] [ 990/2639] eta: 1:20:40 lr: 1.5163270734589267e-05 loss: 0.0335 (0.0366) time: 6.0433 data: 1.1452 max mem: 33370 +Epoch: [29] [1000/2639] eta: 1:20:20 lr: 1.5158403344954448e-05 loss: 0.0358 (0.0365) time: 6.4200 data: 1.4698 max mem: 33370 +Epoch: [29] 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mem: 33370 +Epoch: [29] [1090/2639] eta: 1:17:13 lr: 1.5114589015133098e-05 loss: 0.0363 (0.0364) time: 2.8618 data: 0.0073 max mem: 33370 +Epoch: [29] [1100/2639] eta: 1:16:41 lr: 1.510971988577606e-05 loss: 0.0336 (0.0364) time: 2.8432 data: 0.0076 max mem: 33370 +Epoch: [29] [1110/2639] eta: 1:16:10 lr: 1.5104850582070101e-05 loss: 0.0325 (0.0364) time: 2.8586 data: 0.0075 max mem: 33370 +Epoch: [29] [1120/2639] eta: 1:15:38 lr: 1.509998110394653e-05 loss: 0.0325 (0.0363) time: 2.8493 data: 0.0073 max mem: 33370 +Epoch: [29] [1130/2639] eta: 1:15:06 lr: 1.509511145133659e-05 loss: 0.0327 (0.0363) time: 2.8411 data: 0.0073 max mem: 33370 +Epoch: [29] [1140/2639] eta: 1:14:34 lr: 1.5090241624171491e-05 loss: 0.0323 (0.0363) time: 2.8374 data: 0.0073 max mem: 33370 +Epoch: [29] [1150/2639] eta: 1:14:02 lr: 1.508537162238237e-05 loss: 0.0323 (0.0363) time: 2.8102 data: 0.0073 max mem: 33370 +Epoch: [29] [1160/2639] eta: 1:13:31 lr: 1.508050144590033e-05 loss: 0.0320 (0.0363) time: 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0.0336 (0.0364) time: 2.8834 data: 0.0073 max mem: 33370 +Epoch: [29] [1250/2639] eta: 1:08:51 lr: 1.5036661984985662e-05 loss: 0.0294 (0.0363) time: 2.8785 data: 0.0072 max mem: 33370 +Epoch: [29] [1260/2639] eta: 1:08:21 lr: 1.5031790057773256e-05 loss: 0.0293 (0.0363) time: 2.9001 data: 0.0073 max mem: 33370 +Epoch: [29] [1270/2639] eta: 1:07:50 lr: 1.5026917955106545e-05 loss: 0.0358 (0.0364) time: 2.9018 data: 0.0070 max mem: 33370 +Epoch: [29] [1280/2639] eta: 1:07:20 lr: 1.5022045676916008e-05 loss: 0.0382 (0.0364) time: 2.8947 data: 0.0072 max mem: 33370 +Epoch: [29] [1290/2639] eta: 1:06:49 lr: 1.501717322313205e-05 loss: 0.0333 (0.0364) time: 2.8886 data: 0.0073 max mem: 33370 +Epoch: [29] [1300/2639] eta: 1:06:18 lr: 1.5012300593685044e-05 loss: 0.0321 (0.0364) time: 2.8499 data: 0.0070 max mem: 33370 +Epoch: [29] [1310/2639] eta: 1:05:47 lr: 1.5007427788505293e-05 loss: 0.0321 (0.0364) time: 2.8578 data: 0.0071 max mem: 33370 +Epoch: [29] [1320/2639] eta: 1:05:16 lr: 1.5002554807523067e-05 loss: 0.0291 (0.0363) time: 2.8838 data: 0.0073 max mem: 33370 +Epoch: [29] [1330/2639] eta: 1:04:46 lr: 1.4997681650668557e-05 loss: 0.0291 (0.0364) time: 2.8998 data: 0.0074 max mem: 33370 +Epoch: [29] [1340/2639] eta: 1:04:16 lr: 1.4992808317871931e-05 loss: 0.0341 (0.0364) time: 2.9012 data: 0.0071 max mem: 33370 +Epoch: [29] [1350/2639] eta: 1:03:46 lr: 1.4987934809063275e-05 loss: 0.0351 (0.0364) time: 2.8988 data: 0.0070 max mem: 33370 +Epoch: [29] [1360/2639] eta: 1:03:14 lr: 1.4983061124172642e-05 loss: 0.0351 (0.0364) time: 2.8679 data: 0.0071 max mem: 33370 +Epoch: [29] [1370/2639] eta: 1:02:44 lr: 1.497818726313003e-05 loss: 0.0370 (0.0364) time: 2.8394 data: 0.0073 max mem: 33370 +Epoch: [29] [1380/2639] eta: 1:02:13 lr: 1.4973313225865374e-05 loss: 0.0398 (0.0365) time: 2.8557 data: 0.0075 max mem: 33370 +Epoch: [29] [1390/2639] eta: 1:01:42 lr: 1.4968439012308563e-05 loss: 0.0377 (0.0365) time: 2.8441 data: 0.0074 max mem: 33370 +Epoch: [29] [1400/2639] eta: 1:01:11 lr: 1.4963564622389425e-05 loss: 0.0329 (0.0365) time: 2.8297 data: 0.0074 max mem: 33370 +Epoch: [29] [1410/2639] eta: 1:00:41 lr: 1.4958690056037752e-05 loss: 0.0309 (0.0365) time: 2.8479 data: 0.0074 max mem: 33370 +Epoch: [29] [1420/2639] eta: 1:00:10 lr: 1.4953815313183261e-05 loss: 0.0291 (0.0364) time: 2.8372 data: 0.0071 max mem: 33370 +Epoch: [29] [1430/2639] eta: 0:59:40 lr: 1.4948940393755633e-05 loss: 0.0304 (0.0364) time: 2.8503 data: 0.0073 max mem: 33370 +Epoch: [29] [1440/2639] eta: 0:59:09 lr: 1.4944065297684484e-05 loss: 0.0372 (0.0364) time: 2.8731 data: 0.0075 max mem: 33370 +Epoch: [29] [1450/2639] eta: 0:58:39 lr: 1.4939190024899382e-05 loss: 0.0363 (0.0365) time: 2.8507 data: 0.0074 max mem: 33370 +Epoch: [29] [1460/2639] eta: 0:58:08 lr: 1.4934314575329838e-05 loss: 0.0337 (0.0364) time: 2.8633 data: 0.0074 max mem: 33370 +Epoch: [29] [1470/2639] eta: 0:57:38 lr: 1.4929438948905319e-05 loss: 0.0346 (0.0365) time: 2.8915 data: 0.0072 max mem: 33370 +Epoch: [29] [1480/2639] eta: 0:57:08 lr: 1.4924563145555217e-05 loss: 0.0393 (0.0365) time: 2.8909 data: 0.0072 max mem: 33370 +Epoch: [29] [1490/2639] eta: 0:56:38 lr: 1.4919687165208897e-05 loss: 0.0334 (0.0366) time: 2.8451 data: 0.0072 max mem: 33370 +Epoch: [29] [1500/2639] eta: 0:56:07 lr: 1.4914811007795647e-05 loss: 0.0334 (0.0366) time: 2.8255 data: 0.0072 max mem: 33370 +Epoch: [29] [1510/2639] eta: 0:55:36 lr: 1.4909934673244725e-05 loss: 0.0350 (0.0366) time: 2.8308 data: 0.0072 max mem: 33370 +Epoch: [29] [1520/2639] eta: 0:55:06 lr: 1.4905058161485299e-05 loss: 0.0405 (0.0367) time: 2.8354 data: 0.0076 max mem: 33370 +Epoch: [29] [1530/2639] eta: 0:54:36 lr: 1.4900181472446528e-05 loss: 0.0394 (0.0367) time: 2.8697 data: 0.0076 max mem: 33370 +Epoch: [29] [1540/2639] eta: 0:54:06 lr: 1.4895304606057475e-05 loss: 0.0340 (0.0367) time: 2.8689 data: 0.0076 max mem: 33370 +Epoch: [29] [1550/2639] eta: 0:53:35 lr: 1.4890427562247183e-05 loss: 0.0342 (0.0367) time: 2.8313 data: 0.0077 max mem: 33370 +Epoch: [29] [1560/2639] eta: 0:53:05 lr: 1.4885550340944612e-05 loss: 0.0367 (0.0368) time: 2.8478 data: 0.0075 max mem: 33370 +Epoch: [29] [1570/2639] eta: 0:52:35 lr: 1.4880672942078694e-05 loss: 0.0312 (0.0367) time: 2.8704 data: 0.0074 max mem: 33370 +Epoch: [29] [1580/2639] eta: 0:52:05 lr: 1.4875795365578282e-05 loss: 0.0312 (0.0368) time: 2.8401 data: 0.0075 max mem: 33370 +Epoch: [29] [1590/2639] eta: 0:51:35 lr: 1.4870917611372195e-05 loss: 0.0308 (0.0368) time: 2.8554 data: 0.0072 max mem: 33370 +Epoch: [29] [1600/2639] eta: 0:51:05 lr: 1.4866039679389179e-05 loss: 0.0316 (0.0368) time: 2.8753 data: 0.0071 max mem: 33370 +Epoch: [29] [1610/2639] eta: 0:50:35 lr: 1.4861161569557943e-05 loss: 0.0350 (0.0368) time: 2.8527 data: 0.0074 max mem: 33370 +Epoch: [29] [1620/2639] eta: 0:50:05 lr: 1.485628328180714e-05 loss: 0.0338 (0.0368) time: 2.8847 data: 0.0077 max mem: 33370 +Epoch: [29] [1630/2639] eta: 0:49:35 lr: 1.4851404816065346e-05 loss: 0.0301 (0.0368) time: 2.9255 data: 0.0074 max mem: 33370 +Epoch: [29] [1640/2639] eta: 0:49:05 lr: 1.4846526172261111e-05 loss: 0.0301 (0.0368) time: 2.9171 data: 0.0071 max mem: 33370 +Epoch: [29] [1650/2639] eta: 0:48:36 lr: 1.484164735032291e-05 loss: 0.0315 (0.0368) time: 2.8952 data: 0.0074 max mem: 33370 +Epoch: [29] [1660/2639] eta: 0:48:06 lr: 1.4836768350179176e-05 loss: 0.0309 (0.0367) time: 2.8804 data: 0.0075 max mem: 33370 +Epoch: [29] [1670/2639] eta: 0:47:36 lr: 1.4831889171758276e-05 loss: 0.0305 (0.0367) time: 2.8863 data: 0.0073 max mem: 33370 +Epoch: [29] [1680/2639] eta: 0:47:06 lr: 1.4827009814988536e-05 loss: 0.0325 (0.0367) time: 2.8786 data: 0.0074 max mem: 33370 +Epoch: [29] [1690/2639] eta: 0:46:36 lr: 1.4822130279798205e-05 loss: 0.0325 (0.0367) time: 2.8813 data: 0.0075 max mem: 33370 +Epoch: [29] [1700/2639] eta: 0:46:06 lr: 1.4817250566115507e-05 loss: 0.0332 (0.0367) time: 2.8720 data: 0.0075 max mem: 33370 +Epoch: [29] [1710/2639] eta: 0:45:36 lr: 1.4812370673868578e-05 loss: 0.0323 (0.0367) time: 2.8647 data: 0.0075 max mem: 33370 +Epoch: [29] [1720/2639] eta: 0:45:06 lr: 1.4807490602985533e-05 loss: 0.0341 (0.0367) time: 2.8710 data: 0.0076 max mem: 33370 +Epoch: [29] [1730/2639] eta: 0:44:37 lr: 1.4802610353394397e-05 loss: 0.0331 (0.0367) time: 2.8904 data: 0.0073 max mem: 33370 +Epoch: [29] [1740/2639] eta: 0:44:07 lr: 1.4797729925023169e-05 loss: 0.0353 (0.0367) time: 2.8813 data: 0.0073 max mem: 33370 +Epoch: [29] [1750/2639] eta: 0:43:37 lr: 1.4792849317799768e-05 loss: 0.0413 (0.0367) time: 2.8505 data: 0.0074 max mem: 33370 +Epoch: [29] [1760/2639] eta: 0:43:08 lr: 1.4787968531652083e-05 loss: 0.0378 (0.0367) time: 2.9075 data: 0.0073 max mem: 33370 +Epoch: [29] [1770/2639] eta: 0:42:38 lr: 1.4783087566507922e-05 loss: 0.0363 (0.0367) time: 2.9434 data: 0.0073 max mem: 33370 +Epoch: [29] [1780/2639] eta: 0:42:08 lr: 1.477820642229506e-05 loss: 0.0333 (0.0367) time: 2.8994 data: 0.0072 max mem: 33370 +Epoch: [29] 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2.8675 data: 0.0075 max mem: 33370 +Epoch: [29] [1950/2639] eta: 0:33:43 lr: 1.4695199502897322e-05 loss: 0.0307 (0.0368) time: 2.8244 data: 0.0073 max mem: 33370 +Epoch: [29] [1960/2639] eta: 0:33:14 lr: 1.4690315123031683e-05 loss: 0.0345 (0.0368) time: 2.8353 data: 0.0070 max mem: 33370 +Epoch: [29] [1970/2639] eta: 0:32:44 lr: 1.468543056271422e-05 loss: 0.0349 (0.0368) time: 2.8571 data: 0.0075 max mem: 33370 +Epoch: [29] [1980/2639] eta: 0:32:15 lr: 1.4680545821871555e-05 loss: 0.0318 (0.0368) time: 2.8683 data: 0.0074 max mem: 33370 +Epoch: [29] [1990/2639] eta: 0:31:45 lr: 1.4675660900430285e-05 loss: 0.0357 (0.0368) time: 2.8703 data: 0.0068 max mem: 33370 +Epoch: [29] [2000/2639] eta: 0:31:16 lr: 1.4670775798316921e-05 loss: 0.0333 (0.0368) time: 2.8863 data: 0.0070 max mem: 33370 +Epoch: [29] [2010/2639] eta: 0:30:46 lr: 1.4665890515457945e-05 loss: 0.0308 (0.0368) time: 2.9311 data: 0.0070 max mem: 33370 +Epoch: [29] [2020/2639] eta: 0:30:17 lr: 1.4661005051779752e-05 loss: 0.0331 (0.0368) time: 2.9186 data: 0.0069 max mem: 33370 +Epoch: [29] [2030/2639] eta: 0:29:47 lr: 1.465611940720871e-05 loss: 0.0292 (0.0367) time: 2.8824 data: 0.0069 max mem: 33370 +Epoch: [29] [2040/2639] eta: 0:29:18 lr: 1.4651233581671103e-05 loss: 0.0296 (0.0368) time: 2.8843 data: 0.0071 max mem: 33370 +Epoch: [29] [2050/2639] eta: 0:28:48 lr: 1.464634757509318e-05 loss: 0.0356 (0.0368) time: 2.8775 data: 0.0071 max mem: 33370 +Epoch: [29] [2060/2639] eta: 0:28:19 lr: 1.4641461387401115e-05 loss: 0.0393 (0.0368) time: 2.8952 data: 0.0070 max mem: 33370 +Epoch: [29] [2070/2639] eta: 0:27:49 lr: 1.4636575018521037e-05 loss: 0.0395 (0.0368) time: 2.9260 data: 0.0072 max mem: 33370 +Epoch: [29] [2080/2639] eta: 0:27:20 lr: 1.4631688468379008e-05 loss: 0.0395 (0.0368) time: 2.9139 data: 0.0072 max mem: 33370 +Epoch: [29] [2090/2639] eta: 0:26:50 lr: 1.4626801736901039e-05 loss: 0.0301 (0.0368) time: 2.8876 data: 0.0072 max mem: 33370 +Epoch: [29] [2100/2639] eta: 0:26:21 lr: 1.4621914824013078e-05 loss: 0.0303 (0.0368) time: 2.8696 data: 0.0075 max mem: 33370 +Epoch: [29] [2110/2639] eta: 0:25:51 lr: 1.461702772964102e-05 loss: 0.0340 (0.0368) time: 2.8691 data: 0.0078 max mem: 33370 +Epoch: [29] [2120/2639] eta: 0:25:22 lr: 1.4612140453710708e-05 loss: 0.0340 (0.0368) time: 2.8762 data: 0.0076 max mem: 33370 +Epoch: [29] [2130/2639] eta: 0:24:52 lr: 1.4607252996147902e-05 loss: 0.0396 (0.0368) time: 2.8848 data: 0.0071 max mem: 33370 +Epoch: [29] [2140/2639] eta: 0:24:23 lr: 1.4602365356878342e-05 loss: 0.0384 (0.0368) time: 2.8849 data: 0.0072 max mem: 33370 +Epoch: [29] [2150/2639] eta: 0:23:54 lr: 1.4597477535827671e-05 loss: 0.0312 (0.0368) time: 2.8767 data: 0.0073 max mem: 33370 +Epoch: [29] [2160/2639] eta: 0:23:24 lr: 1.459258953292151e-05 loss: 0.0306 (0.0368) time: 2.8559 data: 0.0071 max mem: 33370 +Epoch: [29] [2170/2639] eta: 0:22:55 lr: 1.458770134808539e-05 loss: 0.0304 (0.0368) time: 2.8435 data: 0.0071 max mem: 33370 +Epoch: [29] [2180/2639] eta: 0:22:25 lr: 1.458281298124481e-05 loss: 0.0295 (0.0367) time: 2.8466 data: 0.0071 max mem: 33370 +Epoch: [29] [2190/2639] eta: 0:21:56 lr: 1.4577924432325185e-05 loss: 0.0329 (0.0368) time: 2.8628 data: 0.0074 max mem: 33370 +Epoch: [29] [2200/2639] eta: 0:21:26 lr: 1.4573035701251897e-05 loss: 0.0350 (0.0368) time: 2.8760 data: 0.0074 max mem: 33370 +Epoch: [29] [2210/2639] eta: 0:20:57 lr: 1.4568146787950252e-05 loss: 0.0357 (0.0368) time: 2.9046 data: 0.0069 max mem: 33370 +Epoch: [29] [2220/2639] eta: 0:20:27 lr: 1.4563257692345508e-05 loss: 0.0361 (0.0368) time: 2.8798 data: 0.0070 max mem: 33370 +Epoch: [29] [2230/2639] eta: 0:19:58 lr: 1.4558368414362855e-05 loss: 0.0316 (0.0368) time: 2.8795 data: 0.0071 max mem: 33370 +Epoch: [29] [2240/2639] eta: 0:19:29 lr: 1.4553478953927435e-05 loss: 0.0346 (0.0368) time: 2.9254 data: 0.0072 max mem: 33370 +Epoch: [29] [2250/2639] eta: 0:18:59 lr: 1.454858931096432e-05 loss: 0.0333 (0.0368) time: 2.8944 data: 0.0073 max mem: 33370 +Epoch: [29] [2260/2639] eta: 0:18:30 lr: 1.4543699485398534e-05 loss: 0.0309 (0.0368) time: 2.8932 data: 0.0075 max mem: 33370 +Epoch: [29] [2270/2639] eta: 0:18:01 lr: 1.4538809477155033e-05 loss: 0.0341 (0.0368) time: 2.8943 data: 0.0074 max mem: 33370 +Epoch: [29] [2280/2639] eta: 0:17:31 lr: 1.4533919286158723e-05 loss: 0.0310 (0.0367) time: 2.8642 data: 0.0071 max mem: 33370 +Epoch: [29] [2290/2639] eta: 0:17:02 lr: 1.4529028912334438e-05 loss: 0.0315 (0.0367) time: 2.8859 data: 0.0072 max mem: 33370 +Epoch: [29] [2300/2639] eta: 0:16:32 lr: 1.4524138355606975e-05 loss: 0.0315 (0.0367) time: 2.8860 data: 0.0072 max mem: 33370 +Epoch: [29] [2310/2639] eta: 0:16:03 lr: 1.4519247615901044e-05 loss: 0.0274 (0.0367) time: 2.8503 data: 0.0072 max mem: 33370 +Epoch: [29] [2320/2639] eta: 0:15:34 lr: 1.4514356693141317e-05 loss: 0.0274 (0.0367) time: 2.8537 data: 0.0076 max mem: 33370 +Epoch: [29] [2330/2639] eta: 0:15:04 lr: 1.4509465587252396e-05 loss: 0.0271 (0.0366) time: 2.8372 data: 0.0079 max mem: 33370 +Epoch: [29] [2340/2639] eta: 0:14:35 lr: 1.4504574298158837e-05 loss: 0.0317 (0.0366) time: 2.8080 data: 0.0080 max mem: 33370 +Epoch: [29] [2350/2639] eta: 0:14:05 lr: 1.4499682825785112e-05 loss: 0.0379 (0.0367) time: 2.8272 data: 0.0074 max mem: 33370 +Epoch: [29] [2360/2639] eta: 0:13:36 lr: 1.449479117005566e-05 loss: 0.0373 (0.0367) time: 2.8722 data: 0.0072 max mem: 33370 +Epoch: [29] [2370/2639] eta: 0:13:07 lr: 1.448989933089485e-05 loss: 0.0346 (0.0367) time: 2.8659 data: 0.0073 max mem: 33370 +Epoch: [29] [2380/2639] eta: 0:12:37 lr: 1.4485007308226977e-05 loss: 0.0341 (0.0367) time: 2.8207 data: 0.0073 max mem: 33370 +Epoch: [29] [2390/2639] eta: 0:12:08 lr: 1.448011510197631e-05 loss: 0.0354 (0.0367) time: 2.8157 data: 0.0071 max mem: 33370 +Epoch: [29] [2400/2639] eta: 0:11:39 lr: 1.447522271206702e-05 loss: 0.0379 (0.0367) time: 2.8498 data: 0.0068 max mem: 33370 +Epoch: [29] [2410/2639] eta: 0:11:09 lr: 1.4470330138423249e-05 loss: 0.0394 (0.0367) time: 2.8688 data: 0.0071 max mem: 33370 +Epoch: [29] [2420/2639] eta: 0:10:40 lr: 1.4465437380969057e-05 loss: 0.0365 (0.0367) time: 2.8721 data: 0.0073 max mem: 33370 +Epoch: [29] [2430/2639] eta: 0:10:11 lr: 1.4460544439628462e-05 loss: 0.0327 (0.0367) time: 2.8854 data: 0.0074 max mem: 33370 +Epoch: [29] [2440/2639] eta: 0:09:42 lr: 1.4455651314325404e-05 loss: 0.0293 (0.0367) time: 2.8970 data: 0.0073 max mem: 33370 +Epoch: [29] [2450/2639] eta: 0:09:12 lr: 1.4450758004983787e-05 loss: 0.0334 (0.0367) time: 2.8824 data: 0.0071 max mem: 33370 +Epoch: [29] [2460/2639] eta: 0:08:43 lr: 1.4445864511527423e-05 loss: 0.0334 (0.0367) time: 2.8812 data: 0.0072 max mem: 33370 +Epoch: [29] [2470/2639] eta: 0:08:14 lr: 1.4440970833880097e-05 loss: 0.0344 (0.0367) time: 2.8916 data: 0.0074 max mem: 33370 +Epoch: [29] [2480/2639] eta: 0:07:44 lr: 1.4436076971965504e-05 loss: 0.0379 (0.0367) time: 2.8235 data: 0.0074 max mem: 33370 +Epoch: [29] [2490/2639] eta: 0:07:15 lr: 1.4431182925707304e-05 loss: 0.0324 (0.0367) time: 2.7820 data: 0.0072 max mem: 33370 +Epoch: [29] [2500/2639] eta: 0:06:46 lr: 1.4426288695029075e-05 loss: 0.0366 (0.0367) time: 2.8283 data: 0.0072 max mem: 33370 +Epoch: [29] [2510/2639] eta: 0:06:17 lr: 1.4421394279854355e-05 loss: 0.0394 (0.0367) time: 2.8874 data: 0.0071 max mem: 33370 +Epoch: [29] [2520/2639] eta: 0:05:47 lr: 1.4416499680106601e-05 loss: 0.0335 (0.0367) time: 2.9204 data: 0.0069 max mem: 33370 +Epoch: [29] [2530/2639] eta: 0:05:18 lr: 1.4411604895709229e-05 loss: 0.0315 (0.0367) time: 2.8954 data: 0.0069 max mem: 33370 +Epoch: [29] [2540/2639] eta: 0:04:49 lr: 1.4406709926585577e-05 loss: 0.0321 (0.0367) time: 2.8707 data: 0.0068 max mem: 33370 +Epoch: [29] [2550/2639] eta: 0:04:20 lr: 1.440181477265894e-05 loss: 0.0372 (0.0367) time: 2.8453 data: 0.0069 max mem: 33370 +Epoch: [29] [2560/2639] eta: 0:03:50 lr: 1.4396919433852527e-05 loss: 0.0317 (0.0367) time: 2.8198 data: 0.0069 max mem: 33370 +Epoch: [29] [2570/2639] eta: 0:03:21 lr: 1.4392023910089514e-05 loss: 0.0327 (0.0367) time: 2.8259 data: 0.0070 max mem: 33370 +Epoch: [29] [2580/2639] eta: 0:02:52 lr: 1.4387128201292995e-05 loss: 0.0318 (0.0367) time: 2.8425 data: 0.0071 max mem: 33370 +Epoch: [29] [2590/2639] eta: 0:02:23 lr: 1.4382232307386015e-05 loss: 0.0313 (0.0367) time: 2.8512 data: 0.0071 max mem: 33370 +Epoch: [29] [2600/2639] eta: 0:01:53 lr: 1.437733622829156e-05 loss: 0.0314 (0.0367) time: 2.8335 data: 0.0070 max mem: 33370 +Epoch: [29] [2610/2639] eta: 0:01:24 lr: 1.4372439963932535e-05 loss: 0.0311 (0.0367) time: 2.8448 data: 0.0072 max mem: 33370 +Epoch: [29] [2620/2639] eta: 0:00:55 lr: 1.4367543514231812e-05 loss: 0.0291 (0.0366) time: 2.8761 data: 0.0076 max mem: 33370 +Epoch: [29] [2630/2639] eta: 0:00:26 lr: 1.4362646879112177e-05 loss: 0.0289 (0.0366) time: 2.8509 data: 0.0074 max mem: 33370 +Epoch: [29] Total time: 2:08:28 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 2:08:03 time: 2.9861 data: 2.8889 max mem: 33370 +Test: [ 100/2573] eta: 0:04:23 time: 0.0777 data: 0.0017 max mem: 33370 +Test: [ 200/2573] eta: 0:03:41 time: 0.0785 data: 0.0013 max mem: 33370 +Test: [ 300/2573] eta: 0:03:20 time: 0.0805 data: 0.0014 max mem: 33370 +Test: [ 400/2573] eta: 0:03:06 time: 0.0809 data: 0.0013 max mem: 33370 +Test: [ 500/2573] eta: 0:02:55 time: 0.0796 data: 0.0014 max mem: 33370 +Test: [ 600/2573] eta: 0:02:45 time: 0.0791 data: 0.0013 max mem: 33370 +Test: [ 700/2573] eta: 0:02:36 time: 0.0790 data: 0.0013 max mem: 33370 +Test: [ 800/2573] eta: 0:02:27 time: 0.0827 data: 0.0014 max mem: 33370 +Test: [ 900/2573] eta: 0:02:18 time: 0.0796 data: 0.0015 max mem: 33370 +Test: [1000/2573] eta: 0:02:09 time: 0.0793 data: 0.0014 max mem: 33370 +Test: [1100/2573] eta: 0:02:01 time: 0.0798 data: 0.0014 max mem: 33370 +Test: [1200/2573] eta: 0:01:52 time: 0.0794 data: 0.0012 max mem: 33370 +Test: [1300/2573] eta: 0:01:44 time: 0.0797 data: 0.0013 max mem: 33370 +Test: [1400/2573] eta: 0:01:35 time: 0.0776 data: 0.0013 max mem: 33370 +Test: [1500/2573] eta: 0:01:27 time: 0.0789 data: 0.0013 max mem: 33370 +Test: [1600/2573] eta: 0:01:19 time: 0.0828 data: 0.0013 max mem: 33370 +Test: [1700/2573] eta: 0:01:11 time: 0.0784 data: 0.0014 max mem: 33370 +Test: [1800/2573] eta: 0:01:02 time: 0.0823 data: 0.0015 max mem: 33370 +Test: [1900/2573] eta: 0:00:54 time: 0.0785 data: 0.0015 max mem: 33370 +Test: [2000/2573] eta: 0:00:46 time: 0.0797 data: 0.0014 max mem: 33370 +Test: [2100/2573] eta: 0:00:38 time: 0.0817 data: 0.0013 max mem: 33370 +Test: [2200/2573] eta: 0:00:30 time: 0.0814 data: 0.0014 max mem: 33370 +Test: [2300/2573] eta: 0:00:22 time: 0.0811 data: 0.0013 max mem: 33370 +Test: [2400/2573] eta: 0:00:13 time: 0.0767 data: 0.0013 max mem: 33370 +Test: [2500/2573] eta: 0:00:05 time: 0.0793 data: 0.0013 max mem: 33370 +Test: Total time: 0:03:28 +Final results: +Mean IoU is 64.37 + + precision@0.5 = 72.49 + precision@0.6 = 66.91 + precision@0.7 = 60.36 + precision@0.8 = 49.37 + precision@0.9 = 24.84 + overall IoU = 61.90 + +Average object IoU 64.37220341072856 +Overall IoU 61.903953552246094 +Better epoch: 29 + +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [30] [ 0/2639] eta: 3:47:16 lr: 1.4358239748907481e-05 loss: 0.0472 (0.0472) time: 5.1675 data: 2.1646 max mem: 33370 +Epoch: [30] [ 10/2639] eta: 2:16:04 lr: 1.4353342761279007e-05 loss: 0.0423 (0.0384) time: 3.1057 data: 0.2041 max mem: 33370 +Epoch: [30] [ 20/2639] eta: 2:09:17 lr: 1.4348445588007381e-05 loss: 0.0326 (0.0376) time: 2.8516 data: 0.0081 max mem: 33370 +Epoch: [30] [ 30/2639] eta: 2:07:40 lr: 1.4343548229015172e-05 loss: 0.0304 (0.0356) time: 2.8429 data: 0.0078 max mem: 33370 +Epoch: [30] [ 40/2639] eta: 2:06:17 lr: 1.4338650684224858e-05 loss: 0.0322 (0.0376) time: 2.8666 data: 0.0072 max mem: 33370 +Epoch: [30] [ 50/2639] eta: 2:05:18 lr: 1.4333752953558887e-05 loss: 0.0333 (0.0367) time: 2.8546 data: 0.0071 max mem: 33370 +Epoch: [30] [ 60/2639] eta: 2:04:03 lr: 1.432885503693962e-05 loss: 0.0268 (0.0357) time: 2.8264 data: 0.0071 max mem: 33370 +Epoch: [30] [ 70/2639] eta: 2:03:48 lr: 1.4323956934289376e-05 loss: 0.0290 (0.0356) time: 2.8593 data: 0.0073 max mem: 33370 +Epoch: [30] [ 80/2639] eta: 2:03:03 lr: 1.4319058645530389e-05 loss: 0.0310 (0.0352) time: 2.8826 data: 0.0073 max mem: 33370 +Epoch: [30] [ 90/2639] eta: 2:02:42 lr: 1.4314160170584856e-05 loss: 0.0279 (0.0343) time: 2.8774 data: 0.0071 max mem: 33370 +Epoch: [30] [ 100/2639] eta: 2:02:06 lr: 1.4309261509374888e-05 loss: 0.0268 (0.0345) time: 2.8869 data: 0.0071 max mem: 33370 +Epoch: [30] [ 110/2639] eta: 2:01:47 lr: 1.430436266182256e-05 loss: 0.0284 (0.0340) time: 2.8950 data: 0.0071 max mem: 33370 +Epoch: [30] [ 120/2639] eta: 2:01:14 lr: 1.4299463627849855e-05 loss: 0.0318 (0.0340) time: 2.8989 data: 0.0073 max mem: 33370 +Epoch: [30] [ 130/2639] eta: 2:00:58 lr: 1.4294564407378724e-05 loss: 0.0344 (0.0341) time: 2.9115 data: 0.0075 max mem: 33370 +Epoch: [30] [ 140/2639] eta: 2:00:22 lr: 1.4289665000331026e-05 loss: 0.0361 (0.0344) time: 2.9052 data: 0.0076 max mem: 33370 +Epoch: [30] [ 150/2639] eta: 1:59:52 lr: 1.4284765406628587e-05 loss: 0.0361 (0.0345) time: 2.8692 data: 0.0079 max mem: 33370 +Epoch: [30] [ 160/2639] eta: 1:59:30 lr: 1.427986562619314e-05 loss: 0.0360 (0.0347) time: 2.9074 data: 0.0077 max mem: 33370 +Epoch: [30] [ 170/2639] eta: 1:58:57 lr: 1.4274965658946385e-05 loss: 0.0350 (0.0347) time: 2.9000 data: 0.0071 max mem: 33370 +Epoch: [30] [ 180/2639] eta: 1:58:30 lr: 1.4270065504809934e-05 loss: 0.0320 (0.0345) time: 2.8864 data: 0.0073 max mem: 33370 +Epoch: [30] [ 190/2639] eta: 1:57:59 lr: 1.4265165163705358e-05 loss: 0.0270 (0.0345) time: 2.8893 data: 0.0075 max mem: 33370 +Epoch: [30] [ 200/2639] eta: 1:57:27 lr: 1.4260264635554141e-05 loss: 0.0309 (0.0345) time: 2.8677 data: 0.0074 max mem: 33370 +Epoch: [30] [ 210/2639] eta: 1:57:03 lr: 1.425536392027773e-05 loss: 0.0330 (0.0345) time: 2.8980 data: 0.0075 max mem: 33370 +Epoch: [30] [ 220/2639] eta: 1:56:32 lr: 1.425046301779749e-05 loss: 0.0320 (0.0345) time: 2.9047 data: 0.0073 max mem: 33370 +Epoch: [30] [ 230/2639] eta: 1:56:02 lr: 1.4245561928034726e-05 loss: 0.0320 (0.0346) time: 2.8747 data: 0.0071 max mem: 33370 +Epoch: [30] [ 240/2639] eta: 1:55:25 lr: 1.4240660650910694e-05 loss: 0.0363 (0.0349) time: 2.8433 data: 0.0075 max mem: 33370 +Epoch: [30] [ 250/2639] eta: 1:54:58 lr: 1.4235759186346567e-05 loss: 0.0354 (0.0349) time: 2.8599 data: 0.0077 max mem: 33370 +Epoch: [30] [ 260/2639] eta: 1:54:29 lr: 1.423085753426347e-05 loss: 0.0329 (0.0350) time: 2.8988 data: 0.0074 max mem: 33370 +Epoch: [30] [ 270/2639] eta: 1:54:03 lr: 1.4225955694582452e-05 loss: 0.0281 (0.0347) time: 2.9013 data: 0.0073 max mem: 33370 +Epoch: [30] [ 280/2639] eta: 1:53:34 lr: 1.422105366722451e-05 loss: 0.0325 (0.0349) time: 2.8999 data: 0.0074 max mem: 33370 +Epoch: [30] [ 290/2639] eta: 1:53:02 lr: 1.4216151452110565e-05 loss: 0.0372 (0.0350) time: 2.8704 data: 0.0073 max mem: 33370 +Epoch: [30] [ 300/2639] eta: 1:52:39 lr: 1.421124904916149e-05 loss: 0.0382 (0.0350) time: 2.9060 data: 0.0072 max mem: 33370 +Epoch: [30] [ 310/2639] eta: 1:52:11 lr: 1.4206346458298078e-05 loss: 0.0330 (0.0349) time: 2.9308 data: 0.0075 max mem: 33370 +Epoch: [30] [ 320/2639] eta: 1:51:44 lr: 1.4201443679441079e-05 loss: 0.0315 (0.0347) time: 2.9102 data: 0.0077 max mem: 33370 +Epoch: [30] [ 330/2639] eta: 1:51:20 lr: 1.4196540712511147e-05 loss: 0.0268 (0.0347) time: 2.9396 data: 0.0076 max mem: 33370 +Epoch: [30] [ 340/2639] eta: 1:50:51 lr: 1.419163755742891e-05 loss: 0.0279 (0.0345) time: 2.9274 data: 0.0073 max mem: 33370 +Epoch: [30] [ 350/2639] eta: 1:50:24 lr: 1.4186734214114896e-05 loss: 0.0302 (0.0344) time: 2.9058 data: 0.0072 max mem: 33370 +Epoch: [30] [ 360/2639] eta: 1:49:54 lr: 1.4181830682489605e-05 loss: 0.0305 (0.0344) time: 2.9024 data: 0.0071 max mem: 33370 +Epoch: [30] [ 370/2639] eta: 1:49:23 lr: 1.4176926962473439e-05 loss: 0.0336 (0.0344) time: 2.8697 data: 0.0082 max mem: 33370 +Epoch: [30] [ 380/2639] eta: 1:48:51 lr: 1.4172023053986758e-05 loss: 0.0348 (0.0345) time: 2.8519 data: 0.0081 max mem: 33370 +Epoch: [30] [ 390/2639] eta: 1:48:22 lr: 1.4167118956949846e-05 loss: 0.0337 (0.0345) time: 2.8694 data: 0.0072 max mem: 33370 +Epoch: [30] [ 400/2639] eta: 1:47:53 lr: 1.4162214671282933e-05 loss: 0.0343 (0.0348) time: 2.8893 data: 0.0074 max mem: 33370 +Epoch: [30] [ 410/2639] eta: 1:47:26 lr: 1.4157310196906173e-05 loss: 0.0364 (0.0348) time: 2.9022 data: 0.0075 max mem: 33370 +Epoch: [30] [ 420/2639] eta: 1:46:57 lr: 1.4152405533739669e-05 loss: 0.0364 (0.0350) time: 2.9099 data: 0.0077 max mem: 33370 +Epoch: [30] [ 430/2639] eta: 1:46:31 lr: 1.4147500681703437e-05 loss: 0.0327 (0.0350) time: 2.9243 data: 0.0076 max mem: 33370 +Epoch: [30] [ 440/2639] eta: 1:45:58 lr: 1.414259564071746e-05 loss: 0.0345 (0.0351) time: 2.8740 data: 0.0075 max mem: 33370 +Epoch: [30] [ 450/2639] eta: 1:45:27 lr: 1.4137690410701627e-05 loss: 0.0368 (0.0351) time: 2.8302 data: 0.0078 max mem: 33370 +Epoch: [30] [ 460/2639] eta: 1:44:57 lr: 1.4132784991575782e-05 loss: 0.0294 (0.0350) time: 2.8607 data: 0.0077 max mem: 33370 +Epoch: [30] [ 470/2639] eta: 1:44:25 lr: 1.4127879383259684e-05 loss: 0.0284 (0.0349) time: 2.8471 data: 0.0076 max mem: 33370 +Epoch: [30] [ 480/2639] eta: 1:43:57 lr: 1.4122973585673052e-05 loss: 0.0294 (0.0348) time: 2.8703 data: 0.0074 max mem: 33370 +Epoch: [30] [ 490/2639] eta: 1:43:30 lr: 1.411806759873553e-05 loss: 0.0304 (0.0348) time: 2.9161 data: 0.0073 max mem: 33370 +Epoch: [30] [ 500/2639] eta: 1:43:02 lr: 1.4113161422366678e-05 loss: 0.0321 (0.0349) time: 2.9221 data: 0.0074 max mem: 33370 +Epoch: [30] [ 510/2639] eta: 1:42:31 lr: 1.4108255056486022e-05 loss: 0.0348 (0.0349) time: 2.8804 data: 0.0074 max mem: 33370 +Epoch: [30] [ 520/2639] eta: 1:42:01 lr: 1.4103348501012998e-05 loss: 0.0358 (0.0351) time: 2.8479 data: 0.0072 max mem: 33370 +Epoch: [30] [ 530/2639] eta: 1:41:32 lr: 1.4098441755866992e-05 loss: 0.0359 (0.0351) time: 2.8766 data: 0.0073 max mem: 33370 +Epoch: [30] [ 540/2639] eta: 1:41:02 lr: 1.409353482096731e-05 loss: 0.0359 (0.0351) time: 2.8748 data: 0.0073 max mem: 33370 +Epoch: [30] [ 550/2639] eta: 1:40:33 lr: 1.4088627696233217e-05 loss: 0.0359 (0.0352) time: 2.8683 data: 0.0072 max mem: 33370 +Epoch: [30] [ 560/2639] eta: 1:40:02 lr: 1.4083720381583879e-05 loss: 0.0334 (0.0351) time: 2.8539 data: 0.0071 max mem: 33370 +Epoch: [30] [ 570/2639] eta: 1:39:33 lr: 1.4078812876938424e-05 loss: 0.0326 (0.0351) time: 2.8588 data: 0.0072 max mem: 33370 +Epoch: [30] [ 580/2639] eta: 1:39:02 lr: 1.4073905182215899e-05 loss: 0.0342 (0.0353) time: 2.8605 data: 0.0072 max mem: 33370 +Epoch: [30] [ 590/2639] eta: 1:38:34 lr: 1.4068997297335296e-05 loss: 0.0321 (0.0352) time: 2.8731 data: 0.0071 max mem: 33370 +Epoch: [30] [ 600/2639] eta: 1:38:06 lr: 1.4064089222215529e-05 loss: 0.0304 (0.0352) time: 2.9117 data: 0.0071 max mem: 33370 +Epoch: [30] [ 610/2639] eta: 1:37:39 lr: 1.4059180956775455e-05 loss: 0.0338 (0.0352) time: 2.9241 data: 0.0071 max mem: 33370 +Epoch: [30] [ 620/2639] eta: 1:37:10 lr: 1.405427250093386e-05 loss: 0.0314 (0.0352) time: 2.9132 data: 0.0072 max mem: 33370 +Epoch: [30] [ 630/2639] eta: 1:36:40 lr: 1.4049363854609474e-05 loss: 0.0321 (0.0353) time: 2.8625 data: 0.0071 max mem: 33370 +Epoch: [30] [ 640/2639] eta: 1:36:11 lr: 1.4044455017720937e-05 loss: 0.0348 (0.0355) time: 2.8590 data: 0.0073 max mem: 33370 +Epoch: [30] [ 650/2639] eta: 1:35:41 lr: 1.4039545990186853e-05 loss: 0.0355 (0.0355) time: 2.8628 data: 0.0075 max mem: 33370 +Epoch: [30] [ 660/2639] eta: 1:35:12 lr: 1.4034636771925736e-05 loss: 0.0310 (0.0355) time: 2.8695 data: 0.0072 max mem: 33370 +Epoch: [30] [ 670/2639] eta: 1:34:43 lr: 1.402972736285605e-05 loss: 0.0317 (0.0354) time: 2.8862 data: 0.0073 max mem: 33370 +Epoch: [30] [ 680/2639] eta: 1:34:13 lr: 1.4024817762896172e-05 loss: 0.0328 (0.0354) time: 2.8682 data: 0.0077 max mem: 33370 +Epoch: [30] [ 690/2639] eta: 1:33:44 lr: 1.401990797196444e-05 loss: 0.0323 (0.0354) time: 2.8724 data: 0.0077 max mem: 33370 +Epoch: [30] [ 700/2639] eta: 1:33:16 lr: 1.4014997989979097e-05 loss: 0.0325 (0.0354) time: 2.8940 data: 0.0078 max mem: 33370 +Epoch: [30] [ 710/2639] eta: 1:32:47 lr: 1.4010087816858347e-05 loss: 0.0326 (0.0354) time: 2.8872 data: 0.0078 max mem: 33370 +Epoch: [30] [ 720/2639] eta: 1:32:17 lr: 1.4005177452520296e-05 loss: 0.0303 (0.0354) time: 2.8562 data: 0.0074 max mem: 33370 +Epoch: [30] [ 730/2639] eta: 1:31:46 lr: 1.400026689688301e-05 loss: 0.0286 (0.0354) time: 2.8335 data: 0.0077 max mem: 33370 +Epoch: [30] [ 740/2639] eta: 1:31:17 lr: 1.399535614986448e-05 loss: 0.0315 (0.0354) time: 2.8506 data: 0.0076 max mem: 33370 +Epoch: [30] [ 750/2639] eta: 1:30:46 lr: 1.3990445211382615e-05 loss: 0.0313 (0.0353) time: 2.8358 data: 0.0075 max mem: 33370 +Epoch: [30] [ 760/2639] eta: 1:30:17 lr: 1.3985534081355287e-05 loss: 0.0313 (0.0353) time: 2.8335 data: 0.0076 max mem: 33370 +Epoch: [30] [ 770/2639] eta: 1:29:47 lr: 1.3980622759700262e-05 loss: 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1.3941325277975542e-05 loss: 0.0331 (0.0352) time: 2.8768 data: 0.0073 max mem: 33370 +Epoch: [30] [ 860/2639] eta: 1:25:24 lr: 1.393641222796061e-05 loss: 0.0361 (0.0354) time: 2.8656 data: 0.0073 max mem: 33370 +Epoch: [30] [ 870/2639] eta: 1:24:55 lr: 1.3931498985492134e-05 loss: 0.0419 (0.0355) time: 2.8669 data: 0.0072 max mem: 33370 +Epoch: [30] [ 880/2639] eta: 1:24:27 lr: 1.3926585550487167e-05 loss: 0.0395 (0.0355) time: 2.8981 data: 0.0073 max mem: 33370 +Epoch: [30] [ 890/2639] eta: 1:23:59 lr: 1.3921671922862669e-05 loss: 0.0297 (0.0355) time: 2.9185 data: 0.0078 max mem: 33370 +Epoch: [30] [ 900/2639] eta: 1:23:30 lr: 1.3916758102535556e-05 loss: 0.0312 (0.0355) time: 2.8993 data: 0.0076 max mem: 33370 +Epoch: [30] [ 910/2639] eta: 1:23:00 lr: 1.3911844089422654e-05 loss: 0.0374 (0.0356) time: 2.8351 data: 0.0070 max mem: 33370 +Epoch: [30] [ 920/2639] eta: 1:22:32 lr: 1.3906929883440742e-05 loss: 0.0361 (0.0357) time: 2.8615 data: 0.0074 max mem: 33370 +Epoch: [30] [ 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mem: 33370 +Epoch: [30] [1010/2639] eta: 1:18:11 lr: 1.3862693336730309e-05 loss: 0.0302 (0.0356) time: 2.8076 data: 0.0076 max mem: 33370 +Epoch: [30] [1020/2639] eta: 1:17:42 lr: 1.3857777197465286e-05 loss: 0.0337 (0.0356) time: 2.8426 data: 0.0079 max mem: 33370 +Epoch: [30] [1030/2639] eta: 1:17:13 lr: 1.3852860864411144e-05 loss: 0.0357 (0.0357) time: 2.8831 data: 0.0075 max mem: 33370 +Epoch: [30] [1040/2639] eta: 1:16:45 lr: 1.3847944337483809e-05 loss: 0.0339 (0.0357) time: 2.9142 data: 0.0072 max mem: 33370 +Epoch: [30] [1050/2639] eta: 1:16:16 lr: 1.3843027616599164e-05 loss: 0.0312 (0.0357) time: 2.8852 data: 0.0072 max mem: 33370 +Epoch: [30] [1060/2639] eta: 1:15:46 lr: 1.3838110701672993e-05 loss: 0.0312 (0.0358) time: 2.8370 data: 0.0074 max mem: 33370 +Epoch: [30] [1070/2639] eta: 1:15:17 lr: 1.383319359262104e-05 loss: 0.0382 (0.0358) time: 2.8374 data: 0.0076 max mem: 33370 +Epoch: [30] [1080/2639] eta: 1:14:48 lr: 1.3828276289358949e-05 loss: 0.0334 (0.0358) time: 2.8473 data: 0.0074 max mem: 33370 +Epoch: [30] [1090/2639] eta: 1:14:19 lr: 1.3823358791802324e-05 loss: 0.0345 (0.0358) time: 2.8654 data: 0.0075 max mem: 33370 +Epoch: [30] [1100/2639] eta: 1:13:50 lr: 1.3818441099866672e-05 loss: 0.0319 (0.0358) time: 2.8638 data: 0.0075 max mem: 33370 +Epoch: [30] [1110/2639] eta: 1:13:21 lr: 1.381352321346745e-05 loss: 0.0319 (0.0358) time: 2.8785 data: 0.0073 max mem: 33370 +Epoch: [30] [1120/2639] eta: 1:12:52 lr: 1.380860513252003e-05 loss: 0.0349 (0.0358) time: 2.8704 data: 0.0077 max mem: 33370 +Epoch: [30] [1130/2639] eta: 1:12:23 lr: 1.3803686856939729e-05 loss: 0.0349 (0.0358) time: 2.8474 data: 0.0078 max mem: 33370 +Epoch: [30] [1140/2639] eta: 1:11:54 lr: 1.3798768386641775e-05 loss: 0.0362 (0.0358) time: 2.8531 data: 0.0075 max mem: 33370 +Epoch: [30] [1150/2639] eta: 1:11:24 lr: 1.3793849721541344e-05 loss: 0.0352 (0.0358) time: 2.8342 data: 0.0073 max mem: 33370 +Epoch: [30] [1160/2639] eta: 1:10:55 lr: 1.3788930861553526e-05 loss: 0.0342 (0.0358) time: 2.8291 data: 0.0072 max mem: 33370 +Epoch: [30] [1170/2639] eta: 1:10:26 lr: 1.3784011806593352e-05 loss: 0.0319 (0.0358) time: 2.8494 data: 0.0075 max mem: 33370 +Epoch: [30] [1180/2639] eta: 1:09:56 lr: 1.3779092556575773e-05 loss: 0.0339 (0.0358) time: 2.8220 data: 0.0077 max mem: 33370 +Epoch: [30] [1190/2639] eta: 1:09:26 lr: 1.3774173111415684e-05 loss: 0.0339 (0.0358) time: 2.7820 data: 0.0077 max mem: 33370 +Epoch: [30] [1200/2639] eta: 1:08:58 lr: 1.3769253471027882e-05 loss: 0.0318 (0.0358) time: 2.8338 data: 0.0074 max mem: 33370 +Epoch: [30] [1210/2639] eta: 1:08:28 lr: 1.376433363532712e-05 loss: 0.0308 (0.0358) time: 2.8525 data: 0.0071 max mem: 33370 +Epoch: [30] [1220/2639] eta: 1:07:59 lr: 1.3759413604228074e-05 loss: 0.0334 (0.0357) time: 2.8492 data: 0.0071 max mem: 33370 +Epoch: [30] [1230/2639] eta: 1:07:31 lr: 1.3754493377645336e-05 loss: 0.0336 (0.0357) time: 2.8783 data: 0.0071 max mem: 33370 +Epoch: [30] [1240/2639] eta: 1:07:02 lr: 1.3749572955493439e-05 loss: 0.0336 (0.0357) time: 2.8903 data: 0.0073 max mem: 33370 +Epoch: [30] [1250/2639] eta: 1:06:34 lr: 1.3744652337686836e-05 loss: 0.0328 (0.0357) time: 2.8928 data: 0.0074 max mem: 33370 +Epoch: [30] [1260/2639] eta: 1:06:04 lr: 1.3739731524139923e-05 loss: 0.0306 (0.0356) time: 2.8517 data: 0.0073 max mem: 33370 +Epoch: [30] [1270/2639] eta: 1:05:35 lr: 1.3734810514767003e-05 loss: 0.0306 (0.0356) time: 2.8437 data: 0.0072 max mem: 33370 +Epoch: [30] [1280/2639] eta: 1:05:06 lr: 1.3729889309482327e-05 loss: 0.0298 (0.0356) time: 2.8447 data: 0.0076 max mem: 33370 +Epoch: [30] [1290/2639] eta: 1:04:37 lr: 1.3724967908200059e-05 loss: 0.0275 (0.0355) time: 2.8382 data: 0.0076 max mem: 33370 +Epoch: [30] [1300/2639] eta: 1:04:08 lr: 1.3720046310834312e-05 loss: 0.0275 (0.0355) time: 2.8556 data: 0.0074 max mem: 33370 +Epoch: [30] [1310/2639] eta: 1:03:39 lr: 1.3715124517299097e-05 loss: 0.0305 (0.0355) time: 2.8650 data: 0.0073 max mem: 33370 +Epoch: [30] [1320/2639] eta: 1:03:10 lr: 1.371020252750838e-05 loss: 0.0372 (0.0355) time: 2.8317 data: 0.0073 max mem: 33370 +Epoch: [30] [1330/2639] eta: 1:02:41 lr: 1.3705280341376039e-05 loss: 0.0364 (0.0356) time: 2.8335 data: 0.0076 max mem: 33370 +Epoch: [30] [1340/2639] eta: 1:02:12 lr: 1.3700357958815896e-05 loss: 0.0326 (0.0355) time: 2.8651 data: 0.0077 max mem: 33370 +Epoch: [30] [1350/2639] eta: 1:01:43 lr: 1.3695435379741675e-05 loss: 0.0319 (0.0355) time: 2.8638 data: 0.0074 max mem: 33370 +Epoch: [30] [1360/2639] eta: 1:01:14 lr: 1.3690512604067054e-05 loss: 0.0364 (0.0355) time: 2.8478 data: 0.0077 max mem: 33370 +Epoch: [30] [1370/2639] eta: 1:00:46 lr: 1.368558963170562e-05 loss: 0.0328 (0.0355) time: 2.8903 data: 0.0077 max mem: 33370 +Epoch: [30] [1380/2639] eta: 1:00:17 lr: 1.3680666462570904e-05 loss: 0.0300 (0.0355) time: 2.9085 data: 0.0076 max mem: 33370 +Epoch: [30] [1390/2639] eta: 0:59:48 lr: 1.3675743096576343e-05 loss: 0.0316 (0.0355) time: 2.8466 data: 0.0078 max mem: 33370 +Epoch: [30] [1400/2639] eta: 0:59:20 lr: 1.3670819533635326e-05 loss: 0.0332 (0.0355) time: 2.8497 data: 0.0078 max mem: 33370 +Epoch: [30] [1410/2639] eta: 0:58:51 lr: 1.3665895773661148e-05 loss: 0.0351 (0.0355) time: 2.8790 data: 0.0078 max mem: 33370 +Epoch: [30] [1420/2639] eta: 0:58:22 lr: 1.3660971816567042e-05 loss: 0.0353 (0.0355) time: 2.8427 data: 0.0082 max mem: 33370 +Epoch: [30] [1430/2639] eta: 0:57:53 lr: 1.3656047662266164e-05 loss: 0.0282 (0.0355) time: 2.8645 data: 0.0084 max mem: 33370 +Epoch: [30] [1440/2639] eta: 0:57:24 lr: 1.3651123310671607e-05 loss: 0.0307 (0.0355) time: 2.8722 data: 0.0080 max mem: 33370 +Epoch: [30] [1450/2639] eta: 0:56:55 lr: 1.364619876169637e-05 loss: 0.0377 (0.0355) time: 2.8253 data: 0.0075 max mem: 33370 +Epoch: [30] [1460/2639] eta: 0:56:26 lr: 1.3641274015253396e-05 loss: 0.0317 (0.0355) time: 2.8473 data: 0.0080 max mem: 33370 +Epoch: [30] [1470/2639] eta: 0:55:57 lr: 1.363634907125556e-05 loss: 0.0298 (0.0355) time: 2.8380 data: 0.0080 max mem: 33370 +Epoch: [30] [1480/2639] eta: 0:55:28 lr: 1.3631423929615638e-05 loss: 0.0302 (0.0354) time: 2.8040 data: 0.0074 max mem: 33370 +Epoch: [30] [1490/2639] eta: 0:54:59 lr: 1.3626498590246365e-05 loss: 0.0341 (0.0355) time: 2.8129 data: 0.0075 max mem: 33370 +Epoch: [30] [1500/2639] eta: 0:54:29 lr: 1.3621573053060366e-05 loss: 0.0341 (0.0355) time: 2.8179 data: 0.0073 max mem: 33370 +Epoch: [30] [1510/2639] eta: 0:54:01 lr: 1.361664731797023e-05 loss: 0.0319 (0.0355) time: 2.8198 data: 0.0071 max mem: 33370 +Epoch: [30] [1520/2639] eta: 0:53:32 lr: 1.3611721384888437e-05 loss: 0.0330 (0.0355) time: 2.8408 data: 0.0071 max mem: 33370 +Epoch: [30] [1530/2639] eta: 0:53:03 lr: 1.3606795253727425e-05 loss: 0.0367 (0.0355) time: 2.8356 data: 0.0072 max mem: 33370 +Epoch: [30] [1540/2639] eta: 0:52:34 lr: 1.360186892439953e-05 loss: 0.0301 (0.0355) time: 2.8375 data: 0.0073 max mem: 33370 +Epoch: [30] [1550/2639] eta: 0:52:05 lr: 1.3596942396817041e-05 loss: 0.0297 (0.0355) time: 2.8730 data: 0.0075 max mem: 33370 +Epoch: [30] [1560/2639] eta: 0:51:37 lr: 1.3592015670892145e-05 loss: 0.0336 (0.0355) time: 2.9195 data: 0.0075 max mem: 33370 +Epoch: [30] [1570/2639] eta: 0:51:08 lr: 1.358708874653698e-05 loss: 0.0326 (0.0355) time: 2.9136 data: 0.0074 max mem: 33370 +Epoch: [30] [1580/2639] eta: 0:50:40 lr: 1.358216162366359e-05 loss: 0.0322 (0.0355) time: 2.8719 data: 0.0076 max mem: 33370 +Epoch: [30] [1590/2639] eta: 0:50:10 lr: 1.3577234302183958e-05 loss: 0.0371 (0.0355) time: 2.8300 data: 0.0079 max mem: 33370 +Epoch: [30] [1600/2639] eta: 0:49:41 lr: 1.357230678200998e-05 loss: 0.0319 (0.0355) time: 2.8064 data: 0.0077 max mem: 33370 +Epoch: [30] [1610/2639] eta: 0:49:12 lr: 1.3567379063053496e-05 loss: 0.0301 (0.0355) time: 2.8192 data: 0.0073 max mem: 33370 +Epoch: [30] [1620/2639] eta: 0:48:44 lr: 1.3562451145226245e-05 loss: 0.0293 (0.0355) time: 2.8473 data: 0.0074 max mem: 33370 +Epoch: [30] [1630/2639] eta: 0:48:15 lr: 1.3557523028439922e-05 loss: 0.0325 (0.0355) time: 2.8592 data: 0.0075 max mem: 33370 +Epoch: [30] [1640/2639] eta: 0:47:46 lr: 1.3552594712606118e-05 loss: 0.0314 (0.0355) time: 2.8517 data: 0.0074 max mem: 33370 +Epoch: [30] [1650/2639] eta: 0:47:17 lr: 1.3547666197636372e-05 loss: 0.0310 (0.0355) time: 2.8106 data: 0.0074 max mem: 33370 +Epoch: [30] [1660/2639] eta: 0:46:48 lr: 1.3542737483442128e-05 loss: 0.0307 (0.0354) time: 2.8307 data: 0.0072 max mem: 33370 +Epoch: [30] [1670/2639] eta: 0:46:19 lr: 1.3537808569934777e-05 loss: 0.0305 (0.0355) time: 2.8654 data: 0.0070 max mem: 33370 +Epoch: [30] [1680/2639] eta: 0:45:51 lr: 1.3532879457025607e-05 loss: 0.0326 (0.0354) time: 2.8611 data: 0.0072 max mem: 33370 +Epoch: [30] [1690/2639] eta: 0:45:22 lr: 1.3527950144625861e-05 loss: 0.0322 (0.0355) time: 2.8587 data: 0.0073 max mem: 33370 +Epoch: [30] [1700/2639] eta: 0:44:53 lr: 1.3523020632646683e-05 loss: 0.0322 (0.0355) time: 2.8121 data: 0.0073 max mem: 33370 +Epoch: [30] 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mem: 33370 +Epoch: [30] [1790/2639] eta: 0:40:36 lr: 1.3478646029062462e-05 loss: 0.0307 (0.0355) time: 2.8648 data: 0.0077 max mem: 33370 +Epoch: [30] [1800/2639] eta: 0:40:07 lr: 1.3473714516385713e-05 loss: 0.0304 (0.0355) time: 2.8950 data: 0.0074 max mem: 33370 +Epoch: [30] [1810/2639] eta: 0:39:38 lr: 1.3468782803147201e-05 loss: 0.0303 (0.0355) time: 2.9065 data: 0.0074 max mem: 33370 +Epoch: [30] [1820/2639] eta: 0:39:10 lr: 1.3463850889257174e-05 loss: 0.0303 (0.0355) time: 2.8826 data: 0.0071 max mem: 33370 +Epoch: [30] [1830/2639] eta: 0:38:41 lr: 1.3458918774625784e-05 loss: 0.0298 (0.0355) time: 2.8937 data: 0.0071 max mem: 33370 +Epoch: [30] [1840/2639] eta: 0:38:13 lr: 1.3453986459163129e-05 loss: 0.0287 (0.0354) time: 2.9045 data: 0.0070 max mem: 33370 +Epoch: [30] [1850/2639] eta: 0:37:44 lr: 1.3449053942779205e-05 loss: 0.0309 (0.0355) time: 2.8818 data: 0.0070 max mem: 33370 +Epoch: [30] [1860/2639] eta: 0:37:15 lr: 1.3444121225383957e-05 loss: 0.0352 (0.0355) time: 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loss: 0.0307 (0.0354) time: 2.8313 data: 0.0075 max mem: 33370 +Epoch: [30] [1950/2639] eta: 0:32:57 lr: 1.3399717708417372e-05 loss: 0.0347 (0.0354) time: 2.8539 data: 0.0074 max mem: 33370 +Epoch: [30] [1960/2639] eta: 0:32:29 lr: 1.3394782975938063e-05 loss: 0.0332 (0.0354) time: 2.8688 data: 0.0072 max mem: 33370 +Epoch: [30] [1970/2639] eta: 0:32:00 lr: 1.3389848041451571e-05 loss: 0.0307 (0.0354) time: 2.9117 data: 0.0070 max mem: 33370 +Epoch: [30] [1980/2639] eta: 0:31:31 lr: 1.3384912904866884e-05 loss: 0.0328 (0.0355) time: 2.8920 data: 0.0071 max mem: 33370 +Epoch: [30] [1990/2639] eta: 0:31:03 lr: 1.3379977566092935e-05 loss: 0.0320 (0.0355) time: 2.8664 data: 0.0074 max mem: 33370 +Epoch: [30] [2000/2639] eta: 0:30:34 lr: 1.3375042025038556e-05 loss: 0.0337 (0.0355) time: 2.8973 data: 0.0073 max mem: 33370 +Epoch: [30] [2010/2639] eta: 0:30:05 lr: 1.3370106281612525e-05 loss: 0.0304 (0.0354) time: 2.8867 data: 0.0071 max mem: 33370 +Epoch: [30] [2020/2639] eta: 0:29:37 lr: 1.3365170335723514e-05 loss: 0.0285 (0.0354) time: 2.9030 data: 0.0074 max mem: 33370 +Epoch: [30] [2030/2639] eta: 0:29:08 lr: 1.3360234187280146e-05 loss: 0.0319 (0.0354) time: 2.9009 data: 0.0075 max mem: 33370 +Epoch: [30] [2040/2639] eta: 0:28:39 lr: 1.3355297836190937e-05 loss: 0.0333 (0.0355) time: 2.8492 data: 0.0073 max mem: 33370 +Epoch: [30] [2050/2639] eta: 0:28:11 lr: 1.3350361282364345e-05 loss: 0.0311 (0.0355) time: 2.8777 data: 0.0073 max mem: 33370 +Epoch: [30] [2060/2639] eta: 0:27:42 lr: 1.3345424525708739e-05 loss: 0.0339 (0.0355) time: 2.9234 data: 0.0075 max mem: 33370 +Epoch: [30] [2070/2639] eta: 0:27:14 lr: 1.3340487566132409e-05 loss: 0.0345 (0.0354) time: 2.9264 data: 0.0074 max mem: 33370 +Epoch: [30] [2080/2639] eta: 0:26:45 lr: 1.3335550403543567e-05 loss: 0.0319 (0.0354) time: 2.9157 data: 0.0071 max mem: 33370 +Epoch: [30] [2090/2639] eta: 0:26:16 lr: 1.3330613037850353e-05 loss: 0.0342 (0.0355) time: 2.8735 data: 0.0070 max mem: 33370 +Epoch: [30] 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mem: 33370 +Epoch: [30] [2180/2639] eta: 0:21:57 lr: 1.3286167591717108e-05 loss: 0.0311 (0.0355) time: 2.8422 data: 0.0071 max mem: 33370 +Epoch: [30] [2190/2639] eta: 0:21:28 lr: 1.3281228189909953e-05 loss: 0.0330 (0.0355) time: 2.8466 data: 0.0068 max mem: 33370 +Epoch: [30] [2200/2639] eta: 0:21:00 lr: 1.3276288583982621e-05 loss: 0.0330 (0.0355) time: 2.8603 data: 0.0070 max mem: 33370 +Epoch: [30] [2210/2639] eta: 0:20:31 lr: 1.3271348773842293e-05 loss: 0.0330 (0.0355) time: 2.8701 data: 0.0073 max mem: 33370 +Epoch: [30] [2220/2639] eta: 0:20:03 lr: 1.3266408759396068e-05 loss: 0.0302 (0.0355) time: 2.9331 data: 0.0074 max mem: 33370 +Epoch: [30] [2230/2639] eta: 0:19:34 lr: 1.3261468540550946e-05 loss: 0.0303 (0.0355) time: 2.9349 data: 0.0071 max mem: 33370 +Epoch: [30] [2240/2639] eta: 0:19:05 lr: 1.325652811721387e-05 loss: 0.0320 (0.0354) time: 2.9316 data: 0.0069 max mem: 33370 +Epoch: [30] [2250/2639] eta: 0:18:37 lr: 1.325158748929168e-05 loss: 0.0349 (0.0355) time: 2.9324 data: 0.0070 max mem: 33370 +Epoch: [30] [2260/2639] eta: 0:18:08 lr: 1.3246646656691158e-05 loss: 0.0376 (0.0355) time: 2.8868 data: 0.0070 max mem: 33370 +Epoch: [30] [2270/2639] eta: 0:17:39 lr: 1.324170561931898e-05 loss: 0.0354 (0.0355) time: 2.8867 data: 0.0071 max mem: 33370 +Epoch: [30] [2280/2639] eta: 0:17:11 lr: 1.3236764377081767e-05 loss: 0.0329 (0.0355) time: 2.9416 data: 0.0069 max mem: 33370 +Epoch: [30] [2290/2639] eta: 0:16:42 lr: 1.3231822929886032e-05 loss: 0.0312 (0.0355) time: 2.9394 data: 0.0069 max mem: 33370 +Epoch: [30] [2300/2639] eta: 0:16:13 lr: 1.3226881277638232e-05 loss: 0.0323 (0.0355) time: 2.9103 data: 0.0070 max mem: 33370 +Epoch: [30] [2310/2639] eta: 0:15:45 lr: 1.3221939420244714e-05 loss: 0.0346 (0.0355) time: 2.8805 data: 0.0069 max mem: 33370 +Epoch: [30] [2320/2639] eta: 0:15:16 lr: 1.321699735761178e-05 loss: 0.0329 (0.0355) time: 2.8512 data: 0.0069 max mem: 33370 +Epoch: [30] [2330/2639] eta: 0:14:47 lr: 1.3212055089645609e-05 loss: 0.0342 (0.0355) time: 2.8407 data: 0.0070 max mem: 33370 +Epoch: [30] [2340/2639] eta: 0:14:18 lr: 1.3207112616252335e-05 loss: 0.0347 (0.0355) time: 2.8481 data: 0.0073 max mem: 33370 +Epoch: [30] [2350/2639] eta: 0:13:50 lr: 1.3202169937337983e-05 loss: 0.0325 (0.0355) time: 2.8677 data: 0.0075 max mem: 33370 +Epoch: [30] [2360/2639] eta: 0:13:21 lr: 1.3197227052808513e-05 loss: 0.0345 (0.0355) time: 2.8970 data: 0.0073 max mem: 33370 +Epoch: [30] [2370/2639] eta: 0:12:52 lr: 1.3192283962569792e-05 loss: 0.0373 (0.0355) time: 2.8767 data: 0.0070 max mem: 33370 +Epoch: [30] [2380/2639] eta: 0:12:24 lr: 1.3187340666527617e-05 loss: 0.0349 (0.0355) time: 2.8771 data: 0.0069 max mem: 33370 +Epoch: [30] [2390/2639] eta: 0:11:55 lr: 1.3182397164587685e-05 loss: 0.0330 (0.0355) time: 2.8684 data: 0.0070 max mem: 33370 +Epoch: [30] [2400/2639] eta: 0:11:26 lr: 1.3177453456655628e-05 loss: 0.0335 (0.0355) time: 2.8627 data: 0.0071 max mem: 33370 +Epoch: [30] [2410/2639] eta: 0:10:57 lr: 1.317250954263698e-05 loss: 0.0335 (0.0355) time: 2.8559 data: 0.0069 max mem: 33370 +Epoch: [30] [2420/2639] eta: 0:10:28 lr: 1.3167565422437208e-05 loss: 0.0320 (0.0355) time: 2.8082 data: 0.0068 max mem: 33370 +Epoch: [30] [2430/2639] eta: 0:10:05 lr: 1.3162621095961683e-05 loss: 0.0323 (0.0356) time: 5.8030 data: 2.5577 max mem: 33370 +Epoch: [30] [2440/2639] eta: 0:09:36 lr: 1.3157676563115703e-05 loss: 0.0314 (0.0356) time: 5.8092 data: 2.5577 max mem: 33370 +Epoch: [30] [2450/2639] eta: 0:09:07 lr: 1.3152731823804468e-05 loss: 0.0324 (0.0356) time: 2.8748 data: 0.0073 max mem: 33370 +Epoch: [30] [2460/2639] eta: 0:08:38 lr: 1.3147786877933114e-05 loss: 0.0286 (0.0356) time: 2.9118 data: 0.0074 max mem: 33370 +Epoch: [30] [2470/2639] eta: 0:08:09 lr: 1.3142841725406684e-05 loss: 0.0322 (0.0356) time: 2.8943 data: 0.0075 max mem: 33370 +Epoch: [30] [2480/2639] eta: 0:07:40 lr: 1.3137896366130136e-05 loss: 0.0322 (0.0356) time: 2.9239 data: 0.0077 max mem: 33370 +Epoch: [30] [2490/2639] eta: 0:07:11 lr: 1.3132950800008354e-05 loss: 0.0318 (0.0356) time: 2.9376 data: 0.0076 max mem: 33370 +Epoch: [30] [2500/2639] eta: 0:06:42 lr: 1.3128005026946116e-05 loss: 0.0346 (0.0356) time: 2.9167 data: 0.0073 max mem: 33370 +Epoch: [30] [2510/2639] eta: 0:06:13 lr: 1.3123059046848146e-05 loss: 0.0341 (0.0356) time: 2.9131 data: 0.0072 max mem: 33370 +Epoch: [30] [2520/2639] eta: 0:05:44 lr: 1.311811285961906e-05 loss: 0.0325 (0.0357) time: 2.8908 data: 0.0073 max mem: 33370 +Epoch: [30] [2530/2639] eta: 0:05:15 lr: 1.311316646516341e-05 loss: 0.0325 (0.0357) time: 2.8625 data: 0.0072 max mem: 33370 +Epoch: [30] [2540/2639] eta: 0:04:46 lr: 1.3108219863385643e-05 loss: 0.0360 (0.0357) time: 2.8702 data: 0.0072 max mem: 33370 +Epoch: [30] [2550/2639] eta: 0:04:17 lr: 1.3103273054190144e-05 loss: 0.0367 (0.0357) time: 2.8920 data: 0.0073 max mem: 33370 +Epoch: [30] [2560/2639] eta: 0:03:48 lr: 1.3098326037481187e-05 loss: 0.0346 (0.0357) time: 2.9074 data: 0.0071 max mem: 33370 +Epoch: [30] [2570/2639] eta: 0:03:19 lr: 1.3093378813162995e-05 loss: 0.0347 (0.0357) time: 2.9200 data: 0.0070 max mem: 33370 +Epoch: [30] [2580/2639] eta: 0:02:50 lr: 1.3088431381139674e-05 loss: 0.0338 (0.0357) time: 2.8792 data: 0.0070 max mem: 33370 +Epoch: [30] [2590/2639] eta: 0:02:21 lr: 1.3083483741315273e-05 loss: 0.0293 (0.0357) time: 2.8727 data: 0.0073 max mem: 33370 +Epoch: [30] [2600/2639] eta: 0:01:52 lr: 1.3078535893593728e-05 loss: 0.0324 (0.0357) time: 2.8489 data: 0.0074 max mem: 33370 +Epoch: [30] [2610/2639] eta: 0:01:23 lr: 1.3073587837878922e-05 loss: 0.0405 (0.0357) time: 2.8458 data: 0.0073 max mem: 33370 +Epoch: [30] [2620/2639] eta: 0:00:55 lr: 1.3068639574074624e-05 loss: 0.0355 (0.0358) time: 2.8616 data: 0.0075 max mem: 33370 +Epoch: [30] [2630/2639] eta: 0:00:26 lr: 1.3063691102084538e-05 loss: 0.0304 (0.0357) time: 2.8391 data: 0.0072 max mem: 33370 +Epoch: [30] Total time: 2:07:21 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 2:25:53 time: 3.4022 data: 3.3125 max mem: 33370 +Test: [ 100/2573] eta: 0:04:33 time: 0.0781 data: 0.0013 max mem: 33370 +Test: [ 200/2573] eta: 0:03:46 time: 0.0798 data: 0.0013 max mem: 33370 +Test: [ 300/2573] eta: 0:03:23 time: 0.0814 data: 0.0015 max mem: 33370 +Test: [ 400/2573] eta: 0:03:09 time: 0.0809 data: 0.0014 max mem: 33370 +Test: [ 500/2573] eta: 0:02:57 time: 0.0793 data: 0.0014 max mem: 33370 +Test: [ 600/2573] eta: 0:02:46 time: 0.0796 data: 0.0014 max mem: 33370 +Test: [ 700/2573] eta: 0:02:37 time: 0.0797 data: 0.0014 max mem: 33370 +Test: [ 800/2573] eta: 0:02:28 time: 0.0830 data: 0.0013 max mem: 33370 +Test: [ 900/2573] eta: 0:02:19 time: 0.0797 data: 0.0014 max mem: 33370 +Test: [1000/2573] eta: 0:02:10 time: 0.0795 data: 0.0013 max mem: 33370 +Test: [1100/2573] eta: 0:02:01 time: 0.0797 data: 0.0013 max mem: 33370 +Test: [1200/2573] eta: 0:01:53 time: 0.0800 data: 0.0014 max mem: 33370 +Test: [1300/2573] eta: 0:01:45 time: 0.0806 data: 0.0015 max mem: 33370 +Test: [1400/2573] eta: 0:01:36 time: 0.0781 data: 0.0014 max mem: 33370 +Test: [1500/2573] eta: 0:01:28 time: 0.0799 data: 0.0013 max mem: 33370 +Test: [1600/2573] eta: 0:01:19 time: 0.0828 data: 0.0014 max mem: 33370 +Test: [1700/2573] eta: 0:01:11 time: 0.0775 data: 0.0015 max mem: 33370 +Test: [1800/2573] eta: 0:01:03 time: 0.0809 data: 0.0014 max mem: 33370 +Test: [1900/2573] eta: 0:00:54 time: 0.0779 data: 0.0013 max mem: 33370 +Test: [2000/2573] eta: 0:00:46 time: 0.0789 data: 0.0012 max mem: 33370 +Test: [2100/2573] eta: 0:00:38 time: 0.0922 data: 0.0115 max mem: 33370 +Test: [2200/2573] eta: 0:00:30 time: 0.0806 data: 0.0013 max mem: 33370 +Test: [2300/2573] eta: 0:00:22 time: 0.0809 data: 0.0013 max mem: 33370 +Test: [2400/2573] eta: 0:00:14 time: 0.4012 data: 0.3247 max mem: 33370 +Test: [2500/2573] eta: 0:00:06 time: 0.0783 data: 0.0012 max mem: 33370 +Test: Total time: 0:03:40 +Final results: +Mean IoU is 64.55 + + precision@0.5 = 72.63 + precision@0.6 = 67.71 + precision@0.7 = 60.52 + precision@0.8 = 49.14 + precision@0.9 = 24.92 + overall IoU = 62.18 + +Average object IoU 64.54898373609078 +Overall IoU 62.17632293701172 +Better epoch: 30 + +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [31] [ 0/2639] eta: 4:31:33 lr: 1.3059237299214946e-05 loss: 0.0413 (0.0413) time: 6.1741 data: 3.2515 max mem: 33370 +Epoch: [31] [ 10/2639] eta: 2:19:11 lr: 1.3054288431406237e-05 loss: 0.0339 (0.0352) time: 3.1768 data: 0.3029 max mem: 33370 +Epoch: [31] [ 20/2639] eta: 2:12:49 lr: 1.3049339355131979e-05 loss: 0.0329 (0.0354) time: 2.8865 data: 0.0073 max mem: 33370 +Epoch: [31] [ 30/2639] eta: 2:10:52 lr: 1.3044390070295528e-05 loss: 0.0295 (0.0335) time: 2.9180 data: 0.0068 max mem: 33370 +Epoch: [31] [ 40/2639] eta: 2:09:12 lr: 1.3039440576800174e-05 loss: 0.0302 (0.0337) time: 2.9200 data: 0.0072 max mem: 33370 +Epoch: [31] [ 50/2639] eta: 2:07:44 lr: 1.3034490874549098e-05 loss: 0.0307 (0.0337) time: 2.8838 data: 0.0073 max mem: 33370 +Epoch: [31] [ 60/2639] eta: 2:06:51 lr: 1.3029540963445419e-05 loss: 0.0318 (0.0345) time: 2.8868 data: 0.0072 max mem: 33370 +Epoch: [31] [ 70/2639] eta: 2:05:49 lr: 1.3024590843392149e-05 loss: 0.0329 (0.0346) time: 2.8834 data: 0.0074 max mem: 33370 +Epoch: [31] [ 80/2639] eta: 2:05:13 lr: 1.3019640514292223e-05 loss: 0.0315 (0.0351) time: 2.8896 data: 0.0079 max mem: 33370 +Epoch: [31] [ 90/2639] eta: 2:04:26 lr: 1.3014689976048502e-05 loss: 0.0307 (0.0353) time: 2.8953 data: 0.0079 max mem: 33370 +Epoch: [31] [ 100/2639] eta: 2:03:53 lr: 1.3009739228563733e-05 loss: 0.0307 (0.0349) time: 2.8938 data: 0.0072 max mem: 33370 +Epoch: [31] [ 110/2639] eta: 2:03:02 lr: 1.3004788271740606e-05 loss: 0.0307 (0.0350) time: 2.8745 data: 0.0071 max mem: 33370 +Epoch: [31] [ 120/2639] eta: 2:02:24 lr: 1.2999837105481699e-05 loss: 0.0304 (0.0350) time: 2.8541 data: 0.0073 max mem: 33370 +Epoch: [31] [ 130/2639] eta: 2:01:42 lr: 1.299488572968953e-05 loss: 0.0284 (0.0349) time: 2.8606 data: 0.0072 max mem: 33370 +Epoch: [31] [ 140/2639] eta: 2:01:00 lr: 1.29899341442665e-05 loss: 0.0289 (0.0351) time: 2.8445 data: 0.0072 max mem: 33370 +Epoch: [31] [ 150/2639] eta: 2:00:21 lr: 1.2984982349114952e-05 loss: 0.0295 (0.0347) time: 2.8424 data: 0.0076 max mem: 33370 +Epoch: [31] [ 160/2639] eta: 1:59:39 lr: 1.2980030344137118e-05 loss: 0.0257 (0.0343) time: 2.8284 data: 0.0075 max mem: 33370 +Epoch: [31] [ 170/2639] eta: 1:59:06 lr: 1.2975078129235163e-05 loss: 0.0300 (0.0355) time: 2.8431 data: 0.0071 max mem: 33370 +Epoch: [31] [ 180/2639] eta: 1:58:26 lr: 1.2970125704311148e-05 loss: 0.0357 (0.0358) time: 2.8415 data: 0.0072 max mem: 33370 +Epoch: [31] [ 190/2639] eta: 1:57:57 lr: 1.2965173069267067e-05 loss: 0.0324 (0.0357) time: 2.8513 data: 0.0072 max mem: 33370 +Epoch: [31] [ 200/2639] eta: 1:57:30 lr: 1.2960220224004798e-05 loss: 0.0316 (0.0355) time: 2.8981 data: 0.0072 max mem: 33370 +Epoch: [31] [ 210/2639] eta: 1:56:56 lr: 1.2955267168426163e-05 loss: 0.0330 (0.0357) time: 2.8770 data: 0.0073 max mem: 33370 +Epoch: [31] [ 220/2639] eta: 1:56:31 lr: 1.295031390243287e-05 loss: 0.0342 (0.0357) time: 2.8860 data: 0.0072 max mem: 33370 +Epoch: [31] [ 230/2639] eta: 1:55:57 lr: 1.2945360425926562e-05 loss: 0.0324 (0.0356) time: 2.8820 data: 0.0074 max mem: 33370 +Epoch: [31] [ 240/2639] eta: 1:55:21 lr: 1.2940406738808766e-05 loss: 0.0270 (0.0357) time: 2.8264 data: 0.0075 max mem: 33370 +Epoch: [31] [ 250/2639] eta: 1:54:54 lr: 1.2935452840980958e-05 loss: 0.0351 (0.0358) time: 2.8577 data: 0.0076 max mem: 33370 +Epoch: [31] [ 260/2639] eta: 1:54:22 lr: 1.2930498732344487e-05 loss: 0.0323 (0.0357) time: 2.8778 data: 0.0080 max mem: 33370 +Epoch: [31] [ 270/2639] eta: 1:53:56 lr: 1.2925544412800643e-05 loss: 0.0317 (0.0360) time: 2.8864 data: 0.0077 max mem: 33370 +Epoch: [31] [ 280/2639] eta: 1:53:23 lr: 1.2920589882250613e-05 loss: 0.0350 (0.0359) time: 2.8785 data: 0.0073 max mem: 33370 +Epoch: [31] [ 290/2639] eta: 1:52:53 lr: 1.2915635140595509e-05 loss: 0.0317 (0.0358) time: 2.8511 data: 0.0071 max mem: 33370 +Epoch: [31] [ 300/2639] eta: 1:52:22 lr: 1.2910680187736328e-05 loss: 0.0292 (0.0355) time: 2.8608 data: 0.0070 max mem: 33370 +Epoch: [31] [ 310/2639] eta: 1:51:47 lr: 1.2905725023574014e-05 loss: 0.0311 (0.0355) time: 2.8321 data: 0.0074 max mem: 33370 +Epoch: [31] [ 320/2639] eta: 1:51:20 lr: 1.2900769648009389e-05 loss: 0.0304 (0.0356) time: 2.8550 data: 0.0078 max mem: 33370 +Epoch: [31] [ 330/2639] eta: 1:50:47 lr: 1.2895814060943208e-05 loss: 0.0303 (0.0354) time: 2.8621 data: 0.0078 max mem: 33370 +Epoch: [31] [ 340/2639] eta: 1:50:13 lr: 1.2890858262276135e-05 loss: 0.0306 (0.0354) time: 2.8129 data: 0.0074 max mem: 33370 +Epoch: [31] [ 350/2639] eta: 1:49:37 lr: 1.2885902251908727e-05 loss: 0.0322 (0.0357) time: 2.7814 data: 0.0075 max mem: 33370 +Epoch: [31] [ 360/2639] eta: 1:49:08 lr: 1.2880946029741478e-05 loss: 0.0322 (0.0356) time: 2.8145 data: 0.0076 max mem: 33370 +Epoch: [31] [ 370/2639] eta: 1:48:38 lr: 1.2875989595674766e-05 loss: 0.0318 (0.0356) time: 2.8639 data: 0.0073 max mem: 33370 +Epoch: [31] [ 380/2639] eta: 1:48:09 lr: 1.287103294960891e-05 loss: 0.0297 (0.0354) time: 2.8630 data: 0.0074 max mem: 33370 +Epoch: [31] [ 390/2639] eta: 1:47:36 lr: 1.2866076091444101e-05 loss: 0.0296 (0.0355) time: 2.8338 data: 0.0075 max mem: 33370 +Epoch: [31] [ 400/2639] eta: 1:47:07 lr: 1.2861119021080482e-05 loss: 0.0324 (0.0354) time: 2.8316 data: 0.0075 max mem: 33370 +Epoch: [31] [ 410/2639] eta: 1:46:39 lr: 1.2856161738418069e-05 loss: 0.0314 (0.0353) time: 2.8682 data: 0.0076 max mem: 33370 +Epoch: [31] [ 420/2639] eta: 1:46:09 lr: 1.2851204243356819e-05 loss: 0.0300 (0.0352) time: 2.8625 data: 0.0077 max mem: 33370 +Epoch: [31] [ 430/2639] eta: 1:45:38 lr: 1.2846246535796569e-05 loss: 0.0331 (0.0354) time: 2.8418 data: 0.0078 max mem: 33370 +Epoch: [31] [ 440/2639] eta: 1:45:07 lr: 1.2841288615637098e-05 loss: 0.0360 (0.0354) time: 2.8253 data: 0.0078 max mem: 33370 +Epoch: [31] [ 450/2639] eta: 1:44:37 lr: 1.2836330482778065e-05 loss: 0.0351 (0.0353) time: 2.8343 data: 0.0075 max mem: 33370 +Epoch: [31] [ 460/2639] eta: 1:44:09 lr: 1.2831372137119061e-05 loss: 0.0346 (0.0353) time: 2.8621 data: 0.0076 max mem: 33370 +Epoch: [31] [ 470/2639] eta: 1:43:43 lr: 1.2826413578559568e-05 loss: 0.0289 (0.0352) time: 2.8996 data: 0.0074 max mem: 33370 +Epoch: [31] [ 480/2639] eta: 1:43:11 lr: 1.2821454806998997e-05 loss: 0.0289 (0.0351) time: 2.8585 data: 0.0073 max mem: 33370 +Epoch: [31] [ 490/2639] eta: 1:42:40 lr: 1.281649582233665e-05 loss: 0.0310 (0.0350) time: 2.8114 data: 0.0074 max mem: 33370 +Epoch: [31] [ 500/2639] eta: 1:42:09 lr: 1.2811536624471752e-05 loss: 0.0302 (0.0351) time: 2.8106 data: 0.0073 max mem: 33370 +Epoch: [31] [ 510/2639] eta: 1:41:37 lr: 1.2806577213303419e-05 loss: 0.0304 (0.0350) time: 2.7935 data: 0.0074 max mem: 33370 +Epoch: [31] [ 520/2639] eta: 1:41:06 lr: 1.2801617588730702e-05 loss: 0.0318 (0.0350) time: 2.8008 data: 0.0074 max mem: 33370 +Epoch: [31] [ 530/2639] eta: 1:40:36 lr: 1.2796657750652536e-05 loss: 0.0292 (0.0348) time: 2.8184 data: 0.0073 max mem: 33370 +Epoch: [31] [ 540/2639] eta: 1:40:04 lr: 1.2791697698967783e-05 loss: 0.0282 (0.0348) time: 2.8024 data: 0.0072 max mem: 33370 +Epoch: [31] [ 550/2639] eta: 1:39:34 lr: 1.2786737433575199e-05 loss: 0.0283 (0.0347) time: 2.7980 data: 0.0071 max mem: 33370 +Epoch: [31] [ 560/2639] eta: 1:39:05 lr: 1.2781776954373461e-05 loss: 0.0275 (0.0346) time: 2.8322 data: 0.0070 max mem: 33370 +Epoch: [31] [ 570/2639] eta: 1:38:38 lr: 1.2776816261261138e-05 loss: 0.0272 (0.0347) time: 2.8711 data: 0.0070 max mem: 33370 +Epoch: [31] [ 580/2639] eta: 1:38:12 lr: 1.2771855354136724e-05 loss: 0.0273 (0.0346) time: 2.9169 data: 0.0071 max mem: 33370 +Epoch: [31] [ 590/2639] eta: 1:37:42 lr: 1.276689423289862e-05 loss: 0.0289 (0.0346) time: 2.8887 data: 0.0071 max mem: 33370 +Epoch: [31] [ 600/2639] eta: 1:37:12 lr: 1.2761932897445117e-05 loss: 0.0331 (0.0346) time: 2.8316 data: 0.0070 max mem: 33370 +Epoch: [31] [ 610/2639] eta: 1:36:45 lr: 1.2756971347674437e-05 loss: 0.0341 (0.0347) time: 2.8551 data: 0.0072 max mem: 33370 +Epoch: [31] [ 620/2639] eta: 1:36:16 lr: 1.2752009583484687e-05 loss: 0.0364 (0.0348) time: 2.8824 data: 0.0072 max mem: 33370 +Epoch: [31] [ 630/2639] eta: 1:35:48 lr: 1.2747047604773906e-05 loss: 0.0352 (0.0348) time: 2.8766 data: 0.0076 max mem: 33370 +Epoch: [31] [ 640/2639] eta: 1:35:21 lr: 1.2742085411440013e-05 loss: 0.0326 (0.0349) time: 2.8888 data: 0.0077 max mem: 33370 +Epoch: [31] [ 650/2639] eta: 1:34:54 lr: 1.2737123003380863e-05 loss: 0.0344 (0.0349) time: 2.9061 data: 0.0073 max mem: 33370 +Epoch: [31] [ 660/2639] eta: 1:34:26 lr: 1.2732160380494187e-05 loss: 0.0321 (0.0348) time: 2.9027 data: 0.0073 max mem: 33370 +Epoch: [31] [ 670/2639] eta: 1:33:58 lr: 1.2727197542677657e-05 loss: 0.0311 (0.0348) time: 2.8900 data: 0.0074 max mem: 33370 +Epoch: [31] [ 680/2639] eta: 1:33:30 lr: 1.2722234489828821e-05 loss: 0.0346 (0.0348) time: 2.8791 data: 0.0074 max mem: 33370 +Epoch: [31] [ 690/2639] eta: 1:33:02 lr: 1.271727122184516e-05 loss: 0.0385 (0.0349) time: 2.8809 data: 0.0072 max mem: 33370 +Epoch: [31] [ 700/2639] eta: 1:32:33 lr: 1.2712307738624036e-05 loss: 0.0327 (0.0350) time: 2.8693 data: 0.0071 max mem: 33370 +Epoch: [31] [ 710/2639] eta: 1:32:06 lr: 1.2707344040062739e-05 loss: 0.0362 (0.0350) time: 2.8817 data: 0.0072 max mem: 33370 +Epoch: [31] [ 720/2639] eta: 1:31:38 lr: 1.270238012605845e-05 loss: 0.0347 (0.0349) time: 2.9170 data: 0.0075 max mem: 33370 +Epoch: [31] [ 730/2639] eta: 1:31:08 lr: 1.2697415996508271e-05 loss: 0.0313 (0.0350) time: 2.8634 data: 0.0077 max mem: 33370 +Epoch: [31] [ 740/2639] eta: 1:30:38 lr: 1.2692451651309195e-05 loss: 0.0340 (0.0350) time: 2.8100 data: 0.0078 max mem: 33370 +Epoch: [31] [ 750/2639] eta: 1:30:10 lr: 1.2687487090358135e-05 loss: 0.0320 (0.0350) time: 2.8439 data: 0.0077 max mem: 33370 +Epoch: [31] [ 760/2639] eta: 1:29:43 lr: 1.2682522313551893e-05 loss: 0.0336 (0.0350) time: 2.9004 data: 0.0078 max mem: 33370 +Epoch: [31] [ 770/2639] eta: 1:29:13 lr: 1.26775573207872e-05 loss: 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1.2637829591740064e-05 loss: 0.0279 (0.0349) time: 2.8585 data: 0.0072 max mem: 33370 +Epoch: [31] [ 860/2639] eta: 1:24:52 lr: 1.2632862650685931e-05 loss: 0.0318 (0.0349) time: 2.8470 data: 0.0073 max mem: 33370 +Epoch: [31] [ 870/2639] eta: 1:24:23 lr: 1.2627895492635304e-05 loss: 0.0352 (0.0350) time: 2.8680 data: 0.0076 max mem: 33370 +Epoch: [31] [ 880/2639] eta: 1:23:55 lr: 1.2622928117483857e-05 loss: 0.0306 (0.0349) time: 2.8731 data: 0.0077 max mem: 33370 +Epoch: [31] [ 890/2639] eta: 1:23:28 lr: 1.2617960525127165e-05 loss: 0.0261 (0.0349) time: 2.9060 data: 0.0078 max mem: 33370 +Epoch: [31] [ 900/2639] eta: 1:23:01 lr: 1.2612992715460712e-05 loss: 0.0297 (0.0348) time: 2.9381 data: 0.0079 max mem: 33370 +Epoch: [31] [ 910/2639] eta: 1:22:33 lr: 1.2608024688379877e-05 loss: 0.0297 (0.0347) time: 2.9363 data: 0.0078 max mem: 33370 +Epoch: [31] [ 920/2639] eta: 1:22:05 lr: 1.2603056443779959e-05 loss: 0.0280 (0.0347) time: 2.9138 data: 0.0074 max mem: 33370 +Epoch: [31] [ 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data: 0.0071 max mem: 33370 +Epoch: [31] [1090/2639] eta: 1:15:20 lr: 1.2518562903226433e-05 loss: 0.0287 (0.0347) time: 2.8911 data: 0.0072 max mem: 33370 +Epoch: [31] [1100/2639] eta: 1:14:50 lr: 1.2513590725266785e-05 loss: 0.0308 (0.0347) time: 2.8405 data: 0.0075 max mem: 33370 +Epoch: [31] [1110/2639] eta: 1:14:19 lr: 1.2508618327780087e-05 loss: 0.0372 (0.0348) time: 2.8509 data: 0.0081 max mem: 33370 +Epoch: [31] [1120/2639] eta: 1:13:50 lr: 1.2503645710659658e-05 loss: 0.0321 (0.0350) time: 2.8883 data: 0.0082 max mem: 33370 +Epoch: [31] [1130/2639] eta: 1:13:21 lr: 1.2498672873798753e-05 loss: 0.0312 (0.0350) time: 2.9272 data: 0.0074 max mem: 33370 +Epoch: [31] [1140/2639] eta: 1:12:52 lr: 1.2493699817090496e-05 loss: 0.0314 (0.0350) time: 2.9128 data: 0.0074 max mem: 33370 +Epoch: [31] [1150/2639] eta: 1:12:23 lr: 1.248872654042794e-05 loss: 0.0354 (0.0350) time: 2.9003 data: 0.0074 max mem: 33370 +Epoch: [31] [1160/2639] eta: 1:11:54 lr: 1.2483753043704009e-05 loss: 0.0328 (0.0350) time: 2.9180 data: 0.0071 max mem: 33370 +Epoch: [31] [1170/2639] eta: 1:11:24 lr: 1.2478779326811561e-05 loss: 0.0303 (0.0350) time: 2.9153 data: 0.0073 max mem: 33370 +Epoch: [31] [1180/2639] eta: 1:10:54 lr: 1.2473805389643324e-05 loss: 0.0347 (0.0350) time: 2.8798 data: 0.0074 max mem: 33370 +Epoch: [31] [1190/2639] eta: 1:10:25 lr: 1.246883123209195e-05 loss: 0.0357 (0.0350) time: 2.8760 data: 0.0076 max mem: 33370 +Epoch: [31] [1200/2639] eta: 1:09:55 lr: 1.2463856854049969e-05 loss: 0.0308 (0.0350) time: 2.8643 data: 0.0077 max mem: 33370 +Epoch: [31] [1210/2639] eta: 1:09:25 lr: 1.2458882255409832e-05 loss: 0.0353 (0.0351) time: 2.8564 data: 0.0074 max mem: 33370 +Epoch: [31] [1220/2639] eta: 1:08:55 lr: 1.2453907436063871e-05 loss: 0.0346 (0.0351) time: 2.8636 data: 0.0076 max mem: 33370 +Epoch: [31] [1230/2639] eta: 1:08:25 lr: 1.2448932395904338e-05 loss: 0.0329 (0.0352) time: 2.8480 data: 0.0076 max mem: 33370 +Epoch: [31] [1240/2639] eta: 1:07:55 lr: 1.244395713482336e-05 loss: 0.0329 (0.0352) time: 2.8284 data: 0.0073 max mem: 33370 +Epoch: [31] [1250/2639] eta: 1:07:26 lr: 1.2438981652712988e-05 loss: 0.0308 (0.0352) time: 2.8715 data: 0.0071 max mem: 33370 +Epoch: [31] [1260/2639] eta: 1:06:57 lr: 1.2434005949465152e-05 loss: 0.0279 (0.0352) time: 2.9135 data: 0.0073 max mem: 33370 +Epoch: [31] [1270/2639] eta: 1:06:27 lr: 1.24290300249717e-05 loss: 0.0275 (0.0352) time: 2.8913 data: 0.0073 max mem: 33370 +Epoch: [31] [1280/2639] eta: 1:05:58 lr: 1.2424053879124354e-05 loss: 0.0305 (0.0352) time: 2.8800 data: 0.0073 max mem: 33370 +Epoch: [31] [1290/2639] eta: 1:05:28 lr: 1.2419077511814767e-05 loss: 0.0307 (0.0352) time: 2.8585 data: 0.0078 max mem: 33370 +Epoch: [31] [1300/2639] eta: 1:04:59 lr: 1.2414100922934459e-05 loss: 0.0295 (0.0351) time: 2.8854 data: 0.0077 max mem: 33370 +Epoch: [31] [1310/2639] eta: 1:04:30 lr: 1.2409124112374867e-05 loss: 0.0295 (0.0352) time: 2.9071 data: 0.0075 max mem: 33370 +Epoch: [31] [1320/2639] eta: 1:04:00 lr: 1.240414708002733e-05 loss: 0.0340 (0.0352) time: 2.8683 data: 0.0076 max mem: 33370 +Epoch: [31] [1330/2639] eta: 1:03:30 lr: 1.2399169825783064e-05 loss: 0.0340 (0.0352) time: 2.8495 data: 0.0074 max mem: 33370 +Epoch: [31] [1340/2639] eta: 1:03:00 lr: 1.2394192349533213e-05 loss: 0.0326 (0.0352) time: 2.8500 data: 0.0072 max mem: 33370 +Epoch: [31] [1350/2639] eta: 1:02:31 lr: 1.2389214651168784e-05 loss: 0.0324 (0.0352) time: 2.8676 data: 0.0071 max mem: 33370 +Epoch: [31] [1360/2639] eta: 1:02:01 lr: 1.2384236730580719e-05 loss: 0.0393 (0.0354) time: 2.8367 data: 0.0073 max mem: 33370 +Epoch: [31] [1370/2639] eta: 1:01:32 lr: 1.2379258587659823e-05 loss: 0.0327 (0.0353) time: 2.8476 data: 0.0074 max mem: 33370 +Epoch: [31] [1380/2639] eta: 1:01:03 lr: 1.2374280222296827e-05 loss: 0.0327 (0.0354) time: 2.9051 data: 0.0071 max mem: 33370 +Epoch: [31] [1390/2639] eta: 1:00:34 lr: 1.2369301634382337e-05 loss: 0.0320 (0.0353) time: 2.9220 data: 0.0072 max mem: 33370 +Epoch: [31] [1400/2639] eta: 1:00:04 lr: 1.2364322823806877e-05 loss: 0.0354 (0.0354) time: 2.8836 data: 0.0072 max mem: 33370 +Epoch: [31] [1410/2639] eta: 0:59:35 lr: 1.2359343790460845e-05 loss: 0.0327 (0.0353) time: 2.8623 data: 0.0071 max mem: 33370 +Epoch: [31] [1420/2639] eta: 0:59:06 lr: 1.235436453423456e-05 loss: 0.0303 (0.0353) time: 2.9067 data: 0.0070 max mem: 33370 +Epoch: [31] [1430/2639] eta: 0:58:36 lr: 1.2349385055018218e-05 loss: 0.0312 (0.0353) time: 2.8998 data: 0.0069 max mem: 33370 +Epoch: [31] [1440/2639] eta: 0:58:07 lr: 1.234440535270193e-05 loss: 0.0301 (0.0353) time: 2.8551 data: 0.0070 max mem: 33370 +Epoch: [31] [1450/2639] eta: 0:57:56 lr: 1.2339425427175679e-05 loss: 0.0310 (0.0353) time: 4.0054 data: 0.5217 max mem: 33370 +Epoch: [31] [1460/2639] eta: 0:57:27 lr: 1.2334445278329373e-05 loss: 0.0263 (0.0353) time: 4.0361 data: 0.5221 max mem: 33370 +Epoch: [31] [1470/2639] eta: 0:56:57 lr: 1.2329464906052791e-05 loss: 0.0285 (0.0354) time: 2.9065 data: 0.0076 max mem: 33370 +Epoch: [31] [1480/2639] eta: 0:56:28 lr: 1.232448431023563e-05 loss: 0.0330 (0.0353) time: 2.9038 data: 0.0075 max mem: 33370 +Epoch: [31] [1490/2639] eta: 0:55:58 lr: 1.2319503490767462e-05 loss: 0.0330 (0.0353) time: 2.8804 data: 0.0076 max mem: 33370 +Epoch: [31] [1500/2639] eta: 0:55:29 lr: 1.2314522447537775e-05 loss: 0.0325 (0.0353) time: 2.8927 data: 0.0073 max mem: 33370 +Epoch: [31] [1510/2639] eta: 0:54:59 lr: 1.2309541180435931e-05 loss: 0.0265 (0.0353) time: 2.8904 data: 0.0072 max mem: 33370 +Epoch: [31] [1520/2639] eta: 0:54:30 lr: 1.2304559689351213e-05 loss: 0.0321 (0.0353) time: 2.8899 data: 0.0073 max mem: 33370 +Epoch: [31] [1530/2639] eta: 0:54:01 lr: 1.2299577974172774e-05 loss: 0.0342 (0.0353) time: 2.8988 data: 0.0072 max mem: 33370 +Epoch: [31] [1540/2639] eta: 0:53:31 lr: 1.2294596034789683e-05 loss: 0.0325 (0.0353) time: 2.8871 data: 0.0073 max mem: 33370 +Epoch: [31] [1550/2639] eta: 0:53:01 lr: 1.2289613871090888e-05 loss: 0.0356 (0.0354) time: 2.8298 data: 0.0073 max mem: 33370 +Epoch: [31] [1560/2639] eta: 0:52:31 lr: 1.228463148296524e-05 loss: 0.0356 (0.0354) time: 2.8099 data: 0.0075 max mem: 33370 +Epoch: [31] [1570/2639] eta: 0:52:01 lr: 1.2279648870301493e-05 loss: 0.0333 (0.0354) time: 2.8248 data: 0.0076 max mem: 33370 +Epoch: [31] [1580/2639] eta: 0:51:32 lr: 1.2274666032988274e-05 loss: 0.0350 (0.0355) time: 2.8453 data: 0.0073 max mem: 33370 +Epoch: [31] [1590/2639] eta: 0:51:02 lr: 1.2269682970914126e-05 loss: 0.0358 (0.0355) time: 2.8576 data: 0.0075 max mem: 33370 +Epoch: [31] [1600/2639] eta: 0:50:32 lr: 1.226469968396747e-05 loss: 0.0358 (0.0355) time: 2.8230 data: 0.0075 max mem: 33370 +Epoch: [31] [1610/2639] eta: 0:50:03 lr: 1.2259716172036638e-05 loss: 0.0330 (0.0355) time: 2.8477 data: 0.0074 max mem: 33370 +Epoch: [31] [1620/2639] eta: 0:49:33 lr: 1.2254732435009837e-05 loss: 0.0330 (0.0355) time: 2.8786 data: 0.0074 max mem: 33370 +Epoch: [31] [1630/2639] eta: 0:49:04 lr: 1.2249748472775187e-05 loss: 0.0287 (0.0355) time: 2.8777 data: 0.0075 max mem: 33370 +Epoch: [31] [1640/2639] eta: 0:48:34 lr: 1.2244764285220681e-05 loss: 0.0296 (0.0355) time: 2.8812 data: 0.0075 max mem: 33370 +Epoch: [31] [1650/2639] eta: 0:48:05 lr: 1.223977987223423e-05 loss: 0.0369 (0.0355) time: 2.8589 data: 0.0071 max mem: 33370 +Epoch: [31] [1660/2639] eta: 0:47:35 lr: 1.2234795233703612e-05 loss: 0.0356 (0.0355) time: 2.8510 data: 0.0071 max mem: 33370 +Epoch: [31] [1670/2639] eta: 0:47:06 lr: 1.2229810369516527e-05 loss: 0.0269 (0.0355) time: 2.8944 data: 0.0071 max mem: 33370 +Epoch: [31] [1680/2639] eta: 0:46:37 lr: 1.2224825279560536e-05 loss: 0.0252 (0.0354) time: 2.9201 data: 0.0072 max mem: 33370 +Epoch: [31] [1690/2639] eta: 0:46:08 lr: 1.2219839963723128e-05 loss: 0.0329 (0.0354) time: 2.9226 data: 0.0077 max mem: 33370 +Epoch: [31] [1700/2639] eta: 0:45:38 lr: 1.221485442189165e-05 loss: 0.0298 (0.0354) time: 2.8919 data: 0.0075 max mem: 33370 +Epoch: [31] 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1.2055197078738868e-05 loss: 0.0321 (0.0353) time: 2.9316 data: 0.0070 max mem: 33370 +Epoch: [31] [2030/2639] eta: 0:29:32 lr: 1.2050204015204382e-05 loss: 0.0327 (0.0353) time: 2.9366 data: 0.0071 max mem: 33370 +Epoch: [31] [2040/2639] eta: 0:29:03 lr: 1.2045210721781383e-05 loss: 0.0319 (0.0353) time: 2.9378 data: 0.0072 max mem: 33370 +Epoch: [31] [2050/2639] eta: 0:28:34 lr: 1.2040217198353371e-05 loss: 0.0342 (0.0353) time: 2.9341 data: 0.0072 max mem: 33370 +Epoch: [31] [2060/2639] eta: 0:28:05 lr: 1.2035223444803766e-05 loss: 0.0333 (0.0353) time: 2.9017 data: 0.0072 max mem: 33370 +Epoch: [31] [2070/2639] eta: 0:27:36 lr: 1.2030229461015859e-05 loss: 0.0314 (0.0352) time: 2.8827 data: 0.0072 max mem: 33370 +Epoch: [31] [2080/2639] eta: 0:27:07 lr: 1.202523524687282e-05 loss: 0.0335 (0.0353) time: 2.8473 data: 0.0072 max mem: 33370 +Epoch: [31] [2090/2639] eta: 0:26:37 lr: 1.2020240802257725e-05 loss: 0.0340 (0.0352) time: 2.8360 data: 0.0074 max mem: 33370 +Epoch: [31] [2100/2639] eta: 0:26:08 lr: 1.2015246127053516e-05 loss: 0.0257 (0.0352) time: 2.8374 data: 0.0075 max mem: 33370 +Epoch: [31] [2110/2639] eta: 0:25:39 lr: 1.2010251221143042e-05 loss: 0.0252 (0.0352) time: 2.8170 data: 0.0073 max mem: 33370 +Epoch: [31] [2120/2639] eta: 0:25:09 lr: 1.2005256084409018e-05 loss: 0.0323 (0.0352) time: 2.8494 data: 0.0073 max mem: 33370 +Epoch: [31] [2130/2639] eta: 0:24:40 lr: 1.2000260716734067e-05 loss: 0.0323 (0.0352) time: 2.8789 data: 0.0074 max mem: 33370 +Epoch: [31] [2140/2639] eta: 0:24:11 lr: 1.1995265118000673e-05 loss: 0.0325 (0.0353) time: 2.8787 data: 0.0075 max mem: 33370 +Epoch: [31] [2150/2639] eta: 0:23:42 lr: 1.1990269288091233e-05 loss: 0.0345 (0.0353) time: 2.8677 data: 0.0076 max mem: 33370 +Epoch: [31] [2160/2639] eta: 0:23:13 lr: 1.1985273226888002e-05 loss: 0.0352 (0.0353) time: 2.8826 data: 0.0075 max mem: 33370 +Epoch: [31] [2170/2639] eta: 0:22:44 lr: 1.1980276934273145e-05 loss: 0.0307 (0.0352) time: 2.8990 data: 0.0075 max mem: 33370 +Epoch: [31] [2180/2639] eta: 0:22:15 lr: 1.1975280410128693e-05 loss: 0.0301 (0.0352) time: 2.8995 data: 0.0074 max mem: 33370 +Epoch: [31] [2190/2639] eta: 0:21:45 lr: 1.197028365433658e-05 loss: 0.0349 (0.0352) time: 2.8935 data: 0.0073 max mem: 33370 +Epoch: [31] [2200/2639] eta: 0:21:16 lr: 1.1965286666778607e-05 loss: 0.0336 (0.0352) time: 2.8990 data: 0.0074 max mem: 33370 +Epoch: [31] [2210/2639] eta: 0:20:47 lr: 1.1960289447336478e-05 loss: 0.0325 (0.0352) time: 2.9017 data: 0.0074 max mem: 33370 +Epoch: [31] [2220/2639] eta: 0:20:18 lr: 1.1955291995891758e-05 loss: 0.0357 (0.0352) time: 2.8870 data: 0.0073 max mem: 33370 +Epoch: [31] [2230/2639] eta: 0:19:49 lr: 1.1950294312325925e-05 loss: 0.0334 (0.0352) time: 2.8856 data: 0.0071 max mem: 33370 +Epoch: [31] [2240/2639] eta: 0:19:20 lr: 1.1945296396520317e-05 loss: 0.0334 (0.0352) time: 2.8727 data: 0.0071 max mem: 33370 +Epoch: [31] [2250/2639] eta: 0:18:51 lr: 1.1940298248356175e-05 loss: 0.0314 (0.0352) time: 2.8620 data: 0.0072 max mem: 33370 +Epoch: [31] [2260/2639] eta: 0:18:22 lr: 1.1935299867714605e-05 loss: 0.0303 (0.0352) time: 2.8995 data: 0.0073 max mem: 33370 +Epoch: [31] [2270/2639] eta: 0:17:52 lr: 1.1930301254476617e-05 loss: 0.0346 (0.0352) time: 2.8570 data: 0.0074 max mem: 33370 +Epoch: [31] [2280/2639] eta: 0:17:23 lr: 1.1925302408523084e-05 loss: 0.0322 (0.0352) time: 2.8272 data: 0.0072 max mem: 33370 +Epoch: [31] [2290/2639] eta: 0:16:54 lr: 1.1920303329734785e-05 loss: 0.0311 (0.0352) time: 2.8656 data: 0.0076 max mem: 33370 +Epoch: [31] [2300/2639] eta: 0:16:25 lr: 1.1915304017992359e-05 loss: 0.0330 (0.0352) time: 2.8476 data: 0.0076 max mem: 33370 +Epoch: [31] [2310/2639] eta: 0:15:56 lr: 1.1910304473176343e-05 loss: 0.0355 (0.0353) time: 2.8375 data: 0.0071 max mem: 33370 +Epoch: [31] [2320/2639] eta: 0:15:27 lr: 1.1905304695167162e-05 loss: 0.0355 (0.0352) time: 2.8341 data: 0.0071 max mem: 33370 +Epoch: [31] [2330/2639] eta: 0:14:57 lr: 1.1900304683845102e-05 loss: 0.0313 (0.0353) time: 2.8401 data: 0.0072 max mem: 33370 +Epoch: [31] [2340/2639] eta: 0:14:28 lr: 1.1895304439090359e-05 loss: 0.0344 (0.0353) time: 2.8162 data: 0.0075 max mem: 33370 +Epoch: [31] [2350/2639] eta: 0:13:59 lr: 1.1890303960782982e-05 loss: 0.0361 (0.0353) time: 2.8291 data: 0.0074 max mem: 33370 +Epoch: [31] [2360/2639] eta: 0:13:30 lr: 1.1885303248802932e-05 loss: 0.0330 (0.0353) time: 2.8884 data: 0.0072 max mem: 33370 +Epoch: [31] [2370/2639] eta: 0:13:01 lr: 1.1880302303030027e-05 loss: 0.0325 (0.0353) time: 2.8797 data: 0.0074 max mem: 33370 +Epoch: [31] [2380/2639] eta: 0:12:32 lr: 1.187530112334399e-05 loss: 0.0332 (0.0353) time: 2.8494 data: 0.0073 max mem: 33370 +Epoch: [31] [2390/2639] eta: 0:12:03 lr: 1.1870299709624397e-05 loss: 0.0329 (0.0353) time: 2.8618 data: 0.0075 max mem: 33370 +Epoch: [31] [2400/2639] eta: 0:11:34 lr: 1.186529806175074e-05 loss: 0.0301 (0.0352) time: 2.8951 data: 0.0080 max mem: 33370 +Epoch: [31] [2410/2639] eta: 0:11:05 lr: 1.186029617960236e-05 loss: 0.0313 (0.0352) time: 2.9092 data: 0.0081 max mem: 33370 +Epoch: [31] [2420/2639] eta: 0:10:36 lr: 1.1855294063058506e-05 loss: 0.0281 (0.0352) time: 2.9094 data: 0.0077 max mem: 33370 +Epoch: [31] [2430/2639] eta: 0:10:07 lr: 1.1850291711998285e-05 loss: 0.0266 (0.0352) time: 2.8993 data: 0.0072 max mem: 33370 +Epoch: [31] [2440/2639] eta: 0:09:38 lr: 1.1845289126300706e-05 loss: 0.0299 (0.0352) time: 2.8750 data: 0.0072 max mem: 33370 +Epoch: [31] [2450/2639] eta: 0:09:08 lr: 1.1840286305844638e-05 loss: 0.0303 (0.0352) time: 2.8569 data: 0.0071 max mem: 33370 +Epoch: [31] [2460/2639] eta: 0:08:39 lr: 1.1835283250508856e-05 loss: 0.0324 (0.0352) time: 2.8338 data: 0.0075 max mem: 33370 +Epoch: [31] [2470/2639] eta: 0:08:10 lr: 1.1830279960171983e-05 loss: 0.0346 (0.0352) time: 2.8259 data: 0.0076 max mem: 33370 +Epoch: [31] [2480/2639] eta: 0:07:41 lr: 1.1825276434712558e-05 loss: 0.0345 (0.0352) time: 2.8583 data: 0.0075 max mem: 33370 +Epoch: [31] [2490/2639] eta: 0:07:12 lr: 1.1820272674008966e-05 loss: 0.0287 (0.0352) time: 2.8804 data: 0.0077 max mem: 33370 +Epoch: [31] [2500/2639] eta: 0:06:43 lr: 1.1815268677939502e-05 loss: 0.0319 (0.0352) time: 2.8763 data: 0.0076 max mem: 33370 +Epoch: [31] [2510/2639] eta: 0:06:14 lr: 1.1810264446382314e-05 loss: 0.0331 (0.0352) time: 2.8765 data: 0.0077 max mem: 33370 +Epoch: [31] [2520/2639] eta: 0:05:45 lr: 1.1805259979215454e-05 loss: 0.0323 (0.0352) time: 2.9070 data: 0.0075 max mem: 33370 +Epoch: [31] [2530/2639] eta: 0:05:16 lr: 1.180025527631683e-05 loss: 0.0331 (0.0352) time: 2.9154 data: 0.0072 max mem: 33370 +Epoch: [31] [2540/2639] eta: 0:04:47 lr: 1.1795250337564246e-05 loss: 0.0331 (0.0352) time: 2.9169 data: 0.0075 max mem: 33370 +Epoch: [31] [2550/2639] eta: 0:04:18 lr: 1.1790245162835387e-05 loss: 0.0317 (0.0352) time: 2.9261 data: 0.0076 max mem: 33370 +Epoch: [31] [2560/2639] eta: 0:03:49 lr: 1.1785239752007797e-05 loss: 0.0314 (0.0352) time: 2.9022 data: 0.0073 max mem: 33370 +Epoch: [31] [2570/2639] eta: 0:03:20 lr: 1.1780234104958923e-05 loss: 0.0290 (0.0351) time: 2.9028 data: 0.0073 max mem: 33370 +Epoch: [31] [2580/2639] eta: 0:02:51 lr: 1.1775228221566065e-05 loss: 0.0305 (0.0351) time: 2.8982 data: 0.0073 max mem: 33370 +Epoch: [31] [2590/2639] eta: 0:02:22 lr: 1.1770222101706432e-05 loss: 0.0303 (0.0351) time: 2.8725 data: 0.0071 max mem: 33370 +Epoch: [31] [2600/2639] eta: 0:01:53 lr: 1.1765215745257076e-05 loss: 0.0282 (0.0351) time: 2.8616 data: 0.0070 max mem: 33370 +Epoch: [31] [2610/2639] eta: 0:01:24 lr: 1.1760209152094963e-05 loss: 0.0299 (0.0351) time: 2.8817 data: 0.0071 max mem: 33370 +Epoch: [31] [2620/2639] eta: 0:00:55 lr: 1.1755202322096902e-05 loss: 0.0330 (0.0351) time: 2.8947 data: 0.0071 max mem: 33370 +Epoch: [31] [2630/2639] eta: 0:00:26 lr: 1.1750195255139611e-05 loss: 0.0339 (0.0351) time: 2.8742 data: 0.0070 max mem: 33370 +Epoch: [31] Total time: 2:07:42 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 2:29:40 time: 3.4903 data: 3.3814 max mem: 33370 +Test: [ 100/2573] eta: 0:04:31 time: 0.0755 data: 0.0014 max mem: 33370 +Test: [ 200/2573] eta: 0:03:43 time: 0.0781 data: 0.0014 max mem: 33370 +Test: [ 300/2573] eta: 0:03:21 time: 0.0796 data: 0.0013 max mem: 33370 +Test: [ 400/2573] eta: 0:03:06 time: 0.0794 data: 0.0014 max mem: 33370 +Test: [ 500/2573] eta: 0:02:54 time: 0.0783 data: 0.0014 max mem: 33370 +Test: [ 600/2573] eta: 0:02:44 time: 0.0778 data: 0.0010 max mem: 33370 +Test: [ 700/2573] eta: 0:02:35 time: 0.0788 data: 0.0013 max mem: 33370 +Test: [ 800/2573] eta: 0:02:26 time: 0.0817 data: 0.0012 max mem: 33370 +Test: [ 900/2573] eta: 0:02:37 time: 0.0788 data: 0.0014 max mem: 33370 +Test: [1000/2573] eta: 0:02:25 time: 0.0785 data: 0.0013 max mem: 33370 +Test: [1100/2573] eta: 0:02:14 time: 0.0798 data: 0.0013 max mem: 33370 +Test: [1200/2573] eta: 0:02:04 time: 0.0789 data: 0.0014 max mem: 33370 +Test: [1300/2573] eta: 0:01:54 time: 0.0795 data: 0.0015 max mem: 33370 +Test: [1400/2573] eta: 0:01:44 time: 0.0787 data: 0.0014 max mem: 33370 +Test: [1500/2573] eta: 0:01:34 time: 0.0781 data: 0.0012 max mem: 33370 +Test: [1600/2573] eta: 0:01:25 time: 0.0826 data: 0.0015 max mem: 33370 +Test: [1700/2573] eta: 0:01:16 time: 0.0769 data: 0.0014 max mem: 33370 +Test: [1800/2573] eta: 0:01:07 time: 0.0808 data: 0.0013 max mem: 33370 +Test: [1900/2573] eta: 0:00:58 time: 0.0774 data: 0.0020 max mem: 33370 +Test: [2000/2573] eta: 0:00:51 time: 0.2950 data: 0.2165 max mem: 33370 +Test: [2100/2573] eta: 0:00:44 time: 0.0815 data: 0.0014 max mem: 33370 +Test: [2200/2573] eta: 0:00:34 time: 0.0803 data: 0.0015 max mem: 33370 +Test: [2300/2573] eta: 0:00:25 time: 0.0800 data: 0.0014 max mem: 33370 +Test: [2400/2573] eta: 0:00:15 time: 0.0753 data: 0.0013 max mem: 33370 +Test: [2500/2573] eta: 0:00:06 time: 0.0787 data: 0.0013 max mem: 33370 +Test: Total time: 0:03:54 +Final results: +Mean IoU is 63.90 + + precision@0.5 = 72.20 + precision@0.6 = 66.73 + precision@0.7 = 59.80 + precision@0.8 = 49.49 + precision@0.9 = 25.06 + overall IoU = 61.44 + +Average object IoU 63.90020618445986 +Overall IoU 61.44015121459961 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [32] [ 0/2639] eta: 5:39:58 lr: 1.1745688692175894e-05 loss: 0.0253 (0.0253) time: 7.7295 data: 4.6150 max mem: 33370 +Epoch: [32] [ 10/2639] eta: 2:27:39 lr: 1.1740681174655926e-05 loss: 0.0321 (0.0321) time: 3.3698 data: 0.4266 max mem: 33370 +Epoch: [32] [ 20/2639] eta: 2:16:57 lr: 1.1735673419818473e-05 loss: 0.0308 (0.0311) time: 2.9080 data: 0.0070 max mem: 33370 +Epoch: [32] [ 30/2639] eta: 2:12:20 lr: 1.1730665427539747e-05 loss: 0.0306 (0.0336) time: 2.8643 data: 0.0069 max mem: 33370 +Epoch: [32] [ 40/2639] eta: 2:09:58 lr: 1.1725657197695861e-05 loss: 0.0304 (0.0328) time: 2.8568 data: 0.0075 max mem: 33370 +Epoch: [32] [ 50/2639] eta: 2:08:12 lr: 1.172064873016278e-05 loss: 0.0299 (0.0324) time: 2.8592 data: 0.0073 max mem: 33370 +Epoch: [32] [ 60/2639] eta: 2:07:21 lr: 1.1715640024816373e-05 loss: 0.0292 (0.0324) time: 2.8863 data: 0.0071 max mem: 33370 +Epoch: [32] [ 70/2639] eta: 2:06:44 lr: 1.1710631081532353e-05 loss: 0.0296 (0.0323) time: 2.9321 data: 0.0071 max mem: 33370 +Epoch: [32] [ 80/2639] eta: 2:05:10 lr: 1.1705621900186343e-05 loss: 0.0280 (0.0317) time: 2.8491 data: 0.0071 max mem: 33370 +Epoch: [32] [ 90/2639] eta: 2:04:28 lr: 1.1700612480653807e-05 loss: 0.0282 (0.0319) time: 2.8229 data: 0.0071 max mem: 33370 +Epoch: [32] [ 100/2639] eta: 2:03:33 lr: 1.1695602822810118e-05 loss: 0.0305 (0.0323) time: 2.8583 data: 0.0072 max mem: 33370 +Epoch: [32] [ 110/2639] eta: 2:03:13 lr: 1.1690592926530499e-05 loss: 0.0321 (0.0323) time: 2.8945 data: 0.0074 max mem: 33370 +Epoch: [32] [ 120/2639] eta: 2:02:29 lr: 1.1685582791690064e-05 loss: 0.0321 (0.0324) time: 2.9061 data: 0.0074 max mem: 33370 +Epoch: [32] [ 130/2639] eta: 2:01:50 lr: 1.168057241816379e-05 loss: 0.0299 (0.0321) time: 2.8579 data: 0.0076 max mem: 33370 +Epoch: [32] [ 140/2639] eta: 2:01:19 lr: 1.1675561805826541e-05 loss: 0.0310 (0.0324) time: 2.8844 data: 0.0077 max mem: 33370 +Epoch: [32] [ 150/2639] eta: 2:00:37 lr: 1.1670550954553043e-05 loss: 0.0310 (0.0321) time: 2.8698 data: 0.0075 max mem: 33370 +Epoch: [32] [ 160/2639] eta: 1:59:59 lr: 1.166553986421791e-05 loss: 0.0265 (0.0320) time: 2.8434 data: 0.0078 max mem: 33370 +Epoch: [32] [ 170/2639] eta: 1:59:14 lr: 1.1660528534695616e-05 loss: 0.0273 (0.0318) time: 2.8200 data: 0.0079 max mem: 33370 +Epoch: [32] [ 180/2639] eta: 1:58:44 lr: 1.165551696586052e-05 loss: 0.0295 (0.0318) time: 2.8407 data: 0.0075 max mem: 33370 +Epoch: [32] [ 190/2639] eta: 1:58:07 lr: 1.1650505157586858e-05 loss: 0.0296 (0.0317) time: 2.8630 data: 0.0074 max mem: 33370 +Epoch: [32] [ 200/2639] eta: 1:57:27 lr: 1.164549310974872e-05 loss: 0.0283 (0.0316) time: 2.8182 data: 0.0076 max mem: 33370 +Epoch: [32] [ 210/2639] eta: 1:56:52 lr: 1.1640480822220096e-05 loss: 0.0242 (0.0314) time: 2.8211 data: 0.0076 max mem: 33370 +Epoch: [32] [ 220/2639] eta: 1:56:17 lr: 1.1635468294874825e-05 loss: 0.0260 (0.0315) time: 2.8374 data: 0.0072 max mem: 33370 +Epoch: [32] [ 230/2639] eta: 1:55:47 lr: 1.1630455527586641e-05 loss: 0.0287 (0.0315) time: 2.8525 data: 0.0069 max mem: 33370 +Epoch: [32] [ 240/2639] eta: 1:55:13 lr: 1.1625442520229127e-05 loss: 0.0323 (0.0317) time: 2.8507 data: 0.0068 max mem: 33370 +Epoch: [32] [ 250/2639] eta: 1:54:39 lr: 1.1620429272675768e-05 loss: 0.0331 (0.0317) time: 2.8280 data: 0.0071 max mem: 33370 +Epoch: [32] [ 260/2639] eta: 1:54:05 lr: 1.161541578479989e-05 loss: 0.0269 (0.0317) time: 2.8266 data: 0.0074 max mem: 33370 +Epoch: [32] [ 270/2639] eta: 1:53:43 lr: 1.161040205647472e-05 loss: 0.0284 (0.0319) time: 2.8885 data: 0.0073 max mem: 33370 +Epoch: [32] [ 280/2639] eta: 1:53:17 lr: 1.1605388087573333e-05 loss: 0.0296 (0.0318) time: 2.9342 data: 0.0072 max mem: 33370 +Epoch: [32] [ 290/2639] eta: 1:52:47 lr: 1.1600373877968699e-05 loss: 0.0291 (0.0318) time: 2.8890 data: 0.0072 max mem: 33370 +Epoch: [32] [ 300/2639] eta: 1:52:23 lr: 1.159535942753364e-05 loss: 0.0289 (0.0319) time: 2.9025 data: 0.0073 max mem: 33370 +Epoch: [32] [ 310/2639] eta: 1:51:56 lr: 1.1590344736140864e-05 loss: 0.0299 (0.0319) time: 2.9284 data: 0.0074 max mem: 33370 +Epoch: [32] [ 320/2639] eta: 1:51:21 lr: 1.1585329803662936e-05 loss: 0.0335 (0.0321) time: 2.8555 data: 0.0073 max mem: 33370 +Epoch: [32] [ 330/2639] eta: 1:50:50 lr: 1.1580314629972311e-05 loss: 0.0295 (0.0322) time: 2.8201 data: 0.0076 max mem: 33370 +Epoch: [32] [ 340/2639] eta: 1:50:18 lr: 1.1575299214941295e-05 loss: 0.0294 (0.0323) time: 2.8395 data: 0.0076 max mem: 33370 +Epoch: [32] [ 350/2639] eta: 1:49:47 lr: 1.1570283558442085e-05 loss: 0.0294 (0.0322) time: 2.8442 data: 0.0073 max mem: 33370 +Epoch: [32] [ 360/2639] eta: 1:49:14 lr: 1.1565267660346727e-05 loss: 0.0273 (0.0322) time: 2.8298 data: 0.0071 max mem: 33370 +Epoch: [32] [ 370/2639] eta: 1:48:49 lr: 1.1560251520527163e-05 loss: 0.0301 (0.0321) time: 2.8708 data: 0.0071 max mem: 33370 +Epoch: [32] [ 380/2639] eta: 1:48:18 lr: 1.1555235138855175e-05 loss: 0.0331 (0.0323) time: 2.8867 data: 0.0073 max mem: 33370 +Epoch: [32] [ 390/2639] eta: 1:47:48 lr: 1.1550218515202448e-05 loss: 0.0327 (0.0322) time: 2.8529 data: 0.0077 max mem: 33370 +Epoch: [32] [ 400/2639] eta: 1:47:18 lr: 1.1545201649440505e-05 loss: 0.0302 (0.0322) time: 2.8531 data: 0.0081 max mem: 33370 +Epoch: [32] [ 410/2639] eta: 1:46:49 lr: 1.154018454144077e-05 loss: 0.0332 (0.0322) time: 2.8626 data: 0.0077 max mem: 33370 +Epoch: [32] [ 420/2639] eta: 1:46:19 lr: 1.1535167191074504e-05 loss: 0.0332 (0.0323) time: 2.8594 data: 0.0073 max mem: 33370 +Epoch: [32] [ 430/2639] eta: 1:45:51 lr: 1.1530149598212862e-05 loss: 0.0290 (0.0323) time: 2.8629 data: 0.0073 max mem: 33370 +Epoch: [32] [ 440/2639] eta: 1:45:24 lr: 1.1525131762726868e-05 loss: 0.0319 (0.0323) time: 2.9070 data: 0.0073 max mem: 33370 +Epoch: [32] [ 450/2639] eta: 1:44:55 lr: 1.1520113684487393e-05 loss: 0.0321 (0.0323) time: 2.8907 data: 0.0076 max mem: 33370 +Epoch: [32] [ 460/2639] eta: 1:44:24 lr: 1.1515095363365204e-05 loss: 0.0265 (0.0322) time: 2.8494 data: 0.0076 max mem: 33370 +Epoch: [32] [ 470/2639] eta: 1:43:53 lr: 1.1510076799230912e-05 loss: 0.0293 (0.0323) time: 2.8307 data: 0.0073 max mem: 33370 +Epoch: [32] [ 480/2639] eta: 1:43:27 lr: 1.1505057991955018e-05 loss: 0.0325 (0.0323) time: 2.8793 data: 0.0073 max mem: 33370 +Epoch: [32] [ 490/2639] eta: 1:42:59 lr: 1.150003894140787e-05 loss: 0.0284 (0.0322) time: 2.9189 data: 0.0072 max mem: 33370 +Epoch: [32] [ 500/2639] eta: 1:42:30 lr: 1.1495019647459706e-05 loss: 0.0275 (0.0321) time: 2.8824 data: 0.0075 max mem: 33370 +Epoch: [32] [ 510/2639] eta: 1:42:00 lr: 1.1490000109980611e-05 loss: 0.0255 (0.0321) time: 2.8548 data: 0.0075 max mem: 33370 +Epoch: [32] [ 520/2639] eta: 1:41:32 lr: 1.1484980328840558e-05 loss: 0.0295 (0.0321) time: 2.8670 data: 0.0072 max mem: 33370 +Epoch: [32] [ 530/2639] eta: 1:41:04 lr: 1.1479960303909364e-05 loss: 0.0312 (0.0322) time: 2.8957 data: 0.0073 max mem: 33370 +Epoch: [32] [ 540/2639] eta: 1:40:35 lr: 1.147494003505674e-05 loss: 0.0326 (0.0323) time: 2.8754 data: 0.0072 max mem: 33370 +Epoch: [32] [ 550/2639] eta: 1:40:05 lr: 1.1469919522152238e-05 loss: 0.0296 (0.0322) time: 2.8554 data: 0.0069 max mem: 33370 +Epoch: [32] [ 560/2639] eta: 1:39:36 lr: 1.1464898765065297e-05 loss: 0.0264 (0.0322) time: 2.8654 data: 0.0072 max mem: 33370 +Epoch: [32] [ 570/2639] eta: 1:39:08 lr: 1.1459877763665207e-05 loss: 0.0297 (0.0322) time: 2.8798 data: 0.0075 max mem: 33370 +Epoch: [32] [ 580/2639] eta: 1:38:40 lr: 1.1454856517821138e-05 loss: 0.0297 (0.0323) time: 2.8961 data: 0.0075 max mem: 33370 +Epoch: [32] [ 590/2639] eta: 1:38:11 lr: 1.1449835027402115e-05 loss: 0.0306 (0.0323) time: 2.8870 data: 0.0073 max mem: 33370 +Epoch: [32] [ 600/2639] eta: 1:37:40 lr: 1.144481329227704e-05 loss: 0.0281 (0.0324) time: 2.8396 data: 0.0071 max mem: 33370 +Epoch: [32] [ 610/2639] eta: 1:37:11 lr: 1.1439791312314663e-05 loss: 0.0261 (0.0323) time: 2.8360 data: 0.0072 max mem: 33370 +Epoch: [32] [ 620/2639] eta: 1:36:43 lr: 1.1434769087383625e-05 loss: 0.0261 (0.0323) time: 2.8700 data: 0.0073 max mem: 33370 +Epoch: [32] [ 630/2639] eta: 1:36:14 lr: 1.1429746617352406e-05 loss: 0.0296 (0.0325) time: 2.8834 data: 0.0072 max mem: 33370 +Epoch: [32] [ 640/2639] eta: 1:35:43 lr: 1.1424723902089374e-05 loss: 0.0310 (0.0325) time: 2.8480 data: 0.0071 max mem: 33370 +Epoch: [32] [ 650/2639] eta: 1:35:16 lr: 1.1419700941462743e-05 loss: 0.0310 (0.0325) time: 2.8531 data: 0.0073 max mem: 33370 +Epoch: [32] [ 660/2639] eta: 1:34:46 lr: 1.1414677735340611e-05 loss: 0.0306 (0.0325) time: 2.8689 data: 0.0073 max mem: 33370 +Epoch: [32] [ 670/2639] eta: 1:34:17 lr: 1.1409654283590914e-05 loss: 0.0311 (0.0325) time: 2.8498 data: 0.0071 max mem: 33370 +Epoch: [32] [ 680/2639] eta: 1:33:48 lr: 1.140463058608148e-05 loss: 0.0333 (0.0326) time: 2.8755 data: 0.0073 max mem: 33370 +Epoch: [32] [ 690/2639] eta: 1:33:22 lr: 1.1399606642679992e-05 loss: 0.0329 (0.0326) time: 2.9144 data: 0.0075 max mem: 33370 +Epoch: [32] [ 700/2639] eta: 1:32:54 lr: 1.1394582453253984e-05 loss: 0.0309 (0.0327) time: 2.9245 data: 0.0074 max mem: 33370 +Epoch: [32] [ 710/2639] eta: 1:32:25 lr: 1.1389558017670873e-05 loss: 0.0326 (0.0327) time: 2.8968 data: 0.0073 max mem: 33370 +Epoch: [32] [ 720/2639] eta: 1:31:58 lr: 1.138453333579792e-05 loss: 0.0304 (0.0326) time: 2.9067 data: 0.0073 max mem: 33370 +Epoch: [32] [ 730/2639] eta: 1:31:29 lr: 1.1379508407502274e-05 loss: 0.0324 (0.0327) time: 2.8897 data: 0.0073 max mem: 33370 +Epoch: [32] [ 740/2639] eta: 1:30:59 lr: 1.1374483232650917e-05 loss: 0.0324 (0.0327) time: 2.8524 data: 0.0076 max mem: 33370 +Epoch: [32] [ 750/2639] eta: 1:30:31 lr: 1.1369457811110725e-05 loss: 0.0319 (0.0327) time: 2.8666 data: 0.0077 max mem: 33370 +Epoch: [32] [ 760/2639] eta: 1:30:03 lr: 1.1364432142748408e-05 loss: 0.0301 (0.0327) time: 2.8934 data: 0.0075 max mem: 33370 +Epoch: [32] [ 770/2639] eta: 1:29:36 lr: 1.1359406227430564e-05 loss: 0.0293 (0.0327) time: 2.9296 data: 0.0072 max mem: 33370 +Epoch: [32] [ 780/2639] eta: 1:29:07 lr: 1.1354380065023629e-05 loss: 0.0319 (0.0326) time: 2.9113 data: 0.0072 max mem: 33370 +Epoch: [32] [ 790/2639] eta: 1:28:39 lr: 1.1349353655393923e-05 loss: 0.0325 (0.0326) time: 2.8938 data: 0.0074 max mem: 33370 +Epoch: [32] [ 800/2639] eta: 1:28:10 lr: 1.1344326998407612e-05 loss: 0.0299 (0.0326) time: 2.9022 data: 0.0071 max mem: 33370 +Epoch: [32] [ 810/2639] eta: 1:27:41 lr: 1.1339300093930736e-05 loss: 0.0312 (0.0327) time: 2.8580 data: 0.0070 max mem: 33370 +Epoch: [32] [ 820/2639] eta: 1:27:11 lr: 1.1334272941829183e-05 loss: 0.0312 (0.0327) time: 2.8253 data: 0.0072 max mem: 33370 +Epoch: [32] [ 830/2639] eta: 1:26:40 lr: 1.1329245541968715e-05 loss: 0.0311 (0.0327) time: 2.8162 data: 0.0075 max mem: 33370 +Epoch: [32] [ 840/2639] eta: 1:26:10 lr: 1.1324217894214943e-05 loss: 0.0310 (0.0328) time: 2.8064 data: 0.0076 max mem: 33370 +Epoch: [32] [ 850/2639] eta: 1:25:41 lr: 1.1319189998433354e-05 loss: 0.0278 (0.0327) time: 2.8343 data: 0.0074 max mem: 33370 +Epoch: [32] [ 860/2639] eta: 1:25:11 lr: 1.1314161854489278e-05 loss: 0.0273 (0.0327) time: 2.8273 data: 0.0072 max mem: 33370 +Epoch: [32] [ 870/2639] eta: 1:24:41 lr: 1.1309133462247921e-05 loss: 0.0273 (0.0328) time: 2.7976 data: 0.0072 max mem: 33370 +Epoch: [32] [ 880/2639] eta: 1:24:11 lr: 1.1304104821574334e-05 loss: 0.0285 (0.0328) time: 2.8229 data: 0.0073 max mem: 33370 +Epoch: [32] [ 890/2639] eta: 1:23:41 lr: 1.1299075932333446e-05 loss: 0.0318 (0.0328) time: 2.8251 data: 0.0076 max mem: 33370 +Epoch: [32] [ 900/2639] eta: 1:23:13 lr: 1.1294046794390024e-05 loss: 0.0295 (0.0328) time: 2.8401 data: 0.0074 max mem: 33370 +Epoch: [32] [ 910/2639] eta: 1:22:43 lr: 1.128901740760872e-05 loss: 0.0269 (0.0329) time: 2.8504 data: 0.0071 max mem: 33370 +Epoch: [32] [ 920/2639] eta: 1:22:14 lr: 1.128398777185402e-05 loss: 0.0285 (0.0329) time: 2.8366 data: 0.0074 max mem: 33370 +Epoch: [32] [ 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mem: 33370 +Epoch: [32] [1010/2639] eta: 1:17:56 lr: 1.123870982383127e-05 loss: 0.0279 (0.0329) time: 2.8639 data: 0.0073 max mem: 33370 +Epoch: [32] [1020/2639] eta: 1:17:28 lr: 1.1233677690858912e-05 loss: 0.0328 (0.0330) time: 2.8914 data: 0.0072 max mem: 33370 +Epoch: [32] [1030/2639] eta: 1:16:59 lr: 1.1228645307413279e-05 loss: 0.0348 (0.0329) time: 2.8885 data: 0.0075 max mem: 33370 +Epoch: [32] [1040/2639] eta: 1:16:30 lr: 1.1223612673357178e-05 loss: 0.0303 (0.0330) time: 2.8658 data: 0.0073 max mem: 33370 +Epoch: [32] [1050/2639] eta: 1:16:01 lr: 1.121857978855324e-05 loss: 0.0327 (0.0330) time: 2.8591 data: 0.0071 max mem: 33370 +Epoch: [32] [1060/2639] eta: 1:15:33 lr: 1.1213546652863988e-05 loss: 0.0310 (0.0330) time: 2.8760 data: 0.0070 max mem: 33370 +Epoch: [32] [1070/2639] eta: 1:15:05 lr: 1.1208513266151767e-05 loss: 0.0295 (0.0330) time: 2.8975 data: 0.0070 max mem: 33370 +Epoch: [32] [1080/2639] eta: 1:14:36 lr: 1.1203479628278806e-05 loss: 0.0301 (0.0330) time: 2.8925 data: 0.0071 max mem: 33370 +Epoch: [32] [1090/2639] eta: 1:14:07 lr: 1.1198445739107163e-05 loss: 0.0334 (0.0331) time: 2.8738 data: 0.0070 max mem: 33370 +Epoch: [32] [1100/2639] eta: 1:13:39 lr: 1.1193411598498781e-05 loss: 0.0327 (0.0332) time: 2.8688 data: 0.0072 max mem: 33370 +Epoch: [32] [1110/2639] eta: 1:13:10 lr: 1.1188377206315428e-05 loss: 0.0327 (0.0332) time: 2.8710 data: 0.0073 max mem: 33370 +Epoch: [32] [1120/2639] eta: 1:12:41 lr: 1.1183342562418754e-05 loss: 0.0295 (0.0331) time: 2.8664 data: 0.0072 max mem: 33370 +Epoch: [32] [1130/2639] eta: 1:12:12 lr: 1.117830766667024e-05 loss: 0.0282 (0.0331) time: 2.8381 data: 0.0077 max mem: 33370 +Epoch: [32] [1140/2639] eta: 1:11:43 lr: 1.1173272518931239e-05 loss: 0.0297 (0.0332) time: 2.8210 data: 0.0081 max mem: 33370 +Epoch: [32] [1150/2639] eta: 1:11:13 lr: 1.1168237119062946e-05 loss: 0.0265 (0.0331) time: 2.8322 data: 0.0079 max mem: 33370 +Epoch: [32] [1160/2639] eta: 1:10:44 lr: 1.1163201466926419e-05 loss: 0.0271 (0.0332) time: 2.8327 data: 0.0076 max mem: 33370 +Epoch: [32] [1170/2639] eta: 1:10:16 lr: 1.1158165562382572e-05 loss: 0.0277 (0.0331) time: 2.8671 data: 0.0074 max mem: 33370 +Epoch: [32] [1180/2639] eta: 1:09:47 lr: 1.1153129405292154e-05 loss: 0.0266 (0.0332) time: 2.8614 data: 0.0077 max mem: 33370 +Epoch: [32] [1190/2639] eta: 1:09:18 lr: 1.1148092995515792e-05 loss: 0.0304 (0.0332) time: 2.8551 data: 0.0079 max mem: 33370 +Epoch: [32] [1200/2639] eta: 1:08:49 lr: 1.1143056332913943e-05 loss: 0.0304 (0.0332) time: 2.8678 data: 0.0085 max mem: 33370 +Epoch: [32] [1210/2639] eta: 1:08:21 lr: 1.1138019417346943e-05 loss: 0.0325 (0.0332) time: 2.8701 data: 0.0081 max mem: 33370 +Epoch: [32] [1220/2639] eta: 1:07:52 lr: 1.1132982248674947e-05 loss: 0.0316 (0.0332) time: 2.8816 data: 0.0072 max mem: 33370 +Epoch: [32] [1230/2639] eta: 1:07:23 lr: 1.1127944826757997e-05 loss: 0.0311 (0.0332) time: 2.8725 data: 0.0072 max mem: 33370 +Epoch: [32] [1240/2639] eta: 1:06:55 lr: 1.1122907151455958e-05 loss: 0.0309 (0.0332) time: 2.8681 data: 0.0072 max mem: 33370 +Epoch: [32] [1250/2639] eta: 1:06:26 lr: 1.1117869222628572e-05 loss: 0.0309 (0.0332) time: 2.8601 data: 0.0072 max mem: 33370 +Epoch: [32] [1260/2639] eta: 1:05:57 lr: 1.1112831040135409e-05 loss: 0.0295 (0.0332) time: 2.8529 data: 0.0077 max mem: 33370 +Epoch: [32] [1270/2639] eta: 1:05:27 lr: 1.1107792603835914e-05 loss: 0.0265 (0.0331) time: 2.8251 data: 0.0078 max mem: 33370 +Epoch: [32] [1280/2639] eta: 1:04:58 lr: 1.1102753913589359e-05 loss: 0.0295 (0.0332) time: 2.8219 data: 0.0075 max mem: 33370 +Epoch: [32] [1290/2639] eta: 1:04:30 lr: 1.1097714969254891e-05 loss: 0.0335 (0.0332) time: 2.8550 data: 0.0075 max mem: 33370 +Epoch: [32] [1300/2639] eta: 1:04:01 lr: 1.1092675770691485e-05 loss: 0.0334 (0.0332) time: 2.8648 data: 0.0073 max mem: 33370 +Epoch: [32] [1310/2639] eta: 1:03:32 lr: 1.1087636317757988e-05 loss: 0.0316 (0.0332) time: 2.8770 data: 0.0075 max mem: 33370 +Epoch: [32] [1320/2639] eta: 1:03:04 lr: 1.1082596610313078e-05 loss: 0.0324 (0.0333) time: 2.8691 data: 0.0078 max mem: 33370 +Epoch: [32] [1330/2639] eta: 1:02:35 lr: 1.1077556648215299e-05 loss: 0.0312 (0.0333) time: 2.8546 data: 0.0073 max mem: 33370 +Epoch: [32] [1340/2639] eta: 1:02:06 lr: 1.107251643132303e-05 loss: 0.0324 (0.0333) time: 2.8673 data: 0.0075 max mem: 33370 +Epoch: [32] [1350/2639] eta: 1:01:37 lr: 1.1067475959494518e-05 loss: 0.0341 (0.0333) time: 2.8562 data: 0.0077 max mem: 33370 +Epoch: [32] [1360/2639] eta: 1:01:08 lr: 1.1062435232587836e-05 loss: 0.0341 (0.0333) time: 2.8421 data: 0.0074 max mem: 33370 +Epoch: [32] [1370/2639] eta: 1:00:40 lr: 1.1057394250460931e-05 loss: 0.0313 (0.0333) time: 2.8639 data: 0.0074 max mem: 33370 +Epoch: [32] [1380/2639] eta: 1:00:11 lr: 1.1052353012971575e-05 loss: 0.0292 (0.0333) time: 2.8825 data: 0.0075 max mem: 33370 +Epoch: [32] [1390/2639] eta: 0:59:42 lr: 1.1047311519977411e-05 loss: 0.0278 (0.0333) time: 2.8489 data: 0.0075 max mem: 33370 +Epoch: [32] [1400/2639] eta: 0:59:13 lr: 1.104226977133591e-05 loss: 0.0283 (0.0333) time: 2.8249 data: 0.0073 max mem: 33370 +Epoch: [32] [1410/2639] eta: 0:58:45 lr: 1.1037227766904403e-05 loss: 0.0306 (0.0333) time: 2.8700 data: 0.0075 max mem: 33370 +Epoch: [32] [1420/2639] eta: 0:58:16 lr: 1.1032185506540076e-05 loss: 0.0322 (0.0333) time: 2.8747 data: 0.0080 max mem: 33370 +Epoch: [32] [1430/2639] eta: 0:57:47 lr: 1.102714299009994e-05 loss: 0.0306 (0.0333) time: 2.8518 data: 0.0079 max mem: 33370 +Epoch: [32] [1440/2639] eta: 0:57:18 lr: 1.1022100217440882e-05 loss: 0.0327 (0.0333) time: 2.8711 data: 0.0076 max mem: 33370 +Epoch: [32] [1450/2639] eta: 0:56:50 lr: 1.1017057188419603e-05 loss: 0.0365 (0.0334) time: 2.8876 data: 0.0076 max mem: 33370 +Epoch: [32] [1460/2639] eta: 0:56:21 lr: 1.1012013902892686e-05 loss: 0.0321 (0.0334) time: 2.8849 data: 0.0074 max mem: 33370 +Epoch: [32] [1470/2639] eta: 0:55:52 lr: 1.1006970360716529e-05 loss: 0.0302 (0.0333) time: 2.8552 data: 0.0073 max mem: 33370 +Epoch: [32] [1480/2639] eta: 0:55:23 lr: 1.1001926561747404e-05 loss: 0.0317 (0.0334) time: 2.8049 data: 0.0074 max mem: 33370 +Epoch: [32] [1490/2639] eta: 0:54:53 lr: 1.0996882505841407e-05 loss: 0.0326 (0.0334) time: 2.7702 data: 0.0076 max mem: 33370 +Epoch: [32] [1500/2639] eta: 0:54:25 lr: 1.0991838192854495e-05 loss: 0.0314 (0.0333) time: 2.8299 data: 0.0077 max mem: 33370 +Epoch: [32] [1510/2639] eta: 0:53:57 lr: 1.098679362264246e-05 loss: 0.0306 (0.0333) time: 2.9016 data: 0.0075 max mem: 33370 +Epoch: [32] [1520/2639] eta: 0:53:28 lr: 1.0981748795060952e-05 loss: 0.0323 (0.0333) time: 2.8807 data: 0.0071 max mem: 33370 +Epoch: [32] [1530/2639] eta: 0:52:59 lr: 1.097670370996545e-05 loss: 0.0323 (0.0334) time: 2.8790 data: 0.0071 max mem: 33370 +Epoch: [32] [1540/2639] eta: 0:52:31 lr: 1.0971658367211296e-05 loss: 0.0335 (0.0333) time: 2.9212 data: 0.0075 max mem: 33370 +Epoch: [32] [1550/2639] eta: 0:52:03 lr: 1.0966612766653656e-05 loss: 0.0307 (0.0333) time: 2.8991 data: 0.0077 max mem: 33370 +Epoch: [32] [1560/2639] eta: 0:51:34 lr: 1.0961566908147568e-05 loss: 0.0272 (0.0333) time: 2.8755 data: 0.0075 max mem: 33370 +Epoch: [32] [1570/2639] eta: 0:51:05 lr: 1.0956520791547884e-05 loss: 0.0301 (0.0334) time: 2.8651 data: 0.0073 max mem: 33370 +Epoch: [32] [1580/2639] eta: 0:50:36 lr: 1.0951474416709323e-05 loss: 0.0325 (0.0334) time: 2.8486 data: 0.0073 max mem: 33370 +Epoch: [32] [1590/2639] eta: 0:50:08 lr: 1.0946427783486433e-05 loss: 0.0293 (0.0334) time: 2.8536 data: 0.0073 max mem: 33370 +Epoch: [32] [1600/2639] eta: 0:49:39 lr: 1.094138089173362e-05 loss: 0.0288 (0.0334) time: 2.8304 data: 0.0075 max mem: 33370 +Epoch: [32] [1610/2639] eta: 0:49:10 lr: 1.0936333741305117e-05 loss: 0.0293 (0.0334) time: 2.8463 data: 0.0076 max mem: 33370 +Epoch: [32] [1620/2639] eta: 0:48:41 lr: 1.0931286332055015e-05 loss: 0.0305 (0.0334) time: 2.8795 data: 0.0074 max mem: 33370 +Epoch: [32] [1630/2639] eta: 0:48:13 lr: 1.0926238663837232e-05 loss: 0.0305 (0.0334) time: 2.8654 data: 0.0074 max mem: 33370 +Epoch: [32] [1640/2639] eta: 0:47:44 lr: 1.0921190736505548e-05 loss: 0.0322 (0.0334) time: 2.8953 data: 0.0073 max mem: 33370 +Epoch: [32] [1650/2639] eta: 0:47:16 lr: 1.0916142549913564e-05 loss: 0.0298 (0.0334) time: 2.9411 data: 0.0075 max mem: 33370 +Epoch: [32] [1660/2639] eta: 0:46:47 lr: 1.091109410391474e-05 loss: 0.0317 (0.0334) time: 2.8867 data: 0.0075 max mem: 33370 +Epoch: [32] [1670/2639] eta: 0:46:19 lr: 1.0906045398362377e-05 loss: 0.0316 (0.0334) time: 2.9074 data: 0.0072 max mem: 33370 +Epoch: [32] [1680/2639] eta: 0:45:50 lr: 1.09009964331096e-05 loss: 0.0304 (0.0334) time: 2.9084 data: 0.0074 max mem: 33370 +Epoch: [32] [1690/2639] eta: 0:45:22 lr: 1.0895947208009398e-05 loss: 0.0295 (0.0333) time: 2.8453 data: 0.0076 max mem: 33370 +Epoch: [32] [1700/2639] eta: 0:44:53 lr: 1.089089772291458e-05 loss: 0.0295 (0.0333) time: 2.8574 data: 0.0076 max mem: 33370 +Epoch: [32] [1710/2639] eta: 0:44:25 lr: 1.0885847977677817e-05 loss: 0.0306 (0.0333) time: 2.9050 data: 0.0074 max mem: 33370 +Epoch: [32] [1720/2639] eta: 0:43:56 lr: 1.0880797972151598e-05 loss: 0.0305 (0.0333) time: 2.9195 data: 0.0072 max mem: 33370 +Epoch: [32] [1730/2639] eta: 0:43:27 lr: 1.0875747706188277e-05 loss: 0.0305 (0.0334) time: 2.8653 data: 0.0079 max mem: 33370 +Epoch: [32] [1740/2639] eta: 0:42:59 lr: 1.0870697179640022e-05 loss: 0.0347 (0.0334) time: 2.8789 data: 0.0086 max mem: 33370 +Epoch: [32] [1750/2639] eta: 0:42:30 lr: 1.0865646392358865e-05 loss: 0.0266 (0.0333) time: 2.9109 data: 0.0081 max mem: 33370 +Epoch: [32] [1760/2639] eta: 0:42:02 lr: 1.0860595344196656e-05 loss: 0.0280 (0.0333) time: 2.8895 data: 0.0077 max mem: 33370 +Epoch: [32] [1770/2639] eta: 0:41:33 lr: 1.0855544035005104e-05 loss: 0.0315 (0.0334) time: 2.8819 data: 0.0078 max mem: 33370 +Epoch: [32] [1780/2639] eta: 0:41:04 lr: 1.0850492464635736e-05 loss: 0.0324 (0.0334) time: 2.8744 data: 0.0077 max 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1.0729176033576159e-05 loss: 0.0299 (0.0336) time: 2.8456 data: 0.0077 max mem: 33370 +Epoch: [32] [2030/2639] eta: 0:29:07 lr: 1.0724117885035164e-05 loss: 0.0315 (0.0336) time: 2.8578 data: 0.0079 max mem: 33370 +Epoch: [32] [2040/2639] eta: 0:28:38 lr: 1.0719059471398985e-05 loss: 0.0313 (0.0336) time: 2.8908 data: 0.0082 max mem: 33370 +Epoch: [32] [2050/2639] eta: 0:28:10 lr: 1.0714000792514701e-05 loss: 0.0310 (0.0336) time: 2.8968 data: 0.0078 max mem: 33370 +Epoch: [32] [2060/2639] eta: 0:27:41 lr: 1.0708941848229246e-05 loss: 0.0309 (0.0336) time: 2.9360 data: 0.0072 max mem: 33370 +Epoch: [32] [2070/2639] eta: 0:27:12 lr: 1.0703882638389364e-05 loss: 0.0296 (0.0336) time: 2.9297 data: 0.0073 max mem: 33370 +Epoch: [32] [2080/2639] eta: 0:26:44 lr: 1.0698823162841648e-05 loss: 0.0287 (0.0336) time: 2.8816 data: 0.0075 max mem: 33370 +Epoch: [32] [2090/2639] eta: 0:26:15 lr: 1.0693763421432505e-05 loss: 0.0336 (0.0336) time: 2.8660 data: 0.0074 max mem: 33370 +Epoch: [32] [2100/2639] eta: 0:25:46 lr: 1.0688703414008193e-05 loss: 0.0320 (0.0336) time: 2.8679 data: 0.0079 max mem: 33370 +Epoch: [32] [2110/2639] eta: 0:25:18 lr: 1.0683643140414772e-05 loss: 0.0315 (0.0336) time: 2.8617 data: 0.0081 max mem: 33370 +Epoch: [32] [2120/2639] eta: 0:24:49 lr: 1.0678582600498167e-05 loss: 0.0316 (0.0336) time: 2.8535 data: 0.0078 max mem: 33370 +Epoch: [32] [2130/2639] eta: 0:24:20 lr: 1.0673521794104097e-05 loss: 0.0338 (0.0337) time: 2.8685 data: 0.0075 max mem: 33370 +Epoch: [32] [2140/2639] eta: 0:23:51 lr: 1.0668460721078142e-05 loss: 0.0361 (0.0337) time: 2.8599 data: 0.0075 max mem: 33370 +Epoch: [32] [2150/2639] eta: 0:23:23 lr: 1.066339938126568e-05 loss: 0.0318 (0.0337) time: 2.8376 data: 0.0076 max mem: 33370 +Epoch: [32] [2160/2639] eta: 0:22:54 lr: 1.0658337774511943e-05 loss: 0.0295 (0.0337) time: 2.8315 data: 0.0076 max mem: 33370 +Epoch: [32] [2170/2639] eta: 0:22:25 lr: 1.0653275900661988e-05 loss: 0.0310 (0.0337) time: 2.8588 data: 0.0076 max mem: 33370 +Epoch: [32] [2180/2639] eta: 0:21:57 lr: 1.0648213759560683e-05 loss: 0.0326 (0.0337) time: 2.9057 data: 0.0073 max mem: 33370 +Epoch: [32] [2190/2639] eta: 0:21:28 lr: 1.0643151351052745e-05 loss: 0.0362 (0.0337) time: 2.8743 data: 0.0072 max mem: 33370 +Epoch: [32] [2200/2639] eta: 0:20:59 lr: 1.06380886749827e-05 loss: 0.0367 (0.0337) time: 2.8137 data: 0.0078 max mem: 33370 +Epoch: [32] [2210/2639] eta: 0:20:30 lr: 1.063302573119492e-05 loss: 0.0328 (0.0337) time: 2.8168 data: 0.0083 max mem: 33370 +Epoch: [32] [2220/2639] eta: 0:20:02 lr: 1.0627962519533587e-05 loss: 0.0334 (0.0337) time: 2.8692 data: 0.0078 max mem: 33370 +Epoch: [32] [2230/2639] eta: 0:19:33 lr: 1.0622899039842724e-05 loss: 0.0376 (0.0338) time: 2.8959 data: 0.0074 max mem: 33370 +Epoch: [32] [2240/2639] eta: 0:19:04 lr: 1.0617835291966163e-05 loss: 0.0335 (0.0338) time: 2.8846 data: 0.0076 max mem: 33370 +Epoch: [32] [2250/2639] eta: 0:18:36 lr: 1.0612771275747588e-05 loss: 0.0303 (0.0338) time: 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0.0348 (0.0338) time: 2.8435 data: 0.0073 max mem: 33370 +Epoch: [32] [2340/2639] eta: 0:14:17 lr: 1.0567183028508396e-05 loss: 0.0349 (0.0338) time: 2.8441 data: 0.0072 max mem: 33370 +Epoch: [32] [2350/2639] eta: 0:13:49 lr: 1.0562116320232963e-05 loss: 0.0329 (0.0337) time: 2.8630 data: 0.0075 max mem: 33370 +Epoch: [32] [2360/2639] eta: 0:13:20 lr: 1.055704934188431e-05 loss: 0.0282 (0.0337) time: 2.9149 data: 0.0077 max mem: 33370 +Epoch: [32] [2370/2639] eta: 0:12:51 lr: 1.0551982093304012e-05 loss: 0.0282 (0.0337) time: 2.9425 data: 0.0076 max mem: 33370 +Epoch: [32] [2380/2639] eta: 0:12:23 lr: 1.0546914574333438e-05 loss: 0.0298 (0.0337) time: 2.8907 data: 0.0072 max mem: 33370 +Epoch: [32] [2390/2639] eta: 0:11:54 lr: 1.0541846784813809e-05 loss: 0.0303 (0.0337) time: 2.8813 data: 0.0072 max mem: 33370 +Epoch: [32] [2400/2639] eta: 0:11:25 lr: 1.0536778724586137e-05 loss: 0.0304 (0.0338) time: 2.9132 data: 0.0076 max mem: 33370 +Epoch: [32] [2410/2639] eta: 0:10:57 lr: 1.053171039349128e-05 loss: 0.0332 (0.0338) time: 2.8896 data: 0.0076 max mem: 33370 +Epoch: [32] [2420/2639] eta: 0:10:28 lr: 1.0526641791369912e-05 loss: 0.0277 (0.0337) time: 2.8585 data: 0.0077 max mem: 33370 +Epoch: [32] [2430/2639] eta: 0:09:59 lr: 1.0521572918062517e-05 loss: 0.0278 (0.0337) time: 2.8466 data: 0.0078 max mem: 33370 +Epoch: [32] [2440/2639] eta: 0:09:31 lr: 1.0516503773409416e-05 loss: 0.0313 (0.0337) time: 2.8366 data: 0.0076 max mem: 33370 +Epoch: [32] [2450/2639] eta: 0:09:02 lr: 1.051143435725073e-05 loss: 0.0313 (0.0338) time: 2.8338 data: 0.0076 max mem: 33370 +Epoch: [32] [2460/2639] eta: 0:08:33 lr: 1.0506364669426423e-05 loss: 0.0302 (0.0337) time: 2.8618 data: 0.0076 max mem: 33370 +Epoch: [32] [2470/2639] eta: 0:08:04 lr: 1.0501294709776258e-05 loss: 0.0304 (0.0337) time: 2.8643 data: 0.0076 max mem: 33370 +Epoch: [32] [2480/2639] eta: 0:07:36 lr: 1.0496224478139836e-05 loss: 0.0277 (0.0337) time: 2.8773 data: 0.0074 max mem: 33370 +Epoch: [32] [2490/2639] eta: 0:07:07 lr: 1.049115397435656e-05 loss: 0.0267 (0.0337) time: 2.8999 data: 0.0073 max mem: 33370 +Epoch: [32] [2500/2639] eta: 0:06:38 lr: 1.0486083198265669e-05 loss: 0.0295 (0.0337) time: 2.9290 data: 0.0075 max mem: 33370 +Epoch: [32] [2510/2639] eta: 0:06:10 lr: 1.0481012149706202e-05 loss: 0.0284 (0.0337) time: 2.9335 data: 0.0077 max mem: 33370 +Epoch: [32] [2520/2639] eta: 0:05:41 lr: 1.0475940828517034e-05 loss: 0.0292 (0.0337) time: 2.9015 data: 0.0082 max mem: 33370 +Epoch: [32] [2530/2639] eta: 0:05:12 lr: 1.0470869234536844e-05 loss: 0.0319 (0.0337) time: 2.9034 data: 0.0083 max mem: 33370 +Epoch: [32] [2540/2639] eta: 0:04:44 lr: 1.0465797367604141e-05 loss: 0.0319 (0.0337) time: 2.9118 data: 0.0079 max mem: 33370 +Epoch: [32] [2550/2639] eta: 0:04:15 lr: 1.0460725227557236e-05 loss: 0.0271 (0.0337) time: 2.9248 data: 0.0082 max mem: 33370 +Epoch: [32] [2560/2639] eta: 0:03:46 lr: 1.0455652814234277e-05 loss: 0.0289 (0.0337) time: 2.9108 data: 0.0085 max mem: 33370 +Epoch: [32] [2570/2639] eta: 0:03:18 lr: 1.0450580127473207e-05 loss: 0.0323 (0.0337) time: 2.9192 data: 0.0083 max mem: 33370 +Epoch: [32] [2580/2639] eta: 0:02:49 lr: 1.0445507167111807e-05 loss: 0.0331 (0.0337) time: 2.9422 data: 0.0079 max mem: 33370 +Epoch: [32] [2590/2639] eta: 0:02:20 lr: 1.0440433932987653e-05 loss: 0.0363 (0.0337) time: 2.9256 data: 0.0080 max mem: 33370 +Epoch: [32] [2600/2639] eta: 0:01:51 lr: 1.0435360424938158e-05 loss: 0.0320 (0.0337) time: 2.9090 data: 0.0083 max mem: 33370 +Epoch: [32] [2610/2639] eta: 0:01:23 lr: 1.0430286642800528e-05 loss: 0.0318 (0.0337) time: 2.9048 data: 0.0082 max mem: 33370 +Epoch: [32] [2620/2639] eta: 0:00:54 lr: 1.0425212586411808e-05 loss: 0.0309 (0.0337) time: 2.9088 data: 0.0082 max mem: 33370 +Epoch: [32] [2630/2639] eta: 0:00:25 lr: 1.0420138255608834e-05 loss: 0.0298 (0.0337) time: 2.9009 data: 0.0080 max mem: 33370 +Epoch: [32] Total time: 2:06:20 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 3:00:54 time: 4.2185 data: 4.1107 max mem: 33370 +Test: [ 100/2573] eta: 0:04:56 time: 0.0786 data: 0.0014 max mem: 33370 +Test: [ 200/2573] eta: 0:03:58 time: 0.0806 data: 0.0016 max mem: 33370 +Test: [ 300/2573] eta: 0:03:32 time: 0.0818 data: 0.0015 max mem: 33370 +Test: [ 400/2573] eta: 0:03:15 time: 0.0818 data: 0.0015 max mem: 33370 +Test: [ 500/2573] eta: 0:03:02 time: 0.0817 data: 0.0015 max mem: 33370 +Test: [ 600/2573] eta: 0:02:51 time: 0.0811 data: 0.0015 max mem: 33370 +Test: [ 700/2573] eta: 0:02:42 time: 0.0814 data: 0.0015 max mem: 33370 +Test: [ 800/2573] eta: 0:02:32 time: 0.0840 data: 0.0016 max mem: 33370 +Test: [ 900/2573] eta: 0:02:23 time: 0.0805 data: 0.0015 max mem: 33370 +Test: [1000/2573] eta: 0:02:14 time: 0.0811 data: 0.0015 max mem: 33370 +Test: [1100/2573] eta: 0:02:05 time: 0.0825 data: 0.0016 max mem: 33370 +Test: [1200/2573] eta: 0:01:56 time: 0.0812 data: 0.0015 max mem: 33370 +Test: [1300/2573] eta: 0:01:47 time: 0.0809 data: 0.0015 max mem: 33370 +Test: [1400/2573] eta: 0:01:38 time: 0.0796 data: 0.0014 max mem: 33370 +Test: [1500/2573] eta: 0:01:30 time: 0.0819 data: 0.0015 max mem: 33370 +Test: [1600/2573] eta: 0:01:21 time: 0.0846 data: 0.0016 max mem: 33370 +Test: [1700/2573] eta: 0:01:13 time: 0.0811 data: 0.0015 max mem: 33370 +Test: [1800/2573] eta: 0:01:04 time: 0.0841 data: 0.0015 max mem: 33370 +Test: [1900/2573] eta: 0:00:56 time: 0.0806 data: 0.0015 max mem: 33370 +Test: [2000/2573] eta: 0:00:47 time: 0.0829 data: 0.0016 max mem: 33370 +Test: [2100/2573] eta: 0:00:39 time: 0.0832 data: 0.0015 max mem: 33370 +Test: [2200/2573] eta: 0:00:31 time: 0.0835 data: 0.0016 max mem: 33370 +Test: [2300/2573] eta: 0:00:22 time: 0.0844 data: 0.0015 max mem: 33370 +Test: [2400/2573] eta: 0:00:14 time: 0.0790 data: 0.0016 max mem: 33370 +Test: [2500/2573] eta: 0:00:06 time: 0.0816 data: 0.0015 max mem: 33370 +Test: Total time: 0:03:35 +Final results: +Mean IoU is 64.62 + + precision@0.5 = 72.45 + precision@0.6 = 67.40 + precision@0.7 = 60.40 + precision@0.8 = 49.80 + precision@0.9 = 25.18 + overall IoU = 61.77 + +Average object IoU 64.61997441400763 +Overall IoU 61.77494430541992 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [33] [ 0/2639] eta: 4:22:37 lr: 1.0415571123126986e-05 loss: 0.0287 (0.0287) time: 5.9710 data: 2.8685 max mem: 33370 +Epoch: [33] [ 10/2639] eta: 2:20:06 lr: 1.0410496270486799e-05 loss: 0.0308 (0.0314) time: 3.1976 data: 0.2685 max mem: 33370 +Epoch: [33] [ 20/2639] eta: 2:13:40 lr: 1.0405421142958168e-05 loss: 0.0308 (0.0297) time: 2.9170 data: 0.0080 max mem: 33370 +Epoch: [33] [ 30/2639] eta: 2:11:57 lr: 1.0400345740377224e-05 loss: 0.0298 (0.0299) time: 2.9452 data: 0.0082 max mem: 33370 +Epoch: [33] [ 40/2639] eta: 2:10:49 lr: 1.0395270062579907e-05 loss: 0.0321 (0.0326) time: 2.9761 data: 0.0088 max mem: 33370 +Epoch: [33] [ 50/2639] eta: 2:09:57 lr: 1.0390194109401955e-05 loss: 0.0319 (0.0317) time: 2.9758 data: 0.0083 max mem: 33370 +Epoch: [33] [ 60/2639] eta: 2:08:34 lr: 1.0385117880678942e-05 loss: 0.0271 (0.0311) time: 2.9318 data: 0.0081 max mem: 33370 +Epoch: [33] [ 70/2639] eta: 2:07:24 lr: 1.0380041376246232e-05 loss: 0.0284 (0.0321) time: 2.8841 data: 0.0081 max mem: 33370 +Epoch: [33] [ 80/2639] eta: 2:06:52 lr: 1.0374964595939023e-05 loss: 0.0332 (0.0321) time: 2.9246 data: 0.0080 max mem: 33370 +Epoch: [33] [ 90/2639] eta: 2:06:03 lr: 1.0369887539592305e-05 loss: 0.0285 (0.0315) time: 2.9364 data: 0.0082 max mem: 33370 +Epoch: [33] [ 100/2639] eta: 2:05:04 lr: 1.0364810207040895e-05 loss: 0.0293 (0.0324) time: 2.8789 data: 0.0086 max mem: 33370 +Epoch: [33] [ 110/2639] eta: 2:04:22 lr: 1.0359732598119406e-05 loss: 0.0332 (0.0324) time: 2.8770 data: 0.0091 max mem: 33370 +Epoch: [33] [ 120/2639] eta: 2:03:43 lr: 1.0354654712662282e-05 loss: 0.0331 (0.0330) time: 2.9026 data: 0.0088 max mem: 33370 +Epoch: [33] [ 130/2639] eta: 2:03:06 lr: 1.0349576550503752e-05 loss: 0.0342 (0.0330) time: 2.9069 data: 0.0084 max mem: 33370 +Epoch: [33] [ 140/2639] eta: 2:02:41 lr: 1.0344498111477883e-05 loss: 0.0343 (0.0331) time: 2.9390 data: 0.0084 max mem: 33370 +Epoch: [33] [ 150/2639] eta: 2:02:01 lr: 1.0339419395418524e-05 loss: 0.0270 (0.0328) time: 2.9253 data: 0.0088 max mem: 33370 +Epoch: [33] [ 160/2639] eta: 2:01:28 lr: 1.0334340402159363e-05 loss: 0.0274 (0.0328) time: 2.8978 data: 0.0087 max mem: 33370 +Epoch: [33] [ 170/2639] eta: 2:01:04 lr: 1.0329261131533865e-05 loss: 0.0298 (0.0326) time: 2.9479 data: 0.0084 max mem: 33370 +Epoch: [33] [ 180/2639] eta: 2:00:36 lr: 1.0324181583375338e-05 loss: 0.0304 (0.0326) time: 2.9673 data: 0.0083 max mem: 33370 +Epoch: [33] [ 190/2639] eta: 2:00:08 lr: 1.0319101757516866e-05 loss: 0.0306 (0.0327) time: 2.9515 data: 0.0080 max mem: 33370 +Epoch: [33] [ 200/2639] eta: 1:59:37 lr: 1.0314021653791366e-05 loss: 0.0302 (0.0331) time: 2.9425 data: 0.0081 max mem: 33370 +Epoch: [33] [ 210/2639] eta: 1:59:11 lr: 1.0308941272031549e-05 loss: 0.0277 (0.0328) time: 2.9540 data: 0.0084 max mem: 33370 +Epoch: [33] [ 220/2639] eta: 1:58:40 lr: 1.0303860612069943e-05 loss: 0.0281 (0.0326) time: 2.9492 data: 0.0083 max mem: 33370 +Epoch: [33] [ 230/2639] eta: 1:58:12 lr: 1.0298779673738871e-05 loss: 0.0285 (0.0325) time: 2.9418 data: 0.0082 max mem: 33370 +Epoch: [33] [ 240/2639] eta: 1:57:45 lr: 1.029369845687048e-05 loss: 0.0320 (0.0325) time: 2.9645 data: 0.0083 max mem: 33370 +Epoch: [33] [ 250/2639] eta: 1:57:14 lr: 1.0288616961296705e-05 loss: 0.0329 (0.0326) time: 2.9471 data: 0.0083 max mem: 33370 +Epoch: [33] [ 260/2639] eta: 1:56:40 lr: 1.0283535186849305e-05 loss: 0.0309 (0.0326) time: 2.9131 data: 0.0090 max mem: 33370 +Epoch: [33] [ 270/2639] eta: 1:56:08 lr: 1.0278453133359826e-05 loss: 0.0286 (0.0325) time: 2.9063 data: 0.0092 max mem: 33370 +Epoch: [33] [ 280/2639] eta: 1:55:40 lr: 1.0273370800659637e-05 loss: 0.0316 (0.0326) time: 2.9339 data: 0.0085 max mem: 33370 +Epoch: [33] [ 290/2639] eta: 1:55:14 lr: 1.0268288188579909e-05 loss: 0.0320 (0.0326) time: 2.9726 data: 0.0084 max mem: 33370 +Epoch: [33] [ 300/2639] eta: 1:54:43 lr: 1.0263205296951603e-05 loss: 0.0303 (0.0327) time: 2.9528 data: 0.0084 max mem: 33370 +Epoch: [33] [ 310/2639] eta: 1:54:17 lr: 1.025812212560551e-05 loss: 0.0303 (0.0327) time: 2.9532 data: 0.0085 max mem: 33370 +Epoch: [33] [ 320/2639] eta: 1:53:50 lr: 1.02530386743722e-05 loss: 0.0285 (0.0326) time: 2.9859 data: 0.0087 max mem: 33370 +Epoch: [33] [ 330/2639] eta: 1:53:23 lr: 1.0247954943082065e-05 loss: 0.0284 (0.0326) time: 2.9791 data: 0.0087 max mem: 33370 +Epoch: [33] [ 340/2639] eta: 1:52:56 lr: 1.0242870931565288e-05 loss: 0.0321 (0.0327) time: 2.9824 data: 0.0086 max mem: 33370 +Epoch: [33] [ 350/2639] eta: 1:52:26 lr: 1.023778663965187e-05 loss: 0.0341 (0.0327) time: 2.9636 data: 0.0085 max mem: 33370 +Epoch: [33] [ 360/2639] eta: 1:51:58 lr: 1.0232702067171596e-05 loss: 0.0350 (0.0328) time: 2.9511 data: 0.0082 max mem: 33370 +Epoch: [33] [ 370/2639] eta: 1:51:26 lr: 1.0227617213954077e-05 loss: 0.0311 (0.0328) time: 2.9384 data: 0.0081 max mem: 33370 +Epoch: [33] [ 380/2639] eta: 1:50:57 lr: 1.0222532079828698e-05 loss: 0.0321 (0.0329) time: 2.9359 data: 0.0080 max mem: 33370 +Epoch: [33] [ 390/2639] eta: 1:50:27 lr: 1.0217446664624675e-05 loss: 0.0321 (0.0329) time: 2.9472 data: 0.0080 max mem: 33370 +Epoch: [33] [ 400/2639] eta: 1:49:56 lr: 1.0212360968171e-05 loss: 0.0289 (0.0328) time: 2.9301 data: 0.0081 max mem: 33370 +Epoch: [33] [ 410/2639] eta: 1:49:24 lr: 1.020727499029649e-05 loss: 0.0293 (0.0328) time: 2.9130 data: 0.0083 max mem: 33370 +Epoch: [33] [ 420/2639] eta: 1:48:56 lr: 1.020218873082974e-05 loss: 0.0312 (0.0328) time: 2.9325 data: 0.0085 max mem: 33370 +Epoch: [33] [ 430/2639] eta: 1:48:26 lr: 1.0197102189599169e-05 loss: 0.0314 (0.0328) time: 2.9458 data: 0.0089 max mem: 33370 +Epoch: [33] [ 440/2639] eta: 1:47:54 lr: 1.019201536643297e-05 loss: 0.0301 (0.0328) time: 2.9150 data: 0.0089 max mem: 33370 +Epoch: [33] [ 450/2639] eta: 1:47:24 lr: 1.0186928261159162e-05 loss: 0.0252 (0.0328) time: 2.9196 data: 0.0085 max mem: 33370 +Epoch: [33] [ 460/2639] eta: 1:46:55 lr: 1.0181840873605542e-05 loss: 0.0267 (0.0328) time: 2.9446 data: 0.0089 max mem: 33370 +Epoch: [33] [ 470/2639] eta: 1:46:22 lr: 1.0176753203599726e-05 loss: 0.0267 (0.0327) time: 2.9094 data: 0.0088 max mem: 33370 +Epoch: [33] [ 480/2639] eta: 1:45:54 lr: 1.0171665250969109e-05 loss: 0.0272 (0.0327) time: 2.9138 data: 0.0085 max mem: 33370 +Epoch: [33] [ 490/2639] eta: 1:45:26 lr: 1.0166577015540902e-05 loss: 0.0345 (0.0328) time: 2.9762 data: 0.0088 max mem: 33370 +Epoch: [33] [ 500/2639] eta: 1:44:58 lr: 1.0161488497142098e-05 loss: 0.0301 (0.0329) time: 2.9849 data: 0.0085 max mem: 33370 +Epoch: [33] [ 510/2639] eta: 1:44:27 lr: 1.0156399695599506e-05 loss: 0.0293 (0.0329) time: 2.9407 data: 0.0081 max mem: 33370 +Epoch: [33] [ 520/2639] eta: 1:43:57 lr: 1.0151310610739715e-05 loss: 0.0300 (0.0328) time: 2.9142 data: 0.0083 max mem: 33370 +Epoch: [33] [ 530/2639] eta: 1:43:25 lr: 1.014622124238912e-05 loss: 0.0278 (0.0327) time: 2.9025 data: 0.0086 max mem: 33370 +Epoch: [33] [ 540/2639] eta: 1:42:55 lr: 1.0141131590373919e-05 loss: 0.0291 (0.0327) time: 2.9063 data: 0.0089 max mem: 33370 +Epoch: [33] [ 550/2639] eta: 1:42:24 lr: 1.0136041654520088e-05 loss: 0.0291 (0.0328) time: 2.9186 data: 0.0091 max mem: 33370 +Epoch: [33] [ 560/2639] eta: 1:41:55 lr: 1.0130951434653423e-05 loss: 0.0280 (0.0327) time: 2.9261 data: 0.0086 max mem: 33370 +Epoch: [33] [ 570/2639] eta: 1:41:26 lr: 1.0125860930599488e-05 loss: 0.0314 (0.0327) time: 2.9497 data: 0.0085 max mem: 33370 +Epoch: [33] [ 580/2639] eta: 1:40:57 lr: 1.0120770142183673e-05 loss: 0.0323 (0.0327) time: 2.9500 data: 0.0086 max mem: 33370 +Epoch: [33] [ 590/2639] eta: 1:40:26 lr: 1.0115679069231135e-05 loss: 0.0294 (0.0326) time: 2.9316 data: 0.0084 max mem: 33370 +Epoch: [33] [ 600/2639] eta: 1:39:56 lr: 1.0110587711566847e-05 loss: 0.0326 (0.0327) time: 2.9111 data: 0.0085 max mem: 33370 +Epoch: [33] [ 610/2639] eta: 1:39:28 lr: 1.0105496069015558e-05 loss: 0.0317 (0.0327) time: 2.9425 data: 0.0084 max mem: 33370 +Epoch: [33] [ 620/2639] eta: 1:38:57 lr: 1.0100404141401832e-05 loss: 0.0259 (0.0326) time: 2.9344 data: 0.0084 max mem: 33370 +Epoch: [33] [ 630/2639] eta: 1:38:27 lr: 1.009531192855e-05 loss: 0.0255 (0.0326) time: 2.9062 data: 0.0084 max mem: 33370 +Epoch: [33] [ 640/2639] eta: 1:37:56 lr: 1.009021943028422e-05 loss: 0.0272 (0.0325) time: 2.9142 data: 0.0085 max mem: 33370 +Epoch: [33] [ 650/2639] eta: 1:37:26 lr: 1.0085126646428407e-05 loss: 0.0285 (0.0325) time: 2.9089 data: 0.0083 max mem: 33370 +Epoch: [33] [ 660/2639] eta: 1:36:54 lr: 1.0080033576806298e-05 loss: 0.0319 (0.0326) time: 2.8743 data: 0.0084 max mem: 33370 +Epoch: [33] [ 670/2639] eta: 1:36:24 lr: 1.0074940221241401e-05 loss: 0.0285 (0.0326) time: 2.8938 data: 0.0086 max mem: 33370 +Epoch: [33] [ 680/2639] eta: 1:35:55 lr: 1.0069846579557033e-05 loss: 0.0283 (0.0325) time: 2.9382 data: 0.0084 max mem: 33370 +Epoch: [33] [ 690/2639] eta: 1:35:23 lr: 1.0064752651576282e-05 loss: 0.0305 (0.0325) time: 2.8958 data: 0.0085 max mem: 33370 +Epoch: [33] [ 700/2639] eta: 1:34:53 lr: 1.0059658437122055e-05 loss: 0.0305 (0.0325) time: 2.8849 data: 0.0082 max mem: 33370 +Epoch: [33] [ 710/2639] eta: 1:34:23 lr: 1.0054563936017018e-05 loss: 0.0304 (0.0325) time: 2.9109 data: 0.0081 max mem: 33370 +Epoch: [33] [ 720/2639] eta: 1:33:54 lr: 1.0049469148083658e-05 loss: 0.0337 (0.0326) time: 2.9304 data: 0.0083 max mem: 33370 +Epoch: [33] [ 730/2639] eta: 1:33:24 lr: 1.0044374073144223e-05 loss: 0.0314 (0.0325) time: 2.9307 data: 0.0086 max mem: 33370 +Epoch: [33] [ 740/2639] eta: 1:32:52 lr: 1.003927871102078e-05 loss: 0.0280 (0.0325) time: 2.8611 data: 0.0086 max mem: 33370 +Epoch: [33] [ 750/2639] eta: 1:32:23 lr: 1.0034183061535153e-05 loss: 0.0316 (0.0327) time: 2.8900 data: 0.0080 max mem: 33370 +Epoch: [33] [ 760/2639] eta: 1:31:53 lr: 1.002908712450899e-05 loss: 0.0335 (0.0327) time: 2.9461 data: 0.0079 max mem: 33370 +Epoch: [33] [ 770/2639] eta: 1:31:22 lr: 1.0023990899763691e-05 loss: 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9.98321072241292e-06 loss: 0.0296 (0.0328) time: 2.9170 data: 0.0086 max mem: 33370 +Epoch: [33] [ 860/2639] eta: 1:26:57 lr: 9.978111900124236e-06 loss: 0.0323 (0.0329) time: 2.8901 data: 0.0079 max mem: 33370 +Epoch: [33] [ 870/2639] eta: 1:26:27 lr: 9.973012788318904e-06 loss: 0.0334 (0.0329) time: 2.8885 data: 0.0082 max mem: 33370 +Epoch: [33] [ 880/2639] eta: 1:25:57 lr: 9.967913386815978e-06 loss: 0.0299 (0.0329) time: 2.9067 data: 0.0090 max mem: 33370 +Epoch: [33] [ 890/2639] eta: 1:25:28 lr: 9.962813695434322e-06 loss: 0.0299 (0.0329) time: 2.9236 data: 0.0087 max mem: 33370 +Epoch: [33] [ 900/2639] eta: 1:24:59 lr: 9.957713713992559e-06 loss: 0.0272 (0.0328) time: 2.9298 data: 0.0085 max mem: 33370 +Epoch: [33] [ 910/2639] eta: 1:24:29 lr: 9.952613442309118e-06 loss: 0.0264 (0.0328) time: 2.9112 data: 0.0085 max mem: 33370 +Epoch: [33] [ 920/2639] eta: 1:23:58 lr: 9.94751288020219e-06 loss: 0.0284 (0.0329) time: 2.8925 data: 0.0079 max mem: 33370 +Epoch: [33] [ 930/2639] eta: 1:23:29 lr: 9.94241202748977e-06 loss: 0.0321 (0.0329) time: 2.9076 data: 0.0084 max mem: 33370 +Epoch: [33] [ 940/2639] eta: 1:23:00 lr: 9.937310883989613e-06 loss: 0.0289 (0.0328) time: 2.9242 data: 0.0084 max mem: 33370 +Epoch: [33] [ 950/2639] eta: 1:22:29 lr: 9.932209449519276e-06 loss: 0.0296 (0.0328) time: 2.9035 data: 0.0081 max mem: 33370 +Epoch: [33] [ 960/2639] eta: 1:22:00 lr: 9.927107723896079e-06 loss: 0.0310 (0.0328) time: 2.9035 data: 0.0083 max mem: 33370 +Epoch: [33] [ 970/2639] eta: 1:21:31 lr: 9.922005706937141e-06 loss: 0.0298 (0.0328) time: 2.9371 data: 0.0083 max mem: 33370 +Epoch: [33] [ 980/2639] eta: 1:21:02 lr: 9.916903398459341e-06 loss: 0.0331 (0.0330) time: 2.9395 data: 0.0088 max mem: 33370 +Epoch: [33] [ 990/2639] eta: 1:20:32 lr: 9.911800798279364e-06 loss: 0.0333 (0.0330) time: 2.9271 data: 0.0088 max mem: 33370 +Epoch: [33] [1000/2639] eta: 1:20:03 lr: 9.906697906213645e-06 loss: 0.0294 (0.0330) time: 2.9185 data: 0.0082 max mem: 33370 +Epoch: 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0.0082 max mem: 33370 +Epoch: [33] [1170/2639] eta: 1:11:43 lr: 9.819903903644385e-06 loss: 0.0266 (0.0329) time: 2.9158 data: 0.0080 max mem: 33370 +Epoch: [33] [1180/2639] eta: 1:11:14 lr: 9.814795725995028e-06 loss: 0.0314 (0.0329) time: 2.9143 data: 0.0080 max mem: 33370 +Epoch: [33] [1190/2639] eta: 1:10:45 lr: 9.809687252930118e-06 loss: 0.0294 (0.0329) time: 2.9753 data: 0.0083 max mem: 33370 +Epoch: [33] [1200/2639] eta: 1:10:16 lr: 9.804578484261629e-06 loss: 0.0264 (0.0329) time: 2.9592 data: 0.0084 max mem: 33370 +Epoch: [33] [1210/2639] eta: 1:09:47 lr: 9.79946941980128e-06 loss: 0.0298 (0.0329) time: 2.9312 data: 0.0088 max mem: 33370 +Epoch: [33] [1220/2639] eta: 1:09:17 lr: 9.794360059360592e-06 loss: 0.0321 (0.0329) time: 2.9073 data: 0.0095 max mem: 33370 +Epoch: [33] [1230/2639] eta: 1:08:48 lr: 9.789250402750827e-06 loss: 0.0312 (0.0329) time: 2.9206 data: 0.0092 max mem: 33370 +Epoch: [33] [1240/2639] eta: 1:08:18 lr: 9.784140449783041e-06 loss: 0.0297 (0.0329) time: 2.9127 data: 0.0084 max mem: 33370 +Epoch: [33] [1250/2639] eta: 1:07:49 lr: 9.779030200268038e-06 loss: 0.0313 (0.0329) time: 2.9191 data: 0.0081 max mem: 33370 +Epoch: [33] [1260/2639] eta: 1:07:19 lr: 9.773919654016407e-06 loss: 0.0323 (0.0330) time: 2.9274 data: 0.0082 max mem: 33370 +Epoch: [33] [1270/2639] eta: 1:06:50 lr: 9.76880881083851e-06 loss: 0.0290 (0.0329) time: 2.9189 data: 0.0085 max mem: 33370 +Epoch: [33] [1280/2639] eta: 1:06:20 lr: 9.763697670544455e-06 loss: 0.0282 (0.0329) time: 2.9099 data: 0.0084 max mem: 33370 +Epoch: [33] [1290/2639] eta: 1:05:52 lr: 9.758586232944145e-06 loss: 0.0291 (0.0329) time: 2.9336 data: 0.0083 max mem: 33370 +Epoch: [33] [1300/2639] eta: 1:05:22 lr: 9.753474497847226e-06 loss: 0.0280 (0.0329) time: 2.9624 data: 0.0082 max mem: 33370 +Epoch: [33] [1310/2639] eta: 1:04:53 lr: 9.748362465063132e-06 loss: 0.0299 (0.0329) time: 2.9412 data: 0.0083 max mem: 33370 +Epoch: [33] [1320/2639] eta: 1:04:25 lr: 9.743250134401044e-06 loss: 0.0298 (0.0329) time: 2.9835 data: 0.0086 max mem: 33370 +Epoch: [33] [1330/2639] eta: 1:03:56 lr: 9.738137505669934e-06 loss: 0.0282 (0.0329) time: 2.9842 data: 0.0084 max mem: 33370 +Epoch: [33] [1340/2639] eta: 1:03:26 lr: 9.73302457867851e-06 loss: 0.0261 (0.0328) time: 2.9396 data: 0.0082 max mem: 33370 +Epoch: [33] [1350/2639] eta: 1:02:57 lr: 9.727911353235277e-06 loss: 0.0263 (0.0328) time: 2.9475 data: 0.0080 max mem: 33370 +Epoch: [33] [1360/2639] eta: 1:02:28 lr: 9.722797829148476e-06 loss: 0.0317 (0.0329) time: 2.9644 data: 0.0081 max mem: 33370 +Epoch: [33] [1370/2639] eta: 1:01:59 lr: 9.717684006226137e-06 loss: 0.0307 (0.0328) time: 2.9258 data: 0.0084 max mem: 33370 +Epoch: [33] [1380/2639] eta: 1:01:29 lr: 9.712569884276033e-06 loss: 0.0277 (0.0329) time: 2.9128 data: 0.0083 max mem: 33370 +Epoch: [33] [1390/2639] eta: 1:01:00 lr: 9.707455463105725e-06 loss: 0.0296 (0.0329) time: 2.9373 data: 0.0085 max mem: 33370 +Epoch: [33] [1400/2639] eta: 1:00:31 lr: 9.702340742522507e-06 loss: 0.0312 (0.0328) time: 2.9350 data: 0.0085 max mem: 33370 +Epoch: [33] [1410/2639] eta: 1:00:02 lr: 9.697225722333468e-06 loss: 0.0314 (0.0328) time: 2.9361 data: 0.0083 max mem: 33370 +Epoch: [33] [1420/2639] eta: 0:59:32 lr: 9.692110402345431e-06 loss: 0.0314 (0.0329) time: 2.9253 data: 0.0082 max mem: 33370 +Epoch: [33] [1430/2639] eta: 0:59:03 lr: 9.686994782365008e-06 loss: 0.0300 (0.0329) time: 2.9131 data: 0.0081 max mem: 33370 +Epoch: [33] [1440/2639] eta: 0:58:33 lr: 9.681878862198545e-06 loss: 0.0300 (0.0329) time: 2.9138 data: 0.0084 max mem: 33370 +Epoch: [33] [1450/2639] eta: 0:58:04 lr: 9.676762641652175e-06 loss: 0.0315 (0.0329) time: 2.9449 data: 0.0087 max mem: 33370 +Epoch: [33] [1460/2639] eta: 0:57:35 lr: 9.67164612053177e-06 loss: 0.0321 (0.0329) time: 2.9213 data: 0.0086 max mem: 33370 +Epoch: [33] [1470/2639] eta: 0:57:05 lr: 9.666529298642983e-06 loss: 0.0308 (0.0329) time: 2.8781 data: 0.0083 max mem: 33370 +Epoch: [33] [1480/2639] eta: 0:56:35 lr: 9.661412175791203e-06 loss: 0.0279 (0.0329) time: 2.9013 data: 0.0081 max mem: 33370 +Epoch: [33] [1490/2639] eta: 0:56:06 lr: 9.656294751781608e-06 loss: 0.0276 (0.0328) time: 2.9094 data: 0.0083 max mem: 33370 +Epoch: [33] [1500/2639] eta: 0:55:37 lr: 9.651177026419104e-06 loss: 0.0276 (0.0328) time: 2.9146 data: 0.0081 max mem: 33370 +Epoch: [33] [1510/2639] eta: 0:55:07 lr: 9.646058999508374e-06 loss: 0.0312 (0.0328) time: 2.9160 data: 0.0081 max mem: 33370 +Epoch: [33] [1520/2639] eta: 0:54:38 lr: 9.640940670853866e-06 loss: 0.0309 (0.0328) time: 2.9257 data: 0.0081 max mem: 33370 +Epoch: [33] [1530/2639] eta: 0:54:09 lr: 9.635822040259763e-06 loss: 0.0301 (0.0328) time: 2.9466 data: 0.0079 max mem: 33370 +Epoch: [33] [1540/2639] eta: 0:53:40 lr: 9.630703107530025e-06 loss: 0.0310 (0.0328) time: 2.9725 data: 0.0078 max mem: 33370 +Epoch: [33] [1550/2639] eta: 0:53:11 lr: 9.625583872468356e-06 loss: 0.0302 (0.0328) time: 2.9766 data: 0.0080 max mem: 33370 +Epoch: [33] [1560/2639] eta: 0:52:41 lr: 9.620464334878228e-06 loss: 0.0287 (0.0328) time: 2.9081 data: 0.0079 max mem: 33370 +Epoch: [33] [1570/2639] eta: 0:52:12 lr: 9.615344494562858e-06 loss: 0.0292 (0.0328) time: 2.8946 data: 0.0081 max mem: 33370 +Epoch: [33] [1580/2639] eta: 0:51:43 lr: 9.610224351325227e-06 loss: 0.0292 (0.0328) time: 2.9443 data: 0.0084 max mem: 33370 +Epoch: [33] [1590/2639] eta: 0:51:13 lr: 9.605103904968062e-06 loss: 0.0316 (0.0328) time: 2.9423 data: 0.0085 max mem: 33370 +Epoch: [33] [1600/2639] eta: 0:50:44 lr: 9.599983155293858e-06 loss: 0.0303 (0.0328) time: 2.9192 data: 0.0084 max mem: 33370 +Epoch: [33] [1610/2639] eta: 0:50:15 lr: 9.594862102104846e-06 loss: 0.0298 (0.0327) time: 2.9412 data: 0.0079 max mem: 33370 +Epoch: [33] [1620/2639] eta: 0:49:46 lr: 9.589740745203033e-06 loss: 0.0291 (0.0327) time: 2.9545 data: 0.0079 max mem: 33370 +Epoch: [33] [1630/2639] eta: 0:49:17 lr: 9.584619084390153e-06 loss: 0.0302 (0.0327) time: 2.9765 data: 0.0085 max mem: 33370 +Epoch: [33] [1640/2639] eta: 0:48:47 lr: 9.579497119467723e-06 loss: 0.0297 (0.0327) time: 2.9605 data: 0.0086 max mem: 33370 +Epoch: [33] [1650/2639] eta: 0:48:18 lr: 9.574374850236981e-06 loss: 0.0297 (0.0328) time: 2.9286 data: 0.0081 max mem: 33370 +Epoch: [33] [1660/2639] eta: 0:47:49 lr: 9.569252276498944e-06 loss: 0.0301 (0.0328) time: 2.9290 data: 0.0080 max mem: 33370 +Epoch: [33] [1670/2639] eta: 0:47:19 lr: 9.564129398054358e-06 loss: 0.0300 (0.0328) time: 2.9192 data: 0.0085 max mem: 33370 +Epoch: [33] [1680/2639] eta: 0:46:50 lr: 9.559006214703744e-06 loss: 0.0321 (0.0328) time: 2.9571 data: 0.0085 max mem: 33370 +Epoch: [33] [1690/2639] eta: 0:46:21 lr: 9.553882726247344e-06 loss: 0.0311 (0.0328) time: 2.9511 data: 0.0082 max mem: 33370 +Epoch: [33] [1700/2639] eta: 0:45:52 lr: 9.548758932485181e-06 loss: 0.0309 (0.0328) time: 2.9164 data: 0.0083 max mem: 33370 +Epoch: [33] [1710/2639] eta: 0:45:23 lr: 9.543634833217e-06 loss: 0.0325 (0.0328) time: 2.9483 data: 0.0083 max mem: 33370 +Epoch: [33] [1720/2639] eta: 0:44:54 lr: 9.538510428242322e-06 loss: 0.0348 (0.0328) time: 2.9912 data: 0.0081 max mem: 33370 +Epoch: [33] [1730/2639] eta: 0:44:24 lr: 9.533385717360387e-06 loss: 0.0313 (0.0328) time: 2.9753 data: 0.0082 max mem: 33370 +Epoch: [33] [1740/2639] eta: 0:43:55 lr: 9.528260700370211e-06 loss: 0.0281 (0.0328) time: 2.9573 data: 0.0082 max mem: 33370 +Epoch: [33] [1750/2639] eta: 0:43:26 lr: 9.523135377070534e-06 loss: 0.0298 (0.0329) time: 2.9492 data: 0.0079 max mem: 33370 +Epoch: [33] [1760/2639] eta: 0:42:57 lr: 9.518009747259863e-06 loss: 0.0303 (0.0328) time: 2.9588 data: 0.0077 max mem: 33370 +Epoch: [33] [1770/2639] eta: 0:42:28 lr: 9.512883810736446e-06 loss: 0.0310 (0.0329) time: 2.9785 data: 0.0081 max mem: 33370 +Epoch: [33] [1780/2639] eta: 0:41:59 lr: 9.507757567298265e-06 loss: 0.0360 (0.0329) time: 2.9678 data: 0.0081 max mem: 33370 +Epoch: [33] [1790/2639] eta: 0:41:30 lr: 9.502631016743069e-06 loss: 0.0360 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9.461607531732978e-06 loss: 0.0247 (0.0330) time: 2.9196 data: 0.0082 max mem: 33370 +Epoch: [33] [1880/2639] eta: 0:37:06 lr: 9.456478207980609e-06 loss: 0.0329 (0.0330) time: 2.9205 data: 0.0081 max mem: 33370 +Epoch: [33] [1890/2639] eta: 0:36:37 lr: 9.451348575074515e-06 loss: 0.0333 (0.0330) time: 2.8866 data: 0.0084 max mem: 33370 +Epoch: [33] [1900/2639] eta: 0:36:07 lr: 9.446218632809601e-06 loss: 0.0332 (0.0330) time: 2.9173 data: 0.0086 max mem: 33370 +Epoch: [33] [1910/2639] eta: 0:35:38 lr: 9.441088380980524e-06 loss: 0.0332 (0.0330) time: 2.9462 data: 0.0085 max mem: 33370 +Epoch: [33] [1920/2639] eta: 0:35:09 lr: 9.435957819381665e-06 loss: 0.0318 (0.0330) time: 2.9483 data: 0.0083 max mem: 33370 +Epoch: [33] [1930/2639] eta: 0:34:40 lr: 9.430826947807165e-06 loss: 0.0301 (0.0330) time: 2.9723 data: 0.0081 max mem: 33370 +Epoch: [33] [1940/2639] eta: 0:34:10 lr: 9.42569576605088e-06 loss: 0.0324 (0.0330) time: 2.9487 data: 0.0081 max mem: 33370 +Epoch: [33] [1950/2639] eta: 0:33:41 lr: 9.420564273906427e-06 loss: 0.0334 (0.0330) time: 2.9130 data: 0.0085 max mem: 33370 +Epoch: [33] [1960/2639] eta: 0:33:11 lr: 9.41543247116714e-06 loss: 0.0357 (0.0330) time: 2.9116 data: 0.0087 max mem: 33370 +Epoch: [33] [1970/2639] eta: 0:32:42 lr: 9.41030035762611e-06 loss: 0.0282 (0.0330) time: 2.9509 data: 0.0081 max mem: 33370 +Epoch: [33] [1980/2639] eta: 0:32:13 lr: 9.405167933076142e-06 loss: 0.0284 (0.0330) time: 2.9492 data: 0.0085 max mem: 33370 +Epoch: [33] [1990/2639] eta: 0:31:43 lr: 9.400035197309805e-06 loss: 0.0322 (0.0330) time: 2.9251 data: 0.0090 max mem: 33370 +Epoch: [33] [2000/2639] eta: 0:31:14 lr: 9.394902150119374e-06 loss: 0.0335 (0.0330) time: 2.9189 data: 0.0084 max mem: 33370 +Epoch: [33] [2010/2639] eta: 0:30:45 lr: 9.38976879129688e-06 loss: 0.0313 (0.0330) time: 2.9028 data: 0.0081 max mem: 33370 +Epoch: [33] [2020/2639] eta: 0:30:15 lr: 9.384635120634089e-06 loss: 0.0288 (0.0330) time: 2.9251 data: 0.0085 max mem: 33370 +Epoch: [33] [2030/2639] eta: 0:29:46 lr: 9.379501137922481e-06 loss: 0.0299 (0.0330) time: 2.9560 data: 0.0084 max mem: 33370 +Epoch: [33] [2040/2639] eta: 0:29:17 lr: 9.3743668429533e-06 loss: 0.0351 (0.0330) time: 2.9915 data: 0.0087 max mem: 33370 +Epoch: [33] [2050/2639] eta: 0:28:48 lr: 9.369232235517488e-06 loss: 0.0339 (0.0330) time: 2.9747 data: 0.0087 max mem: 33370 +Epoch: [33] [2060/2639] eta: 0:28:18 lr: 9.364097315405755e-06 loss: 0.0265 (0.0330) time: 2.9177 data: 0.0083 max mem: 33370 +Epoch: [33] [2070/2639] eta: 0:27:49 lr: 9.358962082408509e-06 loss: 0.0268 (0.0330) time: 2.9137 data: 0.0085 max mem: 33370 +Epoch: [33] [2080/2639] eta: 0:27:19 lr: 9.353826536315925e-06 loss: 0.0290 (0.0330) time: 2.9240 data: 0.0086 max mem: 33370 +Epoch: [33] [2090/2639] eta: 0:26:50 lr: 9.348690676917876e-06 loss: 0.0260 (0.0330) time: 2.9237 data: 0.0087 max mem: 33370 +Epoch: [33] [2100/2639] eta: 0:26:21 lr: 9.343554504003993e-06 loss: 0.0272 (0.0330) time: 2.9007 data: 0.0087 max mem: 33370 +Epoch: [33] [2110/2639] eta: 0:25:51 lr: 9.338418017363612e-06 loss: 0.0326 (0.0330) time: 2.8546 data: 0.0084 max mem: 33370 +Epoch: [33] [2120/2639] eta: 0:25:22 lr: 9.333281216785827e-06 loss: 0.0301 (0.0330) time: 2.8732 data: 0.0080 max mem: 33370 +Epoch: [33] [2130/2639] eta: 0:24:52 lr: 9.328144102059428e-06 loss: 0.0283 (0.0329) time: 2.8839 data: 0.0081 max mem: 33370 +Epoch: [33] [2140/2639] eta: 0:24:23 lr: 9.323006672972969e-06 loss: 0.0291 (0.0329) time: 2.8892 data: 0.0084 max mem: 33370 +Epoch: [33] [2150/2639] eta: 0:23:53 lr: 9.317868929314699e-06 loss: 0.0307 (0.0329) time: 2.9163 data: 0.0081 max mem: 33370 +Epoch: [33] [2160/2639] eta: 0:23:24 lr: 9.312730870872622e-06 loss: 0.0318 (0.0329) time: 2.9356 data: 0.0080 max mem: 33370 +Epoch: [33] [2170/2639] eta: 0:22:55 lr: 9.307592497434446e-06 loss: 0.0309 (0.0329) time: 2.9608 data: 0.0085 max mem: 33370 +Epoch: [33] [2180/2639] eta: 0:22:26 lr: 9.302453808787627e-06 loss: 0.0312 (0.0329) time: 2.9541 data: 0.0083 max mem: 33370 +Epoch: [33] [2190/2639] eta: 0:21:56 lr: 9.297314804719326e-06 loss: 0.0307 (0.0329) time: 2.9461 data: 0.0077 max mem: 33370 +Epoch: [33] [2200/2639] eta: 0:21:27 lr: 9.292175485016452e-06 loss: 0.0291 (0.0329) time: 2.9743 data: 0.0081 max mem: 33370 +Epoch: [33] [2210/2639] eta: 0:20:58 lr: 9.287035849465614e-06 loss: 0.0319 (0.0329) time: 2.9113 data: 0.0084 max mem: 33370 +Epoch: [33] [2220/2639] eta: 0:20:28 lr: 9.28189589785317e-06 loss: 0.0326 (0.0329) time: 2.8628 data: 0.0082 max mem: 33370 +Epoch: [33] [2230/2639] eta: 0:19:59 lr: 9.27675562996518e-06 loss: 0.0305 (0.0329) time: 2.8934 data: 0.0081 max mem: 33370 +Epoch: [33] [2240/2639] eta: 0:19:29 lr: 9.271615045587451e-06 loss: 0.0315 (0.0329) time: 2.8854 data: 0.0085 max mem: 33370 +Epoch: [33] [2250/2639] eta: 0:19:00 lr: 9.266474144505483e-06 loss: 0.0324 (0.0329) time: 2.9058 data: 0.0085 max mem: 33370 +Epoch: [33] [2260/2639] eta: 0:18:31 lr: 9.261332926504524e-06 loss: 0.0302 (0.0329) time: 2.9400 data: 0.0079 max mem: 33370 +Epoch: [33] [2270/2639] eta: 0:18:02 lr: 9.25619139136954e-06 loss: 0.0302 (0.0329) time: 2.9780 data: 0.0079 max mem: 33370 +Epoch: [33] [2280/2639] eta: 0:17:32 lr: 9.251049538885203e-06 loss: 0.0285 (0.0329) time: 3.0098 data: 0.0085 max mem: 33370 +Epoch: [33] [2290/2639] eta: 0:17:03 lr: 9.245907368835924e-06 loss: 0.0290 (0.0329) time: 3.0236 data: 0.0087 max mem: 33370 +Epoch: [33] [2300/2639] eta: 0:16:34 lr: 9.240764881005814e-06 loss: 0.0318 (0.0329) time: 2.9455 data: 0.0081 max mem: 33370 +Epoch: [33] [2310/2639] eta: 0:16:04 lr: 9.235622075178731e-06 loss: 0.0347 (0.0329) time: 2.8714 data: 0.0080 max mem: 33370 +Epoch: [33] [2320/2639] eta: 0:15:35 lr: 9.230478951138225e-06 loss: 0.0321 (0.0329) time: 2.8934 data: 0.0084 max mem: 33370 +Epoch: [33] [2330/2639] eta: 0:15:06 lr: 9.225335508667585e-06 loss: 0.0285 (0.0329) time: 2.9382 data: 0.0084 max mem: 33370 +Epoch: [33] [2340/2639] eta: 0:14:36 lr: 9.220191747549797e-06 loss: 0.0285 (0.0329) time: 2.9610 data: 0.0082 max mem: 33370 +Epoch: [33] [2350/2639] eta: 0:14:07 lr: 9.215047667567593e-06 loss: 0.0319 (0.0329) time: 2.9674 data: 0.0082 max mem: 33370 +Epoch: [33] [2360/2639] eta: 0:13:38 lr: 9.209903268503391e-06 loss: 0.0276 (0.0329) time: 2.9805 data: 0.0080 max mem: 33370 +Epoch: [33] [2370/2639] eta: 0:13:09 lr: 9.204758550139351e-06 loss: 0.0236 (0.0328) time: 2.9485 data: 0.0079 max mem: 33370 +Epoch: [33] [2380/2639] eta: 0:12:39 lr: 9.19961351225733e-06 loss: 0.0316 (0.0329) time: 2.9157 data: 0.0080 max mem: 33370 +Epoch: [33] [2390/2639] eta: 0:12:10 lr: 9.194468154638918e-06 loss: 0.0329 (0.0329) time: 2.9342 data: 0.0080 max mem: 33370 +Epoch: [33] [2400/2639] eta: 0:11:41 lr: 9.189322477065397e-06 loss: 0.0304 (0.0329) time: 2.9841 data: 0.0082 max mem: 33370 +Epoch: [33] [2410/2639] eta: 0:11:11 lr: 9.184176479317792e-06 loss: 0.0294 (0.0328) time: 2.9683 data: 0.0083 max mem: 33370 +Epoch: [33] [2420/2639] eta: 0:10:42 lr: 9.179030161176809e-06 loss: 0.0279 (0.0329) time: 2.9772 data: 0.0081 max mem: 33370 +Epoch: [33] [2430/2639] eta: 0:10:13 lr: 9.173883522422902e-06 loss: 0.0295 (0.0329) time: 2.9619 data: 0.0080 max mem: 33370 +Epoch: [33] [2440/2639] eta: 0:09:43 lr: 9.168736562836205e-06 loss: 0.0285 (0.0329) time: 2.8649 data: 0.0081 max mem: 33370 +Epoch: [33] [2450/2639] eta: 0:09:14 lr: 9.163589282196588e-06 loss: 0.0285 (0.0329) time: 2.8843 data: 0.0084 max mem: 33370 +Epoch: [33] [2460/2639] eta: 0:08:45 lr: 9.158441680283618e-06 loss: 0.0298 (0.0329) time: 2.9234 data: 0.0089 max mem: 33370 +Epoch: [33] [2470/2639] eta: 0:08:15 lr: 9.153293756876583e-06 loss: 0.0268 (0.0329) time: 2.9516 data: 0.0091 max mem: 33370 +Epoch: [33] [2480/2639] eta: 0:07:46 lr: 9.148145511754472e-06 loss: 0.0268 (0.0329) time: 2.9708 data: 0.0090 max mem: 33370 +Epoch: [33] [2490/2639] eta: 0:07:17 lr: 9.142996944695993e-06 loss: 0.0319 (0.0329) time: 2.9272 data: 0.0087 max mem: 33370 +Epoch: [33] [2500/2639] eta: 0:06:47 lr: 9.137848055479552e-06 loss: 0.0319 (0.0329) time: 2.8919 data: 0.0083 max mem: 33370 +Epoch: [33] [2510/2639] eta: 0:06:18 lr: 9.132698843883272e-06 loss: 0.0362 (0.0329) time: 2.8573 data: 0.0082 max mem: 33370 +Epoch: [33] [2520/2639] eta: 0:05:49 lr: 9.12754930968499e-06 loss: 0.0329 (0.0329) time: 2.9072 data: 0.0082 max mem: 33370 +Epoch: [33] [2530/2639] eta: 0:05:19 lr: 9.122399452662233e-06 loss: 0.0320 (0.0329) time: 2.9544 data: 0.0080 max mem: 33370 +Epoch: [33] [2540/2639] eta: 0:04:50 lr: 9.117249272592254e-06 loss: 0.0308 (0.0329) time: 2.9236 data: 0.0080 max mem: 33370 +Epoch: [33] [2550/2639] eta: 0:04:21 lr: 9.11209876925199e-06 loss: 0.0333 (0.0329) time: 2.9377 data: 0.0085 max mem: 33370 +Epoch: [33] [2560/2639] eta: 0:03:51 lr: 9.106947942418111e-06 loss: 0.0329 (0.0329) time: 2.9436 data: 0.0086 max mem: 33370 +Epoch: [33] [2570/2639] eta: 0:03:22 lr: 9.101796791866968e-06 loss: 0.0282 (0.0330) time: 2.9375 data: 0.0081 max mem: 33370 +Epoch: [33] [2580/2639] eta: 0:02:53 lr: 9.096645317374634e-06 loss: 0.0319 (0.0329) time: 2.9610 data: 0.0086 max mem: 33370 +Epoch: [33] [2590/2639] eta: 0:02:23 lr: 9.09149351871687e-06 loss: 0.0316 (0.0330) time: 2.9594 data: 0.0087 max mem: 33370 +Epoch: [33] [2600/2639] eta: 0:01:54 lr: 9.086341395669161e-06 loss: 0.0303 (0.0329) time: 2.9592 data: 0.0084 max mem: 33370 +Epoch: [33] [2610/2639] eta: 0:01:25 lr: 9.08118894800667e-06 loss: 0.0295 (0.0329) time: 2.9566 data: 0.0087 max mem: 33370 +Epoch: [33] [2620/2639] eta: 0:00:55 lr: 9.07603617550429e-06 loss: 0.0295 (0.0329) time: 2.9493 data: 0.0087 max mem: 33370 +Epoch: [33] [2630/2639] eta: 0:00:26 lr: 9.070883077936586e-06 loss: 0.0288 (0.0329) time: 2.9378 data: 0.0080 max mem: 33370 +Epoch: [33] Total time: 2:09:02 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 2:25:00 time: 3.3814 data: 3.2757 max mem: 33370 +Test: [ 100/2573] eta: 0:04:36 time: 0.0795 data: 0.0016 max mem: 33370 +Test: [ 200/2573] eta: 0:03:49 time: 0.0801 data: 0.0015 max mem: 33370 +Test: [ 300/2573] eta: 0:03:27 time: 0.0825 data: 0.0015 max mem: 33370 +Test: [ 400/2573] eta: 0:03:12 time: 0.0826 data: 0.0015 max mem: 33370 +Test: [ 500/2573] eta: 0:03:00 time: 0.0815 data: 0.0016 max mem: 33370 +Test: [ 600/2573] eta: 0:02:50 time: 0.0837 data: 0.0016 max mem: 33370 +Test: [ 700/2573] eta: 0:02:41 time: 0.0811 data: 0.0016 max mem: 33370 +Test: [ 800/2573] eta: 0:02:31 time: 0.0835 data: 0.0014 max mem: 33370 +Test: [ 900/2573] eta: 0:02:22 time: 0.0819 data: 0.0015 max mem: 33370 +Test: [1000/2573] eta: 0:02:13 time: 0.0824 data: 0.0015 max mem: 33370 +Test: [1100/2573] eta: 0:02:04 time: 0.0819 data: 0.0016 max mem: 33370 +Test: [1200/2573] eta: 0:01:55 time: 0.0808 data: 0.0016 max mem: 33370 +Test: [1300/2573] eta: 0:01:47 time: 0.0814 data: 0.0016 max mem: 33370 +Test: [1400/2573] eta: 0:01:38 time: 0.0798 data: 0.0016 max mem: 33370 +Test: [1500/2573] eta: 0:01:29 time: 0.0814 data: 0.0015 max mem: 33370 +Test: [1600/2573] eta: 0:01:21 time: 0.0853 data: 0.0017 max mem: 33370 +Test: [1700/2573] eta: 0:01:12 time: 0.0791 data: 0.0014 max mem: 33370 +Test: [1800/2573] eta: 0:01:04 time: 0.0827 data: 0.0016 max mem: 33370 +Test: [1900/2573] eta: 0:00:56 time: 0.0802 data: 0.0016 max mem: 33370 +Test: [2000/2573] eta: 0:00:47 time: 0.0821 data: 0.0015 max mem: 33370 +Test: [2100/2573] eta: 0:00:39 time: 0.0830 data: 0.0015 max mem: 33370 +Test: [2200/2573] eta: 0:00:30 time: 0.0835 data: 0.0015 max mem: 33370 +Test: [2300/2573] eta: 0:00:22 time: 0.0830 data: 0.0015 max mem: 33370 +Test: [2400/2573] eta: 0:00:14 time: 0.0790 data: 0.0016 max mem: 33370 +Test: [2500/2573] eta: 0:00:06 time: 0.0814 data: 0.0016 max mem: 33370 +Test: Total time: 0:03:33 +Final results: +Mean IoU is 64.46 + + precision@0.5 = 72.67 + precision@0.6 = 67.59 + precision@0.7 = 60.33 + precision@0.8 = 49.84 + precision@0.9 = 25.51 + overall IoU = 61.80 + +Average object IoU 64.4585680571881 +Overall IoU 61.79575729370117 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [34] [ 0/2639] eta: 5:00:11 lr: 9.066245012008258e-06 loss: 0.0159 (0.0159) time: 6.8252 data: 3.5573 max mem: 33370 +Epoch: [34] [ 10/2639] eta: 2:25:55 lr: 9.06109129619436e-06 loss: 0.0247 (0.0264) time: 3.3303 data: 0.3300 max mem: 33370 +Epoch: [34] [ 20/2639] eta: 2:17:32 lr: 9.05593725465973e-06 loss: 0.0252 (0.0389) time: 2.9672 data: 0.0081 max mem: 33370 +Epoch: [34] [ 30/2639] eta: 2:14:40 lr: 9.05078288717779e-06 loss: 0.0287 (0.0362) time: 2.9687 data: 0.0089 max mem: 33370 +Epoch: [34] [ 40/2639] eta: 2:12:06 lr: 9.045628193521643e-06 loss: 0.0317 (0.0365) time: 2.9440 data: 0.0086 max mem: 33370 +Epoch: [34] [ 50/2639] eta: 2:10:30 lr: 9.040473173464108e-06 loss: 0.0368 (0.0362) time: 2.9121 data: 0.0084 max mem: 33370 +Epoch: [34] [ 60/2639] eta: 2:09:26 lr: 9.035317826777679e-06 loss: 0.0311 (0.0353) time: 2.9323 data: 0.0083 max mem: 33370 +Epoch: [34] [ 70/2639] eta: 2:08:30 lr: 9.030162153234572e-06 loss: 0.0290 (0.0346) time: 2.9420 data: 0.0086 max mem: 33370 +Epoch: [34] [ 80/2639] eta: 2:07:41 lr: 9.025006152606676e-06 loss: 0.0296 (0.0343) time: 2.9409 data: 0.0089 max mem: 33370 +Epoch: [34] [ 90/2639] eta: 2:07:01 lr: 9.019849824665596e-06 loss: 0.0321 (0.0342) time: 2.9493 data: 0.0088 max mem: 33370 +Epoch: [34] [ 100/2639] eta: 2:06:17 lr: 9.014693169182615e-06 loss: 0.0302 (0.0335) time: 2.9455 data: 0.0084 max mem: 33370 +Epoch: [34] [ 110/2639] eta: 2:05:26 lr: 9.00953618592873e-06 loss: 0.0277 (0.0334) time: 2.9124 data: 0.0085 max mem: 33370 +Epoch: [34] [ 120/2639] eta: 2:04:55 lr: 9.00437887467461e-06 loss: 0.0301 (0.0331) time: 2.9310 data: 0.0086 max mem: 33370 +Epoch: [34] [ 130/2639] eta: 2:04:22 lr: 8.999221235190633e-06 loss: 0.0249 (0.0325) time: 2.9659 data: 0.0082 max mem: 33370 +Epoch: [34] [ 140/2639] eta: 2:03:52 lr: 8.994063267246872e-06 loss: 0.0249 (0.0323) time: 2.9667 data: 0.0083 max mem: 33370 +Epoch: [34] [ 150/2639] eta: 2:03:19 lr: 8.988904970613074e-06 loss: 0.0297 (0.0325) time: 2.9629 data: 0.0084 max mem: 33370 +Epoch: [34] [ 160/2639] eta: 2:02:42 lr: 8.983746345058701e-06 loss: 0.0297 (0.0322) time: 2.9391 data: 0.0085 max mem: 33370 +Epoch: [34] [ 170/2639] eta: 2:01:57 lr: 8.978587390352884e-06 loss: 0.0274 (0.0322) time: 2.8939 data: 0.0086 max mem: 33370 +Epoch: [34] [ 180/2639] eta: 2:01:20 lr: 8.973428106264467e-06 loss: 0.0288 (0.0323) time: 2.8885 data: 0.0081 max mem: 33370 +Epoch: [34] [ 190/2639] eta: 2:00:40 lr: 8.96826849256196e-06 loss: 0.0296 (0.0324) time: 2.8947 data: 0.0080 max mem: 33370 +Epoch: [34] [ 200/2639] eta: 2:00:13 lr: 8.963108549013586e-06 loss: 0.0302 (0.0327) time: 2.9290 data: 0.0084 max mem: 33370 +Epoch: [34] [ 210/2639] eta: 1:59:45 lr: 8.957948275387232e-06 loss: 0.0302 (0.0326) time: 2.9753 data: 0.0085 max mem: 33370 +Epoch: [34] [ 220/2639] eta: 1:59:12 lr: 8.952787671450498e-06 loss: 0.0297 (0.0327) time: 2.9474 data: 0.0085 max mem: 33370 +Epoch: [34] [ 230/2639] eta: 1:58:40 lr: 8.947626736970648e-06 loss: 0.0286 (0.0327) time: 2.9318 data: 0.0085 max mem: 33370 +Epoch: [34] [ 240/2639] eta: 1:58:09 lr: 8.94246547171466e-06 loss: 0.0282 (0.0327) time: 2.9391 data: 0.0084 max mem: 33370 +Epoch: [34] [ 250/2639] eta: 1:57:37 lr: 8.937303875449161e-06 loss: 0.0297 (0.0326) time: 2.9321 data: 0.0082 max mem: 33370 +Epoch: [34] [ 260/2639] eta: 1:57:07 lr: 8.932141947940505e-06 loss: 0.0297 (0.0328) time: 2.9353 data: 0.0087 max mem: 33370 +Epoch: [34] [ 270/2639] eta: 1:56:33 lr: 8.926979688954694e-06 loss: 0.0297 (0.0326) time: 2.9251 data: 0.0088 max mem: 33370 +Epoch: [34] [ 280/2639] eta: 1:56:04 lr: 8.921817098257446e-06 loss: 0.0289 (0.0325) time: 2.9346 data: 0.0086 max mem: 33370 +Epoch: [34] [ 290/2639] eta: 1:55:36 lr: 8.916654175614133e-06 loss: 0.0299 (0.0325) time: 2.9706 data: 0.0085 max mem: 33370 +Epoch: [34] [ 300/2639] eta: 1:55:10 lr: 8.911490920789836e-06 loss: 0.0320 (0.0326) time: 2.9850 data: 0.0085 max mem: 33370 +Epoch: [34] [ 310/2639] eta: 1:54:37 lr: 8.906327333549296e-06 loss: 0.0333 (0.0326) time: 2.9532 data: 0.0084 max mem: 33370 +Epoch: [34] [ 320/2639] eta: 1:54:10 lr: 8.901163413656962e-06 loss: 0.0284 (0.0324) time: 2.9438 data: 0.0087 max mem: 33370 +Epoch: [34] [ 330/2639] eta: 1:53:38 lr: 8.895999160876932e-06 loss: 0.0281 (0.0324) time: 2.9503 data: 0.0086 max mem: 33370 +Epoch: [34] [ 340/2639] eta: 1:53:09 lr: 8.890834574973015e-06 loss: 0.0286 (0.0324) time: 2.9412 data: 0.0081 max mem: 33370 +Epoch: [34] [ 350/2639] eta: 1:52:38 lr: 8.885669655708673e-06 loss: 0.0299 (0.0327) time: 2.9480 data: 0.0082 max mem: 33370 +Epoch: [34] [ 360/2639] eta: 1:52:10 lr: 8.880504402847072e-06 loss: 0.0334 (0.0327) time: 2.9531 data: 0.0086 max mem: 33370 +Epoch: [34] [ 370/2639] eta: 1:51:40 lr: 8.875338816151038e-06 loss: 0.0334 (0.0326) time: 2.9568 data: 0.0086 max mem: 33370 +Epoch: [34] [ 380/2639] eta: 1:51:13 lr: 8.870172895383079e-06 loss: 0.0332 (0.0327) time: 2.9727 data: 0.0084 max mem: 33370 +Epoch: [34] [ 390/2639] eta: 1:50:40 lr: 8.865006640305395e-06 loss: 0.0328 (0.0326) time: 2.9515 data: 0.0085 max mem: 33370 +Epoch: [34] [ 400/2639] eta: 1:50:09 lr: 8.859840050679838e-06 loss: 0.0308 (0.0326) time: 2.9099 data: 0.0088 max mem: 33370 +Epoch: [34] [ 410/2639] eta: 1:49:34 lr: 8.854673126267958e-06 loss: 0.0319 (0.0326) time: 2.8881 data: 0.0089 max mem: 33370 +Epoch: [34] [ 420/2639] eta: 1:49:06 lr: 8.84950586683096e-06 loss: 0.0326 (0.0327) time: 2.9178 data: 0.0087 max mem: 33370 +Epoch: [34] [ 430/2639] eta: 1:48:34 lr: 8.844338272129746e-06 loss: 0.0321 (0.0327) time: 2.9321 data: 0.0088 max mem: 33370 +Epoch: [34] [ 440/2639] eta: 1:48:04 lr: 8.839170341924868e-06 loss: 0.0312 (0.0327) time: 2.9115 data: 0.0094 max mem: 33370 +Epoch: [34] [ 450/2639] eta: 1:47:30 lr: 8.83400207597658e-06 loss: 0.0312 (0.0328) time: 2.8964 data: 0.0090 max mem: 33370 +Epoch: [34] [ 460/2639] eta: 1:47:02 lr: 8.828833474044773e-06 loss: 0.0319 (0.0329) time: 2.9180 data: 0.0084 max mem: 33370 +Epoch: [34] [ 470/2639] eta: 1:46:34 lr: 8.823664535889046e-06 loss: 0.0319 (0.0329) time: 2.9884 data: 0.0083 max mem: 33370 +Epoch: [34] [ 480/2639] eta: 1:46:08 lr: 8.818495261268642e-06 loss: 0.0317 (0.0328) time: 3.0026 data: 0.0085 max mem: 33370 +Epoch: [34] [ 490/2639] eta: 1:45:40 lr: 8.813325649942495e-06 loss: 0.0318 (0.0329) time: 3.0031 data: 0.0086 max mem: 33370 +Epoch: [34] [ 500/2639] eta: 1:45:11 lr: 8.808155701669188e-06 loss: 0.0329 (0.0329) time: 2.9825 data: 0.0082 max mem: 33370 +Epoch: [34] [ 510/2639] eta: 1:44:39 lr: 8.802985416206997e-06 loss: 0.0301 (0.0328) time: 2.9184 data: 0.0080 max mem: 33370 +Epoch: [34] [ 520/2639] eta: 1:44:06 lr: 8.79781479331384e-06 loss: 0.0263 (0.0327) time: 2.8689 data: 0.0083 max mem: 33370 +Epoch: [34] [ 530/2639] eta: 1:43:35 lr: 8.792643832747336e-06 loss: 0.0296 (0.0327) time: 2.8968 data: 0.0083 max mem: 33370 +Epoch: [34] [ 540/2639] eta: 1:43:05 lr: 8.787472534264734e-06 loss: 0.0303 (0.0327) time: 2.9203 data: 0.0082 max mem: 33370 +Epoch: [34] [ 550/2639] eta: 1:42:33 lr: 8.782300897622987e-06 loss: 0.0270 (0.0326) time: 2.9030 data: 0.0084 max mem: 33370 +Epoch: [34] [ 560/2639] eta: 1:42:04 lr: 8.777128922578677e-06 loss: 0.0283 (0.0327) time: 2.9170 data: 0.0081 max mem: 33370 +Epoch: [34] [ 570/2639] eta: 1:41:33 lr: 8.771956608888087e-06 loss: 0.0297 (0.0327) time: 2.9268 data: 0.0080 max mem: 33370 +Epoch: [34] [ 580/2639] eta: 1:41:03 lr: 8.766783956307132e-06 loss: 0.0297 (0.0326) time: 2.9234 data: 0.0081 max mem: 33370 +Epoch: [34] [ 590/2639] eta: 1:40:34 lr: 8.761610964591423e-06 loss: 0.0302 (0.0327) time: 2.9484 data: 0.0079 max mem: 33370 +Epoch: [34] [ 600/2639] eta: 1:40:02 lr: 8.756437633496201e-06 loss: 0.0309 (0.0327) time: 2.9071 data: 0.0084 max mem: 33370 +Epoch: [34] [ 610/2639] eta: 1:39:31 lr: 8.751263962776402e-06 loss: 0.0280 (0.0326) time: 2.8791 data: 0.0091 max mem: 33370 +Epoch: [34] [ 620/2639] eta: 1:39:00 lr: 8.746089952186593e-06 loss: 0.0262 (0.0326) time: 2.9057 data: 0.0086 max mem: 33370 +Epoch: [34] [ 630/2639] eta: 1:38:33 lr: 8.740915601481027e-06 loss: 0.0309 (0.0326) time: 2.9512 data: 0.0084 max mem: 33370 +Epoch: [34] [ 640/2639] eta: 1:38:03 lr: 8.73574091041361e-06 loss: 0.0333 (0.0327) time: 2.9746 data: 0.0086 max mem: 33370 +Epoch: [34] [ 650/2639] eta: 1:37:34 lr: 8.730565878737899e-06 loss: 0.0308 (0.0326) time: 2.9436 data: 0.0085 max mem: 33370 +Epoch: [34] [ 660/2639] eta: 1:37:05 lr: 8.725390506207125e-06 loss: 0.0272 (0.0326) time: 2.9467 data: 0.0084 max mem: 33370 +Epoch: [34] [ 670/2639] eta: 1:36:35 lr: 8.720214792574158e-06 loss: 0.0296 (0.0326) time: 2.9494 data: 0.0085 max mem: 33370 +Epoch: [34] [ 680/2639] eta: 1:36:06 lr: 8.715038737591552e-06 loss: 0.0275 (0.0325) time: 2.9430 data: 0.0085 max mem: 33370 +Epoch: [34] [ 690/2639] eta: 1:35:36 lr: 8.709862341011486e-06 loss: 0.0275 (0.0326) time: 2.9345 data: 0.0087 max mem: 33370 +Epoch: [34] [ 700/2639] eta: 1:35:06 lr: 8.704685602585829e-06 loss: 0.0306 (0.0325) time: 2.9231 data: 0.0090 max mem: 33370 +Epoch: [34] [ 710/2639] eta: 1:34:38 lr: 8.699508522066078e-06 loss: 0.0330 (0.0327) time: 2.9566 data: 0.0091 max mem: 33370 +Epoch: [34] [ 720/2639] eta: 1:34:08 lr: 8.694331099203403e-06 loss: 0.0328 (0.0327) time: 2.9612 data: 0.0094 max mem: 33370 +Epoch: [34] [ 730/2639] eta: 1:33:37 lr: 8.689153333748613e-06 loss: 0.0284 (0.0327) time: 2.9081 data: 0.0091 max mem: 33370 +Epoch: [34] [ 740/2639] eta: 1:33:06 lr: 8.68397522545219e-06 loss: 0.0268 (0.0326) time: 2.8847 data: 0.0089 max mem: 33370 +Epoch: [34] [ 750/2639] eta: 1:32:36 lr: 8.678796774064247e-06 loss: 0.0279 (0.0326) time: 2.9079 data: 0.0087 max mem: 33370 +Epoch: [34] [ 760/2639] eta: 1:32:06 lr: 8.67361797933457e-06 loss: 0.0285 (0.0326) time: 2.9146 data: 0.0085 max mem: 33370 +Epoch: [34] [ 770/2639] eta: 1:31:37 lr: 8.668438841012575e-06 loss: 0.0314 (0.0326) time: 2.9256 data: 0.0082 max mem: 33370 +Epoch: [34] [ 780/2639] eta: 1:31:08 lr: 8.66325935884735e-06 loss: 0.0279 (0.0326) time: 2.9666 data: 0.0081 max mem: 33370 +Epoch: [34] [ 790/2639] eta: 1:30:39 lr: 8.658079532587614e-06 loss: 0.0284 (0.0326) time: 2.9609 data: 0.0085 max mem: 33370 +Epoch: [34] [ 800/2639] eta: 1:30:10 lr: 8.652899361981753e-06 loss: 0.0310 (0.0326) time: 2.9589 data: 0.0085 max mem: 33370 +Epoch: [34] [ 810/2639] eta: 1:29:40 lr: 8.647718846777783e-06 loss: 0.0305 (0.0326) time: 2.9313 data: 0.0085 max mem: 33370 +Epoch: [34] [ 820/2639] eta: 1:29:10 lr: 8.642537986723387e-06 loss: 0.0341 (0.0327) time: 2.9047 data: 0.0083 max mem: 33370 +Epoch: [34] [ 830/2639] eta: 1:28:41 lr: 8.637356781565873e-06 loss: 0.0313 (0.0326) time: 2.9441 data: 0.0084 max mem: 33370 +Epoch: [34] [ 840/2639] eta: 1:28:11 lr: 8.632175231052221e-06 loss: 0.0281 (0.0326) time: 2.9414 data: 0.0089 max mem: 33370 +Epoch: [34] [ 850/2639] eta: 1:27:41 lr: 8.626993334929031e-06 loss: 0.0288 (0.0326) time: 2.9212 data: 0.0089 max mem: 33370 +Epoch: [34] [ 860/2639] eta: 1:27:10 lr: 8.621811092942572e-06 loss: 0.0285 (0.0326) time: 2.8903 data: 0.0087 max mem: 33370 +Epoch: [34] [ 870/2639] eta: 1:26:39 lr: 8.616628504838733e-06 loss: 0.0302 (0.0326) time: 2.8719 data: 0.0091 max mem: 33370 +Epoch: [34] [ 880/2639] eta: 1:26:09 lr: 8.61144557036306e-06 loss: 0.0319 (0.0326) time: 2.8855 data: 0.0090 max mem: 33370 +Epoch: [34] [ 890/2639] eta: 1:25:39 lr: 8.606262289260754e-06 loss: 0.0318 (0.0326) time: 2.9052 data: 0.0088 max mem: 33370 +Epoch: [34] [ 900/2639] eta: 1:25:09 lr: 8.601078661276626e-06 loss: 0.0318 (0.0326) time: 2.9142 data: 0.0090 max mem: 33370 +Epoch: [34] [ 910/2639] eta: 1:24:39 lr: 8.595894686155162e-06 loss: 0.0277 (0.0326) time: 2.8843 data: 0.0086 max mem: 33370 +Epoch: [34] [ 920/2639] eta: 1:24:08 lr: 8.590710363640458e-06 loss: 0.0309 (0.0327) time: 2.8800 data: 0.0086 max mem: 33370 +Epoch: [34] [ 930/2639] eta: 1:23:39 lr: 8.585525693476275e-06 loss: 0.0310 (0.0327) time: 2.9120 data: 0.0084 max mem: 33370 +Epoch: [34] [ 940/2639] eta: 1:23:09 lr: 8.580340675405992e-06 loss: 0.0307 (0.0327) time: 2.9201 data: 0.0083 max mem: 33370 +Epoch: [34] [ 950/2639] eta: 1:22:41 lr: 8.575155309172649e-06 loss: 0.0289 (0.0327) time: 2.9520 data: 0.0082 max mem: 33370 +Epoch: [34] [ 960/2639] eta: 1:22:11 lr: 8.569969594518896e-06 loss: 0.0283 (0.0327) time: 2.9657 data: 0.0079 max mem: 33370 +Epoch: [34] [ 970/2639] eta: 1:21:44 lr: 8.56478353118705e-06 loss: 0.0276 (0.0326) time: 2.9862 data: 0.0082 max mem: 33370 +Epoch: [34] [ 980/2639] eta: 1:21:14 lr: 8.559597118919032e-06 loss: 0.0326 (0.0327) time: 2.9836 data: 0.0083 max mem: 33370 +Epoch: [34] [ 990/2639] eta: 1:20:43 lr: 8.554410357456428e-06 loss: 0.0353 (0.0327) time: 2.8921 data: 0.0084 max mem: 33370 +Epoch: [34] [1000/2639] eta: 1:20:14 lr: 8.549223246540433e-06 loss: 0.0285 (0.0327) time: 2.9114 data: 0.0084 max mem: 33370 +Epoch: [34] [1010/2639] eta: 1:19:46 lr: 8.544035785911899e-06 loss: 0.0281 (0.0327) time: 2.9713 data: 0.0081 max mem: 33370 +Epoch: [34] [1020/2639] eta: 1:19:15 lr: 8.538847975311285e-06 loss: 0.0281 (0.0327) time: 2.9198 data: 0.0076 max mem: 33370 +Epoch: [34] [1030/2639] eta: 1:18:44 lr: 8.533659814478714e-06 loss: 0.0270 (0.0327) time: 2.8515 data: 0.0072 max mem: 33370 +Epoch: [34] [1040/2639] eta: 1:18:14 lr: 8.528471303153902e-06 loss: 0.0311 (0.0327) time: 2.8461 data: 0.0077 max mem: 33370 +Epoch: [34] [1050/2639] eta: 1:17:43 lr: 8.523282441076235e-06 loss: 0.0324 (0.0327) time: 2.8720 data: 0.0083 max mem: 33370 +Epoch: [34] [1060/2639] eta: 1:17:13 lr: 8.518093227984693e-06 loss: 0.0276 (0.0327) time: 2.8781 data: 0.0080 max mem: 33370 +Epoch: [34] [1070/2639] eta: 1:16:42 lr: 8.512903663617916e-06 loss: 0.0257 (0.0327) time: 2.8484 data: 0.0078 max mem: 33370 +Epoch: [34] [1080/2639] eta: 1:16:11 lr: 8.507713747714145e-06 loss: 0.0277 (0.0326) time: 2.8182 data: 0.0077 max mem: 33370 +Epoch: [34] [1090/2639] eta: 1:15:40 lr: 8.502523480011276e-06 loss: 0.0290 (0.0326) time: 2.8125 data: 0.0075 max mem: 33370 +Epoch: [34] [1100/2639] eta: 1:15:09 lr: 8.4973328602468e-06 loss: 0.0312 (0.0326) time: 2.8190 data: 0.0076 max mem: 33370 +Epoch: [34] [1110/2639] eta: 1:14:39 lr: 8.492141888157859e-06 loss: 0.0285 (0.0326) time: 2.8375 data: 0.0074 max mem: 33370 +Epoch: [34] [1120/2639] eta: 1:14:09 lr: 8.486950563481218e-06 loss: 0.0271 (0.0325) time: 2.8536 data: 0.0071 max mem: 33370 +Epoch: [34] [1130/2639] eta: 1:13:38 lr: 8.481758885953248e-06 loss: 0.0277 (0.0325) time: 2.8564 data: 0.0074 max mem: 33370 +Epoch: [34] [1140/2639] eta: 1:13:09 lr: 8.476566855309965e-06 loss: 0.0325 (0.0325) time: 2.8930 data: 0.0077 max mem: 33370 +Epoch: [34] [1150/2639] eta: 1:12:40 lr: 8.471374471286991e-06 loss: 0.0328 (0.0325) time: 2.9345 data: 0.0080 max mem: 33370 +Epoch: [34] [1160/2639] eta: 1:12:10 lr: 8.466181733619586e-06 loss: 0.0315 (0.0325) time: 2.9047 data: 0.0080 max mem: 33370 +Epoch: [34] [1170/2639] eta: 1:11:40 lr: 8.46098864204261e-06 loss: 0.0286 (0.0326) time: 2.8592 data: 0.0079 max mem: 33370 +Epoch: [34] [1180/2639] eta: 1:11:10 lr: 8.455795196290567e-06 loss: 0.0282 (0.0325) time: 2.8702 data: 0.0080 max mem: 33370 +Epoch: [34] [1190/2639] eta: 1:10:40 lr: 8.450601396097557e-06 loss: 0.0285 (0.0326) time: 2.8806 data: 0.0079 max mem: 33370 +Epoch: [34] [1200/2639] eta: 1:10:10 lr: 8.445407241197324e-06 loss: 0.0302 (0.0326) time: 2.8516 data: 0.0078 max mem: 33370 +Epoch: [34] [1210/2639] eta: 1:09:40 lr: 8.440212731323204e-06 loss: 0.0302 (0.0326) time: 2.8536 data: 0.0081 max mem: 33370 +Epoch: [34] [1220/2639] eta: 1:09:10 lr: 8.435017866208172e-06 loss: 0.0277 (0.0326) time: 2.8617 data: 0.0079 max mem: 33370 +Epoch: [34] [1230/2639] eta: 1:08:39 lr: 8.429822645584801e-06 loss: 0.0249 (0.0325) time: 2.8367 data: 0.0075 max mem: 33370 +Epoch: [34] [1240/2639] eta: 1:08:10 lr: 8.424627069185298e-06 loss: 0.0249 (0.0325) time: 2.8562 data: 0.0078 max mem: 33370 +Epoch: [34] [1250/2639] eta: 1:07:39 lr: 8.419431136741464e-06 loss: 0.0282 (0.0325) time: 2.8472 data: 0.0081 max mem: 33370 +Epoch: [34] [1260/2639] eta: 1:07:09 lr: 8.414234847984734e-06 loss: 0.0284 (0.0325) time: 2.8264 data: 0.0077 max mem: 33370 +Epoch: [34] [1270/2639] eta: 1:06:39 lr: 8.409038202646137e-06 loss: 0.0286 (0.0325) time: 2.8699 data: 0.0072 max mem: 33370 +Epoch: [34] [1280/2639] eta: 1:06:10 lr: 8.403841200456335e-06 loss: 0.0302 (0.0325) time: 2.8856 data: 0.0076 max mem: 33370 +Epoch: [34] [1290/2639] eta: 1:05:40 lr: 8.398643841145577e-06 loss: 0.0307 (0.0325) time: 2.8831 data: 0.0081 max mem: 33370 +Epoch: [34] [1300/2639] eta: 1:05:11 lr: 8.393446124443747e-06 loss: 0.0315 (0.0325) time: 2.8966 data: 0.0079 max mem: 33370 +Epoch: [34] [1310/2639] eta: 1:04:41 lr: 8.388248050080318e-06 loss: 0.0247 (0.0324) time: 2.8650 data: 0.0078 max mem: 33370 +Epoch: [34] [1320/2639] eta: 1:04:11 lr: 8.38304961778439e-06 loss: 0.0280 (0.0325) time: 2.8721 data: 0.0077 max mem: 33370 +Epoch: [34] [1330/2639] eta: 1:03:42 lr: 8.37785082728465e-06 loss: 0.0325 (0.0325) time: 2.9108 data: 0.0075 max mem: 33370 +Epoch: [34] [1340/2639] eta: 1:03:12 lr: 8.372651678309417e-06 loss: 0.0309 (0.0325) time: 2.8918 data: 0.0077 max mem: 33370 +Epoch: [34] [1350/2639] eta: 1:02:43 lr: 8.36745217058659e-06 loss: 0.0279 (0.0324) time: 2.8944 data: 0.0074 max mem: 33370 +Epoch: [34] [1360/2639] eta: 1:02:13 lr: 8.362252303843695e-06 loss: 0.0266 (0.0324) time: 2.8793 data: 0.0078 max mem: 33370 +Epoch: [34] [1370/2639] eta: 1:01:43 lr: 8.357052077807859e-06 loss: 0.0285 (0.0325) time: 2.8248 data: 0.0081 max mem: 33370 +Epoch: [34] [1380/2639] eta: 1:01:13 lr: 8.351851492205795e-06 loss: 0.0286 (0.0324) time: 2.8323 data: 0.0076 max mem: 33370 +Epoch: [34] [1390/2639] eta: 1:00:44 lr: 8.346650546763846e-06 loss: 0.0273 (0.0324) time: 2.8783 data: 0.0077 max mem: 33370 +Epoch: [34] [1400/2639] eta: 1:00:15 lr: 8.34144924120793e-06 loss: 0.0261 (0.0324) time: 2.9165 data: 0.0075 max mem: 33370 +Epoch: [34] [1410/2639] eta: 0:59:45 lr: 8.336247575263592e-06 loss: 0.0261 (0.0324) time: 2.8790 data: 0.0074 max mem: 33370 +Epoch: [34] [1420/2639] eta: 0:59:15 lr: 8.331045548655952e-06 loss: 0.0266 (0.0324) time: 2.8486 data: 0.0076 max mem: 33370 +Epoch: [34] [1430/2639] eta: 0:58:46 lr: 8.325843161109756e-06 loss: 0.0333 (0.0324) time: 2.8610 data: 0.0074 max mem: 33370 +Epoch: [34] [1440/2639] eta: 0:58:16 lr: 8.32064041234932e-06 loss: 0.0317 (0.0324) time: 2.8608 data: 0.0077 max mem: 33370 +Epoch: [34] [1450/2639] eta: 0:57:47 lr: 8.315437302098588e-06 loss: 0.0313 (0.0325) time: 2.8767 data: 0.0081 max mem: 33370 +Epoch: [34] [1460/2639] eta: 0:57:17 lr: 8.31023383008107e-06 loss: 0.0264 (0.0324) time: 2.8846 data: 0.0078 max mem: 33370 +Epoch: [34] [1470/2639] eta: 0:56:48 lr: 8.305029996019902e-06 loss: 0.0244 (0.0324) time: 2.8791 data: 0.0079 max mem: 33370 +Epoch: [34] [1480/2639] eta: 0:56:19 lr: 8.299825799637786e-06 loss: 0.0244 (0.0324) time: 2.8914 data: 0.0082 max mem: 33370 +Epoch: [34] [1490/2639] eta: 0:55:49 lr: 8.294621240657049e-06 loss: 0.0265 (0.0324) time: 2.8892 data: 0.0078 max mem: 33370 +Epoch: [34] [1500/2639] eta: 0:55:19 lr: 8.289416318799582e-06 loss: 0.0275 (0.0324) time: 2.8437 data: 0.0073 max mem: 33370 +Epoch: [34] [1510/2639] eta: 0:54:49 lr: 8.284211033786894e-06 loss: 0.0277 (0.0323) time: 2.8349 data: 0.0074 max mem: 33370 +Epoch: [34] [1520/2639] eta: 0:54:20 lr: 8.279005385340059e-06 loss: 0.0269 (0.0324) time: 2.8690 data: 0.0080 max mem: 33370 +Epoch: [34] [1530/2639] eta: 0:53:50 lr: 8.273799373179771e-06 loss: 0.0322 (0.0323) time: 2.8614 data: 0.0077 max mem: 33370 +Epoch: [34] [1540/2639] eta: 0:53:21 lr: 8.268592997026287e-06 loss: 0.0322 (0.0324) time: 2.8685 data: 0.0074 max mem: 33370 +Epoch: [34] [1550/2639] eta: 0:52:52 lr: 8.263386256599478e-06 loss: 0.0325 (0.0324) time: 2.8927 data: 0.0074 max mem: 33370 +Epoch: [34] [1560/2639] eta: 0:52:22 lr: 8.258179151618776e-06 loss: 0.0317 (0.0323) time: 2.8360 data: 0.0073 max mem: 33370 +Epoch: [34] [1570/2639] eta: 0:51:52 lr: 8.25297168180323e-06 loss: 0.0260 (0.0323) time: 2.8181 data: 0.0076 max mem: 33370 +Epoch: [34] [1580/2639] eta: 0:51:23 lr: 8.247763846871443e-06 loss: 0.0260 (0.0323) time: 2.8805 data: 0.0079 max mem: 33370 +Epoch: [34] [1590/2639] eta: 0:50:54 lr: 8.242555646541636e-06 loss: 0.0288 (0.0323) time: 2.8990 data: 0.0081 max mem: 33370 +Epoch: [34] [1600/2639] eta: 0:50:24 lr: 8.237347080531586e-06 loss: 0.0305 (0.0323) time: 2.8506 data: 0.0085 max mem: 33370 +Epoch: [34] [1610/2639] eta: 0:49:55 lr: 8.232138148558672e-06 loss: 0.0278 (0.0323) time: 2.8624 data: 0.0082 max mem: 33370 +Epoch: [34] [1620/2639] eta: 0:49:25 lr: 8.226928850339858e-06 loss: 0.0274 (0.0323) time: 2.8723 data: 0.0080 max mem: 33370 +Epoch: [34] [1630/2639] eta: 0:48:56 lr: 8.221719185591668e-06 loss: 0.0281 (0.0323) time: 2.8487 data: 0.0081 max mem: 33370 +Epoch: [34] [1640/2639] eta: 0:48:26 lr: 8.216509154030232e-06 loss: 0.0331 (0.0323) time: 2.8445 data: 0.0079 max mem: 33370 +Epoch: [34] [1650/2639] eta: 0:47:57 lr: 8.211298755371236e-06 loss: 0.0325 (0.0323) time: 2.8286 data: 0.0079 max mem: 33370 +Epoch: [34] [1660/2639] eta: 0:47:27 lr: 8.206087989329975e-06 loss: 0.0297 (0.0323) time: 2.8424 data: 0.0078 max mem: 33370 +Epoch: [34] [1670/2639] eta: 0:46:58 lr: 8.200876855621286e-06 loss: 0.0334 (0.0324) time: 2.8513 data: 0.0073 max mem: 33370 +Epoch: [34] [1680/2639] eta: 0:46:28 lr: 8.19566535395962e-06 loss: 0.0279 (0.0323) time: 2.8343 data: 0.0078 max mem: 33370 +Epoch: [34] [1690/2639] eta: 0:45:59 lr: 8.190453484058969e-06 loss: 0.0275 (0.0324) time: 2.8477 data: 0.0078 max mem: 33370 +Epoch: [34] [1700/2639] eta: 0:45:30 lr: 8.185241245632932e-06 loss: 0.0268 (0.0323) time: 2.8464 data: 0.0074 max mem: 33370 +Epoch: [34] [1710/2639] eta: 0:45:00 lr: 8.18002863839466e-06 loss: 0.0259 (0.0323) time: 2.8270 data: 0.0076 max mem: 33370 +Epoch: [34] [1720/2639] eta: 0:44:31 lr: 8.174815662056889e-06 loss: 0.0252 (0.0323) time: 2.8197 data: 0.0075 max mem: 33370 +Epoch: [34] [1730/2639] eta: 0:44:01 lr: 8.16960231633192e-06 loss: 0.0252 (0.0323) time: 2.8499 data: 0.0076 max mem: 33370 +Epoch: [34] [1740/2639] eta: 0:43:32 lr: 8.164388600931636e-06 loss: 0.0327 (0.0323) time: 2.8948 data: 0.0074 max mem: 33370 +Epoch: [34] [1750/2639] eta: 0:43:03 lr: 8.159174515567476e-06 loss: 0.0305 (0.0323) time: 2.8687 data: 0.0073 max mem: 33370 +Epoch: [34] [1760/2639] eta: 0:42:34 lr: 8.153960059950467e-06 loss: 0.0298 (0.0323) time: 2.9062 data: 0.0072 max mem: 33370 +Epoch: [34] [1770/2639] eta: 0:42:05 lr: 8.148745233791183e-06 loss: 0.0336 (0.0323) time: 2.9255 data: 0.0075 max mem: 33370 +Epoch: [34] [1780/2639] eta: 0:41:36 lr: 8.143530036799792e-06 loss: 0.0317 (0.0323) time: 2.9153 data: 0.0076 max mem: 33370 +Epoch: [34] [1790/2639] eta: 0:41:07 lr: 8.138314468685998e-06 loss: 0.0279 (0.0323) time: 2.9229 data: 0.0076 max mem: 33370 +Epoch: [34] [1800/2639] eta: 0:40:38 lr: 8.133098529159103e-06 loss: 0.0264 (0.0323) time: 2.8916 data: 0.0078 max mem: 33370 +Epoch: [34] [1810/2639] eta: 0:40:09 lr: 8.127882217927943e-06 loss: 0.0264 (0.0323) time: 2.8858 data: 0.0078 max mem: 33370 +Epoch: [34] [1820/2639] eta: 0:39:39 lr: 8.12266553470095e-06 loss: 0.0273 (0.0323) time: 2.8543 data: 0.0075 max mem: 33370 +Epoch: [34] [1830/2639] eta: 0:39:10 lr: 8.117448479186085e-06 loss: 0.0309 (0.0323) time: 2.8423 data: 0.0075 max mem: 33370 +Epoch: [34] [1840/2639] eta: 0:38:41 lr: 8.112231051090903e-06 loss: 0.0300 (0.0323) time: 2.8760 data: 0.0078 max mem: 33370 +Epoch: [34] [1850/2639] eta: 0:38:12 lr: 8.107013250122493e-06 loss: 0.0257 (0.0323) time: 2.9042 data: 0.0075 max mem: 33370 +Epoch: [34] [1860/2639] eta: 0:37:42 lr: 8.101795075987523e-06 loss: 0.0256 (0.0323) time: 2.8702 data: 0.0072 max mem: 33370 +Epoch: [34] [1870/2639] eta: 0:37:13 lr: 8.09657652839222e-06 loss: 0.0281 (0.0323) time: 2.8569 data: 0.0075 max mem: 33370 +Epoch: [34] [1880/2639] eta: 0:36:44 lr: 8.091357607042346e-06 loss: 0.0296 (0.0323) time: 2.8467 data: 0.0078 max mem: 33370 +Epoch: [34] [1890/2639] eta: 0:36:14 lr: 8.086138311643256e-06 loss: 0.0296 (0.0323) time: 2.8101 data: 0.0081 max mem: 33370 +Epoch: [34] [1900/2639] eta: 0:35:45 lr: 8.080918641899826e-06 loss: 0.0312 (0.0323) time: 2.8137 data: 0.0077 max mem: 33370 +Epoch: [34] [1910/2639] eta: 0:35:16 lr: 8.075698597516515e-06 loss: 0.0278 (0.0323) time: 2.8388 data: 0.0072 max mem: 33370 +Epoch: [34] [1920/2639] eta: 0:34:47 lr: 8.070478178197314e-06 loss: 0.0271 (0.0322) time: 2.8421 data: 0.0074 max mem: 33370 +Epoch: [34] [1930/2639] eta: 0:34:17 lr: 8.06525738364579e-06 loss: 0.0296 (0.0322) time: 2.8299 data: 0.0078 max mem: 33370 +Epoch: [34] [1940/2639] eta: 0:33:48 lr: 8.060036213565037e-06 loss: 0.0296 (0.0322) time: 2.8366 data: 0.0082 max mem: 33370 +Epoch: [34] [1950/2639] eta: 0:33:19 lr: 8.054814667657725e-06 loss: 0.0307 (0.0322) time: 2.8558 data: 0.0081 max mem: 33370 +Epoch: [34] [1960/2639] eta: 0:32:50 lr: 8.04959274562605e-06 loss: 0.0306 (0.0322) time: 2.8645 data: 0.0081 max mem: 33370 +Epoch: [34] [1970/2639] eta: 0:32:21 lr: 8.044370447171783e-06 loss: 0.0288 (0.0322) time: 2.8479 data: 0.0082 max mem: 33370 +Epoch: [34] [1980/2639] eta: 0:31:51 lr: 8.039147771996215e-06 loss: 0.0296 (0.0322) time: 2.8245 data: 0.0083 max mem: 33370 +Epoch: [34] [1990/2639] eta: 0:31:22 lr: 8.033924719800213e-06 loss: 0.0322 (0.0323) time: 2.8195 data: 0.0081 max mem: 33370 +Epoch: [34] [2000/2639] eta: 0:30:53 lr: 8.028701290284164e-06 loss: 0.0340 (0.0323) time: 2.8681 data: 0.0077 max mem: 33370 +Epoch: [34] [2010/2639] eta: 0:30:24 lr: 8.023477483148026e-06 loss: 0.0340 (0.0323) time: 2.8834 data: 0.0075 max mem: 33370 +Epoch: [34] [2020/2639] eta: 0:29:55 lr: 8.018253298091271e-06 loss: 0.0285 (0.0323) time: 2.8544 data: 0.0074 max mem: 33370 +Epoch: [34] [2030/2639] eta: 0:29:26 lr: 8.013028734812946e-06 loss: 0.0253 (0.0322) time: 2.8614 data: 0.0074 max mem: 33370 +Epoch: [34] [2040/2639] eta: 0:28:57 lr: 8.007803793011611e-06 loss: 0.0297 (0.0322) time: 2.8970 data: 0.0075 max mem: 33370 +Epoch: [34] [2050/2639] eta: 0:28:27 lr: 8.002578472385394e-06 loss: 0.0319 (0.0323) time: 2.8749 data: 0.0074 max mem: 33370 +Epoch: [34] [2060/2639] eta: 0:27:59 lr: 7.997352772631936e-06 loss: 0.0290 (0.0322) time: 2.8734 data: 0.0074 max mem: 33370 +Epoch: [34] [2070/2639] eta: 0:27:30 lr: 7.992126693448442e-06 loss: 0.0251 (0.0322) time: 2.9281 data: 0.0075 max mem: 33370 +Epoch: [34] [2080/2639] eta: 0:27:01 lr: 7.986900234531635e-06 loss: 0.0300 (0.0322) time: 2.9281 data: 0.0075 max mem: 33370 +Epoch: [34] [2090/2639] eta: 0:26:32 lr: 7.981673395577795e-06 loss: 0.0328 (0.0322) time: 2.9038 data: 0.0074 max mem: 33370 +Epoch: [34] [2100/2639] eta: 0:26:03 lr: 7.976446176282711e-06 loss: 0.0305 (0.0322) time: 2.8737 data: 0.0072 max mem: 33370 +Epoch: [34] [2110/2639] eta: 0:25:33 lr: 7.971218576341729e-06 loss: 0.0285 (0.0323) time: 2.8688 data: 0.0073 max mem: 33370 +Epoch: [34] [2120/2639] eta: 0:25:04 lr: 7.965990595449732e-06 loss: 0.0295 (0.0322) time: 2.8935 data: 0.0073 max mem: 33370 +Epoch: [34] [2130/2639] eta: 0:24:36 lr: 7.96076223330111e-06 loss: 0.0295 (0.0323) time: 2.9057 data: 0.0071 max mem: 33370 +Epoch: [34] [2140/2639] eta: 0:24:07 lr: 7.955533489589813e-06 loss: 0.0286 (0.0322) time: 2.9386 data: 0.0073 max mem: 33370 +Epoch: [34] [2150/2639] eta: 0:23:38 lr: 7.950304364009297e-06 loss: 0.0286 (0.0322) time: 2.9525 data: 0.0076 max mem: 33370 +Epoch: [34] [2160/2639] eta: 0:23:09 lr: 7.94507485625257e-06 loss: 0.0293 (0.0322) time: 2.9160 data: 0.0075 max mem: 33370 +Epoch: [34] [2170/2639] eta: 0:22:40 lr: 7.93984496601215e-06 loss: 0.0301 (0.0322) time: 2.8834 data: 0.0075 max mem: 33370 +Epoch: [34] [2180/2639] eta: 0:22:11 lr: 7.934614692980099e-06 loss: 0.0298 (0.0322) time: 2.8742 data: 0.0075 max mem: 33370 +Epoch: [34] [2190/2639] eta: 0:21:41 lr: 7.929384036847985e-06 loss: 0.0264 (0.0322) time: 2.8507 data: 0.0070 max mem: 33370 +Epoch: [34] [2200/2639] eta: 0:21:12 lr: 7.924152997306926e-06 loss: 0.0226 (0.0322) time: 2.8539 data: 0.0074 max mem: 33370 +Epoch: [34] [2210/2639] eta: 0:20:43 lr: 7.918921574047539e-06 loss: 0.0246 (0.0322) time: 2.8715 data: 0.0079 max mem: 33370 +Epoch: [34] [2220/2639] eta: 0:20:14 lr: 7.913689766759987e-06 loss: 0.0251 (0.0321) time: 2.8736 data: 0.0074 max mem: 33370 +Epoch: [34] [2230/2639] eta: 0:19:45 lr: 7.908457575133933e-06 loss: 0.0251 (0.0321) time: 2.8976 data: 0.0071 max mem: 33370 +Epoch: [34] [2240/2639] eta: 0:19:16 lr: 7.903224998858583e-06 loss: 0.0275 (0.0321) time: 2.8768 data: 0.0073 max mem: 33370 +Epoch: [34] [2250/2639] eta: 0:18:47 lr: 7.897992037622643e-06 loss: 0.0279 (0.0321) time: 2.8720 data: 0.0076 max mem: 33370 +Epoch: [34] [2260/2639] eta: 0:18:18 lr: 7.892758691114353e-06 loss: 0.0297 (0.0321) time: 2.9139 data: 0.0081 max mem: 33370 +Epoch: [34] [2270/2639] eta: 0:17:49 lr: 7.887524959021458e-06 loss: 0.0290 (0.0321) time: 2.9046 data: 0.0081 max mem: 33370 +Epoch: [34] [2280/2639] eta: 0:17:20 lr: 7.882290841031236e-06 loss: 0.0295 (0.0321) time: 2.8904 data: 0.0078 max mem: 33370 +Epoch: [34] [2290/2639] eta: 0:16:51 lr: 7.877056336830455e-06 loss: 0.0308 (0.0321) time: 2.9004 data: 0.0078 max mem: 33370 +Epoch: [34] [2300/2639] eta: 0:16:22 lr: 7.871821446105428e-06 loss: 0.0292 (0.0321) time: 2.8717 data: 0.0077 max mem: 33370 +Epoch: [34] [2310/2639] eta: 0:15:53 lr: 7.866586168541954e-06 loss: 0.0290 (0.0321) time: 2.8771 data: 0.0077 max mem: 33370 +Epoch: [34] [2320/2639] eta: 0:15:24 lr: 7.861350503825364e-06 loss: 0.0286 (0.0321) time: 2.8824 data: 0.0076 max mem: 33370 +Epoch: [34] [2330/2639] eta: 0:14:55 lr: 7.856114451640482e-06 loss: 0.0319 (0.0321) time: 2.8535 data: 0.0074 max mem: 33370 +Epoch: [34] [2340/2639] eta: 0:14:26 lr: 7.850878011671665e-06 loss: 0.0327 (0.0321) time: 2.8766 data: 0.0075 max mem: 33370 +Epoch: [34] [2350/2639] eta: 0:13:57 lr: 7.84564118360275e-06 loss: 0.0283 (0.0321) time: 2.8856 data: 0.0077 max mem: 33370 +Epoch: [34] [2360/2639] eta: 0:13:28 lr: 7.840403967117105e-06 loss: 0.0283 (0.0321) time: 2.8650 data: 0.0074 max mem: 33370 +Epoch: [34] [2370/2639] eta: 0:12:59 lr: 7.835166361897601e-06 loss: 0.0301 (0.0321) time: 2.9272 data: 0.0077 max mem: 33370 +Epoch: [34] [2380/2639] eta: 0:12:30 lr: 7.8299283676266e-06 loss: 0.0304 (0.0321) time: 2.9159 data: 0.0079 max mem: 33370 +Epoch: [34] [2390/2639] eta: 0:12:01 lr: 7.824689983985986e-06 loss: 0.0287 (0.0321) time: 2.8457 data: 0.0078 max mem: 33370 +Epoch: [34] [2400/2639] eta: 0:11:32 lr: 7.819451210657129e-06 loss: 0.0298 (0.0321) time: 2.8489 data: 0.0081 max mem: 33370 +Epoch: [34] [2410/2639] eta: 0:11:03 lr: 7.814212047320919e-06 loss: 0.0298 (0.0321) time: 2.8444 data: 0.0081 max mem: 33370 +Epoch: [34] [2420/2639] eta: 0:10:34 lr: 7.808972493657726e-06 loss: 0.0280 (0.0321) time: 2.8786 data: 0.0074 max mem: 33370 +Epoch: [34] [2430/2639] eta: 0:10:05 lr: 7.803732549347445e-06 loss: 0.0281 (0.0321) time: 2.8769 data: 0.0075 max mem: 33370 +Epoch: [34] [2440/2639] eta: 0:09:36 lr: 7.79849221406944e-06 loss: 0.0284 (0.0321) time: 2.8698 data: 0.0081 max mem: 33370 +Epoch: [34] [2450/2639] eta: 0:09:07 lr: 7.793251487502603e-06 loss: 0.0298 (0.0321) time: 2.8933 data: 0.0081 max mem: 33370 +Epoch: [34] [2460/2639] eta: 0:08:38 lr: 7.78801036932529e-06 loss: 0.0309 (0.0321) time: 2.8691 data: 0.0078 max mem: 33370 +Epoch: [34] [2470/2639] eta: 0:08:09 lr: 7.782768859215387e-06 loss: 0.0291 (0.0321) time: 2.8545 data: 0.0074 max mem: 33370 +Epoch: [34] [2480/2639] eta: 0:07:40 lr: 7.777526956850238e-06 loss: 0.0262 (0.0321) time: 2.8480 data: 0.0075 max mem: 33370 +Epoch: [34] [2490/2639] eta: 0:07:11 lr: 7.77228466190671e-06 loss: 0.0301 (0.0321) time: 2.8083 data: 0.0080 max mem: 33370 +Epoch: [34] [2500/2639] eta: 0:06:42 lr: 7.767041974061137e-06 loss: 0.0323 (0.0321) time: 2.8049 data: 0.0077 max mem: 33370 +Epoch: [34] [2510/2639] eta: 0:06:13 lr: 7.761798892989367e-06 loss: 0.0262 (0.0321) time: 2.8598 data: 0.0076 max mem: 33370 +Epoch: [34] [2520/2639] eta: 0:05:44 lr: 7.756555418366713e-06 loss: 0.0274 (0.0321) time: 2.8551 data: 0.0085 max mem: 33370 +Epoch: [34] [2530/2639] eta: 0:05:15 lr: 7.751311549867997e-06 loss: 0.0293 (0.0321) time: 2.8312 data: 0.0083 max mem: 33370 +Epoch: [34] [2540/2639] eta: 0:04:46 lr: 7.746067287167508e-06 loss: 0.0311 (0.0320) time: 2.8531 data: 0.0080 max mem: 33370 +Epoch: [34] [2550/2639] eta: 0:04:17 lr: 7.740822629939042e-06 loss: 0.0316 (0.0321) time: 2.8992 data: 0.0079 max mem: 33370 +Epoch: [34] [2560/2639] eta: 0:03:48 lr: 7.735577577855853e-06 loss: 0.0323 (0.0321) time: 2.9278 data: 0.0075 max mem: 33370 +Epoch: [34] [2570/2639] eta: 0:03:19 lr: 7.730332130590709e-06 loss: 0.0322 (0.0321) time: 2.9153 data: 0.0075 max mem: 33370 +Epoch: [34] [2580/2639] eta: 0:02:50 lr: 7.72508628781583e-06 loss: 0.0306 (0.0321) time: 2.8914 data: 0.0076 max mem: 33370 +Epoch: [34] [2590/2639] eta: 0:02:21 lr: 7.719840049202936e-06 loss: 0.0280 (0.0320) time: 2.8740 data: 0.0077 max mem: 33370 +Epoch: [34] [2600/2639] eta: 0:01:52 lr: 7.714593414423226e-06 loss: 0.0271 (0.0320) time: 2.8470 data: 0.0075 max mem: 33370 +Epoch: [34] [2610/2639] eta: 0:01:23 lr: 7.709346383147361e-06 loss: 0.0272 (0.0320) time: 2.8521 data: 0.0076 max mem: 33370 +Epoch: [34] [2620/2639] eta: 0:00:55 lr: 7.7040989550455e-06 loss: 0.0294 (0.0320) time: 2.8949 data: 0.0075 max mem: 33370 +Epoch: [34] [2630/2639] eta: 0:00:26 lr: 7.698851129787256e-06 loss: 0.0301 (0.0320) time: 2.9066 data: 0.0075 max mem: 33370 +Epoch: [34] Total time: 2:07:21 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 2:10:57 time: 3.0539 data: 2.9608 max mem: 33370 +Test: [ 100/2573] eta: 0:04:22 time: 0.0762 data: 0.0014 max mem: 33370 +Test: [ 200/2573] eta: 0:03:39 time: 0.0777 data: 0.0014 max mem: 33370 +Test: [ 300/2573] eta: 0:03:18 time: 0.0800 data: 0.0013 max mem: 33370 +Test: [ 400/2573] eta: 0:03:05 time: 0.0808 data: 0.0013 max mem: 33370 +Test: [ 500/2573] eta: 0:02:53 time: 0.0787 data: 0.0015 max mem: 33370 +Test: [ 600/2573] eta: 0:02:44 time: 0.0790 data: 0.0013 max mem: 33370 +Test: [ 700/2573] eta: 0:02:35 time: 0.0794 data: 0.0013 max mem: 33370 +Test: [ 800/2573] eta: 0:02:26 time: 0.0816 data: 0.0013 max mem: 33370 +Test: [ 900/2573] eta: 0:02:17 time: 0.0793 data: 0.0014 max mem: 33370 +Test: [1000/2573] eta: 0:02:08 time: 0.0795 data: 0.0014 max mem: 33370 +Test: [1100/2573] eta: 0:02:00 time: 0.0791 data: 0.0014 max mem: 33370 +Test: [1200/2573] eta: 0:01:52 time: 0.0791 data: 0.0013 max mem: 33370 +Test: [1300/2573] eta: 0:01:43 time: 0.0790 data: 0.0013 max mem: 33370 +Test: [1400/2573] eta: 0:01:35 time: 0.0780 data: 0.0013 max mem: 33370 +Test: [1500/2573] eta: 0:01:27 time: 0.0792 data: 0.0013 max mem: 33370 +Test: [1600/2573] eta: 0:01:18 time: 0.0831 data: 0.0014 max mem: 33370 +Test: [1700/2573] eta: 0:01:10 time: 0.0769 data: 0.0013 max mem: 33370 +Test: [1800/2573] eta: 0:01:02 time: 0.0809 data: 0.0014 max mem: 33370 +Test: [1900/2573] eta: 0:00:54 time: 0.0779 data: 0.0014 max mem: 33370 +Test: [2000/2573] eta: 0:00:46 time: 0.0793 data: 0.0015 max mem: 33370 +Test: [2100/2573] eta: 0:00:38 time: 0.0813 data: 0.0013 max mem: 33370 +Test: [2200/2573] eta: 0:00:30 time: 0.0820 data: 0.0014 max mem: 33370 +Test: [2300/2573] eta: 0:00:21 time: 0.0816 data: 0.0013 max mem: 33370 +Test: [2400/2573] eta: 0:00:13 time: 0.0763 data: 0.0014 max mem: 33370 +Test: [2500/2573] eta: 0:00:05 time: 0.0807 data: 0.0016 max mem: 33370 +Test: Total time: 0:03:27 +Final results: +Mean IoU is 64.55 + + precision@0.5 = 72.69 + precision@0.6 = 67.73 + precision@0.7 = 61.17 + precision@0.8 = 50.33 + precision@0.9 = 25.90 + overall IoU = 61.86 + +Average object IoU 64.54738546082916 +Overall IoU 61.85955047607422 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [35] [ 0/2639] eta: 4:52:24 lr: 7.694127747212657e-06 loss: 0.0243 (0.0243) time: 6.6480 data: 3.5477 max mem: 33370 +Epoch: [35] [ 10/2639] eta: 2:18:13 lr: 7.688879166445238e-06 loss: 0.0253 (0.0278) time: 3.1545 data: 0.3295 max mem: 33370 +Epoch: [35] [ 20/2639] eta: 2:11:38 lr: 7.68363018756037e-06 loss: 0.0290 (0.0296) time: 2.8344 data: 0.0072 max mem: 33370 +Epoch: [35] [ 30/2639] eta: 2:09:23 lr: 7.678380810225635e-06 loss: 0.0296 (0.0311) time: 2.8771 data: 0.0072 max mem: 33370 +Epoch: [35] [ 40/2639] eta: 2:07:36 lr: 7.673131034108056e-06 loss: 0.0273 (0.0308) time: 2.8727 data: 0.0081 max mem: 33370 +Epoch: [35] [ 50/2639] eta: 2:06:27 lr: 7.667880858874153e-06 loss: 0.0305 (0.0326) time: 2.8612 data: 0.0085 max mem: 33370 +Epoch: [35] [ 60/2639] eta: 2:05:17 lr: 7.662630284189888e-06 loss: 0.0305 (0.0326) time: 2.8511 data: 0.0084 max mem: 33370 +Epoch: [35] [ 70/2639] eta: 2:04:31 lr: 7.657379309720712e-06 loss: 0.0288 (0.0324) time: 2.8505 data: 0.0082 max mem: 33370 +Epoch: [35] [ 80/2639] eta: 2:03:40 lr: 7.652127935131516e-06 loss: 0.0300 (0.0320) time: 2.8537 data: 0.0079 max mem: 33370 +Epoch: [35] [ 90/2639] eta: 2:03:12 lr: 7.64687616008668e-06 loss: 0.0293 (0.0317) time: 2.8716 data: 0.0081 max mem: 33370 +Epoch: [35] [ 100/2639] eta: 2:02:33 lr: 7.64162398425002e-06 loss: 0.0293 (0.0315) time: 2.8824 data: 0.0080 max mem: 33370 +Epoch: [35] [ 110/2639] eta: 2:01:59 lr: 7.63637140728484e-06 loss: 0.0312 (0.0314) time: 2.8684 data: 0.0076 max mem: 33370 +Epoch: [35] [ 120/2639] eta: 2:01:35 lr: 7.631118428853874e-06 loss: 0.0285 (0.0310) time: 2.8953 data: 0.0075 max mem: 33370 +Epoch: [35] [ 130/2639] eta: 2:01:02 lr: 7.6258650486193475e-06 loss: 0.0285 (0.0309) time: 2.8966 data: 0.0076 max mem: 33370 +Epoch: [35] [ 140/2639] eta: 2:00:41 lr: 7.620611266242908e-06 loss: 0.0303 (0.0312) time: 2.9085 data: 0.0078 max mem: 33370 +Epoch: [35] [ 150/2639] eta: 2:00:05 lr: 7.615357081385692e-06 loss: 0.0325 (0.0314) time: 2.8953 data: 0.0077 max mem: 33370 +Epoch: [35] [ 160/2639] eta: 1:59:34 lr: 7.610102493708262e-06 loss: 0.0325 (0.0315) time: 2.8657 data: 0.0075 max mem: 33370 +Epoch: [35] [ 170/2639] eta: 1:58:59 lr: 7.604847502870654e-06 loss: 0.0288 (0.0313) time: 2.8662 data: 0.0075 max mem: 33370 +Epoch: [35] [ 180/2639] eta: 1:58:27 lr: 7.599592108532341e-06 loss: 0.0290 (0.0313) time: 2.8604 data: 0.0079 max mem: 33370 +Epoch: [35] [ 190/2639] eta: 1:57:57 lr: 7.594336310352264e-06 loss: 0.0309 (0.0313) time: 2.8762 data: 0.0076 max mem: 33370 +Epoch: [35] [ 200/2639] eta: 1:57:26 lr: 7.58908010798879e-06 loss: 0.0313 (0.0313) time: 2.8799 data: 0.0073 max mem: 33370 +Epoch: [35] [ 210/2639] eta: 1:56:58 lr: 7.583823501099758e-06 loss: 0.0297 (0.0311) time: 2.8866 data: 0.0073 max mem: 33370 +Epoch: [35] [ 220/2639] eta: 1:56:20 lr: 7.578566489342433e-06 loss: 0.0272 (0.0310) time: 2.8522 data: 0.0075 max mem: 33370 +Epoch: [35] [ 230/2639] eta: 1:55:45 lr: 7.5733090723735355e-06 loss: 0.0295 (0.0311) time: 2.8132 data: 0.0074 max mem: 33370 +Epoch: [35] [ 240/2639] eta: 1:55:13 lr: 7.5680512498492396e-06 loss: 0.0316 (0.0311) time: 2.8393 data: 0.0072 max mem: 33370 +Epoch: [35] [ 250/2639] eta: 1:54:36 lr: 7.562793021425135e-06 loss: 0.0290 (0.0312) time: 2.8263 data: 0.0076 max mem: 33370 +Epoch: [35] [ 260/2639] eta: 1:54:02 lr: 7.557534386756284e-06 loss: 0.0276 (0.0311) time: 2.8051 data: 0.0075 max mem: 33370 +Epoch: [35] [ 270/2639] eta: 1:53:27 lr: 7.552275345497159e-06 loss: 0.0276 (0.0311) time: 2.8137 data: 0.0074 max mem: 33370 +Epoch: [35] [ 280/2639] eta: 1:52:56 lr: 7.5470158973017e-06 loss: 0.0287 (0.0314) time: 2.8251 data: 0.0077 max mem: 33370 +Epoch: [35] [ 290/2639] eta: 1:52:24 lr: 7.541756041823255e-06 loss: 0.0261 (0.0312) time: 2.8388 data: 0.0076 max mem: 33370 +Epoch: [35] [ 300/2639] eta: 1:51:57 lr: 7.536495778714636e-06 loss: 0.0252 (0.0312) time: 2.8619 data: 0.0075 max mem: 33370 +Epoch: [35] [ 310/2639] eta: 1:51:29 lr: 7.531235107628065e-06 loss: 0.0271 (0.0311) time: 2.8842 data: 0.0076 max mem: 33370 +Epoch: [35] [ 320/2639] eta: 1:51:00 lr: 7.525974028215218e-06 loss: 0.0300 (0.0311) time: 2.8753 data: 0.0079 max mem: 33370 +Epoch: [35] [ 330/2639] eta: 1:50:29 lr: 7.520712540127184e-06 loss: 0.0321 (0.0312) time: 2.8552 data: 0.0077 max mem: 33370 +Epoch: [35] [ 340/2639] eta: 1:50:01 lr: 7.5154506430145004e-06 loss: 0.0297 (0.0312) time: 2.8661 data: 0.0079 max mem: 33370 +Epoch: [35] [ 350/2639] eta: 1:49:31 lr: 7.510188336527114e-06 loss: 0.0310 (0.0312) time: 2.8665 data: 0.0080 max mem: 33370 +Epoch: [35] [ 360/2639] eta: 1:49:02 lr: 7.504925620314422e-06 loss: 0.0316 (0.0312) time: 2.8567 data: 0.0077 max mem: 33370 +Epoch: [35] [ 370/2639] eta: 1:48:30 lr: 7.499662494025222e-06 loss: 0.0291 (0.0312) time: 2.8474 data: 0.0076 max mem: 33370 +Epoch: [35] [ 380/2639] eta: 1:48:02 lr: 7.494398957307766e-06 loss: 0.0279 (0.0311) time: 2.8464 data: 0.0081 max mem: 33370 +Epoch: [35] [ 390/2639] eta: 1:47:33 lr: 7.4891350098096985e-06 loss: 0.0287 (0.0310) time: 2.8672 data: 0.0082 max mem: 33370 +Epoch: [35] [ 400/2639] eta: 1:47:05 lr: 7.483870651178114e-06 loss: 0.0257 (0.0309) time: 2.8787 data: 0.0076 max mem: 33370 +Epoch: [35] [ 410/2639] eta: 1:46:33 lr: 7.478605881059504e-06 loss: 0.0288 (0.0311) time: 2.8446 data: 0.0077 max mem: 33370 +Epoch: [35] [ 420/2639] eta: 1:46:01 lr: 7.473340699099801e-06 loss: 0.0318 (0.0310) time: 2.8068 data: 0.0074 max mem: 33370 +Epoch: [35] [ 430/2639] eta: 1:45:28 lr: 7.468075104944334e-06 loss: 0.0289 (0.0311) time: 2.7926 data: 0.0073 max mem: 33370 +Epoch: [35] [ 440/2639] eta: 1:44:59 lr: 7.46280909823787e-06 loss: 0.0294 (0.0312) time: 2.8209 data: 0.0076 max mem: 33370 +Epoch: [35] [ 450/2639] eta: 1:44:31 lr: 7.45754267862457e-06 loss: 0.0294 (0.0312) time: 2.8693 data: 0.0076 max mem: 33370 +Epoch: [35] [ 460/2639] eta: 1:44:03 lr: 7.4522758457480285e-06 loss: 0.0303 (0.0312) time: 2.8737 data: 0.0077 max mem: 33370 +Epoch: [35] [ 470/2639] eta: 1:43:30 lr: 7.447008599251233e-06 loss: 0.0265 (0.0311) time: 2.8303 data: 0.0082 max mem: 33370 +Epoch: [35] [ 480/2639] eta: 1:43:02 lr: 7.4417409387765965e-06 loss: 0.0265 (0.0311) time: 2.8203 data: 0.0079 max mem: 33370 +Epoch: [35] [ 490/2639] eta: 1:42:31 lr: 7.4364728639659405e-06 loss: 0.0272 (0.0311) time: 2.8397 data: 0.0073 max mem: 33370 +Epoch: [35] [ 500/2639] eta: 1:42:01 lr: 7.43120437446048e-06 loss: 0.0296 (0.0313) time: 2.8294 data: 0.0072 max mem: 33370 +Epoch: [35] [ 510/2639] eta: 1:41:30 lr: 7.425935469900859e-06 loss: 0.0329 (0.0313) time: 2.8217 data: 0.0075 max mem: 33370 +Epoch: [35] [ 520/2639] eta: 1:41:03 lr: 7.4206661499270995e-06 loss: 0.0299 (0.0314) time: 2.8529 data: 0.0078 max mem: 33370 +Epoch: [35] [ 530/2639] eta: 1:40:33 lr: 7.415396414178656e-06 loss: 0.0289 (0.0314) time: 2.8568 data: 0.0081 max mem: 33370 +Epoch: [35] [ 540/2639] eta: 1:40:05 lr: 7.410126262294358e-06 loss: 0.0259 (0.0314) time: 2.8472 data: 0.0078 max mem: 33370 +Epoch: [35] [ 550/2639] eta: 1:39:38 lr: 7.4048556939124605e-06 loss: 0.0259 (0.0313) time: 2.8896 data: 0.0075 max mem: 33370 +Epoch: [35] [ 560/2639] eta: 1:39:09 lr: 7.399584708670591e-06 loss: 0.0299 (0.0314) time: 2.8796 data: 0.0076 max mem: 33370 +Epoch: [35] [ 570/2639] eta: 1:38:40 lr: 7.394313306205804e-06 loss: 0.0332 (0.0314) time: 2.8584 data: 0.0075 max mem: 33370 +Epoch: [35] [ 580/2639] eta: 1:38:10 lr: 7.389041486154523e-06 loss: 0.0311 (0.0315) time: 2.8348 data: 0.0076 max mem: 33370 +Epoch: [35] [ 590/2639] eta: 1:37:42 lr: 7.3837692481525885e-06 loss: 0.0311 (0.0315) time: 2.8435 data: 0.0078 max mem: 33370 +Epoch: [35] [ 600/2639] eta: 1:37:15 lr: 7.378496591835214e-06 loss: 0.0294 (0.0316) time: 2.8932 data: 0.0077 max mem: 33370 +Epoch: [35] [ 610/2639] eta: 1:36:48 lr: 7.373223516837026e-06 loss: 0.0234 (0.0315) time: 2.9189 data: 0.0075 max mem: 33370 +Epoch: [35] [ 620/2639] eta: 1:36:22 lr: 7.367950022792018e-06 loss: 0.0268 (0.0317) time: 2.9216 data: 0.0077 max mem: 33370 +Epoch: [35] [ 630/2639] eta: 1:35:53 lr: 7.362676109333598e-06 loss: 0.0294 (0.0317) time: 2.8892 data: 0.0074 max mem: 33370 +Epoch: [35] [ 640/2639] eta: 1:35:24 lr: 7.3574017760945345e-06 loss: 0.0294 (0.0316) time: 2.8531 data: 0.0074 max mem: 33370 +Epoch: [35] [ 650/2639] eta: 1:34:55 lr: 7.352127022707006e-06 loss: 0.0306 (0.0316) time: 2.8576 data: 0.0079 max mem: 33370 +Epoch: [35] [ 660/2639] eta: 1:34:28 lr: 7.3468518488025524e-06 loss: 0.0292 (0.0316) time: 2.8846 data: 0.0076 max mem: 33370 +Epoch: [35] [ 670/2639] eta: 1:33:57 lr: 7.34157625401212e-06 loss: 0.0239 (0.0316) time: 2.8522 data: 0.0077 max mem: 33370 +Epoch: [35] [ 680/2639] eta: 1:33:30 lr: 7.3363002379660126e-06 loss: 0.0297 (0.0315) time: 2.8518 data: 0.0078 max mem: 33370 +Epoch: [35] [ 690/2639] eta: 1:33:01 lr: 7.331023800293937e-06 loss: 0.0293 (0.0316) time: 2.8745 data: 0.0078 max mem: 33370 +Epoch: [35] [ 700/2639] eta: 1:32:33 lr: 7.325746940624953e-06 loss: 0.0307 (0.0316) time: 2.8823 data: 0.0079 max mem: 33370 +Epoch: [35] [ 710/2639] eta: 1:32:04 lr: 7.320469658587524e-06 loss: 0.0324 (0.0316) time: 2.8792 data: 0.0074 max mem: 33370 +Epoch: [35] [ 720/2639] eta: 1:31:36 lr: 7.315191953809459e-06 loss: 0.0331 (0.0317) time: 2.8604 data: 0.0075 max mem: 33370 +Epoch: [35] [ 730/2639] eta: 1:31:07 lr: 7.309913825917966e-06 loss: 0.0331 (0.0316) time: 2.8656 data: 0.0076 max mem: 33370 +Epoch: [35] [ 740/2639] eta: 1:30:39 lr: 7.304635274539618e-06 loss: 0.0313 (0.0317) time: 2.8662 data: 0.0077 max mem: 33370 +Epoch: [35] [ 750/2639] eta: 1:30:09 lr: 7.299356299300343e-06 loss: 0.0274 (0.0316) time: 2.8492 data: 0.0076 max mem: 33370 +Epoch: [35] [ 760/2639] eta: 1:29:40 lr: 7.294076899825464e-06 loss: 0.0279 (0.0316) time: 2.8391 data: 0.0075 max mem: 33370 +Epoch: [35] [ 770/2639] eta: 1:29:13 lr: 7.288797075739642e-06 loss: 0.0282 (0.0316) time: 2.8916 data: 0.0074 max mem: 33370 +Epoch: [35] [ 780/2639] eta: 1:28:46 lr: 7.283516826666932e-06 loss: 0.0275 (0.0316) time: 2.9281 data: 0.0074 max mem: 33370 +Epoch: [35] [ 790/2639] eta: 1:28:18 lr: 7.2782361522307274e-06 loss: 0.0282 (0.0316) time: 2.9206 data: 0.0073 max mem: 33370 +Epoch: [35] [ 800/2639] eta: 1:27:49 lr: 7.2729550520538074e-06 loss: 0.0287 (0.0316) time: 2.8674 data: 0.0071 max mem: 33370 +Epoch: [35] [ 810/2639] eta: 1:27:19 lr: 7.26767352575829e-06 loss: 0.0287 (0.0316) time: 2.8097 data: 0.0073 max mem: 33370 +Epoch: [35] [ 820/2639] eta: 1:26:51 lr: 7.262391572965672e-06 loss: 0.0304 (0.0316) time: 2.8499 data: 0.0075 max mem: 33370 +Epoch: [35] [ 830/2639] eta: 1:26:24 lr: 7.25710919329679e-06 loss: 0.0298 (0.0316) time: 2.9234 data: 0.0075 max mem: 33370 +Epoch: [35] [ 840/2639] eta: 1:25:57 lr: 7.2518263863718555e-06 loss: 0.0284 (0.0316) time: 2.9421 data: 0.0077 max mem: 33370 +Epoch: [35] [ 850/2639] eta: 1:25:30 lr: 7.246543151810414e-06 loss: 0.0275 (0.0316) time: 2.9516 data: 0.0077 max mem: 33370 +Epoch: [35] [ 860/2639] eta: 1:25:03 lr: 7.241259489231385e-06 loss: 0.0294 (0.0316) time: 2.9472 data: 0.0079 max mem: 33370 +Epoch: [35] [ 870/2639] eta: 1:24:37 lr: 7.235975398253014e-06 loss: 0.0253 (0.0316) time: 2.9638 data: 0.0092 max mem: 33370 +Epoch: [35] [ 880/2639] eta: 1:24:10 lr: 7.230690878492927e-06 loss: 0.0291 (0.0316) time: 2.9753 data: 0.0098 max mem: 33370 +Epoch: [35] [ 890/2639] eta: 1:23:41 lr: 7.2254059295680645e-06 loss: 0.0306 (0.0316) time: 2.9068 data: 0.0088 max mem: 33370 +Epoch: [35] [ 900/2639] eta: 1:23:12 lr: 7.220120551094744e-06 loss: 0.0279 (0.0316) time: 2.8515 data: 0.0079 max mem: 33370 +Epoch: [35] [ 910/2639] eta: 1:22:43 lr: 7.214834742688602e-06 loss: 0.0311 (0.0316) time: 2.8728 data: 0.0075 max mem: 33370 +Epoch: [35] [ 920/2639] eta: 1:22:14 lr: 7.209548503964639e-06 loss: 0.0317 (0.0316) time: 2.8706 data: 0.0079 max mem: 33370 +Epoch: [35] [ 930/2639] eta: 1:21:47 lr: 7.204261834537175e-06 loss: 0.0303 (0.0316) time: 2.9122 data: 0.0083 max mem: 33370 +Epoch: [35] [ 940/2639] eta: 1:21:21 lr: 7.198974734019895e-06 loss: 0.0265 (0.0316) time: 2.9980 data: 0.0083 max mem: 33370 +Epoch: [35] [ 950/2639] eta: 1:20:57 lr: 7.193687202025797e-06 loss: 0.0262 (0.0315) time: 3.0599 data: 0.0094 max mem: 33370 +Epoch: [35] [ 960/2639] eta: 1:20:30 lr: 7.188399238167236e-06 loss: 0.0262 (0.0316) time: 3.0557 data: 0.0104 max mem: 33370 +Epoch: [35] [ 970/2639] eta: 1:20:05 lr: 7.183110842055882e-06 loss: 0.0286 (0.0316) time: 3.0349 data: 0.0100 max mem: 33370 +Epoch: [35] [ 980/2639] eta: 1:19:37 lr: 7.177822013302753e-06 loss: 0.0286 (0.0316) time: 3.0151 data: 0.0096 max mem: 33370 +Epoch: [35] [ 990/2639] eta: 1:19:10 lr: 7.1725327515182015e-06 loss: 0.0304 (0.0316) time: 2.9704 data: 0.0098 max mem: 33370 +Epoch: [35] [1000/2639] eta: 1:18:43 lr: 7.167243056311887e-06 loss: 0.0306 (0.0316) time: 2.9880 data: 0.0100 max mem: 33370 +Epoch: [35] [1010/2639] eta: 1:18:16 lr: 7.161952927292824e-06 loss: 0.0306 (0.0316) time: 2.9840 data: 0.0095 max mem: 33370 +Epoch: [35] [1020/2639] eta: 1:17:49 lr: 7.156662364069326e-06 loss: 0.0310 (0.0317) time: 2.9882 data: 0.0120 max mem: 33370 +Epoch: [35] [1030/2639] eta: 1:17:23 lr: 7.15137136624906e-06 loss: 0.0332 (0.0317) time: 3.0257 data: 0.0121 max mem: 33370 +Epoch: [35] [1040/2639] eta: 1:16:56 lr: 7.1460799334389875e-06 loss: 0.0332 (0.0317) time: 3.0415 data: 0.0095 max mem: 33370 +Epoch: [35] [1050/2639] eta: 1:16:28 lr: 7.140788065245416e-06 loss: 0.0322 (0.0317) time: 2.9982 data: 0.0092 max mem: 33370 +Epoch: [35] [1060/2639] eta: 1:16:00 lr: 7.135495761273946e-06 loss: 0.0317 (0.0317) time: 2.9425 data: 0.0089 max mem: 33370 +Epoch: [35] [1070/2639] eta: 1:15:34 lr: 7.130203021129524e-06 loss: 0.0308 (0.0317) time: 2.9916 data: 0.0091 max mem: 33370 +Epoch: [35] [1080/2639] eta: 1:15:07 lr: 7.124909844416384e-06 loss: 0.0273 (0.0317) time: 3.0364 data: 0.0098 max mem: 33370 +Epoch: [35] [1090/2639] eta: 1:14:39 lr: 7.1196162307381005e-06 loss: 0.0291 (0.0317) time: 3.0214 data: 0.0095 max mem: 33370 +Epoch: [35] [1100/2639] eta: 1:14:12 lr: 7.114322179697536e-06 loss: 0.0306 (0.0318) time: 2.9937 data: 0.0092 max mem: 33370 +Epoch: [35] [1110/2639] eta: 1:13:44 lr: 7.1090276908968845e-06 loss: 0.0348 (0.0318) time: 2.9752 data: 0.0097 max mem: 33370 +Epoch: [35] [1120/2639] eta: 1:13:16 lr: 7.103732763937627e-06 loss: 0.0322 (0.0318) time: 2.9601 data: 0.0096 max mem: 33370 +Epoch: [35] [1130/2639] eta: 1:12:49 lr: 7.098437398420578e-06 loss: 0.0286 (0.0318) time: 2.9942 data: 0.0094 max mem: 33370 +Epoch: [35] [1140/2639] eta: 1:12:21 lr: 7.093141593945828e-06 loss: 0.0328 (0.0318) time: 3.0298 data: 0.0093 max mem: 33370 +Epoch: [35] [1150/2639] eta: 1:11:54 lr: 7.087845350112797e-06 loss: 0.0323 (0.0318) time: 3.0126 data: 0.0094 max mem: 33370 +Epoch: [35] [1160/2639] eta: 1:11:26 lr: 7.082548666520182e-06 loss: 0.0308 (0.0318) time: 3.0180 data: 0.0094 max mem: 33370 +Epoch: [35] [1170/2639] eta: 1:10:59 lr: 7.077251542766005e-06 loss: 0.0300 (0.0318) time: 3.0148 data: 0.0090 max mem: 33370 +Epoch: [35] [1180/2639] eta: 1:10:31 lr: 7.071953978447561e-06 loss: 0.0259 (0.0318) time: 3.0134 data: 0.0092 max mem: 33370 +Epoch: [35] [1190/2639] eta: 1:10:04 lr: 7.066655973161465e-06 loss: 0.0306 (0.0318) time: 3.0118 data: 0.0094 max mem: 33370 +Epoch: [35] [1200/2639] eta: 1:09:36 lr: 7.061357526503604e-06 loss: 0.0321 (0.0318) time: 2.9926 data: 0.0090 max mem: 33370 +Epoch: [35] [1210/2639] eta: 1:09:07 lr: 7.0560586380691714e-06 loss: 0.0285 (0.0317) time: 2.9444 data: 0.0089 max mem: 33370 +Epoch: [35] [1220/2639] eta: 1:08:39 lr: 7.050759307452655e-06 loss: 0.0262 (0.0317) time: 2.9577 data: 0.0091 max mem: 33370 +Epoch: [35] [1230/2639] eta: 1:08:11 lr: 7.04545953424781e-06 loss: 0.0255 (0.0317) time: 3.0282 data: 0.0095 max mem: 33370 +Epoch: [35] [1240/2639] eta: 1:07:44 lr: 7.040159318047708e-06 loss: 0.0264 (0.0317) time: 3.0674 data: 0.0095 max mem: 33370 +Epoch: [35] [1250/2639] eta: 1:07:17 lr: 7.034858658444676e-06 loss: 0.0301 (0.0316) time: 3.0592 data: 0.0096 max mem: 33370 +Epoch: [35] [1260/2639] eta: 1:06:49 lr: 7.029557555030352e-06 loss: 0.0296 (0.0316) time: 3.0410 data: 0.0095 max mem: 33370 +Epoch: [35] [1270/2639] eta: 1:06:21 lr: 7.024256007395627e-06 loss: 0.0296 (0.0316) time: 3.0186 data: 0.0089 max mem: 33370 +Epoch: [35] [1280/2639] eta: 1:05:53 lr: 7.018954015130702e-06 loss: 0.0309 (0.0316) time: 2.9966 data: 0.0091 max mem: 33370 +Epoch: [35] [1290/2639] eta: 1:05:24 lr: 7.013651577825024e-06 loss: 0.0300 (0.0317) time: 2.9472 data: 0.0104 max mem: 33370 +Epoch: [35] [1300/2639] eta: 1:04:55 lr: 7.008348695067347e-06 loss: 0.0276 (0.0317) time: 2.9084 data: 0.0106 max mem: 33370 +Epoch: [35] [1310/2639] eta: 1:04:27 lr: 7.003045366445669e-06 loss: 0.0323 (0.0317) time: 2.9638 data: 0.0102 max mem: 33370 +Epoch: [35] [1320/2639] eta: 1:03:58 lr: 6.99774159154729e-06 loss: 0.0313 (0.0317) time: 2.9785 data: 0.0097 max mem: 33370 +Epoch: [35] [1330/2639] eta: 1:03:30 lr: 6.992437369958747e-06 loss: 0.0252 (0.0316) time: 2.9817 data: 0.0090 max mem: 33370 +Epoch: [35] [1340/2639] eta: 1:03:01 lr: 6.987132701265881e-06 loss: 0.0279 (0.0317) time: 2.9824 data: 0.0091 max mem: 33370 +Epoch: [35] [1350/2639] eta: 1:02:32 lr: 6.981827585053763e-06 loss: 0.0297 (0.0316) time: 2.9345 data: 0.0092 max mem: 33370 +Epoch: [35] [1360/2639] eta: 1:02:04 lr: 6.976522020906761e-06 loss: 0.0291 (0.0316) time: 2.9449 data: 0.0090 max mem: 33370 +Epoch: [35] [1370/2639] eta: 1:01:35 lr: 6.971216008408481e-06 loss: 0.0291 (0.0316) time: 2.9695 data: 0.0094 max mem: 33370 +Epoch: [35] [1380/2639] eta: 1:01:06 lr: 6.9659095471418065e-06 loss: 0.0282 (0.0316) time: 2.9541 data: 0.0098 max mem: 33370 +Epoch: [35] [1390/2639] eta: 1:00:38 lr: 6.960602636688862e-06 loss: 0.0275 (0.0316) time: 2.9704 data: 0.0094 max mem: 33370 +Epoch: [35] [1400/2639] eta: 1:00:10 lr: 6.955295276631052e-06 loss: 0.0275 (0.0316) time: 3.0285 data: 0.0094 max mem: 33370 +Epoch: [35] [1410/2639] eta: 0:59:41 lr: 6.949987466549008e-06 loss: 0.0250 (0.0316) time: 3.0165 data: 0.0096 max mem: 33370 +Epoch: [35] [1420/2639] eta: 0:59:13 lr: 6.944679206022642e-06 loss: 0.0306 (0.0316) time: 2.9747 data: 0.0095 max mem: 33370 +Epoch: [35] [1430/2639] eta: 0:58:44 lr: 6.9393704946310894e-06 loss: 0.0306 (0.0316) time: 2.9757 data: 0.0097 max mem: 33370 +Epoch: [35] [1440/2639] eta: 0:58:15 lr: 6.934061331952761e-06 loss: 0.0288 (0.0316) time: 2.9453 data: 0.0095 max mem: 33370 +Epoch: [35] [1450/2639] eta: 0:57:46 lr: 6.928751717565289e-06 loss: 0.0290 (0.0316) time: 2.9354 data: 0.0089 max mem: 33370 +Epoch: [35] [1460/2639] eta: 0:57:18 lr: 6.923441651045569e-06 loss: 0.0295 (0.0316) time: 2.9764 data: 0.0089 max mem: 33370 +Epoch: [35] [1470/2639] eta: 0:56:49 lr: 6.918131131969738e-06 loss: 0.0281 (0.0316) time: 3.0035 data: 0.0092 max mem: 33370 +Epoch: [35] [1480/2639] eta: 0:56:20 lr: 6.912820159913158e-06 loss: 0.0281 (0.0316) time: 2.9796 data: 0.0095 max mem: 33370 +Epoch: [35] [1490/2639] eta: 0:55:51 lr: 6.907508734450452e-06 loss: 0.0267 (0.0316) time: 2.9350 data: 0.0094 max mem: 33370 +Epoch: [35] [1500/2639] eta: 0:55:22 lr: 6.902196855155454e-06 loss: 0.0286 (0.0316) time: 2.9150 data: 0.0088 max mem: 33370 +Epoch: [35] [1510/2639] eta: 0:54:53 lr: 6.896884521601263e-06 loss: 0.0298 (0.0316) time: 2.9164 data: 0.0087 max mem: 33370 +Epoch: [35] [1520/2639] eta: 0:54:24 lr: 6.891571733360179e-06 loss: 0.0288 (0.0316) time: 2.9464 data: 0.0089 max mem: 33370 +Epoch: [35] [1530/2639] eta: 0:53:55 lr: 6.88625849000376e-06 loss: 0.0289 (0.0316) time: 2.9223 data: 0.0088 max mem: 33370 +Epoch: [35] [1540/2639] eta: 0:53:26 lr: 6.880944791102772e-06 loss: 0.0281 (0.0316) time: 2.9439 data: 0.0085 max mem: 33370 +Epoch: [35] [1550/2639] eta: 0:52:57 lr: 6.875630636227225e-06 loss: 0.0315 (0.0316) time: 2.9504 data: 0.0085 max mem: 33370 +Epoch: [35] [1560/2639] eta: 0:52:27 lr: 6.870316024946333e-06 loss: 0.0281 (0.0316) time: 2.9021 data: 0.0088 max mem: 33370 +Epoch: [35] [1570/2639] eta: 0:51:59 lr: 6.8650009568285575e-06 loss: 0.0262 (0.0316) time: 3.0068 data: 0.0095 max mem: 33370 +Epoch: [35] [1580/2639] eta: 0:51:30 lr: 6.859685431441554e-06 loss: 0.0292 (0.0316) time: 3.0030 data: 0.0093 max mem: 33370 +Epoch: [35] [1590/2639] eta: 0:51:01 lr: 6.85436944835222e-06 loss: 0.0261 (0.0316) time: 2.9379 data: 0.0087 max mem: 33370 +Epoch: [35] [1600/2639] eta: 0:50:33 lr: 6.849053007126647e-06 loss: 0.0261 (0.0316) time: 2.9874 data: 0.0088 max mem: 33370 +Epoch: [35] [1610/2639] eta: 0:50:04 lr: 6.843736107330165e-06 loss: 0.0266 (0.0316) time: 3.0060 data: 0.0089 max mem: 33370 +Epoch: [35] [1620/2639] eta: 0:49:35 lr: 6.838418748527289e-06 loss: 0.0303 (0.0316) time: 2.9915 data: 0.0089 max mem: 33370 +Epoch: [35] [1630/2639] eta: 0:49:06 lr: 6.83310093028177e-06 loss: 0.0289 (0.0316) time: 2.9576 data: 0.0086 max mem: 33370 +Epoch: [35] [1640/2639] eta: 0:48:37 lr: 6.827782652156545e-06 loss: 0.0289 (0.0316) time: 2.9419 data: 0.0084 max mem: 33370 +Epoch: [35] [1650/2639] eta: 0:48:08 lr: 6.822463913713773e-06 loss: 0.0307 (0.0316) time: 2.9322 data: 0.0089 max mem: 33370 +Epoch: [35] [1660/2639] eta: 0:47:40 lr: 6.8171447145148e-06 loss: 0.0282 (0.0316) time: 2.9919 data: 0.0089 max mem: 33370 +Epoch: [35] [1670/2639] eta: 0:47:11 lr: 6.811825054120197e-06 loss: 0.0282 (0.0316) time: 3.0373 data: 0.0088 max mem: 33370 +Epoch: [35] [1680/2639] eta: 0:46:42 lr: 6.806504932089704e-06 loss: 0.0290 (0.0316) time: 2.9883 data: 0.0087 max mem: 33370 +Epoch: [35] [1690/2639] eta: 0:46:13 lr: 6.801184347982287e-06 loss: 0.0290 (0.0316) time: 2.9658 data: 0.0088 max mem: 33370 +Epoch: [35] [1700/2639] eta: 0:45:44 lr: 6.795863301356081e-06 loss: 0.0259 (0.0315) time: 2.9637 data: 0.0090 max mem: 33370 +Epoch: [35] [1710/2639] eta: 0:45:15 lr: 6.790541791768436e-06 loss: 0.0253 (0.0315) time: 2.9885 data: 0.0086 max mem: 33370 +Epoch: [35] [1720/2639] eta: 0:44:46 lr: 6.785219818775884e-06 loss: 0.0277 (0.0315) time: 3.0027 data: 0.0086 max mem: 33370 +Epoch: [35] [1730/2639] eta: 0:44:17 lr: 6.779897381934136e-06 loss: 0.0283 (0.0315) time: 2.9880 data: 0.0090 max mem: 33370 +Epoch: [35] [1740/2639] eta: 0:43:48 lr: 6.774574480798108e-06 loss: 0.0275 (0.0315) time: 2.9362 data: 0.0091 max mem: 33370 +Epoch: [35] [1750/2639] eta: 0:43:19 lr: 6.769251114921878e-06 loss: 0.0252 (0.0315) time: 2.9440 data: 0.0090 max mem: 33370 +Epoch: [35] [1760/2639] eta: 0:42:50 lr: 6.763927283858728e-06 loss: 0.0274 (0.0315) time: 2.9731 data: 0.0087 max mem: 33370 +Epoch: [35] [1770/2639] eta: 0:42:21 lr: 6.758602987161096e-06 loss: 0.0288 (0.0315) time: 2.9492 data: 0.0086 max mem: 33370 +Epoch: [35] [1780/2639] eta: 0:41:51 lr: 6.753278224380623e-06 loss: 0.0276 (0.0315) time: 2.8880 data: 0.0087 max mem: 33370 +Epoch: [35] [1790/2639] eta: 0:41:22 lr: 6.747952995068099e-06 loss: 0.0270 (0.0315) time: 2.8671 data: 0.0088 max mem: 33370 +Epoch: 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mem: 33370 +Epoch: [35] [1880/2639] eta: 0:37:02 lr: 6.700004862784598e-06 loss: 0.0291 (0.0314) time: 3.0018 data: 0.0089 max mem: 33370 +Epoch: [35] [1890/2639] eta: 0:36:33 lr: 6.694674943262672e-06 loss: 0.0282 (0.0314) time: 3.0133 data: 0.0089 max mem: 33370 +Epoch: [35] [1900/2639] eta: 0:36:04 lr: 6.689344552212441e-06 loss: 0.0319 (0.0314) time: 3.0226 data: 0.0087 max mem: 33370 +Epoch: [35] [1910/2639] eta: 0:35:35 lr: 6.68401368917462e-06 loss: 0.0324 (0.0314) time: 2.9815 data: 0.0090 max mem: 33370 +Epoch: [35] [1920/2639] eta: 0:35:06 lr: 6.6786823536890934e-06 loss: 0.0271 (0.0314) time: 2.9734 data: 0.0096 max mem: 33370 +Epoch: [35] [1930/2639] eta: 0:34:37 lr: 6.673350545294862e-06 loss: 0.0273 (0.0314) time: 3.0252 data: 0.0096 max mem: 33370 +Epoch: [35] [1940/2639] eta: 0:34:08 lr: 6.668018263530092e-06 loss: 0.0293 (0.0314) time: 3.0802 data: 0.0096 max mem: 33370 +Epoch: [35] [1950/2639] eta: 0:33:39 lr: 6.662685507932064e-06 loss: 0.0287 (0.0314) time: 3.0564 data: 0.0093 max mem: 33370 +Epoch: [35] [1960/2639] eta: 0:33:10 lr: 6.657352278037213e-06 loss: 0.0270 (0.0314) time: 3.0346 data: 0.0088 max mem: 33370 +Epoch: [35] [1970/2639] eta: 0:32:41 lr: 6.652018573381107e-06 loss: 0.0291 (0.0314) time: 3.0162 data: 0.0087 max mem: 33370 +Epoch: [35] [1980/2639] eta: 0:32:12 lr: 6.646684393498425e-06 loss: 0.0257 (0.0314) time: 2.9924 data: 0.0088 max mem: 33370 +Epoch: [35] [1990/2639] eta: 0:31:43 lr: 6.641349737923003e-06 loss: 0.0264 (0.0314) time: 2.9932 data: 0.0088 max mem: 33370 +Epoch: [35] [2000/2639] eta: 0:31:14 lr: 6.636014606187775e-06 loss: 0.0271 (0.0314) time: 2.9730 data: 0.0091 max mem: 33370 +Epoch: [35] [2010/2639] eta: 0:30:44 lr: 6.630678997824824e-06 loss: 0.0292 (0.0314) time: 2.9670 data: 0.0092 max mem: 33370 +Epoch: [35] [2020/2639] eta: 0:30:15 lr: 6.625342912365332e-06 loss: 0.0312 (0.0314) time: 2.9703 data: 0.0084 max mem: 33370 +Epoch: [35] [2030/2639] eta: 0:29:46 lr: 6.620006349339622e-06 loss: 0.0347 (0.0314) time: 2.9653 data: 0.0084 max mem: 33370 +Epoch: [35] [2040/2639] eta: 0:29:17 lr: 6.614669308277109e-06 loss: 0.0331 (0.0314) time: 2.9876 data: 0.0091 max mem: 33370 +Epoch: [35] [2050/2639] eta: 0:28:48 lr: 6.609331788706349e-06 loss: 0.0275 (0.0315) time: 3.0120 data: 0.0093 max mem: 33370 +Epoch: [35] [2060/2639] eta: 0:28:19 lr: 6.603993790154983e-06 loss: 0.0317 (0.0315) time: 3.0001 data: 0.0091 max mem: 33370 +Epoch: [35] [2070/2639] eta: 0:27:50 lr: 6.598655312149786e-06 loss: 0.0317 (0.0315) time: 3.0167 data: 0.0090 max mem: 33370 +Epoch: [35] [2080/2639] eta: 0:27:20 lr: 6.593316354216614e-06 loss: 0.0316 (0.0315) time: 3.0235 data: 0.0090 max mem: 33370 +Epoch: [35] [2090/2639] eta: 0:26:51 lr: 6.587976915880452e-06 loss: 0.0316 (0.0315) time: 3.0237 data: 0.0091 max mem: 33370 +Epoch: [35] [2100/2639] eta: 0:26:22 lr: 6.582636996665364e-06 loss: 0.0279 (0.0315) time: 3.0569 data: 0.0093 max mem: 33370 +Epoch: [35] [2110/2639] eta: 0:25:53 lr: 6.577296596094537e-06 loss: 0.0289 (0.0315) time: 3.0795 data: 0.0096 max mem: 33370 +Epoch: [35] [2120/2639] eta: 0:25:24 lr: 6.5719557136902265e-06 loss: 0.0289 (0.0315) time: 3.0533 data: 0.0089 max mem: 33370 +Epoch: [35] [2130/2639] eta: 0:24:55 lr: 6.5666143489738125e-06 loss: 0.0288 (0.0315) time: 3.0781 data: 0.0084 max mem: 33370 +Epoch: [35] [2140/2639] eta: 0:24:26 lr: 6.561272501465737e-06 loss: 0.0309 (0.0315) time: 3.1057 data: 0.0087 max mem: 33370 +Epoch: [35] [2150/2639] eta: 0:23:57 lr: 6.5559301706855564e-06 loss: 0.0288 (0.0315) time: 3.0850 data: 0.0087 max mem: 33370 +Epoch: [35] [2160/2639] eta: 0:23:28 lr: 6.550587356151892e-06 loss: 0.0288 (0.0315) time: 3.0551 data: 0.0087 max mem: 33370 +Epoch: [35] [2170/2639] eta: 0:22:59 lr: 6.54524405738247e-06 loss: 0.0308 (0.0315) time: 2.9965 data: 0.0087 max mem: 33370 +Epoch: [35] [2180/2639] eta: 0:22:29 lr: 6.539900273894074e-06 loss: 0.0291 (0.0315) time: 2.9531 data: 0.0087 max mem: 33370 +Epoch: [35] [2190/2639] eta: 0:22:00 lr: 6.534556005202592e-06 loss: 0.0287 (0.0315) time: 2.9375 data: 0.0091 max mem: 33370 +Epoch: [35] [2200/2639] eta: 0:21:30 lr: 6.5292112508229645e-06 loss: 0.0262 (0.0315) time: 2.9577 data: 0.0091 max mem: 33370 +Epoch: [35] [2210/2639] eta: 0:21:01 lr: 6.523866010269218e-06 loss: 0.0267 (0.0315) time: 3.0204 data: 0.0088 max mem: 33370 +Epoch: [35] [2220/2639] eta: 0:20:32 lr: 6.518520283054458e-06 loss: 0.0281 (0.0315) time: 3.0614 data: 0.0090 max mem: 33370 +Epoch: [35] [2230/2639] eta: 0:20:03 lr: 6.513174068690833e-06 loss: 0.0287 (0.0315) time: 3.0563 data: 0.0088 max mem: 33370 +Epoch: [35] [2240/2639] eta: 0:19:34 lr: 6.507827366689588e-06 loss: 0.0323 (0.0315) time: 3.0540 data: 0.0086 max mem: 33370 +Epoch: [35] [2250/2639] eta: 0:19:04 lr: 6.5024801765609985e-06 loss: 0.0248 (0.0315) time: 3.0344 data: 0.0084 max mem: 33370 +Epoch: [35] [2260/2639] eta: 0:18:35 lr: 6.497132497814433e-06 loss: 0.0253 (0.0315) time: 3.0198 data: 0.0084 max mem: 33370 +Epoch: [35] [2270/2639] eta: 0:18:06 lr: 6.491784329958286e-06 loss: 0.0272 (0.0315) time: 3.0328 data: 0.0088 max mem: 33370 +Epoch: [35] [2280/2639] eta: 0:17:36 lr: 6.486435672500038e-06 loss: 0.0326 (0.0315) time: 3.0308 data: 0.0090 max mem: 33370 +Epoch: [35] [2290/2639] eta: 0:17:07 lr: 6.481086524946191e-06 loss: 0.0333 (0.0315) time: 3.0330 data: 0.0090 max mem: 33370 +Epoch: [35] [2300/2639] eta: 0:16:38 lr: 6.475736886802325e-06 loss: 0.0303 (0.0315) time: 3.0295 data: 0.0086 max mem: 33370 +Epoch: [35] [2310/2639] eta: 0:16:08 lr: 6.470386757573041e-06 loss: 0.0307 (0.0315) time: 3.0227 data: 0.0082 max mem: 33370 +Epoch: [35] [2320/2639] eta: 0:15:39 lr: 6.465036136762011e-06 loss: 0.0340 (0.0315) time: 3.0671 data: 0.0085 max mem: 33370 +Epoch: [35] [2330/2639] eta: 0:15:10 lr: 6.459685023871919e-06 loss: 0.0280 (0.0315) time: 3.0767 data: 0.0084 max mem: 33370 +Epoch: [35] [2340/2639] eta: 0:14:41 lr: 6.454333418404518e-06 loss: 0.0269 (0.0315) time: 3.0702 data: 0.0078 max mem: 33370 +Epoch: [35] [2350/2639] eta: 0:14:11 lr: 6.448981319860565e-06 loss: 0.0288 (0.0315) time: 3.0167 data: 0.0077 max mem: 33370 +Epoch: [35] [2360/2639] eta: 0:13:42 lr: 6.443628727739885e-06 loss: 0.0281 (0.0315) time: 2.9466 data: 0.0072 max mem: 33370 +Epoch: [35] [2370/2639] eta: 0:13:12 lr: 6.4382756415413e-06 loss: 0.0297 (0.0315) time: 2.9278 data: 0.0072 max mem: 33370 +Epoch: [35] [2380/2639] eta: 0:12:43 lr: 6.432922060762686e-06 loss: 0.0320 (0.0315) time: 2.8949 data: 0.0076 max mem: 33370 +Epoch: [35] [2390/2639] eta: 0:12:13 lr: 6.427567984900923e-06 loss: 0.0271 (0.0315) time: 2.9124 data: 0.0077 max mem: 33370 +Epoch: [35] [2400/2639] eta: 0:11:44 lr: 6.422213413451934e-06 loss: 0.0271 (0.0315) time: 2.9071 data: 0.0077 max mem: 33370 +Epoch: [35] [2410/2639] eta: 0:11:14 lr: 6.416858345910638e-06 loss: 0.0299 (0.0315) time: 2.8421 data: 0.0076 max mem: 33370 +Epoch: [35] [2420/2639] eta: 0:10:45 lr: 6.411502781770995e-06 loss: 0.0328 (0.0315) time: 2.8457 data: 0.0076 max mem: 33370 +Epoch: [35] [2430/2639] eta: 0:10:15 lr: 6.406146720525953e-06 loss: 0.0318 (0.0315) time: 2.8548 data: 0.0077 max mem: 33370 +Epoch: [35] [2440/2639] eta: 0:09:45 lr: 6.400790161667497e-06 loss: 0.0281 (0.0315) time: 2.8070 data: 0.0075 max mem: 33370 +Epoch: [35] [2450/2639] eta: 0:09:16 lr: 6.395433104686595e-06 loss: 0.0260 (0.0315) time: 2.8195 data: 0.0072 max mem: 33370 +Epoch: [35] [2460/2639] eta: 0:08:46 lr: 6.390075549073236e-06 loss: 0.0289 (0.0315) time: 2.8580 data: 0.0074 max mem: 33370 +Epoch: [35] [2470/2639] eta: 0:08:17 lr: 6.384717494316415e-06 loss: 0.0309 (0.0315) time: 2.8656 data: 0.0074 max mem: 33370 +Epoch: [35] [2480/2639] eta: 0:07:47 lr: 6.379358939904105e-06 loss: 0.0320 (0.0315) time: 2.8806 data: 0.0073 max mem: 33370 +Epoch: [35] [2490/2639] eta: 0:07:18 lr: 6.3739998853233e-06 loss: 0.0294 (0.0315) time: 2.9110 data: 0.0071 max mem: 33370 +Epoch: [35] [2500/2639] eta: 0:06:49 lr: 6.368640330059967e-06 loss: 0.0283 (0.0315) time: 2.8904 data: 0.0071 max mem: 33370 +Epoch: [35] [2510/2639] eta: 0:06:19 lr: 6.3632802735990815e-06 loss: 0.0294 (0.0315) time: 2.8847 data: 0.0072 max mem: 33370 +Epoch: [35] [2520/2639] eta: 0:05:50 lr: 6.357919715424587e-06 loss: 0.0326 (0.0315) time: 2.8973 data: 0.0074 max mem: 33370 +Epoch: [35] [2530/2639] eta: 0:05:20 lr: 6.352558655019435e-06 loss: 0.0312 (0.0315) time: 2.9056 data: 0.0079 max mem: 33370 +Epoch: [35] [2540/2639] eta: 0:04:51 lr: 6.347197091865533e-06 loss: 0.0270 (0.0315) time: 2.9253 data: 0.0079 max mem: 33370 +Epoch: [35] [2550/2639] eta: 0:04:21 lr: 6.341835025443793e-06 loss: 0.0289 (0.0315) time: 2.9089 data: 0.0076 max mem: 33370 +Epoch: [35] [2560/2639] eta: 0:03:52 lr: 6.336472455234077e-06 loss: 0.0284 (0.0315) time: 2.9168 data: 0.0074 max mem: 33370 +Epoch: [35] [2570/2639] eta: 0:03:22 lr: 6.331109380715247e-06 loss: 0.0265 (0.0315) time: 2.9335 data: 0.0073 max mem: 33370 +Epoch: [35] [2580/2639] eta: 0:02:53 lr: 6.325745801365108e-06 loss: 0.0307 (0.0315) time: 2.9244 data: 0.0071 max mem: 33370 +Epoch: [35] [2590/2639] eta: 0:02:24 lr: 6.320381716660458e-06 loss: 0.0307 (0.0315) time: 2.8853 data: 0.0072 max mem: 33370 +Epoch: [35] [2600/2639] eta: 0:01:54 lr: 6.315017126077032e-06 loss: 0.0293 (0.0315) time: 2.8738 data: 0.0072 max mem: 33370 +Epoch: [35] [2610/2639] eta: 0:01:25 lr: 6.309652029089551e-06 loss: 0.0285 (0.0315) time: 2.9216 data: 0.0073 max mem: 33370 +Epoch: [35] [2620/2639] eta: 0:00:55 lr: 6.30428642517167e-06 loss: 0.0299 (0.0315) time: 2.9448 data: 0.0073 max mem: 33370 +Epoch: [35] [2630/2639] eta: 0:00:26 lr: 6.298920313796022e-06 loss: 0.0316 (0.0315) time: 2.9247 data: 0.0081 max mem: 33370 +Epoch: [35] Total time: 2:09:22 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 3:07:42 time: 4.3770 data: 3.9835 max mem: 33370 +Test: [ 100/2573] eta: 0:04:55 time: 0.0763 data: 0.0013 max mem: 33370 +Test: [ 200/2573] eta: 0:03:55 time: 0.0775 data: 0.0014 max mem: 33370 +Test: [ 300/2573] eta: 0:03:28 time: 0.0804 data: 0.0014 max mem: 33370 +Test: [ 400/2573] eta: 0:03:12 time: 0.0805 data: 0.0014 max mem: 33370 +Test: [ 500/2573] eta: 0:02:59 time: 0.0786 data: 0.0013 max mem: 33370 +Test: [ 600/2573] eta: 0:02:48 time: 0.0784 data: 0.0013 max mem: 33370 +Test: [ 700/2573] eta: 0:02:38 time: 0.0801 data: 0.0014 max mem: 33370 +Test: [ 800/2573] eta: 0:02:29 time: 0.0826 data: 0.0013 max mem: 33370 +Test: [ 900/2573] eta: 0:02:20 time: 0.0796 data: 0.0014 max mem: 33370 +Test: [1000/2573] eta: 0:02:11 time: 0.0785 data: 0.0013 max mem: 33370 +Test: [1100/2573] eta: 0:02:02 time: 0.0795 data: 0.0014 max mem: 33370 +Test: [1200/2573] eta: 0:01:53 time: 0.0801 data: 0.0013 max mem: 33370 +Test: [1300/2573] eta: 0:01:45 time: 0.0793 data: 0.0013 max mem: 33370 +Test: [1400/2573] eta: 0:01:36 time: 0.0775 data: 0.0014 max mem: 33370 +Test: [1500/2573] eta: 0:01:28 time: 0.0802 data: 0.0014 max mem: 33370 +Test: [1600/2573] eta: 0:01:19 time: 0.0832 data: 0.0013 max mem: 33370 +Test: [1700/2573] eta: 0:01:11 time: 0.0784 data: 0.0014 max mem: 33370 +Test: [1800/2573] eta: 0:01:03 time: 0.0820 data: 0.0015 max mem: 33370 +Test: [1900/2573] eta: 0:00:55 time: 0.0787 data: 0.0014 max mem: 33370 +Test: [2000/2573] eta: 0:00:47 time: 0.0804 data: 0.0014 max mem: 33370 +Test: [2100/2573] eta: 0:00:38 time: 0.0810 data: 0.0014 max mem: 33370 +Test: [2200/2573] eta: 0:00:30 time: 0.0818 data: 0.0014 max mem: 33370 +Test: [2300/2573] eta: 0:00:22 time: 0.0812 data: 0.0013 max mem: 33370 +Test: [2400/2573] eta: 0:00:14 time: 0.0761 data: 0.0015 max mem: 33370 +Test: [2500/2573] eta: 0:00:05 time: 0.0798 data: 0.0013 max mem: 33370 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: Total time: 0:03:31 +Final results: +Mean IoU is 64.75 + + precision@0.5 = 72.69 + precision@0.6 = 67.83 + precision@0.7 = 61.40 + precision@0.8 = 50.39 + precision@0.9 = 26.29 + overall IoU = 61.81 + +Average object IoU 64.74849851607021 +Overall IoU 61.81315231323242 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [36] [ 0/2639] eta: 4:02:07 lr: 6.294090379244818e-06 loss: 0.0354 (0.0354) time: 5.5051 data: 2.5653 max mem: 33370 +Epoch: [36] [ 10/2639] eta: 2:17:35 lr: 6.2887233022427135e-06 loss: 0.0273 (0.0303) time: 3.1402 data: 0.2402 max mem: 33370 +Epoch: [36] [ 20/2639] eta: 2:13:19 lr: 6.2833557162475044e-06 loss: 0.0273 (0.0309) time: 2.9317 data: 0.0074 max mem: 33370 +Epoch: [36] [ 30/2639] eta: 2:10:54 lr: 6.2779876207276964e-06 loss: 0.0288 (0.0306) time: 2.9389 data: 0.0078 max mem: 33370 +Epoch: [36] [ 40/2639] eta: 2:09:04 lr: 6.272619015150753e-06 loss: 0.0282 (0.0304) time: 2.9013 data: 0.0081 max mem: 33370 +Epoch: [36] [ 50/2639] eta: 2:07:47 lr: 6.267249898983057e-06 loss: 0.0286 (0.0312) time: 2.8861 data: 0.0077 max mem: 33370 +Epoch: [36] [ 60/2639] eta: 2:06:21 lr: 6.261880271689942e-06 loss: 0.0305 (0.0313) time: 2.8582 data: 0.0075 max mem: 33370 +Epoch: [36] [ 70/2639] eta: 2:05:36 lr: 6.256510132735653e-06 loss: 0.0292 (0.0318) time: 2.8624 data: 0.0077 max mem: 33370 +Epoch: [36] [ 80/2639] eta: 2:05:14 lr: 6.251139481583375e-06 loss: 0.0300 (0.0326) time: 2.9272 data: 0.0082 max mem: 33370 +Epoch: [36] [ 90/2639] eta: 2:04:59 lr: 6.24576831769522e-06 loss: 0.0323 (0.0324) time: 2.9718 data: 0.0078 max mem: 33370 +Epoch: [36] [ 100/2639] eta: 2:04:22 lr: 6.240396640532202e-06 loss: 0.0293 (0.0321) time: 2.9492 data: 0.0074 max mem: 33370 +Epoch: [36] [ 110/2639] eta: 2:03:59 lr: 6.235024449554276e-06 loss: 0.0286 (0.0318) time: 2.9402 data: 0.0079 max mem: 33370 +Epoch: [36] [ 120/2639] eta: 2:03:20 lr: 6.229651744220288e-06 loss: 0.0272 (0.0315) time: 2.9312 data: 0.0077 max mem: 33370 +Epoch: [36] [ 130/2639] eta: 2:02:37 lr: 6.2242785239880165e-06 loss: 0.0264 (0.0312) time: 2.8813 data: 0.0074 max mem: 33370 +Epoch: [36] [ 140/2639] eta: 2:01:55 lr: 6.218904788314126e-06 loss: 0.0264 (0.0309) time: 2.8636 data: 0.0073 max mem: 33370 +Epoch: [36] [ 150/2639] eta: 2:01:25 lr: 6.213530536654209e-06 loss: 0.0256 (0.0305) time: 2.8927 data: 0.0077 max mem: 33370 +Epoch: [36] [ 160/2639] eta: 2:00:44 lr: 6.2081557684627356e-06 loss: 0.0274 (0.0307) time: 2.8875 data: 0.0080 max mem: 33370 +Epoch: [36] [ 170/2639] eta: 2:00:08 lr: 6.202780483193095e-06 loss: 0.0274 (0.0304) time: 2.8633 data: 0.0077 max mem: 33370 +Epoch: [36] [ 180/2639] eta: 1:59:34 lr: 6.197404680297551e-06 loss: 0.0254 (0.0304) time: 2.8805 data: 0.0076 max mem: 33370 +Epoch: [36] [ 190/2639] eta: 1:58:56 lr: 6.192028359227281e-06 loss: 0.0292 (0.0305) time: 2.8649 data: 0.0077 max mem: 33370 +Epoch: [36] [ 200/2639] eta: 1:58:29 lr: 6.186651519432324e-06 loss: 0.0294 (0.0304) time: 2.8909 data: 0.0080 max mem: 33370 +Epoch: [36] [ 210/2639] eta: 1:57:57 lr: 6.181274160361632e-06 loss: 0.0282 (0.0304) time: 2.9120 data: 0.0081 max mem: 33370 +Epoch: [36] [ 220/2639] eta: 1:57:24 lr: 6.175896281463011e-06 loss: 0.0317 (0.0306) time: 2.8836 data: 0.0075 max mem: 33370 +Epoch: [36] [ 230/2639] eta: 1:56:56 lr: 6.170517882183171e-06 loss: 0.0328 (0.0328) time: 2.9021 data: 0.0074 max mem: 33370 +Epoch: [36] [ 240/2639] eta: 1:56:32 lr: 6.165138961967671e-06 loss: 0.0313 (0.0329) time: 2.9424 data: 0.0077 max mem: 33370 +Epoch: [36] [ 250/2639] eta: 1:56:01 lr: 6.159759520260965e-06 loss: 0.0313 (0.0329) time: 2.9276 data: 0.0075 max mem: 33370 +Epoch: [36] [ 260/2639] eta: 1:55:32 lr: 6.154379556506354e-06 loss: 0.0315 (0.0328) time: 2.9059 data: 0.0077 max mem: 33370 +Epoch: [36] [ 270/2639] eta: 1:54:56 lr: 6.148999070146023e-06 loss: 0.0300 (0.0327) time: 2.8781 data: 0.0078 max mem: 33370 +Epoch: [36] [ 280/2639] eta: 1:54:29 lr: 6.143618060620997e-06 loss: 0.0296 (0.0325) time: 2.8849 data: 0.0075 max mem: 33370 +Epoch: [36] [ 290/2639] eta: 1:53:59 lr: 6.138236527371182e-06 loss: 0.0310 (0.0326) time: 2.9140 data: 0.0076 max mem: 33370 +Epoch: [36] [ 300/2639] eta: 1:53:30 lr: 6.132854469835311e-06 loss: 0.0311 (0.0325) time: 2.9075 data: 0.0075 max mem: 33370 +Epoch: [36] [ 310/2639] eta: 1:52:54 lr: 6.127471887450998e-06 loss: 0.0267 (0.0323) time: 2.8687 data: 0.0075 max mem: 33370 +Epoch: [36] [ 320/2639] eta: 1:52:27 lr: 6.122088779654675e-06 loss: 0.0275 (0.0322) time: 2.8795 data: 0.0077 max mem: 33370 +Epoch: [36] [ 330/2639] eta: 1:52:02 lr: 6.116705145881636e-06 loss: 0.0289 (0.0322) time: 2.9562 data: 0.0078 max mem: 33370 +Epoch: [36] [ 340/2639] eta: 1:51:33 lr: 6.111320985566017e-06 loss: 0.0284 (0.0321) time: 2.9377 data: 0.0076 max mem: 33370 +Epoch: [36] [ 350/2639] eta: 1:51:01 lr: 6.105936298140772e-06 loss: 0.0271 (0.0320) time: 2.8903 data: 0.0077 max mem: 33370 +Epoch: [36] [ 360/2639] eta: 1:50:39 lr: 6.100551083037712e-06 loss: 0.0303 (0.0321) time: 2.9467 data: 0.0076 max mem: 33370 +Epoch: [36] [ 370/2639] eta: 1:50:08 lr: 6.095165339687453e-06 loss: 0.0297 (0.0321) time: 2.9526 data: 0.0074 max mem: 33370 +Epoch: [36] [ 380/2639] eta: 1:49:36 lr: 6.0897790675194625e-06 loss: 0.0263 (0.0320) time: 2.8737 data: 0.0084 max mem: 33370 +Epoch: [36] [ 390/2639] eta: 1:49:07 lr: 6.084392265962004e-06 loss: 0.0283 (0.0320) time: 2.8839 data: 0.0086 max mem: 33370 +Epoch: [36] [ 400/2639] eta: 1:48:48 lr: 6.079004934442187e-06 loss: 0.0267 (0.0319) time: 3.0015 data: 0.0081 max mem: 33370 +Epoch: [36] [ 410/2639] eta: 1:48:25 lr: 6.073617072385908e-06 loss: 0.0267 (0.0319) time: 3.0641 data: 0.0083 max mem: 33370 +Epoch: [36] [ 420/2639] eta: 1:48:01 lr: 6.068228679217904e-06 loss: 0.0253 (0.0318) time: 3.0219 data: 0.0084 max mem: 33370 +Epoch: [36] [ 430/2639] eta: 1:47:40 lr: 6.0628397543616905e-06 loss: 0.0256 (0.0319) time: 3.0425 data: 0.0082 max mem: 33370 +Epoch: [36] [ 440/2639] eta: 1:47:11 lr: 6.057450297239617e-06 loss: 0.0271 (0.0318) time: 3.0106 data: 0.0083 max mem: 33370 +Epoch: [36] [ 450/2639] eta: 1:46:41 lr: 6.052060307272806e-06 loss: 0.0265 (0.0318) time: 2.9292 data: 0.0081 max mem: 33370 +Epoch: [36] [ 460/2639] eta: 1:46:12 lr: 6.0466697838812e-06 loss: 0.0269 (0.0318) time: 2.9186 data: 0.0080 max mem: 33370 +Epoch: [36] [ 470/2639] eta: 1:45:49 lr: 6.041278726483515e-06 loss: 0.0292 (0.0318) time: 2.9932 data: 0.0081 max mem: 33370 +Epoch: [36] [ 480/2639] eta: 1:45:26 lr: 6.035887134497278e-06 loss: 0.0292 (0.0317) time: 3.0643 data: 0.0079 max mem: 33370 +Epoch: [36] [ 490/2639] eta: 1:45:01 lr: 6.030495007338776e-06 loss: 0.0289 (0.0317) time: 3.0430 data: 0.0079 max mem: 33370 +Epoch: [36] [ 500/2639] eta: 1:44:34 lr: 6.025102344423107e-06 loss: 0.0293 (0.0316) time: 3.0022 data: 0.0083 max mem: 33370 +Epoch: [36] [ 510/2639] eta: 1:44:06 lr: 6.019709145164117e-06 loss: 0.0288 (0.0316) time: 2.9833 data: 0.0081 max mem: 33370 +Epoch: [36] [ 520/2639] eta: 1:43:42 lr: 6.014315408974455e-06 loss: 0.0298 (0.0316) time: 3.0210 data: 0.0077 max mem: 33370 +Epoch: [36] [ 530/2639] eta: 1:43:16 lr: 6.008921135265517e-06 loss: 0.0298 (0.0316) time: 3.0422 data: 0.0080 max mem: 33370 +Epoch: [36] [ 540/2639] eta: 1:42:47 lr: 6.0035263234474884e-06 loss: 0.0304 (0.0315) time: 2.9887 data: 0.0083 max mem: 33370 +Epoch: [36] [ 550/2639] eta: 1:42:17 lr: 5.998130972929293e-06 loss: 0.0304 (0.0316) time: 2.9272 data: 0.0087 max mem: 33370 +Epoch: [36] [ 560/2639] eta: 1:41:51 lr: 5.992735083118639e-06 loss: 0.0304 (0.0316) time: 2.9675 data: 0.0092 max mem: 33370 +Epoch: [36] [ 570/2639] eta: 1:41:21 lr: 5.987338653421968e-06 loss: 0.0310 (0.0316) time: 2.9814 data: 0.0086 max mem: 33370 +Epoch: [36] [ 580/2639] eta: 1:40:49 lr: 5.981941683244487e-06 loss: 0.0298 (0.0316) time: 2.8935 data: 0.0078 max mem: 33370 +Epoch: [36] [ 590/2639] eta: 1:40:17 lr: 5.976544171990153e-06 loss: 0.0263 (0.0315) time: 2.8607 data: 0.0080 max mem: 33370 +Epoch: [36] [ 600/2639] eta: 1:39:50 lr: 5.971146119061651e-06 loss: 0.0268 (0.0314) time: 2.9406 data: 0.0083 max mem: 33370 +Epoch: [36] [ 610/2639] eta: 1:39:27 lr: 5.965747523860426e-06 loss: 0.0282 (0.0314) time: 3.0643 data: 0.0083 max mem: 33370 +Epoch: [36] [ 620/2639] eta: 1:39:02 lr: 5.960348385786636e-06 loss: 0.0269 (0.0313) time: 3.1063 data: 0.0081 max mem: 33370 +Epoch: [36] [ 630/2639] eta: 1:38:37 lr: 5.954948704239198e-06 loss: 0.0251 (0.0313) time: 3.0789 data: 0.0081 max mem: 33370 +Epoch: [36] [ 640/2639] eta: 1:38:10 lr: 5.94954847861573e-06 loss: 0.0258 (0.0313) time: 3.0402 data: 0.0081 max mem: 33370 +Epoch: [36] [ 650/2639] eta: 1:37:42 lr: 5.944147708312598e-06 loss: 0.0292 (0.0313) time: 3.0233 data: 0.0081 max mem: 33370 +Epoch: [36] [ 660/2639] eta: 1:37:16 lr: 5.938746392724866e-06 loss: 0.0292 (0.0313) time: 3.0354 data: 0.0081 max mem: 33370 +Epoch: [36] [ 670/2639] eta: 1:36:48 lr: 5.933344531246339e-06 loss: 0.0284 (0.0313) time: 3.0268 data: 0.0079 max mem: 33370 +Epoch: [36] [ 680/2639] eta: 1:36:21 lr: 5.927942123269504e-06 loss: 0.0333 (0.0314) time: 3.0111 data: 0.0078 max mem: 33370 +Epoch: [36] [ 690/2639] eta: 1:35:53 lr: 5.922539168185588e-06 loss: 0.0294 (0.0313) time: 3.0154 data: 0.0077 max mem: 33370 +Epoch: [36] [ 700/2639] eta: 1:35:26 lr: 5.9171356653844926e-06 loss: 0.0287 (0.0313) time: 3.0305 data: 0.0078 max mem: 33370 +Epoch: [36] [ 710/2639] eta: 1:35:00 lr: 5.911731614254846e-06 loss: 0.0287 (0.0313) time: 3.0590 data: 0.0080 max mem: 33370 +Epoch: [36] [ 720/2639] eta: 1:34:34 lr: 5.906327014183947e-06 loss: 0.0288 (0.0313) time: 3.0796 data: 0.0082 max mem: 33370 +Epoch: [36] [ 730/2639] eta: 1:34:07 lr: 5.900921864557811e-06 loss: 0.0338 (0.0315) time: 3.0738 data: 0.0087 max mem: 33370 +Epoch: [36] [ 740/2639] eta: 1:33:41 lr: 5.8955161647611145e-06 loss: 0.0329 (0.0314) time: 3.0800 data: 0.0086 max mem: 33370 +Epoch: [36] [ 750/2639] eta: 1:33:13 lr: 5.890109914177246e-06 loss: 0.0294 (0.0314) time: 3.0758 data: 0.0081 max mem: 33370 +Epoch: [36] [ 760/2639] eta: 1:32:45 lr: 5.884703112188243e-06 loss: 0.0282 (0.0314) time: 3.0303 data: 0.0081 max mem: 33370 +Epoch: [36] [ 770/2639] eta: 1:32:17 lr: 5.879295758174849e-06 loss: 0.0271 (0.0314) time: 3.0249 data: 0.0084 max mem: 33370 +Epoch: [36] [ 780/2639] eta: 1:31:47 lr: 5.8738878515164486e-06 loss: 0.0280 (0.0313) time: 2.9933 data: 0.0085 max mem: 33370 +Epoch: [36] [ 790/2639] eta: 1:31:19 lr: 5.868479391591121e-06 loss: 0.0287 (0.0314) time: 2.9753 data: 0.0084 max mem: 33370 +Epoch: [36] [ 800/2639] eta: 1:30:50 lr: 5.863070377775582e-06 loss: 0.0259 (0.0313) time: 3.0026 data: 0.0084 max mem: 33370 +Epoch: [36] [ 810/2639] eta: 1:30:21 lr: 5.857660809445229e-06 loss: 0.0237 (0.0313) time: 2.9945 data: 0.0083 max mem: 33370 +Epoch: [36] [ 820/2639] eta: 1:29:51 lr: 5.85225068597409e-06 loss: 0.0288 (0.0313) time: 2.9805 data: 0.0083 max mem: 33370 +Epoch: [36] [ 830/2639] eta: 1:29:24 lr: 5.846840006734862e-06 loss: 0.0280 (0.0313) time: 3.0147 data: 0.0082 max mem: 33370 +Epoch: [36] [ 840/2639] eta: 1:28:59 lr: 5.841428771098888e-06 loss: 0.0249 (0.0313) time: 3.1183 data: 0.0082 max mem: 33370 +Epoch: [36] [ 850/2639] eta: 1:28:31 lr: 5.836016978436128e-06 loss: 0.0292 (0.0314) time: 3.1304 data: 0.0088 max mem: 33370 +Epoch: [36] [ 860/2639] eta: 1:28:06 lr: 5.83060462811521e-06 loss: 0.0326 (0.0313) time: 3.1221 data: 0.0090 max mem: 33370 +Epoch: [36] [ 870/2639] eta: 1:27:38 lr: 5.825191719503365e-06 loss: 0.0306 (0.0313) time: 3.1070 data: 0.0086 max mem: 33370 +Epoch: [36] [ 880/2639] eta: 1:27:07 lr: 5.8197782519664796e-06 loss: 0.0264 (0.0313) time: 3.0004 data: 0.0086 max mem: 33370 +Epoch: [36] [ 890/2639] eta: 1:26:36 lr: 5.814364224869038e-06 loss: 0.0274 (0.0313) time: 2.9221 data: 0.0088 max mem: 33370 +Epoch: [36] [ 900/2639] eta: 1:26:05 lr: 5.808949637574167e-06 loss: 0.0276 (0.0313) time: 2.8984 data: 0.0084 max mem: 33370 +Epoch: [36] [ 910/2639] eta: 1:25:35 lr: 5.8035344894435866e-06 loss: 0.0260 (0.0312) time: 2.9163 data: 0.0082 max mem: 33370 +Epoch: [36] [ 920/2639] eta: 1:25:03 lr: 5.798118779837648e-06 loss: 0.0240 (0.0312) time: 2.9052 data: 0.0083 max mem: 33370 +Epoch: [36] [ 930/2639] eta: 1:24:32 lr: 5.792702508115286e-06 loss: 0.0275 (0.0312) time: 2.8856 data: 0.0085 max mem: 33370 +Epoch: [36] [ 940/2639] eta: 1:24:01 lr: 5.787285673634061e-06 loss: 0.0306 (0.0312) time: 2.9030 data: 0.0084 max mem: 33370 +Epoch: [36] [ 950/2639] eta: 1:23:32 lr: 5.781868275750105e-06 loss: 0.0288 (0.0312) time: 2.9325 data: 0.0083 max mem: 33370 +Epoch: [36] [ 960/2639] eta: 1:23:03 lr: 5.776450313818166e-06 loss: 0.0292 (0.0312) time: 2.9819 data: 0.0083 max mem: 33370 +Epoch: [36] [ 970/2639] eta: 1:22:34 lr: 5.771031787191557e-06 loss: 0.0298 (0.0312) time: 3.0110 data: 0.0080 max mem: 33370 +Epoch: [36] [ 980/2639] eta: 1:22:05 lr: 5.7656126952221965e-06 loss: 0.0312 (0.0312) time: 3.0141 data: 0.0084 max mem: 33370 +Epoch: [36] [ 990/2639] eta: 1:21:35 lr: 5.760193037260559e-06 loss: 0.0312 (0.0312) time: 2.9980 data: 0.0086 max mem: 33370 +Epoch: [36] [1000/2639] eta: 1:21:06 lr: 5.754772812655717e-06 loss: 0.0279 (0.0312) time: 2.9860 data: 0.0083 max mem: 33370 +Epoch: [36] [1010/2639] eta: 1:20:35 lr: 5.749352020755286e-06 loss: 0.0273 (0.0312) time: 2.9398 data: 0.0083 max mem: 33370 +Epoch: [36] [1020/2639] eta: 1:20:05 lr: 5.743930660905473e-06 loss: 0.0287 (0.0312) time: 2.9253 data: 0.0086 max mem: 33370 +Epoch: [36] [1030/2639] eta: 1:19:36 lr: 5.73850873245102e-06 loss: 0.0287 (0.0311) time: 2.9700 data: 0.0086 max mem: 33370 +Epoch: [36] [1040/2639] eta: 1:19:06 lr: 5.733086234735247e-06 loss: 0.0293 (0.0311) time: 2.9888 data: 0.0086 max mem: 33370 +Epoch: [36] [1050/2639] eta: 1:18:38 lr: 5.727663167100002e-06 loss: 0.0298 (0.0311) time: 3.0279 data: 0.0085 max mem: 33370 +Epoch: [36] [1060/2639] eta: 1:18:10 lr: 5.722239528885696e-06 loss: 0.0295 (0.0311) time: 3.0612 data: 0.0085 max mem: 33370 +Epoch: [36] [1070/2639] eta: 1:17:40 lr: 5.716815319431282e-06 loss: 0.0304 (0.0311) time: 3.0278 data: 0.0082 max mem: 33370 +Epoch: [36] [1080/2639] eta: 1:17:12 lr: 5.711390538074232e-06 loss: 0.0304 (0.0312) time: 3.0158 data: 0.0082 max mem: 33370 +Epoch: [36] [1090/2639] eta: 1:16:43 lr: 5.70596518415057e-06 loss: 0.0281 (0.0311) time: 3.0507 data: 0.0083 max mem: 33370 +Epoch: [36] [1100/2639] eta: 1:16:15 lr: 5.7005392569948275e-06 loss: 0.0251 (0.0311) time: 3.0555 data: 0.0081 max mem: 33370 +Epoch: [36] [1110/2639] eta: 1:15:46 lr: 5.695112755940079e-06 loss: 0.0292 (0.0311) time: 3.0471 data: 0.0079 max mem: 33370 +Epoch: [36] [1120/2639] eta: 1:15:17 lr: 5.689685680317891e-06 loss: 0.0292 (0.0311) time: 3.0257 data: 0.0084 max mem: 33370 +Epoch: [36] [1130/2639] eta: 1:14:47 lr: 5.684258029458369e-06 loss: 0.0261 (0.0311) time: 3.0009 data: 0.0085 max mem: 33370 +Epoch: [36] [1140/2639] eta: 1:14:19 lr: 5.678829802690102e-06 loss: 0.0299 (0.0311) time: 3.0339 data: 0.0088 max mem: 33370 +Epoch: [36] [1150/2639] eta: 1:13:50 lr: 5.673400999340202e-06 loss: 0.0266 (0.0310) time: 3.0646 data: 0.0090 max mem: 33370 +Epoch: [36] [1160/2639] eta: 1:13:21 lr: 5.6679716187342555e-06 loss: 0.0295 (0.0311) time: 3.0319 data: 0.0087 max mem: 33370 +Epoch: [36] [1170/2639] eta: 1:12:53 lr: 5.6625416601963705e-06 loss: 0.0312 (0.0311) time: 3.0565 data: 0.0092 max mem: 33370 +Epoch: [36] [1180/2639] eta: 1:12:24 lr: 5.6571111230491095e-06 loss: 0.0308 (0.0311) time: 3.0890 data: 0.0087 max mem: 33370 +Epoch: [36] [1190/2639] eta: 1:11:54 lr: 5.65168000661355e-06 loss: 0.0283 (0.0310) time: 3.0243 data: 0.0081 max mem: 33370 +Epoch: [36] [1200/2639] eta: 1:11:25 lr: 5.6462483102092175e-06 loss: 0.0280 (0.0310) time: 2.9986 data: 0.0089 max mem: 33370 +Epoch: [36] [1210/2639] eta: 1:10:56 lr: 5.640816033154136e-06 loss: 0.0314 (0.0311) time: 3.0165 data: 0.0090 max mem: 33370 +Epoch: [36] [1220/2639] eta: 1:10:26 lr: 5.635383174764773e-06 loss: 0.0316 (0.0311) time: 3.0041 data: 0.0085 max mem: 33370 +Epoch: [36] [1230/2639] eta: 1:09:57 lr: 5.629949734356082e-06 loss: 0.0295 (0.0311) time: 3.0319 data: 0.0081 max mem: 33370 +Epoch: [36] [1240/2639] eta: 1:09:27 lr: 5.6245157112414485e-06 loss: 0.0278 (0.0311) time: 3.0223 data: 0.0078 max mem: 33370 +Epoch: [36] [1250/2639] eta: 1:08:58 lr: 5.619081104732737e-06 loss: 0.0270 (0.0310) time: 3.0110 data: 0.0085 max mem: 33370 +Epoch: [36] [1260/2639] eta: 1:08:29 lr: 5.613645914140232e-06 loss: 0.0265 (0.0310) time: 3.0520 data: 0.0092 max mem: 33370 +Epoch: [36] [1270/2639] eta: 1:08:00 lr: 5.608210138772684e-06 loss: 0.0273 (0.0310) time: 3.0528 data: 0.0086 max mem: 33370 +Epoch: [36] [1280/2639] eta: 1:07:31 lr: 5.602773777937257e-06 loss: 0.0277 (0.0311) time: 3.0219 data: 0.0081 max mem: 33370 +Epoch: [36] [1290/2639] eta: 1:07:02 lr: 5.59733683093957e-06 loss: 0.0304 (0.0312) time: 3.0252 data: 0.0086 max mem: 33370 +Epoch: [36] [1300/2639] eta: 1:06:32 lr: 5.591899297083644e-06 loss: 0.0307 (0.0312) time: 3.0318 data: 0.0089 max mem: 33370 +Epoch: [36] [1310/2639] eta: 1:06:03 lr: 5.586461175671938e-06 loss: 0.0273 (0.0312) time: 3.0506 data: 0.0087 max mem: 33370 +Epoch: [36] [1320/2639] eta: 1:05:34 lr: 5.581022466005328e-06 loss: 0.0278 (0.0312) time: 3.0605 data: 0.0083 max mem: 33370 +Epoch: [36] [1330/2639] eta: 1:05:05 lr: 5.575583167383081e-06 loss: 0.0286 (0.0312) time: 3.0269 data: 0.0082 max mem: 33370 +Epoch: [36] [1340/2639] eta: 1:04:35 lr: 5.570143279102892e-06 loss: 0.0295 (0.0312) time: 3.0370 data: 0.0082 max mem: 33370 +Epoch: [36] [1350/2639] eta: 1:04:06 lr: 5.564702800460833e-06 loss: 0.0281 (0.0312) time: 3.0646 data: 0.0084 max mem: 33370 +Epoch: [36] [1360/2639] eta: 1:03:37 lr: 5.559261730751394e-06 loss: 0.0281 (0.0312) time: 3.0554 data: 0.0082 max mem: 33370 +Epoch: [36] [1370/2639] eta: 1:03:08 lr: 5.553820069267428e-06 loss: 0.0265 (0.0312) time: 3.0326 data: 0.0084 max mem: 33370 +Epoch: [36] [1380/2639] eta: 1:02:38 lr: 5.548377815300197e-06 loss: 0.0300 (0.0312) time: 3.0280 data: 0.0086 max mem: 33370 +Epoch: [36] [1390/2639] eta: 1:02:09 lr: 5.542934968139315e-06 loss: 0.0316 (0.0312) time: 3.0408 data: 0.0085 max mem: 33370 +Epoch: [36] [1400/2639] eta: 1:01:40 lr: 5.537491527072792e-06 loss: 0.0291 (0.0311) time: 3.0640 data: 0.0087 max mem: 33370 +Epoch: [36] [1410/2639] eta: 1:01:11 lr: 5.532047491386984e-06 loss: 0.0291 (0.0312) time: 3.0796 data: 0.0087 max mem: 33370 +Epoch: [36] [1420/2639] eta: 1:00:42 lr: 5.526602860366629e-06 loss: 0.0323 (0.0312) time: 3.0770 data: 0.0084 max mem: 33370 +Epoch: [36] [1430/2639] eta: 1:00:13 lr: 5.5211576332947985e-06 loss: 0.0315 (0.0312) time: 3.0983 data: 0.0086 max mem: 33370 +Epoch: [36] [1440/2639] eta: 0:59:44 lr: 5.515711809452935e-06 loss: 0.0328 (0.0312) time: 3.1011 data: 0.0087 max mem: 33370 +Epoch: [36] [1450/2639] eta: 0:59:15 lr: 5.5102653881208045e-06 loss: 0.0305 (0.0312) time: 3.0781 data: 0.0088 max mem: 33370 +Epoch: [36] [1460/2639] eta: 0:58:46 lr: 5.5048183685765354e-06 loss: 0.0266 (0.0312) time: 3.0937 data: 0.0094 max mem: 33370 +Epoch: [36] [1470/2639] eta: 0:58:17 lr: 5.499370750096564e-06 loss: 0.0261 (0.0312) time: 3.1213 data: 0.0093 max mem: 33370 +Epoch: [36] [1480/2639] eta: 0:57:48 lr: 5.493922531955678e-06 loss: 0.0284 (0.0312) time: 3.1170 data: 0.0087 max mem: 33370 +Epoch: [36] [1490/2639] eta: 0:57:18 lr: 5.488473713426964e-06 loss: 0.0305 (0.0312) time: 3.0692 data: 0.0090 max mem: 33370 +Epoch: [36] [1500/2639] eta: 0:56:49 lr: 5.483024293781848e-06 loss: 0.0293 (0.0312) time: 3.0810 data: 0.0095 max mem: 33370 +Epoch: [36] [1510/2639] eta: 0:56:21 lr: 5.47757427229004e-06 loss: 0.0284 (0.0312) time: 3.1485 data: 0.0093 max mem: 33370 +Epoch: [36] [1520/2639] eta: 0:55:52 lr: 5.472123648219583e-06 loss: 0.0286 (0.0312) time: 3.1424 data: 0.0089 max mem: 33370 +Epoch: [36] [1530/2639] eta: 0:55:22 lr: 5.466672420836792e-06 loss: 0.0294 (0.0312) time: 3.1037 data: 0.0086 max mem: 33370 +Epoch: [36] [1540/2639] eta: 0:54:53 lr: 5.461220589406298e-06 loss: 0.0295 (0.0312) time: 3.1106 data: 0.0085 max mem: 33370 +Epoch: [36] [1550/2639] eta: 0:54:25 lr: 5.455768153190995e-06 loss: 0.0279 (0.0311) time: 3.1544 data: 0.0089 max mem: 33370 +Epoch: [36] [1560/2639] eta: 0:53:55 lr: 5.450315111452078e-06 loss: 0.0274 (0.0311) time: 3.1414 data: 0.0090 max mem: 33370 +Epoch: [36] [1570/2639] eta: 0:53:26 lr: 5.444861463449016e-06 loss: 0.0274 (0.0311) time: 3.0774 data: 0.0088 max mem: 33370 +Epoch: [36] [1580/2639] eta: 0:52:56 lr: 5.439407208439527e-06 loss: 0.0288 (0.0311) time: 3.0119 data: 0.0090 max mem: 33370 +Epoch: [36] [1590/2639] eta: 0:52:26 lr: 5.4339523456796205e-06 loss: 0.0289 (0.0311) time: 2.9951 data: 0.0091 max mem: 33370 +Epoch: [36] [1600/2639] eta: 0:51:56 lr: 5.4284968744235335e-06 loss: 0.0257 (0.0311) time: 3.0607 data: 0.0090 max mem: 33370 +Epoch: [36] [1610/2639] eta: 0:51:27 lr: 5.423040793923784e-06 loss: 0.0235 (0.0311) time: 3.0993 data: 0.0088 max mem: 33370 +Epoch: [36] [1620/2639] eta: 0:50:58 lr: 5.417584103431106e-06 loss: 0.0259 (0.0310) time: 3.0858 data: 0.0087 max mem: 33370 +Epoch: [36] [1630/2639] eta: 0:50:28 lr: 5.4121268021945e-06 loss: 0.0300 (0.0311) time: 3.0727 data: 0.0086 max mem: 33370 +Epoch: [36] [1640/2639] eta: 0:49:59 lr: 5.4066688894611725e-06 loss: 0.0300 (0.0311) time: 3.0963 data: 0.0087 max mem: 33370 +Epoch: [36] [1650/2639] eta: 0:49:29 lr: 5.401210364476584e-06 loss: 0.0264 (0.0311) time: 3.1080 data: 0.0088 max mem: 33370 +Epoch: [36] [1660/2639] eta: 0:49:00 lr: 5.395751226484388e-06 loss: 0.0232 (0.0310) time: 3.0823 data: 0.0088 max mem: 33370 +Epoch: [36] [1670/2639] eta: 0:48:29 lr: 5.390291474726478e-06 loss: 0.0282 (0.0310) time: 3.0290 data: 0.0089 max mem: 33370 +Epoch: [36] [1680/2639] eta: 0:48:00 lr: 5.384831108442932e-06 loss: 0.0282 (0.0310) time: 3.0426 data: 0.0091 max mem: 33370 +Epoch: [36] [1690/2639] eta: 0:47:30 lr: 5.3793701268720526e-06 loss: 0.0306 (0.0311) time: 3.0892 data: 0.0090 max mem: 33370 +Epoch: [36] [1700/2639] eta: 0:47:01 lr: 5.373908529250315e-06 loss: 0.0312 (0.0310) time: 3.0801 data: 0.0086 max mem: 33370 +Epoch: [36] [1710/2639] eta: 0:46:31 lr: 5.368446314812407e-06 loss: 0.0295 (0.0310) time: 3.0538 data: 0.0087 max mem: 33370 +Epoch: [36] [1720/2639] eta: 0:46:02 lr: 5.362983482791175e-06 loss: 0.0281 (0.0310) time: 3.0871 data: 0.0092 max mem: 33370 +Epoch: [36] [1730/2639] eta: 0:45:32 lr: 5.357520032417667e-06 loss: 0.0290 (0.0310) time: 3.1261 data: 0.0091 max mem: 33370 +Epoch: [36] [1740/2639] eta: 0:45:03 lr: 5.352055962921075e-06 loss: 0.0299 (0.0310) time: 3.1262 data: 0.0089 max mem: 33370 +Epoch: [36] [1750/2639] eta: 0:44:33 lr: 5.346591273528781e-06 loss: 0.0271 (0.0310) time: 3.1077 data: 0.0094 max mem: 33370 +Epoch: [36] [1760/2639] eta: 0:44:03 lr: 5.341125963466298e-06 loss: 0.0270 (0.0310) time: 3.0765 data: 0.0093 max mem: 33370 +Epoch: [36] [1770/2639] eta: 0:43:34 lr: 5.335660031957317e-06 loss: 0.0270 (0.0310) time: 3.0921 data: 0.0091 max mem: 33370 +Epoch: [36] [1780/2639] eta: 0:43:04 lr: 5.330193478223644e-06 loss: 0.0282 (0.0310) time: 3.1108 data: 0.0090 max mem: 33370 +Epoch: [36] [1790/2639] eta: 0:42:34 lr: 5.324726301485251e-06 loss: 0.0254 (0.0310) time: 3.0641 data: 0.0088 max mem: 33370 +Epoch: 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0.0091 max mem: 33370 +Epoch: [36] [1960/2639] eta: 0:34:09 lr: 5.231688212190007e-06 loss: 0.0292 (0.0309) time: 3.1468 data: 0.0089 max mem: 33370 +Epoch: [36] [1970/2639] eta: 0:33:39 lr: 5.226209685816215e-06 loss: 0.0269 (0.0309) time: 3.0884 data: 0.0088 max mem: 33370 +Epoch: [36] [1980/2639] eta: 0:33:09 lr: 5.2207305212541056e-06 loss: 0.0269 (0.0309) time: 3.0957 data: 0.0088 max mem: 33370 +Epoch: [36] [1990/2639] eta: 0:32:39 lr: 5.21525071768495e-06 loss: 0.0277 (0.0309) time: 3.1501 data: 0.0086 max mem: 33370 +Epoch: [36] [2000/2639] eta: 0:32:10 lr: 5.209770274288039e-06 loss: 0.0270 (0.0309) time: 3.1510 data: 0.0084 max mem: 33370 +Epoch: [36] [2010/2639] eta: 0:31:40 lr: 5.204289190240621e-06 loss: 0.0266 (0.0309) time: 3.1390 data: 0.0083 max mem: 33370 +Epoch: [36] [2020/2639] eta: 0:31:10 lr: 5.19880746471795e-06 loss: 0.0262 (0.0309) time: 3.1192 data: 0.0087 max mem: 33370 +Epoch: [36] [2030/2639] eta: 0:30:40 lr: 5.193325096893225e-06 loss: 0.0269 (0.0309) time: 3.1056 data: 0.0091 max mem: 33370 +Epoch: [36] [2040/2639] eta: 0:30:10 lr: 5.187842085937631e-06 loss: 0.0285 (0.0309) time: 3.1118 data: 0.0087 max mem: 33370 +Epoch: [36] [2050/2639] eta: 0:29:40 lr: 5.182358431020287e-06 loss: 0.0256 (0.0309) time: 3.1263 data: 0.0087 max mem: 33370 +Epoch: [36] [2060/2639] eta: 0:29:10 lr: 5.176874131308276e-06 loss: 0.0255 (0.0308) time: 3.1037 data: 0.0087 max mem: 33370 +Epoch: [36] [2070/2639] eta: 0:28:40 lr: 5.171389185966625e-06 loss: 0.0267 (0.0308) time: 3.0909 data: 0.0085 max mem: 33370 +Epoch: [36] [2080/2639] eta: 0:28:10 lr: 5.165903594158273e-06 loss: 0.0285 (0.0308) time: 3.1006 data: 0.0084 max mem: 33370 +Epoch: [36] [2090/2639] eta: 0:27:40 lr: 5.160417355044112e-06 loss: 0.0300 (0.0308) time: 3.1098 data: 0.0090 max mem: 33370 +Epoch: [36] [2100/2639] eta: 0:27:10 lr: 5.154930467782924e-06 loss: 0.0291 (0.0308) time: 3.1259 data: 0.0092 max mem: 33370 +Epoch: [36] [2110/2639] eta: 0:26:40 lr: 5.14944293153143e-06 loss: 0.0294 (0.0308) time: 3.1303 data: 0.0089 max mem: 33370 +Epoch: [36] [2120/2639] eta: 0:26:10 lr: 5.143954745444226e-06 loss: 0.0315 (0.0309) time: 3.1432 data: 0.0089 max mem: 33370 +Epoch: [36] [2130/2639] eta: 0:25:40 lr: 5.138465908673833e-06 loss: 0.0284 (0.0309) time: 3.1405 data: 0.0087 max mem: 33370 +Epoch: [36] [2140/2639] eta: 0:25:10 lr: 5.132976420370627e-06 loss: 0.0260 (0.0308) time: 3.1187 data: 0.0088 max mem: 33370 +Epoch: [36] [2150/2639] eta: 0:24:40 lr: 5.127486279682894e-06 loss: 0.0255 (0.0308) time: 3.0984 data: 0.0090 max mem: 33370 +Epoch: [36] [2160/2639] eta: 0:24:10 lr: 5.121995485756766e-06 loss: 0.0257 (0.0308) time: 3.1298 data: 0.0091 max mem: 33370 +Epoch: [36] [2170/2639] eta: 0:23:40 lr: 5.116504037736263e-06 loss: 0.0257 (0.0308) time: 3.1291 data: 0.0090 max mem: 33370 +Epoch: [36] [2180/2639] eta: 0:23:09 lr: 5.111011934763236e-06 loss: 0.0341 (0.0309) time: 3.0661 data: 0.0087 max mem: 33370 +Epoch: [36] [2190/2639] eta: 0:22:39 lr: 5.105519175977411e-06 loss: 0.0284 (0.0308) time: 3.0443 data: 0.0088 max mem: 33370 +Epoch: [36] [2200/2639] eta: 0:22:09 lr: 5.100025760516327e-06 loss: 0.0288 (0.0309) time: 3.0877 data: 0.0086 max mem: 33370 +Epoch: [36] [2210/2639] eta: 0:21:39 lr: 5.09453168751538e-06 loss: 0.0260 (0.0308) time: 3.1224 data: 0.0085 max mem: 33370 +Epoch: [36] [2220/2639] eta: 0:21:09 lr: 5.089036956107767e-06 loss: 0.0269 (0.0308) time: 3.1157 data: 0.0086 max mem: 33370 +Epoch: [36] [2230/2639] eta: 0:20:39 lr: 5.083541565424525e-06 loss: 0.0291 (0.0309) time: 3.1040 data: 0.0087 max mem: 33370 +Epoch: [36] [2240/2639] eta: 0:20:09 lr: 5.078045514594472e-06 loss: 0.0335 (0.0309) time: 3.1208 data: 0.0088 max mem: 33370 +Epoch: [36] [2250/2639] eta: 0:19:38 lr: 5.072548802744255e-06 loss: 0.0298 (0.0309) time: 3.1123 data: 0.0090 max mem: 33370 +Epoch: [36] [2260/2639] eta: 0:19:08 lr: 5.067051428998284e-06 loss: 0.0263 (0.0309) time: 3.1156 data: 0.0096 max mem: 33370 +Epoch: [36] [2270/2639] eta: 0:18:38 lr: 5.061553392478777e-06 loss: 0.0243 (0.0308) time: 3.1421 data: 0.0097 max mem: 33370 +Epoch: [36] [2280/2639] eta: 0:18:08 lr: 5.056054692305705e-06 loss: 0.0259 (0.0308) time: 3.1162 data: 0.0092 max mem: 33370 +Epoch: [36] [2290/2639] eta: 0:17:38 lr: 5.050555327596828e-06 loss: 0.0286 (0.0308) time: 3.0822 data: 0.0089 max mem: 33370 +Epoch: [36] [2300/2639] eta: 0:17:07 lr: 5.045055297467639e-06 loss: 0.0274 (0.0308) time: 3.0844 data: 0.0090 max mem: 33370 +Epoch: [36] [2310/2639] eta: 0:16:37 lr: 5.039554601031401e-06 loss: 0.0274 (0.0308) time: 3.0534 data: 0.0089 max mem: 33370 +Epoch: [36] [2320/2639] eta: 0:16:07 lr: 5.034053237399119e-06 loss: 0.0266 (0.0308) time: 3.0520 data: 0.0087 max mem: 33370 +Epoch: [36] [2330/2639] eta: 0:15:37 lr: 5.028551205679509e-06 loss: 0.0233 (0.0308) time: 3.1207 data: 0.0086 max mem: 33370 +Epoch: [36] [2340/2639] eta: 0:15:06 lr: 5.023048504979039e-06 loss: 0.0249 (0.0308) time: 3.1423 data: 0.0086 max mem: 33370 +Epoch: [36] [2350/2639] eta: 0:14:36 lr: 5.017545134401866e-06 loss: 0.0275 (0.0308) time: 3.1212 data: 0.0088 max mem: 33370 +Epoch: [36] [2360/2639] eta: 0:14:06 lr: 5.012041093049881e-06 loss: 0.0276 (0.0308) time: 3.0706 data: 0.0089 max mem: 33370 +Epoch: [36] [2370/2639] eta: 0:13:36 lr: 5.006536380022647e-06 loss: 0.0285 (0.0308) time: 3.0732 data: 0.0090 max mem: 33370 +Epoch: [36] [2380/2639] eta: 0:13:05 lr: 5.00103099441744e-06 loss: 0.0285 (0.0308) time: 3.0736 data: 0.0092 max mem: 33370 +Epoch: [36] [2390/2639] eta: 0:12:35 lr: 4.995524935329197e-06 loss: 0.0299 (0.0308) time: 3.1280 data: 0.0091 max mem: 33370 +Epoch: [36] [2400/2639] eta: 0:12:05 lr: 4.990018201850546e-06 loss: 0.0275 (0.0308) time: 3.1515 data: 0.0088 max mem: 33370 +Epoch: [36] [2410/2639] eta: 0:11:35 lr: 4.984510793071759e-06 loss: 0.0265 (0.0308) time: 3.1101 data: 0.0086 max mem: 33370 +Epoch: [36] [2420/2639] eta: 0:11:04 lr: 4.9790027080807826e-06 loss: 0.0284 (0.0308) time: 3.1325 data: 0.0090 max mem: 33370 +Epoch: [36] [2430/2639] eta: 0:10:34 lr: 4.973493945963185e-06 loss: 0.0276 (0.0308) time: 3.1330 data: 0.0091 max mem: 33370 +Epoch: [36] [2440/2639] eta: 0:10:04 lr: 4.9679845058021975e-06 loss: 0.0287 (0.0308) time: 3.1132 data: 0.0089 max mem: 33370 +Epoch: [36] [2450/2639] eta: 0:09:33 lr: 4.962474386678654e-06 loss: 0.0267 (0.0308) time: 3.1089 data: 0.0088 max mem: 33370 +Epoch: [36] [2460/2639] eta: 0:09:03 lr: 4.956963587671029e-06 loss: 0.0263 (0.0308) time: 3.1386 data: 0.0089 max mem: 33370 +Epoch: [36] [2470/2639] eta: 0:08:33 lr: 4.951452107855384e-06 loss: 0.0265 (0.0308) time: 3.1276 data: 0.0092 max mem: 33370 +Epoch: [36] [2480/2639] eta: 0:08:03 lr: 4.945939946305403e-06 loss: 0.0298 (0.0308) time: 3.1190 data: 0.0091 max mem: 33370 +Epoch: [36] [2490/2639] eta: 0:07:32 lr: 4.940427102092338e-06 loss: 0.0309 (0.0308) time: 3.1139 data: 0.0088 max mem: 33370 +Epoch: [36] [2500/2639] eta: 0:07:02 lr: 4.934913574285046e-06 loss: 0.0282 (0.0308) time: 3.0748 data: 0.0084 max mem: 33370 +Epoch: [36] [2510/2639] eta: 0:06:31 lr: 4.929399361949933e-06 loss: 0.0310 (0.0308) time: 3.0599 data: 0.0085 max mem: 33370 +Epoch: [36] [2520/2639] eta: 0:06:01 lr: 4.923884464150993e-06 loss: 0.0272 (0.0308) time: 3.0937 data: 0.0089 max mem: 33370 +Epoch: [36] [2530/2639] eta: 0:05:31 lr: 4.918368879949744e-06 loss: 0.0260 (0.0307) time: 3.1196 data: 0.0088 max mem: 33370 +Epoch: [36] [2540/2639] eta: 0:05:00 lr: 4.912852608405272e-06 loss: 0.0260 (0.0307) time: 3.1261 data: 0.0087 max mem: 33370 +Epoch: [36] [2550/2639] eta: 0:04:30 lr: 4.907335648574197e-06 loss: 0.0261 (0.0308) time: 3.1384 data: 0.0088 max mem: 33370 +Epoch: [36] [2560/2639] eta: 0:04:00 lr: 4.901817999510641e-06 loss: 0.0270 (0.0308) time: 3.1287 data: 0.0091 max mem: 33370 +Epoch: [36] [2570/2639] eta: 0:03:29 lr: 4.896299660266273e-06 loss: 0.0269 (0.0308) time: 3.1368 data: 0.0091 max mem: 33370 +Epoch: [36] [2580/2639] eta: 0:02:59 lr: 4.8907806298902365e-06 loss: 0.0282 (0.0308) time: 3.1481 data: 0.0087 max mem: 33370 +Epoch: [36] [2590/2639] eta: 0:02:29 lr: 4.885260907429199e-06 loss: 0.0287 (0.0308) time: 3.1409 data: 0.0090 max mem: 33370 +Epoch: [36] [2600/2639] eta: 0:01:58 lr: 4.879740491927289e-06 loss: 0.0290 (0.0308) time: 3.0924 data: 0.0092 max mem: 33370 +Epoch: [36] [2610/2639] eta: 0:01:28 lr: 4.874219382426137e-06 loss: 0.0279 (0.0308) time: 3.0905 data: 0.0087 max mem: 33370 +Epoch: [36] [2620/2639] eta: 0:00:57 lr: 4.868697577964815e-06 loss: 0.0279 (0.0308) time: 3.1045 data: 0.0085 max mem: 33370 +Epoch: [36] [2630/2639] eta: 0:00:27 lr: 4.863175077579876e-06 loss: 0.0259 (0.0308) time: 3.0983 data: 0.0084 max mem: 33370 +Epoch: [36] Total time: 2:13:48 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 2:28:11 time: 3.4556 data: 3.3688 max mem: 33370 +Test: [ 100/2573] eta: 0:04:41 time: 0.0805 data: 0.0016 max mem: 33370 +Test: [ 200/2573] eta: 0:03:51 time: 0.0811 data: 0.0016 max mem: 33370 +Test: [ 300/2573] eta: 0:03:28 time: 0.0830 data: 0.0015 max mem: 33370 +Test: [ 400/2573] eta: 0:03:14 time: 0.0837 data: 0.0015 max mem: 33370 +Test: [ 500/2573] eta: 0:03:02 time: 0.0823 data: 0.0018 max mem: 33370 +Test: [ 600/2573] eta: 0:02:52 time: 0.0813 data: 0.0016 max mem: 33370 +Test: [ 700/2573] eta: 0:02:42 time: 0.0828 data: 0.0016 max mem: 33370 +Test: [ 800/2573] eta: 0:02:33 time: 0.0851 data: 0.0016 max mem: 33370 +Test: [ 900/2573] eta: 0:02:23 time: 0.0826 data: 0.0015 max mem: 33370 +Test: [1000/2573] eta: 0:02:14 time: 0.0828 data: 0.0015 max mem: 33370 +Test: [1100/2573] eta: 0:02:05 time: 0.0816 data: 0.0015 max mem: 33370 +Test: [1200/2573] eta: 0:01:56 time: 0.0824 data: 0.0016 max mem: 33370 +Test: [1300/2573] eta: 0:01:47 time: 0.0828 data: 0.0016 max mem: 33370 +Test: [1400/2573] eta: 0:01:39 time: 0.0822 data: 0.0017 max mem: 33370 +Test: [1500/2573] eta: 0:01:30 time: 0.0827 data: 0.0017 max mem: 33370 +Test: [1600/2573] eta: 0:01:22 time: 0.0853 data: 0.0016 max mem: 33370 +Test: [1700/2573] eta: 0:01:13 time: 0.0809 data: 0.0016 max mem: 33370 +Test: [1800/2573] eta: 0:01:05 time: 0.0847 data: 0.0015 max mem: 33370 +Test: [1900/2573] eta: 0:00:56 time: 0.0802 data: 0.0016 max mem: 33370 +Test: [2000/2573] eta: 0:00:48 time: 0.0826 data: 0.0017 max mem: 33370 +Test: [2100/2573] eta: 0:00:39 time: 0.0848 data: 0.0016 max mem: 33370 +Test: [2200/2573] eta: 0:00:31 time: 0.0836 data: 0.0016 max mem: 33370 +Test: [2300/2573] eta: 0:00:22 time: 0.0841 data: 0.0016 max mem: 33370 +Test: [2400/2573] eta: 0:00:14 time: 0.0812 data: 0.0017 max mem: 33370 +Test: [2500/2573] eta: 0:00:06 time: 0.0815 data: 0.0016 max mem: 33370 +Test: Total time: 0:03:36 +Final results: +Mean IoU is 64.94 + + precision@0.5 = 73.10 + precision@0.6 = 67.81 + precision@0.7 = 61.54 + precision@0.8 = 50.65 + precision@0.9 = 26.18 + overall IoU = 62.16 + +Average object IoU 64.94045022823263 +Overall IoU 62.164859771728516 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [37] [ 0/2639] eta: 4:41:11 lr: 4.858204231420373e-06 loss: 0.0264 (0.0264) time: 6.3932 data: 3.1570 max mem: 33370 +Epoch: [37] [ 10/2639] eta: 2:27:59 lr: 4.852680406117061e-06 loss: 0.0299 (0.0356) time: 3.3775 data: 0.2951 max mem: 33370 +Epoch: [37] [ 20/2639] eta: 2:21:08 lr: 4.8471558820816275e-06 loss: 0.0299 (0.0376) time: 3.0756 data: 0.0084 max mem: 33370 +Epoch: [37] [ 30/2639] eta: 2:18:32 lr: 4.841630658340586e-06 loss: 0.0265 (0.0345) time: 3.0808 data: 0.0083 max mem: 33370 +Epoch: [37] [ 40/2639] eta: 2:15:55 lr: 4.8361047339178825e-06 loss: 0.0285 (0.0331) time: 3.0377 data: 0.0088 max mem: 33370 +Epoch: [37] [ 50/2639] eta: 2:14:14 lr: 4.830578107834837e-06 loss: 0.0292 (0.0327) time: 2.9946 data: 0.0092 max mem: 33370 +Epoch: [37] [ 60/2639] eta: 2:12:47 lr: 4.825050779110181e-06 loss: 0.0307 (0.0327) time: 2.9894 data: 0.0094 max mem: 33370 +Epoch: [37] [ 70/2639] eta: 2:11:53 lr: 4.819522746759996e-06 loss: 0.0290 (0.0322) time: 3.0027 data: 0.0090 max mem: 33370 +Epoch: [37] [ 80/2639] eta: 2:11:33 lr: 4.81399400979776e-06 loss: 0.0314 (0.0324) time: 3.0705 data: 0.0088 max mem: 33370 +Epoch: [37] [ 90/2639] eta: 2:11:12 lr: 4.808464567234274e-06 loss: 0.0321 (0.0324) time: 3.1169 data: 0.0092 max mem: 33370 +Epoch: [37] [ 100/2639] eta: 2:10:31 lr: 4.8029344180777165e-06 loss: 0.0288 (0.0319) time: 3.0845 data: 0.0093 max mem: 33370 +Epoch: [37] [ 110/2639] eta: 2:10:10 lr: 4.797403561333572e-06 loss: 0.0321 (0.0324) time: 3.0870 data: 0.0093 max mem: 33370 +Epoch: [37] [ 120/2639] eta: 2:09:35 lr: 4.791871996004678e-06 loss: 0.0299 (0.0317) time: 3.0985 data: 0.0091 max mem: 33370 +Epoch: [37] [ 130/2639] eta: 2:09:03 lr: 4.786339721091154e-06 loss: 0.0255 (0.0312) time: 3.0765 data: 0.0087 max mem: 33370 +Epoch: [37] [ 140/2639] eta: 2:08:32 lr: 4.780806735590456e-06 loss: 0.0265 (0.0309) time: 3.0820 data: 0.0089 max mem: 33370 +Epoch: [37] [ 150/2639] eta: 2:08:08 lr: 4.775273038497301e-06 loss: 0.0284 (0.0309) time: 3.1058 data: 0.0090 max mem: 33370 +Epoch: [37] [ 160/2639] eta: 2:07:49 lr: 4.769738628803717e-06 loss: 0.0302 (0.0310) time: 3.1465 data: 0.0087 max mem: 33370 +Epoch: [37] [ 170/2639] eta: 2:07:07 lr: 4.764203505498972e-06 loss: 0.0323 (0.0310) time: 3.0930 data: 0.0086 max mem: 33370 +Epoch: [37] [ 180/2639] eta: 2:06:39 lr: 4.758667667569619e-06 loss: 0.0332 (0.0313) time: 3.0643 data: 0.0086 max mem: 33370 +Epoch: [37] [ 190/2639] eta: 2:06:13 lr: 4.753131113999455e-06 loss: 0.0331 (0.0312) time: 3.1201 data: 0.0085 max mem: 33370 +Epoch: [37] [ 200/2639] eta: 2:05:39 lr: 4.747593843769497e-06 loss: 0.0270 (0.0311) time: 3.0976 data: 0.0087 max mem: 33370 +Epoch: [37] [ 210/2639] eta: 2:05:03 lr: 4.742055855858015e-06 loss: 0.0281 (0.0309) time: 3.0543 data: 0.0087 max mem: 33370 +Epoch: [37] [ 220/2639] eta: 2:04:25 lr: 4.736517149240468e-06 loss: 0.0281 (0.0309) time: 3.0346 data: 0.0091 max mem: 33370 +Epoch: [37] [ 230/2639] eta: 2:03:48 lr: 4.730977722889544e-06 loss: 0.0285 (0.0307) time: 3.0289 data: 0.0089 max mem: 33370 +Epoch: [37] [ 240/2639] eta: 2:03:08 lr: 4.725437575775101e-06 loss: 0.0282 (0.0306) time: 3.0134 data: 0.0086 max mem: 33370 +Epoch: [37] [ 250/2639] eta: 2:02:24 lr: 4.7198967068642015e-06 loss: 0.0262 (0.0305) time: 2.9629 data: 0.0086 max mem: 33370 +Epoch: [37] [ 260/2639] eta: 2:01:43 lr: 4.714355115121052e-06 loss: 0.0246 (0.0302) time: 2.9513 data: 0.0087 max mem: 33370 +Epoch: [37] [ 270/2639] eta: 2:01:17 lr: 4.7088127995070476e-06 loss: 0.0265 (0.0302) time: 3.0426 data: 0.0090 max mem: 33370 +Epoch: [37] [ 280/2639] eta: 2:00:45 lr: 4.7032697589807e-06 loss: 0.0280 (0.0302) time: 3.0885 data: 0.0093 max mem: 33370 +Epoch: [37] [ 290/2639] eta: 2:00:20 lr: 4.6977259924976846e-06 loss: 0.0263 (0.0301) time: 3.0988 data: 0.0092 max mem: 33370 +Epoch: [37] [ 300/2639] eta: 1:59:52 lr: 4.692181499010776e-06 loss: 0.0268 (0.0302) time: 3.1282 data: 0.0090 max mem: 33370 +Epoch: [37] [ 310/2639] eta: 1:59:23 lr: 4.686636277469884e-06 loss: 0.0285 (0.0302) time: 3.1066 data: 0.0086 max mem: 33370 +Epoch: [37] [ 320/2639] eta: 1:58:46 lr: 4.681090326821997e-06 loss: 0.0295 (0.0302) time: 3.0394 data: 0.0089 max mem: 33370 +Epoch: [37] [ 330/2639] eta: 1:58:11 lr: 4.675543646011214e-06 loss: 0.0289 (0.0302) time: 2.9994 data: 0.0087 max mem: 33370 +Epoch: [37] [ 340/2639] eta: 1:57:40 lr: 4.669996233978688e-06 loss: 0.0266 (0.0301) time: 3.0403 data: 0.0084 max mem: 33370 +Epoch: [37] [ 350/2639] eta: 1:57:05 lr: 4.664448089662659e-06 loss: 0.0287 (0.0302) time: 3.0390 data: 0.0091 max mem: 33370 +Epoch: [37] [ 360/2639] eta: 1:56:28 lr: 4.658899211998398e-06 loss: 0.0310 (0.0303) time: 2.9918 data: 0.0093 max mem: 33370 +Epoch: [37] [ 370/2639] eta: 1:55:52 lr: 4.6533495999182405e-06 loss: 0.0318 (0.0303) time: 2.9696 data: 0.0089 max mem: 33370 +Epoch: [37] [ 380/2639] eta: 1:55:14 lr: 4.647799252351525e-06 loss: 0.0275 (0.0302) time: 2.9585 data: 0.0088 max mem: 33370 +Epoch: [37] [ 390/2639] eta: 1:54:38 lr: 4.64224816822463e-06 loss: 0.0242 (0.0301) time: 2.9551 data: 0.0085 max mem: 33370 +Epoch: [37] [ 400/2639] eta: 1:54:06 lr: 4.636696346460917e-06 loss: 0.0233 (0.0301) time: 3.0014 data: 0.0085 max mem: 33370 +Epoch: [37] [ 410/2639] eta: 1:53:40 lr: 4.63114378598076e-06 loss: 0.0265 (0.0301) time: 3.0896 data: 0.0085 max mem: 33370 +Epoch: [37] [ 420/2639] eta: 1:53:12 lr: 4.625590485701491e-06 loss: 0.0300 (0.0302) time: 3.1265 data: 0.0085 max mem: 33370 +Epoch: [37] [ 430/2639] eta: 1:52:41 lr: 4.620036444537424e-06 loss: 0.0300 (0.0302) time: 3.0802 data: 0.0084 max mem: 33370 +Epoch: [37] [ 440/2639] eta: 1:52:09 lr: 4.614481661399829e-06 loss: 0.0301 (0.0302) time: 3.0374 data: 0.0082 max mem: 33370 +Epoch: [37] [ 450/2639] eta: 1:51:39 lr: 4.608926135196899e-06 loss: 0.0314 (0.0302) time: 3.0552 data: 0.0081 max mem: 33370 +Epoch: [37] [ 460/2639] eta: 1:51:10 lr: 4.603369864833779e-06 loss: 0.0279 (0.0301) time: 3.0829 data: 0.0084 max mem: 33370 +Epoch: [37] [ 470/2639] eta: 1:50:40 lr: 4.597812849212508e-06 loss: 0.0284 (0.0301) time: 3.0817 data: 0.0089 max mem: 33370 +Epoch: [37] [ 480/2639] eta: 1:50:11 lr: 4.59225508723205e-06 loss: 0.0266 (0.0301) time: 3.0829 data: 0.0091 max mem: 33370 +Epoch: [37] [ 490/2639] eta: 1:49:39 lr: 4.586696577788237e-06 loss: 0.0266 (0.0301) time: 3.0655 data: 0.0089 max mem: 33370 +Epoch: [37] [ 500/2639] eta: 1:49:10 lr: 4.581137319773802e-06 loss: 0.0289 (0.0301) time: 3.0742 data: 0.0089 max mem: 33370 +Epoch: [37] [ 510/2639] eta: 1:48:41 lr: 4.575577312078318e-06 loss: 0.0265 (0.0300) time: 3.0954 data: 0.0090 max mem: 33370 +Epoch: [37] [ 520/2639] eta: 1:48:11 lr: 4.570016553588234e-06 loss: 0.0256 (0.0300) time: 3.0879 data: 0.0088 max mem: 33370 +Epoch: [37] [ 530/2639] eta: 1:47:40 lr: 4.56445504318681e-06 loss: 0.0252 (0.0299) time: 3.0708 data: 0.0087 max mem: 33370 +Epoch: [37] [ 540/2639] eta: 1:47:08 lr: 4.558892779754159e-06 loss: 0.0267 (0.0300) time: 3.0335 data: 0.0091 max mem: 33370 +Epoch: [37] [ 550/2639] eta: 1:46:39 lr: 4.553329762167178e-06 loss: 0.0279 (0.0299) time: 3.0626 data: 0.0093 max mem: 33370 +Epoch: [37] [ 560/2639] eta: 1:46:07 lr: 4.547765989299589e-06 loss: 0.0304 (0.0300) time: 3.0768 data: 0.0092 max mem: 33370 +Epoch: [37] [ 570/2639] eta: 1:45:35 lr: 4.542201460021869e-06 loss: 0.0307 (0.0300) time: 3.0245 data: 0.0095 max mem: 33370 +Epoch: [37] [ 580/2639] eta: 1:45:04 lr: 4.536636173201297e-06 loss: 0.0299 (0.0300) time: 3.0360 data: 0.0096 max mem: 33370 +Epoch: [37] [ 590/2639] eta: 1:44:35 lr: 4.53107012770188e-06 loss: 0.0279 (0.0300) time: 3.0787 data: 0.0092 max mem: 33370 +Epoch: [37] [ 600/2639] eta: 1:44:03 lr: 4.525503322384394e-06 loss: 0.0264 (0.0299) time: 3.0614 data: 0.0091 max mem: 33370 +Epoch: [37] [ 610/2639] eta: 1:43:32 lr: 4.519935756106321e-06 loss: 0.0266 (0.0299) time: 3.0434 data: 0.0093 max mem: 33370 +Epoch: [37] [ 620/2639] eta: 1:43:01 lr: 4.514367427721883e-06 loss: 0.0265 (0.0299) time: 3.0574 data: 0.0095 max mem: 33370 +Epoch: [37] [ 630/2639] eta: 1:42:29 lr: 4.508798336081979e-06 loss: 0.0256 (0.0299) time: 3.0404 data: 0.0091 max mem: 33370 +Epoch: [37] [ 640/2639] eta: 1:41:56 lr: 4.503228480034221e-06 loss: 0.0271 (0.0299) time: 2.9962 data: 0.0088 max mem: 33370 +Epoch: [37] [ 650/2639] eta: 1:41:24 lr: 4.497657858422869e-06 loss: 0.0296 (0.0299) time: 2.9949 data: 0.0088 max mem: 33370 +Epoch: [37] [ 660/2639] eta: 1:40:53 lr: 4.49208647008887e-06 loss: 0.0286 (0.0299) time: 3.0323 data: 0.0091 max mem: 33370 +Epoch: [37] [ 670/2639] eta: 1:40:21 lr: 4.486514313869786e-06 loss: 0.0269 (0.0299) time: 3.0259 data: 0.0094 max mem: 33370 +Epoch: [37] [ 680/2639] eta: 1:39:52 lr: 4.4809413885998335e-06 loss: 0.0302 (0.0299) time: 3.0557 data: 0.0099 max mem: 33370 +Epoch: [37] [ 690/2639] eta: 1:39:22 lr: 4.475367693109844e-06 loss: 0.0314 (0.0299) time: 3.0969 data: 0.0098 max mem: 33370 +Epoch: [37] [ 700/2639] eta: 1:38:51 lr: 4.469793226227232e-06 loss: 0.0281 (0.0299) time: 3.0670 data: 0.0088 max mem: 33370 +Epoch: [37] [ 710/2639] eta: 1:38:18 lr: 4.464217986776025e-06 loss: 0.0271 (0.0299) time: 3.0152 data: 0.0091 max mem: 33370 +Epoch: [37] [ 720/2639] eta: 1:37:48 lr: 4.458641973576796e-06 loss: 0.0255 (0.0299) time: 3.0162 data: 0.0092 max mem: 33370 +Epoch: [37] [ 730/2639] eta: 1:37:17 lr: 4.453065185446704e-06 loss: 0.0270 (0.0299) time: 3.0515 data: 0.0089 max mem: 33370 +Epoch: [37] [ 740/2639] eta: 1:36:48 lr: 4.447487621199423e-06 loss: 0.0298 (0.0299) time: 3.0950 data: 0.0088 max mem: 33370 +Epoch: [37] [ 750/2639] eta: 1:36:20 lr: 4.441909279645183e-06 loss: 0.0298 (0.0299) time: 3.1345 data: 0.0086 max mem: 33370 +Epoch: [37] [ 760/2639] eta: 1:35:48 lr: 4.4363301595907e-06 loss: 0.0275 (0.0299) time: 3.0760 data: 0.0086 max mem: 33370 +Epoch: [37] [ 770/2639] eta: 1:35:18 lr: 4.430750259839213e-06 loss: 0.0287 (0.0299) time: 3.0527 data: 0.0088 max mem: 33370 +Epoch: [37] [ 780/2639] eta: 1:34:46 lr: 4.42516957919042e-06 loss: 0.0295 (0.0300) time: 3.0355 data: 0.0092 max mem: 33370 +Epoch: [37] [ 790/2639] eta: 1:34:14 lr: 4.419588116440512e-06 loss: 0.0304 (0.0300) time: 3.0050 data: 0.0090 max mem: 33370 +Epoch: [37] [ 800/2639] eta: 1:33:43 lr: 4.414005870382104e-06 loss: 0.0268 (0.0300) time: 3.0263 data: 0.0087 max mem: 33370 +Epoch: [37] [ 810/2639] eta: 1:33:13 lr: 4.408422839804277e-06 loss: 0.0267 (0.0300) time: 3.0495 data: 0.0089 max mem: 33370 +Epoch: [37] [ 820/2639] eta: 1:32:42 lr: 4.402839023492504e-06 loss: 0.0305 (0.0301) time: 3.0659 data: 0.0093 max mem: 33370 +Epoch: [37] [ 830/2639] eta: 1:32:14 lr: 4.397254420228692e-06 loss: 0.0314 (0.0302) time: 3.1030 data: 0.0092 max mem: 33370 +Epoch: [37] [ 840/2639] eta: 1:31:43 lr: 4.391669028791109e-06 loss: 0.0328 (0.0303) time: 3.1069 data: 0.0089 max mem: 33370 +Epoch: [37] [ 850/2639] eta: 1:31:14 lr: 4.386082847954426e-06 loss: 0.0297 (0.0303) time: 3.0977 data: 0.0088 max mem: 33370 +Epoch: 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mem: 33370 +Epoch: [37] [ 940/2639] eta: 1:26:25 lr: 4.335771493467251e-06 loss: 0.0293 (0.0303) time: 2.9349 data: 0.0089 max mem: 33370 +Epoch: [37] [ 950/2639] eta: 1:25:52 lr: 4.330177350436381e-06 loss: 0.0291 (0.0303) time: 2.9444 data: 0.0090 max mem: 33370 +Epoch: [37] [ 960/2639] eta: 1:25:22 lr: 4.324582404283698e-06 loss: 0.0274 (0.0303) time: 3.0079 data: 0.0095 max mem: 33370 +Epoch: [37] [ 970/2639] eta: 1:24:51 lr: 4.318986653739064e-06 loss: 0.0256 (0.0303) time: 3.0395 data: 0.0098 max mem: 33370 +Epoch: [37] [ 980/2639] eta: 1:24:20 lr: 4.313390097528528e-06 loss: 0.0289 (0.0304) time: 3.0333 data: 0.0091 max mem: 33370 +Epoch: [37] [ 990/2639] eta: 1:23:51 lr: 4.307792734374256e-06 loss: 0.0297 (0.0303) time: 3.0710 data: 0.0091 max mem: 33370 +Epoch: [37] [1000/2639] eta: 1:23:22 lr: 4.3021945629945645e-06 loss: 0.0286 (0.0303) time: 3.1141 data: 0.0091 max mem: 33370 +Epoch: [37] [1010/2639] eta: 1:22:51 lr: 4.296595582103853e-06 loss: 0.0268 (0.0303) time: 3.1072 data: 0.0089 max mem: 33370 +Epoch: [37] [1020/2639] eta: 1:22:22 lr: 4.290995790412636e-06 loss: 0.0268 (0.0303) time: 3.0961 data: 0.0087 max mem: 33370 +Epoch: [37] [1030/2639] eta: 1:21:52 lr: 4.285395186627474e-06 loss: 0.0284 (0.0303) time: 3.0895 data: 0.0088 max mem: 33370 +Epoch: [37] [1040/2639] eta: 1:21:21 lr: 4.2797937694510135e-06 loss: 0.0262 (0.0302) time: 3.0466 data: 0.0091 max mem: 33370 +Epoch: [37] [1050/2639] eta: 1:20:51 lr: 4.274191537581907e-06 loss: 0.0274 (0.0303) time: 3.0800 data: 0.0090 max mem: 33370 +Epoch: [37] [1060/2639] eta: 1:20:21 lr: 4.2685884897148545e-06 loss: 0.0274 (0.0303) time: 3.1009 data: 0.0088 max mem: 33370 +Epoch: [37] [1070/2639] eta: 1:19:49 lr: 4.262984624540533e-06 loss: 0.0281 (0.0303) time: 3.0119 data: 0.0087 max mem: 33370 +Epoch: [37] [1080/2639] eta: 1:19:18 lr: 4.257379940745627e-06 loss: 0.0245 (0.0303) time: 2.9788 data: 0.0089 max mem: 33370 +Epoch: [37] [1090/2639] eta: 1:18:46 lr: 4.25177443701276e-06 loss: 0.0257 (0.0302) time: 2.9988 data: 0.0092 max mem: 33370 +Epoch: [37] [1100/2639] eta: 1:18:17 lr: 4.246168112020529e-06 loss: 0.0278 (0.0302) time: 3.0574 data: 0.0090 max mem: 33370 +Epoch: [37] [1110/2639] eta: 1:17:46 lr: 4.240560964443435e-06 loss: 0.0266 (0.0302) time: 3.0720 data: 0.0089 max mem: 33370 +Epoch: [37] [1120/2639] eta: 1:17:15 lr: 4.234952992951913e-06 loss: 0.0266 (0.0302) time: 3.0141 data: 0.0096 max mem: 33370 +Epoch: [37] [1130/2639] eta: 1:16:44 lr: 4.229344196212263e-06 loss: 0.0287 (0.0302) time: 3.0252 data: 0.0097 max mem: 33370 +Epoch: [37] [1140/2639] eta: 1:16:13 lr: 4.2237345728866855e-06 loss: 0.0287 (0.0303) time: 3.0393 data: 0.0088 max mem: 33370 +Epoch: [37] [1150/2639] eta: 1:15:43 lr: 4.218124121633206e-06 loss: 0.0285 (0.0303) time: 3.0347 data: 0.0088 max mem: 33370 +Epoch: [37] [1160/2639] eta: 1:15:10 lr: 4.212512841105706e-06 loss: 0.0313 (0.0303) time: 2.9674 data: 0.0092 max mem: 33370 +Epoch: [37] [1170/2639] eta: 1:14:39 lr: 4.20690072995388e-06 loss: 0.0290 (0.0303) time: 2.9276 data: 0.0093 max mem: 33370 +Epoch: [37] [1180/2639] eta: 1:14:08 lr: 4.201287786823204e-06 loss: 0.0290 (0.0303) time: 2.9913 data: 0.0098 max mem: 33370 +Epoch: [37] [1190/2639] eta: 1:13:38 lr: 4.195674010354951e-06 loss: 0.0269 (0.0303) time: 3.0600 data: 0.0098 max mem: 33370 +Epoch: [37] [1200/2639] eta: 1:13:08 lr: 4.190059399186129e-06 loss: 0.0265 (0.0303) time: 3.0791 data: 0.0094 max mem: 33370 +Epoch: [37] [1210/2639] eta: 1:12:38 lr: 4.184443951949511e-06 loss: 0.0296 (0.0303) time: 3.0804 data: 0.0094 max mem: 33370 +Epoch: [37] [1220/2639] eta: 1:12:08 lr: 4.178827667273559e-06 loss: 0.0277 (0.0302) time: 3.1049 data: 0.0091 max mem: 33370 +Epoch: [37] [1230/2639] eta: 1:11:38 lr: 4.173210543782459e-06 loss: 0.0276 (0.0302) time: 3.0895 data: 0.0090 max mem: 33370 +Epoch: [37] [1240/2639] eta: 1:11:07 lr: 4.167592580096054e-06 loss: 0.0285 (0.0303) time: 3.0420 data: 0.0090 max mem: 33370 +Epoch: [37] [1250/2639] eta: 1:10:36 lr: 4.161973774829865e-06 loss: 0.0296 (0.0303) time: 3.0339 data: 0.0087 max mem: 33370 +Epoch: [37] [1260/2639] eta: 1:10:06 lr: 4.15635412659503e-06 loss: 0.0274 (0.0302) time: 3.0569 data: 0.0087 max mem: 33370 +Epoch: [37] [1270/2639] eta: 1:09:35 lr: 4.150733633998329e-06 loss: 0.0267 (0.0303) time: 3.0311 data: 0.0088 max mem: 33370 +Epoch: [37] [1280/2639] eta: 1:09:03 lr: 4.145112295642113e-06 loss: 0.0273 (0.0302) time: 2.9790 data: 0.0092 max mem: 33370 +Epoch: [37] [1290/2639] eta: 1:08:32 lr: 4.139490110124337e-06 loss: 0.0262 (0.0303) time: 2.9533 data: 0.0093 max mem: 33370 +Epoch: [37] [1300/2639] eta: 1:08:02 lr: 4.133867076038482e-06 loss: 0.0270 (0.0303) time: 3.0282 data: 0.0086 max mem: 33370 +Epoch: [37] [1310/2639] eta: 1:07:32 lr: 4.1282431919735985e-06 loss: 0.0283 (0.0303) time: 3.1049 data: 0.0089 max mem: 33370 +Epoch: [37] [1320/2639] eta: 1:07:02 lr: 4.122618456514216e-06 loss: 0.0279 (0.0303) time: 3.0984 data: 0.0094 max mem: 33370 +Epoch: [37] [1330/2639] eta: 1:06:32 lr: 4.11699286824039e-06 loss: 0.0287 (0.0303) time: 3.0763 data: 0.0090 max mem: 33370 +Epoch: [37] [1340/2639] eta: 1:06:02 lr: 4.111366425727618e-06 loss: 0.0317 (0.0303) time: 3.0801 data: 0.0088 max mem: 33370 +Epoch: [37] [1350/2639] eta: 1:05:31 lr: 4.105739127546876e-06 loss: 0.0278 (0.0303) time: 3.0864 data: 0.0093 max mem: 33370 +Epoch: [37] [1360/2639] eta: 1:05:01 lr: 4.100110972264544e-06 loss: 0.0264 (0.0303) time: 3.0985 data: 0.0095 max mem: 33370 +Epoch: [37] [1370/2639] eta: 1:04:31 lr: 4.094481958442432e-06 loss: 0.0264 (0.0303) time: 3.0943 data: 0.0091 max mem: 33370 +Epoch: [37] [1380/2639] eta: 1:04:00 lr: 4.0888520846377135e-06 loss: 0.0284 (0.0303) time: 3.0368 data: 0.0091 max mem: 33370 +Epoch: [37] [1390/2639] eta: 1:03:30 lr: 4.08322134940295e-06 loss: 0.0257 (0.0303) time: 3.0510 data: 0.0094 max mem: 33370 +Epoch: [37] [1400/2639] eta: 1:03:00 lr: 4.077589751286019e-06 loss: 0.0272 (0.0303) time: 3.0749 data: 0.0092 max mem: 33370 +Epoch: [37] [1410/2639] eta: 1:02:29 lr: 4.07195728883014e-06 loss: 0.0337 (0.0303) time: 3.0659 data: 0.0089 max mem: 33370 +Epoch: [37] [1420/2639] eta: 1:01:59 lr: 4.066323960573824e-06 loss: 0.0295 (0.0303) time: 3.0579 data: 0.0087 max mem: 33370 +Epoch: [37] [1430/2639] eta: 1:01:28 lr: 4.060689765050844e-06 loss: 0.0276 (0.0303) time: 3.0080 data: 0.0087 max mem: 33370 +Epoch: [37] [1440/2639] eta: 1:00:56 lr: 4.055054700790246e-06 loss: 0.0306 (0.0303) time: 2.9655 data: 0.0086 max mem: 33370 +Epoch: [37] [1450/2639] eta: 1:00:25 lr: 4.049418766316284e-06 loss: 0.0311 (0.0303) time: 2.9574 data: 0.0085 max mem: 33370 +Epoch: [37] [1460/2639] eta: 0:59:53 lr: 4.0437819601484425e-06 loss: 0.0286 (0.0303) time: 2.9245 data: 0.0092 max mem: 33370 +Epoch: [37] [1470/2639] eta: 0:59:23 lr: 4.0381442808013635e-06 loss: 0.0257 (0.0303) time: 2.9840 data: 0.0095 max mem: 33370 +Epoch: [37] [1480/2639] eta: 0:58:53 lr: 4.0325057267848766e-06 loss: 0.0266 (0.0303) time: 3.0938 data: 0.0093 max mem: 33370 +Epoch: [37] [1490/2639] eta: 0:58:23 lr: 4.026866296603923e-06 loss: 0.0288 (0.0303) time: 3.1039 data: 0.0090 max mem: 33370 +Epoch: [37] [1500/2639] eta: 0:57:53 lr: 4.021225988758581e-06 loss: 0.0298 (0.0303) time: 3.0940 data: 0.0087 max mem: 33370 +Epoch: [37] [1510/2639] eta: 0:57:23 lr: 4.0155848017439985e-06 loss: 0.0307 (0.0303) time: 3.0922 data: 0.0091 max mem: 33370 +Epoch: [37] [1520/2639] eta: 0:56:52 lr: 4.00994273405041e-06 loss: 0.0267 (0.0303) time: 3.0952 data: 0.0094 max mem: 33370 +Epoch: [37] [1530/2639] eta: 0:56:22 lr: 4.00429978416307e-06 loss: 0.0285 (0.0303) time: 3.0873 data: 0.0093 max mem: 33370 +Epoch: [37] [1540/2639] eta: 0:55:52 lr: 3.998655950562277e-06 loss: 0.0279 (0.0303) time: 3.1046 data: 0.0093 max mem: 33370 +Epoch: [37] [1550/2639] eta: 0:55:22 lr: 3.993011231723297e-06 loss: 0.0279 (0.0303) time: 3.1133 data: 0.0094 max mem: 33370 +Epoch: [37] [1560/2639] eta: 0:54:51 lr: 3.987365626116392e-06 loss: 0.0289 (0.0303) time: 3.0686 data: 0.0089 max mem: 33370 +Epoch: [37] [1570/2639] eta: 0:54:21 lr: 3.9817191322067445e-06 loss: 0.0261 (0.0303) time: 3.0590 data: 0.0085 max mem: 33370 +Epoch: [37] [1580/2639] eta: 0:53:51 lr: 3.976071748454483e-06 loss: 0.0262 (0.0303) time: 3.0844 data: 0.0086 max mem: 33370 +Epoch: [37] [1590/2639] eta: 0:53:20 lr: 3.970423473314604e-06 loss: 0.0306 (0.0304) time: 3.0834 data: 0.0087 max mem: 33370 +Epoch: [37] [1600/2639] eta: 0:52:50 lr: 3.964774305237005e-06 loss: 0.0268 (0.0303) time: 3.0823 data: 0.0087 max mem: 33370 +Epoch: [37] [1610/2639] eta: 0:52:20 lr: 3.959124242666398e-06 loss: 0.0268 (0.0303) time: 3.0575 data: 0.0087 max mem: 33370 +Epoch: [37] [1620/2639] eta: 0:51:49 lr: 3.953473284042345e-06 loss: 0.0306 (0.0303) time: 3.0415 data: 0.0086 max mem: 33370 +Epoch: [37] [1630/2639] eta: 0:51:19 lr: 3.947821427799175e-06 loss: 0.0303 (0.0304) time: 3.0940 data: 0.0085 max mem: 33370 +Epoch: [37] [1640/2639] eta: 0:50:49 lr: 3.942168672366015e-06 loss: 0.0271 (0.0303) time: 3.1351 data: 0.0088 max mem: 33370 +Epoch: [37] [1650/2639] eta: 0:50:19 lr: 3.9365150161667035e-06 loss: 0.0272 (0.0303) time: 3.1038 data: 0.0090 max mem: 33370 +Epoch: [37] [1660/2639] eta: 0:49:49 lr: 3.9308604576198205e-06 loss: 0.0263 (0.0303) time: 3.1001 data: 0.0091 max mem: 33370 +Epoch: [37] [1670/2639] eta: 0:49:18 lr: 3.925204995138637e-06 loss: 0.0277 (0.0303) time: 3.1194 data: 0.0091 max mem: 33370 +Epoch: [37] [1680/2639] eta: 0:48:49 lr: 3.919548627131066e-06 loss: 0.0315 (0.0303) time: 3.1432 data: 0.0086 max mem: 33370 +Epoch: [37] [1690/2639] eta: 0:48:19 lr: 3.913891351999689e-06 loss: 0.0303 (0.0303) time: 3.1711 data: 0.0091 max mem: 33370 +Epoch: [37] [1700/2639] eta: 0:47:48 lr: 3.908233168141669e-06 loss: 0.0303 (0.0304) time: 3.1083 data: 0.0096 max mem: 33370 +Epoch: [37] [1710/2639] eta: 0:47:17 lr: 3.902574073948781e-06 loss: 0.0321 (0.0304) time: 3.0185 data: 0.0093 max mem: 33370 +Epoch: [37] [1720/2639] eta: 0:46:46 lr: 3.896914067807333e-06 loss: 0.0306 (0.0304) time: 2.9923 data: 0.0092 max mem: 33370 +Epoch: [37] [1730/2639] eta: 0:46:16 lr: 3.8912531480981866e-06 loss: 0.0275 (0.0304) time: 3.0273 data: 0.0092 max mem: 33370 +Epoch: [37] [1740/2639] eta: 0:45:45 lr: 3.885591313196684e-06 loss: 0.0261 (0.0303) time: 3.0744 data: 0.0093 max mem: 33370 +Epoch: [37] [1750/2639] eta: 0:45:15 lr: 3.879928561472665e-06 loss: 0.0254 (0.0303) time: 3.0884 data: 0.0096 max mem: 33370 +Epoch: [37] [1760/2639] eta: 0:44:44 lr: 3.8742648912903935e-06 loss: 0.0254 (0.0303) time: 3.0027 data: 0.0095 max mem: 33370 +Epoch: [37] [1770/2639] eta: 0:44:13 lr: 3.868600301008577e-06 loss: 0.0273 (0.0303) time: 2.9458 data: 0.0094 max mem: 33370 +Epoch: [37] [1780/2639] eta: 0:43:42 lr: 3.862934788980291e-06 loss: 0.0259 (0.0303) time: 3.0056 data: 0.0095 max mem: 33370 +Epoch: [37] [1790/2639] eta: 0:43:11 lr: 3.8572683535529975e-06 loss: 0.0237 (0.0302) time: 3.0220 data: 0.0092 max mem: 33370 +Epoch: [37] [1800/2639] eta: 0:42:41 lr: 3.851600993068468e-06 loss: 0.0237 (0.0302) time: 3.0574 data: 0.0088 max mem: 33370 +Epoch: [37] [1810/2639] eta: 0:42:11 lr: 3.845932705862806e-06 loss: 0.0296 (0.0302) time: 3.1131 data: 0.0086 max mem: 33370 +Epoch: [37] [1820/2639] eta: 0:41:41 lr: 3.840263490266366e-06 loss: 0.0276 (0.0302) time: 3.1145 data: 0.0088 max mem: 33370 +Epoch: [37] [1830/2639] eta: 0:41:10 lr: 3.834593344603778e-06 loss: 0.0267 (0.0302) time: 3.1182 data: 0.0087 max mem: 33370 +Epoch: [37] [1840/2639] eta: 0:40:40 lr: 3.82892226719386e-06 loss: 0.0312 (0.0302) time: 3.0991 data: 0.0086 max mem: 33370 +Epoch: [37] [1850/2639] eta: 0:40:09 lr: 3.8232502563496496e-06 loss: 0.0300 (0.0302) time: 3.0595 data: 0.0091 max mem: 33370 +Epoch: [37] [1860/2639] eta: 0:39:39 lr: 3.817577310378315e-06 loss: 0.0236 (0.0302) time: 3.0925 data: 0.0097 max mem: 33370 +Epoch: [37] [1870/2639] eta: 0:39:09 lr: 3.8119034275811825e-06 loss: 0.0253 (0.0302) time: 3.1241 data: 0.0092 max mem: 33370 +Epoch: [37] [1880/2639] eta: 0:38:38 lr: 3.8062286062536477e-06 loss: 0.0257 (0.0302) time: 3.0870 data: 0.0086 max mem: 33370 +Epoch: [37] [1890/2639] eta: 0:38:08 lr: 3.8005528446852053e-06 loss: 0.0276 (0.0302) time: 3.0770 data: 0.0093 max mem: 33370 +Epoch: [37] [1900/2639] eta: 0:37:37 lr: 3.7948761411593604e-06 loss: 0.0288 (0.0302) time: 3.0544 data: 0.0094 max mem: 33370 +Epoch: [37] [1910/2639] eta: 0:37:07 lr: 3.7891984939536456e-06 loss: 0.0275 (0.0302) time: 3.0533 data: 0.0093 max mem: 33370 +Epoch: [37] [1920/2639] eta: 0:36:37 lr: 3.7835199013395695e-06 loss: 0.0262 (0.0302) time: 3.1031 data: 0.0094 max mem: 33370 +Epoch: [37] [1930/2639] eta: 0:36:06 lr: 3.777840361582569e-06 loss: 0.0262 (0.0302) time: 3.1161 data: 0.0090 max mem: 33370 +Epoch: [37] [1940/2639] eta: 0:35:36 lr: 3.7721598729420207e-06 loss: 0.0294 (0.0302) time: 3.1000 data: 0.0089 max mem: 33370 +Epoch: [37] [1950/2639] eta: 0:35:05 lr: 3.766478433671157e-06 loss: 0.0294 (0.0302) time: 3.1057 data: 0.0087 max mem: 33370 +Epoch: [37] [1960/2639] eta: 0:34:35 lr: 3.7607960420170875e-06 loss: 0.0284 (0.0302) time: 3.1002 data: 0.0090 max mem: 33370 +Epoch: [37] [1970/2639] eta: 0:34:04 lr: 3.755112696220716e-06 loss: 0.0292 (0.0302) time: 3.0888 data: 0.0092 max mem: 33370 +Epoch: [37] [1980/2639] eta: 0:33:34 lr: 3.749428394516757e-06 loss: 0.0281 (0.0302) time: 3.0798 data: 0.0088 max mem: 33370 +Epoch: [37] [1990/2639] eta: 0:33:03 lr: 3.743743135133655e-06 loss: 0.0280 (0.0302) time: 3.0521 data: 0.0087 max mem: 33370 +Epoch: [37] [2000/2639] eta: 0:32:33 lr: 3.738056916293602e-06 loss: 0.0300 (0.0302) time: 3.0913 data: 0.0089 max mem: 33370 +Epoch: [37] [2010/2639] eta: 0:32:03 lr: 3.7323697362124523e-06 loss: 0.0303 (0.0302) time: 3.1312 data: 0.0089 max mem: 33370 +Epoch: [37] [2020/2639] eta: 0:31:32 lr: 3.7266815930997422e-06 loss: 0.0290 (0.0302) time: 3.0842 data: 0.0093 max mem: 33370 +Epoch: [37] [2030/2639] eta: 0:31:02 lr: 3.7209924851586025e-06 loss: 0.0290 (0.0302) time: 3.0726 data: 0.0094 max mem: 33370 +Epoch: [37] [2040/2639] eta: 0:30:31 lr: 3.7153024105857816e-06 loss: 0.0285 (0.0302) time: 3.0884 data: 0.0088 max mem: 33370 +Epoch: [37] [2050/2639] eta: 0:30:00 lr: 3.709611367571554e-06 loss: 0.0261 (0.0302) time: 3.0463 data: 0.0091 max mem: 33370 +Epoch: [37] [2060/2639] eta: 0:29:30 lr: 3.7039193542997433e-06 loss: 0.0277 (0.0302) time: 3.0062 data: 0.0096 max mem: 33370 +Epoch: [37] [2070/2639] eta: 0:28:59 lr: 3.698226368947632e-06 loss: 0.0274 (0.0302) time: 3.0448 data: 0.0093 max mem: 33370 +Epoch: [37] [2080/2639] eta: 0:28:29 lr: 3.69253240968598e-06 loss: 0.0271 (0.0302) time: 3.1002 data: 0.0092 max mem: 33370 +Epoch: [37] [2090/2639] eta: 0:27:58 lr: 3.6868374746789407e-06 loss: 0.0271 (0.0302) time: 3.1274 data: 0.0089 max mem: 33370 +Epoch: [37] [2100/2639] eta: 0:27:28 lr: 3.6811415620840735e-06 loss: 0.0305 (0.0302) time: 3.1353 data: 0.0087 max mem: 33370 +Epoch: [37] [2110/2639] eta: 0:26:58 lr: 3.675444670052259e-06 loss: 0.0311 (0.0302) time: 3.1168 data: 0.0090 max mem: 33370 +Epoch: [37] [2120/2639] eta: 0:26:27 lr: 3.6697467967277154e-06 loss: 0.0298 (0.0302) time: 3.0904 data: 0.0090 max mem: 33370 +Epoch: [37] [2130/2639] eta: 0:25:56 lr: 3.664047940247911e-06 loss: 0.0269 (0.0302) time: 3.0725 data: 0.0091 max mem: 33370 +Epoch: [37] [2140/2639] eta: 0:25:26 lr: 3.6583480987435784e-06 loss: 0.0272 (0.0302) time: 3.0715 data: 0.0091 max mem: 33370 +Epoch: [37] [2150/2639] eta: 0:24:55 lr: 3.652647270338628e-06 loss: 0.0272 (0.0302) time: 3.0840 data: 0.0088 max mem: 33370 +Epoch: [37] [2160/2639] eta: 0:24:25 lr: 3.646945453150156e-06 loss: 0.0276 (0.0302) time: 3.0935 data: 0.0088 max mem: 33370 +Epoch: [37] [2170/2639] eta: 0:23:54 lr: 3.6412426452883897e-06 loss: 0.0273 (0.0302) time: 3.0933 data: 0.0092 max mem: 33370 +Epoch: [37] [2180/2639] eta: 0:23:24 lr: 3.6355388448566278e-06 loss: 0.0274 (0.0302) time: 3.1041 data: 0.0091 max mem: 33370 +Epoch: [37] [2190/2639] eta: 0:22:53 lr: 3.6298340499512516e-06 loss: 0.0252 (0.0302) time: 3.0591 data: 0.0094 max mem: 33370 +Epoch: [37] [2200/2639] eta: 0:22:23 lr: 3.624128258661634e-06 loss: 0.0282 (0.0302) time: 3.0404 data: 0.0095 max mem: 33370 +Epoch: [37] [2210/2639] eta: 0:21:52 lr: 3.6184214690701545e-06 loss: 0.0323 (0.0302) time: 3.1170 data: 0.0091 max mem: 33370 +Epoch: [37] [2220/2639] eta: 0:21:22 lr: 3.6127136792521074e-06 loss: 0.0263 (0.0302) time: 3.1415 data: 0.0092 max mem: 33370 +Epoch: [37] [2230/2639] eta: 0:20:51 lr: 3.607004887275717e-06 loss: 0.0271 (0.0302) time: 3.1131 data: 0.0090 max mem: 33370 +Epoch: [37] [2240/2639] eta: 0:20:21 lr: 3.6012950912020455e-06 loss: 0.0271 (0.0302) time: 3.1226 data: 0.0087 max mem: 33370 +Epoch: [37] [2250/2639] eta: 0:19:50 lr: 3.5955842890850087e-06 loss: 0.0288 (0.0302) time: 3.1025 data: 0.0088 max mem: 33370 +Epoch: [37] [2260/2639] eta: 0:19:19 lr: 3.5898724789712796e-06 loss: 0.0312 (0.0302) time: 3.0314 data: 0.0092 max mem: 33370 +Epoch: [37] [2270/2639] eta: 0:18:49 lr: 3.5841596589003087e-06 loss: 0.0302 (0.0302) time: 3.0111 data: 0.0091 max mem: 33370 +Epoch: [37] [2280/2639] eta: 0:18:18 lr: 3.578445826904224e-06 loss: 0.0260 (0.0302) time: 3.0334 data: 0.0089 max mem: 33370 +Epoch: [37] [2290/2639] eta: 0:17:47 lr: 3.5727309810078475e-06 loss: 0.0278 (0.0302) time: 3.0430 data: 0.0089 max mem: 33370 +Epoch: [37] [2300/2639] eta: 0:17:17 lr: 3.5670151192286025e-06 loss: 0.0264 (0.0302) time: 3.0450 data: 0.0089 max mem: 33370 +Epoch: [37] [2310/2639] eta: 0:16:46 lr: 3.5612982395765234e-06 loss: 0.0325 (0.0302) time: 3.0843 data: 0.0087 max mem: 33370 +Epoch: [37] [2320/2639] eta: 0:16:16 lr: 3.555580340054164e-06 loss: 0.0340 (0.0302) time: 3.1188 data: 0.0091 max mem: 33370 +Epoch: [37] [2330/2639] eta: 0:15:45 lr: 3.5498614186566073e-06 loss: 0.0296 (0.0302) time: 3.1217 data: 0.0092 max mem: 33370 +Epoch: [37] [2340/2639] eta: 0:15:15 lr: 3.5441414733713728e-06 loss: 0.0312 (0.0303) time: 3.1256 data: 0.0094 max mem: 33370 +Epoch: [37] [2350/2639] eta: 0:14:44 lr: 3.5384205021784253e-06 loss: 0.0312 (0.0303) time: 3.0727 data: 0.0093 max mem: 33370 +Epoch: [37] [2360/2639] eta: 0:14:13 lr: 3.532698503050081e-06 loss: 0.0266 (0.0303) time: 3.0190 data: 0.0089 max mem: 33370 +Epoch: [37] [2370/2639] eta: 0:13:43 lr: 3.5269754739510204e-06 loss: 0.0288 (0.0303) time: 3.0837 data: 0.0092 max mem: 33370 +Epoch: [37] [2380/2639] eta: 0:13:12 lr: 3.521251412838186e-06 loss: 0.0295 (0.0303) time: 3.1007 data: 0.0094 max mem: 33370 +Epoch: [37] [2390/2639] eta: 0:12:42 lr: 3.5155263176608e-06 loss: 0.0270 (0.0303) time: 3.0703 data: 0.0091 max mem: 33370 +Epoch: [37] [2400/2639] eta: 0:12:11 lr: 3.509800186360261e-06 loss: 0.0271 (0.0303) time: 3.1118 data: 0.0089 max mem: 33370 +Epoch: [37] [2410/2639] eta: 0:11:41 lr: 3.504073016870152e-06 loss: 0.0279 (0.0303) time: 3.1261 data: 0.0089 max mem: 33370 +Epoch: [37] [2420/2639] eta: 0:11:10 lr: 3.498344807116171e-06 loss: 0.0279 (0.0303) time: 3.1141 data: 0.0088 max mem: 33370 +Epoch: [37] [2430/2639] eta: 0:10:39 lr: 3.492615555016071e-06 loss: 0.0284 (0.0303) time: 3.1061 data: 0.0091 max mem: 33370 +Epoch: [37] [2440/2639] eta: 0:10:09 lr: 3.4868852584796613e-06 loss: 0.0269 (0.0303) time: 3.0825 data: 0.0090 max mem: 33370 +Epoch: [37] [2450/2639] eta: 0:09:38 lr: 3.4811539154087066e-06 loss: 0.0262 (0.0303) time: 3.0737 data: 0.0088 max mem: 33370 +Epoch: [37] [2460/2639] eta: 0:09:08 lr: 3.4754215236969366e-06 loss: 0.0281 (0.0303) time: 3.0472 data: 0.0090 max mem: 33370 +Epoch: [37] [2470/2639] eta: 0:08:37 lr: 3.4696880812299473e-06 loss: 0.0318 (0.0303) time: 3.0241 data: 0.0088 max mem: 33370 +Epoch: [37] [2480/2639] eta: 0:08:06 lr: 3.463953585885205e-06 loss: 0.0303 (0.0303) time: 3.0400 data: 0.0091 max mem: 33370 +Epoch: [37] [2490/2639] eta: 0:07:36 lr: 3.4582180355319524e-06 loss: 0.0248 (0.0303) time: 3.0882 data: 0.0096 max mem: 33370 +Epoch: [37] [2500/2639] eta: 0:07:05 lr: 3.452481428031209e-06 loss: 0.0262 (0.0303) time: 3.0923 data: 0.0096 max mem: 33370 +Epoch: [37] [2510/2639] eta: 0:06:35 lr: 3.446743761235674e-06 loss: 0.0252 (0.0303) time: 3.1037 data: 0.0098 max mem: 33370 +Epoch: [37] [2520/2639] eta: 0:06:04 lr: 3.4410050329897315e-06 loss: 0.0247 (0.0303) time: 3.1199 data: 0.0099 max mem: 33370 +Epoch: [37] [2530/2639] eta: 0:05:33 lr: 3.435265241129348e-06 loss: 0.0297 (0.0303) time: 3.0755 data: 0.0094 max mem: 33370 +Epoch: [37] [2540/2639] eta: 0:05:03 lr: 3.4295243834820795e-06 loss: 0.0282 (0.0303) time: 3.0873 data: 0.0097 max mem: 33370 +Epoch: [37] [2550/2639] eta: 0:04:32 lr: 3.423782457866967e-06 loss: 0.0269 (0.0303) time: 3.1009 data: 0.0100 max mem: 33370 +Epoch: [37] [2560/2639] eta: 0:04:01 lr: 3.418039462094544e-06 loss: 0.0263 (0.0303) time: 3.0887 data: 0.0095 max mem: 33370 +Epoch: [37] [2570/2639] eta: 0:03:31 lr: 3.4122953939667293e-06 loss: 0.0281 (0.0303) time: 3.0486 data: 0.0089 max mem: 33370 +Epoch: [37] [2580/2639] eta: 0:03:00 lr: 3.406550251276837e-06 loss: 0.0287 (0.0303) time: 3.0488 data: 0.0090 max mem: 33370 +Epoch: [37] [2590/2639] eta: 0:02:30 lr: 3.4008040318094645e-06 loss: 0.0248 (0.0303) time: 3.0794 data: 0.0091 max mem: 33370 +Epoch: [37] [2600/2639] eta: 0:01:59 lr: 3.3950567333405034e-06 loss: 0.0247 (0.0303) time: 3.1059 data: 0.0088 max mem: 33370 +Epoch: [37] [2610/2639] eta: 0:01:28 lr: 3.389308353637031e-06 loss: 0.0308 (0.0303) time: 3.1149 data: 0.0091 max mem: 33370 +Epoch: [37] [2620/2639] eta: 0:00:58 lr: 3.383558890457312e-06 loss: 0.0313 (0.0303) time: 3.0875 data: 0.0093 max mem: 33370 +Epoch: [37] [2630/2639] eta: 0:00:27 lr: 3.3778083415506957e-06 loss: 0.0274 (0.0303) time: 3.0902 data: 0.0090 max mem: 33370 +Epoch: [37] Total time: 2:14:44 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 2:14:59 time: 3.1478 data: 3.0409 max mem: 33370 +Test: [ 100/2573] eta: 0:04:34 time: 0.0824 data: 0.0018 max mem: 33370 +Test: [ 200/2573] eta: 0:03:50 time: 0.0812 data: 0.0016 max mem: 33370 +Test: [ 300/2573] eta: 0:03:28 time: 0.0837 data: 0.0017 max mem: 33370 +Test: [ 400/2573] eta: 0:03:14 time: 0.0832 data: 0.0016 max mem: 33370 +Test: [ 500/2573] eta: 0:03:02 time: 0.0855 data: 0.0017 max mem: 33370 +Test: [ 600/2573] eta: 0:02:52 time: 0.0835 data: 0.0018 max mem: 33370 +Test: [ 700/2573] eta: 0:02:42 time: 0.0838 data: 0.0019 max mem: 33370 +Test: [ 800/2573] eta: 0:02:33 time: 0.0856 data: 0.0016 max mem: 33370 +Test: [ 900/2573] eta: 0:02:24 time: 0.0844 data: 0.0018 max mem: 33370 +Test: [1000/2573] eta: 0:02:15 time: 0.0839 data: 0.0016 max mem: 33370 +Test: [1100/2573] eta: 0:02:06 time: 0.0836 data: 0.0017 max mem: 33370 +Test: [1200/2573] eta: 0:01:57 time: 0.0811 data: 0.0015 max mem: 33370 +Test: [1300/2573] eta: 0:01:48 time: 0.0827 data: 0.0015 max mem: 33370 +Test: [1400/2573] eta: 0:01:39 time: 0.0818 data: 0.0016 max mem: 33370 +Test: [1500/2573] eta: 0:01:30 time: 0.0816 data: 0.0017 max mem: 33370 +Test: [1600/2573] eta: 0:01:22 time: 0.0852 data: 0.0017 max mem: 33370 +Test: [1700/2573] eta: 0:01:13 time: 0.0815 data: 0.0016 max mem: 33370 +Test: [1800/2573] eta: 0:01:05 time: 0.0835 data: 0.0016 max mem: 33370 +Test: [1900/2573] eta: 0:00:56 time: 0.0808 data: 0.0016 max mem: 33370 +Test: [2000/2573] eta: 0:00:48 time: 0.0837 data: 0.0015 max mem: 33370 +Test: [2100/2573] eta: 0:00:39 time: 0.0843 data: 0.0015 max mem: 33370 +Test: [2200/2573] eta: 0:00:31 time: 0.0841 data: 0.0017 max mem: 33370 +Test: [2300/2573] eta: 0:00:22 time: 0.0842 data: 0.0016 max mem: 33370 +Test: [2400/2573] eta: 0:00:14 time: 0.0796 data: 0.0016 max mem: 33370 +Test: [2500/2573] eta: 0:00:06 time: 0.0825 data: 0.0017 max mem: 33370 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: Total time: 0:03:37 +Final results: +Mean IoU is 64.64 + + precision@0.5 = 72.83 + precision@0.6 = 67.79 + precision@0.7 = 61.15 + precision@0.8 = 49.90 + precision@0.9 = 26.04 + overall IoU = 61.92 + +Average object IoU 64.64090762149513 +Overall IoU 61.92380142211914 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [38] [ 0/2639] eta: 4:10:16 lr: 3.3726319173708947e-06 loss: 0.0172 (0.0172) time: 5.6900 data: 2.5502 max mem: 33370 +Epoch: [38] [ 10/2639] eta: 2:23:38 lr: 3.366879299350617e-06 loss: 0.0286 (0.0275) time: 3.2783 data: 0.2398 max mem: 33370 +Epoch: [38] [ 20/2639] eta: 2:17:36 lr: 3.3611255890258356e-06 loss: 0.0286 (0.0294) time: 3.0256 data: 0.0091 max mem: 33370 +Epoch: [38] [ 30/2639] eta: 2:14:22 lr: 3.3553707841107466e-06 loss: 0.0296 (0.0304) time: 2.9868 data: 0.0098 max mem: 33370 +Epoch: [38] [ 40/2639] eta: 2:13:20 lr: 3.349614882310397e-06 loss: 0.0292 (0.0302) time: 3.0004 data: 0.0094 max mem: 33370 +Epoch: [38] [ 50/2639] eta: 2:13:21 lr: 3.343857881320609e-06 loss: 0.0314 (0.0314) time: 3.0908 data: 0.0092 max mem: 33370 +Epoch: [38] [ 60/2639] eta: 2:13:10 lr: 3.3380997788279757e-06 loss: 0.0311 (0.0307) time: 3.1391 data: 0.0092 max mem: 33370 +Epoch: [38] [ 70/2639] eta: 2:12:15 lr: 3.332340572509748e-06 loss: 0.0279 (0.0303) time: 3.0849 data: 0.0087 max mem: 33370 +Epoch: [38] [ 80/2639] eta: 2:11:50 lr: 3.3265802600338356e-06 loss: 0.0260 (0.0301) time: 3.0693 data: 0.0090 max mem: 33370 +Epoch: [38] [ 90/2639] eta: 2:11:26 lr: 3.320818839058698e-06 loss: 0.0309 (0.0305) time: 3.1124 data: 0.0089 max mem: 33370 +Epoch: [38] [ 100/2639] eta: 2:11:00 lr: 3.315056307233339e-06 loss: 0.0309 (0.0305) time: 3.1148 data: 0.0086 max mem: 33370 +Epoch: [38] [ 110/2639] eta: 2:10:30 lr: 3.3092926621972004e-06 loss: 0.0255 (0.0300) time: 3.1058 data: 0.0088 max mem: 33370 +Epoch: [38] [ 120/2639] eta: 2:10:04 lr: 3.303527901580153e-06 loss: 0.0258 (0.0302) time: 3.1115 data: 0.0089 max mem: 33370 +Epoch: [38] [ 130/2639] eta: 2:09:40 lr: 3.2977620230023903e-06 loss: 0.0307 (0.0302) time: 3.1271 data: 0.0092 max mem: 33370 +Epoch: [38] [ 140/2639] eta: 2:09:11 lr: 3.291995024074423e-06 loss: 0.0285 (0.0302) time: 3.1237 data: 0.0091 max mem: 33370 +Epoch: [38] [ 150/2639] eta: 2:08:31 lr: 3.286226902396962e-06 loss: 0.0273 (0.0299) time: 3.0801 data: 0.0087 max mem: 33370 +Epoch: [38] [ 160/2639] eta: 2:07:52 lr: 3.28045765556092e-06 loss: 0.0279 (0.0299) time: 3.0468 data: 0.0086 max mem: 33370 +Epoch: [38] [ 170/2639] eta: 2:07:02 lr: 3.274687281147294e-06 loss: 0.0292 (0.0300) time: 3.0059 data: 0.0089 max mem: 33370 +Epoch: [38] [ 180/2639] eta: 2:06:15 lr: 3.2689157767271606e-06 loss: 0.0259 (0.0297) time: 2.9655 data: 0.0094 max mem: 33370 +Epoch: [38] [ 190/2639] eta: 2:05:48 lr: 3.2631431398615596e-06 loss: 0.0245 (0.0296) time: 3.0390 data: 0.0095 max mem: 33370 +Epoch: [38] [ 200/2639] eta: 2:05:20 lr: 3.257369368101489e-06 loss: 0.0277 (0.0298) time: 3.1083 data: 0.0091 max mem: 33370 +Epoch: [38] [ 210/2639] eta: 2:04:50 lr: 3.251594458987791e-06 loss: 0.0337 (0.0301) time: 3.0966 data: 0.0090 max mem: 33370 +Epoch: [38] [ 220/2639] eta: 2:04:15 lr: 3.245818410051138e-06 loss: 0.0344 (0.0302) time: 3.0689 data: 0.0094 max mem: 33370 +Epoch: [38] [ 230/2639] eta: 2:03:51 lr: 3.2400412188119227e-06 loss: 0.0279 (0.0302) time: 3.0957 data: 0.0095 max mem: 33370 +Epoch: [38] [ 240/2639] eta: 2:03:19 lr: 3.2342628827802464e-06 loss: 0.0256 (0.0301) time: 3.1110 data: 0.0094 max mem: 33370 +Epoch: [38] [ 250/2639] eta: 2:02:49 lr: 3.2284833994558013e-06 loss: 0.0284 (0.0301) time: 3.0866 data: 0.0096 max mem: 33370 +Epoch: [38] [ 260/2639] eta: 2:02:20 lr: 3.222702766327859e-06 loss: 0.0286 (0.0300) time: 3.0944 data: 0.0097 max mem: 33370 +Epoch: [38] [ 270/2639] eta: 2:01:52 lr: 3.2169209808751565e-06 loss: 0.0273 (0.0300) time: 3.1090 data: 0.0095 max mem: 33370 +Epoch: [38] [ 280/2639] eta: 2:01:31 lr: 3.211138040565874e-06 loss: 0.0256 (0.0299) time: 3.1636 data: 0.0093 max mem: 33370 +Epoch: [38] [ 290/2639] eta: 2:00:55 lr: 3.2053539428575495e-06 loss: 0.0245 (0.0299) time: 3.1207 data: 0.0096 max mem: 33370 +Epoch: [38] [ 300/2639] eta: 2:00:22 lr: 3.1995686851969958e-06 loss: 0.0273 (0.0299) time: 3.0416 data: 0.0096 max mem: 33370 +Epoch: [38] [ 310/2639] eta: 1:59:49 lr: 3.1937822650202764e-06 loss: 0.0279 (0.0298) time: 3.0580 data: 0.0097 max mem: 33370 +Epoch: [38] [ 320/2639] eta: 1:59:21 lr: 3.1879946797525893e-06 loss: 0.0272 (0.0298) time: 3.0980 data: 0.0099 max mem: 33370 +Epoch: [38] [ 330/2639] eta: 1:58:48 lr: 3.182205926808247e-06 loss: 0.0287 (0.0297) time: 3.0949 data: 0.0094 max mem: 33370 +Epoch: [38] [ 340/2639] eta: 1:58:22 lr: 3.1764160035905614e-06 loss: 0.0267 (0.0296) time: 3.1096 data: 0.0090 max mem: 33370 +Epoch: [38] [ 350/2639] eta: 1:57:56 lr: 3.1706249074918216e-06 loss: 0.0259 (0.0296) time: 3.1555 data: 0.0093 max mem: 33370 +Epoch: [38] [ 360/2639] eta: 1:57:28 lr: 3.164832635893176e-06 loss: 0.0296 (0.0297) time: 3.1486 data: 0.0094 max mem: 33370 +Epoch: [38] [ 370/2639] eta: 1:57:03 lr: 3.1590391861646126e-06 loss: 0.0287 (0.0296) time: 3.1632 data: 0.0091 max mem: 33370 +Epoch: [38] [ 380/2639] eta: 1:56:36 lr: 3.1532445556648367e-06 loss: 0.0264 (0.0296) time: 3.1767 data: 0.0090 max mem: 33370 +Epoch: [38] [ 390/2639] eta: 1:56:05 lr: 3.147448741741253e-06 loss: 0.0278 (0.0296) time: 3.1365 data: 0.0088 max mem: 33370 +Epoch: [38] [ 400/2639] eta: 1:55:38 lr: 3.1416517417298397e-06 loss: 0.0235 (0.0294) time: 3.1293 data: 0.0086 max mem: 33370 +Epoch: [38] [ 410/2639] eta: 1:55:08 lr: 3.135853552955127e-06 loss: 0.0235 (0.0295) time: 3.1427 data: 0.0085 max mem: 33370 +Epoch: [38] [ 420/2639] eta: 1:54:39 lr: 3.1300541727300773e-06 loss: 0.0303 (0.0296) time: 3.1275 data: 0.0088 max mem: 33370 +Epoch: [38] [ 430/2639] eta: 1:54:10 lr: 3.124253598356056e-06 loss: 0.0303 (0.0296) time: 3.1388 data: 0.0090 max mem: 33370 +Epoch: [38] [ 440/2639] eta: 1:53:41 lr: 3.1184518271227128e-06 loss: 0.0261 (0.0297) time: 3.1456 data: 0.0087 max mem: 33370 +Epoch: [38] [ 450/2639] eta: 1:53:11 lr: 3.112648856307953e-06 loss: 0.0259 (0.0296) time: 3.1277 data: 0.0085 max mem: 33370 +Epoch: [38] [ 460/2639] eta: 1:52:37 lr: 3.106844683177812e-06 loss: 0.0258 (0.0295) time: 3.0743 data: 0.0086 max mem: 33370 +Epoch: [38] [ 470/2639] eta: 1:52:04 lr: 3.1010393049864333e-06 loss: 0.0263 (0.0296) time: 3.0445 data: 0.0095 max mem: 33370 +Epoch: [38] [ 480/2639] eta: 1:51:30 lr: 3.0952327189759343e-06 loss: 0.0263 (0.0295) time: 3.0548 data: 0.0098 max mem: 33370 +Epoch: [38] [ 490/2639] eta: 1:50:58 lr: 3.0894249223763867e-06 loss: 0.0244 (0.0294) time: 3.0583 data: 0.0097 max mem: 33370 +Epoch: [38] [ 500/2639] eta: 1:50:23 lr: 3.083615912405681e-06 loss: 0.0248 (0.0295) time: 3.0402 data: 0.0100 max mem: 33370 +Epoch: [38] [ 510/2639] eta: 1:49:52 lr: 3.0778056862695044e-06 loss: 0.0276 (0.0295) time: 3.0517 data: 0.0094 max mem: 33370 +Epoch: [38] [ 520/2639] eta: 1:49:20 lr: 3.0719942411612054e-06 loss: 0.0276 (0.0296) time: 3.0752 data: 0.0093 max mem: 33370 +Epoch: [38] [ 530/2639] eta: 1:48:43 lr: 3.0661815742617605e-06 loss: 0.0295 (0.0296) time: 3.0039 data: 0.0095 max mem: 33370 +Epoch: [38] [ 540/2639] eta: 1:48:08 lr: 3.0603676827396764e-06 loss: 0.0249 (0.0296) time: 2.9699 data: 0.0095 max mem: 33370 +Epoch: [38] [ 550/2639] eta: 1:47:31 lr: 3.054552563750883e-06 loss: 0.0259 (0.0296) time: 2.9647 data: 0.0090 max mem: 33370 +Epoch: [38] [ 560/2639] eta: 1:46:59 lr: 3.0487362144387025e-06 loss: 0.0285 (0.0297) time: 2.9923 data: 0.0090 max mem: 33370 +Epoch: [38] [ 570/2639] eta: 1:46:28 lr: 3.04291863193371e-06 loss: 0.0282 (0.0296) time: 3.0652 data: 0.0091 max mem: 33370 +Epoch: [38] [ 580/2639] eta: 1:45:56 lr: 3.037099813353705e-06 loss: 0.0282 (0.0297) time: 3.0770 data: 0.0091 max mem: 33370 +Epoch: [38] [ 590/2639] eta: 1:45:26 lr: 3.031279755803572e-06 loss: 0.0278 (0.0297) time: 3.0840 data: 0.0095 max mem: 33370 +Epoch: [38] [ 600/2639] eta: 1:45:00 lr: 3.0254584563752497e-06 loss: 0.0296 (0.0297) time: 3.1728 data: 0.0104 max mem: 33370 +Epoch: [38] [ 610/2639] eta: 1:44:30 lr: 3.0196359121475918e-06 loss: 0.0303 (0.0297) time: 3.1724 data: 0.0100 max mem: 33370 +Epoch: [38] [ 620/2639] eta: 1:43:55 lr: 3.0138121201863318e-06 loss: 0.0285 (0.0297) time: 3.0354 data: 0.0094 max mem: 33370 +Epoch: [38] [ 630/2639] eta: 1:43:17 lr: 3.007987077543944e-06 loss: 0.0275 (0.0297) time: 2.9268 data: 0.0091 max mem: 33370 +Epoch: [38] [ 640/2639] eta: 1:42:46 lr: 3.002160781259609e-06 loss: 0.0275 (0.0297) time: 2.9649 data: 0.0090 max mem: 33370 +Epoch: [38] [ 650/2639] eta: 1:42:16 lr: 2.996333228359069e-06 loss: 0.0290 (0.0297) time: 3.0975 data: 0.0094 max mem: 33370 +Epoch: [38] [ 660/2639] eta: 1:41:47 lr: 2.9905044158545923e-06 loss: 0.0290 (0.0297) time: 3.1337 data: 0.0092 max mem: 33370 +Epoch: [38] [ 670/2639] eta: 1:41:16 lr: 2.984674340744831e-06 loss: 0.0267 (0.0297) time: 3.1153 data: 0.0093 max mem: 33370 +Epoch: [38] [ 680/2639] eta: 1:40:50 lr: 2.9788430000147798e-06 loss: 0.0264 (0.0297) time: 3.1652 data: 0.0093 max mem: 33370 +Epoch: [38] [ 690/2639] eta: 1:40:21 lr: 2.9730103906356334e-06 loss: 0.0252 (0.0296) time: 3.1910 data: 0.0093 max mem: 33370 +Epoch: [38] [ 700/2639] eta: 1:39:51 lr: 2.9671765095647444e-06 loss: 0.0260 (0.0296) time: 3.1450 data: 0.0090 max mem: 33370 +Epoch: [38] [ 710/2639] eta: 1:39:22 lr: 2.961341353745477e-06 loss: 0.0289 (0.0296) time: 3.1466 data: 0.0090 max mem: 33370 +Epoch: [38] [ 720/2639] eta: 1:38:51 lr: 2.9555049201071666e-06 loss: 0.0283 (0.0296) time: 3.1310 data: 0.0089 max mem: 33370 +Epoch: [38] [ 730/2639] eta: 1:38:19 lr: 2.9496672055649687e-06 loss: 0.0277 (0.0296) time: 3.0738 data: 0.0083 max mem: 33370 +Epoch: [38] [ 740/2639] eta: 1:37:49 lr: 2.9438282070198164e-06 loss: 0.0315 (0.0296) time: 3.0878 data: 0.0086 max mem: 33370 +Epoch: [38] [ 750/2639] eta: 1:37:20 lr: 2.9379879213582714e-06 loss: 0.0281 (0.0296) time: 3.1370 data: 0.0088 max mem: 33370 +Epoch: [38] [ 760/2639] eta: 1:36:51 lr: 2.932146345452477e-06 loss: 0.0261 (0.0296) time: 3.1649 data: 0.0085 max mem: 33370 +Epoch: [38] [ 770/2639] eta: 1:36:22 lr: 2.926303476160006e-06 loss: 0.0256 (0.0296) time: 3.1711 data: 0.0089 max mem: 33370 +Epoch: [38] [ 780/2639] eta: 1:35:51 lr: 2.920459310323809e-06 loss: 0.0271 (0.0296) time: 3.1306 data: 0.0091 max mem: 33370 +Epoch: [38] [ 790/2639] eta: 1:35:22 lr: 2.9146138447720907e-06 loss: 0.0260 (0.0296) time: 3.1379 data: 0.0094 max mem: 33370 +Epoch: [38] [ 800/2639] eta: 1:34:51 lr: 2.908767076318191e-06 loss: 0.0270 (0.0296) time: 3.1400 data: 0.0093 max mem: 33370 +Epoch: [38] [ 810/2639] eta: 1:34:19 lr: 2.902919001760526e-06 loss: 0.0258 (0.0295) time: 3.0716 data: 0.0088 max mem: 33370 +Epoch: [38] [ 820/2639] eta: 1:33:47 lr: 2.8970696178824325e-06 loss: 0.0255 (0.0295) time: 3.0342 data: 0.0090 max mem: 33370 +Epoch: [38] [ 830/2639] eta: 1:33:15 lr: 2.8912189214521173e-06 loss: 0.0288 (0.0296) time: 3.0554 data: 0.0093 max mem: 33370 +Epoch: [38] [ 840/2639] eta: 1:32:45 lr: 2.885366909222496e-06 loss: 0.0294 (0.0296) time: 3.1034 data: 0.0090 max mem: 33370 +Epoch: [38] [ 850/2639] eta: 1:32:17 lr: 2.879513577931142e-06 loss: 0.0283 (0.0295) time: 3.1679 data: 0.0086 max mem: 33370 +Epoch: [38] [ 860/2639] eta: 1:31:48 lr: 2.873658924300124e-06 loss: 0.0260 (0.0295) time: 3.2018 data: 0.0091 max mem: 33370 +Epoch: [38] [ 870/2639] eta: 1:31:17 lr: 2.867802945035951e-06 loss: 0.0230 (0.0294) time: 3.1535 data: 0.0096 max mem: 33370 +Epoch: [38] [ 880/2639] eta: 1:30:44 lr: 2.8619456368294096e-06 loss: 0.0248 (0.0294) time: 3.0579 data: 0.0096 max mem: 33370 +Epoch: [38] [ 890/2639] eta: 1:30:15 lr: 2.856086996355507e-06 loss: 0.0248 (0.0294) time: 3.0782 data: 0.0092 max mem: 33370 +Epoch: [38] [ 900/2639] eta: 1:29:41 lr: 2.850227020273305e-06 loss: 0.0250 (0.0294) time: 3.0512 data: 0.0089 max mem: 33370 +Epoch: [38] [ 910/2639] eta: 1:29:08 lr: 2.8443657052258607e-06 loss: 0.0266 (0.0294) time: 2.9725 data: 0.0089 max mem: 33370 +Epoch: [38] [ 920/2639] eta: 1:28:36 lr: 2.8385030478400616e-06 loss: 0.0274 (0.0294) time: 3.0118 data: 0.0091 max mem: 33370 +Epoch: [38] [ 930/2639] eta: 1:28:03 lr: 2.832639044726559e-06 loss: 0.0282 (0.0294) time: 3.0156 data: 0.0092 max mem: 33370 +Epoch: [38] [ 940/2639] eta: 1:27:31 lr: 2.8267736924796054e-06 loss: 0.0278 (0.0294) time: 2.9999 data: 0.0092 max mem: 33370 +Epoch: [38] [ 950/2639] eta: 1:26:57 lr: 2.8209069876769843e-06 loss: 0.0286 (0.0295) time: 2.9829 data: 0.0089 max mem: 33370 +Epoch: [38] [ 960/2639] eta: 1:26:23 lr: 2.8150389268798437e-06 loss: 0.0315 (0.0295) time: 2.9191 data: 0.0085 max mem: 33370 +Epoch: [38] [ 970/2639] eta: 1:25:51 lr: 2.809169506632627e-06 loss: 0.0305 (0.0295) time: 2.9613 data: 0.0089 max mem: 33370 +Epoch: [38] [ 980/2639] eta: 1:25:22 lr: 2.803298723462901e-06 loss: 0.0276 (0.0295) time: 3.0998 data: 0.0096 max mem: 33370 +Epoch: [38] [ 990/2639] eta: 1:24:52 lr: 2.7974265738812864e-06 loss: 0.0310 (0.0295) time: 3.1546 data: 0.0093 max mem: 33370 +Epoch: [38] [1000/2639] eta: 1:24:23 lr: 2.7915530543812824e-06 loss: 0.0310 (0.0295) time: 3.1812 data: 0.0090 max mem: 33370 +Epoch: [38] [1010/2639] eta: 1:23:54 lr: 2.785678161439196e-06 loss: 0.0284 (0.0295) time: 3.2185 data: 0.0092 max mem: 33370 +Epoch: [38] [1020/2639] eta: 1:23:23 lr: 2.779801891513964e-06 loss: 0.0242 (0.0295) time: 3.1409 data: 0.0092 max mem: 33370 +Epoch: [38] [1030/2639] eta: 1:22:54 lr: 2.7739242410470726e-06 loss: 0.0287 (0.0295) time: 3.1251 data: 0.0092 max mem: 33370 +Epoch: [38] [1040/2639] eta: 1:22:23 lr: 2.7680452064624104e-06 loss: 0.0282 (0.0295) time: 3.1621 data: 0.0088 max mem: 33370 +Epoch: [38] [1050/2639] eta: 1:21:53 lr: 2.762164784166119e-06 loss: 0.0263 (0.0295) time: 3.1183 data: 0.0090 max mem: 33370 +Epoch: [38] [1060/2639] eta: 1:21:22 lr: 2.75628297054651e-06 loss: 0.0263 (0.0295) time: 3.1109 data: 0.0093 max mem: 33370 +Epoch: [38] [1070/2639] eta: 1:20:50 lr: 2.750399761973881e-06 loss: 0.0292 (0.0295) time: 3.0752 data: 0.0091 max mem: 33370 +Epoch: [38] [1080/2639] eta: 1:20:18 lr: 2.7445151548004354e-06 loss: 0.0261 (0.0295) time: 3.0186 data: 0.0090 max mem: 33370 +Epoch: [38] [1090/2639] eta: 1:19:47 lr: 2.738629145360096e-06 loss: 0.0282 (0.0295) time: 3.0285 data: 0.0088 max mem: 33370 +Epoch: [38] [1100/2639] eta: 1:19:16 lr: 2.7327417299684223e-06 loss: 0.0282 (0.0295) time: 3.0867 data: 0.0093 max mem: 33370 +Epoch: [38] [1110/2639] eta: 1:18:45 lr: 2.7268529049224214e-06 loss: 0.0271 (0.0295) time: 3.1110 data: 0.0093 max mem: 33370 +Epoch: [38] [1120/2639] eta: 1:18:17 lr: 2.7209626665004632e-06 loss: 0.0271 (0.0295) time: 3.1780 data: 0.0090 max mem: 33370 +Epoch: [38] [1130/2639] eta: 1:17:45 lr: 2.715071010962088e-06 loss: 0.0264 (0.0295) time: 3.1546 data: 0.0093 max mem: 33370 +Epoch: [38] [1140/2639] eta: 1:17:13 lr: 2.7091779345479194e-06 loss: 0.0256 (0.0295) time: 3.0255 data: 0.0090 max mem: 33370 +Epoch: [38] [1150/2639] eta: 1:16:42 lr: 2.703283433479468e-06 loss: 0.0256 (0.0295) time: 3.0227 data: 0.0088 max mem: 33370 +Epoch: [38] [1160/2639] eta: 1:16:10 lr: 2.6973875039590436e-06 loss: 0.0269 (0.0295) time: 3.0620 data: 0.0089 max mem: 33370 +Epoch: [38] [1170/2639] eta: 1:15:39 lr: 2.6914901421695536e-06 loss: 0.0276 (0.0295) time: 3.0536 data: 0.0089 max mem: 33370 +Epoch: [38] [1180/2639] eta: 1:15:08 lr: 2.685591344274414e-06 loss: 0.0276 (0.0295) time: 3.0813 data: 0.0088 max mem: 33370 +Epoch: [38] [1190/2639] eta: 1:14:37 lr: 2.679691106417344e-06 loss: 0.0267 (0.0295) time: 3.1086 data: 0.0086 max mem: 33370 +Epoch: [38] [1200/2639] eta: 1:14:08 lr: 2.6737894247222755e-06 loss: 0.0301 (0.0295) time: 3.1449 data: 0.0087 max mem: 33370 +Epoch: [38] [1210/2639] eta: 1:13:37 lr: 2.667886295293144e-06 loss: 0.0318 (0.0295) time: 3.1296 data: 0.0092 max mem: 33370 +Epoch: [38] [1220/2639] eta: 1:13:06 lr: 2.6619817142137937e-06 loss: 0.0313 (0.0295) time: 3.0885 data: 0.0090 max mem: 33370 +Epoch: [38] [1230/2639] eta: 1:12:35 lr: 2.6560756775477652e-06 loss: 0.0264 (0.0295) time: 3.0967 data: 0.0089 max mem: 33370 +Epoch: [38] [1240/2639] eta: 1:12:04 lr: 2.650168181338201e-06 loss: 0.0260 (0.0295) time: 3.0779 data: 0.0091 max mem: 33370 +Epoch: [38] [1250/2639] eta: 1:11:33 lr: 2.644259221607628e-06 loss: 0.0263 (0.0295) time: 3.0734 data: 0.0089 max mem: 33370 +Epoch: [38] [1260/2639] eta: 1:11:02 lr: 2.6383487943578502e-06 loss: 0.0263 (0.0295) time: 3.0938 data: 0.0088 max mem: 33370 +Epoch: [38] [1270/2639] eta: 1:10:32 lr: 2.6324368955697674e-06 loss: 0.0282 (0.0295) time: 3.1507 data: 0.0093 max mem: 33370 +Epoch: [38] [1280/2639] eta: 1:10:02 lr: 2.6265235212031925e-06 loss: 0.0282 (0.0296) time: 3.1624 data: 0.0095 max mem: 33370 +Epoch: [38] [1290/2639] eta: 1:09:30 lr: 2.6206086671967363e-06 loss: 0.0258 (0.0295) time: 3.0609 data: 0.0094 max mem: 33370 +Epoch: [38] [1300/2639] eta: 1:08:59 lr: 2.6146923294675865e-06 loss: 0.0285 (0.0296) time: 3.0460 data: 0.0095 max mem: 33370 +Epoch: [38] [1310/2639] eta: 1:08:28 lr: 2.608774503911399e-06 loss: 0.0286 (0.0296) time: 3.1079 data: 0.0092 max mem: 33370 +Epoch: [38] [1320/2639] eta: 1:07:58 lr: 2.60285518640207e-06 loss: 0.0273 (0.0296) time: 3.1447 data: 0.0087 max mem: 33370 +Epoch: [38] [1330/2639] eta: 1:07:28 lr: 2.596934372791625e-06 loss: 0.0278 (0.0296) time: 3.1683 data: 0.0088 max mem: 33370 +Epoch: [38] [1340/2639] eta: 1:06:58 lr: 2.5910120589099884e-06 loss: 0.0296 (0.0296) time: 3.1858 data: 0.0092 max mem: 33370 +Epoch: [38] [1350/2639] eta: 1:06:28 lr: 2.585088240564866e-06 loss: 0.0249 (0.0295) time: 3.1787 data: 0.0091 max mem: 33370 +Epoch: [38] [1360/2639] eta: 1:05:57 lr: 2.5791629135415156e-06 loss: 0.0249 (0.0295) time: 3.1470 data: 0.0091 max mem: 33370 +Epoch: [38] [1370/2639] eta: 1:05:27 lr: 2.5732360736026225e-06 loss: 0.0288 (0.0295) time: 3.1806 data: 0.0093 max mem: 33370 +Epoch: [38] [1380/2639] eta: 1:04:57 lr: 2.567307716488066e-06 loss: 0.0303 (0.0295) time: 3.1772 data: 0.0088 max mem: 33370 +Epoch: [38] [1390/2639] eta: 1:04:27 lr: 2.561377837914793e-06 loss: 0.0303 (0.0295) time: 3.1621 data: 0.0082 max mem: 33370 +Epoch: [38] [1400/2639] eta: 1:03:57 lr: 2.555446433576581e-06 loss: 0.0247 (0.0295) time: 3.1943 data: 0.0086 max mem: 33370 +Epoch: [38] [1410/2639] eta: 1:03:26 lr: 2.5495134991439065e-06 loss: 0.0253 (0.0295) time: 3.1628 data: 0.0087 max mem: 33370 +Epoch: [38] [1420/2639] eta: 1:02:56 lr: 2.5435790302637026e-06 loss: 0.0248 (0.0295) time: 3.1494 data: 0.0085 max mem: 33370 +Epoch: [38] [1430/2639] eta: 1:02:25 lr: 2.5376430225592273e-06 loss: 0.0225 (0.0294) time: 3.1443 data: 0.0085 max mem: 33370 +Epoch: [38] [1440/2639] eta: 1:01:54 lr: 2.531705471629816e-06 loss: 0.0225 (0.0294) time: 3.1259 data: 0.0085 max mem: 33370 +Epoch: [38] [1450/2639] eta: 1:01:24 lr: 2.5257663730507427e-06 loss: 0.0281 (0.0295) time: 3.1587 data: 0.0087 max mem: 33370 +Epoch: [38] [1460/2639] eta: 1:00:54 lr: 2.519825722372971e-06 loss: 0.0297 (0.0294) time: 3.1821 data: 0.0086 max mem: 33370 +Epoch: [38] [1470/2639] eta: 1:00:23 lr: 2.513883515123012e-06 loss: 0.0274 (0.0295) time: 3.1846 data: 0.0084 max mem: 33370 +Epoch: [38] [1480/2639] eta: 0:59:53 lr: 2.507939746802668e-06 loss: 0.0251 (0.0294) time: 3.1597 data: 0.0089 max mem: 33370 +Epoch: [38] [1490/2639] eta: 0:59:21 lr: 2.5019944128888895e-06 loss: 0.0237 (0.0294) time: 3.0914 data: 0.0093 max mem: 33370 +Epoch: [38] [1500/2639] eta: 0:58:50 lr: 2.4960475088335133e-06 loss: 0.0271 (0.0294) time: 3.0947 data: 0.0090 max mem: 33370 +Epoch: [38] [1510/2639] eta: 0:58:19 lr: 2.4900990300631046e-06 loss: 0.0256 (0.0294) time: 3.0999 data: 0.0088 max mem: 33370 +Epoch: [38] [1520/2639] eta: 0:57:47 lr: 2.4841489719787325e-06 loss: 0.0271 (0.0294) time: 3.0301 data: 0.0088 max mem: 33370 +Epoch: [38] [1530/2639] eta: 0:57:16 lr: 2.478197329955733e-06 loss: 0.0275 (0.0294) time: 3.0406 data: 0.0089 max mem: 33370 +Epoch: [38] [1540/2639] eta: 0:56:45 lr: 2.4722440993435483e-06 loss: 0.0264 (0.0294) time: 3.0323 data: 0.0090 max mem: 33370 +Epoch: [38] [1550/2639] eta: 0:56:12 lr: 2.4662892754654566e-06 loss: 0.0280 (0.0294) time: 2.9657 data: 0.0087 max mem: 33370 +Epoch: [38] [1560/2639] eta: 0:55:41 lr: 2.460332853618407e-06 loss: 0.0321 (0.0294) time: 2.9912 data: 0.0086 max mem: 33370 +Epoch: [38] [1570/2639] eta: 0:55:11 lr: 2.4543748290727477e-06 loss: 0.0299 (0.0294) time: 3.1127 data: 0.0088 max mem: 33370 +Epoch: [38] [1580/2639] eta: 0:54:40 lr: 2.4484151970720576e-06 loss: 0.0271 (0.0294) time: 3.1573 data: 0.0088 max mem: 33370 +Epoch: [38] [1590/2639] eta: 0:54:09 lr: 2.442453952832866e-06 loss: 0.0254 (0.0294) time: 3.1521 data: 0.0089 max mem: 33370 +Epoch: [38] [1600/2639] eta: 0:53:38 lr: 2.4364910915444807e-06 loss: 0.0268 (0.0294) time: 3.1100 data: 0.0090 max mem: 33370 +Epoch: [38] [1610/2639] eta: 0:53:07 lr: 2.4305266083687035e-06 loss: 0.0253 (0.0294) time: 3.0256 data: 0.0092 max mem: 33370 +Epoch: [38] [1620/2639] eta: 0:52:36 lr: 2.424560498439653e-06 loss: 0.0260 (0.0294) time: 3.0505 data: 0.0094 max mem: 33370 +Epoch: [38] [1630/2639] eta: 0:52:05 lr: 2.418592756863474e-06 loss: 0.0287 (0.0294) time: 3.1138 data: 0.0090 max mem: 33370 +Epoch: [38] [1640/2639] eta: 0:51:34 lr: 2.4126233787181555e-06 loss: 0.0255 (0.0294) time: 3.1252 data: 0.0087 max mem: 33370 +Epoch: [38] [1650/2639] eta: 0:51:03 lr: 2.4066523590532354e-06 loss: 0.0251 (0.0294) time: 3.1176 data: 0.0088 max mem: 33370 +Epoch: [38] [1660/2639] eta: 0:50:32 lr: 2.4006796928896126e-06 loss: 0.0260 (0.0294) time: 3.1063 data: 0.0086 max mem: 33370 +Epoch: [38] [1670/2639] eta: 0:50:01 lr: 2.394705375219245e-06 loss: 0.0269 (0.0294) time: 3.1203 data: 0.0085 max mem: 33370 +Epoch: [38] [1680/2639] eta: 0:49:30 lr: 2.388729401004959e-06 loss: 0.0263 (0.0293) time: 3.1222 data: 0.0087 max mem: 33370 +Epoch: [38] [1690/2639] eta: 0:49:00 lr: 2.3827517651801386e-06 loss: 0.0278 (0.0294) time: 3.1258 data: 0.0086 max mem: 33370 +Epoch: [38] [1700/2639] eta: 0:48:29 lr: 2.3767724626485313e-06 loss: 0.0308 (0.0294) time: 3.1629 data: 0.0085 max mem: 33370 +Epoch: [38] [1710/2639] eta: 0:47:58 lr: 2.3707914882839312e-06 loss: 0.0305 (0.0294) time: 3.1354 data: 0.0088 max mem: 33370 +Epoch: [38] [1720/2639] eta: 0:47:27 lr: 2.3648088369299787e-06 loss: 0.0261 (0.0294) time: 3.0936 data: 0.0093 max mem: 33370 +Epoch: [38] [1730/2639] eta: 0:46:57 lr: 2.358824503399837e-06 loss: 0.0270 (0.0294) time: 3.1337 data: 0.0095 max mem: 33370 +Epoch: [38] [1740/2639] eta: 0:46:26 lr: 2.3528384824759857e-06 loss: 0.0282 (0.0294) time: 3.1331 data: 0.0089 max mem: 33370 +Epoch: [38] [1750/2639] eta: 0:45:55 lr: 2.346850768909894e-06 loss: 0.0309 (0.0294) time: 3.1403 data: 0.0084 max mem: 33370 +Epoch: [38] [1760/2639] eta: 0:45:24 lr: 2.3408613574217972e-06 loss: 0.0309 (0.0294) time: 3.1282 data: 0.0087 max mem: 33370 +Epoch: [38] [1770/2639] eta: 0:44:53 lr: 2.3348702427004007e-06 loss: 0.0342 (0.0295) time: 3.0573 data: 0.0096 max mem: 33370 +Epoch: [38] [1780/2639] eta: 0:44:21 lr: 2.3288774194025806e-06 loss: 0.0297 (0.0295) time: 3.0577 data: 0.0094 max mem: 33370 +Epoch: [38] [1790/2639] eta: 0:43:51 lr: 2.322882882153149e-06 loss: 0.0292 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2.2748642260561075e-06 loss: 0.0287 (0.0295) time: 3.1230 data: 0.0094 max mem: 33370 +Epoch: [38] [1880/2639] eta: 0:39:13 lr: 2.2688540159190915e-06 loss: 0.0262 (0.0294) time: 3.0647 data: 0.0095 max mem: 33370 +Epoch: [38] [1890/2639] eta: 0:38:42 lr: 2.262842036248972e-06 loss: 0.0259 (0.0294) time: 2.9726 data: 0.0095 max mem: 33370 +Epoch: [38] [1900/2639] eta: 0:38:11 lr: 2.2568282812979368e-06 loss: 0.0276 (0.0294) time: 3.0478 data: 0.0092 max mem: 33370 +Epoch: [38] [1910/2639] eta: 0:37:40 lr: 2.2508127452824517e-06 loss: 0.0253 (0.0294) time: 3.1201 data: 0.0086 max mem: 33370 +Epoch: [38] [1920/2639] eta: 0:37:09 lr: 2.244795422382879e-06 loss: 0.0248 (0.0294) time: 3.0833 data: 0.0084 max mem: 33370 +Epoch: [38] [1930/2639] eta: 0:36:37 lr: 2.2387763067431967e-06 loss: 0.0269 (0.0294) time: 3.0392 data: 0.0084 max mem: 33370 +Epoch: [38] [1940/2639] eta: 0:36:07 lr: 2.2327553924706077e-06 loss: 0.0276 (0.0294) time: 3.0720 data: 0.0089 max mem: 33370 +Epoch: [38] [1950/2639] eta: 0:35:35 lr: 2.2267326736352527e-06 loss: 0.0276 (0.0294) time: 3.0650 data: 0.0096 max mem: 33370 +Epoch: [38] [1960/2639] eta: 0:35:04 lr: 2.220708144269811e-06 loss: 0.0277 (0.0294) time: 3.0055 data: 0.0093 max mem: 33370 +Epoch: [38] [1970/2639] eta: 0:34:33 lr: 2.2146817983692017e-06 loss: 0.0275 (0.0294) time: 3.0489 data: 0.0094 max mem: 33370 +Epoch: [38] [1980/2639] eta: 0:34:02 lr: 2.2086536298901795e-06 loss: 0.0253 (0.0294) time: 3.1348 data: 0.0094 max mem: 33370 +Epoch: [38] [1990/2639] eta: 0:33:31 lr: 2.202623632751028e-06 loss: 0.0256 (0.0294) time: 3.1623 data: 0.0092 max mem: 33370 +Epoch: [38] [2000/2639] eta: 0:33:01 lr: 2.1965918008311424e-06 loss: 0.0248 (0.0294) time: 3.1597 data: 0.0092 max mem: 33370 +Epoch: [38] [2010/2639] eta: 0:32:30 lr: 2.1905581279707087e-06 loss: 0.0256 (0.0294) time: 3.1684 data: 0.0089 max mem: 33370 +Epoch: [38] [2020/2639] eta: 0:31:59 lr: 2.184522607970314e-06 loss: 0.0266 (0.0294) time: 3.1616 data: 0.0088 max mem: 33370 +Epoch: [38] [2030/2639] eta: 0:31:28 lr: 2.1784852345905437e-06 loss: 0.0286 (0.0294) time: 3.1350 data: 0.0089 max mem: 33370 +Epoch: [38] [2040/2639] eta: 0:30:57 lr: 2.172446001551654e-06 loss: 0.0300 (0.0294) time: 3.1439 data: 0.0091 max mem: 33370 +Epoch: [38] [2050/2639] eta: 0:30:26 lr: 2.166404902533126e-06 loss: 0.0251 (0.0294) time: 3.1415 data: 0.0088 max mem: 33370 +Epoch: [38] [2060/2639] eta: 0:29:55 lr: 2.160361931173329e-06 loss: 0.0300 (0.0294) time: 3.1282 data: 0.0085 max mem: 33370 +Epoch: [38] [2070/2639] eta: 0:29:24 lr: 2.154317081069073e-06 loss: 0.0322 (0.0294) time: 3.1301 data: 0.0084 max mem: 33370 +Epoch: [38] [2080/2639] eta: 0:28:53 lr: 2.148270345775258e-06 loss: 0.0271 (0.0294) time: 3.1200 data: 0.0085 max mem: 33370 +Epoch: [38] [2090/2639] eta: 0:28:22 lr: 2.1422217188044147e-06 loss: 0.0270 (0.0294) time: 3.1211 data: 0.0085 max mem: 33370 +Epoch: [38] [2100/2639] eta: 0:27:51 lr: 2.1361711936263465e-06 loss: 0.0257 (0.0294) time: 3.1184 data: 0.0086 max mem: 33370 +Epoch: [38] [2110/2639] eta: 0:27:21 lr: 2.1301187636676578e-06 loss: 0.0296 (0.0294) time: 3.1870 data: 0.0091 max mem: 33370 +Epoch: [38] [2120/2639] eta: 0:26:50 lr: 2.1240644223113846e-06 loss: 0.0278 (0.0294) time: 3.1911 data: 0.0092 max mem: 33370 +Epoch: [38] [2130/2639] eta: 0:26:19 lr: 2.1180081628965154e-06 loss: 0.0240 (0.0294) time: 3.0767 data: 0.0093 max mem: 33370 +Epoch: [38] [2140/2639] eta: 0:25:47 lr: 2.1119499787176087e-06 loss: 0.0279 (0.0294) time: 3.0251 data: 0.0091 max mem: 33370 +Epoch: [38] [2150/2639] eta: 0:25:16 lr: 2.1058898630242986e-06 loss: 0.0272 (0.0294) time: 3.0571 data: 0.0088 max mem: 33370 +Epoch: [38] [2160/2639] eta: 0:24:45 lr: 2.099827809020908e-06 loss: 0.0264 (0.0294) time: 3.1265 data: 0.0091 max mem: 33370 +Epoch: [38] [2170/2639] eta: 0:24:15 lr: 2.093763809865939e-06 loss: 0.0263 (0.0294) time: 3.1791 data: 0.0090 max mem: 33370 +Epoch: [38] [2180/2639] eta: 0:23:43 lr: 2.087697858671673e-06 loss: 0.0279 (0.0294) time: 3.1256 data: 0.0089 max mem: 33370 +Epoch: [38] [2190/2639] eta: 0:23:13 lr: 2.0816299485036516e-06 loss: 0.0283 (0.0294) time: 3.0858 data: 0.0089 max mem: 33370 +Epoch: [38] [2200/2639] eta: 0:22:41 lr: 2.075560072380264e-06 loss: 0.0279 (0.0294) time: 3.0887 data: 0.0090 max mem: 33370 +Epoch: [38] [2210/2639] eta: 0:22:10 lr: 2.0694882232722148e-06 loss: 0.0283 (0.0294) time: 3.0267 data: 0.0092 max mem: 33370 +Epoch: [38] [2220/2639] eta: 0:21:39 lr: 2.063414394102098e-06 loss: 0.0276 (0.0294) time: 3.0543 data: 0.0089 max mem: 33370 +Epoch: [38] [2230/2639] eta: 0:21:08 lr: 2.0573385777438527e-06 loss: 0.0265 (0.0294) time: 3.0606 data: 0.0088 max mem: 33370 +Epoch: [38] [2240/2639] eta: 0:20:37 lr: 2.0512607670223263e-06 loss: 0.0291 (0.0294) time: 2.9759 data: 0.0087 max mem: 33370 +Epoch: [38] [2250/2639] eta: 0:20:06 lr: 2.045180954712714e-06 loss: 0.0308 (0.0294) time: 3.0473 data: 0.0090 max mem: 33370 +Epoch: [38] [2260/2639] eta: 0:19:35 lr: 2.0390991335401023e-06 loss: 0.0311 (0.0295) time: 3.0896 data: 0.0093 max mem: 33370 +Epoch: [38] [2270/2639] eta: 0:19:04 lr: 2.033015296178931e-06 loss: 0.0284 (0.0295) time: 3.0814 data: 0.0093 max mem: 33370 +Epoch: [38] [2280/2639] eta: 0:18:33 lr: 2.02692943525245e-06 loss: 0.0249 (0.0294) time: 3.1356 data: 0.0089 max mem: 33370 +Epoch: [38] [2290/2639] eta: 0:18:02 lr: 2.020841543332241e-06 loss: 0.0266 (0.0295) time: 3.1091 data: 0.0087 max mem: 33370 +Epoch: [38] [2300/2639] eta: 0:17:31 lr: 2.01475161293762e-06 loss: 0.0275 (0.0295) time: 3.0911 data: 0.0095 max mem: 33370 +Epoch: [38] [2310/2639] eta: 0:17:00 lr: 2.0086596365351576e-06 loss: 0.0284 (0.0295) time: 3.1398 data: 0.0093 max mem: 33370 +Epoch: [38] [2320/2639] eta: 0:16:29 lr: 2.0025656065380617e-06 loss: 0.0290 (0.0295) time: 3.1931 data: 0.0088 max mem: 33370 +Epoch: [38] [2330/2639] eta: 0:15:58 lr: 1.9964695153056823e-06 loss: 0.0282 (0.0295) time: 3.1866 data: 0.0088 max mem: 33370 +Epoch: [38] [2340/2639] eta: 0:15:27 lr: 1.990371355142883e-06 loss: 0.0281 (0.0295) time: 3.1475 data: 0.0088 max mem: 33370 +Epoch: [38] [2350/2639] eta: 0:14:56 lr: 1.9842711182995268e-06 loss: 0.0276 (0.0295) time: 3.1515 data: 0.0087 max mem: 33370 +Epoch: [38] [2360/2639] eta: 0:14:25 lr: 1.9781687969698327e-06 loss: 0.0264 (0.0295) time: 3.1719 data: 0.0084 max mem: 33370 +Epoch: [38] [2370/2639] eta: 0:13:54 lr: 1.9720643832918437e-06 loss: 0.0267 (0.0295) time: 3.1781 data: 0.0085 max mem: 33370 +Epoch: [38] [2380/2639] eta: 0:13:23 lr: 1.9659578693467696e-06 loss: 0.0293 (0.0295) time: 3.1950 data: 0.0086 max mem: 33370 +Epoch: [38] [2390/2639] eta: 0:12:52 lr: 1.959849247158437e-06 loss: 0.0293 (0.0295) time: 3.1621 data: 0.0085 max mem: 33370 +Epoch: [38] [2400/2639] eta: 0:12:21 lr: 1.953738508692614e-06 loss: 0.0293 (0.0295) time: 3.1211 data: 0.0083 max mem: 33370 +Epoch: [38] [2410/2639] eta: 0:11:50 lr: 1.947625645856443e-06 loss: 0.0291 (0.0295) time: 3.1278 data: 0.0084 max mem: 33370 +Epoch: [38] [2420/2639] eta: 0:11:19 lr: 1.9415106504977494e-06 loss: 0.0284 (0.0295) time: 3.1027 data: 0.0090 max mem: 33370 +Epoch: [38] [2430/2639] eta: 0:10:48 lr: 1.9353935144044545e-06 loss: 0.0314 (0.0296) time: 3.1154 data: 0.0090 max mem: 33370 +Epoch: [38] [2440/2639] eta: 0:10:17 lr: 1.929274229303866e-06 loss: 0.0320 (0.0296) time: 3.1939 data: 0.0089 max mem: 33370 +Epoch: [38] [2450/2639] eta: 0:09:46 lr: 1.9231527868620742e-06 loss: 0.0273 (0.0296) time: 3.1851 data: 0.0092 max mem: 33370 +Epoch: [38] [2460/2639] eta: 0:09:15 lr: 1.9170291786832204e-06 loss: 0.0274 (0.0296) time: 3.0838 data: 0.0092 max mem: 33370 +Epoch: [38] [2470/2639] eta: 0:08:44 lr: 1.9109033963088755e-06 loss: 0.0274 (0.0296) time: 3.0558 data: 0.0091 max mem: 33370 +Epoch: [38] [2480/2639] eta: 0:08:13 lr: 1.9047754312172892e-06 loss: 0.0255 (0.0295) time: 3.0824 data: 0.0097 max mem: 33370 +Epoch: [38] [2490/2639] eta: 0:07:42 lr: 1.8986452748227469e-06 loss: 0.0255 (0.0295) time: 3.0665 data: 0.0094 max mem: 33370 +Epoch: [38] [2500/2639] eta: 0:07:11 lr: 1.8925129184747998e-06 loss: 0.0267 (0.0295) time: 3.0967 data: 0.0091 max mem: 33370 +Epoch: [38] [2510/2639] eta: 0:06:40 lr: 1.8863783534575924e-06 loss: 0.0279 (0.0295) time: 3.1182 data: 0.0092 max mem: 33370 +Epoch: [38] [2520/2639] eta: 0:06:09 lr: 1.8802415709891094e-06 loss: 0.0289 (0.0295) time: 3.0960 data: 0.0087 max mem: 33370 +Epoch: [38] [2530/2639] eta: 0:05:38 lr: 1.8741025622204079e-06 loss: 0.0302 (0.0296) time: 3.0508 data: 0.0085 max mem: 33370 +Epoch: [38] [2540/2639] eta: 0:05:07 lr: 1.8679613182349138e-06 loss: 0.0284 (0.0296) time: 3.0178 data: 0.0089 max mem: 33370 +Epoch: [38] [2550/2639] eta: 0:04:36 lr: 1.8618178300475973e-06 loss: 0.0263 (0.0296) time: 3.0393 data: 0.0090 max mem: 33370 +Epoch: [38] [2560/2639] eta: 0:04:05 lr: 1.8556720886042537e-06 loss: 0.0296 (0.0296) time: 3.0782 data: 0.0089 max mem: 33370 +Epoch: [38] [2570/2639] eta: 0:03:34 lr: 1.849524084780654e-06 loss: 0.0302 (0.0296) time: 3.0854 data: 0.0090 max mem: 33370 +Epoch: [38] [2580/2639] eta: 0:03:03 lr: 1.8433738093818026e-06 loss: 0.0294 (0.0296) time: 3.1235 data: 0.0094 max mem: 33370 +Epoch: [38] [2590/2639] eta: 0:02:32 lr: 1.837221253141064e-06 loss: 0.0275 (0.0296) time: 3.1485 data: 0.0095 max mem: 33370 +Epoch: [38] [2600/2639] eta: 0:02:01 lr: 1.8310664067193968e-06 loss: 0.0275 (0.0296) time: 3.1314 data: 0.0091 max mem: 33370 +Epoch: [38] [2610/2639] eta: 0:01:30 lr: 1.8249092607044538e-06 loss: 0.0278 (0.0296) time: 3.2237 data: 0.0098 max mem: 33370 +Epoch: [38] [2620/2639] eta: 0:00:58 lr: 1.8187498056097902e-06 loss: 0.0278 (0.0296) time: 3.1625 data: 0.0100 max mem: 33370 +Epoch: [38] [2630/2639] eta: 0:00:27 lr: 1.8125880318739397e-06 loss: 0.0272 (0.0296) time: 3.0360 data: 0.0089 max mem: 33370 +Epoch: [38] Total time: 2:16:30 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 2:57:22 time: 4.1363 data: 4.0316 max mem: 33370 +Test: [ 100/2573] eta: 0:04:53 time: 0.0787 data: 0.0015 max mem: 33370 +Test: [ 200/2573] eta: 0:03:57 time: 0.0798 data: 0.0015 max mem: 33370 +Test: [ 300/2573] eta: 0:03:32 time: 0.0832 data: 0.0015 max mem: 33370 +Test: [ 400/2573] eta: 0:03:16 time: 0.0823 data: 0.0015 max mem: 33370 +Test: [ 500/2573] eta: 0:03:03 time: 0.0812 data: 0.0015 max mem: 33370 +Test: [ 600/2573] eta: 0:02:52 time: 0.0827 data: 0.0018 max mem: 33370 +Test: [ 700/2573] eta: 0:02:42 time: 0.0811 data: 0.0016 max mem: 33370 +Test: [ 800/2573] eta: 0:02:33 time: 0.0855 data: 0.0016 max mem: 33370 +Test: [ 900/2573] eta: 0:02:24 time: 0.0833 data: 0.0017 max mem: 33370 +Test: [1000/2573] eta: 0:02:15 time: 0.0830 data: 0.0016 max mem: 33370 +Test: [1100/2573] eta: 0:02:06 time: 0.0819 data: 0.0017 max mem: 33370 +Test: [1200/2573] eta: 0:01:57 time: 0.0824 data: 0.0016 max mem: 33370 +Test: [1300/2573] eta: 0:01:48 time: 0.0831 data: 0.0017 max mem: 33370 +Test: [1400/2573] eta: 0:01:39 time: 0.0819 data: 0.0017 max mem: 33370 +Test: [1500/2573] eta: 0:01:31 time: 0.0815 data: 0.0016 max mem: 33370 +Test: [1600/2573] eta: 0:01:22 time: 0.0852 data: 0.0016 max mem: 33370 +Test: [1700/2573] eta: 0:01:13 time: 0.0815 data: 0.0016 max mem: 33370 +Test: [1800/2573] eta: 0:01:05 time: 0.0840 data: 0.0016 max mem: 33370 +Test: [1900/2573] eta: 0:00:56 time: 0.0808 data: 0.0016 max mem: 33370 +Test: [2000/2573] eta: 0:00:48 time: 0.0827 data: 0.0017 max mem: 33370 +Test: [2100/2573] eta: 0:00:39 time: 0.0845 data: 0.0016 max mem: 33370 +Test: [2200/2573] eta: 0:00:31 time: 0.0837 data: 0.0016 max mem: 33370 +Test: [2300/2573] eta: 0:00:22 time: 0.0839 data: 0.0016 max mem: 33370 +Test: [2400/2573] eta: 0:00:14 time: 0.0805 data: 0.0016 max mem: 33370 +Test: [2500/2573] eta: 0:00:06 time: 0.0824 data: 0.0016 max mem: 33370 +Test: Total time: 0:03:37 +Final results: +Mean IoU is 64.84 + + precision@0.5 = 72.98 + precision@0.6 = 67.99 + precision@0.7 = 61.38 + precision@0.8 = 50.39 + precision@0.9 = 25.88 + overall IoU = 62.08 + +Average object IoU 64.84495000800756 +Overall IoU 62.083953857421875 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [39] [ 0/2639] eta: 4:34:14 lr: 1.807040445109804e-06 loss: 0.0277 (0.0277) time: 6.2352 data: 2.8841 max mem: 33370 +Epoch: [39] [ 10/2639] eta: 2:26:37 lr: 1.8008742393414706e-06 loss: 0.0251 (0.0256) time: 3.3464 data: 0.2696 max mem: 33370 +Epoch: [39] [ 20/2639] eta: 2:20:25 lr: 1.7947056867714853e-06 loss: 0.0258 (0.0277) time: 3.0660 data: 0.0085 max mem: 33370 +Epoch: [39] [ 30/2639] eta: 2:19:11 lr: 1.78853477753742e-06 loss: 0.0287 (0.0280) time: 3.1213 data: 0.0087 max mem: 33370 +Epoch: [39] [ 40/2639] eta: 2:18:13 lr: 1.7823615016973883e-06 loss: 0.0244 (0.0277) time: 3.1636 data: 0.0085 max mem: 33370 +Epoch: [39] [ 50/2639] eta: 2:17:12 lr: 1.7761858492291547e-06 loss: 0.0244 (0.0282) time: 3.1467 data: 0.0084 max mem: 33370 +Epoch: [39] [ 60/2639] eta: 2:16:12 lr: 1.7700078100291148e-06 loss: 0.0244 (0.0287) time: 3.1237 data: 0.0086 max mem: 33370 +Epoch: [39] [ 70/2639] eta: 2:15:11 lr: 1.7638273739113738e-06 loss: 0.0259 (0.0286) time: 3.1012 data: 0.0090 max mem: 33370 +Epoch: [39] [ 80/2639] eta: 2:14:41 lr: 1.7576445306066953e-06 loss: 0.0272 (0.0286) time: 3.1254 data: 0.0083 max mem: 33370 +Epoch: [39] [ 90/2639] eta: 2:14:22 lr: 1.7514592697615485e-06 loss: 0.0272 (0.0283) time: 3.1816 data: 0.0083 max mem: 33370 +Epoch: [39] [ 100/2639] eta: 2:13:42 lr: 1.7452715809370263e-06 loss: 0.0276 (0.0283) time: 3.1658 data: 0.0087 max mem: 33370 +Epoch: [39] [ 110/2639] eta: 2:12:41 lr: 1.7390814536078575e-06 loss: 0.0276 (0.0281) time: 3.0804 data: 0.0086 max mem: 33370 +Epoch: [39] [ 120/2639] eta: 2:11:45 lr: 1.7328888771612922e-06 loss: 0.0271 (0.0281) time: 3.0300 data: 0.0087 max mem: 33370 +Epoch: [39] [ 130/2639] eta: 2:10:54 lr: 1.7266938408960726e-06 loss: 0.0281 (0.0283) time: 3.0320 data: 0.0090 max mem: 33370 +Epoch: [39] [ 140/2639] eta: 2:09:51 lr: 1.7204963340213202e-06 loss: 0.0274 (0.0283) time: 2.9940 data: 0.0093 max mem: 33370 +Epoch: [39] [ 150/2639] eta: 2:09:10 lr: 1.7142963456553988e-06 loss: 0.0264 (0.0283) time: 3.0049 data: 0.0090 max mem: 33370 +Epoch: [39] [ 160/2639] eta: 2:08:47 lr: 1.7080938648248356e-06 loss: 0.0265 (0.0282) time: 3.1131 data: 0.0090 max mem: 33370 +Epoch: [39] [ 170/2639] eta: 2:08:07 lr: 1.7018888804631143e-06 loss: 0.0265 (0.0282) time: 3.1127 data: 0.0089 max mem: 33370 +Epoch: [39] [ 180/2639] eta: 2:07:33 lr: 1.6956813814095633e-06 loss: 0.0273 (0.0282) time: 3.0730 data: 0.0088 max mem: 33370 +Epoch: [39] [ 190/2639] eta: 2:06:51 lr: 1.6894713564081102e-06 loss: 0.0299 (0.0285) time: 3.0606 data: 0.0093 max mem: 33370 +Epoch: [39] [ 200/2639] eta: 2:06:04 lr: 1.6832587941061316e-06 loss: 0.0300 (0.0285) time: 3.0043 data: 0.0092 max mem: 33370 +Epoch: [39] [ 210/2639] eta: 2:05:27 lr: 1.6770436830531672e-06 loss: 0.0288 (0.0286) time: 3.0131 data: 0.0090 max mem: 33370 +Epoch: [39] [ 220/2639] eta: 2:04:52 lr: 1.6708260116997286e-06 loss: 0.0307 (0.0287) time: 3.0528 data: 0.0090 max mem: 33370 +Epoch: [39] [ 230/2639] eta: 2:04:30 lr: 1.664605768395971e-06 loss: 0.0237 (0.0284) time: 3.1224 data: 0.0088 max mem: 33370 +Epoch: [39] [ 240/2639] eta: 2:03:59 lr: 1.658382941390459e-06 loss: 0.0250 (0.0286) time: 3.1425 data: 0.0090 max mem: 33370 +Epoch: [39] [ 250/2639] eta: 2:03:35 lr: 1.652157518828795e-06 loss: 0.0289 (0.0288) time: 3.1359 data: 0.0095 max mem: 33370 +Epoch: [39] [ 260/2639] eta: 2:03:01 lr: 1.6459294887523402e-06 loss: 0.0296 (0.0288) time: 3.1267 data: 0.0093 max mem: 33370 +Epoch: [39] [ 270/2639] eta: 2:02:21 lr: 1.6396988390967982e-06 loss: 0.0296 (0.0287) time: 3.0403 data: 0.0092 max mem: 33370 +Epoch: [39] [ 280/2639] eta: 2:01:50 lr: 1.6334655576908892e-06 loss: 0.0267 (0.0286) time: 3.0471 data: 0.0092 max mem: 33370 +Epoch: [39] [ 290/2639] eta: 2:01:20 lr: 1.6272296322548834e-06 loss: 0.0279 (0.0286) time: 3.1033 data: 0.0087 max mem: 33370 +Epoch: [39] [ 300/2639] eta: 2:00:35 lr: 1.6209910503992297e-06 loss: 0.0279 (0.0287) time: 3.0134 data: 0.0087 max mem: 33370 +Epoch: [39] [ 310/2639] eta: 1:59:58 lr: 1.6147497996230394e-06 loss: 0.0247 (0.0287) time: 2.9663 data: 0.0089 max mem: 33370 +Epoch: [39] [ 320/2639] eta: 1:59:27 lr: 1.6085058673126616e-06 loss: 0.0247 (0.0286) time: 3.0520 data: 0.0092 max mem: 33370 +Epoch: [39] [ 330/2639] eta: 1:58:59 lr: 1.6022592407401175e-06 loss: 0.0249 (0.0286) time: 3.1117 data: 0.0091 max mem: 33370 +Epoch: [39] [ 340/2639] eta: 1:58:34 lr: 1.5960099070616213e-06 loss: 0.0267 (0.0287) time: 3.1553 data: 0.0089 max mem: 33370 +Epoch: [39] [ 350/2639] eta: 1:58:12 lr: 1.5897578533159603e-06 loss: 0.0281 (0.0287) time: 3.2048 data: 0.0085 max mem: 33370 +Epoch: [39] [ 360/2639] eta: 1:57:41 lr: 1.583503066422962e-06 loss: 0.0273 (0.0287) time: 3.1680 data: 0.0092 max mem: 33370 +Epoch: [39] [ 370/2639] eta: 1:57:11 lr: 1.5772455331818158e-06 loss: 0.0273 (0.0287) time: 3.1021 data: 0.0095 max mem: 33370 +Epoch: [39] [ 380/2639] eta: 1:56:41 lr: 1.570985240269475e-06 loss: 0.0277 (0.0288) time: 3.1147 data: 0.0087 max mem: 33370 +Epoch: [39] [ 390/2639] eta: 1:56:14 lr: 1.5647221742389562e-06 loss: 0.0288 (0.0288) time: 3.1420 data: 0.0085 max mem: 33370 +Epoch: [39] [ 400/2639] eta: 1:55:46 lr: 1.5584563215176094e-06 loss: 0.0289 (0.0291) time: 3.1580 data: 0.0087 max mem: 33370 +Epoch: [39] [ 410/2639] eta: 1:55:18 lr: 1.552187668405425e-06 loss: 0.0242 (0.0290) time: 3.1607 data: 0.0085 max mem: 33370 +Epoch: [39] [ 420/2639] eta: 1:54:52 lr: 1.5459162010732058e-06 loss: 0.0242 (0.0290) time: 3.1783 data: 0.0086 max mem: 33370 +Epoch: [39] [ 430/2639] eta: 1:54:25 lr: 1.5396419055608177e-06 loss: 0.0291 (0.0290) time: 3.1889 data: 0.0092 max mem: 33370 +Epoch: [39] [ 440/2639] eta: 1:53:58 lr: 1.533364767775293e-06 loss: 0.0282 (0.0290) time: 3.1932 data: 0.0090 max mem: 33370 +Epoch: [39] [ 450/2639] eta: 1:53:29 lr: 1.5270847734890161e-06 loss: 0.0289 (0.0291) time: 3.1724 data: 0.0086 max mem: 33370 +Epoch: [39] [ 460/2639] eta: 1:53:01 lr: 1.520801908337754e-06 loss: 0.0301 (0.0291) time: 3.1682 data: 0.0089 max mem: 33370 +Epoch: [39] [ 470/2639] eta: 1:52:27 lr: 1.5145161578187727e-06 loss: 0.0256 (0.0291) time: 3.1170 data: 0.0091 max mem: 33370 +Epoch: [39] [ 480/2639] eta: 1:51:55 lr: 1.5082275072887958e-06 loss: 0.0244 (0.0290) time: 3.0639 data: 0.0092 max mem: 33370 +Epoch: [39] [ 490/2639] eta: 1:51:20 lr: 1.5019359419620458e-06 loss: 0.0266 (0.0290) time: 3.0532 data: 0.0094 max mem: 33370 +Epoch: [39] [ 500/2639] eta: 1:50:48 lr: 1.4956414469081257e-06 loss: 0.0284 (0.0291) time: 3.0586 data: 0.0093 max mem: 33370 +Epoch: [39] [ 510/2639] eta: 1:50:14 lr: 1.4893440070499819e-06 loss: 0.0285 (0.0290) time: 3.0610 data: 0.0089 max mem: 33370 +Epoch: [39] [ 520/2639] eta: 1:49:40 lr: 1.4830436071617089e-06 loss: 0.0253 (0.0290) time: 3.0318 data: 0.0085 max mem: 33370 +Epoch: [39] [ 530/2639] eta: 1:49:06 lr: 1.4767402318664276e-06 loss: 0.0281 (0.0290) time: 3.0356 data: 0.0089 max mem: 33370 +Epoch: [39] [ 540/2639] eta: 1:48:30 lr: 1.4704338656340061e-06 loss: 0.0281 (0.0290) time: 3.0030 data: 0.0094 max mem: 33370 +Epoch: [39] [ 550/2639] eta: 1:47:55 lr: 1.4641244927788546e-06 loss: 0.0281 (0.0290) time: 2.9911 data: 0.0095 max mem: 33370 +Epoch: [39] [ 560/2639] eta: 1:47:21 lr: 1.4578120974575557e-06 loss: 0.0297 (0.0290) time: 3.0163 data: 0.0094 max mem: 33370 +Epoch: [39] [ 570/2639] eta: 1:46:50 lr: 1.451496663666571e-06 loss: 0.0269 (0.0290) time: 3.0520 data: 0.0097 max mem: 33370 +Epoch: [39] [ 580/2639] eta: 1:46:21 lr: 1.4451781752397784e-06 loss: 0.0290 (0.0291) time: 3.1168 data: 0.0096 max mem: 33370 +Epoch: [39] [ 590/2639] eta: 1:45:49 lr: 1.4388566158460838e-06 loss: 0.0353 (0.0292) time: 3.1147 data: 0.0095 max mem: 33370 +Epoch: [39] [ 600/2639] eta: 1:45:18 lr: 1.4325319689868626e-06 loss: 0.0294 (0.0292) time: 3.0857 data: 0.0095 max mem: 33370 +Epoch: [39] [ 610/2639] eta: 1:44:49 lr: 1.4262042179934711e-06 loss: 0.0294 (0.0292) time: 3.1247 data: 0.0092 max mem: 33370 +Epoch: [39] [ 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33370 +Epoch: [39] [ 700/2639] eta: 1:39:55 lr: 1.369111935072674e-06 loss: 0.0261 (0.0293) time: 3.1128 data: 0.0087 max mem: 33370 +Epoch: [39] [ 710/2639] eta: 1:39:28 lr: 1.362752186621071e-06 loss: 0.0251 (0.0293) time: 3.1693 data: 0.0085 max mem: 33370 +Epoch: [39] [ 720/2639] eta: 1:38:59 lr: 1.3563891386736214e-06 loss: 0.0242 (0.0292) time: 3.1996 data: 0.0084 max mem: 33370 +Epoch: [39] [ 730/2639] eta: 1:38:30 lr: 1.3500227723021329e-06 loss: 0.0273 (0.0295) time: 3.1733 data: 0.0083 max mem: 33370 +Epoch: [39] [ 740/2639] eta: 1:38:00 lr: 1.343653068370055e-06 loss: 0.0298 (0.0295) time: 3.1511 data: 0.0083 max mem: 33370 +Epoch: [39] [ 750/2639] eta: 1:37:31 lr: 1.337280007529018e-06 loss: 0.0293 (0.0296) time: 3.1568 data: 0.0090 max mem: 33370 +Epoch: [39] [ 760/2639] eta: 1:37:02 lr: 1.3309035702154111e-06 loss: 0.0283 (0.0295) time: 3.1744 data: 0.0091 max mem: 33370 +Epoch: [39] [ 770/2639] eta: 1:36:33 lr: 1.3245237366467714e-06 loss: 0.0280 (0.0295) time: 3.1750 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mem: 33370 +Epoch: [39] [1090/2639] eta: 1:19:59 lr: 1.1184444574065123e-06 loss: 0.0267 (0.0294) time: 3.1257 data: 0.0084 max mem: 33370 +Epoch: [39] [1100/2639] eta: 1:19:28 lr: 1.1119397680421193e-06 loss: 0.0274 (0.0294) time: 3.0689 data: 0.0085 max mem: 33370 +Epoch: [39] [1110/2639] eta: 1:18:57 lr: 1.1054308479542957e-06 loss: 0.0260 (0.0294) time: 3.1127 data: 0.0087 max mem: 33370 +Epoch: [39] [1120/2639] eta: 1:18:27 lr: 1.0989176666758682e-06 loss: 0.0269 (0.0294) time: 3.1389 data: 0.0089 max mem: 33370 +Epoch: [39] [1130/2639] eta: 1:17:56 lr: 1.0924001933180108e-06 loss: 0.0269 (0.0293) time: 3.1182 data: 0.0086 max mem: 33370 +Epoch: [39] [1140/2639] eta: 1:17:25 lr: 1.0858783965616259e-06 loss: 0.0281 (0.0293) time: 3.0982 data: 0.0087 max mem: 33370 +Epoch: [39] [1150/2639] eta: 1:16:54 lr: 1.0793522446483766e-06 loss: 0.0269 (0.0293) time: 3.1194 data: 0.0089 max mem: 33370 +Epoch: [39] [1160/2639] eta: 1:16:24 lr: 1.0728217053715944e-06 loss: 0.0245 (0.0293) time: 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0.0266 (0.0293) time: 3.1757 data: 0.0086 max mem: 33370 +Epoch: [39] [1250/2639] eta: 1:11:48 lr: 1.0138438719039344e-06 loss: 0.0263 (0.0293) time: 3.2042 data: 0.0087 max mem: 33370 +Epoch: [39] [1260/2639] eta: 1:11:18 lr: 1.007267581903182e-06 loss: 0.0273 (0.0293) time: 3.1786 data: 0.0087 max mem: 33370 +Epoch: [39] [1270/2639] eta: 1:10:46 lr: 1.0006865177823913e-06 loss: 0.0285 (0.0293) time: 3.1069 data: 0.0087 max mem: 33370 +Epoch: [39] [1280/2639] eta: 1:10:15 lr: 9.941006411384698e-07 loss: 0.0283 (0.0293) time: 3.0762 data: 0.0088 max mem: 33370 +Epoch: [39] [1290/2639] eta: 1:09:43 lr: 9.875099129741968e-07 loss: 0.0287 (0.0293) time: 3.0390 data: 0.0092 max mem: 33370 +Epoch: [39] [1300/2639] eta: 1:09:12 lr: 9.809142936846176e-07 loss: 0.0299 (0.0293) time: 3.0414 data: 0.0088 max mem: 33370 +Epoch: [39] [1310/2639] eta: 1:08:40 lr: 9.743137430428951e-07 loss: 0.0269 (0.0293) time: 3.0658 data: 0.0086 max mem: 33370 +Epoch: [39] [1320/2639] eta: 1:08:08 lr: 9.677082201858486e-07 loss: 0.0265 (0.0293) time: 3.0106 data: 0.0090 max mem: 33370 +Epoch: [39] [1330/2639] eta: 1:07:36 lr: 9.610976835989181e-07 loss: 0.0265 (0.0293) time: 2.9913 data: 0.0091 max mem: 33370 +Epoch: [39] [1340/2639] eta: 1:07:04 lr: 9.544820911007832e-07 loss: 0.0314 (0.0294) time: 3.0030 data: 0.0092 max mem: 33370 +Epoch: [39] [1350/2639] eta: 1:06:32 lr: 9.478613998273692e-07 loss: 0.0306 (0.0294) time: 3.0098 data: 0.0092 max mem: 33370 +Epoch: [39] [1360/2639] eta: 1:06:02 lr: 9.412355662154615e-07 loss: 0.0261 (0.0293) time: 3.0885 data: 0.0090 max mem: 33370 +Epoch: [39] [1370/2639] eta: 1:05:31 lr: 9.346045459857169e-07 loss: 0.0287 (0.0294) time: 3.1366 data: 0.0087 max mem: 33370 +Epoch: [39] [1380/2639] eta: 1:04:59 lr: 9.279682941251244e-07 loss: 0.0297 (0.0294) time: 3.0718 data: 0.0084 max mem: 33370 +Epoch: [39] [1390/2639] eta: 1:04:29 lr: 9.213267648689721e-07 loss: 0.0308 (0.0294) time: 3.0691 data: 0.0087 max mem: 33370 +Epoch: [39] [1400/2639] eta: 1:03:58 lr: 9.146799116821058e-07 loss: 0.0277 (0.0294) time: 3.1472 data: 0.0089 max mem: 33370 +Epoch: [39] [1410/2639] eta: 1:03:29 lr: 9.080276872396893e-07 loss: 0.0254 (0.0293) time: 3.2032 data: 0.0091 max mem: 33370 +Epoch: [39] [1420/2639] eta: 1:02:59 lr: 9.013700434071985e-07 loss: 0.0272 (0.0293) time: 3.2463 data: 0.0094 max mem: 33370 +Epoch: [39] [1430/2639] eta: 1:02:29 lr: 8.94706931219867e-07 loss: 0.0253 (0.0293) time: 3.2246 data: 0.0088 max mem: 33370 +Epoch: [39] [1440/2639] eta: 1:01:58 lr: 8.880383008613076e-07 loss: 0.0248 (0.0293) time: 3.1781 data: 0.0085 max mem: 33370 +Epoch: [39] [1450/2639] eta: 1:01:28 lr: 8.81364101641528e-07 loss: 0.0259 (0.0293) time: 3.1794 data: 0.0088 max mem: 33370 +Epoch: [39] [1460/2639] eta: 1:00:57 lr: 8.746842819740607e-07 loss: 0.0270 (0.0293) time: 3.1444 data: 0.0087 max mem: 33370 +Epoch: [39] [1470/2639] eta: 1:00:26 lr: 8.679987893524243e-07 loss: 0.0289 (0.0293) time: 3.1073 data: 0.0083 max mem: 33370 +Epoch: [39] [1480/2639] eta: 0:59:55 lr: 8.613075703256302e-07 loss: 0.0284 (0.0293) time: 3.1434 data: 0.0086 max mem: 33370 +Epoch: [39] [1490/2639] eta: 0:59:25 lr: 8.546105704729485e-07 loss: 0.0257 (0.0293) time: 3.1597 data: 0.0086 max mem: 33370 +Epoch: [39] [1500/2639] eta: 0:58:55 lr: 8.479077343776467e-07 loss: 0.0275 (0.0294) time: 3.1752 data: 0.0086 max mem: 33370 +Epoch: [39] [1510/2639] eta: 0:58:24 lr: 8.411990055999068e-07 loss: 0.0283 (0.0294) time: 3.1821 data: 0.0088 max mem: 33370 +Epoch: [39] [1520/2639] eta: 0:57:54 lr: 8.344843266486317e-07 loss: 0.0236 (0.0293) time: 3.1923 data: 0.0092 max mem: 33370 +Epoch: [39] [1530/2639] eta: 0:57:23 lr: 8.277636389523446e-07 loss: 0.0246 (0.0293) time: 3.1970 data: 0.0094 max mem: 33370 +Epoch: [39] [1540/2639] eta: 0:56:52 lr: 8.210368828288822e-07 loss: 0.0275 (0.0293) time: 3.1448 data: 0.0092 max mem: 33370 +Epoch: [39] [1550/2639] eta: 0:56:21 lr: 8.14303997454085e-07 loss: 0.0294 (0.0293) time: 3.0784 data: 0.0092 max mem: 33370 +Epoch: [39] [1560/2639] eta: 0:55:50 lr: 8.075649208291777e-07 loss: 0.0286 (0.0293) time: 3.0619 data: 0.0095 max mem: 33370 +Epoch: [39] [1570/2639] eta: 0:55:18 lr: 8.008195897470376e-07 loss: 0.0263 (0.0293) time: 3.0486 data: 0.0095 max mem: 33370 +Epoch: [39] [1580/2639] eta: 0:54:46 lr: 7.940679397570379e-07 loss: 0.0278 (0.0293) time: 3.0263 data: 0.0089 max mem: 33370 +Epoch: [39] [1590/2639] eta: 0:54:16 lr: 7.873099051286583e-07 loss: 0.0271 (0.0293) time: 3.0839 data: 0.0090 max mem: 33370 +Epoch: [39] [1600/2639] eta: 0:53:44 lr: 7.805454188135392e-07 loss: 0.0284 (0.0293) time: 3.1065 data: 0.0091 max mem: 33370 +Epoch: [39] [1610/2639] eta: 0:53:13 lr: 7.737744124061614e-07 loss: 0.0311 (0.0293) time: 3.0979 data: 0.0088 max mem: 33370 +Epoch: [39] [1620/2639] eta: 0:52:43 lr: 7.669968161028715e-07 loss: 0.0310 (0.0294) time: 3.1527 data: 0.0088 max mem: 33370 +Epoch: [39] [1630/2639] eta: 0:52:12 lr: 7.602125586592597e-07 loss: 0.0281 (0.0293) time: 3.1691 data: 0.0089 max mem: 33370 +Epoch: [39] [1640/2639] eta: 0:51:41 lr: 7.534215673458819e-07 loss: 0.0281 (0.0294) time: 3.1204 data: 0.0086 max mem: 33370 +Epoch: [39] [1650/2639] eta: 0:51:10 lr: 7.466237679020414e-07 loss: 0.0306 (0.0294) time: 3.0827 data: 0.0082 max mem: 33370 +Epoch: [39] [1660/2639] eta: 0:50:39 lr: 7.398190844877795e-07 loss: 0.0299 (0.0294) time: 3.0993 data: 0.0083 max mem: 33370 +Epoch: [39] [1670/2639] eta: 0:50:07 lr: 7.330074396337245e-07 loss: 0.0295 (0.0294) time: 3.0761 data: 0.0087 max mem: 33370 +Epoch: [39] [1680/2639] eta: 0:49:36 lr: 7.261887541889441e-07 loss: 0.0303 (0.0294) time: 3.0710 data: 0.0084 max mem: 33370 +Epoch: [39] [1690/2639] eta: 0:49:05 lr: 7.193629472664343e-07 loss: 0.0334 (0.0294) time: 3.1064 data: 0.0083 max mem: 33370 +Epoch: [39] [1700/2639] eta: 0:48:34 lr: 7.1252993618638e-07 loss: 0.0277 (0.0294) time: 3.0782 data: 0.0084 max mem: 33370 +Epoch: [39] [1710/2639] eta: 0:48:02 lr: 7.056896364168037e-07 loss: 0.0261 (0.0294) time: 3.0332 data: 0.0079 max mem: 33370 +Epoch: [39] [1720/2639] eta: 0:47:31 lr: 6.988419615117211e-07 loss: 0.0308 (0.0294) time: 3.0181 data: 0.0078 max mem: 33370 +Epoch: [39] [1730/2639] eta: 0:47:00 lr: 6.919868230464006e-07 loss: 0.0288 (0.0294) time: 3.0276 data: 0.0082 max mem: 33370 +Epoch: [39] [1740/2639] eta: 0:46:28 lr: 6.851241305498308e-07 loss: 0.0249 (0.0294) time: 2.9788 data: 0.0084 max mem: 33370 +Epoch: [39] [1750/2639] eta: 0:45:56 lr: 6.782537914339695e-07 loss: 0.0249 (0.0294) time: 2.9527 data: 0.0084 max mem: 33370 +Epoch: [39] [1760/2639] eta: 0:45:24 lr: 6.713757109198568e-07 loss: 0.0278 (0.0294) time: 2.9676 data: 0.0084 max mem: 33370 +Epoch: [39] [1770/2639] eta: 0:44:53 lr: 6.644897919601425e-07 loss: 0.0300 (0.0294) time: 3.0098 data: 0.0080 max mem: 33370 +Epoch: [39] [1780/2639] eta: 0:44:22 lr: 6.575959351580849e-07 loss: 0.0302 (0.0294) time: 3.0545 data: 0.0080 max mem: 33370 +Epoch: [39] [1790/2639] eta: 0:43:51 lr: 6.506940386825428e-07 loss: 0.0286 (0.0294) time: 3.0423 data: 0.0082 max mem: 33370 +Epoch: [39] [1800/2639] eta: 0:43:19 lr: 6.437839981789882e-07 loss: 0.0325 (0.0295) time: 2.9961 data: 0.0081 max mem: 33370 +Epoch: [39] [1810/2639] eta: 0:42:47 lr: 6.368657066760285e-07 loss: 0.0296 (0.0295) time: 2.9663 data: 0.0083 max mem: 33370 +Epoch: [39] [1820/2639] eta: 0:42:16 lr: 6.299390544874298e-07 loss: 0.0286 (0.0295) time: 2.9606 data: 0.0087 max mem: 33370 +Epoch: [39] [1830/2639] eta: 0:41:45 lr: 6.230039291090929e-07 loss: 0.0274 (0.0295) time: 3.0162 data: 0.0087 max mem: 33370 +Epoch: [39] [1840/2639] eta: 0:41:14 lr: 6.160602151109309e-07 loss: 0.0236 (0.0295) time: 3.0855 data: 0.0085 max mem: 33370 +Epoch: [39] [1850/2639] eta: 0:40:43 lr: 6.091077940230542e-07 loss: 0.0249 (0.0295) time: 3.0959 data: 0.0083 max mem: 33370 +Epoch: [39] [1860/2639] eta: 0:40:12 lr: 6.02146544216154e-07 loss: 0.0287 (0.0295) time: 3.1018 data: 0.0081 max mem: 33370 +Epoch: [39] [1870/2639] eta: 0:39:41 lr: 5.951763407754933e-07 loss: 0.0303 (0.0295) time: 3.0825 data: 0.0082 max mem: 33370 +Epoch: [39] [1880/2639] eta: 0:39:10 lr: 5.881970553681669e-07 loss: 0.0292 (0.0295) time: 3.0790 data: 0.0084 max mem: 33370 +Epoch: [39] [1890/2639] eta: 0:38:39 lr: 5.812085561032592e-07 loss: 0.0239 (0.0295) time: 3.0975 data: 0.0085 max mem: 33370 +Epoch: [39] [1900/2639] eta: 0:38:08 lr: 5.742107073842028e-07 loss: 0.0244 (0.0295) time: 3.0977 data: 0.0087 max mem: 33370 +Epoch: [39] [1910/2639] eta: 0:37:37 lr: 5.672033697530656e-07 loss: 0.0264 (0.0295) time: 3.0802 data: 0.0088 max mem: 33370 +Epoch: [39] [1920/2639] eta: 0:37:06 lr: 5.601863997259244e-07 loss: 0.0258 (0.0295) time: 3.1116 data: 0.0085 max mem: 33370 +Epoch: [39] [1930/2639] eta: 0:36:35 lr: 5.531596496189649e-07 loss: 0.0285 (0.0295) time: 3.1422 data: 0.0082 max mem: 33370 +Epoch: [39] [1940/2639] eta: 0:36:04 lr: 5.461229673643678e-07 loss: 0.0316 (0.0295) time: 3.1252 data: 0.0080 max mem: 33370 +Epoch: [39] [1950/2639] eta: 0:35:33 lr: 5.390761963155063e-07 loss: 0.0266 (0.0295) time: 3.1032 data: 0.0080 max mem: 33370 +Epoch: [39] [1960/2639] eta: 0:35:02 lr: 5.320191750403883e-07 loss: 0.0263 (0.0295) time: 3.0763 data: 0.0080 max mem: 33370 +Epoch: [39] [1970/2639] eta: 0:34:31 lr: 5.249517371027315e-07 loss: 0.0271 (0.0295) time: 3.0725 data: 0.0081 max mem: 33370 +Epoch: [39] [1980/2639] eta: 0:34:00 lr: 5.17873710829455e-07 loss: 0.0271 (0.0295) time: 3.0943 data: 0.0083 max mem: 33370 +Epoch: [39] [1990/2639] eta: 0:33:29 lr: 5.107849190638034e-07 loss: 0.0266 (0.0294) time: 3.0811 data: 0.0085 max mem: 33370 +Epoch: [39] [2000/2639] eta: 0:32:58 lr: 5.036851789027012e-07 loss: 0.0266 (0.0294) time: 3.0176 data: 0.0085 max mem: 33370 +Epoch: [39] [2010/2639] eta: 0:32:27 lr: 4.96574301417348e-07 loss: 0.0280 (0.0294) time: 3.0062 data: 0.0086 max mem: 33370 +Epoch: [39] [2020/2639] eta: 0:31:55 lr: 4.894520913554173e-07 loss: 0.0271 (0.0294) time: 3.0321 data: 0.0090 max mem: 33370 +Epoch: [39] [2030/2639] eta: 0:31:24 lr: 4.823183468236159e-07 loss: 0.0273 (0.0294) time: 3.0407 data: 0.0087 max mem: 33370 +Epoch: [39] [2040/2639] eta: 0:30:53 lr: 4.751728589486756e-07 loss: 0.0263 (0.0294) time: 3.0259 data: 0.0083 max mem: 33370 +Epoch: [39] [2050/2639] eta: 0:30:22 lr: 4.680154115152184e-07 loss: 0.0233 (0.0294) time: 3.0192 data: 0.0092 max mem: 33370 +Epoch: [39] [2060/2639] eta: 0:29:51 lr: 4.608457805782017e-07 loss: 0.0248 (0.0294) time: 3.0636 data: 0.0093 max mem: 33370 +Epoch: [39] [2070/2639] eta: 0:29:20 lr: 4.536637340479835e-07 loss: 0.0305 (0.0294) time: 3.0759 data: 0.0084 max mem: 33370 +Epoch: [39] [2080/2639] eta: 0:28:49 lr: 4.4646903124526287e-07 loss: 0.0293 (0.0294) time: 3.0164 data: 0.0084 max mem: 33370 +Epoch: [39] [2090/2639] eta: 0:28:17 lr: 4.3926142242342023e-07 loss: 0.0279 (0.0294) time: 2.9464 data: 0.0086 max mem: 33370 +Epoch: [39] [2100/2639] eta: 0:27:46 lr: 4.320406482549395e-07 loss: 0.0314 (0.0294) time: 2.9568 data: 0.0091 max mem: 33370 +Epoch: [39] [2110/2639] eta: 0:27:15 lr: 4.2480643927877586e-07 loss: 0.0308 (0.0294) time: 2.9908 data: 0.0090 max mem: 33370 +Epoch: [39] [2120/2639] eta: 0:26:44 lr: 4.175585153046684e-07 loss: 0.0282 (0.0294) time: 3.0267 data: 0.0083 max mem: 33370 +Epoch: [39] [2130/2639] eta: 0:26:13 lr: 4.102965847702475e-07 loss: 0.0265 (0.0294) time: 3.0861 data: 0.0080 max mem: 33370 +Epoch: [39] [2140/2639] eta: 0:25:42 lr: 4.0302034404627457e-07 loss: 0.0234 (0.0294) time: 3.1055 data: 0.0078 max mem: 33370 +Epoch: [39] [2150/2639] eta: 0:25:11 lr: 3.95729476684475e-07 loss: 0.0268 (0.0294) time: 3.0730 data: 0.0079 max mem: 33370 +Epoch: [39] [2160/2639] eta: 0:24:40 lr: 3.8842365260223343e-07 loss: 0.0273 (0.0294) time: 3.0661 data: 0.0077 max mem: 33370 +Epoch: [39] [2170/2639] eta: 0:24:09 lr: 3.811025271971174e-07 loss: 0.0273 (0.0294) time: 3.0979 data: 0.0080 max mem: 33370 +Epoch: [39] [2180/2639] eta: 0:23:39 lr: 3.737657403838596e-07 loss: 0.0275 (0.0294) time: 3.0909 data: 0.0084 max mem: 33370 +Epoch: [39] [2190/2639] eta: 0:23:08 lr: 3.6641291554486204e-07 loss: 0.0244 (0.0294) time: 3.0741 data: 0.0085 max mem: 33370 +Epoch: [39] [2200/2639] eta: 0:22:37 lr: 3.590436583846511e-07 loss: 0.0244 (0.0294) time: 3.0782 data: 0.0085 max mem: 33370 +Epoch: [39] [2210/2639] eta: 0:22:06 lr: 3.516575556767922e-07 loss: 0.0244 (0.0294) time: 3.0970 data: 0.0084 max mem: 33370 +Epoch: [39] [2220/2639] eta: 0:21:35 lr: 3.442541738907181e-07 loss: 0.0261 (0.0294) time: 3.0940 data: 0.0083 max mem: 33370 +Epoch: [39] [2230/2639] eta: 0:21:04 lr: 3.3683305768350376e-07 loss: 0.0261 (0.0294) time: 3.0516 data: 0.0082 max mem: 33370 +Epoch: [39] [2240/2639] eta: 0:20:33 lr: 3.2939372823996685e-07 loss: 0.0270 (0.0294) time: 3.0683 data: 0.0083 max mem: 33370 +Epoch: [39] [2250/2639] eta: 0:20:02 lr: 3.219356814413302e-07 loss: 0.0269 (0.0294) time: 3.0746 data: 0.0083 max mem: 33370 +Epoch: [39] [2260/2639] eta: 0:19:31 lr: 3.1445838584016387e-07 loss: 0.0260 (0.0294) time: 2.9915 data: 0.0085 max mem: 33370 +Epoch: [39] [2270/2639] eta: 0:19:00 lr: 3.06961280415122e-07 loss: 0.0267 (0.0293) time: 2.9864 data: 0.0088 max mem: 33370 +Epoch: [39] [2280/2639] eta: 0:18:29 lr: 2.9944377207519256e-07 loss: 0.0276 (0.0294) time: 3.0498 data: 0.0083 max mem: 33370 +Epoch: [39] [2290/2639] eta: 0:17:58 lr: 2.9190523287740245e-07 loss: 0.0283 (0.0294) time: 3.0010 data: 0.0084 max mem: 33370 +Epoch: [39] [2300/2639] eta: 0:17:27 lr: 2.8434499691619174e-07 loss: 0.0261 (0.0294) time: 2.9343 data: 0.0087 max mem: 33370 +Epoch: [39] [2310/2639] eta: 0:16:55 lr: 2.7676235683450313e-07 loss: 0.0298 (0.0294) time: 2.9189 data: 0.0087 max mem: 33370 +Epoch: [39] [2320/2639] eta: 0:16:24 lr: 2.691565598979306e-07 loss: 0.0272 (0.0294) time: 2.9422 data: 0.0085 max mem: 33370 +Epoch: [39] [2330/2639] eta: 0:15:54 lr: 2.6152680356137467e-07 loss: 0.0253 (0.0294) time: 3.0422 data: 0.0081 max mem: 33370 +Epoch: [39] [2340/2639] eta: 0:15:23 lr: 2.538722304442624e-07 loss: 0.0255 (0.0294) time: 3.0853 data: 0.0081 max mem: 33370 +Epoch: [39] [2350/2639] eta: 0:14:52 lr: 2.4619192261253055e-07 loss: 0.0255 (0.0293) time: 3.0327 data: 0.0084 max mem: 33370 +Epoch: [39] [2360/2639] eta: 0:14:21 lr: 2.3848489504456857e-07 loss: 0.0276 (0.0293) time: 2.9460 data: 0.0085 max mem: 33370 +Epoch: [39] [2370/2639] eta: 0:13:49 lr: 2.307500881307244e-07 loss: 0.0313 (0.0293) time: 2.9121 data: 0.0085 max mem: 33370 +Epoch: [39] [2380/2639] eta: 0:13:19 lr: 2.2298635902199563e-07 loss: 0.0301 (0.0294) time: 3.0162 data: 0.0091 max mem: 33370 +Epoch: [39] [2390/2639] eta: 0:12:48 lr: 2.1519247159976585e-07 loss: 0.0274 (0.0293) time: 3.1063 data: 0.0090 max mem: 33370 +Epoch: [39] [2400/2639] eta: 0:12:17 lr: 2.0736708478178274e-07 loss: 0.0271 (0.0293) time: 3.1263 data: 0.0081 max mem: 33370 +Epoch: [39] [2410/2639] eta: 0:11:46 lr: 1.995087388068646e-07 loss: 0.0275 (0.0293) time: 3.1324 data: 0.0082 max mem: 33370 +Epoch: [39] [2420/2639] eta: 0:11:15 lr: 1.9161583904412294e-07 loss: 0.0274 (0.0293) time: 3.1072 data: 0.0083 max mem: 33370 +Epoch: [39] [2430/2639] eta: 0:10:44 lr: 1.8368663674550398e-07 loss: 0.0274 (0.0293) time: 3.0655 data: 0.0081 max mem: 33370 +Epoch: [39] [2440/2639] eta: 0:10:14 lr: 1.7571920598852315e-07 loss: 0.0265 (0.0293) time: 3.0626 data: 0.0084 max mem: 33370 +Epoch: [39] [2450/2639] eta: 0:09:43 lr: 1.6771141582355341e-07 loss: 0.0261 (0.0293) time: 3.0666 data: 0.0083 max mem: 33370 +Epoch: [39] [2460/2639] eta: 0:09:12 lr: 1.5966089631778305e-07 loss: 0.0262 (0.0293) time: 3.0567 data: 0.0078 max mem: 33370 +Epoch: [39] [2470/2639] eta: 0:08:41 lr: 1.5156499673780186e-07 loss: 0.0289 (0.0293) time: 3.0619 data: 0.0079 max mem: 33370 +Epoch: [39] [2480/2639] eta: 0:08:10 lr: 1.4342073346962213e-07 loss: 0.0297 (0.0293) time: 3.0629 data: 0.0081 max mem: 33370 +Epoch: [39] [2490/2639] eta: 0:07:39 lr: 1.3522472434208778e-07 loss: 0.0257 (0.0293) time: 3.0966 data: 0.0081 max mem: 33370 +Epoch: [39] [2500/2639] eta: 0:07:08 lr: 1.269731046340577e-07 loss: 0.0268 (0.0293) time: 3.1054 data: 0.0081 max mem: 33370 +Epoch: [39] [2510/2639] eta: 0:06:38 lr: 1.1866141794230447e-07 loss: 0.0275 (0.0293) time: 3.0899 data: 0.0080 max mem: 33370 +Epoch: [39] [2520/2639] eta: 0:06:07 lr: 1.1028447180330967e-07 loss: 0.0301 (0.0293) time: 3.1046 data: 0.0081 max mem: 33370 +Epoch: [39] [2530/2639] eta: 0:05:36 lr: 1.0183614268114759e-07 loss: 0.0277 (0.0293) time: 3.1231 data: 0.0086 max mem: 33370 +Epoch: [39] [2540/2639] eta: 0:05:05 lr: 9.330910613295523e-08 loss: 0.0263 (0.0293) time: 3.1120 data: 0.0088 max mem: 33370 +Epoch: [39] [2550/2639] eta: 0:04:34 lr: 8.46944526897065e-08 loss: 0.0249 (0.0293) time: 3.0664 data: 0.0086 max mem: 33370 +Epoch: [39] [2560/2639] eta: 0:04:03 lr: 7.59811221657123e-08 loss: 0.0287 (0.0293) time: 3.0325 data: 0.0087 max mem: 33370 +Epoch: [39] [2570/2639] eta: 0:03:32 lr: 6.715503540092055e-08 loss: 0.0295 (0.0293) time: 2.9782 data: 0.0083 max mem: 33370 +Epoch: [39] [2580/2639] eta: 0:03:02 lr: 5.8197691112651246e-08 loss: 0.0300 (0.0293) time: 2.9938 data: 0.0081 max mem: 33370 +Epoch: [39] [2590/2639] eta: 0:02:31 lr: 4.908374312237755e-08 loss: 0.0327 (0.0293) time: 3.0631 data: 0.0083 max mem: 33370 +Epoch: [39] [2600/2639] eta: 0:02:00 lr: 3.9776429634041595e-08 loss: 0.0304 (0.0293) time: 3.0899 data: 0.0083 max mem: 33370 +Epoch: [39] [2610/2639] eta: 0:01:29 lr: 3.0217796291920384e-08 loss: 0.0265 (0.0293) time: 3.0787 data: 0.0083 max mem: 33370 +Epoch: [39] [2620/2639] eta: 0:00:58 lr: 2.0303261840977132e-08 loss: 0.0265 (0.0293) time: 3.0758 data: 0.0087 max mem: 33370 +Epoch: [39] [2630/2639] eta: 0:00:27 lr: 9.785917479894317e-09 loss: 0.0283 (0.0293) time: 3.0936 data: 0.0084 max mem: 33370 +Epoch: [39] Total time: 2:15:41 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 2:20:22 time: 3.2734 data: 3.1560 max mem: 33370 +Test: [ 100/2573] eta: 0:04:34 time: 0.0799 data: 0.0016 max mem: 33370 +Test: [ 200/2573] eta: 0:03:48 time: 0.0811 data: 0.0015 max mem: 33370 +Test: [ 300/2573] eta: 0:03:26 time: 0.0819 data: 0.0014 max mem: 33370 +Test: [ 400/2573] eta: 0:03:11 time: 0.0823 data: 0.0014 max mem: 33370 +Test: [ 500/2573] eta: 0:02:59 time: 0.0811 data: 0.0016 max mem: 33370 +Test: [ 600/2573] eta: 0:02:49 time: 0.0823 data: 0.0017 max mem: 33370 +Test: [ 700/2573] eta: 0:02:40 time: 0.0819 data: 0.0015 max mem: 33370 +Test: [ 800/2573] eta: 0:02:31 time: 0.0842 data: 0.0015 max mem: 33370 +Test: [ 900/2573] eta: 0:02:22 time: 0.0821 data: 0.0015 max mem: 33370 +Test: [1000/2573] eta: 0:02:13 time: 0.0818 data: 0.0015 max mem: 33370 +Test: [1100/2573] eta: 0:02:04 time: 0.0812 data: 0.0015 max mem: 33370 +Test: [1200/2573] eta: 0:01:55 time: 0.0822 data: 0.0016 max mem: 33370 +Test: [1300/2573] eta: 0:01:47 time: 0.0824 data: 0.0016 max mem: 33370 +Test: [1400/2573] eta: 0:01:38 time: 0.0806 data: 0.0017 max mem: 33370 +Test: [1500/2573] eta: 0:01:30 time: 0.0817 data: 0.0017 max mem: 33370 +Test: [1600/2573] eta: 0:01:21 time: 0.0840 data: 0.0015 max mem: 33370 +Test: [1700/2573] eta: 0:01:13 time: 0.0794 data: 0.0015 max mem: 33370 +Test: [1800/2573] eta: 0:01:04 time: 0.0816 data: 0.0014 max mem: 33370 +Test: [1900/2573] eta: 0:00:56 time: 0.0794 data: 0.0014 max mem: 33370 +Test: [2000/2573] eta: 0:00:47 time: 0.0798 data: 0.0014 max mem: 33370 +Test: [2100/2573] eta: 0:00:39 time: 0.0817 data: 0.0014 max mem: 33370 +Test: [2200/2573] eta: 0:00:30 time: 0.0817 data: 0.0013 max mem: 33370 +Test: [2300/2573] eta: 0:00:22 time: 0.0839 data: 0.0016 max mem: 33370 +Test: [2400/2573] eta: 0:00:14 time: 0.0795 data: 0.0015 max mem: 33370 +Test: [2500/2573] eta: 0:00:06 time: 0.0831 data: 0.0016 max mem: 33370 +Test: Total time: 0:03:33 +Final results: +Mean IoU is 64.97 + + precision@0.5 = 73.10 + precision@0.6 = 68.14 + precision@0.7 = 61.34 + precision@0.8 = 50.47 + precision@0.9 = 26.16 + overall IoU = 62.22 + +Average object IoU 64.97094915053147 +Overall IoU 62.217201232910156 +Better epoch: 39 + +Training time 3 days, 15:57:07 +ERROR:torch.distributed.elastic.multiprocessing.api:failed (exitcode: -7) local_rank: 0 (pid: 2956790) of binary: /home/chaeyun/.conda/envs/cris/bin/python +Traceback (most recent call last): + File "/home/chaeyun/.conda/envs/cris/lib/python3.9/runpy.py", line 197, in _run_module_as_main + return _run_code(code, main_globals, None, + File "/home/chaeyun/.conda/envs/cris/lib/python3.9/runpy.py", line 87, in _run_code + exec(code, run_globals) + File "/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torch/distributed/launch.py", line 193, in + main() + File "/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torch/distributed/launch.py", line 189, in main + launch(args) + File "/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torch/distributed/launch.py", line 174, in launch + run(args) + File "/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torch/distributed/run.py", line 752, in run + elastic_launch( + File "/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torch/distributed/launcher/api.py", line 131, in __call__ + return launch_agent(self._config, self._entrypoint, list(args)) + File "/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torch/distributed/launcher/api.py", line 245, in launch_agent + raise ChildFailedError( +torch.distributed.elastic.multiprocessing.errors.ChildFailedError: +======================================================= +train_angle.py FAILED +------------------------------------------------------- +Failures: +[1]: + time : 2024-12-16_02:54:28 + host : node02.localdomain + rank : 1 (local_rank: 1) + exitcode : -7 (pid: 2956791) + error_file: + traceback : Signal 7 (SIGBUS) received by PID 2956791 +------------------------------------------------------- +Root Cause (first observed failure): +[0]: + time : 2024-12-16_02:54:28 + host : node02.localdomain + rank : 0 (local_rank: 0) + exitcode : -7 (pid: 2956790) + error_file: + traceback : Signal 7 (SIGBUS) received by PID 2956790 +======================================================= diff --git a/LAVT-RIS/logs/old/gref_m10_mg15_tmp010_4gpu_bs32_ang.log b/LAVT-RIS/logs/old/gref_m10_mg15_tmp010_4gpu_bs32_ang.log new file mode 100644 index 0000000000000000000000000000000000000000..aba5ebd7fe5cf87dd4bdadc5a185a190cc63ea93 --- /dev/null +++ b/LAVT-RIS/logs/old/gref_m10_mg15_tmp010_4gpu_bs32_ang.log @@ -0,0 +1,12093 @@ +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torch/distributed/launch.py:178: FutureWarning: The module torch.distributed.launch is deprecated +and will be removed in future. Use torchrun. +Note that --use_env is set by default in torchrun. +If your script expects `--local_rank` argument to be set, please +change it to read from `os.environ['LOCAL_RANK']` instead. See +https://pytorch.org/docs/stable/distributed.html#launch-utility for +further instructions + + warnings.warn( +WARNING:torch.distributed.run: +***************************************** +Setting OMP_NUM_THREADS environment variable for each process to be 1 in default, to avoid your system being overloaded, please further tune the variable for optimal performance in your application as needed. +***************************************** +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/timm/models/layers/__init__.py:48: FutureWarning: Importing from timm.models.layers is deprecated, please import via timm.layers + warnings.warn(f"Importing from {__name__} is deprecated, please import via timm.layers", FutureWarning) +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/timm/models/layers/__init__.py:48: FutureWarning: Importing from timm.models.layers is deprecated, please import via timm.layers + warnings.warn(f"Importing from {__name__} is deprecated, please import via timm.layers", FutureWarning) +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/timm/models/layers/__init__.py:48: FutureWarning: Importing from timm.models.layers is deprecated, please import via timm.layers + warnings.warn(f"Importing from {__name__} is deprecated, please import via timm.layers", FutureWarning) +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/timm/models/layers/__init__.py:48: FutureWarning: Importing from timm.models.layers is deprecated, please import via timm.layers + warnings.warn(f"Importing from {__name__} is deprecated, please import via timm.layers", FutureWarning) +RANK and WORLD_SIZE in environment: 2/4RANK and WORLD_SIZE in environment: 3/4RANK and WORLD_SIZE in environment: 1/4 + + +RANK and WORLD_SIZE in environment: 0/4 +Image size: 480 +loading dataset refcocog into memory... +creating index... +index created. +DONE (t=6.61s) +loading dataset refcocog into memory... +creating index... +index created. +DONE (t=6.28s) +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torch/functional.py:478: UserWarning: torch.meshgrid: in an upcoming release, it will be required to pass the indexing argument. (Triggered internally at ../aten/src/ATen/native/TensorShape.cpp:2894.) + return _VF.meshgrid(tensors, **kwargs) # type: ignore[attr-defined] +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torch/functional.py:478: UserWarning: torch.meshgrid: in an upcoming release, it will be required to pass the indexing argument. (Triggered internally at ../aten/src/ATen/native/TensorShape.cpp:2894.) + return _VF.meshgrid(tensors, **kwargs) # type: ignore[attr-defined] +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torch/functional.py:478: UserWarning: torch.meshgrid: in an upcoming release, it will be required to pass the indexing argument. (Triggered internally at ../aten/src/ATen/native/TensorShape.cpp:2894.) + return _VF.meshgrid(tensors, **kwargs) # type: ignore[attr-defined] +local rank 0 / global rank 0 successfully built train dataset. +lavt_one +Window size 12! +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torch/functional.py:478: UserWarning: torch.meshgrid: in an upcoming release, it will be required to pass the indexing argument. (Triggered internally at ../aten/src/ATen/native/TensorShape.cpp:2894.) + return _VF.meshgrid(tensors, **kwargs) # type: ignore[attr-defined] +Initializing Multi-modal Swin Transformer weights from ./pretrained_weights/swin_base_patch4_window12_384_22k.pth +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [0] [ 0/1319] eta: 3:27:28 lr: 4.9999147080313756e-05 loss: 0.5774 (0.5774) time: 9.4380 data: 3.2324 max mem: 20156 +Epoch: [0] [ 10/1319] eta: 1:20:20 lr: 4.999061779453083e-05 loss: 0.3796 (0.4038) time: 3.6830 data: 0.3017 max mem: 26588 +Epoch: [0] [ 20/1319] eta: 1:13:56 lr: 4.9982088347050674e-05 loss: 0.3300 (0.3611) time: 3.1145 data: 0.0081 max mem: 29995 +Epoch: [0] [ 30/1319] eta: 1:12:03 lr: 4.9973558737839576e-05 loss: 0.2908 (0.3396) time: 3.1731 data: 0.0078 max mem: 29995 +Epoch: [0] [ 40/1319] eta: 1:10:24 lr: 4.9965028966863786e-05 loss: 0.2695 (0.3240) time: 3.1839 data: 0.0081 max mem: 29995 +Epoch: [0] [ 50/1319] eta: 1:09:25 lr: 4.995649903408956e-05 loss: 0.2639 (0.3188) time: 3.1709 data: 0.0078 max mem: 29995 +Epoch: [0] [ 60/1319] eta: 1:08:25 lr: 4.9947968939483133e-05 loss: 0.2770 (0.3206) time: 3.1760 data: 0.0078 max mem: 29995 +Epoch: [0] [ 70/1319] eta: 1:07:35 lr: 4.993943868301072e-05 loss: 0.2770 (0.3134) time: 3.1567 data: 0.0084 max mem: 29995 +Epoch: [0] [ 80/1319] eta: 1:06:56 lr: 4.993090826463852e-05 loss: 0.2631 (0.3072) time: 3.1812 data: 0.0087 max mem: 29995 +Epoch: [0] [ 90/1319] eta: 1:06:28 lr: 4.9922377684332736e-05 loss: 0.2473 (0.3026) time: 3.2394 data: 0.0083 max mem: 29995 +Epoch: [0] [ 100/1319] eta: 1:05:47 lr: 4.991384694205954e-05 loss: 0.2394 (0.2978) time: 3.2245 data: 0.0080 max mem: 29995 +Epoch: [0] [ 110/1319] eta: 1:05:10 lr: 4.990531603778512e-05 loss: 0.2678 (0.2987) time: 3.1856 data: 0.0082 max mem: 29995 +Epoch: [0] [ 120/1319] eta: 1:04:28 lr: 4.98967849714756e-05 loss: 0.2678 (0.2956) time: 3.1700 data: 0.0081 max mem: 29995 +Epoch: [0] [ 130/1319] eta: 1:03:55 lr: 4.988825374309713e-05 loss: 0.2419 (0.2926) time: 3.1783 data: 0.0078 max mem: 29995 +Epoch: [0] [ 140/1319] eta: 1:03:16 lr: 4.987972235261584e-05 loss: 0.2459 (0.2895) time: 3.1776 data: 0.0078 max mem: 29995 +Epoch: [0] [ 150/1319] eta: 1:02:42 lr: 4.987119079999784e-05 loss: 0.2459 (0.2889) time: 3.1707 data: 0.0081 max mem: 29995 +Epoch: [0] [ 160/1319] eta: 1:02:00 lr: 4.986265908520923e-05 loss: 0.2356 (0.2860) time: 3.1420 data: 0.0082 max mem: 29995 +Epoch: [0] [ 170/1319] eta: 1:01:22 lr: 4.985412720821609e-05 loss: 0.2399 (0.2851) time: 3.0995 data: 0.0082 max mem: 29995 +Epoch: [0] [ 180/1319] eta: 1:00:49 lr: 4.984559516898449e-05 loss: 0.2264 (0.2817) time: 3.1593 data: 0.0080 max mem: 29995 +Epoch: [0] [ 190/1319] eta: 1:00:13 lr: 4.98370629674805e-05 loss: 0.2337 (0.2809) time: 3.1627 data: 0.0081 max mem: 29995 +Epoch: [0] [ 200/1319] eta: 0:59:40 lr: 4.982853060367015e-05 loss: 0.2536 (0.2794) time: 3.1575 data: 0.0082 max mem: 29995 +Epoch: [0] [ 210/1319] eta: 0:59:08 lr: 4.9819998077519475e-05 loss: 0.2370 (0.2786) time: 3.1906 data: 0.0085 max mem: 29997 +Epoch: [0] [ 220/1319] eta: 0:58:35 lr: 4.98114653889945e-05 loss: 0.2287 (0.2768) time: 3.1839 data: 0.0082 max mem: 29997 +Epoch: [0] [ 230/1319] eta: 0:58:02 lr: 4.980293253806122e-05 loss: 0.2299 (0.2756) time: 3.1798 data: 0.0079 max mem: 29997 +Epoch: [0] [ 240/1319] eta: 0:57:27 lr: 4.9794399524685624e-05 loss: 0.2281 (0.2749) time: 3.1609 data: 0.0085 max mem: 29997 +Epoch: [0] [ 250/1319] eta: 0:56:55 lr: 4.97858663488337e-05 loss: 0.2320 (0.2733) time: 3.1606 data: 0.0084 max mem: 29997 +Epoch: [0] [ 260/1319] eta: 0:56:24 lr: 4.977733301047139e-05 loss: 0.2192 (0.2708) time: 3.1992 data: 0.0082 max mem: 31677 +Epoch: [0] [ 270/1319] eta: 0:55:53 lr: 4.9768799509564675e-05 loss: 0.2385 (0.2703) time: 3.2254 data: 0.0084 max mem: 31677 +Epoch: [0] [ 280/1319] eta: 0:55:22 lr: 4.976026584607946e-05 loss: 0.2312 (0.2685) time: 3.2228 data: 0.0081 max mem: 31677 +Epoch: [0] [ 290/1319] eta: 0:54:49 lr: 4.9751732019981684e-05 loss: 0.2268 (0.2685) time: 3.1939 data: 0.0079 max mem: 31677 +Epoch: [0] [ 300/1319] eta: 0:54:17 lr: 4.974319803123725e-05 loss: 0.2568 (0.2684) time: 3.1795 data: 0.0078 max mem: 31677 +Epoch: [0] [ 310/1319] eta: 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3.1582 data: 0.0077 max mem: 33368 +Epoch: [0] [ 710/1319] eta: 0:32:21 lr: 4.939316403135663e-05 loss: 0.1997 (0.2462) time: 3.1823 data: 0.0078 max mem: 33368 +Epoch: [0] [ 720/1319] eta: 0:31:49 lr: 4.938462318048596e-05 loss: 0.2248 (0.2458) time: 3.1710 data: 0.0080 max mem: 33368 +Epoch: [0] [ 730/1319] eta: 0:31:17 lr: 4.937608216548967e-05 loss: 0.2026 (0.2451) time: 3.1614 data: 0.0078 max mem: 33368 +Epoch: [0] [ 740/1319] eta: 0:30:45 lr: 4.936754098633307e-05 loss: 0.2011 (0.2451) time: 3.1790 data: 0.0076 max mem: 33368 +Epoch: [0] [ 750/1319] eta: 0:30:13 lr: 4.935899964298143e-05 loss: 0.1799 (0.2443) time: 3.2156 data: 0.0079 max mem: 33368 +Epoch: [0] [ 760/1319] eta: 0:29:41 lr: 4.9350458135400046e-05 loss: 0.1741 (0.2436) time: 3.1841 data: 0.0080 max mem: 33368 +Epoch: [0] [ 770/1319] eta: 0:29:10 lr: 4.934191646355415e-05 loss: 0.1839 (0.2434) time: 3.1912 data: 0.0079 max mem: 33368 +Epoch: [0] [ 780/1319] eta: 0:28:38 lr: 4.9333374627409e-05 loss: 0.2045 (0.2430) time: 3.1897 data: 0.0081 max mem: 33368 +Epoch: [0] [ 790/1319] eta: 0:28:06 lr: 4.932483262692982e-05 loss: 0.2031 (0.2426) time: 3.1732 data: 0.0084 max mem: 33368 +Epoch: [0] [ 800/1319] eta: 0:27:34 lr: 4.931629046208183e-05 loss: 0.2029 (0.2421) time: 3.1837 data: 0.0087 max mem: 33368 +Epoch: [0] [ 810/1319] eta: 0:27:02 lr: 4.9307748132830237e-05 loss: 0.2018 (0.2419) time: 3.1804 data: 0.0086 max mem: 33368 +Epoch: [0] [ 820/1319] eta: 0:26:30 lr: 4.929920563914022e-05 loss: 0.2102 (0.2418) time: 3.1758 data: 0.0078 max mem: 33368 +Epoch: [0] [ 830/1319] eta: 0:25:58 lr: 4.929066298097696e-05 loss: 0.2102 (0.2415) time: 3.1519 data: 0.0076 max mem: 33368 +Epoch: [0] [ 840/1319] eta: 0:25:26 lr: 4.928212015830561e-05 loss: 0.1864 (0.2409) time: 3.1739 data: 0.0082 max mem: 33368 +Epoch: [0] [ 850/1319] eta: 0:24:54 lr: 4.927357717109131e-05 loss: 0.1864 (0.2407) time: 3.2077 data: 0.0076 max mem: 33368 +Epoch: [0] [ 860/1319] eta: 0:24:22 lr: 4.926503401929921e-05 loss: 0.2014 (0.2403) time: 3.1880 data: 0.0073 max mem: 33368 +Epoch: [0] [ 870/1319] eta: 0:23:50 lr: 4.925649070289441e-05 loss: 0.2107 (0.2401) time: 3.1805 data: 0.0078 max mem: 33368 +Epoch: [0] [ 880/1319] eta: 0:23:18 lr: 4.9247947221842024e-05 loss: 0.2205 (0.2398) time: 3.1724 data: 0.0081 max mem: 33368 +Epoch: [0] [ 890/1319] eta: 0:22:46 lr: 4.923940357610714e-05 loss: 0.1977 (0.2395) time: 3.1383 data: 0.0085 max mem: 33368 +Epoch: [0] [ 900/1319] eta: 0:22:15 lr: 4.9230859765654824e-05 loss: 0.1870 (0.2392) time: 3.1717 data: 0.0086 max mem: 33368 +Epoch: [0] [ 910/1319] eta: 0:21:43 lr: 4.922231579045014e-05 loss: 0.1880 (0.2385) time: 3.1878 data: 0.0081 max mem: 33368 +Epoch: [0] [ 920/1319] eta: 0:21:11 lr: 4.921377165045815e-05 loss: 0.1947 (0.2381) time: 3.1971 data: 0.0077 max mem: 33368 +Epoch: [0] [ 930/1319] eta: 0:20:39 lr: 4.9205227345643864e-05 loss: 0.2016 (0.2379) time: 3.2258 data: 0.0078 max mem: 33368 +Epoch: [0] [ 940/1319] eta: 0:20:07 lr: 4.919668287597232e-05 loss: 0.2052 (0.2380) time: 3.1898 data: 0.0080 max mem: 33368 +Epoch: [0] [ 950/1319] eta: 0:19:35 lr: 4.918813824140851e-05 loss: 0.2131 (0.2376) time: 3.1684 data: 0.0081 max mem: 33368 +Epoch: [0] [ 960/1319] eta: 0:19:03 lr: 4.9179593441917424e-05 loss: 0.1915 (0.2371) time: 3.1810 data: 0.0079 max mem: 33368 +Epoch: [0] [ 970/1319] eta: 0:18:32 lr: 4.917104847746404e-05 loss: 0.1936 (0.2368) time: 3.1849 data: 0.0079 max mem: 33368 +Epoch: [0] [ 980/1319] eta: 0:18:00 lr: 4.916250334801333e-05 loss: 0.2016 (0.2364) time: 3.1764 data: 0.0082 max mem: 33368 +Epoch: [0] [ 990/1319] eta: 0:17:28 lr: 4.915395805353022e-05 loss: 0.1783 (0.2359) time: 3.1696 data: 0.0079 max mem: 33368 +Epoch: [0] [1000/1319] eta: 0:16:56 lr: 4.9145412593979664e-05 loss: 0.1849 (0.2356) time: 3.1666 data: 0.0081 max mem: 33368 +Epoch: [0] [1010/1319] eta: 0:16:24 lr: 4.913686696932656e-05 loss: 0.1879 (0.2352) time: 3.1819 data: 0.0080 max mem: 33368 +Epoch: [0] [1020/1319] eta: 0:15:52 lr: 4.9128321179535836e-05 loss: 0.1849 (0.2348) time: 3.1823 data: 0.0078 max mem: 33368 +Epoch: [0] [1030/1319] eta: 0:15:20 lr: 4.911977522457237e-05 loss: 0.2025 (0.2347) time: 3.1929 data: 0.0083 max mem: 33368 +Epoch: [0] [1040/1319] eta: 0:14:49 lr: 4.9111229104401044e-05 loss: 0.2083 (0.2346) time: 3.2158 data: 0.0082 max mem: 33368 +Epoch: [0] [1050/1319] eta: 0:14:17 lr: 4.910268281898671e-05 loss: 0.2018 (0.2345) time: 3.1885 data: 0.0088 max mem: 33368 +Epoch: [0] [1060/1319] eta: 0:13:45 lr: 4.9094136368294215e-05 loss: 0.2083 (0.2342) time: 3.1568 data: 0.0092 max mem: 33368 +Epoch: [0] [1070/1319] eta: 0:13:13 lr: 4.90855897522884e-05 loss: 0.2098 (0.2340) time: 3.1490 data: 0.0080 max mem: 33368 +Epoch: [0] [1080/1319] eta: 0:12:41 lr: 4.907704297093409e-05 loss: 0.1784 (0.2335) time: 3.1572 data: 0.0075 max mem: 33368 +Epoch: [0] [1090/1319] eta: 0:12:09 lr: 4.906849602419608e-05 loss: 0.1785 (0.2335) time: 3.1434 data: 0.0075 max mem: 33368 +Epoch: [0] [1100/1319] eta: 0:11:37 lr: 4.905994891203916e-05 loss: 0.2037 (0.2333) time: 3.1459 data: 0.0079 max mem: 33368 +Epoch: [0] [1110/1319] eta: 0:11:05 lr: 4.905140163442811e-05 loss: 0.2061 (0.2331) time: 3.1887 data: 0.0084 max mem: 33368 +Epoch: [0] [1120/1319] eta: 0:10:33 lr: 4.904285419132769e-05 loss: 0.1937 (0.2328) time: 3.1921 data: 0.0081 max mem: 33368 +Epoch: [0] [1130/1319] eta: 0:10:01 lr: 4.903430658270266e-05 loss: 0.1970 (0.2327) time: 3.1829 data: 0.0080 max mem: 33368 +Epoch: [0] [1140/1319] eta: 0:09:30 lr: 4.902575880851773e-05 loss: 0.1970 (0.2323) time: 3.1721 data: 0.0082 max mem: 33368 +Epoch: [0] [1150/1319] eta: 0:08:58 lr: 4.9017210868737634e-05 loss: 0.1692 (0.2319) time: 3.1768 data: 0.0083 max mem: 33368 +Epoch: [0] [1160/1319] eta: 0:08:26 lr: 4.900866276332707e-05 loss: 0.1652 (0.2315) time: 3.1881 data: 0.0086 max mem: 33368 +Epoch: [0] [1170/1319] eta: 0:07:54 lr: 4.9000114492250734e-05 loss: 0.1742 (0.2313) time: 3.2075 data: 0.0086 max mem: 33368 +Epoch: [0] 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+Epoch: [0] [1260/1319] eta: 0:03:07 lr: 4.892317259177062e-05 loss: 0.2054 (0.2291) time: 3.1894 data: 0.0080 max mem: 33368 +Epoch: [0] [1270/1319] eta: 0:02:36 lr: 4.8914622662091334e-05 loss: 0.1956 (0.2289) time: 3.1978 data: 0.0078 max mem: 33368 +Epoch: [0] [1280/1319] eta: 0:02:04 lr: 4.890607256635692e-05 loss: 0.1809 (0.2286) time: 3.1590 data: 0.0079 max mem: 33368 +Epoch: [0] [1290/1319] eta: 0:01:32 lr: 4.8897522304531876e-05 loss: 0.1882 (0.2283) time: 3.1720 data: 0.0083 max mem: 33368 +Epoch: [0] [1300/1319] eta: 0:01:00 lr: 4.888897187658072e-05 loss: 0.1866 (0.2280) time: 3.1795 data: 0.0081 max mem: 33368 +Epoch: [0] [1310/1319] eta: 0:00:28 lr: 4.888042128246795e-05 loss: 0.1866 (0.2278) time: 3.1804 data: 0.0077 max mem: 33368 +Epoch: [0] Total time: 1:10:02 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 2:15:02 time: 3.1489 data: 3.0578 max mem: 33368 +Test: [ 100/2573] eta: 0:04:27 time: 0.0770 data: 0.0015 max mem: 33368 +Test: [ 200/2573] eta: 0:03:43 time: 0.0789 data: 0.0014 max mem: 33368 +Test: [ 300/2573] eta: 0:03:21 time: 0.0814 data: 0.0014 max mem: 33368 +Test: [ 400/2573] eta: 0:03:07 time: 0.0800 data: 0.0014 max mem: 33368 +Test: [ 500/2573] eta: 0:02:56 time: 0.0792 data: 0.0014 max mem: 33368 +Test: [ 600/2573] eta: 0:02:45 time: 0.0795 data: 0.0016 max mem: 33368 +Test: [ 700/2573] eta: 0:02:36 time: 0.0789 data: 0.0015 max mem: 33368 +Test: [ 800/2573] eta: 0:02:27 time: 0.0820 data: 0.0015 max mem: 33368 +Test: [ 900/2573] eta: 0:02:18 time: 0.0787 data: 0.0015 max mem: 33368 +Test: [1000/2573] eta: 0:02:09 time: 0.0805 data: 0.0015 max mem: 33368 +Test: [1100/2573] eta: 0:02:01 time: 0.0798 data: 0.0015 max mem: 33368 +Test: [1200/2573] eta: 0:01:52 time: 0.0796 data: 0.0014 max mem: 33368 +Test: [1300/2573] eta: 0:01:44 time: 0.0789 data: 0.0014 max mem: 33368 +Test: [1400/2573] eta: 0:01:35 time: 0.0785 data: 0.0015 max mem: 33368 +Test: [1500/2573] eta: 0:01:27 time: 0.0800 data: 0.0015 max mem: 33368 +Test: [1600/2573] eta: 0:01:19 time: 0.0833 data: 0.0016 max mem: 33368 +Test: [1700/2573] eta: 0:01:11 time: 0.0781 data: 0.0014 max mem: 33368 +Test: [1800/2573] eta: 0:01:02 time: 0.0814 data: 0.0015 max mem: 33368 +Test: [1900/2573] eta: 0:00:54 time: 0.0770 data: 0.0014 max mem: 33368 +Test: [2000/2573] eta: 0:00:46 time: 0.0787 data: 0.0014 max mem: 33368 +Test: [2100/2573] eta: 0:00:38 time: 0.0817 data: 0.0014 max mem: 33368 +Test: [2200/2573] eta: 0:00:30 time: 0.0808 data: 0.0014 max mem: 33368 +Test: [2300/2573] eta: 0:00:22 time: 0.0802 data: 0.0014 max mem: 33368 +Test: [2400/2573] eta: 0:00:13 time: 0.0766 data: 0.0014 max mem: 33368 +Test: [2500/2573] eta: 0:00:05 time: 0.0794 data: 0.0014 max mem: 33368 +Test: Total time: 0:03:28 +Final results: +Mean IoU is 31.53 + + precision@0.5 = 29.62 + precision@0.6 = 21.65 + precision@0.7 = 14.13 + precision@0.8 = 7.82 + precision@0.9 = 1.47 + overall IoU = 37.48 + +Average object IoU 31.527290309025606 +Overall IoU 37.47739028930664 +Better epoch: 0 + +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [1] [ 0/1319] eta: 1:54:05 lr: 4.8872725605668895e-05 loss: 0.1574 (0.1574) time: 5.1902 data: 1.9353 max mem: 33368 +Epoch: [1] [ 10/1319] eta: 1:13:53 lr: 4.886417469575114e-05 loss: 0.2003 (0.1948) time: 3.3872 data: 0.1824 max mem: 33368 +Epoch: [1] [ 20/1319] eta: 1:11:20 lr: 4.88556236195687e-05 loss: 0.1965 (0.1837) time: 3.2006 data: 0.0070 max mem: 33368 +Epoch: [1] [ 30/1319] eta: 1:10:20 lr: 4.884707237708599e-05 loss: 0.1721 (0.1842) time: 3.2115 data: 0.0074 max mem: 33368 +Epoch: [1] [ 40/1319] eta: 1:08:54 lr: 4.883852096826744e-05 loss: 0.1908 (0.1913) time: 3.1659 data: 0.0081 max mem: 33368 +Epoch: [1] [ 50/1319] eta: 1:08:17 lr: 4.882996939307746e-05 loss: 0.1918 (0.1919) time: 3.1586 data: 0.0084 max mem: 33368 +Epoch: [1] [ 60/1319] eta: 1:07:31 lr: 4.882141765148041e-05 loss: 0.1724 (0.1902) time: 3.1898 data: 0.0085 max mem: 33368 +Epoch: [1] [ 70/1319] eta: 1:06:59 lr: 4.881286574344069e-05 loss: 0.1718 (0.1868) time: 3.1924 data: 0.0086 max mem: 33368 +Epoch: [1] [ 80/1319] eta: 1:06:19 lr: 4.8804313668922646e-05 loss: 0.1718 (0.1872) time: 3.1915 data: 0.0088 max mem: 33368 +Epoch: [1] [ 90/1319] eta: 1:05:43 lr: 4.879576142789063e-05 loss: 0.1687 (0.1854) time: 3.1744 data: 0.0087 max mem: 33368 +Epoch: [1] [ 100/1319] eta: 1:05:09 lr: 4.878720902030896e-05 loss: 0.1764 (0.1863) time: 3.1891 data: 0.0081 max mem: 33368 +Epoch: [1] [ 110/1319] eta: 1:04:37 lr: 4.877865644614197e-05 loss: 0.1641 (0.1848) time: 3.2023 data: 0.0083 max mem: 33368 +Epoch: [1] [ 120/1319] eta: 1:03:58 lr: 4.877010370535394e-05 loss: 0.1672 (0.1858) time: 3.1733 data: 0.0083 max mem: 33368 +Epoch: [1] [ 130/1319] eta: 1:03:26 lr: 4.8761550797909164e-05 loss: 0.1773 (0.1844) time: 3.1692 data: 0.0082 max mem: 33368 +Epoch: [1] [ 140/1319] eta: 1:02:50 lr: 4.875299772377192e-05 loss: 0.1925 (0.1857) time: 3.1766 data: 0.0079 max mem: 33368 +Epoch: [1] [ 150/1319] eta: 1:02:16 lr: 4.874444448290645e-05 loss: 0.1953 (0.1866) time: 3.1642 data: 0.0075 max mem: 33368 +Epoch: [1] [ 160/1319] eta: 1:01:40 lr: 4.873589107527701e-05 loss: 0.1775 (0.1857) time: 3.1550 data: 0.0078 max mem: 33368 +Epoch: [1] [ 170/1319] eta: 1:01:04 lr: 4.872733750084782e-05 loss: 0.1800 (0.1858) time: 3.1335 data: 0.0079 max mem: 33368 +Epoch: [1] [ 180/1319] eta: 1:00:35 lr: 4.871878375958309e-05 loss: 0.1858 (0.1862) time: 3.1839 data: 0.0079 max mem: 33368 +Epoch: [1] [ 190/1319] eta: 1:00:03 lr: 4.871022985144703e-05 loss: 0.1933 (0.1873) time: 3.2130 data: 0.0080 max mem: 33368 +Epoch: [1] [ 200/1319] eta: 0:59:31 lr: 4.870167577640381e-05 loss: 0.2008 (0.1884) time: 3.1888 data: 0.0082 max mem: 33368 +Epoch: [1] [ 210/1319] eta: 0:58:56 lr: 4.869312153441761e-05 loss: 0.1883 (0.1887) time: 3.1634 data: 0.0083 max mem: 33368 +Epoch: [1] [ 220/1319] eta: 0:58:25 lr: 4.868456712545258e-05 loss: 0.1712 (0.1892) time: 3.1746 data: 0.0081 max mem: 33368 +Epoch: [1] [ 230/1319] eta: 0:57:54 lr: 4.8676012549472854e-05 loss: 0.1769 (0.1888) time: 3.2072 data: 0.0078 max mem: 33368 +Epoch: [1] [ 240/1319] eta: 0:57:20 lr: 4.866745780644256e-05 loss: 0.1699 (0.1878) time: 3.1726 data: 0.0083 max mem: 33368 +Epoch: [1] [ 250/1319] eta: 0:56:48 lr: 4.865890289632581e-05 loss: 0.1842 (0.1881) time: 3.1672 data: 0.0082 max mem: 33368 +Epoch: [1] [ 260/1319] eta: 0:56:15 lr: 4.8650347819086694e-05 loss: 0.1938 (0.1879) time: 3.1727 data: 0.0077 max mem: 33368 +Epoch: [1] [ 270/1319] eta: 0:55:41 lr: 4.864179257468931e-05 loss: 0.1679 (0.1875) time: 3.1420 data: 0.0079 max mem: 33368 +Epoch: [1] [ 280/1319] eta: 0:55:11 lr: 4.8633237163097687e-05 loss: 0.1748 (0.1881) time: 3.1803 data: 0.0081 max mem: 33368 +Epoch: [1] [ 290/1319] eta: 0:54:39 lr: 4.862468158427592e-05 loss: 0.1762 (0.1887) time: 3.2087 data: 0.0086 max mem: 33368 +Epoch: [1] [ 300/1319] eta: 0:54:06 lr: 4.861612583818801e-05 loss: 0.1762 (0.1890) time: 3.1751 data: 0.0090 max mem: 33368 +Epoch: [1] [ 310/1319] eta: 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mem: 33368 +Epoch: [1] [ 550/1319] eta: 0:40:49 lr: 4.840217771900089e-05 loss: 0.1705 (0.1879) time: 3.1787 data: 0.0078 max mem: 33368 +Epoch: [1] [ 560/1319] eta: 0:40:16 lr: 4.8393617611321754e-05 loss: 0.1629 (0.1879) time: 3.1606 data: 0.0083 max mem: 33368 +Epoch: [1] [ 570/1319] eta: 0:39:45 lr: 4.838505733539985e-05 loss: 0.1766 (0.1883) time: 3.1935 data: 0.0080 max mem: 33368 +Epoch: [1] [ 580/1319] eta: 0:39:13 lr: 4.83764968911988e-05 loss: 0.1790 (0.1881) time: 3.2160 data: 0.0082 max mem: 33368 +Epoch: [1] [ 590/1319] eta: 0:38:42 lr: 4.836793627868222e-05 loss: 0.1760 (0.1880) time: 3.1965 data: 0.0085 max mem: 33368 +Epoch: [1] [ 600/1319] eta: 0:38:10 lr: 4.835937549781368e-05 loss: 0.1785 (0.1877) time: 3.2034 data: 0.0082 max mem: 33368 +Epoch: [1] [ 610/1319] eta: 0:37:38 lr: 4.835081454855677e-05 loss: 0.1788 (0.1875) time: 3.1922 data: 0.0082 max mem: 33368 +Epoch: [1] [ 620/1319] eta: 0:37:06 lr: 4.8342253430875026e-05 loss: 0.1757 (0.1873) time: 3.1843 data: 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3.1680 data: 0.0080 max mem: 33368 +Epoch: [1] [ 710/1319] eta: 0:32:18 lr: 4.826519578660238e-05 loss: 0.1623 (0.1856) time: 3.1659 data: 0.0078 max mem: 33368 +Epoch: [1] [ 720/1319] eta: 0:31:46 lr: 4.825663298266489e-05 loss: 0.1886 (0.1857) time: 3.1861 data: 0.0075 max mem: 33368 +Epoch: [1] [ 730/1319] eta: 0:31:15 lr: 4.824807000990074e-05 loss: 0.1806 (0.1854) time: 3.1900 data: 0.0078 max mem: 33368 +Epoch: [1] [ 740/1319] eta: 0:30:43 lr: 4.82395068682733e-05 loss: 0.1497 (0.1854) time: 3.1984 data: 0.0079 max mem: 33368 +Epoch: [1] [ 750/1319] eta: 0:30:11 lr: 4.823094355774595e-05 loss: 0.1571 (0.1856) time: 3.1906 data: 0.0080 max mem: 33368 +Epoch: [1] [ 760/1319] eta: 0:29:39 lr: 4.822238007828201e-05 loss: 0.1900 (0.1857) time: 3.1653 data: 0.0078 max mem: 33368 +Epoch: [1] [ 770/1319] eta: 0:29:07 lr: 4.8213816429844826e-05 loss: 0.1960 (0.1856) time: 3.1632 data: 0.0079 max mem: 33368 +Epoch: [1] [ 780/1319] eta: 0:28:36 lr: 4.8205252612397726e-05 loss: 0.1566 (0.1852) time: 3.2110 data: 0.0084 max mem: 33368 +Epoch: [1] [ 790/1319] eta: 0:28:04 lr: 4.8196688625903984e-05 loss: 0.1567 (0.1852) time: 3.2074 data: 0.0082 max mem: 33368 +Epoch: [1] [ 800/1319] eta: 0:27:32 lr: 4.8188124470326915e-05 loss: 0.1601 (0.1850) time: 3.1889 data: 0.0076 max mem: 33369 +Epoch: [1] [ 810/1319] eta: 0:27:00 lr: 4.8179560145629784e-05 loss: 0.1629 (0.1851) time: 3.1594 data: 0.0080 max mem: 33369 +Epoch: [1] [ 820/1319] eta: 0:26:28 lr: 4.817099565177583e-05 loss: 0.1750 (0.1850) time: 3.1584 data: 0.0086 max mem: 33369 +Epoch: [1] [ 830/1319] eta: 0:25:56 lr: 4.8162430988728305e-05 loss: 0.1759 (0.1853) time: 3.1817 data: 0.0084 max mem: 33369 +Epoch: [1] [ 840/1319] eta: 0:25:24 lr: 4.815386615645044e-05 loss: 0.1666 (0.1848) time: 3.1769 data: 0.0081 max mem: 33369 +Epoch: [1] [ 850/1319] eta: 0:24:52 lr: 4.814530115490545e-05 loss: 0.1560 (0.1849) time: 3.1633 data: 0.0080 max mem: 33369 +Epoch: [1] [ 860/1319] eta: 0:24:20 lr: 4.813673598405651e-05 loss: 0.1757 (0.1848) time: 3.1610 data: 0.0081 max mem: 33369 +Epoch: [1] [ 870/1319] eta: 0:23:48 lr: 4.812817064386682e-05 loss: 0.1593 (0.1846) time: 3.1672 data: 0.0082 max mem: 33369 +Epoch: [1] [ 880/1319] eta: 0:23:17 lr: 4.8119605134299526e-05 loss: 0.1569 (0.1844) time: 3.1941 data: 0.0076 max mem: 33369 +Epoch: [1] [ 890/1319] eta: 0:22:45 lr: 4.81110394553178e-05 loss: 0.1523 (0.1842) time: 3.2037 data: 0.0077 max mem: 33369 +Epoch: [1] [ 900/1319] eta: 0:22:13 lr: 4.810247360688475e-05 loss: 0.1548 (0.1839) time: 3.1789 data: 0.0079 max mem: 33369 +Epoch: [1] [ 910/1319] eta: 0:21:41 lr: 4.809390758896352e-05 loss: 0.1477 (0.1836) time: 3.1700 data: 0.0081 max mem: 33369 +Epoch: [1] [ 920/1319] eta: 0:21:09 lr: 4.808534140151719e-05 loss: 0.1577 (0.1836) time: 3.1665 data: 0.0082 max mem: 33369 +Epoch: [1] [ 930/1319] eta: 0:20:37 lr: 4.807677504450886e-05 loss: 0.1577 (0.1834) time: 3.1672 data: 0.0079 max mem: 33369 +Epoch: [1] [ 940/1319] eta: 0:20:06 lr: 4.806820851790161e-05 loss: 0.1735 (0.1834) time: 3.1696 data: 0.0077 max mem: 33369 +Epoch: [1] [ 950/1319] eta: 0:19:34 lr: 4.805964182165848e-05 loss: 0.1861 (0.1834) time: 3.1689 data: 0.0076 max mem: 33369 +Epoch: [1] [ 960/1319] eta: 0:19:02 lr: 4.8051074955742525e-05 loss: 0.1757 (0.1832) time: 3.1620 data: 0.0078 max mem: 33369 +Epoch: [1] [ 970/1319] eta: 0:18:30 lr: 4.804250792011677e-05 loss: 0.1709 (0.1832) time: 3.1727 data: 0.0082 max mem: 33369 +Epoch: [1] [ 980/1319] eta: 0:17:58 lr: 4.803394071474422e-05 loss: 0.1772 (0.1834) time: 3.1815 data: 0.0079 max mem: 33369 +Epoch: [1] [ 990/1319] eta: 0:17:26 lr: 4.802537333958788e-05 loss: 0.1754 (0.1832) time: 3.1671 data: 0.0076 max mem: 33369 +Epoch: [1] [1000/1319] eta: 0:16:54 lr: 4.801680579461071e-05 loss: 0.1779 (0.1834) time: 3.1811 data: 0.0078 max mem: 33369 +Epoch: [1] [1010/1319] eta: 0:16:23 lr: 4.80082380797757e-05 loss: 0.1838 (0.1834) time: 3.1758 data: 0.0080 max mem: 33369 +Epoch: [1] [1020/1319] eta: 0:15:51 lr: 4.79996701950458e-05 loss: 0.2046 (0.1839) time: 3.1849 data: 0.0080 max mem: 33369 +Epoch: [1] [1030/1319] eta: 0:15:19 lr: 4.799110214038392e-05 loss: 0.2046 (0.1839) time: 3.2142 data: 0.0080 max mem: 33369 +Epoch: [1] [1040/1319] eta: 0:14:47 lr: 4.7982533915752995e-05 loss: 0.1881 (0.1840) time: 3.1871 data: 0.0080 max mem: 33369 +Epoch: [1] [1050/1319] eta: 0:14:15 lr: 4.797396552111593e-05 loss: 0.1881 (0.1839) time: 3.1839 data: 0.0080 max mem: 33369 +Epoch: [1] [1060/1319] eta: 0:13:44 lr: 4.7965396956435596e-05 loss: 0.1578 (0.1836) time: 3.2046 data: 0.0079 max mem: 33369 +Epoch: [1] [1070/1319] eta: 0:13:12 lr: 4.795682822167489e-05 loss: 0.1625 (0.1838) time: 3.2066 data: 0.0075 max mem: 33369 +Epoch: [1] [1080/1319] eta: 0:12:40 lr: 4.794825931679665e-05 loss: 0.1860 (0.1840) time: 3.1617 data: 0.0080 max mem: 33369 +Epoch: [1] [1090/1319] eta: 0:12:08 lr: 4.7939690241763725e-05 loss: 0.1596 (0.1836) time: 3.1505 data: 0.0084 max mem: 33369 +Epoch: [1] [1100/1319] eta: 0:11:36 lr: 4.793112099653894e-05 loss: 0.1514 (0.1836) time: 3.1867 data: 0.0080 max mem: 33369 +Epoch: [1] [1110/1319] eta: 0:11:05 lr: 4.79225515810851e-05 loss: 0.1508 (0.1835) time: 3.2104 data: 0.0084 max mem: 33369 +Epoch: [1] [1120/1319] eta: 0:10:33 lr: 4.791398199536501e-05 loss: 0.1645 (0.1836) time: 3.1747 data: 0.0087 max mem: 33369 +Epoch: [1] [1130/1319] eta: 0:10:01 lr: 4.790541223934144e-05 loss: 0.1850 (0.1837) time: 3.1341 data: 0.0078 max mem: 33369 +Epoch: [1] [1140/1319] eta: 0:09:29 lr: 4.7896842312977156e-05 loss: 0.1777 (0.1837) time: 3.1577 data: 0.0075 max mem: 33369 +Epoch: [1] [1150/1319] eta: 0:08:57 lr: 4.788827221623491e-05 loss: 0.1627 (0.1834) time: 3.1812 data: 0.0075 max mem: 33369 +Epoch: [1] [1160/1319] eta: 0:08:25 lr: 4.787970194907743e-05 loss: 0.1627 (0.1835) time: 3.1651 data: 0.0076 max mem: 33369 +Epoch: [1] [1170/1319] eta: 0:07:54 lr: 4.787113151146744e-05 loss: 0.1726 (0.1834) time: 3.1725 data: 0.0080 max mem: 33369 +Epoch: [1] [1180/1319] eta: 0:07:22 lr: 4.786256090336764e-05 loss: 0.1724 (0.1834) time: 3.2012 data: 0.0077 max mem: 33369 +Epoch: [1] [1190/1319] eta: 0:06:50 lr: 4.7853990124740705e-05 loss: 0.1585 (0.1832) time: 3.2143 data: 0.0075 max mem: 33369 +Epoch: [1] [1200/1319] eta: 0:06:18 lr: 4.784541917554932e-05 loss: 0.1582 (0.1830) time: 3.2066 data: 0.0079 max mem: 33369 +Epoch: [1] [1210/1319] eta: 0:05:46 lr: 4.783684805575612e-05 loss: 0.1601 (0.1830) time: 3.1741 data: 0.0080 max mem: 33369 +Epoch: [1] [1220/1319] eta: 0:05:14 lr: 4.782827676532376e-05 loss: 0.1592 (0.1828) time: 3.1522 data: 0.0078 max mem: 33369 +Epoch: [1] [1230/1319] eta: 0:04:43 lr: 4.781970530421487e-05 loss: 0.1592 (0.1827) time: 3.1619 data: 0.0080 max mem: 33369 +Epoch: [1] [1240/1319] eta: 0:04:11 lr: 4.7811133672392044e-05 loss: 0.1488 (0.1824) time: 3.1594 data: 0.0079 max mem: 33369 +Epoch: [1] [1250/1319] eta: 0:03:39 lr: 4.780256186981787e-05 loss: 0.1474 (0.1823) time: 3.1570 data: 0.0081 max mem: 33369 +Epoch: [1] [1260/1319] eta: 0:03:07 lr: 4.779398989645494e-05 loss: 0.1714 (0.1823) time: 3.1637 data: 0.0082 max mem: 33369 +Epoch: [1] [1270/1319] eta: 0:02:35 lr: 4.778541775226581e-05 loss: 0.1704 (0.1824) time: 3.1683 data: 0.0080 max mem: 33369 +Epoch: [1] [1280/1319] eta: 0:02:04 lr: 4.777684543721302e-05 loss: 0.1574 (0.1822) time: 3.1731 data: 0.0081 max mem: 33369 +Epoch: [1] [1290/1319] eta: 0:01:32 lr: 4.776827295125911e-05 loss: 0.1534 (0.1820) time: 3.1991 data: 0.0081 max mem: 33369 +Epoch: [1] [1300/1319] eta: 0:01:00 lr: 4.775970029436657e-05 loss: 0.1332 (0.1817) time: 3.1807 data: 0.0082 max mem: 33369 +Epoch: [1] [1310/1319] eta: 0:00:28 lr: 4.7751127466497925e-05 loss: 0.1569 (0.1817) time: 3.1492 data: 0.0081 max mem: 33369 +Epoch: [1] Total time: 1:09:55 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 2:07:43 time: 2.9785 data: 2.8645 max mem: 33369 +Test: [ 100/2573] eta: 0:04:20 time: 0.0763 data: 0.0014 max mem: 33369 +Test: [ 200/2573] eta: 0:03:38 time: 0.0783 data: 0.0014 max mem: 33369 +Test: [ 300/2573] eta: 0:03:18 time: 0.0802 data: 0.0015 max mem: 33369 +Test: [ 400/2573] eta: 0:03:04 time: 0.0800 data: 0.0014 max mem: 33369 +Test: [ 500/2573] eta: 0:02:53 time: 0.0782 data: 0.0015 max mem: 33369 +Test: [ 600/2573] eta: 0:02:43 time: 0.0785 data: 0.0014 max mem: 33369 +Test: [ 700/2573] eta: 0:02:35 time: 0.0798 data: 0.0015 max mem: 33369 +Test: [ 800/2573] eta: 0:02:26 time: 0.0820 data: 0.0014 max mem: 33369 +Test: [ 900/2573] eta: 0:02:17 time: 0.0799 data: 0.0015 max mem: 33369 +Test: [1000/2573] eta: 0:02:08 time: 0.0785 data: 0.0014 max mem: 33369 +Test: [1100/2573] eta: 0:02:00 time: 0.0792 data: 0.0015 max mem: 33369 +Test: [1200/2573] eta: 0:01:52 time: 0.0800 data: 0.0015 max mem: 33369 +Test: [1300/2573] eta: 0:01:43 time: 0.0803 data: 0.0014 max mem: 33369 +Test: [1400/2573] eta: 0:01:35 time: 0.0785 data: 0.0015 max mem: 33369 +Test: [1500/2573] eta: 0:01:27 time: 0.0798 data: 0.0015 max mem: 33369 +Test: [1600/2573] eta: 0:01:18 time: 0.0830 data: 0.0016 max mem: 33369 +Test: [1700/2573] eta: 0:01:10 time: 0.0778 data: 0.0015 max mem: 33369 +Test: [1800/2573] eta: 0:01:02 time: 0.0803 data: 0.0014 max mem: 33369 +Test: [1900/2573] eta: 0:00:54 time: 0.0802 data: 0.0015 max mem: 33369 +Test: [2000/2573] eta: 0:00:46 time: 0.0790 data: 0.0015 max mem: 33369 +Test: [2100/2573] eta: 0:00:38 time: 0.0820 data: 0.0015 max mem: 33369 +Test: [2200/2573] eta: 0:00:30 time: 0.0809 data: 0.0015 max mem: 33369 +Test: [2300/2573] eta: 0:00:22 time: 0.0825 data: 0.0015 max mem: 33369 +Test: [2400/2573] eta: 0:00:13 time: 0.0758 data: 0.0014 max mem: 33369 +Test: [2500/2573] eta: 0:00:05 time: 0.0799 data: 0.0015 max mem: 33369 +Test: Total time: 0:03:27 +Final results: +Mean IoU is 41.72 + + precision@0.5 = 42.75 + precision@0.6 = 33.62 + precision@0.7 = 24.37 + precision@0.8 = 14.99 + precision@0.9 = 3.92 + overall IoU = 45.33 + +Average object IoU 41.71745826286288 +Overall IoU 45.33454132080078 +Better epoch: 1 + +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [2] [ 0/1319] eta: 1:48:17 lr: 4.774341177520056e-05 loss: 0.1076 (0.1076) time: 4.9263 data: 1.6332 max mem: 33369 +Epoch: [2] [ 10/1319] eta: 1:12:48 lr: 4.773483862237391e-05 loss: 0.1802 (0.1883) time: 3.3375 data: 0.1560 max mem: 33369 +Epoch: [2] [ 20/1319] eta: 1:10:38 lr: 4.772626529846231e-05 loss: 0.1615 (0.1750) time: 3.1799 data: 0.0078 max mem: 33369 +Epoch: [2] [ 30/1319] eta: 1:09:36 lr: 4.771769180342819e-05 loss: 0.1441 (0.1671) time: 3.1862 data: 0.0076 max mem: 33369 +Epoch: [2] [ 40/1319] eta: 1:08:36 lr: 4.7709118137233964e-05 loss: 0.1383 (0.1614) time: 3.1710 data: 0.0082 max mem: 33369 +Epoch: [2] [ 50/1319] eta: 1:08:10 lr: 4.770054429984204e-05 loss: 0.1404 (0.1602) time: 3.1986 data: 0.0085 max mem: 33369 +Epoch: [2] [ 60/1319] eta: 1:07:20 lr: 4.769197029121481e-05 loss: 0.1510 (0.1611) time: 3.1920 data: 0.0085 max mem: 33369 +Epoch: [2] [ 70/1319] eta: 1:06:51 lr: 4.7683396111314645e-05 loss: 0.1630 (0.1688) time: 3.1823 data: 0.0082 max mem: 33369 +Epoch: [2] [ 80/1319] eta: 1:06:11 lr: 4.7674821760103904e-05 loss: 0.1598 (0.1666) time: 3.1918 data: 0.0085 max mem: 33369 +Epoch: [2] [ 90/1319] eta: 1:05:37 lr: 4.766624723754494e-05 loss: 0.1401 (0.1644) time: 3.1735 data: 0.0084 max mem: 33369 +Epoch: [2] [ 100/1319] eta: 1:05:01 lr: 4.7657672543600056e-05 loss: 0.1418 (0.1643) time: 3.1802 data: 0.0079 max mem: 33369 +Epoch: [2] [ 110/1319] eta: 1:04:27 lr: 4.764909767823158e-05 loss: 0.1476 (0.1629) time: 3.1797 data: 0.0083 max mem: 33369 +Epoch: [2] [ 120/1319] eta: 1:03:47 lr: 4.76405226414018e-05 loss: 0.1476 (0.1620) time: 3.1512 data: 0.0085 max mem: 33369 +Epoch: [2] [ 130/1319] eta: 1:03:18 lr: 4.7631947433073e-05 loss: 0.1392 (0.1600) time: 3.1686 data: 0.0082 max mem: 33369 +Epoch: [2] [ 140/1319] eta: 1:02:45 lr: 4.762337205320744e-05 loss: 0.1397 (0.1605) time: 3.2051 data: 0.0084 max mem: 33369 +Epoch: [2] [ 150/1319] eta: 1:02:13 lr: 4.7614796501767376e-05 loss: 0.1593 (0.1613) time: 3.1902 data: 0.0086 max mem: 33369 +Epoch: [2] [ 160/1319] eta: 1:01:42 lr: 4.760622077871502e-05 loss: 0.1614 (0.1610) time: 3.2016 data: 0.0082 max mem: 33369 +Epoch: [2] [ 170/1319] eta: 1:01:10 lr: 4.75976448840126e-05 loss: 0.1462 (0.1602) time: 3.1993 data: 0.0082 max mem: 33369 +Epoch: [2] [ 180/1319] eta: 1:00:37 lr: 4.7589068817622304e-05 loss: 0.1356 (0.1595) time: 3.1797 data: 0.0082 max mem: 33369 +Epoch: [2] [ 190/1319] eta: 1:00:04 lr: 4.758049257950633e-05 loss: 0.1457 (0.1597) time: 3.1755 data: 0.0084 max mem: 33369 +Epoch: [2] [ 200/1319] eta: 0:59:31 lr: 4.757191616962685e-05 loss: 0.1467 (0.1607) time: 3.1747 data: 0.0082 max mem: 33369 +Epoch: [2] [ 210/1319] eta: 0:58:59 lr: 4.756333958794601e-05 loss: 0.1639 (0.1600) time: 3.1799 data: 0.0082 max mem: 33369 +Epoch: [2] [ 220/1319] eta: 0:58:24 lr: 4.7554762834425936e-05 loss: 0.1454 (0.1595) time: 3.1579 data: 0.0082 max mem: 33369 +Epoch: [2] [ 230/1319] eta: 0:57:53 lr: 4.7546185909028754e-05 loss: 0.1734 (0.1612) time: 3.1698 data: 0.0081 max mem: 33369 +Epoch: [2] [ 240/1319] eta: 0:57:21 lr: 4.753760881171657e-05 loss: 0.1683 (0.1608) time: 3.2030 data: 0.0082 max mem: 33369 +Epoch: [2] [ 250/1319] eta: 0:56:50 lr: 4.7529031542451477e-05 loss: 0.1534 (0.1610) time: 3.2020 data: 0.0083 max mem: 33369 +Epoch: [2] [ 260/1319] eta: 0:56:19 lr: 4.7520454101195535e-05 loss: 0.1566 (0.1616) time: 3.2127 data: 0.0085 max mem: 33369 +Epoch: [2] [ 270/1319] eta: 0:55:47 lr: 4.751187648791081e-05 loss: 0.1566 (0.1614) time: 3.2027 data: 0.0084 max mem: 33369 +Epoch: [2] [ 280/1319] eta: 0:55:14 lr: 4.7503298702559326e-05 loss: 0.1495 (0.1617) time: 3.1695 data: 0.0081 max mem: 33369 +Epoch: [2] [ 290/1319] eta: 0:54:43 lr: 4.7494720745103136e-05 loss: 0.1495 (0.1618) time: 3.1782 data: 0.0080 max mem: 33369 +Epoch: [2] [ 300/1319] eta: 0:54:10 lr: 4.748614261550422e-05 loss: 0.1402 (0.1612) time: 3.1971 data: 0.0082 max mem: 33369 +Epoch: [2] [ 310/1319] eta: 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0.0081 max mem: 33369 +Epoch: [2] [ 710/1319] eta: 0:32:21 lr: 4.713429061603002e-05 loss: 0.1289 (0.1595) time: 3.1889 data: 0.0077 max mem: 33369 +Epoch: [2] [ 720/1319] eta: 0:31:49 lr: 4.712570522191704e-05 loss: 0.1413 (0.1593) time: 3.1497 data: 0.0078 max mem: 33369 +Epoch: [2] [ 730/1319] eta: 0:31:17 lr: 4.7117119654012416e-05 loss: 0.1437 (0.1590) time: 3.1599 data: 0.0077 max mem: 33369 +Epoch: [2] [ 740/1319] eta: 0:30:45 lr: 4.7108533912277444e-05 loss: 0.1383 (0.1589) time: 3.1777 data: 0.0075 max mem: 33369 +Epoch: [2] [ 750/1319] eta: 0:30:13 lr: 4.709994799667339e-05 loss: 0.1586 (0.1592) time: 3.1725 data: 0.0073 max mem: 33369 +Epoch: [2] [ 760/1319] eta: 0:29:41 lr: 4.709136190716153e-05 loss: 0.1567 (0.1591) time: 3.2050 data: 0.0074 max mem: 33369 +Epoch: [2] [ 770/1319] eta: 0:29:09 lr: 4.708277564370309e-05 loss: 0.1515 (0.1590) time: 3.2201 data: 0.0078 max mem: 33369 +Epoch: [2] [ 780/1319] eta: 0:28:37 lr: 4.707418920625932e-05 loss: 0.1515 (0.1591) time: 3.1654 data: 0.0079 max mem: 33369 +Epoch: [2] [ 790/1319] eta: 0:28:05 lr: 4.706560259479142e-05 loss: 0.1597 (0.1592) time: 3.1256 data: 0.0075 max mem: 33369 +Epoch: [2] [ 800/1319] eta: 0:27:33 lr: 4.705701580926059e-05 loss: 0.1595 (0.1598) time: 3.1389 data: 0.0074 max mem: 33369 +Epoch: [2] [ 810/1319] eta: 0:27:01 lr: 4.7048428849628004e-05 loss: 0.1595 (0.1599) time: 3.1664 data: 0.0073 max mem: 33369 +Epoch: [2] [ 820/1319] eta: 0:26:29 lr: 4.703984171585482e-05 loss: 0.1442 (0.1597) time: 3.1992 data: 0.0073 max mem: 33369 +Epoch: [2] [ 830/1319] eta: 0:25:57 lr: 4.703125440790219e-05 loss: 0.1442 (0.1597) time: 3.1828 data: 0.0075 max mem: 33369 +Epoch: [2] [ 840/1319] eta: 0:25:26 lr: 4.702266692573125e-05 loss: 0.1659 (0.1597) time: 3.1927 data: 0.0078 max mem: 33369 +Epoch: [2] [ 850/1319] eta: 0:24:54 lr: 4.70140792693031e-05 loss: 0.1510 (0.1596) time: 3.2168 data: 0.0083 max mem: 33369 +Epoch: [2] [ 860/1319] eta: 0:24:22 lr: 4.700549143857884e-05 loss: 0.1586 (0.1597) time: 3.2126 data: 0.0082 max mem: 33369 +Epoch: [2] [ 870/1319] eta: 0:23:50 lr: 4.699690343351954e-05 loss: 0.1570 (0.1598) time: 3.2076 data: 0.0080 max mem: 33369 +Epoch: [2] [ 880/1319] eta: 0:23:19 lr: 4.698831525408628e-05 loss: 0.1565 (0.1599) time: 3.2151 data: 0.0080 max mem: 33369 +Epoch: [2] [ 890/1319] eta: 0:22:47 lr: 4.697972690024009e-05 loss: 0.1565 (0.1599) time: 3.2035 data: 0.0082 max mem: 33369 +Epoch: [2] [ 900/1319] eta: 0:22:15 lr: 4.6971138371942025e-05 loss: 0.1297 (0.1595) time: 3.1711 data: 0.0082 max mem: 33369 +Epoch: [2] [ 910/1319] eta: 0:21:43 lr: 4.696254966915307e-05 loss: 0.1330 (0.1597) time: 3.1713 data: 0.0077 max mem: 33369 +Epoch: [2] [ 920/1319] eta: 0:21:11 lr: 4.695396079183423e-05 loss: 0.1365 (0.1598) time: 3.1857 data: 0.0072 max mem: 33369 +Epoch: [2] [ 930/1319] eta: 0:20:39 lr: 4.694537173994649e-05 loss: 0.1807 (0.1600) time: 3.2007 data: 0.0074 max mem: 33369 +Epoch: [2] [ 940/1319] eta: 0:20:07 lr: 4.69367825134508e-05 loss: 0.1605 (0.1599) time: 3.2038 data: 0.0077 max mem: 33369 +Epoch: [2] [ 950/1319] eta: 0:19:35 lr: 4.692819311230812e-05 loss: 0.1505 (0.1600) time: 3.1779 data: 0.0077 max mem: 33369 +Epoch: [2] [ 960/1319] eta: 0:19:04 lr: 4.6919603536479375e-05 loss: 0.1594 (0.1602) time: 3.1735 data: 0.0080 max mem: 33369 +Epoch: [2] [ 970/1319] eta: 0:18:32 lr: 4.691101378592547e-05 loss: 0.1540 (0.1602) time: 3.1694 data: 0.0081 max mem: 33369 +Epoch: [2] [ 980/1319] eta: 0:18:00 lr: 4.690242386060732e-05 loss: 0.1483 (0.1601) time: 3.1833 data: 0.0082 max mem: 33369 +Epoch: [2] [ 990/1319] eta: 0:17:28 lr: 4.6893833760485775e-05 loss: 0.1414 (0.1599) time: 3.2003 data: 0.0082 max mem: 33369 +Epoch: [2] [1000/1319] eta: 0:16:56 lr: 4.688524348552173e-05 loss: 0.1291 (0.1597) time: 3.1849 data: 0.0081 max mem: 33369 +Epoch: [2] [1010/1319] eta: 0:16:24 lr: 4.6876653035676014e-05 loss: 0.1432 (0.1598) time: 3.1909 data: 0.0082 max mem: 33369 +Epoch: [2] [1020/1319] eta: 0:15:52 lr: 4.6868062410909454e-05 loss: 0.1792 (0.1598) time: 3.1710 data: 0.0080 max mem: 33369 +Epoch: [2] [1030/1319] eta: 0:15:20 lr: 4.685947161118287e-05 loss: 0.1419 (0.1598) time: 3.1346 data: 0.0078 max mem: 33369 +Epoch: [2] [1040/1319] eta: 0:14:48 lr: 4.685088063645705e-05 loss: 0.1355 (0.1598) time: 3.1482 data: 0.0082 max mem: 33369 +Epoch: [2] [1050/1319] eta: 0:14:16 lr: 4.684228948669277e-05 loss: 0.1492 (0.1598) time: 3.1816 data: 0.0082 max mem: 33369 +Epoch: [2] [1060/1319] eta: 0:13:45 lr: 4.683369816185082e-05 loss: 0.1123 (0.1592) time: 3.1895 data: 0.0076 max mem: 33369 +Epoch: [2] [1070/1319] eta: 0:13:13 lr: 4.682510666189191e-05 loss: 0.1113 (0.1591) time: 3.1680 data: 0.0077 max mem: 33369 +Epoch: [2] [1080/1319] eta: 0:12:41 lr: 4.681651498677679e-05 loss: 0.1317 (0.1591) time: 3.1576 data: 0.0077 max mem: 33369 +Epoch: [2] [1090/1319] eta: 0:12:09 lr: 4.680792313646616e-05 loss: 0.1564 (0.1592) time: 3.1563 data: 0.0078 max mem: 33369 +Epoch: [2] [1100/1319] eta: 0:11:37 lr: 4.679933111092072e-05 loss: 0.1564 (0.1591) time: 3.1849 data: 0.0079 max mem: 33369 +Epoch: [2] [1110/1319] eta: 0:11:05 lr: 4.6790738910101147e-05 loss: 0.1599 (0.1594) time: 3.2206 data: 0.0080 max mem: 33369 +Epoch: [2] [1120/1319] eta: 0:10:33 lr: 4.67821465339681e-05 loss: 0.1741 (0.1594) time: 3.1811 data: 0.0081 max mem: 33369 +Epoch: [2] [1130/1319] eta: 0:10:02 lr: 4.677355398248223e-05 loss: 0.1724 (0.1596) time: 3.1810 data: 0.0078 max mem: 33369 +Epoch: [2] [1140/1319] eta: 0:09:30 lr: 4.676496125560416e-05 loss: 0.1639 (0.1596) time: 3.1960 data: 0.0078 max mem: 33369 +Epoch: [2] [1150/1319] eta: 0:08:58 lr: 4.6756368353294506e-05 loss: 0.1419 (0.1593) time: 3.2182 data: 0.0079 max mem: 33369 +Epoch: [2] [1160/1319] eta: 0:08:26 lr: 4.6747775275513856e-05 loss: 0.1152 (0.1592) time: 3.2205 data: 0.0077 max mem: 33369 +Epoch: [2] [1170/1319] eta: 0:07:54 lr: 4.6739182022222775e-05 loss: 0.1365 (0.1590) time: 3.1679 data: 0.0074 max mem: 33369 +Epoch: [2] [1180/1319] eta: 0:07:22 lr: 4.6730588593381847e-05 loss: 0.1398 (0.1590) time: 3.1659 data: 0.0075 max mem: 33369 +Epoch: [2] [1190/1319] eta: 0:06:50 lr: 4.67219949889516e-05 loss: 0.1471 (0.1592) time: 3.1807 data: 0.0082 max mem: 33369 +Epoch: [2] [1200/1319] eta: 0:06:19 lr: 4.6713401208892564e-05 loss: 0.1503 (0.1593) time: 3.1706 data: 0.0084 max mem: 33369 +Epoch: [2] [1210/1319] eta: 0:05:47 lr: 4.6704807253165246e-05 loss: 0.1717 (0.1594) time: 3.1725 data: 0.0080 max mem: 33369 +Epoch: [2] [1220/1319] eta: 0:05:15 lr: 4.6696213121730145e-05 loss: 0.1665 (0.1594) time: 3.1917 data: 0.0080 max mem: 33369 +Epoch: [2] [1230/1319] eta: 0:04:43 lr: 4.668761881454772e-05 loss: 0.1582 (0.1594) time: 3.1878 data: 0.0078 max mem: 33369 +Epoch: [2] [1240/1319] eta: 0:04:11 lr: 4.6679024331578444e-05 loss: 0.1529 (0.1596) time: 3.1747 data: 0.0075 max mem: 33369 +Epoch: [2] [1250/1319] eta: 0:03:39 lr: 4.6670429672782765e-05 loss: 0.1529 (0.1596) time: 3.1809 data: 0.0075 max mem: 33369 +Epoch: [2] [1260/1319] eta: 0:03:07 lr: 4.6661834838121084e-05 loss: 0.1510 (0.1595) time: 3.1671 data: 0.0076 max mem: 33369 +Epoch: [2] [1270/1319] eta: 0:02:36 lr: 4.665323982755382e-05 loss: 0.1398 (0.1594) time: 3.1607 data: 0.0073 max mem: 33369 +Epoch: [2] [1280/1319] eta: 0:02:04 lr: 4.664464464104137e-05 loss: 0.1490 (0.1595) time: 3.1803 data: 0.0075 max mem: 33369 +Epoch: [2] [1290/1319] eta: 0:01:32 lr: 4.6636049278544094e-05 loss: 0.1546 (0.1595) time: 3.1809 data: 0.0076 max mem: 33369 +Epoch: [2] [1300/1319] eta: 0:01:00 lr: 4.662745374002236e-05 loss: 0.1488 (0.1596) time: 3.1863 data: 0.0074 max mem: 33369 +Epoch: [2] [1310/1319] eta: 0:00:28 lr: 4.6618858025436495e-05 loss: 0.1522 (0.1597) time: 3.2059 data: 0.0073 max mem: 33369 +Epoch: [2] Total time: 1:10:01 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 3:09:52 time: 4.4278 data: 4.3432 max mem: 33369 +Test: [ 100/2573] eta: 0:04:59 time: 0.0784 data: 0.0017 max mem: 33369 +Test: [ 200/2573] eta: 0:03:57 time: 0.0787 data: 0.0015 max mem: 33369 +Test: [ 300/2573] eta: 0:03:30 time: 0.0797 data: 0.0015 max mem: 33369 +Test: [ 400/2573] eta: 0:03:13 time: 0.0801 data: 0.0014 max mem: 33369 +Test: [ 500/2573] eta: 0:03:00 time: 0.0790 data: 0.0014 max mem: 33369 +Test: [ 600/2573] eta: 0:02:49 time: 0.0785 data: 0.0014 max mem: 33369 +Test: [ 700/2573] eta: 0:02:39 time: 0.0786 data: 0.0014 max mem: 33369 +Test: [ 800/2573] eta: 0:02:29 time: 0.0818 data: 0.0013 max mem: 33369 +Test: [ 900/2573] eta: 0:02:20 time: 0.0796 data: 0.0014 max mem: 33369 +Test: [1000/2573] eta: 0:02:11 time: 0.0808 data: 0.0016 max mem: 33369 +Test: [1100/2573] eta: 0:02:02 time: 0.0785 data: 0.0013 max mem: 33369 +Test: [1200/2573] eta: 0:01:53 time: 0.0795 data: 0.0014 max mem: 33369 +Test: [1300/2573] eta: 0:01:45 time: 0.0791 data: 0.0014 max mem: 33369 +Test: [1400/2573] eta: 0:01:36 time: 0.0776 data: 0.0015 max mem: 33369 +Test: [1500/2573] eta: 0:01:28 time: 0.0794 data: 0.0014 max mem: 33369 +Test: [1600/2573] eta: 0:01:19 time: 0.0823 data: 0.0014 max mem: 33369 +Test: [1700/2573] eta: 0:01:11 time: 0.0775 data: 0.0015 max mem: 33369 +Test: [1800/2573] eta: 0:01:03 time: 0.0814 data: 0.0015 max mem: 33369 +Test: [1900/2573] eta: 0:00:54 time: 0.0784 data: 0.0017 max mem: 33369 +Test: [2000/2573] eta: 0:00:46 time: 0.0793 data: 0.0015 max mem: 33369 +Test: [2100/2573] eta: 0:00:38 time: 0.0806 data: 0.0014 max mem: 33369 +Test: [2200/2573] eta: 0:00:30 time: 0.0805 data: 0.0014 max mem: 33369 +Test: [2300/2573] eta: 0:00:22 time: 0.0803 data: 0.0014 max mem: 33369 +Test: [2400/2573] eta: 0:00:14 time: 0.0758 data: 0.0014 max mem: 33369 +Test: [2500/2573] eta: 0:00:05 time: 0.0792 data: 0.0014 max mem: 33369 +Test: Total time: 0:03:28 +Final results: +Mean IoU is 45.31 + + precision@0.5 = 49.35 + precision@0.6 = 41.63 + precision@0.7 = 32.70 + precision@0.8 = 22.39 + precision@0.9 = 7.17 + overall IoU = 48.67 + +Average object IoU 45.311768601636125 +Overall IoU 48.667537689208984 +Better epoch: 2 + +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [3] [ 0/1319] eta: 2:00:57 lr: 4.661112173174161e-05 loss: 0.0966 (0.0966) time: 5.5021 data: 2.0774 max mem: 33369 +Epoch: [3] [ 10/1319] eta: 1:12:50 lr: 4.660252568252458e-05 loss: 0.1234 (0.1353) time: 3.3391 data: 0.1962 max mem: 33369 +Epoch: [3] [ 20/1319] eta: 1:10:28 lr: 4.6593929457128314e-05 loss: 0.1234 (0.1395) time: 3.1428 data: 0.0075 max mem: 33369 +Epoch: [3] [ 30/1319] eta: 1:09:23 lr: 4.6585333055513096e-05 loss: 0.1230 (0.1332) time: 3.1698 data: 0.0075 max mem: 33369 +Epoch: [3] [ 40/1319] eta: 1:08:34 lr: 4.657673647763916e-05 loss: 0.1387 (0.1469) time: 3.1764 data: 0.0083 max mem: 33369 +Epoch: [3] [ 50/1319] eta: 1:08:09 lr: 4.656813972346675e-05 loss: 0.1368 (0.1435) time: 3.2113 data: 0.0085 max mem: 33369 +Epoch: [3] [ 60/1319] eta: 1:07:19 lr: 4.655954279295608e-05 loss: 0.1323 (0.1420) time: 3.1924 data: 0.0082 max mem: 33369 +Epoch: [3] [ 70/1319] eta: 1:06:51 lr: 4.655094568606738e-05 loss: 0.1144 (0.1401) time: 3.1849 data: 0.0078 max mem: 33369 +Epoch: [3] [ 80/1319] eta: 1:06:19 lr: 4.6542348402760813e-05 loss: 0.1144 (0.1394) time: 3.2205 data: 0.0079 max mem: 33369 +Epoch: [3] [ 90/1319] eta: 1:05:48 lr: 4.653375094299656e-05 loss: 0.1349 (0.1418) time: 3.2141 data: 0.0083 max mem: 33369 +Epoch: [3] [ 100/1319] eta: 1:05:09 lr: 4.652515330673476e-05 loss: 0.1275 (0.1419) time: 3.1876 data: 0.0083 max mem: 33369 +Epoch: [3] [ 110/1319] eta: 1:04:33 lr: 4.651655549393556e-05 loss: 0.1143 (0.1414) time: 3.1668 data: 0.0080 max mem: 33369 +Epoch: [3] [ 120/1319] eta: 1:03:59 lr: 4.650795750455908e-05 loss: 0.1185 (0.1415) time: 3.1787 data: 0.0081 max mem: 33369 +Epoch: [3] [ 130/1319] eta: 1:03:23 lr: 4.649935933856541e-05 loss: 0.1343 (0.1424) time: 3.1694 data: 0.0081 max mem: 33369 +Epoch: [3] [ 140/1319] eta: 1:02:44 lr: 4.6490760995914644e-05 loss: 0.1321 (0.1413) time: 3.1390 data: 0.0080 max mem: 33369 +Epoch: [3] [ 150/1319] eta: 1:02:11 lr: 4.648216247656684e-05 loss: 0.1217 (0.1411) time: 3.1445 data: 0.0081 max mem: 33369 +Epoch: [3] [ 160/1319] eta: 1:01:38 lr: 4.647356378048206e-05 loss: 0.1343 (0.1411) time: 3.1747 data: 0.0079 max mem: 33369 +Epoch: [3] [ 170/1319] eta: 1:01:07 lr: 4.646496490762032e-05 loss: 0.1471 (0.1423) time: 3.1961 data: 0.0082 max mem: 33369 +Epoch: [3] [ 180/1319] eta: 1:00:32 lr: 4.645636585794164e-05 loss: 0.1367 (0.1416) time: 3.1729 data: 0.0084 max mem: 33369 +Epoch: [3] [ 190/1319] eta: 1:00:00 lr: 4.644776663140602e-05 loss: 0.1250 (0.1415) time: 3.1605 data: 0.0087 max mem: 33369 +Epoch: [3] [ 200/1319] eta: 0:59:25 lr: 4.6439167227973446e-05 loss: 0.1230 (0.1420) time: 3.1622 data: 0.0085 max mem: 33369 +Epoch: [3] [ 210/1319] eta: 0:58:53 lr: 4.643056764760387e-05 loss: 0.1465 (0.1423) time: 3.1620 data: 0.0082 max mem: 33369 +Epoch: [3] [ 220/1319] eta: 0:58:18 lr: 4.642196789025724e-05 loss: 0.1465 (0.1423) time: 3.1526 data: 0.0081 max mem: 33369 +Epoch: [3] [ 230/1319] eta: 0:57:46 lr: 4.641336795589349e-05 loss: 0.1364 (0.1421) time: 3.1550 data: 0.0080 max mem: 33369 +Epoch: [3] [ 240/1319] eta: 0:57:13 lr: 4.6404767844472526e-05 loss: 0.1314 (0.1423) time: 3.1684 data: 0.0081 max mem: 33369 +Epoch: [3] [ 250/1319] eta: 0:56:42 lr: 4.639616755595424e-05 loss: 0.1363 (0.1421) time: 3.1735 data: 0.0082 max mem: 33369 +Epoch: [3] [ 260/1319] eta: 0:56:07 lr: 4.638756709029851e-05 loss: 0.1292 (0.1422) time: 3.1548 data: 0.0081 max mem: 33369 +Epoch: [3] [ 270/1319] eta: 0:55:37 lr: 4.6378966447465196e-05 loss: 0.1292 (0.1427) time: 3.1625 data: 0.0077 max mem: 33369 +Epoch: [3] [ 280/1319] eta: 0:55:05 lr: 4.637036562741414e-05 loss: 0.1284 (0.1426) time: 3.1967 data: 0.0076 max mem: 33369 +Epoch: [3] [ 290/1319] eta: 0:54:34 lr: 4.636176463010516e-05 loss: 0.1211 (0.1425) time: 3.1927 data: 0.0077 max mem: 33369 +Epoch: [3] [ 300/1319] eta: 0:54:02 lr: 4.635316345549808e-05 loss: 0.1149 (0.1415) time: 3.1965 data: 0.0078 max mem: 33369 +Epoch: [3] [ 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3.1419 data: 0.0077 max mem: 33369 +Epoch: [3] [ 630/1319] eta: 0:36:26 lr: 4.606922496512879e-05 loss: 0.1452 (0.1434) time: 3.1423 data: 0.0084 max mem: 33369 +Epoch: [3] [ 640/1319] eta: 0:35:54 lr: 4.606061773834596e-05 loss: 0.1452 (0.1435) time: 3.1539 data: 0.0083 max mem: 33369 +Epoch: [3] [ 650/1319] eta: 0:35:22 lr: 4.60520103328472e-05 loss: 0.1377 (0.1438) time: 3.1582 data: 0.0078 max mem: 33369 +Epoch: [3] [ 660/1319] eta: 0:34:50 lr: 4.60434027485917e-05 loss: 0.1395 (0.1439) time: 3.1395 data: 0.0080 max mem: 33369 +Epoch: [3] [ 670/1319] eta: 0:34:18 lr: 4.6034794985538615e-05 loss: 0.1412 (0.1438) time: 3.1195 data: 0.0079 max mem: 33369 +Epoch: [3] [ 680/1319] eta: 0:33:46 lr: 4.602618704364706e-05 loss: 0.1313 (0.1437) time: 3.1508 data: 0.0079 max mem: 33369 +Epoch: [3] [ 690/1319] eta: 0:33:14 lr: 4.601757892287618e-05 loss: 0.1342 (0.1438) time: 3.1468 data: 0.0078 max mem: 33369 +Epoch: [3] [ 700/1319] eta: 0:32:43 lr: 4.600897062318506e-05 loss: 0.1333 (0.1440) time: 3.1704 data: 0.0079 max mem: 33369 +Epoch: [3] [ 710/1319] eta: 0:32:10 lr: 4.600036214453279e-05 loss: 0.1373 (0.1442) time: 3.1508 data: 0.0082 max mem: 33369 +Epoch: [3] [ 720/1319] eta: 0:31:39 lr: 4.599175348687844e-05 loss: 0.1354 (0.1438) time: 3.1348 data: 0.0079 max mem: 33369 +Epoch: [3] [ 730/1319] eta: 0:31:07 lr: 4.598314465018106e-05 loss: 0.1182 (0.1437) time: 3.1838 data: 0.0081 max mem: 33369 +Epoch: [3] [ 740/1319] eta: 0:30:35 lr: 4.5974535634399665e-05 loss: 0.1186 (0.1437) time: 3.1683 data: 0.0087 max mem: 33369 +Epoch: [3] [ 750/1319] eta: 0:30:03 lr: 4.596592643949328e-05 loss: 0.1427 (0.1439) time: 3.1626 data: 0.0083 max mem: 33369 +Epoch: [3] [ 760/1319] eta: 0:29:31 lr: 4.595731706542089e-05 loss: 0.1347 (0.1439) time: 3.1575 data: 0.0079 max mem: 33369 +Epoch: [3] [ 770/1319] eta: 0:29:00 lr: 4.5948707512141485e-05 loss: 0.1421 (0.1440) time: 3.1403 data: 0.0078 max mem: 33369 +Epoch: [3] [ 780/1319] eta: 0:28:28 lr: 4.594009777961402e-05 loss: 0.1407 (0.1437) time: 3.1613 data: 0.0076 max mem: 33369 +Epoch: [3] [ 790/1319] eta: 0:27:56 lr: 4.593148786779743e-05 loss: 0.1407 (0.1440) time: 3.1595 data: 0.0074 max mem: 33369 +Epoch: [3] [ 800/1319] eta: 0:27:24 lr: 4.592287777665063e-05 loss: 0.1410 (0.1440) time: 3.1549 data: 0.0073 max mem: 33369 +Epoch: [3] [ 810/1319] eta: 0:26:53 lr: 4.5914267506132555e-05 loss: 0.1319 (0.1440) time: 3.1810 data: 0.0074 max mem: 33369 +Epoch: [3] [ 820/1319] eta: 0:26:21 lr: 4.590565705620206e-05 loss: 0.1242 (0.1439) time: 3.1803 data: 0.0078 max mem: 33369 +Epoch: [3] [ 830/1319] eta: 0:25:49 lr: 4.589704642681802e-05 loss: 0.1254 (0.1437) time: 3.1698 data: 0.0078 max mem: 33369 +Epoch: [3] [ 840/1319] eta: 0:25:17 lr: 4.58884356179393e-05 loss: 0.1492 (0.1441) time: 3.1442 data: 0.0079 max mem: 33369 +Epoch: [3] [ 850/1319] eta: 0:24:46 lr: 4.5879824629524725e-05 loss: 0.1397 (0.1439) time: 3.1741 data: 0.0084 max mem: 33369 +Epoch: [3] [ 860/1319] eta: 0:24:14 lr: 4.5871213461533106e-05 loss: 0.1242 (0.1441) time: 3.1745 data: 0.0083 max mem: 33369 +Epoch: [3] [ 870/1319] eta: 0:23:42 lr: 4.5862602113923244e-05 loss: 0.1275 (0.1438) time: 3.1415 data: 0.0081 max mem: 33369 +Epoch: [3] [ 880/1319] eta: 0:23:11 lr: 4.585399058665391e-05 loss: 0.1253 (0.1439) time: 3.1892 data: 0.0081 max mem: 33369 +Epoch: [3] [ 890/1319] eta: 0:22:39 lr: 4.5845378879683885e-05 loss: 0.1360 (0.1439) time: 3.1702 data: 0.0082 max mem: 33369 +Epoch: [3] [ 900/1319] eta: 0:22:07 lr: 4.583676699297189e-05 loss: 0.1377 (0.1440) time: 3.1470 data: 0.0081 max mem: 33369 +Epoch: [3] [ 910/1319] eta: 0:21:36 lr: 4.582815492647665e-05 loss: 0.1378 (0.1441) time: 3.1636 data: 0.0079 max mem: 33369 +Epoch: [3] [ 920/1319] eta: 0:21:04 lr: 4.5819542680156885e-05 loss: 0.1561 (0.1445) time: 3.1603 data: 0.0081 max mem: 33369 +Epoch: [3] [ 930/1319] eta: 0:20:32 lr: 4.5810930253971277e-05 loss: 0.1504 (0.1444) time: 3.1350 data: 0.0080 max mem: 33369 +Epoch: [3] [ 940/1319] eta: 0:20:00 lr: 4.580231764787849e-05 loss: 0.1481 (0.1447) time: 3.1434 data: 0.0072 max mem: 33369 +Epoch: [3] [ 950/1319] eta: 0:19:29 lr: 4.579370486183719e-05 loss: 0.1344 (0.1446) time: 3.1882 data: 0.0077 max mem: 33369 +Epoch: [3] [ 960/1319] eta: 0:18:57 lr: 4.5785091895806004e-05 loss: 0.1171 (0.1443) time: 3.2010 data: 0.0081 max mem: 33369 +Epoch: [3] [ 970/1319] eta: 0:18:26 lr: 4.577647874974354e-05 loss: 0.1210 (0.1443) time: 3.1966 data: 0.0076 max mem: 33369 +Epoch: [3] [ 980/1319] eta: 0:17:54 lr: 4.57678654236084e-05 loss: 0.1274 (0.1440) time: 3.1915 data: 0.0077 max mem: 33369 +Epoch: [3] [ 990/1319] eta: 0:17:22 lr: 4.575925191735917e-05 loss: 0.1069 (0.1439) time: 3.2051 data: 0.0075 max mem: 33369 +Epoch: [3] [1000/1319] eta: 0:16:51 lr: 4.57506382309544e-05 loss: 0.1257 (0.1439) time: 3.1864 data: 0.0074 max mem: 33369 +Epoch: [3] [1010/1319] eta: 0:16:19 lr: 4.574202436435264e-05 loss: 0.1263 (0.1440) time: 3.1476 data: 0.0080 max mem: 33369 +Epoch: [3] [1020/1319] eta: 0:15:47 lr: 4.573341031751242e-05 loss: 0.1289 (0.1439) time: 3.1801 data: 0.0083 max mem: 33369 +Epoch: [3] [1030/1319] eta: 0:15:16 lr: 4.5724796090392234e-05 loss: 0.1300 (0.1438) time: 3.1780 data: 0.0081 max mem: 33369 +Epoch: [3] [1040/1319] eta: 0:14:44 lr: 4.571618168295058e-05 loss: 0.1232 (0.1437) time: 3.1228 data: 0.0083 max mem: 33369 +Epoch: [3] [1050/1319] eta: 0:14:12 lr: 4.570756709514592e-05 loss: 0.1205 (0.1434) time: 3.1243 data: 0.0081 max mem: 33369 +Epoch: [3] [1060/1319] eta: 0:13:40 lr: 4.569895232693671e-05 loss: 0.1260 (0.1434) time: 3.1291 data: 0.0080 max mem: 33369 +Epoch: [3] [1070/1319] eta: 0:13:09 lr: 4.569033737828139e-05 loss: 0.1264 (0.1434) time: 3.1629 data: 0.0081 max mem: 33369 +Epoch: [3] [1080/1319] eta: 0:12:37 lr: 4.568172224913836e-05 loss: 0.1214 (0.1431) time: 3.1909 data: 0.0080 max mem: 33369 +Epoch: [3] [1090/1319] eta: 0:12:05 lr: 4.567310693946603e-05 loss: 0.1246 (0.1431) time: 3.1718 data: 0.0078 max mem: 33369 +Epoch: [3] 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+Epoch: [3] [1180/1319] eta: 0:07:20 lr: 4.559556102172276e-05 loss: 0.1333 (0.1432) time: 3.1599 data: 0.0081 max mem: 33369 +Epoch: [3] [1190/1319] eta: 0:06:48 lr: 4.5586943904465176e-05 loss: 0.1259 (0.1434) time: 3.1971 data: 0.0080 max mem: 33369 +Epoch: [3] [1200/1319] eta: 0:06:17 lr: 4.557832660621944e-05 loss: 0.1294 (0.1433) time: 3.2293 data: 0.0087 max mem: 33369 +Epoch: [3] [1210/1319] eta: 0:05:45 lr: 4.556970912694373e-05 loss: 0.1422 (0.1434) time: 3.2037 data: 0.0086 max mem: 33369 +Epoch: [3] [1220/1319] eta: 0:05:13 lr: 4.5561091466596205e-05 loss: 0.1440 (0.1435) time: 3.1690 data: 0.0082 max mem: 33369 +Epoch: [3] [1230/1319] eta: 0:04:42 lr: 4.555247362513501e-05 loss: 0.1318 (0.1433) time: 3.1646 data: 0.0083 max mem: 33369 +Epoch: [3] [1240/1319] eta: 0:04:10 lr: 4.5543855602518245e-05 loss: 0.1072 (0.1431) time: 3.1696 data: 0.0081 max mem: 33369 +Epoch: [3] [1250/1319] eta: 0:03:38 lr: 4.553523739870403e-05 loss: 0.1128 (0.1429) time: 3.1750 data: 0.0083 max mem: 33369 +Epoch: [3] [1260/1319] eta: 0:03:07 lr: 4.552661901365045e-05 loss: 0.1346 (0.1429) time: 3.1793 data: 0.0084 max mem: 33369 +Epoch: [3] [1270/1319] eta: 0:02:35 lr: 4.551800044731557e-05 loss: 0.1344 (0.1428) time: 3.1881 data: 0.0082 max mem: 33369 +Epoch: [3] [1280/1319] eta: 0:02:03 lr: 4.550938169965743e-05 loss: 0.1229 (0.1427) time: 3.1930 data: 0.0082 max mem: 33369 +Epoch: [3] [1290/1319] eta: 0:01:31 lr: 4.550076277063406e-05 loss: 0.1267 (0.1426) time: 3.1636 data: 0.0083 max mem: 33369 +Epoch: [3] [1300/1319] eta: 0:01:00 lr: 4.549214366020347e-05 loss: 0.1267 (0.1428) time: 3.1563 data: 0.0078 max mem: 33369 +Epoch: [3] [1310/1319] eta: 0:00:28 lr: 4.5483524368323656e-05 loss: 0.1517 (0.1430) time: 3.1815 data: 0.0075 max mem: 33369 +Epoch: [3] Total time: 1:09:43 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 2:15:11 time: 3.1526 data: 3.0498 max mem: 33369 +Test: [ 100/2573] eta: 0:04:25 time: 0.0771 data: 0.0015 max mem: 33369 +Test: [ 200/2573] eta: 0:03:41 time: 0.0782 data: 0.0014 max mem: 33369 +Test: [ 300/2573] eta: 0:03:19 time: 0.0799 data: 0.0014 max mem: 33369 +Test: [ 400/2573] eta: 0:03:05 time: 0.0806 data: 0.0015 max mem: 33369 +Test: [ 500/2573] eta: 0:02:54 time: 0.0783 data: 0.0014 max mem: 33369 +Test: [ 600/2573] eta: 0:02:44 time: 0.0788 data: 0.0014 max mem: 33369 +Test: [ 700/2573] eta: 0:02:35 time: 0.0789 data: 0.0014 max mem: 33369 +Test: [ 800/2573] eta: 0:02:26 time: 0.0817 data: 0.0014 max mem: 33369 +Test: [ 900/2573] eta: 0:02:17 time: 0.0795 data: 0.0014 max mem: 33369 +Test: [1000/2573] eta: 0:02:08 time: 0.0792 data: 0.0014 max mem: 33369 +Test: [1100/2573] eta: 0:02:00 time: 0.0785 data: 0.0014 max mem: 33369 +Test: [1200/2573] eta: 0:01:51 time: 0.0788 data: 0.0014 max mem: 33369 +Test: [1300/2573] eta: 0:01:43 time: 0.0799 data: 0.0015 max mem: 33369 +Test: [1400/2573] eta: 0:01:35 time: 0.0781 data: 0.0014 max mem: 33369 +Test: [1500/2573] eta: 0:01:26 time: 0.0788 data: 0.0015 max mem: 33369 +Test: [1600/2573] eta: 0:01:18 time: 0.0820 data: 0.0014 max mem: 33369 +Test: [1700/2573] eta: 0:01:10 time: 0.0784 data: 0.0014 max mem: 33369 +Test: [1800/2573] eta: 0:01:02 time: 0.0819 data: 0.0016 max mem: 33369 +Test: [1900/2573] eta: 0:00:54 time: 0.0785 data: 0.0015 max mem: 33369 +Test: [2000/2573] eta: 0:00:46 time: 0.0790 data: 0.0015 max mem: 33369 +Test: [2100/2573] eta: 0:00:38 time: 0.0808 data: 0.0013 max mem: 33369 +Test: [2200/2573] eta: 0:00:29 time: 0.0806 data: 0.0013 max mem: 33369 +Test: [2300/2573] eta: 0:00:21 time: 0.0806 data: 0.0014 max mem: 33369 +Test: [2400/2573] eta: 0:00:13 time: 0.0769 data: 0.0015 max mem: 33369 +Test: [2500/2573] eta: 0:00:05 time: 0.0801 data: 0.0014 max mem: 33369 +Test: Total time: 0:03:26 +Final results: +Mean IoU is 52.91 + + precision@0.5 = 58.29 + precision@0.6 = 49.94 + precision@0.7 = 39.28 + precision@0.8 = 26.76 + precision@0.9 = 9.93 + overall IoU = 54.19 + +Average object IoU 52.91120822516858 +Overall IoU 54.18588638305664 +Better epoch: 3 + +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [4] [ 0/1319] eta: 1:50:06 lr: 4.547576685045799e-05 loss: 0.1125 (0.1125) time: 5.0084 data: 1.7894 max mem: 33369 +Epoch: [4] [ 10/1319] eta: 1:12:59 lr: 4.546714721370884e-05 loss: 0.1186 (0.1203) time: 3.3454 data: 0.1696 max mem: 33369 +Epoch: [4] [ 20/1319] eta: 1:10:58 lr: 4.5458527395388535e-05 loss: 0.1212 (0.1199) time: 3.1921 data: 0.0074 max mem: 33369 +Epoch: [4] [ 30/1319] eta: 1:09:10 lr: 4.544990739545498e-05 loss: 0.1176 (0.1225) time: 3.1515 data: 0.0077 max mem: 33369 +Epoch: [4] [ 40/1319] eta: 1:08:09 lr: 4.544128721386609e-05 loss: 0.1100 (0.1233) time: 3.1121 data: 0.0082 max mem: 33369 +Epoch: [4] [ 50/1319] eta: 1:07:40 lr: 4.543266685057974e-05 loss: 0.0961 (0.1194) time: 3.1682 data: 0.0082 max mem: 33369 +Epoch: [4] [ 60/1319] eta: 1:06:59 lr: 4.54240463055538e-05 loss: 0.1111 (0.1217) time: 3.1835 data: 0.0082 max mem: 33369 +Epoch: [4] [ 70/1319] eta: 1:06:27 lr: 4.541542557874611e-05 loss: 0.1146 (0.1210) time: 3.1738 data: 0.0085 max mem: 33369 +Epoch: [4] [ 80/1319] eta: 1:05:55 lr: 4.540680467011449e-05 loss: 0.1101 (0.1222) time: 3.1911 data: 0.0084 max mem: 33369 +Epoch: [4] [ 90/1319] eta: 1:05:21 lr: 4.5398183579616753e-05 loss: 0.1276 (0.1247) time: 3.1837 data: 0.0083 max mem: 33369 +Epoch: [4] [ 100/1319] eta: 1:04:42 lr: 4.5389562307210684e-05 loss: 0.1301 (0.1240) time: 3.1533 data: 0.0083 max mem: 33369 +Epoch: [4] [ 110/1319] eta: 1:04:15 lr: 4.5380940852854056e-05 loss: 0.1122 (0.1245) time: 3.1831 data: 0.0083 max mem: 33369 +Epoch: [4] [ 120/1319] eta: 1:03:45 lr: 4.537231921650461e-05 loss: 0.1120 (0.1240) time: 3.2191 data: 0.0085 max mem: 33369 +Epoch: [4] [ 130/1319] eta: 1:03:16 lr: 4.53636973981201e-05 loss: 0.1079 (0.1237) time: 3.2118 data: 0.0085 max mem: 33369 +Epoch: [4] [ 140/1319] eta: 1:02:39 lr: 4.535507539765821e-05 loss: 0.1224 (0.1249) time: 3.1788 data: 0.0082 max mem: 33369 +Epoch: [4] [ 150/1319] eta: 1:02:08 lr: 4.534645321507665e-05 loss: 0.1405 (0.1269) time: 3.1657 data: 0.0081 max mem: 33369 +Epoch: [4] [ 160/1319] eta: 1:01:33 lr: 4.53378308503331e-05 loss: 0.1347 (0.1282) time: 3.1761 data: 0.0081 max mem: 33369 +Epoch: [4] [ 170/1319] eta: 1:01:04 lr: 4.532920830338521e-05 loss: 0.1324 (0.1295) time: 3.1912 data: 0.0077 max mem: 33369 +Epoch: [4] [ 180/1319] eta: 1:00:33 lr: 4.5320585574190625e-05 loss: 0.1362 (0.1298) time: 3.2112 data: 0.0075 max mem: 33369 +Epoch: [4] [ 190/1319] eta: 0:59:59 lr: 4.5311962662706955e-05 loss: 0.1243 (0.1298) time: 3.1777 data: 0.0080 max mem: 33369 +Epoch: [4] [ 200/1319] eta: 0:59:27 lr: 4.5303339568891794e-05 loss: 0.1074 (0.1284) time: 3.1699 data: 0.0087 max mem: 33369 +Epoch: [4] [ 210/1319] eta: 0:58:54 lr: 4.529471629270274e-05 loss: 0.1087 (0.1282) time: 3.1817 data: 0.0083 max mem: 33369 +Epoch: [4] [ 220/1319] eta: 0:58:19 lr: 4.5286092834097356e-05 loss: 0.1116 (0.1277) time: 3.1523 data: 0.0081 max mem: 33369 +Epoch: [4] [ 230/1319] eta: 0:57:49 lr: 4.527746919303318e-05 loss: 0.1144 (0.1280) time: 3.1743 data: 0.0083 max mem: 33369 +Epoch: [4] [ 240/1319] eta: 0:57:17 lr: 4.5268845369467734e-05 loss: 0.1144 (0.1276) time: 3.1938 data: 0.0081 max mem: 33369 +Epoch: [4] [ 250/1319] eta: 0:56:42 lr: 4.526022136335852e-05 loss: 0.1136 (0.1274) time: 3.1433 data: 0.0082 max mem: 33369 +Epoch: [4] [ 260/1319] eta: 0:56:11 lr: 4.525159717466304e-05 loss: 0.1281 (0.1284) time: 3.1583 data: 0.0088 max mem: 33369 +Epoch: [4] [ 270/1319] eta: 0:55:37 lr: 4.524297280333875e-05 loss: 0.1352 (0.1279) time: 3.1657 data: 0.0084 max mem: 33369 +Epoch: [4] [ 280/1319] eta: 0:55:06 lr: 4.5234348249343114e-05 loss: 0.1060 (0.1281) time: 3.1706 data: 0.0080 max mem: 33369 +Epoch: [4] [ 290/1319] eta: 0:54:33 lr: 4.522572351263354e-05 loss: 0.1076 (0.1281) time: 3.1752 data: 0.0081 max mem: 33369 +Epoch: [4] [ 300/1319] eta: 0:54:00 lr: 4.521709859316746e-05 loss: 0.1142 (0.1280) time: 3.1538 data: 0.0081 max mem: 33369 +Epoch: [4] [ 310/1319] eta: 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loss: 0.1253 (0.1276) time: 3.1823 data: 0.0075 max mem: 33369 +Epoch: [4] [ 870/1319] eta: 0:23:46 lr: 4.4725174693265234e-05 loss: 0.1186 (0.1277) time: 3.1677 data: 0.0080 max mem: 33369 +Epoch: [4] [ 880/1319] eta: 0:23:14 lr: 4.471653910039782e-05 loss: 0.1284 (0.1279) time: 3.1559 data: 0.0079 max mem: 33369 +Epoch: [4] [ 890/1319] eta: 0:22:43 lr: 4.4707903322227184e-05 loss: 0.1300 (0.1279) time: 3.1689 data: 0.0080 max mem: 33369 +Epoch: [4] [ 900/1319] eta: 0:22:11 lr: 4.469926735870959e-05 loss: 0.1258 (0.1280) time: 3.1612 data: 0.0087 max mem: 33369 +Epoch: [4] [ 910/1319] eta: 0:21:39 lr: 4.4690631209801266e-05 loss: 0.1151 (0.1278) time: 3.1421 data: 0.0089 max mem: 33369 +Epoch: [4] [ 920/1319] eta: 0:21:07 lr: 4.4681994875458425e-05 loss: 0.1089 (0.1277) time: 3.1789 data: 0.0084 max mem: 33369 +Epoch: [4] [ 930/1319] eta: 0:20:35 lr: 4.467335835563727e-05 loss: 0.1078 (0.1274) time: 3.2087 data: 0.0080 max mem: 33369 +Epoch: [4] [ 940/1319] eta: 0:20:04 lr: 4.466472165029396e-05 loss: 0.1169 (0.1276) time: 3.1696 data: 0.0078 max mem: 33369 +Epoch: [4] [ 950/1319] eta: 0:19:32 lr: 4.4656084759384645e-05 loss: 0.1294 (0.1277) time: 3.1473 data: 0.0078 max mem: 33369 +Epoch: [4] [ 960/1319] eta: 0:19:00 lr: 4.464744768286547e-05 loss: 0.1311 (0.1278) time: 3.1534 data: 0.0078 max mem: 33369 +Epoch: [4] [ 970/1319] eta: 0:18:28 lr: 4.463881042069255e-05 loss: 0.1232 (0.1278) time: 3.1628 data: 0.0078 max mem: 33369 +Epoch: [4] [ 980/1319] eta: 0:17:56 lr: 4.463017297282197e-05 loss: 0.1222 (0.1277) time: 3.1545 data: 0.0078 max mem: 33369 +Epoch: [4] [ 990/1319] eta: 0:17:25 lr: 4.4621535339209816e-05 loss: 0.1197 (0.1277) time: 3.1737 data: 0.0079 max mem: 33369 +Epoch: [4] [1000/1319] eta: 0:16:53 lr: 4.461289751981212e-05 loss: 0.1180 (0.1277) time: 3.2028 data: 0.0077 max mem: 33369 +Epoch: [4] [1010/1319] eta: 0:16:21 lr: 4.460425951458493e-05 loss: 0.1263 (0.1278) time: 3.1832 data: 0.0076 max mem: 33369 +Epoch: [4] [1020/1319] eta: 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+Epoch: [4] [1180/1319] eta: 0:07:21 lr: 4.4457384951110855e-05 loss: 0.1063 (0.1277) time: 3.1731 data: 0.0080 max mem: 33369 +Epoch: [4] [1190/1319] eta: 0:06:49 lr: 4.44487435934119e-05 loss: 0.1177 (0.1276) time: 3.1861 data: 0.0079 max mem: 33369 +Epoch: [4] [1200/1319] eta: 0:06:17 lr: 4.4440102049044326e-05 loss: 0.1177 (0.1278) time: 3.2273 data: 0.0076 max mem: 33369 +Epoch: [4] [1210/1319] eta: 0:05:46 lr: 4.443146031796374e-05 loss: 0.1121 (0.1277) time: 3.2324 data: 0.0077 max mem: 33369 +Epoch: [4] [1220/1319] eta: 0:05:14 lr: 4.442281840012577e-05 loss: 0.1188 (0.1279) time: 3.1961 data: 0.0079 max mem: 33369 +Epoch: [4] [1230/1319] eta: 0:04:42 lr: 4.441417629548601e-05 loss: 0.1383 (0.1279) time: 3.2127 data: 0.0077 max mem: 33369 +Epoch: [4] [1240/1319] eta: 0:04:11 lr: 4.4405534004000035e-05 loss: 0.1282 (0.1280) time: 3.2424 data: 0.0076 max mem: 33369 +Epoch: [4] [1250/1319] eta: 0:03:39 lr: 4.439689152562339e-05 loss: 0.1261 (0.1281) time: 3.2202 data: 0.0075 max mem: 33369 +Epoch: [4] [1260/1319] eta: 0:03:07 lr: 4.438824886031161e-05 loss: 0.1338 (0.1281) time: 3.2041 data: 0.0076 max mem: 33369 +Epoch: [4] [1270/1319] eta: 0:02:35 lr: 4.437960600802022e-05 loss: 0.1236 (0.1280) time: 3.2110 data: 0.0077 max mem: 33369 +Epoch: [4] [1280/1319] eta: 0:02:03 lr: 4.4370962968704706e-05 loss: 0.1028 (0.1279) time: 3.2260 data: 0.0083 max mem: 33369 +Epoch: [4] [1290/1319] eta: 0:01:32 lr: 4.436231974232054e-05 loss: 0.0968 (0.1278) time: 3.2006 data: 0.0083 max mem: 33369 +Epoch: [4] [1300/1319] eta: 0:01:00 lr: 4.435367632882316e-05 loss: 0.0968 (0.1276) time: 3.1897 data: 0.0075 max mem: 33369 +Epoch: [4] [1310/1319] eta: 0:00:28 lr: 4.434503272816803e-05 loss: 0.1043 (0.1275) time: 3.1804 data: 0.0074 max mem: 33369 +Epoch: [4] Total time: 1:09:53 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 2:15:04 time: 3.1497 data: 3.0308 max mem: 33369 +Test: [ 100/2573] eta: 0:04:26 time: 0.0770 data: 0.0014 max mem: 33369 +Test: [ 200/2573] eta: 0:03:41 time: 0.0779 data: 0.0014 max mem: 33369 +Test: [ 300/2573] eta: 0:03:19 time: 0.0792 data: 0.0014 max mem: 33369 +Test: [ 400/2573] eta: 0:03:05 time: 0.0794 data: 0.0014 max mem: 33369 +Test: [ 500/2573] eta: 0:02:54 time: 0.0789 data: 0.0016 max mem: 33369 +Test: [ 600/2573] eta: 0:02:44 time: 0.0786 data: 0.0015 max mem: 33369 +Test: [ 700/2573] eta: 0:02:35 time: 0.0794 data: 0.0016 max mem: 33369 +Test: [ 800/2573] eta: 0:02:26 time: 0.0818 data: 0.0015 max mem: 33369 +Test: [ 900/2573] eta: 0:02:17 time: 0.0788 data: 0.0015 max mem: 33369 +Test: [1000/2573] eta: 0:02:08 time: 0.0795 data: 0.0016 max mem: 33369 +Test: [1100/2573] eta: 0:02:00 time: 0.0788 data: 0.0014 max mem: 33369 +Test: [1200/2573] eta: 0:01:51 time: 0.0784 data: 0.0013 max mem: 33369 +Test: [1300/2573] eta: 0:01:43 time: 0.0785 data: 0.0014 max mem: 33369 +Test: [1400/2573] eta: 0:01:35 time: 0.0783 data: 0.0015 max mem: 33369 +Test: [1500/2573] eta: 0:01:26 time: 0.0785 data: 0.0014 max mem: 33369 +Test: [1600/2573] eta: 0:01:18 time: 0.0821 data: 0.0015 max mem: 33369 +Test: [1700/2573] eta: 0:01:10 time: 0.0776 data: 0.0014 max mem: 33369 +Test: [1800/2573] eta: 0:01:02 time: 0.0802 data: 0.0014 max mem: 33369 +Test: [1900/2573] eta: 0:00:54 time: 0.0769 data: 0.0014 max mem: 33369 +Test: [2000/2573] eta: 0:00:46 time: 0.0791 data: 0.0014 max mem: 33369 +Test: [2100/2573] eta: 0:00:37 time: 0.0809 data: 0.0015 max mem: 33369 +Test: [2200/2573] eta: 0:00:29 time: 0.0808 data: 0.0014 max mem: 33369 +Test: [2300/2573] eta: 0:00:22 time: 0.0802 data: 0.0014 max mem: 33369 +Test: [2400/2573] eta: 0:00:13 time: 0.0762 data: 0.0015 max mem: 33369 +Test: [2500/2573] eta: 0:00:05 time: 0.0785 data: 0.0014 max mem: 33369 +Test: Total time: 0:03:27 +Final results: +Mean IoU is 53.35 + + precision@0.5 = 59.58 + precision@0.6 = 52.90 + precision@0.7 = 44.08 + precision@0.8 = 32.19 + precision@0.9 = 13.38 + overall IoU = 54.11 + +Average object IoU 53.34925768382753 +Overall IoU 54.114261627197266 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [5] [ 0/1319] eta: 3:24:02 lr: 4.433725332752167e-05 loss: 0.1220 (0.1220) time: 9.2817 data: 3.0006 max mem: 33369 +Epoch: [5] [ 10/1319] eta: 1:21:51 lr: 4.432860937114392e-05 loss: 0.1086 (0.1183) time: 3.7519 data: 0.2800 max mem: 33369 +Epoch: [5] [ 20/1319] eta: 1:15:00 lr: 4.4319965227479046e-05 loss: 0.1086 (0.1202) time: 3.1735 data: 0.0079 max mem: 33369 +Epoch: [5] [ 30/1319] eta: 1:12:25 lr: 4.43113208964824e-05 loss: 0.1167 (0.1200) time: 3.1624 data: 0.0085 max mem: 33369 +Epoch: [5] [ 40/1319] eta: 1:10:58 lr: 4.43026763781093e-05 loss: 0.1054 (0.1160) time: 3.1886 data: 0.0087 max mem: 33369 +Epoch: [5] [ 50/1319] eta: 1:09:54 lr: 4.429403167231508e-05 loss: 0.1154 (0.1189) time: 3.2027 data: 0.0083 max mem: 33369 +Epoch: [5] [ 60/1319] eta: 1:09:03 lr: 4.428538677905502e-05 loss: 0.1056 (0.1179) time: 3.2116 data: 0.0081 max mem: 33369 +Epoch: [5] [ 70/1319] eta: 1:08:09 lr: 4.4276741698284395e-05 loss: 0.1028 (0.1163) time: 3.1942 data: 0.0079 max mem: 33369 +Epoch: [5] [ 80/1319] eta: 1:07:27 lr: 4.4268096429958464e-05 loss: 0.1075 (0.1164) time: 3.1921 data: 0.0081 max mem: 33369 +Epoch: [5] [ 90/1319] eta: 1:06:43 lr: 4.425945097403244e-05 loss: 0.1057 (0.1161) time: 3.1992 data: 0.0081 max mem: 33369 +Epoch: [5] [ 100/1319] eta: 1:06:02 lr: 4.425080533046155e-05 loss: 0.1012 (0.1139) time: 3.1876 data: 0.0083 max mem: 33369 +Epoch: [5] [ 110/1319] eta: 1:05:18 lr: 4.424215949920098e-05 loss: 0.1012 (0.1154) time: 3.1673 data: 0.0081 max mem: 33369 +Epoch: [5] [ 120/1319] eta: 1:04:40 lr: 4.423351348020589e-05 loss: 0.1301 (0.1170) time: 3.1640 data: 0.0076 max mem: 33369 +Epoch: [5] [ 130/1319] eta: 1:04:01 lr: 4.4224867273431445e-05 loss: 0.1098 (0.1157) time: 3.1742 data: 0.0077 max mem: 33369 +Epoch: [5] [ 140/1319] eta: 1:03:23 lr: 4.421622087883277e-05 loss: 0.1001 (0.1155) time: 3.1602 data: 0.0078 max mem: 33369 +Epoch: [5] [ 150/1319] eta: 1:02:47 lr: 4.4207574296364965e-05 loss: 0.0992 (0.1143) time: 3.1714 data: 0.0076 max mem: 33369 +Epoch: [5] [ 160/1319] eta: 1:02:11 lr: 4.419892752598312e-05 loss: 0.0906 (0.1141) time: 3.1791 data: 0.0078 max mem: 33369 +Epoch: [5] [ 170/1319] eta: 1:01:37 lr: 4.419028056764231e-05 loss: 0.1111 (0.1152) time: 3.1820 data: 0.0079 max mem: 33369 +Epoch: [5] [ 180/1319] eta: 1:01:04 lr: 4.418163342129758e-05 loss: 0.1093 (0.1144) time: 3.1953 data: 0.0082 max mem: 33369 +Epoch: [5] [ 190/1319] eta: 1:00:29 lr: 4.417298608690395e-05 loss: 0.1081 (0.1153) time: 3.1817 data: 0.0085 max mem: 33369 +Epoch: [5] [ 200/1319] eta: 0:59:56 lr: 4.416433856441643e-05 loss: 0.1157 (0.1153) time: 3.1811 data: 0.0082 max mem: 33369 +Epoch: [5] [ 210/1319] eta: 0:59:19 lr: 4.415569085379001e-05 loss: 0.1119 (0.1154) time: 3.1653 data: 0.0077 max mem: 33369 +Epoch: [5] [ 220/1319] eta: 0:58:47 lr: 4.4147042954979643e-05 loss: 0.1119 (0.1163) time: 3.1664 data: 0.0074 max mem: 33369 +Epoch: [5] [ 230/1319] eta: 0:58:14 lr: 4.413839486794028e-05 loss: 0.1235 (0.1166) time: 3.1969 data: 0.0075 max mem: 33369 +Epoch: [5] [ 240/1319] eta: 0:57:39 lr: 4.412974659262685e-05 loss: 0.1227 (0.1167) time: 3.1661 data: 0.0081 max mem: 33369 +Epoch: [5] [ 250/1319] eta: 0:57:05 lr: 4.412109812899424e-05 loss: 0.1227 (0.1165) time: 3.1489 data: 0.0082 max mem: 33369 +Epoch: [5] [ 260/1319] eta: 0:56:31 lr: 4.411244947699735e-05 loss: 0.1220 (0.1169) time: 3.1674 data: 0.0080 max mem: 33369 +Epoch: [5] [ 270/1319] eta: 0:55:57 lr: 4.4103800636591036e-05 loss: 0.1220 (0.1173) time: 3.1606 data: 0.0084 max mem: 33369 +Epoch: [5] [ 280/1319] eta: 0:55:24 lr: 4.409515160773014e-05 loss: 0.1100 (0.1176) time: 3.1581 data: 0.0089 max mem: 33369 +Epoch: [5] [ 290/1319] eta: 0:54:51 lr: 4.408650239036947e-05 loss: 0.1068 (0.1180) time: 3.1670 data: 0.0085 max mem: 33369 +Epoch: [5] [ 300/1319] eta: 0:54:17 lr: 4.407785298446384e-05 loss: 0.0965 (0.1177) time: 3.1562 data: 0.0084 max mem: 33369 +Epoch: [5] [ 310/1319] eta: 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mem: 33369 +Epoch: [5] [ 550/1319] eta: 0:40:53 lr: 4.386155642707351e-05 loss: 0.1078 (0.1177) time: 3.1504 data: 0.0075 max mem: 33369 +Epoch: [5] [ 560/1319] eta: 0:40:21 lr: 4.3852902103065404e-05 loss: 0.1165 (0.1179) time: 3.1632 data: 0.0076 max mem: 33369 +Epoch: [5] [ 570/1319] eta: 0:39:49 lr: 4.3844247589284045e-05 loss: 0.1070 (0.1178) time: 3.1834 data: 0.0081 max mem: 33369 +Epoch: [5] [ 580/1319] eta: 0:39:17 lr: 4.383559288568366e-05 loss: 0.0973 (0.1178) time: 3.1931 data: 0.0082 max mem: 33369 +Epoch: [5] [ 590/1319] eta: 0:38:45 lr: 4.382693799221843e-05 loss: 0.1040 (0.1178) time: 3.1998 data: 0.0080 max mem: 33369 +Epoch: [5] [ 600/1319] eta: 0:38:14 lr: 4.381828290884256e-05 loss: 0.1040 (0.1179) time: 3.2012 data: 0.0084 max mem: 33369 +Epoch: [5] [ 610/1319] eta: 0:37:41 lr: 4.380962763551017e-05 loss: 0.0938 (0.1176) time: 3.1842 data: 0.0081 max mem: 33369 +Epoch: [5] [ 620/1319] eta: 0:37:09 lr: 4.38009721721754e-05 loss: 0.1042 (0.1175) time: 3.1717 data: 0.0080 max mem: 33369 +Epoch: [5] [ 630/1319] eta: 0:36:38 lr: 4.3792316518792354e-05 loss: 0.0895 (0.1170) time: 3.1888 data: 0.0077 max mem: 33369 +Epoch: [5] [ 640/1319] eta: 0:36:06 lr: 4.378366067531513e-05 loss: 0.0939 (0.1172) time: 3.1905 data: 0.0076 max mem: 33369 +Epoch: [5] [ 650/1319] eta: 0:35:34 lr: 4.37750046416978e-05 loss: 0.1171 (0.1170) time: 3.1831 data: 0.0079 max mem: 33369 +Epoch: [5] [ 660/1319] eta: 0:35:02 lr: 4.376634841789439e-05 loss: 0.1039 (0.1173) time: 3.1927 data: 0.0079 max mem: 33369 +Epoch: [5] [ 670/1319] eta: 0:34:30 lr: 4.375769200385893e-05 loss: 0.1039 (0.1175) time: 3.1878 data: 0.0078 max mem: 33369 +Epoch: [5] [ 680/1319] eta: 0:33:58 lr: 4.3749035399545434e-05 loss: 0.1099 (0.1176) time: 3.1731 data: 0.0077 max mem: 33369 +Epoch: [5] [ 690/1319] eta: 0:33:25 lr: 4.374037860490788e-05 loss: 0.1099 (0.1174) time: 3.1583 data: 0.0077 max mem: 33369 +Epoch: [5] [ 700/1319] eta: 0:32:54 lr: 4.373172161990022e-05 loss: 0.1099 (0.1175) time: 3.1817 data: 0.0082 max mem: 33369 +Epoch: [5] [ 710/1319] eta: 0:32:22 lr: 4.372306444447641e-05 loss: 0.1172 (0.1176) time: 3.2151 data: 0.0079 max mem: 33369 +Epoch: [5] [ 720/1319] eta: 0:31:50 lr: 4.3714407078590355e-05 loss: 0.1020 (0.1176) time: 3.1797 data: 0.0073 max mem: 33369 +Epoch: [5] [ 730/1319] eta: 0:31:18 lr: 4.370574952219595e-05 loss: 0.1013 (0.1175) time: 3.1583 data: 0.0075 max mem: 33369 +Epoch: [5] [ 740/1319] eta: 0:30:46 lr: 4.369709177524708e-05 loss: 0.1036 (0.1176) time: 3.1747 data: 0.0078 max mem: 33369 +Epoch: [5] [ 750/1319] eta: 0:30:13 lr: 4.36884338376976e-05 loss: 0.1103 (0.1180) time: 3.1520 data: 0.0077 max mem: 33369 +Epoch: [5] [ 760/1319] eta: 0:29:42 lr: 4.3679775709501325e-05 loss: 0.0982 (0.1178) time: 3.1552 data: 0.0077 max mem: 33369 +Epoch: [5] [ 770/1319] eta: 0:29:10 lr: 4.3671117390612085e-05 loss: 0.0965 (0.1179) time: 3.2010 data: 0.0080 max mem: 33369 +Epoch: [5] [ 780/1319] eta: 0:28:38 lr: 4.366245888098367e-05 loss: 0.1212 (0.1184) time: 3.2067 data: 0.0083 max mem: 33369 +Epoch: [5] [ 790/1319] eta: 0:28:06 lr: 4.3653800180569845e-05 loss: 0.1152 (0.1185) time: 3.1877 data: 0.0082 max mem: 33369 +Epoch: [5] [ 800/1319] eta: 0:27:34 lr: 4.364514128932435e-05 loss: 0.1101 (0.1186) time: 3.1821 data: 0.0079 max mem: 33369 +Epoch: [5] [ 810/1319] eta: 0:27:02 lr: 4.363648220720092e-05 loss: 0.1021 (0.1185) time: 3.1880 data: 0.0082 max mem: 33369 +Epoch: [5] [ 820/1319] eta: 0:26:30 lr: 4.3627822934153263e-05 loss: 0.0995 (0.1184) time: 3.1876 data: 0.0082 max mem: 33369 +Epoch: [5] [ 830/1319] eta: 0:25:58 lr: 4.361916347013505e-05 loss: 0.0976 (0.1184) time: 3.1681 data: 0.0083 max mem: 33369 +Epoch: [5] [ 840/1319] eta: 0:25:26 lr: 4.361050381509995e-05 loss: 0.1029 (0.1183) time: 3.1555 data: 0.0086 max mem: 33369 +Epoch: [5] [ 850/1319] eta: 0:24:54 lr: 4.3601843969001596e-05 loss: 0.1137 (0.1182) time: 3.1443 data: 0.0086 max mem: 33369 +Epoch: [5] [ 860/1319] eta: 0:24:22 lr: 4.359318393179363e-05 loss: 0.1141 (0.1182) time: 3.1321 data: 0.0089 max mem: 33369 +Epoch: [5] [ 870/1319] eta: 0:23:50 lr: 4.3584523703429616e-05 loss: 0.1203 (0.1184) time: 3.1189 data: 0.0087 max mem: 33369 +Epoch: [5] [ 880/1319] eta: 0:23:18 lr: 4.357586328386315e-05 loss: 0.1123 (0.1184) time: 3.1329 data: 0.0085 max mem: 33369 +Epoch: [5] [ 890/1319] eta: 0:22:46 lr: 4.356720267304778e-05 loss: 0.1086 (0.1184) time: 3.1640 data: 0.0088 max mem: 33369 +Epoch: [5] [ 900/1319] eta: 0:22:14 lr: 4.3558541870937056e-05 loss: 0.1056 (0.1183) time: 3.1604 data: 0.0088 max mem: 33369 +Epoch: [5] [ 910/1319] eta: 0:21:42 lr: 4.354988087748445e-05 loss: 0.0980 (0.1180) time: 3.1717 data: 0.0080 max mem: 33369 +Epoch: [5] [ 920/1319] eta: 0:21:10 lr: 4.35412196926435e-05 loss: 0.0972 (0.1180) time: 3.1611 data: 0.0078 max mem: 33369 +Epoch: [5] [ 930/1319] eta: 0:20:38 lr: 4.353255831636764e-05 loss: 0.1199 (0.1181) time: 3.1559 data: 0.0081 max mem: 33369 +Epoch: [5] [ 940/1319] eta: 0:20:06 lr: 4.352389674861032e-05 loss: 0.1273 (0.1182) time: 3.1632 data: 0.0081 max mem: 33369 +Epoch: [5] [ 950/1319] eta: 0:19:34 lr: 4.3515234989324975e-05 loss: 0.1040 (0.1183) time: 3.1727 data: 0.0078 max mem: 33369 +Epoch: [5] [ 960/1319] eta: 0:19:02 lr: 4.350657303846501e-05 loss: 0.1001 (0.1185) time: 3.1776 data: 0.0077 max mem: 33369 +Epoch: [5] [ 970/1319] eta: 0:18:30 lr: 4.34979108959838e-05 loss: 0.1055 (0.1185) time: 3.1683 data: 0.0077 max mem: 33369 +Epoch: [5] [ 980/1319] eta: 0:17:59 lr: 4.348924856183469e-05 loss: 0.1160 (0.1187) time: 3.1639 data: 0.0076 max mem: 33369 +Epoch: [5] [ 990/1319] eta: 0:17:27 lr: 4.348058603597104e-05 loss: 0.1274 (0.1187) time: 3.2034 data: 0.0078 max mem: 33369 +Epoch: [5] [1000/1319] eta: 0:16:55 lr: 4.347192331834616e-05 loss: 0.1245 (0.1189) time: 3.2170 data: 0.0081 max mem: 33369 +Epoch: [5] [1010/1319] eta: 0:16:23 lr: 4.346326040891335e-05 loss: 0.1181 (0.1189) time: 3.2158 data: 0.0081 max mem: 33369 +Epoch: [5] [1020/1319] eta: 0:15:52 lr: 4.345459730762588e-05 loss: 0.1181 (0.1192) time: 3.2177 data: 0.0083 max mem: 33369 +Epoch: [5] [1030/1319] eta: 0:15:20 lr: 4.344593401443699e-05 loss: 0.1420 (0.1194) time: 3.1944 data: 0.0087 max mem: 33369 +Epoch: [5] [1040/1319] eta: 0:14:48 lr: 4.343727052929992e-05 loss: 0.1284 (0.1193) time: 3.1824 data: 0.0087 max mem: 33369 +Epoch: [5] [1050/1319] eta: 0:14:16 lr: 4.342860685216788e-05 loss: 0.1051 (0.1191) time: 3.1496 data: 0.0083 max mem: 33369 +Epoch: [5] [1060/1319] eta: 0:13:44 lr: 4.341994298299405e-05 loss: 0.1093 (0.1193) time: 3.1328 data: 0.0083 max mem: 33369 +Epoch: [5] [1070/1319] eta: 0:13:12 lr: 4.341127892173159e-05 loss: 0.1234 (0.1194) time: 3.1556 data: 0.0084 max mem: 33369 +Epoch: [5] [1080/1319] eta: 0:12:40 lr: 4.3402614668333656e-05 loss: 0.1047 (0.1193) time: 3.1648 data: 0.0079 max mem: 33369 +Epoch: [5] [1090/1319] eta: 0:12:08 lr: 4.339395022275336e-05 loss: 0.1019 (0.1193) time: 3.1446 data: 0.0078 max mem: 33369 +Epoch: [5] [1100/1319] eta: 0:11:36 lr: 4.33852855849438e-05 loss: 0.1032 (0.1192) time: 3.1442 data: 0.0076 max mem: 33369 +Epoch: [5] [1110/1319] eta: 0:11:05 lr: 4.337662075485806e-05 loss: 0.1069 (0.1192) time: 3.1529 data: 0.0076 max mem: 33369 +Epoch: [5] [1120/1319] eta: 0:10:33 lr: 4.3367955732449175e-05 loss: 0.1084 (0.1191) time: 3.1658 data: 0.0076 max mem: 33369 +Epoch: [5] [1130/1319] eta: 0:10:01 lr: 4.3359290517670206e-05 loss: 0.1084 (0.1191) time: 3.1674 data: 0.0081 max mem: 33369 +Epoch: [5] [1140/1319] eta: 0:09:29 lr: 4.335062511047415e-05 loss: 0.1071 (0.1190) time: 3.1462 data: 0.0083 max mem: 33369 +Epoch: [5] [1150/1319] eta: 0:08:57 lr: 4.3341959510813994e-05 loss: 0.1101 (0.1189) time: 3.1304 data: 0.0076 max mem: 33369 +Epoch: [5] [1160/1319] eta: 0:08:25 lr: 4.33332937186427e-05 loss: 0.0971 (0.1188) time: 3.1775 data: 0.0075 max mem: 33369 +Epoch: [5] [1170/1319] eta: 0:07:53 lr: 4.332462773391324e-05 loss: 0.0984 (0.1189) time: 3.1851 data: 0.0080 max mem: 33369 +Epoch: [5] [1180/1319] eta: 0:07:22 lr: 4.331596155657851e-05 loss: 0.1128 (0.1190) time: 3.1267 data: 0.0080 max mem: 33369 +Epoch: [5] [1190/1319] eta: 0:06:50 lr: 4.3307295186591415e-05 loss: 0.1128 (0.1189) time: 3.1553 data: 0.0076 max mem: 33369 +Epoch: [5] [1200/1319] eta: 0:06:18 lr: 4.329862862390485e-05 loss: 0.1128 (0.1190) time: 3.1853 data: 0.0075 max mem: 33369 +Epoch: [5] [1210/1319] eta: 0:05:46 lr: 4.328996186847165e-05 loss: 0.1145 (0.1189) time: 3.1728 data: 0.0076 max mem: 33369 +Epoch: [5] [1220/1319] eta: 0:05:14 lr: 4.328129492024467e-05 loss: 0.1011 (0.1191) time: 3.1753 data: 0.0081 max mem: 33369 +Epoch: [5] [1230/1319] eta: 0:04:43 lr: 4.3272627779176715e-05 loss: 0.0974 (0.1190) time: 3.1967 data: 0.0087 max mem: 33369 +Epoch: [5] [1240/1319] eta: 0:04:11 lr: 4.326396044522058e-05 loss: 0.0940 (0.1189) time: 3.1960 data: 0.0085 max mem: 33369 +Epoch: [5] [1250/1319] eta: 0:03:39 lr: 4.3255292918329036e-05 loss: 0.1040 (0.1190) time: 3.1621 data: 0.0081 max mem: 33369 +Epoch: [5] [1260/1319] eta: 0:03:07 lr: 4.324662519845482e-05 loss: 0.1192 (0.1192) time: 3.1510 data: 0.0085 max mem: 33369 +Epoch: [5] [1270/1319] eta: 0:02:35 lr: 4.323795728555066e-05 loss: 0.1135 (0.1192) time: 3.1666 data: 0.0091 max mem: 33369 +Epoch: [5] [1280/1319] eta: 0:02:04 lr: 4.322928917956926e-05 loss: 0.1071 (0.1192) time: 3.1970 data: 0.0085 max mem: 33369 +Epoch: [5] [1290/1319] eta: 0:01:32 lr: 4.322062088046332e-05 loss: 0.1155 (0.1193) time: 3.1935 data: 0.0078 max mem: 33369 +Epoch: [5] [1300/1319] eta: 0:01:00 lr: 4.321195238818547e-05 loss: 0.1128 (0.1193) time: 3.1641 data: 0.0078 max mem: 33369 +Epoch: [5] [1310/1319] eta: 0:00:28 lr: 4.3203283702688355e-05 loss: 0.0986 (0.1192) time: 3.1597 data: 0.0076 max mem: 33369 +Epoch: [5] Total time: 1:09:55 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 2:00:48 time: 2.8173 data: 2.6652 max mem: 33369 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 100/2573] eta: 0:04:18 time: 0.0782 data: 0.0015 max mem: 33369 +Test: [ 200/2573] eta: 0:03:38 time: 0.0778 data: 0.0015 max mem: 33369 +Test: [ 300/2573] eta: 0:03:17 time: 0.0794 data: 0.0014 max mem: 33369 +Test: [ 400/2573] eta: 0:03:04 time: 0.0798 data: 0.0015 max mem: 33369 +Test: [ 500/2573] eta: 0:02:53 time: 0.0782 data: 0.0014 max mem: 33369 +Test: [ 600/2573] eta: 0:02:43 time: 0.0789 data: 0.0015 max mem: 33369 +Test: [ 700/2573] eta: 0:02:34 time: 0.0790 data: 0.0015 max mem: 33369 +Test: [ 800/2573] eta: 0:02:25 time: 0.0827 data: 0.0015 max mem: 33369 +Test: [ 900/2573] eta: 0:02:17 time: 0.0787 data: 0.0014 max mem: 33369 +Test: [1000/2573] eta: 0:02:08 time: 0.0785 data: 0.0014 max mem: 33369 +Test: [1100/2573] eta: 0:02:00 time: 0.0794 data: 0.0015 max mem: 33369 +Test: [1200/2573] eta: 0:01:51 time: 0.0793 data: 0.0014 max mem: 33369 +Test: [1300/2573] eta: 0:01:43 time: 0.0794 data: 0.0015 max mem: 33369 +Test: [1400/2573] eta: 0:01:35 time: 0.0769 data: 0.0014 max mem: 33369 +Test: [1500/2573] eta: 0:01:27 time: 0.0816 data: 0.0015 max mem: 33369 +Test: [1600/2573] eta: 0:01:18 time: 0.0822 data: 0.0015 max mem: 33369 +Test: [1700/2573] eta: 0:01:10 time: 0.0774 data: 0.0014 max mem: 33369 +Test: [1800/2573] eta: 0:01:02 time: 0.0816 data: 0.0015 max mem: 33369 +Test: [1900/2573] eta: 0:00:54 time: 0.0778 data: 0.0015 max mem: 33369 +Test: [2000/2573] eta: 0:00:46 time: 0.0799 data: 0.0015 max mem: 33369 +Test: [2100/2573] eta: 0:00:38 time: 0.0804 data: 0.0013 max mem: 33369 +Test: [2200/2573] eta: 0:00:29 time: 0.0812 data: 0.0015 max mem: 33369 +Test: [2300/2573] eta: 0:00:21 time: 0.0803 data: 0.0014 max mem: 33369 +Test: [2400/2573] eta: 0:00:13 time: 0.0765 data: 0.0015 max mem: 33369 +Test: [2500/2573] eta: 0:00:05 time: 0.0792 data: 0.0014 max mem: 33369 +Test: Total time: 0:03:27 +Final results: +Mean IoU is 55.60 + + precision@0.5 = 62.03 + precision@0.6 = 54.82 + precision@0.7 = 45.92 + precision@0.8 = 33.84 + precision@0.9 = 14.24 + overall IoU = 55.86 + +Average object IoU 55.60350189336917 +Overall IoU 55.860233306884766 +Better epoch: 5 + +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [6] [ 0/1319] eta: 2:08:50 lr: 4.319548172049932e-05 loss: 0.0699 (0.0699) time: 5.8608 data: 2.5179 max mem: 33369 +Epoch: [6] [ 10/1319] eta: 1:15:30 lr: 4.318681266775505e-05 loss: 0.1078 (0.1029) time: 3.4610 data: 0.2367 max mem: 33369 +Epoch: [6] [ 20/1319] eta: 1:11:47 lr: 4.317814342165404e-05 loss: 0.0986 (0.1082) time: 3.1884 data: 0.0076 max mem: 33369 +Epoch: [6] [ 30/1319] eta: 1:10:26 lr: 4.316947398214883e-05 loss: 0.0838 (0.1008) time: 3.1783 data: 0.0075 max mem: 33369 +Epoch: [6] [ 40/1319] eta: 1:09:09 lr: 4.316080434919196e-05 loss: 0.0860 (0.1028) time: 3.1691 data: 0.0079 max mem: 33369 +Epoch: [6] [ 50/1319] eta: 1:08:27 lr: 4.315213452273593e-05 loss: 0.0911 (0.1006) time: 3.1716 data: 0.0081 max mem: 33369 +Epoch: [6] [ 60/1319] eta: 1:07:44 lr: 4.314346450273323e-05 loss: 0.0911 (0.1076) time: 3.1956 data: 0.0083 max mem: 33369 +Epoch: [6] [ 70/1319] eta: 1:07:00 lr: 4.313479428913631e-05 loss: 0.0955 (0.1073) time: 3.1744 data: 0.0081 max mem: 33369 +Epoch: [6] [ 80/1319] eta: 1:06:22 lr: 4.312612388189762e-05 loss: 0.0898 (0.1049) time: 3.1703 data: 0.0081 max mem: 33369 +Epoch: [6] [ 90/1319] eta: 1:05:48 lr: 4.311745328096956e-05 loss: 0.0909 (0.1055) time: 3.1903 data: 0.0078 max mem: 33369 +Epoch: [6] [ 100/1319] eta: 1:05:16 lr: 4.3108782486304546e-05 loss: 0.0961 (0.1058) time: 3.2083 data: 0.0078 max mem: 33369 +Epoch: [6] [ 110/1319] eta: 1:04:40 lr: 4.310011149785494e-05 loss: 0.1035 (0.1065) time: 3.1948 data: 0.0077 max mem: 33369 +Epoch: [6] [ 120/1319] eta: 1:04:03 lr: 4.309144031557308e-05 loss: 0.0956 (0.1061) time: 3.1702 data: 0.0083 max mem: 33369 +Epoch: [6] [ 130/1319] eta: 1:03:28 lr: 4.308276893941131e-05 loss: 0.0889 (0.1056) time: 3.1651 data: 0.0088 max mem: 33369 +Epoch: [6] [ 140/1319] eta: 1:02:56 lr: 4.307409736932192e-05 loss: 0.0818 (0.1040) time: 3.1895 data: 0.0082 max mem: 33369 +Epoch: [6] [ 150/1319] eta: 1:02:25 lr: 4.306542560525721e-05 loss: 0.0845 (0.1050) time: 3.2128 data: 0.0082 max mem: 33369 +Epoch: [6] [ 160/1319] eta: 1:01:50 lr: 4.305675364716942e-05 loss: 0.0945 (0.1046) time: 3.1895 data: 0.0083 max mem: 33369 +Epoch: [6] [ 170/1319] eta: 1:01:18 lr: 4.3048081495010805e-05 loss: 0.0928 (0.1050) time: 3.1801 data: 0.0082 max mem: 33369 +Epoch: [6] [ 180/1319] eta: 1:00:44 lr: 4.303940914873357e-05 loss: 0.1061 (0.1057) time: 3.1822 data: 0.0084 max mem: 33369 +Epoch: [6] [ 190/1319] eta: 1:00:09 lr: 4.30307366082899e-05 loss: 0.1061 (0.1058) time: 3.1636 data: 0.0081 max mem: 33369 +Epoch: [6] [ 200/1319] eta: 0:59:40 lr: 4.302206387363197e-05 loss: 0.1069 (0.1068) time: 3.1981 data: 0.0080 max mem: 33369 +Epoch: [6] [ 210/1319] eta: 0:59:07 lr: 4.301339094471194e-05 loss: 0.1000 (0.1074) time: 3.2101 data: 0.0082 max mem: 33369 +Epoch: [6] [ 220/1319] eta: 0:58:36 lr: 4.300471782148193e-05 loss: 0.1000 (0.1087) time: 3.2057 data: 0.0081 max mem: 33369 +Epoch: [6] [ 230/1319] eta: 0:58:01 lr: 4.299604450389403e-05 loss: 0.1189 (0.1092) time: 3.1840 data: 0.0080 max mem: 33369 +Epoch: [6] [ 240/1319] eta: 0:57:30 lr: 4.298737099190034e-05 loss: 0.1021 (0.1090) time: 3.1736 data: 0.0082 max mem: 33369 +Epoch: [6] [ 250/1319] eta: 0:56:58 lr: 4.297869728545289e-05 loss: 0.0989 (0.1088) time: 3.2015 data: 0.0085 max mem: 33369 +Epoch: [6] [ 260/1319] eta: 0:56:24 lr: 4.2970023384503735e-05 loss: 0.0957 (0.1082) time: 3.1739 data: 0.0083 max mem: 33369 +Epoch: [6] [ 270/1319] eta: 0:55:51 lr: 4.296134928900489e-05 loss: 0.1024 (0.1087) time: 3.1647 data: 0.0078 max mem: 33369 +Epoch: [6] [ 280/1319] eta: 0:55:18 lr: 4.295267499890832e-05 loss: 0.1097 (0.1087) time: 3.1677 data: 0.0078 max mem: 33369 +Epoch: [6] [ 290/1319] eta: 0:54:46 lr: 4.2944000514166015e-05 loss: 0.1074 (0.1089) time: 3.1799 data: 0.0077 max mem: 33369 +Epoch: [6] [ 300/1319] eta: 0:54:12 lr: 4.293532583472992e-05 loss: 0.0897 (0.1083) time: 3.1603 data: 0.0077 max mem: 33369 +Epoch: [6] [ 310/1319] eta: 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mem: 33369 +Epoch: [6] [ 550/1319] eta: 0:40:52 lr: 4.271839543231435e-05 loss: 0.1109 (0.1074) time: 3.1835 data: 0.0080 max mem: 33369 +Epoch: [6] [ 560/1319] eta: 0:40:20 lr: 4.270971567389736e-05 loss: 0.1032 (0.1075) time: 3.1581 data: 0.0082 max mem: 33369 +Epoch: [6] [ 570/1319] eta: 0:39:48 lr: 4.270103571948045e-05 loss: 0.1005 (0.1073) time: 3.1898 data: 0.0079 max mem: 33369 +Epoch: [6] [ 580/1319] eta: 0:39:16 lr: 4.2692355569014936e-05 loss: 0.0953 (0.1076) time: 3.1978 data: 0.0076 max mem: 33369 +Epoch: [6] [ 590/1319] eta: 0:38:44 lr: 4.268367522245208e-05 loss: 0.1113 (0.1076) time: 3.1775 data: 0.0075 max mem: 33369 +Epoch: [6] [ 600/1319] eta: 0:38:12 lr: 4.267499467974314e-05 loss: 0.1074 (0.1078) time: 3.1677 data: 0.0075 max mem: 33369 +Epoch: [6] [ 610/1319] eta: 0:37:39 lr: 4.2666313940839357e-05 loss: 0.1074 (0.1078) time: 3.1531 data: 0.0078 max mem: 33369 +Epoch: [6] [ 620/1319] eta: 0:37:07 lr: 4.2657633005691946e-05 loss: 0.0899 (0.1078) time: 3.1370 data: 0.0085 max mem: 33369 +Epoch: [6] [ 630/1319] eta: 0:36:35 lr: 4.264895187425208e-05 loss: 0.1022 (0.1082) time: 3.1793 data: 0.0082 max mem: 33369 +Epoch: [6] [ 640/1319] eta: 0:36:03 lr: 4.264027054647094e-05 loss: 0.0917 (0.1079) time: 3.1885 data: 0.0081 max mem: 33369 +Epoch: [6] [ 650/1319] eta: 0:35:31 lr: 4.263158902229967e-05 loss: 0.0900 (0.1080) time: 3.1729 data: 0.0081 max mem: 33369 +Epoch: [6] [ 660/1319] eta: 0:34:59 lr: 4.262290730168937e-05 loss: 0.1002 (0.1081) time: 3.1724 data: 0.0076 max mem: 33369 +Epoch: [6] [ 670/1319] eta: 0:34:27 lr: 4.261422538459115e-05 loss: 0.0954 (0.1079) time: 3.1728 data: 0.0079 max mem: 33369 +Epoch: [6] [ 680/1319] eta: 0:33:55 lr: 4.260554327095607e-05 loss: 0.0835 (0.1078) time: 3.1765 data: 0.0081 max mem: 33369 +Epoch: [6] [ 690/1319] eta: 0:33:23 lr: 4.2596860960735204e-05 loss: 0.1015 (0.1080) time: 3.1740 data: 0.0079 max mem: 33369 +Epoch: [6] [ 700/1319] eta: 0:32:51 lr: 4.258817845387955e-05 loss: 0.0991 (0.1080) time: 3.1512 data: 0.0077 max mem: 33369 +Epoch: [6] [ 710/1319] eta: 0:32:19 lr: 4.257949575034011e-05 loss: 0.0920 (0.1077) time: 3.1489 data: 0.0075 max mem: 33369 +Epoch: [6] [ 720/1319] eta: 0:31:47 lr: 4.257081285006789e-05 loss: 0.0862 (0.1077) time: 3.1707 data: 0.0074 max mem: 33369 +Epoch: [6] [ 730/1319] eta: 0:31:15 lr: 4.256212975301382e-05 loss: 0.1040 (0.1079) time: 3.1608 data: 0.0079 max mem: 33369 +Epoch: [6] [ 740/1319] eta: 0:30:43 lr: 4.255344645912884e-05 loss: 0.1040 (0.1080) time: 3.1752 data: 0.0080 max mem: 33369 +Epoch: [6] [ 750/1319] eta: 0:30:11 lr: 4.254476296836386e-05 loss: 0.0852 (0.1077) time: 3.1902 data: 0.0081 max mem: 33369 +Epoch: [6] [ 760/1319] eta: 0:29:40 lr: 4.253607928066978e-05 loss: 0.0997 (0.1080) time: 3.1948 data: 0.0081 max mem: 33369 +Epoch: [6] [ 770/1319] eta: 0:29:08 lr: 4.252739539599743e-05 loss: 0.1219 (0.1084) time: 3.1847 data: 0.0077 max mem: 33369 +Epoch: [6] [ 780/1319] eta: 0:28:36 lr: 4.2518711314297674e-05 loss: 0.1331 (0.1088) time: 3.1723 data: 0.0078 max mem: 33369 +Epoch: [6] [ 790/1319] eta: 0:28:04 lr: 4.2510027035521314e-05 loss: 0.1211 (0.1089) time: 3.1632 data: 0.0081 max mem: 33369 +Epoch: [6] [ 800/1319] eta: 0:27:32 lr: 4.250134255961916e-05 loss: 0.0960 (0.1089) time: 3.1844 data: 0.0079 max mem: 33369 +Epoch: [6] [ 810/1319] eta: 0:27:00 lr: 4.2492657886541955e-05 loss: 0.0896 (0.1088) time: 3.1957 data: 0.0079 max mem: 33369 +Epoch: [6] [ 820/1319] eta: 0:26:28 lr: 4.2483973016240455e-05 loss: 0.0911 (0.1086) time: 3.1757 data: 0.0081 max mem: 33369 +Epoch: [6] [ 830/1319] eta: 0:25:56 lr: 4.247528794866539e-05 loss: 0.0984 (0.1087) time: 3.1734 data: 0.0083 max mem: 33369 +Epoch: [6] [ 840/1319] eta: 0:25:25 lr: 4.2466602683767445e-05 loss: 0.0963 (0.1088) time: 3.1920 data: 0.0085 max mem: 33369 +Epoch: [6] [ 850/1319] eta: 0:24:53 lr: 4.24579172214973e-05 loss: 0.0990 (0.1090) time: 3.1990 data: 0.0083 max mem: 33369 +Epoch: [6] [ 860/1319] eta: 0:24:21 lr: 4.244923156180561e-05 loss: 0.0924 (0.1089) time: 3.1755 data: 0.0076 max mem: 33369 +Epoch: [6] [ 870/1319] eta: 0:23:49 lr: 4.2440545704643e-05 loss: 0.0811 (0.1087) time: 3.1516 data: 0.0075 max mem: 33369 +Epoch: [6] [ 880/1319] eta: 0:23:17 lr: 4.243185964996007e-05 loss: 0.1002 (0.1090) time: 3.1698 data: 0.0077 max mem: 33369 +Epoch: [6] [ 890/1319] eta: 0:22:45 lr: 4.24231733977074e-05 loss: 0.1107 (0.1089) time: 3.1924 data: 0.0078 max mem: 33369 +Epoch: [6] [ 900/1319] eta: 0:22:13 lr: 4.2414486947835554e-05 loss: 0.0959 (0.1091) time: 3.1825 data: 0.0078 max mem: 33369 +Epoch: [6] [ 910/1319] eta: 0:21:42 lr: 4.240580030029505e-05 loss: 0.1036 (0.1091) time: 3.1965 data: 0.0077 max mem: 33369 +Epoch: [6] [ 920/1319] eta: 0:21:10 lr: 4.239711345503641e-05 loss: 0.1121 (0.1092) time: 3.2031 data: 0.0084 max mem: 33369 +Epoch: [6] [ 930/1319] eta: 0:20:38 lr: 4.2388426412010114e-05 loss: 0.0932 (0.1092) time: 3.1992 data: 0.0083 max mem: 33369 +Epoch: [6] [ 940/1319] eta: 0:20:06 lr: 4.237973917116662e-05 loss: 0.0892 (0.1091) time: 3.1688 data: 0.0076 max mem: 33369 +Epoch: [6] [ 950/1319] eta: 0:19:34 lr: 4.237105173245638e-05 loss: 0.1023 (0.1092) time: 3.1679 data: 0.0076 max mem: 33369 +Epoch: [6] [ 960/1319] eta: 0:19:02 lr: 4.23623640958298e-05 loss: 0.1061 (0.1092) time: 3.1701 data: 0.0075 max mem: 33369 +Epoch: [6] [ 970/1319] eta: 0:18:30 lr: 4.235367626123727e-05 loss: 0.1061 (0.1094) time: 3.1575 data: 0.0073 max mem: 33369 +Epoch: [6] [ 980/1319] eta: 0:17:59 lr: 4.234498822862916e-05 loss: 0.1050 (0.1095) time: 3.1676 data: 0.0076 max mem: 33369 +Epoch: [6] [ 990/1319] eta: 0:17:27 lr: 4.23362999979558e-05 loss: 0.0968 (0.1094) time: 3.2138 data: 0.0076 max mem: 33369 +Epoch: [6] [1000/1319] eta: 0:16:55 lr: 4.2327611569167524e-05 loss: 0.1035 (0.1095) time: 3.1893 data: 0.0075 max mem: 33369 +Epoch: [6] [1010/1319] eta: 0:16:23 lr: 4.2318922942214635e-05 loss: 0.0970 (0.1093) time: 3.1608 data: 0.0080 max mem: 33369 +Epoch: [6] [1020/1319] eta: 0:15:51 lr: 4.231023411704738e-05 loss: 0.0958 (0.1093) time: 3.1929 data: 0.0081 max mem: 33369 +Epoch: [6] [1030/1319] eta: 0:15:20 lr: 4.230154509361603e-05 loss: 0.1005 (0.1094) time: 3.1905 data: 0.0076 max mem: 33369 +Epoch: [6] [1040/1319] eta: 0:14:48 lr: 4.229285587187079e-05 loss: 0.1032 (0.1094) time: 3.2056 data: 0.0077 max mem: 33369 +Epoch: [6] [1050/1319] eta: 0:14:16 lr: 4.2284166451761876e-05 loss: 0.1007 (0.1094) time: 3.2062 data: 0.0080 max mem: 33369 +Epoch: [6] [1060/1319] eta: 0:13:44 lr: 4.2275476833239456e-05 loss: 0.0894 (0.1093) time: 3.2088 data: 0.0079 max mem: 33369 +Epoch: [6] [1070/1319] eta: 0:13:12 lr: 4.2266787016253686e-05 loss: 0.0863 (0.1091) time: 3.2052 data: 0.0077 max mem: 33369 +Epoch: [6] [1080/1319] eta: 0:12:41 lr: 4.22580970007547e-05 loss: 0.0962 (0.1092) time: 3.1831 data: 0.0076 max mem: 33369 +Epoch: [6] [1090/1319] eta: 0:12:09 lr: 4.224940678669259e-05 loss: 0.0975 (0.1091) time: 3.1741 data: 0.0077 max mem: 33369 +Epoch: [6] [1100/1319] eta: 0:11:37 lr: 4.2240716374017434e-05 loss: 0.1205 (0.1094) time: 3.1747 data: 0.0078 max mem: 33369 +Epoch: [6] [1110/1319] eta: 0:11:05 lr: 4.2232025762679314e-05 loss: 0.1142 (0.1094) time: 3.1793 data: 0.0080 max mem: 33369 +Epoch: [6] [1120/1319] eta: 0:10:33 lr: 4.2223334952628234e-05 loss: 0.1012 (0.1093) time: 3.1733 data: 0.0082 max mem: 33369 +Epoch: [6] [1130/1319] eta: 0:10:01 lr: 4.221464394381422e-05 loss: 0.1056 (0.1095) time: 3.1798 data: 0.0078 max mem: 33369 +Epoch: [6] [1140/1319] eta: 0:09:29 lr: 4.220595273618725e-05 loss: 0.1077 (0.1095) time: 3.1954 data: 0.0077 max mem: 33369 +Epoch: [6] [1150/1319] eta: 0:08:58 lr: 4.2197261329697285e-05 loss: 0.1077 (0.1095) time: 3.2165 data: 0.0077 max mem: 33369 +Epoch: [6] [1160/1319] eta: 0:08:26 lr: 4.218856972429426e-05 loss: 0.1028 (0.1095) time: 3.2016 data: 0.0077 max mem: 33369 +Epoch: [6] [1170/1319] eta: 0:07:54 lr: 4.2179877919928104e-05 loss: 0.1023 (0.1095) time: 3.1679 data: 0.0085 max mem: 33369 +Epoch: [6] [1180/1319] eta: 0:07:22 lr: 4.217118591654868e-05 loss: 0.0997 (0.1094) time: 3.1772 data: 0.0089 max mem: 33369 +Epoch: [6] [1190/1319] eta: 0:06:50 lr: 4.2162493714105874e-05 loss: 0.0990 (0.1095) time: 3.1782 data: 0.0085 max mem: 33369 +Epoch: [6] [1200/1319] eta: 0:06:18 lr: 4.2153801312549505e-05 loss: 0.0968 (0.1095) time: 3.1712 data: 0.0079 max mem: 33369 +Epoch: [6] [1210/1319] eta: 0:05:47 lr: 4.2145108711829405e-05 loss: 0.0750 (0.1093) time: 3.1696 data: 0.0078 max mem: 33369 +Epoch: [6] [1220/1319] eta: 0:05:15 lr: 4.213641591189537e-05 loss: 0.0750 (0.1091) time: 3.1839 data: 0.0080 max mem: 33369 +Epoch: [6] [1230/1319] eta: 0:04:43 lr: 4.212772291269716e-05 loss: 0.0863 (0.1091) time: 3.1797 data: 0.0079 max mem: 33369 +Epoch: [6] [1240/1319] eta: 0:04:11 lr: 4.2119029714184504e-05 loss: 0.1047 (0.1093) time: 3.1691 data: 0.0081 max mem: 33369 +Epoch: [6] [1250/1319] eta: 0:03:39 lr: 4.211033631630714e-05 loss: 0.1213 (0.1095) time: 3.1644 data: 0.0086 max mem: 33369 +Epoch: [6] [1260/1319] eta: 0:03:07 lr: 4.2101642719014764e-05 loss: 0.1016 (0.1093) time: 3.1959 data: 0.0082 max mem: 33369 +Epoch: [6] [1270/1319] eta: 0:02:36 lr: 4.2092948922257045e-05 loss: 0.1038 (0.1095) time: 3.2005 data: 0.0080 max mem: 33369 +Epoch: [6] [1280/1319] eta: 0:02:04 lr: 4.208425492598362e-05 loss: 0.1160 (0.1095) time: 3.1740 data: 0.0081 max mem: 33369 +Epoch: [6] [1290/1319] eta: 0:01:32 lr: 4.207556073014412e-05 loss: 0.0969 (0.1095) time: 3.1832 data: 0.0078 max mem: 33369 +Epoch: [6] [1300/1319] eta: 0:01:00 lr: 4.2066866334688144e-05 loss: 0.0951 (0.1096) time: 3.1768 data: 0.0076 max mem: 33369 +Epoch: [6] [1310/1319] eta: 0:00:28 lr: 4.205817173956526e-05 loss: 0.0965 (0.1096) time: 3.1865 data: 0.0074 max mem: 33369 +Epoch: [6] Total time: 1:10:00 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 2:11:50 time: 3.0743 data: 2.9846 max mem: 33369 +Test: [ 100/2573] eta: 0:04:23 time: 0.0759 data: 0.0015 max mem: 33369 +Test: [ 200/2573] eta: 0:03:39 time: 0.0788 data: 0.0015 max mem: 33369 +Test: [ 300/2573] eta: 0:03:19 time: 0.0798 data: 0.0014 max mem: 33369 +Test: [ 400/2573] eta: 0:03:05 time: 0.0808 data: 0.0014 max mem: 33369 +Test: [ 500/2573] eta: 0:02:54 time: 0.0789 data: 0.0015 max mem: 33369 +Test: [ 600/2573] eta: 0:02:44 time: 0.0786 data: 0.0014 max mem: 33369 +Test: [ 700/2573] eta: 0:02:35 time: 0.0799 data: 0.0014 max mem: 33369 +Test: [ 800/2573] eta: 0:02:26 time: 0.0813 data: 0.0014 max mem: 33369 +Test: [ 900/2573] eta: 0:02:17 time: 0.0787 data: 0.0015 max mem: 33369 +Test: [1000/2573] eta: 0:02:08 time: 0.0793 data: 0.0016 max mem: 33369 +Test: [1100/2573] eta: 0:02:00 time: 0.0796 data: 0.0015 max mem: 33369 +Test: [1200/2573] eta: 0:01:52 time: 0.0787 data: 0.0013 max mem: 33369 +Test: [1300/2573] eta: 0:01:43 time: 0.0793 data: 0.0015 max mem: 33369 +Test: [1400/2573] eta: 0:01:35 time: 0.0781 data: 0.0015 max mem: 33369 +Test: [1500/2573] eta: 0:01:27 time: 0.0788 data: 0.0015 max mem: 33369 +Test: [1600/2573] eta: 0:01:18 time: 0.0816 data: 0.0014 max mem: 33369 +Test: [1700/2573] eta: 0:01:10 time: 0.0773 data: 0.0014 max mem: 33369 +Test: [1800/2573] eta: 0:01:02 time: 0.0804 data: 0.0015 max mem: 33369 +Test: [1900/2573] eta: 0:00:54 time: 0.0772 data: 0.0015 max mem: 33369 +Test: [2000/2573] eta: 0:00:46 time: 0.0791 data: 0.0014 max mem: 33369 +Test: [2100/2573] eta: 0:00:38 time: 0.0809 data: 0.0015 max mem: 33369 +Test: [2200/2573] eta: 0:00:29 time: 0.0808 data: 0.0014 max mem: 33369 +Test: [2300/2573] eta: 0:00:21 time: 0.0807 data: 0.0014 max mem: 33369 +Test: [2400/2573] eta: 0:00:13 time: 0.0773 data: 0.0015 max mem: 33369 +Test: [2500/2573] eta: 0:00:05 time: 0.0794 data: 0.0014 max mem: 33369 +Test: Total time: 0:03:26 +Final results: +Mean IoU is 57.72 + + precision@0.5 = 64.83 + precision@0.6 = 57.64 + precision@0.7 = 49.06 + precision@0.8 = 35.87 + precision@0.9 = 15.18 + overall IoU = 57.33 + +Average object IoU 57.71954610651184 +Overall IoU 57.32953643798828 +Better epoch: 6 + +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [7] [ 0/1319] eta: 2:00:42 lr: 4.205034643319776e-05 loss: 0.1202 (0.1202) time: 5.4906 data: 2.0530 max mem: 33369 +Epoch: [7] [ 10/1319] eta: 1:14:14 lr: 4.204165145856875e-05 loss: 0.1102 (0.1106) time: 3.4028 data: 0.1934 max mem: 33369 +Epoch: [7] [ 20/1319] eta: 1:11:09 lr: 4.203295628412646e-05 loss: 0.0816 (0.0951) time: 3.1766 data: 0.0078 max mem: 33369 +Epoch: [7] [ 30/1319] eta: 1:09:56 lr: 4.202426090982037e-05 loss: 0.0816 (0.0962) time: 3.1743 data: 0.0082 max mem: 33369 +Epoch: [7] [ 40/1319] eta: 1:08:55 lr: 4.201556533559993e-05 loss: 0.0879 (0.1012) time: 3.1769 data: 0.0082 max mem: 33369 +Epoch: [7] [ 50/1319] eta: 1:08:08 lr: 4.2006869561414584e-05 loss: 0.0909 (0.1012) time: 3.1705 data: 0.0083 max mem: 33369 +Epoch: [7] [ 60/1319] eta: 1:07:08 lr: 4.199817358721372e-05 loss: 0.0904 (0.0999) time: 3.1311 data: 0.0081 max mem: 33369 +Epoch: [7] [ 70/1319] eta: 1:06:34 lr: 4.1989477412946735e-05 loss: 0.1012 (0.1023) time: 3.1361 data: 0.0079 max mem: 33369 +Epoch: [7] [ 80/1319] eta: 1:05:58 lr: 4.1980781038562975e-05 loss: 0.1017 (0.1011) time: 3.1812 data: 0.0079 max mem: 33369 +Epoch: [7] [ 90/1319] eta: 1:05:32 lr: 4.1972084464011784e-05 loss: 0.0950 (0.0999) time: 3.2054 data: 0.0083 max mem: 33369 +Epoch: [7] [ 100/1319] eta: 1:04:50 lr: 4.1963387689242456e-05 loss: 0.0971 (0.1011) time: 3.1776 data: 0.0082 max mem: 33369 +Epoch: [7] [ 110/1319] eta: 1:04:21 lr: 4.1954690714204276e-05 loss: 0.0894 (0.1002) time: 3.1684 data: 0.0079 max mem: 33369 +Epoch: [7] [ 120/1319] eta: 1:03:50 lr: 4.194599353884651e-05 loss: 0.0958 (0.1029) time: 3.2102 data: 0.0079 max mem: 33369 +Epoch: [7] [ 130/1319] eta: 1:03:07 lr: 4.193729616311839e-05 loss: 0.0904 (0.1018) time: 3.1404 data: 0.0080 max mem: 33369 +Epoch: [7] [ 140/1319] eta: 1:02:31 lr: 4.1928598586969124e-05 loss: 0.0942 (0.1043) time: 3.1057 data: 0.0084 max mem: 33369 +Epoch: [7] [ 150/1319] eta: 1:01:55 lr: 4.1919900810347894e-05 loss: 0.1073 (0.1037) time: 3.1308 data: 0.0080 max mem: 33369 +Epoch: [7] [ 160/1319] eta: 1:01:26 lr: 4.191120283320388e-05 loss: 0.0870 (0.1034) time: 3.1689 data: 0.0076 max mem: 33369 +Epoch: [7] [ 170/1319] eta: 1:00:50 lr: 4.190250465548619e-05 loss: 0.0819 (0.1020) time: 3.1703 data: 0.0083 max mem: 33369 +Epoch: [7] [ 180/1319] eta: 1:00:24 lr: 4.189380627714394e-05 loss: 0.0769 (0.1014) time: 3.1935 data: 0.0086 max mem: 33369 +Epoch: [7] [ 190/1319] eta: 0:59:51 lr: 4.188510769812624e-05 loss: 0.0805 (0.1007) time: 3.2105 data: 0.0078 max mem: 33369 +Epoch: [7] [ 200/1319] eta: 0:59:18 lr: 4.1876408918382123e-05 loss: 0.0794 (0.1006) time: 3.1667 data: 0.0078 max mem: 33369 +Epoch: [7] [ 210/1319] eta: 0:58:47 lr: 4.1867709937860646e-05 loss: 0.0797 (0.1004) time: 3.1778 data: 0.0084 max mem: 33369 +Epoch: [7] [ 220/1319] eta: 0:58:12 lr: 4.185901075651081e-05 loss: 0.0797 (0.0998) time: 3.1575 data: 0.0082 max mem: 33369 +Epoch: [7] [ 230/1319] eta: 0:57:41 lr: 4.185031137428161e-05 loss: 0.0802 (0.0994) time: 3.1552 data: 0.0080 max mem: 33369 +Epoch: [7] [ 240/1319] eta: 0:57:10 lr: 4.1841611791121996e-05 loss: 0.0827 (0.0990) time: 3.1944 data: 0.0080 max mem: 33369 +Epoch: [7] [ 250/1319] eta: 0:56:42 lr: 4.183291200698093e-05 loss: 0.0823 (0.0988) time: 3.2298 data: 0.0078 max mem: 33369 +Epoch: [7] [ 260/1319] eta: 0:56:09 lr: 4.182421202180731e-05 loss: 0.0857 (0.0984) time: 3.2129 data: 0.0077 max mem: 33369 +Epoch: [7] [ 270/1319] eta: 0:55:36 lr: 4.181551183555002e-05 loss: 0.0913 (0.0991) time: 3.1562 data: 0.0076 max mem: 33369 +Epoch: [7] [ 280/1319] eta: 0:55:03 lr: 4.180681144815793e-05 loss: 0.0922 (0.0992) time: 3.1376 data: 0.0081 max mem: 33369 +Epoch: [7] [ 290/1319] eta: 0:54:30 lr: 4.179811085957988e-05 loss: 0.0809 (0.0986) time: 3.1524 data: 0.0081 max mem: 33369 +Epoch: [7] [ 300/1319] eta: 0:53:58 lr: 4.178941006976469e-05 loss: 0.0835 (0.0983) time: 3.1720 data: 0.0074 max mem: 33369 +Epoch: [7] [ 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+Epoch: [7] [1100/1319] eta: 0:11:35 lr: 4.109269029695397e-05 loss: 0.0973 (0.1005) time: 3.1501 data: 0.0083 max mem: 33369 +Epoch: [7] [1110/1319] eta: 0:11:03 lr: 4.108397303462358e-05 loss: 0.1010 (0.1007) time: 3.1670 data: 0.0077 max mem: 33369 +Epoch: [7] [1120/1319] eta: 0:10:31 lr: 4.1075255566772506e-05 loss: 0.1072 (0.1007) time: 3.1416 data: 0.0078 max mem: 33369 +Epoch: [7] [1130/1319] eta: 0:09:59 lr: 4.106653789334745e-05 loss: 0.1046 (0.1008) time: 3.1384 data: 0.0081 max mem: 33369 +Epoch: [7] [1140/1319] eta: 0:09:28 lr: 4.105782001429505e-05 loss: 0.1097 (0.1011) time: 3.1772 data: 0.0082 max mem: 33369 +Epoch: [7] [1150/1319] eta: 0:08:56 lr: 4.104910192956196e-05 loss: 0.1018 (0.1011) time: 3.1711 data: 0.0078 max mem: 33369 +Epoch: [7] [1160/1319] eta: 0:08:24 lr: 4.104038363909479e-05 loss: 0.0934 (0.1011) time: 3.1683 data: 0.0075 max mem: 33369 +Epoch: [7] [1170/1319] eta: 0:07:52 lr: 4.1031665142840106e-05 loss: 0.0867 (0.1010) time: 3.1712 data: 0.0077 max mem: 33369 +Epoch: [7] [1180/1319] eta: 0:07:21 lr: 4.1022946440744476e-05 loss: 0.0867 (0.1011) time: 3.2013 data: 0.0075 max mem: 33369 +Epoch: [7] [1190/1319] eta: 0:06:49 lr: 4.1014227532754415e-05 loss: 0.0902 (0.1011) time: 3.2018 data: 0.0075 max mem: 33369 +Epoch: [7] [1200/1319] eta: 0:06:17 lr: 4.100550841881645e-05 loss: 0.0844 (0.1011) time: 3.1650 data: 0.0079 max mem: 33369 +Epoch: [7] [1210/1319] eta: 0:05:46 lr: 4.099678909887704e-05 loss: 0.0813 (0.1010) time: 3.1741 data: 0.0080 max mem: 33369 +Epoch: [7] [1220/1319] eta: 0:05:14 lr: 4.098806957288263e-05 loss: 0.0886 (0.1010) time: 3.1979 data: 0.0078 max mem: 33369 +Epoch: [7] [1230/1319] eta: 0:04:42 lr: 4.0979349840779665e-05 loss: 0.0928 (0.1010) time: 3.2206 data: 0.0076 max mem: 33369 +Epoch: [7] [1240/1319] eta: 0:04:10 lr: 4.0970629902514516e-05 loss: 0.0875 (0.1009) time: 3.2250 data: 0.0078 max mem: 33369 +Epoch: [7] [1250/1319] eta: 0:03:39 lr: 4.0961909758033565e-05 loss: 0.0875 (0.1009) time: 3.1989 data: 0.0079 max mem: 33369 +Epoch: [7] [1260/1319] eta: 0:03:07 lr: 4.095318940728316e-05 loss: 0.0999 (0.1010) time: 3.1722 data: 0.0075 max mem: 33369 +Epoch: [7] [1270/1319] eta: 0:02:35 lr: 4.0944468850209605e-05 loss: 0.0865 (0.1009) time: 3.1614 data: 0.0075 max mem: 33369 +Epoch: [7] [1280/1319] eta: 0:02:03 lr: 4.093574808675919e-05 loss: 0.0797 (0.1008) time: 3.1556 data: 0.0079 max mem: 33369 +Epoch: [7] [1290/1319] eta: 0:01:32 lr: 4.09270271168782e-05 loss: 0.0846 (0.1008) time: 3.1455 data: 0.0080 max mem: 33369 +Epoch: [7] [1300/1319] eta: 0:01:00 lr: 4.091830594051285e-05 loss: 0.1088 (0.1009) time: 3.1668 data: 0.0076 max mem: 33369 +Epoch: [7] [1310/1319] eta: 0:00:28 lr: 4.090958455760934e-05 loss: 0.0881 (0.1008) time: 3.1746 data: 0.0074 max mem: 33369 +Epoch: [7] Total time: 1:09:48 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 2:36:27 time: 3.6484 data: 3.5535 max mem: 33369 +Test: [ 100/2573] eta: 0:04:37 time: 0.0775 data: 0.0014 max mem: 33369 +Test: [ 200/2573] eta: 0:03:47 time: 0.0784 data: 0.0016 max mem: 33369 +Test: [ 300/2573] eta: 0:03:23 time: 0.0795 data: 0.0014 max mem: 33369 +Test: [ 400/2573] eta: 0:03:08 time: 0.0799 data: 0.0014 max mem: 33369 +Test: [ 500/2573] eta: 0:02:56 time: 0.0793 data: 0.0015 max mem: 33369 +Test: [ 600/2573] eta: 0:02:45 time: 0.0789 data: 0.0014 max mem: 33369 +Test: [ 700/2573] eta: 0:02:36 time: 0.0784 data: 0.0015 max mem: 33369 +Test: [ 800/2573] eta: 0:02:27 time: 0.0814 data: 0.0013 max mem: 33369 +Test: [ 900/2573] eta: 0:02:18 time: 0.0791 data: 0.0015 max mem: 33369 +Test: [1000/2573] eta: 0:02:09 time: 0.0797 data: 0.0014 max mem: 33369 +Test: [1100/2573] eta: 0:02:00 time: 0.0796 data: 0.0014 max mem: 33369 +Test: [1200/2573] eta: 0:01:52 time: 0.0797 data: 0.0016 max mem: 33369 +Test: [1300/2573] eta: 0:01:44 time: 0.0786 data: 0.0014 max mem: 33369 +Test: [1400/2573] eta: 0:01:35 time: 0.0769 data: 0.0014 max mem: 33369 +Test: [1500/2573] eta: 0:01:27 time: 0.0797 data: 0.0014 max mem: 33369 +Test: [1600/2573] eta: 0:01:19 time: 0.0829 data: 0.0016 max mem: 33369 +Test: [1700/2573] eta: 0:01:10 time: 0.0774 data: 0.0014 max mem: 33369 +Test: [1800/2573] eta: 0:01:02 time: 0.0814 data: 0.0015 max mem: 33369 +Test: [1900/2573] eta: 0:00:54 time: 0.0780 data: 0.0015 max mem: 33369 +Test: [2000/2573] eta: 0:00:46 time: 0.0797 data: 0.0014 max mem: 33369 +Test: [2100/2573] eta: 0:00:38 time: 0.0809 data: 0.0014 max mem: 33369 +Test: [2200/2573] eta: 0:00:30 time: 0.0812 data: 0.0015 max mem: 33369 +Test: [2300/2573] eta: 0:00:22 time: 0.0810 data: 0.0014 max mem: 33369 +Test: [2400/2573] eta: 0:00:13 time: 0.0769 data: 0.0015 max mem: 33369 +Test: [2500/2573] eta: 0:00:05 time: 0.0790 data: 0.0014 max mem: 33369 +Test: Total time: 0:03:27 +Final results: +Mean IoU is 58.71 + + precision@0.5 = 65.83 + precision@0.6 = 58.37 + precision@0.7 = 49.59 + precision@0.8 = 37.19 + precision@0.9 = 16.14 + overall IoU = 58.70 + +Average object IoU 58.711548225445455 +Overall IoU 58.702293395996094 +Better epoch: 7 + +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [8] [ 0/1319] eta: 1:55:12 lr: 4.09017351363616e-05 loss: 0.1044 (0.1044) time: 5.2405 data: 1.9392 max mem: 33369 +Epoch: [8] [ 10/1319] eta: 1:12:49 lr: 4.089301336088734e-05 loss: 0.0836 (0.0894) time: 3.3382 data: 0.1833 max mem: 33369 +Epoch: [8] [ 20/1319] eta: 1:10:24 lr: 4.088429137871879e-05 loss: 0.0859 (0.0910) time: 3.1525 data: 0.0082 max mem: 33369 +Epoch: [8] [ 30/1319] eta: 1:09:27 lr: 4.087556918980205e-05 loss: 0.0859 (0.0907) time: 3.1757 data: 0.0082 max mem: 33369 +Epoch: [8] [ 40/1319] eta: 1:08:20 lr: 4.0866846794083216e-05 loss: 0.0766 (0.0868) time: 3.1585 data: 0.0078 max mem: 33369 +Epoch: [8] [ 50/1319] eta: 1:07:40 lr: 4.0858124191508315e-05 loss: 0.0789 (0.0898) time: 3.1480 data: 0.0080 max mem: 33369 +Epoch: [8] [ 60/1319] eta: 1:06:57 lr: 4.08494013820234e-05 loss: 0.0998 (0.0945) time: 3.1588 data: 0.0078 max mem: 33369 +Epoch: [8] [ 70/1319] eta: 1:06:29 lr: 4.0840678365574436e-05 loss: 0.1004 (0.0977) time: 3.1799 data: 0.0079 max mem: 33369 +Epoch: [8] [ 80/1319] eta: 1:05:56 lr: 4.083195514210742e-05 loss: 0.0903 (0.0961) time: 3.2026 data: 0.0081 max mem: 33369 +Epoch: [8] [ 90/1319] eta: 1:05:23 lr: 4.0823231711568287e-05 loss: 0.0743 (0.0941) time: 3.1847 data: 0.0089 max mem: 33369 +Epoch: [8] [ 100/1319] eta: 1:04:45 lr: 4.081450807390295e-05 loss: 0.0754 (0.0932) time: 3.1606 data: 0.0088 max mem: 33369 +Epoch: [8] [ 110/1319] eta: 1:04:11 lr: 4.0805784229057304e-05 loss: 0.0759 (0.0927) time: 3.1583 data: 0.0078 max mem: 33369 +Epoch: [8] [ 120/1319] eta: 1:03:38 lr: 4.079706017697721e-05 loss: 0.0851 (0.0930) time: 3.1702 data: 0.0077 max mem: 33369 +Epoch: [8] [ 130/1319] eta: 1:03:05 lr: 4.0788335917608504e-05 loss: 0.0895 (0.0931) time: 3.1692 data: 0.0077 max mem: 33369 +Epoch: [8] [ 140/1319] eta: 1:02:36 lr: 4.077961145089699e-05 loss: 0.0796 (0.0919) time: 3.1969 data: 0.0076 max mem: 33369 +Epoch: [8] [ 150/1319] eta: 1:02:05 lr: 4.0770886776788466e-05 loss: 0.0745 (0.0919) time: 3.2113 data: 0.0076 max mem: 33369 +Epoch: [8] [ 160/1319] eta: 1:01:37 lr: 4.076216189522867e-05 loss: 0.0969 (0.0926) time: 3.2167 data: 0.0082 max mem: 33369 +Epoch: [8] [ 170/1319] eta: 1:01:05 lr: 4.075343680616333e-05 loss: 0.0932 (0.0931) time: 3.2142 data: 0.0085 max mem: 33369 +Epoch: [8] [ 180/1319] eta: 1:00:36 lr: 4.074471150953815e-05 loss: 0.0701 (0.0927) time: 3.2117 data: 0.0084 max mem: 33369 +Epoch: [8] [ 190/1319] eta: 1:00:01 lr: 4.0735986005298814e-05 loss: 0.0871 (0.0925) time: 3.1867 data: 0.0085 max mem: 33369 +Epoch: [8] [ 200/1319] eta: 0:59:30 lr: 4.072726029339096e-05 loss: 0.0902 (0.0923) time: 3.1789 data: 0.0084 max mem: 33369 +Epoch: [8] [ 210/1319] eta: 0:58:59 lr: 4.07185343737602e-05 loss: 0.0859 (0.0919) time: 3.2039 data: 0.0082 max mem: 33369 +Epoch: [8] [ 220/1319] eta: 0:58:26 lr: 4.070980824635213e-05 loss: 0.0739 (0.0914) time: 3.1837 data: 0.0081 max mem: 33369 +Epoch: [8] [ 230/1319] eta: 0:57:51 lr: 4.070108191111232e-05 loss: 0.0691 (0.0914) time: 3.1558 data: 0.0081 max mem: 33369 +Epoch: [8] [ 240/1319] eta: 0:57:21 lr: 4.069235536798631e-05 loss: 0.0715 (0.0905) time: 3.1781 data: 0.0080 max mem: 33369 +Epoch: [8] [ 250/1319] eta: 0:56:48 lr: 4.0683628616919596e-05 loss: 0.0766 (0.0900) time: 3.1868 data: 0.0077 max mem: 33369 +Epoch: [8] [ 260/1319] eta: 0:56:17 lr: 4.0674901657857675e-05 loss: 0.0798 (0.0901) time: 3.1910 data: 0.0080 max mem: 33369 +Epoch: [8] [ 270/1319] eta: 0:55:44 lr: 4.066617449074599e-05 loss: 0.0820 (0.0904) time: 3.1934 data: 0.0083 max mem: 33369 +Epoch: [8] [ 280/1319] eta: 0:55:13 lr: 4.065744711552997e-05 loss: 0.0890 (0.0915) time: 3.1827 data: 0.0088 max mem: 33369 +Epoch: [8] [ 290/1319] eta: 0:54:40 lr: 4.064871953215503e-05 loss: 0.0982 (0.0919) time: 3.1843 data: 0.0095 max mem: 33369 +Epoch: [8] [ 300/1319] eta: 0:54:07 lr: 4.063999174056654e-05 loss: 0.0848 (0.0915) time: 3.1548 data: 0.0096 max mem: 33369 +Epoch: [8] [ 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loss: 0.0827 (0.0919) time: 3.1909 data: 0.0079 max mem: 33369 +Epoch: [8] [ 790/1319] eta: 0:28:01 lr: 4.021207374606688e-05 loss: 0.0861 (0.0919) time: 3.1805 data: 0.0081 max mem: 33369 +Epoch: [8] [ 800/1319] eta: 0:27:29 lr: 4.0203335473541464e-05 loss: 0.0876 (0.0919) time: 3.1646 data: 0.0082 max mem: 33369 +Epoch: [8] [ 810/1319] eta: 0:26:57 lr: 4.01945969899798e-05 loss: 0.0781 (0.0918) time: 3.1506 data: 0.0082 max mem: 33369 +Epoch: [8] [ 820/1319] eta: 0:26:25 lr: 4.0185858295325805e-05 loss: 0.0787 (0.0916) time: 3.1466 data: 0.0078 max mem: 33369 +Epoch: [8] [ 830/1319] eta: 0:25:53 lr: 4.017711938952337e-05 loss: 0.0913 (0.0919) time: 3.1438 data: 0.0074 max mem: 33369 +Epoch: [8] [ 840/1319] eta: 0:25:22 lr: 4.0168380272516376e-05 loss: 0.0995 (0.0919) time: 3.1493 data: 0.0076 max mem: 33369 +Epoch: [8] [ 850/1319] eta: 0:24:50 lr: 4.0159640944248643e-05 loss: 0.0800 (0.0917) time: 3.1435 data: 0.0080 max mem: 33369 +Epoch: [8] [ 860/1319] eta: 0:24:18 lr: 4.0150901404663985e-05 loss: 0.0820 (0.0917) time: 3.1874 data: 0.0079 max mem: 33369 +Epoch: [8] [ 870/1319] eta: 0:23:46 lr: 4.0142161653706185e-05 loss: 0.0860 (0.0919) time: 3.1898 data: 0.0077 max mem: 33369 +Epoch: [8] [ 880/1319] eta: 0:23:15 lr: 4.013342169131899e-05 loss: 0.0794 (0.0919) time: 3.1906 data: 0.0079 max mem: 33369 +Epoch: [8] [ 890/1319] eta: 0:22:43 lr: 4.012468151744613e-05 loss: 0.0911 (0.0920) time: 3.2038 data: 0.0081 max mem: 33369 +Epoch: [8] [ 900/1319] eta: 0:22:11 lr: 4.01159411320313e-05 loss: 0.0928 (0.0921) time: 3.1504 data: 0.0082 max mem: 33369 +Epoch: [8] [ 910/1319] eta: 0:21:39 lr: 4.010720053501816e-05 loss: 0.0900 (0.0921) time: 3.1610 data: 0.0083 max mem: 33369 +Epoch: [8] [ 920/1319] eta: 0:21:07 lr: 4.009845972635034e-05 loss: 0.0748 (0.0920) time: 3.1889 data: 0.0080 max mem: 33369 +Epoch: [8] [ 930/1319] eta: 0:20:36 lr: 4.008971870597147e-05 loss: 0.0715 (0.0918) time: 3.1722 data: 0.0078 max mem: 33369 +Epoch: [8] [ 940/1319] eta: 0:20:04 lr: 4.008097747382511e-05 loss: 0.0797 (0.0918) time: 3.1865 data: 0.0080 max mem: 33369 +Epoch: [8] [ 950/1319] eta: 0:19:32 lr: 4.0072236029854826e-05 loss: 0.0869 (0.0919) time: 3.2044 data: 0.0080 max mem: 33369 +Epoch: [8] [ 960/1319] eta: 0:19:01 lr: 4.006349437400413e-05 loss: 0.0765 (0.0918) time: 3.2092 data: 0.0086 max mem: 33369 +Epoch: [8] [ 970/1319] eta: 0:18:29 lr: 4.005475250621652e-05 loss: 0.0737 (0.0916) time: 3.1680 data: 0.0086 max mem: 33369 +Epoch: [8] [ 980/1319] eta: 0:17:57 lr: 4.004601042643546e-05 loss: 0.0790 (0.0916) time: 3.1386 data: 0.0081 max mem: 33369 +Epoch: [8] [ 990/1319] eta: 0:17:25 lr: 4.003726813460439e-05 loss: 0.0915 (0.0918) time: 3.1900 data: 0.0086 max mem: 33369 +Epoch: [8] [1000/1319] eta: 0:16:53 lr: 4.0028525630666715e-05 loss: 0.0962 (0.0918) time: 3.2053 data: 0.0082 max mem: 33369 +Epoch: [8] [1010/1319] eta: 0:16:21 lr: 4.00197829145658e-05 loss: 0.0895 (0.0920) time: 3.1631 data: 0.0076 max mem: 33369 +Epoch: [8] 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+Epoch: [8] [1100/1319] eta: 0:11:35 lr: 3.994108891295557e-05 loss: 0.0818 (0.0923) time: 3.1666 data: 0.0078 max mem: 33369 +Epoch: [8] [1110/1319] eta: 0:11:04 lr: 3.9932344072101854e-05 loss: 0.0845 (0.0926) time: 3.1927 data: 0.0075 max mem: 33369 +Epoch: [8] [1120/1319] eta: 0:10:32 lr: 3.9923599018460164e-05 loss: 0.0929 (0.0927) time: 3.2240 data: 0.0076 max mem: 33369 +Epoch: [8] [1130/1319] eta: 0:10:00 lr: 3.991485375197353e-05 loss: 0.0968 (0.0928) time: 3.1943 data: 0.0077 max mem: 33369 +Epoch: [8] [1140/1319] eta: 0:09:28 lr: 3.990610827258495e-05 loss: 0.1018 (0.0929) time: 3.1890 data: 0.0078 max mem: 33369 +Epoch: [8] [1150/1319] eta: 0:08:57 lr: 3.9897362580237394e-05 loss: 0.0960 (0.0927) time: 3.2122 data: 0.0076 max mem: 33369 +Epoch: [8] [1160/1319] eta: 0:08:25 lr: 3.988861667487383e-05 loss: 0.0826 (0.0929) time: 3.1962 data: 0.0076 max mem: 33369 +Epoch: [8] [1170/1319] eta: 0:07:53 lr: 3.987987055643715e-05 loss: 0.0934 (0.0929) time: 3.1977 data: 0.0077 max mem: 33369 +Epoch: [8] [1180/1319] eta: 0:07:21 lr: 3.9871124224870237e-05 loss: 0.0934 (0.0930) time: 3.2056 data: 0.0075 max mem: 33369 +Epoch: [8] [1190/1319] eta: 0:06:50 lr: 3.986237768011596e-05 loss: 0.0847 (0.0931) time: 3.1822 data: 0.0079 max mem: 33369 +Epoch: [8] [1200/1319] eta: 0:06:18 lr: 3.985363092211714e-05 loss: 0.0915 (0.0930) time: 3.1683 data: 0.0079 max mem: 33369 +Epoch: [8] [1210/1319] eta: 0:05:46 lr: 3.984488395081657e-05 loss: 0.0915 (0.0932) time: 3.1362 data: 0.0074 max mem: 33369 +Epoch: [8] [1220/1319] eta: 0:05:14 lr: 3.9836136766157016e-05 loss: 0.0946 (0.0934) time: 3.1370 data: 0.0083 max mem: 33369 +Epoch: [8] [1230/1319] eta: 0:04:42 lr: 3.9827389368081224e-05 loss: 0.1117 (0.0935) time: 3.1776 data: 0.0082 max mem: 33369 +Epoch: [8] [1240/1319] eta: 0:04:11 lr: 3.9818641756531906e-05 loss: 0.0917 (0.0934) time: 3.1959 data: 0.0077 max mem: 33369 +Epoch: [8] [1250/1319] eta: 0:03:39 lr: 3.980989393145173e-05 loss: 0.0857 (0.0934) time: 3.1886 data: 0.0081 max mem: 33369 +Epoch: [8] [1260/1319] eta: 0:03:07 lr: 3.9801145892783356e-05 loss: 0.0849 (0.0935) time: 3.1944 data: 0.0080 max mem: 33369 +Epoch: [8] [1270/1319] eta: 0:02:35 lr: 3.97923976404694e-05 loss: 0.0861 (0.0936) time: 3.1761 data: 0.0081 max mem: 33369 +Epoch: [8] [1280/1319] eta: 0:02:03 lr: 3.978364917445246e-05 loss: 0.0892 (0.0937) time: 3.1678 data: 0.0078 max mem: 33369 +Epoch: [8] [1290/1319] eta: 0:01:32 lr: 3.9774900494675086e-05 loss: 0.0889 (0.0937) time: 3.1865 data: 0.0073 max mem: 33369 +Epoch: [8] [1300/1319] eta: 0:01:00 lr: 3.976615160107982e-05 loss: 0.0978 (0.0938) time: 3.1914 data: 0.0072 max mem: 33369 +Epoch: [8] [1310/1319] eta: 0:00:28 lr: 3.975740249360917e-05 loss: 0.0876 (0.0938) time: 3.1867 data: 0.0074 max mem: 33369 +Epoch: [8] Total time: 1:09:53 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 2:40:22 time: 3.7400 data: 3.6484 max mem: 33369 +Test: [ 100/2573] eta: 0:04:40 time: 0.0773 data: 0.0015 max mem: 33369 +Test: [ 200/2573] eta: 0:03:49 time: 0.0790 data: 0.0015 max mem: 33369 +Test: [ 300/2573] eta: 0:03:25 time: 0.0802 data: 0.0014 max mem: 33369 +Test: [ 400/2573] eta: 0:03:09 time: 0.0801 data: 0.0013 max mem: 33369 +Test: [ 500/2573] eta: 0:02:57 time: 0.0786 data: 0.0015 max mem: 33369 +Test: [ 600/2573] eta: 0:02:47 time: 0.0796 data: 0.0015 max mem: 33369 +Test: [ 700/2573] eta: 0:02:37 time: 0.0790 data: 0.0014 max mem: 33369 +Test: [ 800/2573] eta: 0:02:28 time: 0.0823 data: 0.0015 max mem: 33369 +Test: [ 900/2573] eta: 0:02:19 time: 0.0793 data: 0.0016 max mem: 33369 +Test: [1000/2573] eta: 0:02:10 time: 0.0796 data: 0.0014 max mem: 33369 +Test: [1100/2573] eta: 0:02:01 time: 0.0792 data: 0.0014 max mem: 33369 +Test: [1200/2573] eta: 0:01:52 time: 0.0795 data: 0.0013 max mem: 33369 +Test: [1300/2573] eta: 0:01:44 time: 0.0801 data: 0.0015 max mem: 33369 +Test: [1400/2573] eta: 0:01:36 time: 0.0783 data: 0.0015 max mem: 33369 +Test: [1500/2573] eta: 0:01:27 time: 0.0795 data: 0.0015 max mem: 33369 +Test: [1600/2573] eta: 0:01:19 time: 0.0820 data: 0.0014 max mem: 33369 +Test: [1700/2573] eta: 0:01:11 time: 0.0782 data: 0.0015 max mem: 33369 +Test: [1800/2573] eta: 0:01:02 time: 0.0812 data: 0.0014 max mem: 33369 +Test: [1900/2573] eta: 0:00:54 time: 0.0784 data: 0.0015 max mem: 33369 +Test: [2000/2573] eta: 0:00:46 time: 0.0803 data: 0.0014 max mem: 33369 +Test: [2100/2573] eta: 0:00:38 time: 0.0822 data: 0.0015 max mem: 33369 +Test: [2200/2573] eta: 0:00:30 time: 0.0808 data: 0.0013 max mem: 33369 +Test: [2300/2573] eta: 0:00:22 time: 0.0817 data: 0.0015 max mem: 33369 +Test: [2400/2573] eta: 0:00:13 time: 0.0758 data: 0.0014 max mem: 33369 +Test: [2500/2573] eta: 0:00:05 time: 0.0803 data: 0.0015 max mem: 33369 +Test: Total time: 0:03:28 +Final results: +Mean IoU is 59.39 + + precision@0.5 = 66.26 + precision@0.6 = 59.93 + precision@0.7 = 51.33 + precision@0.8 = 39.48 + precision@0.9 = 18.24 + overall IoU = 58.85 + +Average object IoU 59.38506504382407 +Overall IoU 58.845237731933594 +Better epoch: 8 + +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [9] [ 0/1319] eta: 1:50:07 lr: 3.974952811397457e-05 loss: 0.0989 (0.0989) time: 5.0092 data: 1.6135 max mem: 33369 +Epoch: [9] [ 10/1319] eta: 1:13:13 lr: 3.974077859998216e-05 loss: 0.0872 (0.0998) time: 3.3561 data: 0.1542 max mem: 33369 +Epoch: [9] [ 20/1319] eta: 1:10:47 lr: 3.9732028871947454e-05 loss: 0.0868 (0.0966) time: 3.1829 data: 0.0076 max mem: 33369 +Epoch: [9] [ 30/1319] eta: 1:09:24 lr: 3.972327892981283e-05 loss: 0.0803 (0.0905) time: 3.1613 data: 0.0076 max mem: 33369 +Epoch: [9] [ 40/1319] eta: 1:08:28 lr: 3.971452877352066e-05 loss: 0.0719 (0.0881) time: 3.1511 data: 0.0083 max mem: 33369 +Epoch: [9] [ 50/1319] eta: 1:07:47 lr: 3.9705778403013264e-05 loss: 0.0704 (0.0921) time: 3.1669 data: 0.0085 max mem: 33369 +Epoch: [9] [ 60/1319] eta: 1:07:00 lr: 3.969702781823294e-05 loss: 0.0771 (0.0907) time: 3.1557 data: 0.0082 max mem: 33369 +Epoch: [9] [ 70/1319] eta: 1:06:14 lr: 3.9688277019121967e-05 loss: 0.0848 (0.0901) time: 3.1236 data: 0.0082 max mem: 33369 +Epoch: [9] [ 80/1319] eta: 1:05:45 lr: 3.967952600562257e-05 loss: 0.0753 (0.0906) time: 3.1583 data: 0.0086 max mem: 33369 +Epoch: [9] [ 90/1319] eta: 1:05:15 lr: 3.967077477767697e-05 loss: 0.0801 (0.0906) time: 3.1971 data: 0.0079 max mem: 33369 +Epoch: [9] [ 100/1319] eta: 1:04:45 lr: 3.966202333522733e-05 loss: 0.0852 (0.0913) time: 3.1980 data: 0.0080 max mem: 33369 +Epoch: [9] [ 110/1319] eta: 1:04:11 lr: 3.965327167821583e-05 loss: 0.1025 (0.0915) time: 3.1837 data: 0.0087 max mem: 33369 +Epoch: [9] [ 120/1319] eta: 1:03:42 lr: 3.9644519806584564e-05 loss: 0.0929 (0.0933) time: 3.1894 data: 0.0086 max mem: 33369 +Epoch: [9] [ 130/1319] eta: 1:03:03 lr: 3.963576772027564e-05 loss: 0.0814 (0.0923) time: 3.1648 data: 0.0081 max mem: 33369 +Epoch: [9] [ 140/1319] eta: 1:02:36 lr: 3.96270154192311e-05 loss: 0.0767 (0.0916) time: 3.1740 data: 0.0082 max mem: 33369 +Epoch: [9] [ 150/1319] eta: 1:02:01 lr: 3.9618262903393e-05 loss: 0.0765 (0.0904) time: 3.1894 data: 0.0081 max mem: 33369 +Epoch: [9] [ 160/1319] eta: 1:01:31 lr: 3.960951017270332e-05 loss: 0.0643 (0.0888) time: 3.1813 data: 0.0081 max mem: 33369 +Epoch: [9] [ 170/1319] eta: 1:00:57 lr: 3.9600757227104046e-05 loss: 0.0696 (0.0893) time: 3.1830 data: 0.0081 max mem: 33369 +Epoch: [9] [ 180/1319] eta: 1:00:27 lr: 3.95920040665371e-05 loss: 0.1002 (0.0893) time: 3.1790 data: 0.0079 max mem: 33369 +Epoch: [9] [ 190/1319] eta: 0:59:55 lr: 3.958325069094442e-05 loss: 0.0759 (0.0889) time: 3.1980 data: 0.0084 max mem: 33369 +Epoch: [9] [ 200/1319] eta: 0:59:24 lr: 3.957449710026786e-05 loss: 0.0790 (0.0892) time: 3.1944 data: 0.0083 max mem: 33369 +Epoch: [9] [ 210/1319] eta: 0:58:51 lr: 3.9565743294449283e-05 loss: 0.0925 (0.0891) time: 3.1859 data: 0.0085 max mem: 33369 +Epoch: [9] [ 220/1319] eta: 0:58:17 lr: 3.955698927343052e-05 loss: 0.0645 (0.0884) time: 3.1550 data: 0.0088 max mem: 33369 +Epoch: [9] [ 230/1319] eta: 0:57:44 lr: 3.954823503715335e-05 loss: 0.0721 (0.0879) time: 3.1488 data: 0.0082 max mem: 33369 +Epoch: [9] [ 240/1319] eta: 0:57:10 lr: 3.953948058555954e-05 loss: 0.0738 (0.0875) time: 3.1457 data: 0.0083 max mem: 33369 +Epoch: [9] [ 250/1319] eta: 0:56:39 lr: 3.9530725918590825e-05 loss: 0.0686 (0.0874) time: 3.1558 data: 0.0087 max mem: 33369 +Epoch: [9] [ 260/1319] eta: 0:56:05 lr: 3.952197103618889e-05 loss: 0.0721 (0.0868) time: 3.1587 data: 0.0083 max mem: 33369 +Epoch: [9] [ 270/1319] eta: 0:55:32 lr: 3.951321593829542e-05 loss: 0.0725 (0.0868) time: 3.1419 data: 0.0085 max mem: 33369 +Epoch: [9] [ 280/1319] eta: 0:55:00 lr: 3.9504460624852056e-05 loss: 0.0805 (0.0864) time: 3.1547 data: 0.0090 max mem: 33369 +Epoch: [9] [ 290/1319] eta: 0:54:26 lr: 3.94957050958004e-05 loss: 0.0737 (0.0859) time: 3.1476 data: 0.0086 max mem: 33369 +Epoch: [9] [ 300/1319] eta: 0:53:53 lr: 3.9486949351082035e-05 loss: 0.0683 (0.0857) time: 3.1326 data: 0.0080 max mem: 33369 +Epoch: [9] [ 310/1319] eta: 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3.2044 data: 0.0083 max mem: 33369 +Epoch: [9] [ 710/1319] eta: 0:32:12 lr: 3.9127777403509066e-05 loss: 0.0786 (0.0867) time: 3.2160 data: 0.0084 max mem: 33369 +Epoch: [9] [ 720/1319] eta: 0:31:40 lr: 3.9119012547632586e-05 loss: 0.0744 (0.0866) time: 3.1861 data: 0.0079 max mem: 33369 +Epoch: [9] [ 730/1319] eta: 0:31:09 lr: 3.911024747354846e-05 loss: 0.0690 (0.0864) time: 3.1877 data: 0.0082 max mem: 33369 +Epoch: [9] [ 740/1319] eta: 0:30:37 lr: 3.9101482181196904e-05 loss: 0.0831 (0.0869) time: 3.1883 data: 0.0080 max mem: 33369 +Epoch: [9] [ 750/1319] eta: 0:30:06 lr: 3.909271667051812e-05 loss: 0.0871 (0.0869) time: 3.2113 data: 0.0081 max mem: 33369 +Epoch: [9] [ 760/1319] eta: 0:29:33 lr: 3.908395094145227e-05 loss: 0.0811 (0.0868) time: 3.1677 data: 0.0085 max mem: 33369 +Epoch: [9] [ 770/1319] eta: 0:29:02 lr: 3.9075184993939487e-05 loss: 0.0811 (0.0870) time: 3.1518 data: 0.0081 max mem: 33369 +Epoch: [9] [ 780/1319] eta: 0:28:30 lr: 3.906641882791989e-05 loss: 0.0802 (0.0874) time: 3.1953 data: 0.0080 max mem: 33369 +Epoch: [9] [ 790/1319] eta: 0:27:59 lr: 3.9057652443333534e-05 loss: 0.0969 (0.0875) time: 3.1908 data: 0.0080 max mem: 33369 +Epoch: [9] [ 800/1319] eta: 0:27:27 lr: 3.904888584012046e-05 loss: 0.0758 (0.0875) time: 3.1840 data: 0.0081 max mem: 33369 +Epoch: [9] [ 810/1319] eta: 0:26:55 lr: 3.904011901822068e-05 loss: 0.0794 (0.0876) time: 3.1810 data: 0.0079 max mem: 33369 +Epoch: [9] [ 820/1319] eta: 0:26:23 lr: 3.9031351977574175e-05 loss: 0.0767 (0.0874) time: 3.1649 data: 0.0076 max mem: 33369 +Epoch: [9] [ 830/1319] eta: 0:25:52 lr: 3.9022584718120886e-05 loss: 0.0750 (0.0875) time: 3.1698 data: 0.0084 max mem: 33369 +Epoch: [9] [ 840/1319] eta: 0:25:20 lr: 3.901381723980073e-05 loss: 0.0767 (0.0874) time: 3.1886 data: 0.0083 max mem: 33369 +Epoch: [9] [ 850/1319] eta: 0:24:48 lr: 3.900504954255358e-05 loss: 0.0795 (0.0873) time: 3.1637 data: 0.0081 max mem: 33369 +Epoch: [9] [ 860/1319] eta: 0:24:17 lr: 3.899628162631931e-05 loss: 0.0910 (0.0874) time: 3.1823 data: 0.0082 max mem: 33369 +Epoch: [9] [ 870/1319] eta: 0:23:45 lr: 3.898751349103772e-05 loss: 0.0865 (0.0875) time: 3.2112 data: 0.0081 max mem: 33369 +Epoch: [9] [ 880/1319] eta: 0:23:13 lr: 3.8978745136648617e-05 loss: 0.0845 (0.0876) time: 3.1701 data: 0.0082 max mem: 33369 +Epoch: [9] [ 890/1319] eta: 0:22:41 lr: 3.896997656309173e-05 loss: 0.0802 (0.0875) time: 3.1705 data: 0.0080 max mem: 33369 +Epoch: [9] [ 900/1319] eta: 0:22:10 lr: 3.896120777030681e-05 loss: 0.0704 (0.0875) time: 3.1811 data: 0.0077 max mem: 33369 +Epoch: [9] [ 910/1319] eta: 0:21:38 lr: 3.895243875823353e-05 loss: 0.0746 (0.0876) time: 3.1494 data: 0.0078 max mem: 33369 +Epoch: [9] [ 920/1319] eta: 0:21:06 lr: 3.894366952681158e-05 loss: 0.0848 (0.0876) time: 3.1782 data: 0.0082 max mem: 33369 +Epoch: [9] [ 930/1319] eta: 0:20:34 lr: 3.8934900075980555e-05 loss: 0.0918 (0.0878) time: 3.1664 data: 0.0079 max mem: 33369 +Epoch: [9] [ 940/1319] eta: 0:20:02 lr: 3.8926130405680076e-05 loss: 0.0922 (0.0879) time: 3.1345 data: 0.0079 max mem: 33369 +Epoch: [9] [ 950/1319] eta: 0:19:31 lr: 3.8917360515849704e-05 loss: 0.0755 (0.0878) time: 3.1613 data: 0.0081 max mem: 33369 +Epoch: [9] [ 960/1319] eta: 0:18:59 lr: 3.8908590406428975e-05 loss: 0.0755 (0.0877) time: 3.1969 data: 0.0076 max mem: 33369 +Epoch: [9] [ 970/1319] eta: 0:18:27 lr: 3.889982007735738e-05 loss: 0.0771 (0.0877) time: 3.1942 data: 0.0076 max mem: 33369 +Epoch: [9] [ 980/1319] eta: 0:17:56 lr: 3.889104952857442e-05 loss: 0.0671 (0.0876) time: 3.1814 data: 0.0080 max mem: 33369 +Epoch: [9] [ 990/1319] eta: 0:17:24 lr: 3.888227876001951e-05 loss: 0.0784 (0.0877) time: 3.1851 data: 0.0082 max mem: 33369 +Epoch: [9] [1000/1319] eta: 0:16:52 lr: 3.887350777163206e-05 loss: 0.0827 (0.0878) time: 3.1924 data: 0.0078 max mem: 33369 +Epoch: [9] [1010/1319] eta: 0:16:20 lr: 3.886473656335145e-05 loss: 0.0766 (0.0877) time: 3.1740 data: 0.0079 max mem: 33369 +Epoch: [9] [1020/1319] eta: 0:15:49 lr: 3.8855965135117015e-05 loss: 0.0775 (0.0878) time: 3.1717 data: 0.0080 max mem: 33369 +Epoch: [9] [1030/1319] eta: 0:15:17 lr: 3.8847193486868084e-05 loss: 0.0761 (0.0877) time: 3.1736 data: 0.0075 max mem: 33369 +Epoch: [9] [1040/1319] eta: 0:14:45 lr: 3.883842161854392e-05 loss: 0.0740 (0.0876) time: 3.1653 data: 0.0074 max mem: 33369 +Epoch: [9] [1050/1319] eta: 0:14:13 lr: 3.8829649530083775e-05 loss: 0.0846 (0.0877) time: 3.1655 data: 0.0080 max mem: 33369 +Epoch: [9] [1060/1319] eta: 0:13:42 lr: 3.882087722142687e-05 loss: 0.0846 (0.0877) time: 3.1519 data: 0.0085 max mem: 33369 +Epoch: [9] [1070/1319] eta: 0:13:10 lr: 3.8812104692512384e-05 loss: 0.0879 (0.0879) time: 3.1891 data: 0.0084 max mem: 33369 +Epoch: [9] [1080/1319] eta: 0:12:38 lr: 3.880333194327947e-05 loss: 0.0879 (0.0878) time: 3.1875 data: 0.0082 max mem: 33369 +Epoch: [9] [1090/1319] eta: 0:12:07 lr: 3.879455897366725e-05 loss: 0.0675 (0.0878) time: 3.1928 data: 0.0083 max mem: 33369 +Epoch: [9] 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+Epoch: [9] [1180/1319] eta: 0:07:21 lr: 3.871559232002716e-05 loss: 0.0803 (0.0876) time: 3.1719 data: 0.0078 max mem: 33369 +Epoch: [9] [1190/1319] eta: 0:06:49 lr: 3.870681714326634e-05 loss: 0.0901 (0.0878) time: 3.1664 data: 0.0075 max mem: 33369 +Epoch: [9] [1200/1319] eta: 0:06:17 lr: 3.86980417454544e-05 loss: 0.0901 (0.0879) time: 3.1649 data: 0.0075 max mem: 33369 +Epoch: [9] [1210/1319] eta: 0:05:46 lr: 3.8689266126530076e-05 loss: 0.0835 (0.0879) time: 3.1801 data: 0.0074 max mem: 33369 +Epoch: [9] [1220/1319] eta: 0:05:14 lr: 3.868049028643206e-05 loss: 0.0835 (0.0879) time: 3.1663 data: 0.0074 max mem: 33369 +Epoch: [9] [1230/1319] eta: 0:04:42 lr: 3.867171422509902e-05 loss: 0.0922 (0.0879) time: 3.1444 data: 0.0075 max mem: 33369 +Epoch: [9] [1240/1319] eta: 0:04:10 lr: 3.866293794246959e-05 loss: 0.0922 (0.0880) time: 3.1757 data: 0.0075 max mem: 33369 +Epoch: [9] [1250/1319] eta: 0:03:39 lr: 3.8654161438482394e-05 loss: 0.0847 (0.0880) time: 3.1723 data: 0.0078 max mem: 33369 +Epoch: [9] [1260/1319] eta: 0:03:07 lr: 3.864538471307598e-05 loss: 0.0730 (0.0879) time: 3.1660 data: 0.0077 max mem: 33369 +Epoch: [9] [1270/1319] eta: 0:02:35 lr: 3.863660776618888e-05 loss: 0.0809 (0.0880) time: 3.1768 data: 0.0078 max mem: 33369 +Epoch: [9] [1280/1319] eta: 0:02:03 lr: 3.8627830597759606e-05 loss: 0.1077 (0.0881) time: 3.1741 data: 0.0080 max mem: 33369 +Epoch: [9] [1290/1319] eta: 0:01:32 lr: 3.861905320772664e-05 loss: 0.1077 (0.0883) time: 3.1678 data: 0.0080 max mem: 33369 +Epoch: [9] [1300/1319] eta: 0:01:00 lr: 3.861027559602841e-05 loss: 0.0778 (0.0882) time: 3.1677 data: 0.0078 max mem: 33369 +Epoch: [9] [1310/1319] eta: 0:00:28 lr: 3.860149776260333e-05 loss: 0.0734 (0.0884) time: 3.1829 data: 0.0074 max mem: 33369 +Epoch: [9] Total time: 1:09:47 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 2:16:29 time: 3.1828 data: 3.0969 max mem: 33369 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 100/2573] eta: 0:04:26 time: 0.0761 data: 0.0014 max mem: 33369 +Test: [ 200/2573] eta: 0:03:42 time: 0.0786 data: 0.0015 max mem: 33369 +Test: [ 300/2573] eta: 0:03:20 time: 0.0793 data: 0.0014 max mem: 33369 +Test: [ 400/2573] eta: 0:03:06 time: 0.0805 data: 0.0015 max mem: 33369 +Test: [ 500/2573] eta: 0:02:54 time: 0.0782 data: 0.0015 max mem: 33369 +Test: [ 600/2573] eta: 0:02:44 time: 0.0793 data: 0.0015 max mem: 33369 +Test: [ 700/2573] eta: 0:02:35 time: 0.0785 data: 0.0015 max mem: 33369 +Test: [ 800/2573] eta: 0:02:26 time: 0.0823 data: 0.0014 max mem: 33369 +Test: [ 900/2573] eta: 0:02:18 time: 0.0785 data: 0.0014 max mem: 33369 +Test: [1000/2573] eta: 0:02:09 time: 0.0785 data: 0.0015 max mem: 33369 +Test: [1100/2573] eta: 0:02:00 time: 0.0787 data: 0.0014 max mem: 33369 +Test: [1200/2573] eta: 0:01:52 time: 0.0802 data: 0.0016 max mem: 33369 +Test: [1300/2573] eta: 0:01:43 time: 0.0796 data: 0.0015 max mem: 33369 +Test: [1400/2573] eta: 0:01:35 time: 0.0776 data: 0.0015 max mem: 33369 +Test: [1500/2573] eta: 0:01:27 time: 0.0790 data: 0.0014 max mem: 33369 +Test: [1600/2573] eta: 0:01:19 time: 0.0823 data: 0.0014 max mem: 33369 +Test: [1700/2573] eta: 0:01:10 time: 0.0776 data: 0.0014 max mem: 33369 +Test: [1800/2573] eta: 0:01:02 time: 0.0812 data: 0.0015 max mem: 33369 +Test: [1900/2573] eta: 0:00:54 time: 0.0773 data: 0.0015 max mem: 33369 +Test: [2000/2573] eta: 0:00:46 time: 0.0798 data: 0.0015 max mem: 33369 +Test: [2100/2573] eta: 0:00:38 time: 0.0817 data: 0.0014 max mem: 33369 +Test: [2200/2573] eta: 0:00:30 time: 0.0807 data: 0.0014 max mem: 33369 +Test: [2300/2573] eta: 0:00:22 time: 0.0810 data: 0.0015 max mem: 33369 +Test: [2400/2573] eta: 0:00:13 time: 0.0762 data: 0.0015 max mem: 33369 +Test: [2500/2573] eta: 0:00:05 time: 0.0796 data: 0.0014 max mem: 33369 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: Total time: 0:03:27 +Final results: +Mean IoU is 59.71 + + precision@0.5 = 66.65 + precision@0.6 = 60.72 + precision@0.7 = 53.33 + precision@0.8 = 41.14 + precision@0.9 = 18.30 + overall IoU = 59.36 + +Average object IoU 59.71303833036612 +Overall IoU 59.36191940307617 +Better epoch: 9 + +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [10] [ 0/1319] eta: 1:51:28 lr: 3.859359752289337e-05 loss: 0.1196 (0.1196) time: 5.0710 data: 1.7388 max mem: 33369 +Epoch: [10] [ 10/1319] eta: 1:14:18 lr: 3.858481926801746e-05 loss: 0.0787 (0.0802) time: 3.4060 data: 0.1652 max mem: 33369 +Epoch: [10] [ 20/1319] eta: 1:11:00 lr: 3.857604079123589e-05 loss: 0.0773 (0.0826) time: 3.1906 data: 0.0078 max mem: 33369 +Epoch: [10] [ 30/1319] eta: 1:09:40 lr: 3.856726209248695e-05 loss: 0.0707 (0.0803) time: 3.1539 data: 0.0085 max mem: 33369 +Epoch: [10] [ 40/1319] eta: 1:08:47 lr: 3.855848317170887e-05 loss: 0.0782 (0.0837) time: 3.1710 data: 0.0089 max mem: 33369 +Epoch: [10] [ 50/1319] eta: 1:08:06 lr: 3.854970402883988e-05 loss: 0.0704 (0.0814) time: 3.1841 data: 0.0086 max mem: 33369 +Epoch: [10] [ 60/1319] eta: 1:07:21 lr: 3.854092466381814e-05 loss: 0.0701 (0.0800) time: 3.1745 data: 0.0087 max mem: 33369 +Epoch: [10] [ 70/1319] eta: 1:06:39 lr: 3.853214507658182e-05 loss: 0.0746 (0.0800) time: 3.1571 data: 0.0086 max mem: 33369 +Epoch: [10] [ 80/1319] eta: 1:05:57 lr: 3.852336526706903e-05 loss: 0.0750 (0.0801) time: 3.1451 data: 0.0079 max mem: 33369 +Epoch: [10] [ 90/1319] eta: 1:05:16 lr: 3.8514585235217835e-05 loss: 0.0688 (0.0794) time: 3.1319 data: 0.0075 max mem: 33369 +Epoch: [10] [ 100/1319] eta: 1:04:46 lr: 3.850580498096631e-05 loss: 0.0744 (0.0796) time: 3.1655 data: 0.0079 max mem: 33369 +Epoch: [10] [ 110/1319] eta: 1:04:15 lr: 3.849702450425245e-05 loss: 0.0744 (0.0809) time: 3.2006 data: 0.0082 max mem: 33369 +Epoch: [10] [ 120/1319] eta: 1:03:49 lr: 3.8488243805014244e-05 loss: 0.0720 (0.0803) time: 3.2215 data: 0.0083 max mem: 33369 +Epoch: [10] [ 130/1319] eta: 1:03:12 lr: 3.8479462883189646e-05 loss: 0.0734 (0.0810) time: 3.1906 data: 0.0084 max mem: 33369 +Epoch: [10] [ 140/1319] eta: 1:02:41 lr: 3.8470681738716575e-05 loss: 0.0838 (0.0813) time: 3.1683 data: 0.0080 max mem: 33369 +Epoch: [10] [ 150/1319] eta: 1:02:05 lr: 3.846190037153291e-05 loss: 0.0662 (0.0805) time: 3.1713 data: 0.0079 max mem: 33369 +Epoch: [10] [ 160/1319] eta: 1:01:33 lr: 3.84531187815765e-05 loss: 0.0726 (0.0804) time: 3.1638 data: 0.0085 max mem: 33369 +Epoch: [10] [ 170/1319] eta: 1:01:02 lr: 3.844433696878517e-05 loss: 0.0810 (0.0809) time: 3.1888 data: 0.0082 max mem: 33369 +Epoch: [10] [ 180/1319] eta: 1:00:33 lr: 3.843555493309671e-05 loss: 0.0729 (0.0805) time: 3.2144 data: 0.0079 max mem: 33369 +Epoch: [10] [ 190/1319] eta: 0:59:58 lr: 3.842677267444885e-05 loss: 0.0627 (0.0808) time: 3.1905 data: 0.0084 max mem: 33369 +Epoch: [10] [ 200/1319] eta: 0:59:27 lr: 3.8417990192779335e-05 loss: 0.0907 (0.0816) time: 3.1685 data: 0.0084 max mem: 33369 +Epoch: [10] [ 210/1319] eta: 0:58:53 lr: 3.8409207488025836e-05 loss: 0.0915 (0.0819) time: 3.1730 data: 0.0079 max mem: 33369 +Epoch: [10] [ 220/1319] eta: 0:58:23 lr: 3.8400424560126e-05 loss: 0.0677 (0.0813) time: 3.1932 data: 0.0081 max mem: 33369 +Epoch: [10] [ 230/1319] eta: 0:57:50 lr: 3.839164140901745e-05 loss: 0.0677 (0.0816) time: 3.1883 data: 0.0083 max mem: 33369 +Epoch: [10] [ 240/1319] eta: 0:57:19 lr: 3.838285803463778e-05 loss: 0.0698 (0.0816) time: 3.1798 data: 0.0083 max mem: 33369 +Epoch: [10] [ 250/1319] eta: 0:56:47 lr: 3.8374074436924536e-05 loss: 0.0698 (0.0816) time: 3.2040 data: 0.0079 max mem: 33369 +Epoch: [10] [ 260/1319] eta: 0:56:16 lr: 3.836529061581523e-05 loss: 0.0704 (0.0811) time: 3.1950 data: 0.0078 max mem: 33369 +Epoch: [10] [ 270/1319] eta: 0:55:43 lr: 3.8356506571247355e-05 loss: 0.0669 (0.0811) time: 3.1771 data: 0.0082 max mem: 33369 +Epoch: [10] [ 280/1319] eta: 0:55:09 lr: 3.834772230315837e-05 loss: 0.0740 (0.0812) time: 3.1546 data: 0.0085 max mem: 33369 +Epoch: [10] [ 290/1319] eta: 0:54:37 lr: 3.833893781148568e-05 loss: 0.0735 (0.0807) time: 3.1535 data: 0.0081 max mem: 33369 +Epoch: [10] [ 300/1319] eta: 0:54:05 lr: 3.833015309616668e-05 loss: 0.0735 (0.0811) time: 3.1768 data: 0.0081 max mem: 33369 +Epoch: 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+/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 2:10:33 time: 3.0447 data: 2.9203 max mem: 33369 +Test: [ 100/2573] eta: 0:04:23 time: 0.0776 data: 0.0016 max mem: 33369 +Test: [ 200/2573] eta: 0:03:40 time: 0.0780 data: 0.0014 max mem: 33369 +Test: [ 300/2573] eta: 0:03:19 time: 0.0797 data: 0.0016 max mem: 33369 +Test: [ 400/2573] eta: 0:03:05 time: 0.0794 data: 0.0014 max mem: 33369 +Test: [ 500/2573] eta: 0:02:54 time: 0.0788 data: 0.0015 max mem: 33369 +Test: [ 600/2573] eta: 0:02:44 time: 0.0784 data: 0.0015 max mem: 33369 +Test: [ 700/2573] eta: 0:02:35 time: 0.0796 data: 0.0016 max mem: 33369 +Test: [ 800/2573] eta: 0:02:26 time: 0.0822 data: 0.0014 max mem: 33369 +Test: [ 900/2573] eta: 0:02:17 time: 0.0786 data: 0.0014 max mem: 33369 +Test: [1000/2573] eta: 0:02:09 time: 0.0785 data: 0.0014 max mem: 33369 +Test: [1100/2573] eta: 0:02:00 time: 0.0789 data: 0.0014 max mem: 33369 +Test: [1200/2573] eta: 0:01:51 time: 0.0788 data: 0.0014 max mem: 33369 +Test: [1300/2573] eta: 0:01:43 time: 0.0800 data: 0.0015 max mem: 33369 +Test: [1400/2573] eta: 0:01:35 time: 0.0779 data: 0.0015 max mem: 33369 +Test: [1500/2573] eta: 0:01:27 time: 0.0794 data: 0.0014 max mem: 33369 +Test: [1600/2573] eta: 0:01:18 time: 0.0821 data: 0.0015 max mem: 33369 +Test: [1700/2573] eta: 0:01:10 time: 0.0775 data: 0.0014 max mem: 33369 +Test: [1800/2573] eta: 0:01:02 time: 0.0813 data: 0.0014 max mem: 33369 +Test: [1900/2573] eta: 0:00:54 time: 0.0777 data: 0.0015 max mem: 33369 +Test: [2000/2573] eta: 0:00:46 time: 0.0804 data: 0.0016 max mem: 33369 +Test: [2100/2573] eta: 0:00:38 time: 0.0813 data: 0.0014 max mem: 33369 +Test: [2200/2573] eta: 0:00:30 time: 0.0819 data: 0.0015 max mem: 33369 +Test: [2300/2573] eta: 0:00:21 time: 0.0804 data: 0.0014 max mem: 33369 +Test: [2400/2573] eta: 0:00:13 time: 0.0760 data: 0.0015 max mem: 33369 +Test: [2500/2573] eta: 0:00:05 time: 0.0789 data: 0.0015 max mem: 33369 +Test: Total time: 0:03:27 +Final results: +Mean IoU is 60.68 + + precision@0.5 = 67.81 + precision@0.6 = 61.66 + precision@0.7 = 53.00 + precision@0.8 = 41.01 + precision@0.9 = 18.87 + overall IoU = 59.39 + +Average object IoU 60.67869576717288 +Overall IoU 59.3878059387207 +Better epoch: 10 + +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [11] [ 0/1319] eta: 1:54:51 lr: 3.743380655104104e-05 loss: 0.0349 (0.0349) time: 5.2245 data: 1.7831 max mem: 33369 +Epoch: [11] [ 10/1319] eta: 1:14:20 lr: 3.742499848141075e-05 loss: 0.0621 (0.0832) time: 3.4076 data: 0.1703 max mem: 33369 +Epoch: [11] [ 20/1319] eta: 1:11:53 lr: 3.741619018144089e-05 loss: 0.0621 (0.0756) time: 3.2253 data: 0.0085 max mem: 33369 +Epoch: [11] [ 30/1319] eta: 1:10:37 lr: 3.7407381651065185e-05 loss: 0.0671 (0.0761) time: 3.2208 data: 0.0079 max mem: 33369 +Epoch: [11] [ 40/1319] eta: 1:09:40 lr: 3.739857289021734e-05 loss: 0.0791 (0.0783) time: 3.2145 data: 0.0078 max mem: 33369 +Epoch: [11] [ 50/1319] eta: 1:08:39 lr: 3.738976389883098e-05 loss: 0.0791 (0.0799) time: 3.1823 data: 0.0079 max mem: 33369 +Epoch: [11] [ 60/1319] eta: 1:07:56 lr: 3.738095467683973e-05 loss: 0.0631 (0.0795) time: 3.1754 data: 0.0079 max mem: 33369 +Epoch: [11] [ 70/1319] eta: 1:07:01 lr: 3.737214522417717e-05 loss: 0.0669 (0.0783) time: 3.1526 data: 0.0076 max mem: 33369 +Epoch: [11] [ 80/1319] eta: 1:06:27 lr: 3.736333554077684e-05 loss: 0.0682 (0.0772) time: 3.1586 data: 0.0079 max mem: 33369 +Epoch: [11] [ 90/1319] eta: 1:05:50 lr: 3.735452562657224e-05 loss: 0.0719 (0.0784) time: 3.1959 data: 0.0081 max mem: 33369 +Epoch: [11] [ 100/1319] eta: 1:05:15 lr: 3.734571548149683e-05 loss: 0.0719 (0.0775) time: 3.1839 data: 0.0081 max mem: 33369 +Epoch: [11] [ 110/1319] eta: 1:04:33 lr: 3.733690510548406e-05 loss: 0.0546 (0.0766) time: 3.1546 data: 0.0080 max mem: 33369 +Epoch: [11] [ 120/1319] eta: 1:04:03 lr: 3.732809449846732e-05 loss: 0.0617 (0.0770) time: 3.1737 data: 0.0079 max mem: 33369 +Epoch: [11] [ 130/1319] eta: 1:03:27 lr: 3.7319283660379954e-05 loss: 0.0617 (0.0757) time: 3.1969 data: 0.0080 max mem: 33369 +Epoch: [11] [ 140/1319] eta: 1:02:52 lr: 3.7310472591155297e-05 loss: 0.0716 (0.0767) time: 3.1662 data: 0.0079 max mem: 33369 +Epoch: [11] [ 150/1319] eta: 1:02:19 lr: 3.7301661290726626e-05 loss: 0.0850 (0.0782) time: 3.1726 data: 0.0080 max mem: 33369 +Epoch: [11] [ 160/1319] eta: 1:01:44 lr: 3.729284975902719e-05 loss: 0.0790 (0.0784) time: 3.1732 data: 0.0080 max mem: 33369 +Epoch: [11] [ 170/1319] eta: 1:01:11 lr: 3.728403799599019e-05 loss: 0.0728 (0.0779) time: 3.1709 data: 0.0082 max mem: 33369 +Epoch: [11] [ 180/1319] eta: 1:00:38 lr: 3.727522600154881e-05 loss: 0.0710 (0.0782) time: 3.1804 data: 0.0079 max mem: 33369 +Epoch: [11] [ 190/1319] eta: 1:00:07 lr: 3.7266413775636196e-05 loss: 0.0727 (0.0785) time: 3.1931 data: 0.0076 max mem: 33369 +Epoch: [11] [ 200/1319] eta: 0:59:34 lr: 3.725760131818543e-05 loss: 0.0705 (0.0777) time: 3.1873 data: 0.0078 max mem: 33369 +Epoch: [11] [ 210/1319] eta: 0:58:57 lr: 3.724878862912958e-05 loss: 0.0569 (0.0778) time: 3.1394 data: 0.0077 max mem: 33369 +Epoch: [11] [ 220/1319] eta: 0:58:20 lr: 3.723997570840168e-05 loss: 0.0691 (0.0783) time: 3.0978 data: 0.0079 max mem: 33369 +Epoch: [11] [ 230/1319] eta: 0:57:45 lr: 3.723116255593471e-05 loss: 0.0696 (0.0780) time: 3.1015 data: 0.0083 max mem: 33369 +Epoch: [11] [ 240/1319] eta: 0:57:13 lr: 3.7222349171661633e-05 loss: 0.0712 (0.0782) time: 3.1435 data: 0.0082 max mem: 33369 +Epoch: [11] [ 250/1319] eta: 0:56:38 lr: 3.721353555551535e-05 loss: 0.0682 (0.0777) time: 3.1450 data: 0.0081 max mem: 33369 +Epoch: [11] [ 260/1319] eta: 0:56:04 lr: 3.720472170742875e-05 loss: 0.0670 (0.0783) time: 3.1170 data: 0.0083 max mem: 33369 +Epoch: [11] [ 270/1319] eta: 0:55:30 lr: 3.719590762733466e-05 loss: 0.0752 (0.0783) time: 3.1257 data: 0.0083 max mem: 33369 +Epoch: [11] [ 280/1319] eta: 0:54:58 lr: 3.718709331516589e-05 loss: 0.0688 (0.0779) time: 3.1521 data: 0.0079 max mem: 33369 +Epoch: [11] [ 290/1319] eta: 0:54:25 lr: 3.7178278770855225e-05 loss: 0.0691 (0.0778) time: 3.1497 data: 0.0081 max mem: 33369 +Epoch: [11] [ 300/1319] eta: 0:53:56 lr: 3.716946399433537e-05 loss: 0.0691 (0.0773) time: 3.1842 data: 0.0085 max mem: 33369 +Epoch: 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3.647235706276924e-05 loss: 0.0751 (0.0779) time: 3.1893 data: 0.0083 max mem: 33369 +Epoch: [11] [1100/1319] eta: 0:11:35 lr: 3.646352348820711e-05 loss: 0.0743 (0.0777) time: 3.1572 data: 0.0082 max mem: 33369 +Epoch: [11] [1110/1319] eta: 0:11:03 lr: 3.6454689675860496e-05 loss: 0.0645 (0.0777) time: 3.1606 data: 0.0078 max mem: 33369 +Epoch: [11] [1120/1319] eta: 0:10:31 lr: 3.6445855625658975e-05 loss: 0.0757 (0.0778) time: 3.1713 data: 0.0082 max mem: 33369 +Epoch: [11] [1130/1319] eta: 0:10:00 lr: 3.643702133753208e-05 loss: 0.0757 (0.0778) time: 3.1596 data: 0.0083 max mem: 33369 +Epoch: [11] [1140/1319] eta: 0:09:28 lr: 3.6428186811409296e-05 loss: 0.0797 (0.0779) time: 3.1726 data: 0.0080 max mem: 33369 +Epoch: [11] [1150/1319] eta: 0:08:56 lr: 3.641935204722008e-05 loss: 0.0740 (0.0779) time: 3.1969 data: 0.0077 max mem: 33369 +Epoch: [11] [1160/1319] eta: 0:08:25 lr: 3.6410517044893844e-05 loss: 0.0727 (0.0778) time: 3.2097 data: 0.0078 max mem: 33369 +Epoch: [11] 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+/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 2:04:40 time: 2.9071 data: 2.8158 max mem: 33369 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 100/2573] eta: 0:04:21 time: 0.0778 data: 0.0014 max mem: 33369 +Test: [ 200/2573] eta: 0:03:39 time: 0.0775 data: 0.0013 max mem: 33369 +Test: [ 300/2573] eta: 0:03:19 time: 0.0802 data: 0.0014 max mem: 33369 +Test: [ 400/2573] eta: 0:03:05 time: 0.0810 data: 0.0014 max mem: 33369 +Test: [ 500/2573] eta: 0:02:54 time: 0.0787 data: 0.0014 max mem: 33369 +Test: [ 600/2573] eta: 0:02:44 time: 0.0787 data: 0.0014 max mem: 33369 +Test: [ 700/2573] eta: 0:02:35 time: 0.0793 data: 0.0014 max mem: 33369 +Test: [ 800/2573] eta: 0:02:26 time: 0.0820 data: 0.0014 max mem: 33369 +Test: [ 900/2573] eta: 0:02:18 time: 0.0794 data: 0.0014 max mem: 33369 +Test: [1000/2573] eta: 0:02:09 time: 0.0795 data: 0.0015 max mem: 33369 +Test: [1100/2573] eta: 0:02:00 time: 0.0790 data: 0.0014 max mem: 33369 +Test: [1200/2573] eta: 0:01:52 time: 0.0803 data: 0.0015 max mem: 33369 +Test: [1300/2573] eta: 0:01:43 time: 0.0786 data: 0.0014 max mem: 33369 +Test: [1400/2573] eta: 0:01:35 time: 0.0774 data: 0.0014 max mem: 33369 +Test: [1500/2573] eta: 0:01:27 time: 0.0797 data: 0.0015 max mem: 33369 +Test: [1600/2573] eta: 0:01:19 time: 0.0824 data: 0.0014 max mem: 33369 +Test: [1700/2573] eta: 0:01:10 time: 0.0771 data: 0.0014 max mem: 33369 +Test: [1800/2573] eta: 0:01:02 time: 0.0811 data: 0.0015 max mem: 33369 +Test: [1900/2573] eta: 0:00:54 time: 0.0774 data: 0.0014 max mem: 33369 +Test: [2000/2573] eta: 0:00:46 time: 0.0794 data: 0.0014 max mem: 33369 +Test: [2100/2573] eta: 0:00:38 time: 0.0813 data: 0.0015 max mem: 33369 +Test: [2200/2573] eta: 0:00:30 time: 0.0816 data: 0.0015 max mem: 33369 +Test: [2300/2573] eta: 0:00:22 time: 0.0830 data: 0.0015 max mem: 33369 +Test: [2400/2573] eta: 0:00:13 time: 0.0762 data: 0.0014 max mem: 33369 +Test: [2500/2573] eta: 0:00:05 time: 0.0798 data: 0.0015 max mem: 33369 +Test: Total time: 0:03:27 +Final results: +Mean IoU is 61.55 + + precision@0.5 = 68.77 + precision@0.6 = 63.17 + precision@0.7 = 55.31 + precision@0.8 = 42.91 + precision@0.9 = 19.36 + overall IoU = 60.12 + +Average object IoU 61.54779678147408 +Overall IoU 60.11689376831055 +Better epoch: 11 + +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [12] [ 0/1319] eta: 1:50:59 lr: 3.6270008456269996e-05 loss: 0.0804 (0.0804) time: 5.0493 data: 1.6691 max mem: 33369 +Epoch: [12] [ 10/1319] eta: 1:13:33 lr: 3.6261169418713356e-05 loss: 0.0670 (0.0673) time: 3.3718 data: 0.1599 max mem: 33369 +Epoch: [12] [ 20/1319] eta: 1:11:18 lr: 3.62523301417494e-05 loss: 0.0669 (0.0667) time: 3.2061 data: 0.0080 max mem: 33369 +Epoch: [12] [ 30/1319] eta: 1:09:44 lr: 3.624349062530679e-05 loss: 0.0705 (0.0665) time: 3.1768 data: 0.0078 max mem: 33369 +Epoch: [12] [ 40/1319] eta: 1:08:46 lr: 3.623465086931413e-05 loss: 0.0680 (0.0672) time: 3.1552 data: 0.0087 max mem: 33369 +Epoch: [12] [ 50/1319] eta: 1:07:56 lr: 3.62258108737e-05 loss: 0.0600 (0.0709) time: 3.1601 data: 0.0083 max mem: 33369 +Epoch: [12] [ 60/1319] eta: 1:07:06 lr: 3.621697063839292e-05 loss: 0.0600 (0.0699) time: 3.1406 data: 0.0079 max mem: 33369 +Epoch: [12] [ 70/1319] eta: 1:06:34 lr: 3.6208130163321375e-05 loss: 0.0588 (0.0700) time: 3.1619 data: 0.0077 max mem: 33369 +Epoch: [12] [ 80/1319] eta: 1:06:03 lr: 3.619928944841383e-05 loss: 0.0576 (0.0703) time: 3.2016 data: 0.0078 max mem: 33369 +Epoch: [12] [ 90/1319] eta: 1:05:22 lr: 3.6190448493598675e-05 loss: 0.0603 (0.0709) time: 3.1696 data: 0.0084 max mem: 33369 +Epoch: [12] [ 100/1319] eta: 1:04:58 lr: 3.61816072988043e-05 loss: 0.0604 (0.0708) time: 3.1948 data: 0.0088 max mem: 33369 +Epoch: [12] [ 110/1319] eta: 1:04:19 lr: 3.617276586395901e-05 loss: 0.0623 (0.0708) time: 3.1961 data: 0.0083 max mem: 33369 +Epoch: [12] [ 120/1319] eta: 1:03:46 lr: 3.61639241889911e-05 loss: 0.0571 (0.0692) time: 3.1559 data: 0.0079 max mem: 33369 +Epoch: [12] [ 130/1319] eta: 1:03:10 lr: 3.615508227382881e-05 loss: 0.0499 (0.0686) time: 3.1600 data: 0.0079 max mem: 33369 +Epoch: [12] [ 140/1319] eta: 1:02:36 lr: 3.614624011840035e-05 loss: 0.0614 (0.0689) time: 3.1571 data: 0.0084 max mem: 33369 +Epoch: [12] [ 150/1319] eta: 1:02:05 lr: 3.613739772263389e-05 loss: 0.0588 (0.0679) time: 3.1792 data: 0.0084 max mem: 33369 +Epoch: [12] [ 160/1319] eta: 1:01:30 lr: 3.6128555086457536e-05 loss: 0.0544 (0.0675) time: 3.1664 data: 0.0079 max mem: 33369 +Epoch: [12] [ 170/1319] eta: 1:00:58 lr: 3.6119712209799373e-05 loss: 0.0561 (0.0678) time: 3.1644 data: 0.0083 max mem: 33369 +Epoch: [12] [ 180/1319] eta: 1:00:23 lr: 3.6110869092587446e-05 loss: 0.0592 (0.0687) time: 3.1588 data: 0.0086 max mem: 33369 +Epoch: [12] [ 190/1319] eta: 0:59:53 lr: 3.610202573474975e-05 loss: 0.0592 (0.0696) time: 3.1740 data: 0.0085 max mem: 33369 +Epoch: [12] [ 200/1319] eta: 0:59:20 lr: 3.609318213621424e-05 loss: 0.0629 (0.0695) time: 3.1881 data: 0.0085 max mem: 33369 +Epoch: [12] [ 210/1319] eta: 0:58:48 lr: 3.608433829690883e-05 loss: 0.0631 (0.0696) time: 3.1693 data: 0.0082 max mem: 33369 +Epoch: [12] [ 220/1319] eta: 0:58:17 lr: 3.607549421676141e-05 loss: 0.0662 (0.0696) time: 3.1937 data: 0.0081 max mem: 33369 +Epoch: [12] [ 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eta: 0:12:08 lr: 3.5305129002887835e-05 loss: 0.0716 (0.0720) time: 3.1715 data: 0.0087 max mem: 33369 +Epoch: [12] [1100/1319] eta: 0:11:36 lr: 3.529626344126292e-05 loss: 0.0716 (0.0720) time: 3.1881 data: 0.0080 max mem: 33369 +Epoch: [12] [1110/1319] eta: 0:11:04 lr: 3.5287397632207417e-05 loss: 0.0717 (0.0721) time: 3.1766 data: 0.0081 max mem: 33369 +Epoch: [12] [1120/1319] eta: 0:10:32 lr: 3.527853157564535e-05 loss: 0.0700 (0.0721) time: 3.1445 data: 0.0080 max mem: 33369 +Epoch: [12] [1130/1319] eta: 0:10:00 lr: 3.526966527150067e-05 loss: 0.0698 (0.0723) time: 3.1805 data: 0.0081 max mem: 33369 +Epoch: [12] [1140/1319] eta: 0:09:29 lr: 3.5260798719697326e-05 loss: 0.0826 (0.0724) time: 3.1983 data: 0.0084 max mem: 33369 +Epoch: [12] [1150/1319] eta: 0:08:57 lr: 3.52519319201592e-05 loss: 0.0769 (0.0724) time: 3.1895 data: 0.0082 max mem: 33369 +Epoch: [12] [1160/1319] eta: 0:08:25 lr: 3.524306487281011e-05 loss: 0.0611 (0.0723) time: 3.1786 data: 0.0086 max mem: 33369 +Epoch: [12] [1170/1319] eta: 0:07:53 lr: 3.523419757757387e-05 loss: 0.0500 (0.0722) time: 3.1549 data: 0.0085 max mem: 33369 +Epoch: [12] [1180/1319] eta: 0:07:21 lr: 3.5225330034374235e-05 loss: 0.0614 (0.0721) time: 3.1591 data: 0.0082 max mem: 33369 +Epoch: [12] [1190/1319] eta: 0:06:50 lr: 3.5216462243134885e-05 loss: 0.0748 (0.0722) time: 3.1787 data: 0.0082 max mem: 33369 +Epoch: [12] [1200/1319] eta: 0:06:18 lr: 3.52075942037795e-05 loss: 0.0751 (0.0723) time: 3.1780 data: 0.0079 max mem: 33369 +Epoch: [12] [1210/1319] eta: 0:05:46 lr: 3.519872591623169e-05 loss: 0.0607 (0.0722) time: 3.1956 data: 0.0074 max mem: 33369 +Epoch: [12] [1220/1319] eta: 0:05:14 lr: 3.518985738041502e-05 loss: 0.0669 (0.0722) time: 3.1821 data: 0.0075 max mem: 33369 +Epoch: [12] [1230/1319] eta: 0:04:42 lr: 3.518098859625303e-05 loss: 0.0709 (0.0723) time: 3.1669 data: 0.0079 max mem: 33369 +Epoch: [12] [1240/1319] eta: 0:04:11 lr: 3.517211956366918e-05 loss: 0.0764 (0.0723) time: 3.1836 data: 0.0082 max mem: 33369 +Epoch: [12] [1250/1319] eta: 0:03:39 lr: 3.5163250282586914e-05 loss: 0.0670 (0.0723) time: 3.1752 data: 0.0086 max mem: 33369 +Epoch: [12] [1260/1319] eta: 0:03:07 lr: 3.515438075292963e-05 loss: 0.0677 (0.0723) time: 3.1874 data: 0.0083 max mem: 33369 +Epoch: [12] [1270/1319] eta: 0:02:35 lr: 3.514551097462066e-05 loss: 0.0709 (0.0723) time: 3.1944 data: 0.0080 max mem: 33369 +Epoch: [12] [1280/1319] eta: 0:02:03 lr: 3.513664094758331e-05 loss: 0.0717 (0.0723) time: 3.1651 data: 0.0082 max mem: 33369 +Epoch: [12] [1290/1319] eta: 0:01:32 lr: 3.512777067174083e-05 loss: 0.0661 (0.0723) time: 3.1706 data: 0.0077 max mem: 33369 +Epoch: [12] [1300/1319] eta: 0:01:00 lr: 3.511890014701643e-05 loss: 0.0623 (0.0722) time: 3.1628 data: 0.0075 max mem: 33369 +Epoch: [12] [1310/1319] eta: 0:00:28 lr: 3.511002937333328e-05 loss: 0.0670 (0.0723) time: 3.1565 data: 0.0073 max mem: 33369 +Epoch: [12] Total time: 1:09:53 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 2:13:03 time: 3.1030 data: 3.0132 max mem: 33369 +Test: [ 100/2573] eta: 0:04:27 time: 0.0782 data: 0.0016 max mem: 33369 +Test: [ 200/2573] eta: 0:03:42 time: 0.0788 data: 0.0015 max mem: 33369 +Test: [ 300/2573] eta: 0:03:21 time: 0.0803 data: 0.0014 max mem: 33369 +Test: [ 400/2573] eta: 0:03:07 time: 0.0815 data: 0.0016 max mem: 33369 +Test: [ 500/2573] eta: 0:02:55 time: 0.0795 data: 0.0015 max mem: 33369 +Test: [ 600/2573] eta: 0:02:45 time: 0.0781 data: 0.0014 max mem: 33369 +Test: [ 700/2573] eta: 0:02:36 time: 0.0795 data: 0.0014 max mem: 33369 +Test: [ 800/2573] eta: 0:02:27 time: 0.0835 data: 0.0014 max mem: 33369 +Test: [ 900/2573] eta: 0:02:18 time: 0.0793 data: 0.0014 max mem: 33369 +Test: [1000/2573] eta: 0:02:09 time: 0.0787 data: 0.0014 max mem: 33369 +Test: [1100/2573] eta: 0:02:00 time: 0.0787 data: 0.0014 max mem: 33369 +Test: [1200/2573] eta: 0:01:52 time: 0.0790 data: 0.0014 max mem: 33369 +Test: [1300/2573] eta: 0:01:44 time: 0.0795 data: 0.0015 max mem: 33369 +Test: [1400/2573] eta: 0:01:35 time: 0.0781 data: 0.0014 max mem: 33369 +Test: [1500/2573] eta: 0:01:27 time: 0.0792 data: 0.0015 max mem: 33369 +Test: [1600/2573] eta: 0:01:19 time: 0.0825 data: 0.0014 max mem: 33369 +Test: [1700/2573] eta: 0:01:10 time: 0.0770 data: 0.0013 max mem: 33369 +Test: [1800/2573] eta: 0:01:02 time: 0.0806 data: 0.0014 max mem: 33369 +Test: [1900/2573] eta: 0:00:54 time: 0.0780 data: 0.0014 max mem: 33369 +Test: [2000/2573] eta: 0:00:46 time: 0.0794 data: 0.0015 max mem: 33369 +Test: [2100/2573] eta: 0:00:38 time: 0.0829 data: 0.0014 max mem: 33369 +Test: [2200/2573] eta: 0:00:30 time: 0.0801 data: 0.0013 max mem: 33369 +Test: [2300/2573] eta: 0:00:21 time: 0.0824 data: 0.0016 max mem: 33369 +Test: [2400/2573] eta: 0:00:13 time: 0.0760 data: 0.0014 max mem: 33369 +Test: [2500/2573] eta: 0:00:05 time: 0.0804 data: 0.0015 max mem: 33369 +Test: Total time: 0:03:27 +Final results: +Mean IoU is 60.85 + + precision@0.5 = 68.57 + precision@0.6 = 62.60 + precision@0.7 = 54.15 + precision@0.8 = 42.89 + precision@0.9 = 20.18 + overall IoU = 59.41 + +Average object IoU 60.851991121993045 +Overall IoU 59.41252899169922 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [13] [ 0/1319] eta: 3:04:25 lr: 3.510204546409517e-05 loss: 0.0634 (0.0634) time: 8.3895 data: 2.6341 max mem: 33369 +Epoch: [13] [ 10/1319] eta: 1:20:03 lr: 3.509317421717855e-05 loss: 0.0620 (0.0667) time: 3.6693 data: 0.2468 max mem: 33369 +Epoch: [13] [ 20/1319] eta: 1:14:42 lr: 3.50843027210801e-05 loss: 0.0610 (0.0689) time: 3.2042 data: 0.0075 max mem: 33369 +Epoch: [13] [ 30/1319] eta: 1:12:13 lr: 3.5075430975722793e-05 loss: 0.0705 (0.0714) time: 3.1925 data: 0.0078 max mem: 33369 +Epoch: [13] [ 40/1319] eta: 1:10:45 lr: 3.506655898102959e-05 loss: 0.0685 (0.0712) time: 3.1815 data: 0.0089 max mem: 33369 +Epoch: [13] [ 50/1319] eta: 1:09:33 lr: 3.505768673692337e-05 loss: 0.0572 (0.0692) time: 3.1756 data: 0.0087 max mem: 33369 +Epoch: [13] [ 60/1319] eta: 1:08:37 lr: 3.5048814243327e-05 loss: 0.0632 (0.0695) time: 3.1696 data: 0.0081 max mem: 33369 +Epoch: [13] [ 70/1319] eta: 1:07:35 lr: 3.503994150016327e-05 loss: 0.0628 (0.0686) time: 3.1401 data: 0.0085 max mem: 33369 +Epoch: [13] [ 80/1319] eta: 1:06:53 lr: 3.503106850735495e-05 loss: 0.0515 (0.0673) time: 3.1438 data: 0.0087 max mem: 33369 +Epoch: [13] [ 90/1319] eta: 1:06:10 lr: 3.502219526482476e-05 loss: 0.0462 (0.0673) time: 3.1740 data: 0.0087 max mem: 33369 +Epoch: [13] [ 100/1319] eta: 1:05:29 lr: 3.501332177249536e-05 loss: 0.0491 (0.0660) time: 3.1620 data: 0.0084 max mem: 33369 +Epoch: [13] [ 110/1319] eta: 1:04:47 lr: 3.500444803028936e-05 loss: 0.0491 (0.0656) time: 3.1443 data: 0.0078 max mem: 33369 +Epoch: [13] [ 120/1319] eta: 1:04:14 lr: 3.499557403812936e-05 loss: 0.0482 (0.0643) time: 3.1674 data: 0.0085 max mem: 33369 +Epoch: [13] [ 130/1319] eta: 1:03:35 lr: 3.498669979593787e-05 loss: 0.0505 (0.0642) time: 3.1749 data: 0.0086 max mem: 33369 +Epoch: [13] [ 140/1319] eta: 1:03:03 lr: 3.497782530363739e-05 loss: 0.0551 (0.0635) time: 3.1740 data: 0.0080 max mem: 33369 +Epoch: [13] [ 150/1319] eta: 1:02:22 lr: 3.4968950561150356e-05 loss: 0.0546 (0.0629) time: 3.1547 data: 0.0081 max mem: 33369 +Epoch: [13] [ 160/1319] eta: 1:01:48 lr: 3.496007556839915e-05 loss: 0.0626 (0.0641) time: 3.1359 data: 0.0087 max mem: 33369 +Epoch: [13] [ 170/1319] eta: 1:01:12 lr: 3.495120032530614e-05 loss: 0.0627 (0.0634) time: 3.1557 data: 0.0089 max mem: 33369 +Epoch: [13] [ 180/1319] eta: 1:00:38 lr: 3.49423248317936e-05 loss: 0.0475 (0.0632) time: 3.1559 data: 0.0083 max mem: 33369 +Epoch: [13] [ 190/1319] eta: 1:00:06 lr: 3.493344908778381e-05 loss: 0.0541 (0.0634) time: 3.1748 data: 0.0082 max mem: 33369 +Epoch: [13] [ 200/1319] eta: 0:59:31 lr: 3.4924573093198975e-05 loss: 0.0546 (0.0629) time: 3.1663 data: 0.0089 max mem: 33369 +Epoch: [13] [ 210/1319] eta: 0:58:58 lr: 3.491569684796125e-05 loss: 0.0531 (0.0629) time: 3.1621 data: 0.0088 max mem: 33369 +Epoch: [13] [ 220/1319] eta: 0:58:28 lr: 3.490682035199276e-05 loss: 0.0556 (0.0629) time: 3.2013 data: 0.0080 max mem: 33369 +Epoch: [13] [ 230/1319] eta: 0:57:55 lr: 3.4897943605215565e-05 loss: 0.0638 (0.0634) time: 3.1985 data: 0.0082 max mem: 33369 +Epoch: [13] [ 240/1319] eta: 0:57:22 lr: 3.488906660755169e-05 loss: 0.0638 (0.0634) time: 3.1646 data: 0.0087 max mem: 33369 +Epoch: [13] [ 250/1319] eta: 0:56:50 lr: 3.4880189358923125e-05 loss: 0.0451 (0.0629) time: 3.1727 data: 0.0084 max mem: 33369 +Epoch: [13] [ 260/1319] eta: 0:56:18 lr: 3.487131185925179e-05 loss: 0.0496 (0.0626) time: 3.1825 data: 0.0079 max mem: 33369 +Epoch: [13] [ 270/1319] eta: 0:55:45 lr: 3.486243410845958e-05 loss: 0.0496 (0.0623) time: 3.1791 data: 0.0079 max mem: 33369 +Epoch: [13] [ 280/1319] eta: 0:55:12 lr: 3.485355610646832e-05 loss: 0.0507 (0.0627) time: 3.1691 data: 0.0080 max mem: 33369 +Epoch: [13] [ 290/1319] eta: 0:54:40 lr: 3.484467785319982e-05 loss: 0.0558 (0.0627) time: 3.1739 data: 0.0081 max mem: 33369 +Epoch: [13] [ 300/1319] eta: 0:54:09 lr: 3.483579934857581e-05 loss: 0.0537 (0.0629) time: 3.1972 data: 0.0081 max mem: 33369 +Epoch: 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time: 3.1773 data: 0.0077 max mem: 33369 +Epoch: [13] [ 940/1319] eta: 0:20:06 lr: 3.426704861621893e-05 loss: 0.0631 (0.0666) time: 3.1781 data: 0.0083 max mem: 33369 +Epoch: [13] [ 950/1319] eta: 0:19:34 lr: 3.4258153603371135e-05 loss: 0.0668 (0.0668) time: 3.1617 data: 0.0080 max mem: 33369 +Epoch: [13] [ 960/1319] eta: 0:19:02 lr: 3.424925833389819e-05 loss: 0.0668 (0.0669) time: 3.1585 data: 0.0080 max mem: 33369 +Epoch: [13] [ 970/1319] eta: 0:18:30 lr: 3.424036280771861e-05 loss: 0.0592 (0.0668) time: 3.1601 data: 0.0079 max mem: 33369 +Epoch: [13] [ 980/1319] eta: 0:17:58 lr: 3.42314670247509e-05 loss: 0.0615 (0.0674) time: 3.1492 data: 0.0075 max mem: 33369 +Epoch: [13] [ 990/1319] eta: 0:17:26 lr: 3.422257098491348e-05 loss: 0.0724 (0.0674) time: 3.1635 data: 0.0080 max mem: 33369 +Epoch: [13] [1000/1319] eta: 0:16:55 lr: 3.4213674688124745e-05 loss: 0.0655 (0.0673) time: 3.1630 data: 0.0078 max mem: 33369 +Epoch: [13] [1010/1319] eta: 0:16:23 lr: 3.420477813430303e-05 loss: 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3.413359644072625e-05 loss: 0.0625 (0.0676) time: 3.1804 data: 0.0073 max mem: 33369 +Epoch: [13] [1100/1319] eta: 0:11:36 lr: 3.412469756992473e-05 loss: 0.0663 (0.0677) time: 3.2048 data: 0.0074 max mem: 33369 +Epoch: [13] [1110/1319] eta: 0:11:05 lr: 3.411579844127087e-05 loss: 0.0713 (0.0678) time: 3.1891 data: 0.0077 max mem: 33369 +Epoch: [13] [1120/1319] eta: 0:10:33 lr: 3.410689905468246e-05 loss: 0.0581 (0.0678) time: 3.2128 data: 0.0077 max mem: 33369 +Epoch: [13] [1130/1319] eta: 0:10:01 lr: 3.409799941007725e-05 loss: 0.0531 (0.0677) time: 3.2077 data: 0.0075 max mem: 33369 +Epoch: [13] [1140/1319] eta: 0:09:29 lr: 3.408909950737292e-05 loss: 0.0587 (0.0677) time: 3.1851 data: 0.0073 max mem: 33369 +Epoch: [13] [1150/1319] eta: 0:08:58 lr: 3.4080199346487104e-05 loss: 0.0587 (0.0678) time: 3.2053 data: 0.0077 max mem: 33369 +Epoch: [13] [1160/1319] eta: 0:08:26 lr: 3.4071298927337405e-05 loss: 0.0707 (0.0679) time: 3.1895 data: 0.0081 max mem: 33369 +Epoch: [13] [1170/1319] eta: 0:07:54 lr: 3.406239824984136e-05 loss: 0.0819 (0.0681) time: 3.1414 data: 0.0079 max mem: 33369 +Epoch: [13] [1180/1319] eta: 0:07:22 lr: 3.405349731391645e-05 loss: 0.0659 (0.0681) time: 3.1515 data: 0.0076 max mem: 33369 +Epoch: [13] [1190/1319] eta: 0:06:50 lr: 3.404459611948011e-05 loss: 0.0647 (0.0681) time: 3.1535 data: 0.0078 max mem: 33369 +Epoch: [13] [1200/1319] eta: 0:06:18 lr: 3.4035694666449745e-05 loss: 0.0576 (0.0680) time: 3.1773 data: 0.0081 max mem: 33369 +Epoch: [13] [1210/1319] eta: 0:05:46 lr: 3.402679295474268e-05 loss: 0.0572 (0.0680) time: 3.1777 data: 0.0080 max mem: 33369 +Epoch: [13] [1220/1319] eta: 0:05:15 lr: 3.401789098427621e-05 loss: 0.0591 (0.0679) time: 3.1557 data: 0.0079 max mem: 33369 +Epoch: [13] [1230/1319] eta: 0:04:43 lr: 3.400898875496756e-05 loss: 0.0595 (0.0679) time: 3.1669 data: 0.0080 max mem: 33369 +Epoch: [13] [1240/1319] eta: 0:04:11 lr: 3.400008626673392e-05 loss: 0.0621 (0.0678) time: 3.1695 data: 0.0079 max mem: 33369 +Epoch: [13] [1250/1319] eta: 0:03:39 lr: 3.399118351949243e-05 loss: 0.0562 (0.0678) time: 3.1719 data: 0.0082 max mem: 33369 +Epoch: [13] [1260/1319] eta: 0:03:07 lr: 3.398228051316017e-05 loss: 0.0562 (0.0678) time: 3.1651 data: 0.0079 max mem: 33369 +Epoch: [13] [1270/1319] eta: 0:02:35 lr: 3.397337724765419e-05 loss: 0.0643 (0.0678) time: 3.1322 data: 0.0075 max mem: 33369 +Epoch: [13] [1280/1319] eta: 0:02:04 lr: 3.396447372289146e-05 loss: 0.0685 (0.0679) time: 3.1375 data: 0.0076 max mem: 33369 +Epoch: [13] [1290/1319] eta: 0:01:32 lr: 3.395556993878891e-05 loss: 0.0711 (0.0679) time: 3.1917 data: 0.0076 max mem: 33369 +Epoch: [13] [1300/1319] eta: 0:01:00 lr: 3.394666589526343e-05 loss: 0.0639 (0.0679) time: 3.2255 data: 0.0077 max mem: 33369 +Epoch: [13] [1310/1319] eta: 0:00:28 lr: 3.393776159223184e-05 loss: 0.0625 (0.0679) time: 3.1891 data: 0.0075 max mem: 33369 +Epoch: [13] Total time: 1:09:56 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 2:41:05 time: 3.7567 data: 3.6640 max mem: 33369 +Test: [ 100/2573] eta: 0:04:39 time: 0.0775 data: 0.0015 max mem: 33369 +Test: [ 200/2573] eta: 0:03:48 time: 0.0788 data: 0.0016 max mem: 33369 +Test: [ 300/2573] eta: 0:03:24 time: 0.0798 data: 0.0014 max mem: 33369 +Test: [ 400/2573] eta: 0:03:09 time: 0.0812 data: 0.0015 max mem: 33369 +Test: [ 500/2573] eta: 0:02:57 time: 0.0796 data: 0.0015 max mem: 33369 +Test: [ 600/2573] eta: 0:02:47 time: 0.0784 data: 0.0014 max mem: 33369 +Test: [ 700/2573] eta: 0:02:37 time: 0.0790 data: 0.0015 max mem: 33369 +Test: [ 800/2573] eta: 0:02:28 time: 0.0820 data: 0.0013 max mem: 33369 +Test: [ 900/2573] eta: 0:02:19 time: 0.0796 data: 0.0015 max mem: 33369 +Test: [1000/2573] eta: 0:02:10 time: 0.0795 data: 0.0015 max mem: 33369 +Test: [1100/2573] eta: 0:02:01 time: 0.0797 data: 0.0015 max mem: 33369 +Test: [1200/2573] eta: 0:01:53 time: 0.0800 data: 0.0015 max mem: 33369 +Test: [1300/2573] eta: 0:01:44 time: 0.0803 data: 0.0015 max mem: 33369 +Test: [1400/2573] eta: 0:01:36 time: 0.0780 data: 0.0014 max mem: 33369 +Test: [1500/2573] eta: 0:01:28 time: 0.0802 data: 0.0015 max mem: 33369 +Test: [1600/2573] eta: 0:01:19 time: 0.0821 data: 0.0015 max mem: 33369 +Test: [1700/2573] eta: 0:01:11 time: 0.0779 data: 0.0014 max mem: 33369 +Test: [1800/2573] eta: 0:01:03 time: 0.0803 data: 0.0014 max mem: 33369 +Test: [1900/2573] eta: 0:00:54 time: 0.0782 data: 0.0015 max mem: 33369 +Test: [2000/2573] eta: 0:00:46 time: 0.0797 data: 0.0014 max mem: 33369 +Test: [2100/2573] eta: 0:00:38 time: 0.0803 data: 0.0014 max mem: 33369 +Test: [2200/2573] eta: 0:00:30 time: 0.0807 data: 0.0014 max mem: 33369 +Test: [2300/2573] eta: 0:00:22 time: 0.0809 data: 0.0015 max mem: 33369 +Test: [2400/2573] eta: 0:00:13 time: 0.0768 data: 0.0015 max mem: 33369 +Test: [2500/2573] eta: 0:00:05 time: 0.0797 data: 0.0015 max mem: 33369 +Test: Total time: 0:03:28 +Final results: +Mean IoU is 61.73 + + precision@0.5 = 69.02 + precision@0.6 = 63.28 + precision@0.7 = 55.94 + precision@0.8 = 43.77 + precision@0.9 = 20.77 + overall IoU = 60.70 + +Average object IoU 61.73149186129871 +Overall IoU 60.70395278930664 +Better epoch: 13 + +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [14] [ 0/1319] eta: 1:48:16 lr: 3.392974749755691e-05 loss: 0.0947 (0.0947) time: 4.9255 data: 1.7156 max mem: 33369 +Epoch: [14] [ 10/1319] eta: 1:12:58 lr: 3.392084270123441e-05 loss: 0.0592 (0.0729) time: 3.3452 data: 0.1627 max mem: 33369 +Epoch: [14] [ 20/1319] eta: 1:10:12 lr: 3.391193764516433e-05 loss: 0.0592 (0.0705) time: 3.1590 data: 0.0074 max mem: 33369 +Epoch: [14] [ 30/1319] eta: 1:09:31 lr: 3.3903032329263314e-05 loss: 0.0600 (0.0661) time: 3.1761 data: 0.0079 max mem: 33369 +Epoch: [14] [ 40/1319] eta: 1:08:44 lr: 3.389412675344791e-05 loss: 0.0606 (0.0681) time: 3.2061 data: 0.0080 max mem: 33369 +Epoch: [14] [ 50/1319] eta: 1:08:02 lr: 3.388522091763468e-05 loss: 0.0684 (0.0683) time: 3.1867 data: 0.0079 max mem: 33369 +Epoch: [14] [ 60/1319] eta: 1:07:27 lr: 3.387631482174009e-05 loss: 0.0588 (0.0679) time: 3.1930 data: 0.0082 max mem: 33369 +Epoch: [14] [ 70/1319] eta: 1:06:53 lr: 3.386740846568057e-05 loss: 0.0552 (0.0660) time: 3.2041 data: 0.0083 max mem: 33369 +Epoch: [14] [ 80/1319] eta: 1:06:10 lr: 3.385850184937249e-05 loss: 0.0622 (0.0682) time: 3.1755 data: 0.0085 max mem: 33369 +Epoch: [14] [ 90/1319] eta: 1:05:36 lr: 3.3849594972732175e-05 loss: 0.0732 (0.0679) time: 3.1686 data: 0.0089 max mem: 33369 +Epoch: [14] [ 100/1319] eta: 1:04:59 lr: 3.38406878356759e-05 loss: 0.0489 (0.0668) time: 3.1735 data: 0.0086 max mem: 33369 +Epoch: [14] [ 110/1319] eta: 1:04:23 lr: 3.3831780438119907e-05 loss: 0.0523 (0.0660) time: 3.1614 data: 0.0079 max mem: 33369 +Epoch: [14] [ 120/1319] eta: 1:03:47 lr: 3.3822872779980336e-05 loss: 0.0646 (0.0669) time: 3.1575 data: 0.0084 max mem: 33369 +Epoch: [14] [ 130/1319] eta: 1:03:16 lr: 3.381396486117332e-05 loss: 0.0622 (0.0679) time: 3.1783 data: 0.0082 max mem: 33369 +Epoch: [14] [ 140/1319] eta: 1:02:42 lr: 3.380505668161494e-05 loss: 0.0598 (0.0677) time: 3.1886 data: 0.0083 max mem: 33369 +Epoch: [14] [ 150/1319] eta: 1:02:06 lr: 3.3796148241221185e-05 loss: 0.0655 (0.0684) time: 3.1515 data: 0.0084 max mem: 33369 +Epoch: [14] [ 160/1319] eta: 1:01:34 lr: 3.378723953990804e-05 loss: 0.0683 (0.0683) time: 3.1587 data: 0.0079 max mem: 33369 +Epoch: [14] [ 170/1319] eta: 1:01:04 lr: 3.3778330577591404e-05 loss: 0.0639 (0.0689) time: 3.2012 data: 0.0081 max mem: 33369 +Epoch: [14] [ 180/1319] eta: 1:00:29 lr: 3.3769421354187145e-05 loss: 0.0639 (0.0692) time: 3.1826 data: 0.0080 max mem: 33369 +Epoch: [14] [ 190/1319] eta: 0:59:57 lr: 3.376051186961107e-05 loss: 0.0592 (0.0691) time: 3.1601 data: 0.0078 max mem: 33369 +Epoch: [14] [ 200/1319] eta: 0:59:23 lr: 3.375160212377894e-05 loss: 0.0585 (0.0694) time: 3.1640 data: 0.0080 max mem: 33369 +Epoch: [14] [ 210/1319] eta: 0:58:50 lr: 3.374269211660646e-05 loss: 0.0581 (0.0687) time: 3.1581 data: 0.0081 max mem: 33369 +Epoch: [14] [ 220/1319] eta: 0:58:18 lr: 3.373378184800928e-05 loss: 0.0541 (0.0682) time: 3.1695 data: 0.0081 max mem: 33369 +Epoch: [14] [ 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eta: 0:32:48 lr: 3.330577985360116e-05 loss: 0.0588 (0.0649) time: 3.1840 data: 0.0080 max mem: 33369 +Epoch: [14] [ 710/1319] eta: 0:32:17 lr: 3.329685667077455e-05 loss: 0.0577 (0.0647) time: 3.1924 data: 0.0076 max mem: 33369 +Epoch: [14] [ 720/1319] eta: 0:31:44 lr: 3.3287933222238623e-05 loss: 0.0470 (0.0647) time: 3.1645 data: 0.0077 max mem: 33369 +Epoch: [14] [ 730/1319] eta: 0:31:12 lr: 3.327900950790632e-05 loss: 0.0470 (0.0647) time: 3.1477 data: 0.0079 max mem: 33369 +Epoch: [14] [ 740/1319] eta: 0:30:41 lr: 3.327008552769054e-05 loss: 0.0640 (0.0647) time: 3.1687 data: 0.0076 max mem: 33369 +Epoch: [14] [ 750/1319] eta: 0:30:09 lr: 3.32611612815041e-05 loss: 0.0595 (0.0647) time: 3.1567 data: 0.0076 max mem: 33369 +Epoch: [14] [ 760/1319] eta: 0:29:37 lr: 3.325223676925979e-05 loss: 0.0550 (0.0647) time: 3.1548 data: 0.0077 max mem: 33369 +Epoch: [14] [ 770/1319] eta: 0:29:05 lr: 3.324331199087032e-05 loss: 0.0536 (0.0647) time: 3.1683 data: 0.0074 max mem: 33369 +Epoch: 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(0.0649) time: 3.1958 data: 0.0077 max mem: 33369 +Epoch: [14] [1020/1319] eta: 0:15:50 lr: 3.3020105777547046e-05 loss: 0.0635 (0.0649) time: 3.1850 data: 0.0079 max mem: 33369 +Epoch: [14] [1030/1319] eta: 0:15:18 lr: 3.301117404856897e-05 loss: 0.0549 (0.0648) time: 3.1904 data: 0.0081 max mem: 33369 +Epoch: [14] [1040/1319] eta: 0:14:47 lr: 3.300224205106842e-05 loss: 0.0544 (0.0648) time: 3.1910 data: 0.0081 max mem: 33369 +Epoch: [14] [1050/1319] eta: 0:14:15 lr: 3.2993309784956545e-05 loss: 0.0613 (0.0648) time: 3.1933 data: 0.0078 max mem: 33369 +Epoch: [14] [1060/1319] eta: 0:13:43 lr: 3.298437725014447e-05 loss: 0.0537 (0.0647) time: 3.1895 data: 0.0078 max mem: 33369 +Epoch: [14] [1070/1319] eta: 0:13:11 lr: 3.297544444654327e-05 loss: 0.0466 (0.0646) time: 3.1976 data: 0.0081 max mem: 33369 +Epoch: [14] [1080/1319] eta: 0:12:40 lr: 3.296651137406393e-05 loss: 0.0490 (0.0647) time: 3.1863 data: 0.0078 max mem: 33369 +Epoch: [14] [1090/1319] eta: 0:12:08 lr: 3.2957578032617413e-05 loss: 0.0570 (0.0647) time: 3.1878 data: 0.0081 max mem: 33369 +Epoch: [14] [1100/1319] eta: 0:11:36 lr: 3.29486444221146e-05 loss: 0.0634 (0.0648) time: 3.1885 data: 0.0085 max mem: 33369 +Epoch: [14] [1110/1319] eta: 0:11:04 lr: 3.293971054246633e-05 loss: 0.0634 (0.0648) time: 3.1626 data: 0.0080 max mem: 33369 +Epoch: [14] [1120/1319] eta: 0:10:32 lr: 3.293077639358339e-05 loss: 0.0567 (0.0647) time: 3.1494 data: 0.0076 max mem: 33369 +Epoch: [14] [1130/1319] eta: 0:10:01 lr: 3.2921841975376476e-05 loss: 0.0567 (0.0649) time: 3.1701 data: 0.0079 max mem: 33369 +Epoch: [14] [1140/1319] eta: 0:09:29 lr: 3.291290728775627e-05 loss: 0.0559 (0.0648) time: 3.1880 data: 0.0083 max mem: 33369 +Epoch: [14] [1150/1319] eta: 0:08:57 lr: 3.290397233063338e-05 loss: 0.0517 (0.0647) time: 3.1874 data: 0.0086 max mem: 33369 +Epoch: [14] [1160/1319] eta: 0:08:25 lr: 3.2895037103918356e-05 loss: 0.0492 (0.0647) time: 3.1988 data: 0.0083 max mem: 33369 +Epoch: [14] [1170/1319] eta: 0:07:53 lr: 3.2886101607521696e-05 loss: 0.0596 (0.0647) time: 3.2051 data: 0.0079 max mem: 33369 +Epoch: [14] [1180/1319] eta: 0:07:22 lr: 3.287716584135384e-05 loss: 0.0604 (0.0647) time: 3.2123 data: 0.0081 max mem: 33369 +Epoch: [14] [1190/1319] eta: 0:06:50 lr: 3.286822980532516e-05 loss: 0.0607 (0.0648) time: 3.1917 data: 0.0079 max mem: 33369 +Epoch: [14] [1200/1319] eta: 0:06:18 lr: 3.285929349934599e-05 loss: 0.0542 (0.0647) time: 3.1717 data: 0.0080 max mem: 33369 +Epoch: [14] [1210/1319] eta: 0:05:46 lr: 3.28503569233266e-05 loss: 0.0516 (0.0647) time: 3.1713 data: 0.0080 max mem: 33369 +Epoch: [14] [1220/1319] eta: 0:05:14 lr: 3.284142007717719e-05 loss: 0.0566 (0.0647) time: 3.1433 data: 0.0080 max mem: 33369 +Epoch: [14] [1230/1319] eta: 0:04:43 lr: 3.283248296080793e-05 loss: 0.0652 (0.0647) time: 3.1455 data: 0.0078 max mem: 33369 +Epoch: [14] [1240/1319] eta: 0:04:11 lr: 3.2823545574128904e-05 loss: 0.0644 (0.0647) time: 3.1601 data: 0.0079 max mem: 33369 +Epoch: 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+/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 2:03:51 time: 2.8881 data: 2.7994 max mem: 33369 +Test: [ 100/2573] eta: 0:04:19 time: 0.0775 data: 0.0016 max mem: 33369 +Test: [ 200/2573] eta: 0:03:38 time: 0.0783 data: 0.0015 max mem: 33369 +Test: [ 300/2573] eta: 0:03:17 time: 0.0792 data: 0.0014 max mem: 33369 +Test: [ 400/2573] eta: 0:03:03 time: 0.0799 data: 0.0014 max mem: 33369 +Test: [ 500/2573] eta: 0:02:52 time: 0.0783 data: 0.0014 max mem: 33369 +Test: [ 600/2573] eta: 0:02:43 time: 0.0783 data: 0.0014 max mem: 33369 +Test: [ 700/2573] eta: 0:02:34 time: 0.0783 data: 0.0014 max mem: 33369 +Test: [ 800/2573] eta: 0:02:25 time: 0.0821 data: 0.0014 max mem: 33369 +Test: [ 900/2573] eta: 0:02:16 time: 0.0792 data: 0.0014 max mem: 33369 +Test: [1000/2573] eta: 0:02:08 time: 0.0794 data: 0.0015 max mem: 33369 +Test: [1100/2573] eta: 0:01:59 time: 0.0802 data: 0.0016 max mem: 33369 +Test: [1200/2573] eta: 0:01:51 time: 0.0806 data: 0.0015 max mem: 33369 +Test: [1300/2573] eta: 0:01:43 time: 0.0795 data: 0.0015 max mem: 33369 +Test: [1400/2573] eta: 0:01:35 time: 0.0774 data: 0.0014 max mem: 33369 +Test: [1500/2573] eta: 0:01:26 time: 0.0796 data: 0.0014 max mem: 33369 +Test: [1600/2573] eta: 0:01:18 time: 0.0832 data: 0.0015 max mem: 33369 +Test: [1700/2573] eta: 0:01:10 time: 0.0773 data: 0.0014 max mem: 33369 +Test: [1800/2573] eta: 0:01:02 time: 0.0815 data: 0.0016 max mem: 33369 +Test: [1900/2573] eta: 0:00:54 time: 0.0785 data: 0.0014 max mem: 33369 +Test: [2000/2573] eta: 0:00:46 time: 0.0798 data: 0.0017 max mem: 33369 +Test: [2100/2573] eta: 0:00:38 time: 0.0809 data: 0.0014 max mem: 33369 +Test: [2200/2573] eta: 0:00:30 time: 0.0818 data: 0.0015 max mem: 33369 +Test: [2300/2573] eta: 0:00:21 time: 0.0802 data: 0.0014 max mem: 33369 +Test: [2400/2573] eta: 0:00:13 time: 0.0754 data: 0.0014 max mem: 33369 +Test: [2500/2573] eta: 0:00:05 time: 0.0795 data: 0.0014 max mem: 33369 +Test: Total time: 0:03:27 +Final results: +Mean IoU is 61.96 + + precision@0.5 = 69.83 + precision@0.6 = 63.93 + precision@0.7 = 56.21 + precision@0.8 = 44.24 + precision@0.9 = 20.85 + overall IoU = 60.43 + +Average object IoU 61.959356707348 +Overall IoU 60.433746337890625 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [15] [ 0/1319] eta: 3:21:36 lr: 3.275293070617704e-05 loss: 0.0995 (0.0995) time: 9.1712 data: 2.4131 max mem: 33369 +Epoch: [15] [ 10/1319] eta: 1:21:06 lr: 3.274399090977129e-05 loss: 0.0593 (0.0691) time: 3.7179 data: 0.2276 max mem: 33369 +Epoch: [15] [ 20/1319] eta: 1:14:37 lr: 3.2735050842162644e-05 loss: 0.0569 (0.0635) time: 3.1607 data: 0.0086 max mem: 33369 +Epoch: [15] [ 30/1319] eta: 1:11:52 lr: 3.2726110503260586e-05 loss: 0.0537 (0.0628) time: 3.1409 data: 0.0079 max mem: 33369 +Epoch: [15] [ 40/1319] eta: 1:10:36 lr: 3.271716989297451e-05 loss: 0.0494 (0.0592) time: 3.1709 data: 0.0080 max mem: 33369 +Epoch: [15] [ 50/1319] eta: 1:09:27 lr: 3.2708229011213794e-05 loss: 0.0497 (0.0590) time: 3.1880 data: 0.0080 max mem: 33369 +Epoch: [15] [ 60/1319] eta: 1:08:33 lr: 3.269928785788772e-05 loss: 0.0635 (0.0622) time: 3.1749 data: 0.0078 max mem: 33369 +Epoch: [15] [ 70/1319] eta: 1:07:38 lr: 3.2690346432905536e-05 loss: 0.0615 (0.0627) time: 3.1627 data: 0.0080 max mem: 33369 +Epoch: [15] [ 80/1319] eta: 1:07:00 lr: 3.268140473617642e-05 loss: 0.0546 (0.0616) time: 3.1773 data: 0.0080 max mem: 33369 +Epoch: [15] [ 90/1319] eta: 1:06:11 lr: 3.26724627676095e-05 loss: 0.0545 (0.0615) time: 3.1670 data: 0.0080 max mem: 33369 +Epoch: [15] [ 100/1319] eta: 1:05:30 lr: 3.266352052711384e-05 loss: 0.0546 (0.0626) time: 3.1390 data: 0.0086 max mem: 33369 +Epoch: [15] [ 110/1319] eta: 1:04:55 lr: 3.265457801459844e-05 loss: 0.0621 (0.0627) time: 3.1780 data: 0.0085 max mem: 33369 +Epoch: [15] [ 120/1319] eta: 1:04:20 lr: 3.2645635229972264e-05 loss: 0.0523 (0.0616) time: 3.1991 data: 0.0080 max mem: 33369 +Epoch: [15] [ 130/1319] eta: 1:03:45 lr: 3.2636692173144204e-05 loss: 0.0522 (0.0615) time: 3.1921 data: 0.0083 max mem: 33369 +Epoch: [15] [ 140/1319] eta: 1:03:12 lr: 3.2627748844023084e-05 loss: 0.0525 (0.0615) time: 3.1965 data: 0.0083 max mem: 33369 +Epoch: [15] [ 150/1319] eta: 1:02:35 lr: 3.261880524251768e-05 loss: 0.0546 (0.0616) time: 3.1785 data: 0.0086 max mem: 33369 +Epoch: [15] [ 160/1319] eta: 1:01:58 lr: 3.260986136853672e-05 loss: 0.0566 (0.0617) time: 3.1536 data: 0.0083 max mem: 33369 +Epoch: [15] [ 170/1319] eta: 1:01:28 lr: 3.2600917221988844e-05 loss: 0.0541 (0.0620) time: 3.1941 data: 0.0078 max mem: 33369 +Epoch: [15] [ 180/1319] eta: 1:00:56 lr: 3.259197280278268e-05 loss: 0.0561 (0.0622) time: 3.2246 data: 0.0080 max mem: 33369 +Epoch: [15] [ 190/1319] eta: 1:00:23 lr: 3.258302811082674e-05 loss: 0.0538 (0.0618) time: 3.2021 data: 0.0080 max mem: 33369 +Epoch: [15] [ 200/1319] eta: 0:59:48 lr: 3.257408314602953e-05 loss: 0.0532 (0.0618) time: 3.1735 data: 0.0081 max mem: 33369 +Epoch: [15] [ 210/1319] eta: 0:59:12 lr: 3.2565137908299456e-05 loss: 0.0656 (0.0622) time: 3.1436 data: 0.0082 max mem: 33369 +Epoch: [15] [ 220/1319] eta: 0:58:39 lr: 3.25561923975449e-05 loss: 0.0656 (0.0624) time: 3.1568 data: 0.0083 max mem: 33369 +Epoch: [15] [ 230/1319] eta: 0:58:06 lr: 3.2547246613674155e-05 loss: 0.0562 (0.0623) time: 3.1832 data: 0.0084 max mem: 33369 +Epoch: [15] [ 240/1319] eta: 0:57:34 lr: 3.253830055659547e-05 loss: 0.0493 (0.0621) time: 3.1879 data: 0.0081 max mem: 33369 +Epoch: [15] [ 250/1319] eta: 0:57:00 lr: 3.252935422621704e-05 loss: 0.0475 (0.0615) time: 3.1861 data: 0.0081 max mem: 33369 +Epoch: [15] [ 260/1319] eta: 0:56:28 lr: 3.252040762244701e-05 loss: 0.0467 (0.0611) time: 3.1795 data: 0.0082 max mem: 33369 +Epoch: [15] [ 270/1319] eta: 0:55:52 lr: 3.251146074519342e-05 loss: 0.0547 (0.0618) time: 3.1425 data: 0.0085 max mem: 33369 +Epoch: [15] [ 280/1319] eta: 0:55:19 lr: 3.2502513594364305e-05 loss: 0.0663 (0.0618) time: 3.1418 data: 0.0084 max mem: 33369 +Epoch: [15] [ 290/1319] eta: 0:54:48 lr: 3.2493566169867616e-05 loss: 0.0590 (0.0618) time: 3.1946 data: 0.0078 max mem: 33369 +Epoch: [15] [ 300/1319] eta: 0:54:16 lr: 3.248461847161124e-05 loss: 0.0541 (0.0615) time: 3.2015 data: 0.0079 max mem: 33369 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eta: 0:07:54 lr: 3.170511015754181e-05 loss: 0.0633 (0.0622) time: 3.1601 data: 0.0082 max mem: 33369 +Epoch: [15] [1180/1319] eta: 0:07:22 lr: 3.16961380006451e-05 loss: 0.0621 (0.0622) time: 3.1476 data: 0.0078 max mem: 33369 +Epoch: [15] [1190/1319] eta: 0:06:50 lr: 3.16871655615474e-05 loss: 0.0675 (0.0624) time: 3.1737 data: 0.0081 max mem: 33369 +Epoch: [15] [1200/1319] eta: 0:06:19 lr: 3.1678192840151044e-05 loss: 0.0731 (0.0625) time: 3.1944 data: 0.0082 max mem: 33369 +Epoch: [15] [1210/1319] eta: 0:05:47 lr: 3.16692198363583e-05 loss: 0.0633 (0.0625) time: 3.2117 data: 0.0080 max mem: 33369 +Epoch: [15] [1220/1319] eta: 0:05:15 lr: 3.1660246550071386e-05 loss: 0.0590 (0.0625) time: 3.2000 data: 0.0078 max mem: 33369 +Epoch: [15] [1230/1319] eta: 0:04:43 lr: 3.165127298119242e-05 loss: 0.0717 (0.0627) time: 3.1695 data: 0.0078 max mem: 33369 +Epoch: [15] [1240/1319] eta: 0:04:11 lr: 3.164229912962349e-05 loss: 0.0725 (0.0629) time: 3.1950 data: 0.0079 max mem: 33369 +Epoch: 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+/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 2:12:09 time: 3.0817 data: 2.9913 max mem: 33369 +Test: [ 100/2573] eta: 0:04:25 time: 0.0766 data: 0.0015 max mem: 33369 +Test: [ 200/2573] eta: 0:03:41 time: 0.0786 data: 0.0015 max mem: 33369 +Test: [ 300/2573] eta: 0:03:20 time: 0.0800 data: 0.0014 max mem: 33369 +Test: [ 400/2573] eta: 0:03:05 time: 0.0795 data: 0.0013 max mem: 33369 +Test: [ 500/2573] eta: 0:02:54 time: 0.0783 data: 0.0014 max mem: 33369 +Test: [ 600/2573] eta: 0:02:44 time: 0.0798 data: 0.0015 max mem: 33369 +Test: [ 700/2573] eta: 0:02:35 time: 0.0782 data: 0.0014 max mem: 33369 +Test: [ 800/2573] eta: 0:02:26 time: 0.0822 data: 0.0015 max mem: 33369 +Test: [ 900/2573] eta: 0:02:17 time: 0.0792 data: 0.0015 max mem: 33369 +Test: [1000/2573] eta: 0:02:08 time: 0.0791 data: 0.0014 max mem: 33369 +Test: [1100/2573] eta: 0:02:00 time: 0.0800 data: 0.0015 max mem: 33369 +Test: [1200/2573] eta: 0:01:52 time: 0.0796 data: 0.0015 max mem: 33369 +Test: [1300/2573] eta: 0:01:43 time: 0.0793 data: 0.0015 max mem: 33369 +Test: [1400/2573] eta: 0:01:35 time: 0.0772 data: 0.0014 max mem: 33369 +Test: [1500/2573] eta: 0:01:27 time: 0.0797 data: 0.0015 max mem: 33369 +Test: [1600/2573] eta: 0:01:18 time: 0.0822 data: 0.0014 max mem: 33369 +Test: [1700/2573] eta: 0:01:10 time: 0.0774 data: 0.0013 max mem: 33369 +Test: [1800/2573] eta: 0:01:02 time: 0.0808 data: 0.0015 max mem: 33369 +Test: [1900/2573] eta: 0:00:54 time: 0.0772 data: 0.0014 max mem: 33369 +Test: [2000/2573] eta: 0:00:46 time: 0.0795 data: 0.0015 max mem: 33369 +Test: [2100/2573] eta: 0:00:38 time: 0.0809 data: 0.0014 max mem: 33369 +Test: [2200/2573] eta: 0:00:30 time: 0.0806 data: 0.0014 max mem: 33369 +Test: [2300/2573] eta: 0:00:21 time: 0.0806 data: 0.0014 max mem: 33369 +Test: [2400/2573] eta: 0:00:13 time: 0.0772 data: 0.0015 max mem: 33369 +Test: [2500/2573] eta: 0:00:05 time: 0.0786 data: 0.0014 max mem: 33369 +Test: Total time: 0:03:27 +Final results: +Mean IoU is 61.78 + + precision@0.5 = 69.18 + precision@0.6 = 63.03 + precision@0.7 = 55.82 + precision@0.8 = 44.59 + precision@0.9 = 20.94 + overall IoU = 60.49 + +Average object IoU 61.78496505612935 +Overall IoU 60.48982620239258 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [16] [ 0/1319] eta: 2:59:31 lr: 3.157139575288201e-05 loss: 0.0963 (0.0963) time: 8.1666 data: 2.5153 max mem: 33369 +Epoch: [16] [ 10/1319] eta: 1:18:44 lr: 3.1562419381047834e-05 loss: 0.0443 (0.0524) time: 3.6092 data: 0.2357 max mem: 33369 +Epoch: [16] [ 20/1319] eta: 1:13:51 lr: 3.155344272555071e-05 loss: 0.0522 (0.0535) time: 3.1736 data: 0.0080 max mem: 33369 +Epoch: [16] [ 30/1319] eta: 1:11:29 lr: 3.154446578629201e-05 loss: 0.0542 (0.0544) time: 3.1731 data: 0.0084 max mem: 33369 +Epoch: [16] [ 40/1319] eta: 1:10:19 lr: 3.153548856317304e-05 loss: 0.0459 (0.0528) time: 3.1812 data: 0.0085 max mem: 33369 +Epoch: [16] [ 50/1319] eta: 1:09:12 lr: 3.152651105609501e-05 loss: 0.0452 (0.0554) time: 3.1868 data: 0.0083 max mem: 33369 +Epoch: [16] [ 60/1319] eta: 1:08:26 lr: 3.1517533264959104e-05 loss: 0.0452 (0.0541) time: 3.1839 data: 0.0081 max mem: 33369 +Epoch: [16] [ 70/1319] eta: 1:07:38 lr: 3.150855518966642e-05 loss: 0.0455 (0.0559) time: 3.1898 data: 0.0078 max mem: 33369 +Epoch: [16] [ 80/1319] eta: 1:06:55 lr: 3.1499576830118e-05 loss: 0.0508 (0.0547) time: 3.1798 data: 0.0076 max mem: 33369 +Epoch: [16] [ 90/1319] eta: 1:06:11 lr: 3.14905981862148e-05 loss: 0.0469 (0.0545) time: 3.1673 data: 0.0080 max mem: 33369 +Epoch: [16] [ 100/1319] eta: 1:05:36 lr: 3.1481619257857746e-05 loss: 0.0557 (0.0546) time: 3.1807 data: 0.0084 max mem: 33369 +Epoch: [16] [ 110/1319] eta: 1:04:58 lr: 3.147264004494766e-05 loss: 0.0569 (0.0567) time: 3.1954 data: 0.0083 max mem: 33369 +Epoch: [16] [ 120/1319] eta: 1:04:17 lr: 3.1463660547385324e-05 loss: 0.0581 (0.0570) time: 3.1553 data: 0.0083 max mem: 33369 +Epoch: [16] [ 130/1319] eta: 1:03:42 lr: 3.1454680765071425e-05 loss: 0.0549 (0.0572) time: 3.1596 data: 0.0080 max mem: 33369 +Epoch: [16] [ 140/1319] eta: 1:03:02 lr: 3.1445700697906627e-05 loss: 0.0420 (0.0561) time: 3.1575 data: 0.0081 max mem: 33369 +Epoch: [16] [ 150/1319] eta: 1:02:26 lr: 3.1436720345791495e-05 loss: 0.0409 (0.0561) time: 3.1381 data: 0.0083 max mem: 33369 +Epoch: [16] [ 160/1319] eta: 1:01:54 lr: 3.1427739708626534e-05 loss: 0.0519 (0.0556) time: 3.1776 data: 0.0082 max mem: 33369 +Epoch: [16] [ 170/1319] eta: 1:01:17 lr: 3.141875878631219e-05 loss: 0.0495 (0.0567) time: 3.1687 data: 0.0083 max mem: 33369 +Epoch: [16] [ 180/1319] eta: 1:00:44 lr: 3.140977757874883e-05 loss: 0.0538 (0.0572) time: 3.1628 data: 0.0084 max mem: 33369 +Epoch: [16] [ 190/1319] eta: 1:00:13 lr: 3.140079608583676e-05 loss: 0.0535 (0.0568) time: 3.2023 data: 0.0081 max mem: 33369 +Epoch: [16] [ 200/1319] eta: 0:59:38 lr: 3.1391814307476244e-05 loss: 0.0453 (0.0573) time: 3.1796 data: 0.0081 max mem: 33369 +Epoch: [16] [ 210/1319] eta: 0:59:06 lr: 3.138283224356744e-05 loss: 0.0559 (0.0577) time: 3.1748 data: 0.0080 max mem: 33369 +Epoch: [16] [ 220/1319] eta: 0:58:33 lr: 3.137384989401046e-05 loss: 0.0532 (0.0575) time: 3.1885 data: 0.0077 max mem: 33369 +Epoch: [16] [ 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eta: 0:12:08 lr: 3.059128050381978e-05 loss: 0.0479 (0.0585) time: 3.1504 data: 0.0083 max mem: 33369 +Epoch: [16] [1100/1319] eta: 0:11:36 lr: 3.058227261803723e-05 loss: 0.0441 (0.0585) time: 3.1373 data: 0.0080 max mem: 33369 +Epoch: [16] [1110/1319] eta: 0:11:04 lr: 3.0573264437440946e-05 loss: 0.0551 (0.0586) time: 3.1309 data: 0.0081 max mem: 33369 +Epoch: [16] [1120/1319] eta: 0:10:32 lr: 3.056425596192476e-05 loss: 0.0541 (0.0586) time: 3.1479 data: 0.0080 max mem: 33369 +Epoch: [16] [1130/1319] eta: 0:10:00 lr: 3.0555247191382436e-05 loss: 0.0519 (0.0586) time: 3.1477 data: 0.0078 max mem: 33369 +Epoch: [16] [1140/1319] eta: 0:09:29 lr: 3.054623812570766e-05 loss: 0.0514 (0.0585) time: 3.1546 data: 0.0081 max mem: 33369 +Epoch: [16] [1150/1319] eta: 0:08:57 lr: 3.053722876479403e-05 loss: 0.0468 (0.0585) time: 3.1794 data: 0.0081 max mem: 33369 +Epoch: [16] [1160/1319] eta: 0:08:25 lr: 3.0528219108535084e-05 loss: 0.0468 (0.0585) time: 3.1788 data: 0.0082 max mem: 33369 +Epoch: [16] [1170/1319] eta: 0:07:53 lr: 3.0519209156824297e-05 loss: 0.0529 (0.0585) time: 3.1734 data: 0.0084 max mem: 33369 +Epoch: [16] [1180/1319] eta: 0:07:21 lr: 3.0510198909555044e-05 loss: 0.0531 (0.0585) time: 3.1950 data: 0.0084 max mem: 33369 +Epoch: [16] [1190/1319] eta: 0:06:50 lr: 3.0501188366620653e-05 loss: 0.0594 (0.0585) time: 3.2074 data: 0.0087 max mem: 33369 +Epoch: [16] [1200/1319] eta: 0:06:18 lr: 3.0492177527914355e-05 loss: 0.0570 (0.0586) time: 3.1839 data: 0.0084 max mem: 33369 +Epoch: [16] [1210/1319] eta: 0:05:46 lr: 3.0483166393329327e-05 loss: 0.0537 (0.0585) time: 3.1528 data: 0.0079 max mem: 33369 +Epoch: [16] [1220/1319] eta: 0:05:14 lr: 3.0474154962758662e-05 loss: 0.0523 (0.0587) time: 3.1659 data: 0.0084 max mem: 33369 +Epoch: [16] [1230/1319] eta: 0:04:42 lr: 3.0465143236095372e-05 loss: 0.0516 (0.0587) time: 3.1970 data: 0.0085 max mem: 33369 +Epoch: [16] [1240/1319] eta: 0:04:11 lr: 3.045613121323242e-05 loss: 0.0594 (0.0587) time: 3.2103 data: 0.0085 max mem: 33369 +Epoch: [16] [1250/1319] eta: 0:03:39 lr: 3.044711889406267e-05 loss: 0.0589 (0.0587) time: 3.2142 data: 0.0089 max mem: 33369 +Epoch: [16] [1260/1319] eta: 0:03:07 lr: 3.0438106278478923e-05 loss: 0.0595 (0.0587) time: 3.1705 data: 0.0093 max mem: 33369 +Epoch: [16] [1270/1319] eta: 0:02:35 lr: 3.0429093366373907e-05 loss: 0.0595 (0.0588) time: 3.1645 data: 0.0092 max mem: 33369 +Epoch: [16] [1280/1319] eta: 0:02:04 lr: 3.0420080157640274e-05 loss: 0.0568 (0.0588) time: 3.1881 data: 0.0090 max mem: 33369 +Epoch: [16] [1290/1319] eta: 0:01:32 lr: 3.0411066652170593e-05 loss: 0.0568 (0.0588) time: 3.1682 data: 0.0089 max mem: 33369 +Epoch: [16] [1300/1319] eta: 0:01:00 lr: 3.040205284985739e-05 loss: 0.0533 (0.0588) time: 3.1892 data: 0.0085 max mem: 33369 +Epoch: [16] [1310/1319] eta: 0:00:28 lr: 3.039303875059306e-05 loss: 0.0526 (0.0588) time: 3.2144 data: 0.0078 max mem: 33369 +Epoch: [16] Total time: 1:09:55 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 2:09:28 time: 3.0194 data: 2.9233 max mem: 33369 +Test: [ 100/2573] eta: 0:04:22 time: 0.0770 data: 0.0015 max mem: 33369 +Test: [ 200/2573] eta: 0:03:40 time: 0.0783 data: 0.0014 max mem: 33369 +Test: [ 300/2573] eta: 0:03:19 time: 0.0795 data: 0.0014 max mem: 33369 +Test: [ 400/2573] eta: 0:03:05 time: 0.0799 data: 0.0014 max mem: 33369 +Test: [ 500/2573] eta: 0:02:53 time: 0.0784 data: 0.0014 max mem: 33369 +Test: [ 600/2573] eta: 0:02:43 time: 0.0786 data: 0.0015 max mem: 33369 +Test: [ 700/2573] eta: 0:02:34 time: 0.0793 data: 0.0014 max mem: 33369 +Test: [ 800/2573] eta: 0:02:26 time: 0.0822 data: 0.0016 max mem: 33369 +Test: [ 900/2573] eta: 0:02:17 time: 0.0793 data: 0.0015 max mem: 33369 +Test: [1000/2573] eta: 0:02:08 time: 0.0791 data: 0.0015 max mem: 33369 +Test: [1100/2573] eta: 0:02:00 time: 0.0795 data: 0.0015 max mem: 33369 +Test: [1200/2573] eta: 0:01:52 time: 0.0797 data: 0.0014 max mem: 33369 +Test: [1300/2573] eta: 0:01:43 time: 0.0787 data: 0.0014 max mem: 33369 +Test: [1400/2573] eta: 0:01:35 time: 0.0771 data: 0.0013 max mem: 33369 +Test: [1500/2573] eta: 0:01:27 time: 0.0811 data: 0.0015 max mem: 33369 +Test: [1600/2573] eta: 0:01:18 time: 0.0836 data: 0.0016 max mem: 33369 +Test: [1700/2573] eta: 0:01:10 time: 0.0799 data: 0.0014 max mem: 33369 +Test: [1800/2573] eta: 0:01:02 time: 0.0805 data: 0.0015 max mem: 33369 +Test: [1900/2573] eta: 0:00:54 time: 0.0790 data: 0.0014 max mem: 33369 +Test: [2000/2573] eta: 0:00:46 time: 0.0794 data: 0.0014 max mem: 33369 +Test: [2100/2573] eta: 0:00:38 time: 0.0816 data: 0.0014 max mem: 33369 +Test: [2200/2573] eta: 0:00:30 time: 0.0808 data: 0.0014 max mem: 33369 +Test: [2300/2573] eta: 0:00:21 time: 0.0808 data: 0.0014 max mem: 33369 +Test: [2400/2573] eta: 0:00:13 time: 0.0761 data: 0.0014 max mem: 33369 +Test: [2500/2573] eta: 0:00:05 time: 0.0799 data: 0.0015 max mem: 33369 +Test: Total time: 0:03:27 +Final results: +Mean IoU is 62.68 + + precision@0.5 = 69.96 + precision@0.6 = 63.91 + precision@0.7 = 55.96 + precision@0.8 = 45.26 + precision@0.9 = 22.10 + overall IoU = 61.13 + +Average object IoU 62.679462649946025 +Overall IoU 61.12555694580078 +Better epoch: 16 + +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [17] [ 0/1319] eta: 1:49:17 lr: 3.0384925807273e-05 loss: 0.0848 (0.0848) time: 4.9718 data: 1.7026 max mem: 33369 +Epoch: [17] [ 10/1319] eta: 1:14:11 lr: 3.0375911143504937e-05 loss: 0.0601 (0.0613) time: 3.4006 data: 0.1625 max mem: 33369 +Epoch: [17] [ 20/1319] eta: 1:11:13 lr: 3.0366896182473385e-05 loss: 0.0480 (0.0561) time: 3.2059 data: 0.0081 max mem: 33369 +Epoch: [17] [ 30/1319] eta: 1:09:58 lr: 3.035788092407048e-05 loss: 0.0480 (0.0597) time: 3.1779 data: 0.0080 max mem: 33369 +Epoch: [17] [ 40/1319] eta: 1:09:01 lr: 3.034886536818829e-05 loss: 0.0584 (0.0593) time: 3.1840 data: 0.0079 max mem: 33369 +Epoch: [17] [ 50/1319] eta: 1:08:12 lr: 3.0339849514718806e-05 loss: 0.0529 (0.0580) time: 3.1750 data: 0.0082 max mem: 33369 +Epoch: [17] [ 60/1319] eta: 1:07:28 lr: 3.033083336355392e-05 loss: 0.0501 (0.0558) time: 3.1702 data: 0.0081 max mem: 33369 +Epoch: [17] [ 70/1319] eta: 1:06:51 lr: 3.03218169145855e-05 loss: 0.0435 (0.0547) time: 3.1780 data: 0.0075 max mem: 33369 +Epoch: [17] [ 80/1319] eta: 1:06:15 lr: 3.0312800167705292e-05 loss: 0.0458 (0.0550) time: 3.1855 data: 0.0081 max mem: 33369 +Epoch: [17] [ 90/1319] eta: 1:05:42 lr: 3.030378312280498e-05 loss: 0.0479 (0.0547) time: 3.1951 data: 0.0088 max mem: 33369 +Epoch: [17] [ 100/1319] eta: 1:05:05 lr: 3.0294765779776184e-05 loss: 0.0517 (0.0548) time: 3.1852 data: 0.0088 max mem: 33369 +Epoch: [17] [ 110/1319] eta: 1:04:31 lr: 3.0285748138510444e-05 loss: 0.0517 (0.0547) time: 3.1783 data: 0.0085 max mem: 33369 +Epoch: [17] [ 120/1319] eta: 1:03:56 lr: 3.0276730198899216e-05 loss: 0.0435 (0.0540) time: 3.1775 data: 0.0083 max mem: 33369 +Epoch: [17] [ 130/1319] eta: 1:03:23 lr: 3.0267711960833896e-05 loss: 0.0446 (0.0553) time: 3.1766 data: 0.0084 max mem: 33369 +Epoch: [17] [ 140/1319] eta: 1:02:45 lr: 3.0258693424205785e-05 loss: 0.0560 (0.0555) time: 3.1602 data: 0.0089 max mem: 33369 +Epoch: [17] [ 150/1319] eta: 1:02:14 lr: 3.024967458890613e-05 loss: 0.0532 (0.0549) time: 3.1690 data: 0.0087 max mem: 33369 +Epoch: [17] [ 160/1319] eta: 1:01:40 lr: 3.0240655454826085e-05 loss: 0.0485 (0.0558) time: 3.1879 data: 0.0083 max mem: 33369 +Epoch: [17] [ 170/1319] eta: 1:01:10 lr: 3.023163602185673e-05 loss: 0.0566 (0.0557) time: 3.1904 data: 0.0085 max mem: 33369 +Epoch: [17] [ 180/1319] eta: 1:00:36 lr: 3.022261628988908e-05 loss: 0.0548 (0.0556) time: 3.1863 data: 0.0084 max mem: 33369 +Epoch: [17] [ 190/1319] eta: 1:00:08 lr: 3.0213596258814065e-05 loss: 0.0464 (0.0556) time: 3.2121 data: 0.0083 max mem: 33369 +Epoch: [17] [ 200/1319] eta: 0:59:34 lr: 3.020457592852254e-05 loss: 0.0525 (0.0561) time: 3.2133 data: 0.0082 max mem: 33369 +Epoch: [17] [ 210/1319] eta: 0:59:00 lr: 3.0195555298905282e-05 loss: 0.0541 (0.0559) time: 3.1597 data: 0.0082 max mem: 33369 +Epoch: [17] [ 220/1319] eta: 0:58:27 lr: 3.0186534369853002e-05 loss: 0.0498 (0.0566) time: 3.1571 data: 0.0085 max mem: 33369 +Epoch: [17] [ 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eta: 0:37:05 lr: 2.9825450406848343e-05 loss: 0.0501 (0.0552) time: 3.1876 data: 0.0080 max mem: 33369 +Epoch: [17] [ 630/1319] eta: 0:36:32 lr: 2.981641710590631e-05 loss: 0.0540 (0.0555) time: 3.1517 data: 0.0079 max mem: 33369 +Epoch: [17] [ 640/1319] eta: 0:36:00 lr: 2.9807383500869036e-05 loss: 0.0595 (0.0558) time: 3.1502 data: 0.0081 max mem: 33369 +Epoch: [17] [ 650/1319] eta: 0:35:28 lr: 2.9798349591623877e-05 loss: 0.0639 (0.0560) time: 3.1630 data: 0.0081 max mem: 33369 +Epoch: [17] [ 660/1319] eta: 0:34:57 lr: 2.9789315378058107e-05 loss: 0.0607 (0.0562) time: 3.1990 data: 0.0080 max mem: 33369 +Epoch: [17] [ 670/1319] eta: 0:34:25 lr: 2.978028086005893e-05 loss: 0.0577 (0.0562) time: 3.2132 data: 0.0080 max mem: 33369 +Epoch: [17] [ 680/1319] eta: 0:33:54 lr: 2.977124603751345e-05 loss: 0.0510 (0.0561) time: 3.2155 data: 0.0083 max mem: 33369 +Epoch: [17] [ 690/1319] eta: 0:33:23 lr: 2.9762210910308712e-05 loss: 0.0510 (0.0562) time: 3.2410 data: 0.0086 max mem: 33369 +Epoch: [17] [ 700/1319] eta: 0:32:50 lr: 2.9753175478331675e-05 loss: 0.0579 (0.0561) time: 3.1935 data: 0.0083 max mem: 33369 +Epoch: [17] [ 710/1319] eta: 0:32:19 lr: 2.97441397414692e-05 loss: 0.0502 (0.0561) time: 3.1610 data: 0.0084 max mem: 33369 +Epoch: [17] [ 720/1319] eta: 0:31:47 lr: 2.973510369960809e-05 loss: 0.0507 (0.0561) time: 3.1938 data: 0.0083 max mem: 33369 +Epoch: [17] [ 730/1319] eta: 0:31:14 lr: 2.9726067352635072e-05 loss: 0.0536 (0.0563) time: 3.1597 data: 0.0079 max mem: 33369 +Epoch: [17] [ 740/1319] eta: 0:30:43 lr: 2.971703070043676e-05 loss: 0.0532 (0.0563) time: 3.1533 data: 0.0082 max mem: 33369 +Epoch: [17] [ 750/1319] eta: 0:30:11 lr: 2.970799374289972e-05 loss: 0.0495 (0.0563) time: 3.1765 data: 0.0081 max mem: 33369 +Epoch: [17] [ 760/1319] eta: 0:29:39 lr: 2.9698956479910424e-05 loss: 0.0495 (0.0561) time: 3.1619 data: 0.0079 max mem: 33369 +Epoch: [17] [ 770/1319] eta: 0:29:07 lr: 2.9689918911355265e-05 loss: 0.0557 (0.0564) time: 3.1909 data: 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time: 3.1910 data: 0.0078 max mem: 33369 +Epoch: [17] [ 860/1319] eta: 0:24:21 lr: 2.96085670251099e-05 loss: 0.0512 (0.0568) time: 3.1722 data: 0.0082 max mem: 33369 +Epoch: [17] [ 870/1319] eta: 0:23:49 lr: 2.959952639462995e-05 loss: 0.0526 (0.0569) time: 3.1554 data: 0.0080 max mem: 33369 +Epoch: [17] [ 880/1319] eta: 0:23:17 lr: 2.9590485457329127e-05 loss: 0.0691 (0.0570) time: 3.1927 data: 0.0083 max mem: 33369 +Epoch: [17] [ 890/1319] eta: 0:22:45 lr: 2.9581444213092834e-05 loss: 0.0492 (0.0569) time: 3.2273 data: 0.0086 max mem: 33369 +Epoch: [17] [ 900/1319] eta: 0:22:14 lr: 2.957240266180642e-05 loss: 0.0481 (0.0570) time: 3.2077 data: 0.0084 max mem: 33369 +Epoch: [17] [ 910/1319] eta: 0:21:42 lr: 2.956336080335514e-05 loss: 0.0574 (0.0570) time: 3.1823 data: 0.0083 max mem: 33369 +Epoch: [17] [ 920/1319] eta: 0:21:10 lr: 2.955431863762416e-05 loss: 0.0561 (0.0570) time: 3.1583 data: 0.0079 max mem: 33369 +Epoch: [17] [ 930/1319] eta: 0:20:38 lr: 2.9545276164498587e-05 loss: 0.0556 (0.0570) time: 3.1970 data: 0.0075 max mem: 33369 +Epoch: [17] [ 940/1319] eta: 0:20:06 lr: 2.953623338386342e-05 loss: 0.0533 (0.0570) time: 3.1914 data: 0.0078 max mem: 33369 +Epoch: [17] [ 950/1319] eta: 0:19:34 lr: 2.9527190295603586e-05 loss: 0.0513 (0.0570) time: 3.1581 data: 0.0079 max mem: 33369 +Epoch: [17] [ 960/1319] eta: 0:19:02 lr: 2.9518146899603932e-05 loss: 0.0513 (0.0570) time: 3.1857 data: 0.0077 max mem: 33369 +Epoch: [17] [ 970/1319] eta: 0:18:30 lr: 2.9509103195749226e-05 loss: 0.0516 (0.0570) time: 3.1536 data: 0.0076 max mem: 33369 +Epoch: [17] [ 980/1319] eta: 0:17:58 lr: 2.9500059183924145e-05 loss: 0.0518 (0.0571) time: 3.1354 data: 0.0079 max mem: 33369 +Epoch: [17] [ 990/1319] eta: 0:17:27 lr: 2.9491014864013282e-05 loss: 0.0524 (0.0570) time: 3.1578 data: 0.0082 max mem: 33369 +Epoch: [17] [1000/1319] eta: 0:16:55 lr: 2.9481970235901164e-05 loss: 0.0531 (0.0572) time: 3.1923 data: 0.0080 max mem: 33369 +Epoch: [17] [1010/1319] eta: 0:16:23 lr: 2.9472925299472214e-05 loss: 0.0569 (0.0572) time: 3.1969 data: 0.0077 max mem: 33369 +Epoch: [17] [1020/1319] eta: 0:15:51 lr: 2.9463880054610792e-05 loss: 0.0504 (0.0572) time: 3.1820 data: 0.0078 max mem: 33369 +Epoch: [17] [1030/1319] eta: 0:15:19 lr: 2.9454834501201163e-05 loss: 0.0506 (0.0571) time: 3.1859 data: 0.0079 max mem: 33369 +Epoch: [17] [1040/1319] eta: 0:14:48 lr: 2.9445788639127496e-05 loss: 0.0460 (0.0571) time: 3.2000 data: 0.0080 max mem: 33369 +Epoch: [17] [1050/1319] eta: 0:14:16 lr: 2.943674246827392e-05 loss: 0.0532 (0.0571) time: 3.2027 data: 0.0078 max mem: 33369 +Epoch: [17] [1060/1319] eta: 0:13:44 lr: 2.9427695988524433e-05 loss: 0.0526 (0.0571) time: 3.1613 data: 0.0073 max mem: 33369 +Epoch: [17] [1070/1319] eta: 0:13:12 lr: 2.941864919976297e-05 loss: 0.0470 (0.0571) time: 3.1598 data: 0.0075 max mem: 33369 +Epoch: [17] [1080/1319] eta: 0:12:40 lr: 2.9409602101873397e-05 loss: 0.0450 (0.0571) time: 3.1845 data: 0.0079 max mem: 33369 +Epoch: [17] [1090/1319] eta: 0:12:08 lr: 2.9400554694739468e-05 loss: 0.0541 (0.0571) time: 3.1695 data: 0.0079 max mem: 33369 +Epoch: [17] [1100/1319] eta: 0:11:36 lr: 2.9391506978244877e-05 loss: 0.0548 (0.0571) time: 3.1540 data: 0.0080 max mem: 33369 +Epoch: [17] [1110/1319] eta: 0:11:05 lr: 2.9382458952273217e-05 loss: 0.0547 (0.0572) time: 3.1508 data: 0.0079 max mem: 33369 +Epoch: [17] [1120/1319] eta: 0:10:33 lr: 2.937341061670802e-05 loss: 0.0557 (0.0572) time: 3.1841 data: 0.0075 max mem: 33369 +Epoch: [17] [1130/1319] eta: 0:10:01 lr: 2.9364361971432715e-05 loss: 0.0530 (0.0572) time: 3.1690 data: 0.0075 max mem: 33369 +Epoch: [17] [1140/1319] eta: 0:09:29 lr: 2.9355313016330638e-05 loss: 0.0576 (0.0573) time: 3.1283 data: 0.0082 max mem: 33369 +Epoch: [17] [1150/1319] eta: 0:08:57 lr: 2.934626375128508e-05 loss: 0.0511 (0.0572) time: 3.1728 data: 0.0082 max mem: 33369 +Epoch: [17] [1160/1319] eta: 0:08:25 lr: 2.93372141761792e-05 loss: 0.0484 (0.0572) time: 3.1789 data: 0.0077 max mem: 33369 +Epoch: [17] [1170/1319] eta: 0:07:54 lr: 2.9328164290896108e-05 loss: 0.0506 (0.0573) time: 3.1740 data: 0.0074 max mem: 33369 +Epoch: [17] [1180/1319] eta: 0:07:22 lr: 2.9319114095318817e-05 loss: 0.0510 (0.0572) time: 3.1820 data: 0.0072 max mem: 33369 +Epoch: [17] [1190/1319] eta: 0:06:50 lr: 2.9310063589330256e-05 loss: 0.0481 (0.0572) time: 3.1842 data: 0.0075 max mem: 33369 +Epoch: [17] [1200/1319] eta: 0:06:18 lr: 2.9301012772813273e-05 loss: 0.0481 (0.0572) time: 3.1813 data: 0.0081 max mem: 33369 +Epoch: [17] [1210/1319] eta: 0:05:46 lr: 2.9291961645650624e-05 loss: 0.0491 (0.0572) time: 3.1967 data: 0.0079 max mem: 33369 +Epoch: [17] [1220/1319] eta: 0:05:14 lr: 2.9282910207724996e-05 loss: 0.0486 (0.0571) time: 3.1895 data: 0.0076 max mem: 33369 +Epoch: [17] [1230/1319] eta: 0:04:43 lr: 2.9273858458918974e-05 loss: 0.0501 (0.0572) time: 3.1712 data: 0.0079 max mem: 33369 +Epoch: [17] [1240/1319] eta: 0:04:11 lr: 2.9264806399115058e-05 loss: 0.0491 (0.0571) time: 3.1747 data: 0.0083 max mem: 33369 +Epoch: [17] [1250/1319] eta: 0:03:39 lr: 2.925575402819568e-05 loss: 0.0439 (0.0570) time: 3.1731 data: 0.0082 max mem: 33369 +Epoch: [17] [1260/1319] eta: 0:03:07 lr: 2.9246701346043183e-05 loss: 0.0462 (0.0571) time: 3.1589 data: 0.0084 max mem: 33369 +Epoch: [17] [1270/1319] eta: 0:02:35 lr: 2.9237648352539803e-05 loss: 0.0496 (0.0572) time: 3.1713 data: 0.0087 max mem: 33369 +Epoch: [17] [1280/1319] eta: 0:02:04 lr: 2.9228595047567713e-05 loss: 0.0527 (0.0572) time: 3.1949 data: 0.0084 max mem: 33369 +Epoch: [17] [1290/1319] eta: 0:01:32 lr: 2.9219541431009008e-05 loss: 0.0503 (0.0571) time: 3.1681 data: 0.0084 max mem: 33369 +Epoch: [17] [1300/1319] eta: 0:01:00 lr: 2.921048750274567e-05 loss: 0.0475 (0.0571) time: 3.1991 data: 0.0080 max mem: 33369 +Epoch: [17] [1310/1319] eta: 0:00:28 lr: 2.9201433262659623e-05 loss: 0.0542 (0.0571) time: 3.1916 data: 0.0073 max mem: 33369 +Epoch: [17] Total time: 1:09:55 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 2:01:23 time: 2.8306 data: 2.7408 max mem: 33369 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 100/2573] eta: 0:04:21 time: 0.0769 data: 0.0015 max mem: 33369 +Test: [ 200/2573] eta: 0:03:39 time: 0.0790 data: 0.0014 max mem: 33369 +Test: [ 300/2573] eta: 0:03:19 time: 0.0802 data: 0.0016 max mem: 33369 +Test: [ 400/2573] eta: 0:03:05 time: 0.0800 data: 0.0014 max mem: 33369 +Test: [ 500/2573] eta: 0:02:54 time: 0.0797 data: 0.0015 max mem: 33369 +Test: [ 600/2573] eta: 0:02:44 time: 0.0796 data: 0.0015 max mem: 33369 +Test: [ 700/2573] eta: 0:02:35 time: 0.0799 data: 0.0015 max mem: 33369 +Test: [ 800/2573] eta: 0:02:27 time: 0.0835 data: 0.0015 max mem: 33369 +Test: [ 900/2573] eta: 0:02:18 time: 0.0800 data: 0.0015 max mem: 33369 +Test: [1000/2573] eta: 0:02:09 time: 0.0802 data: 0.0015 max mem: 33369 +Test: [1100/2573] eta: 0:02:01 time: 0.0801 data: 0.0015 max mem: 33369 +Test: [1200/2573] eta: 0:01:52 time: 0.0791 data: 0.0014 max mem: 33369 +Test: [1300/2573] eta: 0:01:44 time: 0.0802 data: 0.0014 max mem: 33369 +Test: [1400/2573] eta: 0:01:35 time: 0.0774 data: 0.0014 max mem: 33369 +Test: [1500/2573] eta: 0:01:27 time: 0.0802 data: 0.0015 max mem: 33369 +Test: [1600/2573] eta: 0:01:19 time: 0.0830 data: 0.0014 max mem: 33369 +Test: [1700/2573] eta: 0:01:11 time: 0.0777 data: 0.0014 max mem: 33369 +Test: [1800/2573] eta: 0:01:02 time: 0.0813 data: 0.0014 max mem: 33369 +Test: [1900/2573] eta: 0:00:54 time: 0.0779 data: 0.0015 max mem: 33369 +Test: [2000/2573] eta: 0:00:46 time: 0.0802 data: 0.0014 max mem: 33369 +Test: [2100/2573] eta: 0:00:38 time: 0.0815 data: 0.0014 max mem: 33369 +Test: [2200/2573] eta: 0:00:30 time: 0.0815 data: 0.0015 max mem: 33369 +Test: [2300/2573] eta: 0:00:22 time: 0.0816 data: 0.0015 max mem: 33369 +Test: [2400/2573] eta: 0:00:13 time: 0.0757 data: 0.0014 max mem: 33369 +Test: [2500/2573] eta: 0:00:05 time: 0.0792 data: 0.0014 max mem: 33369 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: Total time: 0:03:28 +Final results: +Mean IoU is 62.09 + + precision@0.5 = 69.61 + precision@0.6 = 63.81 + precision@0.7 = 56.41 + precision@0.8 = 45.10 + precision@0.9 = 21.51 + overall IoU = 60.77 + +Average object IoU 62.09242762564677 +Overall IoU 60.767242431640625 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [18] [ 0/1319] eta: 2:37:56 lr: 2.9193284179876086e-05 loss: 0.0400 (0.0400) time: 7.1846 data: 2.5249 max mem: 33369 +Epoch: [18] [ 10/1319] eta: 1:18:07 lr: 2.9184229347001237e-05 loss: 0.0476 (0.0479) time: 3.5810 data: 0.2374 max mem: 33369 +Epoch: [18] [ 20/1319] eta: 1:13:49 lr: 2.9175174201960736e-05 loss: 0.0478 (0.0501) time: 3.2215 data: 0.0080 max mem: 33369 +Epoch: [18] [ 30/1319] eta: 1:11:34 lr: 2.9166118744636155e-05 loss: 0.0508 (0.0550) time: 3.1941 data: 0.0079 max mem: 33369 +Epoch: [18] [ 40/1319] eta: 1:10:15 lr: 2.9157062974908988e-05 loss: 0.0493 (0.0575) time: 3.1756 data: 0.0082 max mem: 33369 +Epoch: [18] [ 50/1319] eta: 1:09:07 lr: 2.9148006892660646e-05 loss: 0.0472 (0.0561) time: 3.1706 data: 0.0084 max mem: 33369 +Epoch: [18] [ 60/1319] eta: 1:08:15 lr: 2.9138950497772444e-05 loss: 0.0494 (0.0562) time: 3.1650 data: 0.0084 max mem: 33369 +Epoch: [18] [ 70/1319] eta: 1:07:36 lr: 2.9129893790125616e-05 loss: 0.0451 (0.0548) time: 3.1941 data: 0.0081 max mem: 33369 +Epoch: [18] [ 80/1319] eta: 1:07:00 lr: 2.9120836769601318e-05 loss: 0.0435 (0.0534) time: 3.2215 data: 0.0081 max mem: 33369 +Epoch: [18] [ 90/1319] eta: 1:06:19 lr: 2.9111779436080605e-05 loss: 0.0437 (0.0535) time: 3.2043 data: 0.0078 max mem: 33369 +Epoch: [18] [ 100/1319] eta: 1:05:41 lr: 2.910272178944446e-05 loss: 0.0474 (0.0533) time: 3.1875 data: 0.0076 max mem: 33369 +Epoch: [18] [ 110/1319] eta: 1:05:04 lr: 2.9093663829573763e-05 loss: 0.0543 (0.0542) time: 3.1924 data: 0.0078 max mem: 33369 +Epoch: [18] [ 120/1319] eta: 1:04:21 lr: 2.9084605556349322e-05 loss: 0.0546 (0.0542) time: 3.1550 data: 0.0085 max mem: 33369 +Epoch: [18] [ 130/1319] eta: 1:03:49 lr: 2.9075546969651845e-05 loss: 0.0534 (0.0547) time: 3.1691 data: 0.0083 max mem: 33369 +Epoch: [18] [ 140/1319] eta: 1:03:12 lr: 2.906648806936197e-05 loss: 0.0581 (0.0551) time: 3.1907 data: 0.0075 max mem: 33369 +Epoch: [18] [ 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time: 1:09:52 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 2:14:20 time: 3.1328 data: 2.9985 max mem: 33369 +Test: [ 100/2573] eta: 0:04:26 time: 0.0774 data: 0.0015 max mem: 33369 +Test: [ 200/2573] eta: 0:03:42 time: 0.0787 data: 0.0015 max mem: 33369 +Test: [ 300/2573] eta: 0:03:20 time: 0.0799 data: 0.0014 max mem: 33369 +Test: [ 400/2573] eta: 0:03:06 time: 0.0799 data: 0.0015 max mem: 33369 +Test: [ 500/2573] eta: 0:02:54 time: 0.0789 data: 0.0015 max mem: 33369 +Test: [ 600/2573] eta: 0:02:44 time: 0.0793 data: 0.0015 max mem: 33369 +Test: [ 700/2573] eta: 0:02:35 time: 0.0783 data: 0.0014 max mem: 33369 +Test: [ 800/2573] eta: 0:02:26 time: 0.0826 data: 0.0016 max mem: 33369 +Test: [ 900/2573] eta: 0:02:17 time: 0.0790 data: 0.0015 max mem: 33369 +Test: [1000/2573] eta: 0:02:08 time: 0.0795 data: 0.0014 max mem: 33369 +Test: [1100/2573] eta: 0:02:00 time: 0.0799 data: 0.0014 max mem: 33369 +Test: [1200/2573] eta: 0:01:52 time: 0.0799 data: 0.0014 max mem: 33369 +Test: [1300/2573] eta: 0:01:43 time: 0.0785 data: 0.0013 max mem: 33369 +Test: [1400/2573] eta: 0:01:35 time: 0.0785 data: 0.0015 max mem: 33369 +Test: [1500/2573] eta: 0:01:27 time: 0.0791 data: 0.0014 max mem: 33369 +Test: [1600/2573] eta: 0:01:18 time: 0.0826 data: 0.0015 max mem: 33369 +Test: [1700/2573] eta: 0:01:10 time: 0.0780 data: 0.0015 max mem: 33369 +Test: [1800/2573] eta: 0:01:02 time: 0.0813 data: 0.0015 max mem: 33369 +Test: [1900/2573] eta: 0:00:54 time: 0.0799 data: 0.0016 max mem: 33369 +Test: [2000/2573] eta: 0:00:46 time: 0.0813 data: 0.0015 max mem: 33369 +Test: [2100/2573] eta: 0:00:38 time: 0.0808 data: 0.0014 max mem: 33369 +Test: [2200/2573] eta: 0:00:30 time: 0.0820 data: 0.0016 max mem: 33369 +Test: [2300/2573] eta: 0:00:22 time: 0.0814 data: 0.0015 max mem: 33369 +Test: [2400/2573] eta: 0:00:13 time: 0.0762 data: 0.0016 max mem: 33369 +Test: [2500/2573] eta: 0:00:05 time: 0.0788 data: 0.0014 max mem: 33369 +Test: Total time: 0:03:27 +Final results: +Mean IoU is 62.33 + + precision@0.5 = 70.18 + precision@0.6 = 64.40 + precision@0.7 = 57.21 + precision@0.8 = 46.00 + precision@0.9 = 22.06 + overall IoU = 60.64 + +Average object IoU 62.32969971476745 +Overall IoU 60.637229919433594 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [19] [ 0/1319] eta: 3:07:34 lr: 2.7996211513802005e-05 loss: 0.0409 (0.0409) time: 8.5329 data: 2.3465 max mem: 33369 +Epoch: [19] [ 10/1319] eta: 1:19:56 lr: 2.7987114450740563e-05 loss: 0.0453 (0.0481) time: 3.6642 data: 0.2207 max mem: 33369 +Epoch: [19] [ 20/1319] eta: 1:14:20 lr: 2.7978017059117013e-05 loss: 0.0453 (0.0501) time: 3.1789 data: 0.0079 max mem: 33369 +Epoch: [19] [ 30/1319] eta: 1:11:36 lr: 2.7968919338800786e-05 loss: 0.0447 (0.0519) time: 3.1517 data: 0.0077 max mem: 33369 +Epoch: [19] [ 40/1319] eta: 1:10:14 lr: 2.7959821289661182e-05 loss: 0.0447 (0.0499) time: 3.1501 data: 0.0079 max mem: 33369 +Epoch: [19] [ 50/1319] eta: 1:09:18 lr: 2.795072291156743e-05 loss: 0.0443 (0.0496) time: 3.1884 data: 0.0084 max mem: 33369 +Epoch: [19] [ 60/1319] eta: 1:08:22 lr: 2.7941624204388656e-05 loss: 0.0463 (0.0497) time: 3.1833 data: 0.0083 max mem: 33369 +Epoch: [19] [ 70/1319] eta: 1:07:34 lr: 2.7932525167993873e-05 loss: 0.0496 (0.0487) time: 3.1673 data: 0.0078 max mem: 33369 +Epoch: [19] [ 80/1319] eta: 1:06:40 lr: 2.7923425802252002e-05 loss: 0.0381 (0.0479) time: 3.1392 data: 0.0082 max mem: 33369 +Epoch: [19] [ 90/1319] eta: 1:05:59 lr: 2.791432610703186e-05 loss: 0.0513 (0.0499) time: 3.1345 data: 0.0084 max mem: 33369 +Epoch: [19] [ 100/1319] eta: 1:05:17 lr: 2.790522608220219e-05 loss: 0.0580 (0.0514) time: 3.1502 data: 0.0082 max mem: 33369 +Epoch: [19] [ 110/1319] eta: 1:04:46 lr: 2.789612572763159e-05 loss: 0.0475 (0.0527) time: 3.1832 data: 0.0084 max mem: 33369 +Epoch: [19] [ 120/1319] eta: 1:04:13 lr: 2.7887025043188598e-05 loss: 0.0449 (0.0517) time: 3.2156 data: 0.0084 max mem: 33369 +Epoch: [19] [ 130/1319] eta: 1:03:39 lr: 2.7877924028741625e-05 loss: 0.0418 (0.0512) time: 3.2010 data: 0.0081 max mem: 33369 +Epoch: [19] [ 140/1319] eta: 1:03:03 lr: 2.7868822684159008e-05 loss: 0.0424 (0.0506) time: 3.1822 data: 0.0079 max mem: 33369 +Epoch: [19] [ 150/1319] eta: 1:02:32 lr: 2.7859721009308947e-05 loss: 0.0363 (0.0499) time: 3.1933 data: 0.0077 max mem: 33369 +Epoch: [19] [ 160/1319] eta: 1:01:56 lr: 2.7850619004059574e-05 loss: 0.0416 (0.0506) time: 3.1882 data: 0.0076 max mem: 33369 +Epoch: [19] [ 170/1319] eta: 1:01:21 lr: 2.7841516668278917e-05 loss: 0.0546 (0.0508) time: 3.1576 data: 0.0076 max mem: 33369 +Epoch: [19] [ 180/1319] eta: 1:00:48 lr: 2.7832414001834883e-05 loss: 0.0493 (0.0505) time: 3.1724 data: 0.0079 max mem: 33369 +Epoch: [19] [ 190/1319] eta: 1:00:13 lr: 2.782331100459529e-05 loss: 0.0477 (0.0503) time: 3.1717 data: 0.0079 max mem: 33369 +Epoch: [19] [ 200/1319] eta: 0:59:39 lr: 2.781420767642787e-05 loss: 0.0477 (0.0504) time: 3.1635 data: 0.0080 max mem: 33369 +Epoch: [19] [ 210/1319] eta: 0:59:04 lr: 2.7805104017200224e-05 loss: 0.0446 (0.0502) time: 3.1563 data: 0.0081 max mem: 33369 +Epoch: [19] [ 220/1319] eta: 0:58:30 lr: 2.779600002677987e-05 loss: 0.0446 (0.0501) time: 3.1511 data: 0.0079 max mem: 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2.7577404552635017e-05 loss: 0.0497 (0.0511) time: 3.1859 data: 0.0077 max mem: 33369 +Epoch: [19] [ 470/1319] eta: 0:45:10 lr: 2.7568292239041493e-05 loss: 0.0432 (0.0510) time: 3.1726 data: 0.0081 max mem: 33369 +Epoch: [19] [ 480/1319] eta: 0:44:37 lr: 2.7559179590774802e-05 loss: 0.0414 (0.0509) time: 3.1745 data: 0.0085 max mem: 33369 +Epoch: [19] [ 490/1319] eta: 0:44:05 lr: 2.755006660769968e-05 loss: 0.0464 (0.0510) time: 3.1777 data: 0.0084 max mem: 33369 +Epoch: [19] [ 500/1319] eta: 0:43:33 lr: 2.754095328968076e-05 loss: 0.0517 (0.0513) time: 3.1893 data: 0.0081 max mem: 33369 +Epoch: [19] [ 510/1319] eta: 0:43:02 lr: 2.753183963658258e-05 loss: 0.0463 (0.0512) time: 3.1971 data: 0.0077 max mem: 33369 +Epoch: [19] [ 520/1319] eta: 0:42:29 lr: 2.7522725648269566e-05 loss: 0.0442 (0.0512) time: 3.1662 data: 0.0082 max mem: 33369 +Epoch: [19] [ 530/1319] eta: 0:41:56 lr: 2.7513611324606038e-05 loss: 0.0444 (0.0512) time: 3.1441 data: 0.0086 max mem: 33369 +Epoch: [19] [ 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data: 0.0078 max mem: 33369 +Epoch: [19] [ 700/1319] eta: 0:32:51 lr: 2.735861638171675e-05 loss: 0.0421 (0.0514) time: 3.1719 data: 0.0076 max mem: 33369 +Epoch: [19] [ 710/1319] eta: 0:32:20 lr: 2.7349495998423098e-05 loss: 0.0474 (0.0514) time: 3.1806 data: 0.0077 max mem: 33369 +Epoch: [19] [ 720/1319] eta: 0:31:47 lr: 2.7340375277181003e-05 loss: 0.0466 (0.0513) time: 3.1738 data: 0.0078 max mem: 33369 +Epoch: [19] [ 730/1319] eta: 0:31:16 lr: 2.733125421785267e-05 loss: 0.0476 (0.0514) time: 3.1802 data: 0.0089 max mem: 33369 +Epoch: [19] [ 740/1319] eta: 0:30:44 lr: 2.7322132820300196e-05 loss: 0.0513 (0.0515) time: 3.1933 data: 0.0086 max mem: 33369 +Epoch: [19] [ 750/1319] eta: 0:30:12 lr: 2.731301108438557e-05 loss: 0.0487 (0.0514) time: 3.1693 data: 0.0077 max mem: 33369 +Epoch: [19] [ 760/1319] eta: 0:29:40 lr: 2.7303889009970667e-05 loss: 0.0477 (0.0514) time: 3.1955 data: 0.0080 max mem: 33369 +Epoch: [19] [ 770/1319] eta: 0:29:08 lr: 2.7294766596917266e-05 loss: 0.0503 (0.0514) time: 3.1776 data: 0.0082 max mem: 33369 +Epoch: [19] [ 780/1319] eta: 0:28:36 lr: 2.7285643845087027e-05 loss: 0.0528 (0.0515) time: 3.1615 data: 0.0083 max mem: 33369 +Epoch: [19] [ 790/1319] eta: 0:28:04 lr: 2.7276520754341512e-05 loss: 0.0508 (0.0515) time: 3.1743 data: 0.0086 max mem: 33369 +Epoch: [19] [ 800/1319] eta: 0:27:32 lr: 2.726739732454216e-05 loss: 0.0419 (0.0515) time: 3.1673 data: 0.0083 max mem: 33369 +Epoch: [19] [ 810/1319] eta: 0:27:00 lr: 2.7258273555550322e-05 loss: 0.0419 (0.0514) time: 3.1819 data: 0.0079 max mem: 33369 +Epoch: [19] [ 820/1319] eta: 0:26:29 lr: 2.7249149447227223e-05 loss: 0.0479 (0.0514) time: 3.2032 data: 0.0084 max mem: 33369 +Epoch: [19] [ 830/1319] eta: 0:25:57 lr: 2.7240024999433987e-05 loss: 0.0494 (0.0515) time: 3.2047 data: 0.0084 max mem: 33369 +Epoch: [19] [ 840/1319] eta: 0:25:25 lr: 2.723090021203163e-05 loss: 0.0492 (0.0514) time: 3.1539 data: 0.0082 max mem: 33369 +Epoch: [19] [ 850/1319] eta: 0:24:53 lr: 2.7221775084881062e-05 loss: 0.0399 (0.0514) time: 3.1505 data: 0.0083 max mem: 33369 +Epoch: [19] [ 860/1319] eta: 0:24:21 lr: 2.7212649617843082e-05 loss: 0.0424 (0.0515) time: 3.1721 data: 0.0083 max mem: 33369 +Epoch: [19] [ 870/1319] eta: 0:23:49 lr: 2.7203523810778376e-05 loss: 0.0502 (0.0515) time: 3.1530 data: 0.0082 max mem: 33369 +Epoch: [19] [ 880/1319] eta: 0:23:17 lr: 2.7194397663547522e-05 loss: 0.0495 (0.0517) time: 3.1995 data: 0.0079 max mem: 33369 +Epoch: [19] [ 890/1319] eta: 0:22:45 lr: 2.7185271176010996e-05 loss: 0.0485 (0.0515) time: 3.1960 data: 0.0078 max mem: 33369 +Epoch: [19] [ 900/1319] eta: 0:22:14 lr: 2.7176144348029154e-05 loss: 0.0379 (0.0514) time: 3.1856 data: 0.0080 max mem: 33369 +Epoch: [19] [ 910/1319] eta: 0:21:42 lr: 2.7167017179462245e-05 loss: 0.0409 (0.0514) time: 3.1749 data: 0.0082 max mem: 33369 +Epoch: [19] [ 920/1319] eta: 0:21:10 lr: 2.7157889670170428e-05 loss: 0.0444 (0.0513) time: 3.1689 data: 0.0083 max mem: 33369 +Epoch: [19] [ 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33369 +Epoch: [19] [1010/1319] eta: 0:16:23 lr: 2.7075726730791712e-05 loss: 0.0475 (0.0515) time: 3.1651 data: 0.0077 max mem: 33369 +Epoch: [19] [1020/1319] eta: 0:15:51 lr: 2.706659580653433e-05 loss: 0.0475 (0.0516) time: 3.1835 data: 0.0077 max mem: 33369 +Epoch: [19] [1030/1319] eta: 0:15:19 lr: 2.7057464540006328e-05 loss: 0.0541 (0.0517) time: 3.1970 data: 0.0077 max mem: 33369 +Epoch: [19] [1040/1319] eta: 0:14:47 lr: 2.7048332931066517e-05 loss: 0.0513 (0.0516) time: 3.1656 data: 0.0084 max mem: 33369 +Epoch: [19] [1050/1319] eta: 0:14:15 lr: 2.7039200979573614e-05 loss: 0.0480 (0.0517) time: 3.1565 data: 0.0083 max mem: 33369 +Epoch: [19] [1060/1319] eta: 0:13:43 lr: 2.7030068685386206e-05 loss: 0.0431 (0.0516) time: 3.1471 data: 0.0079 max mem: 33369 +Epoch: [19] [1070/1319] eta: 0:13:12 lr: 2.7020936048362782e-05 loss: 0.0431 (0.0518) time: 3.1175 data: 0.0078 max mem: 33369 +Epoch: [19] [1080/1319] eta: 0:12:40 lr: 2.7011803068361714e-05 loss: 0.0485 (0.0518) time: 3.1673 data: 0.0076 max mem: 33369 +Epoch: [19] [1090/1319] eta: 0:12:08 lr: 2.700266974524126e-05 loss: 0.0485 (0.0518) time: 3.1968 data: 0.0074 max mem: 33369 +Epoch: [19] [1100/1319] eta: 0:11:36 lr: 2.699353607885957e-05 loss: 0.0449 (0.0517) time: 3.1913 data: 0.0078 max mem: 33369 +Epoch: [19] [1110/1319] eta: 0:11:04 lr: 2.6984402069074687e-05 loss: 0.0469 (0.0518) time: 3.1849 data: 0.0080 max mem: 33369 +Epoch: [19] [1120/1319] eta: 0:10:33 lr: 2.6975267715744523e-05 loss: 0.0473 (0.0518) time: 3.1897 data: 0.0080 max mem: 33369 +Epoch: [19] [1130/1319] eta: 0:10:01 lr: 2.6966133018726902e-05 loss: 0.0452 (0.0519) time: 3.1928 data: 0.0082 max mem: 33369 +Epoch: [19] [1140/1319] eta: 0:09:29 lr: 2.6956997977879505e-05 loss: 0.0540 (0.0521) time: 3.1719 data: 0.0078 max mem: 33369 +Epoch: [19] [1150/1319] eta: 0:08:57 lr: 2.6947862593059943e-05 loss: 0.0537 (0.0522) time: 3.1783 data: 0.0076 max mem: 33369 +Epoch: [19] [1160/1319] eta: 0:08:25 lr: 2.6938726864125667e-05 loss: 0.0464 (0.0522) time: 3.1543 data: 0.0077 max mem: 33369 +Epoch: [19] [1170/1319] eta: 0:07:53 lr: 2.6929590790934063e-05 loss: 0.0470 (0.0522) time: 3.1418 data: 0.0080 max mem: 33369 +Epoch: [19] [1180/1319] eta: 0:07:22 lr: 2.6920454373342357e-05 loss: 0.0484 (0.0522) time: 3.1770 data: 0.0084 max mem: 33369 +Epoch: [19] [1190/1319] eta: 0:06:50 lr: 2.6911317611207703e-05 loss: 0.0484 (0.0523) time: 3.1735 data: 0.0081 max mem: 33369 +Epoch: [19] [1200/1319] eta: 0:06:18 lr: 2.6902180504387114e-05 loss: 0.0510 (0.0523) time: 3.1811 data: 0.0076 max mem: 33369 +Epoch: [19] [1210/1319] eta: 0:05:46 lr: 2.689304305273751e-05 loss: 0.0463 (0.0523) time: 3.1964 data: 0.0074 max mem: 33369 +Epoch: [19] [1220/1319] eta: 0:05:14 lr: 2.6883905256115667e-05 loss: 0.0455 (0.0524) time: 3.2067 data: 0.0074 max mem: 33369 +Epoch: [19] [1230/1319] eta: 0:04:43 lr: 2.687476711437828e-05 loss: 0.0539 (0.0524) time: 3.2069 data: 0.0078 max mem: 33369 +Epoch: [19] [1240/1319] eta: 0:04:11 lr: 2.6865628627381928e-05 loss: 0.0539 (0.0524) time: 3.1666 data: 0.0078 max mem: 33369 +Epoch: [19] [1250/1319] eta: 0:03:39 lr: 2.6856489794983043e-05 loss: 0.0459 (0.0524) time: 3.1765 data: 0.0076 max mem: 33369 +Epoch: [19] [1260/1319] eta: 0:03:07 lr: 2.6847350617037976e-05 loss: 0.0461 (0.0524) time: 3.1855 data: 0.0075 max mem: 33369 +Epoch: [19] [1270/1319] eta: 0:02:35 lr: 2.683821109340296e-05 loss: 0.0463 (0.0524) time: 3.1537 data: 0.0074 max mem: 33369 +Epoch: [19] [1280/1319] eta: 0:02:04 lr: 2.68290712239341e-05 loss: 0.0463 (0.0523) time: 3.1861 data: 0.0073 max mem: 33369 +Epoch: [19] [1290/1319] eta: 0:01:32 lr: 2.681993100848739e-05 loss: 0.0516 (0.0524) time: 3.2402 data: 0.0073 max mem: 33369 +Epoch: [19] [1300/1319] eta: 0:01:00 lr: 2.6810790446918727e-05 loss: 0.0516 (0.0524) time: 3.2167 data: 0.0076 max mem: 33369 +Epoch: [19] [1310/1319] eta: 0:00:28 lr: 2.680164953908387e-05 loss: 0.0515 (0.0525) time: 3.1717 data: 0.0076 max mem: 33369 +Epoch: [19] Total time: 1:09:57 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 2:30:33 time: 3.5107 data: 3.3679 max mem: 33369 +Test: [ 100/2573] eta: 0:04:35 time: 0.0780 data: 0.0016 max mem: 33369 +Test: [ 200/2573] eta: 0:03:47 time: 0.0787 data: 0.0015 max mem: 33369 +Test: [ 300/2573] eta: 0:03:23 time: 0.0796 data: 0.0014 max mem: 33369 +Test: [ 400/2573] eta: 0:03:08 time: 0.0802 data: 0.0014 max mem: 33369 +Test: [ 500/2573] eta: 0:02:56 time: 0.0797 data: 0.0015 max mem: 33369 +Test: [ 600/2573] eta: 0:02:46 time: 0.0796 data: 0.0014 max mem: 33369 +Test: [ 700/2573] eta: 0:02:37 time: 0.0791 data: 0.0015 max mem: 33369 +Test: [ 800/2573] eta: 0:02:28 time: 0.0836 data: 0.0014 max mem: 33369 +Test: [ 900/2573] eta: 0:02:19 time: 0.0802 data: 0.0016 max mem: 33369 +Test: [1000/2573] eta: 0:02:10 time: 0.0796 data: 0.0015 max mem: 33369 +Test: [1100/2573] eta: 0:02:01 time: 0.0797 data: 0.0015 max mem: 33369 +Test: [1200/2573] eta: 0:01:53 time: 0.0797 data: 0.0015 max mem: 33369 +Test: [1300/2573] eta: 0:01:44 time: 0.0804 data: 0.0015 max mem: 33369 +Test: [1400/2573] eta: 0:01:36 time: 0.0776 data: 0.0014 max mem: 33369 +Test: [1500/2573] eta: 0:01:27 time: 0.0794 data: 0.0016 max mem: 33369 +Test: [1600/2573] eta: 0:01:19 time: 0.0828 data: 0.0015 max mem: 33369 +Test: [1700/2573] eta: 0:01:11 time: 0.0781 data: 0.0014 max mem: 33369 +Test: [1800/2573] eta: 0:01:03 time: 0.0808 data: 0.0015 max mem: 33369 +Test: [1900/2573] eta: 0:00:54 time: 0.0777 data: 0.0014 max mem: 33369 +Test: [2000/2573] eta: 0:00:46 time: 0.0803 data: 0.0015 max mem: 33369 +Test: [2100/2573] eta: 0:00:38 time: 0.0822 data: 0.0014 max mem: 33369 +Test: [2200/2573] eta: 0:00:30 time: 0.0820 data: 0.0015 max mem: 33369 +Test: [2300/2573] eta: 0:00:22 time: 0.0816 data: 0.0014 max mem: 33369 +Test: [2400/2573] eta: 0:00:14 time: 0.0776 data: 0.0015 max mem: 33369 +Test: [2500/2573] eta: 0:00:05 time: 0.0797 data: 0.0014 max mem: 33369 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: Total time: 0:03:28 +Final results: +Mean IoU is 62.52 + + precision@0.5 = 69.87 + precision@0.6 = 64.30 + precision@0.7 = 57.35 + precision@0.8 = 45.94 + precision@0.9 = 22.28 + overall IoU = 60.38 + +Average object IoU 62.523007232725135 +Overall IoU 60.38170623779297 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [20] [ 0/1319] eta: 2:52:10 lr: 2.6793422425855603e-05 loss: 0.0854 (0.0854) time: 7.8324 data: 2.4662 max mem: 33369 +Epoch: [20] [ 10/1319] eta: 1:18:18 lr: 2.678428085971722e-05 loss: 0.0414 (0.0461) time: 3.5895 data: 0.2308 max mem: 33369 +Epoch: [20] [ 20/1319] eta: 1:13:52 lr: 2.6775138946893718e-05 loss: 0.0414 (0.0463) time: 3.1916 data: 0.0073 max mem: 33369 +Epoch: [20] [ 30/1319] eta: 1:11:29 lr: 2.6765996687240426e-05 loss: 0.0433 (0.0481) time: 3.1835 data: 0.0075 max mem: 33369 +Epoch: [20] [ 40/1319] eta: 1:10:15 lr: 2.675685408061254e-05 loss: 0.0428 (0.0468) time: 3.1730 data: 0.0079 max mem: 33369 +Epoch: [20] [ 50/1319] eta: 1:09:11 lr: 2.6747711126865168e-05 loss: 0.0413 (0.0472) time: 3.1842 data: 0.0080 max mem: 33369 +Epoch: [20] [ 60/1319] eta: 1:08:24 lr: 2.6738567825853273e-05 loss: 0.0446 (0.0474) time: 3.1870 data: 0.0081 max mem: 33369 +Epoch: [20] [ 70/1319] eta: 1:07:27 lr: 2.6729424177431713e-05 loss: 0.0453 (0.0480) time: 3.1624 data: 0.0082 max mem: 33369 +Epoch: [20] [ 80/1319] eta: 1:06:42 lr: 2.6720280181455227e-05 loss: 0.0483 (0.0486) time: 3.1399 data: 0.0081 max mem: 33369 +Epoch: [20] [ 90/1319] eta: 1:05:54 lr: 2.671113583777845e-05 loss: 0.0451 (0.0482) time: 3.1358 data: 0.0081 max mem: 33369 +Epoch: [20] [ 100/1319] eta: 1:05:17 lr: 2.670199114625589e-05 loss: 0.0469 (0.0485) time: 3.1475 data: 0.0083 max mem: 33369 +Epoch: [20] [ 110/1319] eta: 1:04:36 lr: 2.6692846106741932e-05 loss: 0.0396 (0.0477) time: 3.1568 data: 0.0085 max mem: 33369 +Epoch: [20] [ 120/1319] eta: 1:04:03 lr: 2.668370071909087e-05 loss: 0.0395 (0.0478) time: 3.1630 data: 0.0084 max mem: 33369 +Epoch: [20] [ 130/1319] eta: 1:03:31 lr: 2.6674554983156852e-05 loss: 0.0459 (0.0483) time: 3.1995 data: 0.0085 max mem: 33369 +Epoch: [20] [ 140/1319] eta: 1:02:51 lr: 2.666540889879393e-05 loss: 0.0503 (0.0487) time: 3.1611 data: 0.0085 max mem: 33369 +Epoch: [20] [ 150/1319] eta: 1:02:16 lr: 2.6656262465856026e-05 loss: 0.0497 (0.0488) time: 3.1328 data: 0.0082 max mem: 33369 +Epoch: [20] [ 160/1319] eta: 1:01:43 lr: 2.6647115684196954e-05 loss: 0.0497 (0.0496) time: 3.1712 data: 0.0079 max mem: 33369 +Epoch: [20] [ 170/1319] eta: 1:01:10 lr: 2.663796855367041e-05 loss: 0.0469 (0.0494) time: 3.1846 data: 0.0078 max mem: 33369 +Epoch: [20] [ 180/1319] eta: 1:00:39 lr: 2.662882107412996e-05 loss: 0.0426 (0.0494) time: 3.1937 data: 0.0082 max mem: 33369 +Epoch: [20] [ 190/1319] eta: 1:00:06 lr: 2.661967324542908e-05 loss: 0.0414 (0.0496) time: 3.1942 data: 0.0084 max mem: 33369 +Epoch: [20] [ 200/1319] eta: 0:59:32 lr: 2.6610525067421092e-05 loss: 0.0390 (0.0490) time: 3.1628 data: 0.0079 max mem: 33369 +Epoch: [20] [ 210/1319] eta: 0:59:01 lr: 2.6601376539959238e-05 loss: 0.0450 (0.0500) time: 3.1785 data: 0.0078 max mem: 33369 +Epoch: [20] [ 220/1319] eta: 0:58:28 lr: 2.6592227662896617e-05 loss: 0.0519 (0.0502) time: 3.1948 data: 0.0079 max mem: 33369 +Epoch: [20] [ 230/1319] eta: 0:57:55 lr: 2.658307843608621e-05 loss: 0.0500 (0.0502) time: 3.1771 data: 0.0081 max mem: 33369 +Epoch: [20] [ 240/1319] eta: 0:57:22 lr: 2.65739288593809e-05 loss: 0.0424 (0.0506) time: 3.1640 data: 0.0082 max mem: 33369 +Epoch: [20] [ 250/1319] eta: 0:56:49 lr: 2.6564778932633426e-05 loss: 0.0410 (0.0502) time: 3.1678 data: 0.0079 max mem: 33369 +Epoch: [20] [ 260/1319] eta: 0:56:17 lr: 2.655562865569643e-05 loss: 0.0378 (0.0500) time: 3.1754 data: 0.0080 max mem: 33369 +Epoch: [20] [ 270/1319] eta: 0:55:43 lr: 2.654647802842242e-05 loss: 0.0477 (0.0501) time: 3.1539 data: 0.0084 max mem: 33369 +Epoch: [20] [ 280/1319] eta: 0:55:12 lr: 2.6537327050663813e-05 loss: 0.0498 (0.0501) time: 3.1756 data: 0.0079 max mem: 33369 +Epoch: [20] [ 290/1319] eta: 0:54:41 lr: 2.6528175722272857e-05 loss: 0.0535 (0.0502) time: 3.2169 data: 0.0074 max mem: 33369 +Epoch: [20] [ 300/1319] eta: 0:54:08 lr: 2.6519024043101733e-05 loss: 0.0537 (0.0504) time: 3.1788 data: 0.0080 max mem: 33369 +Epoch: [20] [ 310/1319] eta: 0:53:34 lr: 2.6509872013002462e-05 loss: 0.0497 (0.0503) time: 3.1360 data: 0.0084 max mem: 33369 +Epoch: [20] [ 320/1319] eta: 0:53:03 lr: 2.6500719631826982e-05 loss: 0.0447 (0.0501) time: 3.1710 data: 0.0082 max mem: 33369 +Epoch: [20] [ 330/1319] eta: 0:52:29 lr: 2.649156689942709e-05 loss: 0.0437 (0.0502) time: 3.1607 data: 0.0079 max mem: 33369 +Epoch: [20] [ 340/1319] eta: 0:51:58 lr: 2.648241381565446e-05 loss: 0.0437 (0.0500) time: 3.1634 data: 0.0080 max mem: 33369 +Epoch: [20] [ 350/1319] eta: 0:51:24 lr: 2.6473260380360663e-05 loss: 0.0465 (0.0502) time: 3.1738 data: 0.0084 max mem: 33369 +Epoch: [20] [ 360/1319] eta: 0:50:53 lr: 2.6464106593397137e-05 loss: 0.0465 (0.0500) time: 3.1596 data: 0.0082 max mem: 33369 +Epoch: [20] [ 370/1319] eta: 0:50:20 lr: 2.6454952454615202e-05 loss: 0.0408 (0.0500) time: 3.1619 data: 0.0078 max mem: 33369 +Epoch: [20] [ 380/1319] eta: 0:49:48 lr: 2.6445797963866064e-05 loss: 0.0402 (0.0497) time: 3.1586 data: 0.0076 max mem: 33369 +Epoch: [20] [ 390/1319] eta: 0:49:15 lr: 2.643664312100081e-05 loss: 0.0393 (0.0497) time: 3.1524 data: 0.0081 max mem: 33369 +Epoch: [20] [ 400/1319] eta: 0:48:43 lr: 2.6427487925870388e-05 loss: 0.0393 (0.0496) time: 3.1537 data: 0.0085 max mem: 33369 +Epoch: [20] [ 410/1319] eta: 0:48:11 lr: 2.641833237832565e-05 loss: 0.0368 (0.0495) time: 3.1760 data: 0.0080 max mem: 33369 +Epoch: [20] [ 420/1319] eta: 0:47:39 lr: 2.6409176478217318e-05 loss: 0.0450 (0.0495) time: 3.1670 data: 0.0078 max mem: 33369 +Epoch: [20] [ 430/1319] eta: 0:47:07 lr: 2.640002022539598e-05 loss: 0.0450 (0.0495) time: 3.1813 data: 0.0079 max mem: 33369 +Epoch: [20] [ 440/1319] eta: 0:46:35 lr: 2.6390863619712137e-05 loss: 0.0441 (0.0495) time: 3.1792 data: 0.0081 max mem: 33369 +Epoch: [20] [ 450/1319] eta: 0:46:03 lr: 2.6381706661016125e-05 loss: 0.0441 (0.0494) time: 3.1610 data: 0.0079 max mem: 33369 +Epoch: [20] [ 460/1319] eta: 0:45:31 lr: 2.637254934915819e-05 loss: 0.0453 (0.0493) time: 3.1631 data: 0.0080 max mem: 33369 +Epoch: [20] [ 470/1319] eta: 0:44:59 lr: 2.6363391683988447e-05 loss: 0.0437 (0.0492) time: 3.1741 data: 0.0083 max mem: 33369 +Epoch: [20] [ 480/1319] eta: 0:44:28 lr: 2.6354233665356892e-05 loss: 0.0395 (0.0492) time: 3.1926 data: 0.0081 max mem: 33369 +Epoch: [20] [ 490/1319] eta: 0:43:56 lr: 2.6345075293113398e-05 loss: 0.0386 (0.0491) time: 3.1977 data: 0.0079 max mem: 33369 +Epoch: [20] [ 500/1319] eta: 0:43:24 lr: 2.633591656710771e-05 loss: 0.0337 (0.0490) time: 3.1913 data: 0.0079 max mem: 33369 +Epoch: [20] [ 510/1319] eta: 0:42:53 lr: 2.6326757487189457e-05 loss: 0.0371 (0.0490) time: 3.1883 data: 0.0076 max mem: 33369 +Epoch: [20] [ 520/1319] eta: 0:42:21 lr: 2.6317598053208148e-05 loss: 0.0393 (0.0489) time: 3.1927 data: 0.0076 max mem: 33369 +Epoch: [20] [ 530/1319] eta: 0:41:49 lr: 2.6308438265013168e-05 loss: 0.0393 (0.0489) time: 3.1911 data: 0.0080 max mem: 33369 +Epoch: [20] [ 540/1319] eta: 0:41:18 lr: 2.6299278122453785e-05 loss: 0.0378 (0.0488) time: 3.2160 data: 0.0082 max mem: 33369 +Epoch: [20] [ 550/1319] eta: 0:40:46 lr: 2.629011762537913e-05 loss: 0.0405 (0.0487) time: 3.1877 data: 0.0080 max mem: 33369 +Epoch: [20] [ 560/1319] eta: 0:40:15 lr: 2.628095677363822e-05 loss: 0.0398 (0.0486) time: 3.1808 data: 0.0085 max mem: 33369 +Epoch: [20] [ 570/1319] eta: 0:39:43 lr: 2.627179556707995e-05 loss: 0.0378 (0.0485) time: 3.2191 data: 0.0088 max mem: 33369 +Epoch: [20] [ 580/1319] eta: 0:39:11 lr: 2.6262634005553095e-05 loss: 0.0380 (0.0484) time: 3.1960 data: 0.0081 max mem: 33369 +Epoch: [20] [ 590/1319] eta: 0:38:39 lr: 2.6253472088906295e-05 loss: 0.0386 (0.0483) time: 3.1714 data: 0.0083 max mem: 33369 +Epoch: [20] [ 600/1319] eta: 0:38:08 lr: 2.624430981698809e-05 loss: 0.0422 (0.0482) time: 3.1764 data: 0.0086 max mem: 33369 +Epoch: [20] [ 610/1319] eta: 0:37:35 lr: 2.6235147189646863e-05 loss: 0.0422 (0.0482) time: 3.1725 data: 0.0080 max mem: 33369 +Epoch: [20] [ 620/1319] eta: 0:37:04 lr: 2.6225984206730902e-05 loss: 0.0421 (0.0481) time: 3.1767 data: 0.0082 max mem: 33369 +Epoch: [20] [ 630/1319] eta: 0:36:32 lr: 2.621682086808836e-05 loss: 0.0424 (0.0482) time: 3.1891 data: 0.0084 max mem: 33369 +Epoch: [20] [ 640/1319] eta: 0:36:00 lr: 2.620765717356726e-05 loss: 0.0424 (0.0482) time: 3.1909 data: 0.0081 max mem: 33369 +Epoch: [20] [ 650/1319] eta: 0:35:28 lr: 2.6198493123015528e-05 loss: 0.0432 (0.0483) time: 3.1864 data: 0.0079 max mem: 33369 +Epoch: [20] [ 660/1319] eta: 0:34:56 lr: 2.6189328716280927e-05 loss: 0.0487 (0.0485) time: 3.1681 data: 0.0077 max mem: 33369 +Epoch: [20] [ 670/1319] eta: 0:34:24 lr: 2.618016395321112e-05 loss: 0.0469 (0.0484) time: 3.1573 data: 0.0077 max mem: 33369 +Epoch: [20] [ 680/1319] eta: 0:33:53 lr: 2.6170998833653637e-05 loss: 0.0466 (0.0484) time: 3.1682 data: 0.0081 max mem: 33369 +Epoch: [20] [ 690/1319] eta: 0:33:21 lr: 2.616183335745589e-05 loss: 0.0491 (0.0484) time: 3.1788 data: 0.0085 max mem: 33369 +Epoch: [20] [ 700/1319] eta: 0:32:49 lr: 2.615266752446517e-05 loss: 0.0482 (0.0484) time: 3.1601 data: 0.0086 max mem: 33369 +Epoch: [20] [ 710/1319] eta: 0:32:17 lr: 2.614350133452863e-05 loss: 0.0443 (0.0484) time: 3.1598 data: 0.0087 max mem: 33369 +Epoch: [20] [ 720/1319] eta: 0:31:45 lr: 2.6134334787493302e-05 loss: 0.0458 (0.0485) time: 3.1606 data: 0.0085 max mem: 33369 +Epoch: [20] [ 730/1319] eta: 0:31:12 lr: 2.6125167883206104e-05 loss: 0.0449 (0.0484) time: 3.1490 data: 0.0081 max mem: 33369 +Epoch: [20] [ 740/1319] eta: 0:30:41 lr: 2.61160006215138e-05 loss: 0.0446 (0.0485) time: 3.1644 data: 0.0083 max mem: 33369 +Epoch: [20] [ 750/1319] eta: 0:30:09 lr: 2.610683300226307e-05 loss: 0.0453 (0.0485) time: 3.2153 data: 0.0086 max mem: 33369 +Epoch: [20] [ 760/1319] eta: 0:29:37 lr: 2.6097665025300437e-05 loss: 0.0459 (0.0486) time: 3.1767 data: 0.0087 max mem: 33369 +Epoch: [20] [ 770/1319] eta: 0:29:06 lr: 2.608849669047231e-05 loss: 0.0557 (0.0489) time: 3.1703 data: 0.0086 max mem: 33369 +Epoch: [20] [ 780/1319] eta: 0:28:34 lr: 2.6079327997624963e-05 loss: 0.0503 (0.0489) time: 3.1861 data: 0.0080 max mem: 33369 +Epoch: [20] [ 790/1319] eta: 0:28:02 lr: 2.6070158946604555e-05 loss: 0.0444 (0.0488) time: 3.1668 data: 0.0079 max mem: 33369 +Epoch: [20] [ 800/1319] eta: 0:27:30 lr: 2.6060989537257118e-05 loss: 0.0446 (0.0488) time: 3.1793 data: 0.0082 max mem: 33369 +Epoch: [20] [ 810/1319] eta: 0:26:58 lr: 2.6051819769428553e-05 loss: 0.0481 (0.0489) time: 3.1477 data: 0.0080 max mem: 33369 +Epoch: [20] [ 820/1319] eta: 0:26:26 lr: 2.604264964296463e-05 loss: 0.0487 (0.0490) time: 3.1623 data: 0.0083 max mem: 33369 +Epoch: [20] [ 830/1319] eta: 0:25:54 lr: 2.6033479157711e-05 loss: 0.0468 (0.0491) time: 3.1706 data: 0.0083 max mem: 33369 +Epoch: [20] [ 840/1319] eta: 0:25:22 lr: 2.6024308313513185e-05 loss: 0.0450 (0.0491) time: 3.1654 data: 0.0082 max mem: 33369 +Epoch: [20] [ 850/1319] eta: 0:24:50 lr: 2.601513711021658e-05 loss: 0.0464 (0.0491) time: 3.1560 data: 0.0083 max mem: 33369 +Epoch: [20] [ 860/1319] eta: 0:24:18 lr: 2.6005965547666454e-05 loss: 0.0452 (0.0490) time: 3.1362 data: 0.0081 max mem: 33369 +Epoch: [20] [ 870/1319] eta: 0:23:47 lr: 2.599679362570795e-05 loss: 0.0410 (0.0489) time: 3.1763 data: 0.0080 max mem: 33369 +Epoch: [20] [ 880/1319] eta: 0:23:15 lr: 2.598762134418607e-05 loss: 0.0410 (0.0489) time: 3.2113 data: 0.0082 max mem: 33369 +Epoch: [20] [ 890/1319] eta: 0:22:43 lr: 2.5978448702945707e-05 loss: 0.0359 (0.0488) time: 3.2037 data: 0.0085 max mem: 33369 +Epoch: [20] [ 900/1319] eta: 0:22:12 lr: 2.596927570183162e-05 loss: 0.0366 (0.0488) time: 3.1826 data: 0.0083 max mem: 33369 +Epoch: [20] [ 910/1319] eta: 0:21:40 lr: 2.5960102340688436e-05 loss: 0.0440 (0.0488) time: 3.1683 data: 0.0080 max mem: 33369 +Epoch: [20] [ 920/1319] eta: 0:21:08 lr: 2.5950928619360655e-05 loss: 0.0421 (0.0488) time: 3.1904 data: 0.0083 max mem: 33369 +Epoch: [20] [ 930/1319] eta: 0:20:36 lr: 2.5941754537692653e-05 loss: 0.0421 (0.0488) time: 3.1769 data: 0.0086 max mem: 33369 +Epoch: [20] [ 940/1319] eta: 0:20:04 lr: 2.5932580095528662e-05 loss: 0.0430 (0.0488) time: 3.1680 data: 0.0083 max mem: 33369 +Epoch: [20] [ 950/1319] eta: 0:19:33 lr: 2.5923405292712815e-05 loss: 0.0435 (0.0487) time: 3.1848 data: 0.0081 max mem: 33369 +Epoch: [20] [ 960/1319] eta: 0:19:01 lr: 2.5914230129089094e-05 loss: 0.0450 (0.0488) time: 3.1814 data: 0.0080 max mem: 33369 +Epoch: [20] [ 970/1319] eta: 0:18:29 lr: 2.590505460450136e-05 loss: 0.0466 (0.0488) time: 3.1679 data: 0.0076 max mem: 33369 +Epoch: [20] [ 980/1319] eta: 0:17:57 lr: 2.589587871879333e-05 loss: 0.0453 (0.0488) time: 3.1739 data: 0.0077 max mem: 33369 +Epoch: [20] [ 990/1319] eta: 0:17:25 lr: 2.5886702471808617e-05 loss: 0.0441 (0.0488) time: 3.1856 data: 0.0082 max mem: 33369 +Epoch: [20] [1000/1319] eta: 0:16:54 lr: 2.5877525863390684e-05 loss: 0.0431 (0.0488) time: 3.2014 data: 0.0080 max mem: 33369 +Epoch: [20] [1010/1319] eta: 0:16:22 lr: 2.586834889338287e-05 loss: 0.0414 (0.0488) time: 3.1961 data: 0.0078 max mem: 33369 +Epoch: [20] [1020/1319] eta: 0:15:50 lr: 2.58591715616284e-05 loss: 0.0437 (0.0489) time: 3.1604 data: 0.0079 max mem: 33369 +Epoch: [20] [1030/1319] eta: 0:15:18 lr: 2.584999386797035e-05 loss: 0.0423 (0.0488) time: 3.1845 data: 0.0076 max mem: 33369 +Epoch: [20] [1040/1319] eta: 0:14:47 lr: 2.5840815812251663e-05 loss: 0.0404 (0.0488) time: 3.1902 data: 0.0076 max mem: 33369 +Epoch: [20] [1050/1319] eta: 0:14:15 lr: 2.583163739431517e-05 loss: 0.0407 (0.0488) time: 3.1686 data: 0.0080 max mem: 33369 +Epoch: [20] [1060/1319] eta: 0:13:43 lr: 2.582245861400355e-05 loss: 0.0533 (0.0489) time: 3.1554 data: 0.0082 max mem: 33369 +Epoch: [20] [1070/1319] eta: 0:13:11 lr: 2.5813279471159375e-05 loss: 0.0418 (0.0488) time: 3.1585 data: 0.0080 max mem: 33369 +Epoch: [20] [1080/1319] eta: 0:12:39 lr: 2.5804099965625085e-05 loss: 0.0439 (0.0488) time: 3.1679 data: 0.0082 max mem: 33369 +Epoch: [20] [1090/1319] eta: 0:12:07 lr: 2.5794920097242954e-05 loss: 0.0453 (0.0488) time: 3.1629 data: 0.0080 max mem: 33369 +Epoch: [20] [1100/1319] eta: 0:11:36 lr: 2.5785739865855164e-05 loss: 0.0388 (0.0488) time: 3.1832 data: 0.0082 max mem: 33369 +Epoch: [20] [1110/1319] eta: 0:11:04 lr: 2.5776559271303753e-05 loss: 0.0412 (0.0488) time: 3.1932 data: 0.0086 max mem: 33369 +Epoch: [20] [1120/1319] eta: 0:10:32 lr: 2.5767378313430623e-05 loss: 0.0374 (0.0487) time: 3.1910 data: 0.0080 max mem: 33369 +Epoch: [20] [1130/1319] eta: 0:10:00 lr: 2.5758196992077554e-05 loss: 0.0399 (0.0488) time: 3.1782 data: 0.0077 max mem: 33369 +Epoch: [20] [1140/1319] eta: 0:09:28 lr: 2.574901530708619e-05 loss: 0.0496 (0.0489) time: 3.1385 data: 0.0081 max mem: 33369 +Epoch: [20] [1150/1319] eta: 0:08:57 lr: 2.573983325829803e-05 loss: 0.0540 (0.0490) time: 3.1634 data: 0.0079 max mem: 33369 +Epoch: [20] [1160/1319] eta: 0:08:25 lr: 2.573065084555446e-05 loss: 0.0480 (0.0489) time: 3.2054 data: 0.0077 max mem: 33369 +Epoch: [20] [1170/1319] eta: 0:07:53 lr: 2.572146806869673e-05 loss: 0.0408 (0.0489) time: 3.2139 data: 0.0078 max mem: 33369 +Epoch: [20] [1180/1319] eta: 0:07:21 lr: 2.5712284927565954e-05 loss: 0.0446 (0.0489) time: 3.1982 data: 0.0080 max mem: 33369 +Epoch: [20] [1190/1319] eta: 0:06:50 lr: 2.5703101422003118e-05 loss: 0.0446 (0.0489) time: 3.1482 data: 0.0079 max mem: 33369 +Epoch: [20] [1200/1319] eta: 0:06:18 lr: 2.569391755184906e-05 loss: 0.0426 (0.0489) time: 3.1267 data: 0.0080 max mem: 33369 +Epoch: [20] [1210/1319] eta: 0:05:46 lr: 2.5684733316944508e-05 loss: 0.0434 (0.0489) time: 3.1358 data: 0.0085 max mem: 33369 +Epoch: [20] [1220/1319] eta: 0:05:14 lr: 2.5675548717130043e-05 loss: 0.0468 (0.0489) time: 3.1459 data: 0.0083 max mem: 33369 +Epoch: [20] [1230/1319] eta: 0:04:42 lr: 2.5666363752246116e-05 loss: 0.0387 (0.0489) time: 3.1474 data: 0.0083 max mem: 33369 +Epoch: [20] [1240/1319] eta: 0:04:11 lr: 2.5657178422133044e-05 loss: 0.0404 (0.0492) time: 3.1539 data: 0.0087 max mem: 33369 +Epoch: [20] [1250/1319] eta: 0:03:39 lr: 2.564799272663101e-05 loss: 0.0465 (0.0492) time: 3.1633 data: 0.0088 max mem: 33369 +Epoch: [20] [1260/1319] eta: 0:03:07 lr: 2.5638806665580068e-05 loss: 0.0395 (0.0492) time: 3.1910 data: 0.0084 max mem: 33369 +Epoch: [20] [1270/1319] eta: 0:02:35 lr: 2.5629620238820134e-05 loss: 0.0471 (0.0492) time: 3.1825 data: 0.0078 max mem: 33369 +Epoch: [20] [1280/1319] eta: 0:02:03 lr: 2.562043344619099e-05 loss: 0.0471 (0.0492) time: 3.1465 data: 0.0075 max mem: 33369 +Epoch: [20] [1290/1319] eta: 0:01:32 lr: 2.5611246287532285e-05 loss: 0.0455 (0.0493) time: 3.1626 data: 0.0083 max mem: 33369 +Epoch: [20] [1300/1319] eta: 0:01:00 lr: 2.560205876268355e-05 loss: 0.0518 (0.0493) time: 3.1783 data: 0.0090 max mem: 33369 +Epoch: [20] [1310/1319] eta: 0:00:28 lr: 2.5592870871484144e-05 loss: 0.0436 (0.0492) time: 3.1567 data: 0.0082 max mem: 33369 +Epoch: [20] Total time: 1:09:50 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 2:11:49 time: 3.0739 data: 2.9019 max mem: 33369 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 100/2573] eta: 0:04:23 time: 0.0768 data: 0.0015 max mem: 33369 +Test: [ 200/2573] eta: 0:03:41 time: 0.0783 data: 0.0015 max mem: 33369 +Test: [ 300/2573] eta: 0:03:19 time: 0.0799 data: 0.0014 max mem: 33369 +Test: [ 400/2573] eta: 0:03:06 time: 0.0806 data: 0.0015 max mem: 33369 +Test: [ 500/2573] eta: 0:02:54 time: 0.0788 data: 0.0015 max mem: 33369 +Test: [ 600/2573] eta: 0:02:44 time: 0.0784 data: 0.0014 max mem: 33369 +Test: [ 700/2573] eta: 0:02:35 time: 0.0792 data: 0.0021 max mem: 33369 +Test: [ 800/2573] eta: 0:02:26 time: 0.0814 data: 0.0014 max mem: 33369 +Test: [ 900/2573] eta: 0:02:17 time: 0.0786 data: 0.0014 max mem: 33369 +Test: [1000/2573] eta: 0:02:08 time: 0.0789 data: 0.0015 max mem: 33369 +Test: [1100/2573] eta: 0:02:00 time: 0.0783 data: 0.0014 max mem: 33369 +Test: [1200/2573] eta: 0:01:52 time: 0.0807 data: 0.0016 max mem: 33369 +Test: [1300/2573] eta: 0:01:43 time: 0.0801 data: 0.0014 max mem: 33369 +Test: [1400/2573] eta: 0:01:35 time: 0.0777 data: 0.0015 max mem: 33369 +Test: [1500/2573] eta: 0:01:27 time: 0.0790 data: 0.0014 max mem: 33369 +Test: [1600/2573] eta: 0:01:18 time: 0.0822 data: 0.0014 max mem: 33369 +Test: [1700/2573] eta: 0:01:10 time: 0.0780 data: 0.0014 max mem: 33369 +Test: [1800/2573] eta: 0:01:02 time: 0.0817 data: 0.0014 max mem: 33369 +Test: [1900/2573] eta: 0:00:54 time: 0.0778 data: 0.0015 max mem: 33369 +Test: [2000/2573] eta: 0:00:46 time: 0.0788 data: 0.0014 max mem: 33369 +Test: [2100/2573] eta: 0:00:38 time: 0.0815 data: 0.0014 max mem: 33369 +Test: [2200/2573] eta: 0:00:30 time: 0.0817 data: 0.0016 max mem: 33369 +Test: [2300/2573] eta: 0:00:21 time: 0.0814 data: 0.0015 max mem: 33369 +Test: [2400/2573] eta: 0:00:13 time: 0.0758 data: 0.0014 max mem: 33369 +Test: [2500/2573] eta: 0:00:05 time: 0.0791 data: 0.0015 max mem: 33369 +Test: Total time: 0:03:27 +Final results: +Mean IoU is 63.09 + + precision@0.5 = 71.00 + precision@0.6 = 65.24 + precision@0.7 = 58.13 + precision@0.8 = 46.65 + precision@0.9 = 22.55 + overall IoU = 60.84 + +Average object IoU 63.09171357155295 +Overall IoU 60.844268798828125 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [21] [ 0/1319] eta: 3:03:31 lr: 2.5584601456041995e-05 loss: 0.0434 (0.0434) time: 8.3480 data: 2.5888 max mem: 33369 +Epoch: [21] [ 10/1319] eta: 1:19:53 lr: 2.5575412868333344e-05 loss: 0.0479 (0.0530) time: 3.6621 data: 0.2431 max mem: 33369 +Epoch: [21] [ 20/1319] eta: 1:14:06 lr: 2.5566223913807464e-05 loss: 0.0431 (0.0513) time: 3.1765 data: 0.0085 max mem: 33369 +Epoch: [21] [ 30/1319] eta: 1:11:49 lr: 2.5557034592303224e-05 loss: 0.0423 (0.0520) time: 3.1684 data: 0.0080 max mem: 33369 +Epoch: [21] [ 40/1319] eta: 1:10:37 lr: 2.5547844903659336e-05 loss: 0.0510 (0.0517) time: 3.1977 data: 0.0074 max mem: 33369 +Epoch: [21] [ 50/1319] eta: 1:09:28 lr: 2.5538654847714393e-05 loss: 0.0464 (0.0503) time: 3.1939 data: 0.0077 max mem: 33369 +Epoch: [21] [ 60/1319] eta: 1:08:33 lr: 2.552946442430683e-05 loss: 0.0419 (0.0489) time: 3.1738 data: 0.0080 max mem: 33369 +Epoch: [21] [ 70/1319] eta: 1:07:37 lr: 2.552027363327497e-05 loss: 0.0395 (0.0509) time: 3.1552 data: 0.0079 max mem: 33369 +Epoch: [21] [ 80/1319] eta: 1:06:50 lr: 2.551108247445699e-05 loss: 0.0424 (0.0512) time: 3.1448 data: 0.0081 max mem: 33369 +Epoch: [21] [ 90/1319] eta: 1:06:06 lr: 2.5501890947690927e-05 loss: 0.0429 (0.0504) time: 3.1540 data: 0.0082 max mem: 33369 +Epoch: [21] [ 100/1319] eta: 1:05:24 lr: 2.5492699052814688e-05 loss: 0.0429 (0.0500) time: 3.1463 data: 0.0081 max mem: 33369 +Epoch: [21] [ 110/1319] eta: 1:04:46 lr: 2.548350678966605e-05 loss: 0.0439 (0.0510) time: 3.1571 data: 0.0080 max mem: 33369 +Epoch: [21] [ 120/1319] eta: 1:04:09 lr: 2.547431415808263e-05 loss: 0.0427 (0.0511) time: 3.1698 data: 0.0078 max mem: 33369 +Epoch: [21] [ 130/1319] eta: 1:03:36 lr: 2.5465121157901932e-05 loss: 0.0442 (0.0512) time: 3.1812 data: 0.0078 max mem: 33369 +Epoch: [21] [ 140/1319] eta: 1:02:55 lr: 2.5455927788961316e-05 loss: 0.0442 (0.0509) time: 3.1494 data: 0.0081 max mem: 33369 +Epoch: [21] [ 150/1319] eta: 1:02:26 lr: 2.5446734051098e-05 loss: 0.0421 (0.0505) time: 3.1714 data: 0.0084 max mem: 33369 +Epoch: [21] [ 160/1319] eta: 1:01:50 lr: 2.5437539944149068e-05 loss: 0.0488 (0.0511) time: 3.1931 data: 0.0089 max mem: 33369 +Epoch: [21] [ 170/1319] eta: 1:01:16 lr: 2.542834546795147e-05 loss: 0.0567 (0.0512) time: 3.1628 data: 0.0094 max mem: 33369 +Epoch: [21] [ 180/1319] eta: 1:00:41 lr: 2.5419150622342014e-05 loss: 0.0507 (0.0511) time: 3.1630 data: 0.0090 max mem: 33369 +Epoch: [21] [ 190/1319] eta: 1:00:03 lr: 2.5409955407157366e-05 loss: 0.0427 (0.0506) time: 3.1262 data: 0.0081 max mem: 33369 +Epoch: [21] [ 200/1319] eta: 0:59:32 lr: 2.5400759822234066e-05 loss: 0.0376 (0.0502) time: 3.1577 data: 0.0083 max mem: 33369 +Epoch: [21] [ 210/1319] eta: 0:59:01 lr: 2.539156386740852e-05 loss: 0.0376 (0.0498) time: 3.2062 data: 0.0083 max mem: 33369 +Epoch: [21] [ 220/1319] eta: 0:58:29 lr: 2.538236754251696e-05 loss: 0.0414 (0.0502) time: 3.1960 data: 0.0079 max mem: 33369 +Epoch: [21] [ 230/1319] eta: 0:57:56 lr: 2.5373170847395516e-05 loss: 0.0483 (0.0500) time: 3.1801 data: 0.0081 max mem: 33369 +Epoch: [21] [ 240/1319] eta: 0:57:19 lr: 2.536397378188018e-05 loss: 0.0434 (0.0500) time: 3.1307 data: 0.0082 max mem: 33369 +Epoch: [21] [ 250/1319] eta: 0:56:47 lr: 2.5354776345806775e-05 loss: 0.0456 (0.0499) time: 3.1303 data: 0.0080 max mem: 33369 +Epoch: [21] [ 260/1319] eta: 0:56:15 lr: 2.534557853901102e-05 loss: 0.0432 (0.0496) time: 3.1795 data: 0.0082 max mem: 33369 +Epoch: [21] [ 270/1319] eta: 0:55:42 lr: 2.5336380361328465e-05 loss: 0.0395 (0.0492) time: 3.1798 data: 0.0083 max mem: 33369 +Epoch: [21] [ 280/1319] eta: 0:55:11 lr: 2.532718181259454e-05 loss: 0.0389 (0.0490) time: 3.1794 data: 0.0085 max mem: 33369 +Epoch: [21] [ 290/1319] eta: 0:54:37 lr: 2.531798289264453e-05 loss: 0.0453 (0.0492) time: 3.1690 data: 0.0085 max mem: 33369 +Epoch: [21] [ 300/1319] eta: 0:54:06 lr: 2.5308783601313586e-05 loss: 0.0475 (0.0494) time: 3.1699 data: 0.0081 max mem: 33369 +Epoch: [21] [ 310/1319] eta: 0:53:35 lr: 2.52995839384367e-05 loss: 0.0449 (0.0492) time: 3.2104 data: 0.0083 max mem: 33369 +Epoch: [21] [ 320/1319] eta: 0:53:02 lr: 2.5290383903848747e-05 loss: 0.0382 (0.0492) time: 3.1887 data: 0.0087 max mem: 33369 +Epoch: [21] [ 330/1319] eta: 0:52:30 lr: 2.5281183497384443e-05 loss: 0.0384 (0.0489) time: 3.1641 data: 0.0086 max mem: 33369 +Epoch: [21] [ 340/1319] eta: 0:51:56 lr: 2.5271982718878386e-05 loss: 0.0421 (0.0488) time: 3.1510 data: 0.0084 max mem: 33369 +Epoch: [21] [ 350/1319] eta: 0:51:24 lr: 2.5262781568165e-05 loss: 0.0465 (0.0487) time: 3.1350 data: 0.0081 max mem: 33369 +Epoch: [21] [ 360/1319] eta: 0:50:53 lr: 2.5253580045078606e-05 loss: 0.0424 (0.0488) time: 3.1807 data: 0.0077 max mem: 33369 +Epoch: [21] [ 370/1319] eta: 0:50:20 lr: 2.5244378149453368e-05 loss: 0.0390 (0.0485) time: 3.1862 data: 0.0076 max mem: 33369 +Epoch: [21] [ 380/1319] eta: 0:49:48 lr: 2.5235175881123296e-05 loss: 0.0373 (0.0483) time: 3.1692 data: 0.0079 max mem: 33369 +Epoch: [21] [ 390/1319] eta: 0:49:17 lr: 2.5225973239922274e-05 loss: 0.0371 (0.0483) time: 3.1896 data: 0.0080 max mem: 33369 +Epoch: [21] [ 400/1319] eta: 0:48:45 lr: 2.5216770225684038e-05 loss: 0.0384 (0.0481) time: 3.1971 data: 0.0078 max mem: 33369 +Epoch: [21] [ 410/1319] eta: 0:48:14 lr: 2.520756683824219e-05 loss: 0.0406 (0.0485) time: 3.2025 data: 0.0076 max mem: 33369 +Epoch: [21] [ 420/1319] eta: 0:47:41 lr: 2.5198363077430187e-05 loss: 0.0422 (0.0489) time: 3.1689 data: 0.0080 max mem: 33369 +Epoch: [21] [ 430/1319] eta: 0:47:09 lr: 2.5189158943081348e-05 loss: 0.0371 (0.0486) time: 3.1488 data: 0.0085 max mem: 33369 +Epoch: [21] [ 440/1319] eta: 0:46:38 lr: 2.5179954435028824e-05 loss: 0.0337 (0.0485) time: 3.1999 data: 0.0081 max mem: 33369 +Epoch: [21] [ 450/1319] eta: 0:46:05 lr: 2.517074955310566e-05 loss: 0.0404 (0.0484) time: 3.1835 data: 0.0080 max mem: 33369 +Epoch: [21] [ 460/1319] eta: 0:45:33 lr: 2.5161544297144735e-05 loss: 0.0430 (0.0487) time: 3.1548 data: 0.0086 max mem: 33369 +Epoch: [21] [ 470/1319] eta: 0:45:01 lr: 2.5152338666978798e-05 loss: 0.0430 (0.0486) time: 3.1731 data: 0.0081 max mem: 33369 +Epoch: [21] [ 480/1319] eta: 0:44:29 lr: 2.5143132662440454e-05 loss: 0.0394 (0.0484) time: 3.1676 data: 0.0077 max mem: 33369 +Epoch: [21] [ 490/1319] eta: 0:43:57 lr: 2.513392628336215e-05 loss: 0.0403 (0.0485) time: 3.1562 data: 0.0076 max mem: 33369 +Epoch: [21] [ 500/1319] eta: 0:43:25 lr: 2.5124719529576212e-05 loss: 0.0400 (0.0485) time: 3.1611 data: 0.0078 max mem: 33369 +Epoch: [21] [ 510/1319] eta: 0:42:53 lr: 2.51155124009148e-05 loss: 0.0344 (0.0483) time: 3.1700 data: 0.0078 max mem: 33369 +Epoch: [21] [ 520/1319] eta: 0:42:22 lr: 2.5106304897209954e-05 loss: 0.0384 (0.0484) time: 3.1998 data: 0.0079 max mem: 33369 +Epoch: [21] [ 530/1319] eta: 0:41:50 lr: 2.5097097018293553e-05 loss: 0.0386 (0.0482) time: 3.1942 data: 0.0080 max mem: 33369 +Epoch: [21] [ 540/1319] eta: 0:41:18 lr: 2.508788876399733e-05 loss: 0.0382 (0.0481) time: 3.1768 data: 0.0080 max mem: 33369 +Epoch: [21] [ 550/1319] eta: 0:40:46 lr: 2.5078680134152888e-05 loss: 0.0402 (0.0480) time: 3.1760 data: 0.0082 max mem: 33369 +Epoch: [21] [ 560/1319] eta: 0:40:14 lr: 2.5069471128591682e-05 loss: 0.0457 (0.0483) time: 3.1768 data: 0.0084 max mem: 33369 +Epoch: [21] [ 570/1319] eta: 0:39:42 lr: 2.5060261747145013e-05 loss: 0.0492 (0.0483) time: 3.1907 data: 0.0085 max mem: 33369 +Epoch: [21] [ 580/1319] eta: 0:39:10 lr: 2.5051051989644047e-05 loss: 0.0432 (0.0483) time: 3.1660 data: 0.0078 max mem: 33369 +Epoch: [21] [ 590/1319] eta: 0:38:38 lr: 2.504184185591981e-05 loss: 0.0418 (0.0482) time: 3.1692 data: 0.0076 max mem: 33369 +Epoch: [21] [ 600/1319] eta: 0:38:07 lr: 2.503263134580316e-05 loss: 0.0466 (0.0483) time: 3.1899 data: 0.0078 max mem: 33369 +Epoch: [21] [ 610/1319] eta: 0:37:35 lr: 2.502342045912483e-05 loss: 0.0441 (0.0482) time: 3.1938 data: 0.0078 max mem: 33369 +Epoch: [21] [ 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data: 0.0078 max mem: 33369 +Epoch: [21] [ 780/1319] eta: 0:28:34 lr: 2.4866777606924187e-05 loss: 0.0475 (0.0482) time: 3.1672 data: 0.0080 max mem: 33369 +Epoch: [21] [ 790/1319] eta: 0:28:02 lr: 2.4857559913023423e-05 loss: 0.0439 (0.0482) time: 3.1942 data: 0.0083 max mem: 33369 +Epoch: [21] [ 800/1319] eta: 0:27:31 lr: 2.4848341839316978e-05 loss: 0.0434 (0.0482) time: 3.1882 data: 0.0085 max mem: 33369 +Epoch: [21] [ 810/1319] eta: 0:26:59 lr: 2.483912338563262e-05 loss: 0.0422 (0.0481) time: 3.1935 data: 0.0085 max mem: 33369 +Epoch: [21] [ 820/1319] eta: 0:26:27 lr: 2.4829904551797996e-05 loss: 0.0420 (0.0482) time: 3.1817 data: 0.0082 max mem: 33369 +Epoch: [21] [ 830/1319] eta: 0:25:55 lr: 2.4820685337640587e-05 loss: 0.0491 (0.0483) time: 3.1689 data: 0.0080 max mem: 33369 +Epoch: [21] [ 840/1319] eta: 0:25:23 lr: 2.481146574298773e-05 loss: 0.0491 (0.0483) time: 3.1646 data: 0.0079 max mem: 33369 +Epoch: [21] [ 850/1319] eta: 0:24:51 lr: 2.480224576766661e-05 loss: 0.0419 (0.0483) time: 3.1416 data: 0.0081 max mem: 33369 +Epoch: [21] [ 860/1319] eta: 0:24:19 lr: 2.4793025411504282e-05 loss: 0.0383 (0.0482) time: 3.1790 data: 0.0084 max mem: 33369 +Epoch: [21] [ 870/1319] eta: 0:23:47 lr: 2.4783804674327604e-05 loss: 0.0386 (0.0481) time: 3.1742 data: 0.0082 max mem: 33369 +Epoch: [21] [ 880/1319] eta: 0:23:16 lr: 2.4774583555963328e-05 loss: 0.0393 (0.0481) time: 3.1735 data: 0.0080 max mem: 33369 +Epoch: [21] [ 890/1319] eta: 0:22:44 lr: 2.4765362056238035e-05 loss: 0.0393 (0.0481) time: 3.1887 data: 0.0083 max mem: 33369 +Epoch: [21] [ 900/1319] eta: 0:22:12 lr: 2.4756140174978167e-05 loss: 0.0400 (0.0481) time: 3.1889 data: 0.0088 max mem: 33369 +Epoch: [21] [ 910/1319] eta: 0:21:40 lr: 2.4746917912010012e-05 loss: 0.0393 (0.0480) time: 3.2026 data: 0.0084 max mem: 33369 +Epoch: [21] [ 920/1319] eta: 0:21:09 lr: 2.4737695267159685e-05 loss: 0.0423 (0.0481) time: 3.1966 data: 0.0079 max mem: 33369 +Epoch: [21] [ 930/1319] eta: 0:20:37 lr: 2.4728472240253183e-05 loss: 0.0483 (0.0481) time: 3.2063 data: 0.0081 max mem: 33369 +Epoch: [21] [ 940/1319] eta: 0:20:05 lr: 2.4719248831116334e-05 loss: 0.0454 (0.0480) time: 3.1944 data: 0.0078 max mem: 33369 +Epoch: [21] [ 950/1319] eta: 0:19:34 lr: 2.4710025039574813e-05 loss: 0.0403 (0.0482) time: 3.2052 data: 0.0075 max mem: 33369 +Epoch: [21] [ 960/1319] eta: 0:19:02 lr: 2.4700800865454158e-05 loss: 0.0440 (0.0481) time: 3.2127 data: 0.0081 max mem: 33369 +Epoch: [21] [ 970/1319] eta: 0:18:30 lr: 2.469157630857973e-05 loss: 0.0394 (0.0481) time: 3.1856 data: 0.0085 max mem: 33369 +Epoch: [21] [ 980/1319] eta: 0:17:58 lr: 2.4682351368776758e-05 loss: 0.0396 (0.0481) time: 3.1822 data: 0.0079 max mem: 33369 +Epoch: [21] [ 990/1319] eta: 0:17:26 lr: 2.467312604587031e-05 loss: 0.0398 (0.0481) time: 3.1908 data: 0.0074 max mem: 33369 +Epoch: [21] [1000/1319] eta: 0:16:55 lr: 2.4663900339685314e-05 loss: 0.0412 (0.0481) time: 3.2039 data: 0.0075 max mem: 33369 +Epoch: [21] [1010/1319] eta: 0:16:23 lr: 2.4654674250046523e-05 loss: 0.0414 (0.0481) time: 3.1959 data: 0.0080 max mem: 33369 +Epoch: [21] [1020/1319] eta: 0:15:51 lr: 2.464544777677856e-05 loss: 0.0441 (0.0482) time: 3.1704 data: 0.0079 max mem: 33369 +Epoch: [21] [1030/1319] eta: 0:15:19 lr: 2.4636220919705875e-05 loss: 0.0461 (0.0482) time: 3.1712 data: 0.0079 max mem: 33369 +Epoch: [21] [1040/1319] eta: 0:14:47 lr: 2.4626993678652773e-05 loss: 0.0461 (0.0482) time: 3.1552 data: 0.0082 max mem: 33369 +Epoch: [21] [1050/1319] eta: 0:14:15 lr: 2.4617766053443412e-05 loss: 0.0415 (0.0481) time: 3.1265 data: 0.0082 max mem: 33369 +Epoch: [21] [1060/1319] eta: 0:13:43 lr: 2.4608538043901786e-05 loss: 0.0391 (0.0482) time: 3.1450 data: 0.0083 max mem: 33369 +Epoch: [21] [1070/1319] eta: 0:13:11 lr: 2.4599309649851742e-05 loss: 0.0391 (0.0481) time: 3.1522 data: 0.0084 max mem: 33369 +Epoch: [21] [1080/1319] eta: 0:12:40 lr: 2.4590080871116966e-05 loss: 0.0380 (0.0481) time: 3.1476 data: 0.0081 max mem: 33369 +Epoch: [21] [1090/1319] eta: 0:12:08 lr: 2.4580851707520996e-05 loss: 0.0384 (0.0480) time: 3.1881 data: 0.0078 max mem: 33369 +Epoch: [21] [1100/1319] eta: 0:11:36 lr: 2.457162215888721e-05 loss: 0.0388 (0.0480) time: 3.1933 data: 0.0079 max mem: 33369 +Epoch: [21] [1110/1319] eta: 0:11:04 lr: 2.456239222503884e-05 loss: 0.0400 (0.0480) time: 3.1808 data: 0.0077 max mem: 33369 +Epoch: [21] [1120/1319] eta: 0:10:32 lr: 2.455316190579896e-05 loss: 0.0388 (0.0479) time: 3.1838 data: 0.0075 max mem: 33369 +Epoch: [21] [1130/1319] eta: 0:10:01 lr: 2.4543931200990468e-05 loss: 0.0397 (0.0479) time: 3.2034 data: 0.0076 max mem: 33369 +Epoch: [21] [1140/1319] eta: 0:09:29 lr: 2.4534700110436136e-05 loss: 0.0468 (0.0478) time: 3.2066 data: 0.0078 max mem: 33369 +Epoch: [21] [1150/1319] eta: 0:08:57 lr: 2.452546863395857e-05 loss: 0.0447 (0.0478) time: 3.1959 data: 0.0080 max mem: 33369 +Epoch: [21] [1160/1319] eta: 0:08:25 lr: 2.451623677138022e-05 loss: 0.0447 (0.0479) time: 3.1973 data: 0.0080 max mem: 33369 +Epoch: [21] [1170/1319] eta: 0:07:54 lr: 2.4507004522523372e-05 loss: 0.0446 (0.0479) time: 3.1706 data: 0.0084 max mem: 33369 +Epoch: [21] [1180/1319] eta: 0:07:22 lr: 2.4497771887210175e-05 loss: 0.0397 (0.0478) time: 3.1594 data: 0.0084 max mem: 33369 +Epoch: [21] [1190/1319] eta: 0:06:50 lr: 2.4488538865262596e-05 loss: 0.0376 (0.0478) time: 3.1821 data: 0.0081 max mem: 33369 +Epoch: [21] [1200/1319] eta: 0:06:18 lr: 2.4479305456502462e-05 loss: 0.0446 (0.0478) time: 3.1709 data: 0.0085 max mem: 33369 +Epoch: [21] [1210/1319] eta: 0:05:46 lr: 2.4470071660751444e-05 loss: 0.0403 (0.0477) time: 3.1618 data: 0.0088 max mem: 33369 +Epoch: [21] [1220/1319] eta: 0:05:14 lr: 2.446083747783105e-05 loss: 0.0413 (0.0479) time: 3.1754 data: 0.0085 max mem: 33369 +Epoch: [21] [1230/1319] eta: 0:04:43 lr: 2.4451602907562637e-05 loss: 0.0471 (0.0479) time: 3.1685 data: 0.0083 max mem: 33369 +Epoch: [21] [1240/1319] eta: 0:04:11 lr: 2.4442367949767393e-05 loss: 0.0437 (0.0479) time: 3.1968 data: 0.0084 max mem: 33369 +Epoch: [21] [1250/1319] eta: 0:03:39 lr: 2.4433132604266355e-05 loss: 0.0424 (0.0479) time: 3.2318 data: 0.0088 max mem: 33369 +Epoch: [21] [1260/1319] eta: 0:03:07 lr: 2.442389687088041e-05 loss: 0.0453 (0.0480) time: 3.2123 data: 0.0088 max mem: 33369 +Epoch: [21] [1270/1319] eta: 0:02:35 lr: 2.441466074943027e-05 loss: 0.0435 (0.0480) time: 3.1982 data: 0.0082 max mem: 33369 +Epoch: [21] [1280/1319] eta: 0:02:04 lr: 2.440542423973651e-05 loss: 0.0418 (0.0480) time: 3.2011 data: 0.0075 max mem: 33369 +Epoch: [21] [1290/1319] eta: 0:01:32 lr: 2.439618734161953e-05 loss: 0.0470 (0.0480) time: 3.1822 data: 0.0074 max mem: 33369 +Epoch: [21] [1300/1319] eta: 0:01:00 lr: 2.4386950054899575e-05 loss: 0.0431 (0.0480) time: 3.1530 data: 0.0078 max mem: 33369 +Epoch: [21] [1310/1319] eta: 0:00:28 lr: 2.4377712379396728e-05 loss: 0.0415 (0.0480) time: 3.1468 data: 0.0077 max mem: 33369 +Epoch: [21] Total time: 1:09:56 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 2:05:59 time: 2.9380 data: 2.7965 max mem: 33369 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 100/2573] eta: 0:04:20 time: 0.0757 data: 0.0014 max mem: 33369 +Test: [ 200/2573] eta: 0:03:38 time: 0.0777 data: 0.0014 max mem: 33369 +Test: [ 300/2573] eta: 0:03:17 time: 0.0797 data: 0.0013 max mem: 33369 +Test: [ 400/2573] eta: 0:03:04 time: 0.0807 data: 0.0015 max mem: 33369 +Test: [ 500/2573] eta: 0:02:53 time: 0.0789 data: 0.0014 max mem: 33369 +Test: [ 600/2573] eta: 0:02:43 time: 0.0784 data: 0.0014 max mem: 33369 +Test: [ 700/2573] eta: 0:02:34 time: 0.0787 data: 0.0014 max mem: 33369 +Test: [ 800/2573] eta: 0:02:25 time: 0.0825 data: 0.0015 max mem: 33369 +Test: [ 900/2573] eta: 0:02:17 time: 0.0790 data: 0.0015 max mem: 33369 +Test: [1000/2573] eta: 0:02:08 time: 0.0799 data: 0.0014 max mem: 33369 +Test: [1100/2573] eta: 0:02:00 time: 0.0798 data: 0.0015 max mem: 33369 +Test: [1200/2573] eta: 0:01:51 time: 0.0788 data: 0.0014 max mem: 33369 +Test: [1300/2573] eta: 0:01:43 time: 0.0795 data: 0.0016 max mem: 33369 +Test: [1400/2573] eta: 0:01:35 time: 0.0771 data: 0.0014 max mem: 33369 +Test: [1500/2573] eta: 0:01:26 time: 0.0788 data: 0.0014 max mem: 33369 +Test: [1600/2573] eta: 0:01:18 time: 0.0819 data: 0.0014 max mem: 33369 +Test: [1700/2573] eta: 0:01:10 time: 0.0783 data: 0.0015 max mem: 33369 +Test: [1800/2573] eta: 0:01:02 time: 0.0819 data: 0.0016 max mem: 33369 +Test: [1900/2573] eta: 0:00:54 time: 0.0778 data: 0.0014 max mem: 33369 +Test: [2000/2573] eta: 0:00:46 time: 0.0795 data: 0.0014 max mem: 33369 +Test: [2100/2573] eta: 0:00:38 time: 0.0802 data: 0.0013 max mem: 33369 +Test: [2200/2573] eta: 0:00:30 time: 0.0805 data: 0.0013 max mem: 33369 +Test: [2300/2573] eta: 0:00:21 time: 0.0810 data: 0.0015 max mem: 33369 +Test: [2400/2573] eta: 0:00:13 time: 0.0761 data: 0.0014 max mem: 33369 +Test: [2500/2573] eta: 0:00:05 time: 0.0801 data: 0.0015 max mem: 33369 +Test: Total time: 0:03:26 +Final results: +Mean IoU is 63.25 + + precision@0.5 = 71.12 + precision@0.6 = 65.26 + precision@0.7 = 57.74 + precision@0.8 = 45.96 + precision@0.9 = 22.59 + overall IoU = 61.32 + +Average object IoU 63.24801552491327 +Overall IoU 61.317440032958984 +Better epoch: 21 + +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [22] [ 0/1319] eta: 1:47:17 lr: 2.4369398138885975e-05 loss: 0.1337 (0.1337) time: 4.8805 data: 1.5863 max mem: 33369 +Epoch: [22] [ 10/1319] eta: 1:13:08 lr: 2.436015972419942e-05 loss: 0.0406 (0.0500) time: 3.3523 data: 0.1523 max mem: 33369 +Epoch: [22] [ 20/1319] eta: 1:11:13 lr: 2.4350920920207323e-05 loss: 0.0406 (0.0519) time: 3.2102 data: 0.0080 max mem: 33369 +Epoch: [22] [ 30/1319] eta: 1:10:04 lr: 2.4341681726729162e-05 loss: 0.0422 (0.0510) time: 3.2120 data: 0.0074 max mem: 33369 +Epoch: [22] [ 40/1319] eta: 1:09:04 lr: 2.4332442143584247e-05 loss: 0.0480 (0.0510) time: 3.1891 data: 0.0083 max mem: 33369 +Epoch: [22] [ 50/1319] eta: 1:08:10 lr: 2.4323202170591704e-05 loss: 0.0512 (0.0514) time: 3.1646 data: 0.0084 max mem: 33369 +Epoch: [22] [ 60/1319] eta: 1:07:28 lr: 2.4313961807570534e-05 loss: 0.0488 (0.0511) time: 3.1643 data: 0.0079 max mem: 33369 +Epoch: [22] [ 70/1319] eta: 1:06:49 lr: 2.430472105433956e-05 loss: 0.0423 (0.0501) time: 3.1754 data: 0.0084 max mem: 33369 +Epoch: [22] [ 80/1319] eta: 1:06:11 lr: 2.4295479910717442e-05 loss: 0.0364 (0.0485) time: 3.1735 data: 0.0088 max mem: 33369 +Epoch: [22] [ 90/1319] eta: 1:05:37 lr: 2.4286238376522685e-05 loss: 0.0439 (0.0504) time: 3.1819 data: 0.0085 max mem: 33369 +Epoch: [22] [ 100/1319] eta: 1:05:02 lr: 2.4276996451573638e-05 loss: 0.0530 (0.0511) time: 3.1867 data: 0.0078 max mem: 33369 +Epoch: [22] [ 110/1319] eta: 1:04:32 lr: 2.426775413568847e-05 loss: 0.0519 (0.0507) time: 3.1988 data: 0.0078 max mem: 33369 +Epoch: [22] [ 120/1319] eta: 1:03:49 lr: 2.4258511428685206e-05 loss: 0.0418 (0.0504) time: 3.1555 data: 0.0083 max mem: 33369 +Epoch: [22] [ 130/1319] eta: 1:03:10 lr: 2.4249268330381702e-05 loss: 0.0401 (0.0494) time: 3.1034 data: 0.0084 max mem: 33369 +Epoch: [22] [ 140/1319] eta: 1:02:40 lr: 2.4240024840595657e-05 loss: 0.0421 (0.0496) time: 3.1648 data: 0.0083 max mem: 33369 +Epoch: [22] [ 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data: 0.0082 max mem: 33369 +Epoch: [22] [ 310/1319] eta: 0:53:36 lr: 2.4082825439961318e-05 loss: 0.0374 (0.0465) time: 3.1918 data: 0.0080 max mem: 33369 +Epoch: [22] [ 320/1319] eta: 0:53:04 lr: 2.4073574872129434e-05 loss: 0.0396 (0.0467) time: 3.2005 data: 0.0077 max mem: 33369 +Epoch: [22] [ 330/1319] eta: 0:52:32 lr: 2.4064323909320154e-05 loss: 0.0454 (0.0467) time: 3.1849 data: 0.0076 max mem: 33369 +Epoch: [22] [ 340/1319] eta: 0:52:00 lr: 2.405507255134789e-05 loss: 0.0454 (0.0470) time: 3.1818 data: 0.0079 max mem: 33369 +Epoch: [22] [ 350/1319] eta: 0:51:28 lr: 2.404582079802688e-05 loss: 0.0449 (0.0469) time: 3.1712 data: 0.0080 max mem: 33369 +Epoch: [22] [ 360/1319] eta: 0:50:57 lr: 2.4036568649171213e-05 loss: 0.0378 (0.0468) time: 3.1878 data: 0.0078 max mem: 33369 +Epoch: [22] [ 370/1319] eta: 0:50:24 lr: 2.402731610459478e-05 loss: 0.0378 (0.0467) time: 3.1967 data: 0.0080 max mem: 33369 +Epoch: [22] [ 380/1319] eta: 0:49:52 lr: 2.401806316411133e-05 loss: 0.0416 (0.0467) time: 3.1809 data: 0.0079 max mem: 33369 +Epoch: [22] [ 390/1319] eta: 0:49:21 lr: 2.400880982753445e-05 loss: 0.0453 (0.0470) time: 3.1865 data: 0.0075 max mem: 33369 +Epoch: [22] [ 400/1319] eta: 0:48:49 lr: 2.399955609467753e-05 loss: 0.0433 (0.0471) time: 3.1848 data: 0.0081 max mem: 33369 +Epoch: [22] [ 410/1319] eta: 0:48:16 lr: 2.3990301965353823e-05 loss: 0.0397 (0.0470) time: 3.1634 data: 0.0084 max mem: 33369 +Epoch: [22] [ 420/1319] eta: 0:47:44 lr: 2.39810474393764e-05 loss: 0.0365 (0.0469) time: 3.1759 data: 0.0083 max mem: 33369 +Epoch: [22] [ 430/1319] eta: 0:47:13 lr: 2.3971792516558155e-05 loss: 0.0394 (0.0467) time: 3.2068 data: 0.0083 max mem: 33369 +Epoch: [22] [ 440/1319] eta: 0:46:41 lr: 2.3962537196711826e-05 loss: 0.0387 (0.0467) time: 3.1844 data: 0.0081 max mem: 33369 +Epoch: [22] [ 450/1319] eta: 0:46:09 lr: 2.3953281479649982e-05 loss: 0.0448 (0.0468) time: 3.1835 data: 0.0076 max mem: 33369 +Epoch: [22] [ 460/1319] eta: 0:45:37 lr: 2.394402536518502e-05 loss: 0.0435 (0.0467) time: 3.1978 data: 0.0079 max mem: 33369 +Epoch: [22] [ 470/1319] eta: 0:45:05 lr: 2.3934768853129168e-05 loss: 0.0372 (0.0467) time: 3.1919 data: 0.0082 max mem: 33369 +Epoch: [22] [ 480/1319] eta: 0:44:34 lr: 2.3925511943294477e-05 loss: 0.0412 (0.0467) time: 3.2009 data: 0.0083 max mem: 33369 +Epoch: [22] [ 490/1319] eta: 0:44:01 lr: 2.3916254635492843e-05 loss: 0.0458 (0.0469) time: 3.1697 data: 0.0086 max mem: 33369 +Epoch: [22] [ 500/1319] eta: 0:43:29 lr: 2.390699692953598e-05 loss: 0.0462 (0.0470) time: 3.1480 data: 0.0089 max mem: 33369 +Epoch: [22] [ 510/1319] eta: 0:42:56 lr: 2.3897738825235443e-05 loss: 0.0445 (0.0472) time: 3.1590 data: 0.0094 max mem: 33369 +Epoch: [22] [ 520/1319] eta: 0:42:24 lr: 2.3888480322402605e-05 loss: 0.0438 (0.0471) time: 3.1546 data: 0.0091 max mem: 33369 +Epoch: [22] [ 530/1319] eta: 0:41:52 lr: 2.3879221420848673e-05 loss: 0.0494 (0.0474) time: 3.1721 data: 0.0088 max mem: 33369 +Epoch: [22] [ 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33369 +Epoch: [22] [ 620/1319] eta: 0:37:04 lr: 2.379587333317862e-05 loss: 0.0427 (0.0472) time: 3.1419 data: 0.0085 max mem: 33369 +Epoch: [22] [ 630/1319] eta: 0:36:32 lr: 2.3786610433992487e-05 loss: 0.0421 (0.0473) time: 3.1583 data: 0.0083 max mem: 33369 +Epoch: [22] [ 640/1319] eta: 0:36:00 lr: 2.3777347133997216e-05 loss: 0.0400 (0.0472) time: 3.1778 data: 0.0081 max mem: 33369 +Epoch: [22] [ 650/1319] eta: 0:35:29 lr: 2.3768083433001952e-05 loss: 0.0373 (0.0472) time: 3.1864 data: 0.0086 max mem: 33369 +Epoch: [22] [ 660/1319] eta: 0:34:56 lr: 2.375881933081567e-05 loss: 0.0341 (0.0470) time: 3.1593 data: 0.0092 max mem: 33369 +Epoch: [22] [ 670/1319] eta: 0:34:24 lr: 2.3749554827247157e-05 loss: 0.0387 (0.0470) time: 3.1422 data: 0.0085 max mem: 33369 +Epoch: [22] [ 680/1319] eta: 0:33:52 lr: 2.3740289922105044e-05 loss: 0.0430 (0.0470) time: 3.1766 data: 0.0082 max mem: 33369 +Epoch: [22] [ 690/1319] eta: 0:33:20 lr: 2.3731024615197766e-05 loss: 0.0457 (0.0469) time: 3.1444 data: 0.0083 max mem: 33369 +Epoch: [22] [ 700/1319] eta: 0:32:48 lr: 2.3721758906333604e-05 loss: 0.0423 (0.0469) time: 3.1389 data: 0.0080 max mem: 33369 +Epoch: [22] [ 710/1319] eta: 0:32:16 lr: 2.3712492795320653e-05 loss: 0.0423 (0.0469) time: 3.1732 data: 0.0080 max mem: 33369 +Epoch: [22] [ 720/1319] eta: 0:31:45 lr: 2.3703226281966838e-05 loss: 0.0450 (0.0470) time: 3.2060 data: 0.0082 max mem: 33369 +Epoch: [22] [ 730/1319] eta: 0:31:13 lr: 2.36939593660799e-05 loss: 0.0405 (0.0470) time: 3.1887 data: 0.0083 max mem: 33369 +Epoch: [22] [ 740/1319] eta: 0:30:41 lr: 2.3684692047467423e-05 loss: 0.0401 (0.0471) time: 3.2011 data: 0.0086 max mem: 33369 +Epoch: [22] [ 750/1319] eta: 0:30:10 lr: 2.3675424325936787e-05 loss: 0.0422 (0.0470) time: 3.2104 data: 0.0084 max mem: 33369 +Epoch: [22] [ 760/1319] eta: 0:29:38 lr: 2.3666156201295225e-05 loss: 0.0357 (0.0470) time: 3.1706 data: 0.0081 max mem: 33369 +Epoch: [22] [ 770/1319] eta: 0:29:05 lr: 2.3656887673349775e-05 loss: 0.0358 (0.0470) time: 3.1481 data: 0.0081 max mem: 33369 +Epoch: [22] [ 780/1319] eta: 0:28:34 lr: 2.364761874190731e-05 loss: 0.0382 (0.0470) time: 3.1517 data: 0.0082 max mem: 33369 +Epoch: [22] [ 790/1319] eta: 0:28:02 lr: 2.363834940677452e-05 loss: 0.0438 (0.0472) time: 3.1825 data: 0.0080 max mem: 33369 +Epoch: [22] [ 800/1319] eta: 0:27:30 lr: 2.3629079667757912e-05 loss: 0.0442 (0.0471) time: 3.1838 data: 0.0078 max mem: 33369 +Epoch: [22] [ 810/1319] eta: 0:26:58 lr: 2.361980952466383e-05 loss: 0.0428 (0.0471) time: 3.1694 data: 0.0080 max mem: 33369 +Epoch: [22] [ 820/1319] eta: 0:26:26 lr: 2.3610538977298433e-05 loss: 0.0367 (0.0470) time: 3.1803 data: 0.0079 max mem: 33369 +Epoch: [22] [ 830/1319] eta: 0:25:55 lr: 2.3601268025467702e-05 loss: 0.0367 (0.0470) time: 3.2153 data: 0.0078 max mem: 33369 +Epoch: [22] [ 840/1319] eta: 0:25:23 lr: 2.3591996668977443e-05 loss: 0.0411 (0.0469) time: 3.2261 data: 0.0081 max mem: 33369 +Epoch: [22] [ 850/1319] eta: 0:24:52 lr: 2.3582724907633285e-05 loss: 0.0377 (0.0469) time: 3.2049 data: 0.0084 max mem: 33369 +Epoch: [22] [ 860/1319] eta: 0:24:20 lr: 2.3573452741240666e-05 loss: 0.0389 (0.0468) time: 3.1864 data: 0.0082 max mem: 33369 +Epoch: [22] [ 870/1319] eta: 0:23:48 lr: 2.3564180169604865e-05 loss: 0.0421 (0.0469) time: 3.1981 data: 0.0080 max mem: 33369 +Epoch: [22] [ 880/1319] eta: 0:23:16 lr: 2.3554907192530968e-05 loss: 0.0450 (0.0470) time: 3.1748 data: 0.0081 max mem: 33369 +Epoch: [22] [ 890/1319] eta: 0:22:44 lr: 2.3545633809823888e-05 loss: 0.0501 (0.0471) time: 3.1400 data: 0.0079 max mem: 33369 +Epoch: [22] [ 900/1319] eta: 0:22:12 lr: 2.353636002128836e-05 loss: 0.0385 (0.0470) time: 3.1611 data: 0.0080 max mem: 33369 +Epoch: [22] [ 910/1319] eta: 0:21:40 lr: 2.3527085826728933e-05 loss: 0.0380 (0.0470) time: 3.1641 data: 0.0089 max mem: 33369 +Epoch: [22] [ 920/1319] eta: 0:21:09 lr: 2.351781122594998e-05 loss: 0.0455 (0.0474) time: 3.1649 data: 0.0088 max mem: 33369 +Epoch: [22] [ 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33369 +Epoch: [22] [1010/1319] eta: 0:16:21 lr: 2.3434321506693e-05 loss: 0.0372 (0.0471) time: 3.1538 data: 0.0077 max mem: 33369 +Epoch: [22] [1020/1319] eta: 0:15:49 lr: 2.342504283291958e-05 loss: 0.0345 (0.0470) time: 3.1521 data: 0.0076 max mem: 33369 +Epoch: [22] [1030/1319] eta: 0:15:18 lr: 2.3415763750762803e-05 loss: 0.0331 (0.0470) time: 3.1679 data: 0.0077 max mem: 33369 +Epoch: [22] [1040/1319] eta: 0:14:46 lr: 2.3406484260024864e-05 loss: 0.0364 (0.0470) time: 3.1830 data: 0.0077 max mem: 33369 +Epoch: [22] [1050/1319] eta: 0:14:14 lr: 2.3397204360507778e-05 loss: 0.0440 (0.0470) time: 3.1682 data: 0.0082 max mem: 33369 +Epoch: [22] [1060/1319] eta: 0:13:42 lr: 2.3387924052013375e-05 loss: 0.0431 (0.0469) time: 3.1593 data: 0.0087 max mem: 33369 +Epoch: [22] [1070/1319] eta: 0:13:10 lr: 2.3378643334343302e-05 loss: 0.0404 (0.0469) time: 3.1709 data: 0.0086 max mem: 33369 +Epoch: [22] [1080/1319] eta: 0:12:39 lr: 2.3369362207299018e-05 loss: 0.0404 (0.0468) time: 3.1534 data: 0.0086 max mem: 33369 +Epoch: [22] [1090/1319] eta: 0:12:07 lr: 2.3360080670681804e-05 loss: 0.0376 (0.0468) time: 3.1894 data: 0.0083 max mem: 33369 +Epoch: [22] [1100/1319] eta: 0:11:35 lr: 2.335079872429276e-05 loss: 0.0365 (0.0467) time: 3.2055 data: 0.0082 max mem: 33369 +Epoch: [22] [1110/1319] eta: 0:11:03 lr: 2.334151636793279e-05 loss: 0.0400 (0.0467) time: 3.1618 data: 0.0081 max mem: 33369 +Epoch: [22] [1120/1319] eta: 0:10:32 lr: 2.333223360140262e-05 loss: 0.0481 (0.0467) time: 3.1581 data: 0.0077 max mem: 33369 +Epoch: [22] [1130/1319] eta: 0:10:00 lr: 2.3322950424502793e-05 loss: 0.0543 (0.0467) time: 3.1838 data: 0.0079 max mem: 33369 +Epoch: [22] [1140/1319] eta: 0:09:28 lr: 2.3313666837033663e-05 loss: 0.0546 (0.0467) time: 3.1707 data: 0.0088 max mem: 33369 +Epoch: [22] [1150/1319] eta: 0:08:56 lr: 2.33043828387954e-05 loss: 0.0432 (0.0467) time: 3.1612 data: 0.0092 max mem: 33369 +Epoch: [22] [1160/1319] eta: 0:08:25 lr: 2.3295098429587987e-05 loss: 0.0426 (0.0467) time: 3.1697 data: 0.0092 max mem: 33369 +Epoch: [22] [1170/1319] eta: 0:07:53 lr: 2.328581360921123e-05 loss: 0.0402 (0.0467) time: 3.1668 data: 0.0087 max mem: 33369 +Epoch: [22] [1180/1319] eta: 0:07:21 lr: 2.327652837746473e-05 loss: 0.0432 (0.0469) time: 3.1853 data: 0.0080 max mem: 33369 +Epoch: [22] [1190/1319] eta: 0:06:49 lr: 2.3267242734147912e-05 loss: 0.0430 (0.0468) time: 3.1913 data: 0.0077 max mem: 33369 +Epoch: [22] [1200/1319] eta: 0:06:17 lr: 2.325795667906002e-05 loss: 0.0412 (0.0468) time: 3.1468 data: 0.0077 max mem: 33369 +Epoch: [22] [1210/1319] eta: 0:05:46 lr: 2.3248670212000107e-05 loss: 0.0452 (0.0469) time: 3.1584 data: 0.0081 max mem: 33369 +Epoch: [22] [1220/1319] eta: 0:05:14 lr: 2.3239383332767037e-05 loss: 0.0478 (0.0469) time: 3.1619 data: 0.0085 max mem: 33369 +Epoch: [22] [1230/1319] eta: 0:04:42 lr: 2.323009604115948e-05 loss: 0.0434 (0.0468) time: 3.1579 data: 0.0081 max mem: 33369 +Epoch: [22] [1240/1319] eta: 0:04:10 lr: 2.322080833697593e-05 loss: 0.0413 (0.0468) time: 3.1626 data: 0.0078 max mem: 33369 +Epoch: [22] [1250/1319] eta: 0:03:39 lr: 2.3211520220014678e-05 loss: 0.0413 (0.0470) time: 3.1511 data: 0.0079 max mem: 33369 +Epoch: [22] [1260/1319] eta: 0:03:07 lr: 2.320223169007385e-05 loss: 0.0375 (0.0469) time: 3.1652 data: 0.0082 max mem: 33369 +Epoch: [22] [1270/1319] eta: 0:02:35 lr: 2.319294274695137e-05 loss: 0.0383 (0.0469) time: 3.1700 data: 0.0082 max mem: 33369 +Epoch: [22] [1280/1319] eta: 0:02:03 lr: 2.318365339044496e-05 loss: 0.0418 (0.0468) time: 3.1866 data: 0.0079 max mem: 33369 +Epoch: [22] [1290/1319] eta: 0:01:32 lr: 2.3174363620352174e-05 loss: 0.0445 (0.0469) time: 3.1782 data: 0.0082 max mem: 33369 +Epoch: [22] [1300/1319] eta: 0:01:00 lr: 2.3165073436470368e-05 loss: 0.0454 (0.0468) time: 3.1654 data: 0.0082 max mem: 33369 +Epoch: [22] [1310/1319] eta: 0:00:28 lr: 2.3155782838596706e-05 loss: 0.0448 (0.0469) time: 3.1701 data: 0.0079 max mem: 33369 +Epoch: [22] Total time: 1:09:49 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 2:11:10 time: 3.0588 data: 2.7678 max mem: 33369 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 100/2573] eta: 0:04:23 time: 0.0765 data: 0.0015 max mem: 33369 +Test: [ 200/2573] eta: 0:03:41 time: 0.0793 data: 0.0016 max mem: 33369 +Test: [ 300/2573] eta: 0:03:19 time: 0.0800 data: 0.0014 max mem: 33369 +Test: [ 400/2573] eta: 0:03:06 time: 0.0803 data: 0.0015 max mem: 33369 +Test: [ 500/2573] eta: 0:02:54 time: 0.0788 data: 0.0015 max mem: 33369 +Test: [ 600/2573] eta: 0:02:44 time: 0.0787 data: 0.0015 max mem: 33369 +Test: [ 700/2573] eta: 0:02:35 time: 0.0793 data: 0.0015 max mem: 33369 +Test: [ 800/2573] eta: 0:02:26 time: 0.0823 data: 0.0014 max mem: 33369 +Test: [ 900/2573] eta: 0:02:17 time: 0.0788 data: 0.0014 max mem: 33369 +Test: [1000/2573] eta: 0:02:09 time: 0.0789 data: 0.0015 max mem: 33369 +Test: [1100/2573] eta: 0:02:00 time: 0.0785 data: 0.0014 max mem: 33369 +Test: [1200/2573] eta: 0:01:52 time: 0.0793 data: 0.0014 max mem: 33369 +Test: [1300/2573] eta: 0:01:43 time: 0.0796 data: 0.0013 max mem: 33369 +Test: [1400/2573] eta: 0:01:35 time: 0.0778 data: 0.0015 max mem: 33369 +Test: [1500/2573] eta: 0:01:27 time: 0.0798 data: 0.0014 max mem: 33369 +Test: [1600/2573] eta: 0:01:18 time: 0.0819 data: 0.0014 max mem: 33369 +Test: [1700/2573] eta: 0:01:10 time: 0.0772 data: 0.0014 max mem: 33369 +Test: [1800/2573] eta: 0:01:02 time: 0.0810 data: 0.0015 max mem: 33369 +Test: [1900/2573] eta: 0:00:54 time: 0.0780 data: 0.0015 max mem: 33369 +Test: [2000/2573] eta: 0:00:46 time: 0.0798 data: 0.0014 max mem: 33369 +Test: [2100/2573] eta: 0:00:38 time: 0.0808 data: 0.0014 max mem: 33369 +Test: [2200/2573] eta: 0:00:30 time: 0.0801 data: 0.0014 max mem: 33369 +Test: [2300/2573] eta: 0:00:21 time: 0.0818 data: 0.0015 max mem: 33369 +Test: [2400/2573] eta: 0:00:13 time: 0.0763 data: 0.0014 max mem: 33369 +Test: [2500/2573] eta: 0:00:05 time: 0.0790 data: 0.0015 max mem: 33369 +Test: Total time: 0:03:27 +Final results: +Mean IoU is 63.06 + + precision@0.5 = 70.55 + precision@0.6 = 65.01 + precision@0.7 = 58.11 + precision@0.8 = 46.45 + precision@0.9 = 23.08 + overall IoU = 61.26 + +Average object IoU 63.06486780453755 +Overall IoU 61.25510025024414 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [23] [ 0/1319] eta: 3:17:16 lr: 2.3147420946379584e-05 loss: 0.0816 (0.0816) time: 8.9735 data: 2.2117 max mem: 33369 +Epoch: [23] [ 10/1319] eta: 1:20:52 lr: 2.313812956136191e-05 loss: 0.0346 (0.0392) time: 3.7071 data: 0.2079 max mem: 33369 +Epoch: [23] [ 20/1319] eta: 1:14:54 lr: 2.3128837761763095e-05 loss: 0.0401 (0.0441) time: 3.1842 data: 0.0078 max mem: 33369 +Epoch: [23] [ 30/1319] eta: 1:12:25 lr: 2.3119545547379566e-05 loss: 0.0447 (0.0430) time: 3.1869 data: 0.0078 max mem: 33369 +Epoch: [23] [ 40/1319] eta: 1:10:49 lr: 2.3110252918007542e-05 loss: 0.0368 (0.0422) time: 3.1784 data: 0.0077 max mem: 33369 +Epoch: [23] [ 50/1319] eta: 1:09:42 lr: 2.3100959873443074e-05 loss: 0.0364 (0.0416) time: 3.1780 data: 0.0082 max mem: 33369 +Epoch: [23] [ 60/1319] eta: 1:08:56 lr: 2.3091666413482015e-05 loss: 0.0392 (0.0423) time: 3.2102 data: 0.0085 max mem: 33369 +Epoch: [23] [ 70/1319] eta: 1:08:09 lr: 2.3082372537920018e-05 loss: 0.0394 (0.0422) time: 3.2198 data: 0.0086 max mem: 33369 +Epoch: [23] [ 80/1319] eta: 1:07:31 lr: 2.307307824655256e-05 loss: 0.0411 (0.0424) time: 3.2204 data: 0.0082 max mem: 33369 +Epoch: [23] [ 90/1319] eta: 1:06:43 lr: 2.3063783539174907e-05 loss: 0.0387 (0.0419) time: 3.1971 data: 0.0079 max mem: 33369 +Epoch: [23] [ 100/1319] eta: 1:06:02 lr: 2.3054488415582145e-05 loss: 0.0346 (0.0417) time: 3.1737 data: 0.0081 max mem: 33369 +Epoch: [23] [ 110/1319] eta: 1:05:23 lr: 2.3045192875569164e-05 loss: 0.0347 (0.0413) time: 3.1901 data: 0.0083 max mem: 33369 +Epoch: [23] [ 120/1319] eta: 1:04:44 lr: 2.3035896918930662e-05 loss: 0.0359 (0.0422) time: 3.1859 data: 0.0085 max mem: 33369 +Epoch: [23] [ 130/1319] eta: 1:04:06 lr: 2.3026600545461138e-05 loss: 0.0380 (0.0427) time: 3.1771 data: 0.0086 max mem: 33369 +Epoch: [23] [ 140/1319] eta: 1:03:34 lr: 2.3017303754954915e-05 loss: 0.0362 (0.0425) time: 3.2076 data: 0.0084 max mem: 33369 +Epoch: [23] [ 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data: 0.0081 max mem: 33369 +Epoch: [23] [ 310/1319] eta: 0:53:54 lr: 2.2859194309475363e-05 loss: 0.0376 (0.0442) time: 3.2122 data: 0.0081 max mem: 33369 +Epoch: [23] [ 320/1319] eta: 0:53:21 lr: 2.2849889976913045e-05 loss: 0.0461 (0.0444) time: 3.1968 data: 0.0081 max mem: 33369 +Epoch: [23] [ 330/1319] eta: 0:52:48 lr: 2.2840585223368763e-05 loss: 0.0460 (0.0445) time: 3.1620 data: 0.0079 max mem: 33369 +Epoch: [23] [ 340/1319] eta: 0:52:16 lr: 2.2831280048632893e-05 loss: 0.0364 (0.0443) time: 3.1873 data: 0.0078 max mem: 33369 +Epoch: [23] [ 350/1319] eta: 0:51:45 lr: 2.282197445249563e-05 loss: 0.0348 (0.0441) time: 3.2281 data: 0.0083 max mem: 33369 +Epoch: [23] [ 360/1319] eta: 0:51:12 lr: 2.2812668434746943e-05 loss: 0.0383 (0.0439) time: 3.2104 data: 0.0083 max mem: 33369 +Epoch: [23] [ 370/1319] eta: 0:50:40 lr: 2.2803361995176614e-05 loss: 0.0390 (0.0441) time: 3.1945 data: 0.0087 max mem: 33369 +Epoch: [23] [ 380/1319] eta: 0:50:08 lr: 2.279405513357423e-05 loss: 0.0459 (0.0443) time: 3.2051 data: 0.0086 max mem: 33369 +Epoch: [23] [ 390/1319] eta: 0:49:36 lr: 2.278474784972917e-05 loss: 0.0384 (0.0441) time: 3.2022 data: 0.0083 max mem: 33369 +Epoch: [23] [ 400/1319] eta: 0:49:03 lr: 2.277544014343061e-05 loss: 0.0373 (0.0442) time: 3.1859 data: 0.0086 max mem: 33369 +Epoch: [23] [ 410/1319] eta: 0:48:31 lr: 2.2766132014467546e-05 loss: 0.0414 (0.0441) time: 3.1713 data: 0.0082 max mem: 33369 +Epoch: [23] [ 420/1319] eta: 0:47:57 lr: 2.2756823462628737e-05 loss: 0.0409 (0.0442) time: 3.1541 data: 0.0081 max mem: 33369 +Epoch: [23] [ 430/1319] eta: 0:47:26 lr: 2.2747514487702767e-05 loss: 0.0429 (0.0442) time: 3.1828 data: 0.0081 max mem: 33369 +Epoch: [23] [ 440/1319] eta: 0:46:54 lr: 2.2738205089478008e-05 loss: 0.0407 (0.0442) time: 3.2175 data: 0.0082 max mem: 33369 +Epoch: [23] [ 450/1319] eta: 0:46:21 lr: 2.272889526774264e-05 loss: 0.0364 (0.0441) time: 3.1785 data: 0.0084 max mem: 33369 +Epoch: [23] [ 460/1319] eta: 0:45:49 lr: 2.2719585022284628e-05 loss: 0.0336 (0.0440) time: 3.1779 data: 0.0082 max mem: 33369 +Epoch: [23] [ 470/1319] eta: 0:45:16 lr: 2.2710274352891738e-05 loss: 0.0404 (0.0440) time: 3.1702 data: 0.0083 max mem: 33369 +Epoch: [23] [ 480/1319] eta: 0:44:44 lr: 2.2700963259351535e-05 loss: 0.0407 (0.0439) time: 3.1658 data: 0.0084 max mem: 33369 +Epoch: [23] [ 490/1319] eta: 0:44:11 lr: 2.269165174145138e-05 loss: 0.0362 (0.0438) time: 3.1766 data: 0.0079 max mem: 33369 +Epoch: [23] [ 500/1319] eta: 0:43:39 lr: 2.2682339798978432e-05 loss: 0.0408 (0.0440) time: 3.1719 data: 0.0082 max mem: 33369 +Epoch: [23] [ 510/1319] eta: 0:43:06 lr: 2.2673027431719644e-05 loss: 0.0439 (0.0441) time: 3.1586 data: 0.0083 max mem: 33369 +Epoch: [23] [ 520/1319] eta: 0:42:34 lr: 2.266371463946176e-05 loss: 0.0437 (0.0441) time: 3.1607 data: 0.0081 max mem: 33369 +Epoch: [23] [ 530/1319] eta: 0:42:01 lr: 2.2654401421991334e-05 loss: 0.0480 (0.0442) time: 3.1774 data: 0.0085 max mem: 33369 +Epoch: [23] [ 540/1319] eta: 0:41:29 lr: 2.2645087779094697e-05 loss: 0.0446 (0.0442) time: 3.1906 data: 0.0083 max mem: 33369 +Epoch: [23] [ 550/1319] eta: 0:40:57 lr: 2.263577371055799e-05 loss: 0.0403 (0.0442) time: 3.1843 data: 0.0082 max mem: 33369 +Epoch: [23] [ 560/1319] eta: 0:40:25 lr: 2.262645921616714e-05 loss: 0.0384 (0.0443) time: 3.1717 data: 0.0083 max mem: 33369 +Epoch: [23] [ 570/1319] eta: 0:39:53 lr: 2.2617144295707877e-05 loss: 0.0391 (0.0443) time: 3.1820 data: 0.0081 max mem: 33369 +Epoch: [23] [ 580/1319] eta: 0:39:21 lr: 2.2607828948965706e-05 loss: 0.0391 (0.0444) time: 3.1890 data: 0.0083 max mem: 33369 +Epoch: [23] [ 590/1319] eta: 0:38:49 lr: 2.259851317572595e-05 loss: 0.0370 (0.0445) time: 3.1974 data: 0.0083 max mem: 33369 +Epoch: [23] [ 600/1319] eta: 0:38:17 lr: 2.2589196975773708e-05 loss: 0.0399 (0.0448) time: 3.1791 data: 0.0079 max mem: 33369 +Epoch: [23] [ 610/1319] eta: 0:37:44 lr: 2.257988034889388e-05 loss: 0.0344 (0.0446) time: 3.1753 data: 0.0079 max mem: 33369 +Epoch: [23] [ 620/1319] eta: 0:37:12 lr: 2.2570563294871165e-05 loss: 0.0329 (0.0446) time: 3.1675 data: 0.0077 max mem: 33369 +Epoch: [23] [ 630/1319] eta: 0:36:40 lr: 2.256124581349004e-05 loss: 0.0420 (0.0445) time: 3.1822 data: 0.0078 max mem: 33369 +Epoch: [23] [ 640/1319] eta: 0:36:08 lr: 2.2551927904534776e-05 loss: 0.0420 (0.0450) time: 3.1726 data: 0.0081 max mem: 33369 +Epoch: [23] [ 650/1319] eta: 0:35:36 lr: 2.254260956778945e-05 loss: 0.0378 (0.0449) time: 3.1784 data: 0.0080 max mem: 33369 +Epoch: [23] [ 660/1319] eta: 0:35:04 lr: 2.253329080303792e-05 loss: 0.0353 (0.0448) time: 3.1973 data: 0.0078 max mem: 33369 +Epoch: [23] [ 670/1319] eta: 0:34:32 lr: 2.252397161006384e-05 loss: 0.0388 (0.0448) time: 3.1789 data: 0.0080 max mem: 33369 +Epoch: [23] [ 680/1319] eta: 0:34:00 lr: 2.251465198865064e-05 loss: 0.0421 (0.0447) time: 3.1754 data: 0.0081 max mem: 33369 +Epoch: [23] [ 690/1319] eta: 0:33:28 lr: 2.250533193858157e-05 loss: 0.0366 (0.0448) time: 3.1728 data: 0.0083 max mem: 33369 +Epoch: [23] [ 700/1319] eta: 0:32:56 lr: 2.2496011459639643e-05 loss: 0.0366 (0.0448) time: 3.1759 data: 0.0085 max mem: 33369 +Epoch: [23] [ 710/1319] eta: 0:32:23 lr: 2.2486690551607674e-05 loss: 0.0389 (0.0449) time: 3.1644 data: 0.0077 max mem: 33369 +Epoch: [23] [ 720/1319] eta: 0:31:51 lr: 2.2477369214268278e-05 loss: 0.0379 (0.0450) time: 3.1569 data: 0.0076 max mem: 33369 +Epoch: [23] [ 730/1319] eta: 0:31:19 lr: 2.246804744740384e-05 loss: 0.0377 (0.0450) time: 3.1664 data: 0.0082 max mem: 33369 +Epoch: [23] [ 740/1319] eta: 0:30:47 lr: 2.245872525079654e-05 loss: 0.0446 (0.0450) time: 3.1614 data: 0.0079 max mem: 33369 +Epoch: [23] [ 750/1319] eta: 0:30:15 lr: 2.244940262422835e-05 loss: 0.0412 (0.0450) time: 3.1642 data: 0.0080 max mem: 33369 +Epoch: [23] [ 760/1319] eta: 0:29:43 lr: 2.244007956748104e-05 loss: 0.0371 (0.0449) time: 3.1712 data: 0.0082 max mem: 33369 +Epoch: [23] [ 770/1319] eta: 0:29:11 lr: 2.243075608033615e-05 loss: 0.0371 (0.0449) time: 3.1592 data: 0.0079 max mem: 33369 +Epoch: [23] [ 780/1319] eta: 0:28:39 lr: 2.242143216257503e-05 loss: 0.0400 (0.0449) time: 3.1675 data: 0.0079 max mem: 33369 +Epoch: [23] [ 790/1319] eta: 0:28:07 lr: 2.2412107813978792e-05 loss: 0.0436 (0.0450) time: 3.1859 data: 0.0081 max mem: 33369 +Epoch: [23] [ 800/1319] eta: 0:27:35 lr: 2.240278303432835e-05 loss: 0.0451 (0.0450) time: 3.1655 data: 0.0079 max mem: 33369 +Epoch: [23] [ 810/1319] eta: 0:27:03 lr: 2.2393457823404408e-05 loss: 0.0462 (0.0451) time: 3.1838 data: 0.0086 max mem: 33369 +Epoch: [23] [ 820/1319] eta: 0:26:31 lr: 2.2384132180987457e-05 loss: 0.0401 (0.0450) time: 3.2057 data: 0.0093 max mem: 33369 +Epoch: [23] [ 830/1319] eta: 0:25:59 lr: 2.2374806106857758e-05 loss: 0.0418 (0.0453) time: 3.1664 data: 0.0089 max mem: 33369 +Epoch: [23] [ 840/1319] eta: 0:25:27 lr: 2.2365479600795384e-05 loss: 0.0530 (0.0454) time: 3.1858 data: 0.0082 max mem: 33369 +Epoch: [23] [ 850/1319] eta: 0:24:55 lr: 2.2356152662580173e-05 loss: 0.0383 (0.0453) time: 3.1751 data: 0.0076 max mem: 33369 +Epoch: [23] [ 860/1319] eta: 0:24:23 lr: 2.234682529199176e-05 loss: 0.0371 (0.0452) time: 3.1641 data: 0.0078 max mem: 33369 +Epoch: [23] [ 870/1319] eta: 0:23:51 lr: 2.2337497488809557e-05 loss: 0.0412 (0.0452) time: 3.1983 data: 0.0079 max mem: 33369 +Epoch: [23] [ 880/1319] eta: 0:23:19 lr: 2.232816925281277e-05 loss: 0.0489 (0.0453) time: 3.1919 data: 0.0078 max mem: 33369 +Epoch: [23] [ 890/1319] eta: 0:22:48 lr: 2.2318840583780386e-05 loss: 0.0429 (0.0453) time: 3.1922 data: 0.0079 max mem: 33369 +Epoch: [23] [ 900/1319] eta: 0:22:15 lr: 2.2309511481491173e-05 loss: 0.0429 (0.0453) time: 3.1762 data: 0.0082 max mem: 33369 +Epoch: [23] [ 910/1319] eta: 0:21:43 lr: 2.2300181945723685e-05 loss: 0.0380 (0.0452) time: 3.1571 data: 0.0082 max mem: 33369 +Epoch: [23] [ 920/1319] eta: 0:21:12 lr: 2.2290851976256266e-05 loss: 0.0380 (0.0452) time: 3.1888 data: 0.0080 max mem: 33369 +Epoch: [23] [ 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mem: 33369 +Epoch: [23] [1010/1319] eta: 0:16:24 lr: 2.2206862697871013e-05 loss: 0.0445 (0.0453) time: 3.1729 data: 0.0078 max mem: 33369 +Epoch: [23] [1020/1319] eta: 0:15:53 lr: 2.2197528379165116e-05 loss: 0.0436 (0.0453) time: 3.1709 data: 0.0079 max mem: 33369 +Epoch: [23] [1030/1319] eta: 0:15:21 lr: 2.218819362430666e-05 loss: 0.0396 (0.0452) time: 3.1942 data: 0.0082 max mem: 33369 +Epoch: [23] [1040/1319] eta: 0:14:49 lr: 2.217885843307136e-05 loss: 0.0387 (0.0452) time: 3.1711 data: 0.0081 max mem: 33369 +Epoch: [23] [1050/1319] eta: 0:14:17 lr: 2.2169522805234726e-05 loss: 0.0461 (0.0452) time: 3.1657 data: 0.0083 max mem: 33369 +Epoch: [23] [1060/1319] eta: 0:13:45 lr: 2.2160186740572026e-05 loss: 0.0423 (0.0451) time: 3.1645 data: 0.0083 max mem: 33369 +Epoch: [23] [1070/1319] eta: 0:13:13 lr: 2.215085023885832e-05 loss: 0.0442 (0.0453) time: 3.1710 data: 0.0080 max mem: 33369 +Epoch: [23] [1080/1319] eta: 0:12:41 lr: 2.2141513299868444e-05 loss: 0.0483 (0.0452) time: 3.1723 data: 0.0083 max mem: 33369 +Epoch: [23] [1090/1319] eta: 0:12:09 lr: 2.2132175923377022e-05 loss: 0.0371 (0.0452) time: 3.1837 data: 0.0081 max mem: 33369 +Epoch: [23] [1100/1319] eta: 0:11:37 lr: 2.2122838109158445e-05 loss: 0.0381 (0.0452) time: 3.1864 data: 0.0075 max mem: 33369 +Epoch: [23] [1110/1319] eta: 0:11:06 lr: 2.211349985698688e-05 loss: 0.0432 (0.0452) time: 3.1764 data: 0.0083 max mem: 33369 +Epoch: [23] [1120/1319] eta: 0:10:34 lr: 2.2104161166636274e-05 loss: 0.0428 (0.0452) time: 3.1744 data: 0.0091 max mem: 33369 +Epoch: [23] [1130/1319] eta: 0:10:02 lr: 2.2094822037880365e-05 loss: 0.0400 (0.0452) time: 3.1212 data: 0.0084 max mem: 33369 +Epoch: [23] [1140/1319] eta: 0:09:30 lr: 2.2085482470492644e-05 loss: 0.0456 (0.0452) time: 3.1561 data: 0.0082 max mem: 33369 +Epoch: [23] [1150/1319] eta: 0:08:58 lr: 2.20761424642464e-05 loss: 0.0406 (0.0452) time: 3.1920 data: 0.0080 max mem: 33369 +Epoch: [23] [1160/1319] eta: 0:08:26 lr: 2.2066802018914685e-05 loss: 0.0340 (0.0453) time: 3.2195 data: 0.0074 max mem: 33369 +Epoch: [23] [1170/1319] eta: 0:07:54 lr: 2.2057461134270328e-05 loss: 0.0367 (0.0454) time: 3.2107 data: 0.0074 max mem: 33369 +Epoch: [23] [1180/1319] eta: 0:07:22 lr: 2.2048119810085938e-05 loss: 0.0390 (0.0454) time: 3.1816 data: 0.0075 max mem: 33369 +Epoch: [23] [1190/1319] eta: 0:06:51 lr: 2.2038778046133896e-05 loss: 0.0436 (0.0454) time: 3.1859 data: 0.0075 max mem: 33369 +Epoch: [23] [1200/1319] eta: 0:06:19 lr: 2.2029435842186362e-05 loss: 0.0449 (0.0454) time: 3.1602 data: 0.0078 max mem: 33369 +Epoch: [23] [1210/1319] eta: 0:05:47 lr: 2.2020093198015273e-05 loss: 0.0390 (0.0454) time: 3.1371 data: 0.0079 max mem: 33369 +Epoch: [23] [1220/1319] eta: 0:05:15 lr: 2.2010750113392324e-05 loss: 0.0382 (0.0453) time: 3.1515 data: 0.0077 max mem: 33369 +Epoch: [23] [1230/1319] eta: 0:04:43 lr: 2.2001406588088997e-05 loss: 0.0412 (0.0453) time: 3.1547 data: 0.0080 max mem: 33369 +Epoch: [23] [1240/1319] eta: 0:04:11 lr: 2.199206262187655e-05 loss: 0.0394 (0.0453) time: 3.1487 data: 0.0084 max mem: 33369 +Epoch: [23] [1250/1319] eta: 0:03:39 lr: 2.1982718214526003e-05 loss: 0.0394 (0.0453) time: 3.1625 data: 0.0080 max mem: 33369 +Epoch: [23] [1260/1319] eta: 0:03:07 lr: 2.1973373365808168e-05 loss: 0.0443 (0.0453) time: 3.1732 data: 0.0076 max mem: 33369 +Epoch: [23] [1270/1319] eta: 0:02:36 lr: 2.1964028075493602e-05 loss: 0.0385 (0.0453) time: 3.1921 data: 0.0078 max mem: 33369 +Epoch: [23] [1280/1319] eta: 0:02:04 lr: 2.1954682343352655e-05 loss: 0.0362 (0.0453) time: 3.1720 data: 0.0078 max mem: 33369 +Epoch: [23] [1290/1319] eta: 0:01:32 lr: 2.1945336169155447e-05 loss: 0.0359 (0.0452) time: 3.1925 data: 0.0077 max mem: 33369 +Epoch: [23] [1300/1319] eta: 0:01:00 lr: 2.1935989552671862e-05 loss: 0.0372 (0.0452) time: 3.2116 data: 0.0078 max mem: 33369 +Epoch: [23] [1310/1319] eta: 0:00:28 lr: 2.192664249367156e-05 loss: 0.0428 (0.0453) time: 3.1923 data: 0.0077 max mem: 33369 +Epoch: [23] Total time: 1:10:00 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 2:04:47 time: 2.9100 data: 2.7908 max mem: 33369 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 100/2573] eta: 0:04:21 time: 0.0765 data: 0.0014 max mem: 33369 +Test: [ 200/2573] eta: 0:03:39 time: 0.0783 data: 0.0014 max mem: 33369 +Test: [ 300/2573] eta: 0:03:18 time: 0.0806 data: 0.0014 max mem: 33369 +Test: [ 400/2573] eta: 0:03:05 time: 0.0806 data: 0.0015 max mem: 33369 +Test: [ 500/2573] eta: 0:02:54 time: 0.0802 data: 0.0015 max mem: 33369 +Test: [ 600/2573] eta: 0:02:44 time: 0.0796 data: 0.0016 max mem: 33369 +Test: [ 700/2573] eta: 0:02:35 time: 0.0792 data: 0.0015 max mem: 33369 +Test: [ 800/2573] eta: 0:02:26 time: 0.0823 data: 0.0014 max mem: 33369 +Test: [ 900/2573] eta: 0:02:17 time: 0.0799 data: 0.0015 max mem: 33369 +Test: [1000/2573] eta: 0:02:09 time: 0.0798 data: 0.0014 max mem: 33369 +Test: [1100/2573] eta: 0:02:00 time: 0.0783 data: 0.0014 max mem: 33369 +Test: [1200/2573] eta: 0:01:52 time: 0.0801 data: 0.0014 max mem: 33369 +Test: [1300/2573] eta: 0:01:43 time: 0.0798 data: 0.0015 max mem: 33369 +Test: [1400/2573] eta: 0:01:35 time: 0.0774 data: 0.0014 max mem: 33369 +Test: [1500/2573] eta: 0:01:27 time: 0.0788 data: 0.0015 max mem: 33369 +Test: [1600/2573] eta: 0:01:19 time: 0.0821 data: 0.0014 max mem: 33369 +Test: [1700/2573] eta: 0:01:10 time: 0.0778 data: 0.0014 max mem: 33369 +Test: [1800/2573] eta: 0:01:02 time: 0.0808 data: 0.0014 max mem: 33369 +Test: [1900/2573] eta: 0:00:54 time: 0.0783 data: 0.0014 max mem: 33369 +Test: [2000/2573] eta: 0:00:46 time: 0.0802 data: 0.0014 max mem: 33369 +Test: [2100/2573] eta: 0:00:38 time: 0.0817 data: 0.0014 max mem: 33369 +Test: [2200/2573] eta: 0:00:30 time: 0.0809 data: 0.0015 max mem: 33369 +Test: [2300/2573] eta: 0:00:22 time: 0.0827 data: 0.0016 max mem: 33369 +Test: [2400/2573] eta: 0:00:13 time: 0.0764 data: 0.0015 max mem: 33369 +Test: [2500/2573] eta: 0:00:05 time: 0.0788 data: 0.0015 max mem: 33369 +Test: Total time: 0:03:27 +Final results: +Mean IoU is 62.47 + + precision@0.5 = 70.51 + precision@0.6 = 64.62 + precision@0.7 = 57.43 + precision@0.8 = 46.57 + precision@0.9 = 22.92 + overall IoU = 60.79 + +Average object IoU 62.470745160626876 +Overall IoU 60.792503356933594 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [24] [ 0/1319] eta: 2:59:27 lr: 2.1918229762028934e-05 loss: 0.0606 (0.0606) time: 8.1635 data: 2.3081 max mem: 33369 +Epoch: [24] [ 10/1319] eta: 1:20:18 lr: 2.1908881861611456e-05 loss: 0.0397 (0.0482) time: 3.6808 data: 0.2169 max mem: 33369 +Epoch: [24] [ 20/1319] eta: 1:14:25 lr: 2.1899533518007982e-05 loss: 0.0397 (0.0472) time: 3.2012 data: 0.0078 max mem: 33369 +Epoch: [24] [ 30/1319] eta: 1:11:57 lr: 2.189018473098726e-05 loss: 0.0412 (0.0479) time: 3.1673 data: 0.0080 max mem: 33369 +Epoch: [24] [ 40/1319] eta: 1:10:20 lr: 2.188083550031783e-05 loss: 0.0365 (0.0448) time: 3.1550 data: 0.0083 max mem: 33369 +Epoch: [24] [ 50/1319] eta: 1:09:14 lr: 2.1871485825767997e-05 loss: 0.0379 (0.0458) time: 3.1557 data: 0.0089 max mem: 33369 +Epoch: [24] [ 60/1319] eta: 1:08:14 lr: 2.1862135707105826e-05 loss: 0.0408 (0.0452) time: 3.1535 data: 0.0088 max mem: 33369 +Epoch: [24] [ 70/1319] eta: 1:07:33 lr: 2.1852785144099174e-05 loss: 0.0364 (0.0441) time: 3.1737 data: 0.0078 max mem: 33369 +Epoch: [24] [ 80/1319] eta: 1:06:45 lr: 2.184343413651562e-05 loss: 0.0357 (0.0436) time: 3.1741 data: 0.0079 max mem: 33369 +Epoch: [24] [ 90/1319] eta: 1:06:02 lr: 2.1834082684122557e-05 loss: 0.0357 (0.0427) time: 3.1486 data: 0.0083 max mem: 33369 +Epoch: [24] [ 100/1319] eta: 1:05:23 lr: 2.1824730786687132e-05 loss: 0.0395 (0.0426) time: 3.1620 data: 0.0083 max mem: 33369 +Epoch: [24] [ 110/1319] eta: 1:04:49 lr: 2.181537844397624e-05 loss: 0.0401 (0.0435) time: 3.1864 data: 0.0082 max mem: 33369 +Epoch: [24] [ 120/1319] eta: 1:04:10 lr: 2.1806025655756576e-05 loss: 0.0393 (0.0438) time: 3.1727 data: 0.0083 max mem: 33369 +Epoch: [24] [ 130/1319] eta: 1:03:30 lr: 2.1796672421794575e-05 loss: 0.0375 (0.0438) time: 3.1374 data: 0.0082 max mem: 33369 +Epoch: [24] [ 140/1319] eta: 1:02:59 lr: 2.1787318741856443e-05 loss: 0.0375 (0.0437) time: 3.1706 data: 0.0080 max mem: 33369 +Epoch: [24] [ 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33369 +Epoch: [24] [ 230/1319] eta: 0:58:04 lr: 2.1703115514795925e-05 loss: 0.0427 (0.0442) time: 3.1748 data: 0.0076 max mem: 33369 +Epoch: [24] [ 240/1319] eta: 0:57:31 lr: 2.1693757362186356e-05 loss: 0.0393 (0.0441) time: 3.1894 data: 0.0082 max mem: 33369 +Epoch: [24] [ 250/1319] eta: 0:56:58 lr: 2.1684398761013434e-05 loss: 0.0368 (0.0440) time: 3.1745 data: 0.0084 max mem: 33369 +Epoch: [24] [ 260/1319] eta: 0:56:23 lr: 2.1675039711040532e-05 loss: 0.0373 (0.0439) time: 3.1473 data: 0.0079 max mem: 33369 +Epoch: [24] [ 270/1319] eta: 0:55:52 lr: 2.166568021203079e-05 loss: 0.0369 (0.0437) time: 3.1630 data: 0.0080 max mem: 33369 +Epoch: [24] [ 280/1319] eta: 0:55:17 lr: 2.1656320263747106e-05 loss: 0.0333 (0.0434) time: 3.1705 data: 0.0085 max mem: 33369 +Epoch: [24] [ 290/1319] eta: 0:54:44 lr: 2.164695986595215e-05 loss: 0.0375 (0.0435) time: 3.1403 data: 0.0082 max mem: 33369 +Epoch: [24] [ 300/1319] eta: 0:54:09 lr: 2.163759901840832e-05 loss: 0.0403 (0.0437) time: 3.1258 data: 0.0085 max mem: 33369 +Epoch: [24] [ 310/1319] eta: 0:53:36 lr: 2.1628237720877814e-05 loss: 0.0430 (0.0436) time: 3.1337 data: 0.0089 max mem: 33369 +Epoch: [24] [ 320/1319] eta: 0:53:02 lr: 2.161887597312257e-05 loss: 0.0445 (0.0438) time: 3.1330 data: 0.0085 max mem: 33369 +Epoch: [24] [ 330/1319] eta: 0:52:28 lr: 2.160951377490428e-05 loss: 0.0445 (0.0438) time: 3.1196 data: 0.0086 max mem: 33369 +Epoch: [24] [ 340/1319] eta: 0:51:57 lr: 2.160015112598442e-05 loss: 0.0365 (0.0439) time: 3.1601 data: 0.0087 max mem: 33369 +Epoch: [24] [ 350/1319] eta: 0:51:24 lr: 2.1590788026124187e-05 loss: 0.0412 (0.0441) time: 3.1695 data: 0.0082 max mem: 33369 +Epoch: [24] [ 360/1319] eta: 0:50:52 lr: 2.158142447508457e-05 loss: 0.0451 (0.0442) time: 3.1650 data: 0.0079 max mem: 33369 +Epoch: [24] [ 370/1319] eta: 0:50:20 lr: 2.1572060472626296e-05 loss: 0.0435 (0.0442) time: 3.1799 data: 0.0079 max mem: 33369 +Epoch: [24] [ 380/1319] eta: 0:49:47 lr: 2.156269601850986e-05 loss: 0.0435 (0.0441) time: 3.1683 data: 0.0080 max mem: 33369 +Epoch: [24] [ 390/1319] eta: 0:49:16 lr: 2.1553331112495514e-05 loss: 0.0365 (0.0440) time: 3.1789 data: 0.0083 max mem: 33369 +Epoch: [24] [ 400/1319] eta: 0:48:44 lr: 2.1543965754343263e-05 loss: 0.0400 (0.0440) time: 3.1890 data: 0.0084 max mem: 33369 +Epoch: [24] [ 410/1319] eta: 0:48:13 lr: 2.1534599943812868e-05 loss: 0.0412 (0.0440) time: 3.1843 data: 0.0084 max mem: 33369 +Epoch: [24] [ 420/1319] eta: 0:47:40 lr: 2.1525233680663844e-05 loss: 0.0382 (0.0438) time: 3.1785 data: 0.0084 max mem: 33369 +Epoch: [24] [ 430/1319] eta: 0:47:08 lr: 2.151586696465547e-05 loss: 0.0378 (0.0437) time: 3.1667 data: 0.0084 max mem: 33369 +Epoch: [24] [ 440/1319] eta: 0:46:36 lr: 2.1506499795546773e-05 loss: 0.0378 (0.0438) time: 3.1624 data: 0.0086 max mem: 33369 +Epoch: [24] [ 450/1319] eta: 0:46:05 lr: 2.1497132173096545e-05 loss: 0.0384 (0.0437) time: 3.1823 data: 0.0087 max mem: 33369 +Epoch: [24] [ 460/1319] eta: 0:45:32 lr: 2.1487764097063317e-05 loss: 0.0413 (0.0437) time: 3.1752 data: 0.0081 max mem: 33369 +Epoch: [24] [ 470/1319] eta: 0:45:00 lr: 2.1478395567205385e-05 loss: 0.0406 (0.0437) time: 3.1665 data: 0.0081 max mem: 33369 +Epoch: [24] [ 480/1319] eta: 0:44:29 lr: 2.14690265832808e-05 loss: 0.0422 (0.0438) time: 3.1833 data: 0.0085 max mem: 33369 +Epoch: [24] [ 490/1319] eta: 0:43:57 lr: 2.1459657145047365e-05 loss: 0.0452 (0.0437) time: 3.1724 data: 0.0089 max mem: 33369 +Epoch: [24] [ 500/1319] eta: 0:43:24 lr: 2.1450287252262635e-05 loss: 0.0321 (0.0436) time: 3.1493 data: 0.0088 max mem: 33369 +Epoch: [24] [ 510/1319] eta: 0:42:52 lr: 2.144091690468391e-05 loss: 0.0364 (0.0436) time: 3.1535 data: 0.0081 max mem: 33369 +Epoch: [24] [ 520/1319] eta: 0:42:20 lr: 2.1431546102068255e-05 loss: 0.0366 (0.0434) time: 3.1645 data: 0.0079 max mem: 33369 +Epoch: [24] [ 530/1319] eta: 0:41:47 lr: 2.142217484417249e-05 loss: 0.0336 (0.0434) time: 3.1472 data: 0.0079 max mem: 33369 +Epoch: [24] [ 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33369 +Epoch: [24] [ 620/1319] eta: 0:37:00 lr: 2.1337812995256205e-05 loss: 0.0473 (0.0441) time: 3.1877 data: 0.0081 max mem: 33369 +Epoch: [24] [ 630/1319] eta: 0:36:28 lr: 2.1328437171129155e-05 loss: 0.0417 (0.0440) time: 3.1627 data: 0.0080 max mem: 33369 +Epoch: [24] [ 640/1319] eta: 0:35:56 lr: 2.1319060889030465e-05 loss: 0.0371 (0.0439) time: 3.1406 data: 0.0079 max mem: 33369 +Epoch: [24] [ 650/1319] eta: 0:35:25 lr: 2.1309684148713934e-05 loss: 0.0353 (0.0438) time: 3.1834 data: 0.0078 max mem: 33369 +Epoch: [24] [ 660/1319] eta: 0:34:53 lr: 2.130030694993313e-05 loss: 0.0360 (0.0438) time: 3.2183 data: 0.0078 max mem: 33369 +Epoch: [24] [ 670/1319] eta: 0:34:22 lr: 2.129092929244134e-05 loss: 0.0391 (0.0437) time: 3.2078 data: 0.0079 max mem: 33369 +Epoch: [24] [ 680/1319] eta: 0:33:50 lr: 2.1281551175991622e-05 loss: 0.0349 (0.0436) time: 3.1998 data: 0.0078 max mem: 33369 +Epoch: [24] [ 690/1319] eta: 0:33:18 lr: 2.127217260033677e-05 loss: 0.0386 (0.0437) time: 3.1864 data: 0.0084 max mem: 33369 +Epoch: [24] [ 700/1319] eta: 0:32:47 lr: 2.126279356522932e-05 loss: 0.0422 (0.0437) time: 3.1923 data: 0.0086 max mem: 33369 +Epoch: [24] [ 710/1319] eta: 0:32:15 lr: 2.1253414070421574e-05 loss: 0.0367 (0.0436) time: 3.1896 data: 0.0080 max mem: 33369 +Epoch: [24] [ 720/1319] eta: 0:31:43 lr: 2.1244034115665552e-05 loss: 0.0373 (0.0437) time: 3.1832 data: 0.0079 max mem: 33369 +Epoch: [24] [ 730/1319] eta: 0:31:11 lr: 2.1234653700713027e-05 loss: 0.0449 (0.0438) time: 3.1720 data: 0.0084 max mem: 33369 +Epoch: [24] [ 740/1319] eta: 0:30:40 lr: 2.122527282531552e-05 loss: 0.0449 (0.0438) time: 3.1917 data: 0.0083 max mem: 33369 +Epoch: [24] [ 750/1319] eta: 0:30:08 lr: 2.12158914892243e-05 loss: 0.0380 (0.0438) time: 3.1649 data: 0.0078 max mem: 33369 +Epoch: [24] [ 760/1319] eta: 0:29:36 lr: 2.120650969219037e-05 loss: 0.0307 (0.0436) time: 3.1356 data: 0.0078 max mem: 33369 +Epoch: [24] [ 770/1319] eta: 0:29:04 lr: 2.1197127433964487e-05 loss: 0.0317 (0.0435) time: 3.1679 data: 0.0078 max mem: 33369 +Epoch: [24] [ 780/1319] eta: 0:28:32 lr: 2.1187744714297132e-05 loss: 0.0360 (0.0435) time: 3.1584 data: 0.0078 max mem: 33369 +Epoch: [24] [ 790/1319] eta: 0:28:00 lr: 2.117836153293854e-05 loss: 0.0375 (0.0434) time: 3.1796 data: 0.0082 max mem: 33369 +Epoch: [24] [ 800/1319] eta: 0:27:29 lr: 2.1168977889638698e-05 loss: 0.0352 (0.0433) time: 3.1794 data: 0.0083 max mem: 33369 +Epoch: [24] [ 810/1319] eta: 0:26:57 lr: 2.1159593784147318e-05 loss: 0.0322 (0.0432) time: 3.1796 data: 0.0082 max mem: 33369 +Epoch: [24] [ 820/1319] eta: 0:26:25 lr: 2.115020921621386e-05 loss: 0.0384 (0.0431) time: 3.1937 data: 0.0078 max mem: 33369 +Epoch: [24] [ 830/1319] eta: 0:25:53 lr: 2.1140824185587522e-05 loss: 0.0384 (0.0431) time: 3.1866 data: 0.0074 max mem: 33369 +Epoch: [24] [ 840/1319] eta: 0:25:22 lr: 2.113143869201724e-05 loss: 0.0379 (0.0431) time: 3.1730 data: 0.0078 max mem: 33369 +Epoch: [24] [ 850/1319] eta: 0:24:50 lr: 2.11220527352517e-05 loss: 0.0415 (0.0431) time: 3.1718 data: 0.0084 max mem: 33369 +Epoch: [24] [ 860/1319] eta: 0:24:18 lr: 2.111266631503932e-05 loss: 0.0366 (0.0431) time: 3.1935 data: 0.0090 max mem: 33369 +Epoch: [24] [ 870/1319] eta: 0:23:47 lr: 2.1103279431128255e-05 loss: 0.0357 (0.0430) time: 3.2038 data: 0.0090 max mem: 33369 +Epoch: [24] [ 880/1319] eta: 0:23:15 lr: 2.1093892083266405e-05 loss: 0.0357 (0.0430) time: 3.1922 data: 0.0082 max mem: 33369 +Epoch: [24] [ 890/1319] eta: 0:22:43 lr: 2.10845042712014e-05 loss: 0.0349 (0.0429) time: 3.1936 data: 0.0078 max mem: 33369 +Epoch: [24] [ 900/1319] eta: 0:22:11 lr: 2.1075115994680607e-05 loss: 0.0374 (0.0429) time: 3.1866 data: 0.0082 max mem: 33369 +Epoch: [24] [ 910/1319] eta: 0:21:40 lr: 2.106572725345115e-05 loss: 0.0338 (0.0428) time: 3.1842 data: 0.0083 max mem: 33369 +Epoch: [24] [ 920/1319] eta: 0:21:08 lr: 2.105633804725987e-05 loss: 0.0381 (0.0429) time: 3.1738 data: 0.0083 max mem: 33369 +Epoch: [24] [ 930/1319] eta: 0:20:36 lr: 2.104694837585335e-05 loss: 0.0442 (0.0429) time: 3.1796 data: 0.0081 max mem: 33369 +Epoch: [24] [ 940/1319] eta: 0:20:04 lr: 2.1037558238977907e-05 loss: 0.0387 (0.0431) time: 3.1831 data: 0.0081 max mem: 33369 +Epoch: [24] [ 950/1319] eta: 0:19:32 lr: 2.1028167636379597e-05 loss: 0.0389 (0.0431) time: 3.1776 data: 0.0083 max mem: 33369 +Epoch: [24] [ 960/1319] eta: 0:19:01 lr: 2.1018776567804213e-05 loss: 0.0394 (0.0432) time: 3.1763 data: 0.0080 max mem: 33369 +Epoch: [24] [ 970/1319] eta: 0:18:29 lr: 2.1009385032997278e-05 loss: 0.0394 (0.0433) time: 3.1563 data: 0.0081 max mem: 33369 +Epoch: [24] [ 980/1319] eta: 0:17:57 lr: 2.0999993031704057e-05 loss: 0.0400 (0.0433) time: 3.1456 data: 0.0077 max mem: 33369 +Epoch: [24] [ 990/1319] eta: 0:17:25 lr: 2.0990600563669546e-05 loss: 0.0400 (0.0433) time: 3.1575 data: 0.0075 max mem: 33369 +Epoch: [24] [1000/1319] eta: 0:16:53 lr: 2.0981207628638462e-05 loss: 0.0401 (0.0433) time: 3.1853 data: 0.0078 max mem: 33369 +Epoch: [24] [1010/1319] eta: 0:16:22 lr: 2.0971814226355274e-05 loss: 0.0445 (0.0434) time: 3.1857 data: 0.0077 max mem: 33369 +Epoch: [24] [1020/1319] eta: 0:15:50 lr: 2.0962420356564173e-05 loss: 0.0416 (0.0434) time: 3.1853 data: 0.0079 max mem: 33369 +Epoch: [24] [1030/1319] eta: 0:15:18 lr: 2.0953026019009095e-05 loss: 0.0394 (0.0435) time: 3.1798 data: 0.0082 max mem: 33369 +Epoch: [24] [1040/1319] eta: 0:14:46 lr: 2.0943631213433694e-05 loss: 0.0430 (0.0435) time: 3.1281 data: 0.0079 max mem: 33369 +Epoch: [24] [1050/1319] eta: 0:14:14 lr: 2.0934235939581352e-05 loss: 0.0430 (0.0435) time: 3.1364 data: 0.0079 max mem: 33369 +Epoch: [24] [1060/1319] eta: 0:13:42 lr: 2.0924840197195202e-05 loss: 0.0399 (0.0435) time: 3.1748 data: 0.0080 max mem: 33369 +Epoch: [24] [1070/1319] eta: 0:13:11 lr: 2.0915443986018095e-05 loss: 0.0368 (0.0434) time: 3.1672 data: 0.0077 max mem: 33369 +Epoch: [24] [1080/1319] eta: 0:12:39 lr: 2.0906047305792607e-05 loss: 0.0385 (0.0434) time: 3.1776 data: 0.0078 max mem: 33369 +Epoch: [24] [1090/1319] eta: 0:12:07 lr: 2.0896650156261064e-05 loss: 0.0422 (0.0434) time: 3.1627 data: 0.0078 max mem: 33369 +Epoch: [24] [1100/1319] eta: 0:11:35 lr: 2.0887252537165494e-05 loss: 0.0376 (0.0434) time: 3.1535 data: 0.0077 max mem: 33369 +Epoch: [24] [1110/1319] eta: 0:11:03 lr: 2.087785444824768e-05 loss: 0.0376 (0.0434) time: 3.1699 data: 0.0081 max mem: 33369 +Epoch: [24] [1120/1319] eta: 0:10:32 lr: 2.086845588924912e-05 loss: 0.0351 (0.0433) time: 3.2101 data: 0.0088 max mem: 33369 +Epoch: [24] [1130/1319] eta: 0:10:00 lr: 2.0859056859911038e-05 loss: 0.0334 (0.0433) time: 3.2240 data: 0.0090 max mem: 33369 +Epoch: [24] [1140/1319] eta: 0:09:28 lr: 2.0849657359974397e-05 loss: 0.0429 (0.0434) time: 3.2028 data: 0.0081 max mem: 33369 +Epoch: [24] [1150/1319] eta: 0:08:57 lr: 2.084025738917989e-05 loss: 0.0414 (0.0434) time: 3.1902 data: 0.0079 max mem: 33369 +Epoch: [24] [1160/1319] eta: 0:08:25 lr: 2.083085694726791e-05 loss: 0.0367 (0.0433) time: 3.1910 data: 0.0081 max mem: 33369 +Epoch: [24] [1170/1319] eta: 0:07:53 lr: 2.0821456033978605e-05 loss: 0.0381 (0.0433) time: 3.1995 data: 0.0082 max mem: 33369 +Epoch: [24] [1180/1319] eta: 0:07:21 lr: 2.0812054649051834e-05 loss: 0.0396 (0.0433) time: 3.1656 data: 0.0081 max mem: 33369 +Epoch: [24] [1190/1319] eta: 0:06:49 lr: 2.0802652792227197e-05 loss: 0.0454 (0.0434) time: 3.1662 data: 0.0078 max mem: 33369 +Epoch: [24] [1200/1319] eta: 0:06:18 lr: 2.0793250463244006e-05 loss: 0.0454 (0.0434) time: 3.1806 data: 0.0078 max mem: 33369 +Epoch: [24] [1210/1319] eta: 0:05:46 lr: 2.07838476618413e-05 loss: 0.0400 (0.0435) time: 3.1709 data: 0.0083 max mem: 33369 +Epoch: [24] [1220/1319] eta: 0:05:14 lr: 2.077444438775784e-05 loss: 0.0434 (0.0436) time: 3.1702 data: 0.0086 max mem: 33369 +Epoch: [24] [1230/1319] eta: 0:04:42 lr: 2.0765040640732118e-05 loss: 0.0435 (0.0437) time: 3.1454 data: 0.0088 max mem: 33369 +Epoch: [24] [1240/1319] eta: 0:04:11 lr: 2.0755636420502354e-05 loss: 0.0396 (0.0436) time: 3.1634 data: 0.0086 max mem: 33369 +Epoch: [24] [1250/1319] eta: 0:03:39 lr: 2.074623172680648e-05 loss: 0.0397 (0.0437) time: 3.1603 data: 0.0077 max mem: 33369 +Epoch: [24] [1260/1319] eta: 0:03:07 lr: 2.0736826559382146e-05 loss: 0.0445 (0.0438) time: 3.1508 data: 0.0074 max mem: 33369 +Epoch: [24] [1270/1319] eta: 0:02:35 lr: 2.072742091796674e-05 loss: 0.0507 (0.0439) time: 3.1760 data: 0.0078 max mem: 33369 +Epoch: [24] [1280/1319] eta: 0:02:03 lr: 2.071801480229737e-05 loss: 0.0413 (0.0438) time: 3.1754 data: 0.0080 max mem: 33369 +Epoch: [24] [1290/1319] eta: 0:01:32 lr: 2.0708608212110852e-05 loss: 0.0413 (0.0439) time: 3.1900 data: 0.0082 max mem: 33369 +Epoch: [24] [1300/1319] eta: 0:01:00 lr: 2.0699201147143737e-05 loss: 0.0462 (0.0439) time: 3.1965 data: 0.0084 max mem: 33369 +Epoch: [24] [1310/1319] eta: 0:00:28 lr: 2.0689793607132295e-05 loss: 0.0344 (0.0439) time: 3.1653 data: 0.0077 max mem: 33369 +Epoch: [24] Total time: 1:09:50 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 2:26:42 time: 3.4210 data: 3.2690 max mem: 33369 +Test: [ 100/2573] eta: 0:04:30 time: 0.0768 data: 0.0014 max mem: 33369 +Test: [ 200/2573] eta: 0:03:44 time: 0.0794 data: 0.0014 max mem: 33369 +Test: [ 300/2573] eta: 0:03:21 time: 0.0796 data: 0.0014 max mem: 33369 +Test: [ 400/2573] eta: 0:03:06 time: 0.0797 data: 0.0014 max mem: 33369 +Test: [ 500/2573] eta: 0:02:55 time: 0.0789 data: 0.0015 max mem: 33369 +Test: [ 600/2573] eta: 0:02:45 time: 0.0792 data: 0.0015 max mem: 33369 +Test: [ 700/2573] eta: 0:02:36 time: 0.0794 data: 0.0018 max mem: 33369 +Test: [ 800/2573] eta: 0:02:26 time: 0.0812 data: 0.0013 max mem: 33369 +Test: [ 900/2573] eta: 0:02:17 time: 0.0792 data: 0.0015 max mem: 33369 +Test: [1000/2573] eta: 0:02:09 time: 0.0793 data: 0.0015 max mem: 33369 +Test: [1100/2573] eta: 0:02:00 time: 0.0787 data: 0.0015 max mem: 33369 +Test: [1200/2573] eta: 0:01:52 time: 0.0794 data: 0.0014 max mem: 33369 +Test: [1300/2573] eta: 0:01:43 time: 0.0787 data: 0.0014 max mem: 33369 +Test: [1400/2573] eta: 0:01:35 time: 0.0793 data: 0.0015 max mem: 33369 +Test: [1500/2573] eta: 0:01:27 time: 0.0810 data: 0.0016 max mem: 33369 +Test: [1600/2573] eta: 0:01:19 time: 0.0827 data: 0.0015 max mem: 33369 +Test: [1700/2573] eta: 0:01:10 time: 0.0768 data: 0.0014 max mem: 33369 +Test: [1800/2573] eta: 0:01:02 time: 0.0801 data: 0.0014 max mem: 33369 +Test: [1900/2573] eta: 0:00:54 time: 0.0780 data: 0.0016 max mem: 33369 +Test: [2000/2573] eta: 0:00:46 time: 0.0786 data: 0.0014 max mem: 33369 +Test: [2100/2573] eta: 0:00:38 time: 0.0806 data: 0.0014 max mem: 33369 +Test: [2200/2573] eta: 0:00:30 time: 0.0813 data: 0.0015 max mem: 33369 +Test: [2300/2573] eta: 0:00:21 time: 0.0808 data: 0.0015 max mem: 33369 +Test: [2400/2573] eta: 0:00:13 time: 0.0770 data: 0.0015 max mem: 33369 +Test: [2500/2573] eta: 0:00:05 time: 0.0803 data: 0.0014 max mem: 33369 +Test: Total time: 0:03:27 +Final results: +Mean IoU is 63.68 + + precision@0.5 = 71.63 + precision@0.6 = 65.83 + precision@0.7 = 59.15 + precision@0.8 = 47.67 + precision@0.9 = 23.43 + overall IoU = 61.30 + +Average object IoU 63.684755202816255 +Overall IoU 61.299861907958984 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [25] [ 0/1319] eta: 3:11:10 lr: 2.0681326414740886e-05 loss: 0.0382 (0.0382) time: 8.6964 data: 2.5096 max mem: 33369 +Epoch: [25] [ 10/1319] eta: 1:21:36 lr: 2.0671917971417626e-05 loss: 0.0382 (0.0369) time: 3.7405 data: 0.2352 max mem: 33369 +Epoch: [25] [ 20/1319] eta: 1:15:15 lr: 2.0662509052283616e-05 loss: 0.0366 (0.0378) time: 3.2154 data: 0.0076 max mem: 33369 +Epoch: [25] [ 30/1319] eta: 1:12:49 lr: 2.0653099657074033e-05 loss: 0.0310 (0.0355) time: 3.1974 data: 0.0082 max mem: 33369 +Epoch: [25] [ 40/1319] eta: 1:11:06 lr: 2.064368978552377e-05 loss: 0.0292 (0.0360) time: 3.1883 data: 0.0085 max mem: 33369 +Epoch: [25] [ 50/1319] eta: 1:10:02 lr: 2.0634279437367437e-05 loss: 0.0337 (0.0358) time: 3.1892 data: 0.0082 max mem: 33369 +Epoch: [25] [ 60/1319] eta: 1:09:01 lr: 2.0624868612339364e-05 loss: 0.0340 (0.0356) time: 3.1939 data: 0.0087 max mem: 33369 +Epoch: [25] [ 70/1319] eta: 1:08:17 lr: 2.0615457310173584e-05 loss: 0.0341 (0.0358) time: 3.2014 data: 0.0093 max mem: 33369 +Epoch: [25] [ 80/1319] eta: 1:07:21 lr: 2.0606045530603866e-05 loss: 0.0406 (0.0362) time: 3.1785 data: 0.0092 max mem: 33369 +Epoch: [25] [ 90/1319] eta: 1:06:35 lr: 2.059663327336368e-05 loss: 0.0377 (0.0371) time: 3.1455 data: 0.0086 max mem: 33369 +Epoch: [25] [ 100/1319] eta: 1:05:54 lr: 2.058722053818622e-05 loss: 0.0349 (0.0374) time: 3.1735 data: 0.0090 max mem: 33369 +Epoch: [25] [ 110/1319] eta: 1:05:12 lr: 2.0577807324804403e-05 loss: 0.0343 (0.0387) time: 3.1721 data: 0.0098 max mem: 33369 +Epoch: [25] [ 120/1319] eta: 1:04:35 lr: 2.0568393632950847e-05 loss: 0.0420 (0.0390) time: 3.1729 data: 0.0095 max mem: 33369 +Epoch: [25] [ 130/1319] eta: 1:03:55 lr: 2.055897946235788e-05 loss: 0.0389 (0.0390) time: 3.1681 data: 0.0089 max mem: 33369 +Epoch: [25] [ 140/1319] eta: 1:03:19 lr: 2.054956481275756e-05 loss: 0.0329 (0.0385) time: 3.1597 data: 0.0083 max mem: 33369 +Epoch: [25] [ 150/1319] eta: 1:02:45 lr: 2.0540149683881653e-05 loss: 0.0346 (0.0391) time: 3.1865 data: 0.0082 max mem: 33369 +Epoch: [25] [ 160/1319] eta: 1:02:13 lr: 2.0530734075461633e-05 loss: 0.0365 (0.0388) time: 3.2166 data: 0.0085 max mem: 33369 +Epoch: [25] [ 170/1319] eta: 1:01:38 lr: 2.05213179872287e-05 loss: 0.0338 (0.0387) time: 3.2041 data: 0.0082 max mem: 33369 +Epoch: [25] [ 180/1319] eta: 1:01:06 lr: 2.051190141891374e-05 loss: 0.0307 (0.0384) time: 3.1976 data: 0.0082 max mem: 33369 +Epoch: [25] [ 190/1319] eta: 1:00:32 lr: 2.050248437024738e-05 loss: 0.0322 (0.0388) time: 3.2071 data: 0.0084 max mem: 33369 +Epoch: [25] [ 200/1319] eta: 0:59:57 lr: 2.049306684095994e-05 loss: 0.0369 (0.0391) time: 3.1766 data: 0.0083 max mem: 33369 +Epoch: [25] [ 210/1319] eta: 0:59:22 lr: 2.048364883078146e-05 loss: 0.0369 (0.0393) time: 3.1623 data: 0.0084 max mem: 33369 +Epoch: [25] [ 220/1319] eta: 0:58:50 lr: 2.0474230339441687e-05 loss: 0.0389 (0.0394) time: 3.1850 data: 0.0085 max mem: 33369 +Epoch: [25] [ 230/1319] eta: 0:58:15 lr: 2.0464811366670074e-05 loss: 0.0345 (0.0392) time: 3.1861 data: 0.0086 max mem: 33369 +Epoch: [25] [ 240/1319] eta: 0:57:42 lr: 2.0455391912195788e-05 loss: 0.0355 (0.0391) time: 3.1761 data: 0.0086 max mem: 33369 +Epoch: [25] [ 250/1319] eta: 0:57:08 lr: 2.0445971975747706e-05 loss: 0.0383 (0.0394) time: 3.1780 data: 0.0090 max mem: 33369 +Epoch: [25] [ 260/1319] eta: 0:56:35 lr: 2.0436551557054405e-05 loss: 0.0384 (0.0393) time: 3.1703 data: 0.0090 max mem: 33369 +Epoch: [25] [ 270/1319] eta: 0:56:01 lr: 2.0427130655844186e-05 loss: 0.0382 (0.0394) time: 3.1656 data: 0.0081 max mem: 33369 +Epoch: [25] [ 280/1319] eta: 0:55:30 lr: 2.041770927184505e-05 loss: 0.0386 (0.0394) time: 3.2003 data: 0.0076 max mem: 33369 +Epoch: [25] [ 290/1319] eta: 0:54:54 lr: 2.0408287404784693e-05 loss: 0.0370 (0.0395) time: 3.1665 data: 0.0078 max mem: 33369 +Epoch: [25] [ 300/1319] eta: 0:54:21 lr: 2.0398865054390533e-05 loss: 0.0383 (0.0399) time: 3.1380 data: 0.0082 max mem: 33369 +Epoch: [25] [ 310/1319] eta: 0:53:49 lr: 2.038944222038969e-05 loss: 0.0408 (0.0400) time: 3.1811 data: 0.0080 max mem: 33369 +Epoch: [25] [ 320/1319] eta: 0:53:16 lr: 2.0380018902508984e-05 loss: 0.0348 (0.0398) time: 3.1762 data: 0.0076 max mem: 33369 +Epoch: [25] [ 330/1319] eta: 0:52:43 lr: 2.0370595100474957e-05 loss: 0.0348 (0.0397) time: 3.1752 data: 0.0076 max mem: 33369 +Epoch: [25] [ 340/1319] eta: 0:52:10 lr: 2.036117081401383e-05 loss: 0.0386 (0.0397) time: 3.1681 data: 0.0074 max mem: 33369 +Epoch: [25] [ 350/1319] eta: 0:51:37 lr: 2.035174604285155e-05 loss: 0.0426 (0.0398) time: 3.1648 data: 0.0076 max mem: 33369 +Epoch: [25] [ 360/1319] eta: 0:51:07 lr: 2.0342320786713757e-05 loss: 0.0365 (0.0398) time: 3.2111 data: 0.0082 max mem: 33369 +Epoch: [25] [ 370/1319] eta: 0:50:33 lr: 2.03328950453258e-05 loss: 0.0355 (0.0398) time: 3.1866 data: 0.0081 max mem: 33369 +Epoch: [25] [ 380/1319] eta: 0:50:01 lr: 2.0323468818412736e-05 loss: 0.0372 (0.0397) time: 3.1695 data: 0.0076 max mem: 33369 +Epoch: [25] [ 390/1319] eta: 0:49:29 lr: 2.03140421056993e-05 loss: 0.0364 (0.0397) time: 3.2028 data: 0.0075 max mem: 33369 +Epoch: [25] [ 400/1319] eta: 0:48:57 lr: 2.0304614906909954e-05 loss: 0.0338 (0.0398) time: 3.1929 data: 0.0076 max mem: 33369 +Epoch: [25] [ 410/1319] eta: 0:48:25 lr: 2.0295187221768858e-05 loss: 0.0411 (0.0399) time: 3.1928 data: 0.0079 max mem: 33369 +Epoch: [25] [ 420/1319] eta: 0:47:54 lr: 2.028575904999986e-05 loss: 0.0391 (0.0399) time: 3.1996 data: 0.0082 max mem: 33369 +Epoch: [25] [ 430/1319] eta: 0:47:22 lr: 2.0276330391326524e-05 loss: 0.0389 (0.0400) time: 3.2086 data: 0.0086 max mem: 33369 +Epoch: [25] [ 440/1319] eta: 0:46:48 lr: 2.026690124547211e-05 loss: 0.0460 (0.0401) time: 3.1614 data: 0.0081 max mem: 33369 +Epoch: [25] [ 450/1319] eta: 0:46:15 lr: 2.025747161215956e-05 loss: 0.0381 (0.0401) time: 3.1139 data: 0.0076 max mem: 33369 +Epoch: [25] [ 460/1319] eta: 0:45:42 lr: 2.0248041491111535e-05 loss: 0.0359 (0.0402) time: 3.1453 data: 0.0078 max mem: 33369 +Epoch: [25] [ 470/1319] eta: 0:45:10 lr: 2.0238610882050398e-05 loss: 0.0384 (0.0404) time: 3.1783 data: 0.0080 max mem: 33369 +Epoch: [25] [ 480/1319] eta: 0:44:38 lr: 2.0229179784698192e-05 loss: 0.0349 (0.0402) time: 3.1861 data: 0.0082 max mem: 33369 +Epoch: [25] [ 490/1319] eta: 0:44:06 lr: 2.0219748198776674e-05 loss: 0.0327 (0.0401) time: 3.1769 data: 0.0080 max mem: 33369 +Epoch: [25] [ 500/1319] eta: 0:43:34 lr: 2.0210316124007283e-05 loss: 0.0376 (0.0404) time: 3.1811 data: 0.0078 max mem: 33369 +Epoch: [25] [ 510/1319] eta: 0:43:02 lr: 2.020088356011117e-05 loss: 0.0408 (0.0405) time: 3.1935 data: 0.0080 max mem: 33369 +Epoch: [25] [ 520/1319] eta: 0:42:30 lr: 2.019145050680917e-05 loss: 0.0373 (0.0405) time: 3.1991 data: 0.0083 max mem: 33369 +Epoch: [25] [ 530/1319] eta: 0:41:58 lr: 2.0182016963821814e-05 loss: 0.0367 (0.0405) time: 3.1700 data: 0.0080 max mem: 33369 +Epoch: [25] [ 540/1319] eta: 0:41:25 lr: 2.0172582930869342e-05 loss: 0.0367 (0.0405) time: 3.1442 data: 0.0081 max mem: 33369 +Epoch: [25] [ 550/1319] eta: 0:40:54 lr: 2.016314840767168e-05 loss: 0.0357 (0.0404) time: 3.1875 data: 0.0081 max mem: 33369 +Epoch: [25] [ 560/1319] eta: 0:40:22 lr: 2.0153713393948443e-05 loss: 0.0366 (0.0404) time: 3.2081 data: 0.0081 max mem: 33369 +Epoch: [25] [ 570/1319] eta: 0:39:50 lr: 2.014427788941894e-05 loss: 0.0373 (0.0403) time: 3.1879 data: 0.0085 max mem: 33369 +Epoch: [25] [ 580/1319] eta: 0:39:18 lr: 2.013484189380218e-05 loss: 0.0379 (0.0403) time: 3.1770 data: 0.0086 max mem: 33369 +Epoch: [25] [ 590/1319] eta: 0:38:46 lr: 2.012540540681687e-05 loss: 0.0346 (0.0403) time: 3.1798 data: 0.0081 max mem: 33369 +Epoch: [25] [ 600/1319] eta: 0:38:14 lr: 2.0115968428181397e-05 loss: 0.0328 (0.0403) time: 3.1825 data: 0.0081 max mem: 33369 +Epoch: [25] [ 610/1319] eta: 0:37:42 lr: 2.0106530957613837e-05 loss: 0.0344 (0.0403) time: 3.1993 data: 0.0084 max mem: 33369 +Epoch: [25] [ 620/1319] eta: 0:37:10 lr: 2.009709299483197e-05 loss: 0.0387 (0.0403) time: 3.2032 data: 0.0083 max mem: 33369 +Epoch: [25] [ 630/1319] eta: 0:36:38 lr: 2.0087654539553264e-05 loss: 0.0395 (0.0403) time: 3.2051 data: 0.0079 max mem: 33369 +Epoch: [25] [ 640/1319] eta: 0:36:07 lr: 2.007821559149487e-05 loss: 0.0374 (0.0403) time: 3.2071 data: 0.0075 max mem: 33369 +Epoch: [25] [ 650/1319] eta: 0:35:35 lr: 2.0068776150373638e-05 loss: 0.0384 (0.0404) time: 3.1994 data: 0.0077 max mem: 33369 +Epoch: [25] [ 660/1319] eta: 0:35:02 lr: 2.0059336215906098e-05 loss: 0.0365 (0.0404) time: 3.1705 data: 0.0077 max mem: 33369 +Epoch: [25] [ 670/1319] eta: 0:34:30 lr: 2.0049895787808467e-05 loss: 0.0356 (0.0403) time: 3.1372 data: 0.0077 max mem: 33369 +Epoch: [25] [ 680/1319] eta: 0:33:58 lr: 2.0040454865796668e-05 loss: 0.0357 (0.0403) time: 3.1576 data: 0.0080 max mem: 33369 +Epoch: [25] [ 690/1319] eta: 0:33:26 lr: 2.0031013449586292e-05 loss: 0.0357 (0.0403) time: 3.1636 data: 0.0080 max mem: 33369 +Epoch: [25] [ 700/1319] eta: 0:32:54 lr: 2.002157153889263e-05 loss: 0.0335 (0.0403) time: 3.1625 data: 0.0083 max mem: 33369 +Epoch: [25] [ 710/1319] eta: 0:32:21 lr: 2.0012129133430658e-05 loss: 0.0354 (0.0403) time: 3.1655 data: 0.0082 max mem: 33369 +Epoch: [25] [ 720/1319] eta: 0:31:49 lr: 2.0002686232915022e-05 loss: 0.0365 (0.0402) time: 3.1664 data: 0.0079 max mem: 33369 +Epoch: [25] [ 730/1319] eta: 0:31:18 lr: 1.9993242837060075e-05 loss: 0.0372 (0.0402) time: 3.1989 data: 0.0079 max mem: 33369 +Epoch: [25] [ 740/1319] eta: 0:30:46 lr: 1.9983798945579848e-05 loss: 0.0381 (0.0404) time: 3.1973 data: 0.0076 max mem: 33369 +Epoch: [25] [ 750/1319] eta: 0:30:14 lr: 1.9974354558188052e-05 loss: 0.0361 (0.0406) time: 3.1873 data: 0.0078 max mem: 33369 +Epoch: [25] [ 760/1319] eta: 0:29:42 lr: 1.9964909674598094e-05 loss: 0.0364 (0.0406) time: 3.1710 data: 0.0079 max mem: 33369 +Epoch: [25] [ 770/1319] eta: 0:29:10 lr: 1.9955464294523043e-05 loss: 0.0350 (0.0406) time: 3.2064 data: 0.0080 max mem: 33369 +Epoch: [25] [ 780/1319] eta: 0:28:38 lr: 1.994601841767567e-05 loss: 0.0361 (0.0407) time: 3.2172 data: 0.0081 max mem: 33369 +Epoch: [25] [ 790/1319] eta: 0:28:07 lr: 1.9936572043768427e-05 loss: 0.0406 (0.0408) time: 3.1911 data: 0.0078 max mem: 33369 +Epoch: [25] [ 800/1319] eta: 0:27:35 lr: 1.9927125172513435e-05 loss: 0.0400 (0.0409) time: 3.1906 data: 0.0080 max mem: 33369 +Epoch: [25] [ 810/1319] eta: 0:27:03 lr: 1.991767780362252e-05 loss: 0.0440 (0.0410) time: 3.1847 data: 0.0082 max mem: 33369 +Epoch: [25] [ 820/1319] eta: 0:26:31 lr: 1.990822993680716e-05 loss: 0.0398 (0.0410) time: 3.1931 data: 0.0078 max mem: 33369 +Epoch: [25] [ 830/1319] eta: 0:25:59 lr: 1.9898781571778537e-05 loss: 0.0398 (0.0410) time: 3.1767 data: 0.0077 max mem: 33369 +Epoch: [25] [ 840/1319] eta: 0:25:27 lr: 1.9889332708247497e-05 loss: 0.0415 (0.0410) time: 3.1976 data: 0.0077 max mem: 33369 +Epoch: [25] [ 850/1319] eta: 0:24:55 lr: 1.9879883345924575e-05 loss: 0.0428 (0.0412) time: 3.2008 data: 0.0076 max mem: 33369 +Epoch: [25] [ 860/1319] eta: 0:24:24 lr: 1.987043348451999e-05 loss: 0.0395 (0.0412) time: 3.1967 data: 0.0081 max mem: 33369 +Epoch: [25] [ 870/1319] eta: 0:23:52 lr: 1.9860983123743625e-05 loss: 0.0344 (0.0411) time: 3.1982 data: 0.0081 max mem: 33369 +Epoch: [25] [ 880/1319] eta: 0:23:20 lr: 1.9851532263305046e-05 loss: 0.0343 (0.0411) time: 3.1789 data: 0.0077 max mem: 33369 +Epoch: [25] [ 890/1319] eta: 0:22:48 lr: 1.98420809029135e-05 loss: 0.0408 (0.0411) time: 3.1804 data: 0.0079 max mem: 33369 +Epoch: [25] [ 900/1319] eta: 0:22:16 lr: 1.9832629042277908e-05 loss: 0.0378 (0.0411) time: 3.1659 data: 0.0078 max mem: 33369 +Epoch: [25] [ 910/1319] eta: 0:21:44 lr: 1.982317668110687e-05 loss: 0.0343 (0.0410) time: 3.1729 data: 0.0074 max mem: 33369 +Epoch: [25] [ 920/1319] eta: 0:21:12 lr: 1.981372381910867e-05 loss: 0.0372 (0.0410) time: 3.1646 data: 0.0076 max mem: 33369 +Epoch: [25] [ 930/1319] eta: 0:20:40 lr: 1.980427045599124e-05 loss: 0.0372 (0.0410) time: 3.1767 data: 0.0076 max mem: 33369 +Epoch: [25] [ 940/1319] eta: 0:20:08 lr: 1.9794816591462205e-05 loss: 0.0402 (0.0410) time: 3.1928 data: 0.0077 max mem: 33369 +Epoch: [25] [ 950/1319] eta: 0:19:36 lr: 1.9785362225228878e-05 loss: 0.0399 (0.0410) time: 3.1707 data: 0.0077 max mem: 33369 +Epoch: [25] [ 960/1319] eta: 0:19:04 lr: 1.9775907356998215e-05 loss: 0.0388 (0.0411) time: 3.1813 data: 0.0073 max mem: 33369 +Epoch: [25] [ 970/1319] eta: 0:18:32 lr: 1.976645198647688e-05 loss: 0.0377 (0.0410) time: 3.2100 data: 0.0075 max mem: 33369 +Epoch: [25] [ 980/1319] eta: 0:18:00 lr: 1.9756996113371165e-05 loss: 0.0327 (0.0410) time: 3.1882 data: 0.0080 max mem: 33369 +Epoch: [25] [ 990/1319] eta: 0:17:28 lr: 1.9747539737387077e-05 loss: 0.0375 (0.0411) time: 3.1615 data: 0.0079 max mem: 33369 +Epoch: [25] [1000/1319] eta: 0:16:57 lr: 1.973808285823027e-05 loss: 0.0348 (0.0410) time: 3.1862 data: 0.0076 max mem: 33369 +Epoch: [25] [1010/1319] eta: 0:16:25 lr: 1.972862547560608e-05 loss: 0.0348 (0.0412) time: 3.1873 data: 0.0077 max mem: 33369 +Epoch: [25] [1020/1319] eta: 0:15:53 lr: 1.9719167589219505e-05 loss: 0.0434 (0.0413) time: 3.1893 data: 0.0080 max mem: 33369 +Epoch: [25] [1030/1319] eta: 0:15:21 lr: 1.9709709198775227e-05 loss: 0.0443 (0.0413) time: 3.1940 data: 0.0080 max mem: 33369 +Epoch: [25] [1040/1319] eta: 0:14:49 lr: 1.9700250303977575e-05 loss: 0.0417 (0.0413) time: 3.1712 data: 0.0075 max mem: 33369 +Epoch: [25] [1050/1319] eta: 0:14:17 lr: 1.969079090453056e-05 loss: 0.0362 (0.0414) time: 3.1777 data: 0.0079 max mem: 33369 +Epoch: [25] [1060/1319] eta: 0:13:45 lr: 1.968133100013787e-05 loss: 0.0362 (0.0413) time: 3.1740 data: 0.0081 max mem: 33369 +Epoch: [25] [1070/1319] eta: 0:13:13 lr: 1.967187059050284e-05 loss: 0.0362 (0.0414) time: 3.1776 data: 0.0077 max mem: 33369 +Epoch: [25] [1080/1319] eta: 0:12:41 lr: 1.9662409675328494e-05 loss: 0.0382 (0.0414) time: 3.1752 data: 0.0076 max mem: 33369 +Epoch: [25] [1090/1319] eta: 0:12:09 lr: 1.9652948254317503e-05 loss: 0.0407 (0.0414) time: 3.1487 data: 0.0073 max mem: 33369 +Epoch: [25] [1100/1319] eta: 0:11:37 lr: 1.9643486327172213e-05 loss: 0.0405 (0.0415) time: 3.1743 data: 0.0075 max mem: 33369 +Epoch: [25] [1110/1319] eta: 0:11:06 lr: 1.9634023893594635e-05 loss: 0.0391 (0.0414) time: 3.1734 data: 0.0076 max mem: 33369 +Epoch: [25] [1120/1319] eta: 0:10:34 lr: 1.9624560953286446e-05 loss: 0.0380 (0.0414) time: 3.1849 data: 0.0082 max mem: 33369 +Epoch: [25] [1130/1319] eta: 0:10:02 lr: 1.961509750594899e-05 loss: 0.0390 (0.0414) time: 3.1866 data: 0.0085 max mem: 33369 +Epoch: [25] [1140/1319] eta: 0:09:30 lr: 1.9605633551283273e-05 loss: 0.0387 (0.0414) time: 3.2002 data: 0.0083 max mem: 33369 +Epoch: [25] [1150/1319] eta: 0:08:58 lr: 1.9596169088989948e-05 loss: 0.0385 (0.0414) time: 3.2084 data: 0.0083 max mem: 33369 +Epoch: [25] [1160/1319] eta: 0:08:26 lr: 1.9586704118769358e-05 loss: 0.0359 (0.0413) time: 3.1961 data: 0.0081 max mem: 33369 +Epoch: [25] [1170/1319] eta: 0:07:54 lr: 1.9577238640321492e-05 loss: 0.0391 (0.0413) time: 3.2029 data: 0.0084 max mem: 33369 +Epoch: [25] [1180/1319] eta: 0:07:23 lr: 1.9567772653346e-05 loss: 0.0373 (0.0413) time: 3.1811 data: 0.0080 max mem: 33369 +Epoch: [25] [1190/1319] eta: 0:06:51 lr: 1.9558306157542204e-05 loss: 0.0361 (0.0413) time: 3.1894 data: 0.0077 max mem: 33369 +Epoch: [25] [1200/1319] eta: 0:06:19 lr: 1.9548839152609067e-05 loss: 0.0390 (0.0413) time: 3.2051 data: 0.0083 max mem: 33369 +Epoch: [25] [1210/1319] eta: 0:05:47 lr: 1.9539371638245233e-05 loss: 0.0355 (0.0413) time: 3.2076 data: 0.0085 max mem: 33369 +Epoch: [25] [1220/1319] eta: 0:05:15 lr: 1.952990361414899e-05 loss: 0.0375 (0.0413) time: 3.2062 data: 0.0083 max mem: 33369 +Epoch: [25] [1230/1319] eta: 0:04:43 lr: 1.9520435080018294e-05 loss: 0.0358 (0.0413) time: 3.1941 data: 0.0076 max mem: 33369 +Epoch: [25] [1240/1319] eta: 0:04:11 lr: 1.9510966035550763e-05 loss: 0.0322 (0.0413) time: 3.1871 data: 0.0076 max mem: 33369 +Epoch: [25] [1250/1319] eta: 0:03:39 lr: 1.9501496480443652e-05 loss: 0.0349 (0.0413) time: 3.1637 data: 0.0079 max mem: 33369 +Epoch: [25] [1260/1319] eta: 0:03:08 lr: 1.9492026414393892e-05 loss: 0.0349 (0.0413) time: 3.1530 data: 0.0078 max mem: 33369 +Epoch: [25] [1270/1319] eta: 0:02:36 lr: 1.9482555837098063e-05 loss: 0.0388 (0.0413) time: 3.1749 data: 0.0077 max mem: 33369 +Epoch: [25] [1280/1319] eta: 0:02:04 lr: 1.9473084748252403e-05 loss: 0.0444 (0.0413) time: 3.1553 data: 0.0076 max mem: 33369 +Epoch: [25] [1290/1319] eta: 0:01:32 lr: 1.9463613147552807e-05 loss: 0.0386 (0.0415) time: 3.1253 data: 0.0078 max mem: 33369 +Epoch: [25] [1300/1319] eta: 0:01:00 lr: 1.9454141034694828e-05 loss: 0.0369 (0.0414) time: 3.1513 data: 0.0082 max mem: 33369 +Epoch: [25] [1310/1319] eta: 0:00:28 lr: 1.9444668409373652e-05 loss: 0.0336 (0.0414) time: 3.1488 data: 0.0076 max mem: 33369 +Epoch: [25] Total time: 1:10:02 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 2:23:41 time: 3.3508 data: 3.2301 max mem: 33369 +Test: [ 100/2573] eta: 0:04:31 time: 0.0775 data: 0.0015 max mem: 33369 +Test: [ 200/2573] eta: 0:03:43 time: 0.0779 data: 0.0015 max mem: 33369 +Test: [ 300/2573] eta: 0:03:21 time: 0.0797 data: 0.0014 max mem: 33369 +Test: [ 400/2573] eta: 0:03:07 time: 0.0797 data: 0.0014 max mem: 33369 +Test: [ 500/2573] eta: 0:02:55 time: 0.0791 data: 0.0016 max mem: 33369 +Test: [ 600/2573] eta: 0:02:45 time: 0.0798 data: 0.0015 max mem: 33369 +Test: [ 700/2573] eta: 0:02:36 time: 0.0802 data: 0.0015 max mem: 33369 +Test: [ 800/2573] eta: 0:02:27 time: 0.0815 data: 0.0013 max mem: 33369 +Test: [ 900/2573] eta: 0:02:18 time: 0.0782 data: 0.0013 max mem: 33369 +Test: [1000/2573] eta: 0:02:09 time: 0.0798 data: 0.0015 max mem: 33369 +Test: [1100/2573] eta: 0:02:00 time: 0.0785 data: 0.0014 max mem: 33369 +Test: [1200/2573] eta: 0:01:52 time: 0.0795 data: 0.0014 max mem: 33369 +Test: [1300/2573] eta: 0:01:43 time: 0.0790 data: 0.0014 max mem: 33369 +Test: [1400/2573] eta: 0:01:35 time: 0.0788 data: 0.0015 max mem: 33369 +Test: [1500/2573] eta: 0:01:27 time: 0.0795 data: 0.0014 max mem: 33369 +Test: [1600/2573] eta: 0:01:19 time: 0.0829 data: 0.0021 max mem: 33369 +Test: [1700/2573] eta: 0:01:10 time: 0.0778 data: 0.0014 max mem: 33369 +Test: [1800/2573] eta: 0:01:02 time: 0.0803 data: 0.0015 max mem: 33369 +Test: [1900/2573] eta: 0:00:54 time: 0.0779 data: 0.0014 max mem: 33369 +Test: [2000/2573] eta: 0:00:46 time: 0.0790 data: 0.0015 max mem: 33369 +Test: [2100/2573] eta: 0:00:38 time: 0.0822 data: 0.0014 max mem: 33369 +Test: [2200/2573] eta: 0:00:30 time: 0.0821 data: 0.0015 max mem: 33369 +Test: [2300/2573] eta: 0:00:22 time: 0.0812 data: 0.0015 max mem: 33369 +Test: [2400/2573] eta: 0:00:13 time: 0.0768 data: 0.0015 max mem: 33369 +Test: [2500/2573] eta: 0:00:05 time: 0.0794 data: 0.0015 max mem: 33369 +Test: Total time: 0:03:27 +Final results: +Mean IoU is 63.65 + + precision@0.5 = 71.92 + precision@0.6 = 66.65 + precision@0.7 = 59.21 + precision@0.8 = 47.65 + precision@0.9 = 23.49 + overall IoU = 61.57 + +Average object IoU 63.65288651323884 +Overall IoU 61.56517791748047 +Better epoch: 25 + +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [26] [ 0/1319] eta: 1:53:42 lr: 1.943614260817638e-05 loss: 0.0326 (0.0326) time: 5.1725 data: 1.8108 max mem: 33369 +Epoch: [26] [ 10/1319] eta: 1:14:25 lr: 1.9426669008334188e-05 loss: 0.0349 (0.0368) time: 3.4110 data: 0.1717 max mem: 33369 +Epoch: [26] [ 20/1319] eta: 1:11:05 lr: 1.941719489514293e-05 loss: 0.0347 (0.0349) time: 3.1889 data: 0.0075 max mem: 33369 +Epoch: [26] [ 30/1319] eta: 1:09:55 lr: 1.9407720268296455e-05 loss: 0.0393 (0.0368) time: 3.1686 data: 0.0076 max mem: 33369 +Epoch: [26] [ 40/1319] eta: 1:09:01 lr: 1.9398245127488253e-05 loss: 0.0384 (0.0361) time: 3.1912 data: 0.0083 max mem: 33369 +Epoch: [26] [ 50/1319] eta: 1:08:15 lr: 1.9388769472411493e-05 loss: 0.0355 (0.0372) time: 3.1843 data: 0.0083 max mem: 33369 +Epoch: [26] [ 60/1319] eta: 1:07:33 lr: 1.9379293302758954e-05 loss: 0.0354 (0.0365) time: 3.1813 data: 0.0080 max mem: 33369 +Epoch: [26] [ 70/1319] eta: 1:06:42 lr: 1.936981661822309e-05 loss: 0.0355 (0.0390) time: 3.1482 data: 0.0081 max mem: 33369 +Epoch: [26] [ 80/1319] eta: 1:06:13 lr: 1.9360339418495996e-05 loss: 0.0393 (0.0389) time: 3.1698 data: 0.0081 max mem: 33369 +Epoch: [26] [ 90/1319] eta: 1:05:35 lr: 1.935086170326942e-05 loss: 0.0372 (0.0387) time: 3.1923 data: 0.0079 max mem: 33369 +Epoch: [26] [ 100/1319] eta: 1:04:56 lr: 1.934138347223476e-05 loss: 0.0350 (0.0386) time: 3.1530 data: 0.0083 max mem: 33369 +Epoch: [26] [ 110/1319] eta: 1:04:18 lr: 1.9331904725083057e-05 loss: 0.0350 (0.0388) time: 3.1438 data: 0.0090 max mem: 33369 +Epoch: [26] [ 120/1319] eta: 1:03:41 lr: 1.9322425461504988e-05 loss: 0.0376 (0.0388) time: 3.1418 data: 0.0087 max mem: 33369 +Epoch: [26] [ 130/1319] eta: 1:03:05 lr: 1.931294568119089e-05 loss: 0.0376 (0.0394) time: 3.1388 data: 0.0086 max mem: 33369 +Epoch: [26] [ 140/1319] eta: 1:02:24 lr: 1.930346538383074e-05 loss: 0.0366 (0.0396) time: 3.1090 data: 0.0085 max mem: 33369 +Epoch: [26] [ 150/1319] eta: 1:01:52 lr: 1.9293984569114164e-05 loss: 0.0387 (0.0397) time: 3.1248 data: 0.0083 max mem: 33369 +Epoch: [26] [ 160/1319] eta: 1:01:20 lr: 1.9284503236730435e-05 loss: 0.0403 (0.0398) time: 3.1672 data: 0.0083 max mem: 33369 +Epoch: [26] [ 170/1319] eta: 1:00:50 lr: 1.927502138636845e-05 loss: 0.0422 (0.0407) time: 3.1912 data: 0.0085 max mem: 33369 +Epoch: [26] [ 180/1319] eta: 1:00:19 lr: 1.9265539017716765e-05 loss: 0.0368 (0.0402) time: 3.2017 data: 0.0084 max mem: 33369 +Epoch: [26] [ 190/1319] eta: 0:59:47 lr: 1.9256056130463582e-05 loss: 0.0324 (0.0409) time: 3.1777 data: 0.0081 max mem: 33369 +Epoch: [26] [ 200/1319] eta: 0:59:14 lr: 1.9246572724296735e-05 loss: 0.0382 (0.0406) time: 3.1581 data: 0.0081 max mem: 33369 +Epoch: [26] [ 210/1319] eta: 0:58:42 lr: 1.9237088798903708e-05 loss: 0.0358 (0.0407) time: 3.1608 data: 0.0084 max mem: 33369 +Epoch: [26] [ 220/1319] eta: 0:58:08 lr: 1.922760435397161e-05 loss: 0.0412 (0.0407) time: 3.1501 data: 0.0086 max mem: 33369 +Epoch: [26] [ 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33369 +Epoch: [26] [ 310/1319] eta: 0:53:22 lr: 1.9142220918520593e-05 loss: 0.0341 (0.0405) time: 3.1910 data: 0.0077 max mem: 33369 +Epoch: [26] [ 320/1319] eta: 0:52:51 lr: 1.9132731260909836e-05 loss: 0.0286 (0.0403) time: 3.1942 data: 0.0076 max mem: 33369 +Epoch: [26] [ 330/1319] eta: 0:52:20 lr: 1.9123241080294413e-05 loss: 0.0392 (0.0403) time: 3.1942 data: 0.0080 max mem: 33369 +Epoch: [26] [ 340/1319] eta: 0:51:47 lr: 1.9113750376357084e-05 loss: 0.0398 (0.0405) time: 3.1674 data: 0.0082 max mem: 33369 +Epoch: [26] [ 350/1319] eta: 0:51:15 lr: 1.9104259148780233e-05 loss: 0.0305 (0.0402) time: 3.1513 data: 0.0083 max mem: 33369 +Epoch: [26] [ 360/1319] eta: 0:50:45 lr: 1.909476739724589e-05 loss: 0.0305 (0.0400) time: 3.1935 data: 0.0086 max mem: 33369 +Epoch: [26] [ 370/1319] eta: 0:50:13 lr: 1.9085275121435705e-05 loss: 0.0329 (0.0400) time: 3.1899 data: 0.0084 max mem: 33369 +Epoch: [26] [ 380/1319] eta: 0:49:42 lr: 1.907578232103095e-05 loss: 0.0337 (0.0400) time: 3.1946 data: 0.0081 max mem: 33369 +Epoch: [26] [ 390/1319] eta: 0:49:10 lr: 1.906628899571255e-05 loss: 0.0371 (0.0401) time: 3.2002 data: 0.0087 max mem: 33369 +Epoch: [26] [ 400/1319] eta: 0:48:39 lr: 1.9056795145161037e-05 loss: 0.0373 (0.0401) time: 3.1885 data: 0.0087 max mem: 33369 +Epoch: [26] [ 410/1319] eta: 0:48:07 lr: 1.9047300769056588e-05 loss: 0.0360 (0.0400) time: 3.1709 data: 0.0088 max mem: 33369 +Epoch: [26] [ 420/1319] eta: 0:47:36 lr: 1.9037805867078998e-05 loss: 0.0356 (0.0400) time: 3.1877 data: 0.0085 max mem: 33369 +Epoch: [26] [ 430/1319] eta: 0:47:04 lr: 1.9028310438907695e-05 loss: 0.0331 (0.0398) time: 3.2054 data: 0.0081 max mem: 33369 +Epoch: [26] [ 440/1319] eta: 0:46:32 lr: 1.901881448422173e-05 loss: 0.0323 (0.0398) time: 3.1548 data: 0.0082 max mem: 33369 +Epoch: [26] [ 450/1319] eta: 0:45:59 lr: 1.900931800269978e-05 loss: 0.0324 (0.0398) time: 3.1336 data: 0.0081 max mem: 33369 +Epoch: [26] [ 460/1319] eta: 0:45:28 lr: 1.8999820994020145e-05 loss: 0.0337 (0.0397) time: 3.1649 data: 0.0091 max mem: 33369 +Epoch: [26] [ 470/1319] eta: 0:44:56 lr: 1.899032345786076e-05 loss: 0.0320 (0.0396) time: 3.1814 data: 0.0087 max mem: 33369 +Epoch: [26] [ 480/1319] eta: 0:44:23 lr: 1.8980825393899182e-05 loss: 0.0331 (0.0398) time: 3.1488 data: 0.0081 max mem: 33369 +Epoch: [26] [ 490/1319] eta: 0:43:52 lr: 1.897132680181258e-05 loss: 0.0379 (0.0397) time: 3.1608 data: 0.0084 max mem: 33369 +Epoch: [26] [ 500/1319] eta: 0:43:19 lr: 1.8961827681277747e-05 loss: 0.0329 (0.0396) time: 3.1674 data: 0.0080 max mem: 33369 +Epoch: [26] [ 510/1319] eta: 0:42:48 lr: 1.8952328031971114e-05 loss: 0.0332 (0.0396) time: 3.1685 data: 0.0080 max mem: 33369 +Epoch: [26] [ 520/1319] eta: 0:42:16 lr: 1.8942827853568723e-05 loss: 0.0340 (0.0396) time: 3.1915 data: 0.0083 max mem: 33369 +Epoch: [26] [ 530/1319] eta: 0:41:45 lr: 1.893332714574624e-05 loss: 0.0350 (0.0396) time: 3.1832 data: 0.0081 max mem: 33369 +Epoch: [26] [ 540/1319] eta: 0:41:13 lr: 1.892382590817894e-05 loss: 0.0321 (0.0395) time: 3.1765 data: 0.0083 max mem: 33369 +Epoch: [26] [ 550/1319] eta: 0:40:41 lr: 1.8914324140541728e-05 loss: 0.0334 (0.0395) time: 3.1586 data: 0.0088 max mem: 33369 +Epoch: [26] [ 560/1319] eta: 0:40:09 lr: 1.8904821842509134e-05 loss: 0.0381 (0.0395) time: 3.1660 data: 0.0089 max mem: 33369 +Epoch: [26] [ 570/1319] eta: 0:39:37 lr: 1.889531901375529e-05 loss: 0.0389 (0.0395) time: 3.1713 data: 0.0084 max mem: 33369 +Epoch: [26] [ 580/1319] eta: 0:39:05 lr: 1.888581565395396e-05 loss: 0.0384 (0.0396) time: 3.1386 data: 0.0076 max mem: 33369 +Epoch: [26] [ 590/1319] eta: 0:38:33 lr: 1.8876311762778523e-05 loss: 0.0384 (0.0397) time: 3.1594 data: 0.0080 max mem: 33369 +Epoch: [26] [ 600/1319] eta: 0:38:02 lr: 1.8866807339901958e-05 loss: 0.0385 (0.0398) time: 3.1823 data: 0.0084 max mem: 33369 +Epoch: [26] [ 610/1319] eta: 0:37:30 lr: 1.885730238499688e-05 loss: 0.0413 (0.0400) time: 3.1762 data: 0.0083 max mem: 33369 +Epoch: [26] [ 620/1319] eta: 0:36:58 lr: 1.8847796897735508e-05 loss: 0.0402 (0.0401) time: 3.1810 data: 0.0080 max mem: 33369 +Epoch: [26] [ 630/1319] eta: 0:36:27 lr: 1.8838290877789684e-05 loss: 0.0348 (0.0400) time: 3.1879 data: 0.0076 max mem: 33369 +Epoch: [26] [ 640/1319] eta: 0:35:55 lr: 1.882878432483085e-05 loss: 0.0380 (0.0400) time: 3.1759 data: 0.0077 max mem: 33369 +Epoch: [26] [ 650/1319] eta: 0:35:23 lr: 1.8819277238530077e-05 loss: 0.0385 (0.0400) time: 3.1559 data: 0.0082 max mem: 33369 +Epoch: [26] [ 660/1319] eta: 0:34:51 lr: 1.880976961855803e-05 loss: 0.0464 (0.0401) time: 3.1489 data: 0.0082 max mem: 33369 +Epoch: [26] [ 670/1319] eta: 0:34:19 lr: 1.8800261464585002e-05 loss: 0.0429 (0.0401) time: 3.1639 data: 0.0081 max mem: 33369 +Epoch: [26] [ 680/1319] eta: 0:33:47 lr: 1.8790752776280883e-05 loss: 0.0358 (0.0401) time: 3.1770 data: 0.0085 max mem: 33369 +Epoch: [26] [ 690/1319] eta: 0:33:15 lr: 1.8781243553315193e-05 loss: 0.0374 (0.0402) time: 3.1375 data: 0.0085 max mem: 33369 +Epoch: [26] [ 700/1319] eta: 0:32:43 lr: 1.8771733795357048e-05 loss: 0.0295 (0.0401) time: 3.1245 data: 0.0087 max mem: 33369 +Epoch: [26] [ 710/1319] eta: 0:32:11 lr: 1.876222350207516e-05 loss: 0.0358 (0.0403) time: 3.1346 data: 0.0085 max mem: 33369 +Epoch: [26] [ 720/1319] eta: 0:31:39 lr: 1.875271267313787e-05 loss: 0.0348 (0.0402) time: 3.1534 data: 0.0078 max mem: 33369 +Epoch: [26] [ 730/1319] eta: 0:31:08 lr: 1.8743201308213124e-05 loss: 0.0348 (0.0402) time: 3.1860 data: 0.0083 max mem: 33369 +Epoch: [26] [ 740/1319] eta: 0:30:36 lr: 1.8733689406968465e-05 loss: 0.0357 (0.0402) time: 3.1880 data: 0.0084 max mem: 33369 +Epoch: [26] [ 750/1319] eta: 0:30:05 lr: 1.872417696907106e-05 loss: 0.0357 (0.0402) time: 3.1965 data: 0.0080 max mem: 33369 +Epoch: [26] [ 760/1319] eta: 0:29:33 lr: 1.871466399418765e-05 loss: 0.0369 (0.0402) time: 3.2193 data: 0.0078 max mem: 33369 +Epoch: [26] [ 770/1319] eta: 0:29:02 lr: 1.870515048198461e-05 loss: 0.0378 (0.0402) time: 3.2019 data: 0.0080 max mem: 33369 +Epoch: [26] [ 780/1319] eta: 0:28:30 lr: 1.8695636432127905e-05 loss: 0.0356 (0.0401) time: 3.1937 data: 0.0084 max mem: 33369 +Epoch: [26] [ 790/1319] eta: 0:27:59 lr: 1.8686121844283114e-05 loss: 0.0353 (0.0401) time: 3.2080 data: 0.0085 max mem: 33369 +Epoch: [26] [ 800/1319] eta: 0:27:27 lr: 1.8676606718115407e-05 loss: 0.0332 (0.0401) time: 3.1746 data: 0.0087 max mem: 33369 +Epoch: [26] [ 810/1319] eta: 0:26:55 lr: 1.866709105328956e-05 loss: 0.0332 (0.0402) time: 3.1443 data: 0.0093 max mem: 33369 +Epoch: [26] [ 820/1319] eta: 0:26:23 lr: 1.8657574849469954e-05 loss: 0.0296 (0.0400) time: 3.1571 data: 0.0088 max mem: 33369 +Epoch: [26] [ 830/1319] eta: 0:25:51 lr: 1.864805810632056e-05 loss: 0.0312 (0.0400) time: 3.1745 data: 0.0078 max mem: 33369 +Epoch: [26] [ 840/1319] eta: 0:25:19 lr: 1.8638540823504965e-05 loss: 0.0327 (0.0399) time: 3.1320 data: 0.0081 max mem: 33369 +Epoch: [26] [ 850/1319] eta: 0:24:48 lr: 1.8629023000686338e-05 loss: 0.0341 (0.0399) time: 3.1573 data: 0.0084 max mem: 33369 +Epoch: [26] [ 860/1319] eta: 0:24:16 lr: 1.8619504637527467e-05 loss: 0.0367 (0.0399) time: 3.1939 data: 0.0079 max mem: 33369 +Epoch: [26] [ 870/1319] eta: 0:23:44 lr: 1.8609985733690715e-05 loss: 0.0367 (0.0398) time: 3.1895 data: 0.0080 max mem: 33369 +Epoch: [26] [ 880/1319] eta: 0:23:13 lr: 1.860046628883806e-05 loss: 0.0346 (0.0398) time: 3.1858 data: 0.0079 max mem: 33369 +Epoch: [26] [ 890/1319] eta: 0:22:41 lr: 1.859094630263106e-05 loss: 0.0385 (0.0398) time: 3.1689 data: 0.0082 max mem: 33369 +Epoch: [26] [ 900/1319] eta: 0:22:09 lr: 1.8581425774730882e-05 loss: 0.0357 (0.0398) time: 3.1713 data: 0.0083 max mem: 33369 +Epoch: [26] [ 910/1319] eta: 0:21:37 lr: 1.8571904704798292e-05 loss: 0.0357 (0.0398) time: 3.1818 data: 0.0080 max mem: 33369 +Epoch: [26] [ 920/1319] eta: 0:21:06 lr: 1.856238309249363e-05 loss: 0.0407 (0.0399) time: 3.1786 data: 0.0079 max mem: 33369 +Epoch: [26] [ 930/1319] eta: 0:20:34 lr: 1.855286093747684e-05 loss: 0.0415 (0.0399) time: 3.1643 data: 0.0081 max mem: 33369 +Epoch: [26] [ 940/1319] eta: 0:20:02 lr: 1.854333823940747e-05 loss: 0.0384 (0.0399) time: 3.1895 data: 0.0082 max mem: 33369 +Epoch: [26] [ 950/1319] eta: 0:19:31 lr: 1.853381499794464e-05 loss: 0.0361 (0.0399) time: 3.1886 data: 0.0077 max mem: 33369 +Epoch: [26] [ 960/1319] eta: 0:18:59 lr: 1.8524291212747084e-05 loss: 0.0396 (0.0399) time: 3.1950 data: 0.0076 max mem: 33369 +Epoch: [26] [ 970/1319] eta: 0:18:27 lr: 1.85147668834731e-05 loss: 0.0317 (0.0398) time: 3.1951 data: 0.0079 max mem: 33369 +Epoch: [26] [ 980/1319] eta: 0:17:56 lr: 1.8505242009780593e-05 loss: 0.0307 (0.0398) time: 3.1723 data: 0.0082 max mem: 33369 +Epoch: [26] [ 990/1319] eta: 0:17:24 lr: 1.8495716591327057e-05 loss: 0.0378 (0.0399) time: 3.1625 data: 0.0082 max mem: 33369 +Epoch: [26] [1000/1319] eta: 0:16:52 lr: 1.848619062776957e-05 loss: 0.0376 (0.0399) time: 3.1642 data: 0.0081 max mem: 33369 +Epoch: [26] [1010/1319] eta: 0:16:20 lr: 1.8476664118764797e-05 loss: 0.0328 (0.0398) time: 3.1675 data: 0.0078 max mem: 33369 +Epoch: [26] [1020/1319] eta: 0:15:49 lr: 1.8467137063969e-05 loss: 0.0334 (0.0400) time: 3.1853 data: 0.0075 max mem: 33369 +Epoch: [26] [1030/1319] eta: 0:15:17 lr: 1.8457609463038007e-05 loss: 0.0352 (0.0399) time: 3.1920 data: 0.0075 max mem: 33369 +Epoch: [26] [1040/1319] eta: 0:14:45 lr: 1.8448081315627246e-05 loss: 0.0339 (0.0399) time: 3.1859 data: 0.0077 max mem: 33369 +Epoch: [26] [1050/1319] eta: 0:14:13 lr: 1.843855262139173e-05 loss: 0.0327 (0.0398) time: 3.1856 data: 0.0084 max mem: 33369 +Epoch: [26] [1060/1319] eta: 0:13:42 lr: 1.8429023379986053e-05 loss: 0.0318 (0.0398) time: 3.1505 data: 0.0084 max mem: 33369 +Epoch: [26] [1070/1319] eta: 0:13:10 lr: 1.8419493591064395e-05 loss: 0.0335 (0.0398) time: 3.1335 data: 0.0081 max mem: 33369 +Epoch: [26] [1080/1319] eta: 0:12:38 lr: 1.840996325428051e-05 loss: 0.0322 (0.0397) time: 3.1654 data: 0.0079 max mem: 33369 +Epoch: [26] [1090/1319] eta: 0:12:06 lr: 1.840043236928774e-05 loss: 0.0319 (0.0397) time: 3.1785 data: 0.0076 max mem: 33369 +Epoch: [26] [1100/1319] eta: 0:11:34 lr: 1.839090093573901e-05 loss: 0.0350 (0.0397) time: 3.1441 data: 0.0084 max mem: 33369 +Epoch: [26] [1110/1319] eta: 0:11:03 lr: 1.838136895328682e-05 loss: 0.0374 (0.0397) time: 3.1452 data: 0.0085 max mem: 33369 +Epoch: [26] [1120/1319] eta: 0:10:31 lr: 1.8371836421583257e-05 loss: 0.0374 (0.0397) time: 3.1934 data: 0.0082 max mem: 33369 +Epoch: [26] [1130/1319] eta: 0:09:59 lr: 1.836230334027998e-05 loss: 0.0369 (0.0397) time: 3.2055 data: 0.0087 max mem: 33369 +Epoch: [26] [1140/1319] eta: 0:09:28 lr: 1.8352769709028224e-05 loss: 0.0342 (0.0397) time: 3.1723 data: 0.0084 max mem: 33369 +Epoch: [26] [1150/1319] eta: 0:08:56 lr: 1.8343235527478807e-05 loss: 0.0333 (0.0397) time: 3.1514 data: 0.0080 max mem: 33369 +Epoch: [26] [1160/1319] eta: 0:08:24 lr: 1.8333700795282125e-05 loss: 0.0365 (0.0397) time: 3.1903 data: 0.0080 max mem: 33369 +Epoch: [26] [1170/1319] eta: 0:07:52 lr: 1.832416551208814e-05 loss: 0.0387 (0.0397) time: 3.2146 data: 0.0081 max mem: 33369 +Epoch: [26] [1180/1319] eta: 0:07:21 lr: 1.8314629677546413e-05 loss: 0.0343 (0.0397) time: 3.1672 data: 0.0087 max mem: 33369 +Epoch: [26] [1190/1319] eta: 0:06:49 lr: 1.8305093291306038e-05 loss: 0.0316 (0.0397) time: 3.1701 data: 0.0086 max mem: 33369 +Epoch: [26] [1200/1319] eta: 0:06:17 lr: 1.829555635301572e-05 loss: 0.0318 (0.0396) time: 3.1834 data: 0.0080 max mem: 33369 +Epoch: [26] [1210/1319] eta: 0:05:45 lr: 1.8286018862323718e-05 loss: 0.0354 (0.0396) time: 3.1664 data: 0.0079 max mem: 33369 +Epoch: [26] [1220/1319] eta: 0:05:14 lr: 1.8276480818877866e-05 loss: 0.0373 (0.0396) time: 3.1691 data: 0.0078 max mem: 33369 +Epoch: [26] [1230/1319] eta: 0:04:42 lr: 1.8266942222325584e-05 loss: 0.0367 (0.0396) time: 3.1818 data: 0.0081 max mem: 33369 +Epoch: [26] [1240/1319] eta: 0:04:10 lr: 1.8257403072313833e-05 loss: 0.0326 (0.0395) time: 3.1862 data: 0.0084 max mem: 33369 +Epoch: [26] [1250/1319] eta: 0:03:39 lr: 1.8247863368489165e-05 loss: 0.0362 (0.0396) time: 3.1762 data: 0.0081 max mem: 33369 +Epoch: [26] [1260/1319] eta: 0:03:07 lr: 1.8238323110497695e-05 loss: 0.0364 (0.0396) time: 3.1664 data: 0.0080 max mem: 33369 +Epoch: [26] [1270/1319] eta: 0:02:35 lr: 1.822878229798511e-05 loss: 0.0364 (0.0396) time: 3.1620 data: 0.0076 max mem: 33369 +Epoch: [26] [1280/1319] eta: 0:02:03 lr: 1.821924093059666e-05 loss: 0.0345 (0.0396) time: 3.1734 data: 0.0079 max mem: 33369 +Epoch: [26] [1290/1319] eta: 0:01:32 lr: 1.8209699007977167e-05 loss: 0.0297 (0.0395) time: 3.1726 data: 0.0085 max mem: 33369 +Epoch: [26] [1300/1319] eta: 0:01:00 lr: 1.8200156529771002e-05 loss: 0.0330 (0.0395) time: 3.1904 data: 0.0082 max mem: 33369 +Epoch: [26] [1310/1319] eta: 0:00:28 lr: 1.819061349562212e-05 loss: 0.0393 (0.0395) time: 3.1733 data: 0.0075 max mem: 33369 +Epoch: [26] Total time: 1:09:46 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 2:25:11 time: 3.3859 data: 3.2947 max mem: 33369 +Test: [ 100/2573] eta: 0:04:31 time: 0.0772 data: 0.0015 max mem: 33369 +Test: [ 200/2573] eta: 0:03:44 time: 0.0786 data: 0.0014 max mem: 33369 +Test: [ 300/2573] eta: 0:03:22 time: 0.0805 data: 0.0014 max mem: 33369 +Test: [ 400/2573] eta: 0:03:07 time: 0.0795 data: 0.0014 max mem: 33369 +Test: [ 500/2573] eta: 0:02:55 time: 0.0785 data: 0.0014 max mem: 33369 +Test: [ 600/2573] eta: 0:02:45 time: 0.0791 data: 0.0015 max mem: 33369 +Test: [ 700/2573] eta: 0:02:36 time: 0.0796 data: 0.0015 max mem: 33369 +Test: [ 800/2573] eta: 0:02:27 time: 0.0820 data: 0.0014 max mem: 33369 +Test: [ 900/2573] eta: 0:02:18 time: 0.0793 data: 0.0015 max mem: 33369 +Test: [1000/2573] eta: 0:02:09 time: 0.0793 data: 0.0014 max mem: 33369 +Test: [1100/2573] eta: 0:02:00 time: 0.0789 data: 0.0015 max mem: 33369 +Test: [1200/2573] eta: 0:01:52 time: 0.0791 data: 0.0014 max mem: 33369 +Test: [1300/2573] eta: 0:01:44 time: 0.0796 data: 0.0015 max mem: 33369 +Test: [1400/2573] eta: 0:01:35 time: 0.0775 data: 0.0015 max mem: 33369 +Test: [1500/2573] eta: 0:01:27 time: 0.0803 data: 0.0015 max mem: 33369 +Test: [1600/2573] eta: 0:01:19 time: 0.0830 data: 0.0015 max mem: 33369 +Test: [1700/2573] eta: 0:01:11 time: 0.0776 data: 0.0014 max mem: 33369 +Test: [1800/2573] eta: 0:01:02 time: 0.0829 data: 0.0015 max mem: 33369 +Test: [1900/2573] eta: 0:00:54 time: 0.0782 data: 0.0015 max mem: 33369 +Test: [2000/2573] eta: 0:00:46 time: 0.0795 data: 0.0015 max mem: 33369 +Test: [2100/2573] eta: 0:00:38 time: 0.0804 data: 0.0013 max mem: 33369 +Test: [2200/2573] eta: 0:00:30 time: 0.0809 data: 0.0013 max mem: 33369 +Test: [2300/2573] eta: 0:00:22 time: 0.0809 data: 0.0014 max mem: 33369 +Test: [2400/2573] eta: 0:00:13 time: 0.0762 data: 0.0014 max mem: 33369 +Test: [2500/2573] eta: 0:00:05 time: 0.0799 data: 0.0014 max mem: 33369 +Test: Total time: 0:03:27 +Final results: +Mean IoU is 64.28 + + precision@0.5 = 72.10 + precision@0.6 = 66.63 + precision@0.7 = 59.35 + precision@0.8 = 48.12 + precision@0.9 = 23.73 + overall IoU = 61.72 + +Average object IoU 64.27837328891222 +Overall IoU 61.718292236328125 +Better epoch: 26 + +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [27] [ 0/1319] eta: 1:52:34 lr: 1.818202428926248e-05 loss: 0.0281 (0.0281) time: 5.1213 data: 1.8197 max mem: 33369 +Epoch: [27] [ 10/1319] eta: 1:13:17 lr: 1.817248019783995e-05 loss: 0.0377 (0.0430) time: 3.3597 data: 0.1731 max mem: 33369 +Epoch: [27] [ 20/1319] eta: 1:10:49 lr: 1.8162935549439682e-05 loss: 0.0410 (0.0423) time: 3.1785 data: 0.0077 max mem: 33369 +Epoch: [27] [ 30/1319] eta: 1:09:20 lr: 1.8153390343703928e-05 loss: 0.0385 (0.0412) time: 3.1554 data: 0.0074 max mem: 33369 +Epoch: [27] [ 40/1319] eta: 1:08:33 lr: 1.8143844580274487e-05 loss: 0.0366 (0.0393) time: 3.1592 data: 0.0077 max mem: 33369 +Epoch: [27] [ 50/1319] eta: 1:07:55 lr: 1.813429825879272e-05 loss: 0.0341 (0.0392) time: 3.1855 data: 0.0077 max mem: 33369 +Epoch: [27] [ 60/1319] eta: 1:07:23 lr: 1.8124751378899558e-05 loss: 0.0387 (0.0399) time: 3.2014 data: 0.0082 max mem: 33369 +Epoch: [27] [ 70/1319] eta: 1:06:48 lr: 1.811520394023548e-05 loss: 0.0369 (0.0398) time: 3.2050 data: 0.0081 max mem: 33369 +Epoch: [27] [ 80/1319] eta: 1:06:18 lr: 1.8105655942440525e-05 loss: 0.0354 (0.0397) time: 3.2094 data: 0.0083 max mem: 33369 +Epoch: [27] [ 90/1319] eta: 1:05:42 lr: 1.8096107385154294e-05 loss: 0.0357 (0.0393) time: 3.2012 data: 0.0087 max mem: 33369 +Epoch: [27] [ 100/1319] eta: 1:05:06 lr: 1.8086558268015952e-05 loss: 0.0357 (0.0390) time: 3.1797 data: 0.0085 max mem: 33369 +Epoch: [27] [ 110/1319] eta: 1:04:36 lr: 1.807700859066419e-05 loss: 0.0376 (0.0392) time: 3.2003 data: 0.0085 max mem: 33369 +Epoch: [27] [ 120/1319] eta: 1:03:59 lr: 1.8067458352737284e-05 loss: 0.0341 (0.0390) time: 3.1906 data: 0.0085 max mem: 33369 +Epoch: [27] [ 130/1319] eta: 1:03:22 lr: 1.8057907553873043e-05 loss: 0.0319 (0.0389) time: 3.1526 data: 0.0086 max mem: 33369 +Epoch: [27] [ 140/1319] eta: 1:02:46 lr: 1.8048356193708847e-05 loss: 0.0323 (0.0388) time: 3.1472 data: 0.0089 max mem: 33369 +Epoch: [27] [ 150/1319] eta: 1:02:13 lr: 1.803880427188162e-05 loss: 0.0301 (0.0389) time: 3.1637 data: 0.0087 max mem: 33369 +Epoch: [27] [ 160/1319] eta: 1:01:40 lr: 1.802925178802783e-05 loss: 0.0355 (0.0388) time: 3.1823 data: 0.0086 max mem: 33369 +Epoch: [27] [ 170/1319] eta: 1:01:09 lr: 1.8019698741783504e-05 loss: 0.0290 (0.0382) time: 3.1956 data: 0.0086 max mem: 33369 +Epoch: [27] [ 180/1319] eta: 1:00:34 lr: 1.8010145132784217e-05 loss: 0.0292 (0.0381) time: 3.1736 data: 0.0083 max mem: 33369 +Epoch: [27] [ 190/1319] eta: 1:00:06 lr: 1.8000590960665095e-05 loss: 0.0327 (0.0388) time: 3.2013 data: 0.0083 max mem: 33369 +Epoch: [27] [ 200/1319] eta: 0:59:31 lr: 1.7991036225060814e-05 loss: 0.0391 (0.0397) time: 3.1987 data: 0.0086 max mem: 33369 +Epoch: [27] [ 210/1319] eta: 0:58:59 lr: 1.7981480925605583e-05 loss: 0.0415 (0.0417) time: 3.1657 data: 0.0083 max mem: 33369 +Epoch: [27] [ 220/1319] eta: 0:58:29 lr: 1.7971925061933174e-05 loss: 0.0390 (0.0415) time: 3.2097 data: 0.0081 max mem: 33369 +Epoch: [27] [ 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mem: 33369 +Epoch: [27] [ 310/1319] eta: 0:53:34 lr: 1.7885896838454187e-05 loss: 0.0404 (0.0406) time: 3.1681 data: 0.0086 max mem: 33369 +Epoch: [27] [ 320/1319] eta: 0:53:01 lr: 1.787633531236672e-05 loss: 0.0357 (0.0406) time: 3.1751 data: 0.0082 max mem: 33369 +Epoch: [27] [ 330/1319] eta: 0:52:29 lr: 1.786677321800332e-05 loss: 0.0354 (0.0406) time: 3.1734 data: 0.0080 max mem: 33369 +Epoch: [27] [ 340/1319] eta: 0:51:59 lr: 1.7857210554992246e-05 loss: 0.0394 (0.0406) time: 3.2117 data: 0.0078 max mem: 33369 +Epoch: [27] [ 350/1319] eta: 0:51:28 lr: 1.7847647322961293e-05 loss: 0.0433 (0.0407) time: 3.2246 data: 0.0078 max mem: 33369 +Epoch: [27] [ 360/1319] eta: 0:50:55 lr: 1.783808352153779e-05 loss: 0.0371 (0.0406) time: 3.1883 data: 0.0079 max mem: 33369 +Epoch: [27] [ 370/1319] eta: 0:50:24 lr: 1.782851915034859e-05 loss: 0.0400 (0.0405) time: 3.1899 data: 0.0080 max mem: 33369 +Epoch: [27] [ 380/1319] eta: 0:49:51 lr: 1.78189542090201e-05 loss: 0.0400 (0.0405) time: 3.1728 data: 0.0084 max mem: 33369 +Epoch: [27] [ 390/1319] eta: 0:49:19 lr: 1.780938869717823e-05 loss: 0.0414 (0.0406) time: 3.1528 data: 0.0085 max mem: 33369 +Epoch: [27] [ 400/1319] eta: 0:48:47 lr: 1.779982261444845e-05 loss: 0.0377 (0.0405) time: 3.1891 data: 0.0081 max mem: 33369 +Epoch: [27] [ 410/1319] eta: 0:48:17 lr: 1.7790255960455746e-05 loss: 0.0347 (0.0405) time: 3.2176 data: 0.0080 max mem: 33369 +Epoch: [27] [ 420/1319] eta: 0:47:45 lr: 1.7780688734824637e-05 loss: 0.0347 (0.0405) time: 3.2157 data: 0.0080 max mem: 33369 +Epoch: [27] [ 430/1319] eta: 0:47:13 lr: 1.777112093717916e-05 loss: 0.0359 (0.0404) time: 3.1950 data: 0.0081 max mem: 33369 +Epoch: [27] [ 440/1319] eta: 0:46:41 lr: 1.7761552567142895e-05 loss: 0.0359 (0.0404) time: 3.1760 data: 0.0085 max mem: 33369 +Epoch: [27] [ 450/1319] eta: 0:46:09 lr: 1.7751983624338938e-05 loss: 0.0326 (0.0402) time: 3.1697 data: 0.0085 max mem: 33369 +Epoch: [27] [ 460/1319] eta: 0:45:35 lr: 1.7742414108389917e-05 loss: 0.0336 (0.0404) time: 3.1338 data: 0.0079 max mem: 33369 +Epoch: [27] [ 470/1319] eta: 0:45:02 lr: 1.7732844018917994e-05 loss: 0.0357 (0.0402) time: 3.0981 data: 0.0080 max mem: 33369 +Epoch: [27] [ 480/1319] eta: 0:44:30 lr: 1.7723273355544827e-05 loss: 0.0341 (0.0402) time: 3.1538 data: 0.0083 max mem: 33369 +Epoch: [27] [ 490/1319] eta: 0:43:58 lr: 1.771370211789162e-05 loss: 0.0333 (0.0402) time: 3.1920 data: 0.0084 max mem: 33369 +Epoch: [27] [ 500/1319] eta: 0:43:27 lr: 1.7704130305579097e-05 loss: 0.0359 (0.0402) time: 3.1884 data: 0.0086 max mem: 33369 +Epoch: [27] [ 510/1319] eta: 0:42:56 lr: 1.76945579182275e-05 loss: 0.0389 (0.0402) time: 3.2069 data: 0.0081 max mem: 33369 +Epoch: [27] [ 520/1319] eta: 0:42:24 lr: 1.7684984955456597e-05 loss: 0.0355 (0.0401) time: 3.2165 data: 0.0080 max mem: 33369 +Epoch: [27] [ 530/1319] eta: 0:41:52 lr: 1.767541141688566e-05 loss: 0.0364 (0.0401) time: 3.1942 data: 0.0079 max mem: 33369 +Epoch: [27] [ 540/1319] eta: 0:41:20 lr: 1.76658373021335e-05 loss: 0.0384 (0.0401) time: 3.1725 data: 0.0076 max mem: 33369 +Epoch: [27] [ 550/1319] eta: 0:40:48 lr: 1.7656262610818425e-05 loss: 0.0376 (0.0400) time: 3.1675 data: 0.0081 max mem: 33369 +Epoch: [27] [ 560/1319] eta: 0:40:16 lr: 1.7646687342558284e-05 loss: 0.0320 (0.0401) time: 3.1773 data: 0.0084 max mem: 33369 +Epoch: [27] [ 570/1319] eta: 0:39:44 lr: 1.7637111496970423e-05 loss: 0.0403 (0.0402) time: 3.1617 data: 0.0083 max mem: 33369 +Epoch: [27] [ 580/1319] eta: 0:39:12 lr: 1.762753507367172e-05 loss: 0.0361 (0.0400) time: 3.1604 data: 0.0086 max mem: 33369 +Epoch: [27] [ 590/1319] eta: 0:38:40 lr: 1.7617958072278543e-05 loss: 0.0353 (0.0401) time: 3.1676 data: 0.0084 max mem: 33369 +Epoch: [27] [ 600/1319] eta: 0:38:08 lr: 1.7608380492406792e-05 loss: 0.0321 (0.0400) time: 3.1693 data: 0.0077 max mem: 33369 +Epoch: [27] [ 610/1319] eta: 0:37:36 lr: 1.759880233367188e-05 loss: 0.0337 (0.0400) time: 3.1642 data: 0.0081 max mem: 33369 +Epoch: [27] [ 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33369 +Epoch: [27] [ 700/1319] eta: 0:32:50 lr: 1.751257279251512e-05 loss: 0.0359 (0.0402) time: 3.2009 data: 0.0078 max mem: 33369 +Epoch: [27] [ 710/1319] eta: 0:32:18 lr: 1.7502988823888103e-05 loss: 0.0308 (0.0401) time: 3.1946 data: 0.0077 max mem: 33369 +Epoch: [27] [ 720/1319] eta: 0:31:46 lr: 1.749340427213497e-05 loss: 0.0388 (0.0403) time: 3.1895 data: 0.0079 max mem: 33369 +Epoch: [27] [ 730/1319] eta: 0:31:14 lr: 1.7483819136865212e-05 loss: 0.0414 (0.0403) time: 3.1774 data: 0.0080 max mem: 33369 +Epoch: [27] [ 740/1319] eta: 0:30:42 lr: 1.7474233417687816e-05 loss: 0.0368 (0.0402) time: 3.1699 data: 0.0077 max mem: 33369 +Epoch: [27] [ 750/1319] eta: 0:30:11 lr: 1.7464647114211257e-05 loss: 0.0312 (0.0403) time: 3.1861 data: 0.0075 max mem: 33369 +Epoch: [27] [ 760/1319] eta: 0:29:39 lr: 1.7455060226043528e-05 loss: 0.0411 (0.0403) time: 3.1991 data: 0.0076 max mem: 33369 +Epoch: [27] [ 770/1319] eta: 0:29:07 lr: 1.744547275279211e-05 loss: 0.0297 (0.0402) time: 3.1779 data: 0.0080 max mem: 33369 +Epoch: [27] [ 780/1319] eta: 0:28:35 lr: 1.7435884694063984e-05 loss: 0.0365 (0.0403) time: 3.1329 data: 0.0082 max mem: 33369 +Epoch: [27] [ 790/1319] eta: 0:28:03 lr: 1.7426296049465625e-05 loss: 0.0361 (0.0404) time: 3.1480 data: 0.0077 max mem: 33369 +Epoch: [27] [ 800/1319] eta: 0:27:31 lr: 1.7416706818602993e-05 loss: 0.0319 (0.0404) time: 3.1509 data: 0.0078 max mem: 33369 +Epoch: [27] [ 810/1319] eta: 0:26:59 lr: 1.7407117001081557e-05 loss: 0.0377 (0.0403) time: 3.1627 data: 0.0082 max mem: 33369 +Epoch: [27] [ 820/1319] eta: 0:26:27 lr: 1.7397526596506272e-05 loss: 0.0341 (0.0403) time: 3.1721 data: 0.0081 max mem: 33369 +Epoch: [27] [ 830/1319] eta: 0:25:55 lr: 1.7387935604481586e-05 loss: 0.0378 (0.0405) time: 3.1835 data: 0.0083 max mem: 33369 +Epoch: [27] [ 840/1319] eta: 0:25:23 lr: 1.7378344024611436e-05 loss: 0.0380 (0.0406) time: 3.1798 data: 0.0081 max mem: 33369 +Epoch: [27] [ 850/1319] eta: 0:24:52 lr: 1.7368751856499257e-05 loss: 0.0334 (0.0405) time: 3.1831 data: 0.0079 max mem: 33369 +Epoch: [27] [ 860/1319] eta: 0:24:20 lr: 1.7359159099747958e-05 loss: 0.0294 (0.0404) time: 3.1951 data: 0.0080 max mem: 33369 +Epoch: [27] [ 870/1319] eta: 0:23:48 lr: 1.7349565753959942e-05 loss: 0.0309 (0.0403) time: 3.1485 data: 0.0079 max mem: 33369 +Epoch: [27] [ 880/1319] eta: 0:23:16 lr: 1.7339971818737108e-05 loss: 0.0328 (0.0403) time: 3.1419 data: 0.0079 max mem: 33369 +Epoch: [27] [ 890/1319] eta: 0:22:44 lr: 1.733037729368083e-05 loss: 0.0363 (0.0402) time: 3.1629 data: 0.0075 max mem: 33369 +Epoch: [27] [ 900/1319] eta: 0:22:12 lr: 1.7320782178391982e-05 loss: 0.0384 (0.0403) time: 3.1739 data: 0.0075 max mem: 33369 +Epoch: [27] [ 910/1319] eta: 0:21:40 lr: 1.7311186472470895e-05 loss: 0.0338 (0.0401) time: 3.1751 data: 0.0077 max mem: 33369 +Epoch: [27] [ 920/1319] eta: 0:21:08 lr: 1.7301590175517403e-05 loss: 0.0322 (0.0401) time: 3.1587 data: 0.0076 max mem: 33369 +Epoch: [27] [ 930/1319] eta: 0:20:36 lr: 1.7291993287130824e-05 loss: 0.0360 (0.0401) time: 3.1467 data: 0.0080 max mem: 33369 +Epoch: [27] [ 940/1319] eta: 0:20:05 lr: 1.728239580690995e-05 loss: 0.0324 (0.0402) time: 3.1746 data: 0.0080 max mem: 33369 +Epoch: [27] [ 950/1319] eta: 0:19:33 lr: 1.727279773445306e-05 loss: 0.0324 (0.0401) time: 3.1951 data: 0.0078 max mem: 33369 +Epoch: [27] [ 960/1319] eta: 0:19:01 lr: 1.7263199069357895e-05 loss: 0.0309 (0.0401) time: 3.1442 data: 0.0078 max mem: 33369 +Epoch: [27] [ 970/1319] eta: 0:18:29 lr: 1.725359981122169e-05 loss: 0.0321 (0.0400) time: 3.1509 data: 0.0079 max mem: 33369 +Epoch: [27] [ 980/1319] eta: 0:17:57 lr: 1.7243999959641156e-05 loss: 0.0335 (0.0400) time: 3.1775 data: 0.0077 max mem: 33369 +Epoch: [27] [ 990/1319] eta: 0:17:25 lr: 1.7234399514212475e-05 loss: 0.0333 (0.0400) time: 3.1813 data: 0.0076 max mem: 33369 +Epoch: [27] [1000/1319] eta: 0:16:54 lr: 1.7224798474531302e-05 loss: 0.0380 (0.0399) time: 3.1809 data: 0.0081 max mem: 33369 +Epoch: [27] [1010/1319] eta: 0:16:22 lr: 1.7215196840192783e-05 loss: 0.0389 (0.0400) time: 3.1850 data: 0.0081 max mem: 33369 +Epoch: [27] [1020/1319] eta: 0:15:50 lr: 1.7205594610791508e-05 loss: 0.0322 (0.0399) time: 3.2100 data: 0.0079 max mem: 33369 +Epoch: [27] [1030/1319] eta: 0:15:18 lr: 1.7195991785921565e-05 loss: 0.0384 (0.0399) time: 3.1926 data: 0.0085 max mem: 33369 +Epoch: [27] [1040/1319] eta: 0:14:47 lr: 1.71863883651765e-05 loss: 0.0389 (0.0399) time: 3.1681 data: 0.0081 max mem: 33369 +Epoch: [27] [1050/1319] eta: 0:14:15 lr: 1.7176784348149333e-05 loss: 0.0343 (0.0399) time: 3.1870 data: 0.0075 max mem: 33369 +Epoch: [27] [1060/1319] eta: 0:13:43 lr: 1.7167179734432558e-05 loss: 0.0339 (0.0399) time: 3.1921 data: 0.0084 max mem: 33369 +Epoch: [27] [1070/1319] eta: 0:13:11 lr: 1.7157574523618118e-05 loss: 0.0370 (0.0400) time: 3.1896 data: 0.0086 max mem: 33369 +Epoch: [27] [1080/1319] eta: 0:12:39 lr: 1.7147968715297445e-05 loss: 0.0370 (0.0400) time: 3.1845 data: 0.0081 max mem: 33369 +Epoch: [27] [1090/1319] eta: 0:12:08 lr: 1.7138362309061432e-05 loss: 0.0360 (0.0400) time: 3.1435 data: 0.0079 max mem: 33369 +Epoch: [27] [1100/1319] eta: 0:11:36 lr: 1.7128755304500424e-05 loss: 0.0424 (0.0400) time: 3.1815 data: 0.0076 max mem: 33369 +Epoch: [27] [1110/1319] eta: 0:11:04 lr: 1.7119147701204254e-05 loss: 0.0424 (0.0400) time: 3.2146 data: 0.0076 max mem: 33369 +Epoch: [27] [1120/1319] eta: 0:10:32 lr: 1.710953949876218e-05 loss: 0.0391 (0.0400) time: 3.2010 data: 0.0079 max mem: 33369 +Epoch: [27] [1130/1319] eta: 0:10:00 lr: 1.709993069676296e-05 loss: 0.0312 (0.0399) time: 3.1704 data: 0.0080 max mem: 33369 +Epoch: [27] [1140/1319] eta: 0:09:29 lr: 1.7090321294794796e-05 loss: 0.0338 (0.0400) time: 3.1553 data: 0.0081 max mem: 33369 +Epoch: [27] [1150/1319] eta: 0:08:57 lr: 1.7080711292445346e-05 loss: 0.0327 (0.0399) time: 3.1379 data: 0.0084 max mem: 33369 +Epoch: [27] [1160/1319] eta: 0:08:25 lr: 1.7071100689301735e-05 loss: 0.0323 (0.0399) time: 3.1432 data: 0.0084 max mem: 33369 +Epoch: [27] [1170/1319] eta: 0:07:53 lr: 1.706148948495055e-05 loss: 0.0388 (0.0399) time: 3.1686 data: 0.0076 max mem: 33369 +Epoch: [27] [1180/1319] eta: 0:07:21 lr: 1.705187767897781e-05 loss: 0.0352 (0.0399) time: 3.1674 data: 0.0074 max mem: 33369 +Epoch: [27] [1190/1319] eta: 0:06:50 lr: 1.704226527096902e-05 loss: 0.0351 (0.0399) time: 3.1755 data: 0.0075 max mem: 33369 +Epoch: [27] [1200/1319] eta: 0:06:18 lr: 1.703265226050912e-05 loss: 0.0328 (0.0398) time: 3.1906 data: 0.0073 max mem: 33369 +Epoch: [27] [1210/1319] eta: 0:05:46 lr: 1.702303864718251e-05 loss: 0.0331 (0.0399) time: 3.1828 data: 0.0079 max mem: 33369 +Epoch: [27] [1220/1319] eta: 0:05:14 lr: 1.7013424430573045e-05 loss: 0.0355 (0.0399) time: 3.1712 data: 0.0083 max mem: 33369 +Epoch: [27] [1230/1319] eta: 0:04:42 lr: 1.7003809610264022e-05 loss: 0.0385 (0.0399) time: 3.1995 data: 0.0078 max mem: 33369 +Epoch: [27] [1240/1319] eta: 0:04:11 lr: 1.6994194185838196e-05 loss: 0.0378 (0.0399) time: 3.2191 data: 0.0075 max mem: 33369 +Epoch: [27] [1250/1319] eta: 0:03:39 lr: 1.698457815687777e-05 loss: 0.0345 (0.0398) time: 3.1921 data: 0.0076 max mem: 33369 +Epoch: [27] [1260/1319] eta: 0:03:07 lr: 1.6974961522964392e-05 loss: 0.0360 (0.0398) time: 3.1646 data: 0.0078 max mem: 33369 +Epoch: [27] [1270/1319] eta: 0:02:35 lr: 1.6965344283679166e-05 loss: 0.0367 (0.0398) time: 3.2017 data: 0.0081 max mem: 33369 +Epoch: [27] [1280/1319] eta: 0:02:04 lr: 1.6955726438602627e-05 loss: 0.0331 (0.0397) time: 3.2088 data: 0.0087 max mem: 33369 +Epoch: [27] [1290/1319] eta: 0:01:32 lr: 1.694610798731476e-05 loss: 0.0322 (0.0397) time: 3.1535 data: 0.0090 max mem: 33369 +Epoch: [27] [1300/1319] eta: 0:01:00 lr: 1.6936488929395006e-05 loss: 0.0331 (0.0396) time: 3.1421 data: 0.0087 max mem: 33369 +Epoch: [27] [1310/1319] eta: 0:00:28 lr: 1.6926869264422233e-05 loss: 0.0318 (0.0396) time: 3.1352 data: 0.0081 max mem: 33369 +Epoch: [27] Total time: 1:09:53 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 2:12:12 time: 3.0828 data: 2.9756 max mem: 33369 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 100/2573] eta: 0:04:24 time: 0.0775 data: 0.0014 max mem: 33369 +Test: [ 200/2573] eta: 0:03:41 time: 0.0783 data: 0.0015 max mem: 33369 +Test: [ 300/2573] eta: 0:03:19 time: 0.0805 data: 0.0014 max mem: 33369 +Test: [ 400/2573] eta: 0:03:05 time: 0.0802 data: 0.0014 max mem: 33369 +Test: [ 500/2573] eta: 0:02:54 time: 0.0793 data: 0.0014 max mem: 33369 +Test: [ 600/2573] eta: 0:02:45 time: 0.0787 data: 0.0015 max mem: 33369 +Test: [ 700/2573] eta: 0:02:36 time: 0.0784 data: 0.0014 max mem: 33369 +Test: [ 800/2573] eta: 0:02:26 time: 0.0823 data: 0.0014 max mem: 33369 +Test: [ 900/2573] eta: 0:02:18 time: 0.0797 data: 0.0015 max mem: 33369 +Test: [1000/2573] eta: 0:02:09 time: 0.0795 data: 0.0014 max mem: 33369 +Test: [1100/2573] eta: 0:02:00 time: 0.0790 data: 0.0015 max mem: 33369 +Test: [1200/2573] eta: 0:01:52 time: 0.0801 data: 0.0014 max mem: 33369 +Test: [1300/2573] eta: 0:01:44 time: 0.0799 data: 0.0014 max mem: 33369 +Test: [1400/2573] eta: 0:01:35 time: 0.0791 data: 0.0015 max mem: 33369 +Test: [1500/2573] eta: 0:01:27 time: 0.0796 data: 0.0016 max mem: 33369 +Test: [1600/2573] eta: 0:01:19 time: 0.0833 data: 0.0015 max mem: 33369 +Test: [1700/2573] eta: 0:01:11 time: 0.0788 data: 0.0015 max mem: 33369 +Test: [1800/2573] eta: 0:01:02 time: 0.0810 data: 0.0014 max mem: 33369 +Test: [1900/2573] eta: 0:00:54 time: 0.0789 data: 0.0015 max mem: 33369 +Test: [2000/2573] eta: 0:00:46 time: 0.0809 data: 0.0015 max mem: 33369 +Test: [2100/2573] eta: 0:00:38 time: 0.0818 data: 0.0013 max mem: 33369 +Test: [2200/2573] eta: 0:00:30 time: 0.0813 data: 0.0014 max mem: 33369 +Test: [2300/2573] eta: 0:00:22 time: 0.0815 data: 0.0015 max mem: 33369 +Test: [2400/2573] eta: 0:00:13 time: 0.0762 data: 0.0014 max mem: 33369 +Test: [2500/2573] eta: 0:00:05 time: 0.0791 data: 0.0013 max mem: 33369 +Test: Total time: 0:03:28 +Final results: +Mean IoU is 64.24 + + precision@0.5 = 72.24 + precision@0.6 = 66.71 + precision@0.7 = 59.97 + precision@0.8 = 48.71 + precision@0.9 = 24.24 + overall IoU = 61.72 + +Average object IoU 64.24044879254859 +Overall IoU 61.72175598144531 +Better epoch: 27 + +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [28] [ 0/1319] eta: 1:50:34 lr: 1.69182110465679e-05 loss: 0.0335 (0.0335) time: 5.0298 data: 1.7256 max mem: 33369 +Epoch: [28] [ 10/1319] eta: 1:12:47 lr: 1.690859022703219e-05 loss: 0.0351 (0.0356) time: 3.3367 data: 0.1644 max mem: 33369 +Epoch: [28] [ 20/1319] eta: 1:10:47 lr: 1.6898968799219036e-05 loss: 0.0351 (0.0369) time: 3.1819 data: 0.0080 max mem: 33369 +Epoch: [28] [ 30/1319] eta: 1:09:23 lr: 1.6889346762705132e-05 loss: 0.0355 (0.0378) time: 3.1713 data: 0.0082 max mem: 33369 +Epoch: [28] [ 40/1319] eta: 1:08:39 lr: 1.6879724117066593e-05 loss: 0.0332 (0.0370) time: 3.1700 data: 0.0084 max mem: 33369 +Epoch: [28] [ 50/1319] eta: 1:08:06 lr: 1.6870100861878995e-05 loss: 0.0328 (0.0380) time: 3.2058 data: 0.0080 max mem: 33369 +Epoch: [28] [ 60/1319] eta: 1:07:36 lr: 1.6860476996717327e-05 loss: 0.0366 (0.0379) time: 3.2228 data: 0.0078 max mem: 33369 +Epoch: [28] [ 70/1319] eta: 1:07:05 lr: 1.6850852521156025e-05 loss: 0.0354 (0.0381) time: 3.2278 data: 0.0077 max mem: 33369 +Epoch: [28] [ 80/1319] eta: 1:06:23 lr: 1.684122743476896e-05 loss: 0.0320 (0.0373) time: 3.1955 data: 0.0083 max mem: 33369 +Epoch: [28] [ 90/1319] eta: 1:05:48 lr: 1.6831601737129412e-05 loss: 0.0320 (0.0384) time: 3.1797 data: 0.0086 max mem: 33369 +Epoch: [28] [ 100/1319] eta: 1:05:09 lr: 1.6821975427810122e-05 loss: 0.0330 (0.0385) time: 3.1727 data: 0.0083 max mem: 33369 +Epoch: [28] [ 110/1319] eta: 1:04:33 lr: 1.6812348506383245e-05 loss: 0.0303 (0.0382) time: 3.1636 data: 0.0081 max mem: 33369 +Epoch: [28] [ 120/1319] eta: 1:03:57 lr: 1.680272097242036e-05 loss: 0.0321 (0.0380) time: 3.1708 data: 0.0080 max mem: 33369 +Epoch: [28] [ 130/1319] eta: 1:03:24 lr: 1.6793092825492484e-05 loss: 0.0332 (0.0377) time: 3.1725 data: 0.0081 max mem: 33369 +Epoch: [28] [ 140/1319] eta: 1:02:49 lr: 1.6783464065170062e-05 loss: 0.0320 (0.0373) time: 3.1761 data: 0.0083 max mem: 33369 +Epoch: [28] [ 150/1319] eta: 1:02:15 lr: 1.6773834691022944e-05 loss: 0.0294 (0.0372) time: 3.1705 data: 0.0081 max mem: 33369 +Epoch: [28] [ 160/1319] eta: 1:01:39 lr: 1.6764204702620422e-05 loss: 0.0345 (0.0373) time: 3.1558 data: 0.0080 max mem: 33369 +Epoch: [28] [ 170/1319] eta: 1:01:10 lr: 1.6754574099531206e-05 loss: 0.0345 (0.0373) time: 3.1883 data: 0.0079 max mem: 33369 +Epoch: [28] [ 180/1319] eta: 1:00:34 lr: 1.6744942881323427e-05 loss: 0.0332 (0.0372) time: 3.1783 data: 0.0077 max mem: 33369 +Epoch: [28] [ 190/1319] eta: 0:59:59 lr: 1.6735311047564646e-05 loss: 0.0319 (0.0372) time: 3.1323 data: 0.0078 max mem: 33369 +Epoch: [28] [ 200/1319] eta: 0:59:27 lr: 1.6725678597821815e-05 loss: 0.0312 (0.0374) time: 3.1661 data: 0.0079 max mem: 33369 +Epoch: [28] [ 210/1319] eta: 0:58:52 lr: 1.6716045531661334e-05 loss: 0.0312 (0.0375) time: 3.1616 data: 0.0086 max mem: 33369 +Epoch: [28] [ 220/1319] eta: 0:58:20 lr: 1.6706411848649008e-05 loss: 0.0385 (0.0376) time: 3.1502 data: 0.0086 max mem: 33369 +Epoch: [28] [ 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mem: 33369 +Epoch: [28] [ 310/1319] eta: 0:53:36 lr: 1.6619680871272843e-05 loss: 0.0359 (0.0376) time: 3.1989 data: 0.0076 max mem: 33369 +Epoch: [28] [ 320/1319] eta: 0:53:05 lr: 1.6610040995732262e-05 loss: 0.0363 (0.0376) time: 3.2088 data: 0.0084 max mem: 33369 +Epoch: [28] [ 330/1319] eta: 0:52:34 lr: 1.6600400498524878e-05 loss: 0.0363 (0.0377) time: 3.2119 data: 0.0084 max mem: 33369 +Epoch: [28] [ 340/1319] eta: 0:52:02 lr: 1.659075937920942e-05 loss: 0.0371 (0.0380) time: 3.1964 data: 0.0081 max mem: 33369 +Epoch: [28] [ 350/1319] eta: 0:51:28 lr: 1.6581117637343994e-05 loss: 0.0354 (0.0379) time: 3.1470 data: 0.0080 max mem: 33369 +Epoch: [28] [ 360/1319] eta: 0:50:56 lr: 1.657147527248612e-05 loss: 0.0321 (0.0377) time: 3.1603 data: 0.0077 max mem: 33369 +Epoch: [28] [ 370/1319] eta: 0:50:25 lr: 1.6561832284192722e-05 loss: 0.0375 (0.0379) time: 3.2046 data: 0.0080 max mem: 33369 +Epoch: [28] [ 380/1319] eta: 0:49:53 lr: 1.6552188672020112e-05 loss: 0.0385 (0.0385) time: 3.1932 data: 0.0084 max mem: 33369 +Epoch: [28] [ 390/1319] eta: 0:49:22 lr: 1.654254443552401e-05 loss: 0.0321 (0.0384) time: 3.1980 data: 0.0082 max mem: 33369 +Epoch: [28] [ 400/1319] eta: 0:48:49 lr: 1.6532899574259518e-05 loss: 0.0326 (0.0383) time: 3.1808 data: 0.0082 max mem: 33369 +Epoch: [28] [ 410/1319] eta: 0:48:15 lr: 1.6523254087781154e-05 loss: 0.0337 (0.0382) time: 3.1298 data: 0.0080 max mem: 33369 +Epoch: [28] [ 420/1319] eta: 0:47:44 lr: 1.651360797564279e-05 loss: 0.0369 (0.0383) time: 3.1538 data: 0.0079 max mem: 33369 +Epoch: [28] [ 430/1319] eta: 0:47:13 lr: 1.6503961237397734e-05 loss: 0.0360 (0.0382) time: 3.2123 data: 0.0086 max mem: 33369 +Epoch: [28] [ 440/1319] eta: 0:46:41 lr: 1.6494313872598656e-05 loss: 0.0320 (0.0381) time: 3.2234 data: 0.0086 max mem: 33369 +Epoch: [28] [ 450/1319] eta: 0:46:09 lr: 1.6484665880797628e-05 loss: 0.0361 (0.0381) time: 3.1934 data: 0.0083 max mem: 33369 +Epoch: [28] [ 460/1319] eta: 0:45:37 lr: 1.6475017261546112e-05 loss: 0.0387 (0.0382) time: 3.1783 data: 0.0085 max mem: 33369 +Epoch: [28] [ 470/1319] eta: 0:45:05 lr: 1.6465368014394945e-05 loss: 0.0401 (0.0382) time: 3.1813 data: 0.0078 max mem: 33369 +Epoch: [28] [ 480/1319] eta: 0:44:33 lr: 1.6455718138894353e-05 loss: 0.0363 (0.0382) time: 3.1733 data: 0.0081 max mem: 33369 +Epoch: [28] [ 490/1319] eta: 0:44:01 lr: 1.6446067634593955e-05 loss: 0.0347 (0.0381) time: 3.1763 data: 0.0082 max mem: 33369 +Epoch: [28] [ 500/1319] eta: 0:43:28 lr: 1.6436416501042754e-05 loss: 0.0319 (0.0380) time: 3.1617 data: 0.0077 max mem: 33369 +Epoch: [28] [ 510/1319] eta: 0:42:57 lr: 1.6426764737789128e-05 loss: 0.0310 (0.0379) time: 3.1795 data: 0.0078 max mem: 33369 +Epoch: [28] [ 520/1319] eta: 0:42:25 lr: 1.6417112344380827e-05 loss: 0.0310 (0.0379) time: 3.2019 data: 0.0078 max mem: 33369 +Epoch: [28] [ 530/1319] eta: 0:41:53 lr: 1.6407459320365e-05 loss: 0.0343 (0.0380) time: 3.1716 data: 0.0076 max mem: 33369 +Epoch: [28] [ 540/1319] eta: 0:41:21 lr: 1.6397805665288162e-05 loss: 0.0313 (0.0379) time: 3.1669 data: 0.0075 max mem: 33369 +Epoch: [28] [ 550/1319] eta: 0:40:49 lr: 1.6388151378696212e-05 loss: 0.0352 (0.0379) time: 3.1790 data: 0.0074 max mem: 33369 +Epoch: [28] [ 560/1319] eta: 0:40:17 lr: 1.6378496460134414e-05 loss: 0.0361 (0.0379) time: 3.1777 data: 0.0076 max mem: 33369 +Epoch: [28] [ 570/1319] eta: 0:39:45 lr: 1.636884090914743e-05 loss: 0.0329 (0.0379) time: 3.1589 data: 0.0077 max mem: 33369 +Epoch: [28] [ 580/1319] eta: 0:39:13 lr: 1.635918472527926e-05 loss: 0.0305 (0.0377) time: 3.1521 data: 0.0079 max mem: 33369 +Epoch: [28] [ 590/1319] eta: 0:38:41 lr: 1.6349527908073296e-05 loss: 0.0306 (0.0377) time: 3.1848 data: 0.0079 max mem: 33369 +Epoch: [28] [ 600/1319] eta: 0:38:09 lr: 1.6339870457072308e-05 loss: 0.0337 (0.0376) time: 3.1967 data: 0.0081 max mem: 33369 +Epoch: [28] [ 610/1319] eta: 0:37:37 lr: 1.6330212371818425e-05 loss: 0.0373 (0.0377) time: 3.1505 data: 0.0080 max mem: 33369 +Epoch: [28] [ 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33370 +Epoch: [28] [ 700/1319] eta: 0:32:50 lr: 1.6243260987290905e-05 loss: 0.0333 (0.0379) time: 3.1697 data: 0.0084 max mem: 33370 +Epoch: [28] [ 710/1319] eta: 0:32:18 lr: 1.6233596534185593e-05 loss: 0.0333 (0.0379) time: 3.1479 data: 0.0081 max mem: 33370 +Epoch: [28] [ 720/1319] eta: 0:31:46 lr: 1.6223931441748828e-05 loss: 0.0328 (0.0379) time: 3.1216 data: 0.0079 max mem: 33370 +Epoch: [28] [ 730/1319] eta: 0:31:14 lr: 1.6214265709515084e-05 loss: 0.0308 (0.0379) time: 3.1697 data: 0.0077 max mem: 33370 +Epoch: [28] [ 740/1319] eta: 0:30:42 lr: 1.620459933701816e-05 loss: 0.0333 (0.0378) time: 3.2055 data: 0.0076 max mem: 33370 +Epoch: [28] [ 750/1319] eta: 0:30:11 lr: 1.6194932323791233e-05 loss: 0.0333 (0.0378) time: 3.2045 data: 0.0079 max mem: 33370 +Epoch: [28] [ 760/1319] eta: 0:29:39 lr: 1.6185264669366818e-05 loss: 0.0319 (0.0378) time: 3.2091 data: 0.0077 max mem: 33370 +Epoch: [28] [ 770/1319] eta: 0:29:07 lr: 1.617559637327677e-05 loss: 0.0352 (0.0378) time: 3.1911 data: 0.0073 max mem: 33370 +Epoch: [28] [ 780/1319] eta: 0:28:36 lr: 1.6165927435052318e-05 loss: 0.0359 (0.0378) time: 3.1960 data: 0.0079 max mem: 33370 +Epoch: [28] [ 790/1319] eta: 0:28:03 lr: 1.6156257854223998e-05 loss: 0.0376 (0.0379) time: 3.1592 data: 0.0087 max mem: 33370 +Epoch: [28] [ 800/1319] eta: 0:27:31 lr: 1.614658763032172e-05 loss: 0.0387 (0.0378) time: 3.1445 data: 0.0085 max mem: 33370 +Epoch: [28] [ 810/1319] eta: 0:26:59 lr: 1.6136916762874727e-05 loss: 0.0346 (0.0379) time: 3.1618 data: 0.0080 max mem: 33370 +Epoch: [28] [ 820/1319] eta: 0:26:28 lr: 1.6127245251411607e-05 loss: 0.0329 (0.0378) time: 3.1671 data: 0.0081 max mem: 33370 +Epoch: [28] [ 830/1319] eta: 0:25:56 lr: 1.6117573095460284e-05 loss: 0.0326 (0.0378) time: 3.1949 data: 0.0079 max mem: 33370 +Epoch: [28] [ 840/1319] eta: 0:25:24 lr: 1.610790029454803e-05 loss: 0.0362 (0.0378) time: 3.1782 data: 0.0075 max mem: 33370 +Epoch: [28] [ 850/1319] eta: 0:24:52 lr: 1.609822684820143e-05 loss: 0.0329 (0.0379) time: 3.1590 data: 0.0075 max mem: 33370 +Epoch: [28] [ 860/1319] eta: 0:24:20 lr: 1.608855275594644e-05 loss: 0.0327 (0.0378) time: 3.1636 data: 0.0083 max mem: 33370 +Epoch: [28] [ 870/1319] eta: 0:23:48 lr: 1.6078878017308325e-05 loss: 0.0296 (0.0378) time: 3.1712 data: 0.0085 max mem: 33370 +Epoch: [28] [ 880/1319] eta: 0:23:16 lr: 1.6069202631811695e-05 loss: 0.0300 (0.0379) time: 3.1488 data: 0.0080 max mem: 33370 +Epoch: [28] [ 890/1319] eta: 0:22:44 lr: 1.6059526598980493e-05 loss: 0.0383 (0.0379) time: 3.1637 data: 0.0080 max mem: 33370 +Epoch: [28] [ 900/1319] eta: 0:22:12 lr: 1.6049849918337977e-05 loss: 0.0393 (0.0379) time: 3.1680 data: 0.0077 max mem: 33370 +Epoch: [28] [ 910/1319] eta: 0:21:40 lr: 1.6040172589406754e-05 loss: 0.0328 (0.0378) time: 3.1228 data: 0.0077 max mem: 33370 +Epoch: [28] [ 920/1319] eta: 0:21:09 lr: 1.603049461170875e-05 loss: 0.0328 (0.0378) time: 3.1692 data: 0.0080 max mem: 33370 +Epoch: [28] [ 930/1319] eta: 0:20:37 lr: 1.602081598476522e-05 loss: 0.0364 (0.0379) time: 3.1856 data: 0.0078 max mem: 33370 +Epoch: [28] [ 940/1319] eta: 0:20:05 lr: 1.6011136708096744e-05 loss: 0.0404 (0.0379) time: 3.1615 data: 0.0076 max mem: 33370 +Epoch: [28] [ 950/1319] eta: 0:19:33 lr: 1.6001456781223216e-05 loss: 0.0348 (0.0379) time: 3.1674 data: 0.0080 max mem: 33370 +Epoch: [28] [ 960/1319] eta: 0:19:01 lr: 1.599177620366387e-05 loss: 0.0342 (0.0379) time: 3.1557 data: 0.0080 max mem: 33370 +Epoch: [28] [ 970/1319] eta: 0:18:29 lr: 1.598209497493724e-05 loss: 0.0372 (0.0379) time: 3.1671 data: 0.0073 max mem: 33370 +Epoch: [28] [ 980/1319] eta: 0:17:57 lr: 1.5972413094561205e-05 loss: 0.0361 (0.0379) time: 3.1672 data: 0.0073 max mem: 33370 +Epoch: [28] [ 990/1319] eta: 0:17:26 lr: 1.5962730562052938e-05 loss: 0.0342 (0.0378) time: 3.1935 data: 0.0075 max mem: 33370 +Epoch: [28] [1000/1319] eta: 0:16:54 lr: 1.5953047376928946e-05 loss: 0.0344 (0.0378) time: 3.2254 data: 0.0076 max mem: 33370 +Epoch: [28] [1010/1319] eta: 0:16:22 lr: 1.5943363538705032e-05 loss: 0.0360 (0.0378) time: 3.2023 data: 0.0077 max mem: 33370 +Epoch: [28] [1020/1319] eta: 0:15:51 lr: 1.5933679046896337e-05 loss: 0.0381 (0.0378) time: 3.1962 data: 0.0077 max mem: 33370 +Epoch: [28] [1030/1319] eta: 0:15:19 lr: 1.592399390101729e-05 loss: 0.0381 (0.0378) time: 3.1920 data: 0.0076 max mem: 33370 +Epoch: [28] [1040/1319] eta: 0:14:47 lr: 1.5914308100581652e-05 loss: 0.0333 (0.0379) time: 3.1761 data: 0.0077 max mem: 33370 +Epoch: [28] [1050/1319] eta: 0:14:15 lr: 1.5904621645102482e-05 loss: 0.0390 (0.0379) time: 3.1838 data: 0.0077 max mem: 33370 +Epoch: [28] [1060/1319] eta: 0:13:43 lr: 1.5894934534092145e-05 loss: 0.0322 (0.0379) time: 3.1672 data: 0.0075 max mem: 33370 +Epoch: [28] [1070/1319] eta: 0:13:11 lr: 1.588524676706232e-05 loss: 0.0322 (0.0379) time: 3.1297 data: 0.0078 max mem: 33370 +Epoch: [28] [1080/1319] eta: 0:12:40 lr: 1.5875558343523986e-05 loss: 0.0398 (0.0380) time: 3.1602 data: 0.0082 max mem: 33370 +Epoch: [28] [1090/1319] eta: 0:12:08 lr: 1.5865869262987425e-05 loss: 0.0374 (0.0380) time: 3.1703 data: 0.0085 max mem: 33370 +Epoch: [28] [1100/1319] eta: 0:11:36 lr: 1.5856179524962237e-05 loss: 0.0363 (0.0380) time: 3.1794 data: 0.0081 max mem: 33370 +Epoch: [28] [1110/1319] eta: 0:11:04 lr: 1.5846489128957288e-05 loss: 0.0364 (0.0381) time: 3.1999 data: 0.0080 max mem: 33370 +Epoch: [28] [1120/1319] eta: 0:10:32 lr: 1.5836798074480774e-05 loss: 0.0387 (0.0381) time: 3.1994 data: 0.0079 max mem: 33370 +Epoch: [28] [1130/1319] eta: 0:10:01 lr: 1.582710636104018e-05 loss: 0.0393 (0.0381) time: 3.1958 data: 0.0074 max mem: 33370 +Epoch: [28] [1140/1319] eta: 0:09:29 lr: 1.5817413988142284e-05 loss: 0.0388 (0.0381) time: 3.1706 data: 0.0079 max mem: 33370 +Epoch: [28] [1150/1319] eta: 0:08:57 lr: 1.5807720955293166e-05 loss: 0.0366 (0.0381) time: 3.1680 data: 0.0084 max mem: 33370 +Epoch: [28] [1160/1319] eta: 0:08:25 lr: 1.579802726199819e-05 loss: 0.0345 (0.0381) time: 3.1903 data: 0.0079 max mem: 33370 +Epoch: [28] [1170/1319] eta: 0:07:53 lr: 1.5788332907762015e-05 loss: 0.0350 (0.0380) time: 3.2045 data: 0.0078 max mem: 33370 +Epoch: [28] [1180/1319] eta: 0:07:22 lr: 1.577863789208859e-05 loss: 0.0402 (0.0381) time: 3.1832 data: 0.0080 max mem: 33370 +Epoch: [28] [1190/1319] eta: 0:06:50 lr: 1.576894221448116e-05 loss: 0.0379 (0.0380) time: 3.1678 data: 0.0086 max mem: 33370 +Epoch: [28] [1200/1319] eta: 0:06:18 lr: 1.5759245874442245e-05 loss: 0.0301 (0.0380) time: 3.1363 data: 0.0089 max mem: 33370 +Epoch: [28] [1210/1319] eta: 0:05:46 lr: 1.5749548871473663e-05 loss: 0.0309 (0.0380) time: 3.1482 data: 0.0088 max mem: 33370 +Epoch: [28] [1220/1319] eta: 0:05:14 lr: 1.57398512050765e-05 loss: 0.0359 (0.0380) time: 3.1613 data: 0.0084 max mem: 33370 +Epoch: [28] [1230/1319] eta: 0:04:42 lr: 1.5730152874751144e-05 loss: 0.0393 (0.0380) time: 3.1652 data: 0.0075 max mem: 33370 +Epoch: [28] [1240/1319] eta: 0:04:11 lr: 1.572045387999725e-05 loss: 0.0363 (0.0380) time: 3.1913 data: 0.0077 max mem: 33370 +Epoch: [28] [1250/1319] eta: 0:03:39 lr: 1.5710754220313764e-05 loss: 0.0359 (0.0380) time: 3.1782 data: 0.0079 max mem: 33370 +Epoch: [28] [1260/1319] eta: 0:03:07 lr: 1.5701053895198906e-05 loss: 0.0331 (0.0379) time: 3.1775 data: 0.0078 max mem: 33370 +Epoch: [28] [1270/1319] eta: 0:02:35 lr: 1.5691352904150157e-05 loss: 0.0308 (0.0381) time: 3.1921 data: 0.0078 max mem: 33370 +Epoch: [28] [1280/1319] eta: 0:02:04 lr: 1.5681651246664294e-05 loss: 0.0303 (0.0381) time: 3.2156 data: 0.0080 max mem: 33370 +Epoch: [28] [1290/1319] eta: 0:01:32 lr: 1.5671948922237363e-05 loss: 0.0323 (0.0381) time: 3.2060 data: 0.0078 max mem: 33370 +Epoch: [28] [1300/1319] eta: 0:01:00 lr: 1.5662245930364672e-05 loss: 0.0324 (0.0380) time: 3.1430 data: 0.0079 max mem: 33370 +Epoch: [28] [1310/1319] eta: 0:00:28 lr: 1.5652542270540813e-05 loss: 0.0371 (0.0382) time: 3.1452 data: 0.0078 max mem: 33370 +Epoch: [28] Total time: 1:09:54 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 2:04:41 time: 2.9078 data: 2.8005 max mem: 33370 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 100/2573] eta: 0:04:21 time: 0.0777 data: 0.0015 max mem: 33370 +Test: [ 200/2573] eta: 0:03:40 time: 0.0788 data: 0.0015 max mem: 33370 +Test: [ 300/2573] eta: 0:03:19 time: 0.0814 data: 0.0014 max mem: 33370 +Test: [ 400/2573] eta: 0:03:05 time: 0.0794 data: 0.0014 max mem: 33370 +Test: [ 500/2573] eta: 0:02:54 time: 0.0785 data: 0.0015 max mem: 33370 +Test: [ 600/2573] eta: 0:02:44 time: 0.0797 data: 0.0015 max mem: 33370 +Test: [ 700/2573] eta: 0:02:35 time: 0.0799 data: 0.0015 max mem: 33370 +Test: [ 800/2573] eta: 0:02:26 time: 0.0822 data: 0.0014 max mem: 33370 +Test: [ 900/2573] eta: 0:02:18 time: 0.0799 data: 0.0016 max mem: 33370 +Test: [1000/2573] eta: 0:02:09 time: 0.0785 data: 0.0014 max mem: 33370 +Test: [1100/2573] eta: 0:02:00 time: 0.0798 data: 0.0014 max mem: 33370 +Test: [1200/2573] eta: 0:01:52 time: 0.0798 data: 0.0015 max mem: 33370 +Test: [1300/2573] eta: 0:01:43 time: 0.0793 data: 0.0014 max mem: 33370 +Test: [1400/2573] eta: 0:01:35 time: 0.0771 data: 0.0014 max mem: 33370 +Test: [1500/2573] eta: 0:01:27 time: 0.0788 data: 0.0013 max mem: 33370 +Test: [1600/2573] eta: 0:01:19 time: 0.0819 data: 0.0015 max mem: 33370 +Test: [1700/2573] eta: 0:01:10 time: 0.0778 data: 0.0014 max mem: 33370 +Test: [1800/2573] eta: 0:01:02 time: 0.0817 data: 0.0014 max mem: 33370 +Test: [1900/2573] eta: 0:00:54 time: 0.0784 data: 0.0015 max mem: 33370 +Test: [2000/2573] eta: 0:00:46 time: 0.0791 data: 0.0014 max mem: 33370 +Test: [2100/2573] eta: 0:00:38 time: 0.0820 data: 0.0014 max mem: 33370 +Test: [2200/2573] eta: 0:00:30 time: 0.0809 data: 0.0013 max mem: 33370 +Test: [2300/2573] eta: 0:00:22 time: 0.0817 data: 0.0015 max mem: 33370 +Test: [2400/2573] eta: 0:00:13 time: 0.0767 data: 0.0015 max mem: 33370 +Test: [2500/2573] eta: 0:00:05 time: 0.0790 data: 0.0014 max mem: 33370 +Test: Total time: 0:03:27 +Final results: +Mean IoU is 63.73 + + precision@0.5 = 71.75 + precision@0.6 = 66.52 + precision@0.7 = 59.78 + precision@0.8 = 48.00 + precision@0.9 = 24.45 + overall IoU = 61.43 + +Average object IoU 63.729281825396185 +Overall IoU 61.43355178833008 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [29] [ 0/1319] eta: 2:46:12 lr: 1.5643808405182777e-05 loss: 0.0326 (0.0326) time: 7.5608 data: 2.5236 max mem: 33370 +Epoch: [29] [ 10/1319] eta: 1:18:11 lr: 1.563410347485666e-05 loss: 0.0296 (0.0359) time: 3.5840 data: 0.2369 max mem: 33370 +Epoch: [29] [ 20/1319] eta: 1:14:06 lr: 1.5624397875109532e-05 loss: 0.0360 (0.0383) time: 3.2161 data: 0.0078 max mem: 33370 +Epoch: [29] [ 30/1319] eta: 1:11:57 lr: 1.5614691605433113e-05 loss: 0.0364 (0.0373) time: 3.2202 data: 0.0078 max mem: 33370 +Epoch: [29] [ 40/1319] eta: 1:10:55 lr: 1.5604984665318397e-05 loss: 0.0311 (0.0358) time: 3.2266 data: 0.0081 max mem: 33370 +Epoch: [29] [ 50/1319] eta: 1:09:44 lr: 1.5595277054255625e-05 loss: 0.0313 (0.0359) time: 3.2175 data: 0.0077 max mem: 33370 +Epoch: [29] [ 60/1319] eta: 1:08:41 lr: 1.558556877173431e-05 loss: 0.0339 (0.0360) time: 3.1626 data: 0.0077 max mem: 33370 +Epoch: [29] [ 70/1319] eta: 1:07:47 lr: 1.557585981724323e-05 loss: 0.0327 (0.0359) time: 3.1514 data: 0.0080 max mem: 33370 +Epoch: [29] [ 80/1319] eta: 1:07:12 lr: 1.5566150190270393e-05 loss: 0.0327 (0.0361) time: 3.1976 data: 0.0084 max mem: 33370 +Epoch: [29] [ 90/1319] eta: 1:06:27 lr: 1.5556439890303075e-05 loss: 0.0322 (0.0361) time: 3.2017 data: 0.0084 max mem: 33370 +Epoch: [29] [ 100/1319] eta: 1:05:48 lr: 1.554672891682782e-05 loss: 0.0299 (0.0366) time: 3.1786 data: 0.0083 max mem: 33370 +Epoch: [29] [ 110/1319] eta: 1:05:09 lr: 1.55370172693304e-05 loss: 0.0299 (0.0363) time: 3.1846 data: 0.0086 max mem: 33370 +Epoch: [29] [ 120/1319] eta: 1:04:29 lr: 1.552730494729585e-05 loss: 0.0325 (0.0359) time: 3.1674 data: 0.0083 max mem: 33370 +Epoch: [29] [ 130/1319] eta: 1:03:52 lr: 1.551759195020846e-05 loss: 0.0333 (0.0360) time: 3.1635 data: 0.0082 max mem: 33370 +Epoch: [29] [ 140/1319] eta: 1:03:18 lr: 1.5507878277551742e-05 loss: 0.0287 (0.0358) time: 3.1892 data: 0.0081 max mem: 33370 +Epoch: [29] [ 150/1319] eta: 1:02:46 lr: 1.5498163928808475e-05 loss: 0.0287 (0.0354) time: 3.2163 data: 0.0079 max mem: 33370 +Epoch: [29] [ 160/1319] eta: 1:02:10 lr: 1.548844890346068e-05 loss: 0.0293 (0.0352) time: 3.1933 data: 0.0078 max mem: 33370 +Epoch: [29] [ 170/1319] eta: 1:01:32 lr: 1.547873320098961e-05 loss: 0.0333 (0.0353) time: 3.1523 data: 0.0078 max mem: 33370 +Epoch: [29] [ 180/1319] eta: 1:00:57 lr: 1.546901682087577e-05 loss: 0.0345 (0.0355) time: 3.1505 data: 0.0078 max mem: 33370 +Epoch: [29] [ 190/1319] eta: 1:00:23 lr: 1.5459299762598884e-05 loss: 0.0358 (0.0355) time: 3.1723 data: 0.0078 max mem: 33370 +Epoch: [29] [ 200/1319] eta: 0:59:52 lr: 1.5449582025637935e-05 loss: 0.0315 (0.0354) time: 3.2009 data: 0.0079 max mem: 33370 +Epoch: [29] [ 210/1319] eta: 0:59:14 lr: 1.543986360947113e-05 loss: 0.0315 (0.0354) time: 3.1640 data: 0.0081 max mem: 33370 +Epoch: [29] [ 220/1319] eta: 0:58:41 lr: 1.543014451357591e-05 loss: 0.0357 (0.0355) time: 3.1444 data: 0.0083 max mem: 33370 +Epoch: [29] [ 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data: 0.0075 max mem: 33370 +Epoch: [29] [ 390/1319] eta: 0:49:25 lr: 1.526481537480438e-05 loss: 0.0286 (0.0358) time: 3.1787 data: 0.0075 max mem: 33370 +Epoch: [29] [ 400/1319] eta: 0:48:51 lr: 1.525508395355664e-05 loss: 0.0324 (0.0360) time: 3.1540 data: 0.0078 max mem: 33370 +Epoch: [29] [ 410/1319] eta: 0:48:17 lr: 1.5245351842504036e-05 loss: 0.0343 (0.0361) time: 3.1068 data: 0.0079 max mem: 33370 +Epoch: [29] [ 420/1319] eta: 0:47:45 lr: 1.5235619041108326e-05 loss: 0.0343 (0.0362) time: 3.1396 data: 0.0076 max mem: 33370 +Epoch: [29] [ 430/1319] eta: 0:47:12 lr: 1.5225885548830468e-05 loss: 0.0328 (0.0362) time: 3.1596 data: 0.0078 max mem: 33370 +Epoch: [29] [ 440/1319] eta: 0:46:41 lr: 1.5216151365130616e-05 loss: 0.0297 (0.0362) time: 3.1836 data: 0.0080 max mem: 33370 +Epoch: [29] [ 450/1319] eta: 0:46:08 lr: 1.520641648946812e-05 loss: 0.0304 (0.0363) time: 3.1804 data: 0.0076 max mem: 33370 +Epoch: [29] [ 460/1319] eta: 0:45:35 lr: 1.519668092130151e-05 loss: 0.0408 (0.0363) time: 3.1337 data: 0.0074 max mem: 33370 +Epoch: [29] [ 470/1319] eta: 0:45:03 lr: 1.5186944660088521e-05 loss: 0.0408 (0.0366) time: 3.1436 data: 0.0076 max mem: 33370 +Epoch: [29] [ 480/1319] eta: 0:44:31 lr: 1.5177207705286068e-05 loss: 0.0366 (0.0366) time: 3.1638 data: 0.0081 max mem: 33370 +Epoch: [29] [ 490/1319] eta: 0:43:58 lr: 1.5167470056350257e-05 loss: 0.0316 (0.0365) time: 3.1401 data: 0.0080 max mem: 33370 +Epoch: [29] [ 500/1319] eta: 0:43:26 lr: 1.5157731712736389e-05 loss: 0.0316 (0.0365) time: 3.1644 data: 0.0079 max mem: 33370 +Epoch: [29] [ 510/1319] eta: 0:42:54 lr: 1.514799267389892e-05 loss: 0.0369 (0.0365) time: 3.1879 data: 0.0078 max mem: 33370 +Epoch: [29] [ 520/1319] eta: 0:42:22 lr: 1.5138252939291514e-05 loss: 0.0328 (0.0364) time: 3.1721 data: 0.0077 max mem: 33370 +Epoch: [29] [ 530/1319] eta: 0:41:50 lr: 1.5128512508367005e-05 loss: 0.0289 (0.0363) time: 3.1601 data: 0.0078 max mem: 33370 +Epoch: [29] [ 540/1319] eta: 0:41:19 lr: 1.5118771380577405e-05 loss: 0.0333 (0.0362) time: 3.1896 data: 0.0079 max mem: 33370 +Epoch: [29] [ 550/1319] eta: 0:40:46 lr: 1.5109029555373904e-05 loss: 0.0359 (0.0364) time: 3.1777 data: 0.0077 max mem: 33370 +Epoch: [29] [ 560/1319] eta: 0:40:14 lr: 1.5099287032206873e-05 loss: 0.0339 (0.0363) time: 3.1307 data: 0.0084 max mem: 33370 +Epoch: [29] [ 570/1319] eta: 0:39:42 lr: 1.5089543810525833e-05 loss: 0.0287 (0.0363) time: 3.1714 data: 0.0088 max mem: 33370 +Epoch: [29] [ 580/1319] eta: 0:39:10 lr: 1.50797998897795e-05 loss: 0.0313 (0.0363) time: 3.1687 data: 0.0082 max mem: 33370 +Epoch: [29] [ 590/1319] eta: 0:38:38 lr: 1.5070055269415744e-05 loss: 0.0367 (0.0363) time: 3.1595 data: 0.0081 max mem: 33370 +Epoch: [29] [ 600/1319] eta: 0:38:05 lr: 1.5060309948881612e-05 loss: 0.0316 (0.0363) time: 3.1326 data: 0.0082 max mem: 33370 +Epoch: [29] [ 610/1319] eta: 0:37:33 lr: 1.5050563927623313e-05 loss: 0.0334 (0.0363) time: 3.1229 data: 0.0079 max mem: 33370 +Epoch: [29] [ 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data: 0.0077 max mem: 33370 +Epoch: [29] [ 780/1319] eta: 0:28:32 lr: 1.4884773814725032e-05 loss: 0.0354 (0.0369) time: 3.1759 data: 0.0080 max mem: 33370 +Epoch: [29] [ 790/1319] eta: 0:28:00 lr: 1.4875015084769944e-05 loss: 0.0320 (0.0370) time: 3.1733 data: 0.0083 max mem: 33370 +Epoch: [29] [ 800/1319] eta: 0:27:29 lr: 1.4865255643407467e-05 loss: 0.0330 (0.0369) time: 3.1848 data: 0.0078 max mem: 33370 +Epoch: [29] [ 810/1319] eta: 0:26:57 lr: 1.4855495490066707e-05 loss: 0.0349 (0.0370) time: 3.1862 data: 0.0077 max mem: 33370 +Epoch: [29] [ 820/1319] eta: 0:26:25 lr: 1.4845734624175911e-05 loss: 0.0349 (0.0370) time: 3.1722 data: 0.0078 max mem: 33370 +Epoch: [29] [ 830/1319] eta: 0:25:53 lr: 1.4835973045162419e-05 loss: 0.0320 (0.0370) time: 3.1765 data: 0.0076 max mem: 33370 +Epoch: [29] [ 840/1319] eta: 0:25:21 lr: 1.4826210752452718e-05 loss: 0.0324 (0.0370) time: 3.1669 data: 0.0078 max mem: 33370 +Epoch: [29] [ 850/1319] eta: 0:24:50 lr: 1.48164477454724e-05 loss: 0.0319 (0.0370) time: 3.1549 data: 0.0086 max mem: 33370 +Epoch: [29] [ 860/1319] eta: 0:24:18 lr: 1.4806684023646183e-05 loss: 0.0318 (0.0370) time: 3.1935 data: 0.0082 max mem: 33370 +Epoch: [29] [ 870/1319] eta: 0:23:46 lr: 1.4796919586397895e-05 loss: 0.0367 (0.0371) time: 3.2027 data: 0.0073 max mem: 33370 +Epoch: [29] [ 880/1319] eta: 0:23:14 lr: 1.4787154433150476e-05 loss: 0.0353 (0.0370) time: 3.1770 data: 0.0078 max mem: 33370 +Epoch: [29] [ 890/1319] eta: 0:22:43 lr: 1.4777388563325976e-05 loss: 0.0308 (0.0370) time: 3.2036 data: 0.0079 max mem: 33370 +Epoch: [29] [ 900/1319] eta: 0:22:11 lr: 1.4767621976345552e-05 loss: 0.0335 (0.0370) time: 3.2022 data: 0.0079 max mem: 33370 +Epoch: [29] [ 910/1319] eta: 0:21:39 lr: 1.4757854671629475e-05 loss: 0.0373 (0.0370) time: 3.1679 data: 0.0078 max mem: 33370 +Epoch: [29] [ 920/1319] eta: 0:21:07 lr: 1.4748086648597121e-05 loss: 0.0375 (0.0370) time: 3.1466 data: 0.0078 max mem: 33370 +Epoch: [29] [ 930/1319] eta: 0:20:35 lr: 1.4738317906666963e-05 loss: 0.0361 (0.0370) time: 3.1376 data: 0.0084 max mem: 33370 +Epoch: [29] [ 940/1319] eta: 0:20:04 lr: 1.4728548445256565e-05 loss: 0.0359 (0.0370) time: 3.1708 data: 0.0080 max mem: 33370 +Epoch: [29] [ 950/1319] eta: 0:19:32 lr: 1.471877826378261e-05 loss: 0.0338 (0.0371) time: 3.1735 data: 0.0077 max mem: 33370 +Epoch: [29] [ 960/1319] eta: 0:19:00 lr: 1.4709007361660864e-05 loss: 0.0366 (0.0371) time: 3.1952 data: 0.0079 max mem: 33370 +Epoch: [29] [ 970/1319] eta: 0:18:28 lr: 1.4699235738306196e-05 loss: 0.0401 (0.0371) time: 3.1759 data: 0.0077 max mem: 33370 +Epoch: [29] [ 980/1319] eta: 0:17:57 lr: 1.4689463393132561e-05 loss: 0.0328 (0.0371) time: 3.1614 data: 0.0077 max mem: 33370 +Epoch: [29] [ 990/1319] eta: 0:17:25 lr: 1.4679690325553006e-05 loss: 0.0315 (0.0371) time: 3.1817 data: 0.0077 max mem: 33370 +Epoch: [29] [1000/1319] eta: 0:16:53 lr: 1.466991653497966e-05 loss: 0.0340 (0.0371) time: 3.1566 data: 0.0077 max mem: 33370 +Epoch: [29] [1010/1319] eta: 0:16:21 lr: 1.466014202082375e-05 loss: 0.0337 (0.0371) time: 3.1562 data: 0.0078 max mem: 33370 +Epoch: [29] [1020/1319] eta: 0:15:49 lr: 1.4650366782495577e-05 loss: 0.0289 (0.0370) time: 3.1920 data: 0.0077 max mem: 33370 +Epoch: [29] [1030/1319] eta: 0:15:18 lr: 1.4640590819404531e-05 loss: 0.0320 (0.0370) time: 3.1872 data: 0.0078 max mem: 33370 +Epoch: [29] [1040/1319] eta: 0:14:46 lr: 1.4630814130959084e-05 loss: 0.0347 (0.0370) time: 3.1642 data: 0.0078 max mem: 33370 +Epoch: [29] [1050/1319] eta: 0:14:14 lr: 1.4621036716566766e-05 loss: 0.0336 (0.0370) time: 3.1658 data: 0.0077 max mem: 33370 +Epoch: [29] [1060/1319] eta: 0:13:42 lr: 1.4611258575634206e-05 loss: 0.0336 (0.0370) time: 3.1793 data: 0.0077 max mem: 33370 +Epoch: [29] [1070/1319] eta: 0:13:10 lr: 1.4601479707567092e-05 loss: 0.0363 (0.0370) time: 3.1755 data: 0.0081 max mem: 33370 +Epoch: [29] [1080/1319] eta: 0:12:39 lr: 1.4591700111770195e-05 loss: 0.0352 (0.0369) time: 3.1626 data: 0.0080 max mem: 33370 +Epoch: [29] [1090/1319] eta: 0:12:07 lr: 1.4581919787647347e-05 loss: 0.0317 (0.0369) time: 3.1707 data: 0.0079 max mem: 33370 +Epoch: [29] [1100/1319] eta: 0:11:35 lr: 1.4572138734601442e-05 loss: 0.0340 (0.0369) time: 3.1669 data: 0.0082 max mem: 33370 +Epoch: [29] [1110/1319] eta: 0:11:03 lr: 1.4562356952034447e-05 loss: 0.0341 (0.0370) time: 3.1454 data: 0.0082 max mem: 33370 +Epoch: [29] [1120/1319] eta: 0:10:31 lr: 1.4552574439347391e-05 loss: 0.0362 (0.0369) time: 3.1436 data: 0.0082 max mem: 33370 +Epoch: [29] [1130/1319] eta: 0:10:00 lr: 1.4542791195940364e-05 loss: 0.0352 (0.0369) time: 3.1393 data: 0.0085 max mem: 33370 +Epoch: [29] [1140/1319] eta: 0:09:28 lr: 1.453300722121251e-05 loss: 0.0366 (0.0370) time: 3.1471 data: 0.0085 max mem: 33370 +Epoch: [29] [1150/1319] eta: 0:08:56 lr: 1.4523222514562035e-05 loss: 0.0299 (0.0369) time: 3.1788 data: 0.0083 max mem: 33370 +Epoch: [29] [1160/1319] eta: 0:08:24 lr: 1.4513437075386188e-05 loss: 0.0277 (0.0369) time: 3.1666 data: 0.0085 max mem: 33370 +Epoch: [29] [1170/1319] eta: 0:07:53 lr: 1.4503650903081281e-05 loss: 0.0321 (0.0369) time: 3.1593 data: 0.0086 max mem: 33370 +Epoch: [29] [1180/1319] eta: 0:07:21 lr: 1.449386399704267e-05 loss: 0.0335 (0.0369) time: 3.1662 data: 0.0086 max mem: 33370 +Epoch: [29] [1190/1319] eta: 0:06:49 lr: 1.4484076356664761e-05 loss: 0.0374 (0.0369) time: 3.1709 data: 0.0089 max mem: 33370 +Epoch: [29] [1200/1319] eta: 0:06:17 lr: 1.447428798134101e-05 loss: 0.0337 (0.0370) time: 3.1738 data: 0.0090 max mem: 33370 +Epoch: [29] [1210/1319] eta: 0:05:46 lr: 1.4464498870463896e-05 loss: 0.0330 (0.0369) time: 3.1864 data: 0.0087 max mem: 33370 +Epoch: [29] [1220/1319] eta: 0:05:14 lr: 1.4454709023424959e-05 loss: 0.0336 (0.0369) time: 3.1753 data: 0.0090 max mem: 33370 +Epoch: [29] [1230/1319] eta: 0:04:42 lr: 1.444491843961477e-05 loss: 0.0346 (0.0369) time: 3.1812 data: 0.0090 max mem: 33370 +Epoch: [29] [1240/1319] eta: 0:04:10 lr: 1.4435127118422938e-05 loss: 0.0344 (0.0369) time: 3.1879 data: 0.0083 max mem: 33370 +Epoch: [29] [1250/1319] eta: 0:03:39 lr: 1.442533505923811e-05 loss: 0.0333 (0.0369) time: 3.1425 data: 0.0079 max mem: 33370 +Epoch: [29] [1260/1319] eta: 0:03:07 lr: 1.4415542261447945e-05 loss: 0.0333 (0.0369) time: 3.1524 data: 0.0078 max mem: 33370 +Epoch: [29] [1270/1319] eta: 0:02:35 lr: 1.4405748724439155e-05 loss: 0.0345 (0.0369) time: 3.1870 data: 0.0076 max mem: 33370 +Epoch: [29] [1280/1319] eta: 0:02:03 lr: 1.4395954447597464e-05 loss: 0.0311 (0.0368) time: 3.1651 data: 0.0080 max mem: 33370 +Epoch: [29] [1290/1319] eta: 0:01:32 lr: 1.4386159430307632e-05 loss: 0.0332 (0.0369) time: 3.1302 data: 0.0084 max mem: 33370 +Epoch: [29] [1300/1319] eta: 0:01:00 lr: 1.4376363671953435e-05 loss: 0.0335 (0.0368) time: 3.1325 data: 0.0084 max mem: 33370 +Epoch: [29] [1310/1319] eta: 0:00:28 lr: 1.4366567171917672e-05 loss: 0.0299 (0.0368) time: 3.1603 data: 0.0078 max mem: 33370 +Epoch: [29] Total time: 1:09:47 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 2:31:06 time: 3.5237 data: 3.4195 max mem: 33370 +Test: [ 100/2573] eta: 0:04:35 time: 0.0767 data: 0.0015 max mem: 33370 +Test: [ 200/2573] eta: 0:03:46 time: 0.0782 data: 0.0014 max mem: 33370 +Test: [ 300/2573] eta: 0:03:23 time: 0.0806 data: 0.0014 max mem: 33370 +Test: [ 400/2573] eta: 0:03:08 time: 0.0817 data: 0.0015 max mem: 33370 +Test: [ 500/2573] eta: 0:02:56 time: 0.0785 data: 0.0015 max mem: 33370 +Test: [ 600/2573] eta: 0:02:46 time: 0.0792 data: 0.0014 max mem: 33370 +Test: [ 700/2573] eta: 0:02:37 time: 0.0782 data: 0.0014 max mem: 33370 +Test: [ 800/2573] eta: 0:02:28 time: 0.0829 data: 0.0016 max mem: 33370 +Test: [ 900/2573] eta: 0:02:19 time: 0.0786 data: 0.0014 max mem: 33370 +Test: [1000/2573] eta: 0:02:10 time: 0.0786 data: 0.0014 max mem: 33370 +Test: [1100/2573] eta: 0:02:01 time: 0.0797 data: 0.0016 max mem: 33370 +Test: [1200/2573] eta: 0:01:52 time: 0.0784 data: 0.0014 max mem: 33370 +Test: [1300/2573] eta: 0:01:44 time: 0.0792 data: 0.0014 max mem: 33370 +Test: [1400/2573] eta: 0:01:35 time: 0.0779 data: 0.0014 max mem: 33370 +Test: [1500/2573] eta: 0:01:27 time: 0.0786 data: 0.0015 max mem: 33370 +Test: [1600/2573] eta: 0:01:19 time: 0.0826 data: 0.0015 max mem: 33370 +Test: [1700/2573] eta: 0:01:11 time: 0.0781 data: 0.0015 max mem: 33370 +Test: [1800/2573] eta: 0:01:02 time: 0.0808 data: 0.0014 max mem: 33370 +Test: [1900/2573] eta: 0:00:54 time: 0.0776 data: 0.0015 max mem: 33370 +Test: [2000/2573] eta: 0:00:46 time: 0.0789 data: 0.0014 max mem: 33370 +Test: [2100/2573] eta: 0:00:38 time: 0.0816 data: 0.0014 max mem: 33370 +Test: [2200/2573] eta: 0:00:30 time: 0.0828 data: 0.0014 max mem: 33370 +Test: [2300/2573] eta: 0:00:22 time: 0.0809 data: 0.0014 max mem: 33370 +Test: [2400/2573] eta: 0:00:13 time: 0.0762 data: 0.0015 max mem: 33370 +Test: [2500/2573] eta: 0:00:05 time: 0.0795 data: 0.0014 max mem: 33370 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: Total time: 0:03:28 +Final results: +Mean IoU is 63.89 + + precision@0.5 = 71.63 + precision@0.6 = 66.20 + precision@0.7 = 59.62 + precision@0.8 = 48.37 + precision@0.9 = 24.51 + overall IoU = 61.10 + +Average object IoU 63.894165788192524 +Overall IoU 61.103599548339844 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [30] [ 0/1319] eta: 2:58:26 lr: 1.4357749687236825e-05 loss: 0.0288 (0.0288) time: 8.1172 data: 2.4761 max mem: 33370 +Epoch: [30] [ 10/1319] eta: 1:19:15 lr: 1.4347951776302166e-05 loss: 0.0347 (0.0439) time: 3.6327 data: 0.2328 max mem: 33370 +Epoch: [30] [ 20/1319] eta: 1:14:42 lr: 1.433815312189048e-05 loss: 0.0337 (0.0426) time: 3.2171 data: 0.0078 max mem: 33370 +Epoch: [30] [ 30/1319] eta: 1:11:57 lr: 1.4328353723380728e-05 loss: 0.0324 (0.0395) time: 3.1936 data: 0.0077 max mem: 33370 +Epoch: [30] [ 40/1319] eta: 1:10:37 lr: 1.431855358015087e-05 loss: 0.0298 (0.0371) time: 3.1690 data: 0.0081 max mem: 33370 +Epoch: [30] [ 50/1319] eta: 1:09:20 lr: 1.4308752691577878e-05 loss: 0.0298 (0.0366) time: 3.1682 data: 0.0080 max mem: 33370 +Epoch: [30] [ 60/1319] eta: 1:08:30 lr: 1.4298951057037729e-05 loss: 0.0328 (0.0361) time: 3.1665 data: 0.0080 max mem: 33370 +Epoch: [30] [ 70/1319] eta: 1:07:45 lr: 1.4289148675905387e-05 loss: 0.0330 (0.0360) time: 3.1959 data: 0.0078 max mem: 33370 +Epoch: [30] [ 80/1319] eta: 1:07:03 lr: 1.4279345547554832e-05 loss: 0.0331 (0.0365) time: 3.1922 data: 0.0081 max mem: 33370 +Epoch: [30] [ 90/1319] eta: 1:06:23 lr: 1.4269541671359036e-05 loss: 0.0331 (0.0361) time: 3.1926 data: 0.0082 max mem: 33370 +Epoch: [30] [ 100/1319] eta: 1:05:47 lr: 1.4259737046689963e-05 loss: 0.0352 (0.0366) time: 3.2048 data: 0.0081 max mem: 33370 +Epoch: [30] [ 110/1319] eta: 1:05:12 lr: 1.424993167291858e-05 loss: 0.0340 (0.0361) time: 3.2138 data: 0.0082 max mem: 33370 +Epoch: [30] [ 120/1319] eta: 1:04:36 lr: 1.4240125549414829e-05 loss: 0.0328 (0.0364) time: 3.2036 data: 0.0081 max mem: 33370 +Epoch: [30] [ 130/1319] eta: 1:04:00 lr: 1.4230318675547643e-05 loss: 0.0343 (0.0363) time: 3.1939 data: 0.0080 max mem: 33370 +Epoch: [30] [ 140/1319] eta: 1:03:27 lr: 1.4220511050684946e-05 loss: 0.0341 (0.0360) time: 3.2088 data: 0.0078 max mem: 33370 +Epoch: [30] [ 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0.0349 (0.0347) time: 3.1741 data: 0.0077 max mem: 33370 +Epoch: [30] [ 390/1319] eta: 0:49:32 lr: 1.3975074485677755e-05 loss: 0.0317 (0.0346) time: 3.1341 data: 0.0078 max mem: 33370 +Epoch: [30] [ 400/1319] eta: 0:49:00 lr: 1.3965247109689372e-05 loss: 0.0341 (0.0347) time: 3.1573 data: 0.0080 max mem: 33370 +Epoch: [30] [ 410/1319] eta: 0:48:28 lr: 1.3955418965246752e-05 loss: 0.0357 (0.0347) time: 3.1941 data: 0.0081 max mem: 33370 +Epoch: [30] [ 420/1319] eta: 0:47:56 lr: 1.394559005168839e-05 loss: 0.0331 (0.0347) time: 3.1999 data: 0.0083 max mem: 33370 +Epoch: [30] [ 430/1319] eta: 0:47:25 lr: 1.39357603683517e-05 loss: 0.0331 (0.0347) time: 3.2192 data: 0.0084 max mem: 33370 +Epoch: [30] [ 440/1319] eta: 0:46:53 lr: 1.3925929914573002e-05 loss: 0.0348 (0.0348) time: 3.2132 data: 0.0080 max mem: 33370 +Epoch: [30] [ 450/1319] eta: 0:46:21 lr: 1.3916098689687517e-05 loss: 0.0340 (0.0351) time: 3.1977 data: 0.0076 max mem: 33370 +Epoch: [30] [ 460/1319] eta: 0:45:48 lr: 1.3906266693029377e-05 loss: 0.0320 (0.0350) time: 3.1834 data: 0.0078 max mem: 33370 +Epoch: [30] [ 470/1319] eta: 0:45:16 lr: 1.3896433923931618e-05 loss: 0.0348 (0.0351) time: 3.1693 data: 0.0080 max mem: 33370 +Epoch: [30] [ 480/1319] eta: 0:44:43 lr: 1.3886600381726167e-05 loss: 0.0303 (0.0349) time: 3.1779 data: 0.0081 max mem: 33370 +Epoch: [30] [ 490/1319] eta: 0:44:11 lr: 1.3876766065743859e-05 loss: 0.0289 (0.0349) time: 3.1845 data: 0.0081 max mem: 33370 +Epoch: [30] [ 500/1319] eta: 0:43:39 lr: 1.3866930975314405e-05 loss: 0.0311 (0.0349) time: 3.1794 data: 0.0080 max mem: 33370 +Epoch: [30] [ 510/1319] eta: 0:43:07 lr: 1.3857095109766416e-05 loss: 0.0311 (0.0349) time: 3.1795 data: 0.0079 max mem: 33370 +Epoch: [30] [ 520/1319] eta: 0:42:35 lr: 1.3847258468427396e-05 loss: 0.0352 (0.0350) time: 3.2081 data: 0.0080 max mem: 33370 +Epoch: [30] [ 530/1319] eta: 0:42:02 lr: 1.3837421050623725e-05 loss: 0.0363 (0.0351) time: 3.1874 data: 0.0077 max mem: 33370 +Epoch: [30] [ 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data: 0.0089 max mem: 33370 +Epoch: [30] [ 700/1319] eta: 0:32:56 lr: 1.3670065490679108e-05 loss: 0.0317 (0.0349) time: 3.2007 data: 0.0087 max mem: 33370 +Epoch: [30] [ 710/1319] eta: 0:32:24 lr: 1.3660213980036074e-05 loss: 0.0324 (0.0349) time: 3.2003 data: 0.0080 max mem: 33370 +Epoch: [30] [ 720/1319] eta: 0:31:52 lr: 1.3650361679914193e-05 loss: 0.0324 (0.0349) time: 3.1849 data: 0.0075 max mem: 33370 +Epoch: [30] [ 730/1319] eta: 0:31:20 lr: 1.3640508589616971e-05 loss: 0.0340 (0.0352) time: 3.1580 data: 0.0080 max mem: 33370 +Epoch: [30] [ 740/1319] eta: 0:30:48 lr: 1.3630654708446738e-05 loss: 0.0415 (0.0352) time: 3.1398 data: 0.0085 max mem: 33370 +Epoch: [30] [ 750/1319] eta: 0:30:15 lr: 1.3620800035704648e-05 loss: 0.0389 (0.0353) time: 3.1599 data: 0.0080 max mem: 33370 +Epoch: [30] [ 760/1319] eta: 0:29:44 lr: 1.3610944570690678e-05 loss: 0.0356 (0.0353) time: 3.1796 data: 0.0077 max mem: 33370 +Epoch: [30] [ 770/1319] eta: 0:29:11 lr: 1.3601088312703605e-05 loss: 0.0346 (0.0352) time: 3.1711 data: 0.0081 max mem: 33370 +Epoch: [30] [ 780/1319] eta: 0:28:39 lr: 1.3591231261041042e-05 loss: 0.0303 (0.0352) time: 3.1713 data: 0.0082 max mem: 33370 +Epoch: [30] [ 790/1319] eta: 0:28:07 lr: 1.3581373414999401e-05 loss: 0.0402 (0.0354) time: 3.1811 data: 0.0079 max mem: 33370 +Epoch: [30] [ 800/1319] eta: 0:27:35 lr: 1.3571514773873906e-05 loss: 0.0358 (0.0354) time: 3.1742 data: 0.0078 max mem: 33370 +Epoch: [30] [ 810/1319] eta: 0:27:04 lr: 1.3561655336958593e-05 loss: 0.0299 (0.0353) time: 3.2109 data: 0.0075 max mem: 33370 +Epoch: [30] [ 820/1319] eta: 0:26:32 lr: 1.3551795103546277e-05 loss: 0.0302 (0.0354) time: 3.2328 data: 0.0078 max mem: 33370 +Epoch: [30] [ 830/1319] eta: 0:26:00 lr: 1.3541934072928603e-05 loss: 0.0351 (0.0354) time: 3.1712 data: 0.0081 max mem: 33370 +Epoch: [30] [ 840/1319] eta: 0:25:28 lr: 1.3532072244395987e-05 loss: 0.0361 (0.0355) time: 3.1485 data: 0.0079 max mem: 33370 +Epoch: [30] [ 850/1319] eta: 0:24:56 lr: 1.3522209617237661e-05 loss: 0.0346 (0.0356) time: 3.1892 data: 0.0083 max mem: 33370 +Epoch: [30] [ 860/1319] eta: 0:24:24 lr: 1.3512346190741623e-05 loss: 0.0369 (0.0356) time: 3.2009 data: 0.0079 max mem: 33370 +Epoch: [30] [ 870/1319] eta: 0:23:52 lr: 1.3502481964194685e-05 loss: 0.0395 (0.0357) time: 3.1742 data: 0.0073 max mem: 33370 +Epoch: [30] [ 880/1319] eta: 0:23:20 lr: 1.3492616936882415e-05 loss: 0.0346 (0.0357) time: 3.1587 data: 0.0082 max mem: 33370 +Epoch: [30] [ 890/1319] eta: 0:22:48 lr: 1.3482751108089178e-05 loss: 0.0308 (0.0357) time: 3.1822 data: 0.0084 max mem: 33370 +Epoch: [30] [ 900/1319] eta: 0:22:16 lr: 1.3472884477098122e-05 loss: 0.0343 (0.0357) time: 3.1738 data: 0.0075 max mem: 33370 +Epoch: [30] [ 910/1319] eta: 0:21:44 lr: 1.3463017043191156e-05 loss: 0.0349 (0.0357) time: 3.1680 data: 0.0078 max mem: 33370 +Epoch: [30] [ 920/1319] eta: 0:21:12 lr: 1.3453148805648974e-05 loss: 0.0329 (0.0357) time: 3.1751 data: 0.0081 max mem: 33370 +Epoch: [30] [ 930/1319] eta: 0:20:40 lr: 1.3443279763751026e-05 loss: 0.0385 (0.0357) time: 3.1732 data: 0.0076 max mem: 33370 +Epoch: [30] [ 940/1319] eta: 0:20:08 lr: 1.3433409916775535e-05 loss: 0.0330 (0.0357) time: 3.2000 data: 0.0078 max mem: 33370 +Epoch: [30] [ 950/1319] eta: 0:19:37 lr: 1.3423539263999488e-05 loss: 0.0299 (0.0357) time: 3.2188 data: 0.0082 max mem: 33370 +Epoch: [30] [ 960/1319] eta: 0:19:05 lr: 1.341366780469863e-05 loss: 0.0336 (0.0357) time: 3.1871 data: 0.0085 max mem: 33370 +Epoch: [30] [ 970/1319] eta: 0:18:33 lr: 1.340379553814746e-05 loss: 0.0370 (0.0357) time: 3.1750 data: 0.0080 max mem: 33370 +Epoch: [30] [ 980/1319] eta: 0:18:01 lr: 1.3393922463619227e-05 loss: 0.0362 (0.0358) time: 3.1669 data: 0.0073 max mem: 33370 +Epoch: [30] [ 990/1319] eta: 0:17:29 lr: 1.3384048580385938e-05 loss: 0.0368 (0.0358) time: 3.1652 data: 0.0078 max mem: 33370 +Epoch: [30] [1000/1319] eta: 0:16:57 lr: 1.3374173887718341e-05 loss: 0.0394 (0.0358) time: 3.2022 data: 0.0079 max mem: 33370 +Epoch: [30] [1010/1319] eta: 0:16:25 lr: 1.3364298384885935e-05 loss: 0.0304 (0.0358) time: 3.2020 data: 0.0076 max mem: 33370 +Epoch: [30] [1020/1319] eta: 0:15:53 lr: 1.3354422071156945e-05 loss: 0.0289 (0.0358) time: 3.1521 data: 0.0082 max mem: 33370 +Epoch: [30] [1030/1319] eta: 0:15:21 lr: 1.3344544945798354e-05 loss: 0.0354 (0.0358) time: 3.1715 data: 0.0083 max mem: 33370 +Epoch: [30] [1040/1319] eta: 0:14:49 lr: 1.3334667008075852e-05 loss: 0.0359 (0.0358) time: 3.1856 data: 0.0081 max mem: 33370 +Epoch: [30] [1050/1319] eta: 0:14:17 lr: 1.3324788257253885e-05 loss: 0.0322 (0.0358) time: 3.1735 data: 0.0084 max mem: 33370 +Epoch: [30] [1060/1319] eta: 0:13:45 lr: 1.3314908692595609e-05 loss: 0.0329 (0.0358) time: 3.1788 data: 0.0086 max mem: 33370 +Epoch: [30] [1070/1319] eta: 0:13:13 lr: 1.3305028313362919e-05 loss: 0.0340 (0.0358) time: 3.1922 data: 0.0083 max mem: 33370 +Epoch: [30] [1080/1319] eta: 0:12:41 lr: 1.3295147118816423e-05 loss: 0.0327 (0.0358) time: 3.1761 data: 0.0081 max mem: 33370 +Epoch: [30] [1090/1319] eta: 0:12:10 lr: 1.328526510821544e-05 loss: 0.0310 (0.0358) time: 3.1769 data: 0.0081 max mem: 33370 +Epoch: [30] [1100/1319] eta: 0:11:38 lr: 1.3275382280818008e-05 loss: 0.0303 (0.0357) time: 3.2002 data: 0.0080 max mem: 33370 +Epoch: [30] [1110/1319] eta: 0:11:06 lr: 1.3265498635880886e-05 loss: 0.0316 (0.0358) time: 3.1943 data: 0.0078 max mem: 33370 +Epoch: [30] [1120/1319] eta: 0:10:34 lr: 1.325561417265953e-05 loss: 0.0323 (0.0357) time: 3.1794 data: 0.0080 max mem: 33370 +Epoch: [30] [1130/1319] eta: 0:10:02 lr: 1.3245728890408104e-05 loss: 0.0362 (0.0359) time: 3.1608 data: 0.0081 max mem: 33370 +Epoch: [30] [1140/1319] eta: 0:09:30 lr: 1.3235842788379476e-05 loss: 0.0370 (0.0359) time: 3.1661 data: 0.0078 max mem: 33370 +Epoch: [30] [1150/1319] eta: 0:08:58 lr: 1.3225955865825202e-05 loss: 0.0299 (0.0359) time: 3.1670 data: 0.0077 max mem: 33370 +Epoch: [30] [1160/1319] eta: 0:08:26 lr: 1.321606812199554e-05 loss: 0.0354 (0.0360) time: 3.1309 data: 0.0077 max mem: 33370 +Epoch: [30] [1170/1319] eta: 0:07:54 lr: 1.320617955613944e-05 loss: 0.0333 (0.0359) time: 3.1277 data: 0.0076 max mem: 33370 +Epoch: [30] [1180/1319] eta: 0:07:22 lr: 1.3196290167504535e-05 loss: 0.0282 (0.0359) time: 3.1585 data: 0.0077 max mem: 33370 +Epoch: [30] [1190/1319] eta: 0:06:51 lr: 1.3186399955337153e-05 loss: 0.0309 (0.0359) time: 3.1530 data: 0.0079 max mem: 33370 +Epoch: [30] [1200/1319] eta: 0:06:19 lr: 1.3176508918882283e-05 loss: 0.0301 (0.0358) time: 3.1416 data: 0.0074 max mem: 33370 +Epoch: [30] [1210/1319] eta: 0:05:47 lr: 1.3166617057383607e-05 loss: 0.0301 (0.0358) time: 3.1362 data: 0.0075 max mem: 33370 +Epoch: [30] [1220/1319] eta: 0:05:15 lr: 1.3156724370083478e-05 loss: 0.0313 (0.0358) time: 3.1683 data: 0.0080 max mem: 33370 +Epoch: [30] [1230/1319] eta: 0:04:43 lr: 1.3146830856222919e-05 loss: 0.0346 (0.0358) time: 3.1699 data: 0.0080 max mem: 33370 +Epoch: [30] [1240/1319] eta: 0:04:11 lr: 1.3136936515041629e-05 loss: 0.0311 (0.0357) time: 3.1862 data: 0.0081 max mem: 33370 +Epoch: [30] [1250/1319] eta: 0:03:39 lr: 1.3127041345777947e-05 loss: 0.0301 (0.0358) time: 3.1946 data: 0.0088 max mem: 33370 +Epoch: [30] [1260/1319] eta: 0:03:07 lr: 1.3117145347668891e-05 loss: 0.0317 (0.0358) time: 3.1839 data: 0.0086 max mem: 33370 +Epoch: [30] [1270/1319] eta: 0:02:36 lr: 1.3107248519950133e-05 loss: 0.0332 (0.0358) time: 3.1941 data: 0.0079 max mem: 33370 +Epoch: [30] [1280/1319] eta: 0:02:04 lr: 1.3097350861856001e-05 loss: 0.0367 (0.0358) time: 3.1687 data: 0.0081 max mem: 33370 +Epoch: [30] [1290/1319] eta: 0:01:32 lr: 1.3087452372619463e-05 loss: 0.0335 (0.0358) time: 3.1586 data: 0.0080 max mem: 33370 +Epoch: [30] [1300/1319] eta: 0:01:00 lr: 1.3077553051472149e-05 loss: 0.0335 (0.0359) time: 3.1389 data: 0.0074 max mem: 33370 +Epoch: [30] [1310/1319] eta: 0:00:28 lr: 1.3067652897644308e-05 loss: 0.0324 (0.0358) time: 3.1347 data: 0.0074 max mem: 33370 +Epoch: [30] Total time: 1:10:00 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 2:03:26 time: 2.8787 data: 2.7253 max mem: 33370 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 100/2573] eta: 0:04:17 time: 0.0763 data: 0.0015 max mem: 33370 +Test: [ 200/2573] eta: 0:03:37 time: 0.0780 data: 0.0014 max mem: 33370 +Test: [ 300/2573] eta: 0:03:17 time: 0.0795 data: 0.0014 max mem: 33370 +Test: [ 400/2573] eta: 0:03:04 time: 0.0806 data: 0.0014 max mem: 33370 +Test: [ 500/2573] eta: 0:02:53 time: 0.0796 data: 0.0015 max mem: 33370 +Test: [ 600/2573] eta: 0:02:43 time: 0.0782 data: 0.0015 max mem: 33370 +Test: [ 700/2573] eta: 0:02:35 time: 0.0798 data: 0.0016 max mem: 33370 +Test: [ 800/2573] eta: 0:02:26 time: 0.0822 data: 0.0014 max mem: 33370 +Test: [ 900/2573] eta: 0:02:17 time: 0.0801 data: 0.0015 max mem: 33370 +Test: [1000/2573] eta: 0:02:08 time: 0.0797 data: 0.0015 max mem: 33370 +Test: [1100/2573] eta: 0:02:00 time: 0.0789 data: 0.0014 max mem: 33370 +Test: [1200/2573] eta: 0:01:51 time: 0.0786 data: 0.0014 max mem: 33370 +Test: [1300/2573] eta: 0:01:43 time: 0.0801 data: 0.0015 max mem: 33370 +Test: [1400/2573] eta: 0:01:35 time: 0.0774 data: 0.0014 max mem: 33370 +Test: [1500/2573] eta: 0:01:27 time: 0.0795 data: 0.0014 max mem: 33370 +Test: [1600/2573] eta: 0:01:18 time: 0.0825 data: 0.0015 max mem: 33370 +Test: [1700/2573] eta: 0:01:10 time: 0.0775 data: 0.0014 max mem: 33370 +Test: [1800/2573] eta: 0:01:02 time: 0.0807 data: 0.0014 max mem: 33370 +Test: [1900/2573] eta: 0:00:54 time: 0.0773 data: 0.0014 max mem: 33370 +Test: [2000/2573] eta: 0:00:46 time: 0.0795 data: 0.0015 max mem: 33370 +Test: [2100/2573] eta: 0:00:38 time: 0.0807 data: 0.0014 max mem: 33370 +Test: [2200/2573] eta: 0:00:30 time: 0.0812 data: 0.0015 max mem: 33370 +Test: [2300/2573] eta: 0:00:21 time: 0.0803 data: 0.0014 max mem: 33370 +Test: [2400/2573] eta: 0:00:13 time: 0.0755 data: 0.0014 max mem: 33370 +Test: [2500/2573] eta: 0:00:05 time: 0.0799 data: 0.0015 max mem: 33370 +Test: Total time: 0:03:27 +Final results: +Mean IoU is 64.63 + + precision@0.5 = 72.34 + precision@0.6 = 67.34 + precision@0.7 = 60.13 + precision@0.8 = 49.04 + precision@0.9 = 24.94 + overall IoU = 62.07 + +Average object IoU 64.63188200873267 +Overall IoU 62.07173538208008 +Better epoch: 30 + +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [31] [ 0/1319] eta: 1:46:21 lr: 1.3058742046620123e-05 loss: 0.0322 (0.0322) time: 4.8381 data: 1.5791 max mem: 33370 +Epoch: [31] [ 10/1319] eta: 1:13:19 lr: 1.3048840308573793e-05 loss: 0.0299 (0.0320) time: 3.3607 data: 0.1503 max mem: 33370 +Epoch: [31] [ 20/1319] eta: 1:11:02 lr: 1.3038937735606992e-05 loss: 0.0283 (0.0314) time: 3.2034 data: 0.0075 max mem: 33370 +Epoch: [31] [ 30/1319] eta: 1:09:51 lr: 1.3029034326944665e-05 loss: 0.0300 (0.0324) time: 3.1920 data: 0.0077 max mem: 33370 +Epoch: [31] [ 40/1319] eta: 1:09:14 lr: 1.3019130081810363e-05 loss: 0.0292 (0.0325) time: 3.2135 data: 0.0083 max mem: 33370 +Epoch: [31] [ 50/1319] eta: 1:08:32 lr: 1.3009224999426282e-05 loss: 0.0280 (0.0338) time: 3.2226 data: 0.0083 max mem: 33370 +Epoch: [31] [ 60/1319] eta: 1:07:48 lr: 1.2999319079013207e-05 loss: 0.0344 (0.0343) time: 3.1966 data: 0.0082 max mem: 33370 +Epoch: [31] [ 70/1319] eta: 1:06:58 lr: 1.298941231979056e-05 loss: 0.0348 (0.0344) time: 3.1591 data: 0.0085 max mem: 33370 +Epoch: [31] [ 80/1319] eta: 1:06:21 lr: 1.2979504720976363e-05 loss: 0.0296 (0.0337) time: 3.1606 data: 0.0082 max mem: 33370 +Epoch: [31] [ 90/1319] eta: 1:05:51 lr: 1.2969596281787253e-05 loss: 0.0290 (0.0337) time: 3.2068 data: 0.0079 max mem: 33370 +Epoch: [31] [ 100/1319] eta: 1:05:13 lr: 1.2959687001438464e-05 loss: 0.0283 (0.0338) time: 3.1979 data: 0.0086 max mem: 33370 +Epoch: [31] [ 110/1319] eta: 1:04:38 lr: 1.2949776879143838e-05 loss: 0.0302 (0.0338) time: 3.1759 data: 0.0089 max mem: 33370 +Epoch: [31] [ 120/1319] eta: 1:04:02 lr: 1.2939865914115796e-05 loss: 0.0302 (0.0338) time: 3.1753 data: 0.0082 max mem: 33370 +Epoch: [31] [ 130/1319] eta: 1:03:26 lr: 1.2929954105565368e-05 loss: 0.0330 (0.0337) time: 3.1657 data: 0.0080 max mem: 33370 +Epoch: [31] [ 140/1319] eta: 1:02:54 lr: 1.2920041452702167e-05 loss: 0.0330 (0.0343) time: 3.1814 data: 0.0080 max mem: 33370 +Epoch: [31] [ 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mem: 33370 +Epoch: [31] [ 230/1319] eta: 0:57:53 lr: 1.2830789451741262e-05 loss: 0.0288 (0.0342) time: 3.1711 data: 0.0088 max mem: 33370 +Epoch: [31] [ 240/1319] eta: 0:57:20 lr: 1.2820868311965862e-05 loss: 0.0272 (0.0341) time: 3.1824 data: 0.0085 max mem: 33370 +Epoch: [31] [ 250/1319] eta: 0:56:48 lr: 1.2810946319089204e-05 loss: 0.0297 (0.0341) time: 3.1674 data: 0.0083 max mem: 33370 +Epoch: [31] [ 260/1319] eta: 0:56:15 lr: 1.2801023472303672e-05 loss: 0.0325 (0.0341) time: 3.1654 data: 0.0077 max mem: 33370 +Epoch: [31] [ 270/1319] eta: 0:55:42 lr: 1.2791099770800195e-05 loss: 0.0334 (0.0341) time: 3.1632 data: 0.0077 max mem: 33370 +Epoch: [31] [ 280/1319] eta: 0:55:10 lr: 1.2781175213768214e-05 loss: 0.0342 (0.0341) time: 3.1808 data: 0.0079 max mem: 33370 +Epoch: [31] [ 290/1319] eta: 0:54:38 lr: 1.277124980039573e-05 loss: 0.0339 (0.0340) time: 3.1756 data: 0.0078 max mem: 33370 +Epoch: [31] [ 300/1319] eta: 0:54:04 lr: 1.2761323529869248e-05 loss: 0.0341 (0.0341) time: 3.1480 data: 0.0087 max mem: 33370 +Epoch: [31] [ 310/1319] eta: 0:53:33 lr: 1.2751396401373813e-05 loss: 0.0367 (0.0342) time: 3.1680 data: 0.0086 max mem: 33370 +Epoch: [31] [ 320/1319] eta: 0:53:00 lr: 1.2741468414092989e-05 loss: 0.0318 (0.0340) time: 3.1810 data: 0.0078 max mem: 33370 +Epoch: [31] [ 330/1319] eta: 0:52:29 lr: 1.2731539567208833e-05 loss: 0.0302 (0.0341) time: 3.1892 data: 0.0081 max mem: 33370 +Epoch: [31] [ 340/1319] eta: 0:51:57 lr: 1.2721609859901942e-05 loss: 0.0315 (0.0342) time: 3.1929 data: 0.0085 max mem: 33370 +Epoch: [31] [ 350/1319] eta: 0:51:26 lr: 1.2711679291351405e-05 loss: 0.0352 (0.0343) time: 3.1885 data: 0.0085 max mem: 33370 +Epoch: [31] [ 360/1319] eta: 0:50:54 lr: 1.2701747860734819e-05 loss: 0.0358 (0.0344) time: 3.1973 data: 0.0084 max mem: 33370 +Epoch: [31] [ 370/1319] eta: 0:50:22 lr: 1.2691815567228285e-05 loss: 0.0386 (0.0345) time: 3.1798 data: 0.0086 max mem: 33370 +Epoch: [31] [ 380/1319] eta: 0:49:50 lr: 1.2681882410006382e-05 loss: 0.0359 (0.0346) time: 3.1694 data: 0.0085 max mem: 33370 +Epoch: [31] [ 390/1319] eta: 0:49:17 lr: 1.26719483882422e-05 loss: 0.0359 (0.0346) time: 3.1670 data: 0.0080 max mem: 33370 +Epoch: [31] [ 400/1319] eta: 0:48:46 lr: 1.2662013501107303e-05 loss: 0.0328 (0.0345) time: 3.1784 data: 0.0081 max mem: 33370 +Epoch: [31] [ 410/1319] eta: 0:48:14 lr: 1.265207774777175e-05 loss: 0.0337 (0.0346) time: 3.1887 data: 0.0080 max mem: 33370 +Epoch: [31] [ 420/1319] eta: 0:47:41 lr: 1.2642141127404073e-05 loss: 0.0337 (0.0345) time: 3.1721 data: 0.0080 max mem: 33370 +Epoch: [31] [ 430/1319] eta: 0:47:09 lr: 1.2632203639171281e-05 loss: 0.0274 (0.0344) time: 3.1649 data: 0.0081 max mem: 33370 +Epoch: [31] [ 440/1319] eta: 0:46:37 lr: 1.2622265282238837e-05 loss: 0.0327 (0.0344) time: 3.1606 data: 0.0079 max mem: 33370 +Epoch: [31] [ 450/1319] eta: 0:46:07 lr: 1.2612326055770701e-05 loss: 0.0327 (0.0343) time: 3.2048 data: 0.0085 max mem: 33370 +Epoch: [31] [ 460/1319] eta: 0:45:35 lr: 1.2602385958929271e-05 loss: 0.0314 (0.0343) time: 3.2220 data: 0.0083 max mem: 33370 +Epoch: [31] [ 470/1319] eta: 0:45:02 lr: 1.2592444990875415e-05 loss: 0.0344 (0.0346) time: 3.1556 data: 0.0077 max mem: 33370 +Epoch: [31] [ 480/1319] eta: 0:44:29 lr: 1.258250315076846e-05 loss: 0.0344 (0.0346) time: 3.1397 data: 0.0078 max mem: 33370 +Epoch: [31] [ 490/1319] eta: 0:43:58 lr: 1.2572560437766163e-05 loss: 0.0321 (0.0346) time: 3.1743 data: 0.0078 max mem: 33370 +Epoch: [31] [ 500/1319] eta: 0:43:26 lr: 1.2562616851024742e-05 loss: 0.0325 (0.0347) time: 3.1883 data: 0.0076 max mem: 33370 +Epoch: [31] [ 510/1319] eta: 0:42:54 lr: 1.2552672389698855e-05 loss: 0.0343 (0.0346) time: 3.1693 data: 0.0079 max mem: 33370 +Epoch: [31] [ 520/1319] eta: 0:42:21 lr: 1.2542727052941597e-05 loss: 0.0327 (0.0347) time: 3.1410 data: 0.0082 max mem: 33370 +Epoch: [31] [ 530/1319] eta: 0:41:49 lr: 1.2532780839904498e-05 loss: 0.0296 (0.0346) time: 3.1515 data: 0.0079 max mem: 33370 +Epoch: [31] [ 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33370 +Epoch: [31] [ 620/1319] eta: 0:37:04 lr: 1.2443225349198233e-05 loss: 0.0296 (0.0349) time: 3.1487 data: 0.0078 max mem: 33370 +Epoch: [31] [ 630/1319] eta: 0:36:32 lr: 1.2433270326348818e-05 loss: 0.0293 (0.0348) time: 3.1622 data: 0.0079 max mem: 33370 +Epoch: [31] [ 640/1319] eta: 0:35:59 lr: 1.2423314417781696e-05 loss: 0.0293 (0.0348) time: 3.1510 data: 0.0083 max mem: 33370 +Epoch: [31] [ 650/1319] eta: 0:35:28 lr: 1.2413357622629242e-05 loss: 0.0339 (0.0348) time: 3.1699 data: 0.0083 max mem: 33370 +Epoch: [31] [ 660/1319] eta: 0:34:56 lr: 1.240339994002222e-05 loss: 0.0336 (0.0349) time: 3.1824 data: 0.0082 max mem: 33370 +Epoch: [31] [ 670/1319] eta: 0:34:24 lr: 1.2393441369089758e-05 loss: 0.0329 (0.0349) time: 3.1725 data: 0.0081 max mem: 33370 +Epoch: [31] [ 680/1319] eta: 0:33:52 lr: 1.2383481908959357e-05 loss: 0.0315 (0.0349) time: 3.1941 data: 0.0082 max mem: 33370 +Epoch: [31] [ 690/1319] eta: 0:33:21 lr: 1.237352155875688e-05 loss: 0.0291 (0.0348) time: 3.1891 data: 0.0084 max mem: 33370 +Epoch: [31] [ 700/1319] eta: 0:32:49 lr: 1.236356031760655e-05 loss: 0.0313 (0.0349) time: 3.2017 data: 0.0083 max mem: 33370 +Epoch: [31] [ 710/1319] eta: 0:32:17 lr: 1.2353598184630927e-05 loss: 0.0330 (0.0348) time: 3.2090 data: 0.0080 max mem: 33370 +Epoch: [31] [ 720/1319] eta: 0:31:46 lr: 1.2343635158950937e-05 loss: 0.0372 (0.0350) time: 3.2049 data: 0.0079 max mem: 33370 +Epoch: [31] [ 730/1319] eta: 0:31:14 lr: 1.2333671239685849e-05 loss: 0.0330 (0.0349) time: 3.2225 data: 0.0077 max mem: 33370 +Epoch: [31] [ 740/1319] eta: 0:30:43 lr: 1.2323706425953264e-05 loss: 0.0318 (0.0349) time: 3.2396 data: 0.0075 max mem: 33370 +Epoch: [31] [ 750/1319] eta: 0:30:11 lr: 1.2313740716869131e-05 loss: 0.0296 (0.0348) time: 3.2073 data: 0.0074 max mem: 33370 +Epoch: [31] [ 760/1319] eta: 0:29:40 lr: 1.2303774111547706e-05 loss: 0.0296 (0.0348) time: 3.2004 data: 0.0075 max mem: 33370 +Epoch: [31] [ 770/1319] eta: 0:29:08 lr: 1.2293806609101593e-05 loss: 0.0342 (0.0348) time: 3.2089 data: 0.0081 max mem: 33370 +Epoch: [31] [ 780/1319] eta: 0:28:36 lr: 1.2283838208641708e-05 loss: 0.0381 (0.0348) time: 3.1938 data: 0.0088 max mem: 33370 +Epoch: [31] [ 790/1319] eta: 0:28:04 lr: 1.2273868909277286e-05 loss: 0.0349 (0.0348) time: 3.1887 data: 0.0084 max mem: 33370 +Epoch: [31] [ 800/1319] eta: 0:27:32 lr: 1.2263898710115878e-05 loss: 0.0321 (0.0348) time: 3.1632 data: 0.0081 max mem: 33370 +Epoch: [31] [ 810/1319] eta: 0:27:00 lr: 1.2253927610263324e-05 loss: 0.0306 (0.0351) time: 3.1769 data: 0.0082 max mem: 33370 +Epoch: [31] [ 820/1319] eta: 0:26:28 lr: 1.2243955608823781e-05 loss: 0.0293 (0.0351) time: 3.1804 data: 0.0085 max mem: 33370 +Epoch: [31] [ 830/1319] eta: 0:25:56 lr: 1.2233982704899707e-05 loss: 0.0360 (0.0351) time: 3.1500 data: 0.0086 max mem: 33370 +Epoch: [31] [ 840/1319] eta: 0:25:24 lr: 1.2224008897591841e-05 loss: 0.0346 (0.0351) time: 3.1646 data: 0.0081 max mem: 33370 +Epoch: [31] [ 850/1319] eta: 0:24:53 lr: 1.2214034185999218e-05 loss: 0.0292 (0.0350) time: 3.1872 data: 0.0081 max mem: 33370 +Epoch: [31] [ 860/1319] eta: 0:24:21 lr: 1.2204058569219158e-05 loss: 0.0283 (0.0350) time: 3.1847 data: 0.0080 max mem: 33370 +Epoch: [31] [ 870/1319] eta: 0:23:49 lr: 1.2194082046347242e-05 loss: 0.0312 (0.0350) time: 3.1859 data: 0.0079 max mem: 33370 +Epoch: [31] [ 880/1319] eta: 0:23:17 lr: 1.2184104616477345e-05 loss: 0.0344 (0.0351) time: 3.1787 data: 0.0077 max mem: 33370 +Epoch: [31] [ 890/1319] eta: 0:22:45 lr: 1.2174126278701602e-05 loss: 0.0335 (0.0350) time: 3.1515 data: 0.0077 max mem: 33370 +Epoch: [31] [ 900/1319] eta: 0:22:13 lr: 1.2164147032110409e-05 loss: 0.0324 (0.0351) time: 3.1845 data: 0.0082 max mem: 33370 +Epoch: [31] [ 910/1319] eta: 0:21:41 lr: 1.215416687579243e-05 loss: 0.0315 (0.0351) time: 3.1771 data: 0.0086 max mem: 33370 +Epoch: [31] [ 920/1319] eta: 0:21:09 lr: 1.2144185808834565e-05 loss: 0.0318 (0.0350) time: 3.1158 data: 0.0085 max mem: 33370 +Epoch: [31] [ 930/1319] eta: 0:20:37 lr: 1.213420383032198e-05 loss: 0.0313 (0.0350) time: 3.1304 data: 0.0086 max mem: 33370 +Epoch: [31] [ 940/1319] eta: 0:20:05 lr: 1.212422093933808e-05 loss: 0.0313 (0.0350) time: 3.1646 data: 0.0087 max mem: 33370 +Epoch: [31] [ 950/1319] eta: 0:19:33 lr: 1.2114237134964505e-05 loss: 0.0298 (0.0349) time: 3.1645 data: 0.0087 max mem: 33370 +Epoch: [31] [ 960/1319] eta: 0:19:01 lr: 1.210425241628114e-05 loss: 0.0313 (0.0350) time: 3.1180 data: 0.0084 max mem: 33370 +Epoch: [31] [ 970/1319] eta: 0:18:29 lr: 1.2094266782366075e-05 loss: 0.0331 (0.0350) time: 3.1181 data: 0.0080 max mem: 33370 +Epoch: [31] [ 980/1319] eta: 0:17:58 lr: 1.208428023229565e-05 loss: 0.0329 (0.0349) time: 3.1648 data: 0.0081 max mem: 33370 +Epoch: [31] [ 990/1319] eta: 0:17:26 lr: 1.2074292765144408e-05 loss: 0.0310 (0.0350) time: 3.1862 data: 0.0083 max mem: 33370 +Epoch: [31] [1000/1319] eta: 0:16:54 lr: 1.2064304379985111e-05 loss: 0.0318 (0.0349) time: 3.1723 data: 0.0083 max mem: 33370 +Epoch: [31] [1010/1319] eta: 0:16:22 lr: 1.2054315075888731e-05 loss: 0.0318 (0.0350) time: 3.1617 data: 0.0081 max mem: 33370 +Epoch: [31] [1020/1319] eta: 0:15:50 lr: 1.2044324851924447e-05 loss: 0.0339 (0.0350) time: 3.1857 data: 0.0081 max mem: 33370 +Epoch: [31] [1030/1319] eta: 0:15:18 lr: 1.2034333707159618e-05 loss: 0.0335 (0.0350) time: 3.1820 data: 0.0082 max mem: 33370 +Epoch: [31] [1040/1319] eta: 0:14:47 lr: 1.2024341640659817e-05 loss: 0.0349 (0.0351) time: 3.1580 data: 0.0083 max mem: 33370 +Epoch: [31] [1050/1319] eta: 0:14:15 lr: 1.2014348651488794e-05 loss: 0.0304 (0.0350) time: 3.1742 data: 0.0085 max mem: 33370 +Epoch: [31] [1060/1319] eta: 0:13:43 lr: 1.2004354738708488e-05 loss: 0.0281 (0.0350) time: 3.1671 data: 0.0083 max mem: 33370 +Epoch: [31] [1070/1319] eta: 0:13:11 lr: 1.1994359901379014e-05 loss: 0.0322 (0.0350) time: 3.1506 data: 0.0082 max mem: 33370 +Epoch: [31] [1080/1319] eta: 0:12:39 lr: 1.1984364138558649e-05 loss: 0.0322 (0.0350) time: 3.1716 data: 0.0084 max mem: 33370 +Epoch: [31] [1090/1319] eta: 0:12:08 lr: 1.1974367449303851e-05 loss: 0.0303 (0.0350) time: 3.1748 data: 0.0089 max mem: 33370 +Epoch: [31] [1100/1319] eta: 0:11:36 lr: 1.1964369832669236e-05 loss: 0.0346 (0.0351) time: 3.1802 data: 0.0096 max mem: 33370 +Epoch: [31] [1110/1319] eta: 0:11:04 lr: 1.195437128770757e-05 loss: 0.0308 (0.0350) time: 3.2039 data: 0.0089 max mem: 33370 +Epoch: [31] [1120/1319] eta: 0:10:32 lr: 1.194437181346979e-05 loss: 0.0299 (0.0350) time: 3.1937 data: 0.0079 max mem: 33370 +Epoch: [31] [1130/1319] eta: 0:10:00 lr: 1.1934371409004944e-05 loss: 0.0344 (0.0350) time: 3.1822 data: 0.0077 max mem: 33370 +Epoch: [31] [1140/1319] eta: 0:09:29 lr: 1.192437007336025e-05 loss: 0.0335 (0.0350) time: 3.1701 data: 0.0078 max mem: 33370 +Epoch: [31] [1150/1319] eta: 0:08:57 lr: 1.1914367805581053e-05 loss: 0.0338 (0.0351) time: 3.1595 data: 0.0081 max mem: 33370 +Epoch: [31] [1160/1319] eta: 0:08:25 lr: 1.1904364604710826e-05 loss: 0.0366 (0.0350) time: 3.1499 data: 0.0078 max mem: 33370 +Epoch: [31] [1170/1319] eta: 0:07:53 lr: 1.1894360469791169e-05 loss: 0.0302 (0.0350) time: 3.1610 data: 0.0079 max mem: 33370 +Epoch: [31] [1180/1319] eta: 0:07:21 lr: 1.1884355399861802e-05 loss: 0.0271 (0.0350) time: 3.1861 data: 0.0080 max mem: 33370 +Epoch: [31] [1190/1319] eta: 0:06:50 lr: 1.1874349393960545e-05 loss: 0.0378 (0.0350) time: 3.1677 data: 0.0081 max mem: 33370 +Epoch: [31] [1200/1319] eta: 0:06:18 lr: 1.1864342451123342e-05 loss: 0.0329 (0.0350) time: 3.1710 data: 0.0085 max mem: 33370 +Epoch: [31] [1210/1319] eta: 0:05:46 lr: 1.1854334570384235e-05 loss: 0.0292 (0.0350) time: 3.1731 data: 0.0083 max mem: 33370 +Epoch: [31] [1220/1319] eta: 0:05:14 lr: 1.1844325750775364e-05 loss: 0.0305 (0.0350) time: 3.1458 data: 0.0082 max mem: 33370 +Epoch: [31] [1230/1319] eta: 0:04:42 lr: 1.183431599132696e-05 loss: 0.0341 (0.0350) time: 3.1643 data: 0.0085 max mem: 33370 +Epoch: [31] [1240/1319] eta: 0:04:11 lr: 1.1824305291067328e-05 loss: 0.0340 (0.0349) time: 3.1955 data: 0.0085 max mem: 33370 +Epoch: [31] [1250/1319] eta: 0:03:39 lr: 1.1814293649022872e-05 loss: 0.0293 (0.0349) time: 3.2013 data: 0.0082 max mem: 33370 +Epoch: [31] [1260/1319] eta: 0:03:07 lr: 1.180428106421806e-05 loss: 0.0319 (0.0349) time: 3.1994 data: 0.0081 max mem: 33370 +Epoch: [31] [1270/1319] eta: 0:02:35 lr: 1.1794267535675433e-05 loss: 0.0317 (0.0349) time: 3.1882 data: 0.0080 max mem: 33370 +Epoch: [31] [1280/1319] eta: 0:02:03 lr: 1.1784253062415594e-05 loss: 0.0317 (0.0349) time: 3.1889 data: 0.0078 max mem: 33370 +Epoch: [31] [1290/1319] eta: 0:01:32 lr: 1.1774237643457209e-05 loss: 0.0329 (0.0349) time: 3.1688 data: 0.0080 max mem: 33370 +Epoch: [31] [1300/1319] eta: 0:01:00 lr: 1.1764221277816978e-05 loss: 0.0350 (0.0350) time: 3.1427 data: 0.0081 max mem: 33370 +Epoch: [31] [1310/1319] eta: 0:00:28 lr: 1.1754203964509668e-05 loss: 0.0358 (0.0350) time: 3.1682 data: 0.0076 max mem: 33370 +Epoch: [31] Total time: 1:09:53 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 2:15:53 time: 3.1689 data: 3.0654 max mem: 33370 +Test: [ 100/2573] eta: 0:04:26 time: 0.0772 data: 0.0014 max mem: 33370 +Test: [ 200/2573] eta: 0:03:41 time: 0.0782 data: 0.0015 max mem: 33370 +Test: [ 300/2573] eta: 0:03:19 time: 0.0792 data: 0.0013 max mem: 33370 +Test: [ 400/2573] eta: 0:03:05 time: 0.0798 data: 0.0014 max mem: 33370 +Test: [ 500/2573] eta: 0:02:54 time: 0.0791 data: 0.0014 max mem: 33370 +Test: [ 600/2573] eta: 0:02:44 time: 0.0793 data: 0.0015 max mem: 33370 +Test: [ 700/2573] eta: 0:02:35 time: 0.0792 data: 0.0015 max mem: 33370 +Test: [ 800/2573] eta: 0:02:26 time: 0.0823 data: 0.0015 max mem: 33370 +Test: [ 900/2573] eta: 0:02:17 time: 0.0793 data: 0.0015 max mem: 33370 +Test: [1000/2573] eta: 0:02:09 time: 0.0789 data: 0.0015 max mem: 33370 +Test: [1100/2573] eta: 0:02:00 time: 0.0794 data: 0.0014 max mem: 33370 +Test: [1200/2573] eta: 0:01:52 time: 0.0792 data: 0.0013 max mem: 33370 +Test: [1300/2573] eta: 0:01:43 time: 0.0794 data: 0.0014 max mem: 33370 +Test: [1400/2573] eta: 0:01:35 time: 0.0779 data: 0.0015 max mem: 33370 +Test: [1500/2573] eta: 0:01:27 time: 0.0788 data: 0.0014 max mem: 33370 +Test: [1600/2573] eta: 0:01:18 time: 0.0830 data: 0.0015 max mem: 33370 +Test: [1700/2573] eta: 0:01:10 time: 0.0777 data: 0.0014 max mem: 33370 +Test: [1800/2573] eta: 0:01:02 time: 0.0810 data: 0.0017 max mem: 33370 +Test: [1900/2573] eta: 0:00:54 time: 0.0777 data: 0.0014 max mem: 33370 +Test: [2000/2573] eta: 0:00:46 time: 0.0799 data: 0.0014 max mem: 33370 +Test: [2100/2573] eta: 0:00:38 time: 0.0820 data: 0.0015 max mem: 33370 +Test: [2200/2573] eta: 0:00:30 time: 0.0813 data: 0.0015 max mem: 33370 +Test: [2300/2573] eta: 0:00:21 time: 0.0809 data: 0.0014 max mem: 33370 +Test: [2400/2573] eta: 0:00:13 time: 0.0760 data: 0.0015 max mem: 33370 +Test: [2500/2573] eta: 0:00:05 time: 0.0791 data: 0.0014 max mem: 33370 +Test: Total time: 0:03:27 +Final results: +Mean IoU is 64.40 + + precision@0.5 = 72.32 + precision@0.6 = 67.79 + precision@0.7 = 60.46 + precision@0.8 = 49.22 + precision@0.9 = 24.59 + overall IoU = 62.11 + +Average object IoU 64.40183338066674 +Overall IoU 62.11466598510742 +Better epoch: 31 + +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [32] [ 0/1319] eta: 1:48:54 lr: 1.1745187571461855e-05 loss: 0.0332 (0.0332) time: 4.9544 data: 1.7120 max mem: 33370 +Epoch: [32] [ 10/1319] eta: 1:13:48 lr: 1.1735168454865734e-05 loss: 0.0324 (0.0386) time: 3.3829 data: 0.1629 max mem: 33370 +Epoch: [32] [ 20/1319] eta: 1:11:01 lr: 1.1725148387734231e-05 loss: 0.0324 (0.0370) time: 3.1969 data: 0.0082 max mem: 33370 +Epoch: [32] [ 30/1319] eta: 1:09:49 lr: 1.1715127369074435e-05 loss: 0.0306 (0.0356) time: 3.1776 data: 0.0083 max mem: 33370 +Epoch: [32] [ 40/1319] eta: 1:08:42 lr: 1.1705105397891451e-05 loss: 0.0299 (0.0341) time: 3.1631 data: 0.0086 max mem: 33370 +Epoch: [32] [ 50/1319] eta: 1:08:03 lr: 1.1695082473188386e-05 loss: 0.0303 (0.0335) time: 3.1670 data: 0.0087 max mem: 33370 +Epoch: [32] [ 60/1319] eta: 1:07:20 lr: 1.1685058593966367e-05 loss: 0.0291 (0.0330) time: 3.1817 data: 0.0085 max mem: 33370 +Epoch: [32] [ 70/1319] eta: 1:06:49 lr: 1.1675033759224512e-05 loss: 0.0260 (0.0324) time: 3.1904 data: 0.0085 max mem: 33370 +Epoch: [32] [ 80/1319] eta: 1:06:05 lr: 1.1665007967959945e-05 loss: 0.0326 (0.0323) time: 3.1739 data: 0.0085 max mem: 33370 +Epoch: [32] [ 90/1319] eta: 1:05:37 lr: 1.1654981219167763e-05 loss: 0.0328 (0.0325) time: 3.1819 data: 0.0083 max mem: 33370 +Epoch: [32] [ 100/1319] eta: 1:05:01 lr: 1.1644953511841062e-05 loss: 0.0311 (0.0322) time: 3.1994 data: 0.0084 max mem: 33370 +Epoch: [32] [ 110/1319] eta: 1:04:24 lr: 1.1634924844970898e-05 loss: 0.0299 (0.0321) time: 3.1630 data: 0.0084 max mem: 33370 +Epoch: [32] [ 120/1319] eta: 1:03:56 lr: 1.1624895217546308e-05 loss: 0.0299 (0.0323) time: 3.1966 data: 0.0080 max mem: 33370 +Epoch: [32] [ 130/1319] eta: 1:03:18 lr: 1.1614864628554293e-05 loss: 0.0331 (0.0324) time: 3.1862 data: 0.0081 max mem: 33370 +Epoch: [32] [ 140/1319] eta: 1:02:49 lr: 1.160483307697981e-05 loss: 0.0305 (0.0323) time: 3.1830 data: 0.0081 max mem: 33370 +Epoch: [32] [ 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33370 +Epoch: [32] [ 230/1319] eta: 0:57:45 lr: 1.1514505628098139e-05 loss: 0.0318 (0.0331) time: 3.1539 data: 0.0082 max mem: 33370 +Epoch: [32] [ 240/1319] eta: 0:57:15 lr: 1.1504464394418176e-05 loss: 0.0318 (0.0331) time: 3.1746 data: 0.0085 max mem: 33370 +Epoch: [32] [ 250/1319] eta: 0:56:43 lr: 1.149442218685379e-05 loss: 0.0303 (0.0328) time: 3.2008 data: 0.0081 max mem: 33370 +Epoch: [32] [ 260/1319] eta: 0:56:15 lr: 1.1484379004364971e-05 loss: 0.0303 (0.0329) time: 3.2319 data: 0.0085 max mem: 33370 +Epoch: [32] [ 270/1319] eta: 0:55:43 lr: 1.147433484590956e-05 loss: 0.0311 (0.0329) time: 3.2308 data: 0.0090 max mem: 33370 +Epoch: [32] [ 280/1319] eta: 0:55:12 lr: 1.1464289710443295e-05 loss: 0.0279 (0.0328) time: 3.1915 data: 0.0084 max mem: 33370 +Epoch: [32] [ 290/1319] eta: 0:54:39 lr: 1.1454243596919765e-05 loss: 0.0294 (0.0329) time: 3.1754 data: 0.0079 max mem: 33370 +Epoch: [32] [ 300/1319] eta: 0:54:05 lr: 1.144419650429042e-05 loss: 0.0303 (0.0329) time: 3.1490 data: 0.0079 max mem: 33370 +Epoch: [32] [ 310/1319] eta: 0:53:35 lr: 1.1434148431504575e-05 loss: 0.0295 (0.0327) time: 3.1844 data: 0.0079 max mem: 33370 +Epoch: [32] [ 320/1319] eta: 0:53:02 lr: 1.1424099377509363e-05 loss: 0.0295 (0.0327) time: 3.1900 data: 0.0083 max mem: 33370 +Epoch: [32] [ 330/1319] eta: 0:52:29 lr: 1.141404934124978e-05 loss: 0.0314 (0.0327) time: 3.1589 data: 0.0084 max mem: 33370 +Epoch: [32] [ 340/1319] eta: 0:51:57 lr: 1.140399832166864e-05 loss: 0.0314 (0.0328) time: 3.1748 data: 0.0081 max mem: 33370 +Epoch: [32] [ 350/1319] eta: 0:51:26 lr: 1.1393946317706594e-05 loss: 0.0291 (0.0329) time: 3.1995 data: 0.0080 max mem: 33370 +Epoch: [32] [ 360/1319] eta: 0:50:56 lr: 1.138389332830211e-05 loss: 0.0331 (0.0330) time: 3.2208 data: 0.0085 max mem: 33370 +Epoch: [32] [ 370/1319] eta: 0:50:23 lr: 1.1373839352391454e-05 loss: 0.0339 (0.0332) time: 3.1872 data: 0.0084 max mem: 33370 +Epoch: [32] [ 380/1319] eta: 0:49:51 lr: 1.1363784388908714e-05 loss: 0.0376 (0.0333) time: 3.1781 data: 0.0076 max mem: 33370 +Epoch: [32] [ 390/1319] eta: 0:49:21 lr: 1.1353728436785773e-05 loss: 0.0311 (0.0333) time: 3.2237 data: 0.0078 max mem: 33370 +Epoch: [32] [ 400/1319] eta: 0:48:49 lr: 1.1343671494952302e-05 loss: 0.0321 (0.0333) time: 3.2087 data: 0.0083 max mem: 33370 +Epoch: [32] [ 410/1319] eta: 0:48:17 lr: 1.1333613562335765e-05 loss: 0.0334 (0.0334) time: 3.1913 data: 0.0084 max mem: 33370 +Epoch: [32] [ 420/1319] eta: 0:47:44 lr: 1.1323554637861402e-05 loss: 0.0322 (0.0334) time: 3.1592 data: 0.0087 max mem: 33370 +Epoch: [32] [ 430/1319] eta: 0:47:13 lr: 1.1313494720452216e-05 loss: 0.0302 (0.0334) time: 3.1625 data: 0.0084 max mem: 33370 +Epoch: [32] [ 440/1319] eta: 0:46:40 lr: 1.1303433809028986e-05 loss: 0.0273 (0.0333) time: 3.1731 data: 0.0081 max mem: 33370 +Epoch: [32] [ 450/1319] eta: 0:46:07 lr: 1.1293371902510248e-05 loss: 0.0322 (0.0334) time: 3.1284 data: 0.0083 max mem: 33370 +Epoch: [32] [ 460/1319] eta: 0:45:35 lr: 1.1283308999812288e-05 loss: 0.0327 (0.0334) time: 3.1527 data: 0.0080 max mem: 33370 +Epoch: [32] [ 470/1319] eta: 0:45:03 lr: 1.1273245099849142e-05 loss: 0.0305 (0.0334) time: 3.1887 data: 0.0079 max mem: 33370 +Epoch: [32] [ 480/1319] eta: 0:44:31 lr: 1.1263180201532567e-05 loss: 0.0300 (0.0335) time: 3.1771 data: 0.0088 max mem: 33370 +Epoch: [32] [ 490/1319] eta: 0:44:00 lr: 1.1253114303772065e-05 loss: 0.0302 (0.0334) time: 3.1893 data: 0.0087 max mem: 33370 +Epoch: [32] [ 500/1319] eta: 0:43:27 lr: 1.1243047405474862e-05 loss: 0.0256 (0.0334) time: 3.1768 data: 0.0079 max mem: 33370 +Epoch: [32] [ 510/1319] eta: 0:42:55 lr: 1.1232979505545897e-05 loss: 0.0311 (0.0334) time: 3.1612 data: 0.0083 max mem: 33370 +Epoch: [32] [ 520/1319] eta: 0:42:23 lr: 1.1222910602887823e-05 loss: 0.0316 (0.0333) time: 3.1759 data: 0.0083 max mem: 33370 +Epoch: [32] [ 530/1319] eta: 0:41:52 lr: 1.121284069640098e-05 loss: 0.0276 (0.0333) time: 3.2089 data: 0.0087 max mem: 33370 +Epoch: [32] [ 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mem: 33370 +Epoch: [32] [ 620/1319] eta: 0:37:04 lr: 1.112216618313668e-05 loss: 0.0291 (0.0334) time: 3.1991 data: 0.0081 max mem: 33370 +Epoch: [32] [ 630/1319] eta: 0:36:33 lr: 1.1112086177371001e-05 loss: 0.0288 (0.0334) time: 3.1930 data: 0.0079 max mem: 33370 +Epoch: [32] [ 640/1319] eta: 0:36:01 lr: 1.1102005155526735e-05 loss: 0.0303 (0.0333) time: 3.1811 data: 0.0082 max mem: 33370 +Epoch: [32] [ 650/1319] eta: 0:35:29 lr: 1.109192311647611e-05 loss: 0.0303 (0.0333) time: 3.1823 data: 0.0083 max mem: 33370 +Epoch: [32] [ 660/1319] eta: 0:34:57 lr: 1.1081840059088951e-05 loss: 0.0315 (0.0333) time: 3.1726 data: 0.0086 max mem: 33370 +Epoch: [32] [ 670/1319] eta: 0:34:25 lr: 1.1071755982232689e-05 loss: 0.0322 (0.0333) time: 3.1788 data: 0.0085 max mem: 33370 +Epoch: [32] [ 680/1319] eta: 0:33:53 lr: 1.1061670884772347e-05 loss: 0.0310 (0.0334) time: 3.1939 data: 0.0082 max mem: 33370 +Epoch: [32] [ 690/1319] eta: 0:33:22 lr: 1.1051584765570521e-05 loss: 0.0292 (0.0335) time: 3.1873 data: 0.0077 max mem: 33370 +Epoch: [32] [ 700/1319] eta: 0:32:50 lr: 1.1041497623487401e-05 loss: 0.0315 (0.0334) time: 3.1750 data: 0.0074 max mem: 33370 +Epoch: [32] [ 710/1319] eta: 0:32:18 lr: 1.103140945738074e-05 loss: 0.0316 (0.0334) time: 3.1817 data: 0.0077 max mem: 33370 +Epoch: [32] [ 720/1319] eta: 0:31:46 lr: 1.1021320266105851e-05 loss: 0.0325 (0.0334) time: 3.1903 data: 0.0078 max mem: 33370 +Epoch: [32] [ 730/1319] eta: 0:31:15 lr: 1.101123004851561e-05 loss: 0.0303 (0.0334) time: 3.2048 data: 0.0076 max mem: 33370 +Epoch: [32] [ 740/1319] eta: 0:30:42 lr: 1.1001138803460437e-05 loss: 0.0293 (0.0334) time: 3.1835 data: 0.0075 max mem: 33370 +Epoch: [32] [ 750/1319] eta: 0:30:11 lr: 1.099104652978828e-05 loss: 0.0292 (0.0333) time: 3.1777 data: 0.0076 max mem: 33370 +Epoch: [32] [ 760/1319] eta: 0:29:39 lr: 1.0980953226344629e-05 loss: 0.0297 (0.0333) time: 3.1764 data: 0.0076 max mem: 33370 +Epoch: [32] [ 770/1319] eta: 0:29:07 lr: 1.09708588919725e-05 loss: 0.0304 (0.0333) time: 3.1734 data: 0.0077 max mem: 33370 +Epoch: [32] [ 780/1319] eta: 0:28:35 lr: 1.096076352551242e-05 loss: 0.0282 (0.0333) time: 3.1878 data: 0.0082 max mem: 33370 +Epoch: [32] [ 790/1319] eta: 0:28:03 lr: 1.0950667125802427e-05 loss: 0.0291 (0.0332) time: 3.1720 data: 0.0083 max mem: 33370 +Epoch: [32] [ 800/1319] eta: 0:27:31 lr: 1.0940569691678052e-05 loss: 0.0346 (0.0333) time: 3.1571 data: 0.0078 max mem: 33370 +Epoch: [32] [ 810/1319] eta: 0:26:59 lr: 1.0930471221972321e-05 loss: 0.0339 (0.0333) time: 3.1656 data: 0.0078 max mem: 33370 +Epoch: [32] [ 820/1319] eta: 0:26:27 lr: 1.0920371715515753e-05 loss: 0.0293 (0.0332) time: 3.1795 data: 0.0079 max mem: 33370 +Epoch: [32] [ 830/1319] eta: 0:25:56 lr: 1.0910271171136331e-05 loss: 0.0346 (0.0333) time: 3.1835 data: 0.0080 max mem: 33370 +Epoch: [32] [ 840/1319] eta: 0:25:24 lr: 1.0900169587659515e-05 loss: 0.0347 (0.0333) time: 3.1855 data: 0.0082 max mem: 33370 +Epoch: [32] [ 850/1319] eta: 0:24:52 lr: 1.0890066963908222e-05 loss: 0.0290 (0.0333) time: 3.1922 data: 0.0081 max mem: 33370 +Epoch: [32] [ 860/1319] eta: 0:24:21 lr: 1.087996329870281e-05 loss: 0.0279 (0.0332) time: 3.2299 data: 0.0078 max mem: 33370 +Epoch: [32] [ 870/1319] eta: 0:23:49 lr: 1.0869858590861098e-05 loss: 0.0318 (0.0332) time: 3.2265 data: 0.0079 max mem: 33370 +Epoch: [32] [ 880/1319] eta: 0:23:17 lr: 1.085975283919833e-05 loss: 0.0309 (0.0332) time: 3.1665 data: 0.0082 max mem: 33370 +Epoch: [32] [ 890/1319] eta: 0:22:45 lr: 1.0849646042527184e-05 loss: 0.0309 (0.0332) time: 3.1423 data: 0.0083 max mem: 33370 +Epoch: [32] [ 900/1319] eta: 0:22:13 lr: 1.0839538199657755e-05 loss: 0.0298 (0.0332) time: 3.1838 data: 0.0085 max mem: 33370 +Epoch: [32] [ 910/1319] eta: 0:21:42 lr: 1.0829429309397535e-05 loss: 0.0298 (0.0332) time: 3.2251 data: 0.0083 max mem: 33370 +Epoch: [32] [ 920/1319] eta: 0:21:10 lr: 1.0819319370551438e-05 loss: 0.0336 (0.0332) time: 3.2171 data: 0.0081 max mem: 33370 +Epoch: [32] [ 930/1319] eta: 0:20:38 lr: 1.0809208381921764e-05 loss: 0.0323 (0.0332) time: 3.1544 data: 0.0080 max mem: 33370 +Epoch: [32] [ 940/1319] eta: 0:20:06 lr: 1.0799096342308196e-05 loss: 0.0308 (0.0332) time: 3.1591 data: 0.0081 max mem: 33370 +Epoch: [32] [ 950/1319] eta: 0:19:34 lr: 1.0788983250507807e-05 loss: 0.0311 (0.0332) time: 3.1716 data: 0.0078 max mem: 33370 +Epoch: [32] [ 960/1319] eta: 0:19:02 lr: 1.0778869105315014e-05 loss: 0.0311 (0.0332) time: 3.1754 data: 0.0076 max mem: 33370 +Epoch: [32] [ 970/1319] eta: 0:18:30 lr: 1.0768753905521617e-05 loss: 0.0301 (0.0332) time: 3.1747 data: 0.0079 max mem: 33370 +Epoch: [32] [ 980/1319] eta: 0:17:59 lr: 1.0758637649916756e-05 loss: 0.0300 (0.0332) time: 3.1780 data: 0.0077 max mem: 33370 +Epoch: [32] [ 990/1319] eta: 0:17:27 lr: 1.074852033728692e-05 loss: 0.0317 (0.0332) time: 3.2219 data: 0.0078 max mem: 33370 +Epoch: [32] [1000/1319] eta: 0:16:55 lr: 1.073840196641593e-05 loss: 0.0308 (0.0332) time: 3.1967 data: 0.0083 max mem: 33370 +Epoch: [32] [1010/1319] eta: 0:16:23 lr: 1.0728282536084938e-05 loss: 0.0312 (0.0332) time: 3.1807 data: 0.0080 max mem: 33370 +Epoch: [32] [1020/1319] eta: 0:15:51 lr: 1.0718162045072395e-05 loss: 0.0312 (0.0332) time: 3.1696 data: 0.0075 max mem: 33370 +Epoch: [32] [1030/1319] eta: 0:15:19 lr: 1.0708040492154082e-05 loss: 0.0276 (0.0332) time: 3.1502 data: 0.0073 max mem: 33370 +Epoch: [32] [1040/1319] eta: 0:14:47 lr: 1.069791787610307e-05 loss: 0.0282 (0.0332) time: 3.1568 data: 0.0076 max mem: 33370 +Epoch: [32] [1050/1319] eta: 0:14:16 lr: 1.0687794195689722e-05 loss: 0.0282 (0.0332) time: 3.1572 data: 0.0077 max mem: 33370 +Epoch: [32] [1060/1319] eta: 0:13:44 lr: 1.0677669449681687e-05 loss: 0.0316 (0.0332) time: 3.1954 data: 0.0076 max mem: 33370 +Epoch: [32] [1070/1319] eta: 0:13:12 lr: 1.0667543636843873e-05 loss: 0.0329 (0.0332) time: 3.2023 data: 0.0075 max mem: 33370 +Epoch: [32] [1080/1319] eta: 0:12:40 lr: 1.0657416755938468e-05 loss: 0.0349 (0.0332) time: 3.1960 data: 0.0077 max mem: 33370 +Epoch: [32] [1090/1319] eta: 0:12:08 lr: 1.0647288805724908e-05 loss: 0.0373 (0.0333) time: 3.2105 data: 0.0079 max mem: 33370 +Epoch: [32] [1100/1319] eta: 0:11:37 lr: 1.0637159784959879e-05 loss: 0.0339 (0.0333) time: 3.1941 data: 0.0081 max mem: 33370 +Epoch: [32] [1110/1319] eta: 0:11:05 lr: 1.0627029692397306e-05 loss: 0.0339 (0.0333) time: 3.1918 data: 0.0082 max mem: 33370 +Epoch: [32] [1120/1319] eta: 0:10:33 lr: 1.0616898526788328e-05 loss: 0.0300 (0.0333) time: 3.1947 data: 0.0079 max mem: 33370 +Epoch: [32] [1130/1319] eta: 0:10:01 lr: 1.0606766286881316e-05 loss: 0.0285 (0.0333) time: 3.1678 data: 0.0079 max mem: 33370 +Epoch: [32] [1140/1319] eta: 0:09:29 lr: 1.059663297142185e-05 loss: 0.0263 (0.0333) time: 3.1318 data: 0.0080 max mem: 33370 +Epoch: [32] [1150/1319] eta: 0:08:57 lr: 1.058649857915271e-05 loss: 0.0304 (0.0334) time: 3.1656 data: 0.0077 max mem: 33370 +Epoch: [32] [1160/1319] eta: 0:08:26 lr: 1.0576363108813862e-05 loss: 0.0320 (0.0334) time: 3.1891 data: 0.0075 max mem: 33370 +Epoch: [32] [1170/1319] eta: 0:07:54 lr: 1.0566226559142468e-05 loss: 0.0326 (0.0334) time: 3.1479 data: 0.0074 max mem: 33370 +Epoch: [32] [1180/1319] eta: 0:07:22 lr: 1.0556088928872841e-05 loss: 0.0305 (0.0334) time: 3.1740 data: 0.0073 max mem: 33370 +Epoch: [32] [1190/1319] eta: 0:06:50 lr: 1.0545950216736473e-05 loss: 0.0300 (0.0334) time: 3.2032 data: 0.0072 max mem: 33370 +Epoch: [32] [1200/1319] eta: 0:06:18 lr: 1.0535810421462011e-05 loss: 0.0316 (0.0334) time: 3.1828 data: 0.0075 max mem: 33370 +Epoch: [32] [1210/1319] eta: 0:05:46 lr: 1.0525669541775238e-05 loss: 0.0307 (0.0333) time: 3.1804 data: 0.0080 max mem: 33370 +Epoch: [32] [1220/1319] eta: 0:05:15 lr: 1.0515527576399085e-05 loss: 0.0352 (0.0333) time: 3.1697 data: 0.0084 max mem: 33370 +Epoch: [32] [1230/1319] eta: 0:04:43 lr: 1.050538452405359e-05 loss: 0.0357 (0.0333) time: 3.1904 data: 0.0083 max mem: 33370 +Epoch: [32] [1240/1319] eta: 0:04:11 lr: 1.049524038345592e-05 loss: 0.0306 (0.0333) time: 3.1939 data: 0.0077 max mem: 33370 +Epoch: [32] [1250/1319] eta: 0:03:39 lr: 1.048509515332035e-05 loss: 0.0280 (0.0333) time: 3.2025 data: 0.0079 max mem: 33370 +Epoch: [32] [1260/1319] eta: 0:03:07 lr: 1.0474948832358245e-05 loss: 0.0300 (0.0333) time: 3.2095 data: 0.0083 max mem: 33370 +Epoch: [32] [1270/1319] eta: 0:02:35 lr: 1.0464801419278068e-05 loss: 0.0339 (0.0333) time: 3.1828 data: 0.0082 max mem: 33370 +Epoch: [32] [1280/1319] eta: 0:02:04 lr: 1.0454652912785337e-05 loss: 0.0342 (0.0333) time: 3.1763 data: 0.0079 max mem: 33370 +Epoch: [32] [1290/1319] eta: 0:01:32 lr: 1.0444503311582662e-05 loss: 0.0342 (0.0333) time: 3.1993 data: 0.0076 max mem: 33370 +Epoch: [32] [1300/1319] eta: 0:01:00 lr: 1.0434352614369702e-05 loss: 0.0317 (0.0333) time: 3.1882 data: 0.0081 max mem: 33370 +Epoch: [32] [1310/1319] eta: 0:00:28 lr: 1.0424200819843158e-05 loss: 0.0317 (0.0333) time: 3.1695 data: 0.0081 max mem: 33370 +Epoch: [32] Total time: 1:09:58 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 2:13:50 time: 3.1209 data: 3.0088 max mem: 33370 +Test: [ 100/2573] eta: 0:04:25 time: 0.0774 data: 0.0016 max mem: 33370 +Test: [ 200/2573] eta: 0:03:41 time: 0.0779 data: 0.0014 max mem: 33370 +Test: [ 300/2573] eta: 0:03:19 time: 0.0802 data: 0.0014 max mem: 33370 +Test: [ 400/2573] eta: 0:03:05 time: 0.0806 data: 0.0014 max mem: 33370 +Test: [ 500/2573] eta: 0:02:54 time: 0.0795 data: 0.0014 max mem: 33370 +Test: [ 600/2573] eta: 0:02:44 time: 0.0784 data: 0.0014 max mem: 33370 +Test: [ 700/2573] eta: 0:02:35 time: 0.0796 data: 0.0014 max mem: 33370 +Test: [ 800/2573] eta: 0:02:26 time: 0.0816 data: 0.0014 max mem: 33370 +Test: [ 900/2573] eta: 0:02:18 time: 0.0799 data: 0.0015 max mem: 33370 +Test: [1000/2573] eta: 0:02:09 time: 0.0790 data: 0.0015 max mem: 33370 +Test: [1100/2573] eta: 0:02:00 time: 0.0796 data: 0.0016 max mem: 33370 +Test: [1200/2573] eta: 0:01:52 time: 0.0795 data: 0.0014 max mem: 33370 +Test: [1300/2573] eta: 0:01:43 time: 0.0787 data: 0.0014 max mem: 33370 +Test: [1400/2573] eta: 0:01:35 time: 0.0782 data: 0.0015 max mem: 33370 +Test: [1500/2573] eta: 0:01:27 time: 0.0788 data: 0.0015 max mem: 33370 +Test: [1600/2573] eta: 0:01:18 time: 0.0818 data: 0.0015 max mem: 33370 +Test: [1700/2573] eta: 0:01:10 time: 0.0785 data: 0.0016 max mem: 33370 +Test: [1800/2573] eta: 0:01:02 time: 0.0811 data: 0.0015 max mem: 33370 +Test: [1900/2573] eta: 0:00:54 time: 0.0787 data: 0.0015 max mem: 33370 +Test: [2000/2573] eta: 0:00:46 time: 0.0799 data: 0.0015 max mem: 33370 +Test: [2100/2573] eta: 0:00:38 time: 0.0811 data: 0.0014 max mem: 33370 +Test: [2200/2573] eta: 0:00:30 time: 0.0819 data: 0.0014 max mem: 33370 +Test: [2300/2573] eta: 0:00:22 time: 0.0809 data: 0.0014 max mem: 33370 +Test: [2400/2573] eta: 0:00:13 time: 0.0768 data: 0.0015 max mem: 33370 +Test: [2500/2573] eta: 0:00:05 time: 0.0787 data: 0.0014 max mem: 33370 +Test: Total time: 0:03:27 +Final results: +Mean IoU is 64.25 + + precision@0.5 = 72.30 + precision@0.6 = 67.22 + precision@0.7 = 60.15 + precision@0.8 = 48.86 + precision@0.9 = 24.78 + overall IoU = 61.89 + +Average object IoU 64.24737122255144 +Overall IoU 61.89162063598633 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [33] [ 0/1319] eta: 2:43:17 lr: 1.04150632654866e-05 loss: 0.0303 (0.0303) time: 7.4283 data: 2.5699 max mem: 33370 +Epoch: [33] [ 10/1319] eta: 1:16:33 lr: 1.0404909382463066e-05 loss: 0.0271 (0.0264) time: 3.5093 data: 0.2408 max mem: 33370 +Epoch: [33] [ 20/1319] eta: 1:12:19 lr: 1.0394754398329612e-05 loss: 0.0271 (0.0315) time: 3.1364 data: 0.0079 max mem: 33370 +Epoch: [33] [ 30/1319] eta: 1:10:43 lr: 1.0384598311771345e-05 loss: 0.0312 (0.0314) time: 3.1728 data: 0.0089 max mem: 33370 +Epoch: [33] [ 40/1319] eta: 1:09:58 lr: 1.0374441121470351e-05 loss: 0.0319 (0.0319) time: 3.2224 data: 0.0092 max mem: 33370 +Epoch: [33] [ 50/1319] eta: 1:08:58 lr: 1.0364282826105723e-05 loss: 0.0309 (0.0320) time: 3.2126 data: 0.0084 max mem: 33370 +Epoch: [33] [ 60/1319] eta: 1:08:07 lr: 1.0354123424353528e-05 loss: 0.0307 (0.0325) time: 3.1716 data: 0.0084 max mem: 33370 +Epoch: [33] [ 70/1319] eta: 1:07:31 lr: 1.0343962914886797e-05 loss: 0.0325 (0.0334) time: 3.1999 data: 0.0082 max mem: 33370 +Epoch: [33] [ 80/1319] eta: 1:06:40 lr: 1.033380129637553e-05 loss: 0.0310 (0.0331) time: 3.1735 data: 0.0077 max mem: 33370 +Epoch: [33] [ 90/1319] eta: 1:05:55 lr: 1.0323638567486653e-05 loss: 0.0282 (0.0329) time: 3.1304 data: 0.0077 max mem: 33370 +Epoch: [33] [ 100/1319] eta: 1:05:20 lr: 1.0313474726884054e-05 loss: 0.0327 (0.0330) time: 3.1666 data: 0.0081 max mem: 33370 +Epoch: [33] [ 110/1319] eta: 1:04:44 lr: 1.0303309773228537e-05 loss: 0.0325 (0.0328) time: 3.1877 data: 0.0081 max mem: 33370 +Epoch: [33] [ 120/1319] eta: 1:04:10 lr: 1.0293143705177821e-05 loss: 0.0291 (0.0323) time: 3.1855 data: 0.0080 max mem: 33370 +Epoch: [33] [ 130/1319] eta: 1:03:30 lr: 1.0282976521386539e-05 loss: 0.0275 (0.0323) time: 3.1587 data: 0.0081 max mem: 33370 +Epoch: [33] [ 140/1319] eta: 1:02:59 lr: 1.0272808220506222e-05 loss: 0.0293 (0.0325) time: 3.1755 data: 0.0077 max mem: 33370 +Epoch: [33] [ 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data: 0.0079 max mem: 33370 +Epoch: [33] [ 310/1319] eta: 0:53:35 lr: 1.0099774868986322e-05 loss: 0.0320 (0.0326) time: 3.1713 data: 0.0079 max mem: 33370 +Epoch: [33] [ 320/1319] eta: 0:53:02 lr: 1.008958622631076e-05 loss: 0.0315 (0.0327) time: 3.1730 data: 0.0081 max mem: 33370 +Epoch: [33] [ 330/1319] eta: 0:52:29 lr: 1.0079396440320953e-05 loss: 0.0315 (0.0328) time: 3.1470 data: 0.0080 max mem: 33370 +Epoch: [33] [ 340/1319] eta: 0:51:56 lr: 1.0069205509604051e-05 loss: 0.0306 (0.0328) time: 3.1401 data: 0.0079 max mem: 33370 +Epoch: [33] [ 350/1319] eta: 0:51:24 lr: 1.0059013432743876e-05 loss: 0.0300 (0.0327) time: 3.1716 data: 0.0078 max mem: 33370 +Epoch: [33] [ 360/1319] eta: 0:50:51 lr: 1.0048820208320883e-05 loss: 0.0300 (0.0327) time: 3.1583 data: 0.0078 max mem: 33370 +Epoch: [33] [ 370/1319] eta: 0:50:20 lr: 1.0038625834912186e-05 loss: 0.0293 (0.0325) time: 3.1626 data: 0.0079 max mem: 33370 +Epoch: [33] [ 380/1319] eta: 0:49:48 lr: 1.0028430311091521e-05 loss: 0.0302 (0.0327) time: 3.2021 data: 0.0078 max mem: 33370 +Epoch: [33] [ 390/1319] eta: 0:49:16 lr: 1.0018233635429235e-05 loss: 0.0327 (0.0326) time: 3.1879 data: 0.0076 max mem: 33370 +Epoch: [33] [ 400/1319] eta: 0:48:44 lr: 1.0008035806492287e-05 loss: 0.0303 (0.0326) time: 3.1731 data: 0.0078 max mem: 33370 +Epoch: [33] [ 410/1319] eta: 0:48:14 lr: 9.99783682284423e-06 loss: 0.0303 (0.0326) time: 3.2091 data: 0.0079 max mem: 33370 +Epoch: [33] [ 420/1319] eta: 0:47:41 lr: 9.987636683045179e-06 loss: 0.0320 (0.0325) time: 3.1893 data: 0.0086 max mem: 33370 +Epoch: [33] [ 430/1319] eta: 0:47:08 lr: 9.977435385651839e-06 loss: 0.0270 (0.0325) time: 3.1360 data: 0.0084 max mem: 33370 +Epoch: [33] [ 440/1319] eta: 0:46:37 lr: 9.967232929217462e-06 loss: 0.0267 (0.0324) time: 3.1750 data: 0.0079 max mem: 33370 +Epoch: [33] [ 450/1319] eta: 0:46:05 lr: 9.957029312291845e-06 loss: 0.0288 (0.0324) time: 3.1912 data: 0.0080 max mem: 33370 +Epoch: [33] [ 460/1319] eta: 0:45:33 lr: 9.946824533421325e-06 loss: 0.0288 (0.0324) time: 3.1733 data: 0.0081 max mem: 33370 +Epoch: [33] [ 470/1319] eta: 0:45:00 lr: 9.936618591148734e-06 loss: 0.0323 (0.0325) time: 3.1593 data: 0.0083 max mem: 33370 +Epoch: [33] [ 480/1319] eta: 0:44:29 lr: 9.92641148401344e-06 loss: 0.0323 (0.0326) time: 3.1602 data: 0.0079 max mem: 33370 +Epoch: [33] [ 490/1319] eta: 0:43:56 lr: 9.916203210551294e-06 loss: 0.0313 (0.0327) time: 3.1737 data: 0.0081 max mem: 33370 +Epoch: [33] [ 500/1319] eta: 0:43:25 lr: 9.905993769294629e-06 loss: 0.0313 (0.0326) time: 3.1738 data: 0.0082 max mem: 33370 +Epoch: [33] [ 510/1319] eta: 0:42:52 lr: 9.895783158772255e-06 loss: 0.0330 (0.0328) time: 3.1608 data: 0.0079 max mem: 33370 +Epoch: [33] [ 520/1319] eta: 0:42:20 lr: 9.885571377509421e-06 loss: 0.0332 (0.0328) time: 3.1437 data: 0.0080 max mem: 33370 +Epoch: [33] [ 530/1319] eta: 0:41:48 lr: 9.875358424027841e-06 loss: 0.0294 (0.0329) time: 3.1573 data: 0.0079 max mem: 33370 +Epoch: [33] [ 540/1319] eta: 0:41:16 lr: 9.865144296845656e-06 loss: 0.0317 (0.0329) time: 3.1711 data: 0.0074 max mem: 33370 +Epoch: [33] [ 550/1319] eta: 0:40:44 lr: 9.85492899447742e-06 loss: 0.0333 (0.0330) time: 3.1748 data: 0.0077 max mem: 33370 +Epoch: [33] [ 560/1319] eta: 0:40:13 lr: 9.844712515434104e-06 loss: 0.0305 (0.0329) time: 3.1897 data: 0.0080 max mem: 33370 +Epoch: [33] [ 570/1319] eta: 0:39:41 lr: 9.83449485822307e-06 loss: 0.0305 (0.0329) time: 3.1856 data: 0.0082 max mem: 33370 +Epoch: [33] [ 580/1319] eta: 0:39:09 lr: 9.824276021348049e-06 loss: 0.0318 (0.0329) time: 3.1721 data: 0.0083 max mem: 33370 +Epoch: [33] [ 590/1319] eta: 0:38:37 lr: 9.814056003309152e-06 loss: 0.0327 (0.0329) time: 3.1839 data: 0.0081 max mem: 33370 +Epoch: [33] [ 600/1319] eta: 0:38:05 lr: 9.803834802602848e-06 loss: 0.0338 (0.0329) time: 3.1764 data: 0.0079 max mem: 33370 +Epoch: [33] [ 610/1319] eta: 0:37:33 lr: 9.793612417721937e-06 loss: 0.0314 (0.0329) time: 3.1624 data: 0.0080 max mem: 33370 +Epoch: [33] [ 620/1319] eta: 0:37:01 lr: 9.783388847155563e-06 loss: 0.0314 (0.0329) time: 3.1589 data: 0.0084 max mem: 33370 +Epoch: [33] [ 630/1319] eta: 0:36:30 lr: 9.773164089389164e-06 loss: 0.0284 (0.0329) time: 3.1824 data: 0.0085 max mem: 33370 +Epoch: [33] [ 640/1319] eta: 0:35:57 lr: 9.762938142904499e-06 loss: 0.0299 (0.0330) time: 3.1668 data: 0.0081 max mem: 33370 +Epoch: [33] [ 650/1319] eta: 0:35:26 lr: 9.752711006179608e-06 loss: 0.0299 (0.0329) time: 3.1502 data: 0.0081 max mem: 33370 +Epoch: [33] [ 660/1319] eta: 0:34:54 lr: 9.742482677688807e-06 loss: 0.0300 (0.0329) time: 3.1642 data: 0.0080 max mem: 33370 +Epoch: [33] [ 670/1319] eta: 0:34:22 lr: 9.732253155902685e-06 loss: 0.0303 (0.0329) time: 3.1695 data: 0.0078 max mem: 33370 +Epoch: [33] [ 680/1319] eta: 0:33:50 lr: 9.722022439288054e-06 loss: 0.0293 (0.0328) time: 3.1728 data: 0.0082 max mem: 33370 +Epoch: [33] [ 690/1319] eta: 0:33:18 lr: 9.711790526307984e-06 loss: 0.0281 (0.0328) time: 3.1753 data: 0.0085 max mem: 33370 +Epoch: [33] [ 700/1319] eta: 0:32:46 lr: 9.701557415421759e-06 loss: 0.0273 (0.0329) time: 3.1757 data: 0.0080 max mem: 33370 +Epoch: [33] [ 710/1319] eta: 0:32:15 lr: 9.69132310508487e-06 loss: 0.0313 (0.0329) time: 3.1941 data: 0.0081 max mem: 33370 +Epoch: [33] [ 720/1319] eta: 0:31:43 lr: 9.681087593749006e-06 loss: 0.0313 (0.0329) time: 3.1994 data: 0.0087 max mem: 33370 +Epoch: [33] [ 730/1319] eta: 0:31:11 lr: 9.670850879862032e-06 loss: 0.0296 (0.0329) time: 3.1646 data: 0.0086 max mem: 33370 +Epoch: [33] [ 740/1319] eta: 0:30:39 lr: 9.660612961867972e-06 loss: 0.0296 (0.0328) time: 3.1432 data: 0.0086 max mem: 33370 +Epoch: [33] [ 750/1319] eta: 0:30:07 lr: 9.650373838207014e-06 loss: 0.0303 (0.0328) time: 3.1355 data: 0.0089 max mem: 33370 +Epoch: [33] [ 760/1319] eta: 0:29:35 lr: 9.640133507315477e-06 loss: 0.0263 (0.0327) time: 3.1406 data: 0.0089 max mem: 33370 +Epoch: [33] [ 770/1319] eta: 0:29:03 lr: 9.62989196762581e-06 loss: 0.0263 (0.0327) time: 3.1662 data: 0.0086 max mem: 33370 +Epoch: [33] [ 780/1319] eta: 0:28:32 lr: 9.61964921756657e-06 loss: 0.0325 (0.0327) time: 3.1867 data: 0.0088 max mem: 33370 +Epoch: [33] [ 790/1319] eta: 0:28:00 lr: 9.609405255562397e-06 loss: 0.0311 (0.0327) time: 3.2148 data: 0.0089 max mem: 33370 +Epoch: [33] [ 800/1319] eta: 0:27:29 lr: 9.599160080034027e-06 loss: 0.0292 (0.0327) time: 3.2090 data: 0.0090 max mem: 33370 +Epoch: [33] [ 810/1319] eta: 0:26:57 lr: 9.588913689398257e-06 loss: 0.0292 (0.0327) time: 3.2127 data: 0.0089 max mem: 33370 +Epoch: [33] [ 820/1319] eta: 0:26:25 lr: 9.578666082067937e-06 loss: 0.0266 (0.0326) time: 3.2077 data: 0.0081 max mem: 33370 +Epoch: [33] [ 830/1319] eta: 0:25:54 lr: 9.568417256451955e-06 loss: 0.0271 (0.0326) time: 3.1782 data: 0.0079 max mem: 33370 +Epoch: [33] [ 840/1319] eta: 0:25:22 lr: 9.558167210955227e-06 loss: 0.0304 (0.0326) time: 3.1995 data: 0.0080 max mem: 33370 +Epoch: [33] [ 850/1319] eta: 0:24:50 lr: 9.547915943978656e-06 loss: 0.0306 (0.0326) time: 3.1878 data: 0.0083 max mem: 33370 +Epoch: [33] [ 860/1319] eta: 0:24:19 lr: 9.537663453919165e-06 loss: 0.0315 (0.0326) time: 3.1927 data: 0.0084 max mem: 33370 +Epoch: [33] [ 870/1319] eta: 0:23:47 lr: 9.52740973916964e-06 loss: 0.0312 (0.0326) time: 3.2063 data: 0.0079 max mem: 33370 +Epoch: [33] [ 880/1319] eta: 0:23:15 lr: 9.517154798118936e-06 loss: 0.0268 (0.0326) time: 3.2018 data: 0.0078 max mem: 33370 +Epoch: [33] [ 890/1319] eta: 0:22:44 lr: 9.506898629151863e-06 loss: 0.0279 (0.0326) time: 3.2037 data: 0.0081 max mem: 33370 +Epoch: [33] [ 900/1319] eta: 0:22:12 lr: 9.496641230649144e-06 loss: 0.0356 (0.0326) time: 3.1907 data: 0.0086 max mem: 33370 +Epoch: [33] [ 910/1319] eta: 0:21:40 lr: 9.48638260098744e-06 loss: 0.0288 (0.0326) time: 3.1888 data: 0.0083 max mem: 33370 +Epoch: [33] [ 920/1319] eta: 0:21:08 lr: 9.476122738539313e-06 loss: 0.0281 (0.0327) time: 3.1830 data: 0.0083 max mem: 33370 +Epoch: [33] [ 930/1319] eta: 0:20:37 lr: 9.465861641673206e-06 loss: 0.0325 (0.0327) time: 3.1840 data: 0.0083 max mem: 33370 +Epoch: [33] [ 940/1319] eta: 0:20:05 lr: 9.455599308753445e-06 loss: 0.0283 (0.0327) time: 3.1856 data: 0.0081 max mem: 33370 +Epoch: [33] [ 950/1319] eta: 0:19:33 lr: 9.445335738140192e-06 loss: 0.0337 (0.0328) time: 3.1447 data: 0.0081 max mem: 33370 +Epoch: [33] [ 960/1319] eta: 0:19:01 lr: 9.435070928189476e-06 loss: 0.0338 (0.0328) time: 3.1668 data: 0.0078 max mem: 33370 +Epoch: [33] [ 970/1319] eta: 0:18:29 lr: 9.424804877253139e-06 loss: 0.0286 (0.0328) time: 3.1868 data: 0.0078 max mem: 33370 +Epoch: [33] [ 980/1319] eta: 0:17:57 lr: 9.414537583678836e-06 loss: 0.0327 (0.0328) time: 3.1682 data: 0.0083 max mem: 33370 +Epoch: [33] [ 990/1319] eta: 0:17:25 lr: 9.404269045810016e-06 loss: 0.0321 (0.0328) time: 3.1692 data: 0.0086 max mem: 33370 +Epoch: [33] [1000/1319] eta: 0:16:54 lr: 9.393999261985916e-06 loss: 0.0318 (0.0328) time: 3.1762 data: 0.0084 max mem: 33370 +Epoch: [33] [1010/1319] eta: 0:16:22 lr: 9.383728230541512e-06 loss: 0.0304 (0.0328) time: 3.1706 data: 0.0082 max mem: 33370 +Epoch: [33] [1020/1319] eta: 0:15:50 lr: 9.373455949807552e-06 loss: 0.0295 (0.0328) time: 3.1837 data: 0.0080 max mem: 33370 +Epoch: [33] [1030/1319] eta: 0:15:18 lr: 9.363182418110507e-06 loss: 0.0280 (0.0328) time: 3.2149 data: 0.0080 max mem: 33370 +Epoch: [33] [1040/1319] eta: 0:14:47 lr: 9.352907633772557e-06 loss: 0.0302 (0.0328) time: 3.1972 data: 0.0087 max mem: 33370 +Epoch: [33] [1050/1319] eta: 0:14:15 lr: 9.342631595111597e-06 loss: 0.0305 (0.0328) time: 3.1690 data: 0.0086 max mem: 33370 +Epoch: [33] [1060/1319] eta: 0:13:43 lr: 9.332354300441178e-06 loss: 0.0296 (0.0328) time: 3.1703 data: 0.0080 max mem: 33370 +Epoch: [33] [1070/1319] eta: 0:13:11 lr: 9.322075748070539e-06 loss: 0.0292 (0.0328) time: 3.1682 data: 0.0078 max mem: 33370 +Epoch: [33] [1080/1319] eta: 0:12:39 lr: 9.311795936304561e-06 loss: 0.0279 (0.0328) time: 3.1686 data: 0.0081 max mem: 33370 +Epoch: [33] [1090/1319] eta: 0:12:07 lr: 9.301514863443759e-06 loss: 0.0283 (0.0328) time: 3.1540 data: 0.0090 max mem: 33370 +Epoch: [33] [1100/1319] eta: 0:11:36 lr: 9.291232527784269e-06 loss: 0.0305 (0.0329) time: 3.1678 data: 0.0088 max mem: 33370 +Epoch: [33] [1110/1319] eta: 0:11:04 lr: 9.280948927617811e-06 loss: 0.0311 (0.0329) time: 3.1800 data: 0.0080 max mem: 33370 +Epoch: [33] [1120/1319] eta: 0:10:32 lr: 9.270664061231702e-06 loss: 0.0311 (0.0329) time: 3.1583 data: 0.0077 max mem: 33370 +Epoch: [33] [1130/1319] eta: 0:10:00 lr: 9.260377926908826e-06 loss: 0.0308 (0.0329) time: 3.1637 data: 0.0077 max mem: 33370 +Epoch: [33] [1140/1319] eta: 0:09:28 lr: 9.250090522927605e-06 loss: 0.0307 (0.0329) time: 3.1708 data: 0.0081 max mem: 33370 +Epoch: [33] [1150/1319] eta: 0:08:57 lr: 9.239801847562006e-06 loss: 0.0307 (0.0329) time: 3.1740 data: 0.0083 max mem: 33370 +Epoch: [33] [1160/1319] eta: 0:08:25 lr: 9.229511899081506e-06 loss: 0.0280 (0.0328) time: 3.1648 data: 0.0079 max mem: 33370 +Epoch: [33] [1170/1319] eta: 0:07:53 lr: 9.219220675751069e-06 loss: 0.0289 (0.0328) time: 3.1628 data: 0.0081 max mem: 33370 +Epoch: [33] [1180/1319] eta: 0:07:21 lr: 9.20892817583115e-06 loss: 0.0299 (0.0328) time: 3.1570 data: 0.0083 max mem: 33370 +Epoch: [33] [1190/1319] eta: 0:06:49 lr: 9.19863439757767e-06 loss: 0.0290 (0.0328) time: 3.1725 data: 0.0080 max mem: 33370 +Epoch: [33] [1200/1319] eta: 0:06:18 lr: 9.188339339241987e-06 loss: 0.0290 (0.0328) time: 3.1787 data: 0.0083 max mem: 33370 +Epoch: [33] [1210/1319] eta: 0:05:46 lr: 9.178042999070898e-06 loss: 0.0295 (0.0328) time: 3.1978 data: 0.0082 max mem: 33370 +Epoch: [33] [1220/1319] eta: 0:05:14 lr: 9.16774537530659e-06 loss: 0.0344 (0.0328) time: 3.1879 data: 0.0080 max mem: 33370 +Epoch: [33] [1230/1319] eta: 0:04:42 lr: 9.157446466186662e-06 loss: 0.0337 (0.0328) time: 3.1461 data: 0.0078 max mem: 33370 +Epoch: [33] [1240/1319] eta: 0:04:11 lr: 9.147146269944078e-06 loss: 0.0312 (0.0328) time: 3.1754 data: 0.0076 max mem: 33370 +Epoch: [33] [1250/1319] eta: 0:03:39 lr: 9.136844784807162e-06 loss: 0.0291 (0.0328) time: 3.1734 data: 0.0078 max mem: 33370 +Epoch: [33] [1260/1319] eta: 0:03:07 lr: 9.126542008999582e-06 loss: 0.0292 (0.0328) time: 3.1715 data: 0.0078 max mem: 33370 +Epoch: [33] [1270/1319] eta: 0:02:35 lr: 9.11623794074031e-06 loss: 0.0304 (0.0328) time: 3.1940 data: 0.0078 max mem: 33370 +Epoch: [33] [1280/1319] eta: 0:02:03 lr: 9.105932578243631e-06 loss: 0.0281 (0.0328) time: 3.2044 data: 0.0079 max mem: 33370 +Epoch: [33] [1290/1319] eta: 0:01:32 lr: 9.095625919719118e-06 loss: 0.0294 (0.0328) time: 3.2124 data: 0.0082 max mem: 33370 +Epoch: [33] [1300/1319] eta: 0:01:00 lr: 9.085317963371604e-06 loss: 0.0337 (0.0328) time: 3.2083 data: 0.0081 max mem: 33370 +Epoch: [33] [1310/1319] eta: 0:00:28 lr: 9.075008707401167e-06 loss: 0.0312 (0.0329) time: 3.2251 data: 0.0074 max mem: 33370 +Epoch: [33] Total time: 1:09:53 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 2:25:28 time: 3.3924 data: 3.2983 max mem: 33370 +Test: [ 100/2573] eta: 0:04:30 time: 0.0767 data: 0.0014 max mem: 33370 +Test: [ 200/2573] eta: 0:03:43 time: 0.0788 data: 0.0015 max mem: 33370 +Test: [ 300/2573] eta: 0:03:21 time: 0.0796 data: 0.0014 max mem: 33370 +Test: [ 400/2573] eta: 0:03:06 time: 0.0798 data: 0.0014 max mem: 33370 +Test: [ 500/2573] eta: 0:02:55 time: 0.0796 data: 0.0015 max mem: 33370 +Test: [ 600/2573] eta: 0:02:45 time: 0.0794 data: 0.0015 max mem: 33370 +Test: [ 700/2573] eta: 0:02:36 time: 0.0795 data: 0.0015 max mem: 33370 +Test: [ 800/2573] eta: 0:02:27 time: 0.0827 data: 0.0015 max mem: 33370 +Test: [ 900/2573] eta: 0:02:18 time: 0.0797 data: 0.0015 max mem: 33370 +Test: [1000/2573] eta: 0:02:09 time: 0.0816 data: 0.0017 max mem: 33370 +Test: [1100/2573] eta: 0:02:01 time: 0.0796 data: 0.0016 max mem: 33370 +Test: [1200/2573] eta: 0:01:52 time: 0.0793 data: 0.0015 max mem: 33370 +Test: [1300/2573] eta: 0:01:44 time: 0.0792 data: 0.0014 max mem: 33370 +Test: [1400/2573] eta: 0:01:35 time: 0.0785 data: 0.0015 max mem: 33370 +Test: [1500/2573] eta: 0:01:27 time: 0.0787 data: 0.0015 max mem: 33370 +Test: [1600/2573] eta: 0:01:19 time: 0.0824 data: 0.0015 max mem: 33370 +Test: [1700/2573] eta: 0:01:11 time: 0.0775 data: 0.0014 max mem: 33370 +Test: [1800/2573] eta: 0:01:02 time: 0.0813 data: 0.0014 max mem: 33370 +Test: [1900/2573] eta: 0:00:54 time: 0.0774 data: 0.0014 max mem: 33370 +Test: [2000/2573] eta: 0:00:46 time: 0.0799 data: 0.0016 max mem: 33370 +Test: [2100/2573] eta: 0:00:38 time: 0.0803 data: 0.0013 max mem: 33370 +Test: [2200/2573] eta: 0:00:30 time: 0.0814 data: 0.0013 max mem: 33370 +Test: [2300/2573] eta: 0:00:22 time: 0.0818 data: 0.0015 max mem: 33370 +Test: [2400/2573] eta: 0:00:13 time: 0.0769 data: 0.0014 max mem: 33370 +Test: [2500/2573] eta: 0:00:05 time: 0.0801 data: 0.0015 max mem: 33370 +Test: Total time: 0:03:28 +Final results: +Mean IoU is 65.00 + + precision@0.5 = 72.55 + precision@0.6 = 67.61 + precision@0.7 = 60.19 + precision@0.8 = 49.78 + precision@0.9 = 25.74 + overall IoU = 62.37 + +Average object IoU 65.00064707890209 +Overall IoU 62.36533737182617 +Better epoch: 33 + +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [34] [ 0/1319] eta: 1:47:54 lr: 9.065729264358701e-06 loss: 0.0226 (0.0226) time: 4.9084 data: 1.6746 max mem: 33370 +Epoch: [34] [ 10/1319] eta: 1:13:04 lr: 9.05541753412883e-06 loss: 0.0261 (0.0333) time: 3.3499 data: 0.1591 max mem: 33370 +Epoch: [34] [ 20/1319] eta: 1:10:30 lr: 9.045104499029229e-06 loss: 0.0294 (0.0321) time: 3.1744 data: 0.0078 max mem: 33370 +Epoch: [34] [ 30/1319] eta: 1:09:50 lr: 9.03479015724125e-06 loss: 0.0294 (0.0320) time: 3.1965 data: 0.0080 max mem: 33370 +Epoch: [34] [ 40/1319] eta: 1:08:48 lr: 9.024474506941415e-06 loss: 0.0290 (0.0310) time: 3.1970 data: 0.0080 max mem: 33370 +Epoch: [34] [ 50/1319] eta: 1:08:02 lr: 9.014157546301385e-06 loss: 0.0265 (0.0307) time: 3.1649 data: 0.0077 max mem: 33370 +Epoch: [34] [ 60/1319] eta: 1:07:22 lr: 9.003839273487931e-06 loss: 0.0300 (0.0313) time: 3.1754 data: 0.0079 max mem: 33370 +Epoch: [34] [ 70/1319] eta: 1:06:53 lr: 8.99351968666293e-06 loss: 0.0302 (0.0307) time: 3.2032 data: 0.0081 max mem: 33370 +Epoch: [34] [ 80/1319] eta: 1:06:09 lr: 8.983198783983315e-06 loss: 0.0321 (0.0317) time: 3.1832 data: 0.0081 max mem: 33370 +Epoch: [34] [ 90/1319] eta: 1:05:36 lr: 8.972876563601101e-06 loss: 0.0327 (0.0318) time: 3.1685 data: 0.0083 max mem: 33370 +Epoch: [34] [ 100/1319] eta: 1:05:00 lr: 8.962553023663333e-06 loss: 0.0301 (0.0330) time: 3.1833 data: 0.0081 max mem: 33370 +Epoch: [34] [ 110/1319] eta: 1:04:30 lr: 8.952228162312077e-06 loss: 0.0295 (0.0326) time: 3.1912 data: 0.0080 max mem: 33370 +Epoch: [34] [ 120/1319] eta: 1:03:55 lr: 8.941901977684397e-06 loss: 0.0295 (0.0328) time: 3.1952 data: 0.0082 max mem: 33370 +Epoch: [34] [ 130/1319] eta: 1:03:21 lr: 8.93157446791234e-06 loss: 0.0315 (0.0327) time: 3.1748 data: 0.0081 max mem: 33370 +Epoch: [34] [ 140/1319] eta: 1:02:48 lr: 8.9212456311229e-06 loss: 0.0327 (0.0329) time: 3.1815 data: 0.0079 max mem: 33370 +Epoch: [34] [ 150/1319] eta: 1:02:14 lr: 8.910915465438025e-06 loss: 0.0334 (0.0331) time: 3.1761 data: 0.0081 max mem: 33370 +Epoch: [34] [ 160/1319] eta: 1:01:40 lr: 8.900583968974578e-06 loss: 0.0321 (0.0329) time: 3.1651 data: 0.0082 max mem: 33370 +Epoch: [34] [ 170/1319] eta: 1:01:10 lr: 8.89025113984432e-06 loss: 0.0309 (0.0327) time: 3.1990 data: 0.0085 max mem: 33370 +Epoch: [34] [ 180/1319] eta: 1:00:38 lr: 8.879916976153894e-06 loss: 0.0299 (0.0326) time: 3.2122 data: 0.0087 max mem: 33370 +Epoch: [34] [ 190/1319] eta: 1:00:06 lr: 8.869581476004788e-06 loss: 0.0308 (0.0326) time: 3.1929 data: 0.0087 max mem: 33370 +Epoch: [34] [ 200/1319] eta: 0:59:34 lr: 8.859244637493344e-06 loss: 0.0308 (0.0326) time: 3.1926 data: 0.0089 max mem: 33370 +Epoch: [34] [ 210/1319] eta: 0:58:59 lr: 8.84890645871071e-06 loss: 0.0308 (0.0326) time: 3.1666 data: 0.0086 max mem: 33370 +Epoch: [34] [ 220/1319] eta: 0:58:29 lr: 8.838566937742836e-06 loss: 0.0334 (0.0327) time: 3.1764 data: 0.0084 max mem: 33370 +Epoch: [34] [ 230/1319] eta: 0:57:56 lr: 8.828226072670449e-06 loss: 0.0300 (0.0325) time: 3.2001 data: 0.0084 max mem: 33370 +Epoch: [34] [ 240/1319] eta: 0:57:25 lr: 8.817883861569014e-06 loss: 0.0300 (0.0325) time: 3.1950 data: 0.0080 max mem: 33370 +Epoch: [34] [ 250/1319] eta: 0:56:53 lr: 8.807540302508743e-06 loss: 0.0337 (0.0328) time: 3.1973 data: 0.0082 max mem: 33370 +Epoch: [34] [ 260/1319] eta: 0:56:20 lr: 8.797195393554557e-06 loss: 0.0320 (0.0327) time: 3.1865 data: 0.0083 max mem: 33370 +Epoch: [34] [ 270/1319] eta: 0:55:47 lr: 8.786849132766063e-06 loss: 0.0282 (0.0325) time: 3.1708 data: 0.0081 max mem: 33370 +Epoch: [34] [ 280/1319] eta: 0:55:16 lr: 8.776501518197541e-06 loss: 0.0292 (0.0324) time: 3.1820 data: 0.0082 max mem: 33370 +Epoch: [34] [ 290/1319] eta: 0:54:42 lr: 8.76615254789792e-06 loss: 0.0301 (0.0324) time: 3.1682 data: 0.0083 max mem: 33370 +Epoch: [34] [ 300/1319] eta: 0:54:10 lr: 8.755802219910735e-06 loss: 0.0320 (0.0324) time: 3.1606 data: 0.0078 max mem: 33370 +Epoch: [34] [ 310/1319] eta: 0:53:37 lr: 8.745450532274145e-06 loss: 0.0320 (0.0325) time: 3.1774 data: 0.0077 max mem: 33370 +Epoch: [34] [ 320/1319] eta: 0:53:05 lr: 8.735097483020883e-06 loss: 0.0316 (0.0325) time: 3.1706 data: 0.0080 max mem: 33370 +Epoch: [34] [ 330/1319] eta: 0:52:33 lr: 8.724743070178239e-06 loss: 0.0316 (0.0325) time: 3.1748 data: 0.0082 max mem: 33370 +Epoch: [34] [ 340/1319] eta: 0:52:00 lr: 8.714387291768046e-06 loss: 0.0280 (0.0325) time: 3.1739 data: 0.0084 max mem: 33370 +Epoch: [34] [ 350/1319] eta: 0:51:27 lr: 8.704030145806636e-06 loss: 0.0268 (0.0326) time: 3.1560 data: 0.0085 max mem: 33370 +Epoch: [34] [ 360/1319] eta: 0:50:57 lr: 8.693671630304845e-06 loss: 0.0305 (0.0326) time: 3.1895 data: 0.0083 max mem: 33370 +Epoch: [34] [ 370/1319] eta: 0:50:25 lr: 8.683311743267978e-06 loss: 0.0310 (0.0326) time: 3.2214 data: 0.0080 max mem: 33370 +Epoch: [34] [ 380/1319] eta: 0:49:53 lr: 8.672950482695785e-06 loss: 0.0298 (0.0325) time: 3.1944 data: 0.0082 max mem: 33370 +Epoch: [34] [ 390/1319] eta: 0:49:22 lr: 8.662587846582436e-06 loss: 0.0307 (0.0325) time: 3.2085 data: 0.0082 max mem: 33370 +Epoch: [34] [ 400/1319] eta: 0:48:50 lr: 8.65222383291651e-06 loss: 0.0343 (0.0327) time: 3.1922 data: 0.0081 max mem: 33370 +Epoch: [34] [ 410/1319] eta: 0:48:18 lr: 8.641858439680947e-06 loss: 0.0302 (0.0327) time: 3.1751 data: 0.0086 max mem: 33370 +Epoch: [34] [ 420/1319] eta: 0:47:47 lr: 8.631491664853054e-06 loss: 0.0290 (0.0327) time: 3.2189 data: 0.0085 max mem: 33370 +Epoch: [34] [ 430/1319] eta: 0:47:14 lr: 8.621123506404469e-06 loss: 0.0273 (0.0326) time: 3.1900 data: 0.0082 max mem: 33370 +Epoch: [34] [ 440/1319] eta: 0:46:43 lr: 8.610753962301133e-06 loss: 0.0291 (0.0326) time: 3.1716 data: 0.0083 max mem: 33370 +Epoch: [34] [ 450/1319] eta: 0:46:11 lr: 8.600383030503278e-06 loss: 0.0313 (0.0326) time: 3.1984 data: 0.0084 max mem: 33370 +Epoch: [34] [ 460/1319] eta: 0:45:38 lr: 8.590010708965377e-06 loss: 0.0334 (0.0326) time: 3.1634 data: 0.0084 max mem: 33370 +Epoch: [34] [ 470/1319] eta: 0:45:06 lr: 8.579636995636159e-06 loss: 0.0327 (0.0326) time: 3.1482 data: 0.0082 max mem: 33370 +Epoch: [34] [ 480/1319] eta: 0:44:34 lr: 8.569261888458558e-06 loss: 0.0288 (0.0327) time: 3.1886 data: 0.0083 max mem: 33370 +Epoch: [34] [ 490/1319] eta: 0:44:02 lr: 8.558885385369697e-06 loss: 0.0277 (0.0328) time: 3.1881 data: 0.0080 max mem: 33370 +Epoch: [34] [ 500/1319] eta: 0:43:31 lr: 8.548507484300866e-06 loss: 0.0287 (0.0327) time: 3.1954 data: 0.0083 max mem: 33370 +Epoch: [34] [ 510/1319] eta: 0:42:58 lr: 8.538128183177479e-06 loss: 0.0305 (0.0328) time: 3.1796 data: 0.0085 max mem: 33370 +Epoch: [34] [ 520/1319] eta: 0:42:26 lr: 8.527747479919078e-06 loss: 0.0353 (0.0329) time: 3.1508 data: 0.0077 max mem: 33370 +Epoch: [34] [ 530/1319] eta: 0:41:54 lr: 8.517365372439296e-06 loss: 0.0330 (0.0328) time: 3.1883 data: 0.0079 max mem: 33370 +Epoch: [34] [ 540/1319] eta: 0:41:21 lr: 8.506981858645828e-06 loss: 0.0266 (0.0328) time: 3.1642 data: 0.0081 max mem: 33370 +Epoch: [34] [ 550/1319] eta: 0:40:50 lr: 8.496596936440405e-06 loss: 0.0266 (0.0328) time: 3.1636 data: 0.0080 max mem: 33370 +Epoch: [34] [ 560/1319] eta: 0:40:17 lr: 8.486210603718787e-06 loss: 0.0256 (0.0327) time: 3.1762 data: 0.0080 max mem: 33370 +Epoch: [34] [ 570/1319] eta: 0:39:46 lr: 8.475822858370701e-06 loss: 0.0263 (0.0326) time: 3.1818 data: 0.0078 max mem: 33370 +Epoch: [34] [ 580/1319] eta: 0:39:13 lr: 8.465433698279856e-06 loss: 0.0278 (0.0326) time: 3.1791 data: 0.0080 max mem: 33370 +Epoch: [34] [ 590/1319] eta: 0:38:42 lr: 8.455043121323896e-06 loss: 0.0300 (0.0326) time: 3.1609 data: 0.0080 max mem: 33370 +Epoch: [34] [ 600/1319] eta: 0:38:09 lr: 8.444651125374376e-06 loss: 0.0304 (0.0326) time: 3.1562 data: 0.0082 max mem: 33370 +Epoch: [34] [ 610/1319] eta: 0:37:37 lr: 8.43425770829675e-06 loss: 0.0301 (0.0326) time: 3.1407 data: 0.0083 max mem: 33370 +Epoch: [34] [ 620/1319] eta: 0:37:05 lr: 8.423862867950307e-06 loss: 0.0293 (0.0326) time: 3.1510 data: 0.0078 max mem: 33370 +Epoch: [34] [ 630/1319] eta: 0:36:33 lr: 8.413466602188201e-06 loss: 0.0292 (0.0326) time: 3.1736 data: 0.0081 max mem: 33370 +Epoch: [34] [ 640/1319] eta: 0:36:01 lr: 8.403068908857377e-06 loss: 0.0272 (0.0326) time: 3.1798 data: 0.0091 max mem: 33370 +Epoch: [34] [ 650/1319] eta: 0:35:29 lr: 8.39266978579857e-06 loss: 0.0276 (0.0325) time: 3.1735 data: 0.0088 max mem: 33370 +Epoch: [34] [ 660/1319] eta: 0:34:57 lr: 8.382269230846276e-06 loss: 0.0314 (0.0325) time: 3.1598 data: 0.0078 max mem: 33370 +Epoch: [34] [ 670/1319] eta: 0:34:25 lr: 8.371867241828703e-06 loss: 0.0316 (0.0325) time: 3.1471 data: 0.0076 max mem: 33370 +Epoch: [34] [ 680/1319] eta: 0:33:53 lr: 8.361463816567778e-06 loss: 0.0299 (0.0325) time: 3.1605 data: 0.0081 max mem: 33370 +Epoch: [34] [ 690/1319] eta: 0:33:21 lr: 8.3510589528791e-06 loss: 0.0308 (0.0325) time: 3.1579 data: 0.0084 max mem: 33370 +Epoch: [34] [ 700/1319] eta: 0:32:49 lr: 8.340652648571916e-06 loss: 0.0300 (0.0325) time: 3.1685 data: 0.0081 max mem: 33370 +Epoch: [34] [ 710/1319] eta: 0:32:17 lr: 8.330244901449094e-06 loss: 0.0291 (0.0326) time: 3.1668 data: 0.0079 max mem: 33370 +Epoch: [34] [ 720/1319] eta: 0:31:45 lr: 8.319835709307101e-06 loss: 0.0296 (0.0326) time: 3.1728 data: 0.0080 max mem: 33370 +Epoch: [34] [ 730/1319] eta: 0:31:14 lr: 8.309425069935955e-06 loss: 0.0326 (0.0326) time: 3.2127 data: 0.0081 max mem: 33370 +Epoch: [34] [ 740/1319] eta: 0:30:42 lr: 8.299012981119228e-06 loss: 0.0287 (0.0326) time: 3.2165 data: 0.0082 max mem: 33370 +Epoch: [34] [ 750/1319] eta: 0:30:10 lr: 8.288599440633996e-06 loss: 0.0238 (0.0325) time: 3.1778 data: 0.0084 max mem: 33370 +Epoch: [34] [ 760/1319] eta: 0:29:38 lr: 8.278184446250822e-06 loss: 0.0256 (0.0325) time: 3.1757 data: 0.0081 max mem: 33370 +Epoch: [34] [ 770/1319] eta: 0:29:07 lr: 8.267767995733725e-06 loss: 0.0266 (0.0325) time: 3.2143 data: 0.0079 max mem: 33370 +Epoch: [34] [ 780/1319] eta: 0:28:35 lr: 8.25735008684013e-06 loss: 0.0304 (0.0325) time: 3.1891 data: 0.0082 max mem: 33370 +Epoch: [34] [ 790/1319] eta: 0:28:03 lr: 8.246930717320888e-06 loss: 0.0292 (0.0325) time: 3.1587 data: 0.0078 max mem: 33370 +Epoch: [34] [ 800/1319] eta: 0:27:31 lr: 8.236509884920197e-06 loss: 0.0296 (0.0325) time: 3.1602 data: 0.0075 max mem: 33370 +Epoch: [34] [ 810/1319] eta: 0:26:59 lr: 8.226087587375607e-06 loss: 0.0302 (0.0325) time: 3.1856 data: 0.0076 max mem: 33370 +Epoch: [34] [ 820/1319] eta: 0:26:27 lr: 8.215663822417979e-06 loss: 0.0311 (0.0325) time: 3.1819 data: 0.0078 max mem: 33370 +Epoch: [34] [ 830/1319] eta: 0:25:56 lr: 8.20523858777144e-06 loss: 0.0292 (0.0324) time: 3.1878 data: 0.0077 max mem: 33370 +Epoch: [34] [ 840/1319] eta: 0:25:24 lr: 8.194811881153384e-06 loss: 0.0292 (0.0324) time: 3.1938 data: 0.0073 max mem: 33370 +Epoch: [34] [ 850/1319] eta: 0:24:52 lr: 8.184383700274422e-06 loss: 0.0309 (0.0324) time: 3.1778 data: 0.0075 max mem: 33370 +Epoch: [34] [ 860/1319] eta: 0:24:20 lr: 8.173954042838362e-06 loss: 0.0321 (0.0324) time: 3.1782 data: 0.0076 max mem: 33370 +Epoch: [34] [ 870/1319] eta: 0:23:48 lr: 8.163522906542168e-06 loss: 0.0331 (0.0324) time: 3.1797 data: 0.0079 max mem: 33370 +Epoch: [34] [ 880/1319] eta: 0:23:17 lr: 8.153090289075947e-06 loss: 0.0298 (0.0324) time: 3.2167 data: 0.0078 max mem: 33370 +Epoch: [34] [ 890/1319] eta: 0:22:45 lr: 8.142656188122887e-06 loss: 0.0298 (0.0324) time: 3.2083 data: 0.0075 max mem: 33370 +Epoch: [34] [ 900/1319] eta: 0:22:13 lr: 8.132220601359272e-06 loss: 0.0303 (0.0324) time: 3.1974 data: 0.0077 max mem: 33370 +Epoch: [34] [ 910/1319] eta: 0:21:41 lr: 8.121783526454415e-06 loss: 0.0302 (0.0324) time: 3.2065 data: 0.0078 max mem: 33370 +Epoch: [34] [ 920/1319] eta: 0:21:10 lr: 8.111344961070641e-06 loss: 0.0298 (0.0324) time: 3.1936 data: 0.0076 max mem: 33370 +Epoch: [34] [ 930/1319] eta: 0:20:38 lr: 8.100904902863262e-06 loss: 0.0307 (0.0324) time: 3.1925 data: 0.0075 max mem: 33370 +Epoch: [34] [ 940/1319] eta: 0:20:06 lr: 8.090463349480519e-06 loss: 0.0296 (0.0324) time: 3.1841 data: 0.0076 max mem: 33370 +Epoch: [34] [ 950/1319] eta: 0:19:34 lr: 8.080020298563588e-06 loss: 0.0311 (0.0324) time: 3.1758 data: 0.0082 max mem: 33370 +Epoch: [34] [ 960/1319] eta: 0:19:02 lr: 8.069575747746527e-06 loss: 0.0317 (0.0323) time: 3.1663 data: 0.0082 max mem: 33370 +Epoch: [34] [ 970/1319] eta: 0:18:30 lr: 8.059129694656241e-06 loss: 0.0258 (0.0323) time: 3.1740 data: 0.0078 max mem: 33370 +Epoch: [34] [ 980/1319] eta: 0:17:58 lr: 8.048682136912463e-06 loss: 0.0251 (0.0323) time: 3.1815 data: 0.0078 max mem: 33370 +Epoch: [34] [ 990/1319] eta: 0:17:27 lr: 8.038233072127722e-06 loss: 0.0286 (0.0323) time: 3.1710 data: 0.0076 max mem: 33370 +Epoch: [34] [1000/1319] eta: 0:16:55 lr: 8.027782497907283e-06 loss: 0.0305 (0.0324) time: 3.1740 data: 0.0081 max mem: 33370 +Epoch: [34] [1010/1319] eta: 0:16:23 lr: 8.017330411849153e-06 loss: 0.0305 (0.0323) time: 3.1554 data: 0.0082 max mem: 33370 +Epoch: [34] [1020/1319] eta: 0:15:51 lr: 8.006876811544029e-06 loss: 0.0276 (0.0323) time: 3.2105 data: 0.0077 max mem: 33370 +Epoch: [34] [1030/1319] eta: 0:15:19 lr: 7.996421694575264e-06 loss: 0.0276 (0.0323) time: 3.2368 data: 0.0081 max mem: 33370 +Epoch: [34] [1040/1319] eta: 0:14:48 lr: 7.985965058518847e-06 loss: 0.0332 (0.0324) time: 3.1959 data: 0.0083 max mem: 33370 +Epoch: [34] [1050/1319] eta: 0:14:16 lr: 7.97550690094334e-06 loss: 0.0357 (0.0324) time: 3.1786 data: 0.0080 max mem: 33370 +Epoch: [34] [1060/1319] eta: 0:13:44 lr: 7.965047219409881e-06 loss: 0.0311 (0.0324) time: 3.1580 data: 0.0078 max mem: 33370 +Epoch: [34] [1070/1319] eta: 0:13:12 lr: 7.95458601147213e-06 loss: 0.0294 (0.0324) time: 3.1938 data: 0.0082 max mem: 33370 +Epoch: [34] [1080/1319] eta: 0:12:40 lr: 7.944123274676236e-06 loss: 0.0291 (0.0324) time: 3.2299 data: 0.0085 max mem: 33370 +Epoch: [34] [1090/1319] eta: 0:12:09 lr: 7.933659006560817e-06 loss: 0.0328 (0.0324) time: 3.1853 data: 0.0079 max mem: 33370 +Epoch: [34] [1100/1319] eta: 0:11:37 lr: 7.923193204656895e-06 loss: 0.0294 (0.0324) time: 3.1786 data: 0.0074 max mem: 33370 +Epoch: [34] [1110/1319] eta: 0:11:05 lr: 7.912725866487896e-06 loss: 0.0290 (0.0324) time: 3.1820 data: 0.0075 max mem: 33370 +Epoch: [34] [1120/1319] eta: 0:10:33 lr: 7.902256989569599e-06 loss: 0.0292 (0.0324) time: 3.1836 data: 0.0077 max mem: 33370 +Epoch: [34] [1130/1319] eta: 0:10:01 lr: 7.891786571410098e-06 loss: 0.0333 (0.0324) time: 3.1922 data: 0.0083 max mem: 33370 +Epoch: [34] [1140/1319] eta: 0:09:29 lr: 7.881314609509776e-06 loss: 0.0331 (0.0324) time: 3.1910 data: 0.0084 max mem: 33370 +Epoch: [34] [1150/1319] eta: 0:08:58 lr: 7.870841101361268e-06 loss: 0.0267 (0.0324) time: 3.1868 data: 0.0076 max mem: 33370 +Epoch: [34] [1160/1319] eta: 0:08:26 lr: 7.860366044449406e-06 loss: 0.0284 (0.0323) time: 3.1591 data: 0.0074 max mem: 33370 +Epoch: [34] [1170/1319] eta: 0:07:54 lr: 7.849889436251218e-06 loss: 0.0284 (0.0324) time: 3.1624 data: 0.0077 max mem: 33370 +Epoch: [34] [1180/1319] eta: 0:07:22 lr: 7.839411274235871e-06 loss: 0.0309 (0.0324) time: 3.1670 data: 0.0076 max mem: 33370 +Epoch: [34] [1190/1319] eta: 0:06:50 lr: 7.82893155586463e-06 loss: 0.0325 (0.0324) time: 3.1884 data: 0.0079 max mem: 33370 +Epoch: [34] [1200/1319] eta: 0:06:18 lr: 7.818450278590844e-06 loss: 0.0344 (0.0324) time: 3.1734 data: 0.0079 max mem: 33370 +Epoch: [34] [1210/1319] eta: 0:05:46 lr: 7.80796743985987e-06 loss: 0.0310 (0.0324) time: 3.1678 data: 0.0075 max mem: 33370 +Epoch: [34] [1220/1319] eta: 0:05:15 lr: 7.797483037109084e-06 loss: 0.0283 (0.0324) time: 3.1888 data: 0.0076 max mem: 33370 +Epoch: [34] [1230/1319] eta: 0:04:43 lr: 7.786997067767811e-06 loss: 0.0272 (0.0324) time: 3.2060 data: 0.0078 max mem: 33370 +Epoch: [34] [1240/1319] eta: 0:04:11 lr: 7.776509529257303e-06 loss: 0.0285 (0.0324) time: 3.2131 data: 0.0080 max mem: 33370 +Epoch: [34] [1250/1319] eta: 0:03:39 lr: 7.766020418990693e-06 loss: 0.0285 (0.0324) time: 3.1774 data: 0.0083 max mem: 33370 +Epoch: [34] [1260/1319] eta: 0:03:07 lr: 7.755529734372952e-06 loss: 0.0288 (0.0324) time: 3.1512 data: 0.0079 max mem: 33370 +Epoch: [34] [1270/1319] eta: 0:02:35 lr: 7.74503747280087e-06 loss: 0.0294 (0.0324) time: 3.1645 data: 0.0076 max mem: 33370 +Epoch: [34] [1280/1319] eta: 0:02:04 lr: 7.734543631663006e-06 loss: 0.0313 (0.0324) time: 3.1821 data: 0.0079 max mem: 33370 +Epoch: [34] [1290/1319] eta: 0:01:32 lr: 7.724048208339646e-06 loss: 0.0303 (0.0324) time: 3.1568 data: 0.0085 max mem: 33370 +Epoch: [34] [1300/1319] eta: 0:01:00 lr: 7.713551200202774e-06 loss: 0.0270 (0.0324) time: 3.1343 data: 0.0084 max mem: 33370 +Epoch: [34] [1310/1319] eta: 0:00:28 lr: 7.703052604616029e-06 loss: 0.0273 (0.0324) time: 3.1517 data: 0.0077 max mem: 33370 +Epoch: [34] Total time: 1:09:57 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 2:18:25 time: 3.2278 data: 3.1406 max mem: 33370 +Test: [ 100/2573] eta: 0:04:26 time: 0.0761 data: 0.0014 max mem: 33370 +Test: [ 200/2573] eta: 0:03:41 time: 0.0783 data: 0.0015 max mem: 33370 +Test: [ 300/2573] eta: 0:03:20 time: 0.0801 data: 0.0014 max mem: 33370 +Test: [ 400/2573] eta: 0:03:05 time: 0.0800 data: 0.0013 max mem: 33370 +Test: [ 500/2573] eta: 0:02:54 time: 0.0787 data: 0.0014 max mem: 33370 +Test: [ 600/2573] eta: 0:02:44 time: 0.0794 data: 0.0015 max mem: 33370 +Test: [ 700/2573] eta: 0:02:35 time: 0.0790 data: 0.0015 max mem: 33370 +Test: [ 800/2573] eta: 0:02:26 time: 0.0815 data: 0.0014 max mem: 33370 +Test: [ 900/2573] eta: 0:02:17 time: 0.0785 data: 0.0014 max mem: 33370 +Test: [1000/2573] eta: 0:02:09 time: 0.0788 data: 0.0014 max mem: 33370 +Test: [1100/2573] eta: 0:02:00 time: 0.0788 data: 0.0016 max mem: 33370 +Test: [1200/2573] eta: 0:01:52 time: 0.0800 data: 0.0015 max mem: 33370 +Test: [1300/2573] eta: 0:01:43 time: 0.0790 data: 0.0015 max mem: 33370 +Test: [1400/2573] eta: 0:01:35 time: 0.0776 data: 0.0014 max mem: 33370 +Test: [1500/2573] eta: 0:01:27 time: 0.0802 data: 0.0016 max mem: 33370 +Test: [1600/2573] eta: 0:01:18 time: 0.0822 data: 0.0015 max mem: 33370 +Test: [1700/2573] eta: 0:01:10 time: 0.0780 data: 0.0013 max mem: 33370 +Test: [1800/2573] eta: 0:01:02 time: 0.0809 data: 0.0015 max mem: 33370 +Test: [1900/2573] eta: 0:00:54 time: 0.0789 data: 0.0015 max mem: 33370 +Test: [2000/2573] eta: 0:00:46 time: 0.0795 data: 0.0015 max mem: 33370 +Test: [2100/2573] eta: 0:00:38 time: 0.0819 data: 0.0014 max mem: 33370 +Test: [2200/2573] eta: 0:00:30 time: 0.0805 data: 0.0014 max mem: 33370 +Test: [2300/2573] eta: 0:00:22 time: 0.0803 data: 0.0014 max mem: 33370 +Test: [2400/2573] eta: 0:00:13 time: 0.0766 data: 0.0015 max mem: 33370 +Test: [2500/2573] eta: 0:00:05 time: 0.0790 data: 0.0014 max mem: 33370 +Test: Total time: 0:03:27 +Final results: +Mean IoU is 65.08 + + precision@0.5 = 72.73 + precision@0.6 = 67.61 + precision@0.7 = 60.58 + precision@0.8 = 49.57 + precision@0.9 = 25.16 + overall IoU = 62.51 + +Average object IoU 65.08313009981173 +Overall IoU 62.50719451904297 +Better epoch: 34 + +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [35] [ 0/1319] eta: 1:54:55 lr: 7.693602509132593e-06 loss: 0.0577 (0.0577) time: 5.2276 data: 1.8490 max mem: 33370 +Epoch: [35] [ 10/1319] eta: 1:13:15 lr: 7.683100890097833e-06 loss: 0.0296 (0.0328) time: 3.3577 data: 0.1756 max mem: 33370 +Epoch: [35] [ 20/1319] eta: 1:10:58 lr: 7.67259767592017e-06 loss: 0.0282 (0.0320) time: 3.1810 data: 0.0080 max mem: 33370 +Epoch: [35] [ 30/1319] eta: 1:09:23 lr: 7.66209286393032e-06 loss: 0.0331 (0.0337) time: 3.1599 data: 0.0078 max mem: 33370 +Epoch: [35] [ 40/1319] eta: 1:08:38 lr: 7.651586451450453e-06 loss: 0.0326 (0.0332) time: 3.1593 data: 0.0082 max mem: 33370 +Epoch: [35] [ 50/1319] eta: 1:07:58 lr: 7.641078435794154e-06 loss: 0.0294 (0.0325) time: 3.1887 data: 0.0082 max mem: 33370 +Epoch: [35] [ 60/1319] eta: 1:07:26 lr: 7.630568814266394e-06 loss: 0.0274 (0.0321) time: 3.2011 data: 0.0078 max mem: 33370 +Epoch: [35] [ 70/1319] eta: 1:06:35 lr: 7.62005758416347e-06 loss: 0.0281 (0.0321) time: 3.1605 data: 0.0080 max mem: 33370 +Epoch: [35] [ 80/1319] eta: 1:06:01 lr: 7.609544742772985e-06 loss: 0.0294 (0.0318) time: 3.1451 data: 0.0079 max mem: 33370 +Epoch: [35] [ 90/1319] eta: 1:05:18 lr: 7.599030287373793e-06 loss: 0.0298 (0.0320) time: 3.1511 data: 0.0078 max mem: 33370 +Epoch: [35] [ 100/1319] eta: 1:04:47 lr: 7.588514215235963e-06 loss: 0.0268 (0.0315) time: 3.1581 data: 0.0081 max mem: 33370 +Epoch: [35] [ 110/1319] eta: 1:04:14 lr: 7.5779965236207366e-06 loss: 0.0256 (0.0313) time: 3.1892 data: 0.0083 max mem: 33370 +Epoch: [35] [ 120/1319] eta: 1:03:47 lr: 7.5674772097804864e-06 loss: 0.0274 (0.0314) time: 3.2073 data: 0.0083 max mem: 33370 +Epoch: [35] [ 130/1319] eta: 1:03:09 lr: 7.556956270958658e-06 loss: 0.0265 (0.0316) time: 3.1806 data: 0.0079 max mem: 33370 +Epoch: [35] [ 140/1319] eta: 1:02:32 lr: 7.546433704389756e-06 loss: 0.0255 (0.0314) time: 3.1273 data: 0.0077 max mem: 33370 +Epoch: [35] [ 150/1319] eta: 1:01:58 lr: 7.535909507299282e-06 loss: 0.0244 (0.0314) time: 3.1409 data: 0.0084 max mem: 33370 +Epoch: [35] [ 160/1319] eta: 1:01:23 lr: 7.525383676903694e-06 loss: 0.0285 (0.0313) time: 3.1471 data: 0.0085 max mem: 33370 +Epoch: [35] [ 170/1319] eta: 1:00:50 lr: 7.514856210410369e-06 loss: 0.0297 (0.0313) time: 3.1465 data: 0.0084 max mem: 33370 +Epoch: [35] [ 180/1319] eta: 1:00:22 lr: 7.504327105017539e-06 loss: 0.0296 (0.0312) time: 3.1963 data: 0.0083 max mem: 33370 +Epoch: [35] [ 190/1319] eta: 0:59:48 lr: 7.493796357914276e-06 loss: 0.0251 (0.0310) time: 3.1872 data: 0.0084 max mem: 33370 +Epoch: [35] [ 200/1319] eta: 0:59:18 lr: 7.483263966280434e-06 loss: 0.0254 (0.0309) time: 3.1722 data: 0.0083 max mem: 33370 +Epoch: [35] [ 210/1319] eta: 0:58:43 lr: 7.4727299272865964e-06 loss: 0.0304 (0.0311) time: 3.1680 data: 0.0082 max mem: 33370 +Epoch: [35] [ 220/1319] eta: 0:58:11 lr: 7.462194238094052e-06 loss: 0.0341 (0.0312) time: 3.1515 data: 0.0087 max mem: 33370 +Epoch: [35] [ 230/1319] eta: 0:57:42 lr: 7.4516568958547115e-06 loss: 0.0317 (0.0312) time: 3.2043 data: 0.0083 max mem: 33370 +Epoch: [35] [ 240/1319] eta: 0:57:10 lr: 7.4411178977111085e-06 loss: 0.0308 (0.0311) time: 3.2000 data: 0.0079 max mem: 33370 +Epoch: [35] [ 250/1319] eta: 0:56:37 lr: 7.430577240796325e-06 loss: 0.0289 (0.0311) time: 3.1661 data: 0.0080 max mem: 33370 +Epoch: [35] [ 260/1319] eta: 0:56:06 lr: 7.420034922233955e-06 loss: 0.0244 (0.0309) time: 3.1817 data: 0.0081 max mem: 33370 +Epoch: [35] [ 270/1319] eta: 0:55:35 lr: 7.4094909391380505e-06 loss: 0.0305 (0.0310) time: 3.1909 data: 0.0082 max mem: 33370 +Epoch: [35] [ 280/1319] eta: 0:55:04 lr: 7.398945288613088e-06 loss: 0.0305 (0.0309) time: 3.1913 data: 0.0088 max mem: 33370 +Epoch: [35] [ 290/1319] eta: 0:54:30 lr: 7.388397967753893e-06 loss: 0.0306 (0.0313) time: 3.1576 data: 0.0082 max mem: 33370 +Epoch: [35] [ 300/1319] eta: 0:54:00 lr: 7.3778489736456335e-06 loss: 0.0311 (0.0313) time: 3.1745 data: 0.0076 max mem: 33370 +Epoch: [35] [ 310/1319] eta: 0:53:27 lr: 7.367298303363743e-06 loss: 0.0311 (0.0315) time: 3.1956 data: 0.0079 max mem: 33370 +Epoch: [35] [ 320/1319] eta: 0:52:56 lr: 7.35674595397388e-06 loss: 0.0287 (0.0312) time: 3.1825 data: 0.0082 max mem: 33370 +Epoch: [35] [ 330/1319] eta: 0:52:24 lr: 7.34619192253189e-06 loss: 0.0248 (0.0311) time: 3.1862 data: 0.0083 max mem: 33370 +Epoch: [35] [ 340/1319] eta: 0:51:52 lr: 7.335636206083729e-06 loss: 0.0312 (0.0312) time: 3.1697 data: 0.0086 max mem: 33370 +Epoch: [35] [ 350/1319] eta: 0:51:20 lr: 7.325078801665445e-06 loss: 0.0325 (0.0313) time: 3.1678 data: 0.0087 max mem: 33370 +Epoch: [35] [ 360/1319] eta: 0:50:49 lr: 7.31451970630312e-06 loss: 0.0326 (0.0314) time: 3.1945 data: 0.0079 max mem: 33370 +Epoch: [35] [ 370/1319] eta: 0:50:18 lr: 7.303958917012809e-06 loss: 0.0308 (0.0314) time: 3.2168 data: 0.0080 max mem: 33370 +Epoch: [35] [ 380/1319] eta: 0:49:45 lr: 7.293396430800509e-06 loss: 0.0290 (0.0315) time: 3.1612 data: 0.0079 max mem: 33370 +Epoch: [35] [ 390/1319] eta: 0:49:13 lr: 7.282832244662077e-06 loss: 0.0307 (0.0315) time: 3.1496 data: 0.0074 max mem: 33370 +Epoch: [35] [ 400/1319] eta: 0:48:41 lr: 7.272266355583221e-06 loss: 0.0316 (0.0316) time: 3.1773 data: 0.0077 max mem: 33370 +Epoch: [35] [ 410/1319] eta: 0:48:10 lr: 7.261698760539424e-06 loss: 0.0296 (0.0316) time: 3.1836 data: 0.0080 max mem: 33370 +Epoch: [35] [ 420/1319] eta: 0:47:38 lr: 7.2511294564958895e-06 loss: 0.0296 (0.0316) time: 3.1929 data: 0.0080 max mem: 33370 +Epoch: [35] [ 430/1319] eta: 0:47:07 lr: 7.240558440407508e-06 loss: 0.0299 (0.0317) time: 3.1969 data: 0.0082 max mem: 33370 +Epoch: [35] [ 440/1319] eta: 0:46:34 lr: 7.229985709218795e-06 loss: 0.0288 (0.0317) time: 3.1734 data: 0.0079 max mem: 33370 +Epoch: [35] [ 450/1319] eta: 0:46:03 lr: 7.219411259863819e-06 loss: 0.0295 (0.0317) time: 3.1731 data: 0.0076 max mem: 33370 +Epoch: [35] [ 460/1319] eta: 0:45:31 lr: 7.208835089266191e-06 loss: 0.0298 (0.0317) time: 3.1780 data: 0.0075 max mem: 33370 +Epoch: [35] [ 470/1319] eta: 0:44:59 lr: 7.198257194338982e-06 loss: 0.0298 (0.0317) time: 3.1625 data: 0.0075 max mem: 33370 +Epoch: [35] [ 480/1319] eta: 0:44:27 lr: 7.187677571984675e-06 loss: 0.0322 (0.0317) time: 3.1676 data: 0.0080 max mem: 33370 +Epoch: [35] [ 490/1319] eta: 0:43:55 lr: 7.177096219095117e-06 loss: 0.0274 (0.0317) time: 3.1748 data: 0.0079 max mem: 33370 +Epoch: [35] [ 500/1319] eta: 0:43:23 lr: 7.166513132551446e-06 loss: 0.0278 (0.0317) time: 3.1867 data: 0.0074 max mem: 33370 +Epoch: [35] [ 510/1319] eta: 0:42:52 lr: 7.15592830922407e-06 loss: 0.0291 (0.0318) time: 3.1902 data: 0.0074 max mem: 33370 +Epoch: [35] [ 520/1319] eta: 0:42:20 lr: 7.145341745972588e-06 loss: 0.0297 (0.0318) time: 3.1783 data: 0.0083 max mem: 33370 +Epoch: [35] [ 530/1319] eta: 0:41:47 lr: 7.134753439645737e-06 loss: 0.0303 (0.0318) time: 3.1536 data: 0.0084 max mem: 33370 +Epoch: [35] [ 540/1319] eta: 0:41:16 lr: 7.124163387081344e-06 loss: 0.0300 (0.0317) time: 3.1598 data: 0.0079 max mem: 33370 +Epoch: [35] [ 550/1319] eta: 0:40:43 lr: 7.1135715851062684e-06 loss: 0.0300 (0.0318) time: 3.1601 data: 0.0078 max mem: 33370 +Epoch: [35] [ 560/1319] eta: 0:40:12 lr: 7.102978030536328e-06 loss: 0.0304 (0.0319) time: 3.1783 data: 0.0076 max mem: 33370 +Epoch: [35] [ 570/1319] eta: 0:39:40 lr: 7.092382720176277e-06 loss: 0.0299 (0.0319) time: 3.1964 data: 0.0081 max mem: 33370 +Epoch: [35] [ 580/1319] eta: 0:39:08 lr: 7.081785650819721e-06 loss: 0.0314 (0.0319) time: 3.1663 data: 0.0083 max mem: 33370 +Epoch: [35] [ 590/1319] eta: 0:38:37 lr: 7.071186819249069e-06 loss: 0.0301 (0.0318) time: 3.1742 data: 0.0082 max mem: 33370 +Epoch: [35] [ 600/1319] eta: 0:38:05 lr: 7.060586222235484e-06 loss: 0.0283 (0.0319) time: 3.2086 data: 0.0083 max mem: 33370 +Epoch: [35] [ 610/1319] eta: 0:37:33 lr: 7.049983856538794e-06 loss: 0.0309 (0.0319) time: 3.1746 data: 0.0085 max mem: 33370 +Epoch: [35] [ 620/1319] eta: 0:37:02 lr: 7.039379718907476e-06 loss: 0.0284 (0.0318) time: 3.1948 data: 0.0081 max mem: 33370 +Epoch: [35] [ 630/1319] eta: 0:36:30 lr: 7.0287738060785644e-06 loss: 0.0300 (0.0318) time: 3.2300 data: 0.0082 max mem: 33370 +Epoch: [35] [ 640/1319] eta: 0:35:59 lr: 7.018166114777613e-06 loss: 0.0296 (0.0318) time: 3.1889 data: 0.0086 max mem: 33370 +Epoch: [35] [ 650/1319] eta: 0:35:26 lr: 7.007556641718624e-06 loss: 0.0277 (0.0318) time: 3.1547 data: 0.0087 max mem: 33370 +Epoch: [35] [ 660/1319] eta: 0:34:54 lr: 6.9969453836039725e-06 loss: 0.0302 (0.0318) time: 3.1436 data: 0.0090 max mem: 33370 +Epoch: [35] [ 670/1319] eta: 0:34:22 lr: 6.986332337124384e-06 loss: 0.0302 (0.0317) time: 3.1552 data: 0.0084 max mem: 33370 +Epoch: [35] [ 680/1319] eta: 0:33:50 lr: 6.975717498958839e-06 loss: 0.0311 (0.0317) time: 3.1553 data: 0.0081 max mem: 33370 +Epoch: [35] [ 690/1319] eta: 0:33:18 lr: 6.965100865774533e-06 loss: 0.0315 (0.0318) time: 3.1602 data: 0.0086 max mem: 33370 +Epoch: [35] [ 700/1319] eta: 0:32:47 lr: 6.954482434226801e-06 loss: 0.0299 (0.0317) time: 3.1843 data: 0.0085 max mem: 33370 +Epoch: [35] [ 710/1319] eta: 0:32:15 lr: 6.9438622009590656e-06 loss: 0.0275 (0.0318) time: 3.1893 data: 0.0087 max mem: 33370 +Epoch: [35] [ 720/1319] eta: 0:31:43 lr: 6.933240162602753e-06 loss: 0.0281 (0.0317) time: 3.1581 data: 0.0086 max mem: 33370 +Epoch: [35] [ 730/1319] eta: 0:31:11 lr: 6.922616315777261e-06 loss: 0.0271 (0.0317) time: 3.1706 data: 0.0080 max mem: 33370 +Epoch: [35] [ 740/1319] eta: 0:30:39 lr: 6.911990657089877e-06 loss: 0.0296 (0.0317) time: 3.1786 data: 0.0082 max mem: 33370 +Epoch: [35] [ 750/1319] eta: 0:30:07 lr: 6.901363183135715e-06 loss: 0.0313 (0.0316) time: 3.1519 data: 0.0084 max mem: 33370 +Epoch: [35] [ 760/1319] eta: 0:29:36 lr: 6.890733890497658e-06 loss: 0.0315 (0.0317) time: 3.1688 data: 0.0081 max mem: 33370 +Epoch: [35] [ 770/1319] eta: 0:29:04 lr: 6.880102775746271e-06 loss: 0.0325 (0.0317) time: 3.1780 data: 0.0084 max mem: 33370 +Epoch: [35] [ 780/1319] eta: 0:28:32 lr: 6.869469835439768e-06 loss: 0.0309 (0.0317) time: 3.1615 data: 0.0084 max mem: 33370 +Epoch: [35] [ 790/1319] eta: 0:28:00 lr: 6.858835066123928e-06 loss: 0.0295 (0.0316) time: 3.1647 data: 0.0081 max mem: 33370 +Epoch: [35] [ 800/1319] eta: 0:27:29 lr: 6.848198464332027e-06 loss: 0.0295 (0.0316) time: 3.1867 data: 0.0084 max mem: 33370 +Epoch: [35] [ 810/1319] eta: 0:26:57 lr: 6.837560026584784e-06 loss: 0.0273 (0.0316) time: 3.2051 data: 0.0083 max mem: 33370 +Epoch: [35] [ 820/1319] eta: 0:26:25 lr: 6.826919749390266e-06 loss: 0.0295 (0.0317) time: 3.1940 data: 0.0084 max mem: 33370 +Epoch: [35] [ 830/1319] eta: 0:25:53 lr: 6.816277629243854e-06 loss: 0.0317 (0.0317) time: 3.1582 data: 0.0085 max mem: 33370 +Epoch: [35] [ 840/1319] eta: 0:25:21 lr: 6.805633662628158e-06 loss: 0.0290 (0.0318) time: 3.1607 data: 0.0085 max mem: 33370 +Epoch: [35] [ 850/1319] eta: 0:24:50 lr: 6.794987846012945e-06 loss: 0.0300 (0.0318) time: 3.1734 data: 0.0082 max mem: 33370 +Epoch: [35] [ 860/1319] eta: 0:24:18 lr: 6.784340175855078e-06 loss: 0.0287 (0.0318) time: 3.1781 data: 0.0079 max mem: 33370 +Epoch: [35] [ 870/1319] eta: 0:23:46 lr: 6.7736906485984466e-06 loss: 0.0258 (0.0317) time: 3.1892 data: 0.0084 max mem: 33370 +Epoch: [35] [ 880/1319] eta: 0:23:14 lr: 6.763039260673876e-06 loss: 0.0249 (0.0317) time: 3.1629 data: 0.0087 max mem: 33370 +Epoch: [35] [ 890/1319] eta: 0:22:43 lr: 6.752386008499089e-06 loss: 0.0274 (0.0316) time: 3.1693 data: 0.0084 max mem: 33370 +Epoch: [35] [ 900/1319] eta: 0:22:11 lr: 6.741730888478615e-06 loss: 0.0312 (0.0317) time: 3.1730 data: 0.0086 max mem: 33370 +Epoch: [35] [ 910/1319] eta: 0:21:39 lr: 6.7310738970037205e-06 loss: 0.0323 (0.0317) time: 3.1525 data: 0.0083 max mem: 33370 +Epoch: [35] [ 920/1319] eta: 0:21:07 lr: 6.7204150304523424e-06 loss: 0.0293 (0.0317) time: 3.1381 data: 0.0080 max mem: 33370 +Epoch: [35] [ 930/1319] eta: 0:20:35 lr: 6.709754285188997e-06 loss: 0.0311 (0.0317) time: 3.1646 data: 0.0081 max mem: 33370 +Epoch: [35] [ 940/1319] eta: 0:20:03 lr: 6.699091657564736e-06 loss: 0.0366 (0.0318) time: 3.1785 data: 0.0083 max mem: 33370 +Epoch: [35] [ 950/1319] eta: 0:19:32 lr: 6.688427143917049e-06 loss: 0.0315 (0.0318) time: 3.1742 data: 0.0085 max mem: 33370 +Epoch: [35] [ 960/1319] eta: 0:19:00 lr: 6.677760740569799e-06 loss: 0.0270 (0.0317) time: 3.1828 data: 0.0087 max mem: 33370 +Epoch: [35] [ 970/1319] eta: 0:18:28 lr: 6.667092443833153e-06 loss: 0.0296 (0.0318) time: 3.1993 data: 0.0086 max mem: 33370 +Epoch: [35] [ 980/1319] eta: 0:17:56 lr: 6.656422250003478e-06 loss: 0.0327 (0.0318) time: 3.1949 data: 0.0078 max mem: 33370 +Epoch: [35] [ 990/1319] eta: 0:17:24 lr: 6.645750155363307e-06 loss: 0.0294 (0.0318) time: 3.1402 data: 0.0077 max mem: 33370 +Epoch: [35] [1000/1319] eta: 0:16:53 lr: 6.635076156181232e-06 loss: 0.0274 (0.0317) time: 3.1358 data: 0.0079 max mem: 33370 +Epoch: [35] [1010/1319] eta: 0:16:21 lr: 6.624400248711836e-06 loss: 0.0297 (0.0318) time: 3.1651 data: 0.0079 max mem: 33370 +Epoch: [35] [1020/1319] eta: 0:15:49 lr: 6.613722429195618e-06 loss: 0.0292 (0.0317) time: 3.1757 data: 0.0080 max mem: 33370 +Epoch: [35] [1030/1319] eta: 0:15:17 lr: 6.603042693858916e-06 loss: 0.0310 (0.0318) time: 3.1829 data: 0.0081 max mem: 33370 +Epoch: [35] [1040/1319] eta: 0:14:46 lr: 6.5923610389138055e-06 loss: 0.0310 (0.0318) time: 3.1865 data: 0.0085 max mem: 33370 +Epoch: [35] [1050/1319] eta: 0:14:14 lr: 6.581677460558057e-06 loss: 0.0267 (0.0317) time: 3.1830 data: 0.0087 max mem: 33370 +Epoch: [35] [1060/1319] eta: 0:13:42 lr: 6.570991954975031e-06 loss: 0.0271 (0.0318) time: 3.1824 data: 0.0084 max mem: 33370 +Epoch: [35] [1070/1319] eta: 0:13:11 lr: 6.560304518333606e-06 loss: 0.0306 (0.0318) time: 3.2121 data: 0.0083 max mem: 33370 +Epoch: [35] [1080/1319] eta: 0:12:39 lr: 6.549615146788095e-06 loss: 0.0340 (0.0318) time: 3.2126 data: 0.0082 max mem: 33370 +Epoch: [35] [1090/1319] eta: 0:12:07 lr: 6.538923836478152e-06 loss: 0.0315 (0.0318) time: 3.1733 data: 0.0079 max mem: 33370 +Epoch: [35] [1100/1319] eta: 0:11:35 lr: 6.528230583528713e-06 loss: 0.0274 (0.0318) time: 3.1548 data: 0.0078 max mem: 33370 +Epoch: [35] [1110/1319] eta: 0:11:03 lr: 6.5175353840499016e-06 loss: 0.0287 (0.0318) time: 3.1730 data: 0.0078 max mem: 33370 +Epoch: [35] [1120/1319] eta: 0:10:32 lr: 6.506838234136938e-06 loss: 0.0307 (0.0318) time: 3.2032 data: 0.0077 max mem: 33370 +Epoch: [35] [1130/1319] eta: 0:10:00 lr: 6.4961391298700616e-06 loss: 0.0290 (0.0318) time: 3.2129 data: 0.0078 max mem: 33370 +Epoch: [35] [1140/1319] eta: 0:09:28 lr: 6.485438067314456e-06 loss: 0.0289 (0.0318) time: 3.2044 data: 0.0080 max mem: 33370 +Epoch: [35] [1150/1319] eta: 0:08:56 lr: 6.4747350425201315e-06 loss: 0.0298 (0.0318) time: 3.1670 data: 0.0077 max mem: 33370 +Epoch: [35] [1160/1319] eta: 0:08:25 lr: 6.464030051521878e-06 loss: 0.0282 (0.0318) time: 3.1716 data: 0.0074 max mem: 33370 +Epoch: [35] [1170/1319] eta: 0:07:53 lr: 6.453323090339156e-06 loss: 0.0281 (0.0317) time: 3.1908 data: 0.0077 max mem: 33370 +Epoch: [35] [1180/1319] eta: 0:07:21 lr: 6.442614154976011e-06 loss: 0.0266 (0.0317) time: 3.1697 data: 0.0083 max mem: 33370 +Epoch: [35] [1190/1319] eta: 0:06:49 lr: 6.431903241420996e-06 loss: 0.0274 (0.0317) time: 3.1805 data: 0.0080 max mem: 33370 +Epoch: [35] [1200/1319] eta: 0:06:18 lr: 6.4211903456470515e-06 loss: 0.0271 (0.0316) time: 3.1759 data: 0.0076 max mem: 33370 +Epoch: [35] [1210/1319] eta: 0:05:46 lr: 6.410475463611462e-06 loss: 0.0298 (0.0316) time: 3.1559 data: 0.0076 max mem: 33370 +Epoch: [35] [1220/1319] eta: 0:05:14 lr: 6.399758591255733e-06 loss: 0.0325 (0.0317) time: 3.1417 data: 0.0078 max mem: 33370 +Epoch: [35] [1230/1319] eta: 0:04:42 lr: 6.389039724505507e-06 loss: 0.0279 (0.0317) time: 3.1475 data: 0.0079 max mem: 33370 +Epoch: [35] [1240/1319] eta: 0:04:10 lr: 6.378318859270487e-06 loss: 0.0289 (0.0317) time: 3.1867 data: 0.0082 max mem: 33370 +Epoch: [35] [1250/1319] eta: 0:03:39 lr: 6.3675959914443046e-06 loss: 0.0302 (0.0317) time: 3.1910 data: 0.0080 max mem: 33370 +Epoch: [35] [1260/1319] eta: 0:03:07 lr: 6.356871116904475e-06 loss: 0.0305 (0.0317) time: 3.1717 data: 0.0079 max mem: 33370 +Epoch: [35] [1270/1319] eta: 0:02:35 lr: 6.34614423151228e-06 loss: 0.0305 (0.0317) time: 3.1905 data: 0.0086 max mem: 33370 +Epoch: [35] [1280/1319] eta: 0:02:03 lr: 6.335415331112665e-06 loss: 0.0287 (0.0317) time: 3.2169 data: 0.0082 max mem: 33370 +Epoch: [35] [1290/1319] eta: 0:01:32 lr: 6.324684411534165e-06 loss: 0.0301 (0.0317) time: 3.1835 data: 0.0077 max mem: 33370 +Epoch: [35] [1300/1319] eta: 0:01:00 lr: 6.313951468588795e-06 loss: 0.0290 (0.0317) time: 3.1816 data: 0.0081 max mem: 33370 +Epoch: [35] [1310/1319] eta: 0:00:28 lr: 6.3032164980719415e-06 loss: 0.0290 (0.0317) time: 3.1842 data: 0.0078 max mem: 33370 +Epoch: [35] Total time: 1:09:51 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 2:17:01 time: 3.1952 data: 3.0950 max mem: 33370 +Test: [ 100/2573] eta: 0:04:26 time: 0.0772 data: 0.0014 max mem: 33370 +Test: [ 200/2573] eta: 0:03:42 time: 0.0788 data: 0.0014 max mem: 33370 +Test: [ 300/2573] eta: 0:03:20 time: 0.0797 data: 0.0014 max mem: 33370 +Test: [ 400/2573] eta: 0:03:06 time: 0.0798 data: 0.0014 max mem: 33370 +Test: [ 500/2573] eta: 0:02:54 time: 0.0782 data: 0.0014 max mem: 33370 +Test: [ 600/2573] eta: 0:02:44 time: 0.0782 data: 0.0014 max mem: 33370 +Test: [ 700/2573] eta: 0:02:35 time: 0.0788 data: 0.0015 max mem: 33370 +Test: [ 800/2573] eta: 0:02:26 time: 0.0821 data: 0.0014 max mem: 33370 +Test: [ 900/2573] eta: 0:02:17 time: 0.0797 data: 0.0016 max mem: 33370 +Test: [1000/2573] eta: 0:02:09 time: 0.0785 data: 0.0015 max mem: 33370 +Test: [1100/2573] eta: 0:02:00 time: 0.0809 data: 0.0015 max mem: 33370 +Test: [1200/2573] eta: 0:01:52 time: 0.0786 data: 0.0014 max mem: 33370 +Test: [1300/2573] eta: 0:01:43 time: 0.0792 data: 0.0014 max mem: 33370 +Test: [1400/2573] eta: 0:01:35 time: 0.0782 data: 0.0015 max mem: 33370 +Test: [1500/2573] eta: 0:01:27 time: 0.0790 data: 0.0014 max mem: 33370 +Test: [1600/2573] eta: 0:01:19 time: 0.0822 data: 0.0015 max mem: 33370 +Test: [1700/2573] eta: 0:01:10 time: 0.0776 data: 0.0016 max mem: 33370 +Test: [1800/2573] eta: 0:01:02 time: 0.0804 data: 0.0014 max mem: 33370 +Test: [1900/2573] eta: 0:00:54 time: 0.0768 data: 0.0014 max mem: 33370 +Test: [2000/2573] eta: 0:00:46 time: 0.0786 data: 0.0014 max mem: 33370 +Test: [2100/2573] eta: 0:00:38 time: 0.0815 data: 0.0013 max mem: 33370 +Test: [2200/2573] eta: 0:00:30 time: 0.0811 data: 0.0014 max mem: 33370 +Test: [2300/2573] eta: 0:00:21 time: 0.0805 data: 0.0014 max mem: 33370 +Test: [2400/2573] eta: 0:00:13 time: 0.0760 data: 0.0015 max mem: 33370 +Test: [2500/2573] eta: 0:00:05 time: 0.0794 data: 0.0014 max mem: 33370 +Test: Total time: 0:03:27 +Final results: +Mean IoU is 65.14 + + precision@0.5 = 72.79 + precision@0.6 = 67.63 + precision@0.7 = 60.87 + precision@0.8 = 49.37 + precision@0.9 = 25.18 + overall IoU = 62.49 + +Average object IoU 65.13769266514855 +Overall IoU 62.49211502075195 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [36] [ 0/1319] eta: 2:46:05 lr: 6.293553287544593e-06 loss: 0.0294 (0.0294) time: 7.5551 data: 2.2993 max mem: 33370 +Epoch: [36] [ 10/1319] eta: 1:18:23 lr: 6.282814452998321e-06 loss: 0.0294 (0.0318) time: 3.5931 data: 0.2169 max mem: 33370 +Epoch: [36] [ 20/1319] eta: 1:13:49 lr: 6.2720735785923675e-06 loss: 0.0321 (0.0322) time: 3.2031 data: 0.0081 max mem: 33370 +Epoch: [36] [ 30/1319] eta: 1:11:52 lr: 6.261330660056396e-06 loss: 0.0321 (0.0313) time: 3.2098 data: 0.0081 max mem: 33370 +Epoch: [36] [ 40/1319] eta: 1:10:26 lr: 6.250585693102968e-06 loss: 0.0305 (0.0323) time: 3.1941 data: 0.0083 max mem: 33370 +Epoch: [36] [ 50/1319] eta: 1:09:21 lr: 6.2398386734274585e-06 loss: 0.0325 (0.0324) time: 3.1768 data: 0.0082 max mem: 33370 +Epoch: [36] [ 60/1319] eta: 1:08:16 lr: 6.229089596707912e-06 loss: 0.0289 (0.0318) time: 3.1499 data: 0.0082 max mem: 33370 +Epoch: [36] [ 70/1319] eta: 1:07:30 lr: 6.218338458604991e-06 loss: 0.0275 (0.0314) time: 3.1500 data: 0.0082 max mem: 33370 +Epoch: [36] [ 80/1319] eta: 1:06:43 lr: 6.207585254761843e-06 loss: 0.0286 (0.0319) time: 3.1607 data: 0.0082 max mem: 33370 +Epoch: [36] [ 90/1319] eta: 1:06:02 lr: 6.196829980804001e-06 loss: 0.0352 (0.0322) time: 3.1559 data: 0.0082 max mem: 33370 +Epoch: [36] [ 100/1319] eta: 1:05:30 lr: 6.1860726323392754e-06 loss: 0.0330 (0.0321) time: 3.1983 data: 0.0081 max mem: 33370 +Epoch: [36] [ 110/1319] eta: 1:04:52 lr: 6.175313204957665e-06 loss: 0.0313 (0.0322) time: 3.1995 data: 0.0080 max mem: 33370 +Epoch: [36] [ 120/1319] eta: 1:04:13 lr: 6.164551694231212e-06 loss: 0.0344 (0.0329) time: 3.1615 data: 0.0080 max mem: 33370 +Epoch: [36] [ 130/1319] eta: 1:03:35 lr: 6.153788095713938e-06 loss: 0.0348 (0.0333) time: 3.1527 data: 0.0077 max mem: 33370 +Epoch: [36] [ 140/1319] eta: 1:03:03 lr: 6.143022404941713e-06 loss: 0.0340 (0.0330) time: 3.1774 data: 0.0082 max mem: 33370 +Epoch: [36] [ 150/1319] eta: 1:02:29 lr: 6.132254617432146e-06 loss: 0.0281 (0.0331) time: 3.1973 data: 0.0089 max mem: 33370 +Epoch: [36] [ 160/1319] eta: 1:01:54 lr: 6.121484728684484e-06 loss: 0.0295 (0.0330) time: 3.1798 data: 0.0085 max mem: 33370 +Epoch: [36] [ 170/1319] eta: 1:01:20 lr: 6.110712734179475e-06 loss: 0.0297 (0.0330) time: 3.1711 data: 0.0081 max mem: 33370 +Epoch: [36] [ 180/1319] eta: 1:00:45 lr: 6.099938629379293e-06 loss: 0.0279 (0.0328) time: 3.1658 data: 0.0081 max mem: 33370 +Epoch: [36] [ 190/1319] eta: 1:00:10 lr: 6.0891624097274035e-06 loss: 0.0271 (0.0327) time: 3.1543 data: 0.0080 max mem: 33370 +Epoch: [36] [ 200/1319] eta: 0:59:40 lr: 6.07838407064845e-06 loss: 0.0291 (0.0329) time: 3.1876 data: 0.0080 max mem: 33370 +Epoch: [36] [ 210/1319] eta: 0:59:07 lr: 6.067603607548146e-06 loss: 0.0302 (0.0325) time: 3.2058 data: 0.0079 max mem: 33370 +Epoch: [36] [ 220/1319] eta: 0:58:34 lr: 6.05682101581314e-06 loss: 0.0306 (0.0327) time: 3.1848 data: 0.0084 max mem: 33370 +Epoch: [36] [ 230/1319] eta: 0:58:02 lr: 6.0460362908109285e-06 loss: 0.0307 (0.0326) time: 3.1864 data: 0.0088 max mem: 33370 +Epoch: [36] [ 240/1319] eta: 0:57:32 lr: 6.035249427889721e-06 loss: 0.0288 (0.0325) time: 3.2128 data: 0.0082 max mem: 33370 +Epoch: [36] [ 250/1319] eta: 0:57:00 lr: 6.024460422378318e-06 loss: 0.0288 (0.0324) time: 3.2213 data: 0.0079 max mem: 33370 +Epoch: [36] [ 260/1319] eta: 0:56:28 lr: 6.013669269586002e-06 loss: 0.0281 (0.0322) time: 3.2049 data: 0.0078 max mem: 33370 +Epoch: [36] [ 270/1319] eta: 0:55:57 lr: 6.002875964802412e-06 loss: 0.0275 (0.0321) time: 3.2179 data: 0.0080 max mem: 33370 +Epoch: [36] [ 280/1319] eta: 0:55:24 lr: 5.992080503297408e-06 loss: 0.0288 (0.0322) time: 3.1957 data: 0.0080 max mem: 33370 +Epoch: [36] [ 290/1319] eta: 0:54:51 lr: 5.981282880320978e-06 loss: 0.0288 (0.0321) time: 3.1685 data: 0.0081 max mem: 33370 +Epoch: [36] [ 300/1319] eta: 0:54:19 lr: 5.97048309110309e-06 loss: 0.0299 (0.0322) time: 3.1801 data: 0.0084 max mem: 33370 +Epoch: [36] [ 310/1319] eta: 0:53:48 lr: 5.959681130853577e-06 loss: 0.0269 (0.0319) time: 3.2064 data: 0.0084 max mem: 33370 +Epoch: [36] [ 320/1319] eta: 0:53:17 lr: 5.948876994762015e-06 loss: 0.0244 (0.0318) time: 3.2314 data: 0.0083 max mem: 33370 +Epoch: [36] [ 330/1319] eta: 0:52:44 lr: 5.938070677997572e-06 loss: 0.0244 (0.0318) time: 3.2092 data: 0.0085 max mem: 33370 +Epoch: [36] [ 340/1319] eta: 0:52:10 lr: 5.927262175708919e-06 loss: 0.0308 (0.0320) time: 3.1575 data: 0.0085 max mem: 33370 +Epoch: [36] [ 350/1319] eta: 0:51:38 lr: 5.916451483024071e-06 loss: 0.0309 (0.0321) time: 3.1536 data: 0.0079 max mem: 33370 +Epoch: [36] [ 360/1319] eta: 0:51:06 lr: 5.905638595050271e-06 loss: 0.0318 (0.0321) time: 3.1909 data: 0.0079 max mem: 33370 +Epoch: [36] [ 370/1319] eta: 0:50:32 lr: 5.894823506873858e-06 loss: 0.0318 (0.0321) time: 3.1689 data: 0.0083 max mem: 33370 +Epoch: [36] [ 380/1319] eta: 0:50:01 lr: 5.884006213560114e-06 loss: 0.0304 (0.0321) time: 3.1862 data: 0.0084 max mem: 33370 +Epoch: [36] [ 390/1319] eta: 0:49:28 lr: 5.873186710153169e-06 loss: 0.0312 (0.0321) time: 3.1810 data: 0.0088 max mem: 33370 +Epoch: [36] [ 400/1319] eta: 0:48:56 lr: 5.862364991675836e-06 loss: 0.0295 (0.0321) time: 3.1635 data: 0.0090 max mem: 33370 +Epoch: [36] [ 410/1319] eta: 0:48:24 lr: 5.85154105312949e-06 loss: 0.0269 (0.0320) time: 3.1994 data: 0.0091 max mem: 33370 +Epoch: [36] [ 420/1319] eta: 0:47:52 lr: 5.840714889493923e-06 loss: 0.0264 (0.0320) time: 3.2024 data: 0.0092 max mem: 33370 +Epoch: [36] [ 430/1319] eta: 0:47:20 lr: 5.829886495727219e-06 loss: 0.0258 (0.0321) time: 3.1917 data: 0.0085 max mem: 33370 +Epoch: [36] [ 440/1319] eta: 0:46:48 lr: 5.819055866765587e-06 loss: 0.0299 (0.0321) time: 3.1792 data: 0.0082 max mem: 33370 +Epoch: [36] [ 450/1319] eta: 0:46:17 lr: 5.808222997523256e-06 loss: 0.0303 (0.0320) time: 3.2162 data: 0.0084 max mem: 33370 +Epoch: [36] [ 460/1319] eta: 0:45:44 lr: 5.797387882892317e-06 loss: 0.0294 (0.0319) time: 3.1963 data: 0.0086 max mem: 33370 +Epoch: [36] [ 470/1319] eta: 0:45:12 lr: 5.786550517742576e-06 loss: 0.0285 (0.0319) time: 3.1580 data: 0.0083 max mem: 33370 +Epoch: [36] [ 480/1319] eta: 0:44:39 lr: 5.775710896921423e-06 loss: 0.0257 (0.0318) time: 3.1771 data: 0.0080 max mem: 33370 +Epoch: [36] [ 490/1319] eta: 0:44:07 lr: 5.764869015253661e-06 loss: 0.0284 (0.0319) time: 3.1818 data: 0.0078 max mem: 33370 +Epoch: [36] [ 500/1319] eta: 0:43:35 lr: 5.7540248675414e-06 loss: 0.0288 (0.0318) time: 3.1659 data: 0.0079 max mem: 33370 +Epoch: [36] [ 510/1319] eta: 0:43:01 lr: 5.743178448563874e-06 loss: 0.0286 (0.0319) time: 3.1298 data: 0.0081 max mem: 33370 +Epoch: [36] [ 520/1319] eta: 0:42:29 lr: 5.732329753077314e-06 loss: 0.0287 (0.0319) time: 3.1380 data: 0.0080 max mem: 33370 +Epoch: [36] [ 530/1319] eta: 0:41:57 lr: 5.7214787758147914e-06 loss: 0.0294 (0.0319) time: 3.1673 data: 0.0078 max mem: 33370 +Epoch: [36] [ 540/1319] eta: 0:41:25 lr: 5.710625511486047e-06 loss: 0.0322 (0.0319) time: 3.1787 data: 0.0080 max mem: 33370 +Epoch: [36] [ 550/1319] eta: 0:40:53 lr: 5.6997699547773765e-06 loss: 0.0296 (0.0319) time: 3.1763 data: 0.0081 max mem: 33370 +Epoch: [36] [ 560/1319] eta: 0:40:21 lr: 5.68891210035145e-06 loss: 0.0256 (0.0318) time: 3.1724 data: 0.0082 max mem: 33370 +Epoch: [36] [ 570/1319] eta: 0:39:49 lr: 5.678051942847162e-06 loss: 0.0309 (0.0319) time: 3.1902 data: 0.0081 max mem: 33370 +Epoch: [36] [ 580/1319] eta: 0:39:17 lr: 5.667189476879478e-06 loss: 0.0334 (0.0320) time: 3.2126 data: 0.0079 max mem: 33370 +Epoch: [36] [ 590/1319] eta: 0:38:45 lr: 5.656324697039277e-06 loss: 0.0329 (0.0320) time: 3.2010 data: 0.0082 max mem: 33370 +Epoch: [36] [ 600/1319] eta: 0:38:14 lr: 5.645457597893177e-06 loss: 0.0298 (0.0320) time: 3.1900 data: 0.0078 max mem: 33370 +Epoch: [36] [ 610/1319] eta: 0:37:42 lr: 5.634588173983401e-06 loss: 0.0281 (0.0320) time: 3.1939 data: 0.0077 max mem: 33370 +Epoch: [36] [ 620/1319] eta: 0:37:10 lr: 5.623716419827592e-06 loss: 0.0266 (0.0319) time: 3.1834 data: 0.0080 max mem: 33370 +Epoch: [36] [ 630/1319] eta: 0:36:38 lr: 5.612842329918665e-06 loss: 0.0258 (0.0318) time: 3.1988 data: 0.0080 max mem: 33370 +Epoch: [36] [ 640/1319] eta: 0:36:05 lr: 5.6019658987246355e-06 loss: 0.0290 (0.0318) time: 3.1528 data: 0.0080 max mem: 33370 +Epoch: [36] [ 650/1319] eta: 0:35:33 lr: 5.591087120688435e-06 loss: 0.0314 (0.0318) time: 3.1321 data: 0.0082 max mem: 33370 +Epoch: [36] [ 660/1319] eta: 0:35:01 lr: 5.5802059902277785e-06 loss: 0.0306 (0.0318) time: 3.2008 data: 0.0080 max mem: 33370 +Epoch: [36] [ 670/1319] eta: 0:34:30 lr: 5.569322501734972e-06 loss: 0.0306 (0.0318) time: 3.2156 data: 0.0077 max mem: 33370 +Epoch: [36] [ 680/1319] eta: 0:33:58 lr: 5.5584366495767425e-06 loss: 0.0299 (0.0318) time: 3.1977 data: 0.0076 max mem: 33370 +Epoch: [36] [ 690/1319] eta: 0:33:26 lr: 5.547548428094075e-06 loss: 0.0266 (0.0317) time: 3.1817 data: 0.0077 max mem: 33370 +Epoch: [36] [ 700/1319] eta: 0:32:53 lr: 5.536657831602032e-06 loss: 0.0273 (0.0317) time: 3.1609 data: 0.0081 max mem: 33370 +Epoch: [36] [ 710/1319] eta: 0:32:22 lr: 5.525764854389564e-06 loss: 0.0273 (0.0316) time: 3.1798 data: 0.0084 max mem: 33370 +Epoch: [36] [ 720/1319] eta: 0:31:50 lr: 5.514869490719365e-06 loss: 0.0295 (0.0316) time: 3.2047 data: 0.0085 max mem: 33370 +Epoch: [36] [ 730/1319] eta: 0:31:18 lr: 5.503971734827667e-06 loss: 0.0301 (0.0316) time: 3.1813 data: 0.0083 max mem: 33370 +Epoch: [36] [ 740/1319] eta: 0:30:46 lr: 5.493071580924068e-06 loss: 0.0303 (0.0316) time: 3.1606 data: 0.0080 max mem: 33370 +Epoch: [36] [ 750/1319] eta: 0:30:14 lr: 5.482169023191358e-06 loss: 0.0279 (0.0315) time: 3.1744 data: 0.0081 max mem: 33370 +Epoch: [36] [ 760/1319] eta: 0:29:42 lr: 5.471264055785306e-06 loss: 0.0277 (0.0315) time: 3.1955 data: 0.0080 max mem: 33370 +Epoch: [36] [ 770/1319] eta: 0:29:10 lr: 5.4603566728345144e-06 loss: 0.0284 (0.0315) time: 3.1909 data: 0.0077 max mem: 33370 +Epoch: [36] [ 780/1319] eta: 0:28:38 lr: 5.449446868440208e-06 loss: 0.0289 (0.0315) time: 3.1963 data: 0.0081 max mem: 33370 +Epoch: [36] [ 790/1319] eta: 0:28:06 lr: 5.43853463667605e-06 loss: 0.0295 (0.0315) time: 3.1840 data: 0.0086 max mem: 33370 +Epoch: [36] [ 800/1319] eta: 0:27:34 lr: 5.427619971587958e-06 loss: 0.0310 (0.0315) time: 3.1494 data: 0.0083 max mem: 33370 +Epoch: [36] [ 810/1319] eta: 0:27:02 lr: 5.416702867193884e-06 loss: 0.0279 (0.0315) time: 3.1760 data: 0.0078 max mem: 33370 +Epoch: [36] [ 820/1319] eta: 0:26:30 lr: 5.4057833174836655e-06 loss: 0.0271 (0.0315) time: 3.1710 data: 0.0077 max mem: 33370 +Epoch: [36] [ 830/1319] eta: 0:25:58 lr: 5.394861316418795e-06 loss: 0.0260 (0.0315) time: 3.1356 data: 0.0078 max mem: 33370 +Epoch: [36] [ 840/1319] eta: 0:25:26 lr: 5.383936857932236e-06 loss: 0.0281 (0.0315) time: 3.1398 data: 0.0078 max mem: 33370 +Epoch: [36] [ 850/1319] eta: 0:24:54 lr: 5.373009935928221e-06 loss: 0.0327 (0.0315) time: 3.1458 data: 0.0079 max mem: 33370 +Epoch: [36] [ 860/1319] eta: 0:24:22 lr: 5.362080544282056e-06 loss: 0.0327 (0.0315) time: 3.1702 data: 0.0077 max mem: 33370 +Epoch: [36] [ 870/1319] eta: 0:23:50 lr: 5.351148676839889e-06 loss: 0.0287 (0.0315) time: 3.1905 data: 0.0079 max mem: 33370 +Epoch: [36] [ 880/1319] eta: 0:23:18 lr: 5.340214327418554e-06 loss: 0.0287 (0.0315) time: 3.1723 data: 0.0081 max mem: 33370 +Epoch: [36] [ 890/1319] eta: 0:22:46 lr: 5.3292774898053224e-06 loss: 0.0262 (0.0314) time: 3.1761 data: 0.0083 max mem: 33370 +Epoch: [36] [ 900/1319] eta: 0:22:14 lr: 5.3183381577577165e-06 loss: 0.0262 (0.0314) time: 3.1746 data: 0.0084 max mem: 33370 +Epoch: [36] [ 910/1319] eta: 0:21:43 lr: 5.307396325003292e-06 loss: 0.0271 (0.0314) time: 3.1884 data: 0.0080 max mem: 33370 +Epoch: [36] [ 920/1319] eta: 0:21:11 lr: 5.296451985239408e-06 loss: 0.0271 (0.0313) time: 3.2274 data: 0.0077 max mem: 33370 +Epoch: [36] [ 930/1319] eta: 0:20:39 lr: 5.285505132133047e-06 loss: 0.0263 (0.0313) time: 3.1943 data: 0.0076 max mem: 33370 +Epoch: [36] [ 940/1319] eta: 0:20:07 lr: 5.274555759320574e-06 loss: 0.0264 (0.0313) time: 3.1788 data: 0.0076 max mem: 33370 +Epoch: [36] [ 950/1319] eta: 0:19:35 lr: 5.263603860407521e-06 loss: 0.0268 (0.0313) time: 3.1860 data: 0.0081 max mem: 33370 +Epoch: [36] [ 960/1319] eta: 0:19:03 lr: 5.252649428968377e-06 loss: 0.0317 (0.0313) time: 3.1744 data: 0.0081 max mem: 33370 +Epoch: [36] [ 970/1319] eta: 0:18:31 lr: 5.241692458546333e-06 loss: 0.0293 (0.0313) time: 3.1886 data: 0.0083 max mem: 33370 +Epoch: [36] [ 980/1319] eta: 0:18:00 lr: 5.230732942653104e-06 loss: 0.0279 (0.0313) time: 3.2112 data: 0.0082 max mem: 33370 +Epoch: [36] [ 990/1319] eta: 0:17:28 lr: 5.2197708747686676e-06 loss: 0.0272 (0.0313) time: 3.1858 data: 0.0076 max mem: 33370 +Epoch: [36] [1000/1319] eta: 0:16:56 lr: 5.208806248341044e-06 loss: 0.0257 (0.0312) time: 3.1956 data: 0.0077 max mem: 33370 +Epoch: [36] [1010/1319] eta: 0:16:24 lr: 5.197839056786066e-06 loss: 0.0257 (0.0312) time: 3.2293 data: 0.0078 max mem: 33370 +Epoch: [36] [1020/1319] eta: 0:15:52 lr: 5.186869293487148e-06 loss: 0.0280 (0.0312) time: 3.1982 data: 0.0081 max mem: 33370 +Epoch: [36] [1030/1319] eta: 0:15:21 lr: 5.175896951795028e-06 loss: 0.0270 (0.0312) time: 3.2072 data: 0.0082 max mem: 33370 +Epoch: [36] [1040/1319] eta: 0:14:49 lr: 5.164922025027563e-06 loss: 0.0264 (0.0311) time: 3.2111 data: 0.0080 max mem: 33370 +Epoch: [36] [1050/1319] eta: 0:14:17 lr: 5.153944506469468e-06 loss: 0.0303 (0.0312) time: 3.1967 data: 0.0077 max mem: 33370 +Epoch: [36] [1060/1319] eta: 0:13:45 lr: 5.142964389372074e-06 loss: 0.0346 (0.0313) time: 3.2147 data: 0.0076 max mem: 33370 +Epoch: [36] [1070/1319] eta: 0:13:13 lr: 5.13198166695309e-06 loss: 0.0328 (0.0314) time: 3.1849 data: 0.0084 max mem: 33370 +Epoch: [36] [1080/1319] eta: 0:12:41 lr: 5.120996332396334e-06 loss: 0.0315 (0.0314) time: 3.1896 data: 0.0086 max mem: 33370 +Epoch: [36] [1090/1319] eta: 0:12:09 lr: 5.1100083788515145e-06 loss: 0.0299 (0.0314) time: 3.1719 data: 0.0079 max mem: 33370 +Epoch: [36] [1100/1319] eta: 0:11:37 lr: 5.0990177994339575e-06 loss: 0.0279 (0.0313) time: 3.1271 data: 0.0079 max mem: 33370 +Epoch: [36] [1110/1319] eta: 0:11:06 lr: 5.088024587224353e-06 loss: 0.0326 (0.0314) time: 3.1735 data: 0.0080 max mem: 33370 +Epoch: [36] [1120/1319] eta: 0:10:34 lr: 5.077028735268508e-06 loss: 0.0328 (0.0314) time: 3.1955 data: 0.0081 max mem: 33370 +Epoch: [36] [1130/1319] eta: 0:10:02 lr: 5.066030236577056e-06 loss: 0.0296 (0.0314) time: 3.2020 data: 0.0081 max mem: 33370 +Epoch: [36] [1140/1319] eta: 0:09:30 lr: 5.055029084125236e-06 loss: 0.0265 (0.0314) time: 3.2044 data: 0.0080 max mem: 33370 +Epoch: [36] [1150/1319] eta: 0:08:58 lr: 5.044025270852602e-06 loss: 0.0268 (0.0314) time: 3.2051 data: 0.0082 max mem: 33370 +Epoch: [36] [1160/1319] eta: 0:08:26 lr: 5.033018789662757e-06 loss: 0.0267 (0.0314) time: 3.1624 data: 0.0076 max mem: 33370 +Epoch: [36] [1170/1319] eta: 0:07:54 lr: 5.022009633423085e-06 loss: 0.0267 (0.0313) time: 3.1546 data: 0.0073 max mem: 33370 +Epoch: [36] [1180/1319] eta: 0:07:22 lr: 5.0109977949644845e-06 loss: 0.0276 (0.0313) time: 3.1689 data: 0.0075 max mem: 33370 +Epoch: [36] [1190/1319] eta: 0:06:51 lr: 4.999983267081064e-06 loss: 0.0309 (0.0315) time: 3.1560 data: 0.0075 max mem: 33370 +Epoch: [36] [1200/1319] eta: 0:06:19 lr: 4.988966042529905e-06 loss: 0.0308 (0.0315) time: 3.1886 data: 0.0077 max mem: 33370 +Epoch: [36] [1210/1319] eta: 0:05:47 lr: 4.977946114030749e-06 loss: 0.0278 (0.0314) time: 3.1908 data: 0.0078 max mem: 33370 +Epoch: [36] [1220/1319] eta: 0:05:15 lr: 4.966923474265728e-06 loss: 0.0271 (0.0314) time: 3.1876 data: 0.0079 max mem: 33370 +Epoch: [36] [1230/1319] eta: 0:04:43 lr: 4.9558981158790714e-06 loss: 0.0275 (0.0314) time: 3.1684 data: 0.0078 max mem: 33370 +Epoch: [36] [1240/1319] eta: 0:04:11 lr: 4.944870031476802e-06 loss: 0.0306 (0.0314) time: 3.1932 data: 0.0079 max mem: 33370 +Epoch: [36] [1250/1319] eta: 0:03:39 lr: 4.9338392136264714e-06 loss: 0.0305 (0.0313) time: 3.1888 data: 0.0079 max mem: 33370 +Epoch: [36] [1260/1319] eta: 0:03:07 lr: 4.922805654856843e-06 loss: 0.0290 (0.0313) time: 3.1676 data: 0.0085 max mem: 33370 +Epoch: [36] [1270/1319] eta: 0:02:36 lr: 4.9117693476576e-06 loss: 0.0305 (0.0314) time: 3.2082 data: 0.0085 max mem: 33370 +Epoch: [36] [1280/1319] eta: 0:02:04 lr: 4.9007302844790375e-06 loss: 0.0313 (0.0314) time: 3.2193 data: 0.0080 max mem: 33370 +Epoch: [36] [1290/1319] eta: 0:01:32 lr: 4.889688457731768e-06 loss: 0.0292 (0.0313) time: 3.2079 data: 0.0083 max mem: 33370 +Epoch: [36] [1300/1319] eta: 0:01:00 lr: 4.878643859786385e-06 loss: 0.0278 (0.0313) time: 3.1812 data: 0.0081 max mem: 33370 +Epoch: [36] [1310/1319] eta: 0:00:28 lr: 4.867596482973188e-06 loss: 0.0295 (0.0313) time: 3.1750 data: 0.0077 max mem: 33370 +Epoch: [36] Total time: 1:10:03 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 2:14:37 time: 3.1392 data: 2.8457 max mem: 33370 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 100/2573] eta: 0:04:24 time: 0.0769 data: 0.0015 max mem: 33370 +Test: [ 200/2573] eta: 0:03:41 time: 0.0779 data: 0.0015 max mem: 33370 +Test: [ 300/2573] eta: 0:03:19 time: 0.0794 data: 0.0013 max mem: 33370 +Test: [ 400/2573] eta: 0:03:05 time: 0.0804 data: 0.0014 max mem: 33370 +Test: [ 500/2573] eta: 0:02:54 time: 0.0803 data: 0.0015 max mem: 33370 +Test: [ 600/2573] eta: 0:02:44 time: 0.0789 data: 0.0016 max mem: 33370 +Test: [ 700/2573] eta: 0:02:35 time: 0.0798 data: 0.0016 max mem: 33370 +Test: [ 800/2573] eta: 0:02:26 time: 0.0835 data: 0.0015 max mem: 33370 +Test: [ 900/2573] eta: 0:02:18 time: 0.0792 data: 0.0015 max mem: 33370 +Test: [1000/2573] eta: 0:02:09 time: 0.0789 data: 0.0015 max mem: 33370 +Test: [1100/2573] eta: 0:02:00 time: 0.0791 data: 0.0014 max mem: 33370 +Test: [1200/2573] eta: 0:01:52 time: 0.0788 data: 0.0014 max mem: 33370 +Test: [1300/2573] eta: 0:01:43 time: 0.0789 data: 0.0014 max mem: 33370 +Test: [1400/2573] eta: 0:01:35 time: 0.0772 data: 0.0014 max mem: 33370 +Test: [1500/2573] eta: 0:01:27 time: 0.0801 data: 0.0015 max mem: 33370 +Test: [1600/2573] eta: 0:01:18 time: 0.0820 data: 0.0016 max mem: 33370 +Test: [1700/2573] eta: 0:01:10 time: 0.0780 data: 0.0014 max mem: 33370 +Test: [1800/2573] eta: 0:01:02 time: 0.0819 data: 0.0016 max mem: 33370 +Test: [1900/2573] eta: 0:00:54 time: 0.0782 data: 0.0015 max mem: 33370 +Test: [2000/2573] eta: 0:00:46 time: 0.0793 data: 0.0015 max mem: 33370 +Test: [2100/2573] eta: 0:00:38 time: 0.0807 data: 0.0014 max mem: 33370 +Test: [2200/2573] eta: 0:00:30 time: 0.0805 data: 0.0014 max mem: 33370 +Test: [2300/2573] eta: 0:00:21 time: 0.0802 data: 0.0014 max mem: 33370 +Test: [2400/2573] eta: 0:00:13 time: 0.0766 data: 0.0014 max mem: 33370 +Test: [2500/2573] eta: 0:00:05 time: 0.0786 data: 0.0014 max mem: 33370 +Test: Total time: 0:03:27 +Final results: +Mean IoU is 64.95 + + precision@0.5 = 72.63 + precision@0.6 = 67.87 + precision@0.7 = 60.91 + precision@0.8 = 49.65 + precision@0.9 = 25.39 + overall IoU = 62.41 + +Average object IoU 64.94613520282438 +Overall IoU 62.40907669067383 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [37] [ 0/1319] eta: 3:03:38 lr: 4.85765146153759e-06 loss: 0.0360 (0.0360) time: 8.3537 data: 2.1486 max mem: 33370 +Epoch: [37] [ 10/1319] eta: 1:20:02 lr: 4.846598783599751e-06 loss: 0.0253 (0.0267) time: 3.6688 data: 0.2025 max mem: 33370 +Epoch: [37] [ 20/1319] eta: 1:13:58 lr: 4.835543304321068e-06 loss: 0.0253 (0.0287) time: 3.1699 data: 0.0076 max mem: 33370 +Epoch: [37] [ 30/1319] eta: 1:11:55 lr: 4.824485015871577e-06 loss: 0.0272 (0.0287) time: 3.1720 data: 0.0076 max mem: 33370 +Epoch: [37] [ 40/1319] eta: 1:10:14 lr: 4.813423910379438e-06 loss: 0.0296 (0.0302) time: 3.1668 data: 0.0078 max mem: 33370 +Epoch: [37] [ 50/1319] eta: 1:09:18 lr: 4.802359979930566e-06 loss: 0.0299 (0.0306) time: 3.1674 data: 0.0083 max mem: 33370 +Epoch: [37] [ 60/1319] eta: 1:08:23 lr: 4.791293216568347e-06 loss: 0.0259 (0.0300) time: 3.1870 data: 0.0085 max mem: 33370 +Epoch: [37] [ 70/1319] eta: 1:07:35 lr: 4.780223612293264e-06 loss: 0.0271 (0.0302) time: 3.1705 data: 0.0079 max mem: 33370 +Epoch: [37] [ 80/1319] eta: 1:07:01 lr: 4.7691511590625665e-06 loss: 0.0321 (0.0306) time: 3.2044 data: 0.0078 max mem: 33370 +Epoch: [37] [ 90/1319] eta: 1:06:24 lr: 4.75807584878992e-06 loss: 0.0328 (0.0308) time: 3.2234 data: 0.0083 max mem: 33370 +Epoch: [37] [ 100/1319] eta: 1:05:45 lr: 4.7469976733450685e-06 loss: 0.0310 (0.0309) time: 3.1999 data: 0.0087 max mem: 33370 +Epoch: [37] [ 110/1319] eta: 1:05:05 lr: 4.735916624553454e-06 loss: 0.0300 (0.0307) time: 3.1794 data: 0.0084 max mem: 33370 +Epoch: [37] [ 120/1319] eta: 1:04:30 lr: 4.724832694195895e-06 loss: 0.0305 (0.0308) time: 3.1829 data: 0.0081 max mem: 33370 +Epoch: [37] [ 130/1319] eta: 1:03:48 lr: 4.713745874008202e-06 loss: 0.0265 (0.0303) time: 3.1600 data: 0.0078 max mem: 33370 +Epoch: [37] [ 140/1319] eta: 1:03:13 lr: 4.702656155680819e-06 loss: 0.0246 (0.0300) time: 3.1570 data: 0.0081 max mem: 33370 +Epoch: [37] [ 150/1319] eta: 1:02:36 lr: 4.691563530858464e-06 loss: 0.0281 (0.0301) time: 3.1704 data: 0.0083 max mem: 33370 +Epoch: [37] [ 160/1319] eta: 1:02:03 lr: 4.6804679911397265e-06 loss: 0.0322 (0.0302) time: 3.1779 data: 0.0080 max mem: 33370 +Epoch: [37] [ 170/1319] eta: 1:01:29 lr: 4.66936952807673e-06 loss: 0.0276 (0.0300) time: 3.1914 data: 0.0082 max mem: 33370 +Epoch: [37] [ 180/1319] eta: 1:00:54 lr: 4.65826813317473e-06 loss: 0.0260 (0.0299) time: 3.1724 data: 0.0080 max mem: 33370 +Epoch: [37] [ 190/1319] eta: 1:00:18 lr: 4.64716379789173e-06 loss: 0.0272 (0.0299) time: 3.1586 data: 0.0081 max mem: 33370 +Epoch: [37] [ 200/1319] eta: 0:59:46 lr: 4.636056513638103e-06 loss: 0.0280 (0.0299) time: 3.1737 data: 0.0082 max mem: 33370 +Epoch: [37] [ 210/1319] eta: 0:59:13 lr: 4.6249462717761695e-06 loss: 0.0330 (0.0302) time: 3.1915 data: 0.0080 max mem: 33370 +Epoch: [37] [ 220/1319] eta: 0:58:40 lr: 4.6138330636198426e-06 loss: 0.0330 (0.0302) time: 3.1856 data: 0.0085 max mem: 33370 +Epoch: [37] [ 230/1319] eta: 0:58:06 lr: 4.602716880434195e-06 loss: 0.0256 (0.0301) time: 3.1795 data: 0.0084 max mem: 33370 +Epoch: [37] [ 240/1319] eta: 0:57:36 lr: 4.591597713435064e-06 loss: 0.0289 (0.0303) time: 3.2087 data: 0.0081 max mem: 33370 +Epoch: [37] [ 250/1319] eta: 0:57:03 lr: 4.580475553788638e-06 loss: 0.0312 (0.0304) time: 3.2087 data: 0.0081 max mem: 33370 +Epoch: [37] [ 260/1319] eta: 0:56:31 lr: 4.569350392611047e-06 loss: 0.0254 (0.0303) time: 3.1863 data: 0.0078 max mem: 33370 +Epoch: [37] [ 270/1319] eta: 0:55:55 lr: 4.558222220967921e-06 loss: 0.0301 (0.0305) time: 3.1512 data: 0.0075 max mem: 33370 +Epoch: [37] [ 280/1319] eta: 0:55:21 lr: 4.547091029873999e-06 loss: 0.0302 (0.0305) time: 3.1205 data: 0.0077 max mem: 33370 +Epoch: [37] [ 290/1319] eta: 0:54:45 lr: 4.5359568102926745e-06 loss: 0.0281 (0.0306) time: 3.1178 data: 0.0082 max mem: 33370 +Epoch: [37] [ 300/1319] eta: 0:54:13 lr: 4.524819553135574e-06 loss: 0.0281 (0.0306) time: 3.1460 data: 0.0082 max mem: 33370 +Epoch: [37] [ 310/1319] eta: 0:53:40 lr: 4.5136792492621144e-06 loss: 0.0295 (0.0305) time: 3.1655 data: 0.0083 max mem: 33370 +Epoch: [37] [ 320/1319] eta: 0:53:07 lr: 4.502535889479041e-06 loss: 0.0253 (0.0303) time: 3.1572 data: 0.0081 max mem: 33370 +Epoch: [37] [ 330/1319] eta: 0:52:34 lr: 4.491389464540016e-06 loss: 0.0242 (0.0302) time: 3.1636 data: 0.0080 max mem: 33370 +Epoch: [37] [ 340/1319] eta: 0:52:01 lr: 4.480239965145135e-06 loss: 0.0272 (0.0304) time: 3.1500 data: 0.0083 max mem: 33370 +Epoch: [37] [ 350/1319] eta: 0:51:27 lr: 4.469087381940477e-06 loss: 0.0339 (0.0305) time: 3.1352 data: 0.0082 max mem: 33370 +Epoch: [37] [ 360/1319] eta: 0:50:55 lr: 4.457931705517646e-06 loss: 0.0271 (0.0303) time: 3.1424 data: 0.0081 max mem: 33370 +Epoch: [37] [ 370/1319] eta: 0:50:22 lr: 4.446772926413276e-06 loss: 0.0262 (0.0305) time: 3.1554 data: 0.0083 max mem: 33370 +Epoch: [37] [ 380/1319] eta: 0:49:48 lr: 4.435611035108594e-06 loss: 0.0277 (0.0304) time: 3.1284 data: 0.0084 max mem: 33370 +Epoch: [37] [ 390/1319] eta: 0:49:15 lr: 4.424446022028913e-06 loss: 0.0275 (0.0303) time: 3.1201 data: 0.0082 max mem: 33370 +Epoch: [37] [ 400/1319] eta: 0:48:44 lr: 4.413277877543152e-06 loss: 0.0270 (0.0302) time: 3.1757 data: 0.0082 max mem: 33370 +Epoch: [37] [ 410/1319] eta: 0:48:11 lr: 4.40210659196335e-06 loss: 0.0278 (0.0303) time: 3.1697 data: 0.0082 max mem: 33370 +Epoch: [37] [ 420/1319] eta: 0:47:38 lr: 4.390932155544163e-06 loss: 0.0320 (0.0304) time: 3.1211 data: 0.0084 max mem: 33370 +Epoch: [37] [ 430/1319] eta: 0:47:07 lr: 4.379754558482349e-06 loss: 0.0269 (0.0304) time: 3.1803 data: 0.0081 max mem: 33370 +Epoch: [37] [ 440/1319] eta: 0:46:35 lr: 4.368573790916289e-06 loss: 0.0276 (0.0305) time: 3.1974 data: 0.0082 max mem: 33370 +Epoch: [37] [ 450/1319] eta: 0:46:03 lr: 4.357389842925446e-06 loss: 0.0263 (0.0305) time: 3.1502 data: 0.0089 max mem: 33370 +Epoch: [37] [ 460/1319] eta: 0:45:31 lr: 4.346202704529857e-06 loss: 0.0266 (0.0304) time: 3.1681 data: 0.0087 max mem: 33370 +Epoch: [37] [ 470/1319] eta: 0:44:59 lr: 4.335012365689605e-06 loss: 0.0286 (0.0305) time: 3.1689 data: 0.0081 max mem: 33370 +Epoch: [37] [ 480/1319] eta: 0:44:26 lr: 4.323818816304266e-06 loss: 0.0309 (0.0304) time: 3.1474 data: 0.0080 max mem: 33370 +Epoch: [37] [ 490/1319] eta: 0:43:55 lr: 4.3126220462124026e-06 loss: 0.0264 (0.0303) time: 3.1857 data: 0.0082 max mem: 33370 +Epoch: [37] [ 500/1319] eta: 0:43:24 lr: 4.3014220451909986e-06 loss: 0.0274 (0.0303) time: 3.2243 data: 0.0086 max mem: 33370 +Epoch: [37] [ 510/1319] eta: 0:42:53 lr: 4.2902188029549045e-06 loss: 0.0274 (0.0303) time: 3.2165 data: 0.0082 max mem: 33370 +Epoch: [37] [ 520/1319] eta: 0:42:20 lr: 4.279012309156296e-06 loss: 0.0266 (0.0302) time: 3.1691 data: 0.0079 max mem: 33370 +Epoch: [37] [ 530/1319] eta: 0:41:49 lr: 4.267802553384072e-06 loss: 0.0274 (0.0302) time: 3.1596 data: 0.0081 max mem: 33370 +Epoch: [37] [ 540/1319] eta: 0:41:17 lr: 4.256589525163327e-06 loss: 0.0293 (0.0302) time: 3.1835 data: 0.0081 max mem: 33370 +Epoch: [37] [ 550/1319] eta: 0:40:45 lr: 4.2453732139547435e-06 loss: 0.0283 (0.0302) time: 3.1691 data: 0.0080 max mem: 33370 +Epoch: [37] [ 560/1319] eta: 0:40:13 lr: 4.234153609154016e-06 loss: 0.0294 (0.0302) time: 3.1773 data: 0.0083 max mem: 33370 +Epoch: [37] [ 570/1319] eta: 0:39:42 lr: 4.222930700091251e-06 loss: 0.0295 (0.0302) time: 3.2148 data: 0.0081 max mem: 33370 +Epoch: [37] [ 580/1319] eta: 0:39:10 lr: 4.211704476030378e-06 loss: 0.0308 (0.0302) time: 3.2087 data: 0.0083 max mem: 33370 +Epoch: [37] [ 590/1319] eta: 0:38:38 lr: 4.200474926168517e-06 loss: 0.0305 (0.0302) time: 3.1566 data: 0.0083 max mem: 33370 +Epoch: [37] [ 600/1319] eta: 0:38:06 lr: 4.189242039635394e-06 loss: 0.0272 (0.0302) time: 3.1750 data: 0.0082 max mem: 33370 +Epoch: [37] [ 610/1319] eta: 0:37:34 lr: 4.178005805492704e-06 loss: 0.0251 (0.0301) time: 3.1933 data: 0.0086 max mem: 33370 +Epoch: [37] [ 620/1319] eta: 0:37:03 lr: 4.166766212733477e-06 loss: 0.0260 (0.0301) time: 3.1995 data: 0.0088 max mem: 33370 +Epoch: [37] [ 630/1319] eta: 0:36:31 lr: 4.15552325028145e-06 loss: 0.0273 (0.0301) time: 3.1922 data: 0.0084 max mem: 33370 +Epoch: [37] [ 640/1319] eta: 0:36:00 lr: 4.1442769069903985e-06 loss: 0.0253 (0.0301) time: 3.1744 data: 0.0077 max mem: 33370 +Epoch: [37] [ 650/1319] eta: 0:35:28 lr: 4.133027171643516e-06 loss: 0.0287 (0.0301) time: 3.1934 data: 0.0082 max mem: 33370 +Epoch: [37] [ 660/1319] eta: 0:34:56 lr: 4.121774032952729e-06 loss: 0.0293 (0.0301) time: 3.1772 data: 0.0090 max mem: 33370 +Epoch: [37] [ 670/1319] eta: 0:34:24 lr: 4.110517479558032e-06 loss: 0.0276 (0.0301) time: 3.1753 data: 0.0089 max mem: 33370 +Epoch: [37] [ 680/1319] eta: 0:33:52 lr: 4.099257500026817e-06 loss: 0.0257 (0.0300) time: 3.1636 data: 0.0082 max mem: 33370 +Epoch: [37] [ 690/1319] eta: 0:33:20 lr: 4.087994082853156e-06 loss: 0.0258 (0.0300) time: 3.1642 data: 0.0084 max mem: 33370 +Epoch: [37] [ 700/1319] eta: 0:32:48 lr: 4.076727216457151e-06 loss: 0.0274 (0.0300) time: 3.1663 data: 0.0089 max mem: 33370 +Epoch: [37] [ 710/1319] eta: 0:32:16 lr: 4.065456889184196e-06 loss: 0.0284 (0.0300) time: 3.1688 data: 0.0082 max mem: 33370 +Epoch: [37] [ 720/1319] eta: 0:31:44 lr: 4.054183089304276e-06 loss: 0.0327 (0.0301) time: 3.1655 data: 0.0077 max mem: 33370 +Epoch: [37] [ 730/1319] eta: 0:31:13 lr: 4.0429058050112415e-06 loss: 0.0297 (0.0300) time: 3.1741 data: 0.0077 max mem: 33370 +Epoch: [37] [ 740/1319] eta: 0:30:41 lr: 4.031625024422082e-06 loss: 0.0280 (0.0301) time: 3.2004 data: 0.0079 max mem: 33370 +Epoch: [37] [ 750/1319] eta: 0:30:09 lr: 4.020340735576163e-06 loss: 0.0285 (0.0301) time: 3.1797 data: 0.0081 max mem: 33370 +Epoch: [37] [ 760/1319] eta: 0:29:37 lr: 4.0090529264345135e-06 loss: 0.0315 (0.0302) time: 3.1718 data: 0.0081 max mem: 33370 +Epoch: [37] [ 770/1319] eta: 0:29:05 lr: 3.997761584879033e-06 loss: 0.0315 (0.0302) time: 3.1552 data: 0.0081 max mem: 33370 +Epoch: [37] [ 780/1319] eta: 0:28:33 lr: 3.986466698711739e-06 loss: 0.0298 (0.0302) time: 3.1536 data: 0.0083 max mem: 33370 +Epoch: [37] [ 790/1319] eta: 0:28:01 lr: 3.975168255653987e-06 loss: 0.0283 (0.0302) time: 3.1673 data: 0.0078 max mem: 33370 +Epoch: [37] [ 800/1319] eta: 0:27:29 lr: 3.963866243345654e-06 loss: 0.0283 (0.0302) time: 3.1690 data: 0.0074 max mem: 33370 +Epoch: [37] [ 810/1319] eta: 0:26:57 lr: 3.952560649344379e-06 loss: 0.0290 (0.0302) time: 3.1563 data: 0.0079 max mem: 33370 +Epoch: [37] [ 820/1319] eta: 0:26:25 lr: 3.94125146112473e-06 loss: 0.0290 (0.0302) time: 3.1343 data: 0.0084 max mem: 33370 +Epoch: [37] [ 830/1319] eta: 0:25:54 lr: 3.929938666077381e-06 loss: 0.0288 (0.0302) time: 3.1523 data: 0.0081 max mem: 33370 +Epoch: [37] [ 840/1319] eta: 0:25:22 lr: 3.918622251508287e-06 loss: 0.0296 (0.0302) time: 3.1692 data: 0.0080 max mem: 33370 +Epoch: [37] [ 850/1319] eta: 0:24:50 lr: 3.907302204637846e-06 loss: 0.0302 (0.0302) time: 3.1481 data: 0.0080 max mem: 33370 +Epoch: [37] [ 860/1319] eta: 0:24:18 lr: 3.895978512600013e-06 loss: 0.0311 (0.0302) time: 3.1214 data: 0.0077 max mem: 33370 +Epoch: [37] [ 870/1319] eta: 0:23:46 lr: 3.8846511624414845e-06 loss: 0.0258 (0.0302) time: 3.1690 data: 0.0076 max mem: 33370 +Epoch: [37] [ 880/1319] eta: 0:23:14 lr: 3.873320141120784e-06 loss: 0.0255 (0.0301) time: 3.1873 data: 0.0077 max mem: 33370 +Epoch: [37] [ 890/1319] eta: 0:22:43 lr: 3.86198543550739e-06 loss: 0.0263 (0.0301) time: 3.1876 data: 0.0081 max mem: 33370 +Epoch: [37] [ 900/1319] eta: 0:22:11 lr: 3.850647032380834e-06 loss: 0.0270 (0.0301) time: 3.1930 data: 0.0080 max mem: 33370 +Epoch: [37] [ 910/1319] eta: 0:21:39 lr: 3.839304918429766e-06 loss: 0.0263 (0.0301) time: 3.1650 data: 0.0077 max mem: 33370 +Epoch: [37] [ 920/1319] eta: 0:21:07 lr: 3.8279590802510684e-06 loss: 0.0286 (0.0301) time: 3.1881 data: 0.0078 max mem: 33370 +Epoch: [37] [ 930/1319] eta: 0:20:35 lr: 3.816609504348892e-06 loss: 0.0286 (0.0302) time: 3.1901 data: 0.0078 max mem: 33370 +Epoch: [37] [ 940/1319] eta: 0:20:04 lr: 3.805256177133712e-06 loss: 0.0266 (0.0301) time: 3.2019 data: 0.0079 max mem: 33370 +Epoch: [37] [ 950/1319] eta: 0:19:32 lr: 3.7938990849213705e-06 loss: 0.0279 (0.0302) time: 3.1951 data: 0.0083 max mem: 33370 +Epoch: [37] [ 960/1319] eta: 0:19:00 lr: 3.782538213932079e-06 loss: 0.0303 (0.0301) time: 3.1519 data: 0.0082 max mem: 33370 +Epoch: [37] [ 970/1319] eta: 0:18:28 lr: 3.771173550289461e-06 loss: 0.0269 (0.0301) time: 3.1651 data: 0.0081 max mem: 33370 +Epoch: [37] [ 980/1319] eta: 0:17:57 lr: 3.7598050800195294e-06 loss: 0.0262 (0.0301) time: 3.1826 data: 0.0083 max mem: 33370 +Epoch: [37] [ 990/1319] eta: 0:17:25 lr: 3.748432789049672e-06 loss: 0.0250 (0.0301) time: 3.1860 data: 0.0080 max mem: 33370 +Epoch: [37] [1000/1319] eta: 0:16:53 lr: 3.7370566632076215e-06 loss: 0.0291 (0.0301) time: 3.1516 data: 0.0082 max mem: 33370 +Epoch: [37] [1010/1319] eta: 0:16:21 lr: 3.725676688220417e-06 loss: 0.0264 (0.0301) time: 3.1344 data: 0.0083 max mem: 33370 +Epoch: [37] [1020/1319] eta: 0:15:49 lr: 3.714292849713318e-06 loss: 0.0264 (0.0301) time: 3.1603 data: 0.0079 max mem: 33370 +Epoch: [37] [1030/1319] eta: 0:15:18 lr: 3.7029051332087708e-06 loss: 0.0296 (0.0301) time: 3.1747 data: 0.0075 max mem: 33370 +Epoch: [37] [1040/1319] eta: 0:14:46 lr: 3.691513524125288e-06 loss: 0.0265 (0.0301) time: 3.1779 data: 0.0080 max mem: 33370 +Epoch: [37] [1050/1319] eta: 0:14:14 lr: 3.680118007776355e-06 loss: 0.0272 (0.0301) time: 3.1868 data: 0.0083 max mem: 33370 +Epoch: [37] [1060/1319] eta: 0:13:42 lr: 3.6687185693693123e-06 loss: 0.0291 (0.0302) time: 3.1864 data: 0.0080 max mem: 33370 +Epoch: [37] [1070/1319] eta: 0:13:11 lr: 3.657315194004196e-06 loss: 0.0287 (0.0302) time: 3.1843 data: 0.0077 max mem: 33370 +Epoch: [37] [1080/1319] eta: 0:12:39 lr: 3.6459078666726217e-06 loss: 0.0250 (0.0302) time: 3.1757 data: 0.0077 max mem: 33370 +Epoch: [37] [1090/1319] eta: 0:12:07 lr: 3.6344965722565904e-06 loss: 0.0250 (0.0302) time: 3.1914 data: 0.0079 max mem: 33370 +Epoch: [37] [1100/1319] eta: 0:11:35 lr: 3.6230812955273095e-06 loss: 0.0293 (0.0303) time: 3.2041 data: 0.0081 max mem: 33370 +Epoch: [37] [1110/1319] eta: 0:11:04 lr: 3.6116620211439967e-06 loss: 0.0293 (0.0302) time: 3.1772 data: 0.0080 max mem: 33370 +Epoch: [37] [1120/1319] eta: 0:10:32 lr: 3.6002387336526318e-06 loss: 0.0286 (0.0302) time: 3.1693 data: 0.0080 max mem: 33370 +Epoch: [37] [1130/1319] eta: 0:10:00 lr: 3.588811417484761e-06 loss: 0.0286 (0.0303) time: 3.1683 data: 0.0078 max mem: 33370 +Epoch: [37] [1140/1319] eta: 0:09:28 lr: 3.577380056956213e-06 loss: 0.0285 (0.0303) time: 3.1772 data: 0.0076 max mem: 33370 +Epoch: [37] [1150/1319] eta: 0:08:56 lr: 3.5659446362658317e-06 loss: 0.0285 (0.0303) time: 3.1673 data: 0.0079 max mem: 33370 +Epoch: [37] [1160/1319] eta: 0:08:25 lr: 3.5545051394941854e-06 loss: 0.0305 (0.0303) time: 3.1762 data: 0.0079 max mem: 33370 +Epoch: [37] [1170/1319] eta: 0:07:53 lr: 3.5430615506022587e-06 loss: 0.0313 (0.0303) time: 3.1763 data: 0.0081 max mem: 33370 +Epoch: [37] [1180/1319] eta: 0:07:21 lr: 3.531613853430098e-06 loss: 0.0265 (0.0303) time: 3.1732 data: 0.0082 max mem: 33370 +Epoch: [37] [1190/1319] eta: 0:06:49 lr: 3.5201620316954973e-06 loss: 0.0261 (0.0302) time: 3.1797 data: 0.0082 max mem: 33370 +Epoch: [37] [1200/1319] eta: 0:06:18 lr: 3.5087060689926057e-06 loss: 0.0283 (0.0302) time: 3.1873 data: 0.0081 max mem: 33370 +Epoch: [37] [1210/1319] eta: 0:05:46 lr: 3.4972459487905388e-06 loss: 0.0281 (0.0302) time: 3.1824 data: 0.0079 max mem: 33370 +Epoch: [37] [1220/1319] eta: 0:05:14 lr: 3.485781654431977e-06 loss: 0.0260 (0.0302) time: 3.1890 data: 0.0078 max mem: 33370 +Epoch: [37] [1230/1319] eta: 0:04:42 lr: 3.4743131691317023e-06 loss: 0.0276 (0.0303) time: 3.1927 data: 0.0078 max mem: 33370 +Epoch: [37] [1240/1319] eta: 0:04:11 lr: 3.462840475975186e-06 loss: 0.0322 (0.0303) time: 3.1798 data: 0.0085 max mem: 33370 +Epoch: [37] [1250/1319] eta: 0:03:39 lr: 3.451363557917087e-06 loss: 0.0290 (0.0303) time: 3.1730 data: 0.0087 max mem: 33370 +Epoch: [37] [1260/1319] eta: 0:03:07 lr: 3.439882397779757e-06 loss: 0.0296 (0.0304) time: 3.1903 data: 0.0080 max mem: 33370 +Epoch: [37] [1270/1319] eta: 0:02:35 lr: 3.4283969782517246e-06 loss: 0.0296 (0.0304) time: 3.2062 data: 0.0079 max mem: 33370 +Epoch: [37] [1280/1319] eta: 0:02:03 lr: 3.416907281886128e-06 loss: 0.0271 (0.0303) time: 3.1872 data: 0.0084 max mem: 33370 +Epoch: [37] [1290/1319] eta: 0:01:32 lr: 3.405413291099184e-06 loss: 0.0259 (0.0303) time: 3.1831 data: 0.0082 max mem: 33370 +Epoch: [37] [1300/1319] eta: 0:01:00 lr: 3.393914988168568e-06 loss: 0.0268 (0.0303) time: 3.1850 data: 0.0078 max mem: 33370 +Epoch: [37] [1310/1319] eta: 0:00:28 lr: 3.3824123552318046e-06 loss: 0.0325 (0.0304) time: 3.1702 data: 0.0073 max mem: 33370 +Epoch: [37] Total time: 1:09:52 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 1:47:13 time: 2.5005 data: 2.3221 max mem: 33370 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 100/2573] eta: 0:04:12 time: 0.0775 data: 0.0015 max mem: 33370 +Test: [ 200/2573] eta: 0:03:35 time: 0.0777 data: 0.0015 max mem: 33370 +Test: [ 300/2573] eta: 0:03:16 time: 0.0795 data: 0.0015 max mem: 33370 +Test: [ 400/2573] eta: 0:03:03 time: 0.0800 data: 0.0014 max mem: 33370 +Test: [ 500/2573] eta: 0:02:52 time: 0.0797 data: 0.0015 max mem: 33370 +Test: [ 600/2573] eta: 0:02:43 time: 0.0794 data: 0.0014 max mem: 33370 +Test: [ 700/2573] eta: 0:02:34 time: 0.0786 data: 0.0016 max mem: 33370 +Test: [ 800/2573] eta: 0:02:25 time: 0.0816 data: 0.0014 max mem: 33370 +Test: [ 900/2573] eta: 0:02:16 time: 0.0791 data: 0.0015 max mem: 33370 +Test: [1000/2573] eta: 0:02:08 time: 0.0799 data: 0.0016 max mem: 33370 +Test: [1100/2573] eta: 0:01:59 time: 0.0784 data: 0.0014 max mem: 33370 +Test: [1200/2573] eta: 0:01:51 time: 0.0794 data: 0.0014 max mem: 33370 +Test: [1300/2573] eta: 0:01:43 time: 0.0795 data: 0.0015 max mem: 33370 +Test: [1400/2573] eta: 0:01:34 time: 0.0776 data: 0.0015 max mem: 33370 +Test: [1500/2573] eta: 0:01:26 time: 0.0789 data: 0.0014 max mem: 33370 +Test: [1600/2573] eta: 0:01:18 time: 0.0829 data: 0.0015 max mem: 33370 +Test: [1700/2573] eta: 0:01:10 time: 0.0793 data: 0.0015 max mem: 33370 +Test: [1800/2573] eta: 0:01:02 time: 0.0805 data: 0.0014 max mem: 33370 +Test: [1900/2573] eta: 0:00:54 time: 0.0783 data: 0.0014 max mem: 33370 +Test: [2000/2573] eta: 0:00:46 time: 0.0790 data: 0.0014 max mem: 33370 +Test: [2100/2573] eta: 0:00:38 time: 0.0808 data: 0.0014 max mem: 33370 +Test: [2200/2573] eta: 0:00:29 time: 0.0810 data: 0.0014 max mem: 33370 +Test: [2300/2573] eta: 0:00:21 time: 0.0806 data: 0.0014 max mem: 33370 +Test: [2400/2573] eta: 0:00:13 time: 0.0758 data: 0.0014 max mem: 33370 +Test: [2500/2573] eta: 0:00:05 time: 0.0802 data: 0.0015 max mem: 33370 +Test: Total time: 0:03:26 +Final results: +Mean IoU is 65.18 + + precision@0.5 = 72.92 + precision@0.6 = 68.10 + precision@0.7 = 61.42 + precision@0.8 = 49.86 + precision@0.9 = 25.69 + overall IoU = 62.68 + +Average object IoU 65.17905469269259 +Overall IoU 62.6811637878418 +Better epoch: 37 + +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [38] [ 0/1319] eta: 1:47:11 lr: 3.3720562685558925e-06 loss: 0.0255 (0.0255) time: 4.8759 data: 1.6501 max mem: 33370 +Epoch: [38] [ 10/1319] eta: 1:11:38 lr: 3.3605453588871517e-06 loss: 0.0275 (0.0299) time: 3.2840 data: 0.1575 max mem: 33370 +Epoch: [38] [ 20/1319] eta: 1:10:34 lr: 3.349030066603249e-06 loss: 0.0288 (0.0306) time: 3.1787 data: 0.0078 max mem: 33370 +Epoch: [38] [ 30/1319] eta: 1:09:36 lr: 3.3375103732791936e-06 loss: 0.0297 (0.0313) time: 3.2154 data: 0.0078 max mem: 33370 +Epoch: [38] [ 40/1319] eta: 1:08:36 lr: 3.3259862603415314e-06 loss: 0.0288 (0.0314) time: 3.1749 data: 0.0085 max mem: 33370 +Epoch: [38] [ 50/1319] eta: 1:07:56 lr: 3.314457709066606e-06 loss: 0.0298 (0.0313) time: 3.1708 data: 0.0086 max mem: 33370 +Epoch: [38] [ 60/1319] eta: 1:07:19 lr: 3.302924700578736e-06 loss: 0.0298 (0.0319) time: 3.1889 data: 0.0084 max mem: 33370 +Epoch: [38] [ 70/1319] eta: 1:06:43 lr: 3.2913872158483893e-06 loss: 0.0267 (0.0314) time: 3.1853 data: 0.0078 max mem: 33370 +Epoch: [38] [ 80/1319] eta: 1:06:00 lr: 3.279845235690334e-06 loss: 0.0270 (0.0309) time: 3.1605 data: 0.0078 max mem: 33370 +Epoch: [38] [ 90/1319] eta: 1:05:26 lr: 3.268298740761722e-06 loss: 0.0272 (0.0307) time: 3.1606 data: 0.0087 max mem: 33370 +Epoch: [38] [ 100/1319] eta: 1:04:53 lr: 3.2567477115602124e-06 loss: 0.0292 (0.0309) time: 3.1840 data: 0.0087 max mem: 33370 +Epoch: [38] [ 110/1319] eta: 1:04:12 lr: 3.2451921284219928e-06 loss: 0.0309 (0.0312) time: 3.1467 data: 0.0083 max mem: 33370 +Epoch: [38] [ 120/1319] eta: 1:03:35 lr: 3.233631971519807e-06 loss: 0.0280 (0.0311) time: 3.1238 data: 0.0088 max mem: 33370 +Epoch: [38] [ 130/1319] eta: 1:03:08 lr: 3.2220672208609392e-06 loss: 0.0270 (0.0310) time: 3.1845 data: 0.0090 max mem: 33370 +Epoch: [38] [ 140/1319] eta: 1:02:32 lr: 3.2104978562851772e-06 loss: 0.0276 (0.0307) time: 3.1858 data: 0.0089 max mem: 33370 +Epoch: [38] [ 150/1319] eta: 1:02:00 lr: 3.1989238574627024e-06 loss: 0.0291 (0.0306) time: 3.1591 data: 0.0089 max mem: 33370 +Epoch: [38] [ 160/1319] eta: 1:01:28 lr: 3.18734520389202e-06 loss: 0.0281 (0.0303) time: 3.1778 data: 0.0090 max mem: 33370 +Epoch: [38] [ 170/1319] eta: 1:00:55 lr: 3.175761874897778e-06 loss: 0.0270 (0.0302) time: 3.1762 data: 0.0089 max mem: 33370 +Epoch: [38] [ 180/1319] eta: 1:00:26 lr: 3.1641738496285912e-06 loss: 0.0304 (0.0303) time: 3.1927 data: 0.0082 max mem: 33370 +Epoch: [38] [ 190/1319] eta: 0:59:54 lr: 3.1525811070548283e-06 loss: 0.0293 (0.0303) time: 3.2011 data: 0.0082 max mem: 33370 +Epoch: [38] [ 200/1319] eta: 0:59:21 lr: 3.1409836259663234e-06 loss: 0.0264 (0.0301) time: 3.1796 data: 0.0087 max mem: 33370 +Epoch: [38] [ 210/1319] eta: 0:58:49 lr: 3.1293813849701203e-06 loss: 0.0264 (0.0300) time: 3.1674 data: 0.0089 max mem: 33370 +Epoch: [38] [ 220/1319] eta: 0:58:17 lr: 3.1177743624881108e-06 loss: 0.0278 (0.0301) time: 3.1742 data: 0.0092 max mem: 33370 +Epoch: [38] [ 230/1319] eta: 0:57:43 lr: 3.1061625367546658e-06 loss: 0.0249 (0.0298) time: 3.1597 data: 0.0093 max mem: 33370 +Epoch: [38] [ 240/1319] eta: 0:57:13 lr: 3.0945458858142194e-06 loss: 0.0255 (0.0299) time: 3.1772 data: 0.0090 max mem: 33370 +Epoch: [38] [ 250/1319] eta: 0:56:40 lr: 3.08292438751882e-06 loss: 0.0318 (0.0300) time: 3.1931 data: 0.0086 max mem: 33370 +Epoch: [38] [ 260/1319] eta: 0:56:10 lr: 3.071298019525602e-06 loss: 0.0320 (0.0301) time: 3.1916 data: 0.0081 max mem: 33370 +Epoch: [38] [ 270/1319] eta: 0:55:36 lr: 3.0596667592942867e-06 loss: 0.0298 (0.0301) time: 3.1676 data: 0.0080 max mem: 33370 +Epoch: [38] [ 280/1319] eta: 0:55:04 lr: 3.048030584084566e-06 loss: 0.0282 (0.0302) time: 3.1543 data: 0.0083 max mem: 33370 +Epoch: [38] [ 290/1319] eta: 0:54:33 lr: 3.036389470953479e-06 loss: 0.0282 (0.0304) time: 3.1972 data: 0.0085 max mem: 33370 +Epoch: [38] [ 300/1319] eta: 0:54:03 lr: 3.024743396752744e-06 loss: 0.0258 (0.0303) time: 3.2098 data: 0.0081 max mem: 33370 +Epoch: [38] [ 310/1319] eta: 0:53:30 lr: 3.013092338126003e-06 loss: 0.0254 (0.0303) time: 3.1937 data: 0.0078 max mem: 33370 +Epoch: [38] [ 320/1319] eta: 0:53:00 lr: 3.0014362715060913e-06 loss: 0.0296 (0.0304) time: 3.2044 data: 0.0083 max mem: 33370 +Epoch: [38] [ 330/1319] eta: 0:52:27 lr: 2.9897751731121923e-06 loss: 0.0300 (0.0305) time: 3.1920 data: 0.0084 max mem: 33370 +Epoch: [38] [ 340/1319] eta: 0:51:57 lr: 2.978109018946967e-06 loss: 0.0287 (0.0305) time: 3.1927 data: 0.0081 max mem: 33370 +Epoch: [38] [ 350/1319] eta: 0:51:26 lr: 2.9664377847936435e-06 loss: 0.0277 (0.0304) time: 3.2288 data: 0.0085 max mem: 33370 +Epoch: [38] [ 360/1319] eta: 0:50:54 lr: 2.954761446213011e-06 loss: 0.0285 (0.0305) time: 3.1890 data: 0.0083 max mem: 33370 +Epoch: [38] [ 370/1319] eta: 0:50:22 lr: 2.943079978540434e-06 loss: 0.0292 (0.0305) time: 3.1781 data: 0.0083 max mem: 33370 +Epoch: [38] [ 380/1319] eta: 0:49:50 lr: 2.931393356882739e-06 loss: 0.0292 (0.0306) time: 3.1771 data: 0.0085 max mem: 33370 +Epoch: [38] [ 390/1319] eta: 0:49:18 lr: 2.919701556115084e-06 loss: 0.0287 (0.0307) time: 3.1769 data: 0.0083 max mem: 33370 +Epoch: [38] [ 400/1319] eta: 0:48:46 lr: 2.908004550877762e-06 loss: 0.0248 (0.0306) time: 3.1873 data: 0.0081 max mem: 33370 +Epoch: [38] [ 410/1319] eta: 0:48:14 lr: 2.8963023155729493e-06 loss: 0.0258 (0.0306) time: 3.1836 data: 0.0082 max mem: 33370 +Epoch: [38] [ 420/1319] eta: 0:47:42 lr: 2.884594824361366e-06 loss: 0.0289 (0.0306) time: 3.1847 data: 0.0083 max mem: 33370 +Epoch: [38] [ 430/1319] eta: 0:47:12 lr: 2.8728820511589384e-06 loss: 0.0289 (0.0306) time: 3.2141 data: 0.0087 max mem: 33370 +Epoch: [38] [ 440/1319] eta: 0:46:40 lr: 2.861163969633332e-06 loss: 0.0272 (0.0305) time: 3.2307 data: 0.0087 max mem: 33370 +Epoch: [38] [ 450/1319] eta: 0:46:08 lr: 2.849440553200456e-06 loss: 0.0260 (0.0304) time: 3.1792 data: 0.0080 max mem: 33370 +Epoch: [38] [ 460/1319] eta: 0:45:36 lr: 2.837711775020899e-06 loss: 0.0277 (0.0304) time: 3.1744 data: 0.0079 max mem: 33370 +Epoch: [38] [ 470/1319] eta: 0:45:04 lr: 2.8259776079962665e-06 loss: 0.0263 (0.0304) time: 3.1756 data: 0.0081 max mem: 33370 +Epoch: [38] [ 480/1319] eta: 0:44:33 lr: 2.814238024765515e-06 loss: 0.0279 (0.0305) time: 3.1884 data: 0.0081 max mem: 33370 +Epoch: [38] [ 490/1319] eta: 0:44:01 lr: 2.8024929977011503e-06 loss: 0.0319 (0.0305) time: 3.2149 data: 0.0079 max mem: 33370 +Epoch: [38] [ 500/1319] eta: 0:43:30 lr: 2.790742498905385e-06 loss: 0.0250 (0.0304) time: 3.2051 data: 0.0078 max mem: 33370 +Epoch: [38] [ 510/1319] eta: 0:42:57 lr: 2.7789865002062234e-06 loss: 0.0251 (0.0304) time: 3.1839 data: 0.0083 max mem: 33370 +Epoch: [38] [ 520/1319] eta: 0:42:26 lr: 2.7672249731534377e-06 loss: 0.0267 (0.0303) time: 3.1848 data: 0.0085 max mem: 33370 +Epoch: [38] [ 530/1319] eta: 0:41:54 lr: 2.7554578890145323e-06 loss: 0.0267 (0.0304) time: 3.2053 data: 0.0080 max mem: 33370 +Epoch: [38] [ 540/1319] eta: 0:41:22 lr: 2.7436852187705646e-06 loss: 0.0264 (0.0303) time: 3.1953 data: 0.0080 max mem: 33370 +Epoch: [38] [ 550/1319] eta: 0:40:48 lr: 2.7319069331119135e-06 loss: 0.0264 (0.0302) time: 3.1137 data: 0.0084 max mem: 33370 +Epoch: [38] [ 560/1319] eta: 0:40:16 lr: 2.7201230024339627e-06 loss: 0.0283 (0.0302) time: 3.1073 data: 0.0085 max mem: 33370 +Epoch: [38] [ 570/1319] eta: 0:39:45 lr: 2.7083333968327037e-06 loss: 0.0278 (0.0302) time: 3.1984 data: 0.0080 max mem: 33370 +Epoch: [38] [ 580/1319] eta: 0:39:13 lr: 2.696538086100214e-06 loss: 0.0282 (0.0302) time: 3.2010 data: 0.0080 max mem: 33370 +Epoch: [38] [ 590/1319] eta: 0:38:41 lr: 2.6847370397201204e-06 loss: 0.0282 (0.0301) time: 3.1716 data: 0.0080 max mem: 33370 +Epoch: [38] [ 600/1319] eta: 0:38:09 lr: 2.6729302268628987e-06 loss: 0.0308 (0.0303) time: 3.1706 data: 0.0080 max mem: 33370 +Epoch: [38] [ 610/1319] eta: 0:37:37 lr: 2.6611176163811112e-06 loss: 0.0364 (0.0303) time: 3.1853 data: 0.0082 max mem: 33370 +Epoch: [38] [ 620/1319] eta: 0:37:06 lr: 2.6492991768045523e-06 loss: 0.0290 (0.0303) time: 3.2075 data: 0.0078 max mem: 33370 +Epoch: [38] [ 630/1319] eta: 0:36:34 lr: 2.637474876335259e-06 loss: 0.0275 (0.0302) time: 3.2235 data: 0.0075 max mem: 33370 +Epoch: [38] [ 640/1319] eta: 0:36:02 lr: 2.6256446828424878e-06 loss: 0.0304 (0.0302) time: 3.1874 data: 0.0079 max mem: 33370 +Epoch: [38] [ 650/1319] eta: 0:35:30 lr: 2.613808563857519e-06 loss: 0.0307 (0.0303) time: 3.1618 data: 0.0080 max mem: 33370 +Epoch: [38] [ 660/1319] eta: 0:34:58 lr: 2.6019664865683917e-06 loss: 0.0276 (0.0302) time: 3.1806 data: 0.0081 max mem: 33370 +Epoch: [38] [ 670/1319] eta: 0:34:27 lr: 2.590118417814524e-06 loss: 0.0265 (0.0302) time: 3.2206 data: 0.0082 max mem: 33370 +Epoch: [38] [ 680/1319] eta: 0:33:56 lr: 2.5782643240811925e-06 loss: 0.0286 (0.0303) time: 3.2265 data: 0.0084 max mem: 33370 +Epoch: [38] [ 690/1319] eta: 0:33:24 lr: 2.566404171493961e-06 loss: 0.0316 (0.0304) time: 3.1995 data: 0.0086 max mem: 33370 +Epoch: [38] [ 700/1319] eta: 0:32:52 lr: 2.5545379258129243e-06 loss: 0.0271 (0.0303) time: 3.1731 data: 0.0084 max mem: 33370 +Epoch: [38] [ 710/1319] eta: 0:32:19 lr: 2.5426655524268633e-06 loss: 0.0244 (0.0303) time: 3.1434 data: 0.0085 max mem: 33370 +Epoch: [38] [ 720/1319] eta: 0:31:47 lr: 2.5307870163472715e-06 loss: 0.0244 (0.0302) time: 3.1552 data: 0.0084 max mem: 33370 +Epoch: [38] [ 730/1319] eta: 0:31:15 lr: 2.5189022822022593e-06 loss: 0.0262 (0.0302) time: 3.1575 data: 0.0080 max mem: 33370 +Epoch: [38] [ 740/1319] eta: 0:30:44 lr: 2.5070113142302914e-06 loss: 0.0286 (0.0302) time: 3.1857 data: 0.0079 max mem: 33370 +Epoch: [38] [ 750/1319] eta: 0:30:11 lr: 2.495114076273858e-06 loss: 0.0292 (0.0302) time: 3.1792 data: 0.0078 max mem: 33370 +Epoch: [38] [ 760/1319] eta: 0:29:39 lr: 2.483210531772943e-06 loss: 0.0274 (0.0302) time: 3.1331 data: 0.0078 max mem: 33370 +Epoch: [38] [ 770/1319] eta: 0:29:07 lr: 2.4713006437583777e-06 loss: 0.0265 (0.0302) time: 3.1394 data: 0.0082 max mem: 33370 +Epoch: [38] [ 780/1319] eta: 0:28:35 lr: 2.4593843748450576e-06 loss: 0.0269 (0.0302) time: 3.1407 data: 0.0086 max mem: 33370 +Epoch: [38] [ 790/1319] eta: 0:28:03 lr: 2.447461687224963e-06 loss: 0.0279 (0.0302) time: 3.1651 data: 0.0089 max mem: 33370 +Epoch: [38] [ 800/1319] eta: 0:27:31 lr: 2.4355325426601037e-06 loss: 0.0299 (0.0302) time: 3.1562 data: 0.0085 max mem: 33370 +Epoch: [38] [ 810/1319] eta: 0:26:59 lr: 2.423596902475233e-06 loss: 0.0269 (0.0302) time: 3.1534 data: 0.0079 max mem: 33370 +Epoch: [38] [ 820/1319] eta: 0:26:27 lr: 2.4116547275504333e-06 loss: 0.0276 (0.0303) time: 3.1576 data: 0.0076 max mem: 33370 +Epoch: [38] [ 830/1319] eta: 0:25:55 lr: 2.3997059783135262e-06 loss: 0.0273 (0.0302) time: 3.1697 data: 0.0075 max mem: 33370 +Epoch: [38] [ 840/1319] eta: 0:25:23 lr: 2.38775061473232e-06 loss: 0.0273 (0.0302) time: 3.1807 data: 0.0082 max mem: 33370 +Epoch: [38] [ 850/1319] eta: 0:24:52 lr: 2.3757885963066428e-06 loss: 0.0293 (0.0302) time: 3.1738 data: 0.0086 max mem: 33370 +Epoch: [38] [ 860/1319] eta: 0:24:20 lr: 2.3638198820602614e-06 loss: 0.0255 (0.0301) time: 3.1701 data: 0.0088 max mem: 33370 +Epoch: [38] [ 870/1319] eta: 0:23:48 lr: 2.351844430532552e-06 loss: 0.0257 (0.0302) time: 3.1719 data: 0.0085 max mem: 33370 +Epoch: [38] [ 880/1319] eta: 0:23:16 lr: 2.339862199770001e-06 loss: 0.0288 (0.0302) time: 3.1826 data: 0.0080 max mem: 33370 +Epoch: [38] [ 890/1319] eta: 0:22:44 lr: 2.327873147317513e-06 loss: 0.0281 (0.0302) time: 3.1896 data: 0.0079 max mem: 33370 +Epoch: [38] [ 900/1319] eta: 0:22:13 lr: 2.315877230209485e-06 loss: 0.0285 (0.0302) time: 3.1970 data: 0.0077 max mem: 33370 +Epoch: [38] [ 910/1319] eta: 0:21:41 lr: 2.303874404960728e-06 loss: 0.0280 (0.0301) time: 3.1863 data: 0.0078 max mem: 33370 +Epoch: [38] [ 920/1319] eta: 0:21:09 lr: 2.291864627557113e-06 loss: 0.0276 (0.0302) time: 3.1804 data: 0.0080 max mem: 33370 +Epoch: [38] [ 930/1319] eta: 0:20:37 lr: 2.2798478534460264e-06 loss: 0.0292 (0.0302) time: 3.1842 data: 0.0084 max mem: 33370 +Epoch: [38] [ 940/1319] eta: 0:20:05 lr: 2.2678240375265906e-06 loss: 0.0291 (0.0301) time: 3.2027 data: 0.0082 max mem: 33370 +Epoch: [38] [ 950/1319] eta: 0:19:34 lr: 2.25579313413962e-06 loss: 0.0279 (0.0302) time: 3.2105 data: 0.0081 max mem: 33370 +Epoch: [38] [ 960/1319] eta: 0:19:02 lr: 2.243755097057401e-06 loss: 0.0268 (0.0301) time: 3.1828 data: 0.0083 max mem: 33370 +Epoch: [38] [ 970/1319] eta: 0:18:30 lr: 2.2317098794731506e-06 loss: 0.0261 (0.0302) time: 3.1615 data: 0.0085 max mem: 33370 +Epoch: [38] [ 980/1319] eta: 0:17:58 lr: 2.2196574339902486e-06 loss: 0.0338 (0.0303) time: 3.1487 data: 0.0091 max mem: 33370 +Epoch: [38] [ 990/1319] eta: 0:17:26 lr: 2.2075977126112046e-06 loss: 0.0362 (0.0303) time: 3.1726 data: 0.0083 max mem: 33370 +Epoch: [38] [1000/1319] eta: 0:16:54 lr: 2.195530666726346e-06 loss: 0.0348 (0.0304) time: 3.1983 data: 0.0076 max mem: 33370 +Epoch: [38] [1010/1319] eta: 0:16:23 lr: 2.183456247102197e-06 loss: 0.0274 (0.0304) time: 3.1765 data: 0.0075 max mem: 33370 +Epoch: [38] [1020/1319] eta: 0:15:51 lr: 2.1713744038696293e-06 loss: 0.0273 (0.0304) time: 3.1988 data: 0.0076 max mem: 33370 +Epoch: [38] [1030/1319] eta: 0:15:19 lr: 2.1592850865116445e-06 loss: 0.0281 (0.0304) time: 3.1861 data: 0.0080 max mem: 33370 +Epoch: [38] [1040/1319] eta: 0:14:47 lr: 2.1471882438508782e-06 loss: 0.0305 (0.0305) time: 3.1643 data: 0.0082 max mem: 33370 +Epoch: [38] [1050/1319] eta: 0:14:15 lr: 2.135083824036786e-06 loss: 0.0309 (0.0305) time: 3.1904 data: 0.0079 max mem: 33370 +Epoch: [38] [1060/1319] eta: 0:13:44 lr: 2.1229717745324578e-06 loss: 0.0265 (0.0304) time: 3.1804 data: 0.0079 max mem: 33370 +Epoch: [38] [1070/1319] eta: 0:13:12 lr: 2.110852042101167e-06 loss: 0.0273 (0.0304) time: 3.1795 data: 0.0081 max mem: 33370 +Epoch: [38] [1080/1319] eta: 0:12:40 lr: 2.0987245727924905e-06 loss: 0.0247 (0.0304) time: 3.1757 data: 0.0084 max mem: 33370 +Epoch: [38] [1090/1319] eta: 0:12:08 lr: 2.086589311928101e-06 loss: 0.0242 (0.0304) time: 3.1843 data: 0.0085 max mem: 33370 +Epoch: [38] [1100/1319] eta: 0:11:36 lr: 2.074446204087186e-06 loss: 0.0289 (0.0304) time: 3.1865 data: 0.0082 max mem: 33370 +Epoch: [38] [1110/1319] eta: 0:11:04 lr: 2.062295193091432e-06 loss: 0.0289 (0.0304) time: 3.1815 data: 0.0080 max mem: 33370 +Epoch: [38] [1120/1319] eta: 0:10:33 lr: 2.050136221989693e-06 loss: 0.0290 (0.0304) time: 3.1559 data: 0.0080 max mem: 33370 +Epoch: [38] [1130/1319] eta: 0:10:01 lr: 2.0379692330421533e-06 loss: 0.0315 (0.0304) time: 3.1571 data: 0.0083 max mem: 33370 +Epoch: [38] [1140/1319] eta: 0:09:29 lr: 2.0257941677041134e-06 loss: 0.0301 (0.0304) time: 3.1856 data: 0.0082 max mem: 33370 +Epoch: [38] [1150/1319] eta: 0:08:57 lr: 2.013610966609312e-06 loss: 0.0288 (0.0304) time: 3.1947 data: 0.0081 max mem: 33370 +Epoch: [38] [1160/1319] eta: 0:08:25 lr: 2.0014195695528014e-06 loss: 0.0298 (0.0304) time: 3.2081 data: 0.0086 max mem: 33370 +Epoch: [38] [1170/1319] eta: 0:07:54 lr: 1.9892199154733075e-06 loss: 0.0270 (0.0304) time: 3.1794 data: 0.0087 max mem: 33370 +Epoch: [38] [1180/1319] eta: 0:07:22 lr: 1.977011942435173e-06 loss: 0.0277 (0.0304) time: 3.1645 data: 0.0086 max mem: 33370 +Epoch: [38] [1190/1319] eta: 0:06:50 lr: 1.964795587609718e-06 loss: 0.0282 (0.0304) time: 3.1769 data: 0.0080 max mem: 33370 +Epoch: [38] [1200/1319] eta: 0:06:18 lr: 1.9525707872561044e-06 loss: 0.0265 (0.0303) time: 3.1766 data: 0.0077 max mem: 33370 +Epoch: [38] [1210/1319] eta: 0:05:46 lr: 1.9403374767016633e-06 loss: 0.0282 (0.0304) time: 3.1804 data: 0.0078 max mem: 33370 +Epoch: [38] [1220/1319] eta: 0:05:14 lr: 1.928095590321611e-06 loss: 0.0300 (0.0304) time: 3.1881 data: 0.0080 max mem: 33370 +Epoch: [38] [1230/1319] eta: 0:04:43 lr: 1.915845061518256e-06 loss: 0.0282 (0.0303) time: 3.1906 data: 0.0083 max mem: 33370 +Epoch: [38] [1240/1319] eta: 0:04:11 lr: 1.9035858226995284e-06 loss: 0.0246 (0.0303) time: 3.1940 data: 0.0083 max mem: 33370 +Epoch: [38] [1250/1319] eta: 0:03:39 lr: 1.8913178052569088e-06 loss: 0.0260 (0.0303) time: 3.1879 data: 0.0082 max mem: 33370 +Epoch: [38] [1260/1319] eta: 0:03:07 lr: 1.8790409395427117e-06 loss: 0.0324 (0.0303) time: 3.1918 data: 0.0081 max mem: 33370 +Epoch: [38] [1270/1319] eta: 0:02:35 lr: 1.8667551548466507e-06 loss: 0.0310 (0.0303) time: 3.1883 data: 0.0078 max mem: 33370 +Epoch: [38] [1280/1319] eta: 0:02:04 lr: 1.8544603793717773e-06 loss: 0.0310 (0.0303) time: 3.1943 data: 0.0077 max mem: 33370 +Epoch: [38] [1290/1319] eta: 0:01:32 lr: 1.8421565402096163e-06 loss: 0.0279 (0.0303) time: 3.1811 data: 0.0076 max mem: 33370 +Epoch: [38] [1300/1319] eta: 0:01:00 lr: 1.8298435633145817e-06 loss: 0.0276 (0.0304) time: 3.1812 data: 0.0078 max mem: 33370 +Epoch: [38] [1310/1319] eta: 0:00:28 lr: 1.8175213734776007e-06 loss: 0.0281 (0.0303) time: 3.1757 data: 0.0077 max mem: 33370 +Epoch: [38] Total time: 1:09:57 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 2:15:25 time: 3.1578 data: 2.9471 max mem: 33370 +Test: [ 100/2573] eta: 0:04:25 time: 0.0775 data: 0.0016 max mem: 33370 +Test: [ 200/2573] eta: 0:03:41 time: 0.0783 data: 0.0015 max mem: 33370 +Test: [ 300/2573] eta: 0:03:20 time: 0.0811 data: 0.0017 max mem: 33370 +Test: [ 400/2573] eta: 0:03:06 time: 0.0812 data: 0.0014 max mem: 33370 +Test: [ 500/2573] eta: 0:02:55 time: 0.0798 data: 0.0015 max mem: 33370 +Test: [ 600/2573] eta: 0:02:45 time: 0.0786 data: 0.0015 max mem: 33370 +Test: [ 700/2573] eta: 0:02:36 time: 0.0795 data: 0.0015 max mem: 33370 +Test: [ 800/2573] eta: 0:02:27 time: 0.0818 data: 0.0014 max mem: 33370 +Test: [ 900/2573] eta: 0:02:18 time: 0.0794 data: 0.0014 max mem: 33370 +Test: [1000/2573] eta: 0:02:09 time: 0.0793 data: 0.0014 max mem: 33370 +Test: [1100/2573] eta: 0:02:00 time: 0.0794 data: 0.0014 max mem: 33370 +Test: [1200/2573] eta: 0:01:52 time: 0.0799 data: 0.0014 max mem: 33370 +Test: [1300/2573] eta: 0:01:44 time: 0.0793 data: 0.0015 max mem: 33370 +Test: [1400/2573] eta: 0:01:35 time: 0.0779 data: 0.0014 max mem: 33370 +Test: [1500/2573] eta: 0:01:27 time: 0.0807 data: 0.0015 max mem: 33370 +Test: [1600/2573] eta: 0:01:19 time: 0.0819 data: 0.0014 max mem: 33370 +Test: [1700/2573] eta: 0:01:10 time: 0.0780 data: 0.0014 max mem: 33370 +Test: [1800/2573] eta: 0:01:02 time: 0.0805 data: 0.0014 max mem: 33370 +Test: [1900/2573] eta: 0:00:54 time: 0.0785 data: 0.0016 max mem: 33370 +Test: [2000/2573] eta: 0:00:46 time: 0.0797 data: 0.0015 max mem: 33370 +Test: [2100/2573] eta: 0:00:38 time: 0.0806 data: 0.0014 max mem: 33370 +Test: [2200/2573] eta: 0:00:30 time: 0.0805 data: 0.0014 max mem: 33370 +Test: [2300/2573] eta: 0:00:22 time: 0.0803 data: 0.0014 max mem: 33370 +Test: [2400/2573] eta: 0:00:13 time: 0.0755 data: 0.0014 max mem: 33370 +Test: [2500/2573] eta: 0:00:05 time: 0.0796 data: 0.0015 max mem: 33370 +Test: Total time: 0:03:27 +Final results: +Mean IoU is 65.29 + + precision@0.5 = 72.86 + precision@0.6 = 68.04 + precision@0.7 = 61.13 + precision@0.8 = 50.25 + precision@0.9 = 25.78 + overall IoU = 62.75 + +Average object IoU 65.29175459849841 +Overall IoU 62.749183654785156 +Better epoch: 38 + +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Epoch: [39] [ 0/1319] eta: 1:51:05 lr: 1.8064234624396156e-06 loss: 0.0319 (0.0319) time: 5.0534 data: 1.6114 max mem: 33370 +Epoch: [39] [ 10/1319] eta: 1:13:06 lr: 1.7940835565249508e-06 loss: 0.0269 (0.0265) time: 3.3513 data: 0.1536 max mem: 33370 +Epoch: [39] [ 20/1319] eta: 1:11:06 lr: 1.7817342127276263e-06 loss: 0.0256 (0.0323) time: 3.1956 data: 0.0073 max mem: 33370 +Epoch: [39] [ 30/1319] eta: 1:09:35 lr: 1.7693753510331764e-06 loss: 0.0264 (0.0312) time: 3.1774 data: 0.0074 max mem: 33370 +Epoch: [39] [ 40/1319] eta: 1:08:53 lr: 1.757006890122028e-06 loss: 0.0296 (0.0319) time: 3.1768 data: 0.0080 max mem: 33370 +Epoch: [39] [ 50/1319] eta: 1:08:17 lr: 1.7446287473378005e-06 loss: 0.0305 (0.0311) time: 3.2137 data: 0.0081 max mem: 33370 +Epoch: [39] [ 60/1319] eta: 1:07:28 lr: 1.7322408386546176e-06 loss: 0.0291 (0.0315) time: 3.1836 data: 0.0083 max mem: 33370 +Epoch: [39] [ 70/1319] eta: 1:06:57 lr: 1.7198430786433514e-06 loss: 0.0313 (0.0311) time: 3.1833 data: 0.0084 max mem: 33370 +Epoch: [39] [ 80/1319] eta: 1:06:19 lr: 1.7074353804367206e-06 loss: 0.0308 (0.0317) time: 3.2001 data: 0.0081 max mem: 33370 +Epoch: [39] [ 90/1319] eta: 1:05:48 lr: 1.6950176556933094e-06 loss: 0.0280 (0.0314) time: 3.2022 data: 0.0076 max mem: 33370 +Epoch: [39] [ 100/1319] eta: 1:05:06 lr: 1.682589814560305e-06 loss: 0.0320 (0.0317) time: 3.1733 data: 0.0080 max mem: 33370 +Epoch: [39] [ 110/1319] eta: 1:04:35 lr: 1.6701517656350208e-06 loss: 0.0311 (0.0313) time: 3.1718 data: 0.0085 max mem: 33370 +Epoch: [39] [ 120/1319] eta: 1:03:53 lr: 1.6577034159251048e-06 loss: 0.0256 (0.0314) time: 3.1637 data: 0.0091 max mem: 33370 +Epoch: [39] [ 130/1319] eta: 1:03:21 lr: 1.6452446708073954e-06 loss: 0.0291 (0.0316) time: 3.1514 data: 0.0094 max mem: 33370 +Epoch: [39] [ 140/1319] eta: 1:02:49 lr: 1.632775433985313e-06 loss: 0.0293 (0.0314) time: 3.1957 data: 0.0093 max mem: 33370 +Epoch: [39] [ 150/1319] eta: 1:02:12 lr: 1.62029560744485e-06 loss: 0.0290 (0.0311) time: 3.1651 data: 0.0089 max mem: 33370 +Epoch: [39] [ 160/1319] eta: 1:01:40 lr: 1.6078050914089353e-06 loss: 0.0283 (0.0310) time: 3.1599 data: 0.0080 max mem: 33370 +Epoch: [39] [ 170/1319] eta: 1:01:07 lr: 1.5953037842902214e-06 loss: 0.0294 (0.0311) time: 3.1818 data: 0.0078 max mem: 33370 +Epoch: [39] [ 180/1319] eta: 1:00:34 lr: 1.5827915826421849e-06 loss: 0.0338 (0.0324) time: 3.1799 data: 0.0085 max mem: 33370 +Epoch: [39] [ 190/1319] eta: 1:00:04 lr: 1.5702683811084266e-06 loss: 0.0322 (0.0322) time: 3.2001 data: 0.0088 max mem: 33370 +Epoch: [39] [ 200/1319] eta: 0:59:31 lr: 1.5577340723702017e-06 loss: 0.0284 (0.0324) time: 3.1921 data: 0.0084 max mem: 33370 +Epoch: [39] [ 210/1319] eta: 0:58:58 lr: 1.5451885470919527e-06 loss: 0.0275 (0.0324) time: 3.1730 data: 0.0083 max mem: 33370 +Epoch: [39] [ 220/1319] eta: 0:58:24 lr: 1.5326316938648584e-06 loss: 0.0275 (0.0323) time: 3.1677 data: 0.0084 max mem: 33370 +Epoch: [39] [ 230/1319] eta: 0:57:52 lr: 1.5200633991482792e-06 loss: 0.0278 (0.0321) time: 3.1672 data: 0.0084 max mem: 33370 +Epoch: [39] [ 240/1319] eta: 0:57:23 lr: 1.5074835472089545e-06 loss: 0.0248 (0.0318) time: 3.2181 data: 0.0085 max mem: 33370 +Epoch: [39] [ 250/1319] eta: 0:56:48 lr: 1.4948920200579605e-06 loss: 0.0238 (0.0317) time: 3.1911 data: 0.0085 max mem: 33370 +Epoch: [39] [ 260/1319] eta: 0:56:16 lr: 1.4822886973851744e-06 loss: 0.0289 (0.0317) time: 3.1503 data: 0.0083 max mem: 33370 +Epoch: [39] [ 270/1319] eta: 0:55:43 lr: 1.4696734564912314e-06 loss: 0.0289 (0.0316) time: 3.1630 data: 0.0082 max mem: 33370 +Epoch: [39] [ 280/1319] eta: 0:55:08 lr: 1.457046172216814e-06 loss: 0.0294 (0.0316) time: 3.1233 data: 0.0082 max mem: 33370 +Epoch: [39] [ 290/1319] eta: 0:54:34 lr: 1.444406716869153e-06 loss: 0.0294 (0.0317) time: 3.1181 data: 0.0083 max mem: 33370 +Epoch: [39] [ 300/1319] eta: 0:54:03 lr: 1.4317549601455566e-06 loss: 0.0295 (0.0317) time: 3.1652 data: 0.0081 max mem: 33370 +Epoch: [39] [ 310/1319] eta: 0:53:32 lr: 1.419090769053936e-06 loss: 0.0323 (0.0318) time: 3.2067 data: 0.0077 max mem: 33370 +Epoch: [39] [ 320/1319] eta: 0:52:58 lr: 1.4064140078300187e-06 loss: 0.0307 (0.0317) time: 3.1720 data: 0.0081 max mem: 33370 +Epoch: [39] [ 330/1319] eta: 0:52:26 lr: 1.3937245378511972e-06 loss: 0.0277 (0.0316) time: 3.1479 data: 0.0084 max mem: 33370 +Epoch: [39] [ 340/1319] eta: 0:51:54 lr: 1.3810222175468009e-06 loss: 0.0277 (0.0316) time: 3.1720 data: 0.0081 max mem: 33370 +Epoch: [39] [ 350/1319] eta: 0:51:20 lr: 1.3683069023045655e-06 loss: 0.0284 (0.0316) time: 3.1436 data: 0.0083 max mem: 33370 +Epoch: [39] [ 360/1319] eta: 0:50:49 lr: 1.355578444373217e-06 loss: 0.0267 (0.0314) time: 3.1627 data: 0.0083 max mem: 33370 +Epoch: [39] [ 370/1319] eta: 0:50:18 lr: 1.3428366927608033e-06 loss: 0.0264 (0.0314) time: 3.2062 data: 0.0084 max mem: 33370 +Epoch: [39] [ 380/1319] eta: 0:49:46 lr: 1.330081493128668e-06 loss: 0.0263 (0.0313) time: 3.1907 data: 0.0083 max mem: 33370 +Epoch: [39] [ 390/1319] eta: 0:49:15 lr: 1.3173126876807778e-06 loss: 0.0256 (0.0313) time: 3.1906 data: 0.0082 max mem: 33370 +Epoch: [39] [ 400/1319] eta: 0:48:44 lr: 1.304530115048165e-06 loss: 0.0292 (0.0313) time: 3.2095 data: 0.0085 max mem: 33370 +Epoch: [39] [ 410/1319] eta: 0:48:13 lr: 1.2917336101681678e-06 loss: 0.0292 (0.0313) time: 3.2142 data: 0.0084 max mem: 33370 +Epoch: [39] [ 420/1319] eta: 0:47:41 lr: 1.2789230041582899e-06 loss: 0.0253 (0.0312) time: 3.2057 data: 0.0081 max mem: 33370 +Epoch: [39] [ 430/1319] eta: 0:47:10 lr: 1.2660981241842216e-06 loss: 0.0267 (0.0311) time: 3.1960 data: 0.0082 max mem: 33370 +Epoch: [39] [ 440/1319] eta: 0:46:38 lr: 1.2532587933218004e-06 loss: 0.0268 (0.0311) time: 3.2021 data: 0.0082 max mem: 33370 +Epoch: [39] [ 450/1319] eta: 0:46:06 lr: 1.2404048304125217e-06 loss: 0.0301 (0.0311) time: 3.1756 data: 0.0079 max mem: 33370 +Epoch: [39] [ 460/1319] eta: 0:45:34 lr: 1.2275360499121832e-06 loss: 0.0320 (0.0312) time: 3.1664 data: 0.0080 max mem: 33370 +Epoch: [39] [ 470/1319] eta: 0:45:02 lr: 1.2146522617323656e-06 loss: 0.0324 (0.0311) time: 3.1670 data: 0.0079 max mem: 33370 +Epoch: [39] [ 480/1319] eta: 0:44:30 lr: 1.2017532710741682e-06 loss: 0.0280 (0.0311) time: 3.1674 data: 0.0078 max mem: 33370 +Epoch: [39] [ 490/1319] eta: 0:43:58 lr: 1.1888388782538434e-06 loss: 0.0253 (0.0310) time: 3.1903 data: 0.0083 max mem: 33370 +Epoch: [39] [ 500/1319] eta: 0:43:27 lr: 1.175908878519789e-06 loss: 0.0257 (0.0310) time: 3.2024 data: 0.0087 max mem: 33370 +Epoch: [39] [ 510/1319] eta: 0:42:55 lr: 1.1629630618603247e-06 loss: 0.0273 (0.0310) time: 3.2015 data: 0.0084 max mem: 33370 +Epoch: [39] [ 520/1319] eta: 0:42:22 lr: 1.150001212801783e-06 loss: 0.0294 (0.0310) time: 3.1583 data: 0.0081 max mem: 33370 +Epoch: [39] [ 530/1319] eta: 0:41:50 lr: 1.1370231101961411e-06 loss: 0.0291 (0.0310) time: 3.1349 data: 0.0080 max mem: 33370 +Epoch: [39] [ 540/1319] eta: 0:41:18 lr: 1.1240285269976361e-06 loss: 0.0268 (0.0311) time: 3.1687 data: 0.0080 max mem: 33370 +Epoch: [39] [ 550/1319] eta: 0:40:46 lr: 1.1110172300275867e-06 loss: 0.0312 (0.0311) time: 3.1696 data: 0.0082 max mem: 33370 +Epoch: [39] [ 560/1319] eta: 0:40:14 lr: 1.097988979726662e-06 loss: 0.0301 (0.0311) time: 3.1669 data: 0.0089 max mem: 33370 +Epoch: [39] [ 570/1319] eta: 0:39:42 lr: 1.084943529893699e-06 loss: 0.0271 (0.0310) time: 3.1755 data: 0.0086 max mem: 33370 +Epoch: [39] [ 580/1319] eta: 0:39:11 lr: 1.0718806274102695e-06 loss: 0.0269 (0.0310) time: 3.1765 data: 0.0082 max mem: 33370 +Epoch: [39] [ 590/1319] eta: 0:38:39 lr: 1.0588000119498569e-06 loss: 0.0284 (0.0310) time: 3.1964 data: 0.0083 max mem: 33370 +Epoch: [39] [ 600/1319] eta: 0:38:07 lr: 1.0457014156706775e-06 loss: 0.0278 (0.0309) time: 3.1890 data: 0.0079 max mem: 33370 +Epoch: [39] [ 610/1319] eta: 0:37:36 lr: 1.032584562890946e-06 loss: 0.0261 (0.0309) time: 3.1994 data: 0.0079 max mem: 33370 +Epoch: [39] [ 620/1319] eta: 0:37:04 lr: 1.0194491697452832e-06 loss: 0.0289 (0.0309) time: 3.2109 data: 0.0083 max mem: 33370 +Epoch: [39] [ 630/1319] eta: 0:36:32 lr: 1.0062949438209979e-06 loss: 0.0294 (0.0309) time: 3.1863 data: 0.0080 max mem: 33370 +Epoch: [39] [ 640/1319] eta: 0:36:00 lr: 9.931215837725994e-07 loss: 0.0288 (0.0309) time: 3.1828 data: 0.0079 max mem: 33370 +Epoch: [39] [ 650/1319] eta: 0:35:29 lr: 9.799287789130144e-07 loss: 0.0281 (0.0309) time: 3.2039 data: 0.0081 max mem: 33370 +Epoch: [39] [ 660/1319] eta: 0:34:57 lr: 9.667162087796925e-07 loss: 0.0293 (0.0309) time: 3.1807 data: 0.0081 max mem: 33370 +Epoch: [39] [ 670/1319] eta: 0:34:25 lr: 9.534835426736097e-07 loss: 0.0304 (0.0309) time: 3.1556 data: 0.0083 max mem: 33370 +Epoch: [39] [ 680/1319] eta: 0:33:53 lr: 9.402304391691554e-07 loss: 0.0288 (0.0308) time: 3.2015 data: 0.0084 max mem: 33370 +Epoch: [39] [ 690/1319] eta: 0:33:22 lr: 9.269565455924141e-07 loss: 0.0280 (0.0308) time: 3.2157 data: 0.0082 max mem: 33370 +Epoch: [39] [ 700/1319] eta: 0:32:50 lr: 9.136614974653884e-07 loss: 0.0284 (0.0308) time: 3.1897 data: 0.0081 max mem: 33370 +Epoch: [39] [ 710/1319] eta: 0:32:18 lr: 9.003449179133091e-07 loss: 0.0287 (0.0308) time: 3.1913 data: 0.0080 max mem: 33370 +Epoch: [39] [ 720/1319] eta: 0:31:47 lr: 8.870064170319405e-07 loss: 0.0285 (0.0308) time: 3.1985 data: 0.0080 max mem: 33370 +Epoch: [39] [ 730/1319] eta: 0:31:14 lr: 8.736455912114245e-07 loss: 0.0278 (0.0307) time: 3.1790 data: 0.0081 max mem: 33370 +Epoch: [39] [ 740/1319] eta: 0:30:43 lr: 8.602620224130043e-07 loss: 0.0278 (0.0308) time: 3.1895 data: 0.0081 max mem: 33370 +Epoch: [39] [ 750/1319] eta: 0:30:11 lr: 8.468552773943076e-07 loss: 0.0316 (0.0307) time: 3.2090 data: 0.0086 max mem: 33370 +Epoch: [39] [ 760/1319] eta: 0:29:39 lr: 8.334249068786857e-07 loss: 0.0275 (0.0307) time: 3.1856 data: 0.0089 max mem: 33370 +Epoch: [39] [ 770/1319] eta: 0:29:07 lr: 8.199704446634483e-07 loss: 0.0272 (0.0307) time: 3.1572 data: 0.0083 max mem: 33370 +Epoch: [39] [ 780/1319] eta: 0:28:35 lr: 8.064914066612595e-07 loss: 0.0282 (0.0307) time: 3.1515 data: 0.0078 max mem: 33370 +Epoch: [39] [ 790/1319] eta: 0:28:03 lr: 7.92987289868475e-07 loss: 0.0330 (0.0307) time: 3.1596 data: 0.0077 max mem: 33370 +Epoch: [39] [ 800/1319] eta: 0:27:31 lr: 7.79457571253187e-07 loss: 0.0336 (0.0308) time: 3.1635 data: 0.0080 max mem: 33370 +Epoch: [39] [ 810/1319] eta: 0:27:00 lr: 7.659017065551902e-07 loss: 0.0330 (0.0308) time: 3.2008 data: 0.0084 max mem: 33370 +Epoch: [39] [ 820/1319] eta: 0:26:28 lr: 7.523191289889679e-07 loss: 0.0329 (0.0308) time: 3.1774 data: 0.0085 max mem: 33370 +Epoch: [39] [ 830/1319] eta: 0:25:56 lr: 7.387092478397154e-07 loss: 0.0266 (0.0308) time: 3.1556 data: 0.0081 max mem: 33370 +Epoch: [39] [ 840/1319] eta: 0:25:24 lr: 7.250714469413284e-07 loss: 0.0266 (0.0308) time: 3.1620 data: 0.0077 max mem: 33370 +Epoch: [39] [ 850/1319] eta: 0:24:52 lr: 7.114050830235778e-07 loss: 0.0273 (0.0307) time: 3.1682 data: 0.0081 max mem: 33370 +Epoch: [39] [ 860/1319] eta: 0:24:20 lr: 6.977094839143229e-07 loss: 0.0290 (0.0308) time: 3.1950 data: 0.0086 max mem: 33370 +Epoch: [39] [ 870/1319] eta: 0:23:48 lr: 6.839839465805414e-07 loss: 0.0290 (0.0307) time: 3.1819 data: 0.0083 max mem: 33370 +Epoch: [39] [ 880/1319] eta: 0:23:17 lr: 6.702277349898191e-07 loss: 0.0271 (0.0307) time: 3.2087 data: 0.0078 max mem: 33370 +Epoch: [39] [ 890/1319] eta: 0:22:45 lr: 6.564400777713066e-07 loss: 0.0300 (0.0307) time: 3.1992 data: 0.0079 max mem: 33370 +Epoch: [39] [ 900/1319] eta: 0:22:13 lr: 6.426201656523381e-07 loss: 0.0337 (0.0307) time: 3.1683 data: 0.0080 max mem: 33370 +Epoch: [39] [ 910/1319] eta: 0:21:41 lr: 6.287671486431178e-07 loss: 0.0298 (0.0308) time: 3.1651 data: 0.0079 max mem: 33370 +Epoch: [39] [ 920/1319] eta: 0:21:09 lr: 6.148801329380617e-07 loss: 0.0279 (0.0307) time: 3.1576 data: 0.0083 max mem: 33370 +Epoch: [39] [ 930/1319] eta: 0:20:37 lr: 6.009581774973726e-07 loss: 0.0273 (0.0307) time: 3.1630 data: 0.0083 max mem: 33370 +Epoch: [39] [ 940/1319] eta: 0:20:05 lr: 5.870002902666957e-07 loss: 0.0259 (0.0307) time: 3.1546 data: 0.0080 max mem: 33370 +Epoch: [39] [ 950/1319] eta: 0:19:34 lr: 5.7300542398606e-07 loss: 0.0253 (0.0306) time: 3.2020 data: 0.0083 max mem: 33370 +Epoch: [39] [ 960/1319] eta: 0:19:02 lr: 5.589724715308914e-07 loss: 0.0273 (0.0306) time: 3.2183 data: 0.0079 max mem: 33370 +Epoch: [39] [ 970/1319] eta: 0:18:30 lr: 5.449002607184345e-07 loss: 0.0279 (0.0306) time: 3.2132 data: 0.0075 max mem: 33370 +Epoch: [39] [ 980/1319] eta: 0:17:58 lr: 5.307875485010082e-07 loss: 0.0292 (0.0306) time: 3.1970 data: 0.0079 max mem: 33370 +Epoch: [39] [ 990/1319] eta: 0:17:26 lr: 5.166330144533874e-07 loss: 0.0307 (0.0306) time: 3.1545 data: 0.0087 max mem: 33370 +Epoch: [39] [1000/1319] eta: 0:16:55 lr: 5.024352534442401e-07 loss: 0.0284 (0.0306) time: 3.1777 data: 0.0084 max mem: 33370 +Epoch: [39] [1010/1319] eta: 0:16:23 lr: 4.881927673605746e-07 loss: 0.0284 (0.0306) time: 3.1621 data: 0.0082 max mem: 33370 +Epoch: [39] [1020/1319] eta: 0:15:51 lr: 4.7390395572780197e-07 loss: 0.0272 (0.0305) time: 3.1642 data: 0.0084 max mem: 33370 +Epoch: [39] [1030/1319] eta: 0:15:19 lr: 4.595671050360423e-07 loss: 0.0260 (0.0305) time: 3.2167 data: 0.0084 max mem: 33370 +Epoch: [39] [1040/1319] eta: 0:14:47 lr: 4.4518037654287396e-07 loss: 0.0269 (0.0305) time: 3.1960 data: 0.0087 max mem: 33370 +Epoch: [39] [1050/1319] eta: 0:14:16 lr: 4.3074179227215756e-07 loss: 0.0277 (0.0305) time: 3.1706 data: 0.0083 max mem: 33370 +Epoch: [39] [1060/1319] eta: 0:13:44 lr: 4.162492188647174e-07 loss: 0.0285 (0.0305) time: 3.1939 data: 0.0076 max mem: 33370 +Epoch: [39] [1070/1319] eta: 0:13:12 lr: 4.01700348854669e-07 loss: 0.0293 (0.0305) time: 3.2130 data: 0.0078 max mem: 33370 +Epoch: [39] [1080/1319] eta: 0:12:40 lr: 3.8709267884030336e-07 loss: 0.0282 (0.0305) time: 3.1983 data: 0.0082 max mem: 33370 +Epoch: [39] [1090/1319] eta: 0:12:08 lr: 3.724234838815835e-07 loss: 0.0296 (0.0305) time: 3.1811 data: 0.0083 max mem: 33370 +Epoch: [39] [1100/1319] eta: 0:11:36 lr: 3.5768978727688177e-07 loss: 0.0306 (0.0305) time: 3.1607 data: 0.0085 max mem: 33370 +Epoch: [39] [1110/1319] eta: 0:11:05 lr: 3.428883246336122e-07 loss: 0.0269 (0.0305) time: 3.1510 data: 0.0086 max mem: 33370 +Epoch: [39] [1120/1319] eta: 0:10:33 lr: 3.280155008272766e-07 loss: 0.0269 (0.0305) time: 3.1727 data: 0.0081 max mem: 33370 +Epoch: [39] [1130/1319] eta: 0:10:01 lr: 3.1306733800860497e-07 loss: 0.0300 (0.0305) time: 3.1566 data: 0.0080 max mem: 33370 +Epoch: [39] [1140/1319] eta: 0:09:29 lr: 2.9803941221786203e-07 loss: 0.0294 (0.0305) time: 3.1465 data: 0.0080 max mem: 33370 +Epoch: [39] [1150/1319] eta: 0:08:57 lr: 2.829267753240405e-07 loss: 0.0264 (0.0306) time: 3.1389 data: 0.0077 max mem: 33370 +Epoch: [39] [1160/1319] eta: 0:08:25 lr: 2.677238578071334e-07 loss: 0.0264 (0.0305) time: 3.1244 data: 0.0078 max mem: 33370 +Epoch: [39] [1170/1319] eta: 0:07:53 lr: 2.524243461593822e-07 loss: 0.0257 (0.0305) time: 3.1747 data: 0.0081 max mem: 33370 +Epoch: [39] [1180/1319] eta: 0:07:22 lr: 2.370210260957732e-07 loss: 0.0261 (0.0305) time: 3.1765 data: 0.0086 max mem: 33370 +Epoch: [39] [1190/1319] eta: 0:06:50 lr: 2.2150557883672493e-07 loss: 0.0277 (0.0305) time: 3.1590 data: 0.0083 max mem: 33370 +Epoch: [39] [1200/1319] eta: 0:06:18 lr: 2.058683115970694e-07 loss: 0.0275 (0.0304) time: 3.2046 data: 0.0082 max mem: 33370 +Epoch: [39] [1210/1319] eta: 0:05:46 lr: 1.9009779355624344e-07 loss: 0.0256 (0.0305) time: 3.2234 data: 0.0084 max mem: 33370 +Epoch: [39] [1220/1319] eta: 0:05:14 lr: 1.7418035215766808e-07 loss: 0.0247 (0.0304) time: 3.2183 data: 0.0081 max mem: 33370 +Epoch: [39] [1230/1319] eta: 0:04:43 lr: 1.5809935607220197e-07 loss: 0.0244 (0.0304) time: 3.1803 data: 0.0081 max mem: 33370 +Epoch: [39] [1240/1319] eta: 0:04:11 lr: 1.4183415922236583e-07 loss: 0.0256 (0.0304) time: 3.1672 data: 0.0083 max mem: 33370 +Epoch: [39] [1250/1319] eta: 0:03:39 lr: 1.2535848000328487e-07 loss: 0.0290 (0.0304) time: 3.1859 data: 0.0085 max mem: 33370 +Epoch: [39] [1260/1319] eta: 0:03:07 lr: 1.0863778202227116e-07 loss: 0.0281 (0.0304) time: 3.1700 data: 0.0082 max mem: 33370 +Epoch: [39] [1270/1319] eta: 0:02:35 lr: 9.162475150165058e-08 loss: 0.0303 (0.0304) time: 3.1698 data: 0.0076 max mem: 33370 +Epoch: [39] [1280/1319] eta: 0:02:04 lr: 7.425076510067331e-08 loss: 0.0299 (0.0304) time: 3.1674 data: 0.0076 max mem: 33370 +Epoch: [39] [1290/1319] eta: 0:01:32 lr: 5.640763927216541e-08 loss: 0.0315 (0.0305) time: 3.1858 data: 0.0082 max mem: 33370 +Epoch: [39] [1300/1319] eta: 0:01:00 lr: 3.790015191412361e-08 loss: 0.0290 (0.0304) time: 3.1730 data: 0.0084 max mem: 33370 +Epoch: [39] [1310/1319] eta: 0:00:28 lr: 1.8267397722216235e-08 loss: 0.0271 (0.0304) time: 3.1714 data: 0.0080 max mem: 33370 +Epoch: [39] Total time: 1:09:56 +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/2573] eta: 2:13:58 time: 3.1240 data: 3.0336 max mem: 33370 +Test: [ 100/2573] eta: 0:04:27 time: 0.0778 data: 0.0016 max mem: 33370 +Test: [ 200/2573] eta: 0:03:42 time: 0.0781 data: 0.0014 max mem: 33370 +Test: [ 300/2573] eta: 0:03:20 time: 0.0801 data: 0.0015 max mem: 33370 +Test: [ 400/2573] eta: 0:03:06 time: 0.0810 data: 0.0015 max mem: 33370 +Test: [ 500/2573] eta: 0:02:55 time: 0.0799 data: 0.0015 max mem: 33370 +Test: [ 600/2573] eta: 0:02:45 time: 0.0791 data: 0.0015 max mem: 33370 +Test: [ 700/2573] eta: 0:02:36 time: 0.0796 data: 0.0014 max mem: 33370 +Test: [ 800/2573] eta: 0:02:27 time: 0.0822 data: 0.0014 max mem: 33370 +Test: [ 900/2573] eta: 0:02:18 time: 0.0788 data: 0.0014 max mem: 33370 +Test: [1000/2573] eta: 0:02:09 time: 0.0788 data: 0.0014 max mem: 33370 +Test: [1100/2573] eta: 0:02:00 time: 0.0798 data: 0.0015 max mem: 33370 +Test: [1200/2573] eta: 0:01:52 time: 0.0797 data: 0.0014 max mem: 33370 +Test: [1300/2573] eta: 0:01:44 time: 0.0798 data: 0.0014 max mem: 33370 +Test: [1400/2573] eta: 0:01:35 time: 0.0790 data: 0.0015 max mem: 33370 +Test: [1500/2573] eta: 0:01:27 time: 0.0810 data: 0.0015 max mem: 33370 +Test: [1600/2573] eta: 0:01:19 time: 0.0831 data: 0.0016 max mem: 33370 +Test: [1700/2573] eta: 0:01:11 time: 0.0771 data: 0.0013 max mem: 33370 +Test: [1800/2573] eta: 0:01:02 time: 0.0812 data: 0.0014 max mem: 33370 +Test: [1900/2573] eta: 0:00:54 time: 0.0780 data: 0.0014 max mem: 33370 +Test: [2000/2573] eta: 0:00:46 time: 0.0797 data: 0.0015 max mem: 33370 +Test: [2100/2573] eta: 0:00:38 time: 0.0817 data: 0.0015 max mem: 33370 +Test: [2200/2573] eta: 0:00:30 time: 0.0815 data: 0.0015 max mem: 33370 +Test: [2300/2573] eta: 0:00:22 time: 0.0817 data: 0.0014 max mem: 33370 +Test: [2400/2573] eta: 0:00:13 time: 0.0766 data: 0.0015 max mem: 33370 +Test: [2500/2573] eta: 0:00:05 time: 0.0821 data: 0.0018 max mem: 33370 +Test: Total time: 0:03:27 +Final results: +Mean IoU is 65.21 + + precision@0.5 = 72.88 + precision@0.6 = 68.14 + precision@0.7 = 61.36 + precision@0.8 = 50.02 + precision@0.9 = 25.78 + overall IoU = 62.70 + +Average object IoU 65.20913224353279 +Overall IoU 62.69542694091797 +Training time 2 days, 0:59:10 diff --git a/LAVT-RIS/logs/rzom_m10_mg12_tmp007_4gpu_bs32_ang.log b/LAVT-RIS/logs/rzom_m10_mg12_tmp007_4gpu_bs32_ang.log new file mode 100644 index 0000000000000000000000000000000000000000..cecc799d59957a0894f1e53e0481768e4b7eabbe --- /dev/null +++ b/LAVT-RIS/logs/rzom_m10_mg12_tmp007_4gpu_bs32_ang.log @@ -0,0 +1,18046 @@ +[2025-01-26 10:05:13,178] torch.distributed.run: [WARNING] +[2025-01-26 10:05:13,178] torch.distributed.run: [WARNING] ***************************************** +[2025-01-26 10:05:13,178] torch.distributed.run: [WARNING] Setting OMP_NUM_THREADS environment variable for each process to be 1 in default, to avoid your system being overloaded, please further tune the variable for optimal performance in your application as needed. +[2025-01-26 10:05:13,178] torch.distributed.run: [WARNING] ***************************************** +/home/chaeyun/.conda/envs/risall/lib/python3.9/site-packages/timm/models/layers/__init__.py:48: FutureWarning: Importing from timm.models.layers is deprecated, please import via timm.layers + warnings.warn(f"Importing from {__name__} is deprecated, please import via timm.layers", FutureWarning) +/home/chaeyun/.conda/envs/risall/lib/python3.9/site-packages/timm/models/layers/__init__.py:48: FutureWarning: Importing from timm.models.layers is deprecated, please import via timm.layers + warnings.warn(f"Importing from {__name__} is deprecated, please import via timm.layers", FutureWarning) +/home/chaeyun/.conda/envs/risall/lib/python3.9/site-packages/timm/models/layers/__init__.py:48: FutureWarning: Importing from timm.models.layers is deprecated, please import via timm.layers + warnings.warn(f"Importing from {__name__} is deprecated, please import via timm.layers", FutureWarning) +/home/chaeyun/.conda/envs/risall/lib/python3.9/site-packages/timm/models/layers/__init__.py:48: FutureWarning: Importing from timm.models.layers is deprecated, please import via timm.layers + warnings.warn(f"Importing from {__name__} is deprecated, please import via timm.layers", FutureWarning) +Local Rank: 2, World Size: 4 +RANK and WORLD_SIZE in environment: 2/4 +Local Rank: 0, World Size: 4 +RANK and WORLD_SIZE in environment: 0/4 +Local Rank: 3, World Size: 4 +RANK and WORLD_SIZE in environment: 3/4 +Local Rank: 1, World Size: 4 +RANK and WORLD_SIZE in environment: 1/4 +Image size: 480 +Metric Learning Ops +metric learning flag : True +metric loss weight : 0.1 +metric mode and hardpos selection : hardpos_only naive +margin value : 12.0 +temperature : 0.07 +add zero in ACE loss : False +Namespace(amsgrad=False, batch_size=8, bert_tokenizer='bert-base-uncased', ck_bert='bert-base-uncased', dataset='ref-zom', ddp_trained_weights=False, device='cuda:0', epochs=40, fusion_drop=0.0, img_size=480, lr=5e-05, mha='', model='lavt_one', model_id='rzom_m10_mg12_tmp007_4gpu_bs32_ang', output_dir='./models/rzom_m10_mg12_tmp007_4gpu_bs32_ang', pin_mem=False, pretrained_swin_weights='./pretrained_weights/swin_base_patch4_window12_384_22k.pth', print_freq=10, refer_data_root='./refer/data/', resume='', split='test', splitBy='final', swin_type='base', weight_decay=0.01, window12=False, workers=8, metric_learning=True, metric_loss_weight=0.1, metric_mode='hardpos_only', exclude_multiobj=True, hn_prob=0.0, hp_selection='naive', margin_value=12.0, temperature=0.07, addzero=False, local_rank=0) +loading dataset ref-zom into memory... +loading dataset split final +creating index... +index created. +DONE (t=7.16s) +loading dataset ref-zom into memory... +loading dataset split final +creating index... +index created. +DONE (t=8.48s) +/home/chaeyun/.conda/envs/risall/lib/python3.9/site-packages/torch/functional.py:504: UserWarning: torch.meshgrid: in an upcoming release, it will be required to pass the indexing argument. (Triggered internally at ../aten/src/ATen/native/TensorShape.cpp:3526.) + return _VF.meshgrid(tensors, **kwargs) # type: ignore[attr-defined] +/home/chaeyun/.conda/envs/risall/lib/python3.9/site-packages/torch/functional.py:504: UserWarning: torch.meshgrid: in an upcoming release, it will be required to pass the indexing argument. (Triggered internally at ../aten/src/ATen/native/TensorShape.cpp:3526.) + return _VF.meshgrid(tensors, **kwargs) # type: ignore[attr-defined] +local rank 0 / global rank 0 successfully built train dataset. +lavt_one +Window size 12! +/home/chaeyun/.conda/envs/risall/lib/python3.9/site-packages/torch/functional.py:504: UserWarning: torch.meshgrid: in an upcoming release, it will be required to pass the indexing argument. (Triggered internally at ../aten/src/ATen/native/TensorShape.cpp:3526.) + return _VF.meshgrid(tensors, **kwargs) # type: ignore[attr-defined] +/home/chaeyun/.conda/envs/risall/lib/python3.9/site-packages/torch/functional.py:504: UserWarning: torch.meshgrid: in an upcoming release, it will be required to pass the indexing argument. (Triggered internally at ../aten/src/ATen/native/TensorShape.cpp:3526.) + return _VF.meshgrid(tensors, **kwargs) # type: ignore[attr-defined] +Initializing Multi-modal Swin Transformer weights from ./pretrained_weights/swin_base_patch4_window12_384_22k.pth +Epoch: [0] [ 0/2138] eta: 4:33:14 lr: 4.99994738069889e-05 loss: 0.6161 (0.6161) time: 7.6683 data: 3.1897 max mem: 17438 +Epoch: [0] [ 10/2138] eta: 1:53:43 lr: 4.999421184303536e-05 loss: 0.5275 (0.5376) time: 3.2064 data: 0.2917 max mem: 19771 +Epoch: [0] [ 20/2138] eta: 1:45:39 lr: 4.998894981754451e-05 loss: 0.4947 (0.4953) time: 2.7594 data: 0.0015 max mem: 19775 +Epoch: [0] [ 30/2138] eta: 1:42:35 lr: 4.998368773050842e-05 loss: 0.4036 (0.4545) time: 2.7622 data: 0.0015 max mem: 19775 +Epoch: [0] [ 40/2138] eta: 1:40:44 lr: 4.997842558191917e-05 loss: 0.3545 (0.4217) time: 2.7632 data: 0.0020 max mem: 19775 +Epoch: [0] [ 50/2138] eta: 1:39:34 lr: 4.9973163371768835e-05 loss: 0.2920 (0.3960) time: 2.7711 data: 0.0020 max mem: 19777 +Epoch: [0] [ 60/2138] eta: 1:38:38 lr: 4.9967901100049515e-05 loss: 0.2867 (0.3836) time: 2.7805 data: 0.0021 max mem: 19777 +Epoch: [0] [ 70/2138] eta: 1:37:49 lr: 4.996263876675326e-05 loss: 0.2930 (0.3703) time: 2.7788 data: 0.0022 max mem: 19778 +Epoch: [0] [ 80/2138] eta: 1:37:05 lr: 4.995737637187215e-05 loss: 0.2930 (0.3603) time: 2.7776 data: 0.0023 max mem: 19778 +Epoch: [0] [ 90/2138] eta: 1:36:25 lr: 4.995211391539826e-05 loss: 0.2750 (0.3505) time: 2.7775 data: 0.0024 max mem: 19778 +Epoch: [0] [ 100/2138] eta: 1:35:49 lr: 4.994685139732366e-05 loss: 0.2613 (0.3436) time: 2.7826 data: 0.0023 max mem: 19780 +Epoch: [0] [ 110/2138] eta: 1:35:12 lr: 4.994158881764041e-05 loss: 0.2567 (0.3387) time: 2.7804 data: 0.0023 max mem: 19780 +Epoch: [0] [ 120/2138] eta: 1:34:37 lr: 4.993632617634058e-05 loss: 0.2567 (0.3314) time: 2.7753 data: 0.0022 max mem: 19780 +Epoch: [0] [ 130/2138] eta: 1:34:03 lr: 4.9931063473416234e-05 loss: 0.2462 (0.3262) time: 2.7764 data: 0.0021 max mem: 19780 +Epoch: [0] [ 140/2138] eta: 1:33:31 lr: 4.992580070885944e-05 loss: 0.2543 (0.3247) time: 2.7767 data: 0.0021 max mem: 19782 +Epoch: [0] [ 150/2138] eta: 1:33:02 lr: 4.9920537882662235e-05 loss: 0.2879 (0.3213) time: 2.7910 data: 0.0021 max mem: 19783 +Epoch: [0] [ 160/2138] eta: 1:32:28 lr: 4.9915274994816705e-05 loss: 0.2506 (0.3159) time: 2.7841 data: 0.0022 max mem: 19783 +Epoch: [0] [ 170/2138] eta: 1:31:56 lr: 4.991001204531489e-05 loss: 0.2571 (0.3151) time: 2.7660 data: 0.0023 max mem: 19783 +Epoch: [0] [ 180/2138] eta: 1:31:23 lr: 4.990474903414884e-05 loss: 0.2599 (0.3118) time: 2.7637 data: 0.0023 max mem: 19785 +Epoch: [0] [ 190/2138] eta: 1:30:52 lr: 4.989948596131061e-05 loss: 0.2467 (0.3085) time: 2.7648 data: 0.0023 max mem: 19785 +Epoch: [0] [ 200/2138] eta: 1:30:23 lr: 4.9894222826792256e-05 loss: 0.2321 (0.3045) time: 2.7772 data: 0.0022 max mem: 19785 +Epoch: [0] [ 210/2138] eta: 1:29:52 lr: 4.988895963058582e-05 loss: 0.2107 (0.3010) time: 2.7748 data: 0.0021 max mem: 19785 +Epoch: [0] [ 220/2138] eta: 1:29:21 lr: 4.988369637268335e-05 loss: 0.2157 (0.2992) time: 2.7669 data: 0.0021 max mem: 19785 +Epoch: [0] [ 230/2138] eta: 1:28:51 lr: 4.987843305307689e-05 loss: 0.2383 (0.2968) time: 2.7657 data: 0.0022 max mem: 19785 +Epoch: [0] [ 240/2138] eta: 1:28:20 lr: 4.987316967175848e-05 loss: 0.2383 (0.2937) time: 2.7617 data: 0.0023 max mem: 19785 +Epoch: [0] [ 250/2138] eta: 1:27:51 lr: 4.986790622872016e-05 loss: 0.2437 (0.2917) time: 2.7685 data: 0.0021 max mem: 19785 +Epoch: [0] [ 260/2138] eta: 1:27:22 lr: 4.986264272395396e-05 loss: 0.2349 (0.2898) time: 2.7783 data: 0.0021 max mem: 19786 +Epoch: [0] [ 270/2138] eta: 1:26:53 lr: 4.9857379157451936e-05 loss: 0.2307 (0.2882) time: 2.7761 data: 0.0022 max mem: 19786 +Epoch: [0] [ 280/2138] eta: 1:26:24 lr: 4.98521155292061e-05 loss: 0.2054 (0.2851) time: 2.7759 data: 0.0021 max mem: 19786 +Epoch: [0] [ 290/2138] eta: 1:25:56 lr: 4.9846851839208495e-05 loss: 0.1962 (0.2841) time: 2.7782 data: 0.0021 max mem: 19786 +Epoch: [0] [ 300/2138] eta: 1:25:28 lr: 4.984158808745115e-05 loss: 0.2410 (0.2833) time: 2.7858 data: 0.0022 max mem: 19786 +Epoch: [0] [ 310/2138] eta: 1:25:00 lr: 4.98363242739261e-05 loss: 0.2147 (0.2808) time: 2.7934 data: 0.0024 max mem: 19788 +Epoch: [0] [ 320/2138] eta: 1:24:31 lr: 4.9831060398625355e-05 loss: 0.2044 (0.2787) time: 2.7810 data: 0.0026 max mem: 19788 +Epoch: [0] [ 330/2138] eta: 1:24:02 lr: 4.982579646154096e-05 loss: 0.2167 (0.2774) time: 2.7726 data: 0.0025 max mem: 19788 +Epoch: [0] [ 340/2138] eta: 1:23:33 lr: 4.982053246266491e-05 loss: 0.2188 (0.2757) time: 2.7731 data: 0.0023 max mem: 19788 +Epoch: [0] [ 350/2138] eta: 1:23:05 lr: 4.981526840198925e-05 loss: 0.2177 (0.2740) time: 2.7756 data: 0.0026 max mem: 19788 +Epoch: [0] [ 360/2138] eta: 1:22:37 lr: 4.981000427950598e-05 loss: 0.2183 (0.2727) time: 2.7814 data: 0.0027 max mem: 19788 +Epoch: [0] [ 370/2138] eta: 1:22:08 lr: 4.9804740095207144e-05 loss: 0.2255 (0.2718) time: 2.7762 data: 0.0026 max mem: 19788 +Epoch: [0] [ 380/2138] eta: 1:21:39 lr: 4.979947584908472e-05 loss: 0.2267 (0.2707) time: 2.7674 data: 0.0023 max mem: 19788 +Epoch: [0] [ 390/2138] eta: 1:21:11 lr: 4.979421154113075e-05 loss: 0.2126 (0.2698) time: 2.7682 data: 0.0024 max mem: 19788 +Epoch: [0] [ 400/2138] eta: 1:20:43 lr: 4.978894717133722e-05 loss: 0.2244 (0.2688) time: 2.7756 data: 0.0024 max mem: 19788 +Epoch: [0] [ 410/2138] eta: 1:20:14 lr: 4.978368273969616e-05 loss: 0.2260 (0.2679) time: 2.7805 data: 0.0024 max mem: 19788 +Epoch: [0] [ 420/2138] eta: 1:19:47 lr: 4.977841824619955e-05 loss: 0.2197 (0.2666) time: 2.7847 data: 0.0023 max mem: 19788 +Epoch: [0] [ 430/2138] eta: 1:19:19 lr: 4.977315369083943e-05 loss: 0.1861 (0.2648) time: 2.7856 data: 0.0025 max mem: 19788 +Epoch: [0] [ 440/2138] eta: 1:18:51 lr: 4.976788907360778e-05 loss: 0.1937 (0.2638) time: 2.7810 data: 0.0025 max mem: 19788 +Epoch: [0] [ 450/2138] eta: 1:18:23 lr: 4.97626243944966e-05 loss: 0.2023 (0.2625) time: 2.7840 data: 0.0022 max mem: 19788 +Epoch: [0] [ 460/2138] eta: 1:17:55 lr: 4.9757359653497886e-05 loss: 0.1830 (0.2610) time: 2.7869 data: 0.0025 max mem: 19788 +Epoch: [0] [ 470/2138] eta: 1:17:27 lr: 4.9752094850603656e-05 loss: 0.1893 (0.2596) time: 2.7851 data: 0.0026 max mem: 19788 +Epoch: [0] [ 480/2138] eta: 1:16:59 lr: 4.9746829985805874e-05 loss: 0.2017 (0.2589) time: 2.7849 data: 0.0026 max mem: 19788 +Epoch: [0] [ 490/2138] eta: 1:16:31 lr: 4.974156505909656e-05 loss: 0.2109 (0.2576) time: 2.7895 data: 0.0026 max mem: 19788 +Epoch: [0] [ 500/2138] eta: 1:16:04 lr: 4.9736300070467686e-05 loss: 0.2041 (0.2570) time: 2.7927 data: 0.0023 max mem: 19788 +Epoch: [0] [ 510/2138] eta: 1:15:35 lr: 4.973103501991126e-05 loss: 0.2041 (0.2566) time: 2.7802 data: 0.0022 max mem: 19788 +Epoch: [0] [ 520/2138] eta: 1:15:07 lr: 4.972576990741924e-05 loss: 0.1983 (0.2555) time: 2.7719 data: 0.0024 max mem: 19788 +Epoch: [0] [ 530/2138] eta: 1:14:39 lr: 4.972050473298364e-05 loss: 0.1974 (0.2545) time: 2.7763 data: 0.0024 max mem: 19788 +Epoch: [0] [ 540/2138] eta: 1:14:11 lr: 4.9715239496596424e-05 loss: 0.1977 (0.2533) time: 2.7827 data: 0.0024 max mem: 19788 +Epoch: [0] [ 550/2138] eta: 1:13:43 lr: 4.970997419824958e-05 loss: 0.2087 (0.2530) time: 2.7849 data: 0.0026 max mem: 19788 +Epoch: [0] [ 560/2138] eta: 1:13:15 lr: 4.970470883793508e-05 loss: 0.2098 (0.2522) time: 2.7772 data: 0.0025 max mem: 19788 +Epoch: [0] [ 570/2138] eta: 1:12:47 lr: 4.9699443415644907e-05 loss: 0.2068 (0.2517) time: 2.7738 data: 0.0024 max mem: 19788 +Epoch: [0] [ 580/2138] eta: 1:12:19 lr: 4.969417793137104e-05 loss: 0.1897 (0.2505) time: 2.7731 data: 0.0022 max mem: 19788 +Epoch: [0] [ 590/2138] eta: 1:11:51 lr: 4.968891238510544e-05 loss: 0.1907 (0.2499) time: 2.7733 data: 0.0025 max mem: 19788 +Epoch: [0] [ 600/2138] eta: 1:11:23 lr: 4.9683646776840085e-05 loss: 0.1915 (0.2492) time: 2.7785 data: 0.0026 max mem: 19788 +Epoch: [0] [ 610/2138] eta: 1:10:55 lr: 4.967838110656694e-05 loss: 0.1762 (0.2482) time: 2.7825 data: 0.0021 max mem: 19788 +Epoch: [0] [ 620/2138] eta: 1:10:27 lr: 4.9673115374277986e-05 loss: 0.1987 (0.2479) time: 2.7846 data: 0.0020 max mem: 19788 +Epoch: [0] [ 630/2138] eta: 1:09:59 lr: 4.9667849579965166e-05 loss: 0.2010 (0.2472) time: 2.7880 data: 0.0021 max mem: 19788 +Epoch: [0] [ 640/2138] eta: 1:09:32 lr: 4.966258372362045e-05 loss: 0.1863 (0.2464) time: 2.7953 data: 0.0022 max mem: 19788 +Epoch: [0] [ 650/2138] eta: 1:09:04 lr: 4.965731780523581e-05 loss: 0.1798 (0.2457) time: 2.7960 data: 0.0024 max mem: 19788 +Epoch: [0] [ 660/2138] eta: 1:08:36 lr: 4.9652051824803196e-05 loss: 0.1851 (0.2449) time: 2.7840 data: 0.0023 max mem: 19788 +Epoch: [0] [ 670/2138] eta: 1:08:08 lr: 4.964678578231457e-05 loss: 0.1851 (0.2442) time: 2.7742 data: 0.0022 max mem: 19788 +Epoch: [0] [ 680/2138] eta: 1:07:40 lr: 4.964151967776187e-05 loss: 0.1862 (0.2434) time: 2.7751 data: 0.0023 max mem: 19788 +Epoch: [0] [ 690/2138] eta: 1:07:12 lr: 4.963625351113707e-05 loss: 0.1651 (0.2425) time: 2.7801 data: 0.0023 max mem: 19788 +Epoch: [0] [ 700/2138] eta: 1:06:44 lr: 4.9630987282432115e-05 loss: 0.1618 (0.2416) time: 2.7842 data: 0.0024 max mem: 19788 +Epoch: [0] [ 710/2138] eta: 1:06:16 lr: 4.9625720991638944e-05 loss: 0.1836 (0.2414) time: 2.7750 data: 0.0023 max mem: 19788 +Epoch: [0] [ 720/2138] eta: 1:05:48 lr: 4.962045463874952e-05 loss: 0.1881 (0.2409) time: 2.7653 data: 0.0021 max mem: 19788 +Epoch: [0] [ 730/2138] eta: 1:05:19 lr: 4.9615188223755774e-05 loss: 0.1765 (0.2399) time: 2.7668 data: 0.0019 max mem: 19788 +Epoch: [0] [ 740/2138] eta: 1:04:51 lr: 4.9609921746649655e-05 loss: 0.1680 (0.2393) time: 2.7691 data: 0.0023 max mem: 19788 +Epoch: [0] [ 750/2138] eta: 1:04:24 lr: 4.96046552074231e-05 loss: 0.1850 (0.2391) time: 2.7772 data: 0.0028 max mem: 19788 +Epoch: [0] [ 760/2138] eta: 1:03:56 lr: 4.959938860606806e-05 loss: 0.1850 (0.2384) time: 2.7851 data: 0.0025 max mem: 19788 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(0.2227) time: 2.7822 data: 0.0023 max mem: 19788 +Epoch: [0] [1090/2138] eta: 0:48:37 lr: 4.9425555854388825e-05 loss: 0.1720 (0.2223) time: 2.7748 data: 0.0027 max mem: 19788 +Epoch: [0] [1100/2138] eta: 0:48:09 lr: 4.9420287135854343e-05 loss: 0.1697 (0.2221) time: 2.7743 data: 0.0026 max mem: 19788 +Epoch: [0] [1110/2138] eta: 0:47:41 lr: 4.9415018354907973e-05 loss: 0.1697 (0.2217) time: 2.7745 data: 0.0026 max mem: 19788 +Epoch: [0] [1120/2138] eta: 0:47:13 lr: 4.9409749511541564e-05 loss: 0.1600 (0.2212) time: 2.7789 data: 0.0028 max mem: 19788 +Epoch: [0] [1130/2138] eta: 0:46:45 lr: 4.9404480605747e-05 loss: 0.1621 (0.2209) time: 2.7843 data: 0.0026 max mem: 19788 +Epoch: [0] [1140/2138] eta: 0:46:17 lr: 4.939921163751613e-05 loss: 0.1767 (0.2206) time: 2.7794 data: 0.0024 max mem: 19788 +Epoch: [0] [1150/2138] eta: 0:45:49 lr: 4.939394260684083e-05 loss: 0.1660 (0.2204) time: 2.7710 data: 0.0025 max mem: 19788 +Epoch: [0] [1160/2138] eta: 0:45:21 lr: 4.9388673513712936e-05 loss: 0.1612 (0.2199) time: 2.7692 data: 0.0027 max mem: 19788 +Epoch: [0] [1170/2138] eta: 0:44:53 lr: 4.938340435812432e-05 loss: 0.1355 (0.2195) time: 2.7686 data: 0.0026 max mem: 19788 +Epoch: [0] [1180/2138] eta: 0:44:26 lr: 4.9378135140066835e-05 loss: 0.1536 (0.2191) time: 2.7802 data: 0.0025 max mem: 19788 +Epoch: [0] [1190/2138] eta: 0:43:58 lr: 4.937286585953232e-05 loss: 0.1544 (0.2186) time: 2.7866 data: 0.0024 max mem: 19788 +Epoch: [0] [1200/2138] eta: 0:43:30 lr: 4.936759651651265e-05 loss: 0.1463 (0.2179) time: 2.7817 data: 0.0025 max mem: 19788 +Epoch: [0] [1210/2138] eta: 0:43:02 lr: 4.936232711099965e-05 loss: 0.1465 (0.2175) time: 2.7845 data: 0.0024 max mem: 19788 +Epoch: [0] [1220/2138] eta: 0:42:34 lr: 4.935705764298518e-05 loss: 0.1526 (0.2170) time: 2.7883 data: 0.0024 max mem: 19788 +Epoch: [0] [1230/2138] eta: 0:42:07 lr: 4.935178811246108e-05 loss: 0.1611 (0.2167) time: 2.7862 data: 0.0025 max mem: 19788 +Epoch: [0] [1240/2138] eta: 0:41:39 lr: 4.934651851941919e-05 loss: 0.1588 (0.2162) time: 2.7903 data: 0.0023 max mem: 19788 +Epoch: [0] [1250/2138] eta: 0:41:11 lr: 4.934124886385136e-05 loss: 0.1601 (0.2159) time: 2.7942 data: 0.0023 max mem: 19788 +Epoch: [0] [1260/2138] eta: 0:40:43 lr: 4.933597914574942e-05 loss: 0.1620 (0.2155) time: 2.7801 data: 0.0026 max mem: 19788 +Epoch: [0] [1270/2138] eta: 0:40:15 lr: 4.933070936510519e-05 loss: 0.1670 (0.2152) time: 2.7679 data: 0.0029 max mem: 19788 +Epoch: [0] [1280/2138] eta: 0:39:47 lr: 4.9325439521910545e-05 loss: 0.1826 (0.2149) time: 2.7686 data: 0.0030 max mem: 19788 +Epoch: [0] [1290/2138] eta: 0:39:19 lr: 4.9320169616157276e-05 loss: 0.1765 (0.2147) time: 2.7737 data: 0.0025 max mem: 19788 +Epoch: [0] [1300/2138] eta: 0:38:52 lr: 4.9314899647837234e-05 loss: 0.1463 (0.2142) time: 2.7817 data: 0.0021 max mem: 19788 +Epoch: [0] [1310/2138] eta: 0:38:24 lr: 4.9309629616942247e-05 loss: 0.1403 (0.2136) time: 2.7875 data: 0.0021 max mem: 19788 +Epoch: [0] [1320/2138] eta: 0:37:56 lr: 4.930435952346414e-05 loss: 0.1481 (0.2134) time: 2.7806 data: 0.0022 max mem: 19788 +Epoch: [0] [1330/2138] eta: 0:37:28 lr: 4.929908936739473e-05 loss: 0.1798 (0.2131) time: 2.7732 data: 0.0024 max mem: 19788 +Epoch: [0] [1340/2138] eta: 0:37:00 lr: 4.929381914872584e-05 loss: 0.1826 (0.2130) time: 2.7738 data: 0.0026 max mem: 19788 +Epoch: [0] [1350/2138] eta: 0:36:32 lr: 4.928854886744929e-05 loss: 0.1800 (0.2128) time: 2.7743 data: 0.0026 max mem: 19788 +Epoch: [0] [1360/2138] eta: 0:36:04 lr: 4.928327852355691e-05 loss: 0.1692 (0.2126) time: 2.7751 data: 0.0025 max mem: 19788 +Epoch: [0] [1370/2138] eta: 0:35:37 lr: 4.92780081170405e-05 loss: 0.1856 (0.2125) time: 2.7842 data: 0.0025 max mem: 19788 +Epoch: [0] [1380/2138] eta: 0:35:09 lr: 4.9272737647891884e-05 loss: 0.1833 (0.2123) time: 2.7911 data: 0.0023 max mem: 19788 +Epoch: [0] [1390/2138] eta: 0:34:41 lr: 4.926746711610286e-05 loss: 0.1757 (0.2120) time: 2.7913 data: 0.0021 max mem: 19788 +Epoch: [0] [1400/2138] eta: 0:34:13 lr: 4.926219652166526e-05 loss: 0.1558 (0.2116) time: 2.7895 data: 0.0020 max mem: 19788 +Epoch: [0] [1410/2138] eta: 0:33:46 lr: 4.925692586457087e-05 loss: 0.1689 (0.2116) time: 2.7893 data: 0.0020 max mem: 19788 +Epoch: [0] [1420/2138] eta: 0:33:18 lr: 4.925165514481151e-05 loss: 0.1710 (0.2112) time: 2.7887 data: 0.0021 max mem: 19788 +Epoch: [0] [1430/2138] eta: 0:32:50 lr: 4.924638436237898e-05 loss: 0.1616 (0.2110) time: 2.7894 data: 0.0022 max mem: 19788 +Epoch: [0] [1440/2138] eta: 0:32:22 lr: 4.924111351726507e-05 loss: 0.1559 (0.2107) time: 2.7927 data: 0.0021 max mem: 19788 +Epoch: [0] [1450/2138] eta: 0:31:54 lr: 4.9235842609461593e-05 loss: 0.1660 (0.2104) time: 2.7815 data: 0.0023 max mem: 19788 +Epoch: [0] [1460/2138] eta: 0:31:26 lr: 4.923057163896034e-05 loss: 0.1660 (0.2101) time: 2.7682 data: 0.0025 max mem: 19788 +Epoch: [0] [1470/2138] eta: 0:30:58 lr: 4.922530060575311e-05 loss: 0.1477 (0.2097) time: 2.7692 data: 0.0023 max mem: 19788 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mem: 19788 +Epoch: [0] [1560/2138] eta: 0:26:49 lr: 4.917785848376421e-05 loss: 0.1725 (0.2080) time: 2.8390 data: 0.0025 max mem: 19788 +Epoch: [0] [1570/2138] eta: 0:26:21 lr: 4.917258682304548e-05 loss: 0.1608 (0.2078) time: 2.8394 data: 0.0024 max mem: 19788 +Epoch: [0] [1580/2138] eta: 0:25:54 lr: 4.916731509953038e-05 loss: 0.1658 (0.2075) time: 2.8320 data: 0.0024 max mem: 19788 +Epoch: [0] [1590/2138] eta: 0:25:26 lr: 4.916204331321069e-05 loss: 0.1662 (0.2074) time: 2.8289 data: 0.0026 max mem: 19788 +Epoch: [0] [1600/2138] eta: 0:24:58 lr: 4.9156771464078175e-05 loss: 0.1682 (0.2072) time: 2.8414 data: 0.0025 max mem: 19788 +Epoch: [0] [1610/2138] eta: 0:24:31 lr: 4.9151499552124606e-05 loss: 0.1682 (0.2069) time: 2.8363 data: 0.0023 max mem: 19788 +Epoch: [0] [1620/2138] eta: 0:24:03 lr: 4.914622757734173e-05 loss: 0.1664 (0.2066) time: 2.8280 data: 0.0025 max mem: 19788 +Epoch: [0] [1630/2138] eta: 0:23:35 lr: 4.914095553972132e-05 loss: 0.1616 (0.2062) time: 2.8332 data: 0.0024 max mem: 19788 +Epoch: [0] [1640/2138] eta: 0:23:07 lr: 4.913568343925514e-05 loss: 0.1548 (0.2059) time: 2.8396 data: 0.0022 max mem: 19788 +Epoch: [0] [1650/2138] eta: 0:22:40 lr: 4.913041127593495e-05 loss: 0.1551 (0.2056) time: 2.8396 data: 0.0021 max mem: 19788 +Epoch: [0] [1660/2138] eta: 0:22:12 lr: 4.91251390497525e-05 loss: 0.1468 (0.2052) time: 2.8404 data: 0.0020 max mem: 19788 +Epoch: [0] [1670/2138] eta: 0:21:44 lr: 4.9119866760699545e-05 loss: 0.1468 (0.2051) time: 2.8389 data: 0.0021 max mem: 19788 +Epoch: [0] [1680/2138] eta: 0:21:17 lr: 4.911459440876783e-05 loss: 0.1515 (0.2048) time: 2.8380 data: 0.0022 max mem: 19788 +Epoch: [0] [1690/2138] eta: 0:20:49 lr: 4.910932199394912e-05 loss: 0.1417 (0.2045) time: 2.8367 data: 0.0024 max mem: 19788 +Epoch: [0] [1700/2138] eta: 0:20:21 lr: 4.9104049516235157e-05 loss: 0.1417 (0.2042) time: 2.8442 data: 0.0023 max mem: 19788 +Epoch: [0] [1710/2138] eta: 0:19:53 lr: 4.909877697561769e-05 loss: 0.1508 (0.2040) time: 2.8575 data: 0.0023 max mem: 19788 +Epoch: [0] [1720/2138] eta: 0:19:26 lr: 4.9093504372088446e-05 loss: 0.1596 (0.2037) time: 2.8559 data: 0.0026 max mem: 19788 +Epoch: [0] [1730/2138] eta: 0:18:58 lr: 4.908823170563919e-05 loss: 0.1902 (0.2037) time: 2.8653 data: 0.0027 max mem: 19788 +Epoch: [0] [1740/2138] eta: 0:18:30 lr: 4.908295897626164e-05 loss: 0.1505 (0.2033) time: 2.8559 data: 0.0023 max mem: 19788 +Epoch: [0] [1750/2138] eta: 0:18:02 lr: 4.907768618394755e-05 loss: 0.1352 (0.2031) time: 2.8434 data: 0.0021 max mem: 19788 +Epoch: [0] [1760/2138] eta: 0:17:35 lr: 4.907241332868865e-05 loss: 0.1498 (0.2028) time: 2.8567 data: 0.0021 max mem: 19788 +Epoch: [0] [1770/2138] eta: 0:17:07 lr: 4.906714041047668e-05 loss: 0.1546 (0.2027) time: 2.8582 data: 0.0021 max mem: 19788 +Epoch: [0] [1780/2138] eta: 0:16:39 lr: 4.906186742930336e-05 loss: 0.1340 (0.2024) time: 2.8640 data: 0.0021 max mem: 19788 +Epoch: [0] [1790/2138] eta: 0:16:11 lr: 4.9056594385160414e-05 loss: 0.1562 (0.2023) time: 2.8614 data: 0.0022 max mem: 19788 +Epoch: [0] [1800/2138] eta: 0:15:43 lr: 4.9051321278039595e-05 loss: 0.1643 (0.2021) time: 2.8633 data: 0.0023 max mem: 19788 +Epoch: [0] [1810/2138] eta: 0:15:16 lr: 4.904604810793259e-05 loss: 0.1701 (0.2019) time: 2.8736 data: 0.0021 max mem: 19788 +Epoch: [0] [1820/2138] eta: 0:14:48 lr: 4.904077487483117e-05 loss: 0.1525 (0.2016) time: 2.8629 data: 0.0021 max mem: 19788 +Epoch: [0] [1830/2138] eta: 0:14:20 lr: 4.903550157872702e-05 loss: 0.1326 (0.2014) time: 2.8565 data: 0.0023 max mem: 19788 +Epoch: [0] [1840/2138] eta: 0:13:52 lr: 4.9030228219611866e-05 loss: 0.1376 (0.2011) time: 2.8634 data: 0.0025 max mem: 19788 +Epoch: [0] [1850/2138] eta: 0:13:24 lr: 4.902495479747743e-05 loss: 0.1449 (0.2009) time: 2.8674 data: 0.0024 max mem: 19788 +Epoch: [0] [1860/2138] eta: 0:12:57 lr: 4.901968131231543e-05 loss: 0.1475 (0.2007) time: 2.8697 data: 0.0024 max mem: 19788 +Epoch: [0] [1870/2138] eta: 0:12:29 lr: 4.9014407764117565e-05 loss: 0.1510 (0.2006) time: 2.8930 data: 0.0024 max mem: 19788 +Epoch: [0] [1880/2138] eta: 0:12:01 lr: 4.900913415287556e-05 loss: 0.1495 (0.2003) time: 2.9136 data: 0.0024 max mem: 19788 +Epoch: [0] [1890/2138] eta: 0:11:33 lr: 4.9003860478581114e-05 loss: 0.1432 (0.2001) time: 2.9120 data: 0.0024 max mem: 19788 +Epoch: [0] [1900/2138] eta: 0:11:05 lr: 4.8998586741225946e-05 loss: 0.1316 (0.1997) time: 2.9304 data: 0.0023 max mem: 19788 +Epoch: [0] [1910/2138] eta: 0:10:38 lr: 4.899331294080175e-05 loss: 0.1389 (0.1995) time: 2.9315 data: 0.0022 max mem: 19788 +Epoch: [0] [1920/2138] eta: 0:10:10 lr: 4.8988039077300226e-05 loss: 0.1677 (0.1994) time: 2.9063 data: 0.0021 max mem: 19788 +Epoch: [0] [1930/2138] eta: 0:09:42 lr: 4.898276515071307e-05 loss: 0.1924 (0.1994) time: 2.9007 data: 0.0021 max mem: 19788 +Epoch: [0] [1940/2138] eta: 0:09:14 lr: 4.8977491161032e-05 loss: 0.1924 (0.1993) time: 2.9417 data: 0.0025 max mem: 19788 +Epoch: [0] [1950/2138] eta: 0:08:46 lr: 4.89722171082487e-05 loss: 0.1564 (0.1991) time: 2.9386 data: 0.0029 max mem: 19788 +Epoch: [0] [1960/2138] eta: 0:08:18 lr: 4.896694299235486e-05 loss: 0.1525 (0.1990) time: 2.9054 data: 0.0031 max mem: 19788 +Epoch: [0] [1970/2138] eta: 0:07:50 lr: 4.896166881334218e-05 loss: 0.1472 (0.1987) time: 2.9255 data: 0.0032 max mem: 19788 +Epoch: [0] [1980/2138] eta: 0:07:22 lr: 4.895639457120235e-05 loss: 0.1472 (0.1986) time: 2.9150 data: 0.0031 max mem: 19788 +Epoch: [0] [1990/2138] eta: 0:06:54 lr: 4.8951120265927045e-05 loss: 0.1522 (0.1984) time: 2.9218 data: 0.0028 max mem: 19788 +Epoch: [0] [2000/2138] eta: 0:06:26 lr: 4.8945845897507964e-05 loss: 0.1405 (0.1980) time: 2.9227 data: 0.0026 max mem: 19788 +Epoch: [0] [2010/2138] eta: 0:05:58 lr: 4.894057146593678e-05 loss: 0.1140 (0.1979) time: 2.9062 data: 0.0027 max mem: 19788 +Epoch: [0] [2020/2138] eta: 0:05:30 lr: 4.893529697120519e-05 loss: 0.1514 (0.1979) time: 2.9139 data: 0.0025 max mem: 19788 +Epoch: [0] [2030/2138] eta: 0:05:03 lr: 4.8930022413304855e-05 loss: 0.1579 (0.1977) time: 2.9527 data: 0.0024 max mem: 19788 +Epoch: [0] [2040/2138] eta: 0:04:35 lr: 4.892474779222747e-05 loss: 0.1543 (0.1975) time: 2.9777 data: 0.0025 max mem: 19788 +Epoch: [0] [2050/2138] eta: 0:04:07 lr: 4.8919473107964694e-05 loss: 0.1430 (0.1973) time: 2.9319 data: 0.0025 max mem: 19788 +Epoch: [0] [2060/2138] eta: 0:03:39 lr: 4.89141983605082e-05 loss: 0.1455 (0.1972) time: 2.9141 data: 0.0029 max mem: 19788 +Epoch: [0] [2070/2138] eta: 0:03:10 lr: 4.890892354984968e-05 loss: 0.1651 (0.1969) time: 2.9468 data: 0.0029 max mem: 19788 +Epoch: [0] [2080/2138] eta: 0:02:42 lr: 4.890364867598078e-05 loss: 0.1610 (0.1968) time: 2.9396 data: 0.0027 max mem: 19788 +Epoch: [0] [2090/2138] eta: 0:02:14 lr: 4.889837373889318e-05 loss: 0.1678 (0.1968) time: 2.9137 data: 0.0025 max mem: 19788 +Epoch: [0] [2100/2138] eta: 0:01:46 lr: 4.889309873857853e-05 loss: 0.1464 (0.1965) time: 3.0126 data: 0.0026 max mem: 19788 +Epoch: [0] [2110/2138] eta: 0:01:18 lr: 4.8887823675028514e-05 loss: 0.1490 (0.1966) time: 3.0403 data: 0.0025 max mem: 19788 +Epoch: [0] [2120/2138] eta: 0:00:50 lr: 4.888254854823477e-05 loss: 0.1819 (0.1966) time: 2.9344 data: 0.0022 max mem: 19788 +Epoch: [0] [2130/2138] eta: 0:00:22 lr: 4.887727335818898e-05 loss: 0.1780 (0.1966) time: 2.9071 data: 0.0021 max mem: 19788 +Epoch: [0] Total time: 1:40:14 +Test: [ 0/21770] eta: 18:37:48 time: 3.0808 data: 2.7858 max mem: 19788 +Test: [ 100/21770] eta: 0:26:39 time: 0.0429 data: 0.0015 max mem: 19788 +Test: [ 200/21770] eta: 0:21:02 time: 0.0437 data: 0.0015 max mem: 19788 +Test: [ 300/21770] eta: 0:19:31 time: 0.0504 data: 0.0019 max mem: 19788 +Test: [ 400/21770] eta: 0:19:03 time: 0.0516 data: 0.0017 max mem: 19788 +Test: [ 500/21770] eta: 0:18:22 time: 0.0429 data: 0.0015 max mem: 19788 +Test: [ 600/21770] eta: 0:17:58 time: 0.0487 data: 0.0017 max mem: 19788 +Test: [ 700/21770] eta: 0:17:40 time: 0.0431 data: 0.0014 max mem: 19788 +Test: [ 800/21770] eta: 0:17:23 time: 0.0518 data: 0.0018 max mem: 19788 +Test: [ 900/21770] eta: 0:17:12 time: 0.0530 data: 0.0014 max mem: 19788 +Test: [ 1000/21770] eta: 0:16:55 time: 0.0437 data: 0.0015 max mem: 19788 +Test: [ 1100/21770] eta: 0:16:49 time: 0.0487 data: 0.0017 max mem: 19788 +Test: [ 1200/21770] eta: 0:16:44 time: 0.0431 data: 0.0014 max mem: 19788 +Test: [ 1300/21770] eta: 0:16:30 time: 0.0446 data: 0.0014 max mem: 19788 +Test: [ 1400/21770] eta: 0:16:22 time: 0.0447 data: 0.0016 max mem: 19788 +Test: [ 1500/21770] eta: 0:16:12 time: 0.0433 data: 0.0016 max mem: 19788 +Test: [ 1600/21770] eta: 0:16:01 time: 0.0459 data: 0.0015 max mem: 19788 +Test: [ 1700/21770] eta: 0:15:51 time: 0.0428 data: 0.0015 max mem: 19788 +Test: [ 1800/21770] eta: 0:15:47 time: 0.0457 data: 0.0015 max mem: 19788 +Test: [ 1900/21770] eta: 0:15:41 time: 0.0437 data: 0.0015 max mem: 19788 +Test: [ 2000/21770] eta: 0:15:35 time: 0.0436 data: 0.0015 max mem: 19788 +Test: [ 2100/21770] eta: 0:15:30 time: 0.0421 data: 0.0015 max mem: 19788 +Test: [ 2200/21770] eta: 0:15:22 time: 0.0419 data: 0.0016 max mem: 19788 +Test: [ 2300/21770] eta: 0:15:18 time: 0.0546 data: 0.0016 max mem: 19788 +Test: [ 2400/21770] eta: 0:15:14 time: 0.0432 data: 0.0015 max mem: 19788 +Test: [ 2500/21770] eta: 0:15:07 time: 0.0438 data: 0.0015 max mem: 19788 +Test: [ 2600/21770] eta: 0:15:05 time: 0.0487 data: 0.0016 max mem: 19788 +Test: [ 2700/21770] eta: 0:14:59 time: 0.0424 data: 0.0015 max mem: 19788 +Test: [ 2800/21770] eta: 0:14:54 time: 0.0492 data: 0.0017 max mem: 19788 +Test: [ 2900/21770] eta: 0:14:53 time: 0.0530 data: 0.0018 max mem: 19788 +Test: [ 3000/21770] eta: 0:14:48 time: 0.0519 data: 0.0018 max mem: 19788 +Test: [ 3100/21770] eta: 0:14:44 time: 0.0468 data: 0.0015 max mem: 19788 +Test: [ 3200/21770] eta: 0:14:39 time: 0.0461 data: 0.0015 max mem: 19788 +Test: [ 3300/21770] eta: 0:14:32 time: 0.0427 data: 0.0014 max mem: 19788 +Test: [ 3400/21770] eta: 0:14:26 time: 0.0441 data: 0.0014 max mem: 19788 +Test: [ 3500/21770] eta: 0:14:22 time: 0.0521 data: 0.0017 max mem: 19788 +Test: [ 3600/21770] eta: 0:14:17 time: 0.0457 data: 0.0015 max mem: 19788 +Test: [ 3700/21770] eta: 0:14:13 time: 0.0505 data: 0.0016 max mem: 19788 +Test: [ 3800/21770] eta: 0:14:09 time: 0.0464 data: 0.0016 max mem: 19788 +Test: [ 3900/21770] eta: 0:14:06 time: 0.0520 data: 0.0015 max mem: 19788 +Test: [ 4000/21770] eta: 0:14:02 time: 0.0474 data: 0.0016 max mem: 19788 +Test: [ 4100/21770] eta: 0:13:57 time: 0.0432 data: 0.0015 max mem: 19788 +Test: [ 4200/21770] eta: 0:13:52 time: 0.0434 data: 0.0017 max mem: 19788 +Test: [ 4300/21770] eta: 0:13:47 time: 0.0544 data: 0.0015 max mem: 19788 +Test: [ 4400/21770] eta: 0:13:42 time: 0.0439 data: 0.0013 max mem: 19788 +Test: [ 4500/21770] eta: 0:13:38 time: 0.0465 data: 0.0014 max mem: 19788 +Test: [ 4600/21770] eta: 0:13:34 time: 0.0521 data: 0.0019 max mem: 19788 +Test: [ 4700/21770] eta: 0:13:29 time: 0.0426 data: 0.0015 max mem: 19788 +Test: [ 4800/21770] eta: 0:13:23 time: 0.0434 data: 0.0015 max mem: 19788 +Test: [ 4900/21770] eta: 0:13:18 time: 0.0492 data: 0.0016 max mem: 19788 +Test: [ 5000/21770] eta: 0:13:12 time: 0.0517 data: 0.0017 max mem: 19788 +Test: [ 5100/21770] eta: 0:13:09 time: 0.0523 data: 0.0018 max mem: 19788 +Test: [ 5200/21770] eta: 0:13:04 time: 0.0442 data: 0.0015 max mem: 19788 +Test: [ 5300/21770] eta: 0:12:58 time: 0.0459 data: 0.0015 max mem: 19788 +Test: [ 5400/21770] eta: 0:12:53 time: 0.0442 data: 0.0014 max mem: 19788 +Test: [ 5500/21770] eta: 0:12:49 time: 0.0451 data: 0.0018 max mem: 19788 +Test: [ 5600/21770] eta: 0:12:44 time: 0.0442 data: 0.0016 max mem: 19788 +Test: [ 5700/21770] eta: 0:12:39 time: 0.0437 data: 0.0015 max mem: 19788 +Test: [ 5800/21770] eta: 0:12:34 time: 0.0476 data: 0.0017 max mem: 19788 +Test: [ 5900/21770] eta: 0:12:28 time: 0.0448 data: 0.0016 max mem: 19788 +Test: [ 6000/21770] eta: 0:12:23 time: 0.0434 data: 0.0016 max mem: 19788 +Test: [ 6100/21770] eta: 0:12:18 time: 0.0436 data: 0.0014 max mem: 19788 +Test: [ 6200/21770] eta: 0:12:13 time: 0.0523 data: 0.0017 max mem: 19788 +Test: [ 6300/21770] eta: 0:12:09 time: 0.0433 data: 0.0014 max mem: 19788 +Test: [ 6400/21770] eta: 0:12:04 time: 0.0448 data: 0.0017 max mem: 19788 +Test: [ 6500/21770] eta: 0:11:59 time: 0.0436 data: 0.0015 max mem: 19788 +Test: [ 6600/21770] eta: 0:11:54 time: 0.0436 data: 0.0014 max mem: 19788 +Test: [ 6700/21770] eta: 0:11:50 time: 0.0461 data: 0.0015 max mem: 19788 +Test: [ 6800/21770] eta: 0:11:45 time: 0.0471 data: 0.0015 max mem: 19788 +Test: [ 6900/21770] eta: 0:11:41 time: 0.0444 data: 0.0014 max mem: 19788 +Test: [ 7000/21770] eta: 0:11:37 time: 0.0519 data: 0.0017 max mem: 19788 +Test: [ 7100/21770] eta: 0:11:32 time: 0.0470 data: 0.0016 max mem: 19788 +Test: [ 7200/21770] eta: 0:11:26 time: 0.0431 data: 0.0015 max mem: 19788 +Test: [ 7300/21770] eta: 0:11:22 time: 0.0447 data: 0.0014 max mem: 19788 +Test: [ 7400/21770] eta: 0:11:17 time: 0.0532 data: 0.0015 max mem: 19788 +Test: [ 7500/21770] eta: 0:11:12 time: 0.0438 data: 0.0015 max mem: 19788 +Test: [ 7600/21770] eta: 0:11:07 time: 0.0454 data: 0.0014 max mem: 19788 +Test: [ 7700/21770] eta: 0:11:03 time: 0.0438 data: 0.0013 max mem: 19788 +Test: [ 7800/21770] eta: 0:10:58 time: 0.0518 data: 0.0018 max mem: 19788 +Test: [ 7900/21770] eta: 0:10:53 time: 0.0434 data: 0.0014 max mem: 19788 +Test: [ 8000/21770] eta: 0:10:48 time: 0.0436 data: 0.0015 max mem: 19788 +Test: [ 8100/21770] eta: 0:10:43 time: 0.0547 data: 0.0016 max mem: 19788 +Test: [ 8200/21770] eta: 0:10:39 time: 0.0472 data: 0.0017 max mem: 19788 +Test: [ 8300/21770] eta: 0:10:34 time: 0.0477 data: 0.0014 max mem: 19788 +Test: [ 8400/21770] eta: 0:10:29 time: 0.0527 data: 0.0019 max mem: 19788 +Test: [ 8500/21770] eta: 0:10:25 time: 0.0532 data: 0.0015 max mem: 19788 +Test: [ 8600/21770] eta: 0:10:21 time: 0.0537 data: 0.0016 max mem: 19788 +Test: [ 8700/21770] eta: 0:10:16 time: 0.0439 data: 0.0016 max mem: 19788 +Test: [ 8800/21770] eta: 0:10:11 time: 0.0438 data: 0.0016 max mem: 19788 +Test: [ 8900/21770] eta: 0:10:06 time: 0.0516 data: 0.0019 max mem: 19788 +Test: [ 9000/21770] eta: 0:10:01 time: 0.0437 data: 0.0016 max mem: 19788 +Test: [ 9100/21770] eta: 0:09:56 time: 0.0425 data: 0.0015 max mem: 19788 +Test: [ 9200/21770] eta: 0:09:52 time: 0.0432 data: 0.0014 max mem: 19788 +Test: [ 9300/21770] eta: 0:09:47 time: 0.0435 data: 0.0015 max mem: 19788 +Test: [ 9400/21770] eta: 0:09:42 time: 0.0443 data: 0.0016 max mem: 19788 +Test: [ 9500/21770] eta: 0:09:38 time: 0.0474 data: 0.0017 max mem: 19788 +Test: [ 9600/21770] eta: 0:09:33 time: 0.0523 data: 0.0018 max mem: 19788 +Test: [ 9700/21770] eta: 0:09:28 time: 0.0441 data: 0.0016 max mem: 19788 +Test: [ 9800/21770] eta: 0:09:23 time: 0.0518 data: 0.0019 max mem: 19788 +Test: [ 9900/21770] eta: 0:09:18 time: 0.0462 data: 0.0015 max mem: 19788 +Test: [10000/21770] eta: 0:09:13 time: 0.0440 data: 0.0015 max mem: 19788 +Test: [10100/21770] eta: 0:09:08 time: 0.0452 data: 0.0018 max mem: 19788 +Test: [10200/21770] eta: 0:09:04 time: 0.0552 data: 0.0019 max mem: 19788 +Test: [10300/21770] eta: 0:08:59 time: 0.0457 data: 0.0018 max mem: 19788 +Test: [10400/21770] eta: 0:08:55 time: 0.0530 data: 0.0019 max mem: 19788 +Test: [10500/21770] eta: 0:08:50 time: 0.0462 data: 0.0017 max mem: 19788 +Test: [10600/21770] eta: 0:08:46 time: 0.0532 data: 0.0017 max mem: 19788 +Test: [10700/21770] eta: 0:08:41 time: 0.0435 data: 0.0014 max mem: 19788 +Test: [10800/21770] eta: 0:08:36 time: 0.0465 data: 0.0018 max mem: 19788 +Test: [10900/21770] eta: 0:08:32 time: 0.0496 data: 0.0019 max mem: 19788 +Test: [11000/21770] eta: 0:08:27 time: 0.0441 data: 0.0017 max mem: 19788 +Test: [11100/21770] eta: 0:08:23 time: 0.0522 data: 0.0016 max mem: 19788 +Test: [11200/21770] eta: 0:08:18 time: 0.0432 data: 0.0016 max mem: 19788 +Test: [11300/21770] eta: 0:08:13 time: 0.0493 data: 0.0018 max mem: 19788 +Test: [11400/21770] eta: 0:08:08 time: 0.0425 data: 0.0014 max mem: 19788 +Test: [11500/21770] eta: 0:08:03 time: 0.0498 data: 0.0016 max mem: 19788 +Test: [11600/21770] eta: 0:07:59 time: 0.0427 data: 0.0014 max mem: 19788 +Test: [11700/21770] eta: 0:07:54 time: 0.0526 data: 0.0017 max mem: 19788 +Test: [11800/21770] eta: 0:07:49 time: 0.0429 data: 0.0014 max mem: 19788 +Test: [11900/21770] eta: 0:07:45 time: 0.0474 data: 0.0018 max mem: 19788 +Test: [12000/21770] eta: 0:07:40 time: 0.0429 data: 0.0015 max mem: 19788 +Test: [12100/21770] eta: 0:07:35 time: 0.0448 data: 0.0016 max mem: 19788 +Test: [12200/21770] eta: 0:07:31 time: 0.0526 data: 0.0016 max mem: 19788 +Test: [12300/21770] eta: 0:07:26 time: 0.0526 data: 0.0017 max mem: 19788 +Test: [12400/21770] eta: 0:07:21 time: 0.0428 data: 0.0013 max mem: 19788 +Test: [12500/21770] eta: 0:07:16 time: 0.0442 data: 0.0017 max mem: 19788 +Test: [12600/21770] eta: 0:07:12 time: 0.0429 data: 0.0013 max mem: 19788 +Test: [12700/21770] eta: 0:07:07 time: 0.0533 data: 0.0018 max mem: 19788 +Test: [12800/21770] eta: 0:07:03 time: 0.0497 data: 0.0018 max mem: 19788 +Test: [12900/21770] eta: 0:06:58 time: 0.0440 data: 0.0016 max mem: 19788 +Test: [13000/21770] eta: 0:06:53 time: 0.0499 data: 0.0017 max mem: 19788 +Test: [13100/21770] eta: 0:06:49 time: 0.0437 data: 0.0016 max mem: 19788 +Test: [13200/21770] eta: 0:06:44 time: 0.0544 data: 0.0015 max mem: 19788 +Test: [13300/21770] eta: 0:06:39 time: 0.0485 data: 0.0014 max mem: 19788 +Test: [13400/21770] eta: 0:06:34 time: 0.0469 data: 0.0015 max mem: 19788 +Test: [13500/21770] eta: 0:06:30 time: 0.0444 data: 0.0016 max mem: 19788 +Test: [13600/21770] eta: 0:06:25 time: 0.0528 data: 0.0018 max mem: 19788 +Test: [13700/21770] eta: 0:06:20 time: 0.0467 data: 0.0015 max mem: 19788 +Test: [13800/21770] eta: 0:06:16 time: 0.0447 data: 0.0014 max mem: 19788 +Test: [13900/21770] eta: 0:06:11 time: 0.0514 data: 0.0018 max mem: 19788 +Test: [14000/21770] eta: 0:06:06 time: 0.0494 data: 0.0017 max mem: 19788 +Test: [14100/21770] eta: 0:06:02 time: 0.0519 data: 0.0017 max mem: 19788 +Test: [14200/21770] eta: 0:05:57 time: 0.0438 data: 0.0016 max mem: 19788 +Test: [14300/21770] eta: 0:05:52 time: 0.0527 data: 0.0019 max mem: 19788 +Test: [14400/21770] eta: 0:05:48 time: 0.0516 data: 0.0018 max mem: 19788 +Test: [14500/21770] eta: 0:05:43 time: 0.0439 data: 0.0013 max mem: 19788 +Test: [14600/21770] eta: 0:05:38 time: 0.0440 data: 0.0015 max mem: 19788 +Test: [14700/21770] eta: 0:05:34 time: 0.0469 data: 0.0016 max mem: 19788 +Test: [14800/21770] eta: 0:05:29 time: 0.0449 data: 0.0015 max mem: 19788 +Test: [14900/21770] eta: 0:05:24 time: 0.0528 data: 0.0018 max mem: 19788 +Test: [15000/21770] eta: 0:05:19 time: 0.0442 data: 0.0015 max mem: 19788 +Test: [15100/21770] eta: 0:05:15 time: 0.0491 data: 0.0016 max mem: 19788 +Test: [15200/21770] eta: 0:05:10 time: 0.0432 data: 0.0014 max mem: 19788 +Test: [15300/21770] eta: 0:05:05 time: 0.0544 data: 0.0016 max mem: 19788 +Test: [15400/21770] eta: 0:05:01 time: 0.0442 data: 0.0016 max mem: 19788 +Test: [15500/21770] eta: 0:04:56 time: 0.0441 data: 0.0017 max mem: 19788 +Test: [15600/21770] eta: 0:04:51 time: 0.0518 data: 0.0018 max mem: 19788 +Test: [15700/21770] eta: 0:04:46 time: 0.0502 data: 0.0017 max mem: 19788 +Test: [15800/21770] eta: 0:04:42 time: 0.0486 data: 0.0016 max mem: 19788 +Test: [15900/21770] eta: 0:04:37 time: 0.0444 data: 0.0015 max mem: 19788 +Test: [16000/21770] eta: 0:04:32 time: 0.0440 data: 0.0014 max mem: 19788 +Test: [16100/21770] eta: 0:04:27 time: 0.0465 data: 0.0017 max mem: 19788 +Test: [16200/21770] eta: 0:04:23 time: 0.0428 data: 0.0014 max mem: 19788 +Test: [16300/21770] eta: 0:04:18 time: 0.0418 data: 0.0014 max mem: 19788 +Test: [16400/21770] eta: 0:04:13 time: 0.0524 data: 0.0017 max mem: 19788 +Test: [16500/21770] eta: 0:04:08 time: 0.0465 data: 0.0014 max mem: 19788 +Test: [16600/21770] eta: 0:04:03 time: 0.0432 data: 0.0015 max mem: 19788 +Test: [16700/21770] eta: 0:03:59 time: 0.0505 data: 0.0017 max mem: 19788 +Test: [16800/21770] eta: 0:03:54 time: 0.0496 data: 0.0017 max mem: 19788 +Test: [16900/21770] eta: 0:03:49 time: 0.0517 data: 0.0018 max mem: 19788 +Test: [17000/21770] eta: 0:03:44 time: 0.0432 data: 0.0017 max mem: 19788 +Test: [17100/21770] eta: 0:03:40 time: 0.0518 data: 0.0019 max mem: 19788 +Test: [17200/21770] eta: 0:03:35 time: 0.0444 data: 0.0015 max mem: 19788 +Test: [17300/21770] eta: 0:03:30 time: 0.0486 data: 0.0017 max mem: 19788 +Test: [17400/21770] eta: 0:03:26 time: 0.0430 data: 0.0014 max mem: 19788 +Test: [17500/21770] eta: 0:03:21 time: 0.0427 data: 0.0015 max mem: 19788 +Test: [17600/21770] eta: 0:03:16 time: 0.0459 data: 0.0015 max mem: 19788 +Test: [17700/21770] eta: 0:03:11 time: 0.0425 data: 0.0014 max mem: 19788 +Test: [17800/21770] eta: 0:03:07 time: 0.0444 data: 0.0015 max mem: 19788 +Test: [17900/21770] eta: 0:03:02 time: 0.0447 data: 0.0016 max mem: 19788 +Test: [18000/21770] eta: 0:02:57 time: 0.0442 data: 0.0014 max mem: 19788 +Test: [18100/21770] eta: 0:02:52 time: 0.0437 data: 0.0013 max mem: 19788 +Test: [18200/21770] eta: 0:02:48 time: 0.0523 data: 0.0018 max mem: 19788 +Test: [18300/21770] eta: 0:02:43 time: 0.0439 data: 0.0017 max mem: 19788 +Test: [18400/21770] eta: 0:02:38 time: 0.0505 data: 0.0019 max mem: 19788 +Test: [18500/21770] eta: 0:02:34 time: 0.0479 data: 0.0016 max mem: 19788 +Test: [18600/21770] eta: 0:02:29 time: 0.0430 data: 0.0016 max mem: 19788 +Test: [18700/21770] eta: 0:02:24 time: 0.0433 data: 0.0014 max mem: 19788 +Test: [18800/21770] eta: 0:02:19 time: 0.0492 data: 0.0019 max mem: 19788 +Test: [18900/21770] eta: 0:02:15 time: 0.0430 data: 0.0015 max mem: 19788 +Test: [19000/21770] eta: 0:02:10 time: 0.0487 data: 0.0017 max mem: 19788 +Test: [19100/21770] eta: 0:02:05 time: 0.0529 data: 0.0019 max mem: 19788 +Test: [19200/21770] eta: 0:02:01 time: 0.0486 data: 0.0016 max mem: 19788 +Test: [19300/21770] eta: 0:01:56 time: 0.0510 data: 0.0017 max mem: 19788 +Test: [19400/21770] eta: 0:01:51 time: 0.0481 data: 0.0016 max mem: 19788 +Test: [19500/21770] eta: 0:01:46 time: 0.0465 data: 0.0017 max mem: 19788 +Test: [19600/21770] eta: 0:01:42 time: 0.0546 data: 0.0016 max mem: 19788 +Test: [19700/21770] eta: 0:01:37 time: 0.0429 data: 0.0016 max mem: 19788 +Test: [19800/21770] eta: 0:01:32 time: 0.0490 data: 0.0016 max mem: 19788 +Test: [19900/21770] eta: 0:01:28 time: 0.0428 data: 0.0016 max mem: 19788 +Test: [20000/21770] eta: 0:01:23 time: 0.0440 data: 0.0014 max mem: 19788 +Test: [20100/21770] eta: 0:01:18 time: 0.0456 data: 0.0016 max mem: 19788 +Test: [20200/21770] eta: 0:01:13 time: 0.0455 data: 0.0016 max mem: 19788 +Test: [20300/21770] eta: 0:01:09 time: 0.0437 data: 0.0014 max mem: 19788 +Test: [20400/21770] eta: 0:01:04 time: 0.0426 data: 0.0014 max mem: 19788 +Test: [20500/21770] eta: 0:00:59 time: 0.0539 data: 0.0017 max mem: 19788 +Test: [20600/21770] eta: 0:00:55 time: 0.0508 data: 0.0016 max mem: 19788 +Test: [20700/21770] eta: 0:00:50 time: 0.0431 data: 0.0016 max mem: 19788 +Test: [20800/21770] eta: 0:00:45 time: 0.0504 data: 0.0017 max mem: 19788 +Test: [20900/21770] eta: 0:00:40 time: 0.0447 data: 0.0016 max mem: 19788 +Test: [21000/21770] eta: 0:00:36 time: 0.0462 data: 0.0017 max mem: 19788 +Test: [21100/21770] eta: 0:00:31 time: 0.0542 data: 0.0016 max mem: 19788 +Test: [21200/21770] eta: 0:00:26 time: 0.0484 data: 0.0016 max mem: 19788 +Test: [21300/21770] eta: 0:00:22 time: 0.0495 data: 0.0018 max mem: 19788 +Test: [21400/21770] eta: 0:00:17 time: 0.0448 data: 0.0015 max mem: 19788 +Test: [21500/21770] eta: 0:00:12 time: 0.0457 data: 0.0014 max mem: 19788 +Test: [21600/21770] eta: 0:00:08 time: 0.0443 data: 0.0016 max mem: 19788 +Test: [21700/21770] eta: 0:00:03 time: 0.0442 data: 0.0015 max mem: 19788 +Test: Total time: 0:17:06 +Final results: +Mean IoU is 50.48 + + precision@0.5 = 54.28 + precision@0.6 = 47.24 + precision@0.7 = 39.21 + precision@0.8 = 28.02 + precision@0.9 = 9.36 + overall IoU = 55.41 + mean IoU = 50.48 + +Mean accuracy for one-to-zero sample is 80.15 + +Average object IoU 0.5048225485427181 +Overall IoU 55.40547180175781 +Better epoch: 0 + +Epoch: [1] [ 0/2138] eta: 8:53:43 lr: 4.8873053160605256e-05 loss: 0.3131 (0.3131) time: 14.9781 data: 1.7204 max mem: 19788 +Epoch: [1] [ 10/2138] eta: 2:23:06 lr: 4.886777785668473e-05 loss: 0.1492 (0.1804) time: 4.0348 data: 0.1587 max mem: 19788 +Epoch: [1] [ 20/2138] eta: 2:03:47 lr: 4.8862502489488774e-05 loss: 0.1360 (0.1805) time: 2.9334 data: 0.0025 max mem: 19788 +Epoch: [1] [ 30/2138] eta: 1:57:00 lr: 4.8857227059009036e-05 loss: 0.1386 (0.1669) time: 2.9433 data: 0.0025 max mem: 19788 +Epoch: [1] [ 40/2138] eta: 1:53:20 lr: 4.885195156523718e-05 loss: 0.1386 (0.1628) time: 2.9622 data: 0.0027 max mem: 19788 +Epoch: [1] [ 50/2138] eta: 1:50:41 lr: 4.884667600816484e-05 loss: 0.1360 (0.1598) time: 2.9486 data: 0.0027 max mem: 19788 +Epoch: [1] [ 60/2138] eta: 1:49:10 lr: 4.884140038778367e-05 loss: 0.1366 (0.1635) time: 2.9700 data: 0.0024 max mem: 19788 +Epoch: [1] [ 70/2138] eta: 1:47:33 lr: 4.883612470408529e-05 loss: 0.1471 (0.1630) time: 2.9676 data: 0.0021 max mem: 19788 +Epoch: [1] [ 80/2138] eta: 1:46:08 lr: 4.8830848957061366e-05 loss: 0.1403 (0.1593) time: 2.9186 data: 0.0021 max mem: 19788 +Epoch: [1] [ 90/2138] eta: 1:45:04 lr: 4.882557314670352e-05 loss: 0.1317 (0.1588) time: 2.9288 data: 0.0021 max mem: 19788 +Epoch: [1] [ 100/2138] eta: 1:44:08 lr: 4.8820297273003384e-05 loss: 0.1410 (0.1579) time: 2.9511 data: 0.0021 max mem: 19788 +Epoch: [1] [ 110/2138] eta: 1:43:18 lr: 4.881502133595261e-05 loss: 0.1542 (0.1607) time: 2.9565 data: 0.0021 max mem: 19788 +Epoch: [1] [ 120/2138] eta: 1:42:26 lr: 4.880974533554281e-05 loss: 0.1337 (0.1581) time: 2.9430 data: 0.0022 max mem: 19788 +Epoch: [1] [ 130/2138] eta: 1:41:36 lr: 4.880446927176563e-05 loss: 0.1248 (0.1575) time: 2.9227 data: 0.0025 max mem: 19788 +Epoch: [1] [ 140/2138] eta: 1:40:49 lr: 4.879919314461268e-05 loss: 0.1390 (0.1583) time: 2.9174 data: 0.0026 max mem: 19788 +Epoch: [1] [ 150/2138] eta: 1:40:06 lr: 4.87939169540756e-05 loss: 0.1535 (0.1602) time: 2.9240 data: 0.0024 max mem: 19788 +Epoch: [1] [ 160/2138] eta: 1:39:26 lr: 4.878864070014601e-05 loss: 0.1482 (0.1587) time: 2.9366 data: 0.0026 max mem: 19788 +Epoch: [1] [ 170/2138] eta: 1:39:05 lr: 4.8783364382815523e-05 loss: 0.1464 (0.1607) time: 3.0213 data: 0.0027 max mem: 19788 +Epoch: [1] [ 180/2138] eta: 1:38:34 lr: 4.877808800207576e-05 loss: 0.1542 (0.1603) time: 3.0546 data: 0.0023 max mem: 19788 +Epoch: [1] [ 190/2138] eta: 1:38:29 lr: 4.877281155791835e-05 loss: 0.1260 (0.1588) time: 3.1388 data: 0.0024 max mem: 19788 +Epoch: [1] [ 200/2138] eta: 1:37:55 lr: 4.876753505033489e-05 loss: 0.1247 (0.1573) time: 3.1319 data: 0.0024 max mem: 19788 +Epoch: [1] [ 210/2138] eta: 1:37:26 lr: 4.8762258479317e-05 loss: 0.1234 (0.1563) time: 3.0220 data: 0.0023 max mem: 19788 +Epoch: [1] [ 220/2138] eta: 1:37:07 lr: 4.875698184485629e-05 loss: 0.1306 (0.1559) time: 3.1038 data: 0.0023 max mem: 19788 +Epoch: [1] [ 230/2138] eta: 1:36:44 lr: 4.875170514694438e-05 loss: 0.1602 (0.1569) time: 3.1432 data: 0.0022 max mem: 19788 +Epoch: [1] [ 240/2138] eta: 1:36:03 lr: 4.874642838557285e-05 loss: 0.1516 (0.1560) time: 3.0204 data: 0.0022 max mem: 19788 +Epoch: [1] [ 250/2138] eta: 1:35:29 lr: 4.8741151560733324e-05 loss: 0.1450 (0.1556) time: 2.9511 data: 0.0022 max mem: 19788 +Epoch: [1] [ 260/2138] eta: 1:34:53 lr: 4.8735874672417394e-05 loss: 0.1450 (0.1553) time: 2.9735 data: 0.0023 max mem: 19788 +Epoch: [1] [ 270/2138] eta: 1:34:18 lr: 4.873059772061667e-05 loss: 0.1357 (0.1556) time: 2.9565 data: 0.0024 max mem: 19788 +Epoch: [1] [ 280/2138] eta: 1:33:40 lr: 4.8725320705322737e-05 loss: 0.1412 (0.1549) time: 2.9381 data: 0.0022 max mem: 19788 +Epoch: [1] [ 290/2138] eta: 1:33:03 lr: 4.87200436265272e-05 loss: 0.1546 (0.1560) time: 2.9194 data: 0.0024 max mem: 19788 +Epoch: [1] [ 300/2138] eta: 1:32:39 lr: 4.8714766484221655e-05 loss: 0.1703 (0.1568) time: 3.0203 data: 0.0024 max mem: 19788 +Epoch: [1] [ 310/2138] eta: 1:32:03 lr: 4.870948927839768e-05 loss: 0.1284 (0.1558) time: 3.0209 data: 0.0026 max mem: 19788 +Epoch: [1] [ 320/2138] eta: 1:31:28 lr: 4.8704212009046874e-05 loss: 0.1161 (0.1549) time: 2.9317 data: 0.0029 max mem: 19788 +Epoch: [1] [ 330/2138] eta: 1:30:53 lr: 4.869893467616082e-05 loss: 0.1328 (0.1551) time: 2.9323 data: 0.0024 max mem: 19788 +Epoch: [1] [ 340/2138] eta: 1:30:20 lr: 4.8693657279731106e-05 loss: 0.1369 (0.1548) time: 2.9459 data: 0.0021 max mem: 19788 +Epoch: [1] [ 350/2138] eta: 1:29:45 lr: 4.8688379819749313e-05 loss: 0.1335 (0.1546) time: 2.9447 data: 0.0021 max mem: 19788 +Epoch: [1] [ 360/2138] eta: 1:29:15 lr: 4.8683102296207015e-05 loss: 0.1479 (0.1544) time: 2.9656 data: 0.0022 max mem: 19788 +Epoch: [1] [ 370/2138] eta: 1:28:40 lr: 4.86778247090958e-05 loss: 0.1551 (0.1547) time: 2.9632 data: 0.0022 max mem: 19788 +Epoch: [1] [ 380/2138] eta: 1:28:10 lr: 4.867254705840724e-05 loss: 0.1551 (0.1549) time: 2.9649 data: 0.0021 max mem: 19788 +Epoch: [1] [ 390/2138] eta: 1:27:38 lr: 4.8667269344132914e-05 loss: 0.1409 (0.1546) time: 2.9913 data: 0.0024 max mem: 19788 +Epoch: [1] [ 400/2138] eta: 1:27:04 lr: 4.866199156626439e-05 loss: 0.1378 (0.1544) time: 2.9350 data: 0.0025 max mem: 19788 +Epoch: [1] [ 410/2138] eta: 1:26:31 lr: 4.865671372479324e-05 loss: 0.1411 (0.1553) time: 2.9267 data: 0.0024 max mem: 19788 +Epoch: [1] [ 420/2138] eta: 1:25:58 lr: 4.865143581971103e-05 loss: 0.1447 (0.1552) time: 2.9417 data: 0.0025 max mem: 19788 +Epoch: [1] [ 430/2138] eta: 1:25:25 lr: 4.864615785100932e-05 loss: 0.1326 (0.1548) time: 2.9322 data: 0.0023 max mem: 19788 +Epoch: [1] [ 440/2138] eta: 1:24:55 lr: 4.864087981867968e-05 loss: 0.1368 (0.1547) time: 2.9573 data: 0.0021 max mem: 19788 +Epoch: [1] [ 450/2138] eta: 1:24:23 lr: 4.8635601722713666e-05 loss: 0.1384 (0.1545) time: 2.9743 data: 0.0021 max mem: 19788 +Epoch: [1] [ 460/2138] eta: 1:24:01 lr: 4.8630323563102845e-05 loss: 0.1267 (0.1541) time: 3.0889 data: 0.0024 max mem: 19788 +Epoch: [1] [ 470/2138] eta: 1:23:30 lr: 4.8625045339838766e-05 loss: 0.1296 (0.1537) time: 3.0895 data: 0.0025 max mem: 19788 +Epoch: [1] [ 480/2138] eta: 1:23:05 lr: 4.8619767052913e-05 loss: 0.1460 (0.1538) time: 3.0561 data: 0.0022 max mem: 19788 +Epoch: [1] [ 490/2138] eta: 1:22:34 lr: 4.861448870231707e-05 loss: 0.1482 (0.1537) time: 3.0617 data: 0.0021 max mem: 19788 +Epoch: [1] [ 500/2138] eta: 1:22:07 lr: 4.860921028804256e-05 loss: 0.1435 (0.1535) time: 3.0438 data: 0.0021 max mem: 19788 +Epoch: [1] [ 510/2138] eta: 1:21:34 lr: 4.8603931810081e-05 loss: 0.1479 (0.1535) time: 3.0167 data: 0.0022 max mem: 19788 +Epoch: [1] [ 520/2138] eta: 1:21:07 lr: 4.859865326842394e-05 loss: 0.1372 (0.1531) time: 3.0161 data: 0.0023 max mem: 19788 +Epoch: [1] [ 530/2138] eta: 1:20:35 lr: 4.859337466306292e-05 loss: 0.1288 (0.1527) time: 3.0186 data: 0.0025 max mem: 19788 +Epoch: [1] [ 540/2138] eta: 1:20:07 lr: 4.858809599398949e-05 loss: 0.1195 (0.1521) time: 3.0117 data: 0.0024 max mem: 19788 +Epoch: [1] [ 550/2138] eta: 1:19:36 lr: 4.858281726119517e-05 loss: 0.1255 (0.1527) time: 3.0373 data: 0.0022 max mem: 19788 +Epoch: [1] [ 560/2138] eta: 1:19:07 lr: 4.857753846467153e-05 loss: 0.1409 (0.1527) time: 3.0057 data: 0.0022 max mem: 19788 +Epoch: [1] [ 570/2138] eta: 1:18:36 lr: 4.857225960441009e-05 loss: 0.1333 (0.1528) time: 3.0033 data: 0.0025 max mem: 19788 +Epoch: [1] [ 580/2138] eta: 1:18:06 lr: 4.856698068040238e-05 loss: 0.1424 (0.1524) time: 3.0007 data: 0.0027 max mem: 19788 +Epoch: [1] [ 590/2138] eta: 1:17:34 lr: 4.8561701692639924e-05 loss: 0.1373 (0.1523) time: 2.9656 data: 0.0028 max mem: 19788 +Epoch: [1] [ 600/2138] eta: 1:17:02 lr: 4.855642264111427e-05 loss: 0.1197 (0.1523) time: 2.9284 data: 0.0026 max mem: 19788 +Epoch: [1] [ 610/2138] eta: 1:16:30 lr: 4.855114352581694e-05 loss: 0.1239 (0.1521) time: 2.9301 data: 0.0022 max mem: 19788 +Epoch: [1] [ 620/2138] eta: 1:15:57 lr: 4.854586434673945e-05 loss: 0.1308 (0.1524) time: 2.9069 data: 0.0024 max mem: 19788 +Epoch: [1] [ 630/2138] eta: 1:15:25 lr: 4.8540585103873324e-05 loss: 0.1307 (0.1521) time: 2.9101 data: 0.0024 max mem: 19788 +Epoch: [1] [ 640/2138] eta: 1:14:53 lr: 4.853530579721009e-05 loss: 0.1274 (0.1518) time: 2.9202 data: 0.0021 max mem: 19788 +Epoch: [1] [ 650/2138] eta: 1:14:21 lr: 4.8530026426741266e-05 loss: 0.1183 (0.1521) time: 2.9217 data: 0.0021 max mem: 19788 +Epoch: [1] [ 660/2138] eta: 1:13:54 lr: 4.8524746992458366e-05 loss: 0.1279 (0.1518) time: 3.0131 data: 0.0022 max mem: 19788 +Epoch: [1] [ 670/2138] eta: 1:13:24 lr: 4.85194674943529e-05 loss: 0.1303 (0.1516) time: 3.0675 data: 0.0022 max mem: 19788 +Epoch: [1] [ 680/2138] eta: 1:12:56 lr: 4.8514187932416384e-05 loss: 0.1340 (0.1514) time: 3.0458 data: 0.0022 max mem: 19788 +Epoch: [1] [ 690/2138] eta: 1:12:25 lr: 4.850890830664032e-05 loss: 0.1354 (0.1514) time: 3.0104 data: 0.0022 max mem: 19788 +Epoch: [1] [ 700/2138] eta: 1:11:56 lr: 4.8503628617016235e-05 loss: 0.1285 (0.1510) time: 3.0034 data: 0.0021 max mem: 19788 +Epoch: [1] [ 710/2138] eta: 1:11:28 lr: 4.8498348863535616e-05 loss: 0.1346 (0.1511) time: 3.0723 data: 0.0022 max mem: 19788 +Epoch: [1] [ 720/2138] eta: 1:10:57 lr: 4.8493069046189974e-05 loss: 0.1410 (0.1509) time: 3.0404 data: 0.0023 max mem: 19788 +Epoch: [1] [ 730/2138] eta: 1:10:30 lr: 4.848778916497081e-05 loss: 0.1337 (0.1506) time: 3.0537 data: 0.0025 max mem: 19788 +Epoch: [1] [ 740/2138] eta: 1:10:04 lr: 4.848250921986962e-05 loss: 0.1221 (0.1506) time: 3.1770 data: 0.0024 max mem: 19788 +Epoch: [1] [ 750/2138] eta: 1:09:34 lr: 4.847722921087791e-05 loss: 0.1588 (0.1508) time: 3.1189 data: 0.0024 max mem: 19788 +Epoch: [1] [ 760/2138] eta: 1:09:02 lr: 4.847194913798715e-05 loss: 0.1520 (0.1507) time: 2.9680 data: 0.0025 max mem: 19788 +Epoch: [1] [ 770/2138] eta: 1:08:31 lr: 4.8466669001188865e-05 loss: 0.1241 (0.1505) time: 2.9395 data: 0.0025 max mem: 19788 +Epoch: [1] [ 780/2138] eta: 1:08:00 lr: 4.8461388800474525e-05 loss: 0.1431 (0.1506) time: 2.9355 data: 0.0025 max mem: 19788 +Epoch: [1] [ 790/2138] eta: 1:07:28 lr: 4.8456108535835625e-05 loss: 0.1202 (0.1501) time: 2.9243 data: 0.0027 max mem: 19788 +Epoch: [1] [ 800/2138] eta: 1:06:57 lr: 4.8450828207263646e-05 loss: 0.1202 (0.1504) time: 2.9242 data: 0.0026 max mem: 19788 +Epoch: [1] [ 810/2138] eta: 1:06:26 lr: 4.844554781475008e-05 loss: 0.1502 (0.1503) time: 2.9275 data: 0.0022 max mem: 19788 +Epoch: [1] [ 820/2138] eta: 1:05:55 lr: 4.84402673582864e-05 loss: 0.1284 (0.1501) time: 2.9543 data: 0.0021 max mem: 19788 +Epoch: [1] [ 830/2138] eta: 1:05:24 lr: 4.84349868378641e-05 loss: 0.1261 (0.1499) time: 2.9623 data: 0.0021 max mem: 19788 +Epoch: [1] [ 840/2138] eta: 1:04:53 lr: 4.842970625347464e-05 loss: 0.1327 (0.1498) time: 2.9398 data: 0.0021 max mem: 19788 +Epoch: [1] [ 850/2138] eta: 1:04:22 lr: 4.84244256051095e-05 loss: 0.1344 (0.1498) time: 2.9327 data: 0.0023 max mem: 19788 +Epoch: [1] [ 860/2138] eta: 1:03:51 lr: 4.841914489276016e-05 loss: 0.1357 (0.1497) time: 2.9207 data: 0.0023 max mem: 19788 +Epoch: [1] [ 870/2138] eta: 1:03:21 lr: 4.841386411641808e-05 loss: 0.1343 (0.1496) time: 2.9399 data: 0.0021 max mem: 19788 +Epoch: [1] [ 880/2138] eta: 1:02:52 lr: 4.8408583276074746e-05 loss: 0.1423 (0.1494) time: 3.0410 data: 0.0021 max mem: 19788 +Epoch: [1] [ 890/2138] eta: 1:02:21 lr: 4.840330237172161e-05 loss: 0.1176 (0.1490) time: 3.0239 data: 0.0023 max mem: 19788 +Epoch: [1] [ 900/2138] eta: 1:01:50 lr: 4.8398021403350134e-05 loss: 0.1139 (0.1487) time: 2.9225 data: 0.0026 max mem: 19788 +Epoch: [1] [ 910/2138] eta: 1:01:21 lr: 4.8392740370951795e-05 loss: 0.1166 (0.1485) time: 2.9759 data: 0.0025 max mem: 19788 +Epoch: [1] [ 920/2138] eta: 1:00:50 lr: 4.838745927451804e-05 loss: 0.1115 (0.1481) time: 2.9717 data: 0.0025 max mem: 19788 +Epoch: [1] [ 930/2138] eta: 1:00:18 lr: 4.8382178114040334e-05 loss: 0.1169 (0.1482) time: 2.9046 data: 0.0027 max mem: 19788 +Epoch: [1] [ 940/2138] eta: 0:59:48 lr: 4.837689688951012e-05 loss: 0.1406 (0.1480) time: 2.9180 data: 0.0026 max mem: 19788 +Epoch: [1] [ 950/2138] eta: 0:59:17 lr: 4.8371615600918875e-05 loss: 0.1374 (0.1480) time: 2.9460 data: 0.0024 max mem: 19788 +Epoch: [1] [ 960/2138] eta: 0:58:48 lr: 4.836633424825803e-05 loss: 0.1153 (0.1476) time: 3.0084 data: 0.0024 max mem: 19788 +Epoch: [1] [ 970/2138] eta: 0:58:19 lr: 4.8361052831519046e-05 loss: 0.1055 (0.1474) time: 3.0478 data: 0.0025 max mem: 19788 +Epoch: [1] [ 980/2138] eta: 0:57:49 lr: 4.8355771350693354e-05 loss: 0.1206 (0.1472) time: 3.0145 data: 0.0026 max mem: 19788 +Epoch: [1] [ 990/2138] eta: 0:57:19 lr: 4.835048980577242e-05 loss: 0.1210 (0.1472) time: 2.9860 data: 0.0026 max mem: 19788 +Epoch: [1] [1000/2138] eta: 0:56:48 lr: 4.834520819674767e-05 loss: 0.1291 (0.1472) time: 2.9602 data: 0.0024 max mem: 19788 +Epoch: [1] [1010/2138] eta: 0:56:17 lr: 4.833992652361055e-05 loss: 0.1307 (0.1471) time: 2.9285 data: 0.0024 max mem: 19788 +Epoch: [1] [1020/2138] eta: 0:55:46 lr: 4.8334644786352506e-05 loss: 0.1450 (0.1472) time: 2.9173 data: 0.0027 max mem: 19788 +Epoch: [1] [1030/2138] eta: 0:55:16 lr: 4.832936298496496e-05 loss: 0.1380 (0.1471) time: 2.9174 data: 0.0026 max mem: 19788 +Epoch: [1] [1040/2138] eta: 0:54:45 lr: 4.8324081119439365e-05 loss: 0.1309 (0.1470) time: 2.9335 data: 0.0024 max mem: 19788 +Epoch: [1] [1050/2138] eta: 0:54:15 lr: 4.8318799189767126e-05 loss: 0.1257 (0.1467) time: 2.9526 data: 0.0023 max mem: 19788 +Epoch: [1] [1060/2138] eta: 0:53:46 lr: 4.83135171959397e-05 loss: 0.1232 (0.1467) time: 3.0131 data: 0.0022 max mem: 19788 +Epoch: [1] [1070/2138] eta: 0:53:15 lr: 4.8308235137948486e-05 loss: 0.1197 (0.1464) time: 2.9865 data: 0.0021 max mem: 19788 +Epoch: [1] [1080/2138] eta: 0:52:45 lr: 4.830295301578493e-05 loss: 0.1281 (0.1463) time: 2.9658 data: 0.0021 max mem: 19788 +Epoch: [1] [1090/2138] eta: 0:52:15 lr: 4.8297670829440454e-05 loss: 0.1281 (0.1463) time: 2.9697 data: 0.0021 max mem: 19788 +Epoch: [1] [1100/2138] eta: 0:51:44 lr: 4.8292388578906476e-05 loss: 0.1251 (0.1463) time: 2.9276 data: 0.0022 max mem: 19788 +Epoch: [1] [1110/2138] eta: 0:51:14 lr: 4.828710626417441e-05 loss: 0.1289 (0.1461) time: 2.9240 data: 0.0021 max mem: 19788 +Epoch: [1] [1120/2138] eta: 0:50:43 lr: 4.828182388523567e-05 loss: 0.1316 (0.1460) time: 2.9173 data: 0.0021 max mem: 19788 +Epoch: [1] [1130/2138] eta: 0:50:13 lr: 4.827654144208168e-05 loss: 0.1377 (0.1458) time: 2.9492 data: 0.0021 max mem: 19788 +Epoch: [1] [1140/2138] eta: 0:49:43 lr: 4.827125893470385e-05 loss: 0.1393 (0.1459) time: 2.9512 data: 0.0023 max mem: 19788 +Epoch: [1] [1150/2138] eta: 0:49:12 lr: 4.8265976363093584e-05 loss: 0.1333 (0.1459) time: 2.9157 data: 0.0027 max mem: 19788 +Epoch: [1] [1160/2138] eta: 0:48:43 lr: 4.826069372724229e-05 loss: 0.1282 (0.1457) time: 3.0014 data: 0.0026 max mem: 19788 +Epoch: [1] [1170/2138] eta: 0:48:12 lr: 4.825541102714138e-05 loss: 0.1130 (0.1457) time: 3.0022 data: 0.0027 max mem: 19788 +Epoch: [1] [1180/2138] eta: 0:47:42 lr: 4.825012826278226e-05 loss: 0.1208 (0.1457) time: 2.9152 data: 0.0028 max mem: 19788 +Epoch: [1] [1190/2138] eta: 0:47:12 lr: 4.824484543415631e-05 loss: 0.1208 (0.1455) time: 2.9609 data: 0.0026 max mem: 19788 +Epoch: [1] [1200/2138] eta: 0:46:43 lr: 4.823956254125495e-05 loss: 0.0991 (0.1451) time: 3.0230 data: 0.0024 max mem: 19788 +Epoch: [1] [1210/2138] eta: 0:46:12 lr: 4.823427958406957e-05 loss: 0.1088 (0.1450) time: 2.9883 data: 0.0023 max mem: 19788 +Epoch: [1] [1220/2138] eta: 0:45:43 lr: 4.822899656259156e-05 loss: 0.1253 (0.1449) time: 2.9990 data: 0.0023 max mem: 19788 +Epoch: [1] [1230/2138] eta: 0:45:14 lr: 4.822371347681233e-05 loss: 0.1289 (0.1447) time: 3.0510 data: 0.0022 max mem: 19788 +Epoch: [1] [1240/2138] eta: 0:44:44 lr: 4.821843032672325e-05 loss: 0.1309 (0.1445) time: 3.0388 data: 0.0022 max mem: 19788 +Epoch: [1] [1250/2138] eta: 0:44:14 lr: 4.821314711231571e-05 loss: 0.1273 (0.1444) time: 3.0194 data: 0.0023 max mem: 19788 +Epoch: [1] [1260/2138] eta: 0:43:44 lr: 4.8207863833581104e-05 loss: 0.1197 (0.1442) time: 2.9593 data: 0.0024 max mem: 19788 +Epoch: [1] [1270/2138] eta: 0:43:13 lr: 4.820258049051081e-05 loss: 0.1227 (0.1441) time: 2.9151 data: 0.0024 max mem: 19788 +Epoch: [1] [1280/2138] eta: 0:42:43 lr: 4.819729708309621e-05 loss: 0.1404 (0.1441) time: 2.9131 data: 0.0022 max mem: 19788 +Epoch: [1] [1290/2138] eta: 0:42:14 lr: 4.819201361132868e-05 loss: 0.1238 (0.1439) time: 2.9770 data: 0.0022 max mem: 19788 +Epoch: [1] [1300/2138] eta: 0:41:43 lr: 4.8186730075199605e-05 loss: 0.1041 (0.1436) time: 2.9781 data: 0.0024 max mem: 19788 +Epoch: [1] [1310/2138] eta: 0:41:14 lr: 4.8181446474700355e-05 loss: 0.1082 (0.1434) time: 3.0034 data: 0.0025 max mem: 19788 +Epoch: [1] [1320/2138] eta: 0:40:44 lr: 4.81761628098223e-05 loss: 0.1339 (0.1436) time: 2.9949 data: 0.0024 max mem: 19788 +Epoch: [1] [1330/2138] eta: 0:40:13 lr: 4.817087908055682e-05 loss: 0.1456 (0.1437) time: 2.9149 data: 0.0025 max mem: 19788 +Epoch: [1] [1340/2138] eta: 0:39:43 lr: 4.816559528689527e-05 loss: 0.1411 (0.1437) time: 2.9523 data: 0.0026 max mem: 19788 +Epoch: [1] [1350/2138] eta: 0:39:13 lr: 4.816031142882903e-05 loss: 0.1413 (0.1437) time: 2.9620 data: 0.0025 max mem: 19788 +Epoch: [1] [1360/2138] eta: 0:38:43 lr: 4.8155027506349434e-05 loss: 0.1413 (0.1437) time: 2.9343 data: 0.0025 max mem: 19788 +Epoch: [1] [1370/2138] eta: 0:38:13 lr: 4.814974351944788e-05 loss: 0.1441 (0.1438) time: 2.9394 data: 0.0025 max mem: 19788 +Epoch: [1] [1380/2138] eta: 0:37:43 lr: 4.8144459468115714e-05 loss: 0.1529 (0.1438) time: 2.9299 data: 0.0024 max mem: 19788 +Epoch: [1] [1390/2138] eta: 0:37:12 lr: 4.813917535234428e-05 loss: 0.1256 (0.1437) time: 2.9084 data: 0.0024 max mem: 19788 +Epoch: [1] [1400/2138] eta: 0:36:42 lr: 4.813389117212495e-05 loss: 0.1230 (0.1437) time: 2.9109 data: 0.0025 max mem: 19788 +Epoch: [1] [1410/2138] eta: 0:36:13 lr: 4.8128606927449064e-05 loss: 0.1353 (0.1438) time: 2.9670 data: 0.0023 max mem: 19788 +Epoch: [1] [1420/2138] eta: 0:35:42 lr: 4.8123322618307984e-05 loss: 0.1275 (0.1436) time: 2.9660 data: 0.0022 max mem: 19788 +Epoch: [1] [1430/2138] eta: 0:35:12 lr: 4.8118038244693046e-05 loss: 0.1188 (0.1435) time: 2.9165 data: 0.0025 max mem: 19788 +Epoch: [1] [1440/2138] eta: 0:34:42 lr: 4.8112753806595604e-05 loss: 0.1140 (0.1434) time: 2.9672 data: 0.0025 max mem: 19788 +Epoch: [1] [1450/2138] eta: 0:34:12 lr: 4.8107469304007004e-05 loss: 0.1294 (0.1434) time: 2.9802 data: 0.0024 max mem: 19788 +Epoch: [1] [1460/2138] eta: 0:33:43 lr: 4.8102184736918574e-05 loss: 0.1383 (0.1434) time: 2.9828 data: 0.0026 max mem: 19788 +Epoch: [1] [1470/2138] eta: 0:33:13 lr: 4.809690010532167e-05 loss: 0.1309 (0.1433) time: 3.0023 data: 0.0024 max mem: 19788 +Epoch: [1] [1480/2138] eta: 0:32:43 lr: 4.809161540920762e-05 loss: 0.1309 (0.1432) time: 2.9703 data: 0.0022 max mem: 19788 +Epoch: [1] [1490/2138] eta: 0:32:13 lr: 4.808633064856776e-05 loss: 0.1376 (0.1433) time: 2.9950 data: 0.0023 max mem: 19788 +Epoch: [1] [1500/2138] eta: 0:31:44 lr: 4.8081045823393415e-05 loss: 0.1321 (0.1431) time: 3.0279 data: 0.0022 max mem: 19788 +Epoch: [1] [1510/2138] eta: 0:31:14 lr: 4.807576093367593e-05 loss: 0.1213 (0.1431) time: 3.0360 data: 0.0021 max mem: 19788 +Epoch: [1] [1520/2138] eta: 0:30:44 lr: 4.807047597940662e-05 loss: 0.1440 (0.1433) time: 2.9924 data: 0.0021 max mem: 19788 +Epoch: [1] [1530/2138] eta: 0:30:14 lr: 4.806519096057682e-05 loss: 0.1360 (0.1433) time: 2.9567 data: 0.0021 max mem: 19788 +Epoch: [1] [1540/2138] eta: 0:29:44 lr: 4.8059905877177844e-05 loss: 0.1083 (0.1432) time: 2.9641 data: 0.0023 max mem: 19788 +Epoch: [1] [1550/2138] eta: 0:29:14 lr: 4.8054620729201036e-05 loss: 0.1266 (0.1433) time: 2.9463 data: 0.0025 max mem: 19788 +Epoch: [1] [1560/2138] eta: 0:28:44 lr: 4.804933551663769e-05 loss: 0.1266 (0.1432) time: 2.9285 data: 0.0026 max mem: 19788 +Epoch: [1] [1570/2138] eta: 0:28:14 lr: 4.8044050239479124e-05 loss: 0.1121 (0.1431) time: 2.9017 data: 0.0027 max mem: 19788 +Epoch: [1] [1580/2138] eta: 0:27:44 lr: 4.803876489771666e-05 loss: 0.1243 (0.1430) time: 2.8915 data: 0.0025 max mem: 19788 +Epoch: [1] [1590/2138] eta: 0:27:14 lr: 4.803347949134162e-05 loss: 0.1396 (0.1431) time: 2.8946 data: 0.0023 max mem: 19788 +Epoch: [1] [1600/2138] eta: 0:26:44 lr: 4.8028194020345303e-05 loss: 0.1319 (0.1429) time: 2.9298 data: 0.0023 max mem: 19788 +Epoch: [1] [1610/2138] eta: 0:26:14 lr: 4.8022908484719015e-05 loss: 0.1319 (0.1429) time: 2.9380 data: 0.0022 max mem: 19788 +Epoch: [1] [1620/2138] eta: 0:25:44 lr: 4.801762288445407e-05 loss: 0.1151 (0.1427) time: 2.9083 data: 0.0020 max mem: 19788 +Epoch: [1] [1630/2138] eta: 0:25:14 lr: 4.801233721954177e-05 loss: 0.1154 (0.1426) time: 2.9279 data: 0.0020 max mem: 19788 +Epoch: [1] [1640/2138] eta: 0:24:44 lr: 4.800705148997341e-05 loss: 0.1216 (0.1425) time: 3.0329 data: 0.0020 max mem: 19788 +Epoch: [1] [1650/2138] eta: 0:24:14 lr: 4.800176569574029e-05 loss: 0.1154 (0.1424) time: 3.0081 data: 0.0021 max mem: 19788 +Epoch: [1] [1660/2138] eta: 0:23:44 lr: 4.799647983683371e-05 loss: 0.1149 (0.1422) time: 2.9278 data: 0.0021 max mem: 19788 +Epoch: [1] [1670/2138] eta: 0:23:15 lr: 4.799119391324497e-05 loss: 0.1155 (0.1421) time: 2.9539 data: 0.0020 max mem: 19788 +Epoch: [1] [1680/2138] eta: 0:22:45 lr: 4.798590792496535e-05 loss: 0.1162 (0.1420) time: 2.9746 data: 0.0021 max mem: 19788 +Epoch: [1] [1690/2138] eta: 0:22:15 lr: 4.798062187198615e-05 loss: 0.1124 (0.1419) time: 2.9634 data: 0.0021 max mem: 19788 +Epoch: [1] [1700/2138] eta: 0:21:45 lr: 4.797533575429866e-05 loss: 0.1155 (0.1419) time: 2.9414 data: 0.0020 max mem: 19788 +Epoch: [1] [1710/2138] eta: 0:21:15 lr: 4.7970049571894146e-05 loss: 0.1268 (0.1419) time: 2.9324 data: 0.0020 max mem: 19788 +Epoch: [1] [1720/2138] eta: 0:20:45 lr: 4.7964763324763915e-05 loss: 0.1243 (0.1418) time: 2.9272 data: 0.0020 max mem: 19788 +Epoch: [1] [1730/2138] eta: 0:20:15 lr: 4.795947701289924e-05 loss: 0.1212 (0.1418) time: 2.9584 data: 0.0022 max mem: 19788 +Epoch: [1] [1740/2138] eta: 0:19:45 lr: 4.79541906362914e-05 loss: 0.1183 (0.1416) time: 2.9826 data: 0.0024 max mem: 19788 +Epoch: [1] [1750/2138] eta: 0:19:16 lr: 4.7948904194931665e-05 loss: 0.1137 (0.1415) time: 3.0214 data: 0.0023 max mem: 19788 +Epoch: [1] [1760/2138] eta: 0:18:46 lr: 4.794361768881132e-05 loss: 0.1201 (0.1415) time: 3.0180 data: 0.0021 max mem: 19788 +Epoch: [1] [1770/2138] eta: 0:18:17 lr: 4.793833111792163e-05 loss: 0.1273 (0.1415) time: 3.0585 data: 0.0022 max mem: 19788 +Epoch: [1] [1780/2138] eta: 0:17:47 lr: 4.793304448225387e-05 loss: 0.1133 (0.1413) time: 3.0763 data: 0.0023 max mem: 19788 +Epoch: [1] [1790/2138] eta: 0:17:17 lr: 4.79277577817993e-05 loss: 0.1204 (0.1413) time: 2.9770 data: 0.0021 max mem: 19788 +Epoch: [1] [1800/2138] eta: 0:16:48 lr: 4.7922471016549196e-05 loss: 0.1204 (0.1413) time: 3.0932 data: 0.0020 max mem: 19788 +Epoch: [1] [1810/2138] eta: 0:16:18 lr: 4.7917184186494814e-05 loss: 0.1200 (0.1412) time: 3.0869 data: 0.0021 max mem: 19788 +Epoch: [1] [1820/2138] eta: 0:15:48 lr: 4.7911897291627416e-05 loss: 0.1104 (0.1410) time: 2.9288 data: 0.0021 max mem: 19788 +Epoch: [1] [1830/2138] eta: 0:15:18 lr: 4.790661033193826e-05 loss: 0.1024 (0.1409) time: 2.9322 data: 0.0020 max mem: 19788 +Epoch: [1] [1840/2138] eta: 0:14:48 lr: 4.790132330741861e-05 loss: 0.1038 (0.1408) time: 2.9346 data: 0.0021 max mem: 19788 +Epoch: [1] [1850/2138] eta: 0:14:18 lr: 4.78960362180597e-05 loss: 0.1042 (0.1407) time: 3.0492 data: 0.0020 max mem: 19788 +Epoch: [1] [1860/2138] eta: 0:13:49 lr: 4.789074906385281e-05 loss: 0.1015 (0.1405) time: 3.0651 data: 0.0021 max mem: 19788 +Epoch: [1] [1870/2138] eta: 0:13:19 lr: 4.788546184478917e-05 loss: 0.1171 (0.1405) time: 2.9531 data: 0.0021 max mem: 19788 +Epoch: [1] [1880/2138] eta: 0:12:49 lr: 4.788017456086004e-05 loss: 0.1319 (0.1404) time: 3.0696 data: 0.0022 max mem: 19788 +Epoch: [1] [1890/2138] eta: 0:12:19 lr: 4.7874887212056646e-05 loss: 0.1123 (0.1403) time: 3.1088 data: 0.0022 max mem: 19788 +Epoch: [1] [1900/2138] eta: 0:11:50 lr: 4.786959979837026e-05 loss: 0.1036 (0.1402) time: 3.1149 data: 0.0021 max mem: 19788 +Epoch: [1] [1910/2138] eta: 0:11:20 lr: 4.786431231979209e-05 loss: 0.1180 (0.1400) time: 3.1715 data: 0.0022 max mem: 19788 +Epoch: [1] [1920/2138] eta: 0:10:50 lr: 4.78590247763134e-05 loss: 0.1242 (0.1401) time: 3.0500 data: 0.0021 max mem: 19788 +Epoch: [1] [1930/2138] eta: 0:10:20 lr: 4.7853737167925414e-05 loss: 0.1330 (0.1401) time: 2.9486 data: 0.0020 max mem: 19788 +Epoch: [1] [1940/2138] eta: 0:09:50 lr: 4.784844949461936e-05 loss: 0.1191 (0.1400) time: 2.9309 data: 0.0020 max mem: 19788 +Epoch: [1] [1950/2138] eta: 0:09:21 lr: 4.784316175638649e-05 loss: 0.1128 (0.1399) time: 2.9156 data: 0.0020 max mem: 19788 +Epoch: [1] [1960/2138] eta: 0:08:51 lr: 4.783787395321802e-05 loss: 0.1077 (0.1398) time: 2.9955 data: 0.0020 max mem: 19788 +Epoch: [1] [1970/2138] eta: 0:08:21 lr: 4.7832586085105176e-05 loss: 0.1115 (0.1397) time: 3.0355 data: 0.0022 max mem: 19788 +Epoch: [1] [1980/2138] eta: 0:07:51 lr: 4.7827298152039185e-05 loss: 0.1135 (0.1395) time: 2.9690 data: 0.0024 max mem: 19788 +Epoch: [1] [1990/2138] eta: 0:07:21 lr: 4.782201015401127e-05 loss: 0.0936 (0.1394) time: 2.9734 data: 0.0023 max mem: 19788 +Epoch: [1] [2000/2138] eta: 0:06:51 lr: 4.781672209101265e-05 loss: 0.0928 (0.1392) time: 2.9738 data: 0.0022 max mem: 19788 +Epoch: [1] [2010/2138] eta: 0:06:22 lr: 4.7811433963034555e-05 loss: 0.0930 (0.1391) time: 2.9723 data: 0.0021 max mem: 19788 +Epoch: [1] [2020/2138] eta: 0:05:52 lr: 4.780614577006818e-05 loss: 0.1149 (0.1390) time: 3.0112 data: 0.0021 max mem: 19788 +Epoch: [1] [2030/2138] eta: 0:05:22 lr: 4.780085751210475e-05 loss: 0.1195 (0.1390) time: 2.9916 data: 0.0020 max mem: 19788 +Epoch: [1] [2040/2138] eta: 0:04:52 lr: 4.779556918913547e-05 loss: 0.1242 (0.1389) time: 2.9338 data: 0.0020 max mem: 19788 +Epoch: [1] [2050/2138] eta: 0:04:22 lr: 4.7790280801151565e-05 loss: 0.1067 (0.1389) time: 2.9250 data: 0.0023 max mem: 19788 +Epoch: [1] [2060/2138] eta: 0:03:52 lr: 4.7784992348144225e-05 loss: 0.1129 (0.1389) time: 2.9103 data: 0.0025 max mem: 19788 +Epoch: [1] [2070/2138] eta: 0:03:22 lr: 4.777970383010467e-05 loss: 0.1159 (0.1387) time: 2.9162 data: 0.0024 max mem: 19788 +Epoch: [1] [2080/2138] eta: 0:02:53 lr: 4.7774415247024076e-05 loss: 0.1051 (0.1387) time: 2.9459 data: 0.0025 max mem: 19788 +Epoch: [1] [2090/2138] eta: 0:02:23 lr: 4.776912659889367e-05 loss: 0.1412 (0.1387) time: 2.9302 data: 0.0022 max mem: 19788 +Epoch: [1] [2100/2138] eta: 0:01:53 lr: 4.7763837885704636e-05 loss: 0.1158 (0.1386) time: 2.9149 data: 0.0020 max mem: 19788 +Epoch: [1] [2110/2138] eta: 0:01:23 lr: 4.775854910744818e-05 loss: 0.1239 (0.1388) time: 2.9244 data: 0.0022 max mem: 19788 +Epoch: [1] [2120/2138] eta: 0:00:53 lr: 4.775326026411548e-05 loss: 0.1469 (0.1388) time: 2.9120 data: 0.0021 max mem: 19788 +Epoch: [1] [2130/2138] eta: 0:00:23 lr: 4.7747971355697735e-05 loss: 0.1301 (0.1388) time: 2.8959 data: 0.0020 max mem: 19788 +Epoch: [1] Total time: 1:46:14 +Test: [ 0/21770] eta: 17:40:36 time: 2.9231 data: 2.7252 max mem: 19788 +Test: [ 100/21770] eta: 0:26:13 time: 0.0438 data: 0.0014 max mem: 19788 +Test: [ 200/21770] eta: 0:21:03 time: 0.0433 data: 0.0014 max mem: 19788 +Test: [ 300/21770] eta: 0:19:45 time: 0.0472 data: 0.0016 max mem: 19788 +Test: [ 400/21770] eta: 0:19:02 time: 0.0448 data: 0.0015 max mem: 19788 +Test: [ 500/21770] eta: 0:18:27 time: 0.0427 data: 0.0015 max mem: 19788 +Test: [ 600/21770] eta: 0:17:57 time: 0.0443 data: 0.0014 max mem: 19788 +Test: [ 700/21770] eta: 0:17:33 time: 0.0501 data: 0.0015 max mem: 19788 +Test: [ 800/21770] eta: 0:17:21 time: 0.0424 data: 0.0014 max mem: 19788 +Test: [ 900/21770] eta: 0:17:14 time: 0.0496 data: 0.0017 max mem: 19788 +Test: [ 1000/21770] eta: 0:16:58 time: 0.0426 data: 0.0014 max mem: 19788 +Test: [ 1100/21770] eta: 0:16:52 time: 0.0523 data: 0.0018 max mem: 19788 +Test: [ 1200/21770] eta: 0:16:51 time: 0.0516 data: 0.0019 max mem: 19788 +Test: [ 1300/21770] eta: 0:16:48 time: 0.0509 data: 0.0017 max mem: 19788 +Test: [ 1400/21770] eta: 0:16:40 time: 0.0420 data: 0.0014 max mem: 19788 +Test: [ 1500/21770] eta: 0:16:29 time: 0.0517 data: 0.0017 max mem: 19788 +Test: [ 1600/21770] eta: 0:16:29 time: 0.0532 data: 0.0018 max mem: 19788 +Test: [ 1700/21770] eta: 0:16:25 time: 0.0525 data: 0.0018 max mem: 19788 +Test: [ 1800/21770] eta: 0:16:17 time: 0.0432 data: 0.0015 max mem: 19788 +Test: [ 1900/21770] eta: 0:16:05 time: 0.0421 data: 0.0014 max mem: 19788 +Test: [ 2000/21770] eta: 0:15:55 time: 0.0455 data: 0.0014 max mem: 19788 +Test: [ 2100/21770] eta: 0:15:47 time: 0.0455 data: 0.0016 max mem: 19788 +Test: [ 2200/21770] eta: 0:15:38 time: 0.0434 data: 0.0015 max mem: 19788 +Test: [ 2300/21770] eta: 0:15:34 time: 0.0526 data: 0.0019 max mem: 19788 +Test: [ 2400/21770] eta: 0:15:27 time: 0.0440 data: 0.0015 max mem: 19788 +Test: [ 2500/21770] eta: 0:15:21 time: 0.0439 data: 0.0015 max mem: 19788 +Test: [ 2600/21770] eta: 0:15:18 time: 0.0441 data: 0.0015 max mem: 19788 +Test: [ 2700/21770] eta: 0:15:12 time: 0.0511 data: 0.0017 max mem: 19788 +Test: [ 2800/21770] eta: 0:15:07 time: 0.0443 data: 0.0013 max mem: 19788 +Test: [ 2900/21770] eta: 0:15:01 time: 0.0449 data: 0.0014 max mem: 19788 +Test: [ 3000/21770] eta: 0:14:54 time: 0.0430 data: 0.0015 max mem: 19788 +Test: [ 3100/21770] eta: 0:14:48 time: 0.0489 data: 0.0017 max mem: 19788 +Test: [ 3200/21770] eta: 0:14:43 time: 0.0477 data: 0.0016 max mem: 19788 +Test: [ 3300/21770] eta: 0:14:39 time: 0.0529 data: 0.0017 max mem: 19788 +Test: [ 3400/21770] eta: 0:14:36 time: 0.0529 data: 0.0017 max mem: 19788 +Test: [ 3500/21770] eta: 0:14:32 time: 0.0467 data: 0.0016 max mem: 19788 +Test: [ 3600/21770] eta: 0:14:27 time: 0.0492 data: 0.0016 max mem: 19788 +Test: [ 3700/21770] eta: 0:14:24 time: 0.0496 data: 0.0017 max mem: 19788 +Test: [ 3800/21770] eta: 0:14:20 time: 0.0437 data: 0.0015 max mem: 19788 +Test: [ 3900/21770] eta: 0:14:15 time: 0.0431 data: 0.0014 max mem: 19788 +Test: [ 4000/21770] eta: 0:14:09 time: 0.0508 data: 0.0018 max mem: 19788 +Test: [ 4100/21770] eta: 0:14:03 time: 0.0524 data: 0.0017 max mem: 19788 +Test: [ 4200/21770] eta: 0:13:58 time: 0.0485 data: 0.0016 max mem: 19788 +Test: [ 4300/21770] eta: 0:13:54 time: 0.0519 data: 0.0016 max mem: 19788 +Test: [ 4400/21770] eta: 0:13:49 time: 0.0537 data: 0.0015 max mem: 19788 +Test: [ 4500/21770] eta: 0:13:43 time: 0.0452 data: 0.0015 max mem: 19788 +Test: [ 4600/21770] eta: 0:13:39 time: 0.0501 data: 0.0017 max mem: 19788 +Test: [ 4700/21770] eta: 0:13:36 time: 0.0530 data: 0.0018 max mem: 19788 +Test: [ 4800/21770] eta: 0:13:31 time: 0.0433 data: 0.0014 max mem: 19788 +Test: [ 4900/21770] eta: 0:13:26 time: 0.0449 data: 0.0013 max mem: 19788 +Test: [ 5000/21770] eta: 0:13:20 time: 0.0449 data: 0.0014 max mem: 19788 +Test: [ 5100/21770] eta: 0:13:14 time: 0.0436 data: 0.0016 max mem: 19788 +Test: [ 5200/21770] eta: 0:13:09 time: 0.0435 data: 0.0014 max mem: 19788 +Test: [ 5300/21770] eta: 0:13:04 time: 0.0454 data: 0.0014 max mem: 19788 +Test: [ 5400/21770] eta: 0:12:59 time: 0.0438 data: 0.0015 max mem: 19788 +Test: [ 5500/21770] eta: 0:12:53 time: 0.0440 data: 0.0016 max mem: 19788 +Test: [ 5600/21770] eta: 0:12:49 time: 0.0439 data: 0.0014 max mem: 19788 +Test: [ 5700/21770] eta: 0:12:43 time: 0.0445 data: 0.0015 max mem: 19788 +Test: [ 5800/21770] eta: 0:12:38 time: 0.0443 data: 0.0016 max mem: 19788 +Test: [ 5900/21770] eta: 0:12:32 time: 0.0434 data: 0.0016 max mem: 19788 +Test: [ 6000/21770] eta: 0:12:28 time: 0.0431 data: 0.0013 max mem: 19788 +Test: [ 6100/21770] eta: 0:12:22 time: 0.0446 data: 0.0015 max mem: 19788 +Test: [ 6200/21770] eta: 0:12:17 time: 0.0469 data: 0.0015 max mem: 19788 +Test: [ 6300/21770] eta: 0:12:13 time: 0.0538 data: 0.0018 max mem: 19788 +Test: [ 6400/21770] eta: 0:12:08 time: 0.0440 data: 0.0015 max mem: 19788 +Test: [ 6500/21770] eta: 0:12:03 time: 0.0447 data: 0.0016 max mem: 19788 +Test: [ 6600/21770] eta: 0:11:58 time: 0.0431 data: 0.0015 max mem: 19788 +Test: [ 6700/21770] eta: 0:11:53 time: 0.0429 data: 0.0015 max mem: 19788 +Test: [ 6800/21770] eta: 0:11:47 time: 0.0446 data: 0.0017 max mem: 19788 +Test: [ 6900/21770] eta: 0:11:42 time: 0.0456 data: 0.0017 max mem: 19788 +Test: [ 7000/21770] eta: 0:11:37 time: 0.0501 data: 0.0016 max mem: 19788 +Test: [ 7100/21770] eta: 0:11:33 time: 0.0458 data: 0.0016 max mem: 19788 +Test: [ 7200/21770] eta: 0:11:28 time: 0.0491 data: 0.0017 max mem: 19788 +Test: [ 7300/21770] eta: 0:11:23 time: 0.0459 data: 0.0016 max mem: 19788 +Test: [ 7400/21770] eta: 0:11:18 time: 0.0440 data: 0.0015 max mem: 19788 +Test: [ 7500/21770] eta: 0:11:13 time: 0.0438 data: 0.0015 max mem: 19788 +Test: [ 7600/21770] eta: 0:11:08 time: 0.0447 data: 0.0018 max mem: 19788 +Test: [ 7700/21770] eta: 0:11:03 time: 0.0516 data: 0.0017 max mem: 19788 +Test: [ 7800/21770] eta: 0:10:58 time: 0.0435 data: 0.0014 max mem: 19788 +Test: [ 7900/21770] eta: 0:10:53 time: 0.0455 data: 0.0014 max mem: 19788 +Test: [ 8000/21770] eta: 0:10:49 time: 0.0441 data: 0.0015 max mem: 19788 +Test: [ 8100/21770] eta: 0:10:45 time: 0.0534 data: 0.0018 max mem: 19788 +Test: [ 8200/21770] eta: 0:10:40 time: 0.0443 data: 0.0015 max mem: 19788 +Test: [ 8300/21770] eta: 0:10:34 time: 0.0438 data: 0.0014 max mem: 19788 +Test: [ 8400/21770] eta: 0:10:30 time: 0.0485 data: 0.0019 max mem: 19788 +Test: [ 8500/21770] eta: 0:10:25 time: 0.0452 data: 0.0019 max mem: 19788 +Test: [ 8600/21770] eta: 0:10:21 time: 0.0524 data: 0.0017 max mem: 19788 +Test: [ 8700/21770] eta: 0:10:16 time: 0.0439 data: 0.0014 max mem: 19788 +Test: [ 8800/21770] eta: 0:10:11 time: 0.0474 data: 0.0016 max mem: 19788 +Test: [ 8900/21770] eta: 0:10:07 time: 0.0517 data: 0.0018 max mem: 19788 +Test: [ 9000/21770] eta: 0:10:02 time: 0.0545 data: 0.0017 max mem: 19788 +Test: [ 9100/21770] eta: 0:09:57 time: 0.0439 data: 0.0013 max mem: 19788 +Test: [ 9200/21770] eta: 0:09:53 time: 0.0492 data: 0.0018 max mem: 19788 +Test: [ 9300/21770] eta: 0:09:49 time: 0.0436 data: 0.0016 max mem: 19788 +Test: [ 9400/21770] eta: 0:09:44 time: 0.0437 data: 0.0016 max mem: 19788 +Test: [ 9500/21770] eta: 0:09:39 time: 0.0519 data: 0.0017 max mem: 19788 +Test: [ 9600/21770] eta: 0:09:34 time: 0.0445 data: 0.0015 max mem: 19788 +Test: [ 9700/21770] eta: 0:09:29 time: 0.0443 data: 0.0016 max mem: 19788 +Test: [ 9800/21770] eta: 0:09:25 time: 0.0534 data: 0.0015 max mem: 19788 +Test: [ 9900/21770] eta: 0:09:20 time: 0.0497 data: 0.0018 max mem: 19788 +Test: [10000/21770] eta: 0:09:16 time: 0.0428 data: 0.0015 max mem: 19788 +Test: [10100/21770] eta: 0:09:11 time: 0.0436 data: 0.0015 max mem: 19788 +Test: [10200/21770] eta: 0:09:06 time: 0.0482 data: 0.0016 max mem: 19788 +Test: [10300/21770] eta: 0:09:01 time: 0.0453 data: 0.0018 max mem: 19788 +Test: [10400/21770] eta: 0:08:57 time: 0.0436 data: 0.0016 max mem: 19788 +Test: [10500/21770] eta: 0:08:52 time: 0.0451 data: 0.0013 max mem: 19788 +Test: [10600/21770] eta: 0:08:47 time: 0.0475 data: 0.0014 max mem: 19788 +Test: [10700/21770] eta: 0:08:42 time: 0.0441 data: 0.0014 max mem: 19788 +Test: [10800/21770] eta: 0:08:38 time: 0.0473 data: 0.0016 max mem: 19788 +Test: [10900/21770] eta: 0:08:33 time: 0.0529 data: 0.0018 max mem: 19788 +Test: [11000/21770] eta: 0:08:29 time: 0.0525 data: 0.0019 max mem: 19788 +Test: [11100/21770] eta: 0:08:24 time: 0.0436 data: 0.0016 max mem: 19788 +Test: [11200/21770] eta: 0:08:19 time: 0.0471 data: 0.0016 max mem: 19788 +Test: [11300/21770] eta: 0:08:15 time: 0.0441 data: 0.0015 max mem: 19788 +Test: [11400/21770] eta: 0:08:10 time: 0.0436 data: 0.0014 max mem: 19788 +Test: [11500/21770] eta: 0:08:05 time: 0.0476 data: 0.0017 max mem: 19788 +Test: [11600/21770] eta: 0:08:01 time: 0.0512 data: 0.0019 max mem: 19788 +Test: [11700/21770] eta: 0:07:56 time: 0.0433 data: 0.0014 max mem: 19788 +Test: [11800/21770] eta: 0:07:51 time: 0.0525 data: 0.0018 max mem: 19788 +Test: [11900/21770] eta: 0:07:47 time: 0.0456 data: 0.0016 max mem: 19788 +Test: [12000/21770] eta: 0:07:42 time: 0.0502 data: 0.0017 max mem: 19788 +Test: [12100/21770] eta: 0:07:37 time: 0.0505 data: 0.0016 max mem: 19788 +Test: [12200/21770] eta: 0:07:33 time: 0.0456 data: 0.0016 max mem: 19788 +Test: [12300/21770] eta: 0:07:28 time: 0.0517 data: 0.0016 max mem: 19788 +Test: [12400/21770] eta: 0:07:24 time: 0.0542 data: 0.0016 max mem: 19788 +Test: [12500/21770] eta: 0:07:19 time: 0.0442 data: 0.0015 max mem: 19788 +Test: [12600/21770] eta: 0:07:14 time: 0.0429 data: 0.0015 max mem: 19788 +Test: [12700/21770] eta: 0:07:09 time: 0.0434 data: 0.0015 max mem: 19788 +Test: [12800/21770] eta: 0:07:05 time: 0.0488 data: 0.0016 max mem: 19788 +Test: [12900/21770] eta: 0:07:00 time: 0.0496 data: 0.0016 max mem: 19788 +Test: [13000/21770] eta: 0:06:55 time: 0.0524 data: 0.0018 max mem: 19788 +Test: [13100/21770] eta: 0:06:51 time: 0.0472 data: 0.0014 max mem: 19788 +Test: [13200/21770] eta: 0:06:46 time: 0.0443 data: 0.0015 max mem: 19788 +Test: [13300/21770] eta: 0:06:41 time: 0.0528 data: 0.0017 max mem: 19788 +Test: [13400/21770] eta: 0:06:37 time: 0.0459 data: 0.0014 max mem: 19788 +Test: [13500/21770] eta: 0:06:32 time: 0.0455 data: 0.0015 max mem: 19788 +Test: [13600/21770] eta: 0:06:27 time: 0.0454 data: 0.0014 max mem: 19788 +Test: [13700/21770] eta: 0:06:22 time: 0.0439 data: 0.0014 max mem: 19788 +Test: [13800/21770] eta: 0:06:17 time: 0.0454 data: 0.0015 max mem: 19788 +Test: [13900/21770] eta: 0:06:13 time: 0.0453 data: 0.0013 max mem: 19788 +Test: [14000/21770] eta: 0:06:08 time: 0.0525 data: 0.0018 max mem: 19788 +Test: [14100/21770] eta: 0:06:03 time: 0.0480 data: 0.0016 max mem: 19788 +Test: [14200/21770] eta: 0:05:59 time: 0.0443 data: 0.0016 max mem: 19788 +Test: [14300/21770] eta: 0:05:54 time: 0.0526 data: 0.0018 max mem: 19788 +Test: [14400/21770] eta: 0:05:49 time: 0.0438 data: 0.0014 max mem: 19788 +Test: [14500/21770] eta: 0:05:44 time: 0.0504 data: 0.0018 max mem: 19788 +Test: [14600/21770] eta: 0:05:40 time: 0.0527 data: 0.0019 max mem: 19788 +Test: [14700/21770] eta: 0:05:35 time: 0.0438 data: 0.0016 max mem: 19788 +Test: [14800/21770] eta: 0:05:30 time: 0.0449 data: 0.0015 max mem: 19788 +Test: [14900/21770] eta: 0:05:25 time: 0.0525 data: 0.0017 max mem: 19788 +Test: [15000/21770] eta: 0:05:21 time: 0.0452 data: 0.0014 max mem: 19788 +Test: [15100/21770] eta: 0:05:16 time: 0.0535 data: 0.0019 max mem: 19788 +Test: [15200/21770] eta: 0:05:11 time: 0.0536 data: 0.0019 max mem: 19788 +Test: [15300/21770] eta: 0:05:07 time: 0.0530 data: 0.0018 max mem: 19788 +Test: [15400/21770] eta: 0:05:02 time: 0.0481 data: 0.0017 max mem: 19788 +Test: [15500/21770] eta: 0:04:58 time: 0.0530 data: 0.0018 max mem: 19788 +Test: [15600/21770] eta: 0:04:53 time: 0.0444 data: 0.0016 max mem: 19788 +Test: [15700/21770] eta: 0:04:48 time: 0.0437 data: 0.0014 max mem: 19788 +Test: [15800/21770] eta: 0:04:44 time: 0.0535 data: 0.0019 max mem: 19788 +Test: [15900/21770] eta: 0:04:39 time: 0.0489 data: 0.0015 max mem: 19788 +Test: [16000/21770] eta: 0:04:34 time: 0.0467 data: 0.0017 max mem: 19788 +Test: [16100/21770] eta: 0:04:30 time: 0.0531 data: 0.0018 max mem: 19788 +Test: [16200/21770] eta: 0:04:25 time: 0.0488 data: 0.0017 max mem: 19788 +Test: [16300/21770] eta: 0:04:20 time: 0.0447 data: 0.0015 max mem: 19788 +Test: [16400/21770] eta: 0:04:15 time: 0.0529 data: 0.0018 max mem: 19788 +Test: [16500/21770] eta: 0:04:11 time: 0.0514 data: 0.0017 max mem: 19788 +Test: [16600/21770] eta: 0:04:06 time: 0.0436 data: 0.0015 max mem: 19788 +Test: [16700/21770] eta: 0:04:01 time: 0.0451 data: 0.0014 max mem: 19788 +Test: [16800/21770] eta: 0:03:56 time: 0.0473 data: 0.0015 max mem: 19788 +Test: [16900/21770] eta: 0:03:52 time: 0.0457 data: 0.0015 max mem: 19788 +Test: [17000/21770] eta: 0:03:47 time: 0.0523 data: 0.0018 max mem: 19788 +Test: [17100/21770] eta: 0:03:42 time: 0.0468 data: 0.0015 max mem: 19788 +Test: [17200/21770] eta: 0:03:37 time: 0.0459 data: 0.0017 max mem: 19788 +Test: [17300/21770] eta: 0:03:33 time: 0.0536 data: 0.0018 max mem: 19788 +Test: [17400/21770] eta: 0:03:28 time: 0.0524 data: 0.0018 max mem: 19788 +Test: [17500/21770] eta: 0:03:23 time: 0.0465 data: 0.0015 max mem: 19788 +Test: [17600/21770] eta: 0:03:19 time: 0.0540 data: 0.0017 max mem: 19788 +Test: [17700/21770] eta: 0:03:14 time: 0.0445 data: 0.0018 max mem: 19788 +Test: [17800/21770] eta: 0:03:09 time: 0.0450 data: 0.0015 max mem: 19788 +Test: [17900/21770] eta: 0:03:04 time: 0.0468 data: 0.0015 max mem: 19788 +Test: [18000/21770] eta: 0:02:59 time: 0.0440 data: 0.0015 max mem: 19788 +Test: [18100/21770] eta: 0:02:55 time: 0.0501 data: 0.0016 max mem: 19788 +Test: [18200/21770] eta: 0:02:50 time: 0.0442 data: 0.0015 max mem: 19788 +Test: [18300/21770] eta: 0:02:45 time: 0.0529 data: 0.0017 max mem: 19788 +Test: [18400/21770] eta: 0:02:40 time: 0.0527 data: 0.0017 max mem: 19788 +Test: [18500/21770] eta: 0:02:36 time: 0.0467 data: 0.0015 max mem: 19788 +Test: [18600/21770] eta: 0:02:31 time: 0.0446 data: 0.0015 max mem: 19788 +Test: [18700/21770] eta: 0:02:26 time: 0.0529 data: 0.0018 max mem: 19788 +Test: [18800/21770] eta: 0:02:21 time: 0.0467 data: 0.0016 max mem: 19788 +Test: [18900/21770] eta: 0:02:16 time: 0.0438 data: 0.0013 max mem: 19788 +Test: [19000/21770] eta: 0:02:12 time: 0.0438 data: 0.0015 max mem: 19788 +Test: [19100/21770] eta: 0:02:07 time: 0.0442 data: 0.0014 max mem: 19788 +Test: [19200/21770] eta: 0:02:02 time: 0.0417 data: 0.0013 max mem: 19788 +Test: [19300/21770] eta: 0:01:57 time: 0.0490 data: 0.0015 max mem: 19788 +Test: [19400/21770] eta: 0:01:52 time: 0.0489 data: 0.0017 max mem: 19788 +Test: [19500/21770] eta: 0:01:48 time: 0.0542 data: 0.0017 max mem: 19788 +Test: [19600/21770] eta: 0:01:43 time: 0.0486 data: 0.0017 max mem: 19788 +Test: [19700/21770] eta: 0:01:38 time: 0.0445 data: 0.0015 max mem: 19788 +Test: [19800/21770] eta: 0:01:33 time: 0.0452 data: 0.0014 max mem: 19788 +Test: [19900/21770] eta: 0:01:29 time: 0.0446 data: 0.0015 max mem: 19788 +Test: [20000/21770] eta: 0:01:24 time: 0.0516 data: 0.0014 max mem: 19788 +Test: [20100/21770] eta: 0:01:19 time: 0.0481 data: 0.0015 max mem: 19788 +Test: [20200/21770] eta: 0:01:14 time: 0.0440 data: 0.0014 max mem: 19788 +Test: [20300/21770] eta: 0:01:10 time: 0.0449 data: 0.0013 max mem: 19788 +Test: [20400/21770] eta: 0:01:05 time: 0.0521 data: 0.0018 max mem: 19788 +Test: [20500/21770] eta: 0:01:00 time: 0.0443 data: 0.0014 max mem: 19788 +Test: [20600/21770] eta: 0:00:55 time: 0.0534 data: 0.0018 max mem: 19788 +Test: [20700/21770] eta: 0:00:51 time: 0.0437 data: 0.0016 max mem: 19788 +Test: [20800/21770] eta: 0:00:46 time: 0.0438 data: 0.0018 max mem: 19788 +Test: [20900/21770] eta: 0:00:41 time: 0.0437 data: 0.0014 max mem: 19788 +Test: [21000/21770] eta: 0:00:36 time: 0.0438 data: 0.0015 max mem: 19788 +Test: [21100/21770] eta: 0:00:31 time: 0.0452 data: 0.0014 max mem: 19788 +Test: [21200/21770] eta: 0:00:27 time: 0.0426 data: 0.0014 max mem: 19788 +Test: [21300/21770] eta: 0:00:22 time: 0.0442 data: 0.0016 max mem: 19788 +Test: [21400/21770] eta: 0:00:17 time: 0.0529 data: 0.0016 max mem: 19788 +Test: [21500/21770] eta: 0:00:12 time: 0.0470 data: 0.0017 max mem: 19788 +Test: [21600/21770] eta: 0:00:08 time: 0.0442 data: 0.0015 max mem: 19788 +Test: [21700/21770] eta: 0:00:03 time: 0.0512 data: 0.0016 max mem: 19788 +Test: Total time: 0:17:17 +Final results: +Mean IoU is 55.86 + + precision@0.5 = 61.20 + precision@0.6 = 54.50 + precision@0.7 = 46.26 + precision@0.8 = 34.88 + precision@0.9 = 14.30 + overall IoU = 59.31 + mean IoU = 55.86 + +Mean accuracy for one-to-zero sample is 76.84 + +Average object IoU 0.558630188401842 +Overall IoU 59.31121826171875 +Better epoch: 1 + +Epoch: [2] [ 0/2138] eta: 3:45:09 lr: 4.774374018209639e-05 loss: 0.2244 (0.2244) time: 6.3190 data: 2.0112 max mem: 19788 +Epoch: [2] [ 10/2138] eta: 1:58:39 lr: 4.7738451156503353e-05 loss: 0.1307 (0.1340) time: 3.3456 data: 0.1855 max mem: 19788 +Epoch: [2] [ 20/2138] eta: 1:52:00 lr: 4.77331620658006e-05 loss: 0.1216 (0.1304) time: 3.0156 data: 0.0022 max mem: 19788 +Epoch: [2] [ 30/2138] eta: 1:50:08 lr: 4.77278729099793e-05 loss: 0.1038 (0.1259) time: 3.0192 data: 0.0020 max mem: 19788 +Epoch: [2] [ 40/2138] eta: 1:50:32 lr: 4.772258368903064e-05 loss: 0.1182 (0.1248) time: 3.1491 data: 0.0025 max mem: 19788 +Epoch: [2] [ 50/2138] eta: 1:49:06 lr: 4.77172944029458e-05 loss: 0.1029 (0.1224) time: 3.1351 data: 0.0026 max mem: 19788 +Epoch: [2] [ 60/2138] eta: 1:47:36 lr: 4.771200505171595e-05 loss: 0.1013 (0.1227) time: 2.9956 data: 0.0025 max mem: 19788 +Epoch: [2] [ 70/2138] eta: 1:46:29 lr: 4.7706715635332264e-05 loss: 0.1052 (0.1221) time: 2.9743 data: 0.0023 max mem: 19788 +Epoch: [2] [ 80/2138] eta: 1:45:16 lr: 4.770142615378591e-05 loss: 0.1089 (0.1207) time: 2.9545 data: 0.0022 max mem: 19788 +Epoch: [2] [ 90/2138] eta: 1:44:09 lr: 4.7696136607068063e-05 loss: 0.1209 (0.1215) time: 2.9158 data: 0.0021 max mem: 19788 +Epoch: [2] [ 100/2138] eta: 1:43:12 lr: 4.769084699516989e-05 loss: 0.1209 (0.1218) time: 2.9136 data: 0.0021 max mem: 19788 +Epoch: [2] [ 110/2138] eta: 1:42:22 lr: 4.768555731808254e-05 loss: 0.1296 (0.1237) time: 2.9266 data: 0.0021 max mem: 19788 +Epoch: [2] [ 120/2138] eta: 1:41:35 lr: 4.7680267575797197e-05 loss: 0.1085 (0.1215) time: 2.9294 data: 0.0022 max mem: 19788 +Epoch: [2] [ 130/2138] eta: 1:40:50 lr: 4.7674977768305e-05 loss: 0.0949 (0.1206) time: 2.9269 data: 0.0023 max mem: 19788 +Epoch: [2] [ 140/2138] eta: 1:40:14 lr: 4.766968789559712e-05 loss: 0.1157 (0.1211) time: 2.9480 data: 0.0022 max mem: 19788 +Epoch: [2] [ 150/2138] eta: 1:39:33 lr: 4.766439795766471e-05 loss: 0.1162 (0.1217) time: 2.9476 data: 0.0022 max mem: 19788 +Epoch: [2] [ 160/2138] eta: 1:38:59 lr: 4.765910795449891e-05 loss: 0.1124 (0.1213) time: 2.9493 data: 0.0022 max mem: 19788 +Epoch: [2] [ 170/2138] eta: 1:38:18 lr: 4.7653817886090884e-05 loss: 0.1273 (0.1227) time: 2.9392 data: 0.0024 max mem: 19788 +Epoch: [2] [ 180/2138] eta: 1:37:47 lr: 4.764852775243177e-05 loss: 0.1273 (0.1226) time: 2.9480 data: 0.0023 max mem: 19788 +Epoch: [2] [ 190/2138] eta: 1:37:14 lr: 4.764323755351273e-05 loss: 0.1067 (0.1216) time: 2.9792 data: 0.0023 max mem: 19788 +Epoch: [2] [ 200/2138] eta: 1:36:40 lr: 4.763794728932489e-05 loss: 0.1006 (0.1208) time: 2.9620 data: 0.0023 max mem: 19788 +Epoch: [2] [ 210/2138] eta: 1:36:06 lr: 4.76326569598594e-05 loss: 0.0948 (0.1198) time: 2.9478 data: 0.0022 max mem: 19788 +Epoch: [2] [ 220/2138] eta: 1:35:28 lr: 4.7627366565107386e-05 loss: 0.0985 (0.1200) time: 2.9209 data: 0.0021 max mem: 19788 +Epoch: [2] [ 230/2138] eta: 1:34:52 lr: 4.762207610506e-05 loss: 0.1367 (0.1207) time: 2.9083 data: 0.0020 max mem: 19788 +Epoch: [2] [ 240/2138] eta: 1:34:23 lr: 4.761678557970837e-05 loss: 0.1134 (0.1200) time: 2.9513 data: 0.0021 max mem: 19788 +Epoch: [2] [ 250/2138] eta: 1:33:52 lr: 4.7611494989043625e-05 loss: 0.1076 (0.1195) time: 2.9776 data: 0.0022 max mem: 19788 +Epoch: [2] [ 260/2138] eta: 1:33:23 lr: 4.76062043330569e-05 loss: 0.1026 (0.1190) time: 2.9821 data: 0.0022 max mem: 19788 +Epoch: [2] [ 270/2138] eta: 1:32:59 lr: 4.760091361173932e-05 loss: 0.0977 (0.1192) time: 3.0325 data: 0.0021 max mem: 19788 +Epoch: [2] [ 280/2138] eta: 1:32:32 lr: 4.759562282508201e-05 loss: 0.1036 (0.1195) time: 3.0557 data: 0.0023 max mem: 19788 +Epoch: [2] [ 290/2138] eta: 1:32:03 lr: 4.7590331973076094e-05 loss: 0.1088 (0.1202) time: 3.0147 data: 0.0028 max mem: 19788 +Epoch: [2] [ 300/2138] eta: 1:31:32 lr: 4.758504105571269e-05 loss: 0.1175 (0.1208) time: 2.9854 data: 0.0029 max mem: 19788 +Epoch: [2] [ 310/2138] eta: 1:30:55 lr: 4.757975007298291e-05 loss: 0.1043 (0.1200) time: 2.9218 data: 0.0024 max mem: 19788 +Epoch: [2] [ 320/2138] eta: 1:30:23 lr: 4.757445902487788e-05 loss: 0.0857 (0.1192) time: 2.9049 data: 0.0023 max mem: 19788 +Epoch: [2] [ 330/2138] eta: 1:29:49 lr: 4.756916791138871e-05 loss: 0.1019 (0.1193) time: 2.9239 data: 0.0022 max mem: 19788 +Epoch: [2] [ 340/2138] eta: 1:29:13 lr: 4.7563876732506505e-05 loss: 0.1074 (0.1194) time: 2.8890 data: 0.0022 max mem: 19788 +Epoch: [2] [ 350/2138] eta: 1:28:38 lr: 4.7558585488222386e-05 loss: 0.1148 (0.1194) time: 2.8721 data: 0.0025 max mem: 19788 +Epoch: [2] [ 360/2138] eta: 1:28:03 lr: 4.7553294178527455e-05 loss: 0.1277 (0.1194) time: 2.8688 data: 0.0025 max mem: 19788 +Epoch: [2] [ 370/2138] eta: 1:27:29 lr: 4.75480028034128e-05 loss: 0.1159 (0.1195) time: 2.8791 data: 0.0023 max mem: 19788 +Epoch: [2] [ 380/2138] eta: 1:26:56 lr: 4.754271136286955e-05 loss: 0.1159 (0.1196) time: 2.8892 data: 0.0022 max mem: 19788 +Epoch: [2] [ 390/2138] eta: 1:26:23 lr: 4.753741985688879e-05 loss: 0.1082 (0.1200) time: 2.8931 data: 0.0022 max mem: 19788 +Epoch: [2] [ 400/2138] eta: 1:25:50 lr: 4.753212828546161e-05 loss: 0.1071 (0.1200) time: 2.8853 data: 0.0025 max mem: 19788 +Epoch: [2] [ 410/2138] eta: 1:25:16 lr: 4.7526836648579124e-05 loss: 0.1073 (0.1201) time: 2.8752 data: 0.0028 max mem: 19788 +Epoch: [2] [ 420/2138] eta: 1:24:43 lr: 4.752154494623241e-05 loss: 0.1074 (0.1199) time: 2.8719 data: 0.0024 max mem: 19788 +Epoch: [2] [ 430/2138] eta: 1:24:10 lr: 4.751625317841256e-05 loss: 0.1074 (0.1198) time: 2.8753 data: 0.0020 max mem: 19788 +Epoch: [2] [ 440/2138] eta: 1:23:37 lr: 4.751096134511066e-05 loss: 0.1058 (0.1197) time: 2.8738 data: 0.0021 max mem: 19788 +Epoch: [2] [ 450/2138] eta: 1:23:05 lr: 4.7505669446317804e-05 loss: 0.1037 (0.1194) time: 2.8704 data: 0.0021 max mem: 19788 +Epoch: [2] [ 460/2138] eta: 1:22:32 lr: 4.750037748202507e-05 loss: 0.1028 (0.1189) time: 2.8757 data: 0.0022 max mem: 19788 +Epoch: [2] [ 470/2138] eta: 1:22:01 lr: 4.749508545222354e-05 loss: 0.1025 (0.1186) time: 2.8857 data: 0.0024 max mem: 19788 +Epoch: [2] [ 480/2138] eta: 1:21:30 lr: 4.74897933569043e-05 loss: 0.1172 (0.1190) time: 2.9027 data: 0.0024 max mem: 19788 +Epoch: [2] [ 490/2138] eta: 1:20:58 lr: 4.748450119605841e-05 loss: 0.1196 (0.1194) time: 2.8896 data: 0.0026 max mem: 19788 +Epoch: [2] [ 500/2138] eta: 1:20:25 lr: 4.747920896967696e-05 loss: 0.1257 (0.1194) time: 2.8643 data: 0.0028 max mem: 19788 +Epoch: [2] [ 510/2138] eta: 1:19:53 lr: 4.7473916677751004e-05 loss: 0.1247 (0.1196) time: 2.8635 data: 0.0029 max mem: 19788 +Epoch: [2] [ 520/2138] eta: 1:19:23 lr: 4.7468624320271635e-05 loss: 0.1196 (0.1195) time: 2.8929 data: 0.0028 max mem: 19788 +Epoch: [2] [ 530/2138] eta: 1:18:53 lr: 4.7463331897229903e-05 loss: 0.1008 (0.1190) time: 2.9150 data: 0.0025 max mem: 19788 +Epoch: [2] [ 540/2138] eta: 1:18:21 lr: 4.745803940861688e-05 loss: 0.0928 (0.1185) time: 2.8939 data: 0.0025 max mem: 19788 +Epoch: [2] [ 550/2138] eta: 1:17:51 lr: 4.745274685442362e-05 loss: 0.0988 (0.1189) time: 2.8898 data: 0.0027 max mem: 19788 +Epoch: [2] [ 560/2138] eta: 1:17:21 lr: 4.7447454234641195e-05 loss: 0.1055 (0.1186) time: 2.9099 data: 0.0027 max mem: 19788 +Epoch: [2] [ 570/2138] eta: 1:16:53 lr: 4.744216154926065e-05 loss: 0.1028 (0.1184) time: 2.9673 data: 0.0026 max mem: 19788 +Epoch: [2] [ 580/2138] eta: 1:16:26 lr: 4.743686879827305e-05 loss: 0.0952 (0.1181) time: 3.0157 data: 0.0024 max mem: 19788 +Epoch: [2] [ 590/2138] eta: 1:15:56 lr: 4.743157598166944e-05 loss: 0.1007 (0.1181) time: 2.9810 data: 0.0022 max mem: 19788 +Epoch: [2] [ 600/2138] eta: 1:15:27 lr: 4.7426283099440886e-05 loss: 0.1007 (0.1180) time: 2.9368 data: 0.0021 max mem: 19788 +Epoch: [2] [ 610/2138] eta: 1:15:01 lr: 4.742099015157842e-05 loss: 0.0944 (0.1177) time: 3.0155 data: 0.0024 max mem: 19788 +Epoch: [2] [ 620/2138] eta: 1:14:32 lr: 4.741569713807309e-05 loss: 0.0977 (0.1177) time: 3.0224 data: 0.0026 max mem: 19788 +Epoch: [2] [ 630/2138] eta: 1:14:01 lr: 4.741040405891595e-05 loss: 0.1066 (0.1175) time: 2.9281 data: 0.0025 max mem: 19788 +Epoch: [2] [ 640/2138] eta: 1:13:31 lr: 4.740511091409803e-05 loss: 0.1010 (0.1172) time: 2.9185 data: 0.0028 max mem: 19788 +Epoch: [2] [ 650/2138] eta: 1:13:01 lr: 4.739981770361038e-05 loss: 0.1010 (0.1172) time: 2.9173 data: 0.0032 max mem: 19788 +Epoch: [2] [ 660/2138] eta: 1:12:31 lr: 4.739452442744403e-05 loss: 0.1044 (0.1171) time: 2.9152 data: 0.0030 max mem: 19788 +Epoch: [2] [ 670/2138] eta: 1:12:01 lr: 4.7389231085590025e-05 loss: 0.0931 (0.1167) time: 2.9073 data: 0.0024 max mem: 19788 +Epoch: [2] [ 680/2138] eta: 1:11:30 lr: 4.738393767803938e-05 loss: 0.0931 (0.1166) time: 2.8993 data: 0.0021 max mem: 19788 +Epoch: [2] [ 690/2138] eta: 1:11:00 lr: 4.737864420478313e-05 loss: 0.1117 (0.1166) time: 2.9076 data: 0.0021 max mem: 19788 +Epoch: [2] [ 700/2138] eta: 1:10:30 lr: 4.737335066581231e-05 loss: 0.1093 (0.1163) time: 2.9091 data: 0.0021 max mem: 19788 +Epoch: [2] [ 710/2138] eta: 1:10:02 lr: 4.736805706111794e-05 loss: 0.1145 (0.1164) time: 2.9541 data: 0.0022 max mem: 19788 +Epoch: [2] [ 720/2138] eta: 1:09:32 lr: 4.736276339069104e-05 loss: 0.1145 (0.1162) time: 2.9614 data: 0.0024 max mem: 19788 +Epoch: [2] [ 730/2138] eta: 1:09:03 lr: 4.735746965452264e-05 loss: 0.0930 (0.1160) time: 2.9419 data: 0.0026 max mem: 19788 +Epoch: [2] [ 740/2138] eta: 1:08:34 lr: 4.735217585260374e-05 loss: 0.1058 (0.1160) time: 2.9659 data: 0.0025 max mem: 19788 +Epoch: [2] [ 750/2138] eta: 1:08:05 lr: 4.734688198492538e-05 loss: 0.1063 (0.1161) time: 2.9680 data: 0.0023 max mem: 19788 +Epoch: [2] [ 760/2138] eta: 1:07:35 lr: 4.734158805147855e-05 loss: 0.1103 (0.1161) time: 2.9436 data: 0.0024 max mem: 19788 +Epoch: [2] [ 770/2138] eta: 1:07:07 lr: 4.733629405225428e-05 loss: 0.1052 (0.1160) time: 2.9628 data: 0.0023 max mem: 19788 +Epoch: [2] [ 780/2138] eta: 1:06:37 lr: 4.7330999987243567e-05 loss: 0.0945 (0.1160) time: 2.9603 data: 0.0022 max mem: 19788 +Epoch: [2] [ 790/2138] eta: 1:06:07 lr: 4.732570585643743e-05 loss: 0.0945 (0.1156) time: 2.9072 data: 0.0023 max mem: 19788 +Epoch: [2] [ 800/2138] eta: 1:05:37 lr: 4.7320411659826853e-05 loss: 0.1020 (0.1158) time: 2.9022 data: 0.0025 max mem: 19788 +Epoch: [2] [ 810/2138] eta: 1:05:07 lr: 4.731511739740285e-05 loss: 0.1115 (0.1158) time: 2.9260 data: 0.0028 max mem: 19788 +Epoch: [2] [ 820/2138] eta: 1:04:37 lr: 4.730982306915642e-05 loss: 0.1065 (0.1158) time: 2.9227 data: 0.0028 max mem: 19788 +Epoch: [2] [ 830/2138] eta: 1:04:07 lr: 4.730452867507856e-05 loss: 0.1035 (0.1157) time: 2.8924 data: 0.0025 max mem: 19788 +Epoch: [2] [ 840/2138] eta: 1:03:37 lr: 4.729923421516026e-05 loss: 0.1080 (0.1158) time: 2.8985 data: 0.0026 max mem: 19788 +Epoch: [2] [ 850/2138] eta: 1:03:07 lr: 4.729393968939253e-05 loss: 0.1100 (0.1158) time: 2.9063 data: 0.0026 max mem: 19788 +Epoch: [2] [ 860/2138] eta: 1:02:38 lr: 4.7288645097766335e-05 loss: 0.0975 (0.1156) time: 2.9277 data: 0.0027 max mem: 19788 +Epoch: [2] [ 870/2138] eta: 1:02:08 lr: 4.7283350440272674e-05 loss: 0.1002 (0.1155) time: 2.9312 data: 0.0026 max mem: 19788 +Epoch: [2] [ 880/2138] eta: 1:01:38 lr: 4.727805571690254e-05 loss: 0.1115 (0.1156) time: 2.9102 data: 0.0022 max mem: 19788 +Epoch: [2] [ 890/2138] eta: 1:01:08 lr: 4.727276092764689e-05 loss: 0.0976 (0.1153) time: 2.9123 data: 0.0022 max mem: 19788 +Epoch: [2] [ 900/2138] eta: 1:00:39 lr: 4.726746607249673e-05 loss: 0.0933 (0.1153) time: 2.9189 data: 0.0024 max mem: 19788 +Epoch: [2] [ 910/2138] eta: 1:00:09 lr: 4.726217115144303e-05 loss: 0.0935 (0.1152) time: 2.9219 data: 0.0026 max mem: 19788 +Epoch: [2] [ 920/2138] eta: 0:59:40 lr: 4.725687616447677e-05 loss: 0.0862 (0.1150) time: 2.9293 data: 0.0025 max mem: 19788 +Epoch: [2] [ 930/2138] eta: 0:59:10 lr: 4.7251581111588915e-05 loss: 0.1041 (0.1151) time: 2.9404 data: 0.0026 max mem: 19788 +Epoch: [2] [ 940/2138] eta: 0:58:41 lr: 4.724628599277044e-05 loss: 0.1266 (0.1151) time: 2.9272 data: 0.0027 max mem: 19788 +Epoch: [2] [ 950/2138] eta: 0:58:11 lr: 4.724099080801231e-05 loss: 0.1121 (0.1151) time: 2.9315 data: 0.0026 max mem: 19788 +Epoch: [2] [ 960/2138] eta: 0:57:42 lr: 4.723569555730551e-05 loss: 0.0925 (0.1148) time: 2.9317 data: 0.0027 max mem: 19788 +Epoch: [2] [ 970/2138] eta: 0:57:12 lr: 4.723040024064098e-05 loss: 0.0820 (0.1147) time: 2.9024 data: 0.0026 max mem: 19788 +Epoch: [2] [ 980/2138] eta: 0:56:42 lr: 4.722510485800969e-05 loss: 0.0897 (0.1146) time: 2.9065 data: 0.0024 max mem: 19788 +Epoch: [2] [ 990/2138] eta: 0:56:12 lr: 4.721980940940259e-05 loss: 0.1044 (0.1145) time: 2.9147 data: 0.0023 max mem: 19788 +Epoch: [2] [1000/2138] eta: 0:55:43 lr: 4.721451389481066e-05 loss: 0.0951 (0.1144) time: 2.9161 data: 0.0023 max mem: 19788 +Epoch: [2] [1010/2138] eta: 0:55:14 lr: 4.720921831422484e-05 loss: 0.0940 (0.1143) time: 2.9688 data: 0.0024 max mem: 19788 +Epoch: [2] [1020/2138] eta: 0:54:45 lr: 4.720392266763608e-05 loss: 0.0965 (0.1142) time: 2.9630 data: 0.0024 max mem: 19788 +Epoch: [2] [1030/2138] eta: 0:54:15 lr: 4.719862695503534e-05 loss: 0.1042 (0.1142) time: 2.9091 data: 0.0023 max mem: 19788 +Epoch: [2] [1040/2138] eta: 0:53:45 lr: 4.719333117641355e-05 loss: 0.1090 (0.1142) time: 2.9051 data: 0.0022 max mem: 19788 +Epoch: [2] [1050/2138] eta: 0:53:16 lr: 4.7188035331761676e-05 loss: 0.1042 (0.1141) time: 2.9281 data: 0.0023 max mem: 19788 +Epoch: [2] [1060/2138] eta: 0:52:46 lr: 4.718273942107065e-05 loss: 0.0999 (0.1140) time: 2.9098 data: 0.0024 max mem: 19788 +Epoch: [2] [1070/2138] eta: 0:52:16 lr: 4.7177443444331405e-05 loss: 0.0983 (0.1138) time: 2.8588 data: 0.0023 max mem: 19788 +Epoch: [2] [1080/2138] eta: 0:51:46 lr: 4.717214740153489e-05 loss: 0.0946 (0.1138) time: 2.8642 data: 0.0023 max mem: 19788 +Epoch: [2] [1090/2138] eta: 0:51:16 lr: 4.716685129267204e-05 loss: 0.1016 (0.1138) time: 2.8759 data: 0.0024 max mem: 19788 +Epoch: [2] [1100/2138] eta: 0:50:46 lr: 4.716155511773378e-05 loss: 0.1066 (0.1140) time: 2.9020 data: 0.0025 max mem: 19788 +Epoch: [2] [1110/2138] eta: 0:50:18 lr: 4.715625887671104e-05 loss: 0.1050 (0.1138) time: 2.9763 data: 0.0025 max mem: 19788 +Epoch: [2] [1120/2138] eta: 0:49:49 lr: 4.715096256959477e-05 loss: 0.0927 (0.1137) time: 3.0185 data: 0.0027 max mem: 19788 +Epoch: [2] [1130/2138] eta: 0:49:20 lr: 4.714566619637587e-05 loss: 0.0981 (0.1137) time: 2.9882 data: 0.0029 max mem: 19788 +Epoch: [2] [1140/2138] eta: 0:48:51 lr: 4.714036975704528e-05 loss: 0.0981 (0.1136) time: 2.9675 data: 0.0028 max mem: 19788 +Epoch: [2] [1150/2138] eta: 0:48:22 lr: 4.713507325159391e-05 loss: 0.1113 (0.1137) time: 2.9960 data: 0.0026 max mem: 19788 +Epoch: [2] [1160/2138] eta: 0:47:54 lr: 4.712977668001269e-05 loss: 0.0977 (0.1135) time: 3.0210 data: 0.0030 max mem: 19788 +Epoch: [2] [1170/2138] eta: 0:47:25 lr: 4.712448004229253e-05 loss: 0.0921 (0.1133) time: 3.0041 data: 0.0030 max mem: 19788 +Epoch: [2] [1180/2138] eta: 0:46:56 lr: 4.7119183338424345e-05 loss: 0.0945 (0.1133) time: 2.9997 data: 0.0025 max mem: 19788 +Epoch: [2] [1190/2138] eta: 0:46:27 lr: 4.7113886568399045e-05 loss: 0.0945 (0.1132) time: 2.9911 data: 0.0025 max mem: 19788 +Epoch: [2] [1200/2138] eta: 0:45:58 lr: 4.710858973220754e-05 loss: 0.0897 (0.1129) time: 3.0089 data: 0.0026 max mem: 19788 +Epoch: [2] [1210/2138] eta: 0:45:29 lr: 4.710329282984074e-05 loss: 0.0965 (0.1129) time: 2.9919 data: 0.0027 max mem: 19788 +Epoch: [2] [1220/2138] eta: 0:44:59 lr: 4.7097995861289543e-05 loss: 0.1023 (0.1128) time: 2.9335 data: 0.0028 max mem: 19788 +Epoch: [2] [1230/2138] eta: 0:44:30 lr: 4.7092698826544865e-05 loss: 0.1029 (0.1127) time: 2.9821 data: 0.0027 max mem: 19788 +Epoch: [2] [1240/2138] eta: 0:44:01 lr: 4.708740172559759e-05 loss: 0.0965 (0.1126) time: 2.9720 data: 0.0024 max mem: 19788 +Epoch: [2] [1250/2138] eta: 0:43:32 lr: 4.708210455843863e-05 loss: 0.1014 (0.1126) time: 2.9488 data: 0.0024 max mem: 19788 +Epoch: [2] [1260/2138] eta: 0:43:02 lr: 4.707680732505886e-05 loss: 0.0949 (0.1124) time: 2.9472 data: 0.0023 max mem: 19788 +Epoch: [2] [1270/2138] eta: 0:42:32 lr: 4.707151002544919e-05 loss: 0.0860 (0.1124) time: 2.9089 data: 0.0023 max mem: 19788 +Epoch: [2] [1280/2138] eta: 0:42:03 lr: 4.706621265960051e-05 loss: 0.1117 (0.1124) time: 2.9640 data: 0.0027 max mem: 19788 +Epoch: [2] [1290/2138] eta: 0:41:34 lr: 4.7060915227503695e-05 loss: 0.1103 (0.1123) time: 2.9637 data: 0.0029 max mem: 19788 +Epoch: [2] [1300/2138] eta: 0:41:04 lr: 4.7055617729149634e-05 loss: 0.0899 (0.1122) time: 2.9080 data: 0.0028 max mem: 19788 +Epoch: [2] [1310/2138] eta: 0:40:35 lr: 4.705032016452923e-05 loss: 0.0850 (0.1120) time: 2.9286 data: 0.0024 max mem: 19788 +Epoch: [2] [1320/2138] eta: 0:40:05 lr: 4.704502253363334e-05 loss: 0.0937 (0.1121) time: 2.9408 data: 0.0024 max mem: 19788 +Epoch: [2] [1330/2138] eta: 0:39:37 lr: 4.703972483645285e-05 loss: 0.1143 (0.1121) time: 3.0104 data: 0.0026 max mem: 19788 +Epoch: [2] [1340/2138] eta: 0:39:08 lr: 4.7034427072978636e-05 loss: 0.1206 (0.1122) time: 3.0291 data: 0.0028 max mem: 19788 +Epoch: [2] [1350/2138] eta: 0:38:38 lr: 4.7029129243201576e-05 loss: 0.1133 (0.1122) time: 2.9477 data: 0.0030 max mem: 19788 +Epoch: [2] [1360/2138] eta: 0:38:08 lr: 4.702383134711253e-05 loss: 0.1099 (0.1122) time: 2.9107 data: 0.0028 max mem: 19788 +Epoch: [2] [1370/2138] eta: 0:37:40 lr: 4.701853338470238e-05 loss: 0.1099 (0.1124) time: 2.9767 data: 0.0026 max mem: 19788 +Epoch: [2] [1380/2138] eta: 0:37:10 lr: 4.701323535596198e-05 loss: 0.1179 (0.1125) time: 2.9893 data: 0.0025 max mem: 19788 +Epoch: [2] [1390/2138] eta: 0:36:41 lr: 4.7007937260882206e-05 loss: 0.1029 (0.1124) time: 2.9246 data: 0.0024 max mem: 19788 +Epoch: [2] [1400/2138] eta: 0:36:11 lr: 4.70026390994539e-05 loss: 0.0877 (0.1123) time: 2.9371 data: 0.0024 max mem: 19788 +Epoch: [2] [1410/2138] eta: 0:35:41 lr: 4.699734087166795e-05 loss: 0.0832 (0.1123) time: 2.9227 data: 0.0025 max mem: 19788 +Epoch: [2] [1420/2138] eta: 0:35:12 lr: 4.6992042577515197e-05 loss: 0.1039 (0.1122) time: 2.9245 data: 0.0026 max mem: 19788 +Epoch: [2] [1430/2138] eta: 0:34:43 lr: 4.698674421698649e-05 loss: 0.1059 (0.1121) time: 3.0063 data: 0.0029 max mem: 19788 +Epoch: [2] [1440/2138] eta: 0:34:14 lr: 4.698144579007268e-05 loss: 0.1028 (0.1121) time: 3.0477 data: 0.0029 max mem: 19788 +Epoch: [2] [1450/2138] eta: 0:33:45 lr: 4.6976147296764635e-05 loss: 0.0921 (0.1120) time: 3.0232 data: 0.0028 max mem: 19788 +Epoch: [2] [1460/2138] eta: 0:33:17 lr: 4.697084873705318e-05 loss: 0.0953 (0.1120) time: 3.1489 data: 0.0026 max mem: 19788 +Epoch: [2] [1470/2138] eta: 0:32:48 lr: 4.6965550110929176e-05 loss: 0.1058 (0.1120) time: 3.1380 data: 0.0023 max mem: 19788 +Epoch: [2] [1480/2138] eta: 0:32:19 lr: 4.696025141838345e-05 loss: 0.1046 (0.1119) time: 3.0190 data: 0.0024 max mem: 19788 +Epoch: [2] [1490/2138] eta: 0:31:50 lr: 4.695495265940685e-05 loss: 0.1055 (0.1121) time: 3.0223 data: 0.0026 max mem: 19788 +Epoch: [2] [1500/2138] eta: 0:31:20 lr: 4.6949653833990226e-05 loss: 0.0970 (0.1120) time: 2.9939 data: 0.0024 max mem: 19788 +Epoch: [2] [1510/2138] eta: 0:30:51 lr: 4.6944354942124394e-05 loss: 0.0936 (0.1119) time: 2.9673 data: 0.0026 max mem: 19788 +Epoch: [2] [1520/2138] eta: 0:30:21 lr: 4.693905598380019e-05 loss: 0.0962 (0.1119) time: 2.9411 data: 0.0028 max mem: 19788 +Epoch: [2] [1530/2138] eta: 0:29:52 lr: 4.6933756959008454e-05 loss: 0.1007 (0.1119) time: 2.9484 data: 0.0027 max mem: 19788 +Epoch: [2] [1540/2138] eta: 0:29:23 lr: 4.692845786774001e-05 loss: 0.0883 (0.1118) time: 2.9555 data: 0.0026 max mem: 19788 +Epoch: [2] [1550/2138] eta: 0:28:53 lr: 4.692315870998566e-05 loss: 0.0908 (0.1119) time: 2.9375 data: 0.0023 max mem: 19788 +Epoch: [2] [1560/2138] eta: 0:28:23 lr: 4.691785948573627e-05 loss: 0.1131 (0.1119) time: 2.9215 data: 0.0020 max mem: 19788 +Epoch: [2] [1570/2138] eta: 0:27:54 lr: 4.691256019498263e-05 loss: 0.0892 (0.1118) time: 2.9218 data: 0.0022 max mem: 19788 +Epoch: [2] [1580/2138] eta: 0:27:24 lr: 4.6907260837715566e-05 loss: 0.0896 (0.1117) time: 2.9576 data: 0.0023 max mem: 19788 +Epoch: [2] [1590/2138] eta: 0:26:55 lr: 4.6901961413925885e-05 loss: 0.0921 (0.1117) time: 2.9451 data: 0.0023 max mem: 19788 +Epoch: [2] [1600/2138] eta: 0:26:25 lr: 4.689666192360442e-05 loss: 0.0954 (0.1117) time: 2.9038 data: 0.0026 max mem: 19788 +Epoch: [2] [1610/2138] eta: 0:25:56 lr: 4.689136236674197e-05 loss: 0.0954 (0.1115) time: 2.9095 data: 0.0025 max mem: 19788 +Epoch: [2] [1620/2138] eta: 0:25:26 lr: 4.688606274332934e-05 loss: 0.0955 (0.1114) time: 2.9230 data: 0.0022 max mem: 19788 +Epoch: [2] [1630/2138] eta: 0:24:57 lr: 4.688076305335735e-05 loss: 0.0955 (0.1113) time: 2.9392 data: 0.0025 max mem: 19788 +Epoch: [2] [1640/2138] eta: 0:24:27 lr: 4.6875463296816785e-05 loss: 0.0911 (0.1112) time: 2.9201 data: 0.0024 max mem: 19788 +Epoch: [2] [1650/2138] eta: 0:23:58 lr: 4.6870163473698455e-05 loss: 0.0908 (0.1111) time: 2.9891 data: 0.0023 max mem: 19788 +Epoch: [2] [1660/2138] eta: 0:23:28 lr: 4.6864863583993165e-05 loss: 0.0867 (0.1110) time: 2.9995 data: 0.0023 max mem: 19788 +Epoch: [2] [1670/2138] eta: 0:22:59 lr: 4.685956362769169e-05 loss: 0.0802 (0.1109) time: 2.9373 data: 0.0022 max mem: 19788 +Epoch: [2] [1680/2138] eta: 0:22:29 lr: 4.685426360478485e-05 loss: 0.0830 (0.1108) time: 2.9329 data: 0.0025 max mem: 19788 +Epoch: [2] [1690/2138] eta: 0:22:00 lr: 4.684896351526342e-05 loss: 0.0916 (0.1108) time: 2.9281 data: 0.0025 max mem: 19788 +Epoch: [2] [1700/2138] eta: 0:21:30 lr: 4.68436633591182e-05 loss: 0.0803 (0.1107) time: 2.9410 data: 0.0022 max mem: 19788 +Epoch: [2] [1710/2138] eta: 0:21:01 lr: 4.683836313633997e-05 loss: 0.0808 (0.1107) time: 2.9664 data: 0.0022 max mem: 19788 +Epoch: [2] [1720/2138] eta: 0:20:32 lr: 4.683306284691951e-05 loss: 0.0927 (0.1106) time: 3.0342 data: 0.0023 max mem: 19788 +Epoch: [2] [1730/2138] eta: 0:20:03 lr: 4.6827762490847606e-05 loss: 0.0981 (0.1106) time: 3.1420 data: 0.0025 max mem: 19788 +Epoch: [2] [1740/2138] eta: 0:19:34 lr: 4.682246206811504e-05 loss: 0.0954 (0.1105) time: 3.1345 data: 0.0027 max mem: 19788 +Epoch: [2] [1750/2138] eta: 0:19:05 lr: 4.6817161578712584e-05 loss: 0.0905 (0.1104) time: 3.1091 data: 0.0027 max mem: 19788 +Epoch: [2] [1760/2138] eta: 0:18:35 lr: 4.681186102263102e-05 loss: 0.0845 (0.1103) time: 3.1228 data: 0.0026 max mem: 19788 +Epoch: [2] [1770/2138] eta: 0:18:06 lr: 4.680656039986112e-05 loss: 0.0896 (0.1103) time: 3.1237 data: 0.0024 max mem: 19788 +Epoch: [2] [1780/2138] eta: 0:17:37 lr: 4.680125971039363e-05 loss: 0.0745 (0.1101) time: 3.0846 data: 0.0024 max mem: 19788 +Epoch: [2] [1790/2138] eta: 0:17:08 lr: 4.6795958954219345e-05 loss: 0.0880 (0.1101) time: 3.0463 data: 0.0025 max mem: 19788 +Epoch: [2] [1800/2138] eta: 0:16:38 lr: 4.679065813132902e-05 loss: 0.0921 (0.1101) time: 3.0358 data: 0.0028 max mem: 19788 +Epoch: [2] [1810/2138] eta: 0:16:09 lr: 4.678535724171342e-05 loss: 0.0992 (0.1100) time: 3.0360 data: 0.0030 max mem: 19788 +Epoch: [2] [1820/2138] eta: 0:15:39 lr: 4.6780056285363295e-05 loss: 0.0874 (0.1099) time: 3.0183 data: 0.0025 max mem: 19788 +Epoch: [2] [1830/2138] eta: 0:15:10 lr: 4.677475526226941e-05 loss: 0.0839 (0.1098) time: 2.9349 data: 0.0022 max mem: 19788 +Epoch: [2] [1840/2138] eta: 0:14:40 lr: 4.676945417242252e-05 loss: 0.0884 (0.1099) time: 2.9202 data: 0.0025 max mem: 19788 +Epoch: [2] [1850/2138] eta: 0:14:11 lr: 4.676415301581338e-05 loss: 0.0819 (0.1098) time: 2.9669 data: 0.0027 max mem: 19788 +Epoch: [2] [1860/2138] eta: 0:13:41 lr: 4.6758851792432726e-05 loss: 0.0802 (0.1098) time: 2.9616 data: 0.0027 max mem: 19788 +Epoch: [2] [1870/2138] eta: 0:13:11 lr: 4.675355050227133e-05 loss: 0.0867 (0.1097) time: 2.8975 data: 0.0028 max mem: 19788 +Epoch: [2] [1880/2138] eta: 0:12:42 lr: 4.674824914531991e-05 loss: 0.0993 (0.1096) time: 2.8921 data: 0.0027 max mem: 19788 +Epoch: [2] [1890/2138] eta: 0:12:12 lr: 4.674294772156923e-05 loss: 0.0993 (0.1096) time: 2.9221 data: 0.0026 max mem: 19788 +Epoch: [2] [1900/2138] eta: 0:11:43 lr: 4.673764623101001e-05 loss: 0.0841 (0.1095) time: 2.9245 data: 0.0026 max mem: 19788 +Epoch: [2] [1910/2138] eta: 0:11:13 lr: 4.673234467363301e-05 loss: 0.0841 (0.1094) time: 2.8989 data: 0.0024 max mem: 19788 +Epoch: [2] [1920/2138] eta: 0:10:43 lr: 4.6727043049428946e-05 loss: 0.1121 (0.1094) time: 2.9211 data: 0.0025 max mem: 19788 +Epoch: [2] [1930/2138] eta: 0:10:14 lr: 4.6721741358388574e-05 loss: 0.1158 (0.1094) time: 2.9551 data: 0.0026 max mem: 19788 +Epoch: [2] [1940/2138] eta: 0:09:44 lr: 4.671643960050259e-05 loss: 0.0883 (0.1093) time: 2.9291 data: 0.0026 max mem: 19788 +Epoch: [2] [1950/2138] eta: 0:09:15 lr: 4.671113777576176e-05 loss: 0.0883 (0.1093) time: 2.9201 data: 0.0026 max mem: 19788 +Epoch: [2] [1960/2138] eta: 0:08:45 lr: 4.670583588415678e-05 loss: 0.0814 (0.1092) time: 2.9624 data: 0.0027 max mem: 19788 +Epoch: [2] [1970/2138] eta: 0:08:16 lr: 4.6700533925678386e-05 loss: 0.0828 (0.1092) time: 2.9567 data: 0.0029 max mem: 19788 +Epoch: [2] [1980/2138] eta: 0:07:46 lr: 4.6695231900317294e-05 loss: 0.1030 (0.1092) time: 2.9132 data: 0.0027 max mem: 19788 +Epoch: [2] [1990/2138] eta: 0:07:17 lr: 4.668992980806423e-05 loss: 0.0900 (0.1091) time: 2.9155 data: 0.0026 max mem: 19788 +Epoch: [2] [2000/2138] eta: 0:06:47 lr: 4.66846276489099e-05 loss: 0.0817 (0.1090) time: 2.9458 data: 0.0027 max mem: 19788 +Epoch: [2] [2010/2138] eta: 0:06:17 lr: 4.6679325422845014e-05 loss: 0.0848 (0.1090) time: 2.9418 data: 0.0028 max mem: 19788 +Epoch: [2] [2020/2138] eta: 0:05:48 lr: 4.66740231298603e-05 loss: 0.0912 (0.1089) time: 3.0349 data: 0.0027 max mem: 19788 +Epoch: [2] [2030/2138] eta: 0:05:19 lr: 4.6668720769946455e-05 loss: 0.0915 (0.1089) time: 3.0756 data: 0.0026 max mem: 19788 +Epoch: [2] [2040/2138] eta: 0:04:49 lr: 4.6663418343094185e-05 loss: 0.0902 (0.1089) time: 3.0213 data: 0.0027 max mem: 19788 +Epoch: [2] [2050/2138] eta: 0:04:20 lr: 4.6658115849294194e-05 loss: 0.0801 (0.1088) time: 3.0735 data: 0.0025 max mem: 19788 +Epoch: [2] [2060/2138] eta: 0:03:50 lr: 4.6652813288537176e-05 loss: 0.0756 (0.1087) time: 3.1256 data: 0.0023 max mem: 19788 +Epoch: [2] [2070/2138] eta: 0:03:21 lr: 4.664751066081385e-05 loss: 0.0710 (0.1086) time: 3.3055 data: 0.0024 max mem: 19788 +Epoch: [2] [2080/2138] eta: 0:02:51 lr: 4.664220796611489e-05 loss: 0.0857 (0.1086) time: 3.3067 data: 0.0025 max mem: 19788 +Epoch: [2] [2090/2138] eta: 0:02:22 lr: 4.6636905204430996e-05 loss: 0.0987 (0.1085) time: 3.0540 data: 0.0024 max mem: 19788 +Epoch: [2] [2100/2138] eta: 0:01:52 lr: 4.6631602375752856e-05 loss: 0.0882 (0.1084) time: 2.9701 data: 0.0026 max mem: 19788 +Epoch: [2] [2110/2138] eta: 0:01:22 lr: 4.662629948007117e-05 loss: 0.0882 (0.1085) time: 2.9477 data: 0.0030 max mem: 19788 +Epoch: [2] [2120/2138] eta: 0:00:53 lr: 4.6620996517376624e-05 loss: 0.1118 (0.1085) time: 2.9769 data: 0.0030 max mem: 19788 +Epoch: [2] [2130/2138] eta: 0:00:23 lr: 4.661569348765988e-05 loss: 0.1113 (0.1086) time: 3.0698 data: 0.0025 max mem: 19788 +Epoch: [2] Total time: 1:45:30 +Test: [ 0/21770] eta: 16:23:53 time: 2.7117 data: 2.6038 max mem: 19788 +Test: [ 100/21770] eta: 0:27:52 time: 0.0445 data: 0.0017 max mem: 19788 +Test: [ 200/21770] eta: 0:22:31 time: 0.0527 data: 0.0018 max mem: 19788 +Test: [ 300/21770] eta: 0:20:24 time: 0.0433 data: 0.0014 max mem: 19788 +Test: [ 400/21770] eta: 0:19:21 time: 0.0494 data: 0.0017 max mem: 19788 +Test: [ 500/21770] eta: 0:18:52 time: 0.0447 data: 0.0015 max mem: 19788 +Test: [ 600/21770] eta: 0:18:43 time: 0.0504 data: 0.0018 max mem: 19788 +Test: [ 700/21770] eta: 0:18:10 time: 0.0425 data: 0.0013 max mem: 19788 +Test: [ 800/21770] eta: 0:17:45 time: 0.0466 data: 0.0015 max mem: 19788 +Test: [ 900/21770] eta: 0:17:34 time: 0.0518 data: 0.0017 max mem: 19788 +Test: [ 1000/21770] eta: 0:17:18 time: 0.0432 data: 0.0017 max mem: 19788 +Test: [ 1100/21770] eta: 0:17:01 time: 0.0439 data: 0.0017 max mem: 19788 +Test: [ 1200/21770] eta: 0:16:56 time: 0.0522 data: 0.0018 max mem: 19788 +Test: [ 1300/21770] eta: 0:16:45 time: 0.0426 data: 0.0014 max mem: 19788 +Test: [ 1400/21770] eta: 0:16:39 time: 0.0498 data: 0.0017 max mem: 19788 +Test: [ 1500/21770] eta: 0:16:30 time: 0.0527 data: 0.0017 max mem: 19788 +Test: [ 1600/21770] eta: 0:16:25 time: 0.0470 data: 0.0017 max mem: 19788 +Test: [ 1700/21770] eta: 0:16:21 time: 0.0450 data: 0.0015 max mem: 19788 +Test: [ 1800/21770] eta: 0:16:14 time: 0.0418 data: 0.0014 max mem: 19788 +Test: [ 1900/21770] eta: 0:16:08 time: 0.0502 data: 0.0017 max mem: 19788 +Test: [ 2000/21770] eta: 0:15:58 time: 0.0434 data: 0.0015 max mem: 19788 +Test: [ 2100/21770] eta: 0:15:52 time: 0.0511 data: 0.0018 max mem: 19788 +Test: [ 2200/21770] eta: 0:15:47 time: 0.0428 data: 0.0014 max mem: 19788 +Test: [ 2300/21770] eta: 0:15:39 time: 0.0424 data: 0.0015 max mem: 19788 +Test: [ 2400/21770] eta: 0:15:30 time: 0.0435 data: 0.0015 max mem: 19788 +Test: [ 2500/21770] eta: 0:15:22 time: 0.0439 data: 0.0015 max mem: 19788 +Test: [ 2600/21770] eta: 0:15:14 time: 0.0457 data: 0.0015 max mem: 19788 +Test: [ 2700/21770] eta: 0:15:13 time: 0.0514 data: 0.0017 max mem: 19788 +Test: [ 2800/21770] eta: 0:15:06 time: 0.0449 data: 0.0016 max mem: 19788 +Test: [ 2900/21770] eta: 0:15:02 time: 0.0535 data: 0.0018 max mem: 19788 +Test: [ 3000/21770] eta: 0:14:57 time: 0.0509 data: 0.0018 max mem: 19788 +Test: [ 3100/21770] eta: 0:14:50 time: 0.0447 data: 0.0014 max mem: 19788 +Test: [ 3200/21770] eta: 0:14:44 time: 0.0488 data: 0.0014 max mem: 19788 +Test: [ 3300/21770] eta: 0:14:38 time: 0.0426 data: 0.0016 max mem: 19788 +Test: [ 3400/21770] eta: 0:14:32 time: 0.0506 data: 0.0016 max mem: 19788 +Test: [ 3500/21770] eta: 0:14:27 time: 0.0524 data: 0.0018 max mem: 19788 +Test: [ 3600/21770] eta: 0:14:23 time: 0.0441 data: 0.0013 max mem: 19788 +Test: [ 3700/21770] eta: 0:14:21 time: 0.0504 data: 0.0016 max mem: 19788 +Test: [ 3800/21770] eta: 0:14:17 time: 0.0523 data: 0.0017 max mem: 19788 +Test: [ 3900/21770] eta: 0:14:13 time: 0.0438 data: 0.0015 max mem: 19788 +Test: [ 4000/21770] eta: 0:14:09 time: 0.0539 data: 0.0015 max mem: 19788 +Test: [ 4100/21770] eta: 0:14:03 time: 0.0466 data: 0.0014 max mem: 19788 +Test: [ 4200/21770] eta: 0:13:59 time: 0.0527 data: 0.0018 max mem: 19788 +Test: [ 4300/21770] eta: 0:13:55 time: 0.0522 data: 0.0017 max mem: 19788 +Test: [ 4400/21770] eta: 0:13:50 time: 0.0454 data: 0.0014 max mem: 19788 +Test: [ 4500/21770] eta: 0:13:46 time: 0.0450 data: 0.0017 max mem: 19788 +Test: [ 4600/21770] eta: 0:13:42 time: 0.0471 data: 0.0015 max mem: 19788 +Test: [ 4700/21770] eta: 0:13:38 time: 0.0515 data: 0.0018 max mem: 19788 +Test: [ 4800/21770] eta: 0:13:34 time: 0.0477 data: 0.0018 max mem: 19788 +Test: [ 4900/21770] eta: 0:13:28 time: 0.0449 data: 0.0014 max mem: 19788 +Test: [ 5000/21770] eta: 0:13:24 time: 0.0431 data: 0.0014 max mem: 19788 +Test: [ 5100/21770] eta: 0:13:19 time: 0.0536 data: 0.0017 max mem: 19788 +Test: [ 5200/21770] eta: 0:13:13 time: 0.0449 data: 0.0014 max mem: 19788 +Test: [ 5300/21770] eta: 0:13:08 time: 0.0470 data: 0.0015 max mem: 19788 +Test: [ 5400/21770] eta: 0:13:03 time: 0.0444 data: 0.0014 max mem: 19788 +Test: [ 5500/21770] eta: 0:12:59 time: 0.0543 data: 0.0016 max mem: 19788 +Test: [ 5600/21770] eta: 0:12:55 time: 0.0527 data: 0.0019 max mem: 19788 +Test: [ 5700/21770] eta: 0:12:51 time: 0.0498 data: 0.0016 max mem: 19788 +Test: [ 5800/21770] eta: 0:12:47 time: 0.0527 data: 0.0018 max mem: 19788 +Test: [ 5900/21770] eta: 0:12:42 time: 0.0452 data: 0.0015 max mem: 19788 +Test: [ 6000/21770] eta: 0:12:36 time: 0.0430 data: 0.0013 max mem: 19788 +Test: [ 6100/21770] eta: 0:12:31 time: 0.0440 data: 0.0014 max mem: 19788 +Test: [ 6200/21770] eta: 0:12:26 time: 0.0482 data: 0.0015 max mem: 19788 +Test: [ 6300/21770] eta: 0:12:20 time: 0.0549 data: 0.0015 max mem: 19788 +Test: [ 6400/21770] eta: 0:12:15 time: 0.0444 data: 0.0013 max mem: 19788 +Test: [ 6500/21770] eta: 0:12:10 time: 0.0434 data: 0.0015 max mem: 19788 +Test: [ 6600/21770] eta: 0:12:05 time: 0.0451 data: 0.0016 max mem: 19788 +Test: [ 6700/21770] eta: 0:12:00 time: 0.0444 data: 0.0014 max mem: 19788 +Test: [ 6800/21770] eta: 0:11:56 time: 0.0536 data: 0.0017 max mem: 19788 +Test: [ 6900/21770] eta: 0:11:51 time: 0.0472 data: 0.0015 max mem: 19788 +Test: [ 7000/21770] eta: 0:11:46 time: 0.0455 data: 0.0014 max mem: 19788 +Test: [ 7100/21770] eta: 0:11:40 time: 0.0439 data: 0.0015 max mem: 19788 +Test: [ 7200/21770] eta: 0:11:35 time: 0.0447 data: 0.0015 max mem: 19788 +Test: [ 7300/21770] eta: 0:11:29 time: 0.0449 data: 0.0015 max mem: 19788 +Test: [ 7400/21770] eta: 0:11:25 time: 0.0551 data: 0.0017 max mem: 19788 +Test: [ 7500/21770] eta: 0:11:20 time: 0.0441 data: 0.0016 max mem: 19788 +Test: [ 7600/21770] eta: 0:11:15 time: 0.0467 data: 0.0018 max mem: 19788 +Test: [ 7700/21770] eta: 0:11:10 time: 0.0471 data: 0.0016 max mem: 19788 +Test: [ 7800/21770] eta: 0:11:06 time: 0.0439 data: 0.0014 max mem: 19788 +Test: [ 7900/21770] eta: 0:11:01 time: 0.0431 data: 0.0014 max mem: 19788 +Test: [ 8000/21770] eta: 0:10:56 time: 0.0446 data: 0.0014 max mem: 19788 +Test: [ 8100/21770] eta: 0:10:51 time: 0.0461 data: 0.0015 max mem: 19788 +Test: [ 8200/21770] eta: 0:10:45 time: 0.0444 data: 0.0015 max mem: 19788 +Test: [ 8300/21770] eta: 0:10:41 time: 0.0512 data: 0.0015 max mem: 19788 +Test: [ 8400/21770] eta: 0:10:37 time: 0.0502 data: 0.0018 max mem: 19788 +Test: [ 8500/21770] eta: 0:10:33 time: 0.0537 data: 0.0018 max mem: 19788 +Test: [ 8600/21770] eta: 0:10:28 time: 0.0504 data: 0.0018 max mem: 19788 +Test: [ 8700/21770] eta: 0:10:23 time: 0.0436 data: 0.0014 max mem: 19788 +Test: [ 8800/21770] eta: 0:10:18 time: 0.0432 data: 0.0016 max mem: 19788 +Test: [ 8900/21770] eta: 0:10:13 time: 0.0463 data: 0.0015 max mem: 19788 +Test: [ 9000/21770] eta: 0:10:08 time: 0.0450 data: 0.0017 max mem: 19788 +Test: [ 9100/21770] eta: 0:10:03 time: 0.0479 data: 0.0017 max mem: 19788 +Test: [ 9200/21770] eta: 0:09:58 time: 0.0454 data: 0.0015 max mem: 19788 +Test: [ 9300/21770] eta: 0:09:53 time: 0.0473 data: 0.0014 max mem: 19788 +Test: [ 9400/21770] eta: 0:09:48 time: 0.0509 data: 0.0015 max mem: 19788 +Test: [ 9500/21770] eta: 0:09:43 time: 0.0490 data: 0.0016 max mem: 19788 +Test: [ 9600/21770] eta: 0:09:39 time: 0.0495 data: 0.0016 max mem: 19788 +Test: [ 9700/21770] eta: 0:09:34 time: 0.0442 data: 0.0014 max mem: 19788 +Test: [ 9800/21770] eta: 0:09:29 time: 0.0453 data: 0.0014 max mem: 19788 +Test: [ 9900/21770] eta: 0:09:24 time: 0.0508 data: 0.0017 max mem: 19788 +Test: [10000/21770] eta: 0:09:20 time: 0.0495 data: 0.0017 max mem: 19788 +Test: [10100/21770] eta: 0:09:15 time: 0.0458 data: 0.0015 max mem: 19788 +Test: [10200/21770] eta: 0:09:10 time: 0.0449 data: 0.0015 max mem: 19788 +Test: [10300/21770] eta: 0:09:05 time: 0.0443 data: 0.0015 max mem: 19788 +Test: [10400/21770] eta: 0:09:01 time: 0.0464 data: 0.0015 max mem: 19788 +Test: [10500/21770] eta: 0:08:56 time: 0.0519 data: 0.0015 max mem: 19788 +Test: [10600/21770] eta: 0:08:51 time: 0.0468 data: 0.0015 max mem: 19788 +Test: [10700/21770] eta: 0:08:46 time: 0.0488 data: 0.0017 max mem: 19788 +Test: [10800/21770] eta: 0:08:42 time: 0.0529 data: 0.0019 max mem: 19788 +Test: [10900/21770] eta: 0:08:38 time: 0.0445 data: 0.0017 max mem: 19788 +Test: [11000/21770] eta: 0:08:33 time: 0.0466 data: 0.0016 max mem: 19788 +Test: [11100/21770] eta: 0:08:28 time: 0.0457 data: 0.0014 max mem: 19788 +Test: [11200/21770] eta: 0:08:23 time: 0.0456 data: 0.0016 max mem: 19788 +Test: [11300/21770] eta: 0:08:18 time: 0.0444 data: 0.0016 max mem: 19788 +Test: [11400/21770] eta: 0:08:13 time: 0.0459 data: 0.0016 max mem: 19788 +Test: [11500/21770] eta: 0:08:09 time: 0.0521 data: 0.0017 max mem: 19788 +Test: [11600/21770] eta: 0:08:04 time: 0.0451 data: 0.0014 max mem: 19788 +Test: [11700/21770] eta: 0:07:59 time: 0.0456 data: 0.0016 max mem: 19788 +Test: [11800/21770] eta: 0:07:54 time: 0.0530 data: 0.0019 max mem: 19788 +Test: [11900/21770] eta: 0:07:50 time: 0.0452 data: 0.0016 max mem: 19788 +Test: [12000/21770] eta: 0:07:45 time: 0.0466 data: 0.0016 max mem: 19788 +Test: [12100/21770] eta: 0:07:40 time: 0.0447 data: 0.0017 max mem: 19788 +Test: [12200/21770] eta: 0:07:35 time: 0.0456 data: 0.0016 max mem: 19788 +Test: [12300/21770] eta: 0:07:30 time: 0.0461 data: 0.0017 max mem: 19788 +Test: [12400/21770] eta: 0:07:25 time: 0.0482 data: 0.0016 max mem: 19788 +Test: [12500/21770] eta: 0:07:20 time: 0.0499 data: 0.0020 max mem: 19788 +Test: [12600/21770] eta: 0:07:16 time: 0.0521 data: 0.0016 max mem: 19788 +Test: [12700/21770] eta: 0:07:11 time: 0.0552 data: 0.0018 max mem: 19788 +Test: [12800/21770] eta: 0:07:06 time: 0.0501 data: 0.0019 max mem: 19788 +Test: [12900/21770] eta: 0:07:02 time: 0.0517 data: 0.0018 max mem: 19788 +Test: [13000/21770] eta: 0:06:57 time: 0.0452 data: 0.0017 max mem: 19788 +Test: [13100/21770] eta: 0:06:53 time: 0.0529 data: 0.0019 max mem: 19788 +Test: [13200/21770] eta: 0:06:48 time: 0.0458 data: 0.0014 max mem: 19788 +Test: [13300/21770] eta: 0:06:43 time: 0.0483 data: 0.0018 max mem: 19788 +Test: [13400/21770] eta: 0:06:38 time: 0.0443 data: 0.0016 max mem: 19788 +Test: [13500/21770] eta: 0:06:33 time: 0.0452 data: 0.0016 max mem: 19788 +Test: [13600/21770] eta: 0:06:29 time: 0.0548 data: 0.0015 max mem: 19788 +Test: [13700/21770] eta: 0:06:24 time: 0.0542 data: 0.0018 max mem: 19788 +Test: [13800/21770] eta: 0:06:19 time: 0.0527 data: 0.0018 max mem: 19788 +Test: [13900/21770] eta: 0:06:15 time: 0.0439 data: 0.0014 max mem: 19788 +Test: [14000/21770] eta: 0:06:10 time: 0.0445 data: 0.0015 max mem: 19788 +Test: [14100/21770] eta: 0:06:05 time: 0.0453 data: 0.0015 max mem: 19788 +Test: [14200/21770] eta: 0:06:00 time: 0.0448 data: 0.0015 max mem: 19788 +Test: [14300/21770] eta: 0:05:55 time: 0.0478 data: 0.0015 max mem: 19788 +Test: [14400/21770] eta: 0:05:50 time: 0.0437 data: 0.0015 max mem: 19788 +Test: [14500/21770] eta: 0:05:46 time: 0.0466 data: 0.0017 max mem: 19788 +Test: [14600/21770] eta: 0:05:41 time: 0.0539 data: 0.0019 max mem: 19788 +Test: [14700/21770] eta: 0:05:36 time: 0.0500 data: 0.0018 max mem: 19788 +Test: [14800/21770] eta: 0:05:32 time: 0.0522 data: 0.0017 max mem: 19788 +Test: [14900/21770] eta: 0:05:27 time: 0.0446 data: 0.0016 max mem: 19788 +Test: [15000/21770] eta: 0:05:22 time: 0.0496 data: 0.0017 max mem: 19788 +Test: [15100/21770] eta: 0:05:18 time: 0.0476 data: 0.0015 max mem: 19788 +Test: [15200/21770] eta: 0:05:13 time: 0.0541 data: 0.0019 max mem: 19788 +Test: [15300/21770] eta: 0:05:08 time: 0.0458 data: 0.0016 max mem: 19788 +Test: [15400/21770] eta: 0:05:03 time: 0.0504 data: 0.0018 max mem: 19788 +Test: [15500/21770] eta: 0:04:59 time: 0.0528 data: 0.0017 max mem: 19788 +Test: [15600/21770] eta: 0:04:54 time: 0.0453 data: 0.0015 max mem: 19788 +Test: [15700/21770] eta: 0:04:49 time: 0.0440 data: 0.0015 max mem: 19788 +Test: [15800/21770] eta: 0:04:44 time: 0.0445 data: 0.0014 max mem: 19788 +Test: [15900/21770] eta: 0:04:39 time: 0.0470 data: 0.0016 max mem: 19788 +Test: [16000/21770] eta: 0:04:35 time: 0.0444 data: 0.0016 max mem: 19788 +Test: [16100/21770] eta: 0:04:30 time: 0.0526 data: 0.0018 max mem: 19788 +Test: [16200/21770] eta: 0:04:25 time: 0.0529 data: 0.0019 max mem: 19788 +Test: [16300/21770] eta: 0:04:21 time: 0.0525 data: 0.0018 max mem: 19788 +Test: [16400/21770] eta: 0:04:16 time: 0.0434 data: 0.0014 max mem: 19788 +Test: [16500/21770] eta: 0:04:11 time: 0.0508 data: 0.0019 max mem: 19788 +Test: [16600/21770] eta: 0:04:06 time: 0.0440 data: 0.0015 max mem: 19788 +Test: [16700/21770] eta: 0:04:01 time: 0.0445 data: 0.0014 max mem: 19788 +Test: [16800/21770] eta: 0:03:57 time: 0.0477 data: 0.0017 max mem: 19788 +Test: [16900/21770] eta: 0:03:52 time: 0.0443 data: 0.0014 max mem: 19788 +Test: [17000/21770] eta: 0:03:47 time: 0.0500 data: 0.0020 max mem: 19788 +Test: [17100/21770] eta: 0:03:42 time: 0.0450 data: 0.0014 max mem: 19788 +Test: [17200/21770] eta: 0:03:37 time: 0.0442 data: 0.0018 max mem: 19788 +Test: [17300/21770] eta: 0:03:33 time: 0.0491 data: 0.0015 max mem: 19788 +Test: [17400/21770] eta: 0:03:28 time: 0.0446 data: 0.0015 max mem: 19788 +Test: [17500/21770] eta: 0:03:23 time: 0.0442 data: 0.0014 max mem: 19788 +Test: [17600/21770] eta: 0:03:18 time: 0.0520 data: 0.0016 max mem: 19788 +Test: [17700/21770] eta: 0:03:13 time: 0.0493 data: 0.0017 max mem: 19788 +Test: [17800/21770] eta: 0:03:09 time: 0.0525 data: 0.0017 max mem: 19788 +Test: [17900/21770] eta: 0:03:04 time: 0.0435 data: 0.0014 max mem: 19788 +Test: [18000/21770] eta: 0:02:59 time: 0.0435 data: 0.0016 max mem: 19788 +Test: [18100/21770] eta: 0:02:54 time: 0.0518 data: 0.0018 max mem: 19788 +Test: [18200/21770] eta: 0:02:49 time: 0.0448 data: 0.0015 max mem: 19788 +Test: [18300/21770] eta: 0:02:45 time: 0.0438 data: 0.0015 max mem: 19788 +Test: [18400/21770] eta: 0:02:40 time: 0.0433 data: 0.0015 max mem: 19788 +Test: [18500/21770] eta: 0:02:35 time: 0.0427 data: 0.0014 max mem: 19788 +Test: [18600/21770] eta: 0:02:30 time: 0.0438 data: 0.0013 max mem: 19788 +Test: [18700/21770] eta: 0:02:25 time: 0.0500 data: 0.0017 max mem: 19788 +Test: [18800/21770] eta: 0:02:21 time: 0.0472 data: 0.0016 max mem: 19788 +Test: [18900/21770] eta: 0:02:16 time: 0.0435 data: 0.0015 max mem: 19788 +Test: [19000/21770] eta: 0:02:11 time: 0.0482 data: 0.0018 max mem: 19788 +Test: [19100/21770] eta: 0:02:06 time: 0.0436 data: 0.0015 max mem: 19788 +Test: [19200/21770] eta: 0:02:02 time: 0.0440 data: 0.0016 max mem: 19788 +Test: [19300/21770] eta: 0:01:57 time: 0.0459 data: 0.0014 max mem: 19788 +Test: [19400/21770] eta: 0:01:52 time: 0.0485 data: 0.0016 max mem: 19788 +Test: [19500/21770] eta: 0:01:47 time: 0.0524 data: 0.0017 max mem: 19788 +Test: [19600/21770] eta: 0:01:42 time: 0.0442 data: 0.0015 max mem: 19788 +Test: [19700/21770] eta: 0:01:38 time: 0.0438 data: 0.0017 max mem: 19788 +Test: [19800/21770] eta: 0:01:33 time: 0.0439 data: 0.0014 max mem: 19788 +Test: [19900/21770] eta: 0:01:28 time: 0.0526 data: 0.0018 max mem: 19788 +Test: [20000/21770] eta: 0:01:24 time: 0.0527 data: 0.0018 max mem: 19788 +Test: [20100/21770] eta: 0:01:19 time: 0.0446 data: 0.0016 max mem: 19788 +Test: [20200/21770] eta: 0:01:14 time: 0.0479 data: 0.0016 max mem: 19788 +Test: [20300/21770] eta: 0:01:09 time: 0.0431 data: 0.0014 max mem: 19788 +Test: [20400/21770] eta: 0:01:05 time: 0.0438 data: 0.0015 max mem: 19788 +Test: [20500/21770] eta: 0:01:00 time: 0.0449 data: 0.0015 max mem: 19788 +Test: [20600/21770] eta: 0:00:55 time: 0.0527 data: 0.0018 max mem: 19788 +Test: [20700/21770] eta: 0:00:50 time: 0.0489 data: 0.0016 max mem: 19788 +Test: [20800/21770] eta: 0:00:46 time: 0.0460 data: 0.0017 max mem: 19788 +Test: [20900/21770] eta: 0:00:41 time: 0.0436 data: 0.0015 max mem: 19788 +Test: [21000/21770] eta: 0:00:36 time: 0.0470 data: 0.0016 max mem: 19788 +Test: [21100/21770] eta: 0:00:31 time: 0.0447 data: 0.0014 max mem: 19788 +Test: [21200/21770] eta: 0:00:27 time: 0.0481 data: 0.0018 max mem: 19788 +Test: [21300/21770] eta: 0:00:22 time: 0.0435 data: 0.0015 max mem: 19788 +Test: [21400/21770] eta: 0:00:17 time: 0.0481 data: 0.0016 max mem: 19788 +Test: [21500/21770] eta: 0:00:12 time: 0.0437 data: 0.0014 max mem: 19788 +Test: [21600/21770] eta: 0:00:08 time: 0.0528 data: 0.0019 max mem: 19788 +Test: [21700/21770] eta: 0:00:03 time: 0.0446 data: 0.0015 max mem: 19788 +Test: Total time: 0:17:13 +Final results: +Mean IoU is 56.67 + + precision@0.5 = 63.03 + precision@0.6 = 57.25 + precision@0.7 = 49.85 + precision@0.8 = 38.42 + precision@0.9 = 16.87 + overall IoU = 60.95 + mean IoU = 56.67 + +Mean accuracy for one-to-zero sample is 79.24 + +Average object IoU 0.5666947167464795 +Overall IoU 60.953861236572266 +Better epoch: 2 + +Epoch: [3] [ 0/2138] eta: 6:02:28 lr: 4.661145101562426e-05 loss: 0.2602 (0.2602) time: 10.1722 data: 1.3325 max mem: 19788 +Epoch: [3] [ 10/2138] eta: 2:07:05 lr: 4.660614786524411e-05 loss: 0.0857 (0.1080) time: 3.5833 data: 0.1229 max mem: 19788 +Epoch: [3] [ 20/2138] eta: 1:55:27 lr: 4.660084464781567e-05 loss: 0.0845 (0.1046) time: 2.9259 data: 0.0018 max mem: 19788 +Epoch: [3] [ 30/2138] eta: 1:51:02 lr: 4.659554136332963e-05 loss: 0.0805 (0.1007) time: 2.9278 data: 0.0022 max mem: 19788 +Epoch: [3] [ 40/2138] eta: 1:48:28 lr: 4.659023801177665e-05 loss: 0.0806 (0.0993) time: 2.9255 data: 0.0027 max mem: 19788 +Epoch: [3] [ 50/2138] eta: 1:47:32 lr: 4.65849345931474e-05 loss: 0.0876 (0.0968) time: 2.9811 data: 0.0025 max mem: 19788 +Epoch: [3] [ 60/2138] eta: 1:46:04 lr: 4.6579631107432545e-05 loss: 0.0758 (0.0951) time: 2.9808 data: 0.0026 max mem: 19788 +Epoch: [3] [ 70/2138] eta: 1:45:10 lr: 4.657432755462277e-05 loss: 0.0845 (0.0945) time: 2.9524 data: 0.0025 max mem: 19788 +Epoch: [3] [ 80/2138] eta: 1:44:28 lr: 4.65690239347087e-05 loss: 0.0910 (0.0944) time: 2.9950 data: 0.0023 max mem: 19788 +Epoch: [3] [ 90/2138] eta: 1:43:31 lr: 4.6563720247681023e-05 loss: 0.0888 (0.0947) time: 2.9689 data: 0.0025 max mem: 19788 +Epoch: [3] [ 100/2138] eta: 1:43:02 lr: 4.655841649353039e-05 loss: 0.0887 (0.0963) time: 2.9846 data: 0.0025 max mem: 19788 +Epoch: [3] [ 110/2138] eta: 1:42:17 lr: 4.6553112672247454e-05 loss: 0.1035 (0.0966) time: 2.9958 data: 0.0022 max mem: 19788 +Epoch: [3] [ 120/2138] eta: 1:41:46 lr: 4.654780878382286e-05 loss: 0.0854 (0.0961) time: 2.9856 data: 0.0022 max mem: 19788 +Epoch: [3] [ 130/2138] eta: 1:41:11 lr: 4.654250482824726e-05 loss: 0.0829 (0.0956) time: 3.0086 data: 0.0025 max mem: 19788 +Epoch: [3] [ 140/2138] eta: 1:41:29 lr: 4.65372008055113e-05 loss: 0.0921 (0.0967) time: 3.1824 data: 0.0026 max mem: 19788 +Epoch: [3] [ 150/2138] eta: 1:41:48 lr: 4.653189671560564e-05 loss: 0.0983 (0.0966) time: 3.3927 data: 0.0025 max mem: 19788 +Epoch: [3] [ 160/2138] eta: 1:41:40 lr: 4.65265925585209e-05 loss: 0.0929 (0.0964) time: 3.3385 data: 0.0023 max mem: 19788 +Epoch: [3] [ 170/2138] eta: 1:41:02 lr: 4.652128833424774e-05 loss: 0.1002 (0.0987) time: 3.1426 data: 0.0024 max mem: 19788 +Epoch: [3] [ 180/2138] eta: 1:40:29 lr: 4.651598404277677e-05 loss: 0.0956 (0.0982) time: 3.0436 data: 0.0025 max mem: 19788 +Epoch: [3] [ 190/2138] eta: 1:39:51 lr: 4.651067968409865e-05 loss: 0.0851 (0.0984) time: 3.0301 data: 0.0026 max mem: 19788 +Epoch: [3] [ 200/2138] eta: 1:39:27 lr: 4.6505375258204e-05 loss: 0.0828 (0.0974) time: 3.0733 data: 0.0024 max mem: 19788 +Epoch: [3] [ 210/2138] eta: 1:38:47 lr: 4.6500070765083455e-05 loss: 0.0700 (0.0966) time: 3.0626 data: 0.0023 max mem: 19788 +Epoch: [3] [ 220/2138] eta: 1:38:09 lr: 4.6494766204727634e-05 loss: 0.0689 (0.0961) time: 2.9841 data: 0.0026 max mem: 19788 +Epoch: [3] [ 230/2138] eta: 1:37:26 lr: 4.648946157712717e-05 loss: 0.0933 (0.0971) time: 2.9560 data: 0.0030 max mem: 19788 +Epoch: [3] [ 240/2138] eta: 1:36:45 lr: 4.648415688227268e-05 loss: 0.0906 (0.0963) time: 2.9278 data: 0.0032 max mem: 19788 +Epoch: [3] [ 250/2138] eta: 1:36:06 lr: 4.6478852120154776e-05 loss: 0.0777 (0.0960) time: 2.9415 data: 0.0029 max mem: 19788 +Epoch: [3] [ 260/2138] eta: 1:35:33 lr: 4.647354729076409e-05 loss: 0.0777 (0.0955) time: 2.9872 data: 0.0026 max mem: 19788 +Epoch: [3] [ 270/2138] eta: 1:34:55 lr: 4.646824239409123e-05 loss: 0.0874 (0.0958) time: 2.9846 data: 0.0026 max mem: 19788 +Epoch: [3] [ 280/2138] eta: 1:34:24 lr: 4.646293743012681e-05 loss: 0.0824 (0.0953) time: 2.9888 data: 0.0026 max mem: 19788 +Epoch: [3] [ 290/2138] eta: 1:33:46 lr: 4.6457632398861426e-05 loss: 0.0909 (0.0967) time: 2.9812 data: 0.0025 max mem: 19788 +Epoch: [3] [ 300/2138] eta: 1:33:09 lr: 4.6452327300285705e-05 loss: 0.1055 (0.0978) time: 2.9332 data: 0.0028 max mem: 19788 +Epoch: [3] [ 310/2138] eta: 1:32:35 lr: 4.644702213439024e-05 loss: 0.0827 (0.0973) time: 2.9598 data: 0.0027 max mem: 19788 +Epoch: [3] [ 320/2138] eta: 1:32:04 lr: 4.644171690116564e-05 loss: 0.0799 (0.0969) time: 3.0102 data: 0.0024 max mem: 19788 +Epoch: [3] [ 330/2138] eta: 1:31:35 lr: 4.643641160060249e-05 loss: 0.0843 (0.0972) time: 3.0477 data: 0.0023 max mem: 19788 +Epoch: [3] [ 340/2138] eta: 1:30:59 lr: 4.64311062326914e-05 loss: 0.0889 (0.0971) time: 2.9953 data: 0.0022 max mem: 19788 +Epoch: [3] [ 350/2138] eta: 1:30:23 lr: 4.6425800797422965e-05 loss: 0.0994 (0.0978) time: 2.9298 data: 0.0022 max mem: 19788 +Epoch: [3] [ 360/2138] eta: 1:29:51 lr: 4.642049529478777e-05 loss: 0.1162 (0.0980) time: 2.9649 data: 0.0022 max mem: 19788 +Epoch: [3] [ 370/2138] eta: 1:29:15 lr: 4.6415189724776405e-05 loss: 0.1086 (0.0983) time: 2.9535 data: 0.0022 max mem: 19788 +Epoch: [3] [ 380/2138] eta: 1:28:42 lr: 4.6409884087379465e-05 loss: 0.0919 (0.0983) time: 2.9348 data: 0.0025 max mem: 19788 +Epoch: [3] [ 390/2138] eta: 1:28:06 lr: 4.640457838258752e-05 loss: 0.0789 (0.0978) time: 2.9406 data: 0.0029 max mem: 19788 +Epoch: [3] [ 400/2138] eta: 1:27:32 lr: 4.6399272610391164e-05 loss: 0.0795 (0.0978) time: 2.9267 data: 0.0025 max mem: 19788 +Epoch: [3] [ 410/2138] eta: 1:26:58 lr: 4.639396677078097e-05 loss: 0.0861 (0.0978) time: 2.9300 data: 0.0021 max mem: 19788 +Epoch: [3] [ 420/2138] eta: 1:26:30 lr: 4.6388660863747525e-05 loss: 0.0774 (0.0977) time: 3.0055 data: 0.0022 max mem: 19788 +Epoch: [3] [ 430/2138] eta: 1:26:01 lr: 4.6383354889281393e-05 loss: 0.0781 (0.0975) time: 3.0675 data: 0.0023 max mem: 19788 +Epoch: [3] [ 440/2138] eta: 1:25:32 lr: 4.637804884737314e-05 loss: 0.0864 (0.0975) time: 3.0416 data: 0.0022 max mem: 19788 +Epoch: [3] [ 450/2138] eta: 1:25:03 lr: 4.6372742738013355e-05 loss: 0.0830 (0.0973) time: 3.0491 data: 0.0024 max mem: 19788 +Epoch: [3] [ 460/2138] eta: 1:24:32 lr: 4.636743656119259e-05 loss: 0.0804 (0.0969) time: 3.0379 data: 0.0025 max mem: 19788 +Epoch: [3] [ 470/2138] eta: 1:24:03 lr: 4.6362130316901416e-05 loss: 0.0718 (0.0966) time: 3.0395 data: 0.0025 max mem: 19788 +Epoch: [3] [ 480/2138] eta: 1:23:33 lr: 4.6356824005130386e-05 loss: 0.0851 (0.0968) time: 3.0425 data: 0.0026 max mem: 19788 +Epoch: [3] [ 490/2138] eta: 1:23:04 lr: 4.635151762587006e-05 loss: 0.0972 (0.0968) time: 3.0455 data: 0.0028 max mem: 19788 +Epoch: [3] [ 500/2138] eta: 1:22:51 lr: 4.634621117911101e-05 loss: 0.0858 (0.0968) time: 3.3026 data: 0.0028 max mem: 19788 +Epoch: [3] [ 510/2138] eta: 1:22:17 lr: 4.6340904664843777e-05 loss: 0.0883 (0.0968) time: 3.2306 data: 0.0024 max mem: 19788 +Epoch: [3] [ 520/2138] eta: 1:21:48 lr: 4.6335598083058904e-05 loss: 0.0980 (0.0969) time: 2.9957 data: 0.0022 max mem: 19788 +Epoch: [3] [ 530/2138] eta: 1:21:16 lr: 4.633029143374697e-05 loss: 0.0792 (0.0964) time: 3.0346 data: 0.0022 max mem: 19788 +Epoch: [3] [ 540/2138] eta: 1:20:44 lr: 4.632498471689849e-05 loss: 0.0689 (0.0959) time: 2.9833 data: 0.0022 max mem: 19788 +Epoch: [3] [ 550/2138] eta: 1:20:12 lr: 4.631967793250403e-05 loss: 0.0719 (0.0962) time: 2.9600 data: 0.0022 max mem: 19788 +Epoch: [3] [ 560/2138] eta: 1:19:42 lr: 4.6314371080554106e-05 loss: 0.0772 (0.0959) time: 2.9995 data: 0.0023 max mem: 19788 +Epoch: [3] [ 570/2138] eta: 1:19:09 lr: 4.630906416103929e-05 loss: 0.0773 (0.0957) time: 2.9893 data: 0.0025 max mem: 19788 +Epoch: [3] [ 580/2138] eta: 1:18:37 lr: 4.630375717395009e-05 loss: 0.0807 (0.0955) time: 2.9628 data: 0.0027 max mem: 19788 +Epoch: [3] [ 590/2138] eta: 1:18:05 lr: 4.629845011927706e-05 loss: 0.0847 (0.0953) time: 2.9600 data: 0.0027 max mem: 19788 +Epoch: [3] [ 600/2138] eta: 1:17:32 lr: 4.6293142997010716e-05 loss: 0.0778 (0.0949) time: 2.9295 data: 0.0026 max mem: 19788 +Epoch: [3] [ 610/2138] eta: 1:17:02 lr: 4.62878358071416e-05 loss: 0.0771 (0.0950) time: 2.9915 data: 0.0025 max mem: 19788 +Epoch: [3] [ 620/2138] eta: 1:16:30 lr: 4.628252854966023e-05 loss: 0.0874 (0.0952) time: 2.9958 data: 0.0023 max mem: 19788 +Epoch: [3] [ 630/2138] eta: 1:15:58 lr: 4.627722122455714e-05 loss: 0.0940 (0.0950) time: 2.9385 data: 0.0021 max mem: 19788 +Epoch: [3] [ 640/2138] eta: 1:15:26 lr: 4.6271913831822826e-05 loss: 0.0787 (0.0948) time: 2.9421 data: 0.0022 max mem: 19788 +Epoch: [3] [ 650/2138] eta: 1:14:53 lr: 4.626660637144784e-05 loss: 0.0787 (0.0947) time: 2.9309 data: 0.0026 max mem: 19788 +Epoch: [3] [ 660/2138] eta: 1:14:24 lr: 4.6261298843422674e-05 loss: 0.0790 (0.0945) time: 2.9947 data: 0.0025 max mem: 19788 +Epoch: [3] [ 670/2138] eta: 1:13:54 lr: 4.625599124773786e-05 loss: 0.0654 (0.0941) time: 3.0588 data: 0.0023 max mem: 19788 +Epoch: [3] [ 680/2138] eta: 1:13:22 lr: 4.625068358438389e-05 loss: 0.0654 (0.0940) time: 2.9913 data: 0.0024 max mem: 19788 +Epoch: [3] [ 690/2138] eta: 1:12:50 lr: 4.624537585335128e-05 loss: 0.0733 (0.0939) time: 2.9338 data: 0.0027 max mem: 19788 +Epoch: [3] [ 700/2138] eta: 1:12:18 lr: 4.624006805463054e-05 loss: 0.0642 (0.0935) time: 2.9177 data: 0.0031 max mem: 19788 +Epoch: [3] [ 710/2138] eta: 1:11:47 lr: 4.623476018821218e-05 loss: 0.0683 (0.0935) time: 2.9465 data: 0.0029 max mem: 19788 +Epoch: [3] [ 720/2138] eta: 1:11:17 lr: 4.622945225408668e-05 loss: 0.0770 (0.0933) time: 3.0027 data: 0.0023 max mem: 19788 +Epoch: [3] [ 730/2138] eta: 1:10:51 lr: 4.622414425224456e-05 loss: 0.0792 (0.0934) time: 3.1219 data: 0.0021 max mem: 19788 +Epoch: [3] [ 740/2138] eta: 1:10:22 lr: 4.62188361826763e-05 loss: 0.0845 (0.0935) time: 3.1525 data: 0.0024 max mem: 19788 +Epoch: [3] [ 750/2138] eta: 1:09:51 lr: 4.62135280453724e-05 loss: 0.0803 (0.0935) time: 3.0486 data: 0.0026 max mem: 19788 +Epoch: [3] [ 760/2138] eta: 1:09:20 lr: 4.620821984032335e-05 loss: 0.0839 (0.0935) time: 2.9993 data: 0.0025 max mem: 19788 +Epoch: [3] [ 770/2138] eta: 1:08:49 lr: 4.620291156751964e-05 loss: 0.0881 (0.0934) time: 2.9758 data: 0.0027 max mem: 19788 +Epoch: [3] [ 780/2138] eta: 1:08:19 lr: 4.6197603226951766e-05 loss: 0.0885 (0.0935) time: 2.9808 data: 0.0030 max mem: 19788 +Epoch: [3] [ 790/2138] eta: 1:07:48 lr: 4.619229481861018e-05 loss: 0.0817 (0.0933) time: 2.9825 data: 0.0031 max mem: 19788 +Epoch: [3] [ 800/2138] eta: 1:07:18 lr: 4.618698634248539e-05 loss: 0.0860 (0.0934) time: 3.0034 data: 0.0031 max mem: 19788 +Epoch: [3] [ 810/2138] eta: 1:06:48 lr: 4.6181677798567866e-05 loss: 0.0911 (0.0934) time: 3.0404 data: 0.0028 max mem: 19788 +Epoch: [3] [ 820/2138] eta: 1:06:17 lr: 4.617636918684809e-05 loss: 0.0838 (0.0934) time: 3.0054 data: 0.0026 max mem: 19788 +Epoch: [3] [ 830/2138] eta: 1:05:47 lr: 4.617106050731652e-05 loss: 0.0735 (0.0933) time: 2.9861 data: 0.0026 max mem: 19788 +Epoch: [3] [ 840/2138] eta: 1:05:15 lr: 4.6165751759963636e-05 loss: 0.0775 (0.0932) time: 2.9774 data: 0.0023 max mem: 19788 +Epoch: [3] [ 850/2138] eta: 1:04:44 lr: 4.61604429447799e-05 loss: 0.0786 (0.0931) time: 2.9327 data: 0.0021 max mem: 19788 +Epoch: [3] [ 860/2138] eta: 1:04:12 lr: 4.61551340617558e-05 loss: 0.0788 (0.0931) time: 2.9216 data: 0.0021 max mem: 19788 +Epoch: [3] [ 870/2138] eta: 1:03:41 lr: 4.614982511088176e-05 loss: 0.0876 (0.0930) time: 2.9307 data: 0.0022 max mem: 19788 +Epoch: [3] [ 880/2138] eta: 1:03:10 lr: 4.614451609214827e-05 loss: 0.0907 (0.0930) time: 2.9331 data: 0.0021 max mem: 19788 +Epoch: [3] [ 890/2138] eta: 1:02:38 lr: 4.613920700554577e-05 loss: 0.0797 (0.0928) time: 2.9241 data: 0.0021 max mem: 19788 +Epoch: [3] [ 900/2138] eta: 1:02:07 lr: 4.613389785106474e-05 loss: 0.0723 (0.0927) time: 2.9220 data: 0.0021 max mem: 19788 +Epoch: [3] [ 910/2138] eta: 1:01:37 lr: 4.6128588628695593e-05 loss: 0.0870 (0.0926) time: 2.9589 data: 0.0021 max mem: 19788 +Epoch: [3] [ 920/2138] eta: 1:01:06 lr: 4.612327933842882e-05 loss: 0.0764 (0.0924) time: 2.9946 data: 0.0020 max mem: 19788 +Epoch: [3] [ 930/2138] eta: 1:00:35 lr: 4.611796998025484e-05 loss: 0.0856 (0.0926) time: 2.9647 data: 0.0020 max mem: 19788 +Epoch: [3] [ 940/2138] eta: 1:00:04 lr: 4.61126605541641e-05 loss: 0.1034 (0.0926) time: 2.9284 data: 0.0020 max mem: 19788 +Epoch: [3] [ 950/2138] eta: 0:59:33 lr: 4.610735106014706e-05 loss: 0.0873 (0.0926) time: 2.9246 data: 0.0022 max mem: 19788 +Epoch: [3] [ 960/2138] eta: 0:59:05 lr: 4.6102041498194157e-05 loss: 0.0773 (0.0924) time: 3.0588 data: 0.0024 max mem: 19788 +Epoch: [3] [ 970/2138] eta: 0:58:34 lr: 4.6096731868295805e-05 loss: 0.0672 (0.0922) time: 3.0570 data: 0.0027 max mem: 19788 +Epoch: [3] [ 980/2138] eta: 0:58:03 lr: 4.609142217044246e-05 loss: 0.0689 (0.0921) time: 2.9449 data: 0.0027 max mem: 19788 +Epoch: [3] [ 990/2138] eta: 0:57:34 lr: 4.608611240462454e-05 loss: 0.0737 (0.0922) time: 3.0034 data: 0.0027 max mem: 19788 +Epoch: [3] [1000/2138] eta: 0:57:04 lr: 4.608080257083249e-05 loss: 0.0774 (0.0920) time: 3.0606 data: 0.0026 max mem: 19788 +Epoch: [3] [1010/2138] eta: 0:56:34 lr: 4.607549266905673e-05 loss: 0.0733 (0.0918) time: 3.0248 data: 0.0025 max mem: 19788 +Epoch: [3] [1020/2138] eta: 0:56:05 lr: 4.6070182699287676e-05 loss: 0.0824 (0.0918) time: 3.0663 data: 0.0026 max mem: 19788 +Epoch: [3] [1030/2138] eta: 0:55:37 lr: 4.606487266151576e-05 loss: 0.0828 (0.0917) time: 3.1585 data: 0.0027 max mem: 19788 +Epoch: [3] [1040/2138] eta: 0:55:09 lr: 4.60595625557314e-05 loss: 0.0843 (0.0916) time: 3.2106 data: 0.0026 max mem: 19788 +Epoch: [3] [1050/2138] eta: 0:54:42 lr: 4.605425238192501e-05 loss: 0.0848 (0.0916) time: 3.2655 data: 0.0025 max mem: 19788 +Epoch: [3] [1060/2138] eta: 0:54:12 lr: 4.604894214008699e-05 loss: 0.0897 (0.0917) time: 3.1413 data: 0.0028 max mem: 19788 +Epoch: [3] [1070/2138] eta: 0:53:42 lr: 4.6043631830207775e-05 loss: 0.0831 (0.0917) time: 3.0204 data: 0.0028 max mem: 19788 +Epoch: [3] [1080/2138] eta: 0:53:11 lr: 4.603832145227776e-05 loss: 0.0795 (0.0916) time: 3.0151 data: 0.0024 max mem: 19788 +Epoch: [3] [1090/2138] eta: 0:52:42 lr: 4.6033011006287364e-05 loss: 0.0795 (0.0916) time: 3.0337 data: 0.0023 max mem: 19788 +Epoch: [3] [1100/2138] eta: 0:52:11 lr: 4.6027700492226966e-05 loss: 0.0727 (0.0916) time: 3.0096 data: 0.0028 max mem: 19788 +Epoch: [3] [1110/2138] eta: 0:51:40 lr: 4.602238991008699e-05 loss: 0.0721 (0.0915) time: 2.9545 data: 0.0031 max mem: 19788 +Epoch: [3] [1120/2138] eta: 0:51:09 lr: 4.601707925985783e-05 loss: 0.0706 (0.0913) time: 2.9519 data: 0.0027 max mem: 19788 +Epoch: [3] [1130/2138] eta: 0:50:38 lr: 4.601176854152987e-05 loss: 0.0714 (0.0912) time: 2.9394 data: 0.0023 max mem: 19788 +Epoch: [3] [1140/2138] eta: 0:50:08 lr: 4.6006457755093514e-05 loss: 0.0838 (0.0913) time: 2.9438 data: 0.0022 max mem: 19788 +Epoch: [3] [1150/2138] eta: 0:49:39 lr: 4.6001146900539146e-05 loss: 0.0816 (0.0913) time: 3.0835 data: 0.0023 max mem: 19788 +Epoch: [3] [1160/2138] eta: 0:49:10 lr: 4.5995835977857166e-05 loss: 0.0792 (0.0912) time: 3.1369 data: 0.0023 max mem: 19788 +Epoch: [3] [1170/2138] eta: 0:48:39 lr: 4.5990524987037944e-05 loss: 0.0686 (0.0911) time: 2.9925 data: 0.0023 max mem: 19788 +Epoch: [3] [1180/2138] eta: 0:48:09 lr: 4.598521392807187e-05 loss: 0.0715 (0.0911) time: 2.9759 data: 0.0025 max mem: 19788 +Epoch: [3] [1190/2138] eta: 0:47:38 lr: 4.5979902800949336e-05 loss: 0.0715 (0.0909) time: 3.0262 data: 0.0027 max mem: 19788 +Epoch: [3] [1200/2138] eta: 0:47:08 lr: 4.597459160566069e-05 loss: 0.0567 (0.0907) time: 2.9743 data: 0.0029 max mem: 19788 +Epoch: [3] [1210/2138] eta: 0:46:37 lr: 4.596928034219634e-05 loss: 0.0685 (0.0906) time: 2.9478 data: 0.0026 max mem: 19788 +Epoch: [3] [1220/2138] eta: 0:46:07 lr: 4.5963969010546635e-05 loss: 0.0685 (0.0904) time: 3.0050 data: 0.0021 max mem: 19788 +Epoch: [3] [1230/2138] eta: 0:45:36 lr: 4.595865761070196e-05 loss: 0.0832 (0.0905) time: 2.9858 data: 0.0021 max mem: 19788 +Epoch: [3] [1240/2138] eta: 0:45:05 lr: 4.595334614265267e-05 loss: 0.0903 (0.0904) time: 2.9173 data: 0.0022 max mem: 19788 +Epoch: [3] [1250/2138] eta: 0:44:35 lr: 4.594803460638914e-05 loss: 0.0807 (0.0904) time: 2.9073 data: 0.0023 max mem: 19788 +Epoch: [3] [1260/2138] eta: 0:44:04 lr: 4.5942723001901724e-05 loss: 0.0747 (0.0903) time: 2.9340 data: 0.0022 max mem: 19788 +Epoch: [3] [1270/2138] eta: 0:43:34 lr: 4.593741132918078e-05 loss: 0.0688 (0.0902) time: 2.9597 data: 0.0021 max mem: 19788 +Epoch: [3] [1280/2138] eta: 0:43:03 lr: 4.5932099588216674e-05 loss: 0.0751 (0.0902) time: 2.9701 data: 0.0024 max mem: 19788 +Epoch: [3] [1290/2138] eta: 0:42:33 lr: 4.5926787778999755e-05 loss: 0.0926 (0.0903) time: 2.9793 data: 0.0027 max mem: 19788 +Epoch: [3] [1300/2138] eta: 0:42:03 lr: 4.592147590152038e-05 loss: 0.0836 (0.0901) time: 2.9883 data: 0.0025 max mem: 19788 +Epoch: [3] [1310/2138] eta: 0:41:35 lr: 4.5916163955768896e-05 loss: 0.0721 (0.0900) time: 3.2054 data: 0.0024 max mem: 19788 +Epoch: [3] [1320/2138] eta: 0:41:05 lr: 4.5910851941735636e-05 loss: 0.0769 (0.0900) time: 3.2263 data: 0.0024 max mem: 19788 +Epoch: [3] [1330/2138] eta: 0:40:36 lr: 4.590553985941096e-05 loss: 0.0928 (0.0901) time: 3.0693 data: 0.0022 max mem: 19788 +Epoch: [3] [1340/2138] eta: 0:40:06 lr: 4.59002277087852e-05 loss: 0.0929 (0.0901) time: 3.1444 data: 0.0022 max mem: 19788 +Epoch: [3] [1350/2138] eta: 0:39:36 lr: 4.58949154898487e-05 loss: 0.0878 (0.0901) time: 3.1005 data: 0.0024 max mem: 19788 +Epoch: [3] [1360/2138] eta: 0:39:06 lr: 4.5889603202591806e-05 loss: 0.0867 (0.0901) time: 3.0327 data: 0.0025 max mem: 19788 +Epoch: [3] [1370/2138] eta: 0:38:36 lr: 4.588429084700483e-05 loss: 0.0860 (0.0902) time: 3.0299 data: 0.0023 max mem: 19788 +Epoch: [3] [1380/2138] eta: 0:38:06 lr: 4.587897842307811e-05 loss: 0.0968 (0.0901) time: 3.0012 data: 0.0021 max mem: 19788 +Epoch: [3] [1390/2138] eta: 0:37:36 lr: 4.5873665930801983e-05 loss: 0.0775 (0.0900) time: 3.0084 data: 0.0021 max mem: 19788 +Epoch: [3] [1400/2138] eta: 0:37:05 lr: 4.5868353370166775e-05 loss: 0.0757 (0.0900) time: 3.0163 data: 0.0021 max mem: 19788 +Epoch: [3] [1410/2138] eta: 0:36:35 lr: 4.586304074116279e-05 loss: 0.0751 (0.0899) time: 3.0259 data: 0.0025 max mem: 19788 +Epoch: [3] [1420/2138] eta: 0:36:05 lr: 4.585772804378037e-05 loss: 0.0770 (0.0898) time: 3.0056 data: 0.0028 max mem: 19788 +Epoch: [3] [1430/2138] eta: 0:35:35 lr: 4.5852415278009816e-05 loss: 0.0777 (0.0898) time: 2.9905 data: 0.0027 max mem: 19788 +Epoch: [3] [1440/2138] eta: 0:35:04 lr: 4.584710244384146e-05 loss: 0.0777 (0.0898) time: 2.9640 data: 0.0026 max mem: 19788 +Epoch: [3] [1450/2138] eta: 0:34:34 lr: 4.5841789541265595e-05 loss: 0.0783 (0.0897) time: 2.9234 data: 0.0025 max mem: 19788 +Epoch: [3] [1460/2138] eta: 0:34:03 lr: 4.583647657027254e-05 loss: 0.0783 (0.0897) time: 2.9260 data: 0.0027 max mem: 19788 +Epoch: [3] [1470/2138] eta: 0:33:33 lr: 4.583116353085262e-05 loss: 0.0764 (0.0897) time: 2.9373 data: 0.0026 max mem: 19788 +Epoch: [3] [1480/2138] eta: 0:33:02 lr: 4.5825850422996105e-05 loss: 0.0734 (0.0896) time: 2.9438 data: 0.0021 max mem: 19788 +Epoch: [3] [1490/2138] eta: 0:32:32 lr: 4.5820537246693325e-05 loss: 0.0907 (0.0897) time: 2.9602 data: 0.0022 max mem: 19788 +Epoch: [3] [1500/2138] eta: 0:32:01 lr: 4.581522400193457e-05 loss: 0.0887 (0.0897) time: 2.9599 data: 0.0024 max mem: 19788 +Epoch: [3] [1510/2138] eta: 0:31:31 lr: 4.580991068871013e-05 loss: 0.0740 (0.0896) time: 2.9601 data: 0.0023 max mem: 19788 +Epoch: [3] [1520/2138] eta: 0:31:01 lr: 4.580459730701031e-05 loss: 0.0738 (0.0895) time: 2.9823 data: 0.0023 max mem: 19788 +Epoch: [3] [1530/2138] eta: 0:30:31 lr: 4.5799283856825394e-05 loss: 0.0763 (0.0896) time: 2.9571 data: 0.0026 max mem: 19788 +Epoch: [3] [1540/2138] eta: 0:30:00 lr: 4.5793970338145677e-05 loss: 0.0732 (0.0895) time: 2.9304 data: 0.0025 max mem: 19788 +Epoch: [3] [1550/2138] eta: 0:29:30 lr: 4.578865675096143e-05 loss: 0.0730 (0.0895) time: 2.9604 data: 0.0023 max mem: 19788 +Epoch: [3] [1560/2138] eta: 0:29:00 lr: 4.578334309526297e-05 loss: 0.0788 (0.0894) time: 2.9754 data: 0.0023 max mem: 19788 +Epoch: [3] [1570/2138] eta: 0:28:30 lr: 4.577802937104054e-05 loss: 0.0816 (0.0894) time: 3.0056 data: 0.0024 max mem: 19788 +Epoch: [3] [1580/2138] eta: 0:27:59 lr: 4.577271557828444e-05 loss: 0.0827 (0.0894) time: 3.0042 data: 0.0027 max mem: 19788 +Epoch: [3] [1590/2138] eta: 0:27:29 lr: 4.576740171698494e-05 loss: 0.0805 (0.0894) time: 2.9896 data: 0.0027 max mem: 19788 +Epoch: [3] [1600/2138] eta: 0:27:00 lr: 4.576208778713231e-05 loss: 0.0769 (0.0894) time: 3.0677 data: 0.0026 max mem: 19788 +Epoch: [3] [1610/2138] eta: 0:26:31 lr: 4.575677378871683e-05 loss: 0.0807 (0.0894) time: 3.2384 data: 0.0027 max mem: 19788 +Epoch: [3] [1620/2138] eta: 0:26:01 lr: 4.575145972172876e-05 loss: 0.0760 (0.0893) time: 3.3244 data: 0.0026 max mem: 19788 +Epoch: [3] [1630/2138] eta: 0:25:33 lr: 4.574614558615836e-05 loss: 0.0662 (0.0892) time: 3.4168 data: 0.0023 max mem: 19788 +Epoch: [3] [1640/2138] eta: 0:25:03 lr: 4.5740831381995914e-05 loss: 0.0871 (0.0892) time: 3.3053 data: 0.0024 max mem: 19788 +Epoch: [3] [1650/2138] eta: 0:24:33 lr: 4.573551710923166e-05 loss: 0.0852 (0.0891) time: 3.0652 data: 0.0025 max mem: 19788 +Epoch: [3] [1660/2138] eta: 0:24:02 lr: 4.573020276785586e-05 loss: 0.0852 (0.0892) time: 3.0248 data: 0.0025 max mem: 19788 +Epoch: [3] [1670/2138] eta: 0:23:33 lr: 4.5724888357858776e-05 loss: 0.0742 (0.0890) time: 3.1338 data: 0.0026 max mem: 19788 +Epoch: [3] [1680/2138] eta: 0:23:04 lr: 4.571957387923065e-05 loss: 0.0721 (0.0889) time: 3.3499 data: 0.0024 max mem: 19788 +Epoch: [3] [1690/2138] eta: 0:22:33 lr: 4.571425933196173e-05 loss: 0.0680 (0.0889) time: 3.1905 data: 0.0027 max mem: 19788 +Epoch: [3] [1700/2138] eta: 0:22:03 lr: 4.570894471604229e-05 loss: 0.0666 (0.0890) time: 3.0311 data: 0.0030 max mem: 19788 +Epoch: [3] [1710/2138] eta: 0:21:33 lr: 4.570363003146254e-05 loss: 0.0810 (0.0890) time: 3.0739 data: 0.0028 max mem: 19788 +Epoch: [3] [1720/2138] eta: 0:21:03 lr: 4.569831527821274e-05 loss: 0.0768 (0.0889) time: 3.0561 data: 0.0028 max mem: 19788 +Epoch: [3] [1730/2138] eta: 0:20:33 lr: 4.569300045628312e-05 loss: 0.0766 (0.0890) time: 3.0278 data: 0.0024 max mem: 19788 +Epoch: [3] [1740/2138] eta: 0:20:02 lr: 4.5687685565663915e-05 loss: 0.0774 (0.0889) time: 2.9608 data: 0.0021 max mem: 19788 +Epoch: [3] [1750/2138] eta: 0:19:32 lr: 4.568237060634537e-05 loss: 0.0647 (0.0888) time: 2.9262 data: 0.0022 max mem: 19788 +Epoch: [3] [1760/2138] eta: 0:19:02 lr: 4.567705557831771e-05 loss: 0.0678 (0.0887) time: 2.9245 data: 0.0024 max mem: 19788 +Epoch: [3] [1770/2138] eta: 0:18:31 lr: 4.567174048157116e-05 loss: 0.0696 (0.0887) time: 2.9438 data: 0.0025 max mem: 19788 +Epoch: [3] [1780/2138] eta: 0:18:01 lr: 4.566642531609594e-05 loss: 0.0714 (0.0886) time: 2.9529 data: 0.0027 max mem: 19788 +Epoch: [3] [1790/2138] eta: 0:17:31 lr: 4.5661110081882285e-05 loss: 0.0714 (0.0886) time: 2.9517 data: 0.0025 max mem: 19788 +Epoch: [3] [1800/2138] eta: 0:17:00 lr: 4.565579477892041e-05 loss: 0.0835 (0.0886) time: 2.9631 data: 0.0021 max mem: 19788 +Epoch: [3] [1810/2138] eta: 0:16:30 lr: 4.5650479407200534e-05 loss: 0.0723 (0.0886) time: 2.9583 data: 0.0023 max mem: 19788 +Epoch: [3] [1820/2138] eta: 0:16:00 lr: 4.5645163966712875e-05 loss: 0.0684 (0.0885) time: 2.9708 data: 0.0025 max mem: 19788 +Epoch: [3] [1830/2138] eta: 0:15:30 lr: 4.563984845744764e-05 loss: 0.0683 (0.0885) time: 3.0701 data: 0.0026 max mem: 19788 +Epoch: [3] [1840/2138] eta: 0:14:59 lr: 4.5634532879395026e-05 loss: 0.0683 (0.0884) time: 3.0660 data: 0.0027 max mem: 19788 +Epoch: [3] [1850/2138] eta: 0:14:29 lr: 4.5629217232545266e-05 loss: 0.0613 (0.0884) time: 2.9545 data: 0.0025 max mem: 19788 +Epoch: [3] [1860/2138] eta: 0:13:59 lr: 4.562390151688855e-05 loss: 0.0613 (0.0883) time: 2.9308 data: 0.0024 max mem: 19788 +Epoch: [3] [1870/2138] eta: 0:13:29 lr: 4.561858573241508e-05 loss: 0.0754 (0.0883) time: 2.9599 data: 0.0026 max mem: 19788 +Epoch: [3] [1880/2138] eta: 0:12:58 lr: 4.561326987911505e-05 loss: 0.0875 (0.0883) time: 2.9732 data: 0.0028 max mem: 19788 +Epoch: [3] [1890/2138] eta: 0:12:28 lr: 4.560795395697867e-05 loss: 0.0742 (0.0883) time: 3.0101 data: 0.0030 max mem: 19788 +Epoch: [3] [1900/2138] eta: 0:11:58 lr: 4.560263796599613e-05 loss: 0.0698 (0.0882) time: 3.0719 data: 0.0031 max mem: 19788 +Epoch: [3] [1910/2138] eta: 0:11:28 lr: 4.559732190615761e-05 loss: 0.0689 (0.0881) time: 3.0438 data: 0.0027 max mem: 19788 +Epoch: [3] [1920/2138] eta: 0:10:58 lr: 4.55920057774533e-05 loss: 0.0731 (0.0881) time: 3.0103 data: 0.0026 max mem: 19788 +Epoch: [3] [1930/2138] eta: 0:10:28 lr: 4.55866895798734e-05 loss: 0.0801 (0.0881) time: 3.0701 data: 0.0028 max mem: 19788 +Epoch: [3] [1940/2138] eta: 0:09:58 lr: 4.5581373313408075e-05 loss: 0.0856 (0.0881) time: 3.1661 data: 0.0028 max mem: 19788 +Epoch: [3] [1950/2138] eta: 0:09:27 lr: 4.557605697804752e-05 loss: 0.0820 (0.0880) time: 3.1642 data: 0.0027 max mem: 19788 +Epoch: [3] [1960/2138] eta: 0:08:57 lr: 4.55707405737819e-05 loss: 0.0663 (0.0880) time: 3.1141 data: 0.0026 max mem: 19788 +Epoch: [3] [1970/2138] eta: 0:08:27 lr: 4.55654241006014e-05 loss: 0.0704 (0.0879) time: 3.0818 data: 0.0026 max mem: 19788 +Epoch: [3] [1980/2138] eta: 0:07:57 lr: 4.556010755849619e-05 loss: 0.0771 (0.0879) time: 2.9643 data: 0.0024 max mem: 19788 +Epoch: [3] [1990/2138] eta: 0:07:27 lr: 4.5554790947456434e-05 loss: 0.0711 (0.0878) time: 2.9376 data: 0.0025 max mem: 19788 +Epoch: [3] [2000/2138] eta: 0:06:56 lr: 4.55494742674723e-05 loss: 0.0666 (0.0877) time: 2.9719 data: 0.0024 max mem: 19788 +Epoch: [3] [2010/2138] eta: 0:06:26 lr: 4.554415751853396e-05 loss: 0.0631 (0.0876) time: 2.9343 data: 0.0025 max mem: 19788 +Epoch: [3] [2020/2138] eta: 0:05:56 lr: 4.553884070063157e-05 loss: 0.0707 (0.0876) time: 2.9254 data: 0.0027 max mem: 19788 +Epoch: [3] [2030/2138] eta: 0:05:26 lr: 4.553352381375528e-05 loss: 0.0846 (0.0876) time: 2.9477 data: 0.0024 max mem: 19788 +Epoch: [3] [2040/2138] eta: 0:04:55 lr: 4.552820685789527e-05 loss: 0.0706 (0.0875) time: 2.9461 data: 0.0021 max mem: 19788 +Epoch: [3] [2050/2138] eta: 0:04:25 lr: 4.552288983304166e-05 loss: 0.0643 (0.0874) time: 2.9563 data: 0.0023 max mem: 19788 +Epoch: [3] [2060/2138] eta: 0:03:55 lr: 4.5517572739184636e-05 loss: 0.0694 (0.0874) time: 2.9834 data: 0.0024 max mem: 19788 +Epoch: [3] [2070/2138] eta: 0:03:25 lr: 4.551225557631432e-05 loss: 0.0649 (0.0872) time: 2.9456 data: 0.0024 max mem: 19788 +Epoch: [3] [2080/2138] eta: 0:02:55 lr: 4.550693834442087e-05 loss: 0.0701 (0.0872) time: 2.9430 data: 0.0024 max mem: 19788 +Epoch: [3] [2090/2138] eta: 0:02:24 lr: 4.550162104349442e-05 loss: 0.0747 (0.0872) time: 2.9954 data: 0.0024 max mem: 19788 +Epoch: [3] [2100/2138] eta: 0:01:54 lr: 4.549630367352512e-05 loss: 0.0619 (0.0871) time: 2.9710 data: 0.0029 max mem: 19788 +Epoch: [3] [2110/2138] eta: 0:01:24 lr: 4.5490986234503095e-05 loss: 0.0615 (0.0872) time: 2.9212 data: 0.0027 max mem: 19788 +Epoch: [3] [2120/2138] eta: 0:00:54 lr: 4.5485668726418494e-05 loss: 0.0949 (0.0872) time: 2.9682 data: 0.0022 max mem: 19788 +Epoch: [3] [2130/2138] eta: 0:00:24 lr: 4.548035114926144e-05 loss: 0.0988 (0.0873) time: 2.9709 data: 0.0022 max mem: 19788 +Epoch: [3] Total time: 1:47:28 +Test: [ 0/21770] eta: 13:51:07 time: 2.2907 data: 2.0018 max mem: 19788 +Test: [ 100/21770] eta: 0:29:19 time: 0.0531 data: 0.0016 max mem: 19788 +Test: [ 200/21770] eta: 0:23:11 time: 0.0510 data: 0.0019 max mem: 19788 +Test: [ 300/21770] eta: 0:21:17 time: 0.0432 data: 0.0017 max mem: 19788 +Test: [ 400/21770] eta: 0:19:48 time: 0.0432 data: 0.0013 max mem: 19788 +Test: [ 500/21770] eta: 0:18:46 time: 0.0424 data: 0.0015 max mem: 19788 +Test: [ 600/21770] eta: 0:18:11 time: 0.0444 data: 0.0014 max mem: 19788 +Test: [ 700/21770] eta: 0:17:42 time: 0.0433 data: 0.0015 max mem: 19788 +Test: [ 800/21770] eta: 0:17:24 time: 0.0430 data: 0.0015 max mem: 19788 +Test: [ 900/21770] eta: 0:17:06 time: 0.0468 data: 0.0015 max mem: 19788 +Test: [ 1000/21770] eta: 0:16:50 time: 0.0425 data: 0.0015 max mem: 19788 +Test: [ 1100/21770] eta: 0:16:36 time: 0.0440 data: 0.0017 max mem: 19788 +Test: [ 1200/21770] eta: 0:16:30 time: 0.0497 data: 0.0017 max mem: 19788 +Test: [ 1300/21770] eta: 0:16:21 time: 0.0431 data: 0.0014 max mem: 19788 +Test: [ 1400/21770] eta: 0:16:09 time: 0.0433 data: 0.0014 max mem: 19788 +Test: [ 1500/21770] eta: 0:16:01 time: 0.0440 data: 0.0014 max mem: 19788 +Test: [ 1600/21770] eta: 0:15:58 time: 0.0425 data: 0.0013 max mem: 19788 +Test: [ 1700/21770] eta: 0:15:58 time: 0.0519 data: 0.0018 max mem: 19788 +Test: [ 1800/21770] eta: 0:15:52 time: 0.0453 data: 0.0015 max mem: 19788 +Test: [ 1900/21770] eta: 0:15:45 time: 0.0487 data: 0.0018 max mem: 19788 +Test: [ 2000/21770] eta: 0:15:44 time: 0.0516 data: 0.0017 max mem: 19788 +Test: [ 2100/21770] eta: 0:15:38 time: 0.0441 data: 0.0013 max mem: 19788 +Test: [ 2200/21770] eta: 0:15:32 time: 0.0523 data: 0.0018 max mem: 19788 +Test: [ 2300/21770] eta: 0:15:27 time: 0.0433 data: 0.0014 max mem: 19788 +Test: [ 2400/21770] eta: 0:15:22 time: 0.0467 data: 0.0017 max mem: 19788 +Test: [ 2500/21770] eta: 0:15:18 time: 0.0474 data: 0.0017 max mem: 19788 +Test: [ 2600/21770] eta: 0:15:12 time: 0.0433 data: 0.0013 max mem: 19788 +Test: [ 2700/21770] eta: 0:15:06 time: 0.0508 data: 0.0016 max mem: 19788 +Test: [ 2800/21770] eta: 0:15:03 time: 0.0524 data: 0.0018 max mem: 19788 +Test: [ 2900/21770] eta: 0:14:59 time: 0.0436 data: 0.0017 max mem: 19788 +Test: [ 3000/21770] eta: 0:14:55 time: 0.0462 data: 0.0017 max mem: 19788 +Test: [ 3100/21770] eta: 0:14:48 time: 0.0438 data: 0.0014 max mem: 19788 +Test: [ 3200/21770] eta: 0:14:45 time: 0.0457 data: 0.0017 max mem: 19788 +Test: [ 3300/21770] eta: 0:14:41 time: 0.0529 data: 0.0018 max mem: 19788 +Test: [ 3400/21770] eta: 0:14:37 time: 0.0468 data: 0.0018 max mem: 19788 +Test: [ 3500/21770] eta: 0:14:32 time: 0.0487 data: 0.0017 max mem: 19788 +Test: [ 3600/21770] eta: 0:14:27 time: 0.0437 data: 0.0017 max mem: 19788 +Test: [ 3700/21770] eta: 0:14:23 time: 0.0546 data: 0.0018 max mem: 19788 +Test: [ 3800/21770] eta: 0:14:19 time: 0.0472 data: 0.0015 max mem: 19788 +Test: [ 3900/21770] eta: 0:14:13 time: 0.0466 data: 0.0015 max mem: 19788 +Test: [ 4000/21770] eta: 0:14:07 time: 0.0427 data: 0.0015 max mem: 19788 +Test: [ 4100/21770] eta: 0:14:01 time: 0.0478 data: 0.0015 max mem: 19788 +Test: [ 4200/21770] eta: 0:13:59 time: 0.0528 data: 0.0018 max mem: 19788 +Test: [ 4300/21770] eta: 0:13:54 time: 0.0502 data: 0.0018 max mem: 19788 +Test: [ 4400/21770] eta: 0:13:49 time: 0.0508 data: 0.0018 max mem: 19788 +Test: [ 4500/21770] eta: 0:13:45 time: 0.0452 data: 0.0016 max mem: 19788 +Test: [ 4600/21770] eta: 0:13:41 time: 0.0444 data: 0.0014 max mem: 19788 +Test: [ 4700/21770] eta: 0:13:35 time: 0.0454 data: 0.0015 max mem: 19788 +Test: [ 4800/21770] eta: 0:13:30 time: 0.0463 data: 0.0014 max mem: 19788 +Test: [ 4900/21770] eta: 0:13:25 time: 0.0511 data: 0.0015 max mem: 19788 +Test: [ 5000/21770] eta: 0:13:21 time: 0.0489 data: 0.0014 max mem: 19788 +Test: [ 5100/21770] eta: 0:13:16 time: 0.0487 data: 0.0017 max mem: 19788 +Test: [ 5200/21770] eta: 0:13:12 time: 0.0439 data: 0.0016 max mem: 19788 +Test: [ 5300/21770] eta: 0:13:07 time: 0.0451 data: 0.0014 max mem: 19788 +Test: [ 5400/21770] eta: 0:13:01 time: 0.0446 data: 0.0014 max mem: 19788 +Test: [ 5500/21770] eta: 0:12:57 time: 0.0501 data: 0.0017 max mem: 19788 +Test: [ 5600/21770] eta: 0:12:51 time: 0.0525 data: 0.0018 max mem: 19788 +Test: [ 5700/21770] eta: 0:12:47 time: 0.0526 data: 0.0018 max mem: 19788 +Test: [ 5800/21770] eta: 0:12:43 time: 0.0450 data: 0.0016 max mem: 19788 +Test: [ 5900/21770] eta: 0:12:39 time: 0.0539 data: 0.0018 max mem: 19788 +Test: [ 6000/21770] eta: 0:12:34 time: 0.0459 data: 0.0014 max mem: 19788 +Test: [ 6100/21770] eta: 0:12:30 time: 0.0436 data: 0.0014 max mem: 19788 +Test: [ 6200/21770] eta: 0:12:26 time: 0.0533 data: 0.0018 max mem: 19788 +Test: [ 6300/21770] eta: 0:12:21 time: 0.0469 data: 0.0016 max mem: 19788 +Test: [ 6400/21770] eta: 0:12:16 time: 0.0440 data: 0.0013 max mem: 19788 +Test: [ 6500/21770] eta: 0:12:11 time: 0.0523 data: 0.0018 max mem: 19788 +Test: [ 6600/21770] eta: 0:12:06 time: 0.0439 data: 0.0013 max mem: 19788 +Test: [ 6700/21770] eta: 0:12:00 time: 0.0441 data: 0.0014 max mem: 19788 +Test: [ 6800/21770] eta: 0:11:55 time: 0.0456 data: 0.0015 max mem: 19788 +Test: [ 6900/21770] eta: 0:11:50 time: 0.0527 data: 0.0018 max mem: 19788 +Test: [ 7000/21770] eta: 0:11:46 time: 0.0546 data: 0.0015 max mem: 19788 +Test: [ 7100/21770] eta: 0:11:42 time: 0.0508 data: 0.0017 max mem: 19788 +Test: [ 7200/21770] eta: 0:11:37 time: 0.0471 data: 0.0015 max mem: 19788 +Test: [ 7300/21770] eta: 0:11:32 time: 0.0451 data: 0.0015 max mem: 19788 +Test: [ 7400/21770] eta: 0:11:27 time: 0.0442 data: 0.0015 max mem: 19788 +Test: [ 7500/21770] eta: 0:11:23 time: 0.0524 data: 0.0019 max mem: 19788 +Test: [ 7600/21770] eta: 0:11:19 time: 0.0506 data: 0.0019 max mem: 19788 +Test: [ 7700/21770] eta: 0:11:14 time: 0.0460 data: 0.0015 max mem: 19788 +Test: [ 7800/21770] eta: 0:11:09 time: 0.0433 data: 0.0016 max mem: 19788 +Test: [ 7900/21770] eta: 0:11:04 time: 0.0514 data: 0.0017 max mem: 19788 +Test: [ 8000/21770] eta: 0:10:59 time: 0.0528 data: 0.0014 max mem: 19788 +Test: [ 8100/21770] eta: 0:10:54 time: 0.0521 data: 0.0017 max mem: 19788 +Test: [ 8200/21770] eta: 0:10:50 time: 0.0482 data: 0.0016 max mem: 19788 +Test: [ 8300/21770] eta: 0:10:45 time: 0.0527 data: 0.0018 max mem: 19788 +Test: [ 8400/21770] eta: 0:10:40 time: 0.0468 data: 0.0013 max mem: 19788 +Test: [ 8500/21770] eta: 0:10:35 time: 0.0509 data: 0.0016 max mem: 19788 +Test: [ 8600/21770] eta: 0:10:30 time: 0.0523 data: 0.0018 max mem: 19788 +Test: [ 8700/21770] eta: 0:10:25 time: 0.0440 data: 0.0015 max mem: 19788 +Test: [ 8800/21770] eta: 0:10:20 time: 0.0517 data: 0.0017 max mem: 19788 +Test: [ 8900/21770] eta: 0:10:15 time: 0.0443 data: 0.0015 max mem: 19788 +Test: [ 9000/21770] eta: 0:10:09 time: 0.0428 data: 0.0015 max mem: 19788 +Test: [ 9100/21770] eta: 0:10:05 time: 0.0481 data: 0.0016 max mem: 19788 +Test: [ 9200/21770] eta: 0:10:00 time: 0.0463 data: 0.0014 max mem: 19788 +Test: [ 9300/21770] eta: 0:09:56 time: 0.0533 data: 0.0017 max mem: 19788 +Test: [ 9400/21770] eta: 0:09:51 time: 0.0522 data: 0.0018 max mem: 19788 +Test: [ 9500/21770] eta: 0:09:46 time: 0.0443 data: 0.0015 max mem: 19788 +Test: [ 9600/21770] eta: 0:09:41 time: 0.0438 data: 0.0016 max mem: 19788 +Test: [ 9700/21770] eta: 0:09:37 time: 0.0435 data: 0.0015 max mem: 19788 +Test: [ 9800/21770] eta: 0:09:32 time: 0.0450 data: 0.0015 max mem: 19788 +Test: [ 9900/21770] eta: 0:09:26 time: 0.0482 data: 0.0017 max mem: 19788 +Test: [10000/21770] eta: 0:09:22 time: 0.0484 data: 0.0016 max mem: 19788 +Test: [10100/21770] eta: 0:09:17 time: 0.0494 data: 0.0017 max mem: 19788 +Test: [10200/21770] eta: 0:09:12 time: 0.0454 data: 0.0014 max mem: 19788 +Test: [10300/21770] eta: 0:09:07 time: 0.0549 data: 0.0015 max mem: 19788 +Test: [10400/21770] eta: 0:09:02 time: 0.0446 data: 0.0014 max mem: 19788 +Test: [10500/21770] eta: 0:08:57 time: 0.0446 data: 0.0017 max mem: 19788 +Test: [10600/21770] eta: 0:08:53 time: 0.0471 data: 0.0016 max mem: 19788 +Test: [10700/21770] eta: 0:08:48 time: 0.0452 data: 0.0015 max mem: 19788 +Test: [10800/21770] eta: 0:08:42 time: 0.0439 data: 0.0016 max mem: 19788 +Test: [10900/21770] eta: 0:08:38 time: 0.0453 data: 0.0014 max mem: 19788 +Test: [11000/21770] eta: 0:08:32 time: 0.0443 data: 0.0016 max mem: 19788 +Test: [11100/21770] eta: 0:08:28 time: 0.0452 data: 0.0016 max mem: 19788 +Test: [11200/21770] eta: 0:08:23 time: 0.0473 data: 0.0016 max mem: 19788 +Test: [11300/21770] eta: 0:08:18 time: 0.0478 data: 0.0016 max mem: 19788 +Test: [11400/21770] eta: 0:08:13 time: 0.0445 data: 0.0015 max mem: 19788 +Test: [11500/21770] eta: 0:08:08 time: 0.0444 data: 0.0015 max mem: 19788 +Test: [11600/21770] eta: 0:08:03 time: 0.0493 data: 0.0017 max mem: 19788 +Test: [11700/21770] eta: 0:07:58 time: 0.0455 data: 0.0015 max mem: 19788 +Test: [11800/21770] eta: 0:07:54 time: 0.0530 data: 0.0019 max mem: 19788 +Test: [11900/21770] eta: 0:07:49 time: 0.0453 data: 0.0014 max mem: 19788 +Test: [12000/21770] eta: 0:07:44 time: 0.0431 data: 0.0015 max mem: 19788 +Test: [12100/21770] eta: 0:07:39 time: 0.0441 data: 0.0013 max mem: 19788 +Test: [12200/21770] eta: 0:07:34 time: 0.0436 data: 0.0015 max mem: 19788 +Test: [12300/21770] eta: 0:07:30 time: 0.0452 data: 0.0015 max mem: 19788 +Test: [12400/21770] eta: 0:07:25 time: 0.0455 data: 0.0013 max mem: 19788 +Test: [12500/21770] eta: 0:07:20 time: 0.0513 data: 0.0017 max mem: 19788 +Test: [12600/21770] eta: 0:07:16 time: 0.0523 data: 0.0018 max mem: 19788 +Test: [12700/21770] eta: 0:07:11 time: 0.0438 data: 0.0015 max mem: 19788 +Test: [12800/21770] eta: 0:07:06 time: 0.0450 data: 0.0014 max mem: 19788 +Test: [12900/21770] eta: 0:07:02 time: 0.0430 data: 0.0014 max mem: 19788 +Test: [13000/21770] eta: 0:06:57 time: 0.0452 data: 0.0015 max mem: 19788 +Test: [13100/21770] eta: 0:06:52 time: 0.0462 data: 0.0014 max mem: 19788 +Test: [13200/21770] eta: 0:06:47 time: 0.0470 data: 0.0015 max mem: 19788 +Test: [13300/21770] eta: 0:06:42 time: 0.0451 data: 0.0015 max mem: 19788 +Test: [13400/21770] eta: 0:06:37 time: 0.0447 data: 0.0014 max mem: 19788 +Test: [13500/21770] eta: 0:06:32 time: 0.0441 data: 0.0016 max mem: 19788 +Test: [13600/21770] eta: 0:06:28 time: 0.0535 data: 0.0016 max mem: 19788 +Test: [13700/21770] eta: 0:06:23 time: 0.0439 data: 0.0016 max mem: 19788 +Test: [13800/21770] eta: 0:06:18 time: 0.0445 data: 0.0015 max mem: 19788 +Test: [13900/21770] eta: 0:06:14 time: 0.0450 data: 0.0013 max mem: 19788 +Test: [14000/21770] eta: 0:06:09 time: 0.0456 data: 0.0015 max mem: 19788 +Test: [14100/21770] eta: 0:06:04 time: 0.0533 data: 0.0018 max mem: 19788 +Test: [14200/21770] eta: 0:05:59 time: 0.0459 data: 0.0015 max mem: 19788 +Test: [14300/21770] eta: 0:05:55 time: 0.0451 data: 0.0014 max mem: 19788 +Test: [14400/21770] eta: 0:05:50 time: 0.0530 data: 0.0018 max mem: 19788 +Test: [14500/21770] eta: 0:05:45 time: 0.0513 data: 0.0018 max mem: 19788 +Test: [14600/21770] eta: 0:05:41 time: 0.0453 data: 0.0015 max mem: 19788 +Test: [14700/21770] eta: 0:05:36 time: 0.0440 data: 0.0014 max mem: 19788 +Test: [14800/21770] eta: 0:05:31 time: 0.0441 data: 0.0018 max mem: 19788 +Test: [14900/21770] eta: 0:05:26 time: 0.0453 data: 0.0017 max mem: 19788 +Test: [15000/21770] eta: 0:05:21 time: 0.0460 data: 0.0015 max mem: 19788 +Test: [15100/21770] eta: 0:05:17 time: 0.0453 data: 0.0013 max mem: 19788 +Test: [15200/21770] eta: 0:05:12 time: 0.0456 data: 0.0016 max mem: 19788 +Test: [15300/21770] eta: 0:05:07 time: 0.0511 data: 0.0016 max mem: 19788 +Test: [15400/21770] eta: 0:05:02 time: 0.0488 data: 0.0017 max mem: 19788 +Test: [15500/21770] eta: 0:04:58 time: 0.0528 data: 0.0019 max mem: 19788 +Test: [15600/21770] eta: 0:04:53 time: 0.0488 data: 0.0017 max mem: 19788 +Test: [15700/21770] eta: 0:04:48 time: 0.0556 data: 0.0017 max mem: 19788 +Test: [15800/21770] eta: 0:04:44 time: 0.0458 data: 0.0016 max mem: 19788 +Test: [15900/21770] eta: 0:04:39 time: 0.0443 data: 0.0015 max mem: 19788 +Test: [16000/21770] eta: 0:04:34 time: 0.0497 data: 0.0017 max mem: 19788 +Test: [16100/21770] eta: 0:04:29 time: 0.0479 data: 0.0018 max mem: 19788 +Test: [16200/21770] eta: 0:04:25 time: 0.0436 data: 0.0015 max mem: 19788 +Test: [16300/21770] eta: 0:04:20 time: 0.0439 data: 0.0015 max mem: 19788 +Test: [16400/21770] eta: 0:04:15 time: 0.0456 data: 0.0019 max mem: 19788 +Test: [16500/21770] eta: 0:04:10 time: 0.0431 data: 0.0015 max mem: 19788 +Test: [16600/21770] eta: 0:04:05 time: 0.0520 data: 0.0014 max mem: 19788 +Test: [16700/21770] eta: 0:04:01 time: 0.0533 data: 0.0016 max mem: 19788 +Test: [16800/21770] eta: 0:03:56 time: 0.0525 data: 0.0018 max mem: 19788 +Test: [16900/21770] eta: 0:03:51 time: 0.0540 data: 0.0017 max mem: 19788 +Test: [17000/21770] eta: 0:03:47 time: 0.0524 data: 0.0018 max mem: 19788 +Test: [17100/21770] eta: 0:03:42 time: 0.0466 data: 0.0015 max mem: 19788 +Test: [17200/21770] eta: 0:03:37 time: 0.0526 data: 0.0018 max mem: 19788 +Test: [17300/21770] eta: 0:03:32 time: 0.0487 data: 0.0018 max mem: 19788 +Test: [17400/21770] eta: 0:03:28 time: 0.0538 data: 0.0018 max mem: 19788 +Test: [17500/21770] eta: 0:03:23 time: 0.0511 data: 0.0017 max mem: 19788 +Test: [17600/21770] eta: 0:03:18 time: 0.0446 data: 0.0015 max mem: 19788 +Test: [17700/21770] eta: 0:03:13 time: 0.0449 data: 0.0015 max mem: 19788 +Test: [17800/21770] eta: 0:03:09 time: 0.0445 data: 0.0014 max mem: 19788 +Test: [17900/21770] eta: 0:03:04 time: 0.0459 data: 0.0014 max mem: 19788 +Test: [18000/21770] eta: 0:02:59 time: 0.0446 data: 0.0018 max mem: 19788 +Test: [18100/21770] eta: 0:02:54 time: 0.0441 data: 0.0015 max mem: 19788 +Test: [18200/21770] eta: 0:02:49 time: 0.0455 data: 0.0014 max mem: 19788 +Test: [18300/21770] eta: 0:02:45 time: 0.0431 data: 0.0015 max mem: 19788 +Test: [18400/21770] eta: 0:02:40 time: 0.0434 data: 0.0015 max mem: 19788 +Test: [18500/21770] eta: 0:02:35 time: 0.0523 data: 0.0018 max mem: 19788 +Test: [18600/21770] eta: 0:02:30 time: 0.0527 data: 0.0017 max mem: 19788 +Test: [18700/21770] eta: 0:02:26 time: 0.0483 data: 0.0015 max mem: 19788 +Test: [18800/21770] eta: 0:02:21 time: 0.0439 data: 0.0014 max mem: 19788 +Test: [18900/21770] eta: 0:02:16 time: 0.0434 data: 0.0016 max mem: 19788 +Test: [19000/21770] eta: 0:02:11 time: 0.0433 data: 0.0016 max mem: 19788 +Test: [19100/21770] eta: 0:02:06 time: 0.0523 data: 0.0019 max mem: 19788 +Test: [19200/21770] eta: 0:02:02 time: 0.0494 data: 0.0018 max mem: 19788 +Test: [19300/21770] eta: 0:01:57 time: 0.0512 data: 0.0017 max mem: 19788 +Test: [19400/21770] eta: 0:01:52 time: 0.0423 data: 0.0014 max mem: 19788 +Test: [19500/21770] eta: 0:01:47 time: 0.0553 data: 0.0016 max mem: 19788 +Test: [19600/21770] eta: 0:01:43 time: 0.0525 data: 0.0018 max mem: 19788 +Test: [19700/21770] eta: 0:01:38 time: 0.0441 data: 0.0014 max mem: 19788 +Test: [19800/21770] eta: 0:01:33 time: 0.0524 data: 0.0017 max mem: 19788 +Test: [19900/21770] eta: 0:01:28 time: 0.0437 data: 0.0013 max mem: 19788 +Test: [20000/21770] eta: 0:01:24 time: 0.0448 data: 0.0014 max mem: 19788 +Test: [20100/21770] eta: 0:01:19 time: 0.0528 data: 0.0017 max mem: 19788 +Test: [20200/21770] eta: 0:01:14 time: 0.0433 data: 0.0014 max mem: 19788 +Test: [20300/21770] eta: 0:01:09 time: 0.0524 data: 0.0018 max mem: 19788 +Test: [20400/21770] eta: 0:01:05 time: 0.0448 data: 0.0014 max mem: 19788 +Test: [20500/21770] eta: 0:01:00 time: 0.0507 data: 0.0018 max mem: 19788 +Test: [20600/21770] eta: 0:00:55 time: 0.0491 data: 0.0016 max mem: 19788 +Test: [20700/21770] eta: 0:00:50 time: 0.0529 data: 0.0017 max mem: 19788 +Test: [20800/21770] eta: 0:00:46 time: 0.0503 data: 0.0018 max mem: 19788 +Test: [20900/21770] eta: 0:00:41 time: 0.0460 data: 0.0016 max mem: 19788 +Test: [21000/21770] eta: 0:00:36 time: 0.0526 data: 0.0019 max mem: 19788 +Test: [21100/21770] eta: 0:00:31 time: 0.0451 data: 0.0016 max mem: 19788 +Test: [21200/21770] eta: 0:00:27 time: 0.0442 data: 0.0020 max mem: 19788 +Test: [21300/21770] eta: 0:00:22 time: 0.0436 data: 0.0015 max mem: 19788 +Test: [21400/21770] eta: 0:00:17 time: 0.0515 data: 0.0017 max mem: 19788 +Test: [21500/21770] eta: 0:00:12 time: 0.0476 data: 0.0017 max mem: 19788 +Test: [21600/21770] eta: 0:00:08 time: 0.0455 data: 0.0018 max mem: 19788 +Test: [21700/21770] eta: 0:00:03 time: 0.0522 data: 0.0018 max mem: 19788 +Test: Total time: 0:17:16 +Final results: +Mean IoU is 58.44 + + precision@0.5 = 65.12 + precision@0.6 = 59.12 + precision@0.7 = 51.43 + precision@0.8 = 40.21 + precision@0.9 = 18.70 + overall IoU = 61.77 + mean IoU = 58.44 + +Mean accuracy for one-to-zero sample is 80.79 + +Average object IoU 0.5843553412767314 +Overall IoU 61.771697998046875 +Better epoch: 3 + +Epoch: [4] [ 0/2138] eta: 10:18:46 lr: 4.5476097037797e-05 loss: 0.1956 (0.1956) time: 17.3652 data: 1.7132 max mem: 19788 +Epoch: [4] [ 10/2138] eta: 2:30:57 lr: 4.5470779336284665e-05 loss: 0.0901 (0.0977) time: 4.2564 data: 0.1585 max mem: 19788 +Epoch: [4] [ 20/2138] eta: 2:09:14 lr: 4.546546156567223e-05 loss: 0.0830 (0.0941) time: 2.9761 data: 0.0021 max mem: 19788 +Epoch: [4] [ 30/2138] eta: 2:00:30 lr: 4.546014372594982e-05 loss: 0.0810 (0.0901) time: 2.9754 data: 0.0018 max mem: 19788 +Epoch: [4] [ 40/2138] eta: 1:56:38 lr: 4.545482581710754e-05 loss: 0.0772 (0.0878) time: 2.9941 data: 0.0023 max mem: 19788 +Epoch: [4] [ 50/2138] eta: 1:53:44 lr: 4.544950783913554e-05 loss: 0.0686 (0.0854) time: 3.0182 data: 0.0024 max mem: 19788 +Epoch: [4] [ 60/2138] eta: 1:52:28 lr: 4.5444189792023915e-05 loss: 0.0682 (0.0855) time: 3.0662 data: 0.0026 max mem: 19788 +Epoch: [4] [ 70/2138] eta: 1:50:36 lr: 4.543887167576277e-05 loss: 0.0674 (0.0829) time: 3.0586 data: 0.0027 max mem: 19788 +Epoch: [4] [ 80/2138] eta: 1:49:07 lr: 4.543355349034222e-05 loss: 0.0674 (0.0823) time: 2.9799 data: 0.0026 max mem: 19788 +Epoch: [4] [ 90/2138] eta: 1:47:41 lr: 4.5428235235752365e-05 loss: 0.0750 (0.0830) time: 2.9621 data: 0.0024 max mem: 19788 +Epoch: [4] [ 100/2138] eta: 1:46:25 lr: 4.5422916911983324e-05 loss: 0.0809 (0.0825) time: 2.9370 data: 0.0025 max mem: 19788 +Epoch: [4] [ 110/2138] eta: 1:45:24 lr: 4.541759851902517e-05 loss: 0.0857 (0.0834) time: 2.9529 data: 0.0025 max mem: 19788 +Epoch: [4] [ 120/2138] eta: 1:44:22 lr: 4.541228005686802e-05 loss: 0.0741 (0.0825) time: 2.9550 data: 0.0023 max mem: 19788 +Epoch: [4] [ 130/2138] eta: 1:43:25 lr: 4.5406961525501965e-05 loss: 0.0668 (0.0822) time: 2.9338 data: 0.0023 max mem: 19788 +Epoch: [4] [ 140/2138] eta: 1:42:31 lr: 4.54016429249171e-05 loss: 0.0790 (0.0823) time: 2.9291 data: 0.0024 max mem: 19788 +Epoch: [4] [ 150/2138] eta: 1:41:41 lr: 4.539632425510351e-05 loss: 0.0800 (0.0821) time: 2.9305 data: 0.0023 max mem: 19788 +Epoch: [4] [ 160/2138] eta: 1:40:54 lr: 4.5391005516051286e-05 loss: 0.0724 (0.0816) time: 2.9331 data: 0.0028 max mem: 19788 +Epoch: [4] [ 170/2138] eta: 1:40:19 lr: 4.53856867077505e-05 loss: 0.0718 (0.0822) time: 2.9805 data: 0.0028 max mem: 19788 +Epoch: [4] [ 180/2138] eta: 1:39:54 lr: 4.538036783019124e-05 loss: 0.0692 (0.0812) time: 3.0678 data: 0.0026 max mem: 19788 +Epoch: [4] [ 190/2138] eta: 1:39:10 lr: 4.537504888336359e-05 loss: 0.0657 (0.0809) time: 3.0204 data: 0.0028 max mem: 19788 +Epoch: [4] [ 200/2138] eta: 1:38:30 lr: 4.536972986725763e-05 loss: 0.0708 (0.0811) time: 2.9416 data: 0.0028 max mem: 19788 +Epoch: [4] [ 210/2138] eta: 1:38:01 lr: 4.53644107818634e-05 loss: 0.0656 (0.0806) time: 3.0115 data: 0.0025 max mem: 19788 +Epoch: [4] [ 220/2138] eta: 1:37:21 lr: 4.535909162717102e-05 loss: 0.0641 (0.0808) time: 3.0041 data: 0.0028 max mem: 19788 +Epoch: [4] [ 230/2138] eta: 1:36:43 lr: 4.5353772403170515e-05 loss: 0.0749 (0.0813) time: 2.9469 data: 0.0031 max mem: 19788 +Epoch: [4] [ 240/2138] eta: 1:36:13 lr: 4.534845310985198e-05 loss: 0.0841 (0.0810) time: 3.0042 data: 0.0027 max mem: 19788 +Epoch: [4] [ 250/2138] eta: 1:35:33 lr: 4.534313374720545e-05 loss: 0.0833 (0.0812) time: 2.9818 data: 0.0023 max mem: 19788 +Epoch: [4] [ 260/2138] eta: 1:35:06 lr: 4.533781431522101e-05 loss: 0.0671 (0.0806) time: 2.9946 data: 0.0025 max mem: 19788 +Epoch: [4] [ 270/2138] eta: 1:34:26 lr: 4.53324948138887e-05 loss: 0.0671 (0.0805) time: 2.9929 data: 0.0028 max mem: 19788 +Epoch: [4] [ 280/2138] eta: 1:33:49 lr: 4.5327175243198575e-05 loss: 0.0746 (0.0802) time: 2.9154 data: 0.0028 max mem: 19788 +Epoch: [4] [ 290/2138] eta: 1:33:12 lr: 4.5321855603140694e-05 loss: 0.0768 (0.0807) time: 2.9241 data: 0.0027 max mem: 19788 +Epoch: [4] [ 300/2138] eta: 1:32:37 lr: 4.531653589370511e-05 loss: 0.0800 (0.0813) time: 2.9436 data: 0.0024 max mem: 19788 +Epoch: [4] [ 310/2138] eta: 1:32:03 lr: 4.531121611488185e-05 loss: 0.0588 (0.0805) time: 2.9543 data: 0.0026 max mem: 19788 +Epoch: [4] [ 320/2138] eta: 1:31:35 lr: 4.5305896266660966e-05 loss: 0.0551 (0.0799) time: 3.0089 data: 0.0029 max mem: 19788 +Epoch: [4] [ 330/2138] eta: 1:30:58 lr: 4.5300576349032515e-05 loss: 0.0684 (0.0799) time: 2.9843 data: 0.0030 max mem: 19788 +Epoch: [4] [ 340/2138] eta: 1:30:29 lr: 4.52952563619865e-05 loss: 0.0666 (0.0796) time: 2.9693 data: 0.0029 max mem: 19788 +Epoch: [4] [ 350/2138] eta: 1:29:56 lr: 4.5289936305512987e-05 loss: 0.0698 (0.0797) time: 2.9960 data: 0.0026 max mem: 19788 +Epoch: [4] [ 360/2138] eta: 1:29:20 lr: 4.5284616179601994e-05 loss: 0.0741 (0.0798) time: 2.9261 data: 0.0025 max mem: 19788 +Epoch: [4] [ 370/2138] eta: 1:28:46 lr: 4.5279295984243555e-05 loss: 0.0801 (0.0806) time: 2.9242 data: 0.0026 max mem: 19788 +Epoch: [4] [ 380/2138] eta: 1:28:12 lr: 4.527397571942769e-05 loss: 0.0897 (0.0807) time: 2.9397 data: 0.0027 max mem: 19788 +Epoch: [4] [ 390/2138] eta: 1:27:44 lr: 4.526865538514444e-05 loss: 0.0778 (0.0804) time: 2.9887 data: 0.0026 max mem: 19788 +Epoch: [4] [ 400/2138] eta: 1:27:09 lr: 4.52633349813838e-05 loss: 0.0700 (0.0803) time: 2.9802 data: 0.0028 max mem: 19788 +Epoch: [4] [ 410/2138] eta: 1:26:39 lr: 4.52580145081358e-05 loss: 0.0755 (0.0804) time: 2.9564 data: 0.0029 max mem: 19788 +Epoch: [4] [ 420/2138] eta: 1:26:13 lr: 4.525269396539047e-05 loss: 0.0724 (0.0806) time: 3.0552 data: 0.0024 max mem: 19788 +Epoch: [4] [ 430/2138] eta: 1:25:43 lr: 4.52473733531378e-05 loss: 0.0824 (0.0809) time: 3.0589 data: 0.0023 max mem: 19788 +Epoch: [4] [ 440/2138] eta: 1:25:16 lr: 4.524205267136782e-05 loss: 0.0836 (0.0811) time: 3.0548 data: 0.0024 max mem: 19788 +Epoch: [4] [ 450/2138] eta: 1:24:44 lr: 4.523673192007053e-05 loss: 0.0788 (0.0809) time: 3.0288 data: 0.0025 max mem: 19788 +Epoch: [4] [ 460/2138] eta: 1:24:13 lr: 4.5231411099235926e-05 loss: 0.0649 (0.0807) time: 2.9759 data: 0.0026 max mem: 19788 +Epoch: [4] [ 470/2138] eta: 1:23:42 lr: 4.522609020885402e-05 loss: 0.0690 (0.0806) time: 2.9879 data: 0.0027 max mem: 19788 +Epoch: [4] [ 480/2138] eta: 1:23:09 lr: 4.522076924891481e-05 loss: 0.0715 (0.0808) time: 2.9507 data: 0.0028 max mem: 19788 +Epoch: [4] [ 490/2138] eta: 1:22:36 lr: 4.521544821940829e-05 loss: 0.0830 (0.0809) time: 2.9307 data: 0.0030 max mem: 19788 +Epoch: [4] [ 500/2138] eta: 1:22:05 lr: 4.5210127120324455e-05 loss: 0.0801 (0.0807) time: 2.9543 data: 0.0027 max mem: 19788 +Epoch: [4] [ 510/2138] eta: 1:21:33 lr: 4.52048059516533e-05 loss: 0.0713 (0.0806) time: 2.9591 data: 0.0022 max mem: 19788 +Epoch: [4] [ 520/2138] eta: 1:21:04 lr: 4.5199484713384805e-05 loss: 0.0775 (0.0806) time: 2.9995 data: 0.0021 max mem: 19788 +Epoch: [4] [ 530/2138] eta: 1:20:34 lr: 4.519416340550896e-05 loss: 0.0756 (0.0803) time: 3.0191 data: 0.0023 max mem: 19788 +Epoch: [4] [ 540/2138] eta: 1:20:02 lr: 4.518884202801575e-05 loss: 0.0562 (0.0798) time: 2.9615 data: 0.0023 max mem: 19788 +Epoch: [4] [ 550/2138] eta: 1:19:30 lr: 4.5183520580895155e-05 loss: 0.0603 (0.0801) time: 2.9413 data: 0.0022 max mem: 19788 +Epoch: [4] [ 560/2138] eta: 1:18:58 lr: 4.517819906413714e-05 loss: 0.0708 (0.0801) time: 2.9510 data: 0.0024 max mem: 19788 +Epoch: [4] [ 570/2138] eta: 1:18:29 lr: 4.51728774777317e-05 loss: 0.0700 (0.0801) time: 2.9867 data: 0.0026 max mem: 19788 +Epoch: [4] [ 580/2138] eta: 1:17:58 lr: 4.51675558216688e-05 loss: 0.0852 (0.0804) time: 3.0053 data: 0.0023 max mem: 19788 +Epoch: [4] [ 590/2138] eta: 1:17:28 lr: 4.516223409593839e-05 loss: 0.0778 (0.0802) time: 2.9919 data: 0.0021 max mem: 19788 +Epoch: [4] [ 600/2138] eta: 1:16:57 lr: 4.5156912300530455e-05 loss: 0.0673 (0.0801) time: 2.9724 data: 0.0024 max mem: 19788 +Epoch: [4] [ 610/2138] eta: 1:16:26 lr: 4.515159043543497e-05 loss: 0.0630 (0.0800) time: 2.9547 data: 0.0028 max mem: 19788 +Epoch: [4] [ 620/2138] eta: 1:16:00 lr: 4.5146268500641864e-05 loss: 0.0662 (0.0803) time: 3.0621 data: 0.0027 max mem: 19788 +Epoch: [4] [ 630/2138] eta: 1:15:29 lr: 4.5140946496141125e-05 loss: 0.0711 (0.0802) time: 3.0707 data: 0.0029 max mem: 19788 +Epoch: [4] [ 640/2138] eta: 1:14:58 lr: 4.513562442192269e-05 loss: 0.0689 (0.0800) time: 2.9651 data: 0.0029 max mem: 19788 +Epoch: [4] [ 650/2138] eta: 1:14:27 lr: 4.513030227797651e-05 loss: 0.0689 (0.0801) time: 2.9556 data: 0.0028 max mem: 19788 +Epoch: [4] [ 660/2138] eta: 1:13:55 lr: 4.512498006429254e-05 loss: 0.0601 (0.0799) time: 2.9420 data: 0.0028 max mem: 19788 +Epoch: [4] [ 670/2138] eta: 1:13:24 lr: 4.511965778086074e-05 loss: 0.0650 (0.0799) time: 2.9391 data: 0.0026 max mem: 19788 +Epoch: [4] [ 680/2138] eta: 1:12:53 lr: 4.511433542767104e-05 loss: 0.0650 (0.0797) time: 2.9558 data: 0.0023 max mem: 19788 +Epoch: [4] [ 690/2138] eta: 1:12:25 lr: 4.510901300471338e-05 loss: 0.0636 (0.0796) time: 3.0251 data: 0.0021 max mem: 19788 +Epoch: [4] [ 700/2138] eta: 1:11:55 lr: 4.51036905119777e-05 loss: 0.0715 (0.0795) time: 3.0499 data: 0.0022 max mem: 19788 +Epoch: [4] [ 710/2138] eta: 1:11:23 lr: 4.509836794945394e-05 loss: 0.0666 (0.0795) time: 2.9574 data: 0.0025 max mem: 19788 +Epoch: [4] [ 720/2138] eta: 1:10:52 lr: 4.5093045317132036e-05 loss: 0.0648 (0.0793) time: 2.9326 data: 0.0025 max mem: 19788 +Epoch: [4] [ 730/2138] eta: 1:10:20 lr: 4.5087722615001904e-05 loss: 0.0666 (0.0792) time: 2.9301 data: 0.0025 max mem: 19788 +Epoch: [4] [ 740/2138] eta: 1:09:49 lr: 4.508239984305349e-05 loss: 0.0701 (0.0792) time: 2.9063 data: 0.0025 max mem: 19788 +Epoch: [4] [ 750/2138] eta: 1:09:18 lr: 4.50770770012767e-05 loss: 0.0795 (0.0792) time: 2.9241 data: 0.0022 max mem: 19788 +Epoch: [4] [ 760/2138] eta: 1:08:49 lr: 4.507175408966148e-05 loss: 0.0695 (0.0791) time: 3.0042 data: 0.0021 max mem: 19788 +Epoch: [4] [ 770/2138] eta: 1:08:20 lr: 4.506643110819772e-05 loss: 0.0681 (0.0790) time: 3.0592 data: 0.0023 max mem: 19788 +Epoch: [4] [ 780/2138] eta: 1:07:50 lr: 4.506110805687536e-05 loss: 0.0699 (0.0789) time: 3.0090 data: 0.0025 max mem: 19788 +Epoch: [4] [ 790/2138] eta: 1:07:21 lr: 4.5055784935684296e-05 loss: 0.0695 (0.0787) time: 3.0122 data: 0.0026 max mem: 19788 +Epoch: [4] [ 800/2138] eta: 1:06:51 lr: 4.505046174461446e-05 loss: 0.0697 (0.0789) time: 3.0282 data: 0.0028 max mem: 19788 +Epoch: [4] [ 810/2138] eta: 1:06:21 lr: 4.504513848365574e-05 loss: 0.0727 (0.0788) time: 2.9956 data: 0.0028 max mem: 19788 +Epoch: [4] [ 820/2138] eta: 1:05:51 lr: 4.503981515279805e-05 loss: 0.0684 (0.0789) time: 3.0113 data: 0.0028 max mem: 19788 +Epoch: [4] [ 830/2138] eta: 1:05:22 lr: 4.5034491752031296e-05 loss: 0.0704 (0.0788) time: 3.0257 data: 0.0026 max mem: 19788 +Epoch: [4] [ 840/2138] eta: 1:04:51 lr: 4.5029168281345366e-05 loss: 0.0656 (0.0786) time: 2.9920 data: 0.0027 max mem: 19788 +Epoch: [4] [ 850/2138] eta: 1:04:20 lr: 4.502384474073017e-05 loss: 0.0611 (0.0787) time: 2.9509 data: 0.0029 max mem: 19788 +Epoch: [4] [ 860/2138] eta: 1:03:50 lr: 4.5018521130175595e-05 loss: 0.0611 (0.0787) time: 2.9663 data: 0.0028 max mem: 19788 +Epoch: [4] [ 870/2138] eta: 1:03:20 lr: 4.501319744967153e-05 loss: 0.0611 (0.0785) time: 2.9794 data: 0.0023 max mem: 19788 +Epoch: [4] [ 880/2138] eta: 1:02:50 lr: 4.5007873699207876e-05 loss: 0.0643 (0.0785) time: 2.9749 data: 0.0022 max mem: 19788 +Epoch: [4] [ 890/2138] eta: 1:02:19 lr: 4.50025498787745e-05 loss: 0.0694 (0.0784) time: 2.9815 data: 0.0023 max mem: 19788 +Epoch: [4] [ 900/2138] eta: 1:01:49 lr: 4.499722598836131e-05 loss: 0.0587 (0.0783) time: 2.9709 data: 0.0026 max mem: 19788 +Epoch: [4] [ 910/2138] eta: 1:01:20 lr: 4.499190202795816e-05 loss: 0.0600 (0.0783) time: 3.0069 data: 0.0028 max mem: 19788 +Epoch: [4] [ 920/2138] eta: 1:00:50 lr: 4.498657799755494e-05 loss: 0.0592 (0.0780) time: 3.0418 data: 0.0025 max mem: 19788 +Epoch: [4] [ 930/2138] eta: 1:00:20 lr: 4.498125389714152e-05 loss: 0.0657 (0.0781) time: 3.0026 data: 0.0023 max mem: 19788 +Epoch: [4] [ 940/2138] eta: 0:59:49 lr: 4.497592972670778e-05 loss: 0.0769 (0.0781) time: 2.9487 data: 0.0026 max mem: 19788 +Epoch: [4] [ 950/2138] eta: 0:59:19 lr: 4.4970605486243586e-05 loss: 0.0775 (0.0781) time: 2.9451 data: 0.0026 max mem: 19788 +Epoch: [4] [ 960/2138] eta: 0:58:48 lr: 4.49652811757388e-05 loss: 0.0695 (0.0780) time: 2.9604 data: 0.0023 max mem: 19788 +Epoch: [4] [ 970/2138] eta: 0:58:18 lr: 4.4959956795183285e-05 loss: 0.0624 (0.0778) time: 2.9604 data: 0.0022 max mem: 19788 +Epoch: [4] [ 980/2138] eta: 0:57:47 lr: 4.49546323445669e-05 loss: 0.0590 (0.0778) time: 2.9566 data: 0.0025 max mem: 19788 +Epoch: [4] [ 990/2138] eta: 0:57:18 lr: 4.4949307823879524e-05 loss: 0.0726 (0.0779) time: 3.0003 data: 0.0027 max mem: 19788 +Epoch: [4] [1000/2138] eta: 0:56:48 lr: 4.4943983233110984e-05 loss: 0.0663 (0.0778) time: 3.0001 data: 0.0029 max mem: 19788 +Epoch: [4] [1010/2138] eta: 0:56:18 lr: 4.4938658572251145e-05 loss: 0.0647 (0.0777) time: 3.0008 data: 0.0029 max mem: 19788 +Epoch: [4] [1020/2138] eta: 0:55:50 lr: 4.4933333841289856e-05 loss: 0.0608 (0.0776) time: 3.0745 data: 0.0027 max mem: 19788 +Epoch: [4] [1030/2138] eta: 0:55:20 lr: 4.492800904021696e-05 loss: 0.0583 (0.0775) time: 3.0671 data: 0.0025 max mem: 19788 +Epoch: [4] [1040/2138] eta: 0:54:54 lr: 4.49226841690223e-05 loss: 0.0625 (0.0775) time: 3.2112 data: 0.0024 max mem: 19788 +Epoch: [4] [1050/2138] eta: 0:54:24 lr: 4.491735922769573e-05 loss: 0.0690 (0.0774) time: 3.1960 data: 0.0025 max mem: 19788 +Epoch: [4] [1060/2138] eta: 0:53:53 lr: 4.491203421622707e-05 loss: 0.0669 (0.0773) time: 2.9635 data: 0.0028 max mem: 19788 +Epoch: [4] [1070/2138] eta: 0:53:23 lr: 4.4906709134606166e-05 loss: 0.0678 (0.0772) time: 2.9270 data: 0.0031 max mem: 19788 +Epoch: [4] [1080/2138] eta: 0:52:53 lr: 4.490138398282285e-05 loss: 0.0787 (0.0772) time: 3.0005 data: 0.0030 max mem: 19788 +Epoch: [4] [1090/2138] eta: 0:52:24 lr: 4.489605876086695e-05 loss: 0.0600 (0.0773) time: 3.0612 data: 0.0025 max mem: 19788 +Epoch: [4] [1100/2138] eta: 0:51:53 lr: 4.4890733468728284e-05 loss: 0.0606 (0.0772) time: 2.9998 data: 0.0022 max mem: 19788 +Epoch: [4] [1110/2138] eta: 0:51:23 lr: 4.48854081063967e-05 loss: 0.0692 (0.0772) time: 2.9660 data: 0.0026 max mem: 19788 +Epoch: [4] [1120/2138] eta: 0:50:53 lr: 4.488008267386199e-05 loss: 0.0613 (0.0771) time: 2.9817 data: 0.0029 max mem: 19788 +Epoch: [4] [1130/2138] eta: 0:50:23 lr: 4.487475717111399e-05 loss: 0.0613 (0.0770) time: 3.0058 data: 0.0030 max mem: 19788 +Epoch: [4] [1140/2138] eta: 0:49:53 lr: 4.486943159814252e-05 loss: 0.0696 (0.0770) time: 3.0036 data: 0.0031 max mem: 19788 +Epoch: [4] [1150/2138] eta: 0:49:23 lr: 4.486410595493738e-05 loss: 0.0696 (0.0769) time: 2.9595 data: 0.0026 max mem: 19788 +Epoch: [4] [1160/2138] eta: 0:48:54 lr: 4.4858780241488385e-05 loss: 0.0631 (0.0769) time: 3.0460 data: 0.0022 max mem: 19788 +Epoch: [4] [1170/2138] eta: 0:48:24 lr: 4.485345445778535e-05 loss: 0.0563 (0.0768) time: 3.0730 data: 0.0024 max mem: 19788 +Epoch: [4] [1180/2138] eta: 0:47:54 lr: 4.484812860381806e-05 loss: 0.0574 (0.0767) time: 2.9884 data: 0.0025 max mem: 19788 +Epoch: [4] [1190/2138] eta: 0:47:23 lr: 4.484280267957633e-05 loss: 0.0574 (0.0767) time: 2.9548 data: 0.0026 max mem: 19788 +Epoch: [4] [1200/2138] eta: 0:46:53 lr: 4.4837476685049965e-05 loss: 0.0567 (0.0765) time: 2.9273 data: 0.0027 max mem: 19788 +Epoch: [4] [1210/2138] eta: 0:46:22 lr: 4.4832150620228746e-05 loss: 0.0601 (0.0765) time: 2.9237 data: 0.0028 max mem: 19788 +Epoch: [4] [1220/2138] eta: 0:45:52 lr: 4.482682448510247e-05 loss: 0.0601 (0.0764) time: 2.9541 data: 0.0026 max mem: 19788 +Epoch: [4] [1230/2138] eta: 0:45:22 lr: 4.482149827966094e-05 loss: 0.0594 (0.0763) time: 2.9907 data: 0.0024 max mem: 19788 +Epoch: [4] [1240/2138] eta: 0:44:52 lr: 4.481617200389392e-05 loss: 0.0617 (0.0762) time: 2.9834 data: 0.0026 max mem: 19788 +Epoch: [4] [1250/2138] eta: 0:44:22 lr: 4.481084565779122e-05 loss: 0.0701 (0.0763) time: 2.9722 data: 0.0028 max mem: 19788 +Epoch: [4] [1260/2138] eta: 0:43:51 lr: 4.480551924134261e-05 loss: 0.0705 (0.0763) time: 2.9671 data: 0.0026 max mem: 19788 +Epoch: [4] [1270/2138] eta: 0:43:21 lr: 4.480019275453786e-05 loss: 0.0637 (0.0763) time: 2.9510 data: 0.0022 max mem: 19788 +Epoch: [4] [1280/2138] eta: 0:42:51 lr: 4.479486619736676e-05 loss: 0.0678 (0.0763) time: 2.9337 data: 0.0022 max mem: 19788 +Epoch: [4] [1290/2138] eta: 0:42:20 lr: 4.4789539569819076e-05 loss: 0.0681 (0.0762) time: 2.9453 data: 0.0024 max mem: 19788 +Epoch: [4] [1300/2138] eta: 0:41:50 lr: 4.4784212871884586e-05 loss: 0.0577 (0.0761) time: 2.9785 data: 0.0023 max mem: 19788 +Epoch: [4] [1310/2138] eta: 0:41:21 lr: 4.4778886103553045e-05 loss: 0.0578 (0.0759) time: 3.0651 data: 0.0024 max mem: 19788 +Epoch: [4] [1320/2138] eta: 0:40:51 lr: 4.477355926481422e-05 loss: 0.0601 (0.0759) time: 3.0331 data: 0.0026 max mem: 19788 +Epoch: [4] [1330/2138] eta: 0:40:21 lr: 4.476823235565788e-05 loss: 0.0644 (0.0759) time: 2.9362 data: 0.0026 max mem: 19788 +Epoch: [4] [1340/2138] eta: 0:39:50 lr: 4.476290537607379e-05 loss: 0.0724 (0.0760) time: 2.9455 data: 0.0025 max mem: 19788 +Epoch: [4] [1350/2138] eta: 0:39:20 lr: 4.475757832605169e-05 loss: 0.0784 (0.0761) time: 2.9755 data: 0.0024 max mem: 19788 +Epoch: [4] [1360/2138] eta: 0:38:50 lr: 4.475225120558135e-05 loss: 0.0777 (0.0761) time: 2.9679 data: 0.0025 max mem: 19788 +Epoch: [4] [1370/2138] eta: 0:38:20 lr: 4.47469240146525e-05 loss: 0.0778 (0.0765) time: 2.9271 data: 0.0026 max mem: 19788 +Epoch: [4] [1380/2138] eta: 0:37:50 lr: 4.474159675325491e-05 loss: 0.0795 (0.0765) time: 2.9500 data: 0.0026 max mem: 19788 +Epoch: [4] [1390/2138] eta: 0:37:20 lr: 4.47362694213783e-05 loss: 0.0633 (0.0764) time: 3.0419 data: 0.0026 max mem: 19788 +Epoch: [4] [1400/2138] eta: 0:36:50 lr: 4.473094201901243e-05 loss: 0.0633 (0.0764) time: 3.0617 data: 0.0024 max mem: 19788 +Epoch: [4] [1410/2138] eta: 0:36:20 lr: 4.472561454614704e-05 loss: 0.0583 (0.0763) time: 3.0024 data: 0.0022 max mem: 19788 +Epoch: [4] [1420/2138] eta: 0:35:51 lr: 4.472028700277186e-05 loss: 0.0557 (0.0762) time: 3.0213 data: 0.0021 max mem: 19788 +Epoch: [4] [1430/2138] eta: 0:35:21 lr: 4.4714959388876617e-05 loss: 0.0643 (0.0762) time: 3.0275 data: 0.0022 max mem: 19788 +Epoch: [4] [1440/2138] eta: 0:34:51 lr: 4.470963170445105e-05 loss: 0.0672 (0.0762) time: 2.9867 data: 0.0024 max mem: 19788 +Epoch: [4] [1450/2138] eta: 0:34:22 lr: 4.4704303949484896e-05 loss: 0.0574 (0.0761) time: 3.0802 data: 0.0025 max mem: 19788 +Epoch: [4] [1460/2138] eta: 0:33:52 lr: 4.469897612396786e-05 loss: 0.0574 (0.0760) time: 3.0788 data: 0.0027 max mem: 19788 +Epoch: [4] [1470/2138] eta: 0:33:22 lr: 4.4693648227889674e-05 loss: 0.0649 (0.0760) time: 3.0020 data: 0.0027 max mem: 19788 +Epoch: [4] [1480/2138] eta: 0:32:52 lr: 4.468832026124006e-05 loss: 0.0661 (0.0759) time: 2.9869 data: 0.0026 max mem: 19788 +Epoch: [4] [1490/2138] eta: 0:32:21 lr: 4.468299222400872e-05 loss: 0.0722 (0.0760) time: 2.9377 data: 0.0029 max mem: 19788 +Epoch: [4] [1500/2138] eta: 0:31:51 lr: 4.46776641161854e-05 loss: 0.0677 (0.0760) time: 2.9338 data: 0.0029 max mem: 19788 +Epoch: [4] [1510/2138] eta: 0:31:21 lr: 4.467233593775977e-05 loss: 0.0676 (0.0759) time: 2.9363 data: 0.0025 max mem: 19788 +Epoch: [4] [1520/2138] eta: 0:30:51 lr: 4.466700768872156e-05 loss: 0.0704 (0.0759) time: 2.9370 data: 0.0022 max mem: 19788 +Epoch: [4] [1530/2138] eta: 0:30:21 lr: 4.466167936906047e-05 loss: 0.0704 (0.0759) time: 2.9322 data: 0.0020 max mem: 19788 +Epoch: [4] [1540/2138] eta: 0:29:50 lr: 4.4656350978766206e-05 loss: 0.0690 (0.0758) time: 2.9312 data: 0.0023 max mem: 19788 +Epoch: [4] [1550/2138] eta: 0:29:20 lr: 4.465102251782845e-05 loss: 0.0667 (0.0759) time: 2.9420 data: 0.0024 max mem: 19788 +Epoch: [4] [1560/2138] eta: 0:28:50 lr: 4.4645693986236936e-05 loss: 0.0719 (0.0758) time: 2.9627 data: 0.0023 max mem: 19788 +Epoch: [4] [1570/2138] eta: 0:28:20 lr: 4.464036538398132e-05 loss: 0.0618 (0.0758) time: 2.9695 data: 0.0024 max mem: 19788 +Epoch: [4] [1580/2138] eta: 0:27:50 lr: 4.46350367110513e-05 loss: 0.0648 (0.0757) time: 2.9569 data: 0.0025 max mem: 19788 +Epoch: [4] [1590/2138] eta: 0:27:20 lr: 4.4629707967436576e-05 loss: 0.0706 (0.0757) time: 2.9424 data: 0.0028 max mem: 19788 +Epoch: [4] [1600/2138] eta: 0:26:50 lr: 4.4624379153126835e-05 loss: 0.0755 (0.0757) time: 2.9373 data: 0.0030 max mem: 19788 +Epoch: [4] [1610/2138] eta: 0:26:20 lr: 4.4619050268111736e-05 loss: 0.0684 (0.0756) time: 2.9536 data: 0.0028 max mem: 19788 +Epoch: [4] [1620/2138] eta: 0:25:50 lr: 4.461372131238098e-05 loss: 0.0576 (0.0755) time: 2.9670 data: 0.0026 max mem: 19788 +Epoch: [4] [1630/2138] eta: 0:25:20 lr: 4.4608392285924234e-05 loss: 0.0517 (0.0754) time: 2.9888 data: 0.0029 max mem: 19788 +Epoch: [4] [1640/2138] eta: 0:24:50 lr: 4.4603063188731164e-05 loss: 0.0594 (0.0754) time: 2.9936 data: 0.0031 max mem: 19788 +Epoch: [4] [1650/2138] eta: 0:24:20 lr: 4.4597734020791455e-05 loss: 0.0649 (0.0754) time: 2.9629 data: 0.0032 max mem: 19788 +Epoch: [4] [1660/2138] eta: 0:23:50 lr: 4.459240478209477e-05 loss: 0.0649 (0.0753) time: 2.9567 data: 0.0031 max mem: 19788 +Epoch: [4] [1670/2138] eta: 0:23:20 lr: 4.458707547263076e-05 loss: 0.0552 (0.0752) time: 2.9924 data: 0.0027 max mem: 19788 +Epoch: [4] [1680/2138] eta: 0:22:50 lr: 4.458174609238911e-05 loss: 0.0549 (0.0752) time: 2.9784 data: 0.0024 max mem: 19788 +Epoch: [4] [1690/2138] eta: 0:22:20 lr: 4.457641664135946e-05 loss: 0.0561 (0.0751) time: 2.9252 data: 0.0023 max mem: 19788 +Epoch: [4] [1700/2138] eta: 0:21:50 lr: 4.4571087119531475e-05 loss: 0.0546 (0.0750) time: 2.9419 data: 0.0023 max mem: 19788 +Epoch: [4] [1710/2138] eta: 0:21:20 lr: 4.456575752689481e-05 loss: 0.0595 (0.0750) time: 2.9417 data: 0.0022 max mem: 19788 +Epoch: [4] [1720/2138] eta: 0:20:50 lr: 4.45604278634391e-05 loss: 0.0646 (0.0750) time: 2.9878 data: 0.0023 max mem: 19788 +Epoch: [4] [1730/2138] eta: 0:20:20 lr: 4.455509812915401e-05 loss: 0.0644 (0.0750) time: 3.0536 data: 0.0025 max mem: 19788 +Epoch: [4] [1740/2138] eta: 0:19:50 lr: 4.454976832402917e-05 loss: 0.0665 (0.0749) time: 3.0026 data: 0.0027 max mem: 19788 +Epoch: [4] [1750/2138] eta: 0:19:20 lr: 4.454443844805424e-05 loss: 0.0625 (0.0749) time: 2.9354 data: 0.0029 max mem: 19788 +Epoch: [4] [1760/2138] eta: 0:18:50 lr: 4.453910850121884e-05 loss: 0.0625 (0.0748) time: 2.9071 data: 0.0029 max mem: 19788 +Epoch: [4] [1770/2138] eta: 0:18:20 lr: 4.4533778483512614e-05 loss: 0.0644 (0.0748) time: 2.9367 data: 0.0027 max mem: 19788 +Epoch: [4] [1780/2138] eta: 0:17:50 lr: 4.45284483949252e-05 loss: 0.0581 (0.0747) time: 2.9850 data: 0.0028 max mem: 19788 +Epoch: [4] [1790/2138] eta: 0:17:20 lr: 4.4523118235446214e-05 loss: 0.0548 (0.0747) time: 2.9802 data: 0.0029 max mem: 19788 +Epoch: [4] [1800/2138] eta: 0:16:50 lr: 4.4517788005065294e-05 loss: 0.0624 (0.0747) time: 2.9995 data: 0.0027 max mem: 19788 +Epoch: [4] [1810/2138] eta: 0:16:21 lr: 4.451245770377206e-05 loss: 0.0624 (0.0747) time: 3.0338 data: 0.0027 max mem: 19788 +Epoch: [4] [1820/2138] eta: 0:15:51 lr: 4.450712733155613e-05 loss: 0.0529 (0.0746) time: 3.0399 data: 0.0026 max mem: 19788 +Epoch: [4] [1830/2138] eta: 0:15:21 lr: 4.4501796888407136e-05 loss: 0.0565 (0.0745) time: 3.0097 data: 0.0027 max mem: 19788 +Epoch: [4] [1840/2138] eta: 0:14:51 lr: 4.4496466374314685e-05 loss: 0.0580 (0.0745) time: 2.9782 data: 0.0026 max mem: 19788 +Epoch: [4] [1850/2138] eta: 0:14:21 lr: 4.449113578926837e-05 loss: 0.0615 (0.0745) time: 2.9851 data: 0.0023 max mem: 19788 +Epoch: [4] [1860/2138] eta: 0:13:51 lr: 4.448580513325783e-05 loss: 0.0587 (0.0744) time: 2.9518 data: 0.0022 max mem: 19788 +Epoch: [4] [1870/2138] eta: 0:13:21 lr: 4.448047440627266e-05 loss: 0.0600 (0.0744) time: 2.9482 data: 0.0021 max mem: 19788 +Epoch: [4] [1880/2138] eta: 0:12:51 lr: 4.4475143608302466e-05 loss: 0.0671 (0.0744) time: 2.9489 data: 0.0021 max mem: 19788 +Epoch: [4] [1890/2138] eta: 0:12:21 lr: 4.446981273933684e-05 loss: 0.0689 (0.0743) time: 2.9650 data: 0.0023 max mem: 19788 +Epoch: [4] [1900/2138] eta: 0:11:51 lr: 4.446448179936539e-05 loss: 0.0633 (0.0743) time: 3.0427 data: 0.0025 max mem: 19788 +Epoch: [4] [1910/2138] eta: 0:11:21 lr: 4.445915078837771e-05 loss: 0.0638 (0.0743) time: 3.0116 data: 0.0027 max mem: 19788 +Epoch: [4] [1920/2138] eta: 0:10:51 lr: 4.44538197063634e-05 loss: 0.0701 (0.0743) time: 2.9485 data: 0.0029 max mem: 19788 +Epoch: [4] [1930/2138] eta: 0:10:21 lr: 4.444848855331202e-05 loss: 0.0698 (0.0743) time: 2.9445 data: 0.0031 max mem: 19788 +Epoch: [4] [1940/2138] eta: 0:09:52 lr: 4.444315732921319e-05 loss: 0.0627 (0.0743) time: 2.9445 data: 0.0028 max mem: 19788 +Epoch: [4] [1950/2138] eta: 0:09:22 lr: 4.4437826034056465e-05 loss: 0.0627 (0.0743) time: 2.9465 data: 0.0023 max mem: 19788 +Epoch: [4] [1960/2138] eta: 0:08:52 lr: 4.4432494667831454e-05 loss: 0.0589 (0.0742) time: 2.9399 data: 0.0023 max mem: 19788 +Epoch: [4] [1970/2138] eta: 0:08:22 lr: 4.442716323052771e-05 loss: 0.0594 (0.0742) time: 2.9840 data: 0.0025 max mem: 19788 +Epoch: [4] [1980/2138] eta: 0:07:52 lr: 4.442183172213482e-05 loss: 0.0700 (0.0742) time: 3.0535 data: 0.0024 max mem: 19788 +Epoch: [4] [1990/2138] eta: 0:07:22 lr: 4.441650014264235e-05 loss: 0.0679 (0.0742) time: 3.0615 data: 0.0026 max mem: 19788 +Epoch: [4] [2000/2138] eta: 0:06:52 lr: 4.4411168492039886e-05 loss: 0.0622 (0.0741) time: 3.0064 data: 0.0026 max mem: 19788 +Epoch: [4] [2010/2138] eta: 0:06:22 lr: 4.440583677031697e-05 loss: 0.0606 (0.0741) time: 2.9604 data: 0.0028 max mem: 19788 +Epoch: [4] [2020/2138] eta: 0:05:52 lr: 4.440050497746317e-05 loss: 0.0568 (0.0740) time: 2.9451 data: 0.0026 max mem: 19788 +Epoch: [4] [2030/2138] eta: 0:05:22 lr: 4.439517311346805e-05 loss: 0.0620 (0.0740) time: 2.9527 data: 0.0022 max mem: 19788 +Epoch: [4] [2040/2138] eta: 0:04:52 lr: 4.438984117832118e-05 loss: 0.0767 (0.0741) time: 2.9710 data: 0.0023 max mem: 19788 +Epoch: [4] [2050/2138] eta: 0:04:23 lr: 4.4384509172012096e-05 loss: 0.0551 (0.0740) time: 3.0730 data: 0.0025 max mem: 19788 +Epoch: [4] [2060/2138] eta: 0:03:53 lr: 4.4379177094530355e-05 loss: 0.0550 (0.0739) time: 3.0716 data: 0.0025 max mem: 19788 +Epoch: [4] [2070/2138] eta: 0:03:23 lr: 4.43738449458655e-05 loss: 0.0533 (0.0739) time: 3.0247 data: 0.0026 max mem: 19788 +Epoch: [4] [2080/2138] eta: 0:02:53 lr: 4.43685127260071e-05 loss: 0.0576 (0.0739) time: 3.0001 data: 0.0028 max mem: 19788 +Epoch: [4] [2090/2138] eta: 0:02:23 lr: 4.4363180434944664e-05 loss: 0.0702 (0.0738) time: 2.9241 data: 0.0028 max mem: 19788 +Epoch: [4] [2100/2138] eta: 0:01:53 lr: 4.435784807266775e-05 loss: 0.0672 (0.0738) time: 2.9287 data: 0.0029 max mem: 19788 +Epoch: [4] [2110/2138] eta: 0:01:23 lr: 4.435251563916589e-05 loss: 0.0765 (0.0738) time: 2.9448 data: 0.0029 max mem: 19788 +Epoch: [4] [2120/2138] eta: 0:00:53 lr: 4.434718313442863e-05 loss: 0.0799 (0.0738) time: 2.9868 data: 0.0030 max mem: 19788 +Epoch: [4] [2130/2138] eta: 0:00:23 lr: 4.4341850558445474e-05 loss: 0.0779 (0.0739) time: 2.9852 data: 0.0026 max mem: 19788 +Epoch: [4] Total time: 1:46:32 +Test: [ 0/21770] eta: 16:35:19 time: 2.7432 data: 2.5386 max mem: 19788 +Test: [ 100/21770] eta: 0:26:44 time: 0.0493 data: 0.0015 max mem: 19788 +Test: [ 200/21770] eta: 0:21:41 time: 0.0518 data: 0.0016 max mem: 19788 +Test: [ 300/21770] eta: 0:20:17 time: 0.0513 data: 0.0016 max mem: 19788 +Test: [ 400/21770] eta: 0:19:15 time: 0.0429 data: 0.0016 max mem: 19788 +Test: [ 500/21770] eta: 0:18:40 time: 0.0423 data: 0.0013 max mem: 19788 +Test: [ 600/21770] eta: 0:18:15 time: 0.0530 data: 0.0017 max mem: 19788 +Test: [ 700/21770] eta: 0:17:59 time: 0.0447 data: 0.0015 max mem: 19788 +Test: [ 800/21770] eta: 0:17:40 time: 0.0466 data: 0.0016 max mem: 19788 +Test: [ 900/21770] eta: 0:17:31 time: 0.0527 data: 0.0018 max mem: 19788 +Test: [ 1000/21770] eta: 0:17:18 time: 0.0462 data: 0.0015 max mem: 19788 +Test: [ 1100/21770] eta: 0:17:18 time: 0.0523 data: 0.0018 max mem: 19788 +Test: [ 1200/21770] eta: 0:17:07 time: 0.0442 data: 0.0014 max mem: 19788 +Test: [ 1300/21770] eta: 0:16:55 time: 0.0513 data: 0.0017 max mem: 19788 +Test: [ 1400/21770] eta: 0:16:52 time: 0.0507 data: 0.0018 max mem: 19788 +Test: [ 1500/21770] eta: 0:16:43 time: 0.0465 data: 0.0016 max mem: 19788 +Test: [ 1600/21770] eta: 0:16:38 time: 0.0436 data: 0.0014 max mem: 19788 +Test: [ 1700/21770] eta: 0:16:35 time: 0.0526 data: 0.0017 max mem: 19788 +Test: [ 1800/21770] eta: 0:16:24 time: 0.0434 data: 0.0014 max mem: 19788 +Test: [ 1900/21770] eta: 0:16:19 time: 0.0525 data: 0.0017 max mem: 19788 +Test: [ 2000/21770] eta: 0:16:13 time: 0.0446 data: 0.0016 max mem: 19788 +Test: [ 2100/21770] eta: 0:16:09 time: 0.0523 data: 0.0018 max mem: 19788 +Test: [ 2200/21770] eta: 0:16:00 time: 0.0440 data: 0.0015 max mem: 19788 +Test: [ 2300/21770] eta: 0:15:54 time: 0.0452 data: 0.0015 max mem: 19788 +Test: [ 2400/21770] eta: 0:15:51 time: 0.0527 data: 0.0017 max mem: 19788 +Test: [ 2500/21770] eta: 0:15:43 time: 0.0444 data: 0.0014 max mem: 19788 +Test: [ 2600/21770] eta: 0:15:34 time: 0.0440 data: 0.0015 max mem: 19788 +Test: [ 2700/21770] eta: 0:15:28 time: 0.0457 data: 0.0014 max mem: 19788 +Test: [ 2800/21770] eta: 0:15:24 time: 0.0443 data: 0.0015 max mem: 19788 +Test: [ 2900/21770] eta: 0:15:18 time: 0.0454 data: 0.0017 max mem: 19788 +Test: [ 3000/21770] eta: 0:15:11 time: 0.0449 data: 0.0015 max mem: 19788 +Test: [ 3100/21770] eta: 0:15:06 time: 0.0531 data: 0.0018 max mem: 19788 +Test: [ 3200/21770] eta: 0:15:02 time: 0.0524 data: 0.0016 max mem: 19788 +Test: [ 3300/21770] eta: 0:14:57 time: 0.0515 data: 0.0014 max mem: 19788 +Test: [ 3400/21770] eta: 0:14:51 time: 0.0436 data: 0.0015 max mem: 19788 +Test: [ 3500/21770] eta: 0:14:44 time: 0.0431 data: 0.0015 max mem: 19788 +Test: [ 3600/21770] eta: 0:14:39 time: 0.0528 data: 0.0017 max mem: 19788 +Test: [ 3700/21770] eta: 0:14:35 time: 0.0527 data: 0.0018 max mem: 19788 +Test: [ 3800/21770] eta: 0:14:31 time: 0.0526 data: 0.0017 max mem: 19788 +Test: [ 3900/21770] eta: 0:14:26 time: 0.0446 data: 0.0015 max mem: 19788 +Test: [ 4000/21770] eta: 0:14:21 time: 0.0449 data: 0.0016 max mem: 19788 +Test: [ 4100/21770] eta: 0:14:16 time: 0.0446 data: 0.0015 max mem: 19788 +Test: [ 4200/21770] eta: 0:14:13 time: 0.0527 data: 0.0018 max mem: 19788 +Test: [ 4300/21770] eta: 0:14:09 time: 0.0444 data: 0.0016 max mem: 19788 +Test: [ 4400/21770] eta: 0:14:03 time: 0.0453 data: 0.0015 max mem: 19788 +Test: [ 4500/21770] eta: 0:13:58 time: 0.0520 data: 0.0018 max mem: 19788 +Test: [ 4600/21770] eta: 0:13:53 time: 0.0532 data: 0.0018 max mem: 19788 +Test: [ 4700/21770] eta: 0:13:50 time: 0.0524 data: 0.0017 max mem: 19788 +Test: [ 4800/21770] eta: 0:13:45 time: 0.0494 data: 0.0017 max mem: 19788 +Test: [ 4900/21770] eta: 0:13:40 time: 0.0450 data: 0.0013 max mem: 19788 +Test: [ 5000/21770] eta: 0:13:34 time: 0.0437 data: 0.0016 max mem: 19788 +Test: [ 5100/21770] eta: 0:13:28 time: 0.0457 data: 0.0015 max mem: 19788 +Test: [ 5200/21770] eta: 0:13:24 time: 0.0497 data: 0.0015 max mem: 19788 +Test: [ 5300/21770] eta: 0:13:19 time: 0.0525 data: 0.0017 max mem: 19788 +Test: [ 5400/21770] eta: 0:13:13 time: 0.0435 data: 0.0016 max mem: 19788 +Test: [ 5500/21770] eta: 0:13:07 time: 0.0484 data: 0.0017 max mem: 19788 +Test: [ 5600/21770] eta: 0:13:03 time: 0.0450 data: 0.0016 max mem: 19788 +Test: [ 5700/21770] eta: 0:12:57 time: 0.0441 data: 0.0016 max mem: 19788 +Test: [ 5800/21770] eta: 0:12:51 time: 0.0437 data: 0.0018 max mem: 19788 +Test: [ 5900/21770] eta: 0:12:45 time: 0.0429 data: 0.0016 max mem: 19788 +Test: [ 6000/21770] eta: 0:12:40 time: 0.0443 data: 0.0015 max mem: 19788 +Test: [ 6100/21770] eta: 0:12:35 time: 0.0462 data: 0.0014 max mem: 19788 +Test: [ 6200/21770] eta: 0:12:31 time: 0.0477 data: 0.0016 max mem: 19788 +Test: [ 6300/21770] eta: 0:12:26 time: 0.0452 data: 0.0016 max mem: 19788 +Test: [ 6400/21770] eta: 0:12:23 time: 0.0486 data: 0.0016 max mem: 19788 +Test: [ 6500/21770] eta: 0:12:17 time: 0.0475 data: 0.0015 max mem: 19788 +Test: [ 6600/21770] eta: 0:12:13 time: 0.0548 data: 0.0014 max mem: 19788 +Test: [ 6700/21770] eta: 0:12:09 time: 0.0436 data: 0.0014 max mem: 19788 +Test: [ 6800/21770] eta: 0:12:04 time: 0.0517 data: 0.0015 max mem: 19788 +Test: [ 6900/21770] eta: 0:11:59 time: 0.0481 data: 0.0016 max mem: 19788 +Test: [ 7000/21770] eta: 0:11:55 time: 0.0537 data: 0.0019 max mem: 19788 +Test: [ 7100/21770] eta: 0:11:50 time: 0.0466 data: 0.0016 max mem: 19788 +Test: [ 7200/21770] eta: 0:11:45 time: 0.0486 data: 0.0015 max mem: 19788 +Test: [ 7300/21770] eta: 0:11:39 time: 0.0439 data: 0.0017 max mem: 19788 +Test: [ 7400/21770] eta: 0:11:34 time: 0.0446 data: 0.0013 max mem: 19788 +Test: [ 7500/21770] eta: 0:11:28 time: 0.0495 data: 0.0017 max mem: 19788 +Test: [ 7600/21770] eta: 0:11:24 time: 0.0454 data: 0.0014 max mem: 19788 +Test: [ 7700/21770] eta: 0:11:19 time: 0.0528 data: 0.0019 max mem: 19788 +Test: [ 7800/21770] eta: 0:11:15 time: 0.0479 data: 0.0016 max mem: 19788 +Test: [ 7900/21770] eta: 0:11:10 time: 0.0450 data: 0.0015 max mem: 19788 +Test: [ 8000/21770] eta: 0:11:05 time: 0.0430 data: 0.0014 max mem: 19788 +Test: [ 8100/21770] eta: 0:10:59 time: 0.0438 data: 0.0014 max mem: 19788 +Test: [ 8200/21770] eta: 0:10:53 time: 0.0435 data: 0.0014 max mem: 19788 +Test: [ 8300/21770] eta: 0:10:48 time: 0.0448 data: 0.0014 max mem: 19788 +Test: [ 8400/21770] eta: 0:10:43 time: 0.0471 data: 0.0016 max mem: 19788 +Test: [ 8500/21770] eta: 0:10:38 time: 0.0433 data: 0.0015 max mem: 19788 +Test: [ 8600/21770] eta: 0:10:33 time: 0.0437 data: 0.0016 max mem: 19788 +Test: [ 8700/21770] eta: 0:10:28 time: 0.0488 data: 0.0014 max mem: 19788 +Test: [ 8800/21770] eta: 0:10:23 time: 0.0543 data: 0.0017 max mem: 19788 +Test: [ 8900/21770] eta: 0:10:19 time: 0.0529 data: 0.0017 max mem: 19788 +Test: [ 9000/21770] eta: 0:10:14 time: 0.0455 data: 0.0016 max mem: 19788 +Test: [ 9100/21770] eta: 0:10:09 time: 0.0503 data: 0.0016 max mem: 19788 +Test: [ 9200/21770] eta: 0:10:04 time: 0.0435 data: 0.0015 max mem: 19788 +Test: [ 9300/21770] eta: 0:09:59 time: 0.0445 data: 0.0014 max mem: 19788 +Test: [ 9400/21770] eta: 0:09:53 time: 0.0449 data: 0.0014 max mem: 19788 +Test: [ 9500/21770] eta: 0:09:48 time: 0.0428 data: 0.0015 max mem: 19788 +Test: [ 9600/21770] eta: 0:09:44 time: 0.0533 data: 0.0018 max mem: 19788 +Test: [ 9700/21770] eta: 0:09:39 time: 0.0488 data: 0.0014 max mem: 19788 +Test: [ 9800/21770] eta: 0:09:35 time: 0.0473 data: 0.0017 max mem: 19788 +Test: [ 9900/21770] eta: 0:09:29 time: 0.0433 data: 0.0013 max mem: 19788 +Test: [10000/21770] eta: 0:09:24 time: 0.0452 data: 0.0015 max mem: 19788 +Test: [10100/21770] eta: 0:09:19 time: 0.0472 data: 0.0016 max mem: 19788 +Test: [10200/21770] eta: 0:09:14 time: 0.0500 data: 0.0017 max mem: 19788 +Test: [10300/21770] eta: 0:09:09 time: 0.0456 data: 0.0016 max mem: 19788 +Test: [10400/21770] eta: 0:09:04 time: 0.0452 data: 0.0014 max mem: 19788 +Test: [10500/21770] eta: 0:09:00 time: 0.0519 data: 0.0018 max mem: 19788 +Test: [10600/21770] eta: 0:08:55 time: 0.0543 data: 0.0018 max mem: 19788 +Test: [10700/21770] eta: 0:08:50 time: 0.0435 data: 0.0015 max mem: 19788 +Test: [10800/21770] eta: 0:08:46 time: 0.0524 data: 0.0017 max mem: 19788 +Test: [10900/21770] eta: 0:08:41 time: 0.0451 data: 0.0015 max mem: 19788 +Test: [11000/21770] eta: 0:08:36 time: 0.0440 data: 0.0015 max mem: 19788 +Test: [11100/21770] eta: 0:08:31 time: 0.0506 data: 0.0017 max mem: 19788 +Test: [11200/21770] eta: 0:08:27 time: 0.0521 data: 0.0016 max mem: 19788 +Test: [11300/21770] eta: 0:08:22 time: 0.0488 data: 0.0017 max mem: 19788 +Test: [11400/21770] eta: 0:08:17 time: 0.0524 data: 0.0017 max mem: 19788 +Test: [11500/21770] eta: 0:08:12 time: 0.0440 data: 0.0015 max mem: 19788 +Test: [11600/21770] eta: 0:08:07 time: 0.0437 data: 0.0015 max mem: 19788 +Test: [11700/21770] eta: 0:08:02 time: 0.0487 data: 0.0016 max mem: 19788 +Test: [11800/21770] eta: 0:07:58 time: 0.0453 data: 0.0014 max mem: 19788 +Test: [11900/21770] eta: 0:07:53 time: 0.0479 data: 0.0017 max mem: 19788 +Test: [12000/21770] eta: 0:07:48 time: 0.0543 data: 0.0018 max mem: 19788 +Test: [12100/21770] eta: 0:07:43 time: 0.0458 data: 0.0016 max mem: 19788 +Test: [12200/21770] eta: 0:07:38 time: 0.0443 data: 0.0014 max mem: 19788 +Test: [12300/21770] eta: 0:07:33 time: 0.0452 data: 0.0017 max mem: 19788 +Test: [12400/21770] eta: 0:07:28 time: 0.0438 data: 0.0016 max mem: 19788 +Test: [12500/21770] eta: 0:07:23 time: 0.0532 data: 0.0018 max mem: 19788 +Test: [12600/21770] eta: 0:07:18 time: 0.0509 data: 0.0019 max mem: 19788 +Test: [12700/21770] eta: 0:07:14 time: 0.0529 data: 0.0017 max mem: 19788 +Test: [12800/21770] eta: 0:07:09 time: 0.0451 data: 0.0015 max mem: 19788 +Test: [12900/21770] eta: 0:07:04 time: 0.0449 data: 0.0015 max mem: 19788 +Test: [13000/21770] eta: 0:06:59 time: 0.0450 data: 0.0016 max mem: 19788 +Test: [13100/21770] eta: 0:06:54 time: 0.0526 data: 0.0018 max mem: 19788 +Test: [13200/21770] eta: 0:06:50 time: 0.0449 data: 0.0014 max mem: 19788 +Test: [13300/21770] eta: 0:06:45 time: 0.0456 data: 0.0016 max mem: 19788 +Test: [13400/21770] eta: 0:06:40 time: 0.0444 data: 0.0014 max mem: 19788 +Test: [13500/21770] eta: 0:06:35 time: 0.0519 data: 0.0018 max mem: 19788 +Test: [13600/21770] eta: 0:06:30 time: 0.0450 data: 0.0014 max mem: 19788 +Test: [13700/21770] eta: 0:06:25 time: 0.0462 data: 0.0015 max mem: 19788 +Test: [13800/21770] eta: 0:06:20 time: 0.0444 data: 0.0016 max mem: 19788 +Test: [13900/21770] eta: 0:06:15 time: 0.0466 data: 0.0016 max mem: 19788 +Test: [14000/21770] eta: 0:06:11 time: 0.0531 data: 0.0016 max mem: 19788 +Test: [14100/21770] eta: 0:06:06 time: 0.0448 data: 0.0016 max mem: 19788 +Test: [14200/21770] eta: 0:06:01 time: 0.0443 data: 0.0014 max mem: 19788 +Test: [14300/21770] eta: 0:05:56 time: 0.0438 data: 0.0015 max mem: 19788 +Test: [14400/21770] eta: 0:05:51 time: 0.0443 data: 0.0015 max mem: 19788 +Test: [14500/21770] eta: 0:05:47 time: 0.0431 data: 0.0016 max mem: 19788 +Test: [14600/21770] eta: 0:05:42 time: 0.0440 data: 0.0015 max mem: 19788 +Test: [14700/21770] eta: 0:05:37 time: 0.0502 data: 0.0016 max mem: 19788 +Test: [14800/21770] eta: 0:05:32 time: 0.0521 data: 0.0016 max mem: 19788 +Test: [14900/21770] eta: 0:05:28 time: 0.0526 data: 0.0016 max mem: 19788 +Test: [15000/21770] eta: 0:05:23 time: 0.0446 data: 0.0014 max mem: 19788 +Test: [15100/21770] eta: 0:05:18 time: 0.0483 data: 0.0016 max mem: 19788 +Test: [15200/21770] eta: 0:05:13 time: 0.0448 data: 0.0015 max mem: 19788 +Test: [15300/21770] eta: 0:05:09 time: 0.0469 data: 0.0016 max mem: 19788 +Test: [15400/21770] eta: 0:05:04 time: 0.0487 data: 0.0016 max mem: 19788 +Test: [15500/21770] eta: 0:04:59 time: 0.0468 data: 0.0016 max mem: 19788 +Test: [15600/21770] eta: 0:04:54 time: 0.0440 data: 0.0013 max mem: 19788 +Test: [15700/21770] eta: 0:04:49 time: 0.0459 data: 0.0018 max mem: 19788 +Test: [15800/21770] eta: 0:04:44 time: 0.0535 data: 0.0019 max mem: 19788 +Test: [15900/21770] eta: 0:04:40 time: 0.0453 data: 0.0017 max mem: 19788 +Test: [16000/21770] eta: 0:04:35 time: 0.0538 data: 0.0019 max mem: 19788 +Test: [16100/21770] eta: 0:04:30 time: 0.0524 data: 0.0018 max mem: 19788 +Test: [16200/21770] eta: 0:04:25 time: 0.0486 data: 0.0016 max mem: 19788 +Test: [16300/21770] eta: 0:04:21 time: 0.0464 data: 0.0015 max mem: 19788 +Test: [16400/21770] eta: 0:04:16 time: 0.0437 data: 0.0014 max mem: 19788 +Test: [16500/21770] eta: 0:04:11 time: 0.0442 data: 0.0015 max mem: 19788 +Test: [16600/21770] eta: 0:04:06 time: 0.0526 data: 0.0017 max mem: 19788 +Test: [16700/21770] eta: 0:04:01 time: 0.0497 data: 0.0016 max mem: 19788 +Test: [16800/21770] eta: 0:03:57 time: 0.0440 data: 0.0014 max mem: 19788 +Test: [16900/21770] eta: 0:03:52 time: 0.0441 data: 0.0015 max mem: 19788 +Test: [17000/21770] eta: 0:03:47 time: 0.0483 data: 0.0016 max mem: 19788 +Test: [17100/21770] eta: 0:03:42 time: 0.0488 data: 0.0016 max mem: 19788 +Test: [17200/21770] eta: 0:03:37 time: 0.0437 data: 0.0014 max mem: 19788 +Test: [17300/21770] eta: 0:03:33 time: 0.0471 data: 0.0015 max mem: 19788 +Test: [17400/21770] eta: 0:03:28 time: 0.0551 data: 0.0017 max mem: 19788 +Test: [17500/21770] eta: 0:03:23 time: 0.0529 data: 0.0017 max mem: 19788 +Test: [17600/21770] eta: 0:03:18 time: 0.0547 data: 0.0016 max mem: 19788 +Test: [17700/21770] eta: 0:03:14 time: 0.0505 data: 0.0017 max mem: 19788 +Test: [17800/21770] eta: 0:03:09 time: 0.0436 data: 0.0015 max mem: 19788 +Test: [17900/21770] eta: 0:03:04 time: 0.0428 data: 0.0014 max mem: 19788 +Test: [18000/21770] eta: 0:02:59 time: 0.0438 data: 0.0016 max mem: 19788 +Test: [18100/21770] eta: 0:02:54 time: 0.0489 data: 0.0016 max mem: 19788 +Test: [18200/21770] eta: 0:02:50 time: 0.0426 data: 0.0014 max mem: 19788 +Test: [18300/21770] eta: 0:02:45 time: 0.0437 data: 0.0013 max mem: 19788 +Test: [18400/21770] eta: 0:02:40 time: 0.0456 data: 0.0014 max mem: 19788 +Test: [18500/21770] eta: 0:02:35 time: 0.0429 data: 0.0015 max mem: 19788 +Test: [18600/21770] eta: 0:02:30 time: 0.0450 data: 0.0016 max mem: 19788 +Test: [18700/21770] eta: 0:02:26 time: 0.0432 data: 0.0015 max mem: 19788 +Test: [18800/21770] eta: 0:02:21 time: 0.0534 data: 0.0018 max mem: 19788 +Test: [18900/21770] eta: 0:02:16 time: 0.0436 data: 0.0016 max mem: 19788 +Test: [19000/21770] eta: 0:02:11 time: 0.0436 data: 0.0016 max mem: 19788 +Test: [19100/21770] eta: 0:02:07 time: 0.0501 data: 0.0015 max mem: 19788 +Test: [19200/21770] eta: 0:02:02 time: 0.0535 data: 0.0018 max mem: 19788 +Test: [19300/21770] eta: 0:01:57 time: 0.0549 data: 0.0017 max mem: 19788 +Test: [19400/21770] eta: 0:01:52 time: 0.0480 data: 0.0015 max mem: 19788 +Test: [19500/21770] eta: 0:01:48 time: 0.0470 data: 0.0015 max mem: 19788 +Test: [19600/21770] eta: 0:01:43 time: 0.0534 data: 0.0017 max mem: 19788 +Test: [19700/21770] eta: 0:01:38 time: 0.0536 data: 0.0018 max mem: 19788 +Test: [19800/21770] eta: 0:01:33 time: 0.0522 data: 0.0018 max mem: 19788 +Test: [19900/21770] eta: 0:01:29 time: 0.0514 data: 0.0017 max mem: 19788 +Test: [20000/21770] eta: 0:01:24 time: 0.0448 data: 0.0014 max mem: 19788 +Test: [20100/21770] eta: 0:01:19 time: 0.0537 data: 0.0018 max mem: 19788 +Test: [20200/21770] eta: 0:01:14 time: 0.0529 data: 0.0018 max mem: 19788 +Test: [20300/21770] eta: 0:01:10 time: 0.0438 data: 0.0014 max mem: 19788 +Test: [20400/21770] eta: 0:01:05 time: 0.0435 data: 0.0014 max mem: 19788 +Test: [20500/21770] eta: 0:01:00 time: 0.0442 data: 0.0019 max mem: 19788 +Test: [20600/21770] eta: 0:00:55 time: 0.0487 data: 0.0018 max mem: 19788 +Test: [20700/21770] eta: 0:00:51 time: 0.0436 data: 0.0017 max mem: 19788 +Test: [20800/21770] eta: 0:00:46 time: 0.0434 data: 0.0015 max mem: 19788 +Test: [20900/21770] eta: 0:00:41 time: 0.0462 data: 0.0016 max mem: 19788 +Test: [21000/21770] eta: 0:00:36 time: 0.0447 data: 0.0014 max mem: 19788 +Test: [21100/21770] eta: 0:00:31 time: 0.0537 data: 0.0017 max mem: 19788 +Test: [21200/21770] eta: 0:00:27 time: 0.0554 data: 0.0015 max mem: 19788 +Test: [21300/21770] eta: 0:00:22 time: 0.0442 data: 0.0016 max mem: 19788 +Test: [21400/21770] eta: 0:00:17 time: 0.0493 data: 0.0017 max mem: 19788 +Test: [21500/21770] eta: 0:00:12 time: 0.0454 data: 0.0017 max mem: 19788 +Test: [21600/21770] eta: 0:00:08 time: 0.0537 data: 0.0017 max mem: 19788 +Test: [21700/21770] eta: 0:00:03 time: 0.0453 data: 0.0015 max mem: 19788 +Test: Total time: 0:17:19 +Final results: +Mean IoU is 60.45 + + precision@0.5 = 67.04 + precision@0.6 = 60.76 + precision@0.7 = 53.19 + precision@0.8 = 42.30 + precision@0.9 = 19.63 + overall IoU = 62.39 + mean IoU = 60.45 + +Mean accuracy for one-to-zero sample is 77.09 + +Average object IoU 0.6044817664858457 +Overall IoU 62.39252471923828 +Better epoch: 4 + +Epoch: [5] [ 0/2138] eta: 2:45:18 lr: 4.433758444635489e-05 loss: 0.1507 (0.1507) time: 4.6394 data: 1.4403 max mem: 19788 +Epoch: [5] [ 10/2138] eta: 1:49:28 lr: 4.4332251742102765e-05 loss: 0.0676 (0.0744) time: 3.0869 data: 0.1331 max mem: 19788 +Epoch: [5] [ 20/2138] eta: 1:46:52 lr: 4.432691896657543e-05 loss: 0.0579 (0.0723) time: 2.9468 data: 0.0026 max mem: 19788 +Epoch: [5] [ 30/2138] eta: 1:45:15 lr: 4.432158611976241e-05 loss: 0.0675 (0.0710) time: 2.9462 data: 0.0026 max mem: 19788 +Epoch: [5] [ 40/2138] eta: 1:44:06 lr: 4.4316253201653214e-05 loss: 0.0642 (0.0718) time: 2.9247 data: 0.0023 max mem: 19788 +Epoch: [5] [ 50/2138] eta: 1:43:43 lr: 4.431092021223736e-05 loss: 0.0613 (0.0697) time: 2.9570 data: 0.0023 max mem: 19788 +Epoch: [5] [ 60/2138] eta: 1:42:54 lr: 4.4305587151504354e-05 loss: 0.0578 (0.0698) time: 2.9592 data: 0.0024 max mem: 19788 +Epoch: [5] [ 70/2138] eta: 1:42:11 lr: 4.43002540194437e-05 loss: 0.0593 (0.0689) time: 2.9249 data: 0.0024 max mem: 19788 +Epoch: [5] [ 80/2138] eta: 1:41:29 lr: 4.429492081604492e-05 loss: 0.0609 (0.0684) time: 2.9208 data: 0.0023 max mem: 19788 +Epoch: [5] [ 90/2138] eta: 1:40:50 lr: 4.42895875412975e-05 loss: 0.0623 (0.0685) time: 2.9159 data: 0.0022 max mem: 19788 +Epoch: [5] [ 100/2138] eta: 1:40:29 lr: 4.428425419519095e-05 loss: 0.0673 (0.0691) time: 2.9583 data: 0.0022 max mem: 19788 +Epoch: [5] [ 110/2138] eta: 1:39:53 lr: 4.4278920777714754e-05 loss: 0.0663 (0.0691) time: 2.9618 data: 0.0023 max mem: 19788 +Epoch: [5] [ 120/2138] eta: 1:39:17 lr: 4.4273587288858415e-05 loss: 0.0649 (0.0684) time: 2.9203 data: 0.0024 max mem: 19788 +Epoch: [5] [ 130/2138] eta: 1:38:48 lr: 4.4268253728611415e-05 loss: 0.0658 (0.0679) time: 2.9356 data: 0.0023 max mem: 19788 +Epoch: [5] [ 140/2138] eta: 1:38:33 lr: 4.426292009696325e-05 loss: 0.0661 (0.0682) time: 3.0032 data: 0.0022 max mem: 19788 +Epoch: [5] [ 150/2138] eta: 1:38:17 lr: 4.42575863939034e-05 loss: 0.0670 (0.0685) time: 3.0581 data: 0.0024 max mem: 19788 +Epoch: [5] [ 160/2138] eta: 1:37:43 lr: 4.425225261942134e-05 loss: 0.0549 (0.0680) time: 2.9973 data: 0.0026 max mem: 19788 +Epoch: [5] [ 170/2138] eta: 1:37:11 lr: 4.424691877350656e-05 loss: 0.0594 (0.0678) time: 2.9382 data: 0.0028 max mem: 19788 +Epoch: [5] [ 180/2138] eta: 1:36:40 lr: 4.424158485614853e-05 loss: 0.0606 (0.0677) time: 2.9460 data: 0.0027 max mem: 19788 +Epoch: [5] [ 190/2138] eta: 1:36:29 lr: 4.423625086733672e-05 loss: 0.0601 (0.0670) time: 3.0453 data: 0.0025 max mem: 19788 +Epoch: [5] [ 200/2138] eta: 1:35:53 lr: 4.4230916807060596e-05 loss: 0.0519 (0.0663) time: 3.0274 data: 0.0025 max mem: 19788 +Epoch: [5] [ 210/2138] eta: 1:35:18 lr: 4.422558267530963e-05 loss: 0.0569 (0.0667) time: 2.9108 data: 0.0027 max mem: 19788 +Epoch: [5] [ 220/2138] eta: 1:34:44 lr: 4.422024847207329e-05 loss: 0.0569 (0.0665) time: 2.9160 data: 0.0027 max mem: 19788 +Epoch: [5] [ 230/2138] eta: 1:34:28 lr: 4.421491419734103e-05 loss: 0.0635 (0.0673) time: 3.0238 data: 0.0025 max mem: 19788 +Epoch: [5] [ 240/2138] eta: 1:33:58 lr: 4.420957985110231e-05 loss: 0.0635 (0.0671) time: 3.0460 data: 0.0022 max mem: 19788 +Epoch: [5] [ 250/2138] eta: 1:33:22 lr: 4.420424543334658e-05 loss: 0.0604 (0.0667) time: 2.9287 data: 0.0022 max mem: 19788 +Epoch: [5] [ 260/2138] eta: 1:33:13 lr: 4.41989109440633e-05 loss: 0.0561 (0.0665) time: 3.0721 data: 0.0023 max mem: 19788 +Epoch: [5] [ 270/2138] eta: 1:32:39 lr: 4.419357638324191e-05 loss: 0.0601 (0.0671) time: 3.0806 data: 0.0022 max mem: 19788 +Epoch: [5] [ 280/2138] eta: 1:32:07 lr: 4.4188241750871855e-05 loss: 0.0648 (0.0671) time: 2.9295 data: 0.0025 max mem: 19788 +Epoch: [5] [ 290/2138] eta: 1:31:43 lr: 4.418290704694259e-05 loss: 0.0693 (0.0676) time: 3.0034 data: 0.0027 max mem: 19788 +Epoch: [5] [ 300/2138] eta: 1:31:25 lr: 4.417757227144354e-05 loss: 0.0722 (0.0677) time: 3.1175 data: 0.0026 max mem: 19788 +Epoch: [5] [ 310/2138] eta: 1:30:53 lr: 4.417223742436415e-05 loss: 0.0498 (0.0675) time: 3.0664 data: 0.0026 max mem: 19788 +Epoch: [5] [ 320/2138] eta: 1:30:22 lr: 4.4166902505693846e-05 loss: 0.0492 (0.0672) time: 2.9564 data: 0.0028 max mem: 19788 +Epoch: [5] [ 330/2138] eta: 1:29:51 lr: 4.416156751542207e-05 loss: 0.0650 (0.0673) time: 2.9552 data: 0.0031 max mem: 19788 +Epoch: [5] [ 340/2138] eta: 1:29:20 lr: 4.4156232453538245e-05 loss: 0.0650 (0.0672) time: 2.9574 data: 0.0029 max mem: 19788 +Epoch: [5] [ 350/2138] eta: 1:28:47 lr: 4.41508973200318e-05 loss: 0.0574 (0.0669) time: 2.9376 data: 0.0027 max mem: 19788 +Epoch: [5] [ 360/2138] eta: 1:28:13 lr: 4.414556211489214e-05 loss: 0.0615 (0.0670) time: 2.9099 data: 0.0029 max mem: 19788 +Epoch: [5] [ 370/2138] eta: 1:27:50 lr: 4.414022683810871e-05 loss: 0.0656 (0.0670) time: 3.0110 data: 0.0027 max mem: 19788 +Epoch: [5] [ 380/2138] eta: 1:27:18 lr: 4.413489148967089e-05 loss: 0.0581 (0.0669) time: 3.0218 data: 0.0023 max mem: 19788 +Epoch: [5] [ 390/2138] eta: 1:26:48 lr: 4.4129556069568135e-05 loss: 0.0465 (0.0664) time: 2.9564 data: 0.0022 max mem: 19788 +Epoch: [5] [ 400/2138] eta: 1:26:17 lr: 4.4124220577789825e-05 loss: 0.0518 (0.0666) time: 2.9650 data: 0.0022 max mem: 19788 +Epoch: [5] [ 410/2138] eta: 1:25:47 lr: 4.411888501432538e-05 loss: 0.0557 (0.0666) time: 2.9625 data: 0.0025 max mem: 19788 +Epoch: [5] [ 420/2138] eta: 1:25:15 lr: 4.411354937916419e-05 loss: 0.0557 (0.0665) time: 2.9526 data: 0.0029 max mem: 19788 +Epoch: [5] [ 430/2138] eta: 1:24:45 lr: 4.4108213672295676e-05 loss: 0.0647 (0.0665) time: 2.9505 data: 0.0026 max mem: 19788 +Epoch: [5] [ 440/2138] eta: 1:24:13 lr: 4.4102877893709224e-05 loss: 0.0643 (0.0666) time: 2.9399 data: 0.0023 max mem: 19788 +Epoch: [5] [ 450/2138] eta: 1:23:41 lr: 4.4097542043394234e-05 loss: 0.0583 (0.0664) time: 2.9106 data: 0.0026 max mem: 19788 +Epoch: [5] [ 460/2138] eta: 1:23:08 lr: 4.409220612134009e-05 loss: 0.0572 (0.0663) time: 2.9023 data: 0.0027 max mem: 19788 +Epoch: [5] [ 470/2138] eta: 1:22:39 lr: 4.408687012753618e-05 loss: 0.0619 (0.0663) time: 2.9390 data: 0.0027 max mem: 19788 +Epoch: [5] [ 480/2138] eta: 1:22:11 lr: 4.40815340619719e-05 loss: 0.0682 (0.0665) time: 3.0052 data: 0.0027 max mem: 19788 +Epoch: [5] [ 490/2138] eta: 1:21:43 lr: 4.407619792463664e-05 loss: 0.0707 (0.0671) time: 3.0221 data: 0.0027 max mem: 19788 +Epoch: [5] [ 500/2138] eta: 1:21:12 lr: 4.407086171551975e-05 loss: 0.0694 (0.0671) time: 2.9811 data: 0.0028 max mem: 19788 +Epoch: [5] [ 510/2138] eta: 1:20:41 lr: 4.4065525434610635e-05 loss: 0.0620 (0.0670) time: 2.9434 data: 0.0028 max mem: 19788 +Epoch: [5] [ 520/2138] eta: 1:20:11 lr: 4.406018908189865e-05 loss: 0.0723 (0.0671) time: 2.9589 data: 0.0024 max mem: 19788 +Epoch: [5] [ 530/2138] eta: 1:19:42 lr: 4.405485265737318e-05 loss: 0.0628 (0.0669) time: 2.9833 data: 0.0022 max mem: 19788 +Epoch: [5] [ 540/2138] eta: 1:19:11 lr: 4.4049516161023595e-05 loss: 0.0486 (0.0666) time: 2.9572 data: 0.0022 max mem: 19788 +Epoch: [5] [ 550/2138] eta: 1:18:41 lr: 4.4044179592839244e-05 loss: 0.0541 (0.0670) time: 2.9516 data: 0.0022 max mem: 19788 +Epoch: [5] [ 560/2138] eta: 1:18:10 lr: 4.40388429528095e-05 loss: 0.0624 (0.0669) time: 2.9471 data: 0.0022 max mem: 19788 +Epoch: [5] [ 570/2138] eta: 1:17:38 lr: 4.4033506240923723e-05 loss: 0.0503 (0.0667) time: 2.9068 data: 0.0024 max mem: 19788 +Epoch: [5] [ 580/2138] eta: 1:17:07 lr: 4.402816945717126e-05 loss: 0.0583 (0.0668) time: 2.9081 data: 0.0025 max mem: 19788 +Epoch: [5] [ 590/2138] eta: 1:16:36 lr: 4.4022832601541477e-05 loss: 0.0629 (0.0669) time: 2.9104 data: 0.0025 max mem: 19788 +Epoch: [5] [ 600/2138] eta: 1:16:05 lr: 4.4017495674023706e-05 loss: 0.0620 (0.0668) time: 2.9220 data: 0.0024 max mem: 19788 +Epoch: [5] [ 610/2138] eta: 1:15:34 lr: 4.4012158674607306e-05 loss: 0.0611 (0.0667) time: 2.9292 data: 0.0025 max mem: 19788 +Epoch: [5] [ 620/2138] eta: 1:15:06 lr: 4.400682160328163e-05 loss: 0.0605 (0.0668) time: 2.9697 data: 0.0025 max mem: 19788 +Epoch: [5] [ 630/2138] eta: 1:14:36 lr: 4.400148446003599e-05 loss: 0.0597 (0.0666) time: 2.9857 data: 0.0027 max mem: 19788 +Epoch: [5] [ 640/2138] eta: 1:14:08 lr: 4.3996147244859755e-05 loss: 0.0571 (0.0667) time: 3.0102 data: 0.0027 max mem: 19788 +Epoch: [5] [ 650/2138] eta: 1:13:39 lr: 4.399080995774224e-05 loss: 0.0623 (0.0667) time: 3.0262 data: 0.0024 max mem: 19788 +Epoch: [5] [ 660/2138] eta: 1:13:11 lr: 4.398547259867278e-05 loss: 0.0600 (0.0668) time: 3.0074 data: 0.0026 max mem: 19788 +Epoch: [5] [ 670/2138] eta: 1:12:43 lr: 4.3980135167640714e-05 loss: 0.0575 (0.0666) time: 3.0390 data: 0.0028 max mem: 19788 +Epoch: [5] [ 680/2138] eta: 1:12:13 lr: 4.3974797664635356e-05 loss: 0.0533 (0.0665) time: 3.0107 data: 0.0027 max mem: 19788 +Epoch: [5] [ 690/2138] eta: 1:11:42 lr: 4.3969460089646034e-05 loss: 0.0497 (0.0666) time: 2.9351 data: 0.0026 max mem: 19788 +Epoch: [5] [ 700/2138] eta: 1:11:12 lr: 4.396412244266207e-05 loss: 0.0613 (0.0665) time: 2.9268 data: 0.0026 max mem: 19788 +Epoch: [5] [ 710/2138] eta: 1:10:41 lr: 4.3958784723672776e-05 loss: 0.0704 (0.0667) time: 2.9418 data: 0.0027 max mem: 19788 +Epoch: [5] [ 720/2138] eta: 1:10:10 lr: 4.395344693266746e-05 loss: 0.0640 (0.0665) time: 2.9160 data: 0.0028 max mem: 19788 +Epoch: [5] [ 730/2138] eta: 1:09:41 lr: 4.394810906963545e-05 loss: 0.0581 (0.0665) time: 2.9499 data: 0.0026 max mem: 19788 +Epoch: [5] [ 740/2138] eta: 1:09:11 lr: 4.394277113456604e-05 loss: 0.0617 (0.0665) time: 2.9921 data: 0.0024 max mem: 19788 +Epoch: [5] [ 750/2138] eta: 1:08:40 lr: 4.3937433127448535e-05 loss: 0.0562 (0.0664) time: 2.9400 data: 0.0023 max mem: 19788 +Epoch: [5] [ 760/2138] eta: 1:08:11 lr: 4.3932095048272244e-05 loss: 0.0562 (0.0664) time: 2.9514 data: 0.0022 max mem: 19788 +Epoch: [5] [ 770/2138] eta: 1:07:41 lr: 4.392675689702646e-05 loss: 0.0602 (0.0663) time: 2.9635 data: 0.0022 max mem: 19788 +Epoch: [5] [ 780/2138] eta: 1:07:10 lr: 4.3921418673700474e-05 loss: 0.0551 (0.0662) time: 2.9201 data: 0.0023 max mem: 19788 +Epoch: [5] [ 790/2138] eta: 1:06:41 lr: 4.391608037828358e-05 loss: 0.0563 (0.0661) time: 2.9496 data: 0.0024 max mem: 19788 +Epoch: [5] [ 800/2138] eta: 1:06:11 lr: 4.391074201076508e-05 loss: 0.0611 (0.0663) time: 2.9741 data: 0.0025 max mem: 19788 +Epoch: [5] [ 810/2138] eta: 1:05:41 lr: 4.390540357113425e-05 loss: 0.0644 (0.0662) time: 2.9607 data: 0.0024 max mem: 19788 +Epoch: [5] [ 820/2138] eta: 1:05:11 lr: 4.390006505938037e-05 loss: 0.0607 (0.0661) time: 2.9433 data: 0.0023 max mem: 19788 +Epoch: [5] [ 830/2138] eta: 1:04:40 lr: 4.389472647549272e-05 loss: 0.0617 (0.0661) time: 2.9263 data: 0.0022 max mem: 19788 +Epoch: [5] [ 840/2138] eta: 1:04:10 lr: 4.388938781946059e-05 loss: 0.0580 (0.0660) time: 2.9188 data: 0.0022 max mem: 19788 +Epoch: [5] [ 850/2138] eta: 1:03:40 lr: 4.388404909127325e-05 loss: 0.0572 (0.0660) time: 2.9237 data: 0.0022 max mem: 19788 +Epoch: [5] [ 860/2138] eta: 1:03:10 lr: 4.387871029091996e-05 loss: 0.0564 (0.0659) time: 2.9519 data: 0.0025 max mem: 19788 +Epoch: [5] [ 870/2138] eta: 1:02:41 lr: 4.387337141838999e-05 loss: 0.0568 (0.0659) time: 2.9936 data: 0.0027 max mem: 19788 +Epoch: [5] [ 880/2138] eta: 1:02:12 lr: 4.386803247367262e-05 loss: 0.0654 (0.0660) time: 2.9991 data: 0.0028 max mem: 19788 +Epoch: [5] [ 890/2138] eta: 1:01:41 lr: 4.3862693456757106e-05 loss: 0.0706 (0.0661) time: 2.9364 data: 0.0024 max mem: 19788 +Epoch: [5] [ 900/2138] eta: 1:01:10 lr: 4.3857354367632694e-05 loss: 0.0593 (0.0660) time: 2.8831 data: 0.0021 max mem: 19788 +Epoch: [5] [ 910/2138] eta: 1:00:41 lr: 4.3852015206288654e-05 loss: 0.0544 (0.0660) time: 2.9216 data: 0.0021 max mem: 19788 +Epoch: [5] [ 920/2138] eta: 1:00:13 lr: 4.384667597271423e-05 loss: 0.0544 (0.0658) time: 3.0263 data: 0.0023 max mem: 19788 +Epoch: [5] [ 930/2138] eta: 0:59:44 lr: 4.3841336666898674e-05 loss: 0.0548 (0.0660) time: 3.0534 data: 0.0024 max mem: 19788 +Epoch: [5] [ 940/2138] eta: 0:59:14 lr: 4.383599728883124e-05 loss: 0.0605 (0.0659) time: 2.9974 data: 0.0024 max mem: 19788 +Epoch: [5] [ 950/2138] eta: 0:58:45 lr: 4.383065783850116e-05 loss: 0.0536 (0.0658) time: 2.9914 data: 0.0024 max mem: 19788 +Epoch: [5] [ 960/2138] eta: 0:58:17 lr: 4.382531831589768e-05 loss: 0.0551 (0.0657) time: 3.0804 data: 0.0024 max mem: 19788 +Epoch: [5] [ 970/2138] eta: 0:57:49 lr: 4.381997872101005e-05 loss: 0.0566 (0.0659) time: 3.0966 data: 0.0024 max mem: 19788 +Epoch: [5] [ 980/2138] eta: 0:57:19 lr: 4.381463905382748e-05 loss: 0.0589 (0.0659) time: 2.9961 data: 0.0025 max mem: 19788 +Epoch: [5] [ 990/2138] eta: 0:56:49 lr: 4.380929931433922e-05 loss: 0.0589 (0.0658) time: 2.9532 data: 0.0027 max mem: 19788 +Epoch: [5] [1000/2138] eta: 0:56:19 lr: 4.380395950253449e-05 loss: 0.0518 (0.0657) time: 2.9352 data: 0.0030 max mem: 19788 +Epoch: [5] [1010/2138] eta: 0:55:51 lr: 4.3798619618402515e-05 loss: 0.0579 (0.0658) time: 3.0272 data: 0.0030 max mem: 19788 +Epoch: [5] [1020/2138] eta: 0:55:23 lr: 4.379327966193252e-05 loss: 0.0621 (0.0658) time: 3.1419 data: 0.0028 max mem: 19788 +Epoch: [5] [1030/2138] eta: 0:54:53 lr: 4.378793963311373e-05 loss: 0.0578 (0.0657) time: 3.0309 data: 0.0024 max mem: 19788 +Epoch: [5] [1040/2138] eta: 0:54:24 lr: 4.378259953193535e-05 loss: 0.0536 (0.0657) time: 3.0130 data: 0.0026 max mem: 19788 +Epoch: [5] [1050/2138] eta: 0:53:54 lr: 4.37772593583866e-05 loss: 0.0507 (0.0656) time: 3.0155 data: 0.0028 max mem: 19788 +Epoch: [5] [1060/2138] eta: 0:53:24 lr: 4.377191911245668e-05 loss: 0.0575 (0.0657) time: 2.9190 data: 0.0026 max mem: 19788 +Epoch: [5] [1070/2138] eta: 0:52:54 lr: 4.376657879413481e-05 loss: 0.0620 (0.0657) time: 2.9211 data: 0.0025 max mem: 19788 +Epoch: [5] [1080/2138] eta: 0:52:23 lr: 4.3761238403410196e-05 loss: 0.0631 (0.0657) time: 2.9201 data: 0.0025 max mem: 19788 +Epoch: [5] [1090/2138] eta: 0:51:53 lr: 4.375589794027203e-05 loss: 0.0633 (0.0659) time: 2.9220 data: 0.0027 max mem: 19788 +Epoch: [5] [1100/2138] eta: 0:51:24 lr: 4.37505574047095e-05 loss: 0.0633 (0.0660) time: 2.9867 data: 0.0029 max mem: 19788 +Epoch: [5] [1110/2138] eta: 0:50:56 lr: 4.3745216796711824e-05 loss: 0.0662 (0.0659) time: 3.0797 data: 0.0029 max mem: 19788 +Epoch: [5] [1120/2138] eta: 0:50:25 lr: 4.373987611626817e-05 loss: 0.0632 (0.0659) time: 3.0147 data: 0.0025 max mem: 19788 +Epoch: [5] [1130/2138] eta: 0:49:56 lr: 4.3734535363367744e-05 loss: 0.0594 (0.0658) time: 2.9371 data: 0.0023 max mem: 19788 +Epoch: [5] [1140/2138] eta: 0:49:26 lr: 4.3729194537999724e-05 loss: 0.0580 (0.0658) time: 2.9473 data: 0.0026 max mem: 19788 +Epoch: [5] [1150/2138] eta: 0:48:56 lr: 4.3723853640153296e-05 loss: 0.0564 (0.0657) time: 2.9871 data: 0.0027 max mem: 19788 +Epoch: [5] [1160/2138] eta: 0:48:27 lr: 4.371851266981763e-05 loss: 0.0528 (0.0656) time: 3.0063 data: 0.0026 max mem: 19788 +Epoch: [5] [1170/2138] eta: 0:47:58 lr: 4.371317162698191e-05 loss: 0.0483 (0.0655) time: 3.0093 data: 0.0026 max mem: 19788 +Epoch: [5] [1180/2138] eta: 0:47:27 lr: 4.370783051163531e-05 loss: 0.0502 (0.0655) time: 2.9799 data: 0.0024 max mem: 19788 +Epoch: [5] [1190/2138] eta: 0:46:57 lr: 4.3702489323766994e-05 loss: 0.0545 (0.0654) time: 2.9183 data: 0.0024 max mem: 19788 +Epoch: [5] [1200/2138] eta: 0:46:28 lr: 4.369714806336614e-05 loss: 0.0536 (0.0653) time: 2.9477 data: 0.0028 max mem: 19788 +Epoch: [5] [1210/2138] eta: 0:45:59 lr: 4.369180673042189e-05 loss: 0.0606 (0.0653) time: 3.0560 data: 0.0026 max mem: 19788 +Epoch: [5] [1220/2138] eta: 0:45:29 lr: 4.368646532492343e-05 loss: 0.0606 (0.0652) time: 3.0181 data: 0.0024 max mem: 19788 +Epoch: [5] [1230/2138] eta: 0:45:00 lr: 4.36811238468599e-05 loss: 0.0502 (0.0652) time: 2.9713 data: 0.0025 max mem: 19788 +Epoch: [5] [1240/2138] eta: 0:44:30 lr: 4.367578229622046e-05 loss: 0.0502 (0.0651) time: 3.0389 data: 0.0023 max mem: 19788 +Epoch: [5] [1250/2138] eta: 0:44:00 lr: 4.3670440672994264e-05 loss: 0.0553 (0.0651) time: 3.0014 data: 0.0024 max mem: 19788 +Epoch: [5] [1260/2138] eta: 0:43:30 lr: 4.366509897717046e-05 loss: 0.0614 (0.0651) time: 2.9471 data: 0.0025 max mem: 19788 +Epoch: [5] [1270/2138] eta: 0:43:01 lr: 4.365975720873819e-05 loss: 0.0551 (0.0650) time: 2.9439 data: 0.0025 max mem: 19788 +Epoch: [5] [1280/2138] eta: 0:42:31 lr: 4.3654415367686595e-05 loss: 0.0680 (0.0652) time: 2.9470 data: 0.0026 max mem: 19788 +Epoch: [5] [1290/2138] eta: 0:42:01 lr: 4.3649073454004816e-05 loss: 0.0680 (0.0652) time: 2.9659 data: 0.0025 max mem: 19788 +Epoch: [5] [1300/2138] eta: 0:41:31 lr: 4.3643731467682e-05 loss: 0.0598 (0.0651) time: 2.9873 data: 0.0023 max mem: 19788 +Epoch: [5] [1310/2138] eta: 0:41:01 lr: 4.363838940870725e-05 loss: 0.0605 (0.0651) time: 2.9572 data: 0.0023 max mem: 19788 +Epoch: [5] [1320/2138] eta: 0:40:32 lr: 4.3633047277069724e-05 loss: 0.0598 (0.0651) time: 2.9999 data: 0.0022 max mem: 19788 +Epoch: [5] [1330/2138] eta: 0:40:03 lr: 4.362770507275854e-05 loss: 0.0568 (0.0651) time: 3.0482 data: 0.0025 max mem: 19788 +Epoch: [5] [1340/2138] eta: 0:39:33 lr: 4.362236279576282e-05 loss: 0.0616 (0.0651) time: 2.9649 data: 0.0027 max mem: 19788 +Epoch: [5] [1350/2138] eta: 0:39:03 lr: 4.361702044607169e-05 loss: 0.0690 (0.0652) time: 2.9159 data: 0.0027 max mem: 19788 +Epoch: [5] [1360/2138] eta: 0:38:33 lr: 4.361167802367426e-05 loss: 0.0751 (0.0653) time: 2.9305 data: 0.0026 max mem: 19788 +Epoch: [5] [1370/2138] eta: 0:38:03 lr: 4.360633552855964e-05 loss: 0.0767 (0.0654) time: 2.9461 data: 0.0023 max mem: 19788 +Epoch: [5] [1380/2138] eta: 0:37:33 lr: 4.360099296071695e-05 loss: 0.0644 (0.0654) time: 2.9698 data: 0.0023 max mem: 19788 +Epoch: [5] [1390/2138] eta: 0:37:03 lr: 4.35956503201353e-05 loss: 0.0559 (0.0654) time: 2.9448 data: 0.0026 max mem: 19788 +Epoch: [5] [1400/2138] eta: 0:36:33 lr: 4.359030760680378e-05 loss: 0.0494 (0.0653) time: 2.9470 data: 0.0027 max mem: 19788 +Epoch: [5] [1410/2138] eta: 0:36:04 lr: 4.3584964820711505e-05 loss: 0.0467 (0.0652) time: 3.0025 data: 0.0025 max mem: 19788 +Epoch: [5] [1420/2138] eta: 0:35:34 lr: 4.3579621961847575e-05 loss: 0.0490 (0.0652) time: 3.0222 data: 0.0024 max mem: 19788 +Epoch: [5] [1430/2138] eta: 0:35:05 lr: 4.3574279030201085e-05 loss: 0.0513 (0.0652) time: 3.0223 data: 0.0025 max mem: 19788 +Epoch: [5] [1440/2138] eta: 0:34:35 lr: 4.356893602576111e-05 loss: 0.0513 (0.0651) time: 2.9764 data: 0.0028 max mem: 19788 +Epoch: [5] [1450/2138] eta: 0:34:05 lr: 4.356359294851676e-05 loss: 0.0501 (0.0651) time: 2.9218 data: 0.0032 max mem: 19788 +Epoch: [5] [1460/2138] eta: 0:33:35 lr: 4.3558249798457105e-05 loss: 0.0618 (0.0650) time: 2.9534 data: 0.0029 max mem: 19788 +Epoch: [5] [1470/2138] eta: 0:33:06 lr: 4.355290657557125e-05 loss: 0.0515 (0.0650) time: 2.9785 data: 0.0027 max mem: 19788 +Epoch: [5] [1480/2138] eta: 0:32:37 lr: 4.354756327984825e-05 loss: 0.0472 (0.0650) time: 3.0497 data: 0.0026 max mem: 19788 +Epoch: [5] [1490/2138] eta: 0:32:07 lr: 4.3542219911277194e-05 loss: 0.0616 (0.0651) time: 3.0662 data: 0.0023 max mem: 19788 +Epoch: [5] [1500/2138] eta: 0:31:37 lr: 4.353687646984716e-05 loss: 0.0627 (0.0651) time: 2.9880 data: 0.0026 max mem: 19788 +Epoch: [5] [1510/2138] eta: 0:31:07 lr: 4.353153295554721e-05 loss: 0.0492 (0.0650) time: 2.9585 data: 0.0027 max mem: 19788 +Epoch: [5] [1520/2138] eta: 0:30:38 lr: 4.35261893683664e-05 loss: 0.0486 (0.0650) time: 3.0199 data: 0.0024 max mem: 19788 +Epoch: [5] [1530/2138] eta: 0:30:08 lr: 4.352084570829383e-05 loss: 0.0567 (0.0649) time: 3.0340 data: 0.0024 max mem: 19788 +Epoch: [5] [1540/2138] eta: 0:29:38 lr: 4.351550197531852e-05 loss: 0.0568 (0.0649) time: 2.9379 data: 0.0024 max mem: 19788 +Epoch: [5] [1550/2138] eta: 0:29:09 lr: 4.351015816942957e-05 loss: 0.0568 (0.0649) time: 2.9444 data: 0.0024 max mem: 19788 +Epoch: [5] [1560/2138] eta: 0:28:39 lr: 4.350481429061599e-05 loss: 0.0611 (0.0649) time: 2.9564 data: 0.0026 max mem: 19788 +Epoch: [5] [1570/2138] eta: 0:28:09 lr: 4.3499470338866864e-05 loss: 0.0594 (0.0649) time: 2.9714 data: 0.0027 max mem: 19788 +Epoch: [5] [1580/2138] eta: 0:27:39 lr: 4.349412631417123e-05 loss: 0.0558 (0.0648) time: 2.9613 data: 0.0024 max mem: 19788 +Epoch: [5] [1590/2138] eta: 0:27:09 lr: 4.348878221651813e-05 loss: 0.0568 (0.0648) time: 2.9093 data: 0.0022 max mem: 19788 +Epoch: [5] [1600/2138] eta: 0:26:39 lr: 4.3483438045896604e-05 loss: 0.0602 (0.0648) time: 2.9616 data: 0.0022 max mem: 19788 +Epoch: [5] [1610/2138] eta: 0:26:09 lr: 4.34780938022957e-05 loss: 0.0590 (0.0648) time: 2.9210 data: 0.0023 max mem: 19788 +Epoch: [5] [1620/2138] eta: 0:25:39 lr: 4.3472749485704456e-05 loss: 0.0555 (0.0648) time: 2.8294 data: 0.0022 max mem: 19788 +Epoch: [5] [1630/2138] eta: 0:25:09 lr: 4.34674050961119e-05 loss: 0.0587 (0.0647) time: 2.8345 data: 0.0025 max mem: 19788 +Epoch: [5] [1640/2138] eta: 0:24:39 lr: 4.346206063350705e-05 loss: 0.0584 (0.0647) time: 2.8345 data: 0.0026 max mem: 19788 +Epoch: [5] [1650/2138] eta: 0:24:09 lr: 4.345671609787895e-05 loss: 0.0551 (0.0647) time: 2.8351 data: 0.0025 max mem: 19788 +Epoch: [5] [1660/2138] eta: 0:23:39 lr: 4.345137148921662e-05 loss: 0.0596 (0.0647) time: 2.8253 data: 0.0022 max mem: 19788 +Epoch: [5] [1670/2138] eta: 0:23:08 lr: 4.344602680750907e-05 loss: 0.0593 (0.0646) time: 2.8037 data: 0.0022 max mem: 19788 +Epoch: [5] [1680/2138] eta: 0:22:38 lr: 4.344068205274533e-05 loss: 0.0559 (0.0646) time: 2.7951 data: 0.0025 max mem: 19788 +Epoch: [5] [1690/2138] eta: 0:22:08 lr: 4.343533722491441e-05 loss: 0.0552 (0.0646) time: 2.7947 data: 0.0025 max mem: 19788 +Epoch: [5] [1700/2138] eta: 0:21:38 lr: 4.3429992324005316e-05 loss: 0.0512 (0.0644) time: 2.7951 data: 0.0025 max mem: 19788 +Epoch: [5] [1710/2138] eta: 0:21:08 lr: 4.3424647350007044e-05 loss: 0.0512 (0.0645) time: 2.7936 data: 0.0025 max mem: 19788 +Epoch: [5] [1720/2138] eta: 0:20:38 lr: 4.341930230290863e-05 loss: 0.0544 (0.0645) time: 2.7936 data: 0.0026 max mem: 19788 +Epoch: [5] [1730/2138] eta: 0:20:08 lr: 4.341395718269905e-05 loss: 0.0505 (0.0644) time: 2.7971 data: 0.0027 max mem: 19788 +Epoch: [5] [1740/2138] eta: 0:19:38 lr: 4.340861198936731e-05 loss: 0.0505 (0.0644) time: 2.7928 data: 0.0025 max mem: 19788 +Epoch: [5] [1750/2138] eta: 0:19:08 lr: 4.340326672290241e-05 loss: 0.0486 (0.0643) time: 2.7878 data: 0.0023 max mem: 19788 +Epoch: [5] [1760/2138] eta: 0:18:38 lr: 4.339792138329333e-05 loss: 0.0590 (0.0643) time: 2.7904 data: 0.0024 max mem: 19788 +Epoch: [5] [1770/2138] eta: 0:18:08 lr: 4.339257597052907e-05 loss: 0.0590 (0.0643) time: 2.7909 data: 0.0027 max mem: 19788 +Epoch: [5] [1780/2138] eta: 0:17:38 lr: 4.3387230484598614e-05 loss: 0.0526 (0.0643) time: 2.7953 data: 0.0028 max mem: 19788 +Epoch: [5] [1790/2138] eta: 0:17:08 lr: 4.338188492549093e-05 loss: 0.0558 (0.0642) time: 2.7895 data: 0.0024 max mem: 19788 +Epoch: [5] [1800/2138] eta: 0:16:38 lr: 4.3376539293195014e-05 loss: 0.0686 (0.0644) time: 2.7799 data: 0.0022 max mem: 19788 +Epoch: [5] [1810/2138] eta: 0:16:08 lr: 4.3371193587699834e-05 loss: 0.0583 (0.0643) time: 2.7811 data: 0.0023 max mem: 19788 +Epoch: [5] [1820/2138] eta: 0:15:39 lr: 4.336584780899437e-05 loss: 0.0492 (0.0643) time: 2.7832 data: 0.0023 max mem: 19788 +Epoch: [5] [1830/2138] eta: 0:15:09 lr: 4.336050195706758e-05 loss: 0.0492 (0.0642) time: 2.7796 data: 0.0023 max mem: 19788 +Epoch: [5] [1840/2138] eta: 0:14:39 lr: 4.335515603190844e-05 loss: 0.0494 (0.0643) time: 2.7814 data: 0.0022 max mem: 19788 +Epoch: [5] [1850/2138] eta: 0:14:09 lr: 4.33498100335059e-05 loss: 0.0540 (0.0642) time: 2.7926 data: 0.0023 max mem: 19788 +Epoch: [5] [1860/2138] eta: 0:13:39 lr: 4.3344463961848945e-05 loss: 0.0550 (0.0642) time: 2.7926 data: 0.0026 max mem: 19788 +Epoch: [5] [1870/2138] eta: 0:13:10 lr: 4.333911781692651e-05 loss: 0.0549 (0.0642) time: 2.7862 data: 0.0028 max mem: 19788 +Epoch: [5] [1880/2138] eta: 0:12:40 lr: 4.333377159872756e-05 loss: 0.0547 (0.0643) time: 2.7816 data: 0.0027 max mem: 19788 +Epoch: [5] [1890/2138] eta: 0:12:10 lr: 4.3328425307241034e-05 loss: 0.0547 (0.0643) time: 2.7782 data: 0.0022 max mem: 19788 +Epoch: [5] [1900/2138] eta: 0:11:41 lr: 4.332307894245589e-05 loss: 0.0615 (0.0643) time: 2.7789 data: 0.0022 max mem: 19788 +Epoch: [5] [1910/2138] eta: 0:11:11 lr: 4.331773250436107e-05 loss: 0.0646 (0.0643) time: 2.7794 data: 0.0026 max mem: 19788 +Epoch: [5] [1920/2138] eta: 0:10:41 lr: 4.3312385992945514e-05 loss: 0.0682 (0.0643) time: 2.7872 data: 0.0027 max mem: 19788 +Epoch: [5] [1930/2138] eta: 0:10:12 lr: 4.330703940819815e-05 loss: 0.0624 (0.0643) time: 2.7970 data: 0.0026 max mem: 19788 +Epoch: [5] [1940/2138] eta: 0:09:42 lr: 4.330169275010793e-05 loss: 0.0584 (0.0643) time: 2.7966 data: 0.0025 max mem: 19788 +Epoch: [5] [1950/2138] eta: 0:09:13 lr: 4.329634601866378e-05 loss: 0.0526 (0.0643) time: 2.7974 data: 0.0025 max mem: 19788 +Epoch: [5] [1960/2138] eta: 0:08:43 lr: 4.329099921385463e-05 loss: 0.0553 (0.0643) time: 2.7983 data: 0.0027 max mem: 19788 +Epoch: [5] [1970/2138] eta: 0:08:14 lr: 4.328565233566939e-05 loss: 0.0553 (0.0642) time: 2.7967 data: 0.0026 max mem: 19788 +Epoch: [5] [1980/2138] eta: 0:07:44 lr: 4.3280305384097e-05 loss: 0.0530 (0.0642) time: 2.7944 data: 0.0025 max mem: 19788 +Epoch: [5] [1990/2138] eta: 0:07:14 lr: 4.3274958359126364e-05 loss: 0.0555 (0.0642) time: 2.7952 data: 0.0028 max mem: 19788 +Epoch: [5] [2000/2138] eta: 0:06:45 lr: 4.326961126074641e-05 loss: 0.0555 (0.0641) time: 2.7987 data: 0.0027 max mem: 19788 +Epoch: [5] [2010/2138] eta: 0:06:16 lr: 4.326426408894604e-05 loss: 0.0551 (0.0642) time: 2.8085 data: 0.0024 max mem: 19788 +Epoch: [5] [2020/2138] eta: 0:05:46 lr: 4.3258916843714174e-05 loss: 0.0590 (0.0641) time: 2.8014 data: 0.0025 max mem: 19788 +Epoch: [5] [2030/2138] eta: 0:05:17 lr: 4.3253569525039705e-05 loss: 0.0590 (0.0641) time: 2.7840 data: 0.0024 max mem: 19788 +Epoch: [5] [2040/2138] eta: 0:04:47 lr: 4.3248222132911555e-05 loss: 0.0556 (0.0642) time: 2.7841 data: 0.0025 max mem: 19788 +Epoch: [5] [2050/2138] eta: 0:04:18 lr: 4.32428746673186e-05 loss: 0.0493 (0.0641) time: 2.7803 data: 0.0024 max mem: 19788 +Epoch: [5] [2060/2138] eta: 0:03:48 lr: 4.323752712824975e-05 loss: 0.0575 (0.0641) time: 2.7798 data: 0.0024 max mem: 19788 +Epoch: [5] [2070/2138] eta: 0:03:19 lr: 4.323217951569389e-05 loss: 0.0463 (0.0640) time: 2.7818 data: 0.0026 max mem: 19788 +Epoch: [5] [2080/2138] eta: 0:02:50 lr: 4.322683182963993e-05 loss: 0.0490 (0.0640) time: 2.7782 data: 0.0025 max mem: 19788 +Epoch: [5] [2090/2138] eta: 0:02:20 lr: 4.322148407007673e-05 loss: 0.0627 (0.0640) time: 2.7779 data: 0.0025 max mem: 19788 +Epoch: [5] [2100/2138] eta: 0:01:51 lr: 4.321613623699319e-05 loss: 0.0505 (0.0639) time: 2.7946 data: 0.0027 max mem: 19788 +Epoch: [5] [2110/2138] eta: 0:01:22 lr: 4.321078833037819e-05 loss: 0.0512 (0.0639) time: 2.8038 data: 0.0027 max mem: 19788 +Epoch: [5] [2120/2138] eta: 0:00:52 lr: 4.320544035022059e-05 loss: 0.0650 (0.0640) time: 2.7959 data: 0.0027 max mem: 19788 +Epoch: [5] [2130/2138] eta: 0:00:23 lr: 4.3200092296509295e-05 loss: 0.0641 (0.0640) time: 2.7875 data: 0.0026 max mem: 19788 +Epoch: [5] Total time: 1:44:22 +Test: [ 0/21770] eta: 15:51:36 time: 2.6227 data: 2.5145 max mem: 19788 +Test: [ 100/21770] eta: 0:27:59 time: 0.0520 data: 0.0017 max mem: 19788 +Test: [ 200/21770] eta: 0:22:33 time: 0.0463 data: 0.0014 max mem: 19788 +Test: [ 300/21770] eta: 0:20:15 time: 0.0419 data: 0.0014 max mem: 19788 +Test: [ 400/21770] eta: 0:18:57 time: 0.0440 data: 0.0014 max mem: 19788 +Test: [ 500/21770] eta: 0:18:12 time: 0.0427 data: 0.0015 max mem: 19788 +Test: [ 600/21770] eta: 0:17:40 time: 0.0425 data: 0.0015 max mem: 19788 +Test: [ 700/21770] eta: 0:17:28 time: 0.0432 data: 0.0015 max mem: 19788 +Test: [ 800/21770] eta: 0:17:24 time: 0.0490 data: 0.0016 max mem: 19788 +Test: [ 900/21770] eta: 0:17:07 time: 0.0428 data: 0.0014 max mem: 19788 +Test: [ 1000/21770] eta: 0:16:49 time: 0.0429 data: 0.0015 max mem: 19788 +Test: [ 1100/21770] eta: 0:16:39 time: 0.0480 data: 0.0017 max mem: 19788 +Test: [ 1200/21770] eta: 0:16:31 time: 0.0451 data: 0.0014 max mem: 19788 +Test: [ 1300/21770] eta: 0:16:20 time: 0.0461 data: 0.0016 max mem: 19788 +Test: [ 1400/21770] eta: 0:16:14 time: 0.0518 data: 0.0018 max mem: 19788 +Test: [ 1500/21770] eta: 0:16:08 time: 0.0487 data: 0.0016 max mem: 19788 +Test: [ 1600/21770] eta: 0:16:01 time: 0.0484 data: 0.0017 max mem: 19788 +Test: [ 1700/21770] eta: 0:15:51 time: 0.0447 data: 0.0015 max mem: 19788 +Test: [ 1800/21770] eta: 0:15:50 time: 0.0520 data: 0.0018 max mem: 19788 +Test: [ 1900/21770] eta: 0:15:44 time: 0.0434 data: 0.0013 max mem: 19788 +Test: [ 2000/21770] eta: 0:15:36 time: 0.0420 data: 0.0013 max mem: 19788 +Test: [ 2100/21770] eta: 0:15:28 time: 0.0465 data: 0.0016 max mem: 19788 +Test: [ 2200/21770] eta: 0:15:20 time: 0.0432 data: 0.0015 max mem: 19788 +Test: [ 2300/21770] eta: 0:15:13 time: 0.0437 data: 0.0017 max mem: 19788 +Test: [ 2400/21770] eta: 0:15:08 time: 0.0439 data: 0.0013 max mem: 19788 +Test: [ 2500/21770] eta: 0:15:03 time: 0.0528 data: 0.0015 max mem: 19788 +Test: [ 2600/21770] eta: 0:15:01 time: 0.0524 data: 0.0018 max mem: 19788 +Test: [ 2700/21770] eta: 0:14:55 time: 0.0446 data: 0.0014 max mem: 19788 +Test: [ 2800/21770] eta: 0:14:52 time: 0.0429 data: 0.0013 max mem: 19788 +Test: [ 2900/21770] eta: 0:14:45 time: 0.0441 data: 0.0014 max mem: 19788 +Test: [ 3000/21770] eta: 0:14:40 time: 0.0467 data: 0.0015 max mem: 19788 +Test: [ 3100/21770] eta: 0:14:33 time: 0.0429 data: 0.0014 max mem: 19788 +Test: [ 3200/21770] eta: 0:14:27 time: 0.0478 data: 0.0017 max mem: 19788 +Test: [ 3300/21770] eta: 0:14:22 time: 0.0432 data: 0.0016 max mem: 19788 +Test: [ 3400/21770] eta: 0:14:17 time: 0.0434 data: 0.0017 max mem: 19788 +Test: [ 3500/21770] eta: 0:14:12 time: 0.0428 data: 0.0013 max mem: 19788 +Test: [ 3600/21770] eta: 0:14:06 time: 0.0433 data: 0.0014 max mem: 19788 +Test: [ 3700/21770] eta: 0:14:00 time: 0.0432 data: 0.0014 max mem: 19788 +Test: [ 3800/21770] eta: 0:13:54 time: 0.0454 data: 0.0014 max mem: 19788 +Test: [ 3900/21770] eta: 0:13:49 time: 0.0446 data: 0.0013 max mem: 19788 +Test: [ 4000/21770] eta: 0:13:43 time: 0.0432 data: 0.0015 max mem: 19788 +Test: [ 4100/21770] eta: 0:13:39 time: 0.0490 data: 0.0016 max mem: 19788 +Test: [ 4200/21770] eta: 0:13:35 time: 0.0507 data: 0.0016 max mem: 19788 +Test: [ 4300/21770] eta: 0:13:31 time: 0.0435 data: 0.0016 max mem: 19788 +Test: [ 4400/21770] eta: 0:13:27 time: 0.0526 data: 0.0018 max mem: 19788 +Test: [ 4500/21770] eta: 0:13:23 time: 0.0505 data: 0.0016 max mem: 19788 +Test: [ 4600/21770] eta: 0:13:18 time: 0.0440 data: 0.0014 max mem: 19788 +Test: [ 4700/21770] eta: 0:13:14 time: 0.0462 data: 0.0016 max mem: 19788 +Test: [ 4800/21770] eta: 0:13:10 time: 0.0530 data: 0.0017 max mem: 19788 +Test: [ 4900/21770] eta: 0:13:06 time: 0.0496 data: 0.0016 max mem: 19788 +Test: [ 5000/21770] eta: 0:13:02 time: 0.0479 data: 0.0015 max mem: 19788 +Test: [ 5100/21770] eta: 0:12:56 time: 0.0441 data: 0.0014 max mem: 19788 +Test: [ 5200/21770] eta: 0:12:51 time: 0.0454 data: 0.0016 max mem: 19788 +Test: [ 5300/21770] eta: 0:12:46 time: 0.0475 data: 0.0016 max mem: 19788 +Test: [ 5400/21770] eta: 0:12:42 time: 0.0474 data: 0.0016 max mem: 19788 +Test: [ 5500/21770] eta: 0:12:36 time: 0.0450 data: 0.0015 max mem: 19788 +Test: [ 5600/21770] eta: 0:12:32 time: 0.0443 data: 0.0013 max mem: 19788 +Test: [ 5700/21770] eta: 0:12:26 time: 0.0439 data: 0.0014 max mem: 19788 +Test: [ 5800/21770] eta: 0:12:23 time: 0.0530 data: 0.0018 max mem: 19788 +Test: [ 5900/21770] eta: 0:12:19 time: 0.0447 data: 0.0015 max mem: 19788 +Test: [ 6000/21770] eta: 0:12:14 time: 0.0444 data: 0.0013 max mem: 19788 +Test: [ 6100/21770] eta: 0:12:10 time: 0.0520 data: 0.0018 max mem: 19788 +Test: [ 6200/21770] eta: 0:12:07 time: 0.0523 data: 0.0018 max mem: 19788 +Test: [ 6300/21770] eta: 0:12:02 time: 0.0433 data: 0.0015 max mem: 19788 +Test: [ 6400/21770] eta: 0:11:58 time: 0.0519 data: 0.0018 max mem: 19788 +Test: [ 6500/21770] eta: 0:11:54 time: 0.0517 data: 0.0017 max mem: 19788 +Test: [ 6600/21770] eta: 0:11:50 time: 0.0510 data: 0.0017 max mem: 19788 +Test: [ 6700/21770] eta: 0:11:45 time: 0.0435 data: 0.0015 max mem: 19788 +Test: [ 6800/21770] eta: 0:11:40 time: 0.0437 data: 0.0013 max mem: 19788 +Test: [ 6900/21770] eta: 0:11:36 time: 0.0514 data: 0.0016 max mem: 19788 +Test: [ 7000/21770] eta: 0:11:31 time: 0.0439 data: 0.0015 max mem: 19788 +Test: [ 7100/21770] eta: 0:11:26 time: 0.0434 data: 0.0015 max mem: 19788 +Test: [ 7200/21770] eta: 0:11:21 time: 0.0507 data: 0.0017 max mem: 19788 +Test: [ 7300/21770] eta: 0:11:17 time: 0.0458 data: 0.0015 max mem: 19788 +Test: [ 7400/21770] eta: 0:11:12 time: 0.0461 data: 0.0016 max mem: 19788 +Test: [ 7500/21770] eta: 0:11:08 time: 0.0450 data: 0.0014 max mem: 19788 +Test: [ 7600/21770] eta: 0:11:03 time: 0.0425 data: 0.0014 max mem: 19788 +Test: [ 7700/21770] eta: 0:10:58 time: 0.0435 data: 0.0013 max mem: 19788 +Test: [ 7800/21770] eta: 0:10:54 time: 0.0431 data: 0.0014 max mem: 19788 +Test: [ 7900/21770] eta: 0:10:49 time: 0.0512 data: 0.0018 max mem: 19788 +Test: [ 8000/21770] eta: 0:10:44 time: 0.0436 data: 0.0015 max mem: 19788 +Test: [ 8100/21770] eta: 0:10:38 time: 0.0435 data: 0.0015 max mem: 19788 +Test: [ 8200/21770] eta: 0:10:33 time: 0.0435 data: 0.0015 max mem: 19788 +Test: [ 8300/21770] eta: 0:10:29 time: 0.0448 data: 0.0014 max mem: 19788 +Test: [ 8400/21770] eta: 0:10:24 time: 0.0430 data: 0.0015 max mem: 19788 +Test: [ 8500/21770] eta: 0:10:19 time: 0.0514 data: 0.0017 max mem: 19788 +Test: [ 8600/21770] eta: 0:10:15 time: 0.0500 data: 0.0018 max mem: 19788 +Test: [ 8700/21770] eta: 0:10:10 time: 0.0432 data: 0.0016 max mem: 19788 +Test: [ 8800/21770] eta: 0:10:05 time: 0.0423 data: 0.0015 max mem: 19788 +Test: [ 8900/21770] eta: 0:10:00 time: 0.0443 data: 0.0014 max mem: 19788 +Test: [ 9000/21770] eta: 0:09:56 time: 0.0433 data: 0.0014 max mem: 19788 +Test: [ 9100/21770] eta: 0:09:51 time: 0.0496 data: 0.0017 max mem: 19788 +Test: [ 9200/21770] eta: 0:09:47 time: 0.0465 data: 0.0015 max mem: 19788 +Test: [ 9300/21770] eta: 0:09:42 time: 0.0436 data: 0.0014 max mem: 19788 +Test: [ 9400/21770] eta: 0:09:37 time: 0.0485 data: 0.0015 max mem: 19788 +Test: [ 9500/21770] eta: 0:09:32 time: 0.0460 data: 0.0014 max mem: 19788 +Test: [ 9600/21770] eta: 0:09:28 time: 0.0489 data: 0.0016 max mem: 19788 +Test: [ 9700/21770] eta: 0:09:23 time: 0.0454 data: 0.0015 max mem: 19788 +Test: [ 9800/21770] eta: 0:09:18 time: 0.0456 data: 0.0017 max mem: 19788 +Test: [ 9900/21770] eta: 0:09:14 time: 0.0467 data: 0.0015 max mem: 19788 +Test: [10000/21770] eta: 0:09:09 time: 0.0437 data: 0.0015 max mem: 19788 +Test: [10100/21770] eta: 0:09:05 time: 0.0516 data: 0.0018 max mem: 19788 +Test: [10200/21770] eta: 0:09:00 time: 0.0432 data: 0.0015 max mem: 19788 +Test: [10300/21770] eta: 0:08:56 time: 0.0447 data: 0.0015 max mem: 19788 +Test: [10400/21770] eta: 0:08:51 time: 0.0457 data: 0.0016 max mem: 19788 +Test: [10500/21770] eta: 0:08:46 time: 0.0498 data: 0.0017 max mem: 19788 +Test: [10600/21770] eta: 0:08:42 time: 0.0526 data: 0.0018 max mem: 19788 +Test: [10700/21770] eta: 0:08:37 time: 0.0443 data: 0.0014 max mem: 19788 +Test: [10800/21770] eta: 0:08:32 time: 0.0528 data: 0.0017 max mem: 19788 +Test: [10900/21770] eta: 0:08:28 time: 0.0482 data: 0.0015 max mem: 19788 +Test: [11000/21770] eta: 0:08:23 time: 0.0472 data: 0.0014 max mem: 19788 +Test: [11100/21770] eta: 0:08:18 time: 0.0503 data: 0.0017 max mem: 19788 +Test: [11200/21770] eta: 0:08:13 time: 0.0424 data: 0.0014 max mem: 19788 +Test: [11300/21770] eta: 0:08:09 time: 0.0443 data: 0.0014 max mem: 19788 +Test: [11400/21770] eta: 0:08:04 time: 0.0439 data: 0.0015 max mem: 19788 +Test: [11500/21770] eta: 0:08:00 time: 0.0517 data: 0.0017 max mem: 19788 +Test: [11600/21770] eta: 0:07:55 time: 0.0448 data: 0.0015 max mem: 19788 +Test: [11700/21770] eta: 0:07:50 time: 0.0443 data: 0.0013 max mem: 19788 +Test: [11800/21770] eta: 0:07:46 time: 0.0470 data: 0.0015 max mem: 19788 +Test: [11900/21770] eta: 0:07:41 time: 0.0470 data: 0.0017 max mem: 19788 +Test: [12000/21770] eta: 0:07:37 time: 0.0431 data: 0.0015 max mem: 19788 +Test: [12100/21770] eta: 0:07:32 time: 0.0441 data: 0.0013 max mem: 19788 +Test: [12200/21770] eta: 0:07:27 time: 0.0472 data: 0.0016 max mem: 19788 +Test: [12300/21770] eta: 0:07:22 time: 0.0444 data: 0.0015 max mem: 19788 +Test: [12400/21770] eta: 0:07:18 time: 0.0505 data: 0.0014 max mem: 19788 +Test: [12500/21770] eta: 0:07:13 time: 0.0493 data: 0.0014 max mem: 19788 +Test: [12600/21770] eta: 0:07:09 time: 0.0438 data: 0.0014 max mem: 19788 +Test: [12700/21770] eta: 0:07:04 time: 0.0512 data: 0.0015 max mem: 19788 +Test: [12800/21770] eta: 0:06:59 time: 0.0437 data: 0.0016 max mem: 19788 +Test: [12900/21770] eta: 0:06:55 time: 0.0445 data: 0.0014 max mem: 19788 +Test: [13000/21770] eta: 0:06:50 time: 0.0446 data: 0.0016 max mem: 19788 +Test: [13100/21770] eta: 0:06:45 time: 0.0456 data: 0.0014 max mem: 19788 +Test: [13200/21770] eta: 0:06:41 time: 0.0458 data: 0.0015 max mem: 19788 +Test: [13300/21770] eta: 0:06:36 time: 0.0490 data: 0.0016 max mem: 19788 +Test: [13400/21770] eta: 0:06:31 time: 0.0525 data: 0.0018 max mem: 19788 +Test: [13500/21770] eta: 0:06:27 time: 0.0531 data: 0.0016 max mem: 19788 +Test: [13600/21770] eta: 0:06:22 time: 0.0436 data: 0.0014 max mem: 19788 +Test: [13700/21770] eta: 0:06:17 time: 0.0513 data: 0.0017 max mem: 19788 +Test: [13800/21770] eta: 0:06:12 time: 0.0438 data: 0.0015 max mem: 19788 +Test: [13900/21770] eta: 0:06:08 time: 0.0436 data: 0.0015 max mem: 19788 +Test: [14000/21770] eta: 0:06:03 time: 0.0511 data: 0.0017 max mem: 19788 +Test: [14100/21770] eta: 0:05:59 time: 0.0446 data: 0.0016 max mem: 19788 +Test: [14200/21770] eta: 0:05:54 time: 0.0519 data: 0.0019 max mem: 19788 +Test: [14300/21770] eta: 0:05:49 time: 0.0447 data: 0.0014 max mem: 19788 +Test: [14400/21770] eta: 0:05:45 time: 0.0432 data: 0.0013 max mem: 19788 +Test: [14500/21770] eta: 0:05:40 time: 0.0476 data: 0.0015 max mem: 19788 +Test: [14600/21770] eta: 0:05:35 time: 0.0431 data: 0.0013 max mem: 19788 +Test: [14700/21770] eta: 0:05:30 time: 0.0436 data: 0.0013 max mem: 19788 +Test: [14800/21770] eta: 0:05:26 time: 0.0445 data: 0.0014 max mem: 19788 +Test: [14900/21770] eta: 0:05:21 time: 0.0437 data: 0.0015 max mem: 19788 +Test: [15000/21770] eta: 0:05:16 time: 0.0528 data: 0.0018 max mem: 19788 +Test: [15100/21770] eta: 0:05:11 time: 0.0436 data: 0.0014 max mem: 19788 +Test: [15200/21770] eta: 0:05:07 time: 0.0454 data: 0.0015 max mem: 19788 +Test: [15300/21770] eta: 0:05:02 time: 0.0504 data: 0.0017 max mem: 19788 +Test: [15400/21770] eta: 0:04:58 time: 0.0445 data: 0.0014 max mem: 19788 +Test: [15500/21770] eta: 0:04:53 time: 0.0433 data: 0.0014 max mem: 19788 +Test: [15600/21770] eta: 0:04:48 time: 0.0435 data: 0.0015 max mem: 19788 +Test: [15700/21770] eta: 0:04:43 time: 0.0446 data: 0.0014 max mem: 19788 +Test: [15800/21770] eta: 0:04:39 time: 0.0454 data: 0.0016 max mem: 19788 +Test: [15900/21770] eta: 0:04:34 time: 0.0471 data: 0.0014 max mem: 19788 +Test: [16000/21770] eta: 0:04:29 time: 0.0441 data: 0.0015 max mem: 19788 +Test: [16100/21770] eta: 0:04:25 time: 0.0460 data: 0.0015 max mem: 19788 +Test: [16200/21770] eta: 0:04:20 time: 0.0426 data: 0.0014 max mem: 19788 +Test: [16300/21770] eta: 0:04:15 time: 0.0462 data: 0.0016 max mem: 19788 +Test: [16400/21770] eta: 0:04:11 time: 0.0527 data: 0.0017 max mem: 19788 +Test: [16500/21770] eta: 0:04:06 time: 0.0456 data: 0.0015 max mem: 19788 +Test: [16600/21770] eta: 0:04:01 time: 0.0438 data: 0.0013 max mem: 19788 +Test: [16700/21770] eta: 0:03:56 time: 0.0497 data: 0.0017 max mem: 19788 +Test: [16800/21770] eta: 0:03:52 time: 0.0459 data: 0.0016 max mem: 19788 +Test: [16900/21770] eta: 0:03:47 time: 0.0484 data: 0.0017 max mem: 19788 +Test: [17000/21770] eta: 0:03:42 time: 0.0459 data: 0.0016 max mem: 19788 +Test: [17100/21770] eta: 0:03:38 time: 0.0439 data: 0.0014 max mem: 19788 +Test: [17200/21770] eta: 0:03:33 time: 0.0520 data: 0.0017 max mem: 19788 +Test: [17300/21770] eta: 0:03:28 time: 0.0438 data: 0.0015 max mem: 19788 +Test: [17400/21770] eta: 0:03:23 time: 0.0479 data: 0.0016 max mem: 19788 +Test: [17500/21770] eta: 0:03:19 time: 0.0463 data: 0.0014 max mem: 19788 +Test: [17600/21770] eta: 0:03:14 time: 0.0434 data: 0.0013 max mem: 19788 +Test: [17700/21770] eta: 0:03:09 time: 0.0465 data: 0.0018 max mem: 19788 +Test: [17800/21770] eta: 0:03:05 time: 0.0451 data: 0.0016 max mem: 19788 +Test: [17900/21770] eta: 0:03:00 time: 0.0532 data: 0.0017 max mem: 19788 +Test: [18000/21770] eta: 0:02:55 time: 0.0506 data: 0.0018 max mem: 19788 +Test: [18100/21770] eta: 0:02:51 time: 0.0493 data: 0.0016 max mem: 19788 +Test: [18200/21770] eta: 0:02:46 time: 0.0434 data: 0.0013 max mem: 19788 +Test: [18300/21770] eta: 0:02:41 time: 0.0453 data: 0.0015 max mem: 19788 +Test: [18400/21770] eta: 0:02:37 time: 0.0441 data: 0.0014 max mem: 19788 +Test: [18500/21770] eta: 0:02:32 time: 0.0429 data: 0.0013 max mem: 19788 +Test: [18600/21770] eta: 0:02:27 time: 0.0445 data: 0.0013 max mem: 19788 +Test: [18700/21770] eta: 0:02:23 time: 0.0491 data: 0.0015 max mem: 19788 +Test: [18800/21770] eta: 0:02:18 time: 0.0502 data: 0.0016 max mem: 19788 +Test: [18900/21770] eta: 0:02:13 time: 0.0486 data: 0.0014 max mem: 19788 +Test: [19000/21770] eta: 0:02:09 time: 0.0526 data: 0.0017 max mem: 19788 +Test: [19100/21770] eta: 0:02:04 time: 0.0452 data: 0.0014 max mem: 19788 +Test: [19200/21770] eta: 0:01:59 time: 0.0435 data: 0.0013 max mem: 19788 +Test: [19300/21770] eta: 0:01:55 time: 0.0437 data: 0.0014 max mem: 19788 +Test: [19400/21770] eta: 0:01:50 time: 0.0493 data: 0.0016 max mem: 19788 +Test: [19500/21770] eta: 0:01:45 time: 0.0435 data: 0.0015 max mem: 19788 +Test: [19600/21770] eta: 0:01:41 time: 0.0421 data: 0.0014 max mem: 19788 +Test: [19700/21770] eta: 0:01:36 time: 0.0455 data: 0.0016 max mem: 19788 +Test: [19800/21770] eta: 0:01:31 time: 0.0461 data: 0.0014 max mem: 19788 +Test: [19900/21770] eta: 0:01:27 time: 0.0493 data: 0.0016 max mem: 19788 +Test: [20000/21770] eta: 0:01:22 time: 0.0528 data: 0.0016 max mem: 19788 +Test: [20100/21770] eta: 0:01:17 time: 0.0456 data: 0.0015 max mem: 19788 +Test: [20200/21770] eta: 0:01:13 time: 0.0506 data: 0.0017 max mem: 19788 +Test: [20300/21770] eta: 0:01:08 time: 0.0488 data: 0.0016 max mem: 19788 +Test: [20400/21770] eta: 0:01:03 time: 0.0438 data: 0.0014 max mem: 19788 +Test: [20500/21770] eta: 0:00:59 time: 0.0487 data: 0.0016 max mem: 19788 +Test: [20600/21770] eta: 0:00:54 time: 0.0440 data: 0.0014 max mem: 19788 +Test: [20700/21770] eta: 0:00:49 time: 0.0420 data: 0.0014 max mem: 19788 +Test: [20800/21770] eta: 0:00:45 time: 0.0478 data: 0.0016 max mem: 19788 +Test: [20900/21770] eta: 0:00:40 time: 0.0444 data: 0.0013 max mem: 19788 +Test: [21000/21770] eta: 0:00:35 time: 0.0518 data: 0.0018 max mem: 19788 +Test: [21100/21770] eta: 0:00:31 time: 0.0443 data: 0.0016 max mem: 19788 +Test: [21200/21770] eta: 0:00:26 time: 0.0434 data: 0.0015 max mem: 19788 +Test: [21300/21770] eta: 0:00:21 time: 0.0457 data: 0.0015 max mem: 19788 +Test: [21400/21770] eta: 0:00:17 time: 0.0517 data: 0.0018 max mem: 19788 +Test: [21500/21770] eta: 0:00:12 time: 0.0442 data: 0.0015 max mem: 19788 +Test: [21600/21770] eta: 0:00:07 time: 0.0438 data: 0.0013 max mem: 19788 +Test: [21700/21770] eta: 0:00:03 time: 0.0461 data: 0.0015 max mem: 19788 +Test: Total time: 0:16:54 +Final results: +Mean IoU is 59.57 + + precision@0.5 = 66.33 + precision@0.6 = 60.14 + precision@0.7 = 52.74 + precision@0.8 = 41.36 + precision@0.9 = 18.92 + overall IoU = 61.98 + mean IoU = 59.57 + +Mean accuracy for one-to-zero sample is 83.11 + +Average object IoU 0.5956736332796396 +Overall IoU 61.978912353515625 +Epoch: [6] [ 0/2138] eta: 4:26:34 lr: 4.31958138005741e-05 loss: 0.1087 (0.1087) time: 7.4809 data: 1.9896 max mem: 19788 +Epoch: [6] [ 10/2138] eta: 1:54:31 lr: 4.3190465614438056e-05 loss: 0.0606 (0.0738) time: 3.2291 data: 0.1830 max mem: 19788 +Epoch: [6] [ 20/2138] eta: 1:47:00 lr: 4.318511735471714e-05 loss: 0.0534 (0.0661) time: 2.8087 data: 0.0019 max mem: 19788 +Epoch: [6] [ 30/2138] eta: 1:44:03 lr: 4.317976902140019e-05 loss: 0.0598 (0.0662) time: 2.8147 data: 0.0022 max mem: 19788 +Epoch: [6] [ 40/2138] eta: 1:42:16 lr: 4.317442061447609e-05 loss: 0.0619 (0.0668) time: 2.8133 data: 0.0028 max mem: 19788 +Epoch: [6] [ 50/2138] eta: 1:41:00 lr: 4.3169072133933666e-05 loss: 0.0544 (0.0642) time: 2.8107 data: 0.0025 max mem: 19788 +Epoch: [6] [ 60/2138] eta: 1:40:02 lr: 4.3163723579761795e-05 loss: 0.0538 (0.0641) time: 2.8144 data: 0.0024 max mem: 19788 +Epoch: [6] [ 70/2138] eta: 1:39:10 lr: 4.3158374951949307e-05 loss: 0.0525 (0.0619) time: 2.8139 data: 0.0023 max mem: 19788 +Epoch: [6] [ 80/2138] eta: 1:38:25 lr: 4.315302625048507e-05 loss: 0.0499 (0.0615) time: 2.8105 data: 0.0022 max mem: 19788 +Epoch: [6] [ 90/2138] eta: 1:37:41 lr: 4.31476774753579e-05 loss: 0.0667 (0.0620) time: 2.8077 data: 0.0022 max mem: 19788 +Epoch: [6] [ 100/2138] eta: 1:37:03 lr: 4.314232862655665e-05 loss: 0.0570 (0.0616) time: 2.8087 data: 0.0023 max mem: 19788 +Epoch: [6] [ 110/2138] eta: 1:36:27 lr: 4.3136979704070164e-05 loss: 0.0576 (0.0626) time: 2.8153 data: 0.0022 max mem: 19788 +Epoch: [6] [ 120/2138] eta: 1:35:53 lr: 4.3131630707887255e-05 loss: 0.0594 (0.0619) time: 2.8181 data: 0.0021 max mem: 19788 +Epoch: [6] [ 130/2138] eta: 1:35:18 lr: 4.312628163799677e-05 loss: 0.0497 (0.0613) time: 2.8167 data: 0.0020 max mem: 19788 +Epoch: [6] [ 140/2138] eta: 1:34:47 lr: 4.312093249438752e-05 loss: 0.0523 (0.0609) time: 2.8191 data: 0.0021 max mem: 19788 +Epoch: [6] [ 150/2138] eta: 1:34:13 lr: 4.311558327704834e-05 loss: 0.0523 (0.0608) time: 2.8167 data: 0.0023 max mem: 19788 +Epoch: [6] [ 160/2138] eta: 1:33:41 lr: 4.3110233985968044e-05 loss: 0.0521 (0.0604) time: 2.8110 data: 0.0027 max mem: 19788 +Epoch: [6] [ 170/2138] eta: 1:33:09 lr: 4.310488462113546e-05 loss: 0.0567 (0.0607) time: 2.8108 data: 0.0027 max mem: 19788 +Epoch: [6] [ 180/2138] eta: 1:32:37 lr: 4.3099535182539366e-05 loss: 0.0531 (0.0601) time: 2.8110 data: 0.0025 max mem: 19788 +Epoch: [6] [ 190/2138] eta: 1:32:06 lr: 4.3094185670168616e-05 loss: 0.0495 (0.0605) time: 2.8126 data: 0.0024 max mem: 19788 +Epoch: [6] [ 200/2138] eta: 1:31:37 lr: 4.308883608401199e-05 loss: 0.0483 (0.0599) time: 2.8177 data: 0.0025 max mem: 19788 +Epoch: [6] [ 210/2138] eta: 1:31:05 lr: 4.308348642405831e-05 loss: 0.0527 (0.0598) time: 2.8104 data: 0.0025 max mem: 19788 +Epoch: [6] [ 220/2138] eta: 1:30:33 lr: 4.3078136690296346e-05 loss: 0.0544 (0.0599) time: 2.7969 data: 0.0026 max mem: 19788 +Epoch: [6] [ 230/2138] eta: 1:30:02 lr: 4.307278688271493e-05 loss: 0.0628 (0.0607) time: 2.7952 data: 0.0025 max mem: 19788 +Epoch: [6] [ 240/2138] eta: 1:29:30 lr: 4.3067437001302826e-05 loss: 0.0623 (0.0605) time: 2.7952 data: 0.0025 max mem: 19788 +Epoch: [6] [ 250/2138] eta: 1:29:00 lr: 4.3062087046048845e-05 loss: 0.0549 (0.0604) time: 2.7956 data: 0.0023 max mem: 19788 +Epoch: [6] [ 260/2138] eta: 1:28:29 lr: 4.305673701694176e-05 loss: 0.0530 (0.0602) time: 2.7940 data: 0.0022 max mem: 19788 +Epoch: [6] [ 270/2138] eta: 1:27:58 lr: 4.305138691397037e-05 loss: 0.0525 (0.0602) time: 2.7911 data: 0.0022 max mem: 19788 +Epoch: [6] [ 280/2138] eta: 1:27:27 lr: 4.304603673712345e-05 loss: 0.0577 (0.0605) time: 2.7904 data: 0.0023 max mem: 19788 +Epoch: [6] [ 290/2138] eta: 1:26:58 lr: 4.304068648638977e-05 loss: 0.0622 (0.0608) time: 2.7992 data: 0.0025 max mem: 19788 +Epoch: [6] [ 300/2138] eta: 1:26:29 lr: 4.303533616175811e-05 loss: 0.0580 (0.0608) time: 2.8085 data: 0.0027 max mem: 19788 +Epoch: [6] [ 310/2138] eta: 1:26:00 lr: 4.302998576321723e-05 loss: 0.0476 (0.0608) time: 2.8085 data: 0.0025 max mem: 19788 +Epoch: [6] [ 320/2138] eta: 1:25:31 lr: 4.302463529075593e-05 loss: 0.0486 (0.0607) time: 2.8102 data: 0.0022 max mem: 19788 +Epoch: [6] [ 330/2138] eta: 1:25:02 lr: 4.301928474436294e-05 loss: 0.0528 (0.0609) time: 2.8150 data: 0.0021 max mem: 19788 +Epoch: [6] [ 340/2138] eta: 1:24:33 lr: 4.301393412402703e-05 loss: 0.0611 (0.0609) time: 2.8087 data: 0.0021 max mem: 19788 +Epoch: [6] [ 350/2138] eta: 1:24:03 lr: 4.300858342973696e-05 loss: 0.0499 (0.0606) time: 2.7983 data: 0.0022 max mem: 19788 +Epoch: [6] [ 360/2138] eta: 1:23:34 lr: 4.30032326614815e-05 loss: 0.0486 (0.0605) time: 2.7927 data: 0.0023 max mem: 19788 +Epoch: [6] [ 370/2138] eta: 1:23:04 lr: 4.299788181924938e-05 loss: 0.0496 (0.0603) time: 2.7879 data: 0.0022 max mem: 19788 +Epoch: [6] [ 380/2138] eta: 1:22:34 lr: 4.299253090302934e-05 loss: 0.0496 (0.0603) time: 2.7867 data: 0.0020 max mem: 19788 +Epoch: [6] [ 390/2138] eta: 1:22:05 lr: 4.298717991281016e-05 loss: 0.0473 (0.0599) time: 2.7911 data: 0.0019 max mem: 19788 +Epoch: [6] [ 400/2138] eta: 1:21:36 lr: 4.298182884858056e-05 loss: 0.0559 (0.0601) time: 2.7921 data: 0.0021 max mem: 19788 +Epoch: [6] [ 410/2138] eta: 1:21:07 lr: 4.297647771032927e-05 loss: 0.0559 (0.0599) time: 2.7929 data: 0.0021 max mem: 19788 +Epoch: [6] [ 420/2138] eta: 1:20:38 lr: 4.2971126498045036e-05 loss: 0.0540 (0.0599) time: 2.7979 data: 0.0021 max mem: 19788 +Epoch: [6] [ 430/2138] eta: 1:20:09 lr: 4.29657752117166e-05 loss: 0.0582 (0.0598) time: 2.8049 data: 0.0025 max mem: 19788 +Epoch: [6] [ 440/2138] eta: 1:19:41 lr: 4.2960423851332675e-05 loss: 0.0565 (0.0598) time: 2.8121 data: 0.0028 max mem: 19788 +Epoch: [6] [ 450/2138] eta: 1:19:13 lr: 4.295507241688199e-05 loss: 0.0553 (0.0596) time: 2.8101 data: 0.0028 max mem: 19788 +Epoch: [6] [ 460/2138] eta: 1:18:44 lr: 4.294972090835326e-05 loss: 0.0483 (0.0598) time: 2.8087 data: 0.0027 max mem: 19788 +Epoch: [6] [ 470/2138] eta: 1:18:16 lr: 4.2944369325735224e-05 loss: 0.0463 (0.0596) time: 2.8081 data: 0.0027 max mem: 19788 +Epoch: [6] [ 480/2138] eta: 1:17:47 lr: 4.2939017669016576e-05 loss: 0.0545 (0.0598) time: 2.8096 data: 0.0025 max mem: 19788 +Epoch: [6] [ 490/2138] eta: 1:17:19 lr: 4.293366593818604e-05 loss: 0.0606 (0.0599) time: 2.8167 data: 0.0023 max mem: 19788 +Epoch: [6] [ 500/2138] eta: 1:16:51 lr: 4.2928314133232325e-05 loss: 0.0587 (0.0600) time: 2.8155 data: 0.0024 max mem: 19788 +Epoch: [6] [ 510/2138] eta: 1:16:23 lr: 4.292296225414412e-05 loss: 0.0537 (0.0599) time: 2.8146 data: 0.0025 max mem: 19788 +Epoch: [6] [ 520/2138] eta: 1:15:55 lr: 4.291761030091015e-05 loss: 0.0597 (0.0600) time: 2.8129 data: 0.0025 max mem: 19788 +Epoch: [6] [ 530/2138] eta: 1:15:26 lr: 4.29122582735191e-05 loss: 0.0582 (0.0599) time: 2.8085 data: 0.0023 max mem: 19788 +Epoch: [6] [ 540/2138] eta: 1:14:58 lr: 4.290690617195968e-05 loss: 0.0473 (0.0597) time: 2.8079 data: 0.0021 max mem: 19788 +Epoch: [6] [ 550/2138] eta: 1:14:30 lr: 4.290155399622056e-05 loss: 0.0503 (0.0600) time: 2.8085 data: 0.0023 max mem: 19788 +Epoch: [6] [ 560/2138] eta: 1:14:01 lr: 4.289620174629045e-05 loss: 0.0563 (0.0601) time: 2.8092 data: 0.0025 max mem: 19788 +Epoch: [6] [ 570/2138] eta: 1:13:33 lr: 4.2890849422158016e-05 loss: 0.0543 (0.0600) time: 2.8089 data: 0.0025 max mem: 19788 +Epoch: [6] [ 580/2138] eta: 1:13:05 lr: 4.288549702381196e-05 loss: 0.0543 (0.0601) time: 2.8078 data: 0.0025 max mem: 19788 +Epoch: [6] [ 590/2138] eta: 1:12:36 lr: 4.288014455124095e-05 loss: 0.0567 (0.0601) time: 2.8096 data: 0.0025 max mem: 19788 +Epoch: [6] [ 600/2138] eta: 1:12:08 lr: 4.2874792004433665e-05 loss: 0.0600 (0.0602) time: 2.8101 data: 0.0023 max mem: 19788 +Epoch: [6] [ 610/2138] eta: 1:11:40 lr: 4.2869439383378774e-05 loss: 0.0559 (0.0601) time: 2.8149 data: 0.0022 max mem: 19788 +Epoch: [6] [ 620/2138] eta: 1:11:12 lr: 4.286408668806495e-05 loss: 0.0559 (0.0602) time: 2.8166 data: 0.0023 max mem: 19788 +Epoch: [6] [ 630/2138] eta: 1:10:44 lr: 4.285873391848086e-05 loss: 0.0563 (0.0601) time: 2.8138 data: 0.0022 max mem: 19788 +Epoch: [6] [ 640/2138] eta: 1:10:16 lr: 4.2853381074615166e-05 loss: 0.0499 (0.0600) time: 2.8156 data: 0.0024 max mem: 19788 +Epoch: [6] [ 650/2138] eta: 1:09:47 lr: 4.284802815645652e-05 loss: 0.0499 (0.0599) time: 2.8046 data: 0.0026 max mem: 19788 +Epoch: [6] [ 660/2138] eta: 1:09:19 lr: 4.2842675163993595e-05 loss: 0.0420 (0.0598) time: 2.7950 data: 0.0027 max mem: 19788 +Epoch: [6] [ 670/2138] eta: 1:08:50 lr: 4.2837322097215026e-05 loss: 0.0423 (0.0597) time: 2.7935 data: 0.0025 max mem: 19788 +Epoch: [6] [ 680/2138] eta: 1:08:22 lr: 4.283196895610947e-05 loss: 0.0417 (0.0595) time: 2.7973 data: 0.0022 max mem: 19788 +Epoch: [6] [ 690/2138] eta: 1:07:53 lr: 4.2826615740665574e-05 loss: 0.0426 (0.0595) time: 2.7988 data: 0.0021 max mem: 19788 +Epoch: [6] [ 700/2138] eta: 1:07:25 lr: 4.282126245087198e-05 loss: 0.0527 (0.0593) time: 2.7960 data: 0.0021 max mem: 19788 +Epoch: [6] [ 710/2138] eta: 1:06:56 lr: 4.2815909086717325e-05 loss: 0.0528 (0.0593) time: 2.7951 data: 0.0022 max mem: 19788 +Epoch: [6] [ 720/2138] eta: 1:06:28 lr: 4.2810555648190245e-05 loss: 0.0500 (0.0592) time: 2.8001 data: 0.0023 max mem: 19788 +Epoch: [6] [ 730/2138] eta: 1:06:00 lr: 4.280520213527938e-05 loss: 0.0500 (0.0592) time: 2.8080 data: 0.0026 max mem: 19788 +Epoch: [6] [ 740/2138] eta: 1:05:31 lr: 4.279984854797336e-05 loss: 0.0546 (0.0591) time: 2.8093 data: 0.0030 max mem: 19788 +Epoch: [6] [ 750/2138] eta: 1:05:03 lr: 4.27944948862608e-05 loss: 0.0526 (0.0591) time: 2.8074 data: 0.0030 max mem: 19788 +Epoch: [6] [ 760/2138] eta: 1:04:35 lr: 4.278914115013033e-05 loss: 0.0530 (0.0591) time: 2.8011 data: 0.0027 max mem: 19788 +Epoch: [6] [ 770/2138] eta: 1:04:06 lr: 4.2783787339570555e-05 loss: 0.0599 (0.0592) time: 2.7969 data: 0.0024 max mem: 19788 +Epoch: [6] [ 780/2138] eta: 1:03:38 lr: 4.277843345457012e-05 loss: 0.0599 (0.0592) time: 2.7985 data: 0.0021 max mem: 19788 +Epoch: [6] [ 790/2138] eta: 1:03:10 lr: 4.277307949511763e-05 loss: 0.0497 (0.0591) time: 2.7982 data: 0.0020 max mem: 19788 +Epoch: [6] [ 800/2138] eta: 1:02:41 lr: 4.276772546120167e-05 loss: 0.0526 (0.0593) time: 2.7937 data: 0.0019 max mem: 19788 +Epoch: [6] [ 810/2138] eta: 1:02:13 lr: 4.276237135281087e-05 loss: 0.0552 (0.0593) time: 2.7926 data: 0.0024 max mem: 19788 +Epoch: [6] [ 820/2138] eta: 1:01:44 lr: 4.275701716993383e-05 loss: 0.0488 (0.0591) time: 2.7930 data: 0.0028 max mem: 19788 +Epoch: [6] [ 830/2138] eta: 1:01:16 lr: 4.275166291255914e-05 loss: 0.0454 (0.0592) time: 2.7990 data: 0.0027 max mem: 19788 +Epoch: [6] [ 840/2138] eta: 1:00:48 lr: 4.274630858067541e-05 loss: 0.0454 (0.0591) time: 2.8112 data: 0.0026 max mem: 19788 +Epoch: [6] [ 850/2138] eta: 1:00:20 lr: 4.2740954174271225e-05 loss: 0.0429 (0.0590) time: 2.8191 data: 0.0026 max mem: 19788 +Epoch: [6] [ 860/2138] eta: 0:59:52 lr: 4.273559969333517e-05 loss: 0.0493 (0.0590) time: 2.8150 data: 0.0026 max mem: 19788 +Epoch: [6] [ 870/2138] eta: 0:59:24 lr: 4.273024513785584e-05 loss: 0.0594 (0.0591) time: 2.8106 data: 0.0026 max mem: 19788 +Epoch: [6] [ 880/2138] eta: 0:58:56 lr: 4.272489050782181e-05 loss: 0.0605 (0.0593) time: 2.8103 data: 0.0026 max mem: 19788 +Epoch: [6] [ 890/2138] eta: 0:58:28 lr: 4.271953580322167e-05 loss: 0.0604 (0.0595) time: 2.8080 data: 0.0025 max mem: 19788 +Epoch: [6] [ 900/2138] eta: 0:58:00 lr: 4.271418102404399e-05 loss: 0.0614 (0.0597) time: 2.8103 data: 0.0022 max mem: 19788 +Epoch: [6] [ 910/2138] eta: 0:57:31 lr: 4.2708826170277344e-05 loss: 0.0664 (0.0598) time: 2.8120 data: 0.0022 max mem: 19788 +Epoch: [6] [ 920/2138] eta: 0:57:03 lr: 4.2703471241910295e-05 loss: 0.0562 (0.0598) time: 2.8123 data: 0.0022 max mem: 19788 +Epoch: [6] [ 930/2138] eta: 0:56:35 lr: 4.269811623893142e-05 loss: 0.0655 (0.0601) time: 2.8138 data: 0.0021 max mem: 19788 +Epoch: [6] [ 940/2138] eta: 0:56:07 lr: 4.269276116132929e-05 loss: 0.0690 (0.0602) time: 2.8134 data: 0.0021 max mem: 19788 +Epoch: [6] [ 950/2138] eta: 0:55:39 lr: 4.2687406009092435e-05 loss: 0.0622 (0.0602) time: 2.8136 data: 0.0021 max mem: 19788 +Epoch: [6] [ 960/2138] eta: 0:55:11 lr: 4.268205078220943e-05 loss: 0.0526 (0.0602) time: 2.8169 data: 0.0022 max mem: 19788 +Epoch: [6] [ 970/2138] eta: 0:54:43 lr: 4.2676695480668826e-05 loss: 0.0479 (0.0601) time: 2.8144 data: 0.0026 max mem: 19788 +Epoch: [6] [ 980/2138] eta: 0:54:15 lr: 4.267134010445918e-05 loss: 0.0512 (0.0601) time: 2.8177 data: 0.0029 max mem: 19788 +Epoch: [6] [ 990/2138] eta: 0:53:47 lr: 4.266598465356903e-05 loss: 0.0514 (0.0602) time: 2.8213 data: 0.0030 max mem: 19788 +Epoch: [6] [1000/2138] eta: 0:53:19 lr: 4.2660629127986904e-05 loss: 0.0519 (0.0602) time: 2.8162 data: 0.0028 max mem: 19788 +Epoch: [6] [1010/2138] eta: 0:52:51 lr: 4.2655273527701375e-05 loss: 0.0557 (0.0601) time: 2.8155 data: 0.0026 max mem: 19788 +Epoch: [6] [1020/2138] eta: 0:52:23 lr: 4.264991785270095e-05 loss: 0.0486 (0.0601) time: 2.8151 data: 0.0026 max mem: 19788 +Epoch: [6] [1030/2138] eta: 0:51:55 lr: 4.264456210297418e-05 loss: 0.0481 (0.0601) time: 2.8123 data: 0.0028 max mem: 19788 +Epoch: [6] [1040/2138] eta: 0:51:26 lr: 4.263920627850958e-05 loss: 0.0572 (0.0603) time: 2.8080 data: 0.0025 max mem: 19788 +Epoch: [6] [1050/2138] eta: 0:50:58 lr: 4.263385037929569e-05 loss: 0.0635 (0.0604) time: 2.8087 data: 0.0022 max mem: 19788 +Epoch: [6] [1060/2138] eta: 0:50:30 lr: 4.262849440532103e-05 loss: 0.0547 (0.0604) time: 2.8149 data: 0.0023 max mem: 19788 +Epoch: [6] [1070/2138] eta: 0:50:02 lr: 4.2623138356574104e-05 loss: 0.0517 (0.0603) time: 2.8142 data: 0.0022 max mem: 19788 +Epoch: [6] [1080/2138] eta: 0:49:34 lr: 4.2617782233043444e-05 loss: 0.0537 (0.0603) time: 2.8097 data: 0.0024 max mem: 19788 +Epoch: [6] [1090/2138] eta: 0:49:06 lr: 4.261242603471756e-05 loss: 0.0537 (0.0603) time: 2.8074 data: 0.0024 max mem: 19788 +Epoch: [6] [1100/2138] eta: 0:48:38 lr: 4.2607069761584964e-05 loss: 0.0533 (0.0603) time: 2.8034 data: 0.0024 max mem: 19788 +Epoch: [6] [1110/2138] eta: 0:48:09 lr: 4.2601713413634145e-05 loss: 0.0532 (0.0603) time: 2.8005 data: 0.0025 max mem: 19788 +Epoch: [6] [1120/2138] eta: 0:47:41 lr: 4.259635699085362e-05 loss: 0.0532 (0.0604) time: 2.8060 data: 0.0026 max mem: 19788 +Epoch: [6] [1130/2138] eta: 0:47:13 lr: 4.259100049323189e-05 loss: 0.0574 (0.0604) time: 2.8107 data: 0.0027 max mem: 19788 +Epoch: [6] [1140/2138] eta: 0:46:45 lr: 4.258564392075745e-05 loss: 0.0574 (0.0605) time: 2.8119 data: 0.0025 max mem: 19788 +Epoch: [6] [1150/2138] eta: 0:46:17 lr: 4.258028727341878e-05 loss: 0.0535 (0.0604) time: 2.8068 data: 0.0022 max mem: 19788 +Epoch: [6] [1160/2138] eta: 0:45:49 lr: 4.257493055120438e-05 loss: 0.0504 (0.0603) time: 2.7998 data: 0.0021 max mem: 19788 +Epoch: [6] [1170/2138] eta: 0:45:20 lr: 4.2569573754102726e-05 loss: 0.0461 (0.0602) time: 2.7990 data: 0.0022 max mem: 19788 +Epoch: [6] [1180/2138] eta: 0:44:52 lr: 4.256421688210232e-05 loss: 0.0461 (0.0602) time: 2.7934 data: 0.0021 max mem: 19788 +Epoch: [6] [1190/2138] eta: 0:44:24 lr: 4.255885993519161e-05 loss: 0.0424 (0.0601) time: 2.7860 data: 0.0021 max mem: 19788 +Epoch: [6] [1200/2138] eta: 0:43:56 lr: 4.2553502913359114e-05 loss: 0.0388 (0.0600) time: 2.7909 data: 0.0024 max mem: 19788 +Epoch: [6] [1210/2138] eta: 0:43:28 lr: 4.254814581659326e-05 loss: 0.0522 (0.0601) time: 2.8035 data: 0.0027 max mem: 19788 +Epoch: [6] [1220/2138] eta: 0:42:59 lr: 4.254278864488254e-05 loss: 0.0545 (0.0600) time: 2.8005 data: 0.0028 max mem: 19788 +Epoch: [6] [1230/2138] eta: 0:42:31 lr: 4.253743139821542e-05 loss: 0.0558 (0.0600) time: 2.7901 data: 0.0028 max mem: 19788 +Epoch: [6] [1240/2138] eta: 0:42:03 lr: 4.253207407658035e-05 loss: 0.0529 (0.0599) time: 2.7866 data: 0.0024 max mem: 19788 +Epoch: [6] [1250/2138] eta: 0:41:35 lr: 4.2526716679965806e-05 loss: 0.0517 (0.0599) time: 2.7900 data: 0.0021 max mem: 19788 +Epoch: [6] [1260/2138] eta: 0:41:06 lr: 4.252135920836022e-05 loss: 0.0517 (0.0598) time: 2.7959 data: 0.0023 max mem: 19788 +Epoch: [6] [1270/2138] eta: 0:40:38 lr: 4.251600166175206e-05 loss: 0.0514 (0.0598) time: 2.7975 data: 0.0026 max mem: 19788 +Epoch: [6] [1280/2138] eta: 0:40:10 lr: 4.251064404012978e-05 loss: 0.0540 (0.0598) time: 2.8032 data: 0.0026 max mem: 19788 +Epoch: [6] [1290/2138] eta: 0:39:42 lr: 4.250528634348181e-05 loss: 0.0510 (0.0599) time: 2.8119 data: 0.0023 max mem: 19788 +Epoch: [6] [1300/2138] eta: 0:39:14 lr: 4.249992857179659e-05 loss: 0.0461 (0.0598) time: 2.8133 data: 0.0022 max mem: 19788 +Epoch: [6] [1310/2138] eta: 0:38:46 lr: 4.2494570725062564e-05 loss: 0.0428 (0.0597) time: 2.8132 data: 0.0023 max mem: 19788 +Epoch: [6] [1320/2138] eta: 0:38:18 lr: 4.248921280326818e-05 loss: 0.0481 (0.0596) time: 2.8158 data: 0.0023 max mem: 19788 +Epoch: [6] [1330/2138] eta: 0:37:50 lr: 4.248385480640186e-05 loss: 0.0544 (0.0596) time: 2.8130 data: 0.0022 max mem: 19788 +Epoch: [6] [1340/2138] eta: 0:37:22 lr: 4.247849673445201e-05 loss: 0.0553 (0.0597) time: 2.8106 data: 0.0022 max mem: 19788 +Epoch: [6] [1350/2138] eta: 0:36:54 lr: 4.2473138587407085e-05 loss: 0.0599 (0.0597) time: 2.8121 data: 0.0025 max mem: 19788 +Epoch: [6] [1360/2138] eta: 0:36:26 lr: 4.246778036525549e-05 loss: 0.0599 (0.0597) time: 2.8145 data: 0.0030 max mem: 19788 +Epoch: [6] [1370/2138] eta: 0:35:57 lr: 4.246242206798566e-05 loss: 0.0575 (0.0597) time: 2.8132 data: 0.0028 max mem: 19788 +Epoch: [6] [1380/2138] eta: 0:35:29 lr: 4.2457063695585986e-05 loss: 0.0575 (0.0597) time: 2.8087 data: 0.0026 max mem: 19788 +Epoch: [6] [1390/2138] eta: 0:35:01 lr: 4.245170524804489e-05 loss: 0.0473 (0.0596) time: 2.8026 data: 0.0028 max mem: 19788 +Epoch: [6] [1400/2138] eta: 0:34:33 lr: 4.2446346725350775e-05 loss: 0.0446 (0.0596) time: 2.7948 data: 0.0028 max mem: 19788 +Epoch: [6] [1410/2138] eta: 0:34:05 lr: 4.244098812749206e-05 loss: 0.0463 (0.0595) time: 2.7917 data: 0.0028 max mem: 19788 +Epoch: [6] [1420/2138] eta: 0:33:37 lr: 4.243562945445713e-05 loss: 0.0463 (0.0595) time: 2.7984 data: 0.0030 max mem: 19788 +Epoch: [6] [1430/2138] eta: 0:33:09 lr: 4.2430270706234385e-05 loss: 0.0498 (0.0595) time: 2.8098 data: 0.0029 max mem: 19788 +Epoch: [6] [1440/2138] eta: 0:32:40 lr: 4.242491188281221e-05 loss: 0.0498 (0.0595) time: 2.8093 data: 0.0025 max mem: 19788 +Epoch: [6] [1450/2138] eta: 0:32:12 lr: 4.2419552984179025e-05 loss: 0.0465 (0.0595) time: 2.8075 data: 0.0022 max mem: 19788 +Epoch: [6] [1460/2138] eta: 0:31:44 lr: 4.2414194010323185e-05 loss: 0.0500 (0.0595) time: 2.8091 data: 0.0021 max mem: 19788 +Epoch: [6] [1470/2138] eta: 0:31:16 lr: 4.240883496123309e-05 loss: 0.0534 (0.0595) time: 2.8001 data: 0.0024 max mem: 19788 +Epoch: [6] [1480/2138] eta: 0:30:48 lr: 4.2403475836897114e-05 loss: 0.0521 (0.0594) time: 2.7926 data: 0.0028 max mem: 19788 +Epoch: [6] [1490/2138] eta: 0:30:20 lr: 4.239811663730364e-05 loss: 0.0521 (0.0595) time: 2.7934 data: 0.0029 max mem: 19788 +Epoch: [6] [1500/2138] eta: 0:29:52 lr: 4.2392757362441035e-05 loss: 0.0607 (0.0595) time: 2.8041 data: 0.0029 max mem: 19788 +Epoch: [6] [1510/2138] eta: 0:29:24 lr: 4.2387398012297666e-05 loss: 0.0613 (0.0596) time: 2.8128 data: 0.0028 max mem: 19788 +Epoch: [6] [1520/2138] eta: 0:28:56 lr: 4.238203858686191e-05 loss: 0.0513 (0.0595) time: 2.8078 data: 0.0029 max mem: 19788 +Epoch: [6] [1530/2138] eta: 0:28:27 lr: 4.237667908612213e-05 loss: 0.0490 (0.0595) time: 2.8059 data: 0.0025 max mem: 19788 +Epoch: [6] [1540/2138] eta: 0:27:59 lr: 4.237131951006667e-05 loss: 0.0484 (0.0594) time: 2.8106 data: 0.0022 max mem: 19788 +Epoch: [6] [1550/2138] eta: 0:27:31 lr: 4.23659598586839e-05 loss: 0.0480 (0.0594) time: 2.8135 data: 0.0023 max mem: 19788 +Epoch: [6] [1560/2138] eta: 0:27:03 lr: 4.236060013196217e-05 loss: 0.0455 (0.0594) time: 2.8133 data: 0.0021 max mem: 19788 +Epoch: [6] [1570/2138] eta: 0:26:35 lr: 4.235524032988982e-05 loss: 0.0434 (0.0594) time: 2.8111 data: 0.0020 max mem: 19788 +Epoch: [6] [1580/2138] eta: 0:26:07 lr: 4.23498804524552e-05 loss: 0.0536 (0.0594) time: 2.8188 data: 0.0021 max mem: 19788 +Epoch: [6] [1590/2138] eta: 0:25:39 lr: 4.234452049964667e-05 loss: 0.0536 (0.0594) time: 2.8196 data: 0.0023 max mem: 19788 +Epoch: [6] [1600/2138] eta: 0:25:11 lr: 4.233916047145255e-05 loss: 0.0557 (0.0594) time: 2.8029 data: 0.0025 max mem: 19788 +Epoch: [6] [1610/2138] eta: 0:24:43 lr: 4.2333800367861175e-05 loss: 0.0549 (0.0594) time: 2.7961 data: 0.0029 max mem: 19788 +Epoch: [6] [1620/2138] eta: 0:24:15 lr: 4.2328440188860885e-05 loss: 0.0536 (0.0593) time: 2.8033 data: 0.0025 max mem: 19788 +Epoch: [6] [1630/2138] eta: 0:23:46 lr: 4.232307993444001e-05 loss: 0.0469 (0.0593) time: 2.8017 data: 0.0024 max mem: 19788 +Epoch: [6] [1640/2138] eta: 0:23:18 lr: 4.2317719604586864e-05 loss: 0.0467 (0.0593) time: 2.7995 data: 0.0027 max mem: 19788 +Epoch: [6] [1650/2138] eta: 0:22:50 lr: 4.231235919928977e-05 loss: 0.0475 (0.0593) time: 2.8084 data: 0.0029 max mem: 19788 +Epoch: [6] [1660/2138] eta: 0:22:22 lr: 4.2306998718537054e-05 loss: 0.0519 (0.0593) time: 2.8108 data: 0.0029 max mem: 19788 +Epoch: [6] [1670/2138] eta: 0:21:54 lr: 4.230163816231704e-05 loss: 0.0532 (0.0593) time: 2.7993 data: 0.0025 max mem: 19788 +Epoch: [6] [1680/2138] eta: 0:21:26 lr: 4.229627753061802e-05 loss: 0.0532 (0.0593) time: 2.7934 data: 0.0022 max mem: 19788 +Epoch: [6] [1690/2138] eta: 0:20:58 lr: 4.22909168234283e-05 loss: 0.0508 (0.0592) time: 2.7967 data: 0.0024 max mem: 19788 +Epoch: [6] [1700/2138] eta: 0:20:30 lr: 4.2285556040736207e-05 loss: 0.0508 (0.0592) time: 2.7967 data: 0.0024 max mem: 19788 +Epoch: [6] [1710/2138] eta: 0:20:02 lr: 4.228019518253002e-05 loss: 0.0532 (0.0592) time: 2.7999 data: 0.0022 max mem: 19788 +Epoch: [6] [1720/2138] eta: 0:19:34 lr: 4.227483424879804e-05 loss: 0.0547 (0.0592) time: 2.8117 data: 0.0022 max mem: 19788 +Epoch: [6] [1730/2138] eta: 0:19:05 lr: 4.2269473239528576e-05 loss: 0.0524 (0.0593) time: 2.8202 data: 0.0025 max mem: 19788 +Epoch: [6] [1740/2138] eta: 0:18:37 lr: 4.2264112154709904e-05 loss: 0.0524 (0.0592) time: 2.8153 data: 0.0028 max mem: 19788 +Epoch: [6] [1750/2138] eta: 0:18:09 lr: 4.2258750994330316e-05 loss: 0.0550 (0.0592) time: 2.8085 data: 0.0028 max mem: 19788 +Epoch: [6] [1760/2138] eta: 0:17:41 lr: 4.2253389758378096e-05 loss: 0.0550 (0.0592) time: 2.8072 data: 0.0028 max mem: 19788 +Epoch: [6] [1770/2138] eta: 0:17:13 lr: 4.2248028446841514e-05 loss: 0.0531 (0.0592) time: 2.8124 data: 0.0027 max mem: 19788 +Epoch: [6] [1780/2138] eta: 0:16:45 lr: 4.224266705970886e-05 loss: 0.0467 (0.0592) time: 2.8117 data: 0.0025 max mem: 19788 +Epoch: [6] [1790/2138] eta: 0:16:17 lr: 4.223730559696841e-05 loss: 0.0459 (0.0591) time: 2.8113 data: 0.0024 max mem: 19788 +Epoch: [6] [1800/2138] eta: 0:15:49 lr: 4.223194405860842e-05 loss: 0.0483 (0.0592) time: 2.8201 data: 0.0023 max mem: 19788 +Epoch: [6] [1810/2138] eta: 0:15:21 lr: 4.222658244461716e-05 loss: 0.0483 (0.0591) time: 2.8141 data: 0.0024 max mem: 19788 +Epoch: [6] [1820/2138] eta: 0:14:53 lr: 4.22212207549829e-05 loss: 0.0498 (0.0591) time: 2.7998 data: 0.0025 max mem: 19788 +Epoch: [6] [1830/2138] eta: 0:14:25 lr: 4.221585898969389e-05 loss: 0.0485 (0.0590) time: 2.7938 data: 0.0024 max mem: 19788 +Epoch: [6] [1840/2138] eta: 0:13:56 lr: 4.221049714873839e-05 loss: 0.0485 (0.0590) time: 2.7907 data: 0.0021 max mem: 19788 +Epoch: [6] [1850/2138] eta: 0:13:28 lr: 4.2205135232104655e-05 loss: 0.0663 (0.0591) time: 2.7924 data: 0.0021 max mem: 19788 +Epoch: [6] [1860/2138] eta: 0:13:00 lr: 4.2199773239780934e-05 loss: 0.0586 (0.0591) time: 2.7918 data: 0.0021 max mem: 19788 +Epoch: [6] [1870/2138] eta: 0:12:32 lr: 4.2194411171755467e-05 loss: 0.0574 (0.0592) time: 2.7917 data: 0.0021 max mem: 19788 +Epoch: [6] [1880/2138] eta: 0:12:04 lr: 4.2189049028016495e-05 loss: 0.0574 (0.0592) time: 2.7966 data: 0.0022 max mem: 19788 +Epoch: [6] [1890/2138] eta: 0:11:36 lr: 4.2183686808552256e-05 loss: 0.0580 (0.0592) time: 2.8051 data: 0.0022 max mem: 19788 +Epoch: [6] [1900/2138] eta: 0:11:08 lr: 4.2178324513351e-05 loss: 0.0595 (0.0593) time: 2.8102 data: 0.0023 max mem: 19788 +Epoch: [6] [1910/2138] eta: 0:10:40 lr: 4.217296214240094e-05 loss: 0.0531 (0.0592) time: 2.8088 data: 0.0021 max mem: 19788 +Epoch: [6] [1920/2138] eta: 0:10:12 lr: 4.2167599695690314e-05 loss: 0.0547 (0.0593) time: 2.8064 data: 0.0020 max mem: 19788 +Epoch: [6] [1930/2138] eta: 0:09:44 lr: 4.2162237173207344e-05 loss: 0.0595 (0.0593) time: 2.7983 data: 0.0023 max mem: 19788 +Epoch: [6] [1940/2138] eta: 0:09:16 lr: 4.215687457494025e-05 loss: 0.0507 (0.0593) time: 2.7930 data: 0.0027 max mem: 19788 +Epoch: [6] [1950/2138] eta: 0:08:47 lr: 4.215151190087725e-05 loss: 0.0477 (0.0593) time: 2.7907 data: 0.0024 max mem: 19788 +Epoch: [6] [1960/2138] eta: 0:08:19 lr: 4.214614915100655e-05 loss: 0.0447 (0.0592) time: 2.7927 data: 0.0020 max mem: 19788 +Epoch: [6] [1970/2138] eta: 0:07:51 lr: 4.214078632531637e-05 loss: 0.0441 (0.0591) time: 2.7977 data: 0.0019 max mem: 19788 +Epoch: [6] [1980/2138] eta: 0:07:23 lr: 4.2135423423794916e-05 loss: 0.0511 (0.0592) time: 2.7980 data: 0.0021 max mem: 19788 +Epoch: [6] [1990/2138] eta: 0:06:55 lr: 4.213006044643039e-05 loss: 0.0511 (0.0591) time: 2.7967 data: 0.0023 max mem: 19788 +Epoch: [6] [2000/2138] eta: 0:06:27 lr: 4.2124697393210995e-05 loss: 0.0439 (0.0591) time: 2.8024 data: 0.0024 max mem: 19788 +Epoch: [6] [2010/2138] eta: 0:05:59 lr: 4.2119334264124925e-05 loss: 0.0417 (0.0590) time: 2.8123 data: 0.0024 max mem: 19788 +Epoch: [6] [2020/2138] eta: 0:05:31 lr: 4.211397105916037e-05 loss: 0.0519 (0.0591) time: 2.8109 data: 0.0023 max mem: 19788 +Epoch: [6] [2030/2138] eta: 0:05:03 lr: 4.210860777830552e-05 loss: 0.0500 (0.0590) time: 2.8044 data: 0.0021 max mem: 19788 +Epoch: [6] [2040/2138] eta: 0:04:35 lr: 4.210324442154856e-05 loss: 0.0421 (0.0590) time: 2.8091 data: 0.0023 max mem: 19788 +Epoch: [6] [2050/2138] eta: 0:04:07 lr: 4.209788098887768e-05 loss: 0.0433 (0.0590) time: 2.8101 data: 0.0026 max mem: 19788 +Epoch: [6] [2060/2138] eta: 0:03:39 lr: 4.2092517480281054e-05 loss: 0.0471 (0.0589) time: 2.8100 data: 0.0026 max mem: 19788 +Epoch: [6] [2070/2138] eta: 0:03:10 lr: 4.208715389574685e-05 loss: 0.0437 (0.0589) time: 2.8122 data: 0.0027 max mem: 19788 +Epoch: [6] [2080/2138] eta: 0:02:42 lr: 4.208179023526325e-05 loss: 0.0464 (0.0589) time: 2.8079 data: 0.0026 max mem: 19788 +Epoch: [6] [2090/2138] eta: 0:02:14 lr: 4.207642649881842e-05 loss: 0.0471 (0.0588) time: 2.8077 data: 0.0023 max mem: 19788 +Epoch: [6] [2100/2138] eta: 0:01:46 lr: 4.207106268640053e-05 loss: 0.0425 (0.0588) time: 2.8079 data: 0.0021 max mem: 19788 +Epoch: [6] [2110/2138] eta: 0:01:18 lr: 4.206569879799773e-05 loss: 0.0479 (0.0588) time: 2.8135 data: 0.0022 max mem: 19788 +Epoch: [6] [2120/2138] eta: 0:00:50 lr: 4.206033483359817e-05 loss: 0.0501 (0.0588) time: 2.8161 data: 0.0026 max mem: 19788 +Epoch: [6] [2130/2138] eta: 0:00:22 lr: 4.205497079319003e-05 loss: 0.0669 (0.0589) time: 2.8054 data: 0.0025 max mem: 19788 +Epoch: [6] Total time: 1:40:04 +Test: [ 0/21770] eta: 16:03:30 time: 2.6555 data: 2.3707 max mem: 19788 +Test: [ 100/21770] eta: 0:26:14 time: 0.0429 data: 0.0015 max mem: 19788 +Test: [ 200/21770] eta: 0:21:02 time: 0.0462 data: 0.0014 max mem: 19788 +Test: [ 300/21770] eta: 0:19:36 time: 0.0439 data: 0.0016 max mem: 19788 +Test: [ 400/21770] eta: 0:18:38 time: 0.0455 data: 0.0014 max mem: 19788 +Test: [ 500/21770] eta: 0:18:04 time: 0.0425 data: 0.0015 max mem: 19788 +Test: [ 600/21770] eta: 0:17:45 time: 0.0492 data: 0.0017 max mem: 19788 +Test: [ 700/21770] eta: 0:17:21 time: 0.0469 data: 0.0016 max mem: 19788 +Test: [ 800/21770] eta: 0:16:57 time: 0.0421 data: 0.0014 max mem: 19788 +Test: [ 900/21770] eta: 0:16:52 time: 0.0525 data: 0.0019 max mem: 19788 +Test: [ 1000/21770] eta: 0:16:51 time: 0.0510 data: 0.0016 max mem: 19788 +Test: [ 1100/21770] eta: 0:16:41 time: 0.0424 data: 0.0014 max mem: 19788 +Test: [ 1200/21770] eta: 0:16:27 time: 0.0429 data: 0.0016 max mem: 19788 +Test: [ 1300/21770] eta: 0:16:24 time: 0.0462 data: 0.0014 max mem: 19788 +Test: [ 1400/21770] eta: 0:16:13 time: 0.0446 data: 0.0014 max mem: 19788 +Test: [ 1500/21770] eta: 0:16:12 time: 0.0520 data: 0.0018 max mem: 19788 +Test: [ 1600/21770] eta: 0:16:04 time: 0.0437 data: 0.0015 max mem: 19788 +Test: [ 1700/21770] eta: 0:15:56 time: 0.0431 data: 0.0016 max mem: 19788 +Test: [ 1800/21770] eta: 0:15:49 time: 0.0425 data: 0.0015 max mem: 19788 +Test: [ 1900/21770] eta: 0:15:42 time: 0.0420 data: 0.0015 max mem: 19788 +Test: [ 2000/21770] eta: 0:15:33 time: 0.0423 data: 0.0015 max mem: 19788 +Test: [ 2100/21770] eta: 0:15:29 time: 0.0431 data: 0.0014 max mem: 19788 +Test: [ 2200/21770] eta: 0:15:21 time: 0.0426 data: 0.0015 max mem: 19788 +Test: [ 2300/21770] eta: 0:15:14 time: 0.0473 data: 0.0014 max mem: 19788 +Test: [ 2400/21770] eta: 0:15:07 time: 0.0438 data: 0.0013 max mem: 19788 +Test: [ 2500/21770] eta: 0:15:01 time: 0.0435 data: 0.0015 max mem: 19788 +Test: [ 2600/21770] eta: 0:14:57 time: 0.0470 data: 0.0015 max mem: 19788 +Test: [ 2700/21770] eta: 0:14:52 time: 0.0477 data: 0.0014 max mem: 19788 +Test: [ 2800/21770] eta: 0:14:47 time: 0.0497 data: 0.0017 max mem: 19788 +Test: [ 2900/21770] eta: 0:14:45 time: 0.0473 data: 0.0015 max mem: 19788 +Test: [ 3000/21770] eta: 0:14:40 time: 0.0443 data: 0.0014 max mem: 19788 +Test: [ 3100/21770] eta: 0:14:34 time: 0.0443 data: 0.0017 max mem: 19788 +Test: [ 3200/21770] eta: 0:14:30 time: 0.0464 data: 0.0015 max mem: 19788 +Test: [ 3300/21770] eta: 0:14:23 time: 0.0436 data: 0.0014 max mem: 19788 +Test: [ 3400/21770] eta: 0:14:20 time: 0.0483 data: 0.0016 max mem: 19788 +Test: [ 3500/21770] eta: 0:14:14 time: 0.0454 data: 0.0016 max mem: 19788 +Test: [ 3600/21770] eta: 0:14:07 time: 0.0431 data: 0.0015 max mem: 19788 +Test: [ 3700/21770] eta: 0:14:01 time: 0.0430 data: 0.0016 max mem: 19788 +Test: [ 3800/21770] eta: 0:13:56 time: 0.0516 data: 0.0016 max mem: 19788 +Test: [ 3900/21770] eta: 0:13:51 time: 0.0452 data: 0.0013 max mem: 19788 +Test: [ 4000/21770] eta: 0:13:46 time: 0.0504 data: 0.0015 max mem: 19788 +Test: [ 4100/21770] eta: 0:13:42 time: 0.0451 data: 0.0016 max mem: 19788 +Test: [ 4200/21770] eta: 0:13:37 time: 0.0435 data: 0.0015 max mem: 19788 +Test: [ 4300/21770] eta: 0:13:34 time: 0.0486 data: 0.0016 max mem: 19788 +Test: [ 4400/21770] eta: 0:13:30 time: 0.0457 data: 0.0015 max mem: 19788 +Test: [ 4500/21770] eta: 0:13:25 time: 0.0503 data: 0.0014 max mem: 19788 +Test: [ 4600/21770] eta: 0:13:19 time: 0.0427 data: 0.0016 max mem: 19788 +Test: [ 4700/21770] eta: 0:13:14 time: 0.0463 data: 0.0015 max mem: 19788 +Test: [ 4800/21770] eta: 0:13:11 time: 0.0492 data: 0.0015 max mem: 19788 +Test: [ 4900/21770] eta: 0:13:06 time: 0.0439 data: 0.0013 max mem: 19788 +Test: [ 5000/21770] eta: 0:13:00 time: 0.0428 data: 0.0013 max mem: 19788 +Test: [ 5100/21770] eta: 0:12:55 time: 0.0443 data: 0.0016 max mem: 19788 +Test: [ 5200/21770] eta: 0:12:51 time: 0.0459 data: 0.0017 max mem: 19788 +Test: [ 5300/21770] eta: 0:12:46 time: 0.0440 data: 0.0014 max mem: 19788 +Test: [ 5400/21770] eta: 0:12:40 time: 0.0437 data: 0.0014 max mem: 19788 +Test: [ 5500/21770] eta: 0:12:36 time: 0.0448 data: 0.0015 max mem: 19788 +Test: [ 5600/21770] eta: 0:12:31 time: 0.0529 data: 0.0017 max mem: 19788 +Test: [ 5700/21770] eta: 0:12:26 time: 0.0490 data: 0.0017 max mem: 19788 +Test: [ 5800/21770] eta: 0:12:21 time: 0.0434 data: 0.0015 max mem: 19788 +Test: [ 5900/21770] eta: 0:12:17 time: 0.0550 data: 0.0017 max mem: 19788 +Test: [ 6000/21770] eta: 0:12:12 time: 0.0438 data: 0.0015 max mem: 19788 +Test: [ 6100/21770] eta: 0:12:07 time: 0.0498 data: 0.0016 max mem: 19788 +Test: [ 6200/21770] eta: 0:12:02 time: 0.0430 data: 0.0013 max mem: 19788 +Test: [ 6300/21770] eta: 0:11:58 time: 0.0495 data: 0.0016 max mem: 19788 +Test: [ 6400/21770] eta: 0:11:53 time: 0.0423 data: 0.0013 max mem: 19788 +Test: [ 6500/21770] eta: 0:11:49 time: 0.0513 data: 0.0015 max mem: 19788 +Test: [ 6600/21770] eta: 0:11:45 time: 0.0436 data: 0.0014 max mem: 19788 +Test: [ 6700/21770] eta: 0:11:40 time: 0.0519 data: 0.0018 max mem: 19788 +Test: [ 6800/21770] eta: 0:11:35 time: 0.0440 data: 0.0014 max mem: 19788 +Test: [ 6900/21770] eta: 0:11:30 time: 0.0464 data: 0.0013 max mem: 19788 +Test: [ 7000/21770] eta: 0:11:25 time: 0.0436 data: 0.0013 max mem: 19788 +Test: [ 7100/21770] eta: 0:11:20 time: 0.0441 data: 0.0016 max mem: 19788 +Test: [ 7200/21770] eta: 0:11:15 time: 0.0436 data: 0.0015 max mem: 19788 +Test: [ 7300/21770] eta: 0:11:10 time: 0.0476 data: 0.0017 max mem: 19788 +Test: [ 7400/21770] eta: 0:11:06 time: 0.0457 data: 0.0014 max mem: 19788 +Test: [ 7500/21770] eta: 0:11:02 time: 0.0517 data: 0.0015 max mem: 19788 +Test: [ 7600/21770] eta: 0:10:58 time: 0.0458 data: 0.0016 max mem: 19788 +Test: [ 7700/21770] eta: 0:10:53 time: 0.0467 data: 0.0017 max mem: 19788 +Test: [ 7800/21770] eta: 0:10:49 time: 0.0519 data: 0.0018 max mem: 19788 +Test: [ 7900/21770] eta: 0:10:44 time: 0.0488 data: 0.0015 max mem: 19788 +Test: [ 8000/21770] eta: 0:10:40 time: 0.0471 data: 0.0016 max mem: 19788 +Test: [ 8100/21770] eta: 0:10:36 time: 0.0520 data: 0.0017 max mem: 19788 +Test: [ 8200/21770] eta: 0:10:31 time: 0.0474 data: 0.0016 max mem: 19788 +Test: [ 8300/21770] eta: 0:10:26 time: 0.0428 data: 0.0014 max mem: 19788 +Test: [ 8400/21770] eta: 0:10:21 time: 0.0430 data: 0.0015 max mem: 19788 +Test: [ 8500/21770] eta: 0:10:16 time: 0.0462 data: 0.0015 max mem: 19788 +Test: [ 8600/21770] eta: 0:10:13 time: 0.0517 data: 0.0018 max mem: 19788 +Test: [ 8700/21770] eta: 0:10:08 time: 0.0441 data: 0.0014 max mem: 19788 +Test: [ 8800/21770] eta: 0:10:04 time: 0.0461 data: 0.0015 max mem: 19788 +Test: [ 8900/21770] eta: 0:09:59 time: 0.0510 data: 0.0016 max mem: 19788 +Test: [ 9000/21770] eta: 0:09:54 time: 0.0437 data: 0.0013 max mem: 19788 +Test: [ 9100/21770] eta: 0:09:49 time: 0.0430 data: 0.0015 max mem: 19788 +Test: [ 9200/21770] eta: 0:09:44 time: 0.0483 data: 0.0016 max mem: 19788 +Test: [ 9300/21770] eta: 0:09:40 time: 0.0475 data: 0.0015 max mem: 19788 +Test: [ 9400/21770] eta: 0:09:35 time: 0.0477 data: 0.0015 max mem: 19788 +Test: [ 9500/21770] eta: 0:09:30 time: 0.0436 data: 0.0015 max mem: 19788 +Test: [ 9600/21770] eta: 0:09:25 time: 0.0435 data: 0.0015 max mem: 19788 +Test: [ 9700/21770] eta: 0:09:21 time: 0.0526 data: 0.0014 max mem: 19788 +Test: [ 9800/21770] eta: 0:09:16 time: 0.0447 data: 0.0016 max mem: 19788 +Test: [ 9900/21770] eta: 0:09:12 time: 0.0462 data: 0.0015 max mem: 19788 +Test: [10000/21770] eta: 0:09:07 time: 0.0442 data: 0.0015 max mem: 19788 +Test: [10100/21770] eta: 0:09:03 time: 0.0463 data: 0.0016 max mem: 19788 +Test: [10200/21770] eta: 0:08:58 time: 0.0525 data: 0.0015 max mem: 19788 +Test: [10300/21770] eta: 0:08:54 time: 0.0439 data: 0.0014 max mem: 19788 +Test: [10400/21770] eta: 0:08:49 time: 0.0452 data: 0.0015 max mem: 19788 +Test: [10500/21770] eta: 0:08:45 time: 0.0519 data: 0.0017 max mem: 19788 +Test: [10600/21770] eta: 0:08:41 time: 0.0491 data: 0.0017 max mem: 19788 +Test: [10700/21770] eta: 0:08:36 time: 0.0444 data: 0.0014 max mem: 19788 +Test: [10800/21770] eta: 0:08:31 time: 0.0473 data: 0.0015 max mem: 19788 +Test: [10900/21770] eta: 0:08:26 time: 0.0431 data: 0.0013 max mem: 19788 +Test: [11000/21770] eta: 0:08:21 time: 0.0482 data: 0.0016 max mem: 19788 +Test: [11100/21770] eta: 0:08:17 time: 0.0436 data: 0.0014 max mem: 19788 +Test: [11200/21770] eta: 0:08:12 time: 0.0511 data: 0.0014 max mem: 19788 +Test: [11300/21770] eta: 0:08:08 time: 0.0548 data: 0.0017 max mem: 19788 +Test: [11400/21770] eta: 0:08:04 time: 0.0468 data: 0.0016 max mem: 19788 +Test: [11500/21770] eta: 0:07:59 time: 0.0475 data: 0.0015 max mem: 19788 +Test: [11600/21770] eta: 0:07:54 time: 0.0442 data: 0.0014 max mem: 19788 +Test: [11700/21770] eta: 0:07:49 time: 0.0437 data: 0.0014 max mem: 19788 +Test: [11800/21770] eta: 0:07:45 time: 0.0504 data: 0.0016 max mem: 19788 +Test: [11900/21770] eta: 0:07:40 time: 0.0435 data: 0.0014 max mem: 19788 +Test: [12000/21770] eta: 0:07:35 time: 0.0437 data: 0.0016 max mem: 19788 +Test: [12100/21770] eta: 0:07:30 time: 0.0485 data: 0.0016 max mem: 19788 +Test: [12200/21770] eta: 0:07:26 time: 0.0476 data: 0.0016 max mem: 19788 +Test: [12300/21770] eta: 0:07:21 time: 0.0513 data: 0.0017 max mem: 19788 +Test: [12400/21770] eta: 0:07:17 time: 0.0443 data: 0.0014 max mem: 19788 +Test: [12500/21770] eta: 0:07:12 time: 0.0451 data: 0.0017 max mem: 19788 +Test: [12600/21770] eta: 0:07:07 time: 0.0433 data: 0.0015 max mem: 19788 +Test: [12700/21770] eta: 0:07:03 time: 0.0477 data: 0.0015 max mem: 19788 +Test: [12800/21770] eta: 0:06:58 time: 0.0476 data: 0.0016 max mem: 19788 +Test: [12900/21770] eta: 0:06:53 time: 0.0507 data: 0.0016 max mem: 19788 +Test: [13000/21770] eta: 0:06:49 time: 0.0454 data: 0.0015 max mem: 19788 +Test: [13100/21770] eta: 0:06:44 time: 0.0440 data: 0.0016 max mem: 19788 +Test: [13200/21770] eta: 0:06:39 time: 0.0448 data: 0.0013 max mem: 19788 +Test: [13300/21770] eta: 0:06:35 time: 0.0436 data: 0.0015 max mem: 19788 +Test: [13400/21770] eta: 0:06:30 time: 0.0439 data: 0.0014 max mem: 19788 +Test: [13500/21770] eta: 0:06:25 time: 0.0469 data: 0.0013 max mem: 19788 +Test: [13600/21770] eta: 0:06:20 time: 0.0435 data: 0.0013 max mem: 19788 +Test: [13700/21770] eta: 0:06:16 time: 0.0436 data: 0.0014 max mem: 19788 +Test: [13800/21770] eta: 0:06:11 time: 0.0507 data: 0.0017 max mem: 19788 +Test: [13900/21770] eta: 0:06:06 time: 0.0434 data: 0.0014 max mem: 19788 +Test: [14000/21770] eta: 0:06:01 time: 0.0451 data: 0.0014 max mem: 19788 +Test: [14100/21770] eta: 0:05:57 time: 0.0473 data: 0.0015 max mem: 19788 +Test: [14200/21770] eta: 0:05:52 time: 0.0477 data: 0.0016 max mem: 19788 +Test: [14300/21770] eta: 0:05:47 time: 0.0459 data: 0.0017 max mem: 19788 +Test: [14400/21770] eta: 0:05:43 time: 0.0517 data: 0.0017 max mem: 19788 +Test: [14500/21770] eta: 0:05:38 time: 0.0426 data: 0.0013 max mem: 19788 +Test: [14600/21770] eta: 0:05:34 time: 0.0445 data: 0.0016 max mem: 19788 +Test: [14700/21770] eta: 0:05:29 time: 0.0445 data: 0.0014 max mem: 19788 +Test: [14800/21770] eta: 0:05:24 time: 0.0435 data: 0.0015 max mem: 19788 +Test: [14900/21770] eta: 0:05:19 time: 0.0442 data: 0.0014 max mem: 19788 +Test: [15000/21770] eta: 0:05:15 time: 0.0439 data: 0.0016 max mem: 19788 +Test: [15100/21770] eta: 0:05:10 time: 0.0445 data: 0.0014 max mem: 19788 +Test: [15200/21770] eta: 0:05:06 time: 0.0521 data: 0.0017 max mem: 19788 +Test: [15300/21770] eta: 0:05:01 time: 0.0437 data: 0.0015 max mem: 19788 +Test: [15400/21770] eta: 0:04:56 time: 0.0446 data: 0.0014 max mem: 19788 +Test: [15500/21770] eta: 0:04:51 time: 0.0434 data: 0.0015 max mem: 19788 +Test: [15600/21770] eta: 0:04:47 time: 0.0522 data: 0.0019 max mem: 19788 +Test: [15700/21770] eta: 0:04:42 time: 0.0464 data: 0.0016 max mem: 19788 +Test: [15800/21770] eta: 0:04:37 time: 0.0444 data: 0.0015 max mem: 19788 +Test: [15900/21770] eta: 0:04:33 time: 0.0466 data: 0.0015 max mem: 19788 +Test: [16000/21770] eta: 0:04:28 time: 0.0518 data: 0.0018 max mem: 19788 +Test: [16100/21770] eta: 0:04:23 time: 0.0514 data: 0.0018 max mem: 19788 +Test: [16200/21770] eta: 0:04:19 time: 0.0457 data: 0.0016 max mem: 19788 +Test: [16300/21770] eta: 0:04:14 time: 0.0505 data: 0.0016 max mem: 19788 +Test: [16400/21770] eta: 0:04:09 time: 0.0437 data: 0.0014 max mem: 19788 +Test: [16500/21770] eta: 0:04:05 time: 0.0433 data: 0.0015 max mem: 19788 +Test: [16600/21770] eta: 0:04:00 time: 0.0516 data: 0.0017 max mem: 19788 +Test: [16700/21770] eta: 0:03:55 time: 0.0427 data: 0.0014 max mem: 19788 +Test: [16800/21770] eta: 0:03:51 time: 0.0423 data: 0.0013 max mem: 19788 +Test: [16900/21770] eta: 0:03:46 time: 0.0488 data: 0.0015 max mem: 19788 +Test: [17000/21770] eta: 0:03:41 time: 0.0506 data: 0.0015 max mem: 19788 +Test: [17100/21770] eta: 0:03:37 time: 0.0434 data: 0.0015 max mem: 19788 +Test: [17200/21770] eta: 0:03:32 time: 0.0463 data: 0.0015 max mem: 19788 +Test: [17300/21770] eta: 0:03:27 time: 0.0430 data: 0.0014 max mem: 19788 +Test: [17400/21770] eta: 0:03:22 time: 0.0471 data: 0.0016 max mem: 19788 +Test: [17500/21770] eta: 0:03:18 time: 0.0428 data: 0.0015 max mem: 19788 +Test: [17600/21770] eta: 0:03:13 time: 0.0465 data: 0.0015 max mem: 19788 +Test: [17700/21770] eta: 0:03:08 time: 0.0440 data: 0.0015 max mem: 19788 +Test: [17800/21770] eta: 0:03:04 time: 0.0486 data: 0.0014 max mem: 19788 +Test: [17900/21770] eta: 0:02:59 time: 0.0439 data: 0.0015 max mem: 19788 +Test: [18000/21770] eta: 0:02:54 time: 0.0462 data: 0.0017 max mem: 19788 +Test: [18100/21770] eta: 0:02:50 time: 0.0452 data: 0.0014 max mem: 19788 +Test: [18200/21770] eta: 0:02:45 time: 0.0538 data: 0.0017 max mem: 19788 +Test: [18300/21770] eta: 0:02:41 time: 0.0446 data: 0.0015 max mem: 19788 +Test: [18400/21770] eta: 0:02:36 time: 0.0433 data: 0.0016 max mem: 19788 +Test: [18500/21770] eta: 0:02:31 time: 0.0431 data: 0.0014 max mem: 19788 +Test: [18600/21770] eta: 0:02:27 time: 0.0438 data: 0.0015 max mem: 19788 +Test: [18700/21770] eta: 0:02:22 time: 0.0501 data: 0.0018 max mem: 19788 +Test: [18800/21770] eta: 0:02:17 time: 0.0438 data: 0.0015 max mem: 19788 +Test: [18900/21770] eta: 0:02:13 time: 0.0507 data: 0.0016 max mem: 19788 +Test: [19000/21770] eta: 0:02:08 time: 0.0426 data: 0.0013 max mem: 19788 +Test: [19100/21770] eta: 0:02:03 time: 0.0433 data: 0.0014 max mem: 19788 +Test: [19200/21770] eta: 0:01:59 time: 0.0501 data: 0.0017 max mem: 19788 +Test: [19300/21770] eta: 0:01:54 time: 0.0438 data: 0.0014 max mem: 19788 +Test: [19400/21770] eta: 0:01:49 time: 0.0441 data: 0.0016 max mem: 19788 +Test: [19500/21770] eta: 0:01:45 time: 0.0445 data: 0.0015 max mem: 19788 +Test: [19600/21770] eta: 0:01:40 time: 0.0440 data: 0.0013 max mem: 19788 +Test: [19700/21770] eta: 0:01:35 time: 0.0516 data: 0.0016 max mem: 19788 +Test: [19800/21770] eta: 0:01:31 time: 0.0432 data: 0.0014 max mem: 19788 +Test: [19900/21770] eta: 0:01:26 time: 0.0459 data: 0.0014 max mem: 19788 +Test: [20000/21770] eta: 0:01:22 time: 0.0425 data: 0.0014 max mem: 19788 +Test: [20100/21770] eta: 0:01:17 time: 0.0436 data: 0.0015 max mem: 19788 +Test: [20200/21770] eta: 0:01:12 time: 0.0439 data: 0.0014 max mem: 19788 +Test: [20300/21770] eta: 0:01:08 time: 0.0437 data: 0.0015 max mem: 19788 +Test: [20400/21770] eta: 0:01:03 time: 0.0467 data: 0.0015 max mem: 19788 +Test: [20500/21770] eta: 0:00:58 time: 0.0442 data: 0.0014 max mem: 19788 +Test: [20600/21770] eta: 0:00:54 time: 0.0492 data: 0.0014 max mem: 19788 +Test: [20700/21770] eta: 0:00:49 time: 0.0468 data: 0.0014 max mem: 19788 +Test: [20800/21770] eta: 0:00:44 time: 0.0480 data: 0.0015 max mem: 19788 +Test: [20900/21770] eta: 0:00:40 time: 0.0438 data: 0.0015 max mem: 19788 +Test: [21000/21770] eta: 0:00:35 time: 0.0430 data: 0.0014 max mem: 19788 +Test: [21100/21770] eta: 0:00:31 time: 0.0521 data: 0.0016 max mem: 19788 +Test: [21200/21770] eta: 0:00:26 time: 0.0437 data: 0.0016 max mem: 19788 +Test: [21300/21770] eta: 0:00:21 time: 0.0485 data: 0.0016 max mem: 19788 +Test: [21400/21770] eta: 0:00:17 time: 0.0475 data: 0.0016 max mem: 19788 +Test: [21500/21770] eta: 0:00:12 time: 0.0440 data: 0.0015 max mem: 19788 +Test: [21600/21770] eta: 0:00:07 time: 0.0448 data: 0.0014 max mem: 19788 +Test: [21700/21770] eta: 0:00:03 time: 0.0437 data: 0.0013 max mem: 19788 +Test: Total time: 0:16:48 +Final results: +Mean IoU is 62.05 + + precision@0.5 = 68.84 + precision@0.6 = 62.67 + precision@0.7 = 55.16 + precision@0.8 = 43.63 + precision@0.9 = 20.75 + overall IoU = 63.44 + mean IoU = 62.05 + +Mean accuracy for one-to-zero sample is 77.40 + +Average object IoU 0.6204715497000163 +Overall IoU 63.440696716308594 +Better epoch: 6 + +Epoch: [7] [ 0/2138] eta: 8:08:58 lr: 4.2050679506129375e-05 loss: 0.1198 (0.1198) time: 13.7222 data: 1.8440 max mem: 19788 +Epoch: [7] [ 10/2138] eta: 2:15:06 lr: 4.20453153288759e-05 loss: 0.0613 (0.0624) time: 3.8097 data: 0.1697 max mem: 19788 +Epoch: [7] [ 20/2138] eta: 1:57:52 lr: 4.2039951075580645e-05 loss: 0.0528 (0.0607) time: 2.8199 data: 0.0019 max mem: 19788 +Epoch: [7] [ 30/2138] eta: 1:51:23 lr: 4.2034586746231765e-05 loss: 0.0564 (0.0598) time: 2.8188 data: 0.0019 max mem: 19788 +Epoch: [7] [ 40/2138] eta: 1:47:51 lr: 4.202922234081736e-05 loss: 0.0501 (0.0590) time: 2.8178 data: 0.0022 max mem: 19788 +Epoch: [7] [ 50/2138] eta: 1:45:33 lr: 4.20238578593256e-05 loss: 0.0458 (0.0579) time: 2.8202 data: 0.0021 max mem: 19788 +Epoch: [7] [ 60/2138] eta: 1:43:42 lr: 4.20184933017446e-05 loss: 0.0513 (0.0582) time: 2.8092 data: 0.0020 max mem: 19788 +Epoch: [7] [ 70/2138] eta: 1:42:13 lr: 4.20131286680625e-05 loss: 0.0498 (0.0571) time: 2.7941 data: 0.0021 max mem: 19788 +Epoch: [7] [ 80/2138] eta: 1:41:01 lr: 4.2007763958267394e-05 loss: 0.0435 (0.0567) time: 2.7957 data: 0.0022 max mem: 19788 +Epoch: [7] [ 90/2138] eta: 1:39:58 lr: 4.200239917234743e-05 loss: 0.0451 (0.0566) time: 2.7990 data: 0.0023 max mem: 19788 +Epoch: [7] [ 100/2138] eta: 1:39:03 lr: 4.1997034310290704e-05 loss: 0.0511 (0.0569) time: 2.7993 data: 0.0021 max mem: 19788 +Epoch: [7] [ 110/2138] eta: 1:38:15 lr: 4.1991669372085346e-05 loss: 0.0571 (0.0578) time: 2.8070 data: 0.0022 max mem: 19788 +Epoch: [7] [ 120/2138] eta: 1:37:30 lr: 4.1986304357719455e-05 loss: 0.0522 (0.0574) time: 2.8118 data: 0.0022 max mem: 19788 +Epoch: [7] [ 130/2138] eta: 1:36:45 lr: 4.198093926718114e-05 loss: 0.0482 (0.0567) time: 2.8035 data: 0.0023 max mem: 19788 +Epoch: [7] [ 140/2138] eta: 1:36:03 lr: 4.1975574100458494e-05 loss: 0.0482 (0.0570) time: 2.7978 data: 0.0023 max mem: 19788 +Epoch: [7] [ 150/2138] eta: 1:35:23 lr: 4.197020885753963e-05 loss: 0.0502 (0.0566) time: 2.7969 data: 0.0021 max mem: 19788 +Epoch: [7] [ 160/2138] eta: 1:34:43 lr: 4.196484353841262e-05 loss: 0.0502 (0.0565) time: 2.7933 data: 0.0022 max mem: 19788 +Epoch: [7] [ 170/2138] eta: 1:34:05 lr: 4.195947814306559e-05 loss: 0.0562 (0.0566) time: 2.7917 data: 0.0023 max mem: 19788 +Epoch: [7] [ 180/2138] eta: 1:33:30 lr: 4.1954112671486594e-05 loss: 0.0514 (0.0564) time: 2.8005 data: 0.0024 max mem: 19788 +Epoch: [7] [ 190/2138] eta: 1:32:55 lr: 4.194874712366374e-05 loss: 0.0462 (0.0560) time: 2.8078 data: 0.0025 max mem: 19788 +Epoch: [7] [ 200/2138] eta: 1:32:22 lr: 4.194338149958509e-05 loss: 0.0434 (0.0555) time: 2.8093 data: 0.0023 max mem: 19788 +Epoch: [7] [ 210/2138] eta: 1:31:49 lr: 4.193801579923874e-05 loss: 0.0435 (0.0554) time: 2.8122 data: 0.0021 max mem: 19788 +Epoch: [7] [ 220/2138] eta: 1:31:17 lr: 4.1932650022612746e-05 loss: 0.0435 (0.0551) time: 2.8143 data: 0.0021 max mem: 19788 +Epoch: [7] [ 230/2138] eta: 1:30:44 lr: 4.192728416969519e-05 loss: 0.0481 (0.0554) time: 2.8134 data: 0.0023 max mem: 19788 +Epoch: [7] [ 240/2138] eta: 1:30:13 lr: 4.1921918240474116e-05 loss: 0.0544 (0.0553) time: 2.8121 data: 0.0026 max mem: 19788 +Epoch: [7] [ 250/2138] eta: 1:29:41 lr: 4.1916552234937625e-05 loss: 0.0458 (0.0551) time: 2.8137 data: 0.0027 max mem: 19788 +Epoch: [7] [ 260/2138] eta: 1:29:11 lr: 4.191118615307374e-05 loss: 0.0458 (0.0549) time: 2.8196 data: 0.0024 max mem: 19788 +Epoch: [7] [ 270/2138] eta: 1:28:40 lr: 4.190581999487054e-05 loss: 0.0460 (0.0547) time: 2.8227 data: 0.0021 max mem: 19788 +Epoch: [7] [ 280/2138] eta: 1:28:10 lr: 4.190045376031607e-05 loss: 0.0432 (0.0545) time: 2.8169 data: 0.0021 max mem: 19788 +Epoch: [7] [ 290/2138] eta: 1:27:39 lr: 4.1895087449398374e-05 loss: 0.0501 (0.0546) time: 2.8117 data: 0.0022 max mem: 19788 +Epoch: [7] [ 300/2138] eta: 1:27:08 lr: 4.18897210621055e-05 loss: 0.0521 (0.0546) time: 2.8110 data: 0.0025 max mem: 19788 +Epoch: [7] [ 310/2138] eta: 1:26:38 lr: 4.188435459842549e-05 loss: 0.0425 (0.0541) time: 2.8136 data: 0.0025 max mem: 19788 +Epoch: [7] [ 320/2138] eta: 1:26:08 lr: 4.187898805834638e-05 loss: 0.0409 (0.0538) time: 2.8105 data: 0.0025 max mem: 19788 +Epoch: [7] [ 330/2138] eta: 1:25:37 lr: 4.187362144185621e-05 loss: 0.0466 (0.0538) time: 2.8075 data: 0.0028 max mem: 19788 +Epoch: [7] [ 340/2138] eta: 1:25:07 lr: 4.1868254748943e-05 loss: 0.0466 (0.0537) time: 2.8117 data: 0.0026 max mem: 19788 +Epoch: [7] [ 350/2138] eta: 1:24:37 lr: 4.186288797959478e-05 loss: 0.0424 (0.0535) time: 2.8083 data: 0.0022 max mem: 19788 +Epoch: [7] [ 360/2138] eta: 1:24:06 lr: 4.185752113379959e-05 loss: 0.0468 (0.0539) time: 2.7949 data: 0.0021 max mem: 19788 +Epoch: [7] [ 370/2138] eta: 1:23:35 lr: 4.185215421154543e-05 loss: 0.0500 (0.0540) time: 2.7892 data: 0.0022 max mem: 19788 +Epoch: [7] [ 380/2138] eta: 1:23:05 lr: 4.184678721282031e-05 loss: 0.0468 (0.0539) time: 2.7923 data: 0.0022 max mem: 19788 +Epoch: [7] [ 390/2138] eta: 1:22:35 lr: 4.184142013761227e-05 loss: 0.0437 (0.0535) time: 2.7963 data: 0.0024 max mem: 19788 +Epoch: [7] [ 400/2138] eta: 1:22:05 lr: 4.1836052985909304e-05 loss: 0.0452 (0.0536) time: 2.7955 data: 0.0027 max mem: 19788 +Epoch: [7] [ 410/2138] eta: 1:21:35 lr: 4.183068575769941e-05 loss: 0.0512 (0.0537) time: 2.7995 data: 0.0027 max mem: 19788 +Epoch: [7] [ 420/2138] eta: 1:21:06 lr: 4.1825318452970604e-05 loss: 0.0469 (0.0536) time: 2.8056 data: 0.0026 max mem: 19788 +Epoch: [7] [ 430/2138] eta: 1:20:36 lr: 4.1819951071710875e-05 loss: 0.0453 (0.0535) time: 2.7994 data: 0.0026 max mem: 19788 +Epoch: [7] [ 440/2138] eta: 1:20:06 lr: 4.181458361390822e-05 loss: 0.0453 (0.0536) time: 2.7945 data: 0.0024 max mem: 19788 +Epoch: [7] [ 450/2138] eta: 1:19:37 lr: 4.180921607955063e-05 loss: 0.0501 (0.0535) time: 2.7952 data: 0.0022 max mem: 19788 +Epoch: [7] [ 460/2138] eta: 1:19:07 lr: 4.18038484686261e-05 loss: 0.0486 (0.0534) time: 2.7931 data: 0.0020 max mem: 19788 +Epoch: [7] [ 470/2138] eta: 1:18:37 lr: 4.17984807811226e-05 loss: 0.0402 (0.0534) time: 2.7933 data: 0.0020 max mem: 19788 +Epoch: [7] [ 480/2138] eta: 1:18:08 lr: 4.179311301702812e-05 loss: 0.0534 (0.0537) time: 2.7979 data: 0.0021 max mem: 19788 +Epoch: [7] [ 490/2138] eta: 1:17:39 lr: 4.178774517633063e-05 loss: 0.0541 (0.0538) time: 2.8075 data: 0.0023 max mem: 19788 +Epoch: [7] [ 500/2138] eta: 1:17:11 lr: 4.178237725901812e-05 loss: 0.0495 (0.0538) time: 2.8124 data: 0.0023 max mem: 19788 +Epoch: [7] [ 510/2138] eta: 1:16:42 lr: 4.177700926507853e-05 loss: 0.0444 (0.0537) time: 2.8071 data: 0.0023 max mem: 19788 +Epoch: [7] [ 520/2138] eta: 1:16:13 lr: 4.177164119449986e-05 loss: 0.0481 (0.0537) time: 2.8058 data: 0.0023 max mem: 19788 +Epoch: [7] [ 530/2138] eta: 1:15:44 lr: 4.176627304727005e-05 loss: 0.0460 (0.0535) time: 2.8084 data: 0.0024 max mem: 19788 +Epoch: [7] [ 540/2138] eta: 1:15:15 lr: 4.176090482337706e-05 loss: 0.0459 (0.0533) time: 2.8096 data: 0.0025 max mem: 19788 +Epoch: [7] [ 550/2138] eta: 1:14:47 lr: 4.175553652280884e-05 loss: 0.0472 (0.0536) time: 2.8110 data: 0.0024 max mem: 19788 +Epoch: [7] [ 560/2138] eta: 1:14:18 lr: 4.175016814555337e-05 loss: 0.0587 (0.0537) time: 2.8148 data: 0.0022 max mem: 19788 +Epoch: [7] [ 570/2138] eta: 1:13:49 lr: 4.174479969159857e-05 loss: 0.0504 (0.0536) time: 2.8156 data: 0.0023 max mem: 19788 +Epoch: [7] [ 580/2138] eta: 1:13:20 lr: 4.1739431160932384e-05 loss: 0.0518 (0.0538) time: 2.8019 data: 0.0023 max mem: 19788 +Epoch: [7] [ 590/2138] eta: 1:12:51 lr: 4.173406255354277e-05 loss: 0.0476 (0.0537) time: 2.7884 data: 0.0023 max mem: 19788 +Epoch: [7] [ 600/2138] eta: 1:12:22 lr: 4.1728693869417656e-05 loss: 0.0484 (0.0537) time: 2.7929 data: 0.0024 max mem: 19788 +Epoch: [7] [ 610/2138] eta: 1:11:53 lr: 4.172332510854498e-05 loss: 0.0484 (0.0537) time: 2.8020 data: 0.0025 max mem: 19788 +Epoch: [7] [ 620/2138] eta: 1:11:25 lr: 4.1717956270912655e-05 loss: 0.0484 (0.0537) time: 2.8020 data: 0.0028 max mem: 19788 +Epoch: [7] [ 630/2138] eta: 1:10:56 lr: 4.171258735650862e-05 loss: 0.0526 (0.0539) time: 2.7999 data: 0.0026 max mem: 19788 +Epoch: [7] [ 640/2138] eta: 1:10:27 lr: 4.1707218365320806e-05 loss: 0.0488 (0.0538) time: 2.8072 data: 0.0025 max mem: 19788 +Epoch: [7] [ 650/2138] eta: 1:09:59 lr: 4.170184929733713e-05 loss: 0.0420 (0.0537) time: 2.8069 data: 0.0024 max mem: 19788 +Epoch: [7] [ 660/2138] eta: 1:09:30 lr: 4.169648015254548e-05 loss: 0.0441 (0.0537) time: 2.7958 data: 0.0021 max mem: 19788 +Epoch: [7] [ 670/2138] eta: 1:09:01 lr: 4.1691110930933796e-05 loss: 0.0413 (0.0536) time: 2.7957 data: 0.0020 max mem: 19788 +Epoch: [7] [ 680/2138] eta: 1:08:32 lr: 4.1685741632489976e-05 loss: 0.0343 (0.0534) time: 2.7954 data: 0.0020 max mem: 19788 +Epoch: [7] [ 690/2138] eta: 1:08:03 lr: 4.168037225720193e-05 loss: 0.0418 (0.0533) time: 2.7891 data: 0.0021 max mem: 19788 +Epoch: [7] [ 700/2138] eta: 1:07:35 lr: 4.1675002805057554e-05 loss: 0.0431 (0.0532) time: 2.7914 data: 0.0022 max mem: 19788 +Epoch: [7] [ 710/2138] eta: 1:07:06 lr: 4.166963327604475e-05 loss: 0.0476 (0.0532) time: 2.8018 data: 0.0027 max mem: 19788 +Epoch: [7] [ 720/2138] eta: 1:06:38 lr: 4.16642636701514e-05 loss: 0.0448 (0.0531) time: 2.8098 data: 0.0028 max mem: 19788 +Epoch: [7] [ 730/2138] eta: 1:06:10 lr: 4.1658893987365405e-05 loss: 0.0448 (0.0531) time: 2.8128 data: 0.0025 max mem: 19788 +Epoch: [7] [ 740/2138] eta: 1:05:41 lr: 4.165352422767464e-05 loss: 0.0531 (0.0532) time: 2.8123 data: 0.0024 max mem: 19788 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mem: 19788 +Epoch: [7] [ 830/2138] eta: 1:01:26 lr: 4.1605192927742886e-05 loss: 0.0454 (0.0529) time: 2.8073 data: 0.0022 max mem: 19788 +Epoch: [7] [ 840/2138] eta: 1:00:58 lr: 4.159982239833744e-05 loss: 0.0408 (0.0528) time: 2.8079 data: 0.0023 max mem: 19788 +Epoch: [7] [ 850/2138] eta: 1:00:29 lr: 4.159445179189373e-05 loss: 0.0424 (0.0528) time: 2.8094 data: 0.0025 max mem: 19788 +Epoch: [7] [ 860/2138] eta: 1:00:01 lr: 4.15890811083996e-05 loss: 0.0387 (0.0527) time: 2.8109 data: 0.0025 max mem: 19788 +Epoch: [7] [ 870/2138] eta: 0:59:33 lr: 4.158371034784291e-05 loss: 0.0436 (0.0527) time: 2.8139 data: 0.0027 max mem: 19788 +Epoch: [7] [ 880/2138] eta: 0:59:05 lr: 4.157833951021147e-05 loss: 0.0500 (0.0526) time: 2.8240 data: 0.0026 max mem: 19788 +Epoch: [7] [ 890/2138] eta: 0:58:37 lr: 4.157296859549312e-05 loss: 0.0438 (0.0526) time: 2.8188 data: 0.0025 max mem: 19788 +Epoch: [7] [ 900/2138] eta: 0:58:08 lr: 4.1567597603675696e-05 loss: 0.0438 (0.0525) time: 2.7983 data: 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2.7981 data: 0.0022 max mem: 19788 +Epoch: [7] [ 990/2138] eta: 0:53:53 lr: 4.151925520584994e-05 loss: 0.0468 (0.0523) time: 2.7959 data: 0.0024 max mem: 19788 +Epoch: [7] [1000/2138] eta: 0:53:24 lr: 4.151388344237142e-05 loss: 0.0401 (0.0522) time: 2.7947 data: 0.0027 max mem: 19788 +Epoch: [7] [1010/2138] eta: 0:52:56 lr: 4.150851160165968e-05 loss: 0.0517 (0.0523) time: 2.7964 data: 0.0025 max mem: 19788 +Epoch: [7] [1020/2138] eta: 0:52:28 lr: 4.15031396837025e-05 loss: 0.0493 (0.0522) time: 2.8038 data: 0.0022 max mem: 19788 +Epoch: [7] [1030/2138] eta: 0:51:59 lr: 4.149776768848766e-05 loss: 0.0440 (0.0522) time: 2.8140 data: 0.0023 max mem: 19788 +Epoch: [7] [1040/2138] eta: 0:51:31 lr: 4.1492395616002945e-05 loss: 0.0471 (0.0522) time: 2.8143 data: 0.0023 max mem: 19788 +Epoch: [7] [1050/2138] eta: 0:51:03 lr: 4.1487023466236113e-05 loss: 0.0468 (0.0522) time: 2.8142 data: 0.0022 max mem: 19788 +Epoch: [7] [1060/2138] eta: 0:50:35 lr: 4.148165123917496e-05 loss: 0.0439 (0.0522) time: 2.8130 data: 0.0025 max mem: 19788 +Epoch: [7] [1070/2138] eta: 0:50:07 lr: 4.147627893480722e-05 loss: 0.0482 (0.0522) time: 2.8059 data: 0.0027 max mem: 19788 +Epoch: [7] [1080/2138] eta: 0:49:38 lr: 4.147090655312067e-05 loss: 0.0423 (0.0521) time: 2.8025 data: 0.0025 max mem: 19788 +Epoch: [7] [1090/2138] eta: 0:49:10 lr: 4.146553409410306e-05 loss: 0.0432 (0.0521) time: 2.8064 data: 0.0023 max mem: 19788 +Epoch: [7] [1100/2138] eta: 0:48:42 lr: 4.146016155774215e-05 loss: 0.0500 (0.0522) time: 2.8188 data: 0.0022 max mem: 19788 +Epoch: [7] [1110/2138] eta: 0:48:14 lr: 4.1454788944025696e-05 loss: 0.0529 (0.0522) time: 2.8199 data: 0.0023 max mem: 19788 +Epoch: [7] [1120/2138] eta: 0:47:46 lr: 4.144941625294144e-05 loss: 0.0529 (0.0522) time: 2.8140 data: 0.0025 max mem: 19788 +Epoch: [7] [1130/2138] eta: 0:47:18 lr: 4.144404348447712e-05 loss: 0.0451 (0.0521) time: 2.8128 data: 0.0026 max mem: 19788 +Epoch: [7] [1140/2138] eta: 0:46:49 lr: 4.1438670638620475e-05 loss: 0.0489 (0.0521) time: 2.8087 data: 0.0026 max mem: 19788 +Epoch: [7] [1150/2138] eta: 0:46:21 lr: 4.143329771535925e-05 loss: 0.0466 (0.0520) time: 2.8043 data: 0.0026 max mem: 19788 +Epoch: [7] [1160/2138] eta: 0:45:53 lr: 4.142792471468116e-05 loss: 0.0427 (0.0520) time: 2.8035 data: 0.0026 max mem: 19788 +Epoch: [7] [1170/2138] eta: 0:45:25 lr: 4.142255163657395e-05 loss: 0.0427 (0.0519) time: 2.8054 data: 0.0024 max mem: 19788 +Epoch: [7] [1180/2138] eta: 0:44:56 lr: 4.141717848102533e-05 loss: 0.0494 (0.0520) time: 2.8095 data: 0.0023 max mem: 19788 +Epoch: [7] [1190/2138] eta: 0:44:28 lr: 4.141180524802304e-05 loss: 0.0538 (0.0519) time: 2.8103 data: 0.0024 max mem: 19788 +Epoch: [7] [1200/2138] eta: 0:44:00 lr: 4.140643193755477e-05 loss: 0.0374 (0.0519) time: 2.8071 data: 0.0027 max mem: 19788 +Epoch: [7] [1210/2138] eta: 0:43:32 lr: 4.1401058549608255e-05 loss: 0.0495 (0.0520) time: 2.8363 data: 0.0029 max mem: 19788 +Epoch: [7] [1220/2138] eta: 0:43:05 lr: 4.1395685084171195e-05 loss: 0.0435 (0.0519) time: 2.9184 data: 0.0029 max mem: 19788 +Epoch: [7] [1230/2138] eta: 0:42:41 lr: 4.139031154123131e-05 loss: 0.0441 (0.0519) time: 3.1310 data: 0.0026 max mem: 19788 +Epoch: [7] [1240/2138] eta: 0:42:16 lr: 4.138493792077627e-05 loss: 0.0469 (0.0518) time: 3.2940 data: 0.0024 max mem: 19788 +Epoch: [7] [1250/2138] eta: 0:41:53 lr: 4.13795642227938e-05 loss: 0.0484 (0.0519) time: 3.4586 data: 0.0024 max mem: 19788 +Epoch: [7] [1260/2138] eta: 0:41:28 lr: 4.13741904472716e-05 loss: 0.0425 (0.0518) time: 3.4503 data: 0.0024 max mem: 19788 +Epoch: [7] [1270/2138] eta: 0:41:04 lr: 4.136881659419734e-05 loss: 0.0440 (0.0519) time: 3.3673 data: 0.0026 max mem: 19788 +Epoch: [7] [1280/2138] eta: 0:40:41 lr: 4.136344266355871e-05 loss: 0.0519 (0.0519) time: 3.5472 data: 0.0026 max mem: 19788 +Epoch: [7] [1290/2138] eta: 0:40:16 lr: 4.1358068655343407e-05 loss: 0.0482 (0.0519) time: 3.5019 data: 0.0028 max mem: 19788 +Epoch: [7] [1300/2138] eta: 0:39:51 lr: 4.135269456953909e-05 loss: 0.0453 (0.0519) time: 3.4220 data: 0.0028 max mem: 19788 +Epoch: [7] [1310/2138] eta: 0:39:25 lr: 4.134732040613346e-05 loss: 0.0433 (0.0519) time: 3.3419 data: 0.0025 max mem: 19788 +Epoch: [7] [1320/2138] eta: 0:38:59 lr: 4.134194616511417e-05 loss: 0.0477 (0.0519) time: 3.2257 data: 0.0028 max mem: 19788 +Epoch: [7] [1330/2138] eta: 0:38:33 lr: 4.13365718464689e-05 loss: 0.0476 (0.0519) time: 3.2821 data: 0.0027 max mem: 19788 +Epoch: [7] [1340/2138] eta: 0:38:06 lr: 4.13311974501853e-05 loss: 0.0519 (0.0520) time: 3.2607 data: 0.0027 max mem: 19788 +Epoch: [7] [1350/2138] eta: 0:37:42 lr: 4.132582297625105e-05 loss: 0.0590 (0.0520) time: 3.4165 data: 0.0029 max mem: 19788 +Epoch: [7] [1360/2138] eta: 0:37:17 lr: 4.1320448424653784e-05 loss: 0.0562 (0.0520) time: 3.5651 data: 0.0026 max mem: 19788 +Epoch: [7] [1370/2138] eta: 0:36:50 lr: 4.131507379538118e-05 loss: 0.0489 (0.0521) time: 3.3569 data: 0.0023 max mem: 19788 +Epoch: [7] [1380/2138] eta: 0:36:24 lr: 4.1309699088420874e-05 loss: 0.0509 (0.0521) time: 3.2884 data: 0.0023 max mem: 19788 +Epoch: [7] [1390/2138] eta: 0:35:59 lr: 4.130432430376052e-05 loss: 0.0462 (0.0520) time: 3.4642 data: 0.0024 max mem: 19788 +Epoch: [7] [1400/2138] eta: 0:35:31 lr: 4.129894944138774e-05 loss: 0.0469 (0.0520) time: 3.3294 data: 0.0025 max mem: 19788 +Epoch: [7] [1410/2138] eta: 0:35:04 lr: 4.1293574501290195e-05 loss: 0.0476 (0.0519) time: 3.1960 data: 0.0027 max mem: 19788 +Epoch: [7] [1420/2138] eta: 0:34:37 lr: 4.128819948345551e-05 loss: 0.0378 (0.0519) time: 3.2770 data: 0.0029 max mem: 19788 +Epoch: [7] [1430/2138] eta: 0:34:09 lr: 4.128282438787132e-05 loss: 0.0458 (0.0519) time: 3.1793 data: 0.0028 max mem: 19788 +Epoch: [7] [1440/2138] eta: 0:33:42 lr: 4.127744921452524e-05 loss: 0.0458 (0.0519) time: 3.1268 data: 0.0026 max mem: 19788 +Epoch: [7] [1450/2138] eta: 0:33:15 lr: 4.1272073963404914e-05 loss: 0.0424 (0.0519) time: 3.2151 data: 0.0025 max mem: 19788 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mem: 19788 +Epoch: [7] [1540/2138] eta: 0:29:11 lr: 4.1223693201436345e-05 loss: 0.0448 (0.0520) time: 3.1561 data: 0.0032 max mem: 19788 +Epoch: [7] [1550/2138] eta: 0:28:43 lr: 4.121831717189189e-05 loss: 0.0485 (0.0520) time: 3.2164 data: 0.0033 max mem: 19788 +Epoch: [7] [1560/2138] eta: 0:28:14 lr: 4.121294106443679e-05 loss: 0.0531 (0.0520) time: 3.2359 data: 0.0027 max mem: 19788 +Epoch: [7] [1570/2138] eta: 0:27:47 lr: 4.120756487905862e-05 loss: 0.0482 (0.0520) time: 3.2900 data: 0.0024 max mem: 19788 +Epoch: [7] [1580/2138] eta: 0:27:20 lr: 4.120218861574496e-05 loss: 0.0451 (0.0519) time: 3.4797 data: 0.0024 max mem: 19788 +Epoch: [7] [1590/2138] eta: 0:26:52 lr: 4.119681227448336e-05 loss: 0.0530 (0.0520) time: 3.4551 data: 0.0025 max mem: 19788 +Epoch: [7] [1600/2138] eta: 0:26:23 lr: 4.119143585526142e-05 loss: 0.0579 (0.0520) time: 3.2642 data: 0.0028 max mem: 19788 +Epoch: [7] [1610/2138] eta: 0:25:55 lr: 4.118605935806667e-05 loss: 0.0474 (0.0520) time: 3.1988 data: 0.0029 max mem: 19788 +Epoch: [7] [1620/2138] eta: 0:25:26 lr: 4.118068278288669e-05 loss: 0.0424 (0.0519) time: 3.2539 data: 0.0033 max mem: 19788 +Epoch: [7] [1630/2138] eta: 0:24:57 lr: 4.1175306129709017e-05 loss: 0.0405 (0.0519) time: 3.2153 data: 0.0034 max mem: 19788 +Epoch: [7] [1640/2138] eta: 0:24:28 lr: 4.116992939852122e-05 loss: 0.0474 (0.0519) time: 3.1337 data: 0.0027 max mem: 19788 +Epoch: [7] [1650/2138] eta: 0:24:00 lr: 4.116455258931084e-05 loss: 0.0501 (0.0518) time: 3.2244 data: 0.0027 max mem: 19788 +Epoch: [7] [1660/2138] eta: 0:23:31 lr: 4.115917570206543e-05 loss: 0.0481 (0.0518) time: 3.2749 data: 0.0027 max mem: 19788 +Epoch: [7] [1670/2138] eta: 0:23:02 lr: 4.115379873677251e-05 loss: 0.0428 (0.0518) time: 3.0896 data: 0.0024 max mem: 19788 +Epoch: [7] [1680/2138] eta: 0:22:32 lr: 4.114842169341963e-05 loss: 0.0426 (0.0517) time: 2.9624 data: 0.0023 max mem: 19788 +Epoch: [7] [1690/2138] eta: 0:22:03 lr: 4.1143044571994325e-05 loss: 0.0418 (0.0517) time: 3.0310 data: 0.0022 max mem: 19788 +Epoch: [7] [1700/2138] eta: 0:21:34 lr: 4.1137667372484115e-05 loss: 0.0421 (0.0517) time: 3.1456 data: 0.0024 max mem: 19788 +Epoch: [7] [1710/2138] eta: 0:21:05 lr: 4.113229009487654e-05 loss: 0.0421 (0.0517) time: 3.0681 data: 0.0026 max mem: 19788 +Epoch: [7] [1720/2138] eta: 0:20:35 lr: 4.11269127391591e-05 loss: 0.0520 (0.0516) time: 2.9914 data: 0.0026 max mem: 19788 +Epoch: [7] [1730/2138] eta: 0:20:06 lr: 4.112153530531933e-05 loss: 0.0537 (0.0517) time: 3.1697 data: 0.0026 max mem: 19788 +Epoch: [7] [1740/2138] eta: 0:19:37 lr: 4.111615779334473e-05 loss: 0.0492 (0.0516) time: 3.1004 data: 0.0025 max mem: 19788 +Epoch: [7] [1750/2138] eta: 0:19:07 lr: 4.111078020322282e-05 loss: 0.0434 (0.0517) time: 2.9386 data: 0.0023 max mem: 19788 +Epoch: [7] [1760/2138] eta: 0:18:38 lr: 4.110540253494111e-05 loss: 0.0543 (0.0517) time: 3.0577 data: 0.0024 max mem: 19788 +Epoch: [7] [1770/2138] eta: 0:18:08 lr: 4.110002478848709e-05 loss: 0.0527 (0.0517) time: 3.0630 data: 0.0025 max mem: 19788 +Epoch: [7] [1780/2138] eta: 0:17:39 lr: 4.109464696384826e-05 loss: 0.0398 (0.0516) time: 2.9343 data: 0.0022 max mem: 19788 +Epoch: [7] [1790/2138] eta: 0:17:09 lr: 4.108926906101212e-05 loss: 0.0449 (0.0517) time: 3.0056 data: 0.0023 max mem: 19788 +Epoch: [7] [1800/2138] eta: 0:16:40 lr: 4.1083891079966155e-05 loss: 0.0505 (0.0517) time: 3.1907 data: 0.0025 max mem: 19788 +Epoch: [7] [1810/2138] eta: 0:16:11 lr: 4.107851302069786e-05 loss: 0.0466 (0.0517) time: 3.0843 data: 0.0026 max mem: 19788 +Epoch: [7] [1820/2138] eta: 0:15:41 lr: 4.107313488319471e-05 loss: 0.0447 (0.0517) time: 2.9148 data: 0.0027 max mem: 19788 +Epoch: [7] [1830/2138] eta: 0:15:12 lr: 4.106775666744419e-05 loss: 0.0477 (0.0517) time: 3.0784 data: 0.0026 max mem: 19788 +Epoch: [7] [1840/2138] eta: 0:14:42 lr: 4.1062378373433775e-05 loss: 0.0441 (0.0517) time: 3.1402 data: 0.0025 max mem: 19788 +Epoch: [7] [1850/2138] eta: 0:14:13 lr: 4.105700000115094e-05 loss: 0.0472 (0.0517) time: 3.0062 data: 0.0024 max mem: 19788 +Epoch: [7] [1860/2138] eta: 0:13:43 lr: 4.105162155058313e-05 loss: 0.0449 (0.0517) time: 3.0042 data: 0.0025 max mem: 19788 +Epoch: [7] [1870/2138] eta: 0:13:14 lr: 4.1046243021717834e-05 loss: 0.0458 (0.0517) time: 3.0783 data: 0.0026 max mem: 19788 +Epoch: [7] [1880/2138] eta: 0:12:44 lr: 4.104086441454251e-05 loss: 0.0458 (0.0517) time: 3.0005 data: 0.0026 max mem: 19788 +Epoch: [7] [1890/2138] eta: 0:12:14 lr: 4.10354857290446e-05 loss: 0.0395 (0.0517) time: 2.8454 data: 0.0026 max mem: 19788 +Epoch: [7] [1900/2138] eta: 0:11:44 lr: 4.1030106965211575e-05 loss: 0.0414 (0.0517) time: 2.8122 data: 0.0026 max mem: 19788 +Epoch: [7] [1910/2138] eta: 0:11:15 lr: 4.102472812303087e-05 loss: 0.0409 (0.0517) time: 2.8151 data: 0.0027 max mem: 19788 +Epoch: [7] [1920/2138] eta: 0:10:45 lr: 4.1019349202489924e-05 loss: 0.0420 (0.0517) time: 2.8135 data: 0.0027 max mem: 19788 +Epoch: [7] [1930/2138] eta: 0:10:15 lr: 4.10139702035762e-05 loss: 0.0481 (0.0516) time: 2.8106 data: 0.0029 max mem: 19788 +Epoch: [7] [1940/2138] eta: 0:09:45 lr: 4.1008591126277116e-05 loss: 0.0487 (0.0516) time: 2.8110 data: 0.0029 max mem: 19788 +Epoch: [7] [1950/2138] eta: 0:09:16 lr: 4.100321197058011e-05 loss: 0.0535 (0.0517) time: 2.8121 data: 0.0026 max mem: 19788 +Epoch: [7] [1960/2138] eta: 0:08:46 lr: 4.099783273647262e-05 loss: 0.0497 (0.0516) time: 2.8083 data: 0.0023 max mem: 19788 +Epoch: [7] [1970/2138] eta: 0:08:16 lr: 4.099245342394206e-05 loss: 0.0459 (0.0516) time: 2.8029 data: 0.0021 max mem: 19788 +Epoch: [7] [1980/2138] eta: 0:07:47 lr: 4.0987074032975855e-05 loss: 0.0504 (0.0517) time: 2.8058 data: 0.0021 max mem: 19788 +Epoch: [7] [1990/2138] eta: 0:07:17 lr: 4.098169456356143e-05 loss: 0.0460 (0.0516) time: 2.8126 data: 0.0021 max mem: 19788 +Epoch: [7] [2000/2138] eta: 0:06:47 lr: 4.0976315015686187e-05 loss: 0.0392 (0.0516) time: 2.8153 data: 0.0023 max mem: 19788 +Epoch: [7] [2010/2138] eta: 0:06:18 lr: 4.097093538933754e-05 loss: 0.0385 (0.0516) time: 2.8117 data: 0.0023 max mem: 19788 +Epoch: [7] [2020/2138] eta: 0:05:48 lr: 4.09655556845029e-05 loss: 0.0429 (0.0516) time: 2.8108 data: 0.0025 max mem: 19788 +Epoch: [7] [2030/2138] eta: 0:05:18 lr: 4.096017590116967e-05 loss: 0.0461 (0.0516) time: 2.8238 data: 0.0027 max mem: 19788 +Epoch: [7] [2040/2138] eta: 0:04:49 lr: 4.095479603932524e-05 loss: 0.0430 (0.0516) time: 2.8260 data: 0.0026 max mem: 19788 +Epoch: [7] [2050/2138] eta: 0:04:19 lr: 4.094941609895701e-05 loss: 0.0421 (0.0516) time: 2.8158 data: 0.0025 max mem: 19788 +Epoch: [7] [2060/2138] eta: 0:03:50 lr: 4.0944036080052364e-05 loss: 0.0423 (0.0515) time: 2.8112 data: 0.0023 max mem: 19788 +Epoch: [7] [2070/2138] eta: 0:03:20 lr: 4.093865598259871e-05 loss: 0.0391 (0.0515) time: 2.8122 data: 0.0024 max mem: 19788 +Epoch: [7] [2080/2138] eta: 0:02:51 lr: 4.093327580658341e-05 loss: 0.0480 (0.0515) time: 2.8116 data: 0.0026 max mem: 19788 +Epoch: [7] [2090/2138] eta: 0:02:21 lr: 4.092789555199385e-05 loss: 0.0499 (0.0515) time: 2.8064 data: 0.0022 max mem: 19788 +Epoch: [7] [2100/2138] eta: 0:01:52 lr: 4.0922515218817404e-05 loss: 0.0442 (0.0515) time: 2.8044 data: 0.0022 max mem: 19788 +Epoch: [7] [2110/2138] eta: 0:01:22 lr: 4.091713480704145e-05 loss: 0.0461 (0.0515) time: 2.8133 data: 0.0024 max mem: 19788 +Epoch: [7] [2120/2138] eta: 0:00:53 lr: 4.0911754316653345e-05 loss: 0.0660 (0.0516) time: 2.8180 data: 0.0023 max mem: 19788 +Epoch: [7] [2130/2138] eta: 0:00:23 lr: 4.090637374764045e-05 loss: 0.0543 (0.0516) time: 2.8027 data: 0.0021 max mem: 19788 +Epoch: [7] Total time: 1:44:57 +Test: [ 0/21770] eta: 18:19:58 time: 3.0316 data: 2.9647 max mem: 19788 +Test: [ 100/21770] eta: 0:26:34 time: 0.0432 data: 0.0017 max mem: 19788 +Test: [ 200/21770] eta: 0:21:20 time: 0.0420 data: 0.0014 max mem: 19788 +Test: [ 300/21770] eta: 0:20:06 time: 0.0487 data: 0.0016 max mem: 19788 +Test: [ 400/21770] eta: 0:19:00 time: 0.0457 data: 0.0015 max mem: 19788 +Test: [ 500/21770] eta: 0:18:24 time: 0.0425 data: 0.0016 max mem: 19788 +Test: [ 600/21770] eta: 0:17:52 time: 0.0446 data: 0.0015 max mem: 19788 +Test: [ 700/21770] eta: 0:17:27 time: 0.0428 data: 0.0014 max mem: 19788 +Test: [ 800/21770] eta: 0:17:11 time: 0.0469 data: 0.0016 max mem: 19788 +Test: [ 900/21770] eta: 0:16:52 time: 0.0427 data: 0.0014 max mem: 19788 +Test: [ 1000/21770] eta: 0:16:40 time: 0.0484 data: 0.0017 max mem: 19788 +Test: [ 1100/21770] eta: 0:16:30 time: 0.0428 data: 0.0015 max mem: 19788 +Test: [ 1200/21770] eta: 0:16:21 time: 0.0474 data: 0.0015 max mem: 19788 +Test: [ 1300/21770] eta: 0:16:09 time: 0.0432 data: 0.0015 max mem: 19788 +Test: [ 1400/21770] eta: 0:16:02 time: 0.0483 data: 0.0017 max mem: 19788 +Test: [ 1500/21770] eta: 0:15:56 time: 0.0423 data: 0.0014 max mem: 19788 +Test: [ 1600/21770] eta: 0:15:47 time: 0.0431 data: 0.0014 max mem: 19788 +Test: [ 1700/21770] eta: 0:15:44 time: 0.0515 data: 0.0018 max mem: 19788 +Test: [ 1800/21770] eta: 0:15:39 time: 0.0436 data: 0.0016 max mem: 19788 +Test: [ 1900/21770] eta: 0:15:30 time: 0.0435 data: 0.0015 max mem: 19788 +Test: [ 2000/21770] eta: 0:15:26 time: 0.0465 data: 0.0015 max mem: 19788 +Test: [ 2100/21770] eta: 0:15:23 time: 0.0451 data: 0.0015 max mem: 19788 +Test: [ 2200/21770] eta: 0:15:20 time: 0.0432 data: 0.0015 max mem: 19788 +Test: [ 2300/21770] eta: 0:15:13 time: 0.0466 data: 0.0017 max mem: 19788 +Test: [ 2400/21770] eta: 0:15:07 time: 0.0485 data: 0.0014 max mem: 19788 +Test: [ 2500/21770] eta: 0:15:04 time: 0.0514 data: 0.0016 max mem: 19788 +Test: [ 2600/21770] eta: 0:15:01 time: 0.0477 data: 0.0019 max mem: 19788 +Test: [ 2700/21770] eta: 0:14:57 time: 0.0553 data: 0.0018 max mem: 19788 +Test: [ 2800/21770] eta: 0:14:55 time: 0.0476 data: 0.0016 max mem: 19788 +Test: [ 2900/21770] eta: 0:14:49 time: 0.0444 data: 0.0015 max mem: 19788 +Test: [ 3000/21770] eta: 0:14:45 time: 0.0472 data: 0.0017 max mem: 19788 +Test: [ 3100/21770] eta: 0:14:42 time: 0.0511 data: 0.0016 max mem: 19788 +Test: [ 3200/21770] eta: 0:14:40 time: 0.0489 data: 0.0019 max mem: 19788 +Test: [ 3300/21770] eta: 0:14:37 time: 0.0468 data: 0.0015 max mem: 19788 +Test: [ 3400/21770] eta: 0:14:32 time: 0.0447 data: 0.0014 max mem: 19788 +Test: [ 3500/21770] eta: 0:14:28 time: 0.0537 data: 0.0018 max mem: 19788 +Test: [ 3600/21770] eta: 0:14:25 time: 0.0541 data: 0.0019 max mem: 19788 +Test: [ 3700/21770] eta: 0:14:21 time: 0.0446 data: 0.0015 max mem: 19788 +Test: [ 3800/21770] eta: 0:14:16 time: 0.0464 data: 0.0015 max mem: 19788 +Test: [ 3900/21770] eta: 0:14:11 time: 0.0523 data: 0.0018 max mem: 19788 +Test: [ 4000/21770] eta: 0:14:09 time: 0.0527 data: 0.0019 max mem: 19788 +Test: [ 4100/21770] eta: 0:14:05 time: 0.0432 data: 0.0014 max mem: 19788 +Test: [ 4200/21770] eta: 0:13:59 time: 0.0479 data: 0.0015 max mem: 19788 +Test: [ 4300/21770] eta: 0:13:54 time: 0.0442 data: 0.0014 max mem: 19788 +Test: [ 4400/21770] eta: 0:13:50 time: 0.0529 data: 0.0017 max mem: 19788 +Test: [ 4500/21770] eta: 0:13:45 time: 0.0501 data: 0.0015 max mem: 19788 +Test: [ 4600/21770] eta: 0:13:40 time: 0.0462 data: 0.0017 max mem: 19788 +Test: [ 4700/21770] eta: 0:13:34 time: 0.0441 data: 0.0014 max mem: 19788 +Test: [ 4800/21770] eta: 0:13:30 time: 0.0502 data: 0.0017 max mem: 19788 +Test: [ 4900/21770] eta: 0:13:24 time: 0.0455 data: 0.0017 max mem: 19788 +Test: [ 5000/21770] eta: 0:13:19 time: 0.0459 data: 0.0015 max mem: 19788 +Test: [ 5100/21770] eta: 0:13:14 time: 0.0426 data: 0.0014 max mem: 19788 +Test: [ 5200/21770] eta: 0:13:09 time: 0.0463 data: 0.0017 max mem: 19788 +Test: [ 5300/21770] eta: 0:13:04 time: 0.0462 data: 0.0017 max mem: 19788 +Test: [ 5400/21770] eta: 0:12:58 time: 0.0434 data: 0.0016 max mem: 19788 +Test: [ 5500/21770] eta: 0:12:55 time: 0.0547 data: 0.0017 max mem: 19788 +Test: [ 5600/21770] eta: 0:12:50 time: 0.0439 data: 0.0014 max mem: 19788 +Test: [ 5700/21770] eta: 0:12:45 time: 0.0463 data: 0.0017 max mem: 19788 +Test: [ 5800/21770] eta: 0:12:41 time: 0.0512 data: 0.0018 max mem: 19788 +Test: [ 5900/21770] eta: 0:12:36 time: 0.0530 data: 0.0018 max mem: 19788 +Test: [ 6000/21770] eta: 0:12:32 time: 0.0543 data: 0.0017 max mem: 19788 +Test: [ 6100/21770] eta: 0:12:28 time: 0.0434 data: 0.0016 max mem: 19788 +Test: [ 6200/21770] eta: 0:12:22 time: 0.0486 data: 0.0015 max mem: 19788 +Test: [ 6300/21770] eta: 0:12:17 time: 0.0439 data: 0.0015 max mem: 19788 +Test: [ 6400/21770] eta: 0:12:13 time: 0.0530 data: 0.0018 max mem: 19788 +Test: [ 6500/21770] eta: 0:12:09 time: 0.0451 data: 0.0016 max mem: 19788 +Test: [ 6600/21770] eta: 0:12:04 time: 0.0492 data: 0.0017 max mem: 19788 +Test: [ 6700/21770] eta: 0:11:59 time: 0.0492 data: 0.0016 max mem: 19788 +Test: [ 6800/21770] eta: 0:11:55 time: 0.0563 data: 0.0018 max mem: 19788 +Test: [ 6900/21770] eta: 0:11:50 time: 0.0427 data: 0.0015 max mem: 19788 +Test: [ 7000/21770] eta: 0:11:45 time: 0.0525 data: 0.0019 max mem: 19788 +Test: [ 7100/21770] eta: 0:11:40 time: 0.0528 data: 0.0020 max mem: 19788 +Test: [ 7200/21770] eta: 0:11:35 time: 0.0451 data: 0.0015 max mem: 19788 +Test: [ 7300/21770] eta: 0:11:31 time: 0.0534 data: 0.0019 max mem: 19788 +Test: [ 7400/21770] eta: 0:11:27 time: 0.0526 data: 0.0018 max mem: 19788 +Test: [ 7500/21770] eta: 0:11:23 time: 0.0441 data: 0.0016 max mem: 19788 +Test: [ 7600/21770] eta: 0:11:18 time: 0.0536 data: 0.0018 max mem: 19788 +Test: [ 7700/21770] eta: 0:11:14 time: 0.0489 data: 0.0019 max mem: 19788 +Test: [ 7800/21770] eta: 0:11:09 time: 0.0440 data: 0.0016 max mem: 19788 +Test: [ 7900/21770] eta: 0:11:04 time: 0.0510 data: 0.0018 max mem: 19788 +Test: [ 8000/21770] eta: 0:10:59 time: 0.0442 data: 0.0015 max mem: 19788 +Test: [ 8100/21770] eta: 0:10:55 time: 0.0528 data: 0.0018 max mem: 19788 +Test: [ 8200/21770] eta: 0:10:50 time: 0.0540 data: 0.0018 max mem: 19788 +Test: [ 8300/21770] eta: 0:10:45 time: 0.0509 data: 0.0016 max mem: 19788 +Test: [ 8400/21770] eta: 0:10:40 time: 0.0445 data: 0.0016 max mem: 19788 +Test: [ 8500/21770] eta: 0:10:36 time: 0.0475 data: 0.0019 max mem: 19788 +Test: [ 8600/21770] eta: 0:10:31 time: 0.0447 data: 0.0015 max mem: 19788 +Test: [ 8700/21770] eta: 0:10:26 time: 0.0526 data: 0.0018 max mem: 19788 +Test: [ 8800/21770] eta: 0:10:22 time: 0.0543 data: 0.0018 max mem: 19788 +Test: [ 8900/21770] eta: 0:10:18 time: 0.0541 data: 0.0020 max mem: 19788 +Test: [ 9000/21770] eta: 0:10:13 time: 0.0490 data: 0.0017 max mem: 19788 +Test: [ 9100/21770] eta: 0:10:08 time: 0.0452 data: 0.0015 max mem: 19788 +Test: [ 9200/21770] eta: 0:10:03 time: 0.0454 data: 0.0015 max mem: 19788 +Test: [ 9300/21770] eta: 0:09:58 time: 0.0536 data: 0.0018 max mem: 19788 +Test: [ 9400/21770] eta: 0:09:54 time: 0.0540 data: 0.0019 max mem: 19788 +Test: [ 9500/21770] eta: 0:09:49 time: 0.0438 data: 0.0016 max mem: 19788 +Test: [ 9600/21770] eta: 0:09:44 time: 0.0452 data: 0.0016 max mem: 19788 +Test: [ 9700/21770] eta: 0:09:40 time: 0.0450 data: 0.0014 max mem: 19788 +Test: [ 9800/21770] eta: 0:09:35 time: 0.0455 data: 0.0017 max mem: 19788 +Test: [ 9900/21770] eta: 0:09:30 time: 0.0478 data: 0.0018 max mem: 19788 +Test: [10000/21770] eta: 0:09:25 time: 0.0487 data: 0.0017 max mem: 19788 +Test: [10100/21770] eta: 0:09:20 time: 0.0444 data: 0.0015 max mem: 19788 +Test: [10200/21770] eta: 0:09:16 time: 0.0542 data: 0.0020 max mem: 19788 +Test: [10300/21770] eta: 0:09:11 time: 0.0456 data: 0.0015 max mem: 19788 +Test: [10400/21770] eta: 0:09:07 time: 0.0481 data: 0.0017 max mem: 19788 +Test: [10500/21770] eta: 0:09:02 time: 0.0495 data: 0.0019 max mem: 19788 +Test: [10600/21770] eta: 0:08:57 time: 0.0458 data: 0.0017 max mem: 19788 +Test: [10700/21770] eta: 0:08:52 time: 0.0465 data: 0.0015 max mem: 19788 +Test: [10800/21770] eta: 0:08:47 time: 0.0539 data: 0.0018 max mem: 19788 +Test: [10900/21770] eta: 0:08:43 time: 0.0444 data: 0.0015 max mem: 19788 +Test: [11000/21770] eta: 0:08:38 time: 0.0452 data: 0.0017 max mem: 19788 +Test: [11100/21770] eta: 0:08:33 time: 0.0437 data: 0.0015 max mem: 19788 +Test: [11200/21770] eta: 0:08:28 time: 0.0458 data: 0.0017 max mem: 19788 +Test: [11300/21770] eta: 0:08:23 time: 0.0453 data: 0.0018 max mem: 19788 +Test: [11400/21770] eta: 0:08:18 time: 0.0540 data: 0.0017 max mem: 19788 +Test: [11500/21770] eta: 0:08:13 time: 0.0446 data: 0.0016 max mem: 19788 +Test: [11600/21770] eta: 0:08:09 time: 0.0495 data: 0.0018 max mem: 19788 +Test: [11700/21770] eta: 0:08:04 time: 0.0542 data: 0.0017 max mem: 19788 +Test: [11800/21770] eta: 0:08:00 time: 0.0556 data: 0.0020 max mem: 19788 +Test: [11900/21770] eta: 0:07:55 time: 0.0502 data: 0.0019 max mem: 19788 +Test: [12000/21770] eta: 0:07:50 time: 0.0482 data: 0.0016 max mem: 19788 +Test: [12100/21770] eta: 0:07:45 time: 0.0469 data: 0.0018 max mem: 19788 +Test: [12200/21770] eta: 0:07:40 time: 0.0462 data: 0.0015 max mem: 19788 +Test: [12300/21770] eta: 0:07:36 time: 0.0539 data: 0.0019 max mem: 19788 +Test: [12400/21770] eta: 0:07:31 time: 0.0494 data: 0.0017 max mem: 19788 +Test: [12500/21770] eta: 0:07:26 time: 0.0446 data: 0.0016 max mem: 19788 +Test: [12600/21770] eta: 0:07:21 time: 0.0454 data: 0.0015 max mem: 19788 +Test: [12700/21770] eta: 0:07:17 time: 0.0534 data: 0.0018 max mem: 19788 +Test: [12800/21770] eta: 0:07:12 time: 0.0459 data: 0.0016 max mem: 19788 +Test: [12900/21770] eta: 0:07:07 time: 0.0455 data: 0.0017 max mem: 19788 +Test: [13000/21770] eta: 0:07:02 time: 0.0454 data: 0.0016 max mem: 19788 +Test: [13100/21770] eta: 0:06:57 time: 0.0535 data: 0.0018 max mem: 19788 +Test: [13200/21770] eta: 0:06:53 time: 0.0537 data: 0.0019 max mem: 19788 +Test: [13300/21770] eta: 0:06:48 time: 0.0484 data: 0.0017 max mem: 19788 +Test: [13400/21770] eta: 0:06:43 time: 0.0478 data: 0.0018 max mem: 19788 +Test: [13500/21770] eta: 0:06:38 time: 0.0459 data: 0.0016 max mem: 19788 +Test: [13600/21770] eta: 0:06:34 time: 0.0461 data: 0.0015 max mem: 19788 +Test: [13700/21770] eta: 0:06:29 time: 0.0524 data: 0.0019 max mem: 19788 +Test: [13800/21770] eta: 0:06:25 time: 0.0559 data: 0.0020 max mem: 19788 +Test: [13900/21770] eta: 0:06:20 time: 0.0459 data: 0.0019 max mem: 19788 +Test: [14000/21770] eta: 0:06:15 time: 0.0456 data: 0.0017 max mem: 19788 +Test: [14100/21770] eta: 0:06:10 time: 0.0532 data: 0.0020 max mem: 19788 +Test: [14200/21770] eta: 0:06:05 time: 0.0546 data: 0.0021 max mem: 19788 +Test: [14300/21770] eta: 0:06:01 time: 0.0545 data: 0.0019 max mem: 19788 +Test: [14400/21770] eta: 0:05:56 time: 0.0452 data: 0.0015 max mem: 19788 +Test: [14500/21770] eta: 0:05:51 time: 0.0509 data: 0.0018 max mem: 19788 +Test: [14600/21770] eta: 0:05:46 time: 0.0513 data: 0.0016 max mem: 19788 +Test: [14700/21770] eta: 0:05:42 time: 0.0520 data: 0.0017 max mem: 19788 +Test: [14800/21770] eta: 0:05:37 time: 0.0548 data: 0.0020 max mem: 19788 +Test: [14900/21770] eta: 0:05:33 time: 0.0494 data: 0.0017 max mem: 19788 +Test: [15000/21770] eta: 0:05:28 time: 0.0446 data: 0.0015 max mem: 19788 +Test: [15100/21770] eta: 0:05:23 time: 0.0497 data: 0.0017 max mem: 19788 +Test: [15200/21770] eta: 0:05:18 time: 0.0447 data: 0.0015 max mem: 19788 +Test: [15300/21770] eta: 0:05:13 time: 0.0539 data: 0.0017 max mem: 19788 +Test: [15400/21770] eta: 0:05:08 time: 0.0457 data: 0.0018 max mem: 19788 +Test: [15500/21770] eta: 0:05:03 time: 0.0456 data: 0.0016 max mem: 19788 +Test: [15600/21770] eta: 0:04:58 time: 0.0521 data: 0.0018 max mem: 19788 +Test: [15700/21770] eta: 0:04:54 time: 0.0546 data: 0.0019 max mem: 19788 +Test: [15800/21770] eta: 0:04:49 time: 0.0506 data: 0.0018 max mem: 19788 +Test: [15900/21770] eta: 0:04:44 time: 0.0547 data: 0.0017 max mem: 19788 +Test: [16000/21770] eta: 0:04:39 time: 0.0449 data: 0.0014 max mem: 19788 +Test: [16100/21770] eta: 0:04:34 time: 0.0478 data: 0.0015 max mem: 19788 +Test: [16200/21770] eta: 0:04:29 time: 0.0435 data: 0.0015 max mem: 19788 +Test: [16300/21770] eta: 0:04:24 time: 0.0528 data: 0.0017 max mem: 19788 +Test: [16400/21770] eta: 0:04:20 time: 0.0559 data: 0.0021 max mem: 19788 +Test: [16500/21770] eta: 0:04:15 time: 0.0468 data: 0.0016 max mem: 19788 +Test: [16600/21770] eta: 0:04:10 time: 0.0538 data: 0.0019 max mem: 19788 +Test: [16700/21770] eta: 0:04:05 time: 0.0446 data: 0.0016 max mem: 19788 +Test: [16800/21770] eta: 0:04:00 time: 0.0445 data: 0.0017 max mem: 19788 +Test: [16900/21770] eta: 0:03:55 time: 0.0448 data: 0.0016 max mem: 19788 +Test: [17000/21770] eta: 0:03:51 time: 0.0567 data: 0.0020 max mem: 19788 +Test: [17100/21770] eta: 0:03:46 time: 0.0520 data: 0.0019 max mem: 19788 +Test: [17200/21770] eta: 0:03:41 time: 0.0491 data: 0.0016 max mem: 19788 +Test: [17300/21770] eta: 0:03:36 time: 0.0500 data: 0.0019 max mem: 19788 +Test: [17400/21770] eta: 0:03:31 time: 0.0451 data: 0.0016 max mem: 19788 +Test: [17500/21770] eta: 0:03:27 time: 0.0500 data: 0.0017 max mem: 19788 +Test: [17600/21770] eta: 0:03:22 time: 0.0553 data: 0.0020 max mem: 19788 +Test: [17700/21770] eta: 0:03:17 time: 0.0440 data: 0.0016 max mem: 19788 +Test: [17800/21770] eta: 0:03:12 time: 0.0544 data: 0.0020 max mem: 19788 +Test: [17900/21770] eta: 0:03:07 time: 0.0533 data: 0.0018 max mem: 19788 +Test: [18000/21770] eta: 0:03:03 time: 0.0494 data: 0.0019 max mem: 19788 +Test: [18100/21770] eta: 0:02:58 time: 0.0452 data: 0.0014 max mem: 19788 +Test: [18200/21770] eta: 0:02:53 time: 0.0541 data: 0.0019 max mem: 19788 +Test: [18300/21770] eta: 0:02:48 time: 0.0538 data: 0.0019 max mem: 19788 +Test: [18400/21770] eta: 0:02:43 time: 0.0459 data: 0.0015 max mem: 19788 +Test: [18500/21770] eta: 0:02:38 time: 0.0543 data: 0.0019 max mem: 19788 +Test: [18600/21770] eta: 0:02:33 time: 0.0507 data: 0.0015 max mem: 19788 +Test: [18700/21770] eta: 0:02:29 time: 0.0478 data: 0.0015 max mem: 19788 +Test: [18800/21770] eta: 0:02:24 time: 0.0533 data: 0.0019 max mem: 19788 +Test: [18900/21770] eta: 0:02:19 time: 0.0468 data: 0.0015 max mem: 19788 +Test: [19000/21770] eta: 0:02:14 time: 0.0449 data: 0.0016 max mem: 19788 +Test: [19100/21770] eta: 0:02:09 time: 0.0451 data: 0.0016 max mem: 19788 +Test: [19200/21770] eta: 0:02:04 time: 0.0509 data: 0.0015 max mem: 19788 +Test: [19300/21770] eta: 0:02:00 time: 0.0466 data: 0.0015 max mem: 19788 +Test: [19400/21770] eta: 0:01:55 time: 0.0552 data: 0.0019 max mem: 19788 +Test: [19500/21770] eta: 0:01:50 time: 0.0525 data: 0.0019 max mem: 19788 +Test: [19600/21770] eta: 0:01:45 time: 0.0463 data: 0.0016 max mem: 19788 +Test: [19700/21770] eta: 0:01:40 time: 0.0451 data: 0.0014 max mem: 19788 +Test: [19800/21770] eta: 0:01:35 time: 0.0447 data: 0.0017 max mem: 19788 +Test: [19900/21770] eta: 0:01:31 time: 0.0475 data: 0.0018 max mem: 19788 +Test: [20000/21770] eta: 0:01:26 time: 0.0546 data: 0.0018 max mem: 19788 +Test: [20100/21770] eta: 0:01:21 time: 0.0531 data: 0.0019 max mem: 19788 +Test: [20200/21770] eta: 0:01:16 time: 0.0442 data: 0.0015 max mem: 19788 +Test: [20300/21770] eta: 0:01:11 time: 0.0449 data: 0.0016 max mem: 19788 +Test: [20400/21770] eta: 0:01:06 time: 0.0534 data: 0.0019 max mem: 19788 +Test: [20500/21770] eta: 0:01:01 time: 0.0444 data: 0.0016 max mem: 19788 +Test: [20600/21770] eta: 0:00:56 time: 0.0440 data: 0.0014 max mem: 19788 +Test: [20700/21770] eta: 0:00:52 time: 0.0516 data: 0.0017 max mem: 19788 +Test: [20800/21770] eta: 0:00:47 time: 0.0434 data: 0.0014 max mem: 19788 +Test: [20900/21770] eta: 0:00:42 time: 0.0433 data: 0.0015 max mem: 19788 +Test: [21000/21770] eta: 0:00:37 time: 0.0528 data: 0.0019 max mem: 19788 +Test: [21100/21770] eta: 0:00:32 time: 0.0458 data: 0.0015 max mem: 19788 +Test: [21200/21770] eta: 0:00:27 time: 0.0510 data: 0.0018 max mem: 19788 +Test: [21300/21770] eta: 0:00:22 time: 0.0502 data: 0.0017 max mem: 19788 +Test: [21400/21770] eta: 0:00:17 time: 0.0537 data: 0.0018 max mem: 19788 +Test: [21500/21770] eta: 0:00:13 time: 0.0546 data: 0.0017 max mem: 19788 +Test: [21600/21770] eta: 0:00:08 time: 0.0496 data: 0.0016 max mem: 19788 +Test: [21700/21770] eta: 0:00:03 time: 0.0449 data: 0.0014 max mem: 19788 +Test: Total time: 0:17:39 +Final results: +Mean IoU is 62.27 + + precision@0.5 = 69.38 + precision@0.6 = 63.32 + precision@0.7 = 55.62 + precision@0.8 = 44.00 + precision@0.9 = 20.93 + overall IoU = 63.21 + mean IoU = 62.27 + +Mean accuracy for one-to-zero sample is 80.02 + +Average object IoU 0.6227023697022857 +Overall IoU 63.209228515625 +Epoch: [8] [ 0/2138] eta: 6:56:12 lr: 4.090206923581181e-05 loss: 0.1169 (0.1169) time: 11.6805 data: 1.4622 max mem: 19788 +Epoch: [8] [ 10/2138] eta: 2:22:31 lr: 4.089668852524245e-05 loss: 0.0390 (0.0532) time: 4.0187 data: 0.1345 max mem: 19788 +Epoch: [8] [ 20/2138] eta: 2:09:31 lr: 4.089130773601292e-05 loss: 0.0405 (0.0507) time: 3.2688 data: 0.0020 max mem: 19788 +Epoch: [8] [ 30/2138] eta: 2:02:02 lr: 4.0885926868110555e-05 loss: 0.0455 (0.0514) time: 3.1742 data: 0.0026 max mem: 19788 +Epoch: [8] [ 40/2138] eta: 1:58:38 lr: 4.088054592152269e-05 loss: 0.0447 (0.0551) time: 3.1029 data: 0.0029 max mem: 19788 +Epoch: [8] [ 50/2138] eta: 1:56:11 lr: 4.087516489623668e-05 loss: 0.0437 (0.0558) time: 3.1298 data: 0.0030 max mem: 19788 +Epoch: [8] [ 60/2138] eta: 1:55:33 lr: 4.0869783792239856e-05 loss: 0.0470 (0.0565) time: 3.2205 data: 0.0030 max mem: 19788 +Epoch: [8] [ 70/2138] eta: 1:55:28 lr: 4.0864402609519556e-05 loss: 0.0484 (0.0554) time: 3.3799 data: 0.0030 max mem: 19788 +Epoch: [8] [ 80/2138] eta: 1:53:47 lr: 4.085902134806311e-05 loss: 0.0449 (0.0544) time: 3.2601 data: 0.0031 max mem: 19788 +Epoch: [8] [ 90/2138] eta: 1:52:31 lr: 4.085364000785784e-05 loss: 0.0395 (0.0539) time: 3.1052 data: 0.0031 max mem: 19788 +Epoch: [8] [ 100/2138] eta: 1:51:46 lr: 4.0848258588891056e-05 loss: 0.0468 (0.0543) time: 3.1810 data: 0.0030 max mem: 19788 +Epoch: [8] [ 110/2138] eta: 1:50:52 lr: 4.08428770911501e-05 loss: 0.0468 (0.0540) time: 3.2063 data: 0.0028 max mem: 19788 +Epoch: [8] [ 120/2138] eta: 1:49:53 lr: 4.083749551462227e-05 loss: 0.0425 (0.0532) time: 3.1515 data: 0.0026 max mem: 19788 +Epoch: [8] [ 130/2138] eta: 1:48:55 lr: 4.083211385929488e-05 loss: 0.0425 (0.0527) time: 3.1125 data: 0.0025 max mem: 19788 +Epoch: [8] [ 140/2138] eta: 1:48:00 lr: 4.082673212515523e-05 loss: 0.0455 (0.0529) time: 3.0969 data: 0.0024 max mem: 19788 +Epoch: [8] [ 150/2138] eta: 1:47:13 lr: 4.082135031219064e-05 loss: 0.0474 (0.0526) time: 3.1153 data: 0.0025 max mem: 19788 +Epoch: [8] [ 160/2138] eta: 1:46:37 lr: 4.08159684203884e-05 loss: 0.0474 (0.0522) time: 3.1694 data: 0.0027 max mem: 19788 +Epoch: [8] [ 170/2138] eta: 1:45:57 lr: 4.081058644973579e-05 loss: 0.0502 (0.0526) time: 3.1847 data: 0.0026 max mem: 19788 +Epoch: [8] [ 180/2138] eta: 1:45:11 lr: 4.080520440022011e-05 loss: 0.0509 (0.0524) time: 3.1360 data: 0.0023 max mem: 19788 +Epoch: [8] [ 190/2138] eta: 1:44:18 lr: 4.079982227182865e-05 loss: 0.0475 (0.0527) time: 3.0642 data: 0.0022 max mem: 19788 +Epoch: [8] [ 200/2138] eta: 1:43:47 lr: 4.07944400645487e-05 loss: 0.0461 (0.0525) time: 3.1210 data: 0.0023 max mem: 19788 +Epoch: [8] [ 210/2138] eta: 1:43:19 lr: 4.0789057778367525e-05 loss: 0.0410 (0.0524) time: 3.2393 data: 0.0024 max mem: 19788 +Epoch: [8] [ 220/2138] eta: 1:43:03 lr: 4.07836754132724e-05 loss: 0.0449 (0.0525) time: 3.3313 data: 0.0024 max mem: 19788 +Epoch: [8] [ 230/2138] eta: 1:42:21 lr: 4.0778292969250606e-05 loss: 0.0466 (0.0525) time: 3.2528 data: 0.0026 max mem: 19788 +Epoch: [8] [ 240/2138] eta: 1:41:53 lr: 4.07729104462894e-05 loss: 0.0466 (0.0522) time: 3.1905 data: 0.0026 max mem: 19788 +Epoch: [8] [ 250/2138] eta: 1:41:14 lr: 4.076752784437605e-05 loss: 0.0456 (0.0519) time: 3.2074 data: 0.0027 max mem: 19788 +Epoch: [8] [ 260/2138] eta: 1:40:42 lr: 4.076214516349782e-05 loss: 0.0420 (0.0519) time: 3.1740 data: 0.0028 max mem: 19788 +Epoch: [8] [ 270/2138] eta: 1:39:56 lr: 4.075676240364195e-05 loss: 0.0428 (0.0518) time: 3.1173 data: 0.0024 max mem: 19788 +Epoch: [8] [ 280/2138] eta: 1:39:03 lr: 4.075137956479571e-05 loss: 0.0491 (0.0521) time: 2.9579 data: 0.0022 max mem: 19788 +Epoch: [8] [ 290/2138] eta: 1:38:12 lr: 4.0745996646946325e-05 loss: 0.0558 (0.0523) time: 2.8919 data: 0.0023 max mem: 19788 +Epoch: [8] [ 300/2138] eta: 1:37:25 lr: 4.0740613650081066e-05 loss: 0.0558 (0.0523) time: 2.9148 data: 0.0025 max mem: 19788 +Epoch: [8] [ 310/2138] eta: 1:36:40 lr: 4.073523057418715e-05 loss: 0.0462 (0.0519) time: 2.9524 data: 0.0024 max mem: 19788 +Epoch: [8] [ 320/2138] eta: 1:35:54 lr: 4.072984741925183e-05 loss: 0.0414 (0.0517) time: 2.9414 data: 0.0024 max mem: 19788 +Epoch: [8] [ 330/2138] eta: 1:35:06 lr: 4.072446418526232e-05 loss: 0.0446 (0.0518) time: 2.8968 data: 0.0024 max mem: 19788 +Epoch: [8] [ 340/2138] eta: 1:34:20 lr: 4.0719080872205865e-05 loss: 0.0442 (0.0516) time: 2.8775 data: 0.0024 max mem: 19788 +Epoch: [8] [ 350/2138] eta: 1:33:40 lr: 4.071369748006967e-05 loss: 0.0375 (0.0512) time: 2.9259 data: 0.0022 max mem: 19788 +Epoch: [8] [ 360/2138] eta: 1:33:01 lr: 4.0708314008840974e-05 loss: 0.0393 (0.0513) time: 2.9789 data: 0.0023 max mem: 19788 +Epoch: [8] [ 370/2138] eta: 1:32:19 lr: 4.070293045850698e-05 loss: 0.0445 (0.0512) time: 2.9585 data: 0.0025 max mem: 19788 +Epoch: [8] [ 380/2138] eta: 1:31:36 lr: 4.06975468290549e-05 loss: 0.0448 (0.0515) time: 2.8986 data: 0.0024 max mem: 19788 +Epoch: [8] [ 390/2138] eta: 1:30:55 lr: 4.069216312047195e-05 loss: 0.0420 (0.0518) time: 2.8920 data: 0.0025 max mem: 19788 +Epoch: [8] [ 400/2138] eta: 1:30:17 lr: 4.068677933274533e-05 loss: 0.0477 (0.0519) time: 2.9364 data: 0.0026 max mem: 19788 +Epoch: [8] [ 410/2138] eta: 1:29:39 lr: 4.068139546586224e-05 loss: 0.0506 (0.0518) time: 2.9569 data: 0.0028 max mem: 19788 +Epoch: [8] [ 420/2138] eta: 1:29:03 lr: 4.067601151980987e-05 loss: 0.0468 (0.0517) time: 2.9758 data: 0.0027 max mem: 19788 +Epoch: [8] [ 430/2138] eta: 1:28:23 lr: 4.067062749457543e-05 loss: 0.0486 (0.0517) time: 2.9471 data: 0.0028 max mem: 19788 +Epoch: [8] [ 440/2138] eta: 1:27:44 lr: 4.066524339014608e-05 loss: 0.0512 (0.0518) time: 2.8906 data: 0.0025 max mem: 19788 +Epoch: [8] [ 450/2138] eta: 1:27:10 lr: 4.0659859206509026e-05 loss: 0.0502 (0.0518) time: 2.9589 data: 0.0022 max mem: 19788 +Epoch: [8] [ 460/2138] eta: 1:26:36 lr: 4.065447494365145e-05 loss: 0.0477 (0.0517) time: 3.0245 data: 0.0021 max mem: 19788 +Epoch: [8] [ 470/2138] eta: 1:26:00 lr: 4.064909060156052e-05 loss: 0.0467 (0.0517) time: 2.9822 data: 0.0021 max mem: 19788 +Epoch: [8] [ 480/2138] eta: 1:25:23 lr: 4.06437061802234e-05 loss: 0.0477 (0.0518) time: 2.9332 data: 0.0022 max mem: 19788 +Epoch: [8] [ 490/2138] eta: 1:24:45 lr: 4.063832167962727e-05 loss: 0.0573 (0.0520) time: 2.9034 data: 0.0024 max mem: 19788 +Epoch: [8] [ 500/2138] eta: 1:24:11 lr: 4.06329370997593e-05 loss: 0.0578 (0.0521) time: 2.9386 data: 0.0025 max mem: 19788 +Epoch: [8] [ 510/2138] eta: 1:23:37 lr: 4.062755244060664e-05 loss: 0.0457 (0.0521) time: 2.9802 data: 0.0025 max mem: 19788 +Epoch: [8] [ 520/2138] eta: 1:23:02 lr: 4.062216770215645e-05 loss: 0.0423 (0.0519) time: 2.9599 data: 0.0024 max mem: 19788 +Epoch: [8] [ 530/2138] eta: 1:22:25 lr: 4.061678288439587e-05 loss: 0.0423 (0.0518) time: 2.9134 data: 0.0022 max mem: 19788 +Epoch: [8] [ 540/2138] eta: 1:21:50 lr: 4.061139798731208e-05 loss: 0.0417 (0.0516) time: 2.9037 data: 0.0023 max mem: 19788 +Epoch: [8] [ 550/2138] eta: 1:21:16 lr: 4.06060130108922e-05 loss: 0.0428 (0.0517) time: 2.9419 data: 0.0024 max mem: 19788 +Epoch: [8] [ 560/2138] eta: 1:20:43 lr: 4.060062795512336e-05 loss: 0.0538 (0.0517) time: 2.9806 data: 0.0024 max mem: 19788 +Epoch: [8] [ 570/2138] eta: 1:20:10 lr: 4.059524281999274e-05 loss: 0.0480 (0.0516) time: 2.9941 data: 0.0023 max mem: 19788 +Epoch: [8] [ 580/2138] eta: 1:19:35 lr: 4.058985760548742e-05 loss: 0.0439 (0.0516) time: 2.9431 data: 0.0023 max mem: 19788 +Epoch: [8] [ 590/2138] eta: 1:19:00 lr: 4.058447231159456e-05 loss: 0.0439 (0.0515) time: 2.8912 data: 0.0024 max mem: 19788 +Epoch: [8] [ 600/2138] eta: 1:18:26 lr: 4.0579086938301284e-05 loss: 0.0464 (0.0515) time: 2.9192 data: 0.0024 max mem: 19788 +Epoch: [8] [ 610/2138] eta: 1:17:54 lr: 4.05737014855947e-05 loss: 0.0462 (0.0514) time: 2.9792 data: 0.0023 max mem: 19788 +Epoch: [8] [ 620/2138] eta: 1:17:20 lr: 4.0568315953461936e-05 loss: 0.0402 (0.0513) time: 2.9654 data: 0.0023 max mem: 19788 +Epoch: [8] [ 630/2138] eta: 1:16:46 lr: 4.05629303418901e-05 loss: 0.0433 (0.0513) time: 2.9053 data: 0.0022 max mem: 19788 +Epoch: [8] [ 640/2138] eta: 1:16:12 lr: 4.0557544650866296e-05 loss: 0.0409 (0.0512) time: 2.8914 data: 0.0022 max mem: 19788 +Epoch: [8] [ 650/2138] eta: 1:15:39 lr: 4.055215888037764e-05 loss: 0.0384 (0.0510) time: 2.9413 data: 0.0024 max mem: 19788 +Epoch: [8] [ 660/2138] eta: 1:15:08 lr: 4.0546773030411216e-05 loss: 0.0384 (0.0511) time: 2.9931 data: 0.0025 max mem: 19788 +Epoch: [8] [ 670/2138] eta: 1:14:36 lr: 4.054138710095414e-05 loss: 0.0433 (0.0511) time: 3.0054 data: 0.0023 max mem: 19788 +Epoch: [8] [ 680/2138] eta: 1:14:03 lr: 4.05360010919935e-05 loss: 0.0430 (0.0511) time: 2.9594 data: 0.0024 max mem: 19788 +Epoch: [8] [ 690/2138] eta: 1:13:29 lr: 4.0530615003516375e-05 loss: 0.0446 (0.0511) time: 2.9064 data: 0.0024 max mem: 19788 +Epoch: [8] [ 700/2138] eta: 1:12:58 lr: 4.0525228835509856e-05 loss: 0.0441 (0.0510) time: 2.9531 data: 0.0022 max mem: 19788 +Epoch: [8] [ 710/2138] eta: 1:12:27 lr: 4.0519842587961015e-05 loss: 0.0448 (0.0509) time: 3.0082 data: 0.0022 max mem: 19788 +Epoch: [8] [ 720/2138] eta: 1:11:55 lr: 4.051445626085694e-05 loss: 0.0433 (0.0509) time: 2.9771 data: 0.0026 max mem: 19788 +Epoch: [8] [ 730/2138] eta: 1:11:20 lr: 4.0509069854184714e-05 loss: 0.0433 (0.0509) time: 2.8749 data: 0.0026 max mem: 19788 +Epoch: [8] [ 740/2138] eta: 1:10:45 lr: 4.0503683367931376e-05 loss: 0.0499 (0.0510) time: 2.8080 data: 0.0025 max mem: 19788 +Epoch: [8] [ 750/2138] eta: 1:10:10 lr: 4.049829680208401e-05 loss: 0.0467 (0.0510) time: 2.8103 data: 0.0027 max mem: 19788 +Epoch: [8] [ 760/2138] eta: 1:09:36 lr: 4.0492910156629674e-05 loss: 0.0476 (0.0510) time: 2.8099 data: 0.0028 max mem: 19788 +Epoch: [8] [ 770/2138] eta: 1:09:02 lr: 4.048752343155543e-05 loss: 0.0510 (0.0510) time: 2.8066 data: 0.0030 max mem: 19788 +Epoch: [8] [ 780/2138] eta: 1:08:27 lr: 4.048213662684832e-05 loss: 0.0449 (0.0510) time: 2.8060 data: 0.0029 max mem: 19788 +Epoch: [8] [ 790/2138] eta: 1:07:54 lr: 4.047674974249539e-05 loss: 0.0416 (0.0509) time: 2.8116 data: 0.0026 max mem: 19788 +Epoch: [8] [ 800/2138] eta: 1:07:20 lr: 4.0471362778483705e-05 loss: 0.0436 (0.0511) time: 2.8095 data: 0.0025 max mem: 19788 +Epoch: [8] [ 810/2138] eta: 1:06:46 lr: 4.046597573480029e-05 loss: 0.0455 (0.0510) time: 2.7936 data: 0.0025 max mem: 19788 +Epoch: [8] [ 820/2138] eta: 1:06:12 lr: 4.046058861143218e-05 loss: 0.0411 (0.0509) time: 2.7909 data: 0.0024 max mem: 19788 +Epoch: [8] [ 830/2138] eta: 1:05:38 lr: 4.045520140836641e-05 loss: 0.0402 (0.0508) time: 2.7969 data: 0.0025 max mem: 19788 +Epoch: [8] [ 840/2138] eta: 1:05:05 lr: 4.0449814125590014e-05 loss: 0.0402 (0.0508) time: 2.7968 data: 0.0023 max mem: 19788 +Epoch: [8] [ 850/2138] eta: 1:04:32 lr: 4.044442676309e-05 loss: 0.0412 (0.0507) time: 2.7988 data: 0.0021 max mem: 19788 +Epoch: [8] [ 860/2138] eta: 1:03:59 lr: 4.0439039320853414e-05 loss: 0.0443 (0.0507) time: 2.8129 data: 0.0022 max mem: 19788 +Epoch: [8] [ 870/2138] eta: 1:03:26 lr: 4.043365179886726e-05 loss: 0.0490 (0.0508) time: 2.8161 data: 0.0022 max mem: 19788 +Epoch: [8] [ 880/2138] eta: 1:02:53 lr: 4.042826419711854e-05 loss: 0.0500 (0.0508) time: 2.7996 data: 0.0025 max mem: 19788 +Epoch: [8] [ 890/2138] eta: 1:02:20 lr: 4.042287651559428e-05 loss: 0.0453 (0.0507) time: 2.7911 data: 0.0024 max mem: 19788 +Epoch: [8] [ 900/2138] eta: 1:01:47 lr: 4.0417488754281475e-05 loss: 0.0385 (0.0506) time: 2.7922 data: 0.0023 max mem: 19788 +Epoch: [8] [ 910/2138] eta: 1:01:15 lr: 4.041210091316712e-05 loss: 0.0380 (0.0505) time: 2.7884 data: 0.0023 max mem: 19788 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mem: 19788 +Epoch: [8] [1000/2138] eta: 0:56:26 lr: 4.036360674992151e-05 loss: 0.0376 (0.0502) time: 2.8019 data: 0.0023 max mem: 19788 +Epoch: [8] [1010/2138] eta: 0:55:54 lr: 4.035821811007585e-05 loss: 0.0443 (0.0503) time: 2.7980 data: 0.0023 max mem: 19788 +Epoch: [8] [1020/2138] eta: 0:55:23 lr: 4.035282939028537e-05 loss: 0.0465 (0.0502) time: 2.8082 data: 0.0024 max mem: 19788 +Epoch: [8] [1030/2138] eta: 0:54:51 lr: 4.034744059053703e-05 loss: 0.0461 (0.0502) time: 2.8030 data: 0.0024 max mem: 19788 +Epoch: [8] [1040/2138] eta: 0:54:19 lr: 4.0342051710817785e-05 loss: 0.0461 (0.0502) time: 2.7927 data: 0.0025 max mem: 19788 +Epoch: [8] [1050/2138] eta: 0:53:48 lr: 4.0336662751114576e-05 loss: 0.0457 (0.0502) time: 2.8070 data: 0.0028 max mem: 19788 +Epoch: [8] [1060/2138] eta: 0:53:17 lr: 4.033127371141434e-05 loss: 0.0437 (0.0502) time: 2.8052 data: 0.0025 max mem: 19788 +Epoch: [8] [1070/2138] eta: 0:52:45 lr: 4.0325884591704e-05 loss: 0.0497 (0.0502) time: 2.7911 data: 0.0023 max mem: 19788 +Epoch: [8] [1080/2138] eta: 0:52:14 lr: 4.0320495391970515e-05 loss: 0.0465 (0.0502) time: 2.7930 data: 0.0021 max mem: 19788 +Epoch: [8] [1090/2138] eta: 0:51:43 lr: 4.0315106112200796e-05 loss: 0.0524 (0.0503) time: 2.8070 data: 0.0022 max mem: 19788 +Epoch: [8] [1100/2138] eta: 0:51:12 lr: 4.030971675238176e-05 loss: 0.0524 (0.0503) time: 2.8121 data: 0.0026 max mem: 19788 +Epoch: [8] [1110/2138] eta: 0:50:41 lr: 4.030432731250033e-05 loss: 0.0500 (0.0504) time: 2.7965 data: 0.0026 max mem: 19788 +Epoch: [8] [1120/2138] eta: 0:50:10 lr: 4.029893779254343e-05 loss: 0.0414 (0.0503) time: 2.8000 data: 0.0024 max mem: 19788 +Epoch: [8] [1130/2138] eta: 0:49:39 lr: 4.029354819249796e-05 loss: 0.0414 (0.0503) time: 2.8062 data: 0.0024 max mem: 19788 +Epoch: [8] [1140/2138] eta: 0:49:08 lr: 4.028815851235084e-05 loss: 0.0460 (0.0502) time: 2.7972 data: 0.0026 max mem: 19788 +Epoch: [8] [1150/2138] eta: 0:48:37 lr: 4.0282768752088956e-05 loss: 0.0379 (0.0501) time: 2.7939 data: 0.0027 max mem: 19788 +Epoch: [8] [1160/2138] eta: 0:48:06 lr: 4.027737891169922e-05 loss: 0.0377 (0.0501) time: 2.7906 data: 0.0027 max mem: 19788 +Epoch: [8] [1170/2138] eta: 0:47:35 lr: 4.0271988991168516e-05 loss: 0.0414 (0.0500) time: 2.7975 data: 0.0026 max mem: 19788 +Epoch: [8] [1180/2138] eta: 0:47:05 lr: 4.0266598990483736e-05 loss: 0.0429 (0.0500) time: 2.8161 data: 0.0024 max mem: 19788 +Epoch: [8] [1190/2138] eta: 0:46:34 lr: 4.0261208909631774e-05 loss: 0.0460 (0.0500) time: 2.8125 data: 0.0022 max mem: 19788 +Epoch: [8] [1200/2138] eta: 0:46:03 lr: 4.0255818748599504e-05 loss: 0.0397 (0.0499) time: 2.7978 data: 0.0024 max mem: 19788 +Epoch: [8] [1210/2138] eta: 0:45:33 lr: 4.025042850737381e-05 loss: 0.0465 (0.0499) time: 2.7955 data: 0.0028 max mem: 19788 +Epoch: [8] [1220/2138] eta: 0:45:02 lr: 4.024503818594156e-05 loss: 0.0453 (0.0498) time: 2.7939 data: 0.0027 max mem: 19788 +Epoch: [8] [1230/2138] eta: 0:44:32 lr: 4.0239647784289634e-05 loss: 0.0446 (0.0498) time: 2.8011 data: 0.0024 max mem: 19788 +Epoch: [8] [1240/2138] eta: 0:44:01 lr: 4.023425730240489e-05 loss: 0.0454 (0.0498) time: 2.8162 data: 0.0024 max mem: 19788 +Epoch: [8] [1250/2138] eta: 0:43:31 lr: 4.022886674027419e-05 loss: 0.0439 (0.0498) time: 2.8186 data: 0.0025 max mem: 19788 +Epoch: [8] [1260/2138] eta: 0:43:01 lr: 4.0223476097884394e-05 loss: 0.0444 (0.0498) time: 2.8005 data: 0.0027 max mem: 19788 +Epoch: [8] [1270/2138] eta: 0:42:30 lr: 4.0218085375222354e-05 loss: 0.0440 (0.0498) time: 2.7897 data: 0.0026 max mem: 19788 +Epoch: [8] [1280/2138] eta: 0:42:00 lr: 4.021269457227492e-05 loss: 0.0404 (0.0498) time: 2.8092 data: 0.0022 max mem: 19788 +Epoch: [8] [1290/2138] eta: 0:41:30 lr: 4.020730368902893e-05 loss: 0.0439 (0.0498) time: 2.8176 data: 0.0020 max mem: 19788 +Epoch: [8] [1300/2138] eta: 0:41:00 lr: 4.0201912725471236e-05 loss: 0.0470 (0.0498) time: 2.7983 data: 0.0020 max mem: 19788 +Epoch: [8] [1310/2138] eta: 0:40:29 lr: 4.0196521681588674e-05 loss: 0.0428 (0.0497) time: 2.7898 data: 0.0021 max mem: 19788 +Epoch: [8] [1320/2138] eta: 0:39:59 lr: 4.019113055736807e-05 loss: 0.0430 (0.0497) time: 2.8057 data: 0.0022 max mem: 19788 +Epoch: [8] [1330/2138] eta: 0:39:29 lr: 4.0185739352796253e-05 loss: 0.0430 (0.0497) time: 2.8202 data: 0.0022 max mem: 19788 +Epoch: [8] [1340/2138] eta: 0:38:59 lr: 4.0180348067860055e-05 loss: 0.0429 (0.0498) time: 2.8050 data: 0.0025 max mem: 19788 +Epoch: [8] [1350/2138] eta: 0:38:29 lr: 4.017495670254629e-05 loss: 0.0600 (0.0499) time: 2.7880 data: 0.0028 max mem: 19788 +Epoch: [8] [1360/2138] eta: 0:37:59 lr: 4.016956525684178e-05 loss: 0.0546 (0.0499) time: 2.8014 data: 0.0027 max mem: 19788 +Epoch: [8] [1370/2138] eta: 0:37:29 lr: 4.0164173730733335e-05 loss: 0.0501 (0.0500) time: 2.8111 data: 0.0024 max mem: 19788 +Epoch: [8] [1380/2138] eta: 0:36:59 lr: 4.0158782124207756e-05 loss: 0.0578 (0.0500) time: 2.8033 data: 0.0022 max mem: 19788 +Epoch: [8] [1390/2138] eta: 0:36:29 lr: 4.015339043725186e-05 loss: 0.0426 (0.0500) time: 2.8004 data: 0.0024 max mem: 19788 +Epoch: [8] [1400/2138] eta: 0:35:59 lr: 4.0147998669852435e-05 loss: 0.0378 (0.0499) time: 2.8007 data: 0.0027 max mem: 19788 +Epoch: [8] [1410/2138] eta: 0:35:29 lr: 4.014260682199628e-05 loss: 0.0355 (0.0499) time: 2.8049 data: 0.0028 max mem: 19788 +Epoch: [8] [1420/2138] eta: 0:34:59 lr: 4.013721489367019e-05 loss: 0.0393 (0.0498) time: 2.8012 data: 0.0024 max mem: 19788 +Epoch: [8] [1430/2138] eta: 0:34:29 lr: 4.013182288486096e-05 loss: 0.0463 (0.0498) time: 2.7924 data: 0.0021 max mem: 19788 +Epoch: [8] [1440/2138] eta: 0:33:59 lr: 4.012643079555535e-05 loss: 0.0439 (0.0498) time: 2.7918 data: 0.0021 max mem: 19788 +Epoch: [8] [1450/2138] eta: 0:33:30 lr: 4.0121038625740164e-05 loss: 0.0419 (0.0498) time: 2.7982 data: 0.0020 max mem: 19788 +Epoch: [8] [1460/2138] eta: 0:33:00 lr: 4.011564637540216e-05 loss: 0.0437 (0.0497) time: 2.8108 data: 0.0021 max mem: 19788 +Epoch: [8] [1470/2138] eta: 0:32:30 lr: 4.011025404452812e-05 loss: 0.0437 (0.0497) time: 2.8102 data: 0.0022 max mem: 19788 +Epoch: [8] [1480/2138] eta: 0:32:00 lr: 4.01048616331048e-05 loss: 0.0516 (0.0498) time: 2.7984 data: 0.0022 max mem: 19788 +Epoch: [8] [1490/2138] eta: 0:31:31 lr: 4.009946914111897e-05 loss: 0.0505 (0.0499) time: 2.7911 data: 0.0023 max mem: 19788 +Epoch: [8] [1500/2138] eta: 0:31:01 lr: 4.009407656855739e-05 loss: 0.0487 (0.0499) time: 2.7931 data: 0.0023 max mem: 19788 +Epoch: [8] [1510/2138] eta: 0:30:31 lr: 4.0088683915406803e-05 loss: 0.0446 (0.0499) time: 2.8101 data: 0.0023 max mem: 19788 +Epoch: [8] [1520/2138] eta: 0:30:02 lr: 4.008329118165397e-05 loss: 0.0392 (0.0498) time: 2.8199 data: 0.0029 max mem: 19788 +Epoch: [8] [1530/2138] eta: 0:29:32 lr: 4.0077898367285635e-05 loss: 0.0426 (0.0498) time: 2.8044 data: 0.0031 max mem: 19788 +Epoch: [8] [1540/2138] eta: 0:29:03 lr: 4.007250547228855e-05 loss: 0.0447 (0.0498) time: 2.7898 data: 0.0029 max mem: 19788 +Epoch: [8] [1550/2138] eta: 0:28:33 lr: 4.006711249664942e-05 loss: 0.0447 (0.0499) time: 2.7872 data: 0.0027 max mem: 19788 +Epoch: [8] [1560/2138] eta: 0:28:03 lr: 4.0061719440355016e-05 loss: 0.0439 (0.0499) time: 2.7895 data: 0.0025 max mem: 19788 +Epoch: [8] [1570/2138] eta: 0:27:34 lr: 4.0056326303392046e-05 loss: 0.0395 (0.0499) time: 2.7901 data: 0.0028 max mem: 19788 +Epoch: [8] [1580/2138] eta: 0:27:04 lr: 4.0050933085747236e-05 loss: 0.0402 (0.0498) time: 2.7869 data: 0.0029 max mem: 19788 +Epoch: [8] [1590/2138] eta: 0:26:35 lr: 4.004553978740732e-05 loss: 0.0427 (0.0498) time: 2.7878 data: 0.0026 max mem: 19788 +Epoch: [8] [1600/2138] eta: 0:26:05 lr: 4.0040146408359e-05 loss: 0.0453 (0.0498) time: 2.7899 data: 0.0026 max mem: 19788 +Epoch: [8] [1610/2138] eta: 0:25:36 lr: 4.0034752948588986e-05 loss: 0.0448 (0.0498) time: 2.7877 data: 0.0023 max mem: 19788 +Epoch: [8] [1620/2138] eta: 0:25:06 lr: 4.0029359408084e-05 loss: 0.0381 (0.0498) time: 2.7831 data: 0.0020 max mem: 19788 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mem: 19788 +Epoch: [8] [1710/2138] eta: 0:20:42 lr: 3.998081390827e-05 loss: 0.0387 (0.0495) time: 2.8052 data: 0.0022 max mem: 19788 +Epoch: [8] [1720/2138] eta: 0:20:13 lr: 3.997541955968328e-05 loss: 0.0414 (0.0495) time: 2.8085 data: 0.0025 max mem: 19788 +Epoch: [8] [1730/2138] eta: 0:19:43 lr: 3.997002513021511e-05 loss: 0.0505 (0.0495) time: 2.8000 data: 0.0028 max mem: 19788 +Epoch: [8] [1740/2138] eta: 0:19:14 lr: 3.9964630619852127e-05 loss: 0.0482 (0.0495) time: 2.7935 data: 0.0026 max mem: 19788 +Epoch: [8] [1750/2138] eta: 0:18:45 lr: 3.9959236028581006e-05 loss: 0.0445 (0.0494) time: 2.7921 data: 0.0026 max mem: 19788 +Epoch: [8] [1760/2138] eta: 0:18:16 lr: 3.995384135638837e-05 loss: 0.0446 (0.0495) time: 2.7896 data: 0.0029 max mem: 19788 +Epoch: [8] [1770/2138] eta: 0:17:46 lr: 3.9948446603260895e-05 loss: 0.0437 (0.0494) time: 2.7883 data: 0.0029 max mem: 19788 +Epoch: [8] [1780/2138] eta: 0:17:17 lr: 3.99430517691852e-05 loss: 0.0352 (0.0494) time: 2.7882 data: 0.0027 max mem: 19788 +Epoch: [8] [1790/2138] eta: 0:16:48 lr: 3.993765685414793e-05 loss: 0.0358 (0.0494) time: 2.7884 data: 0.0027 max mem: 19788 +Epoch: [8] [1800/2138] eta: 0:16:19 lr: 3.9932261858135723e-05 loss: 0.0463 (0.0494) time: 2.7928 data: 0.0026 max mem: 19788 +Epoch: [8] [1810/2138] eta: 0:15:50 lr: 3.99268667811352e-05 loss: 0.0452 (0.0494) time: 2.7965 data: 0.0026 max mem: 19788 +Epoch: [8] [1820/2138] eta: 0:15:21 lr: 3.9921471623132975e-05 loss: 0.0405 (0.0493) time: 2.7937 data: 0.0027 max mem: 19788 +Epoch: [8] [1830/2138] eta: 0:14:51 lr: 3.9916076384115696e-05 loss: 0.0390 (0.0493) time: 2.7893 data: 0.0026 max mem: 19788 +Epoch: [8] [1840/2138] eta: 0:14:22 lr: 3.991068106406996e-05 loss: 0.0433 (0.0493) time: 2.8013 data: 0.0025 max mem: 19788 +Epoch: [8] [1850/2138] eta: 0:13:53 lr: 3.990528566298238e-05 loss: 0.0449 (0.0493) time: 2.8254 data: 0.0025 max mem: 19788 +Epoch: [8] [1860/2138] eta: 0:13:24 lr: 3.989989018083957e-05 loss: 0.0522 (0.0493) time: 2.8238 data: 0.0025 max mem: 19788 +Epoch: [8] [1870/2138] eta: 0:12:55 lr: 3.9894494617628133e-05 loss: 0.0453 (0.0493) time: 2.8112 data: 0.0026 max mem: 19788 +Epoch: [8] [1880/2138] eta: 0:12:26 lr: 3.988909897333465e-05 loss: 0.0389 (0.0493) time: 2.8113 data: 0.0026 max mem: 19788 +Epoch: [8] [1890/2138] eta: 0:11:57 lr: 3.988370324794575e-05 loss: 0.0391 (0.0493) time: 2.8150 data: 0.0027 max mem: 19788 +Epoch: [8] [1900/2138] eta: 0:11:28 lr: 3.9878307441447985e-05 loss: 0.0465 (0.0493) time: 2.8139 data: 0.0029 max mem: 19788 +Epoch: [8] [1910/2138] eta: 0:10:59 lr: 3.987291155382797e-05 loss: 0.0399 (0.0492) time: 2.8070 data: 0.0027 max mem: 19788 +Epoch: [8] [1920/2138] eta: 0:10:30 lr: 3.986751558507228e-05 loss: 0.0411 (0.0492) time: 2.8030 data: 0.0026 max mem: 19788 +Epoch: [8] [1930/2138] eta: 0:10:01 lr: 3.986211953516749e-05 loss: 0.0459 (0.0492) time: 2.8027 data: 0.0026 max mem: 19788 +Epoch: [8] [1940/2138] eta: 0:09:32 lr: 3.985672340410018e-05 loss: 0.0459 (0.0492) time: 2.8091 data: 0.0025 max mem: 19788 +Epoch: [8] [1950/2138] eta: 0:09:03 lr: 3.98513271918569e-05 loss: 0.0435 (0.0492) time: 2.8162 data: 0.0024 max mem: 19788 +Epoch: [8] [1960/2138] eta: 0:08:34 lr: 3.984593089842424e-05 loss: 0.0399 (0.0492) time: 2.8160 data: 0.0025 max mem: 19788 +Epoch: [8] [1970/2138] eta: 0:08:05 lr: 3.984053452378875e-05 loss: 0.0390 (0.0491) time: 2.8123 data: 0.0024 max mem: 19788 +Epoch: [8] [1980/2138] eta: 0:07:36 lr: 3.983513806793698e-05 loss: 0.0447 (0.0491) time: 2.8099 data: 0.0023 max mem: 19788 +Epoch: [8] [1990/2138] eta: 0:07:07 lr: 3.982974153085549e-05 loss: 0.0458 (0.0491) time: 2.8093 data: 0.0022 max mem: 19788 +Epoch: [8] [2000/2138] eta: 0:06:38 lr: 3.982434491253083e-05 loss: 0.0395 (0.0490) time: 2.8059 data: 0.0024 max mem: 19788 +Epoch: [8] [2010/2138] eta: 0:06:09 lr: 3.981894821294954e-05 loss: 0.0401 (0.0490) time: 2.8046 data: 0.0025 max mem: 19788 +Epoch: [8] [2020/2138] eta: 0:05:40 lr: 3.981355143209817e-05 loss: 0.0432 (0.0490) time: 2.8057 data: 0.0025 max mem: 19788 +Epoch: [8] [2030/2138] eta: 0:05:11 lr: 3.9808154569963236e-05 loss: 0.0410 (0.0490) time: 2.7992 data: 0.0024 max mem: 19788 +Epoch: [8] [2040/2138] eta: 0:04:42 lr: 3.9802757626531284e-05 loss: 0.0367 (0.0489) time: 2.7968 data: 0.0021 max mem: 19788 +Epoch: [8] [2050/2138] eta: 0:04:14 lr: 3.979736060178884e-05 loss: 0.0423 (0.0489) time: 2.7984 data: 0.0020 max mem: 19788 +Epoch: [8] [2060/2138] eta: 0:03:45 lr: 3.979196349572242e-05 loss: 0.0414 (0.0489) time: 2.7966 data: 0.0021 max mem: 19788 +Epoch: [8] [2070/2138] eta: 0:03:16 lr: 3.9786566308318546e-05 loss: 0.0386 (0.0489) time: 2.7943 data: 0.0022 max mem: 19788 +Epoch: [8] [2080/2138] eta: 0:02:47 lr: 3.9781169039563736e-05 loss: 0.0381 (0.0488) time: 2.7909 data: 0.0022 max mem: 19788 +Epoch: [8] [2090/2138] eta: 0:02:18 lr: 3.9775771689444494e-05 loss: 0.0381 (0.0488) time: 2.7927 data: 0.0021 max mem: 19788 +Epoch: [8] [2100/2138] eta: 0:01:49 lr: 3.9770374257947326e-05 loss: 0.0388 (0.0488) time: 2.7977 data: 0.0023 max mem: 19788 +Epoch: [8] [2110/2138] eta: 0:01:20 lr: 3.9764976745058736e-05 loss: 0.0422 (0.0488) time: 2.7949 data: 0.0023 max mem: 19788 +Epoch: [8] [2120/2138] eta: 0:00:51 lr: 3.975957915076522e-05 loss: 0.0447 (0.0489) time: 2.7894 data: 0.0021 max mem: 19788 +Epoch: [8] [2130/2138] eta: 0:00:23 lr: 3.975418147505327e-05 loss: 0.0522 (0.0489) time: 2.7886 data: 0.0021 max mem: 19788 +Epoch: [8] Total time: 1:42:44 +Test: [ 0/21770] eta: 16:29:03 time: 2.7259 data: 2.5859 max mem: 19788 +Test: [ 100/21770] eta: 0:25:17 time: 0.0430 data: 0.0016 max mem: 19788 +Test: [ 200/21770] eta: 0:21:09 time: 0.0471 data: 0.0015 max mem: 19788 +Test: [ 300/21770] eta: 0:19:28 time: 0.0428 data: 0.0015 max mem: 19788 +Test: [ 400/21770] eta: 0:18:27 time: 0.0437 data: 0.0015 max mem: 19788 +Test: [ 500/21770] eta: 0:17:52 time: 0.0450 data: 0.0014 max mem: 19788 +Test: [ 600/21770] eta: 0:17:24 time: 0.0431 data: 0.0015 max mem: 19788 +Test: [ 700/21770] eta: 0:17:12 time: 0.0456 data: 0.0014 max mem: 19788 +Test: [ 800/21770] eta: 0:16:56 time: 0.0458 data: 0.0016 max mem: 19788 +Test: [ 900/21770] eta: 0:16:46 time: 0.0434 data: 0.0015 max mem: 19788 +Test: [ 1000/21770] eta: 0:16:35 time: 0.0484 data: 0.0015 max mem: 19788 +Test: [ 1100/21770] eta: 0:16:28 time: 0.0478 data: 0.0014 max mem: 19788 +Test: [ 1200/21770] eta: 0:16:19 time: 0.0434 data: 0.0014 max mem: 19788 +Test: [ 1300/21770] eta: 0:16:08 time: 0.0454 data: 0.0015 max mem: 19788 +Test: [ 1400/21770] eta: 0:15:59 time: 0.0442 data: 0.0016 max mem: 19788 +Test: [ 1500/21770] eta: 0:15:54 time: 0.0424 data: 0.0014 max mem: 19788 +Test: [ 1600/21770] eta: 0:15:46 time: 0.0477 data: 0.0016 max mem: 19788 +Test: [ 1700/21770] eta: 0:15:40 time: 0.0431 data: 0.0016 max mem: 19788 +Test: [ 1800/21770] eta: 0:15:36 time: 0.0473 data: 0.0017 max mem: 19788 +Test: [ 1900/21770] eta: 0:15:32 time: 0.0437 data: 0.0015 max mem: 19788 +Test: [ 2000/21770] eta: 0:15:26 time: 0.0439 data: 0.0016 max mem: 19788 +Test: [ 2100/21770] eta: 0:15:18 time: 0.0433 data: 0.0012 max mem: 19788 +Test: [ 2200/21770] eta: 0:15:15 time: 0.0424 data: 0.0014 max mem: 19788 +Test: [ 2300/21770] eta: 0:15:07 time: 0.0421 data: 0.0014 max mem: 19788 +Test: [ 2400/21770] eta: 0:15:00 time: 0.0419 data: 0.0014 max mem: 19788 +Test: [ 2500/21770] eta: 0:14:55 time: 0.0434 data: 0.0014 max mem: 19788 +Test: [ 2600/21770] eta: 0:14:48 time: 0.0434 data: 0.0014 max mem: 19788 +Test: [ 2700/21770] eta: 0:14:44 time: 0.0475 data: 0.0016 max mem: 19788 +Test: [ 2800/21770] eta: 0:14:40 time: 0.0421 data: 0.0013 max mem: 19788 +Test: [ 2900/21770] eta: 0:14:35 time: 0.0489 data: 0.0017 max mem: 19788 +Test: [ 3000/21770] eta: 0:14:31 time: 0.0462 data: 0.0016 max mem: 19788 +Test: [ 3100/21770] eta: 0:14:26 time: 0.0441 data: 0.0015 max mem: 19788 +Test: [ 3200/21770] eta: 0:14:23 time: 0.0505 data: 0.0015 max mem: 19788 +Test: [ 3300/21770] eta: 0:14:20 time: 0.0451 data: 0.0013 max mem: 19788 +Test: [ 3400/21770] eta: 0:14:15 time: 0.0466 data: 0.0015 max mem: 19788 +Test: [ 3500/21770] eta: 0:14:09 time: 0.0438 data: 0.0015 max mem: 19788 +Test: [ 3600/21770] eta: 0:14:04 time: 0.0464 data: 0.0014 max mem: 19788 +Test: [ 3700/21770] eta: 0:13:59 time: 0.0451 data: 0.0014 max mem: 19788 +Test: [ 3800/21770] eta: 0:13:54 time: 0.0437 data: 0.0014 max mem: 19788 +Test: [ 3900/21770] eta: 0:13:48 time: 0.0457 data: 0.0015 max mem: 19788 +Test: [ 4000/21770] eta: 0:13:44 time: 0.0480 data: 0.0018 max mem: 19788 +Test: [ 4100/21770] eta: 0:13:40 time: 0.0520 data: 0.0018 max mem: 19788 +Test: [ 4200/21770] eta: 0:13:36 time: 0.0457 data: 0.0015 max mem: 19788 +Test: [ 4300/21770] eta: 0:13:31 time: 0.0431 data: 0.0015 max mem: 19788 +Test: [ 4400/21770] eta: 0:13:26 time: 0.0522 data: 0.0015 max mem: 19788 +Test: [ 4500/21770] eta: 0:13:23 time: 0.0470 data: 0.0015 max mem: 19788 +Test: [ 4600/21770] eta: 0:13:17 time: 0.0431 data: 0.0015 max mem: 19788 +Test: [ 4700/21770] eta: 0:13:14 time: 0.0489 data: 0.0016 max mem: 19788 +Test: [ 4800/21770] eta: 0:13:10 time: 0.0454 data: 0.0017 max mem: 19788 +Test: [ 4900/21770] eta: 0:13:04 time: 0.0426 data: 0.0014 max mem: 19788 +Test: [ 5000/21770] eta: 0:12:59 time: 0.0436 data: 0.0018 max mem: 19788 +Test: [ 5100/21770] eta: 0:12:55 time: 0.0514 data: 0.0018 max mem: 19788 +Test: [ 5200/21770] eta: 0:12:52 time: 0.0500 data: 0.0016 max mem: 19788 +Test: [ 5300/21770] eta: 0:12:47 time: 0.0509 data: 0.0017 max mem: 19788 +Test: [ 5400/21770] eta: 0:12:41 time: 0.0438 data: 0.0017 max mem: 19788 +Test: [ 5500/21770] eta: 0:12:37 time: 0.0447 data: 0.0016 max mem: 19788 +Test: [ 5600/21770] eta: 0:12:32 time: 0.0437 data: 0.0015 max mem: 19788 +Test: [ 5700/21770] eta: 0:12:28 time: 0.0491 data: 0.0016 max mem: 19788 +Test: [ 5800/21770] eta: 0:12:23 time: 0.0487 data: 0.0017 max mem: 19788 +Test: [ 5900/21770] eta: 0:12:18 time: 0.0481 data: 0.0017 max mem: 19788 +Test: [ 6000/21770] eta: 0:12:13 time: 0.0439 data: 0.0014 max mem: 19788 +Test: [ 6100/21770] eta: 0:12:08 time: 0.0426 data: 0.0015 max mem: 19788 +Test: [ 6200/21770] eta: 0:12:03 time: 0.0437 data: 0.0015 max mem: 19788 +Test: [ 6300/21770] eta: 0:11:58 time: 0.0434 data: 0.0015 max mem: 19788 +Test: [ 6400/21770] eta: 0:11:53 time: 0.0521 data: 0.0018 max mem: 19788 +Test: [ 6500/21770] eta: 0:11:48 time: 0.0474 data: 0.0016 max mem: 19788 +Test: [ 6600/21770] eta: 0:11:44 time: 0.0449 data: 0.0015 max mem: 19788 +Test: [ 6700/21770] eta: 0:11:39 time: 0.0436 data: 0.0015 max mem: 19788 +Test: [ 6800/21770] eta: 0:11:35 time: 0.0516 data: 0.0018 max mem: 19788 +Test: [ 6900/21770] eta: 0:11:30 time: 0.0436 data: 0.0014 max mem: 19788 +Test: [ 7000/21770] eta: 0:11:24 time: 0.0419 data: 0.0014 max mem: 19788 +Test: [ 7100/21770] eta: 0:11:19 time: 0.0486 data: 0.0016 max mem: 19788 +Test: [ 7200/21770] eta: 0:11:14 time: 0.0433 data: 0.0015 max mem: 19788 +Test: [ 7300/21770] eta: 0:11:09 time: 0.0442 data: 0.0014 max mem: 19788 +Test: [ 7400/21770] eta: 0:11:04 time: 0.0438 data: 0.0013 max mem: 19788 +Test: [ 7500/21770] eta: 0:10:59 time: 0.0439 data: 0.0015 max mem: 19788 +Test: [ 7600/21770] eta: 0:10:54 time: 0.0440 data: 0.0016 max mem: 19788 +Test: [ 7700/21770] eta: 0:10:50 time: 0.0462 data: 0.0014 max mem: 19788 +Test: [ 7800/21770] eta: 0:10:46 time: 0.0528 data: 0.0015 max mem: 19788 +Test: [ 7900/21770] eta: 0:10:42 time: 0.0438 data: 0.0016 max mem: 19788 +Test: [ 8000/21770] eta: 0:10:38 time: 0.0464 data: 0.0015 max mem: 19788 +Test: [ 8100/21770] eta: 0:10:32 time: 0.0439 data: 0.0014 max mem: 19788 +Test: [ 8200/21770] eta: 0:10:28 time: 0.0489 data: 0.0016 max mem: 19788 +Test: [ 8300/21770] eta: 0:10:24 time: 0.0519 data: 0.0017 max mem: 19788 +Test: [ 8400/21770] eta: 0:10:19 time: 0.0438 data: 0.0015 max mem: 19788 +Test: [ 8500/21770] eta: 0:10:14 time: 0.0438 data: 0.0017 max mem: 19788 +Test: [ 8600/21770] eta: 0:10:09 time: 0.0495 data: 0.0017 max mem: 19788 +Test: [ 8700/21770] eta: 0:10:04 time: 0.0442 data: 0.0018 max mem: 19788 +Test: [ 8800/21770] eta: 0:09:59 time: 0.0438 data: 0.0015 max mem: 19788 +Test: [ 8900/21770] eta: 0:09:55 time: 0.0526 data: 0.0018 max mem: 19788 +Test: [ 9000/21770] eta: 0:09:51 time: 0.0493 data: 0.0015 max mem: 19788 +Test: [ 9100/21770] eta: 0:09:46 time: 0.0425 data: 0.0015 max mem: 19788 +Test: [ 9200/21770] eta: 0:09:42 time: 0.0427 data: 0.0015 max mem: 19788 +Test: [ 9300/21770] eta: 0:09:37 time: 0.0481 data: 0.0016 max mem: 19788 +Test: [ 9400/21770] eta: 0:09:32 time: 0.0440 data: 0.0014 max mem: 19788 +Test: [ 9500/21770] eta: 0:09:28 time: 0.0522 data: 0.0017 max mem: 19788 +Test: [ 9600/21770] eta: 0:09:23 time: 0.0451 data: 0.0014 max mem: 19788 +Test: [ 9700/21770] eta: 0:09:18 time: 0.0462 data: 0.0015 max mem: 19788 +Test: [ 9800/21770] eta: 0:09:14 time: 0.0433 data: 0.0014 max mem: 19788 +Test: [ 9900/21770] eta: 0:09:09 time: 0.0520 data: 0.0018 max mem: 19788 +Test: [10000/21770] eta: 0:09:05 time: 0.0430 data: 0.0016 max mem: 19788 +Test: [10100/21770] eta: 0:09:00 time: 0.0436 data: 0.0015 max mem: 19788 +Test: [10200/21770] eta: 0:08:55 time: 0.0430 data: 0.0013 max mem: 19788 +Test: [10300/21770] eta: 0:08:51 time: 0.0511 data: 0.0018 max mem: 19788 +Test: [10400/21770] eta: 0:08:47 time: 0.0518 data: 0.0017 max mem: 19788 +Test: [10500/21770] eta: 0:08:42 time: 0.0476 data: 0.0016 max mem: 19788 +Test: [10600/21770] eta: 0:08:38 time: 0.0490 data: 0.0017 max mem: 19788 +Test: [10700/21770] eta: 0:08:33 time: 0.0528 data: 0.0018 max mem: 19788 +Test: [10800/21770] eta: 0:08:29 time: 0.0459 data: 0.0015 max mem: 19788 +Test: [10900/21770] eta: 0:08:24 time: 0.0428 data: 0.0014 max mem: 19788 +Test: [11000/21770] eta: 0:08:19 time: 0.0435 data: 0.0014 max mem: 19788 +Test: [11100/21770] eta: 0:08:15 time: 0.0538 data: 0.0017 max mem: 19788 +Test: [11200/21770] eta: 0:08:10 time: 0.0499 data: 0.0016 max mem: 19788 +Test: [11300/21770] eta: 0:08:06 time: 0.0517 data: 0.0016 max mem: 19788 +Test: [11400/21770] eta: 0:08:02 time: 0.0493 data: 0.0017 max mem: 19788 +Test: [11500/21770] eta: 0:07:57 time: 0.0488 data: 0.0017 max mem: 19788 +Test: [11600/21770] eta: 0:07:53 time: 0.0480 data: 0.0016 max mem: 19788 +Test: [11700/21770] eta: 0:07:48 time: 0.0427 data: 0.0014 max mem: 19788 +Test: [11800/21770] eta: 0:07:43 time: 0.0509 data: 0.0016 max mem: 19788 +Test: [11900/21770] eta: 0:07:39 time: 0.0519 data: 0.0018 max mem: 19788 +Test: [12000/21770] eta: 0:07:34 time: 0.0445 data: 0.0014 max mem: 19788 +Test: [12100/21770] eta: 0:07:30 time: 0.0423 data: 0.0014 max mem: 19788 +Test: [12200/21770] eta: 0:07:25 time: 0.0479 data: 0.0015 max mem: 19788 +Test: [12300/21770] eta: 0:07:20 time: 0.0451 data: 0.0015 max mem: 19788 +Test: [12400/21770] eta: 0:07:16 time: 0.0427 data: 0.0015 max mem: 19788 +Test: [12500/21770] eta: 0:07:11 time: 0.0531 data: 0.0018 max mem: 19788 +Test: [12600/21770] eta: 0:07:07 time: 0.0472 data: 0.0016 max mem: 19788 +Test: [12700/21770] eta: 0:07:02 time: 0.0498 data: 0.0017 max mem: 19788 +Test: [12800/21770] eta: 0:06:57 time: 0.0423 data: 0.0013 max mem: 19788 +Test: [12900/21770] eta: 0:06:53 time: 0.0427 data: 0.0013 max mem: 19788 +Test: [13000/21770] eta: 0:06:48 time: 0.0463 data: 0.0015 max mem: 19788 +Test: [13100/21770] eta: 0:06:43 time: 0.0489 data: 0.0016 max mem: 19788 +Test: [13200/21770] eta: 0:06:38 time: 0.0518 data: 0.0017 max mem: 19788 +Test: [13300/21770] eta: 0:06:34 time: 0.0451 data: 0.0015 max mem: 19788 +Test: [13400/21770] eta: 0:06:29 time: 0.0498 data: 0.0017 max mem: 19788 +Test: [13500/21770] eta: 0:06:25 time: 0.0435 data: 0.0014 max mem: 19788 +Test: [13600/21770] eta: 0:06:20 time: 0.0433 data: 0.0015 max mem: 19788 +Test: [13700/21770] eta: 0:06:15 time: 0.0481 data: 0.0018 max mem: 19788 +Test: [13800/21770] eta: 0:06:11 time: 0.0513 data: 0.0016 max mem: 19788 +Test: [13900/21770] eta: 0:06:06 time: 0.0522 data: 0.0017 max mem: 19788 +Test: [14000/21770] eta: 0:06:01 time: 0.0510 data: 0.0016 max mem: 19788 +Test: [14100/21770] eta: 0:05:57 time: 0.0428 data: 0.0015 max mem: 19788 +Test: [14200/21770] eta: 0:05:52 time: 0.0468 data: 0.0015 max mem: 19788 +Test: [14300/21770] eta: 0:05:48 time: 0.0445 data: 0.0015 max mem: 19788 +Test: [14400/21770] eta: 0:05:43 time: 0.0427 data: 0.0014 max mem: 19788 +Test: [14500/21770] eta: 0:05:38 time: 0.0521 data: 0.0015 max mem: 19788 +Test: [14600/21770] eta: 0:05:34 time: 0.0430 data: 0.0013 max mem: 19788 +Test: [14700/21770] eta: 0:05:29 time: 0.0433 data: 0.0014 max mem: 19788 +Test: [14800/21770] eta: 0:05:24 time: 0.0434 data: 0.0014 max mem: 19788 +Test: [14900/21770] eta: 0:05:19 time: 0.0473 data: 0.0017 max mem: 19788 +Test: [15000/21770] eta: 0:05:15 time: 0.0517 data: 0.0017 max mem: 19788 +Test: [15100/21770] eta: 0:05:10 time: 0.0532 data: 0.0016 max mem: 19788 +Test: [15200/21770] eta: 0:05:06 time: 0.0525 data: 0.0018 max mem: 19788 +Test: [15300/21770] eta: 0:05:01 time: 0.0468 data: 0.0016 max mem: 19788 +Test: [15400/21770] eta: 0:04:56 time: 0.0430 data: 0.0013 max mem: 19788 +Test: [15500/21770] eta: 0:04:52 time: 0.0458 data: 0.0017 max mem: 19788 +Test: [15600/21770] eta: 0:04:47 time: 0.0459 data: 0.0016 max mem: 19788 +Test: [15700/21770] eta: 0:04:42 time: 0.0441 data: 0.0015 max mem: 19788 +Test: [15800/21770] eta: 0:04:38 time: 0.0431 data: 0.0015 max mem: 19788 +Test: [15900/21770] eta: 0:04:33 time: 0.0484 data: 0.0016 max mem: 19788 +Test: [16000/21770] eta: 0:04:28 time: 0.0496 data: 0.0016 max mem: 19788 +Test: [16100/21770] eta: 0:04:24 time: 0.0541 data: 0.0018 max mem: 19788 +Test: [16200/21770] eta: 0:04:19 time: 0.0426 data: 0.0014 max mem: 19788 +Test: [16300/21770] eta: 0:04:14 time: 0.0438 data: 0.0014 max mem: 19788 +Test: [16400/21770] eta: 0:04:10 time: 0.0445 data: 0.0015 max mem: 19788 +Test: [16500/21770] eta: 0:04:05 time: 0.0437 data: 0.0013 max mem: 19788 +Test: [16600/21770] eta: 0:04:00 time: 0.0434 data: 0.0013 max mem: 19788 +Test: [16700/21770] eta: 0:03:56 time: 0.0494 data: 0.0017 max mem: 19788 +Test: [16800/21770] eta: 0:03:51 time: 0.0449 data: 0.0016 max mem: 19788 +Test: [16900/21770] eta: 0:03:46 time: 0.0482 data: 0.0017 max mem: 19788 +Test: [17000/21770] eta: 0:03:42 time: 0.0444 data: 0.0016 max mem: 19788 +Test: [17100/21770] eta: 0:03:37 time: 0.0444 data: 0.0015 max mem: 19788 +Test: [17200/21770] eta: 0:03:32 time: 0.0469 data: 0.0016 max mem: 19788 +Test: [17300/21770] eta: 0:03:28 time: 0.0511 data: 0.0015 max mem: 19788 +Test: [17400/21770] eta: 0:03:23 time: 0.0444 data: 0.0014 max mem: 19788 +Test: [17500/21770] eta: 0:03:18 time: 0.0525 data: 0.0018 max mem: 19788 +Test: [17600/21770] eta: 0:03:14 time: 0.0440 data: 0.0015 max mem: 19788 +Test: [17700/21770] eta: 0:03:09 time: 0.0435 data: 0.0014 max mem: 19788 +Test: [17800/21770] eta: 0:03:04 time: 0.0429 data: 0.0015 max mem: 19788 +Test: [17900/21770] eta: 0:03:00 time: 0.0536 data: 0.0015 max mem: 19788 +Test: [18000/21770] eta: 0:02:55 time: 0.0430 data: 0.0014 max mem: 19788 +Test: [18100/21770] eta: 0:02:50 time: 0.0425 data: 0.0013 max mem: 19788 +Test: [18200/21770] eta: 0:02:46 time: 0.0516 data: 0.0016 max mem: 19788 +Test: [18300/21770] eta: 0:02:41 time: 0.0441 data: 0.0015 max mem: 19788 +Test: [18400/21770] eta: 0:02:36 time: 0.0432 data: 0.0016 max mem: 19788 +Test: [18500/21770] eta: 0:02:32 time: 0.0438 data: 0.0017 max mem: 19788 +Test: [18600/21770] eta: 0:02:27 time: 0.0442 data: 0.0013 max mem: 19788 +Test: [18700/21770] eta: 0:02:22 time: 0.0515 data: 0.0017 max mem: 19788 +Test: [18800/21770] eta: 0:02:18 time: 0.0423 data: 0.0014 max mem: 19788 +Test: [18900/21770] eta: 0:02:13 time: 0.0435 data: 0.0014 max mem: 19788 +Test: [19000/21770] eta: 0:02:08 time: 0.0493 data: 0.0016 max mem: 19788 +Test: [19100/21770] eta: 0:02:04 time: 0.0522 data: 0.0018 max mem: 19788 +Test: [19200/21770] eta: 0:01:59 time: 0.0430 data: 0.0014 max mem: 19788 +Test: [19300/21770] eta: 0:01:54 time: 0.0468 data: 0.0017 max mem: 19788 +Test: [19400/21770] eta: 0:01:50 time: 0.0442 data: 0.0015 max mem: 19788 +Test: [19500/21770] eta: 0:01:45 time: 0.0492 data: 0.0018 max mem: 19788 +Test: [19600/21770] eta: 0:01:40 time: 0.0433 data: 0.0016 max mem: 19788 +Test: [19700/21770] eta: 0:01:36 time: 0.0476 data: 0.0018 max mem: 19788 +Test: [19800/21770] eta: 0:01:31 time: 0.0475 data: 0.0015 max mem: 19788 +Test: [19900/21770] eta: 0:01:26 time: 0.0515 data: 0.0017 max mem: 19788 +Test: [20000/21770] eta: 0:01:22 time: 0.0443 data: 0.0013 max mem: 19788 +Test: [20100/21770] eta: 0:01:17 time: 0.0430 data: 0.0016 max mem: 19788 +Test: [20200/21770] eta: 0:01:12 time: 0.0505 data: 0.0016 max mem: 19788 +Test: [20300/21770] eta: 0:01:08 time: 0.0440 data: 0.0014 max mem: 19788 +Test: [20400/21770] eta: 0:01:03 time: 0.0430 data: 0.0013 max mem: 19788 +Test: [20500/21770] eta: 0:00:58 time: 0.0431 data: 0.0014 max mem: 19788 +Test: [20600/21770] eta: 0:00:54 time: 0.0444 data: 0.0017 max mem: 19788 +Test: [20700/21770] eta: 0:00:49 time: 0.0469 data: 0.0014 max mem: 19788 +Test: [20800/21770] eta: 0:00:45 time: 0.0436 data: 0.0015 max mem: 19788 +Test: [20900/21770] eta: 0:00:40 time: 0.0453 data: 0.0015 max mem: 19788 +Test: [21000/21770] eta: 0:00:35 time: 0.0436 data: 0.0015 max mem: 19788 +Test: [21100/21770] eta: 0:00:31 time: 0.0444 data: 0.0016 max mem: 19788 +Test: [21200/21770] eta: 0:00:26 time: 0.0430 data: 0.0016 max mem: 19788 +Test: [21300/21770] eta: 0:00:21 time: 0.0440 data: 0.0015 max mem: 19788 +Test: [21400/21770] eta: 0:00:17 time: 0.0442 data: 0.0015 max mem: 19788 +Test: [21500/21770] eta: 0:00:12 time: 0.0431 data: 0.0014 max mem: 19788 +Test: [21600/21770] eta: 0:00:07 time: 0.0486 data: 0.0016 max mem: 19788 +Test: [21700/21770] eta: 0:00:03 time: 0.0445 data: 0.0014 max mem: 19788 +Test: Total time: 0:16:49 +Final results: +Mean IoU is 62.84 + + precision@0.5 = 69.80 + precision@0.6 = 64.35 + precision@0.7 = 57.07 + precision@0.8 = 45.86 + precision@0.9 = 22.22 + overall IoU = 63.97 + mean IoU = 62.84 + +Mean accuracy for one-to-zero sample is 79.16 + +Average object IoU 0.6283890447468565 +Overall IoU 63.96959686279297 +Better epoch: 8 + +Epoch: [9] [ 0/2138] eta: 3:40:06 lr: 3.974986327585336e-05 loss: 0.0553 (0.0553) time: 6.1772 data: 1.3110 max mem: 19788 +Epoch: [9] [ 10/2138] eta: 1:50:32 lr: 3.974446545355418e-05 loss: 0.0356 (0.0455) time: 3.1169 data: 0.1212 max mem: 19788 +Epoch: [9] [ 20/2138] eta: 1:45:00 lr: 3.973906754979872e-05 loss: 0.0372 (0.0439) time: 2.8146 data: 0.0021 max mem: 19788 +Epoch: [9] [ 30/2138] eta: 1:42:40 lr: 3.9733669564573464e-05 loss: 0.0453 (0.0457) time: 2.8155 data: 0.0023 max mem: 19788 +Epoch: [9] [ 40/2138] eta: 1:41:18 lr: 3.9728271497864876e-05 loss: 0.0467 (0.0486) time: 2.8159 data: 0.0024 max mem: 19788 +Epoch: [9] [ 50/2138] eta: 1:40:11 lr: 3.972287334965944e-05 loss: 0.0461 (0.0478) time: 2.8119 data: 0.0024 max mem: 19788 +Epoch: [9] [ 60/2138] eta: 1:39:19 lr: 3.9717475119943605e-05 loss: 0.0473 (0.0497) time: 2.8083 data: 0.0024 max mem: 19788 +Epoch: [9] [ 70/2138] eta: 1:38:34 lr: 3.971207680870382e-05 loss: 0.0455 (0.0489) time: 2.8115 data: 0.0025 max mem: 19788 +Epoch: [9] [ 80/2138] eta: 1:37:54 lr: 3.970667841592656e-05 loss: 0.0424 (0.0481) time: 2.8136 data: 0.0024 max mem: 19788 +Epoch: [9] [ 90/2138] eta: 1:37:16 lr: 3.970127994159828e-05 loss: 0.0372 (0.0472) time: 2.8147 data: 0.0025 max mem: 19788 +Epoch: [9] [ 100/2138] eta: 1:36:39 lr: 3.969588138570541e-05 loss: 0.0444 (0.0489) time: 2.8106 data: 0.0026 max mem: 19788 +Epoch: [9] [ 110/2138] eta: 1:36:03 lr: 3.9690482748234394e-05 loss: 0.0484 (0.0491) time: 2.8060 data: 0.0024 max mem: 19788 +Epoch: [9] [ 120/2138] eta: 1:35:30 lr: 3.968508402917168e-05 loss: 0.0462 (0.0484) time: 2.8086 data: 0.0022 max mem: 19788 +Epoch: [9] [ 130/2138] eta: 1:34:56 lr: 3.967968522850369e-05 loss: 0.0436 (0.0481) time: 2.8092 data: 0.0022 max mem: 19788 +Epoch: [9] [ 140/2138] eta: 1:34:24 lr: 3.967428634621686e-05 loss: 0.0465 (0.0479) time: 2.8064 data: 0.0025 max mem: 19788 +Epoch: [9] [ 150/2138] eta: 1:33:51 lr: 3.9668887382297614e-05 loss: 0.0459 (0.0479) time: 2.8054 data: 0.0028 max mem: 19788 +Epoch: [9] [ 160/2138] eta: 1:33:19 lr: 3.9663488336732376e-05 loss: 0.0439 (0.0482) time: 2.8018 data: 0.0024 max mem: 19788 +Epoch: [9] [ 170/2138] eta: 1:32:48 lr: 3.965808920950755e-05 loss: 0.0439 (0.0481) time: 2.8039 data: 0.0023 max mem: 19788 +Epoch: [9] [ 180/2138] eta: 1:32:17 lr: 3.9652690000609566e-05 loss: 0.0431 (0.0478) time: 2.8052 data: 0.0025 max mem: 19788 +Epoch: [9] [ 190/2138] eta: 1:31:46 lr: 3.9647290710024814e-05 loss: 0.0401 (0.0473) time: 2.8026 data: 0.0024 max mem: 19788 +Epoch: [9] [ 200/2138] eta: 1:31:15 lr: 3.964189133773971e-05 loss: 0.0354 (0.0468) time: 2.8027 data: 0.0024 max mem: 19788 +Epoch: [9] [ 210/2138] eta: 1:30:46 lr: 3.9636491883740646e-05 loss: 0.0342 (0.0465) time: 2.8074 data: 0.0024 max mem: 19788 +Epoch: [9] [ 220/2138] eta: 1:30:16 lr: 3.963109234801402e-05 loss: 0.0357 (0.0463) time: 2.8065 data: 0.0026 max mem: 19788 +Epoch: [9] [ 230/2138] eta: 1:29:45 lr: 3.962569273054622e-05 loss: 0.0447 (0.0465) time: 2.8015 data: 0.0028 max mem: 19788 +Epoch: [9] [ 240/2138] eta: 1:29:16 lr: 3.962029303132364e-05 loss: 0.0482 (0.0463) time: 2.8029 data: 0.0024 max mem: 19788 +Epoch: [9] [ 250/2138] eta: 1:28:46 lr: 3.961489325033265e-05 loss: 0.0389 (0.0461) time: 2.8044 data: 0.0023 max mem: 19788 +Epoch: [9] [ 260/2138] eta: 1:28:17 lr: 3.9609493387559635e-05 loss: 0.0354 (0.0462) time: 2.8046 data: 0.0023 max mem: 19788 +Epoch: [9] [ 270/2138] eta: 1:27:48 lr: 3.9604093442990964e-05 loss: 0.0462 (0.0462) time: 2.8053 data: 0.0025 max mem: 19788 +Epoch: [9] [ 280/2138] eta: 1:27:18 lr: 3.959869341661301e-05 loss: 0.0458 (0.0463) time: 2.8042 data: 0.0024 max mem: 19788 +Epoch: [9] [ 290/2138] eta: 1:26:49 lr: 3.9593293308412136e-05 loss: 0.0475 (0.0466) time: 2.8067 data: 0.0022 max mem: 19788 +Epoch: [9] [ 300/2138] eta: 1:26:21 lr: 3.95878931183747e-05 loss: 0.0510 (0.0467) time: 2.8165 data: 0.0023 max mem: 19788 +Epoch: [9] [ 310/2138] eta: 1:25:53 lr: 3.958249284648706e-05 loss: 0.0429 (0.0465) time: 2.8162 data: 0.0024 max mem: 19788 +Epoch: [9] [ 320/2138] eta: 1:25:24 lr: 3.957709249273556e-05 loss: 0.0328 (0.0461) time: 2.8099 data: 0.0024 max mem: 19788 +Epoch: [9] [ 330/2138] eta: 1:24:55 lr: 3.9571692057106566e-05 loss: 0.0367 (0.0464) time: 2.8079 data: 0.0021 max mem: 19788 +Epoch: [9] [ 340/2138] eta: 1:24:27 lr: 3.95662915395864e-05 loss: 0.0440 (0.0464) time: 2.8080 data: 0.0021 max mem: 19788 +Epoch: [9] [ 350/2138] eta: 1:23:57 lr: 3.9560890940161396e-05 loss: 0.0409 (0.0464) time: 2.8053 data: 0.0023 max mem: 19788 +Epoch: [9] [ 360/2138] eta: 1:23:29 lr: 3.955549025881792e-05 loss: 0.0438 (0.0465) time: 2.8025 data: 0.0023 max mem: 19788 +Epoch: [9] [ 370/2138] eta: 1:23:00 lr: 3.9550089495542276e-05 loss: 0.0422 (0.0465) time: 2.8078 data: 0.0021 max mem: 19788 +Epoch: [9] [ 380/2138] eta: 1:22:32 lr: 3.9544688650320795e-05 loss: 0.0405 (0.0463) time: 2.8103 data: 0.0024 max mem: 19788 +Epoch: [9] [ 390/2138] eta: 1:22:03 lr: 3.953928772313979e-05 loss: 0.0381 (0.0461) time: 2.8092 data: 0.0026 max mem: 19788 +Epoch: [9] [ 400/2138] eta: 1:21:35 lr: 3.95338867139856e-05 loss: 0.0408 (0.0462) time: 2.8107 data: 0.0024 max mem: 19788 +Epoch: [9] [ 410/2138] eta: 1:21:07 lr: 3.9528485622844514e-05 loss: 0.0415 (0.0462) time: 2.8140 data: 0.0024 max mem: 19788 +Epoch: [9] [ 420/2138] eta: 1:20:38 lr: 3.952308444970285e-05 loss: 0.0396 (0.0460) time: 2.8135 data: 0.0025 max mem: 19788 +Epoch: [9] [ 430/2138] eta: 1:20:10 lr: 3.95176831945469e-05 loss: 0.0372 (0.0459) time: 2.8096 data: 0.0028 max mem: 19788 +Epoch: [9] [ 440/2138] eta: 1:19:41 lr: 3.951228185736299e-05 loss: 0.0407 (0.0459) time: 2.8058 data: 0.0030 max mem: 19788 +Epoch: [9] [ 450/2138] eta: 1:19:12 lr: 3.950688043813739e-05 loss: 0.0446 (0.0458) time: 2.8015 data: 0.0029 max mem: 19788 +Epoch: [9] [ 460/2138] eta: 1:18:43 lr: 3.9501478936856395e-05 loss: 0.0417 (0.0457) time: 2.7989 data: 0.0028 max mem: 19788 +Epoch: [9] [ 470/2138] eta: 1:18:15 lr: 3.94960773535063e-05 loss: 0.0396 (0.0457) time: 2.7990 data: 0.0027 max mem: 19788 +Epoch: [9] [ 480/2138] eta: 1:17:46 lr: 3.949067568807338e-05 loss: 0.0451 (0.0460) time: 2.8006 data: 0.0025 max mem: 19788 +Epoch: [9] [ 490/2138] eta: 1:17:17 lr: 3.948527394054391e-05 loss: 0.0466 (0.0459) time: 2.8003 data: 0.0022 max mem: 19788 +Epoch: [9] [ 500/2138] eta: 1:16:49 lr: 3.947987211090417e-05 loss: 0.0454 (0.0459) time: 2.7973 data: 0.0022 max mem: 19788 +Epoch: [9] [ 510/2138] eta: 1:16:20 lr: 3.947447019914042e-05 loss: 0.0362 (0.0458) time: 2.8011 data: 0.0021 max mem: 19788 +Epoch: [9] [ 520/2138] eta: 1:15:52 lr: 3.9469068205238926e-05 loss: 0.0417 (0.0459) time: 2.8076 data: 0.0023 max mem: 19788 +Epoch: [9] [ 530/2138] eta: 1:15:24 lr: 3.946366612918596e-05 loss: 0.0417 (0.0458) time: 2.8114 data: 0.0025 max mem: 19788 +Epoch: [9] [ 540/2138] eta: 1:14:55 lr: 3.945826397096776e-05 loss: 0.0372 (0.0457) time: 2.8076 data: 0.0026 max mem: 19788 +Epoch: [9] [ 550/2138] eta: 1:14:27 lr: 3.945286173057059e-05 loss: 0.0428 (0.0458) time: 2.8039 data: 0.0026 max mem: 19788 +Epoch: [9] [ 560/2138] eta: 1:13:59 lr: 3.944745940798068e-05 loss: 0.0457 (0.0458) time: 2.8030 data: 0.0022 max mem: 19788 +Epoch: [9] [ 570/2138] eta: 1:13:30 lr: 3.94420570031843e-05 loss: 0.0457 (0.0459) time: 2.8042 data: 0.0021 max mem: 19788 +Epoch: [9] [ 580/2138] eta: 1:13:02 lr: 3.943665451616765e-05 loss: 0.0457 (0.0459) time: 2.8087 data: 0.0021 max mem: 19788 +Epoch: [9] [ 590/2138] eta: 1:12:34 lr: 3.9431251946917e-05 loss: 0.0411 (0.0458) time: 2.8053 data: 0.0020 max mem: 19788 +Epoch: [9] [ 600/2138] eta: 1:12:05 lr: 3.9425849295418555e-05 loss: 0.0447 (0.0458) time: 2.8040 data: 0.0023 max mem: 19788 +Epoch: [9] [ 610/2138] eta: 1:11:37 lr: 3.942044656165855e-05 loss: 0.0447 (0.0459) time: 2.8042 data: 0.0025 max mem: 19788 +Epoch: [9] [ 620/2138] eta: 1:11:10 lr: 3.94150437456232e-05 loss: 0.0499 (0.0462) time: 2.8225 data: 0.0025 max mem: 19788 +Epoch: [9] [ 630/2138] eta: 1:10:41 lr: 3.9409640847298725e-05 loss: 0.0470 (0.0461) time: 2.8185 data: 0.0027 max mem: 19788 +Epoch: [9] [ 640/2138] eta: 1:10:12 lr: 3.940423786667133e-05 loss: 0.0398 (0.0461) time: 2.7922 data: 0.0028 max mem: 19788 +Epoch: [9] [ 650/2138] eta: 1:09:44 lr: 3.9398834803727235e-05 loss: 0.0426 (0.0462) time: 2.7888 data: 0.0028 max mem: 19788 +Epoch: [9] [ 660/2138] eta: 1:09:15 lr: 3.939343165845262e-05 loss: 0.0437 (0.0462) time: 2.7882 data: 0.0027 max mem: 19788 +Epoch: [9] [ 670/2138] eta: 1:08:46 lr: 3.938802843083371e-05 loss: 0.0439 (0.0464) time: 2.7880 data: 0.0024 max mem: 19788 +Epoch: [9] [ 680/2138] eta: 1:08:18 lr: 3.938262512085669e-05 loss: 0.0382 (0.0464) time: 2.7900 data: 0.0024 max mem: 19788 +Epoch: [9] [ 690/2138] eta: 1:07:49 lr: 3.937722172850773e-05 loss: 0.0438 (0.0465) time: 2.7912 data: 0.0022 max mem: 19788 +Epoch: [9] [ 700/2138] eta: 1:07:21 lr: 3.937181825377303e-05 loss: 0.0419 (0.0465) time: 2.7915 data: 0.0020 max mem: 19788 +Epoch: [9] [ 710/2138] eta: 1:06:52 lr: 3.936641469663878e-05 loss: 0.0393 (0.0464) time: 2.7935 data: 0.0020 max mem: 19788 +Epoch: [9] [ 720/2138] eta: 1:06:24 lr: 3.936101105709115e-05 loss: 0.0366 (0.0463) time: 2.7925 data: 0.0021 max mem: 19788 +Epoch: [9] [ 730/2138] eta: 1:05:56 lr: 3.935560733511629e-05 loss: 0.0427 (0.0464) time: 2.7932 data: 0.0021 max mem: 19788 +Epoch: [9] [ 740/2138] eta: 1:05:27 lr: 3.93502035307004e-05 loss: 0.0483 (0.0464) time: 2.8036 data: 0.0022 max mem: 19788 +Epoch: [9] [ 750/2138] eta: 1:04:59 lr: 3.9344799643829615e-05 loss: 0.0449 (0.0464) time: 2.8096 data: 0.0026 max mem: 19788 +Epoch: [9] [ 760/2138] eta: 1:04:31 lr: 3.933939567449012e-05 loss: 0.0458 (0.0465) time: 2.8070 data: 0.0028 max mem: 19788 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max mem: 19788 +Epoch: [9] [ 850/2138] eta: 1:00:17 lr: 3.929075623705586e-05 loss: 0.0402 (0.0462) time: 2.7885 data: 0.0025 max mem: 19788 +Epoch: [9] [ 860/2138] eta: 0:59:48 lr: 3.9285351442266836e-05 loss: 0.0402 (0.0462) time: 2.7883 data: 0.0027 max mem: 19788 +Epoch: [9] [ 870/2138] eta: 0:59:20 lr: 3.9279946564856534e-05 loss: 0.0364 (0.0461) time: 2.7915 data: 0.0025 max mem: 19788 +Epoch: [9] [ 880/2138] eta: 0:58:52 lr: 3.927454160481105e-05 loss: 0.0374 (0.0461) time: 2.7934 data: 0.0023 max mem: 19788 +Epoch: [9] [ 890/2138] eta: 0:58:24 lr: 3.92691365621165e-05 loss: 0.0417 (0.0460) time: 2.7910 data: 0.0024 max mem: 19788 +Epoch: [9] [ 900/2138] eta: 0:57:55 lr: 3.926373143675898e-05 loss: 0.0407 (0.0460) time: 2.7887 data: 0.0024 max mem: 19788 +Epoch: [9] [ 910/2138] eta: 0:57:27 lr: 3.9258326228724565e-05 loss: 0.0379 (0.0460) time: 2.7830 data: 0.0023 max mem: 19788 +Epoch: [9] [ 920/2138] eta: 0:56:59 lr: 3.925292093799935e-05 loss: 0.0340 (0.0459) time: 2.7939 data: 0.0024 max mem: 19788 +Epoch: [9] [ 930/2138] eta: 0:56:31 lr: 3.924751556456943e-05 loss: 0.0396 (0.0460) time: 2.8061 data: 0.0025 max mem: 19788 +Epoch: [9] [ 940/2138] eta: 0:56:03 lr: 3.924211010842086e-05 loss: 0.0464 (0.0459) time: 2.8087 data: 0.0025 max mem: 19788 +Epoch: [9] [ 950/2138] eta: 0:55:34 lr: 3.923670456953974e-05 loss: 0.0439 (0.0459) time: 2.8091 data: 0.0027 max mem: 19788 +Epoch: [9] [ 960/2138] eta: 0:55:06 lr: 3.923129894791212e-05 loss: 0.0407 (0.0459) time: 2.8033 data: 0.0029 max mem: 19788 +Epoch: [9] [ 970/2138] eta: 0:54:38 lr: 3.922589324352406e-05 loss: 0.0407 (0.0458) time: 2.8019 data: 0.0026 max mem: 19788 +Epoch: [9] [ 980/2138] eta: 0:54:10 lr: 3.922048745636164e-05 loss: 0.0365 (0.0458) time: 2.8050 data: 0.0025 max mem: 19788 +Epoch: [9] [ 990/2138] eta: 0:53:42 lr: 3.92150815864109e-05 loss: 0.0374 (0.0458) time: 2.8062 data: 0.0027 max mem: 19788 +Epoch: [9] [1000/2138] eta: 0:53:14 lr: 3.92096756336579e-05 loss: 0.0364 (0.0457) time: 2.8036 data: 0.0027 max mem: 19788 +Epoch: [9] [1010/2138] eta: 0:52:46 lr: 3.920426959808868e-05 loss: 0.0364 (0.0456) time: 2.8048 data: 0.0025 max mem: 19788 +Epoch: [9] [1020/2138] eta: 0:52:18 lr: 3.919886347968929e-05 loss: 0.0388 (0.0456) time: 2.8079 data: 0.0024 max mem: 19788 +Epoch: [9] [1030/2138] eta: 0:51:50 lr: 3.919345727844576e-05 loss: 0.0355 (0.0455) time: 2.8048 data: 0.0029 max mem: 19788 +Epoch: [9] [1040/2138] eta: 0:51:22 lr: 3.918805099434412e-05 loss: 0.0417 (0.0456) time: 2.8030 data: 0.0027 max mem: 19788 +Epoch: [9] [1050/2138] eta: 0:50:54 lr: 3.9182644627370416e-05 loss: 0.0417 (0.0456) time: 2.8099 data: 0.0024 max mem: 19788 +Epoch: [9] [1060/2138] eta: 0:50:26 lr: 3.9177238177510654e-05 loss: 0.0412 (0.0456) time: 2.8119 data: 0.0027 max mem: 19788 +Epoch: [9] [1070/2138] eta: 0:49:57 lr: 3.917183164475087e-05 loss: 0.0440 (0.0456) time: 2.8084 data: 0.0028 max mem: 19788 +Epoch: [9] [1080/2138] eta: 0:49:29 lr: 3.9166425029077055e-05 loss: 0.0398 (0.0455) time: 2.8061 data: 0.0024 max mem: 19788 +Epoch: [9] [1090/2138] eta: 0:49:01 lr: 3.9161018330475253e-05 loss: 0.0436 (0.0457) time: 2.8040 data: 0.0023 max mem: 19788 +Epoch: [9] [1100/2138] eta: 0:48:33 lr: 3.9155611548931436e-05 loss: 0.0480 (0.0458) time: 2.8040 data: 0.0027 max mem: 19788 +Epoch: [9] [1110/2138] eta: 0:48:05 lr: 3.915020468443163e-05 loss: 0.0463 (0.0458) time: 2.8036 data: 0.0028 max mem: 19788 +Epoch: [9] [1120/2138] eta: 0:47:37 lr: 3.914479773696182e-05 loss: 0.0370 (0.0457) time: 2.8025 data: 0.0029 max mem: 19788 +Epoch: [9] [1130/2138] eta: 0:47:09 lr: 3.9139390706508005e-05 loss: 0.0375 (0.0457) time: 2.8003 data: 0.0028 max mem: 19788 +Epoch: [9] [1140/2138] eta: 0:46:41 lr: 3.9133983593056164e-05 loss: 0.0409 (0.0457) time: 2.8024 data: 0.0026 max mem: 19788 +Epoch: [9] [1150/2138] eta: 0:46:13 lr: 3.9128576396592296e-05 loss: 0.0352 (0.0456) time: 2.8051 data: 0.0024 max mem: 19788 +Epoch: [9] [1160/2138] eta: 0:45:45 lr: 3.912316911710237e-05 loss: 0.0338 (0.0455) time: 2.8041 data: 0.0023 max mem: 19788 +Epoch: [9] [1170/2138] eta: 0:45:16 lr: 3.911776175457236e-05 loss: 0.0342 (0.0455) time: 2.8033 data: 0.0026 max mem: 19788 +Epoch: [9] [1180/2138] eta: 0:44:48 lr: 3.9112354308988243e-05 loss: 0.0384 (0.0455) time: 2.8070 data: 0.0027 max mem: 19788 +Epoch: [9] [1190/2138] eta: 0:44:20 lr: 3.910694678033597e-05 loss: 0.0368 (0.0455) time: 2.8119 data: 0.0025 max mem: 19788 +Epoch: [9] [1200/2138] eta: 0:43:52 lr: 3.910153916860151e-05 loss: 0.0378 (0.0454) time: 2.8046 data: 0.0025 max mem: 19788 +Epoch: [9] [1210/2138] eta: 0:43:24 lr: 3.909613147377083e-05 loss: 0.0466 (0.0455) time: 2.8031 data: 0.0024 max mem: 19788 +Epoch: [9] [1220/2138] eta: 0:42:56 lr: 3.909072369582987e-05 loss: 0.0432 (0.0454) time: 2.8106 data: 0.0022 max mem: 19788 +Epoch: [9] [1230/2138] eta: 0:42:28 lr: 3.908531583476458e-05 loss: 0.0406 (0.0454) time: 2.8080 data: 0.0021 max mem: 19788 +Epoch: [9] [1240/2138] eta: 0:42:00 lr: 3.9079907890560904e-05 loss: 0.0339 (0.0453) time: 2.8107 data: 0.0021 max mem: 19788 +Epoch: [9] [1250/2138] eta: 0:41:32 lr: 3.9074499863204775e-05 loss: 0.0412 (0.0454) time: 2.8138 data: 0.0022 max mem: 19788 +Epoch: [9] [1260/2138] eta: 0:41:04 lr: 3.9069091752682134e-05 loss: 0.0363 (0.0453) time: 2.8073 data: 0.0023 max mem: 19788 +Epoch: [9] [1270/2138] eta: 0:40:36 lr: 3.9063683558978906e-05 loss: 0.0351 (0.0453) time: 2.8029 data: 0.0024 max mem: 19788 +Epoch: [9] [1280/2138] eta: 0:40:08 lr: 3.9058275282081016e-05 loss: 0.0362 (0.0453) time: 2.8040 data: 0.0024 max mem: 19788 +Epoch: [9] [1290/2138] eta: 0:39:40 lr: 3.905286692197439e-05 loss: 0.0391 (0.0453) time: 2.8082 data: 0.0025 max mem: 19788 +Epoch: [9] [1300/2138] eta: 0:39:12 lr: 3.9047458478644936e-05 loss: 0.0414 (0.0452) time: 2.8078 data: 0.0023 max mem: 19788 +Epoch: [9] [1310/2138] eta: 0:38:44 lr: 3.904204995207857e-05 loss: 0.0390 (0.0453) time: 2.8059 data: 0.0023 max mem: 19788 +Epoch: [9] [1320/2138] eta: 0:38:16 lr: 3.903664134226119e-05 loss: 0.0391 (0.0452) time: 2.8078 data: 0.0024 max mem: 19788 +Epoch: [9] [1330/2138] eta: 0:37:47 lr: 3.903123264917871e-05 loss: 0.0384 (0.0452) time: 2.8117 data: 0.0025 max mem: 19788 +Epoch: [9] [1340/2138] eta: 0:37:19 lr: 3.902582387281703e-05 loss: 0.0447 (0.0453) time: 2.8131 data: 0.0025 max mem: 19788 +Epoch: [9] [1350/2138] eta: 0:36:51 lr: 3.9020415013162016e-05 loss: 0.0531 (0.0454) time: 2.8098 data: 0.0025 max mem: 19788 +Epoch: [9] [1360/2138] eta: 0:36:23 lr: 3.9015006070199585e-05 loss: 0.0491 (0.0454) time: 2.8103 data: 0.0024 max mem: 19788 +Epoch: [9] [1370/2138] eta: 0:35:55 lr: 3.900959704391561e-05 loss: 0.0471 (0.0455) time: 2.8124 data: 0.0023 max mem: 19788 +Epoch: [9] [1380/2138] eta: 0:35:27 lr: 3.900418793429597e-05 loss: 0.0464 (0.0455) time: 2.8102 data: 0.0025 max mem: 19788 +Epoch: [9] [1390/2138] eta: 0:34:59 lr: 3.899877874132654e-05 loss: 0.0422 (0.0455) time: 2.8103 data: 0.0027 max mem: 19788 +Epoch: [9] [1400/2138] eta: 0:34:31 lr: 3.899336946499319e-05 loss: 0.0340 (0.0454) time: 2.8093 data: 0.0027 max mem: 19788 +Epoch: [9] [1410/2138] eta: 0:34:03 lr: 3.898796010528178e-05 loss: 0.0340 (0.0453) time: 2.8027 data: 0.0026 max mem: 19788 +Epoch: [9] [1420/2138] eta: 0:33:35 lr: 3.898255066217818e-05 loss: 0.0387 (0.0453) time: 2.7996 data: 0.0023 max mem: 19788 +Epoch: [9] [1430/2138] eta: 0:33:07 lr: 3.8977141135668246e-05 loss: 0.0428 (0.0453) time: 2.8043 data: 0.0024 max mem: 19788 +Epoch: [9] [1440/2138] eta: 0:32:39 lr: 3.897173152573783e-05 loss: 0.0502 (0.0454) time: 2.8056 data: 0.0027 max mem: 19788 +Epoch: [9] [1450/2138] eta: 0:32:11 lr: 3.896632183237276e-05 loss: 0.0426 (0.0454) time: 2.8054 data: 0.0026 max mem: 19788 +Epoch: [9] [1460/2138] eta: 0:31:43 lr: 3.8960912055558905e-05 loss: 0.0399 (0.0454) time: 2.8088 data: 0.0026 max mem: 19788 +Epoch: [9] [1470/2138] eta: 0:31:15 lr: 3.895550219528209e-05 loss: 0.0390 (0.0454) time: 2.8094 data: 0.0025 max mem: 19788 +Epoch: [9] [1480/2138] eta: 0:30:47 lr: 3.895009225152815e-05 loss: 0.0390 (0.0453) time: 2.8080 data: 0.0026 max mem: 19788 +Epoch: [9] [1490/2138] eta: 0:30:18 lr: 3.894468222428292e-05 loss: 0.0418 (0.0453) time: 2.8051 data: 0.0026 max mem: 19788 +Epoch: [9] [1500/2138] eta: 0:29:50 lr: 3.893927211353221e-05 loss: 0.0432 (0.0453) time: 2.8053 data: 0.0023 max mem: 19788 +Epoch: [9] [1510/2138] eta: 0:29:22 lr: 3.893386191926184e-05 loss: 0.0395 (0.0454) time: 2.8072 data: 0.0025 max mem: 19788 +Epoch: [9] [1520/2138] eta: 0:28:54 lr: 3.892845164145765e-05 loss: 0.0375 (0.0453) time: 2.8048 data: 0.0027 max mem: 19788 +Epoch: [9] [1530/2138] eta: 0:28:26 lr: 3.8923041280105426e-05 loss: 0.0426 (0.0453) time: 2.8066 data: 0.0026 max mem: 19788 +Epoch: [9] [1540/2138] eta: 0:27:58 lr: 3.8917630835190976e-05 loss: 0.0398 (0.0453) time: 2.8069 data: 0.0023 max mem: 19788 +Epoch: [9] [1550/2138] eta: 0:27:30 lr: 3.8912220306700105e-05 loss: 0.0398 (0.0453) time: 2.8044 data: 0.0022 max mem: 19788 +Epoch: [9] [1560/2138] eta: 0:27:02 lr: 3.890680969461862e-05 loss: 0.0424 (0.0453) time: 2.8029 data: 0.0022 max mem: 19788 +Epoch: [9] [1570/2138] eta: 0:26:34 lr: 3.8901398998932295e-05 loss: 0.0379 (0.0453) time: 2.8067 data: 0.0020 max mem: 19788 +Epoch: [9] [1580/2138] eta: 0:26:06 lr: 3.8895988219626924e-05 loss: 0.0382 (0.0453) time: 2.8016 data: 0.0022 max mem: 19788 +Epoch: [9] [1590/2138] eta: 0:25:38 lr: 3.889057735668829e-05 loss: 0.0432 (0.0453) time: 2.7923 data: 0.0025 max mem: 19788 +Epoch: [9] [1600/2138] eta: 0:25:09 lr: 3.888516641010218e-05 loss: 0.0440 (0.0453) time: 2.7931 data: 0.0025 max mem: 19788 +Epoch: [9] [1610/2138] eta: 0:24:41 lr: 3.887975537985436e-05 loss: 0.0420 (0.0453) time: 2.7963 data: 0.0022 max mem: 19788 +Epoch: [9] [1620/2138] eta: 0:24:13 lr: 3.887434426593059e-05 loss: 0.0351 (0.0452) time: 2.7986 data: 0.0021 max mem: 19788 +Epoch: [9] [1630/2138] eta: 0:23:45 lr: 3.886893306831664e-05 loss: 0.0366 (0.0452) time: 2.7956 data: 0.0021 max mem: 19788 +Epoch: [9] [1640/2138] eta: 0:23:17 lr: 3.886352178699828e-05 loss: 0.0402 (0.0452) time: 2.7984 data: 0.0024 max mem: 19788 +Epoch: [9] [1650/2138] eta: 0:22:49 lr: 3.885811042196126e-05 loss: 0.0418 (0.0452) time: 2.7957 data: 0.0027 max mem: 19788 +Epoch: [9] [1660/2138] eta: 0:22:21 lr: 3.8852698973191325e-05 loss: 0.0415 (0.0453) time: 2.7918 data: 0.0028 max mem: 19788 +Epoch: [9] [1670/2138] eta: 0:21:53 lr: 3.884728744067423e-05 loss: 0.0359 (0.0452) time: 2.7991 data: 0.0029 max mem: 19788 +Epoch: [9] [1680/2138] eta: 0:21:25 lr: 3.88418758243957e-05 loss: 0.0339 (0.0452) time: 2.8043 data: 0.0026 max mem: 19788 +Epoch: [9] [1690/2138] eta: 0:20:57 lr: 3.8836464124341484e-05 loss: 0.0448 (0.0452) time: 2.8046 data: 0.0023 max mem: 19788 +Epoch: [9] [1700/2138] eta: 0:20:29 lr: 3.88310523404973e-05 loss: 0.0426 (0.0452) time: 2.8046 data: 0.0022 max mem: 19788 +Epoch: [9] [1710/2138] eta: 0:20:01 lr: 3.8825640472848905e-05 loss: 0.0374 (0.0452) time: 2.8019 data: 0.0023 max mem: 19788 +Epoch: [9] [1720/2138] eta: 0:19:32 lr: 3.882022852138199e-05 loss: 0.0388 (0.0452) time: 2.7981 data: 0.0025 max mem: 19788 +Epoch: [9] [1730/2138] eta: 0:19:04 lr: 3.881481648608229e-05 loss: 0.0398 (0.0452) time: 2.7974 data: 0.0027 max mem: 19788 +Epoch: [9] [1740/2138] eta: 0:18:36 lr: 3.880940436693551e-05 loss: 0.0420 (0.0452) time: 2.8014 data: 0.0028 max mem: 19788 +Epoch: [9] [1750/2138] eta: 0:18:08 lr: 3.8803992163927365e-05 loss: 0.0389 (0.0452) time: 2.8000 data: 0.0024 max mem: 19788 +Epoch: [9] [1760/2138] eta: 0:17:40 lr: 3.8798579877043556e-05 loss: 0.0389 (0.0451) time: 2.7968 data: 0.0021 max mem: 19788 +Epoch: [9] [1770/2138] eta: 0:17:12 lr: 3.8793167506269786e-05 loss: 0.0335 (0.0451) time: 2.7949 data: 0.0022 max mem: 19788 +Epoch: [9] [1780/2138] eta: 0:16:44 lr: 3.878775505159173e-05 loss: 0.0350 (0.0451) time: 2.7948 data: 0.0022 max mem: 19788 +Epoch: [9] [1790/2138] eta: 0:16:16 lr: 3.8782342512995114e-05 loss: 0.0377 (0.0451) time: 2.7956 data: 0.0024 max mem: 19788 +Epoch: [9] [1800/2138] eta: 0:15:48 lr: 3.8776929890465596e-05 loss: 0.0465 (0.0451) time: 2.7997 data: 0.0027 max mem: 19788 +Epoch: [9] [1810/2138] eta: 0:15:20 lr: 3.877151718398886e-05 loss: 0.0418 (0.0451) time: 2.8080 data: 0.0025 max mem: 19788 +Epoch: [9] [1820/2138] eta: 0:14:52 lr: 3.876610439355058e-05 loss: 0.0409 (0.0451) time: 2.8071 data: 0.0022 max mem: 19788 +Epoch: [9] [1830/2138] eta: 0:14:24 lr: 3.876069151913645e-05 loss: 0.0399 (0.0450) time: 2.8086 data: 0.0021 max mem: 19788 +Epoch: [9] [1840/2138] eta: 0:13:56 lr: 3.875527856073211e-05 loss: 0.0387 (0.0450) time: 2.8126 data: 0.0022 max mem: 19788 +Epoch: [9] [1850/2138] eta: 0:13:28 lr: 3.874986551832323e-05 loss: 0.0388 (0.0450) time: 2.8100 data: 0.0021 max mem: 19788 +Epoch: [9] [1860/2138] eta: 0:13:00 lr: 3.874445239189547e-05 loss: 0.0433 (0.0450) time: 2.8090 data: 0.0020 max mem: 19788 +Epoch: [9] [1870/2138] eta: 0:12:31 lr: 3.873903918143449e-05 loss: 0.0428 (0.0450) time: 2.8087 data: 0.0021 max mem: 19788 +Epoch: [9] [1880/2138] eta: 0:12:03 lr: 3.873362588692592e-05 loss: 0.0371 (0.0450) time: 2.8034 data: 0.0023 max mem: 19788 +Epoch: [9] [1890/2138] eta: 0:11:35 lr: 3.8728212508355415e-05 loss: 0.0429 (0.0450) time: 2.8006 data: 0.0023 max mem: 19788 +Epoch: [9] [1900/2138] eta: 0:11:07 lr: 3.8722799045708614e-05 loss: 0.0458 (0.0450) time: 2.8026 data: 0.0022 max mem: 19788 +Epoch: [9] [1910/2138] eta: 0:10:39 lr: 3.8717385498971146e-05 loss: 0.0381 (0.0450) time: 2.8059 data: 0.0024 max mem: 19788 +Epoch: [9] [1920/2138] eta: 0:10:11 lr: 3.871197186812865e-05 loss: 0.0381 (0.0450) time: 2.8084 data: 0.0025 max mem: 19788 +Epoch: [9] [1930/2138] eta: 0:09:43 lr: 3.870655815316673e-05 loss: 0.0405 (0.0450) time: 2.8098 data: 0.0023 max mem: 19788 +Epoch: [9] [1940/2138] eta: 0:09:15 lr: 3.870114435407103e-05 loss: 0.0385 (0.0450) time: 2.8097 data: 0.0023 max mem: 19788 +Epoch: [9] [1950/2138] eta: 0:08:47 lr: 3.8695730470827145e-05 loss: 0.0385 (0.0450) time: 2.8103 data: 0.0025 max mem: 19788 +Epoch: [9] [1960/2138] eta: 0:08:19 lr: 3.8690316503420705e-05 loss: 0.0385 (0.0450) time: 2.8079 data: 0.0026 max mem: 19788 +Epoch: [9] [1970/2138] eta: 0:07:51 lr: 3.8684902451837296e-05 loss: 0.0439 (0.0450) time: 2.8060 data: 0.0026 max mem: 19788 +Epoch: [9] [1980/2138] eta: 0:07:23 lr: 3.867948831606253e-05 loss: 0.0455 (0.0450) time: 2.8046 data: 0.0028 max mem: 19788 +Epoch: [9] [1990/2138] eta: 0:06:55 lr: 3.867407409608201e-05 loss: 0.0418 (0.0450) time: 2.8031 data: 0.0030 max mem: 19788 +Epoch: [9] [2000/2138] eta: 0:06:27 lr: 3.866865979188131e-05 loss: 0.0386 (0.0450) time: 2.8047 data: 0.0028 max mem: 19788 +Epoch: [9] [2010/2138] eta: 0:05:59 lr: 3.866324540344603e-05 loss: 0.0413 (0.0451) time: 2.8091 data: 0.0026 max mem: 19788 +Epoch: [9] [2020/2138] eta: 0:05:31 lr: 3.865783093076175e-05 loss: 0.0429 (0.0450) time: 2.8093 data: 0.0022 max mem: 19788 +Epoch: [9] [2030/2138] eta: 0:05:03 lr: 3.8652416373814044e-05 loss: 0.0410 (0.0450) time: 2.7995 data: 0.0021 max mem: 19788 +Epoch: [9] [2040/2138] eta: 0:04:34 lr: 3.864700173258848e-05 loss: 0.0436 (0.0451) time: 2.7916 data: 0.0024 max mem: 19788 +Epoch: [9] [2050/2138] eta: 0:04:06 lr: 3.864158700707064e-05 loss: 0.0401 (0.0450) time: 2.7899 data: 0.0027 max mem: 19788 +Epoch: [9] [2060/2138] eta: 0:03:38 lr: 3.863617219724609e-05 loss: 0.0437 (0.0451) time: 2.7901 data: 0.0029 max mem: 19788 +Epoch: [9] [2070/2138] eta: 0:03:10 lr: 3.8630757303100364e-05 loss: 0.0393 (0.0450) time: 2.7921 data: 0.0029 max mem: 19788 +Epoch: [9] [2080/2138] eta: 0:02:42 lr: 3.8625342324619034e-05 loss: 0.0393 (0.0450) time: 2.7940 data: 0.0027 max mem: 19788 +Epoch: [9] [2090/2138] eta: 0:02:14 lr: 3.861992726178764e-05 loss: 0.0412 (0.0450) time: 2.7940 data: 0.0024 max mem: 19788 +Epoch: [9] [2100/2138] eta: 0:01:46 lr: 3.861451211459175e-05 loss: 0.0374 (0.0449) time: 2.7948 data: 0.0020 max mem: 19788 +Epoch: [9] [2110/2138] eta: 0:01:18 lr: 3.860909688301688e-05 loss: 0.0383 (0.0449) time: 2.7909 data: 0.0021 max mem: 19788 +Epoch: [9] [2120/2138] eta: 0:00:50 lr: 3.8603681567048564e-05 loss: 0.0433 (0.0450) time: 2.7885 data: 0.0021 max mem: 19788 +Epoch: [9] [2130/2138] eta: 0:00:22 lr: 3.859826616667233e-05 loss: 0.0521 (0.0450) time: 2.7989 data: 0.0021 max mem: 19788 +Epoch: [9] Total time: 1:39:58 +Test: [ 0/21770] eta: 16:36:33 time: 2.7466 data: 2.4539 max mem: 19788 +Test: [ 100/21770] eta: 0:26:24 time: 0.0482 data: 0.0016 max mem: 19788 +Test: [ 200/21770] eta: 0:20:59 time: 0.0429 data: 0.0015 max mem: 19788 +Test: [ 300/21770] eta: 0:19:23 time: 0.0429 data: 0.0015 max mem: 19788 +Test: [ 400/21770] eta: 0:18:39 time: 0.0475 data: 0.0015 max mem: 19788 +Test: [ 500/21770] eta: 0:18:08 time: 0.0517 data: 0.0016 max mem: 19788 +Test: [ 600/21770] eta: 0:17:51 time: 0.0439 data: 0.0014 max mem: 19788 +Test: [ 700/21770] eta: 0:17:24 time: 0.0438 data: 0.0015 max mem: 19788 +Test: [ 800/21770] eta: 0:17:06 time: 0.0491 data: 0.0015 max mem: 19788 +Test: [ 900/21770] eta: 0:16:52 time: 0.0474 data: 0.0017 max mem: 19788 +Test: [ 1000/21770] eta: 0:16:38 time: 0.0439 data: 0.0015 max mem: 19788 +Test: [ 1100/21770] eta: 0:16:28 time: 0.0459 data: 0.0015 max mem: 19788 +Test: [ 1200/21770] eta: 0:16:18 time: 0.0435 data: 0.0014 max mem: 19788 +Test: [ 1300/21770] eta: 0:16:07 time: 0.0424 data: 0.0017 max mem: 19788 +Test: [ 1400/21770] eta: 0:16:00 time: 0.0476 data: 0.0017 max mem: 19788 +Test: [ 1500/21770] eta: 0:15:53 time: 0.0431 data: 0.0015 max mem: 19788 +Test: [ 1600/21770] eta: 0:15:45 time: 0.0432 data: 0.0015 max mem: 19788 +Test: [ 1700/21770] eta: 0:15:38 time: 0.0505 data: 0.0017 max mem: 19788 +Test: [ 1800/21770] eta: 0:15:33 time: 0.0431 data: 0.0016 max mem: 19788 +Test: [ 1900/21770] eta: 0:15:25 time: 0.0442 data: 0.0015 max mem: 19788 +Test: [ 2000/21770] eta: 0:15:18 time: 0.0445 data: 0.0016 max mem: 19788 +Test: [ 2100/21770] eta: 0:15:10 time: 0.0425 data: 0.0016 max mem: 19788 +Test: [ 2200/21770] eta: 0:15:07 time: 0.0509 data: 0.0018 max mem: 19788 +Test: [ 2300/21770] eta: 0:15:03 time: 0.0436 data: 0.0015 max mem: 19788 +Test: [ 2400/21770] eta: 0:14:59 time: 0.0438 data: 0.0015 max mem: 19788 +Test: [ 2500/21770] eta: 0:14:54 time: 0.0434 data: 0.0014 max mem: 19788 +Test: [ 2600/21770] eta: 0:14:48 time: 0.0442 data: 0.0015 max mem: 19788 +Test: [ 2700/21770] eta: 0:14:45 time: 0.0448 data: 0.0015 max mem: 19788 +Test: [ 2800/21770] eta: 0:14:41 time: 0.0447 data: 0.0016 max mem: 19788 +Test: [ 2900/21770] eta: 0:14:34 time: 0.0448 data: 0.0014 max mem: 19788 +Test: [ 3000/21770] eta: 0:14:28 time: 0.0445 data: 0.0015 max mem: 19788 +Test: [ 3100/21770] eta: 0:14:23 time: 0.0473 data: 0.0015 max mem: 19788 +Test: [ 3200/21770] eta: 0:14:20 time: 0.0464 data: 0.0014 max mem: 19788 +Test: [ 3300/21770] eta: 0:14:14 time: 0.0441 data: 0.0015 max mem: 19788 +Test: [ 3400/21770] eta: 0:14:09 time: 0.0430 data: 0.0014 max mem: 19788 +Test: [ 3500/21770] eta: 0:14:03 time: 0.0439 data: 0.0016 max mem: 19788 +Test: [ 3600/21770] eta: 0:13:57 time: 0.0504 data: 0.0018 max mem: 19788 +Test: [ 3700/21770] eta: 0:13:52 time: 0.0435 data: 0.0013 max mem: 19788 +Test: [ 3800/21770] eta: 0:13:47 time: 0.0444 data: 0.0015 max mem: 19788 +Test: [ 3900/21770] eta: 0:13:42 time: 0.0437 data: 0.0015 max mem: 19788 +Test: [ 4000/21770] eta: 0:13:38 time: 0.0503 data: 0.0018 max mem: 19788 +Test: [ 4100/21770] eta: 0:13:34 time: 0.0445 data: 0.0015 max mem: 19788 +Test: [ 4200/21770] eta: 0:13:29 time: 0.0427 data: 0.0013 max mem: 19788 +Test: [ 4300/21770] eta: 0:13:25 time: 0.0520 data: 0.0018 max mem: 19788 +Test: [ 4400/21770] eta: 0:13:22 time: 0.0524 data: 0.0018 max mem: 19788 +Test: [ 4500/21770] eta: 0:13:20 time: 0.0534 data: 0.0017 max mem: 19788 +Test: [ 4600/21770] eta: 0:13:16 time: 0.0425 data: 0.0014 max mem: 19788 +Test: [ 4700/21770] eta: 0:13:11 time: 0.0482 data: 0.0014 max mem: 19788 +Test: [ 4800/21770] eta: 0:13:06 time: 0.0479 data: 0.0015 max mem: 19788 +Test: [ 4900/21770] eta: 0:13:02 time: 0.0436 data: 0.0017 max mem: 19788 +Test: [ 5000/21770] eta: 0:12:56 time: 0.0455 data: 0.0014 max mem: 19788 +Test: [ 5100/21770] eta: 0:12:51 time: 0.0436 data: 0.0015 max mem: 19788 +Test: [ 5200/21770] eta: 0:12:47 time: 0.0490 data: 0.0016 max mem: 19788 +Test: [ 5300/21770] eta: 0:12:44 time: 0.0527 data: 0.0018 max mem: 19788 +Test: [ 5400/21770] eta: 0:12:39 time: 0.0434 data: 0.0014 max mem: 19788 +Test: [ 5500/21770] eta: 0:12:34 time: 0.0482 data: 0.0014 max mem: 19788 +Test: [ 5600/21770] eta: 0:12:30 time: 0.0516 data: 0.0017 max mem: 19788 +Test: [ 5700/21770] eta: 0:12:25 time: 0.0487 data: 0.0016 max mem: 19788 +Test: [ 5800/21770] eta: 0:12:21 time: 0.0436 data: 0.0013 max mem: 19788 +Test: [ 5900/21770] eta: 0:12:16 time: 0.0527 data: 0.0018 max mem: 19788 +Test: [ 6000/21770] eta: 0:12:11 time: 0.0434 data: 0.0016 max mem: 19788 +Test: [ 6100/21770] eta: 0:12:07 time: 0.0524 data: 0.0018 max mem: 19788 +Test: [ 6200/21770] eta: 0:12:03 time: 0.0438 data: 0.0016 max mem: 19788 +Test: [ 6300/21770] eta: 0:11:57 time: 0.0431 data: 0.0014 max mem: 19788 +Test: [ 6400/21770] eta: 0:11:52 time: 0.0430 data: 0.0015 max mem: 19788 +Test: [ 6500/21770] eta: 0:11:47 time: 0.0428 data: 0.0016 max mem: 19788 +Test: [ 6600/21770] eta: 0:11:42 time: 0.0450 data: 0.0015 max mem: 19788 +Test: [ 6700/21770] eta: 0:11:37 time: 0.0431 data: 0.0014 max mem: 19788 +Test: [ 6800/21770] eta: 0:11:33 time: 0.0517 data: 0.0017 max mem: 19788 +Test: [ 6900/21770] eta: 0:11:28 time: 0.0519 data: 0.0018 max mem: 19788 +Test: [ 7000/21770] eta: 0:11:24 time: 0.0493 data: 0.0017 max mem: 19788 +Test: [ 7100/21770] eta: 0:11:19 time: 0.0438 data: 0.0015 max mem: 19788 +Test: [ 7200/21770] eta: 0:11:14 time: 0.0441 data: 0.0014 max mem: 19788 +Test: [ 7300/21770] eta: 0:11:10 time: 0.0437 data: 0.0014 max mem: 19788 +Test: [ 7400/21770] eta: 0:11:05 time: 0.0432 data: 0.0016 max mem: 19788 +Test: [ 7500/21770] eta: 0:11:00 time: 0.0444 data: 0.0016 max mem: 19788 +Test: [ 7600/21770] eta: 0:10:56 time: 0.0477 data: 0.0015 max mem: 19788 +Test: [ 7700/21770] eta: 0:10:51 time: 0.0437 data: 0.0015 max mem: 19788 +Test: [ 7800/21770] eta: 0:10:47 time: 0.0506 data: 0.0017 max mem: 19788 +Test: [ 7900/21770] eta: 0:10:42 time: 0.0517 data: 0.0015 max mem: 19788 +Test: [ 8000/21770] eta: 0:10:37 time: 0.0439 data: 0.0015 max mem: 19788 +Test: [ 8100/21770] eta: 0:10:32 time: 0.0483 data: 0.0014 max mem: 19788 +Test: [ 8200/21770] eta: 0:10:27 time: 0.0437 data: 0.0015 max mem: 19788 +Test: [ 8300/21770] eta: 0:10:22 time: 0.0457 data: 0.0016 max mem: 19788 +Test: [ 8400/21770] eta: 0:10:18 time: 0.0511 data: 0.0017 max mem: 19788 +Test: [ 8500/21770] eta: 0:10:13 time: 0.0438 data: 0.0014 max mem: 19788 +Test: [ 8600/21770] eta: 0:10:09 time: 0.0441 data: 0.0014 max mem: 19788 +Test: [ 8700/21770] eta: 0:10:04 time: 0.0445 data: 0.0017 max mem: 19788 +Test: [ 8800/21770] eta: 0:09:59 time: 0.0430 data: 0.0014 max mem: 19788 +Test: [ 8900/21770] eta: 0:09:55 time: 0.0437 data: 0.0014 max mem: 19788 +Test: [ 9000/21770] eta: 0:09:50 time: 0.0458 data: 0.0018 max mem: 19788 +Test: [ 9100/21770] eta: 0:09:45 time: 0.0446 data: 0.0015 max mem: 19788 +Test: [ 9200/21770] eta: 0:09:41 time: 0.0432 data: 0.0016 max mem: 19788 +Test: [ 9300/21770] eta: 0:09:36 time: 0.0496 data: 0.0017 max mem: 19788 +Test: [ 9400/21770] eta: 0:09:31 time: 0.0427 data: 0.0017 max mem: 19788 +Test: [ 9500/21770] eta: 0:09:27 time: 0.0436 data: 0.0013 max mem: 19788 +Test: [ 9600/21770] eta: 0:09:22 time: 0.0438 data: 0.0015 max mem: 19788 +Test: [ 9700/21770] eta: 0:09:17 time: 0.0458 data: 0.0014 max mem: 19788 +Test: [ 9800/21770] eta: 0:09:13 time: 0.0446 data: 0.0014 max mem: 19788 +Test: [ 9900/21770] eta: 0:09:09 time: 0.0489 data: 0.0016 max mem: 19788 +Test: [10000/21770] eta: 0:09:04 time: 0.0469 data: 0.0016 max mem: 19788 +Test: [10100/21770] eta: 0:09:00 time: 0.0482 data: 0.0016 max mem: 19788 +Test: [10200/21770] eta: 0:08:55 time: 0.0477 data: 0.0015 max mem: 19788 +Test: [10300/21770] eta: 0:08:50 time: 0.0435 data: 0.0013 max mem: 19788 +Test: [10400/21770] eta: 0:08:46 time: 0.0441 data: 0.0017 max mem: 19788 +Test: [10500/21770] eta: 0:08:41 time: 0.0476 data: 0.0017 max mem: 19788 +Test: [10600/21770] eta: 0:08:36 time: 0.0446 data: 0.0014 max mem: 19788 +Test: [10700/21770] eta: 0:08:32 time: 0.0488 data: 0.0016 max mem: 19788 +Test: [10800/21770] eta: 0:08:28 time: 0.0453 data: 0.0016 max mem: 19788 +Test: [10900/21770] eta: 0:08:23 time: 0.0475 data: 0.0015 max mem: 19788 +Test: [11000/21770] eta: 0:08:19 time: 0.0501 data: 0.0017 max mem: 19788 +Test: [11100/21770] eta: 0:08:14 time: 0.0500 data: 0.0017 max mem: 19788 +Test: [11200/21770] eta: 0:08:10 time: 0.0494 data: 0.0016 max mem: 19788 +Test: [11300/21770] eta: 0:08:05 time: 0.0472 data: 0.0016 max mem: 19788 +Test: [11400/21770] eta: 0:08:01 time: 0.0490 data: 0.0016 max mem: 19788 +Test: [11500/21770] eta: 0:07:56 time: 0.0515 data: 0.0016 max mem: 19788 +Test: [11600/21770] eta: 0:07:51 time: 0.0424 data: 0.0014 max mem: 19788 +Test: [11700/21770] eta: 0:07:47 time: 0.0444 data: 0.0015 max mem: 19788 +Test: [11800/21770] eta: 0:07:42 time: 0.0484 data: 0.0015 max mem: 19788 +Test: [11900/21770] eta: 0:07:38 time: 0.0460 data: 0.0014 max mem: 19788 +Test: [12000/21770] eta: 0:07:33 time: 0.0524 data: 0.0018 max mem: 19788 +Test: [12100/21770] eta: 0:07:29 time: 0.0452 data: 0.0014 max mem: 19788 +Test: [12200/21770] eta: 0:07:24 time: 0.0436 data: 0.0014 max mem: 19788 +Test: [12300/21770] eta: 0:07:19 time: 0.0431 data: 0.0013 max mem: 19788 +Test: [12400/21770] eta: 0:07:14 time: 0.0440 data: 0.0016 max mem: 19788 +Test: [12500/21770] eta: 0:07:10 time: 0.0490 data: 0.0016 max mem: 19788 +Test: [12600/21770] eta: 0:07:05 time: 0.0515 data: 0.0017 max mem: 19788 +Test: [12700/21770] eta: 0:07:01 time: 0.0478 data: 0.0016 max mem: 19788 +Test: [12800/21770] eta: 0:06:57 time: 0.0517 data: 0.0017 max mem: 19788 +Test: [12900/21770] eta: 0:06:52 time: 0.0447 data: 0.0013 max mem: 19788 +Test: [13000/21770] eta: 0:06:47 time: 0.0431 data: 0.0015 max mem: 19788 +Test: [13100/21770] eta: 0:06:43 time: 0.0438 data: 0.0014 max mem: 19788 +Test: [13200/21770] eta: 0:06:38 time: 0.0430 data: 0.0014 max mem: 19788 +Test: [13300/21770] eta: 0:06:33 time: 0.0426 data: 0.0015 max mem: 19788 +Test: [13400/21770] eta: 0:06:28 time: 0.0431 data: 0.0014 max mem: 19788 +Test: [13500/21770] eta: 0:06:23 time: 0.0443 data: 0.0016 max mem: 19788 +Test: [13600/21770] eta: 0:06:19 time: 0.0471 data: 0.0016 max mem: 19788 +Test: [13700/21770] eta: 0:06:14 time: 0.0443 data: 0.0014 max mem: 19788 +Test: [13800/21770] eta: 0:06:09 time: 0.0511 data: 0.0016 max mem: 19788 +Test: [13900/21770] eta: 0:06:05 time: 0.0516 data: 0.0016 max mem: 19788 +Test: [14000/21770] eta: 0:06:00 time: 0.0433 data: 0.0014 max mem: 19788 +Test: [14100/21770] eta: 0:05:56 time: 0.0444 data: 0.0016 max mem: 19788 +Test: [14200/21770] eta: 0:05:51 time: 0.0434 data: 0.0013 max mem: 19788 +Test: [14300/21770] eta: 0:05:46 time: 0.0442 data: 0.0014 max mem: 19788 +Test: [14400/21770] eta: 0:05:41 time: 0.0440 data: 0.0016 max mem: 19788 +Test: [14500/21770] eta: 0:05:37 time: 0.0526 data: 0.0018 max mem: 19788 +Test: [14600/21770] eta: 0:05:32 time: 0.0438 data: 0.0013 max mem: 19788 +Test: [14700/21770] eta: 0:05:28 time: 0.0457 data: 0.0018 max mem: 19788 +Test: [14800/21770] eta: 0:05:23 time: 0.0431 data: 0.0015 max mem: 19788 +Test: [14900/21770] eta: 0:05:18 time: 0.0472 data: 0.0018 max mem: 19788 +Test: [15000/21770] eta: 0:05:14 time: 0.0459 data: 0.0015 max mem: 19788 +Test: [15100/21770] eta: 0:05:09 time: 0.0424 data: 0.0013 max mem: 19788 +Test: [15200/21770] eta: 0:05:04 time: 0.0432 data: 0.0015 max mem: 19788 +Test: [15300/21770] eta: 0:05:00 time: 0.0498 data: 0.0016 max mem: 19788 +Test: [15400/21770] eta: 0:04:55 time: 0.0526 data: 0.0016 max mem: 19788 +Test: [15500/21770] eta: 0:04:50 time: 0.0516 data: 0.0017 max mem: 19788 +Test: [15600/21770] eta: 0:04:46 time: 0.0445 data: 0.0015 max mem: 19788 +Test: [15700/21770] eta: 0:04:41 time: 0.0527 data: 0.0018 max mem: 19788 +Test: [15800/21770] eta: 0:04:37 time: 0.0443 data: 0.0015 max mem: 19788 +Test: [15900/21770] eta: 0:04:32 time: 0.0498 data: 0.0015 max mem: 19788 +Test: [16000/21770] eta: 0:04:28 time: 0.0474 data: 0.0016 max mem: 19788 +Test: [16100/21770] eta: 0:04:23 time: 0.0523 data: 0.0017 max mem: 19788 +Test: [16200/21770] eta: 0:04:18 time: 0.0467 data: 0.0016 max mem: 19788 +Test: [16300/21770] eta: 0:04:14 time: 0.0464 data: 0.0016 max mem: 19788 +Test: [16400/21770] eta: 0:04:09 time: 0.0470 data: 0.0015 max mem: 19788 +Test: [16500/21770] eta: 0:04:04 time: 0.0435 data: 0.0014 max mem: 19788 +Test: [16600/21770] eta: 0:04:00 time: 0.0438 data: 0.0015 max mem: 19788 +Test: [16700/21770] eta: 0:03:55 time: 0.0443 data: 0.0016 max mem: 19788 +Test: [16800/21770] eta: 0:03:50 time: 0.0458 data: 0.0013 max mem: 19788 +Test: [16900/21770] eta: 0:03:46 time: 0.0518 data: 0.0017 max mem: 19788 +Test: [17000/21770] eta: 0:03:41 time: 0.0480 data: 0.0016 max mem: 19788 +Test: [17100/21770] eta: 0:03:36 time: 0.0431 data: 0.0014 max mem: 19788 +Test: [17200/21770] eta: 0:03:32 time: 0.0528 data: 0.0017 max mem: 19788 +Test: [17300/21770] eta: 0:03:27 time: 0.0489 data: 0.0015 max mem: 19788 +Test: [17400/21770] eta: 0:03:23 time: 0.0433 data: 0.0015 max mem: 19788 +Test: [17500/21770] eta: 0:03:18 time: 0.0480 data: 0.0015 max mem: 19788 +Test: [17600/21770] eta: 0:03:13 time: 0.0437 data: 0.0013 max mem: 19788 +Test: [17700/21770] eta: 0:03:09 time: 0.0440 data: 0.0016 max mem: 19788 +Test: [17800/21770] eta: 0:03:04 time: 0.0504 data: 0.0016 max mem: 19788 +Test: [17900/21770] eta: 0:02:59 time: 0.0444 data: 0.0014 max mem: 19788 +Test: [18000/21770] eta: 0:02:55 time: 0.0428 data: 0.0015 max mem: 19788 +Test: [18100/21770] eta: 0:02:50 time: 0.0442 data: 0.0017 max mem: 19788 +Test: [18200/21770] eta: 0:02:45 time: 0.0445 data: 0.0016 max mem: 19788 +Test: [18300/21770] eta: 0:02:41 time: 0.0488 data: 0.0017 max mem: 19788 +Test: [18400/21770] eta: 0:02:36 time: 0.0453 data: 0.0016 max mem: 19788 +Test: [18500/21770] eta: 0:02:31 time: 0.0447 data: 0.0014 max mem: 19788 +Test: [18600/21770] eta: 0:02:27 time: 0.0432 data: 0.0015 max mem: 19788 +Test: [18700/21770] eta: 0:02:22 time: 0.0524 data: 0.0017 max mem: 19788 +Test: [18800/21770] eta: 0:02:17 time: 0.0429 data: 0.0014 max mem: 19788 +Test: [18900/21770] eta: 0:02:13 time: 0.0485 data: 0.0015 max mem: 19788 +Test: [19000/21770] eta: 0:02:08 time: 0.0489 data: 0.0016 max mem: 19788 +Test: [19100/21770] eta: 0:02:04 time: 0.0432 data: 0.0013 max mem: 19788 +Test: [19200/21770] eta: 0:01:59 time: 0.0453 data: 0.0014 max mem: 19788 +Test: [19300/21770] eta: 0:01:54 time: 0.0437 data: 0.0014 max mem: 19788 +Test: [19400/21770] eta: 0:01:50 time: 0.0428 data: 0.0014 max mem: 19788 +Test: [19500/21770] eta: 0:01:45 time: 0.0507 data: 0.0017 max mem: 19788 +Test: [19600/21770] eta: 0:01:40 time: 0.0444 data: 0.0014 max mem: 19788 +Test: [19700/21770] eta: 0:01:36 time: 0.0494 data: 0.0016 max mem: 19788 +Test: [19800/21770] eta: 0:01:31 time: 0.0486 data: 0.0017 max mem: 19788 +Test: [19900/21770] eta: 0:01:26 time: 0.0524 data: 0.0017 max mem: 19788 +Test: [20000/21770] eta: 0:01:22 time: 0.0431 data: 0.0014 max mem: 19788 +Test: [20100/21770] eta: 0:01:17 time: 0.0469 data: 0.0017 max mem: 19788 +Test: [20200/21770] eta: 0:01:12 time: 0.0443 data: 0.0016 max mem: 19788 +Test: [20300/21770] eta: 0:01:08 time: 0.0492 data: 0.0015 max mem: 19788 +Test: [20400/21770] eta: 0:01:03 time: 0.0429 data: 0.0015 max mem: 19788 +Test: [20500/21770] eta: 0:00:58 time: 0.0425 data: 0.0015 max mem: 19788 +Test: [20600/21770] eta: 0:00:54 time: 0.0434 data: 0.0015 max mem: 19788 +Test: [20700/21770] eta: 0:00:49 time: 0.0485 data: 0.0017 max mem: 19788 +Test: [20800/21770] eta: 0:00:45 time: 0.0457 data: 0.0014 max mem: 19788 +Test: [20900/21770] eta: 0:00:40 time: 0.0476 data: 0.0019 max mem: 19788 +Test: [21000/21770] eta: 0:00:35 time: 0.0438 data: 0.0016 max mem: 19788 +Test: [21100/21770] eta: 0:00:31 time: 0.0502 data: 0.0017 max mem: 19788 +Test: [21200/21770] eta: 0:00:26 time: 0.0433 data: 0.0014 max mem: 19788 +Test: [21300/21770] eta: 0:00:21 time: 0.0432 data: 0.0013 max mem: 19788 +Test: [21400/21770] eta: 0:00:17 time: 0.0449 data: 0.0013 max mem: 19788 +Test: [21500/21770] eta: 0:00:12 time: 0.0462 data: 0.0014 max mem: 19788 +Test: [21600/21770] eta: 0:00:07 time: 0.0447 data: 0.0014 max mem: 19788 +Test: [21700/21770] eta: 0:00:03 time: 0.0489 data: 0.0015 max mem: 19788 +Test: Total time: 0:16:50 +Final results: +Mean IoU is 62.78 + + precision@0.5 = 69.68 + precision@0.6 = 64.02 + precision@0.7 = 56.98 + precision@0.8 = 45.93 + precision@0.9 = 22.46 + overall IoU = 63.57 + mean IoU = 62.78 + +Mean accuracy for one-to-zero sample is 78.81 + +Average object IoU 0.6277781517372436 +Overall IoU 63.57362747192383 +Epoch: [10] [ 0/2138] eta: 9:52:31 lr: 3.859393378558794e-05 loss: 0.0625 (0.0625) time: 16.6285 data: 1.5269 max mem: 19788 +Epoch: [10] [ 10/2138] eta: 2:24:35 lr: 3.8588518233241e-05 loss: 0.0591 (0.0502) time: 4.0767 data: 0.1407 max mem: 19788 +Epoch: [10] [ 20/2138] eta: 2:02:39 lr: 3.8583102596445614e-05 loss: 0.0387 (0.0475) time: 2.8173 data: 0.0019 max mem: 19788 +Epoch: [10] [ 30/2138] eta: 1:54:40 lr: 3.857768687518729e-05 loss: 0.0431 (0.0479) time: 2.8167 data: 0.0020 max mem: 19788 +Epoch: [10] [ 40/2138] eta: 1:50:17 lr: 3.857227106945154e-05 loss: 0.0449 (0.0476) time: 2.8172 data: 0.0023 max mem: 19788 +Epoch: [10] [ 50/2138] eta: 1:47:25 lr: 3.856685517922386e-05 loss: 0.0420 (0.0474) time: 2.8132 data: 0.0024 max mem: 19788 +Epoch: [10] [ 60/2138] eta: 1:45:19 lr: 3.856143920448975e-05 loss: 0.0412 (0.0478) time: 2.8099 data: 0.0024 max mem: 19788 +Epoch: [10] [ 70/2138] eta: 1:43:42 lr: 3.855602314523471e-05 loss: 0.0419 (0.0469) time: 2.8091 data: 0.0025 max mem: 19788 +Epoch: [10] [ 80/2138] eta: 1:42:22 lr: 3.855060700144422e-05 loss: 0.0419 (0.0468) time: 2.8121 data: 0.0026 max mem: 19788 +Epoch: [10] [ 90/2138] eta: 1:41:13 lr: 3.854519077310377e-05 loss: 0.0406 (0.0464) time: 2.8123 data: 0.0025 max mem: 19788 +Epoch: [10] [ 100/2138] eta: 1:40:12 lr: 3.853977446019884e-05 loss: 0.0427 (0.0473) time: 2.8094 data: 0.0025 max mem: 19788 +Epoch: [10] [ 110/2138] eta: 1:39:18 lr: 3.8534358062714895e-05 loss: 0.0487 (0.0485) time: 2.8127 data: 0.0025 max mem: 19788 +Epoch: [10] [ 120/2138] eta: 1:38:27 lr: 3.85289415806374e-05 loss: 0.0411 (0.0476) time: 2.8137 data: 0.0025 max mem: 19788 +Epoch: [10] [ 130/2138] eta: 1:37:42 lr: 3.852352501395183e-05 loss: 0.0410 (0.0473) time: 2.8184 data: 0.0026 max mem: 19788 +Epoch: [10] [ 140/2138] eta: 1:37:00 lr: 3.851810836264366e-05 loss: 0.0434 (0.0468) time: 2.8268 data: 0.0025 max mem: 19788 +Epoch: [10] [ 150/2138] eta: 1:36:16 lr: 3.851269162669832e-05 loss: 0.0420 (0.0467) time: 2.8127 data: 0.0024 max mem: 19788 +Epoch: [10] [ 160/2138] eta: 1:35:34 lr: 3.8507274806101265e-05 loss: 0.0422 (0.0467) time: 2.8007 data: 0.0026 max mem: 19788 +Epoch: [10] [ 170/2138] eta: 1:34:53 lr: 3.850185790083795e-05 loss: 0.0432 (0.0466) time: 2.7994 data: 0.0025 max mem: 19788 +Epoch: [10] [ 180/2138] eta: 1:34:14 lr: 3.849644091089381e-05 loss: 0.0405 (0.0469) time: 2.7974 data: 0.0025 max mem: 19788 +Epoch: [10] [ 190/2138] eta: 1:33:36 lr: 3.8491023836254295e-05 loss: 0.0388 (0.0465) time: 2.7957 data: 0.0027 max mem: 19788 +Epoch: [10] [ 200/2138] eta: 1:32:58 lr: 3.848560667690481e-05 loss: 0.0346 (0.0461) time: 2.7945 data: 0.0027 max mem: 19788 +Epoch: [10] [ 210/2138] eta: 1:32:22 lr: 3.848018943283079e-05 loss: 0.0338 (0.0459) time: 2.7966 data: 0.0026 max mem: 19788 +Epoch: [10] [ 220/2138] eta: 1:31:47 lr: 3.847477210401767e-05 loss: 0.0346 (0.0459) time: 2.7982 data: 0.0028 max mem: 19788 +Epoch: [10] [ 230/2138] eta: 1:31:12 lr: 3.846935469045086e-05 loss: 0.0432 (0.0465) time: 2.7973 data: 0.0027 max mem: 19788 +Epoch: [10] [ 240/2138] eta: 1:30:38 lr: 3.8463937192115764e-05 loss: 0.0444 (0.0463) time: 2.7989 data: 0.0023 max mem: 19788 +Epoch: [10] [ 250/2138] eta: 1:30:05 lr: 3.845851960899779e-05 loss: 0.0365 (0.0461) time: 2.8054 data: 0.0024 max mem: 19788 +Epoch: [10] [ 260/2138] eta: 1:29:32 lr: 3.8453101941082365e-05 loss: 0.0360 (0.0459) time: 2.8074 data: 0.0025 max mem: 19788 +Epoch: [10] [ 270/2138] eta: 1:29:01 lr: 3.844768418835486e-05 loss: 0.0403 (0.0459) time: 2.8127 data: 0.0023 max mem: 19788 +Epoch: [10] [ 280/2138] eta: 1:28:29 lr: 3.844226635080067e-05 loss: 0.0425 (0.0459) time: 2.8147 data: 0.0022 max mem: 19788 +Epoch: [10] [ 290/2138] eta: 1:27:58 lr: 3.843684842840519e-05 loss: 0.0411 (0.0458) time: 2.8113 data: 0.0024 max mem: 19788 +Epoch: [10] [ 300/2138] eta: 1:27:26 lr: 3.843143042115381e-05 loss: 0.0424 (0.0459) time: 2.8095 data: 0.0025 max mem: 19788 +Epoch: [10] [ 310/2138] eta: 1:26:55 lr: 3.8426012329031894e-05 loss: 0.0413 (0.0456) time: 2.8070 data: 0.0023 max mem: 19788 +Epoch: [10] [ 320/2138] eta: 1:26:23 lr: 3.842059415202482e-05 loss: 0.0350 (0.0455) time: 2.8052 data: 0.0023 max mem: 19788 +Epoch: [10] [ 330/2138] eta: 1:25:52 lr: 3.841517589011797e-05 loss: 0.0411 (0.0458) time: 2.8022 data: 0.0024 max mem: 19788 +Epoch: [10] [ 340/2138] eta: 1:25:21 lr: 3.840975754329669e-05 loss: 0.0419 (0.0457) time: 2.7984 data: 0.0025 max mem: 19788 +Epoch: [10] [ 350/2138] eta: 1:24:50 lr: 3.840433911154635e-05 loss: 0.0400 (0.0456) time: 2.7967 data: 0.0024 max mem: 19788 +Epoch: [10] [ 360/2138] eta: 1:24:19 lr: 3.83989205948523e-05 loss: 0.0400 (0.0460) time: 2.7963 data: 0.0023 max mem: 19788 +Epoch: [10] [ 370/2138] eta: 1:23:48 lr: 3.8393501993199894e-05 loss: 0.0377 (0.0460) time: 2.7933 data: 0.0025 max mem: 19788 +Epoch: [10] [ 380/2138] eta: 1:23:17 lr: 3.8388083306574474e-05 loss: 0.0387 (0.0458) time: 2.7914 data: 0.0026 max mem: 19788 +Epoch: [10] [ 390/2138] eta: 1:22:46 lr: 3.8382664534961374e-05 loss: 0.0327 (0.0455) time: 2.7941 data: 0.0026 max mem: 19788 +Epoch: [10] [ 400/2138] eta: 1:22:16 lr: 3.837724567834593e-05 loss: 0.0372 (0.0454) time: 2.7934 data: 0.0025 max mem: 19788 +Epoch: [10] [ 410/2138] eta: 1:21:45 lr: 3.837182673671349e-05 loss: 0.0378 (0.0452) time: 2.7904 data: 0.0023 max mem: 19788 +Epoch: [10] [ 420/2138] eta: 1:21:15 lr: 3.8366407710049354e-05 loss: 0.0363 (0.0452) time: 2.7941 data: 0.0021 max mem: 19788 +Epoch: [10] [ 430/2138] eta: 1:20:46 lr: 3.836098859833886e-05 loss: 0.0380 (0.0452) time: 2.8037 data: 0.0022 max mem: 19788 +Epoch: [10] [ 440/2138] eta: 1:20:16 lr: 3.835556940156731e-05 loss: 0.0380 (0.0452) time: 2.8073 data: 0.0023 max mem: 19788 +Epoch: [10] [ 450/2138] eta: 1:19:46 lr: 3.8350150119720044e-05 loss: 0.0391 (0.0451) time: 2.8035 data: 0.0023 max mem: 19788 +Epoch: [10] [ 460/2138] eta: 1:19:17 lr: 3.834473075278234e-05 loss: 0.0391 (0.0450) time: 2.8032 data: 0.0022 max mem: 19788 +Epoch: [10] [ 470/2138] eta: 1:18:48 lr: 3.833931130073949e-05 loss: 0.0397 (0.0450) time: 2.8078 data: 0.0022 max mem: 19788 +Epoch: [10] [ 480/2138] eta: 1:18:19 lr: 3.833389176357682e-05 loss: 0.0423 (0.0451) time: 2.8128 data: 0.0022 max mem: 19788 +Epoch: [10] [ 490/2138] eta: 1:17:49 lr: 3.8328472141279614e-05 loss: 0.0434 (0.0452) time: 2.8135 data: 0.0025 max mem: 19788 +Epoch: [10] [ 500/2138] eta: 1:17:20 lr: 3.832305243383315e-05 loss: 0.0427 (0.0452) time: 2.8129 data: 0.0027 max mem: 19788 +Epoch: [10] [ 510/2138] eta: 1:16:51 lr: 3.831763264122271e-05 loss: 0.0350 (0.0452) time: 2.8118 data: 0.0025 max mem: 19788 +Epoch: [10] [ 520/2138] eta: 1:16:22 lr: 3.8312212763433575e-05 loss: 0.0364 (0.0452) time: 2.8089 data: 0.0025 max mem: 19788 +Epoch: [10] [ 530/2138] eta: 1:15:53 lr: 3.8306792800451016e-05 loss: 0.0380 (0.0452) time: 2.8048 data: 0.0024 max mem: 19788 +Epoch: [10] [ 540/2138] eta: 1:15:24 lr: 3.830137275226031e-05 loss: 0.0386 (0.0451) time: 2.8063 data: 0.0025 max mem: 19788 +Epoch: [10] [ 550/2138] eta: 1:14:55 lr: 3.8295952618846706e-05 loss: 0.0416 (0.0452) time: 2.8111 data: 0.0025 max mem: 19788 +Epoch: [10] [ 560/2138] eta: 1:14:26 lr: 3.829053240019546e-05 loss: 0.0416 (0.0452) time: 2.8136 data: 0.0026 max mem: 19788 +Epoch: [10] [ 570/2138] eta: 1:13:58 lr: 3.8285112096291834e-05 loss: 0.0366 (0.0450) time: 2.8122 data: 0.0027 max mem: 19788 +Epoch: [10] [ 580/2138] eta: 1:13:29 lr: 3.827969170712107e-05 loss: 0.0412 (0.0451) time: 2.8069 data: 0.0026 max mem: 19788 +Epoch: [10] [ 590/2138] eta: 1:13:00 lr: 3.827427123266841e-05 loss: 0.0391 (0.0450) time: 2.8094 data: 0.0025 max mem: 19788 +Epoch: [10] [ 600/2138] eta: 1:12:31 lr: 3.8268850672919096e-05 loss: 0.0391 (0.0451) time: 2.8124 data: 0.0023 max mem: 19788 +Epoch: [10] [ 610/2138] eta: 1:12:02 lr: 3.8263430027858364e-05 loss: 0.0381 (0.0449) time: 2.8126 data: 0.0021 max mem: 19788 +Epoch: [10] [ 620/2138] eta: 1:11:34 lr: 3.825800929747144e-05 loss: 0.0381 (0.0450) time: 2.8155 data: 0.0024 max mem: 19788 +Epoch: [10] [ 630/2138] eta: 1:11:05 lr: 3.8252588481743545e-05 loss: 0.0385 (0.0449) time: 2.8103 data: 0.0024 max mem: 19788 +Epoch: [10] [ 640/2138] eta: 1:10:36 lr: 3.8247167580659895e-05 loss: 0.0410 (0.0449) time: 2.8080 data: 0.0022 max mem: 19788 +Epoch: [10] [ 650/2138] eta: 1:10:08 lr: 3.824174659420571e-05 loss: 0.0410 (0.0449) time: 2.8116 data: 0.0023 max mem: 19788 +Epoch: [10] [ 660/2138] eta: 1:09:39 lr: 3.82363255223662e-05 loss: 0.0340 (0.0450) time: 2.8111 data: 0.0026 max mem: 19788 +Epoch: [10] [ 670/2138] eta: 1:09:10 lr: 3.823090436512656e-05 loss: 0.0381 (0.0450) time: 2.8119 data: 0.0027 max mem: 19788 +Epoch: [10] [ 680/2138] eta: 1:08:42 lr: 3.822548312247199e-05 loss: 0.0381 (0.0449) time: 2.8136 data: 0.0027 max mem: 19788 +Epoch: [10] [ 690/2138] eta: 1:08:13 lr: 3.82200617943877e-05 loss: 0.0426 (0.0450) time: 2.8139 data: 0.0027 max mem: 19788 +Epoch: [10] [ 700/2138] eta: 1:07:45 lr: 3.8214640380858845e-05 loss: 0.0424 (0.0449) time: 2.8121 data: 0.0027 max mem: 19788 +Epoch: [10] [ 710/2138] eta: 1:07:16 lr: 3.820921888187064e-05 loss: 0.0385 (0.0449) time: 2.8110 data: 0.0024 max mem: 19788 +Epoch: [10] [ 720/2138] eta: 1:06:47 lr: 3.8203797297408264e-05 loss: 0.0367 (0.0448) time: 2.8124 data: 0.0022 max mem: 19788 +Epoch: [10] [ 730/2138] eta: 1:06:19 lr: 3.8198375627456876e-05 loss: 0.0411 (0.0448) time: 2.8217 data: 0.0023 max mem: 19788 +Epoch: [10] [ 740/2138] eta: 1:05:51 lr: 3.819295387200165e-05 loss: 0.0461 (0.0448) time: 2.8219 data: 0.0026 max mem: 19788 +Epoch: [10] [ 750/2138] eta: 1:05:22 lr: 3.818753203102776e-05 loss: 0.0407 (0.0448) time: 2.8134 data: 0.0030 max mem: 19788 +Epoch: [10] [ 760/2138] eta: 1:04:54 lr: 3.818211010452035e-05 loss: 0.0362 (0.0447) time: 2.8151 data: 0.0027 max mem: 19788 +Epoch: [10] [ 770/2138] eta: 1:04:25 lr: 3.8176688092464594e-05 loss: 0.0384 (0.0447) time: 2.8142 data: 0.0025 max mem: 19788 +Epoch: [10] [ 780/2138] eta: 1:03:57 lr: 3.817126599484562e-05 loss: 0.0366 (0.0447) time: 2.8079 data: 0.0025 max mem: 19788 +Epoch: [10] [ 790/2138] eta: 1:03:28 lr: 3.816584381164859e-05 loss: 0.0387 (0.0446) time: 2.8048 data: 0.0024 max mem: 19788 +Epoch: [10] [ 800/2138] eta: 1:03:00 lr: 3.816042154285864e-05 loss: 0.0420 (0.0446) time: 2.8119 data: 0.0024 max mem: 19788 +Epoch: [10] [ 810/2138] eta: 1:02:31 lr: 3.81549991884609e-05 loss: 0.0431 (0.0445) time: 2.8187 data: 0.0026 max mem: 19788 +Epoch: [10] [ 820/2138] eta: 1:02:03 lr: 3.814957674844049e-05 loss: 0.0357 (0.0446) time: 2.8174 data: 0.0026 max mem: 19788 +Epoch: [10] [ 830/2138] eta: 1:01:35 lr: 3.814415422278257e-05 loss: 0.0346 (0.0445) time: 2.8175 data: 0.0025 max mem: 19788 +Epoch: [10] [ 840/2138] eta: 1:01:06 lr: 3.813873161147223e-05 loss: 0.0349 (0.0445) time: 2.8140 data: 0.0025 max mem: 19788 +Epoch: [10] [ 850/2138] eta: 1:00:38 lr: 3.81333089144946e-05 loss: 0.0354 (0.0444) time: 2.8125 data: 0.0028 max mem: 19788 +Epoch: [10] [ 860/2138] eta: 1:00:09 lr: 3.8127886131834776e-05 loss: 0.0345 (0.0443) time: 2.8154 data: 0.0031 max mem: 19788 +Epoch: [10] [ 870/2138] eta: 0:59:41 lr: 3.8122463263477864e-05 loss: 0.0357 (0.0443) time: 2.8141 data: 0.0028 max mem: 19788 +Epoch: [10] [ 880/2138] eta: 0:59:13 lr: 3.811704030940898e-05 loss: 0.0378 (0.0442) time: 2.8146 data: 0.0025 max mem: 19788 +Epoch: [10] [ 890/2138] eta: 0:58:44 lr: 3.8111617269613226e-05 loss: 0.0371 (0.0442) time: 2.8135 data: 0.0026 max mem: 19788 +Epoch: [10] [ 900/2138] eta: 0:58:16 lr: 3.8106194144075664e-05 loss: 0.0365 (0.0442) time: 2.8112 data: 0.0027 max mem: 19788 +Epoch: [10] [ 910/2138] eta: 0:57:47 lr: 3.810077093278139e-05 loss: 0.0383 (0.0442) time: 2.8118 data: 0.0028 max mem: 19788 +Epoch: [10] [ 920/2138] eta: 0:57:19 lr: 3.80953476357155e-05 loss: 0.0377 (0.0441) time: 2.8115 data: 0.0026 max mem: 19788 +Epoch: [10] [ 930/2138] eta: 0:56:51 lr: 3.808992425286306e-05 loss: 0.0412 (0.0441) time: 2.8141 data: 0.0024 max mem: 19788 +Epoch: [10] [ 940/2138] eta: 0:56:22 lr: 3.8084500784209135e-05 loss: 0.0426 (0.0442) time: 2.8175 data: 0.0024 max mem: 19788 +Epoch: [10] [ 950/2138] eta: 0:55:54 lr: 3.807907722973879e-05 loss: 0.0416 (0.0443) time: 2.8124 data: 0.0024 max mem: 19788 +Epoch: [10] [ 960/2138] eta: 0:55:25 lr: 3.8073653589437095e-05 loss: 0.0421 (0.0443) time: 2.8088 data: 0.0025 max mem: 19788 +Epoch: [10] [ 970/2138] eta: 0:54:57 lr: 3.806822986328911e-05 loss: 0.0400 (0.0442) time: 2.8109 data: 0.0026 max mem: 19788 +Epoch: [10] [ 980/2138] eta: 0:54:29 lr: 3.806280605127987e-05 loss: 0.0394 (0.0442) time: 2.8109 data: 0.0024 max mem: 19788 +Epoch: [10] [ 990/2138] eta: 0:54:00 lr: 3.805738215339443e-05 loss: 0.0356 (0.0442) time: 2.8126 data: 0.0024 max mem: 19788 +Epoch: [10] [1000/2138] eta: 0:53:32 lr: 3.805195816961783e-05 loss: 0.0356 (0.0442) time: 2.8137 data: 0.0024 max mem: 19788 +Epoch: [10] [1010/2138] eta: 0:53:04 lr: 3.804653409993511e-05 loss: 0.0439 (0.0443) time: 2.8122 data: 0.0027 max mem: 19788 +Epoch: [10] [1020/2138] eta: 0:52:35 lr: 3.804110994433129e-05 loss: 0.0418 (0.0442) time: 2.8096 data: 0.0028 max mem: 19788 +Epoch: [10] [1030/2138] eta: 0:52:07 lr: 3.803568570279141e-05 loss: 0.0315 (0.0442) time: 2.8064 data: 0.0025 max mem: 19788 +Epoch: [10] [1040/2138] eta: 0:51:39 lr: 3.803026137530049e-05 loss: 0.0397 (0.0442) time: 2.8160 data: 0.0025 max mem: 19788 +Epoch: [10] [1050/2138] eta: 0:51:10 lr: 3.802483696184353e-05 loss: 0.0342 (0.0442) time: 2.8121 data: 0.0025 max mem: 19788 +Epoch: [10] [1060/2138] eta: 0:50:42 lr: 3.801941246240555e-05 loss: 0.0331 (0.0442) time: 2.7981 data: 0.0026 max mem: 19788 +Epoch: [10] [1070/2138] eta: 0:50:13 lr: 3.801398787697156e-05 loss: 0.0362 (0.0442) time: 2.7955 data: 0.0027 max mem: 19788 +Epoch: [10] [1080/2138] eta: 0:49:45 lr: 3.800856320552657e-05 loss: 0.0367 (0.0442) time: 2.7942 data: 0.0027 max mem: 19788 +Epoch: [10] [1090/2138] eta: 0:49:16 lr: 3.8003138448055546e-05 loss: 0.0418 (0.0442) time: 2.8042 data: 0.0023 max mem: 19788 +Epoch: [10] [1100/2138] eta: 0:48:48 lr: 3.7997713604543514e-05 loss: 0.0435 (0.0443) time: 2.8090 data: 0.0022 max mem: 19788 +Epoch: [10] [1110/2138] eta: 0:48:20 lr: 3.7992288674975435e-05 loss: 0.0441 (0.0443) time: 2.7971 data: 0.0023 max mem: 19788 +Epoch: [10] [1120/2138] eta: 0:47:51 lr: 3.798686365933631e-05 loss: 0.0430 (0.0443) time: 2.7906 data: 0.0024 max mem: 19788 +Epoch: [10] [1130/2138] eta: 0:47:23 lr: 3.7981438557611085e-05 loss: 0.0376 (0.0443) time: 2.7984 data: 0.0026 max mem: 19788 +Epoch: [10] [1140/2138] eta: 0:46:54 lr: 3.797601336978476e-05 loss: 0.0445 (0.0443) time: 2.8017 data: 0.0028 max mem: 19788 +Epoch: [10] [1150/2138] eta: 0:46:26 lr: 3.79705880958423e-05 loss: 0.0408 (0.0442) time: 2.8030 data: 0.0028 max mem: 19788 +Epoch: [10] [1160/2138] eta: 0:45:58 lr: 3.7965162735768654e-05 loss: 0.0367 (0.0442) time: 2.7983 data: 0.0027 max mem: 19788 +Epoch: [10] [1170/2138] eta: 0:45:29 lr: 3.7959737289548784e-05 loss: 0.0369 (0.0443) time: 2.7919 data: 0.0024 max mem: 19788 +Epoch: [10] [1180/2138] eta: 0:45:01 lr: 3.7954311757167624e-05 loss: 0.0452 (0.0443) time: 2.7912 data: 0.0022 max mem: 19788 +Epoch: [10] [1190/2138] eta: 0:44:32 lr: 3.794888613861015e-05 loss: 0.0405 (0.0443) time: 2.7871 data: 0.0021 max mem: 19788 +Epoch: [10] [1200/2138] eta: 0:44:04 lr: 3.794346043386129e-05 loss: 0.0405 (0.0443) time: 2.8021 data: 0.0024 max mem: 19788 +Epoch: [10] [1210/2138] eta: 0:43:36 lr: 3.793803464290597e-05 loss: 0.0421 (0.0443) time: 2.8125 data: 0.0027 max mem: 19788 +Epoch: [10] [1220/2138] eta: 0:43:07 lr: 3.7932608765729126e-05 loss: 0.0402 (0.0443) time: 2.8008 data: 0.0024 max mem: 19788 +Epoch: [10] [1230/2138] eta: 0:42:39 lr: 3.7927182802315695e-05 loss: 0.0388 (0.0443) time: 2.7970 data: 0.0025 max mem: 19788 +Epoch: [10] [1240/2138] eta: 0:42:11 lr: 3.792175675265059e-05 loss: 0.0382 (0.0442) time: 2.7982 data: 0.0028 max mem: 19788 +Epoch: [10] [1250/2138] eta: 0:41:42 lr: 3.791633061671872e-05 loss: 0.0391 (0.0443) time: 2.7950 data: 0.0028 max mem: 19788 +Epoch: [10] [1260/2138] eta: 0:41:14 lr: 3.7910904394505006e-05 loss: 0.0426 (0.0442) time: 2.7985 data: 0.0027 max mem: 19788 +Epoch: [10] [1270/2138] eta: 0:40:46 lr: 3.7905478085994354e-05 loss: 0.0397 (0.0442) time: 2.8116 data: 0.0026 max mem: 19788 +Epoch: [10] [1280/2138] eta: 0:40:17 lr: 3.790005169117166e-05 loss: 0.0365 (0.0442) time: 2.8077 data: 0.0025 max mem: 19788 +Epoch: [10] [1290/2138] eta: 0:39:49 lr: 3.789462521002182e-05 loss: 0.0380 (0.0442) time: 2.7984 data: 0.0024 max mem: 19788 +Epoch: [10] [1300/2138] eta: 0:39:21 lr: 3.788919864252973e-05 loss: 0.0396 (0.0441) time: 2.8018 data: 0.0023 max mem: 19788 +Epoch: [10] [1310/2138] eta: 0:38:53 lr: 3.788377198868027e-05 loss: 0.0388 (0.0441) time: 2.7974 data: 0.0022 max mem: 19788 +Epoch: [10] [1320/2138] eta: 0:38:24 lr: 3.7878345248458314e-05 loss: 0.0388 (0.0441) time: 2.7952 data: 0.0020 max mem: 19788 +Epoch: [10] [1330/2138] eta: 0:37:56 lr: 3.7872918421848744e-05 loss: 0.0401 (0.0441) time: 2.7954 data: 0.0020 max mem: 19788 +Epoch: [10] [1340/2138] eta: 0:37:28 lr: 3.786749150883644e-05 loss: 0.0439 (0.0441) time: 2.7969 data: 0.0020 max mem: 19788 +Epoch: [10] [1350/2138] eta: 0:36:59 lr: 3.786206450940626e-05 loss: 0.0478 (0.0442) time: 2.8019 data: 0.0020 max mem: 19788 +Epoch: [10] [1360/2138] eta: 0:36:31 lr: 3.785663742354306e-05 loss: 0.0426 (0.0442) time: 2.8003 data: 0.0020 max mem: 19788 +Epoch: [10] [1370/2138] eta: 0:36:03 lr: 3.7851210251231695e-05 loss: 0.0406 (0.0443) time: 2.7948 data: 0.0020 max mem: 19788 +Epoch: [10] [1380/2138] eta: 0:35:34 lr: 3.7845782992457025e-05 loss: 0.0464 (0.0444) time: 2.7903 data: 0.0021 max mem: 19788 +Epoch: [10] [1390/2138] eta: 0:35:06 lr: 3.784035564720389e-05 loss: 0.0441 (0.0444) time: 2.7904 data: 0.0021 max mem: 19788 +Epoch: [10] [1400/2138] eta: 0:34:38 lr: 3.7834928215457124e-05 loss: 0.0378 (0.0444) time: 2.7948 data: 0.0021 max mem: 19788 +Epoch: [10] [1410/2138] eta: 0:34:10 lr: 3.782950069720156e-05 loss: 0.0342 (0.0443) time: 2.8018 data: 0.0021 max mem: 19788 +Epoch: [10] [1420/2138] eta: 0:33:41 lr: 3.782407309242205e-05 loss: 0.0342 (0.0443) time: 2.7974 data: 0.0020 max mem: 19788 +Epoch: [10] [1430/2138] eta: 0:33:13 lr: 3.7818645401103406e-05 loss: 0.0409 (0.0443) time: 2.7882 data: 0.0020 max mem: 19788 +Epoch: [10] [1440/2138] eta: 0:32:45 lr: 3.7813217623230436e-05 loss: 0.0409 (0.0443) time: 2.7906 data: 0.0021 max mem: 19788 +Epoch: [10] [1450/2138] eta: 0:32:17 lr: 3.780778975878797e-05 loss: 0.0362 (0.0442) time: 2.7892 data: 0.0021 max mem: 19788 +Epoch: [10] [1460/2138] eta: 0:31:48 lr: 3.78023618077608e-05 loss: 0.0355 (0.0442) time: 2.7932 data: 0.0021 max mem: 19788 +Epoch: [10] [1470/2138] eta: 0:31:20 lr: 3.779693377013376e-05 loss: 0.0374 (0.0442) time: 2.8009 data: 0.0021 max mem: 19788 +Epoch: [10] [1480/2138] eta: 0:30:52 lr: 3.779150564589162e-05 loss: 0.0380 (0.0442) time: 2.7960 data: 0.0023 max mem: 19788 +Epoch: [10] [1490/2138] eta: 0:30:24 lr: 3.7786077435019185e-05 loss: 0.0433 (0.0442) time: 2.7897 data: 0.0023 max mem: 19788 +Epoch: [10] [1500/2138] eta: 0:29:55 lr: 3.778064913750125e-05 loss: 0.0434 (0.0442) time: 2.7902 data: 0.0022 max mem: 19788 +Epoch: [10] [1510/2138] eta: 0:29:27 lr: 3.77752207533226e-05 loss: 0.0371 (0.0442) time: 2.7950 data: 0.0022 max mem: 19788 +Epoch: [10] [1520/2138] eta: 0:28:59 lr: 3.7769792282467995e-05 loss: 0.0369 (0.0442) time: 2.8073 data: 0.0025 max mem: 19788 +Epoch: [10] [1530/2138] eta: 0:28:31 lr: 3.776436372492223e-05 loss: 0.0359 (0.0442) time: 2.8092 data: 0.0027 max mem: 19788 +Epoch: [10] [1540/2138] eta: 0:28:03 lr: 3.7758935080670074e-05 loss: 0.0363 (0.0441) time: 2.7991 data: 0.0027 max mem: 19788 +Epoch: [10] [1550/2138] eta: 0:27:34 lr: 3.775350634969627e-05 loss: 0.0376 (0.0441) time: 2.7975 data: 0.0027 max mem: 19788 +Epoch: [10] [1560/2138] eta: 0:27:06 lr: 3.774807753198559e-05 loss: 0.0467 (0.0442) time: 2.7932 data: 0.0026 max mem: 19788 +Epoch: [10] [1570/2138] eta: 0:26:38 lr: 3.774264862752279e-05 loss: 0.0405 (0.0442) time: 2.7889 data: 0.0024 max mem: 19788 +Epoch: [10] [1580/2138] eta: 0:26:10 lr: 3.773721963629263e-05 loss: 0.0343 (0.0441) time: 2.7976 data: 0.0021 max mem: 19788 +Epoch: [10] [1590/2138] eta: 0:25:42 lr: 3.7731790558279825e-05 loss: 0.0375 (0.0441) time: 2.8057 data: 0.0020 max mem: 19788 +Epoch: [10] [1600/2138] eta: 0:25:13 lr: 3.772636139346912e-05 loss: 0.0443 (0.0441) time: 2.8018 data: 0.0021 max mem: 19788 +Epoch: [10] [1610/2138] eta: 0:24:45 lr: 3.772093214184526e-05 loss: 0.0394 (0.0441) time: 2.7971 data: 0.0025 max mem: 19788 +Epoch: [10] [1620/2138] eta: 0:24:17 lr: 3.771550280339298e-05 loss: 0.0327 (0.0441) time: 2.7974 data: 0.0027 max mem: 19788 +Epoch: [10] [1630/2138] eta: 0:23:49 lr: 3.771007337809697e-05 loss: 0.0325 (0.0440) time: 2.7970 data: 0.0026 max mem: 19788 +Epoch: [10] [1640/2138] eta: 0:23:21 lr: 3.770464386594197e-05 loss: 0.0379 (0.0441) time: 2.7951 data: 0.0023 max mem: 19788 +Epoch: [10] [1650/2138] eta: 0:22:52 lr: 3.7699214266912704e-05 loss: 0.0365 (0.0440) time: 2.7960 data: 0.0023 max mem: 19788 +Epoch: [10] [1660/2138] eta: 0:22:24 lr: 3.769378458099386e-05 loss: 0.0369 (0.0441) time: 2.8047 data: 0.0025 max mem: 19788 +Epoch: [10] [1670/2138] eta: 0:21:56 lr: 3.768835480817014e-05 loss: 0.0404 (0.0441) time: 2.8126 data: 0.0028 max mem: 19788 +Epoch: [10] [1680/2138] eta: 0:21:28 lr: 3.768292494842625e-05 loss: 0.0374 (0.0440) time: 2.8063 data: 0.0028 max mem: 19788 +Epoch: [10] [1690/2138] eta: 0:21:00 lr: 3.767749500174688e-05 loss: 0.0376 (0.0441) time: 2.7976 data: 0.0024 max mem: 19788 +Epoch: [10] [1700/2138] eta: 0:20:32 lr: 3.7672064968116717e-05 loss: 0.0392 (0.0440) time: 2.7932 data: 0.0022 max mem: 19788 +Epoch: [10] [1710/2138] eta: 0:20:03 lr: 3.766663484752044e-05 loss: 0.0381 (0.0440) time: 2.7893 data: 0.0022 max mem: 19788 +Epoch: [10] [1720/2138] eta: 0:19:35 lr: 3.766120463994272e-05 loss: 0.0416 (0.0440) time: 2.7931 data: 0.0024 max mem: 19788 +Epoch: [10] [1730/2138] eta: 0:19:07 lr: 3.765577434536824e-05 loss: 0.0416 (0.0441) time: 2.8098 data: 0.0027 max mem: 19788 +Epoch: [10] [1740/2138] eta: 0:18:39 lr: 3.765034396378166e-05 loss: 0.0438 (0.0441) time: 2.8152 data: 0.0028 max mem: 19788 +Epoch: [10] [1750/2138] eta: 0:18:11 lr: 3.764491349516764e-05 loss: 0.0370 (0.0441) time: 2.8005 data: 0.0029 max mem: 19788 +Epoch: [10] [1760/2138] eta: 0:17:43 lr: 3.7639482939510834e-05 loss: 0.0370 (0.0441) time: 2.7951 data: 0.0025 max mem: 19788 +Epoch: [10] [1770/2138] eta: 0:17:14 lr: 3.763405229679591e-05 loss: 0.0366 (0.0440) time: 2.7965 data: 0.0021 max mem: 19788 +Epoch: [10] [1780/2138] eta: 0:16:46 lr: 3.7628621567007485e-05 loss: 0.0348 (0.0440) time: 2.7967 data: 0.0022 max mem: 19788 +Epoch: [10] [1790/2138] eta: 0:16:18 lr: 3.762319075013022e-05 loss: 0.0348 (0.0440) time: 2.8055 data: 0.0023 max mem: 19788 +Epoch: [10] [1800/2138] eta: 0:15:50 lr: 3.7617759846148745e-05 loss: 0.0430 (0.0440) time: 2.8121 data: 0.0025 max mem: 19788 +Epoch: [10] [1810/2138] eta: 0:15:22 lr: 3.7612328855047684e-05 loss: 0.0430 (0.0440) time: 2.8015 data: 0.0026 max mem: 19788 +Epoch: [10] [1820/2138] eta: 0:14:54 lr: 3.760689777681167e-05 loss: 0.0372 (0.0440) time: 2.7905 data: 0.0022 max mem: 19788 +Epoch: [10] [1830/2138] eta: 0:14:26 lr: 3.7601466611425315e-05 loss: 0.0366 (0.0440) time: 2.7959 data: 0.0022 max mem: 19788 +Epoch: [10] [1840/2138] eta: 0:13:57 lr: 3.759603535887324e-05 loss: 0.0400 (0.0440) time: 2.7982 data: 0.0025 max mem: 19788 +Epoch: [10] [1850/2138] eta: 0:13:29 lr: 3.759060401914006e-05 loss: 0.0400 (0.0440) time: 2.7924 data: 0.0023 max mem: 19788 +Epoch: [10] [1860/2138] eta: 0:13:01 lr: 3.758517259221037e-05 loss: 0.0391 (0.0439) time: 2.7932 data: 0.0021 max mem: 19788 +Epoch: [10] [1870/2138] eta: 0:12:33 lr: 3.757974107806876e-05 loss: 0.0404 (0.0440) time: 2.7959 data: 0.0021 max mem: 19788 +Epoch: [10] [1880/2138] eta: 0:12:05 lr: 3.757430947669984e-05 loss: 0.0387 (0.0439) time: 2.8047 data: 0.0024 max mem: 19788 +Epoch: [10] [1890/2138] eta: 0:11:37 lr: 3.7568877788088184e-05 loss: 0.0325 (0.0439) time: 2.8171 data: 0.0025 max mem: 19788 +Epoch: [10] [1900/2138] eta: 0:11:09 lr: 3.7563446012218395e-05 loss: 0.0383 (0.0439) time: 2.8063 data: 0.0023 max mem: 19788 +Epoch: [10] [1910/2138] eta: 0:10:41 lr: 3.755801414907503e-05 loss: 0.0391 (0.0439) time: 2.7906 data: 0.0024 max mem: 19788 +Epoch: [10] [1920/2138] eta: 0:10:12 lr: 3.755258219864267e-05 loss: 0.0389 (0.0439) time: 2.7919 data: 0.0024 max mem: 19788 +Epoch: [10] [1930/2138] eta: 0:09:44 lr: 3.754715016090589e-05 loss: 0.0462 (0.0439) time: 2.7950 data: 0.0024 max mem: 19788 +Epoch: [10] [1940/2138] eta: 0:09:16 lr: 3.754171803584924e-05 loss: 0.0424 (0.0439) time: 2.7966 data: 0.0025 max mem: 19788 +Epoch: [10] [1950/2138] eta: 0:08:48 lr: 3.753628582345729e-05 loss: 0.0363 (0.0439) time: 2.7993 data: 0.0023 max mem: 19788 +Epoch: [10] [1960/2138] eta: 0:08:20 lr: 3.7530853523714584e-05 loss: 0.0357 (0.0439) time: 2.8081 data: 0.0022 max mem: 19788 +Epoch: [10] [1970/2138] eta: 0:07:52 lr: 3.752542113660567e-05 loss: 0.0354 (0.0438) time: 2.8089 data: 0.0023 max mem: 19788 +Epoch: [10] [1980/2138] eta: 0:07:24 lr: 3.751998866211508e-05 loss: 0.0360 (0.0438) time: 2.7990 data: 0.0025 max mem: 19788 +Epoch: [10] [1990/2138] eta: 0:06:56 lr: 3.7514556100227363e-05 loss: 0.0360 (0.0438) time: 2.7962 data: 0.0029 max mem: 19788 +Epoch: [10] [2000/2138] eta: 0:06:27 lr: 3.7509123450927055e-05 loss: 0.0358 (0.0438) time: 2.7960 data: 0.0028 max mem: 19788 +Epoch: [10] [2010/2138] eta: 0:05:59 lr: 3.7503690714198676e-05 loss: 0.0368 (0.0438) time: 2.8000 data: 0.0029 max mem: 19788 +Epoch: [10] [2020/2138] eta: 0:05:31 lr: 3.7498257890026736e-05 loss: 0.0376 (0.0438) time: 2.8048 data: 0.0030 max mem: 19788 +Epoch: [10] [2030/2138] eta: 0:05:03 lr: 3.749282497839575e-05 loss: 0.0376 (0.0438) time: 2.8010 data: 0.0029 max mem: 19788 +Epoch: [10] [2040/2138] eta: 0:04:35 lr: 3.7487391979290256e-05 loss: 0.0379 (0.0438) time: 2.7968 data: 0.0027 max mem: 19788 +Epoch: [10] [2050/2138] eta: 0:04:07 lr: 3.7481958892694735e-05 loss: 0.0405 (0.0438) time: 2.7946 data: 0.0027 max mem: 19788 +Epoch: [10] [2060/2138] eta: 0:03:39 lr: 3.7476525718593683e-05 loss: 0.0367 (0.0438) time: 2.7897 data: 0.0024 max mem: 19788 +Epoch: [10] [2070/2138] eta: 0:03:11 lr: 3.7471092456971604e-05 loss: 0.0367 (0.0438) time: 2.7931 data: 0.0021 max mem: 19788 +Epoch: [10] [2080/2138] eta: 0:02:43 lr: 3.7465659107812994e-05 loss: 0.0421 (0.0438) time: 2.7950 data: 0.0023 max mem: 19788 +Epoch: [10] [2090/2138] eta: 0:02:14 lr: 3.746022567110233e-05 loss: 0.0408 (0.0438) time: 2.7964 data: 0.0023 max mem: 19788 +Epoch: [10] [2100/2138] eta: 0:01:46 lr: 3.7454792146824085e-05 loss: 0.0386 (0.0438) time: 2.8006 data: 0.0024 max mem: 19788 +Epoch: [10] [2110/2138] eta: 0:01:18 lr: 3.744935853496274e-05 loss: 0.0415 (0.0438) time: 2.7969 data: 0.0024 max mem: 19788 +Epoch: [10] [2120/2138] eta: 0:00:50 lr: 3.744392483550276e-05 loss: 0.0473 (0.0438) time: 2.7937 data: 0.0024 max mem: 19788 +Epoch: [10] [2130/2138] eta: 0:00:22 lr: 3.743849104842861e-05 loss: 0.0483 (0.0438) time: 2.7866 data: 0.0021 max mem: 19788 +Epoch: [10] Total time: 1:40:08 +Test: [ 0/21770] eta: 17:50:01 time: 2.9491 data: 2.8966 max mem: 19788 +Test: [ 100/21770] eta: 0:26:29 time: 0.0429 data: 0.0014 max mem: 19788 +Test: [ 200/21770] eta: 0:20:55 time: 0.0434 data: 0.0014 max mem: 19788 +Test: [ 300/21770] eta: 0:19:33 time: 0.0439 data: 0.0014 max mem: 19788 +Test: [ 400/21770] eta: 0:18:45 time: 0.0466 data: 0.0017 max mem: 19788 +Test: [ 500/21770] eta: 0:18:11 time: 0.0489 data: 0.0016 max mem: 19788 +Test: [ 600/21770] eta: 0:17:43 time: 0.0434 data: 0.0014 max mem: 19788 +Test: [ 700/21770] eta: 0:17:28 time: 0.0474 data: 0.0016 max mem: 19788 +Test: [ 800/21770] eta: 0:17:04 time: 0.0435 data: 0.0014 max mem: 19788 +Test: [ 900/21770] eta: 0:16:56 time: 0.0483 data: 0.0014 max mem: 19788 +Test: [ 1000/21770] eta: 0:16:48 time: 0.0445 data: 0.0015 max mem: 19788 +Test: [ 1100/21770] eta: 0:16:42 time: 0.0475 data: 0.0016 max mem: 19788 +Test: [ 1200/21770] eta: 0:16:30 time: 0.0433 data: 0.0014 max mem: 19788 +Test: [ 1300/21770] eta: 0:16:17 time: 0.0426 data: 0.0016 max mem: 19788 +Test: [ 1400/21770] eta: 0:16:13 time: 0.0502 data: 0.0017 max mem: 19788 +Test: [ 1500/21770] eta: 0:16:04 time: 0.0469 data: 0.0015 max mem: 19788 +Test: [ 1600/21770] eta: 0:15:56 time: 0.0433 data: 0.0015 max mem: 19788 +Test: [ 1700/21770] eta: 0:15:50 time: 0.0435 data: 0.0015 max mem: 19788 +Test: [ 1800/21770] eta: 0:15:42 time: 0.0443 data: 0.0015 max mem: 19788 +Test: [ 1900/21770] eta: 0:15:37 time: 0.0428 data: 0.0014 max mem: 19788 +Test: [ 2000/21770] eta: 0:15:31 time: 0.0515 data: 0.0017 max mem: 19788 +Test: [ 2100/21770] eta: 0:15:23 time: 0.0436 data: 0.0013 max mem: 19788 +Test: [ 2200/21770] eta: 0:15:17 time: 0.0524 data: 0.0018 max mem: 19788 +Test: [ 2300/21770] eta: 0:15:14 time: 0.0512 data: 0.0018 max mem: 19788 +Test: [ 2400/21770] eta: 0:15:08 time: 0.0499 data: 0.0016 max mem: 19788 +Test: [ 2500/21770] eta: 0:15:04 time: 0.0469 data: 0.0016 max mem: 19788 +Test: [ 2600/21770] eta: 0:15:00 time: 0.0525 data: 0.0017 max mem: 19788 +Test: [ 2700/21770] eta: 0:14:55 time: 0.0462 data: 0.0014 max mem: 19788 +Test: [ 2800/21770] eta: 0:14:52 time: 0.0510 data: 0.0017 max mem: 19788 +Test: [ 2900/21770] eta: 0:14:47 time: 0.0514 data: 0.0015 max mem: 19788 +Test: [ 3000/21770] eta: 0:14:42 time: 0.0494 data: 0.0017 max mem: 19788 +Test: [ 3100/21770] eta: 0:14:38 time: 0.0469 data: 0.0015 max mem: 19788 +Test: [ 3200/21770] eta: 0:14:34 time: 0.0482 data: 0.0014 max mem: 19788 +Test: [ 3300/21770] eta: 0:14:28 time: 0.0431 data: 0.0015 max mem: 19788 +Test: [ 3400/21770] eta: 0:14:21 time: 0.0424 data: 0.0014 max mem: 19788 +Test: [ 3500/21770] eta: 0:14:16 time: 0.0433 data: 0.0013 max mem: 19788 +Test: [ 3600/21770] eta: 0:14:11 time: 0.0426 data: 0.0014 max mem: 19788 +Test: [ 3700/21770] eta: 0:14:05 time: 0.0448 data: 0.0015 max mem: 19788 +Test: [ 3800/21770] eta: 0:14:01 time: 0.0501 data: 0.0016 max mem: 19788 +Test: [ 3900/21770] eta: 0:13:56 time: 0.0450 data: 0.0014 max mem: 19788 +Test: [ 4000/21770] eta: 0:13:51 time: 0.0492 data: 0.0015 max mem: 19788 +Test: [ 4100/21770] eta: 0:13:47 time: 0.0514 data: 0.0016 max mem: 19788 +Test: [ 4200/21770] eta: 0:13:43 time: 0.0525 data: 0.0018 max mem: 19788 +Test: [ 4300/21770] eta: 0:13:38 time: 0.0435 data: 0.0015 max mem: 19788 +Test: [ 4400/21770] eta: 0:13:32 time: 0.0417 data: 0.0014 max mem: 19788 +Test: [ 4500/21770] eta: 0:13:28 time: 0.0456 data: 0.0015 max mem: 19788 +Test: [ 4600/21770] eta: 0:13:25 time: 0.0545 data: 0.0018 max mem: 19788 +Test: [ 4700/21770] eta: 0:13:22 time: 0.0457 data: 0.0015 max mem: 19788 +Test: [ 4800/21770] eta: 0:13:18 time: 0.0428 data: 0.0014 max mem: 19788 +Test: [ 4900/21770] eta: 0:13:13 time: 0.0481 data: 0.0015 max mem: 19788 +Test: [ 5000/21770] eta: 0:13:08 time: 0.0473 data: 0.0015 max mem: 19788 +Test: [ 5100/21770] eta: 0:13:03 time: 0.0457 data: 0.0015 max mem: 19788 +Test: [ 5200/21770] eta: 0:12:59 time: 0.0438 data: 0.0015 max mem: 19788 +Test: [ 5300/21770] eta: 0:12:54 time: 0.0527 data: 0.0017 max mem: 19788 +Test: [ 5400/21770] eta: 0:12:50 time: 0.0520 data: 0.0018 max mem: 19788 +Test: [ 5500/21770] eta: 0:12:45 time: 0.0506 data: 0.0017 max mem: 19788 +Test: [ 5600/21770] eta: 0:12:40 time: 0.0448 data: 0.0015 max mem: 19788 +Test: [ 5700/21770] eta: 0:12:36 time: 0.0528 data: 0.0017 max mem: 19788 +Test: [ 5800/21770] eta: 0:12:31 time: 0.0511 data: 0.0016 max mem: 19788 +Test: [ 5900/21770] eta: 0:12:27 time: 0.0494 data: 0.0017 max mem: 19788 +Test: [ 6000/21770] eta: 0:12:22 time: 0.0444 data: 0.0015 max mem: 19788 +Test: [ 6100/21770] eta: 0:12:17 time: 0.0435 data: 0.0014 max mem: 19788 +Test: [ 6200/21770] eta: 0:12:11 time: 0.0460 data: 0.0015 max mem: 19788 +Test: [ 6300/21770] eta: 0:12:06 time: 0.0441 data: 0.0015 max mem: 19788 +Test: [ 6400/21770] eta: 0:12:01 time: 0.0429 data: 0.0014 max mem: 19788 +Test: [ 6500/21770] eta: 0:11:56 time: 0.0436 data: 0.0013 max mem: 19788 +Test: [ 6600/21770] eta: 0:11:50 time: 0.0514 data: 0.0015 max mem: 19788 +Test: [ 6700/21770] eta: 0:11:46 time: 0.0504 data: 0.0017 max mem: 19788 +Test: [ 6800/21770] eta: 0:11:41 time: 0.0465 data: 0.0016 max mem: 19788 +Test: [ 6900/21770] eta: 0:11:36 time: 0.0433 data: 0.0015 max mem: 19788 +Test: [ 7000/21770] eta: 0:11:31 time: 0.0450 data: 0.0015 max mem: 19788 +Test: [ 7100/21770] eta: 0:11:27 time: 0.0468 data: 0.0014 max mem: 19788 +Test: [ 7200/21770] eta: 0:11:22 time: 0.0434 data: 0.0013 max mem: 19788 +Test: [ 7300/21770] eta: 0:11:17 time: 0.0494 data: 0.0016 max mem: 19788 +Test: [ 7400/21770] eta: 0:11:13 time: 0.0438 data: 0.0015 max mem: 19788 +Test: [ 7500/21770] eta: 0:11:08 time: 0.0479 data: 0.0014 max mem: 19788 +Test: [ 7600/21770] eta: 0:11:04 time: 0.0540 data: 0.0017 max mem: 19788 +Test: [ 7700/21770] eta: 0:10:59 time: 0.0448 data: 0.0013 max mem: 19788 +Test: [ 7800/21770] eta: 0:10:54 time: 0.0520 data: 0.0017 max mem: 19788 +Test: [ 7900/21770] eta: 0:10:49 time: 0.0419 data: 0.0013 max mem: 19788 +Test: [ 8000/21770] eta: 0:10:43 time: 0.0460 data: 0.0016 max mem: 19788 +Test: [ 8100/21770] eta: 0:10:39 time: 0.0504 data: 0.0017 max mem: 19788 +Test: [ 8200/21770] eta: 0:10:34 time: 0.0456 data: 0.0016 max mem: 19788 +Test: [ 8300/21770] eta: 0:10:30 time: 0.0453 data: 0.0016 max mem: 19788 +Test: [ 8400/21770] eta: 0:10:25 time: 0.0448 data: 0.0015 max mem: 19788 +Test: [ 8500/21770] eta: 0:10:20 time: 0.0500 data: 0.0014 max mem: 19788 +Test: [ 8600/21770] eta: 0:10:16 time: 0.0541 data: 0.0017 max mem: 19788 +Test: [ 8700/21770] eta: 0:10:11 time: 0.0429 data: 0.0015 max mem: 19788 +Test: [ 8800/21770] eta: 0:10:06 time: 0.0481 data: 0.0016 max mem: 19788 +Test: [ 8900/21770] eta: 0:10:01 time: 0.0433 data: 0.0014 max mem: 19788 +Test: [ 9000/21770] eta: 0:09:56 time: 0.0434 data: 0.0014 max mem: 19788 +Test: [ 9100/21770] eta: 0:09:51 time: 0.0464 data: 0.0015 max mem: 19788 +Test: [ 9200/21770] eta: 0:09:46 time: 0.0537 data: 0.0017 max mem: 19788 +Test: [ 9300/21770] eta: 0:09:41 time: 0.0441 data: 0.0014 max mem: 19788 +Test: [ 9400/21770] eta: 0:09:37 time: 0.0442 data: 0.0017 max mem: 19788 +Test: [ 9500/21770] eta: 0:09:32 time: 0.0433 data: 0.0013 max mem: 19788 +Test: [ 9600/21770] eta: 0:09:27 time: 0.0516 data: 0.0017 max mem: 19788 +Test: [ 9700/21770] eta: 0:09:22 time: 0.0443 data: 0.0015 max mem: 19788 +Test: [ 9800/21770] eta: 0:09:17 time: 0.0437 data: 0.0014 max mem: 19788 +Test: [ 9900/21770] eta: 0:09:12 time: 0.0441 data: 0.0015 max mem: 19788 +Test: [10000/21770] eta: 0:09:08 time: 0.0448 data: 0.0015 max mem: 19788 +Test: [10100/21770] eta: 0:09:03 time: 0.0511 data: 0.0016 max mem: 19788 +Test: [10200/21770] eta: 0:08:59 time: 0.0438 data: 0.0014 max mem: 19788 +Test: [10300/21770] eta: 0:08:54 time: 0.0522 data: 0.0018 max mem: 19788 +Test: [10400/21770] eta: 0:08:50 time: 0.0507 data: 0.0017 max mem: 19788 +Test: [10500/21770] eta: 0:08:45 time: 0.0436 data: 0.0015 max mem: 19788 +Test: [10600/21770] eta: 0:08:40 time: 0.0433 data: 0.0015 max mem: 19788 +Test: [10700/21770] eta: 0:08:36 time: 0.0524 data: 0.0018 max mem: 19788 +Test: [10800/21770] eta: 0:08:31 time: 0.0516 data: 0.0019 max mem: 19788 +Test: [10900/21770] eta: 0:08:26 time: 0.0455 data: 0.0016 max mem: 19788 +Test: [11000/21770] eta: 0:08:22 time: 0.0527 data: 0.0017 max mem: 19788 +Test: [11100/21770] eta: 0:08:17 time: 0.0434 data: 0.0013 max mem: 19788 +Test: [11200/21770] eta: 0:08:12 time: 0.0442 data: 0.0015 max mem: 19788 +Test: [11300/21770] eta: 0:08:08 time: 0.0439 data: 0.0014 max mem: 19788 +Test: [11400/21770] eta: 0:08:03 time: 0.0439 data: 0.0012 max mem: 19788 +Test: [11500/21770] eta: 0:07:58 time: 0.0513 data: 0.0016 max mem: 19788 +Test: [11600/21770] eta: 0:07:54 time: 0.0446 data: 0.0015 max mem: 19788 +Test: [11700/21770] eta: 0:07:49 time: 0.0450 data: 0.0015 max mem: 19788 +Test: [11800/21770] eta: 0:07:44 time: 0.0435 data: 0.0015 max mem: 19788 +Test: [11900/21770] eta: 0:07:40 time: 0.0453 data: 0.0015 max mem: 19788 +Test: [12000/21770] eta: 0:07:35 time: 0.0500 data: 0.0016 max mem: 19788 +Test: [12100/21770] eta: 0:07:30 time: 0.0481 data: 0.0017 max mem: 19788 +Test: [12200/21770] eta: 0:07:25 time: 0.0450 data: 0.0015 max mem: 19788 +Test: [12300/21770] eta: 0:07:21 time: 0.0450 data: 0.0015 max mem: 19788 +Test: [12400/21770] eta: 0:07:16 time: 0.0451 data: 0.0014 max mem: 19788 +Test: [12500/21770] eta: 0:07:12 time: 0.0482 data: 0.0016 max mem: 19788 +Test: [12600/21770] eta: 0:07:07 time: 0.0444 data: 0.0013 max mem: 19788 +Test: [12700/21770] eta: 0:07:02 time: 0.0509 data: 0.0015 max mem: 19788 +Test: [12800/21770] eta: 0:06:58 time: 0.0463 data: 0.0017 max mem: 19788 +Test: [12900/21770] eta: 0:06:53 time: 0.0506 data: 0.0017 max mem: 19788 +Test: [13000/21770] eta: 0:06:49 time: 0.0489 data: 0.0016 max mem: 19788 +Test: [13100/21770] eta: 0:06:44 time: 0.0453 data: 0.0015 max mem: 19788 +Test: [13200/21770] eta: 0:06:39 time: 0.0431 data: 0.0015 max mem: 19788 +Test: [13300/21770] eta: 0:06:35 time: 0.0526 data: 0.0018 max mem: 19788 +Test: [13400/21770] eta: 0:06:30 time: 0.0483 data: 0.0015 max mem: 19788 +Test: [13500/21770] eta: 0:06:26 time: 0.0457 data: 0.0014 max mem: 19788 +Test: [13600/21770] eta: 0:06:21 time: 0.0445 data: 0.0014 max mem: 19788 +Test: [13700/21770] eta: 0:06:16 time: 0.0528 data: 0.0018 max mem: 19788 +Test: [13800/21770] eta: 0:06:12 time: 0.0447 data: 0.0016 max mem: 19788 +Test: [13900/21770] eta: 0:06:07 time: 0.0435 data: 0.0015 max mem: 19788 +Test: [14000/21770] eta: 0:06:03 time: 0.0470 data: 0.0016 max mem: 19788 +Test: [14100/21770] eta: 0:05:58 time: 0.0517 data: 0.0016 max mem: 19788 +Test: [14200/21770] eta: 0:05:53 time: 0.0506 data: 0.0017 max mem: 19788 +Test: [14300/21770] eta: 0:05:49 time: 0.0510 data: 0.0018 max mem: 19788 +Test: [14400/21770] eta: 0:05:44 time: 0.0449 data: 0.0015 max mem: 19788 +Test: [14500/21770] eta: 0:05:40 time: 0.0503 data: 0.0016 max mem: 19788 +Test: [14600/21770] eta: 0:05:35 time: 0.0434 data: 0.0015 max mem: 19788 +Test: [14700/21770] eta: 0:05:30 time: 0.0459 data: 0.0014 max mem: 19788 +Test: [14800/21770] eta: 0:05:25 time: 0.0442 data: 0.0016 max mem: 19788 +Test: [14900/21770] eta: 0:05:21 time: 0.0510 data: 0.0018 max mem: 19788 +Test: [15000/21770] eta: 0:05:16 time: 0.0465 data: 0.0015 max mem: 19788 +Test: [15100/21770] eta: 0:05:11 time: 0.0507 data: 0.0018 max mem: 19788 +Test: [15200/21770] eta: 0:05:06 time: 0.0438 data: 0.0014 max mem: 19788 +Test: [15300/21770] eta: 0:05:02 time: 0.0489 data: 0.0017 max mem: 19788 +Test: [15400/21770] eta: 0:04:57 time: 0.0453 data: 0.0015 max mem: 19788 +Test: [15500/21770] eta: 0:04:52 time: 0.0443 data: 0.0016 max mem: 19788 +Test: [15600/21770] eta: 0:04:48 time: 0.0472 data: 0.0015 max mem: 19788 +Test: [15700/21770] eta: 0:04:43 time: 0.0459 data: 0.0016 max mem: 19788 +Test: [15800/21770] eta: 0:04:38 time: 0.0491 data: 0.0016 max mem: 19788 +Test: [15900/21770] eta: 0:04:34 time: 0.0444 data: 0.0014 max mem: 19788 +Test: [16000/21770] eta: 0:04:29 time: 0.0438 data: 0.0014 max mem: 19788 +Test: [16100/21770] eta: 0:04:24 time: 0.0438 data: 0.0014 max mem: 19788 +Test: [16200/21770] eta: 0:04:19 time: 0.0462 data: 0.0016 max mem: 19788 +Test: [16300/21770] eta: 0:04:15 time: 0.0495 data: 0.0017 max mem: 19788 +Test: [16400/21770] eta: 0:04:10 time: 0.0520 data: 0.0018 max mem: 19788 +Test: [16500/21770] eta: 0:04:06 time: 0.0445 data: 0.0015 max mem: 19788 +Test: [16600/21770] eta: 0:04:01 time: 0.0501 data: 0.0016 max mem: 19788 +Test: [16700/21770] eta: 0:03:56 time: 0.0438 data: 0.0013 max mem: 19788 +Test: [16800/21770] eta: 0:03:51 time: 0.0477 data: 0.0016 max mem: 19788 +Test: [16900/21770] eta: 0:03:47 time: 0.0437 data: 0.0014 max mem: 19788 +Test: [17000/21770] eta: 0:03:42 time: 0.0420 data: 0.0014 max mem: 19788 +Test: [17100/21770] eta: 0:03:37 time: 0.0513 data: 0.0018 max mem: 19788 +Test: [17200/21770] eta: 0:03:33 time: 0.0431 data: 0.0013 max mem: 19788 +Test: [17300/21770] eta: 0:03:28 time: 0.0419 data: 0.0015 max mem: 19788 +Test: [17400/21770] eta: 0:03:23 time: 0.0508 data: 0.0016 max mem: 19788 +Test: [17500/21770] eta: 0:03:19 time: 0.0493 data: 0.0016 max mem: 19788 +Test: [17600/21770] eta: 0:03:14 time: 0.0451 data: 0.0016 max mem: 19788 +Test: [17700/21770] eta: 0:03:09 time: 0.0492 data: 0.0016 max mem: 19788 +Test: [17800/21770] eta: 0:03:05 time: 0.0433 data: 0.0014 max mem: 19788 +Test: [17900/21770] eta: 0:03:00 time: 0.0432 data: 0.0014 max mem: 19788 +Test: [18000/21770] eta: 0:02:55 time: 0.0468 data: 0.0017 max mem: 19788 +Test: [18100/21770] eta: 0:02:51 time: 0.0425 data: 0.0014 max mem: 19788 +Test: [18200/21770] eta: 0:02:46 time: 0.0434 data: 0.0014 max mem: 19788 +Test: [18300/21770] eta: 0:02:41 time: 0.0425 data: 0.0013 max mem: 19788 +Test: [18400/21770] eta: 0:02:37 time: 0.0478 data: 0.0016 max mem: 19788 +Test: [18500/21770] eta: 0:02:32 time: 0.0446 data: 0.0014 max mem: 19788 +Test: [18600/21770] eta: 0:02:27 time: 0.0448 data: 0.0014 max mem: 19788 +Test: [18700/21770] eta: 0:02:23 time: 0.0430 data: 0.0016 max mem: 19788 +Test: [18800/21770] eta: 0:02:18 time: 0.0504 data: 0.0017 max mem: 19788 +Test: [18900/21770] eta: 0:02:13 time: 0.0491 data: 0.0016 max mem: 19788 +Test: [19000/21770] eta: 0:02:09 time: 0.0518 data: 0.0016 max mem: 19788 +Test: [19100/21770] eta: 0:02:04 time: 0.0487 data: 0.0017 max mem: 19788 +Test: [19200/21770] eta: 0:01:59 time: 0.0487 data: 0.0017 max mem: 19788 +Test: [19300/21770] eta: 0:01:55 time: 0.0476 data: 0.0016 max mem: 19788 +Test: [19400/21770] eta: 0:01:50 time: 0.0455 data: 0.0016 max mem: 19788 +Test: [19500/21770] eta: 0:01:45 time: 0.0430 data: 0.0013 max mem: 19788 +Test: [19600/21770] eta: 0:01:41 time: 0.0434 data: 0.0014 max mem: 19788 +Test: [19700/21770] eta: 0:01:36 time: 0.0439 data: 0.0015 max mem: 19788 +Test: [19800/21770] eta: 0:01:31 time: 0.0537 data: 0.0014 max mem: 19788 +Test: [19900/21770] eta: 0:01:27 time: 0.0525 data: 0.0018 max mem: 19788 +Test: [20000/21770] eta: 0:01:22 time: 0.0433 data: 0.0014 max mem: 19788 +Test: [20100/21770] eta: 0:01:17 time: 0.0448 data: 0.0014 max mem: 19788 +Test: [20200/21770] eta: 0:01:13 time: 0.0432 data: 0.0015 max mem: 19788 +Test: [20300/21770] eta: 0:01:08 time: 0.0435 data: 0.0013 max mem: 19788 +Test: [20400/21770] eta: 0:01:03 time: 0.0503 data: 0.0016 max mem: 19788 +Test: [20500/21770] eta: 0:00:59 time: 0.0516 data: 0.0016 max mem: 19788 +Test: [20600/21770] eta: 0:00:54 time: 0.0517 data: 0.0017 max mem: 19788 +Test: [20700/21770] eta: 0:00:49 time: 0.0439 data: 0.0015 max mem: 19788 +Test: [20800/21770] eta: 0:00:45 time: 0.0504 data: 0.0016 max mem: 19788 +Test: [20900/21770] eta: 0:00:40 time: 0.0434 data: 0.0015 max mem: 19788 +Test: [21000/21770] eta: 0:00:35 time: 0.0487 data: 0.0017 max mem: 19788 +Test: [21100/21770] eta: 0:00:31 time: 0.0516 data: 0.0017 max mem: 19788 +Test: [21200/21770] eta: 0:00:26 time: 0.0441 data: 0.0014 max mem: 19788 +Test: [21300/21770] eta: 0:00:21 time: 0.0449 data: 0.0014 max mem: 19788 +Test: [21400/21770] eta: 0:00:17 time: 0.0483 data: 0.0015 max mem: 19788 +Test: [21500/21770] eta: 0:00:12 time: 0.0444 data: 0.0014 max mem: 19788 +Test: [21600/21770] eta: 0:00:07 time: 0.0502 data: 0.0016 max mem: 19788 +Test: [21700/21770] eta: 0:00:03 time: 0.0690 data: 0.0031 max mem: 19788 +Test: Total time: 0:16:56 +Final results: +Mean IoU is 63.08 + + precision@0.5 = 69.98 + precision@0.6 = 63.52 + precision@0.7 = 56.20 + precision@0.8 = 45.23 + precision@0.9 = 22.16 + overall IoU = 63.10 + mean IoU = 63.08 + +Mean accuracy for one-to-zero sample is 77.61 + +Average object IoU 0.6308008154753453 +Overall IoU 63.101383209228516 +Epoch: [11] [ 0/2138] eta: 6:52:04 lr: 3.7434143955676645e-05 loss: 0.0909 (0.0909) time: 11.5644 data: 1.4540 max mem: 19788 +Epoch: [11] [ 10/2138] eta: 2:07:38 lr: 3.7428710010857814e-05 loss: 0.0359 (0.0444) time: 3.5989 data: 0.1342 max mem: 19788 +Epoch: [11] [ 20/2138] eta: 1:53:31 lr: 3.742327597838128e-05 loss: 0.0358 (0.0497) time: 2.7986 data: 0.0016 max mem: 19788 +Epoch: [11] [ 30/2138] eta: 1:48:19 lr: 3.741784185823149e-05 loss: 0.0427 (0.0479) time: 2.7993 data: 0.0016 max mem: 19788 +Epoch: [11] [ 40/2138] eta: 1:45:29 lr: 3.7412407650392866e-05 loss: 0.0443 (0.0470) time: 2.8078 data: 0.0023 max mem: 19788 +Epoch: [11] [ 50/2138] eta: 1:43:30 lr: 3.7406973354849866e-05 loss: 0.0408 (0.0458) time: 2.8060 data: 0.0022 max mem: 19788 +Epoch: [11] [ 60/2138] eta: 1:41:59 lr: 3.7401538971586894e-05 loss: 0.0368 (0.0452) time: 2.7979 data: 0.0020 max mem: 19788 +Epoch: [11] [ 70/2138] eta: 1:40:47 lr: 3.739610450058838e-05 loss: 0.0369 (0.0445) time: 2.7974 data: 0.0023 max mem: 19788 +Epoch: [11] [ 80/2138] eta: 1:39:49 lr: 3.739066994183875e-05 loss: 0.0399 (0.0441) time: 2.8041 data: 0.0026 max mem: 19788 +Epoch: [11] [ 90/2138] eta: 1:38:56 lr: 3.73852352953224e-05 loss: 0.0357 (0.0433) time: 2.8074 data: 0.0027 max mem: 19788 +Epoch: [11] [ 100/2138] eta: 1:38:12 lr: 3.7379800561023745e-05 loss: 0.0367 (0.0435) time: 2.8142 data: 0.0026 max mem: 19788 +Epoch: [11] [ 110/2138] eta: 1:37:28 lr: 3.737436573892718e-05 loss: 0.0397 (0.0446) time: 2.8173 data: 0.0025 max mem: 19788 +Epoch: [11] [ 120/2138] eta: 1:36:45 lr: 3.7368930829017115e-05 loss: 0.0361 (0.0441) time: 2.8028 data: 0.0024 max mem: 19788 +Epoch: [11] [ 130/2138] eta: 1:36:03 lr: 3.736349583127792e-05 loss: 0.0381 (0.0438) time: 2.7929 data: 0.0023 max mem: 19788 +Epoch: [11] [ 140/2138] eta: 1:35:24 lr: 3.735806074569399e-05 loss: 0.0381 (0.0439) time: 2.7948 data: 0.0023 max mem: 19788 +Epoch: [11] [ 150/2138] eta: 1:34:46 lr: 3.735262557224969e-05 loss: 0.0387 (0.0439) time: 2.7974 data: 0.0021 max mem: 19788 +Epoch: [11] [ 160/2138] eta: 1:34:10 lr: 3.734719031092942e-05 loss: 0.0358 (0.0435) time: 2.7995 data: 0.0023 max mem: 19788 +Epoch: [11] [ 170/2138] eta: 1:33:34 lr: 3.7341754961717545e-05 loss: 0.0358 (0.0435) time: 2.7953 data: 0.0025 max mem: 19788 +Epoch: [11] [ 180/2138] eta: 1:32:59 lr: 3.7336319524598406e-05 loss: 0.0407 (0.0436) time: 2.7924 data: 0.0026 max mem: 19788 +Epoch: [11] [ 190/2138] eta: 1:32:26 lr: 3.733088399955637e-05 loss: 0.0391 (0.0436) time: 2.8005 data: 0.0027 max mem: 19788 +Epoch: [11] [ 200/2138] eta: 1:31:55 lr: 3.732544838657581e-05 loss: 0.0388 (0.0434) time: 2.8101 data: 0.0027 max mem: 19788 +Epoch: [11] [ 210/2138] eta: 1:31:24 lr: 3.732001268564106e-05 loss: 0.0358 (0.0432) time: 2.8164 data: 0.0025 max mem: 19788 +Epoch: [11] [ 220/2138] eta: 1:30:53 lr: 3.731457689673645e-05 loss: 0.0339 (0.0432) time: 2.8164 data: 0.0025 max mem: 19788 +Epoch: [11] [ 230/2138] eta: 1:30:24 lr: 3.7309141019846325e-05 loss: 0.0400 (0.0431) time: 2.8255 data: 0.0027 max mem: 19788 +Epoch: [11] [ 240/2138] eta: 1:29:53 lr: 3.730370505495504e-05 loss: 0.0439 (0.0429) time: 2.8225 data: 0.0028 max mem: 19788 +Epoch: [11] [ 250/2138] eta: 1:29:21 lr: 3.729826900204688e-05 loss: 0.0378 (0.0427) time: 2.8022 data: 0.0026 max mem: 19788 +Epoch: [11] [ 260/2138] eta: 1:28:49 lr: 3.72928328611062e-05 loss: 0.0378 (0.0430) time: 2.7953 data: 0.0027 max mem: 19788 +Epoch: [11] [ 270/2138] eta: 1:28:18 lr: 3.72873966321173e-05 loss: 0.0370 (0.0428) time: 2.7975 data: 0.0024 max mem: 19788 +Epoch: [11] [ 280/2138] eta: 1:27:47 lr: 3.7281960315064486e-05 loss: 0.0376 (0.0428) time: 2.8006 data: 0.0021 max mem: 19788 +Epoch: [11] [ 290/2138] eta: 1:27:17 lr: 3.727652390993207e-05 loss: 0.0427 (0.0428) time: 2.8000 data: 0.0021 max mem: 19788 +Epoch: [11] [ 300/2138] eta: 1:26:46 lr: 3.727108741670435e-05 loss: 0.0427 (0.0428) time: 2.7956 data: 0.0020 max mem: 19788 +Epoch: [11] [ 310/2138] eta: 1:26:15 lr: 3.726565083536563e-05 loss: 0.0370 (0.0425) time: 2.7940 data: 0.0020 max mem: 19788 +Epoch: [11] [ 320/2138] eta: 1:25:46 lr: 3.726021416590019e-05 loss: 0.0305 (0.0423) time: 2.8036 data: 0.0024 max mem: 19788 +Epoch: [11] [ 330/2138] eta: 1:25:17 lr: 3.7254777408292315e-05 loss: 0.0325 (0.0422) time: 2.8138 data: 0.0026 max mem: 19788 +Epoch: [11] [ 340/2138] eta: 1:24:48 lr: 3.724934056252628e-05 loss: 0.0368 (0.0422) time: 2.8192 data: 0.0025 max mem: 19788 +Epoch: [11] [ 350/2138] eta: 1:24:19 lr: 3.724390362858636e-05 loss: 0.0338 (0.0421) time: 2.8181 data: 0.0026 max mem: 19788 +Epoch: [11] [ 360/2138] eta: 1:23:49 lr: 3.7238466606456826e-05 loss: 0.0367 (0.0421) time: 2.8102 data: 0.0027 max mem: 19788 +Epoch: [11] [ 370/2138] eta: 1:23:20 lr: 3.7233029496121936e-05 loss: 0.0375 (0.0419) time: 2.8094 data: 0.0027 max mem: 19788 +Epoch: [11] [ 380/2138] eta: 1:22:51 lr: 3.722759229756594e-05 loss: 0.0376 (0.0418) time: 2.8123 data: 0.0026 max mem: 19788 +Epoch: [11] [ 390/2138] eta: 1:22:22 lr: 3.7222155010773115e-05 loss: 0.0344 (0.0416) time: 2.8026 data: 0.0027 max mem: 19788 +Epoch: [11] [ 400/2138] eta: 1:21:52 lr: 3.721671763572768e-05 loss: 0.0360 (0.0420) time: 2.7923 data: 0.0028 max mem: 19788 +Epoch: [11] [ 410/2138] eta: 1:21:22 lr: 3.721128017241389e-05 loss: 0.0381 (0.0418) time: 2.7934 data: 0.0026 max mem: 19788 +Epoch: [11] [ 420/2138] eta: 1:20:53 lr: 3.720584262081597e-05 loss: 0.0353 (0.0417) time: 2.7980 data: 0.0026 max mem: 19788 +Epoch: [11] [ 430/2138] eta: 1:20:23 lr: 3.7200404980918154e-05 loss: 0.0353 (0.0417) time: 2.7984 data: 0.0028 max mem: 19788 +Epoch: [11] [ 440/2138] eta: 1:19:54 lr: 3.7194967252704686e-05 loss: 0.0333 (0.0416) time: 2.7962 data: 0.0029 max mem: 19788 +Epoch: [11] [ 450/2138] eta: 1:19:25 lr: 3.718952943615975e-05 loss: 0.0331 (0.0415) time: 2.7947 data: 0.0029 max mem: 19788 +Epoch: [11] [ 460/2138] eta: 1:18:56 lr: 3.718409153126758e-05 loss: 0.0344 (0.0415) time: 2.7954 data: 0.0026 max mem: 19788 +Epoch: [11] [ 470/2138] eta: 1:18:27 lr: 3.7178653538012385e-05 loss: 0.0384 (0.0414) time: 2.8042 data: 0.0023 max mem: 19788 +Epoch: [11] [ 480/2138] eta: 1:17:58 lr: 3.717321545637837e-05 loss: 0.0473 (0.0418) time: 2.8061 data: 0.0024 max mem: 19788 +Epoch: [11] [ 490/2138] eta: 1:17:29 lr: 3.716777728634972e-05 loss: 0.0413 (0.0418) time: 2.8019 data: 0.0027 max mem: 19788 +Epoch: [11] [ 500/2138] eta: 1:17:00 lr: 3.716233902791063e-05 loss: 0.0401 (0.0418) time: 2.7981 data: 0.0027 max mem: 19788 +Epoch: [11] [ 510/2138] eta: 1:16:31 lr: 3.7156900681045305e-05 loss: 0.0398 (0.0418) time: 2.7952 data: 0.0025 max mem: 19788 +Epoch: [11] [ 520/2138] eta: 1:16:02 lr: 3.715146224573791e-05 loss: 0.0377 (0.0417) time: 2.7920 data: 0.0024 max mem: 19788 +Epoch: [11] [ 530/2138] eta: 1:15:33 lr: 3.714602372197262e-05 loss: 0.0385 (0.0417) time: 2.7886 data: 0.0024 max mem: 19788 +Epoch: [11] [ 540/2138] eta: 1:15:04 lr: 3.7140585109733613e-05 loss: 0.0360 (0.0418) time: 2.7969 data: 0.0024 max mem: 19788 +Epoch: [11] [ 550/2138] eta: 1:14:35 lr: 3.713514640900506e-05 loss: 0.0360 (0.0418) time: 2.8023 data: 0.0025 max mem: 19788 +Epoch: [11] [ 560/2138] eta: 1:14:07 lr: 3.7129707619771104e-05 loss: 0.0399 (0.0418) time: 2.7976 data: 0.0025 max mem: 19788 +Epoch: [11] [ 570/2138] eta: 1:13:38 lr: 3.7124268742015904e-05 loss: 0.0395 (0.0417) time: 2.7934 data: 0.0023 max mem: 19788 +Epoch: [11] [ 580/2138] eta: 1:13:09 lr: 3.7118829775723616e-05 loss: 0.0322 (0.0418) time: 2.8007 data: 0.0022 max mem: 19788 +Epoch: [11] [ 590/2138] eta: 1:12:41 lr: 3.711339072087839e-05 loss: 0.0386 (0.0418) time: 2.8103 data: 0.0022 max mem: 19788 +Epoch: [11] [ 600/2138] eta: 1:12:13 lr: 3.7107951577464336e-05 loss: 0.0386 (0.0418) time: 2.8204 data: 0.0024 max mem: 19788 +Epoch: [11] [ 610/2138] eta: 1:11:45 lr: 3.710251234546562e-05 loss: 0.0355 (0.0417) time: 2.8171 data: 0.0028 max mem: 19788 +Epoch: [11] [ 620/2138] eta: 1:11:16 lr: 3.709707302486635e-05 loss: 0.0355 (0.0419) time: 2.7987 data: 0.0026 max mem: 19788 +Epoch: [11] [ 630/2138] eta: 1:10:47 lr: 3.709163361565066e-05 loss: 0.0397 (0.0419) time: 2.7969 data: 0.0023 max mem: 19788 +Epoch: [11] [ 640/2138] eta: 1:10:19 lr: 3.708619411780264e-05 loss: 0.0397 (0.0419) time: 2.7987 data: 0.0022 max mem: 19788 +Epoch: [11] [ 650/2138] eta: 1:09:50 lr: 3.708075453130643e-05 loss: 0.0358 (0.0418) time: 2.8041 data: 0.0023 max mem: 19788 +Epoch: [11] [ 660/2138] eta: 1:09:21 lr: 3.707531485614613e-05 loss: 0.0342 (0.0418) time: 2.8003 data: 0.0022 max mem: 19788 +Epoch: [11] [ 670/2138] eta: 1:08:53 lr: 3.7069875092305836e-05 loss: 0.0366 (0.0418) time: 2.7906 data: 0.0022 max mem: 19788 +Epoch: [11] [ 680/2138] eta: 1:08:24 lr: 3.706443523976964e-05 loss: 0.0307 (0.0417) time: 2.7949 data: 0.0021 max mem: 19788 +Epoch: [11] [ 690/2138] eta: 1:07:56 lr: 3.705899529852163e-05 loss: 0.0315 (0.0417) time: 2.8040 data: 0.0021 max mem: 19788 +Epoch: [11] [ 700/2138] eta: 1:07:28 lr: 3.70535552685459e-05 loss: 0.0327 (0.0416) time: 2.8061 data: 0.0024 max mem: 19788 +Epoch: [11] [ 710/2138] eta: 1:06:59 lr: 3.704811514982652e-05 loss: 0.0380 (0.0416) time: 2.8089 data: 0.0024 max mem: 19788 +Epoch: [11] [ 720/2138] eta: 1:06:31 lr: 3.704267494234756e-05 loss: 0.0395 (0.0415) time: 2.8064 data: 0.0023 max mem: 19788 +Epoch: [11] [ 730/2138] eta: 1:06:02 lr: 3.7037234646093095e-05 loss: 0.0367 (0.0415) time: 2.7975 data: 0.0024 max mem: 19788 +Epoch: [11] [ 740/2138] eta: 1:05:34 lr: 3.703179426104719e-05 loss: 0.0412 (0.0416) time: 2.7956 data: 0.0024 max mem: 19788 +Epoch: [11] [ 750/2138] eta: 1:05:05 lr: 3.702635378719389e-05 loss: 0.0383 (0.0416) time: 2.7929 data: 0.0022 max mem: 19788 +Epoch: [11] [ 760/2138] eta: 1:04:37 lr: 3.702091322451724e-05 loss: 0.0391 (0.0416) time: 2.7971 data: 0.0024 max mem: 19788 +Epoch: [11] [ 770/2138] eta: 1:04:09 lr: 3.701547257300132e-05 loss: 0.0366 (0.0415) time: 2.8008 data: 0.0024 max mem: 19788 +Epoch: [11] [ 780/2138] eta: 1:03:40 lr: 3.701003183263013e-05 loss: 0.0337 (0.0415) time: 2.7945 data: 0.0022 max mem: 19788 +Epoch: [11] [ 790/2138] eta: 1:03:12 lr: 3.7004591003387735e-05 loss: 0.0322 (0.0414) time: 2.7914 data: 0.0022 max mem: 19788 +Epoch: [11] [ 800/2138] eta: 1:02:43 lr: 3.699915008525814e-05 loss: 0.0365 (0.0416) time: 2.7987 data: 0.0022 max mem: 19788 +Epoch: [11] [ 810/2138] eta: 1:02:15 lr: 3.6993709078225386e-05 loss: 0.0412 (0.0415) time: 2.8046 data: 0.0023 max mem: 19788 +Epoch: [11] [ 820/2138] eta: 1:01:47 lr: 3.698826798227349e-05 loss: 0.0386 (0.0416) time: 2.8166 data: 0.0023 max mem: 19788 +Epoch: [11] [ 830/2138] eta: 1:01:19 lr: 3.6982826797386454e-05 loss: 0.0368 (0.0415) time: 2.8178 data: 0.0024 max mem: 19788 +Epoch: [11] [ 840/2138] eta: 1:00:50 lr: 3.697738552354829e-05 loss: 0.0321 (0.0415) time: 2.7995 data: 0.0023 max mem: 19788 +Epoch: [11] [ 850/2138] eta: 1:00:22 lr: 3.6971944160743e-05 loss: 0.0322 (0.0415) time: 2.7942 data: 0.0024 max mem: 19788 +Epoch: [11] [ 860/2138] eta: 0:59:54 lr: 3.696650270895459e-05 loss: 0.0319 (0.0414) time: 2.7955 data: 0.0025 max mem: 19788 +Epoch: [11] [ 870/2138] eta: 0:59:25 lr: 3.6961061168167036e-05 loss: 0.0351 (0.0415) time: 2.7961 data: 0.0023 max mem: 19788 +Epoch: [11] [ 880/2138] eta: 0:58:57 lr: 3.6955619538364323e-05 loss: 0.0368 (0.0414) time: 2.7996 data: 0.0020 max mem: 19788 +Epoch: [11] [ 890/2138] eta: 0:58:29 lr: 3.695017781953044e-05 loss: 0.0368 (0.0414) time: 2.7990 data: 0.0020 max mem: 19788 +Epoch: [11] [ 900/2138] eta: 0:58:00 lr: 3.694473601164936e-05 loss: 0.0396 (0.0414) time: 2.7973 data: 0.0020 max mem: 19788 +Epoch: [11] [ 910/2138] eta: 0:57:32 lr: 3.693929411470505e-05 loss: 0.0363 (0.0413) time: 2.8000 data: 0.0021 max mem: 19788 +Epoch: [11] [ 920/2138] eta: 0:57:04 lr: 3.6933852128681467e-05 loss: 0.0310 (0.0412) time: 2.8101 data: 0.0022 max mem: 19788 +Epoch: [11] [ 930/2138] eta: 0:56:36 lr: 3.692841005356259e-05 loss: 0.0372 (0.0413) time: 2.8226 data: 0.0026 max mem: 19788 +Epoch: [11] [ 940/2138] eta: 0:56:08 lr: 3.6922967889332345e-05 loss: 0.0378 (0.0413) time: 2.8131 data: 0.0027 max mem: 19788 +Epoch: [11] [ 950/2138] eta: 0:55:40 lr: 3.691752563597468e-05 loss: 0.0341 (0.0413) time: 2.7984 data: 0.0025 max mem: 19788 +Epoch: [11] [ 960/2138] eta: 0:55:11 lr: 3.6912083293473554e-05 loss: 0.0365 (0.0413) time: 2.7967 data: 0.0023 max mem: 19788 +Epoch: [11] [ 970/2138] eta: 0:54:43 lr: 3.69066408618129e-05 loss: 0.0365 (0.0414) time: 2.7961 data: 0.0020 max mem: 19788 +Epoch: [11] [ 980/2138] eta: 0:54:15 lr: 3.6901198340976636e-05 loss: 0.0358 (0.0414) time: 2.7996 data: 0.0023 max mem: 19788 +Epoch: [11] [ 990/2138] eta: 0:53:46 lr: 3.689575573094869e-05 loss: 0.0341 (0.0413) time: 2.7953 data: 0.0024 max mem: 19788 +Epoch: [11] [1000/2138] eta: 0:53:18 lr: 3.689031303171299e-05 loss: 0.0316 (0.0412) time: 2.7873 data: 0.0021 max mem: 19788 +Epoch: [11] [1010/2138] eta: 0:52:50 lr: 3.6884870243253444e-05 loss: 0.0322 (0.0412) time: 2.7937 data: 0.0021 max mem: 19788 +Epoch: [11] [1020/2138] eta: 0:52:22 lr: 3.687942736555396e-05 loss: 0.0384 (0.0412) time: 2.8043 data: 0.0025 max mem: 19788 +Epoch: [11] [1030/2138] eta: 0:51:54 lr: 3.6873984398598434e-05 loss: 0.0346 (0.0412) time: 2.8095 data: 0.0030 max mem: 19788 +Epoch: [11] [1040/2138] eta: 0:51:26 lr: 3.6868541342370765e-05 loss: 0.0393 (0.0412) time: 2.8114 data: 0.0030 max mem: 19788 +Epoch: [11] [1050/2138] eta: 0:50:57 lr: 3.686309819685486e-05 loss: 0.0393 (0.0412) time: 2.8005 data: 0.0027 max mem: 19788 +Epoch: [11] [1060/2138] eta: 0:50:29 lr: 3.685765496203459e-05 loss: 0.0358 (0.0412) time: 2.7950 data: 0.0023 max mem: 19788 +Epoch: [11] [1070/2138] eta: 0:50:01 lr: 3.685221163789383e-05 loss: 0.0352 (0.0412) time: 2.8066 data: 0.0023 max mem: 19788 +Epoch: [11] [1080/2138] eta: 0:49:33 lr: 3.684676822441646e-05 loss: 0.0341 (0.0411) time: 2.8075 data: 0.0022 max mem: 19788 +Epoch: [11] [1090/2138] eta: 0:49:05 lr: 3.684132472158636e-05 loss: 0.0363 (0.0411) time: 2.8000 data: 0.0022 max mem: 19788 +Epoch: [11] [1100/2138] eta: 0:48:36 lr: 3.6835881129387385e-05 loss: 0.0397 (0.0411) time: 2.7979 data: 0.0024 max mem: 19788 +Epoch: [11] [1110/2138] eta: 0:48:08 lr: 3.683043744780339e-05 loss: 0.0405 (0.0411) time: 2.8052 data: 0.0026 max mem: 19788 +Epoch: [11] [1120/2138] eta: 0:47:40 lr: 3.682499367681823e-05 loss: 0.0370 (0.0412) time: 2.8114 data: 0.0025 max mem: 19788 +Epoch: [11] [1130/2138] eta: 0:47:12 lr: 3.681954981641575e-05 loss: 0.0375 (0.0413) time: 2.8096 data: 0.0023 max mem: 19788 +Epoch: [11] [1140/2138] eta: 0:46:44 lr: 3.681410586657981e-05 loss: 0.0451 (0.0414) time: 2.8080 data: 0.0024 max mem: 19788 +Epoch: [11] [1150/2138] eta: 0:46:16 lr: 3.680866182729421e-05 loss: 0.0373 (0.0414) time: 2.8003 data: 0.0027 max mem: 19788 +Epoch: [11] [1160/2138] eta: 0:45:47 lr: 3.6803217698542807e-05 loss: 0.0349 (0.0413) time: 2.7927 data: 0.0028 max mem: 19788 +Epoch: [11] [1170/2138] eta: 0:45:19 lr: 3.6797773480309424e-05 loss: 0.0349 (0.0413) time: 2.7929 data: 0.0023 max mem: 19788 +Epoch: [11] [1180/2138] eta: 0:44:51 lr: 3.679232917257786e-05 loss: 0.0362 (0.0414) time: 2.8039 data: 0.0024 max mem: 19788 +Epoch: [11] [1190/2138] eta: 0:44:23 lr: 3.678688477533195e-05 loss: 0.0360 (0.0413) time: 2.8078 data: 0.0027 max mem: 19788 +Epoch: [11] [1200/2138] eta: 0:43:55 lr: 3.678144028855549e-05 loss: 0.0313 (0.0413) time: 2.8011 data: 0.0026 max mem: 19788 +Epoch: [11] [1210/2138] eta: 0:43:27 lr: 3.677599571223229e-05 loss: 0.0418 (0.0413) time: 2.7988 data: 0.0024 max mem: 19788 +Epoch: [11] [1220/2138] eta: 0:42:58 lr: 3.677055104634614e-05 loss: 0.0422 (0.0413) time: 2.7910 data: 0.0021 max mem: 19788 +Epoch: [11] [1230/2138] eta: 0:42:30 lr: 3.676510629088083e-05 loss: 0.0376 (0.0413) time: 2.7989 data: 0.0021 max mem: 19788 +Epoch: [11] [1240/2138] eta: 0:42:02 lr: 3.675966144582016e-05 loss: 0.0359 (0.0413) time: 2.8093 data: 0.0022 max mem: 19788 +Epoch: [11] [1250/2138] eta: 0:41:34 lr: 3.675421651114789e-05 loss: 0.0351 (0.0413) time: 2.8091 data: 0.0027 max mem: 19788 +Epoch: [11] [1260/2138] eta: 0:41:06 lr: 3.674877148684781e-05 loss: 0.0376 (0.0413) time: 2.8108 data: 0.0028 max mem: 19788 +Epoch: [11] [1270/2138] eta: 0:40:38 lr: 3.6743326372903675e-05 loss: 0.0372 (0.0413) time: 2.8159 data: 0.0025 max mem: 19788 +Epoch: [11] [1280/2138] eta: 0:40:10 lr: 3.673788116929926e-05 loss: 0.0335 (0.0413) time: 2.8082 data: 0.0021 max mem: 19788 +Epoch: [11] [1290/2138] eta: 0:39:42 lr: 3.673243587601831e-05 loss: 0.0338 (0.0413) time: 2.7914 data: 0.0019 max mem: 19788 +Epoch: [11] [1300/2138] eta: 0:39:13 lr: 3.6726990493044585e-05 loss: 0.0380 (0.0412) time: 2.7917 data: 0.0021 max mem: 19788 +Epoch: [11] [1310/2138] eta: 0:38:45 lr: 3.672154502036183e-05 loss: 0.0320 (0.0412) time: 2.7979 data: 0.0024 max mem: 19788 +Epoch: [11] [1320/2138] eta: 0:38:17 lr: 3.6716099457953794e-05 loss: 0.0404 (0.0413) time: 2.8065 data: 0.0024 max mem: 19788 +Epoch: [11] [1330/2138] eta: 0:37:49 lr: 3.671065380580419e-05 loss: 0.0402 (0.0413) time: 2.8022 data: 0.0021 max mem: 19788 +Epoch: [11] [1340/2138] eta: 0:37:21 lr: 3.670520806389677e-05 loss: 0.0399 (0.0414) time: 2.7994 data: 0.0021 max mem: 19788 +Epoch: [11] [1350/2138] eta: 0:36:53 lr: 3.669976223221524e-05 loss: 0.0458 (0.0415) time: 2.7968 data: 0.0023 max mem: 19788 +Epoch: [11] [1360/2138] eta: 0:36:25 lr: 3.669431631074333e-05 loss: 0.0438 (0.0414) time: 2.7992 data: 0.0022 max mem: 19788 +Epoch: [11] [1370/2138] eta: 0:35:57 lr: 3.668887029946475e-05 loss: 0.0388 (0.0415) time: 2.8125 data: 0.0020 max mem: 19788 +Epoch: [11] [1380/2138] eta: 0:35:28 lr: 3.6683424198363204e-05 loss: 0.0421 (0.0415) time: 2.8144 data: 0.0020 max mem: 19788 +Epoch: [11] [1390/2138] eta: 0:35:00 lr: 3.6677978007422384e-05 loss: 0.0381 (0.0414) time: 2.8131 data: 0.0021 max mem: 19788 +Epoch: [11] [1400/2138] eta: 0:34:32 lr: 3.667253172662601e-05 loss: 0.0363 (0.0414) time: 2.8190 data: 0.0023 max mem: 19788 +Epoch: [11] [1410/2138] eta: 0:34:04 lr: 3.666708535595775e-05 loss: 0.0369 (0.0414) time: 2.8093 data: 0.0025 max mem: 19788 +Epoch: [11] [1420/2138] eta: 0:33:36 lr: 3.666163889540129e-05 loss: 0.0349 (0.0414) time: 2.7922 data: 0.0027 max mem: 19788 +Epoch: [11] [1430/2138] eta: 0:33:08 lr: 3.665619234494032e-05 loss: 0.0375 (0.0414) time: 2.7913 data: 0.0027 max mem: 19788 +Epoch: [11] [1440/2138] eta: 0:32:40 lr: 3.6650745704558496e-05 loss: 0.0365 (0.0414) time: 2.7922 data: 0.0023 max mem: 19788 +Epoch: [11] [1450/2138] eta: 0:32:12 lr: 3.664529897423951e-05 loss: 0.0341 (0.0414) time: 2.7949 data: 0.0020 max mem: 19788 +Epoch: [11] [1460/2138] eta: 0:31:43 lr: 3.6639852153967e-05 loss: 0.0341 (0.0414) time: 2.7927 data: 0.0020 max mem: 19788 +Epoch: [11] [1470/2138] eta: 0:31:15 lr: 3.6634405243724626e-05 loss: 0.0348 (0.0414) time: 2.7939 data: 0.0021 max mem: 19788 +Epoch: [11] [1480/2138] eta: 0:30:47 lr: 3.6628958243496056e-05 loss: 0.0368 (0.0414) time: 2.8005 data: 0.0022 max mem: 19788 +Epoch: [11] [1490/2138] eta: 0:30:19 lr: 3.662351115326491e-05 loss: 0.0400 (0.0414) time: 2.7955 data: 0.0021 max mem: 19788 +Epoch: [11] [1500/2138] eta: 0:29:51 lr: 3.6618063973014834e-05 loss: 0.0400 (0.0414) time: 2.7899 data: 0.0022 max mem: 19788 +Epoch: [11] [1510/2138] eta: 0:29:23 lr: 3.6612616702729466e-05 loss: 0.0354 (0.0414) time: 2.7923 data: 0.0027 max mem: 19788 +Epoch: [11] [1520/2138] eta: 0:28:55 lr: 3.660716934239244e-05 loss: 0.0336 (0.0414) time: 2.7937 data: 0.0027 max mem: 19788 +Epoch: [11] [1530/2138] eta: 0:28:26 lr: 3.660172189198736e-05 loss: 0.0336 (0.0413) time: 2.7954 data: 0.0026 max mem: 19788 +Epoch: [11] [1540/2138] eta: 0:27:58 lr: 3.659627435149785e-05 loss: 0.0341 (0.0413) time: 2.7924 data: 0.0025 max mem: 19788 +Epoch: [11] [1550/2138] eta: 0:27:30 lr: 3.659082672090754e-05 loss: 0.0367 (0.0413) time: 2.7957 data: 0.0024 max mem: 19788 +Epoch: [11] [1560/2138] eta: 0:27:02 lr: 3.65853790002e-05 loss: 0.0371 (0.0413) time: 2.8024 data: 0.0023 max mem: 19788 +Epoch: [11] [1570/2138] eta: 0:26:34 lr: 3.6579931189358854e-05 loss: 0.0378 (0.0413) time: 2.8006 data: 0.0021 max mem: 19788 +Epoch: [11] [1580/2138] eta: 0:26:06 lr: 3.657448328836768e-05 loss: 0.0378 (0.0413) time: 2.8027 data: 0.0024 max mem: 19788 +Epoch: [11] [1590/2138] eta: 0:25:38 lr: 3.6569035297210076e-05 loss: 0.0345 (0.0412) time: 2.8111 data: 0.0026 max mem: 19788 +Epoch: [11] [1600/2138] eta: 0:25:10 lr: 3.656358721586962e-05 loss: 0.0414 (0.0413) time: 2.8121 data: 0.0026 max mem: 19788 +Epoch: [11] [1610/2138] eta: 0:24:42 lr: 3.655813904432989e-05 loss: 0.0508 (0.0413) time: 2.8051 data: 0.0025 max mem: 19788 +Epoch: [11] [1620/2138] eta: 0:24:14 lr: 3.6552690782574444e-05 loss: 0.0330 (0.0413) time: 2.8027 data: 0.0025 max mem: 19788 +Epoch: [11] [1630/2138] eta: 0:23:46 lr: 3.6547242430586864e-05 loss: 0.0326 (0.0412) time: 2.7990 data: 0.0025 max mem: 19788 +Epoch: [11] [1640/2138] eta: 0:23:18 lr: 3.654179398835071e-05 loss: 0.0368 (0.0412) time: 2.8864 data: 0.0027 max mem: 19788 +Epoch: [11] [1650/2138] eta: 0:22:51 lr: 3.653634545584951e-05 loss: 0.0408 (0.0413) time: 3.0473 data: 0.0029 max mem: 19788 +Epoch: [11] [1660/2138] eta: 0:22:24 lr: 3.653089683306684e-05 loss: 0.0368 (0.0413) time: 3.2120 data: 0.0026 max mem: 19788 +Epoch: [11] [1670/2138] eta: 0:21:57 lr: 3.6525448119986234e-05 loss: 0.0329 (0.0412) time: 3.2623 data: 0.0027 max mem: 19788 +Epoch: [11] [1680/2138] eta: 0:21:30 lr: 3.651999931659122e-05 loss: 0.0339 (0.0412) time: 3.1683 data: 0.0028 max mem: 19788 +Epoch: [11] [1690/2138] eta: 0:21:03 lr: 3.6514550422865337e-05 loss: 0.0341 (0.0413) time: 3.1636 data: 0.0024 max mem: 19788 +Epoch: [11] [1700/2138] eta: 0:20:36 lr: 3.650910143879209e-05 loss: 0.0322 (0.0413) time: 3.2115 data: 0.0023 max mem: 19788 +Epoch: [11] [1710/2138] eta: 0:20:08 lr: 3.6503652364355033e-05 loss: 0.0355 (0.0413) time: 3.2066 data: 0.0024 max mem: 19788 +Epoch: [11] [1720/2138] eta: 0:19:41 lr: 3.649820319953765e-05 loss: 0.0381 (0.0413) time: 3.1331 data: 0.0023 max mem: 19788 +Epoch: [11] [1730/2138] eta: 0:19:13 lr: 3.649275394432346e-05 loss: 0.0371 (0.0413) time: 3.1376 data: 0.0022 max mem: 19788 +Epoch: [11] [1740/2138] eta: 0:18:46 lr: 3.648730459869596e-05 loss: 0.0362 (0.0412) time: 3.2596 data: 0.0024 max mem: 19788 +Epoch: [11] [1750/2138] eta: 0:18:18 lr: 3.648185516263866e-05 loss: 0.0324 (0.0412) time: 3.2084 data: 0.0027 max mem: 19788 +Epoch: [11] [1760/2138] eta: 0:17:51 lr: 3.647640563613503e-05 loss: 0.0381 (0.0412) time: 3.1428 data: 0.0029 max mem: 19788 +Epoch: [11] [1770/2138] eta: 0:17:23 lr: 3.6470956019168555e-05 loss: 0.0344 (0.0412) time: 3.1787 data: 0.0029 max mem: 19788 +Epoch: [11] [1780/2138] eta: 0:16:55 lr: 3.6465506311722736e-05 loss: 0.0315 (0.0411) time: 3.1574 data: 0.0025 max mem: 19788 +Epoch: [11] [1790/2138] eta: 0:16:28 lr: 3.646005651378103e-05 loss: 0.0326 (0.0412) time: 3.1479 data: 0.0022 max mem: 19788 +Epoch: [11] [1800/2138] eta: 0:16:00 lr: 3.645460662532689e-05 loss: 0.0416 (0.0412) time: 3.2611 data: 0.0023 max mem: 19788 +Epoch: [11] [1810/2138] eta: 0:15:32 lr: 3.64491566463438e-05 loss: 0.0407 (0.0411) time: 3.2331 data: 0.0025 max mem: 19788 +Epoch: [11] [1820/2138] eta: 0:15:04 lr: 3.6443706576815215e-05 loss: 0.0344 (0.0411) time: 3.1517 data: 0.0029 max mem: 19788 +Epoch: [11] [1830/2138] eta: 0:14:37 lr: 3.643825641672458e-05 loss: 0.0312 (0.0411) time: 3.3471 data: 0.0028 max mem: 19788 +Epoch: [11] [1840/2138] eta: 0:14:09 lr: 3.643280616605533e-05 loss: 0.0366 (0.0411) time: 3.2937 data: 0.0024 max mem: 19788 +Epoch: [11] [1850/2138] eta: 0:13:41 lr: 3.642735582479091e-05 loss: 0.0386 (0.0411) time: 3.0820 data: 0.0024 max mem: 19788 +Epoch: [11] [1860/2138] eta: 0:13:13 lr: 3.6421905392914764e-05 loss: 0.0373 (0.0410) time: 3.1247 data: 0.0023 max mem: 19788 +Epoch: [11] [1870/2138] eta: 0:12:45 lr: 3.64164548704103e-05 loss: 0.0370 (0.0411) time: 3.2348 data: 0.0022 max mem: 19788 +Epoch: [11] [1880/2138] eta: 0:12:17 lr: 3.641100425726095e-05 loss: 0.0293 (0.0410) time: 3.4712 data: 0.0022 max mem: 19788 +Epoch: [11] [1890/2138] eta: 0:11:50 lr: 3.640555355345011e-05 loss: 0.0283 (0.0410) time: 3.6115 data: 0.0023 max mem: 19788 +Epoch: [11] [1900/2138] eta: 0:11:22 lr: 3.6400102758961215e-05 loss: 0.0329 (0.0410) time: 3.5559 data: 0.0025 max mem: 19788 +Epoch: [11] [1910/2138] eta: 0:10:54 lr: 3.639465187377767e-05 loss: 0.0345 (0.0410) time: 3.3510 data: 0.0026 max mem: 19788 +Epoch: [11] [1920/2138] eta: 0:10:26 lr: 3.638920089788285e-05 loss: 0.0391 (0.0410) time: 3.3795 data: 0.0025 max mem: 19788 +Epoch: [11] [1930/2138] eta: 0:09:57 lr: 3.638374983126015e-05 loss: 0.0409 (0.0410) time: 3.4272 data: 0.0025 max mem: 19788 +Epoch: [11] [1940/2138] eta: 0:09:29 lr: 3.6378298673892974e-05 loss: 0.0385 (0.0410) time: 3.3869 data: 0.0026 max mem: 19788 +Epoch: [11] [1950/2138] eta: 0:09:01 lr: 3.6372847425764696e-05 loss: 0.0378 (0.0410) time: 3.3129 data: 0.0026 max mem: 19788 +Epoch: [11] [1960/2138] eta: 0:08:33 lr: 3.636739608685868e-05 loss: 0.0344 (0.0409) time: 3.2850 data: 0.0026 max mem: 19788 +Epoch: [11] [1970/2138] eta: 0:08:04 lr: 3.6361944657158297e-05 loss: 0.0342 (0.0409) time: 3.3078 data: 0.0025 max mem: 19788 +Epoch: [11] [1980/2138] eta: 0:07:36 lr: 3.6356493136646924e-05 loss: 0.0342 (0.0409) time: 3.2774 data: 0.0026 max mem: 19788 +Epoch: [11] [1990/2138] eta: 0:07:07 lr: 3.63510415253079e-05 loss: 0.0344 (0.0409) time: 3.4400 data: 0.0025 max mem: 19788 +Epoch: [11] [2000/2138] eta: 0:06:38 lr: 3.634558982312459e-05 loss: 0.0344 (0.0409) time: 3.3588 data: 0.0024 max mem: 19788 +Epoch: [11] [2010/2138] eta: 0:06:10 lr: 3.6340138030080334e-05 loss: 0.0337 (0.0409) time: 3.2313 data: 0.0024 max mem: 19788 +Epoch: [11] [2020/2138] eta: 0:05:41 lr: 3.633468614615847e-05 loss: 0.0352 (0.0409) time: 3.1856 data: 0.0026 max mem: 19788 +Epoch: [11] [2030/2138] eta: 0:05:12 lr: 3.6329234171342335e-05 loss: 0.0348 (0.0409) time: 3.1652 data: 0.0028 max mem: 19788 +Epoch: [11] [2040/2138] eta: 0:04:43 lr: 3.632378210561525e-05 loss: 0.0330 (0.0408) time: 3.1710 data: 0.0025 max mem: 19788 +Epoch: [11] [2050/2138] eta: 0:04:15 lr: 3.631832994896054e-05 loss: 0.0330 (0.0408) time: 3.1529 data: 0.0023 max mem: 19788 +Epoch: [11] [2060/2138] eta: 0:03:46 lr: 3.631287770136153e-05 loss: 0.0369 (0.0409) time: 3.1562 data: 0.0024 max mem: 19788 +Epoch: [11] [2070/2138] eta: 0:03:17 lr: 3.6307425362801524e-05 loss: 0.0360 (0.0408) time: 3.1647 data: 0.0027 max mem: 19788 +Epoch: [11] [2080/2138] eta: 0:02:48 lr: 3.630197293326382e-05 loss: 0.0339 (0.0408) time: 3.1473 data: 0.0027 max mem: 19788 +Epoch: [11] [2090/2138] eta: 0:02:19 lr: 3.629652041273172e-05 loss: 0.0359 (0.0408) time: 3.1996 data: 0.0027 max mem: 19788 +Epoch: [11] [2100/2138] eta: 0:01:50 lr: 3.629106780118853e-05 loss: 0.0347 (0.0408) time: 3.2277 data: 0.0029 max mem: 19788 +Epoch: [11] [2110/2138] eta: 0:01:21 lr: 3.6285615098617517e-05 loss: 0.0367 (0.0408) time: 3.1342 data: 0.0028 max mem: 19788 +Epoch: [11] [2120/2138] eta: 0:00:52 lr: 3.628016230500197e-05 loss: 0.0425 (0.0409) time: 3.1558 data: 0.0027 max mem: 19788 +Epoch: [11] [2130/2138] eta: 0:00:23 lr: 3.627470942032517e-05 loss: 0.0428 (0.0409) time: 3.2603 data: 0.0025 max mem: 19788 +Epoch: [11] Total time: 1:43:42 +Test: [ 0/21770] eta: 12:05:18 time: 1.9990 data: 1.9406 max mem: 19788 +Test: [ 100/21770] eta: 0:23:32 time: 0.0441 data: 0.0015 max mem: 19788 +Test: [ 200/21770] eta: 0:19:46 time: 0.0449 data: 0.0014 max mem: 19788 +Test: [ 300/21770] eta: 0:18:46 time: 0.0538 data: 0.0018 max mem: 19788 +Test: [ 400/21770] eta: 0:18:43 time: 0.0524 data: 0.0019 max mem: 19788 +Test: [ 500/21770] eta: 0:18:38 time: 0.0489 data: 0.0015 max mem: 19788 +Test: [ 600/21770] eta: 0:18:10 time: 0.0475 data: 0.0016 max mem: 19788 +Test: [ 700/21770] eta: 0:17:57 time: 0.0564 data: 0.0018 max mem: 19788 +Test: [ 800/21770] eta: 0:17:46 time: 0.0516 data: 0.0015 max mem: 19788 +Test: [ 900/21770] eta: 0:17:26 time: 0.0448 data: 0.0015 max mem: 19788 +Test: [ 1000/21770] eta: 0:17:26 time: 0.0537 data: 0.0018 max mem: 19788 +Test: [ 1100/21770] eta: 0:17:22 time: 0.0463 data: 0.0016 max mem: 19788 +Test: [ 1200/21770] eta: 0:17:07 time: 0.0440 data: 0.0014 max mem: 19788 +Test: [ 1300/21770] eta: 0:16:55 time: 0.0444 data: 0.0016 max mem: 19788 +Test: [ 1400/21770] eta: 0:16:46 time: 0.0444 data: 0.0015 max mem: 19788 +Test: [ 1500/21770] eta: 0:16:39 time: 0.0537 data: 0.0019 max mem: 19788 +Test: [ 1600/21770] eta: 0:16:38 time: 0.0522 data: 0.0018 max mem: 19788 +Test: [ 1700/21770] eta: 0:16:27 time: 0.0440 data: 0.0014 max mem: 19788 +Test: [ 1800/21770] eta: 0:16:23 time: 0.0542 data: 0.0019 max mem: 19788 +Test: [ 1900/21770] eta: 0:16:15 time: 0.0441 data: 0.0014 max mem: 19788 +Test: [ 2000/21770] eta: 0:16:08 time: 0.0485 data: 0.0016 max mem: 19788 +Test: [ 2100/21770] eta: 0:16:00 time: 0.0444 data: 0.0015 max mem: 19788 +Test: [ 2200/21770] eta: 0:15:52 time: 0.0448 data: 0.0015 max mem: 19788 +Test: [ 2300/21770] eta: 0:15:50 time: 0.0531 data: 0.0018 max mem: 19788 +Test: [ 2400/21770] eta: 0:15:49 time: 0.0535 data: 0.0018 max mem: 19788 +Test: [ 2500/21770] eta: 0:15:45 time: 0.0436 data: 0.0015 max mem: 19788 +Test: [ 2600/21770] eta: 0:15:38 time: 0.0450 data: 0.0016 max mem: 19788 +Test: [ 2700/21770] eta: 0:15:33 time: 0.0460 data: 0.0017 max mem: 19788 +Test: [ 2800/21770] eta: 0:15:31 time: 0.0524 data: 0.0018 max mem: 19788 +Test: [ 2900/21770] eta: 0:15:25 time: 0.0459 data: 0.0014 max mem: 19788 +Test: [ 3000/21770] eta: 0:15:23 time: 0.0545 data: 0.0021 max mem: 19788 +Test: [ 3100/21770] eta: 0:15:17 time: 0.0501 data: 0.0017 max mem: 19788 +Test: [ 3200/21770] eta: 0:15:12 time: 0.0498 data: 0.0017 max mem: 19788 +Test: [ 3300/21770] eta: 0:15:07 time: 0.0473 data: 0.0016 max mem: 19788 +Test: [ 3400/21770] eta: 0:15:03 time: 0.0500 data: 0.0016 max mem: 19788 +Test: [ 3500/21770] eta: 0:14:57 time: 0.0482 data: 0.0016 max mem: 19788 +Test: [ 3600/21770] eta: 0:14:51 time: 0.0482 data: 0.0016 max mem: 19788 +Test: [ 3700/21770] eta: 0:14:45 time: 0.0454 data: 0.0016 max mem: 19788 +Test: [ 3800/21770] eta: 0:14:41 time: 0.0494 data: 0.0017 max mem: 19788 +Test: [ 3900/21770] eta: 0:14:36 time: 0.0482 data: 0.0017 max mem: 19788 +Test: [ 4000/21770] eta: 0:14:31 time: 0.0448 data: 0.0016 max mem: 19788 +Test: [ 4100/21770] eta: 0:14:28 time: 0.0540 data: 0.0019 max mem: 19788 +Test: [ 4200/21770] eta: 0:14:24 time: 0.0465 data: 0.0015 max mem: 19788 +Test: [ 4300/21770] eta: 0:14:19 time: 0.0450 data: 0.0016 max mem: 19788 +Test: [ 4400/21770] eta: 0:14:13 time: 0.0480 data: 0.0015 max mem: 19788 +Test: [ 4500/21770] eta: 0:14:07 time: 0.0433 data: 0.0015 max mem: 19788 +Test: [ 4600/21770] eta: 0:14:02 time: 0.0530 data: 0.0016 max mem: 19788 +Test: [ 4700/21770] eta: 0:13:57 time: 0.0515 data: 0.0019 max mem: 19788 +Test: [ 4800/21770] eta: 0:13:52 time: 0.0489 data: 0.0016 max mem: 19788 +Test: [ 4900/21770] eta: 0:13:47 time: 0.0499 data: 0.0017 max mem: 19788 +Test: [ 5000/21770] eta: 0:13:42 time: 0.0447 data: 0.0016 max mem: 19788 +Test: [ 5100/21770] eta: 0:13:37 time: 0.0449 data: 0.0015 max mem: 19788 +Test: [ 5200/21770] eta: 0:13:34 time: 0.0525 data: 0.0018 max mem: 19788 +Test: [ 5300/21770] eta: 0:13:29 time: 0.0522 data: 0.0017 max mem: 19788 +Test: [ 5400/21770] eta: 0:13:25 time: 0.0547 data: 0.0019 max mem: 19788 +Test: [ 5500/21770] eta: 0:13:21 time: 0.0464 data: 0.0018 max mem: 19788 +Test: [ 5600/21770] eta: 0:13:16 time: 0.0448 data: 0.0016 max mem: 19788 +Test: [ 5700/21770] eta: 0:13:11 time: 0.0484 data: 0.0016 max mem: 19788 +Test: [ 5800/21770] eta: 0:13:06 time: 0.0518 data: 0.0019 max mem: 19788 +Test: [ 5900/21770] eta: 0:13:01 time: 0.0432 data: 0.0015 max mem: 19788 +Test: [ 6000/21770] eta: 0:12:54 time: 0.0445 data: 0.0013 max mem: 19788 +Test: [ 6100/21770] eta: 0:12:50 time: 0.0526 data: 0.0017 max mem: 19788 +Test: [ 6200/21770] eta: 0:12:45 time: 0.0511 data: 0.0017 max mem: 19788 +Test: [ 6300/21770] eta: 0:12:39 time: 0.0487 data: 0.0017 max mem: 19788 +Test: [ 6400/21770] eta: 0:12:33 time: 0.0433 data: 0.0016 max mem: 19788 +Test: [ 6500/21770] eta: 0:12:29 time: 0.0477 data: 0.0014 max mem: 19788 +Test: [ 6600/21770] eta: 0:12:24 time: 0.0500 data: 0.0018 max mem: 19788 +Test: [ 6700/21770] eta: 0:12:18 time: 0.0444 data: 0.0018 max mem: 19788 +Test: [ 6800/21770] eta: 0:12:13 time: 0.0469 data: 0.0015 max mem: 19788 +Test: [ 6900/21770] eta: 0:12:08 time: 0.0534 data: 0.0019 max mem: 19788 +Test: [ 7000/21770] eta: 0:12:05 time: 0.0551 data: 0.0020 max mem: 19788 +Test: [ 7100/21770] eta: 0:12:00 time: 0.0482 data: 0.0017 max mem: 19788 +Test: [ 7200/21770] eta: 0:11:55 time: 0.0453 data: 0.0016 max mem: 19788 +Test: [ 7300/21770] eta: 0:11:50 time: 0.0545 data: 0.0019 max mem: 19788 +Test: [ 7400/21770] eta: 0:11:44 time: 0.0450 data: 0.0015 max mem: 19788 +Test: [ 7500/21770] eta: 0:11:39 time: 0.0460 data: 0.0017 max mem: 19788 +Test: [ 7600/21770] eta: 0:11:35 time: 0.0552 data: 0.0020 max mem: 19788 +Test: [ 7700/21770] eta: 0:11:31 time: 0.0491 data: 0.0016 max mem: 19788 +Test: [ 7800/21770] eta: 0:11:25 time: 0.0505 data: 0.0016 max mem: 19788 +Test: [ 7900/21770] eta: 0:11:21 time: 0.0483 data: 0.0016 max mem: 19788 +Test: [ 8000/21770] eta: 0:11:16 time: 0.0445 data: 0.0014 max mem: 19788 +Test: [ 8100/21770] eta: 0:11:11 time: 0.0470 data: 0.0015 max mem: 19788 +Test: [ 8200/21770] eta: 0:11:05 time: 0.0487 data: 0.0015 max mem: 19788 +Test: [ 8300/21770] eta: 0:11:00 time: 0.0540 data: 0.0019 max mem: 19788 +Test: [ 8400/21770] eta: 0:10:55 time: 0.0442 data: 0.0015 max mem: 19788 +Test: [ 8500/21770] eta: 0:10:49 time: 0.0537 data: 0.0017 max mem: 19788 +Test: [ 8600/21770] eta: 0:10:45 time: 0.0523 data: 0.0017 max mem: 19788 +Test: [ 8700/21770] eta: 0:10:40 time: 0.0434 data: 0.0013 max mem: 19788 +Test: [ 8800/21770] eta: 0:10:34 time: 0.0497 data: 0.0013 max mem: 19788 +Test: [ 8900/21770] eta: 0:10:29 time: 0.0443 data: 0.0016 max mem: 19788 +Test: [ 9000/21770] eta: 0:10:24 time: 0.0477 data: 0.0015 max mem: 19788 +Test: [ 9100/21770] eta: 0:10:19 time: 0.0450 data: 0.0015 max mem: 19788 +Test: [ 9200/21770] eta: 0:10:14 time: 0.0463 data: 0.0015 max mem: 19788 +Test: [ 9300/21770] eta: 0:10:09 time: 0.0534 data: 0.0019 max mem: 19788 +Test: [ 9400/21770] eta: 0:10:04 time: 0.0520 data: 0.0017 max mem: 19788 +Test: [ 9500/21770] eta: 0:09:59 time: 0.0442 data: 0.0014 max mem: 19788 +Test: [ 9600/21770] eta: 0:09:54 time: 0.0494 data: 0.0017 max mem: 19788 +Test: [ 9700/21770] eta: 0:09:49 time: 0.0441 data: 0.0016 max mem: 19788 +Test: [ 9800/21770] eta: 0:09:44 time: 0.0475 data: 0.0016 max mem: 19788 +Test: [ 9900/21770] eta: 0:09:39 time: 0.0444 data: 0.0014 max mem: 19788 +Test: [10000/21770] eta: 0:09:34 time: 0.0450 data: 0.0014 max mem: 19788 +Test: [10100/21770] eta: 0:09:28 time: 0.0441 data: 0.0014 max mem: 19788 +Test: [10200/21770] eta: 0:09:23 time: 0.0457 data: 0.0017 max mem: 19788 +Test: [10300/21770] eta: 0:09:18 time: 0.0434 data: 0.0013 max mem: 19788 +Test: [10400/21770] eta: 0:09:12 time: 0.0454 data: 0.0014 max mem: 19788 +Test: [10500/21770] eta: 0:09:07 time: 0.0441 data: 0.0015 max mem: 19788 +Test: [10600/21770] eta: 0:09:02 time: 0.0431 data: 0.0014 max mem: 19788 +Test: [10700/21770] eta: 0:08:57 time: 0.0495 data: 0.0015 max mem: 19788 +Test: [10800/21770] eta: 0:08:52 time: 0.0432 data: 0.0013 max mem: 19788 +Test: [10900/21770] eta: 0:08:47 time: 0.0438 data: 0.0012 max mem: 19788 +Test: [11000/21770] eta: 0:08:42 time: 0.0466 data: 0.0015 max mem: 19788 +Test: [11100/21770] eta: 0:08:37 time: 0.0465 data: 0.0016 max mem: 19788 +Test: [11200/21770] eta: 0:08:32 time: 0.0459 data: 0.0015 max mem: 19788 +Test: [11300/21770] eta: 0:08:27 time: 0.0520 data: 0.0018 max mem: 19788 +Test: [11400/21770] eta: 0:08:22 time: 0.0458 data: 0.0015 max mem: 19788 +Test: [11500/21770] eta: 0:08:17 time: 0.0442 data: 0.0015 max mem: 19788 +Test: [11600/21770] eta: 0:08:12 time: 0.0446 data: 0.0015 max mem: 19788 +Test: [11700/21770] eta: 0:08:07 time: 0.0493 data: 0.0017 max mem: 19788 +Test: [11800/21770] eta: 0:08:02 time: 0.0462 data: 0.0014 max mem: 19788 +Test: [11900/21770] eta: 0:07:57 time: 0.0517 data: 0.0018 max mem: 19788 +Test: [12000/21770] eta: 0:07:52 time: 0.0491 data: 0.0016 max mem: 19788 +Test: [12100/21770] eta: 0:07:47 time: 0.0491 data: 0.0017 max mem: 19788 +Test: [12200/21770] eta: 0:07:42 time: 0.0437 data: 0.0014 max mem: 19788 +Test: [12300/21770] eta: 0:07:37 time: 0.0482 data: 0.0015 max mem: 19788 +Test: [12400/21770] eta: 0:07:32 time: 0.0440 data: 0.0014 max mem: 19788 +Test: [12500/21770] eta: 0:07:27 time: 0.0530 data: 0.0017 max mem: 19788 +Test: [12600/21770] eta: 0:07:22 time: 0.0469 data: 0.0016 max mem: 19788 +Test: [12700/21770] eta: 0:07:17 time: 0.0451 data: 0.0015 max mem: 19788 +Test: [12800/21770] eta: 0:07:13 time: 0.0423 data: 0.0014 max mem: 19788 +Test: [12900/21770] eta: 0:07:07 time: 0.0431 data: 0.0014 max mem: 19788 +Test: [13000/21770] eta: 0:07:03 time: 0.0431 data: 0.0013 max mem: 19788 +Test: [13100/21770] eta: 0:06:57 time: 0.0439 data: 0.0014 max mem: 19788 +Test: [13200/21770] eta: 0:06:53 time: 0.0457 data: 0.0013 max mem: 19788 +Test: [13300/21770] eta: 0:06:48 time: 0.0494 data: 0.0015 max mem: 19788 +Test: [13400/21770] eta: 0:06:43 time: 0.0508 data: 0.0015 max mem: 19788 +Test: [13500/21770] eta: 0:06:38 time: 0.0461 data: 0.0015 max mem: 19788 +Test: [13600/21770] eta: 0:06:33 time: 0.0467 data: 0.0014 max mem: 19788 +Test: [13700/21770] eta: 0:06:28 time: 0.0503 data: 0.0017 max mem: 19788 +Test: [13800/21770] eta: 0:06:23 time: 0.0434 data: 0.0014 max mem: 19788 +Test: [13900/21770] eta: 0:06:19 time: 0.0441 data: 0.0013 max mem: 19788 +Test: [14000/21770] eta: 0:06:14 time: 0.0433 data: 0.0015 max mem: 19788 +Test: [14100/21770] eta: 0:06:09 time: 0.0435 data: 0.0015 max mem: 19788 +Test: [14200/21770] eta: 0:06:04 time: 0.0447 data: 0.0014 max mem: 19788 +Test: [14300/21770] eta: 0:05:59 time: 0.0438 data: 0.0014 max mem: 19788 +Test: [14400/21770] eta: 0:05:54 time: 0.0434 data: 0.0016 max mem: 19788 +Test: [14500/21770] eta: 0:05:49 time: 0.0444 data: 0.0014 max mem: 19788 +Test: [14600/21770] eta: 0:05:44 time: 0.0520 data: 0.0018 max mem: 19788 +Test: [14700/21770] eta: 0:05:39 time: 0.0440 data: 0.0014 max mem: 19788 +Test: [14800/21770] eta: 0:05:34 time: 0.0436 data: 0.0015 max mem: 19788 +Test: [14900/21770] eta: 0:05:29 time: 0.0445 data: 0.0014 max mem: 19788 +Test: [15000/21770] eta: 0:05:24 time: 0.0432 data: 0.0013 max mem: 19788 +Test: [15100/21770] eta: 0:05:19 time: 0.0473 data: 0.0017 max mem: 19788 +Test: [15200/21770] eta: 0:05:15 time: 0.0433 data: 0.0015 max mem: 19788 +Test: [15300/21770] eta: 0:05:10 time: 0.0512 data: 0.0016 max mem: 19788 +Test: [15400/21770] eta: 0:05:05 time: 0.0454 data: 0.0014 max mem: 19788 +Test: [15500/21770] eta: 0:05:00 time: 0.0448 data: 0.0015 max mem: 19788 +Test: [15600/21770] eta: 0:04:55 time: 0.0493 data: 0.0014 max mem: 19788 +Test: [15700/21770] eta: 0:04:50 time: 0.0456 data: 0.0015 max mem: 19788 +Test: [15800/21770] eta: 0:04:45 time: 0.0440 data: 0.0016 max mem: 19788 +Test: [15900/21770] eta: 0:04:41 time: 0.0530 data: 0.0015 max mem: 19788 +Test: [16000/21770] eta: 0:04:36 time: 0.0472 data: 0.0015 max mem: 19788 +Test: [16100/21770] eta: 0:04:31 time: 0.0499 data: 0.0016 max mem: 19788 +Test: [16200/21770] eta: 0:04:26 time: 0.0433 data: 0.0014 max mem: 19788 +Test: [16300/21770] eta: 0:04:21 time: 0.0433 data: 0.0015 max mem: 19788 +Test: [16400/21770] eta: 0:04:16 time: 0.0423 data: 0.0014 max mem: 19788 +Test: [16500/21770] eta: 0:04:12 time: 0.0523 data: 0.0017 max mem: 19788 +Test: [16600/21770] eta: 0:04:07 time: 0.0520 data: 0.0017 max mem: 19788 +Test: [16700/21770] eta: 0:04:02 time: 0.0413 data: 0.0014 max mem: 19788 +Test: [16800/21770] eta: 0:03:57 time: 0.0444 data: 0.0015 max mem: 19788 +Test: [16900/21770] eta: 0:03:52 time: 0.0437 data: 0.0014 max mem: 19788 +Test: [17000/21770] eta: 0:03:47 time: 0.0433 data: 0.0015 max mem: 19788 +Test: [17100/21770] eta: 0:03:43 time: 0.0526 data: 0.0018 max mem: 19788 +Test: [17200/21770] eta: 0:03:38 time: 0.0443 data: 0.0014 max mem: 19788 +Test: [17300/21770] eta: 0:03:33 time: 0.0513 data: 0.0017 max mem: 19788 +Test: [17400/21770] eta: 0:03:28 time: 0.0426 data: 0.0014 max mem: 19788 +Test: [17500/21770] eta: 0:03:23 time: 0.0492 data: 0.0018 max mem: 19788 +Test: [17600/21770] eta: 0:03:19 time: 0.0462 data: 0.0020 max mem: 19788 +Test: [17700/21770] eta: 0:03:14 time: 0.0478 data: 0.0017 max mem: 19788 +Test: [17800/21770] eta: 0:03:09 time: 0.0485 data: 0.0016 max mem: 19788 +Test: [17900/21770] eta: 0:03:04 time: 0.0486 data: 0.0016 max mem: 19788 +Test: [18000/21770] eta: 0:02:59 time: 0.0526 data: 0.0015 max mem: 19788 +Test: [18100/21770] eta: 0:02:55 time: 0.0440 data: 0.0014 max mem: 19788 +Test: [18200/21770] eta: 0:02:50 time: 0.0438 data: 0.0015 max mem: 19788 +Test: [18300/21770] eta: 0:02:45 time: 0.0499 data: 0.0015 max mem: 19788 +Test: [18400/21770] eta: 0:02:40 time: 0.0521 data: 0.0017 max mem: 19788 +Test: [18500/21770] eta: 0:02:35 time: 0.0522 data: 0.0017 max mem: 19788 +Test: [18600/21770] eta: 0:02:31 time: 0.0427 data: 0.0013 max mem: 19788 +Test: [18700/21770] eta: 0:02:26 time: 0.0501 data: 0.0015 max mem: 19788 +Test: [18800/21770] eta: 0:02:21 time: 0.0430 data: 0.0016 max mem: 19788 +Test: [18900/21770] eta: 0:02:16 time: 0.0454 data: 0.0014 max mem: 19788 +Test: [19000/21770] eta: 0:02:11 time: 0.0434 data: 0.0016 max mem: 19788 +Test: [19100/21770] eta: 0:02:07 time: 0.0473 data: 0.0016 max mem: 19788 +Test: [19200/21770] eta: 0:02:02 time: 0.0432 data: 0.0016 max mem: 19788 +Test: [19300/21770] eta: 0:01:57 time: 0.0429 data: 0.0014 max mem: 19788 +Test: [19400/21770] eta: 0:01:52 time: 0.0467 data: 0.0015 max mem: 19788 +Test: [19500/21770] eta: 0:01:47 time: 0.0443 data: 0.0014 max mem: 19788 +Test: [19600/21770] eta: 0:01:43 time: 0.0462 data: 0.0016 max mem: 19788 +Test: [19700/21770] eta: 0:01:38 time: 0.0425 data: 0.0013 max mem: 19788 +Test: [19800/21770] eta: 0:01:33 time: 0.0427 data: 0.0016 max mem: 19788 +Test: [19900/21770] eta: 0:01:28 time: 0.0429 data: 0.0014 max mem: 19788 +Test: [20000/21770] eta: 0:01:24 time: 0.0446 data: 0.0016 max mem: 19788 +Test: [20100/21770] eta: 0:01:19 time: 0.0498 data: 0.0016 max mem: 19788 +Test: [20200/21770] eta: 0:01:14 time: 0.0441 data: 0.0013 max mem: 19788 +Test: [20300/21770] eta: 0:01:09 time: 0.0526 data: 0.0016 max mem: 19788 +Test: [20400/21770] eta: 0:01:05 time: 0.0458 data: 0.0014 max mem: 19788 +Test: [20500/21770] eta: 0:01:00 time: 0.0518 data: 0.0018 max mem: 19788 +Test: [20600/21770] eta: 0:00:55 time: 0.0438 data: 0.0015 max mem: 19788 +Test: [20700/21770] eta: 0:00:50 time: 0.0460 data: 0.0015 max mem: 19788 +Test: [20800/21770] eta: 0:00:46 time: 0.0472 data: 0.0015 max mem: 19788 +Test: [20900/21770] eta: 0:00:41 time: 0.0450 data: 0.0015 max mem: 19788 +Test: [21000/21770] eta: 0:00:36 time: 0.0442 data: 0.0016 max mem: 19788 +Test: [21100/21770] eta: 0:00:31 time: 0.0443 data: 0.0015 max mem: 19788 +Test: [21200/21770] eta: 0:00:27 time: 0.0434 data: 0.0015 max mem: 19788 +Test: [21300/21770] eta: 0:00:22 time: 0.0487 data: 0.0017 max mem: 19788 +Test: [21400/21770] eta: 0:00:17 time: 0.0495 data: 0.0015 max mem: 19788 +Test: [21500/21770] eta: 0:00:12 time: 0.0465 data: 0.0016 max mem: 19788 +Test: [21600/21770] eta: 0:00:08 time: 0.0513 data: 0.0017 max mem: 19788 +Test: [21700/21770] eta: 0:00:03 time: 0.0475 data: 0.0014 max mem: 19788 +Test: Total time: 0:17:14 +Final results: +Mean IoU is 63.40 + + precision@0.5 = 70.29 + precision@0.6 = 64.58 + precision@0.7 = 57.33 + precision@0.8 = 46.09 + precision@0.9 = 23.02 + overall IoU = 63.42 + mean IoU = 63.40 + +Mean accuracy for one-to-zero sample is 79.20 + +Average object IoU 0.6339684412310658 +Overall IoU 63.42060089111328 +Epoch: [12] [ 0/2138] eta: 8:27:09 lr: 3.6270347047008376e-05 loss: 0.0880 (0.0880) time: 14.2329 data: 1.7574 max mem: 19788 +Epoch: [12] [ 10/2138] eta: 2:16:10 lr: 3.626489399837915e-05 loss: 0.0378 (0.0457) time: 3.8395 data: 0.1613 max mem: 19788 +Epoch: [12] [ 20/2138] eta: 1:57:58 lr: 3.6259440858641795e-05 loss: 0.0336 (0.0405) time: 2.7976 data: 0.0018 max mem: 19788 +Epoch: [12] [ 30/2138] eta: 1:51:14 lr: 3.625398762777959e-05 loss: 0.0362 (0.0404) time: 2.7961 data: 0.0020 max mem: 19788 +Epoch: [12] [ 40/2138] eta: 1:47:36 lr: 3.624853430577575e-05 loss: 0.0370 (0.0409) time: 2.7994 data: 0.0021 max mem: 19788 +Epoch: [12] [ 50/2138] eta: 1:45:10 lr: 3.624308089261354e-05 loss: 0.0418 (0.0414) time: 2.7988 data: 0.0023 max mem: 19788 +Epoch: [12] [ 60/2138] eta: 1:43:27 lr: 3.6237627388276184e-05 loss: 0.0418 (0.0423) time: 2.8020 data: 0.0022 max mem: 19788 +Epoch: [12] [ 70/2138] eta: 1:42:05 lr: 3.6232173792746925e-05 loss: 0.0376 (0.0425) time: 2.8094 data: 0.0021 max mem: 19788 +Epoch: [12] [ 80/2138] eta: 1:40:56 lr: 3.622672010600896e-05 loss: 0.0336 (0.0421) time: 2.8088 data: 0.0021 max mem: 19788 +Epoch: [12] [ 90/2138] eta: 1:39:56 lr: 3.622126632804554e-05 loss: 0.0354 (0.0414) time: 2.8060 data: 0.0021 max mem: 19788 +Epoch: [12] [ 100/2138] eta: 1:39:04 lr: 3.6215812458839854e-05 loss: 0.0360 (0.0412) time: 2.8106 data: 0.0025 max mem: 19788 +Epoch: [12] [ 110/2138] eta: 1:38:15 lr: 3.621035849837512e-05 loss: 0.0380 (0.0410) time: 2.8124 data: 0.0026 max mem: 19788 +Epoch: [12] [ 120/2138] eta: 1:37:28 lr: 3.620490444663452e-05 loss: 0.0371 (0.0404) time: 2.8050 data: 0.0023 max mem: 19788 +Epoch: [12] [ 130/2138] eta: 1:36:44 lr: 3.619945030360127e-05 loss: 0.0346 (0.0400) time: 2.7998 data: 0.0021 max mem: 19788 +Epoch: [12] [ 140/2138] eta: 1:36:00 lr: 3.619399606925854e-05 loss: 0.0346 (0.0400) time: 2.7927 data: 0.0020 max mem: 19788 +Epoch: [12] [ 150/2138] eta: 1:35:19 lr: 3.618854174358952e-05 loss: 0.0339 (0.0399) time: 2.7885 data: 0.0021 max mem: 19788 +Epoch: [12] [ 160/2138] eta: 1:34:41 lr: 3.618308732657739e-05 loss: 0.0339 (0.0396) time: 2.7958 data: 0.0022 max mem: 19788 +Epoch: [12] [ 170/2138] eta: 1:34:04 lr: 3.617763281820531e-05 loss: 0.0396 (0.0402) time: 2.8008 data: 0.0022 max mem: 19788 +Epoch: [12] [ 180/2138] eta: 1:33:29 lr: 3.617217821845646e-05 loss: 0.0406 (0.0402) time: 2.8062 data: 0.0022 max mem: 19788 +Epoch: [12] [ 190/2138] eta: 1:32:54 lr: 3.616672352731398e-05 loss: 0.0317 (0.0400) time: 2.8064 data: 0.0023 max mem: 19788 +Epoch: [12] [ 200/2138] eta: 1:32:19 lr: 3.616126874476103e-05 loss: 0.0317 (0.0397) time: 2.7974 data: 0.0023 max mem: 19788 +Epoch: [12] [ 210/2138] eta: 1:31:44 lr: 3.615581387078077e-05 loss: 0.0317 (0.0397) time: 2.7909 data: 0.0023 max mem: 19788 +Epoch: [12] [ 220/2138] eta: 1:31:10 lr: 3.6150358905356326e-05 loss: 0.0339 (0.0399) time: 2.7873 data: 0.0025 max mem: 19788 +Epoch: [12] [ 230/2138] eta: 1:30:36 lr: 3.614490384847083e-05 loss: 0.0416 (0.0401) time: 2.7897 data: 0.0025 max mem: 19788 +Epoch: [12] [ 240/2138] eta: 1:30:03 lr: 3.613944870010741e-05 loss: 0.0454 (0.0400) time: 2.7899 data: 0.0026 max mem: 19788 +Epoch: [12] [ 250/2138] eta: 1:29:31 lr: 3.6133993460249214e-05 loss: 0.0350 (0.0397) time: 2.7973 data: 0.0028 max mem: 19788 +Epoch: [12] [ 260/2138] eta: 1:29:01 lr: 3.612853812887933e-05 loss: 0.0313 (0.0396) time: 2.8104 data: 0.0026 max mem: 19788 +Epoch: [12] [ 270/2138] eta: 1:28:30 lr: 3.6123082705980885e-05 loss: 0.0325 (0.0395) time: 2.8141 data: 0.0022 max mem: 19788 +Epoch: [12] [ 280/2138] eta: 1:28:00 lr: 3.611762719153697e-05 loss: 0.0383 (0.0394) time: 2.8130 data: 0.0022 max mem: 19788 +Epoch: [12] [ 290/2138] eta: 1:27:29 lr: 3.61121715855307e-05 loss: 0.0389 (0.0396) time: 2.8070 data: 0.0025 max mem: 19788 +Epoch: [12] [ 300/2138] eta: 1:26:58 lr: 3.610671588794515e-05 loss: 0.0408 (0.0396) time: 2.8062 data: 0.0024 max mem: 19788 +Epoch: [12] [ 310/2138] eta: 1:26:27 lr: 3.610126009876342e-05 loss: 0.0400 (0.0396) time: 2.8019 data: 0.0025 max mem: 19788 +Epoch: [12] [ 320/2138] eta: 1:25:56 lr: 3.609580421796859e-05 loss: 0.0282 (0.0394) time: 2.7929 data: 0.0025 max mem: 19788 +Epoch: [12] [ 330/2138] eta: 1:25:26 lr: 3.6090348245543745e-05 loss: 0.0292 (0.0394) time: 2.7949 data: 0.0024 max mem: 19788 +Epoch: [12] [ 340/2138] eta: 1:24:55 lr: 3.608489218147193e-05 loss: 0.0358 (0.0393) time: 2.7951 data: 0.0027 max mem: 19788 +Epoch: [12] [ 350/2138] eta: 1:24:25 lr: 3.607943602573623e-05 loss: 0.0326 (0.0395) time: 2.7936 data: 0.0028 max mem: 19788 +Epoch: [12] [ 360/2138] eta: 1:23:55 lr: 3.6073979778319686e-05 loss: 0.0442 (0.0397) time: 2.7940 data: 0.0029 max mem: 19788 +Epoch: [12] [ 370/2138] eta: 1:23:25 lr: 3.6068523439205365e-05 loss: 0.0439 (0.0398) time: 2.7946 data: 0.0029 max mem: 19788 +Epoch: [12] [ 380/2138] eta: 1:22:55 lr: 3.606306700837631e-05 loss: 0.0417 (0.0403) time: 2.8027 data: 0.0028 max mem: 19788 +Epoch: [12] [ 390/2138] eta: 1:22:26 lr: 3.605761048581554e-05 loss: 0.0357 (0.0402) time: 2.8045 data: 0.0027 max mem: 19788 +Epoch: [12] [ 400/2138] eta: 1:21:56 lr: 3.6052153871506106e-05 loss: 0.0348 (0.0403) time: 2.7946 data: 0.0023 max mem: 19788 +Epoch: [12] [ 410/2138] eta: 1:21:26 lr: 3.604669716543104e-05 loss: 0.0406 (0.0402) time: 2.7907 data: 0.0020 max mem: 19788 +Epoch: [12] [ 420/2138] eta: 1:20:56 lr: 3.6041240367573355e-05 loss: 0.0359 (0.0401) time: 2.7907 data: 0.0020 max mem: 19788 +Epoch: [12] [ 430/2138] eta: 1:20:26 lr: 3.603578347791606e-05 loss: 0.0339 (0.0401) time: 2.7901 data: 0.0021 max mem: 19788 +Epoch: [12] [ 440/2138] eta: 1:19:57 lr: 3.603032649644217e-05 loss: 0.0339 (0.0402) time: 2.7902 data: 0.0024 max mem: 19788 +Epoch: [12] [ 450/2138] eta: 1:19:27 lr: 3.60248694231347e-05 loss: 0.0369 (0.0402) time: 2.7930 data: 0.0025 max mem: 19788 +Epoch: [12] [ 460/2138] eta: 1:18:59 lr: 3.601941225797664e-05 loss: 0.0361 (0.0401) time: 2.8041 data: 0.0022 max mem: 19788 +Epoch: [12] [ 470/2138] eta: 1:18:30 lr: 3.601395500095097e-05 loss: 0.0329 (0.0400) time: 2.8084 data: 0.0023 max mem: 19788 +Epoch: [12] [ 480/2138] eta: 1:18:01 lr: 3.600849765204068e-05 loss: 0.0387 (0.0402) time: 2.8049 data: 0.0023 max mem: 19788 +Epoch: [12] [ 490/2138] eta: 1:17:32 lr: 3.6003040211228763e-05 loss: 0.0402 (0.0402) time: 2.8085 data: 0.0023 max mem: 19788 +Epoch: [12] [ 500/2138] eta: 1:17:03 lr: 3.599758267849818e-05 loss: 0.0394 (0.0403) time: 2.8090 data: 0.0024 max mem: 19788 +Epoch: [12] [ 510/2138] eta: 1:16:35 lr: 3.599212505383189e-05 loss: 0.0331 (0.0402) time: 2.8107 data: 0.0027 max mem: 19788 +Epoch: [12] [ 520/2138] eta: 1:16:06 lr: 3.5986667337212885e-05 loss: 0.0331 (0.0402) time: 2.8126 data: 0.0028 max mem: 19788 +Epoch: [12] [ 530/2138] eta: 1:15:38 lr: 3.5981209528624086e-05 loss: 0.0340 (0.0401) time: 2.8084 data: 0.0025 max mem: 19788 +Epoch: [12] [ 540/2138] eta: 1:15:09 lr: 3.597575162804846e-05 loss: 0.0344 (0.0400) time: 2.8116 data: 0.0024 max mem: 19788 +Epoch: [12] [ 550/2138] eta: 1:14:41 lr: 3.597029363546895e-05 loss: 0.0329 (0.0400) time: 2.8140 data: 0.0024 max mem: 19788 +Epoch: [12] [ 560/2138] eta: 1:14:12 lr: 3.596483555086849e-05 loss: 0.0350 (0.0400) time: 2.8121 data: 0.0025 max mem: 19788 +Epoch: [12] [ 570/2138] eta: 1:13:44 lr: 3.595937737423001e-05 loss: 0.0330 (0.0400) time: 2.8207 data: 0.0026 max mem: 19788 +Epoch: [12] [ 580/2138] eta: 1:13:15 lr: 3.595391910553643e-05 loss: 0.0349 (0.0400) time: 2.8175 data: 0.0024 max mem: 19788 +Epoch: [12] [ 590/2138] eta: 1:12:47 lr: 3.5948460744770673e-05 loss: 0.0363 (0.0399) time: 2.8024 data: 0.0023 max mem: 19788 +Epoch: [12] [ 600/2138] eta: 1:12:18 lr: 3.5943002291915665e-05 loss: 0.0376 (0.0399) time: 2.7994 data: 0.0024 max mem: 19788 +Epoch: [12] [ 610/2138] eta: 1:11:49 lr: 3.59375437469543e-05 loss: 0.0376 (0.0398) time: 2.7934 data: 0.0025 max mem: 19788 +Epoch: [12] [ 620/2138] eta: 1:11:20 lr: 3.593208510986947e-05 loss: 0.0368 (0.0398) time: 2.7930 data: 0.0023 max mem: 19788 +Epoch: [12] [ 630/2138] eta: 1:10:51 lr: 3.592662638064409e-05 loss: 0.0370 (0.0398) time: 2.7998 data: 0.0020 max mem: 19788 +Epoch: [12] [ 640/2138] eta: 1:10:23 lr: 3.592116755926104e-05 loss: 0.0368 (0.0397) time: 2.7999 data: 0.0020 max mem: 19788 +Epoch: [12] [ 650/2138] eta: 1:09:54 lr: 3.59157086457032e-05 loss: 0.0372 (0.0397) time: 2.8022 data: 0.0020 max mem: 19788 +Epoch: [12] [ 660/2138] eta: 1:09:26 lr: 3.5910249639953444e-05 loss: 0.0347 (0.0397) time: 2.8023 data: 0.0023 max mem: 19788 +Epoch: [12] [ 670/2138] eta: 1:08:57 lr: 3.5904790541994646e-05 loss: 0.0338 (0.0397) time: 2.7978 data: 0.0026 max mem: 19788 +Epoch: [12] [ 680/2138] eta: 1:08:28 lr: 3.5899331351809675e-05 loss: 0.0341 (0.0397) time: 2.7965 data: 0.0027 max mem: 19788 +Epoch: [12] [ 690/2138] eta: 1:08:00 lr: 3.5893872069381386e-05 loss: 0.0341 (0.0397) time: 2.7927 data: 0.0029 max mem: 19788 +Epoch: [12] [ 700/2138] eta: 1:07:31 lr: 3.588841269469263e-05 loss: 0.0329 (0.0396) time: 2.7907 data: 0.0027 max mem: 19788 +Epoch: [12] [ 710/2138] eta: 1:07:02 lr: 3.588295322772624e-05 loss: 0.0330 (0.0396) time: 2.7902 data: 0.0024 max mem: 19788 +Epoch: [12] [ 720/2138] eta: 1:06:33 lr: 3.5877493668465084e-05 loss: 0.0323 (0.0394) time: 2.7888 data: 0.0021 max mem: 19788 +Epoch: [12] [ 730/2138] eta: 1:06:05 lr: 3.587203401689198e-05 loss: 0.0325 (0.0395) time: 2.8040 data: 0.0022 max mem: 19788 +Epoch: [12] [ 740/2138] eta: 1:05:37 lr: 3.5866574272989756e-05 loss: 0.0395 (0.0396) time: 2.8165 data: 0.0024 max mem: 19788 +Epoch: [12] [ 750/2138] eta: 1:05:09 lr: 3.586111443674124e-05 loss: 0.0339 (0.0396) time: 2.8265 data: 0.0025 max mem: 19788 +Epoch: [12] [ 760/2138] eta: 1:04:41 lr: 3.585565450812924e-05 loss: 0.0390 (0.0396) time: 2.8283 data: 0.0025 max mem: 19788 +Epoch: [12] [ 770/2138] eta: 1:04:13 lr: 3.585019448713657e-05 loss: 0.0390 (0.0396) time: 2.8164 data: 0.0026 max mem: 19788 +Epoch: [12] [ 780/2138] eta: 1:03:45 lr: 3.584473437374602e-05 loss: 0.0364 (0.0396) time: 2.8125 data: 0.0026 max mem: 19788 +Epoch: [12] [ 790/2138] eta: 1:03:16 lr: 3.583927416794041e-05 loss: 0.0325 (0.0395) time: 2.8130 data: 0.0024 max mem: 19788 +Epoch: [12] [ 800/2138] eta: 1:02:48 lr: 3.583381386970253e-05 loss: 0.0332 (0.0395) time: 2.8139 data: 0.0022 max mem: 19788 +Epoch: [12] [ 810/2138] eta: 1:02:20 lr: 3.582835347901514e-05 loss: 0.0387 (0.0395) time: 2.8134 data: 0.0021 max mem: 19788 +Epoch: [12] [ 820/2138] eta: 1:01:52 lr: 3.582289299586103e-05 loss: 0.0365 (0.0395) time: 2.8126 data: 0.0022 max mem: 19788 +Epoch: [12] [ 830/2138] eta: 1:01:24 lr: 3.581743242022299e-05 loss: 0.0362 (0.0394) time: 2.8117 data: 0.0025 max mem: 19788 +Epoch: [12] [ 840/2138] eta: 1:00:55 lr: 3.5811971752083775e-05 loss: 0.0348 (0.0394) time: 2.8084 data: 0.0023 max mem: 19788 +Epoch: [12] [ 850/2138] eta: 1:00:27 lr: 3.5806510991426136e-05 loss: 0.0348 (0.0394) time: 2.8061 data: 0.0023 max mem: 19788 +Epoch: [12] [ 860/2138] eta: 0:59:59 lr: 3.580105013823284e-05 loss: 0.0332 (0.0393) time: 2.8065 data: 0.0024 max mem: 19788 +Epoch: [12] [ 870/2138] eta: 0:59:30 lr: 3.5795589192486635e-05 loss: 0.0332 (0.0394) time: 2.7970 data: 0.0024 max mem: 19788 +Epoch: [12] [ 880/2138] eta: 0:59:01 lr: 3.5790128154170254e-05 loss: 0.0367 (0.0394) time: 2.7882 data: 0.0025 max mem: 19788 +Epoch: [12] [ 890/2138] eta: 0:58:33 lr: 3.5784667023266436e-05 loss: 0.0351 (0.0393) time: 2.7906 data: 0.0024 max mem: 19788 +Epoch: [12] [ 900/2138] eta: 0:58:04 lr: 3.577920579975792e-05 loss: 0.0351 (0.0394) time: 2.7933 data: 0.0022 max mem: 19788 +Epoch: [12] [ 910/2138] eta: 0:57:36 lr: 3.577374448362743e-05 loss: 0.0330 (0.0393) time: 2.8001 data: 0.0024 max mem: 19788 +Epoch: [12] [ 920/2138] eta: 0:57:08 lr: 3.576828307485767e-05 loss: 0.0306 (0.0392) time: 2.8029 data: 0.0026 max mem: 19788 +Epoch: [12] [ 930/2138] eta: 0:56:39 lr: 3.576282157343135e-05 loss: 0.0373 (0.0392) time: 2.7963 data: 0.0025 max mem: 19788 +Epoch: [12] [ 940/2138] eta: 0:56:11 lr: 3.575735997933119e-05 loss: 0.0390 (0.0392) time: 2.7937 data: 0.0024 max mem: 19788 +Epoch: [12] [ 950/2138] eta: 0:55:43 lr: 3.5751898292539884e-05 loss: 0.0324 (0.0391) time: 2.7896 data: 0.0022 max mem: 19788 +Epoch: [12] [ 960/2138] eta: 0:55:14 lr: 3.574643651304013e-05 loss: 0.0379 (0.0392) time: 2.7859 data: 0.0021 max mem: 19788 +Epoch: [12] [ 970/2138] eta: 0:54:46 lr: 3.5740974640814595e-05 loss: 0.0409 (0.0392) time: 2.7914 data: 0.0022 max mem: 19788 +Epoch: [12] [ 980/2138] eta: 0:54:17 lr: 3.573551267584598e-05 loss: 0.0315 (0.0391) time: 2.8014 data: 0.0023 max mem: 19788 +Epoch: [12] [ 990/2138] eta: 0:53:49 lr: 3.573005061811695e-05 loss: 0.0315 (0.0391) time: 2.8124 data: 0.0022 max mem: 19788 +Epoch: [12] [1000/2138] eta: 0:53:21 lr: 3.5724588467610184e-05 loss: 0.0291 (0.0390) time: 2.8131 data: 0.0023 max mem: 19788 +Epoch: [12] [1010/2138] eta: 0:52:53 lr: 3.5719126224308324e-05 loss: 0.0342 (0.0390) time: 2.8121 data: 0.0022 max mem: 19788 +Epoch: [12] [1020/2138] eta: 0:52:25 lr: 3.571366388819404e-05 loss: 0.0363 (0.0390) time: 2.8036 data: 0.0021 max mem: 19788 +Epoch: [12] [1030/2138] eta: 0:51:56 lr: 3.570820145924998e-05 loss: 0.0338 (0.0389) time: 2.7942 data: 0.0021 max mem: 19788 +Epoch: [12] [1040/2138] eta: 0:51:28 lr: 3.570273893745879e-05 loss: 0.0345 (0.0389) time: 2.7928 data: 0.0024 max mem: 19788 +Epoch: [12] [1050/2138] eta: 0:51:00 lr: 3.5697276322803107e-05 loss: 0.0345 (0.0389) time: 2.7850 data: 0.0025 max mem: 19788 +Epoch: [12] [1060/2138] eta: 0:50:31 lr: 3.5691813615265554e-05 loss: 0.0318 (0.0389) time: 2.7862 data: 0.0023 max mem: 19788 +Epoch: [12] [1070/2138] eta: 0:50:03 lr: 3.568635081482877e-05 loss: 0.0321 (0.0389) time: 2.8009 data: 0.0021 max mem: 19788 +Epoch: [12] [1080/2138] eta: 0:49:35 lr: 3.568088792147535e-05 loss: 0.0343 (0.0389) time: 2.8015 data: 0.0021 max mem: 19788 +Epoch: [12] [1090/2138] eta: 0:49:06 lr: 3.567542493518792e-05 loss: 0.0343 (0.0389) time: 2.7881 data: 0.0023 max mem: 19788 +Epoch: [12] [1100/2138] eta: 0:48:38 lr: 3.56699618559491e-05 loss: 0.0380 (0.0389) time: 2.7857 data: 0.0025 max mem: 19788 +Epoch: [12] [1110/2138] eta: 0:48:10 lr: 3.566449868374147e-05 loss: 0.0377 (0.0389) time: 2.7861 data: 0.0025 max mem: 19788 +Epoch: [12] [1120/2138] eta: 0:47:41 lr: 3.565903541854764e-05 loss: 0.0385 (0.0389) time: 2.7874 data: 0.0025 max mem: 19788 +Epoch: [12] [1130/2138] eta: 0:47:13 lr: 3.565357206035017e-05 loss: 0.0367 (0.0389) time: 2.7942 data: 0.0023 max mem: 19788 +Epoch: [12] [1140/2138] eta: 0:46:45 lr: 3.564810860913168e-05 loss: 0.0336 (0.0389) time: 2.8007 data: 0.0023 max mem: 19788 +Epoch: [12] [1150/2138] eta: 0:46:17 lr: 3.564264506487472e-05 loss: 0.0327 (0.0388) time: 2.8012 data: 0.0024 max mem: 19788 +Epoch: [12] [1160/2138] eta: 0:45:49 lr: 3.5637181427561855e-05 loss: 0.0309 (0.0388) time: 2.8047 data: 0.0023 max mem: 19788 +Epoch: [12] [1170/2138] eta: 0:45:20 lr: 3.563171769717566e-05 loss: 0.0308 (0.0387) time: 2.8093 data: 0.0023 max mem: 19788 +Epoch: [12] [1180/2138] eta: 0:44:52 lr: 3.5626253873698696e-05 loss: 0.0308 (0.0387) time: 2.8075 data: 0.0022 max mem: 19788 +Epoch: [12] [1190/2138] eta: 0:44:24 lr: 3.5620789957113504e-05 loss: 0.0351 (0.0388) time: 2.8105 data: 0.0021 max mem: 19788 +Epoch: [12] [1200/2138] eta: 0:43:56 lr: 3.5615325947402624e-05 loss: 0.0341 (0.0388) time: 2.8078 data: 0.0023 max mem: 19788 +Epoch: [12] [1210/2138] eta: 0:43:28 lr: 3.56098618445486e-05 loss: 0.0390 (0.0389) time: 2.8032 data: 0.0025 max mem: 19788 +Epoch: [12] [1220/2138] eta: 0:43:00 lr: 3.560439764853396e-05 loss: 0.0390 (0.0389) time: 2.8005 data: 0.0024 max mem: 19788 +Epoch: [12] [1230/2138] eta: 0:42:31 lr: 3.559893335934124e-05 loss: 0.0328 (0.0389) time: 2.7920 data: 0.0024 max mem: 19788 +Epoch: [12] [1240/2138] eta: 0:42:03 lr: 3.5593468976952944e-05 loss: 0.0310 (0.0388) time: 2.7895 data: 0.0024 max mem: 19788 +Epoch: [12] [1250/2138] eta: 0:41:35 lr: 3.558800450135159e-05 loss: 0.0315 (0.0388) time: 2.7927 data: 0.0025 max mem: 19788 +Epoch: [12] [1260/2138] eta: 0:41:07 lr: 3.5582539932519694e-05 loss: 0.0340 (0.0388) time: 2.7920 data: 0.0027 max mem: 19788 +Epoch: [12] [1270/2138] eta: 0:40:39 lr: 3.5577075270439744e-05 loss: 0.0308 (0.0388) time: 2.7939 data: 0.0024 max mem: 19788 +Epoch: [12] [1280/2138] eta: 0:40:10 lr: 3.557161051509423e-05 loss: 0.0313 (0.0387) time: 2.7973 data: 0.0022 max mem: 19788 +Epoch: [12] [1290/2138] eta: 0:39:42 lr: 3.5566145666465656e-05 loss: 0.0342 (0.0387) time: 2.7934 data: 0.0022 max mem: 19788 +Epoch: [12] [1300/2138] eta: 0:39:14 lr: 3.556068072453649e-05 loss: 0.0379 (0.0387) time: 2.7945 data: 0.0020 max mem: 19788 +Epoch: [12] [1310/2138] eta: 0:38:46 lr: 3.555521568928922e-05 loss: 0.0356 (0.0387) time: 2.7967 data: 0.0020 max mem: 19788 +Epoch: [12] [1320/2138] eta: 0:38:18 lr: 3.554975056070629e-05 loss: 0.0356 (0.0387) time: 2.7917 data: 0.0020 max mem: 19788 +Epoch: [12] [1330/2138] eta: 0:37:49 lr: 3.5544285338770194e-05 loss: 0.0361 (0.0387) time: 2.8000 data: 0.0021 max mem: 19788 +Epoch: [12] [1340/2138] eta: 0:37:21 lr: 3.553882002346337e-05 loss: 0.0400 (0.0387) time: 2.8116 data: 0.0024 max mem: 19788 +Epoch: [12] [1350/2138] eta: 0:36:53 lr: 3.5533354614768275e-05 loss: 0.0441 (0.0388) time: 2.8068 data: 0.0026 max mem: 19788 +Epoch: [12] [1360/2138] eta: 0:36:25 lr: 3.552788911266734e-05 loss: 0.0427 (0.0388) time: 2.8083 data: 0.0024 max mem: 19788 +Epoch: [12] [1370/2138] eta: 0:35:57 lr: 3.552242351714301e-05 loss: 0.0401 (0.0388) time: 2.8106 data: 0.0022 max mem: 19788 +Epoch: [12] [1380/2138] eta: 0:35:29 lr: 3.5516957828177724e-05 loss: 0.0417 (0.0389) time: 2.8021 data: 0.0021 max mem: 19788 +Epoch: [12] [1390/2138] eta: 0:35:01 lr: 3.551149204575389e-05 loss: 0.0350 (0.0389) time: 2.7955 data: 0.0020 max mem: 19788 +Epoch: [12] [1400/2138] eta: 0:34:33 lr: 3.550602616985394e-05 loss: 0.0322 (0.0389) time: 2.7914 data: 0.0022 max mem: 19788 +Epoch: [12] [1410/2138] eta: 0:34:04 lr: 3.550056020046029e-05 loss: 0.0303 (0.0388) time: 2.7947 data: 0.0023 max mem: 19788 +Epoch: [12] [1420/2138] eta: 0:33:36 lr: 3.549509413755533e-05 loss: 0.0321 (0.0388) time: 2.7994 data: 0.0025 max mem: 19788 +Epoch: [12] [1430/2138] eta: 0:33:08 lr: 3.548962798112146e-05 loss: 0.0348 (0.0389) time: 2.7926 data: 0.0024 max mem: 19788 +Epoch: [12] [1440/2138] eta: 0:32:40 lr: 3.548416173114109e-05 loss: 0.0399 (0.0389) time: 2.7915 data: 0.0021 max mem: 19788 +Epoch: [12] [1450/2138] eta: 0:32:12 lr: 3.547869538759659e-05 loss: 0.0360 (0.0389) time: 2.7932 data: 0.0023 max mem: 19788 +Epoch: [12] [1460/2138] eta: 0:31:44 lr: 3.547322895047035e-05 loss: 0.0321 (0.0389) time: 2.7900 data: 0.0024 max mem: 19788 +Epoch: [12] [1470/2138] eta: 0:31:15 lr: 3.546776241974474e-05 loss: 0.0321 (0.0389) time: 2.7914 data: 0.0023 max mem: 19788 +Epoch: [12] [1480/2138] eta: 0:30:47 lr: 3.546229579540212e-05 loss: 0.0353 (0.0389) time: 2.7977 data: 0.0024 max mem: 19788 +Epoch: [12] [1490/2138] eta: 0:30:19 lr: 3.545682907742488e-05 loss: 0.0369 (0.0389) time: 2.8045 data: 0.0024 max mem: 19788 +Epoch: [12] [1500/2138] eta: 0:29:51 lr: 3.545136226579534e-05 loss: 0.0434 (0.0389) time: 2.8074 data: 0.0024 max mem: 19788 +Epoch: [12] [1510/2138] eta: 0:29:23 lr: 3.544589536049586e-05 loss: 0.0310 (0.0389) time: 2.8037 data: 0.0027 max mem: 19788 +Epoch: [12] [1520/2138] eta: 0:28:55 lr: 3.5440428361508793e-05 loss: 0.0310 (0.0389) time: 2.8026 data: 0.0028 max mem: 19788 +Epoch: [12] [1530/2138] eta: 0:28:27 lr: 3.543496126881647e-05 loss: 0.0341 (0.0389) time: 2.8079 data: 0.0026 max mem: 19788 +Epoch: [12] [1540/2138] eta: 0:27:59 lr: 3.542949408240122e-05 loss: 0.0359 (0.0389) time: 2.8099 data: 0.0025 max mem: 19788 +Epoch: [12] [1550/2138] eta: 0:27:31 lr: 3.542402680224536e-05 loss: 0.0341 (0.0389) time: 2.8076 data: 0.0025 max mem: 19788 +Epoch: [12] [1560/2138] eta: 0:27:03 lr: 3.5418559428331213e-05 loss: 0.0332 (0.0389) time: 2.8091 data: 0.0025 max mem: 19788 +Epoch: [12] [1570/2138] eta: 0:26:35 lr: 3.541309196064109e-05 loss: 0.0332 (0.0389) time: 2.8119 data: 0.0024 max mem: 19788 +Epoch: [12] [1580/2138] eta: 0:26:06 lr: 3.54076243991573e-05 loss: 0.0347 (0.0388) time: 2.8049 data: 0.0023 max mem: 19788 +Epoch: [12] [1590/2138] eta: 0:25:38 lr: 3.5402156743862116e-05 loss: 0.0348 (0.0388) time: 2.8019 data: 0.0023 max mem: 19788 +Epoch: [12] [1600/2138] eta: 0:25:10 lr: 3.539668899473786e-05 loss: 0.0372 (0.0388) time: 2.8012 data: 0.0026 max mem: 19788 +Epoch: [12] [1610/2138] eta: 0:24:42 lr: 3.53912211517668e-05 loss: 0.0372 (0.0389) time: 2.7969 data: 0.0028 max mem: 19788 +Epoch: [12] [1620/2138] eta: 0:24:14 lr: 3.538575321493123e-05 loss: 0.0339 (0.0388) time: 2.8009 data: 0.0025 max mem: 19788 +Epoch: [12] [1630/2138] eta: 0:23:46 lr: 3.53802851842134e-05 loss: 0.0339 (0.0388) time: 2.8015 data: 0.0025 max mem: 19788 +Epoch: [12] [1640/2138] eta: 0:23:18 lr: 3.5374817059595583e-05 loss: 0.0365 (0.0388) time: 2.7924 data: 0.0025 max mem: 19788 +Epoch: [12] [1650/2138] eta: 0:22:50 lr: 3.5369348841060055e-05 loss: 0.0365 (0.0388) time: 2.7884 data: 0.0021 max mem: 19788 +Epoch: [12] [1660/2138] eta: 0:22:22 lr: 3.536388052858905e-05 loss: 0.0372 (0.0389) time: 2.7917 data: 0.0021 max mem: 19788 +Epoch: [12] [1670/2138] eta: 0:21:53 lr: 3.535841212216483e-05 loss: 0.0365 (0.0388) time: 2.8001 data: 0.0021 max mem: 19788 +Epoch: [12] [1680/2138] eta: 0:21:25 lr: 3.535294362176961e-05 loss: 0.0362 (0.0388) time: 2.8056 data: 0.0021 max mem: 19788 +Epoch: [12] [1690/2138] eta: 0:20:57 lr: 3.534747502738566e-05 loss: 0.0360 (0.0388) time: 2.8052 data: 0.0023 max mem: 19788 +Epoch: [12] [1700/2138] eta: 0:20:29 lr: 3.5342006338995174e-05 loss: 0.0338 (0.0388) time: 2.8075 data: 0.0024 max mem: 19788 +Epoch: [12] [1710/2138] eta: 0:20:01 lr: 3.533653755658039e-05 loss: 0.0332 (0.0388) time: 2.8020 data: 0.0025 max mem: 19788 +Epoch: [12] [1720/2138] eta: 0:19:33 lr: 3.5331068680123516e-05 loss: 0.0352 (0.0388) time: 2.7942 data: 0.0024 max mem: 19788 +Epoch: [12] [1730/2138] eta: 0:19:05 lr: 3.5325599709606774e-05 loss: 0.0352 (0.0388) time: 2.7943 data: 0.0021 max mem: 19788 +Epoch: [12] [1740/2138] eta: 0:18:37 lr: 3.5320130645012346e-05 loss: 0.0357 (0.0388) time: 2.7919 data: 0.0020 max mem: 19788 +Epoch: [12] [1750/2138] eta: 0:18:09 lr: 3.531466148632244e-05 loss: 0.0385 (0.0388) time: 2.7975 data: 0.0021 max mem: 19788 +Epoch: [12] [1760/2138] eta: 0:17:41 lr: 3.530919223351924e-05 loss: 0.0388 (0.0388) time: 2.8780 data: 0.0023 max mem: 19788 +Epoch: [12] [1770/2138] eta: 0:17:14 lr: 3.5303722886584926e-05 loss: 0.0354 (0.0388) time: 3.0600 data: 0.0025 max mem: 19788 +Epoch: [12] [1780/2138] eta: 0:16:47 lr: 3.529825344550169e-05 loss: 0.0323 (0.0388) time: 3.2723 data: 0.0022 max mem: 19788 +Epoch: [12] [1790/2138] eta: 0:16:19 lr: 3.529278391025167e-05 loss: 0.0359 (0.0387) time: 3.2779 data: 0.0026 max mem: 19788 +Epoch: [12] [1800/2138] eta: 0:15:52 lr: 3.5287314280817065e-05 loss: 0.0393 (0.0388) time: 3.1783 data: 0.0029 max mem: 19788 +Epoch: [12] [1810/2138] eta: 0:15:24 lr: 3.528184455718001e-05 loss: 0.0393 (0.0388) time: 3.1720 data: 0.0029 max mem: 19788 +Epoch: [12] [1820/2138] eta: 0:14:57 lr: 3.527637473932266e-05 loss: 0.0356 (0.0388) time: 3.3132 data: 0.0026 max mem: 19788 +Epoch: [12] [1830/2138] eta: 0:14:30 lr: 3.5270904827227154e-05 loss: 0.0315 (0.0387) time: 3.3806 data: 0.0024 max mem: 19788 +Epoch: [12] [1840/2138] eta: 0:14:02 lr: 3.5265434820875644e-05 loss: 0.0315 (0.0387) time: 3.2486 data: 0.0024 max mem: 19788 +Epoch: [12] [1850/2138] eta: 0:13:34 lr: 3.525996472025025e-05 loss: 0.0358 (0.0387) time: 3.1557 data: 0.0023 max mem: 19788 +Epoch: [12] [1860/2138] eta: 0:13:07 lr: 3.525449452533309e-05 loss: 0.0336 (0.0387) time: 3.1882 data: 0.0023 max mem: 19788 +Epoch: [12] [1870/2138] eta: 0:12:39 lr: 3.524902423610629e-05 loss: 0.0342 (0.0387) time: 3.4392 data: 0.0024 max mem: 19788 +Epoch: [12] [1880/2138] eta: 0:12:12 lr: 3.5243553852551964e-05 loss: 0.0324 (0.0387) time: 3.5395 data: 0.0025 max mem: 19788 +Epoch: [12] [1890/2138] eta: 0:11:45 lr: 3.523808337465221e-05 loss: 0.0306 (0.0387) time: 3.5323 data: 0.0024 max mem: 19788 +Epoch: [12] [1900/2138] eta: 0:11:17 lr: 3.523261280238913e-05 loss: 0.0333 (0.0387) time: 3.4106 data: 0.0024 max mem: 19788 +Epoch: [12] [1910/2138] eta: 0:10:48 lr: 3.522714213574482e-05 loss: 0.0325 (0.0387) time: 3.1755 data: 0.0023 max mem: 19788 +Epoch: [12] [1920/2138] eta: 0:10:20 lr: 3.522167137470136e-05 loss: 0.0325 (0.0387) time: 3.1291 data: 0.0026 max mem: 19788 +Epoch: [12] [1930/2138] eta: 0:09:52 lr: 3.521620051924083e-05 loss: 0.0367 (0.0387) time: 3.1373 data: 0.0026 max mem: 19788 +Epoch: [12] [1940/2138] eta: 0:09:24 lr: 3.5210729569345295e-05 loss: 0.0367 (0.0387) time: 3.4079 data: 0.0025 max mem: 19788 +Epoch: [12] [1950/2138] eta: 0:08:57 lr: 3.520525852499684e-05 loss: 0.0359 (0.0386) time: 3.6586 data: 0.0024 max mem: 19788 +Epoch: [12] [1960/2138] eta: 0:08:29 lr: 3.519978738617751e-05 loss: 0.0335 (0.0386) time: 3.5359 data: 0.0024 max mem: 19788 +Epoch: [12] [1970/2138] eta: 0:08:00 lr: 3.5194316152869355e-05 loss: 0.0308 (0.0386) time: 3.3808 data: 0.0023 max mem: 19788 +Epoch: [12] [1980/2138] eta: 0:07:32 lr: 3.5188844825054426e-05 loss: 0.0323 (0.0386) time: 3.2730 data: 0.0025 max mem: 19788 +Epoch: [12] [1990/2138] eta: 0:07:04 lr: 3.518337340271477e-05 loss: 0.0378 (0.0386) time: 3.1793 data: 0.0028 max mem: 19788 +Epoch: [12] [2000/2138] eta: 0:06:35 lr: 3.5177901885832427e-05 loss: 0.0342 (0.0386) time: 3.1618 data: 0.0028 max mem: 19788 +Epoch: [12] [2010/2138] eta: 0:06:07 lr: 3.5172430274389396e-05 loss: 0.0334 (0.0386) time: 3.1270 data: 0.0027 max mem: 19788 +Epoch: [12] [2020/2138] eta: 0:05:38 lr: 3.516695856836771e-05 loss: 0.0358 (0.0386) time: 3.1275 data: 0.0025 max mem: 19788 +Epoch: [12] [2030/2138] eta: 0:05:10 lr: 3.51614867677494e-05 loss: 0.0360 (0.0386) time: 3.1266 data: 0.0023 max mem: 19788 +Epoch: [12] [2040/2138] eta: 0:04:41 lr: 3.515601487251645e-05 loss: 0.0360 (0.0386) time: 3.1001 data: 0.0023 max mem: 19788 +Epoch: [12] [2050/2138] eta: 0:04:12 lr: 3.515054288265087e-05 loss: 0.0428 (0.0386) time: 3.1691 data: 0.0026 max mem: 19788 +Epoch: [12] [2060/2138] eta: 0:03:44 lr: 3.5145070798134645e-05 loss: 0.0387 (0.0386) time: 3.2094 data: 0.0026 max mem: 19788 +Epoch: [12] [2070/2138] eta: 0:03:15 lr: 3.513959861894978e-05 loss: 0.0314 (0.0386) time: 3.2375 data: 0.0024 max mem: 19788 +Epoch: [12] [2080/2138] eta: 0:02:46 lr: 3.513412634507825e-05 loss: 0.0327 (0.0386) time: 3.2047 data: 0.0022 max mem: 19788 +Epoch: [12] [2090/2138] eta: 0:02:18 lr: 3.512865397650203e-05 loss: 0.0367 (0.0386) time: 3.1743 data: 0.0022 max mem: 19788 +Epoch: [12] [2100/2138] eta: 0:01:49 lr: 3.512318151320307e-05 loss: 0.0354 (0.0386) time: 3.2001 data: 0.0022 max mem: 19788 +Epoch: [12] [2110/2138] eta: 0:01:20 lr: 3.511770895516337e-05 loss: 0.0381 (0.0386) time: 3.1517 data: 0.0023 max mem: 19788 +Epoch: [12] [2120/2138] eta: 0:00:51 lr: 3.511223630236485e-05 loss: 0.0424 (0.0386) time: 3.2048 data: 0.0026 max mem: 19788 +Epoch: [12] [2130/2138] eta: 0:00:23 lr: 3.510676355478947e-05 loss: 0.0460 (0.0387) time: 3.2743 data: 0.0026 max mem: 19788 +Epoch: [12] Total time: 1:42:54 +Test: [ 0/21770] eta: 16:30:51 time: 2.7309 data: 2.6371 max mem: 19788 +Test: [ 100/21770] eta: 0:28:06 time: 0.0495 data: 0.0017 max mem: 19788 +Test: [ 200/21770] eta: 0:23:03 time: 0.0437 data: 0.0016 max mem: 19788 +Test: [ 300/21770] eta: 0:20:49 time: 0.0432 data: 0.0016 max mem: 19788 +Test: [ 400/21770] eta: 0:19:33 time: 0.0478 data: 0.0015 max mem: 19788 +Test: [ 500/21770] eta: 0:18:54 time: 0.0536 data: 0.0020 max mem: 19788 +Test: [ 600/21770] eta: 0:18:38 time: 0.0506 data: 0.0018 max mem: 19788 +Test: [ 700/21770] eta: 0:18:25 time: 0.0464 data: 0.0016 max mem: 19788 +Test: [ 800/21770] eta: 0:18:03 time: 0.0518 data: 0.0018 max mem: 19788 +Test: [ 900/21770] eta: 0:17:42 time: 0.0453 data: 0.0015 max mem: 19788 +Test: [ 1000/21770] eta: 0:17:22 time: 0.0436 data: 0.0014 max mem: 19788 +Test: [ 1100/21770] eta: 0:17:04 time: 0.0432 data: 0.0014 max mem: 19788 +Test: [ 1200/21770] eta: 0:16:56 time: 0.0451 data: 0.0020 max mem: 19788 +Test: [ 1300/21770] eta: 0:16:49 time: 0.0437 data: 0.0015 max mem: 19788 +Test: [ 1400/21770] eta: 0:16:42 time: 0.0487 data: 0.0015 max mem: 19788 +Test: [ 1500/21770] eta: 0:16:44 time: 0.0570 data: 0.0021 max mem: 19788 +Test: [ 1600/21770] eta: 0:16:45 time: 0.0504 data: 0.0017 max mem: 19788 +Test: [ 1700/21770] eta: 0:16:39 time: 0.0436 data: 0.0015 max mem: 19788 +Test: [ 1800/21770] eta: 0:16:30 time: 0.0521 data: 0.0017 max mem: 19788 +Test: [ 1900/21770] eta: 0:16:23 time: 0.0429 data: 0.0015 max mem: 19788 +Test: [ 2000/21770] eta: 0:16:14 time: 0.0485 data: 0.0017 max mem: 19788 +Test: [ 2100/21770] eta: 0:16:11 time: 0.0541 data: 0.0020 max mem: 19788 +Test: [ 2200/21770] eta: 0:16:04 time: 0.0449 data: 0.0014 max mem: 19788 +Test: [ 2300/21770] eta: 0:15:54 time: 0.0440 data: 0.0016 max mem: 19788 +Test: [ 2400/21770] eta: 0:15:46 time: 0.0455 data: 0.0014 max mem: 19788 +Test: [ 2500/21770] eta: 0:15:43 time: 0.0534 data: 0.0018 max mem: 19788 +Test: [ 2600/21770] eta: 0:15:37 time: 0.0455 data: 0.0017 max mem: 19788 +Test: [ 2700/21770] eta: 0:15:29 time: 0.0453 data: 0.0016 max mem: 19788 +Test: [ 2800/21770] eta: 0:15:22 time: 0.0456 data: 0.0014 max mem: 19788 +Test: [ 2900/21770] eta: 0:15:17 time: 0.0542 data: 0.0019 max mem: 19788 +Test: [ 3000/21770] eta: 0:15:16 time: 0.0544 data: 0.0019 max mem: 19788 +Test: [ 3100/21770] eta: 0:15:10 time: 0.0454 data: 0.0016 max mem: 19788 +Test: [ 3200/21770] eta: 0:15:04 time: 0.0520 data: 0.0016 max mem: 19788 +Test: [ 3300/21770] eta: 0:14:59 time: 0.0506 data: 0.0016 max mem: 19788 +Test: [ 3400/21770] eta: 0:14:54 time: 0.0473 data: 0.0017 max mem: 19788 +Test: [ 3500/21770] eta: 0:14:51 time: 0.0486 data: 0.0019 max mem: 19788 +Test: [ 3600/21770] eta: 0:14:44 time: 0.0453 data: 0.0019 max mem: 19788 +Test: [ 3700/21770] eta: 0:14:38 time: 0.0440 data: 0.0013 max mem: 19788 +Test: [ 3800/21770] eta: 0:14:32 time: 0.0486 data: 0.0016 max mem: 19788 +Test: [ 3900/21770] eta: 0:14:27 time: 0.0437 data: 0.0016 max mem: 19788 +Test: [ 4000/21770] eta: 0:14:20 time: 0.0447 data: 0.0015 max mem: 19788 +Test: [ 4100/21770] eta: 0:14:15 time: 0.0439 data: 0.0015 max mem: 19788 +Test: [ 4200/21770] eta: 0:14:09 time: 0.0458 data: 0.0015 max mem: 19788 +Test: [ 4300/21770] eta: 0:14:04 time: 0.0437 data: 0.0017 max mem: 19788 +Test: [ 4400/21770] eta: 0:13:58 time: 0.0439 data: 0.0015 max mem: 19788 +Test: [ 4500/21770] eta: 0:13:52 time: 0.0452 data: 0.0015 max mem: 19788 +Test: [ 4600/21770] eta: 0:13:47 time: 0.0528 data: 0.0018 max mem: 19788 +Test: [ 4700/21770] eta: 0:13:42 time: 0.0485 data: 0.0014 max mem: 19788 +Test: [ 4800/21770] eta: 0:13:39 time: 0.0534 data: 0.0018 max mem: 19788 +Test: [ 4900/21770] eta: 0:13:34 time: 0.0459 data: 0.0014 max mem: 19788 +Test: [ 5000/21770] eta: 0:13:28 time: 0.0452 data: 0.0014 max mem: 19788 +Test: [ 5100/21770] eta: 0:13:22 time: 0.0437 data: 0.0014 max mem: 19788 +Test: [ 5200/21770] eta: 0:13:18 time: 0.0520 data: 0.0021 max mem: 19788 +Test: [ 5300/21770] eta: 0:13:12 time: 0.0452 data: 0.0016 max mem: 19788 +Test: [ 5400/21770] eta: 0:13:08 time: 0.0502 data: 0.0018 max mem: 19788 +Test: [ 5500/21770] eta: 0:13:03 time: 0.0491 data: 0.0018 max mem: 19788 +Test: [ 5600/21770] eta: 0:12:59 time: 0.0444 data: 0.0013 max mem: 19788 +Test: [ 5700/21770] eta: 0:12:53 time: 0.0529 data: 0.0017 max mem: 19788 +Test: [ 5800/21770] eta: 0:12:49 time: 0.0438 data: 0.0015 max mem: 19788 +Test: [ 5900/21770] eta: 0:12:45 time: 0.0525 data: 0.0018 max mem: 19788 +Test: [ 6000/21770] eta: 0:12:40 time: 0.0483 data: 0.0016 max mem: 19788 +Test: [ 6100/21770] eta: 0:12:37 time: 0.0546 data: 0.0020 max mem: 19788 +Test: [ 6200/21770] eta: 0:12:32 time: 0.0449 data: 0.0016 max mem: 19788 +Test: [ 6300/21770] eta: 0:12:26 time: 0.0427 data: 0.0014 max mem: 19788 +Test: [ 6400/21770] eta: 0:12:21 time: 0.0436 data: 0.0015 max mem: 19788 +Test: [ 6500/21770] eta: 0:12:15 time: 0.0444 data: 0.0016 max mem: 19788 +Test: [ 6600/21770] eta: 0:12:11 time: 0.0554 data: 0.0018 max mem: 19788 +Test: [ 6700/21770] eta: 0:12:07 time: 0.0442 data: 0.0019 max mem: 19788 +Test: [ 6800/21770] eta: 0:12:03 time: 0.0465 data: 0.0016 max mem: 19788 +Test: [ 6900/21770] eta: 0:11:59 time: 0.0517 data: 0.0019 max mem: 19788 +Test: [ 7000/21770] eta: 0:11:54 time: 0.0473 data: 0.0017 max mem: 19788 +Test: [ 7100/21770] eta: 0:11:50 time: 0.0554 data: 0.0019 max mem: 19788 +Test: [ 7200/21770] eta: 0:11:45 time: 0.0450 data: 0.0017 max mem: 19788 +Test: [ 7300/21770] eta: 0:11:40 time: 0.0438 data: 0.0015 max mem: 19788 +Test: [ 7400/21770] eta: 0:11:35 time: 0.0448 data: 0.0016 max mem: 19788 +Test: [ 7500/21770] eta: 0:11:30 time: 0.0552 data: 0.0019 max mem: 19788 +Test: [ 7600/21770] eta: 0:11:26 time: 0.0442 data: 0.0016 max mem: 19788 +Test: [ 7700/21770] eta: 0:11:21 time: 0.0441 data: 0.0016 max mem: 19788 +Test: [ 7800/21770] eta: 0:11:16 time: 0.0469 data: 0.0015 max mem: 19788 +Test: [ 7900/21770] eta: 0:11:11 time: 0.0496 data: 0.0017 max mem: 19788 +Test: [ 8000/21770] eta: 0:11:06 time: 0.0545 data: 0.0018 max mem: 19788 +Test: [ 8100/21770] eta: 0:11:02 time: 0.0434 data: 0.0016 max mem: 19788 +Test: [ 8200/21770] eta: 0:10:56 time: 0.0439 data: 0.0014 max mem: 19788 +Test: [ 8300/21770] eta: 0:10:51 time: 0.0441 data: 0.0016 max mem: 19788 +Test: [ 8400/21770] eta: 0:10:46 time: 0.0452 data: 0.0015 max mem: 19788 +Test: [ 8500/21770] eta: 0:10:40 time: 0.0453 data: 0.0016 max mem: 19788 +Test: [ 8600/21770] eta: 0:10:35 time: 0.0443 data: 0.0016 max mem: 19788 +Test: [ 8700/21770] eta: 0:10:30 time: 0.0538 data: 0.0019 max mem: 19788 +Test: [ 8800/21770] eta: 0:10:26 time: 0.0433 data: 0.0016 max mem: 19788 +Test: [ 8900/21770] eta: 0:10:21 time: 0.0534 data: 0.0018 max mem: 19788 +Test: [ 9000/21770] eta: 0:10:16 time: 0.0434 data: 0.0016 max mem: 19788 +Test: [ 9100/21770] eta: 0:10:11 time: 0.0479 data: 0.0016 max mem: 19788 +Test: [ 9200/21770] eta: 0:10:05 time: 0.0447 data: 0.0014 max mem: 19788 +Test: [ 9300/21770] eta: 0:10:01 time: 0.0536 data: 0.0020 max mem: 19788 +Test: [ 9400/21770] eta: 0:09:56 time: 0.0438 data: 0.0016 max mem: 19788 +Test: [ 9500/21770] eta: 0:09:52 time: 0.0507 data: 0.0017 max mem: 19788 +Test: [ 9600/21770] eta: 0:09:46 time: 0.0441 data: 0.0015 max mem: 19788 +Test: [ 9700/21770] eta: 0:09:41 time: 0.0550 data: 0.0019 max mem: 19788 +Test: [ 9800/21770] eta: 0:09:37 time: 0.0529 data: 0.0019 max mem: 19788 +Test: [ 9900/21770] eta: 0:09:32 time: 0.0540 data: 0.0020 max mem: 19788 +Test: [10000/21770] eta: 0:09:27 time: 0.0448 data: 0.0016 max mem: 19788 +Test: [10100/21770] eta: 0:09:23 time: 0.0459 data: 0.0017 max mem: 19788 +Test: [10200/21770] eta: 0:09:18 time: 0.0527 data: 0.0019 max mem: 19788 +Test: [10300/21770] eta: 0:09:13 time: 0.0464 data: 0.0016 max mem: 19788 +Test: [10400/21770] eta: 0:09:08 time: 0.0455 data: 0.0015 max mem: 19788 +Test: [10500/21770] eta: 0:09:03 time: 0.0444 data: 0.0016 max mem: 19788 +Test: [10600/21770] eta: 0:08:57 time: 0.0469 data: 0.0016 max mem: 19788 +Test: [10700/21770] eta: 0:08:53 time: 0.0557 data: 0.0014 max mem: 19788 +Test: [10800/21770] eta: 0:08:48 time: 0.0453 data: 0.0015 max mem: 19788 +Test: [10900/21770] eta: 0:08:43 time: 0.0541 data: 0.0019 max mem: 19788 +Test: [11000/21770] eta: 0:08:39 time: 0.0518 data: 0.0019 max mem: 19788 +Test: [11100/21770] eta: 0:08:34 time: 0.0443 data: 0.0015 max mem: 19788 +Test: [11200/21770] eta: 0:08:29 time: 0.0448 data: 0.0019 max mem: 19788 +Test: [11300/21770] eta: 0:08:24 time: 0.0447 data: 0.0015 max mem: 19788 +Test: [11400/21770] eta: 0:08:19 time: 0.0505 data: 0.0020 max mem: 19788 +Test: [11500/21770] eta: 0:08:15 time: 0.0478 data: 0.0015 max mem: 19788 +Test: [11600/21770] eta: 0:08:10 time: 0.0441 data: 0.0014 max mem: 19788 +Test: [11700/21770] eta: 0:08:05 time: 0.0542 data: 0.0019 max mem: 19788 +Test: [11800/21770] eta: 0:08:00 time: 0.0566 data: 0.0017 max mem: 19788 +Test: [11900/21770] eta: 0:07:55 time: 0.0452 data: 0.0016 max mem: 19788 +Test: [12000/21770] eta: 0:07:50 time: 0.0457 data: 0.0015 max mem: 19788 +Test: [12100/21770] eta: 0:07:46 time: 0.0498 data: 0.0019 max mem: 19788 +Test: [12200/21770] eta: 0:07:41 time: 0.0488 data: 0.0017 max mem: 19788 +Test: [12300/21770] eta: 0:07:36 time: 0.0466 data: 0.0015 max mem: 19788 +Test: [12400/21770] eta: 0:07:31 time: 0.0486 data: 0.0018 max mem: 19788 +Test: [12500/21770] eta: 0:07:27 time: 0.0494 data: 0.0018 max mem: 19788 +Test: [12600/21770] eta: 0:07:22 time: 0.0466 data: 0.0017 max mem: 19788 +Test: [12700/21770] eta: 0:07:17 time: 0.0548 data: 0.0020 max mem: 19788 +Test: [12800/21770] eta: 0:07:12 time: 0.0480 data: 0.0016 max mem: 19788 +Test: [12900/21770] eta: 0:07:07 time: 0.0454 data: 0.0016 max mem: 19788 +Test: [13000/21770] eta: 0:07:02 time: 0.0433 data: 0.0015 max mem: 19788 +Test: [13100/21770] eta: 0:06:58 time: 0.0450 data: 0.0014 max mem: 19788 +Test: [13200/21770] eta: 0:06:53 time: 0.0452 data: 0.0017 max mem: 19788 +Test: [13300/21770] eta: 0:06:48 time: 0.0476 data: 0.0018 max mem: 19788 +Test: [13400/21770] eta: 0:06:43 time: 0.0538 data: 0.0016 max mem: 19788 +Test: [13500/21770] eta: 0:06:38 time: 0.0544 data: 0.0019 max mem: 19788 +Test: [13600/21770] eta: 0:06:34 time: 0.0456 data: 0.0018 max mem: 19788 +Test: [13700/21770] eta: 0:06:29 time: 0.0441 data: 0.0016 max mem: 19788 +Test: [13800/21770] eta: 0:06:24 time: 0.0455 data: 0.0016 max mem: 19788 +Test: [13900/21770] eta: 0:06:19 time: 0.0464 data: 0.0017 max mem: 19788 +Test: [14000/21770] eta: 0:06:15 time: 0.0548 data: 0.0019 max mem: 19788 +Test: [14100/21770] eta: 0:06:10 time: 0.0540 data: 0.0019 max mem: 19788 +Test: [14200/21770] eta: 0:06:05 time: 0.0477 data: 0.0017 max mem: 19788 +Test: [14300/21770] eta: 0:06:00 time: 0.0529 data: 0.0019 max mem: 19788 +Test: [14400/21770] eta: 0:05:55 time: 0.0444 data: 0.0015 max mem: 19788 +Test: [14500/21770] eta: 0:05:51 time: 0.0522 data: 0.0019 max mem: 19788 +Test: [14600/21770] eta: 0:05:46 time: 0.0479 data: 0.0016 max mem: 19788 +Test: [14700/21770] eta: 0:05:41 time: 0.0463 data: 0.0017 max mem: 19788 +Test: [14800/21770] eta: 0:05:36 time: 0.0458 data: 0.0015 max mem: 19788 +Test: [14900/21770] eta: 0:05:32 time: 0.0456 data: 0.0018 max mem: 19788 +Test: [15000/21770] eta: 0:05:27 time: 0.0486 data: 0.0017 max mem: 19788 +Test: [15100/21770] eta: 0:05:22 time: 0.0451 data: 0.0017 max mem: 19788 +Test: [15200/21770] eta: 0:05:17 time: 0.0550 data: 0.0017 max mem: 19788 +Test: [15300/21770] eta: 0:05:12 time: 0.0458 data: 0.0015 max mem: 19788 +Test: [15400/21770] eta: 0:05:07 time: 0.0458 data: 0.0016 max mem: 19788 +Test: [15500/21770] eta: 0:05:02 time: 0.0453 data: 0.0015 max mem: 19788 +Test: [15600/21770] eta: 0:04:58 time: 0.0447 data: 0.0015 max mem: 19788 +Test: [15700/21770] eta: 0:04:53 time: 0.0443 data: 0.0016 max mem: 19788 +Test: [15800/21770] eta: 0:04:48 time: 0.0535 data: 0.0019 max mem: 19788 +Test: [15900/21770] eta: 0:04:43 time: 0.0454 data: 0.0018 max mem: 19788 +Test: [16000/21770] eta: 0:04:38 time: 0.0512 data: 0.0019 max mem: 19788 +Test: [16100/21770] eta: 0:04:34 time: 0.0537 data: 0.0018 max mem: 19788 +Test: [16200/21770] eta: 0:04:29 time: 0.0440 data: 0.0017 max mem: 19788 +Test: [16300/21770] eta: 0:04:24 time: 0.0439 data: 0.0016 max mem: 19788 +Test: [16400/21770] eta: 0:04:19 time: 0.0546 data: 0.0018 max mem: 19788 +Test: [16500/21770] eta: 0:04:14 time: 0.0448 data: 0.0017 max mem: 19788 +Test: [16600/21770] eta: 0:04:09 time: 0.0503 data: 0.0017 max mem: 19788 +Test: [16700/21770] eta: 0:04:05 time: 0.0493 data: 0.0017 max mem: 19788 +Test: [16800/21770] eta: 0:04:00 time: 0.0449 data: 0.0014 max mem: 19788 +Test: [16900/21770] eta: 0:03:55 time: 0.0443 data: 0.0015 max mem: 19788 +Test: [17000/21770] eta: 0:03:50 time: 0.0434 data: 0.0014 max mem: 19788 +Test: [17100/21770] eta: 0:03:45 time: 0.0444 data: 0.0015 max mem: 19788 +Test: [17200/21770] eta: 0:03:40 time: 0.0472 data: 0.0016 max mem: 19788 +Test: [17300/21770] eta: 0:03:35 time: 0.0542 data: 0.0020 max mem: 19788 +Test: [17400/21770] eta: 0:03:31 time: 0.0445 data: 0.0015 max mem: 19788 +Test: [17500/21770] eta: 0:03:26 time: 0.0501 data: 0.0019 max mem: 19788 +Test: [17600/21770] eta: 0:03:21 time: 0.0441 data: 0.0016 max mem: 19788 +Test: [17700/21770] eta: 0:03:16 time: 0.0509 data: 0.0018 max mem: 19788 +Test: [17800/21770] eta: 0:03:11 time: 0.0426 data: 0.0015 max mem: 19788 +Test: [17900/21770] eta: 0:03:06 time: 0.0442 data: 0.0015 max mem: 19788 +Test: [18000/21770] eta: 0:03:01 time: 0.0461 data: 0.0017 max mem: 19788 +Test: [18100/21770] eta: 0:02:57 time: 0.0520 data: 0.0019 max mem: 19788 +Test: [18200/21770] eta: 0:02:52 time: 0.0561 data: 0.0017 max mem: 19788 +Test: [18300/21770] eta: 0:02:47 time: 0.0541 data: 0.0019 max mem: 19788 +Test: [18400/21770] eta: 0:02:42 time: 0.0451 data: 0.0016 max mem: 19788 +Test: [18500/21770] eta: 0:02:37 time: 0.0444 data: 0.0016 max mem: 19788 +Test: [18600/21770] eta: 0:02:33 time: 0.0470 data: 0.0015 max mem: 19788 +Test: [18700/21770] eta: 0:02:28 time: 0.0533 data: 0.0019 max mem: 19788 +Test: [18800/21770] eta: 0:02:23 time: 0.0444 data: 0.0014 max mem: 19788 +Test: [18900/21770] eta: 0:02:18 time: 0.0479 data: 0.0015 max mem: 19788 +Test: [19000/21770] eta: 0:02:13 time: 0.0490 data: 0.0018 max mem: 19788 +Test: [19100/21770] eta: 0:02:08 time: 0.0434 data: 0.0015 max mem: 19788 +Test: [19200/21770] eta: 0:02:04 time: 0.0539 data: 0.0019 max mem: 19788 +Test: [19300/21770] eta: 0:01:59 time: 0.0491 data: 0.0018 max mem: 19788 +Test: [19400/21770] eta: 0:01:54 time: 0.0469 data: 0.0017 max mem: 19788 +Test: [19500/21770] eta: 0:01:49 time: 0.0449 data: 0.0015 max mem: 19788 +Test: [19600/21770] eta: 0:01:44 time: 0.0480 data: 0.0017 max mem: 19788 +Test: [19700/21770] eta: 0:01:40 time: 0.0481 data: 0.0018 max mem: 19788 +Test: [19800/21770] eta: 0:01:35 time: 0.0543 data: 0.0020 max mem: 19788 +Test: [19900/21770] eta: 0:01:30 time: 0.0445 data: 0.0017 max mem: 19788 +Test: [20000/21770] eta: 0:01:25 time: 0.0445 data: 0.0015 max mem: 19788 +Test: [20100/21770] eta: 0:01:20 time: 0.0524 data: 0.0019 max mem: 19788 +Test: [20200/21770] eta: 0:01:15 time: 0.0441 data: 0.0017 max mem: 19788 +Test: [20300/21770] eta: 0:01:11 time: 0.0472 data: 0.0017 max mem: 19788 +Test: [20400/21770] eta: 0:01:06 time: 0.0535 data: 0.0019 max mem: 19788 +Test: [20500/21770] eta: 0:01:01 time: 0.0522 data: 0.0018 max mem: 19788 +Test: [20600/21770] eta: 0:00:56 time: 0.0457 data: 0.0015 max mem: 19788 +Test: [20700/21770] eta: 0:00:51 time: 0.0508 data: 0.0016 max mem: 19788 +Test: [20800/21770] eta: 0:00:46 time: 0.0441 data: 0.0015 max mem: 19788 +Test: [20900/21770] eta: 0:00:42 time: 0.0539 data: 0.0019 max mem: 19788 +Test: [21000/21770] eta: 0:00:37 time: 0.0511 data: 0.0017 max mem: 19788 +Test: [21100/21770] eta: 0:00:32 time: 0.0566 data: 0.0016 max mem: 19788 +Test: [21200/21770] eta: 0:00:27 time: 0.0540 data: 0.0019 max mem: 19788 +Test: [21300/21770] eta: 0:00:22 time: 0.0453 data: 0.0016 max mem: 19788 +Test: [21400/21770] eta: 0:00:17 time: 0.0541 data: 0.0019 max mem: 19788 +Test: [21500/21770] eta: 0:00:13 time: 0.0523 data: 0.0018 max mem: 19788 +Test: [21600/21770] eta: 0:00:08 time: 0.0454 data: 0.0015 max mem: 19788 +Test: [21700/21770] eta: 0:00:03 time: 0.0463 data: 0.0017 max mem: 19788 +Test: Total time: 0:17:34 +Final results: +Mean IoU is 62.97 + + precision@0.5 = 70.00 + precision@0.6 = 64.00 + precision@0.7 = 56.81 + precision@0.8 = 46.01 + precision@0.9 = 22.90 + overall IoU = 63.35 + mean IoU = 62.97 + +Mean accuracy for one-to-zero sample is 81.13 + +Average object IoU 0.6297294124867199 +Overall IoU 63.34535217285156 +Epoch: [13] [ 0/2138] eta: 13:00:31 lr: 3.5102385288477694e-05 loss: 0.0458 (0.0458) time: 21.9043 data: 1.5608 max mem: 19788 +Epoch: [13] [ 10/2138] eta: 2:53:15 lr: 3.5096912370258456e-05 loss: 0.0375 (0.0396) time: 4.8850 data: 0.1439 max mem: 19788 +Epoch: [13] [ 20/2138] eta: 2:24:56 lr: 3.509143935721177e-05 loss: 0.0330 (0.0371) time: 3.2161 data: 0.0021 max mem: 19788 +Epoch: [13] [ 30/2138] eta: 2:14:57 lr: 3.508596624931958e-05 loss: 0.0376 (0.0380) time: 3.2675 data: 0.0022 max mem: 19788 +Epoch: [13] [ 40/2138] eta: 2:08:42 lr: 3.508049304656379e-05 loss: 0.0377 (0.0381) time: 3.2345 data: 0.0024 max mem: 19788 +Epoch: [13] [ 50/2138] eta: 2:04:19 lr: 3.507501974892631e-05 loss: 0.0377 (0.0381) time: 3.1560 data: 0.0025 max mem: 19788 +Epoch: [13] [ 60/2138] eta: 2:01:24 lr: 3.506954635638904e-05 loss: 0.0388 (0.0395) time: 3.1463 data: 0.0025 max mem: 19788 +Epoch: [13] [ 70/2138] eta: 2:01:11 lr: 3.5064072868933884e-05 loss: 0.0368 (0.0396) time: 3.3720 data: 0.0023 max mem: 19788 +Epoch: [13] [ 80/2138] eta: 2:00:28 lr: 3.505859928654273e-05 loss: 0.0337 (0.0392) time: 3.5329 data: 0.0024 max mem: 19788 +Epoch: [13] [ 90/2138] eta: 1:58:58 lr: 3.505312560919746e-05 loss: 0.0317 (0.0387) time: 3.3772 data: 0.0024 max mem: 19788 +Epoch: [13] [ 100/2138] eta: 1:57:23 lr: 3.5047651836879956e-05 loss: 0.0321 (0.0387) time: 3.2270 data: 0.0024 max mem: 19788 +Epoch: [13] [ 110/2138] eta: 1:56:08 lr: 3.504217796957209e-05 loss: 0.0343 (0.0386) time: 3.2102 data: 0.0024 max mem: 19788 +Epoch: [13] [ 120/2138] eta: 1:54:38 lr: 3.503670400725572e-05 loss: 0.0321 (0.0380) time: 3.1692 data: 0.0026 max mem: 19788 +Epoch: [13] [ 130/2138] eta: 1:53:18 lr: 3.5031229949912705e-05 loss: 0.0317 (0.0377) time: 3.1071 data: 0.0025 max mem: 19788 +Epoch: [13] [ 140/2138] eta: 1:52:47 lr: 3.502575579752489e-05 loss: 0.0338 (0.0377) time: 3.2596 data: 0.0025 max mem: 19788 +Epoch: [13] [ 150/2138] eta: 1:51:51 lr: 3.5020281550074135e-05 loss: 0.0337 (0.0376) time: 3.3107 data: 0.0024 max mem: 19788 +Epoch: [13] [ 160/2138] eta: 1:51:00 lr: 3.5014807207542264e-05 loss: 0.0354 (0.0375) time: 3.2276 data: 0.0023 max mem: 19788 +Epoch: [13] [ 170/2138] eta: 1:50:10 lr: 3.500933276991111e-05 loss: 0.0373 (0.0376) time: 3.2303 data: 0.0024 max mem: 19788 +Epoch: [13] [ 180/2138] eta: 1:49:10 lr: 3.5003858237162494e-05 loss: 0.0340 (0.0373) time: 3.1671 data: 0.0027 max mem: 19788 +Epoch: [13] [ 190/2138] eta: 1:48:15 lr: 3.499838360927825e-05 loss: 0.0302 (0.0369) time: 3.1240 data: 0.0028 max mem: 19788 +Epoch: [13] [ 200/2138] eta: 1:47:40 lr: 3.4992908886240175e-05 loss: 0.0302 (0.0367) time: 3.2273 data: 0.0025 max mem: 19788 +Epoch: [13] [ 210/2138] eta: 1:47:13 lr: 3.498743406803008e-05 loss: 0.0308 (0.0366) time: 3.3619 data: 0.0024 max mem: 19788 +Epoch: [13] [ 220/2138] eta: 1:46:19 lr: 3.4981959154629753e-05 loss: 0.0313 (0.0365) time: 3.2520 data: 0.0024 max mem: 19788 +Epoch: [13] [ 230/2138] eta: 1:45:47 lr: 3.4976484146020995e-05 loss: 0.0313 (0.0365) time: 3.2232 data: 0.0025 max mem: 19788 +Epoch: [13] [ 240/2138] eta: 1:44:57 lr: 3.497100904218558e-05 loss: 0.0342 (0.0365) time: 3.2255 data: 0.0023 max mem: 19788 +Epoch: [13] [ 250/2138] eta: 1:44:11 lr: 3.4965533843105296e-05 loss: 0.0330 (0.0364) time: 3.1315 data: 0.0024 max mem: 19788 +Epoch: [13] [ 260/2138] eta: 1:43:49 lr: 3.496005854876191e-05 loss: 0.0292 (0.0363) time: 3.3080 data: 0.0024 max mem: 19788 +Epoch: [13] [ 270/2138] eta: 1:43:11 lr: 3.4954583159137195e-05 loss: 0.0326 (0.0362) time: 3.3541 data: 0.0024 max mem: 19788 +Epoch: [13] [ 280/2138] eta: 1:42:32 lr: 3.49491076742129e-05 loss: 0.0322 (0.0360) time: 3.2376 data: 0.0027 max mem: 19788 +Epoch: [13] [ 290/2138] eta: 1:41:47 lr: 3.4943632093970766e-05 loss: 0.0322 (0.0363) time: 3.1712 data: 0.0028 max mem: 19788 +Epoch: [13] [ 300/2138] eta: 1:41:12 lr: 3.493815641839255e-05 loss: 0.0403 (0.0365) time: 3.2013 data: 0.0025 max mem: 19788 +Epoch: [13] [ 310/2138] eta: 1:40:31 lr: 3.493268064746001e-05 loss: 0.0335 (0.0364) time: 3.2236 data: 0.0023 max mem: 19788 +Epoch: [13] [ 320/2138] eta: 1:39:48 lr: 3.4927204781154835e-05 loss: 0.0306 (0.0364) time: 3.1398 data: 0.0027 max mem: 19788 +Epoch: [13] [ 330/2138] eta: 1:39:19 lr: 3.492172881945878e-05 loss: 0.0376 (0.0366) time: 3.2492 data: 0.0029 max mem: 19788 +Epoch: [13] [ 340/2138] eta: 1:38:41 lr: 3.4916252762353544e-05 loss: 0.0442 (0.0370) time: 3.2816 data: 0.0029 max mem: 19788 +Epoch: [13] [ 350/2138] eta: 1:37:55 lr: 3.4910776609820854e-05 loss: 0.0360 (0.0368) time: 3.1143 data: 0.0028 max mem: 19788 +Epoch: [13] [ 360/2138] eta: 1:37:13 lr: 3.4905300361842405e-05 loss: 0.0360 (0.0369) time: 3.0749 data: 0.0025 max mem: 19788 +Epoch: [13] [ 370/2138] eta: 1:36:33 lr: 3.489982401839989e-05 loss: 0.0370 (0.0369) time: 3.1130 data: 0.0029 max mem: 19788 +Epoch: [13] [ 380/2138] eta: 1:35:55 lr: 3.489434757947502e-05 loss: 0.0352 (0.0369) time: 3.1467 data: 0.0033 max mem: 19788 +Epoch: [13] [ 390/2138] eta: 1:35:21 lr: 3.4888871045049466e-05 loss: 0.0311 (0.0368) time: 3.2021 data: 0.0027 max mem: 19788 +Epoch: [13] [ 400/2138] eta: 1:34:41 lr: 3.488339441510489e-05 loss: 0.0352 (0.0370) time: 3.1736 data: 0.0022 max mem: 19788 +Epoch: [13] [ 410/2138] eta: 1:34:02 lr: 3.4877917689622994e-05 loss: 0.0335 (0.0368) time: 3.1222 data: 0.0022 max mem: 19788 +Epoch: [13] [ 420/2138] eta: 1:33:30 lr: 3.487244086858542e-05 loss: 0.0278 (0.0369) time: 3.2027 data: 0.0022 max mem: 19788 +Epoch: [13] [ 430/2138] eta: 1:32:55 lr: 3.486696395197383e-05 loss: 0.0385 (0.0370) time: 3.2443 data: 0.0022 max mem: 19788 +Epoch: [13] [ 440/2138] eta: 1:32:23 lr: 3.486148693976989e-05 loss: 0.0358 (0.0371) time: 3.2441 data: 0.0022 max mem: 19788 +Epoch: [13] [ 450/2138] eta: 1:31:46 lr: 3.4856009831955216e-05 loss: 0.0339 (0.0371) time: 3.2087 data: 0.0024 max mem: 19788 +Epoch: [13] [ 460/2138] eta: 1:31:10 lr: 3.4850532628511466e-05 loss: 0.0343 (0.0371) time: 3.1609 data: 0.0024 max mem: 19788 +Epoch: [13] [ 470/2138] eta: 1:30:35 lr: 3.4845055329420274e-05 loss: 0.0343 (0.0371) time: 3.1823 data: 0.0024 max mem: 19788 +Epoch: [13] [ 480/2138] eta: 1:30:03 lr: 3.4839577934663244e-05 loss: 0.0414 (0.0372) time: 3.2355 data: 0.0027 max mem: 19788 +Epoch: [13] [ 490/2138] eta: 1:29:28 lr: 3.4834100444222e-05 loss: 0.0387 (0.0372) time: 3.2283 data: 0.0027 max mem: 19788 +Epoch: [13] [ 500/2138] eta: 1:28:57 lr: 3.482862285807816e-05 loss: 0.0317 (0.0374) time: 3.2407 data: 0.0024 max mem: 19788 +Epoch: [13] [ 510/2138] eta: 1:28:25 lr: 3.482314517621333e-05 loss: 0.0317 (0.0374) time: 3.2876 data: 0.0026 max mem: 19788 +Epoch: [13] [ 520/2138] eta: 1:27:48 lr: 3.48176673986091e-05 loss: 0.0346 (0.0375) time: 3.1933 data: 0.0028 max mem: 19788 +Epoch: [13] [ 530/2138] eta: 1:27:12 lr: 3.481218952524704e-05 loss: 0.0370 (0.0375) time: 3.1290 data: 0.0027 max mem: 19788 +Epoch: [13] [ 540/2138] eta: 1:26:42 lr: 3.480671155610877e-05 loss: 0.0346 (0.0374) time: 3.2386 data: 0.0025 max mem: 19788 +Epoch: [13] [ 550/2138] eta: 1:26:05 lr: 3.480123349117586e-05 loss: 0.0346 (0.0374) time: 3.2339 data: 0.0025 max mem: 19788 +Epoch: [13] [ 560/2138] eta: 1:25:29 lr: 3.479575533042985e-05 loss: 0.0365 (0.0374) time: 3.1193 data: 0.0027 max mem: 19788 +Epoch: [13] [ 570/2138] eta: 1:24:59 lr: 3.479027707385233e-05 loss: 0.0365 (0.0374) time: 3.2325 data: 0.0028 max mem: 19788 +Epoch: [13] [ 580/2138] eta: 1:24:29 lr: 3.4784798721424846e-05 loss: 0.0365 (0.0375) time: 3.3381 data: 0.0026 max mem: 19788 +Epoch: [13] [ 590/2138] eta: 1:23:54 lr: 3.477932027312896e-05 loss: 0.0338 (0.0375) time: 3.2438 data: 0.0025 max mem: 19788 +Epoch: [13] [ 600/2138] eta: 1:23:19 lr: 3.4773841728946195e-05 loss: 0.0332 (0.0375) time: 3.1553 data: 0.0027 max mem: 19788 +Epoch: [13] [ 610/2138] eta: 1:22:48 lr: 3.47683630888581e-05 loss: 0.0332 (0.0374) time: 3.2383 data: 0.0027 max mem: 19788 +Epoch: [13] [ 620/2138] eta: 1:22:15 lr: 3.4762884352846206e-05 loss: 0.0373 (0.0375) time: 3.2736 data: 0.0024 max mem: 19788 +Epoch: [13] [ 630/2138] eta: 1:21:40 lr: 3.4757405520892026e-05 loss: 0.0387 (0.0376) time: 3.1892 data: 0.0023 max mem: 19788 +Epoch: [13] [ 640/2138] eta: 1:21:13 lr: 3.4751926592977076e-05 loss: 0.0348 (0.0376) time: 3.3201 data: 0.0024 max mem: 19788 +Epoch: [13] [ 650/2138] eta: 1:20:39 lr: 3.4746447569082865e-05 loss: 0.0340 (0.0375) time: 3.3301 data: 0.0024 max mem: 19788 +Epoch: [13] [ 660/2138] eta: 1:20:03 lr: 3.474096844919091e-05 loss: 0.0326 (0.0376) time: 3.1456 data: 0.0024 max mem: 19788 +Epoch: [13] [ 670/2138] eta: 1:19:27 lr: 3.473548923328269e-05 loss: 0.0320 (0.0376) time: 3.1094 data: 0.0027 max mem: 19788 +Epoch: [13] [ 680/2138] eta: 1:18:51 lr: 3.473000992133969e-05 loss: 0.0265 (0.0374) time: 3.0770 data: 0.0027 max mem: 19788 +Epoch: [13] [ 690/2138] eta: 1:18:14 lr: 3.472453051334341e-05 loss: 0.0274 (0.0375) time: 3.0448 data: 0.0025 max mem: 19788 +Epoch: [13] [ 700/2138] eta: 1:17:38 lr: 3.4719051009275306e-05 loss: 0.0324 (0.0374) time: 3.0646 data: 0.0024 max mem: 19788 +Epoch: [13] [ 710/2138] eta: 1:17:09 lr: 3.4713571409116846e-05 loss: 0.0324 (0.0374) time: 3.2420 data: 0.0025 max mem: 19788 +Epoch: [13] [ 720/2138] eta: 1:16:38 lr: 3.470809171284951e-05 loss: 0.0361 (0.0373) time: 3.3482 data: 0.0026 max mem: 19788 +Epoch: [13] [ 730/2138] eta: 1:16:05 lr: 3.470261192045474e-05 loss: 0.0366 (0.0373) time: 3.2563 data: 0.0024 max mem: 19788 +Epoch: [13] [ 740/2138] eta: 1:15:33 lr: 3.4697132031913977e-05 loss: 0.0371 (0.0374) time: 3.2564 data: 0.0026 max mem: 19788 +Epoch: [13] [ 750/2138] eta: 1:15:00 lr: 3.4691652047208664e-05 loss: 0.0358 (0.0374) time: 3.2384 data: 0.0028 max mem: 19788 +Epoch: [13] [ 760/2138] eta: 1:14:26 lr: 3.4686171966320246e-05 loss: 0.0347 (0.0375) time: 3.1707 data: 0.0026 max mem: 19788 +Epoch: [13] [ 770/2138] eta: 1:13:56 lr: 3.468069178923015e-05 loss: 0.0331 (0.0374) time: 3.2791 data: 0.0024 max mem: 19788 +Epoch: [13] [ 780/2138] eta: 1:13:26 lr: 3.467521151591978e-05 loss: 0.0305 (0.0374) time: 3.3854 data: 0.0024 max mem: 19788 +Epoch: [13] [ 790/2138] eta: 1:12:53 lr: 3.4669731146370555e-05 loss: 0.0300 (0.0374) time: 3.2796 data: 0.0027 max mem: 19788 +Epoch: [13] [ 800/2138] eta: 1:12:21 lr: 3.4664250680563884e-05 loss: 0.0333 (0.0374) time: 3.2528 data: 0.0027 max mem: 19788 +Epoch: [13] [ 810/2138] eta: 1:11:47 lr: 3.465877011848117e-05 loss: 0.0352 (0.0373) time: 3.2267 data: 0.0026 max mem: 19788 +Epoch: [13] [ 820/2138] eta: 1:11:18 lr: 3.46532894601038e-05 loss: 0.0342 (0.0373) time: 3.2874 data: 0.0027 max mem: 19788 +Epoch: [13] [ 830/2138] eta: 1:10:51 lr: 3.4647808705413164e-05 loss: 0.0314 (0.0373) time: 3.5315 data: 0.0025 max mem: 19788 +Epoch: [13] [ 840/2138] eta: 1:10:16 lr: 3.4642327854390634e-05 loss: 0.0399 (0.0373) time: 3.3420 data: 0.0026 max mem: 19788 +Epoch: [13] [ 850/2138] eta: 1:09:45 lr: 3.463684690701759e-05 loss: 0.0383 (0.0373) time: 3.2026 data: 0.0030 max mem: 19788 +Epoch: [13] [ 860/2138] eta: 1:09:14 lr: 3.4631365863275386e-05 loss: 0.0335 (0.0373) time: 3.3588 data: 0.0029 max mem: 19788 +Epoch: [13] [ 870/2138] eta: 1:08:40 lr: 3.462588472314539e-05 loss: 0.0325 (0.0373) time: 3.2555 data: 0.0025 max mem: 19788 +Epoch: [13] [ 880/2138] eta: 1:08:09 lr: 3.462040348660895e-05 loss: 0.0372 (0.0373) time: 3.2352 data: 0.0022 max mem: 19788 +Epoch: [13] [ 890/2138] eta: 1:07:37 lr: 3.461492215364742e-05 loss: 0.0357 (0.0373) time: 3.3112 data: 0.0026 max mem: 19788 +Epoch: [13] [ 900/2138] eta: 1:07:01 lr: 3.4609440724242115e-05 loss: 0.0323 (0.0373) time: 3.1532 data: 0.0028 max mem: 19788 +Epoch: [13] [ 910/2138] eta: 1:06:29 lr: 3.460395919837438e-05 loss: 0.0324 (0.0372) time: 3.1510 data: 0.0027 max mem: 19788 +Epoch: [13] [ 920/2138] eta: 1:05:57 lr: 3.459847757602554e-05 loss: 0.0324 (0.0371) time: 3.2700 data: 0.0028 max mem: 19788 +Epoch: [13] [ 930/2138] eta: 1:05:26 lr: 3.459299585717692e-05 loss: 0.0359 (0.0372) time: 3.3052 data: 0.0029 max mem: 19788 +Epoch: [13] [ 940/2138] eta: 1:05:02 lr: 3.45875140418098e-05 loss: 0.0382 (0.0372) time: 3.6706 data: 0.0028 max mem: 19788 +Epoch: [13] [ 950/2138] eta: 1:04:26 lr: 3.458203212990551e-05 loss: 0.0345 (0.0371) time: 3.4863 data: 0.0026 max mem: 19788 +Epoch: [13] [ 960/2138] eta: 1:03:53 lr: 3.457655012144534e-05 loss: 0.0344 (0.0372) time: 3.0923 data: 0.0027 max mem: 19788 +Epoch: [13] [ 970/2138] eta: 1:03:26 lr: 3.4571068016410576e-05 loss: 0.0354 (0.0372) time: 3.4583 data: 0.0028 max mem: 19788 +Epoch: [13] [ 980/2138] eta: 1:02:51 lr: 3.45655858147825e-05 loss: 0.0336 (0.0372) time: 3.3654 data: 0.0027 max mem: 19788 +Epoch: [13] [ 990/2138] eta: 1:02:16 lr: 3.4560103516542385e-05 loss: 0.0332 (0.0371) time: 3.0551 data: 0.0028 max mem: 19788 +Epoch: [13] [1000/2138] eta: 1:01:50 lr: 3.455462112167151e-05 loss: 0.0307 (0.0371) time: 3.4269 data: 0.0026 max mem: 19788 +Epoch: [13] [1010/2138] eta: 1:01:19 lr: 3.4549138630151125e-05 loss: 0.0343 (0.0371) time: 3.6181 data: 0.0024 max mem: 19788 +Epoch: [13] [1020/2138] eta: 1:00:46 lr: 3.4543656041962485e-05 loss: 0.0354 (0.0371) time: 3.3564 data: 0.0028 max mem: 19788 +Epoch: [13] [1030/2138] eta: 1:00:17 lr: 3.4538173357086844e-05 loss: 0.0293 (0.0371) time: 3.4139 data: 0.0027 max mem: 19788 +Epoch: [13] [1040/2138] eta: 0:59:44 lr: 3.453269057550544e-05 loss: 0.0311 (0.0371) time: 3.3776 data: 0.0026 max mem: 19788 +Epoch: [13] [1050/2138] eta: 0:59:12 lr: 3.452720769719951e-05 loss: 0.0329 (0.0371) time: 3.2636 data: 0.0028 max mem: 19788 +Epoch: [13] [1060/2138] eta: 0:58:38 lr: 3.452172472215027e-05 loss: 0.0300 (0.0371) time: 3.2460 data: 0.0029 max mem: 19788 +Epoch: [13] [1070/2138] eta: 0:58:09 lr: 3.4516241650338946e-05 loss: 0.0355 (0.0371) time: 3.3777 data: 0.0026 max mem: 19788 +Epoch: [13] [1080/2138] eta: 0:57:44 lr: 3.4510758481746757e-05 loss: 0.0338 (0.0370) time: 3.8351 data: 0.0025 max mem: 19788 +Epoch: [13] [1090/2138] eta: 0:57:12 lr: 3.45052752163549e-05 loss: 0.0338 (0.0370) time: 3.7210 data: 0.0025 max mem: 19788 +Epoch: [13] [1100/2138] eta: 0:56:39 lr: 3.449979185414458e-05 loss: 0.0408 (0.0371) time: 3.2932 data: 0.0024 max mem: 19788 +Epoch: [13] [1110/2138] eta: 0:56:09 lr: 3.449430839509698e-05 loss: 0.0408 (0.0371) time: 3.3933 data: 0.0025 max mem: 19788 +Epoch: [13] [1120/2138] eta: 0:55:36 lr: 3.44888248391933e-05 loss: 0.0354 (0.0371) time: 3.4188 data: 0.0028 max mem: 19788 +Epoch: [13] [1130/2138] eta: 0:55:03 lr: 3.44833411864147e-05 loss: 0.0347 (0.0371) time: 3.2330 data: 0.0025 max mem: 19788 +Epoch: [13] [1140/2138] eta: 0:54:29 lr: 3.4477857436742364e-05 loss: 0.0345 (0.0371) time: 3.1906 data: 0.0024 max mem: 19788 +Epoch: [13] [1150/2138] eta: 0:53:55 lr: 3.4472373590157445e-05 loss: 0.0323 (0.0371) time: 3.1644 data: 0.0025 max mem: 19788 +Epoch: [13] [1160/2138] eta: 0:53:23 lr: 3.446688964664111e-05 loss: 0.0302 (0.0371) time: 3.2705 data: 0.0026 max mem: 19788 +Epoch: [13] [1170/2138] eta: 0:52:49 lr: 3.446140560617451e-05 loss: 0.0312 (0.0370) time: 3.2559 data: 0.0027 max mem: 19788 +Epoch: [13] [1180/2138] eta: 0:52:15 lr: 3.445592146873877e-05 loss: 0.0330 (0.0370) time: 3.0816 data: 0.0028 max mem: 19788 +Epoch: [13] [1190/2138] eta: 0:51:43 lr: 3.445043723431505e-05 loss: 0.0331 (0.0369) time: 3.2217 data: 0.0027 max mem: 19788 +Epoch: [13] [1200/2138] eta: 0:51:10 lr: 3.4444952902884465e-05 loss: 0.0297 (0.0369) time: 3.3482 data: 0.0026 max mem: 19788 +Epoch: [13] [1210/2138] eta: 0:50:35 lr: 3.443946847442814e-05 loss: 0.0367 (0.0369) time: 3.1225 data: 0.0026 max mem: 19788 +Epoch: [13] [1220/2138] eta: 0:50:03 lr: 3.4433983948927185e-05 loss: 0.0338 (0.0369) time: 3.1776 data: 0.0026 max mem: 19788 +Epoch: [13] [1230/2138] eta: 0:49:31 lr: 3.442849932636272e-05 loss: 0.0296 (0.0369) time: 3.3637 data: 0.0030 max mem: 19788 +Epoch: [13] [1240/2138] eta: 0:48:57 lr: 3.442301460671584e-05 loss: 0.0287 (0.0368) time: 3.2245 data: 0.0027 max mem: 19788 +Epoch: [13] [1250/2138] eta: 0:48:24 lr: 3.4417529789967626e-05 loss: 0.0294 (0.0368) time: 3.1871 data: 0.0022 max mem: 19788 +Epoch: [13] [1260/2138] eta: 0:47:51 lr: 3.4412044876099176e-05 loss: 0.0307 (0.0369) time: 3.1927 data: 0.0026 max mem: 19788 +Epoch: [13] [1270/2138] eta: 0:47:19 lr: 3.440655986509157e-05 loss: 0.0306 (0.0369) time: 3.2469 data: 0.0028 max mem: 19788 +Epoch: [13] [1280/2138] eta: 0:46:45 lr: 3.4401074756925895e-05 loss: 0.0321 (0.0369) time: 3.2157 data: 0.0025 max mem: 19788 +Epoch: [13] [1290/2138] eta: 0:46:10 lr: 3.439558955158319e-05 loss: 0.0321 (0.0369) time: 2.9908 data: 0.0022 max mem: 19788 +Epoch: [13] [1300/2138] eta: 0:45:35 lr: 3.4390104249044524e-05 loss: 0.0309 (0.0368) time: 2.9379 data: 0.0023 max mem: 19788 +Epoch: [13] [1310/2138] eta: 0:45:01 lr: 3.438461884929095e-05 loss: 0.0309 (0.0368) time: 3.0332 data: 0.0024 max mem: 19788 +Epoch: [13] [1320/2138] eta: 0:44:27 lr: 3.437913335230352e-05 loss: 0.0346 (0.0368) time: 3.0446 data: 0.0023 max mem: 19788 +Epoch: [13] [1330/2138] eta: 0:43:52 lr: 3.437364775806326e-05 loss: 0.0361 (0.0368) time: 2.9235 data: 0.0021 max mem: 19788 +Epoch: [13] [1340/2138] eta: 0:43:17 lr: 3.43681620665512e-05 loss: 0.0371 (0.0368) time: 2.9012 data: 0.0022 max mem: 19788 +Epoch: [13] [1350/2138] eta: 0:42:44 lr: 3.436267627774838e-05 loss: 0.0429 (0.0369) time: 3.0379 data: 0.0024 max mem: 19788 +Epoch: [13] [1360/2138] eta: 0:42:10 lr: 3.4357190391635796e-05 loss: 0.0379 (0.0369) time: 3.0794 data: 0.0024 max mem: 19788 +Epoch: [13] [1370/2138] eta: 0:41:36 lr: 3.4351704408194464e-05 loss: 0.0358 (0.0369) time: 2.9473 data: 0.0023 max mem: 19788 +Epoch: [13] [1380/2138] eta: 0:41:01 lr: 3.434621832740539e-05 loss: 0.0368 (0.0369) time: 2.9046 data: 0.0022 max mem: 19788 +Epoch: [13] [1390/2138] eta: 0:40:28 lr: 3.4340732149249566e-05 loss: 0.0335 (0.0369) time: 3.0173 data: 0.0022 max mem: 19788 +Epoch: [13] [1400/2138] eta: 0:39:55 lr: 3.4335245873707986e-05 loss: 0.0313 (0.0369) time: 3.0666 data: 0.0023 max mem: 19788 +Epoch: [13] [1410/2138] eta: 0:39:20 lr: 3.4329759500761615e-05 loss: 0.0295 (0.0368) time: 2.9639 data: 0.0022 max mem: 19788 +Epoch: [13] [1420/2138] eta: 0:38:46 lr: 3.432427303039143e-05 loss: 0.0297 (0.0368) time: 2.8977 data: 0.0021 max mem: 19788 +Epoch: [13] [1430/2138] eta: 0:38:13 lr: 3.431878646257843e-05 loss: 0.0348 (0.0368) time: 2.9932 data: 0.0025 max mem: 19788 +Epoch: [13] [1440/2138] eta: 0:37:40 lr: 3.4313299797303534e-05 loss: 0.0357 (0.0368) time: 3.0951 data: 0.0026 max mem: 19788 +Epoch: [13] [1450/2138] eta: 0:37:06 lr: 3.430781303454771e-05 loss: 0.0322 (0.0368) time: 2.9781 data: 0.0027 max mem: 19788 +Epoch: [13] [1460/2138] eta: 0:36:32 lr: 3.4302326174291906e-05 loss: 0.0305 (0.0367) time: 2.8720 data: 0.0031 max mem: 19788 +Epoch: [13] [1470/2138] eta: 0:35:59 lr: 3.429683921651705e-05 loss: 0.0352 (0.0367) time: 2.9645 data: 0.0033 max mem: 19788 +Epoch: [13] [1480/2138] eta: 0:35:26 lr: 3.4291352161204096e-05 loss: 0.0366 (0.0367) time: 3.0594 data: 0.0030 max mem: 19788 +Epoch: [13] [1490/2138] eta: 0:34:52 lr: 3.428586500833394e-05 loss: 0.0312 (0.0367) time: 2.9865 data: 0.0025 max mem: 19788 +Epoch: [13] [1500/2138] eta: 0:34:18 lr: 3.428037775788751e-05 loss: 0.0312 (0.0367) time: 2.8919 data: 0.0027 max mem: 19788 +Epoch: [13] [1510/2138] eta: 0:33:45 lr: 3.427489040984572e-05 loss: 0.0309 (0.0367) time: 2.9594 data: 0.0027 max mem: 19788 +Epoch: [13] [1520/2138] eta: 0:33:12 lr: 3.4269402964189476e-05 loss: 0.0300 (0.0367) time: 3.0507 data: 0.0026 max mem: 19788 +Epoch: [13] [1530/2138] eta: 0:32:39 lr: 3.426391542089966e-05 loss: 0.0320 (0.0367) time: 2.9882 data: 0.0026 max mem: 19788 +Epoch: [13] [1540/2138] eta: 0:32:05 lr: 3.425842777995718e-05 loss: 0.0320 (0.0367) time: 2.8919 data: 0.0025 max mem: 19788 +Epoch: [13] [1550/2138] eta: 0:31:33 lr: 3.4252940041342894e-05 loss: 0.0324 (0.0367) time: 3.0421 data: 0.0026 max mem: 19788 +Epoch: [13] [1560/2138] eta: 0:31:00 lr: 3.424745220503768e-05 loss: 0.0307 (0.0367) time: 3.1327 data: 0.0025 max mem: 19788 +Epoch: [13] [1570/2138] eta: 0:30:27 lr: 3.424196427102242e-05 loss: 0.0307 (0.0367) time: 2.9846 data: 0.0026 max mem: 19788 +Epoch: [13] [1580/2138] eta: 0:29:53 lr: 3.423647623927797e-05 loss: 0.0325 (0.0366) time: 2.8975 data: 0.0027 max mem: 19788 +Epoch: [13] [1590/2138] eta: 0:29:20 lr: 3.423098810978518e-05 loss: 0.0315 (0.0366) time: 2.9361 data: 0.0026 max mem: 19788 +Epoch: [13] [1600/2138] eta: 0:28:48 lr: 3.422549988252488e-05 loss: 0.0342 (0.0367) time: 3.0332 data: 0.0030 max mem: 19788 +Epoch: [13] [1610/2138] eta: 0:28:15 lr: 3.4220011557477924e-05 loss: 0.0358 (0.0367) time: 3.0159 data: 0.0031 max mem: 19788 +Epoch: [13] [1620/2138] eta: 0:27:42 lr: 3.421452313462515e-05 loss: 0.0312 (0.0367) time: 2.9238 data: 0.0028 max mem: 19788 +Epoch: [13] [1630/2138] eta: 0:27:09 lr: 3.420903461394738e-05 loss: 0.0323 (0.0367) time: 2.9199 data: 0.0026 max mem: 19788 +Epoch: [13] [1640/2138] eta: 0:26:36 lr: 3.420354599542541e-05 loss: 0.0350 (0.0366) time: 3.0122 data: 0.0024 max mem: 19788 +Epoch: [13] [1650/2138] eta: 0:26:04 lr: 3.419805727904006e-05 loss: 0.0299 (0.0366) time: 3.0704 data: 0.0023 max mem: 19788 +Epoch: [13] [1660/2138] eta: 0:25:31 lr: 3.419256846477214e-05 loss: 0.0318 (0.0366) time: 2.9712 data: 0.0024 max mem: 19788 +Epoch: [13] [1670/2138] eta: 0:24:58 lr: 3.418707955260245e-05 loss: 0.0320 (0.0366) time: 2.9053 data: 0.0026 max mem: 19788 +Epoch: [13] [1680/2138] eta: 0:24:26 lr: 3.418159054251176e-05 loss: 0.0332 (0.0366) time: 3.0909 data: 0.0025 max mem: 19788 +Epoch: [13] [1690/2138] eta: 0:23:53 lr: 3.417610143448086e-05 loss: 0.0332 (0.0366) time: 3.1049 data: 0.0027 max mem: 19788 +Epoch: [13] [1700/2138] eta: 0:23:20 lr: 3.417061222849052e-05 loss: 0.0307 (0.0365) time: 2.8798 data: 0.0028 max mem: 19788 +Epoch: [13] [1710/2138] eta: 0:22:47 lr: 3.416512292452152e-05 loss: 0.0292 (0.0365) time: 2.7964 data: 0.0026 max mem: 19788 +Epoch: [13] [1720/2138] eta: 0:22:15 lr: 3.41596335225546e-05 loss: 0.0350 (0.0365) time: 2.7961 data: 0.0026 max mem: 19788 +Epoch: [13] [1730/2138] eta: 0:21:42 lr: 3.415414402257052e-05 loss: 0.0343 (0.0365) time: 2.7979 data: 0.0023 max mem: 19788 +Epoch: [13] [1740/2138] eta: 0:21:09 lr: 3.414865442455004e-05 loss: 0.0315 (0.0365) time: 2.8050 data: 0.0020 max mem: 19788 +Epoch: [13] [1750/2138] eta: 0:20:36 lr: 3.414316472847387e-05 loss: 0.0320 (0.0365) time: 2.8113 data: 0.0020 max mem: 19788 +Epoch: [13] [1760/2138] eta: 0:20:03 lr: 3.413767493432275e-05 loss: 0.0313 (0.0365) time: 2.8026 data: 0.0020 max mem: 19788 +Epoch: [13] [1770/2138] eta: 0:19:31 lr: 3.4132185042077416e-05 loss: 0.0301 (0.0364) time: 2.7943 data: 0.0019 max mem: 19788 +Epoch: [13] [1780/2138] eta: 0:18:58 lr: 3.4126695051718564e-05 loss: 0.0301 (0.0364) time: 2.7965 data: 0.0022 max mem: 19788 +Epoch: [13] [1790/2138] eta: 0:18:26 lr: 3.412120496322693e-05 loss: 0.0314 (0.0364) time: 2.7952 data: 0.0024 max mem: 19788 +Epoch: [13] [1800/2138] eta: 0:17:53 lr: 3.411571477658318e-05 loss: 0.0392 (0.0364) time: 2.8069 data: 0.0023 max mem: 19788 +Epoch: [13] [1810/2138] eta: 0:17:21 lr: 3.411022449176803e-05 loss: 0.0380 (0.0364) time: 2.8203 data: 0.0021 max mem: 19788 +Epoch: [13] [1820/2138] eta: 0:16:48 lr: 3.4104734108762166e-05 loss: 0.0321 (0.0364) time: 2.8192 data: 0.0021 max mem: 19788 +Epoch: [13] [1830/2138] eta: 0:16:16 lr: 3.4099243627546265e-05 loss: 0.0341 (0.0364) time: 2.8063 data: 0.0023 max mem: 19788 +Epoch: [13] [1840/2138] eta: 0:15:44 lr: 3.4093753048100995e-05 loss: 0.0329 (0.0363) time: 2.7948 data: 0.0024 max mem: 19788 +Epoch: [13] [1850/2138] eta: 0:15:11 lr: 3.408826237040704e-05 loss: 0.0350 (0.0364) time: 2.7944 data: 0.0023 max mem: 19788 +Epoch: [13] [1860/2138] eta: 0:14:39 lr: 3.408277159444503e-05 loss: 0.0363 (0.0364) time: 2.7978 data: 0.0024 max mem: 19788 +Epoch: [13] [1870/2138] eta: 0:14:07 lr: 3.407728072019562e-05 loss: 0.0365 (0.0364) time: 2.7988 data: 0.0025 max mem: 19788 +Epoch: [13] [1880/2138] eta: 0:13:35 lr: 3.407178974763947e-05 loss: 0.0319 (0.0364) time: 2.7974 data: 0.0027 max mem: 19788 +Epoch: [13] [1890/2138] eta: 0:13:03 lr: 3.406629867675721e-05 loss: 0.0284 (0.0363) time: 2.8062 data: 0.0027 max mem: 19788 +Epoch: [13] [1900/2138] eta: 0:12:31 lr: 3.406080750752947e-05 loss: 0.0333 (0.0364) time: 2.8277 data: 0.0027 max mem: 19788 +Epoch: [13] [1910/2138] eta: 0:11:59 lr: 3.4055316239936864e-05 loss: 0.0349 (0.0364) time: 2.9535 data: 0.0029 max mem: 19788 +Epoch: [13] [1920/2138] eta: 0:11:28 lr: 3.404982487396e-05 loss: 0.0398 (0.0364) time: 3.0785 data: 0.0028 max mem: 19788 +Epoch: [13] [1930/2138] eta: 0:10:56 lr: 3.404433340957951e-05 loss: 0.0383 (0.0364) time: 3.0558 data: 0.0025 max mem: 19788 +Epoch: [13] [1940/2138] eta: 0:10:24 lr: 3.403884184677597e-05 loss: 0.0351 (0.0364) time: 3.0716 data: 0.0023 max mem: 19788 +Epoch: [13] [1950/2138] eta: 0:09:53 lr: 3.403335018552998e-05 loss: 0.0343 (0.0364) time: 3.1756 data: 0.0023 max mem: 19788 +Epoch: [13] [1960/2138] eta: 0:09:22 lr: 3.402785842582212e-05 loss: 0.0343 (0.0364) time: 3.3850 data: 0.0023 max mem: 19788 +Epoch: [13] [1970/2138] eta: 0:08:50 lr: 3.4022366567632985e-05 loss: 0.0305 (0.0364) time: 3.3843 data: 0.0023 max mem: 19788 +Epoch: [13] [1980/2138] eta: 0:08:18 lr: 3.4016874610943125e-05 loss: 0.0332 (0.0364) time: 3.1894 data: 0.0026 max mem: 19788 +Epoch: [13] [1990/2138] eta: 0:07:47 lr: 3.4011382555733114e-05 loss: 0.0339 (0.0364) time: 3.1323 data: 0.0025 max mem: 19788 +Epoch: [13] [2000/2138] eta: 0:07:15 lr: 3.4005890401983505e-05 loss: 0.0318 (0.0364) time: 3.1290 data: 0.0024 max mem: 19788 +Epoch: [13] [2010/2138] eta: 0:06:44 lr: 3.4000398149674844e-05 loss: 0.0340 (0.0364) time: 3.0917 data: 0.0022 max mem: 19788 +Epoch: [13] [2020/2138] eta: 0:06:12 lr: 3.399490579878768e-05 loss: 0.0343 (0.0364) time: 3.1610 data: 0.0022 max mem: 19788 +Epoch: [13] [2030/2138] eta: 0:05:41 lr: 3.398941334930253e-05 loss: 0.0329 (0.0364) time: 3.2294 data: 0.0024 max mem: 19788 +Epoch: [13] [2040/2138] eta: 0:05:09 lr: 3.398392080119994e-05 loss: 0.0329 (0.0364) time: 3.1517 data: 0.0026 max mem: 19788 +Epoch: [13] [2050/2138] eta: 0:04:37 lr: 3.397842815446041e-05 loss: 0.0329 (0.0364) time: 3.1255 data: 0.0028 max mem: 19788 +Epoch: [13] [2060/2138] eta: 0:04:06 lr: 3.3972935409064476e-05 loss: 0.0318 (0.0364) time: 3.1502 data: 0.0028 max mem: 19788 +Epoch: [13] [2070/2138] eta: 0:03:34 lr: 3.396744256499262e-05 loss: 0.0314 (0.0364) time: 3.0990 data: 0.0026 max mem: 19788 +Epoch: [13] [2080/2138] eta: 0:03:03 lr: 3.396194962222534e-05 loss: 0.0324 (0.0364) time: 3.0191 data: 0.0025 max mem: 19788 +Epoch: [13] [2090/2138] eta: 0:02:31 lr: 3.395645658074314e-05 loss: 0.0341 (0.0364) time: 3.0325 data: 0.0027 max mem: 19788 +Epoch: [13] [2100/2138] eta: 0:01:59 lr: 3.3950963440526494e-05 loss: 0.0333 (0.0364) time: 3.0320 data: 0.0027 max mem: 19788 +Epoch: [13] [2110/2138] eta: 0:01:28 lr: 3.394547020155588e-05 loss: 0.0344 (0.0364) time: 3.0234 data: 0.0023 max mem: 19788 +Epoch: [13] [2120/2138] eta: 0:00:56 lr: 3.393997686381176e-05 loss: 0.0428 (0.0364) time: 3.0573 data: 0.0024 max mem: 19788 +Epoch: [13] [2130/2138] eta: 0:00:25 lr: 3.3934483427274595e-05 loss: 0.0396 (0.0365) time: 3.0705 data: 0.0023 max mem: 19788 +Epoch: [13] Total time: 1:52:25 +Test: [ 0/21770] eta: 14:04:06 time: 2.3264 data: 2.2529 max mem: 19788 +Test: [ 100/21770] eta: 0:26:05 time: 0.0489 data: 0.0017 max mem: 19788 +Test: [ 200/21770] eta: 0:21:33 time: 0.0537 data: 0.0019 max mem: 19788 +Test: [ 300/21770] eta: 0:20:13 time: 0.0434 data: 0.0015 max mem: 19788 +Test: [ 400/21770] eta: 0:19:27 time: 0.0452 data: 0.0015 max mem: 19788 +Test: [ 500/21770] eta: 0:18:38 time: 0.0432 data: 0.0015 max mem: 19788 +Test: [ 600/21770] eta: 0:18:08 time: 0.0483 data: 0.0016 max mem: 19788 +Test: [ 700/21770] eta: 0:18:00 time: 0.0436 data: 0.0016 max mem: 19788 +Test: [ 800/21770] eta: 0:17:35 time: 0.0427 data: 0.0014 max mem: 19788 +Test: [ 900/21770] eta: 0:17:17 time: 0.0456 data: 0.0015 max mem: 19788 +Test: [ 1000/21770] eta: 0:17:10 time: 0.0449 data: 0.0019 max mem: 19788 +Test: [ 1100/21770] eta: 0:16:56 time: 0.0453 data: 0.0016 max mem: 19788 +Test: [ 1200/21770] eta: 0:16:42 time: 0.0441 data: 0.0015 max mem: 19788 +Test: [ 1300/21770] eta: 0:16:36 time: 0.0485 data: 0.0016 max mem: 19788 +Test: [ 1400/21770] eta: 0:16:30 time: 0.0440 data: 0.0014 max mem: 19788 +Test: [ 1500/21770] eta: 0:16:19 time: 0.0447 data: 0.0017 max mem: 19788 +Test: [ 1600/21770] eta: 0:16:10 time: 0.0433 data: 0.0016 max mem: 19788 +Test: [ 1700/21770] eta: 0:16:03 time: 0.0475 data: 0.0016 max mem: 19788 +Test: [ 1800/21770] eta: 0:16:04 time: 0.0545 data: 0.0018 max mem: 19788 +Test: [ 1900/21770] eta: 0:15:54 time: 0.0427 data: 0.0015 max mem: 19788 +Test: [ 2000/21770] eta: 0:15:47 time: 0.0443 data: 0.0013 max mem: 19788 +Test: [ 2100/21770] eta: 0:15:43 time: 0.0461 data: 0.0016 max mem: 19788 +Test: [ 2200/21770] eta: 0:15:40 time: 0.0535 data: 0.0017 max mem: 19788 +Test: [ 2300/21770] eta: 0:15:33 time: 0.0452 data: 0.0014 max mem: 19788 +Test: [ 2400/21770] eta: 0:15:25 time: 0.0433 data: 0.0015 max mem: 19788 +Test: [ 2500/21770] eta: 0:15:18 time: 0.0443 data: 0.0015 max mem: 19788 +Test: [ 2600/21770] eta: 0:15:15 time: 0.0534 data: 0.0020 max mem: 19788 +Test: [ 2700/21770] eta: 0:15:13 time: 0.0449 data: 0.0017 max mem: 19788 +Test: [ 2800/21770] eta: 0:15:10 time: 0.0530 data: 0.0018 max mem: 19788 +Test: [ 2900/21770] eta: 0:15:06 time: 0.0459 data: 0.0015 max mem: 19788 +Test: [ 3000/21770] eta: 0:15:03 time: 0.0518 data: 0.0018 max mem: 19788 +Test: [ 3100/21770] eta: 0:14:58 time: 0.0448 data: 0.0015 max mem: 19788 +Test: [ 3200/21770] eta: 0:14:54 time: 0.0559 data: 0.0019 max mem: 19788 +Test: [ 3300/21770] eta: 0:14:51 time: 0.0464 data: 0.0015 max mem: 19788 +Test: [ 3400/21770] eta: 0:14:46 time: 0.0512 data: 0.0017 max mem: 19788 +Test: [ 3500/21770] eta: 0:14:42 time: 0.0564 data: 0.0015 max mem: 19788 +Test: [ 3600/21770] eta: 0:14:37 time: 0.0505 data: 0.0018 max mem: 19788 +Test: [ 3700/21770] eta: 0:14:33 time: 0.0540 data: 0.0019 max mem: 19788 +Test: [ 3800/21770] eta: 0:14:29 time: 0.0534 data: 0.0016 max mem: 19788 +Test: [ 3900/21770] eta: 0:14:26 time: 0.0533 data: 0.0016 max mem: 19788 +Test: [ 4000/21770] eta: 0:14:21 time: 0.0531 data: 0.0019 max mem: 19788 +Test: [ 4100/21770] eta: 0:14:17 time: 0.0434 data: 0.0014 max mem: 19788 +Test: [ 4200/21770] eta: 0:14:12 time: 0.0495 data: 0.0017 max mem: 19788 +Test: [ 4300/21770] eta: 0:14:07 time: 0.0453 data: 0.0015 max mem: 19788 +Test: [ 4400/21770] eta: 0:14:01 time: 0.0468 data: 0.0014 max mem: 19788 +Test: [ 4500/21770] eta: 0:13:57 time: 0.0529 data: 0.0018 max mem: 19788 +Test: [ 4600/21770] eta: 0:13:54 time: 0.0452 data: 0.0017 max mem: 19788 +Test: [ 4700/21770] eta: 0:13:48 time: 0.0451 data: 0.0017 max mem: 19788 +Test: [ 4800/21770] eta: 0:13:43 time: 0.0434 data: 0.0013 max mem: 19788 +Test: [ 4900/21770] eta: 0:13:38 time: 0.0510 data: 0.0018 max mem: 19788 +Test: [ 5000/21770] eta: 0:13:34 time: 0.0524 data: 0.0019 max mem: 19788 +Test: [ 5100/21770] eta: 0:13:32 time: 0.0585 data: 0.0019 max mem: 19788 +Test: [ 5200/21770] eta: 0:13:27 time: 0.0483 data: 0.0015 max mem: 19788 +Test: [ 5300/21770] eta: 0:13:22 time: 0.0464 data: 0.0017 max mem: 19788 +Test: [ 5400/21770] eta: 0:13:16 time: 0.0458 data: 0.0016 max mem: 19788 +Test: [ 5500/21770] eta: 0:13:10 time: 0.0481 data: 0.0016 max mem: 19788 +Test: [ 5600/21770] eta: 0:13:04 time: 0.0440 data: 0.0016 max mem: 19788 +Test: [ 5700/21770] eta: 0:12:58 time: 0.0472 data: 0.0015 max mem: 19788 +Test: [ 5800/21770] eta: 0:12:54 time: 0.0537 data: 0.0019 max mem: 19788 +Test: [ 5900/21770] eta: 0:12:48 time: 0.0436 data: 0.0013 max mem: 19788 +Test: [ 6000/21770] eta: 0:12:42 time: 0.0450 data: 0.0016 max mem: 19788 +Test: [ 6100/21770] eta: 0:12:37 time: 0.0450 data: 0.0013 max mem: 19788 +Test: [ 6200/21770] eta: 0:12:32 time: 0.0525 data: 0.0018 max mem: 19788 +Test: [ 6300/21770] eta: 0:12:28 time: 0.0540 data: 0.0018 max mem: 19788 +Test: [ 6400/21770] eta: 0:12:23 time: 0.0499 data: 0.0018 max mem: 19788 +Test: [ 6500/21770] eta: 0:12:19 time: 0.0449 data: 0.0014 max mem: 19788 +Test: [ 6600/21770] eta: 0:12:13 time: 0.0467 data: 0.0015 max mem: 19788 +Test: [ 6700/21770] eta: 0:12:10 time: 0.0476 data: 0.0018 max mem: 19788 +Test: [ 6800/21770] eta: 0:12:05 time: 0.0463 data: 0.0018 max mem: 19788 +Test: [ 6900/21770] eta: 0:12:00 time: 0.0494 data: 0.0018 max mem: 19788 +Test: [ 7000/21770] eta: 0:11:55 time: 0.0455 data: 0.0016 max mem: 19788 +Test: [ 7100/21770] eta: 0:11:50 time: 0.0543 data: 0.0019 max mem: 19788 +Test: [ 7200/21770] eta: 0:11:46 time: 0.0478 data: 0.0017 max mem: 19788 +Test: [ 7300/21770] eta: 0:11:42 time: 0.0535 data: 0.0018 max mem: 19788 +Test: [ 7400/21770] eta: 0:11:38 time: 0.0442 data: 0.0017 max mem: 19788 +Test: [ 7500/21770] eta: 0:11:33 time: 0.0535 data: 0.0019 max mem: 19788 +Test: [ 7600/21770] eta: 0:11:29 time: 0.0547 data: 0.0018 max mem: 19788 +Test: [ 7700/21770] eta: 0:11:24 time: 0.0474 data: 0.0015 max mem: 19788 +Test: [ 7800/21770] eta: 0:11:18 time: 0.0448 data: 0.0016 max mem: 19788 +Test: [ 7900/21770] eta: 0:11:14 time: 0.0445 data: 0.0016 max mem: 19788 +Test: [ 8000/21770] eta: 0:11:08 time: 0.0536 data: 0.0016 max mem: 19788 +Test: [ 8100/21770] eta: 0:11:03 time: 0.0440 data: 0.0016 max mem: 19788 +Test: [ 8200/21770] eta: 0:10:58 time: 0.0445 data: 0.0016 max mem: 19788 +Test: [ 8300/21770] eta: 0:10:52 time: 0.0450 data: 0.0015 max mem: 19788 +Test: [ 8400/21770] eta: 0:10:47 time: 0.0457 data: 0.0018 max mem: 19788 +Test: [ 8500/21770] eta: 0:10:42 time: 0.0480 data: 0.0015 max mem: 19788 +Test: [ 8600/21770] eta: 0:10:37 time: 0.0446 data: 0.0014 max mem: 19788 +Test: [ 8700/21770] eta: 0:10:33 time: 0.0541 data: 0.0018 max mem: 19788 +Test: [ 8800/21770] eta: 0:10:27 time: 0.0465 data: 0.0015 max mem: 19788 +Test: [ 8900/21770] eta: 0:10:22 time: 0.0436 data: 0.0015 max mem: 19788 +Test: [ 9000/21770] eta: 0:10:17 time: 0.0477 data: 0.0017 max mem: 19788 +Test: [ 9100/21770] eta: 0:10:12 time: 0.0441 data: 0.0014 max mem: 19788 +Test: [ 9200/21770] eta: 0:10:07 time: 0.0441 data: 0.0016 max mem: 19788 +Test: [ 9300/21770] eta: 0:10:03 time: 0.0538 data: 0.0019 max mem: 19788 +Test: [ 9400/21770] eta: 0:09:58 time: 0.0449 data: 0.0015 max mem: 19788 +Test: [ 9500/21770] eta: 0:09:53 time: 0.0459 data: 0.0018 max mem: 19788 +Test: [ 9600/21770] eta: 0:09:48 time: 0.0530 data: 0.0018 max mem: 19788 +Test: [ 9700/21770] eta: 0:09:44 time: 0.0538 data: 0.0019 max mem: 19788 +Test: [ 9800/21770] eta: 0:09:40 time: 0.0553 data: 0.0015 max mem: 19788 +Test: [ 9900/21770] eta: 0:09:35 time: 0.0462 data: 0.0015 max mem: 19788 +Test: [10000/21770] eta: 0:09:30 time: 0.0441 data: 0.0016 max mem: 19788 +Test: [10100/21770] eta: 0:09:25 time: 0.0535 data: 0.0018 max mem: 19788 +Test: [10200/21770] eta: 0:09:20 time: 0.0441 data: 0.0016 max mem: 19788 +Test: [10300/21770] eta: 0:09:15 time: 0.0489 data: 0.0016 max mem: 19788 +Test: [10400/21770] eta: 0:09:11 time: 0.0537 data: 0.0018 max mem: 19788 +Test: [10500/21770] eta: 0:09:07 time: 0.0541 data: 0.0019 max mem: 19788 +Test: [10600/21770] eta: 0:09:02 time: 0.0563 data: 0.0019 max mem: 19788 +Test: [10700/21770] eta: 0:08:57 time: 0.0453 data: 0.0017 max mem: 19788 +Test: [10800/21770] eta: 0:08:52 time: 0.0446 data: 0.0015 max mem: 19788 +Test: [10900/21770] eta: 0:08:47 time: 0.0484 data: 0.0015 max mem: 19788 +Test: [11000/21770] eta: 0:08:42 time: 0.0451 data: 0.0015 max mem: 19788 +Test: [11100/21770] eta: 0:08:37 time: 0.0553 data: 0.0017 max mem: 19788 +Test: [11200/21770] eta: 0:08:33 time: 0.0542 data: 0.0019 max mem: 19788 +Test: [11300/21770] eta: 0:08:28 time: 0.0533 data: 0.0017 max mem: 19788 +Test: [11400/21770] eta: 0:08:24 time: 0.0465 data: 0.0016 max mem: 19788 +Test: [11500/21770] eta: 0:08:18 time: 0.0439 data: 0.0014 max mem: 19788 +Test: [11600/21770] eta: 0:08:14 time: 0.0487 data: 0.0016 max mem: 19788 +Test: [11700/21770] eta: 0:08:09 time: 0.0451 data: 0.0015 max mem: 19788 +Test: [11800/21770] eta: 0:08:04 time: 0.0443 data: 0.0015 max mem: 19788 +Test: [11900/21770] eta: 0:07:59 time: 0.0512 data: 0.0017 max mem: 19788 +Test: [12000/21770] eta: 0:07:54 time: 0.0451 data: 0.0016 max mem: 19788 +Test: [12100/21770] eta: 0:07:49 time: 0.0565 data: 0.0017 max mem: 19788 +Test: [12200/21770] eta: 0:07:44 time: 0.0440 data: 0.0015 max mem: 19788 +Test: [12300/21770] eta: 0:07:39 time: 0.0456 data: 0.0015 max mem: 19788 +Test: [12400/21770] eta: 0:07:34 time: 0.0531 data: 0.0020 max mem: 19788 +Test: [12500/21770] eta: 0:07:30 time: 0.0467 data: 0.0018 max mem: 19788 +Test: [12600/21770] eta: 0:07:25 time: 0.0454 data: 0.0016 max mem: 19788 +Test: [12700/21770] eta: 0:07:20 time: 0.0454 data: 0.0014 max mem: 19788 +Test: [12800/21770] eta: 0:07:15 time: 0.0497 data: 0.0017 max mem: 19788 +Test: [12900/21770] eta: 0:07:10 time: 0.0560 data: 0.0019 max mem: 19788 +Test: [13000/21770] eta: 0:07:05 time: 0.0549 data: 0.0020 max mem: 19788 +Test: [13100/21770] eta: 0:07:01 time: 0.0548 data: 0.0017 max mem: 19788 +Test: [13200/21770] eta: 0:06:56 time: 0.0533 data: 0.0019 max mem: 19788 +Test: [13300/21770] eta: 0:06:51 time: 0.0450 data: 0.0015 max mem: 19788 +Test: [13400/21770] eta: 0:06:46 time: 0.0565 data: 0.0020 max mem: 19788 +Test: [13500/21770] eta: 0:06:42 time: 0.0513 data: 0.0018 max mem: 19788 +Test: [13600/21770] eta: 0:06:37 time: 0.0549 data: 0.0017 max mem: 19788 +Test: [13700/21770] eta: 0:06:32 time: 0.0449 data: 0.0015 max mem: 19788 +Test: [13800/21770] eta: 0:06:27 time: 0.0475 data: 0.0017 max mem: 19788 +Test: [13900/21770] eta: 0:06:22 time: 0.0541 data: 0.0020 max mem: 19788 +Test: [14000/21770] eta: 0:06:18 time: 0.0541 data: 0.0020 max mem: 19788 +Test: [14100/21770] eta: 0:06:13 time: 0.0469 data: 0.0016 max mem: 19788 +Test: [14200/21770] eta: 0:06:08 time: 0.0542 data: 0.0019 max mem: 19788 +Test: [14300/21770] eta: 0:06:04 time: 0.0441 data: 0.0016 max mem: 19788 +Test: [14400/21770] eta: 0:05:59 time: 0.0449 data: 0.0016 max mem: 19788 +Test: [14500/21770] eta: 0:05:54 time: 0.0463 data: 0.0014 max mem: 19788 +Test: [14600/21770] eta: 0:05:49 time: 0.0491 data: 0.0017 max mem: 19788 +Test: [14700/21770] eta: 0:05:44 time: 0.0448 data: 0.0017 max mem: 19788 +Test: [14800/21770] eta: 0:05:39 time: 0.0535 data: 0.0019 max mem: 19788 +Test: [14900/21770] eta: 0:05:34 time: 0.0482 data: 0.0015 max mem: 19788 +Test: [15000/21770] eta: 0:05:29 time: 0.0452 data: 0.0015 max mem: 19788 +Test: [15100/21770] eta: 0:05:24 time: 0.0451 data: 0.0015 max mem: 19788 +Test: [15200/21770] eta: 0:05:19 time: 0.0444 data: 0.0015 max mem: 19788 +Test: [15300/21770] eta: 0:05:14 time: 0.0492 data: 0.0016 max mem: 19788 +Test: [15400/21770] eta: 0:05:09 time: 0.0516 data: 0.0017 max mem: 19788 +Test: [15500/21770] eta: 0:05:04 time: 0.0543 data: 0.0017 max mem: 19788 +Test: [15600/21770] eta: 0:05:00 time: 0.0467 data: 0.0014 max mem: 19788 +Test: [15700/21770] eta: 0:04:55 time: 0.0452 data: 0.0017 max mem: 19788 +Test: [15800/21770] eta: 0:04:50 time: 0.0536 data: 0.0019 max mem: 19788 +Test: [15900/21770] eta: 0:04:45 time: 0.0464 data: 0.0016 max mem: 19788 +Test: [16000/21770] eta: 0:04:40 time: 0.0439 data: 0.0015 max mem: 19788 +Test: [16100/21770] eta: 0:04:35 time: 0.0531 data: 0.0015 max mem: 19788 +Test: [16200/21770] eta: 0:04:30 time: 0.0541 data: 0.0016 max mem: 19788 +Test: [16300/21770] eta: 0:04:26 time: 0.0440 data: 0.0015 max mem: 19788 +Test: [16400/21770] eta: 0:04:21 time: 0.0555 data: 0.0016 max mem: 19788 +Test: [16500/21770] eta: 0:04:16 time: 0.0445 data: 0.0014 max mem: 19788 +Test: [16600/21770] eta: 0:04:11 time: 0.0535 data: 0.0019 max mem: 19788 +Test: [16700/21770] eta: 0:04:06 time: 0.0442 data: 0.0014 max mem: 19788 +Test: [16800/21770] eta: 0:04:01 time: 0.0496 data: 0.0018 max mem: 19788 +Test: [16900/21770] eta: 0:03:57 time: 0.0449 data: 0.0014 max mem: 19788 +Test: [17000/21770] eta: 0:03:52 time: 0.0513 data: 0.0017 max mem: 19788 +Test: [17100/21770] eta: 0:03:47 time: 0.0513 data: 0.0018 max mem: 19788 +Test: [17200/21770] eta: 0:03:42 time: 0.0455 data: 0.0018 max mem: 19788 +Test: [17300/21770] eta: 0:03:37 time: 0.0449 data: 0.0015 max mem: 19788 +Test: [17400/21770] eta: 0:03:32 time: 0.0528 data: 0.0016 max mem: 19788 +Test: [17500/21770] eta: 0:03:27 time: 0.0541 data: 0.0017 max mem: 19788 +Test: [17600/21770] eta: 0:03:23 time: 0.0552 data: 0.0015 max mem: 19788 +Test: [17700/21770] eta: 0:03:18 time: 0.0442 data: 0.0014 max mem: 19788 +Test: [17800/21770] eta: 0:03:13 time: 0.0482 data: 0.0018 max mem: 19788 +Test: [17900/21770] eta: 0:03:08 time: 0.0456 data: 0.0016 max mem: 19788 +Test: [18000/21770] eta: 0:03:03 time: 0.0477 data: 0.0015 max mem: 19788 +Test: [18100/21770] eta: 0:02:58 time: 0.0494 data: 0.0017 max mem: 19788 +Test: [18200/21770] eta: 0:02:53 time: 0.0440 data: 0.0015 max mem: 19788 +Test: [18300/21770] eta: 0:02:48 time: 0.0533 data: 0.0017 max mem: 19788 +Test: [18400/21770] eta: 0:02:44 time: 0.0547 data: 0.0018 max mem: 19788 +Test: [18500/21770] eta: 0:02:39 time: 0.0530 data: 0.0017 max mem: 19788 +Test: [18600/21770] eta: 0:02:34 time: 0.0449 data: 0.0015 max mem: 19788 +Test: [18700/21770] eta: 0:02:29 time: 0.0540 data: 0.0018 max mem: 19788 +Test: [18800/21770] eta: 0:02:24 time: 0.0533 data: 0.0018 max mem: 19788 +Test: [18900/21770] eta: 0:02:19 time: 0.0469 data: 0.0016 max mem: 19788 +Test: [19000/21770] eta: 0:02:15 time: 0.0440 data: 0.0014 max mem: 19788 +Test: [19100/21770] eta: 0:02:10 time: 0.0484 data: 0.0015 max mem: 19788 +Test: [19200/21770] eta: 0:02:05 time: 0.0537 data: 0.0019 max mem: 19788 +Test: [19300/21770] eta: 0:02:00 time: 0.0516 data: 0.0020 max mem: 19788 +Test: [19400/21770] eta: 0:01:55 time: 0.0535 data: 0.0017 max mem: 19788 +Test: [19500/21770] eta: 0:01:50 time: 0.0525 data: 0.0018 max mem: 19788 +Test: [19600/21770] eta: 0:01:45 time: 0.0460 data: 0.0015 max mem: 19788 +Test: [19700/21770] eta: 0:01:41 time: 0.0562 data: 0.0018 max mem: 19788 +Test: [19800/21770] eta: 0:01:36 time: 0.0533 data: 0.0019 max mem: 19788 +Test: [19900/21770] eta: 0:01:31 time: 0.0551 data: 0.0019 max mem: 19788 +Test: [20000/21770] eta: 0:01:26 time: 0.0454 data: 0.0015 max mem: 19788 +Test: [20100/21770] eta: 0:01:21 time: 0.0444 data: 0.0014 max mem: 19788 +Test: [20200/21770] eta: 0:01:16 time: 0.0446 data: 0.0015 max mem: 19788 +Test: [20300/21770] eta: 0:01:11 time: 0.0452 data: 0.0015 max mem: 19788 +Test: [20400/21770] eta: 0:01:06 time: 0.0462 data: 0.0016 max mem: 19788 +Test: [20500/21770] eta: 0:01:02 time: 0.0443 data: 0.0016 max mem: 19788 +Test: [20600/21770] eta: 0:00:57 time: 0.0534 data: 0.0018 max mem: 19788 +Test: [20700/21770] eta: 0:00:52 time: 0.0550 data: 0.0015 max mem: 19788 +Test: [20800/21770] eta: 0:00:47 time: 0.0531 data: 0.0019 max mem: 19788 +Test: [20900/21770] eta: 0:00:42 time: 0.0442 data: 0.0015 max mem: 19788 +Test: [21000/21770] eta: 0:00:37 time: 0.0505 data: 0.0018 max mem: 19788 +Test: [21100/21770] eta: 0:00:32 time: 0.0472 data: 0.0018 max mem: 19788 +Test: [21200/21770] eta: 0:00:27 time: 0.0518 data: 0.0018 max mem: 19788 +Test: [21300/21770] eta: 0:00:22 time: 0.0477 data: 0.0018 max mem: 19788 +Test: [21400/21770] eta: 0:00:18 time: 0.0453 data: 0.0016 max mem: 19788 +Test: [21500/21770] eta: 0:00:13 time: 0.0541 data: 0.0019 max mem: 19788 +Test: [21600/21770] eta: 0:00:08 time: 0.0489 data: 0.0018 max mem: 19788 +Test: [21700/21770] eta: 0:00:03 time: 0.0795 data: 0.0039 max mem: 19788 +Test: Total time: 0:17:45 +Final results: +Mean IoU is 63.66 + + precision@0.5 = 70.68 + precision@0.6 = 65.07 + precision@0.7 = 58.19 + precision@0.8 = 47.02 + precision@0.9 = 23.36 + overall IoU = 63.89 + mean IoU = 63.66 + +Mean accuracy for one-to-zero sample is 81.65 + +Average object IoU 0.6366064267515121 +Overall IoU 63.89299392700195 +Epoch: [14] [ 0/2138] eta: 7:51:07 lr: 3.3930088606900736e-05 loss: 0.0386 (0.0386) time: 13.2215 data: 1.4076 max mem: 19788 +Epoch: [14] [ 10/2138] eta: 2:20:55 lr: 3.392459499248683e-05 loss: 0.0295 (0.0351) time: 3.9735 data: 0.1304 max mem: 19788 +Epoch: [14] [ 20/2138] eta: 2:04:46 lr: 3.391910127922513e-05 loss: 0.0295 (0.0337) time: 3.0503 data: 0.0019 max mem: 19788 +Epoch: [14] [ 30/2138] eta: 1:58:43 lr: 3.391360746709607e-05 loss: 0.0346 (0.0364) time: 3.0528 data: 0.0018 max mem: 19788 +Epoch: [14] [ 40/2138] eta: 1:55:18 lr: 3.390811355608006e-05 loss: 0.0387 (0.0377) time: 3.0492 data: 0.0026 max mem: 19788 +Epoch: [14] [ 50/2138] eta: 1:55:12 lr: 3.390261954615754e-05 loss: 0.0369 (0.0373) time: 3.2036 data: 0.0026 max mem: 19788 +Epoch: [14] [ 60/2138] eta: 1:53:08 lr: 3.3897125437308914e-05 loss: 0.0378 (0.0379) time: 3.2036 data: 0.0023 max mem: 19788 +Epoch: [14] [ 70/2138] eta: 1:51:31 lr: 3.389163122951457e-05 loss: 0.0362 (0.0375) time: 3.0444 data: 0.0024 max mem: 19788 +Epoch: [14] [ 80/2138] eta: 1:50:10 lr: 3.3886136922754914e-05 loss: 0.0318 (0.0372) time: 3.0446 data: 0.0026 max mem: 19788 +Epoch: [14] [ 90/2138] eta: 1:49:11 lr: 3.3880642517010334e-05 loss: 0.0311 (0.0369) time: 3.0701 data: 0.0028 max mem: 19788 +Epoch: [14] [ 100/2138] eta: 1:48:06 lr: 3.387514801226121e-05 loss: 0.0356 (0.0372) time: 3.0646 data: 0.0025 max mem: 19788 +Epoch: [14] [ 110/2138] eta: 1:47:08 lr: 3.386965340848791e-05 loss: 0.0369 (0.0372) time: 3.0376 data: 0.0021 max mem: 19788 +Epoch: [14] [ 120/2138] eta: 1:46:33 lr: 3.3864158705670804e-05 loss: 0.0328 (0.0366) time: 3.0957 data: 0.0025 max mem: 19788 +Epoch: [14] [ 130/2138] eta: 1:45:51 lr: 3.385866390379025e-05 loss: 0.0316 (0.0364) time: 3.1235 data: 0.0028 max mem: 19788 +Epoch: [14] [ 140/2138] eta: 1:45:00 lr: 3.385316900282659e-05 loss: 0.0325 (0.0362) time: 3.0607 data: 0.0027 max mem: 19788 +Epoch: [14] [ 150/2138] eta: 1:44:41 lr: 3.3847674002760176e-05 loss: 0.0347 (0.0362) time: 3.1373 data: 0.0025 max mem: 19788 +Epoch: [14] [ 160/2138] eta: 1:43:51 lr: 3.3842178903571345e-05 loss: 0.0347 (0.0360) time: 3.1297 data: 0.0024 max mem: 19788 +Epoch: [14] [ 170/2138] eta: 1:43:04 lr: 3.383668370524042e-05 loss: 0.0337 (0.0361) time: 3.0149 data: 0.0026 max mem: 19788 +Epoch: [14] [ 180/2138] eta: 1:42:30 lr: 3.383118840774772e-05 loss: 0.0333 (0.0360) time: 3.0678 data: 0.0026 max mem: 19788 +Epoch: [14] [ 190/2138] eta: 1:41:46 lr: 3.382569301107356e-05 loss: 0.0317 (0.0357) time: 3.0696 data: 0.0025 max mem: 19788 +Epoch: [14] [ 200/2138] eta: 1:41:09 lr: 3.3820197515198246e-05 loss: 0.0297 (0.0355) time: 3.0472 data: 0.0025 max mem: 19788 +Epoch: [14] [ 210/2138] eta: 1:40:35 lr: 3.3814701920102085e-05 loss: 0.0304 (0.0355) time: 3.0849 data: 0.0026 max mem: 19788 +Epoch: [14] [ 220/2138] eta: 1:39:59 lr: 3.380920622576535e-05 loss: 0.0300 (0.0354) time: 3.0924 data: 0.0027 max mem: 19788 +Epoch: [14] [ 230/2138] eta: 1:39:19 lr: 3.380371043216833e-05 loss: 0.0300 (0.0357) time: 3.0536 data: 0.0025 max mem: 19788 +Epoch: [14] [ 240/2138] eta: 1:38:52 lr: 3.379821453929131e-05 loss: 0.0352 (0.0358) time: 3.0982 data: 0.0022 max mem: 19788 +Epoch: [14] [ 250/2138] eta: 1:38:13 lr: 3.379271854711456e-05 loss: 0.0346 (0.0357) time: 3.1009 data: 0.0026 max mem: 19788 +Epoch: [14] [ 260/2138] eta: 1:37:42 lr: 3.3787222455618325e-05 loss: 0.0329 (0.0357) time: 3.0742 data: 0.0030 max mem: 19788 +Epoch: [14] [ 270/2138] eta: 1:37:04 lr: 3.3781726264782865e-05 loss: 0.0329 (0.0356) time: 3.0684 data: 0.0030 max mem: 19788 +Epoch: [14] [ 280/2138] eta: 1:36:27 lr: 3.3776229974588435e-05 loss: 0.0343 (0.0356) time: 3.0241 data: 0.0025 max mem: 19788 +Epoch: [14] [ 290/2138] eta: 1:35:55 lr: 3.377073358501526e-05 loss: 0.0323 (0.0356) time: 3.0647 data: 0.0023 max mem: 19788 +Epoch: [14] [ 300/2138] eta: 1:35:38 lr: 3.3765237096043576e-05 loss: 0.0320 (0.0356) time: 3.2216 data: 0.0025 max mem: 19788 +Epoch: [14] [ 310/2138] eta: 1:35:07 lr: 3.3759740507653616e-05 loss: 0.0328 (0.0357) time: 3.2413 data: 0.0024 max mem: 19788 +Epoch: [14] [ 320/2138] eta: 1:34:45 lr: 3.375424381982558e-05 loss: 0.0275 (0.0355) time: 3.2074 data: 0.0024 max mem: 19788 +Epoch: [14] [ 330/2138] eta: 1:34:34 lr: 3.374874703253969e-05 loss: 0.0295 (0.0355) time: 3.3936 data: 0.0024 max mem: 19788 +Epoch: [14] [ 340/2138] eta: 1:34:04 lr: 3.374325014577613e-05 loss: 0.0334 (0.0356) time: 3.3314 data: 0.0024 max mem: 19788 +Epoch: [14] [ 350/2138] eta: 1:33:29 lr: 3.373775315951511e-05 loss: 0.0312 (0.0356) time: 3.1097 data: 0.0027 max mem: 19788 +Epoch: [14] [ 360/2138] eta: 1:33:06 lr: 3.373225607373681e-05 loss: 0.0350 (0.0357) time: 3.1920 data: 0.0028 max mem: 19788 +Epoch: [14] [ 370/2138] eta: 1:32:27 lr: 3.37267588884214e-05 loss: 0.0345 (0.0356) time: 3.1521 data: 0.0026 max mem: 19788 +Epoch: [14] [ 380/2138] eta: 1:31:52 lr: 3.372126160354906e-05 loss: 0.0302 (0.0356) time: 3.0219 data: 0.0027 max mem: 19788 +Epoch: [14] [ 390/2138] eta: 1:31:17 lr: 3.3715764219099954e-05 loss: 0.0287 (0.0354) time: 3.0568 data: 0.0025 max mem: 19788 +Epoch: [14] [ 400/2138] eta: 1:30:48 lr: 3.371026673505424e-05 loss: 0.0333 (0.0355) time: 3.1122 data: 0.0023 max mem: 19788 +Epoch: [14] [ 410/2138] eta: 1:30:19 lr: 3.3704769151392053e-05 loss: 0.0351 (0.0354) time: 3.1807 data: 0.0023 max mem: 19788 +Epoch: [14] [ 420/2138] eta: 1:29:50 lr: 3.369927146809353e-05 loss: 0.0291 (0.0353) time: 3.1956 data: 0.0026 max mem: 19788 +Epoch: [14] [ 430/2138] eta: 1:29:31 lr: 3.369377368513883e-05 loss: 0.0304 (0.0353) time: 3.3237 data: 0.0028 max mem: 19788 +Epoch: [14] [ 440/2138] eta: 1:29:03 lr: 3.368827580250806e-05 loss: 0.0309 (0.0354) time: 3.3473 data: 0.0028 max mem: 19788 +Epoch: [14] [ 450/2138] eta: 1:28:34 lr: 3.3682777820181345e-05 loss: 0.0348 (0.0354) time: 3.2215 data: 0.0028 max mem: 19788 +Epoch: [14] [ 460/2138] eta: 1:28:00 lr: 3.3677279738138784e-05 loss: 0.0352 (0.0355) time: 3.1492 data: 0.0026 max mem: 19788 +Epoch: [14] [ 470/2138] eta: 1:27:33 lr: 3.3671781556360486e-05 loss: 0.0355 (0.0354) time: 3.1800 data: 0.0027 max mem: 19788 +Epoch: [14] [ 480/2138] eta: 1:27:02 lr: 3.3666283274826555e-05 loss: 0.0370 (0.0356) time: 3.2110 data: 0.0028 max mem: 19788 +Epoch: [14] [ 490/2138] eta: 1:26:29 lr: 3.366078489351707e-05 loss: 0.0376 (0.0356) time: 3.1302 data: 0.0025 max mem: 19788 +Epoch: [14] [ 500/2138] eta: 1:25:58 lr: 3.365528641241209e-05 loss: 0.0344 (0.0356) time: 3.1369 data: 0.0024 max mem: 19788 +Epoch: [14] [ 510/2138] eta: 1:25:28 lr: 3.364978783149174e-05 loss: 0.0292 (0.0356) time: 3.1842 data: 0.0025 max mem: 19788 +Epoch: [14] [ 520/2138] eta: 1:24:53 lr: 3.364428915073603e-05 loss: 0.0290 (0.0355) time: 3.1170 data: 0.0023 max mem: 19788 +Epoch: [14] [ 530/2138] eta: 1:24:20 lr: 3.3638790370125046e-05 loss: 0.0335 (0.0355) time: 3.0685 data: 0.0023 max mem: 19788 +Epoch: [14] [ 540/2138] eta: 1:23:46 lr: 3.363329148963883e-05 loss: 0.0335 (0.0355) time: 3.0770 data: 0.0028 max mem: 19788 +Epoch: [14] [ 550/2138] eta: 1:23:11 lr: 3.3627792509257426e-05 loss: 0.0359 (0.0355) time: 3.0479 data: 0.0031 max mem: 19788 +Epoch: [14] [ 560/2138] eta: 1:22:43 lr: 3.362229342896087e-05 loss: 0.0375 (0.0355) time: 3.1493 data: 0.0027 max mem: 19788 +Epoch: [14] [ 570/2138] eta: 1:22:09 lr: 3.361679424872918e-05 loss: 0.0320 (0.0355) time: 3.1518 data: 0.0025 max mem: 19788 +Epoch: [14] [ 580/2138] eta: 1:21:35 lr: 3.361129496854238e-05 loss: 0.0318 (0.0355) time: 3.0466 data: 0.0026 max mem: 19788 +Epoch: [14] [ 590/2138] eta: 1:21:01 lr: 3.3605795588380496e-05 loss: 0.0328 (0.0355) time: 3.0464 data: 0.0026 max mem: 19788 +Epoch: [14] [ 600/2138] eta: 1:20:27 lr: 3.360029610822351e-05 loss: 0.0328 (0.0355) time: 3.0514 data: 0.0026 max mem: 19788 +Epoch: [14] [ 610/2138] eta: 1:19:54 lr: 3.359479652805142e-05 loss: 0.0328 (0.0355) time: 3.0529 data: 0.0024 max mem: 19788 +Epoch: [14] [ 620/2138] eta: 1:19:21 lr: 3.358929684784422e-05 loss: 0.0328 (0.0355) time: 3.0545 data: 0.0022 max mem: 19788 +Epoch: [14] [ 630/2138] eta: 1:18:48 lr: 3.35837970675819e-05 loss: 0.0345 (0.0355) time: 3.0671 data: 0.0025 max mem: 19788 +Epoch: [14] [ 640/2138] eta: 1:18:16 lr: 3.357829718724442e-05 loss: 0.0323 (0.0355) time: 3.0951 data: 0.0026 max mem: 19788 +Epoch: [14] [ 650/2138] eta: 1:17:43 lr: 3.357279720681175e-05 loss: 0.0323 (0.0355) time: 3.0897 data: 0.0024 max mem: 19788 +Epoch: [14] [ 660/2138] eta: 1:17:13 lr: 3.3567297126263845e-05 loss: 0.0326 (0.0355) time: 3.1249 data: 0.0024 max mem: 19788 +Epoch: [14] [ 670/2138] eta: 1:16:44 lr: 3.356179694558067e-05 loss: 0.0322 (0.0354) time: 3.2211 data: 0.0026 max mem: 19788 +Epoch: [14] [ 680/2138] eta: 1:16:22 lr: 3.3556296664742145e-05 loss: 0.0268 (0.0353) time: 3.4154 data: 0.0026 max mem: 19788 +Epoch: [14] [ 690/2138] eta: 1:15:53 lr: 3.355079628372821e-05 loss: 0.0268 (0.0353) time: 3.4073 data: 0.0024 max mem: 19788 +Epoch: [14] [ 700/2138] eta: 1:15:21 lr: 3.35452958025188e-05 loss: 0.0327 (0.0353) time: 3.1767 data: 0.0026 max mem: 19788 +Epoch: [14] [ 710/2138] eta: 1:14:53 lr: 3.353979522109384e-05 loss: 0.0316 (0.0353) time: 3.2226 data: 0.0030 max mem: 19788 +Epoch: [14] [ 720/2138] eta: 1:14:23 lr: 3.353429453943323e-05 loss: 0.0282 (0.0352) time: 3.2740 data: 0.0033 max mem: 19788 +Epoch: [14] [ 730/2138] eta: 1:13:52 lr: 3.3528793757516876e-05 loss: 0.0301 (0.0351) time: 3.2013 data: 0.0034 max mem: 19788 +Epoch: [14] [ 740/2138] eta: 1:13:21 lr: 3.352329287532467e-05 loss: 0.0347 (0.0352) time: 3.1780 data: 0.0030 max mem: 19788 +Epoch: [14] [ 750/2138] eta: 1:12:50 lr: 3.351779189283651e-05 loss: 0.0302 (0.0351) time: 3.1847 data: 0.0024 max mem: 19788 +Epoch: [14] [ 760/2138] eta: 1:12:19 lr: 3.3512290810032285e-05 loss: 0.0320 (0.0352) time: 3.1687 data: 0.0025 max mem: 19788 +Epoch: [14] [ 770/2138] eta: 1:11:48 lr: 3.350678962689184e-05 loss: 0.0319 (0.0352) time: 3.1682 data: 0.0028 max mem: 19788 +Epoch: [14] [ 780/2138] eta: 1:11:18 lr: 3.350128834339506e-05 loss: 0.0297 (0.0352) time: 3.2019 data: 0.0028 max mem: 19788 +Epoch: [14] [ 790/2138] eta: 1:10:49 lr: 3.3495786959521817e-05 loss: 0.0297 (0.0351) time: 3.2675 data: 0.0026 max mem: 19788 +Epoch: [14] [ 800/2138] eta: 1:10:17 lr: 3.349028547525193e-05 loss: 0.0324 (0.0352) time: 3.2180 data: 0.0025 max mem: 19788 +Epoch: [14] [ 810/2138] eta: 1:09:46 lr: 3.348478389056526e-05 loss: 0.0328 (0.0351) time: 3.1444 data: 0.0026 max mem: 19788 +Epoch: [14] [ 820/2138] eta: 1:09:16 lr: 3.3479282205441635e-05 loss: 0.0327 (0.0351) time: 3.2173 data: 0.0024 max mem: 19788 +Epoch: [14] [ 830/2138] eta: 1:08:44 lr: 3.347378041986089e-05 loss: 0.0270 (0.0351) time: 3.1940 data: 0.0024 max mem: 19788 +Epoch: [14] [ 840/2138] eta: 1:08:12 lr: 3.346827853380284e-05 loss: 0.0324 (0.0351) time: 3.1209 data: 0.0027 max mem: 19788 +Epoch: [14] [ 850/2138] eta: 1:07:39 lr: 3.346277654724728e-05 loss: 0.0345 (0.0351) time: 3.0842 data: 0.0027 max mem: 19788 +Epoch: [14] [ 860/2138] eta: 1:07:06 lr: 3.345727446017405e-05 loss: 0.0304 (0.0351) time: 3.0591 data: 0.0026 max mem: 19788 +Epoch: [14] [ 870/2138] eta: 1:06:33 lr: 3.345177227256292e-05 loss: 0.0293 (0.0351) time: 3.0554 data: 0.0027 max mem: 19788 +Epoch: [14] [ 880/2138] eta: 1:06:04 lr: 3.344626998439367e-05 loss: 0.0293 (0.0350) time: 3.1787 data: 0.0025 max mem: 19788 +Epoch: [14] [ 890/2138] eta: 1:05:36 lr: 3.34407675956461e-05 loss: 0.0293 (0.0350) time: 3.3524 data: 0.0022 max mem: 19788 +Epoch: [14] [ 900/2138] eta: 1:05:04 lr: 3.343526510629998e-05 loss: 0.0301 (0.0350) time: 3.2503 data: 0.0022 max mem: 19788 +Epoch: [14] [ 910/2138] eta: 1:04:31 lr: 3.3429762516335075e-05 loss: 0.0301 (0.0349) time: 3.0962 data: 0.0024 max mem: 19788 +Epoch: [14] [ 920/2138] eta: 1:04:02 lr: 3.342425982573113e-05 loss: 0.0288 (0.0348) time: 3.2016 data: 0.0025 max mem: 19788 +Epoch: [14] [ 930/2138] eta: 1:03:34 lr: 3.341875703446791e-05 loss: 0.0339 (0.0349) time: 3.3828 data: 0.0025 max mem: 19788 +Epoch: [14] [ 940/2138] eta: 1:03:02 lr: 3.341325414252515e-05 loss: 0.0350 (0.0349) time: 3.3017 data: 0.0023 max mem: 19788 +Epoch: [14] [ 950/2138] eta: 1:02:33 lr: 3.3407751149882576e-05 loss: 0.0329 (0.0349) time: 3.2452 data: 0.0022 max mem: 19788 +Epoch: [14] [ 960/2138] eta: 1:02:02 lr: 3.340224805651992e-05 loss: 0.0336 (0.0349) time: 3.2753 data: 0.0026 max mem: 19788 +Epoch: [14] [ 970/2138] eta: 1:01:30 lr: 3.3396744862416914e-05 loss: 0.0327 (0.0349) time: 3.1527 data: 0.0026 max mem: 19788 +Epoch: [14] [ 980/2138] eta: 1:00:57 lr: 3.339124156755325e-05 loss: 0.0316 (0.0349) time: 3.0716 data: 0.0023 max mem: 19788 +Epoch: [14] [ 990/2138] eta: 1:00:27 lr: 3.3385738171908635e-05 loss: 0.0319 (0.0348) time: 3.1783 data: 0.0024 max mem: 19788 +Epoch: [14] [1000/2138] eta: 0:59:54 lr: 3.338023467546277e-05 loss: 0.0293 (0.0348) time: 3.1801 data: 0.0025 max mem: 19788 +Epoch: [14] [1010/2138] eta: 0:59:21 lr: 3.337473107819533e-05 loss: 0.0297 (0.0348) time: 3.0519 data: 0.0025 max mem: 19788 +Epoch: [14] [1020/2138] eta: 0:58:51 lr: 3.336922738008601e-05 loss: 0.0302 (0.0347) time: 3.1810 data: 0.0024 max mem: 19788 +Epoch: [14] [1030/2138] eta: 0:58:21 lr: 3.336372358111448e-05 loss: 0.0302 (0.0350) time: 3.3048 data: 0.0027 max mem: 19788 +Epoch: [14] [1040/2138] eta: 0:57:49 lr: 3.335821968126038e-05 loss: 0.0318 (0.0350) time: 3.1996 data: 0.0025 max mem: 19788 +Epoch: [14] [1050/2138] eta: 0:57:17 lr: 3.335271568050339e-05 loss: 0.0347 (0.0350) time: 3.1151 data: 0.0025 max mem: 19788 +Epoch: [14] [1060/2138] eta: 0:56:51 lr: 3.334721157882315e-05 loss: 0.0332 (0.0351) time: 3.3945 data: 0.0026 max mem: 19788 +Epoch: [14] [1070/2138] eta: 0:56:22 lr: 3.334170737619931e-05 loss: 0.0324 (0.0350) time: 3.5756 data: 0.0023 max mem: 19788 +Epoch: [14] [1080/2138] eta: 0:55:55 lr: 3.3336203072611475e-05 loss: 0.0306 (0.0350) time: 3.5512 data: 0.0022 max mem: 19788 +Epoch: [14] [1090/2138] eta: 0:55:27 lr: 3.33306986680393e-05 loss: 0.0365 (0.0350) time: 3.5630 data: 0.0023 max mem: 19788 +Epoch: [14] [1100/2138] eta: 0:54:55 lr: 3.332519416246239e-05 loss: 0.0361 (0.0351) time: 3.3303 data: 0.0026 max mem: 19788 +Epoch: [14] [1110/2138] eta: 0:54:24 lr: 3.3319689555860346e-05 loss: 0.0357 (0.0351) time: 3.2122 data: 0.0027 max mem: 19788 +Epoch: [14] [1120/2138] eta: 0:53:52 lr: 3.331418484821278e-05 loss: 0.0354 (0.0350) time: 3.2017 data: 0.0027 max mem: 19788 +Epoch: [14] [1130/2138] eta: 0:53:20 lr: 3.3308680039499274e-05 loss: 0.0315 (0.0350) time: 3.1544 data: 0.0027 max mem: 19788 +Epoch: [14] [1140/2138] eta: 0:52:49 lr: 3.330317512969943e-05 loss: 0.0324 (0.0350) time: 3.2137 data: 0.0028 max mem: 19788 +Epoch: [14] [1150/2138] eta: 0:52:18 lr: 3.32976701187928e-05 loss: 0.0286 (0.0350) time: 3.2419 data: 0.0031 max mem: 19788 +Epoch: [14] [1160/2138] eta: 0:51:47 lr: 3.3292165006758974e-05 loss: 0.0269 (0.0349) time: 3.2929 data: 0.0030 max mem: 19788 +Epoch: [14] [1170/2138] eta: 0:51:18 lr: 3.328665979357751e-05 loss: 0.0290 (0.0349) time: 3.4095 data: 0.0028 max mem: 19788 +Epoch: [14] [1180/2138] eta: 0:50:46 lr: 3.328115447922797e-05 loss: 0.0307 (0.0349) time: 3.3071 data: 0.0027 max mem: 19788 +Epoch: [14] [1190/2138] eta: 0:50:17 lr: 3.327564906368987e-05 loss: 0.0298 (0.0348) time: 3.3573 data: 0.0028 max mem: 19788 +Epoch: [14] [1200/2138] eta: 0:49:47 lr: 3.327014354694277e-05 loss: 0.0288 (0.0348) time: 3.4631 data: 0.0025 max mem: 19788 +Epoch: [14] [1210/2138] eta: 0:49:14 lr: 3.32646379289662e-05 loss: 0.0349 (0.0349) time: 3.2518 data: 0.0022 max mem: 19788 +Epoch: [14] [1220/2138] eta: 0:48:43 lr: 3.325913220973968e-05 loss: 0.0325 (0.0348) time: 3.2061 data: 0.0023 max mem: 19788 +Epoch: [14] [1230/2138] eta: 0:48:12 lr: 3.3253626389242716e-05 loss: 0.0314 (0.0348) time: 3.2413 data: 0.0023 max mem: 19788 +Epoch: [14] [1240/2138] eta: 0:47:42 lr: 3.3248120467454816e-05 loss: 0.0263 (0.0347) time: 3.3715 data: 0.0025 max mem: 19788 +Epoch: [14] [1250/2138] eta: 0:47:09 lr: 3.3242614444355494e-05 loss: 0.0309 (0.0348) time: 3.2929 data: 0.0026 max mem: 19788 +Epoch: [14] [1260/2138] eta: 0:46:37 lr: 3.323710831992423e-05 loss: 0.0286 (0.0347) time: 3.0564 data: 0.0025 max mem: 19788 +Epoch: [14] [1270/2138] eta: 0:46:06 lr: 3.3231602094140496e-05 loss: 0.0283 (0.0348) time: 3.2048 data: 0.0027 max mem: 19788 +Epoch: [14] [1280/2138] eta: 0:45:36 lr: 3.3226095766983777e-05 loss: 0.0317 (0.0347) time: 3.4364 data: 0.0028 max mem: 19788 +Epoch: [14] [1290/2138] eta: 0:45:06 lr: 3.322058933843355e-05 loss: 0.0331 (0.0348) time: 3.5050 data: 0.0026 max mem: 19788 +Epoch: [14] [1300/2138] eta: 0:44:33 lr: 3.321508280846925e-05 loss: 0.0327 (0.0348) time: 3.2499 data: 0.0026 max mem: 19788 +Epoch: [14] [1310/2138] eta: 0:44:01 lr: 3.320957617707034e-05 loss: 0.0327 (0.0347) time: 3.0537 data: 0.0028 max mem: 19788 +Epoch: [14] [1320/2138] eta: 0:43:31 lr: 3.3204069444216256e-05 loss: 0.0330 (0.0348) time: 3.3425 data: 0.0026 max mem: 19788 +Epoch: [14] [1330/2138] eta: 0:42:59 lr: 3.319856260988645e-05 loss: 0.0353 (0.0348) time: 3.3626 data: 0.0025 max mem: 19788 +Epoch: [14] [1340/2138] eta: 0:42:26 lr: 3.319305567406034e-05 loss: 0.0355 (0.0349) time: 3.1088 data: 0.0025 max mem: 19788 +Epoch: [14] [1350/2138] eta: 0:41:54 lr: 3.318754863671733e-05 loss: 0.0392 (0.0350) time: 3.0822 data: 0.0023 max mem: 19788 +Epoch: [14] [1360/2138] eta: 0:41:22 lr: 3.3182041497836846e-05 loss: 0.0387 (0.0349) time: 3.1776 data: 0.0023 max mem: 19788 +Epoch: [14] [1370/2138] eta: 0:40:50 lr: 3.317653425739829e-05 loss: 0.0355 (0.0350) time: 3.2028 data: 0.0026 max mem: 19788 +Epoch: [14] [1380/2138] eta: 0:40:19 lr: 3.317102691538106e-05 loss: 0.0384 (0.0350) time: 3.2112 data: 0.0026 max mem: 19788 +Epoch: [14] [1390/2138] eta: 0:39:49 lr: 3.3165519471764526e-05 loss: 0.0313 (0.0350) time: 3.4395 data: 0.0024 max mem: 19788 +Epoch: [14] [1400/2138] eta: 0:39:18 lr: 3.3160011926528085e-05 loss: 0.0282 (0.0350) time: 3.4884 data: 0.0027 max mem: 19788 +Epoch: [14] [1410/2138] eta: 0:38:46 lr: 3.315450427965111e-05 loss: 0.0294 (0.0350) time: 3.3090 data: 0.0032 max mem: 19788 +Epoch: [14] [1420/2138] eta: 0:38:15 lr: 3.314899653111294e-05 loss: 0.0354 (0.0350) time: 3.2301 data: 0.0032 max mem: 19788 +Epoch: [14] [1430/2138] eta: 0:37:44 lr: 3.3143488680892957e-05 loss: 0.0339 (0.0350) time: 3.3146 data: 0.0029 max mem: 19788 +Epoch: [14] [1440/2138] eta: 0:37:12 lr: 3.3137980728970485e-05 loss: 0.0347 (0.0350) time: 3.3206 data: 0.0028 max mem: 19788 +Epoch: [14] [1450/2138] eta: 0:36:40 lr: 3.313247267532488e-05 loss: 0.0347 (0.0350) time: 3.2567 data: 0.0028 max mem: 19788 +Epoch: [14] [1460/2138] eta: 0:36:08 lr: 3.3126964519935465e-05 loss: 0.0321 (0.0351) time: 3.2356 data: 0.0028 max mem: 19788 +Epoch: [14] [1470/2138] eta: 0:35:37 lr: 3.312145626278156e-05 loss: 0.0353 (0.0351) time: 3.2541 data: 0.0028 max mem: 19788 +Epoch: [14] [1480/2138] eta: 0:35:05 lr: 3.31159479038425e-05 loss: 0.0387 (0.0351) time: 3.2377 data: 0.0028 max mem: 19788 +Epoch: [14] [1490/2138] eta: 0:34:35 lr: 3.3110439443097565e-05 loss: 0.0387 (0.0352) time: 3.4277 data: 0.0025 max mem: 19788 +Epoch: [14] [1500/2138] eta: 0:34:05 lr: 3.3104930880526064e-05 loss: 0.0361 (0.0352) time: 3.6593 data: 0.0023 max mem: 19788 +Epoch: [14] [1510/2138] eta: 0:33:33 lr: 3.309942221610729e-05 loss: 0.0302 (0.0352) time: 3.4951 data: 0.0025 max mem: 19788 +Epoch: [14] [1520/2138] eta: 0:33:02 lr: 3.309391344982053e-05 loss: 0.0302 (0.0352) time: 3.4436 data: 0.0026 max mem: 19788 +Epoch: [14] [1530/2138] eta: 0:32:31 lr: 3.308840458164505e-05 loss: 0.0336 (0.0352) time: 3.4832 data: 0.0025 max mem: 19788 +Epoch: [14] [1540/2138] eta: 0:32:00 lr: 3.3082895611560106e-05 loss: 0.0330 (0.0352) time: 3.4938 data: 0.0025 max mem: 19788 +Epoch: [14] [1550/2138] eta: 0:31:28 lr: 3.307738653954498e-05 loss: 0.0312 (0.0352) time: 3.3840 data: 0.0027 max mem: 19788 +Epoch: [14] [1560/2138] eta: 0:30:58 lr: 3.307187736557891e-05 loss: 0.0299 (0.0352) time: 3.4001 data: 0.0028 max mem: 19788 +Epoch: [14] [1570/2138] eta: 0:30:25 lr: 3.3066368089641156e-05 loss: 0.0304 (0.0352) time: 3.3125 data: 0.0025 max mem: 19788 +Epoch: [14] [1580/2138] eta: 0:29:52 lr: 3.3060858711710915e-05 loss: 0.0317 (0.0352) time: 3.0882 data: 0.0025 max mem: 19788 +Epoch: [14] [1590/2138] eta: 0:29:21 lr: 3.305534923176745e-05 loss: 0.0317 (0.0352) time: 3.2344 data: 0.0027 max mem: 19788 +Epoch: [14] [1600/2138] eta: 0:28:49 lr: 3.304983964978996e-05 loss: 0.0378 (0.0353) time: 3.2788 data: 0.0025 max mem: 19788 +Epoch: [14] [1610/2138] eta: 0:28:16 lr: 3.304432996575766e-05 loss: 0.0378 (0.0352) time: 3.1367 data: 0.0024 max mem: 19788 +Epoch: [14] [1620/2138] eta: 0:27:44 lr: 3.303882017964975e-05 loss: 0.0287 (0.0352) time: 3.1911 data: 0.0024 max mem: 19788 +Epoch: [14] [1630/2138] eta: 0:27:12 lr: 3.303331029144543e-05 loss: 0.0293 (0.0352) time: 3.3166 data: 0.0025 max mem: 19788 +Epoch: [14] [1640/2138] eta: 0:26:41 lr: 3.302780030112388e-05 loss: 0.0350 (0.0352) time: 3.4054 data: 0.0027 max mem: 19788 +Epoch: [14] [1650/2138] eta: 0:26:09 lr: 3.3022290208664286e-05 loss: 0.0332 (0.0352) time: 3.3468 data: 0.0029 max mem: 19788 +Epoch: [14] [1660/2138] eta: 0:25:37 lr: 3.30167800140458e-05 loss: 0.0313 (0.0352) time: 3.2124 data: 0.0027 max mem: 19788 +Epoch: [14] [1670/2138] eta: 0:25:06 lr: 3.301126971724759e-05 loss: 0.0304 (0.0351) time: 3.4508 data: 0.0023 max mem: 19788 +Epoch: [14] [1680/2138] eta: 0:24:35 lr: 3.300575931824883e-05 loss: 0.0284 (0.0351) time: 3.6714 data: 0.0022 max mem: 19788 +Epoch: [14] [1690/2138] eta: 0:24:04 lr: 3.300024881702864e-05 loss: 0.0284 (0.0351) time: 3.6539 data: 0.0022 max mem: 19788 +Epoch: [14] [1700/2138] eta: 0:23:31 lr: 3.2994738213566166e-05 loss: 0.0287 (0.0351) time: 3.4315 data: 0.0023 max mem: 19788 +Epoch: [14] [1710/2138] eta: 0:23:00 lr: 3.298922750784054e-05 loss: 0.0287 (0.0351) time: 3.3598 data: 0.0026 max mem: 19788 +Epoch: [14] [1720/2138] eta: 0:22:28 lr: 3.2983716699830884e-05 loss: 0.0307 (0.0351) time: 3.3817 data: 0.0027 max mem: 19788 +Epoch: [14] [1730/2138] eta: 0:21:56 lr: 3.2978205789516296e-05 loss: 0.0320 (0.0351) time: 3.3924 data: 0.0026 max mem: 19788 +Epoch: [14] [1740/2138] eta: 0:21:25 lr: 3.297269477687589e-05 loss: 0.0320 (0.0351) time: 3.5467 data: 0.0023 max mem: 19788 +Epoch: [14] [1750/2138] eta: 0:20:53 lr: 3.2967183661888776e-05 loss: 0.0339 (0.0351) time: 3.6269 data: 0.0022 max mem: 19788 +Epoch: [14] [1760/2138] eta: 0:20:22 lr: 3.296167244453403e-05 loss: 0.0329 (0.0351) time: 3.6841 data: 0.0022 max mem: 19788 +Epoch: [14] [1770/2138] eta: 0:19:50 lr: 3.295616112479072e-05 loss: 0.0312 (0.0351) time: 3.5292 data: 0.0026 max mem: 19788 +Epoch: [14] [1780/2138] eta: 0:19:18 lr: 3.2950649702637936e-05 loss: 0.0268 (0.0351) time: 3.3135 data: 0.0031 max mem: 19788 +Epoch: [14] [1790/2138] eta: 0:18:46 lr: 3.294513817805474e-05 loss: 0.0298 (0.0351) time: 3.3150 data: 0.0031 max mem: 19788 +Epoch: [14] [1800/2138] eta: 0:18:13 lr: 3.2939626551020184e-05 loss: 0.0388 (0.0352) time: 3.3019 data: 0.0028 max mem: 19788 +Epoch: [14] [1810/2138] eta: 0:17:41 lr: 3.293411482151331e-05 loss: 0.0370 (0.0352) time: 3.1967 data: 0.0025 max mem: 19788 +Epoch: [14] [1820/2138] eta: 0:17:08 lr: 3.292860298951316e-05 loss: 0.0307 (0.0351) time: 3.1629 data: 0.0022 max mem: 19788 +Epoch: [14] [1830/2138] eta: 0:16:36 lr: 3.292309105499877e-05 loss: 0.0314 (0.0351) time: 3.1450 data: 0.0022 max mem: 19788 +Epoch: [14] [1840/2138] eta: 0:16:03 lr: 3.2917579017949164e-05 loss: 0.0339 (0.0351) time: 3.1792 data: 0.0022 max mem: 19788 +Epoch: [14] [1850/2138] eta: 0:15:31 lr: 3.2912066878343344e-05 loss: 0.0360 (0.0351) time: 3.2502 data: 0.0024 max mem: 19788 +Epoch: [14] [1860/2138] eta: 0:14:59 lr: 3.290655463616033e-05 loss: 0.0318 (0.0351) time: 3.2366 data: 0.0025 max mem: 19788 +Epoch: [14] [1870/2138] eta: 0:14:27 lr: 3.290104229137912e-05 loss: 0.0329 (0.0351) time: 3.3824 data: 0.0025 max mem: 19788 +Epoch: [14] [1880/2138] eta: 0:13:54 lr: 3.289552984397869e-05 loss: 0.0304 (0.0351) time: 3.2950 data: 0.0024 max mem: 19788 +Epoch: [14] [1890/2138] eta: 0:13:22 lr: 3.289001729393804e-05 loss: 0.0264 (0.0351) time: 3.0384 data: 0.0022 max mem: 19788 +Epoch: [14] [1900/2138] eta: 0:12:49 lr: 3.288450464123613e-05 loss: 0.0301 (0.0351) time: 3.0708 data: 0.0022 max mem: 19788 +Epoch: [14] [1910/2138] eta: 0:12:17 lr: 3.2878991885851935e-05 loss: 0.0301 (0.0350) time: 3.2380 data: 0.0024 max mem: 19788 +Epoch: [14] [1920/2138] eta: 0:11:45 lr: 3.2873479027764404e-05 loss: 0.0307 (0.0350) time: 3.5299 data: 0.0023 max mem: 19788 +Epoch: [14] [1930/2138] eta: 0:11:13 lr: 3.286796606695249e-05 loss: 0.0315 (0.0350) time: 3.6740 data: 0.0022 max mem: 19788 +Epoch: [14] [1940/2138] eta: 0:10:41 lr: 3.2862453003395136e-05 loss: 0.0307 (0.0350) time: 3.4980 data: 0.0022 max mem: 19788 +Epoch: [14] [1950/2138] eta: 0:10:08 lr: 3.2856939837071264e-05 loss: 0.0307 (0.0350) time: 3.1505 data: 0.0024 max mem: 19788 +Epoch: [14] [1960/2138] eta: 0:09:36 lr: 3.285142656795982e-05 loss: 0.0295 (0.0350) time: 2.9605 data: 0.0025 max mem: 19788 +Epoch: [14] [1970/2138] eta: 0:09:03 lr: 3.284591319603969e-05 loss: 0.0300 (0.0350) time: 2.9954 data: 0.0027 max mem: 19788 +Epoch: [14] [1980/2138] eta: 0:08:31 lr: 3.2840399721289804e-05 loss: 0.0317 (0.0350) time: 3.0537 data: 0.0029 max mem: 19788 +Epoch: [14] [1990/2138] eta: 0:07:58 lr: 3.283488614368906e-05 loss: 0.0317 (0.0350) time: 3.1470 data: 0.0029 max mem: 19788 +Epoch: [14] [2000/2138] eta: 0:07:26 lr: 3.282937246321634e-05 loss: 0.0318 (0.0349) time: 3.3291 data: 0.0030 max mem: 19788 +Epoch: [14] [2010/2138] eta: 0:06:54 lr: 3.282385867985053e-05 loss: 0.0318 (0.0350) time: 3.3112 data: 0.0029 max mem: 19788 +Epoch: [14] [2020/2138] eta: 0:06:21 lr: 3.2818344793570516e-05 loss: 0.0316 (0.0350) time: 3.0727 data: 0.0027 max mem: 19788 +Epoch: [14] [2030/2138] eta: 0:05:49 lr: 3.2812830804355146e-05 loss: 0.0342 (0.0350) time: 2.9428 data: 0.0024 max mem: 19788 +Epoch: [14] [2040/2138] eta: 0:05:16 lr: 3.280731671218329e-05 loss: 0.0300 (0.0350) time: 2.9301 data: 0.0022 max mem: 19788 +Epoch: [14] [2050/2138] eta: 0:04:44 lr: 3.2801802517033784e-05 loss: 0.0300 (0.0350) time: 2.9288 data: 0.0023 max mem: 19788 +Epoch: [14] [2060/2138] eta: 0:04:11 lr: 3.279628821888549e-05 loss: 0.0323 (0.0350) time: 2.9294 data: 0.0024 max mem: 19788 +Epoch: [14] [2070/2138] eta: 0:03:39 lr: 3.279077381771722e-05 loss: 0.0286 (0.0349) time: 2.9395 data: 0.0026 max mem: 19788 +Epoch: [14] [2080/2138] eta: 0:03:07 lr: 3.278525931350781e-05 loss: 0.0298 (0.0349) time: 2.9660 data: 0.0026 max mem: 19788 +Epoch: [14] [2090/2138] eta: 0:02:34 lr: 3.277974470623608e-05 loss: 0.0331 (0.0349) time: 2.9858 data: 0.0023 max mem: 19788 +Epoch: [14] [2100/2138] eta: 0:02:02 lr: 3.277422999588084e-05 loss: 0.0331 (0.0349) time: 3.0410 data: 0.0023 max mem: 19788 +Epoch: [14] [2110/2138] eta: 0:01:30 lr: 3.276871518242088e-05 loss: 0.0332 (0.0349) time: 3.0743 data: 0.0024 max mem: 19788 +Epoch: [14] [2120/2138] eta: 0:00:58 lr: 3.2763200265834994e-05 loss: 0.0401 (0.0350) time: 3.1029 data: 0.0027 max mem: 19788 +Epoch: [14] [2130/2138] eta: 0:00:25 lr: 3.2757685246101966e-05 loss: 0.0399 (0.0350) time: 3.1066 data: 0.0026 max mem: 19788 +Epoch: [14] Total time: 1:54:48 +Test: [ 0/21770] eta: 18:03:53 time: 2.9873 data: 2.7949 max mem: 19788 +Test: [ 100/21770] eta: 0:28:04 time: 0.0441 data: 0.0015 max mem: 19788 +Test: [ 200/21770] eta: 0:22:47 time: 0.0521 data: 0.0017 max mem: 19788 +Test: [ 300/21770] eta: 0:21:03 time: 0.0490 data: 0.0018 max mem: 19788 +Test: [ 400/21770] eta: 0:20:10 time: 0.0480 data: 0.0015 max mem: 19788 +Test: [ 500/21770] eta: 0:19:16 time: 0.0496 data: 0.0017 max mem: 19788 +Test: [ 600/21770] eta: 0:19:00 time: 0.0437 data: 0.0015 max mem: 19788 +Test: [ 700/21770] eta: 0:18:48 time: 0.0547 data: 0.0019 max mem: 19788 +Test: [ 800/21770] eta: 0:18:18 time: 0.0443 data: 0.0016 max mem: 19788 +Test: [ 900/21770] eta: 0:17:52 time: 0.0431 data: 0.0016 max mem: 19788 +Test: [ 1000/21770] eta: 0:17:39 time: 0.0515 data: 0.0018 max mem: 19788 +Test: [ 1100/21770] eta: 0:17:26 time: 0.0432 data: 0.0017 max mem: 19788 +Test: [ 1200/21770] eta: 0:17:21 time: 0.0516 data: 0.0017 max mem: 19788 +Test: [ 1300/21770] eta: 0:17:14 time: 0.0543 data: 0.0020 max mem: 19788 +Test: [ 1400/21770] eta: 0:17:05 time: 0.0449 data: 0.0017 max mem: 19788 +Test: [ 1500/21770] eta: 0:16:56 time: 0.0463 data: 0.0016 max mem: 19788 +Test: [ 1600/21770] eta: 0:16:54 time: 0.0558 data: 0.0019 max mem: 19788 +Test: [ 1700/21770] eta: 0:16:53 time: 0.0489 data: 0.0017 max mem: 19788 +Test: [ 1800/21770] eta: 0:16:42 time: 0.0454 data: 0.0015 max mem: 19788 +Test: [ 1900/21770] eta: 0:16:37 time: 0.0443 data: 0.0014 max mem: 19788 +Test: [ 2000/21770] eta: 0:16:32 time: 0.0572 data: 0.0016 max mem: 19788 +Test: [ 2100/21770] eta: 0:16:26 time: 0.0469 data: 0.0016 max mem: 19788 +Test: [ 2200/21770] eta: 0:16:16 time: 0.0440 data: 0.0016 max mem: 19788 +Test: [ 2300/21770] eta: 0:16:09 time: 0.0519 data: 0.0018 max mem: 19788 +Test: [ 2400/21770] eta: 0:16:03 time: 0.0486 data: 0.0016 max mem: 19788 +Test: [ 2500/21770] eta: 0:16:00 time: 0.0486 data: 0.0017 max mem: 19788 +Test: [ 2600/21770] eta: 0:15:54 time: 0.0427 data: 0.0015 max mem: 19788 +Test: [ 2700/21770] eta: 0:15:50 time: 0.0551 data: 0.0020 max mem: 19788 +Test: [ 2800/21770] eta: 0:15:45 time: 0.0469 data: 0.0017 max mem: 19788 +Test: [ 2900/21770] eta: 0:15:37 time: 0.0455 data: 0.0015 max mem: 19788 +Test: [ 3000/21770] eta: 0:15:33 time: 0.0538 data: 0.0018 max mem: 19788 +Test: [ 3100/21770] eta: 0:15:28 time: 0.0449 data: 0.0016 max mem: 19788 +Test: [ 3200/21770] eta: 0:15:22 time: 0.0448 data: 0.0013 max mem: 19788 +Test: [ 3300/21770] eta: 0:15:19 time: 0.0556 data: 0.0015 max mem: 19788 +Test: [ 3400/21770] eta: 0:15:12 time: 0.0442 data: 0.0016 max mem: 19788 +Test: [ 3500/21770] eta: 0:15:04 time: 0.0443 data: 0.0018 max mem: 19788 +Test: [ 3600/21770] eta: 0:14:57 time: 0.0466 data: 0.0017 max mem: 19788 +Test: [ 3700/21770] eta: 0:14:54 time: 0.0541 data: 0.0019 max mem: 19788 +Test: [ 3800/21770] eta: 0:14:50 time: 0.0540 data: 0.0018 max mem: 19788 +Test: [ 3900/21770] eta: 0:14:43 time: 0.0443 data: 0.0016 max mem: 19788 +Test: [ 4000/21770] eta: 0:14:37 time: 0.0505 data: 0.0018 max mem: 19788 +Test: [ 4100/21770] eta: 0:14:33 time: 0.0490 data: 0.0016 max mem: 19788 +Test: [ 4200/21770] eta: 0:14:27 time: 0.0453 data: 0.0015 max mem: 19788 +Test: [ 4300/21770] eta: 0:14:21 time: 0.0511 data: 0.0019 max mem: 19788 +Test: [ 4400/21770] eta: 0:14:16 time: 0.0438 data: 0.0016 max mem: 19788 +Test: [ 4500/21770] eta: 0:14:11 time: 0.0447 data: 0.0016 max mem: 19788 +Test: [ 4600/21770] eta: 0:14:06 time: 0.0440 data: 0.0019 max mem: 19788 +Test: [ 4700/21770] eta: 0:14:00 time: 0.0492 data: 0.0016 max mem: 19788 +Test: [ 4800/21770] eta: 0:13:56 time: 0.0442 data: 0.0016 max mem: 19788 +Test: [ 4900/21770] eta: 0:13:51 time: 0.0495 data: 0.0019 max mem: 19788 +Test: [ 5000/21770] eta: 0:13:47 time: 0.0445 data: 0.0017 max mem: 19788 +Test: [ 5100/21770] eta: 0:13:41 time: 0.0471 data: 0.0016 max mem: 19788 +Test: [ 5200/21770] eta: 0:13:36 time: 0.0506 data: 0.0016 max mem: 19788 +Test: [ 5300/21770] eta: 0:13:31 time: 0.0501 data: 0.0016 max mem: 19788 +Test: [ 5400/21770] eta: 0:13:25 time: 0.0496 data: 0.0017 max mem: 19788 +Test: [ 5500/21770] eta: 0:13:21 time: 0.0439 data: 0.0015 max mem: 19788 +Test: [ 5600/21770] eta: 0:13:16 time: 0.0527 data: 0.0019 max mem: 19788 +Test: [ 5700/21770] eta: 0:13:10 time: 0.0446 data: 0.0016 max mem: 19788 +Test: [ 5800/21770] eta: 0:13:06 time: 0.0545 data: 0.0020 max mem: 19788 +Test: [ 5900/21770] eta: 0:13:01 time: 0.0447 data: 0.0015 max mem: 19788 +Test: [ 6000/21770] eta: 0:12:56 time: 0.0507 data: 0.0018 max mem: 19788 +Test: [ 6100/21770] eta: 0:12:50 time: 0.0509 data: 0.0018 max mem: 19788 +Test: [ 6200/21770] eta: 0:12:45 time: 0.0522 data: 0.0020 max mem: 19788 +Test: [ 6300/21770] eta: 0:12:41 time: 0.0558 data: 0.0019 max mem: 19788 +Test: [ 6400/21770] eta: 0:12:37 time: 0.0535 data: 0.0018 max mem: 19788 +Test: [ 6500/21770] eta: 0:12:32 time: 0.0455 data: 0.0017 max mem: 19788 +Test: [ 6600/21770] eta: 0:12:28 time: 0.0454 data: 0.0015 max mem: 19788 +Test: [ 6700/21770] eta: 0:12:22 time: 0.0464 data: 0.0016 max mem: 19788 +Test: [ 6800/21770] eta: 0:12:17 time: 0.0457 data: 0.0014 max mem: 19788 +Test: [ 6900/21770] eta: 0:12:12 time: 0.0541 data: 0.0018 max mem: 19788 +Test: [ 7000/21770] eta: 0:12:07 time: 0.0445 data: 0.0017 max mem: 19788 +Test: [ 7100/21770] eta: 0:12:01 time: 0.0476 data: 0.0015 max mem: 19788 +Test: [ 7200/21770] eta: 0:11:56 time: 0.0503 data: 0.0017 max mem: 19788 +Test: [ 7300/21770] eta: 0:11:52 time: 0.0485 data: 0.0020 max mem: 19788 +Test: [ 7400/21770] eta: 0:11:47 time: 0.0455 data: 0.0017 max mem: 19788 +Test: [ 7500/21770] eta: 0:11:41 time: 0.0456 data: 0.0015 max mem: 19788 +Test: [ 7600/21770] eta: 0:11:36 time: 0.0520 data: 0.0016 max mem: 19788 +Test: [ 7700/21770] eta: 0:11:31 time: 0.0546 data: 0.0018 max mem: 19788 +Test: [ 7800/21770] eta: 0:11:25 time: 0.0441 data: 0.0014 max mem: 19788 +Test: [ 7900/21770] eta: 0:11:21 time: 0.0542 data: 0.0018 max mem: 19788 +Test: [ 8000/21770] eta: 0:11:16 time: 0.0482 data: 0.0016 max mem: 19788 +Test: [ 8100/21770] eta: 0:11:11 time: 0.0472 data: 0.0016 max mem: 19788 +Test: [ 8200/21770] eta: 0:11:07 time: 0.0465 data: 0.0017 max mem: 19788 +Test: [ 8300/21770] eta: 0:11:02 time: 0.0520 data: 0.0018 max mem: 19788 +Test: [ 8400/21770] eta: 0:10:56 time: 0.0441 data: 0.0016 max mem: 19788 +Test: [ 8500/21770] eta: 0:10:51 time: 0.0472 data: 0.0017 max mem: 19788 +Test: [ 8600/21770] eta: 0:10:46 time: 0.0513 data: 0.0018 max mem: 19788 +Test: [ 8700/21770] eta: 0:10:41 time: 0.0487 data: 0.0024 max mem: 19788 +Test: [ 8800/21770] eta: 0:10:35 time: 0.0461 data: 0.0017 max mem: 19788 +Test: [ 8900/21770] eta: 0:10:30 time: 0.0504 data: 0.0024 max mem: 19788 +Test: [ 9000/21770] eta: 0:10:26 time: 0.0564 data: 0.0017 max mem: 19788 +Test: [ 9100/21770] eta: 0:10:22 time: 0.0528 data: 0.0018 max mem: 19788 +Test: [ 9200/21770] eta: 0:10:17 time: 0.0441 data: 0.0015 max mem: 19788 +Test: [ 9300/21770] eta: 0:10:11 time: 0.0501 data: 0.0018 max mem: 19788 +Test: [ 9400/21770] eta: 0:10:07 time: 0.0524 data: 0.0016 max mem: 19788 +Test: [ 9500/21770] eta: 0:10:21 time: 0.2587 data: 0.2115 max mem: 19788 +Test: [ 9600/21770] eta: 0:10:40 time: 0.0482 data: 0.0014 max mem: 19788 +Test: [ 9700/21770] eta: 0:10:34 time: 0.0517 data: 0.0018 max mem: 19788 +Test: [ 9800/21770] eta: 0:10:28 time: 0.0439 data: 0.0016 max mem: 19788 +Test: [ 9900/21770] eta: 0:10:22 time: 0.0522 data: 0.0018 max mem: 19788 +Test: [10000/21770] eta: 0:10:16 time: 0.0529 data: 0.0018 max mem: 19788 +Test: [10100/21770] eta: 0:10:11 time: 0.0530 data: 0.0018 max mem: 19788 +Test: [10200/21770] eta: 0:10:05 time: 0.0500 data: 0.0018 max mem: 19788 +Test: [10300/21770] eta: 0:10:00 time: 0.0491 data: 0.0016 max mem: 19788 +Test: [10400/21770] eta: 0:09:54 time: 0.0470 data: 0.0014 max mem: 19788 +Test: [10500/21770] eta: 0:09:48 time: 0.0509 data: 0.0017 max mem: 19788 +Test: [10600/21770] eta: 0:09:43 time: 0.0477 data: 0.0016 max mem: 19788 +Test: [10700/21770] eta: 0:09:37 time: 0.0469 data: 0.0016 max mem: 19788 +Test: [10800/21770] eta: 0:09:32 time: 0.0462 data: 0.0017 max mem: 19788 +Test: [10900/21770] eta: 0:09:26 time: 0.0503 data: 0.0019 max mem: 19788 +Test: [11000/21770] eta: 0:09:21 time: 0.0528 data: 0.0018 max mem: 19788 +Test: [11100/21770] eta: 0:09:15 time: 0.0455 data: 0.0016 max mem: 19788 +Test: [11200/21770] eta: 0:09:09 time: 0.0483 data: 0.0015 max mem: 19788 +Test: [11300/21770] eta: 0:09:04 time: 0.0535 data: 0.0017 max mem: 19788 +Test: [11400/21770] eta: 0:08:59 time: 0.0510 data: 0.0017 max mem: 19788 +Test: [11500/21770] eta: 0:08:53 time: 0.0443 data: 0.0015 max mem: 19788 +Test: [11600/21770] eta: 0:08:48 time: 0.0434 data: 0.0016 max mem: 19788 +Test: [11700/21770] eta: 0:08:42 time: 0.0472 data: 0.0021 max mem: 19788 +Test: [11800/21770] eta: 0:08:37 time: 0.0444 data: 0.0015 max mem: 19788 +Test: [11900/21770] eta: 0:08:31 time: 0.0546 data: 0.0016 max mem: 19788 +Test: [12000/21770] eta: 0:08:26 time: 0.0504 data: 0.0017 max mem: 19788 +Test: [12100/21770] eta: 0:08:21 time: 0.0531 data: 0.0018 max mem: 19788 +Test: [12200/21770] eta: 0:08:15 time: 0.0476 data: 0.0015 max mem: 19788 +Test: [12300/21770] eta: 0:08:10 time: 0.0440 data: 0.0017 max mem: 19788 +Test: [12400/21770] eta: 0:08:04 time: 0.0444 data: 0.0015 max mem: 19788 +Test: [12500/21770] eta: 0:07:59 time: 0.0442 data: 0.0016 max mem: 19788 +Test: [12600/21770] eta: 0:07:53 time: 0.0514 data: 0.0018 max mem: 19788 +Test: [12700/21770] eta: 0:07:48 time: 0.0533 data: 0.0019 max mem: 19788 +Test: [12800/21770] eta: 0:07:42 time: 0.0438 data: 0.0016 max mem: 19788 +Test: [12900/21770] eta: 0:07:36 time: 0.0438 data: 0.0014 max mem: 19788 +Test: [13000/21770] eta: 0:07:31 time: 0.0495 data: 0.0017 max mem: 19788 +Test: [13100/21770] eta: 0:07:26 time: 0.0523 data: 0.0018 max mem: 19788 +Test: [13200/21770] eta: 0:07:21 time: 0.0556 data: 0.0017 max mem: 19788 +Test: [13300/21770] eta: 0:07:15 time: 0.0493 data: 0.0016 max mem: 19788 +Test: [13400/21770] eta: 0:07:10 time: 0.0540 data: 0.0016 max mem: 19788 +Test: [13500/21770] eta: 0:07:05 time: 0.0438 data: 0.0014 max mem: 19788 +Test: [13600/21770] eta: 0:06:59 time: 0.0451 data: 0.0016 max mem: 19788 +Test: [13700/21770] eta: 0:06:54 time: 0.0456 data: 0.0015 max mem: 19788 +Test: [13800/21770] eta: 0:06:48 time: 0.0491 data: 0.0018 max mem: 19788 +Test: [13900/21770] eta: 0:06:43 time: 0.0537 data: 0.0018 max mem: 19788 +Test: [14000/21770] eta: 0:06:38 time: 0.0428 data: 0.0015 max mem: 19788 +Test: [14100/21770] eta: 0:06:33 time: 0.0450 data: 0.0015 max mem: 19788 +Test: [14200/21770] eta: 0:06:27 time: 0.0538 data: 0.0018 max mem: 19788 +Test: [14300/21770] eta: 0:06:22 time: 0.0447 data: 0.0016 max mem: 19788 +Test: [14400/21770] eta: 0:06:17 time: 0.0542 data: 0.0020 max mem: 19788 +Test: [14500/21770] eta: 0:06:12 time: 0.0527 data: 0.0019 max mem: 19788 +Test: [14600/21770] eta: 0:06:07 time: 0.0502 data: 0.0014 max mem: 19788 +Test: [14700/21770] eta: 0:06:01 time: 0.0456 data: 0.0018 max mem: 19788 +Test: [14800/21770] eta: 0:05:56 time: 0.0523 data: 0.0019 max mem: 19788 +Test: [14900/21770] eta: 0:05:51 time: 0.0494 data: 0.0016 max mem: 19788 +Test: [15000/21770] eta: 0:05:46 time: 0.0452 data: 0.0015 max mem: 19788 +Test: [15100/21770] eta: 0:05:40 time: 0.0450 data: 0.0014 max mem: 19788 +Test: [15200/21770] eta: 0:05:35 time: 0.0545 data: 0.0019 max mem: 19788 +Test: [15300/21770] eta: 0:05:30 time: 0.0450 data: 0.0013 max mem: 19788 +Test: [15400/21770] eta: 0:05:25 time: 0.0446 data: 0.0015 max mem: 19788 +Test: [15500/21770] eta: 0:05:19 time: 0.0454 data: 0.0014 max mem: 19788 +Test: [15600/21770] eta: 0:05:14 time: 0.0497 data: 0.0018 max mem: 19788 +Test: [15700/21770] eta: 0:05:09 time: 0.0504 data: 0.0017 max mem: 19788 +Test: [15800/21770] eta: 0:05:04 time: 0.0472 data: 0.0020 max mem: 19788 +Test: [15900/21770] eta: 0:04:59 time: 0.0432 data: 0.0015 max mem: 19788 +Test: [16000/21770] eta: 0:04:53 time: 0.0463 data: 0.0015 max mem: 19788 +Test: [16100/21770] eta: 0:04:48 time: 0.0446 data: 0.0015 max mem: 19788 +Test: [16200/21770] eta: 0:04:43 time: 0.0548 data: 0.0019 max mem: 19788 +Test: [16300/21770] eta: 0:04:38 time: 0.0482 data: 0.0016 max mem: 19788 +Test: [16400/21770] eta: 0:04:32 time: 0.0454 data: 0.0014 max mem: 19788 +Test: [16500/21770] eta: 0:04:27 time: 0.0432 data: 0.0015 max mem: 19788 +Test: [16600/21770] eta: 0:04:22 time: 0.0545 data: 0.0017 max mem: 19788 +Test: [16700/21770] eta: 0:04:17 time: 0.0453 data: 0.0015 max mem: 19788 +Test: [16800/21770] eta: 0:04:12 time: 0.0435 data: 0.0015 max mem: 19788 +Test: [16900/21770] eta: 0:04:06 time: 0.0522 data: 0.0019 max mem: 19788 +Test: [17000/21770] eta: 0:04:01 time: 0.0539 data: 0.0019 max mem: 19788 +Test: [17100/21770] eta: 0:03:56 time: 0.0429 data: 0.0014 max mem: 19788 +Test: [17200/21770] eta: 0:03:51 time: 0.0486 data: 0.0016 max mem: 19788 +Test: [17300/21770] eta: 0:03:46 time: 0.0440 data: 0.0018 max mem: 19788 +Test: [17400/21770] eta: 0:03:41 time: 0.0543 data: 0.0019 max mem: 19788 +Test: [17500/21770] eta: 0:03:36 time: 0.0441 data: 0.0014 max mem: 19788 +Test: [17600/21770] eta: 0:03:31 time: 0.0535 data: 0.0019 max mem: 19788 +Test: [17700/21770] eta: 0:03:26 time: 0.0512 data: 0.0016 max mem: 19788 +Test: [17800/21770] eta: 0:03:21 time: 0.0476 data: 0.0016 max mem: 19788 +Test: [17900/21770] eta: 0:03:15 time: 0.0538 data: 0.0019 max mem: 19788 +Test: [18000/21770] eta: 0:03:10 time: 0.0486 data: 0.0016 max mem: 19788 +Test: [18100/21770] eta: 0:03:05 time: 0.0471 data: 0.0016 max mem: 19788 +Test: [18200/21770] eta: 0:03:00 time: 0.0506 data: 0.0015 max mem: 19788 +Test: [18300/21770] eta: 0:02:55 time: 0.0456 data: 0.0016 max mem: 19788 +Test: [18400/21770] eta: 0:02:50 time: 0.0493 data: 0.0019 max mem: 19788 +Test: [18500/21770] eta: 0:02:45 time: 0.0532 data: 0.0018 max mem: 19788 +Test: [18600/21770] eta: 0:02:40 time: 0.0438 data: 0.0014 max mem: 19788 +Test: [18700/21770] eta: 0:02:35 time: 0.0446 data: 0.0014 max mem: 19788 +Test: [18800/21770] eta: 0:02:30 time: 0.0508 data: 0.0019 max mem: 19788 +Test: [18900/21770] eta: 0:02:24 time: 0.0468 data: 0.0017 max mem: 19788 +Test: [19000/21770] eta: 0:02:19 time: 0.0453 data: 0.0013 max mem: 19788 +Test: [19100/21770] eta: 0:02:14 time: 0.0443 data: 0.0016 max mem: 19788 +Test: [19200/21770] eta: 0:02:09 time: 0.0443 data: 0.0014 max mem: 19788 +Test: [19300/21770] eta: 0:02:04 time: 0.0521 data: 0.0017 max mem: 19788 +Test: [19400/21770] eta: 0:01:59 time: 0.0452 data: 0.0015 max mem: 19788 +Test: [19500/21770] eta: 0:01:54 time: 0.0440 data: 0.0016 max mem: 19788 +Test: [19600/21770] eta: 0:01:49 time: 0.0530 data: 0.0018 max mem: 19788 +Test: [19700/21770] eta: 0:01:44 time: 0.0440 data: 0.0016 max mem: 19788 +Test: [19800/21770] eta: 0:01:39 time: 0.0549 data: 0.0018 max mem: 19788 +Test: [19900/21770] eta: 0:01:34 time: 0.0533 data: 0.0019 max mem: 19788 +Test: [20000/21770] eta: 0:01:29 time: 0.0459 data: 0.0015 max mem: 19788 +Test: [20100/21770] eta: 0:01:24 time: 0.0541 data: 0.0017 max mem: 19788 +Test: [20200/21770] eta: 0:01:19 time: 0.0487 data: 0.0017 max mem: 19788 +Test: [20300/21770] eta: 0:01:13 time: 0.0439 data: 0.0015 max mem: 19788 +Test: [20400/21770] eta: 0:01:08 time: 0.0446 data: 0.0014 max mem: 19788 +Test: [20500/21770] eta: 0:01:03 time: 0.0447 data: 0.0016 max mem: 19788 +Test: [20600/21770] eta: 0:00:58 time: 0.0447 data: 0.0014 max mem: 19788 +Test: [20700/21770] eta: 0:00:53 time: 0.0441 data: 0.0015 max mem: 19788 +Test: [20800/21770] eta: 0:00:48 time: 0.0484 data: 0.0018 max mem: 19788 +Test: [20900/21770] eta: 0:00:43 time: 0.0441 data: 0.0016 max mem: 19788 +Test: [21000/21770] eta: 0:00:38 time: 0.0442 data: 0.0015 max mem: 19788 +Test: [21100/21770] eta: 0:00:33 time: 0.0463 data: 0.0016 max mem: 19788 +Test: [21200/21770] eta: 0:00:28 time: 0.0487 data: 0.0016 max mem: 19788 +Test: [21300/21770] eta: 0:00:23 time: 0.0522 data: 0.0017 max mem: 19788 +Test: [21400/21770] eta: 0:00:18 time: 0.0464 data: 0.0016 max mem: 19788 +Test: [21500/21770] eta: 0:00:13 time: 0.0460 data: 0.0016 max mem: 19788 +Test: [21600/21770] eta: 0:00:08 time: 0.0547 data: 0.0020 max mem: 19788 +Test: [21700/21770] eta: 0:00:03 time: 0.0495 data: 0.0017 max mem: 19788 +Test: Total time: 0:18:13 +Final results: +Mean IoU is 63.02 + + precision@0.5 = 69.89 + precision@0.6 = 64.26 + precision@0.7 = 57.21 + precision@0.8 = 46.09 + precision@0.9 = 23.07 + overall IoU = 63.80 + mean IoU = 63.02 + +Mean accuracy for one-to-zero sample is 80.83 + +Average object IoU 0.6302416261094471 +Overall IoU 63.79939651489258 +Epoch: [15] [ 0/2138] eta: 13:03:03 lr: 3.2753273156035344e-05 loss: 0.0633 (0.0633) time: 21.9753 data: 1.4850 max mem: 19788 +Epoch: [15] [ 10/2138] eta: 2:57:29 lr: 3.2747757950583966e-05 loss: 0.0305 (0.0380) time: 5.0046 data: 0.1370 max mem: 19788 +Epoch: [15] [ 20/2138] eta: 2:32:12 lr: 3.2742242641926e-05 loss: 0.0305 (0.0342) time: 3.4289 data: 0.0020 max mem: 19788 +Epoch: [15] [ 30/2138] eta: 2:22:45 lr: 3.27367272300402e-05 loss: 0.0312 (0.0347) time: 3.5459 data: 0.0021 max mem: 19788 +Epoch: [15] [ 40/2138] eta: 2:19:56 lr: 3.2731211714905294e-05 loss: 0.0323 (0.0372) time: 3.6771 data: 0.0023 max mem: 19788 +Epoch: [15] [ 50/2138] eta: 2:14:51 lr: 3.2725696096500024e-05 loss: 0.0307 (0.0369) time: 3.5836 data: 0.0026 max mem: 19788 +Epoch: [15] [ 60/2138] eta: 2:10:49 lr: 3.2720180374803125e-05 loss: 0.0347 (0.0375) time: 3.3170 data: 0.0030 max mem: 19788 +Epoch: [15] [ 70/2138] eta: 2:07:04 lr: 3.2714664549793306e-05 loss: 0.0363 (0.0371) time: 3.2057 data: 0.0031 max mem: 19788 +Epoch: [15] [ 80/2138] eta: 2:04:42 lr: 3.2709148621449276e-05 loss: 0.0354 (0.0370) time: 3.2039 data: 0.0028 max mem: 19788 +Epoch: [15] [ 90/2138] eta: 2:02:34 lr: 3.2703632589749736e-05 loss: 0.0301 (0.0363) time: 3.2506 data: 0.0025 max mem: 19788 +Epoch: [15] [ 100/2138] eta: 2:00:21 lr: 3.269811645467339e-05 loss: 0.0328 (0.0366) time: 3.1688 data: 0.0026 max mem: 19788 +Epoch: [15] [ 110/2138] eta: 1:58:20 lr: 3.269260021619891e-05 loss: 0.0331 (0.0366) time: 3.0922 data: 0.0027 max mem: 19788 +Epoch: [15] [ 120/2138] eta: 1:57:37 lr: 3.2687083874304976e-05 loss: 0.0325 (0.0364) time: 3.2648 data: 0.0027 max mem: 19788 +Epoch: [15] [ 130/2138] eta: 1:55:49 lr: 3.268156742897025e-05 loss: 0.0317 (0.0362) time: 3.2374 data: 0.0026 max mem: 19788 +Epoch: [15] [ 140/2138] eta: 1:54:29 lr: 3.267605088017341e-05 loss: 0.0351 (0.0362) time: 3.0783 data: 0.0028 max mem: 19788 +Epoch: [15] [ 150/2138] eta: 1:53:29 lr: 3.2670534227893094e-05 loss: 0.0345 (0.0360) time: 3.1922 data: 0.0027 max mem: 19788 +Epoch: [15] [ 160/2138] eta: 1:52:35 lr: 3.266501747210794e-05 loss: 0.0311 (0.0356) time: 3.2565 data: 0.0025 max mem: 19788 +Epoch: [15] [ 170/2138] eta: 1:51:18 lr: 3.2659500612796585e-05 loss: 0.0339 (0.0356) time: 3.1560 data: 0.0026 max mem: 19788 +Epoch: [15] [ 180/2138] eta: 1:50:07 lr: 3.265398364993767e-05 loss: 0.0347 (0.0356) time: 3.0450 data: 0.0026 max mem: 19788 +Epoch: [15] [ 190/2138] eta: 1:49:04 lr: 3.264846658350979e-05 loss: 0.0305 (0.0353) time: 3.0669 data: 0.0029 max mem: 19788 +Epoch: [15] [ 200/2138] eta: 1:48:30 lr: 3.264294941349156e-05 loss: 0.0297 (0.0354) time: 3.2236 data: 0.0030 max mem: 19788 +Epoch: [15] [ 210/2138] eta: 1:47:32 lr: 3.263743213986159e-05 loss: 0.0292 (0.0354) time: 3.2266 data: 0.0029 max mem: 19788 +Epoch: [15] [ 220/2138] eta: 1:46:37 lr: 3.263191476259847e-05 loss: 0.0292 (0.0351) time: 3.0947 data: 0.0027 max mem: 19788 +Epoch: [15] [ 230/2138] eta: 1:46:18 lr: 3.2626397281680774e-05 loss: 0.0301 (0.0353) time: 3.3009 data: 0.0025 max mem: 19788 +Epoch: [15] [ 240/2138] eta: 1:45:44 lr: 3.262087969708708e-05 loss: 0.0352 (0.0354) time: 3.4199 data: 0.0025 max mem: 19788 +Epoch: [15] [ 250/2138] eta: 1:45:19 lr: 3.261536200879596e-05 loss: 0.0334 (0.0354) time: 3.3994 data: 0.0025 max mem: 19788 +Epoch: [15] [ 260/2138] eta: 1:44:33 lr: 3.2609844216785975e-05 loss: 0.0303 (0.0357) time: 3.3160 data: 0.0025 max mem: 19788 +Epoch: [15] [ 270/2138] eta: 1:43:54 lr: 3.2604326321035665e-05 loss: 0.0316 (0.0356) time: 3.2169 data: 0.0025 max mem: 19788 +Epoch: [15] [ 280/2138] eta: 1:43:09 lr: 3.2598808321523575e-05 loss: 0.0330 (0.0355) time: 3.2103 data: 0.0027 max mem: 19788 +Epoch: [15] [ 290/2138] eta: 1:42:46 lr: 3.259329021822823e-05 loss: 0.0343 (0.0356) time: 3.3228 data: 0.0028 max mem: 19788 +Epoch: [15] [ 300/2138] eta: 1:42:28 lr: 3.258777201112818e-05 loss: 0.0372 (0.0358) time: 3.5425 data: 0.0026 max mem: 19788 +Epoch: [15] [ 310/2138] eta: 1:41:45 lr: 3.258225370020192e-05 loss: 0.0318 (0.0356) time: 3.3837 data: 0.0023 max mem: 19788 +Epoch: [15] [ 320/2138] eta: 1:41:00 lr: 3.257673528542795e-05 loss: 0.0247 (0.0353) time: 3.1574 data: 0.0023 max mem: 19788 +Epoch: [15] [ 330/2138] eta: 1:40:25 lr: 3.257121676678478e-05 loss: 0.0272 (0.0355) time: 3.2248 data: 0.0027 max mem: 19788 +Epoch: [15] [ 340/2138] eta: 1:39:41 lr: 3.256569814425092e-05 loss: 0.0330 (0.0354) time: 3.2170 data: 0.0027 max mem: 19788 +Epoch: [15] [ 350/2138] eta: 1:39:06 lr: 3.256017941780481e-05 loss: 0.0266 (0.0353) time: 3.2135 data: 0.0023 max mem: 19788 +Epoch: [15] [ 360/2138] eta: 1:38:29 lr: 3.255466058742496e-05 loss: 0.0284 (0.0354) time: 3.2769 data: 0.0025 max mem: 19788 +Epoch: [15] [ 370/2138] eta: 1:37:47 lr: 3.254914165308981e-05 loss: 0.0365 (0.0353) time: 3.1883 data: 0.0033 max mem: 19788 +Epoch: [15] [ 380/2138] eta: 1:37:08 lr: 3.254362261477783e-05 loss: 0.0342 (0.0354) time: 3.1646 data: 0.0033 max mem: 19788 +Epoch: [15] [ 390/2138] eta: 1:36:31 lr: 3.2538103472467464e-05 loss: 0.0274 (0.0352) time: 3.2114 data: 0.0031 max mem: 19788 +Epoch: [15] [ 400/2138] eta: 1:35:53 lr: 3.253258422613715e-05 loss: 0.0315 (0.0352) time: 3.2091 data: 0.0030 max mem: 19788 +Epoch: [15] [ 410/2138] eta: 1:35:12 lr: 3.2527064875765325e-05 loss: 0.0315 (0.0351) time: 3.1592 data: 0.0026 max mem: 19788 +Epoch: [15] [ 420/2138] eta: 1:34:31 lr: 3.2521545421330404e-05 loss: 0.0301 (0.0350) time: 3.1179 data: 0.0025 max mem: 19788 +Epoch: [15] [ 430/2138] eta: 1:34:00 lr: 3.251602586281079e-05 loss: 0.0286 (0.0350) time: 3.2415 data: 0.0024 max mem: 19788 +Epoch: [15] [ 440/2138] eta: 1:33:31 lr: 3.251050620018492e-05 loss: 0.0292 (0.0351) time: 3.3844 data: 0.0022 max mem: 19788 +Epoch: [15] [ 450/2138] eta: 1:32:48 lr: 3.250498643343116e-05 loss: 0.0292 (0.0349) time: 3.2143 data: 0.0023 max mem: 19788 +Epoch: [15] [ 460/2138] eta: 1:32:05 lr: 3.249946656252791e-05 loss: 0.0308 (0.0351) time: 3.0339 data: 0.0023 max mem: 19788 +Epoch: [15] [ 470/2138] eta: 1:31:23 lr: 3.249394658745355e-05 loss: 0.0323 (0.0350) time: 3.0266 data: 0.0023 max mem: 19788 +Epoch: [15] [ 480/2138] eta: 1:30:41 lr: 3.2488426508186446e-05 loss: 0.0346 (0.0351) time: 3.0206 data: 0.0024 max mem: 19788 +Epoch: [15] [ 490/2138] eta: 1:29:59 lr: 3.248290632470497e-05 loss: 0.0349 (0.0351) time: 3.0288 data: 0.0026 max mem: 19788 +Epoch: [15] [ 500/2138] eta: 1:29:30 lr: 3.247738603698747e-05 loss: 0.0345 (0.0352) time: 3.2088 data: 0.0025 max mem: 19788 +Epoch: [15] [ 510/2138] eta: 1:28:49 lr: 3.247186564501228e-05 loss: 0.0312 (0.0351) time: 3.2011 data: 0.0023 max mem: 19788 +Epoch: [15] [ 520/2138] eta: 1:28:15 lr: 3.246634514875776e-05 loss: 0.0299 (0.0351) time: 3.1265 data: 0.0025 max mem: 19788 +Epoch: [15] [ 530/2138] eta: 1:27:38 lr: 3.2460824548202215e-05 loss: 0.0314 (0.0351) time: 3.1818 data: 0.0025 max mem: 19788 +Epoch: [15] [ 540/2138] eta: 1:27:04 lr: 3.245530384332398e-05 loss: 0.0314 (0.0350) time: 3.1791 data: 0.0022 max mem: 19788 +Epoch: [15] [ 550/2138] eta: 1:26:27 lr: 3.244978303410135e-05 loss: 0.0331 (0.0351) time: 3.1800 data: 0.0022 max mem: 19788 +Epoch: [15] [ 560/2138] eta: 1:25:53 lr: 3.244426212051265e-05 loss: 0.0346 (0.0352) time: 3.1579 data: 0.0021 max mem: 19788 +Epoch: [15] [ 570/2138] eta: 1:25:14 lr: 3.2438741102536154e-05 loss: 0.0308 (0.0352) time: 3.1216 data: 0.0022 max mem: 19788 +Epoch: [15] [ 580/2138] eta: 1:24:36 lr: 3.243321998015016e-05 loss: 0.0301 (0.0352) time: 3.0570 data: 0.0026 max mem: 19788 +Epoch: [15] [ 590/2138] eta: 1:23:58 lr: 3.2427698753332925e-05 loss: 0.0291 (0.0351) time: 3.0493 data: 0.0025 max mem: 19788 +Epoch: [15] [ 600/2138] eta: 1:23:21 lr: 3.242217742206273e-05 loss: 0.0306 (0.0352) time: 3.0695 data: 0.0023 max mem: 19788 +Epoch: [15] [ 610/2138] eta: 1:22:48 lr: 3.241665598631784e-05 loss: 0.0306 (0.0352) time: 3.1602 data: 0.0025 max mem: 19788 +Epoch: [15] [ 620/2138] eta: 1:22:18 lr: 3.24111344460765e-05 loss: 0.0331 (0.0353) time: 3.2845 data: 0.0027 max mem: 19788 +Epoch: [15] [ 630/2138] eta: 1:21:45 lr: 3.240561280131694e-05 loss: 0.0327 (0.0353) time: 3.2906 data: 0.0027 max mem: 19788 +Epoch: [15] [ 640/2138] eta: 1:21:10 lr: 3.24000910520174e-05 loss: 0.0312 (0.0353) time: 3.1846 data: 0.0027 max mem: 19788 +Epoch: [15] [ 650/2138] eta: 1:20:39 lr: 3.239456919815612e-05 loss: 0.0316 (0.0352) time: 3.2477 data: 0.0026 max mem: 19788 +Epoch: [15] [ 660/2138] eta: 1:20:04 lr: 3.238904723971129e-05 loss: 0.0320 (0.0353) time: 3.2311 data: 0.0025 max mem: 19788 +Epoch: [15] [ 670/2138] eta: 1:19:28 lr: 3.2383525176661136e-05 loss: 0.0337 (0.0353) time: 3.1027 data: 0.0028 max mem: 19788 +Epoch: [15] [ 680/2138] eta: 1:18:54 lr: 3.237800300898386e-05 loss: 0.0267 (0.0352) time: 3.1394 data: 0.0029 max mem: 19788 +Epoch: [15] [ 690/2138] eta: 1:18:23 lr: 3.237248073665763e-05 loss: 0.0289 (0.0351) time: 3.2629 data: 0.0028 max mem: 19788 +Epoch: [15] [ 700/2138] eta: 1:17:48 lr: 3.236695835966064e-05 loss: 0.0303 (0.0351) time: 3.2304 data: 0.0030 max mem: 19788 +Epoch: [15] [ 710/2138] eta: 1:17:16 lr: 3.236143587797106e-05 loss: 0.0314 (0.0351) time: 3.1952 data: 0.0029 max mem: 19788 +Epoch: [15] [ 720/2138] eta: 1:16:48 lr: 3.235591329156706e-05 loss: 0.0306 (0.0350) time: 3.3676 data: 0.0024 max mem: 19788 +Epoch: [15] [ 730/2138] eta: 1:16:16 lr: 3.2350390600426786e-05 loss: 0.0306 (0.0350) time: 3.3593 data: 0.0025 max mem: 19788 +Epoch: [15] [ 740/2138] eta: 1:15:44 lr: 3.2344867804528386e-05 loss: 0.0354 (0.0350) time: 3.2618 data: 0.0027 max mem: 19788 +Epoch: [15] [ 750/2138] eta: 1:15:08 lr: 3.233934490385e-05 loss: 0.0319 (0.0350) time: 3.1857 data: 0.0026 max mem: 19788 +Epoch: [15] [ 760/2138] eta: 1:14:36 lr: 3.2333821898369754e-05 loss: 0.0319 (0.0350) time: 3.1733 data: 0.0028 max mem: 19788 +Epoch: [15] [ 770/2138] eta: 1:14:04 lr: 3.2328298788065774e-05 loss: 0.0305 (0.0349) time: 3.2655 data: 0.0026 max mem: 19788 +Epoch: [15] [ 780/2138] eta: 1:13:35 lr: 3.2322775572916165e-05 loss: 0.0275 (0.0349) time: 3.3617 data: 0.0024 max mem: 19788 +Epoch: [15] [ 790/2138] eta: 1:13:03 lr: 3.231725225289903e-05 loss: 0.0266 (0.0348) time: 3.3633 data: 0.0025 max mem: 19788 +Epoch: [15] [ 800/2138] eta: 1:12:31 lr: 3.2311728827992474e-05 loss: 0.0285 (0.0348) time: 3.2946 data: 0.0022 max mem: 19788 +Epoch: [15] [ 810/2138] eta: 1:11:57 lr: 3.230620529817457e-05 loss: 0.0308 (0.0347) time: 3.2195 data: 0.0024 max mem: 19788 +Epoch: [15] [ 820/2138] eta: 1:11:29 lr: 3.2300681663423386e-05 loss: 0.0288 (0.0347) time: 3.3348 data: 0.0027 max mem: 19788 +Epoch: [15] [ 830/2138] eta: 1:11:00 lr: 3.229515792371701e-05 loss: 0.0281 (0.0347) time: 3.5208 data: 0.0026 max mem: 19788 +Epoch: [15] [ 840/2138] eta: 1:10:29 lr: 3.2289634079033496e-05 loss: 0.0284 (0.0347) time: 3.4375 data: 0.0024 max mem: 19788 +Epoch: [15] [ 850/2138] eta: 1:09:55 lr: 3.228411012935089e-05 loss: 0.0308 (0.0347) time: 3.2496 data: 0.0024 max mem: 19788 +Epoch: [15] [ 860/2138] eta: 1:09:24 lr: 3.2278586074647226e-05 loss: 0.0318 (0.0347) time: 3.2693 data: 0.0024 max mem: 19788 +Epoch: [15] [ 870/2138] eta: 1:08:49 lr: 3.227306191490054e-05 loss: 0.0306 (0.0347) time: 3.2437 data: 0.0024 max mem: 19788 +Epoch: [15] [ 880/2138] eta: 1:08:15 lr: 3.226753765008887e-05 loss: 0.0306 (0.0346) time: 3.1119 data: 0.0025 max mem: 19788 +Epoch: [15] [ 890/2138] eta: 1:07:39 lr: 3.226201328019023e-05 loss: 0.0291 (0.0346) time: 3.0788 data: 0.0025 max mem: 19788 +Epoch: [15] [ 900/2138] eta: 1:07:04 lr: 3.225648880518261e-05 loss: 0.0284 (0.0346) time: 3.0273 data: 0.0026 max mem: 19788 +Epoch: [15] [ 910/2138] eta: 1:06:32 lr: 3.2250964225044e-05 loss: 0.0276 (0.0345) time: 3.1539 data: 0.0026 max mem: 19788 +Epoch: [15] [ 920/2138] eta: 1:05:57 lr: 3.224543953975242e-05 loss: 0.0281 (0.0344) time: 3.2040 data: 0.0027 max mem: 19788 +Epoch: [15] [ 930/2138] eta: 1:05:23 lr: 3.2239914749285834e-05 loss: 0.0325 (0.0345) time: 3.1041 data: 0.0027 max mem: 19788 +Epoch: [15] [ 940/2138] eta: 1:04:50 lr: 3.223438985362221e-05 loss: 0.0359 (0.0345) time: 3.1364 data: 0.0024 max mem: 19788 +Epoch: [15] [ 950/2138] eta: 1:04:13 lr: 3.22288648527395e-05 loss: 0.0310 (0.0345) time: 3.0562 data: 0.0022 max mem: 19788 +Epoch: [15] [ 960/2138] eta: 1:03:37 lr: 3.222333974661568e-05 loss: 0.0321 (0.0345) time: 2.9392 data: 0.0024 max mem: 19788 +Epoch: [15] [ 970/2138] eta: 1:03:02 lr: 3.2217814535228695e-05 loss: 0.0349 (0.0345) time: 2.9736 data: 0.0025 max mem: 19788 +Epoch: [15] [ 980/2138] eta: 1:02:30 lr: 3.2212289218556455e-05 loss: 0.0297 (0.0345) time: 3.1658 data: 0.0024 max mem: 19788 +Epoch: [15] [ 990/2138] eta: 1:01:57 lr: 3.220676379657692e-05 loss: 0.0274 (0.0344) time: 3.2463 data: 0.0025 max mem: 19788 +Epoch: [15] [1000/2138] eta: 1:01:24 lr: 3.220123826926798e-05 loss: 0.0274 (0.0344) time: 3.1644 data: 0.0026 max mem: 19788 +Epoch: [15] [1010/2138] eta: 1:00:55 lr: 3.219571263660755e-05 loss: 0.0308 (0.0344) time: 3.3455 data: 0.0026 max mem: 19788 +Epoch: [15] [1020/2138] eta: 1:00:22 lr: 3.2190186898573544e-05 loss: 0.0328 (0.0344) time: 3.3835 data: 0.0025 max mem: 19788 +Epoch: [15] [1030/2138] eta: 0:59:49 lr: 3.218466105514385e-05 loss: 0.0283 (0.0343) time: 3.1991 data: 0.0024 max mem: 19788 +Epoch: [15] [1040/2138] eta: 0:59:19 lr: 3.217913510629634e-05 loss: 0.0290 (0.0344) time: 3.3237 data: 0.0026 max mem: 19788 +Epoch: [15] [1050/2138] eta: 0:58:46 lr: 3.2173609052008884e-05 loss: 0.0313 (0.0344) time: 3.3229 data: 0.0028 max mem: 19788 +Epoch: [15] [1060/2138] eta: 0:58:15 lr: 3.216808289225937e-05 loss: 0.0300 (0.0344) time: 3.2721 data: 0.0027 max mem: 19788 +Epoch: [15] [1070/2138] eta: 0:57:42 lr: 3.2162556627025635e-05 loss: 0.0330 (0.0344) time: 3.2769 data: 0.0027 max mem: 19788 +Epoch: [15] [1080/2138] eta: 0:57:10 lr: 3.2157030256285545e-05 loss: 0.0296 (0.0344) time: 3.2410 data: 0.0026 max mem: 19788 +Epoch: [15] [1090/2138] eta: 0:56:37 lr: 3.2151503780016914e-05 loss: 0.0296 (0.0343) time: 3.2665 data: 0.0024 max mem: 19788 +Epoch: [15] [1100/2138] eta: 0:56:04 lr: 3.214597719819758e-05 loss: 0.0343 (0.0344) time: 3.1796 data: 0.0023 max mem: 19788 +Epoch: [15] [1110/2138] eta: 0:55:32 lr: 3.214045051080538e-05 loss: 0.0343 (0.0344) time: 3.1966 data: 0.0023 max mem: 19788 +Epoch: [15] [1120/2138] eta: 0:55:01 lr: 3.21349237178181e-05 loss: 0.0376 (0.0344) time: 3.3153 data: 0.0023 max mem: 19788 +Epoch: [15] [1130/2138] eta: 0:54:26 lr: 3.212939681921356e-05 loss: 0.0343 (0.0345) time: 3.2135 data: 0.0025 max mem: 19788 +Epoch: [15] [1140/2138] eta: 0:53:55 lr: 3.2123869814969546e-05 loss: 0.0325 (0.0345) time: 3.1666 data: 0.0026 max mem: 19788 +Epoch: [15] [1150/2138] eta: 0:53:20 lr: 3.211834270506386e-05 loss: 0.0292 (0.0344) time: 3.1747 data: 0.0025 max mem: 19788 +Epoch: [15] [1160/2138] eta: 0:52:46 lr: 3.2112815489474255e-05 loss: 0.0279 (0.0344) time: 3.0473 data: 0.0026 max mem: 19788 +Epoch: [15] [1170/2138] eta: 0:52:13 lr: 3.2107288168178504e-05 loss: 0.0286 (0.0343) time: 3.0547 data: 0.0029 max mem: 19788 +Epoch: [15] [1180/2138] eta: 0:51:39 lr: 3.2101760741154366e-05 loss: 0.0300 (0.0345) time: 3.0517 data: 0.0029 max mem: 19788 +Epoch: [15] [1190/2138] eta: 0:51:05 lr: 3.209623320837961e-05 loss: 0.0306 (0.0345) time: 3.0412 data: 0.0026 max mem: 19788 +Epoch: [15] [1200/2138] eta: 0:50:31 lr: 3.209070556983195e-05 loss: 0.0286 (0.0344) time: 3.0616 data: 0.0025 max mem: 19788 +Epoch: [15] [1210/2138] eta: 0:49:59 lr: 3.2085177825489124e-05 loss: 0.0344 (0.0345) time: 3.1497 data: 0.0026 max mem: 19788 +Epoch: [15] [1220/2138] eta: 0:49:27 lr: 3.207964997532886e-05 loss: 0.0316 (0.0345) time: 3.2287 data: 0.0025 max mem: 19788 +Epoch: [15] [1230/2138] eta: 0:48:55 lr: 3.207412201932887e-05 loss: 0.0316 (0.0345) time: 3.2677 data: 0.0026 max mem: 19788 +Epoch: [15] [1240/2138] eta: 0:48:21 lr: 3.206859395746686e-05 loss: 0.0319 (0.0345) time: 3.1712 data: 0.0028 max mem: 19788 +Epoch: [15] [1250/2138] eta: 0:47:48 lr: 3.2063065789720515e-05 loss: 0.0337 (0.0345) time: 3.0918 data: 0.0028 max mem: 19788 +Epoch: [15] [1260/2138] eta: 0:47:15 lr: 3.2057537516067526e-05 loss: 0.0301 (0.0345) time: 3.0959 data: 0.0027 max mem: 19788 +Epoch: [15] [1270/2138] eta: 0:46:41 lr: 3.2052009136485585e-05 loss: 0.0290 (0.0344) time: 3.0542 data: 0.0025 max mem: 19788 +Epoch: [15] [1280/2138] eta: 0:46:07 lr: 3.2046480650952346e-05 loss: 0.0281 (0.0344) time: 3.0431 data: 0.0025 max mem: 19788 +Epoch: [15] [1290/2138] eta: 0:45:34 lr: 3.204095205944547e-05 loss: 0.0321 (0.0344) time: 3.0641 data: 0.0025 max mem: 19788 +Epoch: [15] [1300/2138] eta: 0:45:01 lr: 3.203542336194261e-05 loss: 0.0321 (0.0344) time: 3.0868 data: 0.0023 max mem: 19788 +Epoch: [15] [1310/2138] eta: 0:44:30 lr: 3.202989455842141e-05 loss: 0.0266 (0.0344) time: 3.2694 data: 0.0024 max mem: 19788 +Epoch: [15] [1320/2138] eta: 0:43:57 lr: 3.20243656488595e-05 loss: 0.0339 (0.0344) time: 3.2813 data: 0.0025 max mem: 19788 +Epoch: [15] [1330/2138] eta: 0:43:24 lr: 3.20188366332345e-05 loss: 0.0339 (0.0344) time: 3.0818 data: 0.0024 max mem: 19788 +Epoch: [15] [1340/2138] eta: 0:42:52 lr: 3.201330751152403e-05 loss: 0.0352 (0.0344) time: 3.1617 data: 0.0028 max mem: 19788 +Epoch: [15] [1350/2138] eta: 0:42:22 lr: 3.2007778283705705e-05 loss: 0.0378 (0.0345) time: 3.4173 data: 0.0028 max mem: 19788 +Epoch: [15] [1360/2138] eta: 0:41:50 lr: 3.200224894975709e-05 loss: 0.0378 (0.0345) time: 3.4085 data: 0.0027 max mem: 19788 +Epoch: [15] [1370/2138] eta: 0:41:18 lr: 3.1996719509655804e-05 loss: 0.0378 (0.0346) time: 3.2475 data: 0.0026 max mem: 19788 +Epoch: [15] [1380/2138] eta: 0:40:45 lr: 3.199118996337942e-05 loss: 0.0363 (0.0346) time: 3.2026 data: 0.0026 max mem: 19788 +Epoch: [15] [1390/2138] eta: 0:40:12 lr: 3.198566031090549e-05 loss: 0.0317 (0.0345) time: 3.1445 data: 0.0031 max mem: 19788 +Epoch: [15] [1400/2138] eta: 0:39:42 lr: 3.198013055221159e-05 loss: 0.0301 (0.0345) time: 3.3402 data: 0.0031 max mem: 19788 +Epoch: [15] [1410/2138] eta: 0:39:10 lr: 3.1974600687275266e-05 loss: 0.0308 (0.0345) time: 3.4796 data: 0.0025 max mem: 19788 +Epoch: [15] [1420/2138] eta: 0:38:38 lr: 3.196907071607407e-05 loss: 0.0304 (0.0345) time: 3.3016 data: 0.0024 max mem: 19788 +Epoch: [15] [1430/2138] eta: 0:38:06 lr: 3.196354063858552e-05 loss: 0.0304 (0.0345) time: 3.2698 data: 0.0026 max mem: 19788 +Epoch: [15] [1440/2138] eta: 0:37:35 lr: 3.195801045478714e-05 loss: 0.0324 (0.0345) time: 3.3609 data: 0.0025 max mem: 19788 +Epoch: [15] [1450/2138] eta: 0:37:02 lr: 3.1952480164656464e-05 loss: 0.0332 (0.0346) time: 3.2809 data: 0.0024 max mem: 19788 +Epoch: [15] [1460/2138] eta: 0:36:29 lr: 3.1946949768170986e-05 loss: 0.0381 (0.0346) time: 3.1384 data: 0.0025 max mem: 19788 +Epoch: [15] [1470/2138] eta: 0:35:56 lr: 3.19414192653082e-05 loss: 0.0363 (0.0347) time: 3.1277 data: 0.0027 max mem: 19788 +Epoch: [15] [1480/2138] eta: 0:35:24 lr: 3.193588865604559e-05 loss: 0.0321 (0.0346) time: 3.1661 data: 0.0029 max mem: 19788 +Epoch: [15] [1490/2138] eta: 0:34:51 lr: 3.193035794036065e-05 loss: 0.0321 (0.0347) time: 3.1126 data: 0.0032 max mem: 19788 +Epoch: [15] [1500/2138] eta: 0:34:18 lr: 3.192482711823084e-05 loss: 0.0354 (0.0347) time: 3.0748 data: 0.0030 max mem: 19788 +Epoch: [15] [1510/2138] eta: 0:33:46 lr: 3.191929618963362e-05 loss: 0.0344 (0.0347) time: 3.1454 data: 0.0027 max mem: 19788 +Epoch: [15] [1520/2138] eta: 0:33:13 lr: 3.1913765154546444e-05 loss: 0.0294 (0.0347) time: 3.1902 data: 0.0031 max mem: 19788 +Epoch: [15] [1530/2138] eta: 0:32:42 lr: 3.190823401294675e-05 loss: 0.0291 (0.0347) time: 3.3309 data: 0.0029 max mem: 19788 +Epoch: [15] [1540/2138] eta: 0:32:11 lr: 3.1902702764811975e-05 loss: 0.0316 (0.0346) time: 3.5298 data: 0.0027 max mem: 19788 +Epoch: [15] [1550/2138] eta: 0:31:40 lr: 3.189717141011955e-05 loss: 0.0330 (0.0347) time: 3.5222 data: 0.0027 max mem: 19788 +Epoch: [15] [1560/2138] eta: 0:31:09 lr: 3.1891639948846875e-05 loss: 0.0311 (0.0347) time: 3.5428 data: 0.0028 max mem: 19788 +Epoch: [15] [1570/2138] eta: 0:30:36 lr: 3.188610838097136e-05 loss: 0.0305 (0.0347) time: 3.4168 data: 0.0027 max mem: 19788 +Epoch: [15] [1580/2138] eta: 0:30:03 lr: 3.1880576706470413e-05 loss: 0.0307 (0.0347) time: 3.1301 data: 0.0024 max mem: 19788 +Epoch: [15] [1590/2138] eta: 0:29:31 lr: 3.1875044925321413e-05 loss: 0.0322 (0.0347) time: 3.1043 data: 0.0023 max mem: 19788 +Epoch: [15] [1600/2138] eta: 0:28:58 lr: 3.186951303750173e-05 loss: 0.0332 (0.0347) time: 3.1373 data: 0.0023 max mem: 19788 +Epoch: [15] [1610/2138] eta: 0:28:26 lr: 3.1863981042988745e-05 loss: 0.0327 (0.0347) time: 3.1636 data: 0.0026 max mem: 19788 +Epoch: [15] [1620/2138] eta: 0:27:53 lr: 3.1858448941759824e-05 loss: 0.0275 (0.0347) time: 3.1840 data: 0.0029 max mem: 19788 +Epoch: [15] [1630/2138] eta: 0:27:22 lr: 3.185291673379229e-05 loss: 0.0273 (0.0346) time: 3.3614 data: 0.0026 max mem: 19788 +Epoch: [15] [1640/2138] eta: 0:26:50 lr: 3.184738441906351e-05 loss: 0.0341 (0.0347) time: 3.4987 data: 0.0024 max mem: 19788 +Epoch: [15] [1650/2138] eta: 0:26:17 lr: 3.1841851997550814e-05 loss: 0.0341 (0.0347) time: 3.2620 data: 0.0026 max mem: 19788 +Epoch: [15] [1660/2138] eta: 0:25:45 lr: 3.183631946923152e-05 loss: 0.0312 (0.0347) time: 3.1876 data: 0.0026 max mem: 19788 +Epoch: [15] [1670/2138] eta: 0:25:12 lr: 3.183078683408294e-05 loss: 0.0284 (0.0347) time: 3.1943 data: 0.0023 max mem: 19788 +Epoch: [15] [1680/2138] eta: 0:24:41 lr: 3.182525409208237e-05 loss: 0.0305 (0.0346) time: 3.3621 data: 0.0022 max mem: 19788 +Epoch: [15] [1690/2138] eta: 0:24:09 lr: 3.1819721243207134e-05 loss: 0.0312 (0.0346) time: 3.4824 data: 0.0023 max mem: 19788 +Epoch: [15] [1700/2138] eta: 0:23:37 lr: 3.1814188287434496e-05 loss: 0.0282 (0.0346) time: 3.2673 data: 0.0023 max mem: 19788 +Epoch: [15] [1710/2138] eta: 0:23:04 lr: 3.180865522474174e-05 loss: 0.0290 (0.0346) time: 3.1211 data: 0.0026 max mem: 19788 +Epoch: [15] [1720/2138] eta: 0:22:31 lr: 3.180312205510613e-05 loss: 0.0316 (0.0346) time: 3.0586 data: 0.0032 max mem: 19788 +Epoch: [15] [1730/2138] eta: 0:21:58 lr: 3.179758877850493e-05 loss: 0.0331 (0.0346) time: 3.0550 data: 0.0029 max mem: 19788 +Epoch: [15] [1740/2138] eta: 0:21:26 lr: 3.179205539491538e-05 loss: 0.0349 (0.0346) time: 3.0524 data: 0.0023 max mem: 19788 +Epoch: [15] [1750/2138] eta: 0:20:54 lr: 3.178652190431473e-05 loss: 0.0349 (0.0346) time: 3.2561 data: 0.0023 max mem: 19788 +Epoch: [15] [1760/2138] eta: 0:20:21 lr: 3.1780988306680205e-05 loss: 0.0323 (0.0347) time: 3.3516 data: 0.0023 max mem: 19788 +Epoch: [15] [1770/2138] eta: 0:19:50 lr: 3.1775454601989035e-05 loss: 0.0300 (0.0346) time: 3.3243 data: 0.0025 max mem: 19788 +Epoch: [15] [1780/2138] eta: 0:19:17 lr: 3.1769920790218426e-05 loss: 0.0297 (0.0346) time: 3.2927 data: 0.0026 max mem: 19788 +Epoch: [15] [1790/2138] eta: 0:18:45 lr: 3.176438687134558e-05 loss: 0.0277 (0.0346) time: 3.2417 data: 0.0024 max mem: 19788 +Epoch: [15] [1800/2138] eta: 0:18:13 lr: 3.175885284534769e-05 loss: 0.0358 (0.0347) time: 3.3419 data: 0.0025 max mem: 19788 +Epoch: [15] [1810/2138] eta: 0:17:40 lr: 3.1753318712201954e-05 loss: 0.0330 (0.0346) time: 3.2945 data: 0.0031 max mem: 19788 +Epoch: [15] [1820/2138] eta: 0:17:09 lr: 3.1747784471885535e-05 loss: 0.0282 (0.0346) time: 3.4113 data: 0.0031 max mem: 19788 +Epoch: [15] [1830/2138] eta: 0:16:37 lr: 3.17422501243756e-05 loss: 0.0278 (0.0346) time: 3.6728 data: 0.0026 max mem: 19788 +Epoch: [15] [1840/2138] eta: 0:16:05 lr: 3.1736715669649305e-05 loss: 0.0291 (0.0346) time: 3.4890 data: 0.0029 max mem: 19788 +Epoch: [15] [1850/2138] eta: 0:15:32 lr: 3.17311811076838e-05 loss: 0.0352 (0.0346) time: 3.1864 data: 0.0030 max mem: 19788 +Epoch: [15] [1860/2138] eta: 0:15:00 lr: 3.172564643845623e-05 loss: 0.0345 (0.0346) time: 3.0918 data: 0.0025 max mem: 19788 +Epoch: [15] [1870/2138] eta: 0:14:27 lr: 3.172011166194371e-05 loss: 0.0345 (0.0346) time: 3.0496 data: 0.0025 max mem: 19788 +Epoch: [15] [1880/2138] eta: 0:13:54 lr: 3.1714576778123365e-05 loss: 0.0307 (0.0346) time: 3.0716 data: 0.0027 max mem: 19788 +Epoch: [15] [1890/2138] eta: 0:13:22 lr: 3.170904178697232e-05 loss: 0.0303 (0.0346) time: 3.0766 data: 0.0025 max mem: 19788 +Epoch: [15] [1900/2138] eta: 0:12:49 lr: 3.1703506688467657e-05 loss: 0.0329 (0.0346) time: 3.0508 data: 0.0025 max mem: 19788 +Epoch: [15] [1910/2138] eta: 0:12:17 lr: 3.169797148258647e-05 loss: 0.0329 (0.0346) time: 3.0528 data: 0.0028 max mem: 19788 +Epoch: [15] [1920/2138] eta: 0:11:44 lr: 3.169243616930585e-05 loss: 0.0311 (0.0346) time: 3.1290 data: 0.0030 max mem: 19788 +Epoch: [15] [1930/2138] eta: 0:11:12 lr: 3.1686900748602863e-05 loss: 0.0326 (0.0346) time: 3.3002 data: 0.0029 max mem: 19788 +Epoch: [15] [1940/2138] eta: 0:10:40 lr: 3.168136522045457e-05 loss: 0.0317 (0.0346) time: 3.3823 data: 0.0025 max mem: 19788 +Epoch: [15] [1950/2138] eta: 0:10:08 lr: 3.167582958483804e-05 loss: 0.0301 (0.0346) time: 3.4760 data: 0.0023 max mem: 19788 +Epoch: [15] [1960/2138] eta: 0:09:35 lr: 3.1670293841730306e-05 loss: 0.0272 (0.0346) time: 3.3485 data: 0.0022 max mem: 19788 +Epoch: [15] [1970/2138] eta: 0:09:03 lr: 3.1664757991108404e-05 loss: 0.0272 (0.0346) time: 3.1114 data: 0.0022 max mem: 19788 +Epoch: [15] [1980/2138] eta: 0:08:31 lr: 3.1659222032949355e-05 loss: 0.0309 (0.0346) time: 3.2341 data: 0.0022 max mem: 19788 +Epoch: [15] [1990/2138] eta: 0:07:58 lr: 3.165368596723019e-05 loss: 0.0309 (0.0346) time: 3.2584 data: 0.0024 max mem: 19788 +Epoch: [15] [2000/2138] eta: 0:07:26 lr: 3.164814979392791e-05 loss: 0.0302 (0.0345) time: 3.1783 data: 0.0025 max mem: 19788 +Epoch: [15] [2010/2138] eta: 0:06:54 lr: 3.1642613513019514e-05 loss: 0.0307 (0.0345) time: 3.1658 data: 0.0024 max mem: 19788 +Epoch: [15] [2020/2138] eta: 0:06:21 lr: 3.163707712448199e-05 loss: 0.0316 (0.0345) time: 3.1849 data: 0.0024 max mem: 19788 +Epoch: [15] [2030/2138] eta: 0:05:49 lr: 3.1631540628292306e-05 loss: 0.0313 (0.0345) time: 3.1678 data: 0.0027 max mem: 19788 +Epoch: [15] [2040/2138] eta: 0:05:16 lr: 3.162600402442745e-05 loss: 0.0304 (0.0345) time: 3.1047 data: 0.0031 max mem: 19788 +Epoch: [15] [2050/2138] eta: 0:04:44 lr: 3.1620467312864375e-05 loss: 0.0305 (0.0345) time: 3.1417 data: 0.0030 max mem: 19788 +Epoch: [15] [2060/2138] eta: 0:04:12 lr: 3.1614930493580034e-05 loss: 0.0328 (0.0345) time: 3.2291 data: 0.0028 max mem: 19788 +Epoch: [15] [2070/2138] eta: 0:03:39 lr: 3.160939356655135e-05 loss: 0.0285 (0.0345) time: 3.3539 data: 0.0026 max mem: 19788 +Epoch: [15] [2080/2138] eta: 0:03:07 lr: 3.1603856531755294e-05 loss: 0.0285 (0.0345) time: 3.3543 data: 0.0026 max mem: 19788 +Epoch: [15] [2090/2138] eta: 0:02:35 lr: 3.159831938916876e-05 loss: 0.0325 (0.0345) time: 3.4150 data: 0.0025 max mem: 19788 +Epoch: [15] [2100/2138] eta: 0:02:02 lr: 3.159278213876866e-05 loss: 0.0325 (0.0345) time: 3.4324 data: 0.0025 max mem: 19788 +Epoch: [15] [2110/2138] eta: 0:01:30 lr: 3.158724478053191e-05 loss: 0.0334 (0.0345) time: 3.2897 data: 0.0026 max mem: 19788 +Epoch: [15] [2120/2138] eta: 0:00:58 lr: 3.15817073144354e-05 loss: 0.0386 (0.0346) time: 3.1962 data: 0.0026 max mem: 19788 +Epoch: [15] [2130/2138] eta: 0:00:25 lr: 3.157616974045602e-05 loss: 0.0358 (0.0346) time: 3.2347 data: 0.0025 max mem: 19788 +Epoch: [15] Total time: 1:55:20 +Test: [ 0/21770] eta: 13:55:46 time: 2.3035 data: 2.2272 max mem: 19788 +Test: [ 100/21770] eta: 0:25:22 time: 0.0437 data: 0.0015 max mem: 19788 +Test: [ 200/21770] eta: 0:20:58 time: 0.0496 data: 0.0015 max mem: 19788 +Test: [ 300/21770] eta: 0:19:14 time: 0.0446 data: 0.0017 max mem: 19788 +Test: [ 400/21770] eta: 0:18:44 time: 0.0434 data: 0.0016 max mem: 19788 +Test: [ 500/21770] eta: 0:18:23 time: 0.0495 data: 0.0017 max mem: 19788 +Test: [ 600/21770] eta: 0:18:05 time: 0.0440 data: 0.0016 max mem: 19788 +Test: [ 700/21770] eta: 0:17:40 time: 0.0428 data: 0.0015 max mem: 19788 +Test: [ 800/21770] eta: 0:17:18 time: 0.0435 data: 0.0015 max mem: 19788 +Test: [ 900/21770] eta: 0:17:05 time: 0.0474 data: 0.0016 max mem: 19788 +Test: [ 1000/21770] eta: 0:16:49 time: 0.0438 data: 0.0015 max mem: 19788 +Test: [ 1100/21770] eta: 0:16:46 time: 0.0440 data: 0.0017 max mem: 19788 +Test: [ 1200/21770] eta: 0:16:42 time: 0.0466 data: 0.0016 max mem: 19788 +Test: [ 1300/21770] eta: 0:16:28 time: 0.0427 data: 0.0014 max mem: 19788 +Test: [ 1400/21770] eta: 0:16:17 time: 0.0455 data: 0.0015 max mem: 19788 +Test: [ 1500/21770] eta: 0:16:13 time: 0.0449 data: 0.0015 max mem: 19788 +Test: [ 1600/21770] eta: 0:16:03 time: 0.0444 data: 0.0014 max mem: 19788 +Test: [ 1700/21770] eta: 0:15:59 time: 0.0506 data: 0.0019 max mem: 19788 +Test: [ 1800/21770] eta: 0:15:51 time: 0.0453 data: 0.0016 max mem: 19788 +Test: [ 1900/21770] eta: 0:15:43 time: 0.0435 data: 0.0014 max mem: 19788 +Test: [ 2000/21770] eta: 0:15:37 time: 0.0463 data: 0.0017 max mem: 19788 +Test: [ 2100/21770] eta: 0:15:29 time: 0.0433 data: 0.0015 max mem: 19788 +Test: [ 2200/21770] eta: 0:15:23 time: 0.0483 data: 0.0015 max mem: 19788 +Test: [ 2300/21770] eta: 0:15:20 time: 0.0534 data: 0.0015 max mem: 19788 +Test: [ 2400/21770] eta: 0:15:14 time: 0.0455 data: 0.0014 max mem: 19788 +Test: [ 2500/21770] eta: 0:15:07 time: 0.0443 data: 0.0015 max mem: 19788 +Test: [ 2600/21770] eta: 0:15:01 time: 0.0441 data: 0.0015 max mem: 19788 +Test: [ 2700/21770] eta: 0:14:55 time: 0.0476 data: 0.0016 max mem: 19788 +Test: [ 2800/21770] eta: 0:14:53 time: 0.0530 data: 0.0018 max mem: 19788 +Test: [ 2900/21770] eta: 0:14:50 time: 0.0530 data: 0.0018 max mem: 19788 +Test: [ 3000/21770] eta: 0:14:50 time: 0.0531 data: 0.0019 max mem: 19788 +Test: [ 3100/21770] eta: 0:14:44 time: 0.0454 data: 0.0014 max mem: 19788 +Test: [ 3200/21770] eta: 0:14:41 time: 0.0545 data: 0.0016 max mem: 19788 +Test: [ 3300/21770] eta: 0:14:38 time: 0.0448 data: 0.0015 max mem: 19788 +Test: [ 3400/21770] eta: 0:14:34 time: 0.0529 data: 0.0018 max mem: 19788 +Test: [ 3500/21770] eta: 0:14:31 time: 0.0489 data: 0.0017 max mem: 19788 +Test: [ 3600/21770] eta: 0:14:25 time: 0.0437 data: 0.0015 max mem: 19788 +Test: [ 3700/21770] eta: 0:14:21 time: 0.0541 data: 0.0018 max mem: 19788 +Test: [ 3800/21770] eta: 0:14:19 time: 0.0541 data: 0.0019 max mem: 19788 +Test: [ 3900/21770] eta: 0:14:15 time: 0.0465 data: 0.0017 max mem: 19788 +Test: [ 4000/21770] eta: 0:14:12 time: 0.0534 data: 0.0017 max mem: 19788 +Test: [ 4100/21770] eta: 0:14:08 time: 0.0510 data: 0.0017 max mem: 19788 +Test: [ 4200/21770] eta: 0:14:04 time: 0.0442 data: 0.0016 max mem: 19788 +Test: [ 4300/21770] eta: 0:14:00 time: 0.0532 data: 0.0017 max mem: 19788 +Test: [ 4400/21770] eta: 0:13:55 time: 0.0460 data: 0.0014 max mem: 19788 +Test: [ 4500/21770] eta: 0:13:52 time: 0.0509 data: 0.0018 max mem: 19788 +Test: [ 4600/21770] eta: 0:13:46 time: 0.0438 data: 0.0016 max mem: 19788 +Test: [ 4700/21770] eta: 0:13:41 time: 0.0474 data: 0.0018 max mem: 19788 +Test: [ 4800/21770] eta: 0:13:36 time: 0.0465 data: 0.0016 max mem: 19788 +Test: [ 4900/21770] eta: 0:13:33 time: 0.0513 data: 0.0017 max mem: 19788 +Test: [ 5000/21770] eta: 0:13:28 time: 0.0442 data: 0.0017 max mem: 19788 +Test: [ 5100/21770] eta: 0:13:24 time: 0.0462 data: 0.0016 max mem: 19788 +Test: [ 5200/21770] eta: 0:13:19 time: 0.0531 data: 0.0018 max mem: 19788 +Test: [ 5300/21770] eta: 0:13:16 time: 0.0544 data: 0.0019 max mem: 19788 +Test: [ 5400/21770] eta: 0:13:12 time: 0.0471 data: 0.0016 max mem: 19788 +Test: [ 5500/21770] eta: 0:13:06 time: 0.0470 data: 0.0016 max mem: 19788 +Test: [ 5600/21770] eta: 0:13:02 time: 0.0532 data: 0.0018 max mem: 19788 +Test: [ 5700/21770] eta: 0:12:58 time: 0.0432 data: 0.0015 max mem: 19788 +Test: [ 5800/21770] eta: 0:12:52 time: 0.0445 data: 0.0016 max mem: 19788 +Test: [ 5900/21770] eta: 0:12:48 time: 0.0528 data: 0.0019 max mem: 19788 +Test: [ 6000/21770] eta: 0:12:44 time: 0.0530 data: 0.0018 max mem: 19788 +Test: [ 6100/21770] eta: 0:12:39 time: 0.0500 data: 0.0015 max mem: 19788 +Test: [ 6200/21770] eta: 0:12:34 time: 0.0451 data: 0.0015 max mem: 19788 +Test: [ 6300/21770] eta: 0:12:28 time: 0.0464 data: 0.0015 max mem: 19788 +Test: [ 6400/21770] eta: 0:12:23 time: 0.0438 data: 0.0015 max mem: 19788 +Test: [ 6500/21770] eta: 0:12:18 time: 0.0512 data: 0.0016 max mem: 19788 +Test: [ 6600/21770] eta: 0:12:14 time: 0.0532 data: 0.0019 max mem: 19788 +Test: [ 6700/21770] eta: 0:12:10 time: 0.0516 data: 0.0019 max mem: 19788 +Test: [ 6800/21770] eta: 0:12:05 time: 0.0540 data: 0.0019 max mem: 19788 +Test: [ 6900/21770] eta: 0:12:01 time: 0.0554 data: 0.0019 max mem: 19788 +Test: [ 7000/21770] eta: 0:11:56 time: 0.0476 data: 0.0017 max mem: 19788 +Test: [ 7100/21770] eta: 0:11:51 time: 0.0487 data: 0.0017 max mem: 19788 +Test: [ 7200/21770] eta: 0:11:46 time: 0.0512 data: 0.0018 max mem: 19788 +Test: [ 7300/21770] eta: 0:11:41 time: 0.0513 data: 0.0017 max mem: 19788 +Test: [ 7400/21770] eta: 0:11:36 time: 0.0450 data: 0.0014 max mem: 19788 +Test: [ 7500/21770] eta: 0:11:31 time: 0.0460 data: 0.0016 max mem: 19788 +Test: [ 7600/21770] eta: 0:11:26 time: 0.0458 data: 0.0015 max mem: 19788 +Test: [ 7700/21770] eta: 0:11:20 time: 0.0468 data: 0.0015 max mem: 19788 +Test: [ 7800/21770] eta: 0:11:16 time: 0.0448 data: 0.0014 max mem: 19788 +Test: [ 7900/21770] eta: 0:11:11 time: 0.0453 data: 0.0016 max mem: 19788 +Test: [ 8000/21770] eta: 0:11:06 time: 0.0439 data: 0.0014 max mem: 19788 +Test: [ 8100/21770] eta: 0:11:00 time: 0.0527 data: 0.0018 max mem: 19788 +Test: [ 8200/21770] eta: 0:10:55 time: 0.0448 data: 0.0015 max mem: 19788 +Test: [ 8300/21770] eta: 0:10:51 time: 0.0445 data: 0.0016 max mem: 19788 +Test: [ 8400/21770] eta: 0:10:46 time: 0.0509 data: 0.0017 max mem: 19788 +Test: [ 8500/21770] eta: 0:10:41 time: 0.0544 data: 0.0019 max mem: 19788 +Test: [ 8600/21770] eta: 0:10:36 time: 0.0440 data: 0.0015 max mem: 19788 +Test: [ 8700/21770] eta: 0:10:31 time: 0.0441 data: 0.0014 max mem: 19788 +Test: [ 8800/21770] eta: 0:10:26 time: 0.0513 data: 0.0018 max mem: 19788 +Test: [ 8900/21770] eta: 0:10:21 time: 0.0440 data: 0.0014 max mem: 19788 +Test: [ 9000/21770] eta: 0:10:16 time: 0.0446 data: 0.0016 max mem: 19788 +Test: [ 9100/21770] eta: 0:10:10 time: 0.0433 data: 0.0015 max mem: 19788 +Test: [ 9200/21770] eta: 0:10:05 time: 0.0440 data: 0.0013 max mem: 19788 +Test: [ 9300/21770] eta: 0:10:00 time: 0.0437 data: 0.0015 max mem: 19788 +Test: [ 9400/21770] eta: 0:09:54 time: 0.0434 data: 0.0015 max mem: 19788 +Test: [ 9500/21770] eta: 0:09:49 time: 0.0432 data: 0.0015 max mem: 19788 +Test: [ 9600/21770] eta: 0:09:44 time: 0.0526 data: 0.0019 max mem: 19788 +Test: [ 9700/21770] eta: 0:09:40 time: 0.0538 data: 0.0018 max mem: 19788 +Test: [ 9800/21770] eta: 0:09:36 time: 0.0540 data: 0.0019 max mem: 19788 +Test: [ 9900/21770] eta: 0:09:31 time: 0.0526 data: 0.0017 max mem: 19788 +Test: [10000/21770] eta: 0:09:27 time: 0.0542 data: 0.0023 max mem: 19788 +Test: [10100/21770] eta: 0:09:22 time: 0.0452 data: 0.0017 max mem: 19788 +Test: [10200/21770] eta: 0:09:17 time: 0.0525 data: 0.0019 max mem: 19788 +Test: [10300/21770] eta: 0:09:13 time: 0.0542 data: 0.0019 max mem: 19788 +Test: [10400/21770] eta: 0:09:09 time: 0.0498 data: 0.0015 max mem: 19788 +Test: [10500/21770] eta: 0:09:04 time: 0.0484 data: 0.0015 max mem: 19788 +Test: [10600/21770] eta: 0:08:59 time: 0.0460 data: 0.0018 max mem: 19788 +Test: [10700/21770] eta: 0:08:54 time: 0.0462 data: 0.0016 max mem: 19788 +Test: [10800/21770] eta: 0:08:49 time: 0.0541 data: 0.0020 max mem: 19788 +Test: [10900/21770] eta: 0:08:45 time: 0.0482 data: 0.0016 max mem: 19788 +Test: [11000/21770] eta: 0:08:40 time: 0.0442 data: 0.0015 max mem: 19788 +Test: [11100/21770] eta: 0:08:35 time: 0.0448 data: 0.0015 max mem: 19788 +Test: [11200/21770] eta: 0:08:30 time: 0.0448 data: 0.0015 max mem: 19788 +Test: [11300/21770] eta: 0:08:25 time: 0.0542 data: 0.0018 max mem: 19788 +Test: [11400/21770] eta: 0:08:20 time: 0.0464 data: 0.0016 max mem: 19788 +Test: [11500/21770] eta: 0:08:15 time: 0.0450 data: 0.0016 max mem: 19788 +Test: [11600/21770] eta: 0:08:10 time: 0.0451 data: 0.0017 max mem: 19788 +Test: [11700/21770] eta: 0:08:06 time: 0.0485 data: 0.0016 max mem: 19788 +Test: [11800/21770] eta: 0:08:01 time: 0.0454 data: 0.0016 max mem: 19788 +Test: [11900/21770] eta: 0:07:56 time: 0.0538 data: 0.0018 max mem: 19788 +Test: [12000/21770] eta: 0:07:52 time: 0.0455 data: 0.0016 max mem: 19788 +Test: [12100/21770] eta: 0:07:47 time: 0.0461 data: 0.0017 max mem: 19788 +Test: [12200/21770] eta: 0:07:43 time: 0.0532 data: 0.0017 max mem: 19788 +Test: [12300/21770] eta: 0:07:38 time: 0.0464 data: 0.0015 max mem: 19788 +Test: [12400/21770] eta: 0:07:33 time: 0.0567 data: 0.0019 max mem: 19788 +Test: [12500/21770] eta: 0:07:29 time: 0.0510 data: 0.0019 max mem: 19788 +Test: [12600/21770] eta: 0:07:24 time: 0.0545 data: 0.0020 max mem: 19788 +Test: [12700/21770] eta: 0:07:19 time: 0.0477 data: 0.0016 max mem: 19788 +Test: [12800/21770] eta: 0:07:14 time: 0.0468 data: 0.0015 max mem: 19788 +Test: [12900/21770] eta: 0:07:10 time: 0.0444 data: 0.0016 max mem: 19788 +Test: [13000/21770] eta: 0:07:05 time: 0.0544 data: 0.0020 max mem: 19788 +Test: [13100/21770] eta: 0:07:01 time: 0.0571 data: 0.0019 max mem: 19788 +Test: [13200/21770] eta: 0:06:56 time: 0.0473 data: 0.0016 max mem: 19788 +Test: [13300/21770] eta: 0:06:51 time: 0.0541 data: 0.0019 max mem: 19788 +Test: [13400/21770] eta: 0:06:46 time: 0.0459 data: 0.0016 max mem: 19788 +Test: [13500/21770] eta: 0:06:41 time: 0.0453 data: 0.0016 max mem: 19788 +Test: [13600/21770] eta: 0:06:36 time: 0.0501 data: 0.0017 max mem: 19788 +Test: [13700/21770] eta: 0:06:32 time: 0.0564 data: 0.0015 max mem: 19788 +Test: [13800/21770] eta: 0:06:27 time: 0.0470 data: 0.0016 max mem: 19788 +Test: [13900/21770] eta: 0:06:22 time: 0.0452 data: 0.0018 max mem: 19788 +Test: [14000/21770] eta: 0:06:17 time: 0.0468 data: 0.0015 max mem: 19788 +Test: [14100/21770] eta: 0:06:12 time: 0.0470 data: 0.0015 max mem: 19788 +Test: [14200/21770] eta: 0:06:07 time: 0.0461 data: 0.0015 max mem: 19788 +Test: [14300/21770] eta: 0:06:03 time: 0.0493 data: 0.0015 max mem: 19788 +Test: [14400/21770] eta: 0:05:58 time: 0.0509 data: 0.0018 max mem: 19788 +Test: [14500/21770] eta: 0:05:53 time: 0.0559 data: 0.0019 max mem: 19788 +Test: [14600/21770] eta: 0:05:48 time: 0.0455 data: 0.0015 max mem: 19788 +Test: [14700/21770] eta: 0:05:43 time: 0.0462 data: 0.0018 max mem: 19788 +Test: [14800/21770] eta: 0:05:38 time: 0.0473 data: 0.0017 max mem: 19788 +Test: [14900/21770] eta: 0:05:34 time: 0.0542 data: 0.0019 max mem: 19788 +Test: [15000/21770] eta: 0:05:29 time: 0.0444 data: 0.0018 max mem: 19788 +Test: [15100/21770] eta: 0:05:24 time: 0.0468 data: 0.0016 max mem: 19788 +Test: [15200/21770] eta: 0:05:19 time: 0.0458 data: 0.0015 max mem: 19788 +Test: [15300/21770] eta: 0:05:14 time: 0.0459 data: 0.0015 max mem: 19788 +Test: [15400/21770] eta: 0:05:09 time: 0.0460 data: 0.0016 max mem: 19788 +Test: [15500/21770] eta: 0:05:04 time: 0.0455 data: 0.0015 max mem: 19788 +Test: [15600/21770] eta: 0:05:00 time: 0.0481 data: 0.0017 max mem: 19788 +Test: [15700/21770] eta: 0:04:55 time: 0.0502 data: 0.0017 max mem: 19788 +Test: [15800/21770] eta: 0:04:50 time: 0.0455 data: 0.0018 max mem: 19788 +Test: [15900/21770] eta: 0:04:45 time: 0.0460 data: 0.0015 max mem: 19788 +Test: [16000/21770] eta: 0:04:40 time: 0.0536 data: 0.0019 max mem: 19788 +Test: [16100/21770] eta: 0:04:36 time: 0.0548 data: 0.0020 max mem: 19788 +Test: [16200/21770] eta: 0:04:31 time: 0.0552 data: 0.0020 max mem: 19788 +Test: [16300/21770] eta: 0:04:26 time: 0.0489 data: 0.0016 max mem: 19788 +Test: [16400/21770] eta: 0:04:21 time: 0.0472 data: 0.0016 max mem: 19788 +Test: [16500/21770] eta: 0:04:17 time: 0.0440 data: 0.0015 max mem: 19788 +Test: [16600/21770] eta: 0:04:12 time: 0.0512 data: 0.0018 max mem: 19788 +Test: [16700/21770] eta: 0:04:07 time: 0.0536 data: 0.0019 max mem: 19788 +Test: [16800/21770] eta: 0:04:02 time: 0.0553 data: 0.0019 max mem: 19788 +Test: [16900/21770] eta: 0:03:57 time: 0.0470 data: 0.0016 max mem: 19788 +Test: [17000/21770] eta: 0:03:52 time: 0.0455 data: 0.0015 max mem: 19788 +Test: [17100/21770] eta: 0:03:47 time: 0.0453 data: 0.0015 max mem: 19788 +Test: [17200/21770] eta: 0:03:42 time: 0.0545 data: 0.0018 max mem: 19788 +Test: [17300/21770] eta: 0:03:38 time: 0.0537 data: 0.0019 max mem: 19788 +Test: [17400/21770] eta: 0:03:33 time: 0.0497 data: 0.0018 max mem: 19788 +Test: [17500/21770] eta: 0:03:28 time: 0.0498 data: 0.0018 max mem: 19788 +Test: [17600/21770] eta: 0:03:23 time: 0.0488 data: 0.0017 max mem: 19788 +Test: [17700/21770] eta: 0:03:18 time: 0.0521 data: 0.0019 max mem: 19788 +Test: [17800/21770] eta: 0:03:13 time: 0.0523 data: 0.0019 max mem: 19788 +Test: [17900/21770] eta: 0:03:08 time: 0.0555 data: 0.0018 max mem: 19788 +Test: [18000/21770] eta: 0:03:04 time: 0.0488 data: 0.0016 max mem: 19788 +Test: [18100/21770] eta: 0:02:59 time: 0.0453 data: 0.0015 max mem: 19788 +Test: [18200/21770] eta: 0:02:54 time: 0.0457 data: 0.0015 max mem: 19788 +Test: [18300/21770] eta: 0:02:49 time: 0.0454 data: 0.0017 max mem: 19788 +Test: [18400/21770] eta: 0:02:44 time: 0.0431 data: 0.0015 max mem: 19788 +Test: [18500/21770] eta: 0:02:39 time: 0.0487 data: 0.0016 max mem: 19788 +Test: [18600/21770] eta: 0:02:34 time: 0.0483 data: 0.0015 max mem: 19788 +Test: [18700/21770] eta: 0:02:29 time: 0.0475 data: 0.0020 max mem: 19788 +Test: [18800/21770] eta: 0:02:24 time: 0.0529 data: 0.0018 max mem: 19788 +Test: [18900/21770] eta: 0:02:19 time: 0.0466 data: 0.0018 max mem: 19788 +Test: [19000/21770] eta: 0:02:15 time: 0.0434 data: 0.0015 max mem: 19788 +Test: [19100/21770] eta: 0:02:10 time: 0.0547 data: 0.0019 max mem: 19788 +Test: [19200/21770] eta: 0:02:05 time: 0.0482 data: 0.0016 max mem: 19788 +Test: [19300/21770] eta: 0:02:00 time: 0.0553 data: 0.0016 max mem: 19788 +Test: [19400/21770] eta: 0:01:55 time: 0.0545 data: 0.0020 max mem: 19788 +Test: [19500/21770] eta: 0:01:50 time: 0.0563 data: 0.0016 max mem: 19788 +Test: [19600/21770] eta: 0:01:45 time: 0.0452 data: 0.0015 max mem: 19788 +Test: [19700/21770] eta: 0:01:41 time: 0.0542 data: 0.0020 max mem: 19788 +Test: [19800/21770] eta: 0:01:36 time: 0.0443 data: 0.0014 max mem: 19788 +Test: [19900/21770] eta: 0:01:31 time: 0.0456 data: 0.0017 max mem: 19788 +Test: [20000/21770] eta: 0:01:26 time: 0.0457 data: 0.0015 max mem: 19788 +Test: [20100/21770] eta: 0:01:21 time: 0.0565 data: 0.0015 max mem: 19788 +Test: [20200/21770] eta: 0:01:16 time: 0.0537 data: 0.0019 max mem: 19788 +Test: [20300/21770] eta: 0:01:11 time: 0.0498 data: 0.0019 max mem: 19788 +Test: [20400/21770] eta: 0:01:06 time: 0.0503 data: 0.0016 max mem: 19788 +Test: [20500/21770] eta: 0:01:02 time: 0.0453 data: 0.0016 max mem: 19788 +Test: [20600/21770] eta: 0:00:57 time: 0.0545 data: 0.0015 max mem: 19788 +Test: [20700/21770] eta: 0:00:52 time: 0.0487 data: 0.0016 max mem: 19788 +Test: [20800/21770] eta: 0:00:47 time: 0.0443 data: 0.0015 max mem: 19788 +Test: [20900/21770] eta: 0:00:42 time: 0.0456 data: 0.0014 max mem: 19788 +Test: [21000/21770] eta: 0:00:37 time: 0.0451 data: 0.0014 max mem: 19788 +Test: [21100/21770] eta: 0:00:32 time: 0.0458 data: 0.0016 max mem: 19788 +Test: [21200/21770] eta: 0:00:27 time: 0.0533 data: 0.0018 max mem: 19788 +Test: [21300/21770] eta: 0:00:22 time: 0.0459 data: 0.0017 max mem: 19788 +Test: [21400/21770] eta: 0:00:18 time: 0.0457 data: 0.0017 max mem: 19788 +Test: [21500/21770] eta: 0:00:13 time: 0.0533 data: 0.0019 max mem: 19788 +Test: [21600/21770] eta: 0:00:08 time: 0.0547 data: 0.0020 max mem: 19788 +Test: [21700/21770] eta: 0:00:03 time: 0.0435 data: 0.0016 max mem: 19788 +Test: Total time: 0:17:43 +Final results: +Mean IoU is 63.35 + + precision@0.5 = 70.38 + precision@0.6 = 64.93 + precision@0.7 = 57.71 + precision@0.8 = 46.75 + precision@0.9 = 23.50 + overall IoU = 64.16 + mean IoU = 63.35 + +Mean accuracy for one-to-zero sample is 84.14 + +Average object IoU 0.633511576679407 +Overall IoU 64.15800476074219 +Better epoch: 15 + +Epoch: [16] [ 0/2138] eta: 7:06:56 lr: 3.157173960358131e-05 loss: 0.0408 (0.0408) time: 11.9816 data: 1.5863 max mem: 19788 +Epoch: [16] [ 10/2138] eta: 2:17:14 lr: 3.1566201835354476e-05 loss: 0.0272 (0.0316) time: 3.8695 data: 0.1463 max mem: 19788 +Epoch: [16] [ 20/2138] eta: 2:02:40 lr: 3.1560663959179984e-05 loss: 0.0272 (0.0295) time: 3.0500 data: 0.0022 max mem: 19788 +Epoch: [16] [ 30/2138] eta: 1:58:14 lr: 3.15551259750347e-05 loss: 0.0322 (0.0312) time: 3.0882 data: 0.0023 max mem: 19788 +Epoch: [16] [ 40/2138] eta: 1:54:50 lr: 3.1549587882895466e-05 loss: 0.0333 (0.0315) time: 3.0841 data: 0.0024 max mem: 19788 +Epoch: [16] [ 50/2138] eta: 1:52:38 lr: 3.1544049682739105e-05 loss: 0.0281 (0.0313) time: 3.0373 data: 0.0025 max mem: 19788 +Epoch: [16] [ 60/2138] eta: 1:51:01 lr: 3.153851137454242e-05 loss: 0.0322 (0.0316) time: 3.0447 data: 0.0026 max mem: 19788 +Epoch: [16] [ 70/2138] eta: 1:50:12 lr: 3.153297295828224e-05 loss: 0.0321 (0.0316) time: 3.0983 data: 0.0027 max mem: 19788 +Epoch: [16] [ 80/2138] eta: 1:51:24 lr: 3.152743443393538e-05 loss: 0.0318 (0.0318) time: 3.3764 data: 0.0026 max mem: 19788 +Epoch: [16] [ 90/2138] eta: 1:50:06 lr: 3.1521895801478614e-05 loss: 0.0278 (0.0321) time: 3.3266 data: 0.0026 max mem: 19788 +Epoch: [16] [ 100/2138] eta: 1:49:19 lr: 3.151635706088872e-05 loss: 0.0310 (0.0326) time: 3.1003 data: 0.0028 max mem: 19788 +Epoch: [16] [ 110/2138] eta: 1:48:17 lr: 3.151081821214247e-05 loss: 0.0352 (0.0330) time: 3.1022 data: 0.0028 max mem: 19788 +Epoch: [16] [ 120/2138] eta: 1:47:41 lr: 3.150527925521665e-05 loss: 0.0321 (0.0327) time: 3.1176 data: 0.0027 max mem: 19788 +Epoch: [16] [ 130/2138] eta: 1:47:38 lr: 3.1499740190088005e-05 loss: 0.0284 (0.0328) time: 3.2870 data: 0.0028 max mem: 19788 +Epoch: [16] [ 140/2138] eta: 1:47:34 lr: 3.149420101673327e-05 loss: 0.0311 (0.0326) time: 3.4031 data: 0.0031 max mem: 19788 +Epoch: [16] [ 150/2138] eta: 1:47:01 lr: 3.148866173512917e-05 loss: 0.0311 (0.0325) time: 3.3194 data: 0.0030 max mem: 19788 +Epoch: [16] [ 160/2138] eta: 1:46:41 lr: 3.148312234525246e-05 loss: 0.0303 (0.0329) time: 3.2758 data: 0.0026 max mem: 19788 +Epoch: [16] [ 170/2138] eta: 1:46:09 lr: 3.147758284707984e-05 loss: 0.0328 (0.0330) time: 3.2845 data: 0.0025 max mem: 19788 +Epoch: [16] [ 180/2138] eta: 1:45:52 lr: 3.147204324058801e-05 loss: 0.0307 (0.0328) time: 3.3106 data: 0.0027 max mem: 19788 +Epoch: [16] [ 190/2138] eta: 1:46:10 lr: 3.146650352575368e-05 loss: 0.0293 (0.0326) time: 3.5608 data: 0.0025 max mem: 19788 +Epoch: [16] [ 200/2138] eta: 1:45:45 lr: 3.146096370255352e-05 loss: 0.0273 (0.0324) time: 3.5449 data: 0.0025 max mem: 19788 +Epoch: [16] [ 210/2138] eta: 1:45:03 lr: 3.145542377096424e-05 loss: 0.0273 (0.0325) time: 3.2576 data: 0.0028 max mem: 19788 +Epoch: [16] [ 220/2138] eta: 1:44:25 lr: 3.144988373096246e-05 loss: 0.0266 (0.0323) time: 3.1888 data: 0.0028 max mem: 19788 +Epoch: [16] [ 230/2138] eta: 1:44:08 lr: 3.144434358252488e-05 loss: 0.0277 (0.0325) time: 3.3376 data: 0.0028 max mem: 19788 +Epoch: [16] [ 240/2138] eta: 1:43:50 lr: 3.143880332562813e-05 loss: 0.0308 (0.0324) time: 3.4600 data: 0.0026 max mem: 19788 +Epoch: [16] [ 250/2138] eta: 1:43:05 lr: 3.1433262960248854e-05 loss: 0.0306 (0.0323) time: 3.2872 data: 0.0024 max mem: 19788 +Epoch: [16] [ 260/2138] eta: 1:42:37 lr: 3.142772248636367e-05 loss: 0.0278 (0.0324) time: 3.2341 data: 0.0024 max mem: 19788 +Epoch: [16] [ 270/2138] eta: 1:41:49 lr: 3.1422181903949225e-05 loss: 0.0292 (0.0323) time: 3.2043 data: 0.0023 max mem: 19788 +Epoch: [16] [ 280/2138] eta: 1:41:07 lr: 3.1416641212982103e-05 loss: 0.0274 (0.0323) time: 3.0904 data: 0.0025 max mem: 19788 +Epoch: [16] [ 290/2138] eta: 1:40:21 lr: 3.141110041343891e-05 loss: 0.0313 (0.0324) time: 3.0913 data: 0.0027 max mem: 19788 +Epoch: [16] [ 300/2138] eta: 1:39:36 lr: 3.140555950529624e-05 loss: 0.0355 (0.0325) time: 3.0591 data: 0.0029 max mem: 19788 +Epoch: [16] [ 310/2138] eta: 1:38:57 lr: 3.140001848853068e-05 loss: 0.0324 (0.0324) time: 3.0986 data: 0.0031 max mem: 19788 +Epoch: [16] [ 320/2138] eta: 1:38:13 lr: 3.13944773631188e-05 loss: 0.0268 (0.0322) time: 3.0942 data: 0.0031 max mem: 19788 +Epoch: [16] [ 330/2138] eta: 1:37:38 lr: 3.138893612903715e-05 loss: 0.0269 (0.0322) time: 3.1211 data: 0.0030 max mem: 19788 +Epoch: [16] [ 340/2138] eta: 1:36:57 lr: 3.1383394786262296e-05 loss: 0.0291 (0.0321) time: 3.1280 data: 0.0029 max mem: 19788 +Epoch: [16] [ 350/2138] eta: 1:36:28 lr: 3.137785333477077e-05 loss: 0.0269 (0.0320) time: 3.1817 data: 0.0029 max mem: 19788 +Epoch: [16] [ 360/2138] eta: 1:35:46 lr: 3.1372311774539125e-05 loss: 0.0309 (0.0324) time: 3.1749 data: 0.0031 max mem: 19788 +Epoch: [16] [ 370/2138] eta: 1:35:07 lr: 3.136677010554387e-05 loss: 0.0369 (0.0325) time: 3.0673 data: 0.0030 max mem: 19788 +Epoch: [16] [ 380/2138] eta: 1:34:33 lr: 3.1361228327761503e-05 loss: 0.0328 (0.0325) time: 3.1419 data: 0.0026 max mem: 19788 +Epoch: [16] [ 390/2138] eta: 1:34:04 lr: 3.1355686441168556e-05 loss: 0.0277 (0.0323) time: 3.2446 data: 0.0027 max mem: 19788 +Epoch: [16] [ 400/2138] eta: 1:33:26 lr: 3.135014444574151e-05 loss: 0.0331 (0.0325) time: 3.1950 data: 0.0025 max mem: 19788 +Epoch: [16] [ 410/2138] eta: 1:33:08 lr: 3.1344602341456854e-05 loss: 0.0332 (0.0325) time: 3.3421 data: 0.0024 max mem: 19788 +Epoch: [16] [ 420/2138] eta: 1:32:34 lr: 3.133906012829106e-05 loss: 0.0266 (0.0325) time: 3.3831 data: 0.0027 max mem: 19788 +Epoch: [16] [ 430/2138] eta: 1:32:05 lr: 3.133351780622059e-05 loss: 0.0282 (0.0325) time: 3.2492 data: 0.0030 max mem: 19788 +Epoch: [16] [ 440/2138] eta: 1:31:36 lr: 3.1327975375221915e-05 loss: 0.0282 (0.0326) time: 3.3240 data: 0.0032 max mem: 19788 +Epoch: [16] [ 450/2138] eta: 1:31:06 lr: 3.132243283527146e-05 loss: 0.0304 (0.0326) time: 3.3064 data: 0.0031 max mem: 19788 +Epoch: [16] [ 460/2138] eta: 1:30:37 lr: 3.131689018634567e-05 loss: 0.0314 (0.0327) time: 3.3058 data: 0.0028 max mem: 19788 +Epoch: [16] [ 470/2138] eta: 1:30:05 lr: 3.131134742842097e-05 loss: 0.0322 (0.0327) time: 3.2991 data: 0.0028 max mem: 19788 +Epoch: [16] [ 480/2138] eta: 1:29:35 lr: 3.130580456147379e-05 loss: 0.0333 (0.0328) time: 3.2922 data: 0.0031 max mem: 19788 +Epoch: [16] [ 490/2138] eta: 1:29:11 lr: 3.130026158548052e-05 loss: 0.0359 (0.0328) time: 3.4059 data: 0.0029 max mem: 19788 +Epoch: [16] [ 500/2138] eta: 1:28:40 lr: 3.129471850041756e-05 loss: 0.0278 (0.0328) time: 3.3934 data: 0.0030 max mem: 19788 +Epoch: [16] [ 510/2138] eta: 1:28:07 lr: 3.1289175306261306e-05 loss: 0.0262 (0.0327) time: 3.2537 data: 0.0030 max mem: 19788 +Epoch: [16] [ 520/2138] eta: 1:27:34 lr: 3.128363200298813e-05 loss: 0.0265 (0.0329) time: 3.2239 data: 0.0026 max mem: 19788 +Epoch: [16] [ 530/2138] eta: 1:27:06 lr: 3.127808859057439e-05 loss: 0.0272 (0.0328) time: 3.3089 data: 0.0024 max mem: 19788 +Epoch: [16] [ 540/2138] eta: 1:26:33 lr: 3.127254506899646e-05 loss: 0.0272 (0.0327) time: 3.3093 data: 0.0025 max mem: 19788 +Epoch: [16] [ 550/2138] eta: 1:25:54 lr: 3.126700143823069e-05 loss: 0.0295 (0.0327) time: 3.1414 data: 0.0026 max mem: 19788 +Epoch: [16] [ 560/2138] eta: 1:25:24 lr: 3.12614576982534e-05 loss: 0.0296 (0.0328) time: 3.1908 data: 0.0026 max mem: 19788 +Epoch: [16] [ 570/2138] eta: 1:24:46 lr: 3.125591384904093e-05 loss: 0.0305 (0.0327) time: 3.1775 data: 0.0027 max mem: 19788 +Epoch: [16] [ 580/2138] eta: 1:24:10 lr: 3.125036989056961e-05 loss: 0.0305 (0.0327) time: 3.0758 data: 0.0026 max mem: 19788 +Epoch: [16] [ 590/2138] eta: 1:23:38 lr: 3.124482582281573e-05 loss: 0.0305 (0.0327) time: 3.1818 data: 0.0026 max mem: 19788 +Epoch: [16] [ 600/2138] eta: 1:23:01 lr: 3.12392816457556e-05 loss: 0.0318 (0.0328) time: 3.1587 data: 0.0026 max mem: 19788 +Epoch: [16] [ 610/2138] eta: 1:22:34 lr: 3.123373735936549e-05 loss: 0.0337 (0.0327) time: 3.2609 data: 0.0025 max mem: 19788 +Epoch: [16] [ 620/2138] eta: 1:21:57 lr: 3.1228192963621725e-05 loss: 0.0341 (0.0328) time: 3.2486 data: 0.0023 max mem: 19788 +Epoch: [16] [ 630/2138] eta: 1:21:20 lr: 3.122264845850053e-05 loss: 0.0320 (0.0328) time: 3.0522 data: 0.0026 max mem: 19788 +Epoch: [16] [ 640/2138] eta: 1:20:45 lr: 3.1217103843978185e-05 loss: 0.0321 (0.0329) time: 3.1025 data: 0.0028 max mem: 19788 +Epoch: [16] [ 650/2138] eta: 1:20:20 lr: 3.121155912003093e-05 loss: 0.0323 (0.0329) time: 3.3432 data: 0.0026 max mem: 19788 +Epoch: [16] [ 660/2138] eta: 1:19:50 lr: 3.120601428663502e-05 loss: 0.0305 (0.0330) time: 3.4496 data: 0.0024 max mem: 19788 +Epoch: [16] [ 670/2138] eta: 1:19:16 lr: 3.120046934376668e-05 loss: 0.0305 (0.0330) time: 3.2512 data: 0.0024 max mem: 19788 +Epoch: [16] [ 680/2138] eta: 1:18:42 lr: 3.119492429140212e-05 loss: 0.0282 (0.0329) time: 3.1667 data: 0.0026 max mem: 19788 +Epoch: [16] [ 690/2138] eta: 1:18:13 lr: 3.118937912951756e-05 loss: 0.0278 (0.0329) time: 3.2971 data: 0.0025 max mem: 19788 +Epoch: [16] [ 700/2138] eta: 1:17:47 lr: 3.118383385808921e-05 loss: 0.0285 (0.0329) time: 3.4662 data: 0.0024 max mem: 19788 +Epoch: [16] [ 710/2138] eta: 1:17:14 lr: 3.1178288477093245e-05 loss: 0.0297 (0.0329) time: 3.3902 data: 0.0026 max mem: 19788 +Epoch: [16] [ 720/2138] eta: 1:16:42 lr: 3.117274298650585e-05 loss: 0.0290 (0.0328) time: 3.2449 data: 0.0026 max mem: 19788 +Epoch: [16] [ 730/2138] eta: 1:16:10 lr: 3.11671973863032e-05 loss: 0.0290 (0.0328) time: 3.2693 data: 0.0027 max mem: 19788 +Epoch: [16] [ 740/2138] eta: 1:15:37 lr: 3.116165167646145e-05 loss: 0.0324 (0.0329) time: 3.2395 data: 0.0026 max mem: 19788 +Epoch: [16] [ 750/2138] eta: 1:15:06 lr: 3.115610585695677e-05 loss: 0.0316 (0.0329) time: 3.2725 data: 0.0025 max mem: 19788 +Epoch: [16] [ 760/2138] eta: 1:14:33 lr: 3.115055992776528e-05 loss: 0.0344 (0.0329) time: 3.2725 data: 0.0027 max mem: 19788 +Epoch: [16] [ 770/2138] eta: 1:14:00 lr: 3.114501388886312e-05 loss: 0.0305 (0.0329) time: 3.2089 data: 0.0030 max mem: 19788 +Epoch: [16] [ 780/2138] eta: 1:13:26 lr: 3.1139467740226414e-05 loss: 0.0293 (0.0329) time: 3.1823 data: 0.0030 max mem: 19788 +Epoch: [16] [ 790/2138] eta: 1:12:55 lr: 3.113392148183127e-05 loss: 0.0293 (0.0328) time: 3.2532 data: 0.0028 max mem: 19788 +Epoch: [16] [ 800/2138] eta: 1:12:20 lr: 3.112837511365379e-05 loss: 0.0300 (0.0328) time: 3.2221 data: 0.0023 max mem: 19788 +Epoch: [16] [ 810/2138] eta: 1:11:46 lr: 3.112282863567007e-05 loss: 0.0325 (0.0328) time: 3.1178 data: 0.0023 max mem: 19788 +Epoch: [16] [ 820/2138] eta: 1:11:15 lr: 3.111728204785618e-05 loss: 0.0279 (0.0328) time: 3.2361 data: 0.0022 max mem: 19788 +Epoch: [16] [ 830/2138] eta: 1:10:43 lr: 3.111173535018821e-05 loss: 0.0265 (0.0328) time: 3.2865 data: 0.0023 max mem: 19788 +Epoch: [16] [ 840/2138] eta: 1:10:09 lr: 3.1106188542642216e-05 loss: 0.0265 (0.0327) time: 3.2119 data: 0.0028 max mem: 19788 +Epoch: [16] [ 850/2138] eta: 1:09:36 lr: 3.110064162519424e-05 loss: 0.0303 (0.0327) time: 3.1708 data: 0.0028 max mem: 19788 +Epoch: [16] [ 860/2138] eta: 1:09:02 lr: 3.1095094597820354e-05 loss: 0.0303 (0.0327) time: 3.1720 data: 0.0024 max mem: 19788 +Epoch: [16] [ 870/2138] eta: 1:08:29 lr: 3.1089547460496546e-05 loss: 0.0283 (0.0328) time: 3.1865 data: 0.0024 max mem: 19788 +Epoch: [16] [ 880/2138] eta: 1:07:56 lr: 3.108400021319886e-05 loss: 0.0321 (0.0328) time: 3.1972 data: 0.0025 max mem: 19788 +Epoch: [16] [ 890/2138] eta: 1:07:23 lr: 3.107845285590332e-05 loss: 0.0293 (0.0327) time: 3.1843 data: 0.0027 max mem: 19788 +Epoch: [16] [ 900/2138] eta: 1:06:50 lr: 3.107290538858592e-05 loss: 0.0293 (0.0327) time: 3.2065 data: 0.0029 max mem: 19788 +Epoch: [16] [ 910/2138] eta: 1:06:20 lr: 3.106735781122263e-05 loss: 0.0289 (0.0327) time: 3.2981 data: 0.0029 max mem: 19788 +Epoch: [16] [ 920/2138] eta: 1:05:46 lr: 3.106181012378946e-05 loss: 0.0274 (0.0327) time: 3.2740 data: 0.0030 max mem: 19788 +Epoch: [16] [ 930/2138] eta: 1:05:14 lr: 3.1056262326262386e-05 loss: 0.0296 (0.0327) time: 3.2106 data: 0.0029 max mem: 19788 +Epoch: [16] [ 940/2138] eta: 1:04:41 lr: 3.105071441861735e-05 loss: 0.0345 (0.0327) time: 3.2139 data: 0.0030 max mem: 19788 +Epoch: [16] [ 950/2138] eta: 1:04:08 lr: 3.104516640083031e-05 loss: 0.0299 (0.0327) time: 3.1873 data: 0.0031 max mem: 19788 +Epoch: [16] [ 960/2138] eta: 1:03:36 lr: 3.1039618272877216e-05 loss: 0.0333 (0.0328) time: 3.2507 data: 0.0030 max mem: 19788 +Epoch: [16] [ 970/2138] eta: 1:03:05 lr: 3.1034070034733995e-05 loss: 0.0333 (0.0328) time: 3.3238 data: 0.0028 max mem: 19788 +Epoch: [16] [ 980/2138] eta: 1:02:34 lr: 3.102852168637657e-05 loss: 0.0258 (0.0327) time: 3.3314 data: 0.0025 max mem: 19788 +Epoch: [16] [ 990/2138] eta: 1:02:02 lr: 3.102297322778084e-05 loss: 0.0271 (0.0327) time: 3.3140 data: 0.0028 max mem: 19788 +Epoch: [16] [1000/2138] eta: 1:01:31 lr: 3.101742465892273e-05 loss: 0.0287 (0.0326) time: 3.3273 data: 0.0033 max mem: 19788 +Epoch: [16] [1010/2138] eta: 1:01:01 lr: 3.101187597977811e-05 loss: 0.0287 (0.0326) time: 3.4026 data: 0.0033 max mem: 19788 +Epoch: [16] [1020/2138] eta: 1:00:30 lr: 3.100632719032289e-05 loss: 0.0308 (0.0326) time: 3.4216 data: 0.0030 max mem: 19788 +Epoch: [16] [1030/2138] eta: 1:00:04 lr: 3.1000778290532914e-05 loss: 0.0276 (0.0326) time: 3.6136 data: 0.0025 max mem: 19788 +Epoch: [16] [1040/2138] eta: 0:59:37 lr: 3.099522928038406e-05 loss: 0.0292 (0.0326) time: 3.8032 data: 0.0025 max mem: 19788 +Epoch: [16] [1050/2138] eta: 0:59:07 lr: 3.098968015985218e-05 loss: 0.0285 (0.0326) time: 3.6510 data: 0.0028 max mem: 19788 +Epoch: [16] [1060/2138] eta: 0:58:34 lr: 3.09841309289131e-05 loss: 0.0316 (0.0326) time: 3.3893 data: 0.0029 max mem: 19788 +Epoch: [16] [1070/2138] eta: 0:58:01 lr: 3.097858158754266e-05 loss: 0.0324 (0.0326) time: 3.2090 data: 0.0028 max mem: 19788 +Epoch: [16] [1080/2138] eta: 0:57:27 lr: 3.0973032135716685e-05 loss: 0.0301 (0.0325) time: 3.1552 data: 0.0026 max mem: 19788 +Epoch: [16] [1090/2138] eta: 0:56:54 lr: 3.096748257341099e-05 loss: 0.0308 (0.0326) time: 3.1888 data: 0.0024 max mem: 19788 +Epoch: [16] [1100/2138] eta: 0:56:21 lr: 3.0961932900601364e-05 loss: 0.0325 (0.0326) time: 3.2073 data: 0.0026 max mem: 19788 +Epoch: [16] [1110/2138] eta: 0:55:50 lr: 3.095638311726361e-05 loss: 0.0330 (0.0326) time: 3.3062 data: 0.0027 max mem: 19788 +Epoch: [16] [1120/2138] eta: 0:55:18 lr: 3.095083322337349e-05 loss: 0.0332 (0.0326) time: 3.4157 data: 0.0027 max mem: 19788 +Epoch: [16] [1130/2138] eta: 0:54:47 lr: 3.0945283218906805e-05 loss: 0.0302 (0.0326) time: 3.4215 data: 0.0025 max mem: 19788 +Epoch: [16] [1140/2138] eta: 0:54:15 lr: 3.0939733103839295e-05 loss: 0.0298 (0.0326) time: 3.3869 data: 0.0026 max mem: 19788 +Epoch: [16] [1150/2138] eta: 0:53:47 lr: 3.0934182878146714e-05 loss: 0.0291 (0.0325) time: 3.5227 data: 0.0027 max mem: 19788 +Epoch: [16] [1160/2138] eta: 0:53:14 lr: 3.09286325418048e-05 loss: 0.0274 (0.0325) time: 3.4958 data: 0.0026 max mem: 19788 +Epoch: [16] [1170/2138] eta: 0:52:41 lr: 3.092308209478929e-05 loss: 0.0291 (0.0325) time: 3.2232 data: 0.0026 max mem: 19788 +Epoch: [16] [1180/2138] eta: 0:52:08 lr: 3.091753153707589e-05 loss: 0.0296 (0.0325) time: 3.2288 data: 0.0024 max mem: 19788 +Epoch: [16] [1190/2138] eta: 0:51:35 lr: 3.091198086864033e-05 loss: 0.0297 (0.0325) time: 3.2211 data: 0.0025 max mem: 19788 +Epoch: [16] [1200/2138] eta: 0:51:01 lr: 3.09064300894583e-05 loss: 0.0283 (0.0325) time: 3.1676 data: 0.0025 max mem: 19788 +Epoch: [16] [1210/2138] eta: 0:50:29 lr: 3.090087919950548e-05 loss: 0.0357 (0.0326) time: 3.2187 data: 0.0025 max mem: 19788 +Epoch: [16] [1220/2138] eta: 0:49:56 lr: 3.089532819875757e-05 loss: 0.0298 (0.0325) time: 3.2833 data: 0.0024 max mem: 19788 +Epoch: [16] [1230/2138] eta: 0:49:23 lr: 3.088977708719021e-05 loss: 0.0278 (0.0325) time: 3.2374 data: 0.0026 max mem: 19788 +Epoch: [16] [1240/2138] eta: 0:48:53 lr: 3.0884225864779094e-05 loss: 0.0277 (0.0325) time: 3.4026 data: 0.0026 max mem: 19788 +Epoch: [16] [1250/2138] eta: 0:48:22 lr: 3.087867453149985e-05 loss: 0.0263 (0.0325) time: 3.6012 data: 0.0027 max mem: 19788 +Epoch: [16] [1260/2138] eta: 0:47:53 lr: 3.087312308732811e-05 loss: 0.0283 (0.0325) time: 3.6540 data: 0.0028 max mem: 19788 +Epoch: [16] [1270/2138] eta: 0:47:22 lr: 3.086757153223951e-05 loss: 0.0285 (0.0325) time: 3.6510 data: 0.0028 max mem: 19788 +Epoch: [16] [1280/2138] eta: 0:46:50 lr: 3.086201986620969e-05 loss: 0.0312 (0.0325) time: 3.4568 data: 0.0029 max mem: 19788 +Epoch: [16] [1290/2138] eta: 0:46:19 lr: 3.0856468089214224e-05 loss: 0.0327 (0.0325) time: 3.4060 data: 0.0028 max mem: 19788 +Epoch: [16] [1300/2138] eta: 0:45:47 lr: 3.0850916201228726e-05 loss: 0.0327 (0.0325) time: 3.4653 data: 0.0026 max mem: 19788 +Epoch: [16] [1310/2138] eta: 0:45:15 lr: 3.084536420222877e-05 loss: 0.0270 (0.0325) time: 3.4139 data: 0.0029 max mem: 19788 +Epoch: [16] [1320/2138] eta: 0:44:44 lr: 3.0839812092189957e-05 loss: 0.0312 (0.0325) time: 3.4524 data: 0.0032 max mem: 19788 +Epoch: [16] [1330/2138] eta: 0:44:11 lr: 3.083425987108784e-05 loss: 0.0313 (0.0326) time: 3.4096 data: 0.0028 max mem: 19788 +Epoch: [16] [1340/2138] eta: 0:43:37 lr: 3.0828707538897964e-05 loss: 0.0324 (0.0326) time: 3.2139 data: 0.0028 max mem: 19788 +Epoch: [16] [1350/2138] eta: 0:43:04 lr: 3.08231550955959e-05 loss: 0.0359 (0.0326) time: 3.2049 data: 0.0031 max mem: 19788 +Epoch: [16] [1360/2138] eta: 0:42:31 lr: 3.0817602541157166e-05 loss: 0.0346 (0.0326) time: 3.2162 data: 0.0026 max mem: 19788 +Epoch: [16] [1370/2138] eta: 0:41:58 lr: 3.08120498755573e-05 loss: 0.0351 (0.0327) time: 3.2094 data: 0.0023 max mem: 19788 +Epoch: [16] [1380/2138] eta: 0:41:25 lr: 3.0806497098771796e-05 loss: 0.0351 (0.0327) time: 3.2702 data: 0.0025 max mem: 19788 +Epoch: [16] [1390/2138] eta: 0:40:52 lr: 3.080094421077618e-05 loss: 0.0321 (0.0327) time: 3.2447 data: 0.0027 max mem: 19788 +Epoch: [16] [1400/2138] eta: 0:40:18 lr: 3.0795391211545945e-05 loss: 0.0298 (0.0327) time: 3.1729 data: 0.0030 max mem: 19788 +Epoch: [16] [1410/2138] eta: 0:39:46 lr: 3.0789838101056565e-05 loss: 0.0298 (0.0326) time: 3.2658 data: 0.0028 max mem: 19788 +Epoch: [16] [1420/2138] eta: 0:39:15 lr: 3.078428487928352e-05 loss: 0.0307 (0.0326) time: 3.4776 data: 0.0029 max mem: 19788 +Epoch: [16] [1430/2138] eta: 0:38:42 lr: 3.077873154620228e-05 loss: 0.0290 (0.0327) time: 3.4645 data: 0.0034 max mem: 19788 +Epoch: [16] [1440/2138] eta: 0:38:09 lr: 3.0773178101788287e-05 loss: 0.0316 (0.0327) time: 3.2849 data: 0.0030 max mem: 19788 +Epoch: [16] [1450/2138] eta: 0:37:38 lr: 3.076762454601699e-05 loss: 0.0304 (0.0327) time: 3.4333 data: 0.0026 max mem: 19788 +Epoch: [16] [1460/2138] eta: 0:37:06 lr: 3.076207087886382e-05 loss: 0.0275 (0.0326) time: 3.5137 data: 0.0029 max mem: 19788 +Epoch: [16] [1470/2138] eta: 0:36:33 lr: 3.075651710030421e-05 loss: 0.0280 (0.0326) time: 3.3449 data: 0.0030 max mem: 19788 +Epoch: [16] [1480/2138] eta: 0:36:01 lr: 3.0750963210313554e-05 loss: 0.0332 (0.0326) time: 3.3396 data: 0.0028 max mem: 19788 +Epoch: [16] [1490/2138] eta: 0:35:28 lr: 3.074540920886726e-05 loss: 0.0305 (0.0326) time: 3.3763 data: 0.0029 max mem: 19788 +Epoch: [16] [1500/2138] eta: 0:34:56 lr: 3.073985509594073e-05 loss: 0.0335 (0.0327) time: 3.3539 data: 0.0030 max mem: 19788 +Epoch: [16] [1510/2138] eta: 0:34:24 lr: 3.0734300871509335e-05 loss: 0.0260 (0.0326) time: 3.4510 data: 0.0030 max mem: 19788 +Epoch: [16] [1520/2138] eta: 0:33:53 lr: 3.072874653554845e-05 loss: 0.0265 (0.0326) time: 3.6491 data: 0.0029 max mem: 19788 +Epoch: [16] [1530/2138] eta: 0:33:20 lr: 3.0723192088033424e-05 loss: 0.0288 (0.0326) time: 3.5247 data: 0.0027 max mem: 19788 +Epoch: [16] [1540/2138] eta: 0:32:48 lr: 3.0717637528939624e-05 loss: 0.0343 (0.0326) time: 3.4630 data: 0.0032 max mem: 19788 +Epoch: [16] [1550/2138] eta: 0:32:17 lr: 3.071208285824238e-05 loss: 0.0311 (0.0327) time: 3.6482 data: 0.0034 max mem: 19788 +Epoch: [16] [1560/2138] eta: 0:31:44 lr: 3.070652807591703e-05 loss: 0.0313 (0.0327) time: 3.5543 data: 0.0029 max mem: 19788 +Epoch: [16] [1570/2138] eta: 0:31:13 lr: 3.070097318193887e-05 loss: 0.0308 (0.0327) time: 3.5705 data: 0.0029 max mem: 19788 +Epoch: [16] [1580/2138] eta: 0:30:42 lr: 3.069541817628323e-05 loss: 0.0284 (0.0327) time: 3.7873 data: 0.0030 max mem: 19788 +Epoch: [16] [1590/2138] eta: 0:30:09 lr: 3.06898630589254e-05 loss: 0.0299 (0.0326) time: 3.5854 data: 0.0028 max mem: 19788 +Epoch: [16] [1600/2138] eta: 0:29:37 lr: 3.068430782984068e-05 loss: 0.0317 (0.0327) time: 3.4450 data: 0.0027 max mem: 19788 +Epoch: [16] [1610/2138] eta: 0:29:04 lr: 3.067875248900433e-05 loss: 0.0315 (0.0327) time: 3.5192 data: 0.0030 max mem: 19788 +Epoch: [16] [1620/2138] eta: 0:28:32 lr: 3.0673197036391607e-05 loss: 0.0257 (0.0326) time: 3.5020 data: 0.0028 max mem: 19788 +Epoch: [16] [1630/2138] eta: 0:28:00 lr: 3.06676414719778e-05 loss: 0.0250 (0.0326) time: 3.5398 data: 0.0025 max mem: 19788 +Epoch: [16] [1640/2138] eta: 0:27:27 lr: 3.0662085795738134e-05 loss: 0.0276 (0.0326) time: 3.5311 data: 0.0027 max mem: 19788 +Epoch: [16] [1650/2138] eta: 0:26:54 lr: 3.065653000764784e-05 loss: 0.0298 (0.0326) time: 3.3623 data: 0.0031 max mem: 19788 +Epoch: [16] [1660/2138] eta: 0:26:22 lr: 3.065097410768215e-05 loss: 0.0316 (0.0326) time: 3.4249 data: 0.0032 max mem: 19788 +Epoch: [16] [1670/2138] eta: 0:25:50 lr: 3.0645418095816285e-05 loss: 0.0267 (0.0326) time: 3.6402 data: 0.0028 max mem: 19788 +Epoch: [16] [1680/2138] eta: 0:25:16 lr: 3.063986197202544e-05 loss: 0.0283 (0.0326) time: 3.3954 data: 0.0025 max mem: 19788 +Epoch: [16] [1690/2138] eta: 0:24:43 lr: 3.0634305736284805e-05 loss: 0.0279 (0.0325) time: 3.2960 data: 0.0027 max mem: 19788 +Epoch: [16] [1700/2138] eta: 0:24:10 lr: 3.062874938856957e-05 loss: 0.0263 (0.0325) time: 3.4201 data: 0.0031 max mem: 19788 +Epoch: [16] [1710/2138] eta: 0:23:37 lr: 3.06231929288549e-05 loss: 0.0287 (0.0325) time: 3.2783 data: 0.0033 max mem: 19788 +Epoch: [16] [1720/2138] eta: 0:23:05 lr: 3.061763635711597e-05 loss: 0.0315 (0.0325) time: 3.4932 data: 0.0030 max mem: 19788 +Epoch: [16] [1730/2138] eta: 0:22:33 lr: 3.061207967332791e-05 loss: 0.0317 (0.0325) time: 3.7151 data: 0.0027 max mem: 19788 +Epoch: [16] [1740/2138] eta: 0:22:00 lr: 3.060652287746588e-05 loss: 0.0317 (0.0325) time: 3.5163 data: 0.0025 max mem: 19788 +Epoch: [16] [1750/2138] eta: 0:21:27 lr: 3.0600965969505e-05 loss: 0.0293 (0.0325) time: 3.5349 data: 0.0025 max mem: 19788 +Epoch: [16] [1760/2138] eta: 0:20:54 lr: 3.05954089494204e-05 loss: 0.0289 (0.0326) time: 3.4907 data: 0.0029 max mem: 19788 +Epoch: [16] [1770/2138] eta: 0:20:21 lr: 3.058985181718717e-05 loss: 0.0284 (0.0325) time: 3.2503 data: 0.0031 max mem: 19788 +Epoch: [16] [1780/2138] eta: 0:19:48 lr: 3.058429457278043e-05 loss: 0.0284 (0.0325) time: 3.3095 data: 0.0030 max mem: 19788 +Epoch: [16] [1790/2138] eta: 0:19:15 lr: 3.0578737216175257e-05 loss: 0.0298 (0.0325) time: 3.4259 data: 0.0030 max mem: 19788 +Epoch: [16] [1800/2138] eta: 0:18:41 lr: 3.057317974734673e-05 loss: 0.0299 (0.0325) time: 3.3468 data: 0.0030 max mem: 19788 +Epoch: [16] [1810/2138] eta: 0:18:10 lr: 3.05676221662699e-05 loss: 0.0314 (0.0325) time: 3.6633 data: 0.0031 max mem: 19788 +Epoch: [16] [1820/2138] eta: 0:17:37 lr: 3.056206447291985e-05 loss: 0.0299 (0.0325) time: 3.8296 data: 0.0035 max mem: 19788 +Epoch: [16] [1830/2138] eta: 0:17:04 lr: 3.055650666727162e-05 loss: 0.0299 (0.0325) time: 3.6724 data: 0.0035 max mem: 19788 +Epoch: [16] [1840/2138] eta: 0:16:32 lr: 3.055094874930022e-05 loss: 0.0314 (0.0325) time: 3.9856 data: 0.0030 max mem: 19788 +Epoch: [16] [1850/2138] eta: 0:16:00 lr: 3.05453907189807e-05 loss: 0.0321 (0.0325) time: 3.9257 data: 0.0028 max mem: 19788 +Epoch: [16] [1860/2138] eta: 0:15:26 lr: 3.053983257628808e-05 loss: 0.0321 (0.0325) time: 3.5287 data: 0.0029 max mem: 19788 +Epoch: [16] [1870/2138] eta: 0:14:54 lr: 3.0534274321197345e-05 loss: 0.0327 (0.0325) time: 3.6216 data: 0.0034 max mem: 19788 +Epoch: [16] [1880/2138] eta: 0:14:21 lr: 3.052871595368348e-05 loss: 0.0264 (0.0325) time: 3.6838 data: 0.0033 max mem: 19788 +Epoch: [16] [1890/2138] eta: 0:13:48 lr: 3.0523157473721494e-05 loss: 0.0261 (0.0325) time: 3.7599 data: 0.0028 max mem: 19788 +Epoch: [16] [1900/2138] eta: 0:13:15 lr: 3.051759888128634e-05 loss: 0.0300 (0.0325) time: 3.8018 data: 0.0028 max mem: 19788 +Epoch: [16] [1910/2138] eta: 0:12:41 lr: 3.051204017635298e-05 loss: 0.0302 (0.0324) time: 3.4159 data: 0.0030 max mem: 19788 +Epoch: [16] [1920/2138] eta: 0:12:08 lr: 3.0506481358896365e-05 loss: 0.0313 (0.0324) time: 3.3087 data: 0.0034 max mem: 19788 +Epoch: [16] [1930/2138] eta: 0:11:35 lr: 3.0500922428891438e-05 loss: 0.0324 (0.0324) time: 3.4795 data: 0.0032 max mem: 19788 +Epoch: [16] [1940/2138] eta: 0:11:01 lr: 3.049536338631313e-05 loss: 0.0307 (0.0324) time: 3.3330 data: 0.0027 max mem: 19788 +Epoch: [16] [1950/2138] eta: 0:10:28 lr: 3.0489804231136353e-05 loss: 0.0284 (0.0324) time: 3.3318 data: 0.0028 max mem: 19788 +Epoch: [16] [1960/2138] eta: 0:09:55 lr: 3.0484244963336018e-05 loss: 0.0284 (0.0324) time: 3.5140 data: 0.0033 max mem: 19788 +Epoch: [16] [1970/2138] eta: 0:09:21 lr: 3.0478685582887013e-05 loss: 0.0302 (0.0324) time: 3.4870 data: 0.0030 max mem: 19788 +Epoch: [16] [1980/2138] eta: 0:08:48 lr: 3.0473126089764238e-05 loss: 0.0318 (0.0324) time: 3.6002 data: 0.0027 max mem: 19788 +Epoch: [16] [1990/2138] eta: 0:08:15 lr: 3.046756648394256e-05 loss: 0.0330 (0.0324) time: 3.5040 data: 0.0027 max mem: 19788 +Epoch: [16] [2000/2138] eta: 0:07:41 lr: 3.0462006765396837e-05 loss: 0.0293 (0.0324) time: 3.2502 data: 0.0026 max mem: 19788 +Epoch: [16] [2010/2138] eta: 0:07:08 lr: 3.045644693410194e-05 loss: 0.0282 (0.0324) time: 3.2307 data: 0.0025 max mem: 19788 +Epoch: [16] [2020/2138] eta: 0:06:34 lr: 3.04508869900327e-05 loss: 0.0303 (0.0325) time: 3.2108 data: 0.0024 max mem: 19788 +Epoch: [16] [2030/2138] eta: 0:06:01 lr: 3.044532693316396e-05 loss: 0.0302 (0.0325) time: 3.2077 data: 0.0027 max mem: 19788 +Epoch: [16] [2040/2138] eta: 0:05:27 lr: 3.0439766763470528e-05 loss: 0.0272 (0.0325) time: 3.2320 data: 0.0028 max mem: 19788 +Epoch: [16] [2050/2138] eta: 0:04:54 lr: 3.043420648092722e-05 loss: 0.0283 (0.0325) time: 3.2340 data: 0.0027 max mem: 19788 +Epoch: [16] [2060/2138] eta: 0:04:20 lr: 3.0428646085508838e-05 loss: 0.0320 (0.0325) time: 3.2001 data: 0.0027 max mem: 19788 +Epoch: [16] [2070/2138] eta: 0:03:47 lr: 3.042308557719018e-05 loss: 0.0296 (0.0325) time: 3.2945 data: 0.0027 max mem: 19788 +Epoch: [16] [2080/2138] eta: 0:03:13 lr: 3.041752495594601e-05 loss: 0.0290 (0.0325) time: 3.4333 data: 0.0028 max mem: 19788 +Epoch: [16] [2090/2138] eta: 0:02:40 lr: 3.0411964221751106e-05 loss: 0.0295 (0.0325) time: 3.4363 data: 0.0025 max mem: 19788 +Epoch: [16] [2100/2138] eta: 0:02:07 lr: 3.0406403374580218e-05 loss: 0.0295 (0.0324) time: 3.4425 data: 0.0026 max mem: 19788 +Epoch: [16] [2110/2138] eta: 0:01:33 lr: 3.040084241440809e-05 loss: 0.0304 (0.0324) time: 3.4310 data: 0.0028 max mem: 19788 +Epoch: [16] [2120/2138] eta: 0:01:00 lr: 3.0395281341209474e-05 loss: 0.0337 (0.0325) time: 3.3861 data: 0.0026 max mem: 19788 +Epoch: [16] [2130/2138] eta: 0:00:26 lr: 3.0389720154959083e-05 loss: 0.0344 (0.0325) time: 3.3413 data: 0.0025 max mem: 19788 +Epoch: [16] Total time: 1:59:09 +Test: [ 0/21770] eta: 14:56:47 time: 2.4716 data: 2.1704 max mem: 19788 +Test: [ 100/21770] eta: 0:26:56 time: 0.0451 data: 0.0016 max mem: 19788 +Test: [ 200/21770] eta: 0:21:38 time: 0.0461 data: 0.0017 max mem: 19788 +Test: [ 300/21770] eta: 0:20:21 time: 0.0547 data: 0.0020 max mem: 19788 +Test: [ 400/21770] eta: 0:19:53 time: 0.0556 data: 0.0019 max mem: 19788 +Test: [ 500/21770] eta: 0:19:37 time: 0.0550 data: 0.0020 max mem: 19788 +Test: [ 600/21770] eta: 0:19:00 time: 0.0433 data: 0.0015 max mem: 19788 +Test: [ 700/21770] eta: 0:18:34 time: 0.0476 data: 0.0017 max mem: 19788 +Test: [ 800/21770] eta: 0:18:18 time: 0.0549 data: 0.0019 max mem: 19788 +Test: [ 900/21770] eta: 0:18:16 time: 0.0550 data: 0.0020 max mem: 19788 +Test: [ 1000/21770] eta: 0:18:19 time: 0.0553 data: 0.0018 max mem: 19788 +Test: [ 1100/21770] eta: 0:18:01 time: 0.0456 data: 0.0015 max mem: 19788 +Test: [ 1200/21770] eta: 0:18:01 time: 0.0573 data: 0.0020 max mem: 19788 +Test: [ 1300/21770] eta: 0:17:44 time: 0.0456 data: 0.0015 max mem: 19788 +Test: [ 1400/21770] eta: 0:17:43 time: 0.0568 data: 0.0016 max mem: 19788 +Test: [ 1500/21770] eta: 0:17:35 time: 0.0480 data: 0.0016 max mem: 19788 +Test: [ 1600/21770] eta: 0:17:32 time: 0.0503 data: 0.0017 max mem: 19788 +Test: [ 1700/21770] eta: 0:17:21 time: 0.0448 data: 0.0016 max mem: 19788 +Test: [ 1800/21770] eta: 0:17:12 time: 0.0475 data: 0.0017 max mem: 19788 +Test: [ 1900/21770] eta: 0:17:07 time: 0.0443 data: 0.0016 max mem: 19788 +Test: [ 2000/21770] eta: 0:16:57 time: 0.0454 data: 0.0015 max mem: 19788 +Test: [ 2100/21770] eta: 0:16:46 time: 0.0458 data: 0.0017 max mem: 19788 +Test: [ 2200/21770] eta: 0:16:36 time: 0.0458 data: 0.0014 max mem: 19788 +Test: [ 2300/21770] eta: 0:16:26 time: 0.0455 data: 0.0015 max mem: 19788 +Test: [ 2400/21770] eta: 0:16:18 time: 0.0459 data: 0.0015 max mem: 19788 +Test: [ 2500/21770] eta: 0:16:12 time: 0.0492 data: 0.0017 max mem: 19788 +Test: [ 2600/21770] eta: 0:16:08 time: 0.0458 data: 0.0015 max mem: 19788 +Test: [ 2700/21770] eta: 0:16:03 time: 0.0481 data: 0.0016 max mem: 19788 +Test: [ 2800/21770] eta: 0:16:01 time: 0.0559 data: 0.0019 max mem: 19788 +Test: [ 2900/21770] eta: 0:15:56 time: 0.0454 data: 0.0014 max mem: 19788 +Test: [ 3000/21770] eta: 0:15:52 time: 0.0545 data: 0.0019 max mem: 19788 +Test: [ 3100/21770] eta: 0:15:50 time: 0.0586 data: 0.0018 max mem: 19788 +Test: [ 3200/21770] eta: 0:15:46 time: 0.0538 data: 0.0018 max mem: 19788 +Test: [ 3300/21770] eta: 0:15:39 time: 0.0518 data: 0.0016 max mem: 19788 +Test: [ 3400/21770] eta: 0:15:31 time: 0.0467 data: 0.0017 max mem: 19788 +Test: [ 3500/21770] eta: 0:15:27 time: 0.0559 data: 0.0019 max mem: 19788 +Test: [ 3600/21770] eta: 0:15:22 time: 0.0561 data: 0.0018 max mem: 19788 +Test: [ 3700/21770] eta: 0:15:15 time: 0.0454 data: 0.0017 max mem: 19788 +Test: [ 3800/21770] eta: 0:15:10 time: 0.0491 data: 0.0016 max mem: 19788 +Test: [ 3900/21770] eta: 0:15:05 time: 0.0479 data: 0.0016 max mem: 19788 +Test: [ 4000/21770] eta: 0:14:59 time: 0.0465 data: 0.0017 max mem: 19788 +Test: [ 4100/21770] eta: 0:14:53 time: 0.0463 data: 0.0018 max mem: 19788 +Test: [ 4200/21770] eta: 0:14:50 time: 0.0561 data: 0.0018 max mem: 19788 +Test: [ 4300/21770] eta: 0:14:45 time: 0.0505 data: 0.0017 max mem: 19788 +Test: [ 4400/21770] eta: 0:14:40 time: 0.0533 data: 0.0018 max mem: 19788 +Test: [ 4500/21770] eta: 0:14:36 time: 0.0531 data: 0.0017 max mem: 19788 +Test: [ 4600/21770] eta: 0:14:29 time: 0.0463 data: 0.0015 max mem: 19788 +Test: [ 4700/21770] eta: 0:14:24 time: 0.0521 data: 0.0018 max mem: 19788 +Test: [ 4800/21770] eta: 0:14:18 time: 0.0542 data: 0.0017 max mem: 19788 +Test: [ 4900/21770] eta: 0:14:13 time: 0.0533 data: 0.0020 max mem: 19788 +Test: [ 5000/21770] eta: 0:14:08 time: 0.0457 data: 0.0017 max mem: 19788 +Test: [ 5100/21770] eta: 0:14:03 time: 0.0539 data: 0.0019 max mem: 19788 +Test: [ 5200/21770] eta: 0:13:58 time: 0.0469 data: 0.0017 max mem: 19788 +Test: [ 5300/21770] eta: 0:13:52 time: 0.0461 data: 0.0017 max mem: 19788 +Test: [ 5400/21770] eta: 0:13:46 time: 0.0470 data: 0.0015 max mem: 19788 +Test: [ 5500/21770] eta: 0:13:40 time: 0.0455 data: 0.0016 max mem: 19788 +Test: [ 5600/21770] eta: 0:13:35 time: 0.0481 data: 0.0018 max mem: 19788 +Test: [ 5700/21770] eta: 0:13:29 time: 0.0460 data: 0.0015 max mem: 19788 +Test: [ 5800/21770] eta: 0:13:24 time: 0.0448 data: 0.0017 max mem: 19788 +Test: [ 5900/21770] eta: 0:13:19 time: 0.0458 data: 0.0016 max mem: 19788 +Test: [ 6000/21770] eta: 0:13:14 time: 0.0502 data: 0.0019 max mem: 19788 +Test: [ 6100/21770] eta: 0:13:08 time: 0.0534 data: 0.0018 max mem: 19788 +Test: [ 6200/21770] eta: 0:13:04 time: 0.0533 data: 0.0018 max mem: 19788 +Test: [ 6300/21770] eta: 0:12:59 time: 0.0453 data: 0.0016 max mem: 19788 +Test: [ 6400/21770] eta: 0:12:55 time: 0.0551 data: 0.0018 max mem: 19788 +Test: [ 6500/21770] eta: 0:12:50 time: 0.0557 data: 0.0019 max mem: 19788 +Test: [ 6600/21770] eta: 0:12:46 time: 0.0560 data: 0.0019 max mem: 19788 +Test: [ 6700/21770] eta: 0:12:40 time: 0.0537 data: 0.0016 max mem: 19788 +Test: [ 6800/21770] eta: 0:12:36 time: 0.0531 data: 0.0016 max mem: 19788 +Test: [ 6900/21770] eta: 0:12:31 time: 0.0456 data: 0.0014 max mem: 19788 +Test: [ 7000/21770] eta: 0:12:26 time: 0.0454 data: 0.0015 max mem: 19788 +Test: [ 7100/21770] eta: 0:12:20 time: 0.0456 data: 0.0015 max mem: 19788 +Test: [ 7200/21770] eta: 0:12:14 time: 0.0466 data: 0.0016 max mem: 19788 +Test: [ 7300/21770] eta: 0:12:08 time: 0.0444 data: 0.0014 max mem: 19788 +Test: [ 7400/21770] eta: 0:12:04 time: 0.0591 data: 0.0017 max mem: 19788 +Test: [ 7500/21770] eta: 0:11:58 time: 0.0470 data: 0.0017 max mem: 19788 +Test: [ 7600/21770] eta: 0:11:53 time: 0.0457 data: 0.0016 max mem: 19788 +Test: [ 7700/21770] eta: 0:11:48 time: 0.0489 data: 0.0018 max mem: 19788 +Test: [ 7800/21770] eta: 0:11:43 time: 0.0486 data: 0.0018 max mem: 19788 +Test: [ 7900/21770] eta: 0:11:38 time: 0.0455 data: 0.0018 max mem: 19788 +Test: [ 8000/21770] eta: 0:11:34 time: 0.0570 data: 0.0019 max mem: 19788 +Test: [ 8100/21770] eta: 0:11:29 time: 0.0475 data: 0.0018 max mem: 19788 +Test: [ 8200/21770] eta: 0:11:25 time: 0.0518 data: 0.0020 max mem: 19788 +Test: [ 8300/21770] eta: 0:11:19 time: 0.0461 data: 0.0016 max mem: 19788 +Test: [ 8400/21770] eta: 0:11:14 time: 0.0521 data: 0.0018 max mem: 19788 +Test: [ 8500/21770] eta: 0:11:09 time: 0.0524 data: 0.0017 max mem: 19788 +Test: [ 8600/21770] eta: 0:11:04 time: 0.0599 data: 0.0017 max mem: 19788 +Test: [ 8700/21770] eta: 0:10:59 time: 0.0455 data: 0.0015 max mem: 19788 +Test: [ 8800/21770] eta: 0:10:54 time: 0.0493 data: 0.0016 max mem: 19788 +Test: [ 8900/21770] eta: 0:10:49 time: 0.0573 data: 0.0018 max mem: 19788 +Test: [ 9000/21770] eta: 0:10:44 time: 0.0555 data: 0.0020 max mem: 19788 +Test: [ 9100/21770] eta: 0:10:39 time: 0.0451 data: 0.0016 max mem: 19788 +Test: [ 9200/21770] eta: 0:10:34 time: 0.0463 data: 0.0016 max mem: 19788 +Test: [ 9300/21770] eta: 0:10:29 time: 0.0497 data: 0.0015 max mem: 19788 +Test: [ 9400/21770] eta: 0:10:24 time: 0.0464 data: 0.0017 max mem: 19788 +Test: [ 9500/21770] eta: 0:10:18 time: 0.0560 data: 0.0019 max mem: 19788 +Test: [ 9600/21770] eta: 0:10:13 time: 0.0441 data: 0.0017 max mem: 19788 +Test: [ 9700/21770] eta: 0:10:07 time: 0.0459 data: 0.0016 max mem: 19788 +Test: [ 9800/21770] eta: 0:10:03 time: 0.0569 data: 0.0021 max mem: 19788 +Test: [ 9900/21770] eta: 0:09:59 time: 0.0572 data: 0.0021 max mem: 19788 +Test: [10000/21770] eta: 0:09:54 time: 0.0587 data: 0.0020 max mem: 19788 +Test: [10100/21770] eta: 0:09:50 time: 0.0565 data: 0.0020 max mem: 19788 +Test: [10200/21770] eta: 0:09:46 time: 0.0573 data: 0.0020 max mem: 19788 +Test: [10300/21770] eta: 0:09:41 time: 0.0582 data: 0.0016 max mem: 19788 +Test: [10400/21770] eta: 0:09:36 time: 0.0489 data: 0.0018 max mem: 19788 +Test: [10500/21770] eta: 0:09:31 time: 0.0506 data: 0.0017 max mem: 19788 +Test: [10600/21770] eta: 0:09:26 time: 0.0517 data: 0.0017 max mem: 19788 +Test: [10700/21770] eta: 0:09:21 time: 0.0469 data: 0.0015 max mem: 19788 +Test: [10800/21770] eta: 0:09:16 time: 0.0515 data: 0.0018 max mem: 19788 +Test: [10900/21770] eta: 0:09:10 time: 0.0465 data: 0.0017 max mem: 19788 +Test: [11000/21770] eta: 0:09:05 time: 0.0470 data: 0.0017 max mem: 19788 +Test: [11100/21770] eta: 0:09:00 time: 0.0581 data: 0.0016 max mem: 19788 +Test: [11200/21770] eta: 0:08:55 time: 0.0528 data: 0.0017 max mem: 19788 +Test: [11300/21770] eta: 0:08:51 time: 0.0530 data: 0.0020 max mem: 19788 +Test: [11400/21770] eta: 0:08:46 time: 0.0489 data: 0.0016 max mem: 19788 +Test: [11500/21770] eta: 0:08:41 time: 0.0555 data: 0.0019 max mem: 19788 +Test: [11600/21770] eta: 0:08:36 time: 0.0578 data: 0.0020 max mem: 19788 +Test: [11700/21770] eta: 0:08:31 time: 0.0519 data: 0.0017 max mem: 19788 +Test: [11800/21770] eta: 0:08:26 time: 0.0449 data: 0.0015 max mem: 19788 +Test: [11900/21770] eta: 0:08:21 time: 0.0570 data: 0.0021 max mem: 19788 +Test: [12000/21770] eta: 0:08:16 time: 0.0569 data: 0.0020 max mem: 19788 +Test: [12100/21770] eta: 0:08:11 time: 0.0496 data: 0.0017 max mem: 19788 +Test: [12200/21770] eta: 0:08:07 time: 0.0572 data: 0.0021 max mem: 19788 +Test: [12300/21770] eta: 0:08:02 time: 0.0561 data: 0.0018 max mem: 19788 +Test: [12400/21770] eta: 0:07:56 time: 0.0452 data: 0.0016 max mem: 19788 +Test: [12500/21770] eta: 0:07:51 time: 0.0498 data: 0.0017 max mem: 19788 +Test: [12600/21770] eta: 0:07:46 time: 0.0494 data: 0.0016 max mem: 19788 +Test: [12700/21770] eta: 0:07:41 time: 0.0562 data: 0.0020 max mem: 19788 +Test: [12800/21770] eta: 0:07:36 time: 0.0543 data: 0.0019 max mem: 19788 +Test: [12900/21770] eta: 0:07:31 time: 0.0467 data: 0.0017 max mem: 19788 +Test: [13000/21770] eta: 0:07:25 time: 0.0569 data: 0.0020 max mem: 19788 +Test: [13100/21770] eta: 0:07:20 time: 0.0515 data: 0.0016 max mem: 19788 +Test: [13200/21770] eta: 0:07:15 time: 0.0452 data: 0.0017 max mem: 19788 +Test: [13300/21770] eta: 0:07:10 time: 0.0454 data: 0.0015 max mem: 19788 +Test: [13400/21770] eta: 0:07:05 time: 0.0456 data: 0.0016 max mem: 19788 +Test: [13500/21770] eta: 0:07:00 time: 0.0492 data: 0.0016 max mem: 19788 +Test: [13600/21770] eta: 0:06:54 time: 0.0451 data: 0.0017 max mem: 19788 +Test: [13700/21770] eta: 0:06:49 time: 0.0459 data: 0.0016 max mem: 19788 +Test: [13800/21770] eta: 0:06:44 time: 0.0591 data: 0.0021 max mem: 19788 +Test: [13900/21770] eta: 0:06:39 time: 0.0538 data: 0.0018 max mem: 19788 +Test: [14000/21770] eta: 0:06:34 time: 0.0453 data: 0.0016 max mem: 19788 +Test: [14100/21770] eta: 0:06:29 time: 0.0487 data: 0.0018 max mem: 19788 +Test: [14200/21770] eta: 0:06:24 time: 0.0575 data: 0.0021 max mem: 19788 +Test: [14300/21770] eta: 0:06:19 time: 0.0462 data: 0.0017 max mem: 19788 +Test: [14400/21770] eta: 0:06:13 time: 0.0518 data: 0.0017 max mem: 19788 +Test: [14500/21770] eta: 0:06:08 time: 0.0471 data: 0.0020 max mem: 19788 +Test: [14600/21770] eta: 0:06:03 time: 0.0480 data: 0.0020 max mem: 19788 +Test: [14700/21770] eta: 0:05:58 time: 0.0565 data: 0.0021 max mem: 19788 +Test: [14800/21770] eta: 0:05:53 time: 0.0576 data: 0.0021 max mem: 19788 +Test: [14900/21770] eta: 0:05:48 time: 0.0496 data: 0.0017 max mem: 19788 +Test: [15000/21770] eta: 0:05:43 time: 0.0473 data: 0.0015 max mem: 19788 +Test: [15100/21770] eta: 0:05:38 time: 0.0475 data: 0.0017 max mem: 19788 +Test: [15200/21770] eta: 0:05:33 time: 0.0534 data: 0.0019 max mem: 19788 +Test: [15300/21770] eta: 0:05:28 time: 0.0469 data: 0.0017 max mem: 19788 +Test: [15400/21770] eta: 0:05:23 time: 0.0536 data: 0.0015 max mem: 19788 +Test: [15500/21770] eta: 0:05:18 time: 0.0493 data: 0.0019 max mem: 19788 +Test: [15600/21770] eta: 0:05:13 time: 0.0451 data: 0.0016 max mem: 19788 +Test: [15700/21770] eta: 0:05:08 time: 0.0452 data: 0.0015 max mem: 19788 +Test: [15800/21770] eta: 0:05:03 time: 0.0484 data: 0.0017 max mem: 19788 +Test: [15900/21770] eta: 0:04:58 time: 0.0559 data: 0.0019 max mem: 19788 +Test: [16000/21770] eta: 0:04:53 time: 0.0597 data: 0.0016 max mem: 19788 +Test: [16100/21770] eta: 0:04:48 time: 0.0520 data: 0.0018 max mem: 19788 +Test: [16200/21770] eta: 0:04:43 time: 0.0569 data: 0.0020 max mem: 19788 +Test: [16300/21770] eta: 0:04:38 time: 0.0464 data: 0.0016 max mem: 19788 +Test: [16400/21770] eta: 0:04:33 time: 0.0576 data: 0.0019 max mem: 19788 +Test: [16500/21770] eta: 0:04:28 time: 0.0576 data: 0.0017 max mem: 19788 +Test: [16600/21770] eta: 0:04:23 time: 0.0477 data: 0.0017 max mem: 19788 +Test: [16700/21770] eta: 0:04:18 time: 0.0576 data: 0.0020 max mem: 19788 +Test: [16800/21770] eta: 0:04:13 time: 0.0456 data: 0.0016 max mem: 19788 +Test: [16900/21770] eta: 0:04:08 time: 0.0592 data: 0.0019 max mem: 19788 +Test: [17000/21770] eta: 0:04:03 time: 0.0456 data: 0.0015 max mem: 19788 +Test: [17100/21770] eta: 0:03:57 time: 0.0466 data: 0.0016 max mem: 19788 +Test: [17200/21770] eta: 0:03:52 time: 0.0570 data: 0.0019 max mem: 19788 +Test: [17300/21770] eta: 0:03:47 time: 0.0556 data: 0.0020 max mem: 19788 +Test: [17400/21770] eta: 0:03:42 time: 0.0469 data: 0.0017 max mem: 19788 +Test: [17500/21770] eta: 0:03:37 time: 0.0574 data: 0.0019 max mem: 19788 +Test: [17600/21770] eta: 0:03:32 time: 0.0456 data: 0.0015 max mem: 19788 +Test: [17700/21770] eta: 0:03:27 time: 0.0566 data: 0.0018 max mem: 19788 +Test: [17800/21770] eta: 0:03:22 time: 0.0461 data: 0.0016 max mem: 19788 +Test: [17900/21770] eta: 0:03:17 time: 0.0513 data: 0.0018 max mem: 19788 +Test: [18000/21770] eta: 0:03:12 time: 0.0531 data: 0.0021 max mem: 19788 +Test: [18100/21770] eta: 0:03:06 time: 0.0444 data: 0.0016 max mem: 19788 +Test: [18200/21770] eta: 0:03:01 time: 0.0569 data: 0.0020 max mem: 19788 +Test: [18300/21770] eta: 0:02:56 time: 0.0556 data: 0.0019 max mem: 19788 +Test: [18400/21770] eta: 0:02:51 time: 0.0484 data: 0.0015 max mem: 19788 +Test: [18500/21770] eta: 0:02:46 time: 0.0450 data: 0.0016 max mem: 19788 +Test: [18600/21770] eta: 0:02:41 time: 0.0462 data: 0.0016 max mem: 19788 +Test: [18700/21770] eta: 0:02:36 time: 0.0556 data: 0.0019 max mem: 19788 +Test: [18800/21770] eta: 0:02:31 time: 0.0582 data: 0.0019 max mem: 19788 +Test: [18900/21770] eta: 0:02:26 time: 0.0558 data: 0.0019 max mem: 19788 +Test: [19000/21770] eta: 0:02:21 time: 0.0450 data: 0.0016 max mem: 19788 +Test: [19100/21770] eta: 0:02:15 time: 0.0478 data: 0.0016 max mem: 19788 +Test: [19200/21770] eta: 0:02:10 time: 0.0581 data: 0.0017 max mem: 19788 +Test: [19300/21770] eta: 0:02:05 time: 0.0470 data: 0.0017 max mem: 19788 +Test: [19400/21770] eta: 0:02:00 time: 0.0572 data: 0.0018 max mem: 19788 +Test: [19500/21770] eta: 0:01:55 time: 0.0496 data: 0.0016 max mem: 19788 +Test: [19600/21770] eta: 0:01:50 time: 0.0462 data: 0.0017 max mem: 19788 +Test: [19700/21770] eta: 0:01:45 time: 0.0549 data: 0.0019 max mem: 19788 +Test: [19800/21770] eta: 0:01:40 time: 0.0462 data: 0.0015 max mem: 19788 +Test: [19900/21770] eta: 0:01:35 time: 0.0457 data: 0.0014 max mem: 19788 +Test: [20000/21770] eta: 0:01:30 time: 0.0513 data: 0.0016 max mem: 19788 +Test: [20100/21770] eta: 0:01:24 time: 0.0456 data: 0.0016 max mem: 19788 +Test: [20200/21770] eta: 0:01:19 time: 0.0506 data: 0.0018 max mem: 19788 +Test: [20300/21770] eta: 0:01:14 time: 0.0497 data: 0.0019 max mem: 19788 +Test: [20400/21770] eta: 0:01:09 time: 0.0544 data: 0.0021 max mem: 19788 +Test: [20500/21770] eta: 0:01:04 time: 0.0457 data: 0.0017 max mem: 19788 +Test: [20600/21770] eta: 0:00:59 time: 0.0503 data: 0.0016 max mem: 19788 +Test: [20700/21770] eta: 0:00:54 time: 0.0469 data: 0.0015 max mem: 19788 +Test: [20800/21770] eta: 0:00:49 time: 0.0471 data: 0.0016 max mem: 19788 +Test: [20900/21770] eta: 0:00:44 time: 0.0591 data: 0.0017 max mem: 19788 +Test: [21000/21770] eta: 0:00:39 time: 0.0467 data: 0.0018 max mem: 19788 +Test: [21100/21770] eta: 0:00:34 time: 0.0468 data: 0.0018 max mem: 19788 +Test: [21200/21770] eta: 0:00:28 time: 0.0560 data: 0.0019 max mem: 19788 +Test: [21300/21770] eta: 0:00:23 time: 0.0469 data: 0.0016 max mem: 19788 +Test: [21400/21770] eta: 0:00:18 time: 0.0468 data: 0.0015 max mem: 19788 +Test: [21500/21770] eta: 0:00:13 time: 0.0568 data: 0.0020 max mem: 19788 +Test: [21600/21770] eta: 0:00:08 time: 0.0506 data: 0.0018 max mem: 19788 +Test: [21700/21770] eta: 0:00:03 time: 0.0549 data: 0.0019 max mem: 19788 +Test: Total time: 0:18:28 +Final results: +Mean IoU is 63.69 + + precision@0.5 = 70.68 + precision@0.6 = 65.05 + precision@0.7 = 58.50 + precision@0.8 = 47.59 + precision@0.9 = 23.56 + overall IoU = 63.99 + mean IoU = 63.69 + +Mean accuracy for one-to-zero sample is 84.19 + +Average object IoU 0.6369099176871791 +Overall IoU 63.98610305786133 +Epoch: [17] [ 0/2138] eta: 7:18:06 lr: 3.0385271124544502e-05 loss: 0.0351 (0.0351) time: 12.2947 data: 1.5541 max mem: 19788 +Epoch: [17] [ 10/2138] eta: 2:29:01 lr: 3.037970973473719e-05 loss: 0.0288 (0.0310) time: 4.2019 data: 0.1441 max mem: 19788 +Epoch: [17] [ 20/2138] eta: 2:16:30 lr: 3.0374148231807275e-05 loss: 0.0288 (0.0318) time: 3.4459 data: 0.0023 max mem: 19788 +Epoch: [17] [ 30/2138] eta: 2:13:42 lr: 3.0368586615729457e-05 loss: 0.0322 (0.0325) time: 3.5878 data: 0.0021 max mem: 19788 +Epoch: [17] [ 40/2138] eta: 2:08:54 lr: 3.036302488647838e-05 loss: 0.0319 (0.0332) time: 3.4969 data: 0.0028 max mem: 19788 +Epoch: [17] [ 50/2138] eta: 2:04:59 lr: 3.0357463044028723e-05 loss: 0.0300 (0.0330) time: 3.2603 data: 0.0028 max mem: 19788 +Epoch: [17] [ 60/2138] eta: 2:04:03 lr: 3.0351901088355144e-05 loss: 0.0302 (0.0330) time: 3.3684 data: 0.0029 max mem: 19788 +Epoch: [17] [ 70/2138] eta: 2:02:58 lr: 3.0346339019432275e-05 loss: 0.0295 (0.0334) time: 3.5077 data: 0.0030 max mem: 19788 +Epoch: [17] [ 80/2138] eta: 2:00:54 lr: 3.034077683723474e-05 loss: 0.0280 (0.0338) time: 3.3497 data: 0.0030 max mem: 19788 +Epoch: [17] [ 90/2138] eta: 1:59:07 lr: 3.0335214541737166e-05 loss: 0.0280 (0.0346) time: 3.2135 data: 0.0029 max mem: 19788 +Epoch: [17] [ 100/2138] eta: 1:57:46 lr: 3.0329652132914164e-05 loss: 0.0320 (0.0346) time: 3.2345 data: 0.0027 max mem: 19788 +Epoch: [17] [ 110/2138] eta: 1:58:06 lr: 3.032408961074033e-05 loss: 0.0318 (0.0343) time: 3.5129 data: 0.0029 max mem: 19788 +Epoch: [17] [ 120/2138] eta: 1:57:28 lr: 3.0318526975190237e-05 loss: 0.0288 (0.0336) time: 3.6210 data: 0.0029 max mem: 19788 +Epoch: [17] [ 130/2138] eta: 1:56:10 lr: 3.0312964226238476e-05 loss: 0.0272 (0.0333) time: 3.3440 data: 0.0028 max mem: 19788 +Epoch: [17] [ 140/2138] eta: 1:55:15 lr: 3.030740136385961e-05 loss: 0.0289 (0.0340) time: 3.2709 data: 0.0029 max mem: 19788 +Epoch: [17] [ 150/2138] eta: 1:54:14 lr: 3.030183838802818e-05 loss: 0.0298 (0.0338) time: 3.2957 data: 0.0030 max mem: 19788 +Epoch: [17] [ 160/2138] eta: 1:53:05 lr: 3.029627529871874e-05 loss: 0.0280 (0.0335) time: 3.2149 data: 0.0028 max mem: 19788 +Epoch: [17] [ 170/2138] eta: 1:52:09 lr: 3.0290712095905828e-05 loss: 0.0325 (0.0336) time: 3.2033 data: 0.0026 max mem: 19788 +Epoch: [17] [ 180/2138] eta: 1:51:29 lr: 3.0285148779563948e-05 loss: 0.0316 (0.0336) time: 3.3023 data: 0.0028 max mem: 19788 +Epoch: [17] [ 190/2138] eta: 1:50:48 lr: 3.0279585349667618e-05 loss: 0.0286 (0.0333) time: 3.3590 data: 0.0030 max mem: 19788 +Epoch: [17] [ 200/2138] eta: 1:50:29 lr: 3.0274021806191332e-05 loss: 0.0263 (0.0331) time: 3.4598 data: 0.0029 max mem: 19788 +Epoch: [17] [ 210/2138] eta: 1:50:15 lr: 3.0268458149109598e-05 loss: 0.0306 (0.0332) time: 3.6022 data: 0.0029 max mem: 19788 +Epoch: [17] [ 220/2138] eta: 1:49:31 lr: 3.0262894378396873e-05 loss: 0.0281 (0.0330) time: 3.4794 data: 0.0030 max mem: 19788 +Epoch: [17] [ 230/2138] eta: 1:48:37 lr: 3.025733049402762e-05 loss: 0.0281 (0.0330) time: 3.2549 data: 0.0029 max mem: 19788 +Epoch: [17] [ 240/2138] eta: 1:47:58 lr: 3.0251766495976308e-05 loss: 0.0292 (0.0328) time: 3.2706 data: 0.0027 max mem: 19788 +Epoch: [17] [ 250/2138] eta: 1:47:33 lr: 3.024620238421738e-05 loss: 0.0286 (0.0327) time: 3.4451 data: 0.0027 max mem: 19788 +Epoch: [17] [ 260/2138] eta: 1:47:03 lr: 3.0240638158725264e-05 loss: 0.0274 (0.0327) time: 3.5053 data: 0.0028 max mem: 19788 +Epoch: [17] [ 270/2138] eta: 1:46:36 lr: 3.0235073819474385e-05 loss: 0.0295 (0.0327) time: 3.5024 data: 0.0028 max mem: 19788 +Epoch: [17] [ 280/2138] eta: 1:46:19 lr: 3.0229509366439145e-05 loss: 0.0296 (0.0326) time: 3.6050 data: 0.0029 max mem: 19788 +Epoch: [17] [ 290/2138] eta: 1:45:43 lr: 3.0223944799593967e-05 loss: 0.0285 (0.0325) time: 3.5427 data: 0.0028 max mem: 19788 +Epoch: [17] [ 300/2138] eta: 1:44:53 lr: 3.021838011891322e-05 loss: 0.0294 (0.0326) time: 3.2911 data: 0.0029 max mem: 19788 +Epoch: [17] [ 310/2138] eta: 1:44:11 lr: 3.0212815324371292e-05 loss: 0.0309 (0.0326) time: 3.2371 data: 0.0029 max mem: 19788 +Epoch: [17] [ 320/2138] eta: 1:43:34 lr: 3.020725041594254e-05 loss: 0.0254 (0.0324) time: 3.3333 data: 0.0026 max mem: 19788 +Epoch: [17] [ 330/2138] eta: 1:42:48 lr: 3.020168539360133e-05 loss: 0.0270 (0.0324) time: 3.2811 data: 0.0026 max mem: 19788 +Epoch: [17] [ 340/2138] eta: 1:42:06 lr: 3.0196120257322015e-05 loss: 0.0325 (0.0324) time: 3.2297 data: 0.0026 max mem: 19788 +Epoch: [17] [ 350/2138] eta: 1:41:29 lr: 3.0190555007078907e-05 loss: 0.0285 (0.0322) time: 3.3094 data: 0.0027 max mem: 19788 +Epoch: [17] [ 360/2138] eta: 1:40:55 lr: 3.018498964284634e-05 loss: 0.0296 (0.0324) time: 3.3843 data: 0.0026 max mem: 19788 +Epoch: [17] [ 370/2138] eta: 1:40:13 lr: 3.017942416459864e-05 loss: 0.0311 (0.0323) time: 3.3281 data: 0.0027 max mem: 19788 +Epoch: [17] [ 380/2138] eta: 1:39:34 lr: 3.0173858572310094e-05 loss: 0.0283 (0.0322) time: 3.2607 data: 0.0030 max mem: 19788 +Epoch: [17] [ 390/2138] eta: 1:38:51 lr: 3.0168292865954984e-05 loss: 0.0254 (0.0321) time: 3.2462 data: 0.0032 max mem: 19788 +Epoch: [17] [ 400/2138] eta: 1:38:18 lr: 3.0162727045507606e-05 loss: 0.0272 (0.0321) time: 3.3031 data: 0.0031 max mem: 19788 +Epoch: [17] [ 410/2138] eta: 1:37:35 lr: 3.0157161110942217e-05 loss: 0.0314 (0.0320) time: 3.2969 data: 0.0026 max mem: 19788 +Epoch: [17] [ 420/2138] eta: 1:36:59 lr: 3.0151595062233084e-05 loss: 0.0268 (0.0319) time: 3.2566 data: 0.0028 max mem: 19788 +Epoch: [17] [ 430/2138] eta: 1:36:17 lr: 3.0146028899354446e-05 loss: 0.0265 (0.0319) time: 3.2522 data: 0.0029 max mem: 19788 +Epoch: [17] [ 440/2138] eta: 1:35:36 lr: 3.0140462622280534e-05 loss: 0.0292 (0.0319) time: 3.1963 data: 0.0030 max mem: 19788 +Epoch: [17] [ 450/2138] eta: 1:35:00 lr: 3.013489623098558e-05 loss: 0.0281 (0.0318) time: 3.2662 data: 0.0030 max mem: 19788 +Epoch: [17] [ 460/2138] eta: 1:34:21 lr: 3.0129329725443796e-05 loss: 0.0281 (0.0318) time: 3.2720 data: 0.0031 max mem: 19788 +Epoch: [17] [ 470/2138] eta: 1:33:45 lr: 3.0123763105629372e-05 loss: 0.0303 (0.0318) time: 3.2613 data: 0.0033 max mem: 19788 +Epoch: [17] [ 480/2138] eta: 1:33:15 lr: 3.011819637151651e-05 loss: 0.0325 (0.0318) time: 3.3916 data: 0.0028 max mem: 19788 +Epoch: [17] [ 490/2138] eta: 1:32:35 lr: 3.011262952307939e-05 loss: 0.0297 (0.0317) time: 3.3419 data: 0.0025 max mem: 19788 +Epoch: [17] [ 500/2138] eta: 1:31:57 lr: 3.0107062560292164e-05 loss: 0.0271 (0.0317) time: 3.2226 data: 0.0026 max mem: 19788 +Epoch: [17] [ 510/2138] eta: 1:31:22 lr: 3.0101495483129005e-05 loss: 0.0247 (0.0316) time: 3.2750 data: 0.0027 max mem: 19788 +Epoch: [17] [ 520/2138] eta: 1:30:45 lr: 3.0095928291564062e-05 loss: 0.0265 (0.0316) time: 3.2928 data: 0.0029 max mem: 19788 +Epoch: [17] [ 530/2138] eta: 1:30:06 lr: 3.0090360985571457e-05 loss: 0.0266 (0.0316) time: 3.2333 data: 0.0031 max mem: 19788 +Epoch: [17] [ 540/2138] eta: 1:29:31 lr: 3.0084793565125313e-05 loss: 0.0278 (0.0316) time: 3.2557 data: 0.0029 max mem: 19788 +Epoch: [17] [ 550/2138] eta: 1:29:09 lr: 3.0079226030199746e-05 loss: 0.0286 (0.0317) time: 3.5428 data: 0.0025 max mem: 19788 +Epoch: [17] [ 560/2138] eta: 1:28:42 lr: 3.007365838076887e-05 loss: 0.0310 (0.0317) time: 3.6880 data: 0.0023 max mem: 19788 +Epoch: [17] [ 570/2138] eta: 1:28:07 lr: 3.006809061680676e-05 loss: 0.0310 (0.0317) time: 3.4620 data: 0.0025 max mem: 19788 +Epoch: [17] [ 580/2138] eta: 1:27:43 lr: 3.0062522738287492e-05 loss: 0.0286 (0.0317) time: 3.5268 data: 0.0027 max mem: 19788 +Epoch: [17] [ 590/2138] eta: 1:27:10 lr: 3.0056954745185134e-05 loss: 0.0290 (0.0317) time: 3.5616 data: 0.0027 max mem: 19788 +Epoch: [17] [ 600/2138] eta: 1:26:31 lr: 3.0051386637473754e-05 loss: 0.0305 (0.0317) time: 3.2904 data: 0.0029 max mem: 19788 +Epoch: [17] [ 610/2138] eta: 1:25:59 lr: 3.004581841512739e-05 loss: 0.0284 (0.0317) time: 3.3132 data: 0.0030 max mem: 19788 +Epoch: [17] [ 620/2138] eta: 1:25:21 lr: 3.0040250078120074e-05 loss: 0.0309 (0.0318) time: 3.3175 data: 0.0028 max mem: 19788 +Epoch: [17] [ 630/2138] eta: 1:24:42 lr: 3.0034681626425832e-05 loss: 0.0330 (0.0318) time: 3.1934 data: 0.0029 max mem: 19788 +Epoch: [17] [ 640/2138] eta: 1:24:12 lr: 3.0029113060018677e-05 loss: 0.0290 (0.0317) time: 3.3505 data: 0.0029 max mem: 19788 +Epoch: [17] [ 650/2138] eta: 1:23:35 lr: 3.0023544378872604e-05 loss: 0.0298 (0.0317) time: 3.3785 data: 0.0026 max mem: 19788 +Epoch: [17] [ 660/2138] eta: 1:22:59 lr: 3.00179755829616e-05 loss: 0.0285 (0.0317) time: 3.2421 data: 0.0024 max mem: 19788 +Epoch: [17] [ 670/2138] eta: 1:22:23 lr: 3.0012406672259646e-05 loss: 0.0277 (0.0317) time: 3.2583 data: 0.0026 max mem: 19788 +Epoch: [17] [ 680/2138] eta: 1:21:45 lr: 3.000683764674071e-05 loss: 0.0236 (0.0316) time: 3.2268 data: 0.0028 max mem: 19788 +Epoch: [17] [ 690/2138] eta: 1:21:17 lr: 3.000126850637875e-05 loss: 0.0236 (0.0316) time: 3.4072 data: 0.0029 max mem: 19788 +Epoch: [17] [ 700/2138] eta: 1:20:41 lr: 2.9995699251147704e-05 loss: 0.0276 (0.0316) time: 3.4414 data: 0.0027 max mem: 19788 +Epoch: [17] [ 710/2138] eta: 1:20:08 lr: 2.9990129881021495e-05 loss: 0.0284 (0.0316) time: 3.3096 data: 0.0025 max mem: 19788 +Epoch: [17] [ 720/2138] eta: 1:19:35 lr: 2.9984560395974064e-05 loss: 0.0308 (0.0316) time: 3.3833 data: 0.0024 max mem: 19788 +Epoch: [17] [ 730/2138] eta: 1:19:03 lr: 2.997899079597932e-05 loss: 0.0308 (0.0316) time: 3.4315 data: 0.0029 max mem: 19788 +Epoch: [17] [ 740/2138] eta: 1:18:26 lr: 2.9973421081011137e-05 loss: 0.0311 (0.0317) time: 3.3411 data: 0.0035 max mem: 19788 +Epoch: [17] [ 750/2138] eta: 1:17:53 lr: 2.9967851251043426e-05 loss: 0.0306 (0.0317) time: 3.2969 data: 0.0031 max mem: 19788 +Epoch: [17] [ 760/2138] eta: 1:17:23 lr: 2.996228130605006e-05 loss: 0.0301 (0.0318) time: 3.4892 data: 0.0026 max mem: 19788 +Epoch: [17] [ 770/2138] eta: 1:16:51 lr: 2.9956711246004888e-05 loss: 0.0293 (0.0318) time: 3.5273 data: 0.0025 max mem: 19788 +Epoch: [17] [ 780/2138] eta: 1:16:22 lr: 2.9951141070881778e-05 loss: 0.0293 (0.0318) time: 3.5539 data: 0.0026 max mem: 19788 +Epoch: [17] [ 790/2138] eta: 1:15:55 lr: 2.9945570780654568e-05 loss: 0.0256 (0.0317) time: 3.7034 data: 0.0030 max mem: 19788 +Epoch: [17] [ 800/2138] eta: 1:15:25 lr: 2.9940000375297095e-05 loss: 0.0288 (0.0317) time: 3.6670 data: 0.0031 max mem: 19788 +Epoch: [17] [ 810/2138] eta: 1:14:49 lr: 2.9934429854783165e-05 loss: 0.0316 (0.0317) time: 3.4279 data: 0.0026 max mem: 19788 +Epoch: [17] [ 820/2138] eta: 1:14:15 lr: 2.992885921908659e-05 loss: 0.0279 (0.0317) time: 3.3080 data: 0.0025 max mem: 19788 +Epoch: [17] [ 830/2138] eta: 1:13:44 lr: 2.9923288468181177e-05 loss: 0.0269 (0.0317) time: 3.4688 data: 0.0028 max mem: 19788 +Epoch: [17] [ 840/2138] eta: 1:13:13 lr: 2.9917717602040695e-05 loss: 0.0250 (0.0316) time: 3.5628 data: 0.0027 max mem: 19788 +Epoch: [17] [ 850/2138] eta: 1:12:40 lr: 2.991214662063893e-05 loss: 0.0292 (0.0316) time: 3.5026 data: 0.0026 max mem: 19788 +Epoch: [17] [ 860/2138] eta: 1:12:04 lr: 2.990657552394964e-05 loss: 0.0295 (0.0316) time: 3.3382 data: 0.0027 max mem: 19788 +Epoch: [17] [ 870/2138] eta: 1:11:34 lr: 2.990100431194657e-05 loss: 0.0271 (0.0316) time: 3.4361 data: 0.0025 max mem: 19788 +Epoch: [17] [ 880/2138] eta: 1:11:03 lr: 2.989543298460347e-05 loss: 0.0253 (0.0316) time: 3.6221 data: 0.0023 max mem: 19788 +Epoch: [17] [ 890/2138] eta: 1:10:27 lr: 2.988986154189406e-05 loss: 0.0273 (0.0316) time: 3.4174 data: 0.0026 max mem: 19788 +Epoch: [17] [ 900/2138] eta: 1:09:52 lr: 2.988428998379206e-05 loss: 0.0284 (0.0317) time: 3.2768 data: 0.0027 max mem: 19788 +Epoch: [17] [ 910/2138] eta: 1:09:16 lr: 2.9878718310271176e-05 loss: 0.0281 (0.0316) time: 3.2837 data: 0.0027 max mem: 19788 +Epoch: [17] [ 920/2138] eta: 1:08:41 lr: 2.9873146521305102e-05 loss: 0.0251 (0.0316) time: 3.2595 data: 0.0028 max mem: 19788 +Epoch: [17] [ 930/2138] eta: 1:08:04 lr: 2.9867574616867516e-05 loss: 0.0306 (0.0316) time: 3.2203 data: 0.0026 max mem: 19788 +Epoch: [17] [ 940/2138] eta: 1:07:28 lr: 2.9862002596932085e-05 loss: 0.0329 (0.0316) time: 3.1899 data: 0.0024 max mem: 19788 +Epoch: [17] [ 950/2138] eta: 1:06:54 lr: 2.9856430461472484e-05 loss: 0.0308 (0.0316) time: 3.2504 data: 0.0025 max mem: 19788 +Epoch: [17] [ 960/2138] eta: 1:06:18 lr: 2.9850858210462355e-05 loss: 0.0304 (0.0317) time: 3.2824 data: 0.0032 max mem: 19788 +Epoch: [17] [ 970/2138] eta: 1:05:45 lr: 2.984528584387532e-05 loss: 0.0312 (0.0317) time: 3.3414 data: 0.0032 max mem: 19788 +Epoch: [17] [ 980/2138] eta: 1:05:11 lr: 2.9839713361685017e-05 loss: 0.0303 (0.0317) time: 3.3746 data: 0.0026 max mem: 19788 +Epoch: [17] [ 990/2138] eta: 1:04:41 lr: 2.9834140763865065e-05 loss: 0.0290 (0.0317) time: 3.5338 data: 0.0026 max mem: 19788 +Epoch: [17] [1000/2138] eta: 1:04:06 lr: 2.9828568050389055e-05 loss: 0.0290 (0.0317) time: 3.4964 data: 0.0025 max mem: 19788 +Epoch: [17] [1010/2138] eta: 1:03:31 lr: 2.9822995221230578e-05 loss: 0.0285 (0.0317) time: 3.2764 data: 0.0025 max mem: 19788 +Epoch: [17] [1020/2138] eta: 1:02:55 lr: 2.9817422276363212e-05 loss: 0.0245 (0.0316) time: 3.2456 data: 0.0026 max mem: 19788 +Epoch: [17] [1030/2138] eta: 1:02:20 lr: 2.9811849215760534e-05 loss: 0.0245 (0.0316) time: 3.2119 data: 0.0025 max mem: 19788 +Epoch: [17] [1040/2138] eta: 1:01:44 lr: 2.9806276039396096e-05 loss: 0.0284 (0.0316) time: 3.2269 data: 0.0027 max mem: 19788 +Epoch: [17] [1050/2138] eta: 1:01:09 lr: 2.980070274724343e-05 loss: 0.0266 (0.0316) time: 3.2148 data: 0.0029 max mem: 19788 +Epoch: [17] [1060/2138] eta: 1:00:34 lr: 2.979512933927609e-05 loss: 0.0297 (0.0316) time: 3.2059 data: 0.0030 max mem: 19788 +Epoch: [17] [1070/2138] eta: 0:59:59 lr: 2.9789555815467584e-05 loss: 0.0298 (0.0316) time: 3.2348 data: 0.0031 max mem: 19788 +Epoch: [17] [1080/2138] eta: 0:59:25 lr: 2.9783982175791414e-05 loss: 0.0298 (0.0315) time: 3.2996 data: 0.0030 max mem: 19788 +Epoch: [17] [1090/2138] eta: 0:58:49 lr: 2.9778408420221093e-05 loss: 0.0303 (0.0316) time: 3.2191 data: 0.0028 max mem: 19788 +Epoch: [17] [1100/2138] eta: 0:58:16 lr: 2.9772834548730105e-05 loss: 0.0322 (0.0316) time: 3.2790 data: 0.0025 max mem: 19788 +Epoch: [17] [1110/2138] eta: 0:57:39 lr: 2.976726056129192e-05 loss: 0.0313 (0.0316) time: 3.2400 data: 0.0022 max mem: 19788 +Epoch: [17] [1120/2138] eta: 0:57:02 lr: 2.976168645788e-05 loss: 0.0303 (0.0315) time: 3.0514 data: 0.0022 max mem: 19788 +Epoch: [17] [1130/2138] eta: 0:56:30 lr: 2.9756112238467802e-05 loss: 0.0291 (0.0315) time: 3.2806 data: 0.0023 max mem: 19788 +Epoch: [17] [1140/2138] eta: 0:55:56 lr: 2.9750537903028768e-05 loss: 0.0286 (0.0315) time: 3.3996 data: 0.0023 max mem: 19788 +Epoch: [17] [1150/2138] eta: 0:55:24 lr: 2.9744963451536323e-05 loss: 0.0255 (0.0315) time: 3.4062 data: 0.0025 max mem: 19788 +Epoch: [17] [1160/2138] eta: 0:54:48 lr: 2.9739388883963874e-05 loss: 0.0231 (0.0314) time: 3.3218 data: 0.0030 max mem: 19788 +Epoch: [17] [1170/2138] eta: 0:54:12 lr: 2.973381420028484e-05 loss: 0.0253 (0.0315) time: 3.1274 data: 0.0028 max mem: 19788 +Epoch: [17] [1180/2138] eta: 0:53:38 lr: 2.972823940047261e-05 loss: 0.0266 (0.0315) time: 3.2135 data: 0.0023 max mem: 19788 +Epoch: [17] [1190/2138] eta: 0:53:03 lr: 2.972266448450058e-05 loss: 0.0285 (0.0315) time: 3.2153 data: 0.0022 max mem: 19788 +Epoch: [17] [1200/2138] eta: 0:52:28 lr: 2.971708945234209e-05 loss: 0.0282 (0.0315) time: 3.1314 data: 0.0023 max mem: 19788 +Epoch: [17] [1210/2138] eta: 0:51:53 lr: 2.9711514303970516e-05 loss: 0.0322 (0.0316) time: 3.2069 data: 0.0025 max mem: 19788 +Epoch: [17] [1220/2138] eta: 0:51:20 lr: 2.9705939039359215e-05 loss: 0.0293 (0.0316) time: 3.3551 data: 0.0025 max mem: 19788 +Epoch: [17] [1230/2138] eta: 0:50:45 lr: 2.9700363658481506e-05 loss: 0.0285 (0.0315) time: 3.2796 data: 0.0025 max mem: 19788 +Epoch: [17] [1240/2138] eta: 0:50:09 lr: 2.9694788161310716e-05 loss: 0.0285 (0.0315) time: 3.0768 data: 0.0024 max mem: 19788 +Epoch: [17] [1250/2138] eta: 0:49:34 lr: 2.968921254782016e-05 loss: 0.0272 (0.0315) time: 3.0538 data: 0.0022 max mem: 19788 +Epoch: [17] [1260/2138] eta: 0:48:59 lr: 2.968363681798314e-05 loss: 0.0272 (0.0315) time: 3.1305 data: 0.0023 max mem: 19788 +Epoch: [17] [1270/2138] eta: 0:48:25 lr: 2.967806097177295e-05 loss: 0.0265 (0.0315) time: 3.1838 data: 0.0025 max mem: 19788 +Epoch: [17] [1280/2138] eta: 0:47:49 lr: 2.9672485009162843e-05 loss: 0.0265 (0.0315) time: 3.1079 data: 0.0030 max mem: 19788 +Epoch: [17] [1290/2138] eta: 0:47:13 lr: 2.9666908930126108e-05 loss: 0.0287 (0.0315) time: 3.0275 data: 0.0033 max mem: 19788 +Epoch: [17] [1300/2138] eta: 0:46:38 lr: 2.9661332734635993e-05 loss: 0.0300 (0.0315) time: 3.0561 data: 0.0030 max mem: 19788 +Epoch: [17] [1310/2138] eta: 0:46:05 lr: 2.9655756422665735e-05 loss: 0.0267 (0.0315) time: 3.2032 data: 0.0027 max mem: 19788 +Epoch: [17] [1320/2138] eta: 0:45:33 lr: 2.9650179994188566e-05 loss: 0.0266 (0.0315) time: 3.4221 data: 0.0024 max mem: 19788 +Epoch: [17] [1330/2138] eta: 0:44:58 lr: 2.9644603449177698e-05 loss: 0.0317 (0.0315) time: 3.3596 data: 0.0026 max mem: 19788 +Epoch: [17] [1340/2138] eta: 0:44:24 lr: 2.9639026787606355e-05 loss: 0.0330 (0.0316) time: 3.1627 data: 0.0027 max mem: 19788 +Epoch: [17] [1350/2138] eta: 0:43:48 lr: 2.963345000944772e-05 loss: 0.0330 (0.0316) time: 3.0803 data: 0.0029 max mem: 19788 +Epoch: [17] [1360/2138] eta: 0:43:13 lr: 2.962787311467497e-05 loss: 0.0329 (0.0316) time: 3.0346 data: 0.0027 max mem: 19788 +Epoch: [17] [1370/2138] eta: 0:42:38 lr: 2.9622296103261287e-05 loss: 0.0313 (0.0317) time: 3.0368 data: 0.0022 max mem: 19788 +Epoch: [17] [1380/2138] eta: 0:42:03 lr: 2.961671897517983e-05 loss: 0.0347 (0.0317) time: 3.0312 data: 0.0021 max mem: 19788 +Epoch: [17] [1390/2138] eta: 0:41:29 lr: 2.9611141730403735e-05 loss: 0.0311 (0.0316) time: 3.0517 data: 0.0021 max mem: 19788 +Epoch: [17] [1400/2138] eta: 0:40:55 lr: 2.960556436890614e-05 loss: 0.0299 (0.0316) time: 3.1496 data: 0.0023 max mem: 19788 +Epoch: [17] [1410/2138] eta: 0:40:23 lr: 2.9599986890660185e-05 loss: 0.0286 (0.0316) time: 3.3787 data: 0.0027 max mem: 19788 +Epoch: [17] [1420/2138] eta: 0:39:50 lr: 2.9594409295638975e-05 loss: 0.0287 (0.0316) time: 3.4984 data: 0.0031 max mem: 19788 +Epoch: [17] [1430/2138] eta: 0:39:17 lr: 2.9588831583815597e-05 loss: 0.0287 (0.0316) time: 3.4220 data: 0.0028 max mem: 19788 +Epoch: [17] [1440/2138] eta: 0:38:43 lr: 2.9583253755163147e-05 loss: 0.0300 (0.0317) time: 3.2963 data: 0.0025 max mem: 19788 +Epoch: [17] [1450/2138] eta: 0:38:10 lr: 2.9577675809654716e-05 loss: 0.0342 (0.0317) time: 3.2371 data: 0.0024 max mem: 19788 +Epoch: [17] [1460/2138] eta: 0:37:38 lr: 2.9572097747263348e-05 loss: 0.0299 (0.0317) time: 3.4329 data: 0.0023 max mem: 19788 +Epoch: [17] [1470/2138] eta: 0:37:04 lr: 2.9566519567962104e-05 loss: 0.0285 (0.0317) time: 3.4755 data: 0.0026 max mem: 19788 +Epoch: [17] [1480/2138] eta: 0:36:30 lr: 2.9560941271724028e-05 loss: 0.0283 (0.0316) time: 3.2250 data: 0.0026 max mem: 19788 +Epoch: [17] [1490/2138] eta: 0:35:56 lr: 2.9555362858522144e-05 loss: 0.0283 (0.0317) time: 3.0812 data: 0.0025 max mem: 19788 +Epoch: [17] [1500/2138] eta: 0:35:21 lr: 2.9549784328329482e-05 loss: 0.0309 (0.0317) time: 3.0611 data: 0.0025 max mem: 19788 +Epoch: [17] [1510/2138] eta: 0:34:47 lr: 2.9544205681119025e-05 loss: 0.0289 (0.0317) time: 3.0584 data: 0.0023 max mem: 19788 +Epoch: [17] [1520/2138] eta: 0:34:13 lr: 2.9538626916863783e-05 loss: 0.0267 (0.0317) time: 3.0843 data: 0.0025 max mem: 19788 +Epoch: [17] [1530/2138] eta: 0:33:41 lr: 2.9533048035536737e-05 loss: 0.0275 (0.0317) time: 3.3700 data: 0.0026 max mem: 19788 +Epoch: [17] [1540/2138] eta: 0:33:07 lr: 2.9527469037110855e-05 loss: 0.0282 (0.0318) time: 3.4466 data: 0.0025 max mem: 19788 +Epoch: [17] [1550/2138] eta: 0:32:33 lr: 2.9521889921559086e-05 loss: 0.0299 (0.0318) time: 3.1930 data: 0.0023 max mem: 19788 +Epoch: [17] [1560/2138] eta: 0:31:59 lr: 2.951631068885438e-05 loss: 0.0299 (0.0318) time: 3.0883 data: 0.0025 max mem: 19788 +Epoch: [17] [1570/2138] eta: 0:31:25 lr: 2.9510731338969687e-05 loss: 0.0296 (0.0318) time: 3.1017 data: 0.0026 max mem: 19788 +Epoch: [17] [1580/2138] eta: 0:30:51 lr: 2.950515187187791e-05 loss: 0.0293 (0.0320) time: 3.1250 data: 0.0027 max mem: 19788 +Epoch: [17] [1590/2138] eta: 0:30:17 lr: 2.9499572287551963e-05 loss: 0.0311 (0.0320) time: 3.0782 data: 0.0030 max mem: 19788 +Epoch: [17] [1600/2138] eta: 0:29:43 lr: 2.9493992585964746e-05 loss: 0.0341 (0.0320) time: 3.0536 data: 0.0031 max mem: 19788 +Epoch: [17] [1610/2138] eta: 0:29:09 lr: 2.948841276708915e-05 loss: 0.0345 (0.0321) time: 3.0769 data: 0.0031 max mem: 19788 +Epoch: [17] [1620/2138] eta: 0:28:35 lr: 2.9482832830898043e-05 loss: 0.0271 (0.0320) time: 3.0765 data: 0.0029 max mem: 19788 +Epoch: [17] [1630/2138] eta: 0:28:01 lr: 2.947725277736429e-05 loss: 0.0264 (0.0320) time: 3.0483 data: 0.0027 max mem: 19788 +Epoch: [17] [1640/2138] eta: 0:27:27 lr: 2.947167260646073e-05 loss: 0.0302 (0.0320) time: 3.0556 data: 0.0026 max mem: 19788 +Epoch: [17] [1650/2138] eta: 0:26:54 lr: 2.9466092318160232e-05 loss: 0.0320 (0.0320) time: 3.2164 data: 0.0026 max mem: 19788 +Epoch: [17] [1660/2138] eta: 0:26:21 lr: 2.9460511912435584e-05 loss: 0.0313 (0.0320) time: 3.2724 data: 0.0025 max mem: 19788 +Epoch: [17] [1670/2138] eta: 0:25:49 lr: 2.9454931389259615e-05 loss: 0.0303 (0.0320) time: 3.3806 data: 0.0023 max mem: 19788 +Epoch: [17] [1680/2138] eta: 0:25:15 lr: 2.9449350748605143e-05 loss: 0.0306 (0.0320) time: 3.3874 data: 0.0027 max mem: 19788 +Epoch: [17] [1690/2138] eta: 0:24:42 lr: 2.9443769990444942e-05 loss: 0.0315 (0.0320) time: 3.1690 data: 0.0030 max mem: 19788 +Epoch: [17] [1700/2138] eta: 0:24:08 lr: 2.9438189114751784e-05 loss: 0.0315 (0.0321) time: 3.1564 data: 0.0030 max mem: 19788 +Epoch: [17] [1710/2138] eta: 0:23:35 lr: 2.9432608121498445e-05 loss: 0.0305 (0.0322) time: 3.1953 data: 0.0031 max mem: 19788 +Epoch: [17] [1720/2138] eta: 0:23:02 lr: 2.942702701065769e-05 loss: 0.0324 (0.0322) time: 3.2725 data: 0.0030 max mem: 19788 +Epoch: [17] [1730/2138] eta: 0:22:29 lr: 2.942144578220224e-05 loss: 0.0308 (0.0322) time: 3.4111 data: 0.0027 max mem: 19788 +Epoch: [17] [1740/2138] eta: 0:21:56 lr: 2.9415864436104836e-05 loss: 0.0308 (0.0322) time: 3.4266 data: 0.0027 max mem: 19788 +Epoch: [17] [1750/2138] eta: 0:21:23 lr: 2.9410282972338186e-05 loss: 0.0310 (0.0322) time: 3.2548 data: 0.0027 max mem: 19788 +Epoch: [17] [1760/2138] eta: 0:20:49 lr: 2.9404701390875018e-05 loss: 0.0292 (0.0322) time: 3.1144 data: 0.0025 max mem: 19788 +Epoch: [17] [1770/2138] eta: 0:20:16 lr: 2.9399119691688006e-05 loss: 0.0281 (0.0322) time: 3.1197 data: 0.0027 max mem: 19788 +Epoch: [17] [1780/2138] eta: 0:19:43 lr: 2.9393537874749834e-05 loss: 0.0252 (0.0322) time: 3.3563 data: 0.0025 max mem: 19788 +Epoch: [17] [1790/2138] eta: 0:19:11 lr: 2.9387955940033168e-05 loss: 0.0251 (0.0322) time: 3.4848 data: 0.0024 max mem: 19788 +Epoch: [17] [1800/2138] eta: 0:18:37 lr: 2.9382373887510685e-05 loss: 0.0396 (0.0322) time: 3.2870 data: 0.0028 max mem: 19788 +Epoch: [17] [1810/2138] eta: 0:18:04 lr: 2.9376791717155012e-05 loss: 0.0319 (0.0323) time: 3.1351 data: 0.0028 max mem: 19788 +Epoch: [17] [1820/2138] eta: 0:17:30 lr: 2.9371209428938784e-05 loss: 0.0269 (0.0322) time: 3.1397 data: 0.0026 max mem: 19788 +Epoch: [17] [1830/2138] eta: 0:16:57 lr: 2.9365627022834625e-05 loss: 0.0265 (0.0322) time: 3.1629 data: 0.0025 max mem: 19788 +Epoch: [17] [1840/2138] eta: 0:16:24 lr: 2.936004449881514e-05 loss: 0.0292 (0.0322) time: 3.1137 data: 0.0025 max mem: 19788 +Epoch: [17] [1850/2138] eta: 0:15:50 lr: 2.9354461856852944e-05 loss: 0.0327 (0.0322) time: 3.0596 data: 0.0026 max mem: 19788 +Epoch: [17] [1860/2138] eta: 0:15:17 lr: 2.934887909692059e-05 loss: 0.0302 (0.0322) time: 3.1590 data: 0.0026 max mem: 19788 +Epoch: [17] [1870/2138] eta: 0:14:45 lr: 2.9343296218990675e-05 loss: 0.0302 (0.0322) time: 3.4157 data: 0.0024 max mem: 19788 +Epoch: [17] [1880/2138] eta: 0:14:12 lr: 2.933771322303575e-05 loss: 0.0271 (0.0322) time: 3.4440 data: 0.0024 max mem: 19788 +Epoch: [17] [1890/2138] eta: 0:13:38 lr: 2.9332130109028372e-05 loss: 0.0257 (0.0322) time: 3.1849 data: 0.0024 max mem: 19788 +Epoch: [17] [1900/2138] eta: 0:13:05 lr: 2.9326546876941058e-05 loss: 0.0276 (0.0322) time: 3.0822 data: 0.0023 max mem: 19788 +Epoch: [17] [1910/2138] eta: 0:12:32 lr: 2.9320963526746342e-05 loss: 0.0264 (0.0322) time: 3.0854 data: 0.0024 max mem: 19788 +Epoch: [17] [1920/2138] eta: 0:11:58 lr: 2.931538005841674e-05 loss: 0.0264 (0.0321) time: 3.0593 data: 0.0027 max mem: 19788 +Epoch: [17] [1930/2138] eta: 0:11:26 lr: 2.9309796471924756e-05 loss: 0.0300 (0.0322) time: 3.1903 data: 0.0028 max mem: 19788 +Epoch: [17] [1940/2138] eta: 0:10:53 lr: 2.9304212767242856e-05 loss: 0.0302 (0.0322) time: 3.3022 data: 0.0028 max mem: 19788 +Epoch: [17] [1950/2138] eta: 0:10:20 lr: 2.9298628944343525e-05 loss: 0.0293 (0.0322) time: 3.3419 data: 0.0028 max mem: 19788 +Epoch: [17] [1960/2138] eta: 0:09:47 lr: 2.9293045003199242e-05 loss: 0.0280 (0.0322) time: 3.4282 data: 0.0026 max mem: 19788 +Epoch: [17] [1970/2138] eta: 0:09:14 lr: 2.928746094378243e-05 loss: 0.0279 (0.0321) time: 3.3560 data: 0.0026 max mem: 19788 +Epoch: [17] [1980/2138] eta: 0:08:41 lr: 2.928187676606554e-05 loss: 0.0284 (0.0321) time: 3.3979 data: 0.0025 max mem: 19788 +Epoch: [17] [1990/2138] eta: 0:08:08 lr: 2.9276292470021006e-05 loss: 0.0283 (0.0321) time: 3.4545 data: 0.0024 max mem: 19788 +Epoch: [17] [2000/2138] eta: 0:07:35 lr: 2.9270708055621228e-05 loss: 0.0283 (0.0321) time: 3.2709 data: 0.0025 max mem: 19788 +Epoch: [17] [2010/2138] eta: 0:07:02 lr: 2.9265123522838607e-05 loss: 0.0290 (0.0321) time: 3.1285 data: 0.0023 max mem: 19788 +Epoch: [17] [2020/2138] eta: 0:06:29 lr: 2.9259538871645537e-05 loss: 0.0306 (0.0321) time: 3.1553 data: 0.0022 max mem: 19788 +Epoch: [17] [2030/2138] eta: 0:05:56 lr: 2.9253954102014397e-05 loss: 0.0306 (0.0321) time: 3.2027 data: 0.0025 max mem: 19788 +Epoch: [17] [2040/2138] eta: 0:05:23 lr: 2.924836921391755e-05 loss: 0.0273 (0.0321) time: 3.1334 data: 0.0026 max mem: 19788 +Epoch: [17] [2050/2138] eta: 0:04:50 lr: 2.924278420732734e-05 loss: 0.0289 (0.0321) time: 3.1886 data: 0.0027 max mem: 19788 +Epoch: [17] [2060/2138] eta: 0:04:17 lr: 2.9237199082216117e-05 loss: 0.0304 (0.0321) time: 3.2068 data: 0.0028 max mem: 19788 +Epoch: [17] [2070/2138] eta: 0:03:44 lr: 2.9231613838556203e-05 loss: 0.0292 (0.0321) time: 3.1965 data: 0.0025 max mem: 19788 +Epoch: [17] [2080/2138] eta: 0:03:11 lr: 2.9226028476319916e-05 loss: 0.0271 (0.0321) time: 3.1783 data: 0.0023 max mem: 19788 +Epoch: [17] [2090/2138] eta: 0:02:38 lr: 2.922044299547955e-05 loss: 0.0271 (0.0321) time: 3.1065 data: 0.0027 max mem: 19788 +Epoch: [17] [2100/2138] eta: 0:02:05 lr: 2.921485739600741e-05 loss: 0.0287 (0.0320) time: 3.1219 data: 0.0031 max mem: 19788 +Epoch: [17] [2110/2138] eta: 0:01:32 lr: 2.9209271677875767e-05 loss: 0.0332 (0.0321) time: 3.1206 data: 0.0031 max mem: 19788 +Epoch: [17] [2120/2138] eta: 0:00:59 lr: 2.920368584105688e-05 loss: 0.0355 (0.0321) time: 3.2384 data: 0.0030 max mem: 19788 +Epoch: [17] [2130/2138] eta: 0:00:26 lr: 2.9198099885523007e-05 loss: 0.0375 (0.0321) time: 3.1937 data: 0.0025 max mem: 19788 +Epoch: [17] Total time: 1:57:17 +Test: [ 0/21770] eta: 16:44:59 time: 2.7698 data: 2.6687 max mem: 19788 +Test: [ 100/21770] eta: 0:27:22 time: 0.0428 data: 0.0014 max mem: 19788 +Test: [ 200/21770] eta: 0:22:15 time: 0.0535 data: 0.0017 max mem: 19788 +Test: [ 300/21770] eta: 0:20:07 time: 0.0446 data: 0.0015 max mem: 19788 +Test: [ 400/21770] eta: 0:19:01 time: 0.0440 data: 0.0016 max mem: 19788 +Test: [ 500/21770] eta: 0:18:15 time: 0.0446 data: 0.0014 max mem: 19788 +Test: [ 600/21770] eta: 0:17:58 time: 0.0511 data: 0.0017 max mem: 19788 +Test: [ 700/21770] eta: 0:17:40 time: 0.0437 data: 0.0013 max mem: 19788 +Test: [ 800/21770] eta: 0:17:27 time: 0.0457 data: 0.0014 max mem: 19788 +Test: [ 900/21770] eta: 0:17:11 time: 0.0435 data: 0.0014 max mem: 19788 +Test: [ 1000/21770] eta: 0:17:13 time: 0.0535 data: 0.0019 max mem: 19788 +Test: [ 1100/21770] eta: 0:17:08 time: 0.0437 data: 0.0016 max mem: 19788 +Test: [ 1200/21770] eta: 0:16:59 time: 0.0480 data: 0.0017 max mem: 19788 +Test: [ 1300/21770] eta: 0:16:54 time: 0.0540 data: 0.0018 max mem: 19788 +Test: [ 1400/21770] eta: 0:16:48 time: 0.0427 data: 0.0015 max mem: 19788 +Test: [ 1500/21770] eta: 0:16:44 time: 0.0439 data: 0.0018 max mem: 19788 +Test: [ 1600/21770] eta: 0:16:41 time: 0.0553 data: 0.0017 max mem: 19788 +Test: [ 1700/21770] eta: 0:16:35 time: 0.0540 data: 0.0017 max mem: 19788 +Test: [ 1800/21770] eta: 0:16:26 time: 0.0440 data: 0.0016 max mem: 19788 +Test: [ 1900/21770] eta: 0:16:16 time: 0.0441 data: 0.0016 max mem: 19788 +Test: [ 2000/21770] eta: 0:16:12 time: 0.0536 data: 0.0018 max mem: 19788 +Test: [ 2100/21770] eta: 0:16:02 time: 0.0442 data: 0.0015 max mem: 19788 +Test: [ 2200/21770] eta: 0:15:54 time: 0.0524 data: 0.0018 max mem: 19788 +Test: [ 2300/21770] eta: 0:15:52 time: 0.0491 data: 0.0016 max mem: 19788 +Test: [ 2400/21770] eta: 0:15:49 time: 0.0531 data: 0.0018 max mem: 19788 +Test: [ 2500/21770] eta: 0:15:46 time: 0.0502 data: 0.0017 max mem: 19788 +Test: [ 2600/21770] eta: 0:15:39 time: 0.0446 data: 0.0015 max mem: 19788 +Test: [ 2700/21770] eta: 0:15:32 time: 0.0443 data: 0.0015 max mem: 19788 +Test: [ 2800/21770] eta: 0:15:26 time: 0.0527 data: 0.0018 max mem: 19788 +Test: [ 2900/21770] eta: 0:15:21 time: 0.0450 data: 0.0015 max mem: 19788 +Test: [ 3000/21770] eta: 0:15:14 time: 0.0448 data: 0.0014 max mem: 19788 +Test: [ 3100/21770] eta: 0:15:07 time: 0.0451 data: 0.0017 max mem: 19788 +Test: [ 3200/21770] eta: 0:15:05 time: 0.0532 data: 0.0018 max mem: 19788 +Test: [ 3300/21770] eta: 0:15:01 time: 0.0538 data: 0.0018 max mem: 19788 +Test: [ 3400/21770] eta: 0:14:58 time: 0.0489 data: 0.0016 max mem: 19788 +Test: [ 3500/21770] eta: 0:14:55 time: 0.0495 data: 0.0017 max mem: 19788 +Test: [ 3600/21770] eta: 0:14:48 time: 0.0463 data: 0.0014 max mem: 19788 +Test: [ 3700/21770] eta: 0:14:43 time: 0.0490 data: 0.0016 max mem: 19788 +Test: [ 3800/21770] eta: 0:14:39 time: 0.0538 data: 0.0018 max mem: 19788 +Test: [ 3900/21770] eta: 0:14:33 time: 0.0479 data: 0.0018 max mem: 19788 +Test: [ 4000/21770] eta: 0:14:27 time: 0.0467 data: 0.0014 max mem: 19788 +Test: [ 4100/21770] eta: 0:14:22 time: 0.0451 data: 0.0014 max mem: 19788 +Test: [ 4200/21770] eta: 0:14:15 time: 0.0449 data: 0.0015 max mem: 19788 +Test: [ 4300/21770] eta: 0:14:09 time: 0.0521 data: 0.0017 max mem: 19788 +Test: [ 4400/21770] eta: 0:14:05 time: 0.0445 data: 0.0014 max mem: 19788 +Test: [ 4500/21770] eta: 0:13:59 time: 0.0444 data: 0.0014 max mem: 19788 +Test: [ 4600/21770] eta: 0:13:53 time: 0.0448 data: 0.0025 max mem: 19788 +Test: [ 4700/21770] eta: 0:13:46 time: 0.0442 data: 0.0014 max mem: 19788 +Test: [ 4800/21770] eta: 0:13:42 time: 0.0532 data: 0.0017 max mem: 19788 +Test: [ 4900/21770] eta: 0:13:38 time: 0.0526 data: 0.0019 max mem: 19788 +Test: [ 5000/21770] eta: 0:13:34 time: 0.0537 data: 0.0017 max mem: 19788 +Test: [ 5100/21770] eta: 0:13:28 time: 0.0452 data: 0.0015 max mem: 19788 +Test: [ 5200/21770] eta: 0:13:22 time: 0.0448 data: 0.0018 max mem: 19788 +Test: [ 5300/21770] eta: 0:13:16 time: 0.0446 data: 0.0015 max mem: 19788 +Test: [ 5400/21770] eta: 0:13:11 time: 0.0510 data: 0.0016 max mem: 19788 +Test: [ 5500/21770] eta: 0:13:07 time: 0.0549 data: 0.0020 max mem: 19788 +Test: [ 5600/21770] eta: 0:13:02 time: 0.0522 data: 0.0018 max mem: 19788 +Test: [ 5700/21770] eta: 0:12:56 time: 0.0452 data: 0.0016 max mem: 19788 +Test: [ 5800/21770] eta: 0:12:52 time: 0.0550 data: 0.0019 max mem: 19788 +Test: [ 5900/21770] eta: 0:12:48 time: 0.0543 data: 0.0018 max mem: 19788 +Test: [ 6000/21770] eta: 0:12:44 time: 0.0545 data: 0.0019 max mem: 19788 +Test: [ 6100/21770] eta: 0:12:39 time: 0.0442 data: 0.0015 max mem: 19788 +Test: [ 6200/21770] eta: 0:12:34 time: 0.0553 data: 0.0017 max mem: 19788 +Test: [ 6300/21770] eta: 0:12:31 time: 0.0545 data: 0.0016 max mem: 19788 +Test: [ 6400/21770] eta: 0:12:25 time: 0.0447 data: 0.0016 max mem: 19788 +Test: [ 6500/21770] eta: 0:12:21 time: 0.0538 data: 0.0015 max mem: 19788 +Test: [ 6600/21770] eta: 0:12:16 time: 0.0534 data: 0.0019 max mem: 19788 +Test: [ 6700/21770] eta: 0:12:11 time: 0.0441 data: 0.0016 max mem: 19788 +Test: [ 6800/21770] eta: 0:12:07 time: 0.0516 data: 0.0017 max mem: 19788 +Test: [ 6900/21770] eta: 0:12:02 time: 0.0548 data: 0.0018 max mem: 19788 +Test: [ 7000/21770] eta: 0:11:58 time: 0.0540 data: 0.0018 max mem: 19788 +Test: [ 7100/21770] eta: 0:11:53 time: 0.0442 data: 0.0016 max mem: 19788 +Test: [ 7200/21770] eta: 0:11:48 time: 0.0536 data: 0.0019 max mem: 19788 +Test: [ 7300/21770] eta: 0:11:44 time: 0.0542 data: 0.0019 max mem: 19788 +Test: [ 7400/21770] eta: 0:11:39 time: 0.0463 data: 0.0016 max mem: 19788 +Test: [ 7500/21770] eta: 0:11:34 time: 0.0463 data: 0.0018 max mem: 19788 +Test: [ 7600/21770] eta: 0:11:29 time: 0.0541 data: 0.0017 max mem: 19788 +Test: [ 7700/21770] eta: 0:11:25 time: 0.0517 data: 0.0018 max mem: 19788 +Test: [ 7800/21770] eta: 0:11:20 time: 0.0537 data: 0.0018 max mem: 19788 +Test: [ 7900/21770] eta: 0:11:15 time: 0.0456 data: 0.0016 max mem: 19788 +Test: [ 8000/21770] eta: 0:11:10 time: 0.0454 data: 0.0017 max mem: 19788 +Test: [ 8100/21770] eta: 0:11:05 time: 0.0546 data: 0.0019 max mem: 19788 +Test: [ 8200/21770] eta: 0:11:01 time: 0.0518 data: 0.0019 max mem: 19788 +Test: [ 8300/21770] eta: 0:10:55 time: 0.0481 data: 0.0016 max mem: 19788 +Test: [ 8400/21770] eta: 0:10:50 time: 0.0449 data: 0.0016 max mem: 19788 +Test: [ 8500/21770] eta: 0:10:45 time: 0.0471 data: 0.0014 max mem: 19788 +Test: [ 8600/21770] eta: 0:10:39 time: 0.0431 data: 0.0015 max mem: 19788 +Test: [ 8700/21770] eta: 0:10:35 time: 0.0483 data: 0.0017 max mem: 19788 +Test: [ 8800/21770] eta: 0:10:29 time: 0.0442 data: 0.0014 max mem: 19788 +Test: [ 8900/21770] eta: 0:10:25 time: 0.0449 data: 0.0016 max mem: 19788 +Test: [ 9000/21770] eta: 0:10:19 time: 0.0450 data: 0.0016 max mem: 19788 +Test: [ 9100/21770] eta: 0:10:14 time: 0.0444 data: 0.0013 max mem: 19788 +Test: [ 9200/21770] eta: 0:10:09 time: 0.0439 data: 0.0014 max mem: 19788 +Test: [ 9300/21770] eta: 0:10:04 time: 0.0485 data: 0.0018 max mem: 19788 +Test: [ 9400/21770] eta: 0:09:59 time: 0.0450 data: 0.0020 max mem: 19788 +Test: [ 9500/21770] eta: 0:09:54 time: 0.0543 data: 0.0018 max mem: 19788 +Test: [ 9600/21770] eta: 0:09:50 time: 0.0547 data: 0.0016 max mem: 19788 +Test: [ 9700/21770] eta: 0:09:45 time: 0.0460 data: 0.0017 max mem: 19788 +Test: [ 9800/21770] eta: 0:09:41 time: 0.0535 data: 0.0018 max mem: 19788 +Test: [ 9900/21770] eta: 0:09:36 time: 0.0464 data: 0.0015 max mem: 19788 +Test: [10000/21770] eta: 0:09:31 time: 0.0541 data: 0.0018 max mem: 19788 +Test: [10100/21770] eta: 0:09:27 time: 0.0517 data: 0.0018 max mem: 19788 +Test: [10200/21770] eta: 0:09:22 time: 0.0448 data: 0.0015 max mem: 19788 +Test: [10300/21770] eta: 0:09:17 time: 0.0542 data: 0.0017 max mem: 19788 +Test: [10400/21770] eta: 0:09:12 time: 0.0436 data: 0.0015 max mem: 19788 +Test: [10500/21770] eta: 0:09:07 time: 0.0517 data: 0.0018 max mem: 19788 +Test: [10600/21770] eta: 0:09:03 time: 0.0509 data: 0.0015 max mem: 19788 +Test: [10700/21770] eta: 0:08:58 time: 0.0506 data: 0.0015 max mem: 19788 +Test: [10800/21770] eta: 0:08:53 time: 0.0444 data: 0.0016 max mem: 19788 +Test: [10900/21770] eta: 0:08:48 time: 0.0510 data: 0.0016 max mem: 19788 +Test: [11000/21770] eta: 0:08:44 time: 0.0532 data: 0.0019 max mem: 19788 +Test: [11100/21770] eta: 0:08:39 time: 0.0528 data: 0.0017 max mem: 19788 +Test: [11200/21770] eta: 0:08:34 time: 0.0442 data: 0.0014 max mem: 19788 +Test: [11300/21770] eta: 0:08:29 time: 0.0441 data: 0.0015 max mem: 19788 +Test: [11400/21770] eta: 0:08:24 time: 0.0481 data: 0.0016 max mem: 19788 +Test: [11500/21770] eta: 0:08:19 time: 0.0445 data: 0.0017 max mem: 19788 +Test: [11600/21770] eta: 0:08:14 time: 0.0485 data: 0.0015 max mem: 19788 +Test: [11700/21770] eta: 0:08:09 time: 0.0535 data: 0.0018 max mem: 19788 +Test: [11800/21770] eta: 0:08:04 time: 0.0489 data: 0.0018 max mem: 19788 +Test: [11900/21770] eta: 0:08:00 time: 0.0483 data: 0.0017 max mem: 19788 +Test: [12000/21770] eta: 0:07:55 time: 0.0543 data: 0.0019 max mem: 19788 +Test: [12100/21770] eta: 0:07:50 time: 0.0442 data: 0.0014 max mem: 19788 +Test: [12200/21770] eta: 0:07:46 time: 0.0458 data: 0.0017 max mem: 19788 +Test: [12300/21770] eta: 0:07:41 time: 0.0539 data: 0.0019 max mem: 19788 +Test: [12400/21770] eta: 0:07:36 time: 0.0473 data: 0.0016 max mem: 19788 +Test: [12500/21770] eta: 0:07:31 time: 0.0531 data: 0.0017 max mem: 19788 +Test: [12600/21770] eta: 0:07:26 time: 0.0529 data: 0.0018 max mem: 19788 +Test: [12700/21770] eta: 0:07:21 time: 0.0532 data: 0.0019 max mem: 19788 +Test: [12800/21770] eta: 0:07:17 time: 0.0493 data: 0.0015 max mem: 19788 +Test: [12900/21770] eta: 0:07:12 time: 0.0537 data: 0.0019 max mem: 19788 +Test: [13000/21770] eta: 0:07:08 time: 0.0513 data: 0.0017 max mem: 19788 +Test: [13100/21770] eta: 0:07:03 time: 0.0461 data: 0.0016 max mem: 19788 +Test: [13200/21770] eta: 0:06:58 time: 0.0531 data: 0.0018 max mem: 19788 +Test: [13300/21770] eta: 0:06:53 time: 0.0442 data: 0.0015 max mem: 19788 +Test: [13400/21770] eta: 0:06:48 time: 0.0464 data: 0.0016 max mem: 19788 +Test: [13500/21770] eta: 0:06:44 time: 0.0530 data: 0.0016 max mem: 19788 +Test: [13600/21770] eta: 0:06:39 time: 0.0513 data: 0.0018 max mem: 19788 +Test: [13700/21770] eta: 0:06:34 time: 0.0502 data: 0.0019 max mem: 19788 +Test: [13800/21770] eta: 0:06:29 time: 0.0441 data: 0.0014 max mem: 19788 +Test: [13900/21770] eta: 0:06:24 time: 0.0452 data: 0.0015 max mem: 19788 +Test: [14000/21770] eta: 0:06:19 time: 0.0535 data: 0.0017 max mem: 19788 +Test: [14100/21770] eta: 0:06:15 time: 0.0545 data: 0.0019 max mem: 19788 +Test: [14200/21770] eta: 0:06:10 time: 0.0502 data: 0.0018 max mem: 19788 +Test: [14300/21770] eta: 0:06:05 time: 0.0456 data: 0.0014 max mem: 19788 +Test: [14400/21770] eta: 0:06:00 time: 0.0472 data: 0.0015 max mem: 19788 +Test: [14500/21770] eta: 0:05:55 time: 0.0473 data: 0.0016 max mem: 19788 +Test: [14600/21770] eta: 0:05:50 time: 0.0501 data: 0.0018 max mem: 19788 +Test: [14700/21770] eta: 0:05:46 time: 0.0512 data: 0.0017 max mem: 19788 +Test: [14800/21770] eta: 0:05:41 time: 0.0493 data: 0.0015 max mem: 19788 +Test: [14900/21770] eta: 0:05:36 time: 0.0558 data: 0.0017 max mem: 19788 +Test: [15000/21770] eta: 0:05:31 time: 0.0448 data: 0.0016 max mem: 19788 +Test: [15100/21770] eta: 0:05:26 time: 0.0466 data: 0.0015 max mem: 19788 +Test: [15200/21770] eta: 0:05:21 time: 0.0517 data: 0.0017 max mem: 19788 +Test: [15300/21770] eta: 0:05:16 time: 0.0454 data: 0.0016 max mem: 19788 +Test: [15400/21770] eta: 0:05:11 time: 0.0511 data: 0.0017 max mem: 19788 +Test: [15500/21770] eta: 0:05:07 time: 0.0543 data: 0.0018 max mem: 19788 +Test: [15600/21770] eta: 0:05:02 time: 0.0450 data: 0.0014 max mem: 19788 +Test: [15700/21770] eta: 0:04:57 time: 0.0512 data: 0.0018 max mem: 19788 +Test: [15800/21770] eta: 0:04:52 time: 0.0503 data: 0.0016 max mem: 19788 +Test: [15900/21770] eta: 0:04:47 time: 0.0461 data: 0.0015 max mem: 19788 +Test: [16000/21770] eta: 0:04:42 time: 0.0450 data: 0.0017 max mem: 19788 +Test: [16100/21770] eta: 0:04:37 time: 0.0458 data: 0.0015 max mem: 19788 +Test: [16200/21770] eta: 0:04:32 time: 0.0513 data: 0.0018 max mem: 19788 +Test: [16300/21770] eta: 0:04:27 time: 0.0503 data: 0.0017 max mem: 19788 +Test: [16400/21770] eta: 0:04:22 time: 0.0486 data: 0.0018 max mem: 19788 +Test: [16500/21770] eta: 0:04:18 time: 0.0438 data: 0.0015 max mem: 19788 +Test: [16600/21770] eta: 0:04:13 time: 0.0459 data: 0.0015 max mem: 19788 +Test: [16700/21770] eta: 0:04:08 time: 0.0536 data: 0.0020 max mem: 19788 +Test: [16800/21770] eta: 0:04:03 time: 0.0441 data: 0.0014 max mem: 19788 +Test: [16900/21770] eta: 0:03:58 time: 0.0456 data: 0.0016 max mem: 19788 +Test: [17000/21770] eta: 0:03:53 time: 0.0437 data: 0.0015 max mem: 19788 +Test: [17100/21770] eta: 0:03:48 time: 0.0540 data: 0.0018 max mem: 19788 +Test: [17200/21770] eta: 0:03:43 time: 0.0490 data: 0.0017 max mem: 19788 +Test: [17300/21770] eta: 0:03:38 time: 0.0470 data: 0.0015 max mem: 19788 +Test: [17400/21770] eta: 0:03:33 time: 0.0449 data: 0.0014 max mem: 19788 +Test: [17500/21770] eta: 0:03:28 time: 0.0444 data: 0.0015 max mem: 19788 +Test: [17600/21770] eta: 0:03:24 time: 0.0481 data: 0.0017 max mem: 19788 +Test: [17700/21770] eta: 0:03:19 time: 0.0503 data: 0.0017 max mem: 19788 +Test: [17800/21770] eta: 0:03:14 time: 0.0445 data: 0.0013 max mem: 19788 +Test: [17900/21770] eta: 0:03:09 time: 0.0529 data: 0.0018 max mem: 19788 +Test: [18000/21770] eta: 0:03:04 time: 0.0483 data: 0.0017 max mem: 19788 +Test: [18100/21770] eta: 0:02:59 time: 0.0495 data: 0.0018 max mem: 19788 +Test: [18200/21770] eta: 0:02:54 time: 0.0549 data: 0.0018 max mem: 19788 +Test: [18300/21770] eta: 0:02:50 time: 0.0451 data: 0.0014 max mem: 19788 +Test: [18400/21770] eta: 0:02:45 time: 0.0469 data: 0.0016 max mem: 19788 +Test: [18500/21770] eta: 0:02:40 time: 0.0499 data: 0.0017 max mem: 19788 +Test: [18600/21770] eta: 0:02:35 time: 0.0461 data: 0.0016 max mem: 19788 +Test: [18700/21770] eta: 0:02:30 time: 0.0442 data: 0.0015 max mem: 19788 +Test: [18800/21770] eta: 0:02:25 time: 0.0454 data: 0.0016 max mem: 19788 +Test: [18900/21770] eta: 0:02:20 time: 0.0495 data: 0.0018 max mem: 19788 +Test: [19000/21770] eta: 0:02:15 time: 0.0497 data: 0.0018 max mem: 19788 +Test: [19100/21770] eta: 0:02:10 time: 0.0548 data: 0.0020 max mem: 19788 +Test: [19200/21770] eta: 0:02:05 time: 0.0531 data: 0.0016 max mem: 19788 +Test: [19300/21770] eta: 0:02:00 time: 0.0483 data: 0.0015 max mem: 19788 +Test: [19400/21770] eta: 0:01:56 time: 0.0459 data: 0.0015 max mem: 19788 +Test: [19500/21770] eta: 0:01:51 time: 0.0437 data: 0.0016 max mem: 19788 +Test: [19600/21770] eta: 0:01:46 time: 0.0465 data: 0.0017 max mem: 19788 +Test: [19700/21770] eta: 0:01:41 time: 0.0429 data: 0.0015 max mem: 19788 +Test: [19800/21770] eta: 0:01:36 time: 0.0439 data: 0.0013 max mem: 19788 +Test: [19900/21770] eta: 0:01:31 time: 0.0508 data: 0.0014 max mem: 19788 +Test: [20000/21770] eta: 0:01:26 time: 0.0528 data: 0.0019 max mem: 19788 +Test: [20100/21770] eta: 0:01:21 time: 0.0442 data: 0.0015 max mem: 19788 +Test: [20200/21770] eta: 0:01:16 time: 0.0451 data: 0.0015 max mem: 19788 +Test: [20300/21770] eta: 0:01:11 time: 0.0555 data: 0.0017 max mem: 19788 +Test: [20400/21770] eta: 0:01:06 time: 0.0447 data: 0.0016 max mem: 19788 +Test: [20500/21770] eta: 0:01:02 time: 0.0500 data: 0.0019 max mem: 19788 +Test: [20600/21770] eta: 0:00:57 time: 0.0473 data: 0.0017 max mem: 19788 +Test: [20700/21770] eta: 0:00:52 time: 0.0509 data: 0.0018 max mem: 19788 +Test: [20800/21770] eta: 0:00:47 time: 0.0451 data: 0.0015 max mem: 19788 +Test: [20900/21770] eta: 0:00:42 time: 0.0540 data: 0.0019 max mem: 19788 +Test: [21000/21770] eta: 0:00:37 time: 0.0457 data: 0.0015 max mem: 19788 +Test: [21100/21770] eta: 0:00:32 time: 0.0545 data: 0.0019 max mem: 19788 +Test: [21200/21770] eta: 0:00:27 time: 0.0528 data: 0.0016 max mem: 19788 +Test: [21300/21770] eta: 0:00:22 time: 0.0446 data: 0.0014 max mem: 19788 +Test: [21400/21770] eta: 0:00:18 time: 0.0513 data: 0.0018 max mem: 19788 +Test: [21500/21770] eta: 0:00:13 time: 0.0455 data: 0.0016 max mem: 19788 +Test: [21600/21770] eta: 0:00:08 time: 0.0482 data: 0.0015 max mem: 19788 +Test: [21700/21770] eta: 0:00:03 time: 0.0544 data: 0.0018 max mem: 19788 +Test: Total time: 0:17:45 +Final results: +Mean IoU is 63.76 + + precision@0.5 = 70.61 + precision@0.6 = 64.71 + precision@0.7 = 57.67 + precision@0.8 = 46.94 + precision@0.9 = 23.46 + overall IoU = 63.56 + mean IoU = 63.76 + +Mean accuracy for one-to-zero sample is 84.36 + +Average object IoU 0.6375573530731636 +Overall IoU 63.56142044067383 +Epoch: [18] [ 0/2138] eta: 6:32:37 lr: 2.919363103560247e-05 loss: 0.0394 (0.0394) time: 11.0184 data: 1.6453 max mem: 19788 +Epoch: [18] [ 10/2138] eta: 2:19:05 lr: 2.918804486631166e-05 loss: 0.0322 (0.0338) time: 3.9219 data: 0.1518 max mem: 19788 +Epoch: [18] [ 20/2138] eta: 2:05:22 lr: 2.9182458578228104e-05 loss: 0.0268 (0.0311) time: 3.1786 data: 0.0020 max mem: 19788 +Epoch: [18] [ 30/2138] eta: 1:59:59 lr: 2.917687217132402e-05 loss: 0.0306 (0.0314) time: 3.1364 data: 0.0018 max mem: 19788 +Epoch: [18] [ 40/2138] eta: 1:58:20 lr: 2.9171285645571594e-05 loss: 0.0315 (0.0321) time: 3.2084 data: 0.0023 max mem: 19788 +Epoch: [18] [ 50/2138] eta: 1:56:02 lr: 2.9165699000942997e-05 loss: 0.0286 (0.0316) time: 3.2095 data: 0.0027 max mem: 19788 +Epoch: [18] [ 60/2138] eta: 1:55:16 lr: 2.9160112237410408e-05 loss: 0.0323 (0.0322) time: 3.2140 data: 0.0026 max mem: 19788 +Epoch: [18] [ 70/2138] eta: 1:53:55 lr: 2.9154525354945987e-05 loss: 0.0299 (0.0320) time: 3.2311 data: 0.0023 max mem: 19788 +Epoch: [18] [ 80/2138] eta: 1:52:14 lr: 2.9148938353521878e-05 loss: 0.0278 (0.0318) time: 3.1015 data: 0.0022 max mem: 19788 +Epoch: [18] [ 90/2138] eta: 1:51:10 lr: 2.9143351233110195e-05 loss: 0.0271 (0.0317) time: 3.0852 data: 0.0021 max mem: 19788 +Epoch: [18] [ 100/2138] eta: 1:51:36 lr: 2.9137763993683075e-05 loss: 0.0290 (0.0318) time: 3.3407 data: 0.0026 max mem: 19788 +Epoch: [18] [ 110/2138] eta: 1:50:26 lr: 2.9132176635212623e-05 loss: 0.0278 (0.0317) time: 3.3162 data: 0.0028 max mem: 19788 +Epoch: [18] [ 120/2138] eta: 1:49:18 lr: 2.9126589157670924e-05 loss: 0.0269 (0.0315) time: 3.0684 data: 0.0026 max mem: 19788 +Epoch: [18] [ 130/2138] eta: 1:48:37 lr: 2.9121001561030057e-05 loss: 0.0268 (0.0315) time: 3.1259 data: 0.0027 max mem: 19788 +Epoch: [18] [ 140/2138] eta: 1:47:58 lr: 2.9115413845262108e-05 loss: 0.0306 (0.0323) time: 3.1980 data: 0.0028 max mem: 19788 +Epoch: [18] [ 150/2138] eta: 1:47:00 lr: 2.910982601033912e-05 loss: 0.0297 (0.0321) time: 3.1213 data: 0.0025 max mem: 19788 +Epoch: [18] [ 160/2138] eta: 1:46:10 lr: 2.910423805623314e-05 loss: 0.0297 (0.0321) time: 3.0651 data: 0.0022 max mem: 19788 +Epoch: [18] [ 170/2138] eta: 1:45:29 lr: 2.90986499829162e-05 loss: 0.0315 (0.0322) time: 3.1174 data: 0.0021 max mem: 19788 +Epoch: [18] [ 180/2138] eta: 1:44:41 lr: 2.9093061790360315e-05 loss: 0.0343 (0.0325) time: 3.1072 data: 0.0024 max mem: 19788 +Epoch: [18] [ 190/2138] eta: 1:44:23 lr: 2.9087473478537503e-05 loss: 0.0299 (0.0323) time: 3.2043 data: 0.0028 max mem: 19788 +Epoch: [18] [ 200/2138] eta: 1:44:50 lr: 2.908188504741975e-05 loss: 0.0276 (0.0325) time: 3.5861 data: 0.0025 max mem: 19788 +Epoch: [18] [ 210/2138] eta: 1:44:31 lr: 2.9076296496979032e-05 loss: 0.0297 (0.0325) time: 3.6115 data: 0.0026 max mem: 19788 +Epoch: [18] [ 220/2138] eta: 1:44:16 lr: 2.907070782718732e-05 loss: 0.0297 (0.0325) time: 3.4263 data: 0.0027 max mem: 19788 +Epoch: [18] [ 230/2138] eta: 1:43:40 lr: 2.906511903801658e-05 loss: 0.0299 (0.0325) time: 3.3415 data: 0.0024 max mem: 19788 +Epoch: [18] [ 240/2138] eta: 1:43:03 lr: 2.905953012943875e-05 loss: 0.0310 (0.0324) time: 3.2116 data: 0.0025 max mem: 19788 +Epoch: [18] [ 250/2138] eta: 1:42:24 lr: 2.9053941101425753e-05 loss: 0.0277 (0.0321) time: 3.1849 data: 0.0026 max mem: 19788 +Epoch: [18] [ 260/2138] eta: 1:41:49 lr: 2.9048351953949516e-05 loss: 0.0266 (0.0321) time: 3.1976 data: 0.0029 max mem: 19788 +Epoch: [18] [ 270/2138] eta: 1:41:53 lr: 2.9042762686981944e-05 loss: 0.0307 (0.0321) time: 3.5033 data: 0.0028 max mem: 19788 +Epoch: [18] [ 280/2138] eta: 1:41:47 lr: 2.903717330049493e-05 loss: 0.0314 (0.0320) time: 3.7309 data: 0.0027 max mem: 19788 +Epoch: [18] [ 290/2138] eta: 1:41:19 lr: 2.903158379446034e-05 loss: 0.0312 (0.0321) time: 3.5242 data: 0.0028 max mem: 19788 +Epoch: [18] [ 300/2138] eta: 1:40:58 lr: 2.902599416885007e-05 loss: 0.0304 (0.0320) time: 3.4199 data: 0.0028 max mem: 19788 +Epoch: [18] [ 310/2138] eta: 1:40:23 lr: 2.902040442363596e-05 loss: 0.0281 (0.0319) time: 3.3654 data: 0.0029 max mem: 19788 +Epoch: [18] [ 320/2138] eta: 1:40:09 lr: 2.9014814558789848e-05 loss: 0.0246 (0.0316) time: 3.4527 data: 0.0029 max mem: 19788 +Epoch: [18] [ 330/2138] eta: 1:40:05 lr: 2.9009224574283567e-05 loss: 0.0265 (0.0317) time: 3.7363 data: 0.0025 max mem: 19788 +Epoch: [18] [ 340/2138] eta: 1:39:29 lr: 2.9003634470088935e-05 loss: 0.0300 (0.0317) time: 3.5467 data: 0.0024 max mem: 19788 +Epoch: [18] [ 350/2138] eta: 1:39:06 lr: 2.8998044246177762e-05 loss: 0.0288 (0.0315) time: 3.3963 data: 0.0024 max mem: 19788 +Epoch: [18] [ 360/2138] eta: 1:38:27 lr: 2.8992453902521834e-05 loss: 0.0275 (0.0316) time: 3.3697 data: 0.0024 max mem: 19788 +Epoch: [18] [ 370/2138] eta: 1:37:51 lr: 2.8986863439092926e-05 loss: 0.0290 (0.0315) time: 3.2323 data: 0.0027 max mem: 19788 +Epoch: [18] [ 380/2138] eta: 1:37:22 lr: 2.898127285586282e-05 loss: 0.0282 (0.0314) time: 3.3332 data: 0.0028 max mem: 19788 +Epoch: [18] [ 390/2138] eta: 1:36:55 lr: 2.897568215280325e-05 loss: 0.0269 (0.0312) time: 3.4452 data: 0.0027 max mem: 19788 +Epoch: [18] [ 400/2138] eta: 1:36:19 lr: 2.8970091329885974e-05 loss: 0.0272 (0.0314) time: 3.3693 data: 0.0027 max mem: 19788 +Epoch: [18] [ 410/2138] eta: 1:35:51 lr: 2.8964500387082704e-05 loss: 0.0264 (0.0313) time: 3.3582 data: 0.0025 max mem: 19788 +Epoch: [18] [ 420/2138] eta: 1:35:17 lr: 2.8958909324365175e-05 loss: 0.0264 (0.0313) time: 3.3814 data: 0.0025 max mem: 19788 +Epoch: [18] [ 430/2138] eta: 1:34:37 lr: 2.8953318141705077e-05 loss: 0.0275 (0.0312) time: 3.2322 data: 0.0027 max mem: 19788 +Epoch: [18] [ 440/2138] eta: 1:33:57 lr: 2.8947726839074095e-05 loss: 0.0275 (0.0312) time: 3.1554 data: 0.0030 max mem: 19788 +Epoch: [18] [ 450/2138] eta: 1:33:18 lr: 2.8942135416443922e-05 loss: 0.0289 (0.0312) time: 3.1573 data: 0.0029 max mem: 19788 +Epoch: [18] [ 460/2138] eta: 1:32:46 lr: 2.8936543873786216e-05 loss: 0.0296 (0.0312) time: 3.2576 data: 0.0028 max mem: 19788 +Epoch: [18] [ 470/2138] eta: 1:32:27 lr: 2.8930952211072625e-05 loss: 0.0296 (0.0311) time: 3.5348 data: 0.0026 max mem: 19788 +Epoch: [18] [ 480/2138] eta: 1:31:53 lr: 2.892536042827479e-05 loss: 0.0309 (0.0313) time: 3.4979 data: 0.0028 max mem: 19788 +Epoch: [18] [ 490/2138] eta: 1:31:14 lr: 2.891976852536433e-05 loss: 0.0305 (0.0312) time: 3.2194 data: 0.0027 max mem: 19788 +Epoch: [18] [ 500/2138] eta: 1:30:45 lr: 2.891417650231288e-05 loss: 0.0274 (0.0312) time: 3.3169 data: 0.0026 max mem: 19788 +Epoch: [18] [ 510/2138] eta: 1:30:20 lr: 2.8908584359092018e-05 loss: 0.0244 (0.0311) time: 3.5221 data: 0.0027 max mem: 19788 +Epoch: [18] [ 520/2138] eta: 1:29:49 lr: 2.8902992095673343e-05 loss: 0.0237 (0.0311) time: 3.4863 data: 0.0023 max mem: 19788 +Epoch: [18] [ 530/2138] eta: 1:29:21 lr: 2.889739971202842e-05 loss: 0.0273 (0.0310) time: 3.4550 data: 0.0023 max mem: 19788 +Epoch: [18] [ 540/2138] eta: 1:28:56 lr: 2.889180720812883e-05 loss: 0.0273 (0.0310) time: 3.5597 data: 0.0026 max mem: 19788 +Epoch: [18] [ 550/2138] eta: 1:28:24 lr: 2.888621458394611e-05 loss: 0.0277 (0.0309) time: 3.5111 data: 0.0028 max mem: 19788 +Epoch: [18] [ 560/2138] eta: 1:27:56 lr: 2.8880621839451792e-05 loss: 0.0283 (0.0310) time: 3.4685 data: 0.0030 max mem: 19788 +Epoch: [18] [ 570/2138] eta: 1:27:37 lr: 2.88750289746174e-05 loss: 0.0285 (0.0310) time: 3.6863 data: 0.0029 max mem: 19788 +Epoch: [18] [ 580/2138] eta: 1:27:18 lr: 2.886943598941446e-05 loss: 0.0284 (0.0310) time: 3.8744 data: 0.0026 max mem: 19788 +Epoch: [18] [ 590/2138] eta: 1:26:51 lr: 2.8863842883814463e-05 loss: 0.0279 (0.0311) time: 3.7544 data: 0.0026 max mem: 19788 +Epoch: [18] [ 600/2138] eta: 1:26:25 lr: 2.885824965778888e-05 loss: 0.0277 (0.0311) time: 3.6397 data: 0.0027 max mem: 19788 +Epoch: [18] [ 610/2138] eta: 1:26:02 lr: 2.88526563113092e-05 loss: 0.0287 (0.0311) time: 3.7314 data: 0.0028 max mem: 19788 +Epoch: [18] [ 620/2138] eta: 1:25:30 lr: 2.8847062844346873e-05 loss: 0.0289 (0.0311) time: 3.6196 data: 0.0028 max mem: 19788 +Epoch: [18] [ 630/2138] eta: 1:25:00 lr: 2.8841469256873343e-05 loss: 0.0300 (0.0311) time: 3.4932 data: 0.0027 max mem: 19788 +Epoch: [18] [ 640/2138] eta: 1:24:25 lr: 2.8835875548860055e-05 loss: 0.0287 (0.0311) time: 3.4378 data: 0.0025 max mem: 19788 +Epoch: [18] [ 650/2138] eta: 1:23:49 lr: 2.883028172027842e-05 loss: 0.0269 (0.0311) time: 3.3121 data: 0.0026 max mem: 19788 +Epoch: [18] [ 660/2138] eta: 1:23:23 lr: 2.8824687771099852e-05 loss: 0.0268 (0.0311) time: 3.5027 data: 0.0027 max mem: 19788 +Epoch: [18] [ 670/2138] eta: 1:22:45 lr: 2.8819093701295735e-05 loss: 0.0257 (0.0310) time: 3.4590 data: 0.0027 max mem: 19788 +Epoch: [18] [ 680/2138] eta: 1:22:11 lr: 2.8813499510837454e-05 loss: 0.0239 (0.0309) time: 3.2890 data: 0.0028 max mem: 19788 +Epoch: [18] [ 690/2138] eta: 1:21:33 lr: 2.880790519969639e-05 loss: 0.0259 (0.0310) time: 3.2905 data: 0.0026 max mem: 19788 +Epoch: [18] [ 700/2138] eta: 1:20:55 lr: 2.880231076784389e-05 loss: 0.0323 (0.0310) time: 3.1859 data: 0.0024 max mem: 19788 +Epoch: [18] [ 710/2138] eta: 1:20:17 lr: 2.8796716215251284e-05 loss: 0.0271 (0.0310) time: 3.1700 data: 0.0023 max mem: 19788 +Epoch: [18] [ 720/2138] eta: 1:19:41 lr: 2.879112154188992e-05 loss: 0.0271 (0.0309) time: 3.2011 data: 0.0026 max mem: 19788 +Epoch: [18] [ 730/2138] eta: 1:19:03 lr: 2.8785526747731106e-05 loss: 0.0278 (0.0309) time: 3.2108 data: 0.0029 max mem: 19788 +Epoch: [18] [ 740/2138] eta: 1:18:32 lr: 2.8779931832746155e-05 loss: 0.0282 (0.0310) time: 3.3420 data: 0.0029 max mem: 19788 +Epoch: [18] [ 750/2138] eta: 1:17:56 lr: 2.8774336796906342e-05 loss: 0.0282 (0.0310) time: 3.3826 data: 0.0029 max mem: 19788 +Epoch: [18] [ 760/2138] eta: 1:17:21 lr: 2.8768741640182955e-05 loss: 0.0291 (0.0310) time: 3.2575 data: 0.0027 max mem: 19788 +Epoch: [18] [ 770/2138] eta: 1:16:45 lr: 2.8763146362547254e-05 loss: 0.0282 (0.0309) time: 3.2694 data: 0.0026 max mem: 19788 +Epoch: [18] [ 780/2138] eta: 1:16:14 lr: 2.8757550963970505e-05 loss: 0.0277 (0.0309) time: 3.3944 data: 0.0027 max mem: 19788 +Epoch: [18] [ 790/2138] eta: 1:15:37 lr: 2.8751955444423915e-05 loss: 0.0279 (0.0309) time: 3.3451 data: 0.0024 max mem: 19788 +Epoch: [18] [ 800/2138] eta: 1:15:05 lr: 2.874635980387874e-05 loss: 0.0285 (0.0309) time: 3.3152 data: 0.0025 max mem: 19788 +Epoch: [18] [ 810/2138] eta: 1:14:31 lr: 2.8740764042306185e-05 loss: 0.0295 (0.0308) time: 3.3924 data: 0.0026 max mem: 19788 +Epoch: [18] [ 820/2138] eta: 1:13:59 lr: 2.8735168159677438e-05 loss: 0.0294 (0.0308) time: 3.3965 data: 0.0026 max mem: 19788 +Epoch: [18] [ 830/2138] eta: 1:13:25 lr: 2.8729572155963692e-05 loss: 0.0255 (0.0308) time: 3.4042 data: 0.0027 max mem: 19788 +Epoch: [18] [ 840/2138] eta: 1:12:52 lr: 2.8723976031136117e-05 loss: 0.0255 (0.0308) time: 3.4012 data: 0.0027 max mem: 19788 +Epoch: [18] [ 850/2138] eta: 1:12:24 lr: 2.8718379785165883e-05 loss: 0.0284 (0.0308) time: 3.5957 data: 0.0027 max mem: 19788 +Epoch: [18] [ 860/2138] eta: 1:11:52 lr: 2.871278341802413e-05 loss: 0.0277 (0.0308) time: 3.6086 data: 0.0025 max mem: 19788 +Epoch: [18] [ 870/2138] eta: 1:11:16 lr: 2.870718692968199e-05 loss: 0.0268 (0.0308) time: 3.3547 data: 0.0025 max mem: 19788 +Epoch: [18] [ 880/2138] eta: 1:10:40 lr: 2.8701590320110582e-05 loss: 0.0291 (0.0307) time: 3.2233 data: 0.0023 max mem: 19788 +Epoch: [18] [ 890/2138] eta: 1:10:06 lr: 2.8695993589281023e-05 loss: 0.0272 (0.0307) time: 3.2600 data: 0.0027 max mem: 19788 +Epoch: [18] [ 900/2138] eta: 1:09:32 lr: 2.8690396737164403e-05 loss: 0.0272 (0.0307) time: 3.3293 data: 0.0031 max mem: 19788 +Epoch: [18] [ 910/2138] eta: 1:08:55 lr: 2.868479976373179e-05 loss: 0.0267 (0.0307) time: 3.2629 data: 0.0027 max mem: 19788 +Epoch: [18] [ 920/2138] eta: 1:08:20 lr: 2.8679202668954276e-05 loss: 0.0254 (0.0306) time: 3.2076 data: 0.0025 max mem: 19788 +Epoch: [18] [ 930/2138] eta: 1:07:43 lr: 2.86736054528029e-05 loss: 0.0287 (0.0306) time: 3.1895 data: 0.0027 max mem: 19788 +Epoch: [18] [ 940/2138] eta: 1:07:08 lr: 2.8668008115248694e-05 loss: 0.0316 (0.0306) time: 3.1843 data: 0.0030 max mem: 19788 +Epoch: [18] [ 950/2138] eta: 1:06:33 lr: 2.8662410656262712e-05 loss: 0.0296 (0.0306) time: 3.2456 data: 0.0030 max mem: 19788 +Epoch: [18] [ 960/2138] eta: 1:06:01 lr: 2.8656813075815953e-05 loss: 0.0300 (0.0306) time: 3.3621 data: 0.0029 max mem: 19788 +Epoch: [18] [ 970/2138] eta: 1:05:25 lr: 2.8651215373879427e-05 loss: 0.0300 (0.0307) time: 3.3443 data: 0.0029 max mem: 19788 +Epoch: [18] [ 980/2138] eta: 1:04:52 lr: 2.864561755042411e-05 loss: 0.0274 (0.0306) time: 3.2874 data: 0.0026 max mem: 19788 +Epoch: [18] [ 990/2138] eta: 1:04:19 lr: 2.8640019605420982e-05 loss: 0.0251 (0.0306) time: 3.3783 data: 0.0023 max mem: 19788 +Epoch: [18] [1000/2138] eta: 1:03:44 lr: 2.8634421538841018e-05 loss: 0.0241 (0.0305) time: 3.3376 data: 0.0024 max mem: 19788 +Epoch: [18] [1010/2138] eta: 1:03:08 lr: 2.8628823350655152e-05 loss: 0.0232 (0.0306) time: 3.2095 data: 0.0026 max mem: 19788 +Epoch: [18] [1020/2138] eta: 1:02:32 lr: 2.862322504083433e-05 loss: 0.0234 (0.0305) time: 3.1608 data: 0.0027 max mem: 19788 +Epoch: [18] [1030/2138] eta: 1:02:00 lr: 2.8617626609349464e-05 loss: 0.0239 (0.0305) time: 3.3387 data: 0.0029 max mem: 19788 +Epoch: [18] [1040/2138] eta: 1:01:26 lr: 2.8612028056171474e-05 loss: 0.0262 (0.0305) time: 3.3770 data: 0.0030 max mem: 19788 +Epoch: [18] [1050/2138] eta: 1:00:54 lr: 2.8606429381271255e-05 loss: 0.0270 (0.0305) time: 3.3863 data: 0.0029 max mem: 19788 +Epoch: [18] [1060/2138] eta: 1:00:24 lr: 2.860083058461968e-05 loss: 0.0283 (0.0305) time: 3.6095 data: 0.0024 max mem: 19788 +Epoch: [18] [1070/2138] eta: 0:59:53 lr: 2.8595231666187627e-05 loss: 0.0304 (0.0305) time: 3.6893 data: 0.0025 max mem: 19788 +Epoch: [18] [1080/2138] eta: 0:59:21 lr: 2.858963262594595e-05 loss: 0.0280 (0.0305) time: 3.5881 data: 0.0028 max mem: 19788 +Epoch: [18] [1090/2138] eta: 0:58:49 lr: 2.8584033463865494e-05 loss: 0.0280 (0.0305) time: 3.5254 data: 0.0029 max mem: 19788 +Epoch: [18] [1100/2138] eta: 0:58:15 lr: 2.857843417991708e-05 loss: 0.0297 (0.0305) time: 3.4333 data: 0.0030 max mem: 19788 +Epoch: [18] [1110/2138] eta: 0:57:41 lr: 2.8572834774071533e-05 loss: 0.0297 (0.0305) time: 3.3479 data: 0.0028 max mem: 19788 +Epoch: [18] [1120/2138] eta: 0:57:07 lr: 2.856723524629965e-05 loss: 0.0310 (0.0305) time: 3.3452 data: 0.0030 max mem: 19788 +Epoch: [18] [1130/2138] eta: 0:56:33 lr: 2.8561635596572234e-05 loss: 0.0284 (0.0305) time: 3.3111 data: 0.0031 max mem: 19788 +Epoch: [18] [1140/2138] eta: 0:56:02 lr: 2.855603582486004e-05 loss: 0.0269 (0.0305) time: 3.4971 data: 0.0029 max mem: 19788 +Epoch: [18] [1150/2138] eta: 0:55:27 lr: 2.8550435931133835e-05 loss: 0.0255 (0.0304) time: 3.4389 data: 0.0030 max mem: 19788 +Epoch: [18] [1160/2138] eta: 0:54:54 lr: 2.8544835915364387e-05 loss: 0.0267 (0.0304) time: 3.3561 data: 0.0029 max mem: 19788 +Epoch: [18] [1170/2138] eta: 0:54:19 lr: 2.8539235777522417e-05 loss: 0.0263 (0.0303) time: 3.3540 data: 0.0026 max mem: 19788 +Epoch: [18] [1180/2138] eta: 0:53:46 lr: 2.8533635517578645e-05 loss: 0.0263 (0.0304) time: 3.3082 data: 0.0027 max mem: 19788 +Epoch: [18] [1190/2138] eta: 0:53:11 lr: 2.852803513550378e-05 loss: 0.0271 (0.0303) time: 3.3033 data: 0.0027 max mem: 19788 +Epoch: [18] [1200/2138] eta: 0:52:36 lr: 2.8522434631268536e-05 loss: 0.0262 (0.0303) time: 3.2124 data: 0.0025 max mem: 19788 +Epoch: [18] [1210/2138] eta: 0:52:01 lr: 2.8516834004843572e-05 loss: 0.0287 (0.0304) time: 3.1947 data: 0.0023 max mem: 19788 +Epoch: [18] [1220/2138] eta: 0:51:27 lr: 2.8511233256199565e-05 loss: 0.0299 (0.0303) time: 3.2249 data: 0.0025 max mem: 19788 +Epoch: [18] [1230/2138] eta: 0:50:53 lr: 2.8505632385307178e-05 loss: 0.0280 (0.0304) time: 3.3519 data: 0.0026 max mem: 19788 +Epoch: [18] [1240/2138] eta: 0:50:19 lr: 2.850003139213705e-05 loss: 0.0265 (0.0303) time: 3.3029 data: 0.0027 max mem: 19788 +Epoch: [18] [1250/2138] eta: 0:49:44 lr: 2.8494430276659793e-05 loss: 0.0265 (0.0303) time: 3.2272 data: 0.0029 max mem: 19788 +Epoch: [18] [1260/2138] eta: 0:49:09 lr: 2.8488829038846042e-05 loss: 0.0281 (0.0303) time: 3.1595 data: 0.0026 max mem: 19788 +Epoch: [18] [1270/2138] eta: 0:48:33 lr: 2.8483227678666398e-05 loss: 0.0282 (0.0303) time: 3.0342 data: 0.0024 max mem: 19788 +Epoch: [18] [1280/2138] eta: 0:47:57 lr: 2.847762619609144e-05 loss: 0.0282 (0.0303) time: 3.0622 data: 0.0027 max mem: 19788 +Epoch: [18] [1290/2138] eta: 0:47:22 lr: 2.847202459109174e-05 loss: 0.0283 (0.0303) time: 3.0614 data: 0.0026 max mem: 19788 +Epoch: [18] [1300/2138] eta: 0:46:46 lr: 2.846642286363786e-05 loss: 0.0299 (0.0304) time: 3.0105 data: 0.0024 max mem: 19788 +Epoch: [18] [1310/2138] eta: 0:46:11 lr: 2.8460821013700363e-05 loss: 0.0310 (0.0304) time: 3.0446 data: 0.0023 max mem: 19788 +Epoch: [18] [1320/2138] eta: 0:45:35 lr: 2.8455219041249763e-05 loss: 0.0314 (0.0304) time: 3.0668 data: 0.0021 max mem: 19788 +Epoch: [18] [1330/2138] eta: 0:45:02 lr: 2.8449616946256592e-05 loss: 0.0314 (0.0304) time: 3.1767 data: 0.0022 max mem: 19788 +Epoch: [18] [1340/2138] eta: 0:44:27 lr: 2.8444014728691354e-05 loss: 0.0327 (0.0305) time: 3.1969 data: 0.0023 max mem: 19788 +Epoch: [18] [1350/2138] eta: 0:43:52 lr: 2.8438412388524545e-05 loss: 0.0348 (0.0306) time: 3.0984 data: 0.0024 max mem: 19788 +Epoch: [18] [1360/2138] eta: 0:43:18 lr: 2.843280992572664e-05 loss: 0.0363 (0.0306) time: 3.1573 data: 0.0024 max mem: 19788 +Epoch: [18] [1370/2138] eta: 0:42:44 lr: 2.8427207340268107e-05 loss: 0.0363 (0.0308) time: 3.2412 data: 0.0023 max mem: 19788 +Epoch: [18] [1380/2138] eta: 0:42:10 lr: 2.842160463211939e-05 loss: 0.0339 (0.0308) time: 3.2702 data: 0.0024 max mem: 19788 +Epoch: [18] [1390/2138] eta: 0:41:36 lr: 2.8416001801250952e-05 loss: 0.0289 (0.0308) time: 3.1960 data: 0.0027 max mem: 19788 +Epoch: [18] [1400/2138] eta: 0:41:01 lr: 2.84103988476332e-05 loss: 0.0272 (0.0308) time: 3.1352 data: 0.0027 max mem: 19788 +Epoch: [18] [1410/2138] eta: 0:40:26 lr: 2.8404795771236542e-05 loss: 0.0283 (0.0308) time: 3.0767 data: 0.0027 max mem: 19788 +Epoch: [18] [1420/2138] eta: 0:39:51 lr: 2.8399192572031384e-05 loss: 0.0289 (0.0308) time: 2.9465 data: 0.0026 max mem: 19788 +Epoch: [18] [1430/2138] eta: 0:39:15 lr: 2.839358924998812e-05 loss: 0.0272 (0.0308) time: 2.8890 data: 0.0026 max mem: 19788 +Epoch: [18] [1440/2138] eta: 0:38:40 lr: 2.83879858050771e-05 loss: 0.0302 (0.0308) time: 2.8987 data: 0.0024 max mem: 19788 +Epoch: [18] [1450/2138] eta: 0:38:05 lr: 2.8382382237268696e-05 loss: 0.0303 (0.0308) time: 2.8957 data: 0.0022 max mem: 19788 +Epoch: [18] [1460/2138] eta: 0:37:29 lr: 2.8376778546533246e-05 loss: 0.0269 (0.0308) time: 2.8999 data: 0.0023 max mem: 19788 +Epoch: [18] [1470/2138] eta: 0:36:54 lr: 2.8371174732841084e-05 loss: 0.0269 (0.0308) time: 2.9144 data: 0.0022 max mem: 19788 +Epoch: [18] [1480/2138] eta: 0:36:20 lr: 2.8365570796162523e-05 loss: 0.0307 (0.0308) time: 2.9334 data: 0.0024 max mem: 19788 +Epoch: [18] [1490/2138] eta: 0:35:45 lr: 2.8359966736467863e-05 loss: 0.0310 (0.0308) time: 3.0039 data: 0.0027 max mem: 19788 +Epoch: [18] [1500/2138] eta: 0:35:11 lr: 2.83543625537274e-05 loss: 0.0285 (0.0309) time: 2.9780 data: 0.0027 max mem: 19788 +Epoch: [18] [1510/2138] eta: 0:34:36 lr: 2.8348758247911406e-05 loss: 0.0285 (0.0309) time: 2.9036 data: 0.0025 max mem: 19788 +Epoch: [18] [1520/2138] eta: 0:34:01 lr: 2.834315381899014e-05 loss: 0.0300 (0.0309) time: 2.9090 data: 0.0026 max mem: 19788 +Epoch: [18] [1530/2138] eta: 0:33:26 lr: 2.833754926693385e-05 loss: 0.0292 (0.0309) time: 2.8958 data: 0.0023 max mem: 19788 +Epoch: [18] [1540/2138] eta: 0:32:52 lr: 2.8331944591712778e-05 loss: 0.0269 (0.0309) time: 2.8954 data: 0.0022 max mem: 19788 +Epoch: [18] [1550/2138] eta: 0:32:17 lr: 2.8326339793297137e-05 loss: 0.0269 (0.0308) time: 2.9068 data: 0.0021 max mem: 19788 +Epoch: [18] [1560/2138] eta: 0:31:43 lr: 2.8320734871657128e-05 loss: 0.0284 (0.0308) time: 2.9275 data: 0.0020 max mem: 19788 +Epoch: [18] [1570/2138] eta: 0:31:09 lr: 2.8315129826762953e-05 loss: 0.0284 (0.0308) time: 2.9915 data: 0.0021 max mem: 19788 +Epoch: [18] [1580/2138] eta: 0:30:35 lr: 2.830952465858479e-05 loss: 0.0285 (0.0308) time: 2.9654 data: 0.0022 max mem: 19788 +Epoch: [18] [1590/2138] eta: 0:30:01 lr: 2.8303919367092808e-05 loss: 0.0285 (0.0308) time: 2.8981 data: 0.0024 max mem: 19788 +Epoch: [18] [1600/2138] eta: 0:29:27 lr: 2.8298313952257145e-05 loss: 0.0324 (0.0308) time: 2.8958 data: 0.0026 max mem: 19788 +Epoch: [18] [1610/2138] eta: 0:28:52 lr: 2.8292708414047946e-05 loss: 0.0324 (0.0308) time: 2.8921 data: 0.0027 max mem: 19788 +Epoch: [18] [1620/2138] eta: 0:28:18 lr: 2.828710275243534e-05 loss: 0.0290 (0.0308) time: 2.8919 data: 0.0029 max mem: 19788 +Epoch: [18] [1630/2138] eta: 0:27:44 lr: 2.8281496967389437e-05 loss: 0.0263 (0.0308) time: 2.9065 data: 0.0027 max mem: 19788 +Epoch: [18] [1640/2138] eta: 0:27:11 lr: 2.8275891058880323e-05 loss: 0.0275 (0.0308) time: 2.9462 data: 0.0027 max mem: 19788 +Epoch: [18] [1650/2138] eta: 0:26:37 lr: 2.8270285026878085e-05 loss: 0.0284 (0.0308) time: 2.9938 data: 0.0030 max mem: 19788 +Epoch: [18] [1660/2138] eta: 0:26:03 lr: 2.8264678871352795e-05 loss: 0.0307 (0.0308) time: 2.9508 data: 0.0029 max mem: 19788 +Epoch: [18] [1670/2138] eta: 0:25:30 lr: 2.825907259227451e-05 loss: 0.0284 (0.0308) time: 2.8867 data: 0.0025 max mem: 19788 +Epoch: [18] [1680/2138] eta: 0:24:56 lr: 2.825346618961326e-05 loss: 0.0282 (0.0308) time: 2.8875 data: 0.0024 max mem: 19788 +Epoch: [18] [1690/2138] eta: 0:24:22 lr: 2.8247859663339076e-05 loss: 0.0283 (0.0308) time: 2.8900 data: 0.0025 max mem: 19788 +Epoch: [18] [1700/2138] eta: 0:23:49 lr: 2.8242253013421983e-05 loss: 0.0272 (0.0308) time: 2.8979 data: 0.0022 max mem: 19788 +Epoch: [18] [1710/2138] eta: 0:23:15 lr: 2.8236646239831964e-05 loss: 0.0274 (0.0308) time: 2.9019 data: 0.0026 max mem: 19788 +Epoch: [18] [1720/2138] eta: 0:22:42 lr: 2.823103934253901e-05 loss: 0.0307 (0.0308) time: 2.9354 data: 0.0028 max mem: 19788 +Epoch: [18] [1730/2138] eta: 0:22:08 lr: 2.8225432321513097e-05 loss: 0.0322 (0.0308) time: 2.9500 data: 0.0025 max mem: 19788 +Epoch: [18] [1740/2138] eta: 0:21:35 lr: 2.821982517672418e-05 loss: 0.0289 (0.0308) time: 2.9059 data: 0.0024 max mem: 19788 +Epoch: [18] [1750/2138] eta: 0:21:02 lr: 2.8214217908142205e-05 loss: 0.0285 (0.0308) time: 2.8829 data: 0.0025 max mem: 19788 +Epoch: [18] [1760/2138] eta: 0:20:28 lr: 2.8208610515737084e-05 loss: 0.0281 (0.0308) time: 2.8824 data: 0.0026 max mem: 19788 +Epoch: [18] [1770/2138] eta: 0:19:55 lr: 2.8203002999478752e-05 loss: 0.0251 (0.0307) time: 2.8842 data: 0.0027 max mem: 19788 +Epoch: [18] [1780/2138] eta: 0:19:22 lr: 2.8197395359337107e-05 loss: 0.0221 (0.0307) time: 2.8920 data: 0.0026 max mem: 19788 +Epoch: [18] [1790/2138] eta: 0:18:49 lr: 2.8191787595282044e-05 loss: 0.0252 (0.0307) time: 2.9145 data: 0.0026 max mem: 19788 +Epoch: [18] [1800/2138] eta: 0:18:16 lr: 2.818617970728341e-05 loss: 0.0288 (0.0307) time: 3.0259 data: 0.0025 max mem: 19788 +Epoch: [18] [1810/2138] eta: 0:17:43 lr: 2.818057169531109e-05 loss: 0.0342 (0.0307) time: 3.1348 data: 0.0021 max mem: 19788 +Epoch: [18] [1820/2138] eta: 0:17:10 lr: 2.8174963559334926e-05 loss: 0.0290 (0.0307) time: 3.0165 data: 0.0021 max mem: 19788 +Epoch: [18] [1830/2138] eta: 0:16:37 lr: 2.8169355299324745e-05 loss: 0.0248 (0.0307) time: 2.8896 data: 0.0024 max mem: 19788 +Epoch: [18] [1840/2138] eta: 0:16:04 lr: 2.816374691525036e-05 loss: 0.0257 (0.0307) time: 2.8933 data: 0.0028 max mem: 19788 +Epoch: [18] [1850/2138] eta: 0:15:31 lr: 2.8158138407081586e-05 loss: 0.0261 (0.0307) time: 2.9000 data: 0.0027 max mem: 19788 +Epoch: [18] [1860/2138] eta: 0:14:59 lr: 2.815252977478821e-05 loss: 0.0294 (0.0307) time: 2.9043 data: 0.0024 max mem: 19788 +Epoch: [18] [1870/2138] eta: 0:14:26 lr: 2.8146921018339995e-05 loss: 0.0294 (0.0307) time: 2.9077 data: 0.0022 max mem: 19788 +Epoch: [18] [1880/2138] eta: 0:13:53 lr: 2.8141312137706717e-05 loss: 0.0236 (0.0306) time: 2.9611 data: 0.0023 max mem: 19788 +Epoch: [18] [1890/2138] eta: 0:13:21 lr: 2.8135703132858114e-05 loss: 0.0235 (0.0306) time: 2.9957 data: 0.0022 max mem: 19788 +Epoch: [18] [1900/2138] eta: 0:12:48 lr: 2.8130094003763934e-05 loss: 0.0263 (0.0306) time: 2.9507 data: 0.0023 max mem: 19788 +Epoch: [18] [1910/2138] eta: 0:12:15 lr: 2.8124484750393882e-05 loss: 0.0256 (0.0306) time: 2.9026 data: 0.0024 max mem: 19788 +Epoch: [18] [1920/2138] eta: 0:11:43 lr: 2.8118875372717662e-05 loss: 0.0266 (0.0306) time: 2.8874 data: 0.0024 max mem: 19788 +Epoch: [18] [1930/2138] eta: 0:11:10 lr: 2.8113265870704975e-05 loss: 0.0297 (0.0306) time: 2.8969 data: 0.0025 max mem: 19788 +Epoch: [18] [1940/2138] eta: 0:10:37 lr: 2.8107656244325496e-05 loss: 0.0287 (0.0306) time: 2.8952 data: 0.0025 max mem: 19788 +Epoch: [18] [1950/2138] eta: 0:10:05 lr: 2.8102046493548882e-05 loss: 0.0287 (0.0306) time: 2.9201 data: 0.0024 max mem: 19788 +Epoch: [18] [1960/2138] eta: 0:09:32 lr: 2.809643661834479e-05 loss: 0.0271 (0.0305) time: 2.9819 data: 0.0025 max mem: 19788 +Epoch: [18] [1970/2138] eta: 0:09:00 lr: 2.8090826618682846e-05 loss: 0.0251 (0.0305) time: 2.9804 data: 0.0025 max mem: 19788 +Epoch: [18] [1980/2138] eta: 0:08:28 lr: 2.8085216494532685e-05 loss: 0.0276 (0.0305) time: 2.9273 data: 0.0024 max mem: 19788 +Epoch: [18] [1990/2138] eta: 0:07:55 lr: 2.8079606245863894e-05 loss: 0.0278 (0.0306) time: 2.8973 data: 0.0024 max mem: 19788 +Epoch: [18] [2000/2138] eta: 0:07:23 lr: 2.807399587264607e-05 loss: 0.0251 (0.0305) time: 2.8894 data: 0.0026 max mem: 19788 +Epoch: [18] [2010/2138] eta: 0:06:51 lr: 2.8068385374848806e-05 loss: 0.0270 (0.0306) time: 2.8962 data: 0.0025 max mem: 19788 +Epoch: [18] [2020/2138] eta: 0:06:18 lr: 2.806277475244165e-05 loss: 0.0281 (0.0306) time: 2.8938 data: 0.0022 max mem: 19788 +Epoch: [18] [2030/2138] eta: 0:05:46 lr: 2.8057164005394154e-05 loss: 0.0278 (0.0305) time: 2.8940 data: 0.0022 max mem: 19788 +Epoch: [18] [2040/2138] eta: 0:05:14 lr: 2.8051553133675855e-05 loss: 0.0294 (0.0305) time: 2.9613 data: 0.0027 max mem: 19788 +Epoch: [18] [2050/2138] eta: 0:04:42 lr: 2.804594213725629e-05 loss: 0.0284 (0.0305) time: 2.9930 data: 0.0029 max mem: 19788 +Epoch: [18] [2060/2138] eta: 0:04:09 lr: 2.8040331016104944e-05 loss: 0.0283 (0.0306) time: 2.9742 data: 0.0025 max mem: 19788 +Epoch: [18] [2070/2138] eta: 0:03:37 lr: 2.8034719770191307e-05 loss: 0.0286 (0.0305) time: 2.9713 data: 0.0023 max mem: 19788 +Epoch: [18] [2080/2138] eta: 0:03:05 lr: 2.8029108399484876e-05 loss: 0.0267 (0.0305) time: 2.9394 data: 0.0021 max mem: 19788 +Epoch: [18] [2090/2138] eta: 0:02:33 lr: 2.802349690395511e-05 loss: 0.0276 (0.0306) time: 2.9030 data: 0.0023 max mem: 19788 +Epoch: [18] [2100/2138] eta: 0:02:01 lr: 2.8017885283571456e-05 loss: 0.0290 (0.0306) time: 2.8958 data: 0.0024 max mem: 19788 +Epoch: [18] [2110/2138] eta: 0:01:29 lr: 2.8012273538303342e-05 loss: 0.0318 (0.0306) time: 2.9091 data: 0.0023 max mem: 19788 +Epoch: [18] [2120/2138] eta: 0:00:57 lr: 2.80066616681202e-05 loss: 0.0318 (0.0306) time: 2.9020 data: 0.0024 max mem: 19788 +Epoch: [18] [2130/2138] eta: 0:00:25 lr: 2.800104967299143e-05 loss: 0.0297 (0.0306) time: 2.8848 data: 0.0024 max mem: 19788 +Epoch: [18] Total time: 1:53:51 +Test: [ 0/21770] eta: 16:15:41 time: 2.6891 data: 2.5424 max mem: 19788 +Test: [ 100/21770] eta: 0:25:25 time: 0.0437 data: 0.0017 max mem: 19788 +Test: [ 200/21770] eta: 0:20:33 time: 0.0445 data: 0.0016 max mem: 19788 +Test: [ 300/21770] eta: 0:19:21 time: 0.0523 data: 0.0017 max mem: 19788 +Test: [ 400/21770] eta: 0:18:53 time: 0.0436 data: 0.0014 max mem: 19788 +Test: [ 500/21770] eta: 0:18:14 time: 0.0436 data: 0.0014 max mem: 19788 +Test: [ 600/21770] eta: 0:17:52 time: 0.0459 data: 0.0017 max mem: 19788 +Test: [ 700/21770] eta: 0:17:51 time: 0.0484 data: 0.0017 max mem: 19788 +Test: [ 800/21770] eta: 0:17:29 time: 0.0440 data: 0.0014 max mem: 19788 +Test: [ 900/21770] eta: 0:17:17 time: 0.0434 data: 0.0015 max mem: 19788 +Test: [ 1000/21770] eta: 0:17:12 time: 0.0447 data: 0.0016 max mem: 19788 +Test: [ 1100/21770] eta: 0:17:00 time: 0.0483 data: 0.0017 max mem: 19788 +Test: [ 1200/21770] eta: 0:16:49 time: 0.0437 data: 0.0015 max mem: 19788 +Test: [ 1300/21770] eta: 0:16:39 time: 0.0527 data: 0.0018 max mem: 19788 +Test: [ 1400/21770] eta: 0:16:30 time: 0.0433 data: 0.0013 max mem: 19788 +Test: [ 1500/21770] eta: 0:16:22 time: 0.0489 data: 0.0018 max mem: 19788 +Test: [ 1600/21770] eta: 0:16:12 time: 0.0452 data: 0.0016 max mem: 19788 +Test: [ 1700/21770] eta: 0:16:01 time: 0.0428 data: 0.0016 max mem: 19788 +Test: [ 1800/21770] eta: 0:15:54 time: 0.0443 data: 0.0014 max mem: 19788 +Test: [ 1900/21770] eta: 0:15:44 time: 0.0425 data: 0.0014 max mem: 19788 +Test: [ 2000/21770] eta: 0:15:36 time: 0.0473 data: 0.0018 max mem: 19788 +Test: [ 2100/21770] eta: 0:15:30 time: 0.0421 data: 0.0015 max mem: 19788 +Test: [ 2200/21770] eta: 0:15:21 time: 0.0424 data: 0.0014 max mem: 19788 +Test: [ 2300/21770] eta: 0:15:14 time: 0.0475 data: 0.0015 max mem: 19788 +Test: [ 2400/21770] eta: 0:15:07 time: 0.0452 data: 0.0014 max mem: 19788 +Test: [ 2500/21770] eta: 0:15:02 time: 0.0455 data: 0.0015 max mem: 19788 +Test: [ 2600/21770] eta: 0:14:55 time: 0.0435 data: 0.0015 max mem: 19788 +Test: [ 2700/21770] eta: 0:14:49 time: 0.0458 data: 0.0015 max mem: 19788 +Test: [ 2800/21770] eta: 0:14:42 time: 0.0437 data: 0.0014 max mem: 19788 +Test: [ 2900/21770] eta: 0:14:36 time: 0.0467 data: 0.0015 max mem: 19788 +Test: [ 3000/21770] eta: 0:14:31 time: 0.0438 data: 0.0015 max mem: 19788 +Test: [ 3100/21770] eta: 0:14:26 time: 0.0419 data: 0.0014 max mem: 19788 +Test: [ 3200/21770] eta: 0:14:20 time: 0.0435 data: 0.0015 max mem: 19788 +Test: [ 3300/21770] eta: 0:14:14 time: 0.0442 data: 0.0015 max mem: 19788 +Test: [ 3400/21770] eta: 0:14:09 time: 0.0534 data: 0.0016 max mem: 19788 +Test: [ 3500/21770] eta: 0:14:05 time: 0.0474 data: 0.0017 max mem: 19788 +Test: [ 3600/21770] eta: 0:14:01 time: 0.0482 data: 0.0016 max mem: 19788 +Test: [ 3700/21770] eta: 0:13:56 time: 0.0437 data: 0.0014 max mem: 19788 +Test: [ 3800/21770] eta: 0:13:51 time: 0.0447 data: 0.0015 max mem: 19788 +Test: [ 3900/21770] eta: 0:13:47 time: 0.0494 data: 0.0017 max mem: 19788 +Test: [ 4000/21770] eta: 0:13:44 time: 0.0473 data: 0.0016 max mem: 19788 +Test: [ 4100/21770] eta: 0:13:40 time: 0.0448 data: 0.0014 max mem: 19788 +Test: [ 4200/21770] eta: 0:13:35 time: 0.0442 data: 0.0015 max mem: 19788 +Test: [ 4300/21770] eta: 0:13:30 time: 0.0461 data: 0.0014 max mem: 19788 +Test: [ 4400/21770] eta: 0:13:25 time: 0.0443 data: 0.0015 max mem: 19788 +Test: [ 4500/21770] eta: 0:13:20 time: 0.0488 data: 0.0016 max mem: 19788 +Test: [ 4600/21770] eta: 0:13:15 time: 0.0466 data: 0.0017 max mem: 19788 +Test: [ 4700/21770] eta: 0:13:10 time: 0.0454 data: 0.0016 max mem: 19788 +Test: [ 4800/21770] eta: 0:13:06 time: 0.0436 data: 0.0014 max mem: 19788 +Test: [ 4900/21770] eta: 0:13:00 time: 0.0437 data: 0.0014 max mem: 19788 +Test: [ 5000/21770] eta: 0:12:56 time: 0.0532 data: 0.0017 max mem: 19788 +Test: [ 5100/21770] eta: 0:12:52 time: 0.0526 data: 0.0016 max mem: 19788 +Test: [ 5200/21770] eta: 0:12:47 time: 0.0442 data: 0.0013 max mem: 19788 +Test: [ 5300/21770] eta: 0:12:42 time: 0.0447 data: 0.0018 max mem: 19788 +Test: [ 5400/21770] eta: 0:12:37 time: 0.0437 data: 0.0015 max mem: 19788 +Test: [ 5500/21770] eta: 0:12:32 time: 0.0441 data: 0.0014 max mem: 19788 +Test: [ 5600/21770] eta: 0:12:27 time: 0.0474 data: 0.0017 max mem: 19788 +Test: [ 5700/21770] eta: 0:12:22 time: 0.0440 data: 0.0016 max mem: 19788 +Test: [ 5800/21770] eta: 0:12:18 time: 0.0477 data: 0.0015 max mem: 19788 +Test: [ 5900/21770] eta: 0:12:14 time: 0.0504 data: 0.0016 max mem: 19788 +Test: [ 6000/21770] eta: 0:12:09 time: 0.0495 data: 0.0015 max mem: 19788 +Test: [ 6100/21770] eta: 0:12:06 time: 0.0532 data: 0.0019 max mem: 19788 +Test: [ 6200/21770] eta: 0:12:02 time: 0.0520 data: 0.0018 max mem: 19788 +Test: [ 6300/21770] eta: 0:11:58 time: 0.0533 data: 0.0019 max mem: 19788 +Test: [ 6400/21770] eta: 0:11:55 time: 0.0467 data: 0.0015 max mem: 19788 +Test: [ 6500/21770] eta: 0:11:50 time: 0.0430 data: 0.0015 max mem: 19788 +Test: [ 6600/21770] eta: 0:11:45 time: 0.0492 data: 0.0018 max mem: 19788 +Test: [ 6700/21770] eta: 0:11:41 time: 0.0470 data: 0.0016 max mem: 19788 +Test: [ 6800/21770] eta: 0:11:37 time: 0.0458 data: 0.0015 max mem: 19788 +Test: [ 6900/21770] eta: 0:11:33 time: 0.0437 data: 0.0014 max mem: 19788 +Test: [ 7000/21770] eta: 0:11:29 time: 0.0524 data: 0.0015 max mem: 19788 +Test: [ 7100/21770] eta: 0:11:25 time: 0.0480 data: 0.0015 max mem: 19788 +Test: [ 7200/21770] eta: 0:11:21 time: 0.0514 data: 0.0017 max mem: 19788 +Test: [ 7300/21770] eta: 0:11:16 time: 0.0465 data: 0.0016 max mem: 19788 +Test: [ 7400/21770] eta: 0:11:11 time: 0.0435 data: 0.0015 max mem: 19788 +Test: [ 7500/21770] eta: 0:11:07 time: 0.0458 data: 0.0014 max mem: 19788 +Test: [ 7600/21770] eta: 0:11:02 time: 0.0485 data: 0.0017 max mem: 19788 +Test: [ 7700/21770] eta: 0:10:57 time: 0.0442 data: 0.0015 max mem: 19788 +Test: [ 7800/21770] eta: 0:10:52 time: 0.0472 data: 0.0016 max mem: 19788 +Test: [ 7900/21770] eta: 0:10:48 time: 0.0521 data: 0.0018 max mem: 19788 +Test: [ 8000/21770] eta: 0:10:43 time: 0.0446 data: 0.0015 max mem: 19788 +Test: [ 8100/21770] eta: 0:10:39 time: 0.0462 data: 0.0017 max mem: 19788 +Test: [ 8200/21770] eta: 0:10:34 time: 0.0499 data: 0.0017 max mem: 19788 +Test: [ 8300/21770] eta: 0:10:30 time: 0.0438 data: 0.0014 max mem: 19788 +Test: [ 8400/21770] eta: 0:10:25 time: 0.0469 data: 0.0016 max mem: 19788 +Test: [ 8500/21770] eta: 0:10:21 time: 0.0553 data: 0.0018 max mem: 19788 +Test: [ 8600/21770] eta: 0:10:17 time: 0.0458 data: 0.0016 max mem: 19788 +Test: [ 8700/21770] eta: 0:10:12 time: 0.0507 data: 0.0017 max mem: 19788 +Test: [ 8800/21770] eta: 0:10:07 time: 0.0441 data: 0.0015 max mem: 19788 +Test: [ 8900/21770] eta: 0:10:02 time: 0.0473 data: 0.0017 max mem: 19788 +Test: [ 9000/21770] eta: 0:09:58 time: 0.0547 data: 0.0016 max mem: 19788 +Test: [ 9100/21770] eta: 0:09:54 time: 0.0436 data: 0.0013 max mem: 19788 +Test: [ 9200/21770] eta: 0:09:50 time: 0.0488 data: 0.0015 max mem: 19788 +Test: [ 9300/21770] eta: 0:09:45 time: 0.0500 data: 0.0016 max mem: 19788 +Test: [ 9400/21770] eta: 0:09:41 time: 0.0524 data: 0.0018 max mem: 19788 +Test: [ 9500/21770] eta: 0:09:36 time: 0.0433 data: 0.0014 max mem: 19788 +Test: [ 9600/21770] eta: 0:09:31 time: 0.0498 data: 0.0015 max mem: 19788 +Test: [ 9700/21770] eta: 0:09:27 time: 0.0449 data: 0.0014 max mem: 19788 +Test: [ 9800/21770] eta: 0:09:22 time: 0.0486 data: 0.0016 max mem: 19788 +Test: [ 9900/21770] eta: 0:09:18 time: 0.0434 data: 0.0016 max mem: 19788 +Test: [10000/21770] eta: 0:09:13 time: 0.0452 data: 0.0014 max mem: 19788 +Test: [10100/21770] eta: 0:09:08 time: 0.0460 data: 0.0016 max mem: 19788 +Test: [10200/21770] eta: 0:09:04 time: 0.0495 data: 0.0016 max mem: 19788 +Test: [10300/21770] eta: 0:08:59 time: 0.0482 data: 0.0016 max mem: 19788 +Test: [10400/21770] eta: 0:08:54 time: 0.0442 data: 0.0014 max mem: 19788 +Test: [10500/21770] eta: 0:08:49 time: 0.0441 data: 0.0016 max mem: 19788 +Test: [10600/21770] eta: 0:08:45 time: 0.0533 data: 0.0018 max mem: 19788 +Test: [10700/21770] eta: 0:08:40 time: 0.0539 data: 0.0016 max mem: 19788 +Test: [10800/21770] eta: 0:08:36 time: 0.0443 data: 0.0013 max mem: 19788 +Test: [10900/21770] eta: 0:08:31 time: 0.0520 data: 0.0017 max mem: 19788 +Test: [11000/21770] eta: 0:08:27 time: 0.0439 data: 0.0014 max mem: 19788 +Test: [11100/21770] eta: 0:08:22 time: 0.0496 data: 0.0015 max mem: 19788 +Test: [11200/21770] eta: 0:08:18 time: 0.0528 data: 0.0019 max mem: 19788 +Test: [11300/21770] eta: 0:08:13 time: 0.0462 data: 0.0016 max mem: 19788 +Test: [11400/21770] eta: 0:08:08 time: 0.0468 data: 0.0015 max mem: 19788 +Test: [11500/21770] eta: 0:08:04 time: 0.0535 data: 0.0019 max mem: 19788 +Test: [11600/21770] eta: 0:07:59 time: 0.0467 data: 0.0016 max mem: 19788 +Test: [11700/21770] eta: 0:07:55 time: 0.0489 data: 0.0015 max mem: 19788 +Test: [11800/21770] eta: 0:07:50 time: 0.0453 data: 0.0016 max mem: 19788 +Test: [11900/21770] eta: 0:07:46 time: 0.0504 data: 0.0016 max mem: 19788 +Test: [12000/21770] eta: 0:07:41 time: 0.0445 data: 0.0016 max mem: 19788 +Test: [12100/21770] eta: 0:07:36 time: 0.0446 data: 0.0016 max mem: 19788 +Test: [12200/21770] eta: 0:07:31 time: 0.0452 data: 0.0013 max mem: 19788 +Test: [12300/21770] eta: 0:07:26 time: 0.0452 data: 0.0015 max mem: 19788 +Test: [12400/21770] eta: 0:07:22 time: 0.0495 data: 0.0016 max mem: 19788 +Test: [12500/21770] eta: 0:07:17 time: 0.0441 data: 0.0015 max mem: 19788 +Test: [12600/21770] eta: 0:07:12 time: 0.0528 data: 0.0017 max mem: 19788 +Test: [12700/21770] eta: 0:07:08 time: 0.0520 data: 0.0018 max mem: 19788 +Test: [12800/21770] eta: 0:07:03 time: 0.0432 data: 0.0015 max mem: 19788 +Test: [12900/21770] eta: 0:06:58 time: 0.0522 data: 0.0017 max mem: 19788 +Test: [13000/21770] eta: 0:06:54 time: 0.0451 data: 0.0015 max mem: 19788 +Test: [13100/21770] eta: 0:06:49 time: 0.0439 data: 0.0016 max mem: 19788 +Test: [13200/21770] eta: 0:06:44 time: 0.0437 data: 0.0014 max mem: 19788 +Test: [13300/21770] eta: 0:06:39 time: 0.0459 data: 0.0017 max mem: 19788 +Test: [13400/21770] eta: 0:06:34 time: 0.0443 data: 0.0014 max mem: 19788 +Test: [13500/21770] eta: 0:06:30 time: 0.0483 data: 0.0015 max mem: 19788 +Test: [13600/21770] eta: 0:06:25 time: 0.0451 data: 0.0016 max mem: 19788 +Test: [13700/21770] eta: 0:06:20 time: 0.0521 data: 0.0017 max mem: 19788 +Test: [13800/21770] eta: 0:06:16 time: 0.0424 data: 0.0015 max mem: 19788 +Test: [13900/21770] eta: 0:06:11 time: 0.0457 data: 0.0016 max mem: 19788 +Test: [14000/21770] eta: 0:06:06 time: 0.0484 data: 0.0015 max mem: 19788 +Test: [14100/21770] eta: 0:06:02 time: 0.0457 data: 0.0015 max mem: 19788 +Test: [14200/21770] eta: 0:05:57 time: 0.0516 data: 0.0017 max mem: 19788 +Test: [14300/21770] eta: 0:05:52 time: 0.0521 data: 0.0019 max mem: 19788 +Test: [14400/21770] eta: 0:05:48 time: 0.0489 data: 0.0016 max mem: 19788 +Test: [14500/21770] eta: 0:05:43 time: 0.0445 data: 0.0016 max mem: 19788 +Test: [14600/21770] eta: 0:05:38 time: 0.0485 data: 0.0015 max mem: 19788 +Test: [14700/21770] eta: 0:05:33 time: 0.0527 data: 0.0019 max mem: 19788 +Test: [14800/21770] eta: 0:05:29 time: 0.0438 data: 0.0015 max mem: 19788 +Test: [14900/21770] eta: 0:05:24 time: 0.0489 data: 0.0017 max mem: 19788 +Test: [15000/21770] eta: 0:05:20 time: 0.0505 data: 0.0017 max mem: 19788 +Test: [15100/21770] eta: 0:05:15 time: 0.0450 data: 0.0015 max mem: 19788 +Test: [15200/21770] eta: 0:05:10 time: 0.0447 data: 0.0014 max mem: 19788 +Test: [15300/21770] eta: 0:05:05 time: 0.0505 data: 0.0016 max mem: 19788 +Test: [15400/21770] eta: 0:05:01 time: 0.0438 data: 0.0013 max mem: 19788 +Test: [15500/21770] eta: 0:04:56 time: 0.0454 data: 0.0016 max mem: 19788 +Test: [15600/21770] eta: 0:04:51 time: 0.0456 data: 0.0014 max mem: 19788 +Test: [15700/21770] eta: 0:04:46 time: 0.0497 data: 0.0016 max mem: 19788 +Test: [15800/21770] eta: 0:04:42 time: 0.0527 data: 0.0019 max mem: 19788 +Test: [15900/21770] eta: 0:04:37 time: 0.0465 data: 0.0017 max mem: 19788 +Test: [16000/21770] eta: 0:04:32 time: 0.0524 data: 0.0017 max mem: 19788 +Test: [16100/21770] eta: 0:04:28 time: 0.0468 data: 0.0016 max mem: 19788 +Test: [16200/21770] eta: 0:04:23 time: 0.0528 data: 0.0019 max mem: 19788 +Test: [16300/21770] eta: 0:04:19 time: 0.0439 data: 0.0017 max mem: 19788 +Test: [16400/21770] eta: 0:04:14 time: 0.0453 data: 0.0015 max mem: 19788 +Test: [16500/21770] eta: 0:04:09 time: 0.0439 data: 0.0014 max mem: 19788 +Test: [16600/21770] eta: 0:04:04 time: 0.0528 data: 0.0018 max mem: 19788 +Test: [16700/21770] eta: 0:04:00 time: 0.0462 data: 0.0019 max mem: 19788 +Test: [16800/21770] eta: 0:03:55 time: 0.0450 data: 0.0015 max mem: 19788 +Test: [16900/21770] eta: 0:03:50 time: 0.0439 data: 0.0013 max mem: 19788 +Test: [17000/21770] eta: 0:03:45 time: 0.0447 data: 0.0016 max mem: 19788 +Test: [17100/21770] eta: 0:03:40 time: 0.0429 data: 0.0013 max mem: 19788 +Test: [17200/21770] eta: 0:03:36 time: 0.0436 data: 0.0014 max mem: 19788 +Test: [17300/21770] eta: 0:03:31 time: 0.0434 data: 0.0016 max mem: 19788 +Test: [17400/21770] eta: 0:03:26 time: 0.0490 data: 0.0017 max mem: 19788 +Test: [17500/21770] eta: 0:03:21 time: 0.0471 data: 0.0015 max mem: 19788 +Test: [17600/21770] eta: 0:03:17 time: 0.0436 data: 0.0015 max mem: 19788 +Test: [17700/21770] eta: 0:03:12 time: 0.0433 data: 0.0016 max mem: 19788 +Test: [17800/21770] eta: 0:03:07 time: 0.0441 data: 0.0017 max mem: 19788 +Test: [17900/21770] eta: 0:03:02 time: 0.0469 data: 0.0016 max mem: 19788 +Test: [18000/21770] eta: 0:02:58 time: 0.0434 data: 0.0015 max mem: 19788 +Test: [18100/21770] eta: 0:02:53 time: 0.0437 data: 0.0015 max mem: 19788 +Test: [18200/21770] eta: 0:02:48 time: 0.0457 data: 0.0016 max mem: 19788 +Test: [18300/21770] eta: 0:02:43 time: 0.0441 data: 0.0016 max mem: 19788 +Test: [18400/21770] eta: 0:02:39 time: 0.0531 data: 0.0019 max mem: 19788 +Test: [18500/21770] eta: 0:02:34 time: 0.0452 data: 0.0015 max mem: 19788 +Test: [18600/21770] eta: 0:02:29 time: 0.0458 data: 0.0018 max mem: 19788 +Test: [18700/21770] eta: 0:02:25 time: 0.0446 data: 0.0013 max mem: 19788 +Test: [18800/21770] eta: 0:02:20 time: 0.0443 data: 0.0016 max mem: 19788 +Test: [18900/21770] eta: 0:02:15 time: 0.0451 data: 0.0015 max mem: 19788 +Test: [19000/21770] eta: 0:02:10 time: 0.0437 data: 0.0014 max mem: 19788 +Test: [19100/21770] eta: 0:02:05 time: 0.0431 data: 0.0015 max mem: 19788 +Test: [19200/21770] eta: 0:02:01 time: 0.0440 data: 0.0015 max mem: 19788 +Test: [19300/21770] eta: 0:01:56 time: 0.0476 data: 0.0015 max mem: 19788 +Test: [19400/21770] eta: 0:01:51 time: 0.0455 data: 0.0015 max mem: 19788 +Test: [19500/21770] eta: 0:01:47 time: 0.0456 data: 0.0015 max mem: 19788 +Test: [19600/21770] eta: 0:01:42 time: 0.0452 data: 0.0014 max mem: 19788 +Test: [19700/21770] eta: 0:01:37 time: 0.0446 data: 0.0013 max mem: 19788 +Test: [19800/21770] eta: 0:01:32 time: 0.0434 data: 0.0015 max mem: 19788 +Test: [19900/21770] eta: 0:01:28 time: 0.0448 data: 0.0014 max mem: 19788 +Test: [20000/21770] eta: 0:01:23 time: 0.0455 data: 0.0016 max mem: 19788 +Test: [20100/21770] eta: 0:01:18 time: 0.0499 data: 0.0016 max mem: 19788 +Test: [20200/21770] eta: 0:01:14 time: 0.0467 data: 0.0016 max mem: 19788 +Test: [20300/21770] eta: 0:01:09 time: 0.0458 data: 0.0016 max mem: 19788 +Test: [20400/21770] eta: 0:01:04 time: 0.0445 data: 0.0016 max mem: 19788 +Test: [20500/21770] eta: 0:00:59 time: 0.0505 data: 0.0017 max mem: 19788 +Test: [20600/21770] eta: 0:00:55 time: 0.0495 data: 0.0017 max mem: 19788 +Test: [20700/21770] eta: 0:00:50 time: 0.0466 data: 0.0016 max mem: 19788 +Test: [20800/21770] eta: 0:00:45 time: 0.0475 data: 0.0017 max mem: 19788 +Test: [20900/21770] eta: 0:00:41 time: 0.0551 data: 0.0019 max mem: 19788 +Test: [21000/21770] eta: 0:00:36 time: 0.0442 data: 0.0014 max mem: 19788 +Test: [21100/21770] eta: 0:00:31 time: 0.0459 data: 0.0015 max mem: 19788 +Test: [21200/21770] eta: 0:00:26 time: 0.0471 data: 0.0016 max mem: 19788 +Test: [21300/21770] eta: 0:00:22 time: 0.0448 data: 0.0015 max mem: 19788 +Test: [21400/21770] eta: 0:00:17 time: 0.0442 data: 0.0016 max mem: 19788 +Test: [21500/21770] eta: 0:00:12 time: 0.0441 data: 0.0015 max mem: 19788 +Test: [21600/21770] eta: 0:00:08 time: 0.0528 data: 0.0018 max mem: 19788 +Test: [21700/21770] eta: 0:00:03 time: 0.0452 data: 0.0014 max mem: 19788 +Test: Total time: 0:17:09 +Final results: +Mean IoU is 64.76 + + precision@0.5 = 71.83 + precision@0.6 = 66.04 + precision@0.7 = 59.24 + precision@0.8 = 48.33 + precision@0.9 = 24.35 + overall IoU = 64.52 + mean IoU = 64.76 + +Mean accuracy for one-to-zero sample is 83.03 + +Average object IoU 0.6475872953740687 +Overall IoU 64.52240753173828 +Better epoch: 18 + +Epoch: [19] [ 0/2138] eta: 5:35:30 lr: 2.7996559986907e-05 loss: 0.0403 (0.0403) time: 9.4155 data: 1.3968 max mem: 19788 +Epoch: [19] [ 10/2138] eta: 2:03:42 lr: 2.7990947766798976e-05 loss: 0.0280 (0.0336) time: 3.4881 data: 0.1287 max mem: 19788 +Epoch: [19] [ 20/2138] eta: 1:52:52 lr: 2.798533542165959e-05 loss: 0.0259 (0.0317) time: 2.8867 data: 0.0020 max mem: 19788 +Epoch: [19] [ 30/2138] eta: 1:48:49 lr: 2.7979722951458194e-05 loss: 0.0290 (0.0321) time: 2.8826 data: 0.0022 max mem: 19788 +Epoch: [19] [ 40/2138] eta: 1:46:34 lr: 2.7974110356164125e-05 loss: 0.0294 (0.0311) time: 2.8903 data: 0.0024 max mem: 19788 +Epoch: [19] [ 50/2138] eta: 1:44:52 lr: 2.7968497635746715e-05 loss: 0.0303 (0.0311) time: 2.8842 data: 0.0022 max mem: 19788 +Epoch: [19] [ 60/2138] eta: 1:43:42 lr: 2.796288479017527e-05 loss: 0.0304 (0.0313) time: 2.8853 data: 0.0023 max mem: 19788 +Epoch: [19] [ 70/2138] eta: 1:43:10 lr: 2.795727181941908e-05 loss: 0.0287 (0.0310) time: 2.9416 data: 0.0023 max mem: 19788 +Epoch: [19] [ 80/2138] eta: 1:42:36 lr: 2.7951658723447426e-05 loss: 0.0271 (0.0310) time: 2.9829 data: 0.0022 max mem: 19788 +Epoch: [19] [ 90/2138] eta: 1:42:05 lr: 2.7946045502229588e-05 loss: 0.0259 (0.0305) time: 2.9812 data: 0.0022 max mem: 19788 +Epoch: [19] [ 100/2138] eta: 1:41:11 lr: 2.794043215573481e-05 loss: 0.0278 (0.0305) time: 2.9294 data: 0.0022 max mem: 19788 +Epoch: [19] [ 110/2138] eta: 1:40:22 lr: 2.7934818683932323e-05 loss: 0.0296 (0.0303) time: 2.8724 data: 0.0025 max mem: 19788 +Epoch: [19] [ 120/2138] eta: 1:39:36 lr: 2.7929205086791353e-05 loss: 0.0251 (0.0298) time: 2.8727 data: 0.0025 max mem: 19788 +Epoch: [19] [ 130/2138] eta: 1:38:57 lr: 2.7923591364281122e-05 loss: 0.0256 (0.0299) time: 2.8889 data: 0.0026 max mem: 19788 +Epoch: [19] [ 140/2138] eta: 1:38:19 lr: 2.7917977516370807e-05 loss: 0.0267 (0.0299) time: 2.8967 data: 0.0027 max mem: 19788 +Epoch: [19] [ 150/2138] eta: 1:37:40 lr: 2.791236354302959e-05 loss: 0.0274 (0.0298) time: 2.8869 data: 0.0028 max mem: 19788 +Epoch: [19] [ 160/2138] eta: 1:37:14 lr: 2.790674944422664e-05 loss: 0.0276 (0.0300) time: 2.9312 data: 0.0029 max mem: 19788 +Epoch: [19] [ 170/2138] eta: 1:36:49 lr: 2.7901135219931124e-05 loss: 0.0306 (0.0301) time: 2.9814 data: 0.0030 max mem: 19788 +Epoch: [19] [ 180/2138] eta: 1:36:18 lr: 2.7895520870112158e-05 loss: 0.0297 (0.0301) time: 2.9637 data: 0.0029 max mem: 19788 +Epoch: [19] [ 190/2138] eta: 1:35:45 lr: 2.7889906394738863e-05 loss: 0.0264 (0.0299) time: 2.9289 data: 0.0028 max mem: 19788 +Epoch: [19] [ 200/2138] eta: 1:35:09 lr: 2.7884291793780354e-05 loss: 0.0264 (0.0300) time: 2.8962 data: 0.0027 max mem: 19788 +Epoch: [19] [ 210/2138] eta: 1:34:33 lr: 2.7878677067205727e-05 loss: 0.0277 (0.0301) time: 2.8783 data: 0.0023 max mem: 19788 +Epoch: [19] [ 220/2138] eta: 1:33:59 lr: 2.7873062214984052e-05 loss: 0.0277 (0.0302) time: 2.8841 data: 0.0021 max mem: 19788 +Epoch: [19] [ 230/2138] eta: 1:33:24 lr: 2.7867447237084392e-05 loss: 0.0303 (0.0307) time: 2.8829 data: 0.0023 max mem: 19788 +Epoch: [19] [ 240/2138] eta: 1:33:02 lr: 2.7861832133475813e-05 loss: 0.0310 (0.0308) time: 2.9517 data: 0.0026 max mem: 19788 +Epoch: [19] [ 250/2138] eta: 1:32:38 lr: 2.7856216904127335e-05 loss: 0.0294 (0.0310) time: 3.0201 data: 0.0027 max mem: 19788 +Epoch: [19] [ 260/2138] eta: 1:32:08 lr: 2.7850601549007976e-05 loss: 0.0262 (0.0309) time: 2.9724 data: 0.0024 max mem: 19788 +Epoch: [19] [ 270/2138] eta: 1:31:35 lr: 2.7844986068086748e-05 loss: 0.0275 (0.0308) time: 2.9171 data: 0.0021 max mem: 19788 +Epoch: [19] [ 280/2138] eta: 1:31:02 lr: 2.7839370461332647e-05 loss: 0.0286 (0.0308) time: 2.8900 data: 0.0021 max mem: 19788 +Epoch: [19] [ 290/2138] eta: 1:30:29 lr: 2.7833754728714644e-05 loss: 0.0311 (0.0310) time: 2.8810 data: 0.0021 max mem: 19788 +Epoch: [19] [ 300/2138] eta: 1:29:56 lr: 2.7828138870201693e-05 loss: 0.0333 (0.0311) time: 2.8828 data: 0.0021 max mem: 19788 +Epoch: [19] [ 310/2138] eta: 1:29:24 lr: 2.7822522885762753e-05 loss: 0.0311 (0.0310) time: 2.8856 data: 0.0024 max mem: 19788 +Epoch: [19] [ 320/2138] eta: 1:28:52 lr: 2.781690677536675e-05 loss: 0.0267 (0.0310) time: 2.8867 data: 0.0025 max mem: 19788 +Epoch: [19] [ 330/2138] eta: 1:28:28 lr: 2.781129053898261e-05 loss: 0.0280 (0.0311) time: 2.9573 data: 0.0025 max mem: 19788 +Epoch: [19] [ 340/2138] eta: 1:27:59 lr: 2.7805674176579223e-05 loss: 0.0300 (0.0310) time: 2.9901 data: 0.0026 max mem: 19788 +Epoch: [19] [ 350/2138] eta: 1:27:28 lr: 2.7800057688125484e-05 loss: 0.0248 (0.0308) time: 2.9227 data: 0.0024 max mem: 19788 +Epoch: [19] [ 360/2138] eta: 1:26:55 lr: 2.7794441073590278e-05 loss: 0.0286 (0.0316) time: 2.8838 data: 0.0021 max mem: 19788 +Epoch: [19] [ 370/2138] eta: 1:26:22 lr: 2.7788824332942454e-05 loss: 0.0315 (0.0316) time: 2.8687 data: 0.0021 max mem: 19788 +Epoch: [19] [ 380/2138] eta: 1:25:51 lr: 2.7783207466150845e-05 loss: 0.0315 (0.0316) time: 2.8726 data: 0.0022 max mem: 19788 +Epoch: [19] [ 390/2138] eta: 1:25:19 lr: 2.77775904731843e-05 loss: 0.0266 (0.0314) time: 2.8822 data: 0.0023 max mem: 19788 +Epoch: [19] [ 400/2138] eta: 1:24:48 lr: 2.7771973354011634e-05 loss: 0.0266 (0.0315) time: 2.8856 data: 0.0024 max mem: 19788 +Epoch: [19] [ 410/2138] eta: 1:24:18 lr: 2.7766356108601637e-05 loss: 0.0260 (0.0312) time: 2.8964 data: 0.0024 max mem: 19788 +Epoch: [19] [ 420/2138] eta: 1:23:53 lr: 2.7760738736923093e-05 loss: 0.0245 (0.0312) time: 2.9625 data: 0.0023 max mem: 19788 +Epoch: [19] [ 430/2138] eta: 1:23:27 lr: 2.775512123894478e-05 loss: 0.0249 (0.0311) time: 3.0251 data: 0.0023 max mem: 19788 +Epoch: [19] [ 440/2138] eta: 1:22:56 lr: 2.774950361463546e-05 loss: 0.0265 (0.0311) time: 2.9552 data: 0.0024 max mem: 19788 +Epoch: [19] [ 450/2138] eta: 1:22:25 lr: 2.7743885863963865e-05 loss: 0.0267 (0.0310) time: 2.8868 data: 0.0024 max mem: 19788 +Epoch: [19] [ 460/2138] eta: 1:21:54 lr: 2.773826798689872e-05 loss: 0.0262 (0.0310) time: 2.8846 data: 0.0023 max mem: 19788 +Epoch: [19] [ 470/2138] eta: 1:21:23 lr: 2.773264998340874e-05 loss: 0.0291 (0.0309) time: 2.8743 data: 0.0024 max mem: 19788 +Epoch: [19] [ 480/2138] eta: 1:20:52 lr: 2.772703185346263e-05 loss: 0.0308 (0.0310) time: 2.8730 data: 0.0026 max mem: 19788 +Epoch: [19] [ 490/2138] eta: 1:20:20 lr: 2.7721413597029073e-05 loss: 0.0307 (0.0309) time: 2.8728 data: 0.0025 max mem: 19788 +Epoch: [19] [ 500/2138] eta: 1:19:52 lr: 2.7715795214076718e-05 loss: 0.0312 (0.0311) time: 2.9120 data: 0.0025 max mem: 19788 +Epoch: [19] [ 510/2138] eta: 1:19:27 lr: 2.7710176704574232e-05 loss: 0.0271 (0.0310) time: 3.0058 data: 0.0024 max mem: 19788 +Epoch: [19] [ 520/2138] eta: 1:18:58 lr: 2.7704558068490255e-05 loss: 0.0246 (0.0310) time: 3.0026 data: 0.0025 max mem: 19788 +Epoch: [19] [ 530/2138] eta: 1:18:27 lr: 2.76989393057934e-05 loss: 0.0287 (0.0310) time: 2.9091 data: 0.0027 max mem: 19788 +Epoch: [19] [ 540/2138] eta: 1:17:57 lr: 2.769332041645228e-05 loss: 0.0267 (0.0309) time: 2.8847 data: 0.0026 max mem: 19788 +Epoch: [19] [ 550/2138] eta: 1:17:27 lr: 2.7687701400435495e-05 loss: 0.0272 (0.0309) time: 2.8878 data: 0.0022 max mem: 19788 +Epoch: [19] [ 560/2138] eta: 1:16:56 lr: 2.7682082257711615e-05 loss: 0.0296 (0.0310) time: 2.8816 data: 0.0021 max mem: 19788 +Epoch: [19] [ 570/2138] eta: 1:16:26 lr: 2.76764629882492e-05 loss: 0.0296 (0.0309) time: 2.8814 data: 0.0027 max mem: 19788 +Epoch: [19] [ 580/2138] eta: 1:15:56 lr: 2.767084359201681e-05 loss: 0.0255 (0.0309) time: 2.8894 data: 0.0029 max mem: 19788 +Epoch: [19] [ 590/2138] eta: 1:15:28 lr: 2.766522406898298e-05 loss: 0.0285 (0.0309) time: 2.9352 data: 0.0026 max mem: 19788 +Epoch: [19] [ 600/2138] eta: 1:14:59 lr: 2.765960441911622e-05 loss: 0.0296 (0.0309) time: 2.9651 data: 0.0025 max mem: 19788 +Epoch: [19] [ 610/2138] eta: 1:14:29 lr: 2.7653984642385033e-05 loss: 0.0282 (0.0309) time: 2.9198 data: 0.0026 max mem: 19788 +Epoch: [19] [ 620/2138] eta: 1:13:59 lr: 2.764836473875791e-05 loss: 0.0277 (0.0309) time: 2.8874 data: 0.0026 max mem: 19788 +Epoch: [19] [ 630/2138] eta: 1:13:28 lr: 2.764274470820333e-05 loss: 0.0295 (0.0309) time: 2.8847 data: 0.0026 max mem: 19788 +Epoch: [19] [ 640/2138] eta: 1:12:58 lr: 2.763712455068976e-05 loss: 0.0295 (0.0309) time: 2.8760 data: 0.0027 max mem: 19788 +Epoch: [19] [ 650/2138] eta: 1:12:28 lr: 2.7631504266185622e-05 loss: 0.0287 (0.0308) time: 2.8792 data: 0.0029 max mem: 19788 +Epoch: [19] [ 660/2138] eta: 1:11:58 lr: 2.762588385465935e-05 loss: 0.0275 (0.0308) time: 2.8929 data: 0.0030 max mem: 19788 +Epoch: [19] [ 670/2138] eta: 1:11:29 lr: 2.762026331607938e-05 loss: 0.0282 (0.0308) time: 2.9224 data: 0.0029 max mem: 19788 +Epoch: [19] [ 680/2138] eta: 1:11:04 lr: 2.7614642650414093e-05 loss: 0.0245 (0.0307) time: 3.0227 data: 0.0026 max mem: 19788 +Epoch: [19] [ 690/2138] eta: 1:10:35 lr: 2.7609021857631867e-05 loss: 0.0240 (0.0307) time: 3.0148 data: 0.0028 max mem: 19788 +Epoch: [19] [ 700/2138] eta: 1:10:05 lr: 2.7603400937701086e-05 loss: 0.0287 (0.0307) time: 2.9065 data: 0.0026 max mem: 19788 +Epoch: [19] [ 710/2138] eta: 1:09:35 lr: 2.7597779890590103e-05 loss: 0.0284 (0.0306) time: 2.8838 data: 0.0022 max mem: 19788 +Epoch: [19] [ 720/2138] eta: 1:09:05 lr: 2.7592158716267254e-05 loss: 0.0277 (0.0306) time: 2.8858 data: 0.0022 max mem: 19788 +Epoch: [19] [ 730/2138] eta: 1:08:35 lr: 2.758653741470085e-05 loss: 0.0260 (0.0306) time: 2.8880 data: 0.0024 max mem: 19788 +Epoch: [19] [ 740/2138] eta: 1:08:05 lr: 2.7580915985859218e-05 loss: 0.0299 (0.0306) time: 2.8798 data: 0.0025 max mem: 19788 +Epoch: [19] [ 750/2138] eta: 1:07:35 lr: 2.7575294429710653e-05 loss: 0.0295 (0.0306) time: 2.8824 data: 0.0025 max mem: 19788 +Epoch: [19] [ 760/2138] eta: 1:07:07 lr: 2.7569672746223424e-05 loss: 0.0294 (0.0306) time: 2.9351 data: 0.0025 max mem: 19788 +Epoch: [19] [ 770/2138] eta: 1:06:38 lr: 2.7564050935365794e-05 loss: 0.0294 (0.0306) time: 2.9734 data: 0.0027 max mem: 19788 +Epoch: [19] [ 780/2138] eta: 1:06:09 lr: 2.7558428997106013e-05 loss: 0.0294 (0.0306) time: 2.9347 data: 0.0025 max mem: 19788 +Epoch: [19] [ 790/2138] eta: 1:05:39 lr: 2.7552806931412324e-05 loss: 0.0276 (0.0305) time: 2.8911 data: 0.0024 max mem: 19788 +Epoch: [19] [ 800/2138] eta: 1:05:09 lr: 2.754718473825294e-05 loss: 0.0262 (0.0305) time: 2.8843 data: 0.0025 max mem: 19788 +Epoch: [19] [ 810/2138] eta: 1:04:39 lr: 2.7541562417596056e-05 loss: 0.0302 (0.0305) time: 2.8856 data: 0.0025 max mem: 19788 +Epoch: [19] [ 820/2138] eta: 1:04:09 lr: 2.7535939969409867e-05 loss: 0.0283 (0.0305) time: 2.8813 data: 0.0022 max mem: 19788 +Epoch: [19] [ 830/2138] eta: 1:03:39 lr: 2.7530317393662553e-05 loss: 0.0247 (0.0305) time: 2.8825 data: 0.0021 max mem: 19788 +Epoch: [19] [ 840/2138] eta: 1:03:10 lr: 2.752469469032226e-05 loss: 0.0236 (0.0304) time: 2.9087 data: 0.0023 max mem: 19788 +Epoch: [19] [ 850/2138] eta: 1:02:42 lr: 2.751907185935713e-05 loss: 0.0269 (0.0304) time: 2.9478 data: 0.0027 max mem: 19788 +Epoch: [19] [ 860/2138] eta: 1:02:13 lr: 2.7513448900735305e-05 loss: 0.0271 (0.0304) time: 2.9485 data: 0.0030 max mem: 19788 +Epoch: [19] [ 870/2138] eta: 1:01:43 lr: 2.7507825814424885e-05 loss: 0.0257 (0.0304) time: 2.9005 data: 0.0029 max mem: 19788 +Epoch: [19] [ 880/2138] eta: 1:01:13 lr: 2.7502202600393973e-05 loss: 0.0257 (0.0303) time: 2.8657 data: 0.0028 max mem: 19788 +Epoch: [19] [ 890/2138] eta: 1:00:43 lr: 2.7496579258610637e-05 loss: 0.0260 (0.0303) time: 2.8672 data: 0.0028 max mem: 19788 +Epoch: [19] [ 900/2138] eta: 1:00:13 lr: 2.7490955789042973e-05 loss: 0.0260 (0.0303) time: 2.8711 data: 0.0024 max mem: 19788 +Epoch: [19] [ 910/2138] eta: 0:59:43 lr: 2.7485332191659002e-05 loss: 0.0260 (0.0303) time: 2.8792 data: 0.0022 max mem: 19788 +Epoch: [19] [ 920/2138] eta: 0:59:14 lr: 2.7479708466426772e-05 loss: 0.0250 (0.0302) time: 2.8941 data: 0.0024 max mem: 19788 +Epoch: [19] [ 930/2138] eta: 0:58:47 lr: 2.7474084613314305e-05 loss: 0.0277 (0.0303) time: 2.9744 data: 0.0024 max mem: 19788 +Epoch: [19] [ 940/2138] eta: 0:58:18 lr: 2.746846063228961e-05 loss: 0.0298 (0.0302) time: 3.0015 data: 0.0024 max mem: 19788 +Epoch: [19] [ 950/2138] eta: 0:57:49 lr: 2.7462836523320674e-05 loss: 0.0271 (0.0302) time: 2.9718 data: 0.0025 max mem: 19788 +Epoch: [19] [ 960/2138] eta: 0:57:20 lr: 2.745721228637546e-05 loss: 0.0294 (0.0302) time: 2.9424 data: 0.0025 max mem: 19788 +Epoch: [19] [ 970/2138] eta: 0:56:50 lr: 2.7451587921421947e-05 loss: 0.0298 (0.0302) time: 2.8902 data: 0.0025 max mem: 19788 +Epoch: [19] [ 980/2138] eta: 0:56:21 lr: 2.744596342842807e-05 loss: 0.0281 (0.0302) time: 2.8800 data: 0.0026 max mem: 19788 +Epoch: [19] [ 990/2138] eta: 0:55:51 lr: 2.744033880736176e-05 loss: 0.0250 (0.0301) time: 2.8908 data: 0.0028 max mem: 19788 +Epoch: [19] [1000/2138] eta: 0:55:21 lr: 2.7434714058190925e-05 loss: 0.0237 (0.0301) time: 2.8860 data: 0.0027 max mem: 19788 +Epoch: [19] [1010/2138] eta: 0:54:52 lr: 2.742908918088347e-05 loss: 0.0239 (0.0301) time: 2.8962 data: 0.0023 max mem: 19788 +Epoch: [19] [1020/2138] eta: 0:54:25 lr: 2.7423464175407283e-05 loss: 0.0244 (0.0300) time: 3.0251 data: 0.0021 max mem: 19788 +Epoch: [19] [1030/2138] eta: 0:53:57 lr: 2.741783904173022e-05 loss: 0.0243 (0.0300) time: 3.0529 data: 0.0021 max mem: 19788 +Epoch: [19] [1040/2138] eta: 0:53:27 lr: 2.7412213779820135e-05 loss: 0.0263 (0.0300) time: 2.9259 data: 0.0022 max mem: 19788 +Epoch: [19] [1050/2138] eta: 0:52:57 lr: 2.7406588389644866e-05 loss: 0.0279 (0.0300) time: 2.8753 data: 0.0023 max mem: 19788 +Epoch: [19] [1060/2138] eta: 0:52:28 lr: 2.740096287117224e-05 loss: 0.0270 (0.0300) time: 2.8774 data: 0.0025 max mem: 19788 +Epoch: [19] [1070/2138] eta: 0:51:58 lr: 2.7395337224370066e-05 loss: 0.0268 (0.0300) time: 2.8828 data: 0.0029 max mem: 19788 +Epoch: [19] [1080/2138] eta: 0:51:29 lr: 2.738971144920612e-05 loss: 0.0268 (0.0300) time: 2.8935 data: 0.0025 max mem: 19788 +Epoch: [19] [1090/2138] eta: 0:50:59 lr: 2.7384085545648186e-05 loss: 0.0269 (0.0300) time: 2.8861 data: 0.0020 max mem: 19788 +Epoch: [19] [1100/2138] eta: 0:50:31 lr: 2.737845951366403e-05 loss: 0.0269 (0.0300) time: 2.9265 data: 0.0021 max mem: 19788 +Epoch: [19] [1110/2138] eta: 0:50:02 lr: 2.737283335322138e-05 loss: 0.0269 (0.0300) time: 2.9642 data: 0.0023 max mem: 19788 +Epoch: [19] [1120/2138] eta: 0:49:32 lr: 2.7367207064287975e-05 loss: 0.0267 (0.0299) time: 2.9257 data: 0.0024 max mem: 19788 +Epoch: [19] [1130/2138] eta: 0:49:03 lr: 2.736158064683153e-05 loss: 0.0277 (0.0300) time: 2.8985 data: 0.0024 max mem: 19788 +Epoch: [19] [1140/2138] eta: 0:48:33 lr: 2.735595410081974e-05 loss: 0.0279 (0.0299) time: 2.8994 data: 0.0026 max mem: 19788 +Epoch: [19] [1150/2138] eta: 0:48:04 lr: 2.7350327426220286e-05 loss: 0.0226 (0.0299) time: 2.8885 data: 0.0025 max mem: 19788 +Epoch: [19] [1160/2138] eta: 0:47:34 lr: 2.7344700623000836e-05 loss: 0.0230 (0.0299) time: 2.8764 data: 0.0023 max mem: 19788 +Epoch: [19] [1170/2138] eta: 0:47:05 lr: 2.7339073691129042e-05 loss: 0.0258 (0.0298) time: 2.8777 data: 0.0026 max mem: 19788 +Epoch: [19] [1180/2138] eta: 0:46:36 lr: 2.733344663057254e-05 loss: 0.0260 (0.0298) time: 2.8960 data: 0.0028 max mem: 19788 +Epoch: [19] [1190/2138] eta: 0:46:07 lr: 2.7327819441298946e-05 loss: 0.0257 (0.0298) time: 2.9372 data: 0.0027 max mem: 19788 +Epoch: [19] [1200/2138] eta: 0:45:38 lr: 2.732219212327587e-05 loss: 0.0256 (0.0298) time: 2.9663 data: 0.0027 max mem: 19788 +Epoch: [19] [1210/2138] eta: 0:45:09 lr: 2.73165646764709e-05 loss: 0.0287 (0.0298) time: 2.9348 data: 0.0025 max mem: 19788 +Epoch: [19] [1220/2138] eta: 0:44:39 lr: 2.731093710085161e-05 loss: 0.0298 (0.0298) time: 2.8873 data: 0.0022 max mem: 19788 +Epoch: [19] [1230/2138] eta: 0:44:10 lr: 2.7305309396385546e-05 loss: 0.0266 (0.0298) time: 2.8746 data: 0.0022 max mem: 19788 +Epoch: [19] [1240/2138] eta: 0:43:40 lr: 2.729968156304027e-05 loss: 0.0266 (0.0298) time: 2.8769 data: 0.0022 max mem: 19788 +Epoch: [19] [1250/2138] eta: 0:43:11 lr: 2.7294053600783303e-05 loss: 0.0279 (0.0298) time: 2.9129 data: 0.0023 max mem: 19788 +Epoch: [19] [1260/2138] eta: 0:42:41 lr: 2.728842550958215e-05 loss: 0.0294 (0.0298) time: 2.9014 data: 0.0025 max mem: 19788 +Epoch: [19] [1270/2138] eta: 0:42:13 lr: 2.7282797289404298e-05 loss: 0.0273 (0.0298) time: 2.9094 data: 0.0025 max mem: 19788 +Epoch: [19] [1280/2138] eta: 0:41:44 lr: 2.7277168940217247e-05 loss: 0.0266 (0.0298) time: 2.9595 data: 0.0026 max mem: 19788 +Epoch: [19] [1290/2138] eta: 0:41:15 lr: 2.7271540461988453e-05 loss: 0.0284 (0.0298) time: 2.9413 data: 0.0028 max mem: 19788 +Epoch: [19] [1300/2138] eta: 0:40:45 lr: 2.726591185468536e-05 loss: 0.0294 (0.0298) time: 2.8990 data: 0.0028 max mem: 19788 +Epoch: [19] [1310/2138] eta: 0:40:16 lr: 2.7260283118275402e-05 loss: 0.0269 (0.0298) time: 2.8818 data: 0.0028 max mem: 19788 +Epoch: [19] [1320/2138] eta: 0:39:46 lr: 2.7254654252726004e-05 loss: 0.0250 (0.0298) time: 2.8849 data: 0.0028 max mem: 19788 +Epoch: [19] [1330/2138] eta: 0:39:17 lr: 2.7249025258004556e-05 loss: 0.0264 (0.0298) time: 2.8891 data: 0.0026 max mem: 19788 +Epoch: [19] [1340/2138] eta: 0:38:47 lr: 2.7243396134078458e-05 loss: 0.0274 (0.0298) time: 2.8821 data: 0.0024 max mem: 19788 +Epoch: [19] [1350/2138] eta: 0:38:18 lr: 2.723776688091506e-05 loss: 0.0304 (0.0298) time: 2.8866 data: 0.0025 max mem: 19788 +Epoch: [19] [1360/2138] eta: 0:37:49 lr: 2.723213749848173e-05 loss: 0.0301 (0.0298) time: 2.9363 data: 0.0027 max mem: 19788 +Epoch: [19] [1370/2138] eta: 0:37:20 lr: 2.7226507986745808e-05 loss: 0.0284 (0.0299) time: 2.9650 data: 0.0026 max mem: 19788 +Epoch: [19] [1380/2138] eta: 0:36:51 lr: 2.7220878345674612e-05 loss: 0.0318 (0.0299) time: 2.9268 data: 0.0026 max mem: 19788 +Epoch: [19] [1390/2138] eta: 0:36:22 lr: 2.721524857523544e-05 loss: 0.0281 (0.0298) time: 2.8854 data: 0.0025 max mem: 19788 +Epoch: [19] [1400/2138] eta: 0:35:52 lr: 2.72096186753956e-05 loss: 0.0253 (0.0298) time: 2.8813 data: 0.0022 max mem: 19788 +Epoch: [19] [1410/2138] eta: 0:35:23 lr: 2.7203988646122363e-05 loss: 0.0261 (0.0298) time: 2.8903 data: 0.0022 max mem: 19788 +Epoch: [19] [1420/2138] eta: 0:34:54 lr: 2.719835848738298e-05 loss: 0.0259 (0.0298) time: 2.8827 data: 0.0022 max mem: 19788 +Epoch: [19] [1430/2138] eta: 0:34:24 lr: 2.71927281991447e-05 loss: 0.0269 (0.0298) time: 2.8705 data: 0.0022 max mem: 19788 +Epoch: [19] [1440/2138] eta: 0:33:55 lr: 2.7187097781374752e-05 loss: 0.0287 (0.0298) time: 2.9062 data: 0.0022 max mem: 19788 +Epoch: [19] [1450/2138] eta: 0:33:26 lr: 2.7181467234040354e-05 loss: 0.0289 (0.0299) time: 2.9432 data: 0.0024 max mem: 19788 +Epoch: [19] [1460/2138] eta: 0:32:57 lr: 2.7175836557108687e-05 loss: 0.0283 (0.0298) time: 2.9237 data: 0.0023 max mem: 19788 +Epoch: [19] [1470/2138] eta: 0:32:28 lr: 2.717020575054694e-05 loss: 0.0275 (0.0298) time: 2.8871 data: 0.0023 max mem: 19788 +Epoch: [19] [1480/2138] eta: 0:31:58 lr: 2.716457481432228e-05 loss: 0.0254 (0.0298) time: 2.8817 data: 0.0026 max mem: 19788 +Epoch: [19] [1490/2138] eta: 0:31:29 lr: 2.7158943748401855e-05 loss: 0.0254 (0.0299) time: 2.8916 data: 0.0024 max mem: 19788 +Epoch: [19] [1500/2138] eta: 0:31:00 lr: 2.7153312552752786e-05 loss: 0.0274 (0.0299) time: 2.8942 data: 0.0021 max mem: 19788 +Epoch: [19] [1510/2138] eta: 0:30:31 lr: 2.7147681227342202e-05 loss: 0.0252 (0.0298) time: 2.8981 data: 0.0024 max mem: 19788 +Epoch: [19] [1520/2138] eta: 0:30:01 lr: 2.7142049772137213e-05 loss: 0.0245 (0.0300) time: 2.8953 data: 0.0027 max mem: 19788 +Epoch: [19] [1530/2138] eta: 0:29:33 lr: 2.7136418187104885e-05 loss: 0.0270 (0.0300) time: 2.9615 data: 0.0027 max mem: 19788 +Epoch: [19] [1540/2138] eta: 0:29:04 lr: 2.713078647221229e-05 loss: 0.0254 (0.0300) time: 2.9881 data: 0.0026 max mem: 19788 +Epoch: [19] [1550/2138] eta: 0:28:34 lr: 2.7125154627426486e-05 loss: 0.0246 (0.0300) time: 2.9139 data: 0.0027 max mem: 19788 +Epoch: [19] [1560/2138] eta: 0:28:05 lr: 2.7119522652714513e-05 loss: 0.0276 (0.0300) time: 2.8758 data: 0.0025 max mem: 19788 +Epoch: [19] [1570/2138] eta: 0:27:36 lr: 2.7113890548043392e-05 loss: 0.0276 (0.0301) time: 2.8696 data: 0.0021 max mem: 19788 +Epoch: [19] [1580/2138] eta: 0:27:06 lr: 2.7108258313380115e-05 loss: 0.0283 (0.0301) time: 2.8790 data: 0.0022 max mem: 19788 +Epoch: [19] [1590/2138] eta: 0:26:37 lr: 2.7102625948691685e-05 loss: 0.0275 (0.0301) time: 2.8809 data: 0.0023 max mem: 19788 +Epoch: [19] [1600/2138] eta: 0:26:08 lr: 2.7096993453945074e-05 loss: 0.0301 (0.0301) time: 2.8752 data: 0.0022 max mem: 19788 +Epoch: [19] [1610/2138] eta: 0:25:39 lr: 2.7091360829107237e-05 loss: 0.0291 (0.0301) time: 2.8965 data: 0.0021 max mem: 19788 +Epoch: [19] [1620/2138] eta: 0:25:10 lr: 2.708572807414511e-05 loss: 0.0231 (0.0300) time: 2.9351 data: 0.0022 max mem: 19788 +Epoch: [19] [1630/2138] eta: 0:24:41 lr: 2.7080095189025622e-05 loss: 0.0230 (0.0300) time: 2.9982 data: 0.0025 max mem: 19788 +Epoch: [19] [1640/2138] eta: 0:24:12 lr: 2.7074462173715686e-05 loss: 0.0278 (0.0300) time: 2.9618 data: 0.0028 max mem: 19788 +Epoch: [19] [1650/2138] eta: 0:23:42 lr: 2.7068829028182196e-05 loss: 0.0278 (0.0300) time: 2.8858 data: 0.0028 max mem: 19788 +Epoch: [19] [1660/2138] eta: 0:23:13 lr: 2.7063195752392013e-05 loss: 0.0292 (0.0300) time: 2.8841 data: 0.0027 max mem: 19788 +Epoch: [19] [1670/2138] eta: 0:22:44 lr: 2.7057562346312015e-05 loss: 0.0274 (0.0300) time: 2.8817 data: 0.0030 max mem: 19788 +Epoch: [19] [1680/2138] eta: 0:22:15 lr: 2.705192880990904e-05 loss: 0.0261 (0.0300) time: 2.8885 data: 0.0027 max mem: 19788 +Epoch: [19] [1690/2138] eta: 0:21:45 lr: 2.704629514314992e-05 loss: 0.0285 (0.0300) time: 2.8876 data: 0.0023 max mem: 19788 +Epoch: [19] [1700/2138] eta: 0:21:17 lr: 2.704066134600146e-05 loss: 0.0264 (0.0300) time: 2.9770 data: 0.0025 max mem: 19788 +Epoch: [19] [1710/2138] eta: 0:20:48 lr: 2.703502741843047e-05 loss: 0.0252 (0.0300) time: 3.0270 data: 0.0025 max mem: 19788 +Epoch: [19] [1720/2138] eta: 0:20:19 lr: 2.7029393360403717e-05 loss: 0.0289 (0.0300) time: 2.9685 data: 0.0025 max mem: 19788 +Epoch: [19] [1730/2138] eta: 0:19:50 lr: 2.7023759171887964e-05 loss: 0.0302 (0.0300) time: 2.9622 data: 0.0028 max mem: 19788 +Epoch: [19] [1740/2138] eta: 0:19:20 lr: 2.7018124852849963e-05 loss: 0.0297 (0.0300) time: 2.9599 data: 0.0025 max mem: 19788 +Epoch: [19] [1750/2138] eta: 0:18:51 lr: 2.701249040325645e-05 loss: 0.0292 (0.0300) time: 2.9168 data: 0.0020 max mem: 19788 +Epoch: [19] [1760/2138] eta: 0:18:22 lr: 2.7006855823074147e-05 loss: 0.0272 (0.0300) time: 2.8891 data: 0.0020 max mem: 19788 +Epoch: [19] [1770/2138] eta: 0:17:53 lr: 2.700122111226973e-05 loss: 0.0255 (0.0299) time: 2.8891 data: 0.0021 max mem: 19788 +Epoch: [19] [1780/2138] eta: 0:17:24 lr: 2.69955862708099e-05 loss: 0.0222 (0.0299) time: 2.8835 data: 0.0021 max mem: 19788 +Epoch: [19] [1790/2138] eta: 0:16:54 lr: 2.698995129866132e-05 loss: 0.0241 (0.0299) time: 2.8821 data: 0.0021 max mem: 19788 +Epoch: [19] [1800/2138] eta: 0:16:25 lr: 2.6984316195790645e-05 loss: 0.0312 (0.0299) time: 2.8957 data: 0.0025 max mem: 19788 +Epoch: [19] [1810/2138] eta: 0:15:56 lr: 2.69786809621645e-05 loss: 0.0320 (0.0299) time: 2.9890 data: 0.0029 max mem: 19788 +Epoch: [19] [1820/2138] eta: 0:15:27 lr: 2.69730455977495e-05 loss: 0.0230 (0.0299) time: 2.9955 data: 0.0026 max mem: 19788 +Epoch: [19] [1830/2138] eta: 0:14:58 lr: 2.6967410102512263e-05 loss: 0.0230 (0.0299) time: 2.9196 data: 0.0025 max mem: 19788 +Epoch: [19] [1840/2138] eta: 0:14:29 lr: 2.6961774476419372e-05 loss: 0.0271 (0.0299) time: 2.9083 data: 0.0024 max mem: 19788 +Epoch: [19] [1850/2138] eta: 0:14:00 lr: 2.6956138719437373e-05 loss: 0.0313 (0.0299) time: 2.8957 data: 0.0022 max mem: 19788 +Epoch: [19] [1860/2138] eta: 0:13:30 lr: 2.695050283153285e-05 loss: 0.0285 (0.0299) time: 2.8902 data: 0.0023 max mem: 19788 +Epoch: [19] [1870/2138] eta: 0:13:01 lr: 2.694486681267232e-05 loss: 0.0285 (0.0299) time: 2.8906 data: 0.0024 max mem: 19788 +Epoch: [19] [1880/2138] eta: 0:12:32 lr: 2.6939230662822312e-05 loss: 0.0245 (0.0299) time: 2.9299 data: 0.0023 max mem: 19788 +Epoch: [19] [1890/2138] eta: 0:12:03 lr: 2.6933594381949324e-05 loss: 0.0238 (0.0299) time: 2.9985 data: 0.0025 max mem: 19788 +Epoch: [19] [1900/2138] eta: 0:11:34 lr: 2.692795797001984e-05 loss: 0.0277 (0.0299) time: 2.9674 data: 0.0026 max mem: 19788 +Epoch: [19] [1910/2138] eta: 0:11:05 lr: 2.6922321427000346e-05 loss: 0.0260 (0.0298) time: 2.8940 data: 0.0026 max mem: 19788 +Epoch: [19] [1920/2138] eta: 0:10:35 lr: 2.6916684752857292e-05 loss: 0.0260 (0.0298) time: 2.8875 data: 0.0027 max mem: 19788 +Epoch: [19] [1930/2138] eta: 0:10:06 lr: 2.69110479475571e-05 loss: 0.0285 (0.0298) time: 2.8937 data: 0.0025 max mem: 19788 +Epoch: [19] [1940/2138] eta: 0:09:37 lr: 2.6905411011066213e-05 loss: 0.0238 (0.0298) time: 2.8908 data: 0.0024 max mem: 19788 +Epoch: [19] [1950/2138] eta: 0:09:08 lr: 2.6899773943351024e-05 loss: 0.0243 (0.0298) time: 2.8875 data: 0.0024 max mem: 19788 +Epoch: [19] [1960/2138] eta: 0:08:39 lr: 2.6894136744377933e-05 loss: 0.0271 (0.0298) time: 2.9171 data: 0.0022 max mem: 19788 +Epoch: [19] [1970/2138] eta: 0:08:10 lr: 2.68884994141133e-05 loss: 0.0269 (0.0298) time: 3.0680 data: 0.0022 max mem: 19788 +Epoch: [19] [1980/2138] eta: 0:07:41 lr: 2.6882861952523487e-05 loss: 0.0269 (0.0298) time: 3.0438 data: 0.0022 max mem: 19788 +Epoch: [19] [1990/2138] eta: 0:07:11 lr: 2.6877224359574844e-05 loss: 0.0266 (0.0298) time: 2.8971 data: 0.0022 max mem: 19788 +Epoch: [19] [2000/2138] eta: 0:06:42 lr: 2.6871586635233674e-05 loss: 0.0252 (0.0298) time: 2.8918 data: 0.0022 max mem: 19788 +Epoch: [19] [2010/2138] eta: 0:06:13 lr: 2.68659487794663e-05 loss: 0.0250 (0.0298) time: 2.8827 data: 0.0022 max mem: 19788 +Epoch: [19] [2020/2138] eta: 0:05:44 lr: 2.6860310792239008e-05 loss: 0.0275 (0.0298) time: 2.8861 data: 0.0024 max mem: 19788 +Epoch: [19] [2030/2138] eta: 0:05:15 lr: 2.685467267351807e-05 loss: 0.0265 (0.0297) time: 2.8894 data: 0.0024 max mem: 19788 +Epoch: [19] [2040/2138] eta: 0:04:45 lr: 2.6849034423269743e-05 loss: 0.0254 (0.0297) time: 2.9055 data: 0.0023 max mem: 19788 +Epoch: [19] [2050/2138] eta: 0:04:16 lr: 2.684339604146026e-05 loss: 0.0265 (0.0297) time: 2.9738 data: 0.0023 max mem: 19788 +Epoch: [19] [2060/2138] eta: 0:03:47 lr: 2.683775752805587e-05 loss: 0.0265 (0.0297) time: 2.9716 data: 0.0023 max mem: 19788 +Epoch: [19] [2070/2138] eta: 0:03:18 lr: 2.6832118883022757e-05 loss: 0.0295 (0.0297) time: 2.9027 data: 0.0023 max mem: 19788 +Epoch: [19] [2080/2138] eta: 0:02:49 lr: 2.6826480106327118e-05 loss: 0.0278 (0.0297) time: 2.8898 data: 0.0021 max mem: 19788 +Epoch: [19] [2090/2138] eta: 0:02:20 lr: 2.6820841197935125e-05 loss: 0.0265 (0.0297) time: 2.8896 data: 0.0024 max mem: 19788 +Epoch: [19] [2100/2138] eta: 0:01:50 lr: 2.681520215781295e-05 loss: 0.0278 (0.0297) time: 2.8868 data: 0.0025 max mem: 19788 +Epoch: [19] [2110/2138] eta: 0:01:21 lr: 2.6809562985926728e-05 loss: 0.0313 (0.0297) time: 2.8888 data: 0.0024 max mem: 19788 +Epoch: [19] [2120/2138] eta: 0:00:52 lr: 2.680392368224257e-05 loss: 0.0315 (0.0298) time: 2.9806 data: 0.0024 max mem: 19788 +Epoch: [19] [2130/2138] eta: 0:00:23 lr: 2.6798284246726596e-05 loss: 0.0327 (0.0299) time: 3.0174 data: 0.0021 max mem: 19788 +Epoch: [19] Total time: 1:43:59 +Test: [ 0/21770] eta: 14:26:08 time: 2.3871 data: 2.1965 max mem: 19788 +Test: [ 100/21770] eta: 0:25:00 time: 0.0440 data: 0.0016 max mem: 19788 +Test: [ 200/21770] eta: 0:20:25 time: 0.0465 data: 0.0014 max mem: 19788 +Test: [ 300/21770] eta: 0:18:52 time: 0.0434 data: 0.0015 max mem: 19788 +Test: [ 400/21770] eta: 0:18:23 time: 0.0431 data: 0.0018 max mem: 19788 +Test: [ 500/21770] eta: 0:17:58 time: 0.0498 data: 0.0016 max mem: 19788 +Test: [ 600/21770] eta: 0:17:36 time: 0.0524 data: 0.0019 max mem: 19788 +Test: [ 700/21770] eta: 0:17:13 time: 0.0437 data: 0.0014 max mem: 19788 +Test: [ 800/21770] eta: 0:17:04 time: 0.0458 data: 0.0015 max mem: 19788 +Test: [ 900/21770] eta: 0:16:50 time: 0.0450 data: 0.0016 max mem: 19788 +Test: [ 1000/21770] eta: 0:16:38 time: 0.0520 data: 0.0017 max mem: 19788 +Test: [ 1100/21770] eta: 0:16:31 time: 0.0473 data: 0.0016 max mem: 19788 +Test: [ 1200/21770] eta: 0:16:25 time: 0.0426 data: 0.0015 max mem: 19788 +Test: [ 1300/21770] eta: 0:16:15 time: 0.0438 data: 0.0015 max mem: 19788 +Test: [ 1400/21770] eta: 0:16:10 time: 0.0448 data: 0.0015 max mem: 19788 +Test: [ 1500/21770] eta: 0:16:02 time: 0.0429 data: 0.0015 max mem: 19788 +Test: [ 1600/21770] eta: 0:15:53 time: 0.0454 data: 0.0018 max mem: 19788 +Test: [ 1700/21770] eta: 0:15:46 time: 0.0436 data: 0.0015 max mem: 19788 +Test: [ 1800/21770] eta: 0:15:39 time: 0.0439 data: 0.0014 max mem: 19788 +Test: [ 1900/21770] eta: 0:15:33 time: 0.0437 data: 0.0015 max mem: 19788 +Test: [ 2000/21770] eta: 0:15:30 time: 0.0432 data: 0.0016 max mem: 19788 +Test: [ 2100/21770] eta: 0:15:23 time: 0.0441 data: 0.0014 max mem: 19788 +Test: [ 2200/21770] eta: 0:15:19 time: 0.0495 data: 0.0017 max mem: 19788 +Test: [ 2300/21770] eta: 0:15:12 time: 0.0436 data: 0.0015 max mem: 19788 +Test: [ 2400/21770] eta: 0:15:06 time: 0.0447 data: 0.0015 max mem: 19788 +Test: [ 2500/21770] eta: 0:15:02 time: 0.0521 data: 0.0017 max mem: 19788 +Test: [ 2600/21770] eta: 0:14:55 time: 0.0443 data: 0.0016 max mem: 19788 +Test: [ 2700/21770] eta: 0:14:49 time: 0.0456 data: 0.0014 max mem: 19788 +Test: [ 2800/21770] eta: 0:14:46 time: 0.0494 data: 0.0014 max mem: 19788 +Test: [ 2900/21770] eta: 0:14:44 time: 0.0542 data: 0.0018 max mem: 19788 +Test: [ 3000/21770] eta: 0:14:39 time: 0.0434 data: 0.0015 max mem: 19788 +Test: [ 3100/21770] eta: 0:14:35 time: 0.0489 data: 0.0017 max mem: 19788 +Test: [ 3200/21770] eta: 0:14:32 time: 0.0438 data: 0.0014 max mem: 19788 +Test: [ 3300/21770] eta: 0:14:27 time: 0.0505 data: 0.0017 max mem: 19788 +Test: [ 3400/21770] eta: 0:14:23 time: 0.0471 data: 0.0016 max mem: 19788 +Test: [ 3500/21770] eta: 0:14:19 time: 0.0442 data: 0.0016 max mem: 19788 +Test: [ 3600/21770] eta: 0:14:15 time: 0.0518 data: 0.0018 max mem: 19788 +Test: [ 3700/21770] eta: 0:14:11 time: 0.0469 data: 0.0018 max mem: 19788 +Test: [ 3800/21770] eta: 0:14:07 time: 0.0530 data: 0.0017 max mem: 19788 +Test: [ 3900/21770] eta: 0:14:02 time: 0.0449 data: 0.0015 max mem: 19788 +Test: [ 4000/21770] eta: 0:13:57 time: 0.0451 data: 0.0015 max mem: 19788 +Test: [ 4100/21770] eta: 0:13:52 time: 0.0445 data: 0.0015 max mem: 19788 +Test: [ 4200/21770] eta: 0:13:46 time: 0.0438 data: 0.0014 max mem: 19788 +Test: [ 4300/21770] eta: 0:13:42 time: 0.0457 data: 0.0015 max mem: 19788 +Test: [ 4400/21770] eta: 0:13:36 time: 0.0451 data: 0.0015 max mem: 19788 +Test: [ 4500/21770] eta: 0:13:30 time: 0.0445 data: 0.0014 max mem: 19788 +Test: [ 4600/21770] eta: 0:13:26 time: 0.0525 data: 0.0017 max mem: 19788 +Test: [ 4700/21770] eta: 0:13:21 time: 0.0434 data: 0.0013 max mem: 19788 +Test: [ 4800/21770] eta: 0:13:15 time: 0.0480 data: 0.0016 max mem: 19788 +Test: [ 4900/21770] eta: 0:13:10 time: 0.0465 data: 0.0015 max mem: 19788 +Test: [ 5000/21770] eta: 0:13:06 time: 0.0458 data: 0.0015 max mem: 19788 +Test: [ 5100/21770] eta: 0:13:00 time: 0.0449 data: 0.0014 max mem: 19788 +Test: [ 5200/21770] eta: 0:12:56 time: 0.0524 data: 0.0019 max mem: 19788 +Test: [ 5300/21770] eta: 0:12:53 time: 0.0539 data: 0.0017 max mem: 19788 +Test: [ 5400/21770] eta: 0:12:48 time: 0.0435 data: 0.0015 max mem: 19788 +Test: [ 5500/21770] eta: 0:12:43 time: 0.0436 data: 0.0017 max mem: 19788 +Test: [ 5600/21770] eta: 0:12:38 time: 0.0444 data: 0.0015 max mem: 19788 +Test: [ 5700/21770] eta: 0:12:33 time: 0.0446 data: 0.0014 max mem: 19788 +Test: [ 5800/21770] eta: 0:12:27 time: 0.0519 data: 0.0018 max mem: 19788 +Test: [ 5900/21770] eta: 0:12:22 time: 0.0449 data: 0.0016 max mem: 19788 +Test: [ 6000/21770] eta: 0:12:17 time: 0.0456 data: 0.0015 max mem: 19788 +Test: [ 6100/21770] eta: 0:12:14 time: 0.0477 data: 0.0015 max mem: 19788 +Test: [ 6200/21770] eta: 0:12:10 time: 0.0504 data: 0.0017 max mem: 19788 +Test: [ 6300/21770] eta: 0:12:06 time: 0.0442 data: 0.0014 max mem: 19788 +Test: [ 6400/21770] eta: 0:12:01 time: 0.0526 data: 0.0015 max mem: 19788 +Test: [ 6500/21770] eta: 0:11:57 time: 0.0507 data: 0.0018 max mem: 19788 +Test: [ 6600/21770] eta: 0:11:52 time: 0.0447 data: 0.0014 max mem: 19788 +Test: [ 6700/21770] eta: 0:11:47 time: 0.0513 data: 0.0018 max mem: 19788 +Test: [ 6800/21770] eta: 0:11:42 time: 0.0436 data: 0.0013 max mem: 19788 +Test: [ 6900/21770] eta: 0:11:37 time: 0.0438 data: 0.0016 max mem: 19788 +Test: [ 7000/21770] eta: 0:11:31 time: 0.0450 data: 0.0016 max mem: 19788 +Test: [ 7100/21770] eta: 0:11:27 time: 0.0496 data: 0.0017 max mem: 19788 +Test: [ 7200/21770] eta: 0:11:23 time: 0.0523 data: 0.0018 max mem: 19788 +Test: [ 7300/21770] eta: 0:11:18 time: 0.0521 data: 0.0018 max mem: 19788 +Test: [ 7400/21770] eta: 0:11:13 time: 0.0441 data: 0.0018 max mem: 19788 +Test: [ 7500/21770] eta: 0:11:09 time: 0.0552 data: 0.0017 max mem: 19788 +Test: [ 7600/21770] eta: 0:11:04 time: 0.0522 data: 0.0018 max mem: 19788 +Test: [ 7700/21770] eta: 0:11:00 time: 0.0440 data: 0.0013 max mem: 19788 +Test: [ 7800/21770] eta: 0:10:55 time: 0.0445 data: 0.0014 max mem: 19788 +Test: [ 7900/21770] eta: 0:10:50 time: 0.0474 data: 0.0016 max mem: 19788 +Test: [ 8000/21770] eta: 0:10:46 time: 0.0440 data: 0.0015 max mem: 19788 +Test: [ 8100/21770] eta: 0:10:40 time: 0.0467 data: 0.0015 max mem: 19788 +Test: [ 8200/21770] eta: 0:10:36 time: 0.0456 data: 0.0014 max mem: 19788 +Test: [ 8300/21770] eta: 0:10:31 time: 0.0500 data: 0.0017 max mem: 19788 +Test: [ 8400/21770] eta: 0:10:27 time: 0.0530 data: 0.0020 max mem: 19788 +Test: [ 8500/21770] eta: 0:10:21 time: 0.0451 data: 0.0015 max mem: 19788 +Test: [ 8600/21770] eta: 0:10:17 time: 0.0520 data: 0.0017 max mem: 19788 +Test: [ 8700/21770] eta: 0:10:12 time: 0.0444 data: 0.0016 max mem: 19788 +Test: [ 8800/21770] eta: 0:10:08 time: 0.0530 data: 0.0018 max mem: 19788 +Test: [ 8900/21770] eta: 0:10:03 time: 0.0441 data: 0.0014 max mem: 19788 +Test: [ 9000/21770] eta: 0:09:59 time: 0.0443 data: 0.0015 max mem: 19788 +Test: [ 9100/21770] eta: 0:09:54 time: 0.0476 data: 0.0015 max mem: 19788 +Test: [ 9200/21770] eta: 0:09:49 time: 0.0433 data: 0.0014 max mem: 19788 +Test: [ 9300/21770] eta: 0:09:44 time: 0.0444 data: 0.0014 max mem: 19788 +Test: [ 9400/21770] eta: 0:09:39 time: 0.0536 data: 0.0020 max mem: 19788 +Test: [ 9500/21770] eta: 0:09:35 time: 0.0442 data: 0.0015 max mem: 19788 +Test: [ 9600/21770] eta: 0:09:30 time: 0.0483 data: 0.0017 max mem: 19788 +Test: [ 9700/21770] eta: 0:09:25 time: 0.0519 data: 0.0017 max mem: 19788 +Test: [ 9800/21770] eta: 0:09:21 time: 0.0448 data: 0.0016 max mem: 19788 +Test: [ 9900/21770] eta: 0:09:16 time: 0.0510 data: 0.0018 max mem: 19788 +Test: [10000/21770] eta: 0:09:11 time: 0.0448 data: 0.0014 max mem: 19788 +Test: [10100/21770] eta: 0:09:06 time: 0.0457 data: 0.0015 max mem: 19788 +Test: [10200/21770] eta: 0:09:02 time: 0.0467 data: 0.0016 max mem: 19788 +Test: [10300/21770] eta: 0:08:57 time: 0.0527 data: 0.0018 max mem: 19788 +Test: [10400/21770] eta: 0:08:53 time: 0.0495 data: 0.0017 max mem: 19788 +Test: [10500/21770] eta: 0:08:48 time: 0.0480 data: 0.0017 max mem: 19788 +Test: [10600/21770] eta: 0:08:43 time: 0.0455 data: 0.0019 max mem: 19788 +Test: [10700/21770] eta: 0:08:39 time: 0.0441 data: 0.0014 max mem: 19788 +Test: [10800/21770] eta: 0:08:34 time: 0.0452 data: 0.0014 max mem: 19788 +Test: [10900/21770] eta: 0:08:30 time: 0.0525 data: 0.0017 max mem: 19788 +Test: [11000/21770] eta: 0:08:25 time: 0.0494 data: 0.0017 max mem: 19788 +Test: [11100/21770] eta: 0:08:20 time: 0.0455 data: 0.0014 max mem: 19788 +Test: [11200/21770] eta: 0:08:15 time: 0.0505 data: 0.0014 max mem: 19788 +Test: [11300/21770] eta: 0:08:11 time: 0.0457 data: 0.0015 max mem: 19788 +Test: [11400/21770] eta: 0:08:07 time: 0.0506 data: 0.0018 max mem: 19788 +Test: [11500/21770] eta: 0:08:02 time: 0.0500 data: 0.0017 max mem: 19788 +Test: [11600/21770] eta: 0:07:58 time: 0.0448 data: 0.0014 max mem: 19788 +Test: [11700/21770] eta: 0:07:53 time: 0.0444 data: 0.0016 max mem: 19788 +Test: [11800/21770] eta: 0:07:48 time: 0.0444 data: 0.0015 max mem: 19788 +Test: [11900/21770] eta: 0:07:44 time: 0.0503 data: 0.0016 max mem: 19788 +Test: [12000/21770] eta: 0:07:39 time: 0.0453 data: 0.0014 max mem: 19788 +Test: [12100/21770] eta: 0:07:34 time: 0.0448 data: 0.0015 max mem: 19788 +Test: [12200/21770] eta: 0:07:30 time: 0.0457 data: 0.0015 max mem: 19788 +Test: [12300/21770] eta: 0:07:25 time: 0.0440 data: 0.0014 max mem: 19788 +Test: [12400/21770] eta: 0:07:21 time: 0.0523 data: 0.0019 max mem: 19788 +Test: [12500/21770] eta: 0:07:16 time: 0.0468 data: 0.0015 max mem: 19788 +Test: [12600/21770] eta: 0:07:11 time: 0.0495 data: 0.0017 max mem: 19788 +Test: [12700/21770] eta: 0:07:06 time: 0.0445 data: 0.0015 max mem: 19788 +Test: [12800/21770] eta: 0:07:02 time: 0.0448 data: 0.0017 max mem: 19788 +Test: [12900/21770] eta: 0:06:57 time: 0.0463 data: 0.0016 max mem: 19788 +Test: [13000/21770] eta: 0:06:52 time: 0.0464 data: 0.0015 max mem: 19788 +Test: [13100/21770] eta: 0:06:48 time: 0.0479 data: 0.0015 max mem: 19788 +Test: [13200/21770] eta: 0:06:43 time: 0.0441 data: 0.0016 max mem: 19788 +Test: [13300/21770] eta: 0:06:38 time: 0.0483 data: 0.0016 max mem: 19788 +Test: [13400/21770] eta: 0:06:33 time: 0.0509 data: 0.0015 max mem: 19788 +Test: [13500/21770] eta: 0:06:29 time: 0.0441 data: 0.0013 max mem: 19788 +Test: [13600/21770] eta: 0:06:24 time: 0.0443 data: 0.0014 max mem: 19788 +Test: [13700/21770] eta: 0:06:19 time: 0.0445 data: 0.0014 max mem: 19788 +Test: [13800/21770] eta: 0:06:14 time: 0.0449 data: 0.0014 max mem: 19788 +Test: [13900/21770] eta: 0:06:10 time: 0.0538 data: 0.0018 max mem: 19788 +Test: [14000/21770] eta: 0:06:05 time: 0.0531 data: 0.0018 max mem: 19788 +Test: [14100/21770] eta: 0:06:01 time: 0.0457 data: 0.0014 max mem: 19788 +Test: [14200/21770] eta: 0:05:56 time: 0.0450 data: 0.0014 max mem: 19788 +Test: [14300/21770] eta: 0:05:51 time: 0.0511 data: 0.0016 max mem: 19788 +Test: [14400/21770] eta: 0:05:47 time: 0.0441 data: 0.0014 max mem: 19788 +Test: [14500/21770] eta: 0:05:42 time: 0.0484 data: 0.0016 max mem: 19788 +Test: [14600/21770] eta: 0:05:37 time: 0.0436 data: 0.0017 max mem: 19788 +Test: [14700/21770] eta: 0:05:32 time: 0.0490 data: 0.0016 max mem: 19788 +Test: [14800/21770] eta: 0:05:28 time: 0.0442 data: 0.0016 max mem: 19788 +Test: [14900/21770] eta: 0:05:23 time: 0.0449 data: 0.0013 max mem: 19788 +Test: [15000/21770] eta: 0:05:18 time: 0.0511 data: 0.0016 max mem: 19788 +Test: [15100/21770] eta: 0:05:14 time: 0.0449 data: 0.0017 max mem: 19788 +Test: [15200/21770] eta: 0:05:09 time: 0.0462 data: 0.0017 max mem: 19788 +Test: [15300/21770] eta: 0:05:04 time: 0.0521 data: 0.0018 max mem: 19788 +Test: [15400/21770] eta: 0:04:59 time: 0.0525 data: 0.0017 max mem: 19788 +Test: [15500/21770] eta: 0:04:55 time: 0.0477 data: 0.0015 max mem: 19788 +Test: [15600/21770] eta: 0:04:50 time: 0.0447 data: 0.0017 max mem: 19788 +Test: [15700/21770] eta: 0:04:45 time: 0.0453 data: 0.0016 max mem: 19788 +Test: [15800/21770] eta: 0:04:41 time: 0.0452 data: 0.0014 max mem: 19788 +Test: [15900/21770] eta: 0:04:36 time: 0.0520 data: 0.0017 max mem: 19788 +Test: [16000/21770] eta: 0:04:31 time: 0.0439 data: 0.0014 max mem: 19788 +Test: [16100/21770] eta: 0:04:27 time: 0.0437 data: 0.0014 max mem: 19788 +Test: [16200/21770] eta: 0:04:22 time: 0.0525 data: 0.0018 max mem: 19788 +Test: [16300/21770] eta: 0:04:17 time: 0.0492 data: 0.0017 max mem: 19788 +Test: [16400/21770] eta: 0:04:12 time: 0.0443 data: 0.0014 max mem: 19788 +Test: [16500/21770] eta: 0:04:08 time: 0.0430 data: 0.0015 max mem: 19788 +Test: [16600/21770] eta: 0:04:03 time: 0.0481 data: 0.0015 max mem: 19788 +Test: [16700/21770] eta: 0:03:58 time: 0.0452 data: 0.0015 max mem: 19788 +Test: [16800/21770] eta: 0:03:54 time: 0.0444 data: 0.0013 max mem: 19788 +Test: [16900/21770] eta: 0:03:49 time: 0.0528 data: 0.0018 max mem: 19788 +Test: [17000/21770] eta: 0:03:44 time: 0.0436 data: 0.0014 max mem: 19788 +Test: [17100/21770] eta: 0:03:40 time: 0.0444 data: 0.0014 max mem: 19788 +Test: [17200/21770] eta: 0:03:35 time: 0.0452 data: 0.0016 max mem: 19788 +Test: [17300/21770] eta: 0:03:30 time: 0.0431 data: 0.0014 max mem: 19788 +Test: [17400/21770] eta: 0:03:25 time: 0.0489 data: 0.0017 max mem: 19788 +Test: [17500/21770] eta: 0:03:21 time: 0.0467 data: 0.0017 max mem: 19788 +Test: [17600/21770] eta: 0:03:16 time: 0.0557 data: 0.0017 max mem: 19788 +Test: [17700/21770] eta: 0:03:11 time: 0.0479 data: 0.0016 max mem: 19788 +Test: [17800/21770] eta: 0:03:07 time: 0.0479 data: 0.0014 max mem: 19788 +Test: [17900/21770] eta: 0:03:02 time: 0.0439 data: 0.0015 max mem: 19788 +Test: [18000/21770] eta: 0:02:57 time: 0.0451 data: 0.0016 max mem: 19788 +Test: [18100/21770] eta: 0:02:52 time: 0.0437 data: 0.0014 max mem: 19788 +Test: [18200/21770] eta: 0:02:48 time: 0.0517 data: 0.0016 max mem: 19788 +Test: [18300/21770] eta: 0:02:43 time: 0.0437 data: 0.0013 max mem: 19788 +Test: [18400/21770] eta: 0:02:38 time: 0.0433 data: 0.0015 max mem: 19788 +Test: [18500/21770] eta: 0:02:34 time: 0.0444 data: 0.0015 max mem: 19788 +Test: [18600/21770] eta: 0:02:29 time: 0.0524 data: 0.0017 max mem: 19788 +Test: [18700/21770] eta: 0:02:24 time: 0.0431 data: 0.0014 max mem: 19788 +Test: [18800/21770] eta: 0:02:19 time: 0.0467 data: 0.0013 max mem: 19788 +Test: [18900/21770] eta: 0:02:15 time: 0.0503 data: 0.0016 max mem: 19788 +Test: [19000/21770] eta: 0:02:10 time: 0.0439 data: 0.0015 max mem: 19788 +Test: [19100/21770] eta: 0:02:05 time: 0.0485 data: 0.0016 max mem: 19788 +Test: [19200/21770] eta: 0:02:00 time: 0.0474 data: 0.0016 max mem: 19788 +Test: [19300/21770] eta: 0:01:56 time: 0.0530 data: 0.0019 max mem: 19788 +Test: [19400/21770] eta: 0:01:51 time: 0.0508 data: 0.0015 max mem: 19788 +Test: [19500/21770] eta: 0:01:46 time: 0.0527 data: 0.0019 max mem: 19788 +Test: [19600/21770] eta: 0:01:42 time: 0.0468 data: 0.0016 max mem: 19788 +Test: [19700/21770] eta: 0:01:37 time: 0.0468 data: 0.0014 max mem: 19788 +Test: [19800/21770] eta: 0:01:32 time: 0.0522 data: 0.0018 max mem: 19788 +Test: [19900/21770] eta: 0:01:28 time: 0.0436 data: 0.0015 max mem: 19788 +Test: [20000/21770] eta: 0:01:23 time: 0.0473 data: 0.0014 max mem: 19788 +Test: [20100/21770] eta: 0:01:18 time: 0.0430 data: 0.0015 max mem: 19788 +Test: [20200/21770] eta: 0:01:13 time: 0.0519 data: 0.0017 max mem: 19788 +Test: [20300/21770] eta: 0:01:09 time: 0.0450 data: 0.0017 max mem: 19788 +Test: [20400/21770] eta: 0:01:04 time: 0.0438 data: 0.0013 max mem: 19788 +Test: [20500/21770] eta: 0:00:59 time: 0.0438 data: 0.0012 max mem: 19788 +Test: [20600/21770] eta: 0:00:55 time: 0.0473 data: 0.0017 max mem: 19788 +Test: [20700/21770] eta: 0:00:50 time: 0.0533 data: 0.0017 max mem: 19788 +Test: [20800/21770] eta: 0:00:45 time: 0.0434 data: 0.0016 max mem: 19788 +Test: [20900/21770] eta: 0:00:40 time: 0.0441 data: 0.0015 max mem: 19788 +Test: [21000/21770] eta: 0:00:36 time: 0.0462 data: 0.0014 max mem: 19788 +Test: [21100/21770] eta: 0:00:31 time: 0.0439 data: 0.0015 max mem: 19788 +Test: [21200/21770] eta: 0:00:26 time: 0.0447 data: 0.0015 max mem: 19788 +Test: [21300/21770] eta: 0:00:22 time: 0.0436 data: 0.0014 max mem: 19788 +Test: [21400/21770] eta: 0:00:17 time: 0.0453 data: 0.0014 max mem: 19788 +Test: [21500/21770] eta: 0:00:12 time: 0.0438 data: 0.0015 max mem: 19788 +Test: [21600/21770] eta: 0:00:08 time: 0.0492 data: 0.0014 max mem: 19788 +Test: [21700/21770] eta: 0:00:03 time: 0.0447 data: 0.0015 max mem: 19788 +Test: Total time: 0:17:05 +Final results: +Mean IoU is 63.42 + + precision@0.5 = 70.45 + precision@0.6 = 65.11 + precision@0.7 = 58.43 + precision@0.8 = 47.55 + precision@0.9 = 23.77 + overall IoU = 64.47 + mean IoU = 63.42 + +Mean accuracy for one-to-zero sample is 85.99 + +Average object IoU 0.6342063750364499 +Overall IoU 64.46617889404297 +Epoch: [20] [ 0/2138] eta: 9:08:31 lr: 2.679377260337213e-05 loss: 0.0637 (0.0637) time: 15.3938 data: 1.4334 max mem: 19788 +Epoch: [20] [ 10/2138] eta: 2:23:13 lr: 2.6788132930473424e-05 loss: 0.0296 (0.0336) time: 4.0385 data: 0.1322 max mem: 19788 +Epoch: [20] [ 20/2138] eta: 2:04:57 lr: 2.6782493125647916e-05 loss: 0.0268 (0.0301) time: 2.9470 data: 0.0021 max mem: 19788 +Epoch: [20] [ 30/2138] eta: 1:58:43 lr: 2.677685318886165e-05 loss: 0.0268 (0.0299) time: 3.0168 data: 0.0024 max mem: 19788 +Epoch: [20] [ 40/2138] eta: 1:54:15 lr: 2.6771213120080657e-05 loss: 0.0275 (0.0304) time: 2.9820 data: 0.0028 max mem: 19788 +Epoch: [20] [ 50/2138] eta: 1:51:10 lr: 2.6765572919270943e-05 loss: 0.0286 (0.0302) time: 2.9079 data: 0.0027 max mem: 19788 +Epoch: [20] [ 60/2138] eta: 1:48:55 lr: 2.6759932586398506e-05 loss: 0.0294 (0.0305) time: 2.8935 data: 0.0027 max mem: 19788 +Epoch: [20] [ 70/2138] eta: 1:47:13 lr: 2.6754292121429316e-05 loss: 0.0275 (0.0300) time: 2.8981 data: 0.0025 max mem: 19788 +Epoch: [20] [ 80/2138] eta: 1:45:46 lr: 2.674865152432935e-05 loss: 0.0269 (0.0298) time: 2.8964 data: 0.0021 max mem: 19788 +Epoch: [20] [ 90/2138] eta: 1:44:33 lr: 2.6743010795064534e-05 loss: 0.0247 (0.0291) time: 2.8940 data: 0.0023 max mem: 19788 +Epoch: [20] [ 100/2138] eta: 1:43:36 lr: 2.673736993360081e-05 loss: 0.0249 (0.0291) time: 2.9156 data: 0.0027 max mem: 19788 +Epoch: [20] [ 110/2138] eta: 1:42:48 lr: 2.6731728939904083e-05 loss: 0.0272 (0.0289) time: 2.9437 data: 0.0027 max mem: 19788 +Epoch: [20] [ 120/2138] eta: 1:41:55 lr: 2.6726087813940247e-05 loss: 0.0248 (0.0287) time: 2.9299 data: 0.0024 max mem: 19788 +Epoch: [20] [ 130/2138] eta: 1:41:03 lr: 2.6720446555675184e-05 loss: 0.0248 (0.0286) time: 2.8981 data: 0.0023 max mem: 19788 +Epoch: [20] [ 140/2138] eta: 1:40:15 lr: 2.6714805165074752e-05 loss: 0.0247 (0.0285) time: 2.8929 data: 0.0025 max mem: 19788 +Epoch: [20] [ 150/2138] eta: 1:39:31 lr: 2.6709163642104788e-05 loss: 0.0247 (0.0285) time: 2.8968 data: 0.0025 max mem: 19788 +Epoch: [20] [ 160/2138] eta: 1:38:45 lr: 2.6703521986731127e-05 loss: 0.0258 (0.0285) time: 2.8889 data: 0.0022 max mem: 19788 +Epoch: [20] [ 170/2138] eta: 1:38:03 lr: 2.6697880198919578e-05 loss: 0.0295 (0.0285) time: 2.8831 data: 0.0025 max mem: 19788 +Epoch: [20] [ 180/2138] eta: 1:37:25 lr: 2.6692238278635932e-05 loss: 0.0280 (0.0284) time: 2.9034 data: 0.0026 max mem: 19788 +Epoch: [20] [ 190/2138] eta: 1:36:56 lr: 2.6686596225845965e-05 loss: 0.0250 (0.0282) time: 2.9556 data: 0.0024 max mem: 19788 +Epoch: [20] [ 200/2138] eta: 1:36:18 lr: 2.6680954040515444e-05 loss: 0.0244 (0.0281) time: 2.9481 data: 0.0022 max mem: 19788 +Epoch: [20] [ 210/2138] eta: 1:35:40 lr: 2.6675311722610098e-05 loss: 0.0255 (0.0281) time: 2.8962 data: 0.0023 max mem: 19788 +Epoch: [20] [ 220/2138] eta: 1:35:03 lr: 2.6669669272095658e-05 loss: 0.0254 (0.0281) time: 2.8898 data: 0.0022 max mem: 19788 +Epoch: [20] [ 230/2138] eta: 1:34:29 lr: 2.6664026688937844e-05 loss: 0.0242 (0.0283) time: 2.9073 data: 0.0021 max mem: 19788 +Epoch: [20] [ 240/2138] eta: 1:33:53 lr: 2.665838397310233e-05 loss: 0.0271 (0.0282) time: 2.9099 data: 0.0024 max mem: 19788 +Epoch: [20] [ 250/2138] eta: 1:33:17 lr: 2.6652741124554804e-05 loss: 0.0271 (0.0285) time: 2.8916 data: 0.0026 max mem: 19788 +Epoch: [20] [ 260/2138] eta: 1:32:48 lr: 2.6647098143260914e-05 loss: 0.0261 (0.0285) time: 2.9292 data: 0.0025 max mem: 19788 +Epoch: [20] [ 270/2138] eta: 1:32:19 lr: 2.6641455029186312e-05 loss: 0.0261 (0.0285) time: 2.9752 data: 0.0023 max mem: 19788 +Epoch: [20] [ 280/2138] eta: 1:31:46 lr: 2.663581178229661e-05 loss: 0.0281 (0.0285) time: 2.9414 data: 0.0023 max mem: 19788 +Epoch: [20] [ 290/2138] eta: 1:31:12 lr: 2.6630168402557426e-05 loss: 0.0268 (0.0285) time: 2.8989 data: 0.0024 max mem: 19788 +Epoch: [20] [ 300/2138] eta: 1:30:37 lr: 2.6624524889934337e-05 loss: 0.0268 (0.0285) time: 2.8875 data: 0.0025 max mem: 19788 +Epoch: [20] [ 310/2138] eta: 1:30:03 lr: 2.6618881244392934e-05 loss: 0.0248 (0.0285) time: 2.8846 data: 0.0026 max mem: 19788 +Epoch: [20] [ 320/2138] eta: 1:29:32 lr: 2.6613237465898756e-05 loss: 0.0228 (0.0284) time: 2.9015 data: 0.0025 max mem: 19788 +Epoch: [20] [ 330/2138] eta: 1:29:01 lr: 2.660759355441735e-05 loss: 0.0269 (0.0285) time: 2.9222 data: 0.0023 max mem: 19788 +Epoch: [20] [ 340/2138] eta: 1:28:30 lr: 2.660194950991423e-05 loss: 0.0279 (0.0285) time: 2.9292 data: 0.0022 max mem: 19788 +Epoch: [20] [ 350/2138] eta: 1:28:09 lr: 2.6596305332354914e-05 loss: 0.0265 (0.0284) time: 3.0252 data: 0.0022 max mem: 19788 +Epoch: [20] [ 360/2138] eta: 1:27:39 lr: 2.6590661021704883e-05 loss: 0.0264 (0.0285) time: 3.0332 data: 0.0022 max mem: 19788 +Epoch: [20] [ 370/2138] eta: 1:27:06 lr: 2.6585016577929605e-05 loss: 0.0273 (0.0284) time: 2.9168 data: 0.0022 max mem: 19788 +Epoch: [20] [ 380/2138] eta: 1:26:33 lr: 2.657937200099453e-05 loss: 0.0271 (0.0284) time: 2.8904 data: 0.0022 max mem: 19788 +Epoch: [20] [ 390/2138] eta: 1:26:02 lr: 2.6573727290865107e-05 loss: 0.0248 (0.0283) time: 2.9011 data: 0.0021 max mem: 19788 +Epoch: [20] [ 400/2138] eta: 1:25:29 lr: 2.6568082447506742e-05 loss: 0.0273 (0.0284) time: 2.9004 data: 0.0022 max mem: 19788 +Epoch: [20] [ 410/2138] eta: 1:24:58 lr: 2.656243747088485e-05 loss: 0.0262 (0.0282) time: 2.8993 data: 0.0024 max mem: 19788 +Epoch: [20] [ 420/2138] eta: 1:24:30 lr: 2.65567923609648e-05 loss: 0.0235 (0.0282) time: 2.9451 data: 0.0025 max mem: 19788 +Epoch: [20] [ 430/2138] eta: 1:24:01 lr: 2.6551147117711978e-05 loss: 0.0244 (0.0283) time: 2.9807 data: 0.0024 max mem: 19788 +Epoch: [20] [ 440/2138] eta: 1:23:30 lr: 2.6545501741091716e-05 loss: 0.0258 (0.0283) time: 2.9365 data: 0.0023 max mem: 19788 +Epoch: [20] [ 450/2138] eta: 1:22:58 lr: 2.653985623106936e-05 loss: 0.0268 (0.0283) time: 2.8968 data: 0.0024 max mem: 19788 +Epoch: [20] [ 460/2138] eta: 1:22:27 lr: 2.653421058761022e-05 loss: 0.0248 (0.0283) time: 2.9051 data: 0.0023 max mem: 19788 +Epoch: [20] [ 470/2138] eta: 1:21:56 lr: 2.6528564810679608e-05 loss: 0.0250 (0.0283) time: 2.8998 data: 0.0021 max mem: 19788 +Epoch: [20] [ 480/2138] eta: 1:21:26 lr: 2.6522918900242784e-05 loss: 0.0289 (0.0286) time: 2.9086 data: 0.0023 max mem: 19788 +Epoch: [20] [ 490/2138] eta: 1:20:54 lr: 2.6517272856265025e-05 loss: 0.0289 (0.0287) time: 2.9102 data: 0.0024 max mem: 19788 +Epoch: [20] [ 500/2138] eta: 1:20:25 lr: 2.6511626678711576e-05 loss: 0.0256 (0.0287) time: 2.9157 data: 0.0022 max mem: 19788 +Epoch: [20] [ 510/2138] eta: 1:19:57 lr: 2.6505980367547666e-05 loss: 0.0232 (0.0286) time: 2.9665 data: 0.0025 max mem: 19788 +Epoch: [20] [ 520/2138] eta: 1:19:26 lr: 2.6500333922738517e-05 loss: 0.0231 (0.0286) time: 2.9441 data: 0.0028 max mem: 19788 +Epoch: [20] [ 530/2138] eta: 1:18:55 lr: 2.6494687344249308e-05 loss: 0.0265 (0.0286) time: 2.8997 data: 0.0026 max mem: 19788 +Epoch: [20] [ 540/2138] eta: 1:18:24 lr: 2.648904063204523e-05 loss: 0.0262 (0.0287) time: 2.9061 data: 0.0024 max mem: 19788 +Epoch: [20] [ 550/2138] eta: 1:17:54 lr: 2.6483393786091436e-05 loss: 0.0255 (0.0286) time: 2.9018 data: 0.0023 max mem: 19788 +Epoch: [20] [ 560/2138] eta: 1:17:23 lr: 2.6477746806353077e-05 loss: 0.0272 (0.0287) time: 2.8946 data: 0.0024 max mem: 19788 +Epoch: [20] [ 570/2138] eta: 1:16:52 lr: 2.6472099692795265e-05 loss: 0.0267 (0.0286) time: 2.9016 data: 0.0026 max mem: 19788 +Epoch: [20] [ 580/2138] eta: 1:16:26 lr: 2.6466452445383127e-05 loss: 0.0252 (0.0287) time: 2.9800 data: 0.0026 max mem: 19788 +Epoch: [20] [ 590/2138] eta: 1:16:02 lr: 2.646080506408174e-05 loss: 0.0288 (0.0287) time: 3.1065 data: 0.0025 max mem: 19788 +Epoch: [20] [ 600/2138] eta: 1:15:31 lr: 2.6455157548856187e-05 loss: 0.0288 (0.0287) time: 3.0320 data: 0.0025 max mem: 19788 +Epoch: [20] [ 610/2138] eta: 1:15:01 lr: 2.6449509899671514e-05 loss: 0.0249 (0.0287) time: 2.9088 data: 0.0025 max mem: 19788 +Epoch: [20] [ 620/2138] eta: 1:14:30 lr: 2.644386211649278e-05 loss: 0.0266 (0.0288) time: 2.8993 data: 0.0026 max mem: 19788 +Epoch: [20] [ 630/2138] eta: 1:13:59 lr: 2.6438214199284977e-05 loss: 0.0255 (0.0288) time: 2.8837 data: 0.0028 max mem: 19788 +Epoch: [20] [ 640/2138] eta: 1:13:29 lr: 2.6432566148013138e-05 loss: 0.0285 (0.0290) time: 2.8891 data: 0.0027 max mem: 19788 +Epoch: [20] [ 650/2138] eta: 1:12:58 lr: 2.6426917962642227e-05 loss: 0.0298 (0.0290) time: 2.8878 data: 0.0023 max mem: 19788 +Epoch: [20] [ 660/2138] eta: 1:12:28 lr: 2.6421269643137235e-05 loss: 0.0260 (0.0290) time: 2.9120 data: 0.0023 max mem: 19788 +Epoch: [20] [ 670/2138] eta: 1:11:59 lr: 2.6415621189463095e-05 loss: 0.0258 (0.0290) time: 2.9403 data: 0.0024 max mem: 19788 +Epoch: [20] [ 680/2138] eta: 1:11:28 lr: 2.6409972601584754e-05 loss: 0.0260 (0.0290) time: 2.9155 data: 0.0026 max mem: 19788 +Epoch: [20] [ 690/2138] eta: 1:10:58 lr: 2.640432387946712e-05 loss: 0.0260 (0.0290) time: 2.8943 data: 0.0025 max mem: 19788 +Epoch: [20] [ 700/2138] eta: 1:10:28 lr: 2.63986750230751e-05 loss: 0.0262 (0.0290) time: 2.8936 data: 0.0026 max mem: 19788 +Epoch: [20] [ 710/2138] eta: 1:09:57 lr: 2.6393026032373563e-05 loss: 0.0255 (0.0289) time: 2.8905 data: 0.0028 max mem: 19788 +Epoch: [20] [ 720/2138] eta: 1:09:27 lr: 2.6387376907327387e-05 loss: 0.0253 (0.0288) time: 2.8980 data: 0.0027 max mem: 19788 +Epoch: [20] [ 730/2138] eta: 1:08:57 lr: 2.6381727647901416e-05 loss: 0.0263 (0.0288) time: 2.8977 data: 0.0029 max mem: 19788 +Epoch: [20] [ 740/2138] eta: 1:08:28 lr: 2.6376078254060478e-05 loss: 0.0294 (0.0289) time: 2.9214 data: 0.0030 max mem: 19788 +Epoch: [20] [ 750/2138] eta: 1:08:00 lr: 2.6370428725769373e-05 loss: 0.0260 (0.0288) time: 2.9961 data: 0.0025 max mem: 19788 +Epoch: [20] [ 760/2138] eta: 1:07:30 lr: 2.6364779062992917e-05 loss: 0.0258 (0.0288) time: 2.9705 data: 0.0021 max mem: 19788 +Epoch: [20] [ 770/2138] eta: 1:07:00 lr: 2.635912926569587e-05 loss: 0.0248 (0.0288) time: 2.8956 data: 0.0024 max mem: 19788 +Epoch: [20] [ 780/2138] eta: 1:06:30 lr: 2.6353479333843e-05 loss: 0.0230 (0.0288) time: 2.8918 data: 0.0028 max mem: 19788 +Epoch: [20] [ 790/2138] eta: 1:06:00 lr: 2.6347829267399036e-05 loss: 0.0240 (0.0287) time: 2.8955 data: 0.0027 max mem: 19788 +Epoch: [20] [ 800/2138] eta: 1:05:30 lr: 2.634217906632872e-05 loss: 0.0258 (0.0287) time: 2.9020 data: 0.0024 max mem: 19788 +Epoch: [20] [ 810/2138] eta: 1:05:00 lr: 2.6336528730596743e-05 loss: 0.0274 (0.0287) time: 2.8979 data: 0.0023 max mem: 19788 +Epoch: [20] [ 820/2138] eta: 1:04:31 lr: 2.6330878260167795e-05 loss: 0.0251 (0.0287) time: 2.9534 data: 0.0021 max mem: 19788 +Epoch: [20] [ 830/2138] eta: 1:04:02 lr: 2.6325227655006557e-05 loss: 0.0235 (0.0287) time: 2.9737 data: 0.0022 max mem: 19788 +Epoch: [20] [ 840/2138] eta: 1:03:32 lr: 2.631957691507766e-05 loss: 0.0251 (0.0287) time: 2.9144 data: 0.0023 max mem: 19788 +Epoch: [20] [ 850/2138] eta: 1:03:02 lr: 2.6313926040345765e-05 loss: 0.0263 (0.0286) time: 2.8955 data: 0.0026 max mem: 19788 +Epoch: [20] [ 860/2138] eta: 1:02:32 lr: 2.630827503077547e-05 loss: 0.0262 (0.0286) time: 2.8916 data: 0.0024 max mem: 19788 +Epoch: [20] [ 870/2138] eta: 1:02:02 lr: 2.6302623886331384e-05 loss: 0.0233 (0.0286) time: 2.8906 data: 0.0020 max mem: 19788 +Epoch: [20] [ 880/2138] eta: 1:01:32 lr: 2.6296972606978083e-05 loss: 0.0246 (0.0285) time: 2.8920 data: 0.0020 max mem: 19788 +Epoch: [20] [ 890/2138] eta: 1:01:02 lr: 2.6291321192680142e-05 loss: 0.0253 (0.0285) time: 2.9002 data: 0.0021 max mem: 19788 +Epoch: [20] [ 900/2138] eta: 1:00:34 lr: 2.6285669643402093e-05 loss: 0.0251 (0.0285) time: 2.9776 data: 0.0023 max mem: 19788 +Epoch: [20] [ 910/2138] eta: 1:00:06 lr: 2.6280017959108477e-05 loss: 0.0247 (0.0285) time: 3.0126 data: 0.0023 max mem: 19788 +Epoch: [20] [ 920/2138] eta: 0:59:36 lr: 2.6274366139763795e-05 loss: 0.0248 (0.0284) time: 2.9337 data: 0.0021 max mem: 19788 +Epoch: [20] [ 930/2138] eta: 0:59:06 lr: 2.626871418533255e-05 loss: 0.0286 (0.0285) time: 2.8893 data: 0.0021 max mem: 19788 +Epoch: [20] [ 940/2138] eta: 0:58:36 lr: 2.62630620957792e-05 loss: 0.0317 (0.0285) time: 2.8968 data: 0.0022 max mem: 19788 +Epoch: [20] [ 950/2138] eta: 0:58:06 lr: 2.6257409871068227e-05 loss: 0.0278 (0.0285) time: 2.8970 data: 0.0023 max mem: 19788 +Epoch: [20] [ 960/2138] eta: 0:57:36 lr: 2.625175751116405e-05 loss: 0.0286 (0.0285) time: 2.9059 data: 0.0024 max mem: 19788 +Epoch: [20] [ 970/2138] eta: 0:57:07 lr: 2.6246105016031104e-05 loss: 0.0286 (0.0285) time: 2.9125 data: 0.0025 max mem: 19788 +Epoch: [20] [ 980/2138] eta: 0:56:38 lr: 2.6240452385633778e-05 loss: 0.0237 (0.0285) time: 2.9328 data: 0.0028 max mem: 19788 +Epoch: [20] [ 990/2138] eta: 0:56:09 lr: 2.6234799619936474e-05 loss: 0.0238 (0.0285) time: 2.9818 data: 0.0026 max mem: 19788 +Epoch: [20] [1000/2138] eta: 0:55:39 lr: 2.6229146718903546e-05 loss: 0.0247 (0.0284) time: 2.9560 data: 0.0021 max mem: 19788 +Epoch: [20] [1010/2138] eta: 0:55:10 lr: 2.6223493682499357e-05 loss: 0.0256 (0.0285) time: 2.9020 data: 0.0021 max mem: 19788 +Epoch: [20] [1020/2138] eta: 0:54:40 lr: 2.6217840510688223e-05 loss: 0.0270 (0.0284) time: 2.8989 data: 0.0022 max mem: 19788 +Epoch: [20] [1030/2138] eta: 0:54:10 lr: 2.6212187203434475e-05 loss: 0.0241 (0.0284) time: 2.9091 data: 0.0024 max mem: 19788 +Epoch: [20] [1040/2138] eta: 0:53:41 lr: 2.6206533760702395e-05 loss: 0.0278 (0.0284) time: 2.9052 data: 0.0025 max mem: 19788 +Epoch: [20] [1050/2138] eta: 0:53:11 lr: 2.620088018245627e-05 loss: 0.0263 (0.0284) time: 2.9060 data: 0.0025 max mem: 19788 +Epoch: [20] [1060/2138] eta: 0:52:42 lr: 2.6195226468660362e-05 loss: 0.0257 (0.0284) time: 2.9417 data: 0.0027 max mem: 19788 +Epoch: [20] [1070/2138] eta: 0:52:13 lr: 2.6189572619278907e-05 loss: 0.0265 (0.0284) time: 2.9815 data: 0.0027 max mem: 19788 +Epoch: [20] [1080/2138] eta: 0:51:44 lr: 2.6183918634276127e-05 loss: 0.0288 (0.0284) time: 2.9437 data: 0.0024 max mem: 19788 +Epoch: [20] [1090/2138] eta: 0:51:14 lr: 2.617826451361624e-05 loss: 0.0314 (0.0284) time: 2.8947 data: 0.0023 max mem: 19788 +Epoch: [20] [1100/2138] eta: 0:50:45 lr: 2.617261025726342e-05 loss: 0.0301 (0.0284) time: 2.9076 data: 0.0026 max mem: 19788 +Epoch: [20] [1110/2138] eta: 0:50:15 lr: 2.616695586518184e-05 loss: 0.0280 (0.0285) time: 2.9073 data: 0.0028 max mem: 19788 +Epoch: [20] [1120/2138] eta: 0:49:45 lr: 2.6161301337335658e-05 loss: 0.0283 (0.0285) time: 2.8910 data: 0.0027 max mem: 19788 +Epoch: [20] [1130/2138] eta: 0:49:16 lr: 2.615564667368901e-05 loss: 0.0283 (0.0285) time: 2.9043 data: 0.0024 max mem: 19788 +Epoch: [20] [1140/2138] eta: 0:48:47 lr: 2.614999187420601e-05 loss: 0.0279 (0.0285) time: 2.9476 data: 0.0023 max mem: 19788 +Epoch: [20] [1150/2138] eta: 0:48:17 lr: 2.6144336938850744e-05 loss: 0.0249 (0.0285) time: 2.9541 data: 0.0024 max mem: 19788 +Epoch: [20] [1160/2138] eta: 0:47:48 lr: 2.6138681867587305e-05 loss: 0.0231 (0.0285) time: 2.9171 data: 0.0022 max mem: 19788 +Epoch: [20] [1170/2138] eta: 0:47:18 lr: 2.6133026660379744e-05 loss: 0.0263 (0.0285) time: 2.9015 data: 0.0021 max mem: 19788 +Epoch: [20] [1180/2138] eta: 0:46:49 lr: 2.6127371317192118e-05 loss: 0.0268 (0.0285) time: 2.9021 data: 0.0023 max mem: 19788 +Epoch: [20] [1190/2138] eta: 0:46:19 lr: 2.6121715837988437e-05 loss: 0.0268 (0.0285) time: 2.8973 data: 0.0026 max mem: 19788 +Epoch: [20] [1200/2138] eta: 0:45:49 lr: 2.6116060222732724e-05 loss: 0.0264 (0.0285) time: 2.8918 data: 0.0027 max mem: 19788 +Epoch: [20] [1210/2138] eta: 0:45:20 lr: 2.611040447138895e-05 loss: 0.0287 (0.0286) time: 2.9063 data: 0.0025 max mem: 19788 +Epoch: [20] [1220/2138] eta: 0:44:51 lr: 2.61047485839211e-05 loss: 0.0306 (0.0286) time: 2.9379 data: 0.0023 max mem: 19788 +Epoch: [20] [1230/2138] eta: 0:44:22 lr: 2.6099092560293115e-05 loss: 0.0302 (0.0286) time: 2.9837 data: 0.0023 max mem: 19788 +Epoch: [20] [1240/2138] eta: 0:43:53 lr: 2.609343640046894e-05 loss: 0.0271 (0.0286) time: 2.9914 data: 0.0023 max mem: 19788 +Epoch: [20] [1250/2138] eta: 0:43:24 lr: 2.6087780104412484e-05 loss: 0.0229 (0.0286) time: 2.9383 data: 0.0024 max mem: 19788 +Epoch: [20] [1260/2138] eta: 0:42:54 lr: 2.608212367208765e-05 loss: 0.0248 (0.0286) time: 2.9040 data: 0.0025 max mem: 19788 +Epoch: [20] [1270/2138] eta: 0:42:24 lr: 2.6076467103458308e-05 loss: 0.0241 (0.0285) time: 2.8898 data: 0.0025 max mem: 19788 +Epoch: [20] [1280/2138] eta: 0:41:55 lr: 2.6070810398488326e-05 loss: 0.0243 (0.0285) time: 2.8826 data: 0.0024 max mem: 19788 +Epoch: [20] [1290/2138] eta: 0:41:25 lr: 2.6065153557141546e-05 loss: 0.0266 (0.0286) time: 2.8925 data: 0.0022 max mem: 19788 +Epoch: [20] [1300/2138] eta: 0:40:56 lr: 2.6059496579381797e-05 loss: 0.0294 (0.0285) time: 2.8902 data: 0.0021 max mem: 19788 +Epoch: [20] [1310/2138] eta: 0:40:26 lr: 2.6053839465172874e-05 loss: 0.0252 (0.0286) time: 2.8943 data: 0.0021 max mem: 19788 +Epoch: [20] [1320/2138] eta: 0:39:57 lr: 2.6048182214478578e-05 loss: 0.0308 (0.0286) time: 2.9630 data: 0.0020 max mem: 19788 +Epoch: [20] [1330/2138] eta: 0:39:28 lr: 2.6042524827262665e-05 loss: 0.0268 (0.0286) time: 3.0023 data: 0.0023 max mem: 19788 +Epoch: [20] [1340/2138] eta: 0:38:59 lr: 2.6036867303488897e-05 loss: 0.0268 (0.0286) time: 2.9365 data: 0.0026 max mem: 19788 +Epoch: [20] [1350/2138] eta: 0:38:29 lr: 2.6031209643121e-05 loss: 0.0305 (0.0287) time: 2.8956 data: 0.0026 max mem: 19788 +Epoch: [20] [1360/2138] eta: 0:38:00 lr: 2.602555184612269e-05 loss: 0.0290 (0.0286) time: 2.8920 data: 0.0024 max mem: 19788 +Epoch: [20] [1370/2138] eta: 0:37:30 lr: 2.6019893912457666e-05 loss: 0.0289 (0.0288) time: 2.8853 data: 0.0023 max mem: 19788 +Epoch: [20] [1380/2138] eta: 0:37:01 lr: 2.6014235842089607e-05 loss: 0.0361 (0.0289) time: 2.9081 data: 0.0021 max mem: 19788 +Epoch: [20] [1390/2138] eta: 0:36:31 lr: 2.6008577634982163e-05 loss: 0.0276 (0.0289) time: 2.9127 data: 0.0024 max mem: 19788 +Epoch: [20] [1400/2138] eta: 0:36:02 lr: 2.6002919291098983e-05 loss: 0.0247 (0.0288) time: 2.9574 data: 0.0027 max mem: 19788 +Epoch: [20] [1410/2138] eta: 0:35:33 lr: 2.5997260810403678e-05 loss: 0.0248 (0.0288) time: 2.9726 data: 0.0027 max mem: 19788 +Epoch: [20] [1420/2138] eta: 0:35:04 lr: 2.5991602192859864e-05 loss: 0.0265 (0.0288) time: 2.9076 data: 0.0025 max mem: 19788 +Epoch: [20] [1430/2138] eta: 0:34:34 lr: 2.5985943438431127e-05 loss: 0.0282 (0.0288) time: 2.8782 data: 0.0026 max mem: 19788 +Epoch: [20] [1440/2138] eta: 0:34:04 lr: 2.5980284547081026e-05 loss: 0.0296 (0.0288) time: 2.8777 data: 0.0026 max mem: 19788 +Epoch: [20] [1450/2138] eta: 0:33:35 lr: 2.597462551877311e-05 loss: 0.0290 (0.0288) time: 2.8887 data: 0.0023 max mem: 19788 +Epoch: [20] [1460/2138] eta: 0:33:05 lr: 2.596896635347091e-05 loss: 0.0260 (0.0288) time: 2.8863 data: 0.0023 max mem: 19788 +Epoch: [20] [1470/2138] eta: 0:32:36 lr: 2.5963307051137942e-05 loss: 0.0260 (0.0288) time: 2.8810 data: 0.0023 max mem: 19788 +Epoch: [20] [1480/2138] eta: 0:32:07 lr: 2.5957647611737683e-05 loss: 0.0235 (0.0288) time: 2.9333 data: 0.0023 max mem: 19788 +Epoch: [20] [1490/2138] eta: 0:31:38 lr: 2.5951988035233632e-05 loss: 0.0246 (0.0288) time: 2.9764 data: 0.0024 max mem: 19788 +Epoch: [20] [1500/2138] eta: 0:31:08 lr: 2.594632832158922e-05 loss: 0.0288 (0.0288) time: 2.9283 data: 0.0027 max mem: 19788 +Epoch: [20] [1510/2138] eta: 0:30:39 lr: 2.5940668470767898e-05 loss: 0.0298 (0.0288) time: 2.8951 data: 0.0028 max mem: 19788 +Epoch: [20] [1520/2138] eta: 0:30:09 lr: 2.5935008482733082e-05 loss: 0.0249 (0.0288) time: 2.8918 data: 0.0025 max mem: 19788 +Epoch: [20] [1530/2138] eta: 0:29:40 lr: 2.592934835744817e-05 loss: 0.0247 (0.0288) time: 2.8936 data: 0.0024 max mem: 19788 +Epoch: [20] [1540/2138] eta: 0:29:11 lr: 2.5923688094876538e-05 loss: 0.0249 (0.0288) time: 2.8998 data: 0.0025 max mem: 19788 +Epoch: [20] [1550/2138] eta: 0:28:41 lr: 2.5918027694981557e-05 loss: 0.0272 (0.0288) time: 2.8870 data: 0.0024 max mem: 19788 +Epoch: [20] [1560/2138] eta: 0:28:12 lr: 2.5912367157726557e-05 loss: 0.0276 (0.0288) time: 2.9240 data: 0.0023 max mem: 19788 +Epoch: [20] [1570/2138] eta: 0:27:43 lr: 2.5906706483074884e-05 loss: 0.0268 (0.0288) time: 2.9667 data: 0.0022 max mem: 19788 +Epoch: [20] [1580/2138] eta: 0:27:13 lr: 2.5901045670989825e-05 loss: 0.0265 (0.0288) time: 2.9257 data: 0.0020 max mem: 19788 +Epoch: [20] [1590/2138] eta: 0:26:44 lr: 2.5895384721434684e-05 loss: 0.0271 (0.0288) time: 2.8848 data: 0.0020 max mem: 19788 +Epoch: [20] [1600/2138] eta: 0:26:15 lr: 2.588972363437271e-05 loss: 0.0290 (0.0288) time: 2.8903 data: 0.0024 max mem: 19788 +Epoch: [20] [1610/2138] eta: 0:25:45 lr: 2.5884062409767175e-05 loss: 0.0281 (0.0288) time: 2.8949 data: 0.0026 max mem: 19788 +Epoch: [20] [1620/2138] eta: 0:25:16 lr: 2.5878401047581285e-05 loss: 0.0247 (0.0288) time: 2.8855 data: 0.0024 max mem: 19788 +Epoch: [20] [1630/2138] eta: 0:24:46 lr: 2.587273954777828e-05 loss: 0.0256 (0.0288) time: 2.8735 data: 0.0023 max mem: 19788 +Epoch: [20] [1640/2138] eta: 0:24:17 lr: 2.586707791032133e-05 loss: 0.0284 (0.0288) time: 2.9244 data: 0.0023 max mem: 19788 +Epoch: [20] [1650/2138] eta: 0:23:48 lr: 2.5861416135173627e-05 loss: 0.0285 (0.0288) time: 2.9638 data: 0.0026 max mem: 19788 +Epoch: [20] [1660/2138] eta: 0:23:19 lr: 2.5855754222298317e-05 loss: 0.0278 (0.0288) time: 2.9200 data: 0.0027 max mem: 19788 +Epoch: [20] [1670/2138] eta: 0:22:49 lr: 2.585009217165854e-05 loss: 0.0261 (0.0288) time: 2.8840 data: 0.0026 max mem: 19788 +Epoch: [20] [1680/2138] eta: 0:22:20 lr: 2.5844429983217416e-05 loss: 0.0258 (0.0288) time: 2.8858 data: 0.0027 max mem: 19788 +Epoch: [20] [1690/2138] eta: 0:21:51 lr: 2.5838767656938046e-05 loss: 0.0266 (0.0288) time: 2.9010 data: 0.0029 max mem: 19788 +Epoch: [20] [1700/2138] eta: 0:21:21 lr: 2.58331051927835e-05 loss: 0.0272 (0.0287) time: 2.8965 data: 0.0029 max mem: 19788 +Epoch: [20] [1710/2138] eta: 0:20:52 lr: 2.5827442590716855e-05 loss: 0.0248 (0.0287) time: 2.8865 data: 0.0030 max mem: 19788 +Epoch: [20] [1720/2138] eta: 0:20:23 lr: 2.5821779850701145e-05 loss: 0.0248 (0.0287) time: 2.9112 data: 0.0028 max mem: 19788 +Epoch: [20] [1730/2138] eta: 0:19:54 lr: 2.5816116972699394e-05 loss: 0.0273 (0.0287) time: 2.9815 data: 0.0025 max mem: 19788 +Epoch: [20] [1740/2138] eta: 0:19:24 lr: 2.5810453956674614e-05 loss: 0.0273 (0.0287) time: 2.9893 data: 0.0022 max mem: 19788 +Epoch: [20] [1750/2138] eta: 0:18:55 lr: 2.580479080258978e-05 loss: 0.0263 (0.0287) time: 2.9167 data: 0.0022 max mem: 19788 +Epoch: [20] [1760/2138] eta: 0:18:26 lr: 2.5799127510407867e-05 loss: 0.0263 (0.0287) time: 2.8875 data: 0.0026 max mem: 19788 +Epoch: [20] [1770/2138] eta: 0:17:56 lr: 2.5793464080091818e-05 loss: 0.0238 (0.0287) time: 2.8859 data: 0.0027 max mem: 19788 +Epoch: [20] [1780/2138] eta: 0:17:27 lr: 2.578780051160457e-05 loss: 0.0234 (0.0286) time: 2.8812 data: 0.0023 max mem: 19788 +Epoch: [20] [1790/2138] eta: 0:16:58 lr: 2.5782136804909023e-05 loss: 0.0259 (0.0287) time: 2.8896 data: 0.0024 max mem: 19788 +Epoch: [20] [1800/2138] eta: 0:16:28 lr: 2.5776472959968084e-05 loss: 0.0324 (0.0287) time: 2.9078 data: 0.0028 max mem: 19788 +Epoch: [20] [1810/2138] eta: 0:15:59 lr: 2.577080897674461e-05 loss: 0.0313 (0.0287) time: 3.0003 data: 0.0026 max mem: 19788 +Epoch: [20] [1820/2138] eta: 0:15:30 lr: 2.5765144855201457e-05 loss: 0.0251 (0.0287) time: 3.0029 data: 0.0026 max mem: 19788 +Epoch: [20] [1830/2138] eta: 0:15:01 lr: 2.5759480595301462e-05 loss: 0.0251 (0.0287) time: 2.9095 data: 0.0028 max mem: 19788 +Epoch: [20] [1840/2138] eta: 0:14:31 lr: 2.575381619700744e-05 loss: 0.0267 (0.0287) time: 2.8873 data: 0.0027 max mem: 19788 +Epoch: [20] [1850/2138] eta: 0:14:02 lr: 2.5748151660282187e-05 loss: 0.0267 (0.0287) time: 2.8852 data: 0.0024 max mem: 19788 +Epoch: [20] [1860/2138] eta: 0:13:33 lr: 2.574248698508848e-05 loss: 0.0267 (0.0287) time: 2.8904 data: 0.0021 max mem: 19788 +Epoch: [20] [1870/2138] eta: 0:13:04 lr: 2.5736822171389074e-05 loss: 0.0282 (0.0287) time: 2.8943 data: 0.0023 max mem: 19788 +Epoch: [20] [1880/2138] eta: 0:12:34 lr: 2.5731157219146713e-05 loss: 0.0250 (0.0287) time: 2.9008 data: 0.0023 max mem: 19788 +Epoch: [20] [1890/2138] eta: 0:12:05 lr: 2.5725492128324107e-05 loss: 0.0231 (0.0287) time: 2.9605 data: 0.0025 max mem: 19788 +Epoch: [20] [1900/2138] eta: 0:11:36 lr: 2.5719826898883962e-05 loss: 0.0270 (0.0287) time: 3.0104 data: 0.0028 max mem: 19788 +Epoch: [20] [1910/2138] eta: 0:11:07 lr: 2.5714161530788967e-05 loss: 0.0248 (0.0287) time: 2.9513 data: 0.0029 max mem: 19788 +Epoch: [20] [1920/2138] eta: 0:10:37 lr: 2.570849602400177e-05 loss: 0.0239 (0.0286) time: 2.8984 data: 0.0026 max mem: 19788 +Epoch: [20] [1930/2138] eta: 0:10:08 lr: 2.570283037848502e-05 loss: 0.0256 (0.0286) time: 2.8953 data: 0.0022 max mem: 19788 +Epoch: [20] [1940/2138] eta: 0:09:39 lr: 2.5697164594201344e-05 loss: 0.0276 (0.0286) time: 2.8890 data: 0.0021 max mem: 19788 +Epoch: [20] [1950/2138] eta: 0:09:09 lr: 2.569149867111334e-05 loss: 0.0252 (0.0286) time: 2.8873 data: 0.0022 max mem: 19788 +Epoch: [20] [1960/2138] eta: 0:08:40 lr: 2.5685832609183604e-05 loss: 0.0249 (0.0286) time: 2.8984 data: 0.0022 max mem: 19788 +Epoch: [20] [1970/2138] eta: 0:08:11 lr: 2.5680166408374685e-05 loss: 0.0243 (0.0286) time: 2.9437 data: 0.0025 max mem: 19788 +Epoch: [20] [1980/2138] eta: 0:07:42 lr: 2.5674500068649143e-05 loss: 0.0249 (0.0286) time: 2.9621 data: 0.0024 max mem: 19788 +Epoch: [20] [1990/2138] eta: 0:07:12 lr: 2.5668833589969494e-05 loss: 0.0257 (0.0286) time: 2.9088 data: 0.0020 max mem: 19788 +Epoch: [20] [2000/2138] eta: 0:06:43 lr: 2.5663166972298257e-05 loss: 0.0254 (0.0286) time: 2.8809 data: 0.0020 max mem: 19788 +Epoch: [20] [2010/2138] eta: 0:06:14 lr: 2.5657500215597918e-05 loss: 0.0285 (0.0286) time: 2.8861 data: 0.0024 max mem: 19788 +Epoch: [20] [2020/2138] eta: 0:05:45 lr: 2.565183331983094e-05 loss: 0.0285 (0.0286) time: 2.8877 data: 0.0026 max mem: 19788 +Epoch: [20] [2030/2138] eta: 0:05:15 lr: 2.5646166284959782e-05 loss: 0.0280 (0.0286) time: 2.8870 data: 0.0026 max mem: 19788 +Epoch: [20] [2040/2138] eta: 0:04:46 lr: 2.564049911094687e-05 loss: 0.0253 (0.0286) time: 2.8825 data: 0.0025 max mem: 19788 +Epoch: [20] [2050/2138] eta: 0:04:17 lr: 2.5634831797754616e-05 loss: 0.0254 (0.0286) time: 2.9776 data: 0.0025 max mem: 19788 +Epoch: [20] [2060/2138] eta: 0:03:48 lr: 2.5629164345345402e-05 loss: 0.0255 (0.0286) time: 3.0272 data: 0.0025 max mem: 19788 +Epoch: [20] [2070/2138] eta: 0:03:18 lr: 2.562349675368162e-05 loss: 0.0257 (0.0286) time: 2.9409 data: 0.0024 max mem: 19788 +Epoch: [20] [2080/2138] eta: 0:02:49 lr: 2.5617829022725603e-05 loss: 0.0252 (0.0286) time: 2.8936 data: 0.0024 max mem: 19788 +Epoch: [20] [2090/2138] eta: 0:02:20 lr: 2.56121611524397e-05 loss: 0.0252 (0.0286) time: 2.8820 data: 0.0022 max mem: 19788 +Epoch: [20] [2100/2138] eta: 0:01:51 lr: 2.560649314278622e-05 loss: 0.0286 (0.0286) time: 2.8803 data: 0.0022 max mem: 19788 +Epoch: [20] [2110/2138] eta: 0:01:21 lr: 2.5600824993727456e-05 loss: 0.0328 (0.0286) time: 2.8847 data: 0.0024 max mem: 19788 +Epoch: [20] [2120/2138] eta: 0:00:52 lr: 2.5595156705225674e-05 loss: 0.0308 (0.0286) time: 2.8846 data: 0.0025 max mem: 19788 +Epoch: [20] [2130/2138] eta: 0:00:23 lr: 2.5589488277243157e-05 loss: 0.0277 (0.0286) time: 2.9458 data: 0.0023 max mem: 19788 +Epoch: [20] Total time: 1:44:14 +Test: [ 0/21770] eta: 16:44:32 time: 2.7686 data: 2.6636 max mem: 19788 +Test: [ 100/21770] eta: 0:29:19 time: 0.0529 data: 0.0019 max mem: 19788 +Test: [ 200/21770] eta: 0:22:33 time: 0.0446 data: 0.0015 max mem: 19788 +Test: [ 300/21770] eta: 0:20:24 time: 0.0430 data: 0.0013 max mem: 19788 +Test: [ 400/21770] eta: 0:19:10 time: 0.0430 data: 0.0015 max mem: 19788 +Test: [ 500/21770] eta: 0:18:35 time: 0.0452 data: 0.0015 max mem: 19788 +Test: [ 600/21770] eta: 0:18:04 time: 0.0485 data: 0.0016 max mem: 19788 +Test: [ 700/21770] eta: 0:17:40 time: 0.0431 data: 0.0016 max mem: 19788 +Test: [ 800/21770] eta: 0:17:32 time: 0.0519 data: 0.0014 max mem: 19788 +Test: [ 900/21770] eta: 0:17:18 time: 0.0457 data: 0.0017 max mem: 19788 +Test: [ 1000/21770] eta: 0:17:01 time: 0.0426 data: 0.0016 max mem: 19788 +Test: [ 1100/21770] eta: 0:16:46 time: 0.0456 data: 0.0014 max mem: 19788 +Test: [ 1200/21770] eta: 0:16:37 time: 0.0481 data: 0.0016 max mem: 19788 +Test: [ 1300/21770] eta: 0:16:27 time: 0.0435 data: 0.0015 max mem: 19788 +Test: [ 1400/21770] eta: 0:16:22 time: 0.0520 data: 0.0018 max mem: 19788 +Test: [ 1500/21770] eta: 0:16:13 time: 0.0464 data: 0.0016 max mem: 19788 +Test: [ 1600/21770] eta: 0:16:10 time: 0.0489 data: 0.0015 max mem: 19788 +Test: [ 1700/21770] eta: 0:16:07 time: 0.0426 data: 0.0016 max mem: 19788 +Test: [ 1800/21770] eta: 0:15:56 time: 0.0430 data: 0.0015 max mem: 19788 +Test: [ 1900/21770] eta: 0:15:46 time: 0.0425 data: 0.0015 max mem: 19788 +Test: [ 2000/21770] eta: 0:15:38 time: 0.0448 data: 0.0016 max mem: 19788 +Test: [ 2100/21770] eta: 0:15:35 time: 0.0516 data: 0.0018 max mem: 19788 +Test: [ 2200/21770] eta: 0:15:28 time: 0.0489 data: 0.0016 max mem: 19788 +Test: [ 2300/21770] eta: 0:15:24 time: 0.0499 data: 0.0016 max mem: 19788 +Test: [ 2400/21770] eta: 0:15:19 time: 0.0524 data: 0.0018 max mem: 19788 +Test: [ 2500/21770] eta: 0:15:14 time: 0.0441 data: 0.0013 max mem: 19788 +Test: [ 2600/21770] eta: 0:15:08 time: 0.0443 data: 0.0016 max mem: 19788 +Test: [ 2700/21770] eta: 0:15:01 time: 0.0440 data: 0.0016 max mem: 19788 +Test: [ 2800/21770] eta: 0:14:54 time: 0.0448 data: 0.0013 max mem: 19788 +Test: [ 2900/21770] eta: 0:14:50 time: 0.0455 data: 0.0016 max mem: 19788 +Test: [ 3000/21770] eta: 0:14:49 time: 0.0526 data: 0.0018 max mem: 19788 +Test: [ 3100/21770] eta: 0:14:44 time: 0.0448 data: 0.0016 max mem: 19788 +Test: [ 3200/21770] eta: 0:14:41 time: 0.0522 data: 0.0017 max mem: 19788 +Test: [ 3300/21770] eta: 0:14:37 time: 0.0484 data: 0.0016 max mem: 19788 +Test: [ 3400/21770] eta: 0:14:31 time: 0.0488 data: 0.0015 max mem: 19788 +Test: [ 3500/21770] eta: 0:14:28 time: 0.0491 data: 0.0017 max mem: 19788 +Test: [ 3600/21770] eta: 0:14:23 time: 0.0497 data: 0.0017 max mem: 19788 +Test: [ 3700/21770] eta: 0:14:19 time: 0.0497 data: 0.0016 max mem: 19788 +Test: [ 3800/21770] eta: 0:14:13 time: 0.0453 data: 0.0015 max mem: 19788 +Test: [ 3900/21770] eta: 0:14:09 time: 0.0470 data: 0.0016 max mem: 19788 +Test: [ 4000/21770] eta: 0:14:03 time: 0.0452 data: 0.0013 max mem: 19788 +Test: [ 4100/21770] eta: 0:14:00 time: 0.0496 data: 0.0016 max mem: 19788 +Test: [ 4200/21770] eta: 0:13:55 time: 0.0528 data: 0.0018 max mem: 19788 +Test: [ 4300/21770] eta: 0:13:50 time: 0.0439 data: 0.0014 max mem: 19788 +Test: [ 4400/21770] eta: 0:13:44 time: 0.0450 data: 0.0014 max mem: 19788 +Test: [ 4500/21770] eta: 0:13:38 time: 0.0451 data: 0.0014 max mem: 19788 +Test: [ 4600/21770] eta: 0:13:34 time: 0.0458 data: 0.0016 max mem: 19788 +Test: [ 4700/21770] eta: 0:13:28 time: 0.0438 data: 0.0014 max mem: 19788 +Test: [ 4800/21770] eta: 0:13:22 time: 0.0432 data: 0.0014 max mem: 19788 +Test: [ 4900/21770] eta: 0:13:17 time: 0.0512 data: 0.0017 max mem: 19788 +Test: [ 5000/21770] eta: 0:13:13 time: 0.0439 data: 0.0013 max mem: 19788 +Test: [ 5100/21770] eta: 0:13:07 time: 0.0447 data: 0.0017 max mem: 19788 +Test: [ 5200/21770] eta: 0:13:03 time: 0.0519 data: 0.0018 max mem: 19788 +Test: [ 5300/21770] eta: 0:12:58 time: 0.0438 data: 0.0016 max mem: 19788 +Test: [ 5400/21770] eta: 0:12:54 time: 0.0528 data: 0.0018 max mem: 19788 +Test: [ 5500/21770] eta: 0:12:50 time: 0.0522 data: 0.0018 max mem: 19788 +Test: [ 5600/21770] eta: 0:12:45 time: 0.0505 data: 0.0016 max mem: 19788 +Test: [ 5700/21770] eta: 0:12:40 time: 0.0448 data: 0.0016 max mem: 19788 +Test: [ 5800/21770] eta: 0:12:35 time: 0.0457 data: 0.0015 max mem: 19788 +Test: [ 5900/21770] eta: 0:12:30 time: 0.0441 data: 0.0015 max mem: 19788 +Test: [ 6000/21770] eta: 0:12:25 time: 0.0432 data: 0.0017 max mem: 19788 +Test: [ 6100/21770] eta: 0:12:19 time: 0.0429 data: 0.0014 max mem: 19788 +Test: [ 6200/21770] eta: 0:12:15 time: 0.0443 data: 0.0014 max mem: 19788 +Test: [ 6300/21770] eta: 0:12:10 time: 0.0524 data: 0.0014 max mem: 19788 +Test: [ 6400/21770] eta: 0:12:04 time: 0.0428 data: 0.0014 max mem: 19788 +Test: [ 6500/21770] eta: 0:11:59 time: 0.0458 data: 0.0015 max mem: 19788 +Test: [ 6600/21770] eta: 0:11:54 time: 0.0481 data: 0.0016 max mem: 19788 +Test: [ 6700/21770] eta: 0:11:49 time: 0.0537 data: 0.0015 max mem: 19788 +Test: [ 6800/21770] eta: 0:11:45 time: 0.0434 data: 0.0015 max mem: 19788 +Test: [ 6900/21770] eta: 0:11:40 time: 0.0438 data: 0.0014 max mem: 19788 +Test: [ 7000/21770] eta: 0:11:36 time: 0.0526 data: 0.0018 max mem: 19788 +Test: [ 7100/21770] eta: 0:11:31 time: 0.0476 data: 0.0016 max mem: 19788 +Test: [ 7200/21770] eta: 0:11:26 time: 0.0541 data: 0.0018 max mem: 19788 +Test: [ 7300/21770] eta: 0:11:21 time: 0.0441 data: 0.0014 max mem: 19788 +Test: [ 7400/21770] eta: 0:11:16 time: 0.0513 data: 0.0018 max mem: 19788 +Test: [ 7500/21770] eta: 0:11:11 time: 0.0470 data: 0.0015 max mem: 19788 +Test: [ 7600/21770] eta: 0:11:07 time: 0.0431 data: 0.0015 max mem: 19788 +Test: [ 7700/21770] eta: 0:11:02 time: 0.0441 data: 0.0013 max mem: 19788 +Test: [ 7800/21770] eta: 0:10:57 time: 0.0487 data: 0.0014 max mem: 19788 +Test: [ 7900/21770] eta: 0:10:52 time: 0.0480 data: 0.0017 max mem: 19788 +Test: [ 8000/21770] eta: 0:10:48 time: 0.0512 data: 0.0015 max mem: 19788 +Test: [ 8100/21770] eta: 0:10:44 time: 0.0460 data: 0.0014 max mem: 19788 +Test: [ 8200/21770] eta: 0:10:39 time: 0.0449 data: 0.0015 max mem: 19788 +Test: [ 8300/21770] eta: 0:10:34 time: 0.0456 data: 0.0018 max mem: 19788 +Test: [ 8400/21770] eta: 0:10:30 time: 0.0509 data: 0.0016 max mem: 19788 +Test: [ 8500/21770] eta: 0:10:26 time: 0.0463 data: 0.0018 max mem: 19788 +Test: [ 8600/21770] eta: 0:10:21 time: 0.0510 data: 0.0015 max mem: 19788 +Test: [ 8700/21770] eta: 0:10:16 time: 0.0439 data: 0.0014 max mem: 19788 +Test: [ 8800/21770] eta: 0:10:12 time: 0.0437 data: 0.0015 max mem: 19788 +Test: [ 8900/21770] eta: 0:10:07 time: 0.0490 data: 0.0016 max mem: 19788 +Test: [ 9000/21770] eta: 0:10:02 time: 0.0430 data: 0.0014 max mem: 19788 +Test: [ 9100/21770] eta: 0:09:57 time: 0.0440 data: 0.0016 max mem: 19788 +Test: [ 9200/21770] eta: 0:09:53 time: 0.0525 data: 0.0018 max mem: 19788 +Test: [ 9300/21770] eta: 0:09:48 time: 0.0437 data: 0.0016 max mem: 19788 +Test: [ 9400/21770] eta: 0:09:43 time: 0.0479 data: 0.0017 max mem: 19788 +Test: [ 9500/21770] eta: 0:09:38 time: 0.0431 data: 0.0014 max mem: 19788 +Test: [ 9600/21770] eta: 0:09:33 time: 0.0440 data: 0.0015 max mem: 19788 +Test: [ 9700/21770] eta: 0:09:28 time: 0.0433 data: 0.0017 max mem: 19788 +Test: [ 9800/21770] eta: 0:09:24 time: 0.0546 data: 0.0015 max mem: 19788 +Test: [ 9900/21770] eta: 0:09:19 time: 0.0454 data: 0.0016 max mem: 19788 +Test: [10000/21770] eta: 0:09:15 time: 0.0455 data: 0.0015 max mem: 19788 +Test: [10100/21770] eta: 0:09:10 time: 0.0446 data: 0.0017 max mem: 19788 +Test: [10200/21770] eta: 0:09:06 time: 0.0540 data: 0.0018 max mem: 19788 +Test: [10300/21770] eta: 0:09:01 time: 0.0442 data: 0.0015 max mem: 19788 +Test: [10400/21770] eta: 0:08:56 time: 0.0452 data: 0.0014 max mem: 19788 +Test: [10500/21770] eta: 0:08:52 time: 0.0505 data: 0.0017 max mem: 19788 +Test: [10600/21770] eta: 0:08:47 time: 0.0467 data: 0.0015 max mem: 19788 +Test: [10700/21770] eta: 0:08:42 time: 0.0439 data: 0.0016 max mem: 19788 +Test: [10800/21770] eta: 0:08:38 time: 0.0486 data: 0.0015 max mem: 19788 +Test: [10900/21770] eta: 0:08:33 time: 0.0439 data: 0.0014 max mem: 19788 +Test: [11000/21770] eta: 0:08:28 time: 0.0443 data: 0.0014 max mem: 19788 +Test: [11100/21770] eta: 0:08:23 time: 0.0449 data: 0.0014 max mem: 19788 +Test: [11200/21770] eta: 0:08:18 time: 0.0528 data: 0.0018 max mem: 19788 +Test: [11300/21770] eta: 0:08:14 time: 0.0453 data: 0.0014 max mem: 19788 +Test: [11400/21770] eta: 0:08:09 time: 0.0515 data: 0.0016 max mem: 19788 +Test: [11500/21770] eta: 0:08:04 time: 0.0457 data: 0.0017 max mem: 19788 +Test: [11600/21770] eta: 0:08:00 time: 0.0520 data: 0.0017 max mem: 19788 +Test: [11700/21770] eta: 0:07:55 time: 0.0499 data: 0.0017 max mem: 19788 +Test: [11800/21770] eta: 0:07:51 time: 0.0431 data: 0.0014 max mem: 19788 +Test: [11900/21770] eta: 0:07:46 time: 0.0450 data: 0.0016 max mem: 19788 +Test: [12000/21770] eta: 0:07:41 time: 0.0438 data: 0.0014 max mem: 19788 +Test: [12100/21770] eta: 0:07:36 time: 0.0456 data: 0.0013 max mem: 19788 +Test: [12200/21770] eta: 0:07:32 time: 0.0486 data: 0.0016 max mem: 19788 +Test: [12300/21770] eta: 0:07:27 time: 0.0458 data: 0.0015 max mem: 19788 +Test: [12400/21770] eta: 0:07:22 time: 0.0440 data: 0.0016 max mem: 19788 +Test: [12500/21770] eta: 0:07:17 time: 0.0445 data: 0.0014 max mem: 19788 +Test: [12600/21770] eta: 0:07:12 time: 0.0442 data: 0.0015 max mem: 19788 +Test: [12700/21770] eta: 0:07:08 time: 0.0518 data: 0.0017 max mem: 19788 +Test: [12800/21770] eta: 0:07:03 time: 0.0518 data: 0.0017 max mem: 19788 +Test: [12900/21770] eta: 0:06:58 time: 0.0500 data: 0.0017 max mem: 19788 +Test: [13000/21770] eta: 0:06:54 time: 0.0521 data: 0.0016 max mem: 19788 +Test: [13100/21770] eta: 0:06:49 time: 0.0470 data: 0.0015 max mem: 19788 +Test: [13200/21770] eta: 0:06:44 time: 0.0439 data: 0.0015 max mem: 19788 +Test: [13300/21770] eta: 0:06:39 time: 0.0450 data: 0.0014 max mem: 19788 +Test: [13400/21770] eta: 0:06:34 time: 0.0446 data: 0.0015 max mem: 19788 +Test: [13500/21770] eta: 0:06:30 time: 0.0463 data: 0.0015 max mem: 19788 +Test: [13600/21770] eta: 0:06:25 time: 0.0441 data: 0.0014 max mem: 19788 +Test: [13700/21770] eta: 0:06:20 time: 0.0437 data: 0.0015 max mem: 19788 +Test: [13800/21770] eta: 0:06:15 time: 0.0467 data: 0.0016 max mem: 19788 +Test: [13900/21770] eta: 0:06:10 time: 0.0473 data: 0.0016 max mem: 19788 +Test: [14000/21770] eta: 0:06:06 time: 0.0525 data: 0.0019 max mem: 19788 +Test: [14100/21770] eta: 0:06:01 time: 0.0444 data: 0.0015 max mem: 19788 +Test: [14200/21770] eta: 0:05:56 time: 0.0436 data: 0.0016 max mem: 19788 +Test: [14300/21770] eta: 0:05:52 time: 0.0521 data: 0.0017 max mem: 19788 +Test: [14400/21770] eta: 0:05:47 time: 0.0441 data: 0.0016 max mem: 19788 +Test: [14500/21770] eta: 0:05:42 time: 0.0454 data: 0.0015 max mem: 19788 +Test: [14600/21770] eta: 0:05:37 time: 0.0436 data: 0.0014 max mem: 19788 +Test: [14700/21770] eta: 0:05:33 time: 0.0510 data: 0.0016 max mem: 19788 +Test: [14800/21770] eta: 0:05:28 time: 0.0507 data: 0.0018 max mem: 19788 +Test: [14900/21770] eta: 0:05:23 time: 0.0445 data: 0.0015 max mem: 19788 +Test: [15000/21770] eta: 0:05:19 time: 0.0456 data: 0.0014 max mem: 19788 +Test: [15100/21770] eta: 0:05:14 time: 0.0535 data: 0.0019 max mem: 19788 +Test: [15200/21770] eta: 0:05:09 time: 0.0467 data: 0.0015 max mem: 19788 +Test: [15300/21770] eta: 0:05:05 time: 0.0431 data: 0.0014 max mem: 19788 +Test: [15400/21770] eta: 0:05:00 time: 0.0514 data: 0.0015 max mem: 19788 +Test: [15500/21770] eta: 0:04:55 time: 0.0461 data: 0.0016 max mem: 19788 +Test: [15600/21770] eta: 0:04:50 time: 0.0509 data: 0.0017 max mem: 19788 +Test: [15700/21770] eta: 0:04:46 time: 0.0459 data: 0.0016 max mem: 19788 +Test: [15800/21770] eta: 0:04:41 time: 0.0446 data: 0.0015 max mem: 19788 +Test: [15900/21770] eta: 0:04:36 time: 0.0436 data: 0.0014 max mem: 19788 +Test: [16000/21770] eta: 0:04:31 time: 0.0483 data: 0.0015 max mem: 19788 +Test: [16100/21770] eta: 0:04:27 time: 0.0518 data: 0.0018 max mem: 19788 +Test: [16200/21770] eta: 0:04:22 time: 0.0461 data: 0.0015 max mem: 19788 +Test: [16300/21770] eta: 0:04:17 time: 0.0429 data: 0.0015 max mem: 19788 +Test: [16400/21770] eta: 0:04:12 time: 0.0521 data: 0.0017 max mem: 19788 +Test: [16500/21770] eta: 0:04:08 time: 0.0524 data: 0.0019 max mem: 19788 +Test: [16600/21770] eta: 0:04:03 time: 0.0499 data: 0.0016 max mem: 19788 +Test: [16700/21770] eta: 0:03:58 time: 0.0463 data: 0.0016 max mem: 19788 +Test: [16800/21770] eta: 0:03:54 time: 0.0436 data: 0.0013 max mem: 19788 +Test: [16900/21770] eta: 0:03:49 time: 0.0437 data: 0.0015 max mem: 19788 +Test: [17000/21770] eta: 0:03:44 time: 0.0520 data: 0.0017 max mem: 19788 +Test: [17100/21770] eta: 0:03:39 time: 0.0506 data: 0.0016 max mem: 19788 +Test: [17200/21770] eta: 0:03:35 time: 0.0430 data: 0.0014 max mem: 19788 +Test: [17300/21770] eta: 0:03:30 time: 0.0428 data: 0.0015 max mem: 19788 +Test: [17400/21770] eta: 0:03:25 time: 0.0472 data: 0.0017 max mem: 19788 +Test: [17500/21770] eta: 0:03:21 time: 0.0494 data: 0.0014 max mem: 19788 +Test: [17600/21770] eta: 0:03:16 time: 0.0437 data: 0.0014 max mem: 19788 +Test: [17700/21770] eta: 0:03:11 time: 0.0432 data: 0.0013 max mem: 19788 +Test: [17800/21770] eta: 0:03:06 time: 0.0511 data: 0.0017 max mem: 19788 +Test: [17900/21770] eta: 0:03:02 time: 0.0530 data: 0.0016 max mem: 19788 +Test: [18000/21770] eta: 0:02:57 time: 0.0493 data: 0.0016 max mem: 19788 +Test: [18100/21770] eta: 0:02:52 time: 0.0521 data: 0.0015 max mem: 19788 +Test: [18200/21770] eta: 0:02:48 time: 0.0433 data: 0.0015 max mem: 19788 +Test: [18300/21770] eta: 0:02:43 time: 0.0440 data: 0.0015 max mem: 19788 +Test: [18400/21770] eta: 0:02:38 time: 0.0429 data: 0.0014 max mem: 19788 +Test: [18500/21770] eta: 0:02:33 time: 0.0507 data: 0.0014 max mem: 19788 +Test: [18600/21770] eta: 0:02:29 time: 0.0439 data: 0.0015 max mem: 19788 +Test: [18700/21770] eta: 0:02:24 time: 0.0429 data: 0.0014 max mem: 19788 +Test: [18800/21770] eta: 0:02:19 time: 0.0438 data: 0.0013 max mem: 19788 +Test: [18900/21770] eta: 0:02:14 time: 0.0523 data: 0.0016 max mem: 19788 +Test: [19000/21770] eta: 0:02:10 time: 0.0429 data: 0.0015 max mem: 19788 +Test: [19100/21770] eta: 0:02:05 time: 0.0461 data: 0.0014 max mem: 19788 +Test: [19200/21770] eta: 0:02:00 time: 0.0509 data: 0.0015 max mem: 19788 +Test: [19300/21770] eta: 0:01:56 time: 0.0440 data: 0.0014 max mem: 19788 +Test: [19400/21770] eta: 0:01:51 time: 0.0530 data: 0.0017 max mem: 19788 +Test: [19500/21770] eta: 0:01:46 time: 0.0533 data: 0.0018 max mem: 19788 +Test: [19600/21770] eta: 0:01:42 time: 0.0488 data: 0.0017 max mem: 19788 +Test: [19700/21770] eta: 0:01:37 time: 0.0527 data: 0.0018 max mem: 19788 +Test: [19800/21770] eta: 0:01:32 time: 0.0451 data: 0.0017 max mem: 19788 +Test: [19900/21770] eta: 0:01:28 time: 0.0530 data: 0.0018 max mem: 19788 +Test: [20000/21770] eta: 0:01:23 time: 0.0508 data: 0.0018 max mem: 19788 +Test: [20100/21770] eta: 0:01:18 time: 0.0442 data: 0.0013 max mem: 19788 +Test: [20200/21770] eta: 0:01:14 time: 0.0526 data: 0.0018 max mem: 19788 +Test: [20300/21770] eta: 0:01:09 time: 0.0470 data: 0.0015 max mem: 19788 +Test: [20400/21770] eta: 0:01:04 time: 0.0525 data: 0.0017 max mem: 19788 +Test: [20500/21770] eta: 0:00:59 time: 0.0435 data: 0.0014 max mem: 19788 +Test: [20600/21770] eta: 0:00:55 time: 0.0414 data: 0.0014 max mem: 19788 +Test: [20700/21770] eta: 0:00:50 time: 0.0425 data: 0.0014 max mem: 19788 +Test: [20800/21770] eta: 0:00:45 time: 0.0437 data: 0.0013 max mem: 19788 +Test: [20900/21770] eta: 0:00:41 time: 0.0432 data: 0.0016 max mem: 19788 +Test: [21000/21770] eta: 0:00:36 time: 0.0448 data: 0.0016 max mem: 19788 +Test: [21100/21770] eta: 0:00:31 time: 0.0500 data: 0.0015 max mem: 19788 +Test: [21200/21770] eta: 0:00:26 time: 0.0490 data: 0.0015 max mem: 19788 +Test: [21300/21770] eta: 0:00:22 time: 0.0432 data: 0.0015 max mem: 19788 +Test: [21400/21770] eta: 0:00:17 time: 0.0485 data: 0.0015 max mem: 19788 +Test: [21500/21770] eta: 0:00:12 time: 0.0469 data: 0.0016 max mem: 19788 +Test: [21600/21770] eta: 0:00:08 time: 0.0509 data: 0.0018 max mem: 19788 +Test: [21700/21770] eta: 0:00:03 time: 0.0442 data: 0.0014 max mem: 19788 +Test: Total time: 0:17:05 +Final results: +Mean IoU is 63.91 + + precision@0.5 = 70.95 + precision@0.6 = 65.61 + precision@0.7 = 58.67 + precision@0.8 = 48.11 + precision@0.9 = 23.95 + overall IoU = 64.51 + mean IoU = 63.91 + +Mean accuracy for one-to-zero sample is 85.69 + +Average object IoU 0.6390997810890765 +Overall IoU 64.51356506347656 +Epoch: [21] [ 0/2138] eta: 11:50:55 lr: 2.5584953434405612e-05 loss: 0.0328 (0.0328) time: 19.9511 data: 1.4282 max mem: 19788 +Epoch: [21] [ 10/2138] eta: 2:37:20 lr: 2.557928475526255e-05 loss: 0.0249 (0.0267) time: 4.4362 data: 0.1328 max mem: 19788 +Epoch: [21] [ 20/2138] eta: 2:10:30 lr: 2.5573615936532952e-05 loss: 0.0241 (0.0256) time: 2.8843 data: 0.0023 max mem: 19788 +Epoch: [21] [ 30/2138] eta: 2:00:40 lr: 2.5567946978178993e-05 loss: 0.0260 (0.0267) time: 2.8837 data: 0.0022 max mem: 19788 +Epoch: [21] [ 40/2138] eta: 1:56:01 lr: 2.556227788016284e-05 loss: 0.0261 (0.0307) time: 2.9202 data: 0.0028 max mem: 19788 +Epoch: [21] [ 50/2138] eta: 1:53:13 lr: 2.5556608642446627e-05 loss: 0.0265 (0.0304) time: 2.9735 data: 0.0027 max mem: 19788 +Epoch: [21] [ 60/2138] eta: 1:50:36 lr: 2.5550939264992485e-05 loss: 0.0278 (0.0305) time: 2.9392 data: 0.0025 max mem: 19788 +Epoch: [21] [ 70/2138] eta: 1:48:33 lr: 2.554526974776251e-05 loss: 0.0278 (0.0303) time: 2.8837 data: 0.0026 max mem: 19788 +Epoch: [21] [ 80/2138] eta: 1:46:54 lr: 2.5539600090718796e-05 loss: 0.0263 (0.0303) time: 2.8815 data: 0.0025 max mem: 19788 +Epoch: [21] [ 90/2138] eta: 1:45:31 lr: 2.5533930293823395e-05 loss: 0.0255 (0.0296) time: 2.8867 data: 0.0022 max mem: 19788 +Epoch: [21] [ 100/2138] eta: 1:44:18 lr: 2.5528260357038358e-05 loss: 0.0262 (0.0296) time: 2.8842 data: 0.0024 max mem: 19788 +Epoch: [21] [ 110/2138] eta: 1:43:12 lr: 2.5522590280325714e-05 loss: 0.0278 (0.0294) time: 2.8783 data: 0.0027 max mem: 19788 +Epoch: [21] [ 120/2138] eta: 1:42:22 lr: 2.5516920063647453e-05 loss: 0.0219 (0.0288) time: 2.9092 data: 0.0029 max mem: 19788 +Epoch: [21] [ 130/2138] eta: 1:41:39 lr: 2.5511249706965575e-05 loss: 0.0264 (0.0288) time: 2.9518 data: 0.0027 max mem: 19788 +Epoch: [21] [ 140/2138] eta: 1:40:55 lr: 2.5505579210242032e-05 loss: 0.0279 (0.0287) time: 2.9504 data: 0.0026 max mem: 19788 +Epoch: [21] [ 150/2138] eta: 1:40:04 lr: 2.5499908573438786e-05 loss: 0.0278 (0.0289) time: 2.9066 data: 0.0024 max mem: 19788 +Epoch: [21] [ 160/2138] eta: 1:39:16 lr: 2.5494237796517744e-05 loss: 0.0278 (0.0291) time: 2.8739 data: 0.0022 max mem: 19788 +Epoch: [21] [ 170/2138] eta: 1:38:30 lr: 2.548856687944083e-05 loss: 0.0274 (0.0289) time: 2.8725 data: 0.0022 max mem: 19788 +Epoch: [21] [ 180/2138] eta: 1:37:48 lr: 2.5482895822169917e-05 loss: 0.0254 (0.0288) time: 2.8818 data: 0.0022 max mem: 19788 +Epoch: [21] [ 190/2138] eta: 1:37:08 lr: 2.547722462466688e-05 loss: 0.0233 (0.0286) time: 2.8975 data: 0.0024 max mem: 19788 +Epoch: [21] [ 200/2138] eta: 1:36:31 lr: 2.5471553286893563e-05 loss: 0.0233 (0.0284) time: 2.9090 data: 0.0027 max mem: 19788 +Epoch: [21] [ 210/2138] eta: 1:36:08 lr: 2.5465881808811793e-05 loss: 0.0237 (0.0284) time: 2.9901 data: 0.0028 max mem: 19788 +Epoch: [21] [ 220/2138] eta: 1:35:31 lr: 2.5460210190383372e-05 loss: 0.0267 (0.0283) time: 2.9914 data: 0.0026 max mem: 19788 +Epoch: [21] [ 230/2138] eta: 1:34:53 lr: 2.5454538431570096e-05 loss: 0.0239 (0.0284) time: 2.8985 data: 0.0028 max mem: 19788 +Epoch: [21] [ 240/2138] eta: 1:34:15 lr: 2.5448866532333726e-05 loss: 0.0288 (0.0283) time: 2.8826 data: 0.0029 max mem: 19788 +Epoch: [21] [ 250/2138] eta: 1:33:37 lr: 2.544319449263602e-05 loss: 0.0259 (0.0281) time: 2.8794 data: 0.0025 max mem: 19788 +Epoch: [21] [ 260/2138] eta: 1:33:00 lr: 2.543752231243869e-05 loss: 0.0246 (0.0281) time: 2.8739 data: 0.0024 max mem: 19788 +Epoch: [21] [ 270/2138] eta: 1:32:24 lr: 2.5431849991703454e-05 loss: 0.0267 (0.0280) time: 2.8767 data: 0.0024 max mem: 19788 +Epoch: [21] [ 280/2138] eta: 1:31:49 lr: 2.5426177530392e-05 loss: 0.0271 (0.0281) time: 2.8857 data: 0.0024 max mem: 19788 +Epoch: [21] [ 290/2138] eta: 1:31:23 lr: 2.542050492846599e-05 loss: 0.0269 (0.0281) time: 2.9571 data: 0.0023 max mem: 19788 +Epoch: [21] [ 300/2138] eta: 1:30:55 lr: 2.5414832185887073e-05 loss: 0.0274 (0.0282) time: 3.0043 data: 0.0024 max mem: 19788 +Epoch: [21] [ 310/2138] eta: 1:30:23 lr: 2.540915930261688e-05 loss: 0.0261 (0.0281) time: 2.9608 data: 0.0024 max mem: 19788 +Epoch: [21] [ 320/2138] eta: 1:29:48 lr: 2.5403486278617017e-05 loss: 0.0239 (0.0280) time: 2.9052 data: 0.0022 max mem: 19788 +Epoch: [21] [ 330/2138] eta: 1:29:15 lr: 2.5397813113849077e-05 loss: 0.0278 (0.0280) time: 2.8849 data: 0.0022 max mem: 19788 +Epoch: [21] [ 340/2138] eta: 1:28:41 lr: 2.5392139808274617e-05 loss: 0.0269 (0.0280) time: 2.8852 data: 0.0026 max mem: 19788 +Epoch: [21] [ 350/2138] eta: 1:28:07 lr: 2.5386466361855198e-05 loss: 0.0240 (0.0279) time: 2.8789 data: 0.0028 max mem: 19788 +Epoch: [21] [ 360/2138] eta: 1:27:35 lr: 2.5380792774552335e-05 loss: 0.0241 (0.0279) time: 2.8886 data: 0.0024 max mem: 19788 +Epoch: [21] [ 370/2138] eta: 1:27:08 lr: 2.537511904632755e-05 loss: 0.0260 (0.0279) time: 2.9538 data: 0.0024 max mem: 19788 +Epoch: [21] [ 380/2138] eta: 1:26:38 lr: 2.5369445177142316e-05 loss: 0.0259 (0.0278) time: 2.9798 data: 0.0028 max mem: 19788 +Epoch: [21] [ 390/2138] eta: 1:26:05 lr: 2.5363771166958112e-05 loss: 0.0243 (0.0277) time: 2.9149 data: 0.0028 max mem: 19788 +Epoch: [21] [ 400/2138] eta: 1:25:33 lr: 2.535809701573638e-05 loss: 0.0262 (0.0278) time: 2.8948 data: 0.0027 max mem: 19788 +Epoch: [21] [ 410/2138] eta: 1:25:00 lr: 2.5352422723438546e-05 loss: 0.0257 (0.0276) time: 2.8918 data: 0.0026 max mem: 19788 +Epoch: [21] [ 420/2138] eta: 1:24:27 lr: 2.5346748290026023e-05 loss: 0.0229 (0.0276) time: 2.8728 data: 0.0023 max mem: 19788 +Epoch: [21] [ 430/2138] eta: 1:23:56 lr: 2.5341073715460185e-05 loss: 0.0236 (0.0276) time: 2.8837 data: 0.0024 max mem: 19788 +Epoch: [21] [ 440/2138] eta: 1:23:24 lr: 2.5335398999702416e-05 loss: 0.0251 (0.0276) time: 2.8877 data: 0.0028 max mem: 19788 +Epoch: [21] [ 450/2138] eta: 1:22:55 lr: 2.5329724142714052e-05 loss: 0.0275 (0.0276) time: 2.9187 data: 0.0028 max mem: 19788 +Epoch: [21] [ 460/2138] eta: 1:22:25 lr: 2.5324049144456425e-05 loss: 0.0246 (0.0275) time: 2.9543 data: 0.0028 max mem: 19788 +Epoch: [21] [ 470/2138] eta: 1:21:53 lr: 2.5318374004890826e-05 loss: 0.0236 (0.0275) time: 2.9101 data: 0.0028 max mem: 19788 +Epoch: [21] [ 480/2138] eta: 1:21:21 lr: 2.5312698723978566e-05 loss: 0.0282 (0.0276) time: 2.8766 data: 0.0025 max mem: 19788 +Epoch: [21] [ 490/2138] eta: 1:20:50 lr: 2.5307023301680894e-05 loss: 0.0277 (0.0276) time: 2.8853 data: 0.0025 max mem: 19788 +Epoch: [21] [ 500/2138] eta: 1:20:19 lr: 2.5301347737959064e-05 loss: 0.0237 (0.0276) time: 2.8876 data: 0.0024 max mem: 19788 +Epoch: [21] [ 510/2138] eta: 1:19:48 lr: 2.5295672032774286e-05 loss: 0.0233 (0.0276) time: 2.8930 data: 0.0026 max mem: 19788 +Epoch: [21] [ 520/2138] eta: 1:19:17 lr: 2.5289996186087784e-05 loss: 0.0256 (0.0276) time: 2.8903 data: 0.0029 max mem: 19788 +Epoch: [21] [ 530/2138] eta: 1:18:48 lr: 2.528432019786073e-05 loss: 0.0255 (0.0276) time: 2.9184 data: 0.0029 max mem: 19788 +Epoch: [21] [ 540/2138] eta: 1:18:20 lr: 2.5278644068054296e-05 loss: 0.0251 (0.0276) time: 2.9697 data: 0.0031 max mem: 19788 +Epoch: [21] [ 550/2138] eta: 1:17:49 lr: 2.5272967796629615e-05 loss: 0.0268 (0.0278) time: 2.9406 data: 0.0030 max mem: 19788 +Epoch: [21] [ 560/2138] eta: 1:17:18 lr: 2.5267291383547825e-05 loss: 0.0291 (0.0279) time: 2.8881 data: 0.0030 max mem: 19788 +Epoch: [21] [ 570/2138] eta: 1:16:47 lr: 2.5261614828770013e-05 loss: 0.0297 (0.0280) time: 2.8814 data: 0.0030 max mem: 19788 +Epoch: [21] [ 580/2138] eta: 1:16:16 lr: 2.5255938132257283e-05 loss: 0.0271 (0.0280) time: 2.8909 data: 0.0028 max mem: 19788 +Epoch: [21] [ 590/2138] eta: 1:15:46 lr: 2.5250261293970673e-05 loss: 0.0266 (0.0280) time: 2.8889 data: 0.0024 max mem: 19788 +Epoch: [21] [ 600/2138] eta: 1:15:15 lr: 2.5244584313871245e-05 loss: 0.0270 (0.0280) time: 2.8786 data: 0.0021 max mem: 19788 +Epoch: [21] [ 610/2138] eta: 1:14:46 lr: 2.5238907191920003e-05 loss: 0.0251 (0.0279) time: 2.9177 data: 0.0021 max mem: 19788 +Epoch: [21] [ 620/2138] eta: 1:14:19 lr: 2.5233229928077968e-05 loss: 0.0251 (0.0280) time: 2.9892 data: 0.0026 max mem: 19788 +Epoch: [21] [ 630/2138] eta: 1:13:49 lr: 2.5227552522306103e-05 loss: 0.0298 (0.0280) time: 2.9702 data: 0.0027 max mem: 19788 +Epoch: [21] [ 640/2138] eta: 1:13:19 lr: 2.5221874974565374e-05 loss: 0.0246 (0.0280) time: 2.9114 data: 0.0023 max mem: 19788 +Epoch: [21] [ 650/2138] eta: 1:12:48 lr: 2.5216197284816722e-05 loss: 0.0259 (0.0280) time: 2.8967 data: 0.0023 max mem: 19788 +Epoch: [21] [ 660/2138] eta: 1:12:17 lr: 2.5210519453021064e-05 loss: 0.0259 (0.0281) time: 2.8814 data: 0.0022 max mem: 19788 +Epoch: [21] [ 670/2138] eta: 1:11:47 lr: 2.5204841479139303e-05 loss: 0.0248 (0.0280) time: 2.8767 data: 0.0024 max mem: 19788 +Epoch: [21] [ 680/2138] eta: 1:11:16 lr: 2.519916336313231e-05 loss: 0.0230 (0.0280) time: 2.8813 data: 0.0026 max mem: 19788 +Epoch: [21] [ 690/2138] eta: 1:10:47 lr: 2.5193485104960946e-05 loss: 0.0254 (0.0280) time: 2.8977 data: 0.0027 max mem: 19788 +Epoch: [21] [ 700/2138] eta: 1:10:18 lr: 2.5187806704586054e-05 loss: 0.0278 (0.0280) time: 2.9465 data: 0.0028 max mem: 19788 +Epoch: [21] [ 710/2138] eta: 1:09:49 lr: 2.5182128161968438e-05 loss: 0.0247 (0.0280) time: 2.9557 data: 0.0027 max mem: 19788 +Epoch: [21] [ 720/2138] eta: 1:09:19 lr: 2.5176449477068898e-05 loss: 0.0269 (0.0280) time: 2.9068 data: 0.0025 max mem: 19788 +Epoch: [21] [ 730/2138] eta: 1:08:48 lr: 2.5170770649848215e-05 loss: 0.0287 (0.0280) time: 2.8809 data: 0.0025 max mem: 19788 +Epoch: [21] [ 740/2138] eta: 1:08:18 lr: 2.5165091680267135e-05 loss: 0.0312 (0.0281) time: 2.8820 data: 0.0025 max mem: 19788 +Epoch: [21] [ 750/2138] eta: 1:07:48 lr: 2.5159412568286396e-05 loss: 0.0289 (0.0281) time: 2.8868 data: 0.0022 max mem: 19788 +Epoch: [21] [ 760/2138] eta: 1:07:18 lr: 2.5153733313866706e-05 loss: 0.0278 (0.0282) time: 2.8965 data: 0.0021 max mem: 19788 +Epoch: [21] [ 770/2138] eta: 1:06:48 lr: 2.5148053916968767e-05 loss: 0.0251 (0.0281) time: 2.8959 data: 0.0024 max mem: 19788 +Epoch: [21] [ 780/2138] eta: 1:06:20 lr: 2.5142374377553234e-05 loss: 0.0250 (0.0281) time: 2.9358 data: 0.0026 max mem: 19788 +Epoch: [21] [ 790/2138] eta: 1:05:51 lr: 2.5136694695580783e-05 loss: 0.0262 (0.0281) time: 2.9719 data: 0.0026 max mem: 19788 +Epoch: [21] [ 800/2138] eta: 1:05:22 lr: 2.5131014871012015e-05 loss: 0.0265 (0.0283) time: 2.9666 data: 0.0026 max mem: 19788 +Epoch: [21] [ 810/2138] eta: 1:04:53 lr: 2.512533490380756e-05 loss: 0.0278 (0.0282) time: 2.9647 data: 0.0027 max mem: 19788 +Epoch: [21] [ 820/2138] eta: 1:04:23 lr: 2.5119654793928003e-05 loss: 0.0261 (0.0282) time: 2.9253 data: 0.0028 max mem: 19788 +Epoch: [21] [ 830/2138] eta: 1:03:53 lr: 2.5113974541333907e-05 loss: 0.0249 (0.0282) time: 2.8918 data: 0.0027 max mem: 19788 +Epoch: [21] [ 840/2138] eta: 1:03:23 lr: 2.5108294145985815e-05 loss: 0.0269 (0.0282) time: 2.8920 data: 0.0025 max mem: 19788 +Epoch: [21] [ 850/2138] eta: 1:02:54 lr: 2.5102613607844265e-05 loss: 0.0269 (0.0282) time: 2.8936 data: 0.0026 max mem: 19788 +Epoch: [21] [ 860/2138] eta: 1:02:24 lr: 2.5096932926869754e-05 loss: 0.0246 (0.0282) time: 2.9114 data: 0.0026 max mem: 19788 +Epoch: [21] [ 870/2138] eta: 1:01:55 lr: 2.509125210302277e-05 loss: 0.0243 (0.0282) time: 2.9139 data: 0.0025 max mem: 19788 +Epoch: [21] [ 880/2138] eta: 1:01:26 lr: 2.5085571136263776e-05 loss: 0.0248 (0.0281) time: 2.9296 data: 0.0027 max mem: 19788 +Epoch: [21] [ 890/2138] eta: 1:00:56 lr: 2.507989002655321e-05 loss: 0.0248 (0.0282) time: 2.9294 data: 0.0029 max mem: 19788 +Epoch: [21] [ 900/2138] eta: 1:00:26 lr: 2.5074208773851493e-05 loss: 0.0249 (0.0282) time: 2.9000 data: 0.0028 max mem: 19788 +Epoch: [21] [ 910/2138] eta: 0:59:56 lr: 2.5068527378119038e-05 loss: 0.0251 (0.0281) time: 2.8974 data: 0.0028 max mem: 19788 +Epoch: [21] [ 920/2138] eta: 0:59:27 lr: 2.5062845839316206e-05 loss: 0.0234 (0.0281) time: 2.8910 data: 0.0029 max mem: 19788 +Epoch: [21] [ 930/2138] eta: 0:58:57 lr: 2.5057164157403373e-05 loss: 0.0265 (0.0281) time: 2.8981 data: 0.0028 max mem: 19788 +Epoch: [21] [ 940/2138] eta: 0:58:28 lr: 2.505148233234087e-05 loss: 0.0282 (0.0281) time: 2.9065 data: 0.0025 max mem: 19788 +Epoch: [21] [ 950/2138] eta: 0:57:58 lr: 2.5045800364089018e-05 loss: 0.0272 (0.0282) time: 2.9163 data: 0.0022 max mem: 19788 +Epoch: [21] [ 960/2138] eta: 0:57:29 lr: 2.50401182526081e-05 loss: 0.0291 (0.0282) time: 2.9285 data: 0.0022 max mem: 19788 +Epoch: [21] [ 970/2138] eta: 0:56:59 lr: 2.5034435997858403e-05 loss: 0.0291 (0.0282) time: 2.9199 data: 0.0023 max mem: 19788 +Epoch: [21] [ 980/2138] eta: 0:56:30 lr: 2.5028753599800176e-05 loss: 0.0251 (0.0282) time: 2.9035 data: 0.0025 max mem: 19788 +Epoch: [21] [ 990/2138] eta: 0:56:00 lr: 2.5023071058393653e-05 loss: 0.0224 (0.0281) time: 2.8967 data: 0.0025 max mem: 19788 +Epoch: [21] [1000/2138] eta: 0:55:30 lr: 2.501738837359905e-05 loss: 0.0219 (0.0281) time: 2.8895 data: 0.0023 max mem: 19788 +Epoch: [21] [1010/2138] eta: 0:55:01 lr: 2.5011705545376553e-05 loss: 0.0217 (0.0281) time: 2.8798 data: 0.0021 max mem: 19788 +Epoch: [21] [1020/2138] eta: 0:54:31 lr: 2.5006022573686333e-05 loss: 0.0234 (0.0281) time: 2.9034 data: 0.0026 max mem: 19788 +Epoch: [21] [1030/2138] eta: 0:54:02 lr: 2.500033945848853e-05 loss: 0.0235 (0.0281) time: 2.9401 data: 0.0029 max mem: 19788 +Epoch: [21] [1040/2138] eta: 0:53:33 lr: 2.4994656199743284e-05 loss: 0.0241 (0.0281) time: 2.9296 data: 0.0027 max mem: 19788 +Epoch: [21] [1050/2138] eta: 0:53:03 lr: 2.4988972797410692e-05 loss: 0.0256 (0.0281) time: 2.9079 data: 0.0025 max mem: 19788 +Epoch: [21] [1060/2138] eta: 0:52:34 lr: 2.4983289251450846e-05 loss: 0.0260 (0.0282) time: 2.9050 data: 0.0023 max mem: 19788 +Epoch: [21] [1070/2138] eta: 0:52:04 lr: 2.4977605561823804e-05 loss: 0.0280 (0.0282) time: 2.9023 data: 0.0022 max mem: 19788 +Epoch: [21] [1080/2138] eta: 0:51:35 lr: 2.4971921728489614e-05 loss: 0.0250 (0.0282) time: 2.8884 data: 0.0022 max mem: 19788 +Epoch: [21] [1090/2138] eta: 0:51:05 lr: 2.496623775140829e-05 loss: 0.0250 (0.0282) time: 2.8797 data: 0.0026 max mem: 19788 +Epoch: [21] [1100/2138] eta: 0:50:36 lr: 2.496055363053984e-05 loss: 0.0276 (0.0282) time: 2.9385 data: 0.0026 max mem: 19788 +Epoch: [21] [1110/2138] eta: 0:50:08 lr: 2.4954869365844232e-05 loss: 0.0277 (0.0282) time: 3.0173 data: 0.0024 max mem: 19788 +Epoch: [21] [1120/2138] eta: 0:49:39 lr: 2.494918495728144e-05 loss: 0.0298 (0.0282) time: 2.9769 data: 0.0026 max mem: 19788 +Epoch: [21] [1130/2138] eta: 0:49:09 lr: 2.494350040481138e-05 loss: 0.0265 (0.0282) time: 2.9003 data: 0.0027 max mem: 19788 +Epoch: [21] [1140/2138] eta: 0:48:40 lr: 2.4937815708393984e-05 loss: 0.0241 (0.0282) time: 2.8852 data: 0.0026 max mem: 19788 +Epoch: [21] [1150/2138] eta: 0:48:10 lr: 2.4932130867989135e-05 loss: 0.0239 (0.0281) time: 2.8838 data: 0.0025 max mem: 19788 +Epoch: [21] [1160/2138] eta: 0:47:41 lr: 2.4926445883556712e-05 loss: 0.0230 (0.0281) time: 2.9033 data: 0.0024 max mem: 19788 +Epoch: [21] [1170/2138] eta: 0:47:11 lr: 2.492076075505656e-05 loss: 0.0232 (0.0281) time: 2.9299 data: 0.0024 max mem: 19788 +Epoch: [21] [1180/2138] eta: 0:46:43 lr: 2.491507548244852e-05 loss: 0.0232 (0.0281) time: 2.9741 data: 0.0025 max mem: 19788 +Epoch: [21] [1190/2138] eta: 0:46:13 lr: 2.490939006569238e-05 loss: 0.0254 (0.0281) time: 2.9542 data: 0.0024 max mem: 19788 +Epoch: [21] [1200/2138] eta: 0:45:44 lr: 2.4903704504747947e-05 loss: 0.0239 (0.0280) time: 2.8948 data: 0.0026 max mem: 19788 +Epoch: [21] [1210/2138] eta: 0:45:15 lr: 2.4898018799574972e-05 loss: 0.0275 (0.0280) time: 2.9031 data: 0.0028 max mem: 19788 +Epoch: [21] [1220/2138] eta: 0:44:45 lr: 2.489233295013321e-05 loss: 0.0273 (0.0280) time: 2.9069 data: 0.0025 max mem: 19788 +Epoch: [21] [1230/2138] eta: 0:44:16 lr: 2.4886646956382376e-05 loss: 0.0259 (0.0280) time: 2.8902 data: 0.0027 max mem: 19788 +Epoch: [21] [1240/2138] eta: 0:43:46 lr: 2.4880960818282174e-05 loss: 0.0229 (0.0280) time: 2.8828 data: 0.0030 max mem: 19788 +Epoch: [21] [1250/2138] eta: 0:43:17 lr: 2.487527453579228e-05 loss: 0.0229 (0.0280) time: 2.9198 data: 0.0027 max mem: 19788 +Epoch: [21] [1260/2138] eta: 0:42:48 lr: 2.486958810887236e-05 loss: 0.0232 (0.0280) time: 2.9373 data: 0.0023 max mem: 19788 +Epoch: [21] [1270/2138] eta: 0:42:18 lr: 2.486390153748204e-05 loss: 0.0232 (0.0280) time: 2.9056 data: 0.0021 max mem: 19788 +Epoch: [21] [1280/2138] eta: 0:41:49 lr: 2.4858214821580946e-05 loss: 0.0271 (0.0280) time: 2.8902 data: 0.0021 max mem: 19788 +Epoch: [21] [1290/2138] eta: 0:41:19 lr: 2.4852527961128655e-05 loss: 0.0271 (0.0280) time: 2.8894 data: 0.0024 max mem: 19788 +Epoch: [21] [1300/2138] eta: 0:40:50 lr: 2.4846840956084756e-05 loss: 0.0274 (0.0280) time: 2.8876 data: 0.0027 max mem: 19788 +Epoch: [21] [1310/2138] eta: 0:40:20 lr: 2.484115380640879e-05 loss: 0.0283 (0.0280) time: 2.8864 data: 0.0025 max mem: 19788 +Epoch: [21] [1320/2138] eta: 0:39:51 lr: 2.483546651206029e-05 loss: 0.0270 (0.0280) time: 2.8995 data: 0.0021 max mem: 19788 +Epoch: [21] [1330/2138] eta: 0:39:22 lr: 2.4829779072998763e-05 loss: 0.0252 (0.0280) time: 2.9653 data: 0.0022 max mem: 19788 +Epoch: [21] [1340/2138] eta: 0:38:53 lr: 2.4824091489183686e-05 loss: 0.0260 (0.0280) time: 2.9553 data: 0.0026 max mem: 19788 +Epoch: [21] [1350/2138] eta: 0:38:23 lr: 2.481840376057453e-05 loss: 0.0301 (0.0280) time: 2.8868 data: 0.0026 max mem: 19788 +Epoch: [21] [1360/2138] eta: 0:37:54 lr: 2.4812715887130733e-05 loss: 0.0288 (0.0280) time: 2.8850 data: 0.0022 max mem: 19788 +Epoch: [21] [1370/2138] eta: 0:37:24 lr: 2.4807027868811725e-05 loss: 0.0279 (0.0280) time: 2.8883 data: 0.0020 max mem: 19788 +Epoch: [21] [1380/2138] eta: 0:36:55 lr: 2.480133970557689e-05 loss: 0.0268 (0.0280) time: 2.9009 data: 0.0023 max mem: 19788 +Epoch: [21] [1390/2138] eta: 0:36:26 lr: 2.4795651397385615e-05 loss: 0.0261 (0.0280) time: 2.9044 data: 0.0027 max mem: 19788 +Epoch: [21] [1400/2138] eta: 0:35:57 lr: 2.478996294419725e-05 loss: 0.0245 (0.0280) time: 2.9210 data: 0.0029 max mem: 19788 +Epoch: [21] [1410/2138] eta: 0:35:27 lr: 2.4784274345971134e-05 loss: 0.0244 (0.0279) time: 2.9244 data: 0.0028 max mem: 19788 +Epoch: [21] [1420/2138] eta: 0:34:58 lr: 2.477858560266657e-05 loss: 0.0255 (0.0279) time: 2.9028 data: 0.0024 max mem: 19788 +Epoch: [21] [1430/2138] eta: 0:34:29 lr: 2.477289671424286e-05 loss: 0.0270 (0.0279) time: 2.8975 data: 0.0021 max mem: 19788 +Epoch: [21] [1440/2138] eta: 0:33:59 lr: 2.476720768065926e-05 loss: 0.0272 (0.0280) time: 2.8886 data: 0.0021 max mem: 19788 +Epoch: [21] [1450/2138] eta: 0:33:30 lr: 2.4761518501875023e-05 loss: 0.0270 (0.0280) time: 2.8942 data: 0.0020 max mem: 19788 +Epoch: [21] [1460/2138] eta: 0:33:01 lr: 2.4755829177849367e-05 loss: 0.0254 (0.0280) time: 2.8972 data: 0.0020 max mem: 19788 +Epoch: [21] [1470/2138] eta: 0:32:31 lr: 2.47501397085415e-05 loss: 0.0254 (0.0280) time: 2.9107 data: 0.0022 max mem: 19788 +Epoch: [21] [1480/2138] eta: 0:32:03 lr: 2.4744450093910597e-05 loss: 0.0230 (0.0280) time: 3.0416 data: 0.0023 max mem: 19788 +Epoch: [21] [1490/2138] eta: 0:31:34 lr: 2.473876033391583e-05 loss: 0.0243 (0.0280) time: 3.0188 data: 0.0021 max mem: 19788 +Epoch: [21] [1500/2138] eta: 0:31:04 lr: 2.4733070428516316e-05 loss: 0.0271 (0.0280) time: 2.8877 data: 0.0021 max mem: 19788 +Epoch: [21] [1510/2138] eta: 0:30:35 lr: 2.472738037767119e-05 loss: 0.0262 (0.0280) time: 2.8881 data: 0.0022 max mem: 19788 +Epoch: [21] [1520/2138] eta: 0:30:06 lr: 2.4721690181339525e-05 loss: 0.0262 (0.0280) time: 2.8908 data: 0.0024 max mem: 19788 +Epoch: [21] [1530/2138] eta: 0:29:36 lr: 2.4715999839480408e-05 loss: 0.0260 (0.0280) time: 2.9015 data: 0.0023 max mem: 19788 +Epoch: [21] [1540/2138] eta: 0:29:07 lr: 2.4710309352052877e-05 loss: 0.0246 (0.0280) time: 2.8953 data: 0.0022 max mem: 19788 +Epoch: [21] [1550/2138] eta: 0:28:38 lr: 2.4704618719015965e-05 loss: 0.0256 (0.0280) time: 2.9461 data: 0.0023 max mem: 19788 +Epoch: [21] [1560/2138] eta: 0:28:09 lr: 2.4698927940328672e-05 loss: 0.0276 (0.0281) time: 2.9523 data: 0.0023 max mem: 19788 +Epoch: [21] [1570/2138] eta: 0:27:39 lr: 2.4693237015949987e-05 loss: 0.0265 (0.0281) time: 2.8921 data: 0.0024 max mem: 19788 +Epoch: [21] [1580/2138] eta: 0:27:10 lr: 2.4687545945838866e-05 loss: 0.0265 (0.0280) time: 2.8858 data: 0.0023 max mem: 19788 +Epoch: [21] [1590/2138] eta: 0:26:41 lr: 2.468185472995425e-05 loss: 0.0266 (0.0280) time: 2.8809 data: 0.0022 max mem: 19788 +Epoch: [21] [1600/2138] eta: 0:26:11 lr: 2.467616336825505e-05 loss: 0.0288 (0.0281) time: 2.8855 data: 0.0025 max mem: 19788 +Epoch: [21] [1610/2138] eta: 0:25:42 lr: 2.4670471860700174e-05 loss: 0.0288 (0.0281) time: 2.8924 data: 0.0027 max mem: 19788 +Epoch: [21] [1620/2138] eta: 0:25:13 lr: 2.466478020724848e-05 loss: 0.0241 (0.0281) time: 2.9088 data: 0.0028 max mem: 19788 +Epoch: [21] [1630/2138] eta: 0:24:44 lr: 2.465908840785882e-05 loss: 0.0240 (0.0281) time: 2.9316 data: 0.0026 max mem: 19788 +Epoch: [21] [1640/2138] eta: 0:24:14 lr: 2.465339646249003e-05 loss: 0.0294 (0.0281) time: 2.9119 data: 0.0022 max mem: 19788 +Epoch: [21] [1650/2138] eta: 0:23:45 lr: 2.4647704371100905e-05 loss: 0.0290 (0.0281) time: 2.8919 data: 0.0020 max mem: 19788 +Epoch: [21] [1660/2138] eta: 0:23:16 lr: 2.464201213365024e-05 loss: 0.0274 (0.0281) time: 2.8919 data: 0.0021 max mem: 19788 +Epoch: [21] [1670/2138] eta: 0:22:47 lr: 2.463631975009679e-05 loss: 0.0269 (0.0281) time: 2.8908 data: 0.0023 max mem: 19788 +Epoch: [21] [1680/2138] eta: 0:22:17 lr: 2.4630627220399296e-05 loss: 0.0261 (0.0280) time: 2.8969 data: 0.0024 max mem: 19788 +Epoch: [21] [1690/2138] eta: 0:21:48 lr: 2.462493454451647e-05 loss: 0.0261 (0.0280) time: 2.8962 data: 0.0024 max mem: 19788 +Epoch: [21] [1700/2138] eta: 0:21:19 lr: 2.4619241722407016e-05 loss: 0.0262 (0.0280) time: 2.9288 data: 0.0022 max mem: 19788 +Epoch: [21] [1710/2138] eta: 0:20:50 lr: 2.4613548754029596e-05 loss: 0.0265 (0.0280) time: 2.9246 data: 0.0020 max mem: 19788 +Epoch: [21] [1720/2138] eta: 0:20:20 lr: 2.460785563934287e-05 loss: 0.0265 (0.0280) time: 2.8855 data: 0.0020 max mem: 19788 +Epoch: [21] [1730/2138] eta: 0:19:51 lr: 2.4602162378305456e-05 loss: 0.0252 (0.0280) time: 2.8924 data: 0.0023 max mem: 19788 +Epoch: [21] [1740/2138] eta: 0:19:22 lr: 2.4596468970875967e-05 loss: 0.0278 (0.0280) time: 2.9199 data: 0.0025 max mem: 19788 +Epoch: [21] [1750/2138] eta: 0:18:53 lr: 2.459077541701298e-05 loss: 0.0292 (0.0280) time: 2.9173 data: 0.0024 max mem: 19788 +Epoch: [21] [1760/2138] eta: 0:18:23 lr: 2.4585081716675062e-05 loss: 0.0287 (0.0281) time: 2.9176 data: 0.0024 max mem: 19788 +Epoch: [21] [1770/2138] eta: 0:17:54 lr: 2.4579387869820747e-05 loss: 0.0237 (0.0280) time: 2.9361 data: 0.0026 max mem: 19788 +Epoch: [21] [1780/2138] eta: 0:17:25 lr: 2.4573693876408554e-05 loss: 0.0237 (0.0280) time: 2.9974 data: 0.0024 max mem: 19788 +Epoch: [21] [1790/2138] eta: 0:16:56 lr: 2.456799973639697e-05 loss: 0.0247 (0.0280) time: 2.9770 data: 0.0026 max mem: 19788 +Epoch: [21] [1800/2138] eta: 0:16:27 lr: 2.4562305449744473e-05 loss: 0.0317 (0.0281) time: 2.8917 data: 0.0027 max mem: 19788 +Epoch: [21] [1810/2138] eta: 0:15:58 lr: 2.455661101640951e-05 loss: 0.0300 (0.0281) time: 2.8890 data: 0.0022 max mem: 19788 +Epoch: [21] [1820/2138] eta: 0:15:28 lr: 2.4550916436350503e-05 loss: 0.0226 (0.0280) time: 2.8901 data: 0.0023 max mem: 19788 +Epoch: [21] [1830/2138] eta: 0:14:59 lr: 2.454522170952586e-05 loss: 0.0249 (0.0280) time: 2.8973 data: 0.0027 max mem: 19788 +Epoch: [21] [1840/2138] eta: 0:14:30 lr: 2.453952683589396e-05 loss: 0.0260 (0.0280) time: 2.9080 data: 0.0029 max mem: 19788 +Epoch: [21] [1850/2138] eta: 0:14:01 lr: 2.453383181541316e-05 loss: 0.0267 (0.0280) time: 2.9429 data: 0.0029 max mem: 19788 +Epoch: [21] [1860/2138] eta: 0:13:31 lr: 2.4528136648041806e-05 loss: 0.0267 (0.0280) time: 2.9306 data: 0.0025 max mem: 19788 +Epoch: [21] [1870/2138] eta: 0:13:02 lr: 2.452244133373819e-05 loss: 0.0266 (0.0280) time: 2.8993 data: 0.0024 max mem: 19788 +Epoch: [21] [1880/2138] eta: 0:12:33 lr: 2.4516745872460624e-05 loss: 0.0226 (0.0280) time: 2.9164 data: 0.0025 max mem: 19788 +Epoch: [21] [1890/2138] eta: 0:12:04 lr: 2.4511050264167363e-05 loss: 0.0215 (0.0280) time: 2.9087 data: 0.0025 max mem: 19788 +Epoch: [21] [1900/2138] eta: 0:11:35 lr: 2.4505354508816667e-05 loss: 0.0252 (0.0280) time: 2.8965 data: 0.0024 max mem: 19788 +Epoch: [21] [1910/2138] eta: 0:11:05 lr: 2.449965860636674e-05 loss: 0.0241 (0.0280) time: 2.9001 data: 0.0026 max mem: 19788 +Epoch: [21] [1920/2138] eta: 0:10:36 lr: 2.4493962556775796e-05 loss: 0.0242 (0.0280) time: 2.9377 data: 0.0027 max mem: 19788 +Epoch: [21] [1930/2138] eta: 0:10:07 lr: 2.448826636000201e-05 loss: 0.0264 (0.0279) time: 2.9749 data: 0.0027 max mem: 19788 +Epoch: [21] [1940/2138] eta: 0:09:38 lr: 2.448257001600353e-05 loss: 0.0264 (0.0279) time: 2.9277 data: 0.0025 max mem: 19788 +Epoch: [21] [1950/2138] eta: 0:09:09 lr: 2.4476873524738495e-05 loss: 0.0264 (0.0279) time: 2.8864 data: 0.0023 max mem: 19788 +Epoch: [21] [1960/2138] eta: 0:08:39 lr: 2.4471176886165007e-05 loss: 0.0259 (0.0280) time: 2.8944 data: 0.0023 max mem: 19788 +Epoch: [21] [1970/2138] eta: 0:08:10 lr: 2.4465480100241166e-05 loss: 0.0234 (0.0280) time: 2.8927 data: 0.0024 max mem: 19788 +Epoch: [21] [1980/2138] eta: 0:07:41 lr: 2.445978316692502e-05 loss: 0.0261 (0.0280) time: 2.9132 data: 0.0023 max mem: 19788 +Epoch: [21] [1990/2138] eta: 0:07:12 lr: 2.445408608617462e-05 loss: 0.0281 (0.0280) time: 2.9482 data: 0.0027 max mem: 19788 +Epoch: [21] [2000/2138] eta: 0:06:43 lr: 2.444838885794798e-05 loss: 0.0260 (0.0279) time: 2.9535 data: 0.0028 max mem: 19788 +Epoch: [21] [2010/2138] eta: 0:06:13 lr: 2.4442691482203105e-05 loss: 0.0237 (0.0279) time: 2.9145 data: 0.0026 max mem: 19788 +Epoch: [21] [2020/2138] eta: 0:05:44 lr: 2.4436993958897953e-05 loss: 0.0264 (0.0279) time: 2.8891 data: 0.0023 max mem: 19788 +Epoch: [21] [2030/2138] eta: 0:05:15 lr: 2.4431296287990484e-05 loss: 0.0252 (0.0279) time: 2.9010 data: 0.0024 max mem: 19788 +Epoch: [21] [2040/2138] eta: 0:04:46 lr: 2.4425598469438616e-05 loss: 0.0252 (0.0279) time: 2.9063 data: 0.0027 max mem: 19788 +Epoch: [21] [2050/2138] eta: 0:04:16 lr: 2.4419900503200264e-05 loss: 0.0256 (0.0279) time: 2.9056 data: 0.0026 max mem: 19788 +Epoch: [21] [2060/2138] eta: 0:03:47 lr: 2.44142023892333e-05 loss: 0.0254 (0.0279) time: 2.8970 data: 0.0024 max mem: 19788 +Epoch: [21] [2070/2138] eta: 0:03:18 lr: 2.440850412749559e-05 loss: 0.0242 (0.0279) time: 2.9683 data: 0.0023 max mem: 19788 +Epoch: [21] [2080/2138] eta: 0:02:49 lr: 2.4402805717944957e-05 loss: 0.0222 (0.0279) time: 2.9783 data: 0.0023 max mem: 19788 +Epoch: [21] [2090/2138] eta: 0:02:20 lr: 2.4397107160539225e-05 loss: 0.0248 (0.0279) time: 2.9003 data: 0.0025 max mem: 19788 +Epoch: [21] [2100/2138] eta: 0:01:50 lr: 2.4391408455236177e-05 loss: 0.0248 (0.0278) time: 2.9040 data: 0.0026 max mem: 19788 +Epoch: [21] [2110/2138] eta: 0:01:21 lr: 2.4385709601993584e-05 loss: 0.0272 (0.0279) time: 2.9070 data: 0.0026 max mem: 19788 +Epoch: [21] [2120/2138] eta: 0:00:52 lr: 2.4380010600769178e-05 loss: 0.0322 (0.0279) time: 2.8936 data: 0.0024 max mem: 19788 +Epoch: [21] [2130/2138] eta: 0:00:23 lr: 2.43743114515207e-05 loss: 0.0337 (0.0280) time: 2.8875 data: 0.0021 max mem: 19788 +Epoch: [21] Total time: 1:44:03 +Test: [ 0/21770] eta: 17:16:52 time: 2.8577 data: 2.8014 max mem: 19788 +Test: [ 100/21770] eta: 0:26:44 time: 0.0433 data: 0.0016 max mem: 19788 +Test: [ 200/21770] eta: 0:22:13 time: 0.0427 data: 0.0018 max mem: 19788 +Test: [ 300/21770] eta: 0:20:15 time: 0.0464 data: 0.0015 max mem: 19788 +Test: [ 400/21770] eta: 0:19:17 time: 0.0441 data: 0.0015 max mem: 19788 +Test: [ 500/21770] eta: 0:18:33 time: 0.0449 data: 0.0016 max mem: 19788 +Test: [ 600/21770] eta: 0:17:57 time: 0.0438 data: 0.0016 max mem: 19788 +Test: [ 700/21770] eta: 0:17:27 time: 0.0444 data: 0.0015 max mem: 19788 +Test: [ 800/21770] eta: 0:17:22 time: 0.0452 data: 0.0017 max mem: 19788 +Test: [ 900/21770] eta: 0:17:09 time: 0.0457 data: 0.0015 max mem: 19788 +Test: [ 1000/21770] eta: 0:17:02 time: 0.0435 data: 0.0014 max mem: 19788 +Test: [ 1100/21770] eta: 0:16:53 time: 0.0540 data: 0.0018 max mem: 19788 +Test: [ 1200/21770] eta: 0:16:49 time: 0.0448 data: 0.0015 max mem: 19788 +Test: [ 1300/21770] eta: 0:16:49 time: 0.0525 data: 0.0018 max mem: 19788 +Test: [ 1400/21770] eta: 0:16:37 time: 0.0458 data: 0.0015 max mem: 19788 +Test: [ 1500/21770] eta: 0:16:29 time: 0.0529 data: 0.0018 max mem: 19788 +Test: [ 1600/21770] eta: 0:16:24 time: 0.0437 data: 0.0017 max mem: 19788 +Test: [ 1700/21770] eta: 0:16:17 time: 0.0437 data: 0.0015 max mem: 19788 +Test: [ 1800/21770] eta: 0:16:07 time: 0.0441 data: 0.0014 max mem: 19788 +Test: [ 1900/21770] eta: 0:16:00 time: 0.0505 data: 0.0015 max mem: 19788 +Test: [ 2000/21770] eta: 0:15:52 time: 0.0428 data: 0.0014 max mem: 19788 +Test: [ 2100/21770] eta: 0:15:45 time: 0.0492 data: 0.0015 max mem: 19788 +Test: [ 2200/21770] eta: 0:15:40 time: 0.0428 data: 0.0014 max mem: 19788 +Test: [ 2300/21770] eta: 0:15:34 time: 0.0443 data: 0.0015 max mem: 19788 +Test: [ 2400/21770] eta: 0:15:29 time: 0.0484 data: 0.0017 max mem: 19788 +Test: [ 2500/21770] eta: 0:15:22 time: 0.0445 data: 0.0016 max mem: 19788 +Test: [ 2600/21770] eta: 0:15:15 time: 0.0445 data: 0.0014 max mem: 19788 +Test: [ 2700/21770] eta: 0:15:12 time: 0.0526 data: 0.0015 max mem: 19788 +Test: [ 2800/21770] eta: 0:15:09 time: 0.0453 data: 0.0016 max mem: 19788 +Test: [ 2900/21770] eta: 0:15:04 time: 0.0430 data: 0.0014 max mem: 19788 +Test: [ 3000/21770] eta: 0:15:02 time: 0.0522 data: 0.0017 max mem: 19788 +Test: [ 3100/21770] eta: 0:14:56 time: 0.0522 data: 0.0016 max mem: 19788 +Test: [ 3200/21770] eta: 0:14:50 time: 0.0429 data: 0.0016 max mem: 19788 +Test: [ 3300/21770] eta: 0:14:45 time: 0.0537 data: 0.0016 max mem: 19788 +Test: [ 3400/21770] eta: 0:14:38 time: 0.0458 data: 0.0015 max mem: 19788 +Test: [ 3500/21770] eta: 0:14:33 time: 0.0437 data: 0.0017 max mem: 19788 +Test: [ 3600/21770] eta: 0:14:27 time: 0.0476 data: 0.0016 max mem: 19788 +Test: [ 3700/21770] eta: 0:14:23 time: 0.0450 data: 0.0015 max mem: 19788 +Test: [ 3800/21770] eta: 0:14:18 time: 0.0464 data: 0.0015 max mem: 19788 +Test: [ 3900/21770] eta: 0:14:12 time: 0.0445 data: 0.0014 max mem: 19788 +Test: [ 4000/21770] eta: 0:14:09 time: 0.0527 data: 0.0018 max mem: 19788 +Test: [ 4100/21770] eta: 0:14:05 time: 0.0508 data: 0.0017 max mem: 19788 +Test: [ 4200/21770] eta: 0:14:00 time: 0.0427 data: 0.0014 max mem: 19788 +Test: [ 4300/21770] eta: 0:13:54 time: 0.0446 data: 0.0015 max mem: 19788 +Test: [ 4400/21770] eta: 0:13:48 time: 0.0438 data: 0.0014 max mem: 19788 +Test: [ 4500/21770] eta: 0:13:41 time: 0.0439 data: 0.0014 max mem: 19788 +Test: [ 4600/21770] eta: 0:13:37 time: 0.0537 data: 0.0017 max mem: 19788 +Test: [ 4700/21770] eta: 0:13:34 time: 0.0536 data: 0.0016 max mem: 19788 +Test: [ 4800/21770] eta: 0:13:31 time: 0.0533 data: 0.0019 max mem: 19788 +Test: [ 4900/21770] eta: 0:13:27 time: 0.0489 data: 0.0017 max mem: 19788 +Test: [ 5000/21770] eta: 0:13:21 time: 0.0439 data: 0.0014 max mem: 19788 +Test: [ 5100/21770] eta: 0:13:17 time: 0.0513 data: 0.0016 max mem: 19788 +Test: [ 5200/21770] eta: 0:13:12 time: 0.0531 data: 0.0017 max mem: 19788 +Test: [ 5300/21770] eta: 0:13:07 time: 0.0427 data: 0.0013 max mem: 19788 +Test: [ 5400/21770] eta: 0:13:03 time: 0.0526 data: 0.0016 max mem: 19788 +Test: [ 5500/21770] eta: 0:12:58 time: 0.0447 data: 0.0015 max mem: 19788 +Test: [ 5600/21770] eta: 0:12:52 time: 0.0499 data: 0.0016 max mem: 19788 +Test: [ 5700/21770] eta: 0:12:47 time: 0.0433 data: 0.0015 max mem: 19788 +Test: [ 5800/21770] eta: 0:12:41 time: 0.0516 data: 0.0016 max mem: 19788 +Test: [ 5900/21770] eta: 0:12:36 time: 0.0432 data: 0.0016 max mem: 19788 +Test: [ 6000/21770] eta: 0:12:32 time: 0.0540 data: 0.0018 max mem: 19788 +Test: [ 6100/21770] eta: 0:12:28 time: 0.0476 data: 0.0016 max mem: 19788 +Test: [ 6200/21770] eta: 0:12:22 time: 0.0523 data: 0.0017 max mem: 19788 +Test: [ 6300/21770] eta: 0:12:18 time: 0.0506 data: 0.0018 max mem: 19788 +Test: [ 6400/21770] eta: 0:12:13 time: 0.0455 data: 0.0014 max mem: 19788 +Test: [ 6500/21770] eta: 0:12:09 time: 0.0541 data: 0.0018 max mem: 19788 +Test: [ 6600/21770] eta: 0:12:03 time: 0.0437 data: 0.0019 max mem: 19788 +Test: [ 6700/21770] eta: 0:11:58 time: 0.0433 data: 0.0015 max mem: 19788 +Test: [ 6800/21770] eta: 0:11:52 time: 0.0431 data: 0.0014 max mem: 19788 +Test: [ 6900/21770] eta: 0:11:47 time: 0.0485 data: 0.0017 max mem: 19788 +Test: [ 7000/21770] eta: 0:11:43 time: 0.0513 data: 0.0018 max mem: 19788 +Test: [ 7100/21770] eta: 0:11:38 time: 0.0548 data: 0.0017 max mem: 19788 +Test: [ 7200/21770] eta: 0:11:34 time: 0.0451 data: 0.0016 max mem: 19788 +Test: [ 7300/21770] eta: 0:11:29 time: 0.0447 data: 0.0015 max mem: 19788 +Test: [ 7400/21770] eta: 0:11:23 time: 0.0432 data: 0.0015 max mem: 19788 +Test: [ 7500/21770] eta: 0:11:18 time: 0.0442 data: 0.0016 max mem: 19788 +Test: [ 7600/21770] eta: 0:11:14 time: 0.0462 data: 0.0016 max mem: 19788 +Test: [ 7700/21770] eta: 0:11:09 time: 0.0490 data: 0.0015 max mem: 19788 +Test: [ 7800/21770] eta: 0:11:04 time: 0.0456 data: 0.0015 max mem: 19788 +Test: [ 7900/21770] eta: 0:10:59 time: 0.0472 data: 0.0016 max mem: 19788 +Test: [ 8000/21770] eta: 0:10:53 time: 0.0451 data: 0.0015 max mem: 19788 +Test: [ 8100/21770] eta: 0:10:49 time: 0.0489 data: 0.0016 max mem: 19788 +Test: [ 8200/21770] eta: 0:10:45 time: 0.0502 data: 0.0017 max mem: 19788 +Test: [ 8300/21770] eta: 0:10:41 time: 0.0533 data: 0.0019 max mem: 19788 +Test: [ 8400/21770] eta: 0:10:36 time: 0.0488 data: 0.0016 max mem: 19788 +Test: [ 8500/21770] eta: 0:10:31 time: 0.0509 data: 0.0018 max mem: 19788 +Test: [ 8600/21770] eta: 0:10:27 time: 0.0475 data: 0.0015 max mem: 19788 +Test: [ 8700/21770] eta: 0:10:22 time: 0.0512 data: 0.0018 max mem: 19788 +Test: [ 8800/21770] eta: 0:10:17 time: 0.0444 data: 0.0014 max mem: 19788 +Test: [ 8900/21770] eta: 0:10:13 time: 0.0483 data: 0.0017 max mem: 19788 +Test: [ 9000/21770] eta: 0:10:08 time: 0.0442 data: 0.0015 max mem: 19788 +Test: [ 9100/21770] eta: 0:10:04 time: 0.0528 data: 0.0019 max mem: 19788 +Test: [ 9200/21770] eta: 0:09:59 time: 0.0439 data: 0.0015 max mem: 19788 +Test: [ 9300/21770] eta: 0:09:55 time: 0.0499 data: 0.0016 max mem: 19788 +Test: [ 9400/21770] eta: 0:09:50 time: 0.0445 data: 0.0016 max mem: 19788 +Test: [ 9500/21770] eta: 0:09:45 time: 0.0466 data: 0.0016 max mem: 19788 +Test: [ 9600/21770] eta: 0:09:40 time: 0.0509 data: 0.0016 max mem: 19788 +Test: [ 9700/21770] eta: 0:09:36 time: 0.0519 data: 0.0017 max mem: 19788 +Test: [ 9800/21770] eta: 0:09:31 time: 0.0448 data: 0.0015 max mem: 19788 +Test: [ 9900/21770] eta: 0:09:26 time: 0.0443 data: 0.0016 max mem: 19788 +Test: [10000/21770] eta: 0:09:21 time: 0.0451 data: 0.0015 max mem: 19788 +Test: [10100/21770] eta: 0:09:16 time: 0.0449 data: 0.0015 max mem: 19788 +Test: [10200/21770] eta: 0:09:11 time: 0.0432 data: 0.0014 max mem: 19788 +Test: [10300/21770] eta: 0:09:07 time: 0.0445 data: 0.0014 max mem: 19788 +Test: [10400/21770] eta: 0:09:02 time: 0.0454 data: 0.0015 max mem: 19788 +Test: [10500/21770] eta: 0:08:57 time: 0.0447 data: 0.0014 max mem: 19788 +Test: [10600/21770] eta: 0:08:52 time: 0.0448 data: 0.0015 max mem: 19788 +Test: [10700/21770] eta: 0:08:47 time: 0.0463 data: 0.0013 max mem: 19788 +Test: [10800/21770] eta: 0:08:43 time: 0.0523 data: 0.0018 max mem: 19788 +Test: [10900/21770] eta: 0:08:38 time: 0.0445 data: 0.0014 max mem: 19788 +Test: [11000/21770] eta: 0:08:33 time: 0.0449 data: 0.0015 max mem: 19788 +Test: [11100/21770] eta: 0:08:28 time: 0.0504 data: 0.0017 max mem: 19788 +Test: [11200/21770] eta: 0:08:23 time: 0.0451 data: 0.0014 max mem: 19788 +Test: [11300/21770] eta: 0:08:18 time: 0.0448 data: 0.0015 max mem: 19788 +Test: [11400/21770] eta: 0:08:13 time: 0.0429 data: 0.0015 max mem: 19788 +Test: [11500/21770] eta: 0:08:08 time: 0.0447 data: 0.0013 max mem: 19788 +Test: [11600/21770] eta: 0:08:04 time: 0.0522 data: 0.0017 max mem: 19788 +Test: [11700/21770] eta: 0:07:59 time: 0.0449 data: 0.0016 max mem: 19788 +Test: [11800/21770] eta: 0:07:54 time: 0.0441 data: 0.0015 max mem: 19788 +Test: [11900/21770] eta: 0:07:49 time: 0.0446 data: 0.0014 max mem: 19788 +Test: [12000/21770] eta: 0:07:44 time: 0.0525 data: 0.0015 max mem: 19788 +Test: [12100/21770] eta: 0:07:40 time: 0.0488 data: 0.0016 max mem: 19788 +Test: [12200/21770] eta: 0:07:35 time: 0.0439 data: 0.0016 max mem: 19788 +Test: [12300/21770] eta: 0:07:30 time: 0.0448 data: 0.0017 max mem: 19788 +Test: [12400/21770] eta: 0:07:25 time: 0.0526 data: 0.0017 max mem: 19788 +Test: [12500/21770] eta: 0:07:20 time: 0.0473 data: 0.0016 max mem: 19788 +Test: [12600/21770] eta: 0:07:16 time: 0.0499 data: 0.0016 max mem: 19788 +Test: [12700/21770] eta: 0:07:11 time: 0.0480 data: 0.0016 max mem: 19788 +Test: [12800/21770] eta: 0:07:06 time: 0.0435 data: 0.0014 max mem: 19788 +Test: [12900/21770] eta: 0:07:01 time: 0.0436 data: 0.0014 max mem: 19788 +Test: [13000/21770] eta: 0:06:56 time: 0.0439 data: 0.0015 max mem: 19788 +Test: [13100/21770] eta: 0:06:51 time: 0.0439 data: 0.0015 max mem: 19788 +Test: [13200/21770] eta: 0:06:46 time: 0.0490 data: 0.0014 max mem: 19788 +Test: [13300/21770] eta: 0:06:42 time: 0.0451 data: 0.0013 max mem: 19788 +Test: [13400/21770] eta: 0:06:37 time: 0.0452 data: 0.0015 max mem: 19788 +Test: [13500/21770] eta: 0:06:32 time: 0.0446 data: 0.0015 max mem: 19788 +Test: [13600/21770] eta: 0:06:27 time: 0.0444 data: 0.0017 max mem: 19788 +Test: [13700/21770] eta: 0:06:22 time: 0.0474 data: 0.0015 max mem: 19788 +Test: [13800/21770] eta: 0:06:18 time: 0.0478 data: 0.0017 max mem: 19788 +Test: [13900/21770] eta: 0:06:13 time: 0.0542 data: 0.0015 max mem: 19788 +Test: [14000/21770] eta: 0:06:08 time: 0.0431 data: 0.0014 max mem: 19788 +Test: [14100/21770] eta: 0:06:03 time: 0.0465 data: 0.0014 max mem: 19788 +Test: [14200/21770] eta: 0:05:59 time: 0.0483 data: 0.0015 max mem: 19788 +Test: [14300/21770] eta: 0:05:54 time: 0.0450 data: 0.0015 max mem: 19788 +Test: [14400/21770] eta: 0:05:49 time: 0.0493 data: 0.0018 max mem: 19788 +Test: [14500/21770] eta: 0:05:45 time: 0.0492 data: 0.0018 max mem: 19788 +Test: [14600/21770] eta: 0:05:40 time: 0.0518 data: 0.0017 max mem: 19788 +Test: [14700/21770] eta: 0:05:35 time: 0.0495 data: 0.0017 max mem: 19788 +Test: [14800/21770] eta: 0:05:30 time: 0.0521 data: 0.0017 max mem: 19788 +Test: [14900/21770] eta: 0:05:26 time: 0.0486 data: 0.0016 max mem: 19788 +Test: [15000/21770] eta: 0:05:21 time: 0.0496 data: 0.0017 max mem: 19788 +Test: [15100/21770] eta: 0:05:16 time: 0.0453 data: 0.0014 max mem: 19788 +Test: [15200/21770] eta: 0:05:12 time: 0.0492 data: 0.0018 max mem: 19788 +Test: [15300/21770] eta: 0:05:07 time: 0.0429 data: 0.0014 max mem: 19788 +Test: [15400/21770] eta: 0:05:02 time: 0.0526 data: 0.0018 max mem: 19788 +Test: [15500/21770] eta: 0:04:58 time: 0.0459 data: 0.0015 max mem: 19788 +Test: [15600/21770] eta: 0:04:53 time: 0.0517 data: 0.0015 max mem: 19788 +Test: [15700/21770] eta: 0:04:48 time: 0.0453 data: 0.0015 max mem: 19788 +Test: [15800/21770] eta: 0:04:43 time: 0.0494 data: 0.0015 max mem: 19788 +Test: [15900/21770] eta: 0:04:39 time: 0.0472 data: 0.0016 max mem: 19788 +Test: [16000/21770] eta: 0:04:34 time: 0.0535 data: 0.0015 max mem: 19788 +Test: [16100/21770] eta: 0:04:29 time: 0.0529 data: 0.0017 max mem: 19788 +Test: [16200/21770] eta: 0:04:24 time: 0.0468 data: 0.0015 max mem: 19788 +Test: [16300/21770] eta: 0:04:19 time: 0.0503 data: 0.0017 max mem: 19788 +Test: [16400/21770] eta: 0:04:15 time: 0.0463 data: 0.0016 max mem: 19788 +Test: [16500/21770] eta: 0:04:10 time: 0.0533 data: 0.0018 max mem: 19788 +Test: [16600/21770] eta: 0:04:05 time: 0.0496 data: 0.0017 max mem: 19788 +Test: [16700/21770] eta: 0:04:00 time: 0.0479 data: 0.0016 max mem: 19788 +Test: [16800/21770] eta: 0:03:56 time: 0.0526 data: 0.0018 max mem: 19788 +Test: [16900/21770] eta: 0:03:51 time: 0.0518 data: 0.0018 max mem: 19788 +Test: [17000/21770] eta: 0:03:46 time: 0.0433 data: 0.0015 max mem: 19788 +Test: [17100/21770] eta: 0:03:42 time: 0.0484 data: 0.0016 max mem: 19788 +Test: [17200/21770] eta: 0:03:37 time: 0.0450 data: 0.0015 max mem: 19788 +Test: [17300/21770] eta: 0:03:32 time: 0.0436 data: 0.0016 max mem: 19788 +Test: [17400/21770] eta: 0:03:27 time: 0.0454 data: 0.0016 max mem: 19788 +Test: [17500/21770] eta: 0:03:22 time: 0.0465 data: 0.0017 max mem: 19788 +Test: [17600/21770] eta: 0:03:18 time: 0.0457 data: 0.0015 max mem: 19788 +Test: [17700/21770] eta: 0:03:13 time: 0.0441 data: 0.0015 max mem: 19788 +Test: [17800/21770] eta: 0:03:08 time: 0.0521 data: 0.0018 max mem: 19788 +Test: [17900/21770] eta: 0:03:03 time: 0.0521 data: 0.0018 max mem: 19788 +Test: [18000/21770] eta: 0:02:59 time: 0.0435 data: 0.0014 max mem: 19788 +Test: [18100/21770] eta: 0:02:54 time: 0.0435 data: 0.0014 max mem: 19788 +Test: [18200/21770] eta: 0:02:49 time: 0.0446 data: 0.0015 max mem: 19788 +Test: [18300/21770] eta: 0:02:44 time: 0.0448 data: 0.0014 max mem: 19788 +Test: [18400/21770] eta: 0:02:39 time: 0.0542 data: 0.0018 max mem: 19788 +Test: [18500/21770] eta: 0:02:35 time: 0.0536 data: 0.0019 max mem: 19788 +Test: [18600/21770] eta: 0:02:30 time: 0.0536 data: 0.0017 max mem: 19788 +Test: [18700/21770] eta: 0:02:25 time: 0.0463 data: 0.0015 max mem: 19788 +Test: [18800/21770] eta: 0:02:21 time: 0.0431 data: 0.0014 max mem: 19788 +Test: [18900/21770] eta: 0:02:16 time: 0.0430 data: 0.0015 max mem: 19788 +Test: [19000/21770] eta: 0:02:11 time: 0.0442 data: 0.0014 max mem: 19788 +Test: [19100/21770] eta: 0:02:06 time: 0.0494 data: 0.0015 max mem: 19788 +Test: [19200/21770] eta: 0:02:01 time: 0.0488 data: 0.0017 max mem: 19788 +Test: [19300/21770] eta: 0:01:57 time: 0.0445 data: 0.0016 max mem: 19788 +Test: [19400/21770] eta: 0:01:52 time: 0.0444 data: 0.0015 max mem: 19788 +Test: [19500/21770] eta: 0:01:47 time: 0.0435 data: 0.0015 max mem: 19788 +Test: [19600/21770] eta: 0:01:42 time: 0.0452 data: 0.0015 max mem: 19788 +Test: [19700/21770] eta: 0:01:38 time: 0.0465 data: 0.0015 max mem: 19788 +Test: [19800/21770] eta: 0:01:33 time: 0.0494 data: 0.0015 max mem: 19788 +Test: [19900/21770] eta: 0:01:28 time: 0.0436 data: 0.0014 max mem: 19788 +Test: [20000/21770] eta: 0:01:23 time: 0.0431 data: 0.0014 max mem: 19788 +Test: [20100/21770] eta: 0:01:19 time: 0.0456 data: 0.0017 max mem: 19788 +Test: [20200/21770] eta: 0:01:14 time: 0.0471 data: 0.0016 max mem: 19788 +Test: [20300/21770] eta: 0:01:09 time: 0.0507 data: 0.0018 max mem: 19788 +Test: [20400/21770] eta: 0:01:04 time: 0.0437 data: 0.0015 max mem: 19788 +Test: [20500/21770] eta: 0:01:00 time: 0.0440 data: 0.0014 max mem: 19788 +Test: [20600/21770] eta: 0:00:55 time: 0.0456 data: 0.0017 max mem: 19788 +Test: [20700/21770] eta: 0:00:50 time: 0.0454 data: 0.0015 max mem: 19788 +Test: [20800/21770] eta: 0:00:45 time: 0.0437 data: 0.0015 max mem: 19788 +Test: [20900/21770] eta: 0:00:41 time: 0.0512 data: 0.0017 max mem: 19788 +Test: [21000/21770] eta: 0:00:36 time: 0.0477 data: 0.0015 max mem: 19788 +Test: [21100/21770] eta: 0:00:31 time: 0.0520 data: 0.0018 max mem: 19788 +Test: [21200/21770] eta: 0:00:27 time: 0.0452 data: 0.0017 max mem: 19788 +Test: [21300/21770] eta: 0:00:22 time: 0.0524 data: 0.0018 max mem: 19788 +Test: [21400/21770] eta: 0:00:17 time: 0.0473 data: 0.0016 max mem: 19788 +Test: [21500/21770] eta: 0:00:12 time: 0.0445 data: 0.0013 max mem: 19788 +Test: [21600/21770] eta: 0:00:08 time: 0.0440 data: 0.0015 max mem: 19788 +Test: [21700/21770] eta: 0:00:03 time: 0.0521 data: 0.0017 max mem: 19788 +Test: Total time: 0:17:13 +Final results: +Mean IoU is 64.04 + + precision@0.5 = 71.19 + precision@0.6 = 65.79 + precision@0.7 = 59.25 + precision@0.8 = 48.24 + precision@0.9 = 23.86 + overall IoU = 64.36 + mean IoU = 64.04 + +Mean accuracy for one-to-zero sample is 83.93 + +Average object IoU 0.6403780505804765 +Overall IoU 64.35953521728516 +Epoch: [22] [ 0/2138] eta: 5:30:27 lr: 2.4369752025516136e-05 loss: 0.0322 (0.0322) time: 9.2740 data: 1.2944 max mem: 19788 +Epoch: [22] [ 10/2138] eta: 2:04:09 lr: 2.436405260971768e-05 loss: 0.0254 (0.0268) time: 3.5008 data: 0.1206 max mem: 19788 +Epoch: [22] [ 20/2138] eta: 1:55:10 lr: 2.435835304577663e-05 loss: 0.0237 (0.0253) time: 2.9623 data: 0.0024 max mem: 19788 +Epoch: [22] [ 30/2138] eta: 1:51:20 lr: 2.4352653333650624e-05 loss: 0.0276 (0.0274) time: 2.9864 data: 0.0020 max mem: 19788 +Epoch: [22] [ 40/2138] eta: 1:48:31 lr: 2.434695347329726e-05 loss: 0.0283 (0.0275) time: 2.9369 data: 0.0025 max mem: 19788 +Epoch: [22] [ 50/2138] eta: 1:46:39 lr: 2.4341253464674138e-05 loss: 0.0252 (0.0276) time: 2.9039 data: 0.0023 max mem: 19788 +Epoch: [22] [ 60/2138] eta: 1:45:23 lr: 2.433555330773881e-05 loss: 0.0292 (0.0284) time: 2.9192 data: 0.0022 max mem: 19788 +Epoch: [22] [ 70/2138] eta: 1:44:04 lr: 2.4329853002448823e-05 loss: 0.0293 (0.0283) time: 2.9037 data: 0.0022 max mem: 19788 +Epoch: [22] [ 80/2138] eta: 1:43:03 lr: 2.4324152548761688e-05 loss: 0.0261 (0.0283) time: 2.8858 data: 0.0021 max mem: 19788 +Epoch: [22] [ 90/2138] eta: 1:42:11 lr: 2.43184519466349e-05 loss: 0.0255 (0.0283) time: 2.9027 data: 0.0023 max mem: 19788 +Epoch: [22] [ 100/2138] eta: 1:42:02 lr: 2.4312751196025933e-05 loss: 0.0274 (0.0281) time: 3.0026 data: 0.0025 max mem: 19788 +Epoch: [22] [ 110/2138] eta: 1:41:20 lr: 2.4307050296892227e-05 loss: 0.0274 (0.0284) time: 3.0174 data: 0.0027 max mem: 19788 +Epoch: [22] [ 120/2138] eta: 1:40:32 lr: 2.430134924919121e-05 loss: 0.0245 (0.0281) time: 2.9166 data: 0.0025 max mem: 19788 +Epoch: [22] [ 130/2138] eta: 1:39:53 lr: 2.429564805288028e-05 loss: 0.0263 (0.0280) time: 2.9109 data: 0.0024 max mem: 19788 +Epoch: [22] [ 140/2138] eta: 1:39:09 lr: 2.428994670791681e-05 loss: 0.0266 (0.0279) time: 2.9061 data: 0.0022 max mem: 19788 +Epoch: [22] [ 150/2138] eta: 1:38:27 lr: 2.4284245214258167e-05 loss: 0.0275 (0.0280) time: 2.8861 data: 0.0021 max mem: 19788 +Epoch: [22] [ 160/2138] eta: 1:37:47 lr: 2.4278543571861666e-05 loss: 0.0264 (0.0282) time: 2.8869 data: 0.0021 max mem: 19788 +Epoch: [22] [ 170/2138] eta: 1:37:28 lr: 2.4272841780684617e-05 loss: 0.0244 (0.0281) time: 2.9730 data: 0.0023 max mem: 19788 +Epoch: [22] [ 180/2138] eta: 1:36:54 lr: 2.4267139840684307e-05 loss: 0.0250 (0.0280) time: 2.9929 data: 0.0027 max mem: 19788 +Epoch: [22] [ 190/2138] eta: 1:36:27 lr: 2.4261437751817996e-05 loss: 0.0250 (0.0278) time: 2.9650 data: 0.0025 max mem: 19788 +Epoch: [22] [ 200/2138] eta: 1:35:55 lr: 2.4255735514042918e-05 loss: 0.0249 (0.0277) time: 2.9733 data: 0.0022 max mem: 19788 +Epoch: [22] [ 210/2138] eta: 1:35:26 lr: 2.425003312731629e-05 loss: 0.0256 (0.0278) time: 2.9603 data: 0.0026 max mem: 19788 +Epoch: [22] [ 220/2138] eta: 1:34:50 lr: 2.424433059159529e-05 loss: 0.0232 (0.0276) time: 2.9399 data: 0.0028 max mem: 19788 +Epoch: [22] [ 230/2138] eta: 1:34:22 lr: 2.42386279068371e-05 loss: 0.0255 (0.0282) time: 2.9404 data: 0.0026 max mem: 19788 +Epoch: [22] [ 240/2138] eta: 1:33:47 lr: 2.423292507299885e-05 loss: 0.0288 (0.0282) time: 2.9433 data: 0.0027 max mem: 19788 +Epoch: [22] [ 250/2138] eta: 1:33:18 lr: 2.4227222090037665e-05 loss: 0.0267 (0.0280) time: 2.9368 data: 0.0027 max mem: 19788 +Epoch: [22] [ 260/2138] eta: 1:32:54 lr: 2.422151895791064e-05 loss: 0.0244 (0.0283) time: 3.0047 data: 0.0026 max mem: 19788 +Epoch: [22] [ 270/2138] eta: 1:32:26 lr: 2.4215815676574845e-05 loss: 0.0249 (0.0282) time: 3.0202 data: 0.0023 max mem: 19788 +Epoch: [22] [ 280/2138] eta: 1:31:54 lr: 2.421011224598733e-05 loss: 0.0249 (0.0281) time: 2.9698 data: 0.0024 max mem: 19788 +Epoch: [22] [ 290/2138] eta: 1:31:23 lr: 2.420440866610511e-05 loss: 0.0286 (0.0284) time: 2.9393 data: 0.0024 max mem: 19788 +Epoch: [22] [ 300/2138] eta: 1:30:49 lr: 2.4198704936885203e-05 loss: 0.0301 (0.0284) time: 2.9202 data: 0.0025 max mem: 19788 +Epoch: [22] [ 310/2138] eta: 1:30:16 lr: 2.419300105828457e-05 loss: 0.0275 (0.0284) time: 2.9035 data: 0.0026 max mem: 19788 +Epoch: [22] [ 320/2138] eta: 1:29:44 lr: 2.4187297030260177e-05 loss: 0.0218 (0.0282) time: 2.9140 data: 0.0023 max mem: 19788 +Epoch: [22] [ 330/2138] eta: 1:29:17 lr: 2.4181592852768946e-05 loss: 0.0235 (0.0283) time: 2.9635 data: 0.0021 max mem: 19788 +Epoch: [22] [ 340/2138] eta: 1:28:52 lr: 2.417588852576779e-05 loss: 0.0264 (0.0282) time: 3.0263 data: 0.0022 max mem: 19788 +Epoch: [22] [ 350/2138] eta: 1:28:19 lr: 2.4170184049213584e-05 loss: 0.0237 (0.0281) time: 2.9775 data: 0.0021 max mem: 19788 +Epoch: [22] [ 360/2138] eta: 1:27:47 lr: 2.4164479423063197e-05 loss: 0.0258 (0.0281) time: 2.9059 data: 0.0022 max mem: 19788 +Epoch: [22] [ 370/2138] eta: 1:27:14 lr: 2.415877464727345e-05 loss: 0.0285 (0.0281) time: 2.9052 data: 0.0024 max mem: 19788 +Epoch: [22] [ 380/2138] eta: 1:26:42 lr: 2.4153069721801165e-05 loss: 0.0271 (0.0280) time: 2.9037 data: 0.0024 max mem: 19788 +Epoch: [22] [ 390/2138] eta: 1:26:10 lr: 2.4147364646603122e-05 loss: 0.0240 (0.0279) time: 2.9049 data: 0.0024 max mem: 19788 +Epoch: [22] [ 400/2138] eta: 1:25:38 lr: 2.4141659421636095e-05 loss: 0.0254 (0.0279) time: 2.9008 data: 0.0024 max mem: 19788 +Epoch: [22] [ 410/2138] eta: 1:25:09 lr: 2.4135954046856814e-05 loss: 0.0263 (0.0278) time: 2.9370 data: 0.0024 max mem: 19788 +Epoch: [22] [ 420/2138] eta: 1:24:37 lr: 2.4130248522221998e-05 loss: 0.0241 (0.0278) time: 2.9410 data: 0.0024 max mem: 19788 +Epoch: [22] [ 430/2138] eta: 1:24:06 lr: 2.4124542847688338e-05 loss: 0.0266 (0.0278) time: 2.9080 data: 0.0025 max mem: 19788 +Epoch: [22] [ 440/2138] eta: 1:23:34 lr: 2.4118837023212506e-05 loss: 0.0251 (0.0278) time: 2.9062 data: 0.0026 max mem: 19788 +Epoch: [22] [ 450/2138] eta: 1:23:04 lr: 2.4113131048751143e-05 loss: 0.0251 (0.0278) time: 2.9113 data: 0.0023 max mem: 19788 +Epoch: [22] [ 460/2138] eta: 1:22:33 lr: 2.410742492426087e-05 loss: 0.0245 (0.0277) time: 2.9237 data: 0.0021 max mem: 19788 +Epoch: [22] [ 470/2138] eta: 1:22:02 lr: 2.4101718649698278e-05 loss: 0.0258 (0.0277) time: 2.9148 data: 0.0022 max mem: 19788 +Epoch: [22] [ 480/2138] eta: 1:21:31 lr: 2.409601222501995e-05 loss: 0.0285 (0.0277) time: 2.9053 data: 0.0024 max mem: 19788 +Epoch: [22] [ 490/2138] eta: 1:21:07 lr: 2.4090305650182425e-05 loss: 0.0263 (0.0277) time: 3.0089 data: 0.0024 max mem: 19788 +Epoch: [22] [ 500/2138] eta: 1:20:36 lr: 2.4084598925142237e-05 loss: 0.0228 (0.0277) time: 3.0078 data: 0.0028 max mem: 19788 +Epoch: [22] [ 510/2138] eta: 1:20:04 lr: 2.4078892049855874e-05 loss: 0.0226 (0.0276) time: 2.9000 data: 0.0029 max mem: 19788 +Epoch: [22] [ 520/2138] eta: 1:19:33 lr: 2.407318502427982e-05 loss: 0.0243 (0.0276) time: 2.9017 data: 0.0027 max mem: 19788 +Epoch: [22] [ 530/2138] eta: 1:19:03 lr: 2.4067477848370527e-05 loss: 0.0270 (0.0276) time: 2.9069 data: 0.0026 max mem: 19788 +Epoch: [22] [ 540/2138] eta: 1:18:32 lr: 2.406177052208442e-05 loss: 0.0274 (0.0277) time: 2.9131 data: 0.0026 max mem: 19788 +Epoch: [22] [ 550/2138] eta: 1:18:02 lr: 2.4056063045377903e-05 loss: 0.0264 (0.0277) time: 2.9207 data: 0.0028 max mem: 19788 +Epoch: [22] [ 560/2138] eta: 1:17:37 lr: 2.405035541820736e-05 loss: 0.0264 (0.0277) time: 3.0136 data: 0.0026 max mem: 19788 +Epoch: [22] [ 570/2138] eta: 1:17:06 lr: 2.4044647640529142e-05 loss: 0.0262 (0.0276) time: 3.0104 data: 0.0026 max mem: 19788 +Epoch: [22] [ 580/2138] eta: 1:16:36 lr: 2.4038939712299585e-05 loss: 0.0247 (0.0277) time: 2.9109 data: 0.0027 max mem: 19788 +Epoch: [22] [ 590/2138] eta: 1:16:05 lr: 2.4033231633474993e-05 loss: 0.0264 (0.0277) time: 2.9067 data: 0.0025 max mem: 19788 +Epoch: [22] [ 600/2138] eta: 1:15:34 lr: 2.4027523404011646e-05 loss: 0.0257 (0.0277) time: 2.8997 data: 0.0024 max mem: 19788 +Epoch: [22] [ 610/2138] eta: 1:15:03 lr: 2.402181502386581e-05 loss: 0.0246 (0.0276) time: 2.8962 data: 0.0022 max mem: 19788 +Epoch: [22] [ 620/2138] eta: 1:14:33 lr: 2.401610649299371e-05 loss: 0.0258 (0.0277) time: 2.8978 data: 0.0021 max mem: 19788 +Epoch: [22] [ 630/2138] eta: 1:14:03 lr: 2.4010397811351567e-05 loss: 0.0286 (0.0277) time: 2.9086 data: 0.0024 max mem: 19788 +Epoch: [22] [ 640/2138] eta: 1:13:34 lr: 2.4004688978895558e-05 loss: 0.0287 (0.0277) time: 2.9615 data: 0.0025 max mem: 19788 +Epoch: [22] [ 650/2138] eta: 1:13:04 lr: 2.3998979995581856e-05 loss: 0.0293 (0.0277) time: 2.9536 data: 0.0024 max mem: 19788 +Epoch: [22] [ 660/2138] eta: 1:12:34 lr: 2.3993270861366582e-05 loss: 0.0252 (0.0277) time: 2.9048 data: 0.0026 max mem: 19788 +Epoch: [22] [ 670/2138] eta: 1:12:05 lr: 2.3987561576205862e-05 loss: 0.0251 (0.0277) time: 2.9478 data: 0.0025 max mem: 19788 +Epoch: [22] [ 680/2138] eta: 1:11:35 lr: 2.398185214005578e-05 loss: 0.0237 (0.0277) time: 2.9607 data: 0.0024 max mem: 19788 +Epoch: [22] [ 690/2138] eta: 1:11:06 lr: 2.39761425528724e-05 loss: 0.0234 (0.0277) time: 2.9450 data: 0.0025 max mem: 19788 +Epoch: [22] [ 700/2138] eta: 1:10:37 lr: 2.3970432814611766e-05 loss: 0.0248 (0.0277) time: 2.9564 data: 0.0024 max mem: 19788 +Epoch: [22] [ 710/2138] eta: 1:10:07 lr: 2.396472292522989e-05 loss: 0.0248 (0.0277) time: 2.9547 data: 0.0026 max mem: 19788 +Epoch: [22] [ 720/2138] eta: 1:09:37 lr: 2.3959012884682757e-05 loss: 0.0213 (0.0276) time: 2.9304 data: 0.0029 max mem: 19788 +Epoch: [22] [ 730/2138] eta: 1:09:07 lr: 2.3953302692926343e-05 loss: 0.0237 (0.0276) time: 2.9040 data: 0.0026 max mem: 19788 +Epoch: [22] [ 740/2138] eta: 1:08:37 lr: 2.3947592349916584e-05 loss: 0.0270 (0.0277) time: 2.9011 data: 0.0023 max mem: 19788 +Epoch: [22] [ 750/2138] eta: 1:08:06 lr: 2.3941881855609407e-05 loss: 0.0270 (0.0277) time: 2.9050 data: 0.0024 max mem: 19788 +Epoch: [22] [ 760/2138] eta: 1:07:36 lr: 2.3936171209960688e-05 loss: 0.0272 (0.0277) time: 2.9116 data: 0.0026 max mem: 19788 +Epoch: [22] [ 770/2138] eta: 1:07:06 lr: 2.393046041292631e-05 loss: 0.0241 (0.0276) time: 2.9022 data: 0.0025 max mem: 19788 +Epoch: [22] [ 780/2138] eta: 1:06:36 lr: 2.3924749464462106e-05 loss: 0.0221 (0.0276) time: 2.9056 data: 0.0026 max mem: 19788 +Epoch: [22] [ 790/2138] eta: 1:06:07 lr: 2.3919038364523912e-05 loss: 0.0246 (0.0276) time: 2.9392 data: 0.0030 max mem: 19788 +Epoch: [22] [ 800/2138] eta: 1:05:38 lr: 2.3913327113067498e-05 loss: 0.0257 (0.0276) time: 2.9546 data: 0.0028 max mem: 19788 +Epoch: [22] [ 810/2138] eta: 1:05:08 lr: 2.3907615710048657e-05 loss: 0.0265 (0.0275) time: 2.9298 data: 0.0026 max mem: 19788 +Epoch: [22] [ 820/2138] eta: 1:04:38 lr: 2.3901904155423116e-05 loss: 0.0248 (0.0275) time: 2.9178 data: 0.0025 max mem: 19788 +Epoch: [22] [ 830/2138] eta: 1:04:08 lr: 2.389619244914661e-05 loss: 0.0234 (0.0275) time: 2.9188 data: 0.0025 max mem: 19788 +Epoch: [22] [ 840/2138] eta: 1:03:38 lr: 2.3890480591174827e-05 loss: 0.0219 (0.0275) time: 2.9190 data: 0.0027 max mem: 19788 +Epoch: [22] [ 850/2138] eta: 1:03:08 lr: 2.3884768581463444e-05 loss: 0.0242 (0.0275) time: 2.9141 data: 0.0024 max mem: 19788 +Epoch: [22] [ 860/2138] eta: 1:02:41 lr: 2.3879056419968096e-05 loss: 0.0242 (0.0275) time: 2.9878 data: 0.0022 max mem: 19788 +Epoch: [22] [ 870/2138] eta: 1:02:12 lr: 2.3873344106644417e-05 loss: 0.0233 (0.0274) time: 3.0153 data: 0.0024 max mem: 19788 +Epoch: [22] [ 880/2138] eta: 1:01:43 lr: 2.3867631641447998e-05 loss: 0.0243 (0.0274) time: 2.9610 data: 0.0024 max mem: 19788 +Epoch: [22] [ 890/2138] eta: 1:01:13 lr: 2.3861919024334414e-05 loss: 0.0262 (0.0274) time: 2.9423 data: 0.0027 max mem: 19788 +Epoch: [22] [ 900/2138] eta: 1:00:43 lr: 2.385620625525921e-05 loss: 0.0231 (0.0274) time: 2.9092 data: 0.0025 max mem: 19788 +Epoch: [22] [ 910/2138] eta: 1:00:13 lr: 2.3850493334177905e-05 loss: 0.0214 (0.0274) time: 2.9015 data: 0.0021 max mem: 19788 +Epoch: [22] [ 920/2138] eta: 0:59:43 lr: 2.3844780261046008e-05 loss: 0.0231 (0.0274) time: 2.9211 data: 0.0022 max mem: 19788 +Epoch: [22] [ 930/2138] eta: 0:59:14 lr: 2.3839067035818977e-05 loss: 0.0276 (0.0274) time: 2.9264 data: 0.0024 max mem: 19788 +Epoch: [22] [ 940/2138] eta: 0:58:45 lr: 2.383335365845227e-05 loss: 0.0281 (0.0274) time: 2.9681 data: 0.0027 max mem: 19788 +Epoch: [22] [ 950/2138] eta: 0:58:15 lr: 2.3827640128901306e-05 loss: 0.0243 (0.0274) time: 2.9663 data: 0.0026 max mem: 19788 +Epoch: [22] [ 960/2138] eta: 0:57:45 lr: 2.3821926447121484e-05 loss: 0.0270 (0.0274) time: 2.9092 data: 0.0026 max mem: 19788 +Epoch: [22] [ 970/2138] eta: 0:57:15 lr: 2.3816212613068177e-05 loss: 0.0288 (0.0274) time: 2.9006 data: 0.0028 max mem: 19788 +Epoch: [22] [ 980/2138] eta: 0:56:46 lr: 2.3810498626696733e-05 loss: 0.0248 (0.0274) time: 2.8971 data: 0.0027 max mem: 19788 +Epoch: [22] [ 990/2138] eta: 0:56:16 lr: 2.380478448796247e-05 loss: 0.0248 (0.0274) time: 2.9209 data: 0.0027 max mem: 19788 +Epoch: [22] [1000/2138] eta: 0:55:46 lr: 2.37990701968207e-05 loss: 0.0241 (0.0274) time: 2.9283 data: 0.0025 max mem: 19788 +Epoch: [22] [1010/2138] eta: 0:55:18 lr: 2.3793355753226676e-05 loss: 0.0232 (0.0274) time: 2.9842 data: 0.0024 max mem: 19788 +Epoch: [22] [1020/2138] eta: 0:54:49 lr: 2.3787641157135665e-05 loss: 0.0256 (0.0275) time: 2.9849 data: 0.0025 max mem: 19788 +Epoch: [22] [1030/2138] eta: 0:54:19 lr: 2.3781926408502873e-05 loss: 0.0253 (0.0275) time: 2.9185 data: 0.0027 max mem: 19788 +Epoch: [22] [1040/2138] eta: 0:53:49 lr: 2.3776211507283517e-05 loss: 0.0252 (0.0275) time: 2.9182 data: 0.0027 max mem: 19788 +Epoch: [22] [1050/2138] eta: 0:53:19 lr: 2.377049645343275e-05 loss: 0.0252 (0.0275) time: 2.9068 data: 0.0024 max mem: 19788 +Epoch: [22] [1060/2138] eta: 0:52:50 lr: 2.376478124690573e-05 loss: 0.0253 (0.0275) time: 2.9159 data: 0.0021 max mem: 19788 +Epoch: [22] [1070/2138] eta: 0:52:20 lr: 2.3759065887657574e-05 loss: 0.0265 (0.0275) time: 2.9190 data: 0.0023 max mem: 19788 +Epoch: [22] [1080/2138] eta: 0:51:50 lr: 2.375335037564339e-05 loss: 0.0227 (0.0275) time: 2.9100 data: 0.0024 max mem: 19788 +Epoch: [22] [1090/2138] eta: 0:51:22 lr: 2.3747634710818234e-05 loss: 0.0227 (0.0275) time: 2.9631 data: 0.0026 max mem: 19788 +Epoch: [22] [1100/2138] eta: 0:50:52 lr: 2.3741918893137167e-05 loss: 0.0267 (0.0275) time: 2.9558 data: 0.0029 max mem: 19788 +Epoch: [22] [1110/2138] eta: 0:50:22 lr: 2.3736202922555198e-05 loss: 0.0261 (0.0275) time: 2.9061 data: 0.0029 max mem: 19788 +Epoch: [22] [1120/2138] eta: 0:49:53 lr: 2.3730486799027332e-05 loss: 0.0234 (0.0274) time: 2.9071 data: 0.0028 max mem: 19788 +Epoch: [22] [1130/2138] eta: 0:49:23 lr: 2.3724770522508535e-05 loss: 0.0216 (0.0274) time: 2.9248 data: 0.0025 max mem: 19788 +Epoch: [22] [1140/2138] eta: 0:48:53 lr: 2.3719054092953757e-05 loss: 0.0252 (0.0274) time: 2.9204 data: 0.0024 max mem: 19788 +Epoch: [22] [1150/2138] eta: 0:48:24 lr: 2.371333751031791e-05 loss: 0.0224 (0.0274) time: 2.8953 data: 0.0024 max mem: 19788 +Epoch: [22] [1160/2138] eta: 0:47:54 lr: 2.37076207745559e-05 loss: 0.0217 (0.0273) time: 2.9246 data: 0.0024 max mem: 19788 +Epoch: [22] [1170/2138] eta: 0:47:25 lr: 2.3701903885622585e-05 loss: 0.0241 (0.0273) time: 2.9351 data: 0.0026 max mem: 19788 +Epoch: [22] [1180/2138] eta: 0:46:55 lr: 2.369618684347282e-05 loss: 0.0246 (0.0273) time: 2.9166 data: 0.0026 max mem: 19788 +Epoch: [22] [1190/2138] eta: 0:46:26 lr: 2.3690469648061413e-05 loss: 0.0246 (0.0273) time: 2.9281 data: 0.0027 max mem: 19788 +Epoch: [22] [1200/2138] eta: 0:45:56 lr: 2.3684752299343164e-05 loss: 0.0230 (0.0272) time: 2.9253 data: 0.0029 max mem: 19788 +Epoch: [22] [1210/2138] eta: 0:45:26 lr: 2.367903479727284e-05 loss: 0.0247 (0.0273) time: 2.9020 data: 0.0029 max mem: 19788 +Epoch: [22] [1220/2138] eta: 0:44:57 lr: 2.3673317141805176e-05 loss: 0.0248 (0.0272) time: 2.9182 data: 0.0027 max mem: 19788 +Epoch: [22] [1230/2138] eta: 0:44:28 lr: 2.3667599332894903e-05 loss: 0.0243 (0.0272) time: 2.9322 data: 0.0027 max mem: 19788 +Epoch: [22] [1240/2138] eta: 0:43:59 lr: 2.3661881370496693e-05 loss: 0.0244 (0.0272) time: 2.9654 data: 0.0027 max mem: 19788 +Epoch: [22] [1250/2138] eta: 0:43:29 lr: 2.365616325456523e-05 loss: 0.0248 (0.0272) time: 2.9554 data: 0.0026 max mem: 19788 +Epoch: [22] [1260/2138] eta: 0:42:59 lr: 2.3650444985055143e-05 loss: 0.0232 (0.0272) time: 2.9041 data: 0.0026 max mem: 19788 +Epoch: [22] [1270/2138] eta: 0:42:30 lr: 2.3644726561921053e-05 loss: 0.0237 (0.0272) time: 2.9048 data: 0.0027 max mem: 19788 +Epoch: [22] [1280/2138] eta: 0:42:00 lr: 2.363900798511754e-05 loss: 0.0242 (0.0271) time: 2.9042 data: 0.0028 max mem: 19788 +Epoch: [22] [1290/2138] eta: 0:41:31 lr: 2.3633289254599177e-05 loss: 0.0259 (0.0272) time: 2.9135 data: 0.0027 max mem: 19788 +Epoch: [22] [1300/2138] eta: 0:41:01 lr: 2.3627570370320492e-05 loss: 0.0265 (0.0271) time: 2.9139 data: 0.0026 max mem: 19788 +Epoch: [22] [1310/2138] eta: 0:40:32 lr: 2.362185133223601e-05 loss: 0.0249 (0.0271) time: 2.9719 data: 0.0026 max mem: 19788 +Epoch: [22] [1320/2138] eta: 0:40:03 lr: 2.36161321403002e-05 loss: 0.0266 (0.0271) time: 3.0091 data: 0.0023 max mem: 19788 +Epoch: [22] [1330/2138] eta: 0:39:34 lr: 2.361041279446754e-05 loss: 0.0242 (0.0271) time: 2.9369 data: 0.0021 max mem: 19788 +Epoch: [22] [1340/2138] eta: 0:39:04 lr: 2.3604693294692444e-05 loss: 0.0243 (0.0271) time: 2.9072 data: 0.0022 max mem: 19788 +Epoch: [22] [1350/2138] eta: 0:38:35 lr: 2.359897364092934e-05 loss: 0.0264 (0.0272) time: 2.9128 data: 0.0025 max mem: 19788 +Epoch: [22] [1360/2138] eta: 0:38:05 lr: 2.3593253833132606e-05 loss: 0.0268 (0.0271) time: 2.9010 data: 0.0026 max mem: 19788 +Epoch: [22] [1370/2138] eta: 0:37:35 lr: 2.3587533871256596e-05 loss: 0.0268 (0.0272) time: 2.9025 data: 0.0024 max mem: 19788 +Epoch: [22] [1380/2138] eta: 0:37:06 lr: 2.358181375525564e-05 loss: 0.0264 (0.0272) time: 2.9102 data: 0.0024 max mem: 19788 +Epoch: [22] [1390/2138] eta: 0:36:37 lr: 2.3576093485084053e-05 loss: 0.0223 (0.0271) time: 2.9907 data: 0.0024 max mem: 19788 +Epoch: [22] [1400/2138] eta: 0:36:08 lr: 2.35703730606961e-05 loss: 0.0219 (0.0271) time: 3.0139 data: 0.0024 max mem: 19788 +Epoch: [22] [1410/2138] eta: 0:35:38 lr: 2.3564652482046054e-05 loss: 0.0234 (0.0271) time: 2.9368 data: 0.0026 max mem: 19788 +Epoch: [22] [1420/2138] eta: 0:35:09 lr: 2.3558931749088123e-05 loss: 0.0256 (0.0271) time: 2.9210 data: 0.0025 max mem: 19788 +Epoch: [22] [1430/2138] eta: 0:34:39 lr: 2.3553210861776522e-05 loss: 0.0257 (0.0271) time: 2.9134 data: 0.0022 max mem: 19788 +Epoch: [22] [1440/2138] eta: 0:34:10 lr: 2.354748982006542e-05 loss: 0.0263 (0.0271) time: 2.9073 data: 0.0021 max mem: 19788 +Epoch: [22] [1450/2138] eta: 0:33:41 lr: 2.3541768623908976e-05 loss: 0.0271 (0.0271) time: 2.9205 data: 0.0021 max mem: 19788 +Epoch: [22] [1460/2138] eta: 0:33:11 lr: 2.3536047273261304e-05 loss: 0.0243 (0.0271) time: 2.9493 data: 0.0024 max mem: 19788 +Epoch: [22] [1470/2138] eta: 0:32:42 lr: 2.3530325768076513e-05 loss: 0.0234 (0.0271) time: 2.9881 data: 0.0026 max mem: 19788 +Epoch: [22] [1480/2138] eta: 0:32:13 lr: 2.3524604108308662e-05 loss: 0.0222 (0.0271) time: 2.9537 data: 0.0026 max mem: 19788 +Epoch: [22] [1490/2138] eta: 0:31:43 lr: 2.351888229391181e-05 loss: 0.0244 (0.0271) time: 2.9053 data: 0.0025 max mem: 19788 +Epoch: [22] [1500/2138] eta: 0:31:14 lr: 2.351316032483997e-05 loss: 0.0255 (0.0271) time: 2.9118 data: 0.0023 max mem: 19788 +Epoch: [22] [1510/2138] eta: 0:30:44 lr: 2.350743820104713e-05 loss: 0.0240 (0.0271) time: 2.9208 data: 0.0022 max mem: 19788 +Epoch: [22] [1520/2138] eta: 0:30:15 lr: 2.3501715922487272e-05 loss: 0.0240 (0.0271) time: 2.9173 data: 0.0023 max mem: 19788 +Epoch: [22] [1530/2138] eta: 0:29:45 lr: 2.349599348911432e-05 loss: 0.0248 (0.0271) time: 2.9171 data: 0.0026 max mem: 19788 +Epoch: [22] [1540/2138] eta: 0:29:16 lr: 2.349027090088221e-05 loss: 0.0247 (0.0270) time: 2.9467 data: 0.0028 max mem: 19788 +Epoch: [22] [1550/2138] eta: 0:28:47 lr: 2.348454815774481e-05 loss: 0.0232 (0.0270) time: 2.9474 data: 0.0026 max mem: 19788 +Epoch: [22] [1560/2138] eta: 0:28:17 lr: 2.3478825259656e-05 loss: 0.0271 (0.0270) time: 2.9112 data: 0.0026 max mem: 19788 +Epoch: [22] [1570/2138] eta: 0:27:48 lr: 2.3473102206569604e-05 loss: 0.0271 (0.0270) time: 2.9071 data: 0.0028 max mem: 19788 +Epoch: [22] [1580/2138] eta: 0:27:18 lr: 2.3467378998439444e-05 loss: 0.0254 (0.0270) time: 2.9161 data: 0.0026 max mem: 19788 +Epoch: [22] [1590/2138] eta: 0:26:49 lr: 2.346165563521929e-05 loss: 0.0260 (0.0270) time: 2.9093 data: 0.0026 max mem: 19788 +Epoch: [22] [1600/2138] eta: 0:26:19 lr: 2.3455932116862918e-05 loss: 0.0287 (0.0270) time: 2.9033 data: 0.0030 max mem: 19788 +Epoch: [22] [1610/2138] eta: 0:25:50 lr: 2.345020844332404e-05 loss: 0.0295 (0.0270) time: 2.9311 data: 0.0027 max mem: 19788 +Epoch: [22] [1620/2138] eta: 0:25:21 lr: 2.3444484614556378e-05 loss: 0.0225 (0.0270) time: 2.9307 data: 0.0024 max mem: 19788 +Epoch: [22] [1630/2138] eta: 0:24:51 lr: 2.34387606305136e-05 loss: 0.0210 (0.0270) time: 2.9093 data: 0.0023 max mem: 19788 +Epoch: [22] [1640/2138] eta: 0:24:22 lr: 2.3433036491149364e-05 loss: 0.0272 (0.0270) time: 2.9297 data: 0.0023 max mem: 19788 +Epoch: [22] [1650/2138] eta: 0:23:52 lr: 2.3427312196417286e-05 loss: 0.0280 (0.0270) time: 2.9243 data: 0.0023 max mem: 19788 +Epoch: [22] [1660/2138] eta: 0:23:23 lr: 2.3421587746270983e-05 loss: 0.0269 (0.0270) time: 2.9067 data: 0.0022 max mem: 19788 +Epoch: [22] [1670/2138] eta: 0:22:53 lr: 2.341586314066401e-05 loss: 0.0222 (0.0270) time: 2.9008 data: 0.0021 max mem: 19788 +Epoch: [22] [1680/2138] eta: 0:22:24 lr: 2.341013837954993e-05 loss: 0.0226 (0.0270) time: 2.9232 data: 0.0024 max mem: 19788 +Epoch: [22] [1690/2138] eta: 0:21:55 lr: 2.3404413462882246e-05 loss: 0.0231 (0.0270) time: 3.0068 data: 0.0026 max mem: 19788 +Epoch: [22] [1700/2138] eta: 0:21:26 lr: 2.339868839061447e-05 loss: 0.0215 (0.0269) time: 2.9802 data: 0.0026 max mem: 19788 +Epoch: [22] [1710/2138] eta: 0:20:56 lr: 2.339296316270005e-05 loss: 0.0221 (0.0269) time: 2.9022 data: 0.0029 max mem: 19788 +Epoch: [22] [1720/2138] eta: 0:20:27 lr: 2.338723777909244e-05 loss: 0.0231 (0.0269) time: 2.9031 data: 0.0027 max mem: 19788 +Epoch: [22] [1730/2138] eta: 0:19:57 lr: 2.3381512239745045e-05 loss: 0.0257 (0.0269) time: 2.9117 data: 0.0028 max mem: 19788 +Epoch: [22] [1740/2138] eta: 0:19:28 lr: 2.3375786544611264e-05 loss: 0.0228 (0.0269) time: 2.9099 data: 0.0028 max mem: 19788 +Epoch: [22] [1750/2138] eta: 0:18:58 lr: 2.3370060693644444e-05 loss: 0.0233 (0.0269) time: 2.9040 data: 0.0024 max mem: 19788 +Epoch: [22] [1760/2138] eta: 0:18:29 lr: 2.336433468679793e-05 loss: 0.0232 (0.0269) time: 2.9582 data: 0.0021 max mem: 19788 +Epoch: [22] [1770/2138] eta: 0:18:00 lr: 2.3358608524025022e-05 loss: 0.0229 (0.0269) time: 2.9744 data: 0.0023 max mem: 19788 +Epoch: [22] [1780/2138] eta: 0:17:31 lr: 2.3352882205279006e-05 loss: 0.0222 (0.0268) time: 2.9243 data: 0.0027 max mem: 19788 +Epoch: [22] [1790/2138] eta: 0:17:01 lr: 2.3347155730513126e-05 loss: 0.0223 (0.0268) time: 2.9074 data: 0.0028 max mem: 19788 +Epoch: [22] [1800/2138] eta: 0:16:32 lr: 2.334142909968062e-05 loss: 0.0266 (0.0269) time: 2.9156 data: 0.0027 max mem: 19788 +Epoch: [22] [1810/2138] eta: 0:16:02 lr: 2.3335702312734688e-05 loss: 0.0261 (0.0269) time: 2.9106 data: 0.0027 max mem: 19788 +Epoch: [22] [1820/2138] eta: 0:15:33 lr: 2.332997536962849e-05 loss: 0.0231 (0.0268) time: 2.9081 data: 0.0028 max mem: 19788 +Epoch: [22] [1830/2138] eta: 0:15:04 lr: 2.3324248270315187e-05 loss: 0.0227 (0.0268) time: 2.9231 data: 0.0030 max mem: 19788 +Epoch: [22] [1840/2138] eta: 0:14:34 lr: 2.3318521014747892e-05 loss: 0.0237 (0.0268) time: 2.9397 data: 0.0026 max mem: 19788 +Epoch: [22] [1850/2138] eta: 0:14:05 lr: 2.33127936028797e-05 loss: 0.0256 (0.0269) time: 2.9286 data: 0.0022 max mem: 19788 +Epoch: [22] [1860/2138] eta: 0:13:35 lr: 2.3307066034663674e-05 loss: 0.0252 (0.0269) time: 2.9055 data: 0.0024 max mem: 19788 +Epoch: [22] [1870/2138] eta: 0:13:06 lr: 2.330133831005286e-05 loss: 0.0267 (0.0269) time: 2.9191 data: 0.0026 max mem: 19788 +Epoch: [22] [1880/2138] eta: 0:12:37 lr: 2.3295610429000258e-05 loss: 0.0216 (0.0269) time: 2.9304 data: 0.0025 max mem: 19788 +Epoch: [22] [1890/2138] eta: 0:12:07 lr: 2.328988239145887e-05 loss: 0.0203 (0.0270) time: 2.9121 data: 0.0025 max mem: 19788 +Epoch: [22] [1900/2138] eta: 0:11:38 lr: 2.328415419738164e-05 loss: 0.0271 (0.0270) time: 2.9128 data: 0.0027 max mem: 19788 +Epoch: [22] [1910/2138] eta: 0:11:09 lr: 2.3278425846721506e-05 loss: 0.0259 (0.0270) time: 2.9419 data: 0.0028 max mem: 19788 +Epoch: [22] [1920/2138] eta: 0:10:39 lr: 2.3272697339431364e-05 loss: 0.0238 (0.0270) time: 2.9647 data: 0.0027 max mem: 19788 +Epoch: [22] [1930/2138] eta: 0:10:10 lr: 2.3266968675464108e-05 loss: 0.0252 (0.0270) time: 2.9390 data: 0.0025 max mem: 19788 +Epoch: [22] [1940/2138] eta: 0:09:41 lr: 2.326123985477257e-05 loss: 0.0252 (0.0270) time: 2.9011 data: 0.0025 max mem: 19788 +Epoch: [22] [1950/2138] eta: 0:09:11 lr: 2.3255510877309583e-05 loss: 0.0267 (0.0270) time: 2.9122 data: 0.0027 max mem: 19788 +Epoch: [22] [1960/2138] eta: 0:08:42 lr: 2.3249781743027937e-05 loss: 0.0247 (0.0270) time: 2.9137 data: 0.0026 max mem: 19788 +Epoch: [22] [1970/2138] eta: 0:08:12 lr: 2.324405245188041e-05 loss: 0.0224 (0.0270) time: 2.9037 data: 0.0024 max mem: 19788 +Epoch: [22] [1980/2138] eta: 0:07:43 lr: 2.3238323003819733e-05 loss: 0.0248 (0.0270) time: 2.9105 data: 0.0026 max mem: 19788 +Epoch: [22] [1990/2138] eta: 0:07:14 lr: 2.323259339879863e-05 loss: 0.0256 (0.0270) time: 2.9379 data: 0.0027 max mem: 19788 +Epoch: [22] [2000/2138] eta: 0:06:44 lr: 2.3226863636769776e-05 loss: 0.0229 (0.0269) time: 2.9447 data: 0.0024 max mem: 19788 +Epoch: [22] [2010/2138] eta: 0:06:15 lr: 2.3221133717685843e-05 loss: 0.0245 (0.0269) time: 2.9368 data: 0.0023 max mem: 19788 +Epoch: [22] [2020/2138] eta: 0:05:46 lr: 2.3215403641499457e-05 loss: 0.0265 (0.0269) time: 2.9443 data: 0.0025 max mem: 19788 +Epoch: [22] [2030/2138] eta: 0:05:16 lr: 2.3209673408163227e-05 loss: 0.0262 (0.0269) time: 2.9413 data: 0.0026 max mem: 19788 +Epoch: [22] [2040/2138] eta: 0:04:47 lr: 2.3203943017629724e-05 loss: 0.0236 (0.0269) time: 2.9235 data: 0.0027 max mem: 19788 +Epoch: [22] [2050/2138] eta: 0:04:18 lr: 2.319821246985151e-05 loss: 0.0235 (0.0269) time: 2.9038 data: 0.0026 max mem: 19788 +Epoch: [22] [2060/2138] eta: 0:03:48 lr: 2.3192481764781095e-05 loss: 0.0237 (0.0269) time: 3.0738 data: 0.0024 max mem: 19788 +Epoch: [22] [2070/2138] eta: 0:03:19 lr: 2.3186750902370988e-05 loss: 0.0253 (0.0269) time: 3.0847 data: 0.0026 max mem: 19788 +Epoch: [22] [2080/2138] eta: 0:02:50 lr: 2.318101988257365e-05 loss: 0.0234 (0.0269) time: 2.9719 data: 0.0029 max mem: 19788 +Epoch: [22] [2090/2138] eta: 0:02:20 lr: 2.3175288705341525e-05 loss: 0.0257 (0.0269) time: 2.9647 data: 0.0030 max mem: 19788 +Epoch: [22] [2100/2138] eta: 0:01:51 lr: 2.316955737062702e-05 loss: 0.0225 (0.0269) time: 2.9102 data: 0.0027 max mem: 19788 +Epoch: [22] [2110/2138] eta: 0:01:22 lr: 2.3163825878382536e-05 loss: 0.0261 (0.0269) time: 2.9296 data: 0.0023 max mem: 19788 +Epoch: [22] [2120/2138] eta: 0:00:52 lr: 2.315809422856042e-05 loss: 0.0294 (0.0269) time: 2.9503 data: 0.0023 max mem: 19788 +Epoch: [22] [2130/2138] eta: 0:00:23 lr: 2.3152362421113002e-05 loss: 0.0294 (0.0270) time: 2.9319 data: 0.0023 max mem: 19788 +Epoch: [22] Total time: 1:44:37 +Test: [ 0/21770] eta: 16:08:22 time: 2.6689 data: 2.6059 max mem: 19788 +Test: [ 100/21770] eta: 0:25:30 time: 0.0434 data: 0.0015 max mem: 19788 +Test: [ 200/21770] eta: 0:20:47 time: 0.0434 data: 0.0013 max mem: 19788 +Test: [ 300/21770] eta: 0:19:22 time: 0.0431 data: 0.0015 max mem: 19788 +Test: [ 400/21770] eta: 0:18:46 time: 0.0490 data: 0.0017 max mem: 19788 +Test: [ 500/21770] eta: 0:18:34 time: 0.0539 data: 0.0016 max mem: 19788 +Test: [ 600/21770] eta: 0:18:17 time: 0.0507 data: 0.0015 max mem: 19788 +Test: [ 700/21770] eta: 0:17:53 time: 0.0451 data: 0.0014 max mem: 19788 +Test: [ 800/21770] eta: 0:17:40 time: 0.0442 data: 0.0013 max mem: 19788 +Test: [ 900/21770] eta: 0:17:23 time: 0.0451 data: 0.0016 max mem: 19788 +Test: [ 1000/21770] eta: 0:17:07 time: 0.0453 data: 0.0015 max mem: 19788 +Test: [ 1100/21770] eta: 0:17:02 time: 0.0504 data: 0.0016 max mem: 19788 +Test: [ 1200/21770] eta: 0:16:53 time: 0.0440 data: 0.0014 max mem: 19788 +Test: [ 1300/21770] eta: 0:16:50 time: 0.0494 data: 0.0018 max mem: 19788 +Test: [ 1400/21770] eta: 0:16:42 time: 0.0521 data: 0.0018 max mem: 19788 +Test: [ 1500/21770] eta: 0:16:31 time: 0.0423 data: 0.0015 max mem: 19788 +Test: [ 1600/21770] eta: 0:16:20 time: 0.0454 data: 0.0016 max mem: 19788 +Test: [ 1700/21770] eta: 0:16:11 time: 0.0425 data: 0.0015 max mem: 19788 +Test: [ 1800/21770] eta: 0:16:01 time: 0.0429 data: 0.0017 max mem: 19788 +Test: [ 1900/21770] eta: 0:15:56 time: 0.0428 data: 0.0015 max mem: 19788 +Test: [ 2000/21770] eta: 0:15:50 time: 0.0426 data: 0.0018 max mem: 19788 +Test: [ 2100/21770] eta: 0:15:47 time: 0.0521 data: 0.0014 max mem: 19788 +Test: [ 2200/21770] eta: 0:15:41 time: 0.0434 data: 0.0014 max mem: 19788 +Test: [ 2300/21770] eta: 0:15:32 time: 0.0436 data: 0.0015 max mem: 19788 +Test: [ 2400/21770] eta: 0:15:25 time: 0.0486 data: 0.0016 max mem: 19788 +Test: [ 2500/21770] eta: 0:15:18 time: 0.0432 data: 0.0014 max mem: 19788 +Test: [ 2600/21770] eta: 0:15:15 time: 0.0513 data: 0.0018 max mem: 19788 +Test: [ 2700/21770] eta: 0:15:10 time: 0.0519 data: 0.0017 max mem: 19788 +Test: [ 2800/21770] eta: 0:15:04 time: 0.0490 data: 0.0016 max mem: 19788 +Test: [ 2900/21770] eta: 0:14:57 time: 0.0472 data: 0.0014 max mem: 19788 +Test: [ 3000/21770] eta: 0:14:53 time: 0.0459 data: 0.0015 max mem: 19788 +Test: [ 3100/21770] eta: 0:14:47 time: 0.0437 data: 0.0016 max mem: 19788 +Test: [ 3200/21770] eta: 0:14:42 time: 0.0447 data: 0.0016 max mem: 19788 +Test: [ 3300/21770] eta: 0:14:37 time: 0.0452 data: 0.0017 max mem: 19788 +Test: [ 3400/21770] eta: 0:14:31 time: 0.0442 data: 0.0015 max mem: 19788 +Test: [ 3500/21770] eta: 0:14:27 time: 0.0482 data: 0.0018 max mem: 19788 +Test: [ 3600/21770] eta: 0:14:21 time: 0.0486 data: 0.0014 max mem: 19788 +Test: [ 3700/21770] eta: 0:14:18 time: 0.0471 data: 0.0017 max mem: 19788 +Test: [ 3800/21770] eta: 0:14:14 time: 0.0476 data: 0.0014 max mem: 19788 +Test: [ 3900/21770] eta: 0:14:08 time: 0.0438 data: 0.0016 max mem: 19788 +Test: [ 4000/21770] eta: 0:14:02 time: 0.0473 data: 0.0016 max mem: 19788 +Test: [ 4100/21770] eta: 0:13:58 time: 0.0436 data: 0.0014 max mem: 19788 +Test: [ 4200/21770] eta: 0:13:51 time: 0.0442 data: 0.0015 max mem: 19788 +Test: [ 4300/21770] eta: 0:13:45 time: 0.0425 data: 0.0014 max mem: 19788 +Test: [ 4400/21770] eta: 0:13:40 time: 0.0438 data: 0.0014 max mem: 19788 +Test: [ 4500/21770] eta: 0:13:35 time: 0.0481 data: 0.0013 max mem: 19788 +Test: [ 4600/21770] eta: 0:13:29 time: 0.0443 data: 0.0017 max mem: 19788 +Test: [ 4700/21770] eta: 0:13:25 time: 0.0467 data: 0.0014 max mem: 19788 +Test: [ 4800/21770] eta: 0:13:20 time: 0.0423 data: 0.0015 max mem: 19788 +Test: [ 4900/21770] eta: 0:13:15 time: 0.0460 data: 0.0015 max mem: 19788 +Test: [ 5000/21770] eta: 0:13:10 time: 0.0475 data: 0.0018 max mem: 19788 +Test: [ 5100/21770] eta: 0:13:04 time: 0.0436 data: 0.0016 max mem: 19788 +Test: [ 5200/21770] eta: 0:13:00 time: 0.0520 data: 0.0016 max mem: 19788 +Test: [ 5300/21770] eta: 0:12:55 time: 0.0446 data: 0.0013 max mem: 19788 +Test: [ 5400/21770] eta: 0:12:52 time: 0.0526 data: 0.0018 max mem: 19788 +Test: [ 5500/21770] eta: 0:12:47 time: 0.0440 data: 0.0013 max mem: 19788 +Test: [ 5600/21770] eta: 0:12:42 time: 0.0438 data: 0.0014 max mem: 19788 +Test: [ 5700/21770] eta: 0:12:36 time: 0.0478 data: 0.0015 max mem: 19788 +Test: [ 5800/21770] eta: 0:12:31 time: 0.0421 data: 0.0016 max mem: 19788 +Test: [ 5900/21770] eta: 0:12:25 time: 0.0444 data: 0.0015 max mem: 19788 +Test: [ 6000/21770] eta: 0:12:21 time: 0.0502 data: 0.0017 max mem: 19788 +Test: [ 6100/21770] eta: 0:12:17 time: 0.0448 data: 0.0017 max mem: 19788 +Test: [ 6200/21770] eta: 0:12:12 time: 0.0482 data: 0.0017 max mem: 19788 +Test: [ 6300/21770] eta: 0:12:07 time: 0.0495 data: 0.0019 max mem: 19788 +Test: [ 6400/21770] eta: 0:12:02 time: 0.0510 data: 0.0017 max mem: 19788 +Test: [ 6500/21770] eta: 0:11:58 time: 0.0469 data: 0.0016 max mem: 19788 +Test: [ 6600/21770] eta: 0:11:54 time: 0.0453 data: 0.0013 max mem: 19788 +Test: [ 6700/21770] eta: 0:11:50 time: 0.0550 data: 0.0015 max mem: 19788 +Test: [ 6800/21770] eta: 0:11:46 time: 0.0448 data: 0.0014 max mem: 19788 +Test: [ 6900/21770] eta: 0:11:42 time: 0.0479 data: 0.0016 max mem: 19788 +Test: [ 7000/21770] eta: 0:11:37 time: 0.0433 data: 0.0015 max mem: 19788 +Test: [ 7100/21770] eta: 0:11:32 time: 0.0496 data: 0.0017 max mem: 19788 +Test: [ 7200/21770] eta: 0:11:28 time: 0.0527 data: 0.0018 max mem: 19788 +Test: [ 7300/21770] eta: 0:11:23 time: 0.0435 data: 0.0014 max mem: 19788 +Test: [ 7400/21770] eta: 0:11:18 time: 0.0534 data: 0.0018 max mem: 19788 +Test: [ 7500/21770] eta: 0:11:14 time: 0.0473 data: 0.0017 max mem: 19788 +Test: [ 7600/21770] eta: 0:11:09 time: 0.0438 data: 0.0015 max mem: 19788 +Test: [ 7700/21770] eta: 0:11:05 time: 0.0472 data: 0.0016 max mem: 19788 +Test: [ 7800/21770] eta: 0:11:00 time: 0.0526 data: 0.0017 max mem: 19788 +Test: [ 7900/21770] eta: 0:10:57 time: 0.0524 data: 0.0018 max mem: 19788 +Test: [ 8000/21770] eta: 0:10:52 time: 0.0440 data: 0.0016 max mem: 19788 +Test: [ 8100/21770] eta: 0:10:47 time: 0.0439 data: 0.0016 max mem: 19788 +Test: [ 8200/21770] eta: 0:10:43 time: 0.0538 data: 0.0017 max mem: 19788 +Test: [ 8300/21770] eta: 0:10:38 time: 0.0433 data: 0.0015 max mem: 19788 +Test: [ 8400/21770] eta: 0:10:33 time: 0.0431 data: 0.0014 max mem: 19788 +Test: [ 8500/21770] eta: 0:10:28 time: 0.0427 data: 0.0014 max mem: 19788 +Test: [ 8600/21770] eta: 0:10:23 time: 0.0441 data: 0.0016 max mem: 19788 +Test: [ 8700/21770] eta: 0:10:18 time: 0.0437 data: 0.0014 max mem: 19788 +Test: [ 8800/21770] eta: 0:10:13 time: 0.0516 data: 0.0016 max mem: 19788 +Test: [ 8900/21770] eta: 0:10:08 time: 0.0448 data: 0.0014 max mem: 19788 +Test: [ 9000/21770] eta: 0:10:03 time: 0.0515 data: 0.0016 max mem: 19788 +Test: [ 9100/21770] eta: 0:09:59 time: 0.0520 data: 0.0017 max mem: 19788 +Test: [ 9200/21770] eta: 0:09:54 time: 0.0439 data: 0.0014 max mem: 19788 +Test: [ 9300/21770] eta: 0:09:49 time: 0.0438 data: 0.0014 max mem: 19788 +Test: [ 9400/21770] eta: 0:09:45 time: 0.0488 data: 0.0017 max mem: 19788 +Test: [ 9500/21770] eta: 0:09:40 time: 0.0468 data: 0.0016 max mem: 19788 +Test: [ 9600/21770] eta: 0:09:35 time: 0.0458 data: 0.0015 max mem: 19788 +Test: [ 9700/21770] eta: 0:09:31 time: 0.0537 data: 0.0017 max mem: 19788 +Test: [ 9800/21770] eta: 0:09:27 time: 0.0439 data: 0.0014 max mem: 19788 +Test: [ 9900/21770] eta: 0:09:22 time: 0.0533 data: 0.0019 max mem: 19788 +Test: [10000/21770] eta: 0:09:17 time: 0.0504 data: 0.0015 max mem: 19788 +Test: [10100/21770] eta: 0:09:13 time: 0.0530 data: 0.0018 max mem: 19788 +Test: [10200/21770] eta: 0:09:08 time: 0.0462 data: 0.0015 max mem: 19788 +Test: [10300/21770] eta: 0:09:03 time: 0.0457 data: 0.0015 max mem: 19788 +Test: [10400/21770] eta: 0:08:58 time: 0.0438 data: 0.0014 max mem: 19788 +Test: [10500/21770] eta: 0:08:54 time: 0.0509 data: 0.0018 max mem: 19788 +Test: [10600/21770] eta: 0:08:50 time: 0.0513 data: 0.0017 max mem: 19788 +Test: [10700/21770] eta: 0:08:45 time: 0.0472 data: 0.0015 max mem: 19788 +Test: [10800/21770] eta: 0:08:40 time: 0.0445 data: 0.0014 max mem: 19788 +Test: [10900/21770] eta: 0:08:35 time: 0.0504 data: 0.0017 max mem: 19788 +Test: [11000/21770] eta: 0:08:31 time: 0.0517 data: 0.0018 max mem: 19788 +Test: [11100/21770] eta: 0:08:26 time: 0.0432 data: 0.0016 max mem: 19788 +Test: [11200/21770] eta: 0:08:21 time: 0.0465 data: 0.0016 max mem: 19788 +Test: [11300/21770] eta: 0:08:16 time: 0.0511 data: 0.0016 max mem: 19788 +Test: [11400/21770] eta: 0:08:11 time: 0.0470 data: 0.0018 max mem: 19788 +Test: [11500/21770] eta: 0:08:06 time: 0.0456 data: 0.0016 max mem: 19788 +Test: [11600/21770] eta: 0:08:01 time: 0.0440 data: 0.0015 max mem: 19788 +Test: [11700/21770] eta: 0:07:57 time: 0.0522 data: 0.0019 max mem: 19788 +Test: [11800/21770] eta: 0:07:52 time: 0.0441 data: 0.0015 max mem: 19788 +Test: [11900/21770] eta: 0:07:47 time: 0.0522 data: 0.0017 max mem: 19788 +Test: [12000/21770] eta: 0:07:43 time: 0.0484 data: 0.0017 max mem: 19788 +Test: [12100/21770] eta: 0:07:38 time: 0.0442 data: 0.0016 max mem: 19788 +Test: [12200/21770] eta: 0:07:33 time: 0.0455 data: 0.0017 max mem: 19788 +Test: [12300/21770] eta: 0:07:28 time: 0.0484 data: 0.0017 max mem: 19788 +Test: [12400/21770] eta: 0:07:23 time: 0.0439 data: 0.0014 max mem: 19788 +Test: [12500/21770] eta: 0:07:19 time: 0.0552 data: 0.0018 max mem: 19788 +Test: [12600/21770] eta: 0:07:14 time: 0.0466 data: 0.0016 max mem: 19788 +Test: [12700/21770] eta: 0:07:09 time: 0.0440 data: 0.0016 max mem: 19788 +Test: [12800/21770] eta: 0:07:05 time: 0.0451 data: 0.0016 max mem: 19788 +Test: [12900/21770] eta: 0:07:00 time: 0.0442 data: 0.0014 max mem: 19788 +Test: [13000/21770] eta: 0:06:55 time: 0.0538 data: 0.0018 max mem: 19788 +Test: [13100/21770] eta: 0:06:51 time: 0.0473 data: 0.0015 max mem: 19788 +Test: [13200/21770] eta: 0:06:46 time: 0.0432 data: 0.0014 max mem: 19788 +Test: [13300/21770] eta: 0:06:41 time: 0.0442 data: 0.0016 max mem: 19788 +Test: [13400/21770] eta: 0:06:36 time: 0.0446 data: 0.0015 max mem: 19788 +Test: [13500/21770] eta: 0:06:31 time: 0.0504 data: 0.0017 max mem: 19788 +Test: [13600/21770] eta: 0:06:26 time: 0.0458 data: 0.0015 max mem: 19788 +Test: [13700/21770] eta: 0:06:22 time: 0.0512 data: 0.0018 max mem: 19788 +Test: [13800/21770] eta: 0:06:17 time: 0.0474 data: 0.0018 max mem: 19788 +Test: [13900/21770] eta: 0:06:12 time: 0.0424 data: 0.0016 max mem: 19788 +Test: [14000/21770] eta: 0:06:07 time: 0.0450 data: 0.0015 max mem: 19788 +Test: [14100/21770] eta: 0:06:03 time: 0.0553 data: 0.0017 max mem: 19788 +Test: [14200/21770] eta: 0:05:58 time: 0.0463 data: 0.0016 max mem: 19788 +Test: [14300/21770] eta: 0:05:54 time: 0.0488 data: 0.0018 max mem: 19788 +Test: [14400/21770] eta: 0:05:49 time: 0.0513 data: 0.0017 max mem: 19788 +Test: [14500/21770] eta: 0:05:44 time: 0.0484 data: 0.0016 max mem: 19788 +Test: [14600/21770] eta: 0:05:39 time: 0.0536 data: 0.0019 max mem: 19788 +Test: [14700/21770] eta: 0:05:35 time: 0.0432 data: 0.0016 max mem: 19788 +Test: [14800/21770] eta: 0:05:30 time: 0.0492 data: 0.0016 max mem: 19788 +Test: [14900/21770] eta: 0:05:25 time: 0.0441 data: 0.0015 max mem: 19788 +Test: [15000/21770] eta: 0:05:20 time: 0.0451 data: 0.0015 max mem: 19788 +Test: [15100/21770] eta: 0:05:16 time: 0.0468 data: 0.0015 max mem: 19788 +Test: [15200/21770] eta: 0:05:11 time: 0.0520 data: 0.0017 max mem: 19788 +Test: [15300/21770] eta: 0:05:06 time: 0.0449 data: 0.0014 max mem: 19788 +Test: [15400/21770] eta: 0:05:01 time: 0.0460 data: 0.0013 max mem: 19788 +Test: [15500/21770] eta: 0:04:57 time: 0.0531 data: 0.0018 max mem: 19788 +Test: [15600/21770] eta: 0:04:52 time: 0.0445 data: 0.0014 max mem: 19788 +Test: [15700/21770] eta: 0:04:47 time: 0.0471 data: 0.0017 max mem: 19788 +Test: [15800/21770] eta: 0:04:42 time: 0.0433 data: 0.0014 max mem: 19788 +Test: [15900/21770] eta: 0:04:37 time: 0.0444 data: 0.0013 max mem: 19788 +Test: [16000/21770] eta: 0:04:33 time: 0.0506 data: 0.0016 max mem: 19788 +Test: [16100/21770] eta: 0:04:28 time: 0.0453 data: 0.0015 max mem: 19788 +Test: [16200/21770] eta: 0:04:23 time: 0.0441 data: 0.0014 max mem: 19788 +Test: [16300/21770] eta: 0:04:18 time: 0.0479 data: 0.0015 max mem: 19788 +Test: [16400/21770] eta: 0:04:14 time: 0.0541 data: 0.0018 max mem: 19788 +Test: [16500/21770] eta: 0:04:09 time: 0.0434 data: 0.0014 max mem: 19788 +Test: [16600/21770] eta: 0:04:04 time: 0.0509 data: 0.0017 max mem: 19788 +Test: [16700/21770] eta: 0:04:00 time: 0.0440 data: 0.0016 max mem: 19788 +Test: [16800/21770] eta: 0:03:55 time: 0.0439 data: 0.0013 max mem: 19788 +Test: [16900/21770] eta: 0:03:50 time: 0.0493 data: 0.0017 max mem: 19788 +Test: [17000/21770] eta: 0:03:45 time: 0.0472 data: 0.0015 max mem: 19788 +Test: [17100/21770] eta: 0:03:41 time: 0.0515 data: 0.0017 max mem: 19788 +Test: [17200/21770] eta: 0:03:36 time: 0.0437 data: 0.0018 max mem: 19788 +Test: [17300/21770] eta: 0:03:31 time: 0.0445 data: 0.0016 max mem: 19788 +Test: [17400/21770] eta: 0:03:26 time: 0.0487 data: 0.0015 max mem: 19788 +Test: [17500/21770] eta: 0:03:22 time: 0.0482 data: 0.0016 max mem: 19788 +Test: [17600/21770] eta: 0:03:17 time: 0.0434 data: 0.0013 max mem: 19788 +Test: [17700/21770] eta: 0:03:12 time: 0.0468 data: 0.0015 max mem: 19788 +Test: [17800/21770] eta: 0:03:07 time: 0.0453 data: 0.0014 max mem: 19788 +Test: [17900/21770] eta: 0:03:03 time: 0.0437 data: 0.0015 max mem: 19788 +Test: [18000/21770] eta: 0:02:58 time: 0.0443 data: 0.0014 max mem: 19788 +Test: [18100/21770] eta: 0:02:53 time: 0.0426 data: 0.0014 max mem: 19788 +Test: [18200/21770] eta: 0:02:48 time: 0.0514 data: 0.0015 max mem: 19788 +Test: [18300/21770] eta: 0:02:44 time: 0.0438 data: 0.0013 max mem: 19788 +Test: [18400/21770] eta: 0:02:39 time: 0.0445 data: 0.0017 max mem: 19788 +Test: [18500/21770] eta: 0:02:34 time: 0.0442 data: 0.0016 max mem: 19788 +Test: [18600/21770] eta: 0:02:29 time: 0.0442 data: 0.0013 max mem: 19788 +Test: [18700/21770] eta: 0:02:25 time: 0.0500 data: 0.0017 max mem: 19788 +Test: [18800/21770] eta: 0:02:20 time: 0.0435 data: 0.0014 max mem: 19788 +Test: [18900/21770] eta: 0:02:15 time: 0.0453 data: 0.0016 max mem: 19788 +Test: [19000/21770] eta: 0:02:10 time: 0.0439 data: 0.0015 max mem: 19788 +Test: [19100/21770] eta: 0:02:06 time: 0.0539 data: 0.0017 max mem: 19788 +Test: [19200/21770] eta: 0:02:01 time: 0.0435 data: 0.0015 max mem: 19788 +Test: [19300/21770] eta: 0:01:56 time: 0.0437 data: 0.0015 max mem: 19788 +Test: [19400/21770] eta: 0:01:51 time: 0.0488 data: 0.0015 max mem: 19788 +Test: [19500/21770] eta: 0:01:47 time: 0.0440 data: 0.0014 max mem: 19788 +Test: [19600/21770] eta: 0:01:42 time: 0.0463 data: 0.0015 max mem: 19788 +Test: [19700/21770] eta: 0:01:37 time: 0.0454 data: 0.0015 max mem: 19788 +Test: [19800/21770] eta: 0:01:32 time: 0.0471 data: 0.0016 max mem: 19788 +Test: [19900/21770] eta: 0:01:28 time: 0.0507 data: 0.0015 max mem: 19788 +Test: [20000/21770] eta: 0:01:23 time: 0.0431 data: 0.0015 max mem: 19788 +Test: [20100/21770] eta: 0:01:18 time: 0.0433 data: 0.0014 max mem: 19788 +Test: [20200/21770] eta: 0:01:14 time: 0.0438 data: 0.0015 max mem: 19788 +Test: [20300/21770] eta: 0:01:09 time: 0.0440 data: 0.0013 max mem: 19788 +Test: [20400/21770] eta: 0:01:04 time: 0.0431 data: 0.0014 max mem: 19788 +Test: [20500/21770] eta: 0:00:59 time: 0.0464 data: 0.0014 max mem: 19788 +Test: [20600/21770] eta: 0:00:55 time: 0.0443 data: 0.0014 max mem: 19788 +Test: [20700/21770] eta: 0:00:50 time: 0.0495 data: 0.0016 max mem: 19788 +Test: [20800/21770] eta: 0:00:45 time: 0.0444 data: 0.0015 max mem: 19788 +Test: [20900/21770] eta: 0:00:41 time: 0.0431 data: 0.0014 max mem: 19788 +Test: [21000/21770] eta: 0:00:36 time: 0.0524 data: 0.0019 max mem: 19788 +Test: [21100/21770] eta: 0:00:31 time: 0.0548 data: 0.0017 max mem: 19788 +Test: [21200/21770] eta: 0:00:26 time: 0.0442 data: 0.0016 max mem: 19788 +Test: [21300/21770] eta: 0:00:22 time: 0.0522 data: 0.0018 max mem: 19788 +Test: [21400/21770] eta: 0:00:17 time: 0.0439 data: 0.0016 max mem: 19788 +Test: [21500/21770] eta: 0:00:12 time: 0.0440 data: 0.0016 max mem: 19788 +Test: [21600/21770] eta: 0:00:08 time: 0.0448 data: 0.0014 max mem: 19788 +Test: [21700/21770] eta: 0:00:03 time: 0.0514 data: 0.0016 max mem: 19788 +Test: Total time: 0:17:07 +Final results: +Mean IoU is 64.08 + + precision@0.5 = 71.08 + precision@0.6 = 65.47 + precision@0.7 = 58.83 + precision@0.8 = 47.90 + precision@0.9 = 23.99 + overall IoU = 64.51 + mean IoU = 64.08 + +Mean accuracy for one-to-zero sample is 81.35 + +Average object IoU 0.6408175922905409 +Overall IoU 64.50819396972656 +Epoch: [23] [ 0/2138] eta: 8:33:17 lr: 2.3147776861632803e-05 loss: 0.0313 (0.0313) time: 14.4049 data: 1.5683 max mem: 19788 +Epoch: [23] [ 10/2138] eta: 2:20:36 lr: 2.314204477033964e-05 loss: 0.0243 (0.0258) time: 3.9644 data: 0.1440 max mem: 19788 +Epoch: [23] [ 20/2138] eta: 2:03:32 lr: 2.3136312521287552e-05 loss: 0.0240 (0.0259) time: 2.9546 data: 0.0015 max mem: 19788 +Epoch: [23] [ 30/2138] eta: 1:58:01 lr: 2.3130580114428785e-05 loss: 0.0259 (0.0272) time: 3.0268 data: 0.0020 max mem: 19788 +Epoch: [23] [ 40/2138] eta: 1:54:12 lr: 2.3124847549715517e-05 loss: 0.0259 (0.0272) time: 3.0209 data: 0.0026 max mem: 19788 +Epoch: [23] [ 50/2138] eta: 1:51:17 lr: 2.3119114827099936e-05 loss: 0.0253 (0.0272) time: 2.9472 data: 0.0026 max mem: 19788 +Epoch: [23] [ 60/2138] eta: 1:49:05 lr: 2.311338194653417e-05 loss: 0.0264 (0.0274) time: 2.9108 data: 0.0025 max mem: 19788 +Epoch: [23] [ 70/2138] eta: 1:47:27 lr: 2.3107648907970354e-05 loss: 0.0264 (0.0280) time: 2.9132 data: 0.0026 max mem: 19788 +Epoch: [23] [ 80/2138] eta: 1:46:02 lr: 2.3101915711360557e-05 loss: 0.0249 (0.0279) time: 2.9136 data: 0.0026 max mem: 19788 +Epoch: [23] [ 90/2138] eta: 1:44:58 lr: 2.309618235665685e-05 loss: 0.0234 (0.0275) time: 2.9268 data: 0.0026 max mem: 19788 +Epoch: [23] [ 100/2138] eta: 1:44:11 lr: 2.309044884381126e-05 loss: 0.0245 (0.0336) time: 2.9710 data: 0.0026 max mem: 19788 +Epoch: [23] [ 110/2138] eta: 1:43:22 lr: 2.30847151727758e-05 loss: 0.0268 (0.0331) time: 2.9800 data: 0.0025 max mem: 19788 +Epoch: [23] [ 120/2138] eta: 1:42:27 lr: 2.3078981343502436e-05 loss: 0.0259 (0.0326) time: 2.9397 data: 0.0028 max mem: 19788 +Epoch: [23] [ 130/2138] eta: 1:41:34 lr: 2.3073247355943133e-05 loss: 0.0266 (0.0322) time: 2.9061 data: 0.0029 max mem: 19788 +Epoch: [23] [ 140/2138] eta: 1:40:46 lr: 2.3067513210049793e-05 loss: 0.0266 (0.0318) time: 2.9057 data: 0.0026 max mem: 19788 +Epoch: [23] [ 150/2138] eta: 1:40:12 lr: 2.3061778905774326e-05 loss: 0.0258 (0.0314) time: 2.9546 data: 0.0025 max mem: 19788 +Epoch: [23] [ 160/2138] eta: 1:39:27 lr: 2.305604444306859e-05 loss: 0.0254 (0.0311) time: 2.9512 data: 0.0025 max mem: 19788 +Epoch: [23] [ 170/2138] eta: 1:38:46 lr: 2.3050309821884417e-05 loss: 0.0256 (0.0309) time: 2.9129 data: 0.0025 max mem: 19788 +Epoch: [23] [ 180/2138] eta: 1:38:18 lr: 2.3044575042173626e-05 loss: 0.0256 (0.0307) time: 2.9744 data: 0.0027 max mem: 19788 +Epoch: [23] [ 190/2138] eta: 1:37:37 lr: 2.3038840103887994e-05 loss: 0.0237 (0.0303) time: 2.9676 data: 0.0027 max mem: 19788 +Epoch: [23] [ 200/2138] eta: 1:36:57 lr: 2.303310500697928e-05 loss: 0.0240 (0.0300) time: 2.9076 data: 0.0028 max mem: 19788 +Epoch: [23] [ 210/2138] eta: 1:36:20 lr: 2.30273697513992e-05 loss: 0.0252 (0.0300) time: 2.9142 data: 0.0027 max mem: 19788 +Epoch: [23] [ 220/2138] eta: 1:35:41 lr: 2.3021634337099465e-05 loss: 0.0239 (0.0297) time: 2.9091 data: 0.0027 max mem: 19788 +Epoch: [23] [ 230/2138] eta: 1:35:04 lr: 2.301589876403173e-05 loss: 0.0227 (0.0296) time: 2.9016 data: 0.0026 max mem: 19788 +Epoch: [23] [ 240/2138] eta: 1:34:29 lr: 2.3010163032147646e-05 loss: 0.0252 (0.0294) time: 2.9125 data: 0.0026 max mem: 19788 +Epoch: [23] [ 250/2138] eta: 1:33:55 lr: 2.300442714139882e-05 loss: 0.0257 (0.0293) time: 2.9282 data: 0.0028 max mem: 19788 +Epoch: [23] [ 260/2138] eta: 1:33:23 lr: 2.2998691091736846e-05 loss: 0.0256 (0.0291) time: 2.9500 data: 0.0027 max mem: 19788 +Epoch: [23] [ 270/2138] eta: 1:32:49 lr: 2.299295488311327e-05 loss: 0.0242 (0.0290) time: 2.9365 data: 0.0028 max mem: 19788 +Epoch: [23] [ 280/2138] eta: 1:32:13 lr: 2.2987218515479632e-05 loss: 0.0245 (0.0289) time: 2.9063 data: 0.0028 max mem: 19788 +Epoch: [23] [ 290/2138] eta: 1:31:40 lr: 2.298148198878742e-05 loss: 0.0245 (0.0288) time: 2.9138 data: 0.0028 max mem: 19788 +Epoch: [23] [ 300/2138] eta: 1:31:06 lr: 2.2975745302988114e-05 loss: 0.0246 (0.0287) time: 2.9128 data: 0.0025 max mem: 19788 +Epoch: [23] [ 310/2138] eta: 1:30:32 lr: 2.2970008458033155e-05 loss: 0.0241 (0.0285) time: 2.9000 data: 0.0023 max mem: 19788 +Epoch: [23] [ 320/2138] eta: 1:29:58 lr: 2.296427145387397e-05 loss: 0.0211 (0.0283) time: 2.8992 data: 0.0024 max mem: 19788 +Epoch: [23] [ 330/2138] eta: 1:29:30 lr: 2.2958534290461923e-05 loss: 0.0235 (0.0283) time: 2.9482 data: 0.0028 max mem: 19788 +Epoch: [23] [ 340/2138] eta: 1:28:58 lr: 2.2952796967748394e-05 loss: 0.0261 (0.0282) time: 2.9620 data: 0.0026 max mem: 19788 +Epoch: [23] [ 350/2138] eta: 1:28:25 lr: 2.2947059485684705e-05 loss: 0.0211 (0.0281) time: 2.9149 data: 0.0022 max mem: 19788 +Epoch: [23] [ 360/2138] eta: 1:27:52 lr: 2.294132184422216e-05 loss: 0.0256 (0.0281) time: 2.9083 data: 0.0021 max mem: 19788 +Epoch: [23] [ 370/2138] eta: 1:27:20 lr: 2.293558404331203e-05 loss: 0.0264 (0.0280) time: 2.9098 data: 0.0022 max mem: 19788 +Epoch: [23] [ 380/2138] eta: 1:26:48 lr: 2.2929846082905567e-05 loss: 0.0232 (0.0279) time: 2.9072 data: 0.0022 max mem: 19788 +Epoch: [23] [ 390/2138] eta: 1:26:15 lr: 2.2924107962953982e-05 loss: 0.0227 (0.0278) time: 2.9045 data: 0.0024 max mem: 19788 +Epoch: [23] [ 400/2138] eta: 1:25:43 lr: 2.2918369683408465e-05 loss: 0.0265 (0.0278) time: 2.9037 data: 0.0026 max mem: 19788 +Epoch: [23] [ 410/2138] eta: 1:25:13 lr: 2.2912631244220174e-05 loss: 0.0240 (0.0277) time: 2.9244 data: 0.0025 max mem: 19788 +Epoch: [23] [ 420/2138] eta: 1:24:41 lr: 2.2906892645340244e-05 loss: 0.0215 (0.0276) time: 2.9191 data: 0.0022 max mem: 19788 +Epoch: [23] [ 430/2138] eta: 1:24:09 lr: 2.2901153886719773e-05 loss: 0.0237 (0.0275) time: 2.8994 data: 0.0021 max mem: 19788 +Epoch: [23] [ 440/2138] eta: 1:23:39 lr: 2.2895414968309843e-05 loss: 0.0271 (0.0276) time: 2.9210 data: 0.0021 max mem: 19788 +Epoch: [23] [ 450/2138] eta: 1:23:08 lr: 2.288967589006149e-05 loss: 0.0255 (0.0275) time: 2.9337 data: 0.0024 max mem: 19788 +Epoch: [23] [ 460/2138] eta: 1:22:38 lr: 2.2883936651925743e-05 loss: 0.0229 (0.0274) time: 2.9322 data: 0.0028 max mem: 19788 +Epoch: [23] [ 470/2138] eta: 1:22:07 lr: 2.2878197253853578e-05 loss: 0.0246 (0.0274) time: 2.9189 data: 0.0030 max mem: 19788 +Epoch: [23] [ 480/2138] eta: 1:21:40 lr: 2.2872457695795957e-05 loss: 0.0266 (0.0274) time: 2.9749 data: 0.0026 max mem: 19788 +Epoch: [23] [ 490/2138] eta: 1:21:09 lr: 2.2866717977703818e-05 loss: 0.0241 (0.0273) time: 2.9786 data: 0.0021 max mem: 19788 +Epoch: [23] [ 500/2138] eta: 1:20:39 lr: 2.2860978099528055e-05 loss: 0.0230 (0.0273) time: 2.9156 data: 0.0022 max mem: 19788 +Epoch: [23] [ 510/2138] eta: 1:20:07 lr: 2.285523806121955e-05 loss: 0.0230 (0.0272) time: 2.9141 data: 0.0028 max mem: 19788 +Epoch: [23] [ 520/2138] eta: 1:19:36 lr: 2.2849497862729132e-05 loss: 0.0215 (0.0272) time: 2.9042 data: 0.0029 max mem: 19788 +Epoch: [23] [ 530/2138] eta: 1:19:05 lr: 2.284375750400764e-05 loss: 0.0228 (0.0271) time: 2.8997 data: 0.0024 max mem: 19788 +Epoch: [23] [ 540/2138] eta: 1:18:34 lr: 2.283801698500584e-05 loss: 0.0228 (0.0271) time: 2.9036 data: 0.0025 max mem: 19788 +Epoch: [23] [ 550/2138] eta: 1:18:04 lr: 2.28322763056745e-05 loss: 0.0233 (0.0270) time: 2.9187 data: 0.0025 max mem: 19788 +Epoch: [23] [ 560/2138] eta: 1:17:35 lr: 2.2826535465964345e-05 loss: 0.0244 (0.0270) time: 2.9419 data: 0.0024 max mem: 19788 +Epoch: [23] [ 570/2138] eta: 1:17:04 lr: 2.2820794465826085e-05 loss: 0.0261 (0.0270) time: 2.9329 data: 0.0024 max mem: 19788 +Epoch: [23] [ 580/2138] eta: 1:16:34 lr: 2.2815053305210378e-05 loss: 0.0229 (0.0270) time: 2.9124 data: 0.0024 max mem: 19788 +Epoch: [23] [ 590/2138] eta: 1:16:05 lr: 2.2809311984067874e-05 loss: 0.0232 (0.0270) time: 2.9345 data: 0.0025 max mem: 19788 +Epoch: [23] [ 600/2138] eta: 1:15:34 lr: 2.280357050234918e-05 loss: 0.0247 (0.0270) time: 2.9341 data: 0.0024 max mem: 19788 +Epoch: [23] [ 610/2138] eta: 1:15:04 lr: 2.2797828860004895e-05 loss: 0.0242 (0.0269) time: 2.9119 data: 0.0026 max mem: 19788 +Epoch: [23] [ 620/2138] eta: 1:14:33 lr: 2.2792087056985554e-05 loss: 0.0245 (0.0270) time: 2.9105 data: 0.0030 max mem: 19788 +Epoch: [23] [ 630/2138] eta: 1:14:05 lr: 2.27863450932417e-05 loss: 0.0288 (0.0270) time: 2.9633 data: 0.0029 max mem: 19788 +Epoch: [23] [ 640/2138] eta: 1:13:35 lr: 2.2780602968723818e-05 loss: 0.0246 (0.0269) time: 2.9683 data: 0.0027 max mem: 19788 +Epoch: [23] [ 650/2138] eta: 1:13:05 lr: 2.277486068338239e-05 loss: 0.0240 (0.0269) time: 2.9173 data: 0.0026 max mem: 19788 +Epoch: [23] [ 660/2138] eta: 1:12:35 lr: 2.2769118237167837e-05 loss: 0.0236 (0.0269) time: 2.9088 data: 0.0026 max mem: 19788 +Epoch: [23] [ 670/2138] eta: 1:12:04 lr: 2.2763375630030585e-05 loss: 0.0237 (0.0269) time: 2.9078 data: 0.0025 max mem: 19788 +Epoch: [23] [ 680/2138] eta: 1:11:35 lr: 2.2757632861921006e-05 loss: 0.0237 (0.0269) time: 2.9366 data: 0.0024 max mem: 19788 +Epoch: [23] [ 690/2138] eta: 1:11:05 lr: 2.275188993278945e-05 loss: 0.0241 (0.0269) time: 2.9371 data: 0.0025 max mem: 19788 +Epoch: [23] [ 700/2138] eta: 1:10:37 lr: 2.2746146842586246e-05 loss: 0.0231 (0.0268) time: 2.9663 data: 0.0026 max mem: 19788 +Epoch: [23] [ 710/2138] eta: 1:10:08 lr: 2.2740403591261684e-05 loss: 0.0225 (0.0268) time: 2.9892 data: 0.0024 max mem: 19788 +Epoch: [23] [ 720/2138] eta: 1:09:38 lr: 2.273466017876602e-05 loss: 0.0214 (0.0267) time: 2.9307 data: 0.0022 max mem: 19788 +Epoch: [23] [ 730/2138] eta: 1:09:08 lr: 2.27289166050495e-05 loss: 0.0218 (0.0267) time: 2.9245 data: 0.0023 max mem: 19788 +Epoch: [23] [ 740/2138] eta: 1:08:38 lr: 2.2723172870062323e-05 loss: 0.0267 (0.0267) time: 2.9267 data: 0.0022 max mem: 19788 +Epoch: [23] [ 750/2138] eta: 1:08:08 lr: 2.2717428973754667e-05 loss: 0.0239 (0.0267) time: 2.9121 data: 0.0023 max mem: 19788 +Epoch: [23] [ 760/2138] eta: 1:07:38 lr: 2.271168491607667e-05 loss: 0.0239 (0.0267) time: 2.9300 data: 0.0026 max mem: 19788 +Epoch: [23] [ 770/2138] eta: 1:07:08 lr: 2.270594069697846e-05 loss: 0.0212 (0.0266) time: 2.9246 data: 0.0025 max mem: 19788 +Epoch: [23] [ 780/2138] eta: 1:06:40 lr: 2.2700196316410122e-05 loss: 0.0212 (0.0266) time: 2.9560 data: 0.0024 max mem: 19788 +Epoch: [23] [ 790/2138] eta: 1:06:10 lr: 2.2694451774321705e-05 loss: 0.0230 (0.0266) time: 2.9665 data: 0.0024 max mem: 19788 +Epoch: [23] [ 800/2138] eta: 1:05:40 lr: 2.2688707070663247e-05 loss: 0.0231 (0.0267) time: 2.9230 data: 0.0025 max mem: 19788 +Epoch: [23] [ 810/2138] eta: 1:05:10 lr: 2.2682962205384733e-05 loss: 0.0252 (0.0266) time: 2.9144 data: 0.0026 max mem: 19788 +Epoch: [23] [ 820/2138] eta: 1:04:40 lr: 2.2677217178436154e-05 loss: 0.0237 (0.0266) time: 2.9094 data: 0.0028 max mem: 19788 +Epoch: [23] [ 830/2138] eta: 1:04:10 lr: 2.267147198976743e-05 loss: 0.0226 (0.0266) time: 2.9053 data: 0.0029 max mem: 19788 +Epoch: [23] [ 840/2138] eta: 1:03:40 lr: 2.266572663932848e-05 loss: 0.0223 (0.0265) time: 2.9127 data: 0.0024 max mem: 19788 +Epoch: [23] [ 850/2138] eta: 1:03:10 lr: 2.265998112706918e-05 loss: 0.0251 (0.0266) time: 2.9191 data: 0.0021 max mem: 19788 +Epoch: [23] [ 860/2138] eta: 1:02:43 lr: 2.265423545293939e-05 loss: 0.0235 (0.0266) time: 2.9918 data: 0.0022 max mem: 19788 +Epoch: [23] [ 870/2138] eta: 1:02:13 lr: 2.2648489616888917e-05 loss: 0.0220 (0.0266) time: 2.9865 data: 0.0023 max mem: 19788 +Epoch: [23] [ 880/2138] eta: 1:01:43 lr: 2.2642743618867567e-05 loss: 0.0257 (0.0266) time: 2.9145 data: 0.0024 max mem: 19788 +Epoch: [23] [ 890/2138] eta: 1:01:13 lr: 2.2636997458825088e-05 loss: 0.0235 (0.0266) time: 2.9217 data: 0.0023 max mem: 19788 +Epoch: [23] [ 900/2138] eta: 1:00:45 lr: 2.2631251136711227e-05 loss: 0.0235 (0.0266) time: 2.9545 data: 0.0022 max mem: 19788 +Epoch: [23] [ 910/2138] eta: 1:00:15 lr: 2.262550465247567e-05 loss: 0.0233 (0.0266) time: 2.9614 data: 0.0023 max mem: 19788 +Epoch: [23] [ 920/2138] eta: 0:59:45 lr: 2.2619758006068098e-05 loss: 0.0229 (0.0265) time: 2.9197 data: 0.0024 max mem: 19788 +Epoch: [23] [ 930/2138] eta: 0:59:16 lr: 2.261401119743815e-05 loss: 0.0250 (0.0265) time: 2.9305 data: 0.0024 max mem: 19788 +Epoch: [23] [ 940/2138] eta: 0:58:48 lr: 2.2608264226535445e-05 loss: 0.0266 (0.0265) time: 3.0273 data: 0.0023 max mem: 19788 +Epoch: [23] [ 950/2138] eta: 0:58:20 lr: 2.260251709330956e-05 loss: 0.0228 (0.0265) time: 3.0625 data: 0.0022 max mem: 19788 +Epoch: [23] [ 960/2138] eta: 0:57:51 lr: 2.2596769797710048e-05 loss: 0.0265 (0.0266) time: 2.9941 data: 0.0022 max mem: 19788 +Epoch: [23] [ 970/2138] eta: 0:57:21 lr: 2.259102233968643e-05 loss: 0.0299 (0.0265) time: 2.9662 data: 0.0023 max mem: 19788 +Epoch: [23] [ 980/2138] eta: 0:56:52 lr: 2.2585274719188206e-05 loss: 0.0216 (0.0265) time: 2.9671 data: 0.0026 max mem: 19788 +Epoch: [23] [ 990/2138] eta: 0:56:23 lr: 2.2579526936164832e-05 loss: 0.0215 (0.0265) time: 2.9917 data: 0.0027 max mem: 19788 +Epoch: [23] [1000/2138] eta: 0:55:54 lr: 2.2573778990565747e-05 loss: 0.0215 (0.0264) time: 2.9856 data: 0.0023 max mem: 19788 +Epoch: [23] [1010/2138] eta: 0:55:26 lr: 2.2568030882340347e-05 loss: 0.0232 (0.0265) time: 3.0308 data: 0.0023 max mem: 19788 +Epoch: [23] [1020/2138] eta: 0:54:57 lr: 2.256228261143801e-05 loss: 0.0213 (0.0264) time: 3.0548 data: 0.0024 max mem: 19788 +Epoch: [23] [1030/2138] eta: 0:54:28 lr: 2.2556534177808072e-05 loss: 0.0213 (0.0264) time: 2.9912 data: 0.0023 max mem: 19788 +Epoch: [23] [1040/2138] eta: 0:54:00 lr: 2.2550785581399854e-05 loss: 0.0225 (0.0264) time: 3.0145 data: 0.0022 max mem: 19788 +Epoch: [23] [1050/2138] eta: 0:53:31 lr: 2.2545036822162634e-05 loss: 0.0235 (0.0264) time: 3.0203 data: 0.0025 max mem: 19788 +Epoch: [23] [1060/2138] eta: 0:53:02 lr: 2.2539287900045664e-05 loss: 0.0252 (0.0264) time: 3.0337 data: 0.0027 max mem: 19788 +Epoch: [23] [1070/2138] eta: 0:52:33 lr: 2.253353881499817e-05 loss: 0.0226 (0.0264) time: 3.0392 data: 0.0025 max mem: 19788 +Epoch: [23] [1080/2138] eta: 0:52:04 lr: 2.2527789566969335e-05 loss: 0.0225 (0.0264) time: 2.9810 data: 0.0023 max mem: 19788 +Epoch: [23] [1090/2138] eta: 0:51:35 lr: 2.2522040155908328e-05 loss: 0.0232 (0.0264) time: 2.9889 data: 0.0023 max mem: 19788 +Epoch: [23] [1100/2138] eta: 0:51:06 lr: 2.2516290581764277e-05 loss: 0.0268 (0.0264) time: 3.0047 data: 0.0024 max mem: 19788 +Epoch: [23] [1110/2138] eta: 0:50:37 lr: 2.2510540844486285e-05 loss: 0.0250 (0.0264) time: 3.0277 data: 0.0024 max mem: 19788 +Epoch: [23] [1120/2138] eta: 0:50:08 lr: 2.2504790944023418e-05 loss: 0.0236 (0.0264) time: 3.0215 data: 0.0025 max mem: 19788 +Epoch: [23] [1130/2138] eta: 0:49:39 lr: 2.2499040880324725e-05 loss: 0.0236 (0.0264) time: 2.9867 data: 0.0026 max mem: 19788 +Epoch: [23] [1140/2138] eta: 0:49:10 lr: 2.2493290653339206e-05 loss: 0.0238 (0.0264) time: 2.9980 data: 0.0025 max mem: 19788 +Epoch: [23] [1150/2138] eta: 0:48:40 lr: 2.248754026301585e-05 loss: 0.0235 (0.0264) time: 2.9869 data: 0.0022 max mem: 19788 +Epoch: [23] [1160/2138] eta: 0:48:11 lr: 2.2481789709303593e-05 loss: 0.0230 (0.0263) time: 2.9595 data: 0.0022 max mem: 19788 +Epoch: [23] [1170/2138] eta: 0:47:42 lr: 2.247603899215137e-05 loss: 0.0230 (0.0263) time: 3.0063 data: 0.0023 max mem: 19788 +Epoch: [23] [1180/2138] eta: 0:47:12 lr: 2.247028811150805e-05 loss: 0.0232 (0.0263) time: 3.0208 data: 0.0022 max mem: 19788 +Epoch: [23] [1190/2138] eta: 0:46:44 lr: 2.2464537067322507e-05 loss: 0.0249 (0.0263) time: 3.0515 data: 0.0022 max mem: 19788 +Epoch: [23] [1200/2138] eta: 0:46:15 lr: 2.245878585954356e-05 loss: 0.0230 (0.0262) time: 3.0801 data: 0.0022 max mem: 19788 +Epoch: [23] [1210/2138] eta: 0:45:46 lr: 2.245303448812001e-05 loss: 0.0249 (0.0262) time: 3.0147 data: 0.0024 max mem: 19788 +Epoch: [23] [1220/2138] eta: 0:45:16 lr: 2.2447282953000613e-05 loss: 0.0249 (0.0262) time: 2.9863 data: 0.0026 max mem: 19788 +Epoch: [23] [1230/2138] eta: 0:44:47 lr: 2.244153125413412e-05 loss: 0.0231 (0.0262) time: 2.9652 data: 0.0026 max mem: 19788 +Epoch: [23] [1240/2138] eta: 0:44:18 lr: 2.2435779391469218e-05 loss: 0.0241 (0.0262) time: 2.9896 data: 0.0024 max mem: 19788 +Epoch: [23] [1250/2138] eta: 0:43:48 lr: 2.2430027364954595e-05 loss: 0.0234 (0.0262) time: 3.0108 data: 0.0023 max mem: 19788 +Epoch: [23] [1260/2138] eta: 0:43:19 lr: 2.242427517453888e-05 loss: 0.0212 (0.0262) time: 2.9936 data: 0.0023 max mem: 19788 +Epoch: [23] [1270/2138] eta: 0:42:50 lr: 2.2418522820170702e-05 loss: 0.0219 (0.0261) time: 2.9956 data: 0.0025 max mem: 19788 +Epoch: [23] [1280/2138] eta: 0:42:21 lr: 2.2412770301798626e-05 loss: 0.0234 (0.0261) time: 3.0569 data: 0.0026 max mem: 19788 +Epoch: [23] [1290/2138] eta: 0:41:52 lr: 2.2407017619371217e-05 loss: 0.0257 (0.0261) time: 3.0570 data: 0.0024 max mem: 19788 +Epoch: [23] [1300/2138] eta: 0:41:22 lr: 2.2401264772836984e-05 loss: 0.0263 (0.0261) time: 2.9971 data: 0.0022 max mem: 19788 +Epoch: [23] [1310/2138] eta: 0:40:53 lr: 2.2395511762144426e-05 loss: 0.0229 (0.0261) time: 3.0087 data: 0.0022 max mem: 19788 +Epoch: [23] [1320/2138] eta: 0:40:24 lr: 2.2389758587241985e-05 loss: 0.0279 (0.0262) time: 3.0510 data: 0.0023 max mem: 19788 +Epoch: [23] [1330/2138] eta: 0:39:55 lr: 2.238400524807811e-05 loss: 0.0246 (0.0262) time: 3.0646 data: 0.0024 max mem: 19788 +Epoch: [23] [1340/2138] eta: 0:39:26 lr: 2.2378251744601177e-05 loss: 0.0239 (0.0262) time: 3.0385 data: 0.0025 max mem: 19788 +Epoch: [23] [1350/2138] eta: 0:38:57 lr: 2.2372498076759567e-05 loss: 0.0286 (0.0262) time: 3.0531 data: 0.0026 max mem: 19788 +Epoch: [23] [1360/2138] eta: 0:38:28 lr: 2.2366744244501604e-05 loss: 0.0284 (0.0262) time: 3.0843 data: 0.0028 max mem: 19788 +Epoch: [23] [1370/2138] eta: 0:37:58 lr: 2.23609902477756e-05 loss: 0.0262 (0.0262) time: 3.0578 data: 0.0030 max mem: 19788 +Epoch: [23] [1380/2138] eta: 0:37:29 lr: 2.2355236086529827e-05 loss: 0.0262 (0.0262) time: 3.0583 data: 0.0030 max mem: 19788 +Epoch: [23] [1390/2138] eta: 0:37:01 lr: 2.2349481760712512e-05 loss: 0.0252 (0.0262) time: 3.1425 data: 0.0029 max mem: 19788 +Epoch: [23] [1400/2138] eta: 0:36:32 lr: 2.234372727027188e-05 loss: 0.0236 (0.0262) time: 3.1132 data: 0.0026 max mem: 19788 +Epoch: [23] [1410/2138] eta: 0:36:03 lr: 2.23379726151561e-05 loss: 0.0259 (0.0262) time: 3.0915 data: 0.0024 max mem: 19788 +Epoch: [23] [1420/2138] eta: 0:35:34 lr: 2.2332217795313335e-05 loss: 0.0245 (0.0262) time: 3.1320 data: 0.0026 max mem: 19788 +Epoch: [23] [1430/2138] eta: 0:35:05 lr: 2.2326462810691683e-05 loss: 0.0269 (0.0262) time: 3.1281 data: 0.0028 max mem: 19788 +Epoch: [23] [1440/2138] eta: 0:34:37 lr: 2.2320707661239245e-05 loss: 0.0272 (0.0262) time: 3.2941 data: 0.0027 max mem: 19788 +Epoch: [23] [1450/2138] eta: 0:34:08 lr: 2.2314952346904062e-05 loss: 0.0270 (0.0262) time: 3.2523 data: 0.0025 max mem: 19788 +Epoch: [23] [1460/2138] eta: 0:33:39 lr: 2.2309196867634173e-05 loss: 0.0236 (0.0262) time: 3.0727 data: 0.0024 max mem: 19788 +Epoch: [23] [1470/2138] eta: 0:33:10 lr: 2.2303441223377553e-05 loss: 0.0248 (0.0262) time: 3.1313 data: 0.0023 max mem: 19788 +Epoch: [23] [1480/2138] eta: 0:32:41 lr: 2.2297685414082174e-05 loss: 0.0248 (0.0262) time: 3.2289 data: 0.0025 max mem: 19788 +Epoch: [23] [1490/2138] eta: 0:32:12 lr: 2.2291929439695953e-05 loss: 0.0237 (0.0262) time: 3.1874 data: 0.0028 max mem: 19788 +Epoch: [23] [1500/2138] eta: 0:31:43 lr: 2.2286173300166806e-05 loss: 0.0266 (0.0262) time: 3.0657 data: 0.0029 max mem: 19788 +Epoch: [23] [1510/2138] eta: 0:31:13 lr: 2.2280416995442584e-05 loss: 0.0241 (0.0262) time: 3.0120 data: 0.0032 max mem: 19788 +Epoch: [23] [1520/2138] eta: 0:30:43 lr: 2.2274660525471132e-05 loss: 0.0236 (0.0262) time: 3.0231 data: 0.0029 max mem: 19788 +Epoch: [23] [1530/2138] eta: 0:30:14 lr: 2.2268903890200244e-05 loss: 0.0247 (0.0262) time: 3.0400 data: 0.0022 max mem: 19788 +Epoch: [23] [1540/2138] eta: 0:29:45 lr: 2.22631470895777e-05 loss: 0.0252 (0.0262) time: 3.1691 data: 0.0021 max mem: 19788 +Epoch: [23] [1550/2138] eta: 0:29:16 lr: 2.225739012355123e-05 loss: 0.0222 (0.0262) time: 3.2798 data: 0.0023 max mem: 19788 +Epoch: [23] [1560/2138] eta: 0:28:48 lr: 2.2251632992068555e-05 loss: 0.0242 (0.0262) time: 3.2948 data: 0.0025 max mem: 19788 +Epoch: [23] [1570/2138] eta: 0:28:18 lr: 2.2245875695077345e-05 loss: 0.0242 (0.0262) time: 3.1840 data: 0.0027 max mem: 19788 +Epoch: [23] [1580/2138] eta: 0:27:48 lr: 2.2240118232525252e-05 loss: 0.0238 (0.0262) time: 3.0009 data: 0.0028 max mem: 19788 +Epoch: [23] [1590/2138] eta: 0:27:18 lr: 2.2234360604359877e-05 loss: 0.0259 (0.0262) time: 3.0027 data: 0.0027 max mem: 19788 +Epoch: [23] [1600/2138] eta: 0:26:48 lr: 2.222860281052882e-05 loss: 0.0285 (0.0263) time: 3.0538 data: 0.0026 max mem: 19788 +Epoch: [23] [1610/2138] eta: 0:26:19 lr: 2.222284485097962e-05 loss: 0.0291 (0.0263) time: 3.0412 data: 0.0026 max mem: 19788 +Epoch: [23] [1620/2138] eta: 0:25:49 lr: 2.22170867256598e-05 loss: 0.0222 (0.0263) time: 3.0641 data: 0.0026 max mem: 19788 +Epoch: [23] [1630/2138] eta: 0:25:20 lr: 2.2211328434516838e-05 loss: 0.0235 (0.0263) time: 3.1520 data: 0.0025 max mem: 19788 +Epoch: [23] [1640/2138] eta: 0:24:51 lr: 2.220556997749821e-05 loss: 0.0262 (0.0263) time: 3.3471 data: 0.0023 max mem: 19788 +Epoch: [23] [1650/2138] eta: 0:24:21 lr: 2.219981135455132e-05 loss: 0.0270 (0.0263) time: 3.2475 data: 0.0023 max mem: 19788 +Epoch: [23] [1660/2138] eta: 0:23:51 lr: 2.2194052565623574e-05 loss: 0.0268 (0.0263) time: 2.9770 data: 0.0025 max mem: 19788 +Epoch: [23] [1670/2138] eta: 0:23:22 lr: 2.2188293610662318e-05 loss: 0.0232 (0.0262) time: 3.0023 data: 0.0025 max mem: 19788 +Epoch: [23] [1680/2138] eta: 0:22:52 lr: 2.2182534489614896e-05 loss: 0.0254 (0.0262) time: 3.0902 data: 0.0026 max mem: 19788 +Epoch: [23] [1690/2138] eta: 0:22:22 lr: 2.2176775202428595e-05 loss: 0.0256 (0.0262) time: 3.0635 data: 0.0024 max mem: 19788 +Epoch: [23] [1700/2138] eta: 0:21:52 lr: 2.2171015749050676e-05 loss: 0.0232 (0.0262) time: 3.0200 data: 0.0021 max mem: 19788 +Epoch: [23] [1710/2138] eta: 0:21:23 lr: 2.216525612942838e-05 loss: 0.0232 (0.0262) time: 3.1192 data: 0.0024 max mem: 19788 +Epoch: [23] [1720/2138] eta: 0:20:53 lr: 2.21594963435089e-05 loss: 0.0262 (0.0262) time: 3.1005 data: 0.0024 max mem: 19788 +Epoch: [23] [1730/2138] eta: 0:20:23 lr: 2.215373639123941e-05 loss: 0.0262 (0.0262) time: 3.0288 data: 0.0022 max mem: 19788 +Epoch: [23] [1740/2138] eta: 0:19:53 lr: 2.2147976272567037e-05 loss: 0.0253 (0.0262) time: 3.0047 data: 0.0026 max mem: 19788 +Epoch: [23] [1750/2138] eta: 0:19:23 lr: 2.21422159874389e-05 loss: 0.0253 (0.0262) time: 2.9982 data: 0.0028 max mem: 19788 +Epoch: [23] [1760/2138] eta: 0:18:53 lr: 2.213645553580206e-05 loss: 0.0250 (0.0262) time: 3.0479 data: 0.0027 max mem: 19788 +Epoch: [23] [1770/2138] eta: 0:18:23 lr: 2.2130694917603563e-05 loss: 0.0233 (0.0262) time: 3.0262 data: 0.0027 max mem: 19788 +Epoch: [23] [1780/2138] eta: 0:17:53 lr: 2.212493413279041e-05 loss: 0.0232 (0.0262) time: 3.0771 data: 0.0025 max mem: 19788 +Epoch: [23] [1790/2138] eta: 0:17:25 lr: 2.2119173181309584e-05 loss: 0.0232 (0.0262) time: 3.3880 data: 0.0024 max mem: 19788 +Epoch: [23] [1800/2138] eta: 0:16:55 lr: 2.211341206310802e-05 loss: 0.0255 (0.0262) time: 3.3325 data: 0.0024 max mem: 19788 +Epoch: [23] [1810/2138] eta: 0:16:25 lr: 2.2107650778132643e-05 loss: 0.0277 (0.0262) time: 3.0448 data: 0.0023 max mem: 19788 +Epoch: [23] [1820/2138] eta: 0:15:55 lr: 2.2101889326330315e-05 loss: 0.0220 (0.0262) time: 3.1336 data: 0.0023 max mem: 19788 +Epoch: [23] [1830/2138] eta: 0:15:25 lr: 2.20961277076479e-05 loss: 0.0235 (0.0262) time: 3.1333 data: 0.0024 max mem: 19788 +Epoch: [23] [1840/2138] eta: 0:14:55 lr: 2.209036592203219e-05 loss: 0.0244 (0.0262) time: 2.9920 data: 0.0023 max mem: 19788 +Epoch: [23] [1850/2138] eta: 0:14:25 lr: 2.208460396942999e-05 loss: 0.0261 (0.0262) time: 2.9703 data: 0.0022 max mem: 19788 +Epoch: [23] [1860/2138] eta: 0:13:55 lr: 2.2078841849788035e-05 loss: 0.0261 (0.0262) time: 3.1166 data: 0.0024 max mem: 19788 +Epoch: [23] [1870/2138] eta: 0:13:25 lr: 2.207307956305305e-05 loss: 0.0259 (0.0262) time: 3.1944 data: 0.0024 max mem: 19788 +Epoch: [23] [1880/2138] eta: 0:12:55 lr: 2.2067317109171706e-05 loss: 0.0223 (0.0262) time: 3.1113 data: 0.0021 max mem: 19788 +Epoch: [23] [1890/2138] eta: 0:12:25 lr: 2.2061554488090674e-05 loss: 0.0214 (0.0262) time: 3.0334 data: 0.0022 max mem: 19788 +Epoch: [23] [1900/2138] eta: 0:11:55 lr: 2.205579169975656e-05 loss: 0.0243 (0.0262) time: 2.9723 data: 0.0024 max mem: 19788 +Epoch: [23] [1910/2138] eta: 0:11:25 lr: 2.205002874411596e-05 loss: 0.0225 (0.0262) time: 3.0016 data: 0.0027 max mem: 19788 +Epoch: [23] [1920/2138] eta: 0:10:55 lr: 2.204426562111542e-05 loss: 0.0224 (0.0261) time: 3.0046 data: 0.0027 max mem: 19788 +Epoch: [23] [1930/2138] eta: 0:10:25 lr: 2.2038502330701468e-05 loss: 0.0231 (0.0261) time: 2.9837 data: 0.0027 max mem: 19788 +Epoch: [23] [1940/2138] eta: 0:09:55 lr: 2.2032738872820585e-05 loss: 0.0231 (0.0261) time: 3.2223 data: 0.0029 max mem: 19788 +Epoch: [23] [1950/2138] eta: 0:09:25 lr: 2.202697524741924e-05 loss: 0.0225 (0.0261) time: 3.2808 data: 0.0030 max mem: 19788 +Epoch: [23] [1960/2138] eta: 0:08:55 lr: 2.2021211454443844e-05 loss: 0.0230 (0.0261) time: 3.0547 data: 0.0028 max mem: 19788 +Epoch: [23] [1970/2138] eta: 0:08:25 lr: 2.2015447493840803e-05 loss: 0.0227 (0.0261) time: 3.1145 data: 0.0027 max mem: 19788 +Epoch: [23] [1980/2138] eta: 0:07:55 lr: 2.2009683365556456e-05 loss: 0.0220 (0.0261) time: 3.1565 data: 0.0029 max mem: 19788 +Epoch: [23] [1990/2138] eta: 0:07:25 lr: 2.2003919069537146e-05 loss: 0.0222 (0.0261) time: 3.0288 data: 0.0030 max mem: 19788 +Epoch: [23] [2000/2138] eta: 0:06:55 lr: 2.199815460572916e-05 loss: 0.0222 (0.0261) time: 3.0764 data: 0.0029 max mem: 19788 +Epoch: [23] [2010/2138] eta: 0:06:25 lr: 2.1992389974078755e-05 loss: 0.0226 (0.0261) time: 3.2818 data: 0.0028 max mem: 19788 +Epoch: [23] [2020/2138] eta: 0:05:55 lr: 2.198662517453216e-05 loss: 0.0262 (0.0261) time: 3.5504 data: 0.0027 max mem: 19788 +Epoch: [23] [2030/2138] eta: 0:05:25 lr: 2.1980860207035563e-05 loss: 0.0262 (0.0261) time: 3.4557 data: 0.0024 max mem: 19788 +Epoch: [23] [2040/2138] eta: 0:04:55 lr: 2.1975095071535143e-05 loss: 0.0236 (0.0261) time: 3.2746 data: 0.0023 max mem: 19788 +Epoch: [23] [2050/2138] eta: 0:04:25 lr: 2.1969329767977007e-05 loss: 0.0229 (0.0261) time: 3.2699 data: 0.0023 max mem: 19788 +Epoch: [23] [2060/2138] eta: 0:03:55 lr: 2.1963564296307266e-05 loss: 0.0229 (0.0261) time: 3.2058 data: 0.0022 max mem: 19788 +Epoch: [23] [2070/2138] eta: 0:03:25 lr: 2.195779865647197e-05 loss: 0.0220 (0.0261) time: 3.1643 data: 0.0023 max mem: 19788 +Epoch: [23] [2080/2138] eta: 0:02:55 lr: 2.1952032848417162e-05 loss: 0.0225 (0.0261) time: 3.0978 data: 0.0025 max mem: 19788 +Epoch: [23] [2090/2138] eta: 0:02:25 lr: 2.1946266872088826e-05 loss: 0.0248 (0.0261) time: 3.1123 data: 0.0029 max mem: 19788 +Epoch: [23] [2100/2138] eta: 0:01:54 lr: 2.1940500727432933e-05 loss: 0.0236 (0.0261) time: 3.2443 data: 0.0029 max mem: 19788 +Epoch: [23] [2110/2138] eta: 0:01:24 lr: 2.1934734414395404e-05 loss: 0.0258 (0.0261) time: 3.1713 data: 0.0025 max mem: 19788 +Epoch: [23] [2120/2138] eta: 0:00:54 lr: 2.192896793292215e-05 loss: 0.0278 (0.0261) time: 3.0477 data: 0.0025 max mem: 19788 +Epoch: [23] [2130/2138] eta: 0:00:24 lr: 2.1923201282959016e-05 loss: 0.0317 (0.0261) time: 3.0401 data: 0.0024 max mem: 19788 +Epoch: [23] Total time: 1:47:45 +Test: [ 0/21770] eta: 15:47:04 time: 2.6102 data: 2.3639 max mem: 19788 +Test: [ 100/21770] eta: 0:27:39 time: 0.0529 data: 0.0018 max mem: 19788 +Test: [ 200/21770] eta: 0:23:12 time: 0.0506 data: 0.0015 max mem: 19788 +Test: [ 300/21770] eta: 0:21:33 time: 0.0456 data: 0.0015 max mem: 19788 +Test: [ 400/21770] eta: 0:20:26 time: 0.0522 data: 0.0018 max mem: 19788 +Test: [ 500/21770] eta: 0:19:53 time: 0.0472 data: 0.0016 max mem: 19788 +Test: [ 600/21770] eta: 0:19:30 time: 0.0529 data: 0.0018 max mem: 19788 +Test: [ 700/21770] eta: 0:19:13 time: 0.0522 data: 0.0018 max mem: 19788 +Test: [ 800/21770] eta: 0:18:57 time: 0.0443 data: 0.0015 max mem: 19788 +Test: [ 900/21770] eta: 0:18:31 time: 0.0441 data: 0.0015 max mem: 19788 +Test: [ 1000/21770] eta: 0:18:12 time: 0.0448 data: 0.0015 max mem: 19788 +Test: [ 1100/21770] eta: 0:17:49 time: 0.0424 data: 0.0014 max mem: 19788 +Test: [ 1200/21770] eta: 0:17:29 time: 0.0444 data: 0.0015 max mem: 19788 +Test: [ 1300/21770] eta: 0:17:13 time: 0.0456 data: 0.0014 max mem: 19788 +Test: [ 1400/21770] eta: 0:17:12 time: 0.0555 data: 0.0017 max mem: 19788 +Test: [ 1500/21770] eta: 0:17:07 time: 0.0433 data: 0.0015 max mem: 19788 +Test: [ 1600/21770] eta: 0:17:00 time: 0.0529 data: 0.0018 max mem: 19788 +Test: [ 1700/21770] eta: 0:16:51 time: 0.0457 data: 0.0016 max mem: 19788 +Test: [ 1800/21770] eta: 0:16:46 time: 0.0543 data: 0.0017 max mem: 19788 +Test: [ 1900/21770] eta: 0:16:41 time: 0.0439 data: 0.0015 max mem: 19788 +Test: [ 2000/21770] eta: 0:16:36 time: 0.0463 data: 0.0016 max mem: 19788 +Test: [ 2100/21770] eta: 0:16:30 time: 0.0533 data: 0.0018 max mem: 19788 +Test: [ 2200/21770] eta: 0:16:22 time: 0.0444 data: 0.0016 max mem: 19788 +Test: [ 2300/21770] eta: 0:16:13 time: 0.0427 data: 0.0015 max mem: 19788 +Test: [ 2400/21770] eta: 0:16:05 time: 0.0484 data: 0.0016 max mem: 19788 +Test: [ 2500/21770] eta: 0:15:57 time: 0.0508 data: 0.0015 max mem: 19788 +Test: [ 2600/21770] eta: 0:15:51 time: 0.0457 data: 0.0014 max mem: 19788 +Test: [ 2700/21770] eta: 0:15:44 time: 0.0446 data: 0.0016 max mem: 19788 +Test: [ 2800/21770] eta: 0:15:36 time: 0.0479 data: 0.0015 max mem: 19788 +Test: [ 2900/21770] eta: 0:15:29 time: 0.0441 data: 0.0014 max mem: 19788 +Test: [ 3000/21770] eta: 0:15:23 time: 0.0449 data: 0.0015 max mem: 19788 +Test: [ 3100/21770] eta: 0:15:19 time: 0.0519 data: 0.0017 max mem: 19788 +Test: [ 3200/21770] eta: 0:15:14 time: 0.0442 data: 0.0018 max mem: 19788 +Test: [ 3300/21770] eta: 0:15:10 time: 0.0551 data: 0.0019 max mem: 19788 +Test: [ 3400/21770] eta: 0:15:06 time: 0.0447 data: 0.0013 max mem: 19788 +Test: [ 3500/21770] eta: 0:15:01 time: 0.0527 data: 0.0019 max mem: 19788 +Test: [ 3600/21770] eta: 0:14:54 time: 0.0439 data: 0.0014 max mem: 19788 +Test: [ 3700/21770] eta: 0:14:48 time: 0.0526 data: 0.0018 max mem: 19788 +Test: [ 3800/21770] eta: 0:14:43 time: 0.0459 data: 0.0016 max mem: 19788 +Test: [ 3900/21770] eta: 0:14:36 time: 0.0530 data: 0.0016 max mem: 19788 +Test: [ 4000/21770] eta: 0:14:31 time: 0.0476 data: 0.0015 max mem: 19788 +Test: [ 4100/21770] eta: 0:14:24 time: 0.0425 data: 0.0014 max mem: 19788 +Test: [ 4200/21770] eta: 0:14:18 time: 0.0454 data: 0.0014 max mem: 19788 +Test: [ 4300/21770] eta: 0:14:11 time: 0.0464 data: 0.0017 max mem: 19788 +Test: [ 4400/21770] eta: 0:14:05 time: 0.0440 data: 0.0015 max mem: 19788 +Test: [ 4500/21770] eta: 0:14:01 time: 0.0529 data: 0.0018 max mem: 19788 +Test: [ 4600/21770] eta: 0:13:55 time: 0.0467 data: 0.0015 max mem: 19788 +Test: [ 4700/21770] eta: 0:13:50 time: 0.0460 data: 0.0015 max mem: 19788 +Test: [ 4800/21770] eta: 0:13:46 time: 0.0521 data: 0.0017 max mem: 19788 +Test: [ 4900/21770] eta: 0:13:41 time: 0.0438 data: 0.0015 max mem: 19788 +Test: [ 5000/21770] eta: 0:13:35 time: 0.0490 data: 0.0016 max mem: 19788 +Test: [ 5100/21770] eta: 0:13:29 time: 0.0444 data: 0.0015 max mem: 19788 +Test: [ 5200/21770] eta: 0:13:23 time: 0.0452 data: 0.0015 max mem: 19788 +Test: [ 5300/21770] eta: 0:13:19 time: 0.0543 data: 0.0016 max mem: 19788 +Test: [ 5400/21770] eta: 0:13:13 time: 0.0492 data: 0.0018 max mem: 19788 +Test: [ 5500/21770] eta: 0:13:08 time: 0.0442 data: 0.0017 max mem: 19788 +Test: [ 5600/21770] eta: 0:13:02 time: 0.0447 data: 0.0016 max mem: 19788 +Test: [ 5700/21770] eta: 0:12:57 time: 0.0438 data: 0.0016 max mem: 19788 +Test: [ 5800/21770] eta: 0:12:51 time: 0.0427 data: 0.0015 max mem: 19788 +Test: [ 5900/21770] eta: 0:12:46 time: 0.0422 data: 0.0015 max mem: 19788 +Test: [ 6000/21770] eta: 0:12:40 time: 0.0468 data: 0.0017 max mem: 19788 +Test: [ 6100/21770] eta: 0:12:35 time: 0.0465 data: 0.0017 max mem: 19788 +Test: [ 6200/21770] eta: 0:12:30 time: 0.0446 data: 0.0015 max mem: 19788 +Test: [ 6300/21770] eta: 0:12:25 time: 0.0490 data: 0.0017 max mem: 19788 +Test: [ 6400/21770] eta: 0:12:20 time: 0.0500 data: 0.0015 max mem: 19788 +Test: [ 6500/21770] eta: 0:12:16 time: 0.0515 data: 0.0019 max mem: 19788 +Test: [ 6600/21770] eta: 0:12:11 time: 0.0483 data: 0.0017 max mem: 19788 +Test: [ 6700/21770] eta: 0:12:07 time: 0.0537 data: 0.0018 max mem: 19788 +Test: [ 6800/21770] eta: 0:12:02 time: 0.0446 data: 0.0017 max mem: 19788 +Test: [ 6900/21770] eta: 0:11:57 time: 0.0479 data: 0.0018 max mem: 19788 +Test: [ 7000/21770] eta: 0:11:52 time: 0.0450 data: 0.0017 max mem: 19788 +Test: [ 7100/21770] eta: 0:11:47 time: 0.0441 data: 0.0017 max mem: 19788 +Test: [ 7200/21770] eta: 0:11:42 time: 0.0444 data: 0.0014 max mem: 19788 +Test: [ 7300/21770] eta: 0:11:37 time: 0.0530 data: 0.0019 max mem: 19788 +Test: [ 7400/21770] eta: 0:11:34 time: 0.0540 data: 0.0019 max mem: 19788 +Test: [ 7500/21770] eta: 0:11:29 time: 0.0465 data: 0.0014 max mem: 19788 +Test: [ 7600/21770] eta: 0:11:24 time: 0.0533 data: 0.0017 max mem: 19788 +Test: [ 7700/21770] eta: 0:11:19 time: 0.0484 data: 0.0018 max mem: 19788 +Test: [ 7800/21770] eta: 0:11:15 time: 0.0492 data: 0.0016 max mem: 19788 +Test: [ 7900/21770] eta: 0:11:10 time: 0.0475 data: 0.0018 max mem: 19788 +Test: [ 8000/21770] eta: 0:11:06 time: 0.0445 data: 0.0016 max mem: 19788 +Test: [ 8100/21770] eta: 0:11:01 time: 0.0484 data: 0.0016 max mem: 19788 +Test: [ 8200/21770] eta: 0:10:56 time: 0.0512 data: 0.0014 max mem: 19788 +Test: [ 8300/21770] eta: 0:10:52 time: 0.0444 data: 0.0015 max mem: 19788 +Test: [ 8400/21770] eta: 0:10:46 time: 0.0435 data: 0.0015 max mem: 19788 +Test: [ 8500/21770] eta: 0:10:41 time: 0.0427 data: 0.0015 max mem: 19788 +Test: [ 8600/21770] eta: 0:10:36 time: 0.0530 data: 0.0019 max mem: 19788 +Test: [ 8700/21770] eta: 0:10:31 time: 0.0436 data: 0.0016 max mem: 19788 +Test: [ 8800/21770] eta: 0:10:26 time: 0.0443 data: 0.0014 max mem: 19788 +Test: [ 8900/21770] eta: 0:10:21 time: 0.0533 data: 0.0019 max mem: 19788 +Test: [ 9000/21770] eta: 0:10:16 time: 0.0453 data: 0.0014 max mem: 19788 +Test: [ 9100/21770] eta: 0:10:12 time: 0.0552 data: 0.0018 max mem: 19788 +Test: [ 9200/21770] eta: 0:10:07 time: 0.0503 data: 0.0016 max mem: 19788 +Test: [ 9300/21770] eta: 0:10:02 time: 0.0443 data: 0.0018 max mem: 19788 +Test: [ 9400/21770] eta: 0:09:57 time: 0.0452 data: 0.0016 max mem: 19788 +Test: [ 9500/21770] eta: 0:09:52 time: 0.0453 data: 0.0018 max mem: 19788 +Test: [ 9600/21770] eta: 0:09:47 time: 0.0450 data: 0.0016 max mem: 19788 +Test: [ 9700/21770] eta: 0:09:42 time: 0.0538 data: 0.0017 max mem: 19788 +Test: [ 9800/21770] eta: 0:09:37 time: 0.0439 data: 0.0014 max mem: 19788 +Test: [ 9900/21770] eta: 0:09:32 time: 0.0439 data: 0.0015 max mem: 19788 +Test: [10000/21770] eta: 0:09:27 time: 0.0533 data: 0.0019 max mem: 19788 +Test: [10100/21770] eta: 0:09:23 time: 0.0463 data: 0.0016 max mem: 19788 +Test: [10200/21770] eta: 0:09:19 time: 0.0524 data: 0.0017 max mem: 19788 +Test: [10300/21770] eta: 0:09:14 time: 0.0497 data: 0.0016 max mem: 19788 +Test: [10400/21770] eta: 0:09:09 time: 0.0444 data: 0.0015 max mem: 19788 +Test: [10500/21770] eta: 0:09:04 time: 0.0523 data: 0.0018 max mem: 19788 +Test: [10600/21770] eta: 0:08:59 time: 0.0461 data: 0.0016 max mem: 19788 +Test: [10700/21770] eta: 0:08:55 time: 0.0485 data: 0.0015 max mem: 19788 +Test: [10800/21770] eta: 0:08:50 time: 0.0504 data: 0.0018 max mem: 19788 +Test: [10900/21770] eta: 0:08:45 time: 0.0451 data: 0.0016 max mem: 19788 +Test: [11000/21770] eta: 0:08:40 time: 0.0450 data: 0.0016 max mem: 19788 +Test: [11100/21770] eta: 0:08:35 time: 0.0448 data: 0.0016 max mem: 19788 +Test: [11200/21770] eta: 0:08:30 time: 0.0526 data: 0.0021 max mem: 19788 +Test: [11300/21770] eta: 0:08:26 time: 0.0471 data: 0.0016 max mem: 19788 +Test: [11400/21770] eta: 0:08:21 time: 0.0548 data: 0.0018 max mem: 19788 +Test: [11500/21770] eta: 0:08:16 time: 0.0447 data: 0.0015 max mem: 19788 +Test: [11600/21770] eta: 0:08:12 time: 0.0517 data: 0.0020 max mem: 19788 +Test: [11700/21770] eta: 0:08:07 time: 0.0539 data: 0.0020 max mem: 19788 +Test: [11800/21770] eta: 0:08:03 time: 0.0457 data: 0.0016 max mem: 19788 +Test: [11900/21770] eta: 0:07:58 time: 0.0446 data: 0.0016 max mem: 19788 +Test: [12000/21770] eta: 0:07:53 time: 0.0497 data: 0.0018 max mem: 19788 +Test: [12100/21770] eta: 0:07:48 time: 0.0547 data: 0.0019 max mem: 19788 +Test: [12200/21770] eta: 0:07:43 time: 0.0452 data: 0.0017 max mem: 19788 +Test: [12300/21770] eta: 0:07:38 time: 0.0459 data: 0.0013 max mem: 19788 +Test: [12400/21770] eta: 0:07:33 time: 0.0493 data: 0.0017 max mem: 19788 +Test: [12500/21770] eta: 0:07:28 time: 0.0488 data: 0.0016 max mem: 19788 +Test: [12600/21770] eta: 0:07:23 time: 0.0446 data: 0.0015 max mem: 19788 +Test: [12700/21770] eta: 0:07:18 time: 0.0526 data: 0.0018 max mem: 19788 +Test: [12800/21770] eta: 0:07:14 time: 0.0459 data: 0.0015 max mem: 19788 +Test: [12900/21770] eta: 0:07:08 time: 0.0454 data: 0.0014 max mem: 19788 +Test: [13000/21770] eta: 0:07:04 time: 0.0442 data: 0.0013 max mem: 19788 +Test: [13100/21770] eta: 0:06:59 time: 0.0450 data: 0.0016 max mem: 19788 +Test: [13200/21770] eta: 0:06:54 time: 0.0541 data: 0.0016 max mem: 19788 +Test: [13300/21770] eta: 0:06:49 time: 0.0449 data: 0.0015 max mem: 19788 +Test: [13400/21770] eta: 0:06:44 time: 0.0538 data: 0.0019 max mem: 19788 +Test: [13500/21770] eta: 0:06:39 time: 0.0488 data: 0.0016 max mem: 19788 +Test: [13600/21770] eta: 0:06:34 time: 0.0452 data: 0.0017 max mem: 19788 +Test: [13700/21770] eta: 0:06:29 time: 0.0518 data: 0.0017 max mem: 19788 +Test: [13800/21770] eta: 0:06:24 time: 0.0454 data: 0.0017 max mem: 19788 +Test: [13900/21770] eta: 0:06:19 time: 0.0440 data: 0.0016 max mem: 19788 +Test: [14000/21770] eta: 0:06:14 time: 0.0436 data: 0.0014 max mem: 19788 +Test: [14100/21770] eta: 0:06:10 time: 0.0469 data: 0.0015 max mem: 19788 +Test: [14200/21770] eta: 0:06:05 time: 0.0455 data: 0.0014 max mem: 19788 +Test: [14300/21770] eta: 0:06:00 time: 0.0432 data: 0.0014 max mem: 19788 +Test: [14400/21770] eta: 0:05:55 time: 0.0532 data: 0.0018 max mem: 19788 +Test: [14500/21770] eta: 0:05:50 time: 0.0447 data: 0.0016 max mem: 19788 +Test: [14600/21770] eta: 0:05:46 time: 0.0534 data: 0.0016 max mem: 19788 +Test: [14700/21770] eta: 0:05:41 time: 0.0525 data: 0.0017 max mem: 19788 +Test: [14800/21770] eta: 0:05:36 time: 0.0517 data: 0.0017 max mem: 19788 +Test: [14900/21770] eta: 0:05:31 time: 0.0446 data: 0.0014 max mem: 19788 +Test: [15000/21770] eta: 0:05:26 time: 0.0467 data: 0.0013 max mem: 19788 +Test: [15100/21770] eta: 0:05:22 time: 0.0447 data: 0.0015 max mem: 19788 +Test: [15200/21770] eta: 0:05:17 time: 0.0534 data: 0.0016 max mem: 19788 +Test: [15300/21770] eta: 0:05:12 time: 0.0522 data: 0.0019 max mem: 19788 +Test: [15400/21770] eta: 0:05:07 time: 0.0463 data: 0.0014 max mem: 19788 +Test: [15500/21770] eta: 0:05:02 time: 0.0445 data: 0.0015 max mem: 19788 +Test: [15600/21770] eta: 0:04:57 time: 0.0457 data: 0.0015 max mem: 19788 +Test: [15700/21770] eta: 0:04:52 time: 0.0532 data: 0.0020 max mem: 19788 +Test: [15800/21770] eta: 0:04:48 time: 0.0446 data: 0.0014 max mem: 19788 +Test: [15900/21770] eta: 0:04:43 time: 0.0493 data: 0.0016 max mem: 19788 +Test: [16000/21770] eta: 0:04:38 time: 0.0526 data: 0.0019 max mem: 19788 +Test: [16100/21770] eta: 0:04:33 time: 0.0442 data: 0.0016 max mem: 19788 +Test: [16200/21770] eta: 0:04:28 time: 0.0513 data: 0.0016 max mem: 19788 +Test: [16300/21770] eta: 0:04:23 time: 0.0505 data: 0.0019 max mem: 19788 +Test: [16400/21770] eta: 0:04:18 time: 0.0511 data: 0.0017 max mem: 19788 +Test: [16500/21770] eta: 0:04:14 time: 0.0446 data: 0.0014 max mem: 19788 +Test: [16600/21770] eta: 0:04:09 time: 0.0446 data: 0.0014 max mem: 19788 +Test: [16700/21770] eta: 0:04:04 time: 0.0553 data: 0.0017 max mem: 19788 +Test: [16800/21770] eta: 0:03:59 time: 0.0443 data: 0.0015 max mem: 19788 +Test: [16900/21770] eta: 0:03:54 time: 0.0531 data: 0.0018 max mem: 19788 +Test: [17000/21770] eta: 0:03:49 time: 0.0447 data: 0.0014 max mem: 19788 +Test: [17100/21770] eta: 0:03:44 time: 0.0434 data: 0.0014 max mem: 19788 +Test: [17200/21770] eta: 0:03:40 time: 0.0450 data: 0.0017 max mem: 19788 +Test: [17300/21770] eta: 0:03:35 time: 0.0443 data: 0.0017 max mem: 19788 +Test: [17400/21770] eta: 0:03:30 time: 0.0444 data: 0.0015 max mem: 19788 +Test: [17500/21770] eta: 0:03:25 time: 0.0435 data: 0.0017 max mem: 19788 +Test: [17600/21770] eta: 0:03:20 time: 0.0467 data: 0.0015 max mem: 19788 +Test: [17700/21770] eta: 0:03:15 time: 0.0444 data: 0.0016 max mem: 19788 +Test: [17800/21770] eta: 0:03:10 time: 0.0440 data: 0.0015 max mem: 19788 +Test: [17900/21770] eta: 0:03:06 time: 0.0530 data: 0.0019 max mem: 19788 +Test: [18000/21770] eta: 0:03:01 time: 0.0536 data: 0.0018 max mem: 19788 +Test: [18100/21770] eta: 0:02:56 time: 0.0463 data: 0.0015 max mem: 19788 +Test: [18200/21770] eta: 0:02:51 time: 0.0492 data: 0.0017 max mem: 19788 +Test: [18300/21770] eta: 0:02:46 time: 0.0434 data: 0.0016 max mem: 19788 +Test: [18400/21770] eta: 0:02:42 time: 0.0452 data: 0.0014 max mem: 19788 +Test: [18500/21770] eta: 0:02:37 time: 0.0475 data: 0.0017 max mem: 19788 +Test: [18600/21770] eta: 0:02:32 time: 0.0448 data: 0.0015 max mem: 19788 +Test: [18700/21770] eta: 0:02:27 time: 0.0453 data: 0.0015 max mem: 19788 +Test: [18800/21770] eta: 0:02:22 time: 0.0501 data: 0.0017 max mem: 19788 +Test: [18900/21770] eta: 0:02:17 time: 0.0436 data: 0.0016 max mem: 19788 +Test: [19000/21770] eta: 0:02:13 time: 0.0516 data: 0.0018 max mem: 19788 +Test: [19100/21770] eta: 0:02:08 time: 0.0480 data: 0.0016 max mem: 19788 +Test: [19200/21770] eta: 0:02:03 time: 0.0520 data: 0.0018 max mem: 19788 +Test: [19300/21770] eta: 0:01:58 time: 0.0499 data: 0.0019 max mem: 19788 +Test: [19400/21770] eta: 0:01:53 time: 0.0466 data: 0.0016 max mem: 19788 +Test: [19500/21770] eta: 0:01:49 time: 0.0475 data: 0.0016 max mem: 19788 +Test: [19600/21770] eta: 0:01:44 time: 0.0442 data: 0.0013 max mem: 19788 +Test: [19700/21770] eta: 0:01:39 time: 0.0473 data: 0.0017 max mem: 19788 +Test: [19800/21770] eta: 0:01:34 time: 0.0464 data: 0.0016 max mem: 19788 +Test: [19900/21770] eta: 0:01:29 time: 0.0532 data: 0.0017 max mem: 19788 +Test: [20000/21770] eta: 0:01:25 time: 0.0431 data: 0.0014 max mem: 19788 +Test: [20100/21770] eta: 0:01:20 time: 0.0530 data: 0.0019 max mem: 19788 +Test: [20200/21770] eta: 0:01:15 time: 0.0451 data: 0.0015 max mem: 19788 +Test: [20300/21770] eta: 0:01:10 time: 0.0527 data: 0.0018 max mem: 19788 +Test: [20400/21770] eta: 0:01:05 time: 0.0497 data: 0.0015 max mem: 19788 +Test: [20500/21770] eta: 0:01:01 time: 0.0452 data: 0.0016 max mem: 19788 +Test: [20600/21770] eta: 0:00:56 time: 0.0427 data: 0.0015 max mem: 19788 +Test: [20700/21770] eta: 0:00:51 time: 0.0453 data: 0.0017 max mem: 19788 +Test: [20800/21770] eta: 0:00:46 time: 0.0453 data: 0.0015 max mem: 19788 +Test: [20900/21770] eta: 0:00:41 time: 0.0441 data: 0.0016 max mem: 19788 +Test: [21000/21770] eta: 0:00:36 time: 0.0459 data: 0.0016 max mem: 19788 +Test: [21100/21770] eta: 0:00:32 time: 0.0460 data: 0.0014 max mem: 19788 +Test: [21200/21770] eta: 0:00:27 time: 0.0443 data: 0.0016 max mem: 19788 +Test: [21300/21770] eta: 0:00:22 time: 0.0533 data: 0.0019 max mem: 19788 +Test: [21400/21770] eta: 0:00:17 time: 0.0465 data: 0.0014 max mem: 19788 +Test: [21500/21770] eta: 0:00:12 time: 0.0456 data: 0.0016 max mem: 19788 +Test: [21600/21770] eta: 0:00:08 time: 0.0462 data: 0.0019 max mem: 19788 +Test: [21700/21770] eta: 0:00:03 time: 0.0494 data: 0.0017 max mem: 19788 +Test: Total time: 0:17:25 +Final results: +Mean IoU is 64.75 + + precision@0.5 = 72.21 + precision@0.6 = 66.50 + precision@0.7 = 59.77 + precision@0.8 = 48.75 + precision@0.9 = 24.31 + overall IoU = 64.61 + mean IoU = 64.75 + +Mean accuracy for one-to-zero sample is 84.27 + +Average object IoU 0.6475215654880204 +Overall IoU 64.6100845336914 +Better epoch: 23 + +Epoch: [24] [ 0/2138] eta: 10:04:42 lr: 2.1918587841639406e-05 loss: 0.0649 (0.0649) time: 16.9705 data: 1.3737 max mem: 19788 +Epoch: [24] [ 10/2138] eta: 2:32:54 lr: 2.1912820888257983e-05 loss: 0.0235 (0.0283) time: 4.3112 data: 0.1264 max mem: 19788 +Epoch: [24] [ 20/2138] eta: 2:10:28 lr: 2.1907053766234922e-05 loss: 0.0223 (0.0254) time: 3.0322 data: 0.0021 max mem: 19788 +Epoch: [24] [ 30/2138] eta: 2:04:30 lr: 2.190128647551598e-05 loss: 0.0252 (0.0266) time: 3.1221 data: 0.0026 max mem: 19788 +Epoch: [24] [ 40/2138] eta: 1:59:14 lr: 2.189551901604685e-05 loss: 0.0264 (0.0264) time: 3.1103 data: 0.0027 max mem: 19788 +Epoch: [24] [ 50/2138] eta: 1:56:29 lr: 2.1889751387773192e-05 loss: 0.0249 (0.0263) time: 3.0425 data: 0.0025 max mem: 19788 +Epoch: [24] [ 60/2138] eta: 1:54:20 lr: 2.1883983590640664e-05 loss: 0.0260 (0.0265) time: 3.0787 data: 0.0024 max mem: 19788 +Epoch: [24] [ 70/2138] eta: 1:53:31 lr: 2.187821562459485e-05 loss: 0.0263 (0.0264) time: 3.1565 data: 0.0026 max mem: 19788 +Epoch: [24] [ 80/2138] eta: 1:53:56 lr: 2.1872447489581336e-05 loss: 0.0259 (0.0263) time: 3.3847 data: 0.0025 max mem: 19788 +Epoch: [24] [ 90/2138] eta: 1:52:16 lr: 2.1866679185545645e-05 loss: 0.0225 (0.0259) time: 3.2746 data: 0.0025 max mem: 19788 +Epoch: [24] [ 100/2138] eta: 1:50:52 lr: 2.186091071243329e-05 loss: 0.0223 (0.0258) time: 3.0294 data: 0.0024 max mem: 19788 +Epoch: [24] [ 110/2138] eta: 1:49:37 lr: 2.1855142070189736e-05 loss: 0.0236 (0.0257) time: 3.0336 data: 0.0025 max mem: 19788 +Epoch: [24] [ 120/2138] eta: 1:48:42 lr: 2.1849373258760424e-05 loss: 0.0214 (0.0253) time: 3.0706 data: 0.0027 max mem: 19788 +Epoch: [24] [ 130/2138] eta: 1:47:54 lr: 2.184360427809075e-05 loss: 0.0225 (0.0253) time: 3.1176 data: 0.0024 max mem: 19788 +Epoch: [24] [ 140/2138] eta: 1:46:53 lr: 2.1837835128126085e-05 loss: 0.0246 (0.0253) time: 3.0752 data: 0.0024 max mem: 19788 +Epoch: [24] [ 150/2138] eta: 1:46:26 lr: 2.183206580881176e-05 loss: 0.0229 (0.0252) time: 3.1356 data: 0.0028 max mem: 19788 +Epoch: [24] [ 160/2138] eta: 1:45:42 lr: 2.1826296320093087e-05 loss: 0.0229 (0.0251) time: 3.1841 data: 0.0029 max mem: 19788 +Epoch: [24] [ 170/2138] eta: 1:44:44 lr: 2.1820526661915323e-05 loss: 0.0236 (0.0250) time: 3.0482 data: 0.0028 max mem: 19788 +Epoch: [24] [ 180/2138] eta: 1:43:49 lr: 2.1814756834223708e-05 loss: 0.0234 (0.0251) time: 2.9785 data: 0.0028 max mem: 19788 +Epoch: [24] [ 190/2138] eta: 1:43:20 lr: 2.180898683696344e-05 loss: 0.0228 (0.0249) time: 3.0955 data: 0.0028 max mem: 19788 +Epoch: [24] [ 200/2138] eta: 1:42:45 lr: 2.1803216670079686e-05 loss: 0.0236 (0.0250) time: 3.1817 data: 0.0028 max mem: 19788 +Epoch: [24] [ 210/2138] eta: 1:42:22 lr: 2.179744633351757e-05 loss: 0.0254 (0.0252) time: 3.2122 data: 0.0027 max mem: 19788 +Epoch: [24] [ 220/2138] eta: 1:41:50 lr: 2.1791675827222207e-05 loss: 0.0220 (0.0251) time: 3.2321 data: 0.0027 max mem: 19788 +Epoch: [24] [ 230/2138] eta: 1:41:20 lr: 2.1785905151138645e-05 loss: 0.0200 (0.0251) time: 3.1983 data: 0.0027 max mem: 19788 +Epoch: [24] [ 240/2138] eta: 1:40:45 lr: 2.178013430521193e-05 loss: 0.0259 (0.0252) time: 3.1746 data: 0.0025 max mem: 19788 +Epoch: [24] [ 250/2138] eta: 1:40:05 lr: 2.177436328938704e-05 loss: 0.0242 (0.0252) time: 3.1148 data: 0.0027 max mem: 19788 +Epoch: [24] [ 260/2138] eta: 1:39:25 lr: 2.1768592103608957e-05 loss: 0.0232 (0.0251) time: 3.0706 data: 0.0026 max mem: 19788 +Epoch: [24] [ 270/2138] eta: 1:38:43 lr: 2.176282074782259e-05 loss: 0.0236 (0.0251) time: 3.0464 data: 0.0027 max mem: 19788 +Epoch: [24] [ 280/2138] eta: 1:38:09 lr: 2.1757049221972854e-05 loss: 0.0246 (0.0251) time: 3.0840 data: 0.0027 max mem: 19788 +Epoch: [24] [ 290/2138] eta: 1:37:42 lr: 2.175127752600459e-05 loss: 0.0247 (0.0251) time: 3.1892 data: 0.0026 max mem: 19788 +Epoch: [24] [ 300/2138] eta: 1:37:24 lr: 2.174550565986264e-05 loss: 0.0249 (0.0253) time: 3.3199 data: 0.0027 max mem: 19788 +Epoch: [24] [ 310/2138] eta: 1:37:18 lr: 2.1739733623491786e-05 loss: 0.0244 (0.0252) time: 3.5095 data: 0.0027 max mem: 19788 +Epoch: [24] [ 320/2138] eta: 1:37:02 lr: 2.1733961416836794e-05 loss: 0.0197 (0.0251) time: 3.5455 data: 0.0026 max mem: 19788 +Epoch: [24] [ 330/2138] eta: 1:36:27 lr: 2.1728189039842373e-05 loss: 0.0236 (0.0252) time: 3.3116 data: 0.0023 max mem: 19788 +Epoch: [24] [ 340/2138] eta: 1:35:46 lr: 2.172241649245323e-05 loss: 0.0239 (0.0251) time: 3.0942 data: 0.0023 max mem: 19788 +Epoch: [24] [ 350/2138] eta: 1:35:06 lr: 2.171664377461401e-05 loss: 0.0219 (0.0251) time: 3.0296 data: 0.0024 max mem: 19788 +Epoch: [24] [ 360/2138] eta: 1:34:26 lr: 2.171087088626933e-05 loss: 0.0232 (0.0251) time: 3.0279 data: 0.0023 max mem: 19788 +Epoch: [24] [ 370/2138] eta: 1:33:50 lr: 2.1705097827363787e-05 loss: 0.0233 (0.0251) time: 3.0716 data: 0.0023 max mem: 19788 +Epoch: [24] [ 380/2138] eta: 1:33:21 lr: 2.1699324597841925e-05 loss: 0.0242 (0.0250) time: 3.1748 data: 0.0023 max mem: 19788 +Epoch: [24] [ 390/2138] eta: 1:32:49 lr: 2.1693551197648268e-05 loss: 0.0220 (0.0250) time: 3.2141 data: 0.0023 max mem: 19788 +Epoch: [24] [ 400/2138] eta: 1:32:10 lr: 2.1687777626727287e-05 loss: 0.0256 (0.0250) time: 3.1027 data: 0.0023 max mem: 19788 +Epoch: [24] [ 410/2138] eta: 1:31:32 lr: 2.1682003885023447e-05 loss: 0.0249 (0.0250) time: 3.0294 data: 0.0025 max mem: 19788 +Epoch: [24] [ 420/2138] eta: 1:30:55 lr: 2.1676229972481146e-05 loss: 0.0234 (0.0250) time: 3.0447 data: 0.0026 max mem: 19788 +Epoch: [24] [ 430/2138] eta: 1:30:18 lr: 2.1670455889044777e-05 loss: 0.0234 (0.0250) time: 3.0397 data: 0.0024 max mem: 19788 +Epoch: [24] [ 440/2138] eta: 1:29:40 lr: 2.1664681634658674e-05 loss: 0.0240 (0.0250) time: 3.0284 data: 0.0024 max mem: 19788 +Epoch: [24] [ 450/2138] eta: 1:29:03 lr: 2.1658907209267156e-05 loss: 0.0248 (0.0251) time: 3.0245 data: 0.0024 max mem: 19788 +Epoch: [24] [ 460/2138] eta: 1:28:35 lr: 2.1653132612814492e-05 loss: 0.0247 (0.0251) time: 3.1474 data: 0.0024 max mem: 19788 +Epoch: [24] [ 470/2138] eta: 1:28:00 lr: 2.164735784524493e-05 loss: 0.0233 (0.0251) time: 3.1592 data: 0.0023 max mem: 19788 +Epoch: [24] [ 480/2138] eta: 1:27:26 lr: 2.1641582906502667e-05 loss: 0.0265 (0.0252) time: 3.0866 data: 0.0022 max mem: 19788 +Epoch: [24] [ 490/2138] eta: 1:26:50 lr: 2.1635807796531884e-05 loss: 0.0260 (0.0251) time: 3.0736 data: 0.0023 max mem: 19788 +Epoch: [24] [ 500/2138] eta: 1:26:16 lr: 2.163003251527671e-05 loss: 0.0224 (0.0251) time: 3.0540 data: 0.0024 max mem: 19788 +Epoch: [24] [ 510/2138] eta: 1:25:38 lr: 2.1624257062681256e-05 loss: 0.0207 (0.0251) time: 3.0307 data: 0.0023 max mem: 19788 +Epoch: [24] [ 520/2138] eta: 1:25:03 lr: 2.1618481438689576e-05 loss: 0.0221 (0.0251) time: 2.9995 data: 0.0024 max mem: 19788 +Epoch: [24] [ 530/2138] eta: 1:24:26 lr: 2.161270564324571e-05 loss: 0.0228 (0.0251) time: 2.9972 data: 0.0026 max mem: 19788 +Epoch: [24] [ 540/2138] eta: 1:23:51 lr: 2.1606929676293657e-05 loss: 0.0228 (0.0251) time: 3.0140 data: 0.0024 max mem: 19788 +Epoch: [24] [ 550/2138] eta: 1:23:23 lr: 2.160115353777738e-05 loss: 0.0236 (0.0251) time: 3.1593 data: 0.0023 max mem: 19788 +Epoch: [24] [ 560/2138] eta: 1:22:50 lr: 2.15953772276408e-05 loss: 0.0240 (0.0251) time: 3.1845 data: 0.0023 max mem: 19788 +Epoch: [24] [ 570/2138] eta: 1:22:14 lr: 2.1589600745827815e-05 loss: 0.0249 (0.0251) time: 3.0381 data: 0.0023 max mem: 19788 +Epoch: [24] [ 580/2138] eta: 1:21:41 lr: 2.1583824092282275e-05 loss: 0.0246 (0.0252) time: 3.0369 data: 0.0024 max mem: 19788 +Epoch: [24] [ 590/2138] eta: 1:21:06 lr: 2.1578047266948018e-05 loss: 0.0246 (0.0252) time: 3.0587 data: 0.0024 max mem: 19788 +Epoch: [24] [ 600/2138] eta: 1:20:31 lr: 2.157227026976881e-05 loss: 0.0254 (0.0252) time: 2.9966 data: 0.0022 max mem: 19788 +Epoch: [24] [ 610/2138] eta: 1:19:56 lr: 2.1566493100688424e-05 loss: 0.0262 (0.0252) time: 2.9959 data: 0.0021 max mem: 19788 +Epoch: [24] [ 620/2138] eta: 1:19:23 lr: 2.156071575965056e-05 loss: 0.0264 (0.0252) time: 3.0432 data: 0.0022 max mem: 19788 +Epoch: [24] [ 630/2138] eta: 1:18:55 lr: 2.155493824659891e-05 loss: 0.0243 (0.0252) time: 3.1761 data: 0.0024 max mem: 19788 +Epoch: [24] [ 640/2138] eta: 1:18:20 lr: 2.1549160561477115e-05 loss: 0.0221 (0.0253) time: 3.1321 data: 0.0024 max mem: 19788 +Epoch: [24] [ 650/2138] eta: 1:17:47 lr: 2.1543382704228795e-05 loss: 0.0238 (0.0252) time: 3.0349 data: 0.0024 max mem: 19788 +Epoch: [24] [ 660/2138] eta: 1:17:12 lr: 2.1537604674797518e-05 loss: 0.0237 (0.0252) time: 3.0283 data: 0.0025 max mem: 19788 +Epoch: [24] [ 670/2138] eta: 1:16:38 lr: 2.153182647312682e-05 loss: 0.0227 (0.0252) time: 2.9929 data: 0.0024 max mem: 19788 +Epoch: [24] [ 680/2138] eta: 1:16:04 lr: 2.152604809916022e-05 loss: 0.0204 (0.0252) time: 3.0111 data: 0.0023 max mem: 19788 +Epoch: [24] [ 690/2138] eta: 1:15:30 lr: 2.1520269552841172e-05 loss: 0.0212 (0.0252) time: 2.9940 data: 0.0024 max mem: 19788 +Epoch: [24] [ 700/2138] eta: 1:14:57 lr: 2.1514490834113128e-05 loss: 0.0239 (0.0251) time: 3.0061 data: 0.0024 max mem: 19788 +Epoch: [24] [ 710/2138] eta: 1:14:24 lr: 2.1508711942919475e-05 loss: 0.0236 (0.0251) time: 3.0412 data: 0.0023 max mem: 19788 +Epoch: [24] [ 720/2138] eta: 1:13:51 lr: 2.1502932879203582e-05 loss: 0.0217 (0.0251) time: 3.0592 data: 0.0024 max mem: 19788 +Epoch: [24] [ 730/2138] eta: 1:13:21 lr: 2.149715364290877e-05 loss: 0.0216 (0.0251) time: 3.1116 data: 0.0024 max mem: 19788 +Epoch: [24] [ 740/2138] eta: 1:12:47 lr: 2.149137423397834e-05 loss: 0.0257 (0.0251) time: 3.0850 data: 0.0023 max mem: 19788 +Epoch: [24] [ 750/2138] eta: 1:12:14 lr: 2.1485594652355543e-05 loss: 0.0257 (0.0251) time: 2.9982 data: 0.0023 max mem: 19788 +Epoch: [24] [ 760/2138] eta: 1:11:43 lr: 2.1479814897983608e-05 loss: 0.0247 (0.0251) time: 3.0726 data: 0.0023 max mem: 19788 +Epoch: [24] [ 770/2138] eta: 1:11:09 lr: 2.147403497080571e-05 loss: 0.0231 (0.0251) time: 3.0743 data: 0.0022 max mem: 19788 +Epoch: [24] [ 780/2138] eta: 1:10:36 lr: 2.1468254870765004e-05 loss: 0.0205 (0.0251) time: 2.9870 data: 0.0022 max mem: 19788 +Epoch: [24] [ 790/2138] eta: 1:10:03 lr: 2.1462474597804608e-05 loss: 0.0218 (0.0250) time: 2.9923 data: 0.0022 max mem: 19788 +Epoch: [24] [ 800/2138] eta: 1:09:32 lr: 2.1456694151867598e-05 loss: 0.0218 (0.0251) time: 3.0710 data: 0.0023 max mem: 19788 +Epoch: [24] [ 810/2138] eta: 1:09:01 lr: 2.145091353289701e-05 loss: 0.0242 (0.0251) time: 3.1295 data: 0.0024 max mem: 19788 +Epoch: [24] [ 820/2138] eta: 1:08:30 lr: 2.1445132740835863e-05 loss: 0.0242 (0.0251) time: 3.1310 data: 0.0025 max mem: 19788 +Epoch: [24] [ 830/2138] eta: 1:07:58 lr: 2.1439351775627117e-05 loss: 0.0229 (0.0251) time: 3.1061 data: 0.0025 max mem: 19788 +Epoch: [24] [ 840/2138] eta: 1:07:25 lr: 2.1433570637213717e-05 loss: 0.0202 (0.0250) time: 3.0457 data: 0.0030 max mem: 19788 +Epoch: [24] [ 850/2138] eta: 1:06:52 lr: 2.142778932553855e-05 loss: 0.0216 (0.0250) time: 3.0167 data: 0.0031 max mem: 19788 +Epoch: [24] [ 860/2138] eta: 1:06:20 lr: 2.1422007840544497e-05 loss: 0.0219 (0.0250) time: 3.0292 data: 0.0025 max mem: 19788 +Epoch: [24] [ 870/2138] eta: 1:05:49 lr: 2.141622618217437e-05 loss: 0.0219 (0.0250) time: 3.0644 data: 0.0022 max mem: 19788 +Epoch: [24] [ 880/2138] eta: 1:05:18 lr: 2.1410444350370965e-05 loss: 0.0205 (0.0250) time: 3.1181 data: 0.0022 max mem: 19788 +Epoch: [24] [ 890/2138] eta: 1:04:48 lr: 2.1404662345077033e-05 loss: 0.0213 (0.0249) time: 3.1643 data: 0.0025 max mem: 19788 +Epoch: [24] [ 900/2138] eta: 1:04:18 lr: 2.1398880166235306e-05 loss: 0.0223 (0.0249) time: 3.1913 data: 0.0028 max mem: 19788 +Epoch: [24] [ 910/2138] eta: 1:03:50 lr: 2.139309781378845e-05 loss: 0.0209 (0.0249) time: 3.2764 data: 0.0028 max mem: 19788 +Epoch: [24] [ 920/2138] eta: 1:03:18 lr: 2.138731528767913e-05 loss: 0.0209 (0.0249) time: 3.2166 data: 0.0029 max mem: 19788 +Epoch: [24] [ 930/2138] eta: 1:02:47 lr: 2.138153258784994e-05 loss: 0.0248 (0.0249) time: 3.0896 data: 0.0026 max mem: 19788 +Epoch: [24] [ 940/2138] eta: 1:02:15 lr: 2.137574971424347e-05 loss: 0.0259 (0.0249) time: 3.1056 data: 0.0027 max mem: 19788 +Epoch: [24] [ 950/2138] eta: 1:01:45 lr: 2.136996666680225e-05 loss: 0.0243 (0.0249) time: 3.1303 data: 0.0030 max mem: 19788 +Epoch: [24] [ 960/2138] eta: 1:01:20 lr: 2.1364183445468774e-05 loss: 0.0252 (0.0250) time: 3.3942 data: 0.0025 max mem: 19788 +Epoch: [24] [ 970/2138] eta: 1:00:55 lr: 2.1358400050185522e-05 loss: 0.0256 (0.0249) time: 3.6439 data: 0.0024 max mem: 19788 +Epoch: [24] [ 980/2138] eta: 1:00:29 lr: 2.1352616480894912e-05 loss: 0.0208 (0.0249) time: 3.6116 data: 0.0024 max mem: 19788 +Epoch: [24] [ 990/2138] eta: 1:00:02 lr: 2.134683273753935e-05 loss: 0.0208 (0.0249) time: 3.5430 data: 0.0024 max mem: 19788 +Epoch: [24] [1000/2138] eta: 0:59:31 lr: 2.134104882006118e-05 loss: 0.0233 (0.0249) time: 3.3475 data: 0.0025 max mem: 19788 +Epoch: [24] [1010/2138] eta: 0:59:02 lr: 2.1335264728402727e-05 loss: 0.0233 (0.0249) time: 3.2925 data: 0.0024 max mem: 19788 +Epoch: [24] [1020/2138] eta: 0:58:34 lr: 2.1329480462506276e-05 loss: 0.0223 (0.0249) time: 3.4156 data: 0.0023 max mem: 19788 +Epoch: [24] [1030/2138] eta: 0:58:03 lr: 2.1323696022314073e-05 loss: 0.0217 (0.0249) time: 3.3199 data: 0.0024 max mem: 19788 +Epoch: [24] [1040/2138] eta: 0:57:33 lr: 2.1317911407768327e-05 loss: 0.0248 (0.0250) time: 3.2384 data: 0.0026 max mem: 19788 +Epoch: [24] [1050/2138] eta: 0:57:04 lr: 2.1312126618811216e-05 loss: 0.0254 (0.0250) time: 3.2945 data: 0.0028 max mem: 19788 +Epoch: [24] [1060/2138] eta: 0:56:32 lr: 2.1306341655384867e-05 loss: 0.0251 (0.0251) time: 3.2399 data: 0.0026 max mem: 19788 +Epoch: [24] [1070/2138] eta: 0:56:01 lr: 2.1300556517431398e-05 loss: 0.0233 (0.0250) time: 3.1779 data: 0.0024 max mem: 19788 +Epoch: [24] [1080/2138] eta: 0:55:33 lr: 2.129477120489285e-05 loss: 0.0232 (0.0250) time: 3.3295 data: 0.0025 max mem: 19788 +Epoch: [24] [1090/2138] eta: 0:55:02 lr: 2.1288985717711275e-05 loss: 0.0252 (0.0250) time: 3.3224 data: 0.0025 max mem: 19788 +Epoch: [24] [1100/2138] eta: 0:54:32 lr: 2.1283200055828646e-05 loss: 0.0264 (0.0251) time: 3.2714 data: 0.0025 max mem: 19788 +Epoch: [24] [1110/2138] eta: 0:54:01 lr: 2.1277414219186925e-05 loss: 0.0237 (0.0250) time: 3.2907 data: 0.0028 max mem: 19788 +Epoch: [24] [1120/2138] eta: 0:53:30 lr: 2.127162820772802e-05 loss: 0.0231 (0.0251) time: 3.1842 data: 0.0030 max mem: 19788 +Epoch: [24] [1130/2138] eta: 0:53:00 lr: 2.1265842021393823e-05 loss: 0.0234 (0.0250) time: 3.2421 data: 0.0026 max mem: 19788 +Epoch: [24] [1140/2138] eta: 0:52:29 lr: 2.1260055660126166e-05 loss: 0.0234 (0.0250) time: 3.2637 data: 0.0022 max mem: 19788 +Epoch: [24] [1150/2138] eta: 0:52:01 lr: 2.1254269123866865e-05 loss: 0.0214 (0.0250) time: 3.3815 data: 0.0023 max mem: 19788 +Epoch: [24] [1160/2138] eta: 0:51:32 lr: 2.124848241255768e-05 loss: 0.0226 (0.0251) time: 3.5320 data: 0.0026 max mem: 19788 +Epoch: [24] [1170/2138] eta: 0:51:02 lr: 2.124269552614035e-05 loss: 0.0229 (0.0251) time: 3.4104 data: 0.0027 max mem: 19788 +Epoch: [24] [1180/2138] eta: 0:50:31 lr: 2.1236908464556567e-05 loss: 0.0228 (0.0250) time: 3.2750 data: 0.0029 max mem: 19788 +Epoch: [24] [1190/2138] eta: 0:49:59 lr: 2.123112122774799e-05 loss: 0.0226 (0.0250) time: 3.2223 data: 0.0030 max mem: 19788 +Epoch: [24] [1200/2138] eta: 0:49:29 lr: 2.1225333815656236e-05 loss: 0.0208 (0.0250) time: 3.2638 data: 0.0030 max mem: 19788 +Epoch: [24] [1210/2138] eta: 0:48:59 lr: 2.12195462282229e-05 loss: 0.0225 (0.0250) time: 3.3899 data: 0.0030 max mem: 19788 +Epoch: [24] [1220/2138] eta: 0:48:28 lr: 2.1213758465389512e-05 loss: 0.0259 (0.0250) time: 3.3498 data: 0.0027 max mem: 19788 +Epoch: [24] [1230/2138] eta: 0:47:58 lr: 2.1207970527097594e-05 loss: 0.0232 (0.0250) time: 3.2740 data: 0.0026 max mem: 19788 +Epoch: [24] [1240/2138] eta: 0:47:26 lr: 2.1202182413288614e-05 loss: 0.0227 (0.0250) time: 3.2455 data: 0.0030 max mem: 19788 +Epoch: [24] [1250/2138] eta: 0:46:56 lr: 2.119639412390401e-05 loss: 0.0224 (0.0250) time: 3.3229 data: 0.0032 max mem: 19788 +Epoch: [24] [1260/2138] eta: 0:46:27 lr: 2.1190605658885175e-05 loss: 0.0218 (0.0250) time: 3.4800 data: 0.0029 max mem: 19788 +Epoch: [24] [1270/2138] eta: 0:45:56 lr: 2.1184817018173465e-05 loss: 0.0220 (0.0250) time: 3.3908 data: 0.0028 max mem: 19788 +Epoch: [24] [1280/2138] eta: 0:45:25 lr: 2.117902820171022e-05 loss: 0.0222 (0.0250) time: 3.2991 data: 0.0029 max mem: 19788 +Epoch: [24] [1290/2138] eta: 0:44:54 lr: 2.11732392094367e-05 loss: 0.0236 (0.0250) time: 3.2925 data: 0.0028 max mem: 19788 +Epoch: [24] [1300/2138] eta: 0:44:22 lr: 2.1167450041294178e-05 loss: 0.0258 (0.0249) time: 3.2371 data: 0.0030 max mem: 19788 +Epoch: [24] [1310/2138] eta: 0:43:51 lr: 2.116166069722385e-05 loss: 0.0213 (0.0249) time: 3.2375 data: 0.0030 max mem: 19788 +Epoch: [24] [1320/2138] eta: 0:43:23 lr: 2.1155871177166894e-05 loss: 0.0216 (0.0249) time: 3.4856 data: 0.0026 max mem: 19788 +Epoch: [24] [1330/2138] eta: 0:42:53 lr: 2.115008148106444e-05 loss: 0.0227 (0.0249) time: 3.6618 data: 0.0026 max mem: 19788 +Epoch: [24] [1340/2138] eta: 0:42:23 lr: 2.1144291608857595e-05 loss: 0.0245 (0.0249) time: 3.5467 data: 0.0027 max mem: 19788 +Epoch: [24] [1350/2138] eta: 0:41:53 lr: 2.1138501560487407e-05 loss: 0.0272 (0.0250) time: 3.4268 data: 0.0028 max mem: 19788 +Epoch: [24] [1360/2138] eta: 0:41:21 lr: 2.113271133589491e-05 loss: 0.0252 (0.0249) time: 3.3145 data: 0.0030 max mem: 19788 +Epoch: [24] [1370/2138] eta: 0:40:49 lr: 2.1126920935021077e-05 loss: 0.0252 (0.0250) time: 3.2278 data: 0.0027 max mem: 19788 +Epoch: [24] [1380/2138] eta: 0:40:17 lr: 2.112113035780687e-05 loss: 0.0250 (0.0250) time: 3.1959 data: 0.0027 max mem: 19788 +Epoch: [24] [1390/2138] eta: 0:39:45 lr: 2.1115339604193183e-05 loss: 0.0222 (0.0249) time: 3.1897 data: 0.0029 max mem: 19788 +Epoch: [24] [1400/2138] eta: 0:39:14 lr: 2.1109548674120898e-05 loss: 0.0217 (0.0249) time: 3.2153 data: 0.0026 max mem: 19788 +Epoch: [24] [1410/2138] eta: 0:38:42 lr: 2.110375756753084e-05 loss: 0.0208 (0.0249) time: 3.2266 data: 0.0025 max mem: 19788 +Epoch: [24] [1420/2138] eta: 0:38:11 lr: 2.1097966284363815e-05 loss: 0.0240 (0.0249) time: 3.2909 data: 0.0025 max mem: 19788 +Epoch: [24] [1430/2138] eta: 0:37:40 lr: 2.109217482456057e-05 loss: 0.0239 (0.0249) time: 3.3645 data: 0.0025 max mem: 19788 +Epoch: [24] [1440/2138] eta: 0:37:09 lr: 2.108638318806184e-05 loss: 0.0238 (0.0249) time: 3.3549 data: 0.0029 max mem: 19788 +Epoch: [24] [1450/2138] eta: 0:36:39 lr: 2.1080591374808283e-05 loss: 0.0243 (0.0249) time: 3.4861 data: 0.0029 max mem: 19788 +Epoch: [24] [1460/2138] eta: 0:36:08 lr: 2.1074799384740567e-05 loss: 0.0250 (0.0249) time: 3.5691 data: 0.0025 max mem: 19788 +Epoch: [24] [1470/2138] eta: 0:35:38 lr: 2.106900721779928e-05 loss: 0.0221 (0.0249) time: 3.5097 data: 0.0024 max mem: 19788 +Epoch: [24] [1480/2138] eta: 0:35:07 lr: 2.1063214873925003e-05 loss: 0.0206 (0.0249) time: 3.4605 data: 0.0026 max mem: 19788 +Epoch: [24] [1490/2138] eta: 0:34:35 lr: 2.105742235305825e-05 loss: 0.0206 (0.0249) time: 3.3541 data: 0.0031 max mem: 19788 +Epoch: [24] [1500/2138] eta: 0:34:03 lr: 2.105162965513953e-05 loss: 0.0251 (0.0249) time: 3.2464 data: 0.0030 max mem: 19788 +Epoch: [24] [1510/2138] eta: 0:33:31 lr: 2.1045836780109284e-05 loss: 0.0238 (0.0249) time: 3.2253 data: 0.0026 max mem: 19788 +Epoch: [24] [1520/2138] eta: 0:32:59 lr: 2.104004372790793e-05 loss: 0.0225 (0.0249) time: 3.2331 data: 0.0026 max mem: 19788 +Epoch: [24] [1530/2138] eta: 0:32:27 lr: 2.1034250498475843e-05 loss: 0.0230 (0.0249) time: 3.2359 data: 0.0026 max mem: 19788 +Epoch: [24] [1540/2138] eta: 0:31:55 lr: 2.1028457091753366e-05 loss: 0.0241 (0.0249) time: 3.2470 data: 0.0029 max mem: 19788 +Epoch: [24] [1550/2138] eta: 0:31:23 lr: 2.1022663507680794e-05 loss: 0.0228 (0.0249) time: 3.2193 data: 0.0032 max mem: 19788 +Epoch: [24] [1560/2138] eta: 0:30:52 lr: 2.1016869746198395e-05 loss: 0.0252 (0.0249) time: 3.3307 data: 0.0030 max mem: 19788 +Epoch: [24] [1570/2138] eta: 0:30:20 lr: 2.1011075807246384e-05 loss: 0.0237 (0.0249) time: 3.3117 data: 0.0032 max mem: 19788 +Epoch: [24] [1580/2138] eta: 0:29:48 lr: 2.100528169076495e-05 loss: 0.0220 (0.0249) time: 3.1772 data: 0.0031 max mem: 19788 +Epoch: [24] [1590/2138] eta: 0:29:16 lr: 2.099948739669424e-05 loss: 0.0230 (0.0249) time: 3.2518 data: 0.0027 max mem: 19788 +Epoch: [24] [1600/2138] eta: 0:28:44 lr: 2.0993692924974354e-05 loss: 0.0241 (0.0249) time: 3.2626 data: 0.0027 max mem: 19788 +Epoch: [24] [1610/2138] eta: 0:28:12 lr: 2.098789827554537e-05 loss: 0.0282 (0.0249) time: 3.1880 data: 0.0024 max mem: 19788 +Epoch: [24] [1620/2138] eta: 0:27:41 lr: 2.098210344834731e-05 loss: 0.0206 (0.0249) time: 3.3460 data: 0.0023 max mem: 19788 +Epoch: [24] [1630/2138] eta: 0:27:09 lr: 2.097630844332018e-05 loss: 0.0219 (0.0249) time: 3.3968 data: 0.0024 max mem: 19788 +Epoch: [24] [1640/2138] eta: 0:26:37 lr: 2.0970513260403916e-05 loss: 0.0240 (0.0249) time: 3.2768 data: 0.0028 max mem: 19788 +Epoch: [24] [1650/2138] eta: 0:26:05 lr: 2.0964717899538445e-05 loss: 0.0250 (0.0249) time: 3.2669 data: 0.0030 max mem: 19788 +Epoch: [24] [1660/2138] eta: 0:25:34 lr: 2.0958922360663634e-05 loss: 0.0250 (0.0249) time: 3.3758 data: 0.0026 max mem: 19788 +Epoch: [24] [1670/2138] eta: 0:25:02 lr: 2.0953126643719326e-05 loss: 0.0223 (0.0249) time: 3.3240 data: 0.0025 max mem: 19788 +Epoch: [24] [1680/2138] eta: 0:24:30 lr: 2.094733074864531e-05 loss: 0.0218 (0.0249) time: 3.1806 data: 0.0027 max mem: 19788 +Epoch: [24] [1690/2138] eta: 0:23:58 lr: 2.094153467538136e-05 loss: 0.0245 (0.0249) time: 3.1867 data: 0.0026 max mem: 19788 +Epoch: [24] [1700/2138] eta: 0:23:25 lr: 2.0935738423867183e-05 loss: 0.0230 (0.0248) time: 3.1929 data: 0.0027 max mem: 19788 +Epoch: [24] [1710/2138] eta: 0:22:53 lr: 2.0929941994042467e-05 loss: 0.0211 (0.0248) time: 3.2405 data: 0.0028 max mem: 19788 +Epoch: [24] [1720/2138] eta: 0:22:22 lr: 2.0924145385846847e-05 loss: 0.0235 (0.0249) time: 3.4426 data: 0.0026 max mem: 19788 +Epoch: [24] [1730/2138] eta: 0:21:51 lr: 2.091834859921994e-05 loss: 0.0240 (0.0249) time: 3.5174 data: 0.0024 max mem: 19788 +Epoch: [24] [1740/2138] eta: 0:21:20 lr: 2.091255163410129e-05 loss: 0.0235 (0.0249) time: 3.5228 data: 0.0026 max mem: 19788 +Epoch: [24] [1750/2138] eta: 0:20:48 lr: 2.0906754490430445e-05 loss: 0.0244 (0.0249) time: 3.5356 data: 0.0026 max mem: 19788 +Epoch: [24] [1760/2138] eta: 0:20:16 lr: 2.090095716814687e-05 loss: 0.0238 (0.0249) time: 3.4375 data: 0.0027 max mem: 19788 +Epoch: [24] [1770/2138] eta: 0:19:44 lr: 2.0895159667190028e-05 loss: 0.0215 (0.0248) time: 3.3146 data: 0.0029 max mem: 19788 +Epoch: [24] [1780/2138] eta: 0:19:12 lr: 2.0889361987499315e-05 loss: 0.0203 (0.0248) time: 3.3230 data: 0.0029 max mem: 19788 +Epoch: [24] [1790/2138] eta: 0:18:40 lr: 2.0883564129014108e-05 loss: 0.0200 (0.0248) time: 3.3158 data: 0.0030 max mem: 19788 +Epoch: [24] [1800/2138] eta: 0:18:08 lr: 2.0877766091673724e-05 loss: 0.0256 (0.0248) time: 3.2658 data: 0.0031 max mem: 19788 +Epoch: [24] [1810/2138] eta: 0:17:36 lr: 2.087196787541747e-05 loss: 0.0232 (0.0248) time: 3.4687 data: 0.0029 max mem: 19788 +Epoch: [24] [1820/2138] eta: 0:17:04 lr: 2.0866169480184583e-05 loss: 0.0217 (0.0248) time: 3.4021 data: 0.0028 max mem: 19788 +Epoch: [24] [1830/2138] eta: 0:16:32 lr: 2.0860370905914282e-05 loss: 0.0208 (0.0248) time: 3.2497 data: 0.0032 max mem: 19788 +Epoch: [24] [1840/2138] eta: 0:16:00 lr: 2.085457215254573e-05 loss: 0.0245 (0.0248) time: 3.3456 data: 0.0031 max mem: 19788 +Epoch: [24] [1850/2138] eta: 0:15:28 lr: 2.084877322001807e-05 loss: 0.0264 (0.0248) time: 3.3521 data: 0.0028 max mem: 19788 +Epoch: [24] [1860/2138] eta: 0:14:56 lr: 2.084297410827038e-05 loss: 0.0241 (0.0248) time: 3.2449 data: 0.0031 max mem: 19788 +Epoch: [24] [1870/2138] eta: 0:14:24 lr: 2.083717481724173e-05 loss: 0.0237 (0.0248) time: 3.2157 data: 0.0031 max mem: 19788 +Epoch: [24] [1880/2138] eta: 0:13:51 lr: 2.0831375346871122e-05 loss: 0.0206 (0.0248) time: 3.1991 data: 0.0027 max mem: 19788 +Epoch: [24] [1890/2138] eta: 0:13:19 lr: 2.0825575697097532e-05 loss: 0.0202 (0.0248) time: 3.1750 data: 0.0026 max mem: 19788 +Epoch: [24] [1900/2138] eta: 0:12:47 lr: 2.0819775867859897e-05 loss: 0.0223 (0.0248) time: 3.1975 data: 0.0028 max mem: 19788 +Epoch: [24] [1910/2138] eta: 0:12:14 lr: 2.0813975859097108e-05 loss: 0.0219 (0.0248) time: 3.2083 data: 0.0027 max mem: 19788 +Epoch: [24] [1920/2138] eta: 0:11:42 lr: 2.0808175670748023e-05 loss: 0.0212 (0.0248) time: 3.2439 data: 0.0029 max mem: 19788 +Epoch: [24] [1930/2138] eta: 0:11:10 lr: 2.080237530275145e-05 loss: 0.0229 (0.0248) time: 3.3303 data: 0.0027 max mem: 19788 +Epoch: [24] [1940/2138] eta: 0:10:38 lr: 2.0796574755046178e-05 loss: 0.0229 (0.0248) time: 3.3629 data: 0.0025 max mem: 19788 +Epoch: [24] [1950/2138] eta: 0:10:06 lr: 2.0790774027570926e-05 loss: 0.0241 (0.0248) time: 3.2769 data: 0.0027 max mem: 19788 +Epoch: [24] [1960/2138] eta: 0:09:34 lr: 2.0784973120264402e-05 loss: 0.0232 (0.0248) time: 3.2203 data: 0.0027 max mem: 19788 +Epoch: [24] [1970/2138] eta: 0:09:02 lr: 2.0779172033065255e-05 loss: 0.0204 (0.0248) time: 3.3546 data: 0.0027 max mem: 19788 +Epoch: [24] [1980/2138] eta: 0:08:30 lr: 2.0773370765912105e-05 loss: 0.0221 (0.0248) time: 3.5113 data: 0.0026 max mem: 19788 +Epoch: [24] [1990/2138] eta: 0:07:57 lr: 2.0767569318743522e-05 loss: 0.0227 (0.0248) time: 3.5036 data: 0.0024 max mem: 19788 +Epoch: [24] [2000/2138] eta: 0:07:25 lr: 2.076176769149805e-05 loss: 0.0209 (0.0248) time: 3.4118 data: 0.0024 max mem: 19788 +Epoch: [24] [2010/2138] eta: 0:06:53 lr: 2.0755965884114173e-05 loss: 0.0246 (0.0248) time: 3.4569 data: 0.0024 max mem: 19788 +Epoch: [24] [2020/2138] eta: 0:06:21 lr: 2.0750163896530356e-05 loss: 0.0246 (0.0248) time: 3.4752 data: 0.0026 max mem: 19788 +Epoch: [24] [2030/2138] eta: 0:05:49 lr: 2.0744361728685007e-05 loss: 0.0246 (0.0248) time: 3.3661 data: 0.0028 max mem: 19788 +Epoch: [24] [2040/2138] eta: 0:05:16 lr: 2.0738559380516513e-05 loss: 0.0248 (0.0248) time: 3.2507 data: 0.0026 max mem: 19788 +Epoch: [24] [2050/2138] eta: 0:04:44 lr: 2.073275685196319e-05 loss: 0.0230 (0.0248) time: 3.1715 data: 0.0022 max mem: 19788 +Epoch: [24] [2060/2138] eta: 0:04:12 lr: 2.072695414296335e-05 loss: 0.0230 (0.0248) time: 3.1717 data: 0.0022 max mem: 19788 +Epoch: [24] [2070/2138] eta: 0:03:39 lr: 2.0721151253455233e-05 loss: 0.0215 (0.0248) time: 3.2375 data: 0.0023 max mem: 19788 +Epoch: [24] [2080/2138] eta: 0:03:07 lr: 2.071534818337707e-05 loss: 0.0207 (0.0248) time: 3.2289 data: 0.0023 max mem: 19788 +Epoch: [24] [2090/2138] eta: 0:02:35 lr: 2.0709544932667015e-05 loss: 0.0227 (0.0248) time: 3.1626 data: 0.0026 max mem: 19788 +Epoch: [24] [2100/2138] eta: 0:02:02 lr: 2.0703741501263217e-05 loss: 0.0228 (0.0248) time: 3.1893 data: 0.0027 max mem: 19788 +Epoch: [24] [2110/2138] eta: 0:01:30 lr: 2.0697937889103757e-05 loss: 0.0270 (0.0248) time: 3.1888 data: 0.0025 max mem: 19788 +Epoch: [24] [2120/2138] eta: 0:00:58 lr: 2.06921340961267e-05 loss: 0.0275 (0.0248) time: 3.1669 data: 0.0026 max mem: 19788 +Epoch: [24] [2130/2138] eta: 0:00:25 lr: 2.0686330122270044e-05 loss: 0.0275 (0.0248) time: 3.1950 data: 0.0025 max mem: 19788 +Epoch: [24] Total time: 1:55:07 +Test: [ 0/21770] eta: 16:57:00 time: 2.8030 data: 2.7216 max mem: 19788 +Test: [ 100/21770] eta: 0:29:27 time: 0.0553 data: 0.0020 max mem: 19788 +Test: [ 200/21770] eta: 0:23:38 time: 0.0453 data: 0.0021 max mem: 19788 +Test: [ 300/21770] eta: 0:21:42 time: 0.0459 data: 0.0015 max mem: 19788 +Test: [ 400/21770] eta: 0:20:52 time: 0.0501 data: 0.0017 max mem: 19788 +Test: [ 500/21770] eta: 0:19:52 time: 0.0490 data: 0.0018 max mem: 19788 +Test: [ 600/21770] eta: 0:19:22 time: 0.0556 data: 0.0019 max mem: 19788 +Test: [ 700/21770] eta: 0:18:56 time: 0.0463 data: 0.0018 max mem: 19788 +Test: [ 800/21770] eta: 0:18:32 time: 0.0552 data: 0.0019 max mem: 19788 +Test: [ 900/21770] eta: 0:18:20 time: 0.0545 data: 0.0019 max mem: 19788 +Test: [ 1000/21770] eta: 0:18:00 time: 0.0439 data: 0.0015 max mem: 19788 +Test: [ 1100/21770] eta: 0:17:41 time: 0.0450 data: 0.0016 max mem: 19788 +Test: [ 1200/21770] eta: 0:17:31 time: 0.0467 data: 0.0016 max mem: 19788 +Test: [ 1300/21770] eta: 0:17:20 time: 0.0435 data: 0.0016 max mem: 19788 +Test: [ 1400/21770] eta: 0:17:14 time: 0.0564 data: 0.0019 max mem: 19788 +Test: [ 1500/21770] eta: 0:17:03 time: 0.0480 data: 0.0017 max mem: 19788 +Test: [ 1600/21770] eta: 0:16:58 time: 0.0520 data: 0.0018 max mem: 19788 +Test: [ 1700/21770] eta: 0:16:48 time: 0.0435 data: 0.0016 max mem: 19788 +Test: [ 1800/21770] eta: 0:16:39 time: 0.0445 data: 0.0016 max mem: 19788 +Test: [ 1900/21770] eta: 0:16:35 time: 0.0548 data: 0.0018 max mem: 19788 +Test: [ 2000/21770] eta: 0:16:32 time: 0.0480 data: 0.0018 max mem: 19788 +Test: [ 2100/21770] eta: 0:16:24 time: 0.0487 data: 0.0018 max mem: 19788 +Test: [ 2200/21770] eta: 0:16:15 time: 0.0446 data: 0.0016 max mem: 19788 +Test: [ 2300/21770] eta: 0:16:11 time: 0.0484 data: 0.0017 max mem: 19788 +Test: [ 2400/21770] eta: 0:16:03 time: 0.0460 data: 0.0014 max mem: 19788 +Test: [ 2500/21770] eta: 0:15:58 time: 0.0456 data: 0.0015 max mem: 19788 +Test: [ 2600/21770] eta: 0:15:51 time: 0.0490 data: 0.0016 max mem: 19788 +Test: [ 2700/21770] eta: 0:15:44 time: 0.0476 data: 0.0015 max mem: 19788 +Test: [ 2800/21770] eta: 0:15:42 time: 0.0548 data: 0.0019 max mem: 19788 +Test: [ 2900/21770] eta: 0:15:40 time: 0.0484 data: 0.0015 max mem: 19788 +Test: [ 3000/21770] eta: 0:15:37 time: 0.0552 data: 0.0020 max mem: 19788 +Test: [ 3100/21770] eta: 0:15:35 time: 0.0535 data: 0.0018 max mem: 19788 +Test: [ 3200/21770] eta: 0:15:29 time: 0.0541 data: 0.0019 max mem: 19788 +Test: [ 3300/21770] eta: 0:15:21 time: 0.0456 data: 0.0015 max mem: 19788 +Test: [ 3400/21770] eta: 0:15:18 time: 0.0552 data: 0.0019 max mem: 19788 +Test: [ 3500/21770] eta: 0:15:15 time: 0.0552 data: 0.0019 max mem: 19788 +Test: [ 3600/21770] eta: 0:15:12 time: 0.0542 data: 0.0018 max mem: 19788 +Test: [ 3700/21770] eta: 0:15:05 time: 0.0454 data: 0.0016 max mem: 19788 +Test: [ 3800/21770] eta: 0:14:58 time: 0.0450 data: 0.0015 max mem: 19788 +Test: [ 3900/21770] eta: 0:14:52 time: 0.0547 data: 0.0018 max mem: 19788 +Test: [ 4000/21770] eta: 0:14:48 time: 0.0454 data: 0.0016 max mem: 19788 +Test: [ 4100/21770] eta: 0:14:43 time: 0.0565 data: 0.0020 max mem: 19788 +Test: [ 4200/21770] eta: 0:14:37 time: 0.0448 data: 0.0015 max mem: 19788 +Test: [ 4300/21770] eta: 0:14:30 time: 0.0454 data: 0.0015 max mem: 19788 +Test: [ 4400/21770] eta: 0:14:27 time: 0.0533 data: 0.0017 max mem: 19788 +Test: [ 4500/21770] eta: 0:14:23 time: 0.0548 data: 0.0019 max mem: 19788 +Test: [ 4600/21770] eta: 0:14:18 time: 0.0494 data: 0.0017 max mem: 19788 +Test: [ 4700/21770] eta: 0:14:14 time: 0.0538 data: 0.0019 max mem: 19788 +Test: [ 4800/21770] eta: 0:14:10 time: 0.0491 data: 0.0018 max mem: 19788 +Test: [ 4900/21770] eta: 0:14:04 time: 0.0489 data: 0.0016 max mem: 19788 +Test: [ 5000/21770] eta: 0:14:00 time: 0.0489 data: 0.0018 max mem: 19788 +Test: [ 5100/21770] eta: 0:13:56 time: 0.0537 data: 0.0020 max mem: 19788 +Test: [ 5200/21770] eta: 0:13:51 time: 0.0465 data: 0.0019 max mem: 19788 +Test: [ 5300/21770] eta: 0:13:46 time: 0.0525 data: 0.0019 max mem: 19788 +Test: [ 5400/21770] eta: 0:13:40 time: 0.0515 data: 0.0018 max mem: 19788 +Test: [ 5500/21770] eta: 0:13:36 time: 0.0473 data: 0.0016 max mem: 19788 +Test: [ 5600/21770] eta: 0:13:31 time: 0.0560 data: 0.0020 max mem: 19788 +Test: [ 5700/21770] eta: 0:13:26 time: 0.0551 data: 0.0017 max mem: 19788 +Test: [ 5800/21770] eta: 0:13:23 time: 0.0551 data: 0.0020 max mem: 19788 +Test: [ 5900/21770] eta: 0:13:18 time: 0.0465 data: 0.0017 max mem: 19788 +Test: [ 6000/21770] eta: 0:13:12 time: 0.0447 data: 0.0015 max mem: 19788 +Test: [ 6100/21770] eta: 0:13:07 time: 0.0576 data: 0.0018 max mem: 19788 +Test: [ 6200/21770] eta: 0:13:03 time: 0.0545 data: 0.0019 max mem: 19788 +Test: [ 6300/21770] eta: 0:12:58 time: 0.0546 data: 0.0019 max mem: 19788 +Test: [ 6400/21770] eta: 0:12:53 time: 0.0491 data: 0.0017 max mem: 19788 +Test: [ 6500/21770] eta: 0:12:48 time: 0.0455 data: 0.0016 max mem: 19788 +Test: [ 6600/21770] eta: 0:12:42 time: 0.0450 data: 0.0015 max mem: 19788 +Test: [ 6700/21770] eta: 0:12:38 time: 0.0562 data: 0.0020 max mem: 19788 +Test: [ 6800/21770] eta: 0:12:32 time: 0.0464 data: 0.0017 max mem: 19788 +Test: [ 6900/21770] eta: 0:12:27 time: 0.0456 data: 0.0015 max mem: 19788 +Test: [ 7000/21770] eta: 0:12:21 time: 0.0448 data: 0.0017 max mem: 19788 +Test: [ 7100/21770] eta: 0:12:16 time: 0.0563 data: 0.0019 max mem: 19788 +Test: [ 7200/21770] eta: 0:12:11 time: 0.0507 data: 0.0017 max mem: 19788 +Test: [ 7300/21770] eta: 0:12:08 time: 0.0559 data: 0.0018 max mem: 19788 +Test: [ 7400/21770] eta: 0:12:02 time: 0.0482 data: 0.0017 max mem: 19788 +Test: [ 7500/21770] eta: 0:11:57 time: 0.0552 data: 0.0019 max mem: 19788 +Test: [ 7600/21770] eta: 0:11:52 time: 0.0482 data: 0.0016 max mem: 19788 +Test: [ 7700/21770] eta: 0:11:48 time: 0.0492 data: 0.0017 max mem: 19788 +Test: [ 7800/21770] eta: 0:11:43 time: 0.0572 data: 0.0021 max mem: 19788 +Test: [ 7900/21770] eta: 0:11:38 time: 0.0528 data: 0.0016 max mem: 19788 +Test: [ 8000/21770] eta: 0:11:32 time: 0.0456 data: 0.0016 max mem: 19788 +Test: [ 8100/21770] eta: 0:11:27 time: 0.0511 data: 0.0016 max mem: 19788 +Test: [ 8200/21770] eta: 0:11:21 time: 0.0471 data: 0.0016 max mem: 19788 +Test: [ 8300/21770] eta: 0:11:15 time: 0.0464 data: 0.0015 max mem: 19788 +Test: [ 8400/21770] eta: 0:11:11 time: 0.0561 data: 0.0018 max mem: 19788 +Test: [ 8500/21770] eta: 0:11:06 time: 0.0467 data: 0.0015 max mem: 19788 +Test: [ 8600/21770] eta: 0:11:00 time: 0.0450 data: 0.0015 max mem: 19788 +Test: [ 8700/21770] eta: 0:10:56 time: 0.0553 data: 0.0020 max mem: 19788 +Test: [ 8800/21770] eta: 0:10:51 time: 0.0469 data: 0.0016 max mem: 19788 +Test: [ 8900/21770] eta: 0:10:46 time: 0.0546 data: 0.0020 max mem: 19788 +Test: [ 9000/21770] eta: 0:10:42 time: 0.0477 data: 0.0015 max mem: 19788 +Test: [ 9100/21770] eta: 0:10:36 time: 0.0446 data: 0.0015 max mem: 19788 +Test: [ 9200/21770] eta: 0:10:31 time: 0.0486 data: 0.0017 max mem: 19788 +Test: [ 9300/21770] eta: 0:10:26 time: 0.0447 data: 0.0017 max mem: 19788 +Test: [ 9400/21770] eta: 0:10:20 time: 0.0450 data: 0.0014 max mem: 19788 +Test: [ 9500/21770] eta: 0:10:15 time: 0.0550 data: 0.0019 max mem: 19788 +Test: [ 9600/21770] eta: 0:10:10 time: 0.0461 data: 0.0019 max mem: 19788 +Test: [ 9700/21770] eta: 0:10:06 time: 0.0537 data: 0.0018 max mem: 19788 +Test: [ 9800/21770] eta: 0:10:01 time: 0.0552 data: 0.0020 max mem: 19788 +Test: [ 9900/21770] eta: 0:09:56 time: 0.0479 data: 0.0015 max mem: 19788 +Test: [10000/21770] eta: 0:09:51 time: 0.0513 data: 0.0017 max mem: 19788 +Test: [10100/21770] eta: 0:09:46 time: 0.0456 data: 0.0016 max mem: 19788 +Test: [10200/21770] eta: 0:09:41 time: 0.0542 data: 0.0019 max mem: 19788 +Test: [10300/21770] eta: 0:09:37 time: 0.0567 data: 0.0017 max mem: 19788 +Test: [10400/21770] eta: 0:09:32 time: 0.0567 data: 0.0018 max mem: 19788 +Test: [10500/21770] eta: 0:09:27 time: 0.0552 data: 0.0020 max mem: 19788 +Test: [10600/21770] eta: 0:09:23 time: 0.0517 data: 0.0019 max mem: 19788 +Test: [10700/21770] eta: 0:09:17 time: 0.0481 data: 0.0015 max mem: 19788 +Test: [10800/21770] eta: 0:09:12 time: 0.0467 data: 0.0017 max mem: 19788 +Test: [10900/21770] eta: 0:09:07 time: 0.0468 data: 0.0016 max mem: 19788 +Test: [11000/21770] eta: 0:09:02 time: 0.0553 data: 0.0020 max mem: 19788 +Test: [11100/21770] eta: 0:08:57 time: 0.0442 data: 0.0015 max mem: 19788 +Test: [11200/21770] eta: 0:08:52 time: 0.0476 data: 0.0016 max mem: 19788 +Test: [11300/21770] eta: 0:08:47 time: 0.0454 data: 0.0016 max mem: 19788 +Test: [11400/21770] eta: 0:08:41 time: 0.0461 data: 0.0018 max mem: 19788 +Test: [11500/21770] eta: 0:08:36 time: 0.0469 data: 0.0016 max mem: 19788 +Test: [11600/21770] eta: 0:08:32 time: 0.0519 data: 0.0018 max mem: 19788 +Test: [11700/21770] eta: 0:08:26 time: 0.0456 data: 0.0015 max mem: 19788 +Test: [11800/21770] eta: 0:08:21 time: 0.0542 data: 0.0018 max mem: 19788 +Test: [11900/21770] eta: 0:08:16 time: 0.0451 data: 0.0017 max mem: 19788 +Test: [12000/21770] eta: 0:08:11 time: 0.0469 data: 0.0017 max mem: 19788 +Test: [12100/21770] eta: 0:08:06 time: 0.0553 data: 0.0019 max mem: 19788 +Test: [12200/21770] eta: 0:08:01 time: 0.0488 data: 0.0018 max mem: 19788 +Test: [12300/21770] eta: 0:07:56 time: 0.0544 data: 0.0018 max mem: 19788 +Test: [12400/21770] eta: 0:07:51 time: 0.0529 data: 0.0019 max mem: 19788 +Test: [12500/21770] eta: 0:07:46 time: 0.0509 data: 0.0017 max mem: 19788 +Test: [12600/21770] eta: 0:07:41 time: 0.0552 data: 0.0018 max mem: 19788 +Test: [12700/21770] eta: 0:07:37 time: 0.0539 data: 0.0020 max mem: 19788 +Test: [12800/21770] eta: 0:07:32 time: 0.0531 data: 0.0019 max mem: 19788 +Test: [12900/21770] eta: 0:07:26 time: 0.0522 data: 0.0018 max mem: 19788 +Test: [13000/21770] eta: 0:07:22 time: 0.0533 data: 0.0017 max mem: 19788 +Test: [13100/21770] eta: 0:07:16 time: 0.0543 data: 0.0017 max mem: 19788 +Test: [13200/21770] eta: 0:07:12 time: 0.0473 data: 0.0016 max mem: 19788 +Test: [13300/21770] eta: 0:07:06 time: 0.0539 data: 0.0018 max mem: 19788 +Test: [13400/21770] eta: 0:07:01 time: 0.0556 data: 0.0018 max mem: 19788 +Test: [13500/21770] eta: 0:06:56 time: 0.0512 data: 0.0016 max mem: 19788 +Test: [13600/21770] eta: 0:06:51 time: 0.0458 data: 0.0016 max mem: 19788 +Test: [13700/21770] eta: 0:06:46 time: 0.0540 data: 0.0019 max mem: 19788 +Test: [13800/21770] eta: 0:06:41 time: 0.0437 data: 0.0015 max mem: 19788 +Test: [13900/21770] eta: 0:06:36 time: 0.0465 data: 0.0017 max mem: 19788 +Test: [14000/21770] eta: 0:06:31 time: 0.0544 data: 0.0019 max mem: 19788 +Test: [14100/21770] eta: 0:06:26 time: 0.0559 data: 0.0018 max mem: 19788 +Test: [14200/21770] eta: 0:06:21 time: 0.0577 data: 0.0019 max mem: 19788 +Test: [14300/21770] eta: 0:06:16 time: 0.0556 data: 0.0016 max mem: 19788 +Test: [14400/21770] eta: 0:06:11 time: 0.0518 data: 0.0016 max mem: 19788 +Test: [14500/21770] eta: 0:06:06 time: 0.0455 data: 0.0015 max mem: 19788 +Test: [14600/21770] eta: 0:06:01 time: 0.0453 data: 0.0017 max mem: 19788 +Test: [14700/21770] eta: 0:05:56 time: 0.0574 data: 0.0015 max mem: 19788 +Test: [14800/21770] eta: 0:05:51 time: 0.0548 data: 0.0020 max mem: 19788 +Test: [14900/21770] eta: 0:05:46 time: 0.0460 data: 0.0014 max mem: 19788 +Test: [15000/21770] eta: 0:05:40 time: 0.0472 data: 0.0016 max mem: 19788 +Test: [15100/21770] eta: 0:05:35 time: 0.0521 data: 0.0017 max mem: 19788 +Test: [15200/21770] eta: 0:05:30 time: 0.0478 data: 0.0016 max mem: 19788 +Test: [15300/21770] eta: 0:05:25 time: 0.0461 data: 0.0018 max mem: 19788 +Test: [15400/21770] eta: 0:05:20 time: 0.0509 data: 0.0018 max mem: 19788 +Test: [15500/21770] eta: 0:05:15 time: 0.0492 data: 0.0017 max mem: 19788 +Test: [15600/21770] eta: 0:05:10 time: 0.0557 data: 0.0019 max mem: 19788 +Test: [15700/21770] eta: 0:05:05 time: 0.0467 data: 0.0017 max mem: 19788 +Test: [15800/21770] eta: 0:05:00 time: 0.0485 data: 0.0017 max mem: 19788 +Test: [15900/21770] eta: 0:04:55 time: 0.0511 data: 0.0017 max mem: 19788 +Test: [16000/21770] eta: 0:04:50 time: 0.0482 data: 0.0015 max mem: 19788 +Test: [16100/21770] eta: 0:04:45 time: 0.0466 data: 0.0016 max mem: 19788 +Test: [16200/21770] eta: 0:04:40 time: 0.0470 data: 0.0017 max mem: 19788 +Test: [16300/21770] eta: 0:04:35 time: 0.0550 data: 0.0018 max mem: 19788 +Test: [16400/21770] eta: 0:04:30 time: 0.0450 data: 0.0015 max mem: 19788 +Test: [16500/21770] eta: 0:04:25 time: 0.0556 data: 0.0019 max mem: 19788 +Test: [16600/21770] eta: 0:04:20 time: 0.0546 data: 0.0018 max mem: 19788 +Test: [16700/21770] eta: 0:04:15 time: 0.0524 data: 0.0016 max mem: 19788 +Test: [16800/21770] eta: 0:04:10 time: 0.0546 data: 0.0020 max mem: 19788 +Test: [16900/21770] eta: 0:04:05 time: 0.0485 data: 0.0017 max mem: 19788 +Test: [17000/21770] eta: 0:04:00 time: 0.0547 data: 0.0018 max mem: 19788 +Test: [17100/21770] eta: 0:03:55 time: 0.0448 data: 0.0016 max mem: 19788 +Test: [17200/21770] eta: 0:03:50 time: 0.0487 data: 0.0015 max mem: 19788 +Test: [17300/21770] eta: 0:03:45 time: 0.0457 data: 0.0016 max mem: 19788 +Test: [17400/21770] eta: 0:03:40 time: 0.0446 data: 0.0013 max mem: 19788 +Test: [17500/21770] eta: 0:03:35 time: 0.0451 data: 0.0015 max mem: 19788 +Test: [17600/21770] eta: 0:03:29 time: 0.0545 data: 0.0019 max mem: 19788 +Test: [17700/21770] eta: 0:03:24 time: 0.0460 data: 0.0017 max mem: 19788 +Test: [17800/21770] eta: 0:03:19 time: 0.0485 data: 0.0016 max mem: 19788 +Test: [17900/21770] eta: 0:03:14 time: 0.0525 data: 0.0018 max mem: 19788 +Test: [18000/21770] eta: 0:03:09 time: 0.0457 data: 0.0018 max mem: 19788 +Test: [18100/21770] eta: 0:03:04 time: 0.0462 data: 0.0017 max mem: 19788 +Test: [18200/21770] eta: 0:02:59 time: 0.0475 data: 0.0015 max mem: 19788 +Test: [18300/21770] eta: 0:02:54 time: 0.0500 data: 0.0017 max mem: 19788 +Test: [18400/21770] eta: 0:02:49 time: 0.0498 data: 0.0016 max mem: 19788 +Test: [18500/21770] eta: 0:02:44 time: 0.0522 data: 0.0015 max mem: 19788 +Test: [18600/21770] eta: 0:02:39 time: 0.0544 data: 0.0018 max mem: 19788 +Test: [18700/21770] eta: 0:02:34 time: 0.0491 data: 0.0015 max mem: 19788 +Test: [18800/21770] eta: 0:02:29 time: 0.0548 data: 0.0019 max mem: 19788 +Test: [18900/21770] eta: 0:02:24 time: 0.0548 data: 0.0020 max mem: 19788 +Test: [19000/21770] eta: 0:02:19 time: 0.0440 data: 0.0016 max mem: 19788 +Test: [19100/21770] eta: 0:02:14 time: 0.0456 data: 0.0016 max mem: 19788 +Test: [19200/21770] eta: 0:02:09 time: 0.0468 data: 0.0017 max mem: 19788 +Test: [19300/21770] eta: 0:02:04 time: 0.0556 data: 0.0019 max mem: 19788 +Test: [19400/21770] eta: 0:01:59 time: 0.0556 data: 0.0019 max mem: 19788 +Test: [19500/21770] eta: 0:01:54 time: 0.0550 data: 0.0017 max mem: 19788 +Test: [19600/21770] eta: 0:01:49 time: 0.0448 data: 0.0015 max mem: 19788 +Test: [19700/21770] eta: 0:01:44 time: 0.0545 data: 0.0018 max mem: 19788 +Test: [19800/21770] eta: 0:01:39 time: 0.0496 data: 0.0017 max mem: 19788 +Test: [19900/21770] eta: 0:01:34 time: 0.0449 data: 0.0016 max mem: 19788 +Test: [20000/21770] eta: 0:01:29 time: 0.0485 data: 0.0015 max mem: 19788 +Test: [20100/21770] eta: 0:01:24 time: 0.0466 data: 0.0016 max mem: 19788 +Test: [20200/21770] eta: 0:01:18 time: 0.0548 data: 0.0018 max mem: 19788 +Test: [20300/21770] eta: 0:01:13 time: 0.0520 data: 0.0019 max mem: 19788 +Test: [20400/21770] eta: 0:01:08 time: 0.0436 data: 0.0015 max mem: 19788 +Test: [20500/21770] eta: 0:01:03 time: 0.0430 data: 0.0014 max mem: 19788 +Test: [20600/21770] eta: 0:00:58 time: 0.0462 data: 0.0018 max mem: 19788 +Test: [20700/21770] eta: 0:00:53 time: 0.0450 data: 0.0017 max mem: 19788 +Test: [20800/21770] eta: 0:00:48 time: 0.0448 data: 0.0015 max mem: 19788 +Test: [20900/21770] eta: 0:00:43 time: 0.0495 data: 0.0018 max mem: 19788 +Test: [21000/21770] eta: 0:00:38 time: 0.0553 data: 0.0018 max mem: 19788 +Test: [21100/21770] eta: 0:00:33 time: 0.0449 data: 0.0016 max mem: 19788 +Test: [21200/21770] eta: 0:00:28 time: 0.0449 data: 0.0016 max mem: 19788 +Test: [21300/21770] eta: 0:00:23 time: 0.0442 data: 0.0015 max mem: 19788 +Test: [21400/21770] eta: 0:00:18 time: 0.0464 data: 0.0016 max mem: 19788 +Test: [21500/21770] eta: 0:00:13 time: 0.0554 data: 0.0018 max mem: 19788 +Test: [21600/21770] eta: 0:00:08 time: 0.0555 data: 0.0018 max mem: 19788 +Test: [21700/21770] eta: 0:00:03 time: 0.0530 data: 0.0019 max mem: 19788 +Test: Total time: 0:18:14 +Final results: +Mean IoU is 63.79 + + precision@0.5 = 70.80 + precision@0.6 = 65.50 + precision@0.7 = 58.96 + precision@0.8 = 48.22 + precision@0.9 = 24.19 + overall IoU = 64.36 + mean IoU = 63.79 + +Mean accuracy for one-to-zero sample is 86.59 + +Average object IoU 0.6379043220893641 +Overall IoU 64.3627700805664 +Epoch: [25] [ 0/2138] eta: 5:04:51 lr: 2.068168681290973e-05 loss: 0.0318 (0.0318) time: 8.5555 data: 1.9593 max mem: 19788 +Epoch: [25] [ 10/2138] eta: 2:12:41 lr: 2.0675882513313462e-05 loss: 0.0228 (0.0261) time: 3.7412 data: 0.1809 max mem: 19788 +Epoch: [25] [ 20/2138] eta: 2:02:35 lr: 2.0670078032663827e-05 loss: 0.0211 (0.0235) time: 3.2187 data: 0.0027 max mem: 19788 +Epoch: [25] [ 30/2138] eta: 1:59:19 lr: 2.066427337089866e-05 loss: 0.0225 (0.0244) time: 3.2069 data: 0.0025 max mem: 19788 +Epoch: [25] [ 40/2138] eta: 1:59:25 lr: 2.0658468527955797e-05 loss: 0.0236 (0.0258) time: 3.3547 data: 0.0025 max mem: 19788 +Epoch: [25] [ 50/2138] eta: 2:01:25 lr: 2.0652663503773e-05 loss: 0.0218 (0.0256) time: 3.6331 data: 0.0026 max mem: 19788 +Epoch: [25] [ 60/2138] eta: 2:02:07 lr: 2.0646858298288015e-05 loss: 0.0243 (0.0261) time: 3.7534 data: 0.0027 max mem: 19788 +Epoch: [25] [ 70/2138] eta: 2:00:48 lr: 2.0641052911438527e-05 loss: 0.0264 (0.0259) time: 3.5457 data: 0.0029 max mem: 19788 +Epoch: [25] [ 80/2138] eta: 1:59:13 lr: 2.0635247343162195e-05 loss: 0.0230 (0.0258) time: 3.3230 data: 0.0028 max mem: 19788 +Epoch: [25] [ 90/2138] eta: 1:58:38 lr: 2.0629441593396627e-05 loss: 0.0210 (0.0254) time: 3.3707 data: 0.0024 max mem: 19788 +Epoch: [25] [ 100/2138] eta: 1:57:16 lr: 2.0623635662079396e-05 loss: 0.0212 (0.0252) time: 3.3591 data: 0.0025 max mem: 19788 +Epoch: [25] [ 110/2138] eta: 1:55:52 lr: 2.0617829549148028e-05 loss: 0.0236 (0.0251) time: 3.2121 data: 0.0027 max mem: 19788 +Epoch: [25] [ 120/2138] eta: 1:54:32 lr: 2.0612023254540023e-05 loss: 0.0213 (0.0248) time: 3.1682 data: 0.0027 max mem: 19788 +Epoch: [25] [ 130/2138] eta: 1:53:29 lr: 2.0606216778192818e-05 loss: 0.0213 (0.0248) time: 3.1858 data: 0.0026 max mem: 19788 +Epoch: [25] [ 140/2138] eta: 1:52:36 lr: 2.0600410120043824e-05 loss: 0.0228 (0.0247) time: 3.2361 data: 0.0024 max mem: 19788 +Epoch: [25] [ 150/2138] eta: 1:51:40 lr: 2.0594603280030406e-05 loss: 0.0211 (0.0246) time: 3.2345 data: 0.0025 max mem: 19788 +Epoch: [25] [ 160/2138] eta: 1:50:39 lr: 2.058879625808989e-05 loss: 0.0236 (0.0246) time: 3.1807 data: 0.0028 max mem: 19788 +Epoch: [25] [ 170/2138] eta: 1:49:46 lr: 2.0582989054159553e-05 loss: 0.0238 (0.0246) time: 3.1701 data: 0.0031 max mem: 19788 +Epoch: [25] [ 180/2138] eta: 1:48:59 lr: 2.057718166817665e-05 loss: 0.0247 (0.0246) time: 3.2059 data: 0.0030 max mem: 19788 +Epoch: [25] [ 190/2138] eta: 1:48:25 lr: 2.057137410007837e-05 loss: 0.0231 (0.0245) time: 3.2741 data: 0.0030 max mem: 19788 +Epoch: [25] [ 200/2138] eta: 1:47:52 lr: 2.056556634980188e-05 loss: 0.0219 (0.0245) time: 3.3396 data: 0.0029 max mem: 19788 +Epoch: [25] [ 210/2138] eta: 1:47:06 lr: 2.0559758417284287e-05 loss: 0.0237 (0.0247) time: 3.2757 data: 0.0028 max mem: 19788 +Epoch: [25] [ 220/2138] eta: 1:46:17 lr: 2.055395030246268e-05 loss: 0.0198 (0.0246) time: 3.1775 data: 0.0030 max mem: 19788 +Epoch: [25] [ 230/2138] eta: 1:45:29 lr: 2.0548142005274087e-05 loss: 0.0204 (0.0246) time: 3.1469 data: 0.0028 max mem: 19788 +Epoch: [25] [ 240/2138] eta: 1:44:48 lr: 2.0542333525655496e-05 loss: 0.0231 (0.0245) time: 3.1771 data: 0.0025 max mem: 19788 +Epoch: [25] [ 250/2138] eta: 1:44:05 lr: 2.0536524863543874e-05 loss: 0.0240 (0.0245) time: 3.2035 data: 0.0025 max mem: 19788 +Epoch: [25] [ 260/2138] eta: 1:43:37 lr: 2.0530716018876116e-05 loss: 0.0249 (0.0245) time: 3.2836 data: 0.0025 max mem: 19788 +Epoch: [25] [ 270/2138] eta: 1:42:59 lr: 2.0524906991589098e-05 loss: 0.0252 (0.0246) time: 3.3107 data: 0.0027 max mem: 19788 +Epoch: [25] [ 280/2138] eta: 1:42:18 lr: 2.0519097781619645e-05 loss: 0.0252 (0.0246) time: 3.2128 data: 0.0027 max mem: 19788 +Epoch: [25] [ 290/2138] eta: 1:41:37 lr: 2.051328838890455e-05 loss: 0.0232 (0.0246) time: 3.1838 data: 0.0028 max mem: 19788 +Epoch: [25] [ 300/2138] eta: 1:41:01 lr: 2.050747881338054e-05 loss: 0.0239 (0.0246) time: 3.2108 data: 0.0025 max mem: 19788 +Epoch: [25] [ 310/2138] eta: 1:40:38 lr: 2.0501669054984333e-05 loss: 0.0239 (0.0245) time: 3.3558 data: 0.0025 max mem: 19788 +Epoch: [25] [ 320/2138] eta: 1:40:13 lr: 2.0495859113652573e-05 loss: 0.0192 (0.0244) time: 3.4620 data: 0.0027 max mem: 19788 +Epoch: [25] [ 330/2138] eta: 1:39:37 lr: 2.0490048989321892e-05 loss: 0.0226 (0.0246) time: 3.3469 data: 0.0027 max mem: 19788 +Epoch: [25] [ 340/2138] eta: 1:38:54 lr: 2.0484238681928855e-05 loss: 0.0249 (0.0245) time: 3.1841 data: 0.0029 max mem: 19788 +Epoch: [25] [ 350/2138] eta: 1:38:15 lr: 2.0478428191410005e-05 loss: 0.0228 (0.0244) time: 3.1555 data: 0.0027 max mem: 19788 +Epoch: [25] [ 360/2138] eta: 1:37:54 lr: 2.047261751770183e-05 loss: 0.0232 (0.0246) time: 3.3649 data: 0.0024 max mem: 19788 +Epoch: [25] [ 370/2138] eta: 1:37:17 lr: 2.0466806660740778e-05 loss: 0.0254 (0.0246) time: 3.3739 data: 0.0024 max mem: 19788 +Epoch: [25] [ 380/2138] eta: 1:36:38 lr: 2.0460995620463258e-05 loss: 0.0253 (0.0246) time: 3.1951 data: 0.0024 max mem: 19788 +Epoch: [25] [ 390/2138] eta: 1:35:58 lr: 2.045518439680564e-05 loss: 0.0218 (0.0245) time: 3.1585 data: 0.0025 max mem: 19788 +Epoch: [25] [ 400/2138] eta: 1:35:20 lr: 2.0449372989704234e-05 loss: 0.0232 (0.0245) time: 3.1578 data: 0.0027 max mem: 19788 +Epoch: [25] [ 410/2138] eta: 1:34:44 lr: 2.0443561399095333e-05 loss: 0.0232 (0.0244) time: 3.2026 data: 0.0027 max mem: 19788 +Epoch: [25] [ 420/2138] eta: 1:34:03 lr: 2.0437749624915172e-05 loss: 0.0204 (0.0244) time: 3.1502 data: 0.0025 max mem: 19788 +Epoch: [25] [ 430/2138] eta: 1:33:30 lr: 2.0431937667099955e-05 loss: 0.0231 (0.0244) time: 3.1789 data: 0.0025 max mem: 19788 +Epoch: [25] [ 440/2138] eta: 1:32:49 lr: 2.042612552558582e-05 loss: 0.0240 (0.0244) time: 3.1820 data: 0.0027 max mem: 19788 +Epoch: [25] [ 450/2138] eta: 1:32:09 lr: 2.0420313200308896e-05 loss: 0.0235 (0.0244) time: 3.0796 data: 0.0024 max mem: 19788 +Epoch: [25] [ 460/2138] eta: 1:31:28 lr: 2.041450069120524e-05 loss: 0.0220 (0.0244) time: 3.0667 data: 0.0025 max mem: 19788 +Epoch: [25] [ 470/2138] eta: 1:30:49 lr: 2.0408687998210887e-05 loss: 0.0225 (0.0244) time: 3.0772 data: 0.0027 max mem: 19788 +Epoch: [25] [ 480/2138] eta: 1:30:21 lr: 2.0402875121261815e-05 loss: 0.0237 (0.0244) time: 3.2560 data: 0.0024 max mem: 19788 +Epoch: [25] [ 490/2138] eta: 1:29:48 lr: 2.039706206029397e-05 loss: 0.0236 (0.0244) time: 3.3274 data: 0.0025 max mem: 19788 +Epoch: [25] [ 500/2138] eta: 1:29:08 lr: 2.039124881524325e-05 loss: 0.0207 (0.0244) time: 3.1477 data: 0.0026 max mem: 19788 +Epoch: [25] [ 510/2138] eta: 1:28:29 lr: 2.0385435386045514e-05 loss: 0.0204 (0.0244) time: 3.0625 data: 0.0028 max mem: 19788 +Epoch: [25] [ 520/2138] eta: 1:27:51 lr: 2.0379621772636574e-05 loss: 0.0213 (0.0244) time: 3.0830 data: 0.0030 max mem: 19788 +Epoch: [25] [ 530/2138] eta: 1:27:17 lr: 2.0373807974952195e-05 loss: 0.0234 (0.0244) time: 3.1408 data: 0.0030 max mem: 19788 +Epoch: [25] [ 540/2138] eta: 1:26:49 lr: 2.0367993992928118e-05 loss: 0.0215 (0.0244) time: 3.3053 data: 0.0027 max mem: 19788 +Epoch: [25] [ 550/2138] eta: 1:26:15 lr: 2.036217982650001e-05 loss: 0.0245 (0.0245) time: 3.3106 data: 0.0026 max mem: 19788 +Epoch: [25] [ 560/2138] eta: 1:25:40 lr: 2.0356365475603536e-05 loss: 0.0247 (0.0245) time: 3.1934 data: 0.0026 max mem: 19788 +Epoch: [25] [ 570/2138] eta: 1:25:06 lr: 2.035055094017428e-05 loss: 0.0231 (0.0244) time: 3.1890 data: 0.0024 max mem: 19788 +Epoch: [25] [ 580/2138] eta: 1:24:30 lr: 2.0344736220147807e-05 loss: 0.0224 (0.0245) time: 3.1667 data: 0.0023 max mem: 19788 +Epoch: [25] [ 590/2138] eta: 1:23:52 lr: 2.0338921315459623e-05 loss: 0.0245 (0.0245) time: 3.0934 data: 0.0025 max mem: 19788 +Epoch: [25] [ 600/2138] eta: 1:23:15 lr: 2.0333106226045213e-05 loss: 0.0227 (0.0245) time: 3.0669 data: 0.0026 max mem: 19788 +Epoch: [25] [ 610/2138] eta: 1:22:45 lr: 2.0327290951839987e-05 loss: 0.0230 (0.0245) time: 3.2071 data: 0.0025 max mem: 19788 +Epoch: [25] [ 620/2138] eta: 1:22:07 lr: 2.0321475492779347e-05 loss: 0.0242 (0.0245) time: 3.1816 data: 0.0027 max mem: 19788 +Epoch: [25] [ 630/2138] eta: 1:21:34 lr: 2.0315659848798615e-05 loss: 0.0241 (0.0246) time: 3.1288 data: 0.0027 max mem: 19788 +Epoch: [25] [ 640/2138] eta: 1:21:05 lr: 2.030984401983311e-05 loss: 0.0232 (0.0246) time: 3.3160 data: 0.0026 max mem: 19788 +Epoch: [25] [ 650/2138] eta: 1:20:35 lr: 2.030402800581807e-05 loss: 0.0230 (0.0246) time: 3.3871 data: 0.0025 max mem: 19788 +Epoch: [25] [ 660/2138] eta: 1:19:59 lr: 2.0298211806688726e-05 loss: 0.0225 (0.0246) time: 3.2217 data: 0.0025 max mem: 19788 +Epoch: [25] [ 670/2138] eta: 1:19:22 lr: 2.029239542238022e-05 loss: 0.0225 (0.0246) time: 3.0676 data: 0.0027 max mem: 19788 +Epoch: [25] [ 680/2138] eta: 1:18:46 lr: 2.0286578852827706e-05 loss: 0.0225 (0.0246) time: 3.0473 data: 0.0032 max mem: 19788 +Epoch: [25] [ 690/2138] eta: 1:18:11 lr: 2.0280762097966245e-05 loss: 0.0236 (0.0246) time: 3.0841 data: 0.0029 max mem: 19788 +Epoch: [25] [ 700/2138] eta: 1:17:34 lr: 2.027494515773089e-05 loss: 0.0242 (0.0246) time: 3.0753 data: 0.0023 max mem: 19788 +Epoch: [25] [ 710/2138] eta: 1:16:58 lr: 2.0269128032056618e-05 loss: 0.0227 (0.0247) time: 3.0428 data: 0.0022 max mem: 19788 +Epoch: [25] [ 720/2138] eta: 1:16:30 lr: 2.0263310720878398e-05 loss: 0.0212 (0.0246) time: 3.2525 data: 0.0023 max mem: 19788 +Epoch: [25] [ 730/2138] eta: 1:15:58 lr: 2.0257493224131126e-05 loss: 0.0210 (0.0246) time: 3.3615 data: 0.0023 max mem: 19788 +Epoch: [25] [ 740/2138] eta: 1:15:30 lr: 2.0251675541749676e-05 loss: 0.0250 (0.0247) time: 3.3750 data: 0.0023 max mem: 19788 +Epoch: [25] [ 750/2138] eta: 1:14:54 lr: 2.024585767366886e-05 loss: 0.0231 (0.0247) time: 3.2584 data: 0.0028 max mem: 19788 +Epoch: [25] [ 760/2138] eta: 1:14:18 lr: 2.024003961982346e-05 loss: 0.0229 (0.0246) time: 3.0325 data: 0.0030 max mem: 19788 +Epoch: [25] [ 770/2138] eta: 1:13:43 lr: 2.02342213801482e-05 loss: 0.0228 (0.0247) time: 3.0564 data: 0.0031 max mem: 19788 +Epoch: [25] [ 780/2138] eta: 1:13:08 lr: 2.022840295457779e-05 loss: 0.0228 (0.0247) time: 3.0727 data: 0.0032 max mem: 19788 +Epoch: [25] [ 790/2138] eta: 1:12:34 lr: 2.022258434304685e-05 loss: 0.0213 (0.0246) time: 3.0966 data: 0.0029 max mem: 19788 +Epoch: [25] [ 800/2138] eta: 1:12:01 lr: 2.0216765545489998e-05 loss: 0.0233 (0.0246) time: 3.1756 data: 0.0027 max mem: 19788 +Epoch: [25] [ 810/2138] eta: 1:11:29 lr: 2.0210946561841784e-05 loss: 0.0234 (0.0246) time: 3.2161 data: 0.0029 max mem: 19788 +Epoch: [25] [ 820/2138] eta: 1:10:55 lr: 2.020512739203673e-05 loss: 0.0225 (0.0246) time: 3.1900 data: 0.0026 max mem: 19788 +Epoch: [25] [ 830/2138] eta: 1:10:20 lr: 2.01993080360093e-05 loss: 0.0213 (0.0246) time: 3.0956 data: 0.0023 max mem: 19788 +Epoch: [25] [ 840/2138] eta: 1:09:47 lr: 2.0193488493693912e-05 loss: 0.0213 (0.0246) time: 3.1021 data: 0.0026 max mem: 19788 +Epoch: [25] [ 850/2138] eta: 1:09:14 lr: 2.0187668765024965e-05 loss: 0.0233 (0.0246) time: 3.1679 data: 0.0027 max mem: 19788 +Epoch: [25] [ 860/2138] eta: 1:08:39 lr: 2.018184884993678e-05 loss: 0.0235 (0.0246) time: 3.1167 data: 0.0025 max mem: 19788 +Epoch: [25] [ 870/2138] eta: 1:08:07 lr: 2.017602874836366e-05 loss: 0.0232 (0.0246) time: 3.1630 data: 0.0024 max mem: 19788 +Epoch: [25] [ 880/2138] eta: 1:07:34 lr: 2.017020846023985e-05 loss: 0.0206 (0.0246) time: 3.1970 data: 0.0023 max mem: 19788 +Epoch: [25] [ 890/2138] eta: 1:07:06 lr: 2.0164387985499555e-05 loss: 0.0206 (0.0246) time: 3.3280 data: 0.0025 max mem: 19788 +Epoch: [25] [ 900/2138] eta: 1:06:33 lr: 2.0158567324076934e-05 loss: 0.0214 (0.0246) time: 3.3637 data: 0.0027 max mem: 19788 +Epoch: [25] [ 910/2138] eta: 1:06:00 lr: 2.015274647590611e-05 loss: 0.0223 (0.0245) time: 3.1664 data: 0.0027 max mem: 19788 +Epoch: [25] [ 920/2138] eta: 1:05:27 lr: 2.014692544092114e-05 loss: 0.0217 (0.0245) time: 3.1441 data: 0.0026 max mem: 19788 +Epoch: [25] [ 930/2138] eta: 1:04:54 lr: 2.014110421905607e-05 loss: 0.0241 (0.0246) time: 3.1885 data: 0.0025 max mem: 19788 +Epoch: [25] [ 940/2138] eta: 1:04:19 lr: 2.0135282810244867e-05 loss: 0.0247 (0.0245) time: 3.1138 data: 0.0024 max mem: 19788 +Epoch: [25] [ 950/2138] eta: 1:03:49 lr: 2.0129461214421482e-05 loss: 0.0224 (0.0248) time: 3.1876 data: 0.0025 max mem: 19788 +Epoch: [25] [ 960/2138] eta: 1:03:17 lr: 2.0123639431519795e-05 loss: 0.0258 (0.0249) time: 3.3247 data: 0.0023 max mem: 19788 +Epoch: [25] [ 970/2138] eta: 1:02:46 lr: 2.011781746147367e-05 loss: 0.0258 (0.0249) time: 3.2953 data: 0.0023 max mem: 19788 +Epoch: [25] [ 980/2138] eta: 1:02:18 lr: 2.0111995304216894e-05 loss: 0.0220 (0.0250) time: 3.4317 data: 0.0027 max mem: 19788 +Epoch: [25] [ 990/2138] eta: 1:01:44 lr: 2.0106172959683238e-05 loss: 0.0213 (0.0249) time: 3.3399 data: 0.0026 max mem: 19788 +Epoch: [25] [1000/2138] eta: 1:01:11 lr: 2.0100350427806412e-05 loss: 0.0200 (0.0249) time: 3.1169 data: 0.0022 max mem: 19788 +Epoch: [25] [1010/2138] eta: 1:00:39 lr: 2.00945277085201e-05 loss: 0.0227 (0.0249) time: 3.1951 data: 0.0026 max mem: 19788 +Epoch: [25] [1020/2138] eta: 1:00:05 lr: 2.0088704801757902e-05 loss: 0.0230 (0.0249) time: 3.1716 data: 0.0029 max mem: 19788 +Epoch: [25] [1030/2138] eta: 0:59:31 lr: 2.008288170745342e-05 loss: 0.0210 (0.0248) time: 3.0687 data: 0.0027 max mem: 19788 +Epoch: [25] [1040/2138] eta: 0:58:57 lr: 2.0077058425540174e-05 loss: 0.0230 (0.0249) time: 3.0465 data: 0.0027 max mem: 19788 +Epoch: [25] [1050/2138] eta: 0:58:25 lr: 2.007123495595167e-05 loss: 0.0234 (0.0250) time: 3.1264 data: 0.0027 max mem: 19788 +Epoch: [25] [1060/2138] eta: 0:57:55 lr: 2.0065411298621333e-05 loss: 0.0242 (0.0250) time: 3.3630 data: 0.0026 max mem: 19788 +Epoch: [25] [1070/2138] eta: 0:57:24 lr: 2.0059587453482583e-05 loss: 0.0242 (0.0250) time: 3.4026 data: 0.0023 max mem: 19788 +Epoch: [25] [1080/2138] eta: 0:56:51 lr: 2.005376342046876e-05 loss: 0.0236 (0.0250) time: 3.2526 data: 0.0022 max mem: 19788 +Epoch: [25] [1090/2138] eta: 0:56:17 lr: 2.0047939199513188e-05 loss: 0.0239 (0.0250) time: 3.1301 data: 0.0022 max mem: 19788 +Epoch: [25] [1100/2138] eta: 0:55:43 lr: 2.004211479054912e-05 loss: 0.0239 (0.0250) time: 3.0405 data: 0.0021 max mem: 19788 +Epoch: [25] [1110/2138] eta: 0:55:10 lr: 2.0036290193509782e-05 loss: 0.0222 (0.0250) time: 3.0434 data: 0.0023 max mem: 19788 +Epoch: [25] [1120/2138] eta: 0:54:36 lr: 2.003046540832834e-05 loss: 0.0216 (0.0250) time: 3.0478 data: 0.0025 max mem: 19788 +Epoch: [25] [1130/2138] eta: 0:54:04 lr: 2.0024640434937938e-05 loss: 0.0235 (0.0249) time: 3.1485 data: 0.0024 max mem: 19788 +Epoch: [25] [1140/2138] eta: 0:53:31 lr: 2.0018815273271646e-05 loss: 0.0235 (0.0249) time: 3.1923 data: 0.0024 max mem: 19788 +Epoch: [25] [1150/2138] eta: 0:52:57 lr: 2.0012989923262504e-05 loss: 0.0203 (0.0249) time: 3.0681 data: 0.0024 max mem: 19788 +Epoch: [25] [1160/2138] eta: 0:52:25 lr: 2.000716438484351e-05 loss: 0.0200 (0.0249) time: 3.1485 data: 0.0026 max mem: 19788 +Epoch: [25] [1170/2138] eta: 0:51:52 lr: 2.0001338657947602e-05 loss: 0.0230 (0.0249) time: 3.1908 data: 0.0026 max mem: 19788 +Epoch: [25] [1180/2138] eta: 0:51:18 lr: 1.9995512742507694e-05 loss: 0.0232 (0.0248) time: 3.0412 data: 0.0023 max mem: 19788 +Epoch: [25] [1190/2138] eta: 0:50:44 lr: 1.9989686638456628e-05 loss: 0.0236 (0.0248) time: 2.9890 data: 0.0023 max mem: 19788 +Epoch: [25] [1200/2138] eta: 0:50:11 lr: 1.9983860345727225e-05 loss: 0.0211 (0.0248) time: 2.9977 data: 0.0025 max mem: 19788 +Epoch: [25] [1210/2138] eta: 0:49:38 lr: 1.9978033864252244e-05 loss: 0.0241 (0.0248) time: 3.1038 data: 0.0026 max mem: 19788 +Epoch: [25] [1220/2138] eta: 0:49:08 lr: 1.9972207193964406e-05 loss: 0.0230 (0.0248) time: 3.2939 data: 0.0027 max mem: 19788 +Epoch: [25] [1230/2138] eta: 0:48:34 lr: 1.996638033479638e-05 loss: 0.0216 (0.0248) time: 3.2131 data: 0.0026 max mem: 19788 +Epoch: [25] [1240/2138] eta: 0:48:01 lr: 1.99605532866808e-05 loss: 0.0210 (0.0248) time: 3.0624 data: 0.0023 max mem: 19788 +Epoch: [25] [1250/2138] eta: 0:47:28 lr: 1.9954726049550236e-05 loss: 0.0209 (0.0248) time: 3.0424 data: 0.0024 max mem: 19788 +Epoch: [25] [1260/2138] eta: 0:46:54 lr: 1.994889862333724e-05 loss: 0.0209 (0.0247) time: 3.0119 data: 0.0023 max mem: 19788 +Epoch: [25] [1270/2138] eta: 0:46:22 lr: 1.9943071007974283e-05 loss: 0.0209 (0.0247) time: 3.0692 data: 0.0025 max mem: 19788 +Epoch: [25] [1280/2138] eta: 0:45:49 lr: 1.993724320339382e-05 loss: 0.0229 (0.0247) time: 3.1265 data: 0.0026 max mem: 19788 +Epoch: [25] [1290/2138] eta: 0:45:17 lr: 1.993141520952824e-05 loss: 0.0229 (0.0247) time: 3.1523 data: 0.0025 max mem: 19788 +Epoch: [25] [1300/2138] eta: 0:44:46 lr: 1.9925587026309906e-05 loss: 0.0242 (0.0247) time: 3.2638 data: 0.0027 max mem: 19788 +Epoch: [25] [1310/2138] eta: 0:44:13 lr: 1.9919758653671108e-05 loss: 0.0224 (0.0247) time: 3.2584 data: 0.0026 max mem: 19788 +Epoch: [25] [1320/2138] eta: 0:43:40 lr: 1.9913930091544117e-05 loss: 0.0208 (0.0247) time: 3.0745 data: 0.0025 max mem: 19788 +Epoch: [25] [1330/2138] eta: 0:43:07 lr: 1.9908101339861134e-05 loss: 0.0237 (0.0247) time: 2.9813 data: 0.0027 max mem: 19788 +Epoch: [25] [1340/2138] eta: 0:42:34 lr: 1.990227239855434e-05 loss: 0.0239 (0.0247) time: 3.0031 data: 0.0027 max mem: 19788 +Epoch: [25] [1350/2138] eta: 0:42:00 lr: 1.9896443267555837e-05 loss: 0.0271 (0.0248) time: 3.0045 data: 0.0024 max mem: 19788 +Epoch: [25] [1360/2138] eta: 0:41:27 lr: 1.9890613946797715e-05 loss: 0.0277 (0.0248) time: 3.0116 data: 0.0022 max mem: 19788 +Epoch: [25] [1370/2138] eta: 0:40:54 lr: 1.9884784436211982e-05 loss: 0.0229 (0.0248) time: 3.0086 data: 0.0022 max mem: 19788 +Epoch: [25] [1380/2138] eta: 0:40:24 lr: 1.987895473573064e-05 loss: 0.0264 (0.0248) time: 3.2734 data: 0.0022 max mem: 19788 +Epoch: [25] [1390/2138] eta: 0:39:55 lr: 1.9873124845285603e-05 loss: 0.0237 (0.0248) time: 3.6013 data: 0.0022 max mem: 19788 +Epoch: [25] [1400/2138] eta: 0:39:23 lr: 1.986729476480877e-05 loss: 0.0227 (0.0248) time: 3.4848 data: 0.0022 max mem: 19788 +Epoch: [25] [1410/2138] eta: 0:38:51 lr: 1.986146449423198e-05 loss: 0.0226 (0.0248) time: 3.2732 data: 0.0022 max mem: 19788 +Epoch: [25] [1420/2138] eta: 0:38:18 lr: 1.9855634033487024e-05 loss: 0.0226 (0.0248) time: 3.0958 data: 0.0024 max mem: 19788 +Epoch: [25] [1430/2138] eta: 0:37:45 lr: 1.9849803382505648e-05 loss: 0.0233 (0.0248) time: 2.9819 data: 0.0028 max mem: 19788 +Epoch: [25] [1440/2138] eta: 0:37:13 lr: 1.984397254121956e-05 loss: 0.0235 (0.0248) time: 3.0331 data: 0.0028 max mem: 19788 +Epoch: [25] [1450/2138] eta: 0:36:39 lr: 1.9838141509560406e-05 loss: 0.0246 (0.0248) time: 3.0290 data: 0.0025 max mem: 19788 +Epoch: [25] [1460/2138] eta: 0:36:07 lr: 1.983231028745979e-05 loss: 0.0246 (0.0248) time: 3.0350 data: 0.0023 max mem: 19788 +Epoch: [25] [1470/2138] eta: 0:35:35 lr: 1.9826478874849283e-05 loss: 0.0205 (0.0248) time: 3.1065 data: 0.0025 max mem: 19788 +Epoch: [25] [1480/2138] eta: 0:35:03 lr: 1.9820647271660383e-05 loss: 0.0199 (0.0248) time: 3.1716 data: 0.0023 max mem: 19788 +Epoch: [25] [1490/2138] eta: 0:34:30 lr: 1.981481547782457e-05 loss: 0.0198 (0.0248) time: 3.1443 data: 0.0025 max mem: 19788 +Epoch: [25] [1500/2138] eta: 0:33:57 lr: 1.9808983493273252e-05 loss: 0.0237 (0.0248) time: 3.0305 data: 0.0028 max mem: 19788 +Epoch: [25] [1510/2138] eta: 0:33:25 lr: 1.9803151317937808e-05 loss: 0.0229 (0.0248) time: 3.0100 data: 0.0027 max mem: 19788 +Epoch: [25] [1520/2138] eta: 0:32:54 lr: 1.9797318951749554e-05 loss: 0.0226 (0.0248) time: 3.1940 data: 0.0025 max mem: 19788 +Epoch: [25] [1530/2138] eta: 0:32:22 lr: 1.9791486394639776e-05 loss: 0.0226 (0.0248) time: 3.2740 data: 0.0024 max mem: 19788 +Epoch: [25] [1540/2138] eta: 0:31:50 lr: 1.9785653646539694e-05 loss: 0.0219 (0.0248) time: 3.2805 data: 0.0025 max mem: 19788 +Epoch: [25] [1550/2138] eta: 0:31:19 lr: 1.9779820707380506e-05 loss: 0.0218 (0.0248) time: 3.3607 data: 0.0024 max mem: 19788 +Epoch: [25] [1560/2138] eta: 0:30:47 lr: 1.9773987577093327e-05 loss: 0.0235 (0.0248) time: 3.2185 data: 0.0025 max mem: 19788 +Epoch: [25] [1570/2138] eta: 0:30:14 lr: 1.9768154255609264e-05 loss: 0.0235 (0.0248) time: 3.0822 data: 0.0026 max mem: 19788 +Epoch: [25] [1580/2138] eta: 0:29:42 lr: 1.9762320742859343e-05 loss: 0.0233 (0.0248) time: 3.0566 data: 0.0024 max mem: 19788 +Epoch: [25] [1590/2138] eta: 0:29:09 lr: 1.975648703877457e-05 loss: 0.0240 (0.0249) time: 3.0329 data: 0.0025 max mem: 19788 +Epoch: [25] [1600/2138] eta: 0:28:37 lr: 1.9750653143285874e-05 loss: 0.0253 (0.0249) time: 2.9965 data: 0.0027 max mem: 19788 +Epoch: [25] [1610/2138] eta: 0:28:04 lr: 1.974481905632417e-05 loss: 0.0251 (0.0249) time: 3.0006 data: 0.0027 max mem: 19788 +Epoch: [25] [1620/2138] eta: 0:27:32 lr: 1.9738984777820294e-05 loss: 0.0205 (0.0249) time: 3.0478 data: 0.0030 max mem: 19788 +Epoch: [25] [1630/2138] eta: 0:27:00 lr: 1.973315030770506e-05 loss: 0.0214 (0.0249) time: 3.2085 data: 0.0032 max mem: 19788 +Epoch: [25] [1640/2138] eta: 0:26:28 lr: 1.9727315645909207e-05 loss: 0.0244 (0.0249) time: 3.2715 data: 0.0030 max mem: 19788 +Epoch: [25] [1650/2138] eta: 0:25:56 lr: 1.972148079236346e-05 loss: 0.0242 (0.0249) time: 3.0831 data: 0.0028 max mem: 19788 +Epoch: [25] [1660/2138] eta: 0:25:23 lr: 1.9715645746998466e-05 loss: 0.0245 (0.0249) time: 2.9663 data: 0.0024 max mem: 19788 +Epoch: [25] [1670/2138] eta: 0:24:51 lr: 1.970981050974484e-05 loss: 0.0238 (0.0249) time: 2.9990 data: 0.0023 max mem: 19788 +Epoch: [25] [1680/2138] eta: 0:24:19 lr: 1.9703975080533146e-05 loss: 0.0222 (0.0248) time: 3.0038 data: 0.0023 max mem: 19788 +Epoch: [25] [1690/2138] eta: 0:23:46 lr: 1.96981394592939e-05 loss: 0.0226 (0.0248) time: 2.9734 data: 0.0020 max mem: 19788 +Epoch: [25] [1700/2138] eta: 0:23:14 lr: 1.969230364595756e-05 loss: 0.0216 (0.0248) time: 3.0229 data: 0.0021 max mem: 19788 +Epoch: [25] [1710/2138] eta: 0:22:42 lr: 1.9686467640454563e-05 loss: 0.0216 (0.0248) time: 3.0924 data: 0.0024 max mem: 19788 +Epoch: [25] [1720/2138] eta: 0:22:10 lr: 1.968063144271526e-05 loss: 0.0261 (0.0248) time: 3.1827 data: 0.0026 max mem: 19788 +Epoch: [25] [1730/2138] eta: 0:21:38 lr: 1.967479505266999e-05 loss: 0.0246 (0.0248) time: 3.1533 data: 0.0027 max mem: 19788 +Epoch: [25] [1740/2138] eta: 0:21:06 lr: 1.966895847024902e-05 loss: 0.0241 (0.0249) time: 3.0604 data: 0.0025 max mem: 19788 +Epoch: [25] [1750/2138] eta: 0:20:34 lr: 1.966312169538257e-05 loss: 0.0239 (0.0249) time: 3.0271 data: 0.0022 max mem: 19788 +Epoch: [25] [1760/2138] eta: 0:20:02 lr: 1.9657284728000832e-05 loss: 0.0239 (0.0248) time: 2.9939 data: 0.0022 max mem: 19788 +Epoch: [25] [1770/2138] eta: 0:19:29 lr: 1.9651447568033923e-05 loss: 0.0217 (0.0248) time: 2.9920 data: 0.0022 max mem: 19788 +Epoch: [25] [1780/2138] eta: 0:18:58 lr: 1.964561021541193e-05 loss: 0.0206 (0.0248) time: 3.0655 data: 0.0021 max mem: 19788 +Epoch: [25] [1790/2138] eta: 0:18:26 lr: 1.963977267006489e-05 loss: 0.0197 (0.0248) time: 3.3363 data: 0.0022 max mem: 19788 +Epoch: [25] [1800/2138] eta: 0:17:56 lr: 1.963393493192278e-05 loss: 0.0254 (0.0248) time: 3.6128 data: 0.0024 max mem: 19788 +Epoch: [25] [1810/2138] eta: 0:17:24 lr: 1.9628097000915535e-05 loss: 0.0256 (0.0248) time: 3.4227 data: 0.0024 max mem: 19788 +Epoch: [25] [1820/2138] eta: 0:16:52 lr: 1.962225887697305e-05 loss: 0.0216 (0.0248) time: 3.0805 data: 0.0026 max mem: 19788 +Epoch: [25] [1830/2138] eta: 0:16:20 lr: 1.961642056002515e-05 loss: 0.0221 (0.0248) time: 3.0917 data: 0.0028 max mem: 19788 +Epoch: [25] [1840/2138] eta: 0:15:48 lr: 1.961058205000164e-05 loss: 0.0233 (0.0248) time: 3.0961 data: 0.0028 max mem: 19788 +Epoch: [25] [1850/2138] eta: 0:15:16 lr: 1.960474334683225e-05 loss: 0.0231 (0.0248) time: 3.0478 data: 0.0029 max mem: 19788 +Epoch: [25] [1860/2138] eta: 0:14:44 lr: 1.9598904450446677e-05 loss: 0.0231 (0.0248) time: 3.0739 data: 0.0028 max mem: 19788 +Epoch: [25] [1870/2138] eta: 0:14:12 lr: 1.959306536077456e-05 loss: 0.0244 (0.0249) time: 3.0592 data: 0.0026 max mem: 19788 +Epoch: [25] [1880/2138] eta: 0:13:40 lr: 1.95872260777455e-05 loss: 0.0224 (0.0248) time: 3.2460 data: 0.0026 max mem: 19788 +Epoch: [25] [1890/2138] eta: 0:13:09 lr: 1.9581386601289028e-05 loss: 0.0192 (0.0248) time: 3.3281 data: 0.0028 max mem: 19788 +Epoch: [25] [1900/2138] eta: 0:12:36 lr: 1.957554693133466e-05 loss: 0.0242 (0.0248) time: 3.1002 data: 0.0027 max mem: 19788 +Epoch: [25] [1910/2138] eta: 0:12:05 lr: 1.9569707067811824e-05 loss: 0.0241 (0.0248) time: 3.0372 data: 0.0024 max mem: 19788 +Epoch: [25] [1920/2138] eta: 0:11:33 lr: 1.9563867010649932e-05 loss: 0.0233 (0.0248) time: 3.0433 data: 0.0024 max mem: 19788 +Epoch: [25] [1930/2138] eta: 0:11:01 lr: 1.9558026759778324e-05 loss: 0.0257 (0.0248) time: 2.9865 data: 0.0027 max mem: 19788 +Epoch: [25] [1940/2138] eta: 0:10:29 lr: 1.955218631512631e-05 loss: 0.0261 (0.0248) time: 3.0071 data: 0.0026 max mem: 19788 +Epoch: [25] [1950/2138] eta: 0:09:57 lr: 1.9546345676623124e-05 loss: 0.0212 (0.0248) time: 3.0459 data: 0.0023 max mem: 19788 +Epoch: [25] [1960/2138] eta: 0:09:25 lr: 1.9540504844197984e-05 loss: 0.0209 (0.0248) time: 3.0876 data: 0.0028 max mem: 19788 +Epoch: [25] [1970/2138] eta: 0:08:53 lr: 1.9534663817780024e-05 loss: 0.0210 (0.0248) time: 3.2327 data: 0.0030 max mem: 19788 +Epoch: [25] [1980/2138] eta: 0:08:22 lr: 1.9528822597298363e-05 loss: 0.0221 (0.0248) time: 3.2895 data: 0.0027 max mem: 19788 +Epoch: [25] [1990/2138] eta: 0:07:50 lr: 1.9522981182682043e-05 loss: 0.0225 (0.0248) time: 3.1299 data: 0.0027 max mem: 19788 +Epoch: [25] [2000/2138] eta: 0:07:18 lr: 1.951713957386007e-05 loss: 0.0223 (0.0248) time: 2.9960 data: 0.0029 max mem: 19788 +Epoch: [25] [2010/2138] eta: 0:06:46 lr: 1.9511297770761397e-05 loss: 0.0215 (0.0248) time: 2.9741 data: 0.0028 max mem: 19788 +Epoch: [25] [2020/2138] eta: 0:06:14 lr: 1.9505455773314933e-05 loss: 0.0219 (0.0248) time: 2.9657 data: 0.0025 max mem: 19788 +Epoch: [25] [2030/2138] eta: 0:05:42 lr: 1.9499613581449522e-05 loss: 0.0237 (0.0248) time: 2.9617 data: 0.0023 max mem: 19788 +Epoch: [25] [2040/2138] eta: 0:05:10 lr: 1.949377119509398e-05 loss: 0.0226 (0.0248) time: 3.0434 data: 0.0023 max mem: 19788 +Epoch: [25] [2050/2138] eta: 0:04:39 lr: 1.9487928614177054e-05 loss: 0.0226 (0.0248) time: 3.2605 data: 0.0024 max mem: 19788 +Epoch: [25] [2060/2138] eta: 0:04:07 lr: 1.9482085838627446e-05 loss: 0.0227 (0.0248) time: 3.2753 data: 0.0024 max mem: 19788 +Epoch: [25] [2070/2138] eta: 0:03:35 lr: 1.9476242868373824e-05 loss: 0.0224 (0.0249) time: 3.0858 data: 0.0023 max mem: 19788 +Epoch: [25] [2080/2138] eta: 0:03:03 lr: 1.9470399703344775e-05 loss: 0.0221 (0.0249) time: 3.0202 data: 0.0027 max mem: 19788 +Epoch: [25] [2090/2138] eta: 0:02:32 lr: 1.9464556343468868e-05 loss: 0.0248 (0.0249) time: 3.0689 data: 0.0029 max mem: 19788 +Epoch: [25] [2100/2138] eta: 0:02:00 lr: 1.94587127886746e-05 loss: 0.0266 (0.0249) time: 3.1426 data: 0.0027 max mem: 19788 +Epoch: [25] [2110/2138] eta: 0:01:28 lr: 1.9452869038890433e-05 loss: 0.0263 (0.0249) time: 3.0951 data: 0.0027 max mem: 19788 +Epoch: [25] [2120/2138] eta: 0:00:57 lr: 1.9447025094044764e-05 loss: 0.0263 (0.0249) time: 3.0792 data: 0.0025 max mem: 19788 +Epoch: [25] [2130/2138] eta: 0:00:25 lr: 1.9441180954065956e-05 loss: 0.0258 (0.0250) time: 3.1727 data: 0.0023 max mem: 19788 +Epoch: [25] Total time: 1:52:59 +Test: [ 0/21770] eta: 16:26:17 time: 2.7183 data: 2.5123 max mem: 19788 +Test: [ 100/21770] eta: 0:27:23 time: 0.0537 data: 0.0019 max mem: 19788 +Test: [ 200/21770] eta: 0:21:49 time: 0.0469 data: 0.0015 max mem: 19788 +Test: [ 300/21770] eta: 0:19:38 time: 0.0435 data: 0.0014 max mem: 19788 +Test: [ 400/21770] eta: 0:18:39 time: 0.0496 data: 0.0018 max mem: 19788 +Test: [ 500/21770] eta: 0:18:35 time: 0.0501 data: 0.0017 max mem: 19788 +Test: [ 600/21770] eta: 0:18:14 time: 0.0499 data: 0.0017 max mem: 19788 +Test: [ 700/21770] eta: 0:18:14 time: 0.0529 data: 0.0017 max mem: 19788 +Test: [ 800/21770] eta: 0:17:58 time: 0.0510 data: 0.0018 max mem: 19788 +Test: [ 900/21770] eta: 0:17:48 time: 0.0514 data: 0.0017 max mem: 19788 +Test: [ 1000/21770] eta: 0:17:32 time: 0.0438 data: 0.0015 max mem: 19788 +Test: [ 1100/21770] eta: 0:17:14 time: 0.0437 data: 0.0016 max mem: 19788 +Test: [ 1200/21770] eta: 0:16:59 time: 0.0442 data: 0.0014 max mem: 19788 +Test: [ 1300/21770] eta: 0:16:50 time: 0.0481 data: 0.0017 max mem: 19788 +Test: [ 1400/21770] eta: 0:16:48 time: 0.0540 data: 0.0017 max mem: 19788 +Test: [ 1500/21770] eta: 0:16:37 time: 0.0437 data: 0.0014 max mem: 19788 +Test: [ 1600/21770] eta: 0:16:30 time: 0.0441 data: 0.0017 max mem: 19788 +Test: [ 1700/21770] eta: 0:16:21 time: 0.0439 data: 0.0013 max mem: 19788 +Test: [ 1800/21770] eta: 0:16:12 time: 0.0452 data: 0.0015 max mem: 19788 +Test: [ 1900/21770] eta: 0:16:10 time: 0.0529 data: 0.0019 max mem: 19788 +Test: [ 2000/21770] eta: 0:16:02 time: 0.0460 data: 0.0015 max mem: 19788 +Test: [ 2100/21770] eta: 0:15:55 time: 0.0486 data: 0.0018 max mem: 19788 +Test: [ 2200/21770] eta: 0:15:47 time: 0.0425 data: 0.0014 max mem: 19788 +Test: [ 2300/21770] eta: 0:15:39 time: 0.0444 data: 0.0017 max mem: 19788 +Test: [ 2400/21770] eta: 0:15:34 time: 0.0446 data: 0.0017 max mem: 19788 +Test: [ 2500/21770] eta: 0:15:26 time: 0.0433 data: 0.0015 max mem: 19788 +Test: [ 2600/21770] eta: 0:15:18 time: 0.0439 data: 0.0015 max mem: 19788 +Test: [ 2700/21770] eta: 0:15:11 time: 0.0440 data: 0.0014 max mem: 19788 +Test: [ 2800/21770] eta: 0:15:05 time: 0.0442 data: 0.0015 max mem: 19788 +Test: [ 2900/21770] eta: 0:15:02 time: 0.0534 data: 0.0015 max mem: 19788 +Test: [ 3000/21770] eta: 0:14:58 time: 0.0535 data: 0.0018 max mem: 19788 +Test: [ 3100/21770] eta: 0:14:51 time: 0.0449 data: 0.0016 max mem: 19788 +Test: [ 3200/21770] eta: 0:14:45 time: 0.0451 data: 0.0015 max mem: 19788 +Test: [ 3300/21770] eta: 0:14:38 time: 0.0450 data: 0.0014 max mem: 19788 +Test: [ 3400/21770] eta: 0:14:34 time: 0.0438 data: 0.0017 max mem: 19788 +Test: [ 3500/21770] eta: 0:14:30 time: 0.0526 data: 0.0016 max mem: 19788 +Test: [ 3600/21770] eta: 0:14:27 time: 0.0526 data: 0.0018 max mem: 19788 +Test: [ 3700/21770] eta: 0:14:21 time: 0.0466 data: 0.0017 max mem: 19788 +Test: [ 3800/21770] eta: 0:14:16 time: 0.0455 data: 0.0015 max mem: 19788 +Test: [ 3900/21770] eta: 0:14:11 time: 0.0457 data: 0.0015 max mem: 19788 +Test: [ 4000/21770] eta: 0:14:05 time: 0.0478 data: 0.0017 max mem: 19788 +Test: [ 4100/21770] eta: 0:14:01 time: 0.0533 data: 0.0018 max mem: 19788 +Test: [ 4200/21770] eta: 0:13:58 time: 0.0534 data: 0.0019 max mem: 19788 +Test: [ 4300/21770] eta: 0:13:55 time: 0.0504 data: 0.0016 max mem: 19788 +Test: [ 4400/21770] eta: 0:13:50 time: 0.0444 data: 0.0016 max mem: 19788 +Test: [ 4500/21770] eta: 0:13:45 time: 0.0472 data: 0.0017 max mem: 19788 +Test: [ 4600/21770] eta: 0:13:41 time: 0.0517 data: 0.0018 max mem: 19788 +Test: [ 4700/21770] eta: 0:13:35 time: 0.0437 data: 0.0015 max mem: 19788 +Test: [ 4800/21770] eta: 0:13:31 time: 0.0511 data: 0.0018 max mem: 19788 +Test: [ 4900/21770] eta: 0:13:26 time: 0.0445 data: 0.0014 max mem: 19788 +Test: [ 5000/21770] eta: 0:13:22 time: 0.0490 data: 0.0016 max mem: 19788 +Test: [ 5100/21770] eta: 0:13:17 time: 0.0479 data: 0.0017 max mem: 19788 +Test: [ 5200/21770] eta: 0:13:12 time: 0.0456 data: 0.0016 max mem: 19788 +Test: [ 5300/21770] eta: 0:13:08 time: 0.0440 data: 0.0016 max mem: 19788 +Test: [ 5400/21770] eta: 0:13:03 time: 0.0529 data: 0.0018 max mem: 19788 +Test: [ 5500/21770] eta: 0:12:58 time: 0.0445 data: 0.0013 max mem: 19788 +Test: [ 5600/21770] eta: 0:12:53 time: 0.0529 data: 0.0015 max mem: 19788 +Test: [ 5700/21770] eta: 0:12:49 time: 0.0472 data: 0.0016 max mem: 19788 +Test: [ 5800/21770] eta: 0:12:44 time: 0.0448 data: 0.0016 max mem: 19788 +Test: [ 5900/21770] eta: 0:12:39 time: 0.0452 data: 0.0014 max mem: 19788 +Test: [ 6000/21770] eta: 0:12:34 time: 0.0438 data: 0.0014 max mem: 19788 +Test: [ 6100/21770] eta: 0:12:29 time: 0.0441 data: 0.0016 max mem: 19788 +Test: [ 6200/21770] eta: 0:12:25 time: 0.0466 data: 0.0016 max mem: 19788 +Test: [ 6300/21770] eta: 0:12:20 time: 0.0532 data: 0.0017 max mem: 19788 +Test: [ 6400/21770] eta: 0:12:15 time: 0.0465 data: 0.0015 max mem: 19788 +Test: [ 6500/21770] eta: 0:12:10 time: 0.0470 data: 0.0018 max mem: 19788 +Test: [ 6600/21770] eta: 0:12:06 time: 0.0443 data: 0.0014 max mem: 19788 +Test: [ 6700/21770] eta: 0:12:01 time: 0.0539 data: 0.0018 max mem: 19788 +Test: [ 6800/21770] eta: 0:11:56 time: 0.0559 data: 0.0017 max mem: 19788 +Test: [ 6900/21770] eta: 0:11:52 time: 0.0516 data: 0.0018 max mem: 19788 +Test: [ 7000/21770] eta: 0:11:46 time: 0.0455 data: 0.0016 max mem: 19788 +Test: [ 7100/21770] eta: 0:11:42 time: 0.0529 data: 0.0016 max mem: 19788 +Test: [ 7200/21770] eta: 0:11:37 time: 0.0459 data: 0.0017 max mem: 19788 +Test: [ 7300/21770] eta: 0:11:32 time: 0.0531 data: 0.0018 max mem: 19788 +Test: [ 7400/21770] eta: 0:11:27 time: 0.0439 data: 0.0016 max mem: 19788 +Test: [ 7500/21770] eta: 0:11:22 time: 0.0471 data: 0.0015 max mem: 19788 +Test: [ 7600/21770] eta: 0:11:17 time: 0.0441 data: 0.0015 max mem: 19788 +Test: [ 7700/21770] eta: 0:11:12 time: 0.0461 data: 0.0017 max mem: 19788 +Test: [ 7800/21770] eta: 0:11:06 time: 0.0436 data: 0.0015 max mem: 19788 +Test: [ 7900/21770] eta: 0:11:01 time: 0.0509 data: 0.0016 max mem: 19788 +Test: [ 8000/21770] eta: 0:10:56 time: 0.0438 data: 0.0016 max mem: 19788 +Test: [ 8100/21770] eta: 0:10:51 time: 0.0447 data: 0.0015 max mem: 19788 +Test: [ 8200/21770] eta: 0:10:46 time: 0.0436 data: 0.0016 max mem: 19788 +Test: [ 8300/21770] eta: 0:10:41 time: 0.0533 data: 0.0019 max mem: 19788 +Test: [ 8400/21770] eta: 0:10:37 time: 0.0453 data: 0.0016 max mem: 19788 +Test: [ 8500/21770] eta: 0:10:33 time: 0.0515 data: 0.0017 max mem: 19788 +Test: [ 8600/21770] eta: 0:10:28 time: 0.0516 data: 0.0018 max mem: 19788 +Test: [ 8700/21770] eta: 0:10:23 time: 0.0509 data: 0.0017 max mem: 19788 +Test: [ 8800/21770] eta: 0:10:18 time: 0.0458 data: 0.0015 max mem: 19788 +Test: [ 8900/21770] eta: 0:10:14 time: 0.0433 data: 0.0015 max mem: 19788 +Test: [ 9000/21770] eta: 0:10:09 time: 0.0437 data: 0.0016 max mem: 19788 +Test: [ 9100/21770] eta: 0:10:04 time: 0.0443 data: 0.0016 max mem: 19788 +Test: [ 9200/21770] eta: 0:09:59 time: 0.0484 data: 0.0014 max mem: 19788 +Test: [ 9300/21770] eta: 0:09:54 time: 0.0443 data: 0.0021 max mem: 19788 +Test: [ 9400/21770] eta: 0:09:49 time: 0.0528 data: 0.0016 max mem: 19788 +Test: [ 9500/21770] eta: 0:09:45 time: 0.0531 data: 0.0014 max mem: 19788 +Test: [ 9600/21770] eta: 0:09:41 time: 0.0438 data: 0.0015 max mem: 19788 +Test: [ 9700/21770] eta: 0:09:36 time: 0.0439 data: 0.0016 max mem: 19788 +Test: [ 9800/21770] eta: 0:09:31 time: 0.0531 data: 0.0019 max mem: 19788 +Test: [ 9900/21770] eta: 0:09:27 time: 0.0467 data: 0.0018 max mem: 19788 +Test: [10000/21770] eta: 0:09:22 time: 0.0530 data: 0.0019 max mem: 19788 +Test: [10100/21770] eta: 0:09:17 time: 0.0467 data: 0.0015 max mem: 19788 +Test: [10200/21770] eta: 0:09:12 time: 0.0516 data: 0.0018 max mem: 19788 +Test: [10300/21770] eta: 0:09:07 time: 0.0444 data: 0.0016 max mem: 19788 +Test: [10400/21770] eta: 0:09:02 time: 0.0515 data: 0.0018 max mem: 19788 +Test: [10500/21770] eta: 0:08:58 time: 0.0534 data: 0.0016 max mem: 19788 +Test: [10600/21770] eta: 0:08:53 time: 0.0467 data: 0.0017 max mem: 19788 +Test: [10700/21770] eta: 0:08:48 time: 0.0442 data: 0.0014 max mem: 19788 +Test: [10800/21770] eta: 0:08:43 time: 0.0448 data: 0.0017 max mem: 19788 +Test: [10900/21770] eta: 0:08:38 time: 0.0462 data: 0.0017 max mem: 19788 +Test: [11000/21770] eta: 0:08:34 time: 0.0448 data: 0.0017 max mem: 19788 +Test: [11100/21770] eta: 0:08:29 time: 0.0521 data: 0.0017 max mem: 19788 +Test: [11200/21770] eta: 0:08:24 time: 0.0442 data: 0.0018 max mem: 19788 +Test: [11300/21770] eta: 0:08:19 time: 0.0525 data: 0.0018 max mem: 19788 +Test: [11400/21770] eta: 0:08:15 time: 0.0554 data: 0.0020 max mem: 19788 +Test: [11500/21770] eta: 0:08:10 time: 0.0458 data: 0.0017 max mem: 19788 +Test: [11600/21770] eta: 0:08:05 time: 0.0450 data: 0.0016 max mem: 19788 +Test: [11700/21770] eta: 0:08:00 time: 0.0536 data: 0.0019 max mem: 19788 +Test: [11800/21770] eta: 0:07:56 time: 0.0542 data: 0.0019 max mem: 19788 +Test: [11900/21770] eta: 0:07:51 time: 0.0445 data: 0.0016 max mem: 19788 +Test: [12000/21770] eta: 0:07:46 time: 0.0526 data: 0.0018 max mem: 19788 +Test: [12100/21770] eta: 0:07:42 time: 0.0474 data: 0.0017 max mem: 19788 +Test: [12200/21770] eta: 0:07:37 time: 0.0498 data: 0.0020 max mem: 19788 +Test: [12300/21770] eta: 0:07:32 time: 0.0466 data: 0.0016 max mem: 19788 +Test: [12400/21770] eta: 0:07:27 time: 0.0464 data: 0.0016 max mem: 19788 +Test: [12500/21770] eta: 0:07:22 time: 0.0461 data: 0.0016 max mem: 19788 +Test: [12600/21770] eta: 0:07:18 time: 0.0534 data: 0.0019 max mem: 19788 +Test: [12700/21770] eta: 0:07:13 time: 0.0537 data: 0.0018 max mem: 19788 +Test: [12800/21770] eta: 0:07:08 time: 0.0466 data: 0.0018 max mem: 19788 +Test: [12900/21770] eta: 0:07:04 time: 0.0472 data: 0.0016 max mem: 19788 +Test: [13000/21770] eta: 0:06:59 time: 0.0509 data: 0.0017 max mem: 19788 +Test: [13100/21770] eta: 0:06:54 time: 0.0453 data: 0.0016 max mem: 19788 +Test: [13200/21770] eta: 0:06:50 time: 0.0540 data: 0.0020 max mem: 19788 +Test: [13300/21770] eta: 0:06:45 time: 0.0445 data: 0.0015 max mem: 19788 +Test: [13400/21770] eta: 0:06:41 time: 0.0534 data: 0.0018 max mem: 19788 +Test: [13500/21770] eta: 0:06:36 time: 0.0443 data: 0.0016 max mem: 19788 +Test: [13600/21770] eta: 0:06:31 time: 0.0454 data: 0.0017 max mem: 19788 +Test: [13700/21770] eta: 0:06:26 time: 0.0540 data: 0.0020 max mem: 19788 +Test: [13800/21770] eta: 0:06:22 time: 0.0478 data: 0.0018 max mem: 19788 +Test: [13900/21770] eta: 0:06:17 time: 0.0478 data: 0.0016 max mem: 19788 +Test: [14000/21770] eta: 0:06:12 time: 0.0529 data: 0.0017 max mem: 19788 +Test: [14100/21770] eta: 0:06:07 time: 0.0482 data: 0.0017 max mem: 19788 +Test: [14200/21770] eta: 0:06:03 time: 0.0537 data: 0.0020 max mem: 19788 +Test: [14300/21770] eta: 0:05:58 time: 0.0444 data: 0.0015 max mem: 19788 +Test: [14400/21770] eta: 0:05:53 time: 0.0473 data: 0.0017 max mem: 19788 +Test: [14500/21770] eta: 0:05:48 time: 0.0488 data: 0.0020 max mem: 19788 +Test: [14600/21770] eta: 0:05:43 time: 0.0441 data: 0.0015 max mem: 19788 +Test: [14700/21770] eta: 0:05:38 time: 0.0454 data: 0.0017 max mem: 19788 +Test: [14800/21770] eta: 0:05:33 time: 0.0457 data: 0.0015 max mem: 19788 +Test: [14900/21770] eta: 0:05:29 time: 0.0496 data: 0.0016 max mem: 19788 +Test: [15000/21770] eta: 0:05:24 time: 0.0534 data: 0.0019 max mem: 19788 +Test: [15100/21770] eta: 0:05:20 time: 0.0486 data: 0.0016 max mem: 19788 +Test: [15200/21770] eta: 0:05:15 time: 0.0509 data: 0.0019 max mem: 19788 +Test: [15300/21770] eta: 0:05:10 time: 0.0535 data: 0.0019 max mem: 19788 +Test: [15400/21770] eta: 0:05:06 time: 0.0543 data: 0.0018 max mem: 19788 +Test: [15500/21770] eta: 0:05:01 time: 0.0502 data: 0.0018 max mem: 19788 +Test: [15600/21770] eta: 0:04:56 time: 0.0522 data: 0.0018 max mem: 19788 +Test: [15700/21770] eta: 0:04:51 time: 0.0462 data: 0.0015 max mem: 19788 +Test: [15800/21770] eta: 0:04:47 time: 0.0540 data: 0.0019 max mem: 19788 +Test: [15900/21770] eta: 0:04:42 time: 0.0538 data: 0.0020 max mem: 19788 +Test: [16000/21770] eta: 0:04:37 time: 0.0454 data: 0.0015 max mem: 19788 +Test: [16100/21770] eta: 0:04:33 time: 0.0528 data: 0.0018 max mem: 19788 +Test: [16200/21770] eta: 0:04:28 time: 0.0525 data: 0.0020 max mem: 19788 +Test: [16300/21770] eta: 0:04:23 time: 0.0478 data: 0.0018 max mem: 19788 +Test: [16400/21770] eta: 0:04:18 time: 0.0455 data: 0.0016 max mem: 19788 +Test: [16500/21770] eta: 0:04:13 time: 0.0447 data: 0.0014 max mem: 19788 +Test: [16600/21770] eta: 0:04:09 time: 0.0542 data: 0.0019 max mem: 19788 +Test: [16700/21770] eta: 0:04:04 time: 0.0454 data: 0.0015 max mem: 19788 +Test: [16800/21770] eta: 0:03:59 time: 0.0441 data: 0.0016 max mem: 19788 +Test: [16900/21770] eta: 0:03:54 time: 0.0511 data: 0.0018 max mem: 19788 +Test: [17000/21770] eta: 0:03:49 time: 0.0461 data: 0.0015 max mem: 19788 +Test: [17100/21770] eta: 0:03:45 time: 0.0447 data: 0.0018 max mem: 19788 +Test: [17200/21770] eta: 0:03:40 time: 0.0451 data: 0.0016 max mem: 19788 +Test: [17300/21770] eta: 0:03:35 time: 0.0478 data: 0.0015 max mem: 19788 +Test: [17400/21770] eta: 0:03:30 time: 0.0532 data: 0.0018 max mem: 19788 +Test: [17500/21770] eta: 0:03:25 time: 0.0455 data: 0.0015 max mem: 19788 +Test: [17600/21770] eta: 0:03:21 time: 0.0446 data: 0.0015 max mem: 19788 +Test: [17700/21770] eta: 0:03:16 time: 0.0528 data: 0.0018 max mem: 19788 +Test: [17800/21770] eta: 0:03:11 time: 0.0453 data: 0.0015 max mem: 19788 +Test: [17900/21770] eta: 0:03:06 time: 0.0483 data: 0.0015 max mem: 19788 +Test: [18000/21770] eta: 0:03:01 time: 0.0509 data: 0.0019 max mem: 19788 +Test: [18100/21770] eta: 0:02:56 time: 0.0442 data: 0.0016 max mem: 19788 +Test: [18200/21770] eta: 0:02:52 time: 0.0537 data: 0.0019 max mem: 19788 +Test: [18300/21770] eta: 0:02:47 time: 0.0443 data: 0.0016 max mem: 19788 +Test: [18400/21770] eta: 0:02:42 time: 0.0438 data: 0.0015 max mem: 19788 +Test: [18500/21770] eta: 0:02:37 time: 0.0480 data: 0.0017 max mem: 19788 +Test: [18600/21770] eta: 0:02:32 time: 0.0436 data: 0.0016 max mem: 19788 +Test: [18700/21770] eta: 0:02:28 time: 0.0537 data: 0.0019 max mem: 19788 +Test: [18800/21770] eta: 0:02:23 time: 0.0435 data: 0.0015 max mem: 19788 +Test: [18900/21770] eta: 0:02:18 time: 0.0440 data: 0.0015 max mem: 19788 +Test: [19000/21770] eta: 0:02:13 time: 0.0466 data: 0.0017 max mem: 19788 +Test: [19100/21770] eta: 0:02:08 time: 0.0444 data: 0.0016 max mem: 19788 +Test: [19200/21770] eta: 0:02:03 time: 0.0444 data: 0.0016 max mem: 19788 +Test: [19300/21770] eta: 0:01:59 time: 0.0459 data: 0.0018 max mem: 19788 +Test: [19400/21770] eta: 0:01:54 time: 0.0450 data: 0.0017 max mem: 19788 +Test: [19500/21770] eta: 0:01:49 time: 0.0488 data: 0.0019 max mem: 19788 +Test: [19600/21770] eta: 0:01:44 time: 0.0442 data: 0.0014 max mem: 19788 +Test: [19700/21770] eta: 0:01:39 time: 0.0511 data: 0.0018 max mem: 19788 +Test: [19800/21770] eta: 0:01:35 time: 0.0527 data: 0.0018 max mem: 19788 +Test: [19900/21770] eta: 0:01:30 time: 0.0534 data: 0.0020 max mem: 19788 +Test: [20000/21770] eta: 0:01:25 time: 0.0484 data: 0.0016 max mem: 19788 +Test: [20100/21770] eta: 0:01:20 time: 0.0446 data: 0.0017 max mem: 19788 +Test: [20200/21770] eta: 0:01:15 time: 0.0514 data: 0.0018 max mem: 19788 +Test: [20300/21770] eta: 0:01:10 time: 0.0450 data: 0.0019 max mem: 19788 +Test: [20400/21770] eta: 0:01:06 time: 0.0461 data: 0.0016 max mem: 19788 +Test: [20500/21770] eta: 0:01:01 time: 0.0452 data: 0.0016 max mem: 19788 +Test: [20600/21770] eta: 0:00:56 time: 0.0433 data: 0.0014 max mem: 19788 +Test: [20700/21770] eta: 0:00:51 time: 0.0540 data: 0.0019 max mem: 19788 +Test: [20800/21770] eta: 0:00:46 time: 0.0541 data: 0.0016 max mem: 19788 +Test: [20900/21770] eta: 0:00:41 time: 0.0508 data: 0.0018 max mem: 19788 +Test: [21000/21770] eta: 0:00:37 time: 0.0510 data: 0.0017 max mem: 19788 +Test: [21100/21770] eta: 0:00:32 time: 0.0466 data: 0.0016 max mem: 19788 +Test: [21200/21770] eta: 0:00:27 time: 0.0460 data: 0.0015 max mem: 19788 +Test: [21300/21770] eta: 0:00:22 time: 0.0539 data: 0.0019 max mem: 19788 +Test: [21400/21770] eta: 0:00:17 time: 0.0481 data: 0.0017 max mem: 19788 +Test: [21500/21770] eta: 0:00:13 time: 0.0450 data: 0.0014 max mem: 19788 +Test: [21600/21770] eta: 0:00:08 time: 0.0458 data: 0.0019 max mem: 19788 +Test: [21700/21770] eta: 0:00:03 time: 0.0545 data: 0.0016 max mem: 19788 +Test: Total time: 0:17:30 +Final results: +Mean IoU is 63.96 + + precision@0.5 = 71.09 + precision@0.6 = 65.50 + precision@0.7 = 59.06 + precision@0.8 = 47.89 + precision@0.9 = 23.61 + overall IoU = 64.18 + mean IoU = 63.96 + +Mean accuracy for one-to-zero sample is 85.30 + +Average object IoU 0.6396496466136105 +Overall IoU 64.17610931396484 +Epoch: [26] [ 0/2138] eta: 9:58:31 lr: 1.9436505501538867e-05 loss: 0.0311 (0.0311) time: 16.7969 data: 1.4889 max mem: 19788 +Epoch: [26] [ 10/2138] eta: 2:36:29 lr: 1.9430661010139682e-05 loss: 0.0233 (0.0265) time: 4.4124 data: 0.1371 max mem: 19788 +Epoch: [26] [ 20/2138] eta: 2:15:01 lr: 1.942481632340649e-05 loss: 0.0215 (0.0239) time: 3.1764 data: 0.0020 max mem: 19788 +Epoch: [26] [ 30/2138] eta: 2:06:18 lr: 1.9418971441267437e-05 loss: 0.0239 (0.0242) time: 3.1459 data: 0.0026 max mem: 19788 +Epoch: [26] [ 40/2138] eta: 2:02:05 lr: 1.9413126363650645e-05 loss: 0.0239 (0.0245) time: 3.1416 data: 0.0028 max mem: 19788 +Epoch: [26] [ 50/2138] eta: 1:58:51 lr: 1.9407281090484167e-05 loss: 0.0221 (0.0243) time: 3.1373 data: 0.0026 max mem: 19788 +Epoch: [26] [ 60/2138] eta: 1:56:35 lr: 1.9401435621696023e-05 loss: 0.0226 (0.0246) time: 3.1106 data: 0.0025 max mem: 19788 +Epoch: [26] [ 70/2138] eta: 1:54:53 lr: 1.939558995721417e-05 loss: 0.0226 (0.0245) time: 3.1244 data: 0.0027 max mem: 19788 +Epoch: [26] [ 80/2138] eta: 1:53:36 lr: 1.938974409696652e-05 loss: 0.0217 (0.0245) time: 3.1462 data: 0.0028 max mem: 19788 +Epoch: [26] [ 90/2138] eta: 1:52:41 lr: 1.938389804088093e-05 loss: 0.0206 (0.0241) time: 3.1875 data: 0.0026 max mem: 19788 +Epoch: [26] [ 100/2138] eta: 1:51:54 lr: 1.937805178888522e-05 loss: 0.0236 (0.0248) time: 3.2226 data: 0.0024 max mem: 19788 +Epoch: [26] [ 110/2138] eta: 1:51:20 lr: 1.9372205340907133e-05 loss: 0.0236 (0.0247) time: 3.2605 data: 0.0024 max mem: 19788 +Epoch: [26] [ 120/2138] eta: 1:51:28 lr: 1.936635869687438e-05 loss: 0.0218 (0.0246) time: 3.4165 data: 0.0026 max mem: 19788 +Epoch: [26] [ 130/2138] eta: 1:50:31 lr: 1.9360511856714624e-05 loss: 0.0235 (0.0245) time: 3.3509 data: 0.0025 max mem: 19788 +Epoch: [26] [ 140/2138] eta: 1:49:52 lr: 1.9354664820355463e-05 loss: 0.0234 (0.0245) time: 3.2089 data: 0.0022 max mem: 19788 +Epoch: [26] [ 150/2138] eta: 1:49:00 lr: 1.9348817587724456e-05 loss: 0.0227 (0.0243) time: 3.2067 data: 0.0023 max mem: 19788 +Epoch: [26] [ 160/2138] eta: 1:48:20 lr: 1.93429701587491e-05 loss: 0.0228 (0.0243) time: 3.1946 data: 0.0023 max mem: 19788 +Epoch: [26] [ 170/2138] eta: 1:47:33 lr: 1.9337122533356862e-05 loss: 0.0228 (0.0242) time: 3.1979 data: 0.0022 max mem: 19788 +Epoch: [26] [ 180/2138] eta: 1:46:48 lr: 1.9331274711475124e-05 loss: 0.0224 (0.0242) time: 3.1636 data: 0.0024 max mem: 19788 +Epoch: [26] [ 190/2138] eta: 1:46:05 lr: 1.9325426693031252e-05 loss: 0.0212 (0.0240) time: 3.1667 data: 0.0025 max mem: 19788 +Epoch: [26] [ 200/2138] eta: 1:45:48 lr: 1.9319578477952527e-05 loss: 0.0211 (0.0240) time: 3.3029 data: 0.0023 max mem: 19788 +Epoch: [26] [ 210/2138] eta: 1:45:09 lr: 1.9313730066166212e-05 loss: 0.0221 (0.0241) time: 3.3229 data: 0.0024 max mem: 19788 +Epoch: [26] [ 220/2138] eta: 1:44:22 lr: 1.9307881457599494e-05 loss: 0.0232 (0.0241) time: 3.1568 data: 0.0025 max mem: 19788 +Epoch: [26] [ 230/2138] eta: 1:43:36 lr: 1.9302032652179523e-05 loss: 0.0232 (0.0242) time: 3.1058 data: 0.0024 max mem: 19788 +Epoch: [26] [ 240/2138] eta: 1:43:25 lr: 1.929618364983338e-05 loss: 0.0237 (0.0242) time: 3.3175 data: 0.0023 max mem: 19788 +Epoch: [26] [ 250/2138] eta: 1:42:45 lr: 1.9290334450488124e-05 loss: 0.0226 (0.0242) time: 3.3535 data: 0.0026 max mem: 19788 +Epoch: [26] [ 260/2138] eta: 1:42:01 lr: 1.9284485054070725e-05 loss: 0.0220 (0.0241) time: 3.1399 data: 0.0030 max mem: 19788 +Epoch: [26] [ 270/2138] eta: 1:41:22 lr: 1.9278635460508138e-05 loss: 0.0220 (0.0241) time: 3.1354 data: 0.0029 max mem: 19788 +Epoch: [26] [ 280/2138] eta: 1:40:39 lr: 1.9272785669727232e-05 loss: 0.0225 (0.0240) time: 3.1291 data: 0.0026 max mem: 19788 +Epoch: [26] [ 290/2138] eta: 1:39:58 lr: 1.926693568165486e-05 loss: 0.0228 (0.0240) time: 3.1051 data: 0.0026 max mem: 19788 +Epoch: [26] [ 300/2138] eta: 1:39:17 lr: 1.926108549621779e-05 loss: 0.0228 (0.0240) time: 3.1119 data: 0.0027 max mem: 19788 +Epoch: [26] [ 310/2138] eta: 1:38:37 lr: 1.925523511334276e-05 loss: 0.0227 (0.0240) time: 3.1079 data: 0.0028 max mem: 19788 +Epoch: [26] [ 320/2138] eta: 1:37:56 lr: 1.9249384532956443e-05 loss: 0.0197 (0.0240) time: 3.1044 data: 0.0028 max mem: 19788 +Epoch: [26] [ 330/2138] eta: 1:37:18 lr: 1.924353375498547e-05 loss: 0.0235 (0.0240) time: 3.1107 data: 0.0026 max mem: 19788 +Epoch: [26] [ 340/2138] eta: 1:36:41 lr: 1.9237682779356412e-05 loss: 0.0225 (0.0244) time: 3.1354 data: 0.0024 max mem: 19788 +Epoch: [26] [ 350/2138] eta: 1:36:11 lr: 1.9231831605995796e-05 loss: 0.0198 (0.0243) time: 3.2004 data: 0.0024 max mem: 19788 +Epoch: [26] [ 360/2138] eta: 1:35:33 lr: 1.9225980234830083e-05 loss: 0.0219 (0.0243) time: 3.1867 data: 0.0028 max mem: 19788 +Epoch: [26] [ 370/2138] eta: 1:34:58 lr: 1.9220128665785707e-05 loss: 0.0233 (0.0243) time: 3.1419 data: 0.0031 max mem: 19788 +Epoch: [26] [ 380/2138] eta: 1:34:30 lr: 1.921427689878902e-05 loss: 0.0212 (0.0242) time: 3.2412 data: 0.0028 max mem: 19788 +Epoch: [26] [ 390/2138] eta: 1:33:58 lr: 1.9208424933766342e-05 loss: 0.0200 (0.0242) time: 3.2742 data: 0.0024 max mem: 19788 +Epoch: [26] [ 400/2138] eta: 1:33:35 lr: 1.9202572770643933e-05 loss: 0.0226 (0.0242) time: 3.3324 data: 0.0023 max mem: 19788 +Epoch: [26] [ 410/2138] eta: 1:32:59 lr: 1.9196720409347994e-05 loss: 0.0226 (0.0241) time: 3.2958 data: 0.0029 max mem: 19788 +Epoch: [26] [ 420/2138] eta: 1:32:24 lr: 1.9190867849804696e-05 loss: 0.0204 (0.0241) time: 3.1608 data: 0.0031 max mem: 19788 +Epoch: [26] [ 430/2138] eta: 1:32:04 lr: 1.9185015091940122e-05 loss: 0.0222 (0.0241) time: 3.3480 data: 0.0027 max mem: 19788 +Epoch: [26] [ 440/2138] eta: 1:31:38 lr: 1.9179162135680347e-05 loss: 0.0223 (0.0241) time: 3.4656 data: 0.0026 max mem: 19788 +Epoch: [26] [ 450/2138] eta: 1:31:07 lr: 1.917330898095135e-05 loss: 0.0246 (0.0241) time: 3.3394 data: 0.0025 max mem: 19788 +Epoch: [26] [ 460/2138] eta: 1:30:30 lr: 1.9167455627679087e-05 loss: 0.0207 (0.0240) time: 3.1920 data: 0.0024 max mem: 19788 +Epoch: [26] [ 470/2138] eta: 1:29:53 lr: 1.9161602075789444e-05 loss: 0.0207 (0.0240) time: 3.1042 data: 0.0027 max mem: 19788 +Epoch: [26] [ 480/2138] eta: 1:29:24 lr: 1.915574832520827e-05 loss: 0.0234 (0.0240) time: 3.2243 data: 0.0032 max mem: 19788 +Epoch: [26] [ 490/2138] eta: 1:28:49 lr: 1.914989437586134e-05 loss: 0.0227 (0.0240) time: 3.2397 data: 0.0028 max mem: 19788 +Epoch: [26] [ 500/2138] eta: 1:28:15 lr: 1.9144040227674404e-05 loss: 0.0205 (0.0240) time: 3.1622 data: 0.0024 max mem: 19788 +Epoch: [26] [ 510/2138] eta: 1:27:39 lr: 1.9138185880573126e-05 loss: 0.0189 (0.0239) time: 3.1503 data: 0.0026 max mem: 19788 +Epoch: [26] [ 520/2138] eta: 1:27:08 lr: 1.9132331334483148e-05 loss: 0.0202 (0.0239) time: 3.1936 data: 0.0025 max mem: 19788 +Epoch: [26] [ 530/2138] eta: 1:26:32 lr: 1.9126476589330032e-05 loss: 0.0226 (0.0239) time: 3.1905 data: 0.0026 max mem: 19788 +Epoch: [26] [ 540/2138] eta: 1:25:57 lr: 1.912062164503931e-05 loss: 0.0209 (0.0239) time: 3.1299 data: 0.0026 max mem: 19788 +Epoch: [26] [ 550/2138] eta: 1:25:22 lr: 1.911476650153645e-05 loss: 0.0221 (0.0239) time: 3.1315 data: 0.0025 max mem: 19788 +Epoch: [26] [ 560/2138] eta: 1:24:47 lr: 1.9108911158746866e-05 loss: 0.0251 (0.0239) time: 3.1345 data: 0.0026 max mem: 19788 +Epoch: [26] [ 570/2138] eta: 1:24:16 lr: 1.9103055616595917e-05 loss: 0.0229 (0.0239) time: 3.2023 data: 0.0029 max mem: 19788 +Epoch: [26] [ 580/2138] eta: 1:23:49 lr: 1.9097199875008915e-05 loss: 0.0219 (0.0239) time: 3.3321 data: 0.0029 max mem: 19788 +Epoch: [26] [ 590/2138] eta: 1:23:17 lr: 1.909134393391111e-05 loss: 0.0223 (0.0239) time: 3.3391 data: 0.0029 max mem: 19788 +Epoch: [26] [ 600/2138] eta: 1:22:43 lr: 1.9085487793227714e-05 loss: 0.0240 (0.0239) time: 3.2064 data: 0.0033 max mem: 19788 +Epoch: [26] [ 610/2138] eta: 1:22:11 lr: 1.9079631452883866e-05 loss: 0.0222 (0.0239) time: 3.1857 data: 0.0031 max mem: 19788 +Epoch: [26] [ 620/2138] eta: 1:21:35 lr: 1.907377491280466e-05 loss: 0.0234 (0.0240) time: 3.1549 data: 0.0027 max mem: 19788 +Epoch: [26] [ 630/2138] eta: 1:21:00 lr: 1.9067918172915146e-05 loss: 0.0229 (0.0240) time: 3.1057 data: 0.0027 max mem: 19788 +Epoch: [26] [ 640/2138] eta: 1:20:25 lr: 1.9062061233140305e-05 loss: 0.0217 (0.0240) time: 3.1029 data: 0.0025 max mem: 19788 +Epoch: [26] [ 650/2138] eta: 1:19:51 lr: 1.9056204093405064e-05 loss: 0.0241 (0.0240) time: 3.1163 data: 0.0023 max mem: 19788 +Epoch: [26] [ 660/2138] eta: 1:19:18 lr: 1.905034675363432e-05 loss: 0.0239 (0.0241) time: 3.1576 data: 0.0023 max mem: 19788 +Epoch: [26] [ 670/2138] eta: 1:18:47 lr: 1.9044489213752878e-05 loss: 0.0240 (0.0241) time: 3.2221 data: 0.0022 max mem: 19788 +Epoch: [26] [ 680/2138] eta: 1:18:15 lr: 1.903863147368553e-05 loss: 0.0215 (0.0240) time: 3.2634 data: 0.0023 max mem: 19788 +Epoch: [26] [ 690/2138] eta: 1:17:43 lr: 1.9032773533356973e-05 loss: 0.0248 (0.0241) time: 3.2411 data: 0.0027 max mem: 19788 +Epoch: [26] [ 700/2138] eta: 1:17:09 lr: 1.9026915392691888e-05 loss: 0.0242 (0.0240) time: 3.1913 data: 0.0029 max mem: 19788 +Epoch: [26] [ 710/2138] eta: 1:16:36 lr: 1.902105705161488e-05 loss: 0.0218 (0.0240) time: 3.1541 data: 0.0028 max mem: 19788 +Epoch: [26] [ 720/2138] eta: 1:16:03 lr: 1.9015198510050493e-05 loss: 0.0211 (0.0240) time: 3.1626 data: 0.0027 max mem: 19788 +Epoch: [26] [ 730/2138] eta: 1:15:32 lr: 1.9009339767923246e-05 loss: 0.0211 (0.0240) time: 3.2267 data: 0.0026 max mem: 19788 +Epoch: [26] [ 740/2138] eta: 1:15:02 lr: 1.900348082515757e-05 loss: 0.0215 (0.0240) time: 3.3075 data: 0.0025 max mem: 19788 +Epoch: [26] [ 750/2138] eta: 1:14:29 lr: 1.899762168167787e-05 loss: 0.0238 (0.0240) time: 3.2640 data: 0.0025 max mem: 19788 +Epoch: [26] [ 760/2138] eta: 1:13:55 lr: 1.899176233740847e-05 loss: 0.0238 (0.0240) time: 3.1516 data: 0.0026 max mem: 19788 +Epoch: [26] [ 770/2138] eta: 1:13:21 lr: 1.8985902792273673e-05 loss: 0.0225 (0.0240) time: 3.1247 data: 0.0030 max mem: 19788 +Epoch: [26] [ 780/2138] eta: 1:12:49 lr: 1.8980043046197684e-05 loss: 0.0223 (0.0240) time: 3.1692 data: 0.0030 max mem: 19788 +Epoch: [26] [ 790/2138] eta: 1:12:17 lr: 1.89741830991047e-05 loss: 0.0219 (0.0239) time: 3.2182 data: 0.0027 max mem: 19788 +Epoch: [26] [ 800/2138] eta: 1:11:46 lr: 1.8968322950918827e-05 loss: 0.0219 (0.0239) time: 3.2727 data: 0.0027 max mem: 19788 +Epoch: [26] [ 810/2138] eta: 1:11:14 lr: 1.8962462601564137e-05 loss: 0.0257 (0.0239) time: 3.2517 data: 0.0025 max mem: 19788 +Epoch: [26] [ 820/2138] eta: 1:10:40 lr: 1.8956602050964634e-05 loss: 0.0241 (0.0239) time: 3.1544 data: 0.0025 max mem: 19788 +Epoch: [26] [ 830/2138] eta: 1:10:06 lr: 1.895074129904428e-05 loss: 0.0231 (0.0239) time: 3.1070 data: 0.0028 max mem: 19788 +Epoch: [26] [ 840/2138] eta: 1:09:33 lr: 1.894488034572697e-05 loss: 0.0216 (0.0239) time: 3.1487 data: 0.0027 max mem: 19788 +Epoch: [26] [ 850/2138] eta: 1:09:04 lr: 1.8939019190936556e-05 loss: 0.0219 (0.0239) time: 3.3004 data: 0.0027 max mem: 19788 +Epoch: [26] [ 860/2138] eta: 1:08:30 lr: 1.8933157834596822e-05 loss: 0.0230 (0.0240) time: 3.2616 data: 0.0030 max mem: 19788 +Epoch: [26] [ 870/2138] eta: 1:07:59 lr: 1.8927296276631508e-05 loss: 0.0221 (0.0240) time: 3.1959 data: 0.0030 max mem: 19788 +Epoch: [26] [ 880/2138] eta: 1:07:25 lr: 1.892143451696429e-05 loss: 0.0211 (0.0239) time: 3.1942 data: 0.0028 max mem: 19788 +Epoch: [26] [ 890/2138] eta: 1:06:52 lr: 1.8915572555518802e-05 loss: 0.0220 (0.0239) time: 3.1034 data: 0.0028 max mem: 19788 +Epoch: [26] [ 900/2138] eta: 1:06:18 lr: 1.8909710392218603e-05 loss: 0.0230 (0.0239) time: 3.1067 data: 0.0028 max mem: 19788 +Epoch: [26] [ 910/2138] eta: 1:05:45 lr: 1.890384802698722e-05 loss: 0.0221 (0.0239) time: 3.1155 data: 0.0029 max mem: 19788 +Epoch: [26] [ 920/2138] eta: 1:05:16 lr: 1.8897985459748098e-05 loss: 0.0221 (0.0239) time: 3.2873 data: 0.0027 max mem: 19788 +Epoch: [26] [ 930/2138] eta: 1:04:46 lr: 1.889212269042466e-05 loss: 0.0237 (0.0239) time: 3.4159 data: 0.0025 max mem: 19788 +Epoch: [26] [ 940/2138] eta: 1:04:13 lr: 1.8886259718940234e-05 loss: 0.0258 (0.0240) time: 3.2697 data: 0.0024 max mem: 19788 +Epoch: [26] [ 950/2138] eta: 1:03:40 lr: 1.8880396545218132e-05 loss: 0.0245 (0.0239) time: 3.1580 data: 0.0022 max mem: 19788 +Epoch: [26] [ 960/2138] eta: 1:03:07 lr: 1.8874533169181574e-05 loss: 0.0245 (0.0240) time: 3.1580 data: 0.0021 max mem: 19788 +Epoch: [26] [ 970/2138] eta: 1:02:34 lr: 1.8868669590753757e-05 loss: 0.0240 (0.0240) time: 3.1544 data: 0.0024 max mem: 19788 +Epoch: [26] [ 980/2138] eta: 1:02:01 lr: 1.8862805809857795e-05 loss: 0.0201 (0.0239) time: 3.1527 data: 0.0027 max mem: 19788 +Epoch: [26] [ 990/2138] eta: 1:01:29 lr: 1.8856941826416773e-05 loss: 0.0202 (0.0239) time: 3.1722 data: 0.0027 max mem: 19788 +Epoch: [26] [1000/2138] eta: 1:00:56 lr: 1.8851077640353683e-05 loss: 0.0203 (0.0239) time: 3.1491 data: 0.0026 max mem: 19788 +Epoch: [26] [1010/2138] eta: 1:00:22 lr: 1.884521325159151e-05 loss: 0.0225 (0.0239) time: 3.1117 data: 0.0023 max mem: 19788 +Epoch: [26] [1020/2138] eta: 0:59:50 lr: 1.883934866005314e-05 loss: 0.0248 (0.0239) time: 3.1333 data: 0.0021 max mem: 19788 +Epoch: [26] [1030/2138] eta: 0:59:17 lr: 1.8833483865661423e-05 loss: 0.0209 (0.0239) time: 3.1611 data: 0.0022 max mem: 19788 +Epoch: [26] [1040/2138] eta: 0:58:44 lr: 1.882761886833915e-05 loss: 0.0214 (0.0239) time: 3.1648 data: 0.0024 max mem: 19788 +Epoch: [26] [1050/2138] eta: 0:58:14 lr: 1.8821753668009056e-05 loss: 0.0232 (0.0239) time: 3.2612 data: 0.0026 max mem: 19788 +Epoch: [26] [1060/2138] eta: 0:57:41 lr: 1.8815888264593825e-05 loss: 0.0232 (0.0239) time: 3.2649 data: 0.0028 max mem: 19788 +Epoch: [26] [1070/2138] eta: 0:57:08 lr: 1.881002265801607e-05 loss: 0.0217 (0.0239) time: 3.1354 data: 0.0030 max mem: 19788 +Epoch: [26] [1080/2138] eta: 0:56:35 lr: 1.880415684819836e-05 loss: 0.0214 (0.0239) time: 3.1063 data: 0.0028 max mem: 19788 +Epoch: [26] [1090/2138] eta: 0:56:02 lr: 1.8798290835063205e-05 loss: 0.0214 (0.0239) time: 3.1366 data: 0.0026 max mem: 19788 +Epoch: [26] [1100/2138] eta: 0:55:30 lr: 1.8792424618533062e-05 loss: 0.0238 (0.0239) time: 3.1592 data: 0.0026 max mem: 19788 +Epoch: [26] [1110/2138] eta: 0:54:57 lr: 1.8786558198530316e-05 loss: 0.0225 (0.0239) time: 3.1421 data: 0.0029 max mem: 19788 +Epoch: [26] [1120/2138] eta: 0:54:24 lr: 1.8780691574977325e-05 loss: 0.0224 (0.0239) time: 3.1129 data: 0.0032 max mem: 19788 +Epoch: [26] [1130/2138] eta: 0:53:52 lr: 1.877482474779635e-05 loss: 0.0210 (0.0238) time: 3.1663 data: 0.0031 max mem: 19788 +Epoch: [26] [1140/2138] eta: 0:53:19 lr: 1.8768957716909644e-05 loss: 0.0213 (0.0239) time: 3.1549 data: 0.0028 max mem: 19788 +Epoch: [26] [1150/2138] eta: 0:52:47 lr: 1.8763090482239353e-05 loss: 0.0203 (0.0238) time: 3.1326 data: 0.0025 max mem: 19788 +Epoch: [26] [1160/2138] eta: 0:52:14 lr: 1.8757223043707605e-05 loss: 0.0187 (0.0238) time: 3.1426 data: 0.0024 max mem: 19788 +Epoch: [26] [1170/2138] eta: 0:51:43 lr: 1.875135540123645e-05 loss: 0.0216 (0.0238) time: 3.2398 data: 0.0027 max mem: 19788 +Epoch: [26] [1180/2138] eta: 0:51:12 lr: 1.874548755474789e-05 loss: 0.0230 (0.0238) time: 3.3509 data: 0.0025 max mem: 19788 +Epoch: [26] [1190/2138] eta: 0:50:39 lr: 1.8739619504163868e-05 loss: 0.0218 (0.0238) time: 3.2212 data: 0.0022 max mem: 19788 +Epoch: [26] [1200/2138] eta: 0:50:08 lr: 1.873375124940627e-05 loss: 0.0208 (0.0238) time: 3.2361 data: 0.0022 max mem: 19788 +Epoch: [26] [1210/2138] eta: 0:49:38 lr: 1.8727882790396917e-05 loss: 0.0214 (0.0238) time: 3.4197 data: 0.0023 max mem: 19788 +Epoch: [26] [1220/2138] eta: 0:49:06 lr: 1.8722014127057595e-05 loss: 0.0213 (0.0238) time: 3.3167 data: 0.0025 max mem: 19788 +Epoch: [26] [1230/2138] eta: 0:48:35 lr: 1.8716145259309997e-05 loss: 0.0207 (0.0238) time: 3.2368 data: 0.0027 max mem: 19788 +Epoch: [26] [1240/2138] eta: 0:48:04 lr: 1.8710276187075802e-05 loss: 0.0207 (0.0238) time: 3.3764 data: 0.0029 max mem: 19788 +Epoch: [26] [1250/2138] eta: 0:47:34 lr: 1.870440691027659e-05 loss: 0.0198 (0.0237) time: 3.4973 data: 0.0028 max mem: 19788 +Epoch: [26] [1260/2138] eta: 0:47:04 lr: 1.8698537428833925e-05 loss: 0.0193 (0.0237) time: 3.4795 data: 0.0026 max mem: 19788 +Epoch: [26] [1270/2138] eta: 0:46:30 lr: 1.8692667742669263e-05 loss: 0.0199 (0.0237) time: 3.2314 data: 0.0027 max mem: 19788 +Epoch: [26] [1280/2138] eta: 0:45:57 lr: 1.868679785170406e-05 loss: 0.0207 (0.0237) time: 3.0822 data: 0.0025 max mem: 19788 +Epoch: [26] [1290/2138] eta: 0:45:24 lr: 1.8680927755859666e-05 loss: 0.0227 (0.0237) time: 3.0337 data: 0.0023 max mem: 19788 +Epoch: [26] [1300/2138] eta: 0:44:50 lr: 1.86750574550574e-05 loss: 0.0227 (0.0237) time: 2.9748 data: 0.0022 max mem: 19788 +Epoch: [26] [1310/2138] eta: 0:44:17 lr: 1.8669186949218513e-05 loss: 0.0216 (0.0237) time: 2.9863 data: 0.0025 max mem: 19788 +Epoch: [26] [1320/2138] eta: 0:43:43 lr: 1.8663316238264207e-05 loss: 0.0205 (0.0237) time: 2.9834 data: 0.0023 max mem: 19788 +Epoch: [26] [1330/2138] eta: 0:43:10 lr: 1.8657445322115617e-05 loss: 0.0219 (0.0237) time: 2.9816 data: 0.0021 max mem: 19788 +Epoch: [26] [1340/2138] eta: 0:42:36 lr: 1.8651574200693813e-05 loss: 0.0230 (0.0237) time: 2.9781 data: 0.0022 max mem: 19788 +Epoch: [26] [1350/2138] eta: 0:42:03 lr: 1.864570287391984e-05 loss: 0.0254 (0.0237) time: 3.0078 data: 0.0026 max mem: 19788 +Epoch: [26] [1360/2138] eta: 0:41:30 lr: 1.8639831341714638e-05 loss: 0.0223 (0.0237) time: 3.0086 data: 0.0028 max mem: 19788 +Epoch: [26] [1370/2138] eta: 0:40:57 lr: 1.8633959603999136e-05 loss: 0.0223 (0.0237) time: 2.9692 data: 0.0030 max mem: 19788 +Epoch: [26] [1380/2138] eta: 0:40:23 lr: 1.8628087660694162e-05 loss: 0.0240 (0.0237) time: 2.9717 data: 0.0029 max mem: 19788 +Epoch: [26] [1390/2138] eta: 0:39:50 lr: 1.8622215511720525e-05 loss: 0.0217 (0.0237) time: 2.9838 data: 0.0027 max mem: 19788 +Epoch: [26] [1400/2138] eta: 0:39:17 lr: 1.861634315699894e-05 loss: 0.0206 (0.0237) time: 2.9839 data: 0.0027 max mem: 19788 +Epoch: [26] [1410/2138] eta: 0:38:44 lr: 1.861047059645009e-05 loss: 0.0196 (0.0237) time: 2.9725 data: 0.0028 max mem: 19788 +Epoch: [26] [1420/2138] eta: 0:38:11 lr: 1.8604597829994588e-05 loss: 0.0222 (0.0237) time: 2.9960 data: 0.0029 max mem: 19788 +Epoch: [26] [1430/2138] eta: 0:37:39 lr: 1.8598724857552992e-05 loss: 0.0231 (0.0238) time: 3.0928 data: 0.0027 max mem: 19788 +Epoch: [26] [1440/2138] eta: 0:37:06 lr: 1.8592851679045794e-05 loss: 0.0233 (0.0238) time: 3.0708 data: 0.0027 max mem: 19788 +Epoch: [26] [1450/2138] eta: 0:36:33 lr: 1.8586978294393446e-05 loss: 0.0226 (0.0238) time: 2.9789 data: 0.0028 max mem: 19788 +Epoch: [26] [1460/2138] eta: 0:36:00 lr: 1.858110470351631e-05 loss: 0.0221 (0.0238) time: 2.9737 data: 0.0025 max mem: 19788 +Epoch: [26] [1470/2138] eta: 0:35:28 lr: 1.857523090633473e-05 loss: 0.0196 (0.0238) time: 2.9794 data: 0.0024 max mem: 19788 +Epoch: [26] [1480/2138] eta: 0:34:55 lr: 1.8569356902768943e-05 loss: 0.0192 (0.0238) time: 2.9902 data: 0.0025 max mem: 19788 +Epoch: [26] [1490/2138] eta: 0:34:22 lr: 1.856348269273918e-05 loss: 0.0195 (0.0238) time: 2.9847 data: 0.0026 max mem: 19788 +Epoch: [26] [1500/2138] eta: 0:33:50 lr: 1.855760827616557e-05 loss: 0.0244 (0.0238) time: 3.0540 data: 0.0025 max mem: 19788 +Epoch: [26] [1510/2138] eta: 0:33:17 lr: 1.8551733652968206e-05 loss: 0.0232 (0.0238) time: 3.0548 data: 0.0027 max mem: 19788 +Epoch: [26] [1520/2138] eta: 0:32:45 lr: 1.854585882306711e-05 loss: 0.0219 (0.0238) time: 2.9885 data: 0.0029 max mem: 19788 +Epoch: [26] [1530/2138] eta: 0:32:12 lr: 1.8539983786382256e-05 loss: 0.0221 (0.0238) time: 2.9974 data: 0.0028 max mem: 19788 +Epoch: [26] [1540/2138] eta: 0:31:40 lr: 1.8534108542833547e-05 loss: 0.0203 (0.0237) time: 2.9860 data: 0.0027 max mem: 19788 +Epoch: [26] [1550/2138] eta: 0:31:07 lr: 1.8528233092340842e-05 loss: 0.0195 (0.0237) time: 2.9724 data: 0.0026 max mem: 19788 +Epoch: [26] [1560/2138] eta: 0:30:35 lr: 1.852235743482392e-05 loss: 0.0227 (0.0237) time: 2.9805 data: 0.0029 max mem: 19788 +Epoch: [26] [1570/2138] eta: 0:30:02 lr: 1.8516481570202525e-05 loss: 0.0231 (0.0237) time: 2.9760 data: 0.0032 max mem: 19788 +Epoch: [26] [1580/2138] eta: 0:29:30 lr: 1.8510605498396313e-05 loss: 0.0214 (0.0237) time: 2.9704 data: 0.0031 max mem: 19788 +Epoch: [26] [1590/2138] eta: 0:28:57 lr: 1.8504729219324916e-05 loss: 0.0228 (0.0237) time: 2.9805 data: 0.0029 max mem: 19788 +Epoch: [26] [1600/2138] eta: 0:28:25 lr: 1.8498852732907864e-05 loss: 0.0246 (0.0237) time: 2.9805 data: 0.0028 max mem: 19788 +Epoch: [26] [1610/2138] eta: 0:27:53 lr: 1.8492976039064673e-05 loss: 0.0249 (0.0237) time: 2.9875 data: 0.0028 max mem: 19788 +Epoch: [26] [1620/2138] eta: 0:27:20 lr: 1.8487099137714762e-05 loss: 0.0196 (0.0237) time: 2.9890 data: 0.0029 max mem: 19788 +Epoch: [26] [1630/2138] eta: 0:26:48 lr: 1.8481222028777503e-05 loss: 0.0201 (0.0237) time: 2.9730 data: 0.0029 max mem: 19788 +Epoch: [26] [1640/2138] eta: 0:26:16 lr: 1.847534471217222e-05 loss: 0.0224 (0.0237) time: 2.9743 data: 0.0027 max mem: 19788 +Epoch: [26] [1650/2138] eta: 0:25:44 lr: 1.8469467187818158e-05 loss: 0.0219 (0.0237) time: 3.0085 data: 0.0028 max mem: 19788 +Epoch: [26] [1660/2138] eta: 0:25:11 lr: 1.846358945563452e-05 loss: 0.0236 (0.0237) time: 2.9654 data: 0.0026 max mem: 19788 +Epoch: [26] [1670/2138] eta: 0:24:39 lr: 1.8457711515540428e-05 loss: 0.0214 (0.0237) time: 2.9391 data: 0.0023 max mem: 19788 +Epoch: [26] [1680/2138] eta: 0:24:07 lr: 1.8451833367454966e-05 loss: 0.0210 (0.0237) time: 2.9764 data: 0.0023 max mem: 19788 +Epoch: [26] [1690/2138] eta: 0:23:35 lr: 1.844595501129714e-05 loss: 0.0219 (0.0237) time: 2.9746 data: 0.0023 max mem: 19788 +Epoch: [26] [1700/2138] eta: 0:23:03 lr: 1.844007644698591e-05 loss: 0.0219 (0.0237) time: 2.9820 data: 0.0025 max mem: 19788 +Epoch: [26] [1710/2138] eta: 0:22:31 lr: 1.843419767444016e-05 loss: 0.0225 (0.0237) time: 2.9817 data: 0.0024 max mem: 19788 +Epoch: [26] [1720/2138] eta: 0:21:59 lr: 1.842831869357874e-05 loss: 0.0231 (0.0237) time: 2.9927 data: 0.0022 max mem: 19788 +Epoch: [26] [1730/2138] eta: 0:21:27 lr: 1.8422439504320403e-05 loss: 0.0209 (0.0237) time: 2.9911 data: 0.0024 max mem: 19788 +Epoch: [26] [1740/2138] eta: 0:20:55 lr: 1.8416560106583873e-05 loss: 0.0205 (0.0237) time: 2.9702 data: 0.0025 max mem: 19788 +Epoch: [26] [1750/2138] eta: 0:20:23 lr: 1.8410680500287794e-05 loss: 0.0219 (0.0237) time: 2.9613 data: 0.0023 max mem: 19788 +Epoch: [26] [1760/2138] eta: 0:19:51 lr: 1.8404800685350767e-05 loss: 0.0219 (0.0237) time: 2.9669 data: 0.0022 max mem: 19788 +Epoch: [26] [1770/2138] eta: 0:19:19 lr: 1.839892066169131e-05 loss: 0.0220 (0.0237) time: 2.9774 data: 0.0021 max mem: 19788 +Epoch: [26] [1780/2138] eta: 0:18:47 lr: 1.83930404292279e-05 loss: 0.0196 (0.0237) time: 2.9847 data: 0.0021 max mem: 19788 +Epoch: [26] [1790/2138] eta: 0:18:16 lr: 1.8387159987878938e-05 loss: 0.0210 (0.0237) time: 2.9850 data: 0.0023 max mem: 19788 +Epoch: [26] [1800/2138] eta: 0:17:44 lr: 1.8381279337562784e-05 loss: 0.0270 (0.0238) time: 2.9908 data: 0.0028 max mem: 19788 +Epoch: [26] [1810/2138] eta: 0:17:12 lr: 1.8375398478197707e-05 loss: 0.0270 (0.0238) time: 2.9878 data: 0.0028 max mem: 19788 +Epoch: [26] [1820/2138] eta: 0:16:40 lr: 1.8369517409701953e-05 loss: 0.0214 (0.0238) time: 2.9919 data: 0.0024 max mem: 19788 +Epoch: [26] [1830/2138] eta: 0:16:09 lr: 1.836363613199367e-05 loss: 0.0206 (0.0238) time: 2.9851 data: 0.0023 max mem: 19788 +Epoch: [26] [1840/2138] eta: 0:15:37 lr: 1.835775464499097e-05 loss: 0.0219 (0.0238) time: 2.9850 data: 0.0023 max mem: 19788 +Epoch: [26] [1850/2138] eta: 0:15:05 lr: 1.8351872948611892e-05 loss: 0.0226 (0.0238) time: 3.0053 data: 0.0026 max mem: 19788 +Epoch: [26] [1860/2138] eta: 0:14:33 lr: 1.8345991042774417e-05 loss: 0.0223 (0.0238) time: 2.9896 data: 0.0025 max mem: 19788 +Epoch: [26] [1870/2138] eta: 0:14:02 lr: 1.834010892739646e-05 loss: 0.0239 (0.0238) time: 2.9880 data: 0.0023 max mem: 19788 +Epoch: [26] [1880/2138] eta: 0:13:30 lr: 1.8334226602395896e-05 loss: 0.0204 (0.0238) time: 2.9904 data: 0.0024 max mem: 19788 +Epoch: [26] [1890/2138] eta: 0:12:59 lr: 1.8328344067690498e-05 loss: 0.0194 (0.0238) time: 2.9709 data: 0.0024 max mem: 19788 +Epoch: [26] [1900/2138] eta: 0:12:27 lr: 1.8322461323198018e-05 loss: 0.0198 (0.0238) time: 2.9910 data: 0.0025 max mem: 19788 +Epoch: [26] [1910/2138] eta: 0:11:55 lr: 1.831657836883612e-05 loss: 0.0205 (0.0238) time: 2.9935 data: 0.0024 max mem: 19788 +Epoch: [26] [1920/2138] eta: 0:11:24 lr: 1.831069520452242e-05 loss: 0.0209 (0.0238) time: 2.9748 data: 0.0022 max mem: 19788 +Epoch: [26] [1930/2138] eta: 0:10:52 lr: 1.8304811830174472e-05 loss: 0.0221 (0.0238) time: 2.9882 data: 0.0025 max mem: 19788 +Epoch: [26] [1940/2138] eta: 0:10:21 lr: 1.8298928245709752e-05 loss: 0.0227 (0.0238) time: 2.9898 data: 0.0024 max mem: 19788 +Epoch: [26] [1950/2138] eta: 0:09:49 lr: 1.8293044451045698e-05 loss: 0.0228 (0.0238) time: 2.9813 data: 0.0023 max mem: 19788 +Epoch: [26] [1960/2138] eta: 0:09:18 lr: 1.8287160446099667e-05 loss: 0.0229 (0.0238) time: 2.9755 data: 0.0026 max mem: 19788 +Epoch: [26] [1970/2138] eta: 0:08:46 lr: 1.828127623078896e-05 loss: 0.0229 (0.0238) time: 2.9612 data: 0.0027 max mem: 19788 +Epoch: [26] [1980/2138] eta: 0:08:15 lr: 1.8275391805030826e-05 loss: 0.0227 (0.0238) time: 2.9893 data: 0.0027 max mem: 19788 +Epoch: [26] [1990/2138] eta: 0:07:43 lr: 1.8269507168742435e-05 loss: 0.0222 (0.0238) time: 3.0008 data: 0.0027 max mem: 19788 +Epoch: [26] [2000/2138] eta: 0:07:12 lr: 1.82636223218409e-05 loss: 0.0206 (0.0238) time: 2.9732 data: 0.0027 max mem: 19788 +Epoch: [26] [2010/2138] eta: 0:06:40 lr: 1.825773726424329e-05 loss: 0.0217 (0.0238) time: 2.9783 data: 0.0026 max mem: 19788 +Epoch: [26] [2020/2138] eta: 0:06:09 lr: 1.8251851995866573e-05 loss: 0.0239 (0.0238) time: 2.9834 data: 0.0024 max mem: 19788 +Epoch: [26] [2030/2138] eta: 0:05:38 lr: 1.8245966516627697e-05 loss: 0.0238 (0.0238) time: 2.9905 data: 0.0027 max mem: 19788 +Epoch: [26] [2040/2138] eta: 0:05:06 lr: 1.8240080826443515e-05 loss: 0.0232 (0.0238) time: 2.9867 data: 0.0027 max mem: 19788 +Epoch: [26] [2050/2138] eta: 0:04:35 lr: 1.823419492523084e-05 loss: 0.0218 (0.0238) time: 2.9657 data: 0.0026 max mem: 19788 +Epoch: [26] [2060/2138] eta: 0:04:03 lr: 1.82283088129064e-05 loss: 0.0218 (0.0238) time: 2.9657 data: 0.0028 max mem: 19788 +Epoch: [26] [2070/2138] eta: 0:03:32 lr: 1.822242248938689e-05 loss: 0.0208 (0.0238) time: 2.9805 data: 0.0029 max mem: 19788 +Epoch: [26] [2080/2138] eta: 0:03:01 lr: 1.821653595458891e-05 loss: 0.0208 (0.0238) time: 2.9838 data: 0.0029 max mem: 19788 +Epoch: [26] [2090/2138] eta: 0:02:30 lr: 1.821064920842902e-05 loss: 0.0232 (0.0238) time: 2.9911 data: 0.0027 max mem: 19788 +Epoch: [26] [2100/2138] eta: 0:01:58 lr: 1.8204762250823706e-05 loss: 0.0232 (0.0237) time: 3.0403 data: 0.0025 max mem: 19788 +Epoch: [26] [2110/2138] eta: 0:01:27 lr: 1.8198875081689397e-05 loss: 0.0239 (0.0238) time: 3.1128 data: 0.0026 max mem: 19788 +Epoch: [26] [2120/2138] eta: 0:00:56 lr: 1.8192987700942455e-05 loss: 0.0277 (0.0238) time: 3.0992 data: 0.0027 max mem: 19788 +Epoch: [26] [2130/2138] eta: 0:00:25 lr: 1.8187100108499182e-05 loss: 0.0264 (0.0238) time: 3.0851 data: 0.0025 max mem: 19788 +Epoch: [26] Total time: 1:51:22 +Test: [ 0/21770] eta: 18:15:25 time: 3.0191 data: 2.8244 max mem: 19788 +Test: [ 100/21770] eta: 0:26:29 time: 0.0441 data: 0.0014 max mem: 19788 +Test: [ 200/21770] eta: 0:21:49 time: 0.0502 data: 0.0018 max mem: 19788 +Test: [ 300/21770] eta: 0:20:35 time: 0.0526 data: 0.0018 max mem: 19788 +Test: [ 400/21770] eta: 0:19:33 time: 0.0429 data: 0.0014 max mem: 19788 +Test: [ 500/21770] eta: 0:18:41 time: 0.0450 data: 0.0015 max mem: 19788 +Test: [ 600/21770] eta: 0:18:06 time: 0.0437 data: 0.0013 max mem: 19788 +Test: [ 700/21770] eta: 0:17:55 time: 0.0515 data: 0.0017 max mem: 19788 +Test: [ 800/21770] eta: 0:17:43 time: 0.0501 data: 0.0016 max mem: 19788 +Test: [ 900/21770] eta: 0:17:39 time: 0.0530 data: 0.0016 max mem: 19788 +Test: [ 1000/21770] eta: 0:17:25 time: 0.0444 data: 0.0016 max mem: 19788 +Test: [ 1100/21770] eta: 0:17:09 time: 0.0459 data: 0.0014 max mem: 19788 +Test: [ 1200/21770] eta: 0:16:55 time: 0.0435 data: 0.0016 max mem: 19788 +Test: [ 1300/21770] eta: 0:16:49 time: 0.0530 data: 0.0018 max mem: 19788 +Test: [ 1400/21770] eta: 0:16:36 time: 0.0435 data: 0.0017 max mem: 19788 +Test: [ 1500/21770] eta: 0:16:32 time: 0.0497 data: 0.0017 max mem: 19788 +Test: [ 1600/21770] eta: 0:16:25 time: 0.0475 data: 0.0016 max mem: 19788 +Test: [ 1700/21770] eta: 0:16:25 time: 0.0531 data: 0.0018 max mem: 19788 +Test: [ 1800/21770] eta: 0:16:17 time: 0.0427 data: 0.0014 max mem: 19788 +Test: [ 1900/21770] eta: 0:16:11 time: 0.0504 data: 0.0016 max mem: 19788 +Test: [ 2000/21770] eta: 0:16:02 time: 0.0473 data: 0.0016 max mem: 19788 +Test: [ 2100/21770] eta: 0:15:57 time: 0.0437 data: 0.0016 max mem: 19788 +Test: [ 2200/21770] eta: 0:15:54 time: 0.0540 data: 0.0016 max mem: 19788 +Test: [ 2300/21770] eta: 0:15:50 time: 0.0432 data: 0.0015 max mem: 19788 +Test: [ 2400/21770] eta: 0:15:45 time: 0.0473 data: 0.0015 max mem: 19788 +Test: [ 2500/21770] eta: 0:15:41 time: 0.0543 data: 0.0015 max mem: 19788 +Test: [ 2600/21770] eta: 0:15:35 time: 0.0437 data: 0.0016 max mem: 19788 +Test: [ 2700/21770] eta: 0:15:27 time: 0.0446 data: 0.0016 max mem: 19788 +Test: [ 2800/21770] eta: 0:15:21 time: 0.0540 data: 0.0019 max mem: 19788 +Test: [ 2900/21770] eta: 0:15:17 time: 0.0540 data: 0.0016 max mem: 19788 +Test: [ 3000/21770] eta: 0:15:14 time: 0.0567 data: 0.0018 max mem: 19788 +Test: [ 3100/21770] eta: 0:15:07 time: 0.0455 data: 0.0016 max mem: 19788 +Test: [ 3200/21770] eta: 0:15:04 time: 0.0529 data: 0.0019 max mem: 19788 +Test: [ 3300/21770] eta: 0:15:00 time: 0.0513 data: 0.0017 max mem: 19788 +Test: [ 3400/21770] eta: 0:14:55 time: 0.0447 data: 0.0014 max mem: 19788 +Test: [ 3500/21770] eta: 0:14:50 time: 0.0519 data: 0.0016 max mem: 19788 +Test: [ 3600/21770] eta: 0:14:45 time: 0.0444 data: 0.0014 max mem: 19788 +Test: [ 3700/21770] eta: 0:14:40 time: 0.0441 data: 0.0017 max mem: 19788 +Test: [ 3800/21770] eta: 0:14:34 time: 0.0491 data: 0.0017 max mem: 19788 +Test: [ 3900/21770] eta: 0:14:30 time: 0.0523 data: 0.0018 max mem: 19788 +Test: [ 4000/21770] eta: 0:14:23 time: 0.0508 data: 0.0016 max mem: 19788 +Test: [ 4100/21770] eta: 0:14:17 time: 0.0449 data: 0.0015 max mem: 19788 +Test: [ 4200/21770] eta: 0:14:14 time: 0.0531 data: 0.0018 max mem: 19788 +Test: [ 4300/21770] eta: 0:14:10 time: 0.0540 data: 0.0018 max mem: 19788 +Test: [ 4400/21770] eta: 0:14:06 time: 0.0549 data: 0.0018 max mem: 19788 +Test: [ 4500/21770] eta: 0:14:02 time: 0.0533 data: 0.0016 max mem: 19788 +Test: [ 4600/21770] eta: 0:13:57 time: 0.0475 data: 0.0018 max mem: 19788 +Test: [ 4700/21770] eta: 0:13:53 time: 0.0514 data: 0.0016 max mem: 19788 +Test: [ 4800/21770] eta: 0:13:46 time: 0.0451 data: 0.0015 max mem: 19788 +Test: [ 4900/21770] eta: 0:13:40 time: 0.0483 data: 0.0017 max mem: 19788 +Test: [ 5000/21770] eta: 0:13:36 time: 0.0460 data: 0.0016 max mem: 19788 +Test: [ 5100/21770] eta: 0:13:31 time: 0.0451 data: 0.0014 max mem: 19788 +Test: [ 5200/21770] eta: 0:13:26 time: 0.0540 data: 0.0018 max mem: 19788 +Test: [ 5300/21770] eta: 0:13:21 time: 0.0531 data: 0.0018 max mem: 19788 +Test: [ 5400/21770] eta: 0:13:18 time: 0.0539 data: 0.0018 max mem: 19788 +Test: [ 5500/21770] eta: 0:13:14 time: 0.0538 data: 0.0019 max mem: 19788 +Test: [ 5600/21770] eta: 0:13:08 time: 0.0452 data: 0.0014 max mem: 19788 +Test: [ 5700/21770] eta: 0:13:03 time: 0.0495 data: 0.0018 max mem: 19788 +Test: [ 5800/21770] eta: 0:12:58 time: 0.0496 data: 0.0017 max mem: 19788 +Test: [ 5900/21770] eta: 0:12:54 time: 0.0528 data: 0.0018 max mem: 19788 +Test: [ 6000/21770] eta: 0:12:50 time: 0.0516 data: 0.0017 max mem: 19788 +Test: [ 6100/21770] eta: 0:12:45 time: 0.0457 data: 0.0015 max mem: 19788 +Test: [ 6200/21770] eta: 0:12:40 time: 0.0534 data: 0.0019 max mem: 19788 +Test: [ 6300/21770] eta: 0:12:35 time: 0.0535 data: 0.0018 max mem: 19788 +Test: [ 6400/21770] eta: 0:12:31 time: 0.0490 data: 0.0017 max mem: 19788 +Test: [ 6500/21770] eta: 0:12:26 time: 0.0516 data: 0.0018 max mem: 19788 +Test: [ 6600/21770] eta: 0:12:21 time: 0.0441 data: 0.0014 max mem: 19788 +Test: [ 6700/21770] eta: 0:12:16 time: 0.0475 data: 0.0015 max mem: 19788 +Test: [ 6800/21770] eta: 0:12:12 time: 0.0499 data: 0.0015 max mem: 19788 +Test: [ 6900/21770] eta: 0:12:07 time: 0.0448 data: 0.0015 max mem: 19788 +Test: [ 7000/21770] eta: 0:12:02 time: 0.0530 data: 0.0018 max mem: 19788 +Test: [ 7100/21770] eta: 0:11:58 time: 0.0550 data: 0.0018 max mem: 19788 +Test: [ 7200/21770] eta: 0:11:53 time: 0.0495 data: 0.0018 max mem: 19788 +Test: [ 7300/21770] eta: 0:11:47 time: 0.0491 data: 0.0016 max mem: 19788 +Test: [ 7400/21770] eta: 0:11:43 time: 0.0489 data: 0.0018 max mem: 19788 +Test: [ 7500/21770] eta: 0:11:38 time: 0.0445 data: 0.0015 max mem: 19788 +Test: [ 7600/21770] eta: 0:11:33 time: 0.0535 data: 0.0018 max mem: 19788 +Test: [ 7700/21770] eta: 0:11:27 time: 0.0461 data: 0.0015 max mem: 19788 +Test: [ 7800/21770] eta: 0:11:22 time: 0.0504 data: 0.0017 max mem: 19788 +Test: [ 7900/21770] eta: 0:11:17 time: 0.0482 data: 0.0015 max mem: 19788 +Test: [ 8000/21770] eta: 0:11:11 time: 0.0458 data: 0.0016 max mem: 19788 +Test: [ 8100/21770] eta: 0:11:06 time: 0.0436 data: 0.0016 max mem: 19788 +Test: [ 8200/21770] eta: 0:11:02 time: 0.0485 data: 0.0017 max mem: 19788 +Test: [ 8300/21770] eta: 0:10:57 time: 0.0469 data: 0.0017 max mem: 19788 +Test: [ 8400/21770] eta: 0:10:52 time: 0.0528 data: 0.0019 max mem: 19788 +Test: [ 8500/21770] eta: 0:10:47 time: 0.0433 data: 0.0015 max mem: 19788 +Test: [ 8600/21770] eta: 0:10:42 time: 0.0439 data: 0.0015 max mem: 19788 +Test: [ 8700/21770] eta: 0:10:37 time: 0.0535 data: 0.0016 max mem: 19788 +Test: [ 8800/21770] eta: 0:10:32 time: 0.0435 data: 0.0014 max mem: 19788 +Test: [ 8900/21770] eta: 0:10:26 time: 0.0440 data: 0.0016 max mem: 19788 +Test: [ 9000/21770] eta: 0:10:21 time: 0.0454 data: 0.0016 max mem: 19788 +Test: [ 9100/21770] eta: 0:10:16 time: 0.0534 data: 0.0019 max mem: 19788 +Test: [ 9200/21770] eta: 0:10:12 time: 0.0478 data: 0.0015 max mem: 19788 +Test: [ 9300/21770] eta: 0:10:07 time: 0.0526 data: 0.0018 max mem: 19788 +Test: [ 9400/21770] eta: 0:10:02 time: 0.0438 data: 0.0014 max mem: 19788 +Test: [ 9500/21770] eta: 0:09:56 time: 0.0443 data: 0.0014 max mem: 19788 +Test: [ 9600/21770] eta: 0:09:51 time: 0.0440 data: 0.0016 max mem: 19788 +Test: [ 9700/21770] eta: 0:09:46 time: 0.0451 data: 0.0017 max mem: 19788 +Test: [ 9800/21770] eta: 0:09:42 time: 0.0540 data: 0.0016 max mem: 19788 +Test: [ 9900/21770] eta: 0:09:37 time: 0.0517 data: 0.0019 max mem: 19788 +Test: [10000/21770] eta: 0:09:32 time: 0.0530 data: 0.0018 max mem: 19788 +Test: [10100/21770] eta: 0:09:27 time: 0.0531 data: 0.0019 max mem: 19788 +Test: [10200/21770] eta: 0:09:22 time: 0.0445 data: 0.0016 max mem: 19788 +Test: [10300/21770] eta: 0:09:18 time: 0.0443 data: 0.0016 max mem: 19788 +Test: [10400/21770] eta: 0:09:12 time: 0.0449 data: 0.0016 max mem: 19788 +Test: [10500/21770] eta: 0:09:07 time: 0.0538 data: 0.0018 max mem: 19788 +Test: [10600/21770] eta: 0:09:03 time: 0.0465 data: 0.0015 max mem: 19788 +Test: [10700/21770] eta: 0:08:57 time: 0.0452 data: 0.0016 max mem: 19788 +Test: [10800/21770] eta: 0:08:52 time: 0.0445 data: 0.0016 max mem: 19788 +Test: [10900/21770] eta: 0:08:47 time: 0.0456 data: 0.0016 max mem: 19788 +Test: [11000/21770] eta: 0:08:42 time: 0.0549 data: 0.0017 max mem: 19788 +Test: [11100/21770] eta: 0:08:38 time: 0.0464 data: 0.0017 max mem: 19788 +Test: [11200/21770] eta: 0:08:33 time: 0.0542 data: 0.0018 max mem: 19788 +Test: [11300/21770] eta: 0:08:28 time: 0.0543 data: 0.0017 max mem: 19788 +Test: [11400/21770] eta: 0:08:24 time: 0.0494 data: 0.0017 max mem: 19788 +Test: [11500/21770] eta: 0:08:19 time: 0.0517 data: 0.0018 max mem: 19788 +Test: [11600/21770] eta: 0:08:15 time: 0.0565 data: 0.0019 max mem: 19788 +Test: [11700/21770] eta: 0:08:11 time: 0.0575 data: 0.0020 max mem: 19788 +Test: [11800/21770] eta: 0:08:06 time: 0.0569 data: 0.0020 max mem: 19788 +Test: [11900/21770] eta: 0:08:02 time: 0.0494 data: 0.0018 max mem: 19788 +Test: [12000/21770] eta: 0:07:57 time: 0.0481 data: 0.0017 max mem: 19788 +Test: [12100/21770] eta: 0:07:53 time: 0.0563 data: 0.0021 max mem: 19788 +Test: [12200/21770] eta: 0:07:48 time: 0.0499 data: 0.0016 max mem: 19788 +Test: [12300/21770] eta: 0:07:44 time: 0.0580 data: 0.0015 max mem: 19788 +Test: [12400/21770] eta: 0:07:39 time: 0.0505 data: 0.0017 max mem: 19788 +Test: [12500/21770] eta: 0:07:34 time: 0.0469 data: 0.0015 max mem: 19788 +Test: [12600/21770] eta: 0:07:29 time: 0.0503 data: 0.0017 max mem: 19788 +Test: [12700/21770] eta: 0:07:25 time: 0.0567 data: 0.0020 max mem: 19788 +Test: [12800/21770] eta: 0:07:20 time: 0.0558 data: 0.0019 max mem: 19788 +Test: [12900/21770] eta: 0:07:16 time: 0.0519 data: 0.0018 max mem: 19788 +Test: [13000/21770] eta: 0:07:10 time: 0.0461 data: 0.0018 max mem: 19788 +Test: [13100/21770] eta: 0:07:06 time: 0.0521 data: 0.0020 max mem: 19788 +Test: [13200/21770] eta: 0:07:01 time: 0.0611 data: 0.0019 max mem: 19788 +Test: [13300/21770] eta: 0:06:56 time: 0.0505 data: 0.0017 max mem: 19788 +Test: [13400/21770] eta: 0:06:52 time: 0.0578 data: 0.0019 max mem: 19788 +Test: [13500/21770] eta: 0:06:47 time: 0.0586 data: 0.0020 max mem: 19788 +Test: [13600/21770] eta: 0:06:42 time: 0.0475 data: 0.0016 max mem: 19788 +Test: [13700/21770] eta: 0:06:37 time: 0.0537 data: 0.0018 max mem: 19788 +Test: [13800/21770] eta: 0:06:32 time: 0.0455 data: 0.0014 max mem: 19788 +Test: [13900/21770] eta: 0:06:28 time: 0.0542 data: 0.0019 max mem: 19788 +Test: [14000/21770] eta: 0:06:23 time: 0.0544 data: 0.0017 max mem: 19788 +Test: [14100/21770] eta: 0:06:18 time: 0.0521 data: 0.0017 max mem: 19788 +Test: [14200/21770] eta: 0:06:13 time: 0.0584 data: 0.0018 max mem: 19788 +Test: [14300/21770] eta: 0:06:08 time: 0.0481 data: 0.0017 max mem: 19788 +Test: [14400/21770] eta: 0:06:03 time: 0.0485 data: 0.0018 max mem: 19788 +Test: [14500/21770] eta: 0:05:58 time: 0.0495 data: 0.0018 max mem: 19788 +Test: [14600/21770] eta: 0:05:54 time: 0.0453 data: 0.0017 max mem: 19788 +Test: [14700/21770] eta: 0:05:49 time: 0.0532 data: 0.0019 max mem: 19788 +Test: [14800/21770] eta: 0:05:44 time: 0.0506 data: 0.0017 max mem: 19788 +Test: [14900/21770] eta: 0:05:39 time: 0.0523 data: 0.0018 max mem: 19788 +Test: [15000/21770] eta: 0:05:34 time: 0.0532 data: 0.0019 max mem: 19788 +Test: [15100/21770] eta: 0:05:29 time: 0.0464 data: 0.0017 max mem: 19788 +Test: [15200/21770] eta: 0:05:24 time: 0.0527 data: 0.0018 max mem: 19788 +Test: [15300/21770] eta: 0:05:19 time: 0.0464 data: 0.0017 max mem: 19788 +Test: [15400/21770] eta: 0:05:14 time: 0.0554 data: 0.0018 max mem: 19788 +Test: [15500/21770] eta: 0:05:10 time: 0.0479 data: 0.0017 max mem: 19788 +Test: [15600/21770] eta: 0:05:05 time: 0.0576 data: 0.0017 max mem: 19788 +Test: [15700/21770] eta: 0:05:00 time: 0.0529 data: 0.0019 max mem: 19788 +Test: [15800/21770] eta: 0:04:55 time: 0.0492 data: 0.0017 max mem: 19788 +Test: [15900/21770] eta: 0:04:50 time: 0.0582 data: 0.0018 max mem: 19788 +Test: [16000/21770] eta: 0:04:45 time: 0.0450 data: 0.0015 max mem: 19788 +Test: [16100/21770] eta: 0:04:40 time: 0.0568 data: 0.0020 max mem: 19788 +Test: [16200/21770] eta: 0:04:35 time: 0.0513 data: 0.0018 max mem: 19788 +Test: [16300/21770] eta: 0:04:31 time: 0.0530 data: 0.0019 max mem: 19788 +Test: [16400/21770] eta: 0:04:26 time: 0.0555 data: 0.0020 max mem: 19788 +Test: [16500/21770] eta: 0:04:21 time: 0.0450 data: 0.0017 max mem: 19788 +Test: [16600/21770] eta: 0:04:16 time: 0.0567 data: 0.0018 max mem: 19788 +Test: [16700/21770] eta: 0:04:11 time: 0.0568 data: 0.0020 max mem: 19788 +Test: [16800/21770] eta: 0:04:06 time: 0.0458 data: 0.0019 max mem: 19788 +Test: [16900/21770] eta: 0:04:01 time: 0.0549 data: 0.0021 max mem: 19788 +Test: [17000/21770] eta: 0:03:56 time: 0.0534 data: 0.0019 max mem: 19788 +Test: [17100/21770] eta: 0:03:51 time: 0.0462 data: 0.0016 max mem: 19788 +Test: [17200/21770] eta: 0:03:46 time: 0.0466 data: 0.0017 max mem: 19788 +Test: [17300/21770] eta: 0:03:41 time: 0.0576 data: 0.0019 max mem: 19788 +Test: [17400/21770] eta: 0:03:36 time: 0.0556 data: 0.0015 max mem: 19788 +Test: [17500/21770] eta: 0:03:31 time: 0.0575 data: 0.0020 max mem: 19788 +Test: [17600/21770] eta: 0:03:27 time: 0.0528 data: 0.0018 max mem: 19788 +Test: [17700/21770] eta: 0:03:22 time: 0.0577 data: 0.0019 max mem: 19788 +Test: [17800/21770] eta: 0:03:17 time: 0.0454 data: 0.0016 max mem: 19788 +Test: [17900/21770] eta: 0:03:12 time: 0.0461 data: 0.0017 max mem: 19788 +Test: [18000/21770] eta: 0:03:07 time: 0.0530 data: 0.0017 max mem: 19788 +Test: [18100/21770] eta: 0:03:02 time: 0.0542 data: 0.0019 max mem: 19788 +Test: [18200/21770] eta: 0:02:57 time: 0.0443 data: 0.0014 max mem: 19788 +Test: [18300/21770] eta: 0:02:52 time: 0.0556 data: 0.0018 max mem: 19788 +Test: [18400/21770] eta: 0:02:47 time: 0.0457 data: 0.0016 max mem: 19788 +Test: [18500/21770] eta: 0:02:42 time: 0.0541 data: 0.0017 max mem: 19788 +Test: [18600/21770] eta: 0:02:37 time: 0.0460 data: 0.0015 max mem: 19788 +Test: [18700/21770] eta: 0:02:32 time: 0.0467 data: 0.0020 max mem: 19788 +Test: [18800/21770] eta: 0:02:27 time: 0.0472 data: 0.0018 max mem: 19788 +Test: [18900/21770] eta: 0:02:22 time: 0.0591 data: 0.0019 max mem: 19788 +Test: [19000/21770] eta: 0:02:17 time: 0.0602 data: 0.0019 max mem: 19788 +Test: [19100/21770] eta: 0:02:12 time: 0.0463 data: 0.0015 max mem: 19788 +Test: [19200/21770] eta: 0:02:07 time: 0.0581 data: 0.0020 max mem: 19788 +Test: [19300/21770] eta: 0:02:02 time: 0.0498 data: 0.0018 max mem: 19788 +Test: [19400/21770] eta: 0:01:57 time: 0.0457 data: 0.0017 max mem: 19788 +Test: [19500/21770] eta: 0:01:52 time: 0.0460 data: 0.0018 max mem: 19788 +Test: [19600/21770] eta: 0:01:47 time: 0.0490 data: 0.0017 max mem: 19788 +Test: [19700/21770] eta: 0:01:42 time: 0.0557 data: 0.0019 max mem: 19788 +Test: [19800/21770] eta: 0:01:38 time: 0.0495 data: 0.0018 max mem: 19788 +Test: [19900/21770] eta: 0:01:32 time: 0.0460 data: 0.0015 max mem: 19788 +Test: [20000/21770] eta: 0:01:27 time: 0.0519 data: 0.0017 max mem: 19788 +Test: [20100/21770] eta: 0:01:23 time: 0.0495 data: 0.0015 max mem: 19788 +Test: [20200/21770] eta: 0:01:18 time: 0.0547 data: 0.0019 max mem: 19788 +Test: [20300/21770] eta: 0:01:13 time: 0.0457 data: 0.0016 max mem: 19788 +Test: [20400/21770] eta: 0:01:08 time: 0.0462 data: 0.0015 max mem: 19788 +Test: [20500/21770] eta: 0:01:03 time: 0.0540 data: 0.0019 max mem: 19788 +Test: [20600/21770] eta: 0:00:58 time: 0.0497 data: 0.0016 max mem: 19788 +Test: [20700/21770] eta: 0:00:53 time: 0.0482 data: 0.0017 max mem: 19788 +Test: [20800/21770] eta: 0:00:48 time: 0.0584 data: 0.0019 max mem: 19788 +Test: [20900/21770] eta: 0:00:43 time: 0.0460 data: 0.0018 max mem: 19788 +Test: [21000/21770] eta: 0:00:38 time: 0.0561 data: 0.0018 max mem: 19788 +Test: [21100/21770] eta: 0:00:33 time: 0.0452 data: 0.0016 max mem: 19788 +Test: [21200/21770] eta: 0:00:28 time: 0.0590 data: 0.0020 max mem: 19788 +Test: [21300/21770] eta: 0:00:23 time: 0.0474 data: 0.0016 max mem: 19788 +Test: [21400/21770] eta: 0:00:18 time: 0.0493 data: 0.0016 max mem: 19788 +Test: [21500/21770] eta: 0:00:13 time: 0.0591 data: 0.0020 max mem: 19788 +Test: [21600/21770] eta: 0:00:08 time: 0.0497 data: 0.0019 max mem: 19788 +Test: [21700/21770] eta: 0:00:03 time: 0.0582 data: 0.0054 max mem: 19788 +Test: Total time: 0:18:08 +Final results: +Mean IoU is 64.15 + + precision@0.5 = 71.43 + precision@0.6 = 65.97 + precision@0.7 = 59.35 + precision@0.8 = 48.18 + precision@0.9 = 23.68 + overall IoU = 64.40 + mean IoU = 64.15 + +Mean accuracy for one-to-zero sample is 84.40 + +Average object IoU 0.6415403274167948 +Overall IoU 64.39644622802734 +Epoch: [27] [ 0/2138] eta: 4:10:06 lr: 1.818238988206691e-05 loss: 0.0287 (0.0287) time: 7.0190 data: 1.3938 max mem: 19788 +Epoch: [27] [ 10/2138] eta: 2:06:43 lr: 1.8176501908359112e-05 loss: 0.0214 (0.0229) time: 3.5731 data: 0.1294 max mem: 19788 +Epoch: [27] [ 20/2138] eta: 1:59:03 lr: 1.8170613722720275e-05 loss: 0.0214 (0.0222) time: 3.1904 data: 0.0021 max mem: 19788 +Epoch: [27] [ 30/2138] eta: 1:56:44 lr: 1.8164725325066475e-05 loss: 0.0233 (0.0237) time: 3.1852 data: 0.0019 max mem: 19788 +Epoch: [27] [ 40/2138] eta: 1:55:51 lr: 1.8158836715313694e-05 loss: 0.0237 (0.0236) time: 3.2515 data: 0.0024 max mem: 19788 +Epoch: [27] [ 50/2138] eta: 1:54:28 lr: 1.815294789337788e-05 loss: 0.0210 (0.0235) time: 3.2374 data: 0.0024 max mem: 19788 +Epoch: [27] [ 60/2138] eta: 1:53:17 lr: 1.8147058859174883e-05 loss: 0.0237 (0.0242) time: 3.1840 data: 0.0026 max mem: 19788 +Epoch: [27] [ 70/2138] eta: 1:52:52 lr: 1.814116961262052e-05 loss: 0.0226 (0.0239) time: 3.2376 data: 0.0029 max mem: 19788 +Epoch: [27] [ 80/2138] eta: 1:52:00 lr: 1.8135280153630527e-05 loss: 0.0219 (0.0240) time: 3.2492 data: 0.0027 max mem: 19788 +Epoch: [27] [ 90/2138] eta: 1:51:05 lr: 1.8129390482120588e-05 loss: 0.0197 (0.0236) time: 3.1842 data: 0.0025 max mem: 19788 +Epoch: [27] [ 100/2138] eta: 1:50:26 lr: 1.812350059800631e-05 loss: 0.0210 (0.0236) time: 3.1943 data: 0.0028 max mem: 19788 +Epoch: [27] [ 110/2138] eta: 1:50:22 lr: 1.8117610501203247e-05 loss: 0.0231 (0.0235) time: 3.3154 data: 0.0029 max mem: 19788 +Epoch: [27] [ 120/2138] eta: 1:49:48 lr: 1.8111720191626875e-05 loss: 0.0217 (0.0233) time: 3.3317 data: 0.0028 max mem: 19788 +Epoch: [27] [ 130/2138] eta: 1:49:04 lr: 1.810582966919263e-05 loss: 0.0228 (0.0233) time: 3.2244 data: 0.0028 max mem: 19788 +Epoch: [27] [ 140/2138] eta: 1:48:21 lr: 1.8099938933815857e-05 loss: 0.0226 (0.0233) time: 3.1885 data: 0.0023 max mem: 19788 +Epoch: [27] [ 150/2138] eta: 1:47:51 lr: 1.8094047985411854e-05 loss: 0.0205 (0.0232) time: 3.2287 data: 0.0024 max mem: 19788 +Epoch: [27] [ 160/2138] eta: 1:47:09 lr: 1.8088156823895846e-05 loss: 0.0203 (0.0232) time: 3.2279 data: 0.0028 max mem: 19788 +Epoch: [27] [ 170/2138] eta: 1:46:27 lr: 1.8082265449183004e-05 loss: 0.0203 (0.0231) time: 3.1731 data: 0.0029 max mem: 19788 +Epoch: [27] [ 180/2138] eta: 1:45:48 lr: 1.8076373861188418e-05 loss: 0.0206 (0.0231) time: 3.1759 data: 0.0031 max mem: 19788 +Epoch: [27] [ 190/2138] eta: 1:45:10 lr: 1.8070482059827133e-05 loss: 0.0205 (0.0230) time: 3.1870 data: 0.0034 max mem: 19788 +Epoch: [27] [ 200/2138] eta: 1:44:48 lr: 1.8064590045014105e-05 loss: 0.0210 (0.0229) time: 3.2683 data: 0.0031 max mem: 19788 +Epoch: [27] [ 210/2138] eta: 1:44:10 lr: 1.8058697816664254e-05 loss: 0.0221 (0.0230) time: 3.2672 data: 0.0028 max mem: 19788 +Epoch: [27] [ 220/2138] eta: 1:43:35 lr: 1.8052805374692412e-05 loss: 0.0221 (0.0229) time: 3.1951 data: 0.0030 max mem: 19788 +Epoch: [27] [ 230/2138] eta: 1:42:57 lr: 1.804691271901336e-05 loss: 0.0198 (0.0229) time: 3.1897 data: 0.0030 max mem: 19788 +Epoch: [27] [ 240/2138] eta: 1:42:23 lr: 1.8041019849541806e-05 loss: 0.0220 (0.0230) time: 3.1942 data: 0.0026 max mem: 19788 +Epoch: [27] [ 250/2138] eta: 1:41:46 lr: 1.80351267661924e-05 loss: 0.0213 (0.0229) time: 3.1959 data: 0.0022 max mem: 19788 +Epoch: [27] [ 260/2138] eta: 1:41:11 lr: 1.8029233468879713e-05 loss: 0.0202 (0.0229) time: 3.1866 data: 0.0027 max mem: 19788 +Epoch: [27] [ 270/2138] eta: 1:40:36 lr: 1.8023339957518276e-05 loss: 0.0214 (0.0228) time: 3.1936 data: 0.0031 max mem: 19788 +Epoch: [27] [ 280/2138] eta: 1:40:08 lr: 1.8017446232022528e-05 loss: 0.0227 (0.0228) time: 3.2488 data: 0.0027 max mem: 19788 +Epoch: [27] [ 290/2138] eta: 1:39:33 lr: 1.8011552292306853e-05 loss: 0.0228 (0.0228) time: 3.2500 data: 0.0025 max mem: 19788 +Epoch: [27] [ 300/2138] eta: 1:38:59 lr: 1.8005658138285577e-05 loss: 0.0218 (0.0228) time: 3.1932 data: 0.0024 max mem: 19788 +Epoch: [27] [ 310/2138] eta: 1:38:22 lr: 1.799976376987295e-05 loss: 0.0200 (0.0228) time: 3.1794 data: 0.0023 max mem: 19788 +Epoch: [27] [ 320/2138] eta: 1:37:51 lr: 1.7993869186983166e-05 loss: 0.0196 (0.0227) time: 3.2071 data: 0.0024 max mem: 19788 +Epoch: [27] [ 330/2138] eta: 1:37:17 lr: 1.7987974389530344e-05 loss: 0.0218 (0.0228) time: 3.2168 data: 0.0027 max mem: 19788 +Epoch: [27] [ 340/2138] eta: 1:36:43 lr: 1.7982079377428545e-05 loss: 0.0226 (0.0231) time: 3.1943 data: 0.0026 max mem: 19788 +Epoch: [27] [ 350/2138] eta: 1:36:24 lr: 1.7976184150591754e-05 loss: 0.0195 (0.0231) time: 3.3440 data: 0.0024 max mem: 19788 +Epoch: [27] [ 360/2138] eta: 1:35:59 lr: 1.797028870893391e-05 loss: 0.0224 (0.0231) time: 3.4412 data: 0.0026 max mem: 19788 +Epoch: [27] [ 370/2138] eta: 1:35:28 lr: 1.7964393052368857e-05 loss: 0.0234 (0.0231) time: 3.3253 data: 0.0028 max mem: 19788 +Epoch: [27] [ 380/2138] eta: 1:35:06 lr: 1.7958497180810403e-05 loss: 0.0206 (0.0231) time: 3.3667 data: 0.0024 max mem: 19788 +Epoch: [27] [ 390/2138] eta: 1:34:39 lr: 1.795260109417226e-05 loss: 0.0204 (0.0230) time: 3.4243 data: 0.0023 max mem: 19788 +Epoch: [27] [ 400/2138] eta: 1:34:06 lr: 1.794670479236811e-05 loss: 0.0222 (0.0231) time: 3.3018 data: 0.0025 max mem: 19788 +Epoch: [27] [ 410/2138] eta: 1:33:32 lr: 1.7940808275311537e-05 loss: 0.0210 (0.0231) time: 3.2202 data: 0.0026 max mem: 19788 +Epoch: [27] [ 420/2138] eta: 1:33:08 lr: 1.793491154291607e-05 loss: 0.0197 (0.0231) time: 3.3287 data: 0.0025 max mem: 19788 +Epoch: [27] [ 430/2138] eta: 1:32:35 lr: 1.7929014595095176e-05 loss: 0.0210 (0.0230) time: 3.3560 data: 0.0027 max mem: 19788 +Epoch: [27] [ 440/2138] eta: 1:32:07 lr: 1.7923117431762256e-05 loss: 0.0211 (0.0231) time: 3.3033 data: 0.0026 max mem: 19788 +Epoch: [27] [ 450/2138] eta: 1:31:36 lr: 1.7917220052830624e-05 loss: 0.0232 (0.0230) time: 3.3291 data: 0.0025 max mem: 19788 +Epoch: [27] [ 460/2138] eta: 1:31:04 lr: 1.7911322458213565e-05 loss: 0.0227 (0.0231) time: 3.2957 data: 0.0027 max mem: 19788 +Epoch: [27] [ 470/2138] eta: 1:30:32 lr: 1.7905424647824258e-05 loss: 0.0239 (0.0230) time: 3.2665 data: 0.0029 max mem: 19788 +Epoch: [27] [ 480/2138] eta: 1:29:57 lr: 1.7899526621575848e-05 loss: 0.0240 (0.0231) time: 3.2216 data: 0.0031 max mem: 19788 +Epoch: [27] [ 490/2138] eta: 1:29:22 lr: 1.7893628379381386e-05 loss: 0.0221 (0.0230) time: 3.1896 data: 0.0032 max mem: 19788 +Epoch: [27] [ 500/2138] eta: 1:28:48 lr: 1.788772992115388e-05 loss: 0.0202 (0.0230) time: 3.1932 data: 0.0032 max mem: 19788 +Epoch: [27] [ 510/2138] eta: 1:28:15 lr: 1.7881831246806248e-05 loss: 0.0193 (0.0230) time: 3.2296 data: 0.0031 max mem: 19788 +Epoch: [27] [ 520/2138] eta: 1:27:57 lr: 1.787593235625137e-05 loss: 0.0193 (0.0230) time: 3.4810 data: 0.0030 max mem: 19788 +Epoch: [27] [ 530/2138] eta: 1:27:26 lr: 1.7870033249402018e-05 loss: 0.0201 (0.0230) time: 3.5056 data: 0.0028 max mem: 19788 +Epoch: [27] [ 540/2138] eta: 1:26:54 lr: 1.786413392617094e-05 loss: 0.0208 (0.0230) time: 3.3088 data: 0.0028 max mem: 19788 +Epoch: [27] [ 550/2138] eta: 1:26:19 lr: 1.7858234386470787e-05 loss: 0.0220 (0.0229) time: 3.2458 data: 0.0027 max mem: 19788 +Epoch: [27] [ 560/2138] eta: 1:25:46 lr: 1.785233463021416e-05 loss: 0.0224 (0.0230) time: 3.2074 data: 0.0026 max mem: 19788 +Epoch: [27] [ 570/2138] eta: 1:25:14 lr: 1.784643465731358e-05 loss: 0.0224 (0.0229) time: 3.2654 data: 0.0026 max mem: 19788 +Epoch: [27] [ 580/2138] eta: 1:24:40 lr: 1.7840534467681513e-05 loss: 0.0207 (0.0230) time: 3.2514 data: 0.0028 max mem: 19788 +Epoch: [27] [ 590/2138] eta: 1:24:07 lr: 1.7834634061230345e-05 loss: 0.0218 (0.0229) time: 3.2267 data: 0.0031 max mem: 19788 +Epoch: [27] [ 600/2138] eta: 1:23:36 lr: 1.7828733437872396e-05 loss: 0.0220 (0.0229) time: 3.2726 data: 0.0029 max mem: 19788 +Epoch: [27] [ 610/2138] eta: 1:23:01 lr: 1.7822832597519927e-05 loss: 0.0219 (0.0229) time: 3.2436 data: 0.0028 max mem: 19788 +Epoch: [27] [ 620/2138] eta: 1:22:27 lr: 1.7816931540085124e-05 loss: 0.0220 (0.0230) time: 3.1993 data: 0.0027 max mem: 19788 +Epoch: [27] [ 630/2138] eta: 1:21:55 lr: 1.7811030265480117e-05 loss: 0.0233 (0.0230) time: 3.2460 data: 0.0029 max mem: 19788 +Epoch: [27] [ 640/2138] eta: 1:21:27 lr: 1.7805128773616942e-05 loss: 0.0216 (0.0230) time: 3.3592 data: 0.0031 max mem: 19788 +Epoch: [27] [ 650/2138] eta: 1:20:53 lr: 1.7799227064407597e-05 loss: 0.0216 (0.0230) time: 3.3220 data: 0.0030 max mem: 19788 +Epoch: [27] [ 660/2138] eta: 1:20:18 lr: 1.7793325137763993e-05 loss: 0.0212 (0.0231) time: 3.1907 data: 0.0030 max mem: 19788 +Epoch: [27] [ 670/2138] eta: 1:19:48 lr: 1.7787422993597984e-05 loss: 0.0214 (0.0230) time: 3.2770 data: 0.0030 max mem: 19788 +Epoch: [27] [ 680/2138] eta: 1:19:20 lr: 1.7781520631821337e-05 loss: 0.0204 (0.0230) time: 3.4105 data: 0.0028 max mem: 19788 +Epoch: [27] [ 690/2138] eta: 1:18:46 lr: 1.7775618052345778e-05 loss: 0.0212 (0.0230) time: 3.3348 data: 0.0025 max mem: 19788 +Epoch: [27] [ 700/2138] eta: 1:18:12 lr: 1.776971525508294e-05 loss: 0.0214 (0.0230) time: 3.2112 data: 0.0024 max mem: 19788 +Epoch: [27] [ 710/2138] eta: 1:17:39 lr: 1.7763812239944404e-05 loss: 0.0201 (0.0230) time: 3.2065 data: 0.0026 max mem: 19788 +Epoch: [27] [ 720/2138] eta: 1:17:07 lr: 1.775790900684167e-05 loss: 0.0204 (0.0229) time: 3.2694 data: 0.0027 max mem: 19788 +Epoch: [27] [ 730/2138] eta: 1:16:33 lr: 1.775200555568619e-05 loss: 0.0206 (0.0229) time: 3.2448 data: 0.0026 max mem: 19788 +Epoch: [27] [ 740/2138] eta: 1:16:00 lr: 1.7746101886389312e-05 loss: 0.0250 (0.0229) time: 3.2264 data: 0.0025 max mem: 19788 +Epoch: [27] [ 750/2138] eta: 1:15:27 lr: 1.7740197998862355e-05 loss: 0.0250 (0.0230) time: 3.2596 data: 0.0024 max mem: 19788 +Epoch: [27] [ 760/2138] eta: 1:14:57 lr: 1.7734293893016534e-05 loss: 0.0251 (0.0230) time: 3.3235 data: 0.0026 max mem: 19788 +Epoch: [27] [ 770/2138] eta: 1:14:23 lr: 1.7728389568763025e-05 loss: 0.0219 (0.0230) time: 3.2969 data: 0.0028 max mem: 19788 +Epoch: [27] [ 780/2138] eta: 1:13:50 lr: 1.772248502601291e-05 loss: 0.0235 (0.0230) time: 3.1981 data: 0.0026 max mem: 19788 +Epoch: [27] [ 790/2138] eta: 1:13:16 lr: 1.7716580264677228e-05 loss: 0.0223 (0.0229) time: 3.1885 data: 0.0024 max mem: 19788 +Epoch: [27] [ 800/2138] eta: 1:12:42 lr: 1.7710675284666914e-05 loss: 0.0218 (0.0229) time: 3.1961 data: 0.0026 max mem: 19788 +Epoch: [27] [ 810/2138] eta: 1:12:12 lr: 1.770477008589287e-05 loss: 0.0229 (0.0229) time: 3.3061 data: 0.0025 max mem: 19788 +Epoch: [27] [ 820/2138] eta: 1:11:40 lr: 1.76988646682659e-05 loss: 0.0219 (0.0229) time: 3.3614 data: 0.0023 max mem: 19788 +Epoch: [27] [ 830/2138] eta: 1:11:10 lr: 1.769295903169676e-05 loss: 0.0205 (0.0229) time: 3.3872 data: 0.0023 max mem: 19788 +Epoch: [27] [ 840/2138] eta: 1:10:42 lr: 1.7687053176096124e-05 loss: 0.0192 (0.0229) time: 3.4749 data: 0.0027 max mem: 19788 +Epoch: [27] [ 850/2138] eta: 1:10:11 lr: 1.7681147101374605e-05 loss: 0.0203 (0.0229) time: 3.4463 data: 0.0031 max mem: 19788 +Epoch: [27] [ 860/2138] eta: 1:09:38 lr: 1.7675240807442725e-05 loss: 0.0204 (0.0229) time: 3.3139 data: 0.0026 max mem: 19788 +Epoch: [27] [ 870/2138] eta: 1:09:07 lr: 1.7669334294210975e-05 loss: 0.0203 (0.0229) time: 3.3132 data: 0.0027 max mem: 19788 +Epoch: [27] [ 880/2138] eta: 1:08:33 lr: 1.766342756158973e-05 loss: 0.0197 (0.0228) time: 3.3016 data: 0.0031 max mem: 19788 +Epoch: [27] [ 890/2138] eta: 1:08:00 lr: 1.7657520609489336e-05 loss: 0.0197 (0.0228) time: 3.2171 data: 0.0031 max mem: 19788 +Epoch: [27] [ 900/2138] eta: 1:07:28 lr: 1.7651613437820046e-05 loss: 0.0210 (0.0228) time: 3.2975 data: 0.0030 max mem: 19788 +Epoch: [27] [ 910/2138] eta: 1:06:59 lr: 1.7645706046492045e-05 loss: 0.0211 (0.0228) time: 3.4448 data: 0.0028 max mem: 19788 +Epoch: [27] [ 920/2138] eta: 1:06:28 lr: 1.7639798435415458e-05 loss: 0.0197 (0.0228) time: 3.4390 data: 0.0028 max mem: 19788 +Epoch: [27] [ 930/2138] eta: 1:05:57 lr: 1.7633890604500323e-05 loss: 0.0224 (0.0228) time: 3.4127 data: 0.0029 max mem: 19788 +Epoch: [27] [ 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19788 +Epoch: [27] [1020/2138] eta: 1:01:03 lr: 1.7580710218652797e-05 loss: 0.0183 (0.0228) time: 3.2369 data: 0.0028 max mem: 19788 +Epoch: [27] [1030/2138] eta: 1:00:29 lr: 1.7574800184389372e-05 loss: 0.0202 (0.0227) time: 3.1414 data: 0.0027 max mem: 19788 +Epoch: [27] [1040/2138] eta: 0:59:55 lr: 1.756888992929328e-05 loss: 0.0212 (0.0227) time: 3.1637 data: 0.0030 max mem: 19788 +Epoch: [27] [1050/2138] eta: 0:59:19 lr: 1.756297945327371e-05 loss: 0.0220 (0.0228) time: 3.0799 data: 0.0031 max mem: 19788 +Epoch: [27] [1060/2138] eta: 0:58:45 lr: 1.7557068756239798e-05 loss: 0.0220 (0.0228) time: 3.0566 data: 0.0030 max mem: 19788 +Epoch: [27] [1070/2138] eta: 0:58:10 lr: 1.7551157838100586e-05 loss: 0.0230 (0.0228) time: 3.0874 data: 0.0026 max mem: 19788 +Epoch: [27] [1080/2138] eta: 0:57:36 lr: 1.754524669876508e-05 loss: 0.0230 (0.0228) time: 3.1068 data: 0.0025 max mem: 19788 +Epoch: [27] [1090/2138] eta: 0:57:02 lr: 1.7539335338142172e-05 loss: 0.0221 (0.0227) time: 3.1157 data: 0.0027 max mem: 19788 +Epoch: [27] [1100/2138] eta: 0:56:27 lr: 1.753342375614072e-05 loss: 0.0226 (0.0228) time: 3.0620 data: 0.0024 max mem: 19788 +Epoch: [27] [1110/2138] eta: 0:55:52 lr: 1.752751195266948e-05 loss: 0.0224 (0.0228) time: 3.0246 data: 0.0023 max mem: 19788 +Epoch: [27] [1120/2138] eta: 0:55:19 lr: 1.752159992763716e-05 loss: 0.0213 (0.0228) time: 3.1050 data: 0.0026 max mem: 19788 +Epoch: [27] [1130/2138] eta: 0:54:44 lr: 1.7515687680952382e-05 loss: 0.0217 (0.0227) time: 3.1053 data: 0.0027 max mem: 19788 +Epoch: [27] [1140/2138] eta: 0:54:10 lr: 1.75097752125237e-05 loss: 0.0217 (0.0227) time: 3.0353 data: 0.0027 max mem: 19788 +Epoch: [27] [1150/2138] eta: 0:53:37 lr: 1.7503862522259593e-05 loss: 0.0191 (0.0227) time: 3.1363 data: 0.0027 max mem: 19788 +Epoch: [27] [1160/2138] eta: 0:53:05 lr: 1.7497949610068482e-05 loss: 0.0186 (0.0227) time: 3.2837 data: 0.0027 max mem: 19788 +Epoch: [27] [1170/2138] eta: 0:52:31 lr: 1.7492036475858688e-05 loss: 0.0206 (0.0227) time: 3.2149 data: 0.0028 max mem: 19788 +Epoch: [27] [1180/2138] eta: 0:51:57 lr: 1.7486123119538492e-05 loss: 0.0210 (0.0227) time: 3.0585 data: 0.0025 max mem: 19788 +Epoch: [27] [1190/2138] eta: 0:51:22 lr: 1.7480209541016078e-05 loss: 0.0192 (0.0227) time: 3.0317 data: 0.0025 max mem: 19788 +Epoch: [27] [1200/2138] eta: 0:50:48 lr: 1.747429574019957e-05 loss: 0.0192 (0.0226) time: 3.0321 data: 0.0029 max mem: 19788 +Epoch: [27] [1210/2138] eta: 0:50:14 lr: 1.7468381716997013e-05 loss: 0.0235 (0.0227) time: 3.0397 data: 0.0030 max mem: 19788 +Epoch: [27] [1220/2138] eta: 0:49:41 lr: 1.7462467471316383e-05 loss: 0.0213 (0.0226) time: 3.0805 data: 0.0028 max mem: 19788 +Epoch: [27] [1230/2138] eta: 0:49:10 lr: 1.745655300306559e-05 loss: 0.0188 (0.0226) time: 3.2856 data: 0.0027 max mem: 19788 +Epoch: [27] [1240/2138] eta: 0:48:37 lr: 1.7450638312152447e-05 loss: 0.0202 (0.0226) time: 3.3456 data: 0.0027 max mem: 19788 +Epoch: [27] [1250/2138] eta: 0:48:05 lr: 1.7444723398484735e-05 loss: 0.0202 (0.0226) time: 3.2957 data: 0.0026 max mem: 19788 +Epoch: [27] [1260/2138] eta: 0:47:31 lr: 1.743880826197011e-05 loss: 0.0195 (0.0226) time: 3.1551 data: 0.0025 max mem: 19788 +Epoch: [27] [1270/2138] eta: 0:46:59 lr: 1.7432892902516202e-05 loss: 0.0198 (0.0226) time: 3.1311 data: 0.0025 max mem: 19788 +Epoch: [27] [1280/2138] eta: 0:46:28 lr: 1.7426977320030547e-05 loss: 0.0218 (0.0226) time: 3.3885 data: 0.0024 max mem: 19788 +Epoch: [27] [1290/2138] eta: 0:45:56 lr: 1.7421061514420603e-05 loss: 0.0218 (0.0226) time: 3.3898 data: 0.0024 max mem: 19788 +Epoch: [27] [1300/2138] eta: 0:45:23 lr: 1.741514548559376e-05 loss: 0.0223 (0.0226) time: 3.2662 data: 0.0028 max mem: 19788 +Epoch: [27] [1310/2138] eta: 0:44:50 lr: 1.740922923345735e-05 loss: 0.0205 (0.0226) time: 3.1925 data: 0.0029 max mem: 19788 +Epoch: [27] [1320/2138] eta: 0:44:19 lr: 1.74033127579186e-05 loss: 0.0207 (0.0226) time: 3.3393 data: 0.0027 max mem: 19788 +Epoch: [27] [1330/2138] eta: 0:43:47 lr: 1.739739605888469e-05 loss: 0.0209 (0.0226) time: 3.3872 data: 0.0026 max mem: 19788 +Epoch: [27] [1340/2138] eta: 0:43:13 lr: 1.7391479136262712e-05 loss: 0.0222 (0.0226) time: 3.1965 data: 0.0027 max mem: 19788 +Epoch: [27] [1350/2138] eta: 0:42:42 lr: 1.7385561989959696e-05 loss: 0.0247 (0.0226) time: 3.3124 data: 0.0028 max mem: 19788 +Epoch: [27] [1360/2138] eta: 0:42:12 lr: 1.7379644619882583e-05 loss: 0.0236 (0.0226) time: 3.5497 data: 0.0026 max mem: 19788 +Epoch: [27] [1370/2138] eta: 0:41:39 lr: 1.7373727025938256e-05 loss: 0.0220 (0.0226) time: 3.3817 data: 0.0024 max mem: 19788 +Epoch: [27] [1380/2138] eta: 0:41:05 lr: 1.7367809208033506e-05 loss: 0.0226 (0.0226) time: 3.1405 data: 0.0024 max mem: 19788 +Epoch: [27] [1390/2138] eta: 0:40:33 lr: 1.7361891166075076e-05 loss: 0.0221 (0.0226) time: 3.2049 data: 0.0028 max mem: 19788 +Epoch: [27] [1400/2138] eta: 0:40:01 lr: 1.7355972899969604e-05 loss: 0.0201 (0.0226) time: 3.2998 data: 0.0029 max mem: 19788 +Epoch: [27] [1410/2138] eta: 0:39:27 lr: 1.7350054409623682e-05 loss: 0.0202 (0.0226) time: 3.1834 data: 0.0026 max mem: 19788 +Epoch: [27] [1420/2138] eta: 0:38:54 lr: 1.73441356949438e-05 loss: 0.0219 (0.0226) time: 3.1063 data: 0.0026 max mem: 19788 +Epoch: [27] [1430/2138] eta: 0:38:21 lr: 1.7338216755836403e-05 loss: 0.0225 (0.0226) time: 3.1162 data: 0.0028 max mem: 19788 +Epoch: [27] [1440/2138] eta: 0:37:48 lr: 1.7332297592207834e-05 loss: 0.0229 (0.0226) time: 3.0891 data: 0.0028 max mem: 19788 +Epoch: [27] [1450/2138] eta: 0:37:15 lr: 1.7326378203964382e-05 loss: 0.0221 (0.0227) time: 3.1625 data: 0.0027 max mem: 19788 +Epoch: [27] [1460/2138] eta: 0:36:43 lr: 1.7320458591012248e-05 loss: 0.0219 (0.0227) time: 3.2735 data: 0.0027 max mem: 19788 +Epoch: [27] [1470/2138] eta: 0:36:10 lr: 1.731453875325757e-05 loss: 0.0196 (0.0227) time: 3.1928 data: 0.0025 max mem: 19788 +Epoch: [27] [1480/2138] eta: 0:35:36 lr: 1.7308618690606397e-05 loss: 0.0186 (0.0227) time: 3.0425 data: 0.0024 max mem: 19788 +Epoch: [27] [1490/2138] eta: 0:35:03 lr: 1.7302698402964714e-05 loss: 0.0186 (0.0227) time: 3.1136 data: 0.0027 max mem: 19788 +Epoch: [27] [1500/2138] eta: 0:34:31 lr: 1.729677789023843e-05 loss: 0.0239 (0.0227) time: 3.2116 data: 0.0026 max mem: 19788 +Epoch: [27] [1510/2138] eta: 0:33:58 lr: 1.729085715233337e-05 loss: 0.0221 (0.0227) time: 3.1543 data: 0.0023 max mem: 19788 +Epoch: [27] [1520/2138] eta: 0:33:25 lr: 1.7284936189155298e-05 loss: 0.0215 (0.0227) time: 3.1103 data: 0.0022 max mem: 19788 +Epoch: [27] [1530/2138] eta: 0:32:52 lr: 1.7279015000609883e-05 loss: 0.0215 (0.0227) time: 3.1653 data: 0.0024 max mem: 19788 +Epoch: [27] [1540/2138] eta: 0:32:19 lr: 1.7273093586602747e-05 loss: 0.0206 (0.0227) time: 3.1762 data: 0.0026 max mem: 19788 +Epoch: [27] [1550/2138] eta: 0:31:47 lr: 1.72671719470394e-05 loss: 0.0203 (0.0227) time: 3.1752 data: 0.0026 max mem: 19788 +Epoch: [27] [1560/2138] eta: 0:31:14 lr: 1.7261250081825314e-05 loss: 0.0232 (0.0227) time: 3.1309 data: 0.0029 max mem: 19788 +Epoch: [27] [1570/2138] eta: 0:30:41 lr: 1.7255327990865858e-05 loss: 0.0225 (0.0227) time: 3.1323 data: 0.0028 max mem: 19788 +Epoch: [27] [1580/2138] eta: 0:30:08 lr: 1.7249405674066338e-05 loss: 0.0225 (0.0227) time: 3.1074 data: 0.0029 max mem: 19788 +Epoch: [27] [1590/2138] eta: 0:29:35 lr: 1.7243483131331976e-05 loss: 0.0238 (0.0227) time: 3.0732 data: 0.0030 max mem: 19788 +Epoch: [27] [1600/2138] eta: 0:29:02 lr: 1.723756036256793e-05 loss: 0.0245 (0.0227) time: 3.1389 data: 0.0031 max mem: 19788 +Epoch: [27] [1610/2138] eta: 0:28:30 lr: 1.723163736767927e-05 loss: 0.0252 (0.0227) time: 3.1719 data: 0.0031 max mem: 19788 +Epoch: [27] [1620/2138] eta: 0:27:57 lr: 1.7225714146571e-05 loss: 0.0194 (0.0227) time: 3.1311 data: 0.0029 max mem: 19788 +Epoch: [27] [1630/2138] eta: 0:27:24 lr: 1.7219790699148032e-05 loss: 0.0193 (0.0227) time: 3.1454 data: 0.0027 max mem: 19788 +Epoch: [27] [1640/2138] eta: 0:26:52 lr: 1.7213867025315224e-05 loss: 0.0231 (0.0227) time: 3.1720 data: 0.0026 max mem: 19788 +Epoch: [27] [1650/2138] eta: 0:26:20 lr: 1.7207943124977336e-05 loss: 0.0233 (0.0227) time: 3.2160 data: 0.0023 max mem: 19788 +Epoch: [27] [1660/2138] eta: 0:25:47 lr: 1.7202018998039072e-05 loss: 0.0241 (0.0227) time: 3.2876 data: 0.0024 max mem: 19788 +Epoch: [27] [1670/2138] eta: 0:25:15 lr: 1.7196094644405034e-05 loss: 0.0202 (0.0227) time: 3.2061 data: 0.0024 max mem: 19788 +Epoch: [27] [1680/2138] eta: 0:24:43 lr: 1.719017006397978e-05 loss: 0.0198 (0.0227) time: 3.2710 data: 0.0023 max mem: 19788 +Epoch: [27] [1690/2138] eta: 0:24:10 lr: 1.7184245256667755e-05 loss: 0.0198 (0.0227) time: 3.3183 data: 0.0028 max mem: 19788 +Epoch: [27] [1700/2138] eta: 0:23:38 lr: 1.717832022237336e-05 loss: 0.0198 (0.0227) time: 3.2876 data: 0.0029 max mem: 19788 +Epoch: [27] [1710/2138] eta: 0:23:05 lr: 1.7172394961000897e-05 loss: 0.0209 (0.0227) time: 3.2259 data: 0.0028 max mem: 19788 +Epoch: [27] [1720/2138] eta: 0:22:33 lr: 1.7166469472454603e-05 loss: 0.0236 (0.0227) time: 3.0916 data: 0.0031 max mem: 19788 +Epoch: [27] [1730/2138] eta: 0:22:00 lr: 1.7160543756638625e-05 loss: 0.0206 (0.0226) time: 3.0388 data: 0.0030 max mem: 19788 +Epoch: [27] [1740/2138] eta: 0:21:27 lr: 1.7154617813457052e-05 loss: 0.0202 (0.0227) time: 3.0971 data: 0.0026 max mem: 19788 +Epoch: [27] [1750/2138] eta: 0:20:55 lr: 1.7148691642813876e-05 loss: 0.0220 (0.0227) time: 3.2347 data: 0.0026 max mem: 19788 +Epoch: [27] [1760/2138] eta: 0:20:23 lr: 1.7142765244613024e-05 loss: 0.0220 (0.0226) time: 3.2712 data: 0.0027 max mem: 19788 +Epoch: [27] [1770/2138] eta: 0:19:50 lr: 1.713683861875834e-05 loss: 0.0207 (0.0226) time: 3.2309 data: 0.0027 max mem: 19788 +Epoch: [27] [1780/2138] eta: 0:19:18 lr: 1.713091176515359e-05 loss: 0.0182 (0.0226) time: 3.3394 data: 0.0025 max mem: 19788 +Epoch: [27] [1790/2138] eta: 0:18:47 lr: 1.7124984683702473e-05 loss: 0.0186 (0.0226) time: 3.4759 data: 0.0023 max mem: 19788 +Epoch: [27] [1800/2138] eta: 0:18:14 lr: 1.71190573743086e-05 loss: 0.0244 (0.0227) time: 3.2626 data: 0.0023 max mem: 19788 +Epoch: [27] [1810/2138] eta: 0:17:41 lr: 1.7113129836875497e-05 loss: 0.0236 (0.0227) time: 3.0962 data: 0.0023 max mem: 19788 +Epoch: [27] [1820/2138] eta: 0:17:08 lr: 1.7107202071306625e-05 loss: 0.0203 (0.0227) time: 3.0771 data: 0.0024 max mem: 19788 +Epoch: [27] [1830/2138] eta: 0:16:36 lr: 1.710127407750537e-05 loss: 0.0197 (0.0226) time: 3.0279 data: 0.0029 max mem: 19788 +Epoch: [27] [1840/2138] eta: 0:16:03 lr: 1.7095345855375018e-05 loss: 0.0217 (0.0227) time: 3.0971 data: 0.0029 max mem: 19788 +Epoch: [27] [1850/2138] eta: 0:15:31 lr: 1.7089417404818807e-05 loss: 0.0231 (0.0227) time: 3.0747 data: 0.0025 max mem: 19788 +Epoch: [27] [1860/2138] eta: 0:14:58 lr: 1.708348872573987e-05 loss: 0.0229 (0.0227) time: 2.9950 data: 0.0028 max mem: 19788 +Epoch: [27] [1870/2138] eta: 0:14:25 lr: 1.707755981804128e-05 loss: 0.0214 (0.0227) time: 3.0493 data: 0.0029 max mem: 19788 +Epoch: [27] [1880/2138] eta: 0:13:53 lr: 1.7071630681626017e-05 loss: 0.0194 (0.0226) time: 3.1829 data: 0.0027 max mem: 19788 +Epoch: [27] [1890/2138] eta: 0:13:21 lr: 1.7065701316397002e-05 loss: 0.0180 (0.0226) time: 3.2154 data: 0.0029 max mem: 19788 +Epoch: [27] [1900/2138] eta: 0:12:48 lr: 1.7059771722257045e-05 loss: 0.0210 (0.0226) time: 3.1731 data: 0.0027 max mem: 19788 +Epoch: [27] [1910/2138] eta: 0:12:16 lr: 1.7053841899108917e-05 loss: 0.0206 (0.0226) time: 3.0838 data: 0.0026 max mem: 19788 +Epoch: [27] [1920/2138] eta: 0:11:43 lr: 1.7047911846855274e-05 loss: 0.0206 (0.0226) time: 2.9948 data: 0.0024 max mem: 19788 +Epoch: [27] [1930/2138] eta: 0:11:11 lr: 1.7041981565398723e-05 loss: 0.0216 (0.0226) time: 2.9988 data: 0.0022 max mem: 19788 +Epoch: [27] [1940/2138] eta: 0:10:38 lr: 1.7036051054641767e-05 loss: 0.0233 (0.0226) time: 3.0011 data: 0.0023 max mem: 19788 +Epoch: [27] [1950/2138] eta: 0:10:06 lr: 1.703012031448685e-05 loss: 0.0238 (0.0226) time: 3.0531 data: 0.0025 max mem: 19788 +Epoch: [27] [1960/2138] eta: 0:09:33 lr: 1.7024189344836317e-05 loss: 0.0236 (0.0226) time: 3.0880 data: 0.0025 max mem: 19788 +Epoch: [27] [1970/2138] eta: 0:09:01 lr: 1.7018258145592456e-05 loss: 0.0189 (0.0226) time: 3.0956 data: 0.0025 max mem: 19788 +Epoch: [27] [1980/2138] eta: 0:08:29 lr: 1.701232671665745e-05 loss: 0.0218 (0.0226) time: 3.3080 data: 0.0026 max mem: 19788 +Epoch: [27] [1990/2138] eta: 0:07:57 lr: 1.700639505793343e-05 loss: 0.0213 (0.0227) time: 3.2797 data: 0.0026 max mem: 19788 +Epoch: [27] [2000/2138] eta: 0:07:24 lr: 1.700046316932242e-05 loss: 0.0196 (0.0227) time: 3.0472 data: 0.0024 max mem: 19788 +Epoch: [27] [2010/2138] eta: 0:06:52 lr: 1.6994531050726394e-05 loss: 0.0217 (0.0227) time: 3.0972 data: 0.0024 max mem: 19788 +Epoch: [27] [2020/2138] eta: 0:06:20 lr: 1.6988598702047215e-05 loss: 0.0226 (0.0227) time: 3.1740 data: 0.0026 max mem: 19788 +Epoch: [27] [2030/2138] eta: 0:05:47 lr: 1.6982666123186688e-05 loss: 0.0218 (0.0227) time: 3.1239 data: 0.0027 max mem: 19788 +Epoch: [27] [2040/2138] eta: 0:05:15 lr: 1.6976733314046525e-05 loss: 0.0214 (0.0227) time: 3.0631 data: 0.0025 max mem: 19788 +Epoch: [27] [2050/2138] eta: 0:04:43 lr: 1.6970800274528373e-05 loss: 0.0201 (0.0227) time: 3.1534 data: 0.0022 max mem: 19788 +Epoch: [27] [2060/2138] eta: 0:04:11 lr: 1.6964867004533778e-05 loss: 0.0203 (0.0227) time: 3.3067 data: 0.0023 max mem: 19788 +Epoch: [27] [2070/2138] eta: 0:03:39 lr: 1.6958933503964232e-05 loss: 0.0200 (0.0227) time: 3.3202 data: 0.0023 max mem: 19788 +Epoch: [27] [2080/2138] eta: 0:03:06 lr: 1.6952999772721116e-05 loss: 0.0200 (0.0227) time: 3.2957 data: 0.0024 max mem: 19788 +Epoch: [27] [2090/2138] eta: 0:02:34 lr: 1.6947065810705757e-05 loss: 0.0217 (0.0227) time: 3.1687 data: 0.0024 max mem: 19788 +Epoch: [27] [2100/2138] eta: 0:02:02 lr: 1.6941131617819385e-05 loss: 0.0196 (0.0227) time: 3.0853 data: 0.0022 max mem: 19788 +Epoch: [27] [2110/2138] eta: 0:01:30 lr: 1.6935197193963157e-05 loss: 0.0235 (0.0227) time: 3.1982 data: 0.0023 max mem: 19788 +Epoch: [27] [2120/2138] eta: 0:00:57 lr: 1.6929262539038147e-05 loss: 0.0260 (0.0227) time: 3.2397 data: 0.0026 max mem: 19788 +Epoch: [27] [2130/2138] eta: 0:00:25 lr: 1.6923327652945344e-05 loss: 0.0259 (0.0227) time: 3.1835 data: 0.0025 max mem: 19788 +Epoch: [27] Total time: 1:54:46 +Test: [ 0/21770] eta: 18:32:36 time: 3.0664 data: 2.9421 max mem: 19788 +Test: [ 100/21770] eta: 0:29:48 time: 0.0501 data: 0.0016 max mem: 19788 +Test: [ 200/21770] eta: 0:24:12 time: 0.0446 data: 0.0015 max mem: 19788 +Test: [ 300/21770] eta: 0:22:13 time: 0.0536 data: 0.0017 max mem: 19788 +Test: [ 400/21770] eta: 0:21:31 time: 0.0546 data: 0.0020 max mem: 19788 +Test: [ 500/21770] eta: 0:21:07 time: 0.0565 data: 0.0020 max mem: 19788 +Test: [ 600/21770] eta: 0:20:17 time: 0.0448 data: 0.0016 max mem: 19788 +Test: [ 700/21770] eta: 0:19:38 time: 0.0453 data: 0.0015 max mem: 19788 +Test: [ 800/21770] eta: 0:19:14 time: 0.0458 data: 0.0017 max mem: 19788 +Test: [ 900/21770] eta: 0:18:48 time: 0.0451 data: 0.0017 max mem: 19788 +Test: [ 1000/21770] eta: 0:18:33 time: 0.0540 data: 0.0019 max mem: 19788 +Test: [ 1100/21770] eta: 0:18:17 time: 0.0447 data: 0.0016 max mem: 19788 +Test: [ 1200/21770] eta: 0:18:02 time: 0.0441 data: 0.0015 max mem: 19788 +Test: [ 1300/21770] eta: 0:17:53 time: 0.0546 data: 0.0018 max mem: 19788 +Test: [ 1400/21770] eta: 0:17:49 time: 0.0557 data: 0.0019 max mem: 19788 +Test: [ 1500/21770] eta: 0:17:45 time: 0.0444 data: 0.0016 max mem: 19788 +Test: [ 1600/21770] eta: 0:17:32 time: 0.0433 data: 0.0015 max mem: 19788 +Test: [ 1700/21770] eta: 0:17:23 time: 0.0497 data: 0.0016 max mem: 19788 +Test: [ 1800/21770] eta: 0:17:11 time: 0.0525 data: 0.0015 max mem: 19788 +Test: [ 1900/21770] eta: 0:17:04 time: 0.0538 data: 0.0018 max mem: 19788 +Test: [ 2000/21770] eta: 0:16:57 time: 0.0453 data: 0.0015 max mem: 19788 +Test: [ 2100/21770] eta: 0:16:51 time: 0.0451 data: 0.0015 max mem: 19788 +Test: [ 2200/21770] eta: 0:16:44 time: 0.0438 data: 0.0015 max mem: 19788 +Test: [ 2300/21770] eta: 0:16:35 time: 0.0432 data: 0.0015 max mem: 19788 +Test: [ 2400/21770] eta: 0:16:29 time: 0.0520 data: 0.0018 max mem: 19788 +Test: [ 2500/21770] eta: 0:16:25 time: 0.0456 data: 0.0016 max mem: 19788 +Test: [ 2600/21770] eta: 0:16:18 time: 0.0537 data: 0.0016 max mem: 19788 +Test: [ 2700/21770] eta: 0:16:11 time: 0.0446 data: 0.0014 max mem: 19788 +Test: [ 2800/21770] eta: 0:16:05 time: 0.0480 data: 0.0018 max mem: 19788 +Test: [ 2900/21770] eta: 0:15:59 time: 0.0474 data: 0.0018 max mem: 19788 +Test: [ 3000/21770] eta: 0:15:52 time: 0.0500 data: 0.0017 max mem: 19788 +Test: [ 3100/21770] eta: 0:15:44 time: 0.0450 data: 0.0015 max mem: 19788 +Test: [ 3200/21770] eta: 0:15:38 time: 0.0532 data: 0.0014 max mem: 19788 +Test: [ 3300/21770] eta: 0:15:33 time: 0.0483 data: 0.0016 max mem: 19788 +Test: [ 3400/21770] eta: 0:15:27 time: 0.0502 data: 0.0018 max mem: 19788 +Test: [ 3500/21770] eta: 0:15:22 time: 0.0466 data: 0.0015 max mem: 19788 +Test: [ 3600/21770] eta: 0:15:14 time: 0.0439 data: 0.0016 max mem: 19788 +Test: [ 3700/21770] eta: 0:15:07 time: 0.0445 data: 0.0016 max mem: 19788 +Test: [ 3800/21770] eta: 0:15:02 time: 0.0550 data: 0.0020 max mem: 19788 +Test: [ 3900/21770] eta: 0:14:56 time: 0.0561 data: 0.0017 max mem: 19788 +Test: [ 4000/21770] eta: 0:14:49 time: 0.0443 data: 0.0015 max mem: 19788 +Test: [ 4100/21770] eta: 0:14:43 time: 0.0508 data: 0.0017 max mem: 19788 +Test: [ 4200/21770] eta: 0:14:39 time: 0.0548 data: 0.0018 max mem: 19788 +Test: [ 4300/21770] eta: 0:14:35 time: 0.0452 data: 0.0014 max mem: 19788 +Test: [ 4400/21770] eta: 0:14:30 time: 0.0475 data: 0.0017 max mem: 19788 +Test: [ 4500/21770] eta: 0:14:24 time: 0.0528 data: 0.0017 max mem: 19788 +Test: [ 4600/21770] eta: 0:14:17 time: 0.0458 data: 0.0014 max mem: 19788 +Test: [ 4700/21770] eta: 0:14:10 time: 0.0453 data: 0.0014 max mem: 19788 +Test: [ 4800/21770] eta: 0:14:06 time: 0.0544 data: 0.0017 max mem: 19788 +Test: [ 4900/21770] eta: 0:14:02 time: 0.0540 data: 0.0019 max mem: 19788 +Test: [ 5000/21770] eta: 0:13:58 time: 0.0536 data: 0.0018 max mem: 19788 +Test: [ 5100/21770] eta: 0:13:53 time: 0.0538 data: 0.0018 max mem: 19788 +Test: [ 5200/21770] eta: 0:13:48 time: 0.0447 data: 0.0015 max mem: 19788 +Test: [ 5300/21770] eta: 0:13:42 time: 0.0543 data: 0.0019 max mem: 19788 +Test: [ 5400/21770] eta: 0:13:39 time: 0.0543 data: 0.0019 max mem: 19788 +Test: [ 5500/21770] eta: 0:13:35 time: 0.0485 data: 0.0016 max mem: 19788 +Test: [ 5600/21770] eta: 0:13:28 time: 0.0533 data: 0.0017 max mem: 19788 +Test: [ 5700/21770] eta: 0:13:24 time: 0.0550 data: 0.0019 max mem: 19788 +Test: [ 5800/21770] eta: 0:13:19 time: 0.0447 data: 0.0015 max mem: 19788 +Test: [ 5900/21770] eta: 0:13:14 time: 0.0554 data: 0.0019 max mem: 19788 +Test: [ 6000/21770] eta: 0:13:08 time: 0.0463 data: 0.0016 max mem: 19788 +Test: [ 6100/21770] eta: 0:13:04 time: 0.0553 data: 0.0020 max mem: 19788 +Test: [ 6200/21770] eta: 0:12:58 time: 0.0460 data: 0.0015 max mem: 19788 +Test: [ 6300/21770] eta: 0:12:54 time: 0.0516 data: 0.0019 max mem: 19788 +Test: [ 6400/21770] eta: 0:12:49 time: 0.0471 data: 0.0016 max mem: 19788 +Test: [ 6500/21770] eta: 0:12:44 time: 0.0460 data: 0.0017 max mem: 19788 +Test: [ 6600/21770] eta: 0:12:39 time: 0.0477 data: 0.0018 max mem: 19788 +Test: [ 6700/21770] eta: 0:12:34 time: 0.0457 data: 0.0014 max mem: 19788 +Test: [ 6800/21770] eta: 0:12:28 time: 0.0460 data: 0.0017 max mem: 19788 +Test: [ 6900/21770] eta: 0:12:22 time: 0.0450 data: 0.0014 max mem: 19788 +Test: [ 7000/21770] eta: 0:12:18 time: 0.0552 data: 0.0020 max mem: 19788 +Test: [ 7100/21770] eta: 0:12:14 time: 0.0527 data: 0.0019 max mem: 19788 +Test: [ 7200/21770] eta: 0:12:10 time: 0.0561 data: 0.0020 max mem: 19788 +Test: [ 7300/21770] eta: 0:12:04 time: 0.0499 data: 0.0016 max mem: 19788 +Test: [ 7400/21770] eta: 0:11:59 time: 0.0460 data: 0.0015 max mem: 19788 +Test: [ 7500/21770] eta: 0:11:53 time: 0.0526 data: 0.0019 max mem: 19788 +Test: [ 7600/21770] eta: 0:11:49 time: 0.0526 data: 0.0019 max mem: 19788 +Test: [ 7700/21770] eta: 0:11:44 time: 0.0554 data: 0.0019 max mem: 19788 +Test: [ 7800/21770] eta: 0:11:39 time: 0.0460 data: 0.0016 max mem: 19788 +Test: [ 7900/21770] eta: 0:11:35 time: 0.0487 data: 0.0016 max mem: 19788 +Test: [ 8000/21770] eta: 0:11:30 time: 0.0512 data: 0.0017 max mem: 19788 +Test: [ 8100/21770] eta: 0:11:25 time: 0.0500 data: 0.0015 max mem: 19788 +Test: [ 8200/21770] eta: 0:11:20 time: 0.0498 data: 0.0017 max mem: 19788 +Test: [ 8300/21770] eta: 0:11:15 time: 0.0454 data: 0.0017 max mem: 19788 +Test: [ 8400/21770] eta: 0:11:09 time: 0.0445 data: 0.0014 max mem: 19788 +Test: [ 8500/21770] eta: 0:11:04 time: 0.0476 data: 0.0016 max mem: 19788 +Test: [ 8600/21770] eta: 0:10:58 time: 0.0526 data: 0.0018 max mem: 19788 +Test: [ 8700/21770] eta: 0:10:53 time: 0.0562 data: 0.0016 max mem: 19788 +Test: [ 8800/21770] eta: 0:10:48 time: 0.0507 data: 0.0014 max mem: 19788 +Test: [ 8900/21770] eta: 0:10:43 time: 0.0511 data: 0.0015 max mem: 19788 +Test: [ 9000/21770] eta: 0:10:37 time: 0.0473 data: 0.0015 max mem: 19788 +Test: [ 9100/21770] eta: 0:10:31 time: 0.0459 data: 0.0014 max mem: 19788 +Test: [ 9200/21770] eta: 0:10:26 time: 0.0480 data: 0.0017 max mem: 19788 +Test: [ 9300/21770] eta: 0:10:21 time: 0.0548 data: 0.0016 max mem: 19788 +Test: [ 9400/21770] eta: 0:10:16 time: 0.0464 data: 0.0018 max mem: 19788 +Test: [ 9500/21770] eta: 0:10:10 time: 0.0491 data: 0.0017 max mem: 19788 +Test: [ 9600/21770] eta: 0:10:05 time: 0.0455 data: 0.0014 max mem: 19788 +Test: [ 9700/21770] eta: 0:10:00 time: 0.0453 data: 0.0015 max mem: 19788 +Test: [ 9800/21770] eta: 0:09:54 time: 0.0440 data: 0.0016 max mem: 19788 +Test: [ 9900/21770] eta: 0:09:49 time: 0.0443 data: 0.0016 max mem: 19788 +Test: [10000/21770] eta: 0:09:44 time: 0.0543 data: 0.0019 max mem: 19788 +Test: [10100/21770] eta: 0:09:40 time: 0.0575 data: 0.0017 max mem: 19788 +Test: [10200/21770] eta: 0:09:35 time: 0.0474 data: 0.0014 max mem: 19788 +Test: [10300/21770] eta: 0:09:30 time: 0.0542 data: 0.0019 max mem: 19788 +Test: [10400/21770] eta: 0:09:24 time: 0.0453 data: 0.0016 max mem: 19788 +Test: [10500/21770] eta: 0:09:19 time: 0.0464 data: 0.0017 max mem: 19788 +Test: [10600/21770] eta: 0:09:14 time: 0.0473 data: 0.0015 max mem: 19788 +Test: [10700/21770] eta: 0:09:09 time: 0.0548 data: 0.0018 max mem: 19788 +Test: [10800/21770] eta: 0:09:04 time: 0.0451 data: 0.0016 max mem: 19788 +Test: [10900/21770] eta: 0:09:00 time: 0.0531 data: 0.0019 max mem: 19788 +Test: [11000/21770] eta: 0:08:55 time: 0.0495 data: 0.0017 max mem: 19788 +Test: [11100/21770] eta: 0:08:50 time: 0.0503 data: 0.0016 max mem: 19788 +Test: [11200/21770] eta: 0:08:45 time: 0.0472 data: 0.0015 max mem: 19788 +Test: [11300/21770] eta: 0:08:40 time: 0.0441 data: 0.0015 max mem: 19788 +Test: [11400/21770] eta: 0:08:35 time: 0.0490 data: 0.0016 max mem: 19788 +Test: [11500/21770] eta: 0:08:30 time: 0.0455 data: 0.0015 max mem: 19788 +Test: [11600/21770] eta: 0:08:24 time: 0.0455 data: 0.0014 max mem: 19788 +Test: [11700/21770] eta: 0:08:20 time: 0.0516 data: 0.0019 max mem: 19788 +Test: [11800/21770] eta: 0:08:15 time: 0.0468 data: 0.0015 max mem: 19788 +Test: [11900/21770] eta: 0:08:10 time: 0.0467 data: 0.0019 max mem: 19788 +Test: [12000/21770] eta: 0:08:05 time: 0.0451 data: 0.0014 max mem: 19788 +Test: [12100/21770] eta: 0:08:00 time: 0.0461 data: 0.0015 max mem: 19788 +Test: [12200/21770] eta: 0:07:55 time: 0.0563 data: 0.0019 max mem: 19788 +Test: [12300/21770] eta: 0:07:50 time: 0.0466 data: 0.0017 max mem: 19788 +Test: [12400/21770] eta: 0:07:44 time: 0.0451 data: 0.0015 max mem: 19788 +Test: [12500/21770] eta: 0:07:40 time: 0.0563 data: 0.0019 max mem: 19788 +Test: [12600/21770] eta: 0:07:35 time: 0.0558 data: 0.0020 max mem: 19788 +Test: [12700/21770] eta: 0:07:30 time: 0.0548 data: 0.0018 max mem: 19788 +Test: [12800/21770] eta: 0:07:25 time: 0.0454 data: 0.0016 max mem: 19788 +Test: [12900/21770] eta: 0:07:21 time: 0.0516 data: 0.0020 max mem: 19788 +Test: [13000/21770] eta: 0:07:16 time: 0.0464 data: 0.0015 max mem: 19788 +Test: [13100/21770] eta: 0:07:11 time: 0.0466 data: 0.0015 max mem: 19788 +Test: [13200/21770] eta: 0:07:06 time: 0.0499 data: 0.0019 max mem: 19788 +Test: [13300/21770] eta: 0:07:00 time: 0.0458 data: 0.0017 max mem: 19788 +Test: [13400/21770] eta: 0:06:55 time: 0.0442 data: 0.0014 max mem: 19788 +Test: [13500/21770] eta: 0:06:50 time: 0.0431 data: 0.0015 max mem: 19788 +Test: [13600/21770] eta: 0:06:45 time: 0.0555 data: 0.0018 max mem: 19788 +Test: [13700/21770] eta: 0:06:40 time: 0.0493 data: 0.0017 max mem: 19788 +Test: [13800/21770] eta: 0:06:35 time: 0.0446 data: 0.0015 max mem: 19788 +Test: [13900/21770] eta: 0:06:30 time: 0.0471 data: 0.0016 max mem: 19788 +Test: [14000/21770] eta: 0:06:25 time: 0.0523 data: 0.0018 max mem: 19788 +Test: [14100/21770] eta: 0:06:20 time: 0.0466 data: 0.0015 max mem: 19788 +Test: [14200/21770] eta: 0:06:15 time: 0.0468 data: 0.0016 max mem: 19788 +Test: [14300/21770] eta: 0:06:10 time: 0.0445 data: 0.0015 max mem: 19788 +Test: [14400/21770] eta: 0:06:05 time: 0.0456 data: 0.0016 max mem: 19788 +Test: [14500/21770] eta: 0:06:00 time: 0.0535 data: 0.0018 max mem: 19788 +Test: [14600/21770] eta: 0:05:55 time: 0.0499 data: 0.0015 max mem: 19788 +Test: [14700/21770] eta: 0:05:50 time: 0.0526 data: 0.0016 max mem: 19788 +Test: [14800/21770] eta: 0:05:45 time: 0.0495 data: 0.0018 max mem: 19788 +Test: [14900/21770] eta: 0:05:40 time: 0.0450 data: 0.0015 max mem: 19788 +Test: [15000/21770] eta: 0:05:35 time: 0.0445 data: 0.0015 max mem: 19788 +Test: [15100/21770] eta: 0:05:30 time: 0.0473 data: 0.0016 max mem: 19788 +Test: [15200/21770] eta: 0:05:25 time: 0.0454 data: 0.0014 max mem: 19788 +Test: [15300/21770] eta: 0:05:20 time: 0.0449 data: 0.0014 max mem: 19788 +Test: [15400/21770] eta: 0:05:15 time: 0.0541 data: 0.0017 max mem: 19788 +Test: [15500/21770] eta: 0:05:10 time: 0.0465 data: 0.0016 max mem: 19788 +Test: [15600/21770] eta: 0:05:05 time: 0.0551 data: 0.0019 max mem: 19788 +Test: [15700/21770] eta: 0:05:01 time: 0.0548 data: 0.0020 max mem: 19788 +Test: [15800/21770] eta: 0:04:56 time: 0.0463 data: 0.0016 max mem: 19788 +Test: [15900/21770] eta: 0:04:51 time: 0.0446 data: 0.0014 max mem: 19788 +Test: [16000/21770] eta: 0:04:45 time: 0.0456 data: 0.0016 max mem: 19788 +Test: [16100/21770] eta: 0:04:40 time: 0.0446 data: 0.0014 max mem: 19788 +Test: [16200/21770] eta: 0:04:35 time: 0.0440 data: 0.0017 max mem: 19788 +Test: [16300/21770] eta: 0:04:30 time: 0.0525 data: 0.0018 max mem: 19788 +Test: [16400/21770] eta: 0:04:25 time: 0.0474 data: 0.0016 max mem: 19788 +Test: [16500/21770] eta: 0:04:20 time: 0.0466 data: 0.0016 max mem: 19788 +Test: [16600/21770] eta: 0:04:15 time: 0.0494 data: 0.0018 max mem: 19788 +Test: [16700/21770] eta: 0:04:10 time: 0.0568 data: 0.0016 max mem: 19788 +Test: [16800/21770] eta: 0:04:05 time: 0.0449 data: 0.0015 max mem: 19788 +Test: [16900/21770] eta: 0:04:00 time: 0.0507 data: 0.0019 max mem: 19788 +Test: [17000/21770] eta: 0:03:55 time: 0.0457 data: 0.0015 max mem: 19788 +Test: [17100/21770] eta: 0:03:50 time: 0.0441 data: 0.0013 max mem: 19788 +Test: [17200/21770] eta: 0:03:45 time: 0.0456 data: 0.0015 max mem: 19788 +Test: [17300/21770] eta: 0:03:40 time: 0.0544 data: 0.0018 max mem: 19788 +Test: [17400/21770] eta: 0:03:35 time: 0.0509 data: 0.0018 max mem: 19788 +Test: [17500/21770] eta: 0:03:30 time: 0.0534 data: 0.0019 max mem: 19788 +Test: [17600/21770] eta: 0:03:26 time: 0.0456 data: 0.0015 max mem: 19788 +Test: [17700/21770] eta: 0:03:21 time: 0.0564 data: 0.0020 max mem: 19788 +Test: [17800/21770] eta: 0:03:16 time: 0.0529 data: 0.0018 max mem: 19788 +Test: [17900/21770] eta: 0:03:11 time: 0.0528 data: 0.0019 max mem: 19788 +Test: [18000/21770] eta: 0:03:06 time: 0.0478 data: 0.0015 max mem: 19788 +Test: [18100/21770] eta: 0:03:01 time: 0.0486 data: 0.0019 max mem: 19788 +Test: [18200/21770] eta: 0:02:56 time: 0.0480 data: 0.0018 max mem: 19788 +Test: [18300/21770] eta: 0:02:51 time: 0.0443 data: 0.0015 max mem: 19788 +Test: [18400/21770] eta: 0:02:46 time: 0.0564 data: 0.0019 max mem: 19788 +Test: [18500/21770] eta: 0:02:41 time: 0.0501 data: 0.0019 max mem: 19788 +Test: [18600/21770] eta: 0:02:37 time: 0.0553 data: 0.0019 max mem: 19788 +Test: [18700/21770] eta: 0:02:32 time: 0.0478 data: 0.0018 max mem: 19788 +Test: [18800/21770] eta: 0:02:27 time: 0.0529 data: 0.0016 max mem: 19788 +Test: [18900/21770] eta: 0:02:22 time: 0.0511 data: 0.0018 max mem: 19788 +Test: [19000/21770] eta: 0:02:17 time: 0.0518 data: 0.0018 max mem: 19788 +Test: [19100/21770] eta: 0:02:12 time: 0.0489 data: 0.0016 max mem: 19788 +Test: [19200/21770] eta: 0:02:07 time: 0.0517 data: 0.0017 max mem: 19788 +Test: [19300/21770] eta: 0:02:02 time: 0.0472 data: 0.0016 max mem: 19788 +Test: [19400/21770] eta: 0:01:57 time: 0.0467 data: 0.0015 max mem: 19788 +Test: [19500/21770] eta: 0:01:52 time: 0.0449 data: 0.0017 max mem: 19788 +Test: [19600/21770] eta: 0:01:47 time: 0.0469 data: 0.0017 max mem: 19788 +Test: [19700/21770] eta: 0:01:42 time: 0.0535 data: 0.0018 max mem: 19788 +Test: [19800/21770] eta: 0:01:37 time: 0.0450 data: 0.0018 max mem: 19788 +Test: [19900/21770] eta: 0:01:32 time: 0.0460 data: 0.0017 max mem: 19788 +Test: [20000/21770] eta: 0:01:27 time: 0.0541 data: 0.0019 max mem: 19788 +Test: [20100/21770] eta: 0:01:22 time: 0.0536 data: 0.0019 max mem: 19788 +Test: [20200/21770] eta: 0:01:17 time: 0.0477 data: 0.0015 max mem: 19788 +Test: [20300/21770] eta: 0:01:12 time: 0.0511 data: 0.0015 max mem: 19788 +Test: [20400/21770] eta: 0:01:07 time: 0.0455 data: 0.0016 max mem: 19788 +Test: [20500/21770] eta: 0:01:02 time: 0.0467 data: 0.0015 max mem: 19788 +Test: [20600/21770] eta: 0:00:57 time: 0.0554 data: 0.0017 max mem: 19788 +Test: [20700/21770] eta: 0:00:52 time: 0.0447 data: 0.0016 max mem: 19788 +Test: [20800/21770] eta: 0:00:48 time: 0.0463 data: 0.0015 max mem: 19788 +Test: [20900/21770] eta: 0:00:43 time: 0.0543 data: 0.0019 max mem: 19788 +Test: [21000/21770] eta: 0:00:38 time: 0.0477 data: 0.0014 max mem: 19788 +Test: [21100/21770] eta: 0:00:33 time: 0.0472 data: 0.0017 max mem: 19788 +Test: [21200/21770] eta: 0:00:28 time: 0.0502 data: 0.0017 max mem: 19788 +Test: [21300/21770] eta: 0:00:23 time: 0.0468 data: 0.0015 max mem: 19788 +Test: [21400/21770] eta: 0:00:18 time: 0.0464 data: 0.0014 max mem: 19788 +Test: [21500/21770] eta: 0:00:13 time: 0.0465 data: 0.0016 max mem: 19788 +Test: [21600/21770] eta: 0:00:08 time: 0.0515 data: 0.0016 max mem: 19788 +Test: [21700/21770] eta: 0:00:03 time: 0.0711 data: 0.0036 max mem: 19788 +Test: Total time: 0:17:58 +Final results: +Mean IoU is 65.02 + + precision@0.5 = 72.25 + precision@0.6 = 66.77 + precision@0.7 = 60.14 + precision@0.8 = 49.44 + precision@0.9 = 24.46 + overall IoU = 64.85 + mean IoU = 65.02 + +Mean accuracy for one-to-zero sample is 84.36 + +Average object IoU 0.6501900176876967 +Overall IoU 64.85259246826172 +Better epoch: 27 + +Epoch: [28] [ 0/2138] eta: 3:08:55 lr: 1.691857957756371e-05 loss: 0.0377 (0.0377) time: 5.3017 data: 1.4070 max mem: 19788 +Epoch: [28] [ 10/2138] eta: 2:04:55 lr: 1.6912644275119132e-05 loss: 0.0191 (0.0229) time: 3.5221 data: 0.1305 max mem: 19788 +Epoch: [28] [ 20/2138] eta: 1:56:53 lr: 1.690670874122911e-05 loss: 0.0191 (0.0219) time: 3.2118 data: 0.0023 max mem: 19788 +Epoch: [28] [ 30/2138] eta: 1:55:39 lr: 1.6900772975794338e-05 loss: 0.0217 (0.0225) time: 3.1657 data: 0.0023 max mem: 19788 +Epoch: [28] [ 40/2138] eta: 1:54:43 lr: 1.6894836978715405e-05 loss: 0.0220 (0.0224) time: 3.2488 data: 0.0026 max mem: 19788 +Epoch: [28] [ 50/2138] eta: 1:55:08 lr: 1.688890074989285e-05 loss: 0.0197 (0.0227) time: 3.3338 data: 0.0024 max mem: 19788 +Epoch: [28] [ 60/2138] eta: 1:53:11 lr: 1.6882964289227097e-05 loss: 0.0214 (0.0231) time: 3.2427 data: 0.0029 max mem: 19788 +Epoch: [28] [ 70/2138] eta: 1:51:34 lr: 1.6877027596618517e-05 loss: 0.0215 (0.0229) time: 3.0558 data: 0.0030 max mem: 19788 +Epoch: [28] [ 80/2138] eta: 1:51:19 lr: 1.6871090671967376e-05 loss: 0.0209 (0.0230) time: 3.1756 data: 0.0026 max mem: 19788 +Epoch: [28] [ 90/2138] eta: 1:49:56 lr: 1.686515351517388e-05 loss: 0.0209 (0.0228) time: 3.1631 data: 0.0026 max mem: 19788 +Epoch: [28] [ 100/2138] eta: 1:48:37 lr: 1.685921612613813e-05 loss: 0.0209 (0.0228) time: 3.0051 data: 0.0029 max mem: 19788 +Epoch: [28] [ 110/2138] eta: 1:47:26 lr: 1.6853278504760167e-05 loss: 0.0209 (0.0227) time: 2.9876 data: 0.0029 max mem: 19788 +Epoch: [28] [ 120/2138] eta: 1:46:50 lr: 1.6847340650939934e-05 loss: 0.0194 (0.0224) time: 3.0685 data: 0.0028 max mem: 19788 +Epoch: [28] [ 130/2138] eta: 1:46:54 lr: 1.68414025645773e-05 loss: 0.0203 (0.0223) time: 3.2810 data: 0.0028 max mem: 19788 +Epoch: [28] [ 140/2138] eta: 1:47:18 lr: 1.6835464245572043e-05 loss: 0.0203 (0.0224) time: 3.5001 data: 0.0024 max mem: 19788 +Epoch: [28] [ 150/2138] eta: 1:46:15 lr: 1.682952569382387e-05 loss: 0.0203 (0.0224) time: 3.2880 data: 0.0024 max mem: 19788 +Epoch: [28] [ 160/2138] eta: 1:45:19 lr: 1.6823586909232404e-05 loss: 0.0214 (0.0225) time: 3.0020 data: 0.0025 max mem: 19788 +Epoch: [28] [ 170/2138] eta: 1:44:25 lr: 1.6817647891697166e-05 loss: 0.0230 (0.0225) time: 3.0078 data: 0.0024 max mem: 19788 +Epoch: [28] [ 180/2138] eta: 1:43:31 lr: 1.6811708641117627e-05 loss: 0.0222 (0.0225) time: 2.9899 data: 0.0024 max mem: 19788 +Epoch: [28] [ 190/2138] eta: 1:42:47 lr: 1.6805769157393144e-05 loss: 0.0211 (0.0223) time: 3.0160 data: 0.0024 max mem: 19788 +Epoch: [28] [ 200/2138] eta: 1:42:17 lr: 1.6799829440423015e-05 loss: 0.0201 (0.0223) time: 3.1171 data: 0.0023 max mem: 19788 +Epoch: [28] [ 210/2138] eta: 1:41:47 lr: 1.6793889490106435e-05 loss: 0.0224 (0.0224) time: 3.1818 data: 0.0025 max mem: 19788 +Epoch: [28] [ 220/2138] eta: 1:41:14 lr: 1.6787949306342533e-05 loss: 0.0205 (0.0223) time: 3.1689 data: 0.0027 max mem: 19788 +Epoch: [28] [ 230/2138] eta: 1:40:41 lr: 1.6782008889030336e-05 loss: 0.0206 (0.0224) time: 3.1526 data: 0.0027 max mem: 19788 +Epoch: [28] [ 240/2138] eta: 1:40:02 lr: 1.6776068238068814e-05 loss: 0.0211 (0.0224) time: 3.1147 data: 0.0025 max mem: 19788 +Epoch: [28] [ 250/2138] eta: 1:39:19 lr: 1.6770127353356824e-05 loss: 0.0211 (0.0223) time: 3.0464 data: 0.0023 max mem: 19788 +Epoch: [28] [ 260/2138] eta: 1:38:37 lr: 1.6764186234793165e-05 loss: 0.0206 (0.0223) time: 3.0076 data: 0.0024 max mem: 19788 +Epoch: [28] [ 270/2138] eta: 1:37:55 lr: 1.6758244882276526e-05 loss: 0.0213 (0.0223) time: 3.0060 data: 0.0026 max mem: 19788 +Epoch: [28] [ 280/2138] eta: 1:37:17 lr: 1.6752303295705545e-05 loss: 0.0217 (0.0222) time: 3.0244 data: 0.0028 max mem: 19788 +Epoch: [28] [ 290/2138] eta: 1:36:35 lr: 1.6746361474978746e-05 loss: 0.0198 (0.0222) time: 3.0093 data: 0.0029 max mem: 19788 +Epoch: [28] [ 300/2138] eta: 1:35:57 lr: 1.6740419419994584e-05 loss: 0.0199 (0.0222) time: 3.0003 data: 0.0031 max mem: 19788 +Epoch: [28] [ 310/2138] eta: 1:35:34 lr: 1.6734477130651425e-05 loss: 0.0205 (0.0222) time: 3.1448 data: 0.0031 max mem: 19788 +Epoch: [28] [ 320/2138] eta: 1:35:05 lr: 1.6728534606847557e-05 loss: 0.0180 (0.0220) time: 3.2299 data: 0.0029 max mem: 19788 +Epoch: [28] [ 330/2138] eta: 1:34:34 lr: 1.6722591848481174e-05 loss: 0.0201 (0.0221) time: 3.1651 data: 0.0027 max mem: 19788 +Epoch: [28] [ 340/2138] eta: 1:34:05 lr: 1.6716648855450395e-05 loss: 0.0214 (0.0222) time: 3.1643 data: 0.0025 max mem: 19788 +Epoch: [28] [ 350/2138] eta: 1:33:30 lr: 1.6710705627653246e-05 loss: 0.0182 (0.0222) time: 3.1322 data: 0.0026 max mem: 19788 +Epoch: [28] [ 360/2138] eta: 1:33:13 lr: 1.6704762164987682e-05 loss: 0.0224 (0.0222) time: 3.2477 data: 0.0026 max mem: 19788 +Epoch: [28] [ 370/2138] eta: 1:32:39 lr: 1.6698818467351553e-05 loss: 0.0224 (0.0222) time: 3.2559 data: 0.0026 max mem: 19788 +Epoch: [28] [ 380/2138] eta: 1:32:02 lr: 1.6692874534642646e-05 loss: 0.0216 (0.0222) time: 3.0576 data: 0.0028 max mem: 19788 +Epoch: [28] [ 390/2138] eta: 1:31:31 lr: 1.6686930366758642e-05 loss: 0.0198 (0.0221) time: 3.0881 data: 0.0026 max mem: 19788 +Epoch: [28] [ 400/2138] eta: 1:31:03 lr: 1.6680985963597153e-05 loss: 0.0210 (0.0222) time: 3.1858 data: 0.0025 max mem: 19788 +Epoch: [28] [ 410/2138] eta: 1:30:46 lr: 1.6675041325055694e-05 loss: 0.0215 (0.0221) time: 3.3492 data: 0.0025 max mem: 19788 +Epoch: [28] [ 420/2138] eta: 1:30:18 lr: 1.6669096451031717e-05 loss: 0.0188 (0.0221) time: 3.3569 data: 0.0024 max mem: 19788 +Epoch: [28] [ 430/2138] eta: 1:29:49 lr: 1.6663151341422555e-05 loss: 0.0192 (0.0221) time: 3.2347 data: 0.0024 max mem: 19788 +Epoch: [28] [ 440/2138] eta: 1:29:18 lr: 1.665720599612548e-05 loss: 0.0209 (0.0221) time: 3.2034 data: 0.0025 max mem: 19788 +Epoch: [28] [ 450/2138] eta: 1:28:50 lr: 1.665126041503767e-05 loss: 0.0209 (0.0221) time: 3.2131 data: 0.0025 max mem: 19788 +Epoch: [28] [ 460/2138] eta: 1:28:21 lr: 1.6645314598056225e-05 loss: 0.0194 (0.0221) time: 3.2420 data: 0.0024 max mem: 19788 +Epoch: [28] [ 470/2138] eta: 1:27:45 lr: 1.6639368545078147e-05 loss: 0.0215 (0.0221) time: 3.1287 data: 0.0023 max mem: 19788 +Epoch: [28] [ 480/2138] eta: 1:27:10 lr: 1.6633422256000352e-05 loss: 0.0233 (0.0221) time: 3.0340 data: 0.0026 max mem: 19788 +Epoch: [28] [ 490/2138] eta: 1:26:38 lr: 1.6627475730719692e-05 loss: 0.0233 (0.0220) time: 3.0948 data: 0.0032 max mem: 19788 +Epoch: [28] [ 500/2138] eta: 1:26:09 lr: 1.6621528969132902e-05 loss: 0.0196 (0.0221) time: 3.1956 data: 0.0029 max mem: 19788 +Epoch: [28] [ 510/2138] eta: 1:25:39 lr: 1.6615581971136656e-05 loss: 0.0185 (0.0220) time: 3.2232 data: 0.0024 max mem: 19788 +Epoch: [28] [ 520/2138] eta: 1:25:01 lr: 1.6609634736627526e-05 loss: 0.0192 (0.0220) time: 3.0758 data: 0.0024 max mem: 19788 +Epoch: [28] [ 530/2138] eta: 1:24:24 lr: 1.660368726550201e-05 loss: 0.0194 (0.0220) time: 2.9624 data: 0.0024 max mem: 19788 +Epoch: [28] [ 540/2138] eta: 1:23:47 lr: 1.65977395576565e-05 loss: 0.0188 (0.0220) time: 2.9588 data: 0.0024 max mem: 19788 +Epoch: [28] [ 550/2138] eta: 1:23:11 lr: 1.659179161298733e-05 loss: 0.0194 (0.0220) time: 2.9756 data: 0.0025 max mem: 19788 +Epoch: [28] [ 560/2138] eta: 1:22:35 lr: 1.6585843431390716e-05 loss: 0.0219 (0.0220) time: 3.0017 data: 0.0025 max mem: 19788 +Epoch: [28] [ 570/2138] eta: 1:22:00 lr: 1.6579895012762818e-05 loss: 0.0206 (0.0220) time: 2.9858 data: 0.0024 max mem: 19788 +Epoch: [28] [ 580/2138] eta: 1:21:25 lr: 1.6573946356999674e-05 loss: 0.0200 (0.0221) time: 2.9896 data: 0.0023 max mem: 19788 +Epoch: [28] [ 590/2138] eta: 1:20:57 lr: 1.656799746399728e-05 loss: 0.0219 (0.0221) time: 3.1336 data: 0.0023 max mem: 19788 +Epoch: [28] [ 600/2138] eta: 1:20:24 lr: 1.6562048333651492e-05 loss: 0.0226 (0.0221) time: 3.1750 data: 0.0025 max mem: 19788 +Epoch: [28] [ 610/2138] eta: 1:19:50 lr: 1.655609896585813e-05 loss: 0.0212 (0.0221) time: 3.0639 data: 0.0025 max mem: 19788 +Epoch: [28] [ 620/2138] eta: 1:19:14 lr: 1.6550149360512886e-05 loss: 0.0228 (0.0222) time: 2.9986 data: 0.0025 max mem: 19788 +Epoch: [28] [ 630/2138] eta: 1:18:40 lr: 1.6544199517511388e-05 loss: 0.0214 (0.0222) time: 2.9749 data: 0.0026 max mem: 19788 +Epoch: [28] [ 640/2138] eta: 1:18:04 lr: 1.653824943674917e-05 loss: 0.0207 (0.0222) time: 2.9744 data: 0.0025 max mem: 19788 +Epoch: [28] [ 650/2138] eta: 1:17:29 lr: 1.6532299118121677e-05 loss: 0.0227 (0.0222) time: 2.9539 data: 0.0023 max mem: 19788 +Epoch: [28] [ 660/2138] eta: 1:16:54 lr: 1.6526348561524263e-05 loss: 0.0221 (0.0223) time: 2.9438 data: 0.0023 max mem: 19788 +Epoch: [28] [ 670/2138] eta: 1:16:19 lr: 1.652039776685221e-05 loss: 0.0208 (0.0222) time: 2.9470 data: 0.0023 max mem: 19788 +Epoch: [28] [ 680/2138] eta: 1:15:44 lr: 1.651444673400068e-05 loss: 0.0194 (0.0222) time: 2.9553 data: 0.0025 max mem: 19788 +Epoch: [28] [ 690/2138] eta: 1:15:14 lr: 1.650849546286479e-05 loss: 0.0211 (0.0222) time: 3.0616 data: 0.0027 max mem: 19788 +Epoch: [28] [ 700/2138] eta: 1:14:43 lr: 1.650254395333953e-05 loss: 0.0210 (0.0222) time: 3.1531 data: 0.0025 max mem: 19788 +Epoch: [28] [ 710/2138] eta: 1:14:11 lr: 1.6496592205319826e-05 loss: 0.0198 (0.0222) time: 3.1111 data: 0.0023 max mem: 19788 +Epoch: [28] [ 720/2138] eta: 1:13:37 lr: 1.64906402187005e-05 loss: 0.0184 (0.0222) time: 3.0171 data: 0.0023 max mem: 19788 +Epoch: [28] [ 730/2138] eta: 1:13:03 lr: 1.64846879933763e-05 loss: 0.0202 (0.0222) time: 2.9553 data: 0.0023 max mem: 19788 +Epoch: [28] [ 740/2138] eta: 1:12:29 lr: 1.6478735529241863e-05 loss: 0.0223 (0.0222) time: 2.9583 data: 0.0024 max mem: 19788 +Epoch: [28] [ 750/2138] eta: 1:11:56 lr: 1.6472782826191776e-05 loss: 0.0213 (0.0222) time: 2.9800 data: 0.0022 max mem: 19788 +Epoch: [28] [ 760/2138] eta: 1:11:21 lr: 1.646682988412049e-05 loss: 0.0206 (0.0222) time: 2.9705 data: 0.0023 max mem: 19788 +Epoch: [28] [ 770/2138] eta: 1:10:48 lr: 1.6460876702922405e-05 loss: 0.0206 (0.0222) time: 2.9478 data: 0.0024 max mem: 19788 +Epoch: [28] [ 780/2138] eta: 1:10:14 lr: 1.6454923282491814e-05 loss: 0.0206 (0.0222) time: 2.9642 data: 0.0025 max mem: 19788 +Epoch: [28] [ 790/2138] eta: 1:09:41 lr: 1.644896962272291e-05 loss: 0.0217 (0.0221) time: 2.9768 data: 0.0025 max mem: 19788 +Epoch: [28] [ 800/2138] eta: 1:09:10 lr: 1.644301572350983e-05 loss: 0.0201 (0.0222) time: 3.0463 data: 0.0025 max mem: 19788 +Epoch: [28] [ 810/2138] eta: 1:08:40 lr: 1.643706158474659e-05 loss: 0.0218 (0.0222) time: 3.1152 data: 0.0025 max mem: 19788 +Epoch: [28] [ 820/2138] eta: 1:08:08 lr: 1.6431107206327128e-05 loss: 0.0216 (0.0222) time: 3.1068 data: 0.0024 max mem: 19788 +Epoch: [28] [ 830/2138] eta: 1:07:35 lr: 1.6425152588145298e-05 loss: 0.0199 (0.0222) time: 3.0280 data: 0.0026 max mem: 19788 +Epoch: [28] [ 840/2138] eta: 1:07:02 lr: 1.641919773009486e-05 loss: 0.0183 (0.0221) time: 2.9513 data: 0.0025 max mem: 19788 +Epoch: [28] [ 850/2138] eta: 1:06:28 lr: 1.6413242632069472e-05 loss: 0.0200 (0.0221) time: 2.9423 data: 0.0022 max mem: 19788 +Epoch: [28] [ 860/2138] eta: 1:05:55 lr: 1.6407287293962726e-05 loss: 0.0224 (0.0221) time: 2.9414 data: 0.0023 max mem: 19788 +Epoch: [28] [ 870/2138] eta: 1:05:22 lr: 1.64013317156681e-05 loss: 0.0211 (0.0221) time: 2.9400 data: 0.0023 max mem: 19788 +Epoch: [28] [ 880/2138] eta: 1:04:49 lr: 1.6395375897079002e-05 loss: 0.0195 (0.0221) time: 2.9541 data: 0.0021 max mem: 19788 +Epoch: [28] [ 890/2138] eta: 1:04:17 lr: 1.6389419838088728e-05 loss: 0.0209 (0.0221) time: 2.9730 data: 0.0023 max mem: 19788 +Epoch: [28] [ 900/2138] eta: 1:03:48 lr: 1.638346353859051e-05 loss: 0.0220 (0.0221) time: 3.1112 data: 0.0023 max mem: 19788 +Epoch: [28] [ 910/2138] eta: 1:03:18 lr: 1.637750699847746e-05 loss: 0.0193 (0.0221) time: 3.2145 data: 0.0024 max mem: 19788 +Epoch: [28] [ 920/2138] eta: 1:02:47 lr: 1.6371550217642633e-05 loss: 0.0193 (0.0221) time: 3.1191 data: 0.0025 max mem: 19788 +Epoch: [28] [ 930/2138] eta: 1:02:14 lr: 1.6365593195978954e-05 loss: 0.0223 (0.0221) time: 2.9927 data: 0.0025 max mem: 19788 +Epoch: [28] [ 940/2138] eta: 1:01:42 lr: 1.6359635933379294e-05 loss: 0.0243 (0.0221) time: 2.9820 data: 0.0024 max mem: 19788 +Epoch: [28] [ 950/2138] eta: 1:01:10 lr: 1.63536784297364e-05 loss: 0.0206 (0.0221) time: 3.0066 data: 0.0023 max mem: 19788 +Epoch: [28] [ 960/2138] eta: 1:00:38 lr: 1.6347720684942965e-05 loss: 0.0220 (0.0222) time: 2.9840 data: 0.0023 max mem: 19788 +Epoch: [28] [ 970/2138] eta: 1:00:05 lr: 1.6341762698891553e-05 loss: 0.0244 (0.0222) time: 2.9793 data: 0.0024 max mem: 19788 +Epoch: [28] [ 980/2138] eta: 0:59:34 lr: 1.6335804471474664e-05 loss: 0.0197 (0.0221) time: 3.0070 data: 0.0025 max mem: 19788 +Epoch: [28] [ 990/2138] eta: 0:59:01 lr: 1.6329846002584684e-05 loss: 0.0186 (0.0221) time: 2.9968 data: 0.0023 max mem: 19788 +Epoch: [28] [1000/2138] eta: 0:58:32 lr: 1.6323887292113938e-05 loss: 0.0184 (0.0221) time: 3.0633 data: 0.0022 max mem: 19788 +Epoch: [28] [1010/2138] eta: 0:58:02 lr: 1.631792833995462e-05 loss: 0.0202 (0.0221) time: 3.1775 data: 0.0022 max mem: 19788 +Epoch: [28] [1020/2138] eta: 0:57:31 lr: 1.6311969145998872e-05 loss: 0.0182 (0.0221) time: 3.1356 data: 0.0024 max mem: 19788 +Epoch: [28] [1030/2138] eta: 0:56:59 lr: 1.630600971013871e-05 loss: 0.0194 (0.0221) time: 3.0371 data: 0.0027 max mem: 19788 +Epoch: [28] [1040/2138] eta: 0:56:29 lr: 1.6300050032266084e-05 loss: 0.0215 (0.0221) time: 3.0903 data: 0.0026 max mem: 19788 +Epoch: [28] [1050/2138] eta: 0:55:57 lr: 1.629409011227283e-05 loss: 0.0216 (0.0221) time: 3.0833 data: 0.0025 max mem: 19788 +Epoch: [28] [1060/2138] eta: 0:55:26 lr: 1.6288129950050717e-05 loss: 0.0216 (0.0221) time: 3.0236 data: 0.0025 max mem: 19788 +Epoch: [28] [1070/2138] eta: 0:54:55 lr: 1.62821695454914e-05 loss: 0.0207 (0.0221) time: 3.0388 data: 0.0023 max mem: 19788 +Epoch: [28] [1080/2138] eta: 0:54:23 lr: 1.627620889848644e-05 loss: 0.0209 (0.0221) time: 3.0172 data: 0.0022 max mem: 19788 +Epoch: [28] [1090/2138] eta: 0:53:53 lr: 1.6270248008927324e-05 loss: 0.0209 (0.0221) time: 3.0700 data: 0.0022 max mem: 19788 +Epoch: [28] [1100/2138] eta: 0:53:23 lr: 1.626428687670543e-05 loss: 0.0219 (0.0221) time: 3.1423 data: 0.0024 max mem: 19788 +Epoch: [28] [1110/2138] eta: 0:52:52 lr: 1.6258325501712056e-05 loss: 0.0201 (0.0221) time: 3.1568 data: 0.0026 max mem: 19788 +Epoch: [28] [1120/2138] eta: 0:52:21 lr: 1.6252363883838395e-05 loss: 0.0197 (0.0221) time: 3.0986 data: 0.0027 max mem: 19788 +Epoch: [28] [1130/2138] eta: 0:51:49 lr: 1.6246402022975558e-05 loss: 0.0197 (0.0221) time: 3.0144 data: 0.0027 max mem: 19788 +Epoch: [28] [1140/2138] eta: 0:51:17 lr: 1.6240439919014544e-05 loss: 0.0211 (0.0221) time: 2.9745 data: 0.0024 max mem: 19788 +Epoch: [28] [1150/2138] eta: 0:50:46 lr: 1.6234477571846287e-05 loss: 0.0182 (0.0221) time: 2.9840 data: 0.0023 max mem: 19788 +Epoch: [28] [1160/2138] eta: 0:50:14 lr: 1.62285149813616e-05 loss: 0.0186 (0.0221) time: 2.9859 data: 0.0023 max mem: 19788 +Epoch: [28] [1170/2138] eta: 0:49:43 lr: 1.6222552147451226e-05 loss: 0.0205 (0.0220) time: 3.0025 data: 0.0022 max mem: 19788 +Epoch: [28] [1180/2138] eta: 0:49:12 lr: 1.621658907000579e-05 loss: 0.0205 (0.0220) time: 3.0278 data: 0.0024 max mem: 19788 +Epoch: [28] [1190/2138] eta: 0:48:40 lr: 1.621062574891584e-05 loss: 0.0193 (0.0220) time: 3.0189 data: 0.0024 max mem: 19788 +Epoch: [28] [1200/2138] eta: 0:48:11 lr: 1.620466218407183e-05 loss: 0.0191 (0.0220) time: 3.1823 data: 0.0023 max mem: 19788 +Epoch: [28] [1210/2138] eta: 0:47:41 lr: 1.6198698375364117e-05 loss: 0.0220 (0.0220) time: 3.2607 data: 0.0023 max mem: 19788 +Epoch: [28] [1220/2138] eta: 0:47:10 lr: 1.6192734322682952e-05 loss: 0.0215 (0.0220) time: 3.1200 data: 0.0024 max mem: 19788 +Epoch: [28] [1230/2138] eta: 0:46:39 lr: 1.6186770025918517e-05 loss: 0.0211 (0.0220) time: 3.0717 data: 0.0026 max mem: 19788 +Epoch: [28] [1240/2138] eta: 0:46:08 lr: 1.6180805484960867e-05 loss: 0.0190 (0.0220) time: 3.0305 data: 0.0026 max mem: 19788 +Epoch: [28] [1250/2138] eta: 0:45:36 lr: 1.61748406997e-05 loss: 0.0190 (0.0220) time: 2.9873 data: 0.0025 max mem: 19788 +Epoch: [28] [1260/2138] eta: 0:45:05 lr: 1.616887567002578e-05 loss: 0.0187 (0.0220) time: 2.9804 data: 0.0024 max mem: 19788 +Epoch: [28] [1270/2138] eta: 0:44:33 lr: 1.6162910395828015e-05 loss: 0.0189 (0.0220) time: 2.9844 data: 0.0023 max mem: 19788 +Epoch: [28] [1280/2138] eta: 0:44:02 lr: 1.6156944876996383e-05 loss: 0.0195 (0.0220) time: 3.0290 data: 0.0022 max mem: 19788 +Epoch: [28] [1290/2138] eta: 0:43:31 lr: 1.6150979113420494e-05 loss: 0.0216 (0.0220) time: 3.0256 data: 0.0024 max mem: 19788 +Epoch: [28] [1300/2138] eta: 0:43:01 lr: 1.6145013104989843e-05 loss: 0.0218 (0.0220) time: 3.0939 data: 0.0025 max mem: 19788 +Epoch: [28] [1310/2138] eta: 0:42:30 lr: 1.6139046851593845e-05 loss: 0.0200 (0.0220) time: 3.1379 data: 0.0025 max mem: 19788 +Epoch: [28] [1320/2138] eta: 0:41:59 lr: 1.6133080353121807e-05 loss: 0.0203 (0.0219) time: 3.0679 data: 0.0026 max mem: 19788 +Epoch: [28] [1330/2138] eta: 0:41:28 lr: 1.6127113609462956e-05 loss: 0.0209 (0.0220) time: 3.0002 data: 0.0026 max mem: 19788 +Epoch: [28] [1340/2138] eta: 0:40:56 lr: 1.61211466205064e-05 loss: 0.0223 (0.0220) time: 2.9400 data: 0.0024 max mem: 19788 +Epoch: [28] [1350/2138] eta: 0:40:24 lr: 1.611517938614118e-05 loss: 0.0226 (0.0220) time: 2.9444 data: 0.0023 max mem: 19788 +Epoch: [28] [1360/2138] eta: 0:39:53 lr: 1.6109211906256215e-05 loss: 0.0218 (0.0220) time: 2.9771 data: 0.0025 max mem: 19788 +Epoch: [28] [1370/2138] eta: 0:39:22 lr: 1.6103244180740347e-05 loss: 0.0204 (0.0220) time: 2.9724 data: 0.0025 max mem: 19788 +Epoch: [28] [1380/2138] eta: 0:38:50 lr: 1.609727620948231e-05 loss: 0.0208 (0.0220) time: 2.9504 data: 0.0023 max mem: 19788 +Epoch: [28] [1390/2138] eta: 0:38:19 lr: 1.6091307992370742e-05 loss: 0.0194 (0.0220) time: 2.9730 data: 0.0022 max mem: 19788 +Epoch: [28] [1400/2138] eta: 0:37:49 lr: 1.6085339529294195e-05 loss: 0.0194 (0.0220) time: 3.0558 data: 0.0024 max mem: 19788 +Epoch: [28] [1410/2138] eta: 0:37:18 lr: 1.6079370820141117e-05 loss: 0.0207 (0.0220) time: 3.1270 data: 0.0026 max mem: 19788 +Epoch: [28] [1420/2138] eta: 0:36:47 lr: 1.607340186479986e-05 loss: 0.0192 (0.0220) time: 3.1043 data: 0.0025 max mem: 19788 +Epoch: [28] [1430/2138] eta: 0:36:16 lr: 1.606743266315867e-05 loss: 0.0204 (0.0220) time: 3.0316 data: 0.0024 max mem: 19788 +Epoch: [28] [1440/2138] eta: 0:35:45 lr: 1.6061463215105725e-05 loss: 0.0222 (0.0220) time: 2.9568 data: 0.0023 max mem: 19788 +Epoch: [28] [1450/2138] eta: 0:35:14 lr: 1.6055493520529068e-05 loss: 0.0228 (0.0220) time: 2.9450 data: 0.0021 max mem: 19788 +Epoch: [28] [1460/2138] eta: 0:34:43 lr: 1.604952357931668e-05 loss: 0.0215 (0.0220) time: 3.0597 data: 0.0022 max mem: 19788 +Epoch: [28] [1470/2138] eta: 0:34:12 lr: 1.6043553391356413e-05 loss: 0.0189 (0.0220) time: 3.1024 data: 0.0023 max mem: 19788 +Epoch: [28] [1480/2138] eta: 0:33:42 lr: 1.603758295653605e-05 loss: 0.0184 (0.0220) time: 3.0510 data: 0.0023 max mem: 19788 +Epoch: [28] [1490/2138] eta: 0:33:11 lr: 1.6031612274743248e-05 loss: 0.0199 (0.0220) time: 3.0923 data: 0.0025 max mem: 19788 +Epoch: [28] [1500/2138] eta: 0:32:41 lr: 1.60256413458656e-05 loss: 0.0220 (0.0220) time: 3.2022 data: 0.0027 max mem: 19788 +Epoch: [28] [1510/2138] eta: 0:32:11 lr: 1.601967016979057e-05 loss: 0.0207 (0.0220) time: 3.2133 data: 0.0029 max mem: 19788 +Epoch: [28] [1520/2138] eta: 0:31:40 lr: 1.6013698746405545e-05 loss: 0.0203 (0.0220) time: 3.1291 data: 0.0028 max mem: 19788 +Epoch: [28] [1530/2138] eta: 0:31:09 lr: 1.60077270755978e-05 loss: 0.0216 (0.0220) time: 3.0509 data: 0.0026 max mem: 19788 +Epoch: [28] [1540/2138] eta: 0:30:38 lr: 1.6001755157254526e-05 loss: 0.0194 (0.0220) time: 3.0040 data: 0.0026 max mem: 19788 +Epoch: [28] [1550/2138] eta: 0:30:07 lr: 1.5995782991262795e-05 loss: 0.0192 (0.0220) time: 2.9919 data: 0.0028 max mem: 19788 +Epoch: [28] [1560/2138] eta: 0:29:36 lr: 1.598981057750961e-05 loss: 0.0206 (0.0220) time: 2.9688 data: 0.0030 max mem: 19788 +Epoch: [28] [1570/2138] eta: 0:29:06 lr: 1.598383791588184e-05 loss: 0.0222 (0.0221) time: 3.1416 data: 0.0029 max mem: 19788 +Epoch: [28] [1580/2138] eta: 0:28:35 lr: 1.5977865006266295e-05 loss: 0.0222 (0.0221) time: 3.1697 data: 0.0026 max mem: 19788 +Epoch: [28] [1590/2138] eta: 0:28:05 lr: 1.597189184854965e-05 loss: 0.0223 (0.0220) time: 3.1663 data: 0.0025 max mem: 19788 +Epoch: [28] [1600/2138] eta: 0:27:35 lr: 1.5965918442618508e-05 loss: 0.0226 (0.0221) time: 3.2402 data: 0.0027 max mem: 19788 +Epoch: [28] [1610/2138] eta: 0:27:04 lr: 1.595994478835935e-05 loss: 0.0239 (0.0221) time: 3.2054 data: 0.0029 max mem: 19788 +Epoch: [28] [1620/2138] eta: 0:26:34 lr: 1.5953970885658583e-05 loss: 0.0197 (0.0221) time: 3.2598 data: 0.0027 max mem: 19788 +Epoch: [28] [1630/2138] eta: 0:26:04 lr: 1.5947996734402488e-05 loss: 0.0192 (0.0220) time: 3.2444 data: 0.0023 max mem: 19788 +Epoch: [28] [1640/2138] eta: 0:25:33 lr: 1.594202233447727e-05 loss: 0.0223 (0.0220) time: 3.1837 data: 0.0023 max mem: 19788 +Epoch: [28] [1650/2138] eta: 0:25:03 lr: 1.5936047685769014e-05 loss: 0.0225 (0.0221) time: 3.1307 data: 0.0024 max mem: 19788 +Epoch: [28] [1660/2138] eta: 0:24:32 lr: 1.5930072788163732e-05 loss: 0.0231 (0.0221) time: 3.1021 data: 0.0027 max mem: 19788 +Epoch: [28] [1670/2138] eta: 0:24:01 lr: 1.5924097641547302e-05 loss: 0.0199 (0.0220) time: 3.1622 data: 0.0029 max mem: 19788 +Epoch: [28] [1680/2138] eta: 0:23:31 lr: 1.5918122245805535e-05 loss: 0.0194 (0.0220) time: 3.2059 data: 0.0027 max mem: 19788 +Epoch: [28] [1690/2138] eta: 0:23:01 lr: 1.5912146600824124e-05 loss: 0.0214 (0.0220) time: 3.2225 data: 0.0026 max mem: 19788 +Epoch: [28] [1700/2138] eta: 0:22:30 lr: 1.590617070648865e-05 loss: 0.0204 (0.0220) time: 3.1686 data: 0.0028 max mem: 19788 +Epoch: [28] [1710/2138] eta: 0:21:59 lr: 1.590019456268463e-05 loss: 0.0204 (0.0220) time: 3.1432 data: 0.0027 max mem: 19788 +Epoch: [28] [1720/2138] eta: 0:21:28 lr: 1.5894218169297444e-05 loss: 0.0219 (0.0220) time: 3.1387 data: 0.0025 max mem: 19788 +Epoch: [28] [1730/2138] eta: 0:20:58 lr: 1.58882415262124e-05 loss: 0.0225 (0.0220) time: 3.1274 data: 0.0027 max mem: 19788 +Epoch: [28] [1740/2138] eta: 0:20:27 lr: 1.5882264633314673e-05 loss: 0.0197 (0.0220) time: 3.2554 data: 0.0026 max mem: 19788 +Epoch: [28] [1750/2138] eta: 0:19:57 lr: 1.5876287490489373e-05 loss: 0.0197 (0.0220) time: 3.2813 data: 0.0026 max mem: 19788 +Epoch: [28] [1760/2138] eta: 0:19:26 lr: 1.5870310097621486e-05 loss: 0.0207 (0.0220) time: 3.1545 data: 0.0024 max mem: 19788 +Epoch: [28] [1770/2138] eta: 0:18:55 lr: 1.5864332454595906e-05 loss: 0.0193 (0.0220) time: 3.0844 data: 0.0023 max mem: 19788 +Epoch: [28] [1780/2138] eta: 0:18:25 lr: 1.5858354561297416e-05 loss: 0.0190 (0.0220) time: 3.1703 data: 0.0023 max mem: 19788 +Epoch: [28] [1790/2138] eta: 0:17:54 lr: 1.5852376417610715e-05 loss: 0.0190 (0.0220) time: 3.1882 data: 0.0025 max mem: 19788 +Epoch: [28] [1800/2138] eta: 0:17:23 lr: 1.584639802342038e-05 loss: 0.0252 (0.0220) time: 3.1218 data: 0.0028 max mem: 19788 +Epoch: [28] [1810/2138] eta: 0:16:52 lr: 1.5840419378610904e-05 loss: 0.0249 (0.0220) time: 3.1540 data: 0.0027 max mem: 19788 +Epoch: [28] [1820/2138] eta: 0:16:22 lr: 1.5834440483066662e-05 loss: 0.0205 (0.0220) time: 3.1613 data: 0.0029 max mem: 19788 +Epoch: [28] [1830/2138] eta: 0:15:51 lr: 1.582846133667195e-05 loss: 0.0197 (0.0220) time: 3.3140 data: 0.0030 max mem: 19788 +Epoch: [28] [1840/2138] eta: 0:15:21 lr: 1.5822481939310933e-05 loss: 0.0222 (0.0220) time: 3.3704 data: 0.0025 max mem: 19788 +Epoch: [28] [1850/2138] eta: 0:14:50 lr: 1.5816502290867698e-05 loss: 0.0224 (0.0220) time: 3.1711 data: 0.0025 max mem: 19788 +Epoch: [28] [1860/2138] eta: 0:14:19 lr: 1.5810522391226216e-05 loss: 0.0213 (0.0220) time: 3.0609 data: 0.0027 max mem: 19788 +Epoch: [28] [1870/2138] eta: 0:13:48 lr: 1.5804542240270364e-05 loss: 0.0221 (0.0220) time: 3.1864 data: 0.0027 max mem: 19788 +Epoch: [28] [1880/2138] eta: 0:13:17 lr: 1.579856183788391e-05 loss: 0.0181 (0.0220) time: 3.2558 data: 0.0026 max mem: 19788 +Epoch: [28] [1890/2138] eta: 0:12:47 lr: 1.579258118395052e-05 loss: 0.0180 (0.0220) time: 3.2047 data: 0.0025 max mem: 19788 +Epoch: [28] [1900/2138] eta: 0:12:16 lr: 1.5786600278353762e-05 loss: 0.0207 (0.0220) time: 3.2203 data: 0.0025 max mem: 19788 +Epoch: [28] [1910/2138] eta: 0:11:45 lr: 1.5780619120977103e-05 loss: 0.0202 (0.0220) time: 3.1271 data: 0.0027 max mem: 19788 +Epoch: [28] [1920/2138] eta: 0:11:14 lr: 1.577463771170389e-05 loss: 0.0197 (0.0220) time: 3.0968 data: 0.0029 max mem: 19788 +Epoch: [28] [1930/2138] eta: 0:10:43 lr: 1.576865605041739e-05 loss: 0.0197 (0.0220) time: 3.1372 data: 0.0027 max mem: 19788 +Epoch: [28] [1940/2138] eta: 0:10:12 lr: 1.576267413700075e-05 loss: 0.0210 (0.0220) time: 3.0863 data: 0.0027 max mem: 19788 +Epoch: [28] [1950/2138] eta: 0:09:41 lr: 1.5756691971337024e-05 loss: 0.0220 (0.0220) time: 3.1157 data: 0.0027 max mem: 19788 +Epoch: [28] [1960/2138] eta: 0:09:11 lr: 1.5750709553309148e-05 loss: 0.0220 (0.0220) time: 3.2747 data: 0.0027 max mem: 19788 +Epoch: [28] [1970/2138] eta: 0:08:40 lr: 1.5744726882799977e-05 loss: 0.0181 (0.0220) time: 3.2961 data: 0.0027 max mem: 19788 +Epoch: [28] [1980/2138] eta: 0:08:09 lr: 1.5738743959692236e-05 loss: 0.0206 (0.0220) time: 3.1638 data: 0.0027 max mem: 19788 +Epoch: [28] [1990/2138] eta: 0:07:38 lr: 1.573276078386857e-05 loss: 0.0206 (0.0221) time: 3.2077 data: 0.0026 max mem: 19788 +Epoch: [28] [2000/2138] eta: 0:07:07 lr: 1.5726777355211503e-05 loss: 0.0196 (0.0221) time: 3.2483 data: 0.0025 max mem: 19788 +Epoch: [28] [2010/2138] eta: 0:06:36 lr: 1.5720793673603454e-05 loss: 0.0207 (0.0220) time: 3.3407 data: 0.0025 max mem: 19788 +Epoch: [28] [2020/2138] eta: 0:06:06 lr: 1.5714809738926758e-05 loss: 0.0216 (0.0221) time: 3.5471 data: 0.0023 max mem: 19788 +Epoch: [28] [2030/2138] eta: 0:05:35 lr: 1.5708825551063616e-05 loss: 0.0217 (0.0221) time: 3.3628 data: 0.0024 max mem: 19788 +Epoch: [28] [2040/2138] eta: 0:05:04 lr: 1.570284110989616e-05 loss: 0.0210 (0.0221) time: 3.2257 data: 0.0025 max mem: 19788 +Epoch: [28] [2050/2138] eta: 0:04:33 lr: 1.569685641530637e-05 loss: 0.0194 (0.0221) time: 3.4834 data: 0.0025 max mem: 19788 +Epoch: [28] [2060/2138] eta: 0:04:02 lr: 1.5690871467176173e-05 loss: 0.0191 (0.0221) time: 3.6087 data: 0.0026 max mem: 19788 +Epoch: [28] [2070/2138] eta: 0:03:31 lr: 1.5684886265387353e-05 loss: 0.0187 (0.0221) time: 3.3929 data: 0.0025 max mem: 19788 +Epoch: [28] [2080/2138] eta: 0:03:00 lr: 1.5678900809821607e-05 loss: 0.0189 (0.0221) time: 3.2043 data: 0.0026 max mem: 19788 +Epoch: [28] [2090/2138] eta: 0:02:29 lr: 1.5672915100360514e-05 loss: 0.0206 (0.0221) time: 3.1390 data: 0.0028 max mem: 19788 +Epoch: [28] [2100/2138] eta: 0:01:58 lr: 1.5666929136885562e-05 loss: 0.0206 (0.0220) time: 3.1369 data: 0.0030 max mem: 19788 +Epoch: [28] [2110/2138] eta: 0:01:27 lr: 1.566094291927812e-05 loss: 0.0234 (0.0221) time: 3.1598 data: 0.0031 max mem: 19788 +Epoch: [28] [2120/2138] eta: 0:00:55 lr: 1.5654956447419467e-05 loss: 0.0246 (0.0221) time: 3.1145 data: 0.0031 max mem: 19788 +Epoch: [28] [2130/2138] eta: 0:00:24 lr: 1.564896972119075e-05 loss: 0.0248 (0.0221) time: 3.1272 data: 0.0025 max mem: 19788 +Epoch: [28] Total time: 1:50:51 +Test: [ 0/21770] eta: 17:22:18 time: 2.8727 data: 2.7952 max mem: 19788 +Test: [ 100/21770] eta: 0:29:47 time: 0.0554 data: 0.0020 max mem: 19788 +Test: [ 200/21770] eta: 0:23:26 time: 0.0439 data: 0.0017 max mem: 19788 +Test: [ 300/21770] eta: 0:20:52 time: 0.0427 data: 0.0013 max mem: 19788 +Test: [ 400/21770] eta: 0:19:37 time: 0.0438 data: 0.0014 max mem: 19788 +Test: [ 500/21770] eta: 0:19:01 time: 0.0551 data: 0.0021 max mem: 19788 +Test: [ 600/21770] eta: 0:18:30 time: 0.0438 data: 0.0014 max mem: 19788 +Test: [ 700/21770] eta: 0:18:21 time: 0.0529 data: 0.0018 max mem: 19788 +Test: [ 800/21770] eta: 0:18:12 time: 0.0440 data: 0.0015 max mem: 19788 +Test: [ 900/21770] eta: 0:18:02 time: 0.0558 data: 0.0019 max mem: 19788 +Test: [ 1000/21770] eta: 0:17:54 time: 0.0538 data: 0.0017 max mem: 19788 +Test: [ 1100/21770] eta: 0:17:47 time: 0.0528 data: 0.0020 max mem: 19788 +Test: [ 1200/21770] eta: 0:17:37 time: 0.0439 data: 0.0014 max mem: 19788 +Test: [ 1300/21770] eta: 0:17:21 time: 0.0445 data: 0.0016 max mem: 19788 +Test: [ 1400/21770] eta: 0:17:13 time: 0.0442 data: 0.0014 max mem: 19788 +Test: [ 1500/21770] eta: 0:17:05 time: 0.0436 data: 0.0017 max mem: 19788 +Test: [ 1600/21770] eta: 0:16:54 time: 0.0506 data: 0.0017 max mem: 19788 +Test: [ 1700/21770] eta: 0:16:50 time: 0.0464 data: 0.0015 max mem: 19788 +Test: [ 1800/21770] eta: 0:16:42 time: 0.0478 data: 0.0015 max mem: 19788 +Test: [ 1900/21770] eta: 0:16:32 time: 0.0448 data: 0.0017 max mem: 19788 +Test: [ 2000/21770] eta: 0:16:22 time: 0.0471 data: 0.0015 max mem: 19788 +Test: [ 2100/21770] eta: 0:16:13 time: 0.0537 data: 0.0019 max mem: 19788 +Test: [ 2200/21770] eta: 0:16:09 time: 0.0427 data: 0.0014 max mem: 19788 +Test: [ 2300/21770] eta: 0:16:02 time: 0.0428 data: 0.0014 max mem: 19788 +Test: [ 2400/21770] eta: 0:15:54 time: 0.0456 data: 0.0015 max mem: 19788 +Test: [ 2500/21770] eta: 0:15:50 time: 0.0506 data: 0.0017 max mem: 19788 +Test: [ 2600/21770] eta: 0:15:46 time: 0.0545 data: 0.0018 max mem: 19788 +Test: [ 2700/21770] eta: 0:15:42 time: 0.0453 data: 0.0015 max mem: 19788 +Test: [ 2800/21770] eta: 0:15:40 time: 0.0552 data: 0.0019 max mem: 19788 +Test: [ 2900/21770] eta: 0:15:33 time: 0.0456 data: 0.0017 max mem: 19788 +Test: [ 3000/21770] eta: 0:15:28 time: 0.0479 data: 0.0015 max mem: 19788 +Test: [ 3100/21770] eta: 0:15:24 time: 0.0519 data: 0.0021 max mem: 19788 +Test: [ 3200/21770] eta: 0:15:22 time: 0.0552 data: 0.0017 max mem: 19788 +Test: [ 3300/21770] eta: 0:15:16 time: 0.0455 data: 0.0016 max mem: 19788 +Test: [ 3400/21770] eta: 0:15:09 time: 0.0455 data: 0.0014 max mem: 19788 +Test: [ 3500/21770] eta: 0:15:02 time: 0.0461 data: 0.0015 max mem: 19788 +Test: [ 3600/21770] eta: 0:14:57 time: 0.0503 data: 0.0019 max mem: 19788 +Test: [ 3700/21770] eta: 0:14:54 time: 0.0535 data: 0.0015 max mem: 19788 +Test: [ 3800/21770] eta: 0:14:51 time: 0.0457 data: 0.0016 max mem: 19788 +Test: [ 3900/21770] eta: 0:14:44 time: 0.0438 data: 0.0015 max mem: 19788 +Test: [ 4000/21770] eta: 0:14:37 time: 0.0493 data: 0.0016 max mem: 19788 +Test: [ 4100/21770] eta: 0:14:32 time: 0.0445 data: 0.0015 max mem: 19788 +Test: [ 4200/21770] eta: 0:14:25 time: 0.0452 data: 0.0015 max mem: 19788 +Test: [ 4300/21770] eta: 0:14:20 time: 0.0535 data: 0.0019 max mem: 19788 +Test: [ 4400/21770] eta: 0:14:15 time: 0.0456 data: 0.0015 max mem: 19788 +Test: [ 4500/21770] eta: 0:14:09 time: 0.0461 data: 0.0016 max mem: 19788 +Test: [ 4600/21770] eta: 0:14:06 time: 0.0528 data: 0.0019 max mem: 19788 +Test: [ 4700/21770] eta: 0:14:01 time: 0.0481 data: 0.0016 max mem: 19788 +Test: [ 4800/21770] eta: 0:13:57 time: 0.0499 data: 0.0017 max mem: 19788 +Test: [ 4900/21770] eta: 0:13:53 time: 0.0558 data: 0.0017 max mem: 19788 +Test: [ 5000/21770] eta: 0:13:49 time: 0.0465 data: 0.0015 max mem: 19788 +Test: [ 5100/21770] eta: 0:13:44 time: 0.0540 data: 0.0019 max mem: 19788 +Test: [ 5200/21770] eta: 0:13:39 time: 0.0458 data: 0.0014 max mem: 19788 +Test: [ 5300/21770] eta: 0:13:33 time: 0.0488 data: 0.0016 max mem: 19788 +Test: [ 5400/21770] eta: 0:13:28 time: 0.0495 data: 0.0018 max mem: 19788 +Test: [ 5500/21770] eta: 0:13:22 time: 0.0448 data: 0.0014 max mem: 19788 +Test: [ 5600/21770] eta: 0:13:17 time: 0.0550 data: 0.0018 max mem: 19788 +Test: [ 5700/21770] eta: 0:13:13 time: 0.0457 data: 0.0015 max mem: 19788 +Test: [ 5800/21770] eta: 0:13:08 time: 0.0468 data: 0.0018 max mem: 19788 +Test: [ 5900/21770] eta: 0:13:02 time: 0.0495 data: 0.0016 max mem: 19788 +Test: [ 6000/21770] eta: 0:12:57 time: 0.0536 data: 0.0018 max mem: 19788 +Test: [ 6100/21770] eta: 0:12:52 time: 0.0494 data: 0.0019 max mem: 19788 +Test: [ 6200/21770] eta: 0:12:46 time: 0.0500 data: 0.0015 max mem: 19788 +Test: [ 6300/21770] eta: 0:12:42 time: 0.0525 data: 0.0018 max mem: 19788 +Test: [ 6400/21770] eta: 0:12:37 time: 0.0494 data: 0.0017 max mem: 19788 +Test: [ 6500/21770] eta: 0:12:33 time: 0.0498 data: 0.0016 max mem: 19788 +Test: [ 6600/21770] eta: 0:12:28 time: 0.0466 data: 0.0018 max mem: 19788 +Test: [ 6700/21770] eta: 0:12:23 time: 0.0520 data: 0.0018 max mem: 19788 +Test: [ 6800/21770] eta: 0:12:18 time: 0.0442 data: 0.0015 max mem: 19788 +Test: [ 6900/21770] eta: 0:12:14 time: 0.0497 data: 0.0018 max mem: 19788 +Test: [ 7000/21770] eta: 0:12:09 time: 0.0459 data: 0.0016 max mem: 19788 +Test: [ 7100/21770] eta: 0:12:04 time: 0.0441 data: 0.0015 max mem: 19788 +Test: [ 7200/21770] eta: 0:11:59 time: 0.0448 data: 0.0015 max mem: 19788 +Test: [ 7300/21770] eta: 0:11:53 time: 0.0467 data: 0.0015 max mem: 19788 +Test: [ 7400/21770] eta: 0:11:47 time: 0.0438 data: 0.0014 max mem: 19788 +Test: [ 7500/21770] eta: 0:11:42 time: 0.0449 data: 0.0015 max mem: 19788 +Test: [ 7600/21770] eta: 0:11:37 time: 0.0506 data: 0.0016 max mem: 19788 +Test: [ 7700/21770] eta: 0:11:32 time: 0.0474 data: 0.0016 max mem: 19788 +Test: [ 7800/21770] eta: 0:11:27 time: 0.0443 data: 0.0015 max mem: 19788 +Test: [ 7900/21770] eta: 0:11:22 time: 0.0458 data: 0.0016 max mem: 19788 +Test: [ 8000/21770] eta: 0:11:17 time: 0.0502 data: 0.0016 max mem: 19788 +Test: [ 8100/21770] eta: 0:11:12 time: 0.0471 data: 0.0016 max mem: 19788 +Test: [ 8200/21770] eta: 0:11:07 time: 0.0508 data: 0.0017 max mem: 19788 +Test: [ 8300/21770] eta: 0:11:01 time: 0.0503 data: 0.0017 max mem: 19788 +Test: [ 8400/21770] eta: 0:10:56 time: 0.0454 data: 0.0014 max mem: 19788 +Test: [ 8500/21770] eta: 0:10:52 time: 0.0530 data: 0.0019 max mem: 19788 +Test: [ 8600/21770] eta: 0:10:48 time: 0.0453 data: 0.0019 max mem: 19788 +Test: [ 8700/21770] eta: 0:10:42 time: 0.0506 data: 0.0018 max mem: 19788 +Test: [ 8800/21770] eta: 0:10:37 time: 0.0534 data: 0.0018 max mem: 19788 +Test: [ 8900/21770] eta: 0:10:32 time: 0.0454 data: 0.0014 max mem: 19788 +Test: [ 9000/21770] eta: 0:10:27 time: 0.0473 data: 0.0015 max mem: 19788 +Test: [ 9100/21770] eta: 0:10:22 time: 0.0456 data: 0.0014 max mem: 19788 +Test: [ 9200/21770] eta: 0:10:17 time: 0.0506 data: 0.0016 max mem: 19788 +Test: [ 9300/21770] eta: 0:10:12 time: 0.0466 data: 0.0015 max mem: 19788 +Test: [ 9400/21770] eta: 0:10:07 time: 0.0446 data: 0.0017 max mem: 19788 +Test: [ 9500/21770] eta: 0:10:02 time: 0.0452 data: 0.0015 max mem: 19788 +Test: [ 9600/21770] eta: 0:09:56 time: 0.0439 data: 0.0014 max mem: 19788 +Test: [ 9700/21770] eta: 0:09:51 time: 0.0508 data: 0.0017 max mem: 19788 +Test: [ 9800/21770] eta: 0:09:47 time: 0.0456 data: 0.0014 max mem: 19788 +Test: [ 9900/21770] eta: 0:09:41 time: 0.0455 data: 0.0016 max mem: 19788 +Test: [10000/21770] eta: 0:09:36 time: 0.0433 data: 0.0015 max mem: 19788 +Test: [10100/21770] eta: 0:09:31 time: 0.0444 data: 0.0015 max mem: 19788 +Test: [10200/21770] eta: 0:09:26 time: 0.0548 data: 0.0019 max mem: 19788 +Test: [10300/21770] eta: 0:09:22 time: 0.0466 data: 0.0016 max mem: 19788 +Test: [10400/21770] eta: 0:09:17 time: 0.0470 data: 0.0016 max mem: 19788 +Test: [10500/21770] eta: 0:09:12 time: 0.0451 data: 0.0015 max mem: 19788 +Test: [10600/21770] eta: 0:09:07 time: 0.0541 data: 0.0017 max mem: 19788 +Test: [10700/21770] eta: 0:09:02 time: 0.0498 data: 0.0016 max mem: 19788 +Test: [10800/21770] eta: 0:08:57 time: 0.0483 data: 0.0015 max mem: 19788 +Test: [10900/21770] eta: 0:08:52 time: 0.0454 data: 0.0017 max mem: 19788 +Test: [11000/21770] eta: 0:08:47 time: 0.0479 data: 0.0017 max mem: 19788 +Test: [11100/21770] eta: 0:08:42 time: 0.0425 data: 0.0015 max mem: 19788 +Test: [11200/21770] eta: 0:08:37 time: 0.0497 data: 0.0019 max mem: 19788 +Test: [11300/21770] eta: 0:08:32 time: 0.0457 data: 0.0014 max mem: 19788 +Test: [11400/21770] eta: 0:08:28 time: 0.0489 data: 0.0014 max mem: 19788 +Test: [11500/21770] eta: 0:08:23 time: 0.0525 data: 0.0017 max mem: 19788 +Test: [11600/21770] eta: 0:08:18 time: 0.0445 data: 0.0015 max mem: 19788 +Test: [11700/21770] eta: 0:08:13 time: 0.0519 data: 0.0018 max mem: 19788 +Test: [11800/21770] eta: 0:08:08 time: 0.0458 data: 0.0016 max mem: 19788 +Test: [11900/21770] eta: 0:08:03 time: 0.0557 data: 0.0019 max mem: 19788 +Test: [12000/21770] eta: 0:07:58 time: 0.0512 data: 0.0018 max mem: 19788 +Test: [12100/21770] eta: 0:07:54 time: 0.0570 data: 0.0017 max mem: 19788 +Test: [12200/21770] eta: 0:07:49 time: 0.0467 data: 0.0016 max mem: 19788 +Test: [12300/21770] eta: 0:07:44 time: 0.0492 data: 0.0017 max mem: 19788 +Test: [12400/21770] eta: 0:07:39 time: 0.0546 data: 0.0019 max mem: 19788 +Test: [12500/21770] eta: 0:07:34 time: 0.0447 data: 0.0014 max mem: 19788 +Test: [12600/21770] eta: 0:07:29 time: 0.0472 data: 0.0016 max mem: 19788 +Test: [12700/21770] eta: 0:07:25 time: 0.0551 data: 0.0019 max mem: 19788 +Test: [12800/21770] eta: 0:07:20 time: 0.0448 data: 0.0015 max mem: 19788 +Test: [12900/21770] eta: 0:07:15 time: 0.0554 data: 0.0018 max mem: 19788 +Test: [13000/21770] eta: 0:07:10 time: 0.0511 data: 0.0017 max mem: 19788 +Test: [13100/21770] eta: 0:07:05 time: 0.0455 data: 0.0013 max mem: 19788 +Test: [13200/21770] eta: 0:07:00 time: 0.0451 data: 0.0016 max mem: 19788 +Test: [13300/21770] eta: 0:06:56 time: 0.0538 data: 0.0019 max mem: 19788 +Test: [13400/21770] eta: 0:06:51 time: 0.0447 data: 0.0016 max mem: 19788 +Test: [13500/21770] eta: 0:06:46 time: 0.0508 data: 0.0020 max mem: 19788 +Test: [13600/21770] eta: 0:06:41 time: 0.0453 data: 0.0015 max mem: 19788 +Test: [13700/21770] eta: 0:06:36 time: 0.0450 data: 0.0016 max mem: 19788 +Test: [13800/21770] eta: 0:06:32 time: 0.0498 data: 0.0016 max mem: 19788 +Test: [13900/21770] eta: 0:06:27 time: 0.0554 data: 0.0020 max mem: 19788 +Test: [14000/21770] eta: 0:06:22 time: 0.0540 data: 0.0018 max mem: 19788 +Test: [14100/21770] eta: 0:06:17 time: 0.0548 data: 0.0018 max mem: 19788 +Test: [14200/21770] eta: 0:06:13 time: 0.0446 data: 0.0017 max mem: 19788 +Test: [14300/21770] eta: 0:06:08 time: 0.0555 data: 0.0018 max mem: 19788 +Test: [14400/21770] eta: 0:06:03 time: 0.0475 data: 0.0016 max mem: 19788 +Test: [14500/21770] eta: 0:05:58 time: 0.0553 data: 0.0018 max mem: 19788 +Test: [14600/21770] eta: 0:05:53 time: 0.0552 data: 0.0020 max mem: 19788 +Test: [14700/21770] eta: 0:05:48 time: 0.0551 data: 0.0014 max mem: 19788 +Test: [14800/21770] eta: 0:05:44 time: 0.0465 data: 0.0016 max mem: 19788 +Test: [14900/21770] eta: 0:05:39 time: 0.0489 data: 0.0016 max mem: 19788 +Test: [15000/21770] eta: 0:05:34 time: 0.0446 data: 0.0017 max mem: 19788 +Test: [15100/21770] eta: 0:05:29 time: 0.0456 data: 0.0014 max mem: 19788 +Test: [15200/21770] eta: 0:05:24 time: 0.0546 data: 0.0018 max mem: 19788 +Test: [15300/21770] eta: 0:05:19 time: 0.0549 data: 0.0019 max mem: 19788 +Test: [15400/21770] eta: 0:05:14 time: 0.0492 data: 0.0017 max mem: 19788 +Test: [15500/21770] eta: 0:05:09 time: 0.0481 data: 0.0016 max mem: 19788 +Test: [15600/21770] eta: 0:05:04 time: 0.0504 data: 0.0020 max mem: 19788 +Test: [15700/21770] eta: 0:04:59 time: 0.0457 data: 0.0016 max mem: 19788 +Test: [15800/21770] eta: 0:04:54 time: 0.0498 data: 0.0017 max mem: 19788 +Test: [15900/21770] eta: 0:04:49 time: 0.0468 data: 0.0015 max mem: 19788 +Test: [16000/21770] eta: 0:04:44 time: 0.0448 data: 0.0016 max mem: 19788 +Test: [16100/21770] eta: 0:04:40 time: 0.0546 data: 0.0018 max mem: 19788 +Test: [16200/21770] eta: 0:04:35 time: 0.0488 data: 0.0017 max mem: 19788 +Test: [16300/21770] eta: 0:04:30 time: 0.0439 data: 0.0015 max mem: 19788 +Test: [16400/21770] eta: 0:04:25 time: 0.0535 data: 0.0016 max mem: 19788 +Test: [16500/21770] eta: 0:04:20 time: 0.0481 data: 0.0017 max mem: 19788 +Test: [16600/21770] eta: 0:04:15 time: 0.0583 data: 0.0019 max mem: 19788 +Test: [16700/21770] eta: 0:04:10 time: 0.0580 data: 0.0018 max mem: 19788 +Test: [16800/21770] eta: 0:04:05 time: 0.0457 data: 0.0016 max mem: 19788 +Test: [16900/21770] eta: 0:04:00 time: 0.0432 data: 0.0015 max mem: 19788 +Test: [17000/21770] eta: 0:03:55 time: 0.0471 data: 0.0016 max mem: 19788 +Test: [17100/21770] eta: 0:03:50 time: 0.0445 data: 0.0016 max mem: 19788 +Test: [17200/21770] eta: 0:03:45 time: 0.0495 data: 0.0017 max mem: 19788 +Test: [17300/21770] eta: 0:03:40 time: 0.0477 data: 0.0016 max mem: 19788 +Test: [17400/21770] eta: 0:03:35 time: 0.0447 data: 0.0015 max mem: 19788 +Test: [17500/21770] eta: 0:03:30 time: 0.0483 data: 0.0016 max mem: 19788 +Test: [17600/21770] eta: 0:03:25 time: 0.0464 data: 0.0016 max mem: 19788 +Test: [17700/21770] eta: 0:03:21 time: 0.0548 data: 0.0019 max mem: 19788 +Test: [17800/21770] eta: 0:03:16 time: 0.0461 data: 0.0014 max mem: 19788 +Test: [17900/21770] eta: 0:03:11 time: 0.0445 data: 0.0014 max mem: 19788 +Test: [18000/21770] eta: 0:03:06 time: 0.0562 data: 0.0017 max mem: 19788 +Test: [18100/21770] eta: 0:03:01 time: 0.0549 data: 0.0017 max mem: 19788 +Test: [18200/21770] eta: 0:02:56 time: 0.0468 data: 0.0014 max mem: 19788 +Test: [18300/21770] eta: 0:02:51 time: 0.0438 data: 0.0014 max mem: 19788 +Test: [18400/21770] eta: 0:02:46 time: 0.0437 data: 0.0015 max mem: 19788 +Test: [18500/21770] eta: 0:02:41 time: 0.0448 data: 0.0016 max mem: 19788 +Test: [18600/21770] eta: 0:02:36 time: 0.0521 data: 0.0018 max mem: 19788 +Test: [18700/21770] eta: 0:02:31 time: 0.0496 data: 0.0014 max mem: 19788 +Test: [18800/21770] eta: 0:02:26 time: 0.0458 data: 0.0016 max mem: 19788 +Test: [18900/21770] eta: 0:02:21 time: 0.0496 data: 0.0018 max mem: 19788 +Test: [19000/21770] eta: 0:02:16 time: 0.0546 data: 0.0019 max mem: 19788 +Test: [19100/21770] eta: 0:02:11 time: 0.0540 data: 0.0016 max mem: 19788 +Test: [19200/21770] eta: 0:02:06 time: 0.0544 data: 0.0019 max mem: 19788 +Test: [19300/21770] eta: 0:02:01 time: 0.0552 data: 0.0019 max mem: 19788 +Test: [19400/21770] eta: 0:01:57 time: 0.0484 data: 0.0016 max mem: 19788 +Test: [19500/21770] eta: 0:01:52 time: 0.0522 data: 0.0015 max mem: 19788 +Test: [19600/21770] eta: 0:01:47 time: 0.0547 data: 0.0018 max mem: 19788 +Test: [19700/21770] eta: 0:01:42 time: 0.0459 data: 0.0017 max mem: 19788 +Test: [19800/21770] eta: 0:01:37 time: 0.0495 data: 0.0016 max mem: 19788 +Test: [19900/21770] eta: 0:01:32 time: 0.0500 data: 0.0016 max mem: 19788 +Test: [20000/21770] eta: 0:01:27 time: 0.0438 data: 0.0017 max mem: 19788 +Test: [20100/21770] eta: 0:01:22 time: 0.0539 data: 0.0019 max mem: 19788 +Test: [20200/21770] eta: 0:01:17 time: 0.0529 data: 0.0017 max mem: 19788 +Test: [20300/21770] eta: 0:01:12 time: 0.0540 data: 0.0018 max mem: 19788 +Test: [20400/21770] eta: 0:01:07 time: 0.0495 data: 0.0016 max mem: 19788 +Test: [20500/21770] eta: 0:01:02 time: 0.0528 data: 0.0020 max mem: 19788 +Test: [20600/21770] eta: 0:00:57 time: 0.0473 data: 0.0016 max mem: 19788 +Test: [20700/21770] eta: 0:00:52 time: 0.0577 data: 0.0016 max mem: 19788 +Test: [20800/21770] eta: 0:00:47 time: 0.0445 data: 0.0015 max mem: 19788 +Test: [20900/21770] eta: 0:00:42 time: 0.0452 data: 0.0016 max mem: 19788 +Test: [21000/21770] eta: 0:00:38 time: 0.0453 data: 0.0016 max mem: 19788 +Test: [21100/21770] eta: 0:00:33 time: 0.0493 data: 0.0019 max mem: 19788 +Test: [21200/21770] eta: 0:00:28 time: 0.0552 data: 0.0019 max mem: 19788 +Test: [21300/21770] eta: 0:00:23 time: 0.0539 data: 0.0019 max mem: 19788 +Test: [21400/21770] eta: 0:00:18 time: 0.0455 data: 0.0016 max mem: 19788 +Test: [21500/21770] eta: 0:00:13 time: 0.0496 data: 0.0017 max mem: 19788 +Test: [21600/21770] eta: 0:00:08 time: 0.0524 data: 0.0020 max mem: 19788 +Test: [21700/21770] eta: 0:00:03 time: 0.0657 data: 0.0031 max mem: 19788 +Test: Total time: 0:17:57 +Final results: +Mean IoU is 63.90 + + precision@0.5 = 70.96 + precision@0.6 = 65.43 + precision@0.7 = 58.87 + precision@0.8 = 48.05 + precision@0.9 = 23.67 + overall IoU = 64.35 + mean IoU = 63.90 + +Mean accuracy for one-to-zero sample is 86.25 + +Average object IoU 0.6390064396078028 +Overall IoU 64.34917449951172 +Epoch: [29] [ 0/2138] eta: 7:24:13 lr: 1.5644180156981413e-05 loss: 0.0632 (0.0632) time: 12.4667 data: 1.5743 max mem: 19788 +Epoch: [29] [ 10/2138] eta: 2:21:51 lr: 1.5638192972586798e-05 loss: 0.0203 (0.0260) time: 3.9996 data: 0.1450 max mem: 19788 +Epoch: [29] [ 20/2138] eta: 2:09:25 lr: 1.5632205533488817e-05 loss: 0.0203 (0.0233) time: 3.2265 data: 0.0020 max mem: 19788 +Epoch: [29] [ 30/2138] eta: 2:02:00 lr: 1.562621783956824e-05 loss: 0.0216 (0.0236) time: 3.1828 data: 0.0025 max mem: 19788 +Epoch: [29] [ 40/2138] eta: 1:59:08 lr: 1.5620229890705708e-05 loss: 0.0223 (0.0234) time: 3.1347 data: 0.0027 max mem: 19788 +Epoch: [29] [ 50/2138] eta: 1:57:21 lr: 1.561424168678177e-05 loss: 0.0214 (0.0232) time: 3.2169 data: 0.0030 max mem: 19788 +Epoch: [29] [ 60/2138] eta: 1:55:06 lr: 1.5608253227676868e-05 loss: 0.0229 (0.0235) time: 3.1521 data: 0.0029 max mem: 19788 +Epoch: [29] [ 70/2138] eta: 1:53:32 lr: 1.5602264513271333e-05 loss: 0.0216 (0.0233) time: 3.0943 data: 0.0025 max mem: 19788 +Epoch: [29] [ 80/2138] eta: 1:52:10 lr: 1.5596275543445392e-05 loss: 0.0201 (0.0234) time: 3.1083 data: 0.0028 max mem: 19788 +Epoch: [29] [ 90/2138] eta: 1:50:53 lr: 1.5590286318079158e-05 loss: 0.0203 (0.0231) time: 3.0878 data: 0.0028 max mem: 19788 +Epoch: [29] [ 100/2138] eta: 1:49:48 lr: 1.5584296837052648e-05 loss: 0.0213 (0.0231) time: 3.0802 data: 0.0025 max mem: 19788 +Epoch: [29] [ 110/2138] eta: 1:48:50 lr: 1.5578307100245755e-05 loss: 0.0210 (0.0228) time: 3.0892 data: 0.0021 max mem: 19788 +Epoch: [29] [ 120/2138] eta: 1:48:02 lr: 1.5572317107538283e-05 loss: 0.0171 (0.0225) time: 3.1085 data: 0.0021 max mem: 19788 +Epoch: [29] [ 130/2138] eta: 1:47:28 lr: 1.556632685880991e-05 loss: 0.0220 (0.0227) time: 3.1646 data: 0.0022 max mem: 19788 +Epoch: [29] [ 140/2138] eta: 1:46:52 lr: 1.5560336353940228e-05 loss: 0.0220 (0.0227) time: 3.1937 data: 0.0023 max mem: 19788 +Epoch: [29] [ 150/2138] eta: 1:46:06 lr: 1.5554345592808687e-05 loss: 0.0203 (0.0226) time: 3.1423 data: 0.0025 max mem: 19788 +Epoch: [29] [ 160/2138] eta: 1:45:13 lr: 1.5548354575294674e-05 loss: 0.0220 (0.0226) time: 3.0675 data: 0.0027 max mem: 19788 +Epoch: [29] [ 170/2138] eta: 1:44:26 lr: 1.554236330127742e-05 loss: 0.0219 (0.0226) time: 3.0480 data: 0.0028 max mem: 19788 +Epoch: [29] [ 180/2138] eta: 1:43:47 lr: 1.553637177063609e-05 loss: 0.0215 (0.0225) time: 3.0888 data: 0.0031 max mem: 19788 +Epoch: [29] [ 190/2138] eta: 1:43:12 lr: 1.5530379983249705e-05 loss: 0.0207 (0.0223) time: 3.1340 data: 0.0032 max mem: 19788 +Epoch: [29] [ 200/2138] eta: 1:42:37 lr: 1.55243879389972e-05 loss: 0.0196 (0.0223) time: 3.1461 data: 0.0030 max mem: 19788 +Epoch: [29] [ 210/2138] eta: 1:41:51 lr: 1.551839563775739e-05 loss: 0.0221 (0.0223) time: 3.0813 data: 0.0032 max mem: 19788 +Epoch: [29] [ 220/2138] eta: 1:41:10 lr: 1.5512403079408992e-05 loss: 0.0201 (0.0222) time: 3.0437 data: 0.0031 max mem: 19788 +Epoch: [29] [ 230/2138] eta: 1:40:26 lr: 1.55064102638306e-05 loss: 0.0193 (0.0223) time: 3.0406 data: 0.0028 max mem: 19788 +Epoch: [29] [ 240/2138] eta: 1:39:51 lr: 1.5500417190900702e-05 loss: 0.0221 (0.0223) time: 3.0668 data: 0.0027 max mem: 19788 +Epoch: [29] [ 250/2138] eta: 1:39:22 lr: 1.5494423860497683e-05 loss: 0.0204 (0.0222) time: 3.1545 data: 0.0027 max mem: 19788 +Epoch: [29] [ 260/2138] eta: 1:38:42 lr: 1.5488430272499814e-05 loss: 0.0203 (0.0222) time: 3.1174 data: 0.0027 max mem: 19788 +Epoch: [29] [ 270/2138] eta: 1:38:11 lr: 1.5482436426785253e-05 loss: 0.0234 (0.0222) time: 3.1027 data: 0.0028 max mem: 19788 +Epoch: [29] [ 280/2138] eta: 1:37:34 lr: 1.5476442323232057e-05 loss: 0.0221 (0.0221) time: 3.1122 data: 0.0027 max mem: 19788 +Epoch: [29] [ 290/2138] eta: 1:37:07 lr: 1.547044796171816e-05 loss: 0.0200 (0.0222) time: 3.1436 data: 0.0026 max mem: 19788 +Epoch: [29] [ 300/2138] eta: 1:36:38 lr: 1.54644533421214e-05 loss: 0.0204 (0.0222) time: 3.2084 data: 0.0025 max mem: 19788 +Epoch: [29] [ 310/2138] eta: 1:36:02 lr: 1.545845846431949e-05 loss: 0.0203 (0.0221) time: 3.1404 data: 0.0026 max mem: 19788 +Epoch: [29] [ 320/2138] eta: 1:35:25 lr: 1.5452463328190044e-05 loss: 0.0192 (0.0221) time: 3.0675 data: 0.0029 max mem: 19788 +Epoch: [29] [ 330/2138] eta: 1:34:47 lr: 1.5446467933610555e-05 loss: 0.0227 (0.0222) time: 3.0361 data: 0.0030 max mem: 19788 +Epoch: [29] [ 340/2138] eta: 1:34:16 lr: 1.5440472280458422e-05 loss: 0.0227 (0.0222) time: 3.0933 data: 0.0030 max mem: 19788 +Epoch: [29] [ 350/2138] eta: 1:33:46 lr: 1.5434476368610917e-05 loss: 0.0193 (0.0222) time: 3.1722 data: 0.0030 max mem: 19788 +Epoch: [29] [ 360/2138] eta: 1:33:16 lr: 1.5428480197945195e-05 loss: 0.0211 (0.0222) time: 3.1754 data: 0.0026 max mem: 19788 +Epoch: [29] [ 370/2138] eta: 1:32:42 lr: 1.542248376833832e-05 loss: 0.0214 (0.0222) time: 3.1294 data: 0.0024 max mem: 19788 +Epoch: [29] [ 380/2138] eta: 1:32:07 lr: 1.541648707966723e-05 loss: 0.0192 (0.0222) time: 3.0863 data: 0.0026 max mem: 19788 +Epoch: [29] [ 390/2138] eta: 1:31:33 lr: 1.5410490131808762e-05 loss: 0.0189 (0.0221) time: 3.0835 data: 0.0028 max mem: 19788 +Epoch: [29] [ 400/2138] eta: 1:30:58 lr: 1.540449292463963e-05 loss: 0.0197 (0.0221) time: 3.0693 data: 0.0029 max mem: 19788 +Epoch: [29] [ 410/2138] eta: 1:30:28 lr: 1.5398495458036442e-05 loss: 0.0202 (0.0220) time: 3.1108 data: 0.0027 max mem: 19788 +Epoch: [29] [ 420/2138] eta: 1:30:10 lr: 1.5392497731875688e-05 loss: 0.0191 (0.0221) time: 3.3170 data: 0.0025 max mem: 19788 +Epoch: [29] [ 430/2138] eta: 1:29:36 lr: 1.538649974603376e-05 loss: 0.0204 (0.0220) time: 3.2862 data: 0.0026 max mem: 19788 +Epoch: [29] [ 440/2138] eta: 1:29:05 lr: 1.5380501500386918e-05 loss: 0.0211 (0.0223) time: 3.1343 data: 0.0028 max mem: 19788 +Epoch: [29] [ 450/2138] eta: 1:28:35 lr: 1.537450299481133e-05 loss: 0.0208 (0.0222) time: 3.1663 data: 0.0027 max mem: 19788 +Epoch: [29] [ 460/2138] eta: 1:27:59 lr: 1.5368504229183027e-05 loss: 0.0200 (0.0222) time: 3.0987 data: 0.0024 max mem: 19788 +Epoch: [29] [ 470/2138] eta: 1:27:29 lr: 1.5362505203377955e-05 loss: 0.0209 (0.0222) time: 3.1140 data: 0.0024 max mem: 19788 +Epoch: [29] [ 480/2138] eta: 1:26:55 lr: 1.5356505917271923e-05 loss: 0.0219 (0.0222) time: 3.1302 data: 0.0026 max mem: 19788 +Epoch: [29] [ 490/2138] eta: 1:26:25 lr: 1.5350506370740644e-05 loss: 0.0213 (0.0222) time: 3.1282 data: 0.0024 max mem: 19788 +Epoch: [29] [ 500/2138] eta: 1:25:51 lr: 1.53445065636597e-05 loss: 0.0195 (0.0222) time: 3.1319 data: 0.0022 max mem: 19788 +Epoch: [29] [ 510/2138] eta: 1:25:16 lr: 1.533850649590458e-05 loss: 0.0174 (0.0221) time: 3.0438 data: 0.0022 max mem: 19788 +Epoch: [29] [ 520/2138] eta: 1:24:43 lr: 1.533250616735064e-05 loss: 0.0191 (0.0221) time: 3.0626 data: 0.0022 max mem: 19788 +Epoch: [29] [ 530/2138] eta: 1:24:15 lr: 1.5326505577873138e-05 loss: 0.0220 (0.0221) time: 3.1773 data: 0.0024 max mem: 19788 +Epoch: [29] [ 540/2138] eta: 1:23:43 lr: 1.5320504727347206e-05 loss: 0.0198 (0.0221) time: 3.1851 data: 0.0027 max mem: 19788 +Epoch: [29] [ 550/2138] eta: 1:23:08 lr: 1.5314503615647875e-05 loss: 0.0198 (0.0220) time: 3.0742 data: 0.0026 max mem: 19788 +Epoch: [29] [ 560/2138] eta: 1:22:34 lr: 1.530850224265004e-05 loss: 0.0219 (0.0222) time: 3.0370 data: 0.0024 max mem: 19788 +Epoch: [29] [ 570/2138] eta: 1:22:01 lr: 1.5302500608228516e-05 loss: 0.0210 (0.0222) time: 3.0691 data: 0.0024 max mem: 19788 +Epoch: [29] [ 580/2138] eta: 1:21:26 lr: 1.529649871225796e-05 loss: 0.0197 (0.0222) time: 3.0533 data: 0.0023 max mem: 19788 +Epoch: [29] [ 590/2138] eta: 1:20:53 lr: 1.5290496554612953e-05 loss: 0.0216 (0.0222) time: 3.0406 data: 0.0023 max mem: 19788 +Epoch: [29] [ 600/2138] eta: 1:20:19 lr: 1.5284494135167935e-05 loss: 0.0218 (0.0223) time: 3.0407 data: 0.0025 max mem: 19788 +Epoch: [29] [ 610/2138] eta: 1:19:46 lr: 1.5278491453797253e-05 loss: 0.0217 (0.0223) time: 3.0518 data: 0.0025 max mem: 19788 +Epoch: [29] [ 620/2138] eta: 1:19:16 lr: 1.5272488510375112e-05 loss: 0.0216 (0.0223) time: 3.1381 data: 0.0028 max mem: 19788 +Epoch: [29] [ 630/2138] eta: 1:18:43 lr: 1.526648530477563e-05 loss: 0.0216 (0.0224) time: 3.1205 data: 0.0027 max mem: 19788 +Epoch: [29] [ 640/2138] eta: 1:18:10 lr: 1.5260481836872786e-05 loss: 0.0198 (0.0224) time: 3.0610 data: 0.0023 max mem: 19788 +Epoch: [29] [ 650/2138] eta: 1:17:39 lr: 1.5254478106540462e-05 loss: 0.0218 (0.0224) time: 3.0935 data: 0.0024 max mem: 19788 +Epoch: [29] [ 660/2138] eta: 1:17:05 lr: 1.5248474113652411e-05 loss: 0.0206 (0.0224) time: 3.0727 data: 0.0025 max mem: 19788 +Epoch: [29] [ 670/2138] eta: 1:16:32 lr: 1.524246985808227e-05 loss: 0.0194 (0.0224) time: 3.0450 data: 0.0026 max mem: 19788 +Epoch: [29] [ 680/2138] eta: 1:15:59 lr: 1.5236465339703573e-05 loss: 0.0183 (0.0223) time: 3.0391 data: 0.0026 max mem: 19788 +Epoch: [29] [ 690/2138] eta: 1:15:26 lr: 1.523046055838972e-05 loss: 0.0189 (0.0223) time: 3.0367 data: 0.0024 max mem: 19788 +Epoch: [29] [ 700/2138] eta: 1:14:57 lr: 1.5224455514014014e-05 loss: 0.0201 (0.0223) time: 3.1389 data: 0.0026 max mem: 19788 +Epoch: [29] [ 710/2138] eta: 1:14:28 lr: 1.5218450206449619e-05 loss: 0.0207 (0.0223) time: 3.2354 data: 0.0030 max mem: 19788 +Epoch: [29] [ 720/2138] eta: 1:13:54 lr: 1.5212444635569606e-05 loss: 0.0202 (0.0222) time: 3.1408 data: 0.0027 max mem: 19788 +Epoch: [29] [ 730/2138] eta: 1:13:21 lr: 1.5206438801246906e-05 loss: 0.0199 (0.0222) time: 3.0316 data: 0.0025 max mem: 19788 +Epoch: [29] [ 740/2138] eta: 1:12:49 lr: 1.5200432703354355e-05 loss: 0.0204 (0.0222) time: 3.0476 data: 0.0026 max mem: 19788 +Epoch: [29] [ 750/2138] eta: 1:12:18 lr: 1.5194426341764653e-05 loss: 0.0215 (0.0222) time: 3.0934 data: 0.0029 max mem: 19788 +Epoch: [29] [ 760/2138] eta: 1:11:47 lr: 1.5188419716350399e-05 loss: 0.0215 (0.0222) time: 3.1342 data: 0.0029 max mem: 19788 +Epoch: [29] [ 770/2138] eta: 1:11:14 lr: 1.5182412826984052e-05 loss: 0.0199 (0.0222) time: 3.0944 data: 0.0026 max mem: 19788 +Epoch: [29] [ 780/2138] eta: 1:10:42 lr: 1.5176405673537983e-05 loss: 0.0190 (0.0222) time: 3.0718 data: 0.0027 max mem: 19788 +Epoch: [29] [ 790/2138] eta: 1:10:10 lr: 1.5170398255884416e-05 loss: 0.0197 (0.0221) time: 3.0693 data: 0.0026 max mem: 19788 +Epoch: [29] [ 800/2138] eta: 1:09:40 lr: 1.5164390573895482e-05 loss: 0.0206 (0.0221) time: 3.1221 data: 0.0026 max mem: 19788 +Epoch: [29] [ 810/2138] eta: 1:09:12 lr: 1.5158382627443169e-05 loss: 0.0213 (0.0221) time: 3.2737 data: 0.0025 max mem: 19788 +Epoch: [29] [ 820/2138] eta: 1:08:39 lr: 1.515237441639937e-05 loss: 0.0211 (0.0221) time: 3.1905 data: 0.0025 max mem: 19788 +Epoch: [29] [ 830/2138] eta: 1:08:07 lr: 1.5146365940635843e-05 loss: 0.0188 (0.0221) time: 3.0372 data: 0.0026 max mem: 19788 +Epoch: [29] [ 840/2138] eta: 1:07:35 lr: 1.5140357200024241e-05 loss: 0.0178 (0.0221) time: 3.0509 data: 0.0027 max mem: 19788 +Epoch: [29] [ 850/2138] eta: 1:07:04 lr: 1.5134348194436082e-05 loss: 0.0210 (0.0221) time: 3.1045 data: 0.0027 max mem: 19788 +Epoch: [29] [ 860/2138] eta: 1:06:31 lr: 1.512833892374278e-05 loss: 0.0210 (0.0222) time: 3.0966 data: 0.0024 max mem: 19788 +Epoch: [29] [ 870/2138] eta: 1:05:59 lr: 1.5122329387815614e-05 loss: 0.0195 (0.0222) time: 3.0627 data: 0.0024 max mem: 19788 +Epoch: [29] [ 880/2138] eta: 1:05:27 lr: 1.5116319586525767e-05 loss: 0.0189 (0.0222) time: 3.0763 data: 0.0026 max mem: 19788 +Epoch: [29] [ 890/2138] eta: 1:04:59 lr: 1.5110309519744276e-05 loss: 0.0197 (0.0222) time: 3.2131 data: 0.0028 max mem: 19788 +Epoch: [29] [ 900/2138] eta: 1:04:28 lr: 1.5104299187342078e-05 loss: 0.0213 (0.0222) time: 3.2345 data: 0.0026 max mem: 19788 +Epoch: [29] [ 910/2138] eta: 1:03:56 lr: 1.5098288589189977e-05 loss: 0.0212 (0.0222) time: 3.1031 data: 0.0024 max mem: 19788 +Epoch: [29] [ 920/2138] eta: 1:03:24 lr: 1.5092277725158669e-05 loss: 0.0186 (0.0222) time: 3.0607 data: 0.0027 max mem: 19788 +Epoch: [29] [ 930/2138] eta: 1:02:53 lr: 1.5086266595118717e-05 loss: 0.0214 (0.0222) time: 3.0713 data: 0.0026 max mem: 19788 +Epoch: [29] [ 940/2138] eta: 1:02:22 lr: 1.5080255198940579e-05 loss: 0.0237 (0.0222) time: 3.1486 data: 0.0027 max mem: 19788 +Epoch: [29] [ 950/2138] eta: 1:01:50 lr: 1.5074243536494582e-05 loss: 0.0212 (0.0222) time: 3.1196 data: 0.0028 max mem: 19788 +Epoch: [29] [ 960/2138] eta: 1:01:18 lr: 1.5068231607650924e-05 loss: 0.0223 (0.0222) time: 3.0523 data: 0.0024 max mem: 19788 +Epoch: [29] [ 970/2138] eta: 1:00:47 lr: 1.5062219412279704e-05 loss: 0.0244 (0.0222) time: 3.0833 data: 0.0022 max mem: 19788 +Epoch: [29] [ 980/2138] eta: 1:00:17 lr: 1.505620695025088e-05 loss: 0.0190 (0.0222) time: 3.1908 data: 0.0025 max mem: 19788 +Epoch: [29] [ 990/2138] eta: 0:59:47 lr: 1.5050194221434305e-05 loss: 0.0184 (0.0222) time: 3.2575 data: 0.0026 max mem: 19788 +Epoch: [29] [1000/2138] eta: 0:59:15 lr: 1.5044181225699693e-05 loss: 0.0184 (0.0221) time: 3.1397 data: 0.0027 max mem: 19788 +Epoch: [29] [1010/2138] eta: 0:58:43 lr: 1.5038167962916664e-05 loss: 0.0187 (0.0222) time: 3.0704 data: 0.0028 max mem: 19788 +Epoch: [29] [1020/2138] eta: 0:58:12 lr: 1.5032154432954676e-05 loss: 0.0197 (0.0221) time: 3.1217 data: 0.0026 max mem: 19788 +Epoch: [29] [1030/2138] eta: 0:57:40 lr: 1.5026140635683105e-05 loss: 0.0192 (0.0221) time: 3.0848 data: 0.0025 max mem: 19788 +Epoch: [29] [1040/2138] eta: 0:57:08 lr: 1.5020126570971178e-05 loss: 0.0202 (0.0221) time: 3.0296 data: 0.0029 max mem: 19788 +Epoch: [29] [1050/2138] eta: 0:56:36 lr: 1.5014112238688018e-05 loss: 0.0222 (0.0221) time: 3.0279 data: 0.0032 max mem: 19788 +Epoch: [29] [1060/2138] eta: 0:56:04 lr: 1.5008097638702608e-05 loss: 0.0217 (0.0221) time: 3.0634 data: 0.0031 max mem: 19788 +Epoch: [29] [1070/2138] eta: 0:55:33 lr: 1.5002082770883827e-05 loss: 0.0209 (0.0221) time: 3.1304 data: 0.0029 max mem: 19788 +Epoch: [29] [1080/2138] eta: 0:55:02 lr: 1.4996067635100413e-05 loss: 0.0201 (0.0221) time: 3.1518 data: 0.0027 max mem: 19788 +Epoch: [29] [1090/2138] eta: 0:54:31 lr: 1.4990052231221002e-05 loss: 0.0204 (0.0222) time: 3.1168 data: 0.0026 max mem: 19788 +Epoch: [29] [1100/2138] eta: 0:54:00 lr: 1.4984036559114081e-05 loss: 0.0228 (0.0222) time: 3.1130 data: 0.0025 max mem: 19788 +Epoch: [29] [1110/2138] eta: 0:53:28 lr: 1.4978020618648043e-05 loss: 0.0216 (0.0222) time: 3.1034 data: 0.0025 max mem: 19788 +Epoch: [29] [1120/2138] eta: 0:52:56 lr: 1.4972004409691127e-05 loss: 0.0200 (0.0222) time: 3.0436 data: 0.0027 max mem: 19788 +Epoch: [29] [1130/2138] eta: 0:52:25 lr: 1.4965987932111477e-05 loss: 0.0196 (0.0221) time: 3.0703 data: 0.0025 max mem: 19788 +Epoch: [29] [1140/2138] eta: 0:51:54 lr: 1.4959971185777093e-05 loss: 0.0198 (0.0221) time: 3.1287 data: 0.0025 max mem: 19788 +Epoch: [29] [1150/2138] eta: 0:51:22 lr: 1.4953954170555868e-05 loss: 0.0180 (0.0221) time: 3.1226 data: 0.0029 max mem: 19788 +Epoch: [29] [1160/2138] eta: 0:50:51 lr: 1.4947936886315547e-05 loss: 0.0177 (0.0221) time: 3.0999 data: 0.0031 max mem: 19788 +Epoch: [29] [1170/2138] eta: 0:50:20 lr: 1.4941919332923781e-05 loss: 0.0203 (0.0221) time: 3.0880 data: 0.0028 max mem: 19788 +Epoch: [29] [1180/2138] eta: 0:49:48 lr: 1.4935901510248065e-05 loss: 0.0206 (0.0221) time: 3.0616 data: 0.0026 max mem: 19788 +Epoch: [29] [1190/2138] eta: 0:49:16 lr: 1.4929883418155801e-05 loss: 0.0209 (0.0221) time: 3.0479 data: 0.0024 max mem: 19788 +Epoch: [29] [1200/2138] eta: 0:48:44 lr: 1.4923865056514239e-05 loss: 0.0174 (0.0221) time: 3.0465 data: 0.0025 max mem: 19788 +Epoch: [29] [1210/2138] eta: 0:48:12 lr: 1.4917846425190523e-05 loss: 0.0225 (0.0221) time: 3.0296 data: 0.0028 max mem: 19788 +Epoch: [29] [1220/2138] eta: 0:47:42 lr: 1.491182752405166e-05 loss: 0.0191 (0.0220) time: 3.1170 data: 0.0026 max mem: 19788 +Epoch: [29] [1230/2138] eta: 0:47:10 lr: 1.4905808352964542e-05 loss: 0.0191 (0.0220) time: 3.1472 data: 0.0027 max mem: 19788 +Epoch: [29] [1240/2138] eta: 0:46:39 lr: 1.489978891179592e-05 loss: 0.0191 (0.0220) time: 3.0905 data: 0.0027 max mem: 19788 +Epoch: [29] [1250/2138] eta: 0:46:08 lr: 1.4893769200412442e-05 loss: 0.0188 (0.0220) time: 3.1418 data: 0.0023 max mem: 19788 +Epoch: [29] [1260/2138] eta: 0:45:37 lr: 1.488774921868061e-05 loss: 0.0181 (0.0220) time: 3.1392 data: 0.0025 max mem: 19788 +Epoch: [29] [1270/2138] eta: 0:45:05 lr: 1.4881728966466807e-05 loss: 0.0195 (0.0220) time: 3.0535 data: 0.0025 max mem: 19788 +Epoch: [29] [1280/2138] eta: 0:44:33 lr: 1.4875708443637295e-05 loss: 0.0204 (0.0220) time: 3.0357 data: 0.0023 max mem: 19788 +Epoch: [29] [1290/2138] eta: 0:44:02 lr: 1.4869687650058197e-05 loss: 0.0219 (0.0220) time: 3.0449 data: 0.0022 max mem: 19788 +Epoch: [29] [1300/2138] eta: 0:43:30 lr: 1.4863666585595532e-05 loss: 0.0219 (0.0220) time: 3.0343 data: 0.0022 max mem: 19788 +Epoch: [29] [1310/2138] eta: 0:42:58 lr: 1.485764525011516e-05 loss: 0.0199 (0.0220) time: 3.0256 data: 0.0023 max mem: 19788 +Epoch: [29] [1320/2138] eta: 0:42:27 lr: 1.4851623643482851e-05 loss: 0.0199 (0.0220) time: 3.0375 data: 0.0027 max mem: 19788 +Epoch: [29] [1330/2138] eta: 0:41:58 lr: 1.4845601765564212e-05 loss: 0.0207 (0.0220) time: 3.2898 data: 0.0026 max mem: 19788 +Epoch: [29] [1340/2138] eta: 0:41:28 lr: 1.4839579616224755e-05 loss: 0.0228 (0.0220) time: 3.4132 data: 0.0024 max mem: 19788 +Epoch: [29] [1350/2138] eta: 0:40:57 lr: 1.4833557195329837e-05 loss: 0.0260 (0.0220) time: 3.2429 data: 0.0025 max mem: 19788 +Epoch: [29] [1360/2138] eta: 0:40:26 lr: 1.4827534502744711e-05 loss: 0.0228 (0.0220) time: 3.1627 data: 0.0024 max mem: 19788 +Epoch: [29] [1370/2138] eta: 0:39:56 lr: 1.4821511538334482e-05 loss: 0.0202 (0.0220) time: 3.1928 data: 0.0025 max mem: 19788 +Epoch: [29] [1380/2138] eta: 0:39:24 lr: 1.4815488301964145e-05 loss: 0.0207 (0.0220) time: 3.1355 data: 0.0027 max mem: 19788 +Epoch: [29] [1390/2138] eta: 0:38:52 lr: 1.4809464793498548e-05 loss: 0.0195 (0.0220) time: 3.0237 data: 0.0028 max mem: 19788 +Epoch: [29] [1400/2138] eta: 0:38:21 lr: 1.4803441012802432e-05 loss: 0.0193 (0.0220) time: 3.0901 data: 0.0027 max mem: 19788 +Epoch: [29] [1410/2138] eta: 0:37:50 lr: 1.4797416959740393e-05 loss: 0.0191 (0.0220) time: 3.1059 data: 0.0027 max mem: 19788 +Epoch: [29] [1420/2138] eta: 0:37:19 lr: 1.4791392634176907e-05 loss: 0.0189 (0.0220) time: 3.1415 data: 0.0028 max mem: 19788 +Epoch: [29] [1430/2138] eta: 0:36:48 lr: 1.4785368035976313e-05 loss: 0.0190 (0.0220) time: 3.1433 data: 0.0026 max mem: 19788 +Epoch: [29] [1440/2138] eta: 0:36:17 lr: 1.4779343165002835e-05 loss: 0.0197 (0.0220) time: 3.1119 data: 0.0027 max mem: 19788 +Epoch: [29] [1450/2138] eta: 0:35:46 lr: 1.4773318021120547e-05 loss: 0.0221 (0.0220) time: 3.2067 data: 0.0027 max mem: 19788 +Epoch: [29] [1460/2138] eta: 0:35:15 lr: 1.4767292604193422e-05 loss: 0.0209 (0.0220) time: 3.2155 data: 0.0024 max mem: 19788 +Epoch: [29] [1470/2138] eta: 0:34:44 lr: 1.476126691408527e-05 loss: 0.0179 (0.0220) time: 3.1536 data: 0.0026 max mem: 19788 +Epoch: [29] [1480/2138] eta: 0:34:13 lr: 1.4755240950659802e-05 loss: 0.0173 (0.0220) time: 3.1493 data: 0.0028 max mem: 19788 +Epoch: [29] [1490/2138] eta: 0:33:42 lr: 1.4749214713780576e-05 loss: 0.0191 (0.0220) time: 3.1541 data: 0.0029 max mem: 19788 +Epoch: [29] [1500/2138] eta: 0:33:10 lr: 1.4743188203311037e-05 loss: 0.0216 (0.0220) time: 3.1028 data: 0.0027 max mem: 19788 +Epoch: [29] [1510/2138] eta: 0:32:39 lr: 1.4737161419114488e-05 loss: 0.0201 (0.0220) time: 3.0455 data: 0.0024 max mem: 19788 +Epoch: [29] [1520/2138] eta: 0:32:07 lr: 1.4731134361054108e-05 loss: 0.0201 (0.0220) time: 3.0469 data: 0.0025 max mem: 19788 +Epoch: [29] [1530/2138] eta: 0:31:37 lr: 1.472510702899294e-05 loss: 0.0211 (0.0220) time: 3.1475 data: 0.0025 max mem: 19788 +Epoch: [29] [1540/2138] eta: 0:31:05 lr: 1.4719079422793907e-05 loss: 0.0216 (0.0220) time: 3.1359 data: 0.0025 max mem: 19788 +Epoch: [29] [1550/2138] eta: 0:30:34 lr: 1.4713051542319784e-05 loss: 0.0209 (0.0220) time: 3.1068 data: 0.0025 max mem: 19788 +Epoch: [29] [1560/2138] eta: 0:30:03 lr: 1.4707023387433234e-05 loss: 0.0220 (0.0220) time: 3.1487 data: 0.0027 max mem: 19788 +Epoch: [29] [1570/2138] eta: 0:29:32 lr: 1.4700994957996773e-05 loss: 0.0221 (0.0220) time: 3.0867 data: 0.0031 max mem: 19788 +Epoch: [29] [1580/2138] eta: 0:29:00 lr: 1.4694966253872785e-05 loss: 0.0204 (0.0220) time: 3.0538 data: 0.0030 max mem: 19788 +Epoch: [29] [1590/2138] eta: 0:28:29 lr: 1.4688937274923544e-05 loss: 0.0216 (0.0220) time: 3.0714 data: 0.0027 max mem: 19788 +Epoch: [29] [1600/2138] eta: 0:27:57 lr: 1.4682908021011164e-05 loss: 0.0235 (0.0220) time: 3.0748 data: 0.0028 max mem: 19788 +Epoch: [29] [1610/2138] eta: 0:27:26 lr: 1.4676878491997646e-05 loss: 0.0235 (0.0220) time: 3.1249 data: 0.0028 max mem: 19788 +Epoch: [29] [1620/2138] eta: 0:26:56 lr: 1.4670848687744846e-05 loss: 0.0184 (0.0220) time: 3.2416 data: 0.0027 max mem: 19788 +Epoch: [29] [1630/2138] eta: 0:26:25 lr: 1.4664818608114506e-05 loss: 0.0206 (0.0220) time: 3.2430 data: 0.0026 max mem: 19788 +Epoch: [29] [1640/2138] eta: 0:25:54 lr: 1.4658788252968209e-05 loss: 0.0212 (0.0220) time: 3.2048 data: 0.0026 max mem: 19788 +Epoch: [29] [1650/2138] eta: 0:25:22 lr: 1.4652757622167428e-05 loss: 0.0212 (0.0220) time: 3.1320 data: 0.0029 max mem: 19788 +Epoch: [29] [1660/2138] eta: 0:24:51 lr: 1.4646726715573492e-05 loss: 0.0220 (0.0220) time: 3.0491 data: 0.0031 max mem: 19788 +Epoch: [29] [1670/2138] eta: 0:24:20 lr: 1.4640695533047602e-05 loss: 0.0195 (0.0220) time: 3.0628 data: 0.0030 max mem: 19788 +Epoch: [29] [1680/2138] eta: 0:23:49 lr: 1.4634664074450815e-05 loss: 0.0193 (0.0219) time: 3.0878 data: 0.0027 max mem: 19788 +Epoch: [29] [1690/2138] eta: 0:23:17 lr: 1.462863233964407e-05 loss: 0.0206 (0.0220) time: 3.0556 data: 0.0025 max mem: 19788 +Epoch: [29] [1700/2138] eta: 0:22:46 lr: 1.4622600328488159e-05 loss: 0.0208 (0.0219) time: 3.0049 data: 0.0028 max mem: 19788 +Epoch: [29] [1710/2138] eta: 0:22:14 lr: 1.4616568040843753e-05 loss: 0.0196 (0.0219) time: 3.0221 data: 0.0028 max mem: 19788 +Epoch: [29] [1720/2138] eta: 0:21:43 lr: 1.4610535476571366e-05 loss: 0.0216 (0.0219) time: 3.0457 data: 0.0028 max mem: 19788 +Epoch: [29] [1730/2138] eta: 0:21:11 lr: 1.4604502635531412e-05 loss: 0.0232 (0.0219) time: 3.0411 data: 0.0030 max mem: 19788 +Epoch: [29] [1740/2138] eta: 0:20:40 lr: 1.4598469517584132e-05 loss: 0.0200 (0.0219) time: 3.0541 data: 0.0030 max mem: 19788 +Epoch: [29] [1750/2138] eta: 0:20:09 lr: 1.4592436122589667e-05 loss: 0.0205 (0.0219) time: 3.1041 data: 0.0030 max mem: 19788 +Epoch: [29] [1760/2138] eta: 0:19:38 lr: 1.4586402450407996e-05 loss: 0.0205 (0.0219) time: 3.1540 data: 0.0030 max mem: 19788 +Epoch: [29] [1770/2138] eta: 0:19:07 lr: 1.4580368500898984e-05 loss: 0.0191 (0.0219) time: 3.1320 data: 0.0026 max mem: 19788 +Epoch: [29] [1780/2138] eta: 0:18:36 lr: 1.4574334273922339e-05 loss: 0.0183 (0.0219) time: 3.1669 data: 0.0024 max mem: 19788 +Epoch: [29] [1790/2138] eta: 0:18:05 lr: 1.4568299769337659e-05 loss: 0.0185 (0.0219) time: 3.1786 data: 0.0025 max mem: 19788 +Epoch: [29] [1800/2138] eta: 0:17:33 lr: 1.4562264987004379e-05 loss: 0.0236 (0.0219) time: 3.1202 data: 0.0025 max mem: 19788 +Epoch: [29] [1810/2138] eta: 0:17:02 lr: 1.4556229926781825e-05 loss: 0.0221 (0.0219) time: 3.1496 data: 0.0027 max mem: 19788 +Epoch: [29] [1820/2138] eta: 0:16:31 lr: 1.4550194588529165e-05 loss: 0.0201 (0.0219) time: 3.1913 data: 0.0026 max mem: 19788 +Epoch: [29] [1830/2138] eta: 0:16:00 lr: 1.4544158972105443e-05 loss: 0.0190 (0.0219) time: 3.1845 data: 0.0023 max mem: 19788 +Epoch: [29] [1840/2138] eta: 0:15:29 lr: 1.4538123077369557e-05 loss: 0.0205 (0.0219) time: 3.0870 data: 0.0023 max mem: 19788 +Epoch: [29] [1850/2138] eta: 0:14:58 lr: 1.4532086904180284e-05 loss: 0.0214 (0.0219) time: 3.0248 data: 0.0022 max mem: 19788 +Epoch: [29] [1860/2138] eta: 0:14:26 lr: 1.4526050452396245e-05 loss: 0.0214 (0.0219) time: 3.0320 data: 0.0023 max mem: 19788 +Epoch: [29] [1870/2138] eta: 0:13:55 lr: 1.452001372187594e-05 loss: 0.0221 (0.0219) time: 3.0364 data: 0.0028 max mem: 19788 +Epoch: [29] [1880/2138] eta: 0:13:24 lr: 1.4513976712477725e-05 loss: 0.0190 (0.0219) time: 3.0955 data: 0.0032 max mem: 19788 +Epoch: [29] [1890/2138] eta: 0:12:53 lr: 1.4507939424059808e-05 loss: 0.0177 (0.0219) time: 3.2188 data: 0.0030 max mem: 19788 +Epoch: [29] [1900/2138] eta: 0:12:22 lr: 1.4501901856480282e-05 loss: 0.0193 (0.0219) time: 3.2704 data: 0.0026 max mem: 19788 +Epoch: [29] [1910/2138] eta: 0:11:51 lr: 1.4495864009597083e-05 loss: 0.0193 (0.0219) time: 3.1692 data: 0.0024 max mem: 19788 +Epoch: [29] [1920/2138] eta: 0:11:19 lr: 1.4489825883268019e-05 loss: 0.0185 (0.0218) time: 3.1297 data: 0.0026 max mem: 19788 +Epoch: [29] [1930/2138] eta: 0:10:48 lr: 1.4483787477350752e-05 loss: 0.0186 (0.0218) time: 3.1487 data: 0.0026 max mem: 19788 +Epoch: [29] [1940/2138] eta: 0:10:17 lr: 1.4477748791702819e-05 loss: 0.0199 (0.0218) time: 3.1139 data: 0.0024 max mem: 19788 +Epoch: [29] [1950/2138] eta: 0:09:46 lr: 1.4471709826181595e-05 loss: 0.0202 (0.0218) time: 3.1200 data: 0.0024 max mem: 19788 +Epoch: [29] [1960/2138] eta: 0:09:15 lr: 1.446567058064435e-05 loss: 0.0202 (0.0218) time: 3.1646 data: 0.0026 max mem: 19788 +Epoch: [29] [1970/2138] eta: 0:08:44 lr: 1.4459631054948175e-05 loss: 0.0189 (0.0218) time: 3.2840 data: 0.0026 max mem: 19788 +Epoch: [29] [1980/2138] eta: 0:08:13 lr: 1.445359124895006e-05 loss: 0.0207 (0.0218) time: 3.2225 data: 0.0024 max mem: 19788 +Epoch: [29] [1990/2138] eta: 0:07:41 lr: 1.4447551162506823e-05 loss: 0.0202 (0.0218) time: 3.1157 data: 0.0026 max mem: 19788 +Epoch: [29] [2000/2138] eta: 0:07:10 lr: 1.4441510795475171e-05 loss: 0.0195 (0.0218) time: 3.0952 data: 0.0026 max mem: 19788 +Epoch: [29] [2010/2138] eta: 0:06:39 lr: 1.4435470147711644e-05 loss: 0.0211 (0.0218) time: 3.0362 data: 0.0028 max mem: 19788 +Epoch: [29] [2020/2138] eta: 0:06:08 lr: 1.4429429219072665e-05 loss: 0.0221 (0.0218) time: 3.0660 data: 0.0028 max mem: 19788 +Epoch: [29] [2030/2138] eta: 0:05:36 lr: 1.4423388009414499e-05 loss: 0.0199 (0.0218) time: 3.0630 data: 0.0026 max mem: 19788 +Epoch: [29] [2040/2138] eta: 0:05:05 lr: 1.4417346518593285e-05 loss: 0.0192 (0.0218) time: 3.0201 data: 0.0028 max mem: 19788 +Epoch: [29] [2050/2138] eta: 0:04:34 lr: 1.441130474646501e-05 loss: 0.0200 (0.0218) time: 3.0296 data: 0.0028 max mem: 19788 +Epoch: [29] [2060/2138] eta: 0:04:03 lr: 1.4405262692885533e-05 loss: 0.0200 (0.0218) time: 3.0919 data: 0.0029 max mem: 19788 +Epoch: [29] [2070/2138] eta: 0:03:32 lr: 1.4399220357710549e-05 loss: 0.0179 (0.0218) time: 3.1424 data: 0.0029 max mem: 19788 +Epoch: [29] [2080/2138] eta: 0:03:00 lr: 1.4393177740795644e-05 loss: 0.0174 (0.0218) time: 3.0994 data: 0.0026 max mem: 19788 +Epoch: [29] [2090/2138] eta: 0:02:29 lr: 1.4387134841996228e-05 loss: 0.0220 (0.0218) time: 3.1422 data: 0.0025 max mem: 19788 +Epoch: [29] [2100/2138] eta: 0:01:58 lr: 1.4381091661167604e-05 loss: 0.0214 (0.0218) time: 3.2463 data: 0.0025 max mem: 19788 +Epoch: [29] [2110/2138] eta: 0:01:27 lr: 1.4375048198164895e-05 loss: 0.0244 (0.0218) time: 3.2046 data: 0.0027 max mem: 19788 +Epoch: [29] [2120/2138] eta: 0:00:56 lr: 1.4369004452843121e-05 loss: 0.0249 (0.0218) time: 3.1512 data: 0.0027 max mem: 19788 +Epoch: [29] [2130/2138] eta: 0:00:24 lr: 1.4362960425057128e-05 loss: 0.0225 (0.0219) time: 3.1123 data: 0.0025 max mem: 19788 +Epoch: [29] Total time: 1:51:10 +Test: [ 0/21770] eta: 17:26:24 time: 2.8840 data: 2.4869 max mem: 19788 +Test: [ 100/21770] eta: 0:27:37 time: 0.0527 data: 0.0018 max mem: 19788 +Test: [ 200/21770] eta: 0:21:53 time: 0.0436 data: 0.0016 max mem: 19788 +Test: [ 300/21770] eta: 0:19:49 time: 0.0489 data: 0.0016 max mem: 19788 +Test: [ 400/21770] eta: 0:19:21 time: 0.0501 data: 0.0018 max mem: 19788 +Test: [ 500/21770] eta: 0:19:01 time: 0.0470 data: 0.0018 max mem: 19788 +Test: [ 600/21770] eta: 0:18:25 time: 0.0448 data: 0.0017 max mem: 19788 +Test: [ 700/21770] eta: 0:17:58 time: 0.0498 data: 0.0018 max mem: 19788 +Test: [ 800/21770] eta: 0:17:58 time: 0.0545 data: 0.0018 max mem: 19788 +Test: [ 900/21770] eta: 0:17:46 time: 0.0446 data: 0.0018 max mem: 19788 +Test: [ 1000/21770] eta: 0:17:30 time: 0.0445 data: 0.0015 max mem: 19788 +Test: [ 1100/21770] eta: 0:17:22 time: 0.0438 data: 0.0014 max mem: 19788 +Test: [ 1200/21770] eta: 0:17:11 time: 0.0447 data: 0.0018 max mem: 19788 +Test: [ 1300/21770] eta: 0:17:00 time: 0.0505 data: 0.0017 max mem: 19788 +Test: [ 1400/21770] eta: 0:16:58 time: 0.0518 data: 0.0018 max mem: 19788 +Test: [ 1500/21770] eta: 0:16:49 time: 0.0440 data: 0.0016 max mem: 19788 +Test: [ 1600/21770] eta: 0:16:38 time: 0.0436 data: 0.0017 max mem: 19788 +Test: [ 1700/21770] eta: 0:16:33 time: 0.0493 data: 0.0017 max mem: 19788 +Test: [ 1800/21770] eta: 0:16:26 time: 0.0434 data: 0.0015 max mem: 19788 +Test: [ 1900/21770] eta: 0:16:15 time: 0.0448 data: 0.0017 max mem: 19788 +Test: [ 2000/21770] eta: 0:16:13 time: 0.0516 data: 0.0017 max mem: 19788 +Test: [ 2100/21770] eta: 0:16:04 time: 0.0443 data: 0.0015 max mem: 19788 +Test: [ 2200/21770] eta: 0:15:59 time: 0.0521 data: 0.0017 max mem: 19788 +Test: [ 2300/21770] eta: 0:15:56 time: 0.0568 data: 0.0014 max mem: 19788 +Test: [ 2400/21770] eta: 0:15:50 time: 0.0457 data: 0.0021 max mem: 19788 +Test: [ 2500/21770] eta: 0:15:46 time: 0.0566 data: 0.0018 max mem: 19788 +Test: [ 2600/21770] eta: 0:15:42 time: 0.0475 data: 0.0035 max mem: 19788 +Test: [ 2700/21770] eta: 0:15:36 time: 0.0443 data: 0.0015 max mem: 19788 +Test: [ 2800/21770] eta: 0:15:31 time: 0.0531 data: 0.0019 max mem: 19788 +Test: [ 2900/21770] eta: 0:15:27 time: 0.0520 data: 0.0019 max mem: 19788 +Test: [ 3000/21770] eta: 0:15:20 time: 0.0474 data: 0.0017 max mem: 19788 +Test: [ 3100/21770] eta: 0:15:17 time: 0.0582 data: 0.0017 max mem: 19788 +Test: [ 3200/21770] eta: 0:15:11 time: 0.0449 data: 0.0014 max mem: 19788 +Test: [ 3300/21770] eta: 0:15:04 time: 0.0462 data: 0.0015 max mem: 19788 +Test: [ 3400/21770] eta: 0:14:58 time: 0.0511 data: 0.0015 max mem: 19788 +Test: [ 3500/21770] eta: 0:14:54 time: 0.0551 data: 0.0018 max mem: 19788 +Test: [ 3600/21770] eta: 0:14:51 time: 0.0467 data: 0.0016 max mem: 19788 +Test: [ 3700/21770] eta: 0:14:47 time: 0.0566 data: 0.0020 max mem: 19788 +Test: [ 3800/21770] eta: 0:14:44 time: 0.0589 data: 0.0019 max mem: 19788 +Test: [ 3900/21770] eta: 0:14:38 time: 0.0459 data: 0.0017 max mem: 19788 +Test: [ 4000/21770] eta: 0:14:31 time: 0.0447 data: 0.0015 max mem: 19788 +Test: [ 4100/21770] eta: 0:14:27 time: 0.0431 data: 0.0015 max mem: 19788 +Test: [ 4200/21770] eta: 0:14:22 time: 0.0449 data: 0.0015 max mem: 19788 +Test: [ 4300/21770] eta: 0:14:19 time: 0.0490 data: 0.0016 max mem: 19788 +Test: [ 4400/21770] eta: 0:14:13 time: 0.0554 data: 0.0019 max mem: 19788 +Test: [ 4500/21770] eta: 0:14:10 time: 0.0567 data: 0.0016 max mem: 19788 +Test: [ 4600/21770] eta: 0:14:06 time: 0.0491 data: 0.0015 max mem: 19788 +Test: [ 4700/21770] eta: 0:14:02 time: 0.0523 data: 0.0017 max mem: 19788 +Test: [ 4800/21770] eta: 0:13:58 time: 0.0548 data: 0.0017 max mem: 19788 +Test: [ 4900/21770] eta: 0:13:53 time: 0.0452 data: 0.0016 max mem: 19788 +Test: [ 5000/21770] eta: 0:13:48 time: 0.0506 data: 0.0018 max mem: 19788 +Test: [ 5100/21770] eta: 0:13:42 time: 0.0442 data: 0.0015 max mem: 19788 +Test: [ 5200/21770] eta: 0:13:37 time: 0.0540 data: 0.0018 max mem: 19788 +Test: [ 5300/21770] eta: 0:13:32 time: 0.0500 data: 0.0018 max mem: 19788 +Test: [ 5400/21770] eta: 0:13:27 time: 0.0521 data: 0.0018 max mem: 19788 +Test: [ 5500/21770] eta: 0:13:22 time: 0.0561 data: 0.0018 max mem: 19788 +Test: [ 5600/21770] eta: 0:13:17 time: 0.0491 data: 0.0016 max mem: 19788 +Test: [ 5700/21770] eta: 0:13:12 time: 0.0439 data: 0.0015 max mem: 19788 +Test: [ 5800/21770] eta: 0:13:07 time: 0.0456 data: 0.0016 max mem: 19788 +Test: [ 5900/21770] eta: 0:13:02 time: 0.0565 data: 0.0015 max mem: 19788 +Test: [ 6000/21770] eta: 0:12:56 time: 0.0466 data: 0.0016 max mem: 19788 +Test: [ 6100/21770] eta: 0:12:52 time: 0.0456 data: 0.0016 max mem: 19788 +Test: [ 6200/21770] eta: 0:12:47 time: 0.0432 data: 0.0015 max mem: 19788 +Test: [ 6300/21770] eta: 0:12:43 time: 0.0544 data: 0.0019 max mem: 19788 +Test: [ 6400/21770] eta: 0:12:39 time: 0.0541 data: 0.0020 max mem: 19788 +Test: [ 6500/21770] eta: 0:12:33 time: 0.0443 data: 0.0015 max mem: 19788 +Test: [ 6600/21770] eta: 0:12:28 time: 0.0516 data: 0.0017 max mem: 19788 +Test: [ 6700/21770] eta: 0:12:24 time: 0.0536 data: 0.0019 max mem: 19788 +Test: [ 6800/21770] eta: 0:12:20 time: 0.0514 data: 0.0019 max mem: 19788 +Test: [ 6900/21770] eta: 0:12:15 time: 0.0453 data: 0.0014 max mem: 19788 +Test: [ 7000/21770] eta: 0:12:10 time: 0.0545 data: 0.0019 max mem: 19788 +Test: [ 7100/21770] eta: 0:12:05 time: 0.0488 data: 0.0019 max mem: 19788 +Test: [ 7200/21770] eta: 0:12:01 time: 0.0561 data: 0.0018 max mem: 19788 +Test: [ 7300/21770] eta: 0:11:56 time: 0.0542 data: 0.0018 max mem: 19788 +Test: [ 7400/21770] eta: 0:11:51 time: 0.0472 data: 0.0017 max mem: 19788 +Test: [ 7500/21770] eta: 0:11:47 time: 0.0505 data: 0.0017 max mem: 19788 +Test: [ 7600/21770] eta: 0:11:42 time: 0.0488 data: 0.0018 max mem: 19788 +Test: [ 7700/21770] eta: 0:11:37 time: 0.0548 data: 0.0018 max mem: 19788 +Test: [ 7800/21770] eta: 0:11:32 time: 0.0514 data: 0.0016 max mem: 19788 +Test: [ 7900/21770] eta: 0:11:27 time: 0.0458 data: 0.0017 max mem: 19788 +Test: [ 8000/21770] eta: 0:11:22 time: 0.0458 data: 0.0016 max mem: 19788 +Test: [ 8100/21770] eta: 0:11:17 time: 0.0498 data: 0.0016 max mem: 19788 +Test: [ 8200/21770] eta: 0:11:12 time: 0.0478 data: 0.0017 max mem: 19788 +Test: [ 8300/21770] eta: 0:11:07 time: 0.0534 data: 0.0018 max mem: 19788 +Test: [ 8400/21770] eta: 0:11:02 time: 0.0530 data: 0.0018 max mem: 19788 +Test: [ 8500/21770] eta: 0:10:58 time: 0.0552 data: 0.0018 max mem: 19788 +Test: [ 8600/21770] eta: 0:10:53 time: 0.0519 data: 0.0017 max mem: 19788 +Test: [ 8700/21770] eta: 0:10:49 time: 0.0549 data: 0.0016 max mem: 19788 +Test: [ 8800/21770] eta: 0:10:43 time: 0.0515 data: 0.0017 max mem: 19788 +Test: [ 8900/21770] eta: 0:10:39 time: 0.0475 data: 0.0017 max mem: 19788 +Test: [ 9000/21770] eta: 0:10:34 time: 0.0557 data: 0.0019 max mem: 19788 +Test: [ 9100/21770] eta: 0:10:30 time: 0.0541 data: 0.0016 max mem: 19788 +Test: [ 9200/21770] eta: 0:10:25 time: 0.0524 data: 0.0016 max mem: 19788 +Test: [ 9300/21770] eta: 0:10:20 time: 0.0543 data: 0.0018 max mem: 19788 +Test: [ 9400/21770] eta: 0:10:15 time: 0.0559 data: 0.0020 max mem: 19788 +Test: [ 9500/21770] eta: 0:10:11 time: 0.0493 data: 0.0017 max mem: 19788 +Test: [ 9600/21770] eta: 0:10:06 time: 0.0450 data: 0.0015 max mem: 19788 +Test: [ 9700/21770] eta: 0:10:01 time: 0.0554 data: 0.0018 max mem: 19788 +Test: [ 9800/21770] eta: 0:09:56 time: 0.0532 data: 0.0018 max mem: 19788 +Test: [ 9900/21770] eta: 0:09:51 time: 0.0448 data: 0.0015 max mem: 19788 +Test: [10000/21770] eta: 0:09:46 time: 0.0526 data: 0.0017 max mem: 19788 +Test: [10100/21770] eta: 0:09:41 time: 0.0459 data: 0.0015 max mem: 19788 +Test: [10200/21770] eta: 0:09:36 time: 0.0473 data: 0.0016 max mem: 19788 +Test: [10300/21770] eta: 0:09:31 time: 0.0533 data: 0.0018 max mem: 19788 +Test: [10400/21770] eta: 0:09:26 time: 0.0474 data: 0.0016 max mem: 19788 +Test: [10500/21770] eta: 0:09:21 time: 0.0459 data: 0.0015 max mem: 19788 +Test: [10600/21770] eta: 0:09:16 time: 0.0467 data: 0.0016 max mem: 19788 +Test: [10700/21770] eta: 0:09:10 time: 0.0459 data: 0.0016 max mem: 19788 +Test: [10800/21770] eta: 0:09:05 time: 0.0456 data: 0.0015 max mem: 19788 +Test: [10900/21770] eta: 0:09:00 time: 0.0445 data: 0.0016 max mem: 19788 +Test: [11000/21770] eta: 0:08:55 time: 0.0510 data: 0.0018 max mem: 19788 +Test: [11100/21770] eta: 0:08:50 time: 0.0449 data: 0.0016 max mem: 19788 +Test: [11200/21770] eta: 0:08:45 time: 0.0438 data: 0.0016 max mem: 19788 +Test: [11300/21770] eta: 0:08:40 time: 0.0468 data: 0.0015 max mem: 19788 +Test: [11400/21770] eta: 0:08:35 time: 0.0546 data: 0.0020 max mem: 19788 +Test: [11500/21770] eta: 0:08:31 time: 0.0551 data: 0.0020 max mem: 19788 +Test: [11600/21770] eta: 0:08:26 time: 0.0456 data: 0.0017 max mem: 19788 +Test: [11700/21770] eta: 0:08:21 time: 0.0577 data: 0.0020 max mem: 19788 +Test: [11800/21770] eta: 0:08:16 time: 0.0498 data: 0.0016 max mem: 19788 +Test: [11900/21770] eta: 0:08:11 time: 0.0493 data: 0.0018 max mem: 19788 +Test: [12000/21770] eta: 0:08:06 time: 0.0547 data: 0.0019 max mem: 19788 +Test: [12100/21770] eta: 0:08:01 time: 0.0448 data: 0.0016 max mem: 19788 +Test: [12200/21770] eta: 0:07:56 time: 0.0499 data: 0.0016 max mem: 19788 +Test: [12300/21770] eta: 0:07:51 time: 0.0477 data: 0.0017 max mem: 19788 +Test: [12400/21770] eta: 0:07:46 time: 0.0541 data: 0.0019 max mem: 19788 +Test: [12500/21770] eta: 0:07:41 time: 0.0532 data: 0.0024 max mem: 19788 +Test: [12600/21770] eta: 0:07:36 time: 0.0438 data: 0.0015 max mem: 19788 +Test: [12700/21770] eta: 0:07:31 time: 0.0455 data: 0.0015 max mem: 19788 +Test: [12800/21770] eta: 0:07:26 time: 0.0514 data: 0.0018 max mem: 19788 +Test: [12900/21770] eta: 0:07:21 time: 0.0506 data: 0.0017 max mem: 19788 +Test: [13000/21770] eta: 0:07:16 time: 0.0450 data: 0.0016 max mem: 19788 +Test: [13100/21770] eta: 0:07:11 time: 0.0491 data: 0.0017 max mem: 19788 +Test: [13200/21770] eta: 0:07:06 time: 0.0451 data: 0.0016 max mem: 19788 +Test: [13300/21770] eta: 0:07:01 time: 0.0436 data: 0.0014 max mem: 19788 +Test: [13400/21770] eta: 0:06:56 time: 0.0550 data: 0.0020 max mem: 19788 +Test: [13500/21770] eta: 0:06:51 time: 0.0519 data: 0.0018 max mem: 19788 +Test: [13600/21770] eta: 0:06:47 time: 0.0547 data: 0.0019 max mem: 19788 +Test: [13700/21770] eta: 0:06:41 time: 0.0469 data: 0.0016 max mem: 19788 +Test: [13800/21770] eta: 0:06:36 time: 0.0530 data: 0.0018 max mem: 19788 +Test: [13900/21770] eta: 0:06:31 time: 0.0547 data: 0.0019 max mem: 19788 +Test: [14000/21770] eta: 0:06:27 time: 0.0467 data: 0.0016 max mem: 19788 +Test: [14100/21770] eta: 0:06:22 time: 0.0482 data: 0.0016 max mem: 19788 +Test: [14200/21770] eta: 0:06:16 time: 0.0524 data: 0.0017 max mem: 19788 +Test: [14300/21770] eta: 0:06:11 time: 0.0509 data: 0.0015 max mem: 19788 +Test: [14400/21770] eta: 0:06:06 time: 0.0471 data: 0.0016 max mem: 19788 +Test: [14500/21770] eta: 0:06:01 time: 0.0465 data: 0.0014 max mem: 19788 +Test: [14600/21770] eta: 0:05:57 time: 0.0568 data: 0.0021 max mem: 19788 +Test: [14700/21770] eta: 0:05:52 time: 0.0540 data: 0.0018 max mem: 19788 +Test: [14800/21770] eta: 0:05:47 time: 0.0441 data: 0.0015 max mem: 19788 +Test: [14900/21770] eta: 0:05:42 time: 0.0510 data: 0.0016 max mem: 19788 +Test: [15000/21770] eta: 0:05:36 time: 0.0487 data: 0.0016 max mem: 19788 +Test: [15100/21770] eta: 0:05:32 time: 0.0517 data: 0.0018 max mem: 19788 +Test: [15200/21770] eta: 0:05:27 time: 0.0537 data: 0.0018 max mem: 19788 +Test: [15300/21770] eta: 0:05:22 time: 0.0460 data: 0.0016 max mem: 19788 +Test: [15400/21770] eta: 0:05:17 time: 0.0469 data: 0.0016 max mem: 19788 +Test: [15500/21770] eta: 0:05:11 time: 0.0449 data: 0.0016 max mem: 19788 +Test: [15600/21770] eta: 0:05:06 time: 0.0557 data: 0.0019 max mem: 19788 +Test: [15700/21770] eta: 0:05:02 time: 0.0548 data: 0.0019 max mem: 19788 +Test: [15800/21770] eta: 0:04:57 time: 0.0573 data: 0.0019 max mem: 19788 +Test: [15900/21770] eta: 0:04:52 time: 0.0474 data: 0.0015 max mem: 19788 +Test: [16000/21770] eta: 0:04:47 time: 0.0489 data: 0.0018 max mem: 19788 +Test: [16100/21770] eta: 0:04:42 time: 0.0470 data: 0.0015 max mem: 19788 +Test: [16200/21770] eta: 0:04:37 time: 0.0455 data: 0.0017 max mem: 19788 +Test: [16300/21770] eta: 0:04:32 time: 0.0500 data: 0.0017 max mem: 19788 +Test: [16400/21770] eta: 0:04:27 time: 0.0473 data: 0.0017 max mem: 19788 +Test: [16500/21770] eta: 0:04:22 time: 0.0462 data: 0.0016 max mem: 19788 +Test: [16600/21770] eta: 0:04:17 time: 0.0552 data: 0.0019 max mem: 19788 +Test: [16700/21770] eta: 0:04:12 time: 0.0564 data: 0.0019 max mem: 19788 +Test: [16800/21770] eta: 0:04:07 time: 0.0475 data: 0.0019 max mem: 19788 +Test: [16900/21770] eta: 0:04:02 time: 0.0446 data: 0.0016 max mem: 19788 +Test: [17000/21770] eta: 0:03:57 time: 0.0485 data: 0.0016 max mem: 19788 +Test: [17100/21770] eta: 0:03:52 time: 0.0499 data: 0.0017 max mem: 19788 +Test: [17200/21770] eta: 0:03:47 time: 0.0563 data: 0.0019 max mem: 19788 +Test: [17300/21770] eta: 0:03:42 time: 0.0546 data: 0.0018 max mem: 19788 +Test: [17400/21770] eta: 0:03:37 time: 0.0540 data: 0.0016 max mem: 19788 +Test: [17500/21770] eta: 0:03:32 time: 0.0469 data: 0.0016 max mem: 19788 +Test: [17600/21770] eta: 0:03:27 time: 0.0443 data: 0.0016 max mem: 19788 +Test: [17700/21770] eta: 0:03:22 time: 0.0447 data: 0.0017 max mem: 19788 +Test: [17800/21770] eta: 0:03:17 time: 0.0530 data: 0.0017 max mem: 19788 +Test: [17900/21770] eta: 0:03:12 time: 0.0435 data: 0.0016 max mem: 19788 +Test: [18000/21770] eta: 0:03:07 time: 0.0444 data: 0.0016 max mem: 19788 +Test: [18100/21770] eta: 0:03:02 time: 0.0525 data: 0.0018 max mem: 19788 +Test: [18200/21770] eta: 0:02:57 time: 0.0535 data: 0.0019 max mem: 19788 +Test: [18300/21770] eta: 0:02:52 time: 0.0521 data: 0.0018 max mem: 19788 +Test: [18400/21770] eta: 0:02:47 time: 0.0523 data: 0.0017 max mem: 19788 +Test: [18500/21770] eta: 0:02:42 time: 0.0459 data: 0.0015 max mem: 19788 +Test: [18600/21770] eta: 0:02:37 time: 0.0561 data: 0.0018 max mem: 19788 +Test: [18700/21770] eta: 0:02:32 time: 0.0507 data: 0.0017 max mem: 19788 +Test: [18800/21770] eta: 0:02:27 time: 0.0480 data: 0.0015 max mem: 19788 +Test: [18900/21770] eta: 0:02:22 time: 0.0452 data: 0.0014 max mem: 19788 +Test: [19000/21770] eta: 0:02:17 time: 0.0526 data: 0.0019 max mem: 19788 +Test: [19100/21770] eta: 0:02:12 time: 0.0448 data: 0.0016 max mem: 19788 +Test: [19200/21770] eta: 0:02:07 time: 0.0551 data: 0.0020 max mem: 19788 +Test: [19300/21770] eta: 0:02:02 time: 0.0529 data: 0.0017 max mem: 19788 +Test: [19400/21770] eta: 0:01:57 time: 0.0539 data: 0.0018 max mem: 19788 +Test: [19500/21770] eta: 0:01:52 time: 0.0458 data: 0.0014 max mem: 19788 +Test: [19600/21770] eta: 0:01:47 time: 0.0523 data: 0.0020 max mem: 19788 +Test: [19700/21770] eta: 0:01:42 time: 0.0550 data: 0.0019 max mem: 19788 +Test: [19800/21770] eta: 0:01:37 time: 0.0528 data: 0.0017 max mem: 19788 +Test: [19900/21770] eta: 0:01:32 time: 0.0465 data: 0.0030 max mem: 19788 +Test: [20000/21770] eta: 0:01:27 time: 0.0566 data: 0.0020 max mem: 19788 +Test: [20100/21770] eta: 0:01:22 time: 0.0552 data: 0.0020 max mem: 19788 +Test: [20200/21770] eta: 0:01:17 time: 0.0459 data: 0.0016 max mem: 19788 +Test: [20300/21770] eta: 0:01:13 time: 0.0563 data: 0.0019 max mem: 19788 +Test: [20400/21770] eta: 0:01:08 time: 0.0564 data: 0.0019 max mem: 19788 +Test: [20500/21770] eta: 0:01:03 time: 0.0460 data: 0.0015 max mem: 19788 +Test: [20600/21770] eta: 0:00:58 time: 0.0459 data: 0.0014 max mem: 19788 +Test: [20700/21770] eta: 0:00:53 time: 0.0466 data: 0.0018 max mem: 19788 +Test: [20800/21770] eta: 0:00:48 time: 0.0543 data: 0.0019 max mem: 19788 +Test: [20900/21770] eta: 0:00:43 time: 0.0465 data: 0.0016 max mem: 19788 +Test: [21000/21770] eta: 0:00:38 time: 0.0542 data: 0.0019 max mem: 19788 +Test: [21100/21770] eta: 0:00:33 time: 0.0537 data: 0.0018 max mem: 19788 +Test: [21200/21770] eta: 0:00:28 time: 0.0442 data: 0.0014 max mem: 19788 +Test: [21300/21770] eta: 0:00:23 time: 0.0544 data: 0.0018 max mem: 19788 +Test: [21400/21770] eta: 0:00:18 time: 0.0457 data: 0.0017 max mem: 19788 +Test: [21500/21770] eta: 0:00:13 time: 0.0530 data: 0.0020 max mem: 19788 +Test: [21600/21770] eta: 0:00:08 time: 0.0554 data: 0.0019 max mem: 19788 +Test: [21700/21770] eta: 0:00:03 time: 0.0555 data: 0.0016 max mem: 19788 +Test: Total time: 0:18:03 +Final results: +Mean IoU is 64.47 + + precision@0.5 = 71.71 + precision@0.6 = 66.53 + precision@0.7 = 60.24 + precision@0.8 = 49.61 + precision@0.9 = 24.65 + overall IoU = 65.05 + mean IoU = 64.47 + +Mean accuracy for one-to-zero sample is 86.72 + +Average object IoU 0.6446707675433456 +Overall IoU 65.04698944091797 +Better epoch: 29 + +Epoch: [30] [ 0/2138] eta: 4:34:57 lr: 1.4358124999356481e-05 loss: 0.0247 (0.0247) time: 7.7163 data: 1.9401 max mem: 19788 +Epoch: [30] [ 10/2138] eta: 2:08:11 lr: 1.4352080462768693e-05 loss: 0.0209 (0.0230) time: 3.6145 data: 0.1790 max mem: 19788 +Epoch: [30] [ 20/2138] eta: 1:58:19 lr: 1.4346035643309543e-05 loss: 0.0206 (0.0211) time: 3.1339 data: 0.0022 max mem: 19788 +Epoch: [30] [ 30/2138] eta: 1:55:07 lr: 1.4339990540833336e-05 loss: 0.0212 (0.0216) time: 3.0910 data: 0.0021 max mem: 19788 +Epoch: [30] [ 40/2138] eta: 1:53:14 lr: 1.4333945155194256e-05 loss: 0.0212 (0.0216) time: 3.1197 data: 0.0025 max mem: 19788 +Epoch: [30] [ 50/2138] eta: 1:51:57 lr: 1.4327899486246322e-05 loss: 0.0205 (0.0216) time: 3.1244 data: 0.0027 max mem: 19788 +Epoch: [30] [ 60/2138] eta: 1:51:04 lr: 1.4321853533843429e-05 loss: 0.0225 (0.0219) time: 3.1427 data: 0.0030 max mem: 19788 +Epoch: [30] [ 70/2138] eta: 1:49:48 lr: 1.4315807297839312e-05 loss: 0.0217 (0.0219) time: 3.1063 data: 0.0028 max mem: 19788 +Epoch: [30] [ 80/2138] eta: 1:49:00 lr: 1.4309760778087574e-05 loss: 0.0210 (0.0221) time: 3.0886 data: 0.0029 max mem: 19788 +Epoch: [30] [ 90/2138] eta: 1:48:09 lr: 1.4303713974441663e-05 loss: 0.0196 (0.0217) time: 3.1076 data: 0.0028 max mem: 19788 +Epoch: [30] [ 100/2138] eta: 1:48:08 lr: 1.4297666886754893e-05 loss: 0.0196 (0.0218) time: 3.2070 data: 0.0024 max mem: 19788 +Epoch: [30] [ 110/2138] eta: 1:47:59 lr: 1.4291619514880423e-05 loss: 0.0196 (0.0216) time: 3.3149 data: 0.0026 max mem: 19788 +Epoch: [30] [ 120/2138] eta: 1:47:37 lr: 1.4285571858671278e-05 loss: 0.0165 (0.0213) time: 3.2831 data: 0.0026 max mem: 19788 +Epoch: [30] [ 130/2138] eta: 1:47:11 lr: 1.4279523917980326e-05 loss: 0.0203 (0.0213) time: 3.2488 data: 0.0028 max mem: 19788 +Epoch: [30] [ 140/2138] eta: 1:46:36 lr: 1.4273475692660298e-05 loss: 0.0208 (0.0214) time: 3.2108 data: 0.0030 max mem: 19788 +Epoch: [30] [ 150/2138] eta: 1:45:53 lr: 1.4267427182563775e-05 loss: 0.0199 (0.0213) time: 3.1491 data: 0.0027 max mem: 19788 +Epoch: [30] [ 160/2138] eta: 1:44:59 lr: 1.4261378387543201e-05 loss: 0.0199 (0.0212) time: 3.0662 data: 0.0023 max mem: 19788 +Epoch: [30] [ 170/2138] eta: 1:44:09 lr: 1.4255329307450857e-05 loss: 0.0213 (0.0213) time: 3.0228 data: 0.0023 max mem: 19788 +Epoch: [30] [ 180/2138] eta: 1:43:40 lr: 1.4249279942138896e-05 loss: 0.0207 (0.0212) time: 3.1157 data: 0.0024 max mem: 19788 +Epoch: [30] [ 190/2138] eta: 1:42:58 lr: 1.4243230291459305e-05 loss: 0.0187 (0.0211) time: 3.1394 data: 0.0025 max mem: 19788 +Epoch: [30] [ 200/2138] eta: 1:42:15 lr: 1.4237180355263955e-05 loss: 0.0190 (0.0211) time: 3.0642 data: 0.0024 max mem: 19788 +Epoch: [30] [ 210/2138] eta: 1:41:50 lr: 1.4231130133404527e-05 loss: 0.0207 (0.0211) time: 3.1459 data: 0.0024 max mem: 19788 +Epoch: [30] [ 220/2138] eta: 1:41:22 lr: 1.42250796257326e-05 loss: 0.0198 (0.0210) time: 3.2226 data: 0.0027 max mem: 19788 +Epoch: [30] [ 230/2138] eta: 1:41:00 lr: 1.421902883209957e-05 loss: 0.0205 (0.0211) time: 3.2471 data: 0.0028 max mem: 19788 +Epoch: [30] [ 240/2138] eta: 1:40:20 lr: 1.4212977752356698e-05 loss: 0.0210 (0.0211) time: 3.1838 data: 0.0026 max mem: 19788 +Epoch: [30] [ 250/2138] eta: 1:39:38 lr: 1.4206926386355113e-05 loss: 0.0207 (0.0211) time: 3.0585 data: 0.0027 max mem: 19788 +Epoch: [30] [ 260/2138] eta: 1:39:00 lr: 1.4200874733945769e-05 loss: 0.0205 (0.0211) time: 3.0535 data: 0.0027 max mem: 19788 +Epoch: [30] [ 270/2138] eta: 1:38:21 lr: 1.4194822794979493e-05 loss: 0.0214 (0.0212) time: 3.0618 data: 0.0027 max mem: 19788 +Epoch: [30] [ 280/2138] eta: 1:37:45 lr: 1.4188770569306948e-05 loss: 0.0217 (0.0211) time: 3.0797 data: 0.0026 max mem: 19788 +Epoch: [30] [ 290/2138] eta: 1:37:06 lr: 1.4182718056778663e-05 loss: 0.0217 (0.0212) time: 3.0690 data: 0.0024 max mem: 19788 +Epoch: [30] [ 300/2138] eta: 1:36:33 lr: 1.4176665257245e-05 loss: 0.0207 (0.0212) time: 3.0789 data: 0.0024 max mem: 19788 +Epoch: [30] [ 310/2138] eta: 1:36:11 lr: 1.41706121705562e-05 loss: 0.0204 (0.0211) time: 3.2213 data: 0.0026 max mem: 19788 +Epoch: [30] [ 320/2138] eta: 1:35:37 lr: 1.4164558796562316e-05 loss: 0.0167 (0.0210) time: 3.2165 data: 0.0024 max mem: 19788 +Epoch: [30] [ 330/2138] eta: 1:34:58 lr: 1.4158505135113292e-05 loss: 0.0194 (0.0211) time: 3.0693 data: 0.0025 max mem: 19788 +Epoch: [30] [ 340/2138] eta: 1:34:23 lr: 1.4152451186058893e-05 loss: 0.0214 (0.0210) time: 3.0505 data: 0.0026 max mem: 19788 +Epoch: [30] [ 350/2138] eta: 1:33:45 lr: 1.414639694924875e-05 loss: 0.0186 (0.0210) time: 3.0548 data: 0.0026 max mem: 19788 +Epoch: [30] [ 360/2138] eta: 1:33:10 lr: 1.4140342424532326e-05 loss: 0.0204 (0.0210) time: 3.0495 data: 0.0027 max mem: 19788 +Epoch: [30] [ 370/2138] eta: 1:32:37 lr: 1.4134287611758964e-05 loss: 0.0219 (0.0210) time: 3.0872 data: 0.0028 max mem: 19788 +Epoch: [30] [ 380/2138] eta: 1:32:05 lr: 1.412823251077782e-05 loss: 0.0186 (0.0210) time: 3.1187 data: 0.0027 max mem: 19788 +Epoch: [30] [ 390/2138] eta: 1:31:34 lr: 1.4122177121437932e-05 loss: 0.0181 (0.0209) time: 3.1477 data: 0.0024 max mem: 19788 +Epoch: [30] [ 400/2138] eta: 1:30:59 lr: 1.4116121443588162e-05 loss: 0.0202 (0.0210) time: 3.1132 data: 0.0022 max mem: 19788 +Epoch: [30] [ 410/2138] eta: 1:30:27 lr: 1.4110065477077238e-05 loss: 0.0200 (0.0209) time: 3.0957 data: 0.0025 max mem: 19788 +Epoch: [30] [ 420/2138] eta: 1:29:55 lr: 1.4104009221753722e-05 loss: 0.0181 (0.0209) time: 3.1241 data: 0.0025 max mem: 19788 +Epoch: [30] [ 430/2138] eta: 1:29:19 lr: 1.409795267746604e-05 loss: 0.0196 (0.0209) time: 3.0706 data: 0.0023 max mem: 19788 +Epoch: [30] [ 440/2138] eta: 1:28:45 lr: 1.4091895844062448e-05 loss: 0.0210 (0.0209) time: 3.0454 data: 0.0026 max mem: 19788 +Epoch: [30] [ 450/2138] eta: 1:28:13 lr: 1.408583872139107e-05 loss: 0.0198 (0.0209) time: 3.0970 data: 0.0029 max mem: 19788 +Epoch: [30] [ 460/2138] eta: 1:27:43 lr: 1.4079781309299857e-05 loss: 0.0197 (0.0209) time: 3.1454 data: 0.0029 max mem: 19788 +Epoch: [30] [ 470/2138] eta: 1:27:20 lr: 1.407372360763663e-05 loss: 0.0197 (0.0209) time: 3.2645 data: 0.0027 max mem: 19788 +Epoch: [30] [ 480/2138] eta: 1:26:57 lr: 1.406766561624903e-05 loss: 0.0215 (0.0209) time: 3.3840 data: 0.0026 max mem: 19788 +Epoch: [30] [ 490/2138] eta: 1:26:28 lr: 1.406160733498457e-05 loss: 0.0215 (0.0208) time: 3.3101 data: 0.0024 max mem: 19788 +Epoch: [30] [ 500/2138] eta: 1:25:56 lr: 1.4055548763690593e-05 loss: 0.0174 (0.0208) time: 3.1736 data: 0.0025 max mem: 19788 +Epoch: [30] [ 510/2138] eta: 1:25:29 lr: 1.4049489902214303e-05 loss: 0.0169 (0.0208) time: 3.2047 data: 0.0025 max mem: 19788 +Epoch: [30] [ 520/2138] eta: 1:24:54 lr: 1.4043430750402733e-05 loss: 0.0169 (0.0208) time: 3.1733 data: 0.0023 max mem: 19788 +Epoch: [30] [ 530/2138] eta: 1:24:21 lr: 1.4037371308102772e-05 loss: 0.0191 (0.0208) time: 3.0718 data: 0.0023 max mem: 19788 +Epoch: [30] [ 540/2138] eta: 1:23:56 lr: 1.4031311575161162e-05 loss: 0.0180 (0.0208) time: 3.2207 data: 0.0024 max mem: 19788 +Epoch: [30] [ 550/2138] eta: 1:23:26 lr: 1.402525155142447e-05 loss: 0.0186 (0.0207) time: 3.2905 data: 0.0026 max mem: 19788 +Epoch: [30] [ 560/2138] eta: 1:22:52 lr: 1.4019191236739132e-05 loss: 0.0208 (0.0208) time: 3.1402 data: 0.0029 max mem: 19788 +Epoch: [30] [ 570/2138] eta: 1:22:17 lr: 1.4013130630951407e-05 loss: 0.0206 (0.0208) time: 3.0474 data: 0.0029 max mem: 19788 +Epoch: [30] [ 580/2138] eta: 1:21:42 lr: 1.4007069733907422e-05 loss: 0.0192 (0.0208) time: 3.0222 data: 0.0027 max mem: 19788 +Epoch: [30] [ 590/2138] eta: 1:21:07 lr: 1.4001008545453123e-05 loss: 0.0192 (0.0208) time: 3.0141 data: 0.0025 max mem: 19788 +Epoch: [30] [ 600/2138] eta: 1:20:37 lr: 1.3994947065434324e-05 loss: 0.0189 (0.0208) time: 3.0982 data: 0.0024 max mem: 19788 +Epoch: [30] [ 610/2138] eta: 1:20:04 lr: 1.3988885293696663e-05 loss: 0.0196 (0.0208) time: 3.1428 data: 0.0028 max mem: 19788 +Epoch: [30] [ 620/2138] eta: 1:19:32 lr: 1.3982823230085643e-05 loss: 0.0203 (0.0209) time: 3.0981 data: 0.0031 max mem: 19788 +Epoch: [30] [ 630/2138] eta: 1:19:05 lr: 1.3976760874446588e-05 loss: 0.0207 (0.0209) time: 3.2174 data: 0.0031 max mem: 19788 +Epoch: [30] [ 640/2138] eta: 1:18:32 lr: 1.3970698226624688e-05 loss: 0.0198 (0.0209) time: 3.2208 data: 0.0029 max mem: 19788 +Epoch: [30] [ 650/2138] eta: 1:17:58 lr: 1.3964635286464953e-05 loss: 0.0199 (0.0209) time: 3.0555 data: 0.0027 max mem: 19788 +Epoch: [30] [ 660/2138] eta: 1:17:24 lr: 1.3958572053812258e-05 loss: 0.0206 (0.0209) time: 3.0194 data: 0.0028 max mem: 19788 +Epoch: [30] [ 670/2138] eta: 1:16:50 lr: 1.3952508528511302e-05 loss: 0.0206 (0.0209) time: 3.0283 data: 0.0031 max mem: 19788 +Epoch: [30] [ 680/2138] eta: 1:16:16 lr: 1.3946444710406648e-05 loss: 0.0189 (0.0209) time: 3.0341 data: 0.0030 max mem: 19788 +Epoch: [30] [ 690/2138] eta: 1:15:42 lr: 1.394038059934267e-05 loss: 0.0192 (0.0209) time: 3.0292 data: 0.0028 max mem: 19788 +Epoch: [30] [ 700/2138] eta: 1:15:08 lr: 1.3934316195163621e-05 loss: 0.0213 (0.0209) time: 3.0173 data: 0.0027 max mem: 19788 +Epoch: [30] [ 710/2138] eta: 1:14:40 lr: 1.3928251497713566e-05 loss: 0.0216 (0.0209) time: 3.1495 data: 0.0026 max mem: 19788 +Epoch: [30] [ 720/2138] eta: 1:14:10 lr: 1.392218650683643e-05 loss: 0.0182 (0.0209) time: 3.2574 data: 0.0025 max mem: 19788 +Epoch: [30] [ 730/2138] eta: 1:13:37 lr: 1.3916121222375964e-05 loss: 0.0173 (0.0209) time: 3.1407 data: 0.0026 max mem: 19788 +Epoch: [30] [ 740/2138] eta: 1:13:05 lr: 1.3910055644175776e-05 loss: 0.0214 (0.0209) time: 3.0588 data: 0.0028 max mem: 19788 +Epoch: [30] [ 750/2138] eta: 1:12:34 lr: 1.3903989772079301e-05 loss: 0.0204 (0.0209) time: 3.1165 data: 0.0027 max mem: 19788 +Epoch: [30] [ 760/2138] eta: 1:12:00 lr: 1.389792360592983e-05 loss: 0.0204 (0.0209) time: 3.0935 data: 0.0024 max mem: 19788 +Epoch: [30] [ 770/2138] eta: 1:11:32 lr: 1.3891857145570475e-05 loss: 0.0192 (0.0209) time: 3.1565 data: 0.0027 max mem: 19788 +Epoch: [30] [ 780/2138] eta: 1:11:02 lr: 1.3885790390844205e-05 loss: 0.0183 (0.0209) time: 3.2649 data: 0.0030 max mem: 19788 +Epoch: [30] [ 790/2138] eta: 1:10:30 lr: 1.387972334159382e-05 loss: 0.0197 (0.0209) time: 3.1634 data: 0.0031 max mem: 19788 +Epoch: [30] [ 800/2138] eta: 1:10:02 lr: 1.3873655997661964e-05 loss: 0.0197 (0.0209) time: 3.2251 data: 0.0027 max mem: 19788 +Epoch: [30] [ 810/2138] eta: 1:09:31 lr: 1.3867588358891112e-05 loss: 0.0205 (0.0209) time: 3.2486 data: 0.0024 max mem: 19788 +Epoch: [30] [ 820/2138] eta: 1:08:59 lr: 1.3861520425123594e-05 loss: 0.0204 (0.0209) time: 3.1132 data: 0.0027 max mem: 19788 +Epoch: [30] [ 830/2138] eta: 1:08:26 lr: 1.3855452196201569e-05 loss: 0.0187 (0.0209) time: 3.0784 data: 0.0028 max mem: 19788 +Epoch: [30] [ 840/2138] eta: 1:07:59 lr: 1.3849383671967022e-05 loss: 0.0183 (0.0209) time: 3.2375 data: 0.0026 max mem: 19788 +Epoch: [30] [ 850/2138] eta: 1:07:28 lr: 1.3843314852261804e-05 loss: 0.0195 (0.0209) time: 3.3132 data: 0.0024 max mem: 19788 +Epoch: [30] [ 860/2138] eta: 1:06:56 lr: 1.3837245736927582e-05 loss: 0.0198 (0.0209) time: 3.1358 data: 0.0024 max mem: 19788 +Epoch: [30] [ 870/2138] eta: 1:06:23 lr: 1.3831176325805872e-05 loss: 0.0191 (0.0209) time: 3.0377 data: 0.0025 max mem: 19788 +Epoch: [30] [ 880/2138] eta: 1:05:52 lr: 1.3825106618738024e-05 loss: 0.0184 (0.0209) time: 3.1305 data: 0.0027 max mem: 19788 +Epoch: [30] [ 890/2138] eta: 1:05:24 lr: 1.3819036615565226e-05 loss: 0.0205 (0.0209) time: 3.2990 data: 0.0026 max mem: 19788 +Epoch: [30] [ 900/2138] eta: 1:04:53 lr: 1.38129663161285e-05 loss: 0.0198 (0.0209) time: 3.2471 data: 0.0024 max mem: 19788 +Epoch: [30] [ 910/2138] eta: 1:04:21 lr: 1.3806895720268717e-05 loss: 0.0188 (0.0209) time: 3.1516 data: 0.0022 max mem: 19788 +Epoch: [30] [ 920/2138] eta: 1:03:51 lr: 1.3800824827826567e-05 loss: 0.0191 (0.0209) time: 3.1789 data: 0.0024 max mem: 19788 +Epoch: [30] [ 930/2138] eta: 1:03:19 lr: 1.379475363864259e-05 loss: 0.0209 (0.0209) time: 3.1744 data: 0.0026 max mem: 19788 +Epoch: [30] [ 940/2138] eta: 1:02:47 lr: 1.3788682152557152e-05 loss: 0.0224 (0.0209) time: 3.1396 data: 0.0025 max mem: 19788 +Epoch: [30] [ 950/2138] eta: 1:02:14 lr: 1.3782610369410474e-05 loss: 0.0211 (0.0209) time: 3.0622 data: 0.0024 max mem: 19788 +Epoch: [30] [ 960/2138] eta: 1:01:43 lr: 1.3776538289042582e-05 loss: 0.0219 (0.0209) time: 3.0823 data: 0.0023 max mem: 19788 +Epoch: [30] [ 970/2138] eta: 1:01:12 lr: 1.3770465911293368e-05 loss: 0.0220 (0.0209) time: 3.1829 data: 0.0024 max mem: 19788 +Epoch: [30] [ 980/2138] eta: 1:00:39 lr: 1.3764393236002538e-05 loss: 0.0191 (0.0209) time: 3.1040 data: 0.0026 max mem: 19788 +Epoch: [30] [ 990/2138] eta: 1:00:07 lr: 1.3758320263009647e-05 loss: 0.0191 (0.0209) time: 3.0332 data: 0.0026 max mem: 19788 +Epoch: [30] [1000/2138] eta: 0:59:34 lr: 1.3752246992154071e-05 loss: 0.0189 (0.0209) time: 3.0381 data: 0.0026 max mem: 19788 +Epoch: [30] [1010/2138] eta: 0:59:01 lr: 1.374617342327504e-05 loss: 0.0187 (0.0209) time: 3.0099 data: 0.0026 max mem: 19788 +Epoch: [30] [1020/2138] eta: 0:58:28 lr: 1.3740099556211598e-05 loss: 0.0173 (0.0209) time: 3.0094 data: 0.0024 max mem: 19788 +Epoch: [30] [1030/2138] eta: 0:57:56 lr: 1.3734025390802636e-05 loss: 0.0170 (0.0209) time: 3.0187 data: 0.0024 max mem: 19788 +Epoch: [30] [1040/2138] eta: 0:57:26 lr: 1.3727950926886864e-05 loss: 0.0198 (0.0209) time: 3.1715 data: 0.0023 max mem: 19788 +Epoch: [30] [1050/2138] eta: 0:56:55 lr: 1.3721876164302853e-05 loss: 0.0211 (0.0209) time: 3.2511 data: 0.0025 max mem: 19788 +Epoch: [30] [1060/2138] eta: 0:56:25 lr: 1.371580110288897e-05 loss: 0.0211 (0.0209) time: 3.2256 data: 0.0029 max mem: 19788 +Epoch: [30] [1070/2138] eta: 0:55:52 lr: 1.3709725742483456e-05 loss: 0.0197 (0.0209) time: 3.1309 data: 0.0027 max mem: 19788 +Epoch: [30] [1080/2138] eta: 0:55:20 lr: 1.3703650082924343e-05 loss: 0.0203 (0.0209) time: 2.9972 data: 0.0024 max mem: 19788 +Epoch: [30] [1090/2138] eta: 0:54:47 lr: 1.3697574124049537e-05 loss: 0.0205 (0.0209) time: 3.0008 data: 0.0026 max mem: 19788 +Epoch: [30] [1100/2138] eta: 0:54:14 lr: 1.3691497865696735e-05 loss: 0.0212 (0.0209) time: 3.0097 data: 0.0029 max mem: 19788 +Epoch: [30] [1110/2138] eta: 0:53:42 lr: 1.3685421307703502e-05 loss: 0.0201 (0.0209) time: 3.0440 data: 0.0030 max mem: 19788 +Epoch: [30] [1120/2138] eta: 0:53:11 lr: 1.3679344449907205e-05 loss: 0.0188 (0.0209) time: 3.1181 data: 0.0028 max mem: 19788 +Epoch: [30] [1130/2138] eta: 0:52:40 lr: 1.3673267292145073e-05 loss: 0.0199 (0.0209) time: 3.1550 data: 0.0025 max mem: 19788 +Epoch: [30] [1140/2138] eta: 0:52:10 lr: 1.3667189834254137e-05 loss: 0.0199 (0.0209) time: 3.1922 data: 0.0026 max mem: 19788 +Epoch: [30] [1150/2138] eta: 0:51:37 lr: 1.3661112076071272e-05 loss: 0.0173 (0.0209) time: 3.0909 data: 0.0026 max mem: 19788 +Epoch: [30] [1160/2138] eta: 0:51:04 lr: 1.365503401743319e-05 loss: 0.0178 (0.0209) time: 2.9468 data: 0.0025 max mem: 19788 +Epoch: [30] [1170/2138] eta: 0:50:31 lr: 1.3648955658176417e-05 loss: 0.0205 (0.0209) time: 2.9467 data: 0.0025 max mem: 19788 +Epoch: [30] [1180/2138] eta: 0:49:58 lr: 1.364287699813733e-05 loss: 0.0205 (0.0209) time: 2.9519 data: 0.0027 max mem: 19788 +Epoch: [30] [1190/2138] eta: 0:49:25 lr: 1.3636798037152113e-05 loss: 0.0196 (0.0209) time: 2.9562 data: 0.0026 max mem: 19788 +Epoch: [30] [1200/2138] eta: 0:48:53 lr: 1.36307187750568e-05 loss: 0.0192 (0.0209) time: 2.9559 data: 0.0024 max mem: 19788 +Epoch: [30] [1210/2138] eta: 0:48:21 lr: 1.3624639211687237e-05 loss: 0.0210 (0.0209) time: 3.0155 data: 0.0025 max mem: 19788 +Epoch: [30] [1220/2138] eta: 0:47:49 lr: 1.361855934687912e-05 loss: 0.0196 (0.0209) time: 3.0396 data: 0.0027 max mem: 19788 +Epoch: [30] [1230/2138] eta: 0:47:17 lr: 1.3612479180467947e-05 loss: 0.0187 (0.0209) time: 3.0134 data: 0.0026 max mem: 19788 +Epoch: [30] [1240/2138] eta: 0:46:45 lr: 1.360639871228907e-05 loss: 0.0185 (0.0209) time: 3.0053 data: 0.0025 max mem: 19788 +Epoch: [30] [1250/2138] eta: 0:46:12 lr: 1.3600317942177648e-05 loss: 0.0185 (0.0209) time: 2.9712 data: 0.0026 max mem: 19788 +Epoch: [30] [1260/2138] eta: 0:45:40 lr: 1.359423686996869e-05 loss: 0.0195 (0.0209) time: 2.9790 data: 0.0026 max mem: 19788 +Epoch: [30] [1270/2138] eta: 0:45:08 lr: 1.3588155495497013e-05 loss: 0.0186 (0.0209) time: 2.9812 data: 0.0026 max mem: 19788 +Epoch: [30] [1280/2138] eta: 0:44:36 lr: 1.3582073818597275e-05 loss: 0.0186 (0.0209) time: 3.0031 data: 0.0026 max mem: 19788 +Epoch: [30] [1290/2138] eta: 0:44:04 lr: 1.3575991839103943e-05 loss: 0.0188 (0.0209) time: 3.0401 data: 0.0027 max mem: 19788 +Epoch: [30] [1300/2138] eta: 0:43:33 lr: 1.3569909556851343e-05 loss: 0.0199 (0.0209) time: 3.0370 data: 0.0028 max mem: 19788 +Epoch: [30] [1310/2138] eta: 0:43:01 lr: 1.3563826971673591e-05 loss: 0.0197 (0.0209) time: 3.0686 data: 0.0032 max mem: 19788 +Epoch: [30] [1320/2138] eta: 0:42:30 lr: 1.355774408340466e-05 loss: 0.0192 (0.0208) time: 3.0983 data: 0.0030 max mem: 19788 +Epoch: [30] [1330/2138] eta: 0:41:59 lr: 1.3551660891878326e-05 loss: 0.0194 (0.0209) time: 3.1312 data: 0.0026 max mem: 19788 +Epoch: [30] [1340/2138] eta: 0:41:27 lr: 1.3545577396928211e-05 loss: 0.0215 (0.0209) time: 3.0684 data: 0.0025 max mem: 19788 +Epoch: [30] [1350/2138] eta: 0:40:55 lr: 1.3539493598387739e-05 loss: 0.0242 (0.0209) time: 2.9664 data: 0.0023 max mem: 19788 +Epoch: [30] [1360/2138] eta: 0:40:23 lr: 1.3533409496090188e-05 loss: 0.0212 (0.0209) time: 2.9729 data: 0.0026 max mem: 19788 +Epoch: [30] [1370/2138] eta: 0:39:52 lr: 1.352732508986863e-05 loss: 0.0192 (0.0209) time: 3.0760 data: 0.0027 max mem: 19788 +Epoch: [30] [1380/2138] eta: 0:39:20 lr: 1.3521240379555994e-05 loss: 0.0193 (0.0209) time: 3.0720 data: 0.0023 max mem: 19788 +Epoch: [30] [1390/2138] eta: 0:38:50 lr: 1.3515155364985005e-05 loss: 0.0204 (0.0209) time: 3.0779 data: 0.0025 max mem: 19788 +Epoch: [30] [1400/2138] eta: 0:38:19 lr: 1.3509070045988235e-05 loss: 0.0199 (0.0209) time: 3.1599 data: 0.0025 max mem: 19788 +Epoch: [30] [1410/2138] eta: 0:37:47 lr: 1.3502984422398057e-05 loss: 0.0203 (0.0209) time: 3.1254 data: 0.0022 max mem: 19788 +Epoch: [30] [1420/2138] eta: 0:37:16 lr: 1.3496898494046695e-05 loss: 0.0203 (0.0209) time: 3.0601 data: 0.0024 max mem: 19788 +Epoch: [30] [1430/2138] eta: 0:36:45 lr: 1.3490812260766166e-05 loss: 0.0210 (0.0209) time: 3.1082 data: 0.0025 max mem: 19788 +Epoch: [30] [1440/2138] eta: 0:36:13 lr: 1.3484725722388342e-05 loss: 0.0213 (0.0209) time: 3.0875 data: 0.0026 max mem: 19788 +Epoch: [30] [1450/2138] eta: 0:35:42 lr: 1.3478638878744892e-05 loss: 0.0227 (0.0209) time: 3.0221 data: 0.0030 max mem: 19788 +Epoch: [30] [1460/2138] eta: 0:35:10 lr: 1.3472551729667315e-05 loss: 0.0206 (0.0209) time: 3.0365 data: 0.0026 max mem: 19788 +Epoch: [30] [1470/2138] eta: 0:34:39 lr: 1.3466464274986945e-05 loss: 0.0184 (0.0209) time: 3.0422 data: 0.0021 max mem: 19788 +Epoch: [30] [1480/2138] eta: 0:34:08 lr: 1.3460376514534914e-05 loss: 0.0179 (0.0209) time: 3.1196 data: 0.0024 max mem: 19788 +Epoch: [30] [1490/2138] eta: 0:33:37 lr: 1.3454288448142208e-05 loss: 0.0187 (0.0209) time: 3.1448 data: 0.0028 max mem: 19788 +Epoch: [30] [1500/2138] eta: 0:33:05 lr: 1.3448200075639598e-05 loss: 0.0214 (0.0210) time: 3.0730 data: 0.0026 max mem: 19788 +Epoch: [30] [1510/2138] eta: 0:32:34 lr: 1.3442111396857709e-05 loss: 0.0214 (0.0210) time: 3.0190 data: 0.0025 max mem: 19788 +Epoch: [30] [1520/2138] eta: 0:32:02 lr: 1.3436022411626962e-05 loss: 0.0194 (0.0210) time: 3.0169 data: 0.0025 max mem: 19788 +Epoch: [30] [1530/2138] eta: 0:31:31 lr: 1.3429933119777616e-05 loss: 0.0200 (0.0210) time: 2.9852 data: 0.0024 max mem: 19788 +Epoch: [30] [1540/2138] eta: 0:30:59 lr: 1.3423843521139737e-05 loss: 0.0203 (0.0210) time: 2.9625 data: 0.0026 max mem: 19788 +Epoch: [30] [1550/2138] eta: 0:30:27 lr: 1.3417753615543227e-05 loss: 0.0190 (0.0210) time: 2.9641 data: 0.0030 max mem: 19788 +Epoch: [30] [1560/2138] eta: 0:29:56 lr: 1.341166340281779e-05 loss: 0.0215 (0.0210) time: 2.9917 data: 0.0027 max mem: 19788 +Epoch: [30] [1570/2138] eta: 0:29:25 lr: 1.3405572882792963e-05 loss: 0.0222 (0.0210) time: 3.0644 data: 0.0027 max mem: 19788 +Epoch: [30] [1580/2138] eta: 0:28:54 lr: 1.3399482055298094e-05 loss: 0.0208 (0.0210) time: 3.0973 data: 0.0026 max mem: 19788 +Epoch: [30] [1590/2138] eta: 0:28:22 lr: 1.3393390920162357e-05 loss: 0.0208 (0.0210) time: 3.0901 data: 0.0024 max mem: 19788 +Epoch: [30] [1600/2138] eta: 0:27:51 lr: 1.3387299477214734e-05 loss: 0.0225 (0.0210) time: 3.0789 data: 0.0025 max mem: 19788 +Epoch: [30] [1610/2138] eta: 0:27:20 lr: 1.3381207726284046e-05 loss: 0.0233 (0.0210) time: 3.0353 data: 0.0025 max mem: 19788 +Epoch: [30] [1620/2138] eta: 0:26:48 lr: 1.33751156671989e-05 loss: 0.0177 (0.0210) time: 2.9887 data: 0.0023 max mem: 19788 +Epoch: [30] [1630/2138] eta: 0:26:17 lr: 1.3369023299787759e-05 loss: 0.0175 (0.0210) time: 2.9696 data: 0.0028 max mem: 19788 +Epoch: [30] [1640/2138] eta: 0:25:46 lr: 1.3362930623878867e-05 loss: 0.0197 (0.0210) time: 2.9883 data: 0.0030 max mem: 19788 +Epoch: [30] [1650/2138] eta: 0:25:14 lr: 1.3356837639300318e-05 loss: 0.0197 (0.0210) time: 3.0208 data: 0.0030 max mem: 19788 +Epoch: [30] [1660/2138] eta: 0:24:44 lr: 1.3350744345879993e-05 loss: 0.0215 (0.0210) time: 3.1149 data: 0.0030 max mem: 19788 +Epoch: [30] [1670/2138] eta: 0:24:13 lr: 1.3344650743445613e-05 loss: 0.0207 (0.0210) time: 3.2175 data: 0.0025 max mem: 19788 +Epoch: [30] [1680/2138] eta: 0:23:42 lr: 1.33385568318247e-05 loss: 0.0184 (0.0210) time: 3.1815 data: 0.0022 max mem: 19788 +Epoch: [30] [1690/2138] eta: 0:23:10 lr: 1.3332462610844609e-05 loss: 0.0184 (0.0210) time: 3.0595 data: 0.0024 max mem: 19788 +Epoch: [30] [1700/2138] eta: 0:22:39 lr: 1.332636808033249e-05 loss: 0.0181 (0.0209) time: 3.0250 data: 0.0026 max mem: 19788 +Epoch: [30] [1710/2138] eta: 0:22:08 lr: 1.3320273240115327e-05 loss: 0.0185 (0.0209) time: 3.0495 data: 0.0024 max mem: 19788 +Epoch: [30] [1720/2138] eta: 0:21:37 lr: 1.3314178090019902e-05 loss: 0.0200 (0.0209) time: 3.0717 data: 0.0026 max mem: 19788 +Epoch: [30] [1730/2138] eta: 0:21:06 lr: 1.3308082629872832e-05 loss: 0.0210 (0.0209) time: 3.1946 data: 0.0027 max mem: 19788 +Epoch: [30] [1740/2138] eta: 0:20:35 lr: 1.3301986859500531e-05 loss: 0.0196 (0.0209) time: 3.1891 data: 0.0024 max mem: 19788 +Epoch: [30] [1750/2138] eta: 0:20:04 lr: 1.329589077872923e-05 loss: 0.0196 (0.0209) time: 3.0907 data: 0.0023 max mem: 19788 +Epoch: [30] [1760/2138] eta: 0:19:33 lr: 1.3289794387384994e-05 loss: 0.0184 (0.0209) time: 3.0611 data: 0.0023 max mem: 19788 +Epoch: [30] [1770/2138] eta: 0:19:02 lr: 1.3283697685293668e-05 loss: 0.0186 (0.0209) time: 3.0164 data: 0.0024 max mem: 19788 +Epoch: [30] [1780/2138] eta: 0:18:30 lr: 1.3277600672280943e-05 loss: 0.0184 (0.0209) time: 2.9817 data: 0.0024 max mem: 19788 +Epoch: [30] [1790/2138] eta: 0:17:59 lr: 1.3271503348172295e-05 loss: 0.0184 (0.0209) time: 3.0185 data: 0.0023 max mem: 19788 +Epoch: [30] [1800/2138] eta: 0:17:28 lr: 1.3265405712793044e-05 loss: 0.0232 (0.0209) time: 3.0155 data: 0.0024 max mem: 19788 +Epoch: [30] [1810/2138] eta: 0:16:57 lr: 1.325930776596829e-05 loss: 0.0212 (0.0209) time: 2.9779 data: 0.0024 max mem: 19788 +Epoch: [30] [1820/2138] eta: 0:16:26 lr: 1.3253209507522974e-05 loss: 0.0187 (0.0209) time: 3.0505 data: 0.0026 max mem: 19788 +Epoch: [30] [1830/2138] eta: 0:15:55 lr: 1.324711093728182e-05 loss: 0.0200 (0.0209) time: 3.0920 data: 0.0025 max mem: 19788 +Epoch: [30] [1840/2138] eta: 0:15:24 lr: 1.3241012055069397e-05 loss: 0.0204 (0.0209) time: 3.0174 data: 0.0025 max mem: 19788 +Epoch: [30] [1850/2138] eta: 0:14:52 lr: 1.3234912860710053e-05 loss: 0.0204 (0.0209) time: 2.9736 data: 0.0025 max mem: 19788 +Epoch: [30] [1860/2138] eta: 0:14:21 lr: 1.3228813354027973e-05 loss: 0.0210 (0.0210) time: 3.0088 data: 0.0026 max mem: 19788 +Epoch: [30] [1870/2138] eta: 0:13:50 lr: 1.322271353484713e-05 loss: 0.0229 (0.0210) time: 2.9956 data: 0.0028 max mem: 19788 +Epoch: [30] [1880/2138] eta: 0:13:19 lr: 1.3216613402991338e-05 loss: 0.0184 (0.0210) time: 2.9673 data: 0.0027 max mem: 19788 +Epoch: [30] [1890/2138] eta: 0:12:48 lr: 1.321051295828418e-05 loss: 0.0170 (0.0209) time: 2.9931 data: 0.0024 max mem: 19788 +Epoch: [30] [1900/2138] eta: 0:12:17 lr: 1.3204412200549094e-05 loss: 0.0191 (0.0209) time: 3.0479 data: 0.0024 max mem: 19788 +Epoch: [30] [1910/2138] eta: 0:11:46 lr: 1.3198311129609284e-05 loss: 0.0192 (0.0209) time: 3.0828 data: 0.0025 max mem: 19788 +Epoch: [30] [1920/2138] eta: 0:11:15 lr: 1.3192209745287804e-05 loss: 0.0186 (0.0209) time: 3.0314 data: 0.0024 max mem: 19788 +Epoch: [30] [1930/2138] eta: 0:10:44 lr: 1.3186108047407481e-05 loss: 0.0204 (0.0209) time: 3.0493 data: 0.0024 max mem: 19788 +Epoch: [30] [1940/2138] eta: 0:10:13 lr: 1.3180006035790981e-05 loss: 0.0189 (0.0209) time: 3.1146 data: 0.0025 max mem: 19788 +Epoch: [30] [1950/2138] eta: 0:09:42 lr: 1.3173903710260751e-05 loss: 0.0203 (0.0210) time: 3.0757 data: 0.0024 max mem: 19788 +Epoch: [30] [1960/2138] eta: 0:09:11 lr: 1.3167801070639074e-05 loss: 0.0209 (0.0210) time: 3.0360 data: 0.0022 max mem: 19788 +Epoch: [30] [1970/2138] eta: 0:08:40 lr: 1.3161698116748017e-05 loss: 0.0167 (0.0210) time: 3.1286 data: 0.0023 max mem: 19788 +Epoch: [30] [1980/2138] eta: 0:08:09 lr: 1.3155594848409469e-05 loss: 0.0188 (0.0210) time: 3.1454 data: 0.0025 max mem: 19788 +Epoch: [30] [1990/2138] eta: 0:07:38 lr: 1.3149491265445113e-05 loss: 0.0208 (0.0210) time: 3.0860 data: 0.0026 max mem: 19788 +Epoch: [30] [2000/2138] eta: 0:07:07 lr: 1.314338736767646e-05 loss: 0.0188 (0.0210) time: 3.1429 data: 0.0030 max mem: 19788 +Epoch: [30] [2010/2138] eta: 0:06:36 lr: 1.3137283154924802e-05 loss: 0.0192 (0.0210) time: 3.1581 data: 0.0028 max mem: 19788 +Epoch: [30] [2020/2138] eta: 0:06:05 lr: 1.3131178627011262e-05 loss: 0.0213 (0.0210) time: 3.1226 data: 0.0023 max mem: 19788 +Epoch: [30] [2030/2138] eta: 0:05:34 lr: 1.3125073783756742e-05 loss: 0.0198 (0.0210) time: 3.0560 data: 0.0024 max mem: 19788 +Epoch: [30] [2040/2138] eta: 0:05:03 lr: 1.3118968624981981e-05 loss: 0.0194 (0.0210) time: 2.9659 data: 0.0024 max mem: 19788 +Epoch: [30] [2050/2138] eta: 0:04:32 lr: 1.3112863150507499e-05 loss: 0.0195 (0.0210) time: 2.9378 data: 0.0022 max mem: 19788 +Epoch: [30] [2060/2138] eta: 0:04:01 lr: 1.310675736015362e-05 loss: 0.0195 (0.0210) time: 2.9700 data: 0.0022 max mem: 19788 +Epoch: [30] [2070/2138] eta: 0:03:30 lr: 1.31006512537405e-05 loss: 0.0189 (0.0210) time: 3.0254 data: 0.0023 max mem: 19788 +Epoch: [30] [2080/2138] eta: 0:02:59 lr: 1.3094544831088062e-05 loss: 0.0190 (0.0210) time: 3.0183 data: 0.0023 max mem: 19788 +Epoch: [30] [2090/2138] eta: 0:02:28 lr: 1.308843809201607e-05 loss: 0.0211 (0.0210) time: 2.9628 data: 0.0025 max mem: 19788 +Epoch: [30] [2100/2138] eta: 0:01:57 lr: 1.3082331036344056e-05 loss: 0.0199 (0.0210) time: 3.0261 data: 0.0024 max mem: 19788 +Epoch: [30] [2110/2138] eta: 0:01:26 lr: 1.3076223663891388e-05 loss: 0.0213 (0.0210) time: 3.1336 data: 0.0026 max mem: 19788 +Epoch: [30] [2120/2138] eta: 0:00:55 lr: 1.307011597447721e-05 loss: 0.0242 (0.0210) time: 3.0938 data: 0.0029 max mem: 19788 +Epoch: [30] [2130/2138] eta: 0:00:24 lr: 1.3064007967920495e-05 loss: 0.0232 (0.0210) time: 2.9774 data: 0.0025 max mem: 19788 +Epoch: [30] Total time: 1:50:14 +Test: [ 0/21770] eta: 16:53:32 time: 2.7934 data: 2.5225 max mem: 19788 +Test: [ 100/21770] eta: 0:28:36 time: 0.0524 data: 0.0019 max mem: 19788 +Test: [ 200/21770] eta: 0:22:25 time: 0.0437 data: 0.0015 max mem: 19788 +Test: [ 300/21770] eta: 0:20:18 time: 0.0489 data: 0.0017 max mem: 19788 +Test: [ 400/21770] eta: 0:19:33 time: 0.0532 data: 0.0018 max mem: 19788 +Test: [ 500/21770] eta: 0:18:55 time: 0.0456 data: 0.0016 max mem: 19788 +Test: [ 600/21770] eta: 0:18:38 time: 0.0519 data: 0.0019 max mem: 19788 +Test: [ 700/21770] eta: 0:18:21 time: 0.0532 data: 0.0017 max mem: 19788 +Test: [ 800/21770] eta: 0:18:07 time: 0.0443 data: 0.0015 max mem: 19788 +Test: [ 900/21770] eta: 0:17:44 time: 0.0494 data: 0.0016 max mem: 19788 +Test: [ 1000/21770] eta: 0:17:41 time: 0.0505 data: 0.0019 max mem: 19788 +Test: [ 1100/21770] eta: 0:17:37 time: 0.0478 data: 0.0016 max mem: 19788 +Test: [ 1200/21770] eta: 0:17:26 time: 0.0434 data: 0.0015 max mem: 19788 +Test: [ 1300/21770] eta: 0:17:14 time: 0.0524 data: 0.0019 max mem: 19788 +Test: [ 1400/21770] eta: 0:17:05 time: 0.0434 data: 0.0014 max mem: 19788 +Test: [ 1500/21770] eta: 0:16:52 time: 0.0514 data: 0.0017 max mem: 19788 +Test: [ 1600/21770] eta: 0:16:44 time: 0.0488 data: 0.0016 max mem: 19788 +Test: [ 1700/21770] eta: 0:16:35 time: 0.0436 data: 0.0014 max mem: 19788 +Test: [ 1800/21770] eta: 0:16:27 time: 0.0477 data: 0.0015 max mem: 19788 +Test: [ 1900/21770] eta: 0:16:20 time: 0.0459 data: 0.0018 max mem: 19788 +Test: [ 2000/21770] eta: 0:16:11 time: 0.0427 data: 0.0015 max mem: 19788 +Test: [ 2100/21770] eta: 0:16:01 time: 0.0468 data: 0.0016 max mem: 19788 +Test: [ 2200/21770] eta: 0:15:54 time: 0.0440 data: 0.0016 max mem: 19788 +Test: [ 2300/21770] eta: 0:15:47 time: 0.0469 data: 0.0017 max mem: 19788 +Test: [ 2400/21770] eta: 0:15:42 time: 0.0526 data: 0.0019 max mem: 19788 +Test: [ 2500/21770] eta: 0:15:40 time: 0.0533 data: 0.0018 max mem: 19788 +Test: [ 2600/21770] eta: 0:15:34 time: 0.0432 data: 0.0014 max mem: 19788 +Test: [ 2700/21770] eta: 0:15:26 time: 0.0426 data: 0.0014 max mem: 19788 +Test: [ 2800/21770] eta: 0:15:21 time: 0.0535 data: 0.0017 max mem: 19788 +Test: [ 2900/21770] eta: 0:15:14 time: 0.0431 data: 0.0016 max mem: 19788 +Test: [ 3000/21770] eta: 0:15:07 time: 0.0480 data: 0.0017 max mem: 19788 +Test: [ 3100/21770] eta: 0:15:00 time: 0.0446 data: 0.0015 max mem: 19788 +Test: [ 3200/21770] eta: 0:14:57 time: 0.0500 data: 0.0018 max mem: 19788 +Test: [ 3300/21770] eta: 0:14:53 time: 0.0534 data: 0.0016 max mem: 19788 +Test: [ 3400/21770] eta: 0:14:47 time: 0.0419 data: 0.0015 max mem: 19788 +Test: [ 3500/21770] eta: 0:14:42 time: 0.0459 data: 0.0020 max mem: 19788 +Test: [ 3600/21770] eta: 0:14:36 time: 0.0447 data: 0.0020 max mem: 19788 +Test: [ 3700/21770] eta: 0:14:31 time: 0.0528 data: 0.0023 max mem: 19788 +Test: [ 3800/21770] eta: 0:14:25 time: 0.0442 data: 0.0016 max mem: 19788 +Test: [ 3900/21770] eta: 0:14:20 time: 0.0503 data: 0.0017 max mem: 19788 +Test: [ 4000/21770] eta: 0:14:15 time: 0.0479 data: 0.0017 max mem: 19788 +Test: [ 4100/21770] eta: 0:14:12 time: 0.0531 data: 0.0018 max mem: 19788 +Test: [ 4200/21770] eta: 0:14:06 time: 0.0443 data: 0.0015 max mem: 19788 +Test: [ 4300/21770] eta: 0:14:02 time: 0.0502 data: 0.0016 max mem: 19788 +Test: [ 4400/21770] eta: 0:13:59 time: 0.0535 data: 0.0018 max mem: 19788 +Test: [ 4500/21770] eta: 0:13:54 time: 0.0432 data: 0.0014 max mem: 19788 +Test: [ 4600/21770] eta: 0:13:48 time: 0.0430 data: 0.0014 max mem: 19788 +Test: [ 4700/21770] eta: 0:13:43 time: 0.0441 data: 0.0015 max mem: 19788 +Test: [ 4800/21770] eta: 0:13:39 time: 0.0447 data: 0.0015 max mem: 19788 +Test: [ 4900/21770] eta: 0:13:35 time: 0.0475 data: 0.0017 max mem: 19788 +Test: [ 5000/21770] eta: 0:13:31 time: 0.0531 data: 0.0019 max mem: 19788 +Test: [ 5100/21770] eta: 0:13:28 time: 0.0527 data: 0.0017 max mem: 19788 +Test: [ 5200/21770] eta: 0:13:24 time: 0.0500 data: 0.0018 max mem: 19788 +Test: [ 5300/21770] eta: 0:13:19 time: 0.0436 data: 0.0016 max mem: 19788 +Test: [ 5400/21770] eta: 0:13:12 time: 0.0430 data: 0.0015 max mem: 19788 +Test: [ 5500/21770] eta: 0:13:08 time: 0.0531 data: 0.0017 max mem: 19788 +Test: [ 5600/21770] eta: 0:13:04 time: 0.0464 data: 0.0015 max mem: 19788 +Test: [ 5700/21770] eta: 0:12:58 time: 0.0454 data: 0.0015 max mem: 19788 +Test: [ 5800/21770] eta: 0:12:54 time: 0.0526 data: 0.0018 max mem: 19788 +Test: [ 5900/21770] eta: 0:12:49 time: 0.0442 data: 0.0014 max mem: 19788 +Test: [ 6000/21770] eta: 0:12:43 time: 0.0443 data: 0.0016 max mem: 19788 +Test: [ 6100/21770] eta: 0:12:38 time: 0.0494 data: 0.0018 max mem: 19788 +Test: [ 6200/21770] eta: 0:12:32 time: 0.0471 data: 0.0018 max mem: 19788 +Test: [ 6300/21770] eta: 0:12:28 time: 0.0450 data: 0.0016 max mem: 19788 +Test: [ 6400/21770] eta: 0:12:24 time: 0.0498 data: 0.0018 max mem: 19788 +Test: [ 6500/21770] eta: 0:12:19 time: 0.0535 data: 0.0017 max mem: 19788 +Test: [ 6600/21770] eta: 0:12:14 time: 0.0444 data: 0.0015 max mem: 19788 +Test: [ 6700/21770] eta: 0:12:09 time: 0.0489 data: 0.0014 max mem: 19788 +Test: [ 6800/21770] eta: 0:12:05 time: 0.0528 data: 0.0018 max mem: 19788 +Test: [ 6900/21770] eta: 0:12:00 time: 0.0533 data: 0.0018 max mem: 19788 +Test: [ 7000/21770] eta: 0:11:55 time: 0.0451 data: 0.0014 max mem: 19788 +Test: [ 7100/21770] eta: 0:11:50 time: 0.0464 data: 0.0015 max mem: 19788 +Test: [ 7200/21770] eta: 0:11:46 time: 0.0468 data: 0.0017 max mem: 19788 +Test: [ 7300/21770] eta: 0:11:40 time: 0.0496 data: 0.0017 max mem: 19788 +Test: [ 7400/21770] eta: 0:11:35 time: 0.0534 data: 0.0018 max mem: 19788 +Test: [ 7500/21770] eta: 0:11:30 time: 0.0438 data: 0.0014 max mem: 19788 +Test: [ 7600/21770] eta: 0:11:25 time: 0.0527 data: 0.0018 max mem: 19788 +Test: [ 7700/21770] eta: 0:11:20 time: 0.0488 data: 0.0017 max mem: 19788 +Test: [ 7800/21770] eta: 0:11:15 time: 0.0532 data: 0.0018 max mem: 19788 +Test: [ 7900/21770] eta: 0:11:10 time: 0.0440 data: 0.0014 max mem: 19788 +Test: [ 8000/21770] eta: 0:11:06 time: 0.0535 data: 0.0017 max mem: 19788 +Test: [ 8100/21770] eta: 0:11:01 time: 0.0438 data: 0.0015 max mem: 19788 +Test: [ 8200/21770] eta: 0:10:55 time: 0.0488 data: 0.0016 max mem: 19788 +Test: [ 8300/21770] eta: 0:10:51 time: 0.0520 data: 0.0018 max mem: 19788 +Test: [ 8400/21770] eta: 0:10:45 time: 0.0437 data: 0.0015 max mem: 19788 +Test: [ 8500/21770] eta: 0:10:40 time: 0.0432 data: 0.0015 max mem: 19788 +Test: [ 8600/21770] eta: 0:10:35 time: 0.0448 data: 0.0014 max mem: 19788 +Test: [ 8700/21770] eta: 0:10:30 time: 0.0521 data: 0.0016 max mem: 19788 +Test: [ 8800/21770] eta: 0:10:25 time: 0.0440 data: 0.0013 max mem: 19788 +Test: [ 8900/21770] eta: 0:10:20 time: 0.0467 data: 0.0015 max mem: 19788 +Test: [ 9000/21770] eta: 0:10:15 time: 0.0542 data: 0.0019 max mem: 19788 +Test: [ 9100/21770] eta: 0:10:10 time: 0.0550 data: 0.0020 max mem: 19788 +Test: [ 9200/21770] eta: 0:10:06 time: 0.0537 data: 0.0017 max mem: 19788 +Test: [ 9300/21770] eta: 0:10:02 time: 0.0508 data: 0.0018 max mem: 19788 +Test: [ 9400/21770] eta: 0:09:57 time: 0.0468 data: 0.0017 max mem: 19788 +Test: [ 9500/21770] eta: 0:09:52 time: 0.0452 data: 0.0014 max mem: 19788 +Test: [ 9600/21770] eta: 0:09:47 time: 0.0526 data: 0.0016 max mem: 19788 +Test: [ 9700/21770] eta: 0:09:42 time: 0.0505 data: 0.0017 max mem: 19788 +Test: [ 9800/21770] eta: 0:09:38 time: 0.0525 data: 0.0018 max mem: 19788 +Test: [ 9900/21770] eta: 0:09:33 time: 0.0514 data: 0.0018 max mem: 19788 +Test: [10000/21770] eta: 0:09:28 time: 0.0505 data: 0.0016 max mem: 19788 +Test: [10100/21770] eta: 0:09:23 time: 0.0451 data: 0.0015 max mem: 19788 +Test: [10200/21770] eta: 0:09:19 time: 0.0495 data: 0.0017 max mem: 19788 +Test: [10300/21770] eta: 0:09:14 time: 0.0530 data: 0.0018 max mem: 19788 +Test: [10400/21770] eta: 0:09:09 time: 0.0533 data: 0.0018 max mem: 19788 +Test: [10500/21770] eta: 0:09:05 time: 0.0512 data: 0.0017 max mem: 19788 +Test: [10600/21770] eta: 0:09:00 time: 0.0508 data: 0.0018 max mem: 19788 +Test: [10700/21770] eta: 0:08:55 time: 0.0523 data: 0.0018 max mem: 19788 +Test: [10800/21770] eta: 0:08:50 time: 0.0453 data: 0.0014 max mem: 19788 +Test: [10900/21770] eta: 0:08:45 time: 0.0437 data: 0.0015 max mem: 19788 +Test: [11000/21770] eta: 0:08:40 time: 0.0467 data: 0.0015 max mem: 19788 +Test: [11100/21770] eta: 0:08:36 time: 0.0443 data: 0.0014 max mem: 19788 +Test: [11200/21770] eta: 0:08:31 time: 0.0445 data: 0.0014 max mem: 19788 +Test: [11300/21770] eta: 0:08:26 time: 0.0454 data: 0.0016 max mem: 19788 +Test: [11400/21770] eta: 0:08:21 time: 0.0485 data: 0.0017 max mem: 19788 +Test: [11500/21770] eta: 0:08:16 time: 0.0527 data: 0.0017 max mem: 19788 +Test: [11600/21770] eta: 0:08:11 time: 0.0445 data: 0.0017 max mem: 19788 +Test: [11700/21770] eta: 0:08:06 time: 0.0487 data: 0.0019 max mem: 19788 +Test: [11800/21770] eta: 0:08:01 time: 0.0470 data: 0.0015 max mem: 19788 +Test: [11900/21770] eta: 0:07:56 time: 0.0455 data: 0.0015 max mem: 19788 +Test: [12000/21770] eta: 0:07:51 time: 0.0442 data: 0.0015 max mem: 19788 +Test: [12100/21770] eta: 0:07:46 time: 0.0443 data: 0.0014 max mem: 19788 +Test: [12200/21770] eta: 0:07:41 time: 0.0440 data: 0.0013 max mem: 19788 +Test: [12300/21770] eta: 0:07:36 time: 0.0482 data: 0.0015 max mem: 19788 +Test: [12400/21770] eta: 0:07:32 time: 0.0498 data: 0.0015 max mem: 19788 +Test: [12500/21770] eta: 0:07:27 time: 0.0537 data: 0.0019 max mem: 19788 +Test: [12600/21770] eta: 0:07:22 time: 0.0447 data: 0.0016 max mem: 19788 +Test: [12700/21770] eta: 0:07:18 time: 0.0537 data: 0.0018 max mem: 19788 +Test: [12800/21770] eta: 0:07:13 time: 0.0437 data: 0.0014 max mem: 19788 +Test: [12900/21770] eta: 0:07:08 time: 0.0507 data: 0.0016 max mem: 19788 +Test: [13000/21770] eta: 0:07:03 time: 0.0431 data: 0.0014 max mem: 19788 +Test: [13100/21770] eta: 0:06:58 time: 0.0440 data: 0.0015 max mem: 19788 +Test: [13200/21770] eta: 0:06:53 time: 0.0534 data: 0.0017 max mem: 19788 +Test: [13300/21770] eta: 0:06:49 time: 0.0459 data: 0.0017 max mem: 19788 +Test: [13400/21770] eta: 0:06:44 time: 0.0436 data: 0.0016 max mem: 19788 +Test: [13500/21770] eta: 0:06:39 time: 0.0449 data: 0.0014 max mem: 19788 +Test: [13600/21770] eta: 0:06:33 time: 0.0435 data: 0.0014 max mem: 19788 +Test: [13700/21770] eta: 0:06:28 time: 0.0481 data: 0.0015 max mem: 19788 +Test: [13800/21770] eta: 0:06:23 time: 0.0447 data: 0.0023 max mem: 19788 +Test: [13900/21770] eta: 0:06:19 time: 0.0472 data: 0.0017 max mem: 19788 +Test: [14000/21770] eta: 0:06:14 time: 0.0461 data: 0.0014 max mem: 19788 +Test: [14100/21770] eta: 0:06:09 time: 0.0505 data: 0.0017 max mem: 19788 +Test: [14200/21770] eta: 0:06:04 time: 0.0501 data: 0.0017 max mem: 19788 +Test: [14300/21770] eta: 0:06:00 time: 0.0477 data: 0.0021 max mem: 19788 +Test: [14400/21770] eta: 0:05:55 time: 0.0499 data: 0.0018 max mem: 19788 +Test: [14500/21770] eta: 0:05:50 time: 0.0495 data: 0.0016 max mem: 19788 +Test: [14600/21770] eta: 0:05:45 time: 0.0452 data: 0.0017 max mem: 19788 +Test: [14700/21770] eta: 0:05:40 time: 0.0481 data: 0.0016 max mem: 19788 +Test: [14800/21770] eta: 0:05:36 time: 0.0469 data: 0.0016 max mem: 19788 +Test: [14900/21770] eta: 0:05:31 time: 0.0445 data: 0.0015 max mem: 19788 +Test: [15000/21770] eta: 0:05:26 time: 0.0450 data: 0.0017 max mem: 19788 +Test: [15100/21770] eta: 0:05:21 time: 0.0431 data: 0.0015 max mem: 19788 +Test: [15200/21770] eta: 0:05:16 time: 0.0513 data: 0.0018 max mem: 19788 +Test: [15300/21770] eta: 0:05:11 time: 0.0523 data: 0.0017 max mem: 19788 +Test: [15400/21770] eta: 0:05:07 time: 0.0524 data: 0.0018 max mem: 19788 +Test: [15500/21770] eta: 0:05:02 time: 0.0505 data: 0.0017 max mem: 19788 +Test: [15600/21770] eta: 0:04:57 time: 0.0469 data: 0.0014 max mem: 19788 +Test: [15700/21770] eta: 0:04:53 time: 0.0526 data: 0.0019 max mem: 19788 +Test: [15800/21770] eta: 0:04:48 time: 0.0453 data: 0.0014 max mem: 19788 +Test: [15900/21770] eta: 0:04:43 time: 0.0449 data: 0.0014 max mem: 19788 +Test: [16000/21770] eta: 0:04:38 time: 0.0528 data: 0.0019 max mem: 19788 +Test: [16100/21770] eta: 0:04:33 time: 0.0452 data: 0.0017 max mem: 19788 +Test: [16200/21770] eta: 0:04:28 time: 0.0481 data: 0.0016 max mem: 19788 +Test: [16300/21770] eta: 0:04:23 time: 0.0438 data: 0.0014 max mem: 19788 +Test: [16400/21770] eta: 0:04:18 time: 0.0430 data: 0.0014 max mem: 19788 +Test: [16500/21770] eta: 0:04:13 time: 0.0528 data: 0.0017 max mem: 19788 +Test: [16600/21770] eta: 0:04:09 time: 0.0505 data: 0.0016 max mem: 19788 +Test: [16700/21770] eta: 0:04:04 time: 0.0500 data: 0.0016 max mem: 19788 +Test: [16800/21770] eta: 0:03:59 time: 0.0458 data: 0.0014 max mem: 19788 +Test: [16900/21770] eta: 0:03:54 time: 0.0440 data: 0.0015 max mem: 19788 +Test: [17000/21770] eta: 0:03:49 time: 0.0452 data: 0.0014 max mem: 19788 +Test: [17100/21770] eta: 0:03:44 time: 0.0445 data: 0.0015 max mem: 19788 +Test: [17200/21770] eta: 0:03:39 time: 0.0463 data: 0.0016 max mem: 19788 +Test: [17300/21770] eta: 0:03:35 time: 0.0465 data: 0.0017 max mem: 19788 +Test: [17400/21770] eta: 0:03:30 time: 0.0438 data: 0.0015 max mem: 19788 +Test: [17500/21770] eta: 0:03:25 time: 0.0443 data: 0.0016 max mem: 19788 +Test: [17600/21770] eta: 0:03:20 time: 0.0493 data: 0.0017 max mem: 19788 +Test: [17700/21770] eta: 0:03:15 time: 0.0534 data: 0.0019 max mem: 19788 +Test: [17800/21770] eta: 0:03:10 time: 0.0525 data: 0.0017 max mem: 19788 +Test: [17900/21770] eta: 0:03:06 time: 0.0443 data: 0.0014 max mem: 19788 +Test: [18000/21770] eta: 0:03:01 time: 0.0435 data: 0.0014 max mem: 19788 +Test: [18100/21770] eta: 0:02:56 time: 0.0442 data: 0.0014 max mem: 19788 +Test: [18200/21770] eta: 0:02:51 time: 0.0472 data: 0.0016 max mem: 19788 +Test: [18300/21770] eta: 0:02:46 time: 0.0517 data: 0.0018 max mem: 19788 +Test: [18400/21770] eta: 0:02:42 time: 0.0435 data: 0.0015 max mem: 19788 +Test: [18500/21770] eta: 0:02:37 time: 0.0468 data: 0.0016 max mem: 19788 +Test: [18600/21770] eta: 0:02:32 time: 0.0450 data: 0.0015 max mem: 19788 +Test: [18700/21770] eta: 0:02:27 time: 0.0464 data: 0.0014 max mem: 19788 +Test: [18800/21770] eta: 0:02:22 time: 0.0435 data: 0.0016 max mem: 19788 +Test: [18900/21770] eta: 0:02:17 time: 0.0515 data: 0.0018 max mem: 19788 +Test: [19000/21770] eta: 0:02:13 time: 0.0468 data: 0.0017 max mem: 19788 +Test: [19100/21770] eta: 0:02:08 time: 0.0508 data: 0.0015 max mem: 19788 +Test: [19200/21770] eta: 0:02:03 time: 0.0536 data: 0.0017 max mem: 19788 +Test: [19300/21770] eta: 0:01:58 time: 0.0508 data: 0.0018 max mem: 19788 +Test: [19400/21770] eta: 0:01:53 time: 0.0446 data: 0.0014 max mem: 19788 +Test: [19500/21770] eta: 0:01:49 time: 0.0456 data: 0.0016 max mem: 19788 +Test: [19600/21770] eta: 0:01:44 time: 0.0503 data: 0.0018 max mem: 19788 +Test: [19700/21770] eta: 0:01:39 time: 0.0436 data: 0.0014 max mem: 19788 +Test: [19800/21770] eta: 0:01:34 time: 0.0447 data: 0.0015 max mem: 19788 +Test: [19900/21770] eta: 0:01:29 time: 0.0431 data: 0.0014 max mem: 19788 +Test: [20000/21770] eta: 0:01:24 time: 0.0441 data: 0.0015 max mem: 19788 +Test: [20100/21770] eta: 0:01:20 time: 0.0468 data: 0.0015 max mem: 19788 +Test: [20200/21770] eta: 0:01:15 time: 0.0474 data: 0.0016 max mem: 19788 +Test: [20300/21770] eta: 0:01:10 time: 0.0542 data: 0.0016 max mem: 19788 +Test: [20400/21770] eta: 0:01:05 time: 0.0441 data: 0.0014 max mem: 19788 +Test: [20500/21770] eta: 0:01:00 time: 0.0431 data: 0.0015 max mem: 19788 +Test: [20600/21770] eta: 0:00:56 time: 0.0434 data: 0.0016 max mem: 19788 +Test: [20700/21770] eta: 0:00:51 time: 0.0491 data: 0.0017 max mem: 19788 +Test: [20800/21770] eta: 0:00:46 time: 0.0509 data: 0.0017 max mem: 19788 +Test: [20900/21770] eta: 0:00:41 time: 0.0457 data: 0.0014 max mem: 19788 +Test: [21000/21770] eta: 0:00:36 time: 0.0490 data: 0.0022 max mem: 19788 +Test: [21100/21770] eta: 0:00:32 time: 0.0452 data: 0.0015 max mem: 19788 +Test: [21200/21770] eta: 0:00:27 time: 0.0547 data: 0.0018 max mem: 19788 +Test: [21300/21770] eta: 0:00:22 time: 0.0491 data: 0.0016 max mem: 19788 +Test: [21400/21770] eta: 0:00:17 time: 0.0507 data: 0.0014 max mem: 19788 +Test: [21500/21770] eta: 0:00:12 time: 0.0440 data: 0.0015 max mem: 19788 +Test: [21600/21770] eta: 0:00:08 time: 0.0516 data: 0.0017 max mem: 19788 +Test: [21700/21770] eta: 0:00:03 time: 0.0453 data: 0.0015 max mem: 19788 +Test: Total time: 0:17:27 +Final results: +Mean IoU is 64.81 + + precision@0.5 = 72.08 + precision@0.6 = 66.70 + precision@0.7 = 60.28 + precision@0.8 = 49.60 + precision@0.9 = 24.58 + overall IoU = 65.07 + mean IoU = 64.81 + +Mean accuracy for one-to-zero sample is 87.02 + +Average object IoU 0.6481209695702671 +Overall IoU 65.07144927978516 +Better epoch: 30 + +Epoch: [31] [ 0/2138] eta: 3:33:24 lr: 1.30591213342107e-05 loss: 0.0288 (0.0288) time: 5.9890 data: 2.3565 max mem: 19788 +Epoch: [31] [ 10/2138] eta: 1:56:08 lr: 1.3053012756340541e-05 loss: 0.0202 (0.0215) time: 3.2745 data: 0.2157 max mem: 19788 +Epoch: [31] [ 20/2138] eta: 1:53:20 lr: 1.304690386081988e-05 loss: 0.0193 (0.0200) time: 3.0721 data: 0.0019 max mem: 19788 +Epoch: [31] [ 30/2138] eta: 1:51:11 lr: 1.3040794647466905e-05 loss: 0.0204 (0.0207) time: 3.1045 data: 0.0024 max mem: 19788 +Epoch: [31] [ 40/2138] eta: 1:48:56 lr: 1.3034685116099643e-05 loss: 0.0208 (0.0208) time: 3.0156 data: 0.0030 max mem: 19788 +Epoch: [31] [ 50/2138] eta: 1:47:22 lr: 1.3028575266535885e-05 loss: 0.0194 (0.0208) time: 2.9630 data: 0.0031 max mem: 19788 +Epoch: [31] [ 60/2138] eta: 1:46:39 lr: 1.3022465098593258e-05 loss: 0.0204 (0.0212) time: 3.0057 data: 0.0025 max mem: 19788 +Epoch: [31] [ 70/2138] eta: 1:46:00 lr: 1.3016354612089154e-05 loss: 0.0206 (0.0212) time: 3.0504 data: 0.0022 max mem: 19788 +Epoch: [31] [ 80/2138] eta: 1:45:16 lr: 1.3010243806840802e-05 loss: 0.0204 (0.0214) time: 3.0369 data: 0.0022 max mem: 19788 +Epoch: [31] [ 90/2138] eta: 1:45:05 lr: 1.3004132682665193e-05 loss: 0.0196 (0.0211) time: 3.0893 data: 0.0023 max mem: 19788 +Epoch: [31] [ 100/2138] eta: 1:44:24 lr: 1.2998021239379152e-05 loss: 0.0192 (0.0211) time: 3.0925 data: 0.0026 max mem: 19788 +Epoch: [31] [ 110/2138] eta: 1:43:47 lr: 1.299190947679928e-05 loss: 0.0193 (0.0209) time: 3.0344 data: 0.0025 max mem: 19788 +Epoch: [31] [ 120/2138] eta: 1:42:58 lr: 1.2985797394741977e-05 loss: 0.0159 (0.0206) time: 3.0008 data: 0.0023 max mem: 19788 +Epoch: [31] [ 130/2138] eta: 1:42:09 lr: 1.2979684993023458e-05 loss: 0.0194 (0.0206) time: 2.9507 data: 0.0024 max mem: 19788 +Epoch: [31] [ 140/2138] eta: 1:41:26 lr: 1.2973572271459718e-05 loss: 0.0201 (0.0207) time: 2.9549 data: 0.0024 max mem: 19788 +Epoch: [31] [ 150/2138] eta: 1:40:55 lr: 1.2967459229866572e-05 loss: 0.0194 (0.0206) time: 3.0033 data: 0.0024 max mem: 19788 +Epoch: [31] [ 160/2138] eta: 1:40:26 lr: 1.2961345868059599e-05 loss: 0.0194 (0.0206) time: 3.0474 data: 0.0024 max mem: 19788 +Epoch: [31] [ 170/2138] eta: 1:39:50 lr: 1.2955232185854211e-05 loss: 0.0204 (0.0205) time: 3.0287 data: 0.0026 max mem: 19788 +Epoch: [31] [ 180/2138] eta: 1:39:30 lr: 1.2949118183065584e-05 loss: 0.0194 (0.0205) time: 3.0704 data: 0.0025 max mem: 19788 +Epoch: [31] [ 190/2138] eta: 1:38:50 lr: 1.2943003859508724e-05 loss: 0.0179 (0.0204) time: 3.0480 data: 0.0024 max mem: 19788 +Epoch: [31] [ 200/2138] eta: 1:38:14 lr: 1.2936889214998397e-05 loss: 0.0186 (0.0204) time: 2.9706 data: 0.0026 max mem: 19788 +Epoch: [31] [ 210/2138] eta: 1:37:35 lr: 1.2930774249349199e-05 loss: 0.0201 (0.0209) time: 2.9677 data: 0.0029 max mem: 19788 +Epoch: [31] [ 220/2138] eta: 1:37:03 lr: 1.2924658962375494e-05 loss: 0.0189 (0.0208) time: 2.9856 data: 0.0028 max mem: 19788 +Epoch: [31] [ 230/2138] eta: 1:36:27 lr: 1.291854335389146e-05 loss: 0.0177 (0.0208) time: 2.9921 data: 0.0026 max mem: 19788 +Epoch: [31] [ 240/2138] eta: 1:36:01 lr: 1.2912427423711057e-05 loss: 0.0194 (0.0208) time: 3.0293 data: 0.0029 max mem: 19788 +Epoch: [31] [ 250/2138] eta: 1:35:37 lr: 1.290631117164805e-05 loss: 0.0194 (0.0207) time: 3.1027 data: 0.0028 max mem: 19788 +Epoch: [31] [ 260/2138] eta: 1:35:00 lr: 1.2900194597515985e-05 loss: 0.0188 (0.0207) time: 3.0324 data: 0.0028 max mem: 19788 +Epoch: [31] [ 270/2138] eta: 1:34:24 lr: 1.2894077701128222e-05 loss: 0.0192 (0.0206) time: 2.9558 data: 0.0029 max mem: 19788 +Epoch: [31] [ 280/2138] eta: 1:33:49 lr: 1.2887960482297883e-05 loss: 0.0199 (0.0207) time: 2.9572 data: 0.0029 max mem: 19788 +Epoch: [31] [ 290/2138] eta: 1:33:13 lr: 1.2881842940837924e-05 loss: 0.0198 (0.0207) time: 2.9502 data: 0.0026 max mem: 19788 +Epoch: [31] [ 300/2138] eta: 1:32:41 lr: 1.2875725076561051e-05 loss: 0.0196 (0.0208) time: 2.9701 data: 0.0022 max mem: 19788 +Epoch: [31] [ 310/2138] eta: 1:32:07 lr: 1.2869606889279797e-05 loss: 0.0190 (0.0207) time: 2.9775 data: 0.0022 max mem: 19788 +Epoch: [31] [ 320/2138] eta: 1:31:33 lr: 1.2863488378806463e-05 loss: 0.0171 (0.0206) time: 2.9588 data: 0.0022 max mem: 19788 +Epoch: [31] [ 330/2138] eta: 1:31:05 lr: 1.2857369544953163e-05 loss: 0.0193 (0.0207) time: 3.0083 data: 0.0024 max mem: 19788 +Epoch: [31] [ 340/2138] eta: 1:30:31 lr: 1.2851250387531776e-05 loss: 0.0212 (0.0206) time: 3.0088 data: 0.0030 max mem: 19788 +Epoch: [31] [ 350/2138] eta: 1:29:58 lr: 1.2845130906354006e-05 loss: 0.0203 (0.0206) time: 2.9579 data: 0.0032 max mem: 19788 +Epoch: [31] [ 360/2138] eta: 1:29:25 lr: 1.2839011101231307e-05 loss: 0.0210 (0.0207) time: 2.9647 data: 0.0028 max mem: 19788 +Epoch: [31] [ 370/2138] eta: 1:29:03 lr: 1.2832890971974965e-05 loss: 0.0214 (0.0207) time: 3.0774 data: 0.0025 max mem: 19788 +Epoch: [31] [ 380/2138] eta: 1:28:30 lr: 1.2826770518396019e-05 loss: 0.0204 (0.0207) time: 3.0674 data: 0.0027 max mem: 19788 +Epoch: [31] [ 390/2138] eta: 1:27:57 lr: 1.282064974030533e-05 loss: 0.0177 (0.0206) time: 2.9571 data: 0.0029 max mem: 19788 +Epoch: [31] [ 400/2138] eta: 1:27:23 lr: 1.2814528637513523e-05 loss: 0.0191 (0.0207) time: 2.9517 data: 0.0027 max mem: 19788 +Epoch: [31] [ 410/2138] eta: 1:26:51 lr: 1.2808407209831017e-05 loss: 0.0191 (0.0206) time: 2.9624 data: 0.0025 max mem: 19788 +Epoch: [31] [ 420/2138] eta: 1:26:29 lr: 1.2802285457068037e-05 loss: 0.0172 (0.0205) time: 3.0908 data: 0.0023 max mem: 19788 +Epoch: [31] [ 430/2138] eta: 1:25:59 lr: 1.2796163379034572e-05 loss: 0.0178 (0.0205) time: 3.1218 data: 0.0023 max mem: 19788 +Epoch: [31] [ 440/2138] eta: 1:25:26 lr: 1.2790040975540421e-05 loss: 0.0194 (0.0206) time: 2.9905 data: 0.0023 max mem: 19788 +Epoch: [31] [ 450/2138] eta: 1:24:53 lr: 1.278391824639515e-05 loss: 0.0202 (0.0205) time: 2.9444 data: 0.0025 max mem: 19788 +Epoch: [31] [ 460/2138] eta: 1:24:21 lr: 1.2777795191408133e-05 loss: 0.0185 (0.0205) time: 2.9515 data: 0.0027 max mem: 19788 +Epoch: [31] [ 470/2138] eta: 1:23:48 lr: 1.2771671810388505e-05 loss: 0.0188 (0.0205) time: 2.9513 data: 0.0025 max mem: 19788 +Epoch: [31] [ 480/2138] eta: 1:23:17 lr: 1.2765548103145218e-05 loss: 0.0208 (0.0206) time: 2.9657 data: 0.0026 max mem: 19788 +Epoch: [31] [ 490/2138] eta: 1:22:45 lr: 1.275942406948698e-05 loss: 0.0208 (0.0205) time: 2.9651 data: 0.0026 max mem: 19788 +Epoch: [31] [ 500/2138] eta: 1:22:14 lr: 1.2753299709222316e-05 loss: 0.0194 (0.0206) time: 2.9665 data: 0.0028 max mem: 19788 +Epoch: [31] [ 510/2138] eta: 1:21:49 lr: 1.2747175022159502e-05 loss: 0.0169 (0.0205) time: 3.0868 data: 0.0029 max mem: 19788 +Epoch: [31] [ 520/2138] eta: 1:21:21 lr: 1.2741050008106634e-05 loss: 0.0173 (0.0205) time: 3.1413 data: 0.0026 max mem: 19788 +Epoch: [31] [ 530/2138] eta: 1:20:51 lr: 1.2734924666871558e-05 loss: 0.0193 (0.0205) time: 3.0457 data: 0.0024 max mem: 19788 +Epoch: [31] [ 540/2138] eta: 1:20:23 lr: 1.272879899826194e-05 loss: 0.0193 (0.0205) time: 3.0511 data: 0.0024 max mem: 19788 +Epoch: [31] [ 550/2138] eta: 1:19:54 lr: 1.2722673002085194e-05 loss: 0.0189 (0.0205) time: 3.0759 data: 0.0027 max mem: 19788 +Epoch: [31] [ 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mem: 19788 +Epoch: [31] [ 640/2138] eta: 1:15:22 lr: 1.2667524264093026e-05 loss: 0.0203 (0.0207) time: 2.9607 data: 0.0027 max mem: 19788 +Epoch: [31] [ 650/2138] eta: 1:14:50 lr: 1.2661394981606061e-05 loss: 0.0214 (0.0207) time: 2.9597 data: 0.0024 max mem: 19788 +Epoch: [31] [ 660/2138] eta: 1:14:20 lr: 1.2655265369419378e-05 loss: 0.0190 (0.0208) time: 2.9746 data: 0.0021 max mem: 19788 +Epoch: [31] [ 670/2138] eta: 1:13:50 lr: 1.264913542733777e-05 loss: 0.0190 (0.0208) time: 3.0228 data: 0.0023 max mem: 19788 +Epoch: [31] [ 680/2138] eta: 1:13:20 lr: 1.264300515516584e-05 loss: 0.0185 (0.0207) time: 3.0220 data: 0.0024 max mem: 19788 +Epoch: [31] [ 690/2138] eta: 1:12:50 lr: 1.2636874552707953e-05 loss: 0.0204 (0.0207) time: 3.0170 data: 0.0024 max mem: 19788 +Epoch: [31] [ 700/2138] eta: 1:12:18 lr: 1.2630743619768261e-05 loss: 0.0195 (0.0207) time: 2.9940 data: 0.0025 max mem: 19788 +Epoch: [31] [ 710/2138] eta: 1:11:47 lr: 1.2624612356150689e-05 loss: 0.0183 (0.0207) time: 2.9542 data: 0.0023 max mem: 19788 +Epoch: [31] [ 720/2138] eta: 1:11:16 lr: 1.2618480761658934e-05 loss: 0.0170 (0.0207) time: 2.9799 data: 0.0025 max mem: 19788 +Epoch: [31] [ 730/2138] eta: 1:10:45 lr: 1.261234883609649e-05 loss: 0.0167 (0.0206) time: 2.9780 data: 0.0029 max mem: 19788 +Epoch: [31] [ 740/2138] eta: 1:10:16 lr: 1.2606216579266605e-05 loss: 0.0196 (0.0207) time: 3.0093 data: 0.0027 max mem: 19788 +Epoch: [31] [ 750/2138] eta: 1:09:44 lr: 1.2600083990972327e-05 loss: 0.0219 (0.0207) time: 3.0075 data: 0.0024 max mem: 19788 +Epoch: [31] [ 760/2138] eta: 1:09:16 lr: 1.2593951071016453e-05 loss: 0.0212 (0.0207) time: 3.0213 data: 0.0024 max mem: 19788 +Epoch: [31] [ 770/2138] eta: 1:08:46 lr: 1.2587817819201584e-05 loss: 0.0191 (0.0207) time: 3.0639 data: 0.0024 max mem: 19788 +Epoch: [31] [ 780/2138] eta: 1:08:16 lr: 1.258168423533007e-05 loss: 0.0189 (0.0207) time: 3.0440 data: 0.0023 max mem: 19788 +Epoch: [31] [ 790/2138] eta: 1:07:45 lr: 1.2575550319204063e-05 loss: 0.0179 (0.0206) time: 3.0087 data: 0.0022 max mem: 19788 +Epoch: [31] [ 800/2138] eta: 1:07:14 lr: 1.2569416070625464e-05 loss: 0.0190 (0.0206) time: 2.9673 data: 0.0022 max mem: 19788 +Epoch: [31] [ 810/2138] eta: 1:06:46 lr: 1.2563281489395972e-05 loss: 0.0202 (0.0206) time: 3.0434 data: 0.0022 max mem: 19788 +Epoch: [31] [ 820/2138] eta: 1:06:16 lr: 1.255714657531704e-05 loss: 0.0195 (0.0206) time: 3.0876 data: 0.0024 max mem: 19788 +Epoch: [31] [ 830/2138] eta: 1:05:46 lr: 1.255101132818991e-05 loss: 0.0194 (0.0206) time: 3.0351 data: 0.0024 max mem: 19788 +Epoch: [31] [ 840/2138] eta: 1:05:18 lr: 1.2544875747815583e-05 loss: 0.0192 (0.0206) time: 3.0877 data: 0.0024 max mem: 19788 +Epoch: [31] [ 850/2138] eta: 1:04:49 lr: 1.2538739833994851e-05 loss: 0.0192 (0.0206) time: 3.1249 data: 0.0023 max mem: 19788 +Epoch: [31] [ 860/2138] eta: 1:04:20 lr: 1.2532603586528251e-05 loss: 0.0187 (0.0206) time: 3.0790 data: 0.0024 max mem: 19788 +Epoch: [31] [ 870/2138] eta: 1:03:50 lr: 1.2526467005216133e-05 loss: 0.0183 (0.0206) time: 3.0750 data: 0.0025 max mem: 19788 +Epoch: [31] [ 880/2138] eta: 1:03:21 lr: 1.252033008985857e-05 loss: 0.0180 (0.0206) time: 3.0681 data: 0.0023 max mem: 19788 +Epoch: [31] [ 890/2138] eta: 1:02:52 lr: 1.2514192840255453e-05 loss: 0.0181 (0.0206) time: 3.0921 data: 0.0023 max mem: 19788 +Epoch: [31] [ 900/2138] eta: 1:02:21 lr: 1.2508055256206406e-05 loss: 0.0194 (0.0206) time: 3.0425 data: 0.0023 max mem: 19788 +Epoch: [31] [ 910/2138] eta: 1:01:50 lr: 1.2501917337510848e-05 loss: 0.0185 (0.0205) time: 2.9620 data: 0.0022 max mem: 19788 +Epoch: [31] [ 920/2138] eta: 1:01:19 lr: 1.2495779083967957e-05 loss: 0.0185 (0.0205) time: 2.9651 data: 0.0025 max mem: 19788 +Epoch: [31] [ 930/2138] eta: 1:00:48 lr: 1.2489640495376692e-05 loss: 0.0209 (0.0205) time: 2.9602 data: 0.0028 max mem: 19788 +Epoch: [31] [ 940/2138] eta: 1:00:17 lr: 1.2483501571535757e-05 loss: 0.0216 (0.0205) time: 2.9605 data: 0.0027 max mem: 19788 +Epoch: [31] [ 950/2138] eta: 0:59:47 lr: 1.2477362312243657e-05 loss: 0.0203 (0.0205) time: 3.0073 data: 0.0027 max mem: 19788 +Epoch: [31] [ 960/2138] eta: 0:59:18 lr: 1.2471222717298639e-05 loss: 0.0209 (0.0206) time: 3.0719 data: 0.0028 max mem: 19788 +Epoch: [31] [ 970/2138] eta: 0:58:49 lr: 1.246508278649874e-05 loss: 0.0212 (0.0206) time: 3.1006 data: 0.0028 max mem: 19788 +Epoch: [31] [ 980/2138] eta: 0:58:20 lr: 1.245894251964174e-05 loss: 0.0172 (0.0206) time: 3.1255 data: 0.0026 max mem: 19788 +Epoch: [31] [ 990/2138] eta: 0:57:49 lr: 1.2452801916525217e-05 loss: 0.0170 (0.0205) time: 3.0663 data: 0.0024 max mem: 19788 +Epoch: [31] [1000/2138] eta: 0:57:19 lr: 1.2446660976946484e-05 loss: 0.0174 (0.0205) time: 2.9962 data: 0.0023 max mem: 19788 +Epoch: [31] [1010/2138] eta: 0:56:48 lr: 1.2440519700702648e-05 loss: 0.0180 (0.0205) time: 2.9881 data: 0.0023 max mem: 19788 +Epoch: [31] [1020/2138] eta: 0:56:17 lr: 1.2434378087590566e-05 loss: 0.0180 (0.0205) time: 2.9615 data: 0.0027 max mem: 19788 +Epoch: [31] [1030/2138] eta: 0:55:47 lr: 1.242823613740686e-05 loss: 0.0178 (0.0205) time: 2.9850 data: 0.0030 max mem: 19788 +Epoch: [31] [1040/2138] eta: 0:55:17 lr: 1.2422093849947933e-05 loss: 0.0210 (0.0205) time: 3.0288 data: 0.0025 max mem: 19788 +Epoch: [31] [1050/2138] eta: 0:54:48 lr: 1.241595122500993e-05 loss: 0.0216 (0.0205) time: 3.0979 data: 0.0025 max mem: 19788 +Epoch: [31] [1060/2138] eta: 0:54:18 lr: 1.240980826238879e-05 loss: 0.0208 (0.0205) time: 3.0956 data: 0.0027 max mem: 19788 +Epoch: [31] [1070/2138] eta: 0:53:47 lr: 1.2403664961880186e-05 loss: 0.0200 (0.0205) time: 3.0071 data: 0.0024 max mem: 19788 +Epoch: [31] [1080/2138] eta: 0:53:19 lr: 1.2397521323279576e-05 loss: 0.0187 (0.0205) time: 3.1010 data: 0.0024 max mem: 19788 +Epoch: [31] [1090/2138] eta: 0:52:48 lr: 1.2391377346382169e-05 loss: 0.0193 (0.0205) time: 3.1107 data: 0.0024 max mem: 19788 +Epoch: [31] [1100/2138] eta: 0:52:18 lr: 1.238523303098295e-05 loss: 0.0195 (0.0205) time: 3.0154 data: 0.0023 max mem: 19788 +Epoch: [31] [1110/2138] eta: 0:51:48 lr: 1.2379088376876651e-05 loss: 0.0196 (0.0206) time: 3.0381 data: 0.0024 max mem: 19788 +Epoch: [31] [1120/2138] eta: 0:51:18 lr: 1.237294338385778e-05 loss: 0.0200 (0.0206) time: 3.0370 data: 0.0028 max mem: 19788 +Epoch: [31] [1130/2138] eta: 0:50:49 lr: 1.2366798051720595e-05 loss: 0.0190 (0.0205) time: 3.1190 data: 0.0028 max mem: 19788 +Epoch: [31] [1140/2138] eta: 0:50:20 lr: 1.236065238025913e-05 loss: 0.0190 (0.0205) time: 3.1818 data: 0.0027 max mem: 19788 +Epoch: [31] [1150/2138] eta: 0:49:51 lr: 1.235450636926716e-05 loss: 0.0172 (0.0205) time: 3.1723 data: 0.0026 max mem: 19788 +Epoch: [31] [1160/2138] eta: 0:49:22 lr: 1.2348360018538245e-05 loss: 0.0170 (0.0205) time: 3.1746 data: 0.0025 max mem: 19788 +Epoch: [31] [1170/2138] eta: 0:48:53 lr: 1.2342213327865682e-05 loss: 0.0189 (0.0205) time: 3.1340 data: 0.0027 max mem: 19788 +Epoch: [31] [1180/2138] eta: 0:48:22 lr: 1.2336066297042544e-05 loss: 0.0190 (0.0205) time: 3.0747 data: 0.0025 max mem: 19788 +Epoch: [31] [1190/2138] eta: 0:47:51 lr: 1.2329918925861653e-05 loss: 0.0197 (0.0205) time: 2.9971 data: 0.0022 max mem: 19788 +Epoch: [31] [1200/2138] eta: 0:47:21 lr: 1.2323771214115602e-05 loss: 0.0197 (0.0205) time: 2.9751 data: 0.0024 max mem: 19788 +Epoch: [31] [1210/2138] eta: 0:46:50 lr: 1.2317623161596724e-05 loss: 0.0198 (0.0205) time: 2.9951 data: 0.0024 max mem: 19788 +Epoch: [31] [1220/2138] eta: 0:46:20 lr: 1.2311474768097133e-05 loss: 0.0195 (0.0205) time: 3.0278 data: 0.0025 max mem: 19788 +Epoch: [31] [1230/2138] eta: 0:45:49 lr: 1.2305326033408677e-05 loss: 0.0190 (0.0205) time: 3.0075 data: 0.0029 max mem: 19788 +Epoch: [31] [1240/2138] eta: 0:45:19 lr: 1.2299176957322988e-05 loss: 0.0190 (0.0205) time: 2.9602 data: 0.0029 max mem: 19788 +Epoch: [31] [1250/2138] eta: 0:44:48 lr: 1.2293027539631422e-05 loss: 0.0195 (0.0205) time: 2.9791 data: 0.0028 max mem: 19788 +Epoch: [31] [1260/2138] eta: 0:44:17 lr: 1.2286877780125128e-05 loss: 0.0186 (0.0205) time: 2.9763 data: 0.0028 max mem: 19788 +Epoch: [31] [1270/2138] eta: 0:43:48 lr: 1.2280727678594977e-05 loss: 0.0186 (0.0205) time: 3.0270 data: 0.0026 max mem: 19788 +Epoch: [31] [1280/2138] eta: 0:43:17 lr: 1.2274577234831622e-05 loss: 0.0200 (0.0204) time: 3.0214 data: 0.0026 max mem: 19788 +Epoch: [31] [1290/2138] eta: 0:42:46 lr: 1.2268426448625453e-05 loss: 0.0204 (0.0205) time: 2.9663 data: 0.0026 max mem: 19788 +Epoch: [31] [1300/2138] eta: 0:42:16 lr: 1.2262275319766633e-05 loss: 0.0204 (0.0204) time: 3.0296 data: 0.0025 max mem: 19788 +Epoch: [31] [1310/2138] eta: 0:41:47 lr: 1.2256123848045054e-05 loss: 0.0192 (0.0204) time: 3.1156 data: 0.0026 max mem: 19788 +Epoch: [31] [1320/2138] eta: 0:41:16 lr: 1.224997203325039e-05 loss: 0.0200 (0.0204) time: 3.0583 data: 0.0026 max mem: 19788 +Epoch: [31] [1330/2138] eta: 0:40:45 lr: 1.2243819875172047e-05 loss: 0.0193 (0.0204) time: 2.9577 data: 0.0026 max mem: 19788 +Epoch: [31] [1340/2138] eta: 0:40:15 lr: 1.2237667373599194e-05 loss: 0.0208 (0.0204) time: 3.0053 data: 0.0028 max mem: 19788 +Epoch: [31] [1350/2138] eta: 0:39:45 lr: 1.2231514528320753e-05 loss: 0.0237 (0.0205) time: 3.0160 data: 0.0028 max mem: 19788 +Epoch: [31] [1360/2138] eta: 0:39:14 lr: 1.222536133912539e-05 loss: 0.0206 (0.0205) time: 2.9686 data: 0.0028 max mem: 19788 +Epoch: [31] [1370/2138] eta: 0:38:43 lr: 1.2219207805801539e-05 loss: 0.0206 (0.0205) time: 2.9583 data: 0.0028 max mem: 19788 +Epoch: [31] [1380/2138] eta: 0:38:13 lr: 1.2213053928137363e-05 loss: 0.0213 (0.0205) time: 2.9545 data: 0.0026 max mem: 19788 +Epoch: [31] [1390/2138] eta: 0:37:43 lr: 1.2206899705920803e-05 loss: 0.0193 (0.0205) time: 3.0801 data: 0.0026 max mem: 19788 +Epoch: [31] [1400/2138] eta: 0:37:13 lr: 1.2200745138939519e-05 loss: 0.0186 (0.0205) time: 3.1400 data: 0.0026 max mem: 19788 +Epoch: [31] [1410/2138] eta: 0:36:43 lr: 1.2194590226980953e-05 loss: 0.0186 (0.0205) time: 3.0397 data: 0.0027 max mem: 19788 +Epoch: [31] [1420/2138] eta: 0:36:13 lr: 1.2188434969832272e-05 loss: 0.0194 (0.0205) time: 3.0579 data: 0.0027 max mem: 19788 +Epoch: [31] [1430/2138] eta: 0:35:43 lr: 1.2182279367280407e-05 loss: 0.0202 (0.0205) time: 3.0502 data: 0.0024 max mem: 19788 +Epoch: [31] [1440/2138] eta: 0:35:13 lr: 1.2176123419112024e-05 loss: 0.0212 (0.0205) time: 3.0173 data: 0.0023 max mem: 19788 +Epoch: [31] [1450/2138] eta: 0:34:43 lr: 1.2169967125113558e-05 loss: 0.0220 (0.0205) time: 3.0611 data: 0.0027 max mem: 19788 +Epoch: [31] [1460/2138] eta: 0:34:12 lr: 1.2163810485071169e-05 loss: 0.0199 (0.0205) time: 3.0407 data: 0.0029 max mem: 19788 +Epoch: [31] [1470/2138] eta: 0:33:42 lr: 1.2157653498770782e-05 loss: 0.0176 (0.0205) time: 3.0081 data: 0.0028 max mem: 19788 +Epoch: [31] [1480/2138] eta: 0:33:12 lr: 1.2151496165998056e-05 loss: 0.0162 (0.0205) time: 3.0678 data: 0.0027 max mem: 19788 +Epoch: [31] [1490/2138] eta: 0:32:42 lr: 1.2145338486538411e-05 loss: 0.0171 (0.0205) time: 3.0804 data: 0.0027 max mem: 19788 +Epoch: [31] [1500/2138] eta: 0:32:11 lr: 1.2139180460176994e-05 loss: 0.0200 (0.0205) time: 2.9982 data: 0.0026 max mem: 19788 +Epoch: [31] [1510/2138] eta: 0:31:41 lr: 1.213302208669872e-05 loss: 0.0196 (0.0206) time: 2.9649 data: 0.0027 max mem: 19788 +Epoch: [31] [1520/2138] eta: 0:31:10 lr: 1.2126863365888226e-05 loss: 0.0200 (0.0206) time: 2.9627 data: 0.0025 max mem: 19788 +Epoch: [31] [1530/2138] eta: 0:30:40 lr: 1.2120704297529918e-05 loss: 0.0200 (0.0206) time: 2.9654 data: 0.0023 max mem: 19788 +Epoch: [31] [1540/2138] eta: 0:30:10 lr: 1.2114544881407922e-05 loss: 0.0199 (0.0206) time: 3.0512 data: 0.0024 max mem: 19788 +Epoch: [31] [1550/2138] eta: 0:29:39 lr: 1.210838511730613e-05 loss: 0.0181 (0.0206) time: 3.0518 data: 0.0026 max mem: 19788 +Epoch: [31] [1560/2138] eta: 0:29:09 lr: 1.2102225005008158e-05 loss: 0.0203 (0.0206) time: 2.9741 data: 0.0028 max mem: 19788 +Epoch: [31] [1570/2138] eta: 0:28:39 lr: 1.2096064544297384e-05 loss: 0.0204 (0.0206) time: 3.0310 data: 0.0027 max mem: 19788 +Epoch: [31] [1580/2138] eta: 0:28:09 lr: 1.2089903734956906e-05 loss: 0.0203 (0.0206) time: 3.0770 data: 0.0027 max mem: 19788 +Epoch: [31] [1590/2138] eta: 0:27:39 lr: 1.2083742576769592e-05 loss: 0.0199 (0.0206) time: 3.1068 data: 0.0026 max mem: 19788 +Epoch: [31] [1600/2138] eta: 0:27:08 lr: 1.207758106951802e-05 loss: 0.0225 (0.0206) time: 3.0782 data: 0.0025 max mem: 19788 +Epoch: [31] [1610/2138] eta: 0:26:38 lr: 1.2071419212984544e-05 loss: 0.0235 (0.0206) time: 2.9866 data: 0.0025 max mem: 19788 +Epoch: [31] [1620/2138] eta: 0:26:08 lr: 1.2065257006951229e-05 loss: 0.0173 (0.0206) time: 3.0166 data: 0.0024 max mem: 19788 +Epoch: [31] [1630/2138] eta: 0:25:37 lr: 1.2059094451199887e-05 loss: 0.0173 (0.0206) time: 3.0261 data: 0.0025 max mem: 19788 +Epoch: [31] [1640/2138] eta: 0:25:07 lr: 1.2052931545512087e-05 loss: 0.0202 (0.0206) time: 2.9705 data: 0.0025 max mem: 19788 +Epoch: [31] [1650/2138] eta: 0:24:36 lr: 1.2046768289669115e-05 loss: 0.0203 (0.0206) time: 2.9654 data: 0.0026 max mem: 19788 +Epoch: [31] [1660/2138] eta: 0:24:06 lr: 1.2040604683452014e-05 loss: 0.0195 (0.0206) time: 2.9934 data: 0.0029 max mem: 19788 +Epoch: [31] [1670/2138] eta: 0:23:36 lr: 1.2034440726641548e-05 loss: 0.0190 (0.0206) time: 3.0899 data: 0.0027 max mem: 19788 +Epoch: [31] [1680/2138] eta: 0:23:06 lr: 1.202827641901824e-05 loss: 0.0180 (0.0206) time: 3.1418 data: 0.0027 max mem: 19788 +Epoch: [31] [1690/2138] eta: 0:22:36 lr: 1.2022111760362325e-05 loss: 0.0186 (0.0205) time: 3.1146 data: 0.0027 max mem: 19788 +Epoch: [31] [1700/2138] eta: 0:22:06 lr: 1.20159467504538e-05 loss: 0.0186 (0.0205) time: 3.0481 data: 0.0023 max mem: 19788 +Epoch: [31] [1710/2138] eta: 0:21:36 lr: 1.200978138907238e-05 loss: 0.0188 (0.0205) time: 3.1305 data: 0.0024 max mem: 19788 +Epoch: [31] [1720/2138] eta: 0:21:06 lr: 1.2003615675997533e-05 loss: 0.0207 (0.0205) time: 3.1670 data: 0.0028 max mem: 19788 +Epoch: [31] [1730/2138] eta: 0:20:36 lr: 1.1997449611008438e-05 loss: 0.0202 (0.0205) time: 3.0665 data: 0.0030 max mem: 19788 +Epoch: [31] [1740/2138] eta: 0:20:05 lr: 1.1991283193884043e-05 loss: 0.0179 (0.0205) time: 3.0471 data: 0.0028 max mem: 19788 +Epoch: [31] [1750/2138] eta: 0:19:35 lr: 1.1985116424402996e-05 loss: 0.0186 (0.0205) time: 3.0198 data: 0.0024 max mem: 19788 +Epoch: [31] [1760/2138] eta: 0:19:05 lr: 1.1978949302343705e-05 loss: 0.0181 (0.0205) time: 3.0113 data: 0.0025 max mem: 19788 +Epoch: [31] [1770/2138] eta: 0:18:35 lr: 1.1972781827484294e-05 loss: 0.0185 (0.0205) time: 3.0466 data: 0.0025 max mem: 19788 +Epoch: [31] [1780/2138] eta: 0:18:05 lr: 1.1966613999602641e-05 loss: 0.0183 (0.0205) time: 3.1517 data: 0.0025 max mem: 19788 +Epoch: [31] [1790/2138] eta: 0:17:34 lr: 1.1960445818476329e-05 loss: 0.0171 (0.0205) time: 3.0950 data: 0.0026 max mem: 19788 +Epoch: [31] [1800/2138] eta: 0:17:04 lr: 1.1954277283882703e-05 loss: 0.0226 (0.0205) time: 2.9676 data: 0.0029 max mem: 19788 +Epoch: [31] [1810/2138] eta: 0:16:33 lr: 1.1948108395598813e-05 loss: 0.0204 (0.0205) time: 2.9874 data: 0.0029 max mem: 19788 +Epoch: [31] [1820/2138] eta: 0:16:03 lr: 1.1941939153401467e-05 loss: 0.0181 (0.0205) time: 2.9946 data: 0.0026 max mem: 19788 +Epoch: [31] [1830/2138] eta: 0:15:33 lr: 1.1935769557067173e-05 loss: 0.0178 (0.0205) time: 2.9883 data: 0.0028 max mem: 19788 +Epoch: [31] [1840/2138] eta: 0:15:02 lr: 1.19295996063722e-05 loss: 0.0202 (0.0205) time: 3.0295 data: 0.0026 max mem: 19788 +Epoch: [31] [1850/2138] eta: 0:14:32 lr: 1.1923429301092524e-05 loss: 0.0211 (0.0205) time: 3.0753 data: 0.0021 max mem: 19788 +Epoch: [31] [1860/2138] eta: 0:14:02 lr: 1.191725864100387e-05 loss: 0.0193 (0.0205) time: 3.1552 data: 0.0022 max mem: 19788 +Epoch: [31] [1870/2138] eta: 0:13:32 lr: 1.191108762588167e-05 loss: 0.0197 (0.0205) time: 3.1133 data: 0.0023 max mem: 19788 +Epoch: [31] [1880/2138] eta: 0:13:01 lr: 1.1904916255501108e-05 loss: 0.0176 (0.0205) time: 2.9881 data: 0.0022 max mem: 19788 +Epoch: [31] [1890/2138] eta: 0:12:31 lr: 1.1898744529637071e-05 loss: 0.0161 (0.0205) time: 2.9588 data: 0.0026 max mem: 19788 +Epoch: [31] [1900/2138] eta: 0:12:01 lr: 1.1892572448064202e-05 loss: 0.0187 (0.0205) time: 3.0331 data: 0.0028 max mem: 19788 +Epoch: [31] [1910/2138] eta: 0:11:31 lr: 1.1886400010556843e-05 loss: 0.0194 (0.0205) time: 3.0754 data: 0.0027 max mem: 19788 +Epoch: [31] [1920/2138] eta: 0:11:00 lr: 1.1880227216889085e-05 loss: 0.0184 (0.0205) time: 3.0331 data: 0.0026 max mem: 19788 +Epoch: [31] [1930/2138] eta: 0:10:30 lr: 1.1874054066834733e-05 loss: 0.0183 (0.0205) time: 3.0477 data: 0.0025 max mem: 19788 +Epoch: [31] [1940/2138] eta: 0:10:00 lr: 1.1867880560167314e-05 loss: 0.0186 (0.0205) time: 3.0223 data: 0.0028 max mem: 19788 +Epoch: [31] [1950/2138] eta: 0:09:29 lr: 1.1861706696660094e-05 loss: 0.0191 (0.0205) time: 3.0220 data: 0.0031 max mem: 19788 +Epoch: [31] [1960/2138] eta: 0:08:59 lr: 1.185553247608605e-05 loss: 0.0191 (0.0205) time: 3.0063 data: 0.0030 max mem: 19788 +Epoch: [31] [1970/2138] eta: 0:08:29 lr: 1.1849357898217896e-05 loss: 0.0172 (0.0204) time: 3.0037 data: 0.0028 max mem: 19788 +Epoch: [31] [1980/2138] eta: 0:07:58 lr: 1.1843182962828053e-05 loss: 0.0180 (0.0205) time: 3.0634 data: 0.0026 max mem: 19788 +Epoch: [31] [1990/2138] eta: 0:07:28 lr: 1.1837007669688688e-05 loss: 0.0189 (0.0205) time: 3.0216 data: 0.0022 max mem: 19788 +Epoch: [31] [2000/2138] eta: 0:06:58 lr: 1.1830832018571664e-05 loss: 0.0186 (0.0205) time: 2.9858 data: 0.0024 max mem: 19788 +Epoch: [31] [2010/2138] eta: 0:06:27 lr: 1.1824656009248592e-05 loss: 0.0203 (0.0205) time: 3.0523 data: 0.0026 max mem: 19788 +Epoch: [31] [2020/2138] eta: 0:05:57 lr: 1.1818479641490778e-05 loss: 0.0207 (0.0205) time: 3.2201 data: 0.0025 max mem: 19788 +Epoch: [31] [2030/2138] eta: 0:05:27 lr: 1.1812302915069279e-05 loss: 0.0210 (0.0205) time: 3.1798 data: 0.0029 max mem: 19788 +Epoch: [31] [2040/2138] eta: 0:04:57 lr: 1.1806125829754843e-05 loss: 0.0204 (0.0205) time: 3.0525 data: 0.0032 max mem: 19788 +Epoch: [31] [2050/2138] eta: 0:04:26 lr: 1.1799948385317963e-05 loss: 0.0183 (0.0205) time: 3.0660 data: 0.0027 max mem: 19788 +Epoch: [31] [2060/2138] eta: 0:03:56 lr: 1.1793770581528832e-05 loss: 0.0183 (0.0205) time: 3.0531 data: 0.0022 max mem: 19788 +Epoch: [31] [2070/2138] eta: 0:03:26 lr: 1.178759241815738e-05 loss: 0.0188 (0.0205) time: 3.0569 data: 0.0022 max mem: 19788 +Epoch: [31] [2080/2138] eta: 0:02:55 lr: 1.1781413894973236e-05 loss: 0.0190 (0.0205) time: 3.0192 data: 0.0024 max mem: 19788 +Epoch: [31] [2090/2138] eta: 0:02:25 lr: 1.1775235011745766e-05 loss: 0.0202 (0.0205) time: 3.0274 data: 0.0023 max mem: 19788 +Epoch: [31] [2100/2138] eta: 0:01:55 lr: 1.1769055768244039e-05 loss: 0.0186 (0.0205) time: 3.0141 data: 0.0023 max mem: 19788 +Epoch: [31] [2110/2138] eta: 0:01:24 lr: 1.1762876164236856e-05 loss: 0.0195 (0.0205) time: 2.9780 data: 0.0025 max mem: 19788 +Epoch: [31] [2120/2138] eta: 0:00:54 lr: 1.1756696199492713e-05 loss: 0.0226 (0.0205) time: 3.0218 data: 0.0023 max mem: 19788 +Epoch: [31] [2130/2138] eta: 0:00:24 lr: 1.1750515873779849e-05 loss: 0.0228 (0.0205) time: 3.0814 data: 0.0022 max mem: 19788 +Epoch: [31] Total time: 1:48:05 +Test: [ 0/21770] eta: 15:31:37 time: 2.5676 data: 2.3568 max mem: 19788 +Test: [ 100/21770] eta: 0:28:00 time: 0.0523 data: 0.0018 max mem: 19788 +Test: [ 200/21770] eta: 0:22:42 time: 0.0530 data: 0.0018 max mem: 19788 +Test: [ 300/21770] eta: 0:21:18 time: 0.0536 data: 0.0016 max mem: 19788 +Test: [ 400/21770] eta: 0:20:10 time: 0.0485 data: 0.0016 max mem: 19788 +Test: [ 500/21770] eta: 0:19:47 time: 0.0478 data: 0.0015 max mem: 19788 +Test: [ 600/21770] eta: 0:19:02 time: 0.0437 data: 0.0015 max mem: 19788 +Test: [ 700/21770] eta: 0:18:36 time: 0.0454 data: 0.0017 max mem: 19788 +Test: [ 800/21770] eta: 0:18:08 time: 0.0431 data: 0.0014 max mem: 19788 +Test: [ 900/21770] eta: 0:17:53 time: 0.0530 data: 0.0018 max mem: 19788 +Test: [ 1000/21770] eta: 0:17:41 time: 0.0487 data: 0.0017 max mem: 19788 +Test: [ 1100/21770] eta: 0:17:31 time: 0.0483 data: 0.0017 max mem: 19788 +Test: [ 1200/21770] eta: 0:17:19 time: 0.0496 data: 0.0018 max mem: 19788 +Test: [ 1300/21770] eta: 0:17:09 time: 0.0503 data: 0.0015 max mem: 19788 +Test: [ 1400/21770] eta: 0:17:06 time: 0.0535 data: 0.0018 max mem: 19788 +Test: [ 1500/21770] eta: 0:17:02 time: 0.0481 data: 0.0017 max mem: 19788 +Test: [ 1600/21770] eta: 0:16:55 time: 0.0445 data: 0.0016 max mem: 19788 +Test: [ 1700/21770] eta: 0:16:50 time: 0.0532 data: 0.0017 max mem: 19788 +Test: [ 1800/21770] eta: 0:16:41 time: 0.0442 data: 0.0015 max mem: 19788 +Test: [ 1900/21770] eta: 0:16:33 time: 0.0476 data: 0.0018 max mem: 19788 +Test: [ 2000/21770] eta: 0:16:23 time: 0.0431 data: 0.0015 max mem: 19788 +Test: [ 2100/21770] eta: 0:16:16 time: 0.0435 data: 0.0015 max mem: 19788 +Test: [ 2200/21770] eta: 0:16:12 time: 0.0511 data: 0.0018 max mem: 19788 +Test: [ 2300/21770] eta: 0:16:05 time: 0.0505 data: 0.0016 max mem: 19788 +Test: [ 2400/21770] eta: 0:16:01 time: 0.0516 data: 0.0015 max mem: 19788 +Test: [ 2500/21770] eta: 0:15:53 time: 0.0443 data: 0.0014 max mem: 19788 +Test: [ 2600/21770] eta: 0:15:45 time: 0.0505 data: 0.0017 max mem: 19788 +Test: [ 2700/21770] eta: 0:15:41 time: 0.0488 data: 0.0016 max mem: 19788 +Test: [ 2800/21770] eta: 0:15:36 time: 0.0529 data: 0.0018 max mem: 19788 +Test: [ 2900/21770] eta: 0:15:29 time: 0.0492 data: 0.0016 max mem: 19788 +Test: [ 3000/21770] eta: 0:15:21 time: 0.0462 data: 0.0015 max mem: 19788 +Test: [ 3100/21770] eta: 0:15:16 time: 0.0432 data: 0.0013 max mem: 19788 +Test: [ 3200/21770] eta: 0:15:09 time: 0.0520 data: 0.0016 max mem: 19788 +Test: [ 3300/21770] eta: 0:15:05 time: 0.0528 data: 0.0018 max mem: 19788 +Test: [ 3400/21770] eta: 0:15:00 time: 0.0530 data: 0.0017 max mem: 19788 +Test: [ 3500/21770] eta: 0:14:53 time: 0.0448 data: 0.0015 max mem: 19788 +Test: [ 3600/21770] eta: 0:14:47 time: 0.0479 data: 0.0018 max mem: 19788 +Test: [ 3700/21770] eta: 0:14:42 time: 0.0535 data: 0.0016 max mem: 19788 +Test: [ 3800/21770] eta: 0:14:36 time: 0.0496 data: 0.0015 max mem: 19788 +Test: [ 3900/21770] eta: 0:14:31 time: 0.0459 data: 0.0016 max mem: 19788 +Test: [ 4000/21770] eta: 0:14:26 time: 0.0532 data: 0.0017 max mem: 19788 +Test: [ 4100/21770] eta: 0:14:21 time: 0.0532 data: 0.0019 max mem: 19788 +Test: [ 4200/21770] eta: 0:14:16 time: 0.0505 data: 0.0018 max mem: 19788 +Test: [ 4300/21770] eta: 0:14:10 time: 0.0496 data: 0.0016 max mem: 19788 +Test: [ 4400/21770] eta: 0:14:05 time: 0.0507 data: 0.0017 max mem: 19788 +Test: [ 4500/21770] eta: 0:14:02 time: 0.0486 data: 0.0019 max mem: 19788 +Test: [ 4600/21770] eta: 0:13:58 time: 0.0480 data: 0.0018 max mem: 19788 +Test: [ 4700/21770] eta: 0:13:53 time: 0.0537 data: 0.0019 max mem: 19788 +Test: [ 4800/21770] eta: 0:13:48 time: 0.0436 data: 0.0014 max mem: 19788 +Test: [ 4900/21770] eta: 0:13:43 time: 0.0498 data: 0.0017 max mem: 19788 +Test: [ 5000/21770] eta: 0:13:37 time: 0.0470 data: 0.0017 max mem: 19788 +Test: [ 5100/21770] eta: 0:13:32 time: 0.0523 data: 0.0018 max mem: 19788 +Test: [ 5200/21770] eta: 0:13:26 time: 0.0477 data: 0.0015 max mem: 19788 +Test: [ 5300/21770] eta: 0:13:21 time: 0.0501 data: 0.0016 max mem: 19788 +Test: [ 5400/21770] eta: 0:13:16 time: 0.0473 data: 0.0017 max mem: 19788 +Test: [ 5500/21770] eta: 0:13:12 time: 0.0516 data: 0.0018 max mem: 19788 +Test: [ 5600/21770] eta: 0:13:06 time: 0.0437 data: 0.0015 max mem: 19788 +Test: [ 5700/21770] eta: 0:13:01 time: 0.0524 data: 0.0018 max mem: 19788 +Test: [ 5800/21770] eta: 0:12:56 time: 0.0522 data: 0.0015 max mem: 19788 +Test: [ 5900/21770] eta: 0:12:52 time: 0.0523 data: 0.0017 max mem: 19788 +Test: [ 6000/21770] eta: 0:12:47 time: 0.0522 data: 0.0018 max mem: 19788 +Test: [ 6100/21770] eta: 0:12:43 time: 0.0485 data: 0.0015 max mem: 19788 +Test: [ 6200/21770] eta: 0:12:38 time: 0.0446 data: 0.0014 max mem: 19788 +Test: [ 6300/21770] eta: 0:12:33 time: 0.0446 data: 0.0013 max mem: 19788 +Test: [ 6400/21770] eta: 0:12:28 time: 0.0502 data: 0.0017 max mem: 19788 +Test: [ 6500/21770] eta: 0:12:23 time: 0.0437 data: 0.0016 max mem: 19788 +Test: [ 6600/21770] eta: 0:12:17 time: 0.0447 data: 0.0015 max mem: 19788 +Test: [ 6700/21770] eta: 0:12:11 time: 0.0446 data: 0.0013 max mem: 19788 +Test: [ 6800/21770] eta: 0:12:06 time: 0.0526 data: 0.0018 max mem: 19788 +Test: [ 6900/21770] eta: 0:12:01 time: 0.0474 data: 0.0015 max mem: 19788 +Test: [ 7000/21770] eta: 0:11:56 time: 0.0462 data: 0.0015 max mem: 19788 +Test: [ 7100/21770] eta: 0:11:51 time: 0.0458 data: 0.0015 max mem: 19788 +Test: [ 7200/21770] eta: 0:11:46 time: 0.0530 data: 0.0018 max mem: 19788 +Test: [ 7300/21770] eta: 0:11:42 time: 0.0432 data: 0.0016 max mem: 19788 +Test: [ 7400/21770] eta: 0:11:36 time: 0.0432 data: 0.0015 max mem: 19788 +Test: [ 7500/21770] eta: 0:11:31 time: 0.0526 data: 0.0018 max mem: 19788 +Test: [ 7600/21770] eta: 0:11:26 time: 0.0451 data: 0.0015 max mem: 19788 +Test: [ 7700/21770] eta: 0:11:20 time: 0.0438 data: 0.0014 max mem: 19788 +Test: [ 7800/21770] eta: 0:11:16 time: 0.0522 data: 0.0017 max mem: 19788 +Test: [ 7900/21770] eta: 0:11:12 time: 0.0523 data: 0.0018 max mem: 19788 +Test: [ 8000/21770] eta: 0:11:07 time: 0.0468 data: 0.0017 max mem: 19788 +Test: [ 8100/21770] eta: 0:11:01 time: 0.0434 data: 0.0014 max mem: 19788 +Test: [ 8200/21770] eta: 0:10:56 time: 0.0529 data: 0.0018 max mem: 19788 +Test: [ 8300/21770] eta: 0:10:52 time: 0.0530 data: 0.0019 max mem: 19788 +Test: [ 8400/21770] eta: 0:10:47 time: 0.0433 data: 0.0015 max mem: 19788 +Test: [ 8500/21770] eta: 0:10:41 time: 0.0441 data: 0.0015 max mem: 19788 +Test: [ 8600/21770] eta: 0:10:36 time: 0.0525 data: 0.0017 max mem: 19788 +Test: [ 8700/21770] eta: 0:10:31 time: 0.0443 data: 0.0016 max mem: 19788 +Test: [ 8800/21770] eta: 0:10:27 time: 0.0508 data: 0.0015 max mem: 19788 +Test: [ 8900/21770] eta: 0:10:21 time: 0.0457 data: 0.0014 max mem: 19788 +Test: [ 9000/21770] eta: 0:10:17 time: 0.0525 data: 0.0018 max mem: 19788 +Test: [ 9100/21770] eta: 0:10:12 time: 0.0448 data: 0.0016 max mem: 19788 +Test: [ 9200/21770] eta: 0:10:06 time: 0.0429 data: 0.0015 max mem: 19788 +Test: [ 9300/21770] eta: 0:10:01 time: 0.0470 data: 0.0017 max mem: 19788 +Test: [ 9400/21770] eta: 0:09:56 time: 0.0493 data: 0.0016 max mem: 19788 +Test: [ 9500/21770] eta: 0:09:51 time: 0.0450 data: 0.0016 max mem: 19788 +Test: [ 9600/21770] eta: 0:09:46 time: 0.0497 data: 0.0018 max mem: 19788 +Test: [ 9700/21770] eta: 0:09:41 time: 0.0551 data: 0.0019 max mem: 19788 +Test: [ 9800/21770] eta: 0:09:36 time: 0.0485 data: 0.0016 max mem: 19788 +Test: [ 9900/21770] eta: 0:09:32 time: 0.0543 data: 0.0019 max mem: 19788 +Test: [10000/21770] eta: 0:09:28 time: 0.0470 data: 0.0016 max mem: 19788 +Test: [10100/21770] eta: 0:09:23 time: 0.0539 data: 0.0019 max mem: 19788 +Test: [10200/21770] eta: 0:09:19 time: 0.0492 data: 0.0017 max mem: 19788 +Test: [10300/21770] eta: 0:09:14 time: 0.0486 data: 0.0016 max mem: 19788 +Test: [10400/21770] eta: 0:09:10 time: 0.0542 data: 0.0017 max mem: 19788 +Test: [10500/21770] eta: 0:09:05 time: 0.0455 data: 0.0015 max mem: 19788 +Test: [10600/21770] eta: 0:09:00 time: 0.0461 data: 0.0016 max mem: 19788 +Test: [10700/21770] eta: 0:08:55 time: 0.0448 data: 0.0013 max mem: 19788 +Test: [10800/21770] eta: 0:08:50 time: 0.0545 data: 0.0018 max mem: 19788 +Test: [10900/21770] eta: 0:08:45 time: 0.0462 data: 0.0016 max mem: 19788 +Test: [11000/21770] eta: 0:08:40 time: 0.0482 data: 0.0015 max mem: 19788 +Test: [11100/21770] eta: 0:08:36 time: 0.0451 data: 0.0017 max mem: 19788 +Test: [11200/21770] eta: 0:08:31 time: 0.0542 data: 0.0015 max mem: 19788 +Test: [11300/21770] eta: 0:08:26 time: 0.0470 data: 0.0015 max mem: 19788 +Test: [11400/21770] eta: 0:08:21 time: 0.0464 data: 0.0017 max mem: 19788 +Test: [11500/21770] eta: 0:08:16 time: 0.0437 data: 0.0014 max mem: 19788 +Test: [11600/21770] eta: 0:08:11 time: 0.0468 data: 0.0016 max mem: 19788 +Test: [11700/21770] eta: 0:08:06 time: 0.0502 data: 0.0016 max mem: 19788 +Test: [11800/21770] eta: 0:08:01 time: 0.0472 data: 0.0014 max mem: 19788 +Test: [11900/21770] eta: 0:07:56 time: 0.0519 data: 0.0019 max mem: 19788 +Test: [12000/21770] eta: 0:07:51 time: 0.0536 data: 0.0019 max mem: 19788 +Test: [12100/21770] eta: 0:07:47 time: 0.0459 data: 0.0014 max mem: 19788 +Test: [12200/21770] eta: 0:07:42 time: 0.0466 data: 0.0016 max mem: 19788 +Test: [12300/21770] eta: 0:07:37 time: 0.0442 data: 0.0017 max mem: 19788 +Test: [12400/21770] eta: 0:07:32 time: 0.0447 data: 0.0016 max mem: 19788 +Test: [12500/21770] eta: 0:07:27 time: 0.0546 data: 0.0019 max mem: 19788 +Test: [12600/21770] eta: 0:07:22 time: 0.0471 data: 0.0017 max mem: 19788 +Test: [12700/21770] eta: 0:07:18 time: 0.0458 data: 0.0016 max mem: 19788 +Test: [12800/21770] eta: 0:07:13 time: 0.0530 data: 0.0018 max mem: 19788 +Test: [12900/21770] eta: 0:07:08 time: 0.0500 data: 0.0016 max mem: 19788 +Test: [13000/21770] eta: 0:07:03 time: 0.0446 data: 0.0016 max mem: 19788 +Test: [13100/21770] eta: 0:06:59 time: 0.0553 data: 0.0018 max mem: 19788 +Test: [13200/21770] eta: 0:06:54 time: 0.0526 data: 0.0018 max mem: 19788 +Test: [13300/21770] eta: 0:06:49 time: 0.0534 data: 0.0019 max mem: 19788 +Test: [13400/21770] eta: 0:06:44 time: 0.0463 data: 0.0015 max mem: 19788 +Test: [13500/21770] eta: 0:06:39 time: 0.0483 data: 0.0026 max mem: 19788 +Test: [13600/21770] eta: 0:06:34 time: 0.0448 data: 0.0015 max mem: 19788 +Test: [13700/21770] eta: 0:06:30 time: 0.0443 data: 0.0014 max mem: 19788 +Test: [13800/21770] eta: 0:06:25 time: 0.0456 data: 0.0016 max mem: 19788 +Test: [13900/21770] eta: 0:06:19 time: 0.0434 data: 0.0015 max mem: 19788 +Test: [14000/21770] eta: 0:06:14 time: 0.0449 data: 0.0015 max mem: 19788 +Test: [14100/21770] eta: 0:06:10 time: 0.0466 data: 0.0016 max mem: 19788 +Test: [14200/21770] eta: 0:06:05 time: 0.0532 data: 0.0018 max mem: 19788 +Test: [14300/21770] eta: 0:06:00 time: 0.0467 data: 0.0017 max mem: 19788 +Test: [14400/21770] eta: 0:05:55 time: 0.0442 data: 0.0016 max mem: 19788 +Test: [14500/21770] eta: 0:05:50 time: 0.0477 data: 0.0018 max mem: 19788 +Test: [14600/21770] eta: 0:05:46 time: 0.0491 data: 0.0018 max mem: 19788 +Test: [14700/21770] eta: 0:05:41 time: 0.0447 data: 0.0016 max mem: 19788 +Test: [14800/21770] eta: 0:05:36 time: 0.0522 data: 0.0019 max mem: 19788 +Test: [14900/21770] eta: 0:05:32 time: 0.0538 data: 0.0019 max mem: 19788 +Test: [15000/21770] eta: 0:05:27 time: 0.0458 data: 0.0015 max mem: 19788 +Test: [15100/21770] eta: 0:05:22 time: 0.0455 data: 0.0015 max mem: 19788 +Test: [15200/21770] eta: 0:05:17 time: 0.0475 data: 0.0016 max mem: 19788 +Test: [15300/21770] eta: 0:05:12 time: 0.0474 data: 0.0015 max mem: 19788 +Test: [15400/21770] eta: 0:05:07 time: 0.0467 data: 0.0017 max mem: 19788 +Test: [15500/21770] eta: 0:05:02 time: 0.0458 data: 0.0015 max mem: 19788 +Test: [15600/21770] eta: 0:04:58 time: 0.0495 data: 0.0017 max mem: 19788 +Test: [15700/21770] eta: 0:04:53 time: 0.0453 data: 0.0017 max mem: 19788 +Test: [15800/21770] eta: 0:04:48 time: 0.0555 data: 0.0020 max mem: 19788 +Test: [15900/21770] eta: 0:04:43 time: 0.0490 data: 0.0014 max mem: 19788 +Test: [16000/21770] eta: 0:04:38 time: 0.0446 data: 0.0015 max mem: 19788 +Test: [16100/21770] eta: 0:04:33 time: 0.0539 data: 0.0017 max mem: 19788 +Test: [16200/21770] eta: 0:04:29 time: 0.0448 data: 0.0017 max mem: 19788 +Test: [16300/21770] eta: 0:04:24 time: 0.0452 data: 0.0014 max mem: 19788 +Test: [16400/21770] eta: 0:04:19 time: 0.0534 data: 0.0017 max mem: 19788 +Test: [16500/21770] eta: 0:04:14 time: 0.0437 data: 0.0016 max mem: 19788 +Test: [16600/21770] eta: 0:04:09 time: 0.0442 data: 0.0015 max mem: 19788 +Test: [16700/21770] eta: 0:04:04 time: 0.0437 data: 0.0017 max mem: 19788 +Test: [16800/21770] eta: 0:03:59 time: 0.0440 data: 0.0016 max mem: 19788 +Test: [16900/21770] eta: 0:03:54 time: 0.0547 data: 0.0018 max mem: 19788 +Test: [17000/21770] eta: 0:03:50 time: 0.0509 data: 0.0017 max mem: 19788 +Test: [17100/21770] eta: 0:03:45 time: 0.0442 data: 0.0014 max mem: 19788 +Test: [17200/21770] eta: 0:03:40 time: 0.0437 data: 0.0014 max mem: 19788 +Test: [17300/21770] eta: 0:03:35 time: 0.0467 data: 0.0016 max mem: 19788 +Test: [17400/21770] eta: 0:03:30 time: 0.0438 data: 0.0016 max mem: 19788 +Test: [17500/21770] eta: 0:03:25 time: 0.0449 data: 0.0016 max mem: 19788 +Test: [17600/21770] eta: 0:03:21 time: 0.0497 data: 0.0019 max mem: 19788 +Test: [17700/21770] eta: 0:03:16 time: 0.0450 data: 0.0015 max mem: 19788 +Test: [17800/21770] eta: 0:03:11 time: 0.0485 data: 0.0018 max mem: 19788 +Test: [17900/21770] eta: 0:03:06 time: 0.0473 data: 0.0016 max mem: 19788 +Test: [18000/21770] eta: 0:03:01 time: 0.0432 data: 0.0014 max mem: 19788 +Test: [18100/21770] eta: 0:02:56 time: 0.0439 data: 0.0015 max mem: 19788 +Test: [18200/21770] eta: 0:02:52 time: 0.0503 data: 0.0016 max mem: 19788 +Test: [18300/21770] eta: 0:02:47 time: 0.0454 data: 0.0016 max mem: 19788 +Test: [18400/21770] eta: 0:02:42 time: 0.0527 data: 0.0018 max mem: 19788 +Test: [18500/21770] eta: 0:02:37 time: 0.0532 data: 0.0019 max mem: 19788 +Test: [18600/21770] eta: 0:02:32 time: 0.0419 data: 0.0014 max mem: 19788 +Test: [18700/21770] eta: 0:02:27 time: 0.0469 data: 0.0016 max mem: 19788 +Test: [18800/21770] eta: 0:02:23 time: 0.0450 data: 0.0014 max mem: 19788 +Test: [18900/21770] eta: 0:02:18 time: 0.0462 data: 0.0015 max mem: 19788 +Test: [19000/21770] eta: 0:02:13 time: 0.0446 data: 0.0016 max mem: 19788 +Test: [19100/21770] eta: 0:02:08 time: 0.0523 data: 0.0018 max mem: 19788 +Test: [19200/21770] eta: 0:02:03 time: 0.0467 data: 0.0016 max mem: 19788 +Test: [19300/21770] eta: 0:01:58 time: 0.0522 data: 0.0016 max mem: 19788 +Test: [19400/21770] eta: 0:01:54 time: 0.0533 data: 0.0015 max mem: 19788 +Test: [19500/21770] eta: 0:01:49 time: 0.0439 data: 0.0015 max mem: 19788 +Test: [19600/21770] eta: 0:01:44 time: 0.0545 data: 0.0018 max mem: 19788 +Test: [19700/21770] eta: 0:01:39 time: 0.0533 data: 0.0016 max mem: 19788 +Test: [19800/21770] eta: 0:01:34 time: 0.0460 data: 0.0016 max mem: 19788 +Test: [19900/21770] eta: 0:01:30 time: 0.0476 data: 0.0016 max mem: 19788 +Test: [20000/21770] eta: 0:01:25 time: 0.0447 data: 0.0016 max mem: 19788 +Test: [20100/21770] eta: 0:01:20 time: 0.0442 data: 0.0014 max mem: 19788 +Test: [20200/21770] eta: 0:01:15 time: 0.0441 data: 0.0016 max mem: 19788 +Test: [20300/21770] eta: 0:01:10 time: 0.0493 data: 0.0018 max mem: 19788 +Test: [20400/21770] eta: 0:01:06 time: 0.0519 data: 0.0016 max mem: 19788 +Test: [20500/21770] eta: 0:01:01 time: 0.0437 data: 0.0013 max mem: 19788 +Test: [20600/21770] eta: 0:00:56 time: 0.0459 data: 0.0016 max mem: 19788 +Test: [20700/21770] eta: 0:00:51 time: 0.0436 data: 0.0015 max mem: 19788 +Test: [20800/21770] eta: 0:00:46 time: 0.0547 data: 0.0016 max mem: 19788 +Test: [20900/21770] eta: 0:00:41 time: 0.0448 data: 0.0017 max mem: 19788 +Test: [21000/21770] eta: 0:00:37 time: 0.0444 data: 0.0015 max mem: 19788 +Test: [21100/21770] eta: 0:00:32 time: 0.0439 data: 0.0015 max mem: 19788 +Test: [21200/21770] eta: 0:00:27 time: 0.0534 data: 0.0016 max mem: 19788 +Test: [21300/21770] eta: 0:00:22 time: 0.0474 data: 0.0016 max mem: 19788 +Test: [21400/21770] eta: 0:00:17 time: 0.0455 data: 0.0016 max mem: 19788 +Test: [21500/21770] eta: 0:00:12 time: 0.0462 data: 0.0014 max mem: 19788 +Test: [21600/21770] eta: 0:00:08 time: 0.0520 data: 0.0017 max mem: 19788 +Test: [21700/21770] eta: 0:00:03 time: 0.0435 data: 0.0014 max mem: 19788 +Test: Total time: 0:17:28 +Final results: +Mean IoU is 64.79 + + precision@0.5 = 72.10 + precision@0.6 = 66.62 + precision@0.7 = 60.29 + precision@0.8 = 49.64 + precision@0.9 = 24.47 + overall IoU = 65.02 + mean IoU = 64.79 + +Mean accuracy for one-to-zero sample is 87.41 + +Average object IoU 0.6478833798848661 +Overall IoU 65.02281188964844 +Epoch: [32] [ 0/2138] eta: 8:51:56 lr: 1.1745571353156134e-05 loss: 0.0238 (0.0238) time: 14.9284 data: 2.0203 max mem: 19788 +Epoch: [32] [ 10/2138] eta: 2:27:54 lr: 1.1739390377114576e-05 loss: 0.0197 (0.0206) time: 4.1702 data: 0.1860 max mem: 19788 +Epoch: [32] [ 20/2138] eta: 2:07:17 lr: 1.17332090394538e-05 loss: 0.0183 (0.0193) time: 3.0397 data: 0.0022 max mem: 19788 +Epoch: [32] [ 30/2138] eta: 1:59:39 lr: 1.1727027339940956e-05 loss: 0.0199 (0.0202) time: 2.9856 data: 0.0025 max mem: 19788 +Epoch: [32] [ 40/2138] eta: 1:55:27 lr: 1.1720845278342888e-05 loss: 0.0203 (0.0203) time: 2.9829 data: 0.0026 max mem: 19788 +Epoch: [32] [ 50/2138] eta: 1:52:43 lr: 1.1714662854426177e-05 loss: 0.0183 (0.0208) time: 2.9806 data: 0.0024 max mem: 19788 +Epoch: [32] [ 60/2138] eta: 1:50:36 lr: 1.170848006795709e-05 loss: 0.0212 (0.0210) time: 2.9723 data: 0.0024 max mem: 19788 +Epoch: [32] [ 70/2138] eta: 1:49:26 lr: 1.170229691870163e-05 loss: 0.0206 (0.0209) time: 3.0127 data: 0.0022 max mem: 19788 +Epoch: [32] [ 80/2138] eta: 1:48:17 lr: 1.169611340642549e-05 loss: 0.0195 (0.0209) time: 3.0456 data: 0.0021 max mem: 19788 +Epoch: [32] [ 90/2138] eta: 1:47:07 lr: 1.1689929530894099e-05 loss: 0.0182 (0.0206) time: 3.0078 data: 0.0024 max mem: 19788 +Epoch: [32] [ 100/2138] eta: 1:46:05 lr: 1.1683745291872567e-05 loss: 0.0178 (0.0206) time: 2.9864 data: 0.0026 max mem: 19788 +Epoch: [32] [ 110/2138] eta: 1:45:17 lr: 1.1677560689125742e-05 loss: 0.0177 (0.0204) time: 3.0076 data: 0.0024 max mem: 19788 +Epoch: [32] [ 120/2138] eta: 1:44:39 lr: 1.1671375722418158e-05 loss: 0.0165 (0.0202) time: 3.0520 data: 0.0024 max mem: 19788 +Epoch: [32] [ 130/2138] eta: 1:43:53 lr: 1.1665190391514077e-05 loss: 0.0192 (0.0203) time: 3.0462 data: 0.0026 max mem: 19788 +Epoch: [32] [ 140/2138] eta: 1:43:17 lr: 1.1659004696177452e-05 loss: 0.0204 (0.0203) time: 3.0427 data: 0.0027 max mem: 19788 +Epoch: [32] [ 150/2138] eta: 1:42:41 lr: 1.1652818636171961e-05 loss: 0.0184 (0.0202) time: 3.0649 data: 0.0025 max mem: 19788 +Epoch: [32] [ 160/2138] eta: 1:42:27 lr: 1.1646632211260971e-05 loss: 0.0191 (0.0202) time: 3.1509 data: 0.0023 max mem: 19788 +Epoch: [32] [ 170/2138] eta: 1:42:11 lr: 1.1640445421207576e-05 loss: 0.0197 (0.0202) time: 3.2393 data: 0.0023 max mem: 19788 +Epoch: [32] [ 180/2138] eta: 1:41:26 lr: 1.1634258265774556e-05 loss: 0.0193 (0.0201) time: 3.1113 data: 0.0025 max mem: 19788 +Epoch: [32] [ 190/2138] eta: 1:40:50 lr: 1.1628070744724416e-05 loss: 0.0183 (0.0200) time: 3.0237 data: 0.0027 max mem: 19788 +Epoch: [32] [ 200/2138] eta: 1:40:06 lr: 1.1621882857819345e-05 loss: 0.0187 (0.0200) time: 3.0174 data: 0.0029 max mem: 19788 +Epoch: [32] [ 210/2138] eta: 1:39:24 lr: 1.1615694604821257e-05 loss: 0.0200 (0.0201) time: 2.9759 data: 0.0028 max mem: 19788 +Epoch: [32] [ 220/2138] eta: 1:38:47 lr: 1.1609505985491751e-05 loss: 0.0195 (0.0200) time: 2.9996 data: 0.0025 max mem: 19788 +Epoch: [32] [ 230/2138] eta: 1:38:14 lr: 1.1603316999592153e-05 loss: 0.0190 (0.0201) time: 3.0453 data: 0.0026 max mem: 19788 +Epoch: [32] [ 240/2138] eta: 1:37:34 lr: 1.1597127646883465e-05 loss: 0.0196 (0.0200) time: 3.0189 data: 0.0029 max mem: 19788 +Epoch: [32] [ 250/2138] eta: 1:36:57 lr: 1.1590937927126415e-05 loss: 0.0191 (0.0200) time: 2.9875 data: 0.0033 max mem: 19788 +Epoch: [32] [ 260/2138] eta: 1:36:23 lr: 1.1584747840081412e-05 loss: 0.0190 (0.0200) time: 3.0237 data: 0.0031 max mem: 19788 +Epoch: [32] [ 270/2138] eta: 1:36:06 lr: 1.1578557385508588e-05 loss: 0.0195 (0.0200) time: 3.1567 data: 0.0029 max mem: 19788 +Epoch: [32] [ 280/2138] eta: 1:35:27 lr: 1.1572366563167758e-05 loss: 0.0204 (0.0200) time: 3.1228 data: 0.0031 max mem: 19788 +Epoch: [32] [ 290/2138] eta: 1:34:49 lr: 1.1566175372818437e-05 loss: 0.0190 (0.0200) time: 2.9711 data: 0.0027 max mem: 19788 +Epoch: [32] [ 300/2138] eta: 1:34:12 lr: 1.1559983814219861e-05 loss: 0.0194 (0.0200) time: 2.9692 data: 0.0027 max mem: 19788 +Epoch: [32] [ 310/2138] eta: 1:33:40 lr: 1.1553791887130936e-05 loss: 0.0194 (0.0200) time: 3.0107 data: 0.0029 max mem: 19788 +Epoch: [32] [ 320/2138] eta: 1:33:02 lr: 1.1547599591310294e-05 loss: 0.0176 (0.0199) time: 3.0044 data: 0.0024 max mem: 19788 +Epoch: [32] [ 330/2138] eta: 1:32:34 lr: 1.1541406926516238e-05 loss: 0.0198 (0.0200) time: 3.0374 data: 0.0021 max mem: 19788 +Epoch: [32] [ 340/2138] eta: 1:32:03 lr: 1.1535213892506793e-05 loss: 0.0207 (0.0200) time: 3.0891 data: 0.0025 max mem: 19788 +Epoch: [32] [ 350/2138] eta: 1:31:30 lr: 1.1529020489039663e-05 loss: 0.0178 (0.0200) time: 3.0490 data: 0.0028 max mem: 19788 +Epoch: [32] [ 360/2138] eta: 1:30:54 lr: 1.1522826715872264e-05 loss: 0.0199 (0.0200) time: 3.0001 data: 0.0028 max mem: 19788 +Epoch: [32] [ 370/2138] eta: 1:30:20 lr: 1.1516632572761687e-05 loss: 0.0213 (0.0200) time: 2.9715 data: 0.0027 max mem: 19788 +Epoch: [32] [ 380/2138] eta: 1:29:45 lr: 1.1510438059464743e-05 loss: 0.0178 (0.0200) time: 2.9786 data: 0.0027 max mem: 19788 +Epoch: [32] [ 390/2138] eta: 1:29:12 lr: 1.1504243175737912e-05 loss: 0.0170 (0.0199) time: 2.9981 data: 0.0029 max mem: 19788 +Epoch: [32] [ 400/2138] eta: 1:28:38 lr: 1.149804792133739e-05 loss: 0.0177 (0.0200) time: 3.0057 data: 0.0026 max mem: 19788 +Epoch: [32] [ 410/2138] eta: 1:28:05 lr: 1.1491852296019051e-05 loss: 0.0178 (0.0199) time: 2.9920 data: 0.0025 max mem: 19788 +Epoch: [32] [ 420/2138] eta: 1:27:39 lr: 1.1485656299538476e-05 loss: 0.0178 (0.0199) time: 3.0815 data: 0.0028 max mem: 19788 +Epoch: [32] [ 430/2138] eta: 1:27:11 lr: 1.147945993165092e-05 loss: 0.0189 (0.0199) time: 3.1533 data: 0.0028 max mem: 19788 +Epoch: [32] [ 440/2138] eta: 1:26:41 lr: 1.1473263192111353e-05 loss: 0.0201 (0.0199) time: 3.1077 data: 0.0030 max mem: 19788 +Epoch: [32] [ 450/2138] eta: 1:26:09 lr: 1.1467066080674407e-05 loss: 0.0203 (0.0199) time: 3.0442 data: 0.0031 max mem: 19788 +Epoch: [32] [ 460/2138] eta: 1:25:39 lr: 1.146086859709444e-05 loss: 0.0190 (0.0199) time: 3.0496 data: 0.0029 max mem: 19788 +Epoch: [32] [ 470/2138] eta: 1:25:07 lr: 1.145467074112546e-05 loss: 0.0186 (0.0199) time: 3.0619 data: 0.0027 max mem: 19788 +Epoch: [32] [ 480/2138] eta: 1:24:33 lr: 1.1448472512521206e-05 loss: 0.0206 (0.0200) time: 2.9997 data: 0.0026 max mem: 19788 +Epoch: [32] [ 490/2138] eta: 1:23:59 lr: 1.1442273911035067e-05 loss: 0.0205 (0.0199) time: 2.9609 data: 0.0024 max mem: 19788 +Epoch: [32] [ 500/2138] eta: 1:23:25 lr: 1.1436074936420154e-05 loss: 0.0178 (0.0199) time: 2.9502 data: 0.0023 max mem: 19788 +Epoch: [32] [ 510/2138] eta: 1:22:52 lr: 1.1429875588429235e-05 loss: 0.0168 (0.0199) time: 2.9549 data: 0.0022 max mem: 19788 +Epoch: [32] [ 520/2138] eta: 1:22:19 lr: 1.1423675866814797e-05 loss: 0.0168 (0.0199) time: 2.9829 data: 0.0021 max mem: 19788 +Epoch: [32] [ 530/2138] eta: 1:21:52 lr: 1.1417475771328982e-05 loss: 0.0180 (0.0199) time: 3.0735 data: 0.0023 max mem: 19788 +Epoch: [32] [ 540/2138] eta: 1:21:19 lr: 1.1411275301723643e-05 loss: 0.0172 (0.0199) time: 3.0680 data: 0.0026 max mem: 19788 +Epoch: [32] [ 550/2138] eta: 1:20:48 lr: 1.1405074457750299e-05 loss: 0.0185 (0.0199) time: 3.0058 data: 0.0026 max mem: 19788 +Epoch: [32] [ 560/2138] eta: 1:20:15 lr: 1.1398873239160174e-05 loss: 0.0214 (0.0199) time: 2.9986 data: 0.0026 max mem: 19788 +Epoch: [32] [ 570/2138] eta: 1:19:42 lr: 1.1392671645704152e-05 loss: 0.0192 (0.0199) time: 2.9701 data: 0.0026 max mem: 19788 +Epoch: [32] [ 580/2138] eta: 1:19:11 lr: 1.138646967713283e-05 loss: 0.0189 (0.0199) time: 2.9924 data: 0.0028 max mem: 19788 +Epoch: [32] [ 590/2138] eta: 1:18:40 lr: 1.1380267333196458e-05 loss: 0.0198 (0.0200) time: 3.0228 data: 0.0027 max mem: 19788 +Epoch: [32] [ 600/2138] eta: 1:18:07 lr: 1.1374064613644984e-05 loss: 0.0192 (0.0200) time: 2.9997 data: 0.0026 max mem: 19788 +Epoch: [32] [ 610/2138] eta: 1:17:37 lr: 1.1367861518228042e-05 loss: 0.0182 (0.0200) time: 3.0069 data: 0.0029 max mem: 19788 +Epoch: [32] [ 620/2138] eta: 1:17:05 lr: 1.1361658046694931e-05 loss: 0.0188 (0.0200) time: 3.0242 data: 0.0025 max mem: 19788 +Epoch: [32] [ 630/2138] eta: 1:16:35 lr: 1.1355454198794652e-05 loss: 0.0192 (0.0200) time: 3.0299 data: 0.0022 max mem: 19788 +Epoch: [32] [ 640/2138] eta: 1:16:02 lr: 1.1349249974275868e-05 loss: 0.0190 (0.0201) time: 3.0041 data: 0.0022 max mem: 19788 +Epoch: [32] [ 650/2138] eta: 1:15:30 lr: 1.1343045372886932e-05 loss: 0.0200 (0.0201) time: 2.9569 data: 0.0023 max mem: 19788 +Epoch: [32] [ 660/2138] eta: 1:14:59 lr: 1.1336840394375864e-05 loss: 0.0200 (0.0201) time: 2.9850 data: 0.0024 max mem: 19788 +Epoch: [32] [ 670/2138] eta: 1:14:27 lr: 1.133063503849038e-05 loss: 0.0191 (0.0201) time: 2.9977 data: 0.0025 max mem: 19788 +Epoch: [32] [ 680/2138] eta: 1:13:55 lr: 1.1324429304977855e-05 loss: 0.0172 (0.0200) time: 2.9882 data: 0.0031 max mem: 19788 +Epoch: [32] [ 690/2138] eta: 1:13:23 lr: 1.131822319358536e-05 loss: 0.0182 (0.0200) time: 2.9828 data: 0.0031 max mem: 19788 +Epoch: [32] [ 700/2138] eta: 1:12:56 lr: 1.131201670405962e-05 loss: 0.0191 (0.0200) time: 3.0849 data: 0.0024 max mem: 19788 +Epoch: [32] [ 710/2138] eta: 1:12:26 lr: 1.1305809836147057e-05 loss: 0.0191 (0.0200) time: 3.1169 data: 0.0025 max mem: 19788 +Epoch: [32] [ 720/2138] eta: 1:11:56 lr: 1.1299602589593749e-05 loss: 0.0164 (0.0200) time: 3.0538 data: 0.0025 max mem: 19788 +Epoch: [32] [ 730/2138] eta: 1:11:24 lr: 1.129339496414547e-05 loss: 0.0168 (0.0200) time: 3.0324 data: 0.0024 max mem: 19788 +Epoch: [32] [ 740/2138] eta: 1:10:57 lr: 1.1287186959547647e-05 loss: 0.0186 (0.0200) time: 3.0983 data: 0.0026 max mem: 19788 +Epoch: [32] [ 750/2138] eta: 1:10:31 lr: 1.1280978575545399e-05 loss: 0.0195 (0.0200) time: 3.2409 data: 0.0028 max mem: 19788 +Epoch: [32] [ 760/2138] eta: 1:10:02 lr: 1.1274769811883493e-05 loss: 0.0207 (0.0200) time: 3.2196 data: 0.0027 max mem: 19788 +Epoch: [32] [ 770/2138] eta: 1:09:31 lr: 1.1268560668306401e-05 loss: 0.0203 (0.0200) time: 3.0850 data: 0.0024 max mem: 19788 +Epoch: [32] [ 780/2138] eta: 1:09:02 lr: 1.1262351144558233e-05 loss: 0.0180 (0.0200) time: 3.0655 data: 0.0021 max mem: 19788 +Epoch: [32] [ 790/2138] eta: 1:08:32 lr: 1.12561412403828e-05 loss: 0.0180 (0.0200) time: 3.1148 data: 0.0021 max mem: 19788 +Epoch: [32] [ 800/2138] eta: 1:08:00 lr: 1.1249930955523552e-05 loss: 0.0192 (0.0200) time: 3.0330 data: 0.0021 max mem: 19788 +Epoch: [32] [ 810/2138] eta: 1:07:28 lr: 1.1243720289723644e-05 loss: 0.0194 (0.0200) time: 2.9553 data: 0.0021 max mem: 19788 +Epoch: [32] [ 820/2138] eta: 1:06:57 lr: 1.1237509242725863e-05 loss: 0.0187 (0.0200) time: 2.9850 data: 0.0025 max mem: 19788 +Epoch: [32] [ 830/2138] eta: 1:06:25 lr: 1.1231297814272698e-05 loss: 0.0182 (0.0200) time: 2.9860 data: 0.0029 max mem: 19788 +Epoch: [32] [ 840/2138] eta: 1:05:55 lr: 1.1225086004106277e-05 loss: 0.0182 (0.0200) time: 3.0259 data: 0.0030 max mem: 19788 +Epoch: [32] [ 850/2138] eta: 1:05:24 lr: 1.1218873811968419e-05 loss: 0.0189 (0.0200) time: 3.0336 data: 0.0031 max mem: 19788 +Epoch: [32] [ 860/2138] eta: 1:04:53 lr: 1.1212661237600589e-05 loss: 0.0186 (0.0200) time: 2.9824 data: 0.0028 max mem: 19788 +Epoch: [32] [ 870/2138] eta: 1:04:24 lr: 1.1206448280743937e-05 loss: 0.0184 (0.0200) time: 3.0952 data: 0.0024 max mem: 19788 +Epoch: [32] [ 880/2138] eta: 1:03:56 lr: 1.1200234941139256e-05 loss: 0.0186 (0.0200) time: 3.2033 data: 0.0024 max mem: 19788 +Epoch: [32] [ 890/2138] eta: 1:03:25 lr: 1.119402121852703e-05 loss: 0.0193 (0.0200) time: 3.1013 data: 0.0028 max mem: 19788 +Epoch: [32] [ 900/2138] eta: 1:02:53 lr: 1.1187807112647387e-05 loss: 0.0188 (0.0200) time: 2.9832 data: 0.0029 max mem: 19788 +Epoch: [32] [ 910/2138] eta: 1:02:22 lr: 1.1181592623240113e-05 loss: 0.0179 (0.0200) time: 2.9675 data: 0.0029 max mem: 19788 +Epoch: [32] [ 920/2138] eta: 1:01:50 lr: 1.1175377750044683e-05 loss: 0.0180 (0.0200) time: 2.9721 data: 0.0029 max mem: 19788 +Epoch: [32] [ 930/2138] eta: 1:01:19 lr: 1.1169162492800207e-05 loss: 0.0217 (0.0200) time: 2.9680 data: 0.0027 max mem: 19788 +Epoch: [32] [ 940/2138] eta: 1:00:47 lr: 1.116294685124548e-05 loss: 0.0217 (0.0201) time: 2.9691 data: 0.0027 max mem: 19788 +Epoch: [32] [ 950/2138] eta: 1:00:16 lr: 1.1156730825118929e-05 loss: 0.0199 (0.0200) time: 2.9696 data: 0.0027 max mem: 19788 +Epoch: [32] [ 960/2138] eta: 0:59:46 lr: 1.1150514414158671e-05 loss: 0.0211 (0.0201) time: 3.0068 data: 0.0026 max mem: 19788 +Epoch: [32] [ 970/2138] eta: 0:59:16 lr: 1.1144297618102459e-05 loss: 0.0223 (0.0201) time: 3.0812 data: 0.0025 max mem: 19788 +Epoch: [32] [ 980/2138] eta: 0:58:45 lr: 1.1138080436687722e-05 loss: 0.0178 (0.0201) time: 3.0409 data: 0.0024 max mem: 19788 +Epoch: [32] [ 990/2138] eta: 0:58:15 lr: 1.113186286965153e-05 loss: 0.0174 (0.0201) time: 3.0256 data: 0.0025 max mem: 19788 +Epoch: [32] [1000/2138] eta: 0:57:45 lr: 1.112564491673063e-05 loss: 0.0172 (0.0200) time: 3.0844 data: 0.0025 max mem: 19788 +Epoch: [32] [1010/2138] eta: 0:57:15 lr: 1.1119426577661401e-05 loss: 0.0172 (0.0201) time: 3.0870 data: 0.0024 max mem: 19788 +Epoch: [32] [1020/2138] eta: 0:56:44 lr: 1.1113207852179907e-05 loss: 0.0167 (0.0200) time: 3.0623 data: 0.0024 max mem: 19788 +Epoch: [32] [1030/2138] eta: 0:56:14 lr: 1.1106988740021842e-05 loss: 0.0168 (0.0200) time: 3.0444 data: 0.0025 max mem: 19788 +Epoch: [32] [1040/2138] eta: 0:55:44 lr: 1.1100769240922571e-05 loss: 0.0189 (0.0200) time: 3.0818 data: 0.0027 max mem: 19788 +Epoch: [32] [1050/2138] eta: 0:55:14 lr: 1.10945493546171e-05 loss: 0.0205 (0.0201) time: 3.0869 data: 0.0029 max mem: 19788 +Epoch: [32] [1060/2138] eta: 0:54:44 lr: 1.1088329080840104e-05 loss: 0.0201 (0.0201) time: 3.0822 data: 0.0027 max mem: 19788 +Epoch: [32] [1070/2138] eta: 0:54:14 lr: 1.1082108419325892e-05 loss: 0.0199 (0.0201) time: 3.0993 data: 0.0023 max mem: 19788 +Epoch: [32] [1080/2138] eta: 0:53:41 lr: 1.1075887369808448e-05 loss: 0.0174 (0.0200) time: 2.9716 data: 0.0022 max mem: 19788 +Epoch: [32] [1090/2138] eta: 0:53:09 lr: 1.106966593202138e-05 loss: 0.0188 (0.0200) time: 2.8504 data: 0.0023 max mem: 19788 +Epoch: [32] [1100/2138] eta: 0:52:37 lr: 1.1063444105697974e-05 loss: 0.0207 (0.0201) time: 2.8447 data: 0.0024 max mem: 19788 +Epoch: [32] [1110/2138] eta: 0:52:04 lr: 1.105722189057114e-05 loss: 0.0194 (0.0201) time: 2.8412 data: 0.0026 max mem: 19788 +Epoch: [32] [1120/2138] eta: 0:51:32 lr: 1.1050999286373464e-05 loss: 0.0189 (0.0201) time: 2.8442 data: 0.0029 max mem: 19788 +Epoch: [32] [1130/2138] eta: 0:51:00 lr: 1.1044776292837155e-05 loss: 0.0171 (0.0201) time: 2.8473 data: 0.0027 max mem: 19788 +Epoch: [32] [1140/2138] eta: 0:50:29 lr: 1.103855290969409e-05 loss: 0.0195 (0.0201) time: 2.8673 data: 0.0022 max mem: 19788 +Epoch: [32] [1150/2138] eta: 0:49:57 lr: 1.1032329136675778e-05 loss: 0.0169 (0.0200) time: 2.9117 data: 0.0022 max mem: 19788 +Epoch: [32] [1160/2138] eta: 0:49:25 lr: 1.1026104973513391e-05 loss: 0.0168 (0.0200) time: 2.8836 data: 0.0025 max mem: 19788 +Epoch: [32] [1170/2138] eta: 0:48:53 lr: 1.1019880419937727e-05 loss: 0.0186 (0.0200) time: 2.8380 data: 0.0025 max mem: 19788 +Epoch: [32] [1180/2138] eta: 0:48:22 lr: 1.1013655475679249e-05 loss: 0.0191 (0.0200) time: 2.8416 data: 0.0023 max mem: 19788 +Epoch: [32] [1190/2138] eta: 0:47:50 lr: 1.1007430140468045e-05 loss: 0.0175 (0.0200) time: 2.8422 data: 0.0024 max mem: 19788 +Epoch: [32] [1200/2138] eta: 0:47:18 lr: 1.100120441403387e-05 loss: 0.0169 (0.0200) time: 2.8406 data: 0.0023 max mem: 19788 +Epoch: [32] [1210/2138] eta: 0:46:46 lr: 1.0994978296106102e-05 loss: 0.0189 (0.0200) time: 2.8471 data: 0.0020 max mem: 19788 +Epoch: [32] [1220/2138] eta: 0:46:15 lr: 1.0988751786413762e-05 loss: 0.0185 (0.0200) time: 2.8496 data: 0.0021 max mem: 19788 +Epoch: [32] [1230/2138] eta: 0:45:43 lr: 1.0982524884685531e-05 loss: 0.0177 (0.0200) time: 2.8555 data: 0.0023 max mem: 19788 +Epoch: [32] [1240/2138] eta: 0:45:13 lr: 1.097629759064971e-05 loss: 0.0187 (0.0200) time: 2.8986 data: 0.0024 max mem: 19788 +Epoch: [32] [1250/2138] eta: 0:44:41 lr: 1.0970069904034259e-05 loss: 0.0187 (0.0200) time: 2.8925 data: 0.0025 max mem: 19788 +Epoch: [32] [1260/2138] eta: 0:44:10 lr: 1.0963841824566754e-05 loss: 0.0173 (0.0199) time: 2.8471 data: 0.0026 max mem: 19788 +Epoch: [32] [1270/2138] eta: 0:43:38 lr: 1.0957613351974443e-05 loss: 0.0175 (0.0199) time: 2.8435 data: 0.0027 max mem: 19788 +Epoch: [32] [1280/2138] eta: 0:43:07 lr: 1.0951384485984174e-05 loss: 0.0180 (0.0199) time: 2.8538 data: 0.0027 max mem: 19788 +Epoch: [32] [1290/2138] eta: 0:42:36 lr: 1.0945155226322469e-05 loss: 0.0181 (0.0199) time: 2.8545 data: 0.0026 max mem: 19788 +Epoch: [32] [1300/2138] eta: 0:42:05 lr: 1.0938925572715454e-05 loss: 0.0190 (0.0199) time: 2.8475 data: 0.0023 max mem: 19788 +Epoch: [32] [1310/2138] eta: 0:41:33 lr: 1.093269552488892e-05 loss: 0.0193 (0.0199) time: 2.8395 data: 0.0020 max mem: 19788 +Epoch: [32] [1320/2138] eta: 0:41:02 lr: 1.092646508256827e-05 loss: 0.0186 (0.0199) time: 2.8401 data: 0.0020 max mem: 19788 +Epoch: [32] [1330/2138] eta: 0:40:32 lr: 1.0920234245478561e-05 loss: 0.0186 (0.0199) time: 2.8845 data: 0.0022 max mem: 19788 +Epoch: [32] [1340/2138] eta: 0:40:01 lr: 1.0914003013344463e-05 loss: 0.0204 (0.0199) time: 2.9071 data: 0.0025 max mem: 19788 +Epoch: [32] [1350/2138] eta: 0:39:30 lr: 1.0907771385890303e-05 loss: 0.0213 (0.0200) time: 2.8680 data: 0.0024 max mem: 19788 +Epoch: [32] [1360/2138] eta: 0:38:59 lr: 1.0901539362840016e-05 loss: 0.0202 (0.0199) time: 2.8507 data: 0.0024 max mem: 19788 +Epoch: [32] [1370/2138] eta: 0:38:28 lr: 1.0895306943917194e-05 loss: 0.0202 (0.0200) time: 2.8515 data: 0.0026 max mem: 19788 +Epoch: [32] [1380/2138] eta: 0:37:57 lr: 1.0889074128845034e-05 loss: 0.0201 (0.0200) time: 2.8460 data: 0.0027 max mem: 19788 +Epoch: [32] [1390/2138] eta: 0:37:26 lr: 1.0882840917346387e-05 loss: 0.0189 (0.0200) time: 2.8478 data: 0.0024 max mem: 19788 +Epoch: [32] [1400/2138] eta: 0:36:55 lr: 1.0876607309143715e-05 loss: 0.0188 (0.0199) time: 2.8540 data: 0.0023 max mem: 19788 +Epoch: [32] [1410/2138] eta: 0:36:24 lr: 1.0870373303959125e-05 loss: 0.0178 (0.0199) time: 2.8524 data: 0.0026 max mem: 19788 +Epoch: [32] [1420/2138] eta: 0:35:54 lr: 1.0864138901514332e-05 loss: 0.0182 (0.0199) time: 2.8642 data: 0.0025 max mem: 19788 +Epoch: [32] [1430/2138] eta: 0:35:23 lr: 1.0857904101530706e-05 loss: 0.0201 (0.0199) time: 2.8930 data: 0.0026 max mem: 19788 +Epoch: [32] [1440/2138] eta: 0:34:53 lr: 1.085166890372921e-05 loss: 0.0204 (0.0199) time: 2.9469 data: 0.0026 max mem: 19788 +Epoch: [32] [1450/2138] eta: 0:34:23 lr: 1.0845433307830467e-05 loss: 0.0204 (0.0200) time: 2.9622 data: 0.0023 max mem: 19788 +Epoch: [32] [1460/2138] eta: 0:33:53 lr: 1.0839197313554697e-05 loss: 0.0201 (0.0200) time: 2.9287 data: 0.0021 max mem: 19788 +Epoch: [32] [1470/2138] eta: 0:33:22 lr: 1.0832960920621765e-05 loss: 0.0173 (0.0200) time: 2.8720 data: 0.0021 max mem: 19788 +Epoch: [32] [1480/2138] eta: 0:32:51 lr: 1.0826724128751142e-05 loss: 0.0167 (0.0200) time: 2.8184 data: 0.0023 max mem: 19788 +Epoch: [32] [1490/2138] eta: 0:32:20 lr: 1.0820486937661941e-05 loss: 0.0178 (0.0200) time: 2.8261 data: 0.0024 max mem: 19788 +Epoch: [32] [1500/2138] eta: 0:31:50 lr: 1.0814249347072883e-05 loss: 0.0193 (0.0200) time: 2.8343 data: 0.0022 max mem: 19788 +Epoch: [32] [1510/2138] eta: 0:31:19 lr: 1.0808011356702307e-05 loss: 0.0185 (0.0200) time: 2.8435 data: 0.0022 max mem: 19788 +Epoch: [32] [1520/2138] eta: 0:30:49 lr: 1.0801772966268192e-05 loss: 0.0199 (0.0200) time: 2.8564 data: 0.0022 max mem: 19788 +Epoch: [32] [1530/2138] eta: 0:30:18 lr: 1.0795534175488115e-05 loss: 0.0199 (0.0200) time: 2.8818 data: 0.0022 max mem: 19788 +Epoch: [32] [1540/2138] eta: 0:29:49 lr: 1.0789294984079292e-05 loss: 0.0178 (0.0200) time: 2.9824 data: 0.0024 max mem: 19788 +Epoch: [32] [1550/2138] eta: 0:29:19 lr: 1.0783055391758536e-05 loss: 0.0176 (0.0200) time: 3.0272 data: 0.0028 max mem: 19788 +Epoch: [32] [1560/2138] eta: 0:28:48 lr: 1.0776815398242302e-05 loss: 0.0186 (0.0200) time: 2.9171 data: 0.0026 max mem: 19788 +Epoch: [32] [1570/2138] eta: 0:28:18 lr: 1.0770575003246636e-05 loss: 0.0200 (0.0200) time: 2.8328 data: 0.0022 max mem: 19788 +Epoch: [32] [1580/2138] eta: 0:27:47 lr: 1.0764334206487226e-05 loss: 0.0186 (0.0200) time: 2.8273 data: 0.0023 max mem: 19788 +Epoch: [32] [1590/2138] eta: 0:27:17 lr: 1.0758093007679352e-05 loss: 0.0202 (0.0200) time: 2.8310 data: 0.0023 max mem: 19788 +Epoch: [32] [1600/2138] eta: 0:26:47 lr: 1.0751851406537929e-05 loss: 0.0224 (0.0200) time: 2.8283 data: 0.0024 max mem: 19788 +Epoch: [32] [1610/2138] eta: 0:26:16 lr: 1.0745609402777465e-05 loss: 0.0225 (0.0200) time: 2.8284 data: 0.0026 max mem: 19788 +Epoch: [32] [1620/2138] eta: 0:25:46 lr: 1.0739366996112102e-05 loss: 0.0165 (0.0200) time: 2.8330 data: 0.0027 max mem: 19788 +Epoch: [32] [1630/2138] eta: 0:25:16 lr: 1.0733124186255577e-05 loss: 0.0163 (0.0200) time: 2.8960 data: 0.0026 max mem: 19788 +Epoch: [32] [1640/2138] eta: 0:24:46 lr: 1.0726880972921253e-05 loss: 0.0186 (0.0199) time: 2.9476 data: 0.0023 max mem: 19788 +Epoch: [32] [1650/2138] eta: 0:24:16 lr: 1.0720637355822087e-05 loss: 0.0196 (0.0200) time: 2.9219 data: 0.0023 max mem: 19788 +Epoch: [32] [1660/2138] eta: 0:23:46 lr: 1.0714393334670665e-05 loss: 0.0200 (0.0200) time: 2.8670 data: 0.0022 max mem: 19788 +Epoch: [32] [1670/2138] eta: 0:23:15 lr: 1.0708148909179163e-05 loss: 0.0189 (0.0199) time: 2.8260 data: 0.0021 max mem: 19788 +Epoch: [32] [1680/2138] eta: 0:22:45 lr: 1.0701904079059386e-05 loss: 0.0176 (0.0199) time: 2.8291 data: 0.0021 max mem: 19788 +Epoch: [32] [1690/2138] eta: 0:22:15 lr: 1.0695658844022724e-05 loss: 0.0185 (0.0199) time: 2.8281 data: 0.0023 max mem: 19788 +Epoch: [32] [1700/2138] eta: 0:21:45 lr: 1.0689413203780196e-05 loss: 0.0176 (0.0199) time: 2.8234 data: 0.0024 max mem: 19788 +Epoch: [32] [1710/2138] eta: 0:21:14 lr: 1.0683167158042405e-05 loss: 0.0176 (0.0199) time: 2.8210 data: 0.0024 max mem: 19788 +Epoch: [32] [1720/2138] eta: 0:20:44 lr: 1.0676920706519582e-05 loss: 0.0199 (0.0199) time: 2.8449 data: 0.0023 max mem: 19788 +Epoch: [32] [1730/2138] eta: 0:20:15 lr: 1.0670673848921538e-05 loss: 0.0200 (0.0199) time: 2.9278 data: 0.0026 max mem: 19788 +Epoch: [32] [1740/2138] eta: 0:19:45 lr: 1.0664426584957715e-05 loss: 0.0180 (0.0199) time: 2.9580 data: 0.0028 max mem: 19788 +Epoch: [32] [1750/2138] eta: 0:19:15 lr: 1.0658178914337125e-05 loss: 0.0192 (0.0199) time: 2.9006 data: 0.0026 max mem: 19788 +Epoch: [32] [1760/2138] eta: 0:18:45 lr: 1.065193083676842e-05 loss: 0.0173 (0.0199) time: 2.8496 data: 0.0025 max mem: 19788 +Epoch: [32] [1770/2138] eta: 0:18:15 lr: 1.0645682351959818e-05 loss: 0.0173 (0.0199) time: 2.8325 data: 0.0024 max mem: 19788 +Epoch: [32] [1780/2138] eta: 0:17:44 lr: 1.0639433459619163e-05 loss: 0.0175 (0.0199) time: 2.8326 data: 0.0026 max mem: 19788 +Epoch: [32] [1790/2138] eta: 0:17:14 lr: 1.0633184159453877e-05 loss: 0.0184 (0.0199) time: 2.8270 data: 0.0024 max mem: 19788 +Epoch: [32] [1800/2138] eta: 0:16:44 lr: 1.0626934451171006e-05 loss: 0.0217 (0.0199) time: 2.8210 data: 0.0025 max mem: 19788 +Epoch: [32] [1810/2138] eta: 0:16:14 lr: 1.0620684334477174e-05 loss: 0.0210 (0.0199) time: 2.8370 data: 0.0028 max mem: 19788 +Epoch: [32] [1820/2138] eta: 0:15:45 lr: 1.06144338090786e-05 loss: 0.0173 (0.0199) time: 2.8909 data: 0.0027 max mem: 19788 +Epoch: [32] [1830/2138] eta: 0:15:15 lr: 1.0608182874681121e-05 loss: 0.0171 (0.0199) time: 2.9691 data: 0.0028 max mem: 19788 +Epoch: [32] [1840/2138] eta: 0:14:45 lr: 1.0601931530990142e-05 loss: 0.0197 (0.0199) time: 2.9673 data: 0.0025 max mem: 19788 +Epoch: [32] [1850/2138] eta: 0:14:15 lr: 1.0595679777710694e-05 loss: 0.0202 (0.0199) time: 2.8732 data: 0.0023 max mem: 19788 +Epoch: [32] [1860/2138] eta: 0:13:45 lr: 1.0589427614547365e-05 loss: 0.0187 (0.0199) time: 2.8219 data: 0.0024 max mem: 19788 +Epoch: [32] [1870/2138] eta: 0:13:15 lr: 1.0583175041204372e-05 loss: 0.0199 (0.0199) time: 2.8220 data: 0.0023 max mem: 19788 +Epoch: [32] [1880/2138] eta: 0:12:45 lr: 1.0576922057385495e-05 loss: 0.0169 (0.0199) time: 2.8239 data: 0.0021 max mem: 19788 +Epoch: [32] [1890/2138] eta: 0:12:16 lr: 1.0570668662794131e-05 loss: 0.0162 (0.0199) time: 2.8263 data: 0.0022 max mem: 19788 +Epoch: [32] [1900/2138] eta: 0:11:46 lr: 1.056441485713324e-05 loss: 0.0172 (0.0199) time: 2.8265 data: 0.0024 max mem: 19788 +Epoch: [32] [1910/2138] eta: 0:11:16 lr: 1.0558160640105401e-05 loss: 0.0191 (0.0199) time: 2.8222 data: 0.0026 max mem: 19788 +Epoch: [32] [1920/2138] eta: 0:10:46 lr: 1.0551906011412754e-05 loss: 0.0191 (0.0199) time: 2.9083 data: 0.0025 max mem: 19788 +Epoch: [32] [1930/2138] eta: 0:10:17 lr: 1.0545650970757054e-05 loss: 0.0196 (0.0199) time: 2.9678 data: 0.0022 max mem: 19788 +Epoch: [32] [1940/2138] eta: 0:09:47 lr: 1.0539395517839615e-05 loss: 0.0197 (0.0199) time: 2.9224 data: 0.0021 max mem: 19788 +Epoch: [32] [1950/2138] eta: 0:09:17 lr: 1.0533139652361363e-05 loss: 0.0197 (0.0199) time: 2.8607 data: 0.0023 max mem: 19788 +Epoch: [32] [1960/2138] eta: 0:08:47 lr: 1.0526883374022791e-05 loss: 0.0190 (0.0199) time: 2.8298 data: 0.0024 max mem: 19788 +Epoch: [32] [1970/2138] eta: 0:08:17 lr: 1.0520626682523992e-05 loss: 0.0177 (0.0199) time: 2.8274 data: 0.0022 max mem: 19788 +Epoch: [32] [1980/2138] eta: 0:07:48 lr: 1.0514369577564623e-05 loss: 0.0178 (0.0199) time: 2.8255 data: 0.0022 max mem: 19788 +Epoch: [32] [1990/2138] eta: 0:07:18 lr: 1.0508112058843948e-05 loss: 0.0181 (0.0199) time: 2.8248 data: 0.0021 max mem: 19788 +Epoch: [32] [2000/2138] eta: 0:06:48 lr: 1.050185412606079e-05 loss: 0.0188 (0.0199) time: 2.8199 data: 0.0021 max mem: 19788 +Epoch: [32] [2010/2138] eta: 0:06:19 lr: 1.0495595778913575e-05 loss: 0.0206 (0.0199) time: 2.8570 data: 0.0025 max mem: 19788 +Epoch: [32] [2020/2138] eta: 0:05:49 lr: 1.0489337017100285e-05 loss: 0.0206 (0.0199) time: 2.9454 data: 0.0029 max mem: 19788 +Epoch: [32] [2030/2138] eta: 0:05:19 lr: 1.048307784031851e-05 loss: 0.0184 (0.0199) time: 2.9620 data: 0.0028 max mem: 19788 +Epoch: [32] [2040/2138] eta: 0:04:50 lr: 1.047681824826539e-05 loss: 0.0184 (0.0199) time: 2.8838 data: 0.0023 max mem: 19788 +Epoch: [32] [2050/2138] eta: 0:04:20 lr: 1.0470558240637667e-05 loss: 0.0173 (0.0199) time: 2.8470 data: 0.0025 max mem: 19788 +Epoch: [32] [2060/2138] eta: 0:03:50 lr: 1.0464297817131638e-05 loss: 0.0188 (0.0199) time: 2.8403 data: 0.0029 max mem: 19788 +Epoch: [32] [2070/2138] eta: 0:03:21 lr: 1.04580369774432e-05 loss: 0.0182 (0.0199) time: 2.8349 data: 0.0028 max mem: 19788 +Epoch: [32] [2080/2138] eta: 0:02:51 lr: 1.0451775721267798e-05 loss: 0.0169 (0.0199) time: 2.8275 data: 0.0025 max mem: 19788 +Epoch: [32] [2090/2138] eta: 0:02:21 lr: 1.044551404830048e-05 loss: 0.0191 (0.0199) time: 2.8211 data: 0.0025 max mem: 19788 +Epoch: [32] [2100/2138] eta: 0:01:52 lr: 1.043925195823584e-05 loss: 0.0191 (0.0199) time: 2.8267 data: 0.0028 max mem: 19788 +Epoch: [32] [2110/2138] eta: 0:01:22 lr: 1.0432989450768071e-05 loss: 0.0204 (0.0199) time: 2.9001 data: 0.0030 max mem: 19788 +Epoch: [32] [2120/2138] eta: 0:00:53 lr: 1.0426726525590917e-05 loss: 0.0230 (0.0199) time: 2.9610 data: 0.0027 max mem: 19788 +Epoch: [32] [2130/2138] eta: 0:00:23 lr: 1.0420463182397695e-05 loss: 0.0222 (0.0199) time: 2.9323 data: 0.0023 max mem: 19788 +Epoch: [32] Total time: 1:45:22 +Test: [ 0/21770] eta: 17:33:28 time: 2.9035 data: 2.8323 max mem: 19788 +Test: [ 100/21770] eta: 0:25:47 time: 0.0462 data: 0.0015 max mem: 19788 +Test: [ 200/21770] eta: 0:20:34 time: 0.0433 data: 0.0015 max mem: 19788 +Test: [ 300/21770] eta: 0:18:52 time: 0.0433 data: 0.0014 max mem: 19788 +Test: [ 400/21770] eta: 0:18:00 time: 0.0421 data: 0.0014 max mem: 19788 +Test: [ 500/21770] eta: 0:17:20 time: 0.0425 data: 0.0014 max mem: 19788 +Test: [ 600/21770] eta: 0:17:09 time: 0.0435 data: 0.0017 max mem: 19788 +Test: [ 700/21770] eta: 0:16:50 time: 0.0426 data: 0.0014 max mem: 19788 +Test: [ 800/21770] eta: 0:16:48 time: 0.0494 data: 0.0015 max mem: 19788 +Test: [ 900/21770] eta: 0:16:32 time: 0.0441 data: 0.0015 max mem: 19788 +Test: [ 1000/21770] eta: 0:16:24 time: 0.0474 data: 0.0017 max mem: 19788 +Test: [ 1100/21770] eta: 0:16:16 time: 0.0448 data: 0.0018 max mem: 19788 +Test: [ 1200/21770] eta: 0:16:05 time: 0.0438 data: 0.0016 max mem: 19788 +Test: [ 1300/21770] eta: 0:15:58 time: 0.0427 data: 0.0013 max mem: 19788 +Test: [ 1400/21770] eta: 0:15:53 time: 0.0481 data: 0.0016 max mem: 19788 +Test: [ 1500/21770] eta: 0:15:47 time: 0.0521 data: 0.0017 max mem: 19788 +Test: [ 1600/21770] eta: 0:15:39 time: 0.0431 data: 0.0015 max mem: 19788 +Test: [ 1700/21770] eta: 0:15:33 time: 0.0490 data: 0.0014 max mem: 19788 +Test: [ 1800/21770] eta: 0:15:28 time: 0.0512 data: 0.0018 max mem: 19788 +Test: [ 1900/21770] eta: 0:15:27 time: 0.0522 data: 0.0018 max mem: 19788 +Test: [ 2000/21770] eta: 0:15:24 time: 0.0429 data: 0.0015 max mem: 19788 +Test: [ 2100/21770] eta: 0:15:19 time: 0.0470 data: 0.0016 max mem: 19788 +Test: [ 2200/21770] eta: 0:15:15 time: 0.0433 data: 0.0015 max mem: 19788 +Test: [ 2300/21770] eta: 0:15:08 time: 0.0499 data: 0.0016 max mem: 19788 +Test: [ 2400/21770] eta: 0:15:01 time: 0.0438 data: 0.0013 max mem: 19788 +Test: [ 2500/21770] eta: 0:14:54 time: 0.0432 data: 0.0015 max mem: 19788 +Test: [ 2600/21770] eta: 0:14:49 time: 0.0513 data: 0.0018 max mem: 19788 +Test: [ 2700/21770] eta: 0:14:45 time: 0.0522 data: 0.0017 max mem: 19788 +Test: [ 2800/21770] eta: 0:14:41 time: 0.0442 data: 0.0015 max mem: 19788 +Test: [ 2900/21770] eta: 0:14:34 time: 0.0439 data: 0.0014 max mem: 19788 +Test: [ 3000/21770] eta: 0:14:31 time: 0.0522 data: 0.0017 max mem: 19788 +Test: [ 3100/21770] eta: 0:14:29 time: 0.0509 data: 0.0017 max mem: 19788 +Test: [ 3200/21770] eta: 0:14:25 time: 0.0488 data: 0.0018 max mem: 19788 +Test: [ 3300/21770] eta: 0:14:22 time: 0.0478 data: 0.0015 max mem: 19788 +Test: [ 3400/21770] eta: 0:14:18 time: 0.0451 data: 0.0015 max mem: 19788 +Test: [ 3500/21770] eta: 0:14:14 time: 0.0443 data: 0.0016 max mem: 19788 +Test: [ 3600/21770] eta: 0:14:08 time: 0.0457 data: 0.0016 max mem: 19788 +Test: [ 3700/21770] eta: 0:14:03 time: 0.0450 data: 0.0015 max mem: 19788 +Test: [ 3800/21770] eta: 0:13:58 time: 0.0447 data: 0.0016 max mem: 19788 +Test: [ 3900/21770] eta: 0:13:54 time: 0.0481 data: 0.0017 max mem: 19788 +Test: [ 4000/21770] eta: 0:13:49 time: 0.0462 data: 0.0015 max mem: 19788 +Test: [ 4100/21770] eta: 0:13:46 time: 0.0442 data: 0.0015 max mem: 19788 +Test: [ 4200/21770] eta: 0:13:42 time: 0.0476 data: 0.0015 max mem: 19788 +Test: [ 4300/21770] eta: 0:13:37 time: 0.0450 data: 0.0014 max mem: 19788 +Test: [ 4400/21770] eta: 0:13:33 time: 0.0527 data: 0.0018 max mem: 19788 +Test: [ 4500/21770] eta: 0:13:28 time: 0.0426 data: 0.0014 max mem: 19788 +Test: [ 4600/21770] eta: 0:13:24 time: 0.0438 data: 0.0015 max mem: 19788 +Test: [ 4700/21770] eta: 0:13:20 time: 0.0450 data: 0.0015 max mem: 19788 +Test: [ 4800/21770] eta: 0:13:16 time: 0.0466 data: 0.0016 max mem: 19788 +Test: [ 4900/21770] eta: 0:13:11 time: 0.0454 data: 0.0016 max mem: 19788 +Test: [ 5000/21770] eta: 0:13:07 time: 0.0542 data: 0.0016 max mem: 19788 +Test: [ 5100/21770] eta: 0:13:03 time: 0.0528 data: 0.0016 max mem: 19788 +Test: [ 5200/21770] eta: 0:12:57 time: 0.0444 data: 0.0015 max mem: 19788 +Test: [ 5300/21770] eta: 0:12:53 time: 0.0423 data: 0.0016 max mem: 19788 +Test: [ 5400/21770] eta: 0:12:49 time: 0.0531 data: 0.0019 max mem: 19788 +Test: [ 5500/21770] eta: 0:12:45 time: 0.0495 data: 0.0018 max mem: 19788 +Test: [ 5600/21770] eta: 0:12:41 time: 0.0512 data: 0.0017 max mem: 19788 +Test: [ 5700/21770] eta: 0:12:36 time: 0.0454 data: 0.0016 max mem: 19788 +Test: [ 5800/21770] eta: 0:12:32 time: 0.0445 data: 0.0016 max mem: 19788 +Test: [ 5900/21770] eta: 0:12:27 time: 0.0441 data: 0.0013 max mem: 19788 +Test: [ 6000/21770] eta: 0:12:22 time: 0.0461 data: 0.0014 max mem: 19788 +Test: [ 6100/21770] eta: 0:12:17 time: 0.0448 data: 0.0015 max mem: 19788 +Test: [ 6200/21770] eta: 0:12:12 time: 0.0435 data: 0.0015 max mem: 19788 +Test: [ 6300/21770] eta: 0:12:07 time: 0.0436 data: 0.0015 max mem: 19788 +Test: [ 6400/21770] eta: 0:12:03 time: 0.0506 data: 0.0017 max mem: 19788 +Test: [ 6500/21770] eta: 0:11:59 time: 0.0527 data: 0.0017 max mem: 19788 +Test: [ 6600/21770] eta: 0:11:54 time: 0.0453 data: 0.0015 max mem: 19788 +Test: [ 6700/21770] eta: 0:11:48 time: 0.0441 data: 0.0015 max mem: 19788 +Test: [ 6800/21770] eta: 0:11:44 time: 0.0518 data: 0.0015 max mem: 19788 +Test: [ 6900/21770] eta: 0:11:40 time: 0.0504 data: 0.0017 max mem: 19788 +Test: [ 7000/21770] eta: 0:11:35 time: 0.0506 data: 0.0017 max mem: 19788 +Test: [ 7100/21770] eta: 0:11:31 time: 0.0520 data: 0.0016 max mem: 19788 +Test: [ 7200/21770] eta: 0:11:25 time: 0.0437 data: 0.0015 max mem: 19788 +Test: [ 7300/21770] eta: 0:11:21 time: 0.0534 data: 0.0016 max mem: 19788 +Test: [ 7400/21770] eta: 0:11:16 time: 0.0444 data: 0.0015 max mem: 19788 +Test: [ 7500/21770] eta: 0:11:11 time: 0.0442 data: 0.0015 max mem: 19788 +Test: [ 7600/21770] eta: 0:11:07 time: 0.0519 data: 0.0018 max mem: 19788 +Test: [ 7700/21770] eta: 0:11:02 time: 0.0477 data: 0.0018 max mem: 19788 +Test: [ 7800/21770] eta: 0:10:57 time: 0.0433 data: 0.0015 max mem: 19788 +Test: [ 7900/21770] eta: 0:10:52 time: 0.0472 data: 0.0015 max mem: 19788 +Test: [ 8000/21770] eta: 0:10:47 time: 0.0529 data: 0.0016 max mem: 19788 +Test: [ 8100/21770] eta: 0:10:43 time: 0.0448 data: 0.0016 max mem: 19788 +Test: [ 8200/21770] eta: 0:10:38 time: 0.0437 data: 0.0015 max mem: 19788 +Test: [ 8300/21770] eta: 0:10:33 time: 0.0477 data: 0.0016 max mem: 19788 +Test: [ 8400/21770] eta: 0:10:27 time: 0.0435 data: 0.0015 max mem: 19788 +Test: [ 8500/21770] eta: 0:10:22 time: 0.0464 data: 0.0014 max mem: 19788 +Test: [ 8600/21770] eta: 0:10:17 time: 0.0432 data: 0.0015 max mem: 19788 +Test: [ 8700/21770] eta: 0:10:13 time: 0.0441 data: 0.0015 max mem: 19788 +Test: [ 8800/21770] eta: 0:10:08 time: 0.0440 data: 0.0014 max mem: 19788 +Test: [ 8900/21770] eta: 0:10:03 time: 0.0433 data: 0.0016 max mem: 19788 +Test: [ 9000/21770] eta: 0:09:58 time: 0.0517 data: 0.0017 max mem: 19788 +Test: [ 9100/21770] eta: 0:09:53 time: 0.0450 data: 0.0014 max mem: 19788 +Test: [ 9200/21770] eta: 0:09:49 time: 0.0525 data: 0.0018 max mem: 19788 +Test: [ 9300/21770] eta: 0:09:44 time: 0.0440 data: 0.0014 max mem: 19788 +Test: [ 9400/21770] eta: 0:09:39 time: 0.0439 data: 0.0015 max mem: 19788 +Test: [ 9500/21770] eta: 0:09:34 time: 0.0463 data: 0.0016 max mem: 19788 +Test: [ 9600/21770] eta: 0:09:30 time: 0.0452 data: 0.0015 max mem: 19788 +Test: [ 9700/21770] eta: 0:09:25 time: 0.0448 data: 0.0014 max mem: 19788 +Test: [ 9800/21770] eta: 0:09:21 time: 0.0444 data: 0.0016 max mem: 19788 +Test: [ 9900/21770] eta: 0:09:16 time: 0.0539 data: 0.0018 max mem: 19788 +Test: [10000/21770] eta: 0:09:12 time: 0.0454 data: 0.0015 max mem: 19788 +Test: [10100/21770] eta: 0:09:07 time: 0.0460 data: 0.0014 max mem: 19788 +Test: [10200/21770] eta: 0:09:03 time: 0.0511 data: 0.0017 max mem: 19788 +Test: [10300/21770] eta: 0:08:58 time: 0.0442 data: 0.0014 max mem: 19788 +Test: [10400/21770] eta: 0:08:54 time: 0.0447 data: 0.0015 max mem: 19788 +Test: [10500/21770] eta: 0:08:49 time: 0.0518 data: 0.0017 max mem: 19788 +Test: [10600/21770] eta: 0:08:45 time: 0.0469 data: 0.0017 max mem: 19788 +Test: [10700/21770] eta: 0:08:40 time: 0.0495 data: 0.0015 max mem: 19788 +Test: [10800/21770] eta: 0:08:36 time: 0.0530 data: 0.0019 max mem: 19788 +Test: [10900/21770] eta: 0:08:31 time: 0.0456 data: 0.0016 max mem: 19788 +Test: [11000/21770] eta: 0:08:26 time: 0.0446 data: 0.0016 max mem: 19788 +Test: [11100/21770] eta: 0:08:22 time: 0.0434 data: 0.0015 max mem: 19788 +Test: [11200/21770] eta: 0:08:17 time: 0.0477 data: 0.0014 max mem: 19788 +Test: [11300/21770] eta: 0:08:12 time: 0.0446 data: 0.0014 max mem: 19788 +Test: [11400/21770] eta: 0:08:07 time: 0.0433 data: 0.0015 max mem: 19788 +Test: [11500/21770] eta: 0:08:02 time: 0.0444 data: 0.0014 max mem: 19788 +Test: [11600/21770] eta: 0:07:57 time: 0.0501 data: 0.0017 max mem: 19788 +Test: [11700/21770] eta: 0:07:53 time: 0.0437 data: 0.0014 max mem: 19788 +Test: [11800/21770] eta: 0:07:48 time: 0.0449 data: 0.0014 max mem: 19788 +Test: [11900/21770] eta: 0:07:43 time: 0.0525 data: 0.0018 max mem: 19788 +Test: [12000/21770] eta: 0:07:39 time: 0.0444 data: 0.0015 max mem: 19788 +Test: [12100/21770] eta: 0:07:34 time: 0.0480 data: 0.0015 max mem: 19788 +Test: [12200/21770] eta: 0:07:30 time: 0.0515 data: 0.0017 max mem: 19788 +Test: [12300/21770] eta: 0:07:25 time: 0.0511 data: 0.0017 max mem: 19788 +Test: [12400/21770] eta: 0:07:20 time: 0.0480 data: 0.0017 max mem: 19788 +Test: [12500/21770] eta: 0:07:15 time: 0.0423 data: 0.0014 max mem: 19788 +Test: [12600/21770] eta: 0:07:11 time: 0.0430 data: 0.0015 max mem: 19788 +Test: [12700/21770] eta: 0:07:06 time: 0.0440 data: 0.0014 max mem: 19788 +Test: [12800/21770] eta: 0:07:01 time: 0.0430 data: 0.0014 max mem: 19788 +Test: [12900/21770] eta: 0:06:56 time: 0.0534 data: 0.0018 max mem: 19788 +Test: [13000/21770] eta: 0:06:52 time: 0.0462 data: 0.0015 max mem: 19788 +Test: [13100/21770] eta: 0:06:47 time: 0.0543 data: 0.0017 max mem: 19788 +Test: [13200/21770] eta: 0:06:42 time: 0.0517 data: 0.0018 max mem: 19788 +Test: [13300/21770] eta: 0:06:38 time: 0.0423 data: 0.0014 max mem: 19788 +Test: [13400/21770] eta: 0:06:33 time: 0.0430 data: 0.0014 max mem: 19788 +Test: [13500/21770] eta: 0:06:28 time: 0.0436 data: 0.0016 max mem: 19788 +Test: [13600/21770] eta: 0:06:23 time: 0.0437 data: 0.0016 max mem: 19788 +Test: [13700/21770] eta: 0:06:19 time: 0.0450 data: 0.0013 max mem: 19788 +Test: [13800/21770] eta: 0:06:14 time: 0.0455 data: 0.0014 max mem: 19788 +Test: [13900/21770] eta: 0:06:09 time: 0.0429 data: 0.0015 max mem: 19788 +Test: [14000/21770] eta: 0:06:04 time: 0.0446 data: 0.0015 max mem: 19788 +Test: [14100/21770] eta: 0:05:59 time: 0.0437 data: 0.0016 max mem: 19788 +Test: [14200/21770] eta: 0:05:55 time: 0.0447 data: 0.0014 max mem: 19788 +Test: [14300/21770] eta: 0:05:50 time: 0.0504 data: 0.0015 max mem: 19788 +Test: [14400/21770] eta: 0:05:46 time: 0.0499 data: 0.0017 max mem: 19788 +Test: [14500/21770] eta: 0:05:41 time: 0.0472 data: 0.0015 max mem: 19788 +Test: [14600/21770] eta: 0:05:36 time: 0.0451 data: 0.0014 max mem: 19788 +Test: [14700/21770] eta: 0:05:32 time: 0.0523 data: 0.0017 max mem: 19788 +Test: [14800/21770] eta: 0:05:27 time: 0.0442 data: 0.0015 max mem: 19788 +Test: [14900/21770] eta: 0:05:22 time: 0.0473 data: 0.0016 max mem: 19788 +Test: [15000/21770] eta: 0:05:17 time: 0.0434 data: 0.0013 max mem: 19788 +Test: [15100/21770] eta: 0:05:12 time: 0.0442 data: 0.0014 max mem: 19788 +Test: [15200/21770] eta: 0:05:08 time: 0.0527 data: 0.0018 max mem: 19788 +Test: [15300/21770] eta: 0:05:03 time: 0.0433 data: 0.0015 max mem: 19788 +Test: [15400/21770] eta: 0:04:58 time: 0.0466 data: 0.0016 max mem: 19788 +Test: [15500/21770] eta: 0:04:53 time: 0.0449 data: 0.0014 max mem: 19788 +Test: [15600/21770] eta: 0:04:49 time: 0.0448 data: 0.0013 max mem: 19788 +Test: [15700/21770] eta: 0:04:44 time: 0.0449 data: 0.0015 max mem: 19788 +Test: [15800/21770] eta: 0:04:39 time: 0.0437 data: 0.0014 max mem: 19788 +Test: [15900/21770] eta: 0:04:35 time: 0.0506 data: 0.0018 max mem: 19788 +Test: [16000/21770] eta: 0:04:30 time: 0.0537 data: 0.0020 max mem: 19788 +Test: [16100/21770] eta: 0:04:26 time: 0.0479 data: 0.0018 max mem: 19788 +Test: [16200/21770] eta: 0:04:21 time: 0.0443 data: 0.0016 max mem: 19788 +Test: [16300/21770] eta: 0:04:16 time: 0.0435 data: 0.0015 max mem: 19788 +Test: [16400/21770] eta: 0:04:11 time: 0.0441 data: 0.0015 max mem: 19788 +Test: [16500/21770] eta: 0:04:07 time: 0.0438 data: 0.0016 max mem: 19788 +Test: [16600/21770] eta: 0:04:02 time: 0.0515 data: 0.0015 max mem: 19788 +Test: [16700/21770] eta: 0:03:57 time: 0.0431 data: 0.0015 max mem: 19788 +Test: [16800/21770] eta: 0:03:53 time: 0.0500 data: 0.0016 max mem: 19788 +Test: [16900/21770] eta: 0:03:48 time: 0.0435 data: 0.0016 max mem: 19788 +Test: [17000/21770] eta: 0:03:43 time: 0.0428 data: 0.0016 max mem: 19788 +Test: [17100/21770] eta: 0:03:38 time: 0.0490 data: 0.0016 max mem: 19788 +Test: [17200/21770] eta: 0:03:34 time: 0.0432 data: 0.0015 max mem: 19788 +Test: [17300/21770] eta: 0:03:29 time: 0.0466 data: 0.0017 max mem: 19788 +Test: [17400/21770] eta: 0:03:24 time: 0.0468 data: 0.0015 max mem: 19788 +Test: [17500/21770] eta: 0:03:20 time: 0.0463 data: 0.0014 max mem: 19788 +Test: [17600/21770] eta: 0:03:15 time: 0.0539 data: 0.0017 max mem: 19788 +Test: [17700/21770] eta: 0:03:10 time: 0.0448 data: 0.0015 max mem: 19788 +Test: [17800/21770] eta: 0:03:06 time: 0.0451 data: 0.0016 max mem: 19788 +Test: [17900/21770] eta: 0:03:01 time: 0.0437 data: 0.0014 max mem: 19788 +Test: [18000/21770] eta: 0:02:56 time: 0.0442 data: 0.0017 max mem: 19788 +Test: [18100/21770] eta: 0:02:52 time: 0.0528 data: 0.0018 max mem: 19788 +Test: [18200/21770] eta: 0:02:47 time: 0.0431 data: 0.0014 max mem: 19788 +Test: [18300/21770] eta: 0:02:42 time: 0.0433 data: 0.0015 max mem: 19788 +Test: [18400/21770] eta: 0:02:37 time: 0.0432 data: 0.0015 max mem: 19788 +Test: [18500/21770] eta: 0:02:33 time: 0.0444 data: 0.0014 max mem: 19788 +Test: [18600/21770] eta: 0:02:28 time: 0.0446 data: 0.0014 max mem: 19788 +Test: [18700/21770] eta: 0:02:23 time: 0.0459 data: 0.0015 max mem: 19788 +Test: [18800/21770] eta: 0:02:19 time: 0.0432 data: 0.0014 max mem: 19788 +Test: [18900/21770] eta: 0:02:14 time: 0.0527 data: 0.0017 max mem: 19788 +Test: [19000/21770] eta: 0:02:09 time: 0.0429 data: 0.0016 max mem: 19788 +Test: [19100/21770] eta: 0:02:04 time: 0.0433 data: 0.0014 max mem: 19788 +Test: [19200/21770] eta: 0:02:00 time: 0.0424 data: 0.0013 max mem: 19788 +Test: [19300/21770] eta: 0:01:55 time: 0.0471 data: 0.0015 max mem: 19788 +Test: [19400/21770] eta: 0:01:50 time: 0.0466 data: 0.0014 max mem: 19788 +Test: [19500/21770] eta: 0:01:46 time: 0.0434 data: 0.0016 max mem: 19788 +Test: [19600/21770] eta: 0:01:41 time: 0.0435 data: 0.0015 max mem: 19788 +Test: [19700/21770] eta: 0:01:36 time: 0.0521 data: 0.0018 max mem: 19788 +Test: [19800/21770] eta: 0:01:32 time: 0.0440 data: 0.0017 max mem: 19788 +Test: [19900/21770] eta: 0:01:27 time: 0.0434 data: 0.0016 max mem: 19788 +Test: [20000/21770] eta: 0:01:22 time: 0.0525 data: 0.0017 max mem: 19788 +Test: [20100/21770] eta: 0:01:18 time: 0.0484 data: 0.0016 max mem: 19788 +Test: [20200/21770] eta: 0:01:13 time: 0.0434 data: 0.0015 max mem: 19788 +Test: [20300/21770] eta: 0:01:08 time: 0.0514 data: 0.0018 max mem: 19788 +Test: [20400/21770] eta: 0:01:04 time: 0.0432 data: 0.0014 max mem: 19788 +Test: [20500/21770] eta: 0:00:59 time: 0.0503 data: 0.0017 max mem: 19788 +Test: [20600/21770] eta: 0:00:54 time: 0.0447 data: 0.0014 max mem: 19788 +Test: [20700/21770] eta: 0:00:50 time: 0.0437 data: 0.0015 max mem: 19788 +Test: [20800/21770] eta: 0:00:45 time: 0.0458 data: 0.0014 max mem: 19788 +Test: [20900/21770] eta: 0:00:40 time: 0.0464 data: 0.0016 max mem: 19788 +Test: [21000/21770] eta: 0:00:35 time: 0.0483 data: 0.0016 max mem: 19788 +Test: [21100/21770] eta: 0:00:31 time: 0.0463 data: 0.0016 max mem: 19788 +Test: [21200/21770] eta: 0:00:26 time: 0.0464 data: 0.0016 max mem: 19788 +Test: [21300/21770] eta: 0:00:21 time: 0.0492 data: 0.0017 max mem: 19788 +Test: [21400/21770] eta: 0:00:17 time: 0.0514 data: 0.0019 max mem: 19788 +Test: [21500/21770] eta: 0:00:12 time: 0.0449 data: 0.0015 max mem: 19788 +Test: [21600/21770] eta: 0:00:07 time: 0.0450 data: 0.0014 max mem: 19788 +Test: [21700/21770] eta: 0:00:03 time: 0.0479 data: 0.0014 max mem: 19788 +Test: Total time: 0:16:57 +Final results: +Mean IoU is 64.96 + + precision@0.5 = 72.28 + precision@0.6 = 66.80 + precision@0.7 = 60.54 + precision@0.8 = 49.63 + precision@0.9 = 24.15 + overall IoU = 65.17 + mean IoU = 64.96 + +Mean accuracy for one-to-zero sample is 87.32 + +Average object IoU 0.6495682850953319 +Overall IoU 65.1701431274414 +Better epoch: 32 + +Epoch: [33] [ 0/2138] eta: 5:59:10 lr: 1.041545220666519e-05 loss: 0.0222 (0.0222) time: 10.0795 data: 1.6833 max mem: 19788 +Epoch: [33] [ 10/2138] eta: 2:09:11 lr: 1.0409188110268857e-05 loss: 0.0195 (0.0199) time: 3.6425 data: 0.1550 max mem: 19788 +Epoch: [33] [ 20/2138] eta: 1:55:18 lr: 1.0402923594995464e-05 loss: 0.0170 (0.0224) time: 2.9261 data: 0.0020 max mem: 19788 +Epoch: [33] [ 30/2138] eta: 1:50:04 lr: 1.039665866053671e-05 loss: 0.0191 (0.0223) time: 2.8528 data: 0.0020 max mem: 19788 +Epoch: [33] [ 40/2138] eta: 1:47:08 lr: 1.0390393306583828e-05 loss: 0.0209 (0.0218) time: 2.8511 data: 0.0025 max mem: 19788 +Epoch: [33] [ 50/2138] eta: 1:45:10 lr: 1.0384127532827644e-05 loss: 0.0185 (0.0215) time: 2.8509 data: 0.0027 max mem: 19788 +Epoch: [33] [ 60/2138] eta: 1:43:43 lr: 1.0377861338958529e-05 loss: 0.0196 (0.0216) time: 2.8528 data: 0.0027 max mem: 19788 +Epoch: [33] [ 70/2138] eta: 1:42:30 lr: 1.0371594724666437e-05 loss: 0.0198 (0.0214) time: 2.8505 data: 0.0026 max mem: 19788 +Epoch: [33] [ 80/2138] eta: 1:41:29 lr: 1.036532768964086e-05 loss: 0.0197 (0.0214) time: 2.8499 data: 0.0023 max mem: 19788 +Epoch: [33] [ 90/2138] eta: 1:41:19 lr: 1.035906023357088e-05 loss: 0.0183 (0.0209) time: 2.9495 data: 0.0023 max mem: 19788 +Epoch: [33] [ 100/2138] eta: 1:40:47 lr: 1.0352792356145113e-05 loss: 0.0164 (0.0208) time: 3.0004 data: 0.0025 max mem: 19788 +Epoch: [33] [ 110/2138] eta: 1:40:05 lr: 1.0346524057051759e-05 loss: 0.0171 (0.0205) time: 2.9290 data: 0.0026 max mem: 19788 +Epoch: [33] [ 120/2138] eta: 1:39:14 lr: 1.0340255335978556e-05 loss: 0.0160 (0.0202) time: 2.8683 data: 0.0026 max mem: 19788 +Epoch: [33] [ 130/2138] eta: 1:38:25 lr: 1.0333986192612822e-05 loss: 0.0186 (0.0203) time: 2.8273 data: 0.0022 max mem: 19788 +Epoch: [33] [ 140/2138] eta: 1:37:39 lr: 1.0327716626641408e-05 loss: 0.0190 (0.0203) time: 2.8240 data: 0.0020 max mem: 19788 +Epoch: [33] [ 150/2138] eta: 1:36:56 lr: 1.0321446637750749e-05 loss: 0.0187 (0.0202) time: 2.8254 data: 0.0022 max mem: 19788 +Epoch: [33] [ 160/2138] eta: 1:36:14 lr: 1.0315176225626809e-05 loss: 0.0187 (0.0201) time: 2.8229 data: 0.0025 max mem: 19788 +Epoch: [33] [ 170/2138] eta: 1:35:33 lr: 1.0308905389955118e-05 loss: 0.0195 (0.0200) time: 2.8204 data: 0.0024 max mem: 19788 +Epoch: [33] [ 180/2138] eta: 1:34:59 lr: 1.030263413042077e-05 loss: 0.0183 (0.0199) time: 2.8434 data: 0.0022 max mem: 19788 +Epoch: [33] [ 190/2138] eta: 1:34:39 lr: 1.0296362446708388e-05 loss: 0.0175 (0.0198) time: 2.9319 data: 0.0021 max mem: 19788 +Epoch: [33] [ 200/2138] eta: 1:34:15 lr: 1.0290090338502176e-05 loss: 0.0175 (0.0198) time: 2.9875 data: 0.0022 max mem: 19788 +Epoch: [33] [ 210/2138] eta: 1:33:43 lr: 1.0283817805485857e-05 loss: 0.0192 (0.0198) time: 2.9289 data: 0.0022 max mem: 19788 +Epoch: [33] [ 220/2138] eta: 1:33:04 lr: 1.0277544847342734e-05 loss: 0.0179 (0.0198) time: 2.8448 data: 0.0023 max mem: 19788 +Epoch: [33] [ 230/2138] eta: 1:32:29 lr: 1.0271271463755634e-05 loss: 0.0189 (0.0200) time: 2.8235 data: 0.0023 max mem: 19788 +Epoch: [33] [ 240/2138] eta: 1:31:52 lr: 1.0264997654406953e-05 loss: 0.0215 (0.0199) time: 2.8252 data: 0.0023 max mem: 19788 +Epoch: [33] [ 250/2138] eta: 1:31:18 lr: 1.0258723418978613e-05 loss: 0.0190 (0.0199) time: 2.8236 data: 0.0024 max mem: 19788 +Epoch: [33] [ 260/2138] eta: 1:30:45 lr: 1.0252448757152108e-05 loss: 0.0181 (0.0199) time: 2.8401 data: 0.0024 max mem: 19788 +Epoch: [33] [ 270/2138] eta: 1:30:12 lr: 1.0246173668608443e-05 loss: 0.0185 (0.0199) time: 2.8405 data: 0.0025 max mem: 19788 +Epoch: [33] [ 280/2138] eta: 1:29:46 lr: 1.0239898153028202e-05 loss: 0.0186 (0.0199) time: 2.8928 data: 0.0025 max mem: 19788 +Epoch: [33] [ 290/2138] eta: 1:29:23 lr: 1.0233622210091488e-05 loss: 0.0196 (0.0199) time: 2.9701 data: 0.0022 max mem: 19788 +Epoch: [33] [ 300/2138] eta: 1:28:54 lr: 1.0227345839477961e-05 loss: 0.0184 (0.0199) time: 2.9460 data: 0.0023 max mem: 19788 +Epoch: [33] [ 310/2138] eta: 1:28:20 lr: 1.0221069040866808e-05 loss: 0.0177 (0.0198) time: 2.8596 data: 0.0025 max mem: 19788 +Epoch: [33] [ 320/2138] eta: 1:27:46 lr: 1.0214791813936774e-05 loss: 0.0159 (0.0197) time: 2.8189 data: 0.0024 max mem: 19788 +Epoch: [33] [ 330/2138] eta: 1:27:13 lr: 1.0208514158366122e-05 loss: 0.0183 (0.0198) time: 2.8190 data: 0.0024 max mem: 19788 +Epoch: [33] [ 340/2138] eta: 1:26:41 lr: 1.0202236073832678e-05 loss: 0.0198 (0.0197) time: 2.8231 data: 0.0022 max mem: 19788 +Epoch: [33] [ 350/2138] eta: 1:26:08 lr: 1.0195957560013777e-05 loss: 0.0190 (0.0197) time: 2.8214 data: 0.0023 max mem: 19788 +Epoch: [33] [ 360/2138] eta: 1:25:35 lr: 1.0189678616586323e-05 loss: 0.0204 (0.0197) time: 2.8173 data: 0.0024 max mem: 19788 +Epoch: [33] [ 370/2138] eta: 1:25:04 lr: 1.0183399243226719e-05 loss: 0.0216 (0.0198) time: 2.8257 data: 0.0023 max mem: 19788 +Epoch: [33] [ 380/2138] eta: 1:24:39 lr: 1.0177119439610941e-05 loss: 0.0177 (0.0197) time: 2.9043 data: 0.0025 max mem: 19788 +Epoch: [33] [ 390/2138] eta: 1:24:11 lr: 1.017083920541446e-05 loss: 0.0166 (0.0196) time: 2.9469 data: 0.0027 max mem: 19788 +Epoch: [33] [ 400/2138] eta: 1:23:45 lr: 1.0164558540312316e-05 loss: 0.0175 (0.0197) time: 2.9283 data: 0.0028 max mem: 19788 +Epoch: [33] [ 410/2138] eta: 1:23:14 lr: 1.0158277443979048e-05 loss: 0.0174 (0.0196) time: 2.8933 data: 0.0027 max mem: 19788 +Epoch: [33] [ 420/2138] eta: 1:22:42 lr: 1.015199591608875e-05 loss: 0.0166 (0.0196) time: 2.8360 data: 0.0026 max mem: 19788 +Epoch: [33] [ 430/2138] eta: 1:22:11 lr: 1.0145713956315026e-05 loss: 0.0176 (0.0196) time: 2.8225 data: 0.0025 max mem: 19788 +Epoch: [33] [ 440/2138] eta: 1:21:40 lr: 1.0139431564331032e-05 loss: 0.0184 (0.0196) time: 2.8261 data: 0.0024 max mem: 19788 +Epoch: [33] [ 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19788 +Epoch: [33] [ 530/2138] eta: 1:17:14 lr: 1.0082870532846209e-05 loss: 0.0176 (0.0196) time: 2.8234 data: 0.0025 max mem: 19788 +Epoch: [33] [ 540/2138] eta: 1:16:43 lr: 1.007658380067776e-05 loss: 0.0163 (0.0196) time: 2.8230 data: 0.0024 max mem: 19788 +Epoch: [33] [ 550/2138] eta: 1:16:13 lr: 1.0070296632672185e-05 loss: 0.0191 (0.0196) time: 2.8287 data: 0.0023 max mem: 19788 +Epoch: [33] [ 560/2138] eta: 1:15:43 lr: 1.0064009028496879e-05 loss: 0.0209 (0.0196) time: 2.8318 data: 0.0022 max mem: 19788 +Epoch: [33] [ 570/2138] eta: 1:15:19 lr: 1.005772098781877e-05 loss: 0.0176 (0.0196) time: 2.9345 data: 0.0023 max mem: 19788 +Epoch: [33] [ 580/2138] eta: 1:14:52 lr: 1.0051432510304278e-05 loss: 0.0176 (0.0196) time: 3.0011 data: 0.0025 max mem: 19788 +Epoch: [33] [ 590/2138] eta: 1:14:26 lr: 1.0045143595619365e-05 loss: 0.0188 (0.0196) time: 2.9697 data: 0.0025 max mem: 19788 +Epoch: [33] [ 600/2138] eta: 1:13:55 lr: 1.0038854243429474e-05 loss: 0.0185 (0.0196) time: 2.8989 data: 0.0025 max mem: 19788 +Epoch: [33] [ 610/2138] eta: 1:13:25 lr: 1.0032564453399584e-05 loss: 0.0192 (0.0196) time: 2.8176 data: 0.0024 max mem: 19788 +Epoch: [33] [ 620/2138] eta: 1:12:54 lr: 1.0026274225194166e-05 loss: 0.0199 (0.0197) time: 2.8142 data: 0.0022 max mem: 19788 +Epoch: [33] [ 630/2138] eta: 1:12:24 lr: 1.0019983558477217e-05 loss: 0.0204 (0.0197) time: 2.8140 data: 0.0023 max mem: 19788 +Epoch: [33] [ 640/2138] eta: 1:11:54 lr: 1.001369245291222e-05 loss: 0.0204 (0.0197) time: 2.8256 data: 0.0026 max mem: 19788 +Epoch: [33] [ 650/2138] eta: 1:11:23 lr: 1.0007400908162189e-05 loss: 0.0196 (0.0197) time: 2.8233 data: 0.0026 max mem: 19788 +Epoch: [33] [ 660/2138] eta: 1:10:54 lr: 1.0001108923889622e-05 loss: 0.0197 (0.0197) time: 2.8339 data: 0.0023 max mem: 19788 +Epoch: [33] [ 670/2138] eta: 1:10:28 lr: 9.994816499756537e-06 loss: 0.0195 (0.0197) time: 2.9198 data: 0.0023 max mem: 19788 +Epoch: [33] [ 680/2138] eta: 1:10:00 lr: 9.988523635424444e-06 loss: 0.0178 (0.0197) time: 2.9569 data: 0.0026 max mem: 19788 +Epoch: [33] [ 690/2138] eta: 1:09:31 lr: 9.982230330554372e-06 loss: 0.0186 (0.0197) time: 2.8972 data: 0.0025 max mem: 19788 +Epoch: [33] [ 700/2138] eta: 1:09:01 lr: 9.975936584806825e-06 loss: 0.0203 (0.0197) time: 2.8449 data: 0.0024 max mem: 19788 +Epoch: [33] [ 710/2138] eta: 1:08:31 lr: 9.969642397841836e-06 loss: 0.0185 (0.0197) time: 2.8177 data: 0.0024 max mem: 19788 +Epoch: [33] [ 720/2138] eta: 1:08:01 lr: 9.963347769318911e-06 loss: 0.0172 (0.0196) time: 2.8175 data: 0.0022 max mem: 19788 +Epoch: [33] [ 730/2138] eta: 1:07:31 lr: 9.95705269889708e-06 loss: 0.0164 (0.0196) time: 2.8218 data: 0.0023 max mem: 19788 +Epoch: [33] [ 740/2138] eta: 1:07:01 lr: 9.950757186234844e-06 loss: 0.0189 (0.0197) time: 2.8214 data: 0.0023 max mem: 19788 +Epoch: [33] [ 750/2138] eta: 1:06:31 lr: 9.944461230990224e-06 loss: 0.0205 (0.0197) time: 2.8165 data: 0.0022 max mem: 19788 +Epoch: [33] [ 760/2138] eta: 1:06:03 lr: 9.938164832820713e-06 loss: 0.0205 (0.0197) time: 2.8629 data: 0.0022 max mem: 19788 +Epoch: [33] [ 770/2138] eta: 1:05:36 lr: 9.931867991383318e-06 loss: 0.0185 (0.0197) time: 2.9362 data: 0.0025 max mem: 19788 +Epoch: [33] [ 780/2138] eta: 1:05:07 lr: 9.925570706334527e-06 loss: 0.0180 (0.0197) time: 2.9342 data: 0.0024 max mem: 19788 +Epoch: [33] [ 790/2138] eta: 1:04:38 lr: 9.919272977330315e-06 loss: 0.0170 (0.0196) time: 2.8663 data: 0.0024 max mem: 19788 +Epoch: [33] [ 800/2138] eta: 1:04:08 lr: 9.912974804026164e-06 loss: 0.0180 (0.0196) time: 2.8227 data: 0.0025 max mem: 19788 +Epoch: [33] [ 810/2138] eta: 1:03:39 lr: 9.906676186077025e-06 loss: 0.0187 (0.0196) time: 2.8273 data: 0.0027 max mem: 19788 +Epoch: [33] [ 820/2138] eta: 1:03:09 lr: 9.90037712313736e-06 loss: 0.0185 (0.0196) time: 2.8224 data: 0.0028 max mem: 19788 +Epoch: [33] [ 830/2138] eta: 1:02:39 lr: 9.894077614861092e-06 loss: 0.0162 (0.0196) time: 2.8183 data: 0.0025 max mem: 19788 +Epoch: [33] [ 840/2138] eta: 1:02:10 lr: 9.887777660901656e-06 loss: 0.0169 (0.0196) time: 2.8194 data: 0.0022 max mem: 19788 +Epoch: [33] [ 850/2138] eta: 1:01:40 lr: 9.881477260911947e-06 loss: 0.0183 (0.0196) time: 2.8196 data: 0.0022 max mem: 19788 +Epoch: [33] [ 860/2138] eta: 1:01:13 lr: 9.875176414544366e-06 loss: 0.0184 (0.0196) time: 2.9067 data: 0.0025 max mem: 19788 +Epoch: [33] [ 870/2138] eta: 1:00:45 lr: 9.868875121450777e-06 loss: 0.0177 (0.0196) time: 2.9527 data: 0.0028 max mem: 19788 +Epoch: [33] [ 880/2138] eta: 1:00:17 lr: 9.862573381282544e-06 loss: 0.0168 (0.0196) time: 2.9076 data: 0.0024 max mem: 19788 +Epoch: [33] [ 890/2138] eta: 0:59:47 lr: 9.85627119369049e-06 loss: 0.0179 (0.0196) time: 2.8628 data: 0.0022 max mem: 19788 +Epoch: [33] [ 900/2138] eta: 0:59:18 lr: 9.849968558324942e-06 loss: 0.0178 (0.0196) time: 2.8256 data: 0.0023 max mem: 19788 +Epoch: [33] [ 910/2138] eta: 0:58:48 lr: 9.843665474835675e-06 loss: 0.0171 (0.0196) time: 2.8203 data: 0.0021 max mem: 19788 +Epoch: [33] [ 920/2138] eta: 0:58:19 lr: 9.837361942871974e-06 loss: 0.0177 (0.0195) time: 2.8184 data: 0.0021 max mem: 19788 +Epoch: [33] [ 930/2138] eta: 0:57:49 lr: 9.831057962082568e-06 loss: 0.0189 (0.0196) time: 2.8221 data: 0.0023 max mem: 19788 +Epoch: [33] [ 940/2138] eta: 0:57:20 lr: 9.824753532115689e-06 loss: 0.0211 (0.0196) time: 2.8242 data: 0.0026 max mem: 19788 +Epoch: [33] [ 950/2138] eta: 0:56:51 lr: 9.818448652619013e-06 loss: 0.0178 (0.0196) time: 2.8559 data: 0.0026 max mem: 19788 +Epoch: [33] [ 960/2138] eta: 0:56:24 lr: 9.812143323239719e-06 loss: 0.0203 (0.0196) time: 2.9371 data: 0.0023 max mem: 19788 +Epoch: [33] [ 970/2138] eta: 0:55:57 lr: 9.805837543624427e-06 loss: 0.0206 (0.0196) time: 2.9990 data: 0.0022 max mem: 19788 +Epoch: [33] [ 980/2138] eta: 0:55:28 lr: 9.799531313419255e-06 loss: 0.0171 (0.0196) time: 2.9238 data: 0.0024 max mem: 19788 +Epoch: [33] [ 990/2138] eta: 0:54:59 lr: 9.79322463226976e-06 loss: 0.0167 (0.0196) time: 2.8275 data: 0.0023 max mem: 19788 +Epoch: [33] [1000/2138] eta: 0:54:29 lr: 9.786917499820999e-06 loss: 0.0164 (0.0195) time: 2.8194 data: 0.0022 max mem: 19788 +Epoch: [33] [1010/2138] eta: 0:54:00 lr: 9.780609915717462e-06 loss: 0.0164 (0.0196) time: 2.8194 data: 0.0025 max mem: 19788 +Epoch: [33] [1020/2138] eta: 0:53:31 lr: 9.774301879603134e-06 loss: 0.0163 (0.0195) time: 2.8185 data: 0.0029 max mem: 19788 +Epoch: [33] [1030/2138] eta: 0:53:01 lr: 9.767993391121439e-06 loss: 0.0159 (0.0195) time: 2.8209 data: 0.0029 max mem: 19788 +Epoch: [33] [1040/2138] eta: 0:52:32 lr: 9.761684449915285e-06 loss: 0.0185 (0.0195) time: 2.8190 data: 0.0027 max mem: 19788 +Epoch: [33] [1050/2138] eta: 0:52:05 lr: 9.75537505562702e-06 loss: 0.0201 (0.0196) time: 2.9085 data: 0.0026 max mem: 19788 +Epoch: [33] [1060/2138] eta: 0:51:37 lr: 9.749065207898476e-06 loss: 0.0199 (0.0196) time: 2.9712 data: 0.0026 max mem: 19788 +Epoch: [33] [1070/2138] eta: 0:51:08 lr: 9.742754906370924e-06 loss: 0.0188 (0.0195) time: 2.9365 data: 0.0029 max mem: 19788 +Epoch: [33] [1080/2138] eta: 0:50:39 lr: 9.736444150685095e-06 loss: 0.0173 (0.0195) time: 2.8754 data: 0.0030 max mem: 19788 +Epoch: [33] [1090/2138] eta: 0:50:10 lr: 9.730132940481193e-06 loss: 0.0182 (0.0195) time: 2.8226 data: 0.0025 max mem: 19788 +Epoch: [33] [1100/2138] eta: 0:49:41 lr: 9.723821275398855e-06 loss: 0.0188 (0.0195) time: 2.8227 data: 0.0023 max mem: 19788 +Epoch: [33] [1110/2138] eta: 0:49:12 lr: 9.717509155077199e-06 loss: 0.0188 (0.0195) time: 2.8273 data: 0.0024 max mem: 19788 +Epoch: [33] [1120/2138] eta: 0:48:42 lr: 9.711196579154761e-06 loss: 0.0190 (0.0195) time: 2.8262 data: 0.0026 max mem: 19788 +Epoch: [33] [1130/2138] eta: 0:48:13 lr: 9.704883547269567e-06 loss: 0.0167 (0.0195) time: 2.8223 data: 0.0027 max mem: 19788 +Epoch: [33] [1140/2138] eta: 0:47:44 lr: 9.698570059059059e-06 loss: 0.0180 (0.0195) time: 2.8331 data: 0.0025 max mem: 19788 +Epoch: [33] [1150/2138] eta: 0:47:17 lr: 9.692256114160158e-06 loss: 0.0177 (0.0195) time: 2.9258 data: 0.0022 max mem: 19788 +Epoch: [33] [1160/2138] eta: 0:46:49 lr: 9.685941712209206e-06 loss: 0.0166 (0.0195) time: 2.9831 data: 0.0022 max mem: 19788 +Epoch: [33] [1170/2138] eta: 0:46:20 lr: 9.679626852842015e-06 loss: 0.0184 (0.0195) time: 2.9165 data: 0.0025 max mem: 19788 +Epoch: [33] [1180/2138] eta: 0:45:51 lr: 9.673311535693824e-06 loss: 0.0191 (0.0195) time: 2.8488 data: 0.0028 max mem: 19788 +Epoch: [33] [1190/2138] eta: 0:45:22 lr: 9.666995760399333e-06 loss: 0.0183 (0.0195) time: 2.8215 data: 0.0026 max mem: 19788 +Epoch: [33] [1200/2138] eta: 0:44:53 lr: 9.660679526592668e-06 loss: 0.0169 (0.0195) time: 2.8350 data: 0.0026 max mem: 19788 +Epoch: [33] [1210/2138] eta: 0:44:24 lr: 9.654362833907418e-06 loss: 0.0180 (0.0195) time: 2.8301 data: 0.0027 max mem: 19788 +Epoch: [33] [1220/2138] eta: 0:43:55 lr: 9.648045681976585e-06 loss: 0.0178 (0.0195) time: 2.8162 data: 0.0028 max mem: 19788 +Epoch: [33] [1230/2138] eta: 0:43:26 lr: 9.641728070432639e-06 loss: 0.0176 (0.0195) time: 2.8218 data: 0.0028 max mem: 19788 +Epoch: [33] [1240/2138] eta: 0:42:58 lr: 9.635409998907463e-06 loss: 0.0175 (0.0195) time: 2.8918 data: 0.0025 max mem: 19788 +Epoch: [33] [1250/2138] eta: 0:42:30 lr: 9.6290914670324e-06 loss: 0.0175 (0.0195) time: 2.9812 data: 0.0024 max mem: 19788 +Epoch: [33] [1260/2138] eta: 0:42:02 lr: 9.622772474438203e-06 loss: 0.0172 (0.0194) time: 3.0066 data: 0.0026 max mem: 19788 +Epoch: [33] [1270/2138] eta: 0:41:33 lr: 9.616453020755089e-06 loss: 0.0168 (0.0194) time: 2.9149 data: 0.0027 max mem: 19788 +Epoch: [33] [1280/2138] eta: 0:41:04 lr: 9.610133105612674e-06 loss: 0.0180 (0.0194) time: 2.8209 data: 0.0027 max mem: 19788 +Epoch: [33] [1290/2138] eta: 0:40:35 lr: 9.603812728640043e-06 loss: 0.0190 (0.0194) time: 2.8196 data: 0.0023 max mem: 19788 +Epoch: [33] [1300/2138] eta: 0:40:06 lr: 9.597491889465672e-06 loss: 0.0190 (0.0194) time: 2.8173 data: 0.0022 max mem: 19788 +Epoch: [33] [1310/2138] eta: 0:39:37 lr: 9.591170587717504e-06 loss: 0.0170 (0.0194) time: 2.8129 data: 0.0023 max mem: 19788 +Epoch: [33] [1320/2138] eta: 0:39:08 lr: 9.584848823022875e-06 loss: 0.0179 (0.0194) time: 2.8152 data: 0.0022 max mem: 19788 +Epoch: [33] [1330/2138] eta: 0:38:39 lr: 9.57852659500858e-06 loss: 0.0179 (0.0194) time: 2.8283 data: 0.0021 max mem: 19788 +Epoch: [33] [1340/2138] eta: 0:38:11 lr: 9.57220390330081e-06 loss: 0.0190 (0.0194) time: 2.9486 data: 0.0025 max mem: 19788 +Epoch: [33] [1350/2138] eta: 0:37:43 lr: 9.565880747525205e-06 loss: 0.0218 (0.0194) time: 2.9811 data: 0.0024 max mem: 19788 +Epoch: [33] [1360/2138] eta: 0:37:14 lr: 9.559557127306802e-06 loss: 0.0190 (0.0194) time: 2.9130 data: 0.0021 max mem: 19788 +Epoch: [33] [1370/2138] eta: 0:36:46 lr: 9.553233042270087e-06 loss: 0.0181 (0.0194) time: 2.9335 data: 0.0023 max mem: 19788 +Epoch: [33] [1380/2138] eta: 0:36:17 lr: 9.546908492038947e-06 loss: 0.0203 (0.0194) time: 2.9369 data: 0.0023 max mem: 19788 +Epoch: [33] [1390/2138] eta: 0:35:49 lr: 9.540583476236683e-06 loss: 0.0189 (0.0194) time: 2.9232 data: 0.0021 max mem: 19788 +Epoch: [33] [1400/2138] eta: 0:35:20 lr: 9.534257994486037e-06 loss: 0.0171 (0.0194) time: 2.8731 data: 0.0023 max mem: 19788 +Epoch: [33] [1410/2138] eta: 0:34:51 lr: 9.527932046409142e-06 loss: 0.0166 (0.0194) time: 2.8326 data: 0.0024 max mem: 19788 +Epoch: [33] [1420/2138] eta: 0:34:22 lr: 9.521605631627564e-06 loss: 0.0181 (0.0194) time: 2.8302 data: 0.0023 max mem: 19788 +Epoch: [33] [1430/2138] eta: 0:33:53 lr: 9.515278749762264e-06 loss: 0.0191 (0.0194) time: 2.8361 data: 0.0027 max mem: 19788 +Epoch: [33] [1440/2138] eta: 0:33:24 lr: 9.50895140043364e-06 loss: 0.0206 (0.0194) time: 2.8380 data: 0.0028 max mem: 19788 +Epoch: [33] [1450/2138] eta: 0:32:55 lr: 9.50262358326147e-06 loss: 0.0204 (0.0195) time: 2.8364 data: 0.0026 max mem: 19788 +Epoch: [33] [1460/2138] eta: 0:32:27 lr: 9.496295297864974e-06 loss: 0.0188 (0.0195) time: 2.8500 data: 0.0024 max mem: 19788 +Epoch: [33] [1470/2138] eta: 0:31:58 lr: 9.489966543862745e-06 loss: 0.0171 (0.0195) time: 2.8826 data: 0.0021 max mem: 19788 +Epoch: [33] [1480/2138] eta: 0:31:30 lr: 9.483637320872816e-06 loss: 0.0166 (0.0195) time: 2.9336 data: 0.0023 max mem: 19788 +Epoch: [33] [1490/2138] eta: 0:31:01 lr: 9.477307628512598e-06 loss: 0.0176 (0.0195) time: 2.9156 data: 0.0025 max mem: 19788 +Epoch: [33] [1500/2138] eta: 0:30:32 lr: 9.470977466398926e-06 loss: 0.0198 (0.0195) time: 2.8497 data: 0.0027 max mem: 19788 +Epoch: [33] [1510/2138] eta: 0:30:03 lr: 9.464646834148023e-06 loss: 0.0190 (0.0195) time: 2.8288 data: 0.0027 max mem: 19788 +Epoch: [33] [1520/2138] eta: 0:29:34 lr: 9.458315731375523e-06 loss: 0.0179 (0.0195) time: 2.8254 data: 0.0025 max mem: 19788 +Epoch: [33] [1530/2138] eta: 0:29:05 lr: 9.451984157696447e-06 loss: 0.0190 (0.0195) time: 2.8319 data: 0.0023 max mem: 19788 +Epoch: [33] [1540/2138] eta: 0:28:37 lr: 9.445652112725236e-06 loss: 0.0193 (0.0195) time: 2.8385 data: 0.0022 max mem: 19788 +Epoch: [33] [1550/2138] eta: 0:28:08 lr: 9.4393195960757e-06 loss: 0.0180 (0.0195) time: 2.8300 data: 0.0021 max mem: 19788 +Epoch: [33] [1560/2138] eta: 0:27:39 lr: 9.432986607361071e-06 loss: 0.0185 (0.0195) time: 2.8416 data: 0.0022 max mem: 19788 +Epoch: [33] [1570/2138] eta: 0:27:10 lr: 9.42665314619395e-06 loss: 0.0197 (0.0195) time: 2.8998 data: 0.0023 max mem: 19788 +Epoch: [33] [1580/2138] eta: 0:26:42 lr: 9.42031921218636e-06 loss: 0.0182 (0.0195) time: 2.9399 data: 0.0023 max mem: 19788 +Epoch: [33] [1590/2138] eta: 0:26:13 lr: 9.413984804949682e-06 loss: 0.0187 (0.0195) time: 2.8857 data: 0.0022 max mem: 19788 +Epoch: [33] [1600/2138] eta: 0:25:44 lr: 9.40764992409472e-06 loss: 0.0199 (0.0195) time: 2.8354 data: 0.0021 max mem: 19788 +Epoch: [33] [1610/2138] eta: 0:25:15 lr: 9.401314569231632e-06 loss: 0.0199 (0.0195) time: 2.8359 data: 0.0022 max mem: 19788 +Epoch: [33] [1620/2138] eta: 0:24:47 lr: 9.39497873997e-06 loss: 0.0163 (0.0195) time: 2.8396 data: 0.0025 max mem: 19788 +Epoch: [33] [1630/2138] eta: 0:24:18 lr: 9.388642435918756e-06 loss: 0.0161 (0.0195) time: 2.8484 data: 0.0025 max mem: 19788 +Epoch: [33] [1640/2138] eta: 0:23:49 lr: 9.382305656686243e-06 loss: 0.0182 (0.0195) time: 2.8463 data: 0.0026 max mem: 19788 +Epoch: [33] [1650/2138] eta: 0:23:20 lr: 9.375968401880171e-06 loss: 0.0192 (0.0195) time: 2.8330 data: 0.0026 max mem: 19788 +Epoch: [33] [1660/2138] eta: 0:22:52 lr: 9.369630671107644e-06 loss: 0.0202 (0.0195) time: 2.8487 data: 0.0025 max mem: 19788 +Epoch: [33] [1670/2138] eta: 0:22:23 lr: 9.36329246397513e-06 loss: 0.0180 (0.0195) time: 2.8865 data: 0.0026 max mem: 19788 +Epoch: [33] [1680/2138] eta: 0:21:54 lr: 9.35695378008849e-06 loss: 0.0175 (0.0195) time: 2.9006 data: 0.0023 max mem: 19788 +Epoch: [33] [1690/2138] eta: 0:21:26 lr: 9.350614619052957e-06 loss: 0.0175 (0.0195) time: 2.8690 data: 0.0023 max mem: 19788 +Epoch: [33] [1700/2138] eta: 0:20:57 lr: 9.344274980473127e-06 loss: 0.0171 (0.0195) time: 2.8320 data: 0.0024 max mem: 19788 +Epoch: [33] [1710/2138] eta: 0:20:28 lr: 9.337934863952997e-06 loss: 0.0176 (0.0195) time: 2.8413 data: 0.0024 max mem: 19788 +Epoch: [33] [1720/2138] eta: 0:19:59 lr: 9.331594269095905e-06 loss: 0.0199 (0.0195) time: 2.8446 data: 0.0025 max mem: 19788 +Epoch: [33] [1730/2138] eta: 0:19:30 lr: 9.325253195504593e-06 loss: 0.0187 (0.0195) time: 2.8403 data: 0.0024 max mem: 19788 +Epoch: [33] [1740/2138] eta: 0:19:02 lr: 9.318911642781142e-06 loss: 0.0187 (0.0195) time: 2.8412 data: 0.0022 max mem: 19788 +Epoch: [33] [1750/2138] eta: 0:18:33 lr: 9.312569610527027e-06 loss: 0.0197 (0.0195) time: 2.8378 data: 0.0023 max mem: 19788 +Epoch: [33] [1760/2138] eta: 0:18:04 lr: 9.306227098343063e-06 loss: 0.0175 (0.0195) time: 2.8526 data: 0.0023 max mem: 19788 +Epoch: [33] [1770/2138] eta: 0:17:36 lr: 9.299884105829459e-06 loss: 0.0174 (0.0195) time: 2.8920 data: 0.0024 max mem: 19788 +Epoch: [33] [1780/2138] eta: 0:17:07 lr: 9.29354063258576e-06 loss: 0.0172 (0.0195) time: 2.9012 data: 0.0028 max mem: 19788 +Epoch: [33] [1790/2138] eta: 0:16:38 lr: 9.287196678210899e-06 loss: 0.0172 (0.0195) time: 2.8582 data: 0.0028 max mem: 19788 +Epoch: [33] [1800/2138] eta: 0:16:09 lr: 9.280852242303146e-06 loss: 0.0213 (0.0195) time: 2.8381 data: 0.0025 max mem: 19788 +Epoch: [33] [1810/2138] eta: 0:15:41 lr: 9.274507324460155e-06 loss: 0.0206 (0.0195) time: 2.8435 data: 0.0025 max mem: 19788 +Epoch: [33] [1820/2138] eta: 0:15:12 lr: 9.268161924278908e-06 loss: 0.0173 (0.0195) time: 2.8392 data: 0.0024 max mem: 19788 +Epoch: [33] [1830/2138] eta: 0:14:43 lr: 9.261816041355774e-06 loss: 0.0173 (0.0195) time: 2.8352 data: 0.0023 max mem: 19788 +Epoch: [33] [1840/2138] eta: 0:14:14 lr: 9.25546967528645e-06 loss: 0.0188 (0.0195) time: 2.8466 data: 0.0024 max mem: 19788 +Epoch: [33] [1850/2138] eta: 0:13:46 lr: 9.249122825666009e-06 loss: 0.0205 (0.0195) time: 2.8545 data: 0.0025 max mem: 19788 +Epoch: [33] [1860/2138] eta: 0:13:17 lr: 9.242775492088852e-06 loss: 0.0194 (0.0195) time: 2.8777 data: 0.0026 max mem: 19788 +Epoch: [33] [1870/2138] eta: 0:12:48 lr: 9.236427674148755e-06 loss: 0.0186 (0.0195) time: 2.9024 data: 0.0024 max mem: 19788 +Epoch: [33] [1880/2138] eta: 0:12:20 lr: 9.23007937143882e-06 loss: 0.0171 (0.0195) time: 2.9097 data: 0.0024 max mem: 19788 +Epoch: [33] [1890/2138] eta: 0:11:51 lr: 9.223730583551516e-06 loss: 0.0158 (0.0195) time: 2.8728 data: 0.0026 max mem: 19788 +Epoch: [33] [1900/2138] eta: 0:11:22 lr: 9.217381310078635e-06 loss: 0.0169 (0.0195) time: 2.8393 data: 0.0025 max mem: 19788 +Epoch: [33] [1910/2138] eta: 0:10:54 lr: 9.211031550611338e-06 loss: 0.0189 (0.0195) time: 2.8376 data: 0.0026 max mem: 19788 +Epoch: [33] [1920/2138] eta: 0:10:25 lr: 9.204681304740106e-06 loss: 0.0176 (0.0194) time: 2.8304 data: 0.0025 max mem: 19788 +Epoch: [33] [1930/2138] eta: 0:09:56 lr: 9.19833057205478e-06 loss: 0.0178 (0.0194) time: 2.8313 data: 0.0022 max mem: 19788 +Epoch: [33] [1940/2138] eta: 0:09:27 lr: 9.191979352144519e-06 loss: 0.0204 (0.0195) time: 2.8298 data: 0.0022 max mem: 19788 +Epoch: [33] [1950/2138] eta: 0:08:59 lr: 9.185627644597844e-06 loss: 0.0187 (0.0195) time: 2.8314 data: 0.0023 max mem: 19788 +Epoch: [33] [1960/2138] eta: 0:08:30 lr: 9.179275449002584e-06 loss: 0.0187 (0.0194) time: 2.8616 data: 0.0022 max mem: 19788 +Epoch: [33] [1970/2138] eta: 0:08:01 lr: 9.172922764945934e-06 loss: 0.0161 (0.0194) time: 2.9210 data: 0.0024 max mem: 19788 +Epoch: [33] [1980/2138] eta: 0:07:33 lr: 9.166569592014391e-06 loss: 0.0171 (0.0195) time: 2.9298 data: 0.0024 max mem: 19788 +Epoch: [33] [1990/2138] eta: 0:07:04 lr: 9.160215929793811e-06 loss: 0.0190 (0.0195) time: 2.8756 data: 0.0025 max mem: 19788 +Epoch: [33] [2000/2138] eta: 0:06:35 lr: 9.153861777869358e-06 loss: 0.0185 (0.0195) time: 2.8347 data: 0.0028 max mem: 19788 +Epoch: [33] [2010/2138] eta: 0:06:07 lr: 9.14750713582553e-06 loss: 0.0192 (0.0194) time: 2.8287 data: 0.0027 max mem: 19788 +Epoch: [33] [2020/2138] eta: 0:05:38 lr: 9.141152003246164e-06 loss: 0.0199 (0.0195) time: 2.8299 data: 0.0025 max mem: 19788 +Epoch: [33] [2030/2138] eta: 0:05:09 lr: 9.1347963797144e-06 loss: 0.0187 (0.0195) time: 2.8411 data: 0.0025 max mem: 19788 +Epoch: [33] [2040/2138] eta: 0:04:41 lr: 9.128440264812723e-06 loss: 0.0184 (0.0195) time: 2.8523 data: 0.0024 max mem: 19788 +Epoch: [33] [2050/2138] eta: 0:04:12 lr: 9.122083658122922e-06 loss: 0.0186 (0.0195) time: 2.8643 data: 0.0025 max mem: 19788 +Epoch: [33] [2060/2138] eta: 0:03:43 lr: 9.115726559226121e-06 loss: 0.0175 (0.0195) time: 2.9191 data: 0.0025 max mem: 19788 +Epoch: [33] [2070/2138] eta: 0:03:15 lr: 9.109368967702745e-06 loss: 0.0169 (0.0194) time: 2.9585 data: 0.0026 max mem: 19788 +Epoch: [33] [2080/2138] eta: 0:02:46 lr: 9.103010883132558e-06 loss: 0.0169 (0.0194) time: 2.9160 data: 0.0027 max mem: 19788 +Epoch: [33] [2090/2138] eta: 0:02:17 lr: 9.096652305094614e-06 loss: 0.0181 (0.0194) time: 2.8569 data: 0.0026 max mem: 19788 +Epoch: [33] [2100/2138] eta: 0:01:49 lr: 9.090293233167305e-06 loss: 0.0181 (0.0194) time: 2.8300 data: 0.0023 max mem: 19788 +Epoch: [33] [2110/2138] eta: 0:01:20 lr: 9.083933666928311e-06 loss: 0.0203 (0.0195) time: 2.8331 data: 0.0021 max mem: 19788 +Epoch: [33] [2120/2138] eta: 0:00:51 lr: 9.077573605954647e-06 loss: 0.0225 (0.0195) time: 2.8356 data: 0.0021 max mem: 19788 +Epoch: [33] [2130/2138] eta: 0:00:22 lr: 9.071213049822608e-06 loss: 0.0224 (0.0195) time: 2.8212 data: 0.0020 max mem: 19788 +Epoch: [33] Total time: 1:42:12 +Test: [ 0/21770] eta: 15:23:01 time: 2.5439 data: 2.4402 max mem: 19788 +Test: [ 100/21770] eta: 0:25:38 time: 0.0429 data: 0.0013 max mem: 19788 +Test: [ 200/21770] eta: 0:21:13 time: 0.0486 data: 0.0017 max mem: 19788 +Test: [ 300/21770] eta: 0:19:36 time: 0.0540 data: 0.0014 max mem: 19788 +Test: [ 400/21770] eta: 0:18:51 time: 0.0429 data: 0.0013 max mem: 19788 +Test: [ 500/21770] eta: 0:18:38 time: 0.0525 data: 0.0018 max mem: 19788 +Test: [ 600/21770] eta: 0:18:20 time: 0.0434 data: 0.0014 max mem: 19788 +Test: [ 700/21770] eta: 0:17:48 time: 0.0436 data: 0.0015 max mem: 19788 +Test: [ 800/21770] eta: 0:17:28 time: 0.0431 data: 0.0013 max mem: 19788 +Test: [ 900/21770] eta: 0:17:07 time: 0.0434 data: 0.0015 max mem: 19788 +Test: [ 1000/21770] eta: 0:16:53 time: 0.0457 data: 0.0014 max mem: 19788 +Test: [ 1100/21770] eta: 0:16:40 time: 0.0492 data: 0.0016 max mem: 19788 +Test: [ 1200/21770] eta: 0:16:33 time: 0.0482 data: 0.0016 max mem: 19788 +Test: [ 1300/21770] eta: 0:16:26 time: 0.0435 data: 0.0015 max mem: 19788 +Test: [ 1400/21770] eta: 0:16:15 time: 0.0432 data: 0.0015 max mem: 19788 +Test: [ 1500/21770] eta: 0:16:04 time: 0.0431 data: 0.0015 max mem: 19788 +Test: [ 1600/21770] eta: 0:15:57 time: 0.0434 data: 0.0016 max mem: 19788 +Test: [ 1700/21770] eta: 0:15:50 time: 0.0431 data: 0.0015 max mem: 19788 +Test: [ 1800/21770] eta: 0:15:42 time: 0.0441 data: 0.0016 max mem: 19788 +Test: [ 1900/21770] eta: 0:15:35 time: 0.0493 data: 0.0017 max mem: 19788 +Test: [ 2000/21770] eta: 0:15:28 time: 0.0430 data: 0.0014 max mem: 19788 +Test: [ 2100/21770] eta: 0:15:25 time: 0.0497 data: 0.0016 max mem: 19788 +Test: [ 2200/21770] eta: 0:15:20 time: 0.0431 data: 0.0013 max mem: 19788 +Test: [ 2300/21770] eta: 0:15:13 time: 0.0421 data: 0.0015 max mem: 19788 +Test: [ 2400/21770] eta: 0:15:06 time: 0.0458 data: 0.0015 max mem: 19788 +Test: [ 2500/21770] eta: 0:14:59 time: 0.0423 data: 0.0013 max mem: 19788 +Test: [ 2600/21770] eta: 0:14:53 time: 0.0480 data: 0.0016 max mem: 19788 +Test: [ 2700/21770] eta: 0:14:47 time: 0.0428 data: 0.0016 max mem: 19788 +Test: [ 2800/21770] eta: 0:14:40 time: 0.0458 data: 0.0015 max mem: 19788 +Test: [ 2900/21770] eta: 0:14:35 time: 0.0437 data: 0.0015 max mem: 19788 +Test: [ 3000/21770] eta: 0:14:31 time: 0.0534 data: 0.0015 max mem: 19788 +Test: [ 3100/21770] eta: 0:14:25 time: 0.0441 data: 0.0016 max mem: 19788 +Test: [ 3200/21770] eta: 0:14:21 time: 0.0468 data: 0.0015 max mem: 19788 +Test: [ 3300/21770] eta: 0:14:16 time: 0.0479 data: 0.0017 max mem: 19788 +Test: [ 3400/21770] eta: 0:14:13 time: 0.0445 data: 0.0016 max mem: 19788 +Test: [ 3500/21770] eta: 0:14:09 time: 0.0521 data: 0.0015 max mem: 19788 +Test: [ 3600/21770] eta: 0:14:05 time: 0.0444 data: 0.0015 max mem: 19788 +Test: [ 3700/21770] eta: 0:14:00 time: 0.0441 data: 0.0014 max mem: 19788 +Test: [ 3800/21770] eta: 0:13:55 time: 0.0445 data: 0.0014 max mem: 19788 +Test: [ 3900/21770] eta: 0:13:50 time: 0.0499 data: 0.0016 max mem: 19788 +Test: [ 4000/21770] eta: 0:13:47 time: 0.0540 data: 0.0016 max mem: 19788 +Test: [ 4100/21770] eta: 0:13:41 time: 0.0500 data: 0.0016 max mem: 19788 +Test: [ 4200/21770] eta: 0:13:37 time: 0.0486 data: 0.0015 max mem: 19788 +Test: [ 4300/21770] eta: 0:13:34 time: 0.0510 data: 0.0018 max mem: 19788 +Test: [ 4400/21770] eta: 0:13:30 time: 0.0486 data: 0.0017 max mem: 19788 +Test: [ 4500/21770] eta: 0:13:25 time: 0.0430 data: 0.0016 max mem: 19788 +Test: [ 4600/21770] eta: 0:13:20 time: 0.0437 data: 0.0016 max mem: 19788 +Test: [ 4700/21770] eta: 0:13:15 time: 0.0457 data: 0.0015 max mem: 19788 +Test: [ 4800/21770] eta: 0:13:10 time: 0.0413 data: 0.0014 max mem: 19788 +Test: [ 4900/21770] eta: 0:13:06 time: 0.0531 data: 0.0019 max mem: 19788 +Test: [ 5000/21770] eta: 0:13:01 time: 0.0437 data: 0.0015 max mem: 19788 +Test: [ 5100/21770] eta: 0:12:56 time: 0.0445 data: 0.0016 max mem: 19788 +Test: [ 5200/21770] eta: 0:12:53 time: 0.0508 data: 0.0017 max mem: 19788 +Test: [ 5300/21770] eta: 0:12:47 time: 0.0451 data: 0.0016 max mem: 19788 +Test: [ 5400/21770] eta: 0:12:43 time: 0.0457 data: 0.0015 max mem: 19788 +Test: [ 5500/21770] eta: 0:12:38 time: 0.0435 data: 0.0014 max mem: 19788 +Test: [ 5600/21770] eta: 0:12:33 time: 0.0433 data: 0.0015 max mem: 19788 +Test: [ 5700/21770] eta: 0:12:27 time: 0.0433 data: 0.0014 max mem: 19788 +Test: [ 5800/21770] eta: 0:12:23 time: 0.0516 data: 0.0018 max mem: 19788 +Test: [ 5900/21770] eta: 0:12:18 time: 0.0432 data: 0.0014 max mem: 19788 +Test: [ 6000/21770] eta: 0:12:13 time: 0.0429 data: 0.0015 max mem: 19788 +Test: [ 6100/21770] eta: 0:12:08 time: 0.0484 data: 0.0016 max mem: 19788 +Test: [ 6200/21770] eta: 0:12:03 time: 0.0517 data: 0.0017 max mem: 19788 +Test: [ 6300/21770] eta: 0:12:00 time: 0.0452 data: 0.0016 max mem: 19788 +Test: [ 6400/21770] eta: 0:11:55 time: 0.0541 data: 0.0014 max mem: 19788 +Test: [ 6500/21770] eta: 0:11:50 time: 0.0442 data: 0.0015 max mem: 19788 +Test: [ 6600/21770] eta: 0:11:45 time: 0.0461 data: 0.0015 max mem: 19788 +Test: [ 6700/21770] eta: 0:11:42 time: 0.0510 data: 0.0018 max mem: 19788 +Test: [ 6800/21770] eta: 0:11:38 time: 0.0509 data: 0.0018 max mem: 19788 +Test: [ 6900/21770] eta: 0:11:33 time: 0.0485 data: 0.0016 max mem: 19788 +Test: [ 7000/21770] eta: 0:11:28 time: 0.0508 data: 0.0017 max mem: 19788 +Test: [ 7100/21770] eta: 0:11:23 time: 0.0482 data: 0.0016 max mem: 19788 +Test: [ 7200/21770] eta: 0:11:19 time: 0.0500 data: 0.0016 max mem: 19788 +Test: [ 7300/21770] eta: 0:11:14 time: 0.0471 data: 0.0016 max mem: 19788 +Test: [ 7400/21770] eta: 0:11:09 time: 0.0449 data: 0.0017 max mem: 19788 +Test: [ 7500/21770] eta: 0:11:04 time: 0.0446 data: 0.0014 max mem: 19788 +Test: [ 7600/21770] eta: 0:11:00 time: 0.0476 data: 0.0015 max mem: 19788 +Test: [ 7700/21770] eta: 0:10:56 time: 0.0535 data: 0.0019 max mem: 19788 +Test: [ 7800/21770] eta: 0:10:51 time: 0.0434 data: 0.0014 max mem: 19788 +Test: [ 7900/21770] eta: 0:10:46 time: 0.0547 data: 0.0016 max mem: 19788 +Test: [ 8000/21770] eta: 0:10:42 time: 0.0494 data: 0.0017 max mem: 19788 +Test: [ 8100/21770] eta: 0:10:37 time: 0.0529 data: 0.0018 max mem: 19788 +Test: [ 8200/21770] eta: 0:10:33 time: 0.0451 data: 0.0016 max mem: 19788 +Test: [ 8300/21770] eta: 0:10:29 time: 0.0500 data: 0.0017 max mem: 19788 +Test: [ 8400/21770] eta: 0:10:24 time: 0.0502 data: 0.0018 max mem: 19788 +Test: [ 8500/21770] eta: 0:10:19 time: 0.0463 data: 0.0015 max mem: 19788 +Test: [ 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time: 0.0449 data: 0.0014 max mem: 19788 +Test: [10000/21770] eta: 0:09:08 time: 0.0492 data: 0.0017 max mem: 19788 +Test: [10100/21770] eta: 0:09:03 time: 0.0528 data: 0.0017 max mem: 19788 +Test: [10200/21770] eta: 0:08:58 time: 0.0513 data: 0.0017 max mem: 19788 +Test: [10300/21770] eta: 0:08:54 time: 0.0451 data: 0.0015 max mem: 19788 +Test: [10400/21770] eta: 0:08:49 time: 0.0444 data: 0.0015 max mem: 19788 +Test: [10500/21770] eta: 0:08:45 time: 0.0518 data: 0.0018 max mem: 19788 +Test: [10600/21770] eta: 0:08:40 time: 0.0463 data: 0.0015 max mem: 19788 +Test: [10700/21770] eta: 0:08:36 time: 0.0486 data: 0.0017 max mem: 19788 +Test: [10800/21770] eta: 0:08:31 time: 0.0434 data: 0.0014 max mem: 19788 +Test: [10900/21770] eta: 0:08:26 time: 0.0445 data: 0.0014 max mem: 19788 +Test: [11000/21770] eta: 0:08:22 time: 0.0516 data: 0.0015 max mem: 19788 +Test: [11100/21770] eta: 0:08:17 time: 0.0451 data: 0.0014 max mem: 19788 +Test: [11200/21770] eta: 0:08:12 time: 0.0439 data: 0.0016 max mem: 19788 +Test: [11300/21770] eta: 0:08:08 time: 0.0466 data: 0.0015 max mem: 19788 +Test: [11400/21770] eta: 0:08:03 time: 0.0444 data: 0.0015 max mem: 19788 +Test: [11500/21770] eta: 0:07:58 time: 0.0443 data: 0.0016 max mem: 19788 +Test: [11600/21770] eta: 0:07:54 time: 0.0442 data: 0.0016 max mem: 19788 +Test: [11700/21770] eta: 0:07:49 time: 0.0462 data: 0.0015 max mem: 19788 +Test: [11800/21770] eta: 0:07:44 time: 0.0440 data: 0.0015 max mem: 19788 +Test: [11900/21770] eta: 0:07:40 time: 0.0454 data: 0.0014 max mem: 19788 +Test: [12000/21770] eta: 0:07:35 time: 0.0448 data: 0.0013 max mem: 19788 +Test: [12100/21770] eta: 0:07:30 time: 0.0454 data: 0.0013 max mem: 19788 +Test: [12200/21770] eta: 0:07:26 time: 0.0456 data: 0.0014 max mem: 19788 +Test: [12300/21770] eta: 0:07:21 time: 0.0495 data: 0.0018 max mem: 19788 +Test: [12400/21770] eta: 0:07:17 time: 0.0523 data: 0.0018 max mem: 19788 +Test: [12500/21770] eta: 0:07:12 time: 0.0430 data: 0.0014 max mem: 19788 +Test: [12600/21770] eta: 0:07:07 time: 0.0437 data: 0.0015 max mem: 19788 +Test: [12700/21770] eta: 0:07:02 time: 0.0494 data: 0.0016 max mem: 19788 +Test: [12800/21770] eta: 0:06:58 time: 0.0438 data: 0.0015 max mem: 19788 +Test: [12900/21770] eta: 0:06:53 time: 0.0471 data: 0.0015 max mem: 19788 +Test: [13000/21770] eta: 0:06:49 time: 0.0522 data: 0.0018 max mem: 19788 +Test: [13100/21770] eta: 0:06:44 time: 0.0500 data: 0.0017 max mem: 19788 +Test: [13200/21770] eta: 0:06:40 time: 0.0445 data: 0.0017 max mem: 19788 +Test: [13300/21770] eta: 0:06:35 time: 0.0523 data: 0.0017 max mem: 19788 +Test: [13400/21770] eta: 0:06:30 time: 0.0465 data: 0.0015 max mem: 19788 +Test: [13500/21770] eta: 0:06:26 time: 0.0476 data: 0.0015 max mem: 19788 +Test: [13600/21770] eta: 0:06:21 time: 0.0495 data: 0.0016 max mem: 19788 +Test: [13700/21770] eta: 0:06:17 time: 0.0440 data: 0.0015 max mem: 19788 +Test: [13800/21770] eta: 0:06:12 time: 0.0475 data: 0.0017 max mem: 19788 +Test: [13900/21770] eta: 0:06:07 time: 0.0496 data: 0.0018 max mem: 19788 +Test: [14000/21770] eta: 0:06:02 time: 0.0436 data: 0.0016 max mem: 19788 +Test: [14100/21770] eta: 0:05:58 time: 0.0427 data: 0.0013 max mem: 19788 +Test: [14200/21770] eta: 0:05:53 time: 0.0504 data: 0.0017 max mem: 19788 +Test: [14300/21770] eta: 0:05:49 time: 0.0531 data: 0.0016 max mem: 19788 +Test: [14400/21770] eta: 0:05:44 time: 0.0501 data: 0.0016 max mem: 19788 +Test: [14500/21770] eta: 0:05:39 time: 0.0439 data: 0.0015 max mem: 19788 +Test: [14600/21770] eta: 0:05:35 time: 0.0444 data: 0.0015 max mem: 19788 +Test: [14700/21770] eta: 0:05:30 time: 0.0448 data: 0.0014 max mem: 19788 +Test: [14800/21770] eta: 0:05:25 time: 0.0436 data: 0.0014 max mem: 19788 +Test: [14900/21770] eta: 0:05:20 time: 0.0516 data: 0.0019 max mem: 19788 +Test: [15000/21770] eta: 0:05:16 time: 0.0435 data: 0.0014 max mem: 19788 +Test: [15100/21770] eta: 0:05:11 time: 0.0500 data: 0.0016 max mem: 19788 +Test: [15200/21770] eta: 0:05:06 time: 0.0444 data: 0.0014 max mem: 19788 +Test: [15300/21770] eta: 0:05:02 time: 0.0466 data: 0.0017 max mem: 19788 +Test: [15400/21770] eta: 0:04:57 time: 0.0441 data: 0.0013 max mem: 19788 +Test: [15500/21770] eta: 0:04:52 time: 0.0472 data: 0.0017 max mem: 19788 +Test: [15600/21770] eta: 0:04:48 time: 0.0476 data: 0.0018 max mem: 19788 +Test: [15700/21770] eta: 0:04:43 time: 0.0533 data: 0.0016 max mem: 19788 +Test: [15800/21770] eta: 0:04:38 time: 0.0531 data: 0.0018 max mem: 19788 +Test: [15900/21770] eta: 0:04:34 time: 0.0438 data: 0.0014 max mem: 19788 +Test: [16000/21770] eta: 0:04:29 time: 0.0458 data: 0.0016 max mem: 19788 +Test: [16100/21770] eta: 0:04:24 time: 0.0448 data: 0.0015 max mem: 19788 +Test: [16200/21770] eta: 0:04:20 time: 0.0462 data: 0.0015 max mem: 19788 +Test: [16300/21770] eta: 0:04:15 time: 0.0435 data: 0.0015 max mem: 19788 +Test: [16400/21770] eta: 0:04:10 time: 0.0482 data: 0.0015 max mem: 19788 +Test: [16500/21770] eta: 0:04:06 time: 0.0480 data: 0.0016 max mem: 19788 +Test: [16600/21770] eta: 0:04:01 time: 0.0435 data: 0.0014 max mem: 19788 +Test: [16700/21770] eta: 0:03:56 time: 0.0527 data: 0.0017 max mem: 19788 +Test: [16800/21770] eta: 0:03:52 time: 0.0442 data: 0.0015 max mem: 19788 +Test: [16900/21770] eta: 0:03:47 time: 0.0474 data: 0.0016 max mem: 19788 +Test: [17000/21770] eta: 0:03:42 time: 0.0442 data: 0.0016 max mem: 19788 +Test: [17100/21770] eta: 0:03:37 time: 0.0436 data: 0.0015 max mem: 19788 +Test: [17200/21770] eta: 0:03:33 time: 0.0433 data: 0.0015 max mem: 19788 +Test: [17300/21770] eta: 0:03:28 time: 0.0531 data: 0.0018 max mem: 19788 +Test: [17400/21770] eta: 0:03:24 time: 0.0427 data: 0.0014 max mem: 19788 +Test: [17500/21770] eta: 0:03:19 time: 0.0496 data: 0.0017 max mem: 19788 +Test: [17600/21770] eta: 0:03:14 time: 0.0466 data: 0.0016 max mem: 19788 +Test: [17700/21770] eta: 0:03:10 time: 0.0434 data: 0.0014 max mem: 19788 +Test: [17800/21770] eta: 0:03:05 time: 0.0433 data: 0.0017 max mem: 19788 +Test: [17900/21770] eta: 0:03:00 time: 0.0454 data: 0.0015 max mem: 19788 +Test: [18000/21770] eta: 0:02:55 time: 0.0500 data: 0.0017 max mem: 19788 +Test: [18100/21770] eta: 0:02:51 time: 0.0501 data: 0.0018 max mem: 19788 +Test: [18200/21770] eta: 0:02:46 time: 0.0437 data: 0.0015 max mem: 19788 +Test: [18300/21770] eta: 0:02:41 time: 0.0454 data: 0.0015 max mem: 19788 +Test: [18400/21770] eta: 0:02:37 time: 0.0533 data: 0.0018 max mem: 19788 +Test: [18500/21770] eta: 0:02:32 time: 0.0444 data: 0.0017 max mem: 19788 +Test: [18600/21770] eta: 0:02:28 time: 0.0422 data: 0.0015 max mem: 19788 +Test: [18700/21770] eta: 0:02:23 time: 0.0442 data: 0.0015 max mem: 19788 +Test: [18800/21770] eta: 0:02:18 time: 0.0441 data: 0.0015 max mem: 19788 +Test: [18900/21770] eta: 0:02:14 time: 0.0528 data: 0.0018 max mem: 19788 +Test: [19000/21770] eta: 0:02:09 time: 0.0442 data: 0.0013 max mem: 19788 +Test: [19100/21770] eta: 0:02:04 time: 0.0523 data: 0.0017 max mem: 19788 +Test: [19200/21770] eta: 0:02:00 time: 0.0527 data: 0.0017 max mem: 19788 +Test: [19300/21770] eta: 0:01:55 time: 0.0474 data: 0.0015 max mem: 19788 +Test: [19400/21770] eta: 0:01:50 time: 0.0437 data: 0.0014 max mem: 19788 +Test: [19500/21770] eta: 0:01:46 time: 0.0503 data: 0.0017 max mem: 19788 +Test: [19600/21770] eta: 0:01:41 time: 0.0522 data: 0.0016 max mem: 19788 +Test: [19700/21770] eta: 0:01:36 time: 0.0449 data: 0.0016 max mem: 19788 +Test: [19800/21770] eta: 0:01:32 time: 0.0526 data: 0.0018 max mem: 19788 +Test: [19900/21770] eta: 0:01:27 time: 0.0457 data: 0.0016 max mem: 19788 +Test: [20000/21770] eta: 0:01:22 time: 0.0437 data: 0.0015 max mem: 19788 +Test: [20100/21770] eta: 0:01:18 time: 0.0518 data: 0.0015 max mem: 19788 +Test: [20200/21770] eta: 0:01:13 time: 0.0538 data: 0.0018 max mem: 19788 +Test: [20300/21770] eta: 0:01:08 time: 0.0434 data: 0.0013 max mem: 19788 +Test: [20400/21770] eta: 0:01:04 time: 0.0451 data: 0.0014 max mem: 19788 +Test: [20500/21770] eta: 0:00:59 time: 0.0441 data: 0.0014 max mem: 19788 +Test: [20600/21770] eta: 0:00:54 time: 0.0429 data: 0.0014 max mem: 19788 +Test: [20700/21770] eta: 0:00:50 time: 0.0434 data: 0.0017 max mem: 19788 +Test: [20800/21770] eta: 0:00:45 time: 0.0522 data: 0.0018 max mem: 19788 +Test: [20900/21770] eta: 0:00:40 time: 0.0475 data: 0.0014 max mem: 19788 +Test: [21000/21770] eta: 0:00:36 time: 0.0522 data: 0.0016 max mem: 19788 +Test: [21100/21770] eta: 0:00:31 time: 0.0496 data: 0.0017 max mem: 19788 +Test: [21200/21770] eta: 0:00:26 time: 0.0442 data: 0.0015 max mem: 19788 +Test: [21300/21770] eta: 0:00:21 time: 0.0432 data: 0.0015 max mem: 19788 +Test: [21400/21770] eta: 0:00:17 time: 0.0472 data: 0.0016 max mem: 19788 +Test: [21500/21770] eta: 0:00:12 time: 0.0453 data: 0.0014 max mem: 19788 +Test: [21600/21770] eta: 0:00:07 time: 0.0446 data: 0.0014 max mem: 19788 +Test: [21700/21770] eta: 0:00:03 time: 0.0478 data: 0.0016 max mem: 19788 +Test: Total time: 0:16:58 +Final results: +Mean IoU is 64.96 + + precision@0.5 = 72.38 + precision@0.6 = 66.94 + precision@0.7 = 60.31 + precision@0.8 = 49.59 + precision@0.9 = 24.07 + overall IoU = 65.18 + mean IoU = 64.96 + +Mean accuracy for one-to-zero sample is 86.76 + +Average object IoU 0.6495950173939578 +Overall IoU 65.17984771728516 +Better epoch: 33 + +Epoch: [34] [ 0/2138] eta: 8:12:13 lr: 9.06612424811779e-06 loss: 0.0222 (0.0222) time: 13.8138 data: 1.7696 max mem: 19788 +Epoch: [34] [ 10/2138] eta: 2:17:09 lr: 9.059762799630787e-06 loss: 0.0182 (0.0198) time: 3.8672 data: 0.1635 max mem: 19788 +Epoch: [34] [ 20/2138] eta: 1:59:53 lr: 9.053400854795385e-06 loss: 0.0173 (0.0184) time: 2.8753 data: 0.0023 max mem: 19788 +Epoch: [34] [ 30/2138] eta: 1:53:11 lr: 9.047038413185262e-06 loss: 0.0186 (0.0192) time: 2.8668 data: 0.0021 max mem: 19788 +Epoch: [34] [ 40/2138] eta: 1:50:04 lr: 9.040675474373383e-06 loss: 0.0190 (0.0194) time: 2.8871 data: 0.0025 max mem: 19788 +Epoch: [34] [ 50/2138] eta: 1:48:08 lr: 9.034312037932008e-06 loss: 0.0182 (0.0197) time: 2.9299 data: 0.0025 max mem: 19788 +Epoch: [34] [ 60/2138] eta: 1:46:46 lr: 9.02794810343271e-06 loss: 0.0201 (0.0201) time: 2.9504 data: 0.0026 max mem: 19788 +Epoch: [34] [ 70/2138] eta: 1:45:10 lr: 9.021583670446336e-06 loss: 0.0192 (0.0200) time: 2.9097 data: 0.0027 max mem: 19788 +Epoch: [34] [ 80/2138] eta: 1:43:47 lr: 9.015218738543049e-06 loss: 0.0177 (0.0201) time: 2.8516 data: 0.0025 max mem: 19788 +Epoch: [34] [ 90/2138] eta: 1:42:33 lr: 9.008853307292282e-06 loss: 0.0175 (0.0198) time: 2.8379 data: 0.0022 max mem: 19788 +Epoch: [34] [ 100/2138] eta: 1:41:30 lr: 9.00248737626278e-06 loss: 0.0172 (0.0198) time: 2.8357 data: 0.0023 max mem: 19788 +Epoch: [34] [ 110/2138] eta: 1:40:31 lr: 8.996120945022555e-06 loss: 0.0182 (0.0196) time: 2.8341 data: 0.0027 max mem: 19788 +Epoch: [34] [ 120/2138] eta: 1:39:38 lr: 8.989754013138922e-06 loss: 0.0156 (0.0194) time: 2.8321 data: 0.0026 max mem: 19788 +Epoch: [34] [ 130/2138] eta: 1:38:50 lr: 8.983386580178468e-06 loss: 0.0180 (0.0194) time: 2.8401 data: 0.0024 max mem: 19788 +Epoch: [34] [ 140/2138] eta: 1:38:11 lr: 8.977018645707081e-06 loss: 0.0191 (0.0194) time: 2.8647 data: 0.0027 max mem: 19788 +Epoch: [34] [ 150/2138] eta: 1:37:38 lr: 8.970650209289907e-06 loss: 0.0182 (0.0194) time: 2.9037 data: 0.0026 max mem: 19788 +Epoch: [34] [ 160/2138] eta: 1:37:00 lr: 8.964281270491393e-06 loss: 0.0185 (0.0193) time: 2.8990 data: 0.0022 max mem: 19788 +Epoch: [34] [ 170/2138] eta: 1:36:19 lr: 8.957911828875244e-06 loss: 0.0185 (0.0193) time: 2.8582 data: 0.0023 max mem: 19788 +Epoch: [34] [ 180/2138] eta: 1:35:39 lr: 8.951541884004466e-06 loss: 0.0183 (0.0192) time: 2.8400 data: 0.0026 max mem: 19788 +Epoch: [34] [ 190/2138] eta: 1:35:02 lr: 8.945171435441311e-06 loss: 0.0180 (0.0191) time: 2.8468 data: 0.0026 max mem: 19788 +Epoch: [34] [ 200/2138] eta: 1:34:23 lr: 8.938800482747331e-06 loss: 0.0180 (0.0191) time: 2.8440 data: 0.0024 max mem: 19788 +Epoch: [34] [ 210/2138] eta: 1:33:46 lr: 8.932429025483322e-06 loss: 0.0187 (0.0191) time: 2.8319 data: 0.0024 max mem: 19788 +Epoch: [34] [ 220/2138] eta: 1:33:09 lr: 8.926057063209373e-06 loss: 0.0182 (0.0191) time: 2.8293 data: 0.0022 max mem: 19788 +Epoch: [34] [ 230/2138] eta: 1:32:35 lr: 8.919684595484821e-06 loss: 0.0169 (0.0191) time: 2.8465 data: 0.0021 max mem: 19788 +Epoch: [34] [ 240/2138] eta: 1:32:10 lr: 8.913311621868286e-06 loss: 0.0186 (0.0191) time: 2.9091 data: 0.0020 max mem: 19788 +Epoch: [34] [ 250/2138] eta: 1:31:40 lr: 8.906938141917634e-06 loss: 0.0185 (0.0191) time: 2.9329 data: 0.0024 max mem: 19788 +Epoch: [34] [ 260/2138] eta: 1:31:11 lr: 8.900564155190008e-06 loss: 0.0179 (0.0190) time: 2.9091 data: 0.0026 max mem: 19788 +Epoch: [34] [ 270/2138] eta: 1:30:36 lr: 8.894189661241798e-06 loss: 0.0181 (0.0191) time: 2.8712 data: 0.0027 max mem: 19788 +Epoch: [34] [ 280/2138] eta: 1:30:03 lr: 8.887814659628666e-06 loss: 0.0190 (0.0190) time: 2.8407 data: 0.0025 max mem: 19788 +Epoch: [34] [ 290/2138] eta: 1:29:30 lr: 8.88143914990551e-06 loss: 0.0184 (0.0190) time: 2.8436 data: 0.0023 max mem: 19788 +Epoch: [34] [ 300/2138] eta: 1:28:57 lr: 8.87506313162651e-06 loss: 0.0175 (0.0191) time: 2.8449 data: 0.0024 max mem: 19788 +Epoch: [34] [ 310/2138] eta: 1:28:24 lr: 8.86868660434507e-06 loss: 0.0167 (0.0190) time: 2.8434 data: 0.0024 max mem: 19788 +Epoch: [34] [ 320/2138] eta: 1:27:51 lr: 8.862309567613872e-06 loss: 0.0162 (0.0189) time: 2.8369 data: 0.0025 max mem: 19788 +Epoch: [34] [ 330/2138] eta: 1:27:22 lr: 8.85593202098482e-06 loss: 0.0173 (0.0190) time: 2.8692 data: 0.0023 max mem: 19788 +Epoch: [34] [ 340/2138] eta: 1:26:53 lr: 8.849553964009087e-06 loss: 0.0198 (0.0189) time: 2.8989 data: 0.0024 max mem: 19788 +Epoch: [34] [ 350/2138] eta: 1:26:27 lr: 8.84317539623708e-06 loss: 0.0174 (0.0189) time: 2.9222 data: 0.0026 max mem: 19788 +Epoch: [34] [ 360/2138] eta: 1:25:54 lr: 8.836796317218444e-06 loss: 0.0191 (0.0190) time: 2.8933 data: 0.0024 max mem: 19788 +Epoch: [34] [ 370/2138] eta: 1:25:24 lr: 8.830416726502088e-06 loss: 0.0215 (0.0190) time: 2.8497 data: 0.0021 max mem: 19788 +Epoch: [34] [ 380/2138] eta: 1:24:52 lr: 8.824036623636128e-06 loss: 0.0189 (0.0190) time: 2.8488 data: 0.0023 max mem: 19788 +Epoch: [34] [ 390/2138] eta: 1:24:20 lr: 8.817656008167952e-06 loss: 0.0161 (0.0189) time: 2.8306 data: 0.0023 max mem: 19788 +Epoch: [34] [ 400/2138] eta: 1:23:48 lr: 8.81127487964415e-06 loss: 0.0177 (0.0189) time: 2.8340 data: 0.0021 max mem: 19788 +Epoch: [34] [ 410/2138] eta: 1:23:18 lr: 8.804893237610579e-06 loss: 0.0178 (0.0189) time: 2.8440 data: 0.0023 max mem: 19788 +Epoch: [34] [ 420/2138] eta: 1:22:47 lr: 8.798511081612298e-06 loss: 0.0155 (0.0189) time: 2.8458 data: 0.0025 max mem: 19788 +Epoch: [34] [ 430/2138] eta: 1:22:18 lr: 8.792128411193618e-06 loss: 0.0166 (0.0188) time: 2.8760 data: 0.0027 max mem: 19788 +Epoch: [34] [ 440/2138] eta: 1:21:51 lr: 8.785745225898062e-06 loss: 0.0174 (0.0189) time: 2.9213 data: 0.0026 max mem: 19788 +Epoch: [34] [ 450/2138] eta: 1:21:23 lr: 8.779361525268395e-06 loss: 0.0185 (0.0189) time: 2.9258 data: 0.0027 max mem: 19788 +Epoch: [34] [ 460/2138] eta: 1:20:52 lr: 8.772977308846589e-06 loss: 0.0182 (0.0189) time: 2.8756 data: 0.0027 max mem: 19788 +Epoch: [34] [ 470/2138] eta: 1:20:21 lr: 8.766592576173857e-06 loss: 0.0183 (0.0189) time: 2.8369 data: 0.0025 max mem: 19788 +Epoch: [34] [ 480/2138] eta: 1:19:51 lr: 8.760207326790609e-06 loss: 0.0195 (0.0189) time: 2.8440 data: 0.0025 max mem: 19788 +Epoch: [34] [ 490/2138] eta: 1:19:20 lr: 8.753821560236502e-06 loss: 0.0194 (0.0189) time: 2.8359 data: 0.0025 max mem: 19788 +Epoch: [34] [ 500/2138] eta: 1:18:50 lr: 8.747435276050378e-06 loss: 0.0156 (0.0189) time: 2.8400 data: 0.0026 max mem: 19788 +Epoch: [34] [ 510/2138] eta: 1:18:19 lr: 8.741048473770323e-06 loss: 0.0154 (0.0188) time: 2.8437 data: 0.0024 max mem: 19788 +Epoch: [34] [ 520/2138] eta: 1:17:49 lr: 8.734661152933609e-06 loss: 0.0165 (0.0188) time: 2.8352 data: 0.0022 max mem: 19788 +Epoch: [34] [ 530/2138] eta: 1:17:21 lr: 8.728273313076744e-06 loss: 0.0181 (0.0188) time: 2.8862 data: 0.0025 max mem: 19788 +Epoch: [34] [ 540/2138] eta: 1:16:58 lr: 8.721884953735419e-06 loss: 0.0181 (0.0188) time: 2.9978 data: 0.0027 max mem: 19788 +Epoch: [34] [ 550/2138] eta: 1:16:29 lr: 8.715496074444552e-06 loss: 0.0174 (0.0188) time: 2.9850 data: 0.0026 max mem: 19788 +Epoch: [34] [ 560/2138] eta: 1:15:59 lr: 8.709106674738252e-06 loss: 0.0196 (0.0189) time: 2.8673 data: 0.0027 max mem: 19788 +Epoch: [34] [ 570/2138] eta: 1:15:28 lr: 8.702716754149844e-06 loss: 0.0182 (0.0188) time: 2.8243 data: 0.0025 max mem: 19788 +Epoch: [34] [ 580/2138] eta: 1:14:58 lr: 8.696326312211833e-06 loss: 0.0182 (0.0189) time: 2.8290 data: 0.0022 max mem: 19788 +Epoch: [34] [ 590/2138] eta: 1:14:28 lr: 8.689935348455948e-06 loss: 0.0189 (0.0189) time: 2.8426 data: 0.0024 max mem: 19788 +Epoch: [34] [ 600/2138] eta: 1:13:58 lr: 8.683543862413087e-06 loss: 0.0178 (0.0189) time: 2.8489 data: 0.0028 max mem: 19788 +Epoch: [34] [ 610/2138] eta: 1:13:28 lr: 8.677151853613368e-06 loss: 0.0178 (0.0189) time: 2.8522 data: 0.0026 max mem: 19788 +Epoch: [34] [ 620/2138] eta: 1:12:59 lr: 8.67075932158608e-06 loss: 0.0188 (0.0189) time: 2.8614 data: 0.0022 max mem: 19788 +Epoch: [34] [ 630/2138] eta: 1:12:30 lr: 8.66436626585972e-06 loss: 0.0189 (0.0190) time: 2.8779 data: 0.0022 max mem: 19788 +Epoch: [34] [ 640/2138] eta: 1:12:03 lr: 8.657972685961956e-06 loss: 0.0178 (0.0190) time: 2.9180 data: 0.0021 max mem: 19788 +Epoch: [34] [ 650/2138] eta: 1:11:34 lr: 8.65157858141966e-06 loss: 0.0198 (0.0190) time: 2.9115 data: 0.0021 max mem: 19788 +Epoch: [34] [ 660/2138] eta: 1:11:04 lr: 8.645183951758876e-06 loss: 0.0198 (0.0190) time: 2.8559 data: 0.0022 max mem: 19788 +Epoch: [34] [ 670/2138] eta: 1:10:34 lr: 8.638788796504823e-06 loss: 0.0189 (0.0190) time: 2.8372 data: 0.0022 max mem: 19788 +Epoch: [34] [ 680/2138] eta: 1:10:04 lr: 8.632393115181923e-06 loss: 0.0171 (0.0190) time: 2.8364 data: 0.0021 max mem: 19788 +Epoch: [34] [ 690/2138] eta: 1:09:34 lr: 8.62599690731375e-06 loss: 0.0183 (0.0190) time: 2.8396 data: 0.0020 max mem: 19788 +Epoch: [34] [ 700/2138] eta: 1:09:05 lr: 8.619600172423082e-06 loss: 0.0182 (0.0190) time: 2.8428 data: 0.0022 max mem: 19788 +Epoch: [34] [ 710/2138] eta: 1:08:35 lr: 8.613202910031835e-06 loss: 0.0179 (0.0190) time: 2.8438 data: 0.0024 max mem: 19788 +Epoch: [34] [ 720/2138] eta: 1:08:06 lr: 8.606805119661135e-06 loss: 0.0169 (0.0189) time: 2.8588 data: 0.0023 max mem: 19788 +Epoch: [34] [ 730/2138] eta: 1:07:38 lr: 8.600406800831243e-06 loss: 0.0164 (0.0189) time: 2.8997 data: 0.0023 max mem: 19788 +Epoch: [34] [ 740/2138] eta: 1:07:09 lr: 8.594007953061615e-06 loss: 0.0189 (0.0190) time: 2.9076 data: 0.0026 max mem: 19788 +Epoch: [34] [ 750/2138] eta: 1:06:40 lr: 8.587608575870846e-06 loss: 0.0189 (0.0190) time: 2.8649 data: 0.0028 max mem: 19788 +Epoch: [34] [ 760/2138] eta: 1:06:10 lr: 8.58120866877672e-06 loss: 0.0194 (0.0190) time: 2.8359 data: 0.0028 max mem: 19788 +Epoch: [34] [ 770/2138] eta: 1:05:40 lr: 8.57480823129616e-06 loss: 0.0188 (0.0190) time: 2.8327 data: 0.0029 max mem: 19788 +Epoch: [34] [ 780/2138] eta: 1:05:11 lr: 8.568407262945264e-06 loss: 0.0173 (0.0190) time: 2.8326 data: 0.0030 max mem: 19788 +Epoch: [34] [ 790/2138] eta: 1:04:41 lr: 8.562005763239272e-06 loss: 0.0162 (0.0189) time: 2.8310 data: 0.0026 max mem: 19788 +Epoch: [34] [ 800/2138] eta: 1:04:12 lr: 8.555603731692594e-06 loss: 0.0175 (0.0189) time: 2.8481 data: 0.0024 max mem: 19788 +Epoch: [34] [ 810/2138] eta: 1:03:42 lr: 8.549201167818774e-06 loss: 0.0189 (0.0189) time: 2.8478 data: 0.0023 max mem: 19788 +Epoch: [34] [ 820/2138] eta: 1:03:15 lr: 8.542798071130524e-06 loss: 0.0179 (0.0189) time: 2.8869 data: 0.0021 max mem: 19788 +Epoch: [34] [ 830/2138] eta: 1:02:46 lr: 8.536394441139686e-06 loss: 0.0166 (0.0189) time: 2.9197 data: 0.0022 max mem: 19788 +Epoch: [34] [ 840/2138] eta: 1:02:18 lr: 8.529990277357268e-06 loss: 0.0159 (0.0189) time: 2.9049 data: 0.0026 max mem: 19788 +Epoch: [34] [ 850/2138] eta: 1:01:48 lr: 8.523585579293396e-06 loss: 0.0177 (0.0189) time: 2.8711 data: 0.0025 max mem: 19788 +Epoch: [34] [ 860/2138] eta: 1:01:19 lr: 8.517180346457367e-06 loss: 0.0180 (0.0189) time: 2.8448 data: 0.0024 max mem: 19788 +Epoch: [34] [ 870/2138] eta: 1:00:50 lr: 8.510774578357585e-06 loss: 0.0171 (0.0189) time: 2.8451 data: 0.0025 max mem: 19788 +Epoch: [34] [ 880/2138] eta: 1:00:20 lr: 8.50436827450162e-06 loss: 0.0171 (0.0189) time: 2.8317 data: 0.0021 max mem: 19788 +Epoch: [34] [ 890/2138] eta: 0:59:51 lr: 8.497961434396148e-06 loss: 0.0181 (0.0189) time: 2.8311 data: 0.0021 max mem: 19788 +Epoch: [34] [ 900/2138] eta: 0:59:21 lr: 8.491554057547008e-06 loss: 0.0186 (0.0189) time: 2.8293 data: 0.0024 max mem: 19788 +Epoch: [34] [ 910/2138] eta: 0:58:52 lr: 8.485146143459138e-06 loss: 0.0173 (0.0189) time: 2.8394 data: 0.0024 max mem: 19788 +Epoch: [34] [ 920/2138] eta: 0:58:24 lr: 8.478737691636632e-06 loss: 0.0171 (0.0189) time: 2.8847 data: 0.0024 max mem: 19788 +Epoch: [34] [ 930/2138] eta: 0:57:56 lr: 8.47232870158268e-06 loss: 0.0191 (0.0189) time: 2.9244 data: 0.0023 max mem: 19788 +Epoch: [34] [ 940/2138] eta: 0:57:27 lr: 8.465919172799627e-06 loss: 0.0196 (0.0189) time: 2.8960 data: 0.0022 max mem: 19788 +Epoch: [34] [ 950/2138] eta: 0:56:58 lr: 8.459509104788915e-06 loss: 0.0190 (0.0189) time: 2.8537 data: 0.0023 max mem: 19788 +Epoch: [34] [ 960/2138] eta: 0:56:28 lr: 8.453098497051105e-06 loss: 0.0193 (0.0189) time: 2.8374 data: 0.0026 max mem: 19788 +Epoch: [34] [ 970/2138] eta: 0:55:59 lr: 8.446687349085894e-06 loss: 0.0193 (0.0189) time: 2.8343 data: 0.0025 max mem: 19788 +Epoch: [34] [ 980/2138] eta: 0:55:30 lr: 8.440275660392066e-06 loss: 0.0169 (0.0189) time: 2.8326 data: 0.0025 max mem: 19788 +Epoch: [34] [ 990/2138] eta: 0:55:01 lr: 8.433863430467546e-06 loss: 0.0164 (0.0189) time: 2.8331 data: 0.0026 max mem: 19788 +Epoch: [34] [1000/2138] eta: 0:54:31 lr: 8.427450658809336e-06 loss: 0.0163 (0.0189) time: 2.8357 data: 0.0023 max mem: 19788 +Epoch: [34] [1010/2138] eta: 0:54:03 lr: 8.421037344913579e-06 loss: 0.0167 (0.0189) time: 2.8554 data: 0.0023 max mem: 19788 +Epoch: [34] [1020/2138] eta: 0:53:34 lr: 8.414623488275487e-06 loss: 0.0156 (0.0189) time: 2.8829 data: 0.0025 max mem: 19788 +Epoch: [34] [1030/2138] eta: 0:53:06 lr: 8.40820908838941e-06 loss: 0.0160 (0.0189) time: 2.9098 data: 0.0026 max mem: 19788 +Epoch: [34] [1040/2138] eta: 0:52:37 lr: 8.401794144748762e-06 loss: 0.0177 (0.0189) time: 2.9005 data: 0.0026 max mem: 19788 +Epoch: [34] [1050/2138] eta: 0:52:08 lr: 8.395378656846087e-06 loss: 0.0196 (0.0189) time: 2.8549 data: 0.0025 max mem: 19788 +Epoch: [34] [1060/2138] eta: 0:51:39 lr: 8.388962624173002e-06 loss: 0.0201 (0.0189) time: 2.8396 data: 0.0024 max mem: 19788 +Epoch: [34] [1070/2138] eta: 0:51:10 lr: 8.38254604622023e-06 loss: 0.0188 (0.0189) time: 2.8305 data: 0.0024 max mem: 19788 +Epoch: [34] [1080/2138] eta: 0:50:40 lr: 8.37612892247757e-06 loss: 0.0183 (0.0189) time: 2.8290 data: 0.0025 max mem: 19788 +Epoch: [34] [1090/2138] eta: 0:50:11 lr: 8.369711252433927e-06 loss: 0.0183 (0.0189) time: 2.8335 data: 0.0027 max mem: 19788 +Epoch: [34] [1100/2138] eta: 0:49:42 lr: 8.363293035577272e-06 loss: 0.0185 (0.0189) time: 2.8353 data: 0.0027 max mem: 19788 +Epoch: [34] [1110/2138] eta: 0:49:14 lr: 8.35687427139468e-06 loss: 0.0190 (0.0189) time: 2.8715 data: 0.0023 max mem: 19788 +Epoch: [34] [1120/2138] eta: 0:48:45 lr: 8.350454959372284e-06 loss: 0.0186 (0.0189) time: 2.9017 data: 0.0024 max mem: 19788 +Epoch: [34] [1130/2138] eta: 0:48:17 lr: 8.344035098995318e-06 loss: 0.0172 (0.0189) time: 2.8925 data: 0.0027 max mem: 19788 +Epoch: [34] [1140/2138] eta: 0:47:48 lr: 8.33761468974807e-06 loss: 0.0175 (0.0189) time: 2.8667 data: 0.0026 max mem: 19788 +Epoch: [34] [1150/2138] eta: 0:47:19 lr: 8.33119373111392e-06 loss: 0.0162 (0.0189) time: 2.8497 data: 0.0026 max mem: 19788 +Epoch: [34] [1160/2138] eta: 0:46:50 lr: 8.324772222575304e-06 loss: 0.0155 (0.0189) time: 2.8432 data: 0.0025 max mem: 19788 +Epoch: [34] [1170/2138] eta: 0:46:21 lr: 8.318350163613743e-06 loss: 0.0173 (0.0189) time: 2.8354 data: 0.0025 max mem: 19788 +Epoch: [34] [1180/2138] eta: 0:45:52 lr: 8.3119275537098e-06 loss: 0.0186 (0.0189) time: 2.8378 data: 0.0027 max mem: 19788 +Epoch: [34] [1190/2138] eta: 0:45:23 lr: 8.305504392343132e-06 loss: 0.0195 (0.0189) time: 2.8382 data: 0.0024 max mem: 19788 +Epoch: [34] [1200/2138] eta: 0:44:54 lr: 8.299080678992422e-06 loss: 0.0165 (0.0188) time: 2.8353 data: 0.0021 max mem: 19788 +Epoch: [34] [1210/2138] eta: 0:44:25 lr: 8.29265641313545e-06 loss: 0.0179 (0.0189) time: 2.8633 data: 0.0022 max mem: 19788 +Epoch: [34] [1220/2138] eta: 0:43:57 lr: 8.28623159424901e-06 loss: 0.0180 (0.0188) time: 2.9093 data: 0.0023 max mem: 19788 +Epoch: [34] [1230/2138] eta: 0:43:28 lr: 8.279806221808992e-06 loss: 0.0175 (0.0188) time: 2.9144 data: 0.0024 max mem: 19788 +Epoch: [34] [1240/2138] eta: 0:42:59 lr: 8.2733802952903e-06 loss: 0.0172 (0.0188) time: 2.8692 data: 0.0024 max mem: 19788 +Epoch: [34] [1250/2138] eta: 0:42:30 lr: 8.266953814166912e-06 loss: 0.0171 (0.0188) time: 2.8420 data: 0.0024 max mem: 19788 +Epoch: [34] [1260/2138] eta: 0:42:01 lr: 8.260526777911841e-06 loss: 0.0175 (0.0188) time: 2.8387 data: 0.0024 max mem: 19788 +Epoch: [34] [1270/2138] eta: 0:41:32 lr: 8.254099185997132e-06 loss: 0.0178 (0.0188) time: 2.8401 data: 0.0025 max mem: 19788 +Epoch: [34] [1280/2138] eta: 0:41:03 lr: 8.247671037893902e-06 loss: 0.0175 (0.0188) time: 2.8358 data: 0.0024 max mem: 19788 +Epoch: [34] [1290/2138] eta: 0:40:34 lr: 8.24124233307227e-06 loss: 0.0186 (0.0188) time: 2.8288 data: 0.0022 max mem: 19788 +Epoch: [34] [1300/2138] eta: 0:40:06 lr: 8.23481307100142e-06 loss: 0.0186 (0.0188) time: 2.8518 data: 0.0022 max mem: 19788 +Epoch: [34] [1310/2138] eta: 0:39:38 lr: 8.228383251149547e-06 loss: 0.0187 (0.0188) time: 2.9178 data: 0.0024 max mem: 19788 +Epoch: [34] [1320/2138] eta: 0:39:09 lr: 8.221952872983896e-06 loss: 0.0187 (0.0188) time: 2.9508 data: 0.0025 max mem: 19788 +Epoch: [34] [1330/2138] eta: 0:38:41 lr: 8.215521935970716e-06 loss: 0.0179 (0.0188) time: 2.9582 data: 0.0025 max mem: 19788 +Epoch: [34] [1340/2138] eta: 0:38:13 lr: 8.209090439575307e-06 loss: 0.0187 (0.0188) time: 2.9492 data: 0.0023 max mem: 19788 +Epoch: [34] [1350/2138] eta: 0:37:44 lr: 8.202658383261967e-06 loss: 0.0207 (0.0189) time: 2.9061 data: 0.0021 max mem: 19788 +Epoch: [34] [1360/2138] eta: 0:37:16 lr: 8.196225766494039e-06 loss: 0.0189 (0.0189) time: 2.9301 data: 0.0023 max mem: 19788 +Epoch: [34] [1370/2138] eta: 0:36:47 lr: 8.189792588733856e-06 loss: 0.0187 (0.0189) time: 2.9001 data: 0.0024 max mem: 19788 +Epoch: [34] [1380/2138] eta: 0:36:18 lr: 8.18335884944279e-06 loss: 0.0193 (0.0189) time: 2.8423 data: 0.0023 max mem: 19788 +Epoch: [34] [1390/2138] eta: 0:35:49 lr: 8.176924548081203e-06 loss: 0.0191 (0.0189) time: 2.8370 data: 0.0023 max mem: 19788 +Epoch: [34] [1400/2138] eta: 0:35:20 lr: 8.170489684108492e-06 loss: 0.0172 (0.0189) time: 2.8371 data: 0.0022 max mem: 19788 +Epoch: [34] [1410/2138] eta: 0:34:51 lr: 8.164054256983028e-06 loss: 0.0163 (0.0188) time: 2.8364 data: 0.0023 max mem: 19788 +Epoch: [34] [1420/2138] eta: 0:34:22 lr: 8.15761826616222e-06 loss: 0.0170 (0.0188) time: 2.8354 data: 0.0024 max mem: 19788 +Epoch: [34] [1430/2138] eta: 0:33:53 lr: 8.151181711102447e-06 loss: 0.0188 (0.0189) time: 2.8375 data: 0.0022 max mem: 19788 +Epoch: [34] [1440/2138] eta: 0:33:25 lr: 8.144744591259113e-06 loss: 0.0194 (0.0189) time: 2.8944 data: 0.0023 max mem: 19788 +Epoch: [34] [1450/2138] eta: 0:32:56 lr: 8.138306906086591e-06 loss: 0.0190 (0.0189) time: 2.9286 data: 0.0026 max mem: 19788 +Epoch: [34] [1460/2138] eta: 0:32:28 lr: 8.131868655038278e-06 loss: 0.0185 (0.0189) time: 2.9003 data: 0.0027 max mem: 19788 +Epoch: [34] [1470/2138] eta: 0:31:59 lr: 8.125429837566527e-06 loss: 0.0164 (0.0189) time: 2.8965 data: 0.0025 max mem: 19788 +Epoch: [34] [1480/2138] eta: 0:31:30 lr: 8.11899045312271e-06 loss: 0.0161 (0.0189) time: 2.8685 data: 0.0024 max mem: 19788 +Epoch: [34] [1490/2138] eta: 0:31:01 lr: 8.112550501157156e-06 loss: 0.0180 (0.0189) time: 2.8409 data: 0.0026 max mem: 19788 +Epoch: [34] [1500/2138] eta: 0:30:32 lr: 8.106109981119203e-06 loss: 0.0195 (0.0189) time: 2.8293 data: 0.0024 max mem: 19788 +Epoch: [34] [1510/2138] eta: 0:30:04 lr: 8.099668892457138e-06 loss: 0.0175 (0.0189) time: 2.8215 data: 0.0020 max mem: 19788 +Epoch: [34] [1520/2138] eta: 0:29:35 lr: 8.093227234618256e-06 loss: 0.0186 (0.0189) time: 2.8243 data: 0.0021 max mem: 19788 +Epoch: [34] [1530/2138] eta: 0:29:06 lr: 8.086785007048794e-06 loss: 0.0186 (0.0189) time: 2.8309 data: 0.0023 max mem: 19788 +Epoch: [34] [1540/2138] eta: 0:28:37 lr: 8.08034220919399e-06 loss: 0.0179 (0.0189) time: 2.8375 data: 0.0025 max mem: 19788 +Epoch: [34] [1550/2138] eta: 0:28:08 lr: 8.073898840498022e-06 loss: 0.0171 (0.0189) time: 2.8770 data: 0.0026 max mem: 19788 +Epoch: [34] [1560/2138] eta: 0:27:40 lr: 8.067454900404056e-06 loss: 0.0189 (0.0189) time: 2.9046 data: 0.0026 max mem: 19788 +Epoch: [34] [1570/2138] eta: 0:27:11 lr: 8.061010388354205e-06 loss: 0.0195 (0.0189) time: 2.9090 data: 0.0025 max mem: 19788 +Epoch: [34] [1580/2138] eta: 0:26:43 lr: 8.05456530378954e-06 loss: 0.0179 (0.0189) time: 2.9220 data: 0.0023 max mem: 19788 +Epoch: [34] [1590/2138] eta: 0:26:14 lr: 8.048119646150107e-06 loss: 0.0196 (0.0189) time: 2.8870 data: 0.0023 max mem: 19788 +Epoch: [34] [1600/2138] eta: 0:25:45 lr: 8.04167341487488e-06 loss: 0.0210 (0.0189) time: 2.8442 data: 0.0023 max mem: 19788 +Epoch: [34] [1610/2138] eta: 0:25:16 lr: 8.03522660940181e-06 loss: 0.0212 (0.0189) time: 2.8420 data: 0.0024 max mem: 19788 +Epoch: [34] [1620/2138] eta: 0:24:47 lr: 8.028779229167767e-06 loss: 0.0168 (0.0189) time: 2.8440 data: 0.0026 max mem: 19788 +Epoch: [34] [1630/2138] eta: 0:24:18 lr: 8.022331273608595e-06 loss: 0.0168 (0.0189) time: 2.8414 data: 0.0026 max mem: 19788 +Epoch: [34] [1640/2138] eta: 0:23:50 lr: 8.015882742159055e-06 loss: 0.0180 (0.0189) time: 2.8394 data: 0.0025 max mem: 19788 +Epoch: [34] [1650/2138] eta: 0:23:21 lr: 8.009433634252867e-06 loss: 0.0180 (0.0189) time: 2.8629 data: 0.0026 max mem: 19788 +Epoch: [34] [1660/2138] eta: 0:22:52 lr: 8.002983949322667e-06 loss: 0.0188 (0.0189) time: 2.8823 data: 0.0029 max mem: 19788 +Epoch: [34] [1670/2138] eta: 0:22:24 lr: 7.996533686800046e-06 loss: 0.0177 (0.0189) time: 2.9156 data: 0.0027 max mem: 19788 +Epoch: [34] [1680/2138] eta: 0:21:55 lr: 7.990082846115503e-06 loss: 0.0165 (0.0189) time: 2.9687 data: 0.0024 max mem: 19788 +Epoch: [34] [1690/2138] eta: 0:21:27 lr: 7.983631426698484e-06 loss: 0.0177 (0.0189) time: 2.9064 data: 0.0023 max mem: 19788 +Epoch: [34] [1700/2138] eta: 0:20:58 lr: 7.977179427977342e-06 loss: 0.0182 (0.0189) time: 2.8303 data: 0.0022 max mem: 19788 +Epoch: [34] [1710/2138] eta: 0:20:29 lr: 7.970726849379368e-06 loss: 0.0182 (0.0189) time: 2.8289 data: 0.0022 max mem: 19788 +Epoch: [34] [1720/2138] eta: 0:20:00 lr: 7.964273690330751e-06 loss: 0.0180 (0.0189) time: 2.8354 data: 0.0024 max mem: 19788 +Epoch: [34] [1730/2138] eta: 0:19:31 lr: 7.95781995025662e-06 loss: 0.0184 (0.0189) time: 2.8352 data: 0.0025 max mem: 19788 +Epoch: [34] [1740/2138] eta: 0:19:02 lr: 7.951365628580984e-06 loss: 0.0184 (0.0189) time: 2.8276 data: 0.0023 max mem: 19788 +Epoch: [34] [1750/2138] eta: 0:18:34 lr: 7.944910724726799e-06 loss: 0.0188 (0.0189) time: 2.8255 data: 0.0020 max mem: 19788 +Epoch: [34] [1760/2138] eta: 0:18:05 lr: 7.93845523811589e-06 loss: 0.0175 (0.0189) time: 2.8762 data: 0.0020 max mem: 19788 +Epoch: [34] [1770/2138] eta: 0:17:36 lr: 7.931999168169015e-06 loss: 0.0169 (0.0189) time: 2.9131 data: 0.0021 max mem: 19788 +Epoch: [34] [1780/2138] eta: 0:17:08 lr: 7.925542514305807e-06 loss: 0.0159 (0.0189) time: 2.9155 data: 0.0023 max mem: 19788 +Epoch: [34] [1790/2138] eta: 0:16:39 lr: 7.91908527594482e-06 loss: 0.0164 (0.0189) time: 2.9055 data: 0.0025 max mem: 19788 +Epoch: [34] [1800/2138] eta: 0:16:10 lr: 7.91262745250348e-06 loss: 0.0212 (0.0189) time: 2.8563 data: 0.0025 max mem: 19788 +Epoch: [34] [1810/2138] eta: 0:15:41 lr: 7.906169043398118e-06 loss: 0.0195 (0.0189) time: 2.8324 data: 0.0023 max mem: 19788 +Epoch: [34] [1820/2138] eta: 0:15:13 lr: 7.899710048043938e-06 loss: 0.0175 (0.0189) time: 2.8274 data: 0.0020 max mem: 19788 +Epoch: [34] [1830/2138] eta: 0:14:44 lr: 7.893250465855052e-06 loss: 0.0175 (0.0189) time: 2.8282 data: 0.0023 max mem: 19788 +Epoch: [34] [1840/2138] eta: 0:14:15 lr: 7.886790296244425e-06 loss: 0.0187 (0.0189) time: 2.8304 data: 0.0024 max mem: 19788 +Epoch: [34] [1850/2138] eta: 0:13:46 lr: 7.880329538623922e-06 loss: 0.0189 (0.0189) time: 2.8341 data: 0.0025 max mem: 19788 +Epoch: [34] [1860/2138] eta: 0:13:18 lr: 7.873868192404264e-06 loss: 0.0188 (0.0189) time: 2.8498 data: 0.0026 max mem: 19788 +Epoch: [34] [1870/2138] eta: 0:12:49 lr: 7.867406256995068e-06 loss: 0.0189 (0.0189) time: 2.8804 data: 0.0025 max mem: 19788 +Epoch: [34] [1880/2138] eta: 0:12:20 lr: 7.860943731804796e-06 loss: 0.0164 (0.0189) time: 2.9053 data: 0.0026 max mem: 19788 +Epoch: [34] [1890/2138] eta: 0:11:52 lr: 7.85448061624078e-06 loss: 0.0152 (0.0189) time: 2.9375 data: 0.0027 max mem: 19788 +Epoch: [34] [1900/2138] eta: 0:11:23 lr: 7.848016909709229e-06 loss: 0.0171 (0.0189) time: 2.9123 data: 0.0026 max mem: 19788 +Epoch: [34] [1910/2138] eta: 0:10:54 lr: 7.841552611615188e-06 loss: 0.0184 (0.0189) time: 2.8457 data: 0.0024 max mem: 19788 +Epoch: [34] [1920/2138] eta: 0:10:25 lr: 7.835087721362584e-06 loss: 0.0174 (0.0189) time: 2.8269 data: 0.0023 max mem: 19788 +Epoch: [34] [1930/2138] eta: 0:09:57 lr: 7.828622238354167e-06 loss: 0.0165 (0.0189) time: 2.8270 data: 0.0021 max mem: 19788 +Epoch: [34] [1940/2138] eta: 0:09:28 lr: 7.822156161991564e-06 loss: 0.0176 (0.0189) time: 2.8325 data: 0.0022 max mem: 19788 +Epoch: [34] [1950/2138] eta: 0:08:59 lr: 7.815689491675221e-06 loss: 0.0178 (0.0189) time: 2.8354 data: 0.0023 max mem: 19788 +Epoch: [34] [1960/2138] eta: 0:08:30 lr: 7.809222226804454e-06 loss: 0.0178 (0.0189) time: 2.8335 data: 0.0022 max mem: 19788 +Epoch: [34] [1970/2138] eta: 0:08:02 lr: 7.80275436677739e-06 loss: 0.0163 (0.0189) time: 2.8569 data: 0.0023 max mem: 19788 +Epoch: [34] [1980/2138] eta: 0:07:33 lr: 7.79628591099102e-06 loss: 0.0178 (0.0189) time: 2.8917 data: 0.0026 max mem: 19788 +Epoch: [34] [1990/2138] eta: 0:07:04 lr: 7.78981685884114e-06 loss: 0.0185 (0.0189) time: 2.9186 data: 0.0029 max mem: 19788 +Epoch: [34] [2000/2138] eta: 0:06:36 lr: 7.7833472097224e-06 loss: 0.0175 (0.0189) time: 2.9255 data: 0.0030 max mem: 19788 +Epoch: [34] [2010/2138] eta: 0:06:07 lr: 7.776876963028254e-06 loss: 0.0192 (0.0189) time: 2.8735 data: 0.0029 max mem: 19788 +Epoch: [34] [2020/2138] eta: 0:05:38 lr: 7.770406118151e-06 loss: 0.0198 (0.0189) time: 2.8340 data: 0.0027 max mem: 19788 +Epoch: [34] [2030/2138] eta: 0:05:10 lr: 7.76393467448173e-06 loss: 0.0182 (0.0189) time: 2.8301 data: 0.0023 max mem: 19788 +Epoch: [34] [2040/2138] eta: 0:04:41 lr: 7.757462631410378e-06 loss: 0.0181 (0.0189) time: 2.8365 data: 0.0023 max mem: 19788 +Epoch: [34] [2050/2138] eta: 0:04:12 lr: 7.750989988325667e-06 loss: 0.0173 (0.0189) time: 2.8374 data: 0.0023 max mem: 19788 +Epoch: [34] [2060/2138] eta: 0:03:43 lr: 7.744516744615152e-06 loss: 0.0176 (0.0189) time: 2.8319 data: 0.0022 max mem: 19788 +Epoch: [34] [2070/2138] eta: 0:03:15 lr: 7.738042899665167e-06 loss: 0.0170 (0.0189) time: 2.8420 data: 0.0024 max mem: 19788 +Epoch: [34] [2080/2138] eta: 0:02:46 lr: 7.731568452860874e-06 loss: 0.0173 (0.0189) time: 2.9103 data: 0.0026 max mem: 19788 +Epoch: [34] [2090/2138] eta: 0:02:17 lr: 7.72509340358621e-06 loss: 0.0201 (0.0189) time: 2.9234 data: 0.0026 max mem: 19788 +Epoch: [34] [2100/2138] eta: 0:01:49 lr: 7.71861775122393e-06 loss: 0.0180 (0.0189) time: 2.9401 data: 0.0025 max mem: 19788 +Epoch: [34] [2110/2138] eta: 0:01:20 lr: 7.712141495155556e-06 loss: 0.0195 (0.0189) time: 2.9357 data: 0.0025 max mem: 19788 +Epoch: [34] [2120/2138] eta: 0:00:51 lr: 7.705664634761423e-06 loss: 0.0211 (0.0189) time: 2.8495 data: 0.0026 max mem: 19788 +Epoch: [34] [2130/2138] eta: 0:00:22 lr: 7.69918716942063e-06 loss: 0.0204 (0.0189) time: 2.8300 data: 0.0024 max mem: 19788 +Epoch: [34] Total time: 1:42:18 +Test: [ 0/21770] eta: 17:01:37 time: 2.8157 data: 2.6716 max mem: 19788 +Test: [ 100/21770] eta: 0:27:27 time: 0.0441 data: 0.0016 max mem: 19788 +Test: [ 200/21770] eta: 0:21:29 time: 0.0431 data: 0.0014 max mem: 19788 +Test: [ 300/21770] eta: 0:19:33 time: 0.0418 data: 0.0015 max mem: 19788 +Test: [ 400/21770] eta: 0:18:41 time: 0.0491 data: 0.0016 max mem: 19788 +Test: [ 500/21770] eta: 0:18:02 time: 0.0454 data: 0.0016 max mem: 19788 +Test: [ 600/21770] eta: 0:17:33 time: 0.0453 data: 0.0016 max mem: 19788 +Test: [ 700/21770] eta: 0:17:12 time: 0.0432 data: 0.0015 max mem: 19788 +Test: [ 800/21770] eta: 0:16:58 time: 0.0510 data: 0.0017 max mem: 19788 +Test: [ 900/21770] eta: 0:16:52 time: 0.0474 data: 0.0017 max mem: 19788 +Test: [ 1000/21770] eta: 0:16:45 time: 0.0508 data: 0.0017 max mem: 19788 +Test: [ 1100/21770] eta: 0:16:31 time: 0.0431 data: 0.0014 max mem: 19788 +Test: [ 1200/21770] eta: 0:16:18 time: 0.0436 data: 0.0014 max mem: 19788 +Test: [ 1300/21770] eta: 0:16:07 time: 0.0421 data: 0.0014 max mem: 19788 +Test: [ 1400/21770] eta: 0:15:58 time: 0.0499 data: 0.0015 max mem: 19788 +Test: [ 1500/21770] eta: 0:15:52 time: 0.0445 data: 0.0015 max mem: 19788 +Test: [ 1600/21770] eta: 0:15:48 time: 0.0437 data: 0.0014 max mem: 19788 +Test: [ 1700/21770] eta: 0:15:39 time: 0.0427 data: 0.0015 max mem: 19788 +Test: [ 1800/21770] eta: 0:15:30 time: 0.0425 data: 0.0013 max mem: 19788 +Test: [ 1900/21770] eta: 0:15:23 time: 0.0484 data: 0.0016 max mem: 19788 +Test: [ 2000/21770] eta: 0:15:17 time: 0.0429 data: 0.0017 max mem: 19788 +Test: [ 2100/21770] eta: 0:15:11 time: 0.0430 data: 0.0014 max mem: 19788 +Test: [ 2200/21770] eta: 0:15:06 time: 0.0440 data: 0.0014 max mem: 19788 +Test: [ 2300/21770] eta: 0:15:03 time: 0.0505 data: 0.0017 max mem: 19788 +Test: [ 2400/21770] eta: 0:14:56 time: 0.0438 data: 0.0014 max mem: 19788 +Test: [ 2500/21770] eta: 0:14:50 time: 0.0440 data: 0.0015 max mem: 19788 +Test: [ 2600/21770] eta: 0:14:47 time: 0.0522 data: 0.0018 max mem: 19788 +Test: [ 2700/21770] eta: 0:14:44 time: 0.0439 data: 0.0014 max mem: 19788 +Test: [ 2800/21770] eta: 0:14:39 time: 0.0499 data: 0.0015 max mem: 19788 +Test: [ 2900/21770] eta: 0:14:36 time: 0.0451 data: 0.0014 max mem: 19788 +Test: [ 3000/21770] eta: 0:14:32 time: 0.0510 data: 0.0017 max mem: 19788 +Test: [ 3100/21770] eta: 0:14:26 time: 0.0454 data: 0.0015 max mem: 19788 +Test: [ 3200/21770] eta: 0:14:22 time: 0.0468 data: 0.0017 max mem: 19788 +Test: [ 3300/21770] eta: 0:14:18 time: 0.0486 data: 0.0016 max mem: 19788 +Test: [ 3400/21770] eta: 0:14:16 time: 0.0492 data: 0.0016 max mem: 19788 +Test: [ 3500/21770] eta: 0:14:12 time: 0.0446 data: 0.0017 max mem: 19788 +Test: [ 3600/21770] eta: 0:14:08 time: 0.0507 data: 0.0016 max mem: 19788 +Test: [ 3700/21770] eta: 0:14:07 time: 0.0543 data: 0.0016 max mem: 19788 +Test: [ 3800/21770] eta: 0:14:02 time: 0.0454 data: 0.0014 max mem: 19788 +Test: [ 3900/21770] eta: 0:13:59 time: 0.0479 data: 0.0016 max mem: 19788 +Test: [ 4000/21770] eta: 0:13:53 time: 0.0436 data: 0.0014 max mem: 19788 +Test: [ 4100/21770] eta: 0:13:48 time: 0.0457 data: 0.0017 max mem: 19788 +Test: [ 4200/21770] eta: 0:13:43 time: 0.0446 data: 0.0020 max mem: 19788 +Test: [ 4300/21770] eta: 0:13:39 time: 0.0455 data: 0.0014 max mem: 19788 +Test: [ 4400/21770] eta: 0:13:34 time: 0.0536 data: 0.0016 max mem: 19788 +Test: [ 4500/21770] eta: 0:13:29 time: 0.0437 data: 0.0015 max mem: 19788 +Test: [ 4600/21770] eta: 0:13:24 time: 0.0459 data: 0.0015 max mem: 19788 +Test: [ 4700/21770] eta: 0:13:19 time: 0.0437 data: 0.0015 max mem: 19788 +Test: [ 4800/21770] eta: 0:13:15 time: 0.0517 data: 0.0017 max mem: 19788 +Test: [ 4900/21770] eta: 0:13:09 time: 0.0441 data: 0.0015 max mem: 19788 +Test: [ 5000/21770] eta: 0:13:06 time: 0.0521 data: 0.0018 max mem: 19788 +Test: [ 5100/21770] eta: 0:13:03 time: 0.0522 data: 0.0018 max mem: 19788 +Test: [ 5200/21770] eta: 0:12:58 time: 0.0485 data: 0.0016 max mem: 19788 +Test: [ 5300/21770] eta: 0:12:53 time: 0.0503 data: 0.0016 max mem: 19788 +Test: [ 5400/21770] eta: 0:12:47 time: 0.0452 data: 0.0013 max mem: 19788 +Test: [ 5500/21770] eta: 0:12:42 time: 0.0505 data: 0.0015 max mem: 19788 +Test: [ 5600/21770] eta: 0:12:37 time: 0.0455 data: 0.0014 max mem: 19788 +Test: [ 5700/21770] eta: 0:12:32 time: 0.0431 data: 0.0014 max mem: 19788 +Test: [ 5800/21770] eta: 0:12:27 time: 0.0448 data: 0.0014 max mem: 19788 +Test: [ 5900/21770] eta: 0:12:22 time: 0.0441 data: 0.0015 max mem: 19788 +Test: [ 6000/21770] eta: 0:12:17 time: 0.0470 data: 0.0015 max mem: 19788 +Test: [ 6100/21770] eta: 0:12:13 time: 0.0464 data: 0.0015 max mem: 19788 +Test: [ 6200/21770] eta: 0:12:08 time: 0.0515 data: 0.0017 max mem: 19788 +Test: [ 6300/21770] eta: 0:12:04 time: 0.0528 data: 0.0018 max mem: 19788 +Test: [ 6400/21770] eta: 0:12:00 time: 0.0433 data: 0.0015 max mem: 19788 +Test: [ 6500/21770] eta: 0:11:55 time: 0.0474 data: 0.0017 max mem: 19788 +Test: [ 6600/21770] eta: 0:11:51 time: 0.0435 data: 0.0015 max mem: 19788 +Test: [ 6700/21770] eta: 0:11:46 time: 0.0507 data: 0.0018 max mem: 19788 +Test: [ 6800/21770] eta: 0:11:41 time: 0.0449 data: 0.0017 max mem: 19788 +Test: [ 6900/21770] eta: 0:11:36 time: 0.0436 data: 0.0016 max mem: 19788 +Test: [ 7000/21770] eta: 0:11:31 time: 0.0462 data: 0.0014 max mem: 19788 +Test: [ 7100/21770] eta: 0:11:26 time: 0.0440 data: 0.0015 max mem: 19788 +Test: [ 7200/21770] eta: 0:11:22 time: 0.0524 data: 0.0018 max mem: 19788 +Test: [ 7300/21770] eta: 0:11:17 time: 0.0549 data: 0.0015 max mem: 19788 +Test: [ 7400/21770] eta: 0:11:13 time: 0.0473 data: 0.0016 max mem: 19788 +Test: [ 7500/21770] eta: 0:11:08 time: 0.0519 data: 0.0016 max mem: 19788 +Test: [ 7600/21770] eta: 0:11:03 time: 0.0441 data: 0.0013 max mem: 19788 +Test: [ 7700/21770] eta: 0:10:58 time: 0.0438 data: 0.0014 max mem: 19788 +Test: [ 7800/21770] eta: 0:10:53 time: 0.0482 data: 0.0016 max mem: 19788 +Test: [ 7900/21770] eta: 0:10:48 time: 0.0437 data: 0.0015 max mem: 19788 +Test: [ 8000/21770] eta: 0:10:43 time: 0.0443 data: 0.0016 max mem: 19788 +Test: [ 8100/21770] eta: 0:10:38 time: 0.0437 data: 0.0017 max mem: 19788 +Test: [ 8200/21770] eta: 0:10:34 time: 0.0437 data: 0.0015 max mem: 19788 +Test: [ 8300/21770] eta: 0:10:29 time: 0.0428 data: 0.0014 max mem: 19788 +Test: [ 8400/21770] eta: 0:10:23 time: 0.0435 data: 0.0015 max mem: 19788 +Test: [ 8500/21770] eta: 0:10:19 time: 0.0458 data: 0.0015 max mem: 19788 +Test: [ 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time: 0.0431 data: 0.0015 max mem: 19788 +Test: [10000/21770] eta: 0:09:08 time: 0.0441 data: 0.0015 max mem: 19788 +Test: [10100/21770] eta: 0:09:04 time: 0.0450 data: 0.0014 max mem: 19788 +Test: [10200/21770] eta: 0:09:00 time: 0.0540 data: 0.0015 max mem: 19788 +Test: [10300/21770] eta: 0:08:55 time: 0.0454 data: 0.0016 max mem: 19788 +Test: [10400/21770] eta: 0:08:50 time: 0.0509 data: 0.0017 max mem: 19788 +Test: [10500/21770] eta: 0:08:46 time: 0.0476 data: 0.0015 max mem: 19788 +Test: [10600/21770] eta: 0:08:42 time: 0.0517 data: 0.0017 max mem: 19788 +Test: [10700/21770] eta: 0:08:37 time: 0.0440 data: 0.0014 max mem: 19788 +Test: [10800/21770] eta: 0:08:32 time: 0.0450 data: 0.0015 max mem: 19788 +Test: [10900/21770] eta: 0:08:28 time: 0.0456 data: 0.0015 max mem: 19788 +Test: [11000/21770] eta: 0:08:23 time: 0.0487 data: 0.0016 max mem: 19788 +Test: [11100/21770] eta: 0:08:19 time: 0.0465 data: 0.0015 max mem: 19788 +Test: [11200/21770] eta: 0:08:14 time: 0.0429 data: 0.0014 max mem: 19788 +Test: [11300/21770] eta: 0:08:09 time: 0.0440 data: 0.0014 max mem: 19788 +Test: [11400/21770] eta: 0:08:04 time: 0.0434 data: 0.0014 max mem: 19788 +Test: [11500/21770] eta: 0:08:00 time: 0.0437 data: 0.0013 max mem: 19788 +Test: [11600/21770] eta: 0:07:55 time: 0.0443 data: 0.0015 max mem: 19788 +Test: [11700/21770] eta: 0:07:50 time: 0.0440 data: 0.0016 max mem: 19788 +Test: [11800/21770] eta: 0:07:46 time: 0.0513 data: 0.0017 max mem: 19788 +Test: [11900/21770] eta: 0:07:41 time: 0.0514 data: 0.0017 max mem: 19788 +Test: [12000/21770] eta: 0:07:37 time: 0.0518 data: 0.0016 max mem: 19788 +Test: [12100/21770] eta: 0:07:32 time: 0.0448 data: 0.0014 max mem: 19788 +Test: [12200/21770] eta: 0:07:28 time: 0.0526 data: 0.0017 max mem: 19788 +Test: [12300/21770] eta: 0:07:23 time: 0.0443 data: 0.0016 max mem: 19788 +Test: [12400/21770] eta: 0:07:18 time: 0.0450 data: 0.0015 max mem: 19788 +Test: [12500/21770] eta: 0:07:14 time: 0.0529 data: 0.0018 max mem: 19788 +Test: [12600/21770] eta: 0:07:09 time: 0.0437 data: 0.0013 max mem: 19788 +Test: [12700/21770] eta: 0:07:04 time: 0.0439 data: 0.0014 max mem: 19788 +Test: [12800/21770] eta: 0:06:59 time: 0.0512 data: 0.0016 max mem: 19788 +Test: [12900/21770] eta: 0:06:55 time: 0.0518 data: 0.0018 max mem: 19788 +Test: [13000/21770] eta: 0:06:50 time: 0.0527 data: 0.0016 max mem: 19788 +Test: [13100/21770] eta: 0:06:46 time: 0.0530 data: 0.0018 max mem: 19788 +Test: [13200/21770] eta: 0:06:41 time: 0.0446 data: 0.0014 max mem: 19788 +Test: [13300/21770] eta: 0:06:36 time: 0.0443 data: 0.0015 max mem: 19788 +Test: [13400/21770] eta: 0:06:31 time: 0.0442 data: 0.0013 max mem: 19788 +Test: [13500/21770] eta: 0:06:27 time: 0.0529 data: 0.0018 max mem: 19788 +Test: [13600/21770] eta: 0:06:22 time: 0.0458 data: 0.0016 max mem: 19788 +Test: [13700/21770] eta: 0:06:17 time: 0.0524 data: 0.0018 max mem: 19788 +Test: [13800/21770] eta: 0:06:13 time: 0.0455 data: 0.0017 max mem: 19788 +Test: [13900/21770] eta: 0:06:08 time: 0.0454 data: 0.0016 max mem: 19788 +Test: [14000/21770] eta: 0:06:03 time: 0.0447 data: 0.0016 max mem: 19788 +Test: [14100/21770] eta: 0:05:59 time: 0.0523 data: 0.0017 max mem: 19788 +Test: [14200/21770] eta: 0:05:54 time: 0.0430 data: 0.0013 max mem: 19788 +Test: [14300/21770] eta: 0:05:49 time: 0.0434 data: 0.0013 max mem: 19788 +Test: [14400/21770] eta: 0:05:44 time: 0.0443 data: 0.0014 max mem: 19788 +Test: [14500/21770] eta: 0:05:40 time: 0.0539 data: 0.0016 max mem: 19788 +Test: [14600/21770] eta: 0:05:35 time: 0.0434 data: 0.0014 max mem: 19788 +Test: [14700/21770] eta: 0:05:30 time: 0.0448 data: 0.0015 max mem: 19788 +Test: [14800/21770] eta: 0:05:25 time: 0.0510 data: 0.0017 max mem: 19788 +Test: [14900/21770] eta: 0:05:21 time: 0.0429 data: 0.0015 max mem: 19788 +Test: [15000/21770] eta: 0:05:16 time: 0.0458 data: 0.0016 max mem: 19788 +Test: [15100/21770] eta: 0:05:11 time: 0.0493 data: 0.0015 max mem: 19788 +Test: [15200/21770] eta: 0:05:07 time: 0.0471 data: 0.0016 max mem: 19788 +Test: [15300/21770] eta: 0:05:02 time: 0.0537 data: 0.0018 max mem: 19788 +Test: [15400/21770] eta: 0:04:58 time: 0.0437 data: 0.0013 max mem: 19788 +Test: [15500/21770] eta: 0:04:53 time: 0.0454 data: 0.0014 max mem: 19788 +Test: [15600/21770] eta: 0:04:48 time: 0.0469 data: 0.0016 max mem: 19788 +Test: [15700/21770] eta: 0:04:43 time: 0.0517 data: 0.0014 max mem: 19788 +Test: [15800/21770] eta: 0:04:39 time: 0.0456 data: 0.0015 max mem: 19788 +Test: [15900/21770] eta: 0:04:34 time: 0.0494 data: 0.0015 max mem: 19788 +Test: [16000/21770] eta: 0:04:29 time: 0.0455 data: 0.0014 max mem: 19788 +Test: [16100/21770] eta: 0:04:25 time: 0.0441 data: 0.0015 max mem: 19788 +Test: [16200/21770] eta: 0:04:20 time: 0.0500 data: 0.0017 max mem: 19788 +Test: [16300/21770] eta: 0:04:16 time: 0.0520 data: 0.0018 max mem: 19788 +Test: [16400/21770] eta: 0:04:11 time: 0.0437 data: 0.0015 max mem: 19788 +Test: [16500/21770] eta: 0:04:06 time: 0.0433 data: 0.0014 max mem: 19788 +Test: [16600/21770] eta: 0:04:02 time: 0.0486 data: 0.0016 max mem: 19788 +Test: [16700/21770] eta: 0:03:57 time: 0.0431 data: 0.0016 max mem: 19788 +Test: [16800/21770] eta: 0:03:52 time: 0.0436 data: 0.0017 max mem: 19788 +Test: [16900/21770] eta: 0:03:47 time: 0.0435 data: 0.0014 max mem: 19788 +Test: [17000/21770] eta: 0:03:43 time: 0.0449 data: 0.0015 max mem: 19788 +Test: [17100/21770] eta: 0:03:38 time: 0.0457 data: 0.0016 max mem: 19788 +Test: [17200/21770] eta: 0:03:33 time: 0.0436 data: 0.0015 max mem: 19788 +Test: [17300/21770] eta: 0:03:29 time: 0.0443 data: 0.0013 max mem: 19788 +Test: [17400/21770] eta: 0:03:24 time: 0.0431 data: 0.0016 max mem: 19788 +Test: [17500/21770] eta: 0:03:19 time: 0.0518 data: 0.0015 max mem: 19788 +Test: [17600/21770] eta: 0:03:15 time: 0.0445 data: 0.0013 max mem: 19788 +Test: [17700/21770] eta: 0:03:10 time: 0.0478 data: 0.0015 max mem: 19788 +Test: [17800/21770] eta: 0:03:05 time: 0.0453 data: 0.0017 max mem: 19788 +Test: [17900/21770] eta: 0:03:01 time: 0.0497 data: 0.0015 max mem: 19788 +Test: [18000/21770] eta: 0:02:56 time: 0.0470 data: 0.0016 max mem: 19788 +Test: [18100/21770] eta: 0:02:51 time: 0.0481 data: 0.0017 max mem: 19788 +Test: [18200/21770] eta: 0:02:47 time: 0.0438 data: 0.0015 max mem: 19788 +Test: [18300/21770] eta: 0:02:42 time: 0.0447 data: 0.0014 max mem: 19788 +Test: [18400/21770] eta: 0:02:37 time: 0.0502 data: 0.0016 max mem: 19788 +Test: [18500/21770] eta: 0:02:33 time: 0.0446 data: 0.0013 max mem: 19788 +Test: [18600/21770] eta: 0:02:28 time: 0.0432 data: 0.0013 max mem: 19788 +Test: [18700/21770] eta: 0:02:23 time: 0.0496 data: 0.0016 max mem: 19788 +Test: [18800/21770] eta: 0:02:19 time: 0.0500 data: 0.0016 max mem: 19788 +Test: [18900/21770] eta: 0:02:14 time: 0.0445 data: 0.0013 max mem: 19788 +Test: [19000/21770] eta: 0:02:09 time: 0.0454 data: 0.0015 max mem: 19788 +Test: [19100/21770] eta: 0:02:04 time: 0.0431 data: 0.0014 max mem: 19788 +Test: [19200/21770] eta: 0:02:00 time: 0.0465 data: 0.0015 max mem: 19788 +Test: [19300/21770] eta: 0:01:55 time: 0.0428 data: 0.0015 max mem: 19788 +Test: [19400/21770] eta: 0:01:50 time: 0.0468 data: 0.0015 max mem: 19788 +Test: [19500/21770] eta: 0:01:46 time: 0.0436 data: 0.0015 max mem: 19788 +Test: [19600/21770] eta: 0:01:41 time: 0.0520 data: 0.0017 max mem: 19788 +Test: [19700/21770] eta: 0:01:36 time: 0.0428 data: 0.0014 max mem: 19788 +Test: [19800/21770] eta: 0:01:32 time: 0.0442 data: 0.0015 max mem: 19788 +Test: [19900/21770] eta: 0:01:27 time: 0.0434 data: 0.0015 max mem: 19788 +Test: [20000/21770] eta: 0:01:22 time: 0.0443 data: 0.0014 max mem: 19788 +Test: [20100/21770] eta: 0:01:18 time: 0.0484 data: 0.0016 max mem: 19788 +Test: [20200/21770] eta: 0:01:13 time: 0.0498 data: 0.0015 max mem: 19788 +Test: [20300/21770] eta: 0:01:08 time: 0.0460 data: 0.0016 max mem: 19788 +Test: [20400/21770] eta: 0:01:04 time: 0.0429 data: 0.0013 max mem: 19788 +Test: [20500/21770] eta: 0:00:59 time: 0.0489 data: 0.0016 max mem: 19788 +Test: [20600/21770] eta: 0:00:54 time: 0.0540 data: 0.0018 max mem: 19788 +Test: [20700/21770] eta: 0:00:50 time: 0.0439 data: 0.0014 max mem: 19788 +Test: [20800/21770] eta: 0:00:45 time: 0.0440 data: 0.0016 max mem: 19788 +Test: [20900/21770] eta: 0:00:40 time: 0.0432 data: 0.0015 max mem: 19788 +Test: [21000/21770] eta: 0:00:36 time: 0.0518 data: 0.0017 max mem: 19788 +Test: [21100/21770] eta: 0:00:31 time: 0.0437 data: 0.0015 max mem: 19788 +Test: [21200/21770] eta: 0:00:26 time: 0.0448 data: 0.0016 max mem: 19788 +Test: [21300/21770] eta: 0:00:21 time: 0.0498 data: 0.0017 max mem: 19788 +Test: [21400/21770] eta: 0:00:17 time: 0.0523 data: 0.0017 max mem: 19788 +Test: [21500/21770] eta: 0:00:12 time: 0.0440 data: 0.0013 max mem: 19788 +Test: [21600/21770] eta: 0:00:07 time: 0.0485 data: 0.0015 max mem: 19788 +Test: [21700/21770] eta: 0:00:03 time: 0.0527 data: 0.0018 max mem: 19788 +Test: Total time: 0:16:58 +Final results: +Mean IoU is 64.66 + + precision@0.5 = 72.03 + precision@0.6 = 66.63 + precision@0.7 = 60.24 + precision@0.8 = 49.52 + precision@0.9 = 24.25 + overall IoU = 65.23 + mean IoU = 64.66 + +Mean accuracy for one-to-zero sample is 87.11 + +Average object IoU 0.6466488183306327 +Overall IoU 65.23008728027344 +Better epoch: 34 + +Epoch: [35] [ 0/2138] eta: 4:21:07 lr: 7.694004761168391e-06 loss: 0.0274 (0.0274) time: 7.3280 data: 1.3593 max mem: 19788 +Epoch: [35] [ 10/2138] eta: 2:00:32 lr: 7.687526205355074e-06 loss: 0.0182 (0.0199) time: 3.3986 data: 0.1261 max mem: 19788 +Epoch: [35] [ 20/2138] eta: 1:52:44 lr: 7.681047042850111e-06 loss: 0.0172 (0.0183) time: 2.9870 data: 0.0023 max mem: 19788 +Epoch: [35] [ 30/2138] eta: 1:49:15 lr: 7.674567273027946e-06 loss: 0.0183 (0.0190) time: 2.9510 data: 0.0022 max mem: 19788 +Epoch: [35] [ 40/2138] eta: 1:46:40 lr: 7.668086895261816e-06 loss: 0.0184 (0.0192) time: 2.9010 data: 0.0027 max mem: 19788 +Epoch: [35] [ 50/2138] eta: 1:44:52 lr: 7.661605908923695e-06 loss: 0.0180 (0.0191) time: 2.8643 data: 0.0026 max mem: 19788 +Epoch: [35] [ 60/2138] eta: 1:43:29 lr: 7.655124313384348e-06 loss: 0.0188 (0.0196) time: 2.8602 data: 0.0026 max mem: 19788 +Epoch: [35] [ 70/2138] eta: 1:42:20 lr: 7.648642108013265e-06 loss: 0.0178 (0.0195) time: 2.8571 data: 0.0025 max mem: 19788 +Epoch: [35] [ 80/2138] eta: 1:41:25 lr: 7.642159292178717e-06 loss: 0.0178 (0.0195) time: 2.8612 data: 0.0022 max mem: 19788 +Epoch: [35] [ 90/2138] eta: 1:40:33 lr: 7.635675865247698e-06 loss: 0.0174 (0.0192) time: 2.8627 data: 0.0022 max mem: 19788 +Epoch: [35] [ 100/2138] eta: 1:39:52 lr: 7.629191826585974e-06 loss: 0.0163 (0.0191) time: 2.8738 data: 0.0024 max mem: 19788 +Epoch: [35] [ 110/2138] eta: 1:39:13 lr: 7.6227071755580306e-06 loss: 0.0172 (0.0189) time: 2.8894 data: 0.0026 max mem: 19788 +Epoch: [35] [ 120/2138] eta: 1:38:42 lr: 7.616221911527111e-06 loss: 0.0162 (0.0189) time: 2.9066 data: 0.0028 max mem: 19788 +Epoch: [35] [ 130/2138] eta: 1:38:23 lr: 7.609736033855172e-06 loss: 0.0183 (0.0189) time: 2.9632 data: 0.0027 max mem: 19788 +Epoch: [35] [ 140/2138] eta: 1:37:42 lr: 7.6032495419029265e-06 loss: 0.0186 (0.0190) time: 2.9307 data: 0.0023 max mem: 19788 +Epoch: [35] [ 150/2138] eta: 1:37:00 lr: 7.5967624350297885e-06 loss: 0.0186 (0.0189) time: 2.8481 data: 0.0021 max mem: 19788 +Epoch: [35] [ 160/2138] eta: 1:36:21 lr: 7.5902747125939214e-06 loss: 0.0186 (0.0189) time: 2.8418 data: 0.0022 max mem: 19788 +Epoch: [35] [ 170/2138] eta: 1:35:40 lr: 7.5837863739521825e-06 loss: 0.0175 (0.0188) time: 2.8339 data: 0.0022 max mem: 19788 +Epoch: [35] [ 180/2138] eta: 1:35:03 lr: 7.57729741846017e-06 loss: 0.0179 (0.0188) time: 2.8340 data: 0.0024 max mem: 19788 +Epoch: [35] [ 190/2138] eta: 1:34:25 lr: 7.570807845472172e-06 loss: 0.0179 (0.0187) time: 2.8372 data: 0.0028 max mem: 19788 +Epoch: [35] [ 200/2138] eta: 1:33:48 lr: 7.564317654341205e-06 loss: 0.0161 (0.0186) time: 2.8243 data: 0.0029 max mem: 19788 +Epoch: [35] [ 210/2138] eta: 1:33:15 lr: 7.557826844418969e-06 loss: 0.0180 (0.0187) time: 2.8417 data: 0.0026 max mem: 19788 +Epoch: [35] [ 220/2138] eta: 1:32:43 lr: 7.551335415055888e-06 loss: 0.0180 (0.0186) time: 2.8643 data: 0.0022 max mem: 19788 +Epoch: [35] [ 230/2138] eta: 1:32:15 lr: 7.544843365601066e-06 loss: 0.0170 (0.0187) time: 2.8921 data: 0.0023 max mem: 19788 +Epoch: [35] [ 240/2138] eta: 1:31:47 lr: 7.538350695402299e-06 loss: 0.0175 (0.0186) time: 2.9140 data: 0.0027 max mem: 19788 +Epoch: [35] [ 250/2138] eta: 1:31:14 lr: 7.53185740380609e-06 loss: 0.0179 (0.0186) time: 2.8805 data: 0.0027 max mem: 19788 +Epoch: [35] [ 260/2138] eta: 1:30:41 lr: 7.525363490157605e-06 loss: 0.0179 (0.0186) time: 2.8461 data: 0.0027 max mem: 19788 +Epoch: [35] [ 270/2138] eta: 1:30:08 lr: 7.518868953800712e-06 loss: 0.0180 (0.0186) time: 2.8443 data: 0.0026 max mem: 19788 +Epoch: [35] [ 280/2138] eta: 1:29:35 lr: 7.5123737940779345e-06 loss: 0.0180 (0.0185) time: 2.8353 data: 0.0024 max mem: 19788 +Epoch: [35] [ 290/2138] eta: 1:29:02 lr: 7.5058780103304945e-06 loss: 0.0179 (0.0186) time: 2.8293 data: 0.0024 max mem: 19788 +Epoch: [35] [ 300/2138] eta: 1:28:29 lr: 7.4993816018982575e-06 loss: 0.0177 (0.0186) time: 2.8299 data: 0.0027 max mem: 19788 +Epoch: [35] [ 310/2138] eta: 1:27:57 lr: 7.49288456811978e-06 loss: 0.0171 (0.0185) time: 2.8254 data: 0.0025 max mem: 19788 +Epoch: [35] [ 320/2138] eta: 1:27:28 lr: 7.486386908332256e-06 loss: 0.0158 (0.0185) time: 2.8549 data: 0.0021 max mem: 19788 +Epoch: [35] [ 330/2138] eta: 1:27:00 lr: 7.479888621871562e-06 loss: 0.0176 (0.0186) time: 2.9017 data: 0.0023 max mem: 19788 +Epoch: [35] [ 340/2138] eta: 1:26:33 lr: 7.473389708072198e-06 loss: 0.0192 (0.0185) time: 2.9199 data: 0.0025 max mem: 19788 +Epoch: [35] [ 350/2138] eta: 1:26:03 lr: 7.466890166267349e-06 loss: 0.0170 (0.0185) time: 2.8956 data: 0.0025 max mem: 19788 +Epoch: [35] [ 360/2138] eta: 1:25:32 lr: 7.4603899957888104e-06 loss: 0.0185 (0.0186) time: 2.8562 data: 0.0023 max mem: 19788 +Epoch: [35] [ 370/2138] eta: 1:25:00 lr: 7.45388919596705e-06 loss: 0.0189 (0.0186) time: 2.8317 data: 0.0022 max mem: 19788 +Epoch: [35] [ 380/2138] eta: 1:24:29 lr: 7.4473877661311435e-06 loss: 0.0172 (0.0185) time: 2.8270 data: 0.0022 max mem: 19788 +Epoch: [35] [ 390/2138] eta: 1:23:58 lr: 7.44088570560883e-06 loss: 0.0157 (0.0185) time: 2.8365 data: 0.0026 max mem: 19788 +Epoch: [35] [ 400/2138] eta: 1:23:27 lr: 7.43438301372645e-06 loss: 0.0166 (0.0185) time: 2.8348 data: 0.0028 max mem: 19788 +Epoch: [35] [ 410/2138] eta: 1:22:56 lr: 7.427879689808992e-06 loss: 0.0171 (0.0184) time: 2.8298 data: 0.0027 max mem: 19788 +Epoch: [35] [ 420/2138] eta: 1:22:27 lr: 7.421375733180044e-06 loss: 0.0161 (0.0184) time: 2.8452 data: 0.0025 max mem: 19788 +Epoch: [35] [ 430/2138] eta: 1:21:57 lr: 7.414871143161833e-06 loss: 0.0172 (0.0184) time: 2.8602 data: 0.0021 max mem: 19788 +Epoch: [35] [ 440/2138] eta: 1:21:29 lr: 7.4083659190751765e-06 loss: 0.0196 (0.0185) time: 2.8761 data: 0.0022 max mem: 19788 +Epoch: [35] [ 450/2138] eta: 1:21:03 lr: 7.401860060239522e-06 loss: 0.0197 (0.0185) time: 2.9280 data: 0.0023 max mem: 19788 +Epoch: [35] [ 460/2138] eta: 1:20:34 lr: 7.395353565972898e-06 loss: 0.0175 (0.0185) time: 2.9156 data: 0.0022 max mem: 19788 +Epoch: [35] [ 470/2138] eta: 1:20:03 lr: 7.388846435591958e-06 loss: 0.0182 (0.0185) time: 2.8522 data: 0.0021 max mem: 19788 +Epoch: [35] [ 480/2138] eta: 1:19:33 lr: 7.3823386684119245e-06 loss: 0.0197 (0.0185) time: 2.8304 data: 0.0023 max mem: 19788 +Epoch: [35] [ 490/2138] eta: 1:19:02 lr: 7.375830263746638e-06 loss: 0.0191 (0.0185) time: 2.8270 data: 0.0025 max mem: 19788 +Epoch: [35] [ 500/2138] eta: 1:18:32 lr: 7.369321220908502e-06 loss: 0.0165 (0.0185) time: 2.8279 data: 0.0024 max mem: 19788 +Epoch: [35] [ 510/2138] eta: 1:18:01 lr: 7.362811539208524e-06 loss: 0.0149 (0.0184) time: 2.8258 data: 0.0025 max mem: 19788 +Epoch: [35] [ 520/2138] eta: 1:17:31 lr: 7.3563012179562755e-06 loss: 0.0150 (0.0184) time: 2.8306 data: 0.0024 max mem: 19788 +Epoch: [35] [ 530/2138] eta: 1:17:03 lr: 7.349790256459899e-06 loss: 0.0167 (0.0184) time: 2.8691 data: 0.0023 max mem: 19788 +Epoch: [35] [ 540/2138] eta: 1:16:36 lr: 7.343278654026125e-06 loss: 0.0167 (0.0185) time: 2.9037 data: 0.0023 max mem: 19788 +Epoch: [35] [ 550/2138] eta: 1:16:08 lr: 7.3367664099602315e-06 loss: 0.0164 (0.0184) time: 2.9192 data: 0.0022 max mem: 19788 +Epoch: [35] [ 560/2138] eta: 1:15:40 lr: 7.330253523566072e-06 loss: 0.0178 (0.0185) time: 2.9161 data: 0.0024 max mem: 19788 +Epoch: [35] [ 570/2138] eta: 1:15:10 lr: 7.323739994146038e-06 loss: 0.0175 (0.0184) time: 2.8679 data: 0.0026 max mem: 19788 +Epoch: [35] [ 580/2138] eta: 1:14:41 lr: 7.317225821001099e-06 loss: 0.0165 (0.0185) time: 2.8381 data: 0.0026 max mem: 19788 +Epoch: [35] [ 590/2138] eta: 1:14:11 lr: 7.310711003430744e-06 loss: 0.0183 (0.0185) time: 2.8365 data: 0.0023 max mem: 19788 +Epoch: [35] [ 600/2138] eta: 1:13:41 lr: 7.304195540733031e-06 loss: 0.0168 (0.0185) time: 2.8378 data: 0.0024 max mem: 19788 +Epoch: [35] [ 610/2138] eta: 1:13:12 lr: 7.297679432204533e-06 loss: 0.0177 (0.0185) time: 2.8409 data: 0.0026 max mem: 19788 +Epoch: [35] [ 620/2138] eta: 1:12:42 lr: 7.291162677140381e-06 loss: 0.0189 (0.0185) time: 2.8329 data: 0.0027 max mem: 19788 +Epoch: [35] [ 630/2138] eta: 1:12:12 lr: 7.284645274834213e-06 loss: 0.0189 (0.0185) time: 2.8327 data: 0.0026 max mem: 19788 +Epoch: [35] [ 640/2138] eta: 1:11:44 lr: 7.278127224578214e-06 loss: 0.0180 (0.0185) time: 2.8672 data: 0.0027 max mem: 19788 +Epoch: [35] [ 650/2138] eta: 1:11:15 lr: 7.2716085256630695e-06 loss: 0.0178 (0.0186) time: 2.8829 data: 0.0027 max mem: 19788 +Epoch: [35] [ 660/2138] eta: 1:10:47 lr: 7.265089177378e-06 loss: 0.0188 (0.0186) time: 2.8935 data: 0.0026 max mem: 19788 +Epoch: [35] [ 670/2138] eta: 1:10:19 lr: 7.258569179010717e-06 loss: 0.0185 (0.0186) time: 2.9101 data: 0.0027 max mem: 19788 +Epoch: [35] [ 680/2138] eta: 1:09:50 lr: 7.252048529847464e-06 loss: 0.0170 (0.0186) time: 2.8805 data: 0.0028 max mem: 19788 +Epoch: [35] [ 690/2138] eta: 1:09:20 lr: 7.245527229172957e-06 loss: 0.0175 (0.0186) time: 2.8455 data: 0.0027 max mem: 19788 +Epoch: [35] [ 700/2138] eta: 1:08:51 lr: 7.239005276270443e-06 loss: 0.0180 (0.0185) time: 2.8377 data: 0.0027 max mem: 19788 +Epoch: [35] [ 710/2138] eta: 1:08:21 lr: 7.232482670421631e-06 loss: 0.0173 (0.0185) time: 2.8293 data: 0.0027 max mem: 19788 +Epoch: [35] [ 720/2138] eta: 1:07:51 lr: 7.225959410906742e-06 loss: 0.0162 (0.0185) time: 2.8177 data: 0.0023 max mem: 19788 +Epoch: [35] [ 730/2138] eta: 1:07:22 lr: 7.219435497004463e-06 loss: 0.0161 (0.0185) time: 2.8178 data: 0.0020 max mem: 19788 +Epoch: [35] [ 740/2138] eta: 1:06:53 lr: 7.212910927991977e-06 loss: 0.0201 (0.0185) time: 2.8333 data: 0.0022 max mem: 19788 +Epoch: [35] [ 750/2138] eta: 1:06:24 lr: 7.20638570314492e-06 loss: 0.0190 (0.0185) time: 2.8598 data: 0.0024 max mem: 19788 +Epoch: [35] [ 760/2138] eta: 1:05:55 lr: 7.1998598217374245e-06 loss: 0.0186 (0.0185) time: 2.8759 data: 0.0027 max mem: 19788 +Epoch: [35] [ 770/2138] eta: 1:05:27 lr: 7.193333283042057e-06 loss: 0.0176 (0.0185) time: 2.8879 data: 0.0026 max mem: 19788 +Epoch: [35] [ 780/2138] eta: 1:04:58 lr: 7.186806086329874e-06 loss: 0.0167 (0.0185) time: 2.8600 data: 0.0024 max mem: 19788 +Epoch: [35] [ 790/2138] eta: 1:04:28 lr: 7.18027823087036e-06 loss: 0.0167 (0.0185) time: 2.8306 data: 0.0025 max mem: 19788 +Epoch: [35] [ 800/2138] eta: 1:03:59 lr: 7.173749715931474e-06 loss: 0.0178 (0.0185) time: 2.8303 data: 0.0024 max mem: 19788 +Epoch: [35] [ 810/2138] eta: 1:03:30 lr: 7.1672205407795966e-06 loss: 0.0183 (0.0185) time: 2.8384 data: 0.0025 max mem: 19788 +Epoch: [35] [ 820/2138] eta: 1:03:00 lr: 7.160690704679575e-06 loss: 0.0178 (0.0185) time: 2.8373 data: 0.0024 max mem: 19788 +Epoch: [35] [ 830/2138] eta: 1:02:31 lr: 7.154160206894669e-06 loss: 0.0169 (0.0185) time: 2.8293 data: 0.0024 max mem: 19788 +Epoch: [35] [ 840/2138] eta: 1:02:02 lr: 7.147629046686574e-06 loss: 0.0161 (0.0185) time: 2.8285 data: 0.0024 max mem: 19788 +Epoch: [35] [ 850/2138] eta: 1:01:33 lr: 7.141097223315428e-06 loss: 0.0174 (0.0185) time: 2.8450 data: 0.0023 max mem: 19788 +Epoch: [35] [ 860/2138] eta: 1:01:04 lr: 7.134564736039762e-06 loss: 0.0173 (0.0185) time: 2.8601 data: 0.0023 max mem: 19788 +Epoch: [35] [ 870/2138] eta: 1:00:36 lr: 7.128031584116551e-06 loss: 0.0169 (0.0185) time: 2.8790 data: 0.0026 max mem: 19788 +Epoch: [35] [ 880/2138] eta: 1:00:08 lr: 7.121497766801155e-06 loss: 0.0167 (0.0184) time: 2.8989 data: 0.0028 max mem: 19788 +Epoch: [35] [ 890/2138] eta: 0:59:38 lr: 7.114963283347366e-06 loss: 0.0171 (0.0184) time: 2.8586 data: 0.0026 max mem: 19788 +Epoch: [35] [ 900/2138] eta: 0:59:09 lr: 7.1084281330073496e-06 loss: 0.0178 (0.0184) time: 2.8296 data: 0.0026 max mem: 19788 +Epoch: [35] [ 910/2138] eta: 0:58:40 lr: 7.1018923150316925e-06 loss: 0.0166 (0.0184) time: 2.8291 data: 0.0027 max mem: 19788 +Epoch: [35] [ 920/2138] eta: 0:58:11 lr: 7.095355828669348e-06 loss: 0.0171 (0.0184) time: 2.8272 data: 0.0029 max mem: 19788 +Epoch: [35] [ 930/2138] eta: 0:57:42 lr: 7.088818673167677e-06 loss: 0.0180 (0.0185) time: 2.8277 data: 0.0029 max mem: 19788 +Epoch: [35] [ 940/2138] eta: 0:57:12 lr: 7.082280847772402e-06 loss: 0.0201 (0.0185) time: 2.8238 data: 0.0025 max mem: 19788 +Epoch: [35] [ 950/2138] eta: 0:56:43 lr: 7.075742351727637e-06 loss: 0.0178 (0.0185) time: 2.8279 data: 0.0021 max mem: 19788 +Epoch: [35] [ 960/2138] eta: 0:56:15 lr: 7.069203184275848e-06 loss: 0.0194 (0.0185) time: 2.8682 data: 0.0021 max mem: 19788 +Epoch: [35] [ 970/2138] eta: 0:55:47 lr: 7.06266334465789e-06 loss: 0.0200 (0.0185) time: 2.9029 data: 0.0021 max mem: 19788 +Epoch: [35] [ 980/2138] eta: 0:55:19 lr: 7.056122832112947e-06 loss: 0.0161 (0.0185) time: 2.9109 data: 0.0024 max mem: 19788 +Epoch: [35] [ 990/2138] eta: 0:54:50 lr: 7.049581645878589e-06 loss: 0.0160 (0.0185) time: 2.8864 data: 0.0026 max mem: 19788 +Epoch: [35] [1000/2138] eta: 0:54:21 lr: 7.043039785190705e-06 loss: 0.0157 (0.0185) time: 2.8424 data: 0.0024 max mem: 19788 +Epoch: [35] [1010/2138] eta: 0:53:52 lr: 7.0364972492835595e-06 loss: 0.0157 (0.0185) time: 2.8269 data: 0.0024 max mem: 19788 +Epoch: [35] [1020/2138] eta: 0:53:23 lr: 7.029954037389721e-06 loss: 0.0158 (0.0185) time: 2.8244 data: 0.0025 max mem: 19788 +Epoch: [35] [1030/2138] eta: 0:52:54 lr: 7.023410148740126e-06 loss: 0.0161 (0.0185) time: 2.8251 data: 0.0026 max mem: 19788 +Epoch: [35] [1040/2138] eta: 0:52:25 lr: 7.016865582564006e-06 loss: 0.0183 (0.0185) time: 2.8269 data: 0.0028 max mem: 19788 +Epoch: [35] [1050/2138] eta: 0:51:56 lr: 7.010320338088945e-06 loss: 0.0186 (0.0185) time: 2.8324 data: 0.0028 max mem: 19788 +Epoch: [35] [1060/2138] eta: 0:51:27 lr: 7.003774414540815e-06 loss: 0.0186 (0.0185) time: 2.8468 data: 0.0029 max mem: 19788 +Epoch: [35] [1070/2138] eta: 0:50:58 lr: 6.9972278111438295e-06 loss: 0.0188 (0.0185) time: 2.8630 data: 0.0030 max mem: 19788 +Epoch: [35] [1080/2138] eta: 0:50:30 lr: 6.990680527120479e-06 loss: 0.0175 (0.0185) time: 2.8802 data: 0.0026 max mem: 19788 +Epoch: [35] [1090/2138] eta: 0:50:02 lr: 6.984132561691581e-06 loss: 0.0179 (0.0185) time: 2.8955 data: 0.0022 max mem: 19788 +Epoch: [35] [1100/2138] eta: 0:49:33 lr: 6.9775839140762234e-06 loss: 0.0189 (0.0185) time: 2.8655 data: 0.0025 max mem: 19788 +Epoch: [35] [1110/2138] eta: 0:49:04 lr: 6.971034583491811e-06 loss: 0.0178 (0.0185) time: 2.8317 data: 0.0026 max mem: 19788 +Epoch: [35] [1120/2138] eta: 0:48:35 lr: 6.9644845691540035e-06 loss: 0.0173 (0.0185) time: 2.8278 data: 0.0026 max mem: 19788 +Epoch: [35] [1130/2138] eta: 0:48:06 lr: 6.957933870276767e-06 loss: 0.0162 (0.0185) time: 2.8323 data: 0.0025 max mem: 19788 +Epoch: [35] [1140/2138] eta: 0:47:37 lr: 6.951382486072322e-06 loss: 0.0170 (0.0185) time: 2.8356 data: 0.0022 max mem: 19788 +Epoch: [35] [1150/2138] eta: 0:47:08 lr: 6.9448304157511555e-06 loss: 0.0157 (0.0185) time: 2.8345 data: 0.0021 max mem: 19788 +Epoch: [35] [1160/2138] eta: 0:46:40 lr: 6.938277658522035e-06 loss: 0.0149 (0.0185) time: 2.8439 data: 0.0021 max mem: 19788 +Epoch: [35] [1170/2138] eta: 0:46:11 lr: 6.93172421359196e-06 loss: 0.0167 (0.0184) time: 2.8603 data: 0.0024 max mem: 19788 +Epoch: [35] [1180/2138] eta: 0:45:42 lr: 6.925170080166206e-06 loss: 0.0174 (0.0184) time: 2.8647 data: 0.0024 max mem: 19788 +Epoch: [35] [1190/2138] eta: 0:45:14 lr: 6.918615257448265e-06 loss: 0.0169 (0.0184) time: 2.8928 data: 0.0022 max mem: 19788 +Epoch: [35] [1200/2138] eta: 0:44:46 lr: 6.912059744639897e-06 loss: 0.0169 (0.0184) time: 2.9299 data: 0.0024 max mem: 19788 +Epoch: [35] [1210/2138] eta: 0:44:17 lr: 6.905503540941069e-06 loss: 0.0177 (0.0184) time: 2.8819 data: 0.0023 max mem: 19788 +Epoch: [35] [1220/2138] eta: 0:43:49 lr: 6.898946645549999e-06 loss: 0.0176 (0.0184) time: 2.8449 data: 0.0021 max mem: 19788 +Epoch: [35] [1230/2138] eta: 0:43:20 lr: 6.892389057663104e-06 loss: 0.0165 (0.0184) time: 2.8429 data: 0.0021 max mem: 19788 +Epoch: [35] [1240/2138] eta: 0:42:51 lr: 6.885830776475038e-06 loss: 0.0165 (0.0184) time: 2.8413 data: 0.0023 max mem: 19788 +Epoch: [35] [1250/2138] eta: 0:42:22 lr: 6.879271801178648e-06 loss: 0.0165 (0.0184) time: 2.8452 data: 0.0024 max mem: 19788 +Epoch: [35] [1260/2138] eta: 0:41:53 lr: 6.872712130965002e-06 loss: 0.0162 (0.0184) time: 2.8389 data: 0.0025 max mem: 19788 +Epoch: [35] [1270/2138] eta: 0:41:25 lr: 6.866151765023343e-06 loss: 0.0173 (0.0184) time: 2.8434 data: 0.0026 max mem: 19788 +Epoch: [35] [1280/2138] eta: 0:40:56 lr: 6.859590702541134e-06 loss: 0.0183 (0.0184) time: 2.8565 data: 0.0025 max mem: 19788 +Epoch: [35] [1290/2138] eta: 0:40:27 lr: 6.853028942703998e-06 loss: 0.0182 (0.0184) time: 2.8678 data: 0.0026 max mem: 19788 +Epoch: [35] [1300/2138] eta: 0:39:59 lr: 6.846466484695764e-06 loss: 0.0181 (0.0184) time: 2.9062 data: 0.0026 max mem: 19788 +Epoch: [35] [1310/2138] eta: 0:39:31 lr: 6.839903327698408e-06 loss: 0.0163 (0.0184) time: 2.8992 data: 0.0022 max mem: 19788 +Epoch: [35] [1320/2138] eta: 0:39:02 lr: 6.833339470892102e-06 loss: 0.0176 (0.0184) time: 2.8439 data: 0.0023 max mem: 19788 +Epoch: [35] [1330/2138] eta: 0:38:33 lr: 6.826774913455155e-06 loss: 0.0175 (0.0184) time: 2.8271 data: 0.0025 max mem: 19788 +Epoch: [35] [1340/2138] eta: 0:38:04 lr: 6.820209654564055e-06 loss: 0.0184 (0.0184) time: 2.8233 data: 0.0024 max mem: 19788 +Epoch: [35] [1350/2138] eta: 0:37:35 lr: 6.8136436933934174e-06 loss: 0.0190 (0.0184) time: 2.8238 data: 0.0022 max mem: 19788 +Epoch: [35] [1360/2138] eta: 0:37:06 lr: 6.807077029116027e-06 loss: 0.0180 (0.0184) time: 2.8171 data: 0.0021 max mem: 19788 +Epoch: [35] [1370/2138] eta: 0:36:37 lr: 6.800509660902777e-06 loss: 0.0170 (0.0184) time: 2.8229 data: 0.0022 max mem: 19788 +Epoch: [35] [1380/2138] eta: 0:36:09 lr: 6.793941587922723e-06 loss: 0.0170 (0.0184) time: 2.8562 data: 0.0023 max mem: 19788 +Epoch: [35] [1390/2138] eta: 0:35:40 lr: 6.7873728093430165e-06 loss: 0.0174 (0.0184) time: 2.8860 data: 0.0022 max mem: 19788 +Epoch: [35] [1400/2138] eta: 0:35:12 lr: 6.780803324328956e-06 loss: 0.0164 (0.0184) time: 2.9407 data: 0.0022 max mem: 19788 +Epoch: [35] [1410/2138] eta: 0:34:44 lr: 6.774233132043926e-06 loss: 0.0160 (0.0184) time: 2.9525 data: 0.0026 max mem: 19788 +Epoch: [35] [1420/2138] eta: 0:34:15 lr: 6.767662231649443e-06 loss: 0.0185 (0.0184) time: 2.8727 data: 0.0025 max mem: 19788 +Epoch: [35] [1430/2138] eta: 0:33:46 lr: 6.761090622305101e-06 loss: 0.0186 (0.0184) time: 2.8272 data: 0.0025 max mem: 19788 +Epoch: [35] [1440/2138] eta: 0:33:18 lr: 6.7545183031686064e-06 loss: 0.0193 (0.0184) time: 2.8286 data: 0.0028 max mem: 19788 +Epoch: [35] [1450/2138] eta: 0:32:49 lr: 6.7479452733957436e-06 loss: 0.0193 (0.0184) time: 2.8274 data: 0.0026 max mem: 19788 +Epoch: [35] [1460/2138] eta: 0:32:20 lr: 6.741371532140369e-06 loss: 0.0184 (0.0184) time: 2.8255 data: 0.0023 max mem: 19788 +Epoch: [35] [1470/2138] eta: 0:31:51 lr: 6.734797078554437e-06 loss: 0.0164 (0.0184) time: 2.8332 data: 0.0023 max mem: 19788 +Epoch: [35] [1480/2138] eta: 0:31:23 lr: 6.728221911787946e-06 loss: 0.0158 (0.0184) time: 2.8348 data: 0.0027 max mem: 19788 +Epoch: [35] [1490/2138] eta: 0:30:54 lr: 6.721646030988979e-06 loss: 0.0188 (0.0184) time: 2.8581 data: 0.0030 max mem: 19788 +Epoch: [35] [1500/2138] eta: 0:30:26 lr: 6.715069435303649e-06 loss: 0.0189 (0.0184) time: 2.8766 data: 0.0027 max mem: 19788 +Epoch: [35] [1510/2138] eta: 0:29:57 lr: 6.7084921238761435e-06 loss: 0.0174 (0.0184) time: 2.8885 data: 0.0026 max mem: 19788 +Epoch: [35] [1520/2138] eta: 0:29:29 lr: 6.7019140958486645e-06 loss: 0.0183 (0.0185) time: 2.9185 data: 0.0027 max mem: 19788 +Epoch: [35] [1530/2138] eta: 0:29:00 lr: 6.695335350361479e-06 loss: 0.0186 (0.0185) time: 2.9230 data: 0.0024 max mem: 19788 +Epoch: [35] [1540/2138] eta: 0:28:32 lr: 6.688755886552851e-06 loss: 0.0178 (0.0185) time: 2.9247 data: 0.0025 max mem: 19788 +Epoch: [35] [1550/2138] eta: 0:28:03 lr: 6.682175703559099e-06 loss: 0.0170 (0.0185) time: 2.9064 data: 0.0025 max mem: 19788 +Epoch: [35] [1560/2138] eta: 0:27:35 lr: 6.675594800514526e-06 loss: 0.0170 (0.0185) time: 2.8629 data: 0.0021 max mem: 19788 +Epoch: [35] [1570/2138] eta: 0:27:06 lr: 6.669013176551471e-06 loss: 0.0186 (0.0185) time: 2.8382 data: 0.0022 max mem: 19788 +Epoch: [35] [1580/2138] eta: 0:26:37 lr: 6.66243083080025e-06 loss: 0.0186 (0.0184) time: 2.8286 data: 0.0024 max mem: 19788 +Epoch: [35] [1590/2138] eta: 0:26:08 lr: 6.655847762389197e-06 loss: 0.0174 (0.0184) time: 2.8223 data: 0.0022 max mem: 19788 +Epoch: [35] [1600/2138] eta: 0:25:40 lr: 6.6492639704446105e-06 loss: 0.0206 (0.0185) time: 2.8231 data: 0.0020 max mem: 19788 +Epoch: [35] [1610/2138] eta: 0:25:11 lr: 6.6426794540907945e-06 loss: 0.0202 (0.0185) time: 2.8280 data: 0.0020 max mem: 19788 +Epoch: [35] [1620/2138] eta: 0:24:42 lr: 6.6360942124500045e-06 loss: 0.0164 (0.0185) time: 2.8576 data: 0.0022 max mem: 19788 +Epoch: [35] [1630/2138] eta: 0:24:14 lr: 6.629508244642486e-06 loss: 0.0165 (0.0185) time: 2.9159 data: 0.0024 max mem: 19788 +Epoch: [35] [1640/2138] eta: 0:23:45 lr: 6.622921549786421e-06 loss: 0.0178 (0.0185) time: 2.9246 data: 0.0026 max mem: 19788 +Epoch: [35] [1650/2138] eta: 0:23:17 lr: 6.616334126997968e-06 loss: 0.0184 (0.0185) time: 2.8811 data: 0.0025 max mem: 19788 +Epoch: [35] [1660/2138] eta: 0:22:48 lr: 6.6097459753912115e-06 loss: 0.0184 (0.0185) time: 2.8396 data: 0.0023 max mem: 19788 +Epoch: [35] [1670/2138] eta: 0:22:19 lr: 6.603157094078196e-06 loss: 0.0176 (0.0185) time: 2.8307 data: 0.0023 max mem: 19788 +Epoch: [35] [1680/2138] eta: 0:21:51 lr: 6.596567482168874e-06 loss: 0.0159 (0.0185) time: 2.8379 data: 0.0023 max mem: 19788 +Epoch: [35] [1690/2138] eta: 0:21:22 lr: 6.58997713877115e-06 loss: 0.0173 (0.0184) time: 2.8332 data: 0.0023 max mem: 19788 +Epoch: [35] [1700/2138] eta: 0:20:53 lr: 6.583386062990822e-06 loss: 0.0167 (0.0184) time: 2.8308 data: 0.0025 max mem: 19788 +Epoch: [35] [1710/2138] eta: 0:20:25 lr: 6.5767942539316216e-06 loss: 0.0172 (0.0184) time: 2.8453 data: 0.0026 max mem: 19788 +Epoch: [35] [1720/2138] eta: 0:19:56 lr: 6.570201710695159e-06 loss: 0.0175 (0.0184) time: 2.9078 data: 0.0028 max mem: 19788 +Epoch: [35] [1730/2138] eta: 0:19:28 lr: 6.5636084323809686e-06 loss: 0.0171 (0.0184) time: 2.9793 data: 0.0028 max mem: 19788 +Epoch: [35] [1740/2138] eta: 0:18:59 lr: 6.557014418086453e-06 loss: 0.0171 (0.0184) time: 2.9440 data: 0.0027 max mem: 19788 +Epoch: [35] [1750/2138] eta: 0:18:31 lr: 6.550419666906897e-06 loss: 0.0180 (0.0184) time: 2.8608 data: 0.0025 max mem: 19788 +Epoch: [35] [1760/2138] eta: 0:18:02 lr: 6.543824177935478e-06 loss: 0.0173 (0.0184) time: 2.8379 data: 0.0023 max mem: 19788 +Epoch: [35] [1770/2138] eta: 0:17:33 lr: 6.537227950263218e-06 loss: 0.0162 (0.0184) time: 2.8404 data: 0.0025 max mem: 19788 +Epoch: [35] [1780/2138] eta: 0:17:05 lr: 6.530630982979021e-06 loss: 0.0156 (0.0184) time: 2.8361 data: 0.0028 max mem: 19788 +Epoch: [35] [1790/2138] eta: 0:16:36 lr: 6.524033275169618e-06 loss: 0.0169 (0.0184) time: 2.8303 data: 0.0024 max mem: 19788 +Epoch: [35] [1800/2138] eta: 0:16:07 lr: 6.517434825919612e-06 loss: 0.0216 (0.0185) time: 2.8264 data: 0.0021 max mem: 19788 +Epoch: [35] [1810/2138] eta: 0:15:39 lr: 6.510835634311418e-06 loss: 0.0201 (0.0184) time: 2.8486 data: 0.0025 max mem: 19788 +Epoch: [35] [1820/2138] eta: 0:15:10 lr: 6.504235699425304e-06 loss: 0.0173 (0.0184) time: 2.9089 data: 0.0028 max mem: 19788 +Epoch: [35] [1830/2138] eta: 0:14:42 lr: 6.4976350203393365e-06 loss: 0.0175 (0.0184) time: 2.9513 data: 0.0024 max mem: 19788 +Epoch: [35] [1840/2138] eta: 0:14:13 lr: 6.491033596129421e-06 loss: 0.0187 (0.0184) time: 2.9059 data: 0.0023 max mem: 19788 +Epoch: [35] [1850/2138] eta: 0:13:44 lr: 6.484431425869245e-06 loss: 0.0187 (0.0185) time: 2.8402 data: 0.0024 max mem: 19788 +Epoch: [35] [1860/2138] eta: 0:13:16 lr: 6.477828508630318e-06 loss: 0.0175 (0.0184) time: 2.8328 data: 0.0026 max mem: 19788 +Epoch: [35] [1870/2138] eta: 0:12:47 lr: 6.47122484348192e-06 loss: 0.0179 (0.0185) time: 2.8358 data: 0.0028 max mem: 19788 +Epoch: [35] [1880/2138] eta: 0:12:18 lr: 6.464620429491138e-06 loss: 0.0161 (0.0184) time: 2.8336 data: 0.0026 max mem: 19788 +Epoch: [35] [1890/2138] eta: 0:11:50 lr: 6.458015265722807e-06 loss: 0.0148 (0.0184) time: 2.8289 data: 0.0024 max mem: 19788 +Epoch: [35] [1900/2138] eta: 0:11:21 lr: 6.45140935123956e-06 loss: 0.0163 (0.0184) time: 2.8261 data: 0.0023 max mem: 19788 +Epoch: [35] [1910/2138] eta: 0:10:52 lr: 6.44480268510176e-06 loss: 0.0173 (0.0184) time: 2.8680 data: 0.0023 max mem: 19788 +Epoch: [35] [1920/2138] eta: 0:10:24 lr: 6.438195266367551e-06 loss: 0.0166 (0.0184) time: 2.9160 data: 0.0023 max mem: 19788 +Epoch: [35] [1930/2138] eta: 0:09:55 lr: 6.431587094092796e-06 loss: 0.0166 (0.0184) time: 2.9033 data: 0.0023 max mem: 19788 +Epoch: [35] [1940/2138] eta: 0:09:26 lr: 6.424978167331118e-06 loss: 0.0170 (0.0184) time: 2.8528 data: 0.0023 max mem: 19788 +Epoch: [35] [1950/2138] eta: 0:08:58 lr: 6.418368485133842e-06 loss: 0.0183 (0.0184) time: 2.8260 data: 0.0022 max mem: 19788 +Epoch: [35] [1960/2138] eta: 0:08:29 lr: 6.411758046550041e-06 loss: 0.0181 (0.0184) time: 2.8269 data: 0.0022 max mem: 19788 +Epoch: [35] [1970/2138] eta: 0:08:00 lr: 6.405146850626474e-06 loss: 0.0151 (0.0184) time: 2.8299 data: 0.0021 max mem: 19788 +Epoch: [35] [1980/2138] eta: 0:07:32 lr: 6.398534896407629e-06 loss: 0.0171 (0.0184) time: 2.8327 data: 0.0020 max mem: 19788 +Epoch: [35] [1990/2138] eta: 0:07:03 lr: 6.391922182935664e-06 loss: 0.0172 (0.0184) time: 2.8312 data: 0.0021 max mem: 19788 +Epoch: [35] [2000/2138] eta: 0:06:35 lr: 6.385308709250451e-06 loss: 0.0163 (0.0184) time: 2.8439 data: 0.0023 max mem: 19788 +Epoch: [35] [2010/2138] eta: 0:06:06 lr: 6.378694474389515e-06 loss: 0.0180 (0.0184) time: 2.8779 data: 0.0023 max mem: 19788 +Epoch: [35] [2020/2138] eta: 0:05:37 lr: 6.372079477388078e-06 loss: 0.0193 (0.0184) time: 2.9048 data: 0.0025 max mem: 19788 +Epoch: [35] [2030/2138] eta: 0:05:09 lr: 6.365463717279001e-06 loss: 0.0182 (0.0185) time: 2.8779 data: 0.0028 max mem: 19788 +Epoch: [35] [2040/2138] eta: 0:04:40 lr: 6.358847193092821e-06 loss: 0.0176 (0.0184) time: 2.8490 data: 0.0025 max mem: 19788 +Epoch: [35] [2050/2138] eta: 0:04:11 lr: 6.3522299038577035e-06 loss: 0.0176 (0.0184) time: 2.8391 data: 0.0023 max mem: 19788 +Epoch: [35] [2060/2138] eta: 0:03:43 lr: 6.345611848599453e-06 loss: 0.0172 (0.0185) time: 2.8345 data: 0.0025 max mem: 19788 +Epoch: [35] [2070/2138] eta: 0:03:14 lr: 6.338993026341522e-06 loss: 0.0164 (0.0184) time: 2.8325 data: 0.0026 max mem: 19788 +Epoch: [35] [2080/2138] eta: 0:02:46 lr: 6.332373436104956e-06 loss: 0.0153 (0.0184) time: 2.8353 data: 0.0023 max mem: 19788 +Epoch: [35] [2090/2138] eta: 0:02:17 lr: 6.32575307690844e-06 loss: 0.0181 (0.0184) time: 2.8400 data: 0.0021 max mem: 19788 +Epoch: [35] [2100/2138] eta: 0:01:48 lr: 6.319131947768234e-06 loss: 0.0179 (0.0184) time: 2.8582 data: 0.0021 max mem: 19788 +Epoch: [35] [2110/2138] eta: 0:01:20 lr: 6.312510047698221e-06 loss: 0.0193 (0.0185) time: 2.9151 data: 0.0023 max mem: 19788 +Epoch: [35] [2120/2138] eta: 0:00:51 lr: 6.305887375709843e-06 loss: 0.0206 (0.0185) time: 2.9295 data: 0.0026 max mem: 19788 +Epoch: [35] [2130/2138] eta: 0:00:22 lr: 6.299263930812145e-06 loss: 0.0203 (0.0185) time: 2.8638 data: 0.0024 max mem: 19788 +Epoch: [35] Total time: 1:42:00 +Test: [ 0/21770] eta: 15:44:44 time: 2.6038 data: 2.4617 max mem: 19788 +Test: [ 100/21770] eta: 0:28:25 time: 0.0518 data: 0.0016 max mem: 19788 +Test: [ 200/21770] eta: 0:21:54 time: 0.0424 data: 0.0015 max mem: 19788 +Test: [ 300/21770] eta: 0:19:58 time: 0.0446 data: 0.0015 max mem: 19788 +Test: [ 400/21770] eta: 0:18:45 time: 0.0436 data: 0.0014 max mem: 19788 +Test: [ 500/21770] eta: 0:18:15 time: 0.0433 data: 0.0014 max mem: 19788 +Test: [ 600/21770] eta: 0:17:44 time: 0.0467 data: 0.0015 max mem: 19788 +Test: [ 700/21770] eta: 0:17:28 time: 0.0445 data: 0.0015 max mem: 19788 +Test: [ 800/21770] eta: 0:17:05 time: 0.0429 data: 0.0016 max mem: 19788 +Test: [ 900/21770] eta: 0:16:55 time: 0.0476 data: 0.0016 max mem: 19788 +Test: [ 1000/21770] eta: 0:16:44 time: 0.0494 data: 0.0016 max mem: 19788 +Test: [ 1100/21770] eta: 0:16:36 time: 0.0439 data: 0.0014 max mem: 19788 +Test: [ 1200/21770] eta: 0:16:24 time: 0.0423 data: 0.0014 max mem: 19788 +Test: [ 1300/21770] eta: 0:16:15 time: 0.0469 data: 0.0017 max mem: 19788 +Test: [ 1400/21770] eta: 0:16:09 time: 0.0430 data: 0.0014 max mem: 19788 +Test: [ 1500/21770] eta: 0:16:03 time: 0.0429 data: 0.0014 max mem: 19788 +Test: [ 1600/21770] eta: 0:15:55 time: 0.0423 data: 0.0015 max mem: 19788 +Test: [ 1700/21770] eta: 0:15:47 time: 0.0466 data: 0.0015 max mem: 19788 +Test: [ 1800/21770] eta: 0:15:39 time: 0.0433 data: 0.0016 max mem: 19788 +Test: [ 1900/21770] eta: 0:15:35 time: 0.0516 data: 0.0018 max mem: 19788 +Test: [ 2000/21770] eta: 0:15:36 time: 0.0535 data: 0.0015 max mem: 19788 +Test: [ 2100/21770] eta: 0:15:31 time: 0.0448 data: 0.0016 max mem: 19788 +Test: [ 2200/21770] eta: 0:15:26 time: 0.0420 data: 0.0013 max mem: 19788 +Test: [ 2300/21770] eta: 0:15:19 time: 0.0454 data: 0.0015 max mem: 19788 +Test: [ 2400/21770] eta: 0:15:12 time: 0.0451 data: 0.0014 max mem: 19788 +Test: [ 2500/21770] eta: 0:15:07 time: 0.0450 data: 0.0015 max mem: 19788 +Test: [ 2600/21770] eta: 0:15:05 time: 0.0490 data: 0.0016 max mem: 19788 +Test: [ 2700/21770] eta: 0:14:59 time: 0.0441 data: 0.0015 max mem: 19788 +Test: [ 2800/21770] eta: 0:14:55 time: 0.0446 data: 0.0014 max mem: 19788 +Test: [ 2900/21770] eta: 0:14:50 time: 0.0442 data: 0.0015 max mem: 19788 +Test: [ 3000/21770] eta: 0:14:47 time: 0.0522 data: 0.0017 max mem: 19788 +Test: [ 3100/21770] eta: 0:14:41 time: 0.0444 data: 0.0017 max mem: 19788 +Test: [ 3200/21770] eta: 0:14:36 time: 0.0442 data: 0.0015 max mem: 19788 +Test: [ 3300/21770] eta: 0:14:30 time: 0.0536 data: 0.0017 max mem: 19788 +Test: [ 3400/21770] eta: 0:14:26 time: 0.0493 data: 0.0016 max mem: 19788 +Test: [ 3500/21770] eta: 0:14:24 time: 0.0533 data: 0.0017 max mem: 19788 +Test: [ 3600/21770] eta: 0:14:21 time: 0.0442 data: 0.0016 max mem: 19788 +Test: [ 3700/21770] eta: 0:14:14 time: 0.0456 data: 0.0014 max mem: 19788 +Test: [ 3800/21770] eta: 0:14:12 time: 0.0544 data: 0.0018 max mem: 19788 +Test: [ 3900/21770] eta: 0:14:07 time: 0.0479 data: 0.0016 max mem: 19788 +Test: [ 4000/21770] eta: 0:14:02 time: 0.0460 data: 0.0015 max mem: 19788 +Test: [ 4100/21770] eta: 0:13:57 time: 0.0478 data: 0.0016 max mem: 19788 +Test: [ 4200/21770] eta: 0:13:53 time: 0.0454 data: 0.0014 max mem: 19788 +Test: [ 4300/21770] eta: 0:13:49 time: 0.0530 data: 0.0018 max mem: 19788 +Test: [ 4400/21770] eta: 0:13:43 time: 0.0431 data: 0.0014 max mem: 19788 +Test: [ 4500/21770] eta: 0:13:37 time: 0.0434 data: 0.0015 max mem: 19788 +Test: [ 4600/21770] eta: 0:13:32 time: 0.0473 data: 0.0015 max mem: 19788 +Test: [ 4700/21770] eta: 0:13:28 time: 0.0461 data: 0.0014 max mem: 19788 +Test: [ 4800/21770] eta: 0:13:24 time: 0.0440 data: 0.0017 max mem: 19788 +Test: [ 4900/21770] eta: 0:13:19 time: 0.0444 data: 0.0019 max mem: 19788 +Test: [ 5000/21770] eta: 0:13:14 time: 0.0436 data: 0.0015 max mem: 19788 +Test: [ 5100/21770] eta: 0:13:08 time: 0.0490 data: 0.0016 max mem: 19788 +Test: [ 5200/21770] eta: 0:13:03 time: 0.0439 data: 0.0014 max mem: 19788 +Test: [ 5300/21770] eta: 0:12:58 time: 0.0471 data: 0.0017 max mem: 19788 +Test: [ 5400/21770] eta: 0:12:53 time: 0.0448 data: 0.0015 max mem: 19788 +Test: [ 5500/21770] eta: 0:12:48 time: 0.0452 data: 0.0013 max mem: 19788 +Test: [ 5600/21770] eta: 0:12:43 time: 0.0440 data: 0.0016 max mem: 19788 +Test: [ 5700/21770] eta: 0:12:38 time: 0.0432 data: 0.0015 max mem: 19788 +Test: [ 5800/21770] eta: 0:12:33 time: 0.0502 data: 0.0018 max mem: 19788 +Test: [ 5900/21770] eta: 0:12:28 time: 0.0435 data: 0.0015 max mem: 19788 +Test: [ 6000/21770] eta: 0:12:22 time: 0.0435 data: 0.0015 max mem: 19788 +Test: [ 6100/21770] eta: 0:12:18 time: 0.0445 data: 0.0018 max mem: 19788 +Test: [ 6200/21770] eta: 0:12:12 time: 0.0440 data: 0.0014 max mem: 19788 +Test: [ 6300/21770] eta: 0:12:08 time: 0.0472 data: 0.0015 max mem: 19788 +Test: [ 6400/21770] eta: 0:12:03 time: 0.0466 data: 0.0016 max mem: 19788 +Test: [ 6500/21770] eta: 0:11:58 time: 0.0437 data: 0.0015 max mem: 19788 +Test: [ 6600/21770] eta: 0:11:54 time: 0.0472 data: 0.0017 max mem: 19788 +Test: [ 6700/21770] eta: 0:11:49 time: 0.0441 data: 0.0015 max mem: 19788 +Test: [ 6800/21770] eta: 0:11:44 time: 0.0446 data: 0.0016 max mem: 19788 +Test: [ 6900/21770] eta: 0:11:39 time: 0.0440 data: 0.0013 max mem: 19788 +Test: [ 7000/21770] eta: 0:11:34 time: 0.0434 data: 0.0015 max mem: 19788 +Test: [ 7100/21770] eta: 0:11:29 time: 0.0477 data: 0.0016 max mem: 19788 +Test: [ 7200/21770] eta: 0:11:25 time: 0.0543 data: 0.0017 max mem: 19788 +Test: [ 7300/21770] eta: 0:11:20 time: 0.0498 data: 0.0017 max mem: 19788 +Test: [ 7400/21770] eta: 0:11:16 time: 0.0470 data: 0.0016 max mem: 19788 +Test: [ 7500/21770] eta: 0:11:11 time: 0.0434 data: 0.0015 max mem: 19788 +Test: [ 7600/21770] eta: 0:11:06 time: 0.0509 data: 0.0016 max mem: 19788 +Test: [ 7700/21770] eta: 0:11:01 time: 0.0451 data: 0.0015 max mem: 19788 +Test: [ 7800/21770] eta: 0:10:56 time: 0.0444 data: 0.0014 max mem: 19788 +Test: [ 7900/21770] eta: 0:10:51 time: 0.0467 data: 0.0016 max mem: 19788 +Test: [ 8000/21770] eta: 0:10:46 time: 0.0446 data: 0.0015 max mem: 19788 +Test: [ 8100/21770] eta: 0:10:40 time: 0.0436 data: 0.0015 max mem: 19788 +Test: [ 8200/21770] eta: 0:10:35 time: 0.0431 data: 0.0015 max mem: 19788 +Test: [ 8300/21770] eta: 0:10:31 time: 0.0525 data: 0.0015 max mem: 19788 +Test: [ 8400/21770] eta: 0:10:27 time: 0.0485 data: 0.0017 max mem: 19788 +Test: [ 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time: 0.0447 data: 0.0016 max mem: 19788 +Test: [ 9900/21770] eta: 0:09:15 time: 0.0435 data: 0.0013 max mem: 19788 +Test: [10000/21770] eta: 0:09:10 time: 0.0447 data: 0.0014 max mem: 19788 +Test: [10100/21770] eta: 0:09:05 time: 0.0447 data: 0.0016 max mem: 19788 +Test: [10200/21770] eta: 0:09:00 time: 0.0441 data: 0.0015 max mem: 19788 +Test: [10300/21770] eta: 0:08:56 time: 0.0474 data: 0.0017 max mem: 19788 +Test: [10400/21770] eta: 0:08:51 time: 0.0451 data: 0.0015 max mem: 19788 +Test: [10500/21770] eta: 0:08:46 time: 0.0436 data: 0.0016 max mem: 19788 +Test: [10600/21770] eta: 0:08:41 time: 0.0467 data: 0.0016 max mem: 19788 +Test: [10700/21770] eta: 0:08:37 time: 0.0464 data: 0.0016 max mem: 19788 +Test: [10800/21770] eta: 0:08:32 time: 0.0452 data: 0.0015 max mem: 19788 +Test: [10900/21770] eta: 0:08:27 time: 0.0527 data: 0.0016 max mem: 19788 +Test: [11000/21770] eta: 0:08:23 time: 0.0461 data: 0.0015 max mem: 19788 +Test: [11100/21770] eta: 0:08:18 time: 0.0517 data: 0.0017 max mem: 19788 +Test: [11200/21770] eta: 0:08:13 time: 0.0445 data: 0.0017 max mem: 19788 +Test: [11300/21770] eta: 0:08:09 time: 0.0441 data: 0.0014 max mem: 19788 +Test: [11400/21770] eta: 0:08:04 time: 0.0441 data: 0.0014 max mem: 19788 +Test: [11500/21770] eta: 0:07:59 time: 0.0473 data: 0.0016 max mem: 19788 +Test: [11600/21770] eta: 0:07:55 time: 0.0440 data: 0.0016 max mem: 19788 +Test: [11700/21770] eta: 0:07:50 time: 0.0455 data: 0.0016 max mem: 19788 +Test: [11800/21770] eta: 0:07:45 time: 0.0438 data: 0.0016 max mem: 19788 +Test: [11900/21770] eta: 0:07:41 time: 0.0524 data: 0.0017 max mem: 19788 +Test: [12000/21770] eta: 0:07:36 time: 0.0547 data: 0.0016 max mem: 19788 +Test: [12100/21770] eta: 0:07:32 time: 0.0489 data: 0.0017 max mem: 19788 +Test: [12200/21770] eta: 0:07:27 time: 0.0459 data: 0.0014 max mem: 19788 +Test: [12300/21770] eta: 0:07:23 time: 0.0444 data: 0.0015 max mem: 19788 +Test: [12400/21770] eta: 0:07:18 time: 0.0483 data: 0.0015 max mem: 19788 +Test: [12500/21770] eta: 0:07:14 time: 0.0527 data: 0.0018 max mem: 19788 +Test: [12600/21770] eta: 0:07:09 time: 0.0460 data: 0.0015 max mem: 19788 +Test: [12700/21770] eta: 0:07:04 time: 0.0478 data: 0.0014 max mem: 19788 +Test: [12800/21770] eta: 0:07:00 time: 0.0504 data: 0.0018 max mem: 19788 +Test: [12900/21770] eta: 0:06:55 time: 0.0456 data: 0.0014 max mem: 19788 +Test: [13000/21770] eta: 0:06:50 time: 0.0526 data: 0.0018 max mem: 19788 +Test: [13100/21770] eta: 0:06:46 time: 0.0527 data: 0.0017 max mem: 19788 +Test: [13200/21770] eta: 0:06:41 time: 0.0520 data: 0.0017 max mem: 19788 +Test: [13300/21770] eta: 0:06:37 time: 0.0502 data: 0.0017 max mem: 19788 +Test: [13400/21770] eta: 0:06:32 time: 0.0524 data: 0.0017 max mem: 19788 +Test: [13500/21770] eta: 0:06:27 time: 0.0457 data: 0.0015 max mem: 19788 +Test: [13600/21770] eta: 0:06:23 time: 0.0529 data: 0.0017 max mem: 19788 +Test: [13700/21770] eta: 0:06:18 time: 0.0460 data: 0.0015 max mem: 19788 +Test: [13800/21770] eta: 0:06:13 time: 0.0455 data: 0.0015 max mem: 19788 +Test: [13900/21770] eta: 0:06:09 time: 0.0515 data: 0.0018 max mem: 19788 +Test: [14000/21770] eta: 0:06:04 time: 0.0438 data: 0.0012 max mem: 19788 +Test: [14100/21770] eta: 0:05:59 time: 0.0497 data: 0.0016 max mem: 19788 +Test: [14200/21770] eta: 0:05:55 time: 0.0519 data: 0.0016 max mem: 19788 +Test: [14300/21770] eta: 0:05:50 time: 0.0443 data: 0.0016 max mem: 19788 +Test: [14400/21770] eta: 0:05:45 time: 0.0449 data: 0.0014 max mem: 19788 +Test: [14500/21770] eta: 0:05:41 time: 0.0445 data: 0.0014 max mem: 19788 +Test: [14600/21770] eta: 0:05:36 time: 0.0449 data: 0.0016 max mem: 19788 +Test: [14700/21770] eta: 0:05:31 time: 0.0425 data: 0.0014 max mem: 19788 +Test: [14800/21770] eta: 0:05:26 time: 0.0468 data: 0.0019 max mem: 19788 +Test: [14900/21770] eta: 0:05:22 time: 0.0452 data: 0.0014 max mem: 19788 +Test: [15000/21770] eta: 0:05:17 time: 0.0449 data: 0.0015 max mem: 19788 +Test: [15100/21770] eta: 0:05:12 time: 0.0500 data: 0.0015 max mem: 19788 +Test: [15200/21770] eta: 0:05:08 time: 0.0439 data: 0.0016 max mem: 19788 +Test: [15300/21770] eta: 0:05:03 time: 0.0448 data: 0.0015 max mem: 19788 +Test: [15400/21770] eta: 0:04:58 time: 0.0446 data: 0.0014 max mem: 19788 +Test: [15500/21770] eta: 0:04:54 time: 0.0440 data: 0.0017 max mem: 19788 +Test: [15600/21770] eta: 0:04:49 time: 0.0448 data: 0.0015 max mem: 19788 +Test: [15700/21770] eta: 0:04:44 time: 0.0474 data: 0.0015 max mem: 19788 +Test: [15800/21770] eta: 0:04:39 time: 0.0523 data: 0.0018 max mem: 19788 +Test: [15900/21770] eta: 0:04:35 time: 0.0446 data: 0.0014 max mem: 19788 +Test: [16000/21770] eta: 0:04:30 time: 0.0451 data: 0.0014 max mem: 19788 +Test: [16100/21770] eta: 0:04:25 time: 0.0492 data: 0.0018 max mem: 19788 +Test: [16200/21770] eta: 0:04:21 time: 0.0448 data: 0.0015 max mem: 19788 +Test: [16300/21770] eta: 0:04:16 time: 0.0439 data: 0.0015 max mem: 19788 +Test: [16400/21770] eta: 0:04:12 time: 0.0523 data: 0.0018 max mem: 19788 +Test: [16500/21770] eta: 0:04:07 time: 0.0442 data: 0.0013 max mem: 19788 +Test: [16600/21770] eta: 0:04:02 time: 0.0447 data: 0.0013 max mem: 19788 +Test: [16700/21770] eta: 0:03:58 time: 0.0482 data: 0.0014 max mem: 19788 +Test: [16800/21770] eta: 0:03:53 time: 0.0432 data: 0.0014 max mem: 19788 +Test: [16900/21770] eta: 0:03:48 time: 0.0448 data: 0.0015 max mem: 19788 +Test: [17000/21770] eta: 0:03:43 time: 0.0454 data: 0.0016 max mem: 19788 +Test: [17100/21770] eta: 0:03:39 time: 0.0466 data: 0.0014 max mem: 19788 +Test: [17200/21770] eta: 0:03:34 time: 0.0427 data: 0.0014 max mem: 19788 +Test: [17300/21770] eta: 0:03:29 time: 0.0516 data: 0.0017 max mem: 19788 +Test: [17400/21770] eta: 0:03:25 time: 0.0447 data: 0.0014 max mem: 19788 +Test: [17500/21770] eta: 0:03:20 time: 0.0431 data: 0.0014 max mem: 19788 +Test: [17600/21770] eta: 0:03:15 time: 0.0476 data: 0.0014 max mem: 19788 +Test: [17700/21770] eta: 0:03:10 time: 0.0422 data: 0.0014 max mem: 19788 +Test: [17800/21770] eta: 0:03:06 time: 0.0439 data: 0.0016 max mem: 19788 +Test: [17900/21770] eta: 0:03:01 time: 0.0439 data: 0.0014 max mem: 19788 +Test: [18000/21770] eta: 0:02:56 time: 0.0426 data: 0.0014 max mem: 19788 +Test: [18100/21770] eta: 0:02:51 time: 0.0442 data: 0.0014 max mem: 19788 +Test: [18200/21770] eta: 0:02:47 time: 0.0433 data: 0.0014 max mem: 19788 +Test: [18300/21770] eta: 0:02:42 time: 0.0495 data: 0.0016 max mem: 19788 +Test: [18400/21770] eta: 0:02:37 time: 0.0467 data: 0.0015 max mem: 19788 +Test: [18500/21770] eta: 0:02:33 time: 0.0427 data: 0.0013 max mem: 19788 +Test: [18600/21770] eta: 0:02:28 time: 0.0436 data: 0.0013 max mem: 19788 +Test: [18700/21770] eta: 0:02:23 time: 0.0485 data: 0.0016 max mem: 19788 +Test: [18800/21770] eta: 0:02:19 time: 0.0453 data: 0.0018 max mem: 19788 +Test: [18900/21770] eta: 0:02:14 time: 0.0435 data: 0.0016 max mem: 19788 +Test: [19000/21770] eta: 0:02:09 time: 0.0448 data: 0.0016 max mem: 19788 +Test: [19100/21770] eta: 0:02:04 time: 0.0442 data: 0.0014 max mem: 19788 +Test: [19200/21770] eta: 0:02:00 time: 0.0448 data: 0.0015 max mem: 19788 +Test: [19300/21770] eta: 0:01:55 time: 0.0526 data: 0.0017 max mem: 19788 +Test: [19400/21770] eta: 0:01:50 time: 0.0447 data: 0.0013 max mem: 19788 +Test: [19500/21770] eta: 0:01:46 time: 0.0429 data: 0.0015 max mem: 19788 +Test: [19600/21770] eta: 0:01:41 time: 0.0441 data: 0.0013 max mem: 19788 +Test: [19700/21770] eta: 0:01:36 time: 0.0433 data: 0.0012 max mem: 19788 +Test: [19800/21770] eta: 0:01:32 time: 0.0522 data: 0.0018 max mem: 19788 +Test: [19900/21770] eta: 0:01:27 time: 0.0467 data: 0.0014 max mem: 19788 +Test: [20000/21770] eta: 0:01:22 time: 0.0446 data: 0.0016 max mem: 19788 +Test: [20100/21770] eta: 0:01:18 time: 0.0529 data: 0.0017 max mem: 19788 +Test: [20200/21770] eta: 0:01:13 time: 0.0495 data: 0.0017 max mem: 19788 +Test: [20300/21770] eta: 0:01:08 time: 0.0442 data: 0.0014 max mem: 19788 +Test: [20400/21770] eta: 0:01:04 time: 0.0472 data: 0.0016 max mem: 19788 +Test: [20500/21770] eta: 0:00:59 time: 0.0514 data: 0.0015 max mem: 19788 +Test: [20600/21770] eta: 0:00:54 time: 0.0459 data: 0.0014 max mem: 19788 +Test: [20700/21770] eta: 0:00:50 time: 0.0528 data: 0.0017 max mem: 19788 +Test: [20800/21770] eta: 0:00:45 time: 0.0502 data: 0.0016 max mem: 19788 +Test: [20900/21770] eta: 0:00:40 time: 0.0467 data: 0.0016 max mem: 19788 +Test: [21000/21770] eta: 0:00:36 time: 0.0470 data: 0.0017 max mem: 19788 +Test: [21100/21770] eta: 0:00:31 time: 0.0490 data: 0.0016 max mem: 19788 +Test: [21200/21770] eta: 0:00:26 time: 0.0455 data: 0.0016 max mem: 19788 +Test: [21300/21770] eta: 0:00:21 time: 0.0508 data: 0.0015 max mem: 19788 +Test: [21400/21770] eta: 0:00:17 time: 0.0438 data: 0.0015 max mem: 19788 +Test: [21500/21770] eta: 0:00:12 time: 0.0444 data: 0.0015 max mem: 19788 +Test: [21600/21770] eta: 0:00:07 time: 0.0497 data: 0.0017 max mem: 19788 +Test: [21700/21770] eta: 0:00:03 time: 0.0468 data: 0.0016 max mem: 19788 +Test: Total time: 0:16:58 +Final results: +Mean IoU is 64.65 + + precision@0.5 = 71.97 + precision@0.6 = 66.72 + precision@0.7 = 60.07 + precision@0.8 = 49.35 + precision@0.9 = 24.31 + overall IoU = 65.12 + mean IoU = 64.65 + +Mean accuracy for one-to-zero sample is 86.55 + +Average object IoU 0.6465126141421689 +Overall IoU 65.11827087402344 +Epoch: [36] [ 0/2138] eta: 13:16:54 lr: 6.293964617731786e-06 loss: 0.0202 (0.0202) time: 22.3642 data: 1.4348 max mem: 19788 +Epoch: [36] [ 10/2138] eta: 2:44:54 lr: 6.28733977909229e-06 loss: 0.0175 (0.0188) time: 4.6498 data: 0.1317 max mem: 19788 +Epoch: [36] [ 20/2138] eta: 2:14:20 lr: 6.280714164755802e-06 loss: 0.0167 (0.0177) time: 2.8778 data: 0.0018 max mem: 19788 +Epoch: [36] [ 30/2138] eta: 2:03:10 lr: 6.274087773722053e-06 loss: 0.0179 (0.0184) time: 2.8766 data: 0.0025 max mem: 19788 +Epoch: [36] [ 40/2138] eta: 1:57:10 lr: 6.267460604988337e-06 loss: 0.0211 (0.0187) time: 2.8738 data: 0.0026 max mem: 19788 +Epoch: [36] [ 50/2138] eta: 1:53:22 lr: 6.260832657549447e-06 loss: 0.0180 (0.0189) time: 2.8739 data: 0.0023 max mem: 19788 +Epoch: [36] [ 60/2138] eta: 1:50:38 lr: 6.254203930397719e-06 loss: 0.0180 (0.0191) time: 2.8741 data: 0.0025 max mem: 19788 +Epoch: [36] [ 70/2138] eta: 1:48:35 lr: 6.247574422522971e-06 loss: 0.0185 (0.0190) time: 2.8760 data: 0.0026 max mem: 19788 +Epoch: [36] [ 80/2138] eta: 1:47:08 lr: 6.240944132912543e-06 loss: 0.0178 (0.0190) time: 2.9068 data: 0.0025 max mem: 19788 +Epoch: [36] [ 90/2138] eta: 1:45:54 lr: 6.2343130605512415e-06 loss: 0.0165 (0.0187) time: 2.9336 data: 0.0027 max mem: 19788 +Epoch: [36] [ 100/2138] eta: 1:44:44 lr: 6.227681204421378e-06 loss: 0.0164 (0.0188) time: 2.9225 data: 0.0027 max mem: 19788 +Epoch: [36] [ 110/2138] eta: 1:43:29 lr: 6.221048563502716e-06 loss: 0.0166 (0.0186) time: 2.8771 data: 0.0024 max mem: 19788 +Epoch: [36] [ 120/2138] eta: 1:42:22 lr: 6.21441513677248e-06 loss: 0.0153 (0.0184) time: 2.8425 data: 0.0023 max mem: 19788 +Epoch: [36] [ 130/2138] eta: 1:41:21 lr: 6.2077809232053644e-06 loss: 0.0182 (0.0184) time: 2.8430 data: 0.0024 max mem: 19788 +Epoch: [36] [ 140/2138] eta: 1:40:23 lr: 6.201145921773485e-06 loss: 0.0183 (0.0184) time: 2.8368 data: 0.0025 max mem: 19788 +Epoch: [36] [ 150/2138] eta: 1:39:29 lr: 6.194510131446413e-06 loss: 0.0169 (0.0184) time: 2.8314 data: 0.0022 max mem: 19788 +Epoch: [36] [ 160/2138] eta: 1:38:37 lr: 6.18787355119112e-06 loss: 0.0172 (0.0184) time: 2.8303 data: 0.0021 max mem: 19788 +Epoch: [36] [ 170/2138] eta: 1:38:00 lr: 6.181236179972018e-06 loss: 0.0192 (0.0184) time: 2.8785 data: 0.0021 max mem: 19788 +Epoch: [36] [ 180/2138] eta: 1:37:21 lr: 6.174598016750897e-06 loss: 0.0184 (0.0184) time: 2.9168 data: 0.0020 max mem: 19788 +Epoch: [36] [ 190/2138] eta: 1:36:43 lr: 6.167959060486969e-06 loss: 0.0174 (0.0183) time: 2.9051 data: 0.0021 max mem: 19788 +Epoch: [36] [ 200/2138] eta: 1:36:01 lr: 6.161319310136806e-06 loss: 0.0175 (0.0183) time: 2.8758 data: 0.0022 max mem: 19788 +Epoch: [36] [ 210/2138] eta: 1:35:19 lr: 6.1546787646543806e-06 loss: 0.0181 (0.0183) time: 2.8431 data: 0.0021 max mem: 19788 +Epoch: [36] [ 220/2138] eta: 1:34:38 lr: 6.148037422991007e-06 loss: 0.0164 (0.0182) time: 2.8398 data: 0.0023 max mem: 19788 +Epoch: [36] [ 230/2138] eta: 1:33:58 lr: 6.1413952840953814e-06 loss: 0.0158 (0.0183) time: 2.8388 data: 0.0024 max mem: 19788 +Epoch: [36] [ 240/2138] eta: 1:33:20 lr: 6.13475234691352e-06 loss: 0.0195 (0.0183) time: 2.8401 data: 0.0024 max mem: 19788 +Epoch: [36] [ 250/2138] eta: 1:32:42 lr: 6.128108610388803e-06 loss: 0.0181 (0.0182) time: 2.8391 data: 0.0026 max mem: 19788 +Epoch: [36] [ 260/2138] eta: 1:32:06 lr: 6.12146407346191e-06 loss: 0.0164 (0.0182) time: 2.8461 data: 0.0026 max mem: 19788 +Epoch: [36] [ 270/2138] eta: 1:31:34 lr: 6.1148187350708655e-06 loss: 0.0164 (0.0182) time: 2.8856 data: 0.0026 max mem: 19788 +Epoch: [36] [ 280/2138] eta: 1:31:07 lr: 6.1081725941509715e-06 loss: 0.0173 (0.0182) time: 2.9462 data: 0.0026 max mem: 19788 +Epoch: [36] [ 290/2138] eta: 1:30:35 lr: 6.1015256496348556e-06 loss: 0.0170 (0.0182) time: 2.9340 data: 0.0024 max mem: 19788 +Epoch: [36] [ 300/2138] eta: 1:30:00 lr: 6.0948779004524034e-06 loss: 0.0181 (0.0183) time: 2.8730 data: 0.0025 max mem: 19788 +Epoch: [36] [ 310/2138] eta: 1:29:25 lr: 6.088229345530805e-06 loss: 0.0181 (0.0182) time: 2.8473 data: 0.0023 max mem: 19788 +Epoch: [36] [ 320/2138] eta: 1:28:50 lr: 6.081579983794488e-06 loss: 0.0152 (0.0181) time: 2.8357 data: 0.0024 max mem: 19788 +Epoch: [36] [ 330/2138] eta: 1:28:15 lr: 6.0749298141651655e-06 loss: 0.0173 (0.0182) time: 2.8314 data: 0.0025 max mem: 19788 +Epoch: [36] [ 340/2138] eta: 1:27:41 lr: 6.068278835561765e-06 loss: 0.0178 (0.0182) time: 2.8378 data: 0.0024 max mem: 19788 +Epoch: [36] [ 350/2138] eta: 1:27:08 lr: 6.061627046900481e-06 loss: 0.0170 (0.0182) time: 2.8455 data: 0.0025 max mem: 19788 +Epoch: [36] [ 360/2138] eta: 1:26:39 lr: 6.054974447094701e-06 loss: 0.0181 (0.0182) time: 2.8886 data: 0.0025 max mem: 19788 +Epoch: [36] [ 370/2138] eta: 1:26:10 lr: 6.048321035055053e-06 loss: 0.0198 (0.0182) time: 2.9327 data: 0.0024 max mem: 19788 +Epoch: [36] [ 380/2138] eta: 1:25:41 lr: 6.041666809689348e-06 loss: 0.0174 (0.0182) time: 2.9297 data: 0.0022 max mem: 19788 +Epoch: [36] [ 390/2138] eta: 1:25:08 lr: 6.035011769902609e-06 loss: 0.0159 (0.0181) time: 2.8823 data: 0.0023 max mem: 19788 +Epoch: [36] [ 400/2138] eta: 1:24:35 lr: 6.028355914597027e-06 loss: 0.0167 (0.0182) time: 2.8423 data: 0.0024 max mem: 19788 +Epoch: [36] [ 410/2138] eta: 1:24:03 lr: 6.02169924267196e-06 loss: 0.0169 (0.0181) time: 2.8459 data: 0.0022 max mem: 19788 +Epoch: [36] [ 420/2138] eta: 1:23:31 lr: 6.01504175302395e-06 loss: 0.0162 (0.0181) time: 2.8516 data: 0.0021 max mem: 19788 +Epoch: [36] [ 430/2138] eta: 1:22:59 lr: 6.00838344454666e-06 loss: 0.0166 (0.0181) time: 2.8456 data: 0.0022 max mem: 19788 +Epoch: [36] [ 440/2138] eta: 1:22:27 lr: 6.001724316130922e-06 loss: 0.0177 (0.0182) time: 2.8393 data: 0.0023 max mem: 19788 +Epoch: [36] [ 450/2138] eta: 1:21:55 lr: 5.995064366664664e-06 loss: 0.0192 (0.0182) time: 2.8403 data: 0.0022 max mem: 19788 +Epoch: [36] [ 460/2138] eta: 1:21:26 lr: 5.988403595032962e-06 loss: 0.0172 (0.0182) time: 2.8753 data: 0.0022 max mem: 19788 +Epoch: [36] [ 470/2138] eta: 1:20:57 lr: 5.98174200011797e-06 loss: 0.0172 (0.0181) time: 2.9233 data: 0.0023 max mem: 19788 +Epoch: [36] [ 480/2138] eta: 1:20:28 lr: 5.975079580798963e-06 loss: 0.0185 (0.0182) time: 2.9246 data: 0.0025 max mem: 19788 +Epoch: [36] [ 490/2138] eta: 1:19:57 lr: 5.968416335952275e-06 loss: 0.0176 (0.0181) time: 2.8789 data: 0.0023 max mem: 19788 +Epoch: [36] [ 500/2138] eta: 1:19:26 lr: 5.961752264451338e-06 loss: 0.0165 (0.0182) time: 2.8533 data: 0.0022 max mem: 19788 +Epoch: [36] [ 510/2138] eta: 1:18:55 lr: 5.955087365166617e-06 loss: 0.0156 (0.0181) time: 2.8498 data: 0.0024 max mem: 19788 +Epoch: [36] [ 520/2138] eta: 1:18:24 lr: 5.948421636965657e-06 loss: 0.0153 (0.0181) time: 2.8368 data: 0.0027 max mem: 19788 +Epoch: [36] [ 530/2138] eta: 1:17:52 lr: 5.941755078713012e-06 loss: 0.0161 (0.0181) time: 2.8388 data: 0.0024 max mem: 19788 +Epoch: [36] [ 540/2138] eta: 1:17:22 lr: 5.935087689270291e-06 loss: 0.0170 (0.0181) time: 2.8446 data: 0.0022 max mem: 19788 +Epoch: [36] [ 550/2138] eta: 1:16:52 lr: 5.928419467496091e-06 loss: 0.0170 (0.0181) time: 2.8622 data: 0.0028 max mem: 19788 +Epoch: [36] [ 560/2138] eta: 1:16:24 lr: 5.921750412246043e-06 loss: 0.0194 (0.0181) time: 2.9150 data: 0.0030 max mem: 19788 +Epoch: [36] [ 570/2138] eta: 1:15:56 lr: 5.915080522372738e-06 loss: 0.0174 (0.0181) time: 2.9508 data: 0.0026 max mem: 19788 +Epoch: [36] [ 580/2138] eta: 1:15:25 lr: 5.90840979672578e-06 loss: 0.0161 (0.0182) time: 2.8927 data: 0.0026 max mem: 19788 +Epoch: [36] [ 590/2138] eta: 1:14:54 lr: 5.901738234151712e-06 loss: 0.0173 (0.0182) time: 2.8363 data: 0.0026 max mem: 19788 +Epoch: [36] [ 600/2138] eta: 1:14:24 lr: 5.895065833494062e-06 loss: 0.0162 (0.0182) time: 2.8379 data: 0.0024 max mem: 19788 +Epoch: [36] [ 610/2138] eta: 1:13:54 lr: 5.888392593593277e-06 loss: 0.0173 (0.0182) time: 2.8487 data: 0.0026 max mem: 19788 +Epoch: [36] [ 620/2138] eta: 1:13:23 lr: 5.881718513286762e-06 loss: 0.0177 (0.0182) time: 2.8490 data: 0.0028 max mem: 19788 +Epoch: [36] [ 630/2138] eta: 1:12:53 lr: 5.87504359140882e-06 loss: 0.0177 (0.0182) time: 2.8499 data: 0.0028 max mem: 19788 +Epoch: [36] [ 640/2138] eta: 1:12:23 lr: 5.868367826790687e-06 loss: 0.0172 (0.0182) time: 2.8491 data: 0.0029 max mem: 19788 +Epoch: [36] [ 650/2138] eta: 1:11:54 lr: 5.861691218260472e-06 loss: 0.0184 (0.0182) time: 2.8694 data: 0.0028 max mem: 19788 +Epoch: [36] [ 660/2138] eta: 1:11:25 lr: 5.855013764643194e-06 loss: 0.0184 (0.0183) time: 2.9140 data: 0.0024 max mem: 19788 +Epoch: [36] [ 670/2138] eta: 1:10:57 lr: 5.848335464760719e-06 loss: 0.0174 (0.0183) time: 2.9199 data: 0.0021 max mem: 19788 +Epoch: [36] [ 680/2138] eta: 1:10:27 lr: 5.8416563174318e-06 loss: 0.0166 (0.0183) time: 2.8864 data: 0.0020 max mem: 19788 +Epoch: [36] [ 690/2138] eta: 1:09:57 lr: 5.834976321472011e-06 loss: 0.0175 (0.0183) time: 2.8628 data: 0.0021 max mem: 19788 +Epoch: [36] [ 700/2138] eta: 1:09:27 lr: 5.82829547569379e-06 loss: 0.0181 (0.0182) time: 2.8595 data: 0.0023 max mem: 19788 +Epoch: [36] [ 710/2138] eta: 1:08:57 lr: 5.8216137789063745e-06 loss: 0.0167 (0.0182) time: 2.8521 data: 0.0025 max mem: 19788 +Epoch: [36] [ 720/2138] eta: 1:08:27 lr: 5.814931229915819e-06 loss: 0.0156 (0.0182) time: 2.8449 data: 0.0026 max mem: 19788 +Epoch: [36] [ 730/2138] eta: 1:07:57 lr: 5.808247827524991e-06 loss: 0.0154 (0.0182) time: 2.8443 data: 0.0025 max mem: 19788 +Epoch: [36] [ 740/2138] eta: 1:07:28 lr: 5.801563570533517e-06 loss: 0.0185 (0.0182) time: 2.8610 data: 0.0026 max mem: 19788 +Epoch: [36] [ 750/2138] eta: 1:06:59 lr: 5.7948784577378244e-06 loss: 0.0188 (0.0182) time: 2.8983 data: 0.0027 max mem: 19788 +Epoch: [36] [ 760/2138] eta: 1:06:31 lr: 5.788192487931074e-06 loss: 0.0188 (0.0182) time: 2.9385 data: 0.0024 max mem: 19788 +Epoch: [36] [ 770/2138] eta: 1:06:02 lr: 5.781505659903198e-06 loss: 0.0176 (0.0182) time: 2.9006 data: 0.0023 max mem: 19788 +Epoch: [36] [ 780/2138] eta: 1:05:32 lr: 5.774817972440839e-06 loss: 0.0167 (0.0182) time: 2.8457 data: 0.0025 max mem: 19788 +Epoch: [36] [ 790/2138] eta: 1:05:02 lr: 5.768129424327383e-06 loss: 0.0156 (0.0182) time: 2.8444 data: 0.0025 max mem: 19788 +Epoch: [36] [ 800/2138] eta: 1:04:32 lr: 5.761440014342902e-06 loss: 0.0174 (0.0182) time: 2.8439 data: 0.0024 max mem: 19788 +Epoch: [36] [ 810/2138] eta: 1:04:02 lr: 5.7547497412641846e-06 loss: 0.0184 (0.0182) time: 2.8427 data: 0.0025 max mem: 19788 +Epoch: [36] [ 820/2138] eta: 1:03:32 lr: 5.7480586038646774e-06 loss: 0.0176 (0.0182) time: 2.8333 data: 0.0023 max mem: 19788 +Epoch: [36] [ 830/2138] eta: 1:03:02 lr: 5.74136660091452e-06 loss: 0.0156 (0.0182) time: 2.8318 data: 0.0021 max mem: 19788 +Epoch: [36] [ 840/2138] eta: 1:02:34 lr: 5.734673731180482e-06 loss: 0.0156 (0.0182) time: 2.8668 data: 0.0025 max mem: 19788 +Epoch: [36] [ 850/2138] eta: 1:02:06 lr: 5.727979993425998e-06 loss: 0.0178 (0.0182) time: 2.9230 data: 0.0026 max mem: 19788 +Epoch: [36] [ 860/2138] eta: 1:01:37 lr: 5.721285386411107e-06 loss: 0.0168 (0.0182) time: 2.9257 data: 0.0023 max mem: 19788 +Epoch: [36] [ 870/2138] eta: 1:01:07 lr: 5.714589908892485e-06 loss: 0.0162 (0.0182) time: 2.8667 data: 0.0022 max mem: 19788 +Epoch: [36] [ 880/2138] eta: 1:00:37 lr: 5.707893559623386e-06 loss: 0.0158 (0.0181) time: 2.8380 data: 0.0025 max mem: 19788 +Epoch: [36] [ 890/2138] eta: 1:00:08 lr: 5.701196337353674e-06 loss: 0.0169 (0.0181) time: 2.8426 data: 0.0026 max mem: 19788 +Epoch: [36] [ 900/2138] eta: 0:59:38 lr: 5.69449824082976e-06 loss: 0.0178 (0.0181) time: 2.8354 data: 0.0025 max mem: 19788 +Epoch: [36] [ 910/2138] eta: 0:59:08 lr: 5.6877992687946426e-06 loss: 0.0170 (0.0181) time: 2.8367 data: 0.0027 max mem: 19788 +Epoch: [36] [ 920/2138] eta: 0:58:39 lr: 5.681099419987837e-06 loss: 0.0170 (0.0181) time: 2.8399 data: 0.0028 max mem: 19788 +Epoch: [36] [ 930/2138] eta: 0:58:10 lr: 5.6743986931454166e-06 loss: 0.0180 (0.0181) time: 2.8624 data: 0.0028 max mem: 19788 +Epoch: [36] [ 940/2138] eta: 0:57:41 lr: 5.667697086999944e-06 loss: 0.0195 (0.0182) time: 2.9001 data: 0.0030 max mem: 19788 +Epoch: [36] [ 950/2138] eta: 0:57:13 lr: 5.660994600280514e-06 loss: 0.0181 (0.0182) time: 2.9270 data: 0.0032 max mem: 19788 +Epoch: [36] [ 960/2138] eta: 0:56:44 lr: 5.65429123171268e-06 loss: 0.0191 (0.0182) time: 2.8944 data: 0.0028 max mem: 19788 +Epoch: [36] [ 970/2138] eta: 0:56:14 lr: 5.647586980018498e-06 loss: 0.0191 (0.0182) time: 2.8454 data: 0.0024 max mem: 19788 +Epoch: [36] [ 980/2138] eta: 0:55:45 lr: 5.640881843916457e-06 loss: 0.0168 (0.0182) time: 2.8392 data: 0.0026 max mem: 19788 +Epoch: [36] [ 990/2138] eta: 0:55:15 lr: 5.634175822121518e-06 loss: 0.0165 (0.0182) time: 2.8484 data: 0.0027 max mem: 19788 +Epoch: [36] [1000/2138] eta: 0:54:46 lr: 5.627468913345044e-06 loss: 0.0160 (0.0182) time: 2.8480 data: 0.0024 max mem: 19788 +Epoch: [36] [1010/2138] eta: 0:54:17 lr: 5.620761116294843e-06 loss: 0.0156 (0.0182) time: 2.8429 data: 0.0021 max mem: 19788 +Epoch: [36] [1020/2138] eta: 0:53:47 lr: 5.614052429675105e-06 loss: 0.0165 (0.0182) time: 2.8457 data: 0.0021 max mem: 19788 +Epoch: [36] [1030/2138] eta: 0:53:19 lr: 5.607342852186402e-06 loss: 0.0164 (0.0182) time: 2.8766 data: 0.0024 max mem: 19788 +Epoch: [36] [1040/2138] eta: 0:52:50 lr: 5.600632382525702e-06 loss: 0.0178 (0.0182) time: 2.9221 data: 0.0025 max mem: 19788 +Epoch: [36] [1050/2138] eta: 0:52:22 lr: 5.593921019386301e-06 loss: 0.0196 (0.0182) time: 2.9221 data: 0.0028 max mem: 19788 +Epoch: [36] [1060/2138] eta: 0:51:52 lr: 5.587208761457865e-06 loss: 0.0178 (0.0182) time: 2.8831 data: 0.0030 max mem: 19788 +Epoch: [36] [1070/2138] eta: 0:51:23 lr: 5.580495607426356e-06 loss: 0.0177 (0.0182) time: 2.8430 data: 0.0028 max mem: 19788 +Epoch: [36] [1080/2138] eta: 0:50:54 lr: 5.573781555974077e-06 loss: 0.0188 (0.0182) time: 2.8334 data: 0.0027 max mem: 19788 +Epoch: [36] [1090/2138] eta: 0:50:24 lr: 5.5670666057795984e-06 loss: 0.0189 (0.0182) time: 2.8330 data: 0.0026 max mem: 19788 +Epoch: [36] [1100/2138] eta: 0:49:55 lr: 5.560350755517799e-06 loss: 0.0186 (0.0182) time: 2.8532 data: 0.0024 max mem: 19788 +Epoch: [36] [1110/2138] eta: 0:49:26 lr: 5.553634003859796e-06 loss: 0.0178 (0.0182) time: 2.8562 data: 0.0023 max mem: 19788 +Epoch: [36] [1120/2138] eta: 0:48:57 lr: 5.5469163494729825e-06 loss: 0.0157 (0.0182) time: 2.8417 data: 0.0023 max mem: 19788 +Epoch: [36] [1130/2138] eta: 0:48:28 lr: 5.5401977910209565e-06 loss: 0.0165 (0.0182) time: 2.8725 data: 0.0023 max mem: 19788 +Epoch: [36] [1140/2138] eta: 0:48:00 lr: 5.533478327163563e-06 loss: 0.0179 (0.0182) time: 2.9177 data: 0.0027 max mem: 19788 +Epoch: [36] [1150/2138] eta: 0:47:31 lr: 5.526757956556823e-06 loss: 0.0158 (0.0182) time: 2.9173 data: 0.0025 max mem: 19788 +Epoch: [36] [1160/2138] eta: 0:47:02 lr: 5.5200366778529686e-06 loss: 0.0150 (0.0182) time: 2.8728 data: 0.0023 max mem: 19788 +Epoch: [36] [1170/2138] eta: 0:46:32 lr: 5.513314489700376e-06 loss: 0.0168 (0.0182) time: 2.8466 data: 0.0022 max mem: 19788 +Epoch: [36] [1180/2138] eta: 0:46:03 lr: 5.506591390743603e-06 loss: 0.0176 (0.0182) time: 2.8402 data: 0.0022 max mem: 19788 +Epoch: [36] [1190/2138] eta: 0:45:34 lr: 5.499867379623319e-06 loss: 0.0170 (0.0182) time: 2.8369 data: 0.0023 max mem: 19788 +Epoch: [36] [1200/2138] eta: 0:45:05 lr: 5.49314245497634e-06 loss: 0.0157 (0.0182) time: 2.8417 data: 0.0024 max mem: 19788 +Epoch: [36] [1210/2138] eta: 0:44:36 lr: 5.486416615435564e-06 loss: 0.0176 (0.0182) time: 2.8391 data: 0.0022 max mem: 19788 +Epoch: [36] [1220/2138] eta: 0:44:07 lr: 5.47968985963e-06 loss: 0.0166 (0.0182) time: 2.8619 data: 0.0022 max mem: 19788 +Epoch: [36] [1230/2138] eta: 0:43:39 lr: 5.472962186184708e-06 loss: 0.0162 (0.0182) time: 2.9264 data: 0.0023 max mem: 19788 +Epoch: [36] [1240/2138] eta: 0:43:10 lr: 5.466233593720826e-06 loss: 0.0162 (0.0182) time: 2.9324 data: 0.0025 max mem: 19788 +Epoch: [36] [1250/2138] eta: 0:42:41 lr: 5.459504080855509e-06 loss: 0.0163 (0.0181) time: 2.8694 data: 0.0026 max mem: 19788 +Epoch: [36] [1260/2138] eta: 0:42:11 lr: 5.452773646201954e-06 loss: 0.0162 (0.0181) time: 2.8382 data: 0.0025 max mem: 19788 +Epoch: [36] [1270/2138] eta: 0:41:42 lr: 5.446042288369344e-06 loss: 0.0162 (0.0181) time: 2.8473 data: 0.0026 max mem: 19788 +Epoch: [36] [1280/2138] eta: 0:41:13 lr: 5.439310005962872e-06 loss: 0.0180 (0.0181) time: 2.8480 data: 0.0025 max mem: 19788 +Epoch: [36] [1290/2138] eta: 0:40:44 lr: 5.4325767975836784e-06 loss: 0.0190 (0.0181) time: 2.8456 data: 0.0024 max mem: 19788 +Epoch: [36] [1300/2138] eta: 0:40:15 lr: 5.425842661828884e-06 loss: 0.0165 (0.0181) time: 2.8432 data: 0.0022 max mem: 19788 +Epoch: [36] [1310/2138] eta: 0:39:46 lr: 5.419107597291518e-06 loss: 0.0165 (0.0181) time: 2.8424 data: 0.0024 max mem: 19788 +Epoch: [36] [1320/2138] eta: 0:39:17 lr: 5.412371602560556e-06 loss: 0.0168 (0.0181) time: 2.8788 data: 0.0027 max mem: 19788 +Epoch: [36] [1330/2138] eta: 0:38:49 lr: 5.4056346762208575e-06 loss: 0.0168 (0.0181) time: 2.9442 data: 0.0025 max mem: 19788 +Epoch: [36] [1340/2138] eta: 0:38:20 lr: 5.398896816853164e-06 loss: 0.0184 (0.0181) time: 2.9300 data: 0.0024 max mem: 19788 +Epoch: [36] [1350/2138] eta: 0:37:51 lr: 5.392158023034104e-06 loss: 0.0192 (0.0181) time: 2.8595 data: 0.0023 max mem: 19788 +Epoch: [36] [1360/2138] eta: 0:37:22 lr: 5.385418293336128e-06 loss: 0.0192 (0.0181) time: 2.8433 data: 0.0023 max mem: 19788 +Epoch: [36] [1370/2138] eta: 0:36:53 lr: 5.378677626327546e-06 loss: 0.0192 (0.0182) time: 2.8448 data: 0.0026 max mem: 19788 +Epoch: [36] [1380/2138] eta: 0:36:24 lr: 5.371936020572451e-06 loss: 0.0193 (0.0182) time: 2.8392 data: 0.0025 max mem: 19788 +Epoch: [36] [1390/2138] eta: 0:35:55 lr: 5.365193474630759e-06 loss: 0.0171 (0.0182) time: 2.8408 data: 0.0022 max mem: 19788 +Epoch: [36] [1400/2138] eta: 0:35:26 lr: 5.3584499870581365e-06 loss: 0.0171 (0.0182) time: 2.8436 data: 0.0023 max mem: 19788 +Epoch: [36] [1410/2138] eta: 0:34:57 lr: 5.351705556406035e-06 loss: 0.0165 (0.0182) time: 2.8604 data: 0.0023 max mem: 19788 +Epoch: [36] [1420/2138] eta: 0:34:29 lr: 5.344960181221616e-06 loss: 0.0168 (0.0182) time: 2.9133 data: 0.0023 max mem: 19788 +Epoch: [36] [1430/2138] eta: 0:34:00 lr: 5.338213860047793e-06 loss: 0.0174 (0.0182) time: 2.9442 data: 0.0024 max mem: 19788 +Epoch: [36] [1440/2138] eta: 0:33:32 lr: 5.331466591423154e-06 loss: 0.0186 (0.0182) time: 2.9238 data: 0.0023 max mem: 19788 +Epoch: [36] [1450/2138] eta: 0:33:03 lr: 5.3247183738819964e-06 loss: 0.0187 (0.0182) time: 2.9059 data: 0.0025 max mem: 19788 +Epoch: [36] [1460/2138] eta: 0:32:34 lr: 5.317969205954259e-06 loss: 0.0181 (0.0182) time: 2.9315 data: 0.0024 max mem: 19788 +Epoch: [36] [1470/2138] eta: 0:32:05 lr: 5.311219086165548e-06 loss: 0.0153 (0.0182) time: 2.9117 data: 0.0025 max mem: 19788 +Epoch: [36] [1480/2138] eta: 0:31:36 lr: 5.304468013037077e-06 loss: 0.0150 (0.0182) time: 2.8587 data: 0.0027 max mem: 19788 +Epoch: [36] [1490/2138] eta: 0:31:07 lr: 5.297715985085688e-06 loss: 0.0165 (0.0182) time: 2.8468 data: 0.0026 max mem: 19788 +Epoch: [36] [1500/2138] eta: 0:30:38 lr: 5.29096300082379e-06 loss: 0.0170 (0.0182) time: 2.8399 data: 0.0024 max mem: 19788 +Epoch: [36] [1510/2138] eta: 0:30:09 lr: 5.2842090587593834e-06 loss: 0.0168 (0.0182) time: 2.8339 data: 0.0023 max mem: 19788 +Epoch: [36] [1520/2138] eta: 0:29:40 lr: 5.277454157395995e-06 loss: 0.0187 (0.0182) time: 2.8327 data: 0.0025 max mem: 19788 +Epoch: [36] [1530/2138] eta: 0:29:11 lr: 5.2706982952327075e-06 loss: 0.0184 (0.0182) time: 2.8384 data: 0.0025 max mem: 19788 +Epoch: [36] [1540/2138] eta: 0:28:43 lr: 5.263941470764085e-06 loss: 0.0175 (0.0182) time: 2.8726 data: 0.0024 max mem: 19788 +Epoch: [36] [1550/2138] eta: 0:28:14 lr: 5.257183682480211e-06 loss: 0.0169 (0.0182) time: 2.9123 data: 0.0026 max mem: 19788 +Epoch: [36] [1560/2138] eta: 0:27:45 lr: 5.250424928866615e-06 loss: 0.0171 (0.0182) time: 2.9334 data: 0.0024 max mem: 19788 +Epoch: [36] [1570/2138] eta: 0:27:16 lr: 5.243665208404298e-06 loss: 0.0192 (0.0182) time: 2.8977 data: 0.0024 max mem: 19788 +Epoch: [36] [1580/2138] eta: 0:26:47 lr: 5.236904519569669e-06 loss: 0.0179 (0.0182) time: 2.8408 data: 0.0025 max mem: 19788 +Epoch: [36] [1590/2138] eta: 0:26:18 lr: 5.230142860834572e-06 loss: 0.0170 (0.0182) time: 2.8339 data: 0.0024 max mem: 19788 +Epoch: [36] [1600/2138] eta: 0:25:50 lr: 5.223380230666215e-06 loss: 0.0194 (0.0182) time: 2.8351 data: 0.0023 max mem: 19788 +Epoch: [36] [1610/2138] eta: 0:25:21 lr: 5.216616627527199e-06 loss: 0.0201 (0.0182) time: 2.8478 data: 0.0023 max mem: 19788 +Epoch: [36] [1620/2138] eta: 0:24:52 lr: 5.209852049875456e-06 loss: 0.0157 (0.0182) time: 2.8582 data: 0.0026 max mem: 19788 +Epoch: [36] [1630/2138] eta: 0:24:23 lr: 5.2030864961642434e-06 loss: 0.0157 (0.0182) time: 2.8551 data: 0.0027 max mem: 19788 +Epoch: [36] [1640/2138] eta: 0:23:54 lr: 5.196319964842146e-06 loss: 0.0189 (0.0182) time: 2.8720 data: 0.0024 max mem: 19788 +Epoch: [36] [1650/2138] eta: 0:23:25 lr: 5.189552454353009e-06 loss: 0.0180 (0.0182) time: 2.9011 data: 0.0023 max mem: 19788 +Epoch: [36] [1660/2138] eta: 0:22:57 lr: 5.182783963135965e-06 loss: 0.0175 (0.0182) time: 2.9131 data: 0.0023 max mem: 19788 +Epoch: [36] [1670/2138] eta: 0:22:28 lr: 5.176014489625365e-06 loss: 0.0174 (0.0182) time: 2.8745 data: 0.0022 max mem: 19788 +Epoch: [36] [1680/2138] eta: 0:21:59 lr: 5.169244032250808e-06 loss: 0.0154 (0.0182) time: 2.8519 data: 0.0021 max mem: 19788 +Epoch: [36] [1690/2138] eta: 0:21:30 lr: 5.162472589437067e-06 loss: 0.0166 (0.0182) time: 2.8628 data: 0.0025 max mem: 19788 +Epoch: [36] [1700/2138] eta: 0:21:01 lr: 5.155700159604118e-06 loss: 0.0170 (0.0182) time: 2.8523 data: 0.0030 max mem: 19788 +Epoch: [36] [1710/2138] eta: 0:20:32 lr: 5.148926741167069e-06 loss: 0.0170 (0.0182) time: 2.8432 data: 0.0030 max mem: 19788 +Epoch: [36] [1720/2138] eta: 0:20:03 lr: 5.142152332536187e-06 loss: 0.0182 (0.0182) time: 2.8417 data: 0.0029 max mem: 19788 +Epoch: [36] [1730/2138] eta: 0:19:34 lr: 5.135376932116825e-06 loss: 0.0181 (0.0182) time: 2.8390 data: 0.0025 max mem: 19788 +Epoch: [36] [1740/2138] eta: 0:19:06 lr: 5.128600538309456e-06 loss: 0.0173 (0.0182) time: 2.8647 data: 0.0021 max mem: 19788 +Epoch: [36] [1750/2138] eta: 0:18:37 lr: 5.121823149509591e-06 loss: 0.0171 (0.0182) time: 2.9194 data: 0.0021 max mem: 19788 +Epoch: [36] [1760/2138] eta: 0:18:08 lr: 5.1150447641078115e-06 loss: 0.0183 (0.0182) time: 2.9313 data: 0.0021 max mem: 19788 +Epoch: [36] [1770/2138] eta: 0:17:39 lr: 5.108265380489701e-06 loss: 0.0154 (0.0182) time: 2.8803 data: 0.0022 max mem: 19788 +Epoch: [36] [1780/2138] eta: 0:17:11 lr: 5.101484997035864e-06 loss: 0.0154 (0.0182) time: 2.8521 data: 0.0025 max mem: 19788 +Epoch: [36] [1790/2138] eta: 0:16:42 lr: 5.094703612121857e-06 loss: 0.0156 (0.0182) time: 2.8512 data: 0.0026 max mem: 19788 +Epoch: [36] [1800/2138] eta: 0:16:13 lr: 5.0879212241182195e-06 loss: 0.0196 (0.0182) time: 2.8399 data: 0.0025 max mem: 19788 +Epoch: [36] [1810/2138] eta: 0:15:44 lr: 5.081137831390393e-06 loss: 0.0187 (0.0182) time: 2.8369 data: 0.0022 max mem: 19788 +Epoch: [36] [1820/2138] eta: 0:15:15 lr: 5.0743534322987525e-06 loss: 0.0170 (0.0182) time: 2.8322 data: 0.0021 max mem: 19788 +Epoch: [36] [1830/2138] eta: 0:14:46 lr: 5.067568025198533e-06 loss: 0.0171 (0.0182) time: 2.8337 data: 0.0023 max mem: 19788 +Epoch: [36] [1840/2138] eta: 0:14:17 lr: 5.060781608439854e-06 loss: 0.0181 (0.0182) time: 2.8664 data: 0.0026 max mem: 19788 +Epoch: [36] [1850/2138] eta: 0:13:49 lr: 5.053994180367647e-06 loss: 0.0197 (0.0182) time: 2.9384 data: 0.0028 max mem: 19788 +Epoch: [36] [1860/2138] eta: 0:13:20 lr: 5.047205739321684e-06 loss: 0.0187 (0.0182) time: 2.9451 data: 0.0030 max mem: 19788 +Epoch: [36] [1870/2138] eta: 0:12:51 lr: 5.040416283636495e-06 loss: 0.0203 (0.0182) time: 2.8830 data: 0.0026 max mem: 19788 +Epoch: [36] [1880/2138] eta: 0:12:22 lr: 5.033625811641407e-06 loss: 0.0171 (0.0182) time: 2.8539 data: 0.0021 max mem: 19788 +Epoch: [36] [1890/2138] eta: 0:11:54 lr: 5.0268343216604555e-06 loss: 0.0155 (0.0182) time: 2.8449 data: 0.0026 max mem: 19788 +Epoch: [36] [1900/2138] eta: 0:11:25 lr: 5.020041812012422e-06 loss: 0.0167 (0.0182) time: 2.8355 data: 0.0025 max mem: 19788 +Epoch: [36] [1910/2138] eta: 0:10:56 lr: 5.01324828101075e-06 loss: 0.0175 (0.0182) time: 2.8365 data: 0.0023 max mem: 19788 +Epoch: [36] [1920/2138] eta: 0:10:27 lr: 5.006453726963579e-06 loss: 0.0163 (0.0182) time: 2.8347 data: 0.0024 max mem: 19788 +Epoch: [36] [1930/2138] eta: 0:09:58 lr: 4.999658148173668e-06 loss: 0.0161 (0.0182) time: 2.8404 data: 0.0023 max mem: 19788 +Epoch: [36] [1940/2138] eta: 0:09:29 lr: 4.992861542938393e-06 loss: 0.0169 (0.0182) time: 2.8991 data: 0.0025 max mem: 19788 +Epoch: [36] [1950/2138] eta: 0:09:01 lr: 4.9860639095497395e-06 loss: 0.0178 (0.0182) time: 2.9309 data: 0.0024 max mem: 19788 +Epoch: [36] [1960/2138] eta: 0:08:32 lr: 4.979265246294236e-06 loss: 0.0178 (0.0182) time: 2.9078 data: 0.0024 max mem: 19788 +Epoch: [36] [1970/2138] eta: 0:08:03 lr: 4.972465551452975e-06 loss: 0.0159 (0.0182) time: 2.8709 data: 0.0026 max mem: 19788 +Epoch: [36] [1980/2138] eta: 0:07:34 lr: 4.965664823301536e-06 loss: 0.0169 (0.0182) time: 2.8431 data: 0.0023 max mem: 19788 +Epoch: [36] [1990/2138] eta: 0:07:06 lr: 4.958863060110016e-06 loss: 0.0176 (0.0182) time: 2.8407 data: 0.0021 max mem: 19788 +Epoch: [36] [2000/2138] eta: 0:06:37 lr: 4.9520602601429485e-06 loss: 0.0155 (0.0182) time: 2.8352 data: 0.0022 max mem: 19788 +Epoch: [36] [2010/2138] eta: 0:06:08 lr: 4.945256421659326e-06 loss: 0.0169 (0.0182) time: 2.8391 data: 0.0023 max mem: 19788 +Epoch: [36] [2020/2138] eta: 0:05:39 lr: 4.93845154291253e-06 loss: 0.0179 (0.0182) time: 2.8372 data: 0.0022 max mem: 19788 +Epoch: [36] [2030/2138] eta: 0:05:10 lr: 4.931645622150346e-06 loss: 0.0173 (0.0182) time: 2.8300 data: 0.0020 max mem: 19788 +Epoch: [36] [2040/2138] eta: 0:04:42 lr: 4.924838657614895e-06 loss: 0.0173 (0.0182) time: 2.8838 data: 0.0021 max mem: 19788 +Epoch: [36] [2050/2138] eta: 0:04:13 lr: 4.918030647542651e-06 loss: 0.0174 (0.0182) time: 2.9244 data: 0.0023 max mem: 19788 +Epoch: [36] [2060/2138] eta: 0:03:44 lr: 4.911221590164365e-06 loss: 0.0162 (0.0182) time: 2.9427 data: 0.0022 max mem: 19788 +Epoch: [36] [2070/2138] eta: 0:03:15 lr: 4.9044114837050925e-06 loss: 0.0162 (0.0182) time: 2.9072 data: 0.0021 max mem: 19788 +Epoch: [36] [2080/2138] eta: 0:02:46 lr: 4.8976003263841075e-06 loss: 0.0158 (0.0182) time: 2.8474 data: 0.0021 max mem: 19788 +Epoch: [36] [2090/2138] eta: 0:02:18 lr: 4.890788116414932e-06 loss: 0.0170 (0.0182) time: 2.8483 data: 0.0021 max mem: 19788 +Epoch: [36] [2100/2138] eta: 0:01:49 lr: 4.883974852005257e-06 loss: 0.0178 (0.0182) time: 2.8426 data: 0.0025 max mem: 19788 +Epoch: [36] [2110/2138] eta: 0:01:20 lr: 4.877160531356961e-06 loss: 0.0193 (0.0182) time: 2.8391 data: 0.0024 max mem: 19788 +Epoch: [36] [2120/2138] eta: 0:00:51 lr: 4.8703451526660365e-06 loss: 0.0210 (0.0182) time: 2.8377 data: 0.0023 max mem: 19788 +Epoch: [36] [2130/2138] eta: 0:00:23 lr: 4.863528714122609e-06 loss: 0.0210 (0.0182) time: 2.8478 data: 0.0024 max mem: 19788 +Epoch: [36] Total time: 1:42:32 +Test: [ 0/21770] eta: 17:13:48 time: 2.8493 data: 2.7236 max mem: 19788 +Test: [ 100/21770] eta: 0:26:39 time: 0.0432 data: 0.0014 max mem: 19788 +Test: [ 200/21770] eta: 0:21:34 time: 0.0527 data: 0.0018 max mem: 19788 +Test: [ 300/21770] eta: 0:20:03 time: 0.0504 data: 0.0014 max mem: 19788 +Test: [ 400/21770] eta: 0:19:22 time: 0.0523 data: 0.0018 max mem: 19788 +Test: [ 500/21770] eta: 0:18:57 time: 0.0524 data: 0.0018 max mem: 19788 +Test: [ 600/21770] eta: 0:18:33 time: 0.0472 data: 0.0016 max mem: 19788 +Test: [ 700/21770] eta: 0:18:08 time: 0.0429 data: 0.0019 max mem: 19788 +Test: [ 800/21770] eta: 0:17:56 time: 0.0523 data: 0.0017 max mem: 19788 +Test: [ 900/21770] eta: 0:17:43 time: 0.0432 data: 0.0013 max mem: 19788 +Test: [ 1000/21770] eta: 0:17:25 time: 0.0428 data: 0.0014 max mem: 19788 +Test: [ 1100/21770] eta: 0:17:15 time: 0.0522 data: 0.0018 max mem: 19788 +Test: [ 1200/21770] eta: 0:17:05 time: 0.0519 data: 0.0018 max mem: 19788 +Test: [ 1300/21770] eta: 0:16:56 time: 0.0426 data: 0.0014 max mem: 19788 +Test: [ 1400/21770] eta: 0:16:42 time: 0.0430 data: 0.0013 max mem: 19788 +Test: [ 1500/21770] eta: 0:16:35 time: 0.0478 data: 0.0016 max mem: 19788 +Test: [ 1600/21770] eta: 0:16:25 time: 0.0417 data: 0.0013 max mem: 19788 +Test: [ 1700/21770] eta: 0:16:16 time: 0.0460 data: 0.0016 max mem: 19788 +Test: [ 1800/21770] eta: 0:16:07 time: 0.0452 data: 0.0015 max mem: 19788 +Test: [ 1900/21770] eta: 0:15:58 time: 0.0430 data: 0.0013 max mem: 19788 +Test: [ 2000/21770] eta: 0:15:53 time: 0.0444 data: 0.0014 max mem: 19788 +Test: [ 2100/21770] eta: 0:15:44 time: 0.0435 data: 0.0017 max mem: 19788 +Test: [ 2200/21770] eta: 0:15:39 time: 0.0428 data: 0.0013 max mem: 19788 +Test: [ 2300/21770] eta: 0:15:31 time: 0.0439 data: 0.0014 max mem: 19788 +Test: [ 2400/21770] eta: 0:15:24 time: 0.0440 data: 0.0013 max mem: 19788 +Test: [ 2500/21770] eta: 0:15:18 time: 0.0508 data: 0.0018 max mem: 19788 +Test: [ 2600/21770] eta: 0:15:09 time: 0.0431 data: 0.0014 max mem: 19788 +Test: [ 2700/21770] eta: 0:15:06 time: 0.0521 data: 0.0017 max mem: 19788 +Test: [ 2800/21770] eta: 0:15:00 time: 0.0450 data: 0.0014 max mem: 19788 +Test: [ 2900/21770] eta: 0:14:53 time: 0.0455 data: 0.0015 max mem: 19788 +Test: [ 3000/21770] eta: 0:14:48 time: 0.0448 data: 0.0014 max mem: 19788 +Test: [ 3100/21770] eta: 0:14:43 time: 0.0454 data: 0.0016 max mem: 19788 +Test: [ 3200/21770] eta: 0:14:39 time: 0.0536 data: 0.0014 max mem: 19788 +Test: [ 3300/21770] eta: 0:14:35 time: 0.0501 data: 0.0017 max mem: 19788 +Test: [ 3400/21770] eta: 0:14:29 time: 0.0435 data: 0.0015 max mem: 19788 +Test: [ 3500/21770] eta: 0:14:25 time: 0.0510 data: 0.0017 max mem: 19788 +Test: [ 3600/21770] eta: 0:14:21 time: 0.0432 data: 0.0015 max mem: 19788 +Test: [ 3700/21770] eta: 0:14:14 time: 0.0429 data: 0.0015 max mem: 19788 +Test: [ 3800/21770] eta: 0:14:11 time: 0.0444 data: 0.0014 max mem: 19788 +Test: [ 3900/21770] eta: 0:14:05 time: 0.0436 data: 0.0014 max mem: 19788 +Test: [ 4000/21770] eta: 0:14:01 time: 0.0528 data: 0.0017 max mem: 19788 +Test: [ 4100/21770] eta: 0:13:56 time: 0.0477 data: 0.0016 max mem: 19788 +Test: [ 4200/21770] eta: 0:13:51 time: 0.0496 data: 0.0016 max mem: 19788 +Test: [ 4300/21770] eta: 0:13:45 time: 0.0441 data: 0.0015 max mem: 19788 +Test: [ 4400/21770] eta: 0:13:41 time: 0.0525 data: 0.0017 max mem: 19788 +Test: [ 4500/21770] eta: 0:13:36 time: 0.0464 data: 0.0015 max mem: 19788 +Test: [ 4600/21770] eta: 0:13:32 time: 0.0519 data: 0.0018 max mem: 19788 +Test: [ 4700/21770] eta: 0:13:27 time: 0.0452 data: 0.0016 max mem: 19788 +Test: [ 4800/21770] eta: 0:13:22 time: 0.0454 data: 0.0016 max mem: 19788 +Test: [ 4900/21770] eta: 0:13:16 time: 0.0484 data: 0.0017 max mem: 19788 +Test: [ 5000/21770] eta: 0:13:12 time: 0.0492 data: 0.0017 max mem: 19788 +Test: [ 5100/21770] eta: 0:13:07 time: 0.0439 data: 0.0015 max mem: 19788 +Test: [ 5200/21770] eta: 0:13:02 time: 0.0459 data: 0.0016 max mem: 19788 +Test: [ 5300/21770] eta: 0:12:57 time: 0.0456 data: 0.0016 max mem: 19788 +Test: [ 5400/21770] eta: 0:12:53 time: 0.0443 data: 0.0014 max mem: 19788 +Test: [ 5500/21770] eta: 0:12:49 time: 0.0520 data: 0.0016 max mem: 19788 +Test: [ 5600/21770] eta: 0:12:44 time: 0.0462 data: 0.0017 max mem: 19788 +Test: [ 5700/21770] eta: 0:12:40 time: 0.0471 data: 0.0016 max mem: 19788 +Test: [ 5800/21770] eta: 0:12:35 time: 0.0434 data: 0.0014 max mem: 19788 +Test: [ 5900/21770] eta: 0:12:30 time: 0.0509 data: 0.0016 max mem: 19788 +Test: [ 6000/21770] eta: 0:12:26 time: 0.0499 data: 0.0016 max mem: 19788 +Test: [ 6100/21770] eta: 0:12:22 time: 0.0525 data: 0.0015 max mem: 19788 +Test: [ 6200/21770] eta: 0:12:16 time: 0.0455 data: 0.0015 max mem: 19788 +Test: [ 6300/21770] eta: 0:12:12 time: 0.0446 data: 0.0015 max mem: 19788 +Test: [ 6400/21770] eta: 0:12:07 time: 0.0439 data: 0.0014 max mem: 19788 +Test: [ 6500/21770] eta: 0:12:01 time: 0.0447 data: 0.0015 max mem: 19788 +Test: [ 6600/21770] eta: 0:11:57 time: 0.0525 data: 0.0018 max mem: 19788 +Test: [ 6700/21770] eta: 0:11:53 time: 0.0522 data: 0.0018 max mem: 19788 +Test: [ 6800/21770] eta: 0:11:49 time: 0.0473 data: 0.0017 max mem: 19788 +Test: [ 6900/21770] eta: 0:11:45 time: 0.0543 data: 0.0017 max mem: 19788 +Test: [ 7000/21770] eta: 0:11:40 time: 0.0468 data: 0.0015 max mem: 19788 +Test: [ 7100/21770] eta: 0:11:36 time: 0.0512 data: 0.0017 max mem: 19788 +Test: [ 7200/21770] eta: 0:11:32 time: 0.0529 data: 0.0018 max mem: 19788 +Test: [ 7300/21770] eta: 0:11:27 time: 0.0541 data: 0.0017 max mem: 19788 +Test: [ 7400/21770] eta: 0:11:22 time: 0.0447 data: 0.0014 max mem: 19788 +Test: [ 7500/21770] eta: 0:11:17 time: 0.0457 data: 0.0027 max mem: 19788 +Test: [ 7600/21770] eta: 0:11:12 time: 0.0512 data: 0.0015 max mem: 19788 +Test: [ 7700/21770] eta: 0:11:07 time: 0.0489 data: 0.0015 max mem: 19788 +Test: [ 7800/21770] eta: 0:11:02 time: 0.0487 data: 0.0015 max mem: 19788 +Test: [ 7900/21770] eta: 0:10:57 time: 0.0428 data: 0.0014 max mem: 19788 +Test: [ 8000/21770] eta: 0:10:52 time: 0.0531 data: 0.0017 max mem: 19788 +Test: [ 8100/21770] eta: 0:10:47 time: 0.0436 data: 0.0015 max mem: 19788 +Test: [ 8200/21770] eta: 0:10:42 time: 0.0461 data: 0.0017 max mem: 19788 +Test: [ 8300/21770] eta: 0:10:37 time: 0.0537 data: 0.0018 max mem: 19788 +Test: [ 8400/21770] eta: 0:10:33 time: 0.0529 data: 0.0016 max mem: 19788 +Test: [ 8500/21770] eta: 0:10:28 time: 0.0428 data: 0.0015 max mem: 19788 +Test: [ 8600/21770] eta: 0:10:22 time: 0.0448 data: 0.0014 max mem: 19788 +Test: [ 8700/21770] eta: 0:10:17 time: 0.0425 data: 0.0015 max mem: 19788 +Test: [ 8800/21770] eta: 0:10:12 time: 0.0436 data: 0.0014 max mem: 19788 +Test: [ 8900/21770] eta: 0:10:08 time: 0.0529 data: 0.0018 max mem: 19788 +Test: [ 9000/21770] eta: 0:10:03 time: 0.0430 data: 0.0016 max mem: 19788 +Test: [ 9100/21770] eta: 0:09:58 time: 0.0436 data: 0.0015 max mem: 19788 +Test: [ 9200/21770] eta: 0:09:53 time: 0.0435 data: 0.0015 max mem: 19788 +Test: [ 9300/21770] eta: 0:09:48 time: 0.0436 data: 0.0015 max mem: 19788 +Test: [ 9400/21770] eta: 0:09:44 time: 0.0519 data: 0.0018 max mem: 19788 +Test: [ 9500/21770] eta: 0:09:39 time: 0.0444 data: 0.0015 max mem: 19788 +Test: [ 9600/21770] eta: 0:09:35 time: 0.0504 data: 0.0017 max mem: 19788 +Test: [ 9700/21770] eta: 0:09:30 time: 0.0443 data: 0.0014 max mem: 19788 +Test: [ 9800/21770] eta: 0:09:25 time: 0.0458 data: 0.0015 max mem: 19788 +Test: [ 9900/21770] eta: 0:09:21 time: 0.0511 data: 0.0016 max mem: 19788 +Test: [10000/21770] eta: 0:09:16 time: 0.0437 data: 0.0014 max mem: 19788 +Test: [10100/21770] eta: 0:09:11 time: 0.0507 data: 0.0018 max mem: 19788 +Test: [10200/21770] eta: 0:09:07 time: 0.0444 data: 0.0014 max mem: 19788 +Test: [10300/21770] eta: 0:09:02 time: 0.0456 data: 0.0014 max mem: 19788 +Test: [10400/21770] eta: 0:08:57 time: 0.0485 data: 0.0016 max mem: 19788 +Test: [10500/21770] eta: 0:08:53 time: 0.0519 data: 0.0017 max mem: 19788 +Test: [10600/21770] eta: 0:08:48 time: 0.0477 data: 0.0015 max mem: 19788 +Test: [10700/21770] eta: 0:08:44 time: 0.0522 data: 0.0017 max mem: 19788 +Test: [10800/21770] eta: 0:08:39 time: 0.0536 data: 0.0016 max mem: 19788 +Test: [10900/21770] eta: 0:08:34 time: 0.0464 data: 0.0016 max mem: 19788 +Test: [11000/21770] eta: 0:08:30 time: 0.0538 data: 0.0015 max mem: 19788 +Test: [11100/21770] eta: 0:08:25 time: 0.0544 data: 0.0017 max mem: 19788 +Test: [11200/21770] eta: 0:08:20 time: 0.0444 data: 0.0014 max mem: 19788 +Test: [11300/21770] eta: 0:08:15 time: 0.0520 data: 0.0017 max mem: 19788 +Test: [11400/21770] eta: 0:08:11 time: 0.0520 data: 0.0017 max mem: 19788 +Test: [11500/21770] eta: 0:08:06 time: 0.0444 data: 0.0015 max mem: 19788 +Test: [11600/21770] eta: 0:08:01 time: 0.0470 data: 0.0017 max mem: 19788 +Test: [11700/21770] eta: 0:07:57 time: 0.0461 data: 0.0016 max mem: 19788 +Test: [11800/21770] eta: 0:07:52 time: 0.0531 data: 0.0018 max mem: 19788 +Test: [11900/21770] eta: 0:07:48 time: 0.0477 data: 0.0016 max mem: 19788 +Test: [12000/21770] eta: 0:07:43 time: 0.0512 data: 0.0017 max mem: 19788 +Test: [12100/21770] eta: 0:07:38 time: 0.0493 data: 0.0017 max mem: 19788 +Test: [12200/21770] eta: 0:07:34 time: 0.0505 data: 0.0017 max mem: 19788 +Test: [12300/21770] eta: 0:07:29 time: 0.0524 data: 0.0018 max mem: 19788 +Test: [12400/21770] eta: 0:07:25 time: 0.0507 data: 0.0019 max mem: 19788 +Test: [12500/21770] eta: 0:07:20 time: 0.0531 data: 0.0018 max mem: 19788 +Test: [12600/21770] eta: 0:07:15 time: 0.0437 data: 0.0014 max mem: 19788 +Test: [12700/21770] eta: 0:07:11 time: 0.0527 data: 0.0018 max mem: 19788 +Test: [12800/21770] eta: 0:07:06 time: 0.0506 data: 0.0016 max mem: 19788 +Test: [12900/21770] eta: 0:07:02 time: 0.0463 data: 0.0019 max mem: 19788 +Test: [13000/21770] eta: 0:06:57 time: 0.0464 data: 0.0015 max mem: 19788 +Test: [13100/21770] eta: 0:06:53 time: 0.0508 data: 0.0016 max mem: 19788 +Test: [13200/21770] eta: 0:06:48 time: 0.0456 data: 0.0015 max mem: 19788 +Test: [13300/21770] eta: 0:06:43 time: 0.0457 data: 0.0014 max mem: 19788 +Test: [13400/21770] eta: 0:06:38 time: 0.0438 data: 0.0015 max mem: 19788 +Test: [13500/21770] eta: 0:06:33 time: 0.0445 data: 0.0014 max mem: 19788 +Test: [13600/21770] eta: 0:06:29 time: 0.0527 data: 0.0018 max mem: 19788 +Test: [13700/21770] eta: 0:06:24 time: 0.0474 data: 0.0016 max mem: 19788 +Test: [13800/21770] eta: 0:06:19 time: 0.0446 data: 0.0015 max mem: 19788 +Test: [13900/21770] eta: 0:06:14 time: 0.0502 data: 0.0014 max mem: 19788 +Test: [14000/21770] eta: 0:06:10 time: 0.0517 data: 0.0017 max mem: 19788 +Test: [14100/21770] eta: 0:06:05 time: 0.0461 data: 0.0015 max mem: 19788 +Test: [14200/21770] eta: 0:06:00 time: 0.0484 data: 0.0017 max mem: 19788 +Test: [14300/21770] eta: 0:05:55 time: 0.0453 data: 0.0016 max mem: 19788 +Test: [14400/21770] eta: 0:05:50 time: 0.0444 data: 0.0015 max mem: 19788 +Test: [14500/21770] eta: 0:05:45 time: 0.0437 data: 0.0015 max mem: 19788 +Test: [14600/21770] eta: 0:05:41 time: 0.0511 data: 0.0017 max mem: 19788 +Test: [14700/21770] eta: 0:05:36 time: 0.0442 data: 0.0013 max mem: 19788 +Test: [14800/21770] eta: 0:05:31 time: 0.0442 data: 0.0015 max mem: 19788 +Test: [14900/21770] eta: 0:05:26 time: 0.0469 data: 0.0015 max mem: 19788 +Test: [15000/21770] eta: 0:05:21 time: 0.0452 data: 0.0013 max mem: 19788 +Test: [15100/21770] eta: 0:05:17 time: 0.0498 data: 0.0016 max mem: 19788 +Test: [15200/21770] eta: 0:05:12 time: 0.0447 data: 0.0015 max mem: 19788 +Test: [15300/21770] eta: 0:05:07 time: 0.0493 data: 0.0016 max mem: 19788 +Test: [15400/21770] eta: 0:05:03 time: 0.0526 data: 0.0016 max mem: 19788 +Test: [15500/21770] eta: 0:04:58 time: 0.0497 data: 0.0017 max mem: 19788 +Test: [15600/21770] eta: 0:04:53 time: 0.0524 data: 0.0017 max mem: 19788 +Test: [15700/21770] eta: 0:04:48 time: 0.0469 data: 0.0016 max mem: 19788 +Test: [15800/21770] eta: 0:04:44 time: 0.0462 data: 0.0015 max mem: 19788 +Test: [15900/21770] eta: 0:04:39 time: 0.0513 data: 0.0016 max mem: 19788 +Test: [16000/21770] eta: 0:04:34 time: 0.0434 data: 0.0016 max mem: 19788 +Test: [16100/21770] eta: 0:04:29 time: 0.0446 data: 0.0016 max mem: 19788 +Test: [16200/21770] eta: 0:04:25 time: 0.0460 data: 0.0014 max mem: 19788 +Test: [16300/21770] eta: 0:04:20 time: 0.0446 data: 0.0013 max mem: 19788 +Test: [16400/21770] eta: 0:04:15 time: 0.0448 data: 0.0014 max mem: 19788 +Test: [16500/21770] eta: 0:04:10 time: 0.0428 data: 0.0014 max mem: 19788 +Test: [16600/21770] eta: 0:04:05 time: 0.0528 data: 0.0017 max mem: 19788 +Test: [16700/21770] eta: 0:04:01 time: 0.0442 data: 0.0014 max mem: 19788 +Test: [16800/21770] eta: 0:03:56 time: 0.0490 data: 0.0016 max mem: 19788 +Test: [16900/21770] eta: 0:03:51 time: 0.0437 data: 0.0014 max mem: 19788 +Test: [17000/21770] eta: 0:03:46 time: 0.0522 data: 0.0016 max mem: 19788 +Test: [17100/21770] eta: 0:03:41 time: 0.0440 data: 0.0014 max mem: 19788 +Test: [17200/21770] eta: 0:03:37 time: 0.0439 data: 0.0017 max mem: 19788 +Test: [17300/21770] eta: 0:03:32 time: 0.0453 data: 0.0015 max mem: 19788 +Test: [17400/21770] eta: 0:03:27 time: 0.0452 data: 0.0015 max mem: 19788 +Test: [17500/21770] eta: 0:03:22 time: 0.0492 data: 0.0018 max mem: 19788 +Test: [17600/21770] eta: 0:03:18 time: 0.0437 data: 0.0013 max mem: 19788 +Test: [17700/21770] eta: 0:03:13 time: 0.0443 data: 0.0016 max mem: 19788 +Test: [17800/21770] eta: 0:03:08 time: 0.0435 data: 0.0014 max mem: 19788 +Test: [17900/21770] eta: 0:03:03 time: 0.0433 data: 0.0013 max mem: 19788 +Test: [18000/21770] eta: 0:02:58 time: 0.0468 data: 0.0018 max mem: 19788 +Test: [18100/21770] eta: 0:02:54 time: 0.0528 data: 0.0018 max mem: 19788 +Test: [18200/21770] eta: 0:02:49 time: 0.0430 data: 0.0014 max mem: 19788 +Test: [18300/21770] eta: 0:02:44 time: 0.0490 data: 0.0016 max mem: 19788 +Test: [18400/21770] eta: 0:02:40 time: 0.0459 data: 0.0016 max mem: 19788 +Test: [18500/21770] eta: 0:02:35 time: 0.0426 data: 0.0016 max mem: 19788 +Test: [18600/21770] eta: 0:02:30 time: 0.0443 data: 0.0013 max mem: 19788 +Test: [18700/21770] eta: 0:02:25 time: 0.0433 data: 0.0013 max mem: 19788 +Test: [18800/21770] eta: 0:02:20 time: 0.0526 data: 0.0018 max mem: 19788 +Test: [18900/21770] eta: 0:02:16 time: 0.0448 data: 0.0013 max mem: 19788 +Test: [19000/21770] eta: 0:02:11 time: 0.0476 data: 0.0016 max mem: 19788 +Test: [19100/21770] eta: 0:02:06 time: 0.0434 data: 0.0014 max mem: 19788 +Test: [19200/21770] eta: 0:02:01 time: 0.0438 data: 0.0015 max mem: 19788 +Test: [19300/21770] eta: 0:01:57 time: 0.0447 data: 0.0015 max mem: 19788 +Test: [19400/21770] eta: 0:01:52 time: 0.0456 data: 0.0017 max mem: 19788 +Test: [19500/21770] eta: 0:01:47 time: 0.0455 data: 0.0017 max mem: 19788 +Test: [19600/21770] eta: 0:01:42 time: 0.0455 data: 0.0016 max mem: 19788 +Test: [19700/21770] eta: 0:01:38 time: 0.0432 data: 0.0016 max mem: 19788 +Test: [19800/21770] eta: 0:01:33 time: 0.0441 data: 0.0013 max mem: 19788 +Test: [19900/21770] eta: 0:01:28 time: 0.0487 data: 0.0016 max mem: 19788 +Test: [20000/21770] eta: 0:01:23 time: 0.0461 data: 0.0015 max mem: 19788 +Test: [20100/21770] eta: 0:01:19 time: 0.0434 data: 0.0013 max mem: 19788 +Test: [20200/21770] eta: 0:01:14 time: 0.0437 data: 0.0015 max mem: 19788 +Test: [20300/21770] eta: 0:01:09 time: 0.0435 data: 0.0014 max mem: 19788 +Test: [20400/21770] eta: 0:01:04 time: 0.0430 data: 0.0013 max mem: 19788 +Test: [20500/21770] eta: 0:01:00 time: 0.0475 data: 0.0015 max mem: 19788 +Test: [20600/21770] eta: 0:00:55 time: 0.0431 data: 0.0013 max mem: 19788 +Test: [20700/21770] eta: 0:00:50 time: 0.0522 data: 0.0018 max mem: 19788 +Test: [20800/21770] eta: 0:00:45 time: 0.0460 data: 0.0015 max mem: 19788 +Test: [20900/21770] eta: 0:00:41 time: 0.0513 data: 0.0019 max mem: 19788 +Test: [21000/21770] eta: 0:00:36 time: 0.0428 data: 0.0016 max mem: 19788 +Test: [21100/21770] eta: 0:00:31 time: 0.0435 data: 0.0013 max mem: 19788 +Test: [21200/21770] eta: 0:00:26 time: 0.0518 data: 0.0016 max mem: 19788 +Test: [21300/21770] eta: 0:00:22 time: 0.0448 data: 0.0015 max mem: 19788 +Test: [21400/21770] eta: 0:00:17 time: 0.0483 data: 0.0015 max mem: 19788 +Test: [21500/21770] eta: 0:00:12 time: 0.0521 data: 0.0017 max mem: 19788 +Test: [21600/21770] eta: 0:00:08 time: 0.0450 data: 0.0014 max mem: 19788 +Test: [21700/21770] eta: 0:00:03 time: 0.0424 data: 0.0014 max mem: 19788 +Test: Total time: 0:17:11 +Final results: +Mean IoU is 64.50 + + precision@0.5 = 71.88 + precision@0.6 = 66.55 + precision@0.7 = 60.09 + precision@0.8 = 49.49 + precision@0.9 = 24.13 + overall IoU = 65.15 + mean IoU = 64.50 + +Mean accuracy for one-to-zero sample is 87.49 + +Average object IoU 0.645033129862 +Overall IoU 65.15399169921875 +Epoch: [37] [ 0/2138] eta: 3:48:24 lr: 4.858074798974034e-06 loss: 0.0206 (0.0206) time: 6.4100 data: 1.4878 max mem: 19788 +Epoch: [37] [ 10/2138] eta: 1:53:21 lr: 4.85125644811626e-06 loss: 0.0173 (0.0196) time: 3.1962 data: 0.1372 max mem: 19788 +Epoch: [37] [ 20/2138] eta: 1:47:28 lr: 4.844437032306703e-06 loss: 0.0162 (0.0177) time: 2.8764 data: 0.0017 max mem: 19788 +Epoch: [37] [ 30/2138] eta: 1:45:34 lr: 4.83761654971284e-06 loss: 0.0177 (0.0182) time: 2.8995 data: 0.0020 max mem: 19788 +Epoch: [37] [ 40/2138] eta: 1:44:22 lr: 4.830794998496095e-06 loss: 0.0183 (0.0185) time: 2.9227 data: 0.0026 max mem: 19788 +Epoch: [37] [ 50/2138] eta: 1:43:35 lr: 4.8239723768118545e-06 loss: 0.0171 (0.0186) time: 2.9337 data: 0.0027 max mem: 19788 +Epoch: [37] [ 60/2138] eta: 1:42:58 lr: 4.817148682809398e-06 loss: 0.0176 (0.0188) time: 2.9482 data: 0.0029 max mem: 19788 +Epoch: [37] [ 70/2138] eta: 1:41:50 lr: 4.8103239146319065e-06 loss: 0.0172 (0.0186) time: 2.8981 data: 0.0025 max mem: 19788 +Epoch: [37] [ 80/2138] eta: 1:40:52 lr: 4.803498070416389e-06 loss: 0.0167 (0.0185) time: 2.8432 data: 0.0025 max mem: 19788 +Epoch: [37] [ 90/2138] eta: 1:40:00 lr: 4.796671148293705e-06 loss: 0.0164 (0.0183) time: 2.8429 data: 0.0029 max mem: 19788 +Epoch: [37] [ 100/2138] eta: 1:39:13 lr: 4.789843146388477e-06 loss: 0.0165 (0.0183) time: 2.8407 data: 0.0025 max mem: 19788 +Epoch: [37] [ 110/2138] eta: 1:38:28 lr: 4.783014062819114e-06 loss: 0.0165 (0.0181) time: 2.8384 data: 0.0022 max mem: 19788 +Epoch: [37] [ 120/2138] eta: 1:37:49 lr: 4.776183895697731e-06 loss: 0.0155 (0.0179) time: 2.8449 data: 0.0024 max mem: 19788 +Epoch: [37] [ 130/2138] eta: 1:37:14 lr: 4.769352643130169e-06 loss: 0.0174 (0.0180) time: 2.8602 data: 0.0023 max mem: 19788 +Epoch: [37] [ 140/2138] eta: 1:36:44 lr: 4.762520303215911e-06 loss: 0.0180 (0.0180) time: 2.8839 data: 0.0024 max mem: 19788 +Epoch: [37] [ 150/2138] eta: 1:36:29 lr: 4.7556868740481e-06 loss: 0.0170 (0.0180) time: 2.9568 data: 0.0027 max mem: 19788 +Epoch: [37] [ 160/2138] eta: 1:35:54 lr: 4.748852353713465e-06 loss: 0.0174 (0.0180) time: 2.9371 data: 0.0027 max mem: 19788 +Epoch: [37] [ 170/2138] eta: 1:35:16 lr: 4.74201674029233e-06 loss: 0.0169 (0.0180) time: 2.8459 data: 0.0025 max mem: 19788 +Epoch: [37] [ 180/2138] eta: 1:34:40 lr: 4.7351800318585374e-06 loss: 0.0179 (0.0180) time: 2.8358 data: 0.0023 max mem: 19788 +Epoch: [37] [ 190/2138] eta: 1:34:04 lr: 4.7283422264794645e-06 loss: 0.0173 (0.0179) time: 2.8391 data: 0.0023 max mem: 19788 +Epoch: [37] [ 200/2138] eta: 1:33:29 lr: 4.721503322215941e-06 loss: 0.0161 (0.0179) time: 2.8361 data: 0.0021 max mem: 19788 +Epoch: [37] [ 210/2138] eta: 1:32:54 lr: 4.714663317122268e-06 loss: 0.0174 (0.0179) time: 2.8301 data: 0.0024 max mem: 19788 +Epoch: [37] [ 220/2138] eta: 1:32:20 lr: 4.7078222092461305e-06 loss: 0.0167 (0.0179) time: 2.8298 data: 0.0025 max mem: 19788 +Epoch: [37] [ 230/2138] eta: 1:31:50 lr: 4.7009799966286215e-06 loss: 0.0149 (0.0179) time: 2.8577 data: 0.0024 max mem: 19788 +Epoch: [37] [ 240/2138] eta: 1:31:22 lr: 4.694136677304153e-06 loss: 0.0174 (0.0179) time: 2.8862 data: 0.0025 max mem: 19788 +Epoch: [37] [ 250/2138] eta: 1:30:57 lr: 4.687292249300477e-06 loss: 0.0174 (0.0178) time: 2.9179 data: 0.0026 max mem: 19788 +Epoch: [37] [ 260/2138] eta: 1:30:30 lr: 4.680446710638597e-06 loss: 0.0162 (0.0178) time: 2.9288 data: 0.0025 max mem: 19788 +Epoch: [37] [ 270/2138] eta: 1:29:59 lr: 4.673600059332787e-06 loss: 0.0168 (0.0178) time: 2.8882 data: 0.0025 max mem: 19788 +Epoch: [37] [ 280/2138] eta: 1:29:28 lr: 4.6667522933905165e-06 loss: 0.0179 (0.0178) time: 2.8593 data: 0.0025 max mem: 19788 +Epoch: [37] [ 290/2138] eta: 1:28:56 lr: 4.659903410812429e-06 loss: 0.0175 (0.0178) time: 2.8477 data: 0.0025 max mem: 19788 +Epoch: [37] [ 300/2138] eta: 1:28:23 lr: 4.653053409592328e-06 loss: 0.0170 (0.0178) time: 2.8345 data: 0.0028 max mem: 19788 +Epoch: [37] [ 310/2138] eta: 1:27:51 lr: 4.6462022877171015e-06 loss: 0.0163 (0.0178) time: 2.8307 data: 0.0025 max mem: 19788 +Epoch: [37] [ 320/2138] eta: 1:27:19 lr: 4.639350043166736e-06 loss: 0.0154 (0.0177) time: 2.8298 data: 0.0023 max mem: 19788 +Epoch: [37] [ 330/2138] eta: 1:26:54 lr: 4.6324966739142274e-06 loss: 0.0170 (0.0178) time: 2.8906 data: 0.0025 max mem: 19788 +Epoch: [37] [ 340/2138] eta: 1:26:28 lr: 4.6256421779256006e-06 loss: 0.0186 (0.0178) time: 2.9388 data: 0.0024 max mem: 19788 +Epoch: [37] [ 350/2138] eta: 1:26:01 lr: 4.61878655315982e-06 loss: 0.0174 (0.0178) time: 2.9246 data: 0.0025 max mem: 19788 +Epoch: [37] [ 360/2138] eta: 1:25:33 lr: 4.6119297975688074e-06 loss: 0.0183 (0.0178) time: 2.9163 data: 0.0025 max mem: 19788 +Epoch: [37] [ 370/2138] eta: 1:25:02 lr: 4.60507190909735e-06 loss: 0.0191 (0.0178) time: 2.8715 data: 0.0024 max mem: 19788 +Epoch: [37] [ 380/2138] eta: 1:24:31 lr: 4.59821288568312e-06 loss: 0.0169 (0.0178) time: 2.8374 data: 0.0025 max mem: 19788 +Epoch: [37] [ 390/2138] eta: 1:24:00 lr: 4.591352725256583e-06 loss: 0.0154 (0.0178) time: 2.8382 data: 0.0028 max mem: 19788 +Epoch: [37] [ 400/2138] eta: 1:23:29 lr: 4.584491425741017e-06 loss: 0.0170 (0.0178) time: 2.8400 data: 0.0025 max mem: 19788 +Epoch: [37] [ 410/2138] eta: 1:22:58 lr: 4.577628985052418e-06 loss: 0.0166 (0.0178) time: 2.8394 data: 0.0021 max mem: 19788 +Epoch: [37] [ 420/2138] eta: 1:22:29 lr: 4.570765401099518e-06 loss: 0.0157 (0.0177) time: 2.8584 data: 0.0025 max mem: 19788 +Epoch: [37] [ 430/2138] eta: 1:22:01 lr: 4.563900671783695e-06 loss: 0.0155 (0.0177) time: 2.8817 data: 0.0025 max mem: 19788 +Epoch: [37] [ 440/2138] eta: 1:21:33 lr: 4.557034794998985e-06 loss: 0.0163 (0.0178) time: 2.8993 data: 0.0023 max mem: 19788 +Epoch: [37] [ 450/2138] eta: 1:21:10 lr: 4.5501677686319925e-06 loss: 0.0179 (0.0178) time: 2.9756 data: 0.0024 max mem: 19788 +Epoch: [37] [ 460/2138] eta: 1:20:41 lr: 4.543299590561908e-06 loss: 0.0165 (0.0178) time: 2.9587 data: 0.0024 max mem: 19788 +Epoch: [37] [ 470/2138] eta: 1:20:13 lr: 4.536430258660409e-06 loss: 0.0165 (0.0177) time: 2.8903 data: 0.0025 max mem: 19788 +Epoch: [37] [ 480/2138] eta: 1:19:44 lr: 4.529559770791685e-06 loss: 0.0185 (0.0178) time: 2.8945 data: 0.0025 max mem: 19788 +Epoch: [37] [ 490/2138] eta: 1:19:13 lr: 4.52268812481233e-06 loss: 0.0180 (0.0177) time: 2.8619 data: 0.0027 max mem: 19788 +Epoch: [37] [ 500/2138] eta: 1:18:44 lr: 4.515815318571371e-06 loss: 0.0153 (0.0177) time: 2.8481 data: 0.0027 max mem: 19788 +Epoch: [37] [ 510/2138] eta: 1:18:14 lr: 4.508941349910166e-06 loss: 0.0143 (0.0177) time: 2.8515 data: 0.0027 max mem: 19788 +Epoch: [37] [ 520/2138] eta: 1:17:44 lr: 4.5020662166624195e-06 loss: 0.0146 (0.0177) time: 2.8469 data: 0.0029 max mem: 19788 +Epoch: [37] [ 530/2138] eta: 1:17:17 lr: 4.4951899166540916e-06 loss: 0.0163 (0.0177) time: 2.9047 data: 0.0028 max mem: 19788 +Epoch: [37] [ 540/2138] eta: 1:16:52 lr: 4.488312447703403e-06 loss: 0.0168 (0.0177) time: 2.9783 data: 0.0027 max mem: 19788 +Epoch: [37] [ 550/2138] eta: 1:16:24 lr: 4.481433807620749e-06 loss: 0.0170 (0.0177) time: 2.9594 data: 0.0027 max mem: 19788 +Epoch: [37] [ 560/2138] eta: 1:15:54 lr: 4.47455399420871e-06 loss: 0.0182 (0.0178) time: 2.8773 data: 0.0027 max mem: 19788 +Epoch: [37] [ 570/2138] eta: 1:15:24 lr: 4.46767300526195e-06 loss: 0.0179 (0.0177) time: 2.8407 data: 0.0025 max mem: 19788 +Epoch: [37] [ 580/2138] eta: 1:14:53 lr: 4.4607908385672365e-06 loss: 0.0156 (0.0178) time: 2.8412 data: 0.0023 max mem: 19788 +Epoch: [37] [ 590/2138] eta: 1:14:23 lr: 4.453907491903347e-06 loss: 0.0177 (0.0178) time: 2.8386 data: 0.0023 max mem: 19788 +Epoch: [37] [ 600/2138] eta: 1:13:53 lr: 4.447022963041049e-06 loss: 0.0177 (0.0178) time: 2.8370 data: 0.0025 max mem: 19788 +Epoch: [37] [ 610/2138] eta: 1:13:23 lr: 4.440137249743074e-06 loss: 0.0169 (0.0178) time: 2.8353 data: 0.0025 max mem: 19788 +Epoch: [37] [ 620/2138] eta: 1:12:53 lr: 4.43325034976403e-06 loss: 0.0179 (0.0178) time: 2.8338 data: 0.0023 max mem: 19788 +Epoch: [37] [ 630/2138] eta: 1:12:27 lr: 4.426362260850413e-06 loss: 0.0178 (0.0179) time: 2.8998 data: 0.0022 max mem: 19788 +Epoch: [37] [ 640/2138] eta: 1:11:59 lr: 4.419472980740508e-06 loss: 0.0169 (0.0179) time: 2.9513 data: 0.0024 max mem: 19788 +Epoch: [37] [ 650/2138] eta: 1:11:31 lr: 4.4125825071643965e-06 loss: 0.0170 (0.0179) time: 2.9229 data: 0.0025 max mem: 19788 +Epoch: [37] [ 660/2138] eta: 1:11:01 lr: 4.405690837843864e-06 loss: 0.0177 (0.0179) time: 2.8847 data: 0.0025 max mem: 19788 +Epoch: [37] [ 670/2138] eta: 1:10:32 lr: 4.398797970492404e-06 loss: 0.0177 (0.0179) time: 2.8696 data: 0.0025 max mem: 19788 +Epoch: [37] [ 680/2138] eta: 1:10:03 lr: 4.391903902815123e-06 loss: 0.0167 (0.0179) time: 2.8575 data: 0.0023 max mem: 19788 +Epoch: [37] [ 690/2138] eta: 1:09:33 lr: 4.385008632508745e-06 loss: 0.0168 (0.0179) time: 2.8351 data: 0.0021 max mem: 19788 +Epoch: [37] [ 700/2138] eta: 1:09:05 lr: 4.3781121572615185e-06 loss: 0.0174 (0.0179) time: 2.8906 data: 0.0020 max mem: 19788 +Epoch: [37] [ 710/2138] eta: 1:08:35 lr: 4.371214474753217e-06 loss: 0.0170 (0.0179) time: 2.8843 data: 0.0020 max mem: 19788 +Epoch: [37] [ 720/2138] eta: 1:08:06 lr: 4.3643155826550435e-06 loss: 0.0155 (0.0178) time: 2.8483 data: 0.0021 max mem: 19788 +Epoch: [37] [ 730/2138] eta: 1:07:38 lr: 4.357415478629639e-06 loss: 0.0155 (0.0178) time: 2.8844 data: 0.0021 max mem: 19788 +Epoch: [37] [ 740/2138] eta: 1:07:10 lr: 4.350514160330977e-06 loss: 0.0178 (0.0179) time: 2.9170 data: 0.0020 max mem: 19788 +Epoch: [37] [ 750/2138] eta: 1:06:42 lr: 4.343611625404374e-06 loss: 0.0179 (0.0179) time: 2.9413 data: 0.0022 max mem: 19788 +Epoch: [37] [ 760/2138] eta: 1:06:13 lr: 4.336707871486386e-06 loss: 0.0181 (0.0179) time: 2.9092 data: 0.0025 max mem: 19788 +Epoch: [37] [ 770/2138] eta: 1:05:44 lr: 4.329802896204818e-06 loss: 0.0177 (0.0179) time: 2.8554 data: 0.0027 max mem: 19788 +Epoch: [37] [ 780/2138] eta: 1:05:14 lr: 4.3228966971786155e-06 loss: 0.0164 (0.0179) time: 2.8352 data: 0.0025 max mem: 19788 +Epoch: [37] [ 790/2138] eta: 1:04:44 lr: 4.315989272017876e-06 loss: 0.0158 (0.0179) time: 2.8324 data: 0.0026 max mem: 19788 +Epoch: [37] [ 800/2138] eta: 1:04:14 lr: 4.309080618323743e-06 loss: 0.0166 (0.0179) time: 2.8317 data: 0.0025 max mem: 19788 +Epoch: [37] [ 810/2138] eta: 1:03:45 lr: 4.302170733688411e-06 loss: 0.0175 (0.0179) time: 2.8343 data: 0.0024 max mem: 19788 +Epoch: [37] [ 820/2138] eta: 1:03:16 lr: 4.295259615695025e-06 loss: 0.0172 (0.0179) time: 2.8414 data: 0.0023 max mem: 19788 +Epoch: [37] [ 830/2138] eta: 1:02:48 lr: 4.288347261917677e-06 loss: 0.0149 (0.0179) time: 2.8905 data: 0.0023 max mem: 19788 +Epoch: [37] [ 840/2138] eta: 1:02:19 lr: 4.281433669921309e-06 loss: 0.0151 (0.0178) time: 2.9277 data: 0.0025 max mem: 19788 +Epoch: [37] [ 850/2138] eta: 1:01:51 lr: 4.274518837261713e-06 loss: 0.0169 (0.0178) time: 2.9125 data: 0.0025 max mem: 19788 +Epoch: [37] [ 860/2138] eta: 1:01:21 lr: 4.2676027614854276e-06 loss: 0.0171 (0.0178) time: 2.8688 data: 0.0023 max mem: 19788 +Epoch: [37] [ 870/2138] eta: 1:00:52 lr: 4.260685440129737e-06 loss: 0.0161 (0.0179) time: 2.8406 data: 0.0024 max mem: 19788 +Epoch: [37] [ 880/2138] eta: 1:00:23 lr: 4.253766870722568e-06 loss: 0.0165 (0.0179) time: 2.8561 data: 0.0027 max mem: 19788 +Epoch: [37] [ 890/2138] eta: 0:59:54 lr: 4.246847050782493e-06 loss: 0.0172 (0.0179) time: 2.8553 data: 0.0026 max mem: 19788 +Epoch: [37] [ 900/2138] eta: 0:59:25 lr: 4.239925977818626e-06 loss: 0.0173 (0.0179) time: 2.8600 data: 0.0023 max mem: 19788 +Epoch: [37] [ 910/2138] eta: 0:58:56 lr: 4.233003649330593e-06 loss: 0.0173 (0.0179) time: 2.8619 data: 0.0022 max mem: 19788 +Epoch: [37] [ 920/2138] eta: 0:58:27 lr: 4.226080062808496e-06 loss: 0.0165 (0.0179) time: 2.8508 data: 0.0024 max mem: 19788 +Epoch: [37] [ 930/2138] eta: 0:57:58 lr: 4.219155215732816e-06 loss: 0.0183 (0.0179) time: 2.8915 data: 0.0027 max mem: 19788 +Epoch: [37] [ 940/2138] eta: 0:57:30 lr: 4.212229105574409e-06 loss: 0.0198 (0.0179) time: 2.9322 data: 0.0028 max mem: 19788 +Epoch: [37] [ 950/2138] eta: 0:57:02 lr: 4.205301729794399e-06 loss: 0.0177 (0.0179) time: 2.9167 data: 0.0024 max mem: 19788 +Epoch: [37] [ 960/2138] eta: 0:56:32 lr: 4.198373085844177e-06 loss: 0.0188 (0.0180) time: 2.8666 data: 0.0022 max mem: 19788 +Epoch: [37] [ 970/2138] eta: 0:56:03 lr: 4.191443171165289e-06 loss: 0.0188 (0.0180) time: 2.8329 data: 0.0021 max mem: 19788 +Epoch: [37] [ 980/2138] eta: 0:55:34 lr: 4.184511983189439e-06 loss: 0.0158 (0.0179) time: 2.8325 data: 0.0023 max mem: 19788 +Epoch: [37] [ 990/2138] eta: 0:55:05 lr: 4.177579519338376e-06 loss: 0.0158 (0.0179) time: 2.8530 data: 0.0025 max mem: 19788 +Epoch: [37] [1000/2138] eta: 0:54:36 lr: 4.170645777023887e-06 loss: 0.0158 (0.0179) time: 2.8613 data: 0.0025 max mem: 19788 +Epoch: [37] [1010/2138] eta: 0:54:06 lr: 4.163710753647694e-06 loss: 0.0158 (0.0179) time: 2.8381 data: 0.0023 max mem: 19788 +Epoch: [37] [1020/2138] eta: 0:53:37 lr: 4.1567744466014455e-06 loss: 0.0155 (0.0179) time: 2.8352 data: 0.0023 max mem: 19788 +Epoch: [37] [1030/2138] eta: 0:53:09 lr: 4.149836853266604e-06 loss: 0.0153 (0.0179) time: 2.8715 data: 0.0024 max mem: 19788 +Epoch: [37] [1040/2138] eta: 0:52:40 lr: 4.142897971014443e-06 loss: 0.0169 (0.0179) time: 2.9186 data: 0.0023 max mem: 19788 +Epoch: [37] [1050/2138] eta: 0:52:13 lr: 4.135957797205936e-06 loss: 0.0183 (0.0179) time: 2.9565 data: 0.0022 max mem: 19788 +Epoch: [37] [1060/2138] eta: 0:51:44 lr: 4.1290163291917446e-06 loss: 0.0181 (0.0179) time: 2.9124 data: 0.0021 max mem: 19788 +Epoch: [37] [1070/2138] eta: 0:51:14 lr: 4.122073564312114e-06 loss: 0.0172 (0.0179) time: 2.8452 data: 0.0022 max mem: 19788 +Epoch: [37] [1080/2138] eta: 0:50:47 lr: 4.1151294998968564e-06 loss: 0.0168 (0.0179) time: 2.9318 data: 0.0021 max mem: 19788 +Epoch: [37] [1090/2138] eta: 0:50:33 lr: 4.108184133265247e-06 loss: 0.0168 (0.0179) time: 3.7380 data: 0.0021 max mem: 19788 +Epoch: [37] [1100/2138] eta: 0:50:04 lr: 4.101237461726006e-06 loss: 0.0200 (0.0179) time: 3.6563 data: 0.0023 max mem: 19788 +Epoch: [37] [1110/2138] eta: 0:49:35 lr: 4.094289482577191e-06 loss: 0.0173 (0.0179) time: 2.8546 data: 0.0025 max mem: 19788 +Epoch: [37] [1120/2138] eta: 0:49:05 lr: 4.087340193106186e-06 loss: 0.0163 (0.0179) time: 2.8528 data: 0.0028 max mem: 19788 +Epoch: [37] [1130/2138] eta: 0:48:37 lr: 4.080389590589583e-06 loss: 0.0161 (0.0179) time: 2.8803 data: 0.0027 max mem: 19788 +Epoch: [37] [1140/2138] eta: 0:48:08 lr: 4.073437672293174e-06 loss: 0.0165 (0.0179) time: 2.9265 data: 0.0026 max mem: 19788 +Epoch: [37] [1150/2138] eta: 0:47:40 lr: 4.066484435471837e-06 loss: 0.0159 (0.0179) time: 2.9507 data: 0.0026 max mem: 19788 +Epoch: [37] [1160/2138] eta: 0:47:10 lr: 4.0595298773695195e-06 loss: 0.0155 (0.0179) time: 2.9128 data: 0.0027 max mem: 19788 +Epoch: [37] [1170/2138] eta: 0:46:41 lr: 4.052573995219125e-06 loss: 0.0156 (0.0179) time: 2.8619 data: 0.0027 max mem: 19788 +Epoch: [37] [1180/2138] eta: 0:46:12 lr: 4.0456167862424975e-06 loss: 0.0164 (0.0179) time: 2.8671 data: 0.0025 max mem: 19788 +Epoch: [37] [1190/2138] eta: 0:45:43 lr: 4.038658247650307e-06 loss: 0.0164 (0.0179) time: 2.8692 data: 0.0025 max mem: 19788 +Epoch: [37] [1200/2138] eta: 0:45:14 lr: 4.031698376642031e-06 loss: 0.0155 (0.0179) time: 2.8611 data: 0.0028 max mem: 19788 +Epoch: [37] [1210/2138] eta: 0:44:44 lr: 4.024737170405848e-06 loss: 0.0176 (0.0179) time: 2.8575 data: 0.0029 max mem: 19788 +Epoch: [37] [1220/2138] eta: 0:44:15 lr: 4.017774626118584e-06 loss: 0.0168 (0.0179) time: 2.8584 data: 0.0025 max mem: 19788 +Epoch: [37] [1230/2138] eta: 0:43:47 lr: 4.010810740945667e-06 loss: 0.0167 (0.0179) time: 2.9065 data: 0.0022 max mem: 19788 +Epoch: [37] [1240/2138] eta: 0:43:18 lr: 4.003845512041015e-06 loss: 0.0160 (0.0179) time: 2.9502 data: 0.0023 max mem: 19788 +Epoch: [37] [1250/2138] eta: 0:42:50 lr: 3.9968789365470135e-06 loss: 0.0161 (0.0179) time: 2.9900 data: 0.0023 max mem: 19788 +Epoch: [37] [1260/2138] eta: 0:42:21 lr: 3.989911011594401e-06 loss: 0.0158 (0.0178) time: 2.9393 data: 0.0024 max mem: 19788 +Epoch: [37] [1270/2138] eta: 0:41:52 lr: 3.982941734302247e-06 loss: 0.0164 (0.0178) time: 2.8722 data: 0.0024 max mem: 19788 +Epoch: [37] [1280/2138] eta: 0:41:23 lr: 3.975971101777829e-06 loss: 0.0175 (0.0178) time: 2.8807 data: 0.0022 max mem: 19788 +Epoch: [37] [1290/2138] eta: 0:40:54 lr: 3.968999111116617e-06 loss: 0.0174 (0.0178) time: 2.8712 data: 0.0024 max mem: 19788 +Epoch: [37] [1300/2138] eta: 0:40:25 lr: 3.962025759402145e-06 loss: 0.0164 (0.0178) time: 2.8739 data: 0.0023 max mem: 19788 +Epoch: [37] [1310/2138] eta: 0:39:56 lr: 3.955051043705995e-06 loss: 0.0171 (0.0178) time: 2.8779 data: 0.0022 max mem: 19788 +Epoch: [37] [1320/2138] eta: 0:39:27 lr: 3.948074961087671e-06 loss: 0.0171 (0.0178) time: 2.8670 data: 0.0024 max mem: 19788 +Epoch: [37] [1330/2138] eta: 0:38:58 lr: 3.941097508594577e-06 loss: 0.0160 (0.0178) time: 2.8810 data: 0.0024 max mem: 19788 +Epoch: [37] [1340/2138] eta: 0:38:29 lr: 3.9341186832618885e-06 loss: 0.0174 (0.0178) time: 2.9216 data: 0.0023 max mem: 19788 +Epoch: [37] [1350/2138] eta: 0:38:00 lr: 3.927138482112538e-06 loss: 0.0200 (0.0179) time: 2.9346 data: 0.0022 max mem: 19788 +Epoch: [37] [1360/2138] eta: 0:37:31 lr: 3.920156902157079e-06 loss: 0.0178 (0.0179) time: 2.9127 data: 0.0024 max mem: 19788 +Epoch: [37] [1370/2138] eta: 0:37:02 lr: 3.913173940393666e-06 loss: 0.0168 (0.0179) time: 2.8766 data: 0.0026 max mem: 19788 +Epoch: [37] [1380/2138] eta: 0:36:33 lr: 3.906189593807928e-06 loss: 0.0168 (0.0179) time: 2.8643 data: 0.0025 max mem: 19788 +Epoch: [37] [1390/2138] eta: 0:36:04 lr: 3.899203859372938e-06 loss: 0.0166 (0.0179) time: 2.8625 data: 0.0026 max mem: 19788 +Epoch: [37] [1400/2138] eta: 0:35:35 lr: 3.8922167340490895e-06 loss: 0.0161 (0.0179) time: 2.8653 data: 0.0026 max mem: 19788 +Epoch: [37] [1410/2138] eta: 0:35:06 lr: 3.8852282147840685e-06 loss: 0.0157 (0.0178) time: 2.8626 data: 0.0021 max mem: 19788 +Epoch: [37] [1420/2138] eta: 0:34:37 lr: 3.878238298512717e-06 loss: 0.0172 (0.0178) time: 2.8612 data: 0.0022 max mem: 19788 +Epoch: [37] [1430/2138] eta: 0:34:08 lr: 3.871246982157014e-06 loss: 0.0180 (0.0179) time: 2.9431 data: 0.0025 max mem: 19788 +Epoch: [37] [1440/2138] eta: 0:33:40 lr: 3.86425426262594e-06 loss: 0.0182 (0.0179) time: 3.0068 data: 0.0025 max mem: 19788 +Epoch: [37] [1450/2138] eta: 0:33:11 lr: 3.857260136815444e-06 loss: 0.0182 (0.0179) time: 2.9454 data: 0.0022 max mem: 19788 +Epoch: [37] [1460/2138] eta: 0:32:42 lr: 3.850264601608316e-06 loss: 0.0178 (0.0179) time: 2.8830 data: 0.0022 max mem: 19788 +Epoch: [37] [1470/2138] eta: 0:32:13 lr: 3.843267653874153e-06 loss: 0.0158 (0.0179) time: 2.8802 data: 0.0022 max mem: 19788 +Epoch: [37] [1480/2138] eta: 0:31:44 lr: 3.836269290469224e-06 loss: 0.0151 (0.0179) time: 2.8881 data: 0.0022 max mem: 19788 +Epoch: [37] [1490/2138] eta: 0:31:15 lr: 3.829269508236444e-06 loss: 0.0177 (0.0179) time: 2.9231 data: 0.0024 max mem: 19788 +Epoch: [37] [1500/2138] eta: 0:30:46 lr: 3.822268304005235e-06 loss: 0.0185 (0.0179) time: 2.9240 data: 0.0024 max mem: 19788 +Epoch: [37] [1510/2138] eta: 0:30:17 lr: 3.815265674591467e-06 loss: 0.0180 (0.0179) time: 2.8854 data: 0.0027 max mem: 19788 +Epoch: [37] [1520/2138] eta: 0:29:48 lr: 3.8082616167973936e-06 loss: 0.0180 (0.0179) time: 2.8906 data: 0.0030 max mem: 19788 +Epoch: [37] [1530/2138] eta: 0:29:19 lr: 3.8012561274115108e-06 loss: 0.0184 (0.0179) time: 2.8893 data: 0.0029 max mem: 19788 +Epoch: [37] [1540/2138] eta: 0:28:50 lr: 3.794249203208532e-06 loss: 0.0176 (0.0179) time: 2.8840 data: 0.0027 max mem: 19788 +Epoch: [37] [1550/2138] eta: 0:28:22 lr: 3.787240840949243e-06 loss: 0.0167 (0.0179) time: 2.9013 data: 0.0025 max mem: 19788 +Epoch: [37] [1560/2138] eta: 0:27:53 lr: 3.7802310373804652e-06 loss: 0.0177 (0.0179) time: 2.8986 data: 0.0025 max mem: 19788 +Epoch: [37] [1570/2138] eta: 0:27:24 lr: 3.773219789234915e-06 loss: 0.0181 (0.0179) time: 2.8827 data: 0.0025 max mem: 19788 +Epoch: [37] [1580/2138] eta: 0:26:55 lr: 3.766207093231168e-06 loss: 0.0176 (0.0179) time: 2.9153 data: 0.0023 max mem: 19788 +Epoch: [37] [1590/2138] eta: 0:26:26 lr: 3.7591929460735114e-06 loss: 0.0167 (0.0179) time: 2.9073 data: 0.0021 max mem: 19788 +Epoch: [37] [1600/2138] eta: 0:25:57 lr: 3.7521773444519097e-06 loss: 0.0193 (0.0179) time: 2.8719 data: 0.0021 max mem: 19788 +Epoch: [37] [1610/2138] eta: 0:25:28 lr: 3.745160285041855e-06 loss: 0.0196 (0.0179) time: 2.8848 data: 0.0021 max mem: 19788 +Epoch: [37] [1620/2138] eta: 0:24:59 lr: 3.7381417645043303e-06 loss: 0.0152 (0.0179) time: 2.8892 data: 0.0021 max mem: 19788 +Epoch: [37] [1630/2138] eta: 0:24:30 lr: 3.731121779485659e-06 loss: 0.0158 (0.0179) time: 2.8906 data: 0.0022 max mem: 19788 +Epoch: [37] [1640/2138] eta: 0:24:01 lr: 3.724100326617468e-06 loss: 0.0170 (0.0179) time: 2.9021 data: 0.0022 max mem: 19788 +Epoch: [37] [1650/2138] eta: 0:23:32 lr: 3.7170774025165333e-06 loss: 0.0177 (0.0179) time: 2.8965 data: 0.0021 max mem: 19788 +Epoch: [37] [1660/2138] eta: 0:23:03 lr: 3.7100530037847406e-06 loss: 0.0178 (0.0179) time: 2.8891 data: 0.0021 max mem: 19788 +Epoch: [37] [1670/2138] eta: 0:22:34 lr: 3.703027127008933e-06 loss: 0.0167 (0.0179) time: 2.9271 data: 0.0022 max mem: 19788 +Epoch: [37] [1680/2138] eta: 0:22:05 lr: 3.6959997687608675e-06 loss: 0.0159 (0.0179) time: 2.9190 data: 0.0025 max mem: 19788 +Epoch: [37] [1690/2138] eta: 0:21:36 lr: 3.688970925597061e-06 loss: 0.0160 (0.0179) time: 2.8778 data: 0.0027 max mem: 19788 +Epoch: [37] [1700/2138] eta: 0:21:07 lr: 3.681940594058745e-06 loss: 0.0163 (0.0179) time: 2.8837 data: 0.0029 max mem: 19788 +Epoch: [37] [1710/2138] eta: 0:20:38 lr: 3.674908770671711e-06 loss: 0.0165 (0.0179) time: 2.8898 data: 0.0027 max mem: 19788 +Epoch: [37] [1720/2138] eta: 0:20:09 lr: 3.667875451946263e-06 loss: 0.0194 (0.0179) time: 2.8845 data: 0.0026 max mem: 19788 +Epoch: [37] [1730/2138] eta: 0:19:41 lr: 3.66084063437706e-06 loss: 0.0182 (0.0179) time: 2.8840 data: 0.0028 max mem: 19788 +Epoch: [37] [1740/2138] eta: 0:19:12 lr: 3.6538043144430675e-06 loss: 0.0170 (0.0179) time: 2.8783 data: 0.0025 max mem: 19788 +Epoch: [37] [1750/2138] eta: 0:18:43 lr: 3.6467664886074005e-06 loss: 0.0169 (0.0179) time: 2.9514 data: 0.0024 max mem: 19788 +Epoch: [37] [1760/2138] eta: 0:18:14 lr: 3.6397271533172683e-06 loss: 0.0168 (0.0179) time: 2.9929 data: 0.0025 max mem: 19788 +Epoch: [37] [1770/2138] eta: 0:17:45 lr: 3.6326863050038186e-06 loss: 0.0158 (0.0179) time: 2.9144 data: 0.0024 max mem: 19788 +Epoch: [37] [1780/2138] eta: 0:17:16 lr: 3.6256439400820815e-06 loss: 0.0161 (0.0179) time: 2.8740 data: 0.0023 max mem: 19788 +Epoch: [37] [1790/2138] eta: 0:16:47 lr: 3.618600054950811e-06 loss: 0.0161 (0.0179) time: 2.8769 data: 0.0023 max mem: 19788 +Epoch: [37] [1800/2138] eta: 0:16:18 lr: 3.6115546459924244e-06 loss: 0.0197 (0.0179) time: 2.8848 data: 0.0026 max mem: 19788 +Epoch: [37] [1810/2138] eta: 0:15:49 lr: 3.6045077095728512e-06 loss: 0.0182 (0.0179) time: 2.8754 data: 0.0026 max mem: 19788 +Epoch: [37] [1820/2138] eta: 0:15:20 lr: 3.5974592420414377e-06 loss: 0.0170 (0.0179) time: 2.8815 data: 0.0025 max mem: 19788 +Epoch: [37] [1830/2138] eta: 0:14:51 lr: 3.5904092397308583e-06 loss: 0.0173 (0.0179) time: 2.8855 data: 0.0026 max mem: 19788 +Epoch: [37] [1840/2138] eta: 0:14:22 lr: 3.583357698956953e-06 loss: 0.0177 (0.0179) time: 2.9221 data: 0.0027 max mem: 19788 +Epoch: [37] [1850/2138] eta: 0:13:53 lr: 3.5763046160186713e-06 loss: 0.0181 (0.0179) time: 2.9276 data: 0.0029 max mem: 19788 +Epoch: [37] [1860/2138] eta: 0:13:24 lr: 3.5692499871978964e-06 loss: 0.0174 (0.0179) time: 2.8827 data: 0.0030 max mem: 19788 +Epoch: [37] [1870/2138] eta: 0:12:55 lr: 3.5621938087593917e-06 loss: 0.0173 (0.0179) time: 2.8830 data: 0.0029 max mem: 19788 +Epoch: [37] [1880/2138] eta: 0:12:26 lr: 3.555136076950623e-06 loss: 0.0156 (0.0179) time: 2.8918 data: 0.0028 max mem: 19788 +Epoch: [37] [1890/2138] eta: 0:11:57 lr: 3.5480767880016966e-06 loss: 0.0144 (0.0179) time: 2.8915 data: 0.0028 max mem: 19788 +Epoch: [37] [1900/2138] eta: 0:11:29 lr: 3.541015938125189e-06 loss: 0.0156 (0.0179) time: 2.8861 data: 0.0027 max mem: 19788 +Epoch: [37] [1910/2138] eta: 0:11:00 lr: 3.533953523516075e-06 loss: 0.0170 (0.0179) time: 2.8858 data: 0.0026 max mem: 19788 +Epoch: [37] [1920/2138] eta: 0:10:31 lr: 3.526889540351557e-06 loss: 0.0160 (0.0179) time: 2.8822 data: 0.0027 max mem: 19788 +Epoch: [37] [1930/2138] eta: 0:10:02 lr: 3.5198239847909953e-06 loss: 0.0161 (0.0179) time: 2.9898 data: 0.0026 max mem: 19788 +Epoch: [37] [1940/2138] eta: 0:09:33 lr: 3.512756852975728e-06 loss: 0.0167 (0.0179) time: 2.9915 data: 0.0026 max mem: 19788 +Epoch: [37] [1950/2138] eta: 0:09:04 lr: 3.5056881410290043e-06 loss: 0.0174 (0.0179) time: 2.8804 data: 0.0030 max mem: 19788 +Epoch: [37] [1960/2138] eta: 0:08:35 lr: 3.498617845055803e-06 loss: 0.0174 (0.0179) time: 2.8852 data: 0.0027 max mem: 19788 +Epoch: [37] [1970/2138] eta: 0:08:06 lr: 3.4915459611427578e-06 loss: 0.0159 (0.0179) time: 2.8936 data: 0.0026 max mem: 19788 +Epoch: [37] [1980/2138] eta: 0:07:37 lr: 3.484472485357978e-06 loss: 0.0170 (0.0179) time: 2.8968 data: 0.0026 max mem: 19788 +Epoch: [37] [1990/2138] eta: 0:07:08 lr: 3.47739741375097e-06 loss: 0.0175 (0.0179) time: 2.8931 data: 0.0025 max mem: 19788 +Epoch: [37] [2000/2138] eta: 0:06:39 lr: 3.4703207423524556e-06 loss: 0.0151 (0.0179) time: 2.8802 data: 0.0024 max mem: 19788 +Epoch: [37] [2010/2138] eta: 0:06:10 lr: 3.4632424671742937e-06 loss: 0.0168 (0.0179) time: 2.8792 data: 0.0023 max mem: 19788 +Epoch: [37] [2020/2138] eta: 0:05:41 lr: 3.4561625842092894e-06 loss: 0.0192 (0.0179) time: 2.9290 data: 0.0022 max mem: 19788 +Epoch: [37] [2030/2138] eta: 0:05:12 lr: 3.449081089431121e-06 loss: 0.0181 (0.0179) time: 2.9321 data: 0.0025 max mem: 19788 +Epoch: [37] [2040/2138] eta: 0:04:43 lr: 3.4419979787941445e-06 loss: 0.0171 (0.0179) time: 2.8849 data: 0.0026 max mem: 19788 +Epoch: [37] [2050/2138] eta: 0:04:14 lr: 3.4349132482333124e-06 loss: 0.0164 (0.0179) time: 2.8903 data: 0.0025 max mem: 19788 +Epoch: [37] [2060/2138] eta: 0:03:45 lr: 3.4278268936639816e-06 loss: 0.0174 (0.0179) time: 2.8943 data: 0.0025 max mem: 19788 +Epoch: [37] [2070/2138] eta: 0:03:16 lr: 3.4207389109818294e-06 loss: 0.0164 (0.0179) time: 2.8987 data: 0.0027 max mem: 19788 +Epoch: [37] [2080/2138] eta: 0:02:47 lr: 3.413649296062658e-06 loss: 0.0162 (0.0179) time: 2.9038 data: 0.0029 max mem: 19788 +Epoch: [37] [2090/2138] eta: 0:02:19 lr: 3.4065580447623055e-06 loss: 0.0185 (0.0179) time: 2.8919 data: 0.0031 max mem: 19788 +Epoch: [37] [2100/2138] eta: 0:01:50 lr: 3.3994651529164494e-06 loss: 0.0166 (0.0179) time: 2.9008 data: 0.0031 max mem: 19788 +Epoch: [37] [2110/2138] eta: 0:01:21 lr: 3.3923706163405158e-06 loss: 0.0180 (0.0179) time: 2.9845 data: 0.0026 max mem: 19788 +Epoch: [37] [2120/2138] eta: 0:00:52 lr: 3.385274430829487e-06 loss: 0.0192 (0.0179) time: 2.9667 data: 0.0023 max mem: 19788 +Epoch: [37] [2130/2138] eta: 0:00:23 lr: 3.378176592157771e-06 loss: 0.0187 (0.0179) time: 2.8737 data: 0.0022 max mem: 19788 +Epoch: [37] Total time: 1:43:13 +Test: [ 0/21770] eta: 18:01:06 time: 2.9796 data: 2.9138 max mem: 19788 +Test: [ 100/21770] eta: 0:27:40 time: 0.0518 data: 0.0017 max mem: 19788 +Test: [ 200/21770] eta: 0:22:33 time: 0.0482 data: 0.0016 max mem: 19788 +Test: [ 300/21770] eta: 0:20:16 time: 0.0435 data: 0.0014 max mem: 19788 +Test: [ 400/21770] eta: 0:18:59 time: 0.0427 data: 0.0015 max mem: 19788 +Test: [ 500/21770] eta: 0:18:27 time: 0.0498 data: 0.0018 max mem: 19788 +Test: [ 600/21770] eta: 0:17:55 time: 0.0433 data: 0.0016 max mem: 19788 +Test: [ 700/21770] eta: 0:17:45 time: 0.0516 data: 0.0017 max mem: 19788 +Test: [ 800/21770] eta: 0:17:39 time: 0.0518 data: 0.0016 max mem: 19788 +Test: [ 900/21770] eta: 0:17:26 time: 0.0434 data: 0.0017 max mem: 19788 +Test: [ 1000/21770] eta: 0:17:12 time: 0.0435 data: 0.0015 max mem: 19788 +Test: [ 1100/21770] eta: 0:16:57 time: 0.0445 data: 0.0016 max mem: 19788 +Test: [ 1200/21770] eta: 0:16:48 time: 0.0518 data: 0.0018 max mem: 19788 +Test: [ 1300/21770] eta: 0:16:48 time: 0.0523 data: 0.0018 max mem: 19788 +Test: [ 1400/21770] eta: 0:16:38 time: 0.0426 data: 0.0014 max mem: 19788 +Test: [ 1500/21770] eta: 0:16:26 time: 0.0436 data: 0.0014 max mem: 19788 +Test: [ 1600/21770] eta: 0:16:18 time: 0.0475 data: 0.0017 max mem: 19788 +Test: [ 1700/21770] eta: 0:16:11 time: 0.0439 data: 0.0017 max mem: 19788 +Test: [ 1800/21770] eta: 0:16:01 time: 0.0438 data: 0.0014 max mem: 19788 +Test: [ 1900/21770] eta: 0:15:59 time: 0.0528 data: 0.0017 max mem: 19788 +Test: [ 2000/21770] eta: 0:15:49 time: 0.0429 data: 0.0014 max mem: 19788 +Test: [ 2100/21770] eta: 0:15:42 time: 0.0438 data: 0.0015 max mem: 19788 +Test: [ 2200/21770] eta: 0:15:36 time: 0.0458 data: 0.0016 max mem: 19788 +Test: [ 2300/21770] eta: 0:15:29 time: 0.0527 data: 0.0017 max mem: 19788 +Test: [ 2400/21770] eta: 0:15:24 time: 0.0434 data: 0.0013 max mem: 19788 +Test: [ 2500/21770] eta: 0:15:17 time: 0.0452 data: 0.0014 max mem: 19788 +Test: [ 2600/21770] eta: 0:15:16 time: 0.0549 data: 0.0014 max mem: 19788 +Test: [ 2700/21770] eta: 0:15:12 time: 0.0520 data: 0.0018 max mem: 19788 +Test: [ 2800/21770] eta: 0:15:06 time: 0.0439 data: 0.0015 max mem: 19788 +Test: [ 2900/21770] eta: 0:14:59 time: 0.0424 data: 0.0014 max mem: 19788 +Test: [ 3000/21770] eta: 0:14:52 time: 0.0449 data: 0.0014 max mem: 19788 +Test: [ 3100/21770] eta: 0:14:45 time: 0.0437 data: 0.0015 max mem: 19788 +Test: [ 3200/21770] eta: 0:14:39 time: 0.0452 data: 0.0015 max mem: 19788 +Test: [ 3300/21770] eta: 0:14:35 time: 0.0451 data: 0.0015 max mem: 19788 +Test: [ 3400/21770] eta: 0:14:30 time: 0.0429 data: 0.0014 max mem: 19788 +Test: [ 3500/21770] eta: 0:14:25 time: 0.0443 data: 0.0014 max mem: 19788 +Test: [ 3600/21770] eta: 0:14:19 time: 0.0463 data: 0.0016 max mem: 19788 +Test: [ 3700/21770] eta: 0:14:13 time: 0.0437 data: 0.0015 max mem: 19788 +Test: [ 3800/21770] eta: 0:14:08 time: 0.0479 data: 0.0017 max mem: 19788 +Test: [ 3900/21770] eta: 0:14:05 time: 0.0526 data: 0.0018 max mem: 19788 +Test: [ 4000/21770] eta: 0:14:01 time: 0.0484 data: 0.0016 max mem: 19788 +Test: [ 4100/21770] eta: 0:13:56 time: 0.0523 data: 0.0017 max mem: 19788 +Test: [ 4200/21770] eta: 0:13:51 time: 0.0438 data: 0.0016 max mem: 19788 +Test: [ 4300/21770] eta: 0:13:47 time: 0.0520 data: 0.0018 max mem: 19788 +Test: [ 4400/21770] eta: 0:13:43 time: 0.0444 data: 0.0015 max mem: 19788 +Test: [ 4500/21770] eta: 0:13:38 time: 0.0510 data: 0.0017 max mem: 19788 +Test: [ 4600/21770] eta: 0:13:32 time: 0.0423 data: 0.0014 max mem: 19788 +Test: [ 4700/21770] eta: 0:13:26 time: 0.0443 data: 0.0013 max mem: 19788 +Test: [ 4800/21770] eta: 0:13:21 time: 0.0448 data: 0.0015 max mem: 19788 +Test: [ 4900/21770] eta: 0:13:16 time: 0.0487 data: 0.0015 max mem: 19788 +Test: [ 5000/21770] eta: 0:13:13 time: 0.0441 data: 0.0014 max mem: 19788 +Test: [ 5100/21770] eta: 0:13:08 time: 0.0443 data: 0.0014 max mem: 19788 +Test: [ 5200/21770] eta: 0:13:03 time: 0.0436 data: 0.0014 max mem: 19788 +Test: [ 5300/21770] eta: 0:12:58 time: 0.0485 data: 0.0016 max mem: 19788 +Test: [ 5400/21770] eta: 0:12:53 time: 0.0499 data: 0.0018 max mem: 19788 +Test: [ 5500/21770] eta: 0:12:49 time: 0.0513 data: 0.0018 max mem: 19788 +Test: [ 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time: 0.0435 data: 0.0015 max mem: 19788 +Test: [ 7000/21770] eta: 0:11:38 time: 0.0436 data: 0.0014 max mem: 19788 +Test: [ 7100/21770] eta: 0:11:33 time: 0.0424 data: 0.0013 max mem: 19788 +Test: [ 7200/21770] eta: 0:11:28 time: 0.0437 data: 0.0016 max mem: 19788 +Test: [ 7300/21770] eta: 0:11:23 time: 0.0431 data: 0.0015 max mem: 19788 +Test: [ 7400/21770] eta: 0:11:17 time: 0.0462 data: 0.0014 max mem: 19788 +Test: [ 7500/21770] eta: 0:11:12 time: 0.0436 data: 0.0014 max mem: 19788 +Test: [ 7600/21770] eta: 0:11:07 time: 0.0432 data: 0.0015 max mem: 19788 +Test: [ 7700/21770] eta: 0:11:02 time: 0.0472 data: 0.0016 max mem: 19788 +Test: [ 7800/21770] eta: 0:10:57 time: 0.0515 data: 0.0018 max mem: 19788 +Test: [ 7900/21770] eta: 0:10:53 time: 0.0453 data: 0.0015 max mem: 19788 +Test: [ 8000/21770] eta: 0:10:48 time: 0.0529 data: 0.0018 max mem: 19788 +Test: [ 8100/21770] eta: 0:10:43 time: 0.0437 data: 0.0014 max mem: 19788 +Test: [ 8200/21770] eta: 0:10:38 time: 0.0438 data: 0.0014 max mem: 19788 +Test: [ 8300/21770] eta: 0:10:33 time: 0.0450 data: 0.0015 max mem: 19788 +Test: [ 8400/21770] eta: 0:10:28 time: 0.0430 data: 0.0014 max mem: 19788 +Test: [ 8500/21770] eta: 0:10:23 time: 0.0452 data: 0.0015 max mem: 19788 +Test: [ 8600/21770] eta: 0:10:18 time: 0.0487 data: 0.0016 max mem: 19788 +Test: [ 8700/21770] eta: 0:10:14 time: 0.0511 data: 0.0017 max mem: 19788 +Test: [ 8800/21770] eta: 0:10:09 time: 0.0468 data: 0.0016 max mem: 19788 +Test: [ 8900/21770] eta: 0:10:04 time: 0.0451 data: 0.0014 max mem: 19788 +Test: [ 9000/21770] eta: 0:09:59 time: 0.0472 data: 0.0015 max mem: 19788 +Test: [ 9100/21770] eta: 0:09:55 time: 0.0488 data: 0.0016 max mem: 19788 +Test: [ 9200/21770] eta: 0:09:50 time: 0.0467 data: 0.0016 max mem: 19788 +Test: [ 9300/21770] eta: 0:09:46 time: 0.0432 data: 0.0014 max mem: 19788 +Test: [ 9400/21770] eta: 0:09:41 time: 0.0446 data: 0.0013 max mem: 19788 +Test: [ 9500/21770] eta: 0:09:35 time: 0.0435 data: 0.0015 max mem: 19788 +Test: [ 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time: 0.0478 data: 0.0017 max mem: 19788 +Test: [11000/21770] eta: 0:08:26 time: 0.0549 data: 0.0017 max mem: 19788 +Test: [11100/21770] eta: 0:08:21 time: 0.0523 data: 0.0017 max mem: 19788 +Test: [11200/21770] eta: 0:08:17 time: 0.0493 data: 0.0015 max mem: 19788 +Test: [11300/21770] eta: 0:08:12 time: 0.0443 data: 0.0015 max mem: 19788 +Test: [11400/21770] eta: 0:08:07 time: 0.0477 data: 0.0015 max mem: 19788 +Test: [11500/21770] eta: 0:08:02 time: 0.0441 data: 0.0015 max mem: 19788 +Test: [11600/21770] eta: 0:07:57 time: 0.0455 data: 0.0014 max mem: 19788 +Test: [11700/21770] eta: 0:07:53 time: 0.0431 data: 0.0014 max mem: 19788 +Test: [11800/21770] eta: 0:07:48 time: 0.0446 data: 0.0015 max mem: 19788 +Test: [11900/21770] eta: 0:07:43 time: 0.0429 data: 0.0014 max mem: 19788 +Test: [12000/21770] eta: 0:07:38 time: 0.0500 data: 0.0017 max mem: 19788 +Test: [12100/21770] eta: 0:07:34 time: 0.0456 data: 0.0017 max mem: 19788 +Test: [12200/21770] eta: 0:07:29 time: 0.0520 data: 0.0017 max mem: 19788 +Test: [12300/21770] eta: 0:07:24 time: 0.0436 data: 0.0014 max mem: 19788 +Test: [12400/21770] eta: 0:07:19 time: 0.0437 data: 0.0014 max mem: 19788 +Test: [12500/21770] eta: 0:07:15 time: 0.0464 data: 0.0015 max mem: 19788 +Test: [12600/21770] eta: 0:07:10 time: 0.0447 data: 0.0015 max mem: 19788 +Test: [12700/21770] eta: 0:07:05 time: 0.0463 data: 0.0016 max mem: 19788 +Test: [12800/21770] eta: 0:07:01 time: 0.0435 data: 0.0016 max mem: 19788 +Test: [12900/21770] eta: 0:06:56 time: 0.0441 data: 0.0014 max mem: 19788 +Test: [13000/21770] eta: 0:06:51 time: 0.0469 data: 0.0016 max mem: 19788 +Test: [13100/21770] eta: 0:06:47 time: 0.0512 data: 0.0018 max mem: 19788 +Test: [13200/21770] eta: 0:06:42 time: 0.0476 data: 0.0016 max mem: 19788 +Test: [13300/21770] eta: 0:06:37 time: 0.0519 data: 0.0017 max mem: 19788 +Test: [13400/21770] eta: 0:06:33 time: 0.0448 data: 0.0016 max mem: 19788 +Test: [13500/21770] eta: 0:06:28 time: 0.0447 data: 0.0015 max mem: 19788 +Test: [13600/21770] eta: 0:06:23 time: 0.0440 data: 0.0013 max mem: 19788 +Test: [13700/21770] eta: 0:06:18 time: 0.0454 data: 0.0015 max mem: 19788 +Test: [13800/21770] eta: 0:06:13 time: 0.0469 data: 0.0017 max mem: 19788 +Test: [13900/21770] eta: 0:06:08 time: 0.0438 data: 0.0015 max mem: 19788 +Test: [14000/21770] eta: 0:06:04 time: 0.0479 data: 0.0016 max mem: 19788 +Test: [14100/21770] eta: 0:05:59 time: 0.0493 data: 0.0017 max mem: 19788 +Test: [14200/21770] eta: 0:05:54 time: 0.0442 data: 0.0015 max mem: 19788 +Test: [14300/21770] eta: 0:05:50 time: 0.0535 data: 0.0018 max mem: 19788 +Test: [14400/21770] eta: 0:05:45 time: 0.0464 data: 0.0016 max mem: 19788 +Test: [14500/21770] eta: 0:05:40 time: 0.0506 data: 0.0017 max mem: 19788 +Test: [14600/21770] eta: 0:05:36 time: 0.0486 data: 0.0015 max mem: 19788 +Test: [14700/21770] eta: 0:05:31 time: 0.0523 data: 0.0015 max mem: 19788 +Test: [14800/21770] eta: 0:05:26 time: 0.0522 data: 0.0018 max mem: 19788 +Test: [14900/21770] eta: 0:05:22 time: 0.0496 data: 0.0018 max mem: 19788 +Test: [15000/21770] eta: 0:05:17 time: 0.0448 data: 0.0013 max mem: 19788 +Test: [15100/21770] eta: 0:05:12 time: 0.0526 data: 0.0018 max mem: 19788 +Test: [15200/21770] eta: 0:05:08 time: 0.0520 data: 0.0017 max mem: 19788 +Test: [15300/21770] eta: 0:05:03 time: 0.0506 data: 0.0017 max mem: 19788 +Test: [15400/21770] eta: 0:04:59 time: 0.0518 data: 0.0016 max mem: 19788 +Test: [15500/21770] eta: 0:04:54 time: 0.0490 data: 0.0016 max mem: 19788 +Test: [15600/21770] eta: 0:04:49 time: 0.0520 data: 0.0018 max mem: 19788 +Test: [15700/21770] eta: 0:04:45 time: 0.0462 data: 0.0017 max mem: 19788 +Test: [15800/21770] eta: 0:04:40 time: 0.0440 data: 0.0015 max mem: 19788 +Test: [15900/21770] eta: 0:04:35 time: 0.0499 data: 0.0017 max mem: 19788 +Test: [16000/21770] eta: 0:04:31 time: 0.0519 data: 0.0017 max mem: 19788 +Test: [16100/21770] eta: 0:04:26 time: 0.0470 data: 0.0015 max mem: 19788 +Test: [16200/21770] eta: 0:04:21 time: 0.0435 data: 0.0015 max mem: 19788 +Test: [16300/21770] eta: 0:04:17 time: 0.0441 data: 0.0013 max mem: 19788 +Test: [16400/21770] eta: 0:04:12 time: 0.0498 data: 0.0016 max mem: 19788 +Test: [16500/21770] eta: 0:04:07 time: 0.0520 data: 0.0018 max mem: 19788 +Test: [16600/21770] eta: 0:04:03 time: 0.0514 data: 0.0017 max mem: 19788 +Test: [16700/21770] eta: 0:03:58 time: 0.0516 data: 0.0016 max mem: 19788 +Test: [16800/21770] eta: 0:03:53 time: 0.0433 data: 0.0013 max mem: 19788 +Test: [16900/21770] eta: 0:03:48 time: 0.0466 data: 0.0015 max mem: 19788 +Test: [17000/21770] eta: 0:03:44 time: 0.0436 data: 0.0016 max mem: 19788 +Test: [17100/21770] eta: 0:03:39 time: 0.0441 data: 0.0013 max mem: 19788 +Test: [17200/21770] eta: 0:03:34 time: 0.0527 data: 0.0018 max mem: 19788 +Test: [17300/21770] eta: 0:03:30 time: 0.0436 data: 0.0015 max mem: 19788 +Test: [17400/21770] eta: 0:03:25 time: 0.0432 data: 0.0014 max mem: 19788 +Test: [17500/21770] eta: 0:03:20 time: 0.0433 data: 0.0015 max mem: 19788 +Test: [17600/21770] eta: 0:03:15 time: 0.0442 data: 0.0016 max mem: 19788 +Test: [17700/21770] eta: 0:03:11 time: 0.0436 data: 0.0015 max mem: 19788 +Test: [17800/21770] eta: 0:03:06 time: 0.0472 data: 0.0015 max mem: 19788 +Test: [17900/21770] eta: 0:03:01 time: 0.0436 data: 0.0014 max mem: 19788 +Test: [18000/21770] eta: 0:02:56 time: 0.0432 data: 0.0016 max mem: 19788 +Test: [18100/21770] eta: 0:02:52 time: 0.0529 data: 0.0017 max mem: 19788 +Test: [18200/21770] eta: 0:02:47 time: 0.0461 data: 0.0016 max mem: 19788 +Test: [18300/21770] eta: 0:02:42 time: 0.0451 data: 0.0014 max mem: 19788 +Test: [18400/21770] eta: 0:02:38 time: 0.0542 data: 0.0017 max mem: 19788 +Test: [18500/21770] eta: 0:02:33 time: 0.0465 data: 0.0017 max mem: 19788 +Test: [18600/21770] eta: 0:02:28 time: 0.0527 data: 0.0018 max mem: 19788 +Test: [18700/21770] eta: 0:02:24 time: 0.0528 data: 0.0018 max mem: 19788 +Test: [18800/21770] eta: 0:02:19 time: 0.0543 data: 0.0015 max mem: 19788 +Test: [18900/21770] eta: 0:02:14 time: 0.0432 data: 0.0014 max mem: 19788 +Test: [19000/21770] eta: 0:02:10 time: 0.0484 data: 0.0017 max mem: 19788 +Test: [19100/21770] eta: 0:02:05 time: 0.0432 data: 0.0013 max mem: 19788 +Test: [19200/21770] eta: 0:02:00 time: 0.0430 data: 0.0013 max mem: 19788 +Test: [19300/21770] eta: 0:01:55 time: 0.0429 data: 0.0016 max mem: 19788 +Test: [19400/21770] eta: 0:01:51 time: 0.0430 data: 0.0014 max mem: 19788 +Test: [19500/21770] eta: 0:01:46 time: 0.0516 data: 0.0017 max mem: 19788 +Test: [19600/21770] eta: 0:01:41 time: 0.0436 data: 0.0015 max mem: 19788 +Test: [19700/21770] eta: 0:01:37 time: 0.0472 data: 0.0016 max mem: 19788 +Test: [19800/21770] eta: 0:01:32 time: 0.0448 data: 0.0016 max mem: 19788 +Test: [19900/21770] eta: 0:01:27 time: 0.0442 data: 0.0013 max mem: 19788 +Test: [20000/21770] eta: 0:01:22 time: 0.0439 data: 0.0014 max mem: 19788 +Test: [20100/21770] eta: 0:01:18 time: 0.0447 data: 0.0014 max mem: 19788 +Test: [20200/21770] eta: 0:01:13 time: 0.0522 data: 0.0018 max mem: 19788 +Test: [20300/21770] eta: 0:01:08 time: 0.0441 data: 0.0017 max mem: 19788 +Test: [20400/21770] eta: 0:01:04 time: 0.0442 data: 0.0014 max mem: 19788 +Test: [20500/21770] eta: 0:00:59 time: 0.0453 data: 0.0016 max mem: 19788 +Test: [20600/21770] eta: 0:00:54 time: 0.0438 data: 0.0015 max mem: 19788 +Test: [20700/21770] eta: 0:00:50 time: 0.0438 data: 0.0014 max mem: 19788 +Test: [20800/21770] eta: 0:00:45 time: 0.0428 data: 0.0013 max mem: 19788 +Test: [20900/21770] eta: 0:00:40 time: 0.0461 data: 0.0015 max mem: 19788 +Test: [21000/21770] eta: 0:00:36 time: 0.0459 data: 0.0015 max mem: 19788 +Test: [21100/21770] eta: 0:00:31 time: 0.0449 data: 0.0014 max mem: 19788 +Test: [21200/21770] eta: 0:00:26 time: 0.0440 data: 0.0015 max mem: 19788 +Test: [21300/21770] eta: 0:00:22 time: 0.0440 data: 0.0017 max mem: 19788 +Test: [21400/21770] eta: 0:00:17 time: 0.0520 data: 0.0018 max mem: 19788 +Test: [21500/21770] eta: 0:00:12 time: 0.0449 data: 0.0015 max mem: 19788 +Test: [21600/21770] eta: 0:00:07 time: 0.0448 data: 0.0015 max mem: 19788 +Test: [21700/21770] eta: 0:00:03 time: 0.0563 data: 0.0023 max mem: 19788 +Test: Total time: 0:17:01 +Final results: +Mean IoU is 64.68 + + precision@0.5 = 72.17 + precision@0.6 = 66.78 + precision@0.7 = 60.33 + precision@0.8 = 49.34 + precision@0.9 = 24.01 + overall IoU = 65.21 + mean IoU = 64.68 + +Mean accuracy for one-to-zero sample is 86.51 + +Average object IoU 0.6468295405561548 +Overall IoU 65.20671081542969 +Epoch: [38] [ 0/2138] eta: 7:55:35 lr: 3.372497128091893e-06 loss: 0.0197 (0.0197) time: 13.3467 data: 1.2832 max mem: 19788 +Epoch: [38] [ 10/2138] eta: 2:16:22 lr: 3.3653963030162514e-06 loss: 0.0168 (0.0189) time: 3.8453 data: 0.1186 max mem: 19788 +Epoch: [38] [ 20/2138] eta: 1:59:44 lr: 3.358293812837573e-06 loss: 0.0158 (0.0174) time: 2.8942 data: 0.0020 max mem: 19788 +Epoch: [38] [ 30/2138] eta: 1:53:32 lr: 3.351189653250742e-06 loss: 0.0176 (0.0179) time: 2.8943 data: 0.0024 max mem: 19788 +Epoch: [38] [ 40/2138] eta: 1:50:06 lr: 3.3440838199293173e-06 loss: 0.0183 (0.0182) time: 2.8937 data: 0.0028 max mem: 19788 +Epoch: [38] [ 50/2138] eta: 1:47:55 lr: 3.336976308525428e-06 loss: 0.0171 (0.0183) time: 2.8989 data: 0.0025 max mem: 19788 +Epoch: [38] [ 60/2138] eta: 1:46:40 lr: 3.3298671146695647e-06 loss: 0.0182 (0.0185) time: 2.9393 data: 0.0023 max mem: 19788 +Epoch: [38] [ 70/2138] eta: 1:45:10 lr: 3.32275623397047e-06 loss: 0.0169 (0.0183) time: 2.9249 data: 0.0024 max mem: 19788 +Epoch: [38] [ 80/2138] eta: 1:43:52 lr: 3.315643662014928e-06 loss: 0.0165 (0.0183) time: 2.8713 data: 0.0024 max mem: 19788 +Epoch: [38] [ 90/2138] eta: 1:42:43 lr: 3.3085293943676545e-06 loss: 0.0160 (0.0181) time: 2.8610 data: 0.0025 max mem: 19788 +Epoch: [38] [ 100/2138] eta: 1:41:43 lr: 3.3014134265710803e-06 loss: 0.0160 (0.0181) time: 2.8586 data: 0.0023 max mem: 19788 +Epoch: [38] [ 110/2138] eta: 1:40:50 lr: 3.2942957541452374e-06 loss: 0.0162 (0.0180) time: 2.8654 data: 0.0021 max mem: 19788 +Epoch: [38] [ 120/2138] eta: 1:40:04 lr: 3.2871763725875413e-06 loss: 0.0159 (0.0178) time: 2.8762 data: 0.0025 max mem: 19788 +Epoch: [38] [ 130/2138] eta: 1:39:20 lr: 3.2800552773726763e-06 loss: 0.0176 (0.0179) time: 2.8832 data: 0.0028 max mem: 19788 +Epoch: [38] [ 140/2138] eta: 1:38:39 lr: 3.2729324639523667e-06 loss: 0.0177 (0.0179) time: 2.8858 data: 0.0025 max mem: 19788 +Epoch: [38] [ 150/2138] eta: 1:38:11 lr: 3.2658079277552648e-06 loss: 0.0154 (0.0178) time: 2.9334 data: 0.0023 max mem: 19788 +Epoch: [38] [ 160/2138] eta: 1:37:29 lr: 3.258681664186726e-06 loss: 0.0173 (0.0178) time: 2.9195 data: 0.0027 max mem: 19788 +Epoch: [38] [ 170/2138] eta: 1:36:50 lr: 3.251553668628656e-06 loss: 0.0171 (0.0178) time: 2.8689 data: 0.0031 max mem: 19788 +Epoch: [38] [ 180/2138] eta: 1:36:11 lr: 3.2444239364393524e-06 loss: 0.0171 (0.0177) time: 2.8705 data: 0.0027 max mem: 19788 +Epoch: [38] [ 190/2138] eta: 1:35:35 lr: 3.2372924629532787e-06 loss: 0.0167 (0.0177) time: 2.8719 data: 0.0022 max mem: 19788 +Epoch: [38] [ 200/2138] eta: 1:34:56 lr: 3.2301592434809395e-06 loss: 0.0168 (0.0176) time: 2.8636 data: 0.0022 max mem: 19788 +Epoch: [38] [ 210/2138] eta: 1:34:20 lr: 3.223024273308642e-06 loss: 0.0183 (0.0177) time: 2.8591 data: 0.0021 max mem: 19788 +Epoch: [38] [ 220/2138] eta: 1:33:44 lr: 3.2158875476983645e-06 loss: 0.0154 (0.0176) time: 2.8648 data: 0.0023 max mem: 19788 +Epoch: [38] [ 230/2138] eta: 1:33:14 lr: 3.2087490618875206e-06 loss: 0.0154 (0.0177) time: 2.8891 data: 0.0027 max mem: 19788 +Epoch: [38] [ 240/2138] eta: 1:32:41 lr: 3.201608811088821e-06 loss: 0.0169 (0.0176) time: 2.9012 data: 0.0027 max mem: 19788 +Epoch: [38] [ 250/2138] eta: 1:32:06 lr: 3.1944667904900307e-06 loss: 0.0169 (0.0176) time: 2.8718 data: 0.0024 max mem: 19788 +Epoch: [38] [ 260/2138] eta: 1:31:34 lr: 3.1873229952538325e-06 loss: 0.0171 (0.0176) time: 2.8778 data: 0.0024 max mem: 19788 +Epoch: [38] [ 270/2138] eta: 1:31:01 lr: 3.180177420517575e-06 loss: 0.0169 (0.0176) time: 2.8785 data: 0.0026 max mem: 19788 +Epoch: [38] [ 280/2138] eta: 1:30:28 lr: 3.173030061393138e-06 loss: 0.0174 (0.0176) time: 2.8675 data: 0.0026 max mem: 19788 +Epoch: [38] [ 290/2138] eta: 1:29:56 lr: 3.165880912966673e-06 loss: 0.0174 (0.0176) time: 2.8703 data: 0.0025 max mem: 19788 +Epoch: [38] [ 300/2138] eta: 1:29:23 lr: 3.1587299702984597e-06 loss: 0.0164 (0.0176) time: 2.8631 data: 0.0023 max mem: 19788 +Epoch: [38] [ 310/2138] eta: 1:28:53 lr: 3.151577228422654e-06 loss: 0.0158 (0.0176) time: 2.8807 data: 0.0024 max mem: 19788 +Epoch: [38] [ 320/2138] eta: 1:28:26 lr: 3.1444226823471326e-06 loss: 0.0147 (0.0175) time: 2.9352 data: 0.0025 max mem: 19788 +Epoch: [38] [ 330/2138] eta: 1:27:54 lr: 3.1372663270532343e-06 loss: 0.0158 (0.0175) time: 2.9138 data: 0.0023 max mem: 19788 +Epoch: [38] [ 340/2138] eta: 1:27:23 lr: 3.130108157495608e-06 loss: 0.0175 (0.0175) time: 2.8716 data: 0.0022 max mem: 19788 +Epoch: [38] [ 350/2138] eta: 1:26:50 lr: 3.122948168601944e-06 loss: 0.0171 (0.0175) time: 2.8643 data: 0.0021 max mem: 19788 +Epoch: [38] [ 360/2138] eta: 1:26:19 lr: 3.1157863552728205e-06 loss: 0.0178 (0.0176) time: 2.8642 data: 0.0022 max mem: 19788 +Epoch: [38] [ 370/2138] eta: 1:25:47 lr: 3.1086227123814304e-06 loss: 0.0188 (0.0176) time: 2.8683 data: 0.0024 max mem: 19788 +Epoch: [38] [ 380/2138] eta: 1:25:16 lr: 3.1014572347734185e-06 loss: 0.0166 (0.0176) time: 2.8623 data: 0.0025 max mem: 19788 +Epoch: [38] [ 390/2138] eta: 1:24:45 lr: 3.0942899172666103e-06 loss: 0.0149 (0.0175) time: 2.8650 data: 0.0026 max mem: 19788 +Epoch: [38] [ 400/2138] eta: 1:24:14 lr: 3.087120754650843e-06 loss: 0.0158 (0.0176) time: 2.8574 data: 0.0026 max mem: 19788 +Epoch: [38] [ 410/2138] eta: 1:23:46 lr: 3.079949741687687e-06 loss: 0.0164 (0.0175) time: 2.8996 data: 0.0022 max mem: 19788 +Epoch: [38] [ 420/2138] eta: 1:23:17 lr: 3.0727768731102726e-06 loss: 0.0153 (0.0175) time: 2.9218 data: 0.0022 max mem: 19788 +Epoch: [38] [ 430/2138] eta: 1:22:46 lr: 3.0656021436230103e-06 loss: 0.0164 (0.0175) time: 2.8816 data: 0.0025 max mem: 19788 +Epoch: [38] [ 440/2138] eta: 1:22:16 lr: 3.058425547901409e-06 loss: 0.0164 (0.0175) time: 2.8785 data: 0.0027 max mem: 19788 +Epoch: [38] [ 450/2138] eta: 1:21:45 lr: 3.0512470805917916e-06 loss: 0.0174 (0.0175) time: 2.8775 data: 0.0027 max mem: 19788 +Epoch: [38] [ 460/2138] eta: 1:21:14 lr: 3.0440667363111116e-06 loss: 0.0161 (0.0175) time: 2.8581 data: 0.0023 max mem: 19788 +Epoch: [38] [ 470/2138] eta: 1:20:44 lr: 3.036884509646666e-06 loss: 0.0163 (0.0175) time: 2.8608 data: 0.0021 max mem: 19788 +Epoch: [38] [ 480/2138] eta: 1:20:13 lr: 3.0297003951558746e-06 loss: 0.0174 (0.0175) time: 2.8636 data: 0.0022 max mem: 19788 +Epoch: [38] [ 490/2138] eta: 1:19:43 lr: 3.0225143873660576e-06 loss: 0.0166 (0.0175) time: 2.8624 data: 0.0023 max mem: 19788 +Epoch: [38] [ 500/2138] eta: 1:19:15 lr: 3.0153264807741386e-06 loss: 0.0145 (0.0175) time: 2.9010 data: 0.0029 max mem: 19788 +Epoch: [38] [ 510/2138] eta: 1:18:45 lr: 3.008136669846453e-06 loss: 0.0144 (0.0174) time: 2.9039 data: 0.0028 max mem: 19788 +Epoch: [38] [ 520/2138] eta: 1:18:15 lr: 3.0009449490184385e-06 loss: 0.0154 (0.0175) time: 2.8665 data: 0.0023 max mem: 19788 +Epoch: [38] [ 530/2138] eta: 1:17:45 lr: 2.9937513126944358e-06 loss: 0.0165 (0.0175) time: 2.8612 data: 0.0024 max mem: 19788 +Epoch: [38] [ 540/2138] eta: 1:17:14 lr: 2.986555755247377e-06 loss: 0.0156 (0.0175) time: 2.8584 data: 0.0022 max mem: 19788 +Epoch: [38] [ 550/2138] eta: 1:16:44 lr: 2.9793582710185785e-06 loss: 0.0164 (0.0174) time: 2.8619 data: 0.0023 max mem: 19788 +Epoch: [38] [ 560/2138] eta: 1:16:14 lr: 2.9721588543174245e-06 loss: 0.0182 (0.0175) time: 2.8678 data: 0.0024 max mem: 19788 +Epoch: [38] [ 570/2138] eta: 1:15:44 lr: 2.964957499421153e-06 loss: 0.0162 (0.0175) time: 2.8646 data: 0.0026 max mem: 19788 +Epoch: [38] [ 580/2138] eta: 1:15:15 lr: 2.9577542005745346e-06 loss: 0.0158 (0.0175) time: 2.8741 data: 0.0027 max mem: 19788 +Epoch: [38] [ 590/2138] eta: 1:14:48 lr: 2.9505489519896536e-06 loss: 0.0172 (0.0175) time: 2.9271 data: 0.0026 max mem: 19788 +Epoch: [38] [ 600/2138] eta: 1:14:19 lr: 2.943341747845578e-06 loss: 0.0156 (0.0175) time: 2.9271 data: 0.0028 max mem: 19788 +Epoch: [38] [ 610/2138] eta: 1:13:49 lr: 2.936132582288136e-06 loss: 0.0163 (0.0175) time: 2.8840 data: 0.0029 max mem: 19788 +Epoch: [38] [ 620/2138] eta: 1:13:19 lr: 2.92892144942958e-06 loss: 0.0174 (0.0175) time: 2.8699 data: 0.0025 max mem: 19788 +Epoch: [38] [ 630/2138] eta: 1:12:49 lr: 2.9217083433483573e-06 loss: 0.0170 (0.0176) time: 2.8538 data: 0.0024 max mem: 19788 +Epoch: [38] [ 640/2138] eta: 1:12:19 lr: 2.9144932580887666e-06 loss: 0.0169 (0.0176) time: 2.8469 data: 0.0024 max mem: 19788 +Epoch: [38] [ 650/2138] eta: 1:11:49 lr: 2.9072761876607215e-06 loss: 0.0171 (0.0176) time: 2.8505 data: 0.0022 max mem: 19788 +Epoch: [38] [ 660/2138] eta: 1:11:19 lr: 2.900057126039403e-06 loss: 0.0170 (0.0176) time: 2.8554 data: 0.0024 max mem: 19788 +Epoch: [38] [ 670/2138] eta: 1:10:50 lr: 2.892836067165015e-06 loss: 0.0170 (0.0176) time: 2.8790 data: 0.0026 max mem: 19788 +Epoch: [38] [ 680/2138] eta: 1:10:22 lr: 2.8856130049424297e-06 loss: 0.0164 (0.0176) time: 2.9144 data: 0.0029 max mem: 19788 +Epoch: [38] [ 690/2138] eta: 1:09:52 lr: 2.878387933240937e-06 loss: 0.0167 (0.0176) time: 2.8950 data: 0.0031 max mem: 19788 +Epoch: [38] [ 700/2138] eta: 1:09:23 lr: 2.871160845893881e-06 loss: 0.0167 (0.0176) time: 2.8718 data: 0.0028 max mem: 19788 +Epoch: [38] [ 710/2138] eta: 1:08:54 lr: 2.863931736698407e-06 loss: 0.0161 (0.0176) time: 2.8833 data: 0.0026 max mem: 19788 +Epoch: [38] [ 720/2138] eta: 1:08:24 lr: 2.856700599415087e-06 loss: 0.0151 (0.0175) time: 2.8748 data: 0.0023 max mem: 19788 +Epoch: [38] [ 730/2138] eta: 1:07:55 lr: 2.8494674277676576e-06 loss: 0.0151 (0.0175) time: 2.8612 data: 0.0024 max mem: 19788 +Epoch: [38] [ 740/2138] eta: 1:07:25 lr: 2.842232215442644e-06 loss: 0.0188 (0.0176) time: 2.8577 data: 0.0024 max mem: 19788 +Epoch: [38] [ 750/2138] eta: 1:06:56 lr: 2.8349949560890866e-06 loss: 0.0175 (0.0176) time: 2.8668 data: 0.0025 max mem: 19788 +Epoch: [38] [ 760/2138] eta: 1:06:27 lr: 2.8277556433181587e-06 loss: 0.0181 (0.0176) time: 2.8970 data: 0.0028 max mem: 19788 +Epoch: [38] [ 770/2138] eta: 1:05:58 lr: 2.820514270702885e-06 loss: 0.0168 (0.0176) time: 2.9017 data: 0.0027 max mem: 19788 +Epoch: [38] [ 780/2138] eta: 1:05:29 lr: 2.8132708317777575e-06 loss: 0.0158 (0.0176) time: 2.8725 data: 0.0023 max mem: 19788 +Epoch: [38] [ 790/2138] eta: 1:04:59 lr: 2.8060253200384136e-06 loss: 0.0155 (0.0176) time: 2.8599 data: 0.0023 max mem: 19788 +Epoch: [38] [ 800/2138] eta: 1:04:30 lr: 2.7987777289413123e-06 loss: 0.0162 (0.0176) time: 2.8582 data: 0.0025 max mem: 19788 +Epoch: [38] [ 810/2138] eta: 1:04:01 lr: 2.791528051903334e-06 loss: 0.0179 (0.0175) time: 2.8705 data: 0.0026 max mem: 19788 +Epoch: [38] [ 820/2138] eta: 1:03:31 lr: 2.7842762823014843e-06 loss: 0.0177 (0.0176) time: 2.8849 data: 0.0026 max mem: 19788 +Epoch: [38] [ 830/2138] eta: 1:03:02 lr: 2.7770224134724794e-06 loss: 0.0151 (0.0176) time: 2.8780 data: 0.0027 max mem: 19788 +Epoch: [38] [ 840/2138] eta: 1:02:33 lr: 2.769766438712439e-06 loss: 0.0153 (0.0176) time: 2.8758 data: 0.0026 max mem: 19788 +Epoch: [38] [ 850/2138] eta: 1:02:06 lr: 2.762508351276464e-06 loss: 0.0164 (0.0176) time: 2.9533 data: 0.0023 max mem: 19788 +Epoch: [38] [ 860/2138] eta: 1:01:37 lr: 2.755248144378323e-06 loss: 0.0166 (0.0176) time: 2.9469 data: 0.0022 max mem: 19788 +Epoch: [38] [ 870/2138] eta: 1:01:08 lr: 2.7479858111900175e-06 loss: 0.0165 (0.0176) time: 2.8649 data: 0.0022 max mem: 19788 +Epoch: [38] [ 880/2138] eta: 1:00:39 lr: 2.74072134484146e-06 loss: 0.0153 (0.0176) time: 2.8779 data: 0.0025 max mem: 19788 +Epoch: [38] [ 890/2138] eta: 1:00:09 lr: 2.7334547384200353e-06 loss: 0.0160 (0.0176) time: 2.8737 data: 0.0025 max mem: 19788 +Epoch: [38] [ 900/2138] eta: 0:59:40 lr: 2.7261859849702617e-06 loss: 0.0160 (0.0176) time: 2.8592 data: 0.0024 max mem: 19788 +Epoch: [38] [ 910/2138] eta: 0:59:11 lr: 2.7189150774933466e-06 loss: 0.0156 (0.0176) time: 2.8640 data: 0.0024 max mem: 19788 +Epoch: [38] [ 920/2138] eta: 0:58:41 lr: 2.71164200894684e-06 loss: 0.0161 (0.0175) time: 2.8647 data: 0.0024 max mem: 19788 +Epoch: [38] [ 930/2138] eta: 0:58:12 lr: 2.704366772244178e-06 loss: 0.0176 (0.0176) time: 2.8536 data: 0.0027 max mem: 19788 +Epoch: [38] [ 940/2138] eta: 0:57:44 lr: 2.6970893602543266e-06 loss: 0.0193 (0.0176) time: 2.9108 data: 0.0029 max mem: 19788 +Epoch: [38] [ 950/2138] eta: 0:57:15 lr: 2.6898097658013137e-06 loss: 0.0175 (0.0176) time: 2.9183 data: 0.0026 max mem: 19788 +Epoch: [38] [ 960/2138] eta: 0:56:45 lr: 2.682527981663867e-06 loss: 0.0183 (0.0176) time: 2.8614 data: 0.0023 max mem: 19788 +Epoch: [38] [ 970/2138] eta: 0:56:16 lr: 2.675244000574934e-06 loss: 0.0197 (0.0176) time: 2.8589 data: 0.0022 max mem: 19788 +Epoch: [38] [ 980/2138] eta: 0:55:47 lr: 2.6679578152213065e-06 loss: 0.0153 (0.0176) time: 2.8606 data: 0.0023 max mem: 19788 +Epoch: [38] [ 990/2138] eta: 0:55:18 lr: 2.660669418243133e-06 loss: 0.0148 (0.0176) time: 2.8648 data: 0.0025 max mem: 19788 +Epoch: [38] [1000/2138] eta: 0:54:48 lr: 2.653378802233533e-06 loss: 0.0150 (0.0176) time: 2.8601 data: 0.0026 max mem: 19788 +Epoch: [38] [1010/2138] eta: 0:54:19 lr: 2.646085959738096e-06 loss: 0.0158 (0.0176) time: 2.8557 data: 0.0026 max mem: 19788 +Epoch: [38] [1020/2138] eta: 0:53:50 lr: 2.6387908832544865e-06 loss: 0.0154 (0.0176) time: 2.8543 data: 0.0027 max mem: 19788 +Epoch: [38] [1030/2138] eta: 0:53:21 lr: 2.6314935652319307e-06 loss: 0.0154 (0.0176) time: 2.9026 data: 0.0028 max mem: 19788 +Epoch: [38] [1040/2138] eta: 0:52:52 lr: 2.624193998070811e-06 loss: 0.0172 (0.0176) time: 2.9144 data: 0.0026 max mem: 19788 +Epoch: [38] [1050/2138] eta: 0:52:24 lr: 2.61689217412214e-06 loss: 0.0180 (0.0176) time: 2.8857 data: 0.0025 max mem: 19788 +Epoch: [38] [1060/2138] eta: 0:51:54 lr: 2.609588085687144e-06 loss: 0.0176 (0.0176) time: 2.8791 data: 0.0026 max mem: 19788 +Epoch: [38] [1070/2138] eta: 0:51:25 lr: 2.602281725016732e-06 loss: 0.0176 (0.0176) time: 2.8631 data: 0.0026 max mem: 19788 +Epoch: [38] [1080/2138] eta: 0:50:56 lr: 2.594973084311031e-06 loss: 0.0168 (0.0176) time: 2.8644 data: 0.0026 max mem: 19788 +Epoch: [38] [1090/2138] eta: 0:50:27 lr: 2.5876621557189144e-06 loss: 0.0169 (0.0176) time: 2.8696 data: 0.0027 max mem: 19788 +Epoch: [38] [1100/2138] eta: 0:49:58 lr: 2.5803489313374527e-06 loss: 0.0187 (0.0176) time: 2.8665 data: 0.0027 max mem: 19788 +Epoch: [38] [1110/2138] eta: 0:49:29 lr: 2.5730334032114655e-06 loss: 0.0176 (0.0176) time: 2.8713 data: 0.0027 max mem: 19788 +Epoch: [38] [1120/2138] eta: 0:49:01 lr: 2.5657155633329522e-06 loss: 0.0167 (0.0176) time: 2.9576 data: 0.0028 max mem: 19788 +Epoch: [38] [1130/2138] eta: 0:48:32 lr: 2.558395403640629e-06 loss: 0.0152 (0.0176) time: 2.9505 data: 0.0026 max mem: 19788 +Epoch: [38] [1140/2138] eta: 0:48:03 lr: 2.551072916019349e-06 loss: 0.0168 (0.0176) time: 2.8627 data: 0.0024 max mem: 19788 +Epoch: [38] [1150/2138] eta: 0:47:34 lr: 2.543748092299623e-06 loss: 0.0147 (0.0176) time: 2.8726 data: 0.0025 max mem: 19788 +Epoch: [38] [1160/2138] eta: 0:47:05 lr: 2.5364209242570267e-06 loss: 0.0144 (0.0176) time: 2.8847 data: 0.0028 max mem: 19788 +Epoch: [38] [1170/2138] eta: 0:46:36 lr: 2.5290914036117097e-06 loss: 0.0159 (0.0176) time: 2.8715 data: 0.0028 max mem: 19788 +Epoch: [38] [1180/2138] eta: 0:46:07 lr: 2.521759522027784e-06 loss: 0.0164 (0.0176) time: 2.8698 data: 0.0026 max mem: 19788 +Epoch: [38] [1190/2138] eta: 0:45:38 lr: 2.5144252711128213e-06 loss: 0.0164 (0.0176) time: 2.8752 data: 0.0025 max mem: 19788 +Epoch: [38] [1200/2138] eta: 0:45:10 lr: 2.5070886424172258e-06 loss: 0.0161 (0.0176) time: 2.9279 data: 0.0024 max mem: 19788 +Epoch: [38] [1210/2138] eta: 0:44:42 lr: 2.499749627433717e-06 loss: 0.0166 (0.0176) time: 2.9827 data: 0.0025 max mem: 19788 +Epoch: [38] [1220/2138] eta: 0:44:15 lr: 2.4924082175966874e-06 loss: 0.0162 (0.0176) time: 3.0505 data: 0.0027 max mem: 19788 +Epoch: [38] [1230/2138] eta: 0:43:46 lr: 2.485064404281669e-06 loss: 0.0153 (0.0176) time: 3.0570 data: 0.0029 max mem: 19788 +Epoch: [38] [1240/2138] eta: 0:43:18 lr: 2.4777181788046755e-06 loss: 0.0158 (0.0175) time: 2.9522 data: 0.0027 max mem: 19788 +Epoch: [38] [1250/2138] eta: 0:42:48 lr: 2.4703695324216514e-06 loss: 0.0159 (0.0175) time: 2.8679 data: 0.0025 max mem: 19788 +Epoch: [38] [1260/2138] eta: 0:42:19 lr: 2.4630184563278013e-06 loss: 0.0159 (0.0175) time: 2.8213 data: 0.0023 max mem: 19788 +Epoch: [38] [1270/2138] eta: 0:41:49 lr: 2.4556649416570204e-06 loss: 0.0159 (0.0175) time: 2.8133 data: 0.0022 max mem: 19788 +Epoch: [38] [1280/2138] eta: 0:41:20 lr: 2.448308979481204e-06 loss: 0.0169 (0.0175) time: 2.8165 data: 0.0021 max mem: 19788 +Epoch: [38] [1290/2138] eta: 0:40:51 lr: 2.440950560809666e-06 loss: 0.0182 (0.0175) time: 2.8213 data: 0.0024 max mem: 19788 +Epoch: [38] [1300/2138] eta: 0:40:21 lr: 2.433589676588428e-06 loss: 0.0182 (0.0175) time: 2.8293 data: 0.0027 max mem: 19788 +Epoch: [38] [1310/2138] eta: 0:39:52 lr: 2.4262263176996194e-06 loss: 0.0172 (0.0175) time: 2.8346 data: 0.0025 max mem: 19788 +Epoch: [38] [1320/2138] eta: 0:39:24 lr: 2.4188604749607524e-06 loss: 0.0173 (0.0175) time: 2.9313 data: 0.0024 max mem: 19788 +Epoch: [38] [1330/2138] eta: 0:38:56 lr: 2.411492139124098e-06 loss: 0.0163 (0.0175) time: 3.0086 data: 0.0027 max mem: 19788 +Epoch: [38] [1340/2138] eta: 0:38:27 lr: 2.4041213008759453e-06 loss: 0.0169 (0.0175) time: 2.9398 data: 0.0026 max mem: 19788 +Epoch: [38] [1350/2138] eta: 0:37:57 lr: 2.39674795083596e-06 loss: 0.0184 (0.0176) time: 2.8577 data: 0.0025 max mem: 19788 +Epoch: [38] [1360/2138] eta: 0:37:28 lr: 2.3893720795564214e-06 loss: 0.0173 (0.0175) time: 2.8225 data: 0.0027 max mem: 19788 +Epoch: [38] [1370/2138] eta: 0:36:59 lr: 2.3819936775215627e-06 loss: 0.0167 (0.0176) time: 2.8232 data: 0.0026 max mem: 19788 +Epoch: [38] [1380/2138] eta: 0:36:30 lr: 2.3746127351467957e-06 loss: 0.0167 (0.0176) time: 2.8264 data: 0.0028 max mem: 19788 +Epoch: [38] [1390/2138] eta: 0:36:00 lr: 2.3672292427779925e-06 loss: 0.0167 (0.0176) time: 2.8298 data: 0.0028 max mem: 19788 +Epoch: [38] [1400/2138] eta: 0:35:31 lr: 2.359843190690763e-06 loss: 0.0158 (0.0175) time: 2.8273 data: 0.0027 max mem: 19788 +Epoch: [38] [1410/2138] eta: 0:35:02 lr: 2.3524545690896446e-06 loss: 0.0158 (0.0175) time: 2.8379 data: 0.0027 max mem: 19788 +Epoch: [38] [1420/2138] eta: 0:34:34 lr: 2.3450633681073914e-06 loss: 0.0166 (0.0175) time: 2.9136 data: 0.0025 max mem: 19788 +Epoch: [38] [1430/2138] eta: 0:34:05 lr: 2.3376695778041364e-06 loss: 0.0167 (0.0175) time: 2.9755 data: 0.0023 max mem: 19788 +Epoch: [38] [1440/2138] eta: 0:33:36 lr: 2.3302731881666593e-06 loss: 0.0181 (0.0175) time: 2.9296 data: 0.0023 max mem: 19788 +Epoch: [38] [1450/2138] eta: 0:33:07 lr: 2.322874189107524e-06 loss: 0.0189 (0.0176) time: 2.8554 data: 0.0023 max mem: 19788 +Epoch: [38] [1460/2138] eta: 0:32:38 lr: 2.3154725704643247e-06 loss: 0.0175 (0.0176) time: 2.8191 data: 0.0025 max mem: 19788 +Epoch: [38] [1470/2138] eta: 0:32:09 lr: 2.3080683219988006e-06 loss: 0.0154 (0.0176) time: 2.8264 data: 0.0028 max mem: 19788 +Epoch: [38] [1480/2138] eta: 0:31:40 lr: 2.3006614333960544e-06 loss: 0.0143 (0.0176) time: 2.8326 data: 0.0028 max mem: 19788 +Epoch: [38] [1490/2138] eta: 0:31:11 lr: 2.293251894263647e-06 loss: 0.0165 (0.0176) time: 2.8308 data: 0.0028 max mem: 19788 +Epoch: [38] [1500/2138] eta: 0:30:41 lr: 2.285839694130789e-06 loss: 0.0181 (0.0176) time: 2.8296 data: 0.0027 max mem: 19788 +Epoch: [38] [1510/2138] eta: 0:30:12 lr: 2.2784248224474105e-06 loss: 0.0175 (0.0176) time: 2.8255 data: 0.0025 max mem: 19788 +Epoch: [38] [1520/2138] eta: 0:29:44 lr: 2.2710072685833262e-06 loss: 0.0172 (0.0176) time: 2.9489 data: 0.0026 max mem: 19788 +Epoch: [38] [1530/2138] eta: 0:29:16 lr: 2.2635870218272815e-06 loss: 0.0182 (0.0176) time: 3.0369 data: 0.0029 max mem: 19788 +Epoch: [38] [1540/2138] eta: 0:28:47 lr: 2.2561640713860873e-06 loss: 0.0168 (0.0176) time: 2.9615 data: 0.0027 max mem: 19788 +Epoch: [38] [1550/2138] eta: 0:28:18 lr: 2.2487384063836402e-06 loss: 0.0167 (0.0176) time: 2.8686 data: 0.0024 max mem: 19788 +Epoch: [38] [1560/2138] eta: 0:27:49 lr: 2.2413100158600316e-06 loss: 0.0181 (0.0176) time: 2.8174 data: 0.0022 max mem: 19788 +Epoch: [38] [1570/2138] eta: 0:27:20 lr: 2.233878888770537e-06 loss: 0.0182 (0.0176) time: 2.8198 data: 0.0023 max mem: 19788 +Epoch: [38] [1580/2138] eta: 0:26:50 lr: 2.2264450139846988e-06 loss: 0.0174 (0.0176) time: 2.8252 data: 0.0024 max mem: 19788 +Epoch: [38] [1590/2138] eta: 0:26:21 lr: 2.219008380285283e-06 loss: 0.0174 (0.0176) time: 2.8208 data: 0.0024 max mem: 19788 +Epoch: [38] [1600/2138] eta: 0:25:52 lr: 2.2115689763673347e-06 loss: 0.0189 (0.0176) time: 2.8251 data: 0.0024 max mem: 19788 +Epoch: [38] [1610/2138] eta: 0:25:23 lr: 2.204126790837105e-06 loss: 0.0190 (0.0176) time: 2.8314 data: 0.0024 max mem: 19788 +Epoch: [38] [1620/2138] eta: 0:24:55 lr: 2.1966818122110723e-06 loss: 0.0158 (0.0176) time: 2.9772 data: 0.0024 max mem: 19788 +Epoch: [38] [1630/2138] eta: 0:24:27 lr: 2.1892340289148412e-06 loss: 0.0158 (0.0176) time: 3.1020 data: 0.0025 max mem: 19788 +Epoch: [38] [1640/2138] eta: 0:23:58 lr: 2.1817834292821292e-06 loss: 0.0168 (0.0176) time: 2.9921 data: 0.0027 max mem: 19788 +Epoch: [38] [1650/2138] eta: 0:23:29 lr: 2.174330001553633e-06 loss: 0.0173 (0.0176) time: 2.8621 data: 0.0024 max mem: 19788 +Epoch: [38] [1660/2138] eta: 0:23:00 lr: 2.1668737338759835e-06 loss: 0.0181 (0.0176) time: 2.8189 data: 0.0021 max mem: 19788 +Epoch: [38] [1670/2138] eta: 0:22:31 lr: 2.159414614300575e-06 loss: 0.0172 (0.0176) time: 2.8230 data: 0.0021 max mem: 19788 +Epoch: [38] [1680/2138] eta: 0:22:02 lr: 2.151952630782488e-06 loss: 0.0158 (0.0176) time: 2.8194 data: 0.0022 max mem: 19788 +Epoch: [38] [1690/2138] eta: 0:21:33 lr: 2.1444877711792904e-06 loss: 0.0156 (0.0176) time: 2.8194 data: 0.0022 max mem: 19788 +Epoch: [38] [1700/2138] eta: 0:21:04 lr: 2.1370200232498852e-06 loss: 0.0164 (0.0176) time: 2.8203 data: 0.0023 max mem: 19788 +Epoch: [38] [1710/2138] eta: 0:20:35 lr: 2.1295493746533486e-06 loss: 0.0164 (0.0176) time: 2.8220 data: 0.0025 max mem: 19788 +Epoch: [38] [1720/2138] eta: 0:20:06 lr: 2.12207581294767e-06 loss: 0.0178 (0.0176) time: 2.9184 data: 0.0024 max mem: 19788 +Epoch: [38] [1730/2138] eta: 0:19:37 lr: 2.1145993255885833e-06 loss: 0.0177 (0.0176) time: 2.9994 data: 0.0023 max mem: 19788 +Epoch: [38] [1740/2138] eta: 0:19:09 lr: 2.107119899928264e-06 loss: 0.0166 (0.0176) time: 2.9500 data: 0.0023 max mem: 19788 +Epoch: [38] [1750/2138] eta: 0:18:40 lr: 2.0996375232141207e-06 loss: 0.0171 (0.0176) time: 2.8675 data: 0.0024 max mem: 19788 +Epoch: [38] [1760/2138] eta: 0:18:11 lr: 2.0921521825874496e-06 loss: 0.0165 (0.0176) time: 2.8200 data: 0.0021 max mem: 19788 +Epoch: [38] [1770/2138] eta: 0:17:42 lr: 2.0846638650821845e-06 loss: 0.0160 (0.0176) time: 2.8241 data: 0.0020 max mem: 19788 +Epoch: [38] [1780/2138] eta: 0:17:13 lr: 2.077172557623511e-06 loss: 0.0152 (0.0176) time: 2.8279 data: 0.0023 max mem: 19788 +Epoch: [38] [1790/2138] eta: 0:16:44 lr: 2.0696782470265717e-06 loss: 0.0151 (0.0176) time: 2.8287 data: 0.0023 max mem: 19788 +Epoch: [38] [1800/2138] eta: 0:16:15 lr: 2.0621809199950353e-06 loss: 0.0188 (0.0176) time: 2.8283 data: 0.0024 max mem: 19788 +Epoch: [38] [1810/2138] eta: 0:15:46 lr: 2.0546805631197585e-06 loss: 0.0187 (0.0176) time: 2.8251 data: 0.0023 max mem: 19788 +Epoch: [38] [1820/2138] eta: 0:15:17 lr: 2.0471771628773097e-06 loss: 0.0163 (0.0176) time: 2.9849 data: 0.0021 max mem: 19788 +Epoch: [38] [1830/2138] eta: 0:14:49 lr: 2.0396707056285815e-06 loss: 0.0171 (0.0176) time: 3.0832 data: 0.0023 max mem: 19788 +Epoch: [38] [1840/2138] eta: 0:14:20 lr: 2.0321611776172675e-06 loss: 0.0183 (0.0176) time: 3.0021 data: 0.0026 max mem: 19788 +Epoch: [38] [1850/2138] eta: 0:13:51 lr: 2.0246485649684276e-06 loss: 0.0187 (0.0176) time: 2.9045 data: 0.0027 max mem: 19788 +Epoch: [38] [1860/2138] eta: 0:13:22 lr: 2.0171328536869126e-06 loss: 0.0177 (0.0176) time: 2.8304 data: 0.0027 max mem: 19788 +Epoch: [38] [1870/2138] eta: 0:12:53 lr: 2.0096140296558785e-06 loss: 0.0172 (0.0176) time: 2.8270 data: 0.0026 max mem: 19788 +Epoch: [38] [1880/2138] eta: 0:12:24 lr: 2.0020920786351613e-06 loss: 0.0159 (0.0176) time: 2.8214 data: 0.0024 max mem: 19788 +Epoch: [38] [1890/2138] eta: 0:11:55 lr: 1.994566986259736e-06 loss: 0.0150 (0.0176) time: 2.8193 data: 0.0024 max mem: 19788 +Epoch: [38] [1900/2138] eta: 0:11:26 lr: 1.987038738038038e-06 loss: 0.0186 (0.0176) time: 2.8270 data: 0.0024 max mem: 19788 +Epoch: [38] [1910/2138] eta: 0:10:57 lr: 1.9795073193503657e-06 loss: 0.0169 (0.0176) time: 2.8421 data: 0.0024 max mem: 19788 +Epoch: [38] [1920/2138] eta: 0:10:29 lr: 1.9719727154471463e-06 loss: 0.0162 (0.0176) time: 2.9320 data: 0.0024 max mem: 19788 +Epoch: [38] [1930/2138] eta: 0:10:00 lr: 1.9644349114472807e-06 loss: 0.0161 (0.0176) time: 2.9851 data: 0.0022 max mem: 19788 +Epoch: [38] [1940/2138] eta: 0:09:31 lr: 1.956893892336349e-06 loss: 0.0161 (0.0176) time: 2.9364 data: 0.0026 max mem: 19788 +Epoch: [38] [1950/2138] eta: 0:09:02 lr: 1.9493496429648946e-06 loss: 0.0174 (0.0176) time: 2.8689 data: 0.0029 max mem: 19788 +Epoch: [38] [1960/2138] eta: 0:08:33 lr: 1.94180214804657e-06 loss: 0.0175 (0.0176) time: 2.8269 data: 0.0029 max mem: 19788 +Epoch: [38] [1970/2138] eta: 0:08:04 lr: 1.9342513921563565e-06 loss: 0.0145 (0.0176) time: 2.8285 data: 0.0028 max mem: 19788 +Epoch: [38] [1980/2138] eta: 0:07:35 lr: 1.926697359728645e-06 loss: 0.0160 (0.0176) time: 2.8249 data: 0.0028 max mem: 19788 +Epoch: [38] [1990/2138] eta: 0:07:07 lr: 1.9191400350553918e-06 loss: 0.0174 (0.0176) time: 2.8272 data: 0.0028 max mem: 19788 +Epoch: [38] [2000/2138] eta: 0:06:38 lr: 1.911579402284135e-06 loss: 0.0151 (0.0176) time: 2.8258 data: 0.0028 max mem: 19788 +Epoch: [38] [2010/2138] eta: 0:06:09 lr: 1.9040154454160506e-06 loss: 0.0162 (0.0176) time: 2.8324 data: 0.0024 max mem: 19788 +Epoch: [38] [2020/2138] eta: 0:05:40 lr: 1.8964481483039666e-06 loss: 0.0185 (0.0176) time: 3.0073 data: 0.0023 max mem: 19788 +Epoch: [38] [2030/2138] eta: 0:05:11 lr: 1.8888774946502752e-06 loss: 0.0171 (0.0176) time: 3.0664 data: 0.0027 max mem: 19788 +Epoch: [38] [2040/2138] eta: 0:04:42 lr: 1.8813034680049136e-06 loss: 0.0171 (0.0176) time: 2.9206 data: 0.0026 max mem: 19788 +Epoch: [38] [2050/2138] eta: 0:04:13 lr: 1.8737260517631872e-06 loss: 0.0172 (0.0176) time: 2.8543 data: 0.0023 max mem: 19788 +Epoch: [38] [2060/2138] eta: 0:03:45 lr: 1.8661452291636773e-06 loss: 0.0172 (0.0176) time: 2.8240 data: 0.0023 max mem: 19788 +Epoch: [38] [2070/2138] eta: 0:03:16 lr: 1.8585609832859862e-06 loss: 0.0166 (0.0176) time: 2.8177 data: 0.0024 max mem: 19788 +Epoch: [38] [2080/2138] eta: 0:02:47 lr: 1.8509732970485593e-06 loss: 0.0161 (0.0176) time: 2.8275 data: 0.0026 max mem: 19788 +Epoch: [38] [2090/2138] eta: 0:02:18 lr: 1.8433821532063533e-06 loss: 0.0179 (0.0176) time: 2.8367 data: 0.0025 max mem: 19788 +Epoch: [38] [2100/2138] eta: 0:01:49 lr: 1.8357875343485712e-06 loss: 0.0163 (0.0176) time: 2.8189 data: 0.0024 max mem: 19788 +Epoch: [38] [2110/2138] eta: 0:01:20 lr: 1.8281894228962427e-06 loss: 0.0187 (0.0176) time: 2.8305 data: 0.0023 max mem: 19788 +Epoch: [38] [2120/2138] eta: 0:00:51 lr: 1.8205878010998733e-06 loss: 0.0202 (0.0176) time: 2.9599 data: 0.0023 max mem: 19788 +Epoch: [38] [2130/2138] eta: 0:00:23 lr: 1.8129826510369329e-06 loss: 0.0194 (0.0176) time: 3.0843 data: 0.0023 max mem: 19788 +Epoch: [38] Total time: 1:42:51 +Test: [ 0/21770] eta: 16:12:28 time: 2.6802 data: 2.5987 max mem: 19788 +Test: [ 100/21770] eta: 0:26:42 time: 0.0422 data: 0.0013 max mem: 19788 +Test: [ 200/21770] eta: 0:21:00 time: 0.0437 data: 0.0014 max mem: 19788 +Test: [ 300/21770] eta: 0:19:49 time: 0.0518 data: 0.0017 max mem: 19788 +Test: [ 400/21770] eta: 0:18:43 time: 0.0426 data: 0.0014 max mem: 19788 +Test: [ 500/21770] eta: 0:18:15 time: 0.0546 data: 0.0017 max mem: 19788 +Test: [ 600/21770] eta: 0:17:58 time: 0.0445 data: 0.0015 max mem: 19788 +Test: [ 700/21770] eta: 0:17:35 time: 0.0451 data: 0.0016 max mem: 19788 +Test: [ 800/21770] eta: 0:17:15 time: 0.0468 data: 0.0016 max mem: 19788 +Test: [ 900/21770] eta: 0:17:06 time: 0.0520 data: 0.0018 max mem: 19788 +Test: [ 1000/21770] eta: 0:16:53 time: 0.0433 data: 0.0015 max mem: 19788 +Test: [ 1100/21770] eta: 0:16:38 time: 0.0438 data: 0.0015 max mem: 19788 +Test: [ 1200/21770] eta: 0:16:27 time: 0.0426 data: 0.0014 max mem: 19788 +Test: [ 1300/21770] eta: 0:16:15 time: 0.0437 data: 0.0016 max mem: 19788 +Test: [ 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time: 0.0423 data: 0.0014 max mem: 19788 +Test: [ 2800/21770] eta: 0:14:43 time: 0.0441 data: 0.0014 max mem: 19788 +Test: [ 2900/21770] eta: 0:14:37 time: 0.0477 data: 0.0015 max mem: 19788 +Test: [ 3000/21770] eta: 0:14:33 time: 0.0437 data: 0.0015 max mem: 19788 +Test: [ 3100/21770] eta: 0:14:27 time: 0.0448 data: 0.0014 max mem: 19788 +Test: [ 3200/21770] eta: 0:14:21 time: 0.0451 data: 0.0015 max mem: 19788 +Test: [ 3300/21770] eta: 0:14:18 time: 0.0499 data: 0.0016 max mem: 19788 +Test: [ 3400/21770] eta: 0:14:13 time: 0.0502 data: 0.0017 max mem: 19788 +Test: [ 3500/21770] eta: 0:14:08 time: 0.0451 data: 0.0015 max mem: 19788 +Test: [ 3600/21770] eta: 0:14:03 time: 0.0429 data: 0.0015 max mem: 19788 +Test: [ 3700/21770] eta: 0:13:58 time: 0.0493 data: 0.0014 max mem: 19788 +Test: [ 3800/21770] eta: 0:13:54 time: 0.0488 data: 0.0018 max mem: 19788 +Test: [ 3900/21770] eta: 0:13:49 time: 0.0434 data: 0.0015 max mem: 19788 +Test: [ 4000/21770] eta: 0:13:45 time: 0.0435 data: 0.0015 max mem: 19788 +Test: [ 4100/21770] eta: 0:13:39 time: 0.0437 data: 0.0015 max mem: 19788 +Test: [ 4200/21770] eta: 0:13:35 time: 0.0430 data: 0.0015 max mem: 19788 +Test: [ 4300/21770] eta: 0:13:31 time: 0.0438 data: 0.0013 max mem: 19788 +Test: [ 4400/21770] eta: 0:13:26 time: 0.0455 data: 0.0013 max mem: 19788 +Test: [ 4500/21770] eta: 0:13:22 time: 0.0444 data: 0.0014 max mem: 19788 +Test: [ 4600/21770] eta: 0:13:16 time: 0.0457 data: 0.0016 max mem: 19788 +Test: [ 4700/21770] eta: 0:13:11 time: 0.0447 data: 0.0015 max mem: 19788 +Test: [ 4800/21770] eta: 0:13:07 time: 0.0468 data: 0.0015 max mem: 19788 +Test: [ 4900/21770] eta: 0:13:01 time: 0.0442 data: 0.0014 max mem: 19788 +Test: [ 5000/21770] eta: 0:12:57 time: 0.0449 data: 0.0016 max mem: 19788 +Test: [ 5100/21770] eta: 0:12:53 time: 0.0518 data: 0.0018 max mem: 19788 +Test: [ 5200/21770] eta: 0:12:48 time: 0.0452 data: 0.0017 max mem: 19788 +Test: [ 5300/21770] eta: 0:12:44 time: 0.0542 data: 0.0018 max mem: 19788 +Test: [ 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time: 0.0422 data: 0.0015 max mem: 19788 +Test: [ 6800/21770] eta: 0:11:37 time: 0.0489 data: 0.0016 max mem: 19788 +Test: [ 6900/21770] eta: 0:11:33 time: 0.0507 data: 0.0016 max mem: 19788 +Test: [ 7000/21770] eta: 0:11:28 time: 0.0523 data: 0.0018 max mem: 19788 +Test: [ 7100/21770] eta: 0:11:24 time: 0.0423 data: 0.0014 max mem: 19788 +Test: [ 7200/21770] eta: 0:11:18 time: 0.0463 data: 0.0016 max mem: 19788 +Test: [ 7300/21770] eta: 0:11:13 time: 0.0440 data: 0.0014 max mem: 19788 +Test: [ 7400/21770] eta: 0:11:08 time: 0.0451 data: 0.0013 max mem: 19788 +Test: [ 7500/21770] eta: 0:11:03 time: 0.0439 data: 0.0014 max mem: 19788 +Test: [ 7600/21770] eta: 0:10:58 time: 0.0517 data: 0.0017 max mem: 19788 +Test: [ 7700/21770] eta: 0:10:54 time: 0.0518 data: 0.0018 max mem: 19788 +Test: [ 7800/21770] eta: 0:10:49 time: 0.0433 data: 0.0014 max mem: 19788 +Test: [ 7900/21770] eta: 0:10:43 time: 0.0449 data: 0.0016 max mem: 19788 +Test: [ 8000/21770] eta: 0:10:39 time: 0.0472 data: 0.0017 max mem: 19788 +Test: [ 8100/21770] eta: 0:10:35 time: 0.0497 data: 0.0018 max mem: 19788 +Test: [ 8200/21770] eta: 0:10:31 time: 0.0518 data: 0.0017 max mem: 19788 +Test: [ 8300/21770] eta: 0:10:27 time: 0.0446 data: 0.0015 max mem: 19788 +Test: [ 8400/21770] eta: 0:10:22 time: 0.0479 data: 0.0015 max mem: 19788 +Test: [ 8500/21770] eta: 0:10:17 time: 0.0483 data: 0.0016 max mem: 19788 +Test: [ 8600/21770] eta: 0:10:12 time: 0.0440 data: 0.0015 max mem: 19788 +Test: [ 8700/21770] eta: 0:10:07 time: 0.0469 data: 0.0015 max mem: 19788 +Test: [ 8800/21770] eta: 0:10:03 time: 0.0523 data: 0.0018 max mem: 19788 +Test: [ 8900/21770] eta: 0:09:58 time: 0.0472 data: 0.0014 max mem: 19788 +Test: [ 9000/21770] eta: 0:09:53 time: 0.0495 data: 0.0017 max mem: 19788 +Test: [ 9100/21770] eta: 0:09:49 time: 0.0476 data: 0.0015 max mem: 19788 +Test: [ 9200/21770] eta: 0:09:44 time: 0.0416 data: 0.0014 max mem: 19788 +Test: [ 9300/21770] eta: 0:09:40 time: 0.0477 data: 0.0014 max mem: 19788 +Test: [ 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time: 0.0443 data: 0.0016 max mem: 19788 +Test: [10800/21770] eta: 0:08:31 time: 0.0484 data: 0.0016 max mem: 19788 +Test: [10900/21770] eta: 0:08:27 time: 0.0443 data: 0.0015 max mem: 19788 +Test: [11000/21770] eta: 0:08:22 time: 0.0444 data: 0.0015 max mem: 19788 +Test: [11100/21770] eta: 0:08:17 time: 0.0471 data: 0.0016 max mem: 19788 +Test: [11200/21770] eta: 0:08:12 time: 0.0432 data: 0.0016 max mem: 19788 +Test: [11300/21770] eta: 0:08:08 time: 0.0451 data: 0.0014 max mem: 19788 +Test: [11400/21770] eta: 0:08:03 time: 0.0446 data: 0.0014 max mem: 19788 +Test: [11500/21770] eta: 0:07:58 time: 0.0441 data: 0.0014 max mem: 19788 +Test: [11600/21770] eta: 0:07:53 time: 0.0496 data: 0.0017 max mem: 19788 +Test: [11700/21770] eta: 0:07:49 time: 0.0502 data: 0.0017 max mem: 19788 +Test: [11800/21770] eta: 0:07:44 time: 0.0451 data: 0.0016 max mem: 19788 +Test: [11900/21770] eta: 0:07:40 time: 0.0484 data: 0.0015 max mem: 19788 +Test: [12000/21770] eta: 0:07:35 time: 0.0502 data: 0.0017 max mem: 19788 +Test: [12100/21770] eta: 0:07:31 time: 0.0437 data: 0.0014 max mem: 19788 +Test: [12200/21770] eta: 0:07:26 time: 0.0430 data: 0.0014 max mem: 19788 +Test: [12300/21770] eta: 0:07:21 time: 0.0492 data: 0.0016 max mem: 19788 +Test: [12400/21770] eta: 0:07:17 time: 0.0507 data: 0.0017 max mem: 19788 +Test: [12500/21770] eta: 0:07:12 time: 0.0434 data: 0.0013 max mem: 19788 +Test: [12600/21770] eta: 0:07:07 time: 0.0527 data: 0.0019 max mem: 19788 +Test: [12700/21770] eta: 0:07:03 time: 0.0500 data: 0.0017 max mem: 19788 +Test: [12800/21770] eta: 0:06:58 time: 0.0447 data: 0.0015 max mem: 19788 +Test: [12900/21770] eta: 0:06:53 time: 0.0503 data: 0.0017 max mem: 19788 +Test: [13000/21770] eta: 0:06:49 time: 0.0460 data: 0.0015 max mem: 19788 +Test: [13100/21770] eta: 0:06:44 time: 0.0431 data: 0.0015 max mem: 19788 +Test: [13200/21770] eta: 0:06:39 time: 0.0477 data: 0.0016 max mem: 19788 +Test: [13300/21770] eta: 0:06:35 time: 0.0443 data: 0.0016 max mem: 19788 +Test: [13400/21770] eta: 0:06:30 time: 0.0478 data: 0.0016 max mem: 19788 +Test: [13500/21770] eta: 0:06:25 time: 0.0500 data: 0.0016 max mem: 19788 +Test: [13600/21770] eta: 0:06:21 time: 0.0443 data: 0.0015 max mem: 19788 +Test: [13700/21770] eta: 0:06:16 time: 0.0533 data: 0.0016 max mem: 19788 +Test: [13800/21770] eta: 0:06:12 time: 0.0458 data: 0.0015 max mem: 19788 +Test: [13900/21770] eta: 0:06:07 time: 0.0451 data: 0.0016 max mem: 19788 +Test: [14000/21770] eta: 0:06:02 time: 0.0486 data: 0.0015 max mem: 19788 +Test: [14100/21770] eta: 0:05:58 time: 0.0450 data: 0.0016 max mem: 19788 +Test: [14200/21770] eta: 0:05:53 time: 0.0483 data: 0.0015 max mem: 19788 +Test: [14300/21770] eta: 0:05:48 time: 0.0482 data: 0.0016 max mem: 19788 +Test: [14400/21770] eta: 0:05:44 time: 0.0441 data: 0.0015 max mem: 19788 +Test: [14500/21770] eta: 0:05:39 time: 0.0464 data: 0.0016 max mem: 19788 +Test: [14600/21770] eta: 0:05:34 time: 0.0435 data: 0.0015 max mem: 19788 +Test: [14700/21770] eta: 0:05:30 time: 0.0425 data: 0.0014 max mem: 19788 +Test: [14800/21770] eta: 0:05:25 time: 0.0496 data: 0.0018 max mem: 19788 +Test: [14900/21770] eta: 0:05:20 time: 0.0454 data: 0.0015 max mem: 19788 +Test: [15000/21770] eta: 0:05:16 time: 0.0473 data: 0.0017 max mem: 19788 +Test: [15100/21770] eta: 0:05:11 time: 0.0433 data: 0.0016 max mem: 19788 +Test: [15200/21770] eta: 0:05:06 time: 0.0515 data: 0.0017 max mem: 19788 +Test: [15300/21770] eta: 0:05:02 time: 0.0500 data: 0.0017 max mem: 19788 +Test: [15400/21770] eta: 0:04:57 time: 0.0513 data: 0.0018 max mem: 19788 +Test: [15500/21770] eta: 0:04:52 time: 0.0482 data: 0.0015 max mem: 19788 +Test: [15600/21770] eta: 0:04:48 time: 0.0433 data: 0.0015 max mem: 19788 +Test: [15700/21770] eta: 0:04:43 time: 0.0436 data: 0.0015 max mem: 19788 +Test: [15800/21770] eta: 0:04:39 time: 0.0440 data: 0.0014 max mem: 19788 +Test: [15900/21770] eta: 0:04:34 time: 0.0431 data: 0.0015 max mem: 19788 +Test: [16000/21770] eta: 0:04:29 time: 0.0472 data: 0.0015 max mem: 19788 +Test: [16100/21770] eta: 0:04:24 time: 0.0499 data: 0.0017 max mem: 19788 +Test: [16200/21770] eta: 0:04:20 time: 0.0460 data: 0.0017 max mem: 19788 +Test: [16300/21770] eta: 0:04:15 time: 0.0464 data: 0.0014 max mem: 19788 +Test: [16400/21770] eta: 0:04:10 time: 0.0467 data: 0.0014 max mem: 19788 +Test: [16500/21770] eta: 0:04:06 time: 0.0493 data: 0.0017 max mem: 19788 +Test: [16600/21770] eta: 0:04:01 time: 0.0466 data: 0.0016 max mem: 19788 +Test: [16700/21770] eta: 0:03:56 time: 0.0445 data: 0.0016 max mem: 19788 +Test: [16800/21770] eta: 0:03:52 time: 0.0450 data: 0.0015 max mem: 19788 +Test: [16900/21770] eta: 0:03:47 time: 0.0528 data: 0.0016 max mem: 19788 +Test: [17000/21770] eta: 0:03:42 time: 0.0513 data: 0.0017 max mem: 19788 +Test: [17100/21770] eta: 0:03:38 time: 0.0501 data: 0.0015 max mem: 19788 +Test: [17200/21770] eta: 0:03:33 time: 0.0532 data: 0.0018 max mem: 19788 +Test: [17300/21770] eta: 0:03:29 time: 0.0481 data: 0.0017 max mem: 19788 +Test: [17400/21770] eta: 0:03:24 time: 0.0540 data: 0.0018 max mem: 19788 +Test: [17500/21770] eta: 0:03:20 time: 0.0433 data: 0.0014 max mem: 19788 +Test: [17600/21770] eta: 0:03:15 time: 0.0457 data: 0.0013 max mem: 19788 +Test: [17700/21770] eta: 0:03:10 time: 0.0487 data: 0.0016 max mem: 19788 +Test: [17800/21770] eta: 0:03:06 time: 0.0532 data: 0.0018 max mem: 19788 +Test: [17900/21770] eta: 0:03:01 time: 0.0478 data: 0.0017 max mem: 19788 +Test: [18000/21770] eta: 0:02:56 time: 0.0489 data: 0.0017 max mem: 19788 +Test: [18100/21770] eta: 0:02:51 time: 0.0551 data: 0.0018 max mem: 19788 +Test: [18200/21770] eta: 0:02:47 time: 0.0436 data: 0.0017 max mem: 19788 +Test: [18300/21770] eta: 0:02:42 time: 0.0438 data: 0.0016 max mem: 19788 +Test: [18400/21770] eta: 0:02:37 time: 0.0507 data: 0.0016 max mem: 19788 +Test: [18500/21770] eta: 0:02:33 time: 0.0442 data: 0.0014 max mem: 19788 +Test: [18600/21770] eta: 0:02:28 time: 0.0495 data: 0.0028 max mem: 19788 +Test: [18700/21770] eta: 0:02:23 time: 0.0434 data: 0.0014 max mem: 19788 +Test: [18800/21770] eta: 0:02:19 time: 0.0537 data: 0.0015 max mem: 19788 +Test: [18900/21770] eta: 0:02:14 time: 0.0428 data: 0.0015 max mem: 19788 +Test: [19000/21770] eta: 0:02:09 time: 0.0460 data: 0.0015 max mem: 19788 +Test: [19100/21770] eta: 0:02:05 time: 0.0526 data: 0.0015 max mem: 19788 +Test: [19200/21770] eta: 0:02:00 time: 0.0480 data: 0.0017 max mem: 19788 +Test: [19300/21770] eta: 0:01:55 time: 0.0537 data: 0.0018 max mem: 19788 +Test: [19400/21770] eta: 0:01:51 time: 0.0438 data: 0.0015 max mem: 19788 +Test: [19500/21770] eta: 0:01:46 time: 0.0431 data: 0.0014 max mem: 19788 +Test: [19600/21770] eta: 0:01:41 time: 0.0441 data: 0.0014 max mem: 19788 +Test: [19700/21770] eta: 0:01:36 time: 0.0454 data: 0.0015 max mem: 19788 +Test: [19800/21770] eta: 0:01:32 time: 0.0483 data: 0.0015 max mem: 19788 +Test: [19900/21770] eta: 0:01:27 time: 0.0433 data: 0.0014 max mem: 19788 +Test: [20000/21770] eta: 0:01:22 time: 0.0429 data: 0.0013 max mem: 19788 +Test: [20100/21770] eta: 0:01:18 time: 0.0465 data: 0.0014 max mem: 19788 +Test: [20200/21770] eta: 0:01:13 time: 0.0518 data: 0.0017 max mem: 19788 +Test: [20300/21770] eta: 0:01:08 time: 0.0439 data: 0.0014 max mem: 19788 +Test: [20400/21770] eta: 0:01:04 time: 0.0467 data: 0.0016 max mem: 19788 +Test: [20500/21770] eta: 0:00:59 time: 0.0491 data: 0.0016 max mem: 19788 +Test: [20600/21770] eta: 0:00:54 time: 0.0452 data: 0.0014 max mem: 19788 +Test: [20700/21770] eta: 0:00:50 time: 0.0436 data: 0.0014 max mem: 19788 +Test: [20800/21770] eta: 0:00:45 time: 0.0424 data: 0.0014 max mem: 19788 +Test: [20900/21770] eta: 0:00:40 time: 0.0542 data: 0.0017 max mem: 19788 +Test: [21000/21770] eta: 0:00:36 time: 0.0522 data: 0.0018 max mem: 19788 +Test: [21100/21770] eta: 0:00:31 time: 0.0451 data: 0.0014 max mem: 19788 +Test: [21200/21770] eta: 0:00:26 time: 0.0435 data: 0.0014 max mem: 19788 +Test: [21300/21770] eta: 0:00:22 time: 0.0501 data: 0.0018 max mem: 19788 +Test: [21400/21770] eta: 0:00:17 time: 0.0456 data: 0.0013 max mem: 19788 +Test: [21500/21770] eta: 0:00:12 time: 0.0487 data: 0.0017 max mem: 19788 +Test: [21600/21770] eta: 0:00:07 time: 0.0444 data: 0.0015 max mem: 19788 +Test: [21700/21770] eta: 0:00:03 time: 0.0494 data: 0.0016 max mem: 19788 +Test: Total time: 0:17:00 +Final results: +Mean IoU is 64.61 + + precision@0.5 = 71.95 + precision@0.6 = 66.54 + precision@0.7 = 60.14 + precision@0.8 = 49.49 + precision@0.9 = 24.11 + overall IoU = 65.20 + mean IoU = 64.61 + +Mean accuracy for one-to-zero sample is 87.71 + +Average object IoU 0.6461388789843667 +Overall IoU 65.19512939453125 +Epoch: [39] [ 0/2138] eta: 6:55:41 lr: 1.8068959784787458e-06 loss: 0.0230 (0.0230) time: 11.6660 data: 2.1423 max mem: 19788 +Epoch: [39] [ 10/2138] eta: 2:11:36 lr: 1.7992844318094101e-06 loss: 0.0172 (0.0189) time: 3.7106 data: 0.1968 max mem: 19788 +Epoch: [39] [ 20/2138] eta: 1:59:34 lr: 1.791669305748589e-06 loss: 0.0161 (0.0170) time: 2.9737 data: 0.0023 max mem: 19788 +Epoch: [39] [ 30/2138] eta: 1:54:41 lr: 1.784050581693132e-06 loss: 0.0161 (0.0174) time: 3.0189 data: 0.0028 max mem: 19788 +Epoch: [39] [ 40/2138] eta: 1:50:55 lr: 1.7764282408544076e-06 loss: 0.0171 (0.0176) time: 2.9465 data: 0.0028 max mem: 19788 +Epoch: [39] [ 50/2138] eta: 1:48:15 lr: 1.7688022642555827e-06 loss: 0.0165 (0.0178) time: 2.8727 data: 0.0024 max mem: 19788 +Epoch: [39] [ 60/2138] eta: 1:46:13 lr: 1.7611726327288473e-06 loss: 0.0180 (0.0181) time: 2.8517 data: 0.0025 max mem: 19788 +Epoch: [39] [ 70/2138] eta: 1:44:41 lr: 1.7535393269125126e-06 loss: 0.0181 (0.0181) time: 2.8504 data: 0.0023 max mem: 19788 +Epoch: [39] [ 80/2138] eta: 1:43:23 lr: 1.7459023272481615e-06 loss: 0.0171 (0.0181) time: 2.8529 data: 0.0022 max mem: 19788 +Epoch: [39] [ 90/2138] eta: 1:42:16 lr: 1.738261613977624e-06 loss: 0.0163 (0.0180) time: 2.8515 data: 0.0023 max mem: 19788 +Epoch: [39] [ 100/2138] eta: 1:41:12 lr: 1.7306171671400094e-06 loss: 0.0166 (0.0180) time: 2.8394 data: 0.0023 max mem: 19788 +Epoch: [39] [ 110/2138] eta: 1:40:25 lr: 1.7229689665685638e-06 loss: 0.0170 (0.0178) time: 2.8544 data: 0.0021 max mem: 19788 +Epoch: [39] [ 120/2138] eta: 1:39:59 lr: 1.7153169918875766e-06 loss: 0.0141 (0.0176) time: 2.9379 data: 0.0023 max mem: 19788 +Epoch: [39] [ 130/2138] eta: 1:39:29 lr: 1.7076612225091129e-06 loss: 0.0170 (0.0177) time: 2.9831 data: 0.0024 max mem: 19788 +Epoch: [39] [ 140/2138] eta: 1:38:41 lr: 1.7000016376297888e-06 loss: 0.0170 (0.0177) time: 2.9105 data: 0.0023 max mem: 19788 +Epoch: [39] [ 150/2138] eta: 1:37:54 lr: 1.6923382162273727e-06 loss: 0.0165 (0.0177) time: 2.8377 data: 0.0024 max mem: 19788 +Epoch: [39] [ 160/2138] eta: 1:37:10 lr: 1.6846709370574245e-06 loss: 0.0177 (0.0177) time: 2.8309 data: 0.0025 max mem: 19788 +Epoch: [39] [ 170/2138] eta: 1:36:27 lr: 1.6769997786497529e-06 loss: 0.0183 (0.0176) time: 2.8338 data: 0.0025 max mem: 19788 +Epoch: [39] [ 180/2138] eta: 1:35:43 lr: 1.6693247193049173e-06 loss: 0.0162 (0.0176) time: 2.8221 data: 0.0022 max mem: 19788 +Epoch: [39] [ 190/2138] eta: 1:35:03 lr: 1.6616457370905329e-06 loss: 0.0162 (0.0175) time: 2.8167 data: 0.0020 max mem: 19788 +Epoch: [39] [ 200/2138] eta: 1:34:23 lr: 1.6539628098376229e-06 loss: 0.0164 (0.0175) time: 2.8205 data: 0.0021 max mem: 19788 +Epoch: [39] [ 210/2138] eta: 1:33:50 lr: 1.64627591513677e-06 loss: 0.0167 (0.0175) time: 2.8499 data: 0.0023 max mem: 19788 +Epoch: [39] [ 220/2138] eta: 1:33:27 lr: 1.638585030334308e-06 loss: 0.0163 (0.0175) time: 2.9340 data: 0.0024 max mem: 19788 +Epoch: [39] [ 230/2138] eta: 1:33:05 lr: 1.6308901325283105e-06 loss: 0.0157 (0.0176) time: 3.0012 data: 0.0027 max mem: 19788 +Epoch: [39] [ 240/2138] eta: 1:32:30 lr: 1.6231911985646127e-06 loss: 0.0177 (0.0176) time: 2.9333 data: 0.0031 max mem: 19788 +Epoch: [39] [ 250/2138] eta: 1:31:53 lr: 1.6154882050326319e-06 loss: 0.0173 (0.0175) time: 2.8356 data: 0.0031 max mem: 19788 +Epoch: [39] [ 260/2138] eta: 1:31:16 lr: 1.6077811282612095e-06 loss: 0.0163 (0.0175) time: 2.8207 data: 0.0027 max mem: 19788 +Epoch: [39] [ 270/2138] eta: 1:30:41 lr: 1.60006994431425e-06 loss: 0.0169 (0.0175) time: 2.8235 data: 0.0027 max mem: 19788 +Epoch: [39] [ 280/2138] eta: 1:30:06 lr: 1.5923546289863772e-06 loss: 0.0179 (0.0175) time: 2.8228 data: 0.0028 max mem: 19788 +Epoch: [39] [ 290/2138] eta: 1:29:30 lr: 1.5846351577983817e-06 loss: 0.0178 (0.0175) time: 2.8175 data: 0.0024 max mem: 19788 +Epoch: [39] [ 300/2138] eta: 1:28:56 lr: 1.576911505992678e-06 loss: 0.0167 (0.0175) time: 2.8200 data: 0.0024 max mem: 19788 +Epoch: [39] [ 310/2138] eta: 1:28:25 lr: 1.5691836485285519e-06 loss: 0.0162 (0.0175) time: 2.8412 data: 0.0027 max mem: 19788 +Epoch: [39] [ 320/2138] eta: 1:28:04 lr: 1.5614515600774097e-06 loss: 0.0146 (0.0174) time: 2.9557 data: 0.0030 max mem: 19788 +Epoch: [39] [ 330/2138] eta: 1:27:40 lr: 1.5537152150178083e-06 loss: 0.0168 (0.0174) time: 3.0225 data: 0.0029 max mem: 19788 +Epoch: [39] [ 340/2138] eta: 1:27:13 lr: 1.5459745874304885e-06 loss: 0.0172 (0.0174) time: 2.9717 data: 0.0024 max mem: 19788 +Epoch: [39] [ 350/2138] eta: 1:26:39 lr: 1.5382296510931834e-06 loss: 0.0172 (0.0174) time: 2.8853 data: 0.0022 max mem: 19788 +Epoch: [39] [ 360/2138] eta: 1:26:06 lr: 1.5304803794753838e-06 loss: 0.0182 (0.0174) time: 2.8265 data: 0.0024 max mem: 19788 +Epoch: [39] [ 370/2138] eta: 1:25:33 lr: 1.52272674573298e-06 loss: 0.0201 (0.0175) time: 2.8272 data: 0.0027 max mem: 19788 +Epoch: [39] [ 380/2138] eta: 1:25:00 lr: 1.5149687227027078e-06 loss: 0.0161 (0.0174) time: 2.8193 data: 0.0029 max mem: 19788 +Epoch: [39] [ 390/2138] eta: 1:24:28 lr: 1.5072062828965747e-06 loss: 0.0146 (0.0173) time: 2.8221 data: 0.0027 max mem: 19788 +Epoch: [39] [ 400/2138] eta: 1:23:55 lr: 1.4994393984960358e-06 loss: 0.0149 (0.0174) time: 2.8219 data: 0.0026 max mem: 19788 +Epoch: [39] [ 410/2138] eta: 1:23:25 lr: 1.4916680413461532e-06 loss: 0.0163 (0.0173) time: 2.8455 data: 0.0026 max mem: 19788 +Epoch: [39] [ 420/2138] eta: 1:23:00 lr: 1.483892182949495e-06 loss: 0.0146 (0.0174) time: 2.9279 data: 0.0024 max mem: 19788 +Epoch: [39] [ 430/2138] eta: 1:22:36 lr: 1.4761117944600106e-06 loss: 0.0164 (0.0173) time: 3.0012 data: 0.0023 max mem: 19788 +Epoch: [39] [ 440/2138] eta: 1:22:05 lr: 1.4683268466766376e-06 loss: 0.0167 (0.0174) time: 2.9380 data: 0.0023 max mem: 19788 +Epoch: [39] [ 450/2138] eta: 1:21:33 lr: 1.460537310036873e-06 loss: 0.0185 (0.0174) time: 2.8378 data: 0.0025 max mem: 19788 +Epoch: [39] [ 460/2138] eta: 1:21:02 lr: 1.4527431546100722e-06 loss: 0.0176 (0.0174) time: 2.8323 data: 0.0027 max mem: 19788 +Epoch: [39] [ 470/2138] eta: 1:20:32 lr: 1.4449443500906982e-06 loss: 0.0176 (0.0174) time: 2.8549 data: 0.0027 max mem: 19788 +Epoch: [39] [ 480/2138] eta: 1:20:01 lr: 1.4371408657912909e-06 loss: 0.0179 (0.0174) time: 2.8556 data: 0.0026 max mem: 19788 +Epoch: [39] [ 490/2138] eta: 1:19:31 lr: 1.4293326706353767e-06 loss: 0.0173 (0.0174) time: 2.8542 data: 0.0022 max mem: 19788 +Epoch: [39] [ 500/2138] eta: 1:19:01 lr: 1.4215197331500866e-06 loss: 0.0149 (0.0174) time: 2.8566 data: 0.0022 max mem: 19788 +Epoch: [39] [ 510/2138] eta: 1:18:33 lr: 1.4137020214587051e-06 loss: 0.0142 (0.0173) time: 2.8876 data: 0.0024 max mem: 19788 +Epoch: [39] [ 520/2138] eta: 1:18:08 lr: 1.405879503272915e-06 loss: 0.0149 (0.0173) time: 2.9727 data: 0.0029 max mem: 19788 +Epoch: [39] [ 530/2138] eta: 1:17:44 lr: 1.398052145884961e-06 loss: 0.0166 (0.0173) time: 3.0430 data: 0.0029 max mem: 19788 +Epoch: [39] [ 540/2138] eta: 1:17:15 lr: 1.390219916159499e-06 loss: 0.0163 (0.0173) time: 2.9864 data: 0.0025 max mem: 19788 +Epoch: [39] [ 550/2138] eta: 1:16:45 lr: 1.3823827805253511e-06 loss: 0.0157 (0.0173) time: 2.8904 data: 0.0024 max mem: 19788 +Epoch: [39] [ 560/2138] eta: 1:16:15 lr: 1.3745407049669294e-06 loss: 0.0184 (0.0173) time: 2.8626 data: 0.0024 max mem: 19788 +Epoch: [39] [ 570/2138] eta: 1:15:45 lr: 1.366693655015558e-06 loss: 0.0181 (0.0173) time: 2.8626 data: 0.0025 max mem: 19788 +Epoch: [39] [ 580/2138] eta: 1:15:15 lr: 1.3588415957404455e-06 loss: 0.0159 (0.0174) time: 2.8656 data: 0.0027 max mem: 19788 +Epoch: [39] [ 590/2138] eta: 1:14:45 lr: 1.3509844917395413e-06 loss: 0.0162 (0.0173) time: 2.8563 data: 0.0027 max mem: 19788 +Epoch: [39] [ 600/2138] eta: 1:14:15 lr: 1.3431223071300293e-06 loss: 0.0162 (0.0173) time: 2.8576 data: 0.0026 max mem: 19788 +Epoch: [39] [ 610/2138] eta: 1:13:46 lr: 1.3352550055386868e-06 loss: 0.0167 (0.0173) time: 2.8892 data: 0.0023 max mem: 19788 +Epoch: [39] [ 620/2138] eta: 1:13:23 lr: 1.3273825500918667e-06 loss: 0.0171 (0.0174) time: 3.0223 data: 0.0024 max mem: 19788 +Epoch: [39] [ 630/2138] eta: 1:12:57 lr: 1.3195049034053253e-06 loss: 0.0173 (0.0174) time: 3.0777 data: 0.0025 max mem: 19788 +Epoch: [39] [ 640/2138] eta: 1:12:27 lr: 1.3116220275736578e-06 loss: 0.0173 (0.0174) time: 2.9368 data: 0.0027 max mem: 19788 +Epoch: [39] [ 650/2138] eta: 1:11:56 lr: 1.3037338841595605e-06 loss: 0.0173 (0.0174) time: 2.8358 data: 0.0028 max mem: 19788 +Epoch: [39] [ 660/2138] eta: 1:11:25 lr: 1.2958404341826858e-06 loss: 0.0175 (0.0175) time: 2.8286 data: 0.0024 max mem: 19788 +Epoch: [39] [ 670/2138] eta: 1:10:55 lr: 1.2879416381082633e-06 loss: 0.0174 (0.0175) time: 2.8305 data: 0.0022 max mem: 19788 +Epoch: [39] [ 680/2138] eta: 1:10:25 lr: 1.280037455835402e-06 loss: 0.0160 (0.0174) time: 2.8338 data: 0.0024 max mem: 19788 +Epoch: [39] [ 690/2138] eta: 1:09:54 lr: 1.2721278466849874e-06 loss: 0.0164 (0.0175) time: 2.8305 data: 0.0023 max mem: 19788 +Epoch: [39] [ 700/2138] eta: 1:09:24 lr: 1.2642127693873504e-06 loss: 0.0169 (0.0174) time: 2.8286 data: 0.0020 max mem: 19788 +Epoch: [39] [ 710/2138] eta: 1:08:55 lr: 1.2562921820694617e-06 loss: 0.0163 (0.0174) time: 2.8748 data: 0.0022 max mem: 19788 +Epoch: [39] [ 720/2138] eta: 1:08:28 lr: 1.2483660422418803e-06 loss: 0.0155 (0.0174) time: 2.9525 data: 0.0024 max mem: 19788 +Epoch: [39] [ 730/2138] eta: 1:08:01 lr: 1.2404343067852014e-06 loss: 0.0155 (0.0174) time: 3.0017 data: 0.0025 max mem: 19788 +Epoch: [39] [ 740/2138] eta: 1:07:31 lr: 1.2324969319362338e-06 loss: 0.0187 (0.0174) time: 2.9248 data: 0.0025 max mem: 19788 +Epoch: [39] [ 750/2138] eta: 1:07:01 lr: 1.224553873273645e-06 loss: 0.0176 (0.0174) time: 2.8347 data: 0.0023 max mem: 19788 +Epoch: [39] [ 760/2138] eta: 1:06:31 lr: 1.2166050857033093e-06 loss: 0.0181 (0.0174) time: 2.8347 data: 0.0024 max mem: 19788 +Epoch: [39] [ 770/2138] eta: 1:06:01 lr: 1.2086505234430922e-06 loss: 0.0171 (0.0174) time: 2.8314 data: 0.0025 max mem: 19788 +Epoch: [39] [ 780/2138] eta: 1:05:31 lr: 1.2006901400073044e-06 loss: 0.0156 (0.0174) time: 2.8291 data: 0.0023 max mem: 19788 +Epoch: [39] [ 790/2138] eta: 1:05:01 lr: 1.1927238881905617e-06 loss: 0.0156 (0.0174) time: 2.8304 data: 0.0025 max mem: 19788 +Epoch: [39] [ 800/2138] eta: 1:04:31 lr: 1.1847517200512748e-06 loss: 0.0165 (0.0174) time: 2.8337 data: 0.0028 max mem: 19788 +Epoch: [39] [ 810/2138] eta: 1:04:02 lr: 1.1767735868945132e-06 loss: 0.0171 (0.0174) time: 2.8854 data: 0.0027 max mem: 19788 +Epoch: [39] [ 820/2138] eta: 1:03:35 lr: 1.1687894392544598e-06 loss: 0.0169 (0.0174) time: 2.9610 data: 0.0023 max mem: 19788 +Epoch: [39] [ 830/2138] eta: 1:03:07 lr: 1.1607992268761954e-06 loss: 0.0142 (0.0174) time: 2.9738 data: 0.0025 max mem: 19788 +Epoch: [39] [ 840/2138] eta: 1:02:37 lr: 1.1528028986970382e-06 loss: 0.0156 (0.0174) time: 2.8968 data: 0.0028 max mem: 19788 +Epoch: [39] [ 850/2138] eta: 1:02:07 lr: 1.1448004028271656e-06 loss: 0.0163 (0.0174) time: 2.8406 data: 0.0024 max mem: 19788 +Epoch: [39] [ 860/2138] eta: 1:01:38 lr: 1.1367916865297445e-06 loss: 0.0160 (0.0174) time: 2.8359 data: 0.0023 max mem: 19788 +Epoch: [39] [ 870/2138] eta: 1:01:08 lr: 1.1287766962003e-06 loss: 0.0162 (0.0174) time: 2.8258 data: 0.0028 max mem: 19788 +Epoch: [39] [ 880/2138] eta: 1:00:38 lr: 1.120755377345537e-06 loss: 0.0160 (0.0173) time: 2.8290 data: 0.0029 max mem: 19788 +Epoch: [39] [ 890/2138] eta: 1:00:08 lr: 1.1127276745613514e-06 loss: 0.0157 (0.0174) time: 2.8339 data: 0.0026 max mem: 19788 +Epoch: [39] [ 900/2138] eta: 0:59:38 lr: 1.1046935315102375e-06 loss: 0.0167 (0.0174) time: 2.8320 data: 0.0023 max mem: 19788 +Epoch: [39] [ 910/2138] eta: 0:59:10 lr: 1.0966528908978244e-06 loss: 0.0163 (0.0174) time: 2.8657 data: 0.0021 max mem: 19788 +Epoch: [39] [ 920/2138] eta: 0:58:43 lr: 1.088605694448753e-06 loss: 0.0162 (0.0173) time: 2.9968 data: 0.0022 max mem: 19788 +Epoch: [39] [ 930/2138] eta: 0:58:16 lr: 1.0805518828816135e-06 loss: 0.0168 (0.0174) time: 3.0495 data: 0.0025 max mem: 19788 +Epoch: [39] [ 940/2138] eta: 0:57:46 lr: 1.072491395883157e-06 loss: 0.0185 (0.0174) time: 2.9303 data: 0.0025 max mem: 19788 +Epoch: [39] [ 950/2138] eta: 0:57:17 lr: 1.064424172081506e-06 loss: 0.0174 (0.0174) time: 2.8414 data: 0.0025 max mem: 19788 +Epoch: [39] [ 960/2138] eta: 0:56:47 lr: 1.056350149018517e-06 loss: 0.0181 (0.0174) time: 2.8376 data: 0.0025 max mem: 19788 +Epoch: [39] [ 970/2138] eta: 0:56:17 lr: 1.048269263121182e-06 loss: 0.0184 (0.0174) time: 2.8400 data: 0.0024 max mem: 19788 +Epoch: [39] [ 980/2138] eta: 0:55:48 lr: 1.040181449671942e-06 loss: 0.0160 (0.0174) time: 2.8332 data: 0.0026 max mem: 19788 +Epoch: [39] [ 990/2138] eta: 0:55:18 lr: 1.0320866427780701e-06 loss: 0.0157 (0.0174) time: 2.8271 data: 0.0024 max mem: 19788 +Epoch: [39] [1000/2138] eta: 0:54:49 lr: 1.0239847753398322e-06 loss: 0.0157 (0.0174) time: 2.8280 data: 0.0026 max mem: 19788 +Epoch: [39] [1010/2138] eta: 0:54:20 lr: 1.0158757790176238e-06 loss: 0.0154 (0.0174) time: 2.8810 data: 0.0030 max mem: 19788 +Epoch: [39] [1020/2138] eta: 0:53:52 lr: 1.007759584197787e-06 loss: 0.0153 (0.0174) time: 2.9576 data: 0.0028 max mem: 19788 +Epoch: [39] [1030/2138] eta: 0:53:24 lr: 9.996361199572952e-07 loss: 0.0146 (0.0174) time: 2.9754 data: 0.0026 max mem: 19788 +Epoch: [39] [1040/2138] eta: 0:52:55 lr: 9.915053140270074e-07 loss: 0.0159 (0.0174) time: 2.9055 data: 0.0023 max mem: 19788 +Epoch: [39] [1050/2138] eta: 0:52:25 lr: 9.83367092753669e-07 loss: 0.0177 (0.0174) time: 2.8301 data: 0.0020 max mem: 19788 +Epoch: [39] [1060/2138] eta: 0:51:55 lr: 9.752213810603572e-07 loss: 0.0174 (0.0174) time: 2.8177 data: 0.0021 max mem: 19788 +Epoch: [39] [1070/2138] eta: 0:51:26 lr: 9.67068102405544e-07 loss: 0.0169 (0.0174) time: 2.8206 data: 0.0024 max mem: 19788 +Epoch: [39] [1080/2138] eta: 0:50:56 lr: 9.589071787404587e-07 loss: 0.0162 (0.0174) time: 2.8304 data: 0.0026 max mem: 19788 +Epoch: [39] [1090/2138] eta: 0:50:27 lr: 9.507385304649222e-07 loss: 0.0167 (0.0174) time: 2.8428 data: 0.0026 max mem: 19788 +Epoch: [39] [1100/2138] eta: 0:49:58 lr: 9.425620763813255e-07 loss: 0.0180 (0.0174) time: 2.8342 data: 0.0027 max mem: 19788 +Epoch: [39] [1110/2138] eta: 0:49:29 lr: 9.343777336469135e-07 loss: 0.0180 (0.0174) time: 2.8771 data: 0.0024 max mem: 19788 +Epoch: [39] [1120/2138] eta: 0:49:02 lr: 9.261854177240348e-07 loss: 0.0168 (0.0174) time: 2.9836 data: 0.0024 max mem: 19788 +Epoch: [39] [1130/2138] eta: 0:48:34 lr: 9.179850423285137e-07 loss: 0.0160 (0.0174) time: 3.0530 data: 0.0026 max mem: 19788 +Epoch: [39] [1140/2138] eta: 0:48:05 lr: 9.097765193757906e-07 loss: 0.0177 (0.0174) time: 2.9507 data: 0.0025 max mem: 19788 +Epoch: [39] [1150/2138] eta: 0:47:35 lr: 9.015597589249747e-07 loss: 0.0157 (0.0174) time: 2.8355 data: 0.0024 max mem: 19788 +Epoch: [39] [1160/2138] eta: 0:47:06 lr: 8.933346691204408e-07 loss: 0.0153 (0.0174) time: 2.8386 data: 0.0024 max mem: 19788 +Epoch: [39] [1170/2138] eta: 0:46:37 lr: 8.851011561311062e-07 loss: 0.0167 (0.0174) time: 2.8327 data: 0.0026 max mem: 19788 +Epoch: [39] [1180/2138] eta: 0:46:07 lr: 8.768591240869986e-07 loss: 0.0165 (0.0174) time: 2.8253 data: 0.0027 max mem: 19788 +Epoch: [39] [1190/2138] eta: 0:45:38 lr: 8.686084750132372e-07 loss: 0.0161 (0.0174) time: 2.8275 data: 0.0026 max mem: 19788 +Epoch: [39] [1200/2138] eta: 0:45:09 lr: 8.603491087610217e-07 loss: 0.0158 (0.0174) time: 2.8301 data: 0.0024 max mem: 19788 +Epoch: [39] [1210/2138] eta: 0:44:41 lr: 8.520809229357311e-07 loss: 0.0162 (0.0174) time: 2.9433 data: 0.0023 max mem: 19788 +Epoch: [39] [1220/2138] eta: 0:44:13 lr: 8.438038128217101e-07 loss: 0.0168 (0.0174) time: 3.0351 data: 0.0022 max mem: 19788 +Epoch: [39] [1230/2138] eta: 0:43:46 lr: 8.3551767130382e-07 loss: 0.0150 (0.0174) time: 3.0637 data: 0.0023 max mem: 19788 +Epoch: [39] [1240/2138] eta: 0:43:17 lr: 8.27222388785312e-07 loss: 0.0164 (0.0174) time: 3.0353 data: 0.0023 max mem: 19788 +Epoch: [39] [1250/2138] eta: 0:42:49 lr: 8.189178531020726e-07 loss: 0.0164 (0.0174) time: 2.9739 data: 0.0024 max mem: 19788 +Epoch: [39] [1260/2138] eta: 0:42:20 lr: 8.106039494327827e-07 loss: 0.0155 (0.0174) time: 2.9624 data: 0.0024 max mem: 19788 +Epoch: [39] [1270/2138] eta: 0:41:51 lr: 8.02280560204954e-07 loss: 0.0155 (0.0174) time: 2.9012 data: 0.0023 max mem: 19788 +Epoch: [39] [1280/2138] eta: 0:41:22 lr: 7.939475649965178e-07 loss: 0.0162 (0.0174) time: 2.8859 data: 0.0024 max mem: 19788 +Epoch: [39] [1290/2138] eta: 0:40:53 lr: 7.856048404326239e-07 loss: 0.0168 (0.0174) time: 2.8921 data: 0.0024 max mem: 19788 +Epoch: [39] [1300/2138] eta: 0:40:24 lr: 7.772522600775587e-07 loss: 0.0154 (0.0173) time: 2.8788 data: 0.0024 max mem: 19788 +Epoch: [39] [1310/2138] eta: 0:39:55 lr: 7.688896943212389e-07 loss: 0.0167 (0.0173) time: 2.8700 data: 0.0021 max mem: 19788 +Epoch: [39] [1320/2138] eta: 0:39:26 lr: 7.605170102602012e-07 loss: 0.0168 (0.0173) time: 2.8668 data: 0.0022 max mem: 19788 +Epoch: [39] [1330/2138] eta: 0:38:57 lr: 7.521340715724864e-07 loss: 0.0162 (0.0173) time: 2.8770 data: 0.0023 max mem: 19788 +Epoch: [39] [1340/2138] eta: 0:38:28 lr: 7.437407383862923e-07 loss: 0.0173 (0.0174) time: 2.9114 data: 0.0024 max mem: 19788 +Epoch: [39] [1350/2138] eta: 0:38:00 lr: 7.353368671417338e-07 loss: 0.0181 (0.0174) time: 2.9698 data: 0.0026 max mem: 19788 +Epoch: [39] [1360/2138] eta: 0:37:31 lr: 7.269223104455271e-07 loss: 0.0179 (0.0174) time: 2.9327 data: 0.0025 max mem: 19788 +Epoch: [39] [1370/2138] eta: 0:37:02 lr: 7.18496916917868e-07 loss: 0.0169 (0.0174) time: 2.8756 data: 0.0022 max mem: 19788 +Epoch: [39] [1380/2138] eta: 0:36:33 lr: 7.100605310312515e-07 loss: 0.0169 (0.0174) time: 2.8821 data: 0.0022 max mem: 19788 +Epoch: [39] [1390/2138] eta: 0:36:04 lr: 7.016129929404212e-07 loss: 0.0168 (0.0174) time: 2.8715 data: 0.0022 max mem: 19788 +Epoch: [39] [1400/2138] eta: 0:35:35 lr: 6.931541383031113e-07 loss: 0.0163 (0.0174) time: 2.8656 data: 0.0021 max mem: 19788 +Epoch: [39] [1410/2138] eta: 0:35:06 lr: 6.846837980906752e-07 loss: 0.0154 (0.0174) time: 2.8660 data: 0.0022 max mem: 19788 +Epoch: [39] [1420/2138] eta: 0:34:37 lr: 6.762017983881569e-07 loss: 0.0154 (0.0174) time: 2.8883 data: 0.0022 max mem: 19788 +Epoch: [39] [1430/2138] eta: 0:34:08 lr: 6.677079601827898e-07 loss: 0.0154 (0.0174) time: 2.9119 data: 0.0021 max mem: 19788 +Epoch: [39] [1440/2138] eta: 0:33:40 lr: 6.5920209914035e-07 loss: 0.0167 (0.0174) time: 2.9682 data: 0.0022 max mem: 19788 +Epoch: [39] [1450/2138] eta: 0:33:11 lr: 6.50684025368211e-07 loss: 0.0185 (0.0174) time: 2.9572 data: 0.0024 max mem: 19788 +Epoch: [39] [1460/2138] eta: 0:32:42 lr: 6.421535431643774e-07 loss: 0.0169 (0.0174) time: 2.8807 data: 0.0025 max mem: 19788 +Epoch: [39] [1470/2138] eta: 0:32:13 lr: 6.336104507511724e-07 loss: 0.0154 (0.0174) time: 2.8728 data: 0.0024 max mem: 19788 +Epoch: [39] [1480/2138] eta: 0:31:44 lr: 6.250545399926742e-07 loss: 0.0152 (0.0174) time: 2.8735 data: 0.0023 max mem: 19788 +Epoch: [39] [1490/2138] eta: 0:31:15 lr: 6.164855960943685e-07 loss: 0.0160 (0.0174) time: 2.8706 data: 0.0023 max mem: 19788 +Epoch: [39] [1500/2138] eta: 0:30:46 lr: 6.079033972838832e-07 loss: 0.0174 (0.0174) time: 2.8703 data: 0.0023 max mem: 19788 +Epoch: [39] [1510/2138] eta: 0:30:17 lr: 5.993077144710203e-07 loss: 0.0166 (0.0174) time: 2.8702 data: 0.0025 max mem: 19788 +Epoch: [39] [1520/2138] eta: 0:29:48 lr: 5.906983108856695e-07 loss: 0.0175 (0.0174) time: 2.8910 data: 0.0027 max mem: 19788 +Epoch: [39] [1530/2138] eta: 0:29:19 lr: 5.820749416915006e-07 loss: 0.0177 (0.0174) time: 2.9359 data: 0.0026 max mem: 19788 +Epoch: [39] [1540/2138] eta: 0:28:50 lr: 5.734373535736714e-07 loss: 0.0173 (0.0174) time: 2.9353 data: 0.0025 max mem: 19788 +Epoch: [39] [1550/2138] eta: 0:28:21 lr: 5.647852842980559e-07 loss: 0.0173 (0.0174) time: 2.8953 data: 0.0025 max mem: 19788 +Epoch: [39] [1560/2138] eta: 0:27:52 lr: 5.561184622397874e-07 loss: 0.0178 (0.0174) time: 2.8735 data: 0.0027 max mem: 19788 +Epoch: [39] [1570/2138] eta: 0:27:23 lr: 5.474366058781372e-07 loss: 0.0182 (0.0174) time: 2.8653 data: 0.0027 max mem: 19788 +Epoch: [39] [1580/2138] eta: 0:26:54 lr: 5.387394232549124e-07 loss: 0.0173 (0.0174) time: 2.8640 data: 0.0026 max mem: 19788 +Epoch: [39] [1590/2138] eta: 0:26:25 lr: 5.300266113929408e-07 loss: 0.0173 (0.0174) time: 2.8676 data: 0.0026 max mem: 19788 +Epoch: [39] [1600/2138] eta: 0:25:56 lr: 5.212978556708312e-07 loss: 0.0182 (0.0174) time: 2.8748 data: 0.0025 max mem: 19788 +Epoch: [39] [1610/2138] eta: 0:25:27 lr: 5.12552829150069e-07 loss: 0.0188 (0.0174) time: 2.8943 data: 0.0025 max mem: 19788 +Epoch: [39] [1620/2138] eta: 0:24:59 lr: 5.037911918495582e-07 loss: 0.0147 (0.0174) time: 2.9411 data: 0.0026 max mem: 19788 +Epoch: [39] [1630/2138] eta: 0:24:30 lr: 4.950125899626973e-07 loss: 0.0150 (0.0174) time: 2.9233 data: 0.0024 max mem: 19788 +Epoch: [39] [1640/2138] eta: 0:24:01 lr: 4.862166550109214e-07 loss: 0.0172 (0.0174) time: 2.8781 data: 0.0025 max mem: 19788 +Epoch: [39] [1650/2138] eta: 0:23:32 lr: 4.774030029274631e-07 loss: 0.0174 (0.0174) time: 2.8836 data: 0.0026 max mem: 19788 +Epoch: [39] [1660/2138] eta: 0:23:03 lr: 4.685712330637316e-07 loss: 0.0183 (0.0174) time: 2.8837 data: 0.0028 max mem: 19788 +Epoch: [39] [1670/2138] eta: 0:22:34 lr: 4.5972092711030764e-07 loss: 0.0170 (0.0174) time: 2.8721 data: 0.0028 max mem: 19788 +Epoch: [39] [1680/2138] eta: 0:22:05 lr: 4.5085164792293195e-07 loss: 0.0152 (0.0174) time: 2.8736 data: 0.0025 max mem: 19788 +Epoch: [39] [1690/2138] eta: 0:21:36 lr: 4.419629382431529e-07 loss: 0.0163 (0.0174) time: 2.8725 data: 0.0023 max mem: 19788 +Epoch: [39] [1700/2138] eta: 0:21:07 lr: 4.3305431930131103e-07 loss: 0.0162 (0.0174) time: 2.8768 data: 0.0022 max mem: 19788 +Epoch: [39] [1710/2138] eta: 0:20:38 lr: 4.241252892883906e-07 loss: 0.0171 (0.0174) time: 2.9876 data: 0.0023 max mem: 19788 +Epoch: [39] [1720/2138] eta: 0:20:09 lr: 4.151753216807653e-07 loss: 0.0192 (0.0174) time: 2.9774 data: 0.0023 max mem: 19788 +Epoch: [39] [1730/2138] eta: 0:19:40 lr: 4.062038634001008e-07 loss: 0.0170 (0.0174) time: 2.8889 data: 0.0027 max mem: 19788 +Epoch: [39] [1740/2138] eta: 0:19:11 lr: 3.972103327874347e-07 loss: 0.0158 (0.0174) time: 2.8970 data: 0.0029 max mem: 19788 +Epoch: [39] [1750/2138] eta: 0:18:42 lr: 3.8819411736780753e-07 loss: 0.0171 (0.0174) time: 2.8776 data: 0.0026 max mem: 19788 +Epoch: [39] [1760/2138] eta: 0:18:13 lr: 3.791545713774987e-07 loss: 0.0171 (0.0174) time: 2.8657 data: 0.0025 max mem: 19788 +Epoch: [39] [1770/2138] eta: 0:17:44 lr: 3.700910130219835e-07 loss: 0.0165 (0.0174) time: 2.8722 data: 0.0025 max mem: 19788 +Epoch: [39] [1780/2138] eta: 0:17:15 lr: 3.610027214268202e-07 loss: 0.0148 (0.0174) time: 2.8794 data: 0.0027 max mem: 19788 +Epoch: [39] [1790/2138] eta: 0:16:47 lr: 3.5188893323780186e-07 loss: 0.0148 (0.0174) time: 2.8934 data: 0.0028 max mem: 19788 +Epoch: [39] [1800/2138] eta: 0:16:18 lr: 3.4274883881841556e-07 loss: 0.0191 (0.0174) time: 2.9608 data: 0.0027 max mem: 19788 +Epoch: [39] [1810/2138] eta: 0:15:49 lr: 3.335815779838248e-07 loss: 0.0182 (0.0174) time: 2.9459 data: 0.0027 max mem: 19788 +Epoch: [39] [1820/2138] eta: 0:15:20 lr: 3.243862351986195e-07 loss: 0.0160 (0.0174) time: 2.8711 data: 0.0026 max mem: 19788 +Epoch: [39] [1830/2138] eta: 0:14:51 lr: 3.1516183415215e-07 loss: 0.0167 (0.0174) time: 2.8644 data: 0.0023 max mem: 19788 +Epoch: [39] [1840/2138] eta: 0:14:22 lr: 3.0590733160747654e-07 loss: 0.0179 (0.0174) time: 2.8595 data: 0.0021 max mem: 19788 +Epoch: [39] [1850/2138] eta: 0:13:53 lr: 2.9662161039916844e-07 loss: 0.0188 (0.0174) time: 2.8648 data: 0.0022 max mem: 19788 +Epoch: [39] [1860/2138] eta: 0:13:24 lr: 2.873034714279703e-07 loss: 0.0161 (0.0174) time: 2.8717 data: 0.0023 max mem: 19788 +Epoch: [39] [1870/2138] eta: 0:12:55 lr: 2.7795162446739944e-07 loss: 0.0168 (0.0174) time: 2.8711 data: 0.0024 max mem: 19788 +Epoch: [39] [1880/2138] eta: 0:12:26 lr: 2.685646775543319e-07 loss: 0.0151 (0.0174) time: 2.8771 data: 0.0024 max mem: 19788 +Epoch: [39] [1890/2138] eta: 0:11:57 lr: 2.5914112468189935e-07 loss: 0.0144 (0.0174) time: 2.9814 data: 0.0022 max mem: 19788 +Epoch: [39] [1900/2138] eta: 0:11:28 lr: 2.4967933144283587e-07 loss: 0.0158 (0.0174) time: 2.9726 data: 0.0021 max mem: 19788 +Epoch: [39] [1910/2138] eta: 0:10:59 lr: 2.4017751818051645e-07 loss: 0.0162 (0.0174) time: 2.8695 data: 0.0021 max mem: 19788 +Epoch: [39] [1920/2138] eta: 0:10:30 lr: 2.3063374008579354e-07 loss: 0.0158 (0.0174) time: 2.8849 data: 0.0023 max mem: 19788 +Epoch: [39] [1930/2138] eta: 0:10:01 lr: 2.2104586351851978e-07 loss: 0.0159 (0.0174) time: 2.8873 data: 0.0027 max mem: 19788 +Epoch: [39] [1940/2138] eta: 0:09:33 lr: 2.1141153761978375e-07 loss: 0.0166 (0.0174) time: 2.8839 data: 0.0024 max mem: 19788 +Epoch: [39] [1950/2138] eta: 0:09:04 lr: 2.0172815998954485e-07 loss: 0.0173 (0.0174) time: 2.8793 data: 0.0021 max mem: 19788 +Epoch: [39] [1960/2138] eta: 0:08:35 lr: 1.9199283480312792e-07 loss: 0.0172 (0.0174) time: 2.8725 data: 0.0024 max mem: 19788 +Epoch: [39] [1970/2138] eta: 0:08:06 lr: 1.822023211754555e-07 loss: 0.0150 (0.0174) time: 2.8893 data: 0.0025 max mem: 19788 +Epoch: [39] [1980/2138] eta: 0:07:37 lr: 1.7235296877704624e-07 loss: 0.0155 (0.0174) time: 2.9411 data: 0.0027 max mem: 19788 +Epoch: [39] [1990/2138] eta: 0:07:08 lr: 1.6244063653278367e-07 loss: 0.0164 (0.0174) time: 2.9289 data: 0.0029 max mem: 19788 +Epoch: [39] [2000/2138] eta: 0:06:39 lr: 1.5246058849162085e-07 loss: 0.0170 (0.0174) time: 2.8764 data: 0.0029 max mem: 19788 +Epoch: [39] [2010/2138] eta: 0:06:10 lr: 1.4240735829943892e-07 loss: 0.0174 (0.0174) time: 2.8751 data: 0.0029 max mem: 19788 +Epoch: [39] [2020/2138] eta: 0:05:41 lr: 1.3227456955259268e-07 loss: 0.0181 (0.0174) time: 2.8703 data: 0.0027 max mem: 19788 +Epoch: [39] [2030/2138] eta: 0:05:12 lr: 1.220546926024544e-07 loss: 0.0165 (0.0174) time: 2.8652 data: 0.0024 max mem: 19788 +Epoch: [39] [2040/2138] eta: 0:04:43 lr: 1.1173870716487489e-07 loss: 0.0165 (0.0174) time: 2.8776 data: 0.0025 max mem: 19788 +Epoch: [39] [2050/2138] eta: 0:04:14 lr: 1.013156205312557e-07 loss: 0.0163 (0.0174) time: 2.8805 data: 0.0026 max mem: 19788 +Epoch: [39] [2060/2138] eta: 0:03:45 lr: 9.077175536454375e-08 loss: 0.0158 (0.0174) time: 2.8869 data: 0.0026 max mem: 19788 +Epoch: [39] [2070/2138] eta: 0:03:16 lr: 8.00896514809128e-08 loss: 0.0158 (0.0174) time: 2.9659 data: 0.0026 max mem: 19788 +Epoch: [39] [2080/2138] eta: 0:02:47 lr: 6.924628063148144e-08 loss: 0.0155 (0.0174) time: 2.9685 data: 0.0023 max mem: 19788 +Epoch: [39] [2090/2138] eta: 0:02:18 lr: 5.820994024959554e-08 loss: 0.0159 (0.0174) time: 2.8891 data: 0.0021 max mem: 19788 +Epoch: [39] [2100/2138] eta: 0:01:49 lr: 4.693433112807911e-08 loss: 0.0179 (0.0174) time: 2.8736 data: 0.0023 max mem: 19788 +Epoch: [39] [2110/2138] eta: 0:01:21 lr: 3.5345690402822716e-08 loss: 0.0185 (0.0174) time: 2.8716 data: 0.0026 max mem: 19788 +Epoch: [39] [2120/2138] eta: 0:00:52 lr: 2.330843478335392e-08 loss: 0.0213 (0.0175) time: 2.8661 data: 0.0025 max mem: 19788 +Epoch: [39] [2130/2138] eta: 0:00:23 lr: 1.048811202260214e-08 loss: 0.0194 (0.0175) time: 2.8699 data: 0.0022 max mem: 19788 +Epoch: [39] Total time: 1:43:07 +Test: [ 0/21770] eta: 16:47:37 time: 2.7771 data: 2.6449 max mem: 19788 +Test: [ 100/21770] eta: 0:27:14 time: 0.0521 data: 0.0018 max mem: 19788 +Test: [ 200/21770] eta: 0:21:57 time: 0.0418 data: 0.0014 max mem: 19788 +Test: [ 300/21770] eta: 0:20:24 time: 0.0470 data: 0.0017 max mem: 19788 +Test: [ 400/21770] eta: 0:19:12 time: 0.0497 data: 0.0017 max mem: 19788 +Test: [ 500/21770] eta: 0:18:20 time: 0.0436 data: 0.0015 max mem: 19788 +Test: [ 600/21770] eta: 0:17:52 time: 0.0439 data: 0.0015 max mem: 19788 +Test: [ 700/21770] eta: 0:17:31 time: 0.0426 data: 0.0015 max mem: 19788 +Test: [ 800/21770] eta: 0:17:17 time: 0.0442 data: 0.0014 max mem: 19788 +Test: [ 900/21770] eta: 0:17:02 time: 0.0485 data: 0.0016 max mem: 19788 +Test: [ 1000/21770] eta: 0:16:43 time: 0.0420 data: 0.0014 max mem: 19788 +Test: [ 1100/21770] eta: 0:16:29 time: 0.0455 data: 0.0014 max mem: 19788 +Test: [ 1200/21770] eta: 0:16:22 time: 0.0533 data: 0.0015 max mem: 19788 +Test: [ 1300/21770] eta: 0:16:17 time: 0.0441 data: 0.0017 max mem: 19788 +Test: [ 1400/21770] eta: 0:16:06 time: 0.0429 data: 0.0015 max mem: 19788 +Test: [ 1500/21770] eta: 0:15:59 time: 0.0438 data: 0.0014 max mem: 19788 +Test: [ 1600/21770] eta: 0:15:49 time: 0.0447 data: 0.0015 max mem: 19788 +Test: [ 1700/21770] eta: 0:15:47 time: 0.0536 data: 0.0017 max mem: 19788 +Test: [ 1800/21770] eta: 0:15:39 time: 0.0430 data: 0.0017 max mem: 19788 +Test: [ 1900/21770] eta: 0:15:33 time: 0.0425 data: 0.0014 max mem: 19788 +Test: [ 2000/21770] eta: 0:15:26 time: 0.0448 data: 0.0015 max mem: 19788 +Test: [ 2100/21770] eta: 0:15:24 time: 0.0478 data: 0.0015 max mem: 19788 +Test: [ 2200/21770] eta: 0:15:20 time: 0.0454 data: 0.0015 max mem: 19788 +Test: [ 2300/21770] eta: 0:15:13 time: 0.0433 data: 0.0017 max mem: 19788 +Test: [ 2400/21770] eta: 0:15:08 time: 0.0435 data: 0.0015 max mem: 19788 +Test: [ 2500/21770] eta: 0:15:02 time: 0.0445 data: 0.0013 max mem: 19788 +Test: [ 2600/21770] eta: 0:14:56 time: 0.0444 data: 0.0016 max mem: 19788 +Test: [ 2700/21770] eta: 0:14:51 time: 0.0441 data: 0.0014 max mem: 19788 +Test: [ 2800/21770] eta: 0:14:48 time: 0.0520 data: 0.0017 max mem: 19788 +Test: [ 2900/21770] eta: 0:14:44 time: 0.0442 data: 0.0016 max mem: 19788 +Test: [ 3000/21770] eta: 0:14:38 time: 0.0472 data: 0.0015 max mem: 19788 +Test: [ 3100/21770] eta: 0:14:34 time: 0.0428 data: 0.0014 max mem: 19788 +Test: [ 3200/21770] eta: 0:14:30 time: 0.0480 data: 0.0016 max mem: 19788 +Test: [ 3300/21770] eta: 0:14:26 time: 0.0545 data: 0.0014 max mem: 19788 +Test: [ 3400/21770] eta: 0:14:21 time: 0.0438 data: 0.0016 max mem: 19788 +Test: [ 3500/21770] eta: 0:14:17 time: 0.0483 data: 0.0016 max mem: 19788 +Test: [ 3600/21770] eta: 0:14:12 time: 0.0431 data: 0.0014 max mem: 19788 +Test: [ 3700/21770] eta: 0:14:06 time: 0.0443 data: 0.0016 max mem: 19788 +Test: [ 3800/21770] eta: 0:14:00 time: 0.0446 data: 0.0013 max mem: 19788 +Test: [ 3900/21770] eta: 0:13:55 time: 0.0494 data: 0.0017 max mem: 19788 +Test: [ 4000/21770] eta: 0:13:52 time: 0.0494 data: 0.0016 max mem: 19788 +Test: [ 4100/21770] eta: 0:13:46 time: 0.0455 data: 0.0018 max mem: 19788 +Test: [ 4200/21770] eta: 0:13:42 time: 0.0502 data: 0.0016 max mem: 19788 +Test: [ 4300/21770] eta: 0:13:37 time: 0.0496 data: 0.0016 max mem: 19788 +Test: [ 4400/21770] eta: 0:13:33 time: 0.0454 data: 0.0017 max mem: 19788 +Test: [ 4500/21770] eta: 0:13:28 time: 0.0439 data: 0.0014 max mem: 19788 +Test: [ 4600/21770] eta: 0:13:24 time: 0.0487 data: 0.0017 max mem: 19788 +Test: [ 4700/21770] eta: 0:13:18 time: 0.0430 data: 0.0015 max mem: 19788 +Test: [ 4800/21770] eta: 0:13:14 time: 0.0510 data: 0.0017 max mem: 19788 +Test: [ 4900/21770] eta: 0:13:09 time: 0.0443 data: 0.0015 max mem: 19788 +Test: [ 5000/21770] eta: 0:13:05 time: 0.0522 data: 0.0018 max mem: 19788 +Test: [ 5100/21770] eta: 0:13:01 time: 0.0445 data: 0.0013 max mem: 19788 +Test: [ 5200/21770] eta: 0:12:56 time: 0.0468 data: 0.0017 max mem: 19788 +Test: [ 5300/21770] eta: 0:12:51 time: 0.0442 data: 0.0016 max mem: 19788 +Test: [ 5400/21770] eta: 0:12:46 time: 0.0524 data: 0.0017 max mem: 19788 +Test: [ 5500/21770] eta: 0:12:41 time: 0.0445 data: 0.0016 max mem: 19788 +Test: [ 5600/21770] eta: 0:12:36 time: 0.0481 data: 0.0017 max mem: 19788 +Test: [ 5700/21770] eta: 0:12:31 time: 0.0488 data: 0.0016 max mem: 19788 +Test: [ 5800/21770] eta: 0:12:27 time: 0.0467 data: 0.0016 max mem: 19788 +Test: [ 5900/21770] eta: 0:12:22 time: 0.0460 data: 0.0015 max mem: 19788 +Test: [ 6000/21770] eta: 0:12:16 time: 0.0425 data: 0.0014 max mem: 19788 +Test: [ 6100/21770] eta: 0:12:11 time: 0.0470 data: 0.0016 max mem: 19788 +Test: [ 6200/21770] eta: 0:12:06 time: 0.0435 data: 0.0014 max mem: 19788 +Test: [ 6300/21770] eta: 0:12:01 time: 0.0441 data: 0.0016 max mem: 19788 +Test: [ 6400/21770] eta: 0:11:56 time: 0.0440 data: 0.0014 max mem: 19788 +Test: [ 6500/21770] eta: 0:11:51 time: 0.0437 data: 0.0013 max mem: 19788 +Test: [ 6600/21770] eta: 0:11:46 time: 0.0423 data: 0.0013 max mem: 19788 +Test: [ 6700/21770] eta: 0:11:41 time: 0.0478 data: 0.0017 max mem: 19788 +Test: [ 6800/21770] eta: 0:11:38 time: 0.0538 data: 0.0017 max mem: 19788 +Test: [ 6900/21770] eta: 0:11:34 time: 0.0510 data: 0.0017 max mem: 19788 +Test: [ 7000/21770] eta: 0:11:29 time: 0.0456 data: 0.0017 max mem: 19788 +Test: [ 7100/21770] eta: 0:11:25 time: 0.0506 data: 0.0018 max mem: 19788 +Test: [ 7200/21770] eta: 0:11:21 time: 0.0446 data: 0.0015 max mem: 19788 +Test: [ 7300/21770] eta: 0:11:16 time: 0.0447 data: 0.0014 max mem: 19788 +Test: [ 7400/21770] eta: 0:11:11 time: 0.0443 data: 0.0015 max mem: 19788 +Test: [ 7500/21770] eta: 0:11:06 time: 0.0443 data: 0.0015 max mem: 19788 +Test: [ 7600/21770] eta: 0:11:01 time: 0.0493 data: 0.0017 max mem: 19788 +Test: [ 7700/21770] eta: 0:10:57 time: 0.0528 data: 0.0017 max mem: 19788 +Test: [ 7800/21770] eta: 0:10:53 time: 0.0434 data: 0.0017 max mem: 19788 +Test: [ 7900/21770] eta: 0:10:47 time: 0.0448 data: 0.0014 max mem: 19788 +Test: [ 8000/21770] eta: 0:10:43 time: 0.0499 data: 0.0016 max mem: 19788 +Test: [ 8100/21770] eta: 0:10:38 time: 0.0489 data: 0.0016 max mem: 19788 +Test: [ 8200/21770] eta: 0:10:33 time: 0.0458 data: 0.0015 max mem: 19788 +Test: [ 8300/21770] eta: 0:10:29 time: 0.0435 data: 0.0017 max mem: 19788 +Test: [ 8400/21770] eta: 0:10:24 time: 0.0435 data: 0.0013 max mem: 19788 +Test: [ 8500/21770] eta: 0:10:19 time: 0.0438 data: 0.0015 max mem: 19788 +Test: [ 8600/21770] eta: 0:10:14 time: 0.0439 data: 0.0014 max mem: 19788 +Test: [ 8700/21770] eta: 0:10:09 time: 0.0447 data: 0.0014 max mem: 19788 +Test: [ 8800/21770] eta: 0:10:05 time: 0.0432 data: 0.0014 max mem: 19788 +Test: [ 8900/21770] eta: 0:10:00 time: 0.0461 data: 0.0017 max mem: 19788 +Test: [ 9000/21770] eta: 0:09:55 time: 0.0443 data: 0.0015 max mem: 19788 +Test: [ 9100/21770] eta: 0:09:50 time: 0.0434 data: 0.0013 max mem: 19788 +Test: [ 9200/21770] eta: 0:09:46 time: 0.0456 data: 0.0015 max mem: 19788 +Test: [ 9300/21770] eta: 0:09:41 time: 0.0471 data: 0.0017 max mem: 19788 +Test: [ 9400/21770] eta: 0:09:36 time: 0.0439 data: 0.0014 max mem: 19788 +Test: [ 9500/21770] eta: 0:09:32 time: 0.0479 data: 0.0017 max mem: 19788 +Test: [ 9600/21770] eta: 0:09:27 time: 0.0478 data: 0.0016 max mem: 19788 +Test: [ 9700/21770] eta: 0:09:22 time: 0.0518 data: 0.0017 max mem: 19788 +Test: [ 9800/21770] eta: 0:09:18 time: 0.0434 data: 0.0014 max mem: 19788 +Test: [ 9900/21770] eta: 0:09:13 time: 0.0513 data: 0.0015 max mem: 19788 +Test: [10000/21770] eta: 0:09:08 time: 0.0453 data: 0.0013 max mem: 19788 +Test: [10100/21770] eta: 0:09:04 time: 0.0525 data: 0.0017 max mem: 19788 +Test: [10200/21770] eta: 0:08:59 time: 0.0445 data: 0.0014 max mem: 19788 +Test: [10300/21770] eta: 0:08:55 time: 0.0499 data: 0.0016 max mem: 19788 +Test: [10400/21770] eta: 0:08:50 time: 0.0454 data: 0.0015 max mem: 19788 +Test: [10500/21770] eta: 0:08:45 time: 0.0460 data: 0.0015 max mem: 19788 +Test: [10600/21770] eta: 0:08:41 time: 0.0532 data: 0.0016 max mem: 19788 +Test: [10700/21770] eta: 0:08:37 time: 0.0520 data: 0.0018 max mem: 19788 +Test: [10800/21770] eta: 0:08:32 time: 0.0482 data: 0.0015 max mem: 19788 +Test: [10900/21770] eta: 0:08:27 time: 0.0446 data: 0.0015 max mem: 19788 +Test: [11000/21770] eta: 0:08:23 time: 0.0525 data: 0.0017 max mem: 19788 +Test: [11100/21770] eta: 0:08:18 time: 0.0462 data: 0.0016 max mem: 19788 +Test: [11200/21770] eta: 0:08:13 time: 0.0473 data: 0.0017 max mem: 19788 +Test: [11300/21770] eta: 0:08:09 time: 0.0455 data: 0.0016 max mem: 19788 +Test: [11400/21770] eta: 0:08:04 time: 0.0489 data: 0.0017 max mem: 19788 +Test: [11500/21770] eta: 0:07:59 time: 0.0447 data: 0.0014 max mem: 19788 +Test: [11600/21770] eta: 0:07:55 time: 0.0478 data: 0.0015 max mem: 19788 +Test: [11700/21770] eta: 0:07:50 time: 0.0430 data: 0.0013 max mem: 19788 +Test: [11800/21770] eta: 0:07:45 time: 0.0519 data: 0.0017 max mem: 19788 +Test: [11900/21770] eta: 0:07:41 time: 0.0493 data: 0.0017 max mem: 19788 +Test: [12000/21770] eta: 0:07:36 time: 0.0444 data: 0.0016 max mem: 19788 +Test: [12100/21770] eta: 0:07:31 time: 0.0454 data: 0.0015 max mem: 19788 +Test: [12200/21770] eta: 0:07:27 time: 0.0495 data: 0.0016 max mem: 19788 +Test: [12300/21770] eta: 0:07:22 time: 0.0464 data: 0.0017 max mem: 19788 +Test: [12400/21770] eta: 0:07:18 time: 0.0453 data: 0.0016 max mem: 19788 +Test: [12500/21770] eta: 0:07:13 time: 0.0532 data: 0.0019 max mem: 19788 +Test: [12600/21770] eta: 0:07:09 time: 0.0529 data: 0.0018 max mem: 19788 +Test: [12700/21770] eta: 0:07:04 time: 0.0447 data: 0.0016 max mem: 19788 +Test: [12800/21770] eta: 0:06:59 time: 0.0459 data: 0.0016 max mem: 19788 +Test: [12900/21770] eta: 0:06:55 time: 0.0439 data: 0.0014 max mem: 19788 +Test: [13000/21770] eta: 0:06:50 time: 0.0438 data: 0.0015 max mem: 19788 +Test: [13100/21770] eta: 0:06:45 time: 0.0531 data: 0.0018 max mem: 19788 +Test: [13200/21770] eta: 0:06:41 time: 0.0481 data: 0.0017 max mem: 19788 +Test: [13300/21770] eta: 0:06:36 time: 0.0507 data: 0.0016 max mem: 19788 +Test: [13400/21770] eta: 0:06:32 time: 0.0472 data: 0.0015 max mem: 19788 +Test: [13500/21770] eta: 0:06:27 time: 0.0531 data: 0.0015 max mem: 19788 +Test: [13600/21770] eta: 0:06:23 time: 0.0436 data: 0.0015 max mem: 19788 +Test: [13700/21770] eta: 0:06:18 time: 0.0440 data: 0.0016 max mem: 19788 +Test: [13800/21770] eta: 0:06:13 time: 0.0546 data: 0.0017 max mem: 19788 +Test: [13900/21770] eta: 0:06:09 time: 0.0454 data: 0.0014 max mem: 19788 +Test: [14000/21770] eta: 0:06:04 time: 0.0428 data: 0.0014 max mem: 19788 +Test: [14100/21770] eta: 0:05:59 time: 0.0458 data: 0.0015 max mem: 19788 +Test: [14200/21770] eta: 0:05:54 time: 0.0447 data: 0.0013 max mem: 19788 +Test: [14300/21770] eta: 0:05:50 time: 0.0524 data: 0.0017 max mem: 19788 +Test: [14400/21770] eta: 0:05:45 time: 0.0526 data: 0.0015 max mem: 19788 +Test: [14500/21770] eta: 0:05:40 time: 0.0475 data: 0.0016 max mem: 19788 +Test: [14600/21770] eta: 0:05:36 time: 0.0486 data: 0.0017 max mem: 19788 +Test: [14700/21770] eta: 0:05:31 time: 0.0438 data: 0.0013 max mem: 19788 +Test: [14800/21770] eta: 0:05:26 time: 0.0537 data: 0.0017 max mem: 19788 +Test: [14900/21770] eta: 0:05:22 time: 0.0498 data: 0.0016 max mem: 19788 +Test: [15000/21770] eta: 0:05:17 time: 0.0470 data: 0.0015 max mem: 19788 +Test: [15100/21770] eta: 0:05:12 time: 0.0530 data: 0.0019 max mem: 19788 +Test: [15200/21770] eta: 0:05:08 time: 0.0447 data: 0.0014 max mem: 19788 +Test: [15300/21770] eta: 0:05:03 time: 0.0440 data: 0.0015 max mem: 19788 +Test: [15400/21770] eta: 0:04:58 time: 0.0449 data: 0.0015 max mem: 19788 +Test: [15500/21770] eta: 0:04:53 time: 0.0447 data: 0.0014 max mem: 19788 +Test: [15600/21770] eta: 0:04:49 time: 0.0473 data: 0.0014 max mem: 19788 +Test: [15700/21770] eta: 0:04:44 time: 0.0441 data: 0.0015 max mem: 19788 +Test: [15800/21770] eta: 0:04:39 time: 0.0457 data: 0.0016 max mem: 19788 +Test: [15900/21770] eta: 0:04:34 time: 0.0437 data: 0.0016 max mem: 19788 +Test: [16000/21770] eta: 0:04:30 time: 0.0433 data: 0.0014 max mem: 19788 +Test: [16100/21770] eta: 0:04:25 time: 0.0452 data: 0.0015 max mem: 19788 +Test: [16200/21770] eta: 0:04:21 time: 0.0513 data: 0.0016 max mem: 19788 +Test: [16300/21770] eta: 0:04:16 time: 0.0527 data: 0.0018 max mem: 19788 +Test: [16400/21770] eta: 0:04:11 time: 0.0441 data: 0.0013 max mem: 19788 +Test: [16500/21770] eta: 0:04:07 time: 0.0440 data: 0.0017 max mem: 19788 +Test: [16600/21770] eta: 0:04:02 time: 0.0511 data: 0.0018 max mem: 19788 +Test: [16700/21770] eta: 0:03:57 time: 0.0436 data: 0.0015 max mem: 19788 +Test: [16800/21770] eta: 0:03:52 time: 0.0433 data: 0.0015 max mem: 19788 +Test: [16900/21770] eta: 0:03:48 time: 0.0458 data: 0.0017 max mem: 19788 +Test: [17000/21770] eta: 0:03:43 time: 0.0463 data: 0.0016 max mem: 19788 +Test: [17100/21770] eta: 0:03:38 time: 0.0522 data: 0.0018 max mem: 19788 +Test: [17200/21770] eta: 0:03:34 time: 0.0515 data: 0.0018 max mem: 19788 +Test: [17300/21770] eta: 0:03:29 time: 0.0427 data: 0.0014 max mem: 19788 +Test: [17400/21770] eta: 0:03:24 time: 0.0458 data: 0.0015 max mem: 19788 +Test: [17500/21770] eta: 0:03:20 time: 0.0429 data: 0.0014 max mem: 19788 +Test: [17600/21770] eta: 0:03:15 time: 0.0444 data: 0.0016 max mem: 19788 +Test: [17700/21770] eta: 0:03:10 time: 0.0539 data: 0.0017 max mem: 19788 +Test: [17800/21770] eta: 0:03:05 time: 0.0445 data: 0.0014 max mem: 19788 +Test: [17900/21770] eta: 0:03:01 time: 0.0424 data: 0.0014 max mem: 19788 +Test: [18000/21770] eta: 0:02:56 time: 0.0461 data: 0.0017 max mem: 19788 +Test: [18100/21770] eta: 0:02:51 time: 0.0440 data: 0.0014 max mem: 19788 +Test: [18200/21770] eta: 0:02:47 time: 0.0511 data: 0.0017 max mem: 19788 +Test: [18300/21770] eta: 0:02:42 time: 0.0448 data: 0.0014 max mem: 19788 +Test: [18400/21770] eta: 0:02:37 time: 0.0525 data: 0.0018 max mem: 19788 +Test: [18500/21770] eta: 0:02:33 time: 0.0460 data: 0.0014 max mem: 19788 +Test: [18600/21770] eta: 0:02:28 time: 0.0447 data: 0.0014 max mem: 19788 +Test: [18700/21770] eta: 0:02:23 time: 0.0520 data: 0.0019 max mem: 19788 +Test: [18800/21770] eta: 0:02:19 time: 0.0442 data: 0.0015 max mem: 19788 +Test: [18900/21770] eta: 0:02:14 time: 0.0517 data: 0.0017 max mem: 19788 +Test: [19000/21770] eta: 0:02:09 time: 0.0437 data: 0.0015 max mem: 19788 +Test: [19100/21770] eta: 0:02:05 time: 0.0445 data: 0.0014 max mem: 19788 +Test: [19200/21770] eta: 0:02:00 time: 0.0466 data: 0.0016 max mem: 19788 +Test: [19300/21770] eta: 0:01:55 time: 0.0510 data: 0.0016 max mem: 19788 +Test: [19400/21770] eta: 0:01:51 time: 0.0434 data: 0.0015 max mem: 19788 +Test: [19500/21770] eta: 0:01:46 time: 0.0514 data: 0.0019 max mem: 19788 +Test: [19600/21770] eta: 0:01:41 time: 0.0442 data: 0.0017 max mem: 19788 +Test: [19700/21770] eta: 0:01:37 time: 0.0440 data: 0.0015 max mem: 19788 +Test: [19800/21770] eta: 0:01:32 time: 0.0473 data: 0.0015 max mem: 19788 +Test: [19900/21770] eta: 0:01:27 time: 0.0446 data: 0.0014 max mem: 19788 +Test: [20000/21770] eta: 0:01:22 time: 0.0427 data: 0.0015 max mem: 19788 +Test: [20100/21770] eta: 0:01:18 time: 0.0442 data: 0.0014 max mem: 19788 +Test: [20200/21770] eta: 0:01:13 time: 0.0464 data: 0.0015 max mem: 19788 +Test: [20300/21770] eta: 0:01:08 time: 0.0439 data: 0.0014 max mem: 19788 +Test: [20400/21770] eta: 0:01:04 time: 0.0435 data: 0.0013 max mem: 19788 +Test: [20500/21770] eta: 0:00:59 time: 0.0444 data: 0.0013 max mem: 19788 +Test: [20600/21770] eta: 0:00:54 time: 0.0441 data: 0.0014 max mem: 19788 +Test: [20700/21770] eta: 0:00:50 time: 0.0528 data: 0.0018 max mem: 19788 +Test: [20800/21770] eta: 0:00:45 time: 0.0447 data: 0.0016 max mem: 19788 +Test: [20900/21770] eta: 0:00:40 time: 0.0520 data: 0.0018 max mem: 19788 +Test: [21000/21770] eta: 0:00:36 time: 0.0441 data: 0.0015 max mem: 19788 +Test: [21100/21770] eta: 0:00:31 time: 0.0443 data: 0.0013 max mem: 19788 +Test: [21200/21770] eta: 0:00:26 time: 0.0444 data: 0.0014 max mem: 19788 +Test: [21300/21770] eta: 0:00:22 time: 0.0480 data: 0.0015 max mem: 19788 +Test: [21400/21770] eta: 0:00:17 time: 0.0452 data: 0.0015 max mem: 19788 +Test: [21500/21770] eta: 0:00:12 time: 0.0438 data: 0.0015 max mem: 19788 +Test: [21600/21770] eta: 0:00:07 time: 0.0471 data: 0.0016 max mem: 19788 +Test: [21700/21770] eta: 0:00:03 time: 0.0434 data: 0.0015 max mem: 19788 +Test: Total time: 0:16:59 +Final results: +Mean IoU is 64.57 + + precision@0.5 = 71.96 + precision@0.6 = 66.68 + precision@0.7 = 60.12 + precision@0.8 = 49.55 + precision@0.9 = 24.25 + overall IoU = 65.25 + mean IoU = 64.57 + +Mean accuracy for one-to-zero sample is 87.58 + +Average object IoU 0.6457385957916628 +Overall IoU 65.24604797363281 +Better epoch: 39 + +Training time 3 days, 10:57:34 diff --git a/LAVT-RIS/logs/rzom_m10_mg12_tmp007_4gpu_bs32_anghf.log b/LAVT-RIS/logs/rzom_m10_mg12_tmp007_4gpu_bs32_anghf.log new file mode 100644 index 0000000000000000000000000000000000000000..b79b82cac5698527f6c7f5ca0b9fe1ed286479f1 --- /dev/null +++ b/LAVT-RIS/logs/rzom_m10_mg12_tmp007_4gpu_bs32_anghf.log @@ -0,0 +1,18048 @@ +[2025-01-26 10:06:23,538] torch.distributed.run: [WARNING] +[2025-01-26 10:06:23,538] torch.distributed.run: [WARNING] ***************************************** +[2025-01-26 10:06:23,538] torch.distributed.run: [WARNING] Setting OMP_NUM_THREADS environment variable for each process to be 1 in default, to avoid your system being overloaded, please further tune the variable for optimal performance in your application as needed. +[2025-01-26 10:06:23,538] torch.distributed.run: [WARNING] ***************************************** +/home/chaeyun/.conda/envs/risall/lib/python3.9/site-packages/timm/models/layers/__init__.py:48: FutureWarning: Importing from timm.models.layers is deprecated, please import via timm.layers + warnings.warn(f"Importing from {__name__} is deprecated, please import via timm.layers", FutureWarning) +/home/chaeyun/.conda/envs/risall/lib/python3.9/site-packages/timm/models/layers/__init__.py:48: FutureWarning: Importing from timm.models.layers is deprecated, please import via timm.layers + warnings.warn(f"Importing from {__name__} is deprecated, please import via timm.layers", FutureWarning) +/home/chaeyun/.conda/envs/risall/lib/python3.9/site-packages/timm/models/layers/__init__.py:48: FutureWarning: Importing from timm.models.layers is deprecated, please import via timm.layers + warnings.warn(f"Importing from {__name__} is deprecated, please import via timm.layers", FutureWarning) +/home/chaeyun/.conda/envs/risall/lib/python3.9/site-packages/timm/models/layers/__init__.py:48: FutureWarning: Importing from timm.models.layers is deprecated, please import via timm.layers + warnings.warn(f"Importing from {__name__} is deprecated, please import via timm.layers", FutureWarning) +Local Rank: 2, World Size: 4 +RANK and WORLD_SIZE in environment: 2/4 +Local Rank: 0, World Size: 4 +RANK and WORLD_SIZE in environment: 0/4 +Local Rank: 3, World Size: 4 +RANK and WORLD_SIZE in environment: 3/4 +Local Rank: 1, World Size: 4 +RANK and WORLD_SIZE in environment: 1/4 +Image size: 480 +Metric Learning Ops +metric learning flag : True +metric loss weight : 0.1 +metric mode and hardpos selection : hardpos_only naive +margin value : 12.0 +temperature : 0.07 +add zero in ACE loss : False +Namespace(amsgrad=False, batch_size=8, bert_tokenizer='bert-base-uncased', ck_bert='bert-base-uncased', dataset='ref-zom', ddp_trained_weights=False, device='cuda:0', epochs=40, fusion_drop=0.0, img_size=480, lr=5e-05, mha='', model='lavt_one', model_id='rzom_m10_mg12_tmp007_4gpu_bs32_anghf', output_dir='./models/rzom_m10_mg12_tmp007_4gpu_bs32_anghf', pin_mem=False, pretrained_swin_weights='./pretrained_weights/swin_base_patch4_window12_384_22k.pth', print_freq=10, refer_data_root='./refer/data/', resume='', split='test', splitBy='final', swin_type='base', weight_decay=0.01, window12=False, workers=8, metric_learning=True, metric_loss_weight=0.1, metric_mode='hardpos_only', exclude_multiobj=True, hn_prob=0.0, hp_selection='naive', margin_value=12.0, temperature=0.07, addzero=False, local_rank=0) +loading dataset ref-zom into memory... +loading dataset split final +creating index... +index created. +DONE (t=9.92s) +loading dataset ref-zom into memory... +loading dataset split final +creating index... +index created. +DONE (t=11.38s) +/home/chaeyun/.conda/envs/risall/lib/python3.9/site-packages/torch/functional.py:504: UserWarning: torch.meshgrid: in an upcoming release, it will be required to pass the indexing argument. (Triggered internally at ../aten/src/ATen/native/TensorShape.cpp:3526.) + return _VF.meshgrid(tensors, **kwargs) # type: ignore[attr-defined] +/home/chaeyun/.conda/envs/risall/lib/python3.9/site-packages/torch/functional.py:504: UserWarning: torch.meshgrid: in an upcoming release, it will be required to pass the indexing argument. (Triggered internally at ../aten/src/ATen/native/TensorShape.cpp:3526.) + return _VF.meshgrid(tensors, **kwargs) # type: ignore[attr-defined] +local rank 0 / global rank 0 successfully built train dataset. +lavt_one +Window size 12! +/home/chaeyun/.conda/envs/risall/lib/python3.9/site-packages/torch/functional.py:504: UserWarning: torch.meshgrid: in an upcoming release, it will be required to pass the indexing argument. (Triggered internally at ../aten/src/ATen/native/TensorShape.cpp:3526.) + return _VF.meshgrid(tensors, **kwargs) # type: ignore[attr-defined] +Initializing Multi-modal Swin Transformer weights from ./pretrained_weights/swin_base_patch4_window12_384_22k.pth +/home/chaeyun/.conda/envs/risall/lib/python3.9/site-packages/torch/functional.py:504: UserWarning: torch.meshgrid: in an upcoming release, it will be required to pass the indexing argument. (Triggered internally at ../aten/src/ATen/native/TensorShape.cpp:3526.) + return _VF.meshgrid(tensors, **kwargs) # type: ignore[attr-defined] +Epoch: [0] [ 0/2138] eta: 5:27:58 lr: 4.99994738069889e-05 loss: 0.6432 (0.6432) time: 9.2040 data: 3.3122 max mem: 17438 +Epoch: [0] [ 10/2138] eta: 2:25:39 lr: 4.999421184303536e-05 loss: 0.6149 (0.6138) time: 4.1069 data: 0.3047 max mem: 19773 +Epoch: [0] [ 20/2138] eta: 2:16:03 lr: 4.998894981754451e-05 loss: 0.5689 (0.5703) time: 3.5871 data: 0.0031 max mem: 19774 +Epoch: [0] [ 30/2138] eta: 2:12:33 lr: 4.998368773050842e-05 loss: 0.4650 (0.5256) time: 3.5891 data: 0.0027 max mem: 19778 +Epoch: [0] [ 40/2138] eta: 2:10:28 lr: 4.997842558191917e-05 loss: 0.3763 (0.4790) time: 3.6017 data: 0.0029 max mem: 19778 +Epoch: [0] [ 50/2138] eta: 2:09:01 lr: 4.9973163371768835e-05 loss: 0.3114 (0.4488) time: 3.6061 data: 0.0028 max mem: 19778 +Epoch: [0] [ 60/2138] eta: 2:07:51 lr: 4.9967901100049515e-05 loss: 0.2924 (0.4223) time: 3.6105 data: 0.0026 max mem: 19778 +Epoch: [0] [ 70/2138] eta: 2:06:50 lr: 4.996263876675326e-05 loss: 0.2628 (0.4005) time: 3.6100 data: 0.0026 max mem: 19778 +Epoch: [0] [ 80/2138] eta: 2:05:57 lr: 4.995737637187215e-05 loss: 0.2628 (0.3872) time: 3.6135 data: 0.0029 max mem: 19778 +Epoch: [0] [ 90/2138] eta: 2:05:15 lr: 4.995211391539826e-05 loss: 0.2709 (0.3774) time: 3.6322 data: 0.0030 max mem: 19778 +Epoch: [0] [ 100/2138] eta: 2:04:27 lr: 4.994685139732366e-05 loss: 0.2795 (0.3703) time: 3.6319 data: 0.0029 max mem: 19778 +Epoch: [0] [ 110/2138] eta: 2:03:43 lr: 4.994158881764041e-05 loss: 0.2871 (0.3638) time: 3.6183 data: 0.0030 max mem: 19779 +Epoch: [0] [ 120/2138] eta: 2:02:59 lr: 4.993632617634058e-05 loss: 0.2888 (0.3570) time: 3.6176 data: 0.0030 max mem: 19779 +Epoch: [0] [ 130/2138] eta: 2:02:17 lr: 4.9931063473416234e-05 loss: 0.2822 (0.3530) time: 3.6190 data: 0.0030 max mem: 19779 +Epoch: [0] [ 140/2138] eta: 2:01:34 lr: 4.992580070885944e-05 loss: 0.2537 (0.3470) time: 3.6160 data: 0.0031 max mem: 19779 +Epoch: [0] [ 150/2138] eta: 2:00:52 lr: 4.9920537882662235e-05 loss: 0.2451 (0.3406) time: 3.6093 data: 0.0029 max mem: 19779 +Epoch: [0] [ 160/2138] eta: 2:00:11 lr: 4.9915274994816705e-05 loss: 0.2366 (0.3364) time: 3.6090 data: 0.0031 max mem: 19779 +Epoch: [0] [ 170/2138] eta: 1:59:31 lr: 4.991001204531489e-05 loss: 0.2544 (0.3309) time: 3.6143 data: 0.0034 max mem: 19779 +Epoch: [0] [ 180/2138] eta: 1:58:51 lr: 4.990474903414884e-05 loss: 0.2425 (0.3266) time: 3.6134 data: 0.0031 max mem: 19779 +Epoch: [0] [ 190/2138] eta: 1:58:11 lr: 4.989948596131061e-05 loss: 0.2326 (0.3226) time: 3.6073 data: 0.0028 max mem: 19779 +Epoch: [0] [ 200/2138] eta: 1:57:31 lr: 4.9894222826792256e-05 loss: 0.2196 (0.3169) time: 3.6075 data: 0.0029 max mem: 19779 +Epoch: [0] [ 210/2138] eta: 1:56:52 lr: 4.988895963058582e-05 loss: 0.2336 (0.3150) time: 3.6080 data: 0.0029 max mem: 19780 +Epoch: [0] [ 220/2138] eta: 1:56:13 lr: 4.988369637268335e-05 loss: 0.2401 (0.3120) time: 3.6065 data: 0.0031 max mem: 19780 +Epoch: [0] [ 230/2138] eta: 1:55:34 lr: 4.987843305307689e-05 loss: 0.2421 (0.3107) time: 3.6058 data: 0.0031 max mem: 19780 +Epoch: [0] [ 240/2138] eta: 1:54:56 lr: 4.987316967175848e-05 loss: 0.2343 (0.3067) time: 3.6083 data: 0.0029 max mem: 19780 +Epoch: [0] [ 250/2138] eta: 1:54:17 lr: 4.986790622872016e-05 loss: 0.2333 (0.3041) time: 3.6060 data: 0.0028 max mem: 19780 +Epoch: [0] [ 260/2138] eta: 1:53:39 lr: 4.986264272395396e-05 loss: 0.2333 (0.3010) time: 3.6014 data: 0.0027 max mem: 19780 +Epoch: [0] [ 270/2138] eta: 1:53:00 lr: 4.9857379157451936e-05 loss: 0.2378 (0.2998) time: 3.6021 data: 0.0028 max mem: 19780 +Epoch: [0] [ 280/2138] eta: 1:52:22 lr: 4.98521155292061e-05 loss: 0.2392 (0.2968) time: 3.6035 data: 0.0030 max mem: 19780 +Epoch: [0] [ 290/2138] eta: 1:51:44 lr: 4.9846851839208495e-05 loss: 0.2153 (0.2947) time: 3.6042 data: 0.0031 max mem: 19780 +Epoch: [0] [ 300/2138] eta: 1:51:06 lr: 4.984158808745115e-05 loss: 0.2105 (0.2920) time: 3.6028 data: 0.0031 max mem: 19780 +Epoch: [0] [ 310/2138] eta: 1:50:29 lr: 4.98363242739261e-05 loss: 0.2062 (0.2890) time: 3.6021 data: 0.0032 max mem: 19780 +Epoch: [0] [ 320/2138] eta: 1:49:51 lr: 4.9831060398625355e-05 loss: 0.2154 (0.2870) time: 3.6015 data: 0.0031 max mem: 19784 +Epoch: [0] [ 330/2138] eta: 1:49:13 lr: 4.982579646154096e-05 loss: 0.2247 (0.2861) time: 3.6003 data: 0.0030 max mem: 19784 +Epoch: [0] [ 340/2138] eta: 1:48:36 lr: 4.982053246266491e-05 loss: 0.2318 (0.2847) time: 3.6061 data: 0.0029 max mem: 19786 +Epoch: [0] [ 350/2138] eta: 1:48:00 lr: 4.981526840198925e-05 loss: 0.2153 (0.2830) time: 3.6152 data: 0.0029 max mem: 19786 +Epoch: [0] [ 360/2138] eta: 1:47:23 lr: 4.981000427950598e-05 loss: 0.2430 (0.2827) time: 3.6122 data: 0.0029 max mem: 19786 +Epoch: [0] [ 370/2138] eta: 1:46:46 lr: 4.9804740095207144e-05 loss: 0.2452 (0.2817) time: 3.6080 data: 0.0028 max mem: 19786 +Epoch: [0] [ 380/2138] eta: 1:46:09 lr: 4.979947584908472e-05 loss: 0.2150 (0.2800) time: 3.6144 data: 0.0027 max mem: 19786 +Epoch: [0] [ 390/2138] eta: 1:45:33 lr: 4.979421154113075e-05 loss: 0.2009 (0.2783) time: 3.6160 data: 0.0028 max mem: 19786 +Epoch: [0] [ 400/2138] eta: 1:44:56 lr: 4.978894717133722e-05 loss: 0.1940 (0.2767) time: 3.6110 data: 0.0027 max mem: 19786 +Epoch: [0] [ 410/2138] eta: 1:44:20 lr: 4.978368273969616e-05 loss: 0.2248 (0.2760) time: 3.6174 data: 0.0029 max mem: 19786 +Epoch: [0] [ 420/2138] eta: 1:43:43 lr: 4.977841824619955e-05 loss: 0.2369 (0.2754) time: 3.6205 data: 0.0030 max mem: 19786 +Epoch: [0] [ 430/2138] eta: 1:43:07 lr: 4.977315369083943e-05 loss: 0.2171 (0.2740) time: 3.6178 data: 0.0031 max mem: 19786 +Epoch: [0] [ 440/2138] eta: 1:42:30 lr: 4.976788907360778e-05 loss: 0.2337 (0.2737) time: 3.6154 data: 0.0031 max mem: 19786 +Epoch: [0] [ 450/2138] eta: 1:41:54 lr: 4.97626243944966e-05 loss: 0.2280 (0.2719) time: 3.6132 data: 0.0029 max mem: 19786 +Epoch: [0] [ 460/2138] eta: 1:41:17 lr: 4.9757359653497886e-05 loss: 0.2028 (0.2707) time: 3.6148 data: 0.0027 max mem: 19786 +Epoch: [0] [ 470/2138] eta: 1:40:41 lr: 4.9752094850603656e-05 loss: 0.2228 (0.2700) time: 3.6110 data: 0.0026 max mem: 19786 +Epoch: [0] [ 480/2138] eta: 1:40:04 lr: 4.9746829985805874e-05 loss: 0.2200 (0.2687) time: 3.6097 data: 0.0026 max mem: 19786 +Epoch: [0] [ 490/2138] eta: 1:39:27 lr: 4.974156505909656e-05 loss: 0.2239 (0.2679) time: 3.6095 data: 0.0027 max mem: 19786 +Epoch: [0] [ 500/2138] eta: 1:38:51 lr: 4.9736300070467686e-05 loss: 0.2239 (0.2671) time: 3.6074 data: 0.0028 max mem: 19787 +Epoch: [0] [ 510/2138] eta: 1:38:14 lr: 4.973103501991126e-05 loss: 0.1913 (0.2658) time: 3.6073 data: 0.0028 max mem: 19787 +Epoch: [0] [ 520/2138] eta: 1:37:37 lr: 4.972576990741924e-05 loss: 0.1907 (0.2648) time: 3.6096 data: 0.0027 max mem: 19787 +Epoch: [0] [ 530/2138] eta: 1:37:01 lr: 4.972050473298364e-05 loss: 0.1984 (0.2638) time: 3.6099 data: 0.0029 max mem: 19787 +Epoch: [0] [ 540/2138] eta: 1:36:24 lr: 4.9715239496596424e-05 loss: 0.1890 (0.2627) time: 3.6077 data: 0.0032 max mem: 19787 +Epoch: [0] [ 550/2138] eta: 1:35:48 lr: 4.970997419824958e-05 loss: 0.1798 (0.2613) time: 3.6075 data: 0.0030 max mem: 19787 +Epoch: [0] [ 560/2138] eta: 1:35:12 lr: 4.970470883793508e-05 loss: 0.2042 (0.2608) time: 3.6166 data: 0.0029 max mem: 19787 +Epoch: [0] [ 570/2138] eta: 1:34:35 lr: 4.9699443415644907e-05 loss: 0.2246 (0.2600) time: 3.6145 data: 0.0030 max mem: 19787 +Epoch: [0] [ 580/2138] eta: 1:33:59 lr: 4.969417793137104e-05 loss: 0.2055 (0.2589) time: 3.6055 data: 0.0031 max mem: 19787 +Epoch: [0] [ 590/2138] eta: 1:33:22 lr: 4.968891238510544e-05 loss: 0.1983 (0.2579) time: 3.6066 data: 0.0031 max mem: 19787 +Epoch: [0] [ 600/2138] eta: 1:32:45 lr: 4.9683646776840085e-05 loss: 0.1924 (0.2573) time: 3.6068 data: 0.0031 max mem: 19787 +Epoch: [0] [ 610/2138] eta: 1:32:09 lr: 4.967838110656694e-05 loss: 0.1924 (0.2564) time: 3.6092 data: 0.0031 max mem: 19787 +Epoch: [0] [ 620/2138] eta: 1:31:33 lr: 4.9673115374277986e-05 loss: 0.1914 (0.2556) time: 3.6126 data: 0.0029 max mem: 19787 +Epoch: [0] [ 630/2138] eta: 1:30:56 lr: 4.9667849579965166e-05 loss: 0.1906 (0.2548) time: 3.6141 data: 0.0029 max mem: 19787 +Epoch: [0] [ 640/2138] eta: 1:30:20 lr: 4.966258372362045e-05 loss: 0.2134 (0.2542) time: 3.6142 data: 0.0030 max mem: 19787 +Epoch: [0] [ 650/2138] eta: 1:29:44 lr: 4.965731780523581e-05 loss: 0.2013 (0.2535) time: 3.6082 data: 0.0029 max mem: 19787 +Epoch: [0] [ 660/2138] eta: 1:29:08 lr: 4.9652051824803196e-05 loss: 0.1757 (0.2527) time: 3.6151 data: 0.0030 max mem: 19787 +Epoch: [0] [ 670/2138] eta: 1:28:31 lr: 4.964678578231457e-05 loss: 0.2153 (0.2522) time: 3.6201 data: 0.0034 max mem: 19787 +Epoch: [0] [ 680/2138] eta: 1:27:55 lr: 4.964151967776187e-05 loss: 0.2153 (0.2521) time: 3.6147 data: 0.0035 max mem: 19787 +Epoch: [0] [ 690/2138] eta: 1:27:19 lr: 4.963625351113707e-05 loss: 0.1806 (0.2511) time: 3.6215 data: 0.0034 max mem: 19787 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3.6175 data: 0.0032 max mem: 19788 +Epoch: [0] [ 940/2138] eta: 1:12:14 lr: 4.950457914850318e-05 loss: 0.2086 (0.2379) time: 3.6199 data: 0.0030 max mem: 19788 +Epoch: [0] [ 950/2138] eta: 1:11:38 lr: 4.949931136517249e-05 loss: 0.1869 (0.2376) time: 3.6162 data: 0.0033 max mem: 19788 +Epoch: [0] [ 960/2138] eta: 1:11:01 lr: 4.949404351955166e-05 loss: 0.2012 (0.2372) time: 3.6143 data: 0.0034 max mem: 19788 +Epoch: [0] [ 970/2138] eta: 1:10:25 lr: 4.9488775611632596e-05 loss: 0.1830 (0.2365) time: 3.6113 data: 0.0033 max mem: 19788 +Epoch: [0] [ 980/2138] eta: 1:09:49 lr: 4.9483507641407175e-05 loss: 0.1637 (0.2360) time: 3.6149 data: 0.0032 max mem: 19788 +Epoch: [0] [ 990/2138] eta: 1:09:13 lr: 4.9478239608867317e-05 loss: 0.1853 (0.2355) time: 3.6218 data: 0.0033 max mem: 19788 +Epoch: [0] [1000/2138] eta: 1:08:37 lr: 4.947297151400489e-05 loss: 0.1649 (0.2349) time: 3.6205 data: 0.0032 max mem: 19788 +Epoch: [0] [1010/2138] eta: 1:08:00 lr: 4.946770335681179e-05 loss: 0.1649 (0.2344) time: 3.6168 data: 0.0030 max mem: 19788 +Epoch: [0] [1020/2138] eta: 1:07:24 lr: 4.946243513727991e-05 loss: 0.1572 (0.2338) time: 3.6137 data: 0.0034 max mem: 19788 +Epoch: [0] [1030/2138] eta: 1:06:48 lr: 4.945716685540113e-05 loss: 0.1606 (0.2332) time: 3.6137 data: 0.0033 max mem: 19788 +Epoch: [0] [1040/2138] eta: 1:06:12 lr: 4.945189851116733e-05 loss: 0.1863 (0.2329) time: 3.6153 data: 0.0032 max mem: 19788 +Epoch: [0] [1050/2138] eta: 1:05:36 lr: 4.9446630104570396e-05 loss: 0.1890 (0.2323) time: 3.6273 data: 0.0033 max mem: 19788 +Epoch: [0] [1060/2138] eta: 1:05:00 lr: 4.94413616356022e-05 loss: 0.1663 (0.2319) time: 3.6313 data: 0.0030 max mem: 19788 +Epoch: [0] [1070/2138] eta: 1:04:23 lr: 4.9436093104254624e-05 loss: 0.1663 (0.2315) time: 3.6199 data: 0.0028 max mem: 19788 +Epoch: [0] [1080/2138] eta: 1:03:47 lr: 4.9430824510519544e-05 loss: 0.1616 (0.2310) time: 3.6226 data: 0.0029 max mem: 19788 +Epoch: [0] [1090/2138] eta: 1:03:11 lr: 4.9425555854388825e-05 loss: 0.1655 (0.2308) time: 3.6211 data: 0.0032 max mem: 19788 +Epoch: [0] [1100/2138] eta: 1:02:35 lr: 4.9420287135854343e-05 loss: 0.1887 (0.2305) time: 3.6188 data: 0.0033 max mem: 19788 +Epoch: [0] [1110/2138] eta: 1:01:59 lr: 4.9415018354907973e-05 loss: 0.1829 (0.2300) time: 3.6265 data: 0.0033 max mem: 19788 +Epoch: [0] [1120/2138] eta: 1:01:23 lr: 4.9409749511541564e-05 loss: 0.1650 (0.2295) time: 3.6241 data: 0.0033 max mem: 19788 +Epoch: [0] [1130/2138] eta: 1:00:47 lr: 4.9404480605747e-05 loss: 0.1962 (0.2293) time: 3.6220 data: 0.0030 max mem: 19788 +Epoch: [0] [1140/2138] eta: 1:00:10 lr: 4.939921163751613e-05 loss: 0.2010 (0.2291) time: 3.6190 data: 0.0028 max mem: 19788 +Epoch: [0] [1150/2138] eta: 0:59:34 lr: 4.939394260684083e-05 loss: 0.1751 (0.2287) time: 3.6174 data: 0.0029 max mem: 19788 +Epoch: [0] [1160/2138] eta: 0:58:58 lr: 4.9388673513712936e-05 loss: 0.1642 (0.2285) time: 3.6241 data: 0.0029 max mem: 19788 +Epoch: [0] [1170/2138] eta: 0:58:22 lr: 4.938340435812432e-05 loss: 0.1878 (0.2282) time: 3.6199 data: 0.0028 max mem: 19788 +Epoch: [0] [1180/2138] eta: 0:57:46 lr: 4.9378135140066835e-05 loss: 0.2117 (0.2280) time: 3.6166 data: 0.0028 max mem: 19788 +Epoch: [0] [1190/2138] eta: 0:57:10 lr: 4.937286585953232e-05 loss: 0.1815 (0.2274) time: 3.6692 data: 0.0028 max mem: 19788 +Epoch: [0] [1200/2138] eta: 0:56:35 lr: 4.936759651651265e-05 loss: 0.1768 (0.2272) time: 3.7202 data: 0.0029 max mem: 19788 +Epoch: [0] [1210/2138] eta: 0:55:59 lr: 4.936232711099965e-05 loss: 0.1716 (0.2267) time: 3.6881 data: 0.0029 max mem: 19788 +Epoch: [0] [1220/2138] eta: 0:55:23 lr: 4.935705764298518e-05 loss: 0.1695 (0.2266) time: 3.6479 data: 0.0029 max mem: 19788 +Epoch: [0] [1230/2138] eta: 0:54:47 lr: 4.935178811246108e-05 loss: 0.1894 (0.2263) time: 3.6351 data: 0.0029 max mem: 19788 +Epoch: [0] [1240/2138] eta: 0:54:11 lr: 4.934651851941919e-05 loss: 0.1877 (0.2261) time: 3.6524 data: 0.0028 max mem: 19788 +Epoch: [0] [1250/2138] eta: 0:53:35 lr: 4.934124886385136e-05 loss: 0.1693 (0.2257) time: 3.6797 data: 0.0029 max mem: 19788 +Epoch: [0] [1260/2138] eta: 0:53:00 lr: 4.933597914574942e-05 loss: 0.1683 (0.2256) time: 3.6802 data: 0.0030 max mem: 19788 +Epoch: [0] [1270/2138] eta: 0:52:24 lr: 4.933070936510519e-05 loss: 0.1669 (0.2252) time: 3.6720 data: 0.0029 max mem: 19788 +Epoch: [0] [1280/2138] eta: 0:51:48 lr: 4.9325439521910545e-05 loss: 0.1592 (0.2251) time: 3.6606 data: 0.0029 max mem: 19788 +Epoch: [0] [1290/2138] eta: 0:51:11 lr: 4.9320169616157276e-05 loss: 0.1838 (0.2250) time: 3.6450 data: 0.0029 max mem: 19788 +Epoch: [0] [1300/2138] eta: 0:50:35 lr: 4.9314899647837234e-05 loss: 0.1845 (0.2247) time: 3.6364 data: 0.0028 max mem: 19788 +Epoch: [0] [1310/2138] eta: 0:49:59 lr: 4.9309629616942247e-05 loss: 0.1798 (0.2245) time: 3.6470 data: 0.0028 max mem: 19788 +Epoch: [0] [1320/2138] eta: 0:49:23 lr: 4.930435952346414e-05 loss: 0.1798 (0.2242) time: 3.6454 data: 0.0028 max mem: 19788 +Epoch: [0] [1330/2138] eta: 0:48:47 lr: 4.929908936739473e-05 loss: 0.1765 (0.2238) time: 3.6350 data: 0.0028 max mem: 19788 +Epoch: [0] [1340/2138] eta: 0:48:11 lr: 4.929381914872584e-05 loss: 0.1765 (0.2237) time: 3.6810 data: 0.0028 max mem: 19788 +Epoch: [0] [1350/2138] eta: 0:47:35 lr: 4.928854886744929e-05 loss: 0.1814 (0.2234) time: 3.6798 data: 0.0029 max mem: 19788 +Epoch: [0] [1360/2138] eta: 0:47:00 lr: 4.928327852355691e-05 loss: 0.1864 (0.2230) time: 3.6986 data: 0.0028 max mem: 19788 +Epoch: [0] [1370/2138] eta: 0:46:24 lr: 4.92780081170405e-05 loss: 0.1886 (0.2228) time: 3.7006 data: 0.0027 max mem: 19788 +Epoch: [0] [1380/2138] eta: 0:45:48 lr: 4.9272737647891884e-05 loss: 0.1819 (0.2225) time: 3.6496 data: 0.0029 max mem: 19788 +Epoch: [0] [1390/2138] eta: 0:45:12 lr: 4.926746711610286e-05 loss: 0.1803 (0.2224) time: 3.7579 data: 0.0030 max mem: 19788 +Epoch: [0] [1400/2138] eta: 0:44:37 lr: 4.926219652166526e-05 loss: 0.1868 (0.2220) time: 3.8420 data: 0.0030 max mem: 19788 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mem: 19788 +Epoch: [0] [1490/2138] eta: 0:39:20 lr: 4.921475835118788e-05 loss: 0.1665 (0.2194) time: 4.0111 data: 0.0029 max mem: 19788 +Epoch: [0] [1500/2138] eta: 0:38:45 lr: 4.920948712981347e-05 loss: 0.1758 (0.2192) time: 3.9004 data: 0.0029 max mem: 19788 +Epoch: [0] [1510/2138] eta: 0:38:11 lr: 4.920421584570023e-05 loss: 0.1748 (0.2189) time: 4.0595 data: 0.0029 max mem: 19788 +Epoch: [0] [1520/2138] eta: 0:37:36 lr: 4.919894449883997e-05 loss: 0.1612 (0.2188) time: 4.1742 data: 0.0028 max mem: 19788 +Epoch: [0] [1530/2138] eta: 0:37:03 lr: 4.9193673089224454e-05 loss: 0.1612 (0.2185) time: 4.2922 data: 0.0028 max mem: 19788 +Epoch: [0] [1540/2138] eta: 0:36:28 lr: 4.918840161684547e-05 loss: 0.1542 (0.2182) time: 4.2901 data: 0.0028 max mem: 19788 +Epoch: [0] [1550/2138] eta: 0:35:54 lr: 4.918313008169479e-05 loss: 0.1565 (0.2178) time: 4.1354 data: 0.0028 max mem: 19788 +Epoch: [0] [1560/2138] eta: 0:35:18 lr: 4.917785848376421e-05 loss: 0.1606 (0.2177) time: 4.0230 data: 0.0028 max mem: 19788 +Epoch: [0] [1570/2138] eta: 0:34:43 lr: 4.917258682304548e-05 loss: 0.1805 (0.2175) time: 4.0236 data: 0.0028 max mem: 19788 +Epoch: [0] [1580/2138] eta: 0:34:07 lr: 4.916731509953038e-05 loss: 0.1923 (0.2174) time: 4.0214 data: 0.0028 max mem: 19788 +Epoch: [0] [1590/2138] eta: 0:33:32 lr: 4.916204331321069e-05 loss: 0.1742 (0.2170) time: 3.9721 data: 0.0028 max mem: 19788 +Epoch: [0] [1600/2138] eta: 0:32:56 lr: 4.9156771464078175e-05 loss: 0.1749 (0.2169) time: 4.0484 data: 0.0028 max mem: 19788 +Epoch: [0] [1610/2138] eta: 0:32:20 lr: 4.9151499552124606e-05 loss: 0.1600 (0.2167) time: 3.9040 data: 0.0029 max mem: 19788 +Epoch: [0] [1620/2138] eta: 0:31:43 lr: 4.914622757734173e-05 loss: 0.1571 (0.2165) time: 3.7090 data: 0.0029 max mem: 19788 +Epoch: [0] [1630/2138] eta: 0:31:08 lr: 4.914095553972132e-05 loss: 0.1605 (0.2163) time: 3.9777 data: 0.0029 max mem: 19788 +Epoch: [0] [1640/2138] eta: 0:30:32 lr: 4.913568343925514e-05 loss: 0.1602 (0.2161) time: 4.1708 data: 0.0030 max mem: 19788 +Epoch: [0] [1650/2138] eta: 0:29:56 lr: 4.913041127593495e-05 loss: 0.1518 (0.2157) time: 3.9497 data: 0.0029 max mem: 19788 +Epoch: [0] [1660/2138] eta: 0:29:20 lr: 4.91251390497525e-05 loss: 0.1518 (0.2154) time: 3.7968 data: 0.0027 max mem: 19788 +Epoch: [0] [1670/2138] eta: 0:28:44 lr: 4.9119866760699545e-05 loss: 0.1490 (0.2149) time: 3.9313 data: 0.0027 max mem: 19788 +Epoch: [0] [1680/2138] eta: 0:28:08 lr: 4.911459440876783e-05 loss: 0.1439 (0.2147) time: 4.1243 data: 0.0027 max mem: 19788 +Epoch: [0] [1690/2138] eta: 0:27:32 lr: 4.910932199394912e-05 loss: 0.1711 (0.2146) time: 3.9391 data: 0.0026 max mem: 19788 +Epoch: [0] [1700/2138] eta: 0:26:55 lr: 4.9104049516235157e-05 loss: 0.1740 (0.2144) time: 3.8180 data: 0.0027 max mem: 19788 +Epoch: [0] [1710/2138] eta: 0:26:19 lr: 4.909877697561769e-05 loss: 0.1768 (0.2141) time: 3.9290 data: 0.0028 max mem: 19788 +Epoch: [0] [1720/2138] eta: 0:25:43 lr: 4.9093504372088446e-05 loss: 0.1697 (0.2137) time: 4.0036 data: 0.0028 max mem: 19788 +Epoch: [0] [1730/2138] eta: 0:25:07 lr: 4.908823170563919e-05 loss: 0.1530 (0.2136) time: 4.0089 data: 0.0027 max mem: 19788 +Epoch: [0] [1740/2138] eta: 0:24:30 lr: 4.908295897626164e-05 loss: 0.1390 (0.2132) time: 3.8996 data: 0.0028 max mem: 19788 +Epoch: [0] [1750/2138] eta: 0:23:53 lr: 4.907768618394755e-05 loss: 0.1481 (0.2129) time: 3.8231 data: 0.0028 max mem: 19788 +Epoch: [0] [1760/2138] eta: 0:23:17 lr: 4.907241332868865e-05 loss: 0.1538 (0.2126) time: 3.8646 data: 0.0028 max mem: 19788 +Epoch: [0] [1770/2138] eta: 0:22:40 lr: 4.906714041047668e-05 loss: 0.1617 (0.2124) time: 3.8992 data: 0.0028 max mem: 19788 +Epoch: [0] [1780/2138] eta: 0:22:04 lr: 4.906186742930336e-05 loss: 0.1700 (0.2122) time: 3.8554 data: 0.0027 max mem: 19788 +Epoch: [0] [1790/2138] eta: 0:21:27 lr: 4.9056594385160414e-05 loss: 0.1840 (0.2120) time: 3.7785 data: 0.0028 max mem: 19788 +Epoch: [0] [1800/2138] eta: 0:20:50 lr: 4.9051321278039595e-05 loss: 0.1807 (0.2120) time: 3.8986 data: 0.0028 max mem: 19788 +Epoch: [0] [1810/2138] eta: 0:20:13 lr: 4.904604810793259e-05 loss: 0.1733 (0.2117) time: 3.8538 data: 0.0028 max mem: 19788 +Epoch: [0] [1820/2138] eta: 0:19:37 lr: 4.904077487483117e-05 loss: 0.1562 (0.2116) time: 3.7795 data: 0.0029 max mem: 19788 +Epoch: [0] [1830/2138] eta: 0:19:00 lr: 4.903550157872702e-05 loss: 0.1509 (0.2113) time: 3.8627 data: 0.0028 max mem: 19788 +Epoch: [0] [1840/2138] eta: 0:18:23 lr: 4.9030228219611866e-05 loss: 0.1685 (0.2113) time: 3.8164 data: 0.0028 max mem: 19788 +Epoch: [0] [1850/2138] eta: 0:17:46 lr: 4.902495479747743e-05 loss: 0.1687 (0.2111) time: 3.9246 data: 0.0028 max mem: 19788 +Epoch: [0] [1860/2138] eta: 0:17:10 lr: 4.901968131231543e-05 loss: 0.1653 (0.2111) time: 3.9677 data: 0.0029 max mem: 19788 +Epoch: [0] [1870/2138] eta: 0:16:33 lr: 4.9014407764117565e-05 loss: 0.1702 (0.2110) time: 3.9731 data: 0.0029 max mem: 19788 +Epoch: [0] [1880/2138] eta: 0:15:56 lr: 4.900913415287556e-05 loss: 0.1615 (0.2107) time: 3.8948 data: 0.0027 max mem: 19788 +Epoch: [0] [1890/2138] eta: 0:15:19 lr: 4.9003860478581114e-05 loss: 0.1552 (0.2104) time: 3.8552 data: 0.0027 max mem: 19788 +Epoch: [0] [1900/2138] eta: 0:14:43 lr: 4.8998586741225946e-05 loss: 0.1552 (0.2101) time: 4.1232 data: 0.0028 max mem: 19788 +Epoch: [0] [1910/2138] eta: 0:14:06 lr: 4.899331294080175e-05 loss: 0.1567 (0.2098) time: 4.0954 data: 0.0028 max mem: 19788 +Epoch: [0] [1920/2138] eta: 0:13:29 lr: 4.8988039077300226e-05 loss: 0.1567 (0.2096) time: 3.8611 data: 0.0027 max mem: 19788 +Epoch: [0] [1930/2138] eta: 0:12:52 lr: 4.898276515071307e-05 loss: 0.1475 (0.2096) time: 3.7706 data: 0.0028 max mem: 19788 +Epoch: [0] [1940/2138] eta: 0:12:15 lr: 4.8977491161032e-05 loss: 0.1475 (0.2093) time: 3.7329 data: 0.0027 max mem: 19788 +Epoch: [0] [1950/2138] eta: 0:11:38 lr: 4.89722171082487e-05 loss: 0.1721 (0.2091) time: 3.8193 data: 0.0027 max mem: 19788 +Epoch: [0] [1960/2138] eta: 0:11:01 lr: 4.896694299235486e-05 loss: 0.1684 (0.2089) time: 3.9580 data: 0.0027 max mem: 19788 +Epoch: [0] [1970/2138] eta: 0:10:24 lr: 4.896166881334218e-05 loss: 0.1486 (0.2087) time: 3.8369 data: 0.0028 max mem: 19788 +Epoch: [0] [1980/2138] eta: 0:09:47 lr: 4.895639457120235e-05 loss: 0.1628 (0.2085) time: 3.7481 data: 0.0028 max mem: 19788 +Epoch: [0] [1990/2138] eta: 0:09:10 lr: 4.8951120265927045e-05 loss: 0.1647 (0.2083) time: 3.8756 data: 0.0027 max mem: 19788 +Epoch: [0] [2000/2138] eta: 0:08:33 lr: 4.8945845897507964e-05 loss: 0.1497 (0.2080) time: 4.1169 data: 0.0027 max mem: 19788 +Epoch: [0] [2010/2138] eta: 0:07:56 lr: 4.894057146593678e-05 loss: 0.1614 (0.2079) time: 4.2305 data: 0.0027 max mem: 19788 +Epoch: [0] [2020/2138] eta: 0:07:19 lr: 4.893529697120519e-05 loss: 0.1617 (0.2077) time: 4.0079 data: 0.0028 max mem: 19788 +Epoch: [0] [2030/2138] eta: 0:06:42 lr: 4.8930022413304855e-05 loss: 0.1617 (0.2075) time: 3.9460 data: 0.0027 max mem: 19788 +Epoch: [0] [2040/2138] eta: 0:06:05 lr: 4.892474779222747e-05 loss: 0.1673 (0.2074) time: 3.8567 data: 0.0027 max mem: 19788 +Epoch: [0] [2050/2138] eta: 0:05:27 lr: 4.8919473107964694e-05 loss: 0.1673 (0.2072) time: 3.6923 data: 0.0027 max mem: 19788 +Epoch: [0] [2060/2138] eta: 0:04:50 lr: 4.89141983605082e-05 loss: 0.1484 (0.2069) time: 3.7344 data: 0.0028 max mem: 19788 +Epoch: [0] [2070/2138] eta: 0:04:13 lr: 4.890892354984968e-05 loss: 0.1422 (0.2067) time: 3.7762 data: 0.0028 max mem: 19788 +Epoch: [0] [2080/2138] eta: 0:03:36 lr: 4.890364867598078e-05 loss: 0.1519 (0.2065) time: 3.8141 data: 0.0026 max mem: 19788 +Epoch: [0] [2090/2138] eta: 0:02:58 lr: 4.889837373889318e-05 loss: 0.1543 (0.2063) time: 3.8530 data: 0.0026 max mem: 19788 +Epoch: [0] [2100/2138] eta: 0:02:21 lr: 4.889309873857853e-05 loss: 0.1508 (0.2061) time: 3.8132 data: 0.0028 max mem: 19788 +Epoch: [0] [2110/2138] eta: 0:01:44 lr: 4.8887823675028514e-05 loss: 0.1576 (0.2061) time: 3.8938 data: 0.0028 max mem: 19788 +Epoch: [0] [2120/2138] eta: 0:01:07 lr: 4.888254854823477e-05 loss: 0.1731 (0.2059) time: 3.8949 data: 0.0029 max mem: 19788 +Epoch: [0] [2130/2138] eta: 0:00:29 lr: 4.887727335818898e-05 loss: 0.1731 (0.2059) time: 3.8992 data: 0.0029 max mem: 19788 +Epoch: [0] Total time: 2:12:55 +Test: [ 0/21770] eta: 17:56:59 time: 2.9683 data: 2.3375 max mem: 19788 +Test: [ 100/21770] eta: 0:33:11 time: 0.0626 data: 0.0021 max mem: 19788 +Test: [ 200/21770] eta: 0:27:59 time: 0.0632 data: 0.0018 max mem: 19788 +Test: [ 300/21770] eta: 0:26:45 time: 0.0849 data: 0.0027 max mem: 19788 +Test: [ 400/21770] eta: 0:25:56 time: 0.0629 data: 0.0019 max mem: 19788 +Test: [ 500/21770] eta: 0:26:24 time: 0.0799 data: 0.0020 max mem: 19788 +Test: [ 600/21770] eta: 0:25:56 time: 0.0862 data: 0.0026 max mem: 19788 +Test: [ 700/21770] eta: 0:25:37 time: 0.0742 data: 0.0024 max mem: 19788 +Test: [ 800/21770] eta: 0:25:58 time: 0.0837 data: 0.0027 max mem: 19788 +Test: [ 900/21770] eta: 0:25:50 time: 0.0834 data: 0.0027 max mem: 19788 +Test: [ 1000/21770] eta: 0:25:32 time: 0.0733 data: 0.0022 max mem: 19788 +Test: [ 1100/21770] eta: 0:25:08 time: 0.0636 data: 0.0018 max mem: 19788 +Test: [ 1200/21770] eta: 0:25:09 time: 0.0790 data: 0.0020 max mem: 19788 +Test: [ 1300/21770] eta: 0:24:57 time: 0.0830 data: 0.0027 max mem: 19788 +Test: [ 1400/21770] eta: 0:24:55 time: 0.0835 data: 0.0027 max mem: 19788 +Test: [ 1500/21770] eta: 0:25:03 time: 0.0842 data: 0.0026 max mem: 19788 +Test: [ 1600/21770] eta: 0:25:09 time: 0.0864 data: 0.0025 max mem: 19788 +Test: [ 1700/21770] eta: 0:25:14 time: 0.0843 data: 0.0026 max mem: 19788 +Test: [ 1800/21770] eta: 0:25:16 time: 0.0845 data: 0.0027 max mem: 19788 +Test: [ 1900/21770] eta: 0:25:01 time: 0.0622 data: 0.0021 max mem: 19788 +Test: [ 2000/21770] eta: 0:24:44 time: 0.0765 data: 0.0020 max mem: 19788 +Test: [ 2100/21770] eta: 0:24:40 time: 0.0837 data: 0.0026 max mem: 19788 +Test: [ 2200/21770] eta: 0:24:37 time: 0.0692 data: 0.0024 max mem: 19788 +Test: [ 2300/21770] eta: 0:24:33 time: 0.0721 data: 0.0022 max mem: 19788 +Test: [ 2400/21770] eta: 0:24:17 time: 0.0763 data: 0.0022 max mem: 19788 +Test: [ 2500/21770] eta: 0:24:02 time: 0.0698 data: 0.0021 max mem: 19788 +Test: [ 2600/21770] eta: 0:23:47 time: 0.0710 data: 0.0021 max mem: 19788 +Test: [ 2700/21770] eta: 0:23:38 time: 0.0643 data: 0.0018 max mem: 19788 +Test: [ 2800/21770] eta: 0:23:26 time: 0.0646 data: 0.0019 max mem: 19788 +Test: [ 2900/21770] eta: 0:23:17 time: 0.0655 data: 0.0020 max mem: 19788 +Test: [ 3000/21770] eta: 0:23:03 time: 0.0639 data: 0.0021 max mem: 19788 +Test: [ 3100/21770] eta: 0:23:00 time: 0.0739 data: 0.0022 max mem: 19788 +Test: [ 3200/21770] eta: 0:22:53 time: 0.0778 data: 0.0025 max mem: 19788 +Test: [ 3300/21770] eta: 0:22:42 time: 0.0646 data: 0.0019 max mem: 19788 +Test: [ 3400/21770] eta: 0:22:30 time: 0.0673 data: 0.0021 max mem: 19788 +Test: [ 3500/21770] eta: 0:22:25 time: 0.0838 data: 0.0026 max mem: 19788 +Test: [ 3600/21770] eta: 0:22:22 time: 0.0735 data: 0.0023 max mem: 19788 +Test: [ 3700/21770] eta: 0:22:20 time: 0.0863 data: 0.0025 max mem: 19788 +Test: [ 3800/21770] eta: 0:22:15 time: 0.0648 data: 0.0021 max mem: 19788 +Test: [ 3900/21770] eta: 0:22:04 time: 0.0707 data: 0.0022 max mem: 19788 +Test: [ 4000/21770] eta: 0:21:53 time: 0.0723 data: 0.0023 max mem: 19788 +Test: [ 4100/21770] eta: 0:21:50 time: 0.0861 data: 0.0027 max mem: 19788 +Test: [ 4200/21770] eta: 0:21:47 time: 0.0860 data: 0.0022 max mem: 19788 +Test: [ 4300/21770] eta: 0:21:42 time: 0.0852 data: 0.0026 max mem: 19788 +Test: [ 4400/21770] eta: 0:21:30 time: 0.0640 data: 0.0020 max mem: 19788 +Test: [ 4500/21770] eta: 0:21:20 time: 0.0651 data: 0.0021 max mem: 19788 +Test: [ 4600/21770] eta: 0:21:09 time: 0.0653 data: 0.0020 max mem: 19788 +Test: [ 4700/21770] eta: 0:20:59 time: 0.0667 data: 0.0019 max mem: 19788 +Test: [ 4800/21770] eta: 0:20:51 time: 0.0618 data: 0.0019 max mem: 19788 +Test: [ 4900/21770] eta: 0:20:40 time: 0.0630 data: 0.0020 max mem: 19788 +Test: [ 5000/21770] eta: 0:20:30 time: 0.0617 data: 0.0019 max mem: 19788 +Test: [ 5100/21770] eta: 0:20:19 time: 0.0656 data: 0.0020 max mem: 19788 +Test: [ 5200/21770] eta: 0:20:09 time: 0.0642 data: 0.0020 max mem: 19788 +Test: [ 5300/21770] eta: 0:19:59 time: 0.0636 data: 0.0020 max mem: 19788 +Test: [ 5400/21770] eta: 0:19:50 time: 0.0669 data: 0.0021 max mem: 19788 +Test: [ 5500/21770] eta: 0:19:40 time: 0.0629 data: 0.0018 max mem: 19788 +Test: [ 5600/21770] eta: 0:19:33 time: 0.0639 data: 0.0019 max mem: 19788 +Test: [ 5700/21770] eta: 0:19:26 time: 0.0678 data: 0.0019 max mem: 19788 +Test: [ 5800/21770] eta: 0:19:19 time: 0.0662 data: 0.0020 max mem: 19788 +Test: [ 5900/21770] eta: 0:19:09 time: 0.0688 data: 0.0023 max mem: 19788 +Test: [ 6000/21770] eta: 0:19:01 time: 0.0636 data: 0.0020 max mem: 19788 +Test: [ 6100/21770] eta: 0:18:54 time: 0.0848 data: 0.0026 max mem: 19788 +Test: [ 6200/21770] eta: 0:18:47 time: 0.0648 data: 0.0020 max mem: 19788 +Test: [ 6300/21770] eta: 0:18:37 time: 0.0638 data: 0.0020 max mem: 19788 +Test: [ 6400/21770] eta: 0:18:29 time: 0.0769 data: 0.0025 max mem: 19788 +Test: [ 6500/21770] eta: 0:18:22 time: 0.0752 data: 0.0025 max mem: 19788 +Test: [ 6600/21770] eta: 0:18:16 time: 0.0875 data: 0.0027 max mem: 19788 +Test: [ 6700/21770] eta: 0:18:11 time: 0.0832 data: 0.0024 max mem: 19788 +Test: [ 6800/21770] eta: 0:18:02 time: 0.0730 data: 0.0022 max mem: 19788 +Test: [ 6900/21770] eta: 0:17:54 time: 0.0656 data: 0.0020 max mem: 19788 +Test: [ 7000/21770] eta: 0:17:46 time: 0.0774 data: 0.0024 max mem: 19788 +Test: [ 7100/21770] eta: 0:17:39 time: 0.0644 data: 0.0020 max mem: 19788 +Test: [ 7200/21770] eta: 0:17:32 time: 0.0655 data: 0.0020 max mem: 19788 +Test: [ 7300/21770] eta: 0:17:24 time: 0.0850 data: 0.0019 max mem: 19788 +Test: [ 7400/21770] eta: 0:17:19 time: 0.0850 data: 0.0020 max mem: 19788 +Test: [ 7500/21770] eta: 0:17:12 time: 0.0717 data: 0.0021 max mem: 19788 +Test: [ 7600/21770] eta: 0:17:04 time: 0.0678 data: 0.0022 max mem: 19788 +Test: [ 7700/21770] eta: 0:16:56 time: 0.0639 data: 0.0020 max mem: 19788 +Test: [ 7800/21770] eta: 0:16:48 time: 0.0619 data: 0.0019 max mem: 19788 +Test: [ 7900/21770] eta: 0:16:41 time: 0.0869 data: 0.0027 max mem: 19788 +Test: [ 8000/21770] eta: 0:16:35 time: 0.0855 data: 0.0028 max mem: 19788 +Test: [ 8100/21770] eta: 0:16:27 time: 0.0766 data: 0.0022 max mem: 19788 +Test: [ 8200/21770] eta: 0:16:19 time: 0.0675 data: 0.0022 max mem: 19788 +Test: [ 8300/21770] eta: 0:16:13 time: 0.0874 data: 0.0024 max mem: 19788 +Test: [ 8400/21770] eta: 0:16:07 time: 0.0859 data: 0.0026 max mem: 19788 +Test: [ 8500/21770] eta: 0:16:00 time: 0.0675 data: 0.0021 max mem: 19788 +Test: [ 8600/21770] eta: 0:15:52 time: 0.0620 data: 0.0019 max mem: 19788 +Test: [ 8700/21770] eta: 0:15:44 time: 0.0640 data: 0.0019 max mem: 19788 +Test: [ 8800/21770] eta: 0:15:36 time: 0.0702 data: 0.0022 max mem: 19788 +Test: [ 8900/21770] eta: 0:15:30 time: 0.0699 data: 0.0022 max mem: 19788 +Test: [ 9000/21770] eta: 0:15:22 time: 0.0630 data: 0.0020 max mem: 19788 +Test: [ 9100/21770] eta: 0:15:17 time: 0.0862 data: 0.0029 max mem: 19788 +Test: [ 9200/21770] eta: 0:15:09 time: 0.0659 data: 0.0021 max mem: 19788 +Test: [ 9300/21770] eta: 0:15:03 time: 0.0766 data: 0.0025 max mem: 19788 +Test: [ 9400/21770] eta: 0:14:56 time: 0.0743 data: 0.0024 max mem: 19788 +Test: [ 9500/21770] eta: 0:14:49 time: 0.0851 data: 0.0026 max mem: 19788 +Test: [ 9600/21770] eta: 0:14:43 time: 0.0839 data: 0.0027 max mem: 19788 +Test: [ 9700/21770] eta: 0:14:36 time: 0.0612 data: 0.0018 max mem: 19788 +Test: [ 9800/21770] eta: 0:14:29 time: 0.0662 data: 0.0020 max mem: 19788 +Test: [ 9900/21770] eta: 0:14:21 time: 0.0629 data: 0.0020 max mem: 19788 +Test: [10000/21770] eta: 0:14:13 time: 0.0702 data: 0.0021 max mem: 19788 +Test: [10100/21770] eta: 0:14:06 time: 0.0829 data: 0.0024 max mem: 19788 +Test: [10200/21770] eta: 0:13:59 time: 0.0841 data: 0.0021 max mem: 19788 +Test: [10300/21770] eta: 0:13:53 time: 0.0669 data: 0.0024 max mem: 19788 +Test: [10400/21770] eta: 0:13:46 time: 0.0855 data: 0.0027 max mem: 19788 +Test: [10500/21770] eta: 0:13:39 time: 0.0748 data: 0.0022 max mem: 19788 +Test: [10600/21770] eta: 0:13:32 time: 0.0844 data: 0.0024 max mem: 19788 +Test: [10700/21770] eta: 0:13:26 time: 0.0663 data: 0.0025 max mem: 19788 +Test: [10800/21770] eta: 0:13:18 time: 0.0630 data: 0.0020 max mem: 19788 +Test: [10900/21770] eta: 0:13:10 time: 0.0667 data: 0.0019 max mem: 19788 +Test: [11000/21770] eta: 0:13:02 time: 0.0676 data: 0.0021 max mem: 19788 +Test: [11100/21770] eta: 0:12:55 time: 0.0761 data: 0.0025 max mem: 19788 +Test: [11200/21770] eta: 0:12:48 time: 0.0744 data: 0.0022 max mem: 19788 +Test: [11300/21770] eta: 0:12:41 time: 0.0664 data: 0.0020 max mem: 19788 +Test: [11400/21770] eta: 0:12:33 time: 0.0774 data: 0.0020 max mem: 19788 +Test: [11500/21770] eta: 0:12:27 time: 0.0799 data: 0.0025 max mem: 19788 +Test: [11600/21770] eta: 0:12:19 time: 0.0663 data: 0.0020 max mem: 19788 +Test: [11700/21770] eta: 0:12:12 time: 0.0778 data: 0.0023 max mem: 19788 +Test: [11800/21770] eta: 0:12:04 time: 0.0626 data: 0.0020 max mem: 19788 +Test: [11900/21770] eta: 0:11:56 time: 0.0642 data: 0.0019 max mem: 19788 +Test: [12000/21770] eta: 0:11:49 time: 0.0824 data: 0.0026 max mem: 19788 +Test: [12100/21770] eta: 0:11:43 time: 0.0839 data: 0.0026 max mem: 19788 +Test: [12200/21770] eta: 0:11:35 time: 0.0723 data: 0.0023 max mem: 19788 +Test: [12300/21770] eta: 0:11:28 time: 0.0853 data: 0.0022 max mem: 19788 +Test: [12400/21770] eta: 0:11:21 time: 0.0802 data: 0.0019 max mem: 19788 +Test: [12500/21770] eta: 0:11:13 time: 0.0802 data: 0.0025 max mem: 19788 +Test: [12600/21770] eta: 0:11:06 time: 0.0857 data: 0.0025 max mem: 19788 +Test: [12700/21770] eta: 0:11:00 time: 0.0846 data: 0.0026 max mem: 19788 +Test: [12800/21770] eta: 0:10:53 time: 0.0870 data: 0.0027 max mem: 19788 +Test: [12900/21770] eta: 0:10:47 time: 0.0859 data: 0.0022 max mem: 19788 +Test: [13000/21770] eta: 0:10:40 time: 0.0793 data: 0.0022 max mem: 19788 +Test: [13100/21770] eta: 0:10:33 time: 0.0854 data: 0.0026 max mem: 19788 +Test: [13200/21770] eta: 0:10:26 time: 0.0725 data: 0.0021 max mem: 19788 +Test: [13300/21770] eta: 0:10:19 time: 0.0685 data: 0.0020 max mem: 19788 +Test: [13400/21770] eta: 0:10:12 time: 0.0732 data: 0.0022 max mem: 19788 +Test: [13500/21770] eta: 0:10:05 time: 0.0840 data: 0.0025 max mem: 19788 +Test: [13600/21770] eta: 0:09:58 time: 0.0736 data: 0.0022 max mem: 19788 +Test: [13700/21770] eta: 0:09:51 time: 0.0789 data: 0.0026 max mem: 19788 +Test: [13800/21770] eta: 0:09:44 time: 0.0631 data: 0.0021 max mem: 19788 +Test: [13900/21770] eta: 0:09:36 time: 0.0789 data: 0.0024 max mem: 19788 +Test: [14000/21770] eta: 0:09:29 time: 0.0684 data: 0.0020 max mem: 19788 +Test: [14100/21770] eta: 0:09:21 time: 0.0749 data: 0.0021 max mem: 19788 +Test: [14200/21770] eta: 0:09:13 time: 0.0642 data: 0.0021 max mem: 19788 +Test: [14300/21770] eta: 0:09:06 time: 0.0791 data: 0.0021 max mem: 19788 +Test: [14400/21770] eta: 0:08:59 time: 0.0674 data: 0.0020 max mem: 19788 +Test: [14500/21770] eta: 0:08:51 time: 0.0647 data: 0.0019 max mem: 19788 +Test: [14600/21770] eta: 0:08:44 time: 0.0726 data: 0.0024 max mem: 19788 +Test: [14700/21770] eta: 0:08:37 time: 0.0842 data: 0.0026 max mem: 19788 +Test: [14800/21770] eta: 0:08:30 time: 0.0837 data: 0.0026 max mem: 19788 +Test: [14900/21770] eta: 0:08:23 time: 0.0848 data: 0.0028 max mem: 19788 +Test: [15000/21770] eta: 0:08:15 time: 0.0648 data: 0.0018 max mem: 19788 +Test: [15100/21770] eta: 0:08:08 time: 0.0678 data: 0.0021 max mem: 19788 +Test: [15200/21770] eta: 0:08:00 time: 0.0670 data: 0.0020 max mem: 19788 +Test: [15300/21770] eta: 0:07:53 time: 0.0636 data: 0.0020 max mem: 19788 +Test: [15400/21770] eta: 0:07:46 time: 0.0730 data: 0.0022 max mem: 19788 +Test: [15500/21770] eta: 0:07:38 time: 0.0655 data: 0.0019 max mem: 19788 +Test: [15600/21770] eta: 0:07:31 time: 0.0849 data: 0.0028 max mem: 19788 +Test: [15700/21770] eta: 0:07:24 time: 0.0674 data: 0.0019 max mem: 19788 +Test: [15800/21770] eta: 0:07:16 time: 0.0652 data: 0.0018 max mem: 19788 +Test: [15900/21770] eta: 0:07:09 time: 0.0859 data: 0.0022 max mem: 19788 +Test: [16000/21770] eta: 0:07:02 time: 0.0787 data: 0.0023 max mem: 19788 +Test: [16100/21770] eta: 0:06:55 time: 0.0678 data: 0.0024 max mem: 19788 +Test: [16200/21770] eta: 0:06:48 time: 0.0634 data: 0.0020 max mem: 19788 +Test: [16300/21770] eta: 0:06:40 time: 0.0638 data: 0.0018 max mem: 19788 +Test: [16400/21770] eta: 0:06:33 time: 0.0745 data: 0.0022 max mem: 19788 +Test: [16500/21770] eta: 0:06:25 time: 0.0739 data: 0.0023 max mem: 19788 +Test: [16600/21770] eta: 0:06:18 time: 0.0663 data: 0.0021 max mem: 19788 +Test: [16700/21770] eta: 0:06:11 time: 0.0652 data: 0.0019 max mem: 19788 +Test: [16800/21770] eta: 0:06:03 time: 0.0646 data: 0.0020 max mem: 19788 +Test: [16900/21770] eta: 0:05:56 time: 0.0816 data: 0.0025 max mem: 19788 +Test: [17000/21770] eta: 0:05:49 time: 0.0676 data: 0.0021 max mem: 19788 +Test: [17100/21770] eta: 0:05:41 time: 0.0851 data: 0.0028 max mem: 19788 +Test: [17200/21770] eta: 0:05:34 time: 0.0847 data: 0.0027 max mem: 19788 +Test: [17300/21770] eta: 0:05:27 time: 0.0637 data: 0.0020 max mem: 19788 +Test: [17400/21770] eta: 0:05:19 time: 0.0686 data: 0.0021 max mem: 19788 +Test: [17500/21770] eta: 0:05:12 time: 0.0848 data: 0.0026 max mem: 19788 +Test: [17600/21770] eta: 0:05:05 time: 0.0842 data: 0.0027 max mem: 19788 +Test: [17700/21770] eta: 0:04:58 time: 0.0716 data: 0.0023 max mem: 19788 +Test: [17800/21770] eta: 0:04:50 time: 0.0852 data: 0.0028 max mem: 19788 +Test: [17900/21770] eta: 0:04:43 time: 0.0746 data: 0.0020 max mem: 19788 +Test: [18000/21770] eta: 0:04:36 time: 0.0664 data: 0.0021 max mem: 19788 +Test: [18100/21770] eta: 0:04:28 time: 0.0714 data: 0.0024 max mem: 19788 +Test: [18200/21770] eta: 0:04:21 time: 0.0719 data: 0.0022 max mem: 19788 +Test: [18300/21770] eta: 0:04:14 time: 0.0650 data: 0.0019 max mem: 19788 +Test: [18400/21770] eta: 0:04:06 time: 0.0777 data: 0.0024 max mem: 19788 +Test: [18500/21770] eta: 0:03:59 time: 0.0632 data: 0.0021 max mem: 19788 +Test: [18600/21770] eta: 0:03:52 time: 0.0778 data: 0.0024 max mem: 19788 +Test: [18700/21770] eta: 0:03:44 time: 0.0656 data: 0.0020 max mem: 19788 +Test: [18800/21770] eta: 0:03:37 time: 0.0642 data: 0.0019 max mem: 19788 +Test: [18900/21770] eta: 0:03:29 time: 0.0866 data: 0.0026 max mem: 19788 +Test: [19000/21770] eta: 0:03:22 time: 0.0816 data: 0.0022 max mem: 19788 +Test: [19100/21770] eta: 0:03:15 time: 0.0639 data: 0.0019 max mem: 19788 +Test: [19200/21770] eta: 0:03:08 time: 0.0833 data: 0.0026 max mem: 19788 +Test: [19300/21770] eta: 0:03:00 time: 0.0647 data: 0.0020 max mem: 19788 +Test: [19400/21770] eta: 0:02:53 time: 0.0652 data: 0.0020 max mem: 19788 +Test: [19500/21770] eta: 0:02:46 time: 0.0846 data: 0.0024 max mem: 19788 +Test: [19600/21770] eta: 0:02:39 time: 0.0846 data: 0.0026 max mem: 19788 +Test: [19700/21770] eta: 0:02:31 time: 0.0722 data: 0.0020 max mem: 19788 +Test: [19800/21770] eta: 0:02:24 time: 0.0637 data: 0.0020 max mem: 19788 +Test: [19900/21770] eta: 0:02:17 time: 0.0647 data: 0.0020 max mem: 19788 +Test: [20000/21770] eta: 0:02:09 time: 0.0652 data: 0.0022 max mem: 19788 +Test: [20100/21770] eta: 0:02:02 time: 0.0852 data: 0.0028 max mem: 19788 +Test: [20200/21770] eta: 0:01:55 time: 0.0646 data: 0.0022 max mem: 19788 +Test: [20300/21770] eta: 0:01:47 time: 0.0838 data: 0.0024 max mem: 19788 +Test: [20400/21770] eta: 0:01:40 time: 0.0840 data: 0.0026 max mem: 19788 +Test: [20500/21770] eta: 0:01:33 time: 0.0838 data: 0.0025 max mem: 19788 +Test: [20600/21770] eta: 0:01:25 time: 0.0840 data: 0.0025 max mem: 19788 +Test: [20700/21770] eta: 0:01:18 time: 0.0839 data: 0.0024 max mem: 19788 +Test: [20800/21770] eta: 0:01:11 time: 0.0841 data: 0.0024 max mem: 19788 +Test: [20900/21770] eta: 0:01:03 time: 0.0648 data: 0.0019 max mem: 19788 +Test: [21000/21770] eta: 0:00:56 time: 0.0635 data: 0.0021 max mem: 19788 +Test: [21100/21770] eta: 0:00:49 time: 0.0697 data: 0.0020 max mem: 19788 +Test: [21200/21770] eta: 0:00:41 time: 0.0631 data: 0.0020 max mem: 19788 +Test: [21300/21770] eta: 0:00:34 time: 0.0639 data: 0.0020 max mem: 19788 +Test: [21400/21770] eta: 0:00:27 time: 0.0668 data: 0.0021 max mem: 19788 +Test: [21500/21770] eta: 0:00:19 time: 0.0637 data: 0.0021 max mem: 19788 +Test: [21600/21770] eta: 0:00:12 time: 0.0702 data: 0.0020 max mem: 19788 +Test: [21700/21770] eta: 0:00:05 time: 0.0653 data: 0.0021 max mem: 19788 +Test: Total time: 0:26:37 +Final results: +Mean IoU is 48.68 + + precision@0.5 = 52.97 + precision@0.6 = 46.55 + precision@0.7 = 38.71 + precision@0.8 = 27.92 + precision@0.9 = 9.50 + overall IoU = 54.72 + mean IoU = 48.68 + +Mean accuracy for one-to-zero sample is 75.72 + +Average object IoU 0.4867554023424406 +Overall IoU 54.71723556518555 +Better epoch: 0 + +Epoch: [1] [ 0/2138] eta: 17:49:45 lr: 4.8873053160605256e-05 loss: 0.2448 (0.2448) time: 30.0212 data: 1.5315 max mem: 19788 +Epoch: [1] [ 10/2138] eta: 3:46:56 lr: 4.886777785668473e-05 loss: 0.1437 (0.1710) time: 6.3985 data: 0.1416 max mem: 19788 +Epoch: [1] [ 20/2138] eta: 3:06:32 lr: 4.8862502489488774e-05 loss: 0.1365 (0.1555) time: 4.0477 data: 0.0027 max mem: 19788 +Epoch: [1] [ 30/2138] eta: 2:49:26 lr: 4.8857227059009036e-05 loss: 0.1374 (0.1517) time: 3.9564 data: 0.0030 max mem: 19788 +Epoch: [1] [ 40/2138] eta: 2:43:01 lr: 4.885195156523718e-05 loss: 0.1410 (0.1500) time: 4.0091 data: 0.0032 max mem: 19788 +Epoch: [1] [ 50/2138] eta: 2:37:18 lr: 4.884667600816484e-05 loss: 0.1479 (0.1547) time: 4.0517 data: 0.0031 max mem: 19788 +Epoch: [1] [ 60/2138] eta: 2:34:06 lr: 4.884140038778367e-05 loss: 0.1588 (0.1561) time: 4.0137 data: 0.0035 max mem: 19788 +Epoch: [1] [ 70/2138] eta: 2:29:55 lr: 4.883612470408529e-05 loss: 0.1344 (0.1526) time: 3.9139 data: 0.0036 max mem: 19788 +Epoch: [1] [ 80/2138] eta: 2:27:22 lr: 4.8830848957061366e-05 loss: 0.1335 (0.1556) time: 3.8295 data: 0.0034 max mem: 19788 +Epoch: [1] [ 90/2138] eta: 2:25:32 lr: 4.882557314670352e-05 loss: 0.1489 (0.1586) time: 3.9587 data: 0.0032 max mem: 19788 +Epoch: [1] [ 100/2138] eta: 2:23:38 lr: 4.8820297273003384e-05 loss: 0.1444 (0.1583) time: 3.9546 data: 0.0030 max mem: 19788 +Epoch: [1] [ 110/2138] eta: 2:22:14 lr: 4.881502133595261e-05 loss: 0.1422 (0.1590) time: 3.9552 data: 0.0030 max mem: 19788 +Epoch: [1] [ 120/2138] eta: 2:21:21 lr: 4.880974533554281e-05 loss: 0.1404 (0.1570) time: 4.0711 data: 0.0030 max mem: 19788 +Epoch: [1] [ 130/2138] eta: 2:20:21 lr: 4.880446927176563e-05 loss: 0.1404 (0.1602) time: 4.1157 data: 0.0030 max mem: 19788 +Epoch: [1] [ 140/2138] eta: 2:19:37 lr: 4.879919314461268e-05 loss: 0.1419 (0.1614) time: 4.1344 data: 0.0031 max mem: 19788 +Epoch: [1] [ 150/2138] eta: 2:18:18 lr: 4.87939169540756e-05 loss: 0.1401 (0.1605) time: 4.0470 data: 0.0034 max mem: 19788 +Epoch: [1] [ 160/2138] eta: 2:17:37 lr: 4.878864070014601e-05 loss: 0.1488 (0.1611) time: 4.0449 data: 0.0034 max mem: 19788 +Epoch: [1] [ 170/2138] eta: 2:16:45 lr: 4.8783364382815523e-05 loss: 0.1499 (0.1606) time: 4.1320 data: 0.0031 max mem: 19788 +Epoch: [1] [ 180/2138] eta: 2:15:56 lr: 4.877808800207576e-05 loss: 0.1405 (0.1601) time: 4.0934 data: 0.0032 max mem: 19788 +Epoch: [1] [ 190/2138] eta: 2:14:58 lr: 4.877281155791835e-05 loss: 0.1461 (0.1598) time: 4.0546 data: 0.0033 max mem: 19788 +Epoch: [1] [ 200/2138] eta: 2:13:55 lr: 4.876753505033489e-05 loss: 0.1324 (0.1581) time: 3.9716 data: 0.0033 max mem: 19788 +Epoch: [1] [ 210/2138] eta: 2:12:39 lr: 4.8762258479317e-05 loss: 0.1364 (0.1587) time: 3.8521 data: 0.0034 max mem: 19788 +Epoch: [1] [ 220/2138] eta: 2:11:46 lr: 4.875698184485629e-05 loss: 0.1613 (0.1589) time: 3.8804 data: 0.0035 max mem: 19788 +Epoch: [1] [ 230/2138] eta: 2:11:09 lr: 4.875170514694438e-05 loss: 0.1577 (0.1593) time: 4.0827 data: 0.0033 max mem: 19788 +Epoch: [1] [ 240/2138] eta: 2:10:25 lr: 4.874642838557285e-05 loss: 0.1581 (0.1591) time: 4.1307 data: 0.0033 max mem: 19788 +Epoch: [1] [ 250/2138] eta: 2:09:52 lr: 4.8741151560733324e-05 loss: 0.1581 (0.1594) time: 4.1564 data: 0.0034 max mem: 19788 +Epoch: [1] [ 260/2138] eta: 2:08:49 lr: 4.8735874672417394e-05 loss: 0.1401 (0.1589) time: 4.0306 data: 0.0031 max mem: 19788 +Epoch: [1] [ 270/2138] eta: 2:08:00 lr: 4.873059772061667e-05 loss: 0.1568 (0.1596) time: 3.9157 data: 0.0031 max mem: 19788 +Epoch: [1] [ 280/2138] eta: 2:07:27 lr: 4.8725320705322737e-05 loss: 0.1738 (0.1596) time: 4.1144 data: 0.0032 max mem: 19788 +Epoch: [1] [ 290/2138] eta: 2:06:45 lr: 4.87200436265272e-05 loss: 0.1485 (0.1594) time: 4.1666 data: 0.0032 max mem: 19788 +Epoch: [1] [ 300/2138] eta: 2:05:46 lr: 4.8714766484221655e-05 loss: 0.1474 (0.1591) time: 3.9647 data: 0.0036 max mem: 19788 +Epoch: [1] [ 310/2138] eta: 2:05:13 lr: 4.870948927839768e-05 loss: 0.1253 (0.1585) time: 4.0378 data: 0.0037 max mem: 19788 +Epoch: [1] [ 320/2138] eta: 2:04:30 lr: 4.8704212009046874e-05 loss: 0.1224 (0.1579) time: 4.1629 data: 0.0034 max mem: 19788 +Epoch: [1] [ 330/2138] eta: 2:03:51 lr: 4.869893467616082e-05 loss: 0.1314 (0.1581) time: 4.1135 data: 0.0032 max mem: 19788 +Epoch: [1] [ 340/2138] eta: 2:03:13 lr: 4.8693657279731106e-05 loss: 0.1433 (0.1579) time: 4.1576 data: 0.0031 max mem: 19788 +Epoch: [1] [ 350/2138] eta: 2:02:35 lr: 4.8688379819749313e-05 loss: 0.1431 (0.1576) time: 4.1661 data: 0.0032 max mem: 19788 +Epoch: [1] [ 360/2138] eta: 2:01:40 lr: 4.8683102296207015e-05 loss: 0.1470 (0.1584) time: 4.0016 data: 0.0032 max mem: 19788 +Epoch: [1] [ 370/2138] eta: 2:00:54 lr: 4.86778247090958e-05 loss: 0.1470 (0.1583) time: 3.9147 data: 0.0032 max mem: 19788 +Epoch: [1] [ 380/2138] eta: 2:00:20 lr: 4.867254705840724e-05 loss: 0.1401 (0.1578) time: 4.1241 data: 0.0031 max mem: 19788 +Epoch: [1] [ 390/2138] eta: 1:59:27 lr: 4.8667269344132914e-05 loss: 0.1398 (0.1579) time: 4.0573 data: 0.0032 max mem: 19788 +Epoch: [1] [ 400/2138] eta: 1:58:55 lr: 4.866199156626439e-05 loss: 0.1441 (0.1577) time: 4.0747 data: 0.0033 max mem: 19788 +Epoch: [1] [ 410/2138] eta: 1:58:06 lr: 4.865671372479324e-05 loss: 0.1476 (0.1578) time: 4.1099 data: 0.0035 max mem: 19788 +Epoch: [1] [ 420/2138] eta: 1:57:18 lr: 4.865143581971103e-05 loss: 0.1553 (0.1581) time: 3.9240 data: 0.0034 max mem: 19788 +Epoch: [1] [ 430/2138] eta: 1:56:30 lr: 4.864615785100932e-05 loss: 0.1553 (0.1577) time: 3.9245 data: 0.0031 max mem: 19788 +Epoch: [1] [ 440/2138] eta: 1:55:43 lr: 4.864087981867968e-05 loss: 0.1616 (0.1584) time: 3.9254 data: 0.0031 max mem: 19788 +Epoch: [1] [ 450/2138] eta: 1:54:49 lr: 4.8635601722713666e-05 loss: 0.1349 (0.1580) time: 3.8350 data: 0.0032 max mem: 19788 +Epoch: [1] [ 460/2138] eta: 1:54:02 lr: 4.8630323563102845e-05 loss: 0.1331 (0.1582) time: 3.8371 data: 0.0033 max mem: 19788 +Epoch: [1] [ 470/2138] eta: 1:53:24 lr: 4.8625045339838766e-05 loss: 0.1663 (0.1586) time: 4.0344 data: 0.0032 max mem: 19788 +Epoch: [1] [ 480/2138] eta: 1:52:32 lr: 4.8619767052913e-05 loss: 0.1595 (0.1586) time: 3.9503 data: 0.0034 max mem: 19788 +Epoch: [1] [ 490/2138] eta: 1:51:52 lr: 4.861448870231707e-05 loss: 0.1447 (0.1587) time: 3.9301 data: 0.0033 max mem: 19788 +Epoch: [1] [ 500/2138] eta: 1:51:08 lr: 4.860921028804256e-05 loss: 0.1447 (0.1590) time: 4.0307 data: 0.0031 max mem: 19788 +Epoch: [1] [ 510/2138] eta: 1:50:25 lr: 4.8603931810081e-05 loss: 0.1391 (0.1590) time: 3.9839 data: 0.0032 max mem: 19788 +Epoch: [1] [ 520/2138] eta: 1:49:39 lr: 4.859865326842394e-05 loss: 0.1463 (0.1592) time: 3.9572 data: 0.0030 max mem: 19788 +Epoch: [1] [ 530/2138] eta: 1:49:01 lr: 4.859337466306292e-05 loss: 0.1518 (0.1592) time: 4.0295 data: 0.0029 max mem: 19788 +Epoch: [1] [ 540/2138] eta: 1:48:21 lr: 4.858809599398949e-05 loss: 0.1392 (0.1588) time: 4.1175 data: 0.0030 max mem: 19788 +Epoch: [1] [ 550/2138] eta: 1:47:34 lr: 4.858281726119517e-05 loss: 0.1265 (0.1581) time: 3.9659 data: 0.0033 max mem: 19788 +Epoch: [1] [ 560/2138] eta: 1:46:56 lr: 4.857753846467153e-05 loss: 0.1374 (0.1586) time: 4.0014 data: 0.0034 max mem: 19788 +Epoch: [1] [ 570/2138] eta: 1:46:14 lr: 4.857225960441009e-05 loss: 0.1483 (0.1585) time: 4.0782 data: 0.0031 max mem: 19788 +Epoch: [1] [ 580/2138] eta: 1:45:27 lr: 4.856698068040238e-05 loss: 0.1458 (0.1582) time: 3.9225 data: 0.0032 max mem: 19788 +Epoch: [1] [ 590/2138] eta: 1:44:49 lr: 4.8561701692639924e-05 loss: 0.1364 (0.1580) time: 4.0007 data: 0.0033 max mem: 19788 +Epoch: [1] [ 600/2138] eta: 1:44:06 lr: 4.855642264111427e-05 loss: 0.1364 (0.1580) time: 4.0722 data: 0.0034 max mem: 19788 +Epoch: [1] [ 610/2138] eta: 1:43:24 lr: 4.855114352581694e-05 loss: 0.1493 (0.1580) time: 3.9846 data: 0.0035 max mem: 19788 +Epoch: [1] [ 620/2138] eta: 1:42:44 lr: 4.854586434673945e-05 loss: 0.1468 (0.1579) time: 4.0433 data: 0.0032 max mem: 19788 +Epoch: [1] [ 630/2138] eta: 1:41:58 lr: 4.8540585103873324e-05 loss: 0.1493 (0.1579) time: 3.9648 data: 0.0031 max mem: 19788 +Epoch: [1] [ 640/2138] eta: 1:41:19 lr: 4.853530579721009e-05 loss: 0.1551 (0.1578) time: 3.9682 data: 0.0034 max mem: 19788 +Epoch: [1] [ 650/2138] eta: 1:40:35 lr: 4.8530026426741266e-05 loss: 0.1257 (0.1576) time: 4.0282 data: 0.0033 max mem: 19788 +Epoch: [1] [ 660/2138] eta: 1:39:50 lr: 4.8524746992458366e-05 loss: 0.1306 (0.1576) time: 3.8987 data: 0.0030 max mem: 19788 +Epoch: [1] [ 670/2138] eta: 1:39:18 lr: 4.85194674943529e-05 loss: 0.1488 (0.1575) time: 4.1363 data: 0.0031 max mem: 19788 +Epoch: [1] [ 680/2138] eta: 1:38:36 lr: 4.8514187932416384e-05 loss: 0.1505 (0.1577) time: 4.2133 data: 0.0033 max mem: 19788 +Epoch: [1] [ 690/2138] eta: 1:37:53 lr: 4.850890830664032e-05 loss: 0.1517 (0.1576) time: 3.9629 data: 0.0033 max mem: 19788 +Epoch: [1] [ 700/2138] eta: 1:37:09 lr: 4.8503628617016235e-05 loss: 0.1517 (0.1579) time: 3.9194 data: 0.0032 max mem: 19788 +Epoch: [1] [ 710/2138] eta: 1:36:26 lr: 4.8498348863535616e-05 loss: 0.1765 (0.1583) time: 3.9115 data: 0.0034 max mem: 19788 +Epoch: [1] [ 720/2138] eta: 1:35:41 lr: 4.8493069046189974e-05 loss: 0.1736 (0.1586) time: 3.8698 data: 0.0038 max mem: 19788 +Epoch: [1] [ 730/2138] eta: 1:34:55 lr: 4.848778916497081e-05 loss: 0.1546 (0.1584) time: 3.7938 data: 0.0037 max mem: 19788 +Epoch: [1] [ 740/2138] eta: 1:34:15 lr: 4.848250921986962e-05 loss: 0.1254 (0.1580) time: 3.9191 data: 0.0035 max mem: 19788 +Epoch: [1] [ 750/2138] eta: 1:33:31 lr: 4.847722921087791e-05 loss: 0.1276 (0.1578) time: 3.9614 data: 0.0033 max mem: 19788 +Epoch: [1] [ 760/2138] eta: 1:32:51 lr: 4.847194913798715e-05 loss: 0.1560 (0.1579) time: 3.9623 data: 0.0032 max mem: 19788 +Epoch: [1] [ 770/2138] eta: 1:32:09 lr: 4.8466669001188865e-05 loss: 0.1575 (0.1578) time: 4.0096 data: 0.0031 max mem: 19788 +Epoch: [1] [ 780/2138] eta: 1:31:26 lr: 4.8461388800474525e-05 loss: 0.1572 (0.1577) time: 3.9233 data: 0.0031 max mem: 19788 +Epoch: [1] [ 790/2138] eta: 1:30:44 lr: 4.8456108535835625e-05 loss: 0.1679 (0.1578) time: 3.9163 data: 0.0034 max mem: 19788 +Epoch: [1] [ 800/2138] eta: 1:30:08 lr: 4.8450828207263646e-05 loss: 0.1483 (0.1574) time: 4.1172 data: 0.0035 max mem: 19788 +Epoch: [1] [ 810/2138] eta: 1:29:32 lr: 4.844554781475008e-05 loss: 0.1427 (0.1572) time: 4.3190 data: 0.0034 max mem: 19788 +Epoch: [1] [ 820/2138] eta: 1:28:57 lr: 4.84402673582864e-05 loss: 0.1355 (0.1569) time: 4.3576 data: 0.0031 max mem: 19788 +Epoch: [1] [ 830/2138] eta: 1:28:16 lr: 4.84349868378641e-05 loss: 0.1316 (0.1568) time: 4.1870 data: 0.0031 max mem: 19788 +Epoch: [1] [ 840/2138] eta: 1:27:33 lr: 4.842970625347464e-05 loss: 0.1273 (0.1566) time: 3.9503 data: 0.0031 max mem: 19788 +Epoch: [1] [ 850/2138] eta: 1:26:53 lr: 4.84244256051095e-05 loss: 0.1274 (0.1566) time: 4.0064 data: 0.0031 max mem: 19788 +Epoch: [1] [ 860/2138] eta: 1:26:14 lr: 4.841914489276016e-05 loss: 0.1411 (0.1565) time: 4.0955 data: 0.0034 max mem: 19788 +Epoch: [1] [ 870/2138] eta: 1:25:30 lr: 4.841386411641808e-05 loss: 0.1411 (0.1563) time: 3.9678 data: 0.0033 max mem: 19788 +Epoch: [1] [ 880/2138] eta: 1:24:51 lr: 4.8408583276074746e-05 loss: 0.1410 (0.1562) time: 4.0045 data: 0.0031 max mem: 19788 +Epoch: [1] [ 890/2138] eta: 1:24:13 lr: 4.840330237172161e-05 loss: 0.1592 (0.1562) time: 4.1794 data: 0.0031 max mem: 19788 +Epoch: [1] [ 900/2138] eta: 1:23:32 lr: 4.8398021403350134e-05 loss: 0.1596 (0.1569) time: 4.1066 data: 0.0031 max mem: 19788 +Epoch: [1] [ 910/2138] eta: 1:22:50 lr: 4.8392740370951795e-05 loss: 0.1512 (0.1568) time: 3.9989 data: 0.0032 max mem: 19788 +Epoch: [1] [ 920/2138] eta: 1:22:08 lr: 4.838745927451804e-05 loss: 0.1418 (0.1569) time: 3.9204 data: 0.0033 max mem: 19788 +Epoch: [1] [ 930/2138] eta: 1:21:25 lr: 4.8382178114040334e-05 loss: 0.1425 (0.1568) time: 3.8902 data: 0.0035 max mem: 19788 +Epoch: [1] [ 940/2138] eta: 1:20:42 lr: 4.837689688951012e-05 loss: 0.1423 (0.1568) time: 3.8703 data: 0.0033 max mem: 19788 +Epoch: [1] [ 950/2138] eta: 1:20:03 lr: 4.8371615600918875e-05 loss: 0.1394 (0.1568) time: 4.0004 data: 0.0030 max mem: 19788 +Epoch: [1] [ 960/2138] eta: 1:19:24 lr: 4.836633424825803e-05 loss: 0.1438 (0.1567) time: 4.1325 data: 0.0032 max mem: 19788 +Epoch: [1] [ 970/2138] eta: 1:18:43 lr: 4.8361052831519046e-05 loss: 0.1357 (0.1564) time: 4.0830 data: 0.0033 max mem: 19788 +Epoch: [1] [ 980/2138] eta: 1:18:04 lr: 4.8355771350693354e-05 loss: 0.1484 (0.1564) time: 4.1159 data: 0.0032 max mem: 19788 +Epoch: [1] [ 990/2138] eta: 1:17:23 lr: 4.835048980577242e-05 loss: 0.1513 (0.1562) time: 4.0829 data: 0.0031 max mem: 19788 +Epoch: [1] [1000/2138] eta: 1:16:42 lr: 4.834520819674767e-05 loss: 0.1250 (0.1560) time: 3.9628 data: 0.0030 max mem: 19788 +Epoch: [1] [1010/2138] eta: 1:16:00 lr: 4.833992652361055e-05 loss: 0.1374 (0.1559) time: 3.9217 data: 0.0031 max mem: 19788 +Epoch: [1] [1020/2138] eta: 1:15:19 lr: 4.8334644786352506e-05 loss: 0.1275 (0.1556) time: 3.9515 data: 0.0035 max mem: 19788 +Epoch: [1] [1030/2138] eta: 1:14:37 lr: 4.832936298496496e-05 loss: 0.1147 (0.1554) time: 3.9475 data: 0.0036 max mem: 19788 +Epoch: [1] [1040/2138] eta: 1:13:55 lr: 4.8324081119439365e-05 loss: 0.1527 (0.1555) time: 3.9162 data: 0.0035 max mem: 19788 +Epoch: [1] [1050/2138] eta: 1:13:15 lr: 4.8318799189767126e-05 loss: 0.1546 (0.1553) time: 3.9913 data: 0.0032 max mem: 19788 +Epoch: [1] [1060/2138] eta: 1:12:37 lr: 4.83135171959397e-05 loss: 0.1344 (0.1552) time: 4.1711 data: 0.0030 max mem: 19788 +Epoch: [1] [1070/2138] eta: 1:11:58 lr: 4.8308235137948486e-05 loss: 0.1243 (0.1550) time: 4.2375 data: 0.0031 max mem: 19788 +Epoch: [1] [1080/2138] eta: 1:11:17 lr: 4.830295301578493e-05 loss: 0.1307 (0.1549) time: 4.1018 data: 0.0031 max mem: 19788 +Epoch: [1] [1090/2138] eta: 1:10:37 lr: 4.8297670829440454e-05 loss: 0.1336 (0.1550) time: 4.0405 data: 0.0030 max mem: 19788 +Epoch: [1] [1100/2138] eta: 1:09:55 lr: 4.8292388578906476e-05 loss: 0.1493 (0.1551) time: 3.9705 data: 0.0036 max mem: 19788 +Epoch: [1] [1110/2138] eta: 1:09:13 lr: 4.828710626417441e-05 loss: 0.1411 (0.1548) time: 3.8840 data: 0.0038 max mem: 19788 +Epoch: [1] [1120/2138] eta: 1:08:32 lr: 4.828182388523567e-05 loss: 0.1283 (0.1547) time: 3.9431 data: 0.0035 max mem: 19788 +Epoch: [1] [1130/2138] eta: 1:07:51 lr: 4.827654144208168e-05 loss: 0.1492 (0.1548) time: 3.9543 data: 0.0033 max mem: 19788 +Epoch: [1] [1140/2138] eta: 1:07:10 lr: 4.827125893470385e-05 loss: 0.1492 (0.1547) time: 3.9624 data: 0.0032 max mem: 19788 +Epoch: [1] [1150/2138] eta: 1:06:29 lr: 4.8265976363093584e-05 loss: 0.1265 (0.1545) time: 3.9761 data: 0.0033 max mem: 19788 +Epoch: [1] [1160/2138] eta: 1:05:48 lr: 4.826069372724229e-05 loss: 0.1155 (0.1546) time: 3.9454 data: 0.0034 max mem: 19788 +Epoch: [1] [1170/2138] eta: 1:05:08 lr: 4.825541102714138e-05 loss: 0.1318 (0.1545) time: 4.0010 data: 0.0032 max mem: 19788 +Epoch: [1] [1180/2138] eta: 1:04:25 lr: 4.825012826278226e-05 loss: 0.1469 (0.1547) time: 3.9144 data: 0.0032 max mem: 19788 +Epoch: [1] [1190/2138] eta: 1:03:45 lr: 4.824484543415631e-05 loss: 0.1653 (0.1545) time: 3.8909 data: 0.0033 max mem: 19788 +Epoch: [1] [1200/2138] eta: 1:03:03 lr: 4.823956254125495e-05 loss: 0.1387 (0.1545) time: 3.9535 data: 0.0034 max mem: 19788 +Epoch: [1] [1210/2138] eta: 1:02:23 lr: 4.823427958406957e-05 loss: 0.1402 (0.1544) time: 3.9773 data: 0.0034 max mem: 19788 +Epoch: [1] [1220/2138] eta: 1:01:46 lr: 4.822899656259156e-05 loss: 0.1409 (0.1546) time: 4.2663 data: 0.0032 max mem: 19788 +Epoch: [1] [1230/2138] eta: 1:01:07 lr: 4.822371347681233e-05 loss: 0.1410 (0.1546) time: 4.3236 data: 0.0032 max mem: 19788 +Epoch: [1] [1240/2138] eta: 1:00:25 lr: 4.821843032672325e-05 loss: 0.1448 (0.1545) time: 4.0159 data: 0.0031 max mem: 19788 +Epoch: [1] [1250/2138] eta: 0:59:44 lr: 4.821314711231571e-05 loss: 0.1411 (0.1544) time: 3.8734 data: 0.0034 max mem: 19788 +Epoch: [1] [1260/2138] eta: 0:59:02 lr: 4.8207863833581104e-05 loss: 0.1371 (0.1544) time: 3.8588 data: 0.0037 max mem: 19788 +Epoch: [1] [1270/2138] eta: 0:58:24 lr: 4.820258049051081e-05 loss: 0.1371 (0.1544) time: 4.0914 data: 0.0033 max mem: 19788 +Epoch: [1] [1280/2138] eta: 0:57:44 lr: 4.819729708309621e-05 loss: 0.1358 (0.1545) time: 4.2757 data: 0.0032 max mem: 19788 +Epoch: [1] [1290/2138] eta: 0:57:03 lr: 4.819201361132868e-05 loss: 0.1441 (0.1546) time: 4.0120 data: 0.0032 max mem: 19788 +Epoch: [1] [1300/2138] eta: 0:56:23 lr: 4.8186730075199605e-05 loss: 0.1567 (0.1546) time: 4.0016 data: 0.0031 max mem: 19788 +Epoch: [1] [1310/2138] eta: 0:55:41 lr: 4.8181446474700355e-05 loss: 0.1506 (0.1545) time: 3.9927 data: 0.0030 max mem: 19788 +Epoch: [1] [1320/2138] eta: 0:55:02 lr: 4.81761628098223e-05 loss: 0.1495 (0.1545) time: 3.9827 data: 0.0030 max mem: 19788 +Epoch: [1] [1330/2138] eta: 0:54:21 lr: 4.817087908055682e-05 loss: 0.1316 (0.1543) time: 4.0535 data: 0.0032 max mem: 19788 +Epoch: [1] [1340/2138] eta: 0:53:41 lr: 4.816559528689527e-05 loss: 0.1340 (0.1544) time: 4.0218 data: 0.0033 max mem: 19788 +Epoch: [1] [1350/2138] eta: 0:53:01 lr: 4.816031142882903e-05 loss: 0.1388 (0.1542) time: 4.1208 data: 0.0032 max mem: 19788 +Epoch: [1] [1360/2138] eta: 0:52:22 lr: 4.8155027506349434e-05 loss: 0.1317 (0.1540) time: 4.2538 data: 0.0032 max mem: 19788 +Epoch: [1] [1370/2138] eta: 0:51:42 lr: 4.814974351944788e-05 loss: 0.1331 (0.1539) time: 4.1552 data: 0.0032 max mem: 19788 +Epoch: [1] [1380/2138] eta: 0:51:03 lr: 4.8144459468115714e-05 loss: 0.1282 (0.1538) time: 4.1836 data: 0.0033 max mem: 19788 +Epoch: [1] [1390/2138] eta: 0:50:23 lr: 4.813917535234428e-05 loss: 0.1397 (0.1538) time: 4.2504 data: 0.0033 max mem: 19788 +Epoch: [1] [1400/2138] eta: 0:49:45 lr: 4.813389117212495e-05 loss: 0.1461 (0.1537) time: 4.2915 data: 0.0032 max mem: 19788 +Epoch: [1] [1410/2138] eta: 0:49:04 lr: 4.8128606927449064e-05 loss: 0.1125 (0.1535) time: 4.2017 data: 0.0032 max mem: 19788 +Epoch: [1] [1420/2138] eta: 0:48:25 lr: 4.8123322618307984e-05 loss: 0.1100 (0.1533) time: 4.1007 data: 0.0034 max mem: 19788 +Epoch: [1] [1430/2138] eta: 0:47:44 lr: 4.8118038244693046e-05 loss: 0.1231 (0.1532) time: 4.1337 data: 0.0034 max mem: 19788 +Epoch: [1] [1440/2138] eta: 0:47:04 lr: 4.8112753806595604e-05 loss: 0.1251 (0.1530) time: 4.0718 data: 0.0033 max mem: 19788 +Epoch: [1] [1450/2138] eta: 0:46:25 lr: 4.8107469304007004e-05 loss: 0.1251 (0.1530) time: 4.2750 data: 0.0032 max mem: 19788 +Epoch: [1] [1460/2138] eta: 0:45:44 lr: 4.8102184736918574e-05 loss: 0.1369 (0.1530) time: 4.1518 data: 0.0032 max mem: 19788 +Epoch: [1] [1470/2138] eta: 0:45:05 lr: 4.809690010532167e-05 loss: 0.1449 (0.1530) time: 4.1099 data: 0.0034 max mem: 19788 +Epoch: [1] [1480/2138] eta: 0:44:26 lr: 4.809161540920762e-05 loss: 0.1449 (0.1529) time: 4.3411 data: 0.0034 max mem: 19788 +Epoch: [1] [1490/2138] eta: 0:43:44 lr: 4.808633064856776e-05 loss: 0.1466 (0.1529) time: 4.1071 data: 0.0033 max mem: 19788 +Epoch: [1] [1500/2138] eta: 0:43:03 lr: 4.8081045823393415e-05 loss: 0.1482 (0.1529) time: 3.8555 data: 0.0033 max mem: 19788 +Epoch: [1] [1510/2138] eta: 0:42:22 lr: 4.807576093367593e-05 loss: 0.1316 (0.1528) time: 3.9511 data: 0.0032 max mem: 19788 +Epoch: [1] [1520/2138] eta: 0:41:42 lr: 4.807047597940662e-05 loss: 0.1319 (0.1529) time: 4.0894 data: 0.0030 max mem: 19788 +Epoch: [1] [1530/2138] eta: 0:41:01 lr: 4.806519096057682e-05 loss: 0.1350 (0.1528) time: 4.0291 data: 0.0031 max mem: 19788 +Epoch: [1] [1540/2138] eta: 0:40:21 lr: 4.8059905877177844e-05 loss: 0.1250 (0.1527) time: 3.9884 data: 0.0032 max mem: 19788 +Epoch: [1] [1550/2138] eta: 0:39:39 lr: 4.8054620729201036e-05 loss: 0.1233 (0.1526) time: 3.9163 data: 0.0031 max mem: 19788 +Epoch: [1] [1560/2138] eta: 0:38:59 lr: 4.804933551663769e-05 loss: 0.1261 (0.1526) time: 3.9812 data: 0.0033 max mem: 19788 +Epoch: [1] [1570/2138] eta: 0:38:18 lr: 4.8044050239479124e-05 loss: 0.1411 (0.1525) time: 4.0257 data: 0.0033 max mem: 19788 +Epoch: [1] [1580/2138] eta: 0:37:38 lr: 4.803876489771666e-05 loss: 0.1444 (0.1525) time: 4.0000 data: 0.0031 max mem: 19788 +Epoch: [1] [1590/2138] eta: 0:36:58 lr: 4.803347949134162e-05 loss: 0.1214 (0.1523) time: 4.1921 data: 0.0031 max mem: 19788 +Epoch: [1] [1600/2138] eta: 0:36:17 lr: 4.8028194020345303e-05 loss: 0.1314 (0.1523) time: 4.0946 data: 0.0032 max mem: 19788 +Epoch: [1] [1610/2138] eta: 0:35:37 lr: 4.8022908484719015e-05 loss: 0.1314 (0.1522) time: 3.9625 data: 0.0033 max mem: 19788 +Epoch: [1] [1620/2138] eta: 0:34:57 lr: 4.801762288445407e-05 loss: 0.1306 (0.1522) time: 4.0800 data: 0.0032 max mem: 19788 +Epoch: [1] [1630/2138] eta: 0:34:16 lr: 4.801233721954177e-05 loss: 0.1458 (0.1523) time: 4.0751 data: 0.0031 max mem: 19788 +Epoch: [1] [1640/2138] eta: 0:33:35 lr: 4.800705148997341e-05 loss: 0.1191 (0.1521) time: 3.9956 data: 0.0032 max mem: 19788 +Epoch: [1] [1650/2138] eta: 0:32:54 lr: 4.800176569574029e-05 loss: 0.1103 (0.1519) time: 3.8722 data: 0.0033 max mem: 19788 +Epoch: [1] [1660/2138] eta: 0:32:13 lr: 4.799647983683371e-05 loss: 0.1184 (0.1518) time: 3.8554 data: 0.0032 max mem: 19788 +Epoch: [1] [1670/2138] eta: 0:31:32 lr: 4.799119391324497e-05 loss: 0.1173 (0.1516) time: 3.9384 data: 0.0032 max mem: 19788 +Epoch: [1] [1680/2138] eta: 0:30:52 lr: 4.798590792496535e-05 loss: 0.1183 (0.1514) time: 4.0405 data: 0.0031 max mem: 19788 +Epoch: [1] [1690/2138] eta: 0:30:12 lr: 4.798062187198615e-05 loss: 0.1228 (0.1515) time: 4.0787 data: 0.0032 max mem: 19788 +Epoch: [1] [1700/2138] eta: 0:29:31 lr: 4.797533575429866e-05 loss: 0.1341 (0.1515) time: 3.9888 data: 0.0035 max mem: 19788 +Epoch: [1] [1710/2138] eta: 0:28:51 lr: 4.7970049571894146e-05 loss: 0.1384 (0.1514) time: 4.1197 data: 0.0033 max mem: 19788 +Epoch: [1] [1720/2138] eta: 0:28:10 lr: 4.7964763324763915e-05 loss: 0.1388 (0.1513) time: 4.0457 data: 0.0032 max mem: 19788 +Epoch: [1] [1730/2138] eta: 0:27:29 lr: 4.795947701289924e-05 loss: 0.1215 (0.1512) time: 3.7982 data: 0.0034 max mem: 19788 +Epoch: [1] [1740/2138] eta: 0:26:48 lr: 4.79541906362914e-05 loss: 0.1116 (0.1510) time: 3.7084 data: 0.0032 max mem: 19788 +Epoch: [1] [1750/2138] eta: 0:26:07 lr: 4.7948904194931665e-05 loss: 0.1182 (0.1510) time: 3.7319 data: 0.0030 max mem: 19788 +Epoch: [1] [1760/2138] eta: 0:25:26 lr: 4.794361768881132e-05 loss: 0.1202 (0.1509) time: 3.7798 data: 0.0030 max mem: 19788 +Epoch: [1] [1770/2138] eta: 0:24:46 lr: 4.793833111792163e-05 loss: 0.1216 (0.1508) time: 3.9516 data: 0.0030 max mem: 19788 +Epoch: [1] [1780/2138] eta: 0:24:05 lr: 4.793304448225387e-05 loss: 0.1297 (0.1507) time: 3.9895 data: 0.0030 max mem: 19788 +Epoch: [1] [1790/2138] eta: 0:23:24 lr: 4.79277577817993e-05 loss: 0.1396 (0.1507) time: 3.8272 data: 0.0030 max mem: 19788 +Epoch: [1] [1800/2138] eta: 0:22:44 lr: 4.7922471016549196e-05 loss: 0.1428 (0.1509) time: 3.9077 data: 0.0031 max mem: 19788 +Epoch: [1] [1810/2138] eta: 0:22:03 lr: 4.7917184186494814e-05 loss: 0.1393 (0.1508) time: 3.8823 data: 0.0032 max mem: 19788 +Epoch: [1] [1820/2138] eta: 0:21:22 lr: 4.7911897291627416e-05 loss: 0.1322 (0.1509) time: 3.7834 data: 0.0035 max mem: 19788 +Epoch: [1] [1830/2138] eta: 0:20:41 lr: 4.790661033193826e-05 loss: 0.1219 (0.1508) time: 3.8175 data: 0.0036 max mem: 19788 +Epoch: [1] [1840/2138] eta: 0:20:01 lr: 4.790132330741861e-05 loss: 0.1287 (0.1509) time: 3.8222 data: 0.0033 max mem: 19788 +Epoch: [1] [1850/2138] eta: 0:19:20 lr: 4.78960362180597e-05 loss: 0.1435 (0.1508) time: 3.8346 data: 0.0033 max mem: 19788 +Epoch: [1] [1860/2138] eta: 0:18:40 lr: 4.789074906385281e-05 loss: 0.1326 (0.1509) time: 4.0132 data: 0.0031 max mem: 19788 +Epoch: [1] [1870/2138] eta: 0:18:00 lr: 4.788546184478917e-05 loss: 0.1507 (0.1510) time: 4.0833 data: 0.0031 max mem: 19788 +Epoch: [1] [1880/2138] eta: 0:17:19 lr: 4.788017456086004e-05 loss: 0.1390 (0.1509) time: 3.8846 data: 0.0033 max mem: 19788 +Epoch: [1] [1890/2138] eta: 0:16:38 lr: 4.7874887212056646e-05 loss: 0.1286 (0.1508) time: 3.7966 data: 0.0034 max mem: 19788 +Epoch: [1] [1900/2138] eta: 0:15:58 lr: 4.786959979837026e-05 loss: 0.1271 (0.1506) time: 3.9168 data: 0.0032 max mem: 19788 +Epoch: [1] [1910/2138] eta: 0:15:18 lr: 4.786431231979209e-05 loss: 0.1237 (0.1506) time: 3.9904 data: 0.0030 max mem: 19788 +Epoch: [1] [1920/2138] eta: 0:14:37 lr: 4.78590247763134e-05 loss: 0.1278 (0.1505) time: 3.8657 data: 0.0032 max mem: 19788 +Epoch: [1] [1930/2138] eta: 0:13:57 lr: 4.7853737167925414e-05 loss: 0.1420 (0.1505) time: 3.7570 data: 0.0032 max mem: 19788 +Epoch: [1] [1940/2138] eta: 0:13:16 lr: 4.784844949461936e-05 loss: 0.1326 (0.1504) time: 3.7557 data: 0.0031 max mem: 19788 +Epoch: [1] [1950/2138] eta: 0:12:36 lr: 4.784316175638649e-05 loss: 0.1236 (0.1503) time: 3.8704 data: 0.0031 max mem: 19788 +Epoch: [1] [1960/2138] eta: 0:11:55 lr: 4.783787395321802e-05 loss: 0.1333 (0.1502) time: 3.9078 data: 0.0032 max mem: 19788 +Epoch: [1] [1970/2138] eta: 0:11:15 lr: 4.7832586085105176e-05 loss: 0.1333 (0.1501) time: 3.8657 data: 0.0033 max mem: 19788 +Epoch: [1] [1980/2138] eta: 0:10:35 lr: 4.7827298152039185e-05 loss: 0.1241 (0.1501) time: 3.9834 data: 0.0034 max mem: 19788 +Epoch: [1] [1990/2138] eta: 0:09:55 lr: 4.782201015401127e-05 loss: 0.1285 (0.1500) time: 4.1825 data: 0.0032 max mem: 19788 +Epoch: [1] [2000/2138] eta: 0:09:15 lr: 4.781672209101265e-05 loss: 0.1318 (0.1499) time: 4.1415 data: 0.0031 max mem: 19788 +Epoch: [1] [2010/2138] eta: 0:08:34 lr: 4.7811433963034555e-05 loss: 0.1385 (0.1499) time: 3.9561 data: 0.0035 max mem: 19788 +Epoch: [1] [2020/2138] eta: 0:07:54 lr: 4.780614577006818e-05 loss: 0.1403 (0.1499) time: 3.8817 data: 0.0039 max mem: 19788 +Epoch: [1] [2030/2138] eta: 0:07:14 lr: 4.780085751210475e-05 loss: 0.1319 (0.1499) time: 3.9529 data: 0.0037 max mem: 19788 +Epoch: [1] [2040/2138] eta: 0:06:34 lr: 4.779556918913547e-05 loss: 0.1273 (0.1499) time: 4.0609 data: 0.0033 max mem: 19788 +Epoch: [1] [2050/2138] eta: 0:05:53 lr: 4.7790280801151565e-05 loss: 0.1303 (0.1498) time: 4.0644 data: 0.0033 max mem: 19788 +Epoch: [1] [2060/2138] eta: 0:05:13 lr: 4.7784992348144225e-05 loss: 0.1391 (0.1497) time: 4.0803 data: 0.0034 max mem: 19788 +Epoch: [1] [2070/2138] eta: 0:04:33 lr: 4.777970383010467e-05 loss: 0.1379 (0.1497) time: 4.0726 data: 0.0034 max mem: 19788 +Epoch: [1] [2080/2138] eta: 0:03:53 lr: 4.7774415247024076e-05 loss: 0.1182 (0.1495) time: 4.0801 data: 0.0035 max mem: 19788 +Epoch: [1] [2090/2138] eta: 0:03:13 lr: 4.776912659889367e-05 loss: 0.1245 (0.1495) time: 4.0584 data: 0.0034 max mem: 19788 +Epoch: [1] [2100/2138] eta: 0:02:32 lr: 4.7763837885704636e-05 loss: 0.1240 (0.1494) time: 3.9539 data: 0.0033 max mem: 19788 +Epoch: [1] [2110/2138] eta: 0:01:52 lr: 4.775854910744818e-05 loss: 0.1429 (0.1496) time: 3.8998 data: 0.0035 max mem: 19788 +Epoch: [1] [2120/2138] eta: 0:01:12 lr: 4.775326026411548e-05 loss: 0.1507 (0.1497) time: 3.9648 data: 0.0034 max mem: 19788 +Epoch: [1] [2130/2138] eta: 0:00:32 lr: 4.7747971355697735e-05 loss: 0.1679 (0.1498) time: 3.9446 data: 0.0030 max mem: 19788 +Epoch: [1] Total time: 2:23:16 +Test: [ 0/21770] eta: 16:37:23 time: 2.7489 data: 2.5911 max mem: 19788 +Test: [ 100/21770] eta: 0:33:50 time: 0.0788 data: 0.0024 max mem: 19788 +Test: [ 200/21770] eta: 0:29:35 time: 0.0636 data: 0.0020 max mem: 19788 +Test: [ 300/21770] eta: 0:27:09 time: 0.0636 data: 0.0020 max mem: 19788 +Test: [ 400/21770] eta: 0:26:12 time: 0.0641 data: 0.0021 max mem: 19788 +Test: [ 500/21770] eta: 0:25:33 time: 0.0766 data: 0.0022 max mem: 19788 +Test: [ 600/21770] eta: 0:24:41 time: 0.0599 data: 0.0018 max mem: 19788 +Test: [ 700/21770] eta: 0:24:39 time: 0.0628 data: 0.0019 max mem: 19788 +Test: [ 800/21770] eta: 0:24:30 time: 0.0610 data: 0.0018 max mem: 19788 +Test: [ 900/21770] eta: 0:24:07 time: 0.0618 data: 0.0018 max mem: 19788 +Test: [ 1000/21770] eta: 0:23:42 time: 0.0588 data: 0.0018 max mem: 19788 +Test: [ 1100/21770] eta: 0:23:21 time: 0.0629 data: 0.0020 max mem: 19788 +Test: [ 1200/21770] eta: 0:23:13 time: 0.0637 data: 0.0021 max mem: 19788 +Test: [ 1300/21770] eta: 0:23:00 time: 0.0604 data: 0.0018 max mem: 19788 +Test: [ 1400/21770] eta: 0:22:45 time: 0.0630 data: 0.0019 max mem: 19788 +Test: [ 1500/21770] eta: 0:22:47 time: 0.0785 data: 0.0023 max mem: 19788 +Test: [ 1600/21770] eta: 0:22:53 time: 0.0812 data: 0.0025 max mem: 19788 +Test: [ 1700/21770] eta: 0:22:48 time: 0.0674 data: 0.0021 max mem: 19788 +Test: [ 1800/21770] eta: 0:22:56 time: 0.0836 data: 0.0026 max mem: 19788 +Test: [ 1900/21770] eta: 0:22:50 time: 0.0612 data: 0.0019 max mem: 19788 +Test: [ 2000/21770] eta: 0:22:41 time: 0.0638 data: 0.0019 max mem: 19788 +Test: [ 2100/21770] eta: 0:22:34 time: 0.0616 data: 0.0017 max mem: 19788 +Test: [ 2200/21770] eta: 0:22:28 time: 0.0675 data: 0.0022 max mem: 19788 +Test: [ 2300/21770] eta: 0:22:28 time: 0.0821 data: 0.0024 max mem: 19788 +Test: [ 2400/21770] eta: 0:22:15 time: 0.0611 data: 0.0018 max mem: 19788 +Test: [ 2500/21770] eta: 0:22:10 time: 0.0782 data: 0.0026 max mem: 19788 +Test: [ 2600/21770] eta: 0:22:08 time: 0.0654 data: 0.0020 max mem: 19788 +Test: [ 2700/21770] eta: 0:22:04 time: 0.0626 data: 0.0020 max mem: 19788 +Test: [ 2800/21770] eta: 0:21:54 time: 0.0715 data: 0.0023 max mem: 19788 +Test: [ 2900/21770] eta: 0:21:49 time: 0.0731 data: 0.0023 max mem: 19788 +Test: [ 3000/21770] eta: 0:21:50 time: 0.0819 data: 0.0025 max mem: 19788 +Test: [ 3100/21770] eta: 0:21:51 time: 0.0820 data: 0.0026 max mem: 19788 +Test: [ 3200/21770] eta: 0:21:40 time: 0.0624 data: 0.0019 max mem: 19788 +Test: [ 3300/21770] eta: 0:21:39 time: 0.0820 data: 0.0023 max mem: 19788 +Test: [ 3400/21770] eta: 0:21:35 time: 0.0802 data: 0.0024 max mem: 19788 +Test: [ 3500/21770] eta: 0:21:24 time: 0.0620 data: 0.0019 max mem: 19788 +Test: [ 3600/21770] eta: 0:21:20 time: 0.0827 data: 0.0025 max mem: 19788 +Test: [ 3700/21770] eta: 0:21:14 time: 0.0813 data: 0.0025 max mem: 19788 +Test: [ 3800/21770] eta: 0:21:08 time: 0.0612 data: 0.0019 max mem: 19788 +Test: [ 3900/21770] eta: 0:20:58 time: 0.0698 data: 0.0018 max mem: 19788 +Test: [ 4000/21770] eta: 0:20:48 time: 0.0636 data: 0.0021 max mem: 19788 +Test: [ 4100/21770] eta: 0:20:38 time: 0.0633 data: 0.0018 max mem: 19788 +Test: [ 4200/21770] eta: 0:20:28 time: 0.0603 data: 0.0018 max mem: 19788 +Test: [ 4300/21770] eta: 0:20:24 time: 0.0774 data: 0.0023 max mem: 19788 +Test: [ 4400/21770] eta: 0:20:22 time: 0.0819 data: 0.0024 max mem: 19788 +Test: [ 4500/21770] eta: 0:20:19 time: 0.0820 data: 0.0026 max mem: 19788 +Test: [ 4600/21770] eta: 0:20:14 time: 0.0677 data: 0.0020 max mem: 19788 +Test: [ 4700/21770] eta: 0:20:10 time: 0.0829 data: 0.0019 max mem: 19788 +Test: [ 4800/21770] eta: 0:20:01 time: 0.0629 data: 0.0018 max mem: 19788 +Test: [ 4900/21770] eta: 0:19:52 time: 0.0611 data: 0.0018 max mem: 19788 +Test: [ 5000/21770] eta: 0:19:42 time: 0.0629 data: 0.0019 max mem: 19788 +Test: [ 5100/21770] eta: 0:19:36 time: 0.0836 data: 0.0026 max mem: 19788 +Test: [ 5200/21770] eta: 0:19:30 time: 0.0834 data: 0.0025 max mem: 19788 +Test: [ 5300/21770] eta: 0:19:24 time: 0.0709 data: 0.0023 max mem: 19788 +Test: [ 5400/21770] eta: 0:19:15 time: 0.0642 data: 0.0019 max mem: 19788 +Test: [ 5500/21770] eta: 0:19:10 time: 0.0834 data: 0.0025 max mem: 19788 +Test: [ 5600/21770] eta: 0:19:03 time: 0.0676 data: 0.0020 max mem: 19788 +Test: [ 5700/21770] eta: 0:18:57 time: 0.0749 data: 0.0024 max mem: 19788 +Test: [ 5800/21770] eta: 0:18:50 time: 0.0833 data: 0.0026 max mem: 19788 +Test: [ 5900/21770] eta: 0:18:46 time: 0.0820 data: 0.0025 max mem: 19788 +Test: [ 6000/21770] eta: 0:18:42 time: 0.0818 data: 0.0024 max mem: 19788 +Test: [ 6100/21770] eta: 0:18:34 time: 0.0629 data: 0.0020 max mem: 19788 +Test: [ 6200/21770] eta: 0:18:25 time: 0.0595 data: 0.0018 max mem: 19788 +Test: [ 6300/21770] eta: 0:18:17 time: 0.0735 data: 0.0022 max mem: 19788 +Test: [ 6400/21770] eta: 0:18:12 time: 0.0822 data: 0.0025 max mem: 19788 +Test: [ 6500/21770] eta: 0:18:08 time: 0.0820 data: 0.0025 max mem: 19788 +Test: [ 6600/21770] eta: 0:18:03 time: 0.0822 data: 0.0026 max mem: 19788 +Test: [ 6700/21770] eta: 0:17:59 time: 0.0823 data: 0.0026 max mem: 19788 +Test: [ 6800/21770] eta: 0:17:54 time: 0.0820 data: 0.0025 max mem: 19788 +Test: [ 6900/21770] eta: 0:17:47 time: 0.0655 data: 0.0019 max mem: 19788 +Test: [ 7000/21770] eta: 0:17:39 time: 0.0616 data: 0.0018 max mem: 19788 +Test: [ 7100/21770] eta: 0:17:30 time: 0.0645 data: 0.0019 max mem: 19788 +Test: [ 7200/21770] eta: 0:17:22 time: 0.0622 data: 0.0018 max mem: 19788 +Test: [ 7300/21770] eta: 0:17:16 time: 0.0817 data: 0.0020 max mem: 19788 +Test: [ 7400/21770] eta: 0:17:07 time: 0.0600 data: 0.0018 max mem: 19788 +Test: [ 7500/21770] eta: 0:17:00 time: 0.0649 data: 0.0019 max mem: 19788 +Test: [ 7600/21770] eta: 0:16:51 time: 0.0637 data: 0.0018 max mem: 19788 +Test: [ 7700/21770] eta: 0:16:42 time: 0.0636 data: 0.0023 max mem: 19788 +Test: [ 7800/21770] eta: 0:16:33 time: 0.0622 data: 0.0018 max mem: 19788 +Test: [ 7900/21770] eta: 0:16:24 time: 0.0633 data: 0.0018 max mem: 19788 +Test: [ 8000/21770] eta: 0:16:18 time: 0.0818 data: 0.0023 max mem: 19788 +Test: [ 8100/21770] eta: 0:16:11 time: 0.0695 data: 0.0020 max mem: 19788 +Test: [ 8200/21770] eta: 0:16:04 time: 0.0684 data: 0.0022 max mem: 19788 +Test: [ 8300/21770] eta: 0:15:57 time: 0.0695 data: 0.0019 max mem: 19788 +Test: [ 8400/21770] eta: 0:15:49 time: 0.0662 data: 0.0020 max mem: 19788 +Test: [ 8500/21770] eta: 0:15:42 time: 0.0643 data: 0.0019 max mem: 19788 +Test: [ 8600/21770] eta: 0:15:34 time: 0.0637 data: 0.0018 max mem: 19788 +Test: [ 8700/21770] eta: 0:15:26 time: 0.0618 data: 0.0018 max mem: 19788 +Test: [ 8800/21770] eta: 0:15:17 time: 0.0619 data: 0.0018 max mem: 19788 +Test: [ 8900/21770] eta: 0:15:10 time: 0.0679 data: 0.0022 max mem: 19788 +Test: [ 9000/21770] eta: 0:15:02 time: 0.0626 data: 0.0018 max mem: 19788 +Test: [ 9100/21770] eta: 0:14:56 time: 0.0821 data: 0.0024 max mem: 19788 +Test: [ 9200/21770] eta: 0:14:49 time: 0.0612 data: 0.0017 max mem: 19788 +Test: [ 9300/21770] eta: 0:14:41 time: 0.0637 data: 0.0020 max mem: 19788 +Test: [ 9400/21770] eta: 0:14:33 time: 0.0640 data: 0.0017 max mem: 19788 +Test: [ 9500/21770] eta: 0:14:25 time: 0.0616 data: 0.0020 max mem: 19788 +Test: [ 9600/21770] eta: 0:14:19 time: 0.0819 data: 0.0025 max mem: 19788 +Test: [ 9700/21770] eta: 0:14:14 time: 0.0819 data: 0.0025 max mem: 19788 +Test: [ 9800/21770] eta: 0:14:08 time: 0.0729 data: 0.0022 max mem: 19788 +Test: [ 9900/21770] eta: 0:14:00 time: 0.0749 data: 0.0022 max mem: 19788 +Test: [10000/21770] eta: 0:13:54 time: 0.0704 data: 0.0020 max mem: 19788 +Test: [10100/21770] eta: 0:13:48 time: 0.0823 data: 0.0025 max mem: 19788 +Test: [10200/21770] eta: 0:13:40 time: 0.0705 data: 0.0019 max mem: 19788 +Test: [10300/21770] eta: 0:13:34 time: 0.0805 data: 0.0025 max mem: 19788 +Test: [10400/21770] eta: 0:13:28 time: 0.0703 data: 0.0019 max mem: 19788 +Test: [10500/21770] eta: 0:13:20 time: 0.0679 data: 0.0019 max mem: 19788 +Test: [10600/21770] eta: 0:13:12 time: 0.0653 data: 0.0019 max mem: 19788 +Test: [10700/21770] eta: 0:13:05 time: 0.0716 data: 0.0021 max mem: 19788 +Test: [10800/21770] eta: 0:12:58 time: 0.0660 data: 0.0018 max mem: 19788 +Test: [10900/21770] eta: 0:12:51 time: 0.0805 data: 0.0018 max mem: 19788 +Test: [11000/21770] eta: 0:12:44 time: 0.0811 data: 0.0025 max mem: 19788 +Test: [11100/21770] eta: 0:12:36 time: 0.0640 data: 0.0018 max mem: 19788 +Test: [11200/21770] eta: 0:12:30 time: 0.0733 data: 0.0022 max mem: 19788 +Test: [11300/21770] eta: 0:12:23 time: 0.0819 data: 0.0024 max mem: 19788 +Test: [11400/21770] eta: 0:12:17 time: 0.0817 data: 0.0023 max mem: 19788 +Test: [11500/21770] eta: 0:12:10 time: 0.0659 data: 0.0022 max mem: 19788 +Test: [11600/21770] eta: 0:12:03 time: 0.0814 data: 0.0023 max mem: 19788 +Test: [11700/21770] eta: 0:11:57 time: 0.0816 data: 0.0025 max mem: 19788 +Test: [11800/21770] eta: 0:11:50 time: 0.0740 data: 0.0022 max mem: 19788 +Test: [11900/21770] eta: 0:11:43 time: 0.0796 data: 0.0023 max mem: 19788 +Test: [12000/21770] eta: 0:11:36 time: 0.0698 data: 0.0022 max mem: 19788 +Test: [12100/21770] eta: 0:11:29 time: 0.0796 data: 0.0020 max mem: 19788 +Test: [12200/21770] eta: 0:11:23 time: 0.0827 data: 0.0024 max mem: 19788 +Test: [12300/21770] eta: 0:11:16 time: 0.0794 data: 0.0022 max mem: 19788 +Test: [12400/21770] eta: 0:11:10 time: 0.0668 data: 0.0020 max mem: 19788 +Test: [12500/21770] eta: 0:11:02 time: 0.0626 data: 0.0019 max mem: 19788 +Test: [12600/21770] eta: 0:10:54 time: 0.0651 data: 0.0019 max mem: 19788 +Test: [12700/21770] eta: 0:10:47 time: 0.0706 data: 0.0019 max mem: 19788 +Test: [12800/21770] eta: 0:10:41 time: 0.0836 data: 0.0025 max mem: 19788 +Test: [12900/21770] eta: 0:10:33 time: 0.0700 data: 0.0020 max mem: 19788 +Test: [13000/21770] eta: 0:10:25 time: 0.0636 data: 0.0020 max mem: 19788 +Test: [13100/21770] eta: 0:10:18 time: 0.0821 data: 0.0024 max mem: 19788 +Test: [13200/21770] eta: 0:10:11 time: 0.0634 data: 0.0018 max mem: 19788 +Test: [13300/21770] eta: 0:10:04 time: 0.0624 data: 0.0020 max mem: 19788 +Test: [13400/21770] eta: 0:09:56 time: 0.0650 data: 0.0018 max mem: 19788 +Test: [13500/21770] eta: 0:09:48 time: 0.0632 data: 0.0018 max mem: 19788 +Test: [13600/21770] eta: 0:09:41 time: 0.0642 data: 0.0019 max mem: 19788 +Test: [13700/21770] eta: 0:09:33 time: 0.0621 data: 0.0018 max mem: 19788 +Test: [13800/21770] eta: 0:09:26 time: 0.0614 data: 0.0018 max mem: 19788 +Test: [13900/21770] eta: 0:09:19 time: 0.0739 data: 0.0022 max mem: 19788 +Test: [14000/21770] eta: 0:09:12 time: 0.0818 data: 0.0025 max mem: 19788 +Test: [14100/21770] eta: 0:09:06 time: 0.0635 data: 0.0018 max mem: 19788 +Test: [14200/21770] eta: 0:08:58 time: 0.0645 data: 0.0020 max mem: 19788 +Test: [14300/21770] eta: 0:08:51 time: 0.0827 data: 0.0024 max mem: 19788 +Test: [14400/21770] eta: 0:08:44 time: 0.0639 data: 0.0019 max mem: 19788 +Test: [14500/21770] eta: 0:08:37 time: 0.0613 data: 0.0019 max mem: 19788 +Test: [14600/21770] eta: 0:08:29 time: 0.0643 data: 0.0019 max mem: 19788 +Test: [14700/21770] eta: 0:08:22 time: 0.0639 data: 0.0020 max mem: 19788 +Test: [14800/21770] eta: 0:08:15 time: 0.0675 data: 0.0019 max mem: 19788 +Test: [14900/21770] eta: 0:08:08 time: 0.0621 data: 0.0019 max mem: 19788 +Test: [15000/21770] eta: 0:08:00 time: 0.0638 data: 0.0020 max mem: 19788 +Test: [15100/21770] eta: 0:07:53 time: 0.0726 data: 0.0019 max mem: 19788 +Test: [15200/21770] eta: 0:07:46 time: 0.0678 data: 0.0018 max mem: 19788 +Test: [15300/21770] eta: 0:07:38 time: 0.0780 data: 0.0020 max mem: 19788 +Test: [15400/21770] eta: 0:07:31 time: 0.0612 data: 0.0020 max mem: 19788 +Test: [15500/21770] eta: 0:07:24 time: 0.0638 data: 0.0019 max mem: 19788 +Test: [15600/21770] eta: 0:07:17 time: 0.0651 data: 0.0019 max mem: 19788 +Test: [15700/21770] eta: 0:07:09 time: 0.0636 data: 0.0019 max mem: 19788 +Test: [15800/21770] eta: 0:07:03 time: 0.0835 data: 0.0025 max mem: 19788 +Test: [15900/21770] eta: 0:06:56 time: 0.0816 data: 0.0025 max mem: 19788 +Test: [16000/21770] eta: 0:06:49 time: 0.0738 data: 0.0023 max mem: 19788 +Test: [16100/21770] eta: 0:06:42 time: 0.0637 data: 0.0019 max mem: 19788 +Test: [16200/21770] eta: 0:06:34 time: 0.0619 data: 0.0019 max mem: 19788 +Test: [16300/21770] eta: 0:06:27 time: 0.0621 data: 0.0020 max mem: 19788 +Test: [16400/21770] eta: 0:06:20 time: 0.0626 data: 0.0020 max mem: 19788 +Test: [16500/21770] eta: 0:06:13 time: 0.0656 data: 0.0019 max mem: 19788 +Test: [16600/21770] eta: 0:06:06 time: 0.0738 data: 0.0022 max mem: 19788 +Test: [16700/21770] eta: 0:05:58 time: 0.0636 data: 0.0018 max mem: 19788 +Test: [16800/21770] eta: 0:05:51 time: 0.0632 data: 0.0018 max mem: 19788 +Test: [16900/21770] eta: 0:05:44 time: 0.0819 data: 0.0025 max mem: 19788 +Test: [17000/21770] eta: 0:05:37 time: 0.0817 data: 0.0025 max mem: 19788 +Test: [17100/21770] eta: 0:05:30 time: 0.0612 data: 0.0018 max mem: 19788 +Test: [17200/21770] eta: 0:05:23 time: 0.0686 data: 0.0022 max mem: 19788 +Test: [17300/21770] eta: 0:05:16 time: 0.0646 data: 0.0018 max mem: 19788 +Test: [17400/21770] eta: 0:05:09 time: 0.0819 data: 0.0025 max mem: 19788 +Test: [17500/21770] eta: 0:05:02 time: 0.0779 data: 0.0024 max mem: 19788 +Test: [17600/21770] eta: 0:04:55 time: 0.0640 data: 0.0020 max mem: 19788 +Test: [17700/21770] eta: 0:04:48 time: 0.0644 data: 0.0019 max mem: 19788 +Test: [17800/21770] eta: 0:04:40 time: 0.0619 data: 0.0019 max mem: 19788 +Test: [17900/21770] eta: 0:04:33 time: 0.0643 data: 0.0018 max mem: 19788 +Test: [18000/21770] eta: 0:04:26 time: 0.0816 data: 0.0023 max mem: 19788 +Test: [18100/21770] eta: 0:04:19 time: 0.0720 data: 0.0024 max mem: 19788 +Test: [18200/21770] eta: 0:04:12 time: 0.0612 data: 0.0018 max mem: 19788 +Test: [18300/21770] eta: 0:04:05 time: 0.0662 data: 0.0019 max mem: 19788 +Test: [18400/21770] eta: 0:03:58 time: 0.0819 data: 0.0025 max mem: 19788 +Test: [18500/21770] eta: 0:03:51 time: 0.0643 data: 0.0020 max mem: 19788 +Test: [18600/21770] eta: 0:03:44 time: 0.0610 data: 0.0018 max mem: 19788 +Test: [18700/21770] eta: 0:03:37 time: 0.0618 data: 0.0019 max mem: 19788 +Test: [18800/21770] eta: 0:03:30 time: 0.0656 data: 0.0021 max mem: 19788 +Test: [18900/21770] eta: 0:03:23 time: 0.0816 data: 0.0024 max mem: 19788 +Test: [19000/21770] eta: 0:03:16 time: 0.0816 data: 0.0024 max mem: 19788 +Test: [19100/21770] eta: 0:03:09 time: 0.0624 data: 0.0019 max mem: 19788 +Test: [19200/21770] eta: 0:03:02 time: 0.0834 data: 0.0022 max mem: 19788 +Test: [19300/21770] eta: 0:02:55 time: 0.0832 data: 0.0025 max mem: 19788 +Test: [19400/21770] eta: 0:02:48 time: 0.0820 data: 0.0025 max mem: 19788 +Test: [19500/21770] eta: 0:02:41 time: 0.0808 data: 0.0019 max mem: 19788 +Test: [19600/21770] eta: 0:02:34 time: 0.0640 data: 0.0019 max mem: 19788 +Test: [19700/21770] eta: 0:02:26 time: 0.0662 data: 0.0021 max mem: 19788 +Test: [19800/21770] eta: 0:02:19 time: 0.0604 data: 0.0019 max mem: 19788 +Test: [19900/21770] eta: 0:02:12 time: 0.0827 data: 0.0025 max mem: 19788 +Test: [20000/21770] eta: 0:02:05 time: 0.0676 data: 0.0020 max mem: 19788 +Test: [20100/21770] eta: 0:01:58 time: 0.0648 data: 0.0018 max mem: 19788 +Test: [20200/21770] eta: 0:01:51 time: 0.0622 data: 0.0018 max mem: 19788 +Test: [20300/21770] eta: 0:01:44 time: 0.0651 data: 0.0021 max mem: 19788 +Test: [20400/21770] eta: 0:01:37 time: 0.0821 data: 0.0027 max mem: 19788 +Test: [20500/21770] eta: 0:01:30 time: 0.0671 data: 0.0020 max mem: 19788 +Test: [20600/21770] eta: 0:01:22 time: 0.0736 data: 0.0021 max mem: 19788 +Test: [20700/21770] eta: 0:01:15 time: 0.0600 data: 0.0018 max mem: 19788 +Test: [20800/21770] eta: 0:01:08 time: 0.0619 data: 0.0017 max mem: 19788 +Test: [20900/21770] eta: 0:01:01 time: 0.0776 data: 0.0023 max mem: 19788 +Test: [21000/21770] eta: 0:00:54 time: 0.0630 data: 0.0018 max mem: 19788 +Test: [21100/21770] eta: 0:00:47 time: 0.0818 data: 0.0023 max mem: 19788 +Test: [21200/21770] eta: 0:00:40 time: 0.0818 data: 0.0024 max mem: 19788 +Test: [21300/21770] eta: 0:00:33 time: 0.0843 data: 0.0022 max mem: 19788 +Test: [21400/21770] eta: 0:00:26 time: 0.0834 data: 0.0019 max mem: 19788 +Test: [21500/21770] eta: 0:00:19 time: 0.0817 data: 0.0024 max mem: 19788 +Test: [21600/21770] eta: 0:00:12 time: 0.0818 data: 0.0023 max mem: 19788 +Test: [21700/21770] eta: 0:00:04 time: 0.0815 data: 0.0023 max mem: 19788 +Test: Total time: 0:25:47 +Final results: +Mean IoU is 52.94 + + precision@0.5 = 57.59 + precision@0.6 = 50.79 + precision@0.7 = 42.74 + precision@0.8 = 31.67 + precision@0.9 = 12.80 + overall IoU = 57.16 + mean IoU = 52.94 + +Mean accuracy for one-to-zero sample is 77.70 + +Average object IoU 0.5294337600725911 +Overall IoU 57.15830612182617 +Better epoch: 1 + +Epoch: [2] [ 0/2138] eta: 22:23:57 lr: 4.774374018209639e-05 loss: 0.1489 (0.1489) time: 37.7163 data: 1.5630 max mem: 19788 +Epoch: [2] [ 10/2138] eta: 4:00:01 lr: 4.7738451156503353e-05 loss: 0.1562 (0.1566) time: 6.7676 data: 0.1450 max mem: 19788 +Epoch: [2] [ 20/2138] eta: 3:09:21 lr: 4.77331620658006e-05 loss: 0.1173 (0.1331) time: 3.7465 data: 0.0030 max mem: 19788 +Epoch: [2] [ 30/2138] eta: 2:50:57 lr: 4.77278729099793e-05 loss: 0.1068 (0.1281) time: 3.8201 data: 0.0030 max mem: 19788 +Epoch: [2] [ 40/2138] eta: 2:41:10 lr: 4.772258368903064e-05 loss: 0.1101 (0.1233) time: 3.8172 data: 0.0033 max mem: 19788 +Epoch: [2] [ 50/2138] eta: 2:33:57 lr: 4.77172944029458e-05 loss: 0.1185 (0.1291) time: 3.7394 data: 0.0033 max mem: 19788 +Epoch: [2] [ 60/2138] eta: 2:29:05 lr: 4.771200505171595e-05 loss: 0.1235 (0.1288) time: 3.6797 data: 0.0031 max mem: 19788 +Epoch: [2] [ 70/2138] eta: 2:25:13 lr: 4.7706715635332264e-05 loss: 0.1066 (0.1252) time: 3.6759 data: 0.0032 max mem: 19788 +Epoch: [2] [ 80/2138] eta: 2:22:49 lr: 4.770142615378591e-05 loss: 0.1111 (0.1270) time: 3.7356 data: 0.0032 max mem: 19788 +Epoch: [2] [ 90/2138] eta: 2:20:32 lr: 4.7696136607068063e-05 loss: 0.1221 (0.1297) time: 3.7776 data: 0.0030 max mem: 19788 +Epoch: [2] [ 100/2138] eta: 2:18:53 lr: 4.769084699516989e-05 loss: 0.1198 (0.1295) time: 3.7838 data: 0.0030 max mem: 19788 +Epoch: [2] [ 110/2138] eta: 2:17:17 lr: 4.768555731808254e-05 loss: 0.1149 (0.1297) time: 3.8089 data: 0.0032 max mem: 19788 +Epoch: [2] [ 120/2138] eta: 2:16:17 lr: 4.7680267575797197e-05 loss: 0.1227 (0.1288) time: 3.8663 data: 0.0032 max mem: 19788 +Epoch: [2] [ 130/2138] eta: 2:14:48 lr: 4.7674977768305e-05 loss: 0.1160 (0.1298) time: 3.8406 data: 0.0030 max mem: 19788 +Epoch: [2] [ 140/2138] eta: 2:13:39 lr: 4.766968789559712e-05 loss: 0.1154 (0.1307) time: 3.7832 data: 0.0031 max mem: 19788 +Epoch: [2] [ 150/2138] eta: 2:12:20 lr: 4.766439795766471e-05 loss: 0.1154 (0.1300) time: 3.7713 data: 0.0033 max mem: 19788 +Epoch: [2] [ 160/2138] eta: 2:11:04 lr: 4.765910795449891e-05 loss: 0.1186 (0.1304) time: 3.7102 data: 0.0034 max mem: 19788 +Epoch: [2] [ 170/2138] eta: 2:09:55 lr: 4.7653817886090884e-05 loss: 0.1187 (0.1304) time: 3.7134 data: 0.0032 max mem: 19788 +Epoch: [2] [ 180/2138] eta: 2:09:04 lr: 4.764852775243177e-05 loss: 0.1187 (0.1310) time: 3.7852 data: 0.0031 max mem: 19788 +Epoch: [2] [ 190/2138] eta: 2:08:01 lr: 4.764323755351273e-05 loss: 0.1156 (0.1307) time: 3.7870 data: 0.0031 max mem: 19788 +Epoch: [2] [ 200/2138] eta: 2:06:57 lr: 4.763794728932489e-05 loss: 0.1072 (0.1294) time: 3.7106 data: 0.0032 max mem: 19788 +Epoch: [2] [ 210/2138] eta: 2:06:08 lr: 4.76326569598594e-05 loss: 0.1072 (0.1295) time: 3.7606 data: 0.0035 max mem: 19788 +Epoch: [2] [ 220/2138] eta: 2:05:27 lr: 4.7627366565107386e-05 loss: 0.1306 (0.1296) time: 3.8609 data: 0.0035 max mem: 19788 +Epoch: [2] [ 230/2138] eta: 2:04:41 lr: 4.762207610506e-05 loss: 0.1346 (0.1303) time: 3.8693 data: 0.0032 max mem: 19788 +Epoch: [2] [ 240/2138] eta: 2:03:43 lr: 4.761678557970837e-05 loss: 0.1324 (0.1302) time: 3.7625 data: 0.0031 max mem: 19788 +Epoch: [2] [ 250/2138] eta: 2:02:48 lr: 4.7611494989043625e-05 loss: 0.1266 (0.1304) time: 3.6971 data: 0.0032 max mem: 19788 +Epoch: [2] [ 260/2138] eta: 2:01:58 lr: 4.76062043330569e-05 loss: 0.1259 (0.1301) time: 3.7257 data: 0.0033 max mem: 19788 +Epoch: [2] [ 270/2138] eta: 2:01:08 lr: 4.760091361173932e-05 loss: 0.1438 (0.1312) time: 3.7390 data: 0.0035 max mem: 19788 +Epoch: [2] [ 280/2138] eta: 2:00:24 lr: 4.759562282508201e-05 loss: 0.1450 (0.1311) time: 3.7808 data: 0.0033 max mem: 19788 +Epoch: [2] [ 290/2138] eta: 1:59:41 lr: 4.7590331973076094e-05 loss: 0.1163 (0.1309) time: 3.8226 data: 0.0031 max mem: 19788 +Epoch: [2] [ 300/2138] eta: 1:58:49 lr: 4.758504105571269e-05 loss: 0.1251 (0.1309) time: 3.7452 data: 0.0033 max mem: 19788 +Epoch: [2] [ 310/2138] eta: 1:58:06 lr: 4.757975007298291e-05 loss: 0.1170 (0.1306) time: 3.7410 data: 0.0033 max mem: 19788 +Epoch: [2] [ 320/2138] eta: 1:57:16 lr: 4.757445902487788e-05 loss: 0.1125 (0.1301) time: 3.7428 data: 0.0033 max mem: 19788 +Epoch: [2] [ 330/2138] eta: 1:56:32 lr: 4.756916791138871e-05 loss: 0.1125 (0.1302) time: 3.7260 data: 0.0033 max mem: 19788 +Epoch: [2] [ 340/2138] eta: 1:55:55 lr: 4.7563876732506505e-05 loss: 0.1187 (0.1299) time: 3.8343 data: 0.0031 max mem: 19788 +Epoch: [2] [ 350/2138] eta: 1:55:17 lr: 4.7558585488222386e-05 loss: 0.1187 (0.1297) time: 3.8906 data: 0.0031 max mem: 19788 +Epoch: [2] [ 360/2138] eta: 1:54:36 lr: 4.7553294178527455e-05 loss: 0.1226 (0.1302) time: 3.8547 data: 0.0031 max mem: 19788 +Epoch: [2] [ 370/2138] eta: 1:53:52 lr: 4.75480028034128e-05 loss: 0.1228 (0.1303) time: 3.7819 data: 0.0031 max mem: 19788 +Epoch: [2] [ 380/2138] eta: 1:53:10 lr: 4.754271136286955e-05 loss: 0.1201 (0.1301) time: 3.7743 data: 0.0032 max mem: 19788 +Epoch: [2] [ 390/2138] eta: 1:52:24 lr: 4.753741985688879e-05 loss: 0.1198 (0.1299) time: 3.7519 data: 0.0033 max mem: 19788 +Epoch: [2] [ 400/2138] eta: 1:51:54 lr: 4.753212828546161e-05 loss: 0.1243 (0.1301) time: 3.8741 data: 0.0034 max mem: 19788 +Epoch: [2] [ 410/2138] eta: 1:51:17 lr: 4.7526836648579124e-05 loss: 0.1350 (0.1302) time: 3.9804 data: 0.0032 max mem: 19788 +Epoch: [2] [ 420/2138] eta: 1:50:34 lr: 4.752154494623241e-05 loss: 0.1350 (0.1306) time: 3.8287 data: 0.0032 max mem: 19788 +Epoch: [2] [ 430/2138] eta: 1:49:48 lr: 4.751625317841256e-05 loss: 0.1331 (0.1305) time: 3.7055 data: 0.0031 max mem: 19788 +Epoch: [2] [ 440/2138] eta: 1:49:05 lr: 4.751096134511066e-05 loss: 0.1273 (0.1308) time: 3.7083 data: 0.0030 max mem: 19788 +Epoch: [2] [ 450/2138] eta: 1:48:31 lr: 4.7505669446317804e-05 loss: 0.1165 (0.1306) time: 3.8621 data: 0.0029 max mem: 19788 +Epoch: [2] [ 460/2138] eta: 1:47:54 lr: 4.750037748202507e-05 loss: 0.1086 (0.1305) time: 3.9377 data: 0.0030 max mem: 19788 +Epoch: [2] [ 470/2138] eta: 1:47:22 lr: 4.749508545222354e-05 loss: 0.1374 (0.1307) time: 3.9807 data: 0.0030 max mem: 19788 +Epoch: [2] [ 480/2138] eta: 1:46:42 lr: 4.74897933569043e-05 loss: 0.1221 (0.1305) time: 3.9430 data: 0.0030 max mem: 19788 +Epoch: [2] [ 490/2138] eta: 1:45:59 lr: 4.748450119605841e-05 loss: 0.1114 (0.1307) time: 3.7751 data: 0.0033 max mem: 19788 +Epoch: [2] [ 500/2138] eta: 1:45:17 lr: 4.747920896967696e-05 loss: 0.1056 (0.1306) time: 3.7369 data: 0.0034 max mem: 19788 +Epoch: [2] [ 510/2138] eta: 1:44:40 lr: 4.7473916677751004e-05 loss: 0.1152 (0.1305) time: 3.8205 data: 0.0033 max mem: 19788 +Epoch: [2] [ 520/2138] eta: 1:44:03 lr: 4.7468624320271635e-05 loss: 0.1184 (0.1306) time: 3.9085 data: 0.0031 max mem: 19788 +Epoch: [2] [ 530/2138] eta: 1:43:28 lr: 4.7463331897229903e-05 loss: 0.1341 (0.1307) time: 3.9472 data: 0.0030 max mem: 19788 +Epoch: [2] [ 540/2138] eta: 1:42:47 lr: 4.745803940861688e-05 loss: 0.1191 (0.1304) time: 3.8698 data: 0.0032 max mem: 19788 +Epoch: [2] [ 550/2138] eta: 1:42:05 lr: 4.745274685442362e-05 loss: 0.0970 (0.1300) time: 3.7574 data: 0.0031 max mem: 19788 +Epoch: [2] [ 560/2138] eta: 1:41:21 lr: 4.7447454234641195e-05 loss: 0.1112 (0.1302) time: 3.7127 data: 0.0031 max mem: 19788 +Epoch: [2] [ 570/2138] eta: 1:40:42 lr: 4.744216154926065e-05 loss: 0.1292 (0.1304) time: 3.7600 data: 0.0033 max mem: 19788 +Epoch: [2] [ 580/2138] eta: 1:40:08 lr: 4.743686879827305e-05 loss: 0.1245 (0.1304) time: 3.9240 data: 0.0033 max mem: 19788 +Epoch: [2] [ 590/2138] eta: 1:39:34 lr: 4.743157598166944e-05 loss: 0.1186 (0.1302) time: 4.0306 data: 0.0033 max mem: 19788 +Epoch: [2] [ 600/2138] eta: 1:38:53 lr: 4.7426283099440886e-05 loss: 0.1170 (0.1302) time: 3.8993 data: 0.0034 max mem: 19788 +Epoch: [2] [ 610/2138] eta: 1:38:12 lr: 4.742099015157842e-05 loss: 0.1149 (0.1301) time: 3.7531 data: 0.0033 max mem: 19788 +Epoch: [2] [ 620/2138] eta: 1:37:33 lr: 4.741569713807309e-05 loss: 0.1164 (0.1302) time: 3.8118 data: 0.0031 max mem: 19788 +Epoch: [2] [ 630/2138] eta: 1:36:54 lr: 4.741040405891595e-05 loss: 0.1180 (0.1300) time: 3.8453 data: 0.0032 max mem: 19788 +Epoch: [2] [ 640/2138] eta: 1:36:13 lr: 4.740511091409803e-05 loss: 0.1172 (0.1300) time: 3.7921 data: 0.0032 max mem: 19788 +Epoch: [2] [ 650/2138] eta: 1:35:33 lr: 4.739981770361038e-05 loss: 0.1225 (0.1297) time: 3.7737 data: 0.0032 max mem: 19788 +Epoch: [2] [ 660/2138] eta: 1:34:51 lr: 4.739452442744403e-05 loss: 0.1182 (0.1298) time: 3.7278 data: 0.0032 max mem: 19788 +Epoch: [2] [ 670/2138] eta: 1:34:12 lr: 4.7389231085590025e-05 loss: 0.1181 (0.1296) time: 3.7501 data: 0.0031 max mem: 19788 +Epoch: [2] [ 680/2138] eta: 1:33:33 lr: 4.738393767803938e-05 loss: 0.1119 (0.1295) time: 3.8443 data: 0.0031 max mem: 19788 +Epoch: [2] [ 690/2138] eta: 1:32:56 lr: 4.737864420478313e-05 loss: 0.1105 (0.1293) time: 3.8750 data: 0.0032 max mem: 19788 +Epoch: [2] [ 700/2138] eta: 1:32:25 lr: 4.737335066581231e-05 loss: 0.1114 (0.1294) time: 4.0659 data: 0.0030 max mem: 19788 +Epoch: [2] [ 710/2138] eta: 1:31:46 lr: 4.736805706111794e-05 loss: 0.1251 (0.1297) time: 4.0272 data: 0.0030 max mem: 19788 +Epoch: [2] [ 720/2138] eta: 1:31:07 lr: 4.736276339069104e-05 loss: 0.1273 (0.1298) time: 3.8350 data: 0.0033 max mem: 19788 +Epoch: [2] [ 730/2138] eta: 1:30:25 lr: 4.735746965452264e-05 loss: 0.1273 (0.1297) time: 3.7609 data: 0.0034 max mem: 19788 +Epoch: [2] [ 740/2138] eta: 1:29:43 lr: 4.735217585260374e-05 loss: 0.1060 (0.1294) time: 3.6664 data: 0.0032 max mem: 19788 +Epoch: [2] [ 750/2138] eta: 1:29:07 lr: 4.734688198492538e-05 loss: 0.1044 (0.1293) time: 3.8168 data: 0.0032 max mem: 19788 +Epoch: [2] [ 760/2138] eta: 1:28:27 lr: 4.734158805147855e-05 loss: 0.1291 (0.1295) time: 3.8944 data: 0.0031 max mem: 19788 +Epoch: [2] [ 770/2138] eta: 1:27:51 lr: 4.733629405225428e-05 loss: 0.1353 (0.1296) time: 3.8889 data: 0.0034 max mem: 19788 +Epoch: [2] [ 780/2138] eta: 1:27:14 lr: 4.7330999987243567e-05 loss: 0.1371 (0.1295) time: 3.9458 data: 0.0035 max mem: 19788 +Epoch: [2] [ 790/2138] eta: 1:26:35 lr: 4.732570585643743e-05 loss: 0.1327 (0.1298) time: 3.8936 data: 0.0034 max mem: 19788 +Epoch: [2] [ 800/2138] eta: 1:25:55 lr: 4.7320411659826853e-05 loss: 0.1207 (0.1296) time: 3.7918 data: 0.0035 max mem: 19788 +Epoch: [2] [ 810/2138] eta: 1:25:16 lr: 4.731511739740285e-05 loss: 0.1123 (0.1295) time: 3.7953 data: 0.0035 max mem: 19788 +Epoch: [2] [ 820/2138] eta: 1:24:38 lr: 4.730982306915642e-05 loss: 0.1145 (0.1294) time: 3.8670 data: 0.0034 max mem: 19788 +Epoch: [2] [ 830/2138] eta: 1:23:59 lr: 4.730452867507856e-05 loss: 0.1145 (0.1294) time: 3.8494 data: 0.0035 max mem: 19788 +Epoch: [2] [ 840/2138] eta: 1:23:25 lr: 4.729923421516026e-05 loss: 0.0963 (0.1292) time: 3.9809 data: 0.0034 max mem: 19788 +Epoch: [2] [ 850/2138] eta: 1:22:44 lr: 4.729393968939253e-05 loss: 0.1008 (0.1291) time: 3.9345 data: 0.0033 max mem: 19788 +Epoch: [2] [ 860/2138] eta: 1:22:04 lr: 4.7288645097766335e-05 loss: 0.1213 (0.1291) time: 3.7257 data: 0.0032 max mem: 19788 +Epoch: [2] [ 870/2138] eta: 1:21:28 lr: 4.7283350440272674e-05 loss: 0.1134 (0.1289) time: 3.8770 data: 0.0033 max mem: 19788 +Epoch: [2] [ 880/2138] eta: 1:20:48 lr: 4.727805571690254e-05 loss: 0.1081 (0.1288) time: 3.9083 data: 0.0033 max mem: 19788 +Epoch: [2] [ 890/2138] eta: 1:20:10 lr: 4.727276092764689e-05 loss: 0.1104 (0.1288) time: 3.8183 data: 0.0034 max mem: 19788 +Epoch: [2] [ 900/2138] eta: 1:19:30 lr: 4.726746607249673e-05 loss: 0.1277 (0.1293) time: 3.8190 data: 0.0036 max mem: 19788 +Epoch: [2] [ 910/2138] eta: 1:18:53 lr: 4.726217115144303e-05 loss: 0.1477 (0.1292) time: 3.8476 data: 0.0034 max mem: 19788 +Epoch: [2] [ 920/2138] eta: 1:18:17 lr: 4.725687616447677e-05 loss: 0.1213 (0.1294) time: 4.0133 data: 0.0037 max mem: 19788 +Epoch: [2] [ 930/2138] eta: 1:17:42 lr: 4.7251581111588915e-05 loss: 0.1157 (0.1291) time: 4.0884 data: 0.0037 max mem: 19788 +Epoch: [2] [ 940/2138] eta: 1:17:01 lr: 4.724628599277044e-05 loss: 0.1157 (0.1292) time: 3.8961 data: 0.0034 max mem: 19788 +Epoch: [2] [ 950/2138] eta: 1:16:23 lr: 4.724099080801231e-05 loss: 0.1163 (0.1291) time: 3.8134 data: 0.0034 max mem: 19788 +Epoch: [2] [ 960/2138] eta: 1:15:45 lr: 4.723569555730551e-05 loss: 0.1109 (0.1290) time: 3.9032 data: 0.0034 max mem: 19788 +Epoch: [2] [ 970/2138] eta: 1:15:05 lr: 4.723040024064098e-05 loss: 0.1081 (0.1289) time: 3.8243 data: 0.0034 max mem: 19788 +Epoch: [2] [ 980/2138] eta: 1:14:25 lr: 4.722510485800969e-05 loss: 0.1081 (0.1289) time: 3.7208 data: 0.0034 max mem: 19788 +Epoch: [2] [ 990/2138] eta: 1:13:48 lr: 4.721980940940259e-05 loss: 0.1113 (0.1288) time: 3.8569 data: 0.0032 max mem: 19788 +Epoch: [2] [1000/2138] eta: 1:13:10 lr: 4.721451389481066e-05 loss: 0.1064 (0.1286) time: 3.9394 data: 0.0031 max mem: 19788 +Epoch: [2] [1010/2138] eta: 1:12:32 lr: 4.720921831422484e-05 loss: 0.1120 (0.1287) time: 3.9040 data: 0.0032 max mem: 19788 +Epoch: [2] [1020/2138] eta: 1:11:53 lr: 4.720392266763608e-05 loss: 0.1092 (0.1284) time: 3.9039 data: 0.0033 max mem: 19788 +Epoch: [2] [1030/2138] eta: 1:11:15 lr: 4.719862695503534e-05 loss: 0.0952 (0.1283) time: 3.8601 data: 0.0033 max mem: 19788 +Epoch: [2] [1040/2138] eta: 1:10:35 lr: 4.719333117641355e-05 loss: 0.1148 (0.1283) time: 3.7957 data: 0.0032 max mem: 19788 +Epoch: [2] [1050/2138] eta: 1:09:56 lr: 4.7188035331761676e-05 loss: 0.1012 (0.1282) time: 3.7609 data: 0.0032 max mem: 19788 +Epoch: [2] [1060/2138] eta: 1:09:16 lr: 4.718273942107065e-05 loss: 0.0968 (0.1280) time: 3.7702 data: 0.0032 max mem: 19788 +Epoch: [2] [1070/2138] eta: 1:08:36 lr: 4.7177443444331405e-05 loss: 0.0989 (0.1278) time: 3.7372 data: 0.0032 max mem: 19788 +Epoch: [2] [1080/2138] eta: 1:07:59 lr: 4.717214740153489e-05 loss: 0.1041 (0.1276) time: 3.8657 data: 0.0031 max mem: 19788 +Epoch: [2] [1090/2138] eta: 1:07:19 lr: 4.716685129267204e-05 loss: 0.1124 (0.1275) time: 3.8576 data: 0.0030 max mem: 19788 +Epoch: [2] [1100/2138] eta: 1:06:40 lr: 4.716155511773378e-05 loss: 0.1156 (0.1275) time: 3.7499 data: 0.0032 max mem: 19788 +Epoch: [2] [1110/2138] eta: 1:06:01 lr: 4.715625887671104e-05 loss: 0.1143 (0.1274) time: 3.8059 data: 0.0033 max mem: 19788 +Epoch: [2] [1120/2138] eta: 1:05:21 lr: 4.715096256959477e-05 loss: 0.1069 (0.1274) time: 3.7760 data: 0.0032 max mem: 19788 +Epoch: [2] [1130/2138] eta: 1:04:41 lr: 4.714566619637587e-05 loss: 0.1221 (0.1274) time: 3.6955 data: 0.0032 max mem: 19788 +Epoch: [2] [1140/2138] eta: 1:04:01 lr: 4.714036975704528e-05 loss: 0.1218 (0.1274) time: 3.6620 data: 0.0032 max mem: 19788 +Epoch: [2] [1150/2138] eta: 1:03:21 lr: 4.713507325159391e-05 loss: 0.1095 (0.1272) time: 3.6632 data: 0.0031 max mem: 19788 +Epoch: [2] [1160/2138] eta: 1:02:41 lr: 4.712977668001269e-05 loss: 0.0951 (0.1273) time: 3.6958 data: 0.0029 max mem: 19788 +Epoch: [2] [1170/2138] eta: 1:02:03 lr: 4.712448004229253e-05 loss: 0.0983 (0.1273) time: 3.7976 data: 0.0030 max mem: 19788 +Epoch: [2] [1180/2138] eta: 1:01:23 lr: 4.7119183338424345e-05 loss: 0.1334 (0.1274) time: 3.7642 data: 0.0033 max mem: 19788 +Epoch: [2] [1190/2138] eta: 1:00:43 lr: 4.7113886568399045e-05 loss: 0.1322 (0.1273) time: 3.6725 data: 0.0032 max mem: 19788 +Epoch: [2] [1200/2138] eta: 1:00:04 lr: 4.710858973220754e-05 loss: 0.1150 (0.1273) time: 3.6717 data: 0.0030 max mem: 19788 +Epoch: [2] [1210/2138] eta: 0:59:24 lr: 4.710329282984074e-05 loss: 0.1219 (0.1273) time: 3.7066 data: 0.0030 max mem: 19788 +Epoch: [2] [1220/2138] eta: 0:58:46 lr: 4.7097995861289543e-05 loss: 0.1207 (0.1275) time: 3.8197 data: 0.0031 max mem: 19788 +Epoch: [2] [1230/2138] eta: 0:58:07 lr: 4.7092698826544865e-05 loss: 0.1287 (0.1276) time: 3.7850 data: 0.0031 max mem: 19788 +Epoch: [2] [1240/2138] eta: 0:57:27 lr: 4.708740172559759e-05 loss: 0.1287 (0.1275) time: 3.6700 data: 0.0032 max mem: 19788 +Epoch: [2] [1250/2138] eta: 0:56:47 lr: 4.708210455843863e-05 loss: 0.1124 (0.1275) time: 3.6603 data: 0.0033 max mem: 19788 +Epoch: [2] [1260/2138] eta: 0:56:08 lr: 4.707680732505886e-05 loss: 0.1193 (0.1275) time: 3.6607 data: 0.0034 max mem: 19788 +Epoch: [2] [1270/2138] eta: 0:55:28 lr: 4.707151002544919e-05 loss: 0.1147 (0.1274) time: 3.6599 data: 0.0032 max mem: 19788 +Epoch: [2] [1280/2138] eta: 0:54:49 lr: 4.706621265960051e-05 loss: 0.1051 (0.1275) time: 3.6573 data: 0.0032 max mem: 19788 +Epoch: [2] [1290/2138] eta: 0:54:09 lr: 4.7060915227503695e-05 loss: 0.1237 (0.1276) time: 3.6682 data: 0.0031 max mem: 19788 +Epoch: [2] [1300/2138] eta: 0:53:30 lr: 4.7055617729149634e-05 loss: 0.1237 (0.1276) time: 3.6751 data: 0.0031 max mem: 19788 +Epoch: [2] [1310/2138] eta: 0:52:52 lr: 4.705032016452923e-05 loss: 0.1253 (0.1276) time: 3.7424 data: 0.0031 max mem: 19788 +Epoch: [2] [1320/2138] eta: 0:52:12 lr: 4.704502253363334e-05 loss: 0.1261 (0.1276) time: 3.7339 data: 0.0030 max mem: 19788 +Epoch: [2] [1330/2138] eta: 0:51:33 lr: 4.703972483645285e-05 loss: 0.1168 (0.1275) time: 3.6647 data: 0.0032 max mem: 19788 +Epoch: [2] [1340/2138] eta: 0:50:54 lr: 4.7034427072978636e-05 loss: 0.1143 (0.1276) time: 3.6681 data: 0.0033 max mem: 19788 +Epoch: [2] [1350/2138] eta: 0:50:15 lr: 4.7029129243201576e-05 loss: 0.1071 (0.1274) time: 3.7403 data: 0.0030 max mem: 19788 +Epoch: [2] [1360/2138] eta: 0:49:38 lr: 4.702383134711253e-05 loss: 0.1057 (0.1273) time: 3.8696 data: 0.0029 max mem: 19788 +Epoch: [2] [1370/2138] eta: 0:48:58 lr: 4.701853338470238e-05 loss: 0.1112 (0.1272) time: 3.7896 data: 0.0030 max mem: 19788 +Epoch: [2] [1380/2138] eta: 0:48:19 lr: 4.701323535596198e-05 loss: 0.1148 (0.1271) time: 3.6721 data: 0.0032 max mem: 19788 +Epoch: [2] [1390/2138] eta: 0:47:40 lr: 4.7007937260882206e-05 loss: 0.1148 (0.1271) time: 3.6702 data: 0.0034 max mem: 19788 +Epoch: [2] [1400/2138] eta: 0:47:01 lr: 4.70026390994539e-05 loss: 0.0993 (0.1270) time: 3.6549 data: 0.0032 max mem: 19788 +Epoch: [2] [1410/2138] eta: 0:46:22 lr: 4.699734087166795e-05 loss: 0.1018 (0.1269) time: 3.7012 data: 0.0030 max mem: 19788 +Epoch: [2] [1420/2138] eta: 0:45:43 lr: 4.6992042577515197e-05 loss: 0.1073 (0.1269) time: 3.7084 data: 0.0032 max mem: 19788 +Epoch: [2] [1430/2138] eta: 0:45:04 lr: 4.698674421698649e-05 loss: 0.0982 (0.1268) time: 3.6630 data: 0.0032 max mem: 19788 +Epoch: [2] [1440/2138] eta: 0:44:25 lr: 4.698144579007268e-05 loss: 0.0982 (0.1266) time: 3.6594 data: 0.0030 max mem: 19788 +Epoch: [2] [1450/2138] eta: 0:43:47 lr: 4.6976147296764635e-05 loss: 0.1190 (0.1266) time: 3.7672 data: 0.0030 max mem: 19788 +Epoch: [2] [1460/2138] eta: 0:43:09 lr: 4.697084873705318e-05 loss: 0.1233 (0.1266) time: 3.8338 data: 0.0032 max mem: 19788 +Epoch: [2] [1470/2138] eta: 0:42:30 lr: 4.6965550110929176e-05 loss: 0.1189 (0.1266) time: 3.7237 data: 0.0034 max mem: 19788 +Epoch: [2] [1480/2138] eta: 0:41:51 lr: 4.696025141838345e-05 loss: 0.1188 (0.1266) time: 3.6644 data: 0.0034 max mem: 19788 +Epoch: [2] [1490/2138] eta: 0:41:12 lr: 4.695495265940685e-05 loss: 0.1188 (0.1266) time: 3.6638 data: 0.0032 max mem: 19788 +Epoch: [2] [1500/2138] eta: 0:40:34 lr: 4.6949653833990226e-05 loss: 0.1227 (0.1266) time: 3.7185 data: 0.0031 max mem: 19788 +Epoch: [2] [1510/2138] eta: 0:39:56 lr: 4.6944354942124394e-05 loss: 0.1003 (0.1264) time: 3.7855 data: 0.0031 max mem: 19788 +Epoch: [2] [1520/2138] eta: 0:39:17 lr: 4.693905598380019e-05 loss: 0.0984 (0.1264) time: 3.7289 data: 0.0031 max mem: 19788 +Epoch: [2] [1530/2138] eta: 0:38:38 lr: 4.6933756959008454e-05 loss: 0.1082 (0.1263) time: 3.6682 data: 0.0030 max mem: 19788 +Epoch: [2] [1540/2138] eta: 0:38:00 lr: 4.692845786774001e-05 loss: 0.1065 (0.1264) time: 3.7000 data: 0.0031 max mem: 19788 +Epoch: [2] [1550/2138] eta: 0:37:22 lr: 4.692315870998566e-05 loss: 0.1067 (0.1263) time: 3.7727 data: 0.0031 max mem: 19788 +Epoch: [2] [1560/2138] eta: 0:36:43 lr: 4.691785948573627e-05 loss: 0.0954 (0.1263) time: 3.7309 data: 0.0031 max mem: 19788 +Epoch: [2] [1570/2138] eta: 0:36:04 lr: 4.691256019498263e-05 loss: 0.1221 (0.1263) time: 3.6614 data: 0.0032 max mem: 19788 +Epoch: [2] [1580/2138] eta: 0:35:26 lr: 4.6907260837715566e-05 loss: 0.1221 (0.1263) time: 3.6637 data: 0.0032 max mem: 19788 +Epoch: [2] [1590/2138] eta: 0:34:47 lr: 4.6901961413925885e-05 loss: 0.1069 (0.1261) time: 3.6563 data: 0.0030 max mem: 19788 +Epoch: [2] [1600/2138] eta: 0:34:09 lr: 4.689666192360442e-05 loss: 0.1021 (0.1261) time: 3.7614 data: 0.0029 max mem: 19788 +Epoch: [2] [1610/2138] eta: 0:33:31 lr: 4.689136236674197e-05 loss: 0.1010 (0.1260) time: 3.7661 data: 0.0032 max mem: 19788 +Epoch: [2] [1620/2138] eta: 0:32:52 lr: 4.688606274332934e-05 loss: 0.1089 (0.1260) time: 3.6675 data: 0.0033 max mem: 19788 +Epoch: [2] [1630/2138] eta: 0:32:14 lr: 4.688076305335735e-05 loss: 0.1208 (0.1260) time: 3.6693 data: 0.0032 max mem: 19788 +Epoch: [2] [1640/2138] eta: 0:31:35 lr: 4.6875463296816785e-05 loss: 0.1105 (0.1259) time: 3.6727 data: 0.0033 max mem: 19788 +Epoch: [2] [1650/2138] eta: 0:30:57 lr: 4.6870163473698455e-05 loss: 0.0958 (0.1258) time: 3.6744 data: 0.0032 max mem: 19788 +Epoch: [2] [1660/2138] eta: 0:30:18 lr: 4.6864863583993165e-05 loss: 0.1035 (0.1258) time: 3.6785 data: 0.0030 max mem: 19788 +Epoch: [2] [1670/2138] eta: 0:29:40 lr: 4.685956362769169e-05 loss: 0.1035 (0.1255) time: 3.6648 data: 0.0029 max mem: 19788 +Epoch: [2] [1680/2138] eta: 0:29:01 lr: 4.685426360478485e-05 loss: 0.0932 (0.1254) time: 3.6334 data: 0.0029 max mem: 19788 +Epoch: [2] [1690/2138] eta: 0:28:23 lr: 4.684896351526342e-05 loss: 0.1025 (0.1255) time: 3.6231 data: 0.0028 max mem: 19788 +Epoch: [2] [1700/2138] eta: 0:27:44 lr: 4.68436633591182e-05 loss: 0.1106 (0.1254) time: 3.6267 data: 0.0028 max mem: 19788 +Epoch: [2] [1710/2138] eta: 0:27:06 lr: 4.683836313633997e-05 loss: 0.1153 (0.1253) time: 3.6274 data: 0.0028 max mem: 19788 +Epoch: [2] [1720/2138] eta: 0:26:27 lr: 4.683306284691951e-05 loss: 0.1106 (0.1252) time: 3.6224 data: 0.0028 max mem: 19788 +Epoch: [2] [1730/2138] eta: 0:25:49 lr: 4.6827762490847606e-05 loss: 0.1020 (0.1252) time: 3.6400 data: 0.0030 max mem: 19788 +Epoch: [2] [1740/2138] eta: 0:25:11 lr: 4.682246206811504e-05 loss: 0.0917 (0.1250) time: 3.6481 data: 0.0033 max mem: 19788 +Epoch: [2] [1750/2138] eta: 0:24:32 lr: 4.6817161578712584e-05 loss: 0.0962 (0.1250) time: 3.6334 data: 0.0033 max mem: 19788 +Epoch: [2] [1760/2138] eta: 0:23:54 lr: 4.681186102263102e-05 loss: 0.1096 (0.1249) time: 3.6374 data: 0.0030 max mem: 19788 +Epoch: [2] [1770/2138] eta: 0:23:16 lr: 4.680656039986112e-05 loss: 0.0982 (0.1248) time: 3.6430 data: 0.0028 max mem: 19788 +Epoch: [2] [1780/2138] eta: 0:22:38 lr: 4.680125971039363e-05 loss: 0.0986 (0.1246) time: 3.6374 data: 0.0027 max mem: 19788 +Epoch: [2] [1790/2138] eta: 0:21:59 lr: 4.6795958954219345e-05 loss: 0.1067 (0.1246) time: 3.6392 data: 0.0029 max mem: 19788 +Epoch: [2] [1800/2138] eta: 0:21:21 lr: 4.679065813132902e-05 loss: 0.1168 (0.1248) time: 3.6459 data: 0.0029 max mem: 19788 +Epoch: [2] [1810/2138] eta: 0:20:43 lr: 4.678535724171342e-05 loss: 0.1181 (0.1248) time: 3.6363 data: 0.0029 max mem: 19788 +Epoch: [2] [1820/2138] eta: 0:20:05 lr: 4.6780056285363295e-05 loss: 0.1119 (0.1248) time: 3.6276 data: 0.0030 max mem: 19788 +Epoch: [2] [1830/2138] eta: 0:19:27 lr: 4.677475526226941e-05 loss: 0.1103 (0.1247) time: 3.6376 data: 0.0031 max mem: 19788 +Epoch: [2] [1840/2138] eta: 0:18:48 lr: 4.676945417242252e-05 loss: 0.1098 (0.1249) time: 3.6407 data: 0.0029 max mem: 19788 +Epoch: [2] [1850/2138] eta: 0:18:10 lr: 4.676415301581338e-05 loss: 0.1098 (0.1249) time: 3.6302 data: 0.0028 max mem: 19788 +Epoch: [2] [1860/2138] eta: 0:17:32 lr: 4.6758851792432726e-05 loss: 0.1188 (0.1249) time: 3.6269 data: 0.0031 max mem: 19788 +Epoch: [2] [1870/2138] eta: 0:16:54 lr: 4.675355050227133e-05 loss: 0.1272 (0.1250) time: 3.6318 data: 0.0034 max mem: 19788 +Epoch: [2] [1880/2138] eta: 0:16:16 lr: 4.674824914531991e-05 loss: 0.1178 (0.1249) time: 3.6374 data: 0.0032 max mem: 19788 +Epoch: [2] [1890/2138] eta: 0:15:38 lr: 4.674294772156923e-05 loss: 0.1050 (0.1248) time: 3.6442 data: 0.0033 max mem: 19788 +Epoch: [2] [1900/2138] eta: 0:15:00 lr: 4.673764623101001e-05 loss: 0.1050 (0.1247) time: 3.6391 data: 0.0033 max mem: 19788 +Epoch: [2] [1910/2138] eta: 0:14:22 lr: 4.673234467363301e-05 loss: 0.0960 (0.1246) time: 3.6299 data: 0.0031 max mem: 19788 +Epoch: [2] [1920/2138] eta: 0:13:44 lr: 4.6727043049428946e-05 loss: 0.1203 (0.1247) time: 3.6343 data: 0.0030 max mem: 19788 +Epoch: [2] [1930/2138] eta: 0:13:06 lr: 4.6721741358388574e-05 loss: 0.1203 (0.1246) time: 3.6419 data: 0.0029 max mem: 19788 +Epoch: [2] [1940/2138] eta: 0:12:28 lr: 4.671643960050259e-05 loss: 0.1139 (0.1246) time: 3.6453 data: 0.0028 max mem: 19788 +Epoch: [2] [1950/2138] eta: 0:11:50 lr: 4.671113777576176e-05 loss: 0.1047 (0.1245) time: 3.6505 data: 0.0028 max mem: 19788 +Epoch: [2] [1960/2138] eta: 0:11:12 lr: 4.670583588415678e-05 loss: 0.0993 (0.1243) time: 3.6533 data: 0.0031 max mem: 19788 +Epoch: [2] [1970/2138] eta: 0:10:34 lr: 4.6700533925678386e-05 loss: 0.1012 (0.1243) time: 3.6474 data: 0.0030 max mem: 19788 +Epoch: [2] [1980/2138] eta: 0:09:56 lr: 4.6695231900317294e-05 loss: 0.1116 (0.1243) time: 3.6354 data: 0.0028 max mem: 19788 +Epoch: [2] [1990/2138] eta: 0:09:19 lr: 4.668992980806423e-05 loss: 0.1155 (0.1242) time: 3.6348 data: 0.0030 max mem: 19788 +Epoch: [2] [2000/2138] eta: 0:08:41 lr: 4.66846276489099e-05 loss: 0.1110 (0.1241) time: 3.6414 data: 0.0030 max mem: 19788 +Epoch: [2] [2010/2138] eta: 0:08:03 lr: 4.6679325422845014e-05 loss: 0.1048 (0.1241) time: 3.6305 data: 0.0030 max mem: 19788 +Epoch: [2] [2020/2138] eta: 0:07:25 lr: 4.66740231298603e-05 loss: 0.1174 (0.1241) time: 3.6259 data: 0.0031 max mem: 19788 +Epoch: [2] [2030/2138] eta: 0:06:47 lr: 4.6668720769946455e-05 loss: 0.1024 (0.1241) time: 3.6266 data: 0.0031 max mem: 19788 +Epoch: [2] [2040/2138] eta: 0:06:09 lr: 4.6663418343094185e-05 loss: 0.0999 (0.1241) time: 3.6345 data: 0.0030 max mem: 19788 +Epoch: [2] [2050/2138] eta: 0:05:32 lr: 4.6658115849294194e-05 loss: 0.0999 (0.1240) time: 3.6447 data: 0.0031 max mem: 19788 +Epoch: [2] [2060/2138] eta: 0:04:54 lr: 4.6652813288537176e-05 loss: 0.0991 (0.1239) time: 3.6383 data: 0.0033 max mem: 19788 +Epoch: [2] [2070/2138] eta: 0:04:16 lr: 4.664751066081385e-05 loss: 0.0987 (0.1238) time: 3.6278 data: 0.0031 max mem: 19788 +Epoch: [2] [2080/2138] eta: 0:03:38 lr: 4.664220796611489e-05 loss: 0.1036 (0.1238) time: 3.6330 data: 0.0028 max mem: 19788 +Epoch: [2] [2090/2138] eta: 0:03:00 lr: 4.6636905204430996e-05 loss: 0.1063 (0.1237) time: 3.6437 data: 0.0030 max mem: 19788 +Epoch: [2] [2100/2138] eta: 0:02:23 lr: 4.6631602375752856e-05 loss: 0.0969 (0.1236) time: 3.6392 data: 0.0039 max mem: 19788 +Epoch: [2] [2110/2138] eta: 0:01:45 lr: 4.662629948007117e-05 loss: 0.1191 (0.1238) time: 3.6416 data: 0.0038 max mem: 19788 +Epoch: [2] [2120/2138] eta: 0:01:07 lr: 4.6620996517376624e-05 loss: 0.1286 (0.1238) time: 3.6388 data: 0.0029 max mem: 19788 +Epoch: [2] [2130/2138] eta: 0:00:30 lr: 4.661569348765988e-05 loss: 0.1066 (0.1238) time: 3.6181 data: 0.0027 max mem: 19788 +Epoch: [2] Total time: 2:14:15 +Test: [ 0/21770] eta: 17:15:27 time: 2.8538 data: 2.6451 max mem: 19788 +Test: [ 100/21770] eta: 0:33:55 time: 0.0576 data: 0.0018 max mem: 19788 +Test: [ 200/21770] eta: 0:29:59 time: 0.0675 data: 0.0018 max mem: 19788 +Test: [ 300/21770] eta: 0:27:52 time: 0.0624 data: 0.0019 max mem: 19788 +Test: [ 400/21770] eta: 0:26:45 time: 0.0615 data: 0.0019 max mem: 19788 +Test: [ 500/21770] eta: 0:26:19 time: 0.0702 data: 0.0020 max mem: 19788 +Test: [ 600/21770] eta: 0:25:54 time: 0.0741 data: 0.0021 max mem: 19788 +Test: [ 700/21770] eta: 0:25:16 time: 0.0625 data: 0.0018 max mem: 19788 +Test: [ 800/21770] eta: 0:24:46 time: 0.0623 data: 0.0020 max mem: 19788 +Test: [ 900/21770] eta: 0:24:26 time: 0.0758 data: 0.0022 max mem: 19788 +Test: [ 1000/21770] eta: 0:24:15 time: 0.0763 data: 0.0020 max mem: 19788 +Test: [ 1100/21770] eta: 0:24:12 time: 0.0805 data: 0.0024 max mem: 19788 +Test: [ 1200/21770] eta: 0:23:57 time: 0.0630 data: 0.0018 max mem: 19788 +Test: [ 1300/21770] eta: 0:23:45 time: 0.0599 data: 0.0017 max mem: 19788 +Test: [ 1400/21770] eta: 0:23:30 time: 0.0616 data: 0.0017 max mem: 19788 +Test: [ 1500/21770] eta: 0:23:12 time: 0.0653 data: 0.0020 max mem: 19788 +Test: [ 1600/21770] eta: 0:23:04 time: 0.0695 data: 0.0021 max mem: 19788 +Test: [ 1700/21770] eta: 0:22:51 time: 0.0608 data: 0.0018 max mem: 19788 +Test: [ 1800/21770] eta: 0:22:38 time: 0.0619 data: 0.0019 max mem: 19788 +Test: [ 1900/21770] eta: 0:22:29 time: 0.0665 data: 0.0020 max mem: 19788 +Test: [ 2000/21770] eta: 0:22:18 time: 0.0595 data: 0.0018 max mem: 19788 +Test: [ 2100/21770] eta: 0:22:15 time: 0.0818 data: 0.0020 max mem: 19788 +Test: [ 2200/21770] eta: 0:22:10 time: 0.0749 data: 0.0018 max mem: 19788 +Test: [ 2300/21770] eta: 0:22:03 time: 0.0620 data: 0.0019 max mem: 19788 +Test: [ 2400/21770] eta: 0:21:53 time: 0.0672 data: 0.0019 max mem: 19788 +Test: [ 2500/21770] eta: 0:21:46 time: 0.0622 data: 0.0017 max mem: 19788 +Test: [ 2600/21770] eta: 0:21:37 time: 0.0619 data: 0.0017 max mem: 19788 +Test: [ 2700/21770] eta: 0:21:34 time: 0.0810 data: 0.0023 max mem: 19788 +Test: [ 2800/21770] eta: 0:21:30 time: 0.0647 data: 0.0018 max mem: 19788 +Test: [ 2900/21770] eta: 0:21:19 time: 0.0633 data: 0.0019 max mem: 19788 +Test: [ 3000/21770] eta: 0:21:11 time: 0.0742 data: 0.0020 max mem: 19788 +Test: [ 3100/21770] eta: 0:21:07 time: 0.0728 data: 0.0022 max mem: 19788 +Test: [ 3200/21770] eta: 0:21:01 time: 0.0621 data: 0.0018 max mem: 19788 +Test: [ 3300/21770] eta: 0:20:53 time: 0.0634 data: 0.0017 max mem: 19788 +Test: [ 3400/21770] eta: 0:20:46 time: 0.0616 data: 0.0018 max mem: 19788 +Test: [ 3500/21770] eta: 0:20:37 time: 0.0631 data: 0.0016 max mem: 19788 +Test: [ 3600/21770] eta: 0:20:27 time: 0.0620 data: 0.0017 max mem: 19788 +Test: [ 3700/21770] eta: 0:20:19 time: 0.0624 data: 0.0019 max mem: 19788 +Test: [ 3800/21770] eta: 0:20:13 time: 0.0621 data: 0.0018 max mem: 19788 +Test: [ 3900/21770] eta: 0:20:07 time: 0.0765 data: 0.0021 max mem: 19788 +Test: [ 4000/21770] eta: 0:20:00 time: 0.0659 data: 0.0020 max mem: 19788 +Test: [ 4100/21770] eta: 0:19:53 time: 0.0652 data: 0.0018 max mem: 19788 +Test: [ 4200/21770] eta: 0:19:47 time: 0.0692 data: 0.0019 max mem: 19788 +Test: [ 4300/21770] eta: 0:19:39 time: 0.0654 data: 0.0020 max mem: 19788 +Test: [ 4400/21770] eta: 0:19:33 time: 0.0768 data: 0.0023 max mem: 19788 +Test: [ 4500/21770] eta: 0:19:27 time: 0.0647 data: 0.0017 max mem: 19788 +Test: [ 4600/21770] eta: 0:19:19 time: 0.0716 data: 0.0022 max mem: 19788 +Test: [ 4700/21770] eta: 0:19:13 time: 0.0811 data: 0.0025 max mem: 19788 +Test: [ 4800/21770] eta: 0:19:09 time: 0.0615 data: 0.0018 max mem: 19788 +Test: [ 4900/21770] eta: 0:19:00 time: 0.0591 data: 0.0016 max mem: 19788 +Test: [ 5000/21770] eta: 0:18:55 time: 0.0787 data: 0.0023 max mem: 19788 +Test: [ 5100/21770] eta: 0:18:48 time: 0.0778 data: 0.0024 max mem: 19788 +Test: [ 5200/21770] eta: 0:18:41 time: 0.0612 data: 0.0017 max mem: 19788 +Test: [ 5300/21770] eta: 0:18:34 time: 0.0740 data: 0.0021 max mem: 19788 +Test: [ 5400/21770] eta: 0:18:31 time: 0.0818 data: 0.0025 max mem: 19788 +Test: [ 5500/21770] eta: 0:18:25 time: 0.0785 data: 0.0024 max mem: 19788 +Test: [ 5600/21770] eta: 0:18:19 time: 0.0711 data: 0.0022 max mem: 19788 +Test: [ 5700/21770] eta: 0:18:12 time: 0.0613 data: 0.0018 max mem: 19788 +Test: [ 5800/21770] eta: 0:18:05 time: 0.0652 data: 0.0018 max mem: 19788 +Test: [ 5900/21770] eta: 0:17:58 time: 0.0819 data: 0.0018 max mem: 19788 +Test: [ 6000/21770] eta: 0:17:52 time: 0.0709 data: 0.0018 max mem: 19788 +Test: [ 6100/21770] eta: 0:17:46 time: 0.0707 data: 0.0022 max mem: 19788 +Test: [ 6200/21770] eta: 0:17:39 time: 0.0705 data: 0.0020 max mem: 19788 +Test: [ 6300/21770] eta: 0:17:32 time: 0.0621 data: 0.0017 max mem: 19788 +Test: [ 6400/21770] eta: 0:17:25 time: 0.0684 data: 0.0022 max mem: 19788 +Test: [ 6500/21770] eta: 0:17:17 time: 0.0697 data: 0.0021 max mem: 19788 +Test: [ 6600/21770] eta: 0:17:11 time: 0.0764 data: 0.0019 max mem: 19788 +Test: [ 6700/21770] eta: 0:17:04 time: 0.0625 data: 0.0019 max mem: 19788 +Test: [ 6800/21770] eta: 0:16:57 time: 0.0649 data: 0.0017 max mem: 19788 +Test: [ 6900/21770] eta: 0:16:49 time: 0.0626 data: 0.0020 max mem: 19788 +Test: [ 7000/21770] eta: 0:16:43 time: 0.0654 data: 0.0020 max mem: 19788 +Test: [ 7100/21770] eta: 0:16:35 time: 0.0643 data: 0.0019 max mem: 19788 +Test: [ 7200/21770] eta: 0:16:29 time: 0.0615 data: 0.0017 max mem: 19788 +Test: [ 7300/21770] eta: 0:16:21 time: 0.0634 data: 0.0018 max mem: 19788 +Test: [ 7400/21770] eta: 0:16:14 time: 0.0612 data: 0.0019 max mem: 19788 +Test: [ 7500/21770] eta: 0:16:07 time: 0.0791 data: 0.0021 max mem: 19788 +Test: [ 7600/21770] eta: 0:16:01 time: 0.0664 data: 0.0019 max mem: 19788 +Test: [ 7700/21770] eta: 0:15:55 time: 0.0606 data: 0.0018 max mem: 19788 +Test: [ 7800/21770] eta: 0:15:49 time: 0.0794 data: 0.0021 max mem: 19788 +Test: [ 7900/21770] eta: 0:15:43 time: 0.0733 data: 0.0019 max mem: 19788 +Test: [ 8000/21770] eta: 0:15:36 time: 0.0745 data: 0.0020 max mem: 19788 +Test: [ 8100/21770] eta: 0:15:30 time: 0.0700 data: 0.0021 max mem: 19788 +Test: [ 8200/21770] eta: 0:15:23 time: 0.0717 data: 0.0020 max mem: 19788 +Test: [ 8300/21770] eta: 0:15:16 time: 0.0635 data: 0.0018 max mem: 19788 +Test: [ 8400/21770] eta: 0:15:09 time: 0.0677 data: 0.0020 max mem: 19788 +Test: [ 8500/21770] eta: 0:15:02 time: 0.0625 data: 0.0019 max mem: 19788 +Test: [ 8600/21770] eta: 0:14:55 time: 0.0682 data: 0.0019 max mem: 19788 +Test: [ 8700/21770] eta: 0:14:48 time: 0.0815 data: 0.0026 max mem: 19788 +Test: [ 8800/21770] eta: 0:14:41 time: 0.0600 data: 0.0017 max mem: 19788 +Test: [ 8900/21770] eta: 0:14:33 time: 0.0617 data: 0.0018 max mem: 19788 +Test: [ 9000/21770] eta: 0:14:26 time: 0.0619 data: 0.0020 max mem: 19788 +Test: [ 9100/21770] eta: 0:14:18 time: 0.0628 data: 0.0017 max mem: 19788 +Test: [ 9200/21770] eta: 0:14:12 time: 0.0649 data: 0.0018 max mem: 19788 +Test: [ 9300/21770] eta: 0:14:05 time: 0.0619 data: 0.0017 max mem: 19788 +Test: [ 9400/21770] eta: 0:13:58 time: 0.0603 data: 0.0017 max mem: 19788 +Test: [ 9500/21770] eta: 0:13:51 time: 0.0794 data: 0.0023 max mem: 19788 +Test: [ 9600/21770] eta: 0:13:44 time: 0.0628 data: 0.0019 max mem: 19788 +Test: [ 9700/21770] eta: 0:13:37 time: 0.0650 data: 0.0020 max mem: 19788 +Test: [ 9800/21770] eta: 0:13:30 time: 0.0627 data: 0.0018 max mem: 19788 +Test: [ 9900/21770] eta: 0:13:24 time: 0.0803 data: 0.0023 max mem: 19788 +Test: [10000/21770] eta: 0:13:18 time: 0.0816 data: 0.0022 max mem: 19788 +Test: [10100/21770] eta: 0:13:12 time: 0.0744 data: 0.0022 max mem: 19788 +Test: [10200/21770] eta: 0:13:06 time: 0.0693 data: 0.0021 max mem: 19788 +Test: [10300/21770] eta: 0:13:00 time: 0.0803 data: 0.0024 max mem: 19788 +Test: [10400/21770] eta: 0:12:53 time: 0.0627 data: 0.0019 max mem: 19788 +Test: [10500/21770] eta: 0:12:46 time: 0.0796 data: 0.0018 max mem: 19788 +Test: [10600/21770] eta: 0:12:40 time: 0.0677 data: 0.0020 max mem: 19788 +Test: [10700/21770] eta: 0:12:33 time: 0.0645 data: 0.0019 max mem: 19788 +Test: [10800/21770] eta: 0:12:26 time: 0.0636 data: 0.0020 max mem: 19788 +Test: [10900/21770] eta: 0:12:20 time: 0.0732 data: 0.0020 max mem: 19788 +Test: [11000/21770] eta: 0:12:13 time: 0.0623 data: 0.0018 max mem: 19788 +Test: [11100/21770] eta: 0:12:06 time: 0.0637 data: 0.0019 max mem: 19788 +Test: [11200/21770] eta: 0:11:59 time: 0.0794 data: 0.0023 max mem: 19788 +Test: [11300/21770] eta: 0:11:52 time: 0.0742 data: 0.0023 max mem: 19788 +Test: [11400/21770] eta: 0:11:46 time: 0.0700 data: 0.0018 max mem: 19788 +Test: [11500/21770] eta: 0:11:40 time: 0.0657 data: 0.0019 max mem: 19788 +Test: [11600/21770] eta: 0:11:33 time: 0.0698 data: 0.0019 max mem: 19788 +Test: [11700/21770] eta: 0:11:26 time: 0.0621 data: 0.0019 max mem: 19788 +Test: [11800/21770] eta: 0:11:18 time: 0.0619 data: 0.0017 max mem: 19788 +Test: [11900/21770] eta: 0:11:12 time: 0.0655 data: 0.0020 max mem: 19788 +Test: [12000/21770] eta: 0:11:05 time: 0.0709 data: 0.0020 max mem: 19788 +Test: [12100/21770] eta: 0:10:59 time: 0.0794 data: 0.0025 max mem: 19788 +Test: [12200/21770] eta: 0:10:52 time: 0.0669 data: 0.0020 max mem: 19788 +Test: [12300/21770] eta: 0:10:45 time: 0.0717 data: 0.0021 max mem: 19788 +Test: [12400/21770] eta: 0:10:39 time: 0.0727 data: 0.0019 max mem: 19788 +Test: [12500/21770] eta: 0:10:32 time: 0.0793 data: 0.0024 max mem: 19788 +Test: [12600/21770] eta: 0:10:25 time: 0.0644 data: 0.0019 max mem: 19788 +Test: [12700/21770] eta: 0:10:18 time: 0.0816 data: 0.0019 max mem: 19788 +Test: [12800/21770] eta: 0:10:12 time: 0.0629 data: 0.0017 max mem: 19788 +Test: [12900/21770] eta: 0:10:05 time: 0.0673 data: 0.0020 max mem: 19788 +Test: [13000/21770] eta: 0:09:58 time: 0.0817 data: 0.0024 max mem: 19788 +Test: [13100/21770] eta: 0:09:52 time: 0.0703 data: 0.0019 max mem: 19788 +Test: [13200/21770] eta: 0:09:45 time: 0.0783 data: 0.0023 max mem: 19788 +Test: [13300/21770] eta: 0:09:38 time: 0.0779 data: 0.0023 max mem: 19788 +Test: [13400/21770] eta: 0:09:32 time: 0.0812 data: 0.0021 max mem: 19788 +Test: [13500/21770] eta: 0:09:25 time: 0.0625 data: 0.0018 max mem: 19788 +Test: [13600/21770] eta: 0:09:18 time: 0.0691 data: 0.0021 max mem: 19788 +Test: [13700/21770] eta: 0:09:11 time: 0.0658 data: 0.0020 max mem: 19788 +Test: [13800/21770] eta: 0:09:05 time: 0.0735 data: 0.0022 max mem: 19788 +Test: [13900/21770] eta: 0:08:58 time: 0.0614 data: 0.0019 max mem: 19788 +Test: [14000/21770] eta: 0:08:51 time: 0.0764 data: 0.0025 max mem: 19788 +Test: [14100/21770] eta: 0:08:44 time: 0.0728 data: 0.0018 max mem: 19788 +Test: [14200/21770] eta: 0:08:38 time: 0.0667 data: 0.0021 max mem: 19788 +Test: [14300/21770] eta: 0:08:31 time: 0.0616 data: 0.0017 max mem: 19788 +Test: [14400/21770] eta: 0:08:24 time: 0.0698 data: 0.0020 max mem: 19788 +Test: [14500/21770] eta: 0:08:17 time: 0.0626 data: 0.0018 max mem: 19788 +Test: [14600/21770] eta: 0:08:10 time: 0.0796 data: 0.0022 max mem: 19788 +Test: [14700/21770] eta: 0:08:03 time: 0.0631 data: 0.0018 max mem: 19788 +Test: [14800/21770] eta: 0:07:56 time: 0.0625 data: 0.0017 max mem: 19788 +Test: [14900/21770] eta: 0:07:50 time: 0.0647 data: 0.0021 max mem: 19788 +Test: [15000/21770] eta: 0:07:43 time: 0.0615 data: 0.0017 max mem: 19788 +Test: [15100/21770] eta: 0:07:36 time: 0.0723 data: 0.0019 max mem: 19788 +Test: [15200/21770] eta: 0:07:29 time: 0.0691 data: 0.0020 max mem: 19788 +Test: [15300/21770] eta: 0:07:22 time: 0.0624 data: 0.0018 max mem: 19788 +Test: [15400/21770] eta: 0:07:15 time: 0.0813 data: 0.0020 max mem: 19788 +Test: [15500/21770] eta: 0:07:08 time: 0.0605 data: 0.0017 max mem: 19788 +Test: [15600/21770] eta: 0:07:01 time: 0.0594 data: 0.0017 max mem: 19788 +Test: [15700/21770] eta: 0:06:55 time: 0.0608 data: 0.0017 max mem: 19788 +Test: [15800/21770] eta: 0:06:48 time: 0.0726 data: 0.0019 max mem: 19788 +Test: [15900/21770] eta: 0:06:41 time: 0.0619 data: 0.0018 max mem: 19788 +Test: [16000/21770] eta: 0:06:34 time: 0.0630 data: 0.0020 max mem: 19788 +Test: [16100/21770] eta: 0:06:27 time: 0.0615 data: 0.0018 max mem: 19788 +Test: [16200/21770] eta: 0:06:20 time: 0.0716 data: 0.0021 max mem: 19788 +Test: [16300/21770] eta: 0:06:13 time: 0.0716 data: 0.0019 max mem: 19788 +Test: [16400/21770] eta: 0:06:07 time: 0.0712 data: 0.0021 max mem: 19788 +Test: [16500/21770] eta: 0:06:00 time: 0.0710 data: 0.0020 max mem: 19788 +Test: [16600/21770] eta: 0:05:53 time: 0.0579 data: 0.0017 max mem: 19788 +Test: [16700/21770] eta: 0:05:46 time: 0.0617 data: 0.0018 max mem: 19788 +Test: [16800/21770] eta: 0:05:39 time: 0.0662 data: 0.0018 max mem: 19788 +Test: [16900/21770] eta: 0:05:32 time: 0.0597 data: 0.0017 max mem: 19788 +Test: [17000/21770] eta: 0:05:25 time: 0.0594 data: 0.0019 max mem: 19788 +Test: [17100/21770] eta: 0:05:19 time: 0.0677 data: 0.0020 max mem: 19788 +Test: [17200/21770] eta: 0:05:12 time: 0.0662 data: 0.0020 max mem: 19788 +Test: [17300/21770] eta: 0:05:05 time: 0.0707 data: 0.0021 max mem: 19788 +Test: [17400/21770] eta: 0:04:58 time: 0.0631 data: 0.0017 max mem: 19788 +Test: [17500/21770] eta: 0:04:51 time: 0.0601 data: 0.0018 max mem: 19788 +Test: [17600/21770] eta: 0:04:44 time: 0.0687 data: 0.0023 max mem: 19788 +Test: [17700/21770] eta: 0:04:37 time: 0.0678 data: 0.0018 max mem: 19788 +Test: [17800/21770] eta: 0:04:30 time: 0.0810 data: 0.0025 max mem: 19788 +Test: [17900/21770] eta: 0:04:24 time: 0.0622 data: 0.0018 max mem: 19788 +Test: [18000/21770] eta: 0:04:17 time: 0.0612 data: 0.0019 max mem: 19788 +Test: [18100/21770] eta: 0:04:10 time: 0.0822 data: 0.0024 max mem: 19788 +Test: [18200/21770] eta: 0:04:03 time: 0.0620 data: 0.0019 max mem: 19788 +Test: [18300/21770] eta: 0:03:57 time: 0.0594 data: 0.0016 max mem: 19788 +Test: [18400/21770] eta: 0:03:50 time: 0.0651 data: 0.0019 max mem: 19788 +Test: [18500/21770] eta: 0:03:43 time: 0.0652 data: 0.0019 max mem: 19788 +Test: [18600/21770] eta: 0:03:36 time: 0.0666 data: 0.0019 max mem: 19788 +Test: [18700/21770] eta: 0:03:29 time: 0.0695 data: 0.0020 max mem: 19788 +Test: [18800/21770] eta: 0:03:22 time: 0.0647 data: 0.0017 max mem: 19788 +Test: [18900/21770] eta: 0:03:16 time: 0.0629 data: 0.0017 max mem: 19788 +Test: [19000/21770] eta: 0:03:09 time: 0.0600 data: 0.0017 max mem: 19788 +Test: [19100/21770] eta: 0:03:02 time: 0.0758 data: 0.0022 max mem: 19788 +Test: [19200/21770] eta: 0:02:55 time: 0.0659 data: 0.0019 max mem: 19788 +Test: [19300/21770] eta: 0:02:48 time: 0.0615 data: 0.0017 max mem: 19788 +Test: [19400/21770] eta: 0:02:41 time: 0.0708 data: 0.0020 max mem: 19788 +Test: [19500/21770] eta: 0:02:35 time: 0.0755 data: 0.0021 max mem: 19788 +Test: [19600/21770] eta: 0:02:28 time: 0.0674 data: 0.0020 max mem: 19788 +Test: [19700/21770] eta: 0:02:21 time: 0.0692 data: 0.0020 max mem: 19788 +Test: [19800/21770] eta: 0:02:14 time: 0.0732 data: 0.0021 max mem: 19788 +Test: [19900/21770] eta: 0:02:07 time: 0.0651 data: 0.0022 max mem: 19788 +Test: [20000/21770] eta: 0:02:00 time: 0.0758 data: 0.0022 max mem: 19788 +Test: [20100/21770] eta: 0:01:54 time: 0.0799 data: 0.0019 max mem: 19788 +Test: [20200/21770] eta: 0:01:47 time: 0.0634 data: 0.0019 max mem: 19788 +Test: [20300/21770] eta: 0:01:40 time: 0.0660 data: 0.0020 max mem: 19788 +Test: [20400/21770] eta: 0:01:33 time: 0.0650 data: 0.0018 max mem: 19788 +Test: [20500/21770] eta: 0:01:26 time: 0.0745 data: 0.0022 max mem: 19788 +Test: [20600/21770] eta: 0:01:20 time: 0.0800 data: 0.0029 max mem: 19788 +Test: [20700/21770] eta: 0:01:13 time: 0.0614 data: 0.0018 max mem: 19788 +Test: [20800/21770] eta: 0:01:06 time: 0.0619 data: 0.0017 max mem: 19788 +Test: [20900/21770] eta: 0:00:59 time: 0.0594 data: 0.0017 max mem: 19788 +Test: [21000/21770] eta: 0:00:52 time: 0.0623 data: 0.0019 max mem: 19788 +Test: [21100/21770] eta: 0:00:45 time: 0.0632 data: 0.0017 max mem: 19788 +Test: [21200/21770] eta: 0:00:38 time: 0.0678 data: 0.0019 max mem: 19788 +Test: [21300/21770] eta: 0:00:32 time: 0.0767 data: 0.0023 max mem: 19788 +Test: [21400/21770] eta: 0:00:25 time: 0.0610 data: 0.0020 max mem: 19788 +Test: [21500/21770] eta: 0:00:18 time: 0.0737 data: 0.0020 max mem: 19788 +Test: [21600/21770] eta: 0:00:11 time: 0.0626 data: 0.0018 max mem: 19788 +Test: [21700/21770] eta: 0:00:04 time: 0.0693 data: 0.0019 max mem: 19788 +Test: Total time: 0:24:49 +Final results: +Mean IoU is 54.68 + + precision@0.5 = 59.80 + precision@0.6 = 53.65 + precision@0.7 = 46.49 + precision@0.8 = 35.50 + precision@0.9 = 15.51 + overall IoU = 58.95 + mean IoU = 54.68 + +Mean accuracy for one-to-zero sample is 80.10 + +Average object IoU 0.5468451610492931 +Overall IoU 58.95405197143555 +Better epoch: 2 + +Epoch: [3] [ 0/2138] eta: 3:14:47 lr: 4.661145101562426e-05 loss: 0.1213 (0.1213) time: 5.4666 data: 1.4219 max mem: 19788 +Epoch: [3] [ 10/2138] eta: 2:15:15 lr: 4.660614786524411e-05 loss: 0.1213 (0.1297) time: 3.8136 data: 0.1319 max mem: 19788 +Epoch: [3] [ 20/2138] eta: 2:12:02 lr: 4.660084464781567e-05 loss: 0.0899 (0.1071) time: 3.6543 data: 0.0029 max mem: 19788 +Epoch: [3] [ 30/2138] eta: 2:10:12 lr: 4.659554136332963e-05 loss: 0.0801 (0.1048) time: 3.6467 data: 0.0029 max mem: 19788 +Epoch: [3] [ 40/2138] eta: 2:09:08 lr: 4.659023801177665e-05 loss: 0.0919 (0.1035) time: 3.6432 data: 0.0030 max mem: 19788 +Epoch: [3] [ 50/2138] eta: 2:08:02 lr: 4.65849345931474e-05 loss: 0.0947 (0.1075) time: 3.6383 data: 0.0031 max mem: 19788 +Epoch: [3] [ 60/2138] eta: 2:07:16 lr: 4.6579631107432545e-05 loss: 0.1079 (0.1071) time: 3.6376 data: 0.0032 max mem: 19788 +Epoch: [3] [ 70/2138] eta: 2:06:26 lr: 4.657432755462277e-05 loss: 0.0889 (0.1043) time: 3.6403 data: 0.0030 max mem: 19788 +Epoch: [3] [ 80/2138] eta: 2:05:41 lr: 4.65690239347087e-05 loss: 0.0889 (0.1055) time: 3.6322 data: 0.0028 max mem: 19788 +Epoch: [3] [ 90/2138] eta: 2:05:01 lr: 4.6563720247681023e-05 loss: 0.1006 (0.1076) time: 3.6440 data: 0.0029 max mem: 19788 +Epoch: [3] [ 100/2138] eta: 2:04:20 lr: 4.655841649353039e-05 loss: 0.0998 (0.1076) time: 3.6457 data: 0.0030 max mem: 19788 +Epoch: [3] [ 110/2138] eta: 2:03:43 lr: 4.6553112672247454e-05 loss: 0.0903 (0.1071) time: 3.6491 data: 0.0032 max mem: 19788 +Epoch: [3] [ 120/2138] eta: 2:03:00 lr: 4.654780878382286e-05 loss: 0.0954 (0.1066) time: 3.6416 data: 0.0033 max mem: 19788 +Epoch: [3] [ 130/2138] eta: 2:02:20 lr: 4.654250482824726e-05 loss: 0.1060 (0.1081) time: 3.6283 data: 0.0032 max mem: 19788 +Epoch: [3] [ 140/2138] eta: 2:01:40 lr: 4.65372008055113e-05 loss: 0.1038 (0.1091) time: 3.6336 data: 0.0033 max mem: 19788 +Epoch: [3] [ 150/2138] eta: 2:01:21 lr: 4.653189671560564e-05 loss: 0.0947 (0.1081) time: 3.7076 data: 0.0032 max mem: 19788 +Epoch: [3] [ 160/2138] eta: 2:00:40 lr: 4.65265925585209e-05 loss: 0.0978 (0.1087) time: 3.7053 data: 0.0031 max mem: 19788 +Epoch: [3] [ 170/2138] eta: 2:00:02 lr: 4.652128833424774e-05 loss: 0.1107 (0.1083) time: 3.6389 data: 0.0031 max mem: 19788 +Epoch: [3] [ 180/2138] eta: 1:59:23 lr: 4.651598404277677e-05 loss: 0.0961 (0.1084) time: 3.6436 data: 0.0031 max mem: 19788 +Epoch: [3] [ 190/2138] eta: 1:58:46 lr: 4.651067968409865e-05 loss: 0.0831 (0.1080) time: 3.6470 data: 0.0030 max mem: 19788 +Epoch: [3] [ 200/2138] eta: 1:58:08 lr: 4.6505375258204e-05 loss: 0.0831 (0.1073) time: 3.6481 data: 0.0029 max mem: 19788 +Epoch: [3] [ 210/2138] eta: 1:57:32 lr: 4.6500070765083455e-05 loss: 0.0937 (0.1077) time: 3.6512 data: 0.0030 max mem: 19788 +Epoch: [3] [ 220/2138] eta: 1:56:59 lr: 4.6494766204727634e-05 loss: 0.1017 (0.1076) time: 3.6804 data: 0.0031 max mem: 19788 +Epoch: [3] [ 230/2138] eta: 1:56:24 lr: 4.648946157712717e-05 loss: 0.0983 (0.1077) time: 3.6889 data: 0.0031 max mem: 19788 +Epoch: [3] [ 240/2138] eta: 1:55:46 lr: 4.648415688227268e-05 loss: 0.0937 (0.1076) time: 3.6659 data: 0.0030 max mem: 19788 +Epoch: [3] [ 250/2138] eta: 1:55:07 lr: 4.6478852120154776e-05 loss: 0.0943 (0.1079) time: 3.6401 data: 0.0029 max mem: 19788 +Epoch: [3] [ 260/2138] eta: 1:54:30 lr: 4.647354729076409e-05 loss: 0.0945 (0.1072) time: 3.6343 data: 0.0028 max mem: 19788 +Epoch: [3] [ 270/2138] eta: 1:53:52 lr: 4.646824239409123e-05 loss: 0.0980 (0.1081) time: 3.6441 data: 0.0029 max mem: 19788 +Epoch: [3] [ 280/2138] eta: 1:53:13 lr: 4.646293743012681e-05 loss: 0.1159 (0.1079) time: 3.6351 data: 0.0030 max mem: 19788 +Epoch: [3] [ 290/2138] eta: 1:52:35 lr: 4.6457632398861426e-05 loss: 0.1022 (0.1076) time: 3.6250 data: 0.0030 max mem: 19788 +Epoch: [3] [ 300/2138] eta: 1:51:57 lr: 4.6452327300285705e-05 loss: 0.0987 (0.1076) time: 3.6271 data: 0.0031 max mem: 19788 +Epoch: [3] [ 310/2138] eta: 1:51:18 lr: 4.644702213439024e-05 loss: 0.0942 (0.1072) time: 3.6277 data: 0.0030 max mem: 19788 +Epoch: [3] [ 320/2138] eta: 1:50:41 lr: 4.644171690116564e-05 loss: 0.0933 (0.1070) time: 3.6303 data: 0.0029 max mem: 19788 +Epoch: [3] [ 330/2138] eta: 1:50:04 lr: 4.643641160060249e-05 loss: 0.1062 (0.1070) time: 3.6423 data: 0.0028 max mem: 19788 +Epoch: [3] [ 340/2138] eta: 1:49:27 lr: 4.64311062326914e-05 loss: 0.1108 (0.1070) time: 3.6425 data: 0.0030 max mem: 19788 +Epoch: [3] [ 350/2138] eta: 1:48:50 lr: 4.6425800797422965e-05 loss: 0.1102 (0.1070) time: 3.6446 data: 0.0031 max mem: 19788 +Epoch: [3] [ 360/2138] eta: 1:48:12 lr: 4.642049529478777e-05 loss: 0.1075 (0.1070) time: 3.6373 data: 0.0030 max mem: 19788 +Epoch: [3] [ 370/2138] eta: 1:47:34 lr: 4.6415189724776405e-05 loss: 0.1035 (0.1074) time: 3.6226 data: 0.0029 max mem: 19788 +Epoch: [3] [ 380/2138] eta: 1:46:58 lr: 4.6409884087379465e-05 loss: 0.1031 (0.1070) time: 3.6356 data: 0.0029 max mem: 19788 +Epoch: [3] [ 390/2138] eta: 1:46:20 lr: 4.640457838258752e-05 loss: 0.1013 (0.1071) time: 3.6391 data: 0.0030 max mem: 19788 +Epoch: [3] [ 400/2138] eta: 1:45:43 lr: 4.6399272610391164e-05 loss: 0.1034 (0.1069) time: 3.6357 data: 0.0030 max mem: 19788 +Epoch: [3] [ 410/2138] eta: 1:45:06 lr: 4.639396677078097e-05 loss: 0.1019 (0.1070) time: 3.6367 data: 0.0031 max mem: 19788 +Epoch: [3] [ 420/2138] eta: 1:44:28 lr: 4.6388660863747525e-05 loss: 0.0975 (0.1071) time: 3.6278 data: 0.0030 max mem: 19788 +Epoch: [3] [ 430/2138] eta: 1:43:52 lr: 4.6383354889281393e-05 loss: 0.1014 (0.1073) time: 3.6308 data: 0.0028 max mem: 19788 +Epoch: [3] [ 440/2138] eta: 1:43:14 lr: 4.637804884737314e-05 loss: 0.1153 (0.1076) time: 3.6362 data: 0.0029 max mem: 19788 +Epoch: [3] [ 450/2138] eta: 1:42:38 lr: 4.6372742738013355e-05 loss: 0.0968 (0.1074) time: 3.6400 data: 0.0030 max mem: 19788 +Epoch: [3] [ 460/2138] eta: 1:42:01 lr: 4.636743656119259e-05 loss: 0.0874 (0.1075) time: 3.6427 data: 0.0029 max mem: 19788 +Epoch: [3] [ 470/2138] eta: 1:41:24 lr: 4.6362130316901416e-05 loss: 0.1075 (0.1077) time: 3.6317 data: 0.0029 max mem: 19788 +Epoch: [3] [ 480/2138] eta: 1:40:47 lr: 4.6356824005130386e-05 loss: 0.1036 (0.1075) time: 3.6262 data: 0.0029 max mem: 19788 +Epoch: [3] [ 490/2138] eta: 1:40:09 lr: 4.635151762587006e-05 loss: 0.0917 (0.1073) time: 3.6237 data: 0.0029 max mem: 19788 +Epoch: [3] [ 500/2138] eta: 1:39:33 lr: 4.634621117911101e-05 loss: 0.0901 (0.1075) time: 3.6357 data: 0.0029 max mem: 19788 +Epoch: [3] [ 510/2138] eta: 1:38:56 lr: 4.6340904664843777e-05 loss: 0.0905 (0.1074) time: 3.6468 data: 0.0029 max mem: 19788 +Epoch: [3] [ 520/2138] eta: 1:38:19 lr: 4.6335598083058904e-05 loss: 0.1147 (0.1077) time: 3.6321 data: 0.0030 max mem: 19788 +Epoch: [3] [ 530/2138] eta: 1:37:42 lr: 4.633029143374697e-05 loss: 0.1126 (0.1078) time: 3.6281 data: 0.0030 max mem: 19788 +Epoch: [3] [ 540/2138] eta: 1:37:05 lr: 4.632498471689849e-05 loss: 0.0969 (0.1076) time: 3.6342 data: 0.0030 max mem: 19788 +Epoch: [3] [ 550/2138] eta: 1:36:29 lr: 4.631967793250403e-05 loss: 0.0875 (0.1073) time: 3.6352 data: 0.0031 max mem: 19788 +Epoch: [3] [ 560/2138] eta: 1:35:52 lr: 4.6314371080554106e-05 loss: 0.0887 (0.1076) time: 3.6387 data: 0.0029 max mem: 19788 +Epoch: [3] [ 570/2138] eta: 1:35:15 lr: 4.630906416103929e-05 loss: 0.1248 (0.1078) time: 3.6401 data: 0.0028 max mem: 19788 +Epoch: [3] [ 580/2138] eta: 1:34:39 lr: 4.630375717395009e-05 loss: 0.1096 (0.1077) time: 3.6441 data: 0.0031 max mem: 19788 +Epoch: [3] [ 590/2138] eta: 1:34:02 lr: 4.629845011927706e-05 loss: 0.0897 (0.1075) time: 3.6422 data: 0.0032 max mem: 19788 +Epoch: [3] [ 600/2138] eta: 1:33:26 lr: 4.6293142997010716e-05 loss: 0.0907 (0.1075) time: 3.6360 data: 0.0031 max mem: 19788 +Epoch: [3] [ 610/2138] eta: 1:32:49 lr: 4.62878358071416e-05 loss: 0.0950 (0.1072) time: 3.6411 data: 0.0029 max mem: 19788 +Epoch: [3] [ 620/2138] eta: 1:32:13 lr: 4.628252854966023e-05 loss: 0.0878 (0.1073) time: 3.6581 data: 0.0028 max mem: 19788 +Epoch: [3] [ 630/2138] eta: 1:31:36 lr: 4.627722122455714e-05 loss: 0.0878 (0.1071) time: 3.6455 data: 0.0027 max mem: 19788 +Epoch: [3] [ 640/2138] eta: 1:31:00 lr: 4.6271913831822826e-05 loss: 0.0982 (0.1071) time: 3.6300 data: 0.0028 max mem: 19788 +Epoch: [3] [ 650/2138] eta: 1:30:23 lr: 4.626660637144784e-05 loss: 0.0982 (0.1068) time: 3.6364 data: 0.0028 max mem: 19788 +Epoch: [3] [ 660/2138] eta: 1:29:47 lr: 4.6261298843422674e-05 loss: 0.0913 (0.1069) time: 3.6429 data: 0.0029 max mem: 19788 +Epoch: [3] [ 670/2138] eta: 1:29:10 lr: 4.625599124773786e-05 loss: 0.0932 (0.1066) time: 3.6510 data: 0.0031 max mem: 19788 +Epoch: [3] [ 680/2138] eta: 1:28:34 lr: 4.625068358438389e-05 loss: 0.0882 (0.1065) time: 3.6407 data: 0.0029 max mem: 19788 +Epoch: [3] [ 690/2138] eta: 1:27:57 lr: 4.624537585335128e-05 loss: 0.0968 (0.1065) time: 3.6268 data: 0.0030 max mem: 19788 +Epoch: [3] [ 700/2138] eta: 1:27:20 lr: 4.624006805463054e-05 loss: 0.0968 (0.1064) time: 3.6364 data: 0.0031 max mem: 19788 +Epoch: [3] [ 710/2138] eta: 1:26:44 lr: 4.623476018821218e-05 loss: 0.0931 (0.1065) time: 3.6481 data: 0.0029 max mem: 19788 +Epoch: [3] [ 720/2138] eta: 1:26:07 lr: 4.622945225408668e-05 loss: 0.1054 (0.1066) time: 3.6378 data: 0.0028 max mem: 19788 +Epoch: [3] [ 730/2138] eta: 1:25:31 lr: 4.622414425224456e-05 loss: 0.1066 (0.1065) time: 3.6370 data: 0.0028 max mem: 19788 +Epoch: [3] [ 740/2138] eta: 1:24:54 lr: 4.62188361826763e-05 loss: 0.0868 (0.1063) time: 3.6341 data: 0.0029 max mem: 19788 +Epoch: [3] [ 750/2138] eta: 1:24:18 lr: 4.62135280453724e-05 loss: 0.0868 (0.1062) time: 3.6412 data: 0.0029 max mem: 19788 +Epoch: [3] [ 760/2138] eta: 1:23:41 lr: 4.620821984032335e-05 loss: 0.0999 (0.1062) time: 3.6431 data: 0.0029 max mem: 19788 +Epoch: [3] [ 770/2138] eta: 1:23:05 lr: 4.620291156751964e-05 loss: 0.0990 (0.1060) time: 3.6331 data: 0.0030 max mem: 19788 +Epoch: [3] [ 780/2138] eta: 1:22:28 lr: 4.6197603226951766e-05 loss: 0.0974 (0.1059) time: 3.6326 data: 0.0030 max mem: 19788 +Epoch: [3] [ 790/2138] eta: 1:21:51 lr: 4.619229481861018e-05 loss: 0.1112 (0.1063) time: 3.6334 data: 0.0030 max mem: 19788 +Epoch: [3] [ 800/2138] eta: 1:21:15 lr: 4.618698634248539e-05 loss: 0.1163 (0.1062) time: 3.6308 data: 0.0030 max mem: 19788 +Epoch: [3] [ 810/2138] eta: 1:20:38 lr: 4.6181677798567866e-05 loss: 0.0851 (0.1061) time: 3.6379 data: 0.0029 max mem: 19788 +Epoch: [3] [ 820/2138] eta: 1:20:02 lr: 4.617636918684809e-05 loss: 0.0906 (0.1059) time: 3.6456 data: 0.0029 max mem: 19788 +Epoch: [3] [ 830/2138] eta: 1:19:25 lr: 4.617106050731652e-05 loss: 0.0890 (0.1060) time: 3.6335 data: 0.0030 max mem: 19788 +Epoch: [3] [ 840/2138] eta: 1:18:48 lr: 4.6165751759963636e-05 loss: 0.0818 (0.1057) time: 3.6315 data: 0.0029 max mem: 19788 +Epoch: [3] [ 850/2138] eta: 1:18:12 lr: 4.61604429447799e-05 loss: 0.0872 (0.1057) time: 3.6340 data: 0.0028 max mem: 19788 +Epoch: [3] [ 860/2138] eta: 1:17:35 lr: 4.61551340617558e-05 loss: 0.0905 (0.1056) time: 3.6355 data: 0.0028 max mem: 19788 +Epoch: [3] [ 870/2138] eta: 1:16:59 lr: 4.614982511088176e-05 loss: 0.0843 (0.1054) time: 3.6417 data: 0.0028 max mem: 19788 +Epoch: [3] [ 880/2138] eta: 1:16:22 lr: 4.614451609214827e-05 loss: 0.0874 (0.1053) time: 3.6330 data: 0.0030 max mem: 19788 +Epoch: [3] [ 890/2138] eta: 1:15:46 lr: 4.613920700554577e-05 loss: 0.0922 (0.1054) time: 3.6202 data: 0.0031 max mem: 19788 +Epoch: [3] [ 900/2138] eta: 1:15:09 lr: 4.613389785106474e-05 loss: 0.1238 (0.1058) time: 3.6387 data: 0.0030 max mem: 19788 +Epoch: [3] [ 910/2138] eta: 1:14:33 lr: 4.6128588628695593e-05 loss: 0.1238 (0.1058) time: 3.6478 data: 0.0029 max mem: 19788 +Epoch: [3] [ 920/2138] eta: 1:13:56 lr: 4.612327933842882e-05 loss: 0.0940 (0.1060) time: 3.6344 data: 0.0033 max mem: 19788 +Epoch: [3] [ 930/2138] eta: 1:13:20 lr: 4.611796998025484e-05 loss: 0.1105 (0.1059) time: 3.6333 data: 0.0034 max mem: 19788 +Epoch: [3] [ 940/2138] eta: 1:12:43 lr: 4.61126605541641e-05 loss: 0.1105 (0.1060) time: 3.6317 data: 0.0030 max mem: 19788 +Epoch: [3] [ 950/2138] eta: 1:12:07 lr: 4.610735106014706e-05 loss: 0.0945 (0.1059) time: 3.6301 data: 0.0028 max mem: 19788 +Epoch: [3] [ 960/2138] eta: 1:11:30 lr: 4.6102041498194157e-05 loss: 0.0954 (0.1060) time: 3.6420 data: 0.0026 max mem: 19788 +Epoch: [3] [ 970/2138] eta: 1:10:54 lr: 4.6096731868295805e-05 loss: 0.0920 (0.1058) time: 3.6484 data: 0.0028 max mem: 19788 +Epoch: [3] [ 980/2138] eta: 1:10:18 lr: 4.609142217044246e-05 loss: 0.0867 (0.1057) time: 3.6501 data: 0.0032 max mem: 19788 +Epoch: [3] [ 990/2138] eta: 1:09:41 lr: 4.608611240462454e-05 loss: 0.1016 (0.1056) time: 3.6452 data: 0.0030 max mem: 19788 +Epoch: [3] [1000/2138] eta: 1:09:05 lr: 4.608080257083249e-05 loss: 0.0985 (0.1055) time: 3.6411 data: 0.0029 max mem: 19788 +Epoch: [3] [1010/2138] eta: 1:08:28 lr: 4.607549266905673e-05 loss: 0.0987 (0.1054) time: 3.6419 data: 0.0030 max mem: 19788 +Epoch: [3] [1020/2138] eta: 1:07:52 lr: 4.6070182699287676e-05 loss: 0.0974 (0.1052) time: 3.6433 data: 0.0031 max mem: 19788 +Epoch: [3] [1030/2138] eta: 1:07:15 lr: 4.606487266151576e-05 loss: 0.0791 (0.1051) time: 3.6402 data: 0.0031 max mem: 19788 +Epoch: [3] [1040/2138] eta: 1:06:39 lr: 4.60595625557314e-05 loss: 0.0915 (0.1049) time: 3.6448 data: 0.0032 max mem: 19788 +Epoch: [3] [1050/2138] eta: 1:06:03 lr: 4.605425238192501e-05 loss: 0.0848 (0.1048) time: 3.6518 data: 0.0033 max mem: 19788 +Epoch: [3] [1060/2138] eta: 1:05:26 lr: 4.604894214008699e-05 loss: 0.0835 (0.1047) time: 3.6352 data: 0.0032 max mem: 19788 +Epoch: [3] [1070/2138] eta: 1:04:50 lr: 4.6043631830207775e-05 loss: 0.0867 (0.1046) time: 3.6284 data: 0.0031 max mem: 19788 +Epoch: [3] [1080/2138] eta: 1:04:13 lr: 4.603832145227776e-05 loss: 0.0865 (0.1045) time: 3.6324 data: 0.0029 max mem: 19788 +Epoch: [3] [1090/2138] eta: 1:03:36 lr: 4.6033011006287364e-05 loss: 0.0911 (0.1044) time: 3.6282 data: 0.0029 max mem: 19788 +Epoch: [3] [1100/2138] eta: 1:03:00 lr: 4.6027700492226966e-05 loss: 0.0964 (0.1045) time: 3.6372 data: 0.0029 max mem: 19788 +Epoch: [3] [1110/2138] eta: 1:02:24 lr: 4.602238991008699e-05 loss: 0.0946 (0.1044) time: 3.6422 data: 0.0029 max mem: 19788 +Epoch: [3] [1120/2138] eta: 1:01:47 lr: 4.601707925985783e-05 loss: 0.0946 (0.1045) time: 3.6413 data: 0.0030 max mem: 19788 +Epoch: [3] [1130/2138] eta: 1:01:11 lr: 4.601176854152987e-05 loss: 0.1084 (0.1045) time: 3.6408 data: 0.0032 max mem: 19788 +Epoch: [3] [1140/2138] eta: 1:00:34 lr: 4.6006457755093514e-05 loss: 0.1167 (0.1047) time: 3.6314 data: 0.0032 max mem: 19788 +Epoch: [3] [1150/2138] eta: 0:59:58 lr: 4.6001146900539146e-05 loss: 0.0924 (0.1046) time: 3.6299 data: 0.0030 max mem: 19788 +Epoch: [3] [1160/2138] eta: 0:59:21 lr: 4.5995835977857166e-05 loss: 0.0829 (0.1046) time: 3.6424 data: 0.0029 max mem: 19788 +Epoch: [3] [1170/2138] eta: 0:58:45 lr: 4.5990524987037944e-05 loss: 0.0973 (0.1048) time: 3.6446 data: 0.0029 max mem: 19788 +Epoch: [3] [1180/2138] eta: 0:58:08 lr: 4.598521392807187e-05 loss: 0.1143 (0.1051) time: 3.6305 data: 0.0028 max mem: 19788 +Epoch: [3] [1190/2138] eta: 0:57:32 lr: 4.5979902800949336e-05 loss: 0.1025 (0.1050) time: 3.6411 data: 0.0027 max mem: 19788 +Epoch: [3] [1200/2138] eta: 0:56:56 lr: 4.597459160566069e-05 loss: 0.1022 (0.1051) time: 3.6523 data: 0.0028 max mem: 19788 +Epoch: [3] [1210/2138] eta: 0:56:19 lr: 4.596928034219634e-05 loss: 0.1020 (0.1050) time: 3.6398 data: 0.0029 max mem: 19788 +Epoch: [3] [1220/2138] eta: 0:55:43 lr: 4.5963969010546635e-05 loss: 0.0996 (0.1052) time: 3.6296 data: 0.0030 max mem: 19788 +Epoch: [3] [1230/2138] eta: 0:55:06 lr: 4.595865761070196e-05 loss: 0.1012 (0.1052) time: 3.6289 data: 0.0029 max mem: 19788 +Epoch: [3] [1240/2138] eta: 0:54:30 lr: 4.595334614265267e-05 loss: 0.1018 (0.1052) time: 3.6367 data: 0.0029 max mem: 19788 +Epoch: [3] [1250/2138] eta: 0:53:53 lr: 4.594803460638914e-05 loss: 0.0978 (0.1051) time: 3.6366 data: 0.0029 max mem: 19788 +Epoch: [3] [1260/2138] eta: 0:53:17 lr: 4.5942723001901724e-05 loss: 0.0917 (0.1050) time: 3.6362 data: 0.0029 max mem: 19788 +Epoch: [3] [1270/2138] eta: 0:52:40 lr: 4.593741132918078e-05 loss: 0.0940 (0.1049) time: 3.6492 data: 0.0031 max mem: 19788 +Epoch: [3] [1280/2138] eta: 0:52:04 lr: 4.5932099588216674e-05 loss: 0.0889 (0.1050) time: 3.6488 data: 0.0031 max mem: 19788 +Epoch: [3] [1290/2138] eta: 0:51:28 lr: 4.5926787778999755e-05 loss: 0.0959 (0.1052) time: 3.6385 data: 0.0032 max mem: 19788 +Epoch: [3] [1300/2138] eta: 0:50:51 lr: 4.592147590152038e-05 loss: 0.0957 (0.1051) time: 3.6365 data: 0.0030 max mem: 19788 +Epoch: [3] [1310/2138] eta: 0:50:15 lr: 4.5916163955768896e-05 loss: 0.0950 (0.1051) time: 3.6441 data: 0.0029 max mem: 19788 +Epoch: [3] [1320/2138] eta: 0:49:38 lr: 4.5910851941735636e-05 loss: 0.1064 (0.1051) time: 3.6452 data: 0.0031 max mem: 19788 +Epoch: [3] [1330/2138] eta: 0:49:02 lr: 4.590553985941096e-05 loss: 0.0991 (0.1050) time: 3.6358 data: 0.0031 max mem: 19788 +Epoch: [3] [1340/2138] eta: 0:48:26 lr: 4.59002277087852e-05 loss: 0.0910 (0.1050) time: 3.6449 data: 0.0033 max mem: 19788 +Epoch: [3] [1350/2138] eta: 0:47:49 lr: 4.58949154898487e-05 loss: 0.0963 (0.1050) time: 3.6395 data: 0.0034 max mem: 19788 +Epoch: [3] [1360/2138] eta: 0:47:13 lr: 4.5889603202591806e-05 loss: 0.0878 (0.1049) time: 3.6269 data: 0.0031 max mem: 19788 +Epoch: [3] [1370/2138] eta: 0:46:36 lr: 4.588429084700483e-05 loss: 0.0840 (0.1048) time: 3.6320 data: 0.0030 max mem: 19788 +Epoch: [3] [1380/2138] eta: 0:46:00 lr: 4.587897842307811e-05 loss: 0.0840 (0.1047) time: 3.6299 data: 0.0030 max mem: 19788 +Epoch: [3] [1390/2138] eta: 0:45:23 lr: 4.5873665930801983e-05 loss: 0.0911 (0.1048) time: 3.6286 data: 0.0030 max mem: 19788 +Epoch: [3] [1400/2138] eta: 0:44:47 lr: 4.5868353370166775e-05 loss: 0.0970 (0.1048) time: 3.6343 data: 0.0030 max mem: 19788 +Epoch: [3] [1410/2138] eta: 0:44:10 lr: 4.586304074116279e-05 loss: 0.0965 (0.1048) time: 3.6401 data: 0.0029 max mem: 19788 +Epoch: [3] [1420/2138] eta: 0:43:34 lr: 4.585772804378037e-05 loss: 0.0922 (0.1046) time: 3.6314 data: 0.0028 max mem: 19788 +Epoch: [3] [1430/2138] eta: 0:42:57 lr: 4.5852415278009816e-05 loss: 0.0802 (0.1045) time: 3.6259 data: 0.0029 max mem: 19788 +Epoch: [3] [1440/2138] eta: 0:42:21 lr: 4.584710244384146e-05 loss: 0.0813 (0.1045) time: 3.6276 data: 0.0030 max mem: 19788 +Epoch: [3] [1450/2138] eta: 0:41:44 lr: 4.5841789541265595e-05 loss: 0.0908 (0.1045) time: 3.6310 data: 0.0031 max mem: 19788 +Epoch: [3] [1460/2138] eta: 0:41:08 lr: 4.583647657027254e-05 loss: 0.0937 (0.1045) time: 3.6287 data: 0.0030 max mem: 19788 +Epoch: [3] [1470/2138] eta: 0:40:31 lr: 4.583116353085262e-05 loss: 0.0935 (0.1045) time: 3.6271 data: 0.0028 max mem: 19788 +Epoch: [3] [1480/2138] eta: 0:39:55 lr: 4.5825850422996105e-05 loss: 0.0935 (0.1045) time: 3.6369 data: 0.0028 max mem: 19788 +Epoch: [3] [1490/2138] eta: 0:39:19 lr: 4.5820537246693325e-05 loss: 0.0994 (0.1045) time: 3.6387 data: 0.0031 max mem: 19788 +Epoch: [3] [1500/2138] eta: 0:38:42 lr: 4.581522400193457e-05 loss: 0.1010 (0.1046) time: 3.6424 data: 0.0032 max mem: 19788 +Epoch: [3] [1510/2138] eta: 0:38:06 lr: 4.580991068871013e-05 loss: 0.0969 (0.1045) time: 3.6567 data: 0.0031 max mem: 19788 +Epoch: [3] [1520/2138] eta: 0:37:30 lr: 4.580459730701031e-05 loss: 0.0969 (0.1045) time: 3.6501 data: 0.0032 max mem: 19788 +Epoch: [3] [1530/2138] eta: 0:36:53 lr: 4.5799283856825394e-05 loss: 0.0987 (0.1044) time: 3.6321 data: 0.0030 max mem: 19788 +Epoch: [3] [1540/2138] eta: 0:36:17 lr: 4.5793970338145677e-05 loss: 0.0900 (0.1043) time: 3.6265 data: 0.0027 max mem: 19788 +Epoch: [3] [1550/2138] eta: 0:35:40 lr: 4.578865675096143e-05 loss: 0.0891 (0.1043) time: 3.6338 data: 0.0029 max mem: 19788 +Epoch: [3] [1560/2138] eta: 0:35:04 lr: 4.578334309526297e-05 loss: 0.0937 (0.1043) time: 3.6315 data: 0.0029 max mem: 19788 +Epoch: [3] [1570/2138] eta: 0:34:27 lr: 4.577802937104054e-05 loss: 0.1018 (0.1043) time: 3.6231 data: 0.0028 max mem: 19788 +Epoch: [3] [1580/2138] eta: 0:33:51 lr: 4.577271557828444e-05 loss: 0.0972 (0.1042) time: 3.6373 data: 0.0030 max mem: 19788 +Epoch: [3] [1590/2138] eta: 0:33:14 lr: 4.576740171698494e-05 loss: 0.0830 (0.1041) time: 3.6382 data: 0.0030 max mem: 19788 +Epoch: [3] [1600/2138] eta: 0:32:38 lr: 4.576208778713231e-05 loss: 0.0831 (0.1041) time: 3.6370 data: 0.0031 max mem: 19788 +Epoch: [3] [1610/2138] eta: 0:32:02 lr: 4.575677378871683e-05 loss: 0.0942 (0.1041) time: 3.6321 data: 0.0031 max mem: 19788 +Epoch: [3] [1620/2138] eta: 0:31:25 lr: 4.575145972172876e-05 loss: 0.0942 (0.1041) time: 3.6517 data: 0.0030 max mem: 19788 +Epoch: [3] [1630/2138] eta: 0:30:49 lr: 4.574614558615836e-05 loss: 0.0986 (0.1040) time: 3.6722 data: 0.0030 max mem: 19788 +Epoch: [3] [1640/2138] eta: 0:30:13 lr: 4.5740831381995914e-05 loss: 0.0867 (0.1040) time: 3.6555 data: 0.0030 max mem: 19788 +Epoch: [3] [1650/2138] eta: 0:29:36 lr: 4.573551710923166e-05 loss: 0.0925 (0.1040) time: 3.6444 data: 0.0030 max mem: 19788 +Epoch: [3] [1660/2138] eta: 0:29:00 lr: 4.573020276785586e-05 loss: 0.0948 (0.1039) time: 3.6343 data: 0.0031 max mem: 19788 +Epoch: [3] [1670/2138] eta: 0:28:23 lr: 4.5724888357858776e-05 loss: 0.0878 (0.1038) time: 3.6339 data: 0.0032 max mem: 19788 +Epoch: [3] [1680/2138] eta: 0:27:47 lr: 4.571957387923065e-05 loss: 0.0848 (0.1037) time: 3.6470 data: 0.0030 max mem: 19788 +Epoch: [3] [1690/2138] eta: 0:27:11 lr: 4.571425933196173e-05 loss: 0.0894 (0.1038) time: 3.6469 data: 0.0029 max mem: 19788 +Epoch: [3] [1700/2138] eta: 0:26:34 lr: 4.570894471604229e-05 loss: 0.0928 (0.1037) time: 3.6316 data: 0.0029 max mem: 19788 +Epoch: [3] [1710/2138] eta: 0:25:58 lr: 4.570363003146254e-05 loss: 0.0950 (0.1037) time: 3.6266 data: 0.0029 max mem: 19788 +Epoch: [3] [1720/2138] eta: 0:25:21 lr: 4.569831527821274e-05 loss: 0.0909 (0.1036) time: 3.6465 data: 0.0030 max mem: 19788 +Epoch: [3] [1730/2138] eta: 0:24:45 lr: 4.569300045628312e-05 loss: 0.0887 (0.1036) time: 3.6523 data: 0.0032 max mem: 19788 +Epoch: [3] [1740/2138] eta: 0:24:08 lr: 4.5687685565663915e-05 loss: 0.0725 (0.1034) time: 3.6348 data: 0.0030 max mem: 19788 +Epoch: [3] [1750/2138] eta: 0:23:32 lr: 4.568237060634537e-05 loss: 0.0775 (0.1033) time: 3.6378 data: 0.0027 max mem: 19788 +Epoch: [3] [1760/2138] eta: 0:22:56 lr: 4.567705557831771e-05 loss: 0.0979 (0.1033) time: 3.6376 data: 0.0027 max mem: 19788 +Epoch: [3] [1770/2138] eta: 0:22:19 lr: 4.567174048157116e-05 loss: 0.0979 (0.1033) time: 3.6452 data: 0.0028 max mem: 19788 +Epoch: [3] [1780/2138] eta: 0:21:43 lr: 4.566642531609594e-05 loss: 0.0942 (0.1032) time: 3.6546 data: 0.0030 max mem: 19788 +Epoch: [3] [1790/2138] eta: 0:21:06 lr: 4.5661110081882285e-05 loss: 0.0978 (0.1032) time: 3.6352 data: 0.0034 max mem: 19788 +Epoch: [3] [1800/2138] eta: 0:20:30 lr: 4.565579477892041e-05 loss: 0.1048 (0.1034) time: 3.6329 data: 0.0033 max mem: 19788 +Epoch: [3] [1810/2138] eta: 0:19:54 lr: 4.5650479407200534e-05 loss: 0.0985 (0.1033) time: 3.6351 data: 0.0030 max mem: 19788 +Epoch: [3] [1820/2138] eta: 0:19:17 lr: 4.5645163966712875e-05 loss: 0.0930 (0.1034) time: 3.6375 data: 0.0031 max mem: 19788 +Epoch: [3] [1830/2138] eta: 0:18:41 lr: 4.563984845744764e-05 loss: 0.0933 (0.1033) time: 3.6354 data: 0.0033 max mem: 19788 +Epoch: [3] [1840/2138] eta: 0:18:04 lr: 4.5634532879395026e-05 loss: 0.0885 (0.1034) time: 3.6196 data: 0.0033 max mem: 19788 +Epoch: [3] [1850/2138] eta: 0:17:28 lr: 4.5629217232545266e-05 loss: 0.1045 (0.1035) time: 3.6271 data: 0.0030 max mem: 19788 +Epoch: [3] [1860/2138] eta: 0:16:52 lr: 4.562390151688855e-05 loss: 0.1084 (0.1036) time: 3.6326 data: 0.0029 max mem: 19788 +Epoch: [3] [1870/2138] eta: 0:16:15 lr: 4.561858573241508e-05 loss: 0.1036 (0.1036) time: 3.6316 data: 0.0030 max mem: 19788 +Epoch: [3] [1880/2138] eta: 0:15:39 lr: 4.561326987911505e-05 loss: 0.0950 (0.1036) time: 3.6338 data: 0.0032 max mem: 19788 +Epoch: [3] [1890/2138] eta: 0:15:02 lr: 4.560795395697867e-05 loss: 0.0808 (0.1034) time: 3.6375 data: 0.0033 max mem: 19788 +Epoch: [3] [1900/2138] eta: 0:14:26 lr: 4.560263796599613e-05 loss: 0.0778 (0.1033) time: 3.6338 data: 0.0030 max mem: 19788 +Epoch: [3] [1910/2138] eta: 0:13:49 lr: 4.559732190615761e-05 loss: 0.0801 (0.1032) time: 3.6329 data: 0.0028 max mem: 19788 +Epoch: [3] [1920/2138] eta: 0:13:13 lr: 4.55920057774533e-05 loss: 0.0872 (0.1032) time: 3.7681 data: 0.0029 max mem: 19788 +Epoch: [3] [1930/2138] eta: 0:12:37 lr: 4.55866895798734e-05 loss: 0.0944 (0.1032) time: 3.9023 data: 0.0030 max mem: 19788 +Epoch: [3] [1940/2138] eta: 0:12:01 lr: 4.5581373313408075e-05 loss: 0.0921 (0.1031) time: 3.8645 data: 0.0030 max mem: 19788 +Epoch: [3] [1950/2138] eta: 0:11:25 lr: 4.557605697804752e-05 loss: 0.0928 (0.1031) time: 3.7792 data: 0.0030 max mem: 19788 +Epoch: [3] [1960/2138] eta: 0:10:48 lr: 4.55707405737819e-05 loss: 0.0806 (0.1030) time: 3.6862 data: 0.0030 max mem: 19788 +Epoch: [3] [1970/2138] eta: 0:10:12 lr: 4.55654241006014e-05 loss: 0.0838 (0.1030) time: 3.6405 data: 0.0028 max mem: 19788 +Epoch: [3] [1980/2138] eta: 0:09:35 lr: 4.556010755849619e-05 loss: 0.0853 (0.1029) time: 3.6346 data: 0.0027 max mem: 19788 +Epoch: [3] [1990/2138] eta: 0:08:59 lr: 4.5554790947456434e-05 loss: 0.0866 (0.1029) time: 3.6303 data: 0.0028 max mem: 19788 +Epoch: [3] [2000/2138] eta: 0:08:22 lr: 4.55494742674723e-05 loss: 0.0989 (0.1029) time: 3.6825 data: 0.0030 max mem: 19788 +Epoch: [3] [2010/2138] eta: 0:07:46 lr: 4.554415751853396e-05 loss: 0.0899 (0.1029) time: 3.7733 data: 0.0031 max mem: 19788 +Epoch: [3] [2020/2138] eta: 0:07:10 lr: 4.553884070063157e-05 loss: 0.0880 (0.1028) time: 3.8619 data: 0.0032 max mem: 19788 +Epoch: [3] [2030/2138] eta: 0:06:33 lr: 4.553352381375528e-05 loss: 0.0840 (0.1028) time: 3.8739 data: 0.0032 max mem: 19788 +Epoch: [3] [2040/2138] eta: 0:05:57 lr: 4.552820685789527e-05 loss: 0.0881 (0.1028) time: 3.7572 data: 0.0032 max mem: 19788 +Epoch: [3] [2050/2138] eta: 0:05:21 lr: 4.552288983304166e-05 loss: 0.1107 (0.1028) time: 3.6575 data: 0.0033 max mem: 19788 +Epoch: [3] [2060/2138] eta: 0:04:44 lr: 4.5517572739184636e-05 loss: 0.0925 (0.1028) time: 3.6405 data: 0.0032 max mem: 19788 +Epoch: [3] [2070/2138] eta: 0:04:08 lr: 4.551225557631432e-05 loss: 0.0925 (0.1027) time: 3.6843 data: 0.0032 max mem: 19788 +Epoch: [3] [2080/2138] eta: 0:03:31 lr: 4.550693834442087e-05 loss: 0.0911 (0.1027) time: 3.8225 data: 0.0032 max mem: 19788 +Epoch: [3] [2090/2138] eta: 0:02:55 lr: 4.550162104349442e-05 loss: 0.0911 (0.1026) time: 3.9523 data: 0.0033 max mem: 19788 +Epoch: [3] [2100/2138] eta: 0:02:18 lr: 4.549630367352512e-05 loss: 0.0874 (0.1025) time: 3.9898 data: 0.0032 max mem: 19788 +Epoch: [3] [2110/2138] eta: 0:01:42 lr: 4.5490986234503095e-05 loss: 0.0971 (0.1027) time: 3.8218 data: 0.0032 max mem: 19788 +Epoch: [3] [2120/2138] eta: 0:01:05 lr: 4.5485668726418494e-05 loss: 0.1154 (0.1027) time: 3.6403 data: 0.0031 max mem: 19788 +Epoch: [3] [2130/2138] eta: 0:00:29 lr: 4.548035114926144e-05 loss: 0.1137 (0.1028) time: 3.6116 data: 0.0028 max mem: 19788 +Epoch: [3] Total time: 2:10:09 +Test: [ 0/21770] eta: 17:38:51 time: 2.9183 data: 2.5305 max mem: 19788 +Test: [ 100/21770] eta: 0:35:56 time: 0.0741 data: 0.0021 max mem: 19788 +Test: [ 200/21770] eta: 0:30:38 time: 0.0592 data: 0.0017 max mem: 19788 +Test: [ 300/21770] eta: 0:28:10 time: 0.0628 data: 0.0018 max mem: 19788 +Test: [ 400/21770] eta: 0:27:05 time: 0.0719 data: 0.0023 max mem: 19788 +Test: [ 500/21770] eta: 0:25:54 time: 0.0613 data: 0.0017 max mem: 19788 +Test: [ 600/21770] eta: 0:25:37 time: 0.0671 data: 0.0019 max mem: 19788 +Test: [ 700/21770] eta: 0:24:58 time: 0.0618 data: 0.0017 max mem: 19788 +Test: [ 800/21770] eta: 0:24:29 time: 0.0608 data: 0.0019 max mem: 19788 +Test: [ 900/21770] eta: 0:24:39 time: 0.0832 data: 0.0020 max mem: 19788 +Test: [ 1000/21770] eta: 0:24:50 time: 0.0798 data: 0.0022 max mem: 19788 +Test: [ 1100/21770] eta: 0:24:34 time: 0.0640 data: 0.0019 max mem: 19788 +Test: [ 1200/21770] eta: 0:24:16 time: 0.0724 data: 0.0020 max mem: 19788 +Test: [ 1300/21770] eta: 0:24:00 time: 0.0681 data: 0.0020 max mem: 19788 +Test: [ 1400/21770] eta: 0:23:48 time: 0.0611 data: 0.0019 max mem: 19788 +Test: [ 1500/21770] eta: 0:23:36 time: 0.0615 data: 0.0018 max mem: 19788 +Test: [ 1600/21770] eta: 0:23:18 time: 0.0633 data: 0.0019 max mem: 19788 +Test: [ 1700/21770] eta: 0:23:21 time: 0.0830 data: 0.0023 max mem: 19788 +Test: [ 1800/21770] eta: 0:23:11 time: 0.0619 data: 0.0018 max mem: 19788 +Test: [ 1900/21770] eta: 0:22:55 time: 0.0627 data: 0.0018 max mem: 19788 +Test: [ 2000/21770] eta: 0:22:40 time: 0.0612 data: 0.0019 max mem: 19788 +Test: [ 2100/21770] eta: 0:22:32 time: 0.0832 data: 0.0025 max mem: 19788 +Test: [ 2200/21770] eta: 0:22:27 time: 0.0620 data: 0.0018 max mem: 19788 +Test: [ 2300/21770] eta: 0:22:24 time: 0.0822 data: 0.0025 max mem: 19788 +Test: [ 2400/21770] eta: 0:22:27 time: 0.0823 data: 0.0025 max mem: 19788 +Test: [ 2500/21770] eta: 0:22:19 time: 0.0644 data: 0.0020 max mem: 19788 +Test: [ 2600/21770] eta: 0:22:20 time: 0.0841 data: 0.0021 max mem: 19788 +Test: [ 2700/21770] eta: 0:22:18 time: 0.0738 data: 0.0022 max mem: 19788 +Test: [ 2800/21770] eta: 0:22:06 time: 0.0620 data: 0.0021 max mem: 19788 +Test: [ 2900/21770] eta: 0:21:54 time: 0.0648 data: 0.0018 max mem: 19788 +Test: [ 3000/21770] eta: 0:21:44 time: 0.0639 data: 0.0018 max mem: 19788 +Test: [ 3100/21770] eta: 0:21:34 time: 0.0616 data: 0.0018 max mem: 19788 +Test: [ 3200/21770] eta: 0:21:28 time: 0.0690 data: 0.0019 max mem: 19788 +Test: [ 3300/21770] eta: 0:21:19 time: 0.0655 data: 0.0021 max mem: 19788 +Test: [ 3400/21770] eta: 0:21:13 time: 0.0735 data: 0.0025 max mem: 19788 +Test: [ 3500/21770] eta: 0:21:09 time: 0.0805 data: 0.0020 max mem: 19788 +Test: [ 3600/21770] eta: 0:21:05 time: 0.0789 data: 0.0023 max mem: 19788 +Test: [ 3700/21770] eta: 0:20:58 time: 0.0690 data: 0.0019 max mem: 19788 +Test: [ 3800/21770] eta: 0:20:52 time: 0.0820 data: 0.0025 max mem: 19788 +Test: [ 3900/21770] eta: 0:20:44 time: 0.0623 data: 0.0017 max mem: 19788 +Test: [ 4000/21770] eta: 0:20:34 time: 0.0639 data: 0.0019 max mem: 19788 +Test: [ 4100/21770] eta: 0:20:30 time: 0.0768 data: 0.0021 max mem: 19788 +Test: [ 4200/21770] eta: 0:20:23 time: 0.0598 data: 0.0016 max mem: 19788 +Test: [ 4300/21770] eta: 0:20:16 time: 0.0721 data: 0.0021 max mem: 19788 +Test: [ 4400/21770] eta: 0:20:11 time: 0.0796 data: 0.0020 max mem: 19788 +Test: [ 4500/21770] eta: 0:20:06 time: 0.0756 data: 0.0023 max mem: 19788 +Test: [ 4600/21770] eta: 0:20:00 time: 0.0828 data: 0.0018 max mem: 19788 +Test: [ 4700/21770] eta: 0:19:52 time: 0.0635 data: 0.0017 max mem: 19788 +Test: [ 4800/21770] eta: 0:19:43 time: 0.0767 data: 0.0022 max mem: 19788 +Test: [ 4900/21770] eta: 0:19:35 time: 0.0642 data: 0.0020 max mem: 19788 +Test: [ 5000/21770] eta: 0:19:28 time: 0.0665 data: 0.0019 max mem: 19788 +Test: [ 5100/21770] eta: 0:19:21 time: 0.0632 data: 0.0018 max mem: 19788 +Test: [ 5200/21770] eta: 0:19:15 time: 0.0803 data: 0.0024 max mem: 19788 +Test: [ 5300/21770] eta: 0:19:07 time: 0.0632 data: 0.0018 max mem: 19788 +Test: [ 5400/21770] eta: 0:18:59 time: 0.0621 data: 0.0021 max mem: 19788 +Test: [ 5500/21770] eta: 0:18:51 time: 0.0646 data: 0.0018 max mem: 19788 +Test: [ 5600/21770] eta: 0:18:43 time: 0.0716 data: 0.0022 max mem: 19788 +Test: [ 5700/21770] eta: 0:18:36 time: 0.0614 data: 0.0017 max mem: 19788 +Test: [ 5800/21770] eta: 0:18:28 time: 0.0704 data: 0.0021 max mem: 19788 +Test: [ 5900/21770] eta: 0:18:22 time: 0.0763 data: 0.0021 max mem: 19788 +Test: [ 6000/21770] eta: 0:18:17 time: 0.0754 data: 0.0019 max mem: 19788 +Test: [ 6100/21770] eta: 0:18:09 time: 0.0619 data: 0.0018 max mem: 19788 +Test: [ 6200/21770] eta: 0:18:02 time: 0.0648 data: 0.0020 max mem: 19788 +Test: [ 6300/21770] eta: 0:17:55 time: 0.0673 data: 0.0020 max mem: 19788 +Test: [ 6400/21770] eta: 0:17:48 time: 0.0619 data: 0.0019 max mem: 19788 +Test: [ 6500/21770] eta: 0:17:40 time: 0.0667 data: 0.0019 max mem: 19788 +Test: [ 6600/21770] eta: 0:17:34 time: 0.0817 data: 0.0022 max mem: 19788 +Test: [ 6700/21770] eta: 0:17:27 time: 0.0682 data: 0.0019 max mem: 19788 +Test: [ 6800/21770] eta: 0:17:21 time: 0.0635 data: 0.0020 max mem: 19788 +Test: [ 6900/21770] eta: 0:17:13 time: 0.0604 data: 0.0018 max mem: 19788 +Test: [ 7000/21770] eta: 0:17:05 time: 0.0739 data: 0.0019 max mem: 19788 +Test: [ 7100/21770] eta: 0:16:58 time: 0.0783 data: 0.0019 max mem: 19788 +Test: [ 7200/21770] eta: 0:16:51 time: 0.0817 data: 0.0025 max mem: 19788 +Test: [ 7300/21770] eta: 0:16:44 time: 0.0714 data: 0.0018 max mem: 19788 +Test: [ 7400/21770] eta: 0:16:38 time: 0.0786 data: 0.0024 max mem: 19788 +Test: [ 7500/21770] eta: 0:16:32 time: 0.0784 data: 0.0021 max mem: 19788 +Test: [ 7600/21770] eta: 0:16:26 time: 0.0720 data: 0.0019 max mem: 19788 +Test: [ 7700/21770] eta: 0:16:19 time: 0.0645 data: 0.0018 max mem: 19788 +Test: [ 7800/21770] eta: 0:16:12 time: 0.0753 data: 0.0022 max mem: 19788 +Test: [ 7900/21770] eta: 0:16:04 time: 0.0622 data: 0.0018 max mem: 19788 +Test: [ 8000/21770] eta: 0:15:57 time: 0.0711 data: 0.0021 max mem: 19788 +Test: [ 8100/21770] eta: 0:15:51 time: 0.0766 data: 0.0018 max mem: 19788 +Test: [ 8200/21770] eta: 0:15:44 time: 0.0801 data: 0.0020 max mem: 19788 +Test: [ 8300/21770] eta: 0:15:36 time: 0.0726 data: 0.0019 max mem: 19788 +Test: [ 8400/21770] eta: 0:15:29 time: 0.0773 data: 0.0021 max mem: 19788 +Test: [ 8500/21770] eta: 0:15:23 time: 0.0763 data: 0.0023 max mem: 19788 +Test: [ 8600/21770] eta: 0:15:15 time: 0.0639 data: 0.0019 max mem: 19788 +Test: [ 8700/21770] eta: 0:15:08 time: 0.0642 data: 0.0019 max mem: 19788 +Test: [ 8800/21770] eta: 0:15:02 time: 0.0608 data: 0.0018 max mem: 19788 +Test: [ 8900/21770] eta: 0:14:55 time: 0.0757 data: 0.0022 max mem: 19788 +Test: [ 9000/21770] eta: 0:14:49 time: 0.0683 data: 0.0020 max mem: 19788 +Test: [ 9100/21770] eta: 0:14:42 time: 0.0803 data: 0.0024 max mem: 19788 +Test: [ 9200/21770] eta: 0:14:35 time: 0.0709 data: 0.0020 max mem: 19788 +Test: [ 9300/21770] eta: 0:14:29 time: 0.0658 data: 0.0019 max mem: 19788 +Test: [ 9400/21770] eta: 0:14:21 time: 0.0592 data: 0.0016 max mem: 19788 +Test: [ 9500/21770] eta: 0:14:14 time: 0.0606 data: 0.0018 max mem: 19788 +Test: [ 9600/21770] eta: 0:14:08 time: 0.0816 data: 0.0024 max mem: 19788 +Test: [ 9700/21770] eta: 0:14:01 time: 0.0814 data: 0.0023 max mem: 19788 +Test: [ 9800/21770] eta: 0:13:54 time: 0.0785 data: 0.0022 max mem: 19788 +Test: [ 9900/21770] eta: 0:13:47 time: 0.0634 data: 0.0017 max mem: 19788 +Test: [10000/21770] eta: 0:13:40 time: 0.0682 data: 0.0022 max mem: 19788 +Test: [10100/21770] eta: 0:13:34 time: 0.0789 data: 0.0023 max mem: 19788 +Test: [10200/21770] eta: 0:13:27 time: 0.0789 data: 0.0023 max mem: 19788 +Test: [10300/21770] eta: 0:13:20 time: 0.0801 data: 0.0024 max mem: 19788 +Test: [10400/21770] eta: 0:13:14 time: 0.0827 data: 0.0020 max mem: 19788 +Test: [10500/21770] eta: 0:13:06 time: 0.0624 data: 0.0020 max mem: 19788 +Test: [10600/21770] eta: 0:12:59 time: 0.0654 data: 0.0017 max mem: 19788 +Test: [10700/21770] eta: 0:12:53 time: 0.0718 data: 0.0018 max mem: 19788 +Test: [10800/21770] eta: 0:12:46 time: 0.0736 data: 0.0020 max mem: 19788 +Test: [10900/21770] eta: 0:12:39 time: 0.0672 data: 0.0020 max mem: 19788 +Test: [11000/21770] eta: 0:12:32 time: 0.0782 data: 0.0023 max mem: 19788 +Test: [11100/21770] eta: 0:12:25 time: 0.0676 data: 0.0017 max mem: 19788 +Test: [11200/21770] eta: 0:12:18 time: 0.0675 data: 0.0021 max mem: 19788 +Test: [11300/21770] eta: 0:12:11 time: 0.0675 data: 0.0019 max mem: 19788 +Test: [11400/21770] eta: 0:12:03 time: 0.0749 data: 0.0021 max mem: 19788 +Test: [11500/21770] eta: 0:11:57 time: 0.0697 data: 0.0019 max mem: 19788 +Test: [11600/21770] eta: 0:11:51 time: 0.0704 data: 0.0017 max mem: 19788 +Test: [11700/21770] eta: 0:11:44 time: 0.0786 data: 0.0019 max mem: 19788 +Test: [11800/21770] eta: 0:11:37 time: 0.0701 data: 0.0020 max mem: 19788 +Test: [11900/21770] eta: 0:11:30 time: 0.0619 data: 0.0017 max mem: 19788 +Test: [12000/21770] eta: 0:11:23 time: 0.0809 data: 0.0024 max mem: 19788 +Test: [12100/21770] eta: 0:11:16 time: 0.0634 data: 0.0018 max mem: 19788 +Test: [12200/21770] eta: 0:11:09 time: 0.0654 data: 0.0018 max mem: 19788 +Test: [12300/21770] eta: 0:11:02 time: 0.0772 data: 0.0020 max mem: 19788 +Test: [12400/21770] eta: 0:10:54 time: 0.0629 data: 0.0018 max mem: 19788 +Test: [12500/21770] eta: 0:10:47 time: 0.0664 data: 0.0017 max mem: 19788 +Test: [12600/21770] eta: 0:10:40 time: 0.0723 data: 0.0020 max mem: 19788 +Test: [12700/21770] eta: 0:10:33 time: 0.0614 data: 0.0018 max mem: 19788 +Test: [12800/21770] eta: 0:10:26 time: 0.0614 data: 0.0019 max mem: 19788 +Test: [12900/21770] eta: 0:10:19 time: 0.0632 data: 0.0017 max mem: 19788 +Test: [13000/21770] eta: 0:10:12 time: 0.0606 data: 0.0018 max mem: 19788 +Test: [13100/21770] eta: 0:10:05 time: 0.0629 data: 0.0018 max mem: 19788 +Test: [13200/21770] eta: 0:09:58 time: 0.0613 data: 0.0018 max mem: 19788 +Test: [13300/21770] eta: 0:09:50 time: 0.0608 data: 0.0017 max mem: 19788 +Test: [13400/21770] eta: 0:09:43 time: 0.0705 data: 0.0019 max mem: 19788 +Test: [13500/21770] eta: 0:09:36 time: 0.0685 data: 0.0019 max mem: 19788 +Test: [13600/21770] eta: 0:09:29 time: 0.0687 data: 0.0022 max mem: 19788 +Test: [13700/21770] eta: 0:09:22 time: 0.0747 data: 0.0020 max mem: 19788 +Test: [13800/21770] eta: 0:09:15 time: 0.0814 data: 0.0024 max mem: 19788 +Test: [13900/21770] eta: 0:09:08 time: 0.0593 data: 0.0017 max mem: 19788 +Test: [14000/21770] eta: 0:09:01 time: 0.0654 data: 0.0020 max mem: 19788 +Test: [14100/21770] eta: 0:08:54 time: 0.0734 data: 0.0023 max mem: 19788 +Test: [14200/21770] eta: 0:08:47 time: 0.0642 data: 0.0020 max mem: 19788 +Test: [14300/21770] eta: 0:08:40 time: 0.0815 data: 0.0025 max mem: 19788 +Test: [14400/21770] eta: 0:08:33 time: 0.0771 data: 0.0019 max mem: 19788 +Test: [14500/21770] eta: 0:08:26 time: 0.0652 data: 0.0019 max mem: 19788 +Test: [14600/21770] eta: 0:08:19 time: 0.0601 data: 0.0018 max mem: 19788 +Test: [14700/21770] eta: 0:08:12 time: 0.0645 data: 0.0018 max mem: 19788 +Test: [14800/21770] eta: 0:08:05 time: 0.0621 data: 0.0020 max mem: 19788 +Test: [14900/21770] eta: 0:07:58 time: 0.0812 data: 0.0024 max mem: 19788 +Test: [15000/21770] eta: 0:07:51 time: 0.0801 data: 0.0025 max mem: 19788 +Test: [15100/21770] eta: 0:07:44 time: 0.0647 data: 0.0017 max mem: 19788 +Test: [15200/21770] eta: 0:07:37 time: 0.0627 data: 0.0017 max mem: 19788 +Test: [15300/21770] eta: 0:07:30 time: 0.0798 data: 0.0023 max mem: 19788 +Test: [15400/21770] eta: 0:07:22 time: 0.0619 data: 0.0018 max mem: 19788 +Test: [15500/21770] eta: 0:07:15 time: 0.0625 data: 0.0019 max mem: 19788 +Test: [15600/21770] eta: 0:07:08 time: 0.0621 data: 0.0018 max mem: 19788 +Test: [15700/21770] eta: 0:07:01 time: 0.0727 data: 0.0019 max mem: 19788 +Test: [15800/21770] eta: 0:06:54 time: 0.0810 data: 0.0024 max mem: 19788 +Test: [15900/21770] eta: 0:06:47 time: 0.0624 data: 0.0017 max mem: 19788 +Test: [16000/21770] eta: 0:06:40 time: 0.0680 data: 0.0020 max mem: 19788 +Test: [16100/21770] eta: 0:06:33 time: 0.0624 data: 0.0017 max mem: 19788 +Test: [16200/21770] eta: 0:06:26 time: 0.0617 data: 0.0020 max mem: 19788 +Test: [16300/21770] eta: 0:06:19 time: 0.0741 data: 0.0020 max mem: 19788 +Test: [16400/21770] eta: 0:06:12 time: 0.0734 data: 0.0022 max mem: 19788 +Test: [16500/21770] eta: 0:06:05 time: 0.0614 data: 0.0017 max mem: 19788 +Test: [16600/21770] eta: 0:05:58 time: 0.0824 data: 0.0025 max mem: 19788 +Test: [16700/21770] eta: 0:05:51 time: 0.0609 data: 0.0017 max mem: 19788 +Test: [16800/21770] eta: 0:05:44 time: 0.0726 data: 0.0019 max mem: 19788 +Test: [16900/21770] eta: 0:05:37 time: 0.0612 data: 0.0017 max mem: 19788 +Test: [17000/21770] eta: 0:05:31 time: 0.0620 data: 0.0018 max mem: 19788 +Test: [17100/21770] eta: 0:05:23 time: 0.0656 data: 0.0018 max mem: 19788 +Test: [17200/21770] eta: 0:05:16 time: 0.0791 data: 0.0023 max mem: 19788 +Test: [17300/21770] eta: 0:05:10 time: 0.0608 data: 0.0020 max mem: 19788 +Test: [17400/21770] eta: 0:05:03 time: 0.0722 data: 0.0021 max mem: 19788 +Test: [17500/21770] eta: 0:04:56 time: 0.0755 data: 0.0022 max mem: 19788 +Test: [17600/21770] eta: 0:04:49 time: 0.0749 data: 0.0021 max mem: 19788 +Test: [17700/21770] eta: 0:04:42 time: 0.0714 data: 0.0022 max mem: 19788 +Test: [17800/21770] eta: 0:04:35 time: 0.0659 data: 0.0018 max mem: 19788 +Test: [17900/21770] eta: 0:04:28 time: 0.0693 data: 0.0021 max mem: 19788 +Test: [18000/21770] eta: 0:04:21 time: 0.0659 data: 0.0020 max mem: 19788 +Test: [18100/21770] eta: 0:04:14 time: 0.0700 data: 0.0020 max mem: 19788 +Test: [18200/21770] eta: 0:04:07 time: 0.0761 data: 0.0019 max mem: 19788 +Test: [18300/21770] eta: 0:04:00 time: 0.0653 data: 0.0019 max mem: 19788 +Test: [18400/21770] eta: 0:03:53 time: 0.0719 data: 0.0021 max mem: 19788 +Test: [18500/21770] eta: 0:03:46 time: 0.0755 data: 0.0022 max mem: 19788 +Test: [18600/21770] eta: 0:03:39 time: 0.0700 data: 0.0021 max mem: 19788 +Test: [18700/21770] eta: 0:03:32 time: 0.0650 data: 0.0018 max mem: 19788 +Test: [18800/21770] eta: 0:03:25 time: 0.0686 data: 0.0021 max mem: 19788 +Test: [18900/21770] eta: 0:03:19 time: 0.0609 data: 0.0018 max mem: 19788 +Test: [19000/21770] eta: 0:03:12 time: 0.0660 data: 0.0020 max mem: 19788 +Test: [19100/21770] eta: 0:03:05 time: 0.0688 data: 0.0022 max mem: 19788 +Test: [19200/21770] eta: 0:02:58 time: 0.0623 data: 0.0018 max mem: 19788 +Test: [19300/21770] eta: 0:02:51 time: 0.0624 data: 0.0017 max mem: 19788 +Test: [19400/21770] eta: 0:02:44 time: 0.0817 data: 0.0025 max mem: 19788 +Test: [19500/21770] eta: 0:02:37 time: 0.0713 data: 0.0021 max mem: 19788 +Test: [19600/21770] eta: 0:02:30 time: 0.0620 data: 0.0019 max mem: 19788 +Test: [19700/21770] eta: 0:02:23 time: 0.0605 data: 0.0019 max mem: 19788 +Test: [19800/21770] eta: 0:02:16 time: 0.0733 data: 0.0019 max mem: 19788 +Test: [19900/21770] eta: 0:02:09 time: 0.0727 data: 0.0023 max mem: 19788 +Test: [20000/21770] eta: 0:02:02 time: 0.0697 data: 0.0021 max mem: 19788 +Test: [20100/21770] eta: 0:01:55 time: 0.0621 data: 0.0020 max mem: 19788 +Test: [20200/21770] eta: 0:01:48 time: 0.0823 data: 0.0024 max mem: 19788 +Test: [20300/21770] eta: 0:01:41 time: 0.0702 data: 0.0023 max mem: 19788 +Test: [20400/21770] eta: 0:01:34 time: 0.0648 data: 0.0019 max mem: 19788 +Test: [20500/21770] eta: 0:01:28 time: 0.0646 data: 0.0019 max mem: 19788 +Test: [20600/21770] eta: 0:01:21 time: 0.0615 data: 0.0018 max mem: 19788 +Test: [20700/21770] eta: 0:01:14 time: 0.0782 data: 0.0023 max mem: 19788 +Test: [20800/21770] eta: 0:01:07 time: 0.0657 data: 0.0019 max mem: 19788 +Test: [20900/21770] eta: 0:01:00 time: 0.0808 data: 0.0023 max mem: 19788 +Test: [21000/21770] eta: 0:00:53 time: 0.0766 data: 0.0024 max mem: 19788 +Test: [21100/21770] eta: 0:00:46 time: 0.0639 data: 0.0017 max mem: 19788 +Test: [21200/21770] eta: 0:00:39 time: 0.0622 data: 0.0018 max mem: 19788 +Test: [21300/21770] eta: 0:00:32 time: 0.0680 data: 0.0018 max mem: 19788 +Test: [21400/21770] eta: 0:00:25 time: 0.0633 data: 0.0019 max mem: 19788 +Test: [21500/21770] eta: 0:00:18 time: 0.0633 data: 0.0019 max mem: 19788 +Test: [21600/21770] eta: 0:00:11 time: 0.0579 data: 0.0019 max mem: 19788 +Test: [21700/21770] eta: 0:00:04 time: 0.0547 data: 0.0017 max mem: 19788 +Test: Total time: 0:25:09 +Final results: +Mean IoU is 56.60 + + precision@0.5 = 62.63 + precision@0.6 = 56.48 + precision@0.7 = 48.69 + precision@0.8 = 37.40 + precision@0.9 = 16.62 + overall IoU = 59.74 + mean IoU = 56.60 + +Mean accuracy for one-to-zero sample is 79.59 + +Average object IoU 0.5659720136851341 +Overall IoU 59.74282455444336 +Better epoch: 3 + +Epoch: [4] [ 0/2138] eta: 3:18:09 lr: 4.5476097037797e-05 loss: 0.1110 (0.1110) time: 5.5611 data: 1.5249 max mem: 19788 +Epoch: [4] [ 10/2138] eta: 2:15:32 lr: 4.5470779336284665e-05 loss: 0.0787 (0.0857) time: 3.8217 data: 0.1418 max mem: 19788 +Epoch: [4] [ 20/2138] eta: 2:11:54 lr: 4.546546156567223e-05 loss: 0.0683 (0.0755) time: 3.6454 data: 0.0026 max mem: 19788 +Epoch: [4] [ 30/2138] eta: 2:10:10 lr: 4.546014372594982e-05 loss: 0.0670 (0.0782) time: 3.6410 data: 0.0023 max mem: 19788 +Epoch: [4] [ 40/2138] eta: 2:09:07 lr: 4.545482581710754e-05 loss: 0.0726 (0.0786) time: 3.6463 data: 0.0031 max mem: 19788 +Epoch: [4] [ 50/2138] eta: 2:08:10 lr: 4.544950783913554e-05 loss: 0.0759 (0.0833) time: 3.6496 data: 0.0033 max mem: 19788 +Epoch: [4] [ 60/2138] eta: 2:07:20 lr: 4.5444189792023915e-05 loss: 0.0812 (0.0828) time: 3.6452 data: 0.0032 max mem: 19788 +Epoch: [4] [ 70/2138] eta: 2:06:35 lr: 4.543887167576277e-05 loss: 0.0734 (0.0809) time: 3.6463 data: 0.0031 max mem: 19788 +Epoch: [4] [ 80/2138] eta: 2:05:52 lr: 4.543355349034222e-05 loss: 0.0773 (0.0839) time: 3.6478 data: 0.0031 max mem: 19788 +Epoch: [4] [ 90/2138] eta: 2:05:10 lr: 4.5428235235752365e-05 loss: 0.0911 (0.0861) time: 3.6479 data: 0.0032 max mem: 19788 +Epoch: [4] [ 100/2138] eta: 2:04:30 lr: 4.5422916911983324e-05 loss: 0.0800 (0.0853) time: 3.6488 data: 0.0034 max mem: 19788 +Epoch: [4] [ 110/2138] eta: 2:03:48 lr: 4.541759851902517e-05 loss: 0.0800 (0.0862) time: 3.6441 data: 0.0032 max mem: 19788 +Epoch: [4] [ 120/2138] eta: 2:03:06 lr: 4.541228005686802e-05 loss: 0.0838 (0.0858) time: 3.6342 data: 0.0030 max mem: 19788 +Epoch: [4] [ 130/2138] eta: 2:02:27 lr: 4.5406961525501965e-05 loss: 0.0838 (0.0870) time: 3.6366 data: 0.0031 max mem: 19788 +Epoch: [4] [ 140/2138] eta: 2:01:49 lr: 4.54016429249171e-05 loss: 0.0870 (0.0872) time: 3.6464 data: 0.0031 max mem: 19788 +Epoch: [4] [ 150/2138] eta: 2:01:10 lr: 4.539632425510351e-05 loss: 0.0778 (0.0869) time: 3.6461 data: 0.0031 max mem: 19788 +Epoch: [4] [ 160/2138] eta: 2:00:33 lr: 4.5391005516051286e-05 loss: 0.0843 (0.0875) time: 3.6457 data: 0.0030 max mem: 19788 +Epoch: [4] [ 170/2138] eta: 1:59:56 lr: 4.53856867077505e-05 loss: 0.0878 (0.0875) time: 3.6511 data: 0.0030 max mem: 19788 +Epoch: [4] [ 180/2138] eta: 1:59:18 lr: 4.538036783019124e-05 loss: 0.0871 (0.0880) time: 3.6510 data: 0.0032 max mem: 19788 +Epoch: [4] [ 190/2138] eta: 1:58:40 lr: 4.537504888336359e-05 loss: 0.0879 (0.0882) time: 3.6453 data: 0.0030 max mem: 19788 +Epoch: [4] [ 200/2138] eta: 1:58:03 lr: 4.536972986725763e-05 loss: 0.0785 (0.0879) time: 3.6423 data: 0.0030 max mem: 19788 +Epoch: [4] [ 210/2138] eta: 1:57:24 lr: 4.53644107818634e-05 loss: 0.0785 (0.0884) time: 3.6368 data: 0.0032 max mem: 19788 +Epoch: [4] [ 220/2138] eta: 1:56:45 lr: 4.535909162717102e-05 loss: 0.0792 (0.0880) time: 3.6299 data: 0.0034 max mem: 19788 +Epoch: [4] [ 230/2138] eta: 1:56:08 lr: 4.5353772403170515e-05 loss: 0.0792 (0.0884) time: 3.6397 data: 0.0034 max mem: 19788 +Epoch: [4] [ 240/2138] eta: 1:55:31 lr: 4.534845310985198e-05 loss: 0.0898 (0.0884) time: 3.6484 data: 0.0032 max mem: 19788 +Epoch: [4] [ 250/2138] eta: 1:54:55 lr: 4.534313374720545e-05 loss: 0.0898 (0.0885) time: 3.6491 data: 0.0031 max mem: 19788 +Epoch: [4] [ 260/2138] eta: 1:54:18 lr: 4.533781431522101e-05 loss: 0.0772 (0.0882) time: 3.6484 data: 0.0031 max mem: 19788 +Epoch: [4] [ 270/2138] eta: 1:53:41 lr: 4.53324948138887e-05 loss: 0.0808 (0.0888) time: 3.6484 data: 0.0029 max mem: 19788 +Epoch: [4] [ 280/2138] eta: 1:53:04 lr: 4.5327175243198575e-05 loss: 0.0851 (0.0890) time: 3.6490 data: 0.0029 max mem: 19788 +Epoch: [4] [ 290/2138] eta: 1:52:27 lr: 4.5321855603140694e-05 loss: 0.0721 (0.0885) time: 3.6452 data: 0.0029 max mem: 19788 +Epoch: [4] [ 300/2138] eta: 1:51:50 lr: 4.531653589370511e-05 loss: 0.0748 (0.0882) time: 3.6419 data: 0.0031 max mem: 19788 +Epoch: [4] [ 310/2138] eta: 1:51:12 lr: 4.531121611488185e-05 loss: 0.0792 (0.0879) time: 3.6339 data: 0.0032 max mem: 19788 +Epoch: [4] [ 320/2138] eta: 1:50:35 lr: 4.5305896266660966e-05 loss: 0.0792 (0.0878) time: 3.6348 data: 0.0030 max mem: 19788 +Epoch: [4] [ 330/2138] eta: 1:49:59 lr: 4.5300576349032515e-05 loss: 0.0968 (0.0880) time: 3.6452 data: 0.0027 max mem: 19788 +Epoch: [4] [ 340/2138] eta: 1:49:22 lr: 4.52952563619865e-05 loss: 0.0892 (0.0881) time: 3.6460 data: 0.0030 max mem: 19788 +Epoch: [4] [ 350/2138] eta: 1:48:45 lr: 4.5289936305512987e-05 loss: 0.0831 (0.0882) time: 3.6439 data: 0.0031 max mem: 19788 +Epoch: [4] [ 360/2138] eta: 1:48:09 lr: 4.5284616179601994e-05 loss: 0.0828 (0.0885) time: 3.6482 data: 0.0030 max mem: 19788 +Epoch: [4] [ 370/2138] eta: 1:47:32 lr: 4.5279295984243555e-05 loss: 0.0974 (0.0889) time: 3.6488 data: 0.0034 max mem: 19788 +Epoch: [4] [ 380/2138] eta: 1:46:56 lr: 4.527397571942769e-05 loss: 0.0829 (0.0888) time: 3.6481 data: 0.0034 max mem: 19788 +Epoch: [4] [ 390/2138] eta: 1:46:19 lr: 4.526865538514444e-05 loss: 0.0829 (0.0889) time: 3.6460 data: 0.0030 max mem: 19788 +Epoch: [4] [ 400/2138] eta: 1:45:42 lr: 4.52633349813838e-05 loss: 0.0911 (0.0891) time: 3.6392 data: 0.0030 max mem: 19788 +Epoch: [4] [ 410/2138] eta: 1:45:04 lr: 4.52580145081358e-05 loss: 0.0883 (0.0891) time: 3.6330 data: 0.0029 max mem: 19788 +Epoch: [4] [ 420/2138] eta: 1:44:27 lr: 4.525269396539047e-05 loss: 0.0860 (0.0889) time: 3.6340 data: 0.0032 max mem: 19788 +Epoch: [4] [ 430/2138] eta: 1:43:51 lr: 4.52473733531378e-05 loss: 0.0838 (0.0890) time: 3.6442 data: 0.0035 max mem: 19788 +Epoch: [4] [ 440/2138] eta: 1:43:15 lr: 4.524205267136782e-05 loss: 0.0895 (0.0892) time: 3.6500 data: 0.0032 max mem: 19788 +Epoch: [4] [ 450/2138] eta: 1:42:38 lr: 4.523673192007053e-05 loss: 0.0814 (0.0892) time: 3.6488 data: 0.0030 max mem: 19788 +Epoch: [4] [ 460/2138] eta: 1:42:02 lr: 4.5231411099235926e-05 loss: 0.0811 (0.0893) time: 3.6491 data: 0.0030 max mem: 19788 +Epoch: [4] [ 470/2138] eta: 1:41:25 lr: 4.522609020885402e-05 loss: 0.0882 (0.0893) time: 3.6521 data: 0.0030 max mem: 19788 +Epoch: [4] [ 480/2138] eta: 1:40:49 lr: 4.522076924891481e-05 loss: 0.0793 (0.0893) time: 3.6525 data: 0.0031 max mem: 19788 +Epoch: [4] [ 490/2138] eta: 1:40:12 lr: 4.521544821940829e-05 loss: 0.0763 (0.0892) time: 3.6470 data: 0.0032 max mem: 19788 +Epoch: [4] [ 500/2138] eta: 1:39:35 lr: 4.5210127120324455e-05 loss: 0.0790 (0.0894) time: 3.6380 data: 0.0033 max mem: 19788 +Epoch: [4] [ 510/2138] eta: 1:38:58 lr: 4.52048059516533e-05 loss: 0.0790 (0.0892) time: 3.6325 data: 0.0034 max mem: 19788 +Epoch: [4] [ 520/2138] eta: 1:38:22 lr: 4.5199484713384805e-05 loss: 0.0860 (0.0896) time: 3.6402 data: 0.0033 max mem: 19788 +Epoch: [4] [ 530/2138] eta: 1:37:45 lr: 4.519416340550896e-05 loss: 0.0882 (0.0899) time: 3.6338 data: 0.0031 max mem: 19788 +Epoch: [4] [ 540/2138] eta: 1:37:08 lr: 4.518884202801575e-05 loss: 0.0930 (0.0899) time: 3.6264 data: 0.0030 max mem: 19788 +Epoch: [4] [ 550/2138] eta: 1:36:31 lr: 4.5183520580895155e-05 loss: 0.0796 (0.0896) time: 3.6368 data: 0.0029 max mem: 19788 +Epoch: [4] [ 560/2138] eta: 1:35:54 lr: 4.517819906413714e-05 loss: 0.0772 (0.0895) time: 3.6362 data: 0.0031 max mem: 19788 +Epoch: [4] [ 570/2138] eta: 1:35:17 lr: 4.51728774777317e-05 loss: 0.0911 (0.0898) time: 3.6346 data: 0.0031 max mem: 19788 +Epoch: [4] [ 580/2138] eta: 1:34:41 lr: 4.51675558216688e-05 loss: 0.0982 (0.0899) time: 3.6353 data: 0.0028 max mem: 19788 +Epoch: [4] [ 590/2138] eta: 1:34:04 lr: 4.516223409593839e-05 loss: 0.0850 (0.0898) time: 3.6456 data: 0.0027 max mem: 19788 +Epoch: [4] [ 600/2138] eta: 1:33:28 lr: 4.5156912300530455e-05 loss: 0.0911 (0.0900) time: 3.6467 data: 0.0028 max mem: 19788 +Epoch: [4] [ 610/2138] eta: 1:32:51 lr: 4.515159043543497e-05 loss: 0.0783 (0.0897) time: 3.6346 data: 0.0029 max mem: 19788 +Epoch: [4] [ 620/2138] eta: 1:32:15 lr: 4.5146268500641864e-05 loss: 0.0757 (0.0896) time: 3.6481 data: 0.0027 max mem: 19788 +Epoch: [4] [ 630/2138] eta: 1:31:38 lr: 4.5140946496141125e-05 loss: 0.0889 (0.0896) time: 3.6490 data: 0.0027 max mem: 19788 +Epoch: [4] [ 640/2138] eta: 1:31:01 lr: 4.513562442192269e-05 loss: 0.0908 (0.0897) time: 3.6337 data: 0.0028 max mem: 19788 +Epoch: [4] [ 650/2138] eta: 1:30:24 lr: 4.513030227797651e-05 loss: 0.0752 (0.0894) time: 3.6329 data: 0.0030 max mem: 19788 +Epoch: [4] [ 660/2138] eta: 1:29:48 lr: 4.512498006429254e-05 loss: 0.0752 (0.0894) time: 3.6314 data: 0.0031 max mem: 19788 +Epoch: [4] [ 670/2138] eta: 1:29:11 lr: 4.511965778086074e-05 loss: 0.0887 (0.0892) time: 3.6308 data: 0.0032 max mem: 19788 +Epoch: [4] [ 680/2138] eta: 1:28:34 lr: 4.511433542767104e-05 loss: 0.0762 (0.0891) time: 3.6365 data: 0.0032 max mem: 19788 +Epoch: [4] [ 690/2138] eta: 1:27:58 lr: 4.510901300471338e-05 loss: 0.0857 (0.0892) time: 3.6376 data: 0.0031 max mem: 19788 +Epoch: [4] [ 700/2138] eta: 1:27:21 lr: 4.51036905119777e-05 loss: 0.0929 (0.0894) time: 3.6314 data: 0.0030 max mem: 19788 +Epoch: [4] [ 710/2138] eta: 1:26:44 lr: 4.509836794945394e-05 loss: 0.0859 (0.0895) time: 3.6254 data: 0.0033 max mem: 19788 +Epoch: [4] [ 720/2138] eta: 1:26:07 lr: 4.5093045317132036e-05 loss: 0.0863 (0.0896) time: 3.6211 data: 0.0031 max mem: 19788 +Epoch: [4] [ 730/2138] eta: 1:25:30 lr: 4.5087722615001904e-05 loss: 0.0889 (0.0896) time: 3.6251 data: 0.0030 max mem: 19788 +Epoch: [4] [ 740/2138] eta: 1:24:54 lr: 4.508239984305349e-05 loss: 0.0778 (0.0895) time: 3.6268 data: 0.0031 max mem: 19788 +Epoch: [4] [ 750/2138] eta: 1:24:17 lr: 4.50770770012767e-05 loss: 0.0726 (0.0893) time: 3.6226 data: 0.0029 max mem: 19788 +Epoch: [4] [ 760/2138] eta: 1:23:40 lr: 4.507175408966148e-05 loss: 0.0822 (0.0893) time: 3.6276 data: 0.0028 max mem: 19788 +Epoch: [4] [ 770/2138] eta: 1:23:03 lr: 4.506643110819772e-05 loss: 0.0824 (0.0892) time: 3.6276 data: 0.0030 max mem: 19788 +Epoch: [4] [ 780/2138] eta: 1:22:26 lr: 4.506110805687536e-05 loss: 0.0748 (0.0892) time: 3.6211 data: 0.0031 max mem: 19788 +Epoch: [4] [ 790/2138] eta: 1:21:50 lr: 4.5055784935684296e-05 loss: 0.0898 (0.0896) time: 3.6209 data: 0.0029 max mem: 19788 +Epoch: [4] [ 800/2138] eta: 1:21:13 lr: 4.505046174461446e-05 loss: 0.0884 (0.0895) time: 3.6261 data: 0.0028 max mem: 19788 +Epoch: [4] [ 810/2138] eta: 1:20:36 lr: 4.504513848365574e-05 loss: 0.0749 (0.0893) time: 3.6243 data: 0.0028 max mem: 19788 +Epoch: [4] [ 820/2138] eta: 1:20:00 lr: 4.503981515279805e-05 loss: 0.0754 (0.0892) time: 3.6264 data: 0.0029 max mem: 19788 +Epoch: [4] [ 830/2138] eta: 1:19:23 lr: 4.5034491752031296e-05 loss: 0.0751 (0.0892) time: 3.6310 data: 0.0029 max mem: 19788 +Epoch: [4] [ 840/2138] eta: 1:18:46 lr: 4.5029168281345366e-05 loss: 0.0751 (0.0890) time: 3.6261 data: 0.0029 max mem: 19788 +Epoch: [4] [ 850/2138] eta: 1:18:10 lr: 4.502384474073017e-05 loss: 0.0764 (0.0890) time: 3.6224 data: 0.0027 max mem: 19788 +Epoch: [4] [ 860/2138] eta: 1:17:33 lr: 4.5018521130175595e-05 loss: 0.0764 (0.0889) time: 3.6221 data: 0.0025 max mem: 19788 +Epoch: [4] [ 870/2138] eta: 1:16:56 lr: 4.501319744967153e-05 loss: 0.0725 (0.0887) time: 3.6313 data: 0.0029 max mem: 19788 +Epoch: [4] [ 880/2138] eta: 1:16:20 lr: 4.5007873699207876e-05 loss: 0.0753 (0.0886) time: 3.6539 data: 0.0038 max mem: 19788 +Epoch: [4] [ 890/2138] eta: 1:15:44 lr: 4.50025498787745e-05 loss: 0.0753 (0.0886) time: 3.6467 data: 0.0036 max mem: 19788 +Epoch: [4] [ 900/2138] eta: 1:15:07 lr: 4.499722598836131e-05 loss: 0.0922 (0.0888) time: 3.6240 data: 0.0029 max mem: 19788 +Epoch: [4] [ 910/2138] eta: 1:14:31 lr: 4.499190202795816e-05 loss: 0.0749 (0.0888) time: 3.6312 data: 0.0028 max mem: 19788 +Epoch: [4] [ 920/2138] eta: 1:13:54 lr: 4.498657799755494e-05 loss: 0.0718 (0.0888) time: 3.6356 data: 0.0028 max mem: 19788 +Epoch: [4] [ 930/2138] eta: 1:13:18 lr: 4.498125389714152e-05 loss: 0.0767 (0.0887) time: 3.6307 data: 0.0029 max mem: 19788 +Epoch: [4] [ 940/2138] eta: 1:12:41 lr: 4.497592972670778e-05 loss: 0.0879 (0.0887) time: 3.6271 data: 0.0027 max mem: 19788 +Epoch: [4] [ 950/2138] eta: 1:12:05 lr: 4.4970605486243586e-05 loss: 0.0835 (0.0887) time: 3.6417 data: 0.0027 max mem: 19788 +Epoch: [4] [ 960/2138] eta: 1:11:28 lr: 4.49652811757388e-05 loss: 0.0835 (0.0887) time: 3.6461 data: 0.0027 max mem: 19788 +Epoch: [4] [ 970/2138] eta: 1:10:52 lr: 4.4959956795183285e-05 loss: 0.0817 (0.0884) time: 3.6329 data: 0.0028 max mem: 19788 +Epoch: [4] [ 980/2138] eta: 1:10:15 lr: 4.49546323445669e-05 loss: 0.0725 (0.0884) time: 3.6366 data: 0.0029 max mem: 19788 +Epoch: [4] [ 990/2138] eta: 1:09:39 lr: 4.4949307823879524e-05 loss: 0.0823 (0.0883) time: 3.6423 data: 0.0030 max mem: 19788 +Epoch: [4] [1000/2138] eta: 1:09:02 lr: 4.4943983233110984e-05 loss: 0.0784 (0.0882) time: 3.6362 data: 0.0029 max mem: 19788 +Epoch: [4] [1010/2138] eta: 1:08:26 lr: 4.4938658572251145e-05 loss: 0.0739 (0.0881) time: 3.6408 data: 0.0028 max mem: 19788 +Epoch: [4] [1020/2138] eta: 1:07:50 lr: 4.4933333841289856e-05 loss: 0.0739 (0.0880) time: 3.6445 data: 0.0029 max mem: 19788 +Epoch: [4] [1030/2138] eta: 1:07:13 lr: 4.492800904021696e-05 loss: 0.0707 (0.0878) time: 3.6307 data: 0.0031 max mem: 19788 +Epoch: [4] [1040/2138] eta: 1:06:37 lr: 4.49226841690223e-05 loss: 0.0869 (0.0880) time: 3.6266 data: 0.0030 max mem: 19788 +Epoch: [4] [1050/2138] eta: 1:06:00 lr: 4.491735922769573e-05 loss: 0.0869 (0.0879) time: 3.6335 data: 0.0027 max mem: 19788 +Epoch: [4] [1060/2138] eta: 1:05:24 lr: 4.491203421622707e-05 loss: 0.0690 (0.0877) time: 3.6267 data: 0.0027 max mem: 19788 +Epoch: [4] [1070/2138] eta: 1:04:47 lr: 4.4906709134606166e-05 loss: 0.0690 (0.0876) time: 3.6239 data: 0.0028 max mem: 19788 +Epoch: [4] [1080/2138] eta: 1:04:11 lr: 4.490138398282285e-05 loss: 0.0707 (0.0875) time: 3.6302 data: 0.0027 max mem: 19788 +Epoch: [4] [1090/2138] eta: 1:03:34 lr: 4.489605876086695e-05 loss: 0.0720 (0.0875) time: 3.6282 data: 0.0026 max mem: 19788 +Epoch: [4] [1100/2138] eta: 1:02:58 lr: 4.4890733468728284e-05 loss: 0.0744 (0.0874) time: 3.6321 data: 0.0028 max mem: 19788 +Epoch: [4] [1110/2138] eta: 1:02:21 lr: 4.48854081063967e-05 loss: 0.0733 (0.0874) time: 3.6353 data: 0.0033 max mem: 19788 +Epoch: [4] [1120/2138] eta: 1:01:45 lr: 4.488008267386199e-05 loss: 0.0811 (0.0876) time: 3.6441 data: 0.0036 max mem: 19788 +Epoch: [4] [1130/2138] eta: 1:01:08 lr: 4.487475717111399e-05 loss: 0.0903 (0.0876) time: 3.6364 data: 0.0033 max mem: 19788 +Epoch: [4] [1140/2138] eta: 1:00:32 lr: 4.486943159814252e-05 loss: 0.0895 (0.0878) time: 3.6195 data: 0.0030 max mem: 19788 +Epoch: [4] [1150/2138] eta: 0:59:55 lr: 4.486410595493738e-05 loss: 0.0722 (0.0876) time: 3.6288 data: 0.0029 max mem: 19788 +Epoch: [4] [1160/2138] eta: 0:59:19 lr: 4.4858780241488385e-05 loss: 0.0617 (0.0875) time: 3.6321 data: 0.0030 max mem: 19788 +Epoch: [4] [1170/2138] eta: 0:58:42 lr: 4.485345445778535e-05 loss: 0.0745 (0.0874) time: 3.6256 data: 0.0030 max mem: 19788 +Epoch: [4] [1180/2138] eta: 0:58:06 lr: 4.484812860381806e-05 loss: 0.0892 (0.0876) time: 3.6322 data: 0.0029 max mem: 19788 +Epoch: [4] [1190/2138] eta: 0:57:30 lr: 4.484280267957633e-05 loss: 0.0944 (0.0876) time: 3.6392 data: 0.0027 max mem: 19788 +Epoch: [4] [1200/2138] eta: 0:56:53 lr: 4.4837476685049965e-05 loss: 0.0793 (0.0877) time: 3.6295 data: 0.0028 max mem: 19788 +Epoch: [4] [1210/2138] eta: 0:56:17 lr: 4.4832150620228746e-05 loss: 0.0811 (0.0876) time: 3.6285 data: 0.0031 max mem: 19788 +Epoch: [4] [1220/2138] eta: 0:55:40 lr: 4.482682448510247e-05 loss: 0.0800 (0.0877) time: 3.6320 data: 0.0032 max mem: 19788 +Epoch: [4] [1230/2138] eta: 0:55:04 lr: 4.482149827966094e-05 loss: 0.0747 (0.0877) time: 3.6310 data: 0.0031 max mem: 19788 +Epoch: [4] [1240/2138] eta: 0:54:27 lr: 4.481617200389392e-05 loss: 0.0833 (0.0877) time: 3.6374 data: 0.0031 max mem: 19788 +Epoch: [4] [1250/2138] eta: 0:53:51 lr: 4.481084565779122e-05 loss: 0.0814 (0.0877) time: 3.6448 data: 0.0029 max mem: 19788 +Epoch: [4] [1260/2138] eta: 0:53:15 lr: 4.480551924134261e-05 loss: 0.0713 (0.0878) time: 3.6447 data: 0.0027 max mem: 19788 +Epoch: [4] [1270/2138] eta: 0:52:38 lr: 4.480019275453786e-05 loss: 0.0755 (0.0877) time: 3.6421 data: 0.0027 max mem: 19788 +Epoch: [4] [1280/2138] eta: 0:52:02 lr: 4.479486619736676e-05 loss: 0.0737 (0.0876) time: 3.6304 data: 0.0028 max mem: 19788 +Epoch: [4] [1290/2138] eta: 0:51:25 lr: 4.4789539569819076e-05 loss: 0.0851 (0.0878) time: 3.6243 data: 0.0028 max mem: 19788 +Epoch: [4] [1300/2138] eta: 0:50:49 lr: 4.4784212871884586e-05 loss: 0.0841 (0.0877) time: 3.6269 data: 0.0028 max mem: 19788 +Epoch: [4] [1310/2138] eta: 0:50:12 lr: 4.4778886103553045e-05 loss: 0.0737 (0.0876) time: 3.6195 data: 0.0028 max mem: 19788 +Epoch: [4] [1320/2138] eta: 0:49:36 lr: 4.477355926481422e-05 loss: 0.0798 (0.0877) time: 3.6374 data: 0.0030 max mem: 19788 +Epoch: [4] [1330/2138] eta: 0:49:00 lr: 4.476823235565788e-05 loss: 0.0697 (0.0875) time: 3.6442 data: 0.0029 max mem: 19788 +Epoch: [4] [1340/2138] eta: 0:48:23 lr: 4.476290537607379e-05 loss: 0.0698 (0.0876) time: 3.6311 data: 0.0028 max mem: 19788 +Epoch: [4] [1350/2138] eta: 0:47:47 lr: 4.475757832605169e-05 loss: 0.0848 (0.0876) time: 3.6363 data: 0.0028 max mem: 19788 +Epoch: [4] [1360/2138] eta: 0:47:10 lr: 4.475225120558135e-05 loss: 0.0813 (0.0875) time: 3.6353 data: 0.0028 max mem: 19788 +Epoch: [4] [1370/2138] eta: 0:46:34 lr: 4.47469240146525e-05 loss: 0.0758 (0.0874) time: 3.6300 data: 0.0028 max mem: 19788 +Epoch: [4] [1380/2138] eta: 0:45:57 lr: 4.474159675325491e-05 loss: 0.0719 (0.0874) time: 3.6300 data: 0.0029 max mem: 19788 +Epoch: [4] [1390/2138] eta: 0:45:21 lr: 4.47362694213783e-05 loss: 0.0830 (0.0874) time: 3.6315 data: 0.0028 max mem: 19788 +Epoch: [4] [1400/2138] eta: 0:44:45 lr: 4.473094201901243e-05 loss: 0.0912 (0.0874) time: 3.6256 data: 0.0027 max mem: 19788 +Epoch: [4] [1410/2138] eta: 0:44:08 lr: 4.472561454614704e-05 loss: 0.0810 (0.0875) time: 3.6216 data: 0.0030 max mem: 19788 +Epoch: [4] [1420/2138] eta: 0:43:32 lr: 4.472028700277186e-05 loss: 0.0754 (0.0874) time: 3.6199 data: 0.0031 max mem: 19788 +Epoch: [4] [1430/2138] eta: 0:42:55 lr: 4.4714959388876617e-05 loss: 0.0669 (0.0873) time: 3.6175 data: 0.0030 max mem: 19788 +Epoch: [4] [1440/2138] eta: 0:42:19 lr: 4.470963170445105e-05 loss: 0.0647 (0.0872) time: 3.6209 data: 0.0029 max mem: 19788 +Epoch: [4] [1450/2138] eta: 0:41:42 lr: 4.4704303949484896e-05 loss: 0.0799 (0.0871) time: 3.6172 data: 0.0028 max mem: 19788 +Epoch: [4] [1460/2138] eta: 0:41:06 lr: 4.469897612396786e-05 loss: 0.0808 (0.0871) time: 3.6139 data: 0.0028 max mem: 19788 +Epoch: [4] [1470/2138] eta: 0:40:29 lr: 4.4693648227889674e-05 loss: 0.0881 (0.0871) time: 3.6162 data: 0.0029 max mem: 19788 +Epoch: [4] [1480/2138] eta: 0:39:53 lr: 4.468832026124006e-05 loss: 0.0881 (0.0872) time: 3.6267 data: 0.0030 max mem: 19788 +Epoch: [4] [1490/2138] eta: 0:39:16 lr: 4.468299222400872e-05 loss: 0.0777 (0.0871) time: 3.6275 data: 0.0029 max mem: 19788 +Epoch: [4] [1500/2138] eta: 0:38:40 lr: 4.46776641161854e-05 loss: 0.0872 (0.0872) time: 3.6194 data: 0.0027 max mem: 19788 +Epoch: [4] [1510/2138] eta: 0:38:04 lr: 4.467233593775977e-05 loss: 0.0784 (0.0871) time: 3.6324 data: 0.0026 max mem: 19788 +Epoch: [4] [1520/2138] eta: 0:37:27 lr: 4.466700768872156e-05 loss: 0.0698 (0.0870) time: 3.6378 data: 0.0028 max mem: 19788 +Epoch: [4] [1530/2138] eta: 0:36:51 lr: 4.466167936906047e-05 loss: 0.0699 (0.0869) time: 3.6304 data: 0.0029 max mem: 19788 +Epoch: [4] [1540/2138] eta: 0:36:14 lr: 4.4656350978766206e-05 loss: 0.0756 (0.0869) time: 3.6333 data: 0.0029 max mem: 19788 +Epoch: [4] [1550/2138] eta: 0:35:38 lr: 4.465102251782845e-05 loss: 0.0826 (0.0868) time: 3.6288 data: 0.0032 max mem: 19788 +Epoch: [4] [1560/2138] eta: 0:35:02 lr: 4.4645693986236936e-05 loss: 0.0832 (0.0869) time: 3.6278 data: 0.0032 max mem: 19788 +Epoch: [4] [1570/2138] eta: 0:34:25 lr: 4.464036538398132e-05 loss: 0.0949 (0.0869) time: 3.6330 data: 0.0031 max mem: 19788 +Epoch: [4] [1580/2138] eta: 0:33:49 lr: 4.46350367110513e-05 loss: 0.0953 (0.0869) time: 3.6411 data: 0.0031 max mem: 19788 +Epoch: [4] [1590/2138] eta: 0:33:13 lr: 4.4629707967436576e-05 loss: 0.0720 (0.0868) time: 3.6501 data: 0.0029 max mem: 19788 +Epoch: [4] [1600/2138] eta: 0:32:36 lr: 4.4624379153126835e-05 loss: 0.0846 (0.0870) time: 3.6389 data: 0.0029 max mem: 19788 +Epoch: [4] [1610/2138] eta: 0:32:00 lr: 4.4619050268111736e-05 loss: 0.0938 (0.0870) time: 3.6276 data: 0.0028 max mem: 19788 +Epoch: [4] [1620/2138] eta: 0:31:23 lr: 4.461372131238098e-05 loss: 0.0769 (0.0870) time: 3.6252 data: 0.0027 max mem: 19788 +Epoch: [4] [1630/2138] eta: 0:30:47 lr: 4.4608392285924234e-05 loss: 0.0760 (0.0869) time: 3.6243 data: 0.0028 max mem: 19788 +Epoch: [4] [1640/2138] eta: 0:30:11 lr: 4.4603063188731164e-05 loss: 0.0773 (0.0869) time: 3.6284 data: 0.0028 max mem: 19788 +Epoch: [4] [1650/2138] eta: 0:29:34 lr: 4.4597734020791455e-05 loss: 0.0599 (0.0868) time: 3.6271 data: 0.0027 max mem: 19788 +Epoch: [4] [1660/2138] eta: 0:28:58 lr: 4.459240478209477e-05 loss: 0.0651 (0.0867) time: 3.6245 data: 0.0030 max mem: 19788 +Epoch: [4] [1670/2138] eta: 0:28:21 lr: 4.458707547263076e-05 loss: 0.0614 (0.0866) time: 3.6287 data: 0.0032 max mem: 19788 +Epoch: [4] [1680/2138] eta: 0:27:45 lr: 4.458174609238911e-05 loss: 0.0645 (0.0866) time: 3.6252 data: 0.0029 max mem: 19788 +Epoch: [4] [1690/2138] eta: 0:27:09 lr: 4.457641664135946e-05 loss: 0.0766 (0.0867) time: 3.6187 data: 0.0030 max mem: 19788 +Epoch: [4] [1700/2138] eta: 0:26:32 lr: 4.4571087119531475e-05 loss: 0.0804 (0.0867) time: 3.6234 data: 0.0031 max mem: 19788 +Epoch: [4] [1710/2138] eta: 0:25:56 lr: 4.456575752689481e-05 loss: 0.0795 (0.0867) time: 3.6223 data: 0.0031 max mem: 19788 +Epoch: [4] [1720/2138] eta: 0:25:19 lr: 4.45604278634391e-05 loss: 0.0698 (0.0866) time: 3.6185 data: 0.0031 max mem: 19788 +Epoch: [4] [1730/2138] eta: 0:24:43 lr: 4.455509812915401e-05 loss: 0.0676 (0.0866) time: 3.6281 data: 0.0029 max mem: 19788 +Epoch: [4] [1740/2138] eta: 0:24:07 lr: 4.454976832402917e-05 loss: 0.0625 (0.0865) time: 3.6375 data: 0.0028 max mem: 19788 +Epoch: [4] [1750/2138] eta: 0:23:30 lr: 4.454443844805424e-05 loss: 0.0681 (0.0865) time: 3.6326 data: 0.0028 max mem: 19788 +Epoch: [4] [1760/2138] eta: 0:22:54 lr: 4.453910850121884e-05 loss: 0.0795 (0.0865) time: 3.6332 data: 0.0028 max mem: 19788 +Epoch: [4] [1770/2138] eta: 0:22:18 lr: 4.4533778483512614e-05 loss: 0.0667 (0.0864) time: 3.6415 data: 0.0027 max mem: 19788 +Epoch: [4] [1780/2138] eta: 0:21:41 lr: 4.45284483949252e-05 loss: 0.0700 (0.0863) time: 3.6355 data: 0.0026 max mem: 19788 +Epoch: [4] [1790/2138] eta: 0:21:05 lr: 4.4523118235446214e-05 loss: 0.0755 (0.0864) time: 3.6262 data: 0.0029 max mem: 19788 +Epoch: [4] [1800/2138] eta: 0:20:28 lr: 4.4517788005065294e-05 loss: 0.0876 (0.0865) time: 3.6224 data: 0.0030 max mem: 19788 +Epoch: [4] [1810/2138] eta: 0:19:52 lr: 4.451245770377206e-05 loss: 0.0866 (0.0865) time: 3.6398 data: 0.0030 max mem: 19788 +Epoch: [4] [1820/2138] eta: 0:19:16 lr: 4.450712733155613e-05 loss: 0.0857 (0.0865) time: 3.6448 data: 0.0031 max mem: 19788 +Epoch: [4] [1830/2138] eta: 0:18:39 lr: 4.4501796888407136e-05 loss: 0.0788 (0.0865) time: 3.6334 data: 0.0029 max mem: 19788 +Epoch: [4] [1840/2138] eta: 0:18:03 lr: 4.4496466374314685e-05 loss: 0.0924 (0.0866) time: 3.6387 data: 0.0028 max mem: 19788 +Epoch: [4] [1850/2138] eta: 0:17:27 lr: 4.449113578926837e-05 loss: 0.0718 (0.0866) time: 3.6534 data: 0.0027 max mem: 19788 +Epoch: [4] [1860/2138] eta: 0:16:50 lr: 4.448580513325783e-05 loss: 0.0704 (0.0866) time: 3.6475 data: 0.0027 max mem: 19788 +Epoch: [4] [1870/2138] eta: 0:16:14 lr: 4.448047440627266e-05 loss: 0.0864 (0.0867) time: 3.6382 data: 0.0027 max mem: 19788 +Epoch: [4] [1880/2138] eta: 0:15:38 lr: 4.4475143608302466e-05 loss: 0.0864 (0.0867) time: 3.6436 data: 0.0029 max mem: 19788 +Epoch: [4] [1890/2138] eta: 0:15:01 lr: 4.446981273933684e-05 loss: 0.0824 (0.0866) time: 3.6323 data: 0.0031 max mem: 19788 +Epoch: [4] [1900/2138] eta: 0:14:25 lr: 4.446448179936539e-05 loss: 0.0700 (0.0866) time: 3.6233 data: 0.0030 max mem: 19788 +Epoch: [4] [1910/2138] eta: 0:13:49 lr: 4.445915078837771e-05 loss: 0.0716 (0.0866) time: 3.6324 data: 0.0028 max mem: 19788 +Epoch: [4] [1920/2138] eta: 0:13:12 lr: 4.44538197063634e-05 loss: 0.0733 (0.0866) time: 3.6331 data: 0.0029 max mem: 19788 +Epoch: [4] [1930/2138] eta: 0:12:36 lr: 4.444848855331202e-05 loss: 0.0794 (0.0867) time: 3.6375 data: 0.0030 max mem: 19788 +Epoch: [4] [1940/2138] eta: 0:11:59 lr: 4.444315732921319e-05 loss: 0.0804 (0.0867) time: 3.6434 data: 0.0029 max mem: 19788 +Epoch: [4] [1950/2138] eta: 0:11:23 lr: 4.4437826034056465e-05 loss: 0.0781 (0.0867) time: 3.6485 data: 0.0028 max mem: 19788 +Epoch: [4] [1960/2138] eta: 0:10:47 lr: 4.4432494667831454e-05 loss: 0.0634 (0.0866) time: 3.6426 data: 0.0029 max mem: 19788 +Epoch: [4] [1970/2138] eta: 0:10:10 lr: 4.442716323052771e-05 loss: 0.0631 (0.0866) time: 3.6324 data: 0.0031 max mem: 19788 +Epoch: [4] [1980/2138] eta: 0:09:34 lr: 4.442183172213482e-05 loss: 0.0631 (0.0865) time: 3.6418 data: 0.0031 max mem: 19788 +Epoch: [4] [1990/2138] eta: 0:08:58 lr: 4.441650014264235e-05 loss: 0.0598 (0.0865) time: 3.6501 data: 0.0029 max mem: 19788 +Epoch: [4] [2000/2138] eta: 0:08:21 lr: 4.4411168492039886e-05 loss: 0.0632 (0.0864) time: 3.6493 data: 0.0031 max mem: 19788 +Epoch: [4] [2010/2138] eta: 0:07:45 lr: 4.440583677031697e-05 loss: 0.0775 (0.0864) time: 3.6481 data: 0.0031 max mem: 19788 +Epoch: [4] [2020/2138] eta: 0:07:09 lr: 4.440050497746317e-05 loss: 0.0814 (0.0863) time: 3.6422 data: 0.0032 max mem: 19788 +Epoch: [4] [2030/2138] eta: 0:06:32 lr: 4.439517311346805e-05 loss: 0.0672 (0.0863) time: 3.6318 data: 0.0032 max mem: 19788 +Epoch: [4] [2040/2138] eta: 0:05:56 lr: 4.438984117832118e-05 loss: 0.0695 (0.0863) time: 3.6321 data: 0.0029 max mem: 19788 +Epoch: [4] [2050/2138] eta: 0:05:20 lr: 4.4384509172012096e-05 loss: 0.0861 (0.0864) time: 3.6412 data: 0.0027 max mem: 19788 +Epoch: [4] [2060/2138] eta: 0:04:43 lr: 4.4379177094530355e-05 loss: 0.0861 (0.0863) time: 3.6432 data: 0.0027 max mem: 19788 +Epoch: [4] [2070/2138] eta: 0:04:07 lr: 4.43738449458655e-05 loss: 0.0771 (0.0863) time: 3.6303 data: 0.0029 max mem: 19788 +Epoch: [4] [2080/2138] eta: 0:03:30 lr: 4.43685127260071e-05 loss: 0.0728 (0.0862) time: 3.6289 data: 0.0029 max mem: 19788 +Epoch: [4] [2090/2138] eta: 0:02:54 lr: 4.4363180434944664e-05 loss: 0.0745 (0.0862) time: 3.6265 data: 0.0027 max mem: 19788 +Epoch: [4] [2100/2138] eta: 0:02:18 lr: 4.435784807266775e-05 loss: 0.0739 (0.0862) time: 3.6248 data: 0.0027 max mem: 19788 +Epoch: [4] [2110/2138] eta: 0:01:41 lr: 4.435251563916589e-05 loss: 0.0823 (0.0862) time: 3.6260 data: 0.0028 max mem: 19788 +Epoch: [4] [2120/2138] eta: 0:01:05 lr: 4.434718313442863e-05 loss: 0.0813 (0.0863) time: 3.6241 data: 0.0028 max mem: 19788 +Epoch: [4] [2130/2138] eta: 0:00:29 lr: 4.4341850558445474e-05 loss: 0.0788 (0.0863) time: 3.6123 data: 0.0028 max mem: 19788 +Epoch: [4] Total time: 2:09:34 +Test: [ 0/21770] eta: 18:13:15 time: 3.0131 data: 2.8794 max mem: 19788 +Test: [ 100/21770] eta: 0:35:36 time: 0.0604 data: 0.0018 max mem: 19788 +Test: [ 200/21770] eta: 0:29:20 time: 0.0605 data: 0.0017 max mem: 19788 +Test: [ 300/21770] eta: 0:27:51 time: 0.0634 data: 0.0019 max mem: 19788 +Test: [ 400/21770] eta: 0:26:46 time: 0.0655 data: 0.0018 max mem: 19788 +Test: [ 500/21770] eta: 0:26:02 time: 0.0731 data: 0.0023 max mem: 19788 +Test: [ 600/21770] eta: 0:25:42 time: 0.0714 data: 0.0021 max mem: 19788 +Test: [ 700/21770] eta: 0:25:18 time: 0.0600 data: 0.0017 max mem: 19788 +Test: [ 800/21770] eta: 0:24:53 time: 0.0669 data: 0.0019 max mem: 19788 +Test: [ 900/21770] eta: 0:24:54 time: 0.0695 data: 0.0020 max mem: 19788 +Test: [ 1000/21770] eta: 0:24:39 time: 0.0774 data: 0.0021 max mem: 19788 +Test: [ 1100/21770] eta: 0:24:17 time: 0.0718 data: 0.0021 max mem: 19788 +Test: [ 1200/21770] eta: 0:24:02 time: 0.0734 data: 0.0020 max mem: 19788 +Test: [ 1300/21770] eta: 0:23:44 time: 0.0602 data: 0.0020 max mem: 19788 +Test: [ 1400/21770] eta: 0:23:36 time: 0.0741 data: 0.0022 max mem: 19788 +Test: [ 1500/21770] eta: 0:23:22 time: 0.0619 data: 0.0019 max mem: 19788 +Test: [ 1600/21770] eta: 0:23:17 time: 0.0819 data: 0.0020 max mem: 19788 +Test: [ 1700/21770] eta: 0:23:11 time: 0.0803 data: 0.0024 max mem: 19788 +Test: [ 1800/21770] eta: 0:23:06 time: 0.0797 data: 0.0024 max mem: 19788 +Test: [ 1900/21770] eta: 0:22:58 time: 0.0660 data: 0.0020 max mem: 19788 +Test: [ 2000/21770] eta: 0:22:49 time: 0.0825 data: 0.0025 max mem: 19788 +Test: [ 2100/21770] eta: 0:22:41 time: 0.0631 data: 0.0018 max mem: 19788 +Test: [ 2200/21770] eta: 0:22:31 time: 0.0655 data: 0.0020 max mem: 19788 +Test: [ 2300/21770] eta: 0:22:18 time: 0.0638 data: 0.0018 max mem: 19788 +Test: [ 2400/21770] eta: 0:22:07 time: 0.0641 data: 0.0019 max mem: 19788 +Test: [ 2500/21770] eta: 0:21:57 time: 0.0674 data: 0.0020 max mem: 19788 +Test: [ 2600/21770] eta: 0:21:53 time: 0.0629 data: 0.0018 max mem: 19788 +Test: [ 2700/21770] eta: 0:21:49 time: 0.0816 data: 0.0023 max mem: 19788 +Test: [ 2800/21770] eta: 0:21:42 time: 0.0625 data: 0.0019 max mem: 19788 +Test: [ 2900/21770] eta: 0:21:35 time: 0.0713 data: 0.0020 max mem: 19788 +Test: [ 3000/21770] eta: 0:21:30 time: 0.0700 data: 0.0018 max mem: 19788 +Test: [ 3100/21770] eta: 0:21:20 time: 0.0607 data: 0.0016 max mem: 19788 +Test: [ 3200/21770] eta: 0:21:16 time: 0.0801 data: 0.0024 max mem: 19788 +Test: [ 3300/21770] eta: 0:21:11 time: 0.0713 data: 0.0020 max mem: 19788 +Test: [ 3400/21770] eta: 0:21:03 time: 0.0681 data: 0.0018 max mem: 19788 +Test: [ 3500/21770] eta: 0:20:55 time: 0.0635 data: 0.0017 max mem: 19788 +Test: [ 3600/21770] eta: 0:20:48 time: 0.0694 data: 0.0019 max mem: 19788 +Test: [ 3700/21770] eta: 0:20:39 time: 0.0753 data: 0.0020 max mem: 19788 +Test: [ 3800/21770] eta: 0:20:30 time: 0.0627 data: 0.0020 max mem: 19788 +Test: [ 3900/21770] eta: 0:20:25 time: 0.0729 data: 0.0021 max mem: 19788 +Test: [ 4000/21770] eta: 0:20:20 time: 0.0736 data: 0.0023 max mem: 19788 +Test: [ 4100/21770] eta: 0:20:11 time: 0.0600 data: 0.0017 max mem: 19788 +Test: [ 4200/21770] eta: 0:20:04 time: 0.0756 data: 0.0020 max mem: 19788 +Test: [ 4300/21770] eta: 0:19:55 time: 0.0622 data: 0.0018 max mem: 19788 +Test: [ 4400/21770] eta: 0:19:48 time: 0.0695 data: 0.0020 max mem: 19788 +Test: [ 4500/21770] eta: 0:19:39 time: 0.0636 data: 0.0018 max mem: 19788 +Test: [ 4600/21770] eta: 0:19:32 time: 0.0701 data: 0.0020 max mem: 19788 +Test: [ 4700/21770] eta: 0:19:24 time: 0.0696 data: 0.0023 max mem: 19788 +Test: [ 4800/21770] eta: 0:19:18 time: 0.0692 data: 0.0020 max mem: 19788 +Test: [ 4900/21770] eta: 0:19:10 time: 0.0695 data: 0.0020 max mem: 19788 +Test: [ 5000/21770] eta: 0:19:04 time: 0.0744 data: 0.0021 max mem: 19788 +Test: [ 5100/21770] eta: 0:18:56 time: 0.0627 data: 0.0018 max mem: 19788 +Test: [ 5200/21770] eta: 0:18:49 time: 0.0633 data: 0.0018 max mem: 19788 +Test: [ 5300/21770] eta: 0:18:42 time: 0.0752 data: 0.0021 max mem: 19788 +Test: [ 5400/21770] eta: 0:18:36 time: 0.0689 data: 0.0021 max mem: 19788 +Test: [ 5500/21770] eta: 0:18:31 time: 0.0789 data: 0.0020 max mem: 19788 +Test: [ 5600/21770] eta: 0:18:22 time: 0.0623 data: 0.0017 max mem: 19788 +Test: [ 5700/21770] eta: 0:18:15 time: 0.0697 data: 0.0021 max mem: 19788 +Test: [ 5800/21770] eta: 0:18:07 time: 0.0637 data: 0.0017 max mem: 19788 +Test: [ 5900/21770] eta: 0:17:59 time: 0.0685 data: 0.0018 max mem: 19788 +Test: [ 6000/21770] eta: 0:17:52 time: 0.0798 data: 0.0019 max mem: 19788 +Test: [ 6100/21770] eta: 0:17:48 time: 0.0728 data: 0.0022 max mem: 19788 +Test: [ 6200/21770] eta: 0:17:42 time: 0.0759 data: 0.0023 max mem: 19788 +Test: [ 6300/21770] eta: 0:17:36 time: 0.0784 data: 0.0023 max mem: 19788 +Test: [ 6400/21770] eta: 0:17:30 time: 0.0672 data: 0.0019 max mem: 19788 +Test: [ 6500/21770] eta: 0:17:23 time: 0.0824 data: 0.0019 max mem: 19788 +Test: [ 6600/21770] eta: 0:17:16 time: 0.0710 data: 0.0021 max mem: 19788 +Test: [ 6700/21770] eta: 0:17:09 time: 0.0623 data: 0.0019 max mem: 19788 +Test: [ 6800/21770] eta: 0:17:01 time: 0.0615 data: 0.0018 max mem: 19788 +Test: [ 6900/21770] eta: 0:16:53 time: 0.0631 data: 0.0019 max mem: 19788 +Test: [ 7000/21770] eta: 0:16:47 time: 0.0640 data: 0.0019 max mem: 19788 +Test: [ 7100/21770] eta: 0:16:40 time: 0.0618 data: 0.0023 max mem: 19788 +Test: [ 7200/21770] eta: 0:16:33 time: 0.0679 data: 0.0022 max mem: 19788 +Test: [ 7300/21770] eta: 0:16:27 time: 0.0737 data: 0.0019 max mem: 19788 +Test: [ 7400/21770] eta: 0:16:20 time: 0.0608 data: 0.0018 max mem: 19788 +Test: [ 7500/21770] eta: 0:16:14 time: 0.0713 data: 0.0020 max mem: 19788 +Test: [ 7600/21770] eta: 0:16:06 time: 0.0636 data: 0.0018 max mem: 19788 +Test: [ 7700/21770] eta: 0:16:00 time: 0.0684 data: 0.0020 max mem: 19788 +Test: [ 7800/21770] eta: 0:15:53 time: 0.0696 data: 0.0022 max mem: 19788 +Test: [ 7900/21770] eta: 0:15:46 time: 0.0668 data: 0.0020 max mem: 19788 +Test: [ 8000/21770] eta: 0:15:39 time: 0.0632 data: 0.0018 max mem: 19788 +Test: [ 8100/21770] eta: 0:15:33 time: 0.0677 data: 0.0020 max mem: 19788 +Test: [ 8200/21770] eta: 0:15:26 time: 0.0659 data: 0.0017 max mem: 19788 +Test: [ 8300/21770] eta: 0:15:19 time: 0.0754 data: 0.0024 max mem: 19788 +Test: [ 8400/21770] eta: 0:15:11 time: 0.0618 data: 0.0018 max mem: 19788 +Test: [ 8500/21770] eta: 0:15:04 time: 0.0703 data: 0.0019 max mem: 19788 +Test: [ 8600/21770] eta: 0:14:57 time: 0.0624 data: 0.0020 max mem: 19788 +Test: [ 8700/21770] eta: 0:14:50 time: 0.0660 data: 0.0020 max mem: 19788 +Test: [ 8800/21770] eta: 0:14:44 time: 0.0632 data: 0.0017 max mem: 19788 +Test: [ 8900/21770] eta: 0:14:37 time: 0.0635 data: 0.0019 max mem: 19788 +Test: [ 9000/21770] eta: 0:14:29 time: 0.0625 data: 0.0019 max mem: 19788 +Test: [ 9100/21770] eta: 0:14:23 time: 0.0616 data: 0.0017 max mem: 19788 +Test: [ 9200/21770] eta: 0:14:16 time: 0.0770 data: 0.0017 max mem: 19788 +Test: [ 9300/21770] eta: 0:14:10 time: 0.0648 data: 0.0018 max mem: 19788 +Test: [ 9400/21770] eta: 0:14:03 time: 0.0607 data: 0.0017 max mem: 19788 +Test: [ 9500/21770] eta: 0:13:57 time: 0.0703 data: 0.0020 max mem: 19788 +Test: [ 9600/21770] eta: 0:13:50 time: 0.0631 data: 0.0019 max mem: 19788 +Test: [ 9700/21770] eta: 0:13:43 time: 0.0640 data: 0.0019 max mem: 19788 +Test: [ 9800/21770] eta: 0:13:36 time: 0.0639 data: 0.0019 max mem: 19788 +Test: [ 9900/21770] eta: 0:13:28 time: 0.0655 data: 0.0017 max mem: 19788 +Test: [10000/21770] eta: 0:13:21 time: 0.0641 data: 0.0019 max mem: 19788 +Test: [10100/21770] eta: 0:13:15 time: 0.0767 data: 0.0019 max mem: 19788 +Test: [10200/21770] eta: 0:13:09 time: 0.0722 data: 0.0021 max mem: 19788 +Test: [10300/21770] eta: 0:13:02 time: 0.0629 data: 0.0017 max mem: 19788 +Test: [10400/21770] eta: 0:12:55 time: 0.0699 data: 0.0020 max mem: 19788 +Test: [10500/21770] eta: 0:12:49 time: 0.0688 data: 0.0018 max mem: 19788 +Test: [10600/21770] eta: 0:12:42 time: 0.0637 data: 0.0018 max mem: 19788 +Test: [10700/21770] eta: 0:12:35 time: 0.0707 data: 0.0019 max mem: 19788 +Test: [10800/21770] eta: 0:12:29 time: 0.0635 data: 0.0018 max mem: 19788 +Test: [10900/21770] eta: 0:12:22 time: 0.0818 data: 0.0024 max mem: 19788 +Test: [11000/21770] eta: 0:12:15 time: 0.0645 data: 0.0018 max mem: 19788 +Test: [11100/21770] eta: 0:12:08 time: 0.0638 data: 0.0017 max mem: 19788 +Test: [11200/21770] eta: 0:12:01 time: 0.0650 data: 0.0018 max mem: 19788 +Test: [11300/21770] eta: 0:11:54 time: 0.0712 data: 0.0022 max mem: 19788 +Test: [11400/21770] eta: 0:11:48 time: 0.0794 data: 0.0018 max mem: 19788 +Test: [11500/21770] eta: 0:11:42 time: 0.0703 data: 0.0021 max mem: 19788 +Test: [11600/21770] eta: 0:11:35 time: 0.0628 data: 0.0019 max mem: 19788 +Test: [11700/21770] eta: 0:11:28 time: 0.0673 data: 0.0018 max mem: 19788 +Test: [11800/21770] eta: 0:11:21 time: 0.0631 data: 0.0019 max mem: 19788 +Test: [11900/21770] eta: 0:11:15 time: 0.0804 data: 0.0024 max mem: 19788 +Test: [12000/21770] eta: 0:11:08 time: 0.0789 data: 0.0024 max mem: 19788 +Test: [12100/21770] eta: 0:11:02 time: 0.0648 data: 0.0019 max mem: 19788 +Test: [12200/21770] eta: 0:10:54 time: 0.0615 data: 0.0018 max mem: 19788 +Test: [12300/21770] eta: 0:10:48 time: 0.0717 data: 0.0020 max mem: 19788 +Test: [12400/21770] eta: 0:10:41 time: 0.0797 data: 0.0020 max mem: 19788 +Test: [12500/21770] eta: 0:10:35 time: 0.0733 data: 0.0022 max mem: 19788 +Test: [12600/21770] eta: 0:10:28 time: 0.0807 data: 0.0023 max mem: 19788 +Test: [12700/21770] eta: 0:10:21 time: 0.0742 data: 0.0020 max mem: 19788 +Test: [12800/21770] eta: 0:10:15 time: 0.0806 data: 0.0024 max mem: 19788 +Test: [12900/21770] eta: 0:10:08 time: 0.0755 data: 0.0021 max mem: 19788 +Test: [13000/21770] eta: 0:10:01 time: 0.0611 data: 0.0017 max mem: 19788 +Test: [13100/21770] eta: 0:09:54 time: 0.0657 data: 0.0018 max mem: 19788 +Test: [13200/21770] eta: 0:09:47 time: 0.0788 data: 0.0021 max mem: 19788 +Test: [13300/21770] eta: 0:09:41 time: 0.0650 data: 0.0018 max mem: 19788 +Test: [13400/21770] eta: 0:09:34 time: 0.0761 data: 0.0019 max mem: 19788 +Test: [13500/21770] eta: 0:09:27 time: 0.0637 data: 0.0017 max mem: 19788 +Test: [13600/21770] eta: 0:09:20 time: 0.0736 data: 0.0018 max mem: 19788 +Test: [13700/21770] eta: 0:09:12 time: 0.0656 data: 0.0018 max mem: 19788 +Test: [13800/21770] eta: 0:09:06 time: 0.0702 data: 0.0022 max mem: 19788 +Test: [13900/21770] eta: 0:08:59 time: 0.0610 data: 0.0019 max mem: 19788 +Test: [14000/21770] eta: 0:08:52 time: 0.0745 data: 0.0020 max mem: 19788 +Test: [14100/21770] eta: 0:08:46 time: 0.0744 data: 0.0022 max mem: 19788 +Test: [14200/21770] eta: 0:08:39 time: 0.0660 data: 0.0019 max mem: 19788 +Test: [14300/21770] eta: 0:08:32 time: 0.0673 data: 0.0020 max mem: 19788 +Test: [14400/21770] eta: 0:08:26 time: 0.0637 data: 0.0018 max mem: 19788 +Test: [14500/21770] eta: 0:08:19 time: 0.0611 data: 0.0018 max mem: 19788 +Test: [14600/21770] eta: 0:08:12 time: 0.0753 data: 0.0021 max mem: 19788 +Test: [14700/21770] eta: 0:08:05 time: 0.0615 data: 0.0016 max mem: 19788 +Test: [14800/21770] eta: 0:07:58 time: 0.0738 data: 0.0022 max mem: 19788 +Test: [14900/21770] eta: 0:07:51 time: 0.0642 data: 0.0018 max mem: 19788 +Test: [15000/21770] eta: 0:07:44 time: 0.0780 data: 0.0022 max mem: 19788 +Test: [15100/21770] eta: 0:07:37 time: 0.0678 data: 0.0021 max mem: 19788 +Test: [15200/21770] eta: 0:07:30 time: 0.0667 data: 0.0019 max mem: 19788 +Test: [15300/21770] eta: 0:07:24 time: 0.0807 data: 0.0024 max mem: 19788 +Test: [15400/21770] eta: 0:07:17 time: 0.0617 data: 0.0019 max mem: 19788 +Test: [15500/21770] eta: 0:07:10 time: 0.0843 data: 0.0025 max mem: 19788 +Test: [15600/21770] eta: 0:07:03 time: 0.0632 data: 0.0017 max mem: 19788 +Test: [15700/21770] eta: 0:06:56 time: 0.0619 data: 0.0018 max mem: 19788 +Test: [15800/21770] eta: 0:06:49 time: 0.0614 data: 0.0019 max mem: 19788 +Test: [15900/21770] eta: 0:06:42 time: 0.0699 data: 0.0020 max mem: 19788 +Test: [16000/21770] eta: 0:06:36 time: 0.0809 data: 0.0024 max mem: 19788 +Test: [16100/21770] eta: 0:06:29 time: 0.0810 data: 0.0024 max mem: 19788 +Test: [16200/21770] eta: 0:06:22 time: 0.0707 data: 0.0021 max mem: 19788 +Test: [16300/21770] eta: 0:06:15 time: 0.0669 data: 0.0020 max mem: 19788 +Test: [16400/21770] eta: 0:06:09 time: 0.0637 data: 0.0021 max mem: 19788 +Test: [16500/21770] eta: 0:06:01 time: 0.0632 data: 0.0018 max mem: 19788 +Test: [16600/21770] eta: 0:05:54 time: 0.0624 data: 0.0018 max mem: 19788 +Test: [16700/21770] eta: 0:05:47 time: 0.0634 data: 0.0017 max mem: 19788 +Test: [16800/21770] eta: 0:05:41 time: 0.0718 data: 0.0022 max mem: 19788 +Test: [16900/21770] eta: 0:05:34 time: 0.0632 data: 0.0017 max mem: 19788 +Test: [17000/21770] eta: 0:05:27 time: 0.0688 data: 0.0021 max mem: 19788 +Test: [17100/21770] eta: 0:05:20 time: 0.0629 data: 0.0017 max mem: 19788 +Test: [17200/21770] eta: 0:05:13 time: 0.0616 data: 0.0018 max mem: 19788 +Test: [17300/21770] eta: 0:05:06 time: 0.0627 data: 0.0019 max mem: 19788 +Test: [17400/21770] eta: 0:04:59 time: 0.0746 data: 0.0022 max mem: 19788 +Test: [17500/21770] eta: 0:04:52 time: 0.0605 data: 0.0019 max mem: 19788 +Test: [17600/21770] eta: 0:04:45 time: 0.0622 data: 0.0018 max mem: 19788 +Test: [17700/21770] eta: 0:04:38 time: 0.0726 data: 0.0021 max mem: 19788 +Test: [17800/21770] eta: 0:04:32 time: 0.0652 data: 0.0019 max mem: 19788 +Test: [17900/21770] eta: 0:04:25 time: 0.0632 data: 0.0019 max mem: 19788 +Test: [18000/21770] eta: 0:04:18 time: 0.0800 data: 0.0025 max mem: 19788 +Test: [18100/21770] eta: 0:04:11 time: 0.0684 data: 0.0020 max mem: 19788 +Test: [18200/21770] eta: 0:04:04 time: 0.0728 data: 0.0023 max mem: 19788 +Test: [18300/21770] eta: 0:03:57 time: 0.0622 data: 0.0019 max mem: 19788 +Test: [18400/21770] eta: 0:03:50 time: 0.0732 data: 0.0019 max mem: 19788 +Test: [18500/21770] eta: 0:03:43 time: 0.0672 data: 0.0021 max mem: 19788 +Test: [18600/21770] eta: 0:03:37 time: 0.0613 data: 0.0018 max mem: 19788 +Test: [18700/21770] eta: 0:03:30 time: 0.0793 data: 0.0024 max mem: 19788 +Test: [18800/21770] eta: 0:03:23 time: 0.0651 data: 0.0021 max mem: 19788 +Test: [18900/21770] eta: 0:03:16 time: 0.0777 data: 0.0023 max mem: 19788 +Test: [19000/21770] eta: 0:03:09 time: 0.0612 data: 0.0017 max mem: 19788 +Test: [19100/21770] eta: 0:03:02 time: 0.0718 data: 0.0019 max mem: 19788 +Test: [19200/21770] eta: 0:02:56 time: 0.0632 data: 0.0019 max mem: 19788 +Test: [19300/21770] eta: 0:02:49 time: 0.0736 data: 0.0022 max mem: 19788 +Test: [19400/21770] eta: 0:02:42 time: 0.0615 data: 0.0016 max mem: 19788 +Test: [19500/21770] eta: 0:02:35 time: 0.0625 data: 0.0018 max mem: 19788 +Test: [19600/21770] eta: 0:02:28 time: 0.0635 data: 0.0018 max mem: 19788 +Test: [19700/21770] eta: 0:02:21 time: 0.0649 data: 0.0019 max mem: 19788 +Test: [19800/21770] eta: 0:02:14 time: 0.0615 data: 0.0017 max mem: 19788 +Test: [19900/21770] eta: 0:02:07 time: 0.0800 data: 0.0023 max mem: 19788 +Test: [20000/21770] eta: 0:02:01 time: 0.0613 data: 0.0018 max mem: 19788 +Test: [20100/21770] eta: 0:01:54 time: 0.0630 data: 0.0018 max mem: 19788 +Test: [20200/21770] eta: 0:01:47 time: 0.0814 data: 0.0022 max mem: 19788 +Test: [20300/21770] eta: 0:01:40 time: 0.0722 data: 0.0019 max mem: 19788 +Test: [20400/21770] eta: 0:01:33 time: 0.0787 data: 0.0022 max mem: 19788 +Test: [20500/21770] eta: 0:01:26 time: 0.0675 data: 0.0021 max mem: 19788 +Test: [20600/21770] eta: 0:01:20 time: 0.0778 data: 0.0024 max mem: 19788 +Test: [20700/21770] eta: 0:01:13 time: 0.0653 data: 0.0017 max mem: 19788 +Test: [20800/21770] eta: 0:01:06 time: 0.0645 data: 0.0019 max mem: 19788 +Test: [20900/21770] eta: 0:00:59 time: 0.0598 data: 0.0019 max mem: 19788 +Test: [21000/21770] eta: 0:00:52 time: 0.0680 data: 0.0019 max mem: 19788 +Test: [21100/21770] eta: 0:00:45 time: 0.0676 data: 0.0022 max mem: 19788 +Test: [21200/21770] eta: 0:00:39 time: 0.0643 data: 0.0020 max mem: 19788 +Test: [21300/21770] eta: 0:00:32 time: 0.0787 data: 0.0019 max mem: 19788 +Test: [21400/21770] eta: 0:00:25 time: 0.0670 data: 0.0019 max mem: 19788 +Test: [21500/21770] eta: 0:00:18 time: 0.0633 data: 0.0020 max mem: 19788 +Test: [21600/21770] eta: 0:00:11 time: 0.0589 data: 0.0017 max mem: 19788 +Test: [21700/21770] eta: 0:00:04 time: 0.0584 data: 0.0017 max mem: 19788 +Test: Total time: 0:24:51 +Final results: +Mean IoU is 58.91 + + precision@0.5 = 65.10 + precision@0.6 = 58.87 + precision@0.7 = 51.44 + precision@0.8 = 40.26 + precision@0.9 = 18.43 + overall IoU = 60.92 + mean IoU = 58.91 + +Mean accuracy for one-to-zero sample is 79.85 + +Average object IoU 0.5890778859798311 +Overall IoU 60.91598129272461 +Better epoch: 4 + +Epoch: [5] [ 0/2138] eta: 3:10:58 lr: 4.433758444635489e-05 loss: 0.0993 (0.0993) time: 5.3592 data: 1.3528 max mem: 19788 +Epoch: [5] [ 10/2138] eta: 2:14:57 lr: 4.4332251742102765e-05 loss: 0.0671 (0.0729) time: 3.8053 data: 0.1258 max mem: 19788 +Epoch: [5] [ 20/2138] eta: 2:11:32 lr: 4.432691896657543e-05 loss: 0.0613 (0.0667) time: 3.6446 data: 0.0027 max mem: 19788 +Epoch: [5] [ 30/2138] eta: 2:09:47 lr: 4.432158611976241e-05 loss: 0.0568 (0.0658) time: 3.6334 data: 0.0026 max mem: 19788 +Epoch: [5] [ 40/2138] eta: 2:08:39 lr: 4.4316253201653214e-05 loss: 0.0654 (0.0685) time: 3.6304 data: 0.0030 max mem: 19788 +Epoch: [5] [ 50/2138] eta: 2:07:46 lr: 4.431092021223736e-05 loss: 0.0744 (0.0718) time: 3.6366 data: 0.0028 max mem: 19788 +Epoch: [5] [ 60/2138] eta: 2:06:52 lr: 4.4305587151504354e-05 loss: 0.0688 (0.0719) time: 3.6311 data: 0.0028 max mem: 19788 +Epoch: [5] [ 70/2138] eta: 2:06:05 lr: 4.43002540194437e-05 loss: 0.0578 (0.0701) time: 3.6240 data: 0.0030 max mem: 19788 +Epoch: [5] [ 80/2138] eta: 2:05:23 lr: 4.429492081604492e-05 loss: 0.0651 (0.0717) time: 3.6323 data: 0.0032 max mem: 19788 +Epoch: [5] [ 90/2138] eta: 2:04:39 lr: 4.42895875412975e-05 loss: 0.0746 (0.0730) time: 3.6299 data: 0.0032 max mem: 19788 +Epoch: [5] [ 100/2138] eta: 2:03:56 lr: 4.428425419519095e-05 loss: 0.0747 (0.0728) time: 3.6198 data: 0.0031 max mem: 19788 +Epoch: [5] [ 110/2138] eta: 2:03:17 lr: 4.4278920777714754e-05 loss: 0.0650 (0.0730) time: 3.6283 data: 0.0031 max mem: 19788 +Epoch: [5] [ 120/2138] eta: 2:02:35 lr: 4.4273587288858415e-05 loss: 0.0650 (0.0728) time: 3.6270 data: 0.0028 max mem: 19788 +Epoch: [5] [ 130/2138] eta: 2:01:57 lr: 4.4268253728611415e-05 loss: 0.0730 (0.0733) time: 3.6240 data: 0.0028 max mem: 19788 +Epoch: [5] [ 140/2138] eta: 2:01:17 lr: 4.426292009696325e-05 loss: 0.0735 (0.0734) time: 3.6274 data: 0.0030 max mem: 19788 +Epoch: [5] [ 150/2138] eta: 2:00:39 lr: 4.42575863939034e-05 loss: 0.0688 (0.0736) time: 3.6254 data: 0.0030 max mem: 19788 +Epoch: [5] [ 160/2138] eta: 2:00:03 lr: 4.425225261942134e-05 loss: 0.0800 (0.0744) time: 3.6343 data: 0.0029 max mem: 19788 +Epoch: [5] [ 170/2138] eta: 1:59:27 lr: 4.424691877350656e-05 loss: 0.0697 (0.0741) time: 3.6427 data: 0.0029 max mem: 19788 +Epoch: [5] [ 180/2138] eta: 1:58:48 lr: 4.424158485614853e-05 loss: 0.0706 (0.0747) time: 3.6344 data: 0.0028 max mem: 19788 +Epoch: [5] [ 190/2138] eta: 1:58:10 lr: 4.423625086733672e-05 loss: 0.0713 (0.0747) time: 3.6227 data: 0.0027 max mem: 19788 +Epoch: [5] [ 200/2138] eta: 1:57:34 lr: 4.4230916807060596e-05 loss: 0.0641 (0.0746) time: 3.6355 data: 0.0028 max mem: 19788 +Epoch: [5] [ 210/2138] eta: 1:56:58 lr: 4.422558267530963e-05 loss: 0.0753 (0.0749) time: 3.6445 data: 0.0031 max mem: 19788 +Epoch: [5] [ 220/2138] eta: 1:56:20 lr: 4.422024847207329e-05 loss: 0.0755 (0.0748) time: 3.6321 data: 0.0030 max mem: 19788 +Epoch: [5] [ 230/2138] eta: 1:55:42 lr: 4.421491419734103e-05 loss: 0.0754 (0.0751) time: 3.6195 data: 0.0028 max mem: 19788 +Epoch: [5] [ 240/2138] eta: 1:55:04 lr: 4.420957985110231e-05 loss: 0.0754 (0.0755) time: 3.6205 data: 0.0030 max mem: 19788 +Epoch: [5] [ 250/2138] eta: 1:54:27 lr: 4.420424543334658e-05 loss: 0.0715 (0.0755) time: 3.6234 data: 0.0031 max mem: 19788 +Epoch: [5] [ 260/2138] eta: 1:53:50 lr: 4.41989109440633e-05 loss: 0.0640 (0.0750) time: 3.6265 data: 0.0034 max mem: 19788 +Epoch: [5] [ 270/2138] eta: 1:53:12 lr: 4.419357638324191e-05 loss: 0.0588 (0.0755) time: 3.6269 data: 0.0034 max mem: 19788 +Epoch: [5] [ 280/2138] eta: 1:52:35 lr: 4.4188241750871855e-05 loss: 0.0625 (0.0752) time: 3.6236 data: 0.0032 max mem: 19788 +Epoch: [5] [ 290/2138] eta: 1:51:59 lr: 4.418290704694259e-05 loss: 0.0593 (0.0749) time: 3.6283 data: 0.0029 max mem: 19788 +Epoch: [5] [ 300/2138] eta: 1:51:22 lr: 4.417757227144354e-05 loss: 0.0592 (0.0746) time: 3.6267 data: 0.0027 max mem: 19788 +Epoch: [5] [ 310/2138] eta: 1:50:45 lr: 4.417223742436415e-05 loss: 0.0652 (0.0748) time: 3.6311 data: 0.0027 max mem: 19788 +Epoch: [5] [ 320/2138] eta: 1:50:10 lr: 4.4166902505693846e-05 loss: 0.0785 (0.0749) time: 3.6440 data: 0.0027 max mem: 19788 +Epoch: [5] [ 330/2138] eta: 1:49:34 lr: 4.416156751542207e-05 loss: 0.0653 (0.0749) time: 3.6448 data: 0.0027 max mem: 19788 +Epoch: [5] [ 340/2138] eta: 1:48:57 lr: 4.4156232453538245e-05 loss: 0.0732 (0.0751) time: 3.6381 data: 0.0028 max mem: 19788 +Epoch: [5] [ 350/2138] eta: 1:48:21 lr: 4.41508973200318e-05 loss: 0.0799 (0.0756) time: 3.6385 data: 0.0029 max mem: 19788 +Epoch: [5] [ 360/2138] eta: 1:47:44 lr: 4.414556211489214e-05 loss: 0.0694 (0.0757) time: 3.6292 data: 0.0030 max mem: 19788 +Epoch: [5] [ 370/2138] eta: 1:47:07 lr: 4.414022683810871e-05 loss: 0.0800 (0.0762) time: 3.6251 data: 0.0031 max mem: 19788 +Epoch: [5] [ 380/2138] eta: 1:46:31 lr: 4.413489148967089e-05 loss: 0.0697 (0.0761) time: 3.6355 data: 0.0029 max mem: 19788 +Epoch: [5] [ 390/2138] eta: 1:45:54 lr: 4.4129556069568135e-05 loss: 0.0682 (0.0760) time: 3.6323 data: 0.0029 max mem: 19788 +Epoch: [5] [ 400/2138] eta: 1:45:18 lr: 4.4124220577789825e-05 loss: 0.0746 (0.0761) time: 3.6299 data: 0.0029 max mem: 19788 +Epoch: [5] [ 410/2138] eta: 1:44:41 lr: 4.411888501432538e-05 loss: 0.0777 (0.0768) time: 3.6333 data: 0.0032 max mem: 19788 +Epoch: [5] [ 420/2138] eta: 1:44:05 lr: 4.411354937916419e-05 loss: 0.0759 (0.0770) time: 3.6313 data: 0.0033 max mem: 19788 +Epoch: [5] [ 430/2138] eta: 1:43:28 lr: 4.4108213672295676e-05 loss: 0.0794 (0.0771) time: 3.6304 data: 0.0031 max mem: 19788 +Epoch: [5] [ 440/2138] eta: 1:42:52 lr: 4.4102877893709224e-05 loss: 0.0744 (0.0772) time: 3.6279 data: 0.0032 max mem: 19788 +Epoch: [5] [ 450/2138] eta: 1:42:15 lr: 4.4097542043394234e-05 loss: 0.0738 (0.0769) time: 3.6232 data: 0.0031 max mem: 19788 +Epoch: [5] [ 460/2138] eta: 1:41:38 lr: 4.409220612134009e-05 loss: 0.0661 (0.0772) time: 3.6235 data: 0.0030 max mem: 19788 +Epoch: [5] [ 470/2138] eta: 1:41:01 lr: 4.408687012753618e-05 loss: 0.0756 (0.0773) time: 3.6262 data: 0.0032 max mem: 19788 +Epoch: [5] [ 480/2138] eta: 1:40:25 lr: 4.40815340619719e-05 loss: 0.0724 (0.0771) time: 3.6318 data: 0.0030 max mem: 19788 +Epoch: [5] [ 490/2138] eta: 1:39:49 lr: 4.407619792463664e-05 loss: 0.0657 (0.0770) time: 3.6344 data: 0.0031 max mem: 19788 +Epoch: [5] [ 500/2138] eta: 1:39:12 lr: 4.407086171551975e-05 loss: 0.0657 (0.0770) time: 3.6338 data: 0.0034 max mem: 19788 +Epoch: [5] [ 510/2138] eta: 1:38:36 lr: 4.4065525434610635e-05 loss: 0.0679 (0.0770) time: 3.6336 data: 0.0031 max mem: 19788 +Epoch: [5] [ 520/2138] eta: 1:38:00 lr: 4.406018908189865e-05 loss: 0.0738 (0.0771) time: 3.6310 data: 0.0029 max mem: 19788 +Epoch: [5] [ 530/2138] eta: 1:37:23 lr: 4.405485265737318e-05 loss: 0.0738 (0.0772) time: 3.6307 data: 0.0028 max mem: 19788 +Epoch: [5] [ 540/2138] eta: 1:36:47 lr: 4.4049516161023595e-05 loss: 0.0706 (0.0770) time: 3.6370 data: 0.0028 max mem: 19788 +Epoch: [5] [ 550/2138] eta: 1:36:10 lr: 4.4044179592839244e-05 loss: 0.0636 (0.0767) time: 3.6327 data: 0.0029 max mem: 19788 +Epoch: [5] [ 560/2138] eta: 1:35:34 lr: 4.40388429528095e-05 loss: 0.0683 (0.0766) time: 3.6353 data: 0.0030 max mem: 19788 +Epoch: [5] [ 570/2138] eta: 1:34:58 lr: 4.4033506240923723e-05 loss: 0.0808 (0.0767) time: 3.6330 data: 0.0030 max mem: 19788 +Epoch: [5] [ 580/2138] eta: 1:34:21 lr: 4.402816945717126e-05 loss: 0.0737 (0.0768) time: 3.6195 data: 0.0029 max mem: 19788 +Epoch: [5] [ 590/2138] eta: 1:33:44 lr: 4.4022832601541477e-05 loss: 0.0700 (0.0768) time: 3.6210 data: 0.0030 max mem: 19788 +Epoch: [5] [ 600/2138] eta: 1:33:08 lr: 4.4017495674023706e-05 loss: 0.0790 (0.0769) time: 3.6274 data: 0.0030 max mem: 19788 +Epoch: [5] [ 610/2138] eta: 1:32:32 lr: 4.4012158674607306e-05 loss: 0.0790 (0.0768) time: 3.6408 data: 0.0029 max mem: 19788 +Epoch: [5] [ 620/2138] eta: 1:31:55 lr: 4.400682160328163e-05 loss: 0.0685 (0.0770) time: 3.6333 data: 0.0029 max mem: 19788 +Epoch: [5] [ 630/2138] eta: 1:31:19 lr: 4.400148446003599e-05 loss: 0.0653 (0.0769) time: 3.6203 data: 0.0030 max mem: 19788 +Epoch: [5] [ 640/2138] eta: 1:30:42 lr: 4.3996147244859755e-05 loss: 0.0611 (0.0768) time: 3.6247 data: 0.0031 max mem: 19788 +Epoch: [5] [ 650/2138] eta: 1:30:06 lr: 4.399080995774224e-05 loss: 0.0582 (0.0765) time: 3.6245 data: 0.0033 max mem: 19788 +Epoch: [5] [ 660/2138] eta: 1:29:29 lr: 4.398547259867278e-05 loss: 0.0667 (0.0766) time: 3.6265 data: 0.0033 max mem: 19788 +Epoch: [5] [ 670/2138] eta: 1:28:53 lr: 4.3980135167640714e-05 loss: 0.0698 (0.0764) time: 3.6387 data: 0.0033 max mem: 19788 +Epoch: [5] [ 680/2138] eta: 1:28:17 lr: 4.3974797664635356e-05 loss: 0.0659 (0.0764) time: 3.6391 data: 0.0031 max mem: 19788 +Epoch: [5] [ 690/2138] eta: 1:27:41 lr: 4.3969460089646034e-05 loss: 0.0682 (0.0764) time: 3.6351 data: 0.0030 max mem: 19788 +Epoch: [5] [ 700/2138] eta: 1:27:04 lr: 4.396412244266207e-05 loss: 0.0776 (0.0766) time: 3.6289 data: 0.0030 max mem: 19788 +Epoch: [5] [ 710/2138] eta: 1:26:28 lr: 4.3958784723672776e-05 loss: 0.0776 (0.0768) time: 3.6284 data: 0.0029 max mem: 19788 +Epoch: [5] [ 720/2138] eta: 1:25:51 lr: 4.395344693266746e-05 loss: 0.0717 (0.0771) time: 3.6284 data: 0.0030 max mem: 19788 +Epoch: [5] [ 730/2138] eta: 1:25:15 lr: 4.394810906963545e-05 loss: 0.0783 (0.0772) time: 3.6267 data: 0.0030 max mem: 19788 +Epoch: [5] [ 740/2138] eta: 1:24:38 lr: 4.394277113456604e-05 loss: 0.0656 (0.0771) time: 3.6266 data: 0.0029 max mem: 19788 +Epoch: [5] [ 750/2138] eta: 1:24:02 lr: 4.3937433127448535e-05 loss: 0.0656 (0.0770) time: 3.6341 data: 0.0029 max mem: 19788 +Epoch: [5] [ 760/2138] eta: 1:23:26 lr: 4.3932095048272244e-05 loss: 0.0783 (0.0771) time: 3.6388 data: 0.0030 max mem: 19788 +Epoch: [5] [ 770/2138] eta: 1:22:50 lr: 4.392675689702646e-05 loss: 0.0722 (0.0769) time: 3.6354 data: 0.0030 max mem: 19788 +Epoch: [5] [ 780/2138] eta: 1:22:13 lr: 4.3921418673700474e-05 loss: 0.0716 (0.0769) time: 3.6412 data: 0.0028 max mem: 19788 +Epoch: [5] [ 790/2138] eta: 1:21:37 lr: 4.391608037828358e-05 loss: 0.0751 (0.0771) time: 3.6308 data: 0.0029 max mem: 19788 +Epoch: [5] [ 800/2138] eta: 1:21:01 lr: 4.391074201076508e-05 loss: 0.0735 (0.0770) time: 3.6360 data: 0.0031 max mem: 19788 +Epoch: [5] [ 810/2138] eta: 1:20:25 lr: 4.390540357113425e-05 loss: 0.0622 (0.0768) time: 3.6451 data: 0.0031 max mem: 19788 +Epoch: [5] [ 820/2138] eta: 1:19:48 lr: 4.390006505938037e-05 loss: 0.0622 (0.0767) time: 3.6410 data: 0.0031 max mem: 19788 +Epoch: [5] [ 830/2138] eta: 1:19:12 lr: 4.389472647549272e-05 loss: 0.0589 (0.0766) time: 3.6373 data: 0.0032 max mem: 19788 +Epoch: [5] [ 840/2138] eta: 1:18:36 lr: 4.388938781946059e-05 loss: 0.0582 (0.0764) time: 3.6314 data: 0.0032 max mem: 19788 +Epoch: [5] [ 850/2138] eta: 1:17:59 lr: 4.388404909127325e-05 loss: 0.0609 (0.0763) time: 3.6282 data: 0.0031 max mem: 19788 +Epoch: [5] [ 860/2138] eta: 1:17:23 lr: 4.387871029091996e-05 loss: 0.0700 (0.0762) time: 3.6249 data: 0.0031 max mem: 19788 +Epoch: [5] [ 870/2138] eta: 1:16:47 lr: 4.387337141838999e-05 loss: 0.0598 (0.0763) time: 3.6402 data: 0.0031 max mem: 19788 +Epoch: [5] [ 880/2138] eta: 1:16:11 lr: 4.386803247367262e-05 loss: 0.0686 (0.0762) time: 3.6504 data: 0.0028 max mem: 19788 +Epoch: [5] [ 890/2138] eta: 1:15:34 lr: 4.3862693456757106e-05 loss: 0.0621 (0.0761) time: 3.6333 data: 0.0030 max mem: 19788 +Epoch: [5] [ 900/2138] eta: 1:14:58 lr: 4.3857354367632694e-05 loss: 0.0726 (0.0764) time: 3.6290 data: 0.0030 max mem: 19788 +Epoch: [5] [ 910/2138] eta: 1:14:21 lr: 4.3852015206288654e-05 loss: 0.0726 (0.0763) time: 3.6303 data: 0.0028 max mem: 19788 +Epoch: [5] [ 920/2138] eta: 1:13:45 lr: 4.384667597271423e-05 loss: 0.0687 (0.0763) time: 3.6248 data: 0.0030 max mem: 19788 +Epoch: [5] [ 930/2138] eta: 1:13:08 lr: 4.3841336666898674e-05 loss: 0.0761 (0.0763) time: 3.6228 data: 0.0029 max mem: 19788 +Epoch: [5] [ 940/2138] eta: 1:12:32 lr: 4.383599728883124e-05 loss: 0.0793 (0.0767) time: 3.6298 data: 0.0027 max mem: 19788 +Epoch: [5] [ 950/2138] eta: 1:11:56 lr: 4.383065783850116e-05 loss: 0.0685 (0.0767) time: 3.6344 data: 0.0030 max mem: 19788 +Epoch: [5] [ 960/2138] eta: 1:11:19 lr: 4.382531831589768e-05 loss: 0.0654 (0.0767) time: 3.6281 data: 0.0033 max mem: 19788 +Epoch: [5] [ 970/2138] eta: 1:10:43 lr: 4.381997872101005e-05 loss: 0.0675 (0.0766) time: 3.6250 data: 0.0033 max mem: 19788 +Epoch: [5] [ 980/2138] eta: 1:10:07 lr: 4.381463905382748e-05 loss: 0.0708 (0.0766) time: 3.6314 data: 0.0030 max mem: 19788 +Epoch: [5] [ 990/2138] eta: 1:09:30 lr: 4.380929931433922e-05 loss: 0.0737 (0.0767) time: 3.6304 data: 0.0030 max mem: 19788 +Epoch: [5] [1000/2138] eta: 1:08:54 lr: 4.380395950253449e-05 loss: 0.0665 (0.0766) time: 3.6320 data: 0.0029 max mem: 19788 +Epoch: [5] [1010/2138] eta: 1:08:18 lr: 4.3798619618402515e-05 loss: 0.0669 (0.0765) time: 3.6339 data: 0.0029 max mem: 19788 +Epoch: [5] [1020/2138] eta: 1:07:41 lr: 4.379327966193252e-05 loss: 0.0727 (0.0764) time: 3.6257 data: 0.0030 max mem: 19788 +Epoch: [5] [1030/2138] eta: 1:07:05 lr: 4.378793963311373e-05 loss: 0.0657 (0.0763) time: 3.6524 data: 0.0030 max mem: 19788 +Epoch: [5] [1040/2138] eta: 1:06:29 lr: 4.378259953193535e-05 loss: 0.0636 (0.0763) time: 3.6584 data: 0.0030 max mem: 19788 +Epoch: [5] [1050/2138] eta: 1:05:53 lr: 4.37772593583866e-05 loss: 0.0687 (0.0763) time: 3.6352 data: 0.0030 max mem: 19788 +Epoch: [5] [1060/2138] eta: 1:05:16 lr: 4.377191911245668e-05 loss: 0.0664 (0.0762) time: 3.6284 data: 0.0028 max mem: 19788 +Epoch: [5] [1070/2138] eta: 1:04:40 lr: 4.376657879413481e-05 loss: 0.0669 (0.0761) time: 3.6274 data: 0.0028 max mem: 19788 +Epoch: [5] [1080/2138] eta: 1:04:04 lr: 4.3761238403410196e-05 loss: 0.0640 (0.0759) time: 3.6308 data: 0.0027 max mem: 19788 +Epoch: [5] [1090/2138] eta: 1:03:27 lr: 4.375589794027203e-05 loss: 0.0555 (0.0758) time: 3.6279 data: 0.0027 max mem: 19788 +Epoch: [5] [1100/2138] eta: 1:02:51 lr: 4.37505574047095e-05 loss: 0.0576 (0.0759) time: 3.6479 data: 0.0027 max mem: 19788 +Epoch: [5] [1110/2138] eta: 1:02:15 lr: 4.3745216796711824e-05 loss: 0.0711 (0.0758) time: 3.6534 data: 0.0027 max mem: 19788 +Epoch: [5] [1120/2138] eta: 1:01:39 lr: 4.373987611626817e-05 loss: 0.0671 (0.0759) time: 3.6403 data: 0.0027 max mem: 19788 +Epoch: [5] [1130/2138] eta: 1:01:02 lr: 4.3734535363367744e-05 loss: 0.0768 (0.0760) time: 3.6423 data: 0.0027 max mem: 19788 +Epoch: [5] [1140/2138] eta: 1:00:26 lr: 4.3729194537999724e-05 loss: 0.0770 (0.0761) time: 3.6337 data: 0.0029 max mem: 19788 +Epoch: [5] [1150/2138] eta: 0:59:50 lr: 4.3723853640153296e-05 loss: 0.0662 (0.0760) time: 3.6319 data: 0.0028 max mem: 19788 +Epoch: [5] [1160/2138] eta: 0:59:13 lr: 4.371851266981763e-05 loss: 0.0623 (0.0760) time: 3.6315 data: 0.0028 max mem: 19788 +Epoch: [5] [1170/2138] eta: 0:58:37 lr: 4.371317162698191e-05 loss: 0.0753 (0.0760) time: 3.6258 data: 0.0029 max mem: 19788 +Epoch: [5] [1180/2138] eta: 0:58:00 lr: 4.370783051163531e-05 loss: 0.0751 (0.0761) time: 3.6311 data: 0.0031 max mem: 19788 +Epoch: [5] [1190/2138] eta: 0:57:24 lr: 4.3702489323766994e-05 loss: 0.0733 (0.0761) time: 3.6315 data: 0.0032 max mem: 19788 +Epoch: [5] [1200/2138] eta: 0:56:48 lr: 4.369714806336614e-05 loss: 0.0723 (0.0761) time: 3.6243 data: 0.0029 max mem: 19788 +Epoch: [5] [1210/2138] eta: 0:56:11 lr: 4.369180673042189e-05 loss: 0.0652 (0.0762) time: 3.6351 data: 0.0027 max mem: 19788 +Epoch: [5] [1220/2138] eta: 0:55:35 lr: 4.368646532492343e-05 loss: 0.0748 (0.0763) time: 3.6380 data: 0.0029 max mem: 19788 +Epoch: [5] [1230/2138] eta: 0:54:59 lr: 4.36811238468599e-05 loss: 0.0769 (0.0763) time: 3.6250 data: 0.0030 max mem: 19788 +Epoch: [5] [1240/2138] eta: 0:54:22 lr: 4.367578229622046e-05 loss: 0.0799 (0.0763) time: 3.6250 data: 0.0029 max mem: 19788 +Epoch: [5] [1250/2138] eta: 0:53:46 lr: 4.3670440672994264e-05 loss: 0.0669 (0.0762) time: 3.6217 data: 0.0028 max mem: 19788 +Epoch: [5] [1260/2138] eta: 0:53:09 lr: 4.366509897717046e-05 loss: 0.0669 (0.0763) time: 3.6211 data: 0.0028 max mem: 19788 +Epoch: [5] [1270/2138] eta: 0:52:33 lr: 4.365975720873819e-05 loss: 0.0753 (0.0762) time: 3.6308 data: 0.0027 max mem: 19788 +Epoch: [5] [1280/2138] eta: 0:51:57 lr: 4.3654415367686595e-05 loss: 0.0582 (0.0761) time: 3.6385 data: 0.0029 max mem: 19788 +Epoch: [5] [1290/2138] eta: 0:51:20 lr: 4.3649073454004816e-05 loss: 0.0679 (0.0762) time: 3.6304 data: 0.0029 max mem: 19788 +Epoch: [5] [1300/2138] eta: 0:50:44 lr: 4.3643731467682e-05 loss: 0.0774 (0.0761) time: 3.6286 data: 0.0028 max mem: 19788 +Epoch: [5] [1310/2138] eta: 0:50:08 lr: 4.363838940870725e-05 loss: 0.0677 (0.0761) time: 3.6361 data: 0.0027 max mem: 19788 +Epoch: [5] [1320/2138] eta: 0:49:31 lr: 4.3633047277069724e-05 loss: 0.0762 (0.0761) time: 3.6309 data: 0.0028 max mem: 19788 +Epoch: [5] [1330/2138] eta: 0:48:55 lr: 4.362770507275854e-05 loss: 0.0681 (0.0760) time: 3.6412 data: 0.0029 max mem: 19788 +Epoch: [5] [1340/2138] eta: 0:48:19 lr: 4.362236279576282e-05 loss: 0.0675 (0.0761) time: 3.6424 data: 0.0029 max mem: 19788 +Epoch: [5] [1350/2138] eta: 0:47:43 lr: 4.361702044607169e-05 loss: 0.0737 (0.0762) time: 3.6334 data: 0.0028 max mem: 19788 +Epoch: [5] [1360/2138] eta: 0:47:06 lr: 4.361167802367426e-05 loss: 0.0661 (0.0761) time: 3.6334 data: 0.0027 max mem: 19788 +Epoch: [5] [1370/2138] eta: 0:46:30 lr: 4.360633552855964e-05 loss: 0.0584 (0.0760) time: 3.6504 data: 0.0027 max mem: 19788 +Epoch: [5] [1380/2138] eta: 0:45:54 lr: 4.360099296071695e-05 loss: 0.0624 (0.0760) time: 3.6475 data: 0.0030 max mem: 19788 +Epoch: [5] [1390/2138] eta: 0:45:17 lr: 4.35956503201353e-05 loss: 0.0778 (0.0760) time: 3.6320 data: 0.0032 max mem: 19788 +Epoch: [5] [1400/2138] eta: 0:44:41 lr: 4.359030760680378e-05 loss: 0.0668 (0.0760) time: 3.6336 data: 0.0029 max mem: 19788 +Epoch: [5] [1410/2138] eta: 0:44:05 lr: 4.3584964820711505e-05 loss: 0.0703 (0.0759) time: 3.6286 data: 0.0028 max mem: 19788 +Epoch: [5] [1420/2138] eta: 0:43:28 lr: 4.3579621961847575e-05 loss: 0.0722 (0.0759) time: 3.6264 data: 0.0028 max mem: 19788 +Epoch: [5] [1430/2138] eta: 0:42:52 lr: 4.3574279030201085e-05 loss: 0.0694 (0.0759) time: 3.6302 data: 0.0027 max mem: 19788 +Epoch: [5] [1440/2138] eta: 0:42:16 lr: 4.356893602576111e-05 loss: 0.0694 (0.0758) time: 3.6387 data: 0.0029 max mem: 19788 +Epoch: [5] [1450/2138] eta: 0:41:39 lr: 4.356359294851676e-05 loss: 0.0610 (0.0758) time: 3.6436 data: 0.0031 max mem: 19788 +Epoch: [5] [1460/2138] eta: 0:41:03 lr: 4.3558249798457105e-05 loss: 0.0621 (0.0757) time: 3.6388 data: 0.0029 max mem: 19788 +Epoch: [5] [1470/2138] eta: 0:40:27 lr: 4.355290657557125e-05 loss: 0.0752 (0.0758) time: 3.6301 data: 0.0027 max mem: 19788 +Epoch: [5] [1480/2138] eta: 0:39:51 lr: 4.354756327984825e-05 loss: 0.0759 (0.0759) time: 3.6477 data: 0.0028 max mem: 19788 +Epoch: [5] [1490/2138] eta: 0:39:14 lr: 4.3542219911277194e-05 loss: 0.0727 (0.0758) time: 3.6465 data: 0.0031 max mem: 19788 +Epoch: [5] [1500/2138] eta: 0:38:38 lr: 4.353687646984716e-05 loss: 0.0626 (0.0758) time: 3.6270 data: 0.0032 max mem: 19788 +Epoch: [5] [1510/2138] eta: 0:38:01 lr: 4.353153295554721e-05 loss: 0.0626 (0.0757) time: 3.6305 data: 0.0030 max mem: 19788 +Epoch: [5] [1520/2138] eta: 0:37:25 lr: 4.35261893683664e-05 loss: 0.0645 (0.0756) time: 3.6344 data: 0.0028 max mem: 19788 +Epoch: [5] [1530/2138] eta: 0:36:49 lr: 4.352084570829383e-05 loss: 0.0645 (0.0756) time: 3.6378 data: 0.0028 max mem: 19788 +Epoch: [5] [1540/2138] eta: 0:36:12 lr: 4.351550197531852e-05 loss: 0.0677 (0.0755) time: 3.6364 data: 0.0029 max mem: 19788 +Epoch: [5] [1550/2138] eta: 0:35:36 lr: 4.351015816942957e-05 loss: 0.0688 (0.0755) time: 3.6389 data: 0.0029 max mem: 19788 +Epoch: [5] [1560/2138] eta: 0:35:00 lr: 4.350481429061599e-05 loss: 0.0688 (0.0755) time: 3.6332 data: 0.0029 max mem: 19788 +Epoch: [5] [1570/2138] eta: 0:34:23 lr: 4.3499470338866864e-05 loss: 0.0701 (0.0755) time: 3.6309 data: 0.0028 max mem: 19788 +Epoch: [5] [1580/2138] eta: 0:33:47 lr: 4.349412631417123e-05 loss: 0.0724 (0.0755) time: 3.6332 data: 0.0027 max mem: 19788 +Epoch: [5] [1590/2138] eta: 0:33:11 lr: 4.348878221651813e-05 loss: 0.0597 (0.0754) time: 3.6262 data: 0.0029 max mem: 19788 +Epoch: [5] [1600/2138] eta: 0:32:34 lr: 4.3483438045896604e-05 loss: 0.0679 (0.0755) time: 3.6267 data: 0.0029 max mem: 19788 +Epoch: [5] [1610/2138] eta: 0:31:58 lr: 4.34780938022957e-05 loss: 0.0680 (0.0754) time: 3.6261 data: 0.0030 max mem: 19788 +Epoch: [5] [1620/2138] eta: 0:31:22 lr: 4.3472749485704456e-05 loss: 0.0598 (0.0753) time: 3.6265 data: 0.0032 max mem: 19788 +Epoch: [5] [1630/2138] eta: 0:30:45 lr: 4.34674050961119e-05 loss: 0.0619 (0.0753) time: 3.6335 data: 0.0029 max mem: 19788 +Epoch: [5] [1640/2138] eta: 0:30:09 lr: 4.346206063350705e-05 loss: 0.0670 (0.0753) time: 3.6522 data: 0.0027 max mem: 19788 +Epoch: [5] [1650/2138] eta: 0:29:33 lr: 4.345671609787895e-05 loss: 0.0577 (0.0752) time: 3.6591 data: 0.0027 max mem: 19788 +Epoch: [5] [1660/2138] eta: 0:28:56 lr: 4.345137148921662e-05 loss: 0.0582 (0.0752) time: 3.6449 data: 0.0030 max mem: 19788 +Epoch: [5] [1670/2138] eta: 0:28:20 lr: 4.344602680750907e-05 loss: 0.0550 (0.0750) time: 3.6316 data: 0.0033 max mem: 19788 +Epoch: [5] [1680/2138] eta: 0:27:44 lr: 4.344068205274533e-05 loss: 0.0563 (0.0750) time: 3.6373 data: 0.0030 max mem: 19788 +Epoch: [5] [1690/2138] eta: 0:27:07 lr: 4.343533722491441e-05 loss: 0.0697 (0.0751) time: 3.6324 data: 0.0031 max mem: 19788 +Epoch: [5] [1700/2138] eta: 0:26:31 lr: 4.3429992324005316e-05 loss: 0.0697 (0.0751) time: 3.6261 data: 0.0029 max mem: 19788 +Epoch: [5] [1710/2138] eta: 0:25:55 lr: 4.3424647350007044e-05 loss: 0.0679 (0.0751) time: 3.6323 data: 0.0027 max mem: 19788 +Epoch: [5] [1720/2138] eta: 0:25:18 lr: 4.341930230290863e-05 loss: 0.0588 (0.0750) time: 3.6263 data: 0.0027 max mem: 19788 +Epoch: [5] [1730/2138] eta: 0:24:42 lr: 4.341395718269905e-05 loss: 0.0539 (0.0750) time: 3.6223 data: 0.0027 max mem: 19788 +Epoch: [5] [1740/2138] eta: 0:24:06 lr: 4.340861198936731e-05 loss: 0.0583 (0.0749) time: 3.6331 data: 0.0027 max mem: 19788 +Epoch: [5] [1750/2138] eta: 0:23:29 lr: 4.340326672290241e-05 loss: 0.0664 (0.0749) time: 3.6401 data: 0.0029 max mem: 19788 +Epoch: [5] [1760/2138] eta: 0:22:53 lr: 4.339792138329333e-05 loss: 0.0738 (0.0749) time: 3.6424 data: 0.0031 max mem: 19788 +Epoch: [5] [1770/2138] eta: 0:22:17 lr: 4.339257597052907e-05 loss: 0.0599 (0.0749) time: 3.7470 data: 0.0030 max mem: 19788 +Epoch: [5] [1780/2138] eta: 0:21:41 lr: 4.3387230484598614e-05 loss: 0.0552 (0.0748) time: 3.8450 data: 0.0031 max mem: 19788 +Epoch: [5] [1790/2138] eta: 0:21:06 lr: 4.338188492549093e-05 loss: 0.0640 (0.0748) time: 4.0581 data: 0.0033 max mem: 19788 +Epoch: [5] [1800/2138] eta: 0:20:31 lr: 4.3376539293195014e-05 loss: 0.0718 (0.0749) time: 4.3175 data: 0.0034 max mem: 19788 +Epoch: [5] [1810/2138] eta: 0:19:56 lr: 4.3371193587699834e-05 loss: 0.0760 (0.0749) time: 4.3996 data: 0.0033 max mem: 19788 +Epoch: [5] [1820/2138] eta: 0:19:21 lr: 4.336584780899437e-05 loss: 0.0683 (0.0748) time: 4.3918 data: 0.0033 max mem: 19788 +Epoch: [5] [1830/2138] eta: 0:18:45 lr: 4.336050195706758e-05 loss: 0.0616 (0.0748) time: 4.3287 data: 0.0034 max mem: 19788 +Epoch: [5] [1840/2138] eta: 0:18:09 lr: 4.335515603190844e-05 loss: 0.0553 (0.0748) time: 4.1529 data: 0.0034 max mem: 19788 +Epoch: [5] [1850/2138] eta: 0:17:34 lr: 4.33498100335059e-05 loss: 0.0590 (0.0748) time: 4.1004 data: 0.0036 max mem: 19788 +Epoch: [5] [1860/2138] eta: 0:16:58 lr: 4.3344463961848945e-05 loss: 0.0687 (0.0749) time: 4.1326 data: 0.0036 max mem: 19788 +Epoch: [5] [1870/2138] eta: 0:16:22 lr: 4.333911781692651e-05 loss: 0.0818 (0.0749) time: 4.0831 data: 0.0033 max mem: 19788 +Epoch: [5] [1880/2138] eta: 0:15:46 lr: 4.333377159872756e-05 loss: 0.0711 (0.0749) time: 4.0568 data: 0.0033 max mem: 19788 +Epoch: [5] [1890/2138] eta: 0:15:09 lr: 4.3328425307241034e-05 loss: 0.0635 (0.0748) time: 4.0852 data: 0.0035 max mem: 19788 +Epoch: [5] [1900/2138] eta: 0:14:33 lr: 4.332307894245589e-05 loss: 0.0602 (0.0748) time: 4.0733 data: 0.0034 max mem: 19788 +Epoch: [5] [1910/2138] eta: 0:13:57 lr: 4.331773250436107e-05 loss: 0.0597 (0.0747) time: 4.0843 data: 0.0033 max mem: 19788 +Epoch: [5] [1920/2138] eta: 0:13:21 lr: 4.3312385992945514e-05 loss: 0.0559 (0.0747) time: 4.1276 data: 0.0034 max mem: 19788 +Epoch: [5] [1930/2138] eta: 0:12:45 lr: 4.330703940819815e-05 loss: 0.0602 (0.0748) time: 4.1145 data: 0.0035 max mem: 19788 +Epoch: [5] [1940/2138] eta: 0:12:08 lr: 4.330169275010793e-05 loss: 0.0699 (0.0748) time: 4.1299 data: 0.0036 max mem: 19788 +Epoch: [5] [1950/2138] eta: 0:11:32 lr: 4.329634601866378e-05 loss: 0.0662 (0.0748) time: 4.0388 data: 0.0033 max mem: 19788 +Epoch: [5] [1960/2138] eta: 0:10:55 lr: 4.329099921385463e-05 loss: 0.0610 (0.0747) time: 4.1080 data: 0.0033 max mem: 19788 +Epoch: [5] [1970/2138] eta: 0:10:19 lr: 4.328565233566939e-05 loss: 0.0610 (0.0747) time: 4.1644 data: 0.0034 max mem: 19788 +Epoch: [5] [1980/2138] eta: 0:09:43 lr: 4.3280305384097e-05 loss: 0.0604 (0.0747) time: 4.3413 data: 0.0033 max mem: 19788 +Epoch: [5] [1990/2138] eta: 0:09:06 lr: 4.3274958359126364e-05 loss: 0.0605 (0.0747) time: 4.3322 data: 0.0034 max mem: 19788 +Epoch: [5] [2000/2138] eta: 0:08:30 lr: 4.326961126074641e-05 loss: 0.0748 (0.0747) time: 4.2111 data: 0.0034 max mem: 19788 +Epoch: [5] [2010/2138] eta: 0:07:53 lr: 4.326426408894604e-05 loss: 0.0731 (0.0746) time: 4.3441 data: 0.0033 max mem: 19788 +Epoch: [5] [2020/2138] eta: 0:07:16 lr: 4.3258916843714174e-05 loss: 0.0677 (0.0746) time: 4.2894 data: 0.0033 max mem: 19788 +Epoch: [5] [2030/2138] eta: 0:06:40 lr: 4.3253569525039705e-05 loss: 0.0618 (0.0746) time: 4.1225 data: 0.0036 max mem: 19788 +Epoch: [5] [2040/2138] eta: 0:06:03 lr: 4.3248222132911555e-05 loss: 0.0553 (0.0745) time: 4.1197 data: 0.0036 max mem: 19788 +Epoch: [5] [2050/2138] eta: 0:05:26 lr: 4.32428746673186e-05 loss: 0.0672 (0.0746) time: 4.1065 data: 0.0036 max mem: 19788 +Epoch: [5] [2060/2138] eta: 0:04:49 lr: 4.323752712824975e-05 loss: 0.0713 (0.0746) time: 4.0348 data: 0.0037 max mem: 19788 +Epoch: [5] [2070/2138] eta: 0:04:12 lr: 4.323217951569389e-05 loss: 0.0651 (0.0745) time: 4.0400 data: 0.0036 max mem: 19788 +Epoch: [5] [2080/2138] eta: 0:03:35 lr: 4.322683182963993e-05 loss: 0.0651 (0.0745) time: 4.0171 data: 0.0036 max mem: 19788 +Epoch: [5] [2090/2138] eta: 0:02:58 lr: 4.322148407007673e-05 loss: 0.0636 (0.0744) time: 3.9865 data: 0.0035 max mem: 19788 +Epoch: [5] [2100/2138] eta: 0:02:21 lr: 4.321613623699319e-05 loss: 0.0566 (0.0744) time: 3.9212 data: 0.0035 max mem: 19788 +Epoch: [5] [2110/2138] eta: 0:01:44 lr: 4.321078833037819e-05 loss: 0.0646 (0.0745) time: 4.1223 data: 0.0036 max mem: 19788 +Epoch: [5] [2120/2138] eta: 0:01:06 lr: 4.320544035022059e-05 loss: 0.0658 (0.0744) time: 4.3372 data: 0.0036 max mem: 19788 +Epoch: [5] [2130/2138] eta: 0:00:29 lr: 4.3200092296509295e-05 loss: 0.0645 (0.0744) time: 4.1603 data: 0.0034 max mem: 19788 +Epoch: [5] Total time: 2:12:39 +Test: [ 0/21770] eta: 19:49:34 time: 3.2786 data: 3.1623 max mem: 19788 +Test: [ 100/21770] eta: 0:41:13 time: 0.0866 data: 0.0027 max mem: 19788 +Test: [ 200/21770] eta: 0:34:24 time: 0.0662 data: 0.0022 max mem: 19788 +Test: [ 300/21770] eta: 0:30:59 time: 0.0782 data: 0.0022 max mem: 19788 +Test: [ 400/21770] eta: 0:29:52 time: 0.0695 data: 0.0021 max mem: 19788 +Test: [ 500/21770] eta: 0:28:33 time: 0.0658 data: 0.0020 max mem: 19788 +Test: [ 600/21770] eta: 0:27:49 time: 0.0871 data: 0.0027 max mem: 19788 +Test: [ 700/21770] eta: 0:27:54 time: 0.0668 data: 0.0021 max mem: 19788 +Test: [ 800/21770] eta: 0:27:42 time: 0.0651 data: 0.0024 max mem: 19788 +Test: [ 900/21770] eta: 0:27:02 time: 0.0675 data: 0.0020 max mem: 19788 +Test: [ 1000/21770] eta: 0:26:32 time: 0.0723 data: 0.0022 max mem: 19788 +Test: [ 1100/21770] eta: 0:26:05 time: 0.0656 data: 0.0021 max mem: 19788 +Test: [ 1200/21770] eta: 0:25:39 time: 0.0620 data: 0.0021 max mem: 19788 +Test: [ 1300/21770] eta: 0:25:21 time: 0.0717 data: 0.0021 max mem: 19788 +Test: [ 1400/21770] eta: 0:25:26 time: 0.0862 data: 0.0027 max mem: 19788 +Test: [ 1500/21770] eta: 0:25:29 time: 0.0809 data: 0.0022 max mem: 19788 +Test: [ 1600/21770] eta: 0:25:26 time: 0.0874 data: 0.0026 max mem: 19788 +Test: [ 1700/21770] eta: 0:25:14 time: 0.0772 data: 0.0024 max mem: 19788 +Test: [ 1800/21770] eta: 0:25:09 time: 0.0653 data: 0.0022 max mem: 19788 +Test: [ 1900/21770] eta: 0:24:52 time: 0.0648 data: 0.0022 max mem: 19788 +Test: [ 2000/21770] eta: 0:24:35 time: 0.0650 data: 0.0019 max mem: 19788 +Test: [ 2100/21770] eta: 0:24:18 time: 0.0644 data: 0.0022 max mem: 19788 +Test: [ 2200/21770] eta: 0:24:04 time: 0.0663 data: 0.0022 max mem: 19788 +Test: [ 2300/21770] eta: 0:23:52 time: 0.0828 data: 0.0023 max mem: 19788 +Test: [ 2400/21770] eta: 0:23:44 time: 0.0698 data: 0.0021 max mem: 19788 +Test: [ 2500/21770] eta: 0:23:47 time: 0.0903 data: 0.0024 max mem: 19788 +Test: [ 2600/21770] eta: 0:23:45 time: 0.0809 data: 0.0023 max mem: 19788 +Test: [ 2700/21770] eta: 0:23:36 time: 0.0675 data: 0.0021 max mem: 19788 +Test: [ 2800/21770] eta: 0:23:33 time: 0.0868 data: 0.0027 max mem: 19788 +Test: [ 2900/21770] eta: 0:23:28 time: 0.0788 data: 0.0023 max mem: 19788 +Test: [ 3000/21770] eta: 0:23:19 time: 0.0742 data: 0.0023 max mem: 19788 +Test: [ 3100/21770] eta: 0:23:08 time: 0.0678 data: 0.0021 max mem: 19788 +Test: [ 3200/21770] eta: 0:22:56 time: 0.0704 data: 0.0023 max mem: 19788 +Test: [ 3300/21770] eta: 0:22:53 time: 0.0801 data: 0.0024 max mem: 19788 +Test: [ 3400/21770] eta: 0:22:47 time: 0.0870 data: 0.0029 max mem: 19788 +Test: [ 3500/21770] eta: 0:22:38 time: 0.0693 data: 0.0022 max mem: 19788 +Test: [ 3600/21770] eta: 0:22:26 time: 0.0667 data: 0.0020 max mem: 19788 +Test: [ 3700/21770] eta: 0:22:16 time: 0.0647 data: 0.0018 max mem: 19788 +Test: [ 3800/21770] eta: 0:22:12 time: 0.0766 data: 0.0023 max mem: 19788 +Test: [ 3900/21770] eta: 0:22:08 time: 0.0746 data: 0.0024 max mem: 19788 +Test: [ 4000/21770] eta: 0:22:04 time: 0.0709 data: 0.0022 max mem: 19788 +Test: [ 4100/21770] eta: 0:21:57 time: 0.0826 data: 0.0026 max mem: 19788 +Test: [ 4200/21770] eta: 0:21:55 time: 0.0877 data: 0.0029 max mem: 19788 +Test: [ 4300/21770] eta: 0:21:53 time: 0.0869 data: 0.0028 max mem: 19788 +Test: [ 4400/21770] eta: 0:21:43 time: 0.0673 data: 0.0023 max mem: 19788 +Test: [ 4500/21770] eta: 0:21:41 time: 0.0862 data: 0.0027 max mem: 19788 +Test: [ 4600/21770] eta: 0:21:31 time: 0.0687 data: 0.0020 max mem: 19788 +Test: [ 4700/21770] eta: 0:21:22 time: 0.0741 data: 0.0023 max mem: 19788 +Test: [ 4800/21770] eta: 0:21:13 time: 0.0746 data: 0.0021 max mem: 19788 +Test: [ 4900/21770] eta: 0:21:03 time: 0.0687 data: 0.0020 max mem: 19788 +Test: [ 5000/21770] eta: 0:20:55 time: 0.0646 data: 0.0021 max mem: 19788 +Test: [ 5100/21770] eta: 0:20:45 time: 0.0655 data: 0.0019 max mem: 19788 +Test: [ 5200/21770] eta: 0:20:36 time: 0.0648 data: 0.0023 max mem: 19788 +Test: [ 5300/21770] eta: 0:20:29 time: 0.0643 data: 0.0021 max mem: 19788 +Test: [ 5400/21770] eta: 0:20:18 time: 0.0633 data: 0.0019 max mem: 19788 +Test: [ 5500/21770] eta: 0:20:08 time: 0.0645 data: 0.0018 max mem: 19788 +Test: [ 5600/21770] eta: 0:20:02 time: 0.0838 data: 0.0024 max mem: 19788 +Test: [ 5700/21770] eta: 0:19:54 time: 0.0643 data: 0.0020 max mem: 19788 +Test: [ 5800/21770] eta: 0:19:43 time: 0.0616 data: 0.0019 max mem: 19788 +Test: [ 5900/21770] eta: 0:19:36 time: 0.0689 data: 0.0020 max mem: 19788 +Test: [ 6000/21770] eta: 0:19:31 time: 0.0832 data: 0.0026 max mem: 19788 +Test: [ 6100/21770] eta: 0:19:26 time: 0.0833 data: 0.0027 max mem: 19788 +Test: [ 6200/21770] eta: 0:19:21 time: 0.0833 data: 0.0026 max mem: 19788 +Test: [ 6300/21770] eta: 0:19:15 time: 0.0842 data: 0.0025 max mem: 19788 +Test: [ 6400/21770] eta: 0:19:10 time: 0.0847 data: 0.0024 max mem: 19788 +Test: [ 6500/21770] eta: 0:19:05 time: 0.0817 data: 0.0023 max mem: 19788 +Test: [ 6600/21770] eta: 0:18:57 time: 0.0830 data: 0.0024 max mem: 19788 +Test: [ 6700/21770] eta: 0:18:50 time: 0.0614 data: 0.0017 max mem: 19788 +Test: [ 6800/21770] eta: 0:18:40 time: 0.0658 data: 0.0019 max mem: 19788 +Test: [ 6900/21770] eta: 0:18:32 time: 0.0622 data: 0.0017 max mem: 19788 +Test: [ 7000/21770] eta: 0:18:23 time: 0.0612 data: 0.0017 max mem: 19788 +Test: [ 7100/21770] eta: 0:18:13 time: 0.0610 data: 0.0018 max mem: 19788 +Test: [ 7200/21770] eta: 0:18:04 time: 0.0623 data: 0.0019 max mem: 19788 +Test: [ 7300/21770] eta: 0:17:54 time: 0.0646 data: 0.0019 max mem: 19788 +Test: [ 7400/21770] eta: 0:17:45 time: 0.0615 data: 0.0019 max mem: 19788 +Test: [ 7500/21770] eta: 0:17:35 time: 0.0614 data: 0.0018 max mem: 19788 +Test: [ 7600/21770] eta: 0:17:26 time: 0.0618 data: 0.0018 max mem: 19788 +Test: [ 7700/21770] eta: 0:17:17 time: 0.0634 data: 0.0017 max mem: 19788 +Test: [ 7800/21770] eta: 0:17:09 time: 0.0764 data: 0.0021 max mem: 19788 +Test: [ 7900/21770] eta: 0:17:01 time: 0.0641 data: 0.0020 max mem: 19788 +Test: [ 8000/21770] eta: 0:16:54 time: 0.0686 data: 0.0020 max mem: 19788 +Test: [ 8100/21770] eta: 0:16:45 time: 0.0742 data: 0.0021 max mem: 19788 +Test: [ 8200/21770] eta: 0:16:38 time: 0.0624 data: 0.0019 max mem: 19788 +Test: [ 8300/21770] eta: 0:16:29 time: 0.0648 data: 0.0019 max mem: 19788 +Test: [ 8400/21770] eta: 0:16:22 time: 0.0656 data: 0.0020 max mem: 19788 +Test: [ 8500/21770] eta: 0:16:14 time: 0.0660 data: 0.0018 max mem: 19788 +Test: [ 8600/21770] eta: 0:16:06 time: 0.0620 data: 0.0019 max mem: 19788 +Test: [ 8700/21770] eta: 0:15:58 time: 0.0789 data: 0.0020 max mem: 19788 +Test: [ 8800/21770] eta: 0:15:49 time: 0.0600 data: 0.0017 max mem: 19788 +Test: [ 8900/21770] eta: 0:15:40 time: 0.0645 data: 0.0018 max mem: 19788 +Test: [ 9000/21770] eta: 0:15:34 time: 0.0824 data: 0.0019 max mem: 19788 +Test: [ 9100/21770] eta: 0:15:27 time: 0.0831 data: 0.0019 max mem: 19788 +Test: [ 9200/21770] eta: 0:15:21 time: 0.0817 data: 0.0025 max mem: 19788 +Test: [ 9300/21770] eta: 0:15:14 time: 0.0823 data: 0.0020 max mem: 19788 +Test: [ 9400/21770] eta: 0:15:06 time: 0.0638 data: 0.0020 max mem: 19788 +Test: [ 9500/21770] eta: 0:14:58 time: 0.0612 data: 0.0019 max mem: 19788 +Test: [ 9600/21770] eta: 0:14:52 time: 0.0816 data: 0.0025 max mem: 19788 +Test: [ 9700/21770] eta: 0:14:44 time: 0.0651 data: 0.0019 max mem: 19788 +Test: [ 9800/21770] eta: 0:14:38 time: 0.0818 data: 0.0025 max mem: 19788 +Test: [ 9900/21770] eta: 0:14:30 time: 0.0729 data: 0.0023 max mem: 19788 +Test: [10000/21770] eta: 0:14:22 time: 0.0612 data: 0.0019 max mem: 19788 +Test: [10100/21770] eta: 0:14:14 time: 0.0635 data: 0.0020 max mem: 19788 +Test: [10200/21770] eta: 0:14:06 time: 0.0649 data: 0.0018 max mem: 19788 +Test: [10300/21770] eta: 0:13:58 time: 0.0698 data: 0.0018 max mem: 19788 +Test: [10400/21770] eta: 0:13:51 time: 0.0760 data: 0.0022 max mem: 19788 +Test: [10500/21770] eta: 0:13:43 time: 0.0608 data: 0.0018 max mem: 19788 +Test: [10600/21770] eta: 0:13:35 time: 0.0630 data: 0.0018 max mem: 19788 +Test: [10700/21770] eta: 0:13:27 time: 0.0652 data: 0.0020 max mem: 19788 +Test: [10800/21770] eta: 0:13:19 time: 0.0730 data: 0.0019 max mem: 19788 +Test: [10900/21770] eta: 0:13:13 time: 0.0826 data: 0.0026 max mem: 19788 +Test: [11000/21770] eta: 0:13:05 time: 0.0622 data: 0.0019 max mem: 19788 +Test: [11100/21770] eta: 0:12:57 time: 0.0833 data: 0.0025 max mem: 19788 +Test: [11200/21770] eta: 0:12:49 time: 0.0663 data: 0.0020 max mem: 19788 +Test: [11300/21770] eta: 0:12:43 time: 0.0757 data: 0.0025 max mem: 19788 +Test: [11400/21770] eta: 0:12:35 time: 0.0632 data: 0.0018 max mem: 19788 +Test: [11500/21770] eta: 0:12:28 time: 0.0664 data: 0.0021 max mem: 19788 +Test: [11600/21770] eta: 0:12:20 time: 0.0814 data: 0.0025 max mem: 19788 +Test: [11700/21770] eta: 0:12:13 time: 0.0736 data: 0.0019 max mem: 19788 +Test: [11800/21770] eta: 0:12:06 time: 0.0649 data: 0.0019 max mem: 19788 +Test: [11900/21770] eta: 0:11:58 time: 0.0804 data: 0.0024 max mem: 19788 +Test: [12000/21770] eta: 0:11:50 time: 0.0637 data: 0.0020 max mem: 19788 +Test: [12100/21770] eta: 0:11:43 time: 0.0752 data: 0.0018 max mem: 19788 +Test: [12200/21770] eta: 0:11:36 time: 0.0695 data: 0.0020 max mem: 19788 +Test: [12300/21770] eta: 0:11:28 time: 0.0796 data: 0.0020 max mem: 19788 +Test: [12400/21770] eta: 0:11:21 time: 0.0650 data: 0.0018 max mem: 19788 +Test: [12500/21770] eta: 0:11:13 time: 0.0654 data: 0.0019 max mem: 19788 +Test: [12600/21770] eta: 0:11:05 time: 0.0772 data: 0.0023 max mem: 19788 +Test: [12700/21770] eta: 0:10:58 time: 0.0623 data: 0.0018 max mem: 19788 +Test: [12800/21770] eta: 0:10:50 time: 0.0833 data: 0.0018 max mem: 19788 +Test: [12900/21770] eta: 0:10:43 time: 0.0568 data: 0.0018 max mem: 19788 +Test: [13000/21770] eta: 0:10:35 time: 0.0816 data: 0.0024 max mem: 19788 +Test: [13100/21770] eta: 0:10:28 time: 0.0680 data: 0.0020 max mem: 19788 +Test: [13200/21770] eta: 0:10:21 time: 0.0763 data: 0.0022 max mem: 19788 +Test: [13300/21770] eta: 0:10:14 time: 0.0693 data: 0.0020 max mem: 19788 +Test: [13400/21770] eta: 0:10:07 time: 0.0820 data: 0.0019 max mem: 19788 +Test: [13500/21770] eta: 0:10:00 time: 0.0773 data: 0.0022 max mem: 19788 +Test: [13600/21770] eta: 0:09:52 time: 0.0658 data: 0.0020 max mem: 19788 +Test: [13700/21770] eta: 0:09:44 time: 0.0630 data: 0.0017 max mem: 19788 +Test: [13800/21770] eta: 0:09:37 time: 0.0635 data: 0.0016 max mem: 19788 +Test: [13900/21770] eta: 0:09:29 time: 0.0719 data: 0.0022 max mem: 19788 +Test: [14000/21770] eta: 0:09:22 time: 0.0774 data: 0.0022 max mem: 19788 +Test: [14100/21770] eta: 0:09:14 time: 0.0808 data: 0.0023 max mem: 19788 +Test: [14200/21770] eta: 0:09:07 time: 0.0819 data: 0.0019 max mem: 19788 +Test: [14300/21770] eta: 0:09:00 time: 0.0696 data: 0.0020 max mem: 19788 +Test: [14400/21770] eta: 0:08:52 time: 0.0773 data: 0.0019 max mem: 19788 +Test: [14500/21770] eta: 0:08:44 time: 0.0664 data: 0.0019 max mem: 19788 +Test: [14600/21770] eta: 0:08:37 time: 0.0705 data: 0.0020 max mem: 19788 +Test: [14700/21770] eta: 0:08:30 time: 0.0693 data: 0.0020 max mem: 19788 +Test: [14800/21770] eta: 0:08:22 time: 0.0785 data: 0.0024 max mem: 19788 +Test: [14900/21770] eta: 0:08:15 time: 0.0764 data: 0.0020 max mem: 19788 +Test: [15000/21770] eta: 0:08:08 time: 0.0682 data: 0.0018 max mem: 19788 +Test: [15100/21770] eta: 0:08:00 time: 0.0600 data: 0.0018 max mem: 19788 +Test: [15200/21770] eta: 0:07:53 time: 0.0726 data: 0.0020 max mem: 19788 +Test: [15300/21770] eta: 0:07:45 time: 0.0614 data: 0.0018 max mem: 19788 +Test: [15400/21770] eta: 0:07:38 time: 0.0616 data: 0.0018 max mem: 19788 +Test: [15500/21770] eta: 0:07:30 time: 0.0644 data: 0.0020 max mem: 19788 +Test: [15600/21770] eta: 0:07:23 time: 0.0670 data: 0.0018 max mem: 19788 +Test: [15700/21770] eta: 0:07:15 time: 0.0674 data: 0.0020 max mem: 19788 +Test: [15800/21770] eta: 0:07:08 time: 0.0682 data: 0.0021 max mem: 19788 +Test: [15900/21770] eta: 0:07:01 time: 0.0619 data: 0.0018 max mem: 19788 +Test: [16000/21770] eta: 0:06:53 time: 0.0624 data: 0.0017 max mem: 19788 +Test: [16100/21770] eta: 0:06:46 time: 0.0636 data: 0.0018 max mem: 19788 +Test: [16200/21770] eta: 0:06:39 time: 0.0625 data: 0.0018 max mem: 19788 +Test: [16300/21770] eta: 0:06:31 time: 0.0735 data: 0.0021 max mem: 19788 +Test: [16400/21770] eta: 0:06:24 time: 0.0619 data: 0.0018 max mem: 19788 +Test: [16500/21770] eta: 0:06:17 time: 0.0644 data: 0.0018 max mem: 19788 +Test: [16600/21770] eta: 0:06:09 time: 0.0746 data: 0.0022 max mem: 19788 +Test: [16700/21770] eta: 0:06:02 time: 0.0607 data: 0.0017 max mem: 19788 +Test: [16800/21770] eta: 0:05:55 time: 0.0744 data: 0.0021 max mem: 19788 +Test: [16900/21770] eta: 0:05:48 time: 0.0757 data: 0.0022 max mem: 19788 +Test: [17000/21770] eta: 0:05:40 time: 0.0615 data: 0.0017 max mem: 19788 +Test: [17100/21770] eta: 0:05:33 time: 0.0648 data: 0.0018 max mem: 19788 +Test: [17200/21770] eta: 0:05:26 time: 0.0633 data: 0.0018 max mem: 19788 +Test: [17300/21770] eta: 0:05:19 time: 0.0815 data: 0.0019 max mem: 19788 +Test: [17400/21770] eta: 0:05:12 time: 0.0787 data: 0.0022 max mem: 19788 +Test: [17500/21770] eta: 0:05:04 time: 0.0617 data: 0.0018 max mem: 19788 +Test: [17600/21770] eta: 0:04:57 time: 0.0624 data: 0.0017 max mem: 19788 +Test: [17700/21770] eta: 0:04:50 time: 0.0619 data: 0.0018 max mem: 19788 +Test: [17800/21770] eta: 0:04:43 time: 0.0747 data: 0.0018 max mem: 19788 +Test: [17900/21770] eta: 0:04:35 time: 0.0603 data: 0.0018 max mem: 19788 +Test: [18000/21770] eta: 0:04:28 time: 0.0803 data: 0.0024 max mem: 19788 +Test: [18100/21770] eta: 0:04:21 time: 0.0633 data: 0.0018 max mem: 19788 +Test: [18200/21770] eta: 0:04:14 time: 0.0667 data: 0.0019 max mem: 19788 +Test: [18300/21770] eta: 0:04:07 time: 0.0809 data: 0.0024 max mem: 19788 +Test: [18400/21770] eta: 0:04:00 time: 0.0819 data: 0.0026 max mem: 19788 +Test: [18500/21770] eta: 0:03:53 time: 0.0753 data: 0.0022 max mem: 19788 +Test: [18600/21770] eta: 0:03:46 time: 0.0658 data: 0.0019 max mem: 19788 +Test: [18700/21770] eta: 0:03:39 time: 0.0811 data: 0.0021 max mem: 19788 +Test: [18800/21770] eta: 0:03:31 time: 0.0658 data: 0.0019 max mem: 19788 +Test: [18900/21770] eta: 0:03:24 time: 0.0623 data: 0.0020 max mem: 19788 +Test: [19000/21770] eta: 0:03:17 time: 0.0688 data: 0.0021 max mem: 19788 +Test: [19100/21770] eta: 0:03:10 time: 0.0830 data: 0.0021 max mem: 19788 +Test: [19200/21770] eta: 0:03:03 time: 0.0649 data: 0.0020 max mem: 19788 +Test: [19300/21770] eta: 0:02:56 time: 0.0743 data: 0.0022 max mem: 19788 +Test: [19400/21770] eta: 0:02:48 time: 0.0692 data: 0.0022 max mem: 19788 +Test: [19500/21770] eta: 0:02:41 time: 0.0610 data: 0.0017 max mem: 19788 +Test: [19600/21770] eta: 0:02:34 time: 0.0650 data: 0.0019 max mem: 19788 +Test: [19700/21770] eta: 0:02:27 time: 0.0630 data: 0.0018 max mem: 19788 +Test: [19800/21770] eta: 0:02:20 time: 0.0611 data: 0.0020 max mem: 19788 +Test: [19900/21770] eta: 0:02:13 time: 0.0674 data: 0.0020 max mem: 19788 +Test: [20000/21770] eta: 0:02:06 time: 0.0715 data: 0.0021 max mem: 19788 +Test: [20100/21770] eta: 0:01:58 time: 0.0772 data: 0.0023 max mem: 19788 +Test: [20200/21770] eta: 0:01:51 time: 0.0773 data: 0.0025 max mem: 19788 +Test: [20300/21770] eta: 0:01:44 time: 0.0767 data: 0.0025 max mem: 19788 +Test: [20400/21770] eta: 0:01:37 time: 0.0721 data: 0.0025 max mem: 19788 +Test: [20500/21770] eta: 0:01:30 time: 0.0812 data: 0.0025 max mem: 19788 +Test: [20600/21770] eta: 0:01:23 time: 0.0871 data: 0.0026 max mem: 19788 +Test: [20700/21770] eta: 0:01:16 time: 0.0846 data: 0.0023 max mem: 19788 +Test: [20800/21770] eta: 0:01:09 time: 0.0756 data: 0.0024 max mem: 19788 +Test: [20900/21770] eta: 0:01:02 time: 0.0677 data: 0.0021 max mem: 19788 +Test: [21000/21770] eta: 0:00:55 time: 0.0719 data: 0.0024 max mem: 19788 +Test: [21100/21770] eta: 0:00:48 time: 0.0702 data: 0.0023 max mem: 19788 +Test: [21200/21770] eta: 0:00:40 time: 0.0691 data: 0.0023 max mem: 19788 +Test: [21300/21770] eta: 0:00:33 time: 0.0870 data: 0.0026 max mem: 19788 +Test: [21400/21770] eta: 0:00:26 time: 0.0873 data: 0.0028 max mem: 19788 +Test: [21500/21770] eta: 0:00:19 time: 0.0675 data: 0.0021 max mem: 19788 +Test: [21600/21770] eta: 0:00:12 time: 0.0722 data: 0.0024 max mem: 19788 +Test: [21700/21770] eta: 0:00:05 time: 0.0695 data: 0.0021 max mem: 19788 +Test: Total time: 0:26:01 +Final results: +Mean IoU is 58.98 + + precision@0.5 = 65.30 + precision@0.6 = 59.32 + precision@0.7 = 52.27 + precision@0.8 = 41.25 + precision@0.9 = 19.16 + overall IoU = 61.39 + mean IoU = 58.98 + +Mean accuracy for one-to-zero sample is 81.05 + +Average object IoU 0.5897537750652014 +Overall IoU 61.386192321777344 +Better epoch: 5 + +Epoch: [6] [ 0/2138] eta: 13:45:09 lr: 4.31958138005741e-05 loss: 0.0722 (0.0722) time: 23.1571 data: 2.0516 max mem: 19788 +Epoch: [6] [ 10/2138] eta: 3:29:28 lr: 4.3190465614438056e-05 loss: 0.0572 (0.0580) time: 5.9063 data: 0.1889 max mem: 19788 +Epoch: [6] [ 20/2138] eta: 2:59:31 lr: 4.318511735471714e-05 loss: 0.0489 (0.0525) time: 4.1821 data: 0.0026 max mem: 19788 +Epoch: [6] [ 30/2138] eta: 2:49:20 lr: 4.317976902140019e-05 loss: 0.0495 (0.0601) time: 4.2226 data: 0.0031 max mem: 19788 +Epoch: [6] [ 40/2138] eta: 2:41:22 lr: 4.317442061447609e-05 loss: 0.0638 (0.0623) time: 4.1209 data: 0.0037 max mem: 19788 +Epoch: [6] [ 50/2138] eta: 2:36:27 lr: 4.3169072133933666e-05 loss: 0.0643 (0.0655) time: 3.9930 data: 0.0040 max mem: 19788 +Epoch: [6] [ 60/2138] eta: 2:33:21 lr: 4.3163723579761795e-05 loss: 0.0584 (0.0644) time: 4.0448 data: 0.0040 max mem: 19788 +Epoch: [6] [ 70/2138] eta: 2:30:30 lr: 4.3158374951949307e-05 loss: 0.0497 (0.0619) time: 4.0384 data: 0.0040 max mem: 19788 +Epoch: [6] [ 80/2138] eta: 2:28:31 lr: 4.315302625048507e-05 loss: 0.0609 (0.0638) time: 4.0317 data: 0.0038 max mem: 19788 +Epoch: [6] [ 90/2138] eta: 2:26:46 lr: 4.31476774753579e-05 loss: 0.0753 (0.0655) time: 4.0631 data: 0.0035 max mem: 19788 +Epoch: [6] [ 100/2138] eta: 2:25:52 lr: 4.314232862655665e-05 loss: 0.0689 (0.0660) time: 4.1506 data: 0.0034 max mem: 19788 +Epoch: [6] [ 110/2138] eta: 2:26:04 lr: 4.3136979704070164e-05 loss: 0.0545 (0.0659) time: 4.4195 data: 0.0034 max mem: 19788 +Epoch: [6] [ 120/2138] eta: 2:25:24 lr: 4.3131630707887255e-05 loss: 0.0545 (0.0658) time: 4.4689 data: 0.0036 max mem: 19788 +Epoch: [6] [ 130/2138] eta: 2:24:03 lr: 4.312628163799677e-05 loss: 0.0628 (0.0665) time: 4.2103 data: 0.0035 max mem: 19788 +Epoch: [6] [ 140/2138] eta: 2:22:31 lr: 4.312093249438752e-05 loss: 0.0504 (0.0661) time: 4.0187 data: 0.0037 max mem: 19788 +Epoch: [6] [ 150/2138] eta: 2:22:06 lr: 4.311558327704834e-05 loss: 0.0487 (0.0655) time: 4.1875 data: 0.0037 max mem: 19788 +Epoch: [6] [ 160/2138] eta: 2:21:32 lr: 4.3110233985968044e-05 loss: 0.0555 (0.0662) time: 4.3849 data: 0.0033 max mem: 19788 +Epoch: [6] [ 170/2138] eta: 2:20:00 lr: 4.310488462113546e-05 loss: 0.0589 (0.0660) time: 4.1131 data: 0.0034 max mem: 19788 +Epoch: [6] [ 180/2138] eta: 2:18:34 lr: 4.3099535182539366e-05 loss: 0.0667 (0.0663) time: 3.8709 data: 0.0034 max mem: 19788 +Epoch: [6] [ 190/2138] eta: 2:18:01 lr: 4.3094185670168616e-05 loss: 0.0578 (0.0665) time: 4.1049 data: 0.0034 max mem: 19788 +Epoch: [6] [ 200/2138] eta: 2:17:00 lr: 4.308883608401199e-05 loss: 0.0538 (0.0656) time: 4.1989 data: 0.0036 max mem: 19788 +Epoch: [6] [ 210/2138] eta: 2:16:16 lr: 4.308348642405831e-05 loss: 0.0581 (0.0658) time: 4.1383 data: 0.0036 max mem: 19788 +Epoch: [6] [ 220/2138] eta: 2:15:25 lr: 4.3078136690296346e-05 loss: 0.0581 (0.0654) time: 4.1840 data: 0.0035 max mem: 19788 +Epoch: [6] [ 230/2138] eta: 2:14:29 lr: 4.307278688271493e-05 loss: 0.0539 (0.0658) time: 4.1113 data: 0.0035 max mem: 19788 +Epoch: [6] [ 240/2138] eta: 2:13:34 lr: 4.3067437001302826e-05 loss: 0.0670 (0.0664) time: 4.0649 data: 0.0035 max mem: 19788 +Epoch: [6] [ 250/2138] eta: 2:12:52 lr: 4.3062087046048845e-05 loss: 0.0683 (0.0667) time: 4.1455 data: 0.0037 max mem: 19788 +Epoch: [6] [ 260/2138] eta: 2:11:56 lr: 4.305673701694176e-05 loss: 0.0560 (0.0663) time: 4.1296 data: 0.0037 max mem: 19788 +Epoch: [6] [ 270/2138] eta: 2:10:56 lr: 4.305138691397037e-05 loss: 0.0540 (0.0669) time: 3.9937 data: 0.0035 max mem: 19788 +Epoch: [6] [ 280/2138] eta: 2:10:44 lr: 4.304603673712345e-05 loss: 0.0629 (0.0669) time: 4.3126 data: 0.0035 max mem: 19788 +Epoch: [6] [ 290/2138] eta: 2:10:21 lr: 4.304068648638977e-05 loss: 0.0520 (0.0667) time: 4.5901 data: 0.0036 max mem: 19788 +Epoch: [6] [ 300/2138] eta: 2:09:26 lr: 4.303533616175811e-05 loss: 0.0513 (0.0664) time: 4.2723 data: 0.0037 max mem: 19788 +Epoch: [6] [ 310/2138] eta: 2:08:41 lr: 4.302998576321723e-05 loss: 0.0601 (0.0663) time: 4.1045 data: 0.0037 max mem: 19788 +Epoch: [6] [ 320/2138] eta: 2:07:53 lr: 4.302463529075593e-05 loss: 0.0613 (0.0662) time: 4.1546 data: 0.0033 max mem: 19788 +Epoch: [6] [ 330/2138] eta: 2:07:04 lr: 4.301928474436294e-05 loss: 0.0603 (0.0662) time: 4.1122 data: 0.0034 max mem: 19788 +Epoch: [6] [ 340/2138] eta: 2:06:16 lr: 4.301393412402703e-05 loss: 0.0552 (0.0661) time: 4.0986 data: 0.0037 max mem: 19788 +Epoch: [6] [ 350/2138] eta: 2:05:58 lr: 4.300858342973696e-05 loss: 0.0576 (0.0663) time: 4.3914 data: 0.0035 max mem: 19788 +Epoch: [6] [ 360/2138] eta: 2:05:06 lr: 4.30032326614815e-05 loss: 0.0576 (0.0665) time: 4.3533 data: 0.0033 max mem: 19788 +Epoch: [6] [ 370/2138] eta: 2:04:22 lr: 4.299788181924938e-05 loss: 0.0586 (0.0666) time: 4.1111 data: 0.0033 max mem: 19788 +Epoch: [6] [ 380/2138] eta: 2:03:30 lr: 4.299253090302934e-05 loss: 0.0670 (0.0667) time: 4.1056 data: 0.0034 max mem: 19788 +Epoch: [6] [ 390/2138] eta: 2:02:40 lr: 4.298717991281016e-05 loss: 0.0606 (0.0665) time: 4.0269 data: 0.0036 max mem: 19788 +Epoch: [6] [ 400/2138] eta: 2:01:50 lr: 4.298182884858056e-05 loss: 0.0606 (0.0666) time: 4.0352 data: 0.0034 max mem: 19788 +Epoch: [6] [ 410/2138] eta: 2:01:11 lr: 4.297647771032927e-05 loss: 0.0639 (0.0668) time: 4.1478 data: 0.0033 max mem: 19788 +Epoch: [6] [ 420/2138] eta: 2:00:40 lr: 4.2971126498045036e-05 loss: 0.0592 (0.0664) time: 4.3748 data: 0.0032 max mem: 19788 +Epoch: [6] [ 430/2138] eta: 2:00:00 lr: 4.29657752117166e-05 loss: 0.0559 (0.0665) time: 4.3751 data: 0.0033 max mem: 19788 +Epoch: [6] [ 440/2138] eta: 1:59:11 lr: 4.2960423851332675e-05 loss: 0.0749 (0.0668) time: 4.1574 data: 0.0037 max mem: 19788 +Epoch: [6] [ 450/2138] eta: 1:58:26 lr: 4.295507241688199e-05 loss: 0.0584 (0.0667) time: 4.0906 data: 0.0038 max mem: 19788 +Epoch: [6] [ 460/2138] eta: 1:57:48 lr: 4.294972090835326e-05 loss: 0.0599 (0.0669) time: 4.2240 data: 0.0040 max mem: 19788 +Epoch: [6] [ 470/2138] eta: 1:57:09 lr: 4.2944369325735224e-05 loss: 0.0677 (0.0669) time: 4.3124 data: 0.0037 max mem: 19788 +Epoch: [6] [ 480/2138] eta: 1:56:25 lr: 4.2939017669016576e-05 loss: 0.0610 (0.0670) time: 4.2234 data: 0.0032 max mem: 19788 +Epoch: [6] [ 490/2138] eta: 1:55:29 lr: 4.293366593818604e-05 loss: 0.0569 (0.0668) time: 3.9749 data: 0.0033 max mem: 19788 +Epoch: [6] [ 500/2138] eta: 1:54:29 lr: 4.2928314133232325e-05 loss: 0.0499 (0.0668) time: 3.7421 data: 0.0032 max mem: 19788 +Epoch: [6] [ 510/2138] eta: 1:53:31 lr: 4.292296225414412e-05 loss: 0.0617 (0.0668) time: 3.6659 data: 0.0030 max mem: 19788 +Epoch: [6] [ 520/2138] eta: 1:52:34 lr: 4.291761030091015e-05 loss: 0.0648 (0.0668) time: 3.6827 data: 0.0031 max mem: 19788 +Epoch: [6] [ 530/2138] eta: 1:51:39 lr: 4.29122582735191e-05 loss: 0.0599 (0.0667) time: 3.7271 data: 0.0033 max mem: 19788 +Epoch: [6] [ 540/2138] eta: 1:50:45 lr: 4.290690617195968e-05 loss: 0.0550 (0.0666) time: 3.7518 data: 0.0033 max mem: 19788 +Epoch: [6] [ 550/2138] eta: 1:49:58 lr: 4.290155399622056e-05 loss: 0.0521 (0.0665) time: 3.8575 data: 0.0031 max mem: 19788 +Epoch: [6] [ 560/2138] eta: 1:49:05 lr: 4.289620174629045e-05 loss: 0.0582 (0.0666) time: 3.8494 data: 0.0031 max mem: 19788 +Epoch: [6] [ 570/2138] eta: 1:48:15 lr: 4.2890849422158016e-05 loss: 0.0676 (0.0666) time: 3.8009 data: 0.0032 max mem: 19788 +Epoch: [6] [ 580/2138] eta: 1:47:22 lr: 4.288549702381196e-05 loss: 0.0712 (0.0666) time: 3.7709 data: 0.0031 max mem: 19788 +Epoch: [6] [ 590/2138] eta: 1:46:29 lr: 4.288014455124095e-05 loss: 0.0697 (0.0667) time: 3.6884 data: 0.0029 max mem: 19788 +Epoch: [6] [ 600/2138] eta: 1:45:42 lr: 4.2874792004433665e-05 loss: 0.0697 (0.0668) time: 3.8089 data: 0.0031 max mem: 19788 +Epoch: [6] [ 610/2138] eta: 1:44:53 lr: 4.2869439383378774e-05 loss: 0.0582 (0.0667) time: 3.8569 data: 0.0031 max mem: 19788 +Epoch: [6] [ 620/2138] eta: 1:44:00 lr: 4.286408668806495e-05 loss: 0.0582 (0.0667) time: 3.7134 data: 0.0030 max mem: 19788 +Epoch: [6] [ 630/2138] eta: 1:43:07 lr: 4.285873391848086e-05 loss: 0.0568 (0.0667) time: 3.6271 data: 0.0029 max mem: 19788 +Epoch: [6] [ 640/2138] eta: 1:42:15 lr: 4.2853381074615166e-05 loss: 0.0549 (0.0667) time: 3.6340 data: 0.0028 max mem: 19788 +Epoch: [6] [ 650/2138] eta: 1:41:24 lr: 4.284802815645652e-05 loss: 0.0551 (0.0665) time: 3.6398 data: 0.0029 max mem: 19788 +Epoch: [6] [ 660/2138] eta: 1:40:33 lr: 4.2842675163993595e-05 loss: 0.0595 (0.0665) time: 3.6341 data: 0.0028 max mem: 19788 +Epoch: [6] [ 670/2138] eta: 1:39:42 lr: 4.2837322097215026e-05 loss: 0.0606 (0.0664) time: 3.6329 data: 0.0027 max mem: 19788 +Epoch: [6] [ 680/2138] eta: 1:38:52 lr: 4.283196895610947e-05 loss: 0.0556 (0.0664) time: 3.6300 data: 0.0027 max mem: 19788 +Epoch: [6] [ 690/2138] eta: 1:38:02 lr: 4.2826615740665574e-05 loss: 0.0567 (0.0664) time: 3.6282 data: 0.0028 max mem: 19788 +Epoch: [6] [ 700/2138] eta: 1:37:12 lr: 4.282126245087198e-05 loss: 0.0682 (0.0664) time: 3.6273 data: 0.0029 max mem: 19788 +Epoch: [6] [ 710/2138] eta: 1:36:23 lr: 4.2815909086717325e-05 loss: 0.0701 (0.0667) time: 3.6314 data: 0.0027 max mem: 19788 +Epoch: [6] [ 720/2138] eta: 1:35:34 lr: 4.2810555648190245e-05 loss: 0.0658 (0.0669) time: 3.6329 data: 0.0027 max mem: 19788 +Epoch: [6] [ 730/2138] eta: 1:34:46 lr: 4.280520213527938e-05 loss: 0.0658 (0.0669) time: 3.6324 data: 0.0027 max mem: 19788 +Epoch: [6] [ 740/2138] eta: 1:33:58 lr: 4.279984854797336e-05 loss: 0.0652 (0.0669) time: 3.6324 data: 0.0028 max mem: 19788 +Epoch: [6] [ 750/2138] eta: 1:33:10 lr: 4.27944948862608e-05 loss: 0.0565 (0.0668) time: 3.6387 data: 0.0028 max mem: 19788 +Epoch: [6] [ 760/2138] eta: 1:32:23 lr: 4.278914115013033e-05 loss: 0.0596 (0.0669) time: 3.6497 data: 0.0029 max mem: 19788 +Epoch: [6] [ 770/2138] eta: 1:31:36 lr: 4.2783787339570555e-05 loss: 0.0596 (0.0668) time: 3.6468 data: 0.0029 max mem: 19788 +Epoch: [6] [ 780/2138] eta: 1:30:50 lr: 4.277843345457012e-05 loss: 0.0561 (0.0667) time: 3.6421 data: 0.0029 max mem: 19788 +Epoch: [6] [ 790/2138] eta: 1:30:03 lr: 4.277307949511763e-05 loss: 0.0641 (0.0667) time: 3.6396 data: 0.0028 max mem: 19788 +Epoch: [6] [ 800/2138] eta: 1:29:17 lr: 4.276772546120167e-05 loss: 0.0685 (0.0666) time: 3.6318 data: 0.0028 max mem: 19788 +Epoch: [6] [ 810/2138] eta: 1:28:30 lr: 4.276237135281087e-05 loss: 0.0546 (0.0665) time: 3.6277 data: 0.0028 max mem: 19788 +Epoch: [6] [ 820/2138] eta: 1:27:44 lr: 4.275701716993383e-05 loss: 0.0644 (0.0666) time: 3.6278 data: 0.0028 max mem: 19788 +Epoch: [6] [ 830/2138] eta: 1:26:59 lr: 4.275166291255914e-05 loss: 0.0580 (0.0666) time: 3.6242 data: 0.0029 max mem: 19788 +Epoch: [6] [ 840/2138] eta: 1:26:13 lr: 4.274630858067541e-05 loss: 0.0576 (0.0665) time: 3.6242 data: 0.0029 max mem: 19788 +Epoch: [6] [ 850/2138] eta: 1:25:28 lr: 4.2740954174271225e-05 loss: 0.0636 (0.0665) time: 3.6240 data: 0.0029 max mem: 19788 +Epoch: [6] [ 860/2138] eta: 1:24:43 lr: 4.273559969333517e-05 loss: 0.0637 (0.0666) time: 3.6258 data: 0.0029 max mem: 19788 +Epoch: [6] [ 870/2138] eta: 1:23:58 lr: 4.273024513785584e-05 loss: 0.0564 (0.0664) time: 3.6305 data: 0.0029 max mem: 19788 +Epoch: [6] [ 880/2138] eta: 1:23:13 lr: 4.272489050782181e-05 loss: 0.0531 (0.0664) time: 3.6296 data: 0.0028 max mem: 19788 +Epoch: [6] [ 890/2138] eta: 1:22:29 lr: 4.271953580322167e-05 loss: 0.0583 (0.0663) time: 3.6275 data: 0.0028 max mem: 19788 +Epoch: [6] [ 900/2138] eta: 1:21:45 lr: 4.271418102404399e-05 loss: 0.0655 (0.0665) time: 3.6347 data: 0.0028 max mem: 19788 +Epoch: [6] [ 910/2138] eta: 1:21:00 lr: 4.2708826170277344e-05 loss: 0.0587 (0.0664) time: 3.6310 data: 0.0028 max mem: 19788 +Epoch: [6] [ 920/2138] eta: 1:20:17 lr: 4.2703471241910295e-05 loss: 0.0549 (0.0665) time: 3.6275 data: 0.0029 max mem: 19788 +Epoch: [6] [ 930/2138] eta: 1:19:33 lr: 4.269811623893142e-05 loss: 0.0561 (0.0666) time: 3.6318 data: 0.0029 max mem: 19788 +Epoch: [6] [ 940/2138] eta: 1:18:49 lr: 4.269276116132929e-05 loss: 0.0643 (0.0667) time: 3.6258 data: 0.0028 max mem: 19788 +Epoch: [6] [ 950/2138] eta: 1:18:06 lr: 4.2687406009092435e-05 loss: 0.0607 (0.0667) time: 3.6288 data: 0.0029 max mem: 19788 +Epoch: [6] [ 960/2138] eta: 1:17:22 lr: 4.268205078220943e-05 loss: 0.0600 (0.0667) time: 3.6325 data: 0.0031 max mem: 19788 +Epoch: [6] [ 970/2138] eta: 1:16:39 lr: 4.2676695480668826e-05 loss: 0.0594 (0.0665) time: 3.6399 data: 0.0030 max mem: 19788 +Epoch: [6] [ 980/2138] eta: 1:15:57 lr: 4.267134010445918e-05 loss: 0.0594 (0.0665) time: 3.6421 data: 0.0032 max mem: 19788 +Epoch: [6] [ 990/2138] eta: 1:15:14 lr: 4.266598465356903e-05 loss: 0.0661 (0.0665) time: 3.6351 data: 0.0032 max mem: 19788 +Epoch: [6] [1000/2138] eta: 1:14:31 lr: 4.2660629127986904e-05 loss: 0.0648 (0.0665) time: 3.6438 data: 0.0030 max mem: 19788 +Epoch: [6] [1010/2138] eta: 1:13:49 lr: 4.2655273527701375e-05 loss: 0.0640 (0.0664) time: 3.6515 data: 0.0031 max mem: 19788 +Epoch: [6] [1020/2138] eta: 1:13:06 lr: 4.264991785270095e-05 loss: 0.0552 (0.0663) time: 3.6492 data: 0.0032 max mem: 19788 +Epoch: [6] [1030/2138] eta: 1:12:24 lr: 4.264456210297418e-05 loss: 0.0472 (0.0663) time: 3.6445 data: 0.0031 max mem: 19788 +Epoch: [6] [1040/2138] eta: 1:11:42 lr: 4.263920627850958e-05 loss: 0.0521 (0.0662) time: 3.6382 data: 0.0033 max mem: 19788 +Epoch: [6] [1050/2138] eta: 1:11:00 lr: 4.263385037929569e-05 loss: 0.0552 (0.0661) time: 3.6325 data: 0.0032 max mem: 19788 +Epoch: [6] [1060/2138] eta: 1:10:18 lr: 4.262849440532103e-05 loss: 0.0567 (0.0661) time: 3.6332 data: 0.0030 max mem: 19788 +Epoch: [6] [1070/2138] eta: 1:09:36 lr: 4.2623138356574104e-05 loss: 0.0585 (0.0661) time: 3.6357 data: 0.0029 max mem: 19788 +Epoch: [6] [1080/2138] eta: 1:08:54 lr: 4.2617782233043444e-05 loss: 0.0575 (0.0661) time: 3.6360 data: 0.0028 max mem: 19788 +Epoch: [6] [1090/2138] eta: 1:08:12 lr: 4.261242603471756e-05 loss: 0.0566 (0.0661) time: 3.6331 data: 0.0031 max mem: 19788 +Epoch: [6] [1100/2138] eta: 1:07:31 lr: 4.2607069761584964e-05 loss: 0.0677 (0.0662) time: 3.6328 data: 0.0032 max mem: 19788 +Epoch: [6] [1110/2138] eta: 1:06:49 lr: 4.2601713413634145e-05 loss: 0.0604 (0.0661) time: 3.6330 data: 0.0029 max mem: 19788 +Epoch: [6] [1120/2138] eta: 1:06:08 lr: 4.259635699085362e-05 loss: 0.0552 (0.0662) time: 3.6270 data: 0.0028 max mem: 19788 +Epoch: [6] [1130/2138] eta: 1:05:26 lr: 4.259100049323189e-05 loss: 0.0628 (0.0662) time: 3.6210 data: 0.0029 max mem: 19788 +Epoch: [6] [1140/2138] eta: 1:04:45 lr: 4.258564392075745e-05 loss: 0.0673 (0.0663) time: 3.6260 data: 0.0029 max mem: 19788 +Epoch: [6] [1150/2138] eta: 1:04:04 lr: 4.258028727341878e-05 loss: 0.0574 (0.0663) time: 3.6247 data: 0.0029 max mem: 19788 +Epoch: [6] [1160/2138] eta: 1:03:22 lr: 4.257493055120438e-05 loss: 0.0527 (0.0663) time: 3.6150 data: 0.0028 max mem: 19788 +Epoch: [6] [1170/2138] eta: 1:02:41 lr: 4.2569573754102726e-05 loss: 0.0599 (0.0662) time: 3.6208 data: 0.0027 max mem: 19788 +Epoch: [6] [1180/2138] eta: 1:02:00 lr: 4.256421688210232e-05 loss: 0.0595 (0.0662) time: 3.6305 data: 0.0028 max mem: 19788 +Epoch: [6] [1190/2138] eta: 1:01:20 lr: 4.255885993519161e-05 loss: 0.0535 (0.0662) time: 3.6328 data: 0.0027 max mem: 19788 +Epoch: [6] [1200/2138] eta: 1:00:39 lr: 4.2553502913359114e-05 loss: 0.0499 (0.0663) time: 3.6283 data: 0.0029 max mem: 19788 +Epoch: [6] [1210/2138] eta: 0:59:58 lr: 4.254814581659326e-05 loss: 0.0602 (0.0663) time: 3.6305 data: 0.0031 max mem: 19788 +Epoch: [6] [1220/2138] eta: 0:59:17 lr: 4.254278864488254e-05 loss: 0.0621 (0.0664) time: 3.6313 data: 0.0030 max mem: 19788 +Epoch: [6] [1230/2138] eta: 0:58:37 lr: 4.253743139821542e-05 loss: 0.0621 (0.0664) time: 3.6259 data: 0.0030 max mem: 19788 +Epoch: [6] [1240/2138] eta: 0:57:56 lr: 4.253207407658035e-05 loss: 0.0555 (0.0665) time: 3.6258 data: 0.0032 max mem: 19788 +Epoch: [6] [1250/2138] eta: 0:57:16 lr: 4.2526716679965806e-05 loss: 0.0555 (0.0665) time: 3.6271 data: 0.0031 max mem: 19788 +Epoch: [6] [1260/2138] eta: 0:56:36 lr: 4.252135920836022e-05 loss: 0.0576 (0.0664) time: 3.6330 data: 0.0029 max mem: 19788 +Epoch: [6] [1270/2138] eta: 0:55:55 lr: 4.251600166175206e-05 loss: 0.0559 (0.0663) time: 3.6388 data: 0.0029 max mem: 19788 +Epoch: [6] [1280/2138] eta: 0:55:15 lr: 4.251064404012978e-05 loss: 0.0475 (0.0663) time: 3.6347 data: 0.0028 max mem: 19788 +Epoch: [6] [1290/2138] eta: 0:54:35 lr: 4.250528634348181e-05 loss: 0.0612 (0.0663) time: 3.6326 data: 0.0030 max mem: 19788 +Epoch: [6] [1300/2138] eta: 0:53:55 lr: 4.249992857179659e-05 loss: 0.0626 (0.0663) time: 3.6359 data: 0.0032 max mem: 19788 +Epoch: [6] [1310/2138] eta: 0:53:15 lr: 4.2494570725062564e-05 loss: 0.0626 (0.0664) time: 3.6301 data: 0.0031 max mem: 19788 +Epoch: [6] [1320/2138] eta: 0:52:35 lr: 4.248921280326818e-05 loss: 0.0730 (0.0664) time: 3.6274 data: 0.0031 max mem: 19788 +Epoch: [6] [1330/2138] eta: 0:51:55 lr: 4.248385480640186e-05 loss: 0.0499 (0.0663) time: 3.6363 data: 0.0031 max mem: 19788 +Epoch: [6] [1340/2138] eta: 0:51:15 lr: 4.247849673445201e-05 loss: 0.0509 (0.0663) time: 3.6382 data: 0.0032 max mem: 19788 +Epoch: [6] [1350/2138] eta: 0:50:35 lr: 4.2473138587407085e-05 loss: 0.0664 (0.0665) time: 3.6322 data: 0.0028 max mem: 19788 +Epoch: [6] [1360/2138] eta: 0:49:55 lr: 4.246778036525549e-05 loss: 0.0718 (0.0664) time: 3.6272 data: 0.0029 max mem: 19788 +Epoch: [6] [1370/2138] eta: 0:49:16 lr: 4.246242206798566e-05 loss: 0.0561 (0.0664) time: 3.6230 data: 0.0030 max mem: 19788 +Epoch: [6] [1380/2138] eta: 0:48:36 lr: 4.2457063695585986e-05 loss: 0.0591 (0.0665) time: 3.6246 data: 0.0027 max mem: 19788 +Epoch: [6] [1390/2138] eta: 0:47:56 lr: 4.245170524804489e-05 loss: 0.0650 (0.0665) time: 3.6280 data: 0.0028 max mem: 19788 +Epoch: [6] [1400/2138] eta: 0:47:17 lr: 4.2446346725350775e-05 loss: 0.0593 (0.0665) time: 3.6299 data: 0.0029 max mem: 19788 +Epoch: [6] [1410/2138] eta: 0:46:37 lr: 4.244098812749206e-05 loss: 0.0559 (0.0664) time: 3.6296 data: 0.0028 max mem: 19788 +Epoch: [6] [1420/2138] eta: 0:45:57 lr: 4.243562945445713e-05 loss: 0.0575 (0.0664) time: 3.6231 data: 0.0029 max mem: 19788 +Epoch: [6] [1430/2138] eta: 0:45:18 lr: 4.2430270706234385e-05 loss: 0.0590 (0.0664) time: 3.6192 data: 0.0028 max mem: 19788 +Epoch: [6] [1440/2138] eta: 0:44:39 lr: 4.242491188281221e-05 loss: 0.0520 (0.0663) time: 3.6272 data: 0.0027 max mem: 19788 +Epoch: [6] [1450/2138] eta: 0:43:59 lr: 4.2419552984179025e-05 loss: 0.0564 (0.0663) time: 3.6347 data: 0.0030 max mem: 19788 +Epoch: [6] [1460/2138] eta: 0:43:20 lr: 4.2414194010323185e-05 loss: 0.0654 (0.0663) time: 3.6287 data: 0.0030 max mem: 19788 +Epoch: [6] [1470/2138] eta: 0:42:41 lr: 4.240883496123309e-05 loss: 0.0727 (0.0663) time: 3.6218 data: 0.0028 max mem: 19788 +Epoch: [6] [1480/2138] eta: 0:42:01 lr: 4.2403475836897114e-05 loss: 0.0751 (0.0664) time: 3.6208 data: 0.0029 max mem: 19788 +Epoch: [6] [1490/2138] eta: 0:41:22 lr: 4.239811663730364e-05 loss: 0.0732 (0.0665) time: 3.6250 data: 0.0028 max mem: 19788 +Epoch: [6] [1500/2138] eta: 0:40:43 lr: 4.2392757362441035e-05 loss: 0.0653 (0.0665) time: 3.6328 data: 0.0029 max mem: 19788 +Epoch: [6] [1510/2138] eta: 0:40:04 lr: 4.2387398012297666e-05 loss: 0.0568 (0.0664) time: 3.6323 data: 0.0032 max mem: 19788 +Epoch: [6] [1520/2138] eta: 0:39:25 lr: 4.238203858686191e-05 loss: 0.0501 (0.0663) time: 3.6367 data: 0.0031 max mem: 19788 +Epoch: [6] [1530/2138] eta: 0:38:46 lr: 4.237667908612213e-05 loss: 0.0549 (0.0663) time: 3.6444 data: 0.0029 max mem: 19788 +Epoch: [6] [1540/2138] eta: 0:38:07 lr: 4.237131951006667e-05 loss: 0.0598 (0.0664) time: 3.6385 data: 0.0029 max mem: 19788 +Epoch: [6] [1550/2138] eta: 0:37:28 lr: 4.23659598586839e-05 loss: 0.0636 (0.0664) time: 3.6355 data: 0.0028 max mem: 19788 +Epoch: [6] [1560/2138] eta: 0:36:49 lr: 4.236060013196217e-05 loss: 0.0628 (0.0663) time: 3.6351 data: 0.0028 max mem: 19788 +Epoch: [6] [1570/2138] eta: 0:36:10 lr: 4.235524032988982e-05 loss: 0.0619 (0.0663) time: 3.6375 data: 0.0028 max mem: 19788 +Epoch: [6] [1580/2138] eta: 0:35:31 lr: 4.23498804524552e-05 loss: 0.0641 (0.0664) time: 3.6389 data: 0.0029 max mem: 19788 +Epoch: [6] [1590/2138] eta: 0:34:52 lr: 4.234452049964667e-05 loss: 0.0646 (0.0663) time: 3.6337 data: 0.0028 max mem: 19788 +Epoch: [6] [1600/2138] eta: 0:34:13 lr: 4.233916047145255e-05 loss: 0.0678 (0.0664) time: 3.6317 data: 0.0027 max mem: 19788 +Epoch: [6] [1610/2138] eta: 0:33:35 lr: 4.2333800367861175e-05 loss: 0.0531 (0.0663) time: 3.6335 data: 0.0029 max mem: 19788 +Epoch: [6] [1620/2138] eta: 0:32:56 lr: 4.2328440188860885e-05 loss: 0.0514 (0.0662) time: 3.6364 data: 0.0032 max mem: 19788 +Epoch: [6] [1630/2138] eta: 0:32:17 lr: 4.232307993444001e-05 loss: 0.0564 (0.0662) time: 3.6332 data: 0.0031 max mem: 19788 +Epoch: [6] [1640/2138] eta: 0:31:38 lr: 4.2317719604586864e-05 loss: 0.0601 (0.0662) time: 3.6271 data: 0.0029 max mem: 19788 +Epoch: [6] [1650/2138] eta: 0:31:00 lr: 4.231235919928977e-05 loss: 0.0431 (0.0661) time: 3.6333 data: 0.0028 max mem: 19788 +Epoch: [6] [1660/2138] eta: 0:30:21 lr: 4.2306998718537054e-05 loss: 0.0481 (0.0660) time: 3.6375 data: 0.0028 max mem: 19788 +Epoch: [6] [1670/2138] eta: 0:29:43 lr: 4.230163816231704e-05 loss: 0.0551 (0.0660) time: 3.6394 data: 0.0030 max mem: 19788 +Epoch: [6] [1680/2138] eta: 0:29:04 lr: 4.229627753061802e-05 loss: 0.0569 (0.0659) time: 3.6372 data: 0.0031 max mem: 19788 +Epoch: [6] [1690/2138] eta: 0:28:25 lr: 4.22909168234283e-05 loss: 0.0628 (0.0660) time: 3.6295 data: 0.0030 max mem: 19788 +Epoch: [6] [1700/2138] eta: 0:27:47 lr: 4.2285556040736207e-05 loss: 0.0574 (0.0660) time: 3.6253 data: 0.0028 max mem: 19788 +Epoch: [6] [1710/2138] eta: 0:27:08 lr: 4.228019518253002e-05 loss: 0.0574 (0.0660) time: 3.6225 data: 0.0029 max mem: 19788 +Epoch: [6] [1720/2138] eta: 0:26:30 lr: 4.227483424879804e-05 loss: 0.0598 (0.0659) time: 3.6242 data: 0.0030 max mem: 19788 +Epoch: [6] [1730/2138] eta: 0:25:51 lr: 4.2269473239528576e-05 loss: 0.0598 (0.0659) time: 3.6247 data: 0.0031 max mem: 19788 +Epoch: [6] [1740/2138] eta: 0:25:13 lr: 4.2264112154709904e-05 loss: 0.0519 (0.0658) time: 3.6249 data: 0.0031 max mem: 19788 +Epoch: [6] [1750/2138] eta: 0:24:35 lr: 4.2258750994330316e-05 loss: 0.0571 (0.0659) time: 3.6284 data: 0.0031 max mem: 19788 +Epoch: [6] [1760/2138] eta: 0:23:56 lr: 4.2253389758378096e-05 loss: 0.0675 (0.0659) time: 3.6414 data: 0.0029 max mem: 19788 +Epoch: [6] [1770/2138] eta: 0:23:18 lr: 4.2248028446841514e-05 loss: 0.0534 (0.0658) time: 3.6476 data: 0.0028 max mem: 19788 +Epoch: [6] [1780/2138] eta: 0:22:40 lr: 4.224266705970886e-05 loss: 0.0495 (0.0657) time: 3.6373 data: 0.0029 max mem: 19788 +Epoch: [6] [1790/2138] eta: 0:22:01 lr: 4.223730559696841e-05 loss: 0.0509 (0.0657) time: 3.6342 data: 0.0028 max mem: 19788 +Epoch: [6] [1800/2138] eta: 0:21:23 lr: 4.223194405860842e-05 loss: 0.0644 (0.0658) time: 3.6365 data: 0.0028 max mem: 19788 +Epoch: [6] [1810/2138] eta: 0:20:45 lr: 4.222658244461716e-05 loss: 0.0646 (0.0658) time: 3.6355 data: 0.0029 max mem: 19788 +Epoch: [6] [1820/2138] eta: 0:20:06 lr: 4.22212207549829e-05 loss: 0.0598 (0.0658) time: 3.6311 data: 0.0028 max mem: 19788 +Epoch: [6] [1830/2138] eta: 0:19:28 lr: 4.221585898969389e-05 loss: 0.0598 (0.0658) time: 3.6402 data: 0.0028 max mem: 19788 +Epoch: [6] [1840/2138] eta: 0:18:50 lr: 4.221049714873839e-05 loss: 0.0494 (0.0658) time: 3.6444 data: 0.0031 max mem: 19788 +Epoch: [6] [1850/2138] eta: 0:18:12 lr: 4.2205135232104655e-05 loss: 0.0607 (0.0659) time: 3.6355 data: 0.0031 max mem: 19788 +Epoch: [6] [1860/2138] eta: 0:17:34 lr: 4.2199773239780934e-05 loss: 0.0715 (0.0660) time: 3.6355 data: 0.0031 max mem: 19788 +Epoch: [6] [1870/2138] eta: 0:16:56 lr: 4.2194411171755467e-05 loss: 0.0710 (0.0661) time: 3.6351 data: 0.0030 max mem: 19788 +Epoch: [6] [1880/2138] eta: 0:16:17 lr: 4.2189049028016495e-05 loss: 0.0652 (0.0660) time: 3.6322 data: 0.0030 max mem: 19788 +Epoch: [6] [1890/2138] eta: 0:15:39 lr: 4.2183686808552256e-05 loss: 0.0522 (0.0660) time: 3.6454 data: 0.0029 max mem: 19788 +Epoch: [6] [1900/2138] eta: 0:15:01 lr: 4.2178324513351e-05 loss: 0.0491 (0.0659) time: 3.6445 data: 0.0030 max mem: 19788 +Epoch: [6] [1910/2138] eta: 0:14:23 lr: 4.217296214240094e-05 loss: 0.0537 (0.0659) time: 3.6289 data: 0.0031 max mem: 19788 +Epoch: [6] [1920/2138] eta: 0:13:45 lr: 4.2167599695690314e-05 loss: 0.0589 (0.0659) time: 3.6331 data: 0.0028 max mem: 19788 +Epoch: [6] [1930/2138] eta: 0:13:07 lr: 4.2162237173207344e-05 loss: 0.0581 (0.0658) time: 3.6379 data: 0.0029 max mem: 19788 +Epoch: [6] [1940/2138] eta: 0:12:29 lr: 4.215687457494025e-05 loss: 0.0604 (0.0658) time: 3.6376 data: 0.0027 max mem: 19788 +Epoch: [6] [1950/2138] eta: 0:11:51 lr: 4.215151190087725e-05 loss: 0.0617 (0.0659) time: 3.6388 data: 0.0028 max mem: 19788 +Epoch: [6] [1960/2138] eta: 0:11:13 lr: 4.214614915100655e-05 loss: 0.0613 (0.0659) time: 3.6332 data: 0.0030 max mem: 19788 +Epoch: [6] [1970/2138] eta: 0:10:35 lr: 4.214078632531637e-05 loss: 0.0519 (0.0659) time: 3.6276 data: 0.0028 max mem: 19788 +Epoch: [6] [1980/2138] eta: 0:09:57 lr: 4.2135423423794916e-05 loss: 0.0518 (0.0659) time: 3.6344 data: 0.0029 max mem: 19788 +Epoch: [6] [1990/2138] eta: 0:09:19 lr: 4.213006044643039e-05 loss: 0.0687 (0.0660) time: 3.6349 data: 0.0029 max mem: 19788 +Epoch: [6] [2000/2138] eta: 0:08:41 lr: 4.2124697393210995e-05 loss: 0.0612 (0.0660) time: 3.6277 data: 0.0028 max mem: 19788 +Epoch: [6] [2010/2138] eta: 0:08:03 lr: 4.2119334264124925e-05 loss: 0.0603 (0.0660) time: 3.6197 data: 0.0029 max mem: 19788 +Epoch: [6] [2020/2138] eta: 0:07:25 lr: 4.211397105916037e-05 loss: 0.0544 (0.0659) time: 3.6293 data: 0.0029 max mem: 19788 +Epoch: [6] [2030/2138] eta: 0:06:48 lr: 4.210860777830552e-05 loss: 0.0544 (0.0660) time: 3.6389 data: 0.0029 max mem: 19788 +Epoch: [6] [2040/2138] eta: 0:06:10 lr: 4.210324442154856e-05 loss: 0.0673 (0.0660) time: 3.6320 data: 0.0027 max mem: 19788 +Epoch: [6] [2050/2138] eta: 0:05:32 lr: 4.209788098887768e-05 loss: 0.0575 (0.0660) time: 3.6312 data: 0.0027 max mem: 19788 +Epoch: [6] [2060/2138] eta: 0:04:54 lr: 4.2092517480281054e-05 loss: 0.0638 (0.0659) time: 3.6261 data: 0.0029 max mem: 19788 +Epoch: [6] [2070/2138] eta: 0:04:16 lr: 4.208715389574685e-05 loss: 0.0514 (0.0659) time: 3.6268 data: 0.0030 max mem: 19788 +Epoch: [6] [2080/2138] eta: 0:03:38 lr: 4.208179023526325e-05 loss: 0.0489 (0.0659) time: 3.6294 data: 0.0030 max mem: 19788 +Epoch: [6] [2090/2138] eta: 0:03:01 lr: 4.207642649881842e-05 loss: 0.0522 (0.0658) time: 3.6322 data: 0.0028 max mem: 19788 +Epoch: [6] [2100/2138] eta: 0:02:23 lr: 4.207106268640053e-05 loss: 0.0546 (0.0658) time: 3.6399 data: 0.0028 max mem: 19788 +Epoch: [6] [2110/2138] eta: 0:01:45 lr: 4.206569879799773e-05 loss: 0.0656 (0.0659) time: 3.6343 data: 0.0030 max mem: 19788 +Epoch: [6] [2120/2138] eta: 0:01:07 lr: 4.206033483359817e-05 loss: 0.0714 (0.0659) time: 3.6382 data: 0.0029 max mem: 19788 +Epoch: [6] [2130/2138] eta: 0:00:30 lr: 4.205497079319003e-05 loss: 0.0660 (0.0659) time: 3.6227 data: 0.0027 max mem: 19788 +Epoch: [6] Total time: 2:14:23 +Test: [ 0/21770] eta: 17:49:15 time: 2.9470 data: 2.7243 max mem: 19788 +Test: [ 100/21770] eta: 0:37:08 time: 0.0816 data: 0.0024 max mem: 19788 +Test: [ 200/21770] eta: 0:30:57 time: 0.0720 data: 0.0020 max mem: 19788 +Test: [ 300/21770] eta: 0:28:44 time: 0.0755 data: 0.0022 max mem: 19788 +Test: [ 400/21770] eta: 0:27:26 time: 0.0600 data: 0.0019 max mem: 19788 +Test: [ 500/21770] eta: 0:26:34 time: 0.0663 data: 0.0019 max mem: 19788 +Test: [ 600/21770] eta: 0:26:11 time: 0.0608 data: 0.0016 max mem: 19788 +Test: [ 700/21770] eta: 0:25:36 time: 0.0606 data: 0.0018 max mem: 19788 +Test: [ 800/21770] eta: 0:25:06 time: 0.0644 data: 0.0018 max mem: 19788 +Test: [ 900/21770] eta: 0:25:03 time: 0.0760 data: 0.0022 max mem: 19788 +Test: [ 1000/21770] eta: 0:24:42 time: 0.0637 data: 0.0019 max mem: 19788 +Test: [ 1100/21770] eta: 0:24:32 time: 0.0596 data: 0.0019 max mem: 19788 +Test: [ 1200/21770] eta: 0:24:28 time: 0.0747 data: 0.0018 max mem: 19788 +Test: [ 1300/21770] eta: 0:24:11 time: 0.0637 data: 0.0020 max mem: 19788 +Test: [ 1400/21770] eta: 0:24:12 time: 0.0751 data: 0.0023 max mem: 19788 +Test: [ 1500/21770] eta: 0:23:57 time: 0.0706 data: 0.0021 max mem: 19788 +Test: [ 1600/21770] eta: 0:23:39 time: 0.0610 data: 0.0018 max mem: 19788 +Test: [ 1700/21770] eta: 0:23:25 time: 0.0664 data: 0.0020 max mem: 19788 +Test: [ 1800/21770] eta: 0:23:17 time: 0.0676 data: 0.0020 max mem: 19788 +Test: [ 1900/21770] eta: 0:23:08 time: 0.0700 data: 0.0017 max mem: 19788 +Test: [ 2000/21770] eta: 0:22:54 time: 0.0597 data: 0.0017 max mem: 19788 +Test: [ 2100/21770] eta: 0:22:42 time: 0.0652 data: 0.0017 max mem: 19788 +Test: [ 2200/21770] eta: 0:22:32 time: 0.0745 data: 0.0019 max mem: 19788 +Test: [ 2300/21770] eta: 0:22:19 time: 0.0638 data: 0.0018 max mem: 19788 +Test: [ 2400/21770] eta: 0:22:14 time: 0.0653 data: 0.0021 max mem: 19788 +Test: [ 2500/21770] eta: 0:22:03 time: 0.0613 data: 0.0019 max mem: 19788 +Test: [ 2600/21770] eta: 0:22:01 time: 0.0733 data: 0.0020 max mem: 19788 +Test: [ 2700/21770] eta: 0:21:52 time: 0.0715 data: 0.0019 max mem: 19788 +Test: [ 2800/21770] eta: 0:21:47 time: 0.0713 data: 0.0019 max mem: 19788 +Test: [ 2900/21770] eta: 0:21:36 time: 0.0722 data: 0.0020 max mem: 19788 +Test: [ 3000/21770] eta: 0:21:29 time: 0.0711 data: 0.0021 max mem: 19788 +Test: [ 3100/21770] eta: 0:21:20 time: 0.0617 data: 0.0017 max mem: 19788 +Test: [ 3200/21770] eta: 0:21:12 time: 0.0759 data: 0.0023 max mem: 19788 +Test: [ 3300/21770] eta: 0:21:04 time: 0.0667 data: 0.0020 max mem: 19788 +Test: [ 3400/21770] eta: 0:20:56 time: 0.0623 data: 0.0018 max mem: 19788 +Test: [ 3500/21770] eta: 0:20:50 time: 0.0705 data: 0.0018 max mem: 19788 +Test: [ 3600/21770] eta: 0:20:40 time: 0.0621 data: 0.0020 max mem: 19788 +Test: [ 3700/21770] eta: 0:20:32 time: 0.0675 data: 0.0021 max mem: 19788 +Test: [ 3800/21770] eta: 0:20:25 time: 0.0623 data: 0.0019 max mem: 19788 +Test: [ 3900/21770] eta: 0:20:16 time: 0.0687 data: 0.0020 max mem: 19788 +Test: [ 4000/21770] eta: 0:20:13 time: 0.0817 data: 0.0019 max mem: 19788 +Test: [ 4100/21770] eta: 0:20:05 time: 0.0696 data: 0.0020 max mem: 19788 +Test: [ 4200/21770] eta: 0:19:58 time: 0.0623 data: 0.0019 max mem: 19788 +Test: [ 4300/21770] eta: 0:19:55 time: 0.0815 data: 0.0024 max mem: 19788 +Test: [ 4400/21770] eta: 0:19:48 time: 0.0655 data: 0.0019 max mem: 19788 +Test: [ 4500/21770] eta: 0:19:38 time: 0.0590 data: 0.0017 max mem: 19788 +Test: [ 4600/21770] eta: 0:19:34 time: 0.0816 data: 0.0025 max mem: 19788 +Test: [ 4700/21770] eta: 0:19:26 time: 0.0677 data: 0.0018 max mem: 19788 +Test: [ 4800/21770] eta: 0:19:18 time: 0.0612 data: 0.0018 max mem: 19788 +Test: [ 4900/21770] eta: 0:19:13 time: 0.0738 data: 0.0021 max mem: 19788 +Test: [ 5000/21770] eta: 0:19:06 time: 0.0765 data: 0.0022 max mem: 19788 +Test: [ 5100/21770] eta: 0:19:01 time: 0.0704 data: 0.0020 max mem: 19788 +Test: [ 5200/21770] eta: 0:18:55 time: 0.0789 data: 0.0024 max mem: 19788 +Test: [ 5300/21770] eta: 0:18:49 time: 0.0734 data: 0.0021 max mem: 19788 +Test: [ 5400/21770] eta: 0:18:42 time: 0.0620 data: 0.0020 max mem: 19788 +Test: [ 5500/21770] eta: 0:18:35 time: 0.0710 data: 0.0020 max mem: 19788 +Test: [ 5600/21770] eta: 0:18:27 time: 0.0736 data: 0.0024 max mem: 19788 +Test: [ 5700/21770] eta: 0:18:19 time: 0.0659 data: 0.0019 max mem: 19788 +Test: [ 5800/21770] eta: 0:18:11 time: 0.0623 data: 0.0017 max mem: 19788 +Test: [ 5900/21770] eta: 0:18:02 time: 0.0623 data: 0.0017 max mem: 19788 +Test: [ 6000/21770] eta: 0:17:56 time: 0.0809 data: 0.0025 max mem: 19788 +Test: [ 6100/21770] eta: 0:17:49 time: 0.0613 data: 0.0019 max mem: 19788 +Test: [ 6200/21770] eta: 0:17:40 time: 0.0638 data: 0.0020 max mem: 19788 +Test: [ 6300/21770] eta: 0:17:32 time: 0.0603 data: 0.0016 max mem: 19788 +Test: [ 6400/21770] eta: 0:17:25 time: 0.0726 data: 0.0022 max mem: 19788 +Test: [ 6500/21770] eta: 0:17:20 time: 0.0799 data: 0.0023 max mem: 19788 +Test: [ 6600/21770] eta: 0:17:13 time: 0.0668 data: 0.0018 max mem: 19788 +Test: [ 6700/21770] eta: 0:17:05 time: 0.0668 data: 0.0018 max mem: 19788 +Test: [ 6800/21770] eta: 0:16:57 time: 0.0665 data: 0.0021 max mem: 19788 +Test: [ 6900/21770] eta: 0:16:50 time: 0.0655 data: 0.0018 max mem: 19788 +Test: [ 7000/21770] eta: 0:16:45 time: 0.0717 data: 0.0022 max mem: 19788 +Test: [ 7100/21770] eta: 0:16:38 time: 0.0758 data: 0.0023 max mem: 19788 +Test: [ 7200/21770] eta: 0:16:31 time: 0.0648 data: 0.0019 max mem: 19788 +Test: [ 7300/21770] eta: 0:16:24 time: 0.0619 data: 0.0021 max mem: 19788 +Test: [ 7400/21770] eta: 0:16:17 time: 0.0670 data: 0.0020 max mem: 19788 +Test: [ 7500/21770] eta: 0:16:10 time: 0.0630 data: 0.0018 max mem: 19788 +Test: [ 7600/21770] eta: 0:16:03 time: 0.0749 data: 0.0018 max mem: 19788 +Test: [ 7700/21770] eta: 0:15:58 time: 0.0785 data: 0.0020 max mem: 19788 +Test: [ 7800/21770] eta: 0:15:51 time: 0.0711 data: 0.0022 max mem: 19788 +Test: [ 7900/21770] eta: 0:15:45 time: 0.0723 data: 0.0022 max mem: 19788 +Test: [ 8000/21770] eta: 0:15:39 time: 0.0607 data: 0.0018 max mem: 19788 +Test: [ 8100/21770] eta: 0:15:32 time: 0.0761 data: 0.0020 max mem: 19788 +Test: [ 8200/21770] eta: 0:15:25 time: 0.0633 data: 0.0018 max mem: 19788 +Test: [ 8300/21770] eta: 0:15:18 time: 0.0803 data: 0.0021 max mem: 19788 +Test: [ 8400/21770] eta: 0:15:12 time: 0.0631 data: 0.0018 max mem: 19788 +Test: [ 8500/21770] eta: 0:15:06 time: 0.0766 data: 0.0023 max mem: 19788 +Test: [ 8600/21770] eta: 0:14:59 time: 0.0685 data: 0.0022 max mem: 19788 +Test: [ 8700/21770] eta: 0:14:51 time: 0.0631 data: 0.0017 max mem: 19788 +Test: [ 8800/21770] eta: 0:14:45 time: 0.0620 data: 0.0017 max mem: 19788 +Test: [ 8900/21770] eta: 0:14:37 time: 0.0646 data: 0.0019 max mem: 19788 +Test: [ 9000/21770] eta: 0:14:30 time: 0.0652 data: 0.0019 max mem: 19788 +Test: [ 9100/21770] eta: 0:14:24 time: 0.0816 data: 0.0023 max mem: 19788 +Test: [ 9200/21770] eta: 0:14:17 time: 0.0610 data: 0.0017 max mem: 19788 +Test: [ 9300/21770] eta: 0:14:10 time: 0.0737 data: 0.0022 max mem: 19788 +Test: [ 9400/21770] eta: 0:14:03 time: 0.0715 data: 0.0020 max mem: 19788 +Test: [ 9500/21770] eta: 0:13:57 time: 0.0683 data: 0.0020 max mem: 19788 +Test: [ 9600/21770] eta: 0:13:50 time: 0.0808 data: 0.0023 max mem: 19788 +Test: [ 9700/21770] eta: 0:13:43 time: 0.0628 data: 0.0017 max mem: 19788 +Test: [ 9800/21770] eta: 0:13:37 time: 0.0803 data: 0.0025 max mem: 19788 +Test: [ 9900/21770] eta: 0:13:31 time: 0.0804 data: 0.0024 max mem: 19788 +Test: [10000/21770] eta: 0:13:23 time: 0.0626 data: 0.0018 max mem: 19788 +Test: [10100/21770] eta: 0:13:16 time: 0.0707 data: 0.0020 max mem: 19788 +Test: [10200/21770] eta: 0:13:09 time: 0.0647 data: 0.0018 max mem: 19788 +Test: [10300/21770] eta: 0:13:03 time: 0.0632 data: 0.0018 max mem: 19788 +Test: [10400/21770] eta: 0:12:57 time: 0.0799 data: 0.0024 max mem: 19788 +Test: [10500/21770] eta: 0:12:50 time: 0.0671 data: 0.0019 max mem: 19788 +Test: [10600/21770] eta: 0:12:43 time: 0.0633 data: 0.0018 max mem: 19788 +Test: [10700/21770] eta: 0:12:36 time: 0.0622 data: 0.0018 max mem: 19788 +Test: [10800/21770] eta: 0:12:29 time: 0.0715 data: 0.0022 max mem: 19788 +Test: [10900/21770] eta: 0:12:22 time: 0.0719 data: 0.0022 max mem: 19788 +Test: [11000/21770] eta: 0:12:15 time: 0.0616 data: 0.0018 max mem: 19788 +Test: [11100/21770] eta: 0:12:08 time: 0.0738 data: 0.0021 max mem: 19788 +Test: [11200/21770] eta: 0:12:01 time: 0.0644 data: 0.0018 max mem: 19788 +Test: [11300/21770] eta: 0:11:55 time: 0.0627 data: 0.0018 max mem: 19788 +Test: [11400/21770] eta: 0:11:48 time: 0.0624 data: 0.0017 max mem: 19788 +Test: [11500/21770] eta: 0:11:41 time: 0.0633 data: 0.0018 max mem: 19788 +Test: [11600/21770] eta: 0:11:34 time: 0.0674 data: 0.0019 max mem: 19788 +Test: [11700/21770] eta: 0:11:27 time: 0.0676 data: 0.0020 max mem: 19788 +Test: [11800/21770] eta: 0:11:20 time: 0.0617 data: 0.0019 max mem: 19788 +Test: [11900/21770] eta: 0:11:14 time: 0.0710 data: 0.0021 max mem: 19788 +Test: [12000/21770] eta: 0:11:07 time: 0.0761 data: 0.0022 max mem: 19788 +Test: [12100/21770] eta: 0:11:01 time: 0.0634 data: 0.0017 max mem: 19788 +Test: [12200/21770] eta: 0:10:53 time: 0.0610 data: 0.0016 max mem: 19788 +Test: [12300/21770] eta: 0:10:47 time: 0.0618 data: 0.0017 max mem: 19788 +Test: [12400/21770] eta: 0:10:40 time: 0.0793 data: 0.0024 max mem: 19788 +Test: [12500/21770] eta: 0:10:33 time: 0.0615 data: 0.0017 max mem: 19788 +Test: [12600/21770] eta: 0:10:26 time: 0.0641 data: 0.0018 max mem: 19788 +Test: [12700/21770] eta: 0:10:19 time: 0.0619 data: 0.0018 max mem: 19788 +Test: [12800/21770] eta: 0:10:12 time: 0.0721 data: 0.0019 max mem: 19788 +Test: [12900/21770] eta: 0:10:05 time: 0.0634 data: 0.0017 max mem: 19788 +Test: [13000/21770] eta: 0:09:58 time: 0.0643 data: 0.0018 max mem: 19788 +Test: [13100/21770] eta: 0:09:51 time: 0.0701 data: 0.0020 max mem: 19788 +Test: [13200/21770] eta: 0:09:44 time: 0.0752 data: 0.0021 max mem: 19788 +Test: [13300/21770] eta: 0:09:38 time: 0.0769 data: 0.0019 max mem: 19788 +Test: [13400/21770] eta: 0:09:31 time: 0.0729 data: 0.0020 max mem: 19788 +Test: [13500/21770] eta: 0:09:25 time: 0.0814 data: 0.0024 max mem: 19788 +Test: [13600/21770] eta: 0:09:19 time: 0.0722 data: 0.0019 max mem: 19788 +Test: [13700/21770] eta: 0:09:11 time: 0.0626 data: 0.0018 max mem: 19788 +Test: [13800/21770] eta: 0:09:05 time: 0.0788 data: 0.0023 max mem: 19788 +Test: [13900/21770] eta: 0:08:58 time: 0.0673 data: 0.0020 max mem: 19788 +Test: [14000/21770] eta: 0:08:51 time: 0.0767 data: 0.0024 max mem: 19788 +Test: [14100/21770] eta: 0:08:44 time: 0.0610 data: 0.0020 max mem: 19788 +Test: [14200/21770] eta: 0:08:37 time: 0.0626 data: 0.0018 max mem: 19788 +Test: [14300/21770] eta: 0:08:30 time: 0.0673 data: 0.0018 max mem: 19788 +Test: [14400/21770] eta: 0:08:23 time: 0.0625 data: 0.0019 max mem: 19788 +Test: [14500/21770] eta: 0:08:16 time: 0.0716 data: 0.0023 max mem: 19788 +Test: [14600/21770] eta: 0:08:10 time: 0.0810 data: 0.0023 max mem: 19788 +Test: [14700/21770] eta: 0:08:03 time: 0.0654 data: 0.0019 max mem: 19788 +Test: [14800/21770] eta: 0:07:56 time: 0.0612 data: 0.0018 max mem: 19788 +Test: [14900/21770] eta: 0:07:49 time: 0.0800 data: 0.0024 max mem: 19788 +Test: [15000/21770] eta: 0:07:42 time: 0.0702 data: 0.0021 max mem: 19788 +Test: [15100/21770] eta: 0:07:36 time: 0.0687 data: 0.0018 max mem: 19788 +Test: [15200/21770] eta: 0:07:29 time: 0.0784 data: 0.0020 max mem: 19788 +Test: [15300/21770] eta: 0:07:22 time: 0.0627 data: 0.0018 max mem: 19788 +Test: [15400/21770] eta: 0:07:15 time: 0.0726 data: 0.0020 max mem: 19788 +Test: [15500/21770] eta: 0:07:08 time: 0.0701 data: 0.0019 max mem: 19788 +Test: [15600/21770] eta: 0:07:01 time: 0.0777 data: 0.0023 max mem: 19788 +Test: [15700/21770] eta: 0:06:55 time: 0.0795 data: 0.0024 max mem: 19788 +Test: [15800/21770] eta: 0:06:48 time: 0.0651 data: 0.0020 max mem: 19788 +Test: [15900/21770] eta: 0:06:41 time: 0.0683 data: 0.0019 max mem: 19788 +Test: [16000/21770] eta: 0:06:34 time: 0.0637 data: 0.0018 max mem: 19788 +Test: [16100/21770] eta: 0:06:28 time: 0.0633 data: 0.0019 max mem: 19788 +Test: [16200/21770] eta: 0:06:21 time: 0.0630 data: 0.0020 max mem: 19788 +Test: [16300/21770] eta: 0:06:14 time: 0.0710 data: 0.0026 max mem: 19788 +Test: [16400/21770] eta: 0:06:07 time: 0.0710 data: 0.0021 max mem: 19788 +Test: [16500/21770] eta: 0:06:00 time: 0.0638 data: 0.0018 max mem: 19788 +Test: [16600/21770] eta: 0:05:53 time: 0.0598 data: 0.0017 max mem: 19788 +Test: [16700/21770] eta: 0:05:46 time: 0.0664 data: 0.0018 max mem: 19788 +Test: [16800/21770] eta: 0:05:39 time: 0.0660 data: 0.0019 max mem: 19788 +Test: [16900/21770] eta: 0:05:32 time: 0.0620 data: 0.0019 max mem: 19788 +Test: [17000/21770] eta: 0:05:26 time: 0.0784 data: 0.0020 max mem: 19788 +Test: [17100/21770] eta: 0:05:19 time: 0.0650 data: 0.0018 max mem: 19788 +Test: [17200/21770] eta: 0:05:12 time: 0.0652 data: 0.0019 max mem: 19788 +Test: [17300/21770] eta: 0:05:05 time: 0.0740 data: 0.0018 max mem: 19788 +Test: [17400/21770] eta: 0:04:58 time: 0.0594 data: 0.0017 max mem: 19788 +Test: [17500/21770] eta: 0:04:51 time: 0.0637 data: 0.0018 max mem: 19788 +Test: [17600/21770] eta: 0:04:44 time: 0.0687 data: 0.0020 max mem: 19788 +Test: [17700/21770] eta: 0:04:38 time: 0.0623 data: 0.0017 max mem: 19788 +Test: [17800/21770] eta: 0:04:31 time: 0.0617 data: 0.0018 max mem: 19788 +Test: [17900/21770] eta: 0:04:24 time: 0.0757 data: 0.0018 max mem: 19788 +Test: [18000/21770] eta: 0:04:17 time: 0.0598 data: 0.0018 max mem: 19788 +Test: [18100/21770] eta: 0:04:10 time: 0.0614 data: 0.0018 max mem: 19788 +Test: [18200/21770] eta: 0:04:03 time: 0.0623 data: 0.0018 max mem: 19788 +Test: [18300/21770] eta: 0:03:56 time: 0.0598 data: 0.0021 max mem: 19788 +Test: [18400/21770] eta: 0:03:49 time: 0.0623 data: 0.0018 max mem: 19788 +Test: [18500/21770] eta: 0:03:43 time: 0.0749 data: 0.0022 max mem: 19788 +Test: [18600/21770] eta: 0:03:36 time: 0.0613 data: 0.0016 max mem: 19788 +Test: [18700/21770] eta: 0:03:29 time: 0.0635 data: 0.0018 max mem: 19788 +Test: [18800/21770] eta: 0:03:22 time: 0.0674 data: 0.0020 max mem: 19788 +Test: [18900/21770] eta: 0:03:15 time: 0.0677 data: 0.0020 max mem: 19788 +Test: [19000/21770] eta: 0:03:08 time: 0.0638 data: 0.0018 max mem: 19788 +Test: [19100/21770] eta: 0:03:01 time: 0.0623 data: 0.0018 max mem: 19788 +Test: [19200/21770] eta: 0:02:55 time: 0.0776 data: 0.0021 max mem: 19788 +Test: [19300/21770] eta: 0:02:48 time: 0.0680 data: 0.0018 max mem: 19788 +Test: [19400/21770] eta: 0:02:41 time: 0.0663 data: 0.0019 max mem: 19788 +Test: [19500/21770] eta: 0:02:34 time: 0.0782 data: 0.0019 max mem: 19788 +Test: [19600/21770] eta: 0:02:27 time: 0.0813 data: 0.0018 max mem: 19788 +Test: [19700/21770] eta: 0:02:20 time: 0.0650 data: 0.0020 max mem: 19788 +Test: [19800/21770] eta: 0:02:14 time: 0.0655 data: 0.0019 max mem: 19788 +Test: [19900/21770] eta: 0:02:07 time: 0.0760 data: 0.0022 max mem: 19788 +Test: [20000/21770] eta: 0:02:00 time: 0.0711 data: 0.0020 max mem: 19788 +Test: [20100/21770] eta: 0:01:53 time: 0.0683 data: 0.0021 max mem: 19788 +Test: [20200/21770] eta: 0:01:46 time: 0.0799 data: 0.0023 max mem: 19788 +Test: [20300/21770] eta: 0:01:40 time: 0.0614 data: 0.0019 max mem: 19788 +Test: [20400/21770] eta: 0:01:33 time: 0.0774 data: 0.0022 max mem: 19788 +Test: [20500/21770] eta: 0:01:26 time: 0.0751 data: 0.0021 max mem: 19788 +Test: [20600/21770] eta: 0:01:19 time: 0.0608 data: 0.0018 max mem: 19788 +Test: [20700/21770] eta: 0:01:12 time: 0.0642 data: 0.0020 max mem: 19788 +Test: [20800/21770] eta: 0:01:06 time: 0.0731 data: 0.0019 max mem: 19788 +Test: [20900/21770] eta: 0:00:59 time: 0.0791 data: 0.0022 max mem: 19788 +Test: [21000/21770] eta: 0:00:52 time: 0.0705 data: 0.0020 max mem: 19788 +Test: [21100/21770] eta: 0:00:45 time: 0.0656 data: 0.0018 max mem: 19788 +Test: [21200/21770] eta: 0:00:38 time: 0.0749 data: 0.0022 max mem: 19788 +Test: [21300/21770] eta: 0:00:32 time: 0.0624 data: 0.0017 max mem: 19788 +Test: [21400/21770] eta: 0:00:25 time: 0.0784 data: 0.0023 max mem: 19788 +Test: [21500/21770] eta: 0:00:18 time: 0.0629 data: 0.0018 max mem: 19788 +Test: [21600/21770] eta: 0:00:11 time: 0.0624 data: 0.0016 max mem: 19788 +Test: [21700/21770] eta: 0:00:04 time: 0.0682 data: 0.0020 max mem: 19788 +Test: Total time: 0:24:47 +Final results: +Mean IoU is 60.72 + + precision@0.5 = 67.23 + precision@0.6 = 61.29 + precision@0.7 = 54.00 + precision@0.8 = 43.09 + precision@0.9 = 20.48 + overall IoU = 61.91 + mean IoU = 60.72 + +Mean accuracy for one-to-zero sample is 75.46 + +Average object IoU 0.6072336644818944 +Overall IoU 61.90858459472656 +Better epoch: 6 + +Epoch: [7] [ 0/2138] eta: 3:46:13 lr: 4.2050679506129375e-05 loss: 0.0901 (0.0901) time: 6.3487 data: 2.1429 max mem: 19788 +Epoch: [7] [ 10/2138] eta: 2:17:58 lr: 4.20453153288759e-05 loss: 0.0433 (0.0497) time: 3.8905 data: 0.1969 max mem: 19788 +Epoch: [7] [ 20/2138] eta: 2:13:07 lr: 4.2039951075580645e-05 loss: 0.0433 (0.0492) time: 3.6425 data: 0.0020 max mem: 19788 +Epoch: [7] [ 30/2138] eta: 2:10:54 lr: 4.2034586746231765e-05 loss: 0.0454 (0.0494) time: 3.6353 data: 0.0023 max mem: 19788 +Epoch: [7] [ 40/2138] eta: 2:09:20 lr: 4.202922234081736e-05 loss: 0.0551 (0.0527) time: 3.6231 data: 0.0030 max mem: 19788 +Epoch: [7] [ 50/2138] eta: 2:08:10 lr: 4.20238578593256e-05 loss: 0.0569 (0.0538) time: 3.6169 data: 0.0030 max mem: 19788 +Epoch: [7] [ 60/2138] eta: 2:07:15 lr: 4.20184933017446e-05 loss: 0.0432 (0.0528) time: 3.6237 data: 0.0030 max mem: 19788 +Epoch: [7] [ 70/2138] eta: 2:06:26 lr: 4.20131286680625e-05 loss: 0.0416 (0.0518) time: 3.6306 data: 0.0029 max mem: 19788 +Epoch: [7] [ 80/2138] eta: 2:05:39 lr: 4.2007763958267394e-05 loss: 0.0553 (0.0533) time: 3.6304 data: 0.0030 max mem: 19788 +Epoch: [7] [ 90/2138] eta: 2:04:52 lr: 4.200239917234743e-05 loss: 0.0618 (0.0539) time: 3.6243 data: 0.0030 max mem: 19788 +Epoch: [7] [ 100/2138] eta: 2:04:11 lr: 4.1997034310290704e-05 loss: 0.0495 (0.0543) time: 3.6272 data: 0.0029 max mem: 19788 +Epoch: [7] [ 110/2138] eta: 2:03:32 lr: 4.1991669372085346e-05 loss: 0.0524 (0.0547) time: 3.6399 data: 0.0029 max mem: 19788 +Epoch: [7] [ 120/2138] eta: 2:02:51 lr: 4.1986304357719455e-05 loss: 0.0503 (0.0552) time: 3.6352 data: 0.0029 max mem: 19788 +Epoch: [7] [ 130/2138] eta: 2:02:11 lr: 4.198093926718114e-05 loss: 0.0503 (0.0569) time: 3.6276 data: 0.0029 max mem: 19788 +Epoch: [7] [ 140/2138] eta: 2:01:30 lr: 4.1975574100458494e-05 loss: 0.0603 (0.0570) time: 3.6254 data: 0.0028 max mem: 19788 +Epoch: [7] [ 150/2138] eta: 2:00:51 lr: 4.197020885753963e-05 loss: 0.0508 (0.0571) time: 3.6244 data: 0.0029 max mem: 19788 +Epoch: [7] [ 160/2138] eta: 2:00:12 lr: 4.196484353841262e-05 loss: 0.0624 (0.0579) time: 3.6302 data: 0.0030 max mem: 19788 +Epoch: [7] [ 170/2138] eta: 1:59:35 lr: 4.195947814306559e-05 loss: 0.0624 (0.0581) time: 3.6332 data: 0.0033 max mem: 19788 +Epoch: [7] [ 180/2138] eta: 1:58:58 lr: 4.1954112671486594e-05 loss: 0.0642 (0.0589) time: 3.6398 data: 0.0034 max mem: 19788 +Epoch: [7] [ 190/2138] eta: 1:58:20 lr: 4.194874712366374e-05 loss: 0.0524 (0.0585) time: 3.6391 data: 0.0032 max mem: 19788 +Epoch: [7] [ 200/2138] eta: 1:57:43 lr: 4.194338149958509e-05 loss: 0.0487 (0.0579) time: 3.6351 data: 0.0031 max mem: 19788 +Epoch: [7] [ 210/2138] eta: 1:57:07 lr: 4.193801579923874e-05 loss: 0.0551 (0.0582) time: 3.6408 data: 0.0031 max mem: 19788 +Epoch: [7] [ 220/2138] eta: 1:56:29 lr: 4.1932650022612746e-05 loss: 0.0551 (0.0582) time: 3.6402 data: 0.0029 max mem: 19788 +Epoch: [7] [ 230/2138] eta: 1:55:52 lr: 4.192728416969519e-05 loss: 0.0549 (0.0585) time: 3.6345 data: 0.0028 max mem: 19788 +Epoch: [7] [ 240/2138] eta: 1:55:15 lr: 4.1921918240474116e-05 loss: 0.0561 (0.0584) time: 3.6330 data: 0.0030 max mem: 19788 +Epoch: [7] [ 250/2138] eta: 1:54:37 lr: 4.1916552234937625e-05 loss: 0.0574 (0.0585) time: 3.6329 data: 0.0031 max mem: 19788 +Epoch: [7] [ 260/2138] eta: 1:54:00 lr: 4.191118615307374e-05 loss: 0.0517 (0.0581) time: 3.6300 data: 0.0032 max mem: 19788 +Epoch: [7] [ 270/2138] eta: 1:53:22 lr: 4.190581999487054e-05 loss: 0.0518 (0.0582) time: 3.6272 data: 0.0029 max mem: 19788 +Epoch: [7] [ 280/2138] eta: 1:52:45 lr: 4.190045376031607e-05 loss: 0.0537 (0.0583) time: 3.6285 data: 0.0030 max mem: 19788 +Epoch: [7] [ 290/2138] eta: 1:52:07 lr: 4.1895087449398374e-05 loss: 0.0534 (0.0581) time: 3.6229 data: 0.0030 max mem: 19788 +Epoch: [7] [ 300/2138] eta: 1:51:30 lr: 4.18897210621055e-05 loss: 0.0514 (0.0578) time: 3.6226 data: 0.0030 max mem: 19788 +Epoch: [7] [ 310/2138] eta: 1:50:53 lr: 4.188435459842549e-05 loss: 0.0514 (0.0579) time: 3.6316 data: 0.0030 max mem: 19788 +Epoch: [7] [ 320/2138] eta: 1:50:16 lr: 4.187898805834638e-05 loss: 0.0541 (0.0580) time: 3.6248 data: 0.0029 max mem: 19788 +Epoch: [7] [ 330/2138] eta: 1:49:39 lr: 4.187362144185621e-05 loss: 0.0550 (0.0582) time: 3.6226 data: 0.0028 max mem: 19788 +Epoch: [7] [ 340/2138] eta: 1:49:02 lr: 4.1868254748943e-05 loss: 0.0525 (0.0582) time: 3.6335 data: 0.0028 max mem: 19788 +Epoch: [7] [ 350/2138] eta: 1:48:26 lr: 4.186288797959478e-05 loss: 0.0506 (0.0581) time: 3.6405 data: 0.0031 max mem: 19788 +Epoch: [7] [ 360/2138] eta: 1:47:49 lr: 4.185752113379959e-05 loss: 0.0506 (0.0580) time: 3.6321 data: 0.0031 max mem: 19788 +Epoch: [7] [ 370/2138] eta: 1:47:12 lr: 4.185215421154543e-05 loss: 0.0555 (0.0584) time: 3.6220 data: 0.0030 max mem: 19788 +Epoch: [7] [ 380/2138] eta: 1:46:35 lr: 4.184678721282031e-05 loss: 0.0555 (0.0582) time: 3.6281 data: 0.0031 max mem: 19788 +Epoch: [7] [ 390/2138] eta: 1:45:58 lr: 4.184142013761227e-05 loss: 0.0540 (0.0582) time: 3.6250 data: 0.0031 max mem: 19788 +Epoch: [7] [ 400/2138] eta: 1:45:21 lr: 4.1836052985909304e-05 loss: 0.0540 (0.0582) time: 3.6216 data: 0.0031 max mem: 19788 +Epoch: [7] [ 410/2138] eta: 1:44:44 lr: 4.183068575769941e-05 loss: 0.0599 (0.0584) time: 3.6257 data: 0.0033 max mem: 19788 +Epoch: [7] [ 420/2138] eta: 1:44:07 lr: 4.1825318452970604e-05 loss: 0.0590 (0.0583) time: 3.6285 data: 0.0031 max mem: 19788 +Epoch: [7] [ 430/2138] eta: 1:43:31 lr: 4.1819951071710875e-05 loss: 0.0547 (0.0585) time: 3.6341 data: 0.0029 max mem: 19788 +Epoch: [7] [ 440/2138] eta: 1:42:55 lr: 4.181458361390822e-05 loss: 0.0547 (0.0585) time: 3.6372 data: 0.0029 max mem: 19788 +Epoch: [7] [ 450/2138] eta: 1:42:18 lr: 4.180921607955063e-05 loss: 0.0522 (0.0585) time: 3.6397 data: 0.0028 max mem: 19788 +Epoch: [7] [ 460/2138] eta: 1:41:42 lr: 4.18038484686261e-05 loss: 0.0620 (0.0586) time: 3.6439 data: 0.0030 max mem: 19788 +Epoch: [7] [ 470/2138] eta: 1:41:06 lr: 4.17984807811226e-05 loss: 0.0604 (0.0587) time: 3.6380 data: 0.0031 max mem: 19788 +Epoch: [7] [ 480/2138] eta: 1:40:29 lr: 4.179311301702812e-05 loss: 0.0627 (0.0590) time: 3.6311 data: 0.0031 max mem: 19788 +Epoch: [7] [ 490/2138] eta: 1:39:53 lr: 4.178774517633063e-05 loss: 0.0573 (0.0589) time: 3.6309 data: 0.0032 max mem: 19788 +Epoch: [7] [ 500/2138] eta: 1:39:16 lr: 4.178237725901812e-05 loss: 0.0481 (0.0589) time: 3.6281 data: 0.0032 max mem: 19788 +Epoch: [7] [ 510/2138] eta: 1:38:39 lr: 4.177700926507853e-05 loss: 0.0548 (0.0590) time: 3.6270 data: 0.0030 max mem: 19788 +Epoch: [7] [ 520/2138] eta: 1:38:03 lr: 4.177164119449986e-05 loss: 0.0561 (0.0590) time: 3.6360 data: 0.0028 max mem: 19788 +Epoch: [7] [ 530/2138] eta: 1:37:27 lr: 4.176627304727005e-05 loss: 0.0504 (0.0590) time: 3.6376 data: 0.0029 max mem: 19788 +Epoch: [7] [ 540/2138] eta: 1:36:50 lr: 4.176090482337706e-05 loss: 0.0504 (0.0589) time: 3.6274 data: 0.0029 max mem: 19788 +Epoch: [7] [ 550/2138] eta: 1:36:13 lr: 4.175553652280884e-05 loss: 0.0501 (0.0588) time: 3.6280 data: 0.0029 max mem: 19788 +Epoch: [7] [ 560/2138] eta: 1:35:37 lr: 4.175016814555337e-05 loss: 0.0522 (0.0587) time: 3.6259 data: 0.0031 max mem: 19788 +Epoch: [7] [ 570/2138] eta: 1:35:00 lr: 4.174479969159857e-05 loss: 0.0557 (0.0591) time: 3.6242 data: 0.0029 max mem: 19788 +Epoch: [7] [ 580/2138] eta: 1:34:24 lr: 4.1739431160932384e-05 loss: 0.0693 (0.0591) time: 3.6274 data: 0.0028 max mem: 19788 +Epoch: [7] [ 590/2138] eta: 1:33:47 lr: 4.173406255354277e-05 loss: 0.0521 (0.0591) time: 3.6270 data: 0.0029 max mem: 19788 +Epoch: [7] [ 600/2138] eta: 1:33:10 lr: 4.1728693869417656e-05 loss: 0.0583 (0.0592) time: 3.6286 data: 0.0031 max mem: 19788 +Epoch: [7] [ 610/2138] eta: 1:32:34 lr: 4.172332510854498e-05 loss: 0.0559 (0.0591) time: 3.6260 data: 0.0032 max mem: 19788 +Epoch: [7] [ 620/2138] eta: 1:31:57 lr: 4.1717956270912655e-05 loss: 0.0558 (0.0592) time: 3.6200 data: 0.0031 max mem: 19788 +Epoch: [7] [ 630/2138] eta: 1:31:20 lr: 4.171258735650862e-05 loss: 0.0589 (0.0592) time: 3.6177 data: 0.0030 max mem: 19788 +Epoch: [7] [ 640/2138] eta: 1:30:44 lr: 4.1707218365320806e-05 loss: 0.0548 (0.0592) time: 3.6210 data: 0.0029 max mem: 19788 +Epoch: [7] [ 650/2138] eta: 1:30:07 lr: 4.170184929733713e-05 loss: 0.0496 (0.0592) time: 3.6205 data: 0.0029 max mem: 19788 +Epoch: [7] [ 660/2138] eta: 1:29:30 lr: 4.169648015254548e-05 loss: 0.0471 (0.0591) time: 3.6213 data: 0.0030 max mem: 19788 +Epoch: [7] [ 670/2138] eta: 1:28:54 lr: 4.1691110930933796e-05 loss: 0.0476 (0.0590) time: 3.6232 data: 0.0032 max mem: 19788 +Epoch: [7] [ 680/2138] eta: 1:28:18 lr: 4.1685741632489976e-05 loss: 0.0490 (0.0589) time: 3.6313 data: 0.0031 max mem: 19788 +Epoch: [7] [ 690/2138] eta: 1:27:41 lr: 4.168037225720193e-05 loss: 0.0560 (0.0590) time: 3.6341 data: 0.0030 max mem: 19788 +Epoch: [7] [ 700/2138] eta: 1:27:05 lr: 4.1675002805057554e-05 loss: 0.0571 (0.0591) time: 3.6319 data: 0.0030 max mem: 19788 +Epoch: [7] [ 710/2138] eta: 1:26:29 lr: 4.166963327604475e-05 loss: 0.0570 (0.0592) time: 3.6354 data: 0.0032 max mem: 19788 +Epoch: [7] [ 720/2138] eta: 1:25:52 lr: 4.16642636701514e-05 loss: 0.0591 (0.0592) time: 3.6373 data: 0.0033 max mem: 19788 +Epoch: [7] [ 730/2138] eta: 1:25:16 lr: 4.1658893987365405e-05 loss: 0.0591 (0.0593) time: 3.6372 data: 0.0032 max mem: 19788 +Epoch: [7] [ 740/2138] eta: 1:24:39 lr: 4.165352422767464e-05 loss: 0.0584 (0.0594) time: 3.6281 data: 0.0031 max mem: 19788 +Epoch: [7] [ 750/2138] eta: 1:24:03 lr: 4.164815439106701e-05 loss: 0.0548 (0.0594) time: 3.6262 data: 0.0031 max mem: 19788 +Epoch: [7] [ 760/2138] eta: 1:23:27 lr: 4.164278447753036e-05 loss: 0.0557 (0.0594) time: 3.6321 data: 0.0031 max mem: 19788 +Epoch: [7] [ 770/2138] eta: 1:22:50 lr: 4.16374144870526e-05 loss: 0.0578 (0.0595) time: 3.6326 data: 0.0031 max mem: 19788 +Epoch: [7] [ 780/2138] eta: 1:22:14 lr: 4.163204441962157e-05 loss: 0.0539 (0.0594) time: 3.6325 data: 0.0031 max mem: 19788 +Epoch: [7] [ 790/2138] eta: 1:21:38 lr: 4.162667427522516e-05 loss: 0.0539 (0.0594) time: 3.6525 data: 0.0029 max mem: 19788 +Epoch: [7] [ 800/2138] eta: 1:21:02 lr: 4.162130405385123e-05 loss: 0.0516 (0.0592) time: 3.6535 data: 0.0030 max mem: 19788 +Epoch: [7] [ 810/2138] eta: 1:20:26 lr: 4.161593375548764e-05 loss: 0.0500 (0.0592) time: 3.6343 data: 0.0029 max mem: 19788 +Epoch: [7] [ 820/2138] eta: 1:19:49 lr: 4.1610563380122234e-05 loss: 0.0550 (0.0592) time: 3.6281 data: 0.0029 max mem: 19788 +Epoch: [7] [ 830/2138] eta: 1:19:13 lr: 4.1605192927742886e-05 loss: 0.0550 (0.0592) time: 3.6303 data: 0.0029 max mem: 19788 +Epoch: [7] [ 840/2138] eta: 1:18:36 lr: 4.159982239833744e-05 loss: 0.0540 (0.0591) time: 3.6321 data: 0.0028 max mem: 19788 +Epoch: [7] [ 850/2138] eta: 1:18:00 lr: 4.159445179189373e-05 loss: 0.0546 (0.0591) time: 3.6230 data: 0.0030 max mem: 19788 +Epoch: [7] [ 860/2138] eta: 1:17:24 lr: 4.15890811083996e-05 loss: 0.0563 (0.0591) time: 3.6313 data: 0.0032 max mem: 19788 +Epoch: [7] [ 870/2138] eta: 1:16:47 lr: 4.158371034784291e-05 loss: 0.0491 (0.0590) time: 3.6348 data: 0.0030 max mem: 19788 +Epoch: [7] [ 880/2138] eta: 1:16:11 lr: 4.157833951021147e-05 loss: 0.0498 (0.0590) time: 3.6189 data: 0.0031 max mem: 19788 +Epoch: [7] [ 890/2138] eta: 1:15:34 lr: 4.157296859549312e-05 loss: 0.0531 (0.0590) time: 3.6167 data: 0.0031 max mem: 19788 +Epoch: [7] [ 900/2138] eta: 1:14:57 lr: 4.1567597603675696e-05 loss: 0.0614 (0.0593) time: 3.6213 data: 0.0029 max mem: 19788 +Epoch: [7] [ 910/2138] eta: 1:14:21 lr: 4.1562226534747015e-05 loss: 0.0570 (0.0592) time: 3.6254 data: 0.0030 max mem: 19788 +Epoch: [7] [ 920/2138] eta: 1:13:45 lr: 4.1556855388694894e-05 loss: 0.0467 (0.0592) time: 3.6394 data: 0.0031 max mem: 19788 +Epoch: [7] [ 930/2138] eta: 1:13:09 lr: 4.155148416550715e-05 loss: 0.0602 (0.0592) time: 3.6406 data: 0.0030 max mem: 19788 +Epoch: [7] [ 940/2138] eta: 1:12:32 lr: 4.15461128651716e-05 loss: 0.0643 (0.0593) time: 3.6276 data: 0.0031 max mem: 19788 +Epoch: [7] [ 950/2138] eta: 1:11:56 lr: 4.1540741487676054e-05 loss: 0.0552 (0.0594) time: 3.6298 data: 0.0030 max mem: 19788 +Epoch: [7] [ 960/2138] eta: 1:11:19 lr: 4.153537003300832e-05 loss: 0.0505 (0.0594) time: 3.6307 data: 0.0030 max mem: 19788 +Epoch: [7] [ 970/2138] eta: 1:10:43 lr: 4.152999850115619e-05 loss: 0.0505 (0.0592) time: 3.6271 data: 0.0030 max mem: 19788 +Epoch: [7] [ 980/2138] eta: 1:10:07 lr: 4.152462689210746e-05 loss: 0.0477 (0.0591) time: 3.6239 data: 0.0028 max mem: 19788 +Epoch: [7] [ 990/2138] eta: 1:09:30 lr: 4.151925520584994e-05 loss: 0.0495 (0.0591) time: 3.6225 data: 0.0029 max mem: 19788 +Epoch: [7] [1000/2138] eta: 1:08:54 lr: 4.151388344237142e-05 loss: 0.0495 (0.0590) time: 3.6299 data: 0.0029 max mem: 19788 +Epoch: [7] [1010/2138] eta: 1:08:18 lr: 4.150851160165968e-05 loss: 0.0479 (0.0590) time: 3.6445 data: 0.0028 max mem: 19788 +Epoch: [7] [1020/2138] eta: 1:07:41 lr: 4.15031396837025e-05 loss: 0.0479 (0.0589) time: 3.6455 data: 0.0030 max mem: 19788 +Epoch: [7] [1030/2138] eta: 1:07:05 lr: 4.149776768848766e-05 loss: 0.0459 (0.0588) time: 3.6337 data: 0.0031 max mem: 19788 +Epoch: [7] [1040/2138] eta: 1:06:29 lr: 4.1492395616002945e-05 loss: 0.0516 (0.0589) time: 3.6281 data: 0.0029 max mem: 19788 +Epoch: [7] [1050/2138] eta: 1:05:52 lr: 4.1487023466236113e-05 loss: 0.0597 (0.0590) time: 3.6249 data: 0.0030 max mem: 19788 +Epoch: [7] [1060/2138] eta: 1:05:16 lr: 4.148165123917496e-05 loss: 0.0516 (0.0589) time: 3.6250 data: 0.0030 max mem: 19788 +Epoch: [7] [1070/2138] eta: 1:04:40 lr: 4.147627893480722e-05 loss: 0.0536 (0.0590) time: 3.6299 data: 0.0031 max mem: 19788 +Epoch: [7] [1080/2138] eta: 1:04:03 lr: 4.147090655312067e-05 loss: 0.0521 (0.0589) time: 3.6317 data: 0.0032 max mem: 19788 +Epoch: [7] [1090/2138] eta: 1:03:27 lr: 4.146553409410306e-05 loss: 0.0499 (0.0589) time: 3.6316 data: 0.0031 max mem: 19788 +Epoch: [7] [1100/2138] eta: 1:02:51 lr: 4.146016155774215e-05 loss: 0.0532 (0.0589) time: 3.6329 data: 0.0030 max mem: 19788 +Epoch: [7] [1110/2138] eta: 1:02:14 lr: 4.1454788944025696e-05 loss: 0.0518 (0.0589) time: 3.6302 data: 0.0030 max mem: 19788 +Epoch: [7] [1120/2138] eta: 1:01:38 lr: 4.144941625294144e-05 loss: 0.0542 (0.0591) time: 3.6256 data: 0.0032 max mem: 19788 +Epoch: [7] [1130/2138] eta: 1:01:01 lr: 4.144404348447712e-05 loss: 0.0581 (0.0591) time: 3.6253 data: 0.0033 max mem: 19788 +Epoch: [7] [1140/2138] eta: 1:00:25 lr: 4.1438670638620475e-05 loss: 0.0592 (0.0591) time: 3.6309 data: 0.0030 max mem: 19788 +Epoch: [7] [1150/2138] eta: 0:59:49 lr: 4.143329771535925e-05 loss: 0.0545 (0.0590) time: 3.6308 data: 0.0029 max mem: 19788 +Epoch: [7] [1160/2138] eta: 0:59:12 lr: 4.142792471468116e-05 loss: 0.0526 (0.0590) time: 3.6266 data: 0.0031 max mem: 19788 +Epoch: [7] [1170/2138] eta: 0:58:36 lr: 4.142255163657395e-05 loss: 0.0528 (0.0589) time: 3.6242 data: 0.0031 max mem: 19788 +Epoch: [7] [1180/2138] eta: 0:57:59 lr: 4.141717848102533e-05 loss: 0.0545 (0.0591) time: 3.6220 data: 0.0033 max mem: 19788 +Epoch: [7] [1190/2138] eta: 0:57:23 lr: 4.141180524802304e-05 loss: 0.0606 (0.0590) time: 3.6235 data: 0.0034 max mem: 19788 +Epoch: [7] [1200/2138] eta: 0:56:47 lr: 4.140643193755477e-05 loss: 0.0554 (0.0591) time: 3.6267 data: 0.0032 max mem: 19788 +Epoch: [7] [1210/2138] eta: 0:56:10 lr: 4.1401058549608255e-05 loss: 0.0582 (0.0591) time: 3.6231 data: 0.0028 max mem: 19788 +Epoch: [7] [1220/2138] eta: 0:55:34 lr: 4.1395685084171195e-05 loss: 0.0597 (0.0593) time: 3.6214 data: 0.0028 max mem: 19788 +Epoch: [7] [1230/2138] eta: 0:54:58 lr: 4.139031154123131e-05 loss: 0.0566 (0.0593) time: 3.6270 data: 0.0029 max mem: 19788 +Epoch: [7] [1240/2138] eta: 0:54:21 lr: 4.138493792077627e-05 loss: 0.0563 (0.0593) time: 3.6295 data: 0.0031 max mem: 19788 +Epoch: [7] [1250/2138] eta: 0:53:45 lr: 4.13795642227938e-05 loss: 0.0495 (0.0593) time: 3.6480 data: 0.0031 max mem: 19788 +Epoch: [7] [1260/2138] eta: 0:53:09 lr: 4.13741904472716e-05 loss: 0.0566 (0.0594) time: 3.6517 data: 0.0030 max mem: 19788 +Epoch: [7] [1270/2138] eta: 0:52:32 lr: 4.136881659419734e-05 loss: 0.0572 (0.0594) time: 3.6278 data: 0.0030 max mem: 19788 +Epoch: [7] [1280/2138] eta: 0:51:56 lr: 4.136344266355871e-05 loss: 0.0572 (0.0594) time: 3.6260 data: 0.0030 max mem: 19788 +Epoch: [7] [1290/2138] eta: 0:51:20 lr: 4.1358068655343407e-05 loss: 0.0587 (0.0595) time: 3.6257 data: 0.0030 max mem: 19788 +Epoch: [7] [1300/2138] eta: 0:50:43 lr: 4.135269456953909e-05 loss: 0.0570 (0.0594) time: 3.6248 data: 0.0029 max mem: 19788 +Epoch: [7] [1310/2138] eta: 0:50:07 lr: 4.134732040613346e-05 loss: 0.0505 (0.0594) time: 3.6265 data: 0.0031 max mem: 19788 +Epoch: [7] [1320/2138] eta: 0:49:31 lr: 4.134194616511417e-05 loss: 0.0608 (0.0594) time: 3.6254 data: 0.0030 max mem: 19788 +Epoch: [7] [1330/2138] eta: 0:48:54 lr: 4.13365718464689e-05 loss: 0.0543 (0.0594) time: 3.6367 data: 0.0030 max mem: 19788 +Epoch: [7] [1340/2138] eta: 0:48:18 lr: 4.13311974501853e-05 loss: 0.0500 (0.0595) time: 3.6336 data: 0.0029 max mem: 19788 +Epoch: [7] [1350/2138] eta: 0:47:42 lr: 4.132582297625105e-05 loss: 0.0642 (0.0595) time: 3.6292 data: 0.0029 max mem: 19788 +Epoch: [7] [1360/2138] eta: 0:47:05 lr: 4.1320448424653784e-05 loss: 0.0601 (0.0595) time: 3.6357 data: 0.0031 max mem: 19788 +Epoch: [7] [1370/2138] eta: 0:46:29 lr: 4.131507379538118e-05 loss: 0.0532 (0.0594) time: 3.6491 data: 0.0029 max mem: 19788 +Epoch: [7] [1380/2138] eta: 0:45:53 lr: 4.1309699088420874e-05 loss: 0.0508 (0.0595) time: 3.6481 data: 0.0028 max mem: 19788 +Epoch: [7] [1390/2138] eta: 0:45:17 lr: 4.130432430376052e-05 loss: 0.0549 (0.0595) time: 3.6486 data: 0.0029 max mem: 19788 +Epoch: [7] [1400/2138] eta: 0:44:41 lr: 4.129894944138774e-05 loss: 0.0539 (0.0594) time: 3.6618 data: 0.0028 max mem: 19788 +Epoch: [7] [1410/2138] eta: 0:44:04 lr: 4.1293574501290195e-05 loss: 0.0545 (0.0595) time: 3.6447 data: 0.0028 max mem: 19788 +Epoch: [7] [1420/2138] eta: 0:43:28 lr: 4.128819948345551e-05 loss: 0.0530 (0.0594) time: 3.6325 data: 0.0028 max mem: 19788 +Epoch: [7] [1430/2138] eta: 0:42:52 lr: 4.128282438787132e-05 loss: 0.0496 (0.0595) time: 3.6306 data: 0.0030 max mem: 19788 +Epoch: [7] [1440/2138] eta: 0:42:15 lr: 4.127744921452524e-05 loss: 0.0519 (0.0594) time: 3.6257 data: 0.0032 max mem: 19788 +Epoch: [7] [1450/2138] eta: 0:41:39 lr: 4.1272073963404914e-05 loss: 0.0524 (0.0594) time: 3.6361 data: 0.0031 max mem: 19788 +Epoch: [7] [1460/2138] eta: 0:41:03 lr: 4.1266698634497944e-05 loss: 0.0541 (0.0594) time: 3.6389 data: 0.0032 max mem: 19788 +Epoch: [7] [1470/2138] eta: 0:40:26 lr: 4.1261323227791954e-05 loss: 0.0641 (0.0595) time: 3.6228 data: 0.0034 max mem: 19788 +Epoch: [7] [1480/2138] eta: 0:39:50 lr: 4.125594774327455e-05 loss: 0.0629 (0.0595) time: 3.6237 data: 0.0035 max mem: 19788 +Epoch: [7] [1490/2138] eta: 0:39:13 lr: 4.125057218093335e-05 loss: 0.0619 (0.0595) time: 3.6258 data: 0.0032 max mem: 19788 +Epoch: [7] [1500/2138] eta: 0:38:37 lr: 4.1245196540755956e-05 loss: 0.0564 (0.0595) time: 3.6285 data: 0.0028 max mem: 19788 +Epoch: [7] [1510/2138] eta: 0:38:01 lr: 4.123982082272995e-05 loss: 0.0564 (0.0596) time: 3.6307 data: 0.0029 max mem: 19788 +Epoch: [7] [1520/2138] eta: 0:37:24 lr: 4.123444502684296e-05 loss: 0.0519 (0.0595) time: 3.6292 data: 0.0030 max mem: 19788 +Epoch: [7] [1530/2138] eta: 0:36:48 lr: 4.1229069153082553e-05 loss: 0.0450 (0.0595) time: 3.6319 data: 0.0030 max mem: 19788 +Epoch: [7] [1540/2138] eta: 0:36:12 lr: 4.1223693201436345e-05 loss: 0.0553 (0.0595) time: 3.6292 data: 0.0029 max mem: 19788 +Epoch: [7] [1550/2138] eta: 0:35:36 lr: 4.121831717189189e-05 loss: 0.0496 (0.0594) time: 3.6366 data: 0.0028 max mem: 19788 +Epoch: [7] [1560/2138] eta: 0:34:59 lr: 4.121294106443679e-05 loss: 0.0496 (0.0594) time: 3.6346 data: 0.0030 max mem: 19788 +Epoch: [7] [1570/2138] eta: 0:34:23 lr: 4.120756487905862e-05 loss: 0.0562 (0.0595) time: 3.6268 data: 0.0030 max mem: 19788 +Epoch: [7] [1580/2138] eta: 0:33:46 lr: 4.120218861574496e-05 loss: 0.0509 (0.0595) time: 3.6317 data: 0.0029 max mem: 19788 +Epoch: [7] [1590/2138] eta: 0:33:10 lr: 4.119681227448336e-05 loss: 0.0503 (0.0594) time: 3.6421 data: 0.0029 max mem: 19788 +Epoch: [7] [1600/2138] eta: 0:32:34 lr: 4.119143585526142e-05 loss: 0.0624 (0.0595) time: 3.6420 data: 0.0032 max mem: 19788 +Epoch: [7] [1610/2138] eta: 0:31:58 lr: 4.118605935806667e-05 loss: 0.0524 (0.0594) time: 3.6319 data: 0.0032 max mem: 19788 +Epoch: [7] [1620/2138] eta: 0:31:21 lr: 4.118068278288669e-05 loss: 0.0519 (0.0594) time: 3.6281 data: 0.0028 max mem: 19788 +Epoch: [7] [1630/2138] eta: 0:30:45 lr: 4.1175306129709017e-05 loss: 0.0541 (0.0594) time: 3.6308 data: 0.0028 max mem: 19788 +Epoch: [7] [1640/2138] eta: 0:30:09 lr: 4.116992939852122e-05 loss: 0.0548 (0.0595) time: 3.6325 data: 0.0030 max mem: 19788 +Epoch: [7] [1650/2138] eta: 0:29:32 lr: 4.116455258931084e-05 loss: 0.0400 (0.0594) time: 3.6409 data: 0.0031 max mem: 19788 +Epoch: [7] [1660/2138] eta: 0:28:56 lr: 4.115917570206543e-05 loss: 0.0474 (0.0593) time: 3.6443 data: 0.0029 max mem: 19788 +Epoch: [7] [1670/2138] eta: 0:28:20 lr: 4.115379873677251e-05 loss: 0.0474 (0.0593) time: 3.6342 data: 0.0029 max mem: 19788 +Epoch: [7] [1680/2138] eta: 0:27:43 lr: 4.114842169341963e-05 loss: 0.0505 (0.0593) time: 3.6303 data: 0.0030 max mem: 19788 +Epoch: [7] [1690/2138] eta: 0:27:07 lr: 4.1143044571994325e-05 loss: 0.0555 (0.0593) time: 3.6298 data: 0.0028 max mem: 19788 +Epoch: [7] [1700/2138] eta: 0:26:31 lr: 4.1137667372484115e-05 loss: 0.0505 (0.0593) time: 3.6288 data: 0.0028 max mem: 19788 +Epoch: [7] [1710/2138] eta: 0:25:54 lr: 4.113229009487654e-05 loss: 0.0466 (0.0593) time: 3.6287 data: 0.0030 max mem: 19788 +Epoch: [7] [1720/2138] eta: 0:25:18 lr: 4.11269127391591e-05 loss: 0.0469 (0.0592) time: 3.6242 data: 0.0029 max mem: 19788 +Epoch: [7] [1730/2138] eta: 0:24:42 lr: 4.112153530531933e-05 loss: 0.0505 (0.0592) time: 3.6169 data: 0.0027 max mem: 19788 +Epoch: [7] [1740/2138] eta: 0:24:05 lr: 4.111615779334473e-05 loss: 0.0458 (0.0591) time: 3.6160 data: 0.0028 max mem: 19788 +Epoch: [7] [1750/2138] eta: 0:23:29 lr: 4.111078020322282e-05 loss: 0.0445 (0.0592) time: 3.6302 data: 0.0031 max mem: 19788 +Epoch: [7] [1760/2138] eta: 0:22:53 lr: 4.110540253494111e-05 loss: 0.0554 (0.0591) time: 3.6363 data: 0.0034 max mem: 19788 +Epoch: [7] [1770/2138] eta: 0:22:16 lr: 4.110002478848709e-05 loss: 0.0459 (0.0591) time: 3.6311 data: 0.0033 max mem: 19788 +Epoch: [7] [1780/2138] eta: 0:21:40 lr: 4.109464696384826e-05 loss: 0.0459 (0.0590) time: 3.6239 data: 0.0030 max mem: 19788 +Epoch: [7] [1790/2138] eta: 0:21:04 lr: 4.108926906101212e-05 loss: 0.0523 (0.0591) time: 3.6230 data: 0.0029 max mem: 19788 +Epoch: [7] [1800/2138] eta: 0:20:27 lr: 4.1083891079966155e-05 loss: 0.0567 (0.0591) time: 3.6286 data: 0.0029 max mem: 19788 +Epoch: [7] [1810/2138] eta: 0:19:51 lr: 4.107851302069786e-05 loss: 0.0527 (0.0591) time: 3.6356 data: 0.0030 max mem: 19788 +Epoch: [7] [1820/2138] eta: 0:19:15 lr: 4.107313488319471e-05 loss: 0.0598 (0.0592) time: 3.6396 data: 0.0032 max mem: 19788 +Epoch: [7] [1830/2138] eta: 0:18:38 lr: 4.106775666744419e-05 loss: 0.0559 (0.0591) time: 3.6319 data: 0.0031 max mem: 19788 +Epoch: [7] [1840/2138] eta: 0:18:02 lr: 4.1062378373433775e-05 loss: 0.0485 (0.0591) time: 3.6329 data: 0.0030 max mem: 19788 +Epoch: [7] [1850/2138] eta: 0:17:26 lr: 4.105700000115094e-05 loss: 0.0561 (0.0592) time: 3.6313 data: 0.0029 max mem: 19788 +Epoch: [7] [1860/2138] eta: 0:16:49 lr: 4.105162155058313e-05 loss: 0.0718 (0.0593) time: 3.6271 data: 0.0029 max mem: 19788 +Epoch: [7] [1870/2138] eta: 0:16:13 lr: 4.1046243021717834e-05 loss: 0.0627 (0.0593) time: 3.6263 data: 0.0030 max mem: 19788 +Epoch: [7] [1880/2138] eta: 0:15:37 lr: 4.104086441454251e-05 loss: 0.0579 (0.0593) time: 3.6254 data: 0.0033 max mem: 19788 +Epoch: [7] [1890/2138] eta: 0:15:00 lr: 4.10354857290446e-05 loss: 0.0542 (0.0593) time: 3.6287 data: 0.0032 max mem: 19788 +Epoch: [7] [1900/2138] eta: 0:14:24 lr: 4.1030106965211575e-05 loss: 0.0516 (0.0592) time: 3.6290 data: 0.0030 max mem: 19788 +Epoch: [7] [1910/2138] eta: 0:13:48 lr: 4.102472812303087e-05 loss: 0.0496 (0.0592) time: 3.6388 data: 0.0030 max mem: 19788 +Epoch: [7] [1920/2138] eta: 0:13:11 lr: 4.1019349202489924e-05 loss: 0.0474 (0.0591) time: 3.6458 data: 0.0032 max mem: 19788 +Epoch: [7] [1930/2138] eta: 0:12:35 lr: 4.10139702035762e-05 loss: 0.0554 (0.0591) time: 3.6348 data: 0.0031 max mem: 19788 +Epoch: [7] [1940/2138] eta: 0:11:59 lr: 4.1008591126277116e-05 loss: 0.0554 (0.0591) time: 3.6323 data: 0.0029 max mem: 19788 +Epoch: [7] [1950/2138] eta: 0:11:22 lr: 4.100321197058011e-05 loss: 0.0527 (0.0591) time: 3.6283 data: 0.0029 max mem: 19788 +Epoch: [7] [1960/2138] eta: 0:10:46 lr: 4.099783273647262e-05 loss: 0.0479 (0.0590) time: 3.6230 data: 0.0029 max mem: 19788 +Epoch: [7] [1970/2138] eta: 0:10:10 lr: 4.099245342394206e-05 loss: 0.0466 (0.0590) time: 3.6360 data: 0.0028 max mem: 19788 +Epoch: [7] [1980/2138] eta: 0:09:33 lr: 4.0987074032975855e-05 loss: 0.0470 (0.0590) time: 3.6391 data: 0.0029 max mem: 19788 +Epoch: [7] [1990/2138] eta: 0:08:57 lr: 4.098169456356143e-05 loss: 0.0471 (0.0590) time: 3.6333 data: 0.0029 max mem: 19788 +Epoch: [7] [2000/2138] eta: 0:08:21 lr: 4.0976315015686187e-05 loss: 0.0496 (0.0589) time: 3.6247 data: 0.0027 max mem: 19788 +Epoch: [7] [2010/2138] eta: 0:07:44 lr: 4.097093538933754e-05 loss: 0.0510 (0.0589) time: 3.6200 data: 0.0029 max mem: 19788 +Epoch: [7] [2020/2138] eta: 0:07:08 lr: 4.09655556845029e-05 loss: 0.0629 (0.0590) time: 3.6264 data: 0.0031 max mem: 19788 +Epoch: [7] [2030/2138] eta: 0:06:32 lr: 4.096017590116967e-05 loss: 0.0586 (0.0590) time: 3.6241 data: 0.0032 max mem: 19788 +Epoch: [7] [2040/2138] eta: 0:05:55 lr: 4.095479603932524e-05 loss: 0.0564 (0.0590) time: 3.6248 data: 0.0031 max mem: 19788 +Epoch: [7] [2050/2138] eta: 0:05:19 lr: 4.094941609895701e-05 loss: 0.0613 (0.0591) time: 3.6261 data: 0.0031 max mem: 19788 +Epoch: [7] [2060/2138] eta: 0:04:43 lr: 4.0944036080052364e-05 loss: 0.0626 (0.0591) time: 3.6205 data: 0.0028 max mem: 19788 +Epoch: [7] [2070/2138] eta: 0:04:06 lr: 4.093865598259871e-05 loss: 0.0490 (0.0591) time: 3.6179 data: 0.0027 max mem: 19788 +Epoch: [7] [2080/2138] eta: 0:03:30 lr: 4.093327580658341e-05 loss: 0.0474 (0.0591) time: 3.6208 data: 0.0030 max mem: 19788 +Epoch: [7] [2090/2138] eta: 0:02:54 lr: 4.092789555199385e-05 loss: 0.0503 (0.0590) time: 3.6213 data: 0.0030 max mem: 19788 +Epoch: [7] [2100/2138] eta: 0:02:18 lr: 4.0922515218817404e-05 loss: 0.0503 (0.0590) time: 3.6390 data: 0.0030 max mem: 19788 +Epoch: [7] [2110/2138] eta: 0:01:41 lr: 4.091713480704145e-05 loss: 0.0565 (0.0591) time: 3.6378 data: 0.0032 max mem: 19788 +Epoch: [7] [2120/2138] eta: 0:01:05 lr: 4.0911754316653345e-05 loss: 0.0706 (0.0591) time: 3.6267 data: 0.0031 max mem: 19788 +Epoch: [7] [2130/2138] eta: 0:00:29 lr: 4.090637374764045e-05 loss: 0.0524 (0.0591) time: 3.6226 data: 0.0028 max mem: 19788 +Epoch: [7] Total time: 2:09:25 +Test: [ 0/21770] eta: 17:36:15 time: 2.9111 data: 2.7661 max mem: 19788 +Test: [ 100/21770] eta: 0:34:16 time: 0.0693 data: 0.0019 max mem: 19788 +Test: [ 200/21770] eta: 0:29:53 time: 0.0656 data: 0.0019 max mem: 19788 +Test: [ 300/21770] eta: 0:27:44 time: 0.0719 data: 0.0021 max mem: 19788 +Test: [ 400/21770] eta: 0:26:52 time: 0.0646 data: 0.0021 max mem: 19788 +Test: [ 500/21770] eta: 0:26:01 time: 0.0663 data: 0.0020 max mem: 19788 +Test: [ 600/21770] eta: 0:25:20 time: 0.0600 data: 0.0020 max mem: 19788 +Test: [ 700/21770] eta: 0:24:55 time: 0.0593 data: 0.0018 max mem: 19788 +Test: [ 800/21770] eta: 0:24:31 time: 0.0600 data: 0.0017 max mem: 19788 +Test: [ 900/21770] eta: 0:24:11 time: 0.0744 data: 0.0019 max mem: 19788 +Test: [ 1000/21770] eta: 0:23:58 time: 0.0658 data: 0.0020 max mem: 19788 +Test: [ 1100/21770] eta: 0:23:43 time: 0.0598 data: 0.0019 max mem: 19788 +Test: [ 1200/21770] eta: 0:23:38 time: 0.0734 data: 0.0021 max mem: 19788 +Test: [ 1300/21770] eta: 0:23:21 time: 0.0611 data: 0.0019 max mem: 19788 +Test: [ 1400/21770] eta: 0:23:10 time: 0.0616 data: 0.0016 max mem: 19788 +Test: [ 1500/21770] eta: 0:22:52 time: 0.0600 data: 0.0019 max mem: 19788 +Test: [ 1600/21770] eta: 0:22:40 time: 0.0684 data: 0.0020 max mem: 19788 +Test: [ 1700/21770] eta: 0:22:27 time: 0.0638 data: 0.0016 max mem: 19788 +Test: [ 1800/21770] eta: 0:22:19 time: 0.0658 data: 0.0019 max mem: 19788 +Test: [ 1900/21770] eta: 0:22:11 time: 0.0601 data: 0.0019 max mem: 19788 +Test: [ 2000/21770] eta: 0:22:05 time: 0.0610 data: 0.0017 max mem: 19788 +Test: [ 2100/21770] eta: 0:22:00 time: 0.0676 data: 0.0021 max mem: 19788 +Test: [ 2200/21770] eta: 0:21:54 time: 0.0607 data: 0.0019 max mem: 19788 +Test: [ 2300/21770] eta: 0:21:54 time: 0.0657 data: 0.0020 max mem: 19788 +Test: [ 2400/21770] eta: 0:21:49 time: 0.0625 data: 0.0020 max mem: 19788 +Test: [ 2500/21770] eta: 0:21:44 time: 0.0634 data: 0.0018 max mem: 19788 +Test: [ 2600/21770] eta: 0:21:40 time: 0.0646 data: 0.0018 max mem: 19788 +Test: [ 2700/21770] eta: 0:21:35 time: 0.0642 data: 0.0017 max mem: 19788 +Test: [ 2800/21770] eta: 0:21:24 time: 0.0626 data: 0.0017 max mem: 19788 +Test: [ 2900/21770] eta: 0:21:18 time: 0.0620 data: 0.0019 max mem: 19788 +Test: [ 3000/21770] eta: 0:21:10 time: 0.0628 data: 0.0018 max mem: 19788 +Test: [ 3100/21770] eta: 0:21:03 time: 0.0655 data: 0.0021 max mem: 19788 +Test: [ 3200/21770] eta: 0:20:56 time: 0.0637 data: 0.0020 max mem: 19788 +Test: [ 3300/21770] eta: 0:20:47 time: 0.0626 data: 0.0017 max mem: 19788 +Test: [ 3400/21770] eta: 0:20:39 time: 0.0631 data: 0.0020 max mem: 19788 +Test: [ 3500/21770] eta: 0:20:32 time: 0.0682 data: 0.0020 max mem: 19788 +Test: [ 3600/21770] eta: 0:20:24 time: 0.0598 data: 0.0018 max mem: 19788 +Test: [ 3700/21770] eta: 0:20:17 time: 0.0591 data: 0.0018 max mem: 19788 +Test: [ 3800/21770] eta: 0:20:10 time: 0.0596 data: 0.0018 max mem: 19788 +Test: [ 3900/21770] eta: 0:20:03 time: 0.0622 data: 0.0018 max mem: 19788 +Test: [ 4000/21770] eta: 0:19:59 time: 0.0714 data: 0.0021 max mem: 19788 +Test: [ 4100/21770] eta: 0:19:54 time: 0.0640 data: 0.0019 max mem: 19788 +Test: [ 4200/21770] eta: 0:19:50 time: 0.0749 data: 0.0019 max mem: 19788 +Test: [ 4300/21770] eta: 0:19:45 time: 0.0814 data: 0.0018 max mem: 19788 +Test: [ 4400/21770] eta: 0:19:39 time: 0.0604 data: 0.0018 max mem: 19788 +Test: [ 4500/21770] eta: 0:19:31 time: 0.0678 data: 0.0020 max mem: 19788 +Test: [ 4600/21770] eta: 0:19:25 time: 0.0622 data: 0.0018 max mem: 19788 +Test: [ 4700/21770] eta: 0:19:17 time: 0.0629 data: 0.0021 max mem: 19788 +Test: [ 4800/21770] eta: 0:19:10 time: 0.0673 data: 0.0019 max mem: 19788 +Test: [ 4900/21770] eta: 0:19:02 time: 0.0613 data: 0.0018 max mem: 19788 +Test: [ 5000/21770] eta: 0:18:55 time: 0.0624 data: 0.0018 max mem: 19788 +Test: [ 5100/21770] eta: 0:18:48 time: 0.0760 data: 0.0022 max mem: 19788 +Test: [ 5200/21770] eta: 0:18:40 time: 0.0642 data: 0.0017 max mem: 19788 +Test: [ 5300/21770] eta: 0:18:33 time: 0.0627 data: 0.0018 max mem: 19788 +Test: [ 5400/21770] eta: 0:18:26 time: 0.0765 data: 0.0020 max mem: 19788 +Test: [ 5500/21770] eta: 0:18:19 time: 0.0628 data: 0.0018 max mem: 19788 +Test: [ 5600/21770] eta: 0:18:11 time: 0.0612 data: 0.0017 max mem: 19788 +Test: [ 5700/21770] eta: 0:18:03 time: 0.0622 data: 0.0017 max mem: 19788 +Test: [ 5800/21770] eta: 0:17:56 time: 0.0677 data: 0.0018 max mem: 19788 +Test: [ 5900/21770] eta: 0:17:51 time: 0.0750 data: 0.0021 max mem: 19788 +Test: [ 6000/21770] eta: 0:17:43 time: 0.0612 data: 0.0018 max mem: 19788 +Test: [ 6100/21770] eta: 0:17:37 time: 0.0682 data: 0.0021 max mem: 19788 +Test: [ 6200/21770] eta: 0:17:29 time: 0.0655 data: 0.0019 max mem: 19788 +Test: [ 6300/21770] eta: 0:17:23 time: 0.0711 data: 0.0019 max mem: 19788 +Test: [ 6400/21770] eta: 0:17:17 time: 0.0615 data: 0.0020 max mem: 19788 +Test: [ 6500/21770] eta: 0:17:09 time: 0.0597 data: 0.0017 max mem: 19788 +Test: [ 6600/21770] eta: 0:17:02 time: 0.0634 data: 0.0018 max mem: 19788 +Test: [ 6700/21770] eta: 0:16:55 time: 0.0617 data: 0.0018 max mem: 19788 +Test: [ 6800/21770] eta: 0:16:48 time: 0.0657 data: 0.0019 max mem: 19788 +Test: [ 6900/21770] eta: 0:16:44 time: 0.0804 data: 0.0024 max mem: 19788 +Test: [ 7000/21770] eta: 0:16:39 time: 0.0789 data: 0.0022 max mem: 19788 +Test: [ 7100/21770] eta: 0:16:33 time: 0.0739 data: 0.0022 max mem: 19788 +Test: [ 7200/21770] eta: 0:16:26 time: 0.0654 data: 0.0019 max mem: 19788 +Test: [ 7300/21770] eta: 0:16:18 time: 0.0613 data: 0.0017 max mem: 19788 +Test: [ 7400/21770] eta: 0:16:11 time: 0.0786 data: 0.0020 max mem: 19788 +Test: [ 7500/21770] eta: 0:16:07 time: 0.0771 data: 0.0022 max mem: 19788 +Test: [ 7600/21770] eta: 0:16:00 time: 0.0700 data: 0.0021 max mem: 19788 +Test: [ 7700/21770] eta: 0:15:55 time: 0.0772 data: 0.0020 max mem: 19788 +Test: [ 7800/21770] eta: 0:15:47 time: 0.0640 data: 0.0018 max mem: 19788 +Test: [ 7900/21770] eta: 0:15:40 time: 0.0642 data: 0.0018 max mem: 19788 +Test: [ 8000/21770] eta: 0:15:34 time: 0.0695 data: 0.0021 max mem: 19788 +Test: [ 8100/21770] eta: 0:15:27 time: 0.0629 data: 0.0017 max mem: 19788 +Test: [ 8200/21770] eta: 0:15:21 time: 0.0628 data: 0.0017 max mem: 19788 +Test: [ 8300/21770] eta: 0:15:13 time: 0.0681 data: 0.0019 max mem: 19788 +Test: [ 8400/21770] eta: 0:15:07 time: 0.0709 data: 0.0020 max mem: 19788 +Test: [ 8500/21770] eta: 0:15:00 time: 0.0755 data: 0.0021 max mem: 19788 +Test: [ 8600/21770] eta: 0:14:53 time: 0.0685 data: 0.0021 max mem: 19788 +Test: [ 8700/21770] eta: 0:14:45 time: 0.0616 data: 0.0016 max mem: 19788 +Test: [ 8800/21770] eta: 0:14:39 time: 0.0777 data: 0.0023 max mem: 19788 +Test: [ 8900/21770] eta: 0:14:33 time: 0.0750 data: 0.0023 max mem: 19788 +Test: [ 9000/21770] eta: 0:14:26 time: 0.0596 data: 0.0016 max mem: 19788 +Test: [ 9100/21770] eta: 0:14:19 time: 0.0731 data: 0.0021 max mem: 19788 +Test: [ 9200/21770] eta: 0:14:12 time: 0.0609 data: 0.0018 max mem: 19788 +Test: [ 9300/21770] eta: 0:14:05 time: 0.0603 data: 0.0018 max mem: 19788 +Test: [ 9400/21770] eta: 0:13:58 time: 0.0739 data: 0.0022 max mem: 19788 +Test: [ 9500/21770] eta: 0:13:51 time: 0.0660 data: 0.0019 max mem: 19788 +Test: [ 9600/21770] eta: 0:13:45 time: 0.0766 data: 0.0023 max mem: 19788 +Test: [ 9700/21770] eta: 0:13:39 time: 0.0711 data: 0.0021 max mem: 19788 +Test: [ 9800/21770] eta: 0:13:32 time: 0.0719 data: 0.0021 max mem: 19788 +Test: [ 9900/21770] eta: 0:13:25 time: 0.0611 data: 0.0019 max mem: 19788 +Test: [10000/21770] eta: 0:13:18 time: 0.0684 data: 0.0019 max mem: 19788 +Test: [10100/21770] eta: 0:13:11 time: 0.0619 data: 0.0017 max mem: 19788 +Test: [10200/21770] eta: 0:13:04 time: 0.0636 data: 0.0018 max mem: 19788 +Test: [10300/21770] eta: 0:12:58 time: 0.0627 data: 0.0018 max mem: 19788 +Test: [10400/21770] eta: 0:12:51 time: 0.0694 data: 0.0018 max mem: 19788 +Test: [10500/21770] eta: 0:12:44 time: 0.0627 data: 0.0018 max mem: 19788 +Test: [10600/21770] eta: 0:12:37 time: 0.0653 data: 0.0019 max mem: 19788 +Test: [10700/21770] eta: 0:12:31 time: 0.0631 data: 0.0021 max mem: 19788 +Test: [10800/21770] eta: 0:12:24 time: 0.0637 data: 0.0018 max mem: 19788 +Test: [10900/21770] eta: 0:12:19 time: 0.0730 data: 0.0020 max mem: 19788 +Test: [11000/21770] eta: 0:12:13 time: 0.0815 data: 0.0025 max mem: 19788 +Test: [11100/21770] eta: 0:12:06 time: 0.0633 data: 0.0018 max mem: 19788 +Test: [11200/21770] eta: 0:11:59 time: 0.0714 data: 0.0022 max mem: 19788 +Test: [11300/21770] eta: 0:11:52 time: 0.0652 data: 0.0020 max mem: 19788 +Test: [11400/21770] eta: 0:11:45 time: 0.0733 data: 0.0018 max mem: 19788 +Test: [11500/21770] eta: 0:11:38 time: 0.0701 data: 0.0020 max mem: 19788 +Test: [11600/21770] eta: 0:11:31 time: 0.0655 data: 0.0017 max mem: 19788 +Test: [11700/21770] eta: 0:11:25 time: 0.0719 data: 0.0020 max mem: 19788 +Test: [11800/21770] eta: 0:11:18 time: 0.0664 data: 0.0020 max mem: 19788 +Test: [11900/21770] eta: 0:11:11 time: 0.0822 data: 0.0025 max mem: 19788 +Test: [12000/21770] eta: 0:11:04 time: 0.0615 data: 0.0018 max mem: 19788 +Test: [12100/21770] eta: 0:10:57 time: 0.0671 data: 0.0018 max mem: 19788 +Test: [12200/21770] eta: 0:10:50 time: 0.0655 data: 0.0019 max mem: 19788 +Test: [12300/21770] eta: 0:10:44 time: 0.0640 data: 0.0017 max mem: 19788 +Test: [12400/21770] eta: 0:10:36 time: 0.0599 data: 0.0018 max mem: 19788 +Test: [12500/21770] eta: 0:10:29 time: 0.0624 data: 0.0019 max mem: 19788 +Test: [12600/21770] eta: 0:10:23 time: 0.0622 data: 0.0019 max mem: 19788 +Test: [12700/21770] eta: 0:10:16 time: 0.0667 data: 0.0019 max mem: 19788 +Test: [12800/21770] eta: 0:10:10 time: 0.0794 data: 0.0022 max mem: 19788 +Test: [12900/21770] eta: 0:10:04 time: 0.0732 data: 0.0020 max mem: 19788 +Test: [13000/21770] eta: 0:09:57 time: 0.0684 data: 0.0018 max mem: 19788 +Test: [13100/21770] eta: 0:09:50 time: 0.0804 data: 0.0023 max mem: 19788 +Test: [13200/21770] eta: 0:09:43 time: 0.0657 data: 0.0022 max mem: 19788 +Test: [13300/21770] eta: 0:09:36 time: 0.0617 data: 0.0019 max mem: 19788 +Test: [13400/21770] eta: 0:09:30 time: 0.0781 data: 0.0021 max mem: 19788 +Test: [13500/21770] eta: 0:09:23 time: 0.0590 data: 0.0017 max mem: 19788 +Test: [13600/21770] eta: 0:09:16 time: 0.0671 data: 0.0021 max mem: 19788 +Test: [13700/21770] eta: 0:09:09 time: 0.0656 data: 0.0018 max mem: 19788 +Test: [13800/21770] eta: 0:09:02 time: 0.0621 data: 0.0017 max mem: 19788 +Test: [13900/21770] eta: 0:08:56 time: 0.0753 data: 0.0022 max mem: 19788 +Test: [14000/21770] eta: 0:08:49 time: 0.0626 data: 0.0018 max mem: 19788 +Test: [14100/21770] eta: 0:08:42 time: 0.0613 data: 0.0017 max mem: 19788 +Test: [14200/21770] eta: 0:08:35 time: 0.0698 data: 0.0021 max mem: 19788 +Test: [14300/21770] eta: 0:08:29 time: 0.0676 data: 0.0018 max mem: 19788 +Test: [14400/21770] eta: 0:08:22 time: 0.0619 data: 0.0019 max mem: 19788 +Test: [14500/21770] eta: 0:08:15 time: 0.0640 data: 0.0018 max mem: 19788 +Test: [14600/21770] eta: 0:08:08 time: 0.0654 data: 0.0019 max mem: 19788 +Test: [14700/21770] eta: 0:08:02 time: 0.0688 data: 0.0020 max mem: 19788 +Test: [14800/21770] eta: 0:07:55 time: 0.0703 data: 0.0018 max mem: 19788 +Test: [14900/21770] eta: 0:07:48 time: 0.0619 data: 0.0017 max mem: 19788 +Test: [15000/21770] eta: 0:07:41 time: 0.0815 data: 0.0019 max mem: 19788 +Test: [15100/21770] eta: 0:07:35 time: 0.0676 data: 0.0018 max mem: 19788 +Test: [15200/21770] eta: 0:07:28 time: 0.0627 data: 0.0018 max mem: 19788 +Test: [15300/21770] eta: 0:07:21 time: 0.0738 data: 0.0020 max mem: 19788 +Test: [15400/21770] eta: 0:07:14 time: 0.0746 data: 0.0022 max mem: 19788 +Test: [15500/21770] eta: 0:07:07 time: 0.0653 data: 0.0020 max mem: 19788 +Test: [15600/21770] eta: 0:07:01 time: 0.0773 data: 0.0026 max mem: 19788 +Test: [15700/21770] eta: 0:06:54 time: 0.0744 data: 0.0019 max mem: 19788 +Test: [15800/21770] eta: 0:06:47 time: 0.0823 data: 0.0023 max mem: 19788 +Test: [15900/21770] eta: 0:06:40 time: 0.0710 data: 0.0022 max mem: 19788 +Test: [16000/21770] eta: 0:06:33 time: 0.0613 data: 0.0018 max mem: 19788 +Test: [16100/21770] eta: 0:06:26 time: 0.0625 data: 0.0018 max mem: 19788 +Test: [16200/21770] eta: 0:06:19 time: 0.0684 data: 0.0021 max mem: 19788 +Test: [16300/21770] eta: 0:06:12 time: 0.0789 data: 0.0024 max mem: 19788 +Test: [16400/21770] eta: 0:06:06 time: 0.0636 data: 0.0019 max mem: 19788 +Test: [16500/21770] eta: 0:05:59 time: 0.0712 data: 0.0021 max mem: 19788 +Test: [16600/21770] eta: 0:05:52 time: 0.0724 data: 0.0022 max mem: 19788 +Test: [16700/21770] eta: 0:05:45 time: 0.0618 data: 0.0016 max mem: 19788 +Test: [16800/21770] eta: 0:05:39 time: 0.0734 data: 0.0021 max mem: 19788 +Test: [16900/21770] eta: 0:05:32 time: 0.0789 data: 0.0022 max mem: 19788 +Test: [17000/21770] eta: 0:05:25 time: 0.0769 data: 0.0025 max mem: 19788 +Test: [17100/21770] eta: 0:05:18 time: 0.0688 data: 0.0017 max mem: 19788 +Test: [17200/21770] eta: 0:05:12 time: 0.0606 data: 0.0017 max mem: 19788 +Test: [17300/21770] eta: 0:05:05 time: 0.0600 data: 0.0017 max mem: 19788 +Test: [17400/21770] eta: 0:04:58 time: 0.0615 data: 0.0019 max mem: 19788 +Test: [17500/21770] eta: 0:04:51 time: 0.0812 data: 0.0022 max mem: 19788 +Test: [17600/21770] eta: 0:04:44 time: 0.0618 data: 0.0020 max mem: 19788 +Test: [17700/21770] eta: 0:04:37 time: 0.0645 data: 0.0018 max mem: 19788 +Test: [17800/21770] eta: 0:04:31 time: 0.0655 data: 0.0020 max mem: 19788 +Test: [17900/21770] eta: 0:04:24 time: 0.0718 data: 0.0021 max mem: 19788 +Test: [18000/21770] eta: 0:04:17 time: 0.0739 data: 0.0019 max mem: 19788 +Test: [18100/21770] eta: 0:04:10 time: 0.0634 data: 0.0019 max mem: 19788 +Test: [18200/21770] eta: 0:04:04 time: 0.0749 data: 0.0018 max mem: 19788 +Test: [18300/21770] eta: 0:03:57 time: 0.0706 data: 0.0020 max mem: 19788 +Test: [18400/21770] eta: 0:03:50 time: 0.0813 data: 0.0025 max mem: 19788 +Test: [18500/21770] eta: 0:03:43 time: 0.0655 data: 0.0019 max mem: 19788 +Test: [18600/21770] eta: 0:03:37 time: 0.0617 data: 0.0017 max mem: 19788 +Test: [18700/21770] eta: 0:03:30 time: 0.0637 data: 0.0018 max mem: 19788 +Test: [18800/21770] eta: 0:03:23 time: 0.0613 data: 0.0019 max mem: 19788 +Test: [18900/21770] eta: 0:03:16 time: 0.0644 data: 0.0019 max mem: 19788 +Test: [19000/21770] eta: 0:03:09 time: 0.0666 data: 0.0019 max mem: 19788 +Test: [19100/21770] eta: 0:03:02 time: 0.0581 data: 0.0017 max mem: 19788 +Test: [19200/21770] eta: 0:02:55 time: 0.0606 data: 0.0017 max mem: 19788 +Test: [19300/21770] eta: 0:02:48 time: 0.0606 data: 0.0019 max mem: 19788 +Test: [19400/21770] eta: 0:02:42 time: 0.0601 data: 0.0018 max mem: 19788 +Test: [19500/21770] eta: 0:02:35 time: 0.0637 data: 0.0017 max mem: 19788 +Test: [19600/21770] eta: 0:02:28 time: 0.0622 data: 0.0018 max mem: 19788 +Test: [19700/21770] eta: 0:02:21 time: 0.0822 data: 0.0025 max mem: 19788 +Test: [19800/21770] eta: 0:02:14 time: 0.0623 data: 0.0020 max mem: 19788 +Test: [19900/21770] eta: 0:02:07 time: 0.0677 data: 0.0020 max mem: 19788 +Test: [20000/21770] eta: 0:02:00 time: 0.0607 data: 0.0019 max mem: 19788 +Test: [20100/21770] eta: 0:01:54 time: 0.0788 data: 0.0020 max mem: 19788 +Test: [20200/21770] eta: 0:01:47 time: 0.0599 data: 0.0018 max mem: 19788 +Test: [20300/21770] eta: 0:01:40 time: 0.0624 data: 0.0017 max mem: 19788 +Test: [20400/21770] eta: 0:01:33 time: 0.0628 data: 0.0018 max mem: 19788 +Test: [20500/21770] eta: 0:01:26 time: 0.0815 data: 0.0019 max mem: 19788 +Test: [20600/21770] eta: 0:01:19 time: 0.0773 data: 0.0023 max mem: 19788 +Test: [20700/21770] eta: 0:01:13 time: 0.0710 data: 0.0017 max mem: 19788 +Test: [20800/21770] eta: 0:01:06 time: 0.0683 data: 0.0019 max mem: 19788 +Test: [20900/21770] eta: 0:00:59 time: 0.0610 data: 0.0016 max mem: 19788 +Test: [21000/21770] eta: 0:00:52 time: 0.0793 data: 0.0023 max mem: 19788 +Test: [21100/21770] eta: 0:00:45 time: 0.0720 data: 0.0021 max mem: 19788 +Test: [21200/21770] eta: 0:00:38 time: 0.0726 data: 0.0022 max mem: 19788 +Test: [21300/21770] eta: 0:00:32 time: 0.0617 data: 0.0018 max mem: 19788 +Test: [21400/21770] eta: 0:00:25 time: 0.0729 data: 0.0020 max mem: 19788 +Test: [21500/21770] eta: 0:00:18 time: 0.0647 data: 0.0019 max mem: 19788 +Test: [21600/21770] eta: 0:00:11 time: 0.0814 data: 0.0024 max mem: 19788 +Test: [21700/21770] eta: 0:00:04 time: 0.0688 data: 0.0020 max mem: 19788 +Test: Total time: 0:24:48 +Final results: +Mean IoU is 60.93 + + precision@0.5 = 67.15 + precision@0.6 = 61.31 + precision@0.7 = 54.26 + precision@0.8 = 43.10 + precision@0.9 = 20.45 + overall IoU = 61.86 + mean IoU = 60.93 + +Mean accuracy for one-to-zero sample is 77.09 + +Average object IoU 0.6092566705319603 +Overall IoU 61.86091232299805 +Epoch: [8] [ 0/2138] eta: 7:43:54 lr: 4.090206923581181e-05 loss: 0.1012 (0.1012) time: 13.0192 data: 2.5028 max mem: 19788 +Epoch: [8] [ 10/2138] eta: 2:39:25 lr: 4.089668852524245e-05 loss: 0.0469 (0.0513) time: 4.4950 data: 0.2302 max mem: 19788 +Epoch: [8] [ 20/2138] eta: 2:24:12 lr: 4.089130773601292e-05 loss: 0.0361 (0.0468) time: 3.6385 data: 0.0024 max mem: 19788 +Epoch: [8] [ 30/2138] eta: 2:18:16 lr: 4.0885926868110555e-05 loss: 0.0365 (0.0445) time: 3.6278 data: 0.0025 max mem: 19788 +Epoch: [8] [ 40/2138] eta: 2:14:59 lr: 4.088054592152269e-05 loss: 0.0443 (0.0469) time: 3.6248 data: 0.0032 max mem: 19788 +Epoch: [8] [ 50/2138] eta: 2:12:43 lr: 4.087516489623668e-05 loss: 0.0508 (0.0484) time: 3.6249 data: 0.0029 max mem: 19788 +Epoch: [8] [ 60/2138] eta: 2:11:01 lr: 4.0869783792239856e-05 loss: 0.0443 (0.0478) time: 3.6247 data: 0.0027 max mem: 19788 +Epoch: [8] [ 70/2138] eta: 2:09:40 lr: 4.0864402609519556e-05 loss: 0.0383 (0.0466) time: 3.6316 data: 0.0027 max mem: 19788 +Epoch: [8] [ 80/2138] eta: 2:08:32 lr: 4.085902134806311e-05 loss: 0.0524 (0.0481) time: 3.6391 data: 0.0030 max mem: 19788 +Epoch: [8] [ 90/2138] eta: 2:07:27 lr: 4.085364000785784e-05 loss: 0.0572 (0.0487) time: 3.6338 data: 0.0032 max mem: 19788 +Epoch: [8] [ 100/2138] eta: 2:06:25 lr: 4.0848258588891056e-05 loss: 0.0432 (0.0489) time: 3.6192 data: 0.0031 max mem: 19788 +Epoch: [8] [ 110/2138] eta: 2:05:32 lr: 4.08428770911501e-05 loss: 0.0521 (0.0498) time: 3.6230 data: 0.0031 max mem: 19788 +Epoch: [8] [ 120/2138] eta: 2:04:41 lr: 4.083749551462227e-05 loss: 0.0521 (0.0503) time: 3.6316 data: 0.0031 max mem: 19788 +Epoch: [8] [ 130/2138] eta: 2:03:54 lr: 4.083211385929488e-05 loss: 0.0507 (0.0502) time: 3.6373 data: 0.0029 max mem: 19788 +Epoch: [8] [ 140/2138] eta: 2:03:09 lr: 4.082673212515523e-05 loss: 0.0400 (0.0502) time: 3.6444 data: 0.0029 max mem: 19788 +Epoch: [8] [ 150/2138] eta: 2:02:22 lr: 4.082135031219064e-05 loss: 0.0403 (0.0499) time: 3.6363 data: 0.0031 max mem: 19788 +Epoch: [8] [ 160/2138] eta: 2:01:40 lr: 4.08159684203884e-05 loss: 0.0455 (0.0505) time: 3.6399 data: 0.0030 max mem: 19788 +Epoch: [8] [ 170/2138] eta: 2:00:57 lr: 4.081058644973579e-05 loss: 0.0456 (0.0507) time: 3.6439 data: 0.0027 max mem: 19788 +Epoch: [8] [ 180/2138] eta: 2:00:15 lr: 4.080520440022011e-05 loss: 0.0532 (0.0513) time: 3.6366 data: 0.0026 max mem: 19788 +Epoch: [8] [ 190/2138] eta: 1:59:34 lr: 4.079982227182865e-05 loss: 0.0528 (0.0515) time: 3.6423 data: 0.0026 max mem: 19788 +Epoch: [8] [ 200/2138] eta: 1:58:53 lr: 4.07944400645487e-05 loss: 0.0494 (0.0514) time: 3.6414 data: 0.0028 max mem: 19788 +Epoch: [8] [ 210/2138] eta: 1:58:12 lr: 4.0789057778367525e-05 loss: 0.0549 (0.0520) time: 3.6372 data: 0.0028 max mem: 19788 +Epoch: [8] [ 220/2138] eta: 1:57:31 lr: 4.07836754132724e-05 loss: 0.0546 (0.0521) time: 3.6334 data: 0.0029 max mem: 19788 +Epoch: [8] [ 230/2138] eta: 1:56:50 lr: 4.0778292969250606e-05 loss: 0.0468 (0.0523) time: 3.6267 data: 0.0030 max mem: 19788 +Epoch: [8] [ 240/2138] eta: 1:56:11 lr: 4.07729104462894e-05 loss: 0.0528 (0.0523) time: 3.6363 data: 0.0029 max mem: 19788 +Epoch: [8] [ 250/2138] eta: 1:55:31 lr: 4.076752784437605e-05 loss: 0.0509 (0.0524) time: 3.6413 data: 0.0031 max mem: 19788 +Epoch: [8] [ 260/2138] eta: 1:54:52 lr: 4.076214516349782e-05 loss: 0.0476 (0.0522) time: 3.6335 data: 0.0030 max mem: 19788 +Epoch: [8] [ 270/2138] eta: 1:54:12 lr: 4.075676240364195e-05 loss: 0.0483 (0.0529) time: 3.6270 data: 0.0028 max mem: 19788 +Epoch: [8] [ 280/2138] eta: 1:53:33 lr: 4.075137956479571e-05 loss: 0.0565 (0.0530) time: 3.6253 data: 0.0028 max mem: 19788 +Epoch: [8] [ 290/2138] eta: 1:52:54 lr: 4.0745996646946325e-05 loss: 0.0492 (0.0527) time: 3.6365 data: 0.0028 max mem: 19788 +Epoch: [8] [ 300/2138] eta: 1:52:15 lr: 4.0740613650081066e-05 loss: 0.0444 (0.0524) time: 3.6335 data: 0.0031 max mem: 19788 +Epoch: [8] [ 310/2138] eta: 1:51:36 lr: 4.073523057418715e-05 loss: 0.0439 (0.0524) time: 3.6201 data: 0.0031 max mem: 19788 +Epoch: [8] [ 320/2138] eta: 1:50:59 lr: 4.072984741925183e-05 loss: 0.0493 (0.0525) time: 3.6424 data: 0.0029 max mem: 19788 +Epoch: [8] [ 330/2138] eta: 1:50:21 lr: 4.072446418526232e-05 loss: 0.0523 (0.0526) time: 3.6466 data: 0.0032 max mem: 19788 +Epoch: [8] [ 340/2138] eta: 1:49:42 lr: 4.0719080872205865e-05 loss: 0.0473 (0.0526) time: 3.6243 data: 0.0031 max mem: 19788 +Epoch: [8] [ 350/2138] eta: 1:49:03 lr: 4.071369748006967e-05 loss: 0.0451 (0.0524) time: 3.6209 data: 0.0029 max mem: 19788 +Epoch: [8] [ 360/2138] eta: 1:48:25 lr: 4.0708314008840974e-05 loss: 0.0425 (0.0522) time: 3.6226 data: 0.0030 max mem: 19788 +Epoch: [8] [ 370/2138] eta: 1:47:46 lr: 4.070293045850698e-05 loss: 0.0559 (0.0527) time: 3.6217 data: 0.0030 max mem: 19788 +Epoch: [8] [ 380/2138] eta: 1:47:08 lr: 4.06975468290549e-05 loss: 0.0559 (0.0526) time: 3.6223 data: 0.0030 max mem: 19788 +Epoch: [8] [ 390/2138] eta: 1:46:31 lr: 4.069216312047195e-05 loss: 0.0493 (0.0526) time: 3.6316 data: 0.0031 max mem: 19788 +Epoch: [8] [ 400/2138] eta: 1:45:53 lr: 4.068677933274533e-05 loss: 0.0514 (0.0528) time: 3.6313 data: 0.0029 max mem: 19788 +Epoch: [8] [ 410/2138] eta: 1:45:15 lr: 4.068139546586224e-05 loss: 0.0516 (0.0528) time: 3.6280 data: 0.0029 max mem: 19788 +Epoch: [8] [ 420/2138] eta: 1:44:38 lr: 4.067601151980987e-05 loss: 0.0562 (0.0527) time: 3.6336 data: 0.0031 max mem: 19788 +Epoch: [8] [ 430/2138] eta: 1:44:01 lr: 4.067062749457543e-05 loss: 0.0487 (0.0531) time: 3.6330 data: 0.0030 max mem: 19788 +Epoch: [8] [ 440/2138] eta: 1:43:23 lr: 4.066524339014608e-05 loss: 0.0522 (0.0535) time: 3.6276 data: 0.0028 max mem: 19788 +Epoch: [8] [ 450/2138] eta: 1:42:46 lr: 4.0659859206509026e-05 loss: 0.0543 (0.0535) time: 3.6295 data: 0.0026 max mem: 19788 +Epoch: [8] [ 460/2138] eta: 1:42:09 lr: 4.065447494365145e-05 loss: 0.0501 (0.0535) time: 3.6443 data: 0.0027 max mem: 19788 +Epoch: [8] [ 470/2138] eta: 1:41:32 lr: 4.064909060156052e-05 loss: 0.0532 (0.0537) time: 3.6449 data: 0.0029 max mem: 19788 +Epoch: [8] [ 480/2138] eta: 1:40:55 lr: 4.06437061802234e-05 loss: 0.0562 (0.0537) time: 3.6318 data: 0.0032 max mem: 19788 +Epoch: [8] [ 490/2138] eta: 1:40:18 lr: 4.063832167962727e-05 loss: 0.0485 (0.0537) time: 3.6374 data: 0.0032 max mem: 19788 +Epoch: [8] [ 500/2138] eta: 1:39:41 lr: 4.06329370997593e-05 loss: 0.0423 (0.0536) time: 3.6364 data: 0.0031 max mem: 19788 +Epoch: [8] [ 510/2138] eta: 1:39:03 lr: 4.062755244060664e-05 loss: 0.0474 (0.0536) time: 3.6284 data: 0.0030 max mem: 19788 +Epoch: [8] [ 520/2138] eta: 1:38:27 lr: 4.062216770215645e-05 loss: 0.0499 (0.0535) time: 3.6352 data: 0.0030 max mem: 19788 +Epoch: [8] [ 530/2138] eta: 1:37:49 lr: 4.061678288439587e-05 loss: 0.0499 (0.0535) time: 3.6351 data: 0.0030 max mem: 19788 +Epoch: [8] [ 540/2138] eta: 1:37:12 lr: 4.061139798731208e-05 loss: 0.0463 (0.0534) time: 3.6268 data: 0.0029 max mem: 19788 +Epoch: [8] [ 550/2138] eta: 1:36:35 lr: 4.06060130108922e-05 loss: 0.0423 (0.0532) time: 3.6283 data: 0.0028 max mem: 19788 +Epoch: [8] [ 560/2138] eta: 1:35:58 lr: 4.060062795512336e-05 loss: 0.0478 (0.0532) time: 3.6279 data: 0.0027 max mem: 19788 +Epoch: [8] [ 570/2138] eta: 1:35:21 lr: 4.059524281999274e-05 loss: 0.0533 (0.0532) time: 3.6249 data: 0.0029 max mem: 19788 +Epoch: [8] [ 580/2138] eta: 1:34:43 lr: 4.058985760548742e-05 loss: 0.0547 (0.0532) time: 3.6210 data: 0.0029 max mem: 19788 +Epoch: [8] [ 590/2138] eta: 1:34:06 lr: 4.058447231159456e-05 loss: 0.0503 (0.0532) time: 3.6217 data: 0.0030 max mem: 19788 +Epoch: [8] [ 600/2138] eta: 1:33:29 lr: 4.0579086938301284e-05 loss: 0.0492 (0.0533) time: 3.6256 data: 0.0031 max mem: 19788 +Epoch: [8] [ 610/2138] eta: 1:32:52 lr: 4.05737014855947e-05 loss: 0.0486 (0.0533) time: 3.6290 data: 0.0031 max mem: 19788 +Epoch: [8] [ 620/2138] eta: 1:32:15 lr: 4.0568315953461936e-05 loss: 0.0482 (0.0533) time: 3.6294 data: 0.0030 max mem: 19788 +Epoch: [8] [ 630/2138] eta: 1:31:39 lr: 4.05629303418901e-05 loss: 0.0486 (0.0534) time: 3.6263 data: 0.0028 max mem: 19788 +Epoch: [8] [ 640/2138] eta: 1:31:02 lr: 4.0557544650866296e-05 loss: 0.0486 (0.0534) time: 3.6293 data: 0.0028 max mem: 19788 +Epoch: [8] [ 650/2138] eta: 1:30:25 lr: 4.055215888037764e-05 loss: 0.0460 (0.0534) time: 3.6309 data: 0.0028 max mem: 19788 +Epoch: [8] [ 660/2138] eta: 1:29:48 lr: 4.0546773030411216e-05 loss: 0.0444 (0.0534) time: 3.6306 data: 0.0028 max mem: 19788 +Epoch: [8] [ 670/2138] eta: 1:29:11 lr: 4.054138710095414e-05 loss: 0.0563 (0.0534) time: 3.6329 data: 0.0027 max mem: 19788 +Epoch: [8] [ 680/2138] eta: 1:28:35 lr: 4.05360010919935e-05 loss: 0.0563 (0.0535) time: 3.6398 data: 0.0029 max mem: 19788 +Epoch: [8] [ 690/2138] eta: 1:27:58 lr: 4.0530615003516375e-05 loss: 0.0556 (0.0536) time: 3.6341 data: 0.0032 max mem: 19788 +Epoch: [8] [ 700/2138] eta: 1:27:21 lr: 4.0525228835509856e-05 loss: 0.0556 (0.0536) time: 3.6337 data: 0.0030 max mem: 19788 +Epoch: [8] [ 710/2138] eta: 1:26:45 lr: 4.0519842587961015e-05 loss: 0.0507 (0.0537) time: 3.6357 data: 0.0028 max mem: 19788 +Epoch: [8] [ 720/2138] eta: 1:26:08 lr: 4.051445626085694e-05 loss: 0.0507 (0.0538) time: 3.6278 data: 0.0029 max mem: 19788 +Epoch: [8] [ 730/2138] eta: 1:25:31 lr: 4.0509069854184714e-05 loss: 0.0517 (0.0540) time: 3.6278 data: 0.0028 max mem: 19788 +Epoch: [8] [ 740/2138] eta: 1:24:55 lr: 4.0503683367931376e-05 loss: 0.0495 (0.0540) time: 3.6371 data: 0.0030 max mem: 19788 +Epoch: [8] [ 750/2138] eta: 1:24:18 lr: 4.049829680208401e-05 loss: 0.0432 (0.0540) time: 3.6426 data: 0.0031 max mem: 19788 +Epoch: [8] [ 760/2138] eta: 1:23:42 lr: 4.0492910156629674e-05 loss: 0.0532 (0.0541) time: 3.6465 data: 0.0030 max mem: 19788 +Epoch: [8] [ 770/2138] eta: 1:23:05 lr: 4.048752343155543e-05 loss: 0.0526 (0.0541) time: 3.6417 data: 0.0029 max mem: 19788 +Epoch: [8] [ 780/2138] eta: 1:22:29 lr: 4.048213662684832e-05 loss: 0.0505 (0.0541) time: 3.6342 data: 0.0028 max mem: 19788 +Epoch: [8] [ 790/2138] eta: 1:21:52 lr: 4.047674974249539e-05 loss: 0.0564 (0.0541) time: 3.6321 data: 0.0027 max mem: 19788 +Epoch: [8] [ 800/2138] eta: 1:21:15 lr: 4.0471362778483705e-05 loss: 0.0503 (0.0540) time: 3.6282 data: 0.0027 max mem: 19788 +Epoch: [8] [ 810/2138] eta: 1:20:39 lr: 4.046597573480029e-05 loss: 0.0455 (0.0539) time: 3.6305 data: 0.0027 max mem: 19788 +Epoch: [8] [ 820/2138] eta: 1:20:02 lr: 4.046058861143218e-05 loss: 0.0469 (0.0539) time: 3.6357 data: 0.0027 max mem: 19788 +Epoch: [8] [ 830/2138] eta: 1:19:25 lr: 4.045520140836641e-05 loss: 0.0498 (0.0540) time: 3.6383 data: 0.0031 max mem: 19788 +Epoch: [8] [ 840/2138] eta: 1:18:49 lr: 4.0449814125590014e-05 loss: 0.0487 (0.0540) time: 3.6420 data: 0.0033 max mem: 19788 +Epoch: [8] [ 850/2138] eta: 1:18:13 lr: 4.044442676309e-05 loss: 0.0465 (0.0539) time: 3.6452 data: 0.0032 max mem: 19788 +Epoch: [8] [ 860/2138] eta: 1:17:36 lr: 4.0439039320853414e-05 loss: 0.0465 (0.0539) time: 3.6373 data: 0.0032 max mem: 19788 +Epoch: [8] [ 870/2138] eta: 1:16:59 lr: 4.043365179886726e-05 loss: 0.0490 (0.0539) time: 3.6277 data: 0.0032 max mem: 19788 +Epoch: [8] [ 880/2138] eta: 1:16:23 lr: 4.042826419711854e-05 loss: 0.0490 (0.0538) time: 3.6267 data: 0.0030 max mem: 19788 +Epoch: [8] [ 890/2138] eta: 1:15:46 lr: 4.042287651559428e-05 loss: 0.0494 (0.0538) time: 3.6348 data: 0.0028 max mem: 19788 +Epoch: [8] [ 900/2138] eta: 1:15:09 lr: 4.0417488754281475e-05 loss: 0.0525 (0.0539) time: 3.6292 data: 0.0029 max mem: 19788 +Epoch: [8] [ 910/2138] eta: 1:14:33 lr: 4.041210091316712e-05 loss: 0.0496 (0.0539) time: 3.6251 data: 0.0028 max mem: 19788 +Epoch: [8] [ 920/2138] eta: 1:13:56 lr: 4.040671299223822e-05 loss: 0.0467 (0.0540) time: 3.6333 data: 0.0032 max mem: 19788 +Epoch: [8] [ 930/2138] eta: 1:13:20 lr: 4.0401324991481766e-05 loss: 0.0535 (0.0540) time: 3.6420 data: 0.0036 max mem: 19788 +Epoch: [8] [ 940/2138] eta: 1:12:43 lr: 4.0395936910884746e-05 loss: 0.0538 (0.0541) time: 3.6408 data: 0.0036 max mem: 19788 +Epoch: [8] [ 950/2138] eta: 1:12:07 lr: 4.0390548750434136e-05 loss: 0.0516 (0.0541) time: 3.6299 data: 0.0033 max mem: 19788 +Epoch: [8] [ 960/2138] eta: 1:11:30 lr: 4.0385160510116924e-05 loss: 0.0508 (0.0542) time: 3.6303 data: 0.0030 max mem: 19788 +Epoch: [8] [ 970/2138] eta: 1:10:54 lr: 4.037977218992009e-05 loss: 0.0466 (0.0541) time: 3.6294 data: 0.0029 max mem: 19788 +Epoch: [8] [ 980/2138] eta: 1:10:17 lr: 4.03743837898306e-05 loss: 0.0431 (0.0540) time: 3.6298 data: 0.0031 max mem: 19788 +Epoch: [8] [ 990/2138] eta: 1:09:41 lr: 4.0368995309835415e-05 loss: 0.0487 (0.0540) time: 3.6330 data: 0.0030 max mem: 19788 +Epoch: [8] [1000/2138] eta: 1:09:04 lr: 4.036360674992151e-05 loss: 0.0532 (0.0540) time: 3.6280 data: 0.0029 max mem: 19788 +Epoch: [8] [1010/2138] eta: 1:08:27 lr: 4.035821811007585e-05 loss: 0.0483 (0.0539) time: 3.6282 data: 0.0027 max mem: 19788 +Epoch: [8] [1020/2138] eta: 1:07:51 lr: 4.035282939028537e-05 loss: 0.0455 (0.0538) time: 3.6300 data: 0.0028 max mem: 19788 +Epoch: [8] [1030/2138] eta: 1:07:14 lr: 4.034744059053703e-05 loss: 0.0443 (0.0538) time: 3.6286 data: 0.0029 max mem: 19788 +Epoch: [8] [1040/2138] eta: 1:06:38 lr: 4.0342051710817785e-05 loss: 0.0445 (0.0538) time: 3.6273 data: 0.0027 max mem: 19788 +Epoch: [8] [1050/2138] eta: 1:06:01 lr: 4.0336662751114576e-05 loss: 0.0480 (0.0537) time: 3.6306 data: 0.0027 max mem: 19788 +Epoch: [8] [1060/2138] eta: 1:05:25 lr: 4.033127371141434e-05 loss: 0.0467 (0.0537) time: 3.6312 data: 0.0029 max mem: 19788 +Epoch: [8] [1070/2138] eta: 1:04:48 lr: 4.0325884591704e-05 loss: 0.0466 (0.0538) time: 3.6323 data: 0.0033 max mem: 19788 +Epoch: [8] [1080/2138] eta: 1:04:12 lr: 4.0320495391970515e-05 loss: 0.0506 (0.0537) time: 3.6295 data: 0.0032 max mem: 19788 +Epoch: [8] [1090/2138] eta: 1:03:35 lr: 4.0315106112200796e-05 loss: 0.0515 (0.0537) time: 3.6247 data: 0.0028 max mem: 19788 +Epoch: [8] [1100/2138] eta: 1:02:59 lr: 4.030971675238176e-05 loss: 0.0551 (0.0538) time: 3.6310 data: 0.0029 max mem: 19788 +Epoch: [8] [1110/2138] eta: 1:02:22 lr: 4.030432731250033e-05 loss: 0.0519 (0.0538) time: 3.6328 data: 0.0031 max mem: 19788 +Epoch: [8] [1120/2138] eta: 1:01:46 lr: 4.029893779254343e-05 loss: 0.0473 (0.0539) time: 3.6283 data: 0.0031 max mem: 19788 +Epoch: [8] [1130/2138] eta: 1:01:09 lr: 4.029354819249796e-05 loss: 0.0549 (0.0540) time: 3.6292 data: 0.0029 max mem: 19788 +Epoch: [8] [1140/2138] eta: 1:00:33 lr: 4.028815851235084e-05 loss: 0.0636 (0.0541) time: 3.6295 data: 0.0027 max mem: 19788 +Epoch: [8] [1150/2138] eta: 0:59:56 lr: 4.0282768752088956e-05 loss: 0.0438 (0.0540) time: 3.6303 data: 0.0030 max mem: 19788 +Epoch: [8] [1160/2138] eta: 0:59:20 lr: 4.027737891169922e-05 loss: 0.0382 (0.0540) time: 3.6309 data: 0.0030 max mem: 19788 +Epoch: [8] [1170/2138] eta: 0:58:43 lr: 4.0271988991168516e-05 loss: 0.0444 (0.0540) time: 3.6237 data: 0.0029 max mem: 19788 +Epoch: [8] [1180/2138] eta: 0:58:07 lr: 4.0266598990483736e-05 loss: 0.0610 (0.0541) time: 3.6281 data: 0.0031 max mem: 19788 +Epoch: [8] [1190/2138] eta: 0:57:30 lr: 4.0261208909631774e-05 loss: 0.0633 (0.0542) time: 3.6379 data: 0.0029 max mem: 19788 +Epoch: [8] [1200/2138] eta: 0:56:54 lr: 4.0255818748599504e-05 loss: 0.0578 (0.0542) time: 3.6347 data: 0.0027 max mem: 19788 +Epoch: [8] [1210/2138] eta: 0:56:17 lr: 4.025042850737381e-05 loss: 0.0489 (0.0541) time: 3.6322 data: 0.0027 max mem: 19788 +Epoch: [8] [1220/2138] eta: 0:55:41 lr: 4.024503818594156e-05 loss: 0.0549 (0.0543) time: 3.6279 data: 0.0027 max mem: 19788 +Epoch: [8] [1230/2138] eta: 0:55:04 lr: 4.0239647784289634e-05 loss: 0.0555 (0.0543) time: 3.6330 data: 0.0028 max mem: 19788 +Epoch: [8] [1240/2138] eta: 0:54:28 lr: 4.023425730240489e-05 loss: 0.0479 (0.0543) time: 3.6368 data: 0.0027 max mem: 19788 +Epoch: [8] [1250/2138] eta: 0:53:51 lr: 4.022886674027419e-05 loss: 0.0465 (0.0543) time: 3.6265 data: 0.0028 max mem: 19788 +Epoch: [8] [1260/2138] eta: 0:53:15 lr: 4.0223476097884394e-05 loss: 0.0509 (0.0543) time: 3.6254 data: 0.0027 max mem: 19788 +Epoch: [8] [1270/2138] eta: 0:52:38 lr: 4.0218085375222354e-05 loss: 0.0537 (0.0543) time: 3.6242 data: 0.0026 max mem: 19788 +Epoch: [8] [1280/2138] eta: 0:52:02 lr: 4.021269457227492e-05 loss: 0.0444 (0.0543) time: 3.6291 data: 0.0026 max mem: 19788 +Epoch: [8] [1290/2138] eta: 0:51:26 lr: 4.020730368902893e-05 loss: 0.0505 (0.0544) time: 3.6341 data: 0.0026 max mem: 19788 +Epoch: [8] [1300/2138] eta: 0:50:49 lr: 4.0201912725471236e-05 loss: 0.0559 (0.0543) time: 3.6354 data: 0.0027 max mem: 19788 +Epoch: [8] [1310/2138] eta: 0:50:13 lr: 4.0196521681588674e-05 loss: 0.0459 (0.0543) time: 3.6347 data: 0.0029 max mem: 19788 +Epoch: [8] [1320/2138] eta: 0:49:36 lr: 4.019113055736807e-05 loss: 0.0453 (0.0543) time: 3.6242 data: 0.0032 max mem: 19788 +Epoch: [8] [1330/2138] eta: 0:49:00 lr: 4.0185739352796253e-05 loss: 0.0421 (0.0542) time: 3.6307 data: 0.0030 max mem: 19788 +Epoch: [8] [1340/2138] eta: 0:48:23 lr: 4.0180348067860055e-05 loss: 0.0474 (0.0544) time: 3.6335 data: 0.0030 max mem: 19788 +Epoch: [8] [1350/2138] eta: 0:47:47 lr: 4.017495670254629e-05 loss: 0.0613 (0.0544) time: 3.6287 data: 0.0030 max mem: 19788 +Epoch: [8] [1360/2138] eta: 0:47:10 lr: 4.016956525684178e-05 loss: 0.0565 (0.0544) time: 3.6302 data: 0.0028 max mem: 19788 +Epoch: [8] [1370/2138] eta: 0:46:34 lr: 4.0164173730733335e-05 loss: 0.0443 (0.0544) time: 3.6264 data: 0.0030 max mem: 19788 +Epoch: [8] [1380/2138] eta: 0:45:58 lr: 4.0158782124207756e-05 loss: 0.0509 (0.0544) time: 3.6254 data: 0.0031 max mem: 19788 +Epoch: [8] [1390/2138] eta: 0:45:21 lr: 4.015339043725186e-05 loss: 0.0532 (0.0544) time: 3.6275 data: 0.0031 max mem: 19788 +Epoch: [8] [1400/2138] eta: 0:44:45 lr: 4.0147998669852435e-05 loss: 0.0472 (0.0543) time: 3.6305 data: 0.0029 max mem: 19788 +Epoch: [8] [1410/2138] eta: 0:44:08 lr: 4.014260682199628e-05 loss: 0.0477 (0.0543) time: 3.6345 data: 0.0027 max mem: 19788 +Epoch: [8] [1420/2138] eta: 0:43:32 lr: 4.013721489367019e-05 loss: 0.0460 (0.0542) time: 3.6303 data: 0.0028 max mem: 19788 +Epoch: [8] [1430/2138] eta: 0:42:55 lr: 4.013182288486096e-05 loss: 0.0474 (0.0542) time: 3.6285 data: 0.0029 max mem: 19788 +Epoch: [8] [1440/2138] eta: 0:42:19 lr: 4.012643079555535e-05 loss: 0.0490 (0.0542) time: 3.6372 data: 0.0027 max mem: 19788 +Epoch: [8] [1450/2138] eta: 0:41:43 lr: 4.0121038625740164e-05 loss: 0.0475 (0.0542) time: 3.6331 data: 0.0028 max mem: 19788 +Epoch: [8] [1460/2138] eta: 0:41:06 lr: 4.011564637540216e-05 loss: 0.0548 (0.0542) time: 3.6396 data: 0.0029 max mem: 19788 +Epoch: [8] [1470/2138] eta: 0:40:30 lr: 4.011025404452812e-05 loss: 0.0578 (0.0542) time: 3.6360 data: 0.0027 max mem: 19788 +Epoch: [8] [1480/2138] eta: 0:39:53 lr: 4.01048616331048e-05 loss: 0.0532 (0.0543) time: 3.6229 data: 0.0027 max mem: 19788 +Epoch: [8] [1490/2138] eta: 0:39:17 lr: 4.009946914111897e-05 loss: 0.0478 (0.0542) time: 3.6303 data: 0.0027 max mem: 19788 +Epoch: [8] [1500/2138] eta: 0:38:41 lr: 4.009407656855739e-05 loss: 0.0470 (0.0542) time: 3.6273 data: 0.0026 max mem: 19788 +Epoch: [8] [1510/2138] eta: 0:38:04 lr: 4.0088683915406803e-05 loss: 0.0511 (0.0542) time: 3.6261 data: 0.0028 max mem: 19788 +Epoch: [8] [1520/2138] eta: 0:37:28 lr: 4.008329118165397e-05 loss: 0.0431 (0.0542) time: 3.6297 data: 0.0031 max mem: 19788 +Epoch: [8] [1530/2138] eta: 0:36:51 lr: 4.0077898367285635e-05 loss: 0.0426 (0.0541) time: 3.6361 data: 0.0031 max mem: 19788 +Epoch: [8] [1540/2138] eta: 0:36:15 lr: 4.007250547228855e-05 loss: 0.0437 (0.0541) time: 3.6347 data: 0.0030 max mem: 19788 +Epoch: [8] [1550/2138] eta: 0:35:39 lr: 4.006711249664942e-05 loss: 0.0504 (0.0541) time: 3.6267 data: 0.0029 max mem: 19788 +Epoch: [8] [1560/2138] eta: 0:35:02 lr: 4.0061719440355016e-05 loss: 0.0499 (0.0541) time: 3.6251 data: 0.0028 max mem: 19788 +Epoch: [8] [1570/2138] eta: 0:34:26 lr: 4.0056326303392046e-05 loss: 0.0482 (0.0541) time: 3.6310 data: 0.0030 max mem: 19788 +Epoch: [8] [1580/2138] eta: 0:33:49 lr: 4.0050933085747236e-05 loss: 0.0431 (0.0540) time: 3.6295 data: 0.0029 max mem: 19788 +Epoch: [8] [1590/2138] eta: 0:33:13 lr: 4.004553978740732e-05 loss: 0.0444 (0.0540) time: 3.6216 data: 0.0029 max mem: 19788 +Epoch: [8] [1600/2138] eta: 0:32:36 lr: 4.0040146408359e-05 loss: 0.0534 (0.0541) time: 3.6217 data: 0.0030 max mem: 19788 +Epoch: [8] [1610/2138] eta: 0:32:00 lr: 4.0034752948588986e-05 loss: 0.0473 (0.0540) time: 3.6232 data: 0.0029 max mem: 19788 +Epoch: [8] [1620/2138] eta: 0:31:24 lr: 4.0029359408084e-05 loss: 0.0453 (0.0540) time: 3.6353 data: 0.0029 max mem: 19788 +Epoch: [8] [1630/2138] eta: 0:30:47 lr: 4.002396578683075e-05 loss: 0.0503 (0.0540) time: 3.6421 data: 0.0028 max mem: 19788 +Epoch: [8] [1640/2138] eta: 0:30:11 lr: 4.0018572084815916e-05 loss: 0.0493 (0.0540) time: 3.6351 data: 0.0028 max mem: 19788 +Epoch: [8] [1650/2138] eta: 0:29:34 lr: 4.001317830202621e-05 loss: 0.0388 (0.0539) time: 3.6294 data: 0.0027 max mem: 19788 +Epoch: [8] [1660/2138] eta: 0:28:58 lr: 4.000778443844832e-05 loss: 0.0427 (0.0539) time: 3.6292 data: 0.0027 max mem: 19788 +Epoch: [8] [1670/2138] eta: 0:28:22 lr: 4.000239049406894e-05 loss: 0.0444 (0.0538) time: 3.6254 data: 0.0030 max mem: 19788 +Epoch: [8] [1680/2138] eta: 0:27:45 lr: 3.999699646887473e-05 loss: 0.0453 (0.0538) time: 3.6235 data: 0.0028 max mem: 19788 +Epoch: [8] [1690/2138] eta: 0:27:09 lr: 3.9991602362852384e-05 loss: 0.0493 (0.0538) time: 3.6368 data: 0.0029 max mem: 19788 +Epoch: [8] [1700/2138] eta: 0:26:33 lr: 3.9986208175988586e-05 loss: 0.0459 (0.0538) time: 3.6375 data: 0.0030 max mem: 19788 +Epoch: [8] [1710/2138] eta: 0:25:56 lr: 3.998081390827e-05 loss: 0.0454 (0.0538) time: 3.6285 data: 0.0028 max mem: 19788 +Epoch: [8] [1720/2138] eta: 0:25:20 lr: 3.997541955968328e-05 loss: 0.0458 (0.0538) time: 3.6341 data: 0.0030 max mem: 19788 +Epoch: [8] [1730/2138] eta: 0:24:43 lr: 3.997002513021511e-05 loss: 0.0513 (0.0538) time: 3.6294 data: 0.0029 max mem: 19788 +Epoch: [8] [1740/2138] eta: 0:24:07 lr: 3.9964630619852127e-05 loss: 0.0484 (0.0537) time: 3.6252 data: 0.0028 max mem: 19788 +Epoch: [8] [1750/2138] eta: 0:23:31 lr: 3.9959236028581006e-05 loss: 0.0444 (0.0537) time: 3.6289 data: 0.0028 max mem: 19788 +Epoch: [8] [1760/2138] eta: 0:22:54 lr: 3.995384135638837e-05 loss: 0.0512 (0.0537) time: 3.6308 data: 0.0028 max mem: 19788 +Epoch: [8] [1770/2138] eta: 0:22:18 lr: 3.9948446603260895e-05 loss: 0.0512 (0.0537) time: 3.6281 data: 0.0028 max mem: 19788 +Epoch: [8] [1780/2138] eta: 0:21:41 lr: 3.99430517691852e-05 loss: 0.0494 (0.0537) time: 3.6268 data: 0.0028 max mem: 19788 +Epoch: [8] [1790/2138] eta: 0:21:05 lr: 3.993765685414793e-05 loss: 0.0504 (0.0537) time: 3.6283 data: 0.0028 max mem: 19788 +Epoch: [8] [1800/2138] eta: 0:20:29 lr: 3.9932261858135723e-05 loss: 0.0527 (0.0538) time: 3.6252 data: 0.0027 max mem: 19788 +Epoch: [8] [1810/2138] eta: 0:19:52 lr: 3.99268667811352e-05 loss: 0.0553 (0.0538) time: 3.6256 data: 0.0028 max mem: 19788 +Epoch: [8] [1820/2138] eta: 0:19:16 lr: 3.9921471623132975e-05 loss: 0.0478 (0.0538) time: 3.6315 data: 0.0028 max mem: 19788 +Epoch: [8] [1830/2138] eta: 0:18:40 lr: 3.9916076384115696e-05 loss: 0.0478 (0.0537) time: 3.6373 data: 0.0029 max mem: 19788 +Epoch: [8] [1840/2138] eta: 0:18:03 lr: 3.991068106406996e-05 loss: 0.0437 (0.0538) time: 3.6475 data: 0.0030 max mem: 19788 +Epoch: [8] [1850/2138] eta: 0:17:27 lr: 3.990528566298238e-05 loss: 0.0461 (0.0538) time: 3.6466 data: 0.0030 max mem: 19788 +Epoch: [8] [1860/2138] eta: 0:16:51 lr: 3.989989018083957e-05 loss: 0.0508 (0.0538) time: 3.6432 data: 0.0031 max mem: 19788 +Epoch: [8] [1870/2138] eta: 0:16:14 lr: 3.9894494617628133e-05 loss: 0.0476 (0.0539) time: 3.6372 data: 0.0030 max mem: 19788 +Epoch: [8] [1880/2138] eta: 0:15:38 lr: 3.988909897333465e-05 loss: 0.0500 (0.0539) time: 3.6360 data: 0.0030 max mem: 19788 +Epoch: [8] [1890/2138] eta: 0:15:01 lr: 3.988370324794575e-05 loss: 0.0447 (0.0539) time: 3.6394 data: 0.0033 max mem: 19788 +Epoch: [8] [1900/2138] eta: 0:14:25 lr: 3.9878307441447985e-05 loss: 0.0373 (0.0538) time: 3.6307 data: 0.0031 max mem: 19788 +Epoch: [8] [1910/2138] eta: 0:13:49 lr: 3.987291155382797e-05 loss: 0.0451 (0.0538) time: 3.6258 data: 0.0029 max mem: 19788 +Epoch: [8] [1920/2138] eta: 0:13:12 lr: 3.986751558507228e-05 loss: 0.0460 (0.0537) time: 3.6263 data: 0.0031 max mem: 19788 +Epoch: [8] [1930/2138] eta: 0:12:36 lr: 3.986211953516749e-05 loss: 0.0460 (0.0537) time: 3.6315 data: 0.0031 max mem: 19788 +Epoch: [8] [1940/2138] eta: 0:12:00 lr: 3.985672340410018e-05 loss: 0.0543 (0.0538) time: 3.6292 data: 0.0027 max mem: 19788 +Epoch: [8] [1950/2138] eta: 0:11:23 lr: 3.98513271918569e-05 loss: 0.0525 (0.0537) time: 3.6311 data: 0.0027 max mem: 19788 +Epoch: [8] [1960/2138] eta: 0:10:47 lr: 3.984593089842424e-05 loss: 0.0395 (0.0537) time: 3.6383 data: 0.0028 max mem: 19788 +Epoch: [8] [1970/2138] eta: 0:10:10 lr: 3.984053452378875e-05 loss: 0.0460 (0.0537) time: 3.6456 data: 0.0028 max mem: 19788 +Epoch: [8] [1980/2138] eta: 0:09:34 lr: 3.983513806793698e-05 loss: 0.0481 (0.0537) time: 3.6456 data: 0.0029 max mem: 19788 +Epoch: [8] [1990/2138] eta: 0:08:58 lr: 3.982974153085549e-05 loss: 0.0461 (0.0537) time: 3.6313 data: 0.0029 max mem: 19788 +Epoch: [8] [2000/2138] eta: 0:08:21 lr: 3.982434491253083e-05 loss: 0.0502 (0.0537) time: 3.6224 data: 0.0029 max mem: 19788 +Epoch: [8] [2010/2138] eta: 0:07:45 lr: 3.981894821294954e-05 loss: 0.0502 (0.0537) time: 3.6297 data: 0.0029 max mem: 19788 +Epoch: [8] [2020/2138] eta: 0:07:09 lr: 3.981355143209817e-05 loss: 0.0500 (0.0537) time: 3.6333 data: 0.0029 max mem: 19788 +Epoch: [8] [2030/2138] eta: 0:06:32 lr: 3.9808154569963236e-05 loss: 0.0500 (0.0537) time: 3.6274 data: 0.0028 max mem: 19788 +Epoch: [8] [2040/2138] eta: 0:05:56 lr: 3.9802757626531284e-05 loss: 0.0474 (0.0537) time: 3.6265 data: 0.0029 max mem: 19788 +Epoch: [8] [2050/2138] eta: 0:05:19 lr: 3.979736060178884e-05 loss: 0.0488 (0.0537) time: 3.6308 data: 0.0029 max mem: 19788 +Epoch: [8] [2060/2138] eta: 0:04:43 lr: 3.979196349572242e-05 loss: 0.0488 (0.0536) time: 3.6277 data: 0.0026 max mem: 19788 +Epoch: [8] [2070/2138] eta: 0:04:07 lr: 3.9786566308318546e-05 loss: 0.0474 (0.0536) time: 3.6298 data: 0.0026 max mem: 19788 +Epoch: [8] [2080/2138] eta: 0:03:30 lr: 3.9781169039563736e-05 loss: 0.0466 (0.0536) time: 3.6337 data: 0.0026 max mem: 19788 +Epoch: [8] [2090/2138] eta: 0:02:54 lr: 3.9775771689444494e-05 loss: 0.0470 (0.0536) time: 3.6325 data: 0.0026 max mem: 19788 +Epoch: [8] [2100/2138] eta: 0:02:18 lr: 3.9770374257947326e-05 loss: 0.0441 (0.0535) time: 3.6267 data: 0.0027 max mem: 19788 +Epoch: [8] [2110/2138] eta: 0:01:41 lr: 3.9764976745058736e-05 loss: 0.0526 (0.0536) time: 3.6264 data: 0.0027 max mem: 19788 +Epoch: [8] [2120/2138] eta: 0:01:05 lr: 3.975957915076522e-05 loss: 0.0611 (0.0536) time: 3.6314 data: 0.0027 max mem: 19788 +Epoch: [8] [2130/2138] eta: 0:00:29 lr: 3.975418147505327e-05 loss: 0.0568 (0.0536) time: 3.6163 data: 0.0028 max mem: 19788 +Epoch: [8] Total time: 2:09:34 +Test: [ 0/21770] eta: 13:36:01 time: 2.2491 data: 1.8392 max mem: 19788 +Test: [ 100/21770] eta: 0:33:59 time: 0.0694 data: 0.0020 max mem: 19788 +Test: [ 200/21770] eta: 0:28:34 time: 0.0616 data: 0.0019 max mem: 19788 +Test: [ 300/21770] eta: 0:27:28 time: 0.0683 data: 0.0021 max mem: 19788 +Test: [ 400/21770] eta: 0:26:49 time: 0.0762 data: 0.0020 max mem: 19788 +Test: [ 500/21770] eta: 0:26:00 time: 0.0669 data: 0.0021 max mem: 19788 +Test: [ 600/21770] eta: 0:25:44 time: 0.0639 data: 0.0022 max mem: 19788 +Test: [ 700/21770] eta: 0:25:26 time: 0.0848 data: 0.0020 max mem: 19788 +Test: [ 800/21770] eta: 0:25:05 time: 0.0631 data: 0.0019 max mem: 19788 +Test: [ 900/21770] eta: 0:25:08 time: 0.0841 data: 0.0025 max mem: 19788 +Test: [ 1000/21770] eta: 0:24:52 time: 0.0626 data: 0.0020 max mem: 19788 +Test: [ 1100/21770] eta: 0:24:30 time: 0.0626 data: 0.0019 max mem: 19788 +Test: [ 1200/21770] eta: 0:24:35 time: 0.0839 data: 0.0024 max mem: 19788 +Test: [ 1300/21770] eta: 0:24:42 time: 0.0714 data: 0.0022 max mem: 19788 +Test: [ 1400/21770] eta: 0:24:51 time: 0.0841 data: 0.0024 max mem: 19788 +Test: [ 1500/21770] eta: 0:24:58 time: 0.0836 data: 0.0026 max mem: 19788 +Test: [ 1600/21770] eta: 0:24:59 time: 0.0849 data: 0.0026 max mem: 19788 +Test: [ 1700/21770] eta: 0:25:07 time: 0.0870 data: 0.0026 max mem: 19788 +Test: [ 1800/21770] eta: 0:25:13 time: 0.0877 data: 0.0025 max mem: 19788 +Test: [ 1900/21770] eta: 0:25:14 time: 0.0869 data: 0.0028 max mem: 19788 +Test: [ 2000/21770] eta: 0:25:12 time: 0.0697 data: 0.0022 max mem: 19788 +Test: [ 2100/21770] eta: 0:25:00 time: 0.0797 data: 0.0024 max mem: 19788 +Test: [ 2200/21770] eta: 0:25:02 time: 0.0879 data: 0.0028 max mem: 19788 +Test: [ 2300/21770] eta: 0:24:51 time: 0.0655 data: 0.0020 max mem: 19788 +Test: [ 2400/21770] eta: 0:24:40 time: 0.0753 data: 0.0024 max mem: 19788 +Test: [ 2500/21770] eta: 0:24:31 time: 0.0862 data: 0.0026 max mem: 19788 +Test: [ 2600/21770] eta: 0:24:25 time: 0.0888 data: 0.0029 max mem: 19788 +Test: [ 2700/21770] eta: 0:24:17 time: 0.0833 data: 0.0022 max mem: 19788 +Test: [ 2800/21770] eta: 0:24:08 time: 0.0759 data: 0.0024 max mem: 19788 +Test: [ 2900/21770] eta: 0:23:54 time: 0.0683 data: 0.0021 max mem: 19788 +Test: [ 3000/21770] eta: 0:23:46 time: 0.0680 data: 0.0023 max mem: 19788 +Test: [ 3100/21770] eta: 0:23:42 time: 0.0690 data: 0.0021 max mem: 19788 +Test: [ 3200/21770] eta: 0:23:33 time: 0.0888 data: 0.0026 max mem: 19788 +Test: [ 3300/21770] eta: 0:23:28 time: 0.0900 data: 0.0027 max mem: 19788 +Test: [ 3400/21770] eta: 0:23:21 time: 0.0829 data: 0.0027 max mem: 19788 +Test: [ 3500/21770] eta: 0:23:10 time: 0.0680 data: 0.0021 max mem: 19788 +Test: [ 3600/21770] eta: 0:23:05 time: 0.0691 data: 0.0022 max mem: 19788 +Test: [ 3700/21770] eta: 0:22:58 time: 0.0708 data: 0.0022 max mem: 19788 +Test: [ 3800/21770] eta: 0:22:46 time: 0.0674 data: 0.0022 max mem: 19788 +Test: [ 3900/21770] eta: 0:22:39 time: 0.0817 data: 0.0026 max mem: 19788 +Test: [ 4000/21770] eta: 0:22:35 time: 0.0866 data: 0.0026 max mem: 19788 +Test: [ 4100/21770] eta: 0:22:27 time: 0.0739 data: 0.0026 max mem: 19788 +Test: [ 4200/21770] eta: 0:22:21 time: 0.0866 data: 0.0028 max mem: 19788 +Test: [ 4300/21770] eta: 0:22:17 time: 0.0853 data: 0.0028 max mem: 19788 +Test: [ 4400/21770] eta: 0:22:07 time: 0.0853 data: 0.0025 max mem: 19788 +Test: [ 4500/21770] eta: 0:21:59 time: 0.0869 data: 0.0029 max mem: 19788 +Test: [ 4600/21770] eta: 0:21:55 time: 0.0881 data: 0.0029 max mem: 19788 +Test: [ 4700/21770] eta: 0:21:46 time: 0.0658 data: 0.0022 max mem: 19788 +Test: [ 4800/21770] eta: 0:21:37 time: 0.0874 data: 0.0023 max mem: 19788 +Test: [ 4900/21770] eta: 0:21:28 time: 0.0704 data: 0.0025 max mem: 19788 +Test: [ 5000/21770] eta: 0:21:24 time: 0.0892 data: 0.0025 max mem: 19788 +Test: [ 5100/21770] eta: 0:21:17 time: 0.0704 data: 0.0024 max mem: 19788 +Test: [ 5200/21770] eta: 0:21:07 time: 0.0696 data: 0.0021 max mem: 19788 +Test: [ 5300/21770] eta: 0:20:57 time: 0.0685 data: 0.0022 max mem: 19788 +Test: [ 5400/21770] eta: 0:20:47 time: 0.0647 data: 0.0019 max mem: 19788 +Test: [ 5500/21770] eta: 0:20:38 time: 0.0657 data: 0.0022 max mem: 19788 +Test: [ 5600/21770] eta: 0:20:28 time: 0.0673 data: 0.0024 max mem: 19788 +Test: [ 5700/21770] eta: 0:20:19 time: 0.0887 data: 0.0025 max mem: 19788 +Test: [ 5800/21770] eta: 0:20:12 time: 0.0873 data: 0.0029 max mem: 19788 +Test: [ 5900/21770] eta: 0:20:05 time: 0.0835 data: 0.0027 max mem: 19788 +Test: [ 6000/21770] eta: 0:19:59 time: 0.0684 data: 0.0021 max mem: 19788 +Test: [ 6100/21770] eta: 0:19:49 time: 0.0649 data: 0.0023 max mem: 19788 +Test: [ 6200/21770] eta: 0:19:40 time: 0.0792 data: 0.0026 max mem: 19788 +Test: [ 6300/21770] eta: 0:19:32 time: 0.0678 data: 0.0020 max mem: 19788 +Test: [ 6400/21770] eta: 0:19:23 time: 0.0772 data: 0.0025 max mem: 19788 +Test: [ 6500/21770] eta: 0:19:15 time: 0.0671 data: 0.0021 max mem: 19788 +Test: [ 6600/21770] eta: 0:19:07 time: 0.0900 data: 0.0026 max mem: 19788 +Test: [ 6700/21770] eta: 0:19:03 time: 0.0901 data: 0.0028 max mem: 19788 +Test: [ 6800/21770] eta: 0:18:58 time: 0.0889 data: 0.0026 max mem: 19788 +Test: [ 6900/21770] eta: 0:18:53 time: 0.0887 data: 0.0025 max mem: 19788 +Test: [ 7000/21770] eta: 0:18:48 time: 0.0879 data: 0.0025 max mem: 19788 +Test: [ 7100/21770] eta: 0:18:43 time: 0.0880 data: 0.0026 max mem: 19788 +Test: [ 7200/21770] eta: 0:18:38 time: 0.0885 data: 0.0027 max mem: 19788 +Test: [ 7300/21770] eta: 0:18:32 time: 0.0872 data: 0.0025 max mem: 19788 +Test: [ 7400/21770] eta: 0:18:27 time: 0.0884 data: 0.0028 max mem: 19788 +Test: [ 7500/21770] eta: 0:18:21 time: 0.0890 data: 0.0031 max mem: 19788 +Test: [ 7600/21770] eta: 0:18:16 time: 0.0888 data: 0.0031 max mem: 19788 +Test: [ 7700/21770] eta: 0:18:10 time: 0.0897 data: 0.0024 max mem: 19788 +Test: [ 7800/21770] eta: 0:18:02 time: 0.0692 data: 0.0023 max mem: 19788 +Test: [ 7900/21770] eta: 0:17:55 time: 0.0784 data: 0.0022 max mem: 19788 +Test: [ 8000/21770] eta: 0:17:46 time: 0.0724 data: 0.0021 max mem: 19788 +Test: [ 8100/21770] eta: 0:17:39 time: 0.0796 data: 0.0024 max mem: 19788 +Test: [ 8200/21770] eta: 0:17:33 time: 0.0892 data: 0.0027 max mem: 19788 +Test: [ 8300/21770] eta: 0:17:26 time: 0.0753 data: 0.0024 max mem: 19788 +Test: [ 8400/21770] eta: 0:17:19 time: 0.0865 data: 0.0029 max mem: 19788 +Test: [ 8500/21770] eta: 0:17:10 time: 0.0679 data: 0.0022 max mem: 19788 +Test: [ 8600/21770] eta: 0:17:02 time: 0.0669 data: 0.0019 max mem: 19788 +Test: [ 8700/21770] eta: 0:16:52 time: 0.0679 data: 0.0020 max mem: 19788 +Test: [ 8800/21770] eta: 0:16:45 time: 0.0891 data: 0.0023 max mem: 19788 +Test: [ 8900/21770] eta: 0:16:38 time: 0.0724 data: 0.0025 max mem: 19788 +Test: [ 9000/21770] eta: 0:16:29 time: 0.0800 data: 0.0026 max mem: 19788 +Test: [ 9100/21770] eta: 0:16:22 time: 0.0687 data: 0.0021 max mem: 19788 +Test: [ 9200/21770] eta: 0:16:13 time: 0.0709 data: 0.0022 max mem: 19788 +Test: [ 9300/21770] eta: 0:16:05 time: 0.0688 data: 0.0021 max mem: 19788 +Test: [ 9400/21770] eta: 0:15:57 time: 0.0898 data: 0.0029 max mem: 19788 +Test: [ 9500/21770] eta: 0:15:50 time: 0.0679 data: 0.0025 max mem: 19788 +Test: [ 9600/21770] eta: 0:15:44 time: 0.0906 data: 0.0030 max mem: 19788 +Test: [ 9700/21770] eta: 0:15:36 time: 0.0720 data: 0.0021 max mem: 19788 +Test: [ 9800/21770] eta: 0:15:28 time: 0.0691 data: 0.0023 max mem: 19788 +Test: [ 9900/21770] eta: 0:15:19 time: 0.0702 data: 0.0023 max mem: 19788 +Test: [10000/21770] eta: 0:15:10 time: 0.0694 data: 0.0021 max mem: 19788 +Test: [10100/21770] eta: 0:15:02 time: 0.0662 data: 0.0020 max mem: 19788 +Test: [10200/21770] eta: 0:14:54 time: 0.0890 data: 0.0030 max mem: 19788 +Test: [10300/21770] eta: 0:14:47 time: 0.0722 data: 0.0021 max mem: 19788 +Test: [10400/21770] eta: 0:14:40 time: 0.0890 data: 0.0025 max mem: 19788 +Test: [10500/21770] eta: 0:14:33 time: 0.0795 data: 0.0023 max mem: 19788 +Test: [10600/21770] eta: 0:14:26 time: 0.0870 data: 0.0027 max mem: 19788 +Test: [10700/21770] eta: 0:14:19 time: 0.0873 data: 0.0025 max mem: 19788 +Test: [10800/21770] eta: 0:14:11 time: 0.0746 data: 0.0022 max mem: 19788 +Test: [10900/21770] eta: 0:14:03 time: 0.0872 data: 0.0025 max mem: 19788 +Test: [11000/21770] eta: 0:13:57 time: 0.0885 data: 0.0029 max mem: 19788 +Test: [11100/21770] eta: 0:13:48 time: 0.0780 data: 0.0026 max mem: 19788 +Test: [11200/21770] eta: 0:13:40 time: 0.0666 data: 0.0020 max mem: 19788 +Test: [11300/21770] eta: 0:13:32 time: 0.0904 data: 0.0028 max mem: 19788 +Test: [11400/21770] eta: 0:13:26 time: 0.0893 data: 0.0025 max mem: 19788 +Test: [11500/21770] eta: 0:13:19 time: 0.0897 data: 0.0027 max mem: 19788 +Test: [11600/21770] eta: 0:13:12 time: 0.0899 data: 0.0026 max mem: 19788 +Test: [11700/21770] eta: 0:13:05 time: 0.0893 data: 0.0026 max mem: 19788 +Test: [11800/21770] eta: 0:12:57 time: 0.0689 data: 0.0024 max mem: 19788 +Test: [11900/21770] eta: 0:12:50 time: 0.0878 data: 0.0028 max mem: 19788 +Test: [12000/21770] eta: 0:12:42 time: 0.0757 data: 0.0024 max mem: 19788 +Test: [12100/21770] eta: 0:12:34 time: 0.0686 data: 0.0021 max mem: 19788 +Test: [12200/21770] eta: 0:12:27 time: 0.0878 data: 0.0025 max mem: 19788 +Test: [12300/21770] eta: 0:12:20 time: 0.0710 data: 0.0023 max mem: 19788 +Test: [12400/21770] eta: 0:12:12 time: 0.0831 data: 0.0026 max mem: 19788 +Test: [12500/21770] eta: 0:12:04 time: 0.0700 data: 0.0022 max mem: 19788 +Test: [12600/21770] eta: 0:11:56 time: 0.0677 data: 0.0020 max mem: 19788 +Test: [12700/21770] eta: 0:11:48 time: 0.0873 data: 0.0026 max mem: 19788 +Test: [12800/21770] eta: 0:11:40 time: 0.0750 data: 0.0021 max mem: 19788 +Test: [12900/21770] eta: 0:11:32 time: 0.0669 data: 0.0022 max mem: 19788 +Test: [13000/21770] eta: 0:11:24 time: 0.0682 data: 0.0022 max mem: 19788 +Test: [13100/21770] eta: 0:11:15 time: 0.0711 data: 0.0024 max mem: 19788 +Test: [13200/21770] eta: 0:11:08 time: 0.0888 data: 0.0027 max mem: 19788 +Test: [13300/21770] eta: 0:11:00 time: 0.0763 data: 0.0023 max mem: 19788 +Test: [13400/21770] eta: 0:10:53 time: 0.0887 data: 0.0021 max mem: 19788 +Test: [13500/21770] eta: 0:10:44 time: 0.0708 data: 0.0025 max mem: 19788 +Test: [13600/21770] eta: 0:10:37 time: 0.0889 data: 0.0028 max mem: 19788 +Test: [13700/21770] eta: 0:10:29 time: 0.0698 data: 0.0021 max mem: 19788 +Test: [13800/21770] eta: 0:10:21 time: 0.0890 data: 0.0025 max mem: 19788 +Test: [13900/21770] eta: 0:10:13 time: 0.0703 data: 0.0021 max mem: 19788 +Test: [14000/21770] eta: 0:10:05 time: 0.0715 data: 0.0023 max mem: 19788 +Test: [14100/21770] eta: 0:09:58 time: 0.0891 data: 0.0028 max mem: 19788 +Test: [14200/21770] eta: 0:09:50 time: 0.0900 data: 0.0031 max mem: 19788 +Test: [14300/21770] eta: 0:09:43 time: 0.0834 data: 0.0030 max mem: 19788 +Test: [14400/21770] eta: 0:09:35 time: 0.0679 data: 0.0022 max mem: 19788 +Test: [14500/21770] eta: 0:09:27 time: 0.0728 data: 0.0024 max mem: 19788 +Test: [14600/21770] eta: 0:09:19 time: 0.0694 data: 0.0024 max mem: 19788 +Test: [14700/21770] eta: 0:09:11 time: 0.0879 data: 0.0025 max mem: 19788 +Test: [14800/21770] eta: 0:09:04 time: 0.0877 data: 0.0026 max mem: 19788 +Test: [14900/21770] eta: 0:08:56 time: 0.0670 data: 0.0020 max mem: 19788 +Test: [15000/21770] eta: 0:08:48 time: 0.0676 data: 0.0022 max mem: 19788 +Test: [15100/21770] eta: 0:08:40 time: 0.0857 data: 0.0027 max mem: 19788 +Test: [15200/21770] eta: 0:08:32 time: 0.0845 data: 0.0026 max mem: 19788 +Test: [15300/21770] eta: 0:08:25 time: 0.0658 data: 0.0022 max mem: 19788 +Test: [15400/21770] eta: 0:08:17 time: 0.0754 data: 0.0024 max mem: 19788 +Test: [15500/21770] eta: 0:08:09 time: 0.0768 data: 0.0024 max mem: 19788 +Test: [15600/21770] eta: 0:08:01 time: 0.0715 data: 0.0022 max mem: 19788 +Test: [15700/21770] eta: 0:07:53 time: 0.0704 data: 0.0022 max mem: 19788 +Test: [15800/21770] eta: 0:07:45 time: 0.0865 data: 0.0026 max mem: 19788 +Test: [15900/21770] eta: 0:07:38 time: 0.0900 data: 0.0030 max mem: 19788 +Test: [16000/21770] eta: 0:07:30 time: 0.0707 data: 0.0024 max mem: 19788 +Test: [16100/21770] eta: 0:07:22 time: 0.0807 data: 0.0023 max mem: 19788 +Test: [16200/21770] eta: 0:07:14 time: 0.0716 data: 0.0022 max mem: 19788 +Test: [16300/21770] eta: 0:07:06 time: 0.0873 data: 0.0025 max mem: 19788 +Test: [16400/21770] eta: 0:06:59 time: 0.0872 data: 0.0025 max mem: 19788 +Test: [16500/21770] eta: 0:06:51 time: 0.0864 data: 0.0025 max mem: 19788 +Test: [16600/21770] eta: 0:06:43 time: 0.0642 data: 0.0019 max mem: 19788 +Test: [16700/21770] eta: 0:06:35 time: 0.0705 data: 0.0023 max mem: 19788 +Test: [16800/21770] eta: 0:06:27 time: 0.0826 data: 0.0024 max mem: 19788 +Test: [16900/21770] eta: 0:06:19 time: 0.0715 data: 0.0022 max mem: 19788 +Test: [17000/21770] eta: 0:06:11 time: 0.0787 data: 0.0025 max mem: 19788 +Test: [17100/21770] eta: 0:06:04 time: 0.0803 data: 0.0024 max mem: 19788 +Test: [17200/21770] eta: 0:05:56 time: 0.0894 data: 0.0025 max mem: 19788 +Test: [17300/21770] eta: 0:05:48 time: 0.0860 data: 0.0028 max mem: 19788 +Test: [17400/21770] eta: 0:05:40 time: 0.0687 data: 0.0020 max mem: 19788 +Test: [17500/21770] eta: 0:05:32 time: 0.0666 data: 0.0021 max mem: 19788 +Test: [17600/21770] eta: 0:05:24 time: 0.0675 data: 0.0021 max mem: 19788 +Test: [17700/21770] eta: 0:05:16 time: 0.0749 data: 0.0027 max mem: 19788 +Test: [17800/21770] eta: 0:05:08 time: 0.0677 data: 0.0021 max mem: 19788 +Test: [17900/21770] eta: 0:05:00 time: 0.0715 data: 0.0023 max mem: 19788 +Test: [18000/21770] eta: 0:04:53 time: 0.0702 data: 0.0021 max mem: 19788 +Test: [18100/21770] eta: 0:04:45 time: 0.0677 data: 0.0021 max mem: 19788 +Test: [18200/21770] eta: 0:04:37 time: 0.0664 data: 0.0021 max mem: 19788 +Test: [18300/21770] eta: 0:04:29 time: 0.0646 data: 0.0021 max mem: 19788 +Test: [18400/21770] eta: 0:04:21 time: 0.0875 data: 0.0021 max mem: 19788 +Test: [18500/21770] eta: 0:04:14 time: 0.0750 data: 0.0023 max mem: 19788 +Test: [18600/21770] eta: 0:04:06 time: 0.0657 data: 0.0020 max mem: 19788 +Test: [18700/21770] eta: 0:03:58 time: 0.0662 data: 0.0020 max mem: 19788 +Test: [18800/21770] eta: 0:03:50 time: 0.0637 data: 0.0021 max mem: 19788 +Test: [18900/21770] eta: 0:03:42 time: 0.0661 data: 0.0021 max mem: 19788 +Test: [19000/21770] eta: 0:03:34 time: 0.0725 data: 0.0022 max mem: 19788 +Test: [19100/21770] eta: 0:03:26 time: 0.0660 data: 0.0020 max mem: 19788 +Test: [19200/21770] eta: 0:03:18 time: 0.0641 data: 0.0020 max mem: 19788 +Test: [19300/21770] eta: 0:03:11 time: 0.0659 data: 0.0020 max mem: 19788 +Test: [19400/21770] eta: 0:03:03 time: 0.0878 data: 0.0025 max mem: 19788 +Test: [19500/21770] eta: 0:02:55 time: 0.0880 data: 0.0025 max mem: 19788 +Test: [19600/21770] eta: 0:02:48 time: 0.0896 data: 0.0026 max mem: 19788 +Test: [19700/21770] eta: 0:02:40 time: 0.0886 data: 0.0027 max mem: 19788 +Test: [19800/21770] eta: 0:02:32 time: 0.0874 data: 0.0027 max mem: 19788 +Test: [19900/21770] eta: 0:02:25 time: 0.0874 data: 0.0028 max mem: 19788 +Test: [20000/21770] eta: 0:02:17 time: 0.0895 data: 0.0020 max mem: 19788 +Test: [20100/21770] eta: 0:02:09 time: 0.0832 data: 0.0027 max mem: 19788 +Test: [20200/21770] eta: 0:02:01 time: 0.0657 data: 0.0021 max mem: 19788 +Test: [20300/21770] eta: 0:01:53 time: 0.0719 data: 0.0020 max mem: 19788 +Test: [20400/21770] eta: 0:01:46 time: 0.0884 data: 0.0022 max mem: 19788 +Test: [20500/21770] eta: 0:01:38 time: 0.0841 data: 0.0026 max mem: 19788 +Test: [20600/21770] eta: 0:01:30 time: 0.0721 data: 0.0022 max mem: 19788 +Test: [20700/21770] eta: 0:01:23 time: 0.0645 data: 0.0020 max mem: 19788 +Test: [20800/21770] eta: 0:01:15 time: 0.0659 data: 0.0021 max mem: 19788 +Test: [20900/21770] eta: 0:01:07 time: 0.0657 data: 0.0020 max mem: 19788 +Test: [21000/21770] eta: 0:00:59 time: 0.0653 data: 0.0020 max mem: 19788 +Test: [21100/21770] eta: 0:00:51 time: 0.0774 data: 0.0024 max mem: 19788 +Test: [21200/21770] eta: 0:00:44 time: 0.0895 data: 0.0028 max mem: 19788 +Test: [21300/21770] eta: 0:00:36 time: 0.0642 data: 0.0021 max mem: 19788 +Test: [21400/21770] eta: 0:00:28 time: 0.0658 data: 0.0023 max mem: 19788 +Test: [21500/21770] eta: 0:00:20 time: 0.0775 data: 0.0024 max mem: 19788 +Test: [21600/21770] eta: 0:00:13 time: 0.0920 data: 0.0038 max mem: 19788 +Test: [21700/21770] eta: 0:00:05 time: 0.0693 data: 0.0023 max mem: 19788 +Test: Total time: 0:28:06 +Final results: +Mean IoU is 60.42 + + precision@0.5 = 67.02 + precision@0.6 = 61.47 + precision@0.7 = 54.43 + precision@0.8 = 43.29 + precision@0.9 = 21.22 + overall IoU = 62.45 + mean IoU = 60.42 + +Mean accuracy for one-to-zero sample is 79.85 + +Average object IoU 0.6042023559815227 +Overall IoU 62.4466552734375 +Better epoch: 8 + +Epoch: [9] [ 0/2138] eta: 5:04:04 lr: 3.974986327585336e-05 loss: 0.0689 (0.0689) time: 8.5334 data: 1.6103 max mem: 19788 +Epoch: [9] [ 10/2138] eta: 2:33:04 lr: 3.974446545355418e-05 loss: 0.0417 (0.0436) time: 4.3160 data: 0.1493 max mem: 19788 +Epoch: [9] [ 20/2138] eta: 2:30:28 lr: 3.973906754979872e-05 loss: 0.0398 (0.0433) time: 4.0491 data: 0.0034 max mem: 19788 +Epoch: [9] [ 30/2138] eta: 2:25:54 lr: 3.9733669564573464e-05 loss: 0.0365 (0.0425) time: 4.0632 data: 0.0035 max mem: 19788 +Epoch: [9] [ 40/2138] eta: 2:27:28 lr: 3.9728271497864876e-05 loss: 0.0377 (0.0440) time: 4.1700 data: 0.0035 max mem: 19788 +Epoch: [9] [ 50/2138] eta: 2:24:24 lr: 3.972287334965944e-05 loss: 0.0445 (0.0457) time: 4.1451 data: 0.0038 max mem: 19788 +Epoch: [9] [ 60/2138] eta: 2:24:09 lr: 3.9717475119943605e-05 loss: 0.0371 (0.0448) time: 4.0489 data: 0.0039 max mem: 19788 +Epoch: [9] [ 70/2138] eta: 2:22:05 lr: 3.971207680870382e-05 loss: 0.0328 (0.0432) time: 4.0535 data: 0.0038 max mem: 19788 +Epoch: [9] [ 80/2138] eta: 2:21:36 lr: 3.970667841592656e-05 loss: 0.0412 (0.0447) time: 4.0262 data: 0.0039 max mem: 19788 +Epoch: [9] [ 90/2138] eta: 2:20:54 lr: 3.970127994159828e-05 loss: 0.0489 (0.0458) time: 4.1478 data: 0.0036 max mem: 19788 +Epoch: [9] [ 100/2138] eta: 2:19:38 lr: 3.969588138570541e-05 loss: 0.0439 (0.0456) time: 4.0412 data: 0.0036 max mem: 19788 +Epoch: [9] [ 110/2138] eta: 2:19:08 lr: 3.9690482748234394e-05 loss: 0.0444 (0.0460) time: 4.0630 data: 0.0037 max mem: 19788 +Epoch: [9] [ 120/2138] eta: 2:18:49 lr: 3.968508402917168e-05 loss: 0.0472 (0.0465) time: 4.2089 data: 0.0036 max mem: 19788 +Epoch: [9] [ 130/2138] eta: 2:18:31 lr: 3.967968522850369e-05 loss: 0.0408 (0.0469) time: 4.2651 data: 0.0035 max mem: 19788 +Epoch: [9] [ 140/2138] eta: 2:17:29 lr: 3.967428634621686e-05 loss: 0.0408 (0.0468) time: 4.1378 data: 0.0035 max mem: 19788 +Epoch: [9] [ 150/2138] eta: 2:16:10 lr: 3.9668887382297614e-05 loss: 0.0424 (0.0469) time: 3.9174 data: 0.0035 max mem: 19788 +Epoch: [9] [ 160/2138] eta: 2:14:55 lr: 3.9663488336732376e-05 loss: 0.0448 (0.0476) time: 3.8371 data: 0.0032 max mem: 19788 +Epoch: [9] [ 170/2138] eta: 2:14:03 lr: 3.965808920950755e-05 loss: 0.0467 (0.0476) time: 3.9152 data: 0.0033 max mem: 19788 +Epoch: [9] [ 180/2138] eta: 2:12:41 lr: 3.9652690000609566e-05 loss: 0.0489 (0.0482) time: 3.8521 data: 0.0034 max mem: 19788 +Epoch: [9] [ 190/2138] eta: 2:12:15 lr: 3.9647290710024814e-05 loss: 0.0484 (0.0483) time: 3.9594 data: 0.0033 max mem: 19788 +Epoch: [9] [ 200/2138] eta: 2:11:38 lr: 3.964189133773971e-05 loss: 0.0408 (0.0477) time: 4.1643 data: 0.0033 max mem: 19788 +Epoch: [9] [ 210/2138] eta: 2:11:05 lr: 3.9636491883740646e-05 loss: 0.0480 (0.0480) time: 4.1343 data: 0.0032 max mem: 19788 +Epoch: [9] [ 220/2138] eta: 2:10:02 lr: 3.963109234801402e-05 loss: 0.0486 (0.0480) time: 3.9870 data: 0.0031 max mem: 19788 +Epoch: [9] [ 230/2138] eta: 2:09:19 lr: 3.962569273054622e-05 loss: 0.0494 (0.0484) time: 3.9338 data: 0.0031 max mem: 19788 +Epoch: [9] [ 240/2138] eta: 2:08:14 lr: 3.962029303132364e-05 loss: 0.0483 (0.0484) time: 3.9033 data: 0.0032 max mem: 19788 +Epoch: [9] [ 250/2138] eta: 2:07:16 lr: 3.961489325033265e-05 loss: 0.0449 (0.0484) time: 3.7912 data: 0.0031 max mem: 19788 +Epoch: [9] [ 260/2138] eta: 2:06:07 lr: 3.9609493387559635e-05 loss: 0.0428 (0.0484) time: 3.7345 data: 0.0031 max mem: 19788 +Epoch: [9] [ 270/2138] eta: 2:05:07 lr: 3.9604093442990964e-05 loss: 0.0446 (0.0486) time: 3.6919 data: 0.0034 max mem: 19788 +Epoch: [9] [ 280/2138] eta: 2:04:08 lr: 3.959869341661301e-05 loss: 0.0456 (0.0486) time: 3.7391 data: 0.0034 max mem: 19788 +Epoch: [9] [ 290/2138] eta: 2:03:17 lr: 3.9593293308412136e-05 loss: 0.0456 (0.0486) time: 3.7918 data: 0.0033 max mem: 19788 +Epoch: [9] [ 300/2138] eta: 2:02:17 lr: 3.95878931183747e-05 loss: 0.0473 (0.0487) time: 3.7527 data: 0.0031 max mem: 19788 +Epoch: [9] [ 310/2138] eta: 2:01:35 lr: 3.958249284648706e-05 loss: 0.0466 (0.0488) time: 3.8100 data: 0.0031 max mem: 19788 +Epoch: [9] [ 320/2138] eta: 2:00:44 lr: 3.957709249273556e-05 loss: 0.0452 (0.0488) time: 3.8770 data: 0.0033 max mem: 19788 +Epoch: [9] [ 330/2138] eta: 1:59:51 lr: 3.9571692057106566e-05 loss: 0.0470 (0.0489) time: 3.7741 data: 0.0032 max mem: 19788 +Epoch: [9] [ 340/2138] eta: 1:58:54 lr: 3.95662915395864e-05 loss: 0.0467 (0.0488) time: 3.7006 data: 0.0030 max mem: 19788 +Epoch: [9] [ 350/2138] eta: 1:58:14 lr: 3.9560890940161396e-05 loss: 0.0438 (0.0488) time: 3.8012 data: 0.0030 max mem: 19788 +Epoch: [9] [ 360/2138] eta: 1:57:25 lr: 3.955549025881792e-05 loss: 0.0394 (0.0487) time: 3.8712 data: 0.0031 max mem: 19788 +Epoch: [9] [ 370/2138] eta: 1:56:32 lr: 3.9550089495542276e-05 loss: 0.0440 (0.0490) time: 3.7378 data: 0.0031 max mem: 19788 +Epoch: [9] [ 380/2138] eta: 1:55:46 lr: 3.9544688650320795e-05 loss: 0.0477 (0.0491) time: 3.7508 data: 0.0031 max mem: 19788 +Epoch: [9] [ 390/2138] eta: 1:55:17 lr: 3.953928772313979e-05 loss: 0.0458 (0.0491) time: 3.9918 data: 0.0031 max mem: 19788 +Epoch: [9] [ 400/2138] eta: 1:54:25 lr: 3.95338867139856e-05 loss: 0.0462 (0.0491) time: 3.9278 data: 0.0030 max mem: 19788 +Epoch: [9] [ 410/2138] eta: 1:53:32 lr: 3.9528485622844514e-05 loss: 0.0508 (0.0492) time: 3.6605 data: 0.0031 max mem: 19788 +Epoch: [9] [ 420/2138] eta: 1:52:40 lr: 3.952308444970285e-05 loss: 0.0507 (0.0493) time: 3.6254 data: 0.0032 max mem: 19788 +Epoch: [9] [ 430/2138] eta: 1:51:48 lr: 3.95176831945469e-05 loss: 0.0454 (0.0494) time: 3.6258 data: 0.0031 max mem: 19788 +Epoch: [9] [ 440/2138] eta: 1:50:58 lr: 3.951228185736299e-05 loss: 0.0461 (0.0494) time: 3.6282 data: 0.0028 max mem: 19788 +Epoch: [9] [ 450/2138] eta: 1:50:07 lr: 3.950688043813739e-05 loss: 0.0455 (0.0494) time: 3.6272 data: 0.0028 max mem: 19788 +Epoch: [9] [ 460/2138] eta: 1:49:19 lr: 3.9501478936856395e-05 loss: 0.0444 (0.0494) time: 3.6396 data: 0.0030 max mem: 19788 +Epoch: [9] [ 470/2138] eta: 1:48:30 lr: 3.94960773535063e-05 loss: 0.0490 (0.0493) time: 3.6474 data: 0.0032 max mem: 19788 +Epoch: [9] [ 480/2138] eta: 1:47:42 lr: 3.949067568807338e-05 loss: 0.0488 (0.0494) time: 3.6449 data: 0.0033 max mem: 19788 +Epoch: [9] [ 490/2138] eta: 1:46:54 lr: 3.948527394054391e-05 loss: 0.0424 (0.0492) time: 3.6394 data: 0.0032 max mem: 19788 +Epoch: [9] [ 500/2138] eta: 1:46:07 lr: 3.947987211090417e-05 loss: 0.0390 (0.0493) time: 3.6399 data: 0.0032 max mem: 19788 +Epoch: [9] [ 510/2138] eta: 1:45:20 lr: 3.947447019914042e-05 loss: 0.0470 (0.0493) time: 3.6398 data: 0.0031 max mem: 19788 +Epoch: [9] [ 520/2138] eta: 1:44:34 lr: 3.9469068205238926e-05 loss: 0.0451 (0.0493) time: 3.6378 data: 0.0030 max mem: 19788 +Epoch: [9] [ 530/2138] eta: 1:43:48 lr: 3.946366612918596e-05 loss: 0.0447 (0.0493) time: 3.6344 data: 0.0029 max mem: 19788 +Epoch: [9] [ 540/2138] eta: 1:43:02 lr: 3.945826397096776e-05 loss: 0.0411 (0.0492) time: 3.6374 data: 0.0030 max mem: 19788 +Epoch: [9] [ 550/2138] eta: 1:42:17 lr: 3.945286173057059e-05 loss: 0.0430 (0.0493) time: 3.6387 data: 0.0031 max mem: 19788 +Epoch: [9] [ 560/2138] eta: 1:41:31 lr: 3.944745940798068e-05 loss: 0.0437 (0.0493) time: 3.6240 data: 0.0030 max mem: 19788 +Epoch: [9] [ 570/2138] eta: 1:40:46 lr: 3.94420570031843e-05 loss: 0.0540 (0.0494) time: 3.6210 data: 0.0032 max mem: 19788 +Epoch: [9] [ 580/2138] eta: 1:40:02 lr: 3.943665451616765e-05 loss: 0.0557 (0.0496) time: 3.6314 data: 0.0032 max mem: 19788 +Epoch: [9] [ 590/2138] eta: 1:39:17 lr: 3.9431251946917e-05 loss: 0.0494 (0.0495) time: 3.6281 data: 0.0029 max mem: 19788 +Epoch: [9] [ 600/2138] eta: 1:38:33 lr: 3.9425849295418555e-05 loss: 0.0463 (0.0496) time: 3.6220 data: 0.0027 max mem: 19788 +Epoch: [9] [ 610/2138] eta: 1:37:49 lr: 3.942044656165855e-05 loss: 0.0406 (0.0495) time: 3.6265 data: 0.0028 max mem: 19788 +Epoch: [9] [ 620/2138] eta: 1:37:05 lr: 3.94150437456232e-05 loss: 0.0446 (0.0497) time: 3.6232 data: 0.0032 max mem: 19788 +Epoch: [9] [ 630/2138] eta: 1:36:21 lr: 3.9409640847298725e-05 loss: 0.0528 (0.0496) time: 3.6190 data: 0.0031 max mem: 19788 +Epoch: [9] [ 640/2138] eta: 1:35:39 lr: 3.940423786667133e-05 loss: 0.0501 (0.0496) time: 3.6271 data: 0.0028 max mem: 19788 +Epoch: [9] [ 650/2138] eta: 1:34:55 lr: 3.9398834803727235e-05 loss: 0.0409 (0.0495) time: 3.6278 data: 0.0028 max mem: 19788 +Epoch: [9] [ 660/2138] eta: 1:34:12 lr: 3.939343165845262e-05 loss: 0.0417 (0.0496) time: 3.6160 data: 0.0029 max mem: 19788 +Epoch: [9] [ 670/2138] eta: 1:33:29 lr: 3.938802843083371e-05 loss: 0.0483 (0.0496) time: 3.6121 data: 0.0031 max mem: 19788 +Epoch: [9] [ 680/2138] eta: 1:32:47 lr: 3.938262512085669e-05 loss: 0.0506 (0.0497) time: 3.6186 data: 0.0031 max mem: 19788 +Epoch: [9] [ 690/2138] eta: 1:32:04 lr: 3.937722172850773e-05 loss: 0.0482 (0.0497) time: 3.6200 data: 0.0032 max mem: 19788 +Epoch: [9] [ 700/2138] eta: 1:31:23 lr: 3.937181825377303e-05 loss: 0.0451 (0.0499) time: 3.6224 data: 0.0031 max mem: 19788 +Epoch: [9] [ 710/2138] eta: 1:30:41 lr: 3.936641469663878e-05 loss: 0.0463 (0.0499) time: 3.6342 data: 0.0030 max mem: 19788 +Epoch: [9] [ 720/2138] eta: 1:29:59 lr: 3.936101105709115e-05 loss: 0.0488 (0.0500) time: 3.6348 data: 0.0031 max mem: 19788 +Epoch: [9] [ 730/2138] eta: 1:29:18 lr: 3.935560733511629e-05 loss: 0.0456 (0.0500) time: 3.6295 data: 0.0033 max mem: 19788 +Epoch: [9] [ 740/2138] eta: 1:28:37 lr: 3.93502035307004e-05 loss: 0.0399 (0.0499) time: 3.6363 data: 0.0031 max mem: 19788 +Epoch: [9] [ 750/2138] eta: 1:27:55 lr: 3.9344799643829615e-05 loss: 0.0386 (0.0498) time: 3.6350 data: 0.0031 max mem: 19788 +Epoch: [9] [ 760/2138] eta: 1:27:14 lr: 3.933939567449012e-05 loss: 0.0449 (0.0498) time: 3.6310 data: 0.0031 max mem: 19788 +Epoch: [9] [ 770/2138] eta: 1:26:33 lr: 3.9333991622668036e-05 loss: 0.0453 (0.0498) time: 3.6357 data: 0.0029 max mem: 19788 +Epoch: [9] [ 780/2138] eta: 1:25:53 lr: 3.932858748834954e-05 loss: 0.0453 (0.0498) time: 3.6327 data: 0.0029 max mem: 19788 +Epoch: [9] [ 790/2138] eta: 1:25:12 lr: 3.9323183271520765e-05 loss: 0.0501 (0.0499) time: 3.6322 data: 0.0029 max mem: 19788 +Epoch: [9] [ 800/2138] eta: 1:24:31 lr: 3.931777897216786e-05 loss: 0.0488 (0.0498) time: 3.6331 data: 0.0030 max mem: 19788 +Epoch: [9] [ 810/2138] eta: 1:23:51 lr: 3.931237459027694e-05 loss: 0.0445 (0.0497) time: 3.6301 data: 0.0030 max mem: 19788 +Epoch: [9] [ 820/2138] eta: 1:23:11 lr: 3.9306970125834164e-05 loss: 0.0447 (0.0498) time: 3.6367 data: 0.0031 max mem: 19788 +Epoch: [9] [ 830/2138] eta: 1:22:30 lr: 3.9301565578825644e-05 loss: 0.0429 (0.0497) time: 3.6419 data: 0.0031 max mem: 19788 +Epoch: [9] [ 840/2138] eta: 1:21:50 lr: 3.9296160949237503e-05 loss: 0.0398 (0.0496) time: 3.6359 data: 0.0034 max mem: 19788 +Epoch: [9] [ 850/2138] eta: 1:21:10 lr: 3.929075623705586e-05 loss: 0.0403 (0.0497) time: 3.6493 data: 0.0033 max mem: 19788 +Epoch: [9] [ 860/2138] eta: 1:20:31 lr: 3.9285351442266836e-05 loss: 0.0497 (0.0496) time: 3.6545 data: 0.0028 max mem: 19788 +Epoch: [9] [ 870/2138] eta: 1:19:51 lr: 3.9279946564856534e-05 loss: 0.0476 (0.0497) time: 3.6339 data: 0.0029 max mem: 19788 +Epoch: [9] [ 880/2138] eta: 1:19:11 lr: 3.927454160481105e-05 loss: 0.0477 (0.0497) time: 3.6263 data: 0.0030 max mem: 19788 +Epoch: [9] [ 890/2138] eta: 1:18:31 lr: 3.92691365621165e-05 loss: 0.0509 (0.0497) time: 3.6241 data: 0.0029 max mem: 19788 +Epoch: [9] [ 900/2138] eta: 1:17:51 lr: 3.926373143675898e-05 loss: 0.0574 (0.0499) time: 3.6291 data: 0.0028 max mem: 19788 +Epoch: [9] [ 910/2138] eta: 1:17:11 lr: 3.9258326228724565e-05 loss: 0.0461 (0.0499) time: 3.6318 data: 0.0030 max mem: 19788 +Epoch: [9] [ 920/2138] eta: 1:16:32 lr: 3.925292093799935e-05 loss: 0.0425 (0.0499) time: 3.6227 data: 0.0030 max mem: 19788 +Epoch: [9] [ 930/2138] eta: 1:15:52 lr: 3.924751556456943e-05 loss: 0.0437 (0.0500) time: 3.6269 data: 0.0031 max mem: 19788 +Epoch: [9] [ 940/2138] eta: 1:15:13 lr: 3.924211010842086e-05 loss: 0.0546 (0.0500) time: 3.6257 data: 0.0031 max mem: 19788 +Epoch: [9] [ 950/2138] eta: 1:14:33 lr: 3.923670456953974e-05 loss: 0.0397 (0.0500) time: 3.6218 data: 0.0029 max mem: 19788 +Epoch: [9] [ 960/2138] eta: 1:13:54 lr: 3.923129894791212e-05 loss: 0.0399 (0.0499) time: 3.6270 data: 0.0031 max mem: 19788 +Epoch: [9] [ 970/2138] eta: 1:13:15 lr: 3.922589324352406e-05 loss: 0.0399 (0.0498) time: 3.6317 data: 0.0030 max mem: 19788 +Epoch: [9] [ 980/2138] eta: 1:12:35 lr: 3.922048745636164e-05 loss: 0.0374 (0.0497) time: 3.6326 data: 0.0030 max mem: 19788 +Epoch: [9] [ 990/2138] eta: 1:11:56 lr: 3.92150815864109e-05 loss: 0.0404 (0.0497) time: 3.6251 data: 0.0031 max mem: 19788 +Epoch: [9] [1000/2138] eta: 1:11:17 lr: 3.92096756336579e-05 loss: 0.0438 (0.0497) time: 3.6266 data: 0.0031 max mem: 19788 +Epoch: [9] [1010/2138] eta: 1:10:38 lr: 3.920426959808868e-05 loss: 0.0402 (0.0496) time: 3.6356 data: 0.0029 max mem: 19788 +Epoch: [9] [1020/2138] eta: 1:09:59 lr: 3.919886347968929e-05 loss: 0.0390 (0.0495) time: 3.6440 data: 0.0028 max mem: 19788 +Epoch: [9] [1030/2138] eta: 1:09:20 lr: 3.919345727844576e-05 loss: 0.0416 (0.0495) time: 3.6378 data: 0.0030 max mem: 19788 +Epoch: [9] [1040/2138] eta: 1:08:41 lr: 3.918805099434412e-05 loss: 0.0471 (0.0495) time: 3.6236 data: 0.0029 max mem: 19788 +Epoch: [9] [1050/2138] eta: 1:08:02 lr: 3.9182644627370416e-05 loss: 0.0453 (0.0495) time: 3.6210 data: 0.0028 max mem: 19788 +Epoch: [9] [1060/2138] eta: 1:07:24 lr: 3.9177238177510654e-05 loss: 0.0419 (0.0495) time: 3.6596 data: 0.0028 max mem: 19788 +Epoch: [9] [1070/2138] eta: 1:06:46 lr: 3.917183164475087e-05 loss: 0.0437 (0.0495) time: 3.6643 data: 0.0029 max mem: 19788 +Epoch: [9] [1080/2138] eta: 1:06:07 lr: 3.9166425029077055e-05 loss: 0.0453 (0.0495) time: 3.6244 data: 0.0031 max mem: 19788 +Epoch: [9] [1090/2138] eta: 1:05:28 lr: 3.9161018330475253e-05 loss: 0.0453 (0.0495) time: 3.6261 data: 0.0030 max mem: 19788 +Epoch: [9] [1100/2138] eta: 1:04:50 lr: 3.9155611548931436e-05 loss: 0.0463 (0.0496) time: 3.6326 data: 0.0031 max mem: 19788 +Epoch: [9] [1110/2138] eta: 1:04:11 lr: 3.915020468443163e-05 loss: 0.0447 (0.0495) time: 3.6296 data: 0.0032 max mem: 19788 +Epoch: [9] [1120/2138] eta: 1:03:33 lr: 3.914479773696182e-05 loss: 0.0422 (0.0496) time: 3.6327 data: 0.0030 max mem: 19788 +Epoch: [9] [1130/2138] eta: 1:02:54 lr: 3.9139390706508005e-05 loss: 0.0436 (0.0495) time: 3.6329 data: 0.0029 max mem: 19788 +Epoch: [9] [1140/2138] eta: 1:02:16 lr: 3.9133983593056164e-05 loss: 0.0465 (0.0495) time: 3.6364 data: 0.0028 max mem: 19788 +Epoch: [9] [1150/2138] eta: 1:01:37 lr: 3.9128576396592296e-05 loss: 0.0465 (0.0496) time: 3.6358 data: 0.0028 max mem: 19788 +Epoch: [9] [1160/2138] eta: 1:00:59 lr: 3.912316911710237e-05 loss: 0.0466 (0.0497) time: 3.6224 data: 0.0027 max mem: 19788 +Epoch: [9] [1170/2138] eta: 1:00:20 lr: 3.911776175457236e-05 loss: 0.0446 (0.0497) time: 3.6183 data: 0.0027 max mem: 19788 +Epoch: [9] [1180/2138] eta: 0:59:42 lr: 3.9112354308988243e-05 loss: 0.0446 (0.0497) time: 3.6179 data: 0.0027 max mem: 19788 +Epoch: [9] [1190/2138] eta: 0:59:04 lr: 3.910694678033597e-05 loss: 0.0424 (0.0497) time: 3.6212 data: 0.0027 max mem: 19788 +Epoch: [9] [1200/2138] eta: 0:58:25 lr: 3.910153916860151e-05 loss: 0.0450 (0.0498) time: 3.6194 data: 0.0027 max mem: 19788 +Epoch: [9] [1210/2138] eta: 0:57:47 lr: 3.909613147377083e-05 loss: 0.0491 (0.0498) time: 3.6182 data: 0.0028 max mem: 19788 +Epoch: [9] [1220/2138] eta: 0:57:09 lr: 3.909072369582987e-05 loss: 0.0502 (0.0500) time: 3.6175 data: 0.0030 max mem: 19788 +Epoch: [9] [1230/2138] eta: 0:56:30 lr: 3.908531583476458e-05 loss: 0.0477 (0.0500) time: 3.6099 data: 0.0029 max mem: 19788 +Epoch: [9] [1240/2138] eta: 0:55:52 lr: 3.9079907890560904e-05 loss: 0.0442 (0.0500) time: 3.6050 data: 0.0028 max mem: 19788 +Epoch: [9] [1250/2138] eta: 0:55:14 lr: 3.9074499863204775e-05 loss: 0.0434 (0.0500) time: 3.6091 data: 0.0027 max mem: 19788 +Epoch: [9] [1260/2138] eta: 0:54:36 lr: 3.9069091752682134e-05 loss: 0.0454 (0.0500) time: 3.6135 data: 0.0028 max mem: 19788 +Epoch: [9] [1270/2138] eta: 0:53:58 lr: 3.9063683558978906e-05 loss: 0.0471 (0.0500) time: 3.6096 data: 0.0029 max mem: 19788 +Epoch: [9] [1280/2138] eta: 0:53:20 lr: 3.9058275282081016e-05 loss: 0.0429 (0.0500) time: 3.6095 data: 0.0029 max mem: 19788 +Epoch: [9] [1290/2138] eta: 0:52:42 lr: 3.905286692197439e-05 loss: 0.0505 (0.0501) time: 3.6113 data: 0.0030 max mem: 19788 +Epoch: [9] [1300/2138] eta: 0:52:03 lr: 3.9047458478644936e-05 loss: 0.0515 (0.0501) time: 3.6113 data: 0.0028 max mem: 19788 +Epoch: [9] [1310/2138] eta: 0:51:25 lr: 3.904204995207857e-05 loss: 0.0436 (0.0500) time: 3.6095 data: 0.0028 max mem: 19788 +Epoch: [9] [1320/2138] eta: 0:50:47 lr: 3.903664134226119e-05 loss: 0.0489 (0.0501) time: 3.6063 data: 0.0030 max mem: 19788 +Epoch: [9] [1330/2138] eta: 0:50:09 lr: 3.903123264917871e-05 loss: 0.0444 (0.0501) time: 3.6069 data: 0.0029 max mem: 19788 +Epoch: [9] [1340/2138] eta: 0:49:31 lr: 3.902582387281703e-05 loss: 0.0444 (0.0503) time: 3.6079 data: 0.0029 max mem: 19788 +Epoch: [9] [1350/2138] eta: 0:48:54 lr: 3.9020415013162016e-05 loss: 0.0515 (0.0503) time: 3.6092 data: 0.0028 max mem: 19788 +Epoch: [9] [1360/2138] eta: 0:48:16 lr: 3.9015006070199585e-05 loss: 0.0515 (0.0503) time: 3.6121 data: 0.0027 max mem: 19788 +Epoch: [9] [1370/2138] eta: 0:47:38 lr: 3.900959704391561e-05 loss: 0.0492 (0.0503) time: 3.6192 data: 0.0030 max mem: 19788 +Epoch: [9] [1380/2138] eta: 0:47:00 lr: 3.900418793429597e-05 loss: 0.0466 (0.0503) time: 3.6156 data: 0.0032 max mem: 19788 +Epoch: [9] [1390/2138] eta: 0:46:22 lr: 3.899877874132654e-05 loss: 0.0466 (0.0503) time: 3.6065 data: 0.0028 max mem: 19788 +Epoch: [9] [1400/2138] eta: 0:45:44 lr: 3.899336946499319e-05 loss: 0.0461 (0.0502) time: 3.6048 data: 0.0026 max mem: 19788 +Epoch: [9] [1410/2138] eta: 0:45:07 lr: 3.898796010528178e-05 loss: 0.0446 (0.0502) time: 3.6113 data: 0.0027 max mem: 19788 +Epoch: [9] [1420/2138] eta: 0:44:29 lr: 3.898255066217818e-05 loss: 0.0446 (0.0502) time: 3.6113 data: 0.0026 max mem: 19788 +Epoch: [9] [1430/2138] eta: 0:43:51 lr: 3.8977141135668246e-05 loss: 0.0425 (0.0502) time: 3.6083 data: 0.0026 max mem: 19788 +Epoch: [9] [1440/2138] eta: 0:43:14 lr: 3.897173152573783e-05 loss: 0.0433 (0.0501) time: 3.6149 data: 0.0027 max mem: 19788 +Epoch: [9] [1450/2138] eta: 0:42:36 lr: 3.896632183237276e-05 loss: 0.0458 (0.0502) time: 3.6161 data: 0.0029 max mem: 19788 +Epoch: [9] [1460/2138] eta: 0:41:58 lr: 3.8960912055558905e-05 loss: 0.0488 (0.0503) time: 3.6132 data: 0.0029 max mem: 19788 +Epoch: [9] [1470/2138] eta: 0:41:21 lr: 3.895550219528209e-05 loss: 0.0539 (0.0503) time: 3.6090 data: 0.0027 max mem: 19788 +Epoch: [9] [1480/2138] eta: 0:40:43 lr: 3.895009225152815e-05 loss: 0.0467 (0.0503) time: 3.6075 data: 0.0030 max mem: 19788 +Epoch: [9] [1490/2138] eta: 0:40:06 lr: 3.894468222428292e-05 loss: 0.0485 (0.0503) time: 3.6134 data: 0.0031 max mem: 19788 +Epoch: [9] [1500/2138] eta: 0:39:28 lr: 3.893927211353221e-05 loss: 0.0481 (0.0503) time: 3.6187 data: 0.0030 max mem: 19788 +Epoch: [9] [1510/2138] eta: 0:38:51 lr: 3.893386191926184e-05 loss: 0.0432 (0.0503) time: 3.6242 data: 0.0029 max mem: 19788 +Epoch: [9] [1520/2138] eta: 0:38:13 lr: 3.892845164145765e-05 loss: 0.0426 (0.0503) time: 3.6201 data: 0.0028 max mem: 19788 +Epoch: [9] [1530/2138] eta: 0:37:36 lr: 3.8923041280105426e-05 loss: 0.0450 (0.0503) time: 3.6161 data: 0.0029 max mem: 19788 +Epoch: [9] [1540/2138] eta: 0:36:58 lr: 3.8917630835190976e-05 loss: 0.0481 (0.0503) time: 3.6174 data: 0.0028 max mem: 19788 +Epoch: [9] [1550/2138] eta: 0:36:21 lr: 3.8912220306700105e-05 loss: 0.0464 (0.0503) time: 3.6179 data: 0.0028 max mem: 19788 +Epoch: [9] [1560/2138] eta: 0:35:43 lr: 3.890680969461862e-05 loss: 0.0432 (0.0503) time: 3.6266 data: 0.0028 max mem: 19788 +Epoch: [9] [1570/2138] eta: 0:35:06 lr: 3.8901398998932295e-05 loss: 0.0479 (0.0503) time: 3.6238 data: 0.0030 max mem: 19788 +Epoch: [9] [1580/2138] eta: 0:34:28 lr: 3.8895988219626924e-05 loss: 0.0487 (0.0503) time: 3.6219 data: 0.0032 max mem: 19788 +Epoch: [9] [1590/2138] eta: 0:33:51 lr: 3.889057735668829e-05 loss: 0.0472 (0.0503) time: 3.6242 data: 0.0033 max mem: 19788 +Epoch: [9] [1600/2138] eta: 0:33:14 lr: 3.888516641010218e-05 loss: 0.0476 (0.0503) time: 3.6195 data: 0.0032 max mem: 19788 +Epoch: [9] [1610/2138] eta: 0:32:36 lr: 3.887975537985436e-05 loss: 0.0426 (0.0503) time: 3.6180 data: 0.0031 max mem: 19788 +Epoch: [9] [1620/2138] eta: 0:31:59 lr: 3.887434426593059e-05 loss: 0.0428 (0.0503) time: 3.6210 data: 0.0031 max mem: 19788 +Epoch: [9] [1630/2138] eta: 0:31:22 lr: 3.886893306831664e-05 loss: 0.0440 (0.0503) time: 3.6197 data: 0.0033 max mem: 19788 +Epoch: [9] [1640/2138] eta: 0:30:44 lr: 3.886352178699828e-05 loss: 0.0405 (0.0502) time: 3.6265 data: 0.0033 max mem: 19788 +Epoch: [9] [1650/2138] eta: 0:30:07 lr: 3.885811042196126e-05 loss: 0.0348 (0.0501) time: 3.6254 data: 0.0032 max mem: 19788 +Epoch: [9] [1660/2138] eta: 0:29:30 lr: 3.8852698973191325e-05 loss: 0.0360 (0.0501) time: 3.6152 data: 0.0031 max mem: 19788 +Epoch: [9] [1670/2138] eta: 0:28:53 lr: 3.884728744067423e-05 loss: 0.0374 (0.0500) time: 3.6165 data: 0.0030 max mem: 19788 +Epoch: [9] [1680/2138] eta: 0:28:15 lr: 3.88418758243957e-05 loss: 0.0424 (0.0501) time: 3.6180 data: 0.0031 max mem: 19788 +Epoch: [9] [1690/2138] eta: 0:27:38 lr: 3.8836464124341484e-05 loss: 0.0476 (0.0501) time: 3.6164 data: 0.0033 max mem: 19788 +Epoch: [9] [1700/2138] eta: 0:27:01 lr: 3.88310523404973e-05 loss: 0.0426 (0.0500) time: 3.6193 data: 0.0030 max mem: 19788 +Epoch: [9] [1710/2138] eta: 0:26:24 lr: 3.8825640472848905e-05 loss: 0.0421 (0.0500) time: 3.6254 data: 0.0029 max mem: 19788 +Epoch: [9] [1720/2138] eta: 0:25:46 lr: 3.882022852138199e-05 loss: 0.0421 (0.0500) time: 3.6187 data: 0.0032 max mem: 19788 +Epoch: [9] [1730/2138] eta: 0:25:09 lr: 3.881481648608229e-05 loss: 0.0441 (0.0500) time: 3.6269 data: 0.0031 max mem: 19788 +Epoch: [9] [1740/2138] eta: 0:24:32 lr: 3.880940436693551e-05 loss: 0.0417 (0.0500) time: 3.6328 data: 0.0029 max mem: 19788 +Epoch: [9] [1750/2138] eta: 0:23:55 lr: 3.8803992163927365e-05 loss: 0.0429 (0.0500) time: 3.6308 data: 0.0028 max mem: 19788 +Epoch: [9] [1760/2138] eta: 0:23:18 lr: 3.8798579877043556e-05 loss: 0.0504 (0.0500) time: 3.6353 data: 0.0027 max mem: 19788 +Epoch: [9] [1770/2138] eta: 0:22:41 lr: 3.8793167506269786e-05 loss: 0.0411 (0.0500) time: 3.6261 data: 0.0028 max mem: 19788 +Epoch: [9] [1780/2138] eta: 0:22:03 lr: 3.878775505159173e-05 loss: 0.0386 (0.0500) time: 3.6172 data: 0.0027 max mem: 19788 +Epoch: [9] [1790/2138] eta: 0:21:26 lr: 3.8782342512995114e-05 loss: 0.0399 (0.0499) time: 3.6195 data: 0.0028 max mem: 19788 +Epoch: [9] [1800/2138] eta: 0:20:49 lr: 3.8776929890465596e-05 loss: 0.0439 (0.0500) time: 3.6247 data: 0.0030 max mem: 19788 +Epoch: [9] [1810/2138] eta: 0:20:12 lr: 3.877151718398886e-05 loss: 0.0446 (0.0499) time: 3.6216 data: 0.0029 max mem: 19788 +Epoch: [9] [1820/2138] eta: 0:19:35 lr: 3.876610439355058e-05 loss: 0.0419 (0.0499) time: 3.6247 data: 0.0029 max mem: 19788 +Epoch: [9] [1830/2138] eta: 0:18:58 lr: 3.876069151913645e-05 loss: 0.0421 (0.0499) time: 3.6335 data: 0.0031 max mem: 19788 +Epoch: [9] [1840/2138] eta: 0:18:21 lr: 3.875527856073211e-05 loss: 0.0452 (0.0500) time: 3.6382 data: 0.0032 max mem: 19788 +Epoch: [9] [1850/2138] eta: 0:17:44 lr: 3.874986551832323e-05 loss: 0.0510 (0.0500) time: 3.6363 data: 0.0029 max mem: 19788 +Epoch: [9] [1860/2138] eta: 0:17:07 lr: 3.874445239189547e-05 loss: 0.0498 (0.0500) time: 3.6233 data: 0.0030 max mem: 19788 +Epoch: [9] [1870/2138] eta: 0:16:30 lr: 3.873903918143449e-05 loss: 0.0536 (0.0501) time: 3.6211 data: 0.0034 max mem: 19788 +Epoch: [9] [1880/2138] eta: 0:15:53 lr: 3.873362588692592e-05 loss: 0.0524 (0.0501) time: 3.6259 data: 0.0033 max mem: 19788 +Epoch: [9] [1890/2138] eta: 0:15:16 lr: 3.8728212508355415e-05 loss: 0.0448 (0.0500) time: 3.6271 data: 0.0032 max mem: 19788 +Epoch: [9] [1900/2138] eta: 0:14:39 lr: 3.8722799045708614e-05 loss: 0.0414 (0.0500) time: 3.6274 data: 0.0030 max mem: 19788 +Epoch: [9] [1910/2138] eta: 0:14:02 lr: 3.8717385498971146e-05 loss: 0.0414 (0.0500) time: 3.6192 data: 0.0031 max mem: 19788 +Epoch: [9] [1920/2138] eta: 0:13:25 lr: 3.871197186812865e-05 loss: 0.0452 (0.0500) time: 3.6157 data: 0.0032 max mem: 19788 +Epoch: [9] [1930/2138] eta: 0:12:48 lr: 3.870655815316673e-05 loss: 0.0464 (0.0500) time: 3.6161 data: 0.0031 max mem: 19788 +Epoch: [9] [1940/2138] eta: 0:12:11 lr: 3.870114435407103e-05 loss: 0.0419 (0.0499) time: 3.6214 data: 0.0031 max mem: 19788 +Epoch: [9] [1950/2138] eta: 0:11:34 lr: 3.8695730470827145e-05 loss: 0.0441 (0.0499) time: 3.6217 data: 0.0032 max mem: 19788 +Epoch: [9] [1960/2138] eta: 0:10:57 lr: 3.8690316503420705e-05 loss: 0.0426 (0.0499) time: 3.6189 data: 0.0033 max mem: 19788 +Epoch: [9] [1970/2138] eta: 0:10:20 lr: 3.8684902451837296e-05 loss: 0.0426 (0.0499) time: 3.6170 data: 0.0033 max mem: 19788 +Epoch: [9] [1980/2138] eta: 0:09:43 lr: 3.867948831606253e-05 loss: 0.0399 (0.0499) time: 3.6157 data: 0.0030 max mem: 19788 +Epoch: [9] [1990/2138] eta: 0:09:06 lr: 3.867407409608201e-05 loss: 0.0438 (0.0499) time: 3.6192 data: 0.0031 max mem: 19788 +Epoch: [9] [2000/2138] eta: 0:08:29 lr: 3.866865979188131e-05 loss: 0.0438 (0.0498) time: 3.6163 data: 0.0030 max mem: 19788 +Epoch: [9] [2010/2138] eta: 0:07:52 lr: 3.866324540344603e-05 loss: 0.0434 (0.0499) time: 3.6188 data: 0.0029 max mem: 19788 +Epoch: [9] [2020/2138] eta: 0:07:15 lr: 3.865783093076175e-05 loss: 0.0457 (0.0499) time: 3.6185 data: 0.0028 max mem: 19788 +Epoch: [9] [2030/2138] eta: 0:06:38 lr: 3.8652416373814044e-05 loss: 0.0446 (0.0499) time: 3.6253 data: 0.0027 max mem: 19788 +Epoch: [9] [2040/2138] eta: 0:06:01 lr: 3.864700173258848e-05 loss: 0.0414 (0.0499) time: 3.6249 data: 0.0029 max mem: 19788 +Epoch: [9] [2050/2138] eta: 0:05:24 lr: 3.864158700707064e-05 loss: 0.0467 (0.0499) time: 3.6156 data: 0.0029 max mem: 19788 +Epoch: [9] [2060/2138] eta: 0:04:47 lr: 3.863617219724609e-05 loss: 0.0467 (0.0499) time: 3.6231 data: 0.0028 max mem: 19788 +Epoch: [9] [2070/2138] eta: 0:04:10 lr: 3.8630757303100364e-05 loss: 0.0416 (0.0499) time: 3.6256 data: 0.0030 max mem: 19788 +Epoch: [9] [2080/2138] eta: 0:03:33 lr: 3.8625342324619034e-05 loss: 0.0416 (0.0499) time: 3.6195 data: 0.0033 max mem: 19788 +Epoch: [9] [2090/2138] eta: 0:02:56 lr: 3.861992726178764e-05 loss: 0.0411 (0.0498) time: 3.6183 data: 0.0032 max mem: 19788 +Epoch: [9] [2100/2138] eta: 0:02:20 lr: 3.861451211459175e-05 loss: 0.0435 (0.0498) time: 3.6233 data: 0.0029 max mem: 19788 +Epoch: [9] [2110/2138] eta: 0:01:43 lr: 3.860909688301688e-05 loss: 0.0530 (0.0500) time: 3.6256 data: 0.0030 max mem: 19788 +Epoch: [9] [2120/2138] eta: 0:01:06 lr: 3.8603681567048564e-05 loss: 0.0570 (0.0500) time: 3.6291 data: 0.0033 max mem: 19788 +Epoch: [9] [2130/2138] eta: 0:00:29 lr: 3.859826616667233e-05 loss: 0.0570 (0.0500) time: 3.6087 data: 0.0030 max mem: 19788 +Epoch: [9] Total time: 2:11:20 +Test: [ 0/21770] eta: 17:10:33 time: 2.8403 data: 2.7341 max mem: 19788 +Test: [ 100/21770] eta: 0:32:00 time: 0.0616 data: 0.0020 max mem: 19788 +Test: [ 200/21770] eta: 0:28:07 time: 0.0596 data: 0.0018 max mem: 19788 +Test: [ 300/21770] eta: 0:26:45 time: 0.0605 data: 0.0017 max mem: 19788 +Test: [ 400/21770] eta: 0:25:57 time: 0.0741 data: 0.0021 max mem: 19788 +Test: [ 500/21770] eta: 0:25:06 time: 0.0607 data: 0.0018 max mem: 19788 +Test: [ 600/21770] eta: 0:24:56 time: 0.0820 data: 0.0022 max mem: 19788 +Test: [ 700/21770] eta: 0:24:42 time: 0.0718 data: 0.0022 max mem: 19788 +Test: [ 800/21770] eta: 0:24:23 time: 0.0722 data: 0.0025 max mem: 19788 +Test: [ 900/21770] eta: 0:24:04 time: 0.0662 data: 0.0019 max mem: 19788 +Test: [ 1000/21770] eta: 0:23:55 time: 0.0810 data: 0.0024 max mem: 19788 +Test: [ 1100/21770] eta: 0:23:34 time: 0.0616 data: 0.0018 max mem: 19788 +Test: [ 1200/21770] eta: 0:23:22 time: 0.0651 data: 0.0019 max mem: 19788 +Test: [ 1300/21770] eta: 0:23:23 time: 0.0723 data: 0.0021 max mem: 19788 +Test: [ 1400/21770] eta: 0:23:11 time: 0.0679 data: 0.0020 max mem: 19788 +Test: [ 1500/21770] eta: 0:23:03 time: 0.0716 data: 0.0021 max mem: 19788 +Test: [ 1600/21770] eta: 0:22:54 time: 0.0620 data: 0.0018 max mem: 19788 +Test: [ 1700/21770] eta: 0:22:45 time: 0.0624 data: 0.0020 max mem: 19788 +Test: [ 1800/21770] eta: 0:22:37 time: 0.0779 data: 0.0023 max mem: 19788 +Test: [ 1900/21770] eta: 0:22:30 time: 0.0674 data: 0.0019 max mem: 19788 +Test: [ 2000/21770] eta: 0:22:27 time: 0.0752 data: 0.0020 max mem: 19788 +Test: [ 2100/21770] eta: 0:22:21 time: 0.0773 data: 0.0024 max mem: 19788 +Test: [ 2200/21770] eta: 0:22:21 time: 0.0742 data: 0.0021 max mem: 19788 +Test: [ 2300/21770] eta: 0:22:15 time: 0.0809 data: 0.0023 max mem: 19788 +Test: [ 2400/21770] eta: 0:22:11 time: 0.0631 data: 0.0018 max mem: 19788 +Test: [ 2500/21770] eta: 0:22:02 time: 0.0629 data: 0.0019 max mem: 19788 +Test: [ 2600/21770] eta: 0:21:53 time: 0.0809 data: 0.0024 max mem: 19788 +Test: [ 2700/21770] eta: 0:21:48 time: 0.0625 data: 0.0019 max mem: 19788 +Test: [ 2800/21770] eta: 0:21:46 time: 0.0634 data: 0.0019 max mem: 19788 +Test: [ 2900/21770] eta: 0:21:40 time: 0.0692 data: 0.0021 max mem: 19788 +Test: [ 3000/21770] eta: 0:21:30 time: 0.0627 data: 0.0018 max mem: 19788 +Test: [ 3100/21770] eta: 0:21:24 time: 0.0830 data: 0.0019 max mem: 19788 +Test: [ 3200/21770] eta: 0:21:15 time: 0.0658 data: 0.0019 max mem: 19788 +Test: [ 3300/21770] eta: 0:21:06 time: 0.0622 data: 0.0020 max mem: 19788 +Test: [ 3400/21770] eta: 0:20:59 time: 0.0635 data: 0.0020 max mem: 19788 +Test: [ 3500/21770] eta: 0:20:52 time: 0.0709 data: 0.0022 max mem: 19788 +Test: [ 3600/21770] eta: 0:20:44 time: 0.0738 data: 0.0020 max mem: 19788 +Test: [ 3700/21770] eta: 0:20:36 time: 0.0660 data: 0.0018 max mem: 19788 +Test: [ 3800/21770] eta: 0:20:29 time: 0.0625 data: 0.0018 max mem: 19788 +Test: [ 3900/21770] eta: 0:20:23 time: 0.0817 data: 0.0023 max mem: 19788 +Test: [ 4000/21770] eta: 0:20:15 time: 0.0696 data: 0.0022 max mem: 19788 +Test: [ 4100/21770] eta: 0:20:08 time: 0.0646 data: 0.0021 max mem: 19788 +Test: [ 4200/21770] eta: 0:20:01 time: 0.0619 data: 0.0018 max mem: 19788 +Test: [ 4300/21770] eta: 0:19:53 time: 0.0637 data: 0.0020 max mem: 19788 +Test: [ 4400/21770] eta: 0:19:44 time: 0.0616 data: 0.0018 max mem: 19788 +Test: [ 4500/21770] eta: 0:19:39 time: 0.0795 data: 0.0023 max mem: 19788 +Test: [ 4600/21770] eta: 0:19:31 time: 0.0622 data: 0.0017 max mem: 19788 +Test: [ 4700/21770] eta: 0:19:25 time: 0.0658 data: 0.0018 max mem: 19788 +Test: [ 4800/21770] eta: 0:19:20 time: 0.0808 data: 0.0025 max mem: 19788 +Test: [ 4900/21770] eta: 0:19:16 time: 0.0691 data: 0.0018 max mem: 19788 +Test: [ 5000/21770] eta: 0:19:07 time: 0.0630 data: 0.0018 max mem: 19788 +Test: [ 5100/21770] eta: 0:18:59 time: 0.0588 data: 0.0017 max mem: 19788 +Test: [ 5200/21770] eta: 0:18:52 time: 0.0702 data: 0.0021 max mem: 19788 +Test: [ 5300/21770] eta: 0:18:45 time: 0.0672 data: 0.0020 max mem: 19788 +Test: [ 5400/21770] eta: 0:18:37 time: 0.0605 data: 0.0018 max mem: 19788 +Test: [ 5500/21770] eta: 0:18:29 time: 0.0656 data: 0.0020 max mem: 19788 +Test: [ 5600/21770] eta: 0:18:23 time: 0.0662 data: 0.0019 max mem: 19788 +Test: [ 5700/21770] eta: 0:18:17 time: 0.0695 data: 0.0020 max mem: 19788 +Test: [ 5800/21770] eta: 0:18:11 time: 0.0641 data: 0.0020 max mem: 19788 +Test: [ 5900/21770] eta: 0:18:04 time: 0.0719 data: 0.0021 max mem: 19788 +Test: [ 6000/21770] eta: 0:17:56 time: 0.0670 data: 0.0021 max mem: 19788 +Test: [ 6100/21770] eta: 0:17:50 time: 0.0702 data: 0.0020 max mem: 19788 +Test: [ 6200/21770] eta: 0:17:43 time: 0.0626 data: 0.0020 max mem: 19788 +Test: [ 6300/21770] eta: 0:17:38 time: 0.0790 data: 0.0019 max mem: 19788 +Test: [ 6400/21770] eta: 0:17:30 time: 0.0627 data: 0.0017 max mem: 19788 +Test: [ 6500/21770] eta: 0:17:24 time: 0.0674 data: 0.0018 max mem: 19788 +Test: [ 6600/21770] eta: 0:17:19 time: 0.0820 data: 0.0025 max mem: 19788 +Test: [ 6700/21770] eta: 0:17:12 time: 0.0682 data: 0.0018 max mem: 19788 +Test: [ 6800/21770] eta: 0:17:06 time: 0.0758 data: 0.0022 max mem: 19788 +Test: [ 6900/21770] eta: 0:16:59 time: 0.0757 data: 0.0021 max mem: 19788 +Test: [ 7000/21770] eta: 0:16:52 time: 0.0732 data: 0.0023 max mem: 19788 +Test: [ 7100/21770] eta: 0:16:45 time: 0.0758 data: 0.0019 max mem: 19788 +Test: [ 7200/21770] eta: 0:16:39 time: 0.0699 data: 0.0018 max mem: 19788 +Test: [ 7300/21770] eta: 0:16:33 time: 0.0782 data: 0.0022 max mem: 19788 +Test: [ 7400/21770] eta: 0:16:26 time: 0.0646 data: 0.0020 max mem: 19788 +Test: [ 7500/21770] eta: 0:16:19 time: 0.0647 data: 0.0020 max mem: 19788 +Test: [ 7600/21770] eta: 0:16:12 time: 0.0682 data: 0.0022 max mem: 19788 +Test: [ 7700/21770] eta: 0:16:05 time: 0.0766 data: 0.0020 max mem: 19788 +Test: [ 7800/21770] eta: 0:15:57 time: 0.0619 data: 0.0017 max mem: 19788 +Test: [ 7900/21770] eta: 0:15:50 time: 0.0653 data: 0.0019 max mem: 19788 +Test: [ 8000/21770] eta: 0:15:44 time: 0.0758 data: 0.0023 max mem: 19788 +Test: [ 8100/21770] eta: 0:15:37 time: 0.0611 data: 0.0018 max mem: 19788 +Test: [ 8200/21770] eta: 0:15:29 time: 0.0700 data: 0.0021 max mem: 19788 +Test: [ 8300/21770] eta: 0:15:22 time: 0.0613 data: 0.0018 max mem: 19788 +Test: [ 8400/21770] eta: 0:15:14 time: 0.0603 data: 0.0025 max mem: 19788 +Test: [ 8500/21770] eta: 0:15:06 time: 0.0627 data: 0.0019 max mem: 19788 +Test: [ 8600/21770] eta: 0:15:00 time: 0.0816 data: 0.0023 max mem: 19788 +Test: [ 8700/21770] eta: 0:14:53 time: 0.0634 data: 0.0020 max mem: 19788 +Test: [ 8800/21770] eta: 0:14:45 time: 0.0669 data: 0.0021 max mem: 19788 +Test: [ 8900/21770] eta: 0:14:39 time: 0.0676 data: 0.0021 max mem: 19788 +Test: [ 9000/21770] eta: 0:14:32 time: 0.0615 data: 0.0019 max mem: 19788 +Test: [ 9100/21770] eta: 0:14:24 time: 0.0626 data: 0.0019 max mem: 19788 +Test: [ 9200/21770] eta: 0:14:18 time: 0.0679 data: 0.0020 max mem: 19788 +Test: [ 9300/21770] eta: 0:14:12 time: 0.0827 data: 0.0019 max mem: 19788 +Test: [ 9400/21770] eta: 0:14:05 time: 0.0823 data: 0.0023 max mem: 19788 +Test: [ 9500/21770] eta: 0:13:58 time: 0.0621 data: 0.0018 max mem: 19788 +Test: [ 9600/21770] eta: 0:13:50 time: 0.0644 data: 0.0019 max mem: 19788 +Test: [ 9700/21770] eta: 0:13:43 time: 0.0714 data: 0.0021 max mem: 19788 +Test: [ 9800/21770] eta: 0:13:37 time: 0.0749 data: 0.0023 max mem: 19788 +Test: [ 9900/21770] eta: 0:13:31 time: 0.0804 data: 0.0023 max mem: 19788 +Test: [10000/21770] eta: 0:13:23 time: 0.0600 data: 0.0017 max mem: 19788 +Test: [10100/21770] eta: 0:13:17 time: 0.0796 data: 0.0023 max mem: 19788 +Test: [10200/21770] eta: 0:13:11 time: 0.0690 data: 0.0019 max mem: 19788 +Test: [10300/21770] eta: 0:13:04 time: 0.0694 data: 0.0020 max mem: 19788 +Test: [10400/21770] eta: 0:12:57 time: 0.0615 data: 0.0018 max mem: 19788 +Test: [10500/21770] eta: 0:12:50 time: 0.0616 data: 0.0019 max mem: 19788 +Test: [10600/21770] eta: 0:12:44 time: 0.0685 data: 0.0019 max mem: 19788 +Test: [10700/21770] eta: 0:12:37 time: 0.0778 data: 0.0022 max mem: 19788 +Test: [10800/21770] eta: 0:12:31 time: 0.0694 data: 0.0021 max mem: 19788 +Test: [10900/21770] eta: 0:12:24 time: 0.0677 data: 0.0018 max mem: 19788 +Test: [11000/21770] eta: 0:12:17 time: 0.0646 data: 0.0019 max mem: 19788 +Test: [11100/21770] eta: 0:12:10 time: 0.0634 data: 0.0018 max mem: 19788 +Test: [11200/21770] eta: 0:12:04 time: 0.0774 data: 0.0024 max mem: 19788 +Test: [11300/21770] eta: 0:11:57 time: 0.0777 data: 0.0024 max mem: 19788 +Test: [11400/21770] eta: 0:11:51 time: 0.0744 data: 0.0025 max mem: 19788 +Test: [11500/21770] eta: 0:11:44 time: 0.0734 data: 0.0022 max mem: 19788 +Test: [11600/21770] eta: 0:11:38 time: 0.0776 data: 0.0017 max mem: 19788 +Test: [11700/21770] eta: 0:11:31 time: 0.0655 data: 0.0017 max mem: 19788 +Test: [11800/21770] eta: 0:11:24 time: 0.0622 data: 0.0016 max mem: 19788 +Test: [11900/21770] eta: 0:11:17 time: 0.0697 data: 0.0020 max mem: 19788 +Test: [12000/21770] eta: 0:11:11 time: 0.0803 data: 0.0025 max mem: 19788 +Test: [12100/21770] eta: 0:11:04 time: 0.0700 data: 0.0020 max mem: 19788 +Test: [12200/21770] eta: 0:10:57 time: 0.0618 data: 0.0017 max mem: 19788 +Test: [12300/21770] eta: 0:10:50 time: 0.0622 data: 0.0018 max mem: 19788 +Test: [12400/21770] eta: 0:10:43 time: 0.0665 data: 0.0020 max mem: 19788 +Test: [12500/21770] eta: 0:10:36 time: 0.0780 data: 0.0023 max mem: 19788 +Test: [12600/21770] eta: 0:10:30 time: 0.0766 data: 0.0021 max mem: 19788 +Test: [12700/21770] eta: 0:10:23 time: 0.0809 data: 0.0024 max mem: 19788 +Test: [12800/21770] eta: 0:10:16 time: 0.0662 data: 0.0018 max mem: 19788 +Test: [12900/21770] eta: 0:10:09 time: 0.0795 data: 0.0023 max mem: 19788 +Test: [13000/21770] eta: 0:10:03 time: 0.0737 data: 0.0018 max mem: 19788 +Test: [13100/21770] eta: 0:09:56 time: 0.0692 data: 0.0019 max mem: 19788 +Test: [13200/21770] eta: 0:09:49 time: 0.0808 data: 0.0025 max mem: 19788 +Test: [13300/21770] eta: 0:09:42 time: 0.0632 data: 0.0018 max mem: 19788 +Test: [13400/21770] eta: 0:09:35 time: 0.0647 data: 0.0019 max mem: 19788 +Test: [13500/21770] eta: 0:09:28 time: 0.0631 data: 0.0017 max mem: 19788 +Test: [13600/21770] eta: 0:09:21 time: 0.0651 data: 0.0022 max mem: 19788 +Test: [13700/21770] eta: 0:09:14 time: 0.0629 data: 0.0017 max mem: 19788 +Test: [13800/21770] eta: 0:09:07 time: 0.0617 data: 0.0017 max mem: 19788 +Test: [13900/21770] eta: 0:09:00 time: 0.0789 data: 0.0024 max mem: 19788 +Test: [14000/21770] eta: 0:08:54 time: 0.0710 data: 0.0020 max mem: 19788 +Test: [14100/21770] eta: 0:08:47 time: 0.0642 data: 0.0018 max mem: 19788 +Test: [14200/21770] eta: 0:08:40 time: 0.0816 data: 0.0025 max mem: 19788 +Test: [14300/21770] eta: 0:08:33 time: 0.0669 data: 0.0019 max mem: 19788 +Test: [14400/21770] eta: 0:08:26 time: 0.0622 data: 0.0020 max mem: 19788 +Test: [14500/21770] eta: 0:08:19 time: 0.0680 data: 0.0021 max mem: 19788 +Test: [14600/21770] eta: 0:08:13 time: 0.0629 data: 0.0018 max mem: 19788 +Test: [14700/21770] eta: 0:08:06 time: 0.0828 data: 0.0025 max mem: 19788 +Test: [14800/21770] eta: 0:07:59 time: 0.0638 data: 0.0017 max mem: 19788 +Test: [14900/21770] eta: 0:07:52 time: 0.0616 data: 0.0019 max mem: 19788 +Test: [15000/21770] eta: 0:07:46 time: 0.0637 data: 0.0018 max mem: 19788 +Test: [15100/21770] eta: 0:07:38 time: 0.0609 data: 0.0017 max mem: 19788 +Test: [15200/21770] eta: 0:07:32 time: 0.0803 data: 0.0026 max mem: 19788 +Test: [15300/21770] eta: 0:07:25 time: 0.0630 data: 0.0019 max mem: 19788 +Test: [15400/21770] eta: 0:07:18 time: 0.0634 data: 0.0018 max mem: 19788 +Test: [15500/21770] eta: 0:07:11 time: 0.0750 data: 0.0023 max mem: 19788 +Test: [15600/21770] eta: 0:07:04 time: 0.0639 data: 0.0017 max mem: 19788 +Test: [15700/21770] eta: 0:06:57 time: 0.0645 data: 0.0017 max mem: 19788 +Test: [15800/21770] eta: 0:06:50 time: 0.0643 data: 0.0018 max mem: 19788 +Test: [15900/21770] eta: 0:06:44 time: 0.0804 data: 0.0024 max mem: 19788 +Test: [16000/21770] eta: 0:06:37 time: 0.0643 data: 0.0020 max mem: 19788 +Test: [16100/21770] eta: 0:06:30 time: 0.0667 data: 0.0019 max mem: 19788 +Test: [16200/21770] eta: 0:06:23 time: 0.0813 data: 0.0023 max mem: 19788 +Test: [16300/21770] eta: 0:06:16 time: 0.0628 data: 0.0019 max mem: 19788 +Test: [16400/21770] eta: 0:06:09 time: 0.0625 data: 0.0018 max mem: 19788 +Test: [16500/21770] eta: 0:06:02 time: 0.0618 data: 0.0018 max mem: 19788 +Test: [16600/21770] eta: 0:05:55 time: 0.0759 data: 0.0021 max mem: 19788 +Test: [16700/21770] eta: 0:05:48 time: 0.0723 data: 0.0020 max mem: 19788 +Test: [16800/21770] eta: 0:05:41 time: 0.0651 data: 0.0019 max mem: 19788 +Test: [16900/21770] eta: 0:05:34 time: 0.0730 data: 0.0020 max mem: 19788 +Test: [17000/21770] eta: 0:05:27 time: 0.0702 data: 0.0021 max mem: 19788 +Test: [17100/21770] eta: 0:05:21 time: 0.0772 data: 0.0023 max mem: 19788 +Test: [17200/21770] eta: 0:05:14 time: 0.0628 data: 0.0019 max mem: 19788 +Test: [17300/21770] eta: 0:05:07 time: 0.0632 data: 0.0017 max mem: 19788 +Test: [17400/21770] eta: 0:05:00 time: 0.0628 data: 0.0018 max mem: 19788 +Test: [17500/21770] eta: 0:04:53 time: 0.0641 data: 0.0017 max mem: 19788 +Test: [17600/21770] eta: 0:04:46 time: 0.0624 data: 0.0019 max mem: 19788 +Test: [17700/21770] eta: 0:04:39 time: 0.0664 data: 0.0018 max mem: 19788 +Test: [17800/21770] eta: 0:04:32 time: 0.0632 data: 0.0017 max mem: 19788 +Test: [17900/21770] eta: 0:04:25 time: 0.0614 data: 0.0018 max mem: 19788 +Test: [18000/21770] eta: 0:04:18 time: 0.0796 data: 0.0023 max mem: 19788 +Test: [18100/21770] eta: 0:04:11 time: 0.0633 data: 0.0019 max mem: 19788 +Test: [18200/21770] eta: 0:04:04 time: 0.0798 data: 0.0023 max mem: 19788 +Test: [18300/21770] eta: 0:03:57 time: 0.0708 data: 0.0021 max mem: 19788 +Test: [18400/21770] eta: 0:03:51 time: 0.0739 data: 0.0023 max mem: 19788 +Test: [18500/21770] eta: 0:03:44 time: 0.0631 data: 0.0018 max mem: 19788 +Test: [18600/21770] eta: 0:03:37 time: 0.0670 data: 0.0020 max mem: 19788 +Test: [18700/21770] eta: 0:03:30 time: 0.0618 data: 0.0017 max mem: 19788 +Test: [18800/21770] eta: 0:03:23 time: 0.0632 data: 0.0020 max mem: 19788 +Test: [18900/21770] eta: 0:03:16 time: 0.0717 data: 0.0020 max mem: 19788 +Test: [19000/21770] eta: 0:03:09 time: 0.0724 data: 0.0022 max mem: 19788 +Test: [19100/21770] eta: 0:03:02 time: 0.0693 data: 0.0022 max mem: 19788 +Test: [19200/21770] eta: 0:02:56 time: 0.0627 data: 0.0020 max mem: 19788 +Test: [19300/21770] eta: 0:02:49 time: 0.0635 data: 0.0018 max mem: 19788 +Test: [19400/21770] eta: 0:02:42 time: 0.0617 data: 0.0018 max mem: 19788 +Test: [19500/21770] eta: 0:02:35 time: 0.0812 data: 0.0024 max mem: 19788 +Test: [19600/21770] eta: 0:02:28 time: 0.0805 data: 0.0021 max mem: 19788 +Test: [19700/21770] eta: 0:02:21 time: 0.0743 data: 0.0022 max mem: 19788 +Test: [19800/21770] eta: 0:02:14 time: 0.0626 data: 0.0017 max mem: 19788 +Test: [19900/21770] eta: 0:02:08 time: 0.0673 data: 0.0018 max mem: 19788 +Test: [20000/21770] eta: 0:02:01 time: 0.0784 data: 0.0022 max mem: 19788 +Test: [20100/21770] eta: 0:01:54 time: 0.0721 data: 0.0022 max mem: 19788 +Test: [20200/21770] eta: 0:01:47 time: 0.0743 data: 0.0022 max mem: 19788 +Test: [20300/21770] eta: 0:01:40 time: 0.0615 data: 0.0019 max mem: 19788 +Test: [20400/21770] eta: 0:01:33 time: 0.0627 data: 0.0017 max mem: 19788 +Test: [20500/21770] eta: 0:01:27 time: 0.0695 data: 0.0020 max mem: 19788 +Test: [20600/21770] eta: 0:01:20 time: 0.0707 data: 0.0020 max mem: 19788 +Test: [20700/21770] eta: 0:01:13 time: 0.0645 data: 0.0017 max mem: 19788 +Test: [20800/21770] eta: 0:01:06 time: 0.0663 data: 0.0019 max mem: 19788 +Test: [20900/21770] eta: 0:00:59 time: 0.0618 data: 0.0019 max mem: 19788 +Test: [21000/21770] eta: 0:00:52 time: 0.0757 data: 0.0024 max mem: 19788 +Test: [21100/21770] eta: 0:00:45 time: 0.0674 data: 0.0020 max mem: 19788 +Test: [21200/21770] eta: 0:00:39 time: 0.0693 data: 0.0021 max mem: 19788 +Test: [21300/21770] eta: 0:00:32 time: 0.0812 data: 0.0023 max mem: 19788 +Test: [21400/21770] eta: 0:00:25 time: 0.0651 data: 0.0017 max mem: 19788 +Test: [21500/21770] eta: 0:00:18 time: 0.0791 data: 0.0024 max mem: 19788 +Test: [21600/21770] eta: 0:00:11 time: 0.0931 data: 0.0055 max mem: 19788 +Test: [21700/21770] eta: 0:00:04 time: 0.0609 data: 0.0016 max mem: 19788 +Test: Total time: 0:24:53 +Final results: +Mean IoU is 60.67 + + precision@0.5 = 67.14 + precision@0.6 = 61.70 + precision@0.7 = 54.71 + precision@0.8 = 44.00 + precision@0.9 = 21.23 + overall IoU = 62.32 + mean IoU = 60.67 + +Mean accuracy for one-to-zero sample is 81.95 + +Average object IoU 0.6067209538703281 +Overall IoU 62.31675338745117 +Epoch: [10] [ 0/2138] eta: 3:10:18 lr: 3.859393378558794e-05 loss: 0.0482 (0.0482) time: 5.3406 data: 1.3791 max mem: 19788 +Epoch: [10] [ 10/2138] eta: 2:14:51 lr: 3.8588518233241e-05 loss: 0.0400 (0.0389) time: 3.8024 data: 0.1276 max mem: 19788 +Epoch: [10] [ 20/2138] eta: 2:11:13 lr: 3.8583102596445614e-05 loss: 0.0391 (0.0394) time: 3.6365 data: 0.0025 max mem: 19788 +Epoch: [10] [ 30/2138] eta: 2:09:32 lr: 3.857768687518729e-05 loss: 0.0395 (0.0406) time: 3.6236 data: 0.0026 max mem: 19788 +Epoch: [10] [ 40/2138] eta: 2:08:32 lr: 3.857227106945154e-05 loss: 0.0438 (0.0433) time: 3.6325 data: 0.0027 max mem: 19788 +Epoch: [10] [ 50/2138] eta: 2:07:32 lr: 3.856685517922386e-05 loss: 0.0429 (0.0444) time: 3.6313 data: 0.0028 max mem: 19788 +Epoch: [10] [ 60/2138] eta: 2:06:44 lr: 3.856143920448975e-05 loss: 0.0371 (0.0434) time: 3.6261 data: 0.0028 max mem: 19788 +Epoch: [10] [ 70/2138] eta: 2:05:56 lr: 3.855602314523471e-05 loss: 0.0342 (0.0422) time: 3.6249 data: 0.0030 max mem: 19788 +Epoch: [10] [ 80/2138] eta: 2:05:10 lr: 3.855060700144422e-05 loss: 0.0394 (0.0441) time: 3.6178 data: 0.0032 max mem: 19788 +Epoch: [10] [ 90/2138] eta: 2:04:27 lr: 3.854519077310377e-05 loss: 0.0477 (0.0439) time: 3.6202 data: 0.0031 max mem: 19788 +Epoch: [10] [ 100/2138] eta: 2:03:45 lr: 3.853977446019884e-05 loss: 0.0403 (0.0436) time: 3.6204 data: 0.0030 max mem: 19788 +Epoch: [10] [ 110/2138] eta: 2:03:05 lr: 3.8534358062714895e-05 loss: 0.0403 (0.0438) time: 3.6213 data: 0.0030 max mem: 19788 +Epoch: [10] [ 120/2138] eta: 2:02:27 lr: 3.85289415806374e-05 loss: 0.0417 (0.0438) time: 3.6267 data: 0.0029 max mem: 19788 +Epoch: [10] [ 130/2138] eta: 2:01:47 lr: 3.852352501395183e-05 loss: 0.0383 (0.0436) time: 3.6226 data: 0.0030 max mem: 19788 +Epoch: [10] [ 140/2138] eta: 2:01:09 lr: 3.851810836264366e-05 loss: 0.0369 (0.0433) time: 3.6228 data: 0.0030 max mem: 19788 +Epoch: [10] [ 150/2138] eta: 2:00:30 lr: 3.851269162669832e-05 loss: 0.0395 (0.0433) time: 3.6239 data: 0.0030 max mem: 19788 +Epoch: [10] [ 160/2138] eta: 1:59:52 lr: 3.8507274806101265e-05 loss: 0.0417 (0.0442) time: 3.6239 data: 0.0031 max mem: 19788 +Epoch: [10] [ 170/2138] eta: 1:59:15 lr: 3.850185790083795e-05 loss: 0.0484 (0.0445) time: 3.6300 data: 0.0031 max mem: 19788 +Epoch: [10] [ 180/2138] eta: 1:58:37 lr: 3.849644091089381e-05 loss: 0.0494 (0.0451) time: 3.6243 data: 0.0031 max mem: 19788 +Epoch: [10] [ 190/2138] eta: 1:57:59 lr: 3.8491023836254295e-05 loss: 0.0467 (0.0458) time: 3.6198 data: 0.0029 max mem: 19788 +Epoch: [10] [ 200/2138] eta: 1:57:22 lr: 3.848560667690481e-05 loss: 0.0385 (0.0452) time: 3.6238 data: 0.0028 max mem: 19788 +Epoch: [10] [ 210/2138] eta: 1:56:44 lr: 3.848018943283079e-05 loss: 0.0371 (0.0456) time: 3.6192 data: 0.0028 max mem: 19788 +Epoch: [10] [ 220/2138] eta: 1:56:06 lr: 3.847477210401767e-05 loss: 0.0412 (0.0453) time: 3.6125 data: 0.0029 max mem: 19788 +Epoch: [10] [ 230/2138] eta: 1:55:29 lr: 3.846935469045086e-05 loss: 0.0404 (0.0455) time: 3.6189 data: 0.0031 max mem: 19788 +Epoch: [10] [ 240/2138] eta: 1:54:52 lr: 3.8463937192115764e-05 loss: 0.0468 (0.0462) time: 3.6217 data: 0.0031 max mem: 19788 +Epoch: [10] [ 250/2138] eta: 1:54:15 lr: 3.845851960899779e-05 loss: 0.0456 (0.0461) time: 3.6199 data: 0.0030 max mem: 19788 +Epoch: [10] [ 260/2138] eta: 1:53:37 lr: 3.8453101941082365e-05 loss: 0.0403 (0.0458) time: 3.6198 data: 0.0029 max mem: 19788 +Epoch: [10] [ 270/2138] eta: 1:53:00 lr: 3.844768418835486e-05 loss: 0.0424 (0.0468) time: 3.6199 data: 0.0029 max mem: 19788 +Epoch: [10] [ 280/2138] eta: 1:52:23 lr: 3.844226635080067e-05 loss: 0.0418 (0.0466) time: 3.6188 data: 0.0030 max mem: 19788 +Epoch: [10] [ 290/2138] eta: 1:51:46 lr: 3.843684842840519e-05 loss: 0.0384 (0.0466) time: 3.6143 data: 0.0029 max mem: 19788 +Epoch: [10] [ 300/2138] eta: 1:51:09 lr: 3.843143042115381e-05 loss: 0.0388 (0.0464) time: 3.6154 data: 0.0028 max mem: 19788 +Epoch: [10] [ 310/2138] eta: 1:50:33 lr: 3.8426012329031894e-05 loss: 0.0406 (0.0463) time: 3.6245 data: 0.0027 max mem: 19788 +Epoch: [10] [ 320/2138] eta: 1:49:55 lr: 3.842059415202482e-05 loss: 0.0428 (0.0463) time: 3.6219 data: 0.0028 max mem: 19788 +Epoch: [10] [ 330/2138] eta: 1:49:18 lr: 3.841517589011797e-05 loss: 0.0428 (0.0464) time: 3.6116 data: 0.0031 max mem: 19788 +Epoch: [10] [ 340/2138] eta: 1:48:42 lr: 3.840975754329669e-05 loss: 0.0395 (0.0462) time: 3.6198 data: 0.0030 max mem: 19788 +Epoch: [10] [ 350/2138] eta: 1:48:05 lr: 3.840433911154635e-05 loss: 0.0403 (0.0461) time: 3.6234 data: 0.0029 max mem: 19788 +Epoch: [10] [ 360/2138] eta: 1:47:29 lr: 3.83989205948523e-05 loss: 0.0422 (0.0461) time: 3.6192 data: 0.0030 max mem: 19788 +Epoch: [10] [ 370/2138] eta: 1:46:53 lr: 3.8393501993199894e-05 loss: 0.0461 (0.0463) time: 3.6256 data: 0.0029 max mem: 19788 +Epoch: [10] [ 380/2138] eta: 1:46:16 lr: 3.8388083306574474e-05 loss: 0.0457 (0.0464) time: 3.6245 data: 0.0030 max mem: 19788 +Epoch: [10] [ 390/2138] eta: 1:45:39 lr: 3.8382664534961374e-05 loss: 0.0435 (0.0464) time: 3.6163 data: 0.0031 max mem: 19788 +Epoch: [10] [ 400/2138] eta: 1:45:03 lr: 3.837724567834593e-05 loss: 0.0419 (0.0463) time: 3.6223 data: 0.0030 max mem: 19788 +Epoch: [10] [ 410/2138] eta: 1:44:26 lr: 3.837182673671349e-05 loss: 0.0434 (0.0463) time: 3.6230 data: 0.0028 max mem: 19788 +Epoch: [10] [ 420/2138] eta: 1:43:50 lr: 3.8366407710049354e-05 loss: 0.0464 (0.0463) time: 3.6234 data: 0.0027 max mem: 19788 +Epoch: [10] [ 430/2138] eta: 1:43:14 lr: 3.836098859833886e-05 loss: 0.0439 (0.0463) time: 3.6340 data: 0.0027 max mem: 19788 +Epoch: [10] [ 440/2138] eta: 1:42:38 lr: 3.835556940156731e-05 loss: 0.0459 (0.0465) time: 3.6288 data: 0.0028 max mem: 19788 +Epoch: [10] [ 450/2138] eta: 1:42:01 lr: 3.8350150119720044e-05 loss: 0.0450 (0.0464) time: 3.6238 data: 0.0028 max mem: 19788 +Epoch: [10] [ 460/2138] eta: 1:41:25 lr: 3.834473075278234e-05 loss: 0.0483 (0.0465) time: 3.6220 data: 0.0029 max mem: 19788 +Epoch: [10] [ 470/2138] eta: 1:40:48 lr: 3.833931130073949e-05 loss: 0.0483 (0.0465) time: 3.6171 data: 0.0029 max mem: 19788 +Epoch: [10] [ 480/2138] eta: 1:40:12 lr: 3.833389176357682e-05 loss: 0.0428 (0.0465) time: 3.6233 data: 0.0027 max mem: 19788 +Epoch: [10] [ 490/2138] eta: 1:39:36 lr: 3.8328472141279614e-05 loss: 0.0373 (0.0463) time: 3.6354 data: 0.0027 max mem: 19788 +Epoch: [10] [ 500/2138] eta: 1:39:00 lr: 3.832305243383315e-05 loss: 0.0362 (0.0462) time: 3.6271 data: 0.0028 max mem: 19788 +Epoch: [10] [ 510/2138] eta: 1:38:23 lr: 3.831763264122271e-05 loss: 0.0401 (0.0463) time: 3.6104 data: 0.0028 max mem: 19788 +Epoch: [10] [ 520/2138] eta: 1:37:46 lr: 3.8312212763433575e-05 loss: 0.0478 (0.0463) time: 3.6093 data: 0.0029 max mem: 19788 +Epoch: [10] [ 530/2138] eta: 1:37:10 lr: 3.8306792800451016e-05 loss: 0.0369 (0.0462) time: 3.6199 data: 0.0030 max mem: 19788 +Epoch: [10] [ 540/2138] eta: 1:36:34 lr: 3.830137275226031e-05 loss: 0.0369 (0.0461) time: 3.6263 data: 0.0029 max mem: 19788 +Epoch: [10] [ 550/2138] eta: 1:35:57 lr: 3.8295952618846706e-05 loss: 0.0373 (0.0460) time: 3.6217 data: 0.0029 max mem: 19788 +Epoch: [10] [ 560/2138] eta: 1:35:21 lr: 3.829053240019546e-05 loss: 0.0373 (0.0461) time: 3.6223 data: 0.0028 max mem: 19788 +Epoch: [10] [ 570/2138] eta: 1:34:44 lr: 3.8285112096291834e-05 loss: 0.0459 (0.0462) time: 3.6237 data: 0.0028 max mem: 19788 +Epoch: [10] [ 580/2138] eta: 1:34:08 lr: 3.827969170712107e-05 loss: 0.0485 (0.0462) time: 3.6202 data: 0.0027 max mem: 19788 +Epoch: [10] [ 590/2138] eta: 1:33:31 lr: 3.827427123266841e-05 loss: 0.0447 (0.0463) time: 3.6151 data: 0.0028 max mem: 19788 +Epoch: [10] [ 600/2138] eta: 1:32:55 lr: 3.8268850672919096e-05 loss: 0.0428 (0.0463) time: 3.6210 data: 0.0031 max mem: 19788 +Epoch: [10] [ 610/2138] eta: 1:32:19 lr: 3.8263430027858364e-05 loss: 0.0428 (0.0463) time: 3.6246 data: 0.0032 max mem: 19788 +Epoch: [10] [ 620/2138] eta: 1:31:43 lr: 3.825800929747144e-05 loss: 0.0477 (0.0465) time: 3.6235 data: 0.0034 max mem: 19788 +Epoch: [10] [ 630/2138] eta: 1:31:06 lr: 3.8252588481743545e-05 loss: 0.0461 (0.0465) time: 3.6214 data: 0.0032 max mem: 19788 +Epoch: [10] [ 640/2138] eta: 1:30:30 lr: 3.8247167580659895e-05 loss: 0.0435 (0.0464) time: 3.6178 data: 0.0030 max mem: 19788 +Epoch: [10] [ 650/2138] eta: 1:29:54 lr: 3.824174659420571e-05 loss: 0.0435 (0.0464) time: 3.6248 data: 0.0029 max mem: 19788 +Epoch: [10] [ 660/2138] eta: 1:29:17 lr: 3.82363255223662e-05 loss: 0.0415 (0.0463) time: 3.6255 data: 0.0028 max mem: 19788 +Epoch: [10] [ 670/2138] eta: 1:28:41 lr: 3.823090436512656e-05 loss: 0.0405 (0.0463) time: 3.6190 data: 0.0028 max mem: 19788 +Epoch: [10] [ 680/2138] eta: 1:28:05 lr: 3.822548312247199e-05 loss: 0.0410 (0.0463) time: 3.6221 data: 0.0028 max mem: 19788 +Epoch: [10] [ 690/2138] eta: 1:27:28 lr: 3.82200617943877e-05 loss: 0.0425 (0.0462) time: 3.6268 data: 0.0029 max mem: 19788 +Epoch: [10] [ 700/2138] eta: 1:26:52 lr: 3.8214640380858845e-05 loss: 0.0425 (0.0463) time: 3.6220 data: 0.0028 max mem: 19788 +Epoch: [10] [ 710/2138] eta: 1:26:16 lr: 3.820921888187064e-05 loss: 0.0424 (0.0463) time: 3.6183 data: 0.0029 max mem: 19788 +Epoch: [10] [ 720/2138] eta: 1:25:39 lr: 3.8203797297408264e-05 loss: 0.0474 (0.0465) time: 3.6150 data: 0.0029 max mem: 19788 +Epoch: [10] [ 730/2138] eta: 1:25:03 lr: 3.8198375627456876e-05 loss: 0.0467 (0.0466) time: 3.6165 data: 0.0028 max mem: 19788 +Epoch: [10] [ 740/2138] eta: 1:24:27 lr: 3.819295387200165e-05 loss: 0.0422 (0.0465) time: 3.6258 data: 0.0028 max mem: 19788 +Epoch: [10] [ 750/2138] eta: 1:23:51 lr: 3.818753203102776e-05 loss: 0.0368 (0.0465) time: 3.6318 data: 0.0028 max mem: 19788 +Epoch: [10] [ 760/2138] eta: 1:23:15 lr: 3.818211010452035e-05 loss: 0.0439 (0.0466) time: 3.6319 data: 0.0028 max mem: 19788 +Epoch: [10] [ 770/2138] eta: 1:22:38 lr: 3.8176688092464594e-05 loss: 0.0441 (0.0466) time: 3.6299 data: 0.0029 max mem: 19788 +Epoch: [10] [ 780/2138] eta: 1:22:02 lr: 3.817126599484562e-05 loss: 0.0407 (0.0466) time: 3.6267 data: 0.0028 max mem: 19788 +Epoch: [10] [ 790/2138] eta: 1:21:26 lr: 3.816584381164859e-05 loss: 0.0474 (0.0467) time: 3.6224 data: 0.0027 max mem: 19788 +Epoch: [10] [ 800/2138] eta: 1:20:50 lr: 3.816042154285864e-05 loss: 0.0447 (0.0466) time: 3.6232 data: 0.0028 max mem: 19788 +Epoch: [10] [ 810/2138] eta: 1:20:13 lr: 3.81549991884609e-05 loss: 0.0415 (0.0466) time: 3.6261 data: 0.0027 max mem: 19788 +Epoch: [10] [ 820/2138] eta: 1:19:37 lr: 3.814957674844049e-05 loss: 0.0450 (0.0466) time: 3.6307 data: 0.0027 max mem: 19788 +Epoch: [10] [ 830/2138] eta: 1:19:01 lr: 3.814415422278257e-05 loss: 0.0456 (0.0466) time: 3.6331 data: 0.0028 max mem: 19788 +Epoch: [10] [ 840/2138] eta: 1:18:25 lr: 3.813873161147223e-05 loss: 0.0352 (0.0465) time: 3.6248 data: 0.0029 max mem: 19788 +Epoch: [10] [ 850/2138] eta: 1:17:48 lr: 3.81333089144946e-05 loss: 0.0366 (0.0465) time: 3.6157 data: 0.0030 max mem: 19788 +Epoch: [10] [ 860/2138] eta: 1:17:12 lr: 3.8127886131834776e-05 loss: 0.0435 (0.0466) time: 3.6257 data: 0.0028 max mem: 19788 +Epoch: [10] [ 870/2138] eta: 1:16:36 lr: 3.8122463263477864e-05 loss: 0.0435 (0.0465) time: 3.6284 data: 0.0027 max mem: 19788 +Epoch: [10] [ 880/2138] eta: 1:16:00 lr: 3.811704030940898e-05 loss: 0.0452 (0.0466) time: 3.6201 data: 0.0028 max mem: 19788 +Epoch: [10] [ 890/2138] eta: 1:15:23 lr: 3.8111617269613226e-05 loss: 0.0405 (0.0465) time: 3.6148 data: 0.0030 max mem: 19788 +Epoch: [10] [ 900/2138] eta: 1:14:47 lr: 3.8106194144075664e-05 loss: 0.0464 (0.0467) time: 3.6142 data: 0.0030 max mem: 19788 +Epoch: [10] [ 910/2138] eta: 1:14:11 lr: 3.810077093278139e-05 loss: 0.0497 (0.0467) time: 3.6226 data: 0.0030 max mem: 19788 +Epoch: [10] [ 920/2138] eta: 1:13:34 lr: 3.80953476357155e-05 loss: 0.0384 (0.0466) time: 3.6255 data: 0.0031 max mem: 19788 +Epoch: [10] [ 930/2138] eta: 1:12:58 lr: 3.808992425286306e-05 loss: 0.0434 (0.0466) time: 3.6277 data: 0.0033 max mem: 19788 +Epoch: [10] [ 940/2138] eta: 1:12:22 lr: 3.8084500784209135e-05 loss: 0.0468 (0.0467) time: 3.6237 data: 0.0033 max mem: 19788 +Epoch: [10] [ 950/2138] eta: 1:11:45 lr: 3.807907722973879e-05 loss: 0.0470 (0.0467) time: 3.6160 data: 0.0030 max mem: 19788 +Epoch: [10] [ 960/2138] eta: 1:11:09 lr: 3.8073653589437095e-05 loss: 0.0440 (0.0467) time: 3.6186 data: 0.0027 max mem: 19788 +Epoch: [10] [ 970/2138] eta: 1:10:33 lr: 3.806822986328911e-05 loss: 0.0425 (0.0465) time: 3.6238 data: 0.0027 max mem: 19788 +Epoch: [10] [ 980/2138] eta: 1:09:57 lr: 3.806280605127987e-05 loss: 0.0393 (0.0465) time: 3.6196 data: 0.0028 max mem: 19788 +Epoch: [10] [ 990/2138] eta: 1:09:20 lr: 3.805738215339443e-05 loss: 0.0395 (0.0465) time: 3.6204 data: 0.0029 max mem: 19788 +Epoch: [10] [1000/2138] eta: 1:08:44 lr: 3.805195816961783e-05 loss: 0.0426 (0.0465) time: 3.6254 data: 0.0029 max mem: 19788 +Epoch: [10] [1010/2138] eta: 1:08:08 lr: 3.804653409993511e-05 loss: 0.0430 (0.0465) time: 3.6271 data: 0.0028 max mem: 19788 +Epoch: [10] [1020/2138] eta: 1:07:32 lr: 3.804110994433129e-05 loss: 0.0385 (0.0464) time: 3.6313 data: 0.0028 max mem: 19788 +Epoch: [10] [1030/2138] eta: 1:06:56 lr: 3.803568570279141e-05 loss: 0.0380 (0.0464) time: 3.6345 data: 0.0028 max mem: 19788 +Epoch: [10] [1040/2138] eta: 1:06:20 lr: 3.803026137530049e-05 loss: 0.0382 (0.0463) time: 3.6468 data: 0.0029 max mem: 19788 +Epoch: [10] [1050/2138] eta: 1:05:43 lr: 3.802483696184353e-05 loss: 0.0395 (0.0464) time: 3.6348 data: 0.0030 max mem: 19788 +Epoch: [10] [1060/2138] eta: 1:05:07 lr: 3.801941246240555e-05 loss: 0.0400 (0.0463) time: 3.6130 data: 0.0030 max mem: 19788 +Epoch: [10] [1070/2138] eta: 1:04:31 lr: 3.801398787697156e-05 loss: 0.0400 (0.0463) time: 3.6166 data: 0.0033 max mem: 19788 +Epoch: [10] [1080/2138] eta: 1:03:54 lr: 3.800856320552657e-05 loss: 0.0408 (0.0463) time: 3.6160 data: 0.0034 max mem: 19788 +Epoch: [10] [1090/2138] eta: 1:03:18 lr: 3.8003138448055546e-05 loss: 0.0408 (0.0462) time: 3.6113 data: 0.0030 max mem: 19788 +Epoch: [10] [1100/2138] eta: 1:02:42 lr: 3.7997713604543514e-05 loss: 0.0404 (0.0463) time: 3.6164 data: 0.0028 max mem: 19788 +Epoch: [10] [1110/2138] eta: 1:02:05 lr: 3.7992288674975435e-05 loss: 0.0383 (0.0462) time: 3.6180 data: 0.0029 max mem: 19788 +Epoch: [10] [1120/2138] eta: 1:01:29 lr: 3.798686365933631e-05 loss: 0.0400 (0.0463) time: 3.6183 data: 0.0032 max mem: 19788 +Epoch: [10] [1130/2138] eta: 1:00:53 lr: 3.7981438557611085e-05 loss: 0.0418 (0.0463) time: 3.6269 data: 0.0031 max mem: 19788 +Epoch: [10] [1140/2138] eta: 1:00:17 lr: 3.797601336978476e-05 loss: 0.0424 (0.0463) time: 3.6237 data: 0.0029 max mem: 19788 +Epoch: [10] [1150/2138] eta: 0:59:40 lr: 3.79705880958423e-05 loss: 0.0424 (0.0462) time: 3.6183 data: 0.0030 max mem: 19788 +Epoch: [10] [1160/2138] eta: 0:59:04 lr: 3.7965162735768654e-05 loss: 0.0384 (0.0462) time: 3.6168 data: 0.0029 max mem: 19788 +Epoch: [10] [1170/2138] eta: 0:58:28 lr: 3.7959737289548784e-05 loss: 0.0443 (0.0462) time: 3.6140 data: 0.0030 max mem: 19788 +Epoch: [10] [1180/2138] eta: 0:57:51 lr: 3.7954311757167624e-05 loss: 0.0454 (0.0462) time: 3.6175 data: 0.0029 max mem: 19788 +Epoch: [10] [1190/2138] eta: 0:57:15 lr: 3.794888613861015e-05 loss: 0.0450 (0.0462) time: 3.6170 data: 0.0027 max mem: 19788 +Epoch: [10] [1200/2138] eta: 0:56:39 lr: 3.794346043386129e-05 loss: 0.0421 (0.0462) time: 3.6197 data: 0.0027 max mem: 19788 +Epoch: [10] [1210/2138] eta: 0:56:03 lr: 3.793803464290597e-05 loss: 0.0424 (0.0462) time: 3.6232 data: 0.0030 max mem: 19788 +Epoch: [10] [1220/2138] eta: 0:55:26 lr: 3.7932608765729126e-05 loss: 0.0467 (0.0463) time: 3.6233 data: 0.0030 max mem: 19788 +Epoch: [10] [1230/2138] eta: 0:54:50 lr: 3.7927182802315695e-05 loss: 0.0467 (0.0463) time: 3.6271 data: 0.0028 max mem: 19788 +Epoch: [10] [1240/2138] eta: 0:54:14 lr: 3.792175675265059e-05 loss: 0.0409 (0.0463) time: 3.6197 data: 0.0027 max mem: 19788 +Epoch: [10] [1250/2138] eta: 0:53:37 lr: 3.791633061671872e-05 loss: 0.0401 (0.0463) time: 3.6114 data: 0.0028 max mem: 19788 +Epoch: [10] [1260/2138] eta: 0:53:01 lr: 3.7910904394505006e-05 loss: 0.0347 (0.0463) time: 3.6219 data: 0.0027 max mem: 19788 +Epoch: [10] [1270/2138] eta: 0:52:25 lr: 3.7905478085994354e-05 loss: 0.0347 (0.0463) time: 3.6298 data: 0.0028 max mem: 19788 +Epoch: [10] [1280/2138] eta: 0:51:49 lr: 3.790005169117166e-05 loss: 0.0320 (0.0462) time: 3.6346 data: 0.0029 max mem: 19788 +Epoch: [10] [1290/2138] eta: 0:51:13 lr: 3.789462521002182e-05 loss: 0.0373 (0.0462) time: 3.6280 data: 0.0030 max mem: 19788 +Epoch: [10] [1300/2138] eta: 0:50:36 lr: 3.788919864252973e-05 loss: 0.0430 (0.0462) time: 3.6201 data: 0.0031 max mem: 19788 +Epoch: [10] [1310/2138] eta: 0:50:00 lr: 3.788377198868027e-05 loss: 0.0430 (0.0462) time: 3.6238 data: 0.0033 max mem: 19788 +Epoch: [10] [1320/2138] eta: 0:49:24 lr: 3.7878345248458314e-05 loss: 0.0420 (0.0462) time: 3.6186 data: 0.0031 max mem: 19788 +Epoch: [10] [1330/2138] eta: 0:48:48 lr: 3.7872918421848744e-05 loss: 0.0391 (0.0461) time: 3.6186 data: 0.0030 max mem: 19788 +Epoch: [10] [1340/2138] eta: 0:48:11 lr: 3.786749150883644e-05 loss: 0.0415 (0.0463) time: 3.6227 data: 0.0030 max mem: 19788 +Epoch: [10] [1350/2138] eta: 0:47:35 lr: 3.786206450940626e-05 loss: 0.0498 (0.0464) time: 3.6229 data: 0.0027 max mem: 19788 +Epoch: [10] [1360/2138] eta: 0:46:59 lr: 3.785663742354306e-05 loss: 0.0498 (0.0464) time: 3.6188 data: 0.0028 max mem: 19788 +Epoch: [10] [1370/2138] eta: 0:46:23 lr: 3.7851210251231695e-05 loss: 0.0430 (0.0464) time: 3.6157 data: 0.0031 max mem: 19788 +Epoch: [10] [1380/2138] eta: 0:45:46 lr: 3.7845782992457025e-05 loss: 0.0397 (0.0465) time: 3.6279 data: 0.0031 max mem: 19788 +Epoch: [10] [1390/2138] eta: 0:45:10 lr: 3.784035564720389e-05 loss: 0.0477 (0.0465) time: 3.6349 data: 0.0030 max mem: 19788 +Epoch: [10] [1400/2138] eta: 0:44:34 lr: 3.7834928215457124e-05 loss: 0.0397 (0.0465) time: 3.6202 data: 0.0029 max mem: 19788 +Epoch: [10] [1410/2138] eta: 0:43:58 lr: 3.782950069720156e-05 loss: 0.0397 (0.0465) time: 3.6135 data: 0.0030 max mem: 19788 +Epoch: [10] [1420/2138] eta: 0:43:21 lr: 3.782407309242205e-05 loss: 0.0411 (0.0465) time: 3.6121 data: 0.0033 max mem: 19788 +Epoch: [10] [1430/2138] eta: 0:42:45 lr: 3.7818645401103406e-05 loss: 0.0414 (0.0464) time: 3.6131 data: 0.0032 max mem: 19788 +Epoch: [10] [1440/2138] eta: 0:42:09 lr: 3.7813217623230436e-05 loss: 0.0414 (0.0464) time: 3.6206 data: 0.0029 max mem: 19788 +Epoch: [10] [1450/2138] eta: 0:41:33 lr: 3.780778975878797e-05 loss: 0.0390 (0.0464) time: 3.6212 data: 0.0029 max mem: 19788 +Epoch: [10] [1460/2138] eta: 0:40:56 lr: 3.78023618077608e-05 loss: 0.0439 (0.0464) time: 3.6178 data: 0.0029 max mem: 19788 +Epoch: [10] [1470/2138] eta: 0:40:20 lr: 3.779693377013376e-05 loss: 0.0429 (0.0464) time: 3.6186 data: 0.0029 max mem: 19788 +Epoch: [10] [1480/2138] eta: 0:39:44 lr: 3.779150564589162e-05 loss: 0.0429 (0.0464) time: 3.6217 data: 0.0028 max mem: 19788 +Epoch: [10] [1490/2138] eta: 0:39:08 lr: 3.7786077435019185e-05 loss: 0.0499 (0.0465) time: 3.6302 data: 0.0028 max mem: 19788 +Epoch: [10] [1500/2138] eta: 0:38:31 lr: 3.778064913750125e-05 loss: 0.0417 (0.0464) time: 3.6398 data: 0.0030 max mem: 19788 +Epoch: [10] [1510/2138] eta: 0:37:55 lr: 3.77752207533226e-05 loss: 0.0417 (0.0464) time: 3.6355 data: 0.0031 max mem: 19788 +Epoch: [10] [1520/2138] eta: 0:37:19 lr: 3.7769792282467995e-05 loss: 0.0375 (0.0464) time: 3.6250 data: 0.0028 max mem: 19788 +Epoch: [10] [1530/2138] eta: 0:36:43 lr: 3.776436372492223e-05 loss: 0.0384 (0.0464) time: 3.6228 data: 0.0029 max mem: 19788 +Epoch: [10] [1540/2138] eta: 0:36:06 lr: 3.7758935080670074e-05 loss: 0.0400 (0.0464) time: 3.6215 data: 0.0035 max mem: 19788 +Epoch: [10] [1550/2138] eta: 0:35:30 lr: 3.775350634969627e-05 loss: 0.0394 (0.0463) time: 3.6226 data: 0.0035 max mem: 19788 +Epoch: [10] [1560/2138] eta: 0:34:54 lr: 3.774807753198559e-05 loss: 0.0502 (0.0464) time: 3.6220 data: 0.0031 max mem: 19788 +Epoch: [10] [1570/2138] eta: 0:34:18 lr: 3.774264862752279e-05 loss: 0.0509 (0.0464) time: 3.6164 data: 0.0029 max mem: 19788 +Epoch: [10] [1580/2138] eta: 0:33:42 lr: 3.773721963629263e-05 loss: 0.0418 (0.0464) time: 3.6197 data: 0.0028 max mem: 19788 +Epoch: [10] [1590/2138] eta: 0:33:05 lr: 3.7731790558279825e-05 loss: 0.0419 (0.0464) time: 3.6261 data: 0.0030 max mem: 19788 +Epoch: [10] [1600/2138] eta: 0:32:29 lr: 3.772636139346912e-05 loss: 0.0451 (0.0464) time: 3.6241 data: 0.0032 max mem: 19788 +Epoch: [10] [1610/2138] eta: 0:31:53 lr: 3.772093214184526e-05 loss: 0.0435 (0.0464) time: 3.6171 data: 0.0032 max mem: 19788 +Epoch: [10] [1620/2138] eta: 0:31:17 lr: 3.771550280339298e-05 loss: 0.0394 (0.0464) time: 3.6221 data: 0.0032 max mem: 19788 +Epoch: [10] [1630/2138] eta: 0:30:40 lr: 3.771007337809697e-05 loss: 0.0435 (0.0464) time: 3.6228 data: 0.0032 max mem: 19788 +Epoch: [10] [1640/2138] eta: 0:30:04 lr: 3.770464386594197e-05 loss: 0.0435 (0.0464) time: 3.6232 data: 0.0031 max mem: 19788 +Epoch: [10] [1650/2138] eta: 0:29:28 lr: 3.7699214266912704e-05 loss: 0.0350 (0.0463) time: 3.6285 data: 0.0029 max mem: 19788 +Epoch: [10] [1660/2138] eta: 0:28:52 lr: 3.769378458099386e-05 loss: 0.0362 (0.0463) time: 3.6202 data: 0.0029 max mem: 19788 +Epoch: [10] [1670/2138] eta: 0:28:15 lr: 3.768835480817014e-05 loss: 0.0349 (0.0462) time: 3.6200 data: 0.0030 max mem: 19788 +Epoch: [10] [1680/2138] eta: 0:27:39 lr: 3.768292494842625e-05 loss: 0.0378 (0.0462) time: 3.6232 data: 0.0030 max mem: 19788 +Epoch: [10] [1690/2138] eta: 0:27:03 lr: 3.767749500174688e-05 loss: 0.0426 (0.0462) time: 3.6231 data: 0.0031 max mem: 19788 +Epoch: [10] [1700/2138] eta: 0:26:27 lr: 3.7672064968116717e-05 loss: 0.0389 (0.0462) time: 3.6279 data: 0.0031 max mem: 19788 +Epoch: [10] [1710/2138] eta: 0:25:50 lr: 3.766663484752044e-05 loss: 0.0358 (0.0462) time: 3.6241 data: 0.0030 max mem: 19788 +Epoch: [10] [1720/2138] eta: 0:25:14 lr: 3.766120463994272e-05 loss: 0.0360 (0.0461) time: 3.6198 data: 0.0030 max mem: 19788 +Epoch: [10] [1730/2138] eta: 0:24:38 lr: 3.765577434536824e-05 loss: 0.0396 (0.0461) time: 3.6208 data: 0.0030 max mem: 19788 +Epoch: [10] [1740/2138] eta: 0:24:02 lr: 3.765034396378166e-05 loss: 0.0373 (0.0461) time: 3.6237 data: 0.0028 max mem: 19788 +Epoch: [10] [1750/2138] eta: 0:23:25 lr: 3.764491349516764e-05 loss: 0.0381 (0.0461) time: 3.6315 data: 0.0026 max mem: 19788 +Epoch: [10] [1760/2138] eta: 0:22:49 lr: 3.7639482939510834e-05 loss: 0.0428 (0.0461) time: 3.6254 data: 0.0027 max mem: 19788 +Epoch: [10] [1770/2138] eta: 0:22:13 lr: 3.763405229679591e-05 loss: 0.0379 (0.0461) time: 3.6237 data: 0.0027 max mem: 19788 +Epoch: [10] [1780/2138] eta: 0:21:37 lr: 3.7628621567007485e-05 loss: 0.0374 (0.0460) time: 3.6313 data: 0.0029 max mem: 19788 +Epoch: [10] [1790/2138] eta: 0:21:01 lr: 3.762319075013022e-05 loss: 0.0401 (0.0461) time: 3.6278 data: 0.0034 max mem: 19788 +Epoch: [10] [1800/2138] eta: 0:20:24 lr: 3.7617759846148745e-05 loss: 0.0421 (0.0461) time: 3.6288 data: 0.0034 max mem: 19788 +Epoch: [10] [1810/2138] eta: 0:19:48 lr: 3.7612328855047684e-05 loss: 0.0421 (0.0461) time: 3.6220 data: 0.0031 max mem: 19788 +Epoch: [10] [1820/2138] eta: 0:19:12 lr: 3.760689777681167e-05 loss: 0.0378 (0.0461) time: 3.6161 data: 0.0030 max mem: 19788 +Epoch: [10] [1830/2138] eta: 0:18:36 lr: 3.7601466611425315e-05 loss: 0.0403 (0.0461) time: 3.6254 data: 0.0030 max mem: 19788 +Epoch: [10] [1840/2138] eta: 0:17:59 lr: 3.759603535887324e-05 loss: 0.0424 (0.0461) time: 3.6213 data: 0.0030 max mem: 19788 +Epoch: [10] [1850/2138] eta: 0:17:23 lr: 3.759060401914006e-05 loss: 0.0422 (0.0461) time: 3.6230 data: 0.0029 max mem: 19788 +Epoch: [10] [1860/2138] eta: 0:16:47 lr: 3.758517259221037e-05 loss: 0.0435 (0.0461) time: 3.6236 data: 0.0028 max mem: 19788 +Epoch: [10] [1870/2138] eta: 0:16:11 lr: 3.757974107806876e-05 loss: 0.0435 (0.0462) time: 3.6150 data: 0.0030 max mem: 19788 +Epoch: [10] [1880/2138] eta: 0:15:34 lr: 3.757430947669984e-05 loss: 0.0405 (0.0462) time: 3.6150 data: 0.0029 max mem: 19788 +Epoch: [10] [1890/2138] eta: 0:14:58 lr: 3.7568877788088184e-05 loss: 0.0381 (0.0461) time: 3.6201 data: 0.0029 max mem: 19788 +Epoch: [10] [1900/2138] eta: 0:14:22 lr: 3.7563446012218395e-05 loss: 0.0381 (0.0461) time: 3.6327 data: 0.0029 max mem: 19788 +Epoch: [10] [1910/2138] eta: 0:13:46 lr: 3.755801414907503e-05 loss: 0.0408 (0.0461) time: 3.6354 data: 0.0028 max mem: 19788 +Epoch: [10] [1920/2138] eta: 0:13:09 lr: 3.755258219864267e-05 loss: 0.0408 (0.0460) time: 3.6240 data: 0.0030 max mem: 19788 +Epoch: [10] [1930/2138] eta: 0:12:33 lr: 3.754715016090589e-05 loss: 0.0441 (0.0461) time: 3.6168 data: 0.0030 max mem: 19788 +Epoch: [10] [1940/2138] eta: 0:11:57 lr: 3.754171803584924e-05 loss: 0.0458 (0.0461) time: 3.6170 data: 0.0029 max mem: 19788 +Epoch: [10] [1950/2138] eta: 0:11:21 lr: 3.753628582345729e-05 loss: 0.0369 (0.0460) time: 3.6175 data: 0.0027 max mem: 19788 +Epoch: [10] [1960/2138] eta: 0:10:44 lr: 3.7530853523714584e-05 loss: 0.0374 (0.0460) time: 3.6171 data: 0.0027 max mem: 19788 +Epoch: [10] [1970/2138] eta: 0:10:08 lr: 3.752542113660567e-05 loss: 0.0470 (0.0461) time: 3.6169 data: 0.0028 max mem: 19788 +Epoch: [10] [1980/2138] eta: 0:09:32 lr: 3.751998866211508e-05 loss: 0.0486 (0.0461) time: 3.6192 data: 0.0029 max mem: 19788 +Epoch: [10] [1990/2138] eta: 0:08:56 lr: 3.7514556100227363e-05 loss: 0.0357 (0.0460) time: 3.6205 data: 0.0032 max mem: 19788 +Epoch: [10] [2000/2138] eta: 0:08:20 lr: 3.7509123450927055e-05 loss: 0.0390 (0.0461) time: 3.6182 data: 0.0033 max mem: 19788 +Epoch: [10] [2010/2138] eta: 0:07:43 lr: 3.7503690714198676e-05 loss: 0.0467 (0.0461) time: 3.6159 data: 0.0031 max mem: 19788 +Epoch: [10] [2020/2138] eta: 0:07:07 lr: 3.7498257890026736e-05 loss: 0.0411 (0.0460) time: 3.6248 data: 0.0029 max mem: 19788 +Epoch: [10] [2030/2138] eta: 0:06:31 lr: 3.749282497839575e-05 loss: 0.0411 (0.0460) time: 3.6298 data: 0.0030 max mem: 19788 +Epoch: [10] [2040/2138] eta: 0:05:55 lr: 3.7487391979290256e-05 loss: 0.0398 (0.0460) time: 3.6316 data: 0.0032 max mem: 19788 +Epoch: [10] [2050/2138] eta: 0:05:18 lr: 3.7481958892694735e-05 loss: 0.0389 (0.0460) time: 3.6459 data: 0.0031 max mem: 19788 +Epoch: [10] [2060/2138] eta: 0:04:42 lr: 3.7476525718593683e-05 loss: 0.0425 (0.0460) time: 3.6337 data: 0.0031 max mem: 19788 +Epoch: [10] [2070/2138] eta: 0:04:06 lr: 3.7471092456971604e-05 loss: 0.0438 (0.0460) time: 3.6154 data: 0.0028 max mem: 19788 +Epoch: [10] [2080/2138] eta: 0:03:30 lr: 3.7465659107812994e-05 loss: 0.0385 (0.0460) time: 3.6180 data: 0.0027 max mem: 19788 +Epoch: [10] [2090/2138] eta: 0:02:53 lr: 3.746022567110233e-05 loss: 0.0366 (0.0460) time: 3.6215 data: 0.0029 max mem: 19788 +Epoch: [10] [2100/2138] eta: 0:02:17 lr: 3.7454792146824085e-05 loss: 0.0411 (0.0460) time: 3.6217 data: 0.0030 max mem: 19788 +Epoch: [10] [2110/2138] eta: 0:01:41 lr: 3.744935853496274e-05 loss: 0.0547 (0.0461) time: 3.6196 data: 0.0031 max mem: 19788 +Epoch: [10] [2120/2138] eta: 0:01:05 lr: 3.744392483550276e-05 loss: 0.0571 (0.0461) time: 3.6164 data: 0.0030 max mem: 19788 +Epoch: [10] [2130/2138] eta: 0:00:28 lr: 3.743849104842861e-05 loss: 0.0440 (0.0461) time: 3.6000 data: 0.0028 max mem: 19788 +Epoch: [10] Total time: 2:09:07 +Test: [ 0/21770] eta: 18:11:40 time: 3.0088 data: 2.7135 max mem: 19788 +Test: [ 100/21770] eta: 0:34:34 time: 0.0701 data: 0.0018 max mem: 19788 +Test: [ 200/21770] eta: 0:28:50 time: 0.0695 data: 0.0021 max mem: 19788 +Test: [ 300/21770] eta: 0:26:29 time: 0.0669 data: 0.0021 max mem: 19788 +Test: [ 400/21770] eta: 0:25:35 time: 0.0581 data: 0.0017 max mem: 19788 +Test: [ 500/21770] eta: 0:24:45 time: 0.0660 data: 0.0021 max mem: 19788 +Test: [ 600/21770] eta: 0:24:20 time: 0.0701 data: 0.0021 max mem: 19788 +Test: [ 700/21770] eta: 0:24:03 time: 0.0623 data: 0.0019 max mem: 19788 +Test: [ 800/21770] eta: 0:23:50 time: 0.0576 data: 0.0018 max mem: 19788 +Test: [ 900/21770] eta: 0:23:31 time: 0.0636 data: 0.0019 max mem: 19788 +Test: [ 1000/21770] eta: 0:23:13 time: 0.0610 data: 0.0023 max mem: 19788 +Test: [ 1100/21770] eta: 0:23:10 time: 0.0673 data: 0.0022 max mem: 19788 +Test: [ 1200/21770] eta: 0:23:04 time: 0.0597 data: 0.0018 max mem: 19788 +Test: [ 1300/21770] eta: 0:23:08 time: 0.0662 data: 0.0019 max mem: 19788 +Test: [ 1400/21770] eta: 0:23:02 time: 0.0671 data: 0.0021 max mem: 19788 +Test: [ 1500/21770] eta: 0:22:55 time: 0.0749 data: 0.0020 max mem: 19788 +Test: [ 1600/21770] eta: 0:22:56 time: 0.0814 data: 0.0018 max mem: 19788 +Test: [ 1700/21770] eta: 0:22:57 time: 0.0726 data: 0.0022 max mem: 19788 +Test: [ 1800/21770] eta: 0:22:46 time: 0.0605 data: 0.0019 max mem: 19788 +Test: [ 1900/21770] eta: 0:22:33 time: 0.0631 data: 0.0018 max mem: 19788 +Test: [ 2000/21770] eta: 0:22:25 time: 0.0778 data: 0.0021 max mem: 19788 +Test: [ 2100/21770] eta: 0:22:15 time: 0.0632 data: 0.0018 max mem: 19788 +Test: [ 2200/21770] eta: 0:22:07 time: 0.0611 data: 0.0017 max mem: 19788 +Test: [ 2300/21770] eta: 0:22:03 time: 0.0717 data: 0.0021 max mem: 19788 +Test: [ 2400/21770] eta: 0:21:56 time: 0.0644 data: 0.0019 max mem: 19788 +Test: [ 2500/21770] eta: 0:21:47 time: 0.0601 data: 0.0016 max mem: 19788 +Test: [ 2600/21770] eta: 0:21:39 time: 0.0687 data: 0.0019 max mem: 19788 +Test: [ 2700/21770] eta: 0:21:31 time: 0.0645 data: 0.0019 max mem: 19788 +Test: [ 2800/21770] eta: 0:21:24 time: 0.0690 data: 0.0020 max mem: 19788 +Test: [ 2900/21770] eta: 0:21:14 time: 0.0652 data: 0.0019 max mem: 19788 +Test: [ 3000/21770] eta: 0:21:09 time: 0.0645 data: 0.0019 max mem: 19788 +Test: [ 3100/21770] eta: 0:21:04 time: 0.0687 data: 0.0020 max mem: 19788 +Test: [ 3200/21770] eta: 0:21:01 time: 0.0762 data: 0.0021 max mem: 19788 +Test: [ 3300/21770] eta: 0:20:55 time: 0.0755 data: 0.0021 max mem: 19788 +Test: [ 3400/21770] eta: 0:20:50 time: 0.0673 data: 0.0020 max mem: 19788 +Test: [ 3500/21770] eta: 0:20:43 time: 0.0611 data: 0.0018 max mem: 19788 +Test: [ 3600/21770] eta: 0:20:36 time: 0.0622 data: 0.0018 max mem: 19788 +Test: [ 3700/21770] eta: 0:20:29 time: 0.0622 data: 0.0018 max mem: 19788 +Test: [ 3800/21770] eta: 0:20:25 time: 0.0716 data: 0.0020 max mem: 19788 +Test: [ 3900/21770] eta: 0:20:21 time: 0.0738 data: 0.0021 max mem: 19788 +Test: [ 4000/21770] eta: 0:20:15 time: 0.0616 data: 0.0018 max mem: 19788 +Test: [ 4100/21770] eta: 0:20:06 time: 0.0624 data: 0.0017 max mem: 19788 +Test: [ 4200/21770] eta: 0:19:59 time: 0.0762 data: 0.0023 max mem: 19788 +Test: [ 4300/21770] eta: 0:19:51 time: 0.0628 data: 0.0017 max mem: 19788 +Test: [ 4400/21770] eta: 0:19:43 time: 0.0708 data: 0.0020 max mem: 19788 +Test: [ 4500/21770] eta: 0:19:35 time: 0.0599 data: 0.0018 max mem: 19788 +Test: [ 4600/21770] eta: 0:19:27 time: 0.0636 data: 0.0018 max mem: 19788 +Test: [ 4700/21770] eta: 0:19:21 time: 0.0788 data: 0.0020 max mem: 19788 +Test: [ 4800/21770] eta: 0:19:15 time: 0.0637 data: 0.0019 max mem: 19788 +Test: [ 4900/21770] eta: 0:19:07 time: 0.0627 data: 0.0018 max mem: 19788 +Test: [ 5000/21770] eta: 0:18:59 time: 0.0641 data: 0.0017 max mem: 19788 +Test: [ 5100/21770] eta: 0:18:52 time: 0.0773 data: 0.0023 max mem: 19788 +Test: [ 5200/21770] eta: 0:18:47 time: 0.0641 data: 0.0018 max mem: 19788 +Test: [ 5300/21770] eta: 0:18:40 time: 0.0736 data: 0.0021 max mem: 19788 +Test: [ 5400/21770] eta: 0:18:34 time: 0.0616 data: 0.0017 max mem: 19788 +Test: [ 5500/21770] eta: 0:18:27 time: 0.0634 data: 0.0017 max mem: 19788 +Test: [ 5600/21770] eta: 0:18:19 time: 0.0623 data: 0.0019 max mem: 19788 +Test: [ 5700/21770] eta: 0:18:11 time: 0.0638 data: 0.0020 max mem: 19788 +Test: [ 5800/21770] eta: 0:18:03 time: 0.0631 data: 0.0018 max mem: 19788 +Test: [ 5900/21770] eta: 0:17:56 time: 0.0720 data: 0.0023 max mem: 19788 +Test: [ 6000/21770] eta: 0:17:49 time: 0.0670 data: 0.0022 max mem: 19788 +Test: [ 6100/21770] eta: 0:17:42 time: 0.0619 data: 0.0019 max mem: 19788 +Test: [ 6200/21770] eta: 0:17:35 time: 0.0714 data: 0.0018 max mem: 19788 +Test: [ 6300/21770] eta: 0:17:27 time: 0.0659 data: 0.0019 max mem: 19788 +Test: [ 6400/21770] eta: 0:17:20 time: 0.0620 data: 0.0018 max mem: 19788 +Test: [ 6500/21770] eta: 0:17:13 time: 0.0664 data: 0.0019 max mem: 19788 +Test: [ 6600/21770] eta: 0:17:07 time: 0.0683 data: 0.0020 max mem: 19788 +Test: [ 6700/21770] eta: 0:17:00 time: 0.0620 data: 0.0018 max mem: 19788 +Test: [ 6800/21770] eta: 0:16:54 time: 0.0601 data: 0.0017 max mem: 19788 +Test: [ 6900/21770] eta: 0:16:49 time: 0.0819 data: 0.0019 max mem: 19788 +Test: [ 7000/21770] eta: 0:16:41 time: 0.0637 data: 0.0020 max mem: 19788 +Test: [ 7100/21770] eta: 0:16:34 time: 0.0684 data: 0.0020 max mem: 19788 +Test: [ 7200/21770] eta: 0:16:27 time: 0.0682 data: 0.0021 max mem: 19788 +Test: [ 7300/21770] eta: 0:16:21 time: 0.0707 data: 0.0020 max mem: 19788 +Test: [ 7400/21770] eta: 0:16:14 time: 0.0747 data: 0.0023 max mem: 19788 +Test: [ 7500/21770] eta: 0:16:09 time: 0.0829 data: 0.0025 max mem: 19788 +Test: [ 7600/21770] eta: 0:16:03 time: 0.0657 data: 0.0019 max mem: 19788 +Test: [ 7700/21770] eta: 0:15:57 time: 0.0805 data: 0.0022 max mem: 19788 +Test: [ 7800/21770] eta: 0:15:50 time: 0.0744 data: 0.0020 max mem: 19788 +Test: [ 7900/21770] eta: 0:15:44 time: 0.0772 data: 0.0022 max mem: 19788 +Test: [ 8000/21770] eta: 0:15:37 time: 0.0659 data: 0.0018 max mem: 19788 +Test: [ 8100/21770] eta: 0:15:32 time: 0.0819 data: 0.0025 max mem: 19788 +Test: [ 8200/21770] eta: 0:15:25 time: 0.0635 data: 0.0018 max mem: 19788 +Test: [ 8300/21770] eta: 0:15:18 time: 0.0722 data: 0.0020 max mem: 19788 +Test: [ 8400/21770] eta: 0:15:10 time: 0.0605 data: 0.0020 max mem: 19788 +Test: [ 8500/21770] eta: 0:15:04 time: 0.0746 data: 0.0022 max mem: 19788 +Test: [ 8600/21770] eta: 0:14:57 time: 0.0713 data: 0.0021 max mem: 19788 +Test: [ 8700/21770] eta: 0:14:51 time: 0.0750 data: 0.0019 max mem: 19788 +Test: [ 8800/21770] eta: 0:14:44 time: 0.0710 data: 0.0020 max mem: 19788 +Test: [ 8900/21770] eta: 0:14:37 time: 0.0631 data: 0.0019 max mem: 19788 +Test: [ 9000/21770] eta: 0:14:31 time: 0.0798 data: 0.0024 max mem: 19788 +Test: [ 9100/21770] eta: 0:14:24 time: 0.0702 data: 0.0021 max mem: 19788 +Test: [ 9200/21770] eta: 0:14:17 time: 0.0769 data: 0.0022 max mem: 19788 +Test: [ 9300/21770] eta: 0:14:10 time: 0.0675 data: 0.0018 max mem: 19788 +Test: [ 9400/21770] eta: 0:14:03 time: 0.0614 data: 0.0018 max mem: 19788 +Test: [ 9500/21770] eta: 0:13:56 time: 0.0615 data: 0.0019 max mem: 19788 +Test: [ 9600/21770] eta: 0:13:48 time: 0.0657 data: 0.0020 max mem: 19788 +Test: [ 9700/21770] eta: 0:13:41 time: 0.0650 data: 0.0021 max mem: 19788 +Test: [ 9800/21770] eta: 0:13:36 time: 0.0745 data: 0.0022 max mem: 19788 +Test: [ 9900/21770] eta: 0:13:30 time: 0.0791 data: 0.0023 max mem: 19788 +Test: [10000/21770] eta: 0:13:24 time: 0.0766 data: 0.0022 max mem: 19788 +Test: [10100/21770] eta: 0:13:17 time: 0.0807 data: 0.0024 max mem: 19788 +Test: [10200/21770] eta: 0:13:11 time: 0.0696 data: 0.0021 max mem: 19788 +Test: [10300/21770] eta: 0:13:05 time: 0.0631 data: 0.0018 max mem: 19788 +Test: [10400/21770] eta: 0:12:57 time: 0.0702 data: 0.0018 max mem: 19788 +Test: [10500/21770] eta: 0:12:50 time: 0.0628 data: 0.0017 max mem: 19788 +Test: [10600/21770] eta: 0:12:43 time: 0.0617 data: 0.0017 max mem: 19788 +Test: [10700/21770] eta: 0:12:36 time: 0.0623 data: 0.0017 max mem: 19788 +Test: [10800/21770] eta: 0:12:29 time: 0.0650 data: 0.0019 max mem: 19788 +Test: [10900/21770] eta: 0:12:22 time: 0.0687 data: 0.0020 max mem: 19788 +Test: [11000/21770] eta: 0:12:16 time: 0.0701 data: 0.0023 max mem: 19788 +Test: [11100/21770] eta: 0:12:09 time: 0.0717 data: 0.0019 max mem: 19788 +Test: [11200/21770] eta: 0:12:02 time: 0.0756 data: 0.0021 max mem: 19788 +Test: [11300/21770] eta: 0:11:55 time: 0.0734 data: 0.0020 max mem: 19788 +Test: [11400/21770] eta: 0:11:49 time: 0.0697 data: 0.0021 max mem: 19788 +Test: [11500/21770] eta: 0:11:42 time: 0.0620 data: 0.0018 max mem: 19788 +Test: [11600/21770] eta: 0:11:34 time: 0.0663 data: 0.0018 max mem: 19788 +Test: [11700/21770] eta: 0:11:27 time: 0.0820 data: 0.0019 max mem: 19788 +Test: [11800/21770] eta: 0:11:21 time: 0.0652 data: 0.0017 max mem: 19788 +Test: [11900/21770] eta: 0:11:14 time: 0.0614 data: 0.0019 max mem: 19788 +Test: [12000/21770] eta: 0:11:07 time: 0.0804 data: 0.0023 max mem: 19788 +Test: [12100/21770] eta: 0:11:01 time: 0.0702 data: 0.0020 max mem: 19788 +Test: [12200/21770] eta: 0:10:54 time: 0.0655 data: 0.0019 max mem: 19788 +Test: [12300/21770] eta: 0:10:47 time: 0.0629 data: 0.0019 max mem: 19788 +Test: [12400/21770] eta: 0:10:40 time: 0.0763 data: 0.0019 max mem: 19788 +Test: [12500/21770] eta: 0:10:33 time: 0.0696 data: 0.0019 max mem: 19788 +Test: [12600/21770] eta: 0:10:26 time: 0.0672 data: 0.0018 max mem: 19788 +Test: [12700/21770] eta: 0:10:20 time: 0.0694 data: 0.0021 max mem: 19788 +Test: [12800/21770] eta: 0:10:12 time: 0.0642 data: 0.0019 max mem: 19788 +Test: [12900/21770] eta: 0:10:06 time: 0.0825 data: 0.0024 max mem: 19788 +Test: [13000/21770] eta: 0:09:59 time: 0.0733 data: 0.0022 max mem: 19788 +Test: [13100/21770] eta: 0:09:52 time: 0.0787 data: 0.0024 max mem: 19788 +Test: [13200/21770] eta: 0:09:46 time: 0.0605 data: 0.0016 max mem: 19788 +Test: [13300/21770] eta: 0:09:39 time: 0.0702 data: 0.0018 max mem: 19788 +Test: [13400/21770] eta: 0:09:32 time: 0.0756 data: 0.0021 max mem: 19788 +Test: [13500/21770] eta: 0:09:26 time: 0.0687 data: 0.0020 max mem: 19788 +Test: [13600/21770] eta: 0:09:19 time: 0.0807 data: 0.0024 max mem: 19788 +Test: [13700/21770] eta: 0:09:12 time: 0.0810 data: 0.0023 max mem: 19788 +Test: [13800/21770] eta: 0:09:05 time: 0.0679 data: 0.0021 max mem: 19788 +Test: [13900/21770] eta: 0:08:59 time: 0.0701 data: 0.0018 max mem: 19788 +Test: [14000/21770] eta: 0:08:52 time: 0.0666 data: 0.0018 max mem: 19788 +Test: [14100/21770] eta: 0:08:45 time: 0.0812 data: 0.0025 max mem: 19788 +Test: [14200/21770] eta: 0:08:38 time: 0.0709 data: 0.0021 max mem: 19788 +Test: [14300/21770] eta: 0:08:32 time: 0.0701 data: 0.0019 max mem: 19788 +Test: [14400/21770] eta: 0:08:25 time: 0.0633 data: 0.0018 max mem: 19788 +Test: [14500/21770] eta: 0:08:18 time: 0.0669 data: 0.0020 max mem: 19788 +Test: [14600/21770] eta: 0:08:11 time: 0.0604 data: 0.0019 max mem: 19788 +Test: [14700/21770] eta: 0:08:04 time: 0.0637 data: 0.0018 max mem: 19788 +Test: [14800/21770] eta: 0:07:57 time: 0.0679 data: 0.0020 max mem: 19788 +Test: [14900/21770] eta: 0:07:51 time: 0.0725 data: 0.0023 max mem: 19788 +Test: [15000/21770] eta: 0:07:44 time: 0.0663 data: 0.0019 max mem: 19788 +Test: [15100/21770] eta: 0:07:37 time: 0.0781 data: 0.0024 max mem: 19788 +Test: [15200/21770] eta: 0:07:31 time: 0.0754 data: 0.0024 max mem: 19788 +Test: [15300/21770] eta: 0:07:24 time: 0.0760 data: 0.0020 max mem: 19788 +Test: [15400/21770] eta: 0:07:17 time: 0.0678 data: 0.0019 max mem: 19788 +Test: [15500/21770] eta: 0:07:10 time: 0.0665 data: 0.0018 max mem: 19788 +Test: [15600/21770] eta: 0:07:03 time: 0.0663 data: 0.0020 max mem: 19788 +Test: [15700/21770] eta: 0:06:56 time: 0.0631 data: 0.0019 max mem: 19788 +Test: [15800/21770] eta: 0:06:50 time: 0.0752 data: 0.0023 max mem: 19788 +Test: [15900/21770] eta: 0:06:43 time: 0.0811 data: 0.0023 max mem: 19788 +Test: [16000/21770] eta: 0:06:36 time: 0.0724 data: 0.0023 max mem: 19788 +Test: [16100/21770] eta: 0:06:29 time: 0.0671 data: 0.0019 max mem: 19788 +Test: [16200/21770] eta: 0:06:22 time: 0.0744 data: 0.0021 max mem: 19788 +Test: [16300/21770] eta: 0:06:15 time: 0.0628 data: 0.0017 max mem: 19788 +Test: [16400/21770] eta: 0:06:08 time: 0.0641 data: 0.0019 max mem: 19788 +Test: [16500/21770] eta: 0:06:01 time: 0.0803 data: 0.0025 max mem: 19788 +Test: [16600/21770] eta: 0:05:55 time: 0.0656 data: 0.0019 max mem: 19788 +Test: [16700/21770] eta: 0:05:48 time: 0.0674 data: 0.0019 max mem: 19788 +Test: [16800/21770] eta: 0:05:41 time: 0.0624 data: 0.0017 max mem: 19788 +Test: [16900/21770] eta: 0:05:34 time: 0.0607 data: 0.0017 max mem: 19788 +Test: [17000/21770] eta: 0:05:27 time: 0.0615 data: 0.0017 max mem: 19788 +Test: [17100/21770] eta: 0:05:20 time: 0.0717 data: 0.0021 max mem: 19788 +Test: [17200/21770] eta: 0:05:13 time: 0.0630 data: 0.0018 max mem: 19788 +Test: [17300/21770] eta: 0:05:06 time: 0.0629 data: 0.0017 max mem: 19788 +Test: [17400/21770] eta: 0:04:59 time: 0.0813 data: 0.0023 max mem: 19788 +Test: [17500/21770] eta: 0:04:52 time: 0.0765 data: 0.0022 max mem: 19788 +Test: [17600/21770] eta: 0:04:45 time: 0.0617 data: 0.0018 max mem: 19788 +Test: [17700/21770] eta: 0:04:38 time: 0.0804 data: 0.0020 max mem: 19788 +Test: [17800/21770] eta: 0:04:32 time: 0.0826 data: 0.0019 max mem: 19788 +Test: [17900/21770] eta: 0:04:25 time: 0.0618 data: 0.0018 max mem: 19788 +Test: [18000/21770] eta: 0:04:18 time: 0.0615 data: 0.0021 max mem: 19788 +Test: [18100/21770] eta: 0:04:11 time: 0.0645 data: 0.0019 max mem: 19788 +Test: [18200/21770] eta: 0:04:04 time: 0.0679 data: 0.0019 max mem: 19788 +Test: [18300/21770] eta: 0:03:57 time: 0.0764 data: 0.0022 max mem: 19788 +Test: [18400/21770] eta: 0:03:50 time: 0.0631 data: 0.0020 max mem: 19788 +Test: [18500/21770] eta: 0:03:43 time: 0.0671 data: 0.0019 max mem: 19788 +Test: [18600/21770] eta: 0:03:36 time: 0.0677 data: 0.0019 max mem: 19788 +Test: [18700/21770] eta: 0:03:30 time: 0.0715 data: 0.0021 max mem: 19788 +Test: [18800/21770] eta: 0:03:23 time: 0.0681 data: 0.0019 max mem: 19788 +Test: [18900/21770] eta: 0:03:16 time: 0.0626 data: 0.0018 max mem: 19788 +Test: [19000/21770] eta: 0:03:09 time: 0.0621 data: 0.0019 max mem: 19788 +Test: [19100/21770] eta: 0:03:02 time: 0.0639 data: 0.0018 max mem: 19788 +Test: [19200/21770] eta: 0:02:55 time: 0.0723 data: 0.0021 max mem: 19788 +Test: [19300/21770] eta: 0:02:48 time: 0.0612 data: 0.0020 max mem: 19788 +Test: [19400/21770] eta: 0:02:42 time: 0.0739 data: 0.0021 max mem: 19788 +Test: [19500/21770] eta: 0:02:35 time: 0.0587 data: 0.0017 max mem: 19788 +Test: [19600/21770] eta: 0:02:28 time: 0.0630 data: 0.0020 max mem: 19788 +Test: [19700/21770] eta: 0:02:21 time: 0.0610 data: 0.0018 max mem: 19788 +Test: [19800/21770] eta: 0:02:14 time: 0.0650 data: 0.0018 max mem: 19788 +Test: [19900/21770] eta: 0:02:07 time: 0.0611 data: 0.0018 max mem: 19788 +Test: [20000/21770] eta: 0:02:00 time: 0.0717 data: 0.0022 max mem: 19788 +Test: [20100/21770] eta: 0:01:54 time: 0.0607 data: 0.0018 max mem: 19788 +Test: [20200/21770] eta: 0:01:47 time: 0.0629 data: 0.0017 max mem: 19788 +Test: [20300/21770] eta: 0:01:40 time: 0.0652 data: 0.0020 max mem: 19788 +Test: [20400/21770] eta: 0:01:33 time: 0.0678 data: 0.0018 max mem: 19788 +Test: [20500/21770] eta: 0:01:26 time: 0.0769 data: 0.0024 max mem: 19788 +Test: [20600/21770] eta: 0:01:19 time: 0.0639 data: 0.0019 max mem: 19788 +Test: [20700/21770] eta: 0:01:13 time: 0.0752 data: 0.0023 max mem: 19788 +Test: [20800/21770] eta: 0:01:06 time: 0.0762 data: 0.0021 max mem: 19788 +Test: [20900/21770] eta: 0:00:59 time: 0.0716 data: 0.0021 max mem: 19788 +Test: [21000/21770] eta: 0:00:52 time: 0.0620 data: 0.0017 max mem: 19788 +Test: [21100/21770] eta: 0:00:45 time: 0.0629 data: 0.0019 max mem: 19788 +Test: [21200/21770] eta: 0:00:38 time: 0.0694 data: 0.0021 max mem: 19788 +Test: [21300/21770] eta: 0:00:32 time: 0.0742 data: 0.0019 max mem: 19788 +Test: [21400/21770] eta: 0:00:25 time: 0.0658 data: 0.0021 max mem: 19788 +Test: [21500/21770] eta: 0:00:18 time: 0.0675 data: 0.0020 max mem: 19788 +Test: [21600/21770] eta: 0:00:11 time: 0.0625 data: 0.0018 max mem: 19788 +Test: [21700/21770] eta: 0:00:04 time: 0.0811 data: 0.0043 max mem: 19788 +Test: Total time: 0:24:47 +Final results: +Mean IoU is 62.00 + + precision@0.5 = 68.75 + precision@0.6 = 63.13 + precision@0.7 = 56.18 + precision@0.8 = 45.40 + precision@0.9 = 22.03 + overall IoU = 62.79 + mean IoU = 62.00 + +Mean accuracy for one-to-zero sample is 77.87 + +Average object IoU 0.6200093216231713 +Overall IoU 62.78554153442383 +Better epoch: 10 + +Epoch: [11] [ 0/2138] eta: 3:14:24 lr: 3.7434143955676645e-05 loss: 0.0504 (0.0504) time: 5.4557 data: 1.5045 max mem: 19788 +Epoch: [11] [ 10/2138] eta: 2:15:17 lr: 3.7428710010857814e-05 loss: 0.0337 (0.0356) time: 3.8147 data: 0.1392 max mem: 19788 +Epoch: [11] [ 20/2138] eta: 2:11:29 lr: 3.742327597838128e-05 loss: 0.0347 (0.0368) time: 3.6384 data: 0.0022 max mem: 19788 +Epoch: [11] [ 30/2138] eta: 2:09:46 lr: 3.741784185823149e-05 loss: 0.0387 (0.0387) time: 3.6275 data: 0.0024 max mem: 19788 +Epoch: [11] [ 40/2138] eta: 2:08:40 lr: 3.7412407650392866e-05 loss: 0.0417 (0.0394) time: 3.6323 data: 0.0031 max mem: 19788 +Epoch: [11] [ 50/2138] eta: 2:07:41 lr: 3.7406973354849866e-05 loss: 0.0387 (0.0403) time: 3.6310 data: 0.0029 max mem: 19788 +Epoch: [11] [ 60/2138] eta: 2:06:46 lr: 3.7401538971586894e-05 loss: 0.0322 (0.0396) time: 3.6205 data: 0.0027 max mem: 19788 +Epoch: [11] [ 70/2138] eta: 2:05:56 lr: 3.739610450058838e-05 loss: 0.0263 (0.0382) time: 3.6149 data: 0.0027 max mem: 19788 +Epoch: [11] [ 80/2138] eta: 2:05:12 lr: 3.739066994183875e-05 loss: 0.0358 (0.0393) time: 3.6191 data: 0.0026 max mem: 19788 +Epoch: [11] [ 90/2138] eta: 2:04:28 lr: 3.73852352953224e-05 loss: 0.0431 (0.0401) time: 3.6219 data: 0.0028 max mem: 19788 +Epoch: [11] [ 100/2138] eta: 2:03:45 lr: 3.7379800561023745e-05 loss: 0.0375 (0.0397) time: 3.6167 data: 0.0030 max mem: 19788 +Epoch: [11] [ 110/2138] eta: 2:03:03 lr: 3.737436573892718e-05 loss: 0.0374 (0.0398) time: 3.6121 data: 0.0028 max mem: 19788 +Epoch: [11] [ 120/2138] eta: 2:02:23 lr: 3.7368930829017115e-05 loss: 0.0385 (0.0407) time: 3.6175 data: 0.0027 max mem: 19788 +Epoch: [11] [ 130/2138] eta: 2:01:44 lr: 3.736349583127792e-05 loss: 0.0404 (0.0410) time: 3.6215 data: 0.0026 max mem: 19788 +Epoch: [11] [ 140/2138] eta: 2:01:05 lr: 3.735806074569399e-05 loss: 0.0382 (0.0415) time: 3.6183 data: 0.0027 max mem: 19788 +Epoch: [11] [ 150/2138] eta: 2:00:25 lr: 3.735262557224969e-05 loss: 0.0382 (0.0413) time: 3.6147 data: 0.0028 max mem: 19788 +Epoch: [11] [ 160/2138] eta: 1:59:46 lr: 3.734719031092942e-05 loss: 0.0395 (0.0421) time: 3.6114 data: 0.0030 max mem: 19788 +Epoch: [11] [ 170/2138] eta: 1:59:08 lr: 3.7341754961717545e-05 loss: 0.0461 (0.0422) time: 3.6137 data: 0.0030 max mem: 19788 +Epoch: [11] [ 180/2138] eta: 1:58:32 lr: 3.7336319524598406e-05 loss: 0.0378 (0.0426) time: 3.6290 data: 0.0029 max mem: 19788 +Epoch: [11] [ 190/2138] eta: 1:57:56 lr: 3.733088399955637e-05 loss: 0.0428 (0.0426) time: 3.6361 data: 0.0030 max mem: 19788 +Epoch: [11] [ 200/2138] eta: 1:57:19 lr: 3.732544838657581e-05 loss: 0.0356 (0.0421) time: 3.6265 data: 0.0030 max mem: 19788 +Epoch: [11] [ 210/2138] eta: 1:56:41 lr: 3.732001268564106e-05 loss: 0.0378 (0.0426) time: 3.6211 data: 0.0032 max mem: 19788 +Epoch: [11] [ 220/2138] eta: 1:56:03 lr: 3.731457689673645e-05 loss: 0.0443 (0.0427) time: 3.6162 data: 0.0031 max mem: 19788 +Epoch: [11] [ 230/2138] eta: 1:55:25 lr: 3.7309141019846325e-05 loss: 0.0420 (0.0429) time: 3.6112 data: 0.0030 max mem: 19788 +Epoch: [11] [ 240/2138] eta: 1:54:47 lr: 3.730370505495504e-05 loss: 0.0412 (0.0429) time: 3.6092 data: 0.0030 max mem: 19788 +Epoch: [11] [ 250/2138] eta: 1:54:12 lr: 3.729826900204688e-05 loss: 0.0396 (0.0429) time: 3.6242 data: 0.0028 max mem: 19788 +Epoch: [11] [ 260/2138] eta: 1:53:35 lr: 3.72928328611062e-05 loss: 0.0393 (0.0427) time: 3.6300 data: 0.0027 max mem: 19788 +Epoch: [11] [ 270/2138] eta: 1:52:57 lr: 3.72873966321173e-05 loss: 0.0410 (0.0429) time: 3.6164 data: 0.0029 max mem: 19788 +Epoch: [11] [ 280/2138] eta: 1:52:20 lr: 3.7281960315064486e-05 loss: 0.0377 (0.0427) time: 3.6133 data: 0.0029 max mem: 19788 +Epoch: [11] [ 290/2138] eta: 1:51:43 lr: 3.727652390993207e-05 loss: 0.0367 (0.0428) time: 3.6155 data: 0.0029 max mem: 19788 +Epoch: [11] [ 300/2138] eta: 1:51:08 lr: 3.727108741670435e-05 loss: 0.0361 (0.0426) time: 3.6298 data: 0.0029 max mem: 19788 +Epoch: [11] [ 310/2138] eta: 1:50:31 lr: 3.726565083536563e-05 loss: 0.0366 (0.0426) time: 3.6316 data: 0.0028 max mem: 19788 +Epoch: [11] [ 320/2138] eta: 1:49:55 lr: 3.726021416590019e-05 loss: 0.0340 (0.0425) time: 3.6281 data: 0.0028 max mem: 19788 +Epoch: [11] [ 330/2138] eta: 1:49:19 lr: 3.7254777408292315e-05 loss: 0.0379 (0.0426) time: 3.6329 data: 0.0029 max mem: 19788 +Epoch: [11] [ 340/2138] eta: 1:48:42 lr: 3.724934056252628e-05 loss: 0.0384 (0.0424) time: 3.6267 data: 0.0031 max mem: 19788 +Epoch: [11] [ 350/2138] eta: 1:48:07 lr: 3.724390362858636e-05 loss: 0.0364 (0.0423) time: 3.6300 data: 0.0029 max mem: 19788 +Epoch: [11] [ 360/2138] eta: 1:47:30 lr: 3.7238466606456826e-05 loss: 0.0376 (0.0423) time: 3.6245 data: 0.0029 max mem: 19788 +Epoch: [11] [ 370/2138] eta: 1:46:53 lr: 3.7233029496121936e-05 loss: 0.0402 (0.0425) time: 3.6138 data: 0.0031 max mem: 19788 +Epoch: [11] [ 380/2138] eta: 1:46:16 lr: 3.722759229756594e-05 loss: 0.0439 (0.0430) time: 3.6216 data: 0.0032 max mem: 19788 +Epoch: [11] [ 390/2138] eta: 1:45:40 lr: 3.7222155010773115e-05 loss: 0.0422 (0.0429) time: 3.6216 data: 0.0030 max mem: 19788 +Epoch: [11] [ 400/2138] eta: 1:45:04 lr: 3.721671763572768e-05 loss: 0.0415 (0.0430) time: 3.6259 data: 0.0029 max mem: 19788 +Epoch: [11] [ 410/2138] eta: 1:44:27 lr: 3.721128017241389e-05 loss: 0.0471 (0.0432) time: 3.6281 data: 0.0029 max mem: 19788 +Epoch: [11] [ 420/2138] eta: 1:43:51 lr: 3.720584262081597e-05 loss: 0.0438 (0.0432) time: 3.6233 data: 0.0029 max mem: 19788 +Epoch: [11] [ 430/2138] eta: 1:43:14 lr: 3.7200404980918154e-05 loss: 0.0400 (0.0434) time: 3.6245 data: 0.0029 max mem: 19788 +Epoch: [11] [ 440/2138] eta: 1:42:38 lr: 3.7194967252704686e-05 loss: 0.0402 (0.0435) time: 3.6206 data: 0.0028 max mem: 19788 +Epoch: [11] [ 450/2138] eta: 1:42:01 lr: 3.718952943615975e-05 loss: 0.0402 (0.0434) time: 3.6182 data: 0.0028 max mem: 19788 +Epoch: [11] [ 460/2138] eta: 1:41:25 lr: 3.718409153126758e-05 loss: 0.0395 (0.0434) time: 3.6168 data: 0.0029 max mem: 19788 +Epoch: [11] [ 470/2138] eta: 1:40:48 lr: 3.7178653538012385e-05 loss: 0.0404 (0.0435) time: 3.6233 data: 0.0031 max mem: 19788 +Epoch: [11] [ 480/2138] eta: 1:40:12 lr: 3.717321545637837e-05 loss: 0.0407 (0.0434) time: 3.6224 data: 0.0029 max mem: 19788 +Epoch: [11] [ 490/2138] eta: 1:39:36 lr: 3.716777728634972e-05 loss: 0.0431 (0.0435) time: 3.6202 data: 0.0029 max mem: 19788 +Epoch: [11] [ 500/2138] eta: 1:38:59 lr: 3.716233902791063e-05 loss: 0.0389 (0.0435) time: 3.6255 data: 0.0031 max mem: 19788 +Epoch: [11] [ 510/2138] eta: 1:38:23 lr: 3.7156900681045305e-05 loss: 0.0389 (0.0434) time: 3.6206 data: 0.0031 max mem: 19788 +Epoch: [11] [ 520/2138] eta: 1:37:46 lr: 3.715146224573791e-05 loss: 0.0416 (0.0434) time: 3.6167 data: 0.0029 max mem: 19788 +Epoch: [11] [ 530/2138] eta: 1:37:09 lr: 3.714602372197262e-05 loss: 0.0405 (0.0435) time: 3.6136 data: 0.0027 max mem: 19788 +Epoch: [11] [ 540/2138] eta: 1:36:33 lr: 3.7140585109733613e-05 loss: 0.0370 (0.0434) time: 3.6149 data: 0.0029 max mem: 19788 +Epoch: [11] [ 550/2138] eta: 1:35:57 lr: 3.713514640900506e-05 loss: 0.0370 (0.0434) time: 3.6227 data: 0.0029 max mem: 19788 +Epoch: [11] [ 560/2138] eta: 1:35:20 lr: 3.7129707619771104e-05 loss: 0.0373 (0.0433) time: 3.6244 data: 0.0028 max mem: 19788 +Epoch: [11] [ 570/2138] eta: 1:34:44 lr: 3.7124268742015904e-05 loss: 0.0421 (0.0434) time: 3.6221 data: 0.0029 max mem: 19788 +Epoch: [11] [ 580/2138] eta: 1:34:08 lr: 3.7118829775723616e-05 loss: 0.0440 (0.0434) time: 3.6267 data: 0.0030 max mem: 19788 +Epoch: [11] [ 590/2138] eta: 1:33:31 lr: 3.711339072087839e-05 loss: 0.0440 (0.0433) time: 3.6221 data: 0.0031 max mem: 19788 +Epoch: [11] [ 600/2138] eta: 1:32:56 lr: 3.7107951577464336e-05 loss: 0.0444 (0.0435) time: 3.6272 data: 0.0032 max mem: 19788 +Epoch: [11] [ 610/2138] eta: 1:32:20 lr: 3.710251234546562e-05 loss: 0.0442 (0.0434) time: 3.6436 data: 0.0032 max mem: 19788 +Epoch: [11] [ 620/2138] eta: 1:31:44 lr: 3.709707302486635e-05 loss: 0.0386 (0.0434) time: 3.6425 data: 0.0029 max mem: 19788 +Epoch: [11] [ 630/2138] eta: 1:31:08 lr: 3.709163361565066e-05 loss: 0.0379 (0.0433) time: 3.6375 data: 0.0029 max mem: 19788 +Epoch: [11] [ 640/2138] eta: 1:30:31 lr: 3.708619411780264e-05 loss: 0.0371 (0.0432) time: 3.6289 data: 0.0029 max mem: 19788 +Epoch: [11] [ 650/2138] eta: 1:29:55 lr: 3.708075453130643e-05 loss: 0.0362 (0.0431) time: 3.6217 data: 0.0028 max mem: 19788 +Epoch: [11] [ 660/2138] eta: 1:29:19 lr: 3.707531485614613e-05 loss: 0.0365 (0.0430) time: 3.6182 data: 0.0029 max mem: 19788 +Epoch: [11] [ 670/2138] eta: 1:28:42 lr: 3.7069875092305836e-05 loss: 0.0373 (0.0429) time: 3.6202 data: 0.0030 max mem: 19788 +Epoch: [11] [ 680/2138] eta: 1:28:06 lr: 3.706443523976964e-05 loss: 0.0399 (0.0430) time: 3.6206 data: 0.0030 max mem: 19788 +Epoch: [11] [ 690/2138] eta: 1:27:30 lr: 3.705899529852163e-05 loss: 0.0408 (0.0430) time: 3.6245 data: 0.0030 max mem: 19788 +Epoch: [11] [ 700/2138] eta: 1:26:53 lr: 3.70535552685459e-05 loss: 0.0426 (0.0431) time: 3.6230 data: 0.0030 max mem: 19788 +Epoch: [11] [ 710/2138] eta: 1:26:17 lr: 3.704811514982652e-05 loss: 0.0434 (0.0431) time: 3.6188 data: 0.0033 max mem: 19788 +Epoch: [11] [ 720/2138] eta: 1:25:40 lr: 3.704267494234756e-05 loss: 0.0426 (0.0432) time: 3.6186 data: 0.0034 max mem: 19788 +Epoch: [11] [ 730/2138] eta: 1:25:04 lr: 3.7037234646093095e-05 loss: 0.0387 (0.0433) time: 3.6141 data: 0.0031 max mem: 19788 +Epoch: [11] [ 740/2138] eta: 1:24:28 lr: 3.703179426104719e-05 loss: 0.0376 (0.0432) time: 3.6199 data: 0.0031 max mem: 19788 +Epoch: [11] [ 750/2138] eta: 1:23:51 lr: 3.702635378719389e-05 loss: 0.0375 (0.0432) time: 3.6192 data: 0.0030 max mem: 19788 +Epoch: [11] [ 760/2138] eta: 1:23:15 lr: 3.702091322451724e-05 loss: 0.0418 (0.0433) time: 3.6205 data: 0.0031 max mem: 19788 +Epoch: [11] [ 770/2138] eta: 1:22:39 lr: 3.701547257300132e-05 loss: 0.0429 (0.0433) time: 3.6305 data: 0.0031 max mem: 19788 +Epoch: [11] [ 780/2138] eta: 1:22:02 lr: 3.701003183263013e-05 loss: 0.0437 (0.0433) time: 3.6231 data: 0.0029 max mem: 19788 +Epoch: [11] [ 790/2138] eta: 1:21:26 lr: 3.7004591003387735e-05 loss: 0.0464 (0.0433) time: 3.6128 data: 0.0027 max mem: 19788 +Epoch: [11] [ 800/2138] eta: 1:20:50 lr: 3.699915008525814e-05 loss: 0.0431 (0.0434) time: 3.6200 data: 0.0029 max mem: 19788 +Epoch: [11] [ 810/2138] eta: 1:20:13 lr: 3.6993709078225386e-05 loss: 0.0405 (0.0434) time: 3.6212 data: 0.0032 max mem: 19788 +Epoch: [11] [ 820/2138] eta: 1:19:37 lr: 3.698826798227349e-05 loss: 0.0453 (0.0435) time: 3.6156 data: 0.0031 max mem: 19788 +Epoch: [11] [ 830/2138] eta: 1:19:01 lr: 3.6982826797386454e-05 loss: 0.0459 (0.0435) time: 3.6157 data: 0.0030 max mem: 19788 +Epoch: [11] [ 840/2138] eta: 1:18:24 lr: 3.697738552354829e-05 loss: 0.0349 (0.0434) time: 3.6119 data: 0.0031 max mem: 19788 +Epoch: [11] [ 850/2138] eta: 1:17:48 lr: 3.6971944160743e-05 loss: 0.0349 (0.0434) time: 3.6121 data: 0.0031 max mem: 19788 +Epoch: [11] [ 860/2138] eta: 1:17:11 lr: 3.696650270895459e-05 loss: 0.0413 (0.0434) time: 3.6136 data: 0.0030 max mem: 19788 +Epoch: [11] [ 870/2138] eta: 1:16:35 lr: 3.6961061168167036e-05 loss: 0.0413 (0.0434) time: 3.6132 data: 0.0030 max mem: 19788 +Epoch: [11] [ 880/2138] eta: 1:15:59 lr: 3.6955619538364323e-05 loss: 0.0408 (0.0434) time: 3.6170 data: 0.0030 max mem: 19788 +Epoch: [11] [ 890/2138] eta: 1:15:22 lr: 3.695017781953044e-05 loss: 0.0353 (0.0434) time: 3.6153 data: 0.0029 max mem: 19788 +Epoch: [11] [ 900/2138] eta: 1:14:46 lr: 3.694473601164936e-05 loss: 0.0446 (0.0435) time: 3.6148 data: 0.0030 max mem: 19788 +Epoch: [11] [ 910/2138] eta: 1:14:10 lr: 3.693929411470505e-05 loss: 0.0459 (0.0434) time: 3.6178 data: 0.0031 max mem: 19788 +Epoch: [11] [ 920/2138] eta: 1:13:33 lr: 3.6933852128681467e-05 loss: 0.0390 (0.0434) time: 3.6168 data: 0.0030 max mem: 19788 +Epoch: [11] [ 930/2138] eta: 1:12:57 lr: 3.692841005356259e-05 loss: 0.0391 (0.0435) time: 3.6132 data: 0.0030 max mem: 19788 +Epoch: [11] [ 940/2138] eta: 1:12:21 lr: 3.6922967889332345e-05 loss: 0.0477 (0.0435) time: 3.6180 data: 0.0032 max mem: 19788 +Epoch: [11] [ 950/2138] eta: 1:11:44 lr: 3.691752563597468e-05 loss: 0.0429 (0.0435) time: 3.6285 data: 0.0031 max mem: 19788 +Epoch: [11] [ 960/2138] eta: 1:11:08 lr: 3.6912083293473554e-05 loss: 0.0429 (0.0436) time: 3.6297 data: 0.0033 max mem: 19788 +Epoch: [11] [ 970/2138] eta: 1:10:32 lr: 3.69066408618129e-05 loss: 0.0413 (0.0435) time: 3.6323 data: 0.0034 max mem: 19788 +Epoch: [11] [ 980/2138] eta: 1:09:56 lr: 3.6901198340976636e-05 loss: 0.0366 (0.0434) time: 3.6317 data: 0.0032 max mem: 19788 +Epoch: [11] [ 990/2138] eta: 1:09:20 lr: 3.689575573094869e-05 loss: 0.0365 (0.0434) time: 3.6196 data: 0.0028 max mem: 19788 +Epoch: [11] [1000/2138] eta: 1:08:43 lr: 3.689031303171299e-05 loss: 0.0406 (0.0434) time: 3.6116 data: 0.0028 max mem: 19788 +Epoch: [11] [1010/2138] eta: 1:08:07 lr: 3.6884870243253444e-05 loss: 0.0431 (0.0435) time: 3.6197 data: 0.0031 max mem: 19788 +Epoch: [11] [1020/2138] eta: 1:07:31 lr: 3.687942736555396e-05 loss: 0.0420 (0.0434) time: 3.6199 data: 0.0030 max mem: 19788 +Epoch: [11] [1030/2138] eta: 1:06:55 lr: 3.6873984398598434e-05 loss: 0.0401 (0.0434) time: 3.6291 data: 0.0029 max mem: 19788 +Epoch: [11] [1040/2138] eta: 1:06:18 lr: 3.6868541342370765e-05 loss: 0.0418 (0.0434) time: 3.6322 data: 0.0030 max mem: 19788 +Epoch: [11] [1050/2138] eta: 1:05:42 lr: 3.686309819685486e-05 loss: 0.0388 (0.0434) time: 3.6165 data: 0.0030 max mem: 19788 +Epoch: [11] [1060/2138] eta: 1:05:06 lr: 3.685765496203459e-05 loss: 0.0392 (0.0434) time: 3.6184 data: 0.0028 max mem: 19788 +Epoch: [11] [1070/2138] eta: 1:04:30 lr: 3.685221163789383e-05 loss: 0.0413 (0.0434) time: 3.6238 data: 0.0027 max mem: 19788 +Epoch: [11] [1080/2138] eta: 1:03:53 lr: 3.684676822441646e-05 loss: 0.0388 (0.0434) time: 3.6248 data: 0.0027 max mem: 19788 +Epoch: [11] [1090/2138] eta: 1:03:17 lr: 3.684132472158636e-05 loss: 0.0389 (0.0433) time: 3.6309 data: 0.0027 max mem: 19788 +Epoch: [11] [1100/2138] eta: 1:02:41 lr: 3.6835881129387385e-05 loss: 0.0405 (0.0434) time: 3.6275 data: 0.0027 max mem: 19788 +Epoch: [11] [1110/2138] eta: 1:02:05 lr: 3.683043744780339e-05 loss: 0.0391 (0.0434) time: 3.6150 data: 0.0029 max mem: 19788 +Epoch: [11] [1120/2138] eta: 1:01:28 lr: 3.682499367681823e-05 loss: 0.0391 (0.0435) time: 3.6175 data: 0.0029 max mem: 19788 +Epoch: [11] [1130/2138] eta: 1:00:52 lr: 3.681954981641575e-05 loss: 0.0396 (0.0434) time: 3.6179 data: 0.0028 max mem: 19788 +Epoch: [11] [1140/2138] eta: 1:00:16 lr: 3.681410586657981e-05 loss: 0.0396 (0.0435) time: 3.6150 data: 0.0028 max mem: 19788 +Epoch: [11] [1150/2138] eta: 0:59:39 lr: 3.680866182729421e-05 loss: 0.0377 (0.0435) time: 3.6150 data: 0.0029 max mem: 19788 +Epoch: [11] [1160/2138] eta: 0:59:03 lr: 3.6803217698542807e-05 loss: 0.0377 (0.0435) time: 3.6264 data: 0.0028 max mem: 19788 +Epoch: [11] [1170/2138] eta: 0:58:27 lr: 3.6797773480309424e-05 loss: 0.0428 (0.0435) time: 3.6334 data: 0.0027 max mem: 19788 +Epoch: [11] [1180/2138] eta: 0:57:51 lr: 3.679232917257786e-05 loss: 0.0437 (0.0435) time: 3.6219 data: 0.0028 max mem: 19788 +Epoch: [11] [1190/2138] eta: 0:57:15 lr: 3.678688477533195e-05 loss: 0.0342 (0.0434) time: 3.6211 data: 0.0031 max mem: 19788 +Epoch: [11] [1200/2138] eta: 0:56:38 lr: 3.678144028855549e-05 loss: 0.0386 (0.0434) time: 3.6259 data: 0.0031 max mem: 19788 +Epoch: [11] [1210/2138] eta: 0:56:02 lr: 3.677599571223229e-05 loss: 0.0405 (0.0434) time: 3.6201 data: 0.0031 max mem: 19788 +Epoch: [11] [1220/2138] eta: 0:55:26 lr: 3.677055104634614e-05 loss: 0.0396 (0.0436) time: 3.6211 data: 0.0031 max mem: 19788 +Epoch: [11] [1230/2138] eta: 0:54:50 lr: 3.676510629088083e-05 loss: 0.0353 (0.0435) time: 3.6229 data: 0.0029 max mem: 19788 +Epoch: [11] [1240/2138] eta: 0:54:13 lr: 3.675966144582016e-05 loss: 0.0353 (0.0435) time: 3.6255 data: 0.0029 max mem: 19788 +Epoch: [11] [1250/2138] eta: 0:53:37 lr: 3.675421651114789e-05 loss: 0.0412 (0.0436) time: 3.6210 data: 0.0030 max mem: 19788 +Epoch: [11] [1260/2138] eta: 0:53:01 lr: 3.674877148684781e-05 loss: 0.0450 (0.0436) time: 3.6135 data: 0.0029 max mem: 19788 +Epoch: [11] [1270/2138] eta: 0:52:25 lr: 3.6743326372903675e-05 loss: 0.0347 (0.0435) time: 3.6181 data: 0.0029 max mem: 19788 +Epoch: [11] [1280/2138] eta: 0:51:48 lr: 3.673788116929926e-05 loss: 0.0353 (0.0435) time: 3.6153 data: 0.0029 max mem: 19788 +Epoch: [11] [1290/2138] eta: 0:51:12 lr: 3.673243587601831e-05 loss: 0.0394 (0.0436) time: 3.6130 data: 0.0027 max mem: 19788 +Epoch: [11] [1300/2138] eta: 0:50:36 lr: 3.6726990493044585e-05 loss: 0.0384 (0.0435) time: 3.6170 data: 0.0029 max mem: 19788 +Epoch: [11] [1310/2138] eta: 0:50:00 lr: 3.672154502036183e-05 loss: 0.0383 (0.0435) time: 3.6305 data: 0.0028 max mem: 19788 +Epoch: [11] [1320/2138] eta: 0:49:23 lr: 3.6716099457953794e-05 loss: 0.0441 (0.0435) time: 3.6334 data: 0.0027 max mem: 19788 +Epoch: [11] [1330/2138] eta: 0:48:47 lr: 3.671065380580419e-05 loss: 0.0384 (0.0435) time: 3.6195 data: 0.0029 max mem: 19788 +Epoch: [11] [1340/2138] eta: 0:48:11 lr: 3.670520806389677e-05 loss: 0.0370 (0.0435) time: 3.6255 data: 0.0028 max mem: 19788 +Epoch: [11] [1350/2138] eta: 0:47:35 lr: 3.669976223221524e-05 loss: 0.0496 (0.0435) time: 3.6288 data: 0.0029 max mem: 19788 +Epoch: [11] [1360/2138] eta: 0:47:06 lr: 3.669431631074333e-05 loss: 0.0437 (0.0435) time: 4.2490 data: 0.0029 max mem: 19788 +Epoch: [11] [1370/2138] eta: 0:46:31 lr: 3.668887029946475e-05 loss: 0.0351 (0.0435) time: 4.3674 data: 0.0029 max mem: 19788 +Epoch: [11] [1380/2138] eta: 0:45:54 lr: 3.6683424198363204e-05 loss: 0.0351 (0.0435) time: 3.7324 data: 0.0030 max mem: 19788 +Epoch: [11] [1390/2138] eta: 0:45:18 lr: 3.6677978007422384e-05 loss: 0.0461 (0.0435) time: 3.6129 data: 0.0030 max mem: 19788 +Epoch: [11] [1400/2138] eta: 0:44:42 lr: 3.667253172662601e-05 loss: 0.0421 (0.0435) time: 3.6942 data: 0.0029 max mem: 19788 +Epoch: [11] [1410/2138] eta: 0:44:06 lr: 3.666708535595775e-05 loss: 0.0352 (0.0435) time: 3.7695 data: 0.0027 max mem: 19788 +Epoch: [11] [1420/2138] eta: 0:43:31 lr: 3.666163889540129e-05 loss: 0.0352 (0.0434) time: 3.7560 data: 0.0028 max mem: 19788 +Epoch: [11] [1430/2138] eta: 0:42:54 lr: 3.665619234494032e-05 loss: 0.0392 (0.0434) time: 3.7205 data: 0.0030 max mem: 19788 +Epoch: [11] [1440/2138] eta: 0:42:18 lr: 3.6650745704558496e-05 loss: 0.0392 (0.0434) time: 3.6953 data: 0.0031 max mem: 19788 +Epoch: [11] [1450/2138] eta: 0:41:43 lr: 3.664529897423951e-05 loss: 0.0405 (0.0434) time: 3.7840 data: 0.0030 max mem: 19788 +Epoch: [11] [1460/2138] eta: 0:41:08 lr: 3.6639852153967e-05 loss: 0.0419 (0.0434) time: 3.8526 data: 0.0030 max mem: 19788 +Epoch: [11] [1470/2138] eta: 0:40:31 lr: 3.6634405243724626e-05 loss: 0.0432 (0.0434) time: 3.7219 data: 0.0028 max mem: 19788 +Epoch: [11] [1480/2138] eta: 0:39:55 lr: 3.6628958243496056e-05 loss: 0.0422 (0.0434) time: 3.6154 data: 0.0027 max mem: 19788 +Epoch: [11] [1490/2138] eta: 0:39:18 lr: 3.662351115326491e-05 loss: 0.0425 (0.0435) time: 3.6193 data: 0.0028 max mem: 19788 +Epoch: [11] [1500/2138] eta: 0:38:42 lr: 3.6618063973014834e-05 loss: 0.0396 (0.0435) time: 3.6317 data: 0.0028 max mem: 19788 +Epoch: [11] [1510/2138] eta: 0:38:05 lr: 3.6612616702729466e-05 loss: 0.0436 (0.0435) time: 3.6273 data: 0.0029 max mem: 19788 +Epoch: [11] [1520/2138] eta: 0:37:29 lr: 3.660716934239244e-05 loss: 0.0400 (0.0435) time: 3.6104 data: 0.0031 max mem: 19788 +Epoch: [11] [1530/2138] eta: 0:36:52 lr: 3.660172189198736e-05 loss: 0.0335 (0.0434) time: 3.6110 data: 0.0029 max mem: 19788 +Epoch: [11] [1540/2138] eta: 0:36:16 lr: 3.659627435149785e-05 loss: 0.0332 (0.0434) time: 3.6161 data: 0.0029 max mem: 19788 +Epoch: [11] [1550/2138] eta: 0:35:39 lr: 3.659082672090754e-05 loss: 0.0391 (0.0434) time: 3.6211 data: 0.0028 max mem: 19788 +Epoch: [11] [1560/2138] eta: 0:35:03 lr: 3.65853790002e-05 loss: 0.0400 (0.0434) time: 3.6203 data: 0.0027 max mem: 19788 +Epoch: [11] [1570/2138] eta: 0:34:26 lr: 3.6579931189358854e-05 loss: 0.0449 (0.0435) time: 3.6150 data: 0.0028 max mem: 19788 +Epoch: [11] [1580/2138] eta: 0:33:50 lr: 3.657448328836768e-05 loss: 0.0395 (0.0434) time: 3.6132 data: 0.0029 max mem: 19788 +Epoch: [11] [1590/2138] eta: 0:33:13 lr: 3.6569035297210076e-05 loss: 0.0399 (0.0434) time: 3.6135 data: 0.0030 max mem: 19788 +Epoch: [11] [1600/2138] eta: 0:32:37 lr: 3.656358721586962e-05 loss: 0.0427 (0.0435) time: 3.6197 data: 0.0031 max mem: 19788 +Epoch: [11] [1610/2138] eta: 0:32:00 lr: 3.655813904432989e-05 loss: 0.0392 (0.0434) time: 3.6228 data: 0.0031 max mem: 19788 +Epoch: [11] [1620/2138] eta: 0:31:24 lr: 3.6552690782574444e-05 loss: 0.0343 (0.0434) time: 3.6179 data: 0.0033 max mem: 19788 +Epoch: [11] [1630/2138] eta: 0:30:48 lr: 3.6547242430586864e-05 loss: 0.0387 (0.0434) time: 3.6166 data: 0.0034 max mem: 19788 +Epoch: [11] [1640/2138] eta: 0:30:11 lr: 3.654179398835071e-05 loss: 0.0393 (0.0434) time: 3.6554 data: 0.0033 max mem: 19788 +Epoch: [11] [1650/2138] eta: 0:29:37 lr: 3.653634545584951e-05 loss: 0.0346 (0.0433) time: 3.9336 data: 0.0031 max mem: 19788 +Epoch: [11] [1660/2138] eta: 0:29:01 lr: 3.653089683306684e-05 loss: 0.0338 (0.0433) time: 4.0132 data: 0.0031 max mem: 19788 +Epoch: [11] [1670/2138] eta: 0:28:26 lr: 3.6525448119986234e-05 loss: 0.0353 (0.0433) time: 4.0899 data: 0.0033 max mem: 19788 +Epoch: [11] [1680/2138] eta: 0:27:50 lr: 3.651999931659122e-05 loss: 0.0372 (0.0433) time: 4.0534 data: 0.0032 max mem: 19788 +Epoch: [11] [1690/2138] eta: 0:27:15 lr: 3.6514550422865337e-05 loss: 0.0401 (0.0433) time: 4.0164 data: 0.0029 max mem: 19788 +Epoch: [11] [1700/2138] eta: 0:26:40 lr: 3.650910143879209e-05 loss: 0.0368 (0.0433) time: 4.2491 data: 0.0028 max mem: 19788 +Epoch: [11] [1710/2138] eta: 0:26:06 lr: 3.6503652364355033e-05 loss: 0.0349 (0.0433) time: 4.3200 data: 0.0029 max mem: 19788 +Epoch: [11] [1720/2138] eta: 0:25:30 lr: 3.649820319953765e-05 loss: 0.0369 (0.0433) time: 4.2793 data: 0.0029 max mem: 19788 +Epoch: [11] [1730/2138] eta: 0:24:54 lr: 3.649275394432346e-05 loss: 0.0401 (0.0433) time: 4.0530 data: 0.0030 max mem: 19788 +Epoch: [11] [1740/2138] eta: 0:24:18 lr: 3.648730459869596e-05 loss: 0.0364 (0.0432) time: 3.9339 data: 0.0030 max mem: 19788 +Epoch: [11] [1750/2138] eta: 0:23:42 lr: 3.648185516263866e-05 loss: 0.0389 (0.0432) time: 3.9278 data: 0.0028 max mem: 19788 +Epoch: [11] [1760/2138] eta: 0:23:06 lr: 3.647640563613503e-05 loss: 0.0403 (0.0432) time: 3.9428 data: 0.0028 max mem: 19788 +Epoch: [11] [1770/2138] eta: 0:22:30 lr: 3.6470956019168555e-05 loss: 0.0391 (0.0432) time: 3.9847 data: 0.0028 max mem: 19788 +Epoch: [11] [1780/2138] eta: 0:21:53 lr: 3.6465506311722736e-05 loss: 0.0411 (0.0432) time: 3.8176 data: 0.0029 max mem: 19788 +Epoch: [11] [1790/2138] eta: 0:21:17 lr: 3.646005651378103e-05 loss: 0.0411 (0.0433) time: 3.6250 data: 0.0030 max mem: 19788 +Epoch: [11] [1800/2138] eta: 0:20:40 lr: 3.645460662532689e-05 loss: 0.0395 (0.0433) time: 3.6283 data: 0.0030 max mem: 19788 +Epoch: [11] [1810/2138] eta: 0:20:03 lr: 3.64491566463438e-05 loss: 0.0381 (0.0433) time: 3.6230 data: 0.0031 max mem: 19788 +Epoch: [11] [1820/2138] eta: 0:19:26 lr: 3.6443706576815215e-05 loss: 0.0380 (0.0433) time: 3.6186 data: 0.0030 max mem: 19788 +Epoch: [11] [1830/2138] eta: 0:18:49 lr: 3.643825641672458e-05 loss: 0.0376 (0.0433) time: 3.6172 data: 0.0029 max mem: 19788 +Epoch: [11] [1840/2138] eta: 0:18:13 lr: 3.643280616605533e-05 loss: 0.0375 (0.0433) time: 3.6236 data: 0.0028 max mem: 19788 +Epoch: [11] [1850/2138] eta: 0:17:36 lr: 3.642735582479091e-05 loss: 0.0404 (0.0433) time: 3.6285 data: 0.0029 max mem: 19788 +Epoch: [11] [1860/2138] eta: 0:16:59 lr: 3.6421905392914764e-05 loss: 0.0460 (0.0435) time: 3.6217 data: 0.0030 max mem: 19788 +Epoch: [11] [1870/2138] eta: 0:16:22 lr: 3.64164548704103e-05 loss: 0.0495 (0.0435) time: 3.6226 data: 0.0028 max mem: 19788 +Epoch: [11] [1880/2138] eta: 0:15:46 lr: 3.641100425726095e-05 loss: 0.0428 (0.0435) time: 3.6221 data: 0.0029 max mem: 19788 +Epoch: [11] [1890/2138] eta: 0:15:09 lr: 3.640555355345011e-05 loss: 0.0421 (0.0435) time: 3.6277 data: 0.0033 max mem: 19788 +Epoch: [11] [1900/2138] eta: 0:14:32 lr: 3.6400102758961215e-05 loss: 0.0321 (0.0434) time: 3.6802 data: 0.0033 max mem: 19788 +Epoch: [11] [1910/2138] eta: 0:13:56 lr: 3.639465187377767e-05 loss: 0.0355 (0.0435) time: 3.6706 data: 0.0032 max mem: 19788 +Epoch: [11] [1920/2138] eta: 0:13:19 lr: 3.638920089788285e-05 loss: 0.0458 (0.0436) time: 3.8169 data: 0.0030 max mem: 19788 +Epoch: [11] [1930/2138] eta: 0:12:43 lr: 3.638374983126015e-05 loss: 0.0417 (0.0436) time: 3.9794 data: 0.0030 max mem: 19788 +Epoch: [11] [1940/2138] eta: 0:12:07 lr: 3.6378298673892974e-05 loss: 0.0364 (0.0435) time: 4.0220 data: 0.0031 max mem: 19788 +Epoch: [11] [1950/2138] eta: 0:11:30 lr: 3.6372847425764696e-05 loss: 0.0376 (0.0435) time: 4.1113 data: 0.0031 max mem: 19788 +Epoch: [11] [1960/2138] eta: 0:10:54 lr: 3.636739608685868e-05 loss: 0.0364 (0.0435) time: 3.8838 data: 0.0030 max mem: 19788 +Epoch: [11] [1970/2138] eta: 0:10:17 lr: 3.6361944657158297e-05 loss: 0.0358 (0.0435) time: 3.6341 data: 0.0029 max mem: 19788 +Epoch: [11] [1980/2138] eta: 0:09:40 lr: 3.6356493136646924e-05 loss: 0.0346 (0.0434) time: 3.6218 data: 0.0030 max mem: 19788 +Epoch: [11] [1990/2138] eta: 0:09:03 lr: 3.63510415253079e-05 loss: 0.0349 (0.0435) time: 3.6161 data: 0.0030 max mem: 19788 +Epoch: [11] [2000/2138] eta: 0:08:26 lr: 3.634558982312459e-05 loss: 0.0390 (0.0434) time: 3.6151 data: 0.0030 max mem: 19788 +Epoch: [11] [2010/2138] eta: 0:07:50 lr: 3.6340138030080334e-05 loss: 0.0415 (0.0434) time: 3.9689 data: 0.0029 max mem: 19788 +Epoch: [11] [2020/2138] eta: 0:07:14 lr: 3.633468614615847e-05 loss: 0.0407 (0.0434) time: 4.1231 data: 0.0028 max mem: 19788 +Epoch: [11] [2030/2138] eta: 0:06:37 lr: 3.6329234171342335e-05 loss: 0.0390 (0.0434) time: 3.8493 data: 0.0028 max mem: 19788 +Epoch: [11] [2040/2138] eta: 0:06:00 lr: 3.632378210561525e-05 loss: 0.0380 (0.0434) time: 3.7343 data: 0.0027 max mem: 19788 +Epoch: [11] [2050/2138] eta: 0:05:23 lr: 3.631832994896054e-05 loss: 0.0410 (0.0434) time: 3.7742 data: 0.0028 max mem: 19788 +Epoch: [11] [2060/2138] eta: 0:04:46 lr: 3.631287770136153e-05 loss: 0.0488 (0.0435) time: 3.7315 data: 0.0031 max mem: 19788 +Epoch: [11] [2070/2138] eta: 0:04:10 lr: 3.6307425362801524e-05 loss: 0.0460 (0.0435) time: 3.8613 data: 0.0029 max mem: 19788 +Epoch: [11] [2080/2138] eta: 0:03:33 lr: 3.630197293326382e-05 loss: 0.0390 (0.0435) time: 4.2577 data: 0.0028 max mem: 19788 +Epoch: [11] [2090/2138] eta: 0:02:56 lr: 3.629652041273172e-05 loss: 0.0390 (0.0435) time: 4.2148 data: 0.0028 max mem: 19788 +Epoch: [11] [2100/2138] eta: 0:02:20 lr: 3.629106780118853e-05 loss: 0.0374 (0.0435) time: 3.8381 data: 0.0029 max mem: 19788 +Epoch: [11] [2110/2138] eta: 0:01:43 lr: 3.6285615098617517e-05 loss: 0.0401 (0.0435) time: 3.7568 data: 0.0031 max mem: 19788 +Epoch: [11] [2120/2138] eta: 0:01:06 lr: 3.628016230500197e-05 loss: 0.0533 (0.0436) time: 3.9347 data: 0.0034 max mem: 19788 +Epoch: [11] [2130/2138] eta: 0:00:29 lr: 3.627470942032517e-05 loss: 0.0492 (0.0437) time: 3.9091 data: 0.0032 max mem: 19788 +Epoch: [11] Total time: 2:11:31 +Test: [ 0/21770] eta: 12:28:51 time: 2.0639 data: 1.8506 max mem: 19788 +Test: [ 100/21770] eta: 0:37:28 time: 0.0672 data: 0.0019 max mem: 19788 +Test: [ 200/21770] eta: 0:31:31 time: 0.0745 data: 0.0019 max mem: 19788 +Test: [ 300/21770] eta: 0:29:52 time: 0.0801 data: 0.0022 max mem: 19788 +Test: [ 400/21770] eta: 0:28:39 time: 0.0685 data: 0.0020 max mem: 19788 +Test: [ 500/21770] eta: 0:27:14 time: 0.0597 data: 0.0018 max mem: 19788 +Test: [ 600/21770] eta: 0:27:06 time: 0.0802 data: 0.0023 max mem: 19788 +Test: [ 700/21770] eta: 0:27:09 time: 0.0804 data: 0.0022 max mem: 19788 +Test: [ 800/21770] eta: 0:27:08 time: 0.0805 data: 0.0023 max mem: 19788 +Test: [ 900/21770] eta: 0:27:07 time: 0.0801 data: 0.0022 max mem: 19788 +Test: [ 1000/21770] eta: 0:27:04 time: 0.0804 data: 0.0022 max mem: 19788 +Test: [ 1100/21770] eta: 0:26:42 time: 0.0630 data: 0.0019 max mem: 19788 +Test: [ 1200/21770] eta: 0:26:26 time: 0.0821 data: 0.0024 max mem: 19788 +Test: [ 1300/21770] eta: 0:26:16 time: 0.0601 data: 0.0018 max mem: 19788 +Test: [ 1400/21770] eta: 0:26:03 time: 0.0731 data: 0.0020 max mem: 19788 +Test: [ 1500/21770] eta: 0:25:39 time: 0.0749 data: 0.0022 max mem: 19788 +Test: [ 1600/21770] eta: 0:25:29 time: 0.0762 data: 0.0019 max mem: 19788 +Test: [ 1700/21770] eta: 0:25:14 time: 0.0633 data: 0.0019 max mem: 19788 +Test: [ 1800/21770] eta: 0:24:54 time: 0.0730 data: 0.0022 max mem: 19788 +Test: [ 1900/21770] eta: 0:24:38 time: 0.0608 data: 0.0018 max mem: 19788 +Test: [ 2000/21770] eta: 0:24:19 time: 0.0610 data: 0.0016 max mem: 19788 +Test: [ 2100/21770] eta: 0:24:02 time: 0.0672 data: 0.0018 max mem: 19788 +Test: [ 2200/21770] eta: 0:23:49 time: 0.0594 data: 0.0018 max mem: 19788 +Test: [ 2300/21770] eta: 0:23:35 time: 0.0798 data: 0.0023 max mem: 19788 +Test: [ 2400/21770] eta: 0:23:28 time: 0.0652 data: 0.0020 max mem: 19788 +Test: [ 2500/21770] eta: 0:23:18 time: 0.0683 data: 0.0019 max mem: 19788 +Test: [ 2600/21770] eta: 0:23:04 time: 0.0654 data: 0.0019 max mem: 19788 +Test: [ 2700/21770] eta: 0:22:55 time: 0.0727 data: 0.0023 max mem: 19788 +Test: [ 2800/21770] eta: 0:22:43 time: 0.0643 data: 0.0019 max mem: 19788 +Test: [ 2900/21770] eta: 0:22:32 time: 0.0626 data: 0.0018 max mem: 19788 +Test: [ 3000/21770] eta: 0:22:23 time: 0.0637 data: 0.0018 max mem: 19788 +Test: [ 3100/21770] eta: 0:22:14 time: 0.0680 data: 0.0020 max mem: 19788 +Test: [ 3200/21770] eta: 0:22:03 time: 0.0689 data: 0.0021 max mem: 19788 +Test: [ 3300/21770] eta: 0:21:56 time: 0.0756 data: 0.0021 max mem: 19788 +Test: [ 3400/21770] eta: 0:21:47 time: 0.0616 data: 0.0018 max mem: 19788 +Test: [ 3500/21770] eta: 0:21:41 time: 0.0621 data: 0.0018 max mem: 19788 +Test: [ 3600/21770] eta: 0:21:33 time: 0.0673 data: 0.0019 max mem: 19788 +Test: [ 3700/21770] eta: 0:21:28 time: 0.0737 data: 0.0021 max mem: 19788 +Test: [ 3800/21770] eta: 0:21:25 time: 0.0769 data: 0.0023 max mem: 19788 +Test: [ 3900/21770] eta: 0:21:15 time: 0.0721 data: 0.0021 max mem: 19788 +Test: [ 4000/21770] eta: 0:21:06 time: 0.0720 data: 0.0020 max mem: 19788 +Test: [ 4100/21770] eta: 0:20:59 time: 0.0613 data: 0.0016 max mem: 19788 +Test: [ 4200/21770] eta: 0:20:51 time: 0.0662 data: 0.0019 max mem: 19788 +Test: [ 4300/21770] eta: 0:20:44 time: 0.0741 data: 0.0024 max mem: 19788 +Test: [ 4400/21770] eta: 0:20:35 time: 0.0672 data: 0.0019 max mem: 19788 +Test: [ 4500/21770] eta: 0:20:26 time: 0.0695 data: 0.0018 max mem: 19788 +Test: [ 4600/21770] eta: 0:20:18 time: 0.0617 data: 0.0019 max mem: 19788 +Test: [ 4700/21770] eta: 0:20:09 time: 0.0659 data: 0.0019 max mem: 19788 +Test: [ 4800/21770] eta: 0:20:02 time: 0.0802 data: 0.0020 max mem: 19788 +Test: [ 4900/21770] eta: 0:19:53 time: 0.0643 data: 0.0019 max mem: 19788 +Test: [ 5000/21770] eta: 0:19:45 time: 0.0619 data: 0.0018 max mem: 19788 +Test: [ 5100/21770] eta: 0:19:37 time: 0.0811 data: 0.0024 max mem: 19788 +Test: [ 5200/21770] eta: 0:19:29 time: 0.0619 data: 0.0017 max mem: 19788 +Test: [ 5300/21770] eta: 0:19:21 time: 0.0769 data: 0.0023 max mem: 19788 +Test: [ 5400/21770] eta: 0:19:15 time: 0.0826 data: 0.0020 max mem: 19788 +Test: [ 5500/21770] eta: 0:19:06 time: 0.0619 data: 0.0019 max mem: 19788 +Test: [ 5600/21770] eta: 0:18:59 time: 0.0634 data: 0.0018 max mem: 19788 +Test: [ 5700/21770] eta: 0:18:52 time: 0.0627 data: 0.0017 max mem: 19788 +Test: [ 5800/21770] eta: 0:18:45 time: 0.0764 data: 0.0021 max mem: 19788 +Test: [ 5900/21770] eta: 0:18:39 time: 0.0774 data: 0.0025 max mem: 19788 +Test: [ 6000/21770] eta: 0:18:30 time: 0.0627 data: 0.0017 max mem: 19788 +Test: [ 6100/21770] eta: 0:18:22 time: 0.0616 data: 0.0019 max mem: 19788 +Test: [ 6200/21770] eta: 0:18:12 time: 0.0653 data: 0.0020 max mem: 19788 +Test: [ 6300/21770] eta: 0:18:04 time: 0.0625 data: 0.0017 max mem: 19788 +Test: [ 6400/21770] eta: 0:17:56 time: 0.0683 data: 0.0020 max mem: 19788 +Test: [ 6500/21770] eta: 0:17:49 time: 0.0647 data: 0.0019 max mem: 19788 +Test: [ 6600/21770] eta: 0:17:40 time: 0.0634 data: 0.0020 max mem: 19788 +Test: [ 6700/21770] eta: 0:17:32 time: 0.0630 data: 0.0018 max mem: 19788 +Test: [ 6800/21770] eta: 0:17:23 time: 0.0643 data: 0.0018 max mem: 19788 +Test: [ 6900/21770] eta: 0:17:16 time: 0.0593 data: 0.0019 max mem: 19788 +Test: [ 7000/21770] eta: 0:17:07 time: 0.0640 data: 0.0016 max mem: 19788 +Test: [ 7100/21770] eta: 0:17:00 time: 0.0627 data: 0.0018 max mem: 19788 +Test: [ 7200/21770] eta: 0:16:53 time: 0.0733 data: 0.0021 max mem: 19788 +Test: [ 7300/21770] eta: 0:16:46 time: 0.0620 data: 0.0019 max mem: 19788 +Test: [ 7400/21770] eta: 0:16:37 time: 0.0619 data: 0.0017 max mem: 19788 +Test: [ 7500/21770] eta: 0:16:29 time: 0.0651 data: 0.0019 max mem: 19788 +Test: [ 7600/21770] eta: 0:16:21 time: 0.0613 data: 0.0019 max mem: 19788 +Test: [ 7700/21770] eta: 0:16:13 time: 0.0612 data: 0.0017 max mem: 19788 +Test: [ 7800/21770] eta: 0:16:06 time: 0.0753 data: 0.0023 max mem: 19788 +Test: [ 7900/21770] eta: 0:15:59 time: 0.0643 data: 0.0019 max mem: 19788 +Test: [ 8000/21770] eta: 0:15:52 time: 0.0742 data: 0.0020 max mem: 19788 +Test: [ 8100/21770] eta: 0:15:45 time: 0.0633 data: 0.0021 max mem: 19788 +Test: [ 8200/21770] eta: 0:15:38 time: 0.0708 data: 0.0021 max mem: 19788 +Test: [ 8300/21770] eta: 0:15:30 time: 0.0632 data: 0.0025 max mem: 19788 +Test: [ 8400/21770] eta: 0:15:23 time: 0.0731 data: 0.0021 max mem: 19788 +Test: [ 8500/21770] eta: 0:15:17 time: 0.0654 data: 0.0019 max mem: 19788 +Test: [ 8600/21770] eta: 0:15:09 time: 0.0636 data: 0.0018 max mem: 19788 +Test: [ 8700/21770] eta: 0:15:02 time: 0.0619 data: 0.0018 max mem: 19788 +Test: [ 8800/21770] eta: 0:14:55 time: 0.0687 data: 0.0020 max mem: 19788 +Test: [ 8900/21770] eta: 0:14:48 time: 0.0621 data: 0.0018 max mem: 19788 +Test: [ 9000/21770] eta: 0:14:40 time: 0.0636 data: 0.0019 max mem: 19788 +Test: [ 9100/21770] eta: 0:14:33 time: 0.0602 data: 0.0019 max mem: 19788 +Test: [ 9200/21770] eta: 0:14:25 time: 0.0670 data: 0.0018 max mem: 19788 +Test: [ 9300/21770] eta: 0:14:19 time: 0.0684 data: 0.0022 max mem: 19788 +Test: [ 9400/21770] eta: 0:14:12 time: 0.0751 data: 0.0020 max mem: 19788 +Test: [ 9500/21770] eta: 0:14:05 time: 0.0718 data: 0.0022 max mem: 19788 +Test: [ 9600/21770] eta: 0:13:58 time: 0.0649 data: 0.0018 max mem: 19788 +Test: [ 9700/21770] eta: 0:13:51 time: 0.0637 data: 0.0019 max mem: 19788 +Test: [ 9800/21770] eta: 0:13:44 time: 0.0674 data: 0.0020 max mem: 19788 +Test: [ 9900/21770] eta: 0:13:37 time: 0.0733 data: 0.0024 max mem: 19788 +Test: [10000/21770] eta: 0:13:30 time: 0.0783 data: 0.0021 max mem: 19788 +Test: [10100/21770] eta: 0:13:24 time: 0.0786 data: 0.0022 max mem: 19788 +Test: [10200/21770] eta: 0:13:18 time: 0.0801 data: 0.0018 max mem: 19788 +Test: [10300/21770] eta: 0:13:11 time: 0.0685 data: 0.0021 max mem: 19788 +Test: [10400/21770] eta: 0:13:04 time: 0.0746 data: 0.0021 max mem: 19788 +Test: [10500/21770] eta: 0:12:57 time: 0.0663 data: 0.0020 max mem: 19788 +Test: [10600/21770] eta: 0:12:50 time: 0.0644 data: 0.0018 max mem: 19788 +Test: [10700/21770] eta: 0:12:43 time: 0.0697 data: 0.0021 max mem: 19788 +Test: [10800/21770] eta: 0:12:36 time: 0.0648 data: 0.0020 max mem: 19788 +Test: [10900/21770] eta: 0:12:30 time: 0.0813 data: 0.0023 max mem: 19788 +Test: [11000/21770] eta: 0:12:24 time: 0.0785 data: 0.0024 max mem: 19788 +Test: [11100/21770] eta: 0:12:16 time: 0.0666 data: 0.0018 max mem: 19788 +Test: [11200/21770] eta: 0:12:09 time: 0.0670 data: 0.0021 max mem: 19788 +Test: [11300/21770] eta: 0:12:02 time: 0.0701 data: 0.0021 max mem: 19788 +Test: [11400/21770] eta: 0:11:56 time: 0.0676 data: 0.0021 max mem: 19788 +Test: [11500/21770] eta: 0:11:48 time: 0.0616 data: 0.0018 max mem: 19788 +Test: [11600/21770] eta: 0:11:41 time: 0.0759 data: 0.0022 max mem: 19788 +Test: [11700/21770] eta: 0:11:35 time: 0.0676 data: 0.0019 max mem: 19788 +Test: [11800/21770] eta: 0:11:28 time: 0.0632 data: 0.0018 max mem: 19788 +Test: [11900/21770] eta: 0:11:21 time: 0.0659 data: 0.0021 max mem: 19788 +Test: [12000/21770] eta: 0:11:14 time: 0.0793 data: 0.0022 max mem: 19788 +Test: [12100/21770] eta: 0:11:07 time: 0.0791 data: 0.0024 max mem: 19788 +Test: [12200/21770] eta: 0:11:01 time: 0.0701 data: 0.0021 max mem: 19788 +Test: [12300/21770] eta: 0:10:54 time: 0.0641 data: 0.0019 max mem: 19788 +Test: [12400/21770] eta: 0:10:47 time: 0.0758 data: 0.0023 max mem: 19788 +Test: [12500/21770] eta: 0:10:40 time: 0.0644 data: 0.0018 max mem: 19788 +Test: [12600/21770] eta: 0:10:33 time: 0.0641 data: 0.0019 max mem: 19788 +Test: [12700/21770] eta: 0:10:25 time: 0.0609 data: 0.0019 max mem: 19788 +Test: [12800/21770] eta: 0:10:18 time: 0.0615 data: 0.0019 max mem: 19788 +Test: [12900/21770] eta: 0:10:11 time: 0.0642 data: 0.0018 max mem: 19788 +Test: [13000/21770] eta: 0:10:04 time: 0.0691 data: 0.0018 max mem: 19788 +Test: [13100/21770] eta: 0:09:58 time: 0.0775 data: 0.0023 max mem: 19788 +Test: [13200/21770] eta: 0:09:51 time: 0.0693 data: 0.0019 max mem: 19788 +Test: [13300/21770] eta: 0:09:44 time: 0.0619 data: 0.0019 max mem: 19788 +Test: [13400/21770] eta: 0:09:37 time: 0.0671 data: 0.0020 max mem: 19788 +Test: [13500/21770] eta: 0:09:30 time: 0.0739 data: 0.0022 max mem: 19788 +Test: [13600/21770] eta: 0:09:23 time: 0.0625 data: 0.0018 max mem: 19788 +Test: [13700/21770] eta: 0:09:16 time: 0.0643 data: 0.0018 max mem: 19788 +Test: [13800/21770] eta: 0:09:09 time: 0.0735 data: 0.0024 max mem: 19788 +Test: [13900/21770] eta: 0:09:03 time: 0.0603 data: 0.0018 max mem: 19788 +Test: [14000/21770] eta: 0:08:56 time: 0.0650 data: 0.0018 max mem: 19788 +Test: [14100/21770] eta: 0:08:48 time: 0.0669 data: 0.0019 max mem: 19788 +Test: [14200/21770] eta: 0:08:42 time: 0.0623 data: 0.0021 max mem: 19788 +Test: [14300/21770] eta: 0:08:35 time: 0.0666 data: 0.0017 max mem: 19788 +Test: [14400/21770] eta: 0:08:28 time: 0.0676 data: 0.0020 max mem: 19788 +Test: [14500/21770] eta: 0:08:21 time: 0.0628 data: 0.0018 max mem: 19788 +Test: [14600/21770] eta: 0:08:14 time: 0.0637 data: 0.0018 max mem: 19788 +Test: [14700/21770] eta: 0:08:07 time: 0.0688 data: 0.0019 max mem: 19788 +Test: [14800/21770] eta: 0:08:00 time: 0.0608 data: 0.0018 max mem: 19788 +Test: [14900/21770] eta: 0:07:54 time: 0.0779 data: 0.0022 max mem: 19788 +Test: [15000/21770] eta: 0:07:47 time: 0.0811 data: 0.0025 max mem: 19788 +Test: [15100/21770] eta: 0:07:40 time: 0.0630 data: 0.0018 max mem: 19788 +Test: [15200/21770] eta: 0:07:33 time: 0.0609 data: 0.0018 max mem: 19788 +Test: [15300/21770] eta: 0:07:26 time: 0.0619 data: 0.0019 max mem: 19788 +Test: [15400/21770] eta: 0:07:19 time: 0.0734 data: 0.0022 max mem: 19788 +Test: [15500/21770] eta: 0:07:12 time: 0.0645 data: 0.0019 max mem: 19788 +Test: [15600/21770] eta: 0:07:05 time: 0.0599 data: 0.0019 max mem: 19788 +Test: [15700/21770] eta: 0:06:58 time: 0.0654 data: 0.0018 max mem: 19788 +Test: [15800/21770] eta: 0:06:51 time: 0.0821 data: 0.0025 max mem: 19788 +Test: [15900/21770] eta: 0:06:45 time: 0.0830 data: 0.0021 max mem: 19788 +Test: [16000/21770] eta: 0:06:38 time: 0.0682 data: 0.0020 max mem: 19788 +Test: [16100/21770] eta: 0:06:31 time: 0.0804 data: 0.0024 max mem: 19788 +Test: [16200/21770] eta: 0:06:24 time: 0.0698 data: 0.0020 max mem: 19788 +Test: [16300/21770] eta: 0:06:17 time: 0.0764 data: 0.0018 max mem: 19788 +Test: [16400/21770] eta: 0:06:10 time: 0.0729 data: 0.0019 max mem: 19788 +Test: [16500/21770] eta: 0:06:03 time: 0.0729 data: 0.0022 max mem: 19788 +Test: [16600/21770] eta: 0:05:56 time: 0.0672 data: 0.0018 max mem: 19788 +Test: [16700/21770] eta: 0:05:49 time: 0.0655 data: 0.0018 max mem: 19788 +Test: [16800/21770] eta: 0:05:42 time: 0.0622 data: 0.0016 max mem: 19788 +Test: [16900/21770] eta: 0:05:35 time: 0.0645 data: 0.0018 max mem: 19788 +Test: [17000/21770] eta: 0:05:28 time: 0.0650 data: 0.0021 max mem: 19788 +Test: [17100/21770] eta: 0:05:21 time: 0.0640 data: 0.0019 max mem: 19788 +Test: [17200/21770] eta: 0:05:14 time: 0.0683 data: 0.0020 max mem: 19788 +Test: [17300/21770] eta: 0:05:07 time: 0.0618 data: 0.0018 max mem: 19788 +Test: [17400/21770] eta: 0:05:01 time: 0.0825 data: 0.0021 max mem: 19788 +Test: [17500/21770] eta: 0:04:54 time: 0.0802 data: 0.0024 max mem: 19788 +Test: [17600/21770] eta: 0:04:47 time: 0.0714 data: 0.0020 max mem: 19788 +Test: [17700/21770] eta: 0:04:40 time: 0.0621 data: 0.0018 max mem: 19788 +Test: [17800/21770] eta: 0:04:33 time: 0.0618 data: 0.0017 max mem: 19788 +Test: [17900/21770] eta: 0:04:26 time: 0.0616 data: 0.0019 max mem: 19788 +Test: [18000/21770] eta: 0:04:19 time: 0.0637 data: 0.0018 max mem: 19788 +Test: [18100/21770] eta: 0:04:12 time: 0.0620 data: 0.0018 max mem: 19788 +Test: [18200/21770] eta: 0:04:05 time: 0.0629 data: 0.0018 max mem: 19788 +Test: [18300/21770] eta: 0:03:58 time: 0.0700 data: 0.0021 max mem: 19788 +Test: [18400/21770] eta: 0:03:51 time: 0.0676 data: 0.0020 max mem: 19788 +Test: [18500/21770] eta: 0:03:44 time: 0.0623 data: 0.0018 max mem: 19788 +Test: [18600/21770] eta: 0:03:38 time: 0.0783 data: 0.0024 max mem: 19788 +Test: [18700/21770] eta: 0:03:31 time: 0.0808 data: 0.0024 max mem: 19788 +Test: [18800/21770] eta: 0:03:24 time: 0.0809 data: 0.0024 max mem: 19788 +Test: [18900/21770] eta: 0:03:17 time: 0.0814 data: 0.0023 max mem: 19788 +Test: [19000/21770] eta: 0:03:11 time: 0.0607 data: 0.0019 max mem: 19788 +Test: [19100/21770] eta: 0:03:04 time: 0.0793 data: 0.0022 max mem: 19788 +Test: [19200/21770] eta: 0:02:57 time: 0.0839 data: 0.0025 max mem: 19788 +Test: [19300/21770] eta: 0:02:50 time: 0.0806 data: 0.0022 max mem: 19788 +Test: [19400/21770] eta: 0:02:43 time: 0.0812 data: 0.0022 max mem: 19788 +Test: [19500/21770] eta: 0:02:37 time: 0.0814 data: 0.0023 max mem: 19788 +Test: [19600/21770] eta: 0:02:30 time: 0.0806 data: 0.0022 max mem: 19788 +Test: [19700/21770] eta: 0:02:23 time: 0.0806 data: 0.0022 max mem: 19788 +Test: [19800/21770] eta: 0:02:16 time: 0.0813 data: 0.0022 max mem: 19788 +Test: [19900/21770] eta: 0:02:09 time: 0.0811 data: 0.0023 max mem: 19788 +Test: [20000/21770] eta: 0:02:02 time: 0.0806 data: 0.0022 max mem: 19788 +Test: [20100/21770] eta: 0:01:56 time: 0.0809 data: 0.0022 max mem: 19788 +Test: [20200/21770] eta: 0:01:49 time: 0.0812 data: 0.0022 max mem: 19788 +Test: [20300/21770] eta: 0:01:42 time: 0.0807 data: 0.0022 max mem: 19788 +Test: [20400/21770] eta: 0:01:35 time: 0.0807 data: 0.0022 max mem: 19788 +Test: [20500/21770] eta: 0:01:28 time: 0.0780 data: 0.0021 max mem: 19788 +Test: [20600/21770] eta: 0:01:21 time: 0.0764 data: 0.0019 max mem: 19788 +Test: [20700/21770] eta: 0:01:14 time: 0.0786 data: 0.0023 max mem: 19788 +Test: [20800/21770] eta: 0:01:07 time: 0.0720 data: 0.0019 max mem: 19788 +Test: [20900/21770] eta: 0:01:00 time: 0.0647 data: 0.0021 max mem: 19788 +Test: [21000/21770] eta: 0:00:53 time: 0.0630 data: 0.0020 max mem: 19788 +Test: [21100/21770] eta: 0:00:46 time: 0.0632 data: 0.0020 max mem: 19788 +Test: [21200/21770] eta: 0:00:39 time: 0.0615 data: 0.0018 max mem: 19788 +Test: [21300/21770] eta: 0:00:32 time: 0.0694 data: 0.0019 max mem: 19788 +Test: [21400/21770] eta: 0:00:25 time: 0.0634 data: 0.0019 max mem: 19788 +Test: [21500/21770] eta: 0:00:18 time: 0.0731 data: 0.0019 max mem: 19788 +Test: [21600/21770] eta: 0:00:11 time: 0.0783 data: 0.0024 max mem: 19788 +Test: [21700/21770] eta: 0:00:04 time: 0.0625 data: 0.0016 max mem: 19788 +Test: Total time: 0:25:17 +Final results: +Mean IoU is 61.87 + + precision@0.5 = 68.50 + precision@0.6 = 62.90 + precision@0.7 = 55.70 + precision@0.8 = 44.79 + precision@0.9 = 21.61 + overall IoU = 62.83 + mean IoU = 61.87 + +Mean accuracy for one-to-zero sample is 79.80 + +Average object IoU 0.6186511480938738 +Overall IoU 62.826786041259766 +Better epoch: 11 + +Epoch: [12] [ 0/2138] eta: 4:19:47 lr: 3.6270347047008376e-05 loss: 0.0434 (0.0434) time: 7.2905 data: 1.5749 max mem: 19788 +Epoch: [12] [ 10/2138] eta: 2:23:08 lr: 3.626489399837915e-05 loss: 0.0400 (0.0407) time: 4.0361 data: 0.1455 max mem: 19788 +Epoch: [12] [ 20/2138] eta: 2:15:49 lr: 3.6259440858641795e-05 loss: 0.0356 (0.0395) time: 3.6757 data: 0.0023 max mem: 19788 +Epoch: [12] [ 30/2138] eta: 2:12:39 lr: 3.625398762777959e-05 loss: 0.0347 (0.0390) time: 3.6330 data: 0.0026 max mem: 19788 +Epoch: [12] [ 40/2138] eta: 2:13:31 lr: 3.624853430577575e-05 loss: 0.0358 (0.0404) time: 3.7880 data: 0.0030 max mem: 19788 +Epoch: [12] [ 50/2138] eta: 2:11:33 lr: 3.624308089261354e-05 loss: 0.0374 (0.0410) time: 3.7875 data: 0.0027 max mem: 19788 +Epoch: [12] [ 60/2138] eta: 2:12:40 lr: 3.6237627388276184e-05 loss: 0.0332 (0.0398) time: 3.8553 data: 0.0026 max mem: 19788 +Epoch: [12] [ 70/2138] eta: 2:13:17 lr: 3.6232173792746925e-05 loss: 0.0319 (0.0397) time: 4.0888 data: 0.0027 max mem: 19788 +Epoch: [12] [ 80/2138] eta: 2:12:14 lr: 3.622672010600896e-05 loss: 0.0379 (0.0402) time: 3.9314 data: 0.0030 max mem: 19788 +Epoch: [12] [ 90/2138] eta: 2:11:09 lr: 3.622126632804554e-05 loss: 0.0458 (0.0417) time: 3.7535 data: 0.0032 max mem: 19788 +Epoch: [12] [ 100/2138] eta: 2:09:46 lr: 3.6215812458839854e-05 loss: 0.0440 (0.0415) time: 3.6799 data: 0.0031 max mem: 19788 +Epoch: [12] [ 110/2138] eta: 2:08:30 lr: 3.621035849837512e-05 loss: 0.0429 (0.0424) time: 3.6199 data: 0.0031 max mem: 19788 +Epoch: [12] [ 120/2138] eta: 2:07:21 lr: 3.620490444663452e-05 loss: 0.0423 (0.0422) time: 3.6148 data: 0.0029 max mem: 19788 +Epoch: [12] [ 130/2138] eta: 2:06:17 lr: 3.619945030360127e-05 loss: 0.0418 (0.0420) time: 3.6153 data: 0.0028 max mem: 19788 +Epoch: [12] [ 140/2138] eta: 2:05:18 lr: 3.619399606925854e-05 loss: 0.0367 (0.0419) time: 3.6188 data: 0.0027 max mem: 19788 +Epoch: [12] [ 150/2138] eta: 2:04:21 lr: 3.618854174358952e-05 loss: 0.0345 (0.0415) time: 3.6190 data: 0.0030 max mem: 19788 +Epoch: [12] [ 160/2138] eta: 2:03:27 lr: 3.618308732657739e-05 loss: 0.0378 (0.0419) time: 3.6185 data: 0.0029 max mem: 19788 +Epoch: [12] [ 170/2138] eta: 2:02:37 lr: 3.617763281820531e-05 loss: 0.0435 (0.0428) time: 3.6260 data: 0.0029 max mem: 19788 +Epoch: [12] [ 180/2138] eta: 2:01:46 lr: 3.617217821845646e-05 loss: 0.0478 (0.0429) time: 3.6240 data: 0.0032 max mem: 19788 +Epoch: [12] [ 190/2138] eta: 2:00:58 lr: 3.616672352731398e-05 loss: 0.0382 (0.0425) time: 3.6193 data: 0.0033 max mem: 19788 +Epoch: [12] [ 200/2138] eta: 2:00:10 lr: 3.616126874476103e-05 loss: 0.0315 (0.0420) time: 3.6187 data: 0.0033 max mem: 19788 +Epoch: [12] [ 210/2138] eta: 1:59:23 lr: 3.615581387078077e-05 loss: 0.0358 (0.0424) time: 3.6141 data: 0.0032 max mem: 19788 +Epoch: [12] [ 220/2138] eta: 1:58:37 lr: 3.6150358905356326e-05 loss: 0.0427 (0.0421) time: 3.6181 data: 0.0029 max mem: 19788 +Epoch: [12] [ 230/2138] eta: 1:57:53 lr: 3.614490384847083e-05 loss: 0.0347 (0.0422) time: 3.6202 data: 0.0029 max mem: 19788 +Epoch: [12] [ 240/2138] eta: 1:57:09 lr: 3.613944870010741e-05 loss: 0.0380 (0.0421) time: 3.6215 data: 0.0030 max mem: 19788 +Epoch: [12] [ 250/2138] eta: 1:56:26 lr: 3.6133993460249214e-05 loss: 0.0370 (0.0419) time: 3.6227 data: 0.0029 max mem: 19788 +Epoch: [12] [ 260/2138] eta: 1:55:43 lr: 3.612853812887933e-05 loss: 0.0342 (0.0416) time: 3.6198 data: 0.0029 max mem: 19788 +Epoch: [12] [ 270/2138] eta: 1:55:02 lr: 3.6123082705980885e-05 loss: 0.0350 (0.0421) time: 3.6286 data: 0.0029 max mem: 19788 +Epoch: [12] [ 280/2138] eta: 1:54:20 lr: 3.611762719153697e-05 loss: 0.0355 (0.0421) time: 3.6283 data: 0.0027 max mem: 19788 +Epoch: [12] [ 290/2138] eta: 1:53:39 lr: 3.61121715855307e-05 loss: 0.0346 (0.0422) time: 3.6213 data: 0.0028 max mem: 19788 +Epoch: [12] [ 300/2138] eta: 1:52:57 lr: 3.610671588794515e-05 loss: 0.0358 (0.0421) time: 3.6176 data: 0.0029 max mem: 19788 +Epoch: [12] [ 310/2138] eta: 1:52:16 lr: 3.610126009876342e-05 loss: 0.0390 (0.0421) time: 3.6159 data: 0.0031 max mem: 19788 +Epoch: [12] [ 320/2138] eta: 1:51:36 lr: 3.609580421796859e-05 loss: 0.0358 (0.0419) time: 3.6206 data: 0.0031 max mem: 19788 +Epoch: [12] [ 330/2138] eta: 1:50:56 lr: 3.6090348245543745e-05 loss: 0.0369 (0.0419) time: 3.6225 data: 0.0031 max mem: 19788 +Epoch: [12] [ 340/2138] eta: 1:50:15 lr: 3.608489218147193e-05 loss: 0.0389 (0.0418) time: 3.6194 data: 0.0032 max mem: 19788 +Epoch: [12] [ 350/2138] eta: 1:49:35 lr: 3.607943602573623e-05 loss: 0.0391 (0.0418) time: 3.6133 data: 0.0030 max mem: 19788 +Epoch: [12] [ 360/2138] eta: 1:48:55 lr: 3.6073979778319686e-05 loss: 0.0350 (0.0416) time: 3.6146 data: 0.0030 max mem: 19788 +Epoch: [12] [ 370/2138] eta: 1:48:15 lr: 3.6068523439205365e-05 loss: 0.0358 (0.0417) time: 3.6141 data: 0.0029 max mem: 19788 +Epoch: [12] [ 380/2138] eta: 1:47:36 lr: 3.606306700837631e-05 loss: 0.0359 (0.0418) time: 3.6171 data: 0.0029 max mem: 19788 +Epoch: [12] [ 390/2138] eta: 1:46:57 lr: 3.605761048581554e-05 loss: 0.0358 (0.0419) time: 3.6249 data: 0.0029 max mem: 19788 +Epoch: [12] [ 400/2138] eta: 1:46:19 lr: 3.6052153871506106e-05 loss: 0.0387 (0.0418) time: 3.6264 data: 0.0028 max mem: 19788 +Epoch: [12] [ 410/2138] eta: 1:45:40 lr: 3.604669716543104e-05 loss: 0.0417 (0.0420) time: 3.6214 data: 0.0030 max mem: 19788 +Epoch: [12] [ 420/2138] eta: 1:45:01 lr: 3.6041240367573355e-05 loss: 0.0417 (0.0420) time: 3.6190 data: 0.0030 max mem: 19788 +Epoch: [12] [ 430/2138] eta: 1:44:22 lr: 3.603578347791606e-05 loss: 0.0367 (0.0421) time: 3.6174 data: 0.0031 max mem: 19788 +Epoch: [12] [ 440/2138] eta: 1:43:43 lr: 3.603032649644217e-05 loss: 0.0379 (0.0422) time: 3.6105 data: 0.0032 max mem: 19788 +Epoch: [12] [ 450/2138] eta: 1:43:05 lr: 3.60248694231347e-05 loss: 0.0436 (0.0422) time: 3.6162 data: 0.0031 max mem: 19788 +Epoch: [12] [ 460/2138] eta: 1:42:28 lr: 3.601941225797664e-05 loss: 0.0419 (0.0422) time: 3.6330 data: 0.0033 max mem: 19788 +Epoch: [12] [ 470/2138] eta: 1:41:50 lr: 3.601395500095097e-05 loss: 0.0414 (0.0422) time: 3.6339 data: 0.0032 max mem: 19788 +Epoch: [12] [ 480/2138] eta: 1:41:12 lr: 3.600849765204068e-05 loss: 0.0414 (0.0422) time: 3.6245 data: 0.0032 max mem: 19788 +Epoch: [12] [ 490/2138] eta: 1:40:34 lr: 3.6003040211228763e-05 loss: 0.0407 (0.0421) time: 3.6206 data: 0.0031 max mem: 19788 +Epoch: [12] [ 500/2138] eta: 1:39:56 lr: 3.599758267849818e-05 loss: 0.0342 (0.0420) time: 3.6279 data: 0.0029 max mem: 19788 +Epoch: [12] [ 510/2138] eta: 1:39:19 lr: 3.599212505383189e-05 loss: 0.0371 (0.0420) time: 3.6336 data: 0.0029 max mem: 19788 +Epoch: [12] [ 520/2138] eta: 1:38:41 lr: 3.5986667337212885e-05 loss: 0.0378 (0.0420) time: 3.6247 data: 0.0029 max mem: 19788 +Epoch: [12] [ 530/2138] eta: 1:38:03 lr: 3.5981209528624086e-05 loss: 0.0354 (0.0419) time: 3.6213 data: 0.0030 max mem: 19788 +Epoch: [12] [ 540/2138] eta: 1:37:25 lr: 3.597575162804846e-05 loss: 0.0325 (0.0418) time: 3.6163 data: 0.0032 max mem: 19788 +Epoch: [12] [ 550/2138] eta: 1:36:47 lr: 3.597029363546895e-05 loss: 0.0335 (0.0418) time: 3.6141 data: 0.0034 max mem: 19788 +Epoch: [12] [ 560/2138] eta: 1:36:09 lr: 3.596483555086849e-05 loss: 0.0399 (0.0418) time: 3.6153 data: 0.0033 max mem: 19788 +Epoch: [12] [ 570/2138] eta: 1:35:32 lr: 3.595937737423001e-05 loss: 0.0416 (0.0420) time: 3.6197 data: 0.0031 max mem: 19788 +Epoch: [12] [ 580/2138] eta: 1:34:55 lr: 3.595391910553643e-05 loss: 0.0445 (0.0420) time: 3.6291 data: 0.0029 max mem: 19788 +Epoch: [12] [ 590/2138] eta: 1:34:17 lr: 3.5948460744770673e-05 loss: 0.0420 (0.0421) time: 3.6237 data: 0.0028 max mem: 19788 +Epoch: [12] [ 600/2138] eta: 1:33:40 lr: 3.5943002291915665e-05 loss: 0.0445 (0.0422) time: 3.6202 data: 0.0029 max mem: 19788 +Epoch: [12] [ 610/2138] eta: 1:33:03 lr: 3.59375437469543e-05 loss: 0.0430 (0.0422) time: 3.6267 data: 0.0029 max mem: 19788 +Epoch: [12] [ 620/2138] eta: 1:32:25 lr: 3.593208510986947e-05 loss: 0.0394 (0.0423) time: 3.6203 data: 0.0030 max mem: 19788 +Epoch: [12] [ 630/2138] eta: 1:31:48 lr: 3.592662638064409e-05 loss: 0.0377 (0.0423) time: 3.6229 data: 0.0030 max mem: 19788 +Epoch: [12] [ 640/2138] eta: 1:31:11 lr: 3.592116755926104e-05 loss: 0.0348 (0.0422) time: 3.6323 data: 0.0029 max mem: 19788 +Epoch: [12] [ 650/2138] eta: 1:30:34 lr: 3.59157086457032e-05 loss: 0.0354 (0.0422) time: 3.6205 data: 0.0030 max mem: 19788 +Epoch: [12] [ 660/2138] eta: 1:29:56 lr: 3.5910249639953444e-05 loss: 0.0414 (0.0422) time: 3.6153 data: 0.0031 max mem: 19788 +Epoch: [12] [ 670/2138] eta: 1:29:19 lr: 3.5904790541994646e-05 loss: 0.0437 (0.0423) time: 3.6208 data: 0.0029 max mem: 19788 +Epoch: [12] [ 680/2138] eta: 1:28:42 lr: 3.5899331351809675e-05 loss: 0.0388 (0.0423) time: 3.6277 data: 0.0028 max mem: 19788 +Epoch: [12] [ 690/2138] eta: 1:28:05 lr: 3.5893872069381386e-05 loss: 0.0384 (0.0423) time: 3.6253 data: 0.0029 max mem: 19788 +Epoch: [12] [ 700/2138] eta: 1:27:28 lr: 3.588841269469263e-05 loss: 0.0412 (0.0423) time: 3.6162 data: 0.0030 max mem: 19788 +Epoch: [12] [ 710/2138] eta: 1:26:51 lr: 3.588295322772624e-05 loss: 0.0417 (0.0423) time: 3.6147 data: 0.0029 max mem: 19788 +Epoch: [12] [ 720/2138] eta: 1:26:13 lr: 3.5877493668465084e-05 loss: 0.0427 (0.0424) time: 3.6134 data: 0.0028 max mem: 19788 +Epoch: [12] [ 730/2138] eta: 1:25:36 lr: 3.587203401689198e-05 loss: 0.0431 (0.0425) time: 3.6119 data: 0.0031 max mem: 19788 +Epoch: [12] [ 740/2138] eta: 1:24:59 lr: 3.5866574272989756e-05 loss: 0.0387 (0.0424) time: 3.6128 data: 0.0031 max mem: 19788 +Epoch: [12] [ 750/2138] eta: 1:24:22 lr: 3.586111443674124e-05 loss: 0.0334 (0.0423) time: 3.6149 data: 0.0028 max mem: 19788 +Epoch: [12] [ 760/2138] eta: 1:23:45 lr: 3.585565450812924e-05 loss: 0.0382 (0.0423) time: 3.6164 data: 0.0030 max mem: 19788 +Epoch: [12] [ 770/2138] eta: 1:23:08 lr: 3.585019448713657e-05 loss: 0.0411 (0.0423) time: 3.6161 data: 0.0030 max mem: 19788 +Epoch: [12] [ 780/2138] eta: 1:22:31 lr: 3.584473437374602e-05 loss: 0.0423 (0.0424) time: 3.6153 data: 0.0028 max mem: 19788 +Epoch: [12] [ 790/2138] eta: 1:21:54 lr: 3.583927416794041e-05 loss: 0.0423 (0.0425) time: 3.6161 data: 0.0030 max mem: 19788 +Epoch: [12] [ 800/2138] eta: 1:21:17 lr: 3.583381386970253e-05 loss: 0.0386 (0.0425) time: 3.6148 data: 0.0032 max mem: 19788 +Epoch: [12] [ 810/2138] eta: 1:20:40 lr: 3.582835347901514e-05 loss: 0.0370 (0.0425) time: 3.6167 data: 0.0033 max mem: 19788 +Epoch: [12] [ 820/2138] eta: 1:20:03 lr: 3.582289299586103e-05 loss: 0.0417 (0.0425) time: 3.6154 data: 0.0031 max mem: 19788 +Epoch: [12] [ 830/2138] eta: 1:19:26 lr: 3.581743242022299e-05 loss: 0.0387 (0.0425) time: 3.6181 data: 0.0030 max mem: 19788 +Epoch: [12] [ 840/2138] eta: 1:18:50 lr: 3.5811971752083775e-05 loss: 0.0367 (0.0424) time: 3.6225 data: 0.0029 max mem: 19788 +Epoch: [12] [ 850/2138] eta: 1:18:13 lr: 3.5806510991426136e-05 loss: 0.0369 (0.0424) time: 3.6169 data: 0.0028 max mem: 19788 +Epoch: [12] [ 860/2138] eta: 1:17:36 lr: 3.580105013823284e-05 loss: 0.0370 (0.0424) time: 3.6126 data: 0.0027 max mem: 19788 +Epoch: [12] [ 870/2138] eta: 1:16:59 lr: 3.5795589192486635e-05 loss: 0.0382 (0.0424) time: 3.6133 data: 0.0029 max mem: 19788 +Epoch: [12] [ 880/2138] eta: 1:16:22 lr: 3.5790128154170254e-05 loss: 0.0372 (0.0423) time: 3.6141 data: 0.0031 max mem: 19788 +Epoch: [12] [ 890/2138] eta: 1:15:45 lr: 3.5784667023266436e-05 loss: 0.0349 (0.0423) time: 3.6110 data: 0.0030 max mem: 19788 +Epoch: [12] [ 900/2138] eta: 1:15:08 lr: 3.577920579975792e-05 loss: 0.0371 (0.0424) time: 3.6148 data: 0.0028 max mem: 19788 +Epoch: [12] [ 910/2138] eta: 1:14:32 lr: 3.577374448362743e-05 loss: 0.0385 (0.0423) time: 3.6245 data: 0.0029 max mem: 19788 +Epoch: [12] [ 920/2138] eta: 1:13:55 lr: 3.576828307485767e-05 loss: 0.0346 (0.0423) time: 3.6275 data: 0.0031 max mem: 19788 +Epoch: [12] [ 930/2138] eta: 1:13:19 lr: 3.576282157343135e-05 loss: 0.0426 (0.0423) time: 3.6247 data: 0.0031 max mem: 19788 +Epoch: [12] [ 940/2138] eta: 1:12:42 lr: 3.575735997933119e-05 loss: 0.0426 (0.0424) time: 3.6241 data: 0.0033 max mem: 19788 +Epoch: [12] [ 950/2138] eta: 1:12:05 lr: 3.5751898292539884e-05 loss: 0.0374 (0.0423) time: 3.6210 data: 0.0034 max mem: 19788 +Epoch: [12] [ 960/2138] eta: 1:11:29 lr: 3.574643651304013e-05 loss: 0.0373 (0.0423) time: 3.6211 data: 0.0031 max mem: 19788 +Epoch: [12] [ 970/2138] eta: 1:10:52 lr: 3.5740974640814595e-05 loss: 0.0381 (0.0422) time: 3.6260 data: 0.0031 max mem: 19788 +Epoch: [12] [ 980/2138] eta: 1:10:15 lr: 3.573551267584598e-05 loss: 0.0368 (0.0422) time: 3.6227 data: 0.0030 max mem: 19788 +Epoch: [12] [ 990/2138] eta: 1:09:39 lr: 3.573005061811695e-05 loss: 0.0405 (0.0422) time: 3.6159 data: 0.0031 max mem: 19788 +Epoch: [12] [1000/2138] eta: 1:09:02 lr: 3.5724588467610184e-05 loss: 0.0427 (0.0422) time: 3.6261 data: 0.0031 max mem: 19788 +Epoch: [12] [1010/2138] eta: 1:08:26 lr: 3.5719126224308324e-05 loss: 0.0379 (0.0422) time: 3.6440 data: 0.0030 max mem: 19788 +Epoch: [12] [1020/2138] eta: 1:07:49 lr: 3.571366388819404e-05 loss: 0.0413 (0.0422) time: 3.6430 data: 0.0030 max mem: 19788 +Epoch: [12] [1030/2138] eta: 1:07:13 lr: 3.570820145924998e-05 loss: 0.0374 (0.0421) time: 3.6255 data: 0.0028 max mem: 19788 +Epoch: [12] [1040/2138] eta: 1:06:36 lr: 3.570273893745879e-05 loss: 0.0402 (0.0422) time: 3.6229 data: 0.0029 max mem: 19788 +Epoch: [12] [1050/2138] eta: 1:06:00 lr: 3.5697276322803107e-05 loss: 0.0407 (0.0422) time: 3.6296 data: 0.0030 max mem: 19788 +Epoch: [12] [1060/2138] eta: 1:05:23 lr: 3.5691813615265554e-05 loss: 0.0390 (0.0421) time: 3.6331 data: 0.0030 max mem: 19788 +Epoch: [12] [1070/2138] eta: 1:04:47 lr: 3.568635081482877e-05 loss: 0.0381 (0.0421) time: 3.6346 data: 0.0029 max mem: 19788 +Epoch: [12] [1080/2138] eta: 1:04:10 lr: 3.568088792147535e-05 loss: 0.0371 (0.0421) time: 3.6262 data: 0.0030 max mem: 19788 +Epoch: [12] [1090/2138] eta: 1:03:34 lr: 3.567542493518792e-05 loss: 0.0416 (0.0421) time: 3.6227 data: 0.0029 max mem: 19788 +Epoch: [12] [1100/2138] eta: 1:02:57 lr: 3.56699618559491e-05 loss: 0.0399 (0.0422) time: 3.6209 data: 0.0027 max mem: 19788 +Epoch: [12] [1110/2138] eta: 1:02:21 lr: 3.566449868374147e-05 loss: 0.0374 (0.0421) time: 3.6224 data: 0.0027 max mem: 19788 +Epoch: [12] [1120/2138] eta: 1:01:44 lr: 3.565903541854764e-05 loss: 0.0347 (0.0422) time: 3.6306 data: 0.0030 max mem: 19788 +Epoch: [12] [1130/2138] eta: 1:01:08 lr: 3.565357206035017e-05 loss: 0.0419 (0.0421) time: 3.6306 data: 0.0031 max mem: 19788 +Epoch: [12] [1140/2138] eta: 1:00:31 lr: 3.564810860913168e-05 loss: 0.0406 (0.0422) time: 3.6252 data: 0.0031 max mem: 19788 +Epoch: [12] [1150/2138] eta: 0:59:55 lr: 3.564264506487472e-05 loss: 0.0332 (0.0421) time: 3.6240 data: 0.0032 max mem: 19788 +Epoch: [12] [1160/2138] eta: 0:59:18 lr: 3.5637181427561855e-05 loss: 0.0332 (0.0421) time: 3.6271 data: 0.0029 max mem: 19788 +Epoch: [12] [1170/2138] eta: 0:58:42 lr: 3.563171769717566e-05 loss: 0.0350 (0.0420) time: 3.6285 data: 0.0027 max mem: 19788 +Epoch: [12] [1180/2138] eta: 0:58:05 lr: 3.5626253873698696e-05 loss: 0.0349 (0.0420) time: 3.6288 data: 0.0026 max mem: 19788 +Epoch: [12] [1190/2138] eta: 0:57:29 lr: 3.5620789957113504e-05 loss: 0.0349 (0.0419) time: 3.6251 data: 0.0026 max mem: 19788 +Epoch: [12] [1200/2138] eta: 0:56:52 lr: 3.5615325947402624e-05 loss: 0.0371 (0.0420) time: 3.6204 data: 0.0027 max mem: 19788 +Epoch: [12] [1210/2138] eta: 0:56:16 lr: 3.56098618445486e-05 loss: 0.0395 (0.0419) time: 3.6205 data: 0.0028 max mem: 19788 +Epoch: [12] [1220/2138] eta: 0:55:39 lr: 3.560439764853396e-05 loss: 0.0374 (0.0420) time: 3.6241 data: 0.0030 max mem: 19788 +Epoch: [12] [1230/2138] eta: 0:55:03 lr: 3.559893335934124e-05 loss: 0.0355 (0.0420) time: 3.6262 data: 0.0029 max mem: 19788 +Epoch: [12] [1240/2138] eta: 0:54:26 lr: 3.5593468976952944e-05 loss: 0.0408 (0.0420) time: 3.6226 data: 0.0028 max mem: 19788 +Epoch: [12] [1250/2138] eta: 0:53:50 lr: 3.558800450135159e-05 loss: 0.0396 (0.0420) time: 3.6202 data: 0.0028 max mem: 19788 +Epoch: [12] [1260/2138] eta: 0:53:13 lr: 3.5582539932519694e-05 loss: 0.0396 (0.0420) time: 3.6324 data: 0.0027 max mem: 19788 +Epoch: [12] [1270/2138] eta: 0:52:37 lr: 3.5577075270439744e-05 loss: 0.0404 (0.0421) time: 3.6300 data: 0.0030 max mem: 19788 +Epoch: [12] [1280/2138] eta: 0:52:00 lr: 3.557161051509423e-05 loss: 0.0381 (0.0420) time: 3.6256 data: 0.0032 max mem: 19788 +Epoch: [12] [1290/2138] eta: 0:51:24 lr: 3.5566145666465656e-05 loss: 0.0381 (0.0421) time: 3.6298 data: 0.0030 max mem: 19788 +Epoch: [12] [1300/2138] eta: 0:50:48 lr: 3.556068072453649e-05 loss: 0.0345 (0.0420) time: 3.6216 data: 0.0028 max mem: 19788 +Epoch: [12] [1310/2138] eta: 0:50:11 lr: 3.555521568928922e-05 loss: 0.0362 (0.0420) time: 3.6170 data: 0.0027 max mem: 19788 +Epoch: [12] [1320/2138] eta: 0:49:35 lr: 3.554975056070629e-05 loss: 0.0384 (0.0420) time: 3.6172 data: 0.0028 max mem: 19788 +Epoch: [12] [1330/2138] eta: 0:48:58 lr: 3.5544285338770194e-05 loss: 0.0357 (0.0420) time: 3.6306 data: 0.0029 max mem: 19788 +Epoch: [12] [1340/2138] eta: 0:48:22 lr: 3.553882002346337e-05 loss: 0.0406 (0.0421) time: 3.6350 data: 0.0028 max mem: 19788 +Epoch: [12] [1350/2138] eta: 0:47:45 lr: 3.5533354614768275e-05 loss: 0.0482 (0.0421) time: 3.6285 data: 0.0028 max mem: 19788 +Epoch: [12] [1360/2138] eta: 0:47:09 lr: 3.552788911266734e-05 loss: 0.0455 (0.0421) time: 3.6244 data: 0.0029 max mem: 19788 +Epoch: [12] [1370/2138] eta: 0:46:34 lr: 3.552242351714301e-05 loss: 0.0373 (0.0421) time: 3.7779 data: 0.0029 max mem: 19788 +Epoch: [12] [1380/2138] eta: 0:45:58 lr: 3.5516957828177724e-05 loss: 0.0358 (0.0421) time: 3.7769 data: 0.0030 max mem: 19788 +Epoch: [12] [1390/2138] eta: 0:45:21 lr: 3.551149204575389e-05 loss: 0.0423 (0.0421) time: 3.6274 data: 0.0031 max mem: 19788 +Epoch: [12] [1400/2138] eta: 0:44:45 lr: 3.550602616985394e-05 loss: 0.0393 (0.0421) time: 3.6470 data: 0.0031 max mem: 19788 +Epoch: [12] [1410/2138] eta: 0:44:09 lr: 3.550056020046029e-05 loss: 0.0370 (0.0420) time: 3.6492 data: 0.0028 max mem: 19788 +Epoch: [12] [1420/2138] eta: 0:43:32 lr: 3.549509413755533e-05 loss: 0.0341 (0.0420) time: 3.6314 data: 0.0029 max mem: 19788 +Epoch: [12] [1430/2138] eta: 0:42:56 lr: 3.548962798112146e-05 loss: 0.0342 (0.0420) time: 3.6185 data: 0.0032 max mem: 19788 +Epoch: [12] [1440/2138] eta: 0:42:19 lr: 3.548416173114109e-05 loss: 0.0390 (0.0420) time: 3.6306 data: 0.0030 max mem: 19788 +Epoch: [12] [1450/2138] eta: 0:41:43 lr: 3.547869538759659e-05 loss: 0.0385 (0.0420) time: 3.6371 data: 0.0028 max mem: 19788 +Epoch: [12] [1460/2138] eta: 0:41:07 lr: 3.547322895047035e-05 loss: 0.0413 (0.0420) time: 3.6376 data: 0.0028 max mem: 19788 +Epoch: [12] [1470/2138] eta: 0:40:30 lr: 3.546776241974474e-05 loss: 0.0383 (0.0420) time: 3.6440 data: 0.0029 max mem: 19788 +Epoch: [12] [1480/2138] eta: 0:39:54 lr: 3.546229579540212e-05 loss: 0.0382 (0.0420) time: 3.6344 data: 0.0029 max mem: 19788 +Epoch: [12] [1490/2138] eta: 0:39:17 lr: 3.545682907742488e-05 loss: 0.0423 (0.0420) time: 3.6386 data: 0.0028 max mem: 19788 +Epoch: [12] [1500/2138] eta: 0:38:41 lr: 3.545136226579534e-05 loss: 0.0341 (0.0420) time: 3.6419 data: 0.0028 max mem: 19788 +Epoch: [12] [1510/2138] eta: 0:38:05 lr: 3.544589536049586e-05 loss: 0.0378 (0.0420) time: 3.6534 data: 0.0030 max mem: 19788 +Epoch: [12] [1520/2138] eta: 0:37:28 lr: 3.5440428361508793e-05 loss: 0.0356 (0.0419) time: 3.6517 data: 0.0029 max mem: 19788 +Epoch: [12] [1530/2138] eta: 0:36:52 lr: 3.543496126881647e-05 loss: 0.0356 (0.0419) time: 3.6390 data: 0.0027 max mem: 19788 +Epoch: [12] [1540/2138] eta: 0:36:16 lr: 3.542949408240122e-05 loss: 0.0370 (0.0419) time: 3.6547 data: 0.0028 max mem: 19788 +Epoch: [12] [1550/2138] eta: 0:35:39 lr: 3.542402680224536e-05 loss: 0.0367 (0.0419) time: 3.6599 data: 0.0028 max mem: 19788 +Epoch: [12] [1560/2138] eta: 0:35:03 lr: 3.5418559428331213e-05 loss: 0.0429 (0.0419) time: 3.6419 data: 0.0027 max mem: 19788 +Epoch: [12] [1570/2138] eta: 0:34:26 lr: 3.541309196064109e-05 loss: 0.0429 (0.0419) time: 3.6318 data: 0.0027 max mem: 19788 +Epoch: [12] [1580/2138] eta: 0:33:50 lr: 3.54076243991573e-05 loss: 0.0374 (0.0419) time: 3.6394 data: 0.0027 max mem: 19788 +Epoch: [12] [1590/2138] eta: 0:33:14 lr: 3.5402156743862116e-05 loss: 0.0388 (0.0419) time: 3.6385 data: 0.0029 max mem: 19788 +Epoch: [12] [1600/2138] eta: 0:32:37 lr: 3.539668899473786e-05 loss: 0.0479 (0.0420) time: 3.6461 data: 0.0030 max mem: 19788 +Epoch: [12] [1610/2138] eta: 0:32:01 lr: 3.53912211517668e-05 loss: 0.0416 (0.0420) time: 3.6614 data: 0.0029 max mem: 19788 +Epoch: [12] [1620/2138] eta: 0:31:25 lr: 3.538575321493123e-05 loss: 0.0369 (0.0420) time: 3.6511 data: 0.0030 max mem: 19788 +Epoch: [12] [1630/2138] eta: 0:30:48 lr: 3.53802851842134e-05 loss: 0.0377 (0.0420) time: 3.6335 data: 0.0032 max mem: 19788 +Epoch: [12] [1640/2138] eta: 0:30:12 lr: 3.5374817059595583e-05 loss: 0.0363 (0.0420) time: 3.6308 data: 0.0031 max mem: 19788 +Epoch: [12] [1650/2138] eta: 0:29:35 lr: 3.5369348841060055e-05 loss: 0.0296 (0.0419) time: 3.6282 data: 0.0028 max mem: 19788 +Epoch: [12] [1660/2138] eta: 0:28:59 lr: 3.536388052858905e-05 loss: 0.0342 (0.0419) time: 3.6300 data: 0.0027 max mem: 19788 +Epoch: [12] [1670/2138] eta: 0:28:23 lr: 3.535841212216483e-05 loss: 0.0320 (0.0418) time: 3.6368 data: 0.0026 max mem: 19788 +Epoch: [12] [1680/2138] eta: 0:27:46 lr: 3.535294362176961e-05 loss: 0.0357 (0.0418) time: 3.6342 data: 0.0027 max mem: 19788 +Epoch: [12] [1690/2138] eta: 0:27:10 lr: 3.534747502738566e-05 loss: 0.0359 (0.0418) time: 3.6304 data: 0.0027 max mem: 19788 +Epoch: [12] [1700/2138] eta: 0:26:33 lr: 3.5342006338995174e-05 loss: 0.0348 (0.0418) time: 3.6306 data: 0.0029 max mem: 19788 +Epoch: [12] [1710/2138] eta: 0:25:57 lr: 3.533653755658039e-05 loss: 0.0348 (0.0418) time: 3.6270 data: 0.0030 max mem: 19788 +Epoch: [12] [1720/2138] eta: 0:25:21 lr: 3.5331068680123516e-05 loss: 0.0360 (0.0418) time: 3.6328 data: 0.0028 max mem: 19788 +Epoch: [12] [1730/2138] eta: 0:24:44 lr: 3.5325599709606774e-05 loss: 0.0366 (0.0418) time: 3.6361 data: 0.0027 max mem: 19788 +Epoch: [12] [1740/2138] eta: 0:24:08 lr: 3.5320130645012346e-05 loss: 0.0389 (0.0418) time: 3.6338 data: 0.0027 max mem: 19788 +Epoch: [12] [1750/2138] eta: 0:23:31 lr: 3.531466148632244e-05 loss: 0.0392 (0.0418) time: 3.6436 data: 0.0029 max mem: 19788 +Epoch: [12] [1760/2138] eta: 0:22:55 lr: 3.530919223351924e-05 loss: 0.0413 (0.0418) time: 3.6424 data: 0.0029 max mem: 19788 +Epoch: [12] [1770/2138] eta: 0:22:19 lr: 3.5303722886584926e-05 loss: 0.0378 (0.0418) time: 3.6337 data: 0.0030 max mem: 19788 +Epoch: [12] [1780/2138] eta: 0:21:42 lr: 3.529825344550169e-05 loss: 0.0355 (0.0418) time: 3.6396 data: 0.0030 max mem: 19788 +Epoch: [12] [1790/2138] eta: 0:21:06 lr: 3.529278391025167e-05 loss: 0.0355 (0.0418) time: 3.6386 data: 0.0030 max mem: 19788 +Epoch: [12] [1800/2138] eta: 0:20:29 lr: 3.5287314280817065e-05 loss: 0.0347 (0.0418) time: 3.6409 data: 0.0029 max mem: 19788 +Epoch: [12] [1810/2138] eta: 0:19:53 lr: 3.528184455718001e-05 loss: 0.0347 (0.0418) time: 3.6464 data: 0.0031 max mem: 19788 +Epoch: [12] [1820/2138] eta: 0:19:17 lr: 3.527637473932266e-05 loss: 0.0360 (0.0418) time: 3.6381 data: 0.0034 max mem: 19788 +Epoch: [12] [1830/2138] eta: 0:18:40 lr: 3.5270904827227154e-05 loss: 0.0359 (0.0418) time: 3.6333 data: 0.0032 max mem: 19788 +Epoch: [12] [1840/2138] eta: 0:18:04 lr: 3.5265434820875644e-05 loss: 0.0393 (0.0418) time: 3.6280 data: 0.0029 max mem: 19788 +Epoch: [12] [1850/2138] eta: 0:17:27 lr: 3.525996472025025e-05 loss: 0.0443 (0.0419) time: 3.6276 data: 0.0031 max mem: 19788 +Epoch: [12] [1860/2138] eta: 0:16:51 lr: 3.525449452533309e-05 loss: 0.0443 (0.0420) time: 3.6283 data: 0.0029 max mem: 19788 +Epoch: [12] [1870/2138] eta: 0:16:15 lr: 3.524902423610629e-05 loss: 0.0536 (0.0422) time: 3.6380 data: 0.0030 max mem: 19788 +Epoch: [12] [1880/2138] eta: 0:15:38 lr: 3.5243553852551964e-05 loss: 0.0468 (0.0422) time: 3.6445 data: 0.0033 max mem: 19788 +Epoch: [12] [1890/2138] eta: 0:15:02 lr: 3.523808337465221e-05 loss: 0.0360 (0.0421) time: 3.6393 data: 0.0031 max mem: 19788 +Epoch: [12] [1900/2138] eta: 0:14:26 lr: 3.523261280238913e-05 loss: 0.0318 (0.0421) time: 3.6402 data: 0.0029 max mem: 19788 +Epoch: [12] [1910/2138] eta: 0:13:49 lr: 3.522714213574482e-05 loss: 0.0385 (0.0421) time: 3.6399 data: 0.0028 max mem: 19788 +Epoch: [12] [1920/2138] eta: 0:13:13 lr: 3.522167137470136e-05 loss: 0.0385 (0.0421) time: 3.6430 data: 0.0030 max mem: 19788 +Epoch: [12] [1930/2138] eta: 0:12:36 lr: 3.521620051924083e-05 loss: 0.0384 (0.0421) time: 3.6373 data: 0.0031 max mem: 19788 +Epoch: [12] [1940/2138] eta: 0:12:00 lr: 3.5210729569345295e-05 loss: 0.0372 (0.0421) time: 3.6440 data: 0.0029 max mem: 19788 +Epoch: [12] [1950/2138] eta: 0:11:24 lr: 3.520525852499684e-05 loss: 0.0352 (0.0420) time: 3.6539 data: 0.0029 max mem: 19788 +Epoch: [12] [1960/2138] eta: 0:10:47 lr: 3.519978738617751e-05 loss: 0.0385 (0.0420) time: 3.6455 data: 0.0029 max mem: 19788 +Epoch: [12] [1970/2138] eta: 0:10:11 lr: 3.5194316152869355e-05 loss: 0.0397 (0.0420) time: 3.6365 data: 0.0029 max mem: 19788 +Epoch: [12] [1980/2138] eta: 0:09:34 lr: 3.5188844825054426e-05 loss: 0.0326 (0.0420) time: 3.6241 data: 0.0028 max mem: 19788 +Epoch: [12] [1990/2138] eta: 0:08:58 lr: 3.518337340271477e-05 loss: 0.0326 (0.0420) time: 3.6358 data: 0.0029 max mem: 19788 +Epoch: [12] [2000/2138] eta: 0:08:22 lr: 3.5177901885832427e-05 loss: 0.0345 (0.0420) time: 3.6402 data: 0.0031 max mem: 19788 +Epoch: [12] [2010/2138] eta: 0:07:45 lr: 3.5172430274389396e-05 loss: 0.0418 (0.0420) time: 3.6340 data: 0.0030 max mem: 19788 +Epoch: [12] [2020/2138] eta: 0:07:09 lr: 3.516695856836771e-05 loss: 0.0412 (0.0420) time: 3.6389 data: 0.0027 max mem: 19788 +Epoch: [12] [2030/2138] eta: 0:06:32 lr: 3.51614867677494e-05 loss: 0.0383 (0.0420) time: 3.6303 data: 0.0029 max mem: 19788 +Epoch: [12] [2040/2138] eta: 0:05:56 lr: 3.515601487251645e-05 loss: 0.0360 (0.0420) time: 3.6263 data: 0.0030 max mem: 19788 +Epoch: [12] [2050/2138] eta: 0:05:20 lr: 3.515054288265087e-05 loss: 0.0397 (0.0420) time: 3.6423 data: 0.0029 max mem: 19788 +Epoch: [12] [2060/2138] eta: 0:04:43 lr: 3.5145070798134645e-05 loss: 0.0397 (0.0420) time: 3.6409 data: 0.0028 max mem: 19788 +Epoch: [12] [2070/2138] eta: 0:04:07 lr: 3.513959861894978e-05 loss: 0.0390 (0.0420) time: 3.6311 data: 0.0028 max mem: 19788 +Epoch: [12] [2080/2138] eta: 0:03:31 lr: 3.513412634507825e-05 loss: 0.0379 (0.0420) time: 3.6330 data: 0.0027 max mem: 19788 +Epoch: [12] [2090/2138] eta: 0:02:54 lr: 3.512865397650203e-05 loss: 0.0369 (0.0420) time: 3.6340 data: 0.0028 max mem: 19788 +Epoch: [12] [2100/2138] eta: 0:02:18 lr: 3.512318151320307e-05 loss: 0.0331 (0.0419) time: 3.6365 data: 0.0029 max mem: 19788 +Epoch: [12] [2110/2138] eta: 0:01:41 lr: 3.511770895516337e-05 loss: 0.0409 (0.0420) time: 3.6339 data: 0.0027 max mem: 19788 +Epoch: [12] [2120/2138] eta: 0:01:05 lr: 3.511223630236485e-05 loss: 0.0466 (0.0420) time: 3.6291 data: 0.0029 max mem: 19788 +Epoch: [12] [2130/2138] eta: 0:00:29 lr: 3.510676355478947e-05 loss: 0.0424 (0.0420) time: 3.6169 data: 0.0028 max mem: 19788 +Epoch: [12] Total time: 2:09:39 +Test: [ 0/21770] eta: 18:06:29 time: 2.9945 data: 2.8813 max mem: 19788 +Test: [ 100/21770] eta: 0:33:07 time: 0.0626 data: 0.0018 max mem: 19788 +Test: [ 200/21770] eta: 0:29:02 time: 0.0658 data: 0.0018 max mem: 19788 +Test: [ 300/21770] eta: 0:26:37 time: 0.0650 data: 0.0019 max mem: 19788 +Test: [ 400/21770] eta: 0:25:24 time: 0.0623 data: 0.0018 max mem: 19788 +Test: [ 500/21770] eta: 0:24:58 time: 0.0727 data: 0.0023 max mem: 19788 +Test: [ 600/21770] eta: 0:24:23 time: 0.0648 data: 0.0018 max mem: 19788 +Test: [ 700/21770] eta: 0:24:15 time: 0.0594 data: 0.0019 max mem: 19788 +Test: [ 800/21770] eta: 0:23:52 time: 0.0699 data: 0.0020 max mem: 19788 +Test: [ 900/21770] eta: 0:23:30 time: 0.0606 data: 0.0019 max mem: 19788 +Test: [ 1000/21770] eta: 0:23:26 time: 0.0604 data: 0.0017 max mem: 19788 +Test: [ 1100/21770] eta: 0:23:09 time: 0.0617 data: 0.0018 max mem: 19788 +Test: [ 1200/21770] eta: 0:23:09 time: 0.0672 data: 0.0018 max mem: 19788 +Test: [ 1300/21770] eta: 0:23:03 time: 0.0635 data: 0.0018 max mem: 19788 +Test: [ 1400/21770] eta: 0:23:05 time: 0.0760 data: 0.0023 max mem: 19788 +Test: [ 1500/21770] eta: 0:22:56 time: 0.0593 data: 0.0018 max mem: 19788 +Test: [ 1600/21770] eta: 0:22:54 time: 0.0742 data: 0.0023 max mem: 19788 +Test: [ 1700/21770] eta: 0:22:48 time: 0.0664 data: 0.0020 max mem: 19788 +Test: [ 1800/21770] eta: 0:22:41 time: 0.0595 data: 0.0017 max mem: 19788 +Test: [ 1900/21770] eta: 0:22:31 time: 0.0685 data: 0.0022 max mem: 19788 +Test: [ 2000/21770] eta: 0:22:28 time: 0.0707 data: 0.0021 max mem: 19788 +Test: [ 2100/21770] eta: 0:22:21 time: 0.0740 data: 0.0023 max mem: 19788 +Test: [ 2200/21770] eta: 0:22:19 time: 0.0618 data: 0.0017 max mem: 19788 +Test: [ 2300/21770] eta: 0:22:08 time: 0.0701 data: 0.0019 max mem: 19788 +Test: [ 2400/21770] eta: 0:21:59 time: 0.0632 data: 0.0019 max mem: 19788 +Test: [ 2500/21770] eta: 0:21:52 time: 0.0815 data: 0.0025 max mem: 19788 +Test: [ 2600/21770] eta: 0:21:46 time: 0.0751 data: 0.0020 max mem: 19788 +Test: [ 2700/21770] eta: 0:21:38 time: 0.0596 data: 0.0017 max mem: 19788 +Test: [ 2800/21770] eta: 0:21:31 time: 0.0681 data: 0.0022 max mem: 19788 +Test: [ 2900/21770] eta: 0:21:22 time: 0.0651 data: 0.0018 max mem: 19788 +Test: [ 3000/21770] eta: 0:21:12 time: 0.0632 data: 0.0018 max mem: 19788 +Test: [ 3100/21770] eta: 0:21:03 time: 0.0670 data: 0.0019 max mem: 19788 +Test: [ 3200/21770] eta: 0:20:57 time: 0.0713 data: 0.0021 max mem: 19788 +Test: [ 3300/21770] eta: 0:20:50 time: 0.0650 data: 0.0019 max mem: 19788 +Test: [ 3400/21770] eta: 0:20:43 time: 0.0755 data: 0.0023 max mem: 19788 +Test: [ 3500/21770] eta: 0:20:35 time: 0.0750 data: 0.0023 max mem: 19788 +Test: [ 3600/21770] eta: 0:20:27 time: 0.0617 data: 0.0019 max mem: 19788 +Test: [ 3700/21770] eta: 0:20:18 time: 0.0601 data: 0.0018 max mem: 19788 +Test: [ 3800/21770] eta: 0:20:13 time: 0.0813 data: 0.0024 max mem: 19788 +Test: [ 3900/21770] eta: 0:20:08 time: 0.0702 data: 0.0022 max mem: 19788 +Test: [ 4000/21770] eta: 0:20:01 time: 0.0582 data: 0.0019 max mem: 19788 +Test: [ 4100/21770] eta: 0:19:55 time: 0.0685 data: 0.0020 max mem: 19788 +Test: [ 4200/21770] eta: 0:19:46 time: 0.0605 data: 0.0018 max mem: 19788 +Test: [ 4300/21770] eta: 0:19:41 time: 0.0784 data: 0.0022 max mem: 19788 +Test: [ 4400/21770] eta: 0:19:37 time: 0.0778 data: 0.0024 max mem: 19788 +Test: [ 4500/21770] eta: 0:19:31 time: 0.0772 data: 0.0020 max mem: 19788 +Test: [ 4600/21770] eta: 0:19:27 time: 0.0666 data: 0.0019 max mem: 19788 +Test: [ 4700/21770] eta: 0:19:20 time: 0.0647 data: 0.0018 max mem: 19788 +Test: [ 4800/21770] eta: 0:19:12 time: 0.0799 data: 0.0024 max mem: 19788 +Test: [ 4900/21770] eta: 0:19:07 time: 0.0693 data: 0.0019 max mem: 19788 +Test: [ 5000/21770] eta: 0:18:59 time: 0.0665 data: 0.0018 max mem: 19788 +Test: [ 5100/21770] eta: 0:18:54 time: 0.0635 data: 0.0017 max mem: 19788 +Test: [ 5200/21770] eta: 0:18:48 time: 0.0768 data: 0.0018 max mem: 19788 +Test: [ 5300/21770] eta: 0:18:43 time: 0.0727 data: 0.0022 max mem: 19788 +Test: [ 5400/21770] eta: 0:18:38 time: 0.0812 data: 0.0023 max mem: 19788 +Test: [ 5500/21770] eta: 0:18:32 time: 0.0707 data: 0.0021 max mem: 19788 +Test: [ 5600/21770] eta: 0:18:27 time: 0.0800 data: 0.0024 max mem: 19788 +Test: [ 5700/21770] eta: 0:18:19 time: 0.0621 data: 0.0018 max mem: 19788 +Test: [ 5800/21770] eta: 0:18:11 time: 0.0627 data: 0.0020 max mem: 19788 +Test: [ 5900/21770] eta: 0:18:03 time: 0.0618 data: 0.0017 max mem: 19788 +Test: [ 6000/21770] eta: 0:17:55 time: 0.0612 data: 0.0017 max mem: 19788 +Test: [ 6100/21770] eta: 0:17:48 time: 0.0619 data: 0.0018 max mem: 19788 +Test: [ 6200/21770] eta: 0:17:40 time: 0.0620 data: 0.0019 max mem: 19788 +Test: [ 6300/21770] eta: 0:17:32 time: 0.0626 data: 0.0019 max mem: 19788 +Test: [ 6400/21770] eta: 0:17:27 time: 0.0815 data: 0.0024 max mem: 19788 +Test: [ 6500/21770] eta: 0:17:19 time: 0.0715 data: 0.0020 max mem: 19788 +Test: [ 6600/21770] eta: 0:17:12 time: 0.0624 data: 0.0017 max mem: 19788 +Test: [ 6700/21770] eta: 0:17:04 time: 0.0753 data: 0.0022 max mem: 19788 +Test: [ 6800/21770] eta: 0:16:58 time: 0.0645 data: 0.0018 max mem: 19788 +Test: [ 6900/21770] eta: 0:16:51 time: 0.0612 data: 0.0019 max mem: 19788 +Test: [ 7000/21770] eta: 0:16:44 time: 0.0674 data: 0.0020 max mem: 19788 +Test: [ 7100/21770] eta: 0:16:37 time: 0.0620 data: 0.0020 max mem: 19788 +Test: [ 7200/21770] eta: 0:16:29 time: 0.0650 data: 0.0020 max mem: 19788 +Test: [ 7300/21770] eta: 0:16:23 time: 0.0693 data: 0.0018 max mem: 19788 +Test: [ 7400/21770] eta: 0:16:16 time: 0.0719 data: 0.0020 max mem: 19788 +Test: [ 7500/21770] eta: 0:16:10 time: 0.0740 data: 0.0017 max mem: 19788 +Test: [ 7600/21770] eta: 0:16:02 time: 0.0621 data: 0.0019 max mem: 19788 +Test: [ 7700/21770] eta: 0:15:57 time: 0.0778 data: 0.0023 max mem: 19788 +Test: [ 7800/21770] eta: 0:15:50 time: 0.0685 data: 0.0019 max mem: 19788 +Test: [ 7900/21770] eta: 0:15:44 time: 0.0657 data: 0.0018 max mem: 19788 +Test: [ 8000/21770] eta: 0:15:36 time: 0.0718 data: 0.0021 max mem: 19788 +Test: [ 8100/21770] eta: 0:15:29 time: 0.0606 data: 0.0018 max mem: 19788 +Test: [ 8200/21770] eta: 0:15:21 time: 0.0688 data: 0.0019 max mem: 19788 +Test: [ 8300/21770] eta: 0:15:14 time: 0.0638 data: 0.0018 max mem: 19788 +Test: [ 8400/21770] eta: 0:15:08 time: 0.0739 data: 0.0022 max mem: 19788 +Test: [ 8500/21770] eta: 0:15:01 time: 0.0604 data: 0.0017 max mem: 19788 +Test: [ 8600/21770] eta: 0:14:54 time: 0.0606 data: 0.0020 max mem: 19788 +Test: [ 8700/21770] eta: 0:14:46 time: 0.0622 data: 0.0019 max mem: 19788 +Test: [ 8800/21770] eta: 0:14:40 time: 0.0781 data: 0.0024 max mem: 19788 +Test: [ 8900/21770] eta: 0:14:33 time: 0.0669 data: 0.0018 max mem: 19788 +Test: [ 9000/21770] eta: 0:14:26 time: 0.0601 data: 0.0019 max mem: 19788 +Test: [ 9100/21770] eta: 0:14:19 time: 0.0676 data: 0.0017 max mem: 19788 +Test: [ 9200/21770] eta: 0:14:11 time: 0.0622 data: 0.0018 max mem: 19788 +Test: [ 9300/21770] eta: 0:14:05 time: 0.0752 data: 0.0021 max mem: 19788 +Test: [ 9400/21770] eta: 0:13:58 time: 0.0660 data: 0.0019 max mem: 19788 +Test: [ 9500/21770] eta: 0:13:51 time: 0.0700 data: 0.0022 max mem: 19788 +Test: [ 9600/21770] eta: 0:13:45 time: 0.0680 data: 0.0021 max mem: 19788 +Test: [ 9700/21770] eta: 0:13:37 time: 0.0626 data: 0.0016 max mem: 19788 +Test: [ 9800/21770] eta: 0:13:30 time: 0.0707 data: 0.0020 max mem: 19788 +Test: [ 9900/21770] eta: 0:13:24 time: 0.0750 data: 0.0021 max mem: 19788 +Test: [10000/21770] eta: 0:13:18 time: 0.0749 data: 0.0022 max mem: 19788 +Test: [10100/21770] eta: 0:13:11 time: 0.0618 data: 0.0019 max mem: 19788 +Test: [10200/21770] eta: 0:13:06 time: 0.0770 data: 0.0023 max mem: 19788 +Test: [10300/21770] eta: 0:12:59 time: 0.0763 data: 0.0023 max mem: 19788 +Test: [10400/21770] eta: 0:12:52 time: 0.0722 data: 0.0019 max mem: 19788 +Test: [10500/21770] eta: 0:12:46 time: 0.0686 data: 0.0022 max mem: 19788 +Test: [10600/21770] eta: 0:12:39 time: 0.0684 data: 0.0017 max mem: 19788 +Test: [10700/21770] eta: 0:12:33 time: 0.0715 data: 0.0019 max mem: 19788 +Test: [10800/21770] eta: 0:12:26 time: 0.0681 data: 0.0019 max mem: 19788 +Test: [10900/21770] eta: 0:12:20 time: 0.0775 data: 0.0022 max mem: 19788 +Test: [11000/21770] eta: 0:12:14 time: 0.0717 data: 0.0022 max mem: 19788 +Test: [11100/21770] eta: 0:12:07 time: 0.0648 data: 0.0018 max mem: 19788 +Test: [11200/21770] eta: 0:12:00 time: 0.0611 data: 0.0018 max mem: 19788 +Test: [11300/21770] eta: 0:11:53 time: 0.0628 data: 0.0017 max mem: 19788 +Test: [11400/21770] eta: 0:11:46 time: 0.0810 data: 0.0024 max mem: 19788 +Test: [11500/21770] eta: 0:11:40 time: 0.0652 data: 0.0020 max mem: 19788 +Test: [11600/21770] eta: 0:11:33 time: 0.0660 data: 0.0019 max mem: 19788 +Test: [11700/21770] eta: 0:11:26 time: 0.0642 data: 0.0020 max mem: 19788 +Test: [11800/21770] eta: 0:11:20 time: 0.0689 data: 0.0019 max mem: 19788 +Test: [11900/21770] eta: 0:11:13 time: 0.0821 data: 0.0018 max mem: 19788 +Test: [12000/21770] eta: 0:11:07 time: 0.0724 data: 0.0021 max mem: 19788 +Test: [12100/21770] eta: 0:11:01 time: 0.0684 data: 0.0020 max mem: 19788 +Test: [12200/21770] eta: 0:10:54 time: 0.0629 data: 0.0018 max mem: 19788 +Test: [12300/21770] eta: 0:10:48 time: 0.0816 data: 0.0023 max mem: 19788 +Test: [12400/21770] eta: 0:10:41 time: 0.0624 data: 0.0019 max mem: 19788 +Test: [12500/21770] eta: 0:10:34 time: 0.0797 data: 0.0023 max mem: 19788 +Test: [12600/21770] eta: 0:10:27 time: 0.0623 data: 0.0017 max mem: 19788 +Test: [12700/21770] eta: 0:10:21 time: 0.0785 data: 0.0021 max mem: 19788 +Test: [12800/21770] eta: 0:10:14 time: 0.0623 data: 0.0019 max mem: 19788 +Test: [12900/21770] eta: 0:10:07 time: 0.0759 data: 0.0020 max mem: 19788 +Test: [13000/21770] eta: 0:10:00 time: 0.0623 data: 0.0020 max mem: 19788 +Test: [13100/21770] eta: 0:09:53 time: 0.0649 data: 0.0018 max mem: 19788 +Test: [13200/21770] eta: 0:09:47 time: 0.0730 data: 0.0022 max mem: 19788 +Test: [13300/21770] eta: 0:09:40 time: 0.0769 data: 0.0022 max mem: 19788 +Test: [13400/21770] eta: 0:09:33 time: 0.0608 data: 0.0016 max mem: 19788 +Test: [13500/21770] eta: 0:09:26 time: 0.0791 data: 0.0023 max mem: 19788 +Test: [13600/21770] eta: 0:09:20 time: 0.0752 data: 0.0021 max mem: 19788 +Test: [13700/21770] eta: 0:09:13 time: 0.0614 data: 0.0020 max mem: 19788 +Test: [13800/21770] eta: 0:09:06 time: 0.0733 data: 0.0019 max mem: 19788 +Test: [13900/21770] eta: 0:08:59 time: 0.0720 data: 0.0022 max mem: 19788 +Test: [14000/21770] eta: 0:08:52 time: 0.0637 data: 0.0020 max mem: 19788 +Test: [14100/21770] eta: 0:08:46 time: 0.0697 data: 0.0021 max mem: 19788 +Test: [14200/21770] eta: 0:08:38 time: 0.0709 data: 0.0021 max mem: 19788 +Test: [14300/21770] eta: 0:08:32 time: 0.0622 data: 0.0016 max mem: 19788 +Test: [14400/21770] eta: 0:08:25 time: 0.0726 data: 0.0019 max mem: 19788 +Test: [14500/21770] eta: 0:08:18 time: 0.0642 data: 0.0019 max mem: 19788 +Test: [14600/21770] eta: 0:08:11 time: 0.0697 data: 0.0021 max mem: 19788 +Test: [14700/21770] eta: 0:08:04 time: 0.0798 data: 0.0019 max mem: 19788 +Test: [14800/21770] eta: 0:07:57 time: 0.0687 data: 0.0019 max mem: 19788 +Test: [14900/21770] eta: 0:07:50 time: 0.0729 data: 0.0022 max mem: 19788 +Test: [15000/21770] eta: 0:07:43 time: 0.0624 data: 0.0018 max mem: 19788 +Test: [15100/21770] eta: 0:07:36 time: 0.0710 data: 0.0023 max mem: 19788 +Test: [15200/21770] eta: 0:07:30 time: 0.0700 data: 0.0019 max mem: 19788 +Test: [15300/21770] eta: 0:07:23 time: 0.0625 data: 0.0017 max mem: 19788 +Test: [15400/21770] eta: 0:07:16 time: 0.0669 data: 0.0019 max mem: 19788 +Test: [15500/21770] eta: 0:07:09 time: 0.0779 data: 0.0022 max mem: 19788 +Test: [15600/21770] eta: 0:07:03 time: 0.0723 data: 0.0020 max mem: 19788 +Test: [15700/21770] eta: 0:06:56 time: 0.0659 data: 0.0019 max mem: 19788 +Test: [15800/21770] eta: 0:06:49 time: 0.0617 data: 0.0019 max mem: 19788 +Test: [15900/21770] eta: 0:06:42 time: 0.0654 data: 0.0018 max mem: 19788 +Test: [16000/21770] eta: 0:06:35 time: 0.0752 data: 0.0024 max mem: 19788 +Test: [16100/21770] eta: 0:06:28 time: 0.0767 data: 0.0025 max mem: 19788 +Test: [16200/21770] eta: 0:06:21 time: 0.0655 data: 0.0019 max mem: 19788 +Test: [16300/21770] eta: 0:06:15 time: 0.0719 data: 0.0021 max mem: 19788 +Test: [16400/21770] eta: 0:06:08 time: 0.0664 data: 0.0018 max mem: 19788 +Test: [16500/21770] eta: 0:06:01 time: 0.0601 data: 0.0019 max mem: 19788 +Test: [16600/21770] eta: 0:05:54 time: 0.0815 data: 0.0025 max mem: 19788 +Test: [16700/21770] eta: 0:05:47 time: 0.0699 data: 0.0021 max mem: 19788 +Test: [16800/21770] eta: 0:05:40 time: 0.0745 data: 0.0022 max mem: 19788 +Test: [16900/21770] eta: 0:05:33 time: 0.0604 data: 0.0018 max mem: 19788 +Test: [17000/21770] eta: 0:05:26 time: 0.0727 data: 0.0021 max mem: 19788 +Test: [17100/21770] eta: 0:05:19 time: 0.0704 data: 0.0020 max mem: 19788 +Test: [17200/21770] eta: 0:05:12 time: 0.0699 data: 0.0021 max mem: 19788 +Test: [17300/21770] eta: 0:05:06 time: 0.0724 data: 0.0023 max mem: 19788 +Test: [17400/21770] eta: 0:04:59 time: 0.0654 data: 0.0019 max mem: 19788 +Test: [17500/21770] eta: 0:04:52 time: 0.0599 data: 0.0017 max mem: 19788 +Test: [17600/21770] eta: 0:04:45 time: 0.0700 data: 0.0018 max mem: 19788 +Test: [17700/21770] eta: 0:04:38 time: 0.0625 data: 0.0020 max mem: 19788 +Test: [17800/21770] eta: 0:04:31 time: 0.0742 data: 0.0024 max mem: 19788 +Test: [17900/21770] eta: 0:04:25 time: 0.0609 data: 0.0017 max mem: 19788 +Test: [18000/21770] eta: 0:04:18 time: 0.0642 data: 0.0018 max mem: 19788 +Test: [18100/21770] eta: 0:04:11 time: 0.0750 data: 0.0024 max mem: 19788 +Test: [18200/21770] eta: 0:04:04 time: 0.0708 data: 0.0023 max mem: 19788 +Test: [18300/21770] eta: 0:03:57 time: 0.0684 data: 0.0019 max mem: 19788 +Test: [18400/21770] eta: 0:03:50 time: 0.0706 data: 0.0020 max mem: 19788 +Test: [18500/21770] eta: 0:03:43 time: 0.0624 data: 0.0022 max mem: 19788 +Test: [18600/21770] eta: 0:03:37 time: 0.0681 data: 0.0018 max mem: 19788 +Test: [18700/21770] eta: 0:03:30 time: 0.0613 data: 0.0019 max mem: 19788 +Test: [18800/21770] eta: 0:03:23 time: 0.0646 data: 0.0020 max mem: 19788 +Test: [18900/21770] eta: 0:03:16 time: 0.0588 data: 0.0019 max mem: 19788 +Test: [19000/21770] eta: 0:03:09 time: 0.0615 data: 0.0019 max mem: 19788 +Test: [19100/21770] eta: 0:03:02 time: 0.0713 data: 0.0021 max mem: 19788 +Test: [19200/21770] eta: 0:02:55 time: 0.0660 data: 0.0021 max mem: 19788 +Test: [19300/21770] eta: 0:02:48 time: 0.0636 data: 0.0018 max mem: 19788 +Test: [19400/21770] eta: 0:02:41 time: 0.0664 data: 0.0021 max mem: 19788 +Test: [19500/21770] eta: 0:02:35 time: 0.0613 data: 0.0017 max mem: 19788 +Test: [19600/21770] eta: 0:02:28 time: 0.0636 data: 0.0019 max mem: 19788 +Test: [19700/21770] eta: 0:02:21 time: 0.0710 data: 0.0022 max mem: 19788 +Test: [19800/21770] eta: 0:02:14 time: 0.0622 data: 0.0018 max mem: 19788 +Test: [19900/21770] eta: 0:02:07 time: 0.0727 data: 0.0020 max mem: 19788 +Test: [20000/21770] eta: 0:02:00 time: 0.0776 data: 0.0024 max mem: 19788 +Test: [20100/21770] eta: 0:01:54 time: 0.0628 data: 0.0018 max mem: 19788 +Test: [20200/21770] eta: 0:01:47 time: 0.0622 data: 0.0018 max mem: 19788 +Test: [20300/21770] eta: 0:01:40 time: 0.0604 data: 0.0017 max mem: 19788 +Test: [20400/21770] eta: 0:01:33 time: 0.0657 data: 0.0018 max mem: 19788 +Test: [20500/21770] eta: 0:01:26 time: 0.0701 data: 0.0021 max mem: 19788 +Test: [20600/21770] eta: 0:01:19 time: 0.0696 data: 0.0019 max mem: 19788 +Test: [20700/21770] eta: 0:01:13 time: 0.0772 data: 0.0020 max mem: 19788 +Test: [20800/21770] eta: 0:01:06 time: 0.0743 data: 0.0019 max mem: 19788 +Test: [20900/21770] eta: 0:00:59 time: 0.0614 data: 0.0018 max mem: 19788 +Test: [21000/21770] eta: 0:00:52 time: 0.0648 data: 0.0018 max mem: 19788 +Test: [21100/21770] eta: 0:00:45 time: 0.0803 data: 0.0024 max mem: 19788 +Test: [21200/21770] eta: 0:00:38 time: 0.0740 data: 0.0018 max mem: 19788 +Test: [21300/21770] eta: 0:00:32 time: 0.0753 data: 0.0022 max mem: 19788 +Test: [21400/21770] eta: 0:00:25 time: 0.0623 data: 0.0018 max mem: 19788 +Test: [21500/21770] eta: 0:00:18 time: 0.0653 data: 0.0019 max mem: 19788 +Test: [21600/21770] eta: 0:00:11 time: 0.0620 data: 0.0018 max mem: 19788 +Test: [21700/21770] eta: 0:00:04 time: 0.0613 data: 0.0019 max mem: 19788 +Test: Total time: 0:24:46 +Final results: +Mean IoU is 62.11 + + precision@0.5 = 68.47 + precision@0.6 = 63.47 + precision@0.7 = 56.65 + precision@0.8 = 46.11 + precision@0.9 = 23.03 + overall IoU = 62.98 + mean IoU = 62.11 + +Mean accuracy for one-to-zero sample is 82.64 + +Average object IoU 0.6210637474719044 +Overall IoU 62.97929763793945 +Better epoch: 12 + +Epoch: [13] [ 0/2138] eta: 3:09:54 lr: 3.5102385288477694e-05 loss: 0.0407 (0.0407) time: 5.3293 data: 1.3840 max mem: 19788 +Epoch: [13] [ 10/2138] eta: 2:14:42 lr: 3.5096912370258456e-05 loss: 0.0323 (0.0333) time: 3.7982 data: 0.1287 max mem: 19788 +Epoch: [13] [ 20/2138] eta: 2:11:17 lr: 3.509143935721177e-05 loss: 0.0306 (0.0336) time: 3.6389 data: 0.0027 max mem: 19788 +Epoch: [13] [ 30/2138] eta: 2:09:36 lr: 3.508596624931958e-05 loss: 0.0307 (0.0328) time: 3.6292 data: 0.0028 max mem: 19788 +Epoch: [13] [ 40/2138] eta: 2:08:33 lr: 3.508049304656379e-05 loss: 0.0356 (0.0386) time: 3.6319 data: 0.0030 max mem: 19788 +Epoch: [13] [ 50/2138] eta: 2:07:33 lr: 3.507501974892631e-05 loss: 0.0434 (0.0388) time: 3.6285 data: 0.0029 max mem: 19788 +Epoch: [13] [ 60/2138] eta: 2:06:42 lr: 3.506954635638904e-05 loss: 0.0300 (0.0374) time: 3.6210 data: 0.0029 max mem: 19788 +Epoch: [13] [ 70/2138] eta: 2:05:57 lr: 3.5064072868933884e-05 loss: 0.0255 (0.0364) time: 3.6271 data: 0.0030 max mem: 19788 +Epoch: [13] [ 80/2138] eta: 2:05:14 lr: 3.505859928654273e-05 loss: 0.0361 (0.0371) time: 3.6307 data: 0.0030 max mem: 19788 +Epoch: [13] [ 90/2138] eta: 2:04:31 lr: 3.505312560919746e-05 loss: 0.0391 (0.0376) time: 3.6265 data: 0.0034 max mem: 19788 +Epoch: [13] [ 100/2138] eta: 2:03:50 lr: 3.5047651836879956e-05 loss: 0.0327 (0.0374) time: 3.6226 data: 0.0037 max mem: 19788 +Epoch: [13] [ 110/2138] eta: 2:03:10 lr: 3.504217796957209e-05 loss: 0.0347 (0.0385) time: 3.6258 data: 0.0033 max mem: 19788 +Epoch: [13] [ 120/2138] eta: 2:02:30 lr: 3.503670400725572e-05 loss: 0.0376 (0.0387) time: 3.6252 data: 0.0030 max mem: 19788 +Epoch: [13] [ 130/2138] eta: 2:01:54 lr: 3.5031229949912705e-05 loss: 0.0367 (0.0390) time: 3.6318 data: 0.0030 max mem: 19788 +Epoch: [13] [ 140/2138] eta: 2:01:17 lr: 3.502575579752489e-05 loss: 0.0340 (0.0390) time: 3.6417 data: 0.0028 max mem: 19788 +Epoch: [13] [ 150/2138] eta: 2:00:40 lr: 3.5020281550074135e-05 loss: 0.0320 (0.0384) time: 3.6388 data: 0.0029 max mem: 19788 +Epoch: [13] [ 160/2138] eta: 2:00:02 lr: 3.5014807207542264e-05 loss: 0.0341 (0.0403) time: 3.6354 data: 0.0029 max mem: 19788 +Epoch: [13] [ 170/2138] eta: 1:59:25 lr: 3.500933276991111e-05 loss: 0.0434 (0.0403) time: 3.6322 data: 0.0028 max mem: 19788 +Epoch: [13] [ 180/2138] eta: 1:58:48 lr: 3.5003858237162494e-05 loss: 0.0413 (0.0406) time: 3.6355 data: 0.0030 max mem: 19788 +Epoch: [13] [ 190/2138] eta: 1:58:13 lr: 3.499838360927825e-05 loss: 0.0358 (0.0402) time: 3.6446 data: 0.0030 max mem: 19788 +Epoch: [13] [ 200/2138] eta: 1:57:37 lr: 3.4992908886240175e-05 loss: 0.0297 (0.0396) time: 3.6494 data: 0.0029 max mem: 19788 +Epoch: [13] [ 210/2138] eta: 1:57:01 lr: 3.498743406803008e-05 loss: 0.0342 (0.0397) time: 3.6473 data: 0.0030 max mem: 19788 +Epoch: [13] [ 220/2138] eta: 1:56:23 lr: 3.4981959154629753e-05 loss: 0.0367 (0.0395) time: 3.6373 data: 0.0029 max mem: 19788 +Epoch: [13] [ 230/2138] eta: 1:55:46 lr: 3.4976484146020995e-05 loss: 0.0351 (0.0397) time: 3.6300 data: 0.0029 max mem: 19788 +Epoch: [13] [ 240/2138] eta: 1:55:09 lr: 3.497100904218558e-05 loss: 0.0403 (0.0398) time: 3.6332 data: 0.0029 max mem: 19788 +Epoch: [13] [ 250/2138] eta: 1:54:34 lr: 3.4965533843105296e-05 loss: 0.0350 (0.0396) time: 3.6458 data: 0.0029 max mem: 19788 +Epoch: [13] [ 260/2138] eta: 1:53:57 lr: 3.496005854876191e-05 loss: 0.0310 (0.0393) time: 3.6430 data: 0.0028 max mem: 19788 +Epoch: [13] [ 270/2138] eta: 1:53:22 lr: 3.4954583159137195e-05 loss: 0.0316 (0.0394) time: 3.6442 data: 0.0030 max mem: 19788 +Epoch: [13] [ 280/2138] eta: 1:52:44 lr: 3.49491076742129e-05 loss: 0.0329 (0.0392) time: 3.6438 data: 0.0031 max mem: 19788 +Epoch: [13] [ 290/2138] eta: 1:52:07 lr: 3.4943632093970766e-05 loss: 0.0329 (0.0391) time: 3.6311 data: 0.0031 max mem: 19788 +Epoch: [13] [ 300/2138] eta: 1:51:31 lr: 3.493815641839255e-05 loss: 0.0314 (0.0389) time: 3.6322 data: 0.0030 max mem: 19788 +Epoch: [13] [ 310/2138] eta: 1:50:53 lr: 3.493268064746001e-05 loss: 0.0347 (0.0390) time: 3.6302 data: 0.0029 max mem: 19788 +Epoch: [13] [ 320/2138] eta: 1:50:16 lr: 3.4927204781154835e-05 loss: 0.0350 (0.0389) time: 3.6287 data: 0.0029 max mem: 19788 +Epoch: [13] [ 330/2138] eta: 1:49:39 lr: 3.492172881945878e-05 loss: 0.0367 (0.0389) time: 3.6265 data: 0.0028 max mem: 19788 +Epoch: [13] [ 340/2138] eta: 1:49:02 lr: 3.4916252762353544e-05 loss: 0.0357 (0.0388) time: 3.6236 data: 0.0028 max mem: 19788 +Epoch: [13] [ 350/2138] eta: 1:48:25 lr: 3.4910776609820854e-05 loss: 0.0345 (0.0388) time: 3.6252 data: 0.0029 max mem: 19788 +Epoch: [13] [ 360/2138] eta: 1:47:48 lr: 3.4905300361842405e-05 loss: 0.0369 (0.0388) time: 3.6295 data: 0.0029 max mem: 19788 +Epoch: [13] [ 370/2138] eta: 1:47:11 lr: 3.489982401839989e-05 loss: 0.0384 (0.0389) time: 3.6299 data: 0.0028 max mem: 19788 +Epoch: [13] [ 380/2138] eta: 1:46:35 lr: 3.489434757947502e-05 loss: 0.0389 (0.0389) time: 3.6319 data: 0.0027 max mem: 19788 +Epoch: [13] [ 390/2138] eta: 1:45:58 lr: 3.4888871045049466e-05 loss: 0.0389 (0.0389) time: 3.6347 data: 0.0029 max mem: 19788 +Epoch: [13] [ 400/2138] eta: 1:45:22 lr: 3.488339441510489e-05 loss: 0.0354 (0.0388) time: 3.6339 data: 0.0031 max mem: 19788 +Epoch: [13] [ 410/2138] eta: 1:44:45 lr: 3.4877917689622994e-05 loss: 0.0382 (0.0390) time: 3.6338 data: 0.0031 max mem: 19788 +Epoch: [13] [ 420/2138] eta: 1:44:09 lr: 3.487244086858542e-05 loss: 0.0375 (0.0390) time: 3.6328 data: 0.0031 max mem: 19788 +Epoch: [13] [ 430/2138] eta: 1:43:32 lr: 3.486696395197383e-05 loss: 0.0345 (0.0391) time: 3.6337 data: 0.0029 max mem: 19788 +Epoch: [13] [ 440/2138] eta: 1:42:56 lr: 3.486148693976989e-05 loss: 0.0389 (0.0392) time: 3.6358 data: 0.0029 max mem: 19788 +Epoch: [13] [ 450/2138] eta: 1:42:19 lr: 3.4856009831955216e-05 loss: 0.0379 (0.0392) time: 3.6341 data: 0.0031 max mem: 19788 +Epoch: [13] [ 460/2138] eta: 1:41:43 lr: 3.4850532628511466e-05 loss: 0.0364 (0.0392) time: 3.6317 data: 0.0032 max mem: 19788 +Epoch: [13] [ 470/2138] eta: 1:41:06 lr: 3.4845055329420274e-05 loss: 0.0347 (0.0391) time: 3.6334 data: 0.0030 max mem: 19788 +Epoch: [13] [ 480/2138] eta: 1:40:30 lr: 3.4839577934663244e-05 loss: 0.0347 (0.0392) time: 3.6357 data: 0.0030 max mem: 19788 +Epoch: [13] [ 490/2138] eta: 1:39:53 lr: 3.4834100444222e-05 loss: 0.0325 (0.0391) time: 3.6346 data: 0.0029 max mem: 19788 +Epoch: [13] [ 500/2138] eta: 1:39:17 lr: 3.482862285807816e-05 loss: 0.0313 (0.0391) time: 3.6351 data: 0.0028 max mem: 19788 +Epoch: [13] [ 510/2138] eta: 1:38:40 lr: 3.482314517621333e-05 loss: 0.0369 (0.0391) time: 3.6336 data: 0.0029 max mem: 19788 +Epoch: [13] [ 520/2138] eta: 1:38:04 lr: 3.48176673986091e-05 loss: 0.0365 (0.0391) time: 3.6312 data: 0.0028 max mem: 19788 +Epoch: [13] [ 530/2138] eta: 1:37:28 lr: 3.481218952524704e-05 loss: 0.0334 (0.0391) time: 3.6410 data: 0.0029 max mem: 19788 +Epoch: [13] [ 540/2138] eta: 1:36:52 lr: 3.480671155610877e-05 loss: 0.0366 (0.0392) time: 3.6465 data: 0.0031 max mem: 19788 +Epoch: [13] [ 550/2138] eta: 1:36:15 lr: 3.480123349117586e-05 loss: 0.0382 (0.0391) time: 3.6440 data: 0.0031 max mem: 19788 +Epoch: [13] [ 560/2138] eta: 1:35:39 lr: 3.479575533042985e-05 loss: 0.0374 (0.0391) time: 3.6382 data: 0.0031 max mem: 19788 +Epoch: [13] [ 570/2138] eta: 1:35:03 lr: 3.479027707385233e-05 loss: 0.0386 (0.0392) time: 3.6334 data: 0.0031 max mem: 19788 +Epoch: [13] [ 580/2138] eta: 1:34:26 lr: 3.4784798721424846e-05 loss: 0.0401 (0.0392) time: 3.6319 data: 0.0030 max mem: 19788 +Epoch: [13] [ 590/2138] eta: 1:33:49 lr: 3.477932027312896e-05 loss: 0.0406 (0.0392) time: 3.6268 data: 0.0029 max mem: 19788 +Epoch: [13] [ 600/2138] eta: 1:33:13 lr: 3.4773841728946195e-05 loss: 0.0340 (0.0392) time: 3.6273 data: 0.0029 max mem: 19788 +Epoch: [13] [ 610/2138] eta: 1:32:36 lr: 3.47683630888581e-05 loss: 0.0352 (0.0393) time: 3.6255 data: 0.0031 max mem: 19788 +Epoch: [13] [ 620/2138] eta: 1:31:59 lr: 3.4762884352846206e-05 loss: 0.0366 (0.0393) time: 3.6245 data: 0.0030 max mem: 19788 +Epoch: [13] [ 630/2138] eta: 1:31:23 lr: 3.4757405520892026e-05 loss: 0.0359 (0.0393) time: 3.6266 data: 0.0028 max mem: 19788 +Epoch: [13] [ 640/2138] eta: 1:30:46 lr: 3.4751926592977076e-05 loss: 0.0292 (0.0392) time: 3.6253 data: 0.0030 max mem: 19788 +Epoch: [13] [ 650/2138] eta: 1:30:09 lr: 3.4746447569082865e-05 loss: 0.0335 (0.0392) time: 3.6242 data: 0.0029 max mem: 19788 +Epoch: [13] [ 660/2138] eta: 1:29:33 lr: 3.474096844919091e-05 loss: 0.0369 (0.0392) time: 3.6264 data: 0.0030 max mem: 19788 +Epoch: [13] [ 670/2138] eta: 1:28:57 lr: 3.473548923328269e-05 loss: 0.0350 (0.0392) time: 3.6312 data: 0.0030 max mem: 19788 +Epoch: [13] [ 680/2138] eta: 1:28:20 lr: 3.473000992133969e-05 loss: 0.0350 (0.0392) time: 3.6309 data: 0.0027 max mem: 19788 +Epoch: [13] [ 690/2138] eta: 1:27:43 lr: 3.472453051334341e-05 loss: 0.0356 (0.0393) time: 3.6243 data: 0.0029 max mem: 19788 +Epoch: [13] [ 700/2138] eta: 1:27:07 lr: 3.4719051009275306e-05 loss: 0.0397 (0.0393) time: 3.6243 data: 0.0030 max mem: 19788 +Epoch: [13] [ 710/2138] eta: 1:26:31 lr: 3.4713571409116846e-05 loss: 0.0371 (0.0392) time: 3.6328 data: 0.0029 max mem: 19788 +Epoch: [13] [ 720/2138] eta: 1:25:54 lr: 3.470809171284951e-05 loss: 0.0357 (0.0393) time: 3.6306 data: 0.0030 max mem: 19788 +Epoch: [13] [ 730/2138] eta: 1:25:18 lr: 3.470261192045474e-05 loss: 0.0343 (0.0393) time: 3.6275 data: 0.0031 max mem: 19788 +Epoch: [13] [ 740/2138] eta: 1:24:41 lr: 3.4697132031913977e-05 loss: 0.0306 (0.0392) time: 3.6258 data: 0.0031 max mem: 19788 +Epoch: [13] [ 750/2138] eta: 1:24:05 lr: 3.4691652047208664e-05 loss: 0.0304 (0.0391) time: 3.6255 data: 0.0030 max mem: 19788 +Epoch: [13] [ 760/2138] eta: 1:23:28 lr: 3.4686171966320246e-05 loss: 0.0378 (0.0392) time: 3.6298 data: 0.0029 max mem: 19788 +Epoch: [13] [ 770/2138] eta: 1:22:52 lr: 3.468069178923015e-05 loss: 0.0388 (0.0392) time: 3.6333 data: 0.0029 max mem: 19788 +Epoch: [13] [ 780/2138] eta: 1:22:15 lr: 3.467521151591978e-05 loss: 0.0379 (0.0392) time: 3.6365 data: 0.0028 max mem: 19788 +Epoch: [13] [ 790/2138] eta: 1:21:39 lr: 3.4669731146370555e-05 loss: 0.0379 (0.0393) time: 3.6363 data: 0.0027 max mem: 19788 +Epoch: [13] [ 800/2138] eta: 1:21:03 lr: 3.4664250680563884e-05 loss: 0.0347 (0.0392) time: 3.6306 data: 0.0030 max mem: 19788 +Epoch: [13] [ 810/2138] eta: 1:20:26 lr: 3.465877011848117e-05 loss: 0.0325 (0.0391) time: 3.6302 data: 0.0030 max mem: 19788 +Epoch: [13] [ 820/2138] eta: 1:19:50 lr: 3.46532894601038e-05 loss: 0.0352 (0.0391) time: 3.6323 data: 0.0031 max mem: 19788 +Epoch: [13] [ 830/2138] eta: 1:19:13 lr: 3.4647808705413164e-05 loss: 0.0364 (0.0391) time: 3.6305 data: 0.0031 max mem: 19788 +Epoch: [13] [ 840/2138] eta: 1:18:37 lr: 3.4642327854390634e-05 loss: 0.0313 (0.0390) time: 3.6327 data: 0.0032 max mem: 19788 +Epoch: [13] [ 850/2138] eta: 1:18:01 lr: 3.463684690701759e-05 loss: 0.0314 (0.0390) time: 3.6339 data: 0.0032 max mem: 19788 +Epoch: [13] [ 860/2138] eta: 1:17:24 lr: 3.4631365863275386e-05 loss: 0.0379 (0.0392) time: 3.6309 data: 0.0030 max mem: 19788 +Epoch: [13] [ 870/2138] eta: 1:16:48 lr: 3.462588472314539e-05 loss: 0.0382 (0.0392) time: 3.6328 data: 0.0029 max mem: 19788 +Epoch: [13] [ 880/2138] eta: 1:16:12 lr: 3.462040348660895e-05 loss: 0.0346 (0.0392) time: 3.6393 data: 0.0028 max mem: 19788 +Epoch: [13] [ 890/2138] eta: 1:15:35 lr: 3.461492215364742e-05 loss: 0.0345 (0.0391) time: 3.6389 data: 0.0028 max mem: 19788 +Epoch: [13] [ 900/2138] eta: 1:14:59 lr: 3.4609440724242115e-05 loss: 0.0348 (0.0392) time: 3.6321 data: 0.0028 max mem: 19788 +Epoch: [13] [ 910/2138] eta: 1:14:23 lr: 3.460395919837438e-05 loss: 0.0428 (0.0394) time: 3.6299 data: 0.0029 max mem: 19788 +Epoch: [13] [ 920/2138] eta: 1:13:46 lr: 3.459847757602554e-05 loss: 0.0349 (0.0393) time: 3.6279 data: 0.0028 max mem: 19788 +Epoch: [13] [ 930/2138] eta: 1:13:10 lr: 3.459299585717692e-05 loss: 0.0336 (0.0394) time: 3.6355 data: 0.0027 max mem: 19788 +Epoch: [13] [ 940/2138] eta: 1:12:34 lr: 3.45875140418098e-05 loss: 0.0408 (0.0395) time: 3.6382 data: 0.0027 max mem: 19788 +Epoch: [13] [ 950/2138] eta: 1:11:57 lr: 3.458203212990551e-05 loss: 0.0427 (0.0396) time: 3.6291 data: 0.0029 max mem: 19788 +Epoch: [13] [ 960/2138] eta: 1:11:21 lr: 3.457655012144534e-05 loss: 0.0375 (0.0396) time: 3.6294 data: 0.0030 max mem: 19788 +Epoch: [13] [ 970/2138] eta: 1:10:45 lr: 3.4571068016410576e-05 loss: 0.0361 (0.0396) time: 3.6380 data: 0.0029 max mem: 19788 +Epoch: [13] [ 980/2138] eta: 1:10:08 lr: 3.45655858147825e-05 loss: 0.0337 (0.0395) time: 3.6402 data: 0.0032 max mem: 19788 +Epoch: [13] [ 990/2138] eta: 1:09:32 lr: 3.4560103516542385e-05 loss: 0.0346 (0.0395) time: 3.6335 data: 0.0031 max mem: 19788 +Epoch: [13] [1000/2138] eta: 1:08:56 lr: 3.455462112167151e-05 loss: 0.0362 (0.0395) time: 3.6356 data: 0.0029 max mem: 19788 +Epoch: [13] [1010/2138] eta: 1:08:19 lr: 3.4549138630151125e-05 loss: 0.0357 (0.0394) time: 3.6364 data: 0.0029 max mem: 19788 +Epoch: [13] [1020/2138] eta: 1:07:43 lr: 3.4543656041962485e-05 loss: 0.0330 (0.0393) time: 3.6393 data: 0.0028 max mem: 19788 +Epoch: [13] [1030/2138] eta: 1:07:07 lr: 3.4538173357086844e-05 loss: 0.0327 (0.0393) time: 3.6427 data: 0.0029 max mem: 19788 +Epoch: [13] [1040/2138] eta: 1:06:30 lr: 3.453269057550544e-05 loss: 0.0361 (0.0393) time: 3.6351 data: 0.0030 max mem: 19788 +Epoch: [13] [1050/2138] eta: 1:05:54 lr: 3.452720769719951e-05 loss: 0.0351 (0.0393) time: 3.6307 data: 0.0028 max mem: 19788 +Epoch: [13] [1060/2138] eta: 1:05:18 lr: 3.452172472215027e-05 loss: 0.0368 (0.0393) time: 3.6328 data: 0.0026 max mem: 19788 +Epoch: [13] [1070/2138] eta: 1:04:41 lr: 3.4516241650338946e-05 loss: 0.0368 (0.0393) time: 3.6320 data: 0.0029 max mem: 19788 +Epoch: [13] [1080/2138] eta: 1:04:05 lr: 3.4510758481746757e-05 loss: 0.0350 (0.0393) time: 3.6342 data: 0.0029 max mem: 19788 +Epoch: [13] [1090/2138] eta: 1:03:29 lr: 3.45052752163549e-05 loss: 0.0350 (0.0392) time: 3.6390 data: 0.0028 max mem: 19788 +Epoch: [13] [1100/2138] eta: 1:02:52 lr: 3.449979185414458e-05 loss: 0.0368 (0.0393) time: 3.6397 data: 0.0028 max mem: 19788 +Epoch: [13] [1110/2138] eta: 1:02:16 lr: 3.449430839509698e-05 loss: 0.0368 (0.0393) time: 3.6478 data: 0.0028 max mem: 19788 +Epoch: [13] [1120/2138] eta: 1:01:40 lr: 3.44888248391933e-05 loss: 0.0360 (0.0393) time: 3.6430 data: 0.0028 max mem: 19788 +Epoch: [13] [1130/2138] eta: 1:01:03 lr: 3.44833411864147e-05 loss: 0.0360 (0.0393) time: 3.6324 data: 0.0029 max mem: 19788 +Epoch: [13] [1140/2138] eta: 1:00:27 lr: 3.4477857436742364e-05 loss: 0.0367 (0.0393) time: 3.6367 data: 0.0029 max mem: 19788 +Epoch: [13] [1150/2138] eta: 0:59:51 lr: 3.4472373590157445e-05 loss: 0.0365 (0.0393) time: 3.6401 data: 0.0028 max mem: 19788 +Epoch: [13] [1160/2138] eta: 0:59:14 lr: 3.446688964664111e-05 loss: 0.0362 (0.0393) time: 3.6354 data: 0.0029 max mem: 19788 +Epoch: [13] [1170/2138] eta: 0:58:38 lr: 3.446140560617451e-05 loss: 0.0395 (0.0393) time: 3.6351 data: 0.0030 max mem: 19788 +Epoch: [13] [1180/2138] eta: 0:58:02 lr: 3.445592146873877e-05 loss: 0.0384 (0.0393) time: 3.6356 data: 0.0028 max mem: 19788 +Epoch: [13] [1190/2138] eta: 0:57:25 lr: 3.445043723431505e-05 loss: 0.0372 (0.0393) time: 3.6274 data: 0.0027 max mem: 19788 +Epoch: [13] [1200/2138] eta: 0:56:49 lr: 3.4444952902884465e-05 loss: 0.0376 (0.0394) time: 3.6302 data: 0.0028 max mem: 19788 +Epoch: [13] [1210/2138] eta: 0:56:13 lr: 3.443946847442814e-05 loss: 0.0407 (0.0394) time: 3.6382 data: 0.0028 max mem: 19788 +Epoch: [13] [1220/2138] eta: 0:55:37 lr: 3.4433983948927185e-05 loss: 0.0376 (0.0394) time: 3.6547 data: 0.0028 max mem: 19788 +Epoch: [13] [1230/2138] eta: 0:55:00 lr: 3.442849932636272e-05 loss: 0.0331 (0.0394) time: 3.6503 data: 0.0030 max mem: 19788 +Epoch: [13] [1240/2138] eta: 0:54:24 lr: 3.442301460671584e-05 loss: 0.0349 (0.0394) time: 3.6302 data: 0.0031 max mem: 19788 +Epoch: [13] [1250/2138] eta: 0:53:47 lr: 3.4417529789967626e-05 loss: 0.0360 (0.0394) time: 3.6293 data: 0.0030 max mem: 19788 +Epoch: [13] [1260/2138] eta: 0:53:11 lr: 3.4412044876099176e-05 loss: 0.0369 (0.0394) time: 3.6300 data: 0.0030 max mem: 19788 +Epoch: [13] [1270/2138] eta: 0:52:35 lr: 3.440655986509157e-05 loss: 0.0381 (0.0394) time: 3.6266 data: 0.0030 max mem: 19788 +Epoch: [13] [1280/2138] eta: 0:51:58 lr: 3.4401074756925895e-05 loss: 0.0381 (0.0394) time: 3.6270 data: 0.0028 max mem: 19788 +Epoch: [13] [1290/2138] eta: 0:51:22 lr: 3.439558955158319e-05 loss: 0.0394 (0.0395) time: 3.6343 data: 0.0028 max mem: 19788 +Epoch: [13] [1300/2138] eta: 0:50:46 lr: 3.4390104249044524e-05 loss: 0.0334 (0.0395) time: 3.6400 data: 0.0029 max mem: 19788 +Epoch: [13] [1310/2138] eta: 0:50:09 lr: 3.438461884929095e-05 loss: 0.0332 (0.0395) time: 3.6459 data: 0.0029 max mem: 19788 +Epoch: [13] [1320/2138] eta: 0:49:33 lr: 3.437913335230352e-05 loss: 0.0372 (0.0396) time: 3.6510 data: 0.0028 max mem: 19788 +Epoch: [13] [1330/2138] eta: 0:48:57 lr: 3.437364775806326e-05 loss: 0.0342 (0.0395) time: 3.6396 data: 0.0027 max mem: 19788 +Epoch: [13] [1340/2138] eta: 0:48:20 lr: 3.43681620665512e-05 loss: 0.0322 (0.0395) time: 3.6306 data: 0.0027 max mem: 19788 +Epoch: [13] [1350/2138] eta: 0:47:44 lr: 3.436267627774838e-05 loss: 0.0407 (0.0396) time: 3.6325 data: 0.0028 max mem: 19788 +Epoch: [13] [1360/2138] eta: 0:47:08 lr: 3.4357190391635796e-05 loss: 0.0399 (0.0396) time: 3.6304 data: 0.0029 max mem: 19788 +Epoch: [13] [1370/2138] eta: 0:46:31 lr: 3.4351704408194464e-05 loss: 0.0407 (0.0397) time: 3.6278 data: 0.0028 max mem: 19788 +Epoch: [13] [1380/2138] eta: 0:45:55 lr: 3.434621832740539e-05 loss: 0.0425 (0.0397) time: 3.6380 data: 0.0028 max mem: 19788 +Epoch: [13] [1390/2138] eta: 0:45:18 lr: 3.4340732149249566e-05 loss: 0.0386 (0.0398) time: 3.6396 data: 0.0029 max mem: 19788 +Epoch: [13] [1400/2138] eta: 0:44:42 lr: 3.4335245873707986e-05 loss: 0.0385 (0.0398) time: 3.6295 data: 0.0029 max mem: 19788 +Epoch: [13] [1410/2138] eta: 0:44:06 lr: 3.4329759500761615e-05 loss: 0.0325 (0.0398) time: 3.6295 data: 0.0028 max mem: 19788 +Epoch: [13] [1420/2138] eta: 0:43:29 lr: 3.432427303039143e-05 loss: 0.0321 (0.0397) time: 3.6304 data: 0.0028 max mem: 19788 +Epoch: [13] [1430/2138] eta: 0:42:53 lr: 3.431878646257843e-05 loss: 0.0374 (0.0397) time: 3.6353 data: 0.0027 max mem: 19788 +Epoch: [13] [1440/2138] eta: 0:42:17 lr: 3.4313299797303534e-05 loss: 0.0390 (0.0397) time: 3.6410 data: 0.0028 max mem: 19788 +Epoch: [13] [1450/2138] eta: 0:41:40 lr: 3.430781303454771e-05 loss: 0.0421 (0.0398) time: 3.6368 data: 0.0028 max mem: 19788 +Epoch: [13] [1460/2138] eta: 0:41:04 lr: 3.4302326174291906e-05 loss: 0.0421 (0.0398) time: 3.6309 data: 0.0029 max mem: 19788 +Epoch: [13] [1470/2138] eta: 0:40:28 lr: 3.429683921651705e-05 loss: 0.0373 (0.0398) time: 3.6335 data: 0.0029 max mem: 19788 +Epoch: [13] [1480/2138] eta: 0:39:51 lr: 3.4291352161204096e-05 loss: 0.0355 (0.0398) time: 3.6379 data: 0.0031 max mem: 19788 +Epoch: [13] [1490/2138] eta: 0:39:15 lr: 3.428586500833394e-05 loss: 0.0409 (0.0398) time: 3.6340 data: 0.0032 max mem: 19788 +Epoch: [13] [1500/2138] eta: 0:38:39 lr: 3.428037775788751e-05 loss: 0.0416 (0.0398) time: 3.6341 data: 0.0029 max mem: 19788 +Epoch: [13] [1510/2138] eta: 0:38:02 lr: 3.427489040984572e-05 loss: 0.0428 (0.0398) time: 3.6342 data: 0.0029 max mem: 19788 +Epoch: [13] [1520/2138] eta: 0:37:26 lr: 3.4269402964189476e-05 loss: 0.0345 (0.0398) time: 3.6314 data: 0.0029 max mem: 19788 +Epoch: [13] [1530/2138] eta: 0:36:50 lr: 3.426391542089966e-05 loss: 0.0345 (0.0398) time: 3.6345 data: 0.0030 max mem: 19788 +Epoch: [13] [1540/2138] eta: 0:36:13 lr: 3.425842777995718e-05 loss: 0.0334 (0.0398) time: 3.6375 data: 0.0029 max mem: 19788 +Epoch: [13] [1550/2138] eta: 0:35:37 lr: 3.4252940041342894e-05 loss: 0.0333 (0.0398) time: 3.6403 data: 0.0029 max mem: 19788 +Epoch: [13] [1560/2138] eta: 0:35:01 lr: 3.424745220503768e-05 loss: 0.0362 (0.0398) time: 3.6430 data: 0.0032 max mem: 19788 +Epoch: [13] [1570/2138] eta: 0:34:24 lr: 3.424196427102242e-05 loss: 0.0362 (0.0398) time: 3.6370 data: 0.0031 max mem: 19788 +Epoch: [13] [1580/2138] eta: 0:33:48 lr: 3.423647623927797e-05 loss: 0.0341 (0.0397) time: 3.6306 data: 0.0031 max mem: 19788 +Epoch: [13] [1590/2138] eta: 0:33:11 lr: 3.423098810978518e-05 loss: 0.0369 (0.0399) time: 3.6365 data: 0.0031 max mem: 19788 +Epoch: [13] [1600/2138] eta: 0:32:35 lr: 3.422549988252488e-05 loss: 0.0443 (0.0399) time: 3.6388 data: 0.0030 max mem: 19788 +Epoch: [13] [1610/2138] eta: 0:31:59 lr: 3.4220011557477924e-05 loss: 0.0391 (0.0399) time: 3.6374 data: 0.0029 max mem: 19788 +Epoch: [13] [1620/2138] eta: 0:31:22 lr: 3.421452313462515e-05 loss: 0.0344 (0.0399) time: 3.6358 data: 0.0027 max mem: 19788 +Epoch: [13] [1630/2138] eta: 0:30:46 lr: 3.420903461394738e-05 loss: 0.0391 (0.0399) time: 3.6344 data: 0.0028 max mem: 19788 +Epoch: [13] [1640/2138] eta: 0:30:10 lr: 3.420354599542541e-05 loss: 0.0385 (0.0399) time: 3.6309 data: 0.0031 max mem: 19788 +Epoch: [13] [1650/2138] eta: 0:29:33 lr: 3.419805727904006e-05 loss: 0.0309 (0.0399) time: 3.6290 data: 0.0032 max mem: 19788 +Epoch: [13] [1660/2138] eta: 0:28:57 lr: 3.419256846477214e-05 loss: 0.0313 (0.0398) time: 3.6325 data: 0.0029 max mem: 19788 +Epoch: [13] [1670/2138] eta: 0:28:21 lr: 3.418707955260245e-05 loss: 0.0318 (0.0398) time: 3.6390 data: 0.0027 max mem: 19788 +Epoch: [13] [1680/2138] eta: 0:27:44 lr: 3.418159054251176e-05 loss: 0.0359 (0.0398) time: 3.6323 data: 0.0029 max mem: 19788 +Epoch: [13] [1690/2138] eta: 0:27:08 lr: 3.417610143448086e-05 loss: 0.0388 (0.0398) time: 3.6301 data: 0.0028 max mem: 19788 +Epoch: [13] [1700/2138] eta: 0:26:32 lr: 3.417061222849052e-05 loss: 0.0334 (0.0398) time: 3.6363 data: 0.0027 max mem: 19788 +Epoch: [13] [1710/2138] eta: 0:25:55 lr: 3.416512292452152e-05 loss: 0.0316 (0.0398) time: 3.6303 data: 0.0028 max mem: 19788 +Epoch: [13] [1720/2138] eta: 0:25:19 lr: 3.41596335225546e-05 loss: 0.0364 (0.0398) time: 3.6311 data: 0.0030 max mem: 19788 +Epoch: [13] [1730/2138] eta: 0:24:43 lr: 3.415414402257052e-05 loss: 0.0372 (0.0398) time: 3.6361 data: 0.0029 max mem: 19788 +Epoch: [13] [1740/2138] eta: 0:24:06 lr: 3.414865442455004e-05 loss: 0.0341 (0.0398) time: 3.6343 data: 0.0029 max mem: 19788 +Epoch: [13] [1750/2138] eta: 0:23:30 lr: 3.414316472847387e-05 loss: 0.0352 (0.0398) time: 3.6348 data: 0.0028 max mem: 19788 +Epoch: [13] [1760/2138] eta: 0:22:54 lr: 3.413767493432275e-05 loss: 0.0355 (0.0398) time: 3.6522 data: 0.0028 max mem: 19788 +Epoch: [13] [1770/2138] eta: 0:22:17 lr: 3.4132185042077416e-05 loss: 0.0327 (0.0398) time: 3.6487 data: 0.0031 max mem: 19788 +Epoch: [13] [1780/2138] eta: 0:21:41 lr: 3.4126695051718564e-05 loss: 0.0319 (0.0398) time: 3.6323 data: 0.0031 max mem: 19788 +Epoch: [13] [1790/2138] eta: 0:21:05 lr: 3.412120496322693e-05 loss: 0.0319 (0.0398) time: 3.6392 data: 0.0029 max mem: 19788 +Epoch: [13] [1800/2138] eta: 0:20:28 lr: 3.411571477658318e-05 loss: 0.0325 (0.0398) time: 3.6408 data: 0.0027 max mem: 19788 +Epoch: [13] [1810/2138] eta: 0:19:52 lr: 3.411022449176803e-05 loss: 0.0343 (0.0398) time: 3.6374 data: 0.0028 max mem: 19788 +Epoch: [13] [1820/2138] eta: 0:19:15 lr: 3.4104734108762166e-05 loss: 0.0370 (0.0398) time: 3.6354 data: 0.0031 max mem: 19788 +Epoch: [13] [1830/2138] eta: 0:18:39 lr: 3.4099243627546265e-05 loss: 0.0340 (0.0398) time: 3.6322 data: 0.0030 max mem: 19788 +Epoch: [13] [1840/2138] eta: 0:18:03 lr: 3.4093753048100995e-05 loss: 0.0340 (0.0399) time: 3.6351 data: 0.0029 max mem: 19788 +Epoch: [13] [1850/2138] eta: 0:17:26 lr: 3.408826237040704e-05 loss: 0.0369 (0.0399) time: 3.6320 data: 0.0028 max mem: 19788 +Epoch: [13] [1860/2138] eta: 0:16:50 lr: 3.408277159444503e-05 loss: 0.0383 (0.0399) time: 3.6322 data: 0.0030 max mem: 19788 +Epoch: [13] [1870/2138] eta: 0:16:14 lr: 3.407728072019562e-05 loss: 0.0383 (0.0399) time: 3.6408 data: 0.0030 max mem: 19788 +Epoch: [13] [1880/2138] eta: 0:15:37 lr: 3.407178974763947e-05 loss: 0.0352 (0.0399) time: 3.6424 data: 0.0028 max mem: 19788 +Epoch: [13] [1890/2138] eta: 0:15:01 lr: 3.406629867675721e-05 loss: 0.0314 (0.0399) time: 3.6396 data: 0.0028 max mem: 19788 +Epoch: [13] [1900/2138] eta: 0:14:25 lr: 3.406080750752947e-05 loss: 0.0314 (0.0398) time: 3.6325 data: 0.0030 max mem: 19788 +Epoch: [13] [1910/2138] eta: 0:13:48 lr: 3.4055316239936864e-05 loss: 0.0339 (0.0399) time: 3.6348 data: 0.0031 max mem: 19788 +Epoch: [13] [1920/2138] eta: 0:13:12 lr: 3.404982487396e-05 loss: 0.0362 (0.0399) time: 3.6375 data: 0.0029 max mem: 19788 +Epoch: [13] [1930/2138] eta: 0:12:36 lr: 3.404433340957951e-05 loss: 0.0366 (0.0399) time: 3.6311 data: 0.0027 max mem: 19788 +Epoch: [13] [1940/2138] eta: 0:11:59 lr: 3.403884184677597e-05 loss: 0.0393 (0.0399) time: 3.6315 data: 0.0029 max mem: 19788 +Epoch: [13] [1950/2138] eta: 0:11:23 lr: 3.403335018552998e-05 loss: 0.0343 (0.0399) time: 3.6369 data: 0.0030 max mem: 19788 +Epoch: [13] [1960/2138] eta: 0:10:47 lr: 3.402785842582212e-05 loss: 0.0329 (0.0399) time: 3.6410 data: 0.0030 max mem: 19788 +Epoch: [13] [1970/2138] eta: 0:10:10 lr: 3.4022366567632985e-05 loss: 0.0340 (0.0399) time: 3.6410 data: 0.0030 max mem: 19788 +Epoch: [13] [1980/2138] eta: 0:09:34 lr: 3.4016874610943125e-05 loss: 0.0340 (0.0398) time: 3.6399 data: 0.0028 max mem: 19788 +Epoch: [13] [1990/2138] eta: 0:08:58 lr: 3.4011382555733114e-05 loss: 0.0342 (0.0399) time: 3.6411 data: 0.0027 max mem: 19788 +Epoch: [13] [2000/2138] eta: 0:08:21 lr: 3.4005890401983505e-05 loss: 0.0369 (0.0399) time: 3.6481 data: 0.0027 max mem: 19788 +Epoch: [13] [2010/2138] eta: 0:07:45 lr: 3.4000398149674844e-05 loss: 0.0371 (0.0399) time: 3.6420 data: 0.0029 max mem: 19788 +Epoch: [13] [2020/2138] eta: 0:07:08 lr: 3.399490579878768e-05 loss: 0.0375 (0.0399) time: 3.6327 data: 0.0030 max mem: 19788 +Epoch: [13] [2030/2138] eta: 0:06:32 lr: 3.398941334930253e-05 loss: 0.0355 (0.0399) time: 3.6334 data: 0.0030 max mem: 19788 +Epoch: [13] [2040/2138] eta: 0:05:56 lr: 3.398392080119994e-05 loss: 0.0351 (0.0399) time: 3.6278 data: 0.0030 max mem: 19788 +Epoch: [13] [2050/2138] eta: 0:05:19 lr: 3.397842815446041e-05 loss: 0.0357 (0.0399) time: 3.6261 data: 0.0029 max mem: 19788 +Epoch: [13] [2060/2138] eta: 0:04:43 lr: 3.3972935409064476e-05 loss: 0.0382 (0.0399) time: 3.6279 data: 0.0028 max mem: 19788 +Epoch: [13] [2070/2138] eta: 0:04:07 lr: 3.396744256499262e-05 loss: 0.0428 (0.0399) time: 3.6309 data: 0.0029 max mem: 19788 +Epoch: [13] [2080/2138] eta: 0:03:30 lr: 3.396194962222534e-05 loss: 0.0380 (0.0399) time: 3.6322 data: 0.0030 max mem: 19788 +Epoch: [13] [2090/2138] eta: 0:02:54 lr: 3.395645658074314e-05 loss: 0.0352 (0.0399) time: 3.6396 data: 0.0028 max mem: 19788 +Epoch: [13] [2100/2138] eta: 0:02:18 lr: 3.3950963440526494e-05 loss: 0.0348 (0.0399) time: 3.6455 data: 0.0027 max mem: 19788 +Epoch: [13] [2110/2138] eta: 0:01:41 lr: 3.394547020155588e-05 loss: 0.0449 (0.0400) time: 3.6409 data: 0.0028 max mem: 19788 +Epoch: [13] [2120/2138] eta: 0:01:05 lr: 3.393997686381176e-05 loss: 0.0471 (0.0400) time: 3.6392 data: 0.0028 max mem: 19788 +Epoch: [13] [2130/2138] eta: 0:00:29 lr: 3.3934483427274595e-05 loss: 0.0397 (0.0400) time: 3.6249 data: 0.0026 max mem: 19788 +Epoch: [13] Total time: 2:09:32 +Test: [ 0/21770] eta: 19:33:30 time: 3.2343 data: 3.1388 max mem: 19788 +Test: [ 100/21770] eta: 0:36:27 time: 0.0608 data: 0.0018 max mem: 19788 +Test: [ 200/21770] eta: 0:29:35 time: 0.0631 data: 0.0018 max mem: 19788 +Test: [ 300/21770] eta: 0:27:49 time: 0.0624 data: 0.0020 max mem: 19788 +Test: [ 400/21770] eta: 0:26:41 time: 0.0820 data: 0.0024 max mem: 19788 +Test: [ 500/21770] eta: 0:26:01 time: 0.0695 data: 0.0020 max mem: 19788 +Test: [ 600/21770] eta: 0:25:24 time: 0.0629 data: 0.0018 max mem: 19788 +Test: [ 700/21770] eta: 0:24:58 time: 0.0688 data: 0.0018 max mem: 19788 +Test: [ 800/21770] eta: 0:24:47 time: 0.0745 data: 0.0017 max mem: 19788 +Test: [ 900/21770] eta: 0:24:19 time: 0.0630 data: 0.0021 max mem: 19788 +Test: [ 1000/21770] eta: 0:24:04 time: 0.0618 data: 0.0017 max mem: 19788 +Test: [ 1100/21770] eta: 0:23:56 time: 0.0637 data: 0.0018 max mem: 19788 +Test: [ 1200/21770] eta: 0:23:40 time: 0.0608 data: 0.0018 max mem: 19788 +Test: [ 1300/21770] eta: 0:23:33 time: 0.0693 data: 0.0022 max mem: 19788 +Test: [ 1400/21770] eta: 0:23:23 time: 0.0645 data: 0.0019 max mem: 19788 +Test: [ 1500/21770] eta: 0:23:12 time: 0.0663 data: 0.0020 max mem: 19788 +Test: [ 1600/21770] eta: 0:23:02 time: 0.0649 data: 0.0018 max mem: 19788 +Test: [ 1700/21770] eta: 0:22:48 time: 0.0663 data: 0.0020 max mem: 19788 +Test: [ 1800/21770] eta: 0:22:43 time: 0.0625 data: 0.0017 max mem: 19788 +Test: [ 1900/21770] eta: 0:22:32 time: 0.0760 data: 0.0023 max mem: 19788 +Test: [ 2000/21770] eta: 0:22:21 time: 0.0770 data: 0.0022 max mem: 19788 +Test: [ 2100/21770] eta: 0:22:15 time: 0.0664 data: 0.0021 max mem: 19788 +Test: [ 2200/21770] eta: 0:22:07 time: 0.0643 data: 0.0019 max mem: 19788 +Test: [ 2300/21770] eta: 0:21:55 time: 0.0605 data: 0.0019 max mem: 19788 +Test: [ 2400/21770] eta: 0:21:47 time: 0.0702 data: 0.0019 max mem: 19788 +Test: [ 2500/21770] eta: 0:21:44 time: 0.0695 data: 0.0019 max mem: 19788 +Test: [ 2600/21770] eta: 0:21:39 time: 0.0699 data: 0.0023 max mem: 19788 +Test: [ 2700/21770] eta: 0:21:33 time: 0.0641 data: 0.0019 max mem: 19788 +Test: [ 2800/21770] eta: 0:21:25 time: 0.0778 data: 0.0019 max mem: 19788 +Test: [ 2900/21770] eta: 0:21:17 time: 0.0685 data: 0.0020 max mem: 19788 +Test: [ 3000/21770] eta: 0:21:08 time: 0.0751 data: 0.0020 max mem: 19788 +Test: [ 3100/21770] eta: 0:21:04 time: 0.0765 data: 0.0020 max mem: 19788 +Test: [ 3200/21770] eta: 0:20:57 time: 0.0614 data: 0.0018 max mem: 19788 +Test: [ 3300/21770] eta: 0:20:56 time: 0.0731 data: 0.0018 max mem: 19788 +Test: [ 3400/21770] eta: 0:20:52 time: 0.0760 data: 0.0022 max mem: 19788 +Test: [ 3500/21770] eta: 0:20:42 time: 0.0605 data: 0.0017 max mem: 19788 +Test: [ 3600/21770] eta: 0:20:32 time: 0.0620 data: 0.0018 max mem: 19788 +Test: [ 3700/21770] eta: 0:20:27 time: 0.0750 data: 0.0022 max mem: 19788 +Test: [ 3800/21770] eta: 0:20:22 time: 0.0740 data: 0.0022 max mem: 19788 +Test: [ 3900/21770] eta: 0:20:14 time: 0.0753 data: 0.0021 max mem: 19788 +Test: [ 4000/21770] eta: 0:20:05 time: 0.0641 data: 0.0019 max mem: 19788 +Test: [ 4100/21770] eta: 0:20:01 time: 0.0616 data: 0.0017 max mem: 19788 +Test: [ 4200/21770] eta: 0:19:53 time: 0.0614 data: 0.0016 max mem: 19788 +Test: [ 4300/21770] eta: 0:19:48 time: 0.0606 data: 0.0019 max mem: 19788 +Test: [ 4400/21770] eta: 0:19:42 time: 0.0750 data: 0.0022 max mem: 19788 +Test: [ 4500/21770] eta: 0:19:36 time: 0.0641 data: 0.0018 max mem: 19788 +Test: [ 4600/21770] eta: 0:19:27 time: 0.0628 data: 0.0018 max mem: 19788 +Test: [ 4700/21770] eta: 0:19:20 time: 0.0673 data: 0.0019 max mem: 19788 +Test: [ 4800/21770] eta: 0:19:13 time: 0.0707 data: 0.0020 max mem: 19788 +Test: [ 4900/21770] eta: 0:19:08 time: 0.0627 data: 0.0018 max mem: 19788 +Test: [ 5000/21770] eta: 0:19:03 time: 0.0720 data: 0.0019 max mem: 19788 +Test: [ 5100/21770] eta: 0:18:57 time: 0.0634 data: 0.0019 max mem: 19788 +Test: [ 5200/21770] eta: 0:18:51 time: 0.0736 data: 0.0021 max mem: 19788 +Test: [ 5300/21770] eta: 0:18:43 time: 0.0667 data: 0.0020 max mem: 19788 +Test: [ 5400/21770] eta: 0:18:37 time: 0.0768 data: 0.0019 max mem: 19788 +Test: [ 5500/21770] eta: 0:18:31 time: 0.0679 data: 0.0018 max mem: 19788 +Test: [ 5600/21770] eta: 0:18:23 time: 0.0628 data: 0.0018 max mem: 19788 +Test: [ 5700/21770] eta: 0:18:16 time: 0.0800 data: 0.0022 max mem: 19788 +Test: [ 5800/21770] eta: 0:18:09 time: 0.0600 data: 0.0017 max mem: 19788 +Test: [ 5900/21770] eta: 0:18:01 time: 0.0691 data: 0.0019 max mem: 19788 +Test: [ 6000/21770] eta: 0:17:54 time: 0.0634 data: 0.0017 max mem: 19788 +Test: [ 6100/21770] eta: 0:17:46 time: 0.0600 data: 0.0017 max mem: 19788 +Test: [ 6200/21770] eta: 0:17:38 time: 0.0623 data: 0.0018 max mem: 19788 +Test: [ 6300/21770] eta: 0:17:31 time: 0.0641 data: 0.0018 max mem: 19788 +Test: [ 6400/21770] eta: 0:17:23 time: 0.0622 data: 0.0018 max mem: 19788 +Test: [ 6500/21770] eta: 0:17:16 time: 0.0696 data: 0.0022 max mem: 19788 +Test: [ 6600/21770] eta: 0:17:10 time: 0.0635 data: 0.0019 max mem: 19788 +Test: [ 6700/21770] eta: 0:17:02 time: 0.0630 data: 0.0017 max mem: 19788 +Test: [ 6800/21770] eta: 0:16:56 time: 0.0688 data: 0.0022 max mem: 19788 +Test: [ 6900/21770] eta: 0:16:50 time: 0.0624 data: 0.0017 max mem: 19788 +Test: [ 7000/21770] eta: 0:16:42 time: 0.0636 data: 0.0018 max mem: 19788 +Test: [ 7100/21770] eta: 0:16:34 time: 0.0605 data: 0.0017 max mem: 19788 +Test: [ 7200/21770] eta: 0:16:28 time: 0.0772 data: 0.0019 max mem: 19788 +Test: [ 7300/21770] eta: 0:16:21 time: 0.0627 data: 0.0018 max mem: 19788 +Test: [ 7400/21770] eta: 0:16:16 time: 0.0748 data: 0.0022 max mem: 19788 +Test: [ 7500/21770] eta: 0:16:09 time: 0.0701 data: 0.0022 max mem: 19788 +Test: [ 7600/21770] eta: 0:16:04 time: 0.0800 data: 0.0023 max mem: 19788 +Test: [ 7700/21770] eta: 0:15:57 time: 0.0701 data: 0.0021 max mem: 19788 +Test: [ 7800/21770] eta: 0:15:50 time: 0.0606 data: 0.0021 max mem: 19788 +Test: [ 7900/21770] eta: 0:15:44 time: 0.0753 data: 0.0023 max mem: 19788 +Test: [ 8000/21770] eta: 0:15:37 time: 0.0727 data: 0.0020 max mem: 19788 +Test: [ 8100/21770] eta: 0:15:30 time: 0.0631 data: 0.0019 max mem: 19788 +Test: [ 8200/21770] eta: 0:15:23 time: 0.0776 data: 0.0023 max mem: 19788 +Test: [ 8300/21770] eta: 0:15:16 time: 0.0630 data: 0.0017 max mem: 19788 +Test: [ 8400/21770] eta: 0:15:09 time: 0.0638 data: 0.0016 max mem: 19788 +Test: [ 8500/21770] eta: 0:15:02 time: 0.0753 data: 0.0019 max mem: 19788 +Test: [ 8600/21770] eta: 0:14:56 time: 0.0630 data: 0.0018 max mem: 19788 +Test: [ 8700/21770] eta: 0:14:48 time: 0.0607 data: 0.0018 max mem: 19788 +Test: [ 8800/21770] eta: 0:14:42 time: 0.0776 data: 0.0024 max mem: 19788 +Test: [ 8900/21770] eta: 0:14:35 time: 0.0712 data: 0.0020 max mem: 19788 +Test: [ 9000/21770] eta: 0:14:29 time: 0.0786 data: 0.0019 max mem: 19788 +Test: [ 9100/21770] eta: 0:14:23 time: 0.0698 data: 0.0020 max mem: 19788 +Test: [ 9200/21770] eta: 0:14:15 time: 0.0593 data: 0.0018 max mem: 19788 +Test: [ 9300/21770] eta: 0:14:08 time: 0.0609 data: 0.0018 max mem: 19788 +Test: [ 9400/21770] eta: 0:14:02 time: 0.0605 data: 0.0021 max mem: 19788 +Test: [ 9500/21770] eta: 0:13:55 time: 0.0723 data: 0.0022 max mem: 19788 +Test: [ 9600/21770] eta: 0:13:48 time: 0.0610 data: 0.0017 max mem: 19788 +Test: [ 9700/21770] eta: 0:13:41 time: 0.0807 data: 0.0020 max mem: 19788 +Test: [ 9800/21770] eta: 0:13:35 time: 0.0815 data: 0.0024 max mem: 19788 +Test: [ 9900/21770] eta: 0:13:28 time: 0.0636 data: 0.0020 max mem: 19788 +Test: [10000/21770] eta: 0:13:22 time: 0.0691 data: 0.0023 max mem: 19788 +Test: [10100/21770] eta: 0:13:14 time: 0.0629 data: 0.0018 max mem: 19788 +Test: [10200/21770] eta: 0:13:07 time: 0.0764 data: 0.0022 max mem: 19788 +Test: [10300/21770] eta: 0:13:00 time: 0.0627 data: 0.0017 max mem: 19788 +Test: [10400/21770] eta: 0:12:53 time: 0.0756 data: 0.0018 max mem: 19788 +Test: [10500/21770] eta: 0:12:47 time: 0.0728 data: 0.0022 max mem: 19788 +Test: [10600/21770] eta: 0:12:40 time: 0.0657 data: 0.0019 max mem: 19788 +Test: [10700/21770] eta: 0:12:33 time: 0.0649 data: 0.0019 max mem: 19788 +Test: [10800/21770] eta: 0:12:26 time: 0.0809 data: 0.0024 max mem: 19788 +Test: [10900/21770] eta: 0:12:19 time: 0.0635 data: 0.0017 max mem: 19788 +Test: [11000/21770] eta: 0:12:12 time: 0.0650 data: 0.0019 max mem: 19788 +Test: [11100/21770] eta: 0:12:05 time: 0.0630 data: 0.0018 max mem: 19788 +Test: [11200/21770] eta: 0:11:58 time: 0.0750 data: 0.0021 max mem: 19788 +Test: [11300/21770] eta: 0:11:51 time: 0.0818 data: 0.0024 max mem: 19788 +Test: [11400/21770] eta: 0:11:44 time: 0.0651 data: 0.0020 max mem: 19788 +Test: [11500/21770] eta: 0:11:37 time: 0.0645 data: 0.0020 max mem: 19788 +Test: [11600/21770] eta: 0:11:30 time: 0.0644 data: 0.0020 max mem: 19788 +Test: [11700/21770] eta: 0:11:24 time: 0.0689 data: 0.0021 max mem: 19788 +Test: [11800/21770] eta: 0:11:17 time: 0.0702 data: 0.0021 max mem: 19788 +Test: [11900/21770] eta: 0:11:10 time: 0.0713 data: 0.0020 max mem: 19788 +Test: [12000/21770] eta: 0:11:03 time: 0.0687 data: 0.0020 max mem: 19788 +Test: [12100/21770] eta: 0:10:57 time: 0.0817 data: 0.0020 max mem: 19788 +Test: [12200/21770] eta: 0:10:50 time: 0.0630 data: 0.0018 max mem: 19788 +Test: [12300/21770] eta: 0:10:43 time: 0.0807 data: 0.0023 max mem: 19788 +Test: [12400/21770] eta: 0:10:37 time: 0.0611 data: 0.0018 max mem: 19788 +Test: [12500/21770] eta: 0:10:30 time: 0.0759 data: 0.0022 max mem: 19788 +Test: [12600/21770] eta: 0:10:24 time: 0.0741 data: 0.0020 max mem: 19788 +Test: [12700/21770] eta: 0:10:17 time: 0.0632 data: 0.0019 max mem: 19788 +Test: [12800/21770] eta: 0:10:11 time: 0.0805 data: 0.0024 max mem: 19788 +Test: [12900/21770] eta: 0:10:04 time: 0.0644 data: 0.0019 max mem: 19788 +Test: [13000/21770] eta: 0:09:57 time: 0.0625 data: 0.0017 max mem: 19788 +Test: [13100/21770] eta: 0:09:50 time: 0.0799 data: 0.0025 max mem: 19788 +Test: [13200/21770] eta: 0:09:43 time: 0.0761 data: 0.0022 max mem: 19788 +Test: [13300/21770] eta: 0:09:37 time: 0.0707 data: 0.0020 max mem: 19788 +Test: [13400/21770] eta: 0:09:30 time: 0.0696 data: 0.0021 max mem: 19788 +Test: [13500/21770] eta: 0:09:23 time: 0.0812 data: 0.0022 max mem: 19788 +Test: [13600/21770] eta: 0:09:17 time: 0.0748 data: 0.0021 max mem: 19788 +Test: [13700/21770] eta: 0:09:10 time: 0.0734 data: 0.0022 max mem: 19788 +Test: [13800/21770] eta: 0:09:03 time: 0.0617 data: 0.0017 max mem: 19788 +Test: [13900/21770] eta: 0:08:56 time: 0.0698 data: 0.0018 max mem: 19788 +Test: [14000/21770] eta: 0:08:49 time: 0.0815 data: 0.0024 max mem: 19788 +Test: [14100/21770] eta: 0:08:43 time: 0.0813 data: 0.0023 max mem: 19788 +Test: [14200/21770] eta: 0:08:37 time: 0.0671 data: 0.0020 max mem: 19788 +Test: [14300/21770] eta: 0:08:30 time: 0.0818 data: 0.0019 max mem: 19788 +Test: [14400/21770] eta: 0:08:23 time: 0.0770 data: 0.0020 max mem: 19788 +Test: [14500/21770] eta: 0:08:16 time: 0.0657 data: 0.0019 max mem: 19788 +Test: [14600/21770] eta: 0:08:09 time: 0.0711 data: 0.0022 max mem: 19788 +Test: [14700/21770] eta: 0:08:03 time: 0.0761 data: 0.0022 max mem: 19788 +Test: [14800/21770] eta: 0:07:56 time: 0.0721 data: 0.0023 max mem: 19788 +Test: [14900/21770] eta: 0:07:49 time: 0.0627 data: 0.0018 max mem: 19788 +Test: [15000/21770] eta: 0:07:42 time: 0.0657 data: 0.0018 max mem: 19788 +Test: [15100/21770] eta: 0:07:35 time: 0.0618 data: 0.0018 max mem: 19788 +Test: [15200/21770] eta: 0:07:28 time: 0.0634 data: 0.0020 max mem: 19788 +Test: [15300/21770] eta: 0:07:22 time: 0.0696 data: 0.0021 max mem: 19788 +Test: [15400/21770] eta: 0:07:15 time: 0.0793 data: 0.0021 max mem: 19788 +Test: [15500/21770] eta: 0:07:09 time: 0.0726 data: 0.0020 max mem: 19788 +Test: [15600/21770] eta: 0:07:02 time: 0.0746 data: 0.0022 max mem: 19788 +Test: [15700/21770] eta: 0:06:55 time: 0.0785 data: 0.0022 max mem: 19788 +Test: [15800/21770] eta: 0:06:48 time: 0.0754 data: 0.0023 max mem: 19788 +Test: [15900/21770] eta: 0:06:42 time: 0.0666 data: 0.0019 max mem: 19788 +Test: [16000/21770] eta: 0:06:35 time: 0.0772 data: 0.0023 max mem: 19788 +Test: [16100/21770] eta: 0:06:28 time: 0.0698 data: 0.0018 max mem: 19788 +Test: [16200/21770] eta: 0:06:21 time: 0.0764 data: 0.0023 max mem: 19788 +Test: [16300/21770] eta: 0:06:14 time: 0.0646 data: 0.0017 max mem: 19788 +Test: [16400/21770] eta: 0:06:07 time: 0.0651 data: 0.0021 max mem: 19788 +Test: [16500/21770] eta: 0:06:01 time: 0.0639 data: 0.0020 max mem: 19788 +Test: [16600/21770] eta: 0:05:54 time: 0.0641 data: 0.0025 max mem: 19788 +Test: [16700/21770] eta: 0:05:47 time: 0.0598 data: 0.0017 max mem: 19788 +Test: [16800/21770] eta: 0:05:40 time: 0.0727 data: 0.0023 max mem: 19788 +Test: [16900/21770] eta: 0:05:33 time: 0.0650 data: 0.0019 max mem: 19788 +Test: [17000/21770] eta: 0:05:26 time: 0.0643 data: 0.0017 max mem: 19788 +Test: [17100/21770] eta: 0:05:19 time: 0.0665 data: 0.0017 max mem: 19788 +Test: [17200/21770] eta: 0:05:12 time: 0.0755 data: 0.0022 max mem: 19788 +Test: [17300/21770] eta: 0:05:05 time: 0.0608 data: 0.0016 max mem: 19788 +Test: [17400/21770] eta: 0:04:58 time: 0.0606 data: 0.0017 max mem: 19788 +Test: [17500/21770] eta: 0:04:52 time: 0.0706 data: 0.0021 max mem: 19788 +Test: [17600/21770] eta: 0:04:45 time: 0.0718 data: 0.0020 max mem: 19788 +Test: [17700/21770] eta: 0:04:38 time: 0.0656 data: 0.0020 max mem: 19788 +Test: [17800/21770] eta: 0:04:31 time: 0.0734 data: 0.0021 max mem: 19788 +Test: [17900/21770] eta: 0:04:24 time: 0.0803 data: 0.0025 max mem: 19788 +Test: [18000/21770] eta: 0:04:18 time: 0.0702 data: 0.0021 max mem: 19788 +Test: [18100/21770] eta: 0:04:11 time: 0.0802 data: 0.0024 max mem: 19788 +Test: [18200/21770] eta: 0:04:04 time: 0.0668 data: 0.0020 max mem: 19788 +Test: [18300/21770] eta: 0:03:57 time: 0.0779 data: 0.0024 max mem: 19788 +Test: [18400/21770] eta: 0:03:50 time: 0.0618 data: 0.0020 max mem: 19788 +Test: [18500/21770] eta: 0:03:44 time: 0.0764 data: 0.0019 max mem: 19788 +Test: [18600/21770] eta: 0:03:37 time: 0.0803 data: 0.0023 max mem: 19788 +Test: [18700/21770] eta: 0:03:30 time: 0.0630 data: 0.0019 max mem: 19788 +Test: [18800/21770] eta: 0:03:23 time: 0.0611 data: 0.0019 max mem: 19788 +Test: [18900/21770] eta: 0:03:16 time: 0.0725 data: 0.0020 max mem: 19788 +Test: [19000/21770] eta: 0:03:09 time: 0.0700 data: 0.0022 max mem: 19788 +Test: [19100/21770] eta: 0:03:02 time: 0.0620 data: 0.0019 max mem: 19788 +Test: [19200/21770] eta: 0:02:55 time: 0.0609 data: 0.0020 max mem: 19788 +Test: [19300/21770] eta: 0:02:48 time: 0.0633 data: 0.0019 max mem: 19788 +Test: [19400/21770] eta: 0:02:42 time: 0.0650 data: 0.0019 max mem: 19788 +Test: [19500/21770] eta: 0:02:35 time: 0.0631 data: 0.0018 max mem: 19788 +Test: [19600/21770] eta: 0:02:28 time: 0.0614 data: 0.0021 max mem: 19788 +Test: [19700/21770] eta: 0:02:21 time: 0.0664 data: 0.0020 max mem: 19788 +Test: [19800/21770] eta: 0:02:14 time: 0.0821 data: 0.0021 max mem: 19788 +Test: [19900/21770] eta: 0:02:07 time: 0.0669 data: 0.0020 max mem: 19788 +Test: [20000/21770] eta: 0:02:00 time: 0.0621 data: 0.0018 max mem: 19788 +Test: [20100/21770] eta: 0:01:54 time: 0.0730 data: 0.0018 max mem: 19788 +Test: [20200/21770] eta: 0:01:47 time: 0.0689 data: 0.0019 max mem: 19788 +Test: [20300/21770] eta: 0:01:40 time: 0.0617 data: 0.0018 max mem: 19788 +Test: [20400/21770] eta: 0:01:33 time: 0.0691 data: 0.0020 max mem: 19788 +Test: [20500/21770] eta: 0:01:26 time: 0.0786 data: 0.0022 max mem: 19788 +Test: [20600/21770] eta: 0:01:19 time: 0.0728 data: 0.0024 max mem: 19788 +Test: [20700/21770] eta: 0:01:13 time: 0.0616 data: 0.0018 max mem: 19788 +Test: [20800/21770] eta: 0:01:06 time: 0.0619 data: 0.0017 max mem: 19788 +Test: [20900/21770] eta: 0:00:59 time: 0.0739 data: 0.0022 max mem: 19788 +Test: [21000/21770] eta: 0:00:52 time: 0.0625 data: 0.0018 max mem: 19788 +Test: [21100/21770] eta: 0:00:45 time: 0.0650 data: 0.0022 max mem: 19788 +Test: [21200/21770] eta: 0:00:38 time: 0.0644 data: 0.0018 max mem: 19788 +Test: [21300/21770] eta: 0:00:32 time: 0.0626 data: 0.0017 max mem: 19788 +Test: [21400/21770] eta: 0:00:25 time: 0.0723 data: 0.0021 max mem: 19788 +Test: [21500/21770] eta: 0:00:18 time: 0.0782 data: 0.0021 max mem: 19788 +Test: [21600/21770] eta: 0:00:11 time: 0.0641 data: 0.0019 max mem: 19788 +Test: [21700/21770] eta: 0:00:04 time: 0.0903 data: 0.0018 max mem: 19788 +Test: Total time: 0:24:48 +Final results: +Mean IoU is 61.85 + + precision@0.5 = 68.62 + precision@0.6 = 63.31 + precision@0.7 = 56.65 + precision@0.8 = 45.95 + precision@0.9 = 22.77 + overall IoU = 63.49 + mean IoU = 61.85 + +Mean accuracy for one-to-zero sample is 83.11 + +Average object IoU 0.6184882910676565 +Overall IoU 63.48967361450195 +Better epoch: 13 + +Epoch: [14] [ 0/2138] eta: 3:15:46 lr: 3.3930088606900736e-05 loss: 0.0695 (0.0695) time: 5.4942 data: 1.4483 max mem: 19788 +Epoch: [14] [ 10/2138] eta: 2:15:06 lr: 3.392459499248683e-05 loss: 0.0303 (0.0354) time: 3.8095 data: 0.1345 max mem: 19788 +Epoch: [14] [ 20/2138] eta: 2:11:43 lr: 3.391910127922513e-05 loss: 0.0296 (0.0339) time: 3.6437 data: 0.0026 max mem: 19788 +Epoch: [14] [ 30/2138] eta: 2:11:12 lr: 3.391360746709607e-05 loss: 0.0296 (0.0333) time: 3.6932 data: 0.0026 max mem: 19788 +Epoch: [14] [ 40/2138] eta: 2:09:39 lr: 3.390811355608006e-05 loss: 0.0327 (0.0349) time: 3.6830 data: 0.0031 max mem: 19788 +Epoch: [14] [ 50/2138] eta: 2:08:29 lr: 3.390261954615754e-05 loss: 0.0335 (0.0350) time: 3.6268 data: 0.0029 max mem: 19788 +Epoch: [14] [ 60/2138] eta: 2:07:29 lr: 3.3897125437308914e-05 loss: 0.0305 (0.0350) time: 3.6263 data: 0.0029 max mem: 19788 +Epoch: [14] [ 70/2138] eta: 2:06:38 lr: 3.389163122951457e-05 loss: 0.0275 (0.0343) time: 3.6284 data: 0.0031 max mem: 19788 +Epoch: [14] [ 80/2138] eta: 2:05:52 lr: 3.3886136922754914e-05 loss: 0.0308 (0.0352) time: 3.6347 data: 0.0030 max mem: 19788 +Epoch: [14] [ 90/2138] eta: 2:05:05 lr: 3.3880642517010334e-05 loss: 0.0331 (0.0358) time: 3.6312 data: 0.0029 max mem: 19788 +Epoch: [14] [ 100/2138] eta: 2:04:30 lr: 3.387514801226121e-05 loss: 0.0328 (0.0354) time: 3.6492 data: 0.0029 max mem: 19788 +Epoch: [14] [ 110/2138] eta: 2:03:48 lr: 3.386965340848791e-05 loss: 0.0333 (0.0357) time: 3.6552 data: 0.0028 max mem: 19788 +Epoch: [14] [ 120/2138] eta: 2:03:06 lr: 3.3864158705670804e-05 loss: 0.0349 (0.0357) time: 3.6343 data: 0.0027 max mem: 19788 +Epoch: [14] [ 130/2138] eta: 2:02:25 lr: 3.385866390379025e-05 loss: 0.0344 (0.0360) time: 3.6320 data: 0.0027 max mem: 19788 +Epoch: [14] [ 140/2138] eta: 2:01:45 lr: 3.385316900282659e-05 loss: 0.0358 (0.0361) time: 3.6310 data: 0.0028 max mem: 19788 +Epoch: [14] [ 150/2138] eta: 2:01:04 lr: 3.3847674002760176e-05 loss: 0.0362 (0.0363) time: 3.6268 data: 0.0028 max mem: 19788 +Epoch: [14] [ 160/2138] eta: 2:00:25 lr: 3.3842178903571345e-05 loss: 0.0363 (0.0367) time: 3.6274 data: 0.0029 max mem: 19788 +Epoch: [14] [ 170/2138] eta: 1:59:44 lr: 3.383668370524042e-05 loss: 0.0371 (0.0368) time: 3.6252 data: 0.0029 max mem: 19788 +Epoch: [14] [ 180/2138] eta: 1:59:18 lr: 3.383118840774772e-05 loss: 0.0368 (0.0369) time: 3.6836 data: 0.0029 max mem: 19788 +Epoch: [14] [ 190/2138] eta: 1:58:38 lr: 3.382569301107356e-05 loss: 0.0368 (0.0373) time: 3.6837 data: 0.0029 max mem: 19788 +Epoch: [14] [ 200/2138] eta: 1:57:59 lr: 3.3820197515198246e-05 loss: 0.0321 (0.0369) time: 3.6261 data: 0.0031 max mem: 19788 +Epoch: [14] [ 210/2138] eta: 1:57:21 lr: 3.3814701920102085e-05 loss: 0.0385 (0.0378) time: 3.6319 data: 0.0031 max mem: 19788 +Epoch: [14] [ 220/2138] eta: 1:56:43 lr: 3.380920622576535e-05 loss: 0.0405 (0.0375) time: 3.6337 data: 0.0028 max mem: 19788 +Epoch: [14] [ 230/2138] eta: 1:56:05 lr: 3.380371043216833e-05 loss: 0.0364 (0.0377) time: 3.6355 data: 0.0028 max mem: 19788 +Epoch: [14] [ 240/2138] eta: 1:55:26 lr: 3.379821453929131e-05 loss: 0.0392 (0.0378) time: 3.6303 data: 0.0032 max mem: 19788 +Epoch: [14] [ 250/2138] eta: 1:54:49 lr: 3.379271854711456e-05 loss: 0.0384 (0.0378) time: 3.6333 data: 0.0033 max mem: 19788 +Epoch: [14] [ 260/2138] eta: 1:54:13 lr: 3.3787222455618325e-05 loss: 0.0326 (0.0376) time: 3.6490 data: 0.0029 max mem: 19788 +Epoch: [14] [ 270/2138] eta: 1:53:36 lr: 3.3781726264782865e-05 loss: 0.0332 (0.0378) time: 3.6445 data: 0.0028 max mem: 19788 +Epoch: [14] [ 280/2138] eta: 1:52:58 lr: 3.3776229974588435e-05 loss: 0.0361 (0.0377) time: 3.6348 data: 0.0028 max mem: 19788 +Epoch: [14] [ 290/2138] eta: 1:52:21 lr: 3.377073358501526e-05 loss: 0.0331 (0.0377) time: 3.6379 data: 0.0029 max mem: 19788 +Epoch: [14] [ 300/2138] eta: 1:51:44 lr: 3.3765237096043576e-05 loss: 0.0328 (0.0377) time: 3.6377 data: 0.0030 max mem: 19788 +Epoch: [14] [ 310/2138] eta: 1:51:07 lr: 3.3759740507653616e-05 loss: 0.0344 (0.0377) time: 3.6377 data: 0.0029 max mem: 19788 +Epoch: [14] [ 320/2138] eta: 1:50:30 lr: 3.375424381982558e-05 loss: 0.0346 (0.0377) time: 3.6367 data: 0.0026 max mem: 19788 +Epoch: [14] [ 330/2138] eta: 1:49:53 lr: 3.374874703253969e-05 loss: 0.0379 (0.0380) time: 3.6337 data: 0.0027 max mem: 19788 +Epoch: [14] [ 340/2138] eta: 1:49:15 lr: 3.374325014577613e-05 loss: 0.0426 (0.0381) time: 3.6316 data: 0.0028 max mem: 19788 +Epoch: [14] [ 350/2138] eta: 1:48:38 lr: 3.373775315951511e-05 loss: 0.0388 (0.0385) time: 3.6315 data: 0.0030 max mem: 19788 +Epoch: [14] [ 360/2138] eta: 1:48:01 lr: 3.373225607373681e-05 loss: 0.0366 (0.0385) time: 3.6291 data: 0.0029 max mem: 19788 +Epoch: [14] [ 370/2138] eta: 1:47:26 lr: 3.37267588884214e-05 loss: 0.0366 (0.0386) time: 3.6499 data: 0.0028 max mem: 19788 +Epoch: [14] [ 380/2138] eta: 1:46:49 lr: 3.372126160354906e-05 loss: 0.0376 (0.0386) time: 3.6594 data: 0.0028 max mem: 19788 +Epoch: [14] [ 390/2138] eta: 1:46:12 lr: 3.3715764219099954e-05 loss: 0.0361 (0.0387) time: 3.6349 data: 0.0027 max mem: 19788 +Epoch: [14] [ 400/2138] eta: 1:45:35 lr: 3.371026673505424e-05 loss: 0.0353 (0.0388) time: 3.6319 data: 0.0027 max mem: 19788 +Epoch: [14] [ 410/2138] eta: 1:44:58 lr: 3.3704769151392053e-05 loss: 0.0385 (0.0388) time: 3.6308 data: 0.0029 max mem: 19788 +Epoch: [14] [ 420/2138] eta: 1:44:21 lr: 3.369927146809353e-05 loss: 0.0407 (0.0390) time: 3.6265 data: 0.0030 max mem: 19788 +Epoch: [14] [ 430/2138] eta: 1:43:43 lr: 3.369377368513883e-05 loss: 0.0408 (0.0391) time: 3.6246 data: 0.0030 max mem: 19788 +Epoch: [14] [ 440/2138] eta: 1:43:06 lr: 3.368827580250806e-05 loss: 0.0408 (0.0392) time: 3.6196 data: 0.0029 max mem: 19788 +Epoch: [14] [ 450/2138] eta: 1:42:29 lr: 3.3682777820181345e-05 loss: 0.0364 (0.0391) time: 3.6237 data: 0.0027 max mem: 19788 +Epoch: [14] [ 460/2138] eta: 1:41:52 lr: 3.3677279738138784e-05 loss: 0.0328 (0.0390) time: 3.6279 data: 0.0026 max mem: 19788 +Epoch: [14] [ 470/2138] eta: 1:41:15 lr: 3.3671781556360486e-05 loss: 0.0328 (0.0390) time: 3.6293 data: 0.0026 max mem: 19788 +Epoch: [14] [ 480/2138] eta: 1:40:40 lr: 3.3666283274826555e-05 loss: 0.0365 (0.0390) time: 3.6549 data: 0.0026 max mem: 19788 +Epoch: [14] [ 490/2138] eta: 1:40:03 lr: 3.366078489351707e-05 loss: 0.0333 (0.0389) time: 3.6528 data: 0.0028 max mem: 19788 +Epoch: [14] [ 500/2138] eta: 1:39:27 lr: 3.365528641241209e-05 loss: 0.0331 (0.0389) time: 3.6367 data: 0.0030 max mem: 19788 +Epoch: [14] [ 510/2138] eta: 1:38:50 lr: 3.364978783149174e-05 loss: 0.0357 (0.0389) time: 3.6461 data: 0.0028 max mem: 19788 +Epoch: [14] [ 520/2138] eta: 1:38:14 lr: 3.364428915073603e-05 loss: 0.0357 (0.0389) time: 3.6412 data: 0.0027 max mem: 19788 +Epoch: [14] [ 530/2138] eta: 1:37:40 lr: 3.3638790370125046e-05 loss: 0.0330 (0.0388) time: 3.6888 data: 0.0027 max mem: 19788 +Epoch: [14] [ 540/2138] eta: 1:37:04 lr: 3.363329148963883e-05 loss: 0.0320 (0.0387) time: 3.6945 data: 0.0028 max mem: 19788 +Epoch: [14] [ 550/2138] eta: 1:36:27 lr: 3.3627792509257426e-05 loss: 0.0330 (0.0387) time: 3.6433 data: 0.0028 max mem: 19788 +Epoch: [14] [ 560/2138] eta: 1:35:51 lr: 3.362229342896087e-05 loss: 0.0354 (0.0387) time: 3.6402 data: 0.0026 max mem: 19788 +Epoch: [14] [ 570/2138] eta: 1:35:14 lr: 3.361679424872918e-05 loss: 0.0352 (0.0387) time: 3.6407 data: 0.0027 max mem: 19788 +Epoch: [14] [ 580/2138] eta: 1:34:38 lr: 3.361129496854238e-05 loss: 0.0406 (0.0387) time: 3.6468 data: 0.0029 max mem: 19788 +Epoch: [14] [ 590/2138] eta: 1:34:01 lr: 3.3605795588380496e-05 loss: 0.0356 (0.0386) time: 3.6453 data: 0.0031 max mem: 19788 +Epoch: [14] [ 600/2138] eta: 1:33:25 lr: 3.360029610822351e-05 loss: 0.0317 (0.0386) time: 3.6365 data: 0.0029 max mem: 19788 +Epoch: [14] [ 610/2138] eta: 1:32:48 lr: 3.359479652805142e-05 loss: 0.0331 (0.0386) time: 3.6379 data: 0.0027 max mem: 19788 +Epoch: [14] [ 620/2138] eta: 1:32:11 lr: 3.358929684784422e-05 loss: 0.0399 (0.0387) time: 3.6361 data: 0.0027 max mem: 19788 +Epoch: [14] [ 630/2138] eta: 1:31:34 lr: 3.35837970675819e-05 loss: 0.0344 (0.0386) time: 3.6326 data: 0.0028 max mem: 19788 +Epoch: [14] [ 640/2138] eta: 1:30:58 lr: 3.357829718724442e-05 loss: 0.0322 (0.0385) time: 3.6282 data: 0.0030 max mem: 19788 +Epoch: [14] [ 650/2138] eta: 1:30:21 lr: 3.357279720681175e-05 loss: 0.0353 (0.0385) time: 3.6256 data: 0.0032 max mem: 19788 +Epoch: [14] [ 660/2138] eta: 1:29:44 lr: 3.3567297126263845e-05 loss: 0.0368 (0.0384) time: 3.6313 data: 0.0030 max mem: 19788 +Epoch: [14] [ 670/2138] eta: 1:29:08 lr: 3.356179694558067e-05 loss: 0.0339 (0.0384) time: 3.6379 data: 0.0028 max mem: 19788 +Epoch: [14] [ 680/2138] eta: 1:28:31 lr: 3.3556296664742145e-05 loss: 0.0366 (0.0384) time: 3.6312 data: 0.0027 max mem: 19788 +Epoch: [14] [ 690/2138] eta: 1:27:54 lr: 3.355079628372821e-05 loss: 0.0366 (0.0384) time: 3.6256 data: 0.0029 max mem: 19788 +Epoch: [14] [ 700/2138] eta: 1:27:17 lr: 3.35452958025188e-05 loss: 0.0366 (0.0384) time: 3.6245 data: 0.0032 max mem: 19788 +Epoch: [14] [ 710/2138] eta: 1:26:40 lr: 3.353979522109384e-05 loss: 0.0372 (0.0384) time: 3.6181 data: 0.0030 max mem: 19788 +Epoch: [14] [ 720/2138] eta: 1:26:03 lr: 3.353429453943323e-05 loss: 0.0352 (0.0384) time: 3.6149 data: 0.0029 max mem: 19788 +Epoch: [14] [ 730/2138] eta: 1:25:26 lr: 3.3528793757516876e-05 loss: 0.0346 (0.0385) time: 3.6164 data: 0.0031 max mem: 19788 +Epoch: [14] [ 740/2138] eta: 1:24:50 lr: 3.352329287532467e-05 loss: 0.0322 (0.0384) time: 3.6194 data: 0.0030 max mem: 19788 +Epoch: [14] [ 750/2138] eta: 1:24:13 lr: 3.351779189283651e-05 loss: 0.0316 (0.0385) time: 3.6227 data: 0.0027 max mem: 19788 +Epoch: [14] [ 760/2138] eta: 1:23:36 lr: 3.3512290810032285e-05 loss: 0.0392 (0.0386) time: 3.6246 data: 0.0026 max mem: 19788 +Epoch: [14] [ 770/2138] eta: 1:22:59 lr: 3.350678962689184e-05 loss: 0.0409 (0.0387) time: 3.6197 data: 0.0026 max mem: 19788 +Epoch: [14] [ 780/2138] eta: 1:22:23 lr: 3.350128834339506e-05 loss: 0.0394 (0.0387) time: 3.6159 data: 0.0027 max mem: 19788 +Epoch: [14] [ 790/2138] eta: 1:21:46 lr: 3.3495786959521817e-05 loss: 0.0374 (0.0387) time: 3.6170 data: 0.0028 max mem: 19788 +Epoch: [14] [ 800/2138] eta: 1:21:09 lr: 3.349028547525193e-05 loss: 0.0355 (0.0386) time: 3.6159 data: 0.0029 max mem: 19788 +Epoch: [14] [ 810/2138] eta: 1:20:32 lr: 3.348478389056526e-05 loss: 0.0367 (0.0386) time: 3.6190 data: 0.0030 max mem: 19788 +Epoch: [14] [ 820/2138] eta: 1:19:56 lr: 3.3479282205441635e-05 loss: 0.0375 (0.0387) time: 3.6215 data: 0.0029 max mem: 19788 +Epoch: [14] [ 830/2138] eta: 1:19:19 lr: 3.347378041986089e-05 loss: 0.0373 (0.0386) time: 3.6194 data: 0.0029 max mem: 19788 +Epoch: [14] [ 840/2138] eta: 1:18:42 lr: 3.346827853380284e-05 loss: 0.0297 (0.0385) time: 3.6182 data: 0.0028 max mem: 19788 +Epoch: [14] [ 850/2138] eta: 1:18:05 lr: 3.346277654724728e-05 loss: 0.0328 (0.0385) time: 3.6157 data: 0.0027 max mem: 19788 +Epoch: [14] [ 860/2138] eta: 1:17:29 lr: 3.345727446017405e-05 loss: 0.0368 (0.0385) time: 3.6131 data: 0.0028 max mem: 19788 +Epoch: [14] [ 870/2138] eta: 1:16:52 lr: 3.345177227256292e-05 loss: 0.0342 (0.0385) time: 3.6156 data: 0.0029 max mem: 19788 +Epoch: [14] [ 880/2138] eta: 1:16:15 lr: 3.344626998439367e-05 loss: 0.0342 (0.0384) time: 3.6180 data: 0.0030 max mem: 19788 +Epoch: [14] [ 890/2138] eta: 1:15:39 lr: 3.34407675956461e-05 loss: 0.0308 (0.0384) time: 3.6168 data: 0.0031 max mem: 19788 +Epoch: [14] [ 900/2138] eta: 1:15:02 lr: 3.343526510629998e-05 loss: 0.0347 (0.0385) time: 3.6141 data: 0.0030 max mem: 19788 +Epoch: [14] [ 910/2138] eta: 1:14:25 lr: 3.3429762516335075e-05 loss: 0.0347 (0.0385) time: 3.6115 data: 0.0030 max mem: 19788 +Epoch: [14] [ 920/2138] eta: 1:13:49 lr: 3.342425982573113e-05 loss: 0.0319 (0.0385) time: 3.6191 data: 0.0029 max mem: 19788 +Epoch: [14] [ 930/2138] eta: 1:13:12 lr: 3.341875703446791e-05 loss: 0.0333 (0.0385) time: 3.6260 data: 0.0028 max mem: 19788 +Epoch: [14] [ 940/2138] eta: 1:12:36 lr: 3.341325414252515e-05 loss: 0.0408 (0.0385) time: 3.6293 data: 0.0030 max mem: 19788 +Epoch: [14] [ 950/2138] eta: 1:12:00 lr: 3.3407751149882576e-05 loss: 0.0355 (0.0385) time: 3.6394 data: 0.0029 max mem: 19788 +Epoch: [14] [ 960/2138] eta: 1:11:23 lr: 3.340224805651992e-05 loss: 0.0341 (0.0385) time: 3.6404 data: 0.0028 max mem: 19788 +Epoch: [14] [ 970/2138] eta: 1:10:47 lr: 3.3396744862416914e-05 loss: 0.0341 (0.0385) time: 3.6330 data: 0.0027 max mem: 19788 +Epoch: [14] [ 980/2138] eta: 1:10:10 lr: 3.339124156755325e-05 loss: 0.0280 (0.0384) time: 3.6286 data: 0.0028 max mem: 19788 +Epoch: [14] [ 990/2138] eta: 1:09:34 lr: 3.3385738171908635e-05 loss: 0.0327 (0.0384) time: 3.6363 data: 0.0029 max mem: 19788 +Epoch: [14] [1000/2138] eta: 1:08:58 lr: 3.338023467546277e-05 loss: 0.0375 (0.0384) time: 3.6473 data: 0.0029 max mem: 19788 +Epoch: [14] [1010/2138] eta: 1:08:21 lr: 3.337473107819533e-05 loss: 0.0347 (0.0383) time: 3.6458 data: 0.0029 max mem: 19788 +Epoch: [14] [1020/2138] eta: 1:07:45 lr: 3.336922738008601e-05 loss: 0.0317 (0.0383) time: 3.6427 data: 0.0030 max mem: 19788 +Epoch: [14] [1030/2138] eta: 1:07:09 lr: 3.336372358111448e-05 loss: 0.0360 (0.0383) time: 3.6454 data: 0.0029 max mem: 19788 +Epoch: [14] [1040/2138] eta: 1:06:32 lr: 3.335821968126038e-05 loss: 0.0400 (0.0383) time: 3.6365 data: 0.0028 max mem: 19788 +Epoch: [14] [1050/2138] eta: 1:05:56 lr: 3.335271568050339e-05 loss: 0.0340 (0.0383) time: 3.6315 data: 0.0029 max mem: 19788 +Epoch: [14] [1060/2138] eta: 1:05:20 lr: 3.334721157882315e-05 loss: 0.0329 (0.0383) time: 3.6398 data: 0.0027 max mem: 19788 +Epoch: [14] [1070/2138] eta: 1:04:43 lr: 3.334170737619931e-05 loss: 0.0324 (0.0382) time: 3.6382 data: 0.0027 max mem: 19788 +Epoch: [14] [1080/2138] eta: 1:04:07 lr: 3.3336203072611475e-05 loss: 0.0339 (0.0382) time: 3.6365 data: 0.0027 max mem: 19788 +Epoch: [14] [1090/2138] eta: 1:03:31 lr: 3.33306986680393e-05 loss: 0.0346 (0.0382) time: 3.6389 data: 0.0027 max mem: 19788 +Epoch: [14] [1100/2138] eta: 1:02:54 lr: 3.332519416246239e-05 loss: 0.0358 (0.0382) time: 3.6331 data: 0.0029 max mem: 19788 +Epoch: [14] [1110/2138] eta: 1:02:18 lr: 3.3319689555860346e-05 loss: 0.0321 (0.0382) time: 3.6349 data: 0.0029 max mem: 19788 +Epoch: [14] [1120/2138] eta: 1:01:41 lr: 3.331418484821278e-05 loss: 0.0329 (0.0382) time: 3.6346 data: 0.0028 max mem: 19788 +Epoch: [14] [1130/2138] eta: 1:01:05 lr: 3.3308680039499274e-05 loss: 0.0380 (0.0382) time: 3.6313 data: 0.0027 max mem: 19788 +Epoch: [14] [1140/2138] eta: 1:00:29 lr: 3.330317512969943e-05 loss: 0.0402 (0.0382) time: 3.6323 data: 0.0027 max mem: 19788 +Epoch: [14] [1150/2138] eta: 0:59:52 lr: 3.32976701187928e-05 loss: 0.0310 (0.0381) time: 3.6306 data: 0.0028 max mem: 19788 +Epoch: [14] [1160/2138] eta: 0:59:16 lr: 3.3292165006758974e-05 loss: 0.0311 (0.0381) time: 3.6404 data: 0.0030 max mem: 19788 +Epoch: [14] [1170/2138] eta: 0:58:40 lr: 3.328665979357751e-05 loss: 0.0327 (0.0381) time: 3.6370 data: 0.0029 max mem: 19788 +Epoch: [14] [1180/2138] eta: 0:58:03 lr: 3.328115447922797e-05 loss: 0.0355 (0.0381) time: 3.6267 data: 0.0030 max mem: 19788 +Epoch: [14] [1190/2138] eta: 0:57:27 lr: 3.327564906368987e-05 loss: 0.0354 (0.0381) time: 3.6289 data: 0.0030 max mem: 19788 +Epoch: [14] [1200/2138] eta: 0:56:50 lr: 3.327014354694277e-05 loss: 0.0354 (0.0381) time: 3.6290 data: 0.0028 max mem: 19788 +Epoch: [14] [1210/2138] eta: 0:56:14 lr: 3.32646379289662e-05 loss: 0.0373 (0.0381) time: 3.6330 data: 0.0030 max mem: 19788 +Epoch: [14] [1220/2138] eta: 0:55:38 lr: 3.325913220973968e-05 loss: 0.0328 (0.0380) time: 3.6349 data: 0.0032 max mem: 19788 +Epoch: [14] [1230/2138] eta: 0:55:01 lr: 3.3253626389242716e-05 loss: 0.0316 (0.0380) time: 3.6284 data: 0.0033 max mem: 19788 +Epoch: [14] [1240/2138] eta: 0:54:25 lr: 3.3248120467454816e-05 loss: 0.0326 (0.0380) time: 3.6282 data: 0.0031 max mem: 19788 +Epoch: [14] [1250/2138] eta: 0:53:48 lr: 3.3242614444355494e-05 loss: 0.0308 (0.0380) time: 3.6348 data: 0.0028 max mem: 19788 +Epoch: [14] [1260/2138] eta: 0:53:12 lr: 3.323710831992423e-05 loss: 0.0301 (0.0379) time: 3.6311 data: 0.0029 max mem: 19788 +Epoch: [14] [1270/2138] eta: 0:52:36 lr: 3.3231602094140496e-05 loss: 0.0282 (0.0379) time: 3.6275 data: 0.0029 max mem: 19788 +Epoch: [14] [1280/2138] eta: 0:51:59 lr: 3.3226095766983777e-05 loss: 0.0315 (0.0379) time: 3.6344 data: 0.0029 max mem: 19788 +Epoch: [14] [1290/2138] eta: 0:51:23 lr: 3.322058933843355e-05 loss: 0.0322 (0.0379) time: 3.6349 data: 0.0031 max mem: 19788 +Epoch: [14] [1300/2138] eta: 0:50:46 lr: 3.321508280846925e-05 loss: 0.0360 (0.0379) time: 3.6349 data: 0.0032 max mem: 19788 +Epoch: [14] [1310/2138] eta: 0:50:10 lr: 3.320957617707034e-05 loss: 0.0360 (0.0379) time: 3.6411 data: 0.0030 max mem: 19788 +Epoch: [14] [1320/2138] eta: 0:49:34 lr: 3.3204069444216256e-05 loss: 0.0377 (0.0380) time: 3.6402 data: 0.0028 max mem: 19788 +Epoch: [14] [1330/2138] eta: 0:48:57 lr: 3.319856260988645e-05 loss: 0.0356 (0.0380) time: 3.6331 data: 0.0029 max mem: 19788 +Epoch: [14] [1340/2138] eta: 0:48:21 lr: 3.319305567406034e-05 loss: 0.0369 (0.0381) time: 3.6318 data: 0.0029 max mem: 19788 +Epoch: [14] [1350/2138] eta: 0:47:45 lr: 3.318754863671733e-05 loss: 0.0415 (0.0381) time: 3.6321 data: 0.0030 max mem: 19788 +Epoch: [14] [1360/2138] eta: 0:47:08 lr: 3.3182041497836846e-05 loss: 0.0393 (0.0381) time: 3.6350 data: 0.0031 max mem: 19788 +Epoch: [14] [1370/2138] eta: 0:46:32 lr: 3.317653425739829e-05 loss: 0.0343 (0.0381) time: 3.6341 data: 0.0029 max mem: 19788 +Epoch: [14] [1380/2138] eta: 0:45:56 lr: 3.317102691538106e-05 loss: 0.0343 (0.0381) time: 3.6320 data: 0.0028 max mem: 19788 +Epoch: [14] [1390/2138] eta: 0:45:19 lr: 3.3165519471764526e-05 loss: 0.0362 (0.0381) time: 3.6319 data: 0.0029 max mem: 19788 +Epoch: [14] [1400/2138] eta: 0:44:43 lr: 3.3160011926528085e-05 loss: 0.0345 (0.0381) time: 3.6314 data: 0.0028 max mem: 19788 +Epoch: [14] [1410/2138] eta: 0:44:06 lr: 3.315450427965111e-05 loss: 0.0335 (0.0381) time: 3.6357 data: 0.0028 max mem: 19788 +Epoch: [14] [1420/2138] eta: 0:43:30 lr: 3.314899653111294e-05 loss: 0.0313 (0.0381) time: 3.6351 data: 0.0031 max mem: 19788 +Epoch: [14] [1430/2138] eta: 0:42:54 lr: 3.3143488680892957e-05 loss: 0.0339 (0.0381) time: 3.6902 data: 0.0031 max mem: 19788 +Epoch: [14] [1440/2138] eta: 0:42:18 lr: 3.3137980728970485e-05 loss: 0.0325 (0.0380) time: 3.6856 data: 0.0032 max mem: 19788 +Epoch: [14] [1450/2138] eta: 0:41:41 lr: 3.313247267532488e-05 loss: 0.0346 (0.0381) time: 3.6318 data: 0.0030 max mem: 19788 +Epoch: [14] [1460/2138] eta: 0:41:05 lr: 3.3126964519935465e-05 loss: 0.0396 (0.0381) time: 3.6318 data: 0.0028 max mem: 19788 +Epoch: [14] [1470/2138] eta: 0:40:29 lr: 3.312145626278156e-05 loss: 0.0394 (0.0382) time: 3.6246 data: 0.0028 max mem: 19788 +Epoch: [14] [1480/2138] eta: 0:39:52 lr: 3.31159479038425e-05 loss: 0.0386 (0.0382) time: 3.6234 data: 0.0027 max mem: 19788 +Epoch: [14] [1490/2138] eta: 0:39:16 lr: 3.3110439443097565e-05 loss: 0.0386 (0.0382) time: 3.6256 data: 0.0028 max mem: 19788 +Epoch: [14] [1500/2138] eta: 0:38:39 lr: 3.3104930880526064e-05 loss: 0.0320 (0.0382) time: 3.6249 data: 0.0028 max mem: 19788 +Epoch: [14] [1510/2138] eta: 0:38:03 lr: 3.309942221610729e-05 loss: 0.0321 (0.0382) time: 3.6213 data: 0.0027 max mem: 19788 +Epoch: [14] [1520/2138] eta: 0:37:27 lr: 3.309391344982053e-05 loss: 0.0328 (0.0381) time: 3.6765 data: 0.0027 max mem: 19788 +Epoch: [14] [1530/2138] eta: 0:36:51 lr: 3.308840458164505e-05 loss: 0.0326 (0.0381) time: 3.6757 data: 0.0027 max mem: 19788 +Epoch: [14] [1540/2138] eta: 0:36:14 lr: 3.3082895611560106e-05 loss: 0.0330 (0.0381) time: 3.6217 data: 0.0028 max mem: 19788 +Epoch: [14] [1550/2138] eta: 0:35:38 lr: 3.307738653954498e-05 loss: 0.0320 (0.0381) time: 3.6221 data: 0.0028 max mem: 19788 +Epoch: [14] [1560/2138] eta: 0:35:01 lr: 3.307187736557891e-05 loss: 0.0320 (0.0381) time: 3.6263 data: 0.0030 max mem: 19788 +Epoch: [14] [1570/2138] eta: 0:34:25 lr: 3.3066368089641156e-05 loss: 0.0380 (0.0381) time: 3.6315 data: 0.0030 max mem: 19788 +Epoch: [14] [1580/2138] eta: 0:33:49 lr: 3.3060858711710915e-05 loss: 0.0372 (0.0381) time: 3.6405 data: 0.0030 max mem: 19788 +Epoch: [14] [1590/2138] eta: 0:33:12 lr: 3.305534923176745e-05 loss: 0.0371 (0.0381) time: 3.6374 data: 0.0031 max mem: 19788 +Epoch: [14] [1600/2138] eta: 0:32:36 lr: 3.304983964978996e-05 loss: 0.0375 (0.0381) time: 3.6307 data: 0.0029 max mem: 19788 +Epoch: [14] [1610/2138] eta: 0:31:59 lr: 3.304432996575766e-05 loss: 0.0353 (0.0381) time: 3.6261 data: 0.0027 max mem: 19788 +Epoch: [14] [1620/2138] eta: 0:31:23 lr: 3.303882017964975e-05 loss: 0.0353 (0.0381) time: 3.6217 data: 0.0027 max mem: 19788 +Epoch: [14] [1630/2138] eta: 0:30:47 lr: 3.303331029144543e-05 loss: 0.0467 (0.0382) time: 3.6204 data: 0.0028 max mem: 19788 +Epoch: [14] [1640/2138] eta: 0:30:10 lr: 3.302780030112388e-05 loss: 0.0377 (0.0382) time: 3.6178 data: 0.0028 max mem: 19788 +Epoch: [14] [1650/2138] eta: 0:29:34 lr: 3.3022290208664286e-05 loss: 0.0336 (0.0381) time: 3.6220 data: 0.0030 max mem: 19788 +Epoch: [14] [1660/2138] eta: 0:28:57 lr: 3.30167800140458e-05 loss: 0.0322 (0.0381) time: 3.6204 data: 0.0032 max mem: 19788 +Epoch: [14] [1670/2138] eta: 0:28:21 lr: 3.301126971724759e-05 loss: 0.0322 (0.0381) time: 3.6149 data: 0.0033 max mem: 19788 +Epoch: [14] [1680/2138] eta: 0:27:45 lr: 3.300575931824883e-05 loss: 0.0341 (0.0381) time: 3.6204 data: 0.0032 max mem: 19788 +Epoch: [14] [1690/2138] eta: 0:27:08 lr: 3.300024881702864e-05 loss: 0.0373 (0.0381) time: 3.6255 data: 0.0028 max mem: 19788 +Epoch: [14] [1700/2138] eta: 0:26:32 lr: 3.2994738213566166e-05 loss: 0.0373 (0.0381) time: 3.6196 data: 0.0034 max mem: 19788 +Epoch: [14] [1710/2138] eta: 0:25:55 lr: 3.298922750784054e-05 loss: 0.0345 (0.0381) time: 3.6157 data: 0.0037 max mem: 19788 +Epoch: [14] [1720/2138] eta: 0:25:19 lr: 3.2983716699830884e-05 loss: 0.0345 (0.0381) time: 3.6178 data: 0.0031 max mem: 19788 +Epoch: [14] [1730/2138] eta: 0:24:43 lr: 3.2978205789516296e-05 loss: 0.0355 (0.0381) time: 3.6155 data: 0.0028 max mem: 19788 +Epoch: [14] [1740/2138] eta: 0:24:06 lr: 3.297269477687589e-05 loss: 0.0346 (0.0381) time: 3.6142 data: 0.0027 max mem: 19788 +Epoch: [14] [1750/2138] eta: 0:23:30 lr: 3.2967183661888776e-05 loss: 0.0335 (0.0381) time: 3.6297 data: 0.0028 max mem: 19788 +Epoch: [14] [1760/2138] eta: 0:22:53 lr: 3.296167244453403e-05 loss: 0.0366 (0.0381) time: 3.6265 data: 0.0028 max mem: 19788 +Epoch: [14] [1770/2138] eta: 0:22:17 lr: 3.295616112479072e-05 loss: 0.0366 (0.0381) time: 3.6145 data: 0.0029 max mem: 19788 +Epoch: [14] [1780/2138] eta: 0:21:41 lr: 3.2950649702637936e-05 loss: 0.0328 (0.0381) time: 3.6145 data: 0.0029 max mem: 19788 +Epoch: [14] [1790/2138] eta: 0:21:04 lr: 3.294513817805474e-05 loss: 0.0325 (0.0381) time: 3.6126 data: 0.0028 max mem: 19788 +Epoch: [14] [1800/2138] eta: 0:20:28 lr: 3.2939626551020184e-05 loss: 0.0335 (0.0381) time: 3.6157 data: 0.0029 max mem: 19788 +Epoch: [14] [1810/2138] eta: 0:19:52 lr: 3.293411482151331e-05 loss: 0.0374 (0.0381) time: 3.6148 data: 0.0028 max mem: 19788 +Epoch: [14] [1820/2138] eta: 0:19:15 lr: 3.292860298951316e-05 loss: 0.0309 (0.0381) time: 3.6179 data: 0.0026 max mem: 19788 +Epoch: [14] [1830/2138] eta: 0:18:39 lr: 3.292309105499877e-05 loss: 0.0309 (0.0381) time: 3.6197 data: 0.0027 max mem: 19788 +Epoch: [14] [1840/2138] eta: 0:18:02 lr: 3.2917579017949164e-05 loss: 0.0325 (0.0381) time: 3.6214 data: 0.0028 max mem: 19788 +Epoch: [14] [1850/2138] eta: 0:17:26 lr: 3.2912066878343344e-05 loss: 0.0365 (0.0381) time: 3.6258 data: 0.0030 max mem: 19788 +Epoch: [14] [1860/2138] eta: 0:16:50 lr: 3.290655463616033e-05 loss: 0.0398 (0.0381) time: 3.6277 data: 0.0029 max mem: 19788 +Epoch: [14] [1870/2138] eta: 0:16:13 lr: 3.290104229137912e-05 loss: 0.0385 (0.0381) time: 3.6277 data: 0.0028 max mem: 19788 +Epoch: [14] [1880/2138] eta: 0:15:37 lr: 3.289552984397869e-05 loss: 0.0339 (0.0381) time: 3.6285 data: 0.0029 max mem: 19788 +Epoch: [14] [1890/2138] eta: 0:15:01 lr: 3.289001729393804e-05 loss: 0.0307 (0.0381) time: 3.6303 data: 0.0028 max mem: 19788 +Epoch: [14] [1900/2138] eta: 0:14:24 lr: 3.288450464123613e-05 loss: 0.0300 (0.0381) time: 3.6398 data: 0.0027 max mem: 19788 +Epoch: [14] [1910/2138] eta: 0:13:48 lr: 3.2878991885851935e-05 loss: 0.0300 (0.0380) time: 3.6456 data: 0.0026 max mem: 19788 +Epoch: [14] [1920/2138] eta: 0:13:12 lr: 3.2873479027764404e-05 loss: 0.0313 (0.0380) time: 3.6354 data: 0.0027 max mem: 19788 +Epoch: [14] [1930/2138] eta: 0:12:35 lr: 3.286796606695249e-05 loss: 0.0324 (0.0380) time: 3.6338 data: 0.0028 max mem: 19788 +Epoch: [14] [1940/2138] eta: 0:11:59 lr: 3.2862453003395136e-05 loss: 0.0343 (0.0380) time: 3.6347 data: 0.0027 max mem: 19788 +Epoch: [14] [1950/2138] eta: 0:11:23 lr: 3.2856939837071264e-05 loss: 0.0346 (0.0380) time: 3.6330 data: 0.0028 max mem: 19788 +Epoch: [14] [1960/2138] eta: 0:10:46 lr: 3.285142656795982e-05 loss: 0.0355 (0.0380) time: 3.6468 data: 0.0028 max mem: 19788 +Epoch: [14] [1970/2138] eta: 0:10:10 lr: 3.284591319603969e-05 loss: 0.0342 (0.0380) time: 3.6649 data: 0.0028 max mem: 19788 +Epoch: [14] [1980/2138] eta: 0:09:34 lr: 3.2840399721289804e-05 loss: 0.0309 (0.0379) time: 3.6608 data: 0.0028 max mem: 19788 +Epoch: [14] [1990/2138] eta: 0:08:57 lr: 3.283488614368906e-05 loss: 0.0298 (0.0379) time: 3.6398 data: 0.0028 max mem: 19788 +Epoch: [14] [2000/2138] eta: 0:08:21 lr: 3.282937246321634e-05 loss: 0.0343 (0.0379) time: 3.6292 data: 0.0029 max mem: 19788 +Epoch: [14] [2010/2138] eta: 0:07:45 lr: 3.282385867985053e-05 loss: 0.0346 (0.0379) time: 3.6351 data: 0.0029 max mem: 19788 +Epoch: [14] [2020/2138] eta: 0:07:08 lr: 3.2818344793570516e-05 loss: 0.0354 (0.0379) time: 3.6300 data: 0.0030 max mem: 19788 +Epoch: [14] [2030/2138] eta: 0:06:32 lr: 3.2812830804355146e-05 loss: 0.0354 (0.0379) time: 3.6225 data: 0.0030 max mem: 19788 +Epoch: [14] [2040/2138] eta: 0:05:56 lr: 3.280731671218329e-05 loss: 0.0350 (0.0379) time: 3.6223 data: 0.0030 max mem: 19788 +Epoch: [14] [2050/2138] eta: 0:05:19 lr: 3.2801802517033784e-05 loss: 0.0352 (0.0379) time: 3.6211 data: 0.0028 max mem: 19788 +Epoch: [14] [2060/2138] eta: 0:04:43 lr: 3.279628821888549e-05 loss: 0.0352 (0.0379) time: 3.6246 data: 0.0026 max mem: 19788 +Epoch: [14] [2070/2138] eta: 0:04:07 lr: 3.279077381771722e-05 loss: 0.0351 (0.0379) time: 3.6242 data: 0.0027 max mem: 19788 +Epoch: [14] [2080/2138] eta: 0:03:30 lr: 3.278525931350781e-05 loss: 0.0312 (0.0379) time: 3.6210 data: 0.0030 max mem: 19788 +Epoch: [14] [2090/2138] eta: 0:02:54 lr: 3.277974470623608e-05 loss: 0.0357 (0.0379) time: 3.6206 data: 0.0030 max mem: 19788 +Epoch: [14] [2100/2138] eta: 0:02:18 lr: 3.277422999588084e-05 loss: 0.0370 (0.0379) time: 3.6189 data: 0.0027 max mem: 19788 +Epoch: [14] [2110/2138] eta: 0:01:41 lr: 3.276871518242088e-05 loss: 0.0438 (0.0380) time: 3.6171 data: 0.0028 max mem: 19788 +Epoch: [14] [2120/2138] eta: 0:01:05 lr: 3.2763200265834994e-05 loss: 0.0417 (0.0380) time: 3.6163 data: 0.0031 max mem: 19788 +Epoch: [14] [2130/2138] eta: 0:00:29 lr: 3.2757685246101966e-05 loss: 0.0411 (0.0380) time: 3.6027 data: 0.0029 max mem: 19788 +Epoch: [14] Total time: 2:09:28 +Test: [ 0/21770] eta: 15:38:00 time: 2.5852 data: 2.3957 max mem: 19788 +Test: [ 100/21770] eta: 0:32:42 time: 0.0704 data: 0.0021 max mem: 19788 +Test: [ 200/21770] eta: 0:28:39 time: 0.0715 data: 0.0024 max mem: 19788 +Test: [ 300/21770] eta: 0:27:01 time: 0.0609 data: 0.0021 max mem: 19788 +Test: [ 400/21770] eta: 0:26:20 time: 0.0625 data: 0.0020 max mem: 19788 +Test: [ 500/21770] eta: 0:25:37 time: 0.0667 data: 0.0019 max mem: 19788 +Test: [ 600/21770] eta: 0:25:21 time: 0.0813 data: 0.0020 max mem: 19788 +Test: [ 700/21770] eta: 0:25:23 time: 0.0751 data: 0.0023 max mem: 19788 +Test: [ 800/21770] eta: 0:24:58 time: 0.0639 data: 0.0019 max mem: 19788 +Test: [ 900/21770] eta: 0:24:47 time: 0.0787 data: 0.0023 max mem: 19788 +Test: [ 1000/21770] eta: 0:24:31 time: 0.0706 data: 0.0021 max mem: 19788 +Test: [ 1100/21770] eta: 0:24:25 time: 0.0799 data: 0.0022 max mem: 19788 +Test: [ 1200/21770] eta: 0:24:09 time: 0.0610 data: 0.0018 max mem: 19788 +Test: [ 1300/21770] eta: 0:24:00 time: 0.0720 data: 0.0021 max mem: 19788 +Test: [ 1400/21770] eta: 0:23:42 time: 0.0650 data: 0.0018 max mem: 19788 +Test: [ 1500/21770] eta: 0:23:38 time: 0.0794 data: 0.0022 max mem: 19788 +Test: [ 1600/21770] eta: 0:23:27 time: 0.0793 data: 0.0022 max mem: 19788 +Test: [ 1700/21770] eta: 0:23:23 time: 0.0743 data: 0.0024 max mem: 19788 +Test: [ 1800/21770] eta: 0:23:08 time: 0.0676 data: 0.0019 max mem: 19788 +Test: [ 1900/21770] eta: 0:22:59 time: 0.0673 data: 0.0022 max mem: 19788 +Test: [ 2000/21770] eta: 0:22:47 time: 0.0623 data: 0.0018 max mem: 19788 +Test: [ 2100/21770] eta: 0:22:38 time: 0.0604 data: 0.0019 max mem: 19788 +Test: [ 2200/21770] eta: 0:22:33 time: 0.0681 data: 0.0022 max mem: 19788 +Test: [ 2300/21770] eta: 0:22:21 time: 0.0613 data: 0.0018 max mem: 19788 +Test: [ 2400/21770] eta: 0:22:09 time: 0.0648 data: 0.0019 max mem: 19788 +Test: [ 2500/21770] eta: 0:22:00 time: 0.0604 data: 0.0018 max mem: 19788 +Test: [ 2600/21770] eta: 0:21:53 time: 0.0642 data: 0.0018 max mem: 19788 +Test: [ 2700/21770] eta: 0:21:42 time: 0.0620 data: 0.0018 max mem: 19788 +Test: [ 2800/21770] eta: 0:21:33 time: 0.0643 data: 0.0019 max mem: 19788 +Test: [ 2900/21770] eta: 0:21:26 time: 0.0621 data: 0.0019 max mem: 19788 +Test: [ 3000/21770] eta: 0:21:18 time: 0.0631 data: 0.0019 max mem: 19788 +Test: [ 3100/21770] eta: 0:21:08 time: 0.0629 data: 0.0016 max mem: 19788 +Test: [ 3200/21770] eta: 0:21:01 time: 0.0795 data: 0.0022 max mem: 19788 +Test: [ 3300/21770] eta: 0:20:53 time: 0.0734 data: 0.0018 max mem: 19788 +Test: [ 3400/21770] eta: 0:20:46 time: 0.0684 data: 0.0017 max mem: 19788 +Test: [ 3500/21770] eta: 0:20:37 time: 0.0716 data: 0.0022 max mem: 19788 +Test: [ 3600/21770] eta: 0:20:28 time: 0.0670 data: 0.0020 max mem: 19788 +Test: [ 3700/21770] eta: 0:20:20 time: 0.0613 data: 0.0018 max mem: 19788 +Test: [ 3800/21770] eta: 0:20:12 time: 0.0723 data: 0.0021 max mem: 19788 +Test: [ 3900/21770] eta: 0:20:05 time: 0.0678 data: 0.0020 max mem: 19788 +Test: [ 4000/21770] eta: 0:19:58 time: 0.0623 data: 0.0018 max mem: 19788 +Test: [ 4100/21770] eta: 0:19:53 time: 0.0607 data: 0.0019 max mem: 19788 +Test: [ 4200/21770] eta: 0:19:47 time: 0.0747 data: 0.0022 max mem: 19788 +Test: [ 4300/21770] eta: 0:19:39 time: 0.0675 data: 0.0019 max mem: 19788 +Test: [ 4400/21770] eta: 0:19:30 time: 0.0609 data: 0.0018 max mem: 19788 +Test: [ 4500/21770] eta: 0:19:24 time: 0.0637 data: 0.0020 max mem: 19788 +Test: [ 4600/21770] eta: 0:19:15 time: 0.0608 data: 0.0018 max mem: 19788 +Test: [ 4700/21770] eta: 0:19:06 time: 0.0658 data: 0.0019 max mem: 19788 +Test: [ 4800/21770] eta: 0:18:59 time: 0.0628 data: 0.0017 max mem: 19788 +Test: [ 4900/21770] eta: 0:18:53 time: 0.0779 data: 0.0019 max mem: 19788 +Test: [ 5000/21770] eta: 0:18:46 time: 0.0614 data: 0.0019 max mem: 19788 +Test: [ 5100/21770] eta: 0:18:40 time: 0.0800 data: 0.0023 max mem: 19788 +Test: [ 5200/21770] eta: 0:18:33 time: 0.0689 data: 0.0017 max mem: 19788 +Test: [ 5300/21770] eta: 0:18:27 time: 0.0645 data: 0.0018 max mem: 19788 +Test: [ 5400/21770] eta: 0:18:20 time: 0.0598 data: 0.0017 max mem: 19788 +Test: [ 5500/21770] eta: 0:18:13 time: 0.0785 data: 0.0024 max mem: 19788 +Test: [ 5600/21770] eta: 0:18:08 time: 0.0666 data: 0.0018 max mem: 19788 +Test: [ 5700/21770] eta: 0:18:02 time: 0.0671 data: 0.0021 max mem: 19788 +Test: [ 5800/21770] eta: 0:17:56 time: 0.0758 data: 0.0021 max mem: 19788 +Test: [ 5900/21770] eta: 0:17:49 time: 0.0618 data: 0.0020 max mem: 19788 +Test: [ 6000/21770] eta: 0:17:42 time: 0.0729 data: 0.0018 max mem: 19788 +Test: [ 6100/21770] eta: 0:17:36 time: 0.0679 data: 0.0019 max mem: 19788 +Test: [ 6200/21770] eta: 0:17:29 time: 0.0639 data: 0.0021 max mem: 19788 +Test: [ 6300/21770] eta: 0:17:23 time: 0.0675 data: 0.0018 max mem: 19788 +Test: [ 6400/21770] eta: 0:17:16 time: 0.0617 data: 0.0018 max mem: 19788 +Test: [ 6500/21770] eta: 0:17:08 time: 0.0596 data: 0.0017 max mem: 19788 +Test: [ 6600/21770] eta: 0:17:00 time: 0.0662 data: 0.0019 max mem: 19788 +Test: [ 6700/21770] eta: 0:16:54 time: 0.0644 data: 0.0018 max mem: 19788 +Test: [ 6800/21770] eta: 0:16:48 time: 0.0782 data: 0.0022 max mem: 19788 +Test: [ 6900/21770] eta: 0:16:42 time: 0.0598 data: 0.0017 max mem: 19788 +Test: [ 7000/21770] eta: 0:16:36 time: 0.0757 data: 0.0018 max mem: 19788 +Test: [ 7100/21770] eta: 0:16:30 time: 0.0778 data: 0.0020 max mem: 19788 +Test: [ 7200/21770] eta: 0:16:23 time: 0.0647 data: 0.0017 max mem: 19788 +Test: [ 7300/21770] eta: 0:16:17 time: 0.0738 data: 0.0023 max mem: 19788 +Test: [ 7400/21770] eta: 0:16:10 time: 0.0615 data: 0.0018 max mem: 19788 +Test: [ 7500/21770] eta: 0:16:03 time: 0.0634 data: 0.0021 max mem: 19788 +Test: [ 7600/21770] eta: 0:15:56 time: 0.0810 data: 0.0020 max mem: 19788 +Test: [ 7700/21770] eta: 0:15:50 time: 0.0749 data: 0.0023 max mem: 19788 +Test: [ 7800/21770] eta: 0:15:44 time: 0.0628 data: 0.0018 max mem: 19788 +Test: [ 7900/21770] eta: 0:15:36 time: 0.0632 data: 0.0020 max mem: 19788 +Test: [ 8000/21770] eta: 0:15:30 time: 0.0775 data: 0.0019 max mem: 19788 +Test: [ 8100/21770] eta: 0:15:24 time: 0.0658 data: 0.0019 max mem: 19788 +Test: [ 8200/21770] eta: 0:15:17 time: 0.0597 data: 0.0017 max mem: 19788 +Test: [ 8300/21770] eta: 0:15:11 time: 0.0667 data: 0.0019 max mem: 19788 +Test: [ 8400/21770] eta: 0:15:04 time: 0.0716 data: 0.0019 max mem: 19788 +Test: [ 8500/21770] eta: 0:14:57 time: 0.0670 data: 0.0018 max mem: 19788 +Test: [ 8600/21770] eta: 0:14:50 time: 0.0651 data: 0.0020 max mem: 19788 +Test: [ 8700/21770] eta: 0:14:44 time: 0.0641 data: 0.0017 max mem: 19788 +Test: [ 8800/21770] eta: 0:14:37 time: 0.0761 data: 0.0019 max mem: 19788 +Test: [ 8900/21770] eta: 0:14:30 time: 0.0631 data: 0.0018 max mem: 19788 +Test: [ 9000/21770] eta: 0:14:23 time: 0.0797 data: 0.0023 max mem: 19788 +Test: [ 9100/21770] eta: 0:14:16 time: 0.0632 data: 0.0017 max mem: 19788 +Test: [ 9200/21770] eta: 0:14:10 time: 0.0682 data: 0.0022 max mem: 19788 +Test: [ 9300/21770] eta: 0:14:03 time: 0.0632 data: 0.0020 max mem: 19788 +Test: [ 9400/21770] eta: 0:13:56 time: 0.0618 data: 0.0020 max mem: 19788 +Test: [ 9500/21770] eta: 0:13:50 time: 0.0673 data: 0.0018 max mem: 19788 +Test: [ 9600/21770] eta: 0:13:42 time: 0.0620 data: 0.0020 max mem: 19788 +Test: [ 9700/21770] eta: 0:13:36 time: 0.0688 data: 0.0018 max mem: 19788 +Test: [ 9800/21770] eta: 0:13:30 time: 0.0660 data: 0.0021 max mem: 19788 +Test: [ 9900/21770] eta: 0:13:23 time: 0.0665 data: 0.0019 max mem: 19788 +Test: [10000/21770] eta: 0:13:18 time: 0.0730 data: 0.0021 max mem: 19788 +Test: [10100/21770] eta: 0:13:12 time: 0.0805 data: 0.0025 max mem: 19788 +Test: [10200/21770] eta: 0:13:05 time: 0.0674 data: 0.0020 max mem: 19788 +Test: [10300/21770] eta: 0:12:57 time: 0.0604 data: 0.0018 max mem: 19788 +Test: [10400/21770] eta: 0:12:50 time: 0.0677 data: 0.0020 max mem: 19788 +Test: [10500/21770] eta: 0:12:43 time: 0.0662 data: 0.0018 max mem: 19788 +Test: [10600/21770] eta: 0:12:37 time: 0.0760 data: 0.0019 max mem: 19788 +Test: [10700/21770] eta: 0:12:31 time: 0.0782 data: 0.0025 max mem: 19788 +Test: [10800/21770] eta: 0:12:24 time: 0.0659 data: 0.0018 max mem: 19788 +Test: [10900/21770] eta: 0:12:17 time: 0.0612 data: 0.0018 max mem: 19788 +Test: [11000/21770] eta: 0:12:10 time: 0.0650 data: 0.0018 max mem: 19788 +Test: [11100/21770] eta: 0:12:04 time: 0.0638 data: 0.0019 max mem: 19788 +Test: [11200/21770] eta: 0:11:57 time: 0.0645 data: 0.0020 max mem: 19788 +Test: [11300/21770] eta: 0:11:50 time: 0.0603 data: 0.0019 max mem: 19788 +Test: [11400/21770] eta: 0:11:44 time: 0.0630 data: 0.0016 max mem: 19788 +Test: [11500/21770] eta: 0:11:37 time: 0.0806 data: 0.0021 max mem: 19788 +Test: [11600/21770] eta: 0:11:31 time: 0.0731 data: 0.0021 max mem: 19788 +Test: [11700/21770] eta: 0:11:23 time: 0.0594 data: 0.0017 max mem: 19788 +Test: [11800/21770] eta: 0:11:16 time: 0.0673 data: 0.0018 max mem: 19788 +Test: [11900/21770] eta: 0:11:09 time: 0.0632 data: 0.0020 max mem: 19788 +Test: [12000/21770] eta: 0:11:02 time: 0.0635 data: 0.0017 max mem: 19788 +Test: [12100/21770] eta: 0:10:56 time: 0.0634 data: 0.0019 max mem: 19788 +Test: [12200/21770] eta: 0:10:49 time: 0.0819 data: 0.0024 max mem: 19788 +Test: [12300/21770] eta: 0:10:42 time: 0.0627 data: 0.0018 max mem: 19788 +Test: [12400/21770] eta: 0:10:36 time: 0.0661 data: 0.0021 max mem: 19788 +Test: [12500/21770] eta: 0:10:30 time: 0.0701 data: 0.0021 max mem: 19788 +Test: [12600/21770] eta: 0:10:23 time: 0.0682 data: 0.0020 max mem: 19788 +Test: [12700/21770] eta: 0:10:16 time: 0.0783 data: 0.0023 max mem: 19788 +Test: [12800/21770] eta: 0:10:09 time: 0.0609 data: 0.0016 max mem: 19788 +Test: [12900/21770] eta: 0:10:02 time: 0.0739 data: 0.0018 max mem: 19788 +Test: [13000/21770] eta: 0:09:56 time: 0.0626 data: 0.0017 max mem: 19788 +Test: [13100/21770] eta: 0:09:49 time: 0.0747 data: 0.0021 max mem: 19788 +Test: [13200/21770] eta: 0:09:42 time: 0.0601 data: 0.0018 max mem: 19788 +Test: [13300/21770] eta: 0:09:35 time: 0.0617 data: 0.0018 max mem: 19788 +Test: [13400/21770] eta: 0:09:28 time: 0.0804 data: 0.0025 max mem: 19788 +Test: [13500/21770] eta: 0:09:21 time: 0.0624 data: 0.0018 max mem: 19788 +Test: [13600/21770] eta: 0:09:14 time: 0.0758 data: 0.0022 max mem: 19788 +Test: [13700/21770] eta: 0:09:08 time: 0.0724 data: 0.0021 max mem: 19788 +Test: [13800/21770] eta: 0:09:01 time: 0.0596 data: 0.0017 max mem: 19788 +Test: [13900/21770] eta: 0:08:55 time: 0.0752 data: 0.0022 max mem: 19788 +Test: [14000/21770] eta: 0:08:48 time: 0.0747 data: 0.0022 max mem: 19788 +Test: [14100/21770] eta: 0:08:41 time: 0.0716 data: 0.0020 max mem: 19788 +Test: [14200/21770] eta: 0:08:35 time: 0.0644 data: 0.0018 max mem: 19788 +Test: [14300/21770] eta: 0:08:28 time: 0.0701 data: 0.0019 max mem: 19788 +Test: [14400/21770] eta: 0:08:21 time: 0.0798 data: 0.0024 max mem: 19788 +Test: [14500/21770] eta: 0:08:14 time: 0.0762 data: 0.0019 max mem: 19788 +Test: [14600/21770] eta: 0:08:07 time: 0.0700 data: 0.0019 max mem: 19788 +Test: [14700/21770] eta: 0:08:00 time: 0.0761 data: 0.0020 max mem: 19788 +Test: [14800/21770] eta: 0:07:53 time: 0.0642 data: 0.0018 max mem: 19788 +Test: [14900/21770] eta: 0:07:47 time: 0.0695 data: 0.0018 max mem: 19788 +Test: [15000/21770] eta: 0:07:40 time: 0.0730 data: 0.0020 max mem: 19788 +Test: [15100/21770] eta: 0:07:33 time: 0.0752 data: 0.0019 max mem: 19788 +Test: [15200/21770] eta: 0:07:26 time: 0.0616 data: 0.0018 max mem: 19788 +Test: [15300/21770] eta: 0:07:20 time: 0.0726 data: 0.0022 max mem: 19788 +Test: [15400/21770] eta: 0:07:13 time: 0.0635 data: 0.0019 max mem: 19788 +Test: [15500/21770] eta: 0:07:06 time: 0.0697 data: 0.0019 max mem: 19788 +Test: [15600/21770] eta: 0:06:59 time: 0.0645 data: 0.0018 max mem: 19788 +Test: [15700/21770] eta: 0:06:52 time: 0.0764 data: 0.0024 max mem: 19788 +Test: [15800/21770] eta: 0:06:45 time: 0.0626 data: 0.0018 max mem: 19788 +Test: [15900/21770] eta: 0:06:39 time: 0.0784 data: 0.0022 max mem: 19788 +Test: [16000/21770] eta: 0:06:32 time: 0.0616 data: 0.0018 max mem: 19788 +Test: [16100/21770] eta: 0:06:25 time: 0.0780 data: 0.0022 max mem: 19788 +Test: [16200/21770] eta: 0:06:19 time: 0.0821 data: 0.0024 max mem: 19788 +Test: [16300/21770] eta: 0:06:12 time: 0.0705 data: 0.0022 max mem: 19788 +Test: [16400/21770] eta: 0:06:05 time: 0.0659 data: 0.0018 max mem: 19788 +Test: [16500/21770] eta: 0:05:58 time: 0.0761 data: 0.0020 max mem: 19788 +Test: [16600/21770] eta: 0:05:51 time: 0.0624 data: 0.0017 max mem: 19788 +Test: [16700/21770] eta: 0:05:44 time: 0.0718 data: 0.0020 max mem: 19788 +Test: [16800/21770] eta: 0:05:37 time: 0.0703 data: 0.0022 max mem: 19788 +Test: [16900/21770] eta: 0:05:31 time: 0.0606 data: 0.0017 max mem: 19788 +Test: [17000/21770] eta: 0:05:24 time: 0.0597 data: 0.0018 max mem: 19788 +Test: [17100/21770] eta: 0:05:17 time: 0.0597 data: 0.0018 max mem: 19788 +Test: [17200/21770] eta: 0:05:10 time: 0.0738 data: 0.0023 max mem: 19788 +Test: [17300/21770] eta: 0:05:03 time: 0.0641 data: 0.0020 max mem: 19788 +Test: [17400/21770] eta: 0:04:57 time: 0.0669 data: 0.0020 max mem: 19788 +Test: [17500/21770] eta: 0:04:50 time: 0.0733 data: 0.0018 max mem: 19788 +Test: [17600/21770] eta: 0:04:43 time: 0.0627 data: 0.0018 max mem: 19788 +Test: [17700/21770] eta: 0:04:36 time: 0.0650 data: 0.0020 max mem: 19788 +Test: [17800/21770] eta: 0:04:30 time: 0.0813 data: 0.0024 max mem: 19788 +Test: [17900/21770] eta: 0:04:23 time: 0.0606 data: 0.0019 max mem: 19788 +Test: [18000/21770] eta: 0:04:16 time: 0.0745 data: 0.0020 max mem: 19788 +Test: [18100/21770] eta: 0:04:09 time: 0.0666 data: 0.0018 max mem: 19788 +Test: [18200/21770] eta: 0:04:02 time: 0.0715 data: 0.0019 max mem: 19788 +Test: [18300/21770] eta: 0:03:55 time: 0.0617 data: 0.0018 max mem: 19788 +Test: [18400/21770] eta: 0:03:49 time: 0.0666 data: 0.0019 max mem: 19788 +Test: [18500/21770] eta: 0:03:42 time: 0.0732 data: 0.0020 max mem: 19788 +Test: [18600/21770] eta: 0:03:35 time: 0.0714 data: 0.0019 max mem: 19788 +Test: [18700/21770] eta: 0:03:28 time: 0.0612 data: 0.0019 max mem: 19788 +Test: [18800/21770] eta: 0:03:21 time: 0.0812 data: 0.0024 max mem: 19788 +Test: [18900/21770] eta: 0:03:15 time: 0.0641 data: 0.0021 max mem: 19788 +Test: [19000/21770] eta: 0:03:08 time: 0.0770 data: 0.0021 max mem: 19788 +Test: [19100/21770] eta: 0:03:01 time: 0.0654 data: 0.0017 max mem: 19788 +Test: [19200/21770] eta: 0:02:54 time: 0.0702 data: 0.0019 max mem: 19788 +Test: [19300/21770] eta: 0:02:48 time: 0.0652 data: 0.0020 max mem: 19788 +Test: [19400/21770] eta: 0:02:41 time: 0.0720 data: 0.0022 max mem: 19788 +Test: [19500/21770] eta: 0:02:34 time: 0.0739 data: 0.0020 max mem: 19788 +Test: [19600/21770] eta: 0:02:27 time: 0.0741 data: 0.0020 max mem: 19788 +Test: [19700/21770] eta: 0:02:20 time: 0.0736 data: 0.0023 max mem: 19788 +Test: [19800/21770] eta: 0:02:14 time: 0.0790 data: 0.0024 max mem: 19788 +Test: [19900/21770] eta: 0:02:07 time: 0.0803 data: 0.0025 max mem: 19788 +Test: [20000/21770] eta: 0:02:00 time: 0.0795 data: 0.0021 max mem: 19788 +Test: [20100/21770] eta: 0:01:53 time: 0.0637 data: 0.0018 max mem: 19788 +Test: [20200/21770] eta: 0:01:46 time: 0.0696 data: 0.0017 max mem: 19788 +Test: [20300/21770] eta: 0:01:40 time: 0.0819 data: 0.0021 max mem: 19788 +Test: [20400/21770] eta: 0:01:33 time: 0.0714 data: 0.0020 max mem: 19788 +Test: [20500/21770] eta: 0:01:26 time: 0.0617 data: 0.0018 max mem: 19788 +Test: [20600/21770] eta: 0:01:19 time: 0.0793 data: 0.0023 max mem: 19788 +Test: [20700/21770] eta: 0:01:12 time: 0.0817 data: 0.0018 max mem: 19788 +Test: [20800/21770] eta: 0:01:06 time: 0.0794 data: 0.0019 max mem: 19788 +Test: [20900/21770] eta: 0:00:59 time: 0.0676 data: 0.0019 max mem: 19788 +Test: [21000/21770] eta: 0:00:52 time: 0.0659 data: 0.0019 max mem: 19788 +Test: [21100/21770] eta: 0:00:45 time: 0.0609 data: 0.0018 max mem: 19788 +Test: [21200/21770] eta: 0:00:38 time: 0.0622 data: 0.0018 max mem: 19788 +Test: [21300/21770] eta: 0:00:32 time: 0.0705 data: 0.0020 max mem: 19788 +Test: [21400/21770] eta: 0:00:25 time: 0.0777 data: 0.0021 max mem: 19788 +Test: [21500/21770] eta: 0:00:18 time: 0.0699 data: 0.0021 max mem: 19788 +Test: [21600/21770] eta: 0:00:11 time: 0.0645 data: 0.0019 max mem: 19788 +Test: [21700/21770] eta: 0:00:04 time: 0.0637 data: 0.0019 max mem: 19788 +Test: Total time: 0:24:47 +Final results: +Mean IoU is 62.26 + + precision@0.5 = 69.09 + precision@0.6 = 63.64 + precision@0.7 = 56.47 + precision@0.8 = 45.72 + precision@0.9 = 22.78 + overall IoU = 63.26 + mean IoU = 62.26 + +Mean accuracy for one-to-zero sample is 82.55 + +Average object IoU 0.6226250896984419 +Overall IoU 63.25818634033203 +Epoch: [15] [ 0/2138] eta: 6:01:33 lr: 3.2753273156035344e-05 loss: 0.0897 (0.0897) time: 10.1465 data: 1.6149 max mem: 19788 +Epoch: [15] [ 10/2138] eta: 2:29:53 lr: 3.2747757950583966e-05 loss: 0.0301 (0.0352) time: 4.2262 data: 0.1493 max mem: 19788 +Epoch: [15] [ 20/2138] eta: 2:19:26 lr: 3.2742242641926e-05 loss: 0.0278 (0.0328) time: 3.6403 data: 0.0027 max mem: 19788 +Epoch: [15] [ 30/2138] eta: 2:15:16 lr: 3.27367272300402e-05 loss: 0.0278 (0.0327) time: 3.6439 data: 0.0028 max mem: 19788 +Epoch: [15] [ 40/2138] eta: 2:12:49 lr: 3.2731211714905294e-05 loss: 0.0322 (0.0353) time: 3.6396 data: 0.0031 max mem: 19788 +Epoch: [15] [ 50/2138] eta: 2:11:02 lr: 3.2725696096500024e-05 loss: 0.0331 (0.0364) time: 3.6335 data: 0.0032 max mem: 19788 +Epoch: [15] [ 60/2138] eta: 2:09:41 lr: 3.2720180374803125e-05 loss: 0.0297 (0.0357) time: 3.6336 data: 0.0030 max mem: 19788 +Epoch: [15] [ 70/2138] eta: 2:08:32 lr: 3.2714664549793306e-05 loss: 0.0256 (0.0346) time: 3.6386 data: 0.0029 max mem: 19788 +Epoch: [15] [ 80/2138] eta: 2:07:31 lr: 3.2709148621449276e-05 loss: 0.0299 (0.0349) time: 3.6365 data: 0.0031 max mem: 19788 +Epoch: [15] [ 90/2138] eta: 2:06:35 lr: 3.2703632589749736e-05 loss: 0.0309 (0.0351) time: 3.6341 data: 0.0030 max mem: 19788 +Epoch: [15] [ 100/2138] eta: 2:05:42 lr: 3.269811645467339e-05 loss: 0.0307 (0.0347) time: 3.6318 data: 0.0029 max mem: 19788 +Epoch: [15] [ 110/2138] eta: 2:04:57 lr: 3.269260021619891e-05 loss: 0.0324 (0.0353) time: 3.6437 data: 0.0029 max mem: 19788 +Epoch: [15] [ 120/2138] eta: 2:04:09 lr: 3.2687083874304976e-05 loss: 0.0347 (0.0352) time: 3.6454 data: 0.0029 max mem: 19788 +Epoch: [15] [ 130/2138] eta: 2:03:24 lr: 3.268156742897025e-05 loss: 0.0304 (0.0351) time: 3.6348 data: 0.0028 max mem: 19788 +Epoch: [15] [ 140/2138] eta: 2:02:40 lr: 3.267605088017341e-05 loss: 0.0303 (0.0349) time: 3.6376 data: 0.0029 max mem: 19788 +Epoch: [15] [ 150/2138] eta: 2:01:57 lr: 3.2670534227893094e-05 loss: 0.0301 (0.0347) time: 3.6378 data: 0.0028 max mem: 19788 +Epoch: [15] [ 160/2138] eta: 2:01:14 lr: 3.266501747210794e-05 loss: 0.0321 (0.0350) time: 3.6328 data: 0.0027 max mem: 19788 +Epoch: [15] [ 170/2138] eta: 2:00:32 lr: 3.2659500612796585e-05 loss: 0.0318 (0.0349) time: 3.6311 data: 0.0028 max mem: 19788 +Epoch: [15] [ 180/2138] eta: 1:59:51 lr: 3.265398364993767e-05 loss: 0.0334 (0.0360) time: 3.6367 data: 0.0030 max mem: 19788 +Epoch: [15] [ 190/2138] eta: 1:59:11 lr: 3.264846658350979e-05 loss: 0.0367 (0.0359) time: 3.6376 data: 0.0031 max mem: 19788 +Epoch: [15] [ 200/2138] eta: 1:58:30 lr: 3.264294941349156e-05 loss: 0.0270 (0.0354) time: 3.6322 data: 0.0030 max mem: 19788 +Epoch: [15] [ 210/2138] eta: 1:57:49 lr: 3.263743213986159e-05 loss: 0.0327 (0.0357) time: 3.6254 data: 0.0029 max mem: 19788 +Epoch: [15] [ 220/2138] eta: 1:57:09 lr: 3.263191476259847e-05 loss: 0.0354 (0.0355) time: 3.6262 data: 0.0029 max mem: 19788 +Epoch: [15] [ 230/2138] eta: 1:56:29 lr: 3.2626397281680774e-05 loss: 0.0319 (0.0356) time: 3.6282 data: 0.0030 max mem: 19788 +Epoch: [15] [ 240/2138] eta: 1:55:50 lr: 3.262087969708708e-05 loss: 0.0340 (0.0357) time: 3.6257 data: 0.0029 max mem: 19788 +Epoch: [15] [ 250/2138] eta: 1:55:10 lr: 3.261536200879596e-05 loss: 0.0309 (0.0357) time: 3.6261 data: 0.0027 max mem: 19788 +Epoch: [15] [ 260/2138] eta: 1:54:31 lr: 3.2609844216785975e-05 loss: 0.0281 (0.0355) time: 3.6256 data: 0.0028 max mem: 19788 +Epoch: [15] [ 270/2138] eta: 1:53:52 lr: 3.2604326321035665e-05 loss: 0.0337 (0.0356) time: 3.6229 data: 0.0028 max mem: 19788 +Epoch: [15] [ 280/2138] eta: 1:53:13 lr: 3.2598808321523575e-05 loss: 0.0344 (0.0355) time: 3.6240 data: 0.0029 max mem: 19788 +Epoch: [15] [ 290/2138] eta: 1:52:34 lr: 3.259329021822823e-05 loss: 0.0344 (0.0356) time: 3.6207 data: 0.0027 max mem: 19788 +Epoch: [15] [ 300/2138] eta: 1:51:55 lr: 3.258777201112818e-05 loss: 0.0319 (0.0355) time: 3.6140 data: 0.0027 max mem: 19788 +Epoch: [15] [ 310/2138] eta: 1:51:16 lr: 3.258225370020192e-05 loss: 0.0338 (0.0356) time: 3.6108 data: 0.0028 max mem: 19788 +Epoch: [15] [ 320/2138] eta: 1:50:37 lr: 3.257673528542795e-05 loss: 0.0348 (0.0355) time: 3.6128 data: 0.0028 max mem: 19788 +Epoch: [15] [ 330/2138] eta: 1:49:59 lr: 3.257121676678478e-05 loss: 0.0328 (0.0355) time: 3.6143 data: 0.0029 max mem: 19788 +Epoch: [15] [ 340/2138] eta: 1:49:20 lr: 3.256569814425092e-05 loss: 0.0352 (0.0356) time: 3.6116 data: 0.0029 max mem: 19788 +Epoch: [15] [ 350/2138] eta: 1:48:42 lr: 3.256017941780481e-05 loss: 0.0353 (0.0356) time: 3.6158 data: 0.0029 max mem: 19788 +Epoch: [15] [ 360/2138] eta: 1:48:04 lr: 3.255466058742496e-05 loss: 0.0330 (0.0355) time: 3.6180 data: 0.0029 max mem: 19788 +Epoch: [15] [ 370/2138] eta: 1:47:26 lr: 3.254914165308981e-05 loss: 0.0330 (0.0356) time: 3.6146 data: 0.0030 max mem: 19788 +Epoch: [15] [ 380/2138] eta: 1:46:48 lr: 3.254362261477783e-05 loss: 0.0354 (0.0356) time: 3.6126 data: 0.0029 max mem: 19788 +Epoch: [15] [ 390/2138] eta: 1:46:10 lr: 3.2538103472467464e-05 loss: 0.0366 (0.0357) time: 3.6124 data: 0.0028 max mem: 19788 +Epoch: [15] [ 400/2138] eta: 1:45:32 lr: 3.253258422613715e-05 loss: 0.0367 (0.0358) time: 3.6144 data: 0.0029 max mem: 19788 +Epoch: [15] [ 410/2138] eta: 1:44:55 lr: 3.2527064875765325e-05 loss: 0.0413 (0.0362) time: 3.6173 data: 0.0029 max mem: 19788 +Epoch: [15] [ 420/2138] eta: 1:44:17 lr: 3.2521545421330404e-05 loss: 0.0378 (0.0362) time: 3.6162 data: 0.0027 max mem: 19788 +Epoch: [15] [ 430/2138] eta: 1:43:40 lr: 3.251602586281079e-05 loss: 0.0330 (0.0363) time: 3.6151 data: 0.0026 max mem: 19788 +Epoch: [15] [ 440/2138] eta: 1:43:02 lr: 3.251050620018492e-05 loss: 0.0358 (0.0364) time: 3.6151 data: 0.0027 max mem: 19788 +Epoch: [15] [ 450/2138] eta: 1:42:25 lr: 3.250498643343116e-05 loss: 0.0354 (0.0363) time: 3.6142 data: 0.0027 max mem: 19788 +Epoch: [15] [ 460/2138] eta: 1:41:48 lr: 3.249946656252791e-05 loss: 0.0321 (0.0365) time: 3.6162 data: 0.0028 max mem: 19788 +Epoch: [15] [ 470/2138] eta: 1:41:10 lr: 3.249394658745355e-05 loss: 0.0392 (0.0365) time: 3.6167 data: 0.0031 max mem: 19788 +Epoch: [15] [ 480/2138] eta: 1:40:33 lr: 3.2488426508186446e-05 loss: 0.0348 (0.0364) time: 3.6156 data: 0.0031 max mem: 19788 +Epoch: [15] [ 490/2138] eta: 1:39:56 lr: 3.248290632470497e-05 loss: 0.0306 (0.0363) time: 3.6122 data: 0.0030 max mem: 19788 +Epoch: [15] [ 500/2138] eta: 1:39:19 lr: 3.247738603698747e-05 loss: 0.0325 (0.0365) time: 3.6138 data: 0.0033 max mem: 19788 +Epoch: [15] [ 510/2138] eta: 1:38:42 lr: 3.247186564501228e-05 loss: 0.0331 (0.0364) time: 3.6158 data: 0.0033 max mem: 19788 +Epoch: [15] [ 520/2138] eta: 1:38:05 lr: 3.246634514875776e-05 loss: 0.0331 (0.0364) time: 3.6163 data: 0.0030 max mem: 19788 +Epoch: [15] [ 530/2138] eta: 1:37:28 lr: 3.2460824548202215e-05 loss: 0.0329 (0.0364) time: 3.6209 data: 0.0028 max mem: 19788 +Epoch: [15] [ 540/2138] eta: 1:36:51 lr: 3.245530384332398e-05 loss: 0.0329 (0.0363) time: 3.6235 data: 0.0028 max mem: 19788 +Epoch: [15] [ 550/2138] eta: 1:36:14 lr: 3.244978303410135e-05 loss: 0.0332 (0.0363) time: 3.6219 data: 0.0028 max mem: 19788 +Epoch: [15] [ 560/2138] eta: 1:35:38 lr: 3.244426212051265e-05 loss: 0.0325 (0.0363) time: 3.6265 data: 0.0028 max mem: 19788 +Epoch: [15] [ 570/2138] eta: 1:35:01 lr: 3.2438741102536154e-05 loss: 0.0324 (0.0363) time: 3.6288 data: 0.0028 max mem: 19788 +Epoch: [15] [ 580/2138] eta: 1:34:24 lr: 3.243321998015016e-05 loss: 0.0417 (0.0365) time: 3.6238 data: 0.0027 max mem: 19788 +Epoch: [15] [ 590/2138] eta: 1:33:48 lr: 3.2427698753332925e-05 loss: 0.0356 (0.0365) time: 3.6275 data: 0.0029 max mem: 19788 +Epoch: [15] [ 600/2138] eta: 1:33:11 lr: 3.242217742206273e-05 loss: 0.0327 (0.0365) time: 3.6267 data: 0.0031 max mem: 19788 +Epoch: [15] [ 610/2138] eta: 1:32:35 lr: 3.241665598631784e-05 loss: 0.0345 (0.0366) time: 3.6256 data: 0.0030 max mem: 19788 +Epoch: [15] [ 620/2138] eta: 1:31:58 lr: 3.24111344460765e-05 loss: 0.0376 (0.0367) time: 3.6301 data: 0.0027 max mem: 19788 +Epoch: [15] [ 630/2138] eta: 1:31:22 lr: 3.240561280131694e-05 loss: 0.0350 (0.0366) time: 3.6312 data: 0.0027 max mem: 19788 +Epoch: [15] [ 640/2138] eta: 1:30:45 lr: 3.24000910520174e-05 loss: 0.0308 (0.0365) time: 3.6309 data: 0.0028 max mem: 19788 +Epoch: [15] [ 650/2138] eta: 1:30:09 lr: 3.239456919815612e-05 loss: 0.0337 (0.0365) time: 3.6318 data: 0.0028 max mem: 19788 +Epoch: [15] [ 660/2138] eta: 1:29:33 lr: 3.238904723971129e-05 loss: 0.0350 (0.0365) time: 3.6340 data: 0.0029 max mem: 19788 +Epoch: [15] [ 670/2138] eta: 1:28:56 lr: 3.2383525176661136e-05 loss: 0.0358 (0.0365) time: 3.6382 data: 0.0030 max mem: 19788 +Epoch: [15] [ 680/2138] eta: 1:28:20 lr: 3.237800300898386e-05 loss: 0.0344 (0.0365) time: 3.6341 data: 0.0029 max mem: 19788 +Epoch: [15] [ 690/2138] eta: 1:27:43 lr: 3.237248073665763e-05 loss: 0.0333 (0.0365) time: 3.6333 data: 0.0028 max mem: 19788 +Epoch: [15] [ 700/2138] eta: 1:27:07 lr: 3.236695835966064e-05 loss: 0.0333 (0.0367) time: 3.6381 data: 0.0028 max mem: 19788 +Epoch: [15] [ 710/2138] eta: 1:26:31 lr: 3.236143587797106e-05 loss: 0.0363 (0.0367) time: 3.6378 data: 0.0030 max mem: 19788 +Epoch: [15] [ 720/2138] eta: 1:25:55 lr: 3.235591329156706e-05 loss: 0.0359 (0.0368) time: 3.6437 data: 0.0030 max mem: 19788 +Epoch: [15] [ 730/2138] eta: 1:25:18 lr: 3.2350390600426786e-05 loss: 0.0332 (0.0368) time: 3.6356 data: 0.0028 max mem: 19788 +Epoch: [15] [ 740/2138] eta: 1:24:42 lr: 3.2344867804528386e-05 loss: 0.0292 (0.0367) time: 3.6239 data: 0.0028 max mem: 19788 +Epoch: [15] [ 750/2138] eta: 1:24:05 lr: 3.233934490385e-05 loss: 0.0292 (0.0366) time: 3.6234 data: 0.0027 max mem: 19788 +Epoch: [15] [ 760/2138] eta: 1:23:29 lr: 3.2333821898369754e-05 loss: 0.0332 (0.0366) time: 3.6260 data: 0.0029 max mem: 19788 +Epoch: [15] [ 770/2138] eta: 1:22:53 lr: 3.2328298788065774e-05 loss: 0.0359 (0.0366) time: 3.6475 data: 0.0029 max mem: 19788 +Epoch: [15] [ 780/2138] eta: 1:22:16 lr: 3.2322775572916165e-05 loss: 0.0372 (0.0367) time: 3.6442 data: 0.0030 max mem: 19788 +Epoch: [15] [ 790/2138] eta: 1:21:40 lr: 3.231725225289903e-05 loss: 0.0380 (0.0367) time: 3.6258 data: 0.0032 max mem: 19788 +Epoch: [15] [ 800/2138] eta: 1:21:03 lr: 3.2311728827992474e-05 loss: 0.0331 (0.0366) time: 3.6259 data: 0.0032 max mem: 19788 +Epoch: [15] [ 810/2138] eta: 1:20:27 lr: 3.230620529817457e-05 loss: 0.0314 (0.0366) time: 3.6259 data: 0.0030 max mem: 19788 +Epoch: [15] [ 820/2138] eta: 1:19:50 lr: 3.2300681663423386e-05 loss: 0.0324 (0.0366) time: 3.6313 data: 0.0028 max mem: 19788 +Epoch: [15] [ 830/2138] eta: 1:19:14 lr: 3.229515792371701e-05 loss: 0.0320 (0.0365) time: 3.6298 data: 0.0030 max mem: 19788 +Epoch: [15] [ 840/2138] eta: 1:18:37 lr: 3.2289634079033496e-05 loss: 0.0271 (0.0364) time: 3.6241 data: 0.0031 max mem: 19788 +Epoch: [15] [ 850/2138] eta: 1:18:01 lr: 3.228411012935089e-05 loss: 0.0295 (0.0364) time: 3.6228 data: 0.0029 max mem: 19788 +Epoch: [15] [ 860/2138] eta: 1:17:24 lr: 3.2278586074647226e-05 loss: 0.0342 (0.0364) time: 3.6210 data: 0.0027 max mem: 19788 +Epoch: [15] [ 870/2138] eta: 1:16:48 lr: 3.227306191490054e-05 loss: 0.0323 (0.0363) time: 3.6212 data: 0.0028 max mem: 19788 +Epoch: [15] [ 880/2138] eta: 1:16:11 lr: 3.226753765008887e-05 loss: 0.0311 (0.0363) time: 3.6276 data: 0.0030 max mem: 19788 +Epoch: [15] [ 890/2138] eta: 1:15:35 lr: 3.226201328019023e-05 loss: 0.0314 (0.0363) time: 3.6290 data: 0.0031 max mem: 19788 +Epoch: [15] [ 900/2138] eta: 1:14:58 lr: 3.225648880518261e-05 loss: 0.0325 (0.0363) time: 3.6203 data: 0.0028 max mem: 19788 +Epoch: [15] [ 910/2138] eta: 1:14:22 lr: 3.2250964225044e-05 loss: 0.0310 (0.0363) time: 3.6176 data: 0.0029 max mem: 19788 +Epoch: [15] [ 920/2138] eta: 1:13:45 lr: 3.224543953975242e-05 loss: 0.0306 (0.0362) time: 3.6215 data: 0.0030 max mem: 19788 +Epoch: [15] [ 930/2138] eta: 1:13:09 lr: 3.2239914749285834e-05 loss: 0.0332 (0.0363) time: 3.6287 data: 0.0030 max mem: 19788 +Epoch: [15] [ 940/2138] eta: 1:12:32 lr: 3.223438985362221e-05 loss: 0.0368 (0.0363) time: 3.6274 data: 0.0033 max mem: 19788 +Epoch: [15] [ 950/2138] eta: 1:11:56 lr: 3.22288648527395e-05 loss: 0.0368 (0.0363) time: 3.6199 data: 0.0033 max mem: 19788 +Epoch: [15] [ 960/2138] eta: 1:11:19 lr: 3.222333974661568e-05 loss: 0.0374 (0.0363) time: 3.6198 data: 0.0032 max mem: 19788 +Epoch: [15] [ 970/2138] eta: 1:10:43 lr: 3.2217814535228695e-05 loss: 0.0364 (0.0362) time: 3.6202 data: 0.0030 max mem: 19788 +Epoch: [15] [ 980/2138] eta: 1:10:07 lr: 3.2212289218556455e-05 loss: 0.0264 (0.0362) time: 3.6246 data: 0.0028 max mem: 19788 +Epoch: [15] [ 990/2138] eta: 1:09:30 lr: 3.220676379657692e-05 loss: 0.0301 (0.0362) time: 3.6235 data: 0.0028 max mem: 19788 +Epoch: [15] [1000/2138] eta: 1:08:54 lr: 3.220123826926798e-05 loss: 0.0351 (0.0362) time: 3.6174 data: 0.0030 max mem: 19788 +Epoch: [15] [1010/2138] eta: 1:08:17 lr: 3.219571263660755e-05 loss: 0.0327 (0.0361) time: 3.6184 data: 0.0029 max mem: 19788 +Epoch: [15] [1020/2138] eta: 1:07:41 lr: 3.2190186898573544e-05 loss: 0.0297 (0.0361) time: 3.6245 data: 0.0028 max mem: 19788 +Epoch: [15] [1030/2138] eta: 1:07:04 lr: 3.218466105514385e-05 loss: 0.0292 (0.0360) time: 3.6258 data: 0.0031 max mem: 19788 +Epoch: [15] [1040/2138] eta: 1:06:28 lr: 3.217913510629634e-05 loss: 0.0304 (0.0360) time: 3.6263 data: 0.0031 max mem: 19788 +Epoch: [15] [1050/2138] eta: 1:05:51 lr: 3.2173609052008884e-05 loss: 0.0318 (0.0360) time: 3.6237 data: 0.0029 max mem: 19788 +Epoch: [15] [1060/2138] eta: 1:05:15 lr: 3.216808289225937e-05 loss: 0.0337 (0.0360) time: 3.6182 data: 0.0031 max mem: 19788 +Epoch: [15] [1070/2138] eta: 1:04:39 lr: 3.2162556627025635e-05 loss: 0.0308 (0.0360) time: 3.6205 data: 0.0032 max mem: 19788 +Epoch: [15] [1080/2138] eta: 1:04:02 lr: 3.2157030256285545e-05 loss: 0.0324 (0.0360) time: 3.6236 data: 0.0032 max mem: 19788 +Epoch: [15] [1090/2138] eta: 1:03:26 lr: 3.2151503780016914e-05 loss: 0.0324 (0.0359) time: 3.6202 data: 0.0032 max mem: 19788 +Epoch: [15] [1100/2138] eta: 1:02:49 lr: 3.214597719819758e-05 loss: 0.0343 (0.0360) time: 3.6184 data: 0.0032 max mem: 19788 +Epoch: [15] [1110/2138] eta: 1:02:13 lr: 3.214045051080538e-05 loss: 0.0347 (0.0360) time: 3.6242 data: 0.0030 max mem: 19788 +Epoch: [15] [1120/2138] eta: 1:01:36 lr: 3.21349237178181e-05 loss: 0.0340 (0.0360) time: 3.6216 data: 0.0029 max mem: 19788 +Epoch: [15] [1130/2138] eta: 1:01:00 lr: 3.212939681921356e-05 loss: 0.0340 (0.0360) time: 3.6226 data: 0.0030 max mem: 19788 +Epoch: [15] [1140/2138] eta: 1:00:24 lr: 3.2123869814969546e-05 loss: 0.0316 (0.0360) time: 3.6284 data: 0.0031 max mem: 19788 +Epoch: [15] [1150/2138] eta: 0:59:47 lr: 3.211834270506386e-05 loss: 0.0299 (0.0360) time: 3.6220 data: 0.0031 max mem: 19788 +Epoch: [15] [1160/2138] eta: 0:59:11 lr: 3.2112815489474255e-05 loss: 0.0301 (0.0359) time: 3.6186 data: 0.0031 max mem: 19788 +Epoch: [15] [1170/2138] eta: 0:58:35 lr: 3.2107288168178504e-05 loss: 0.0320 (0.0359) time: 3.6216 data: 0.0033 max mem: 19788 +Epoch: [15] [1180/2138] eta: 0:57:58 lr: 3.2101760741154366e-05 loss: 0.0378 (0.0359) time: 3.6209 data: 0.0031 max mem: 19788 +Epoch: [15] [1190/2138] eta: 0:57:22 lr: 3.209623320837961e-05 loss: 0.0337 (0.0359) time: 3.6213 data: 0.0030 max mem: 19788 +Epoch: [15] [1200/2138] eta: 0:56:45 lr: 3.209070556983195e-05 loss: 0.0337 (0.0359) time: 3.6224 data: 0.0030 max mem: 19788 +Epoch: [15] [1210/2138] eta: 0:56:09 lr: 3.2085177825489124e-05 loss: 0.0343 (0.0359) time: 3.6247 data: 0.0030 max mem: 19788 +Epoch: [15] [1220/2138] eta: 0:55:33 lr: 3.207964997532886e-05 loss: 0.0308 (0.0359) time: 3.6220 data: 0.0031 max mem: 19788 +Epoch: [15] [1230/2138] eta: 0:54:56 lr: 3.207412201932887e-05 loss: 0.0308 (0.0359) time: 3.6163 data: 0.0032 max mem: 19788 +Epoch: [15] [1240/2138] eta: 0:54:20 lr: 3.206859395746686e-05 loss: 0.0325 (0.0360) time: 3.6184 data: 0.0031 max mem: 19788 +Epoch: [15] [1250/2138] eta: 0:53:43 lr: 3.2063065789720515e-05 loss: 0.0350 (0.0360) time: 3.6218 data: 0.0028 max mem: 19788 +Epoch: [15] [1260/2138] eta: 0:53:07 lr: 3.2057537516067526e-05 loss: 0.0356 (0.0360) time: 3.6245 data: 0.0028 max mem: 19788 +Epoch: [15] [1270/2138] eta: 0:52:31 lr: 3.2052009136485585e-05 loss: 0.0283 (0.0359) time: 3.6235 data: 0.0030 max mem: 19788 +Epoch: [15] [1280/2138] eta: 0:51:54 lr: 3.2046480650952346e-05 loss: 0.0291 (0.0359) time: 3.6200 data: 0.0033 max mem: 19788 +Epoch: [15] [1290/2138] eta: 0:51:18 lr: 3.204095205944547e-05 loss: 0.0310 (0.0359) time: 3.6189 data: 0.0033 max mem: 19788 +Epoch: [15] [1300/2138] eta: 0:50:42 lr: 3.203542336194261e-05 loss: 0.0315 (0.0360) time: 3.6156 data: 0.0034 max mem: 19788 +Epoch: [15] [1310/2138] eta: 0:50:05 lr: 3.202989455842141e-05 loss: 0.0313 (0.0360) time: 3.6135 data: 0.0034 max mem: 19788 +Epoch: [15] [1320/2138] eta: 0:49:29 lr: 3.20243656488595e-05 loss: 0.0313 (0.0360) time: 3.6187 data: 0.0031 max mem: 19788 +Epoch: [15] [1330/2138] eta: 0:48:53 lr: 3.20188366332345e-05 loss: 0.0303 (0.0360) time: 3.6251 data: 0.0028 max mem: 19788 +Epoch: [15] [1340/2138] eta: 0:48:16 lr: 3.201330751152403e-05 loss: 0.0337 (0.0360) time: 3.6279 data: 0.0028 max mem: 19788 +Epoch: [15] [1350/2138] eta: 0:47:40 lr: 3.2007778283705705e-05 loss: 0.0384 (0.0361) time: 3.6258 data: 0.0029 max mem: 19788 +Epoch: [15] [1360/2138] eta: 0:47:04 lr: 3.200224894975709e-05 loss: 0.0360 (0.0361) time: 3.6276 data: 0.0029 max mem: 19788 +Epoch: [15] [1370/2138] eta: 0:46:27 lr: 3.1996719509655804e-05 loss: 0.0345 (0.0361) time: 3.6315 data: 0.0029 max mem: 19788 +Epoch: [15] [1380/2138] eta: 0:45:51 lr: 3.199118996337942e-05 loss: 0.0337 (0.0361) time: 3.6246 data: 0.0030 max mem: 19788 +Epoch: [15] [1390/2138] eta: 0:45:15 lr: 3.198566031090549e-05 loss: 0.0360 (0.0361) time: 3.6333 data: 0.0033 max mem: 19788 +Epoch: [15] [1400/2138] eta: 0:44:38 lr: 3.198013055221159e-05 loss: 0.0321 (0.0361) time: 3.6372 data: 0.0034 max mem: 19788 +Epoch: [15] [1410/2138] eta: 0:44:02 lr: 3.1974600687275266e-05 loss: 0.0307 (0.0360) time: 3.6288 data: 0.0032 max mem: 19788 +Epoch: [15] [1420/2138] eta: 0:43:26 lr: 3.196907071607407e-05 loss: 0.0281 (0.0360) time: 3.6253 data: 0.0029 max mem: 19788 +Epoch: [15] [1430/2138] eta: 0:42:49 lr: 3.196354063858552e-05 loss: 0.0321 (0.0360) time: 3.6258 data: 0.0027 max mem: 19788 +Epoch: [15] [1440/2138] eta: 0:42:13 lr: 3.195801045478714e-05 loss: 0.0321 (0.0360) time: 3.6273 data: 0.0027 max mem: 19788 +Epoch: [15] [1450/2138] eta: 0:41:37 lr: 3.1952480164656464e-05 loss: 0.0340 (0.0360) time: 3.6228 data: 0.0028 max mem: 19788 +Epoch: [15] [1460/2138] eta: 0:41:00 lr: 3.1946949768170986e-05 loss: 0.0376 (0.0360) time: 3.6226 data: 0.0030 max mem: 19788 +Epoch: [15] [1470/2138] eta: 0:40:24 lr: 3.19414192653082e-05 loss: 0.0361 (0.0360) time: 3.6283 data: 0.0031 max mem: 19788 +Epoch: [15] [1480/2138] eta: 0:39:48 lr: 3.193588865604559e-05 loss: 0.0337 (0.0360) time: 3.6278 data: 0.0028 max mem: 19788 +Epoch: [15] [1490/2138] eta: 0:39:12 lr: 3.193035794036065e-05 loss: 0.0352 (0.0360) time: 3.6231 data: 0.0028 max mem: 19788 +Epoch: [15] [1500/2138] eta: 0:38:35 lr: 3.192482711823084e-05 loss: 0.0334 (0.0360) time: 3.6217 data: 0.0029 max mem: 19788 +Epoch: [15] [1510/2138] eta: 0:37:59 lr: 3.191929618963362e-05 loss: 0.0303 (0.0360) time: 3.6235 data: 0.0028 max mem: 19788 +Epoch: [15] [1520/2138] eta: 0:37:23 lr: 3.1913765154546444e-05 loss: 0.0303 (0.0359) time: 3.6283 data: 0.0029 max mem: 19788 +Epoch: [15] [1530/2138] eta: 0:36:46 lr: 3.190823401294675e-05 loss: 0.0311 (0.0359) time: 3.6243 data: 0.0030 max mem: 19788 +Epoch: [15] [1540/2138] eta: 0:36:10 lr: 3.1902702764811975e-05 loss: 0.0331 (0.0359) time: 3.6235 data: 0.0029 max mem: 19788 +Epoch: [15] [1550/2138] eta: 0:35:34 lr: 3.189717141011955e-05 loss: 0.0321 (0.0359) time: 3.6258 data: 0.0030 max mem: 19788 +Epoch: [15] [1560/2138] eta: 0:34:57 lr: 3.1891639948846875e-05 loss: 0.0321 (0.0359) time: 3.6242 data: 0.0030 max mem: 19788 +Epoch: [15] [1570/2138] eta: 0:34:21 lr: 3.188610838097136e-05 loss: 0.0359 (0.0359) time: 3.6230 data: 0.0029 max mem: 19788 +Epoch: [15] [1580/2138] eta: 0:33:45 lr: 3.1880576706470413e-05 loss: 0.0342 (0.0359) time: 3.6243 data: 0.0029 max mem: 19788 +Epoch: [15] [1590/2138] eta: 0:33:08 lr: 3.1875044925321413e-05 loss: 0.0335 (0.0359) time: 3.6285 data: 0.0031 max mem: 19788 +Epoch: [15] [1600/2138] eta: 0:32:32 lr: 3.186951303750173e-05 loss: 0.0344 (0.0360) time: 3.6295 data: 0.0031 max mem: 19788 +Epoch: [15] [1610/2138] eta: 0:31:56 lr: 3.1863981042988745e-05 loss: 0.0330 (0.0359) time: 3.6255 data: 0.0028 max mem: 19788 +Epoch: [15] [1620/2138] eta: 0:31:19 lr: 3.1858448941759824e-05 loss: 0.0321 (0.0359) time: 3.6246 data: 0.0028 max mem: 19788 +Epoch: [15] [1630/2138] eta: 0:30:43 lr: 3.185291673379229e-05 loss: 0.0355 (0.0360) time: 3.6239 data: 0.0028 max mem: 19788 +Epoch: [15] [1640/2138] eta: 0:30:07 lr: 3.184738441906351e-05 loss: 0.0335 (0.0359) time: 3.6267 data: 0.0028 max mem: 19788 +Epoch: [15] [1650/2138] eta: 0:29:31 lr: 3.1841851997550814e-05 loss: 0.0276 (0.0359) time: 3.6289 data: 0.0029 max mem: 19788 +Epoch: [15] [1660/2138] eta: 0:28:54 lr: 3.183631946923152e-05 loss: 0.0318 (0.0359) time: 3.6238 data: 0.0031 max mem: 19788 +Epoch: [15] [1670/2138] eta: 0:28:18 lr: 3.183078683408294e-05 loss: 0.0297 (0.0359) time: 3.6247 data: 0.0032 max mem: 19788 +Epoch: [15] [1680/2138] eta: 0:27:42 lr: 3.182525409208237e-05 loss: 0.0304 (0.0359) time: 3.6294 data: 0.0031 max mem: 19788 +Epoch: [15] [1690/2138] eta: 0:27:05 lr: 3.1819721243207134e-05 loss: 0.0324 (0.0359) time: 3.6312 data: 0.0029 max mem: 19788 +Epoch: [15] [1700/2138] eta: 0:26:29 lr: 3.1814188287434496e-05 loss: 0.0314 (0.0358) time: 3.6314 data: 0.0030 max mem: 19788 +Epoch: [15] [1710/2138] eta: 0:25:53 lr: 3.180865522474174e-05 loss: 0.0306 (0.0358) time: 3.6290 data: 0.0031 max mem: 19788 +Epoch: [15] [1720/2138] eta: 0:25:17 lr: 3.180312205510613e-05 loss: 0.0309 (0.0358) time: 3.6284 data: 0.0031 max mem: 19788 +Epoch: [15] [1730/2138] eta: 0:24:40 lr: 3.179758877850493e-05 loss: 0.0309 (0.0358) time: 3.6317 data: 0.0031 max mem: 19788 +Epoch: [15] [1740/2138] eta: 0:24:04 lr: 3.179205539491538e-05 loss: 0.0336 (0.0358) time: 3.6287 data: 0.0029 max mem: 19788 +Epoch: [15] [1750/2138] eta: 0:23:28 lr: 3.178652190431473e-05 loss: 0.0337 (0.0358) time: 3.6245 data: 0.0029 max mem: 19788 +Epoch: [15] [1760/2138] eta: 0:22:51 lr: 3.1780988306680205e-05 loss: 0.0346 (0.0358) time: 3.6295 data: 0.0030 max mem: 19788 +Epoch: [15] [1770/2138] eta: 0:22:15 lr: 3.1775454601989035e-05 loss: 0.0343 (0.0358) time: 3.6311 data: 0.0029 max mem: 19788 +Epoch: [15] [1780/2138] eta: 0:21:39 lr: 3.1769920790218426e-05 loss: 0.0322 (0.0358) time: 3.6269 data: 0.0029 max mem: 19788 +Epoch: [15] [1790/2138] eta: 0:21:02 lr: 3.176438687134558e-05 loss: 0.0338 (0.0358) time: 3.6229 data: 0.0030 max mem: 19788 +Epoch: [15] [1800/2138] eta: 0:20:26 lr: 3.175885284534769e-05 loss: 0.0361 (0.0358) time: 3.6286 data: 0.0031 max mem: 19788 +Epoch: [15] [1810/2138] eta: 0:19:50 lr: 3.1753318712201954e-05 loss: 0.0347 (0.0358) time: 3.6332 data: 0.0031 max mem: 19788 +Epoch: [15] [1820/2138] eta: 0:19:14 lr: 3.1747784471885535e-05 loss: 0.0347 (0.0358) time: 3.6296 data: 0.0030 max mem: 19788 +Epoch: [15] [1830/2138] eta: 0:18:37 lr: 3.17422501243756e-05 loss: 0.0342 (0.0358) time: 3.6310 data: 0.0031 max mem: 19788 +Epoch: [15] [1840/2138] eta: 0:18:01 lr: 3.1736715669649305e-05 loss: 0.0314 (0.0359) time: 3.6318 data: 0.0031 max mem: 19788 +Epoch: [15] [1850/2138] eta: 0:17:25 lr: 3.17311811076838e-05 loss: 0.0353 (0.0359) time: 3.6283 data: 0.0032 max mem: 19788 +Epoch: [15] [1860/2138] eta: 0:16:48 lr: 3.172564643845623e-05 loss: 0.0347 (0.0359) time: 3.6315 data: 0.0032 max mem: 19788 +Epoch: [15] [1870/2138] eta: 0:16:12 lr: 3.172011166194371e-05 loss: 0.0327 (0.0359) time: 3.6347 data: 0.0030 max mem: 19788 +Epoch: [15] [1880/2138] eta: 0:15:36 lr: 3.1714576778123365e-05 loss: 0.0340 (0.0359) time: 3.6323 data: 0.0031 max mem: 19788 +Epoch: [15] [1890/2138] eta: 0:15:00 lr: 3.170904178697232e-05 loss: 0.0296 (0.0359) time: 3.6320 data: 0.0030 max mem: 19788 +Epoch: [15] [1900/2138] eta: 0:14:23 lr: 3.1703506688467657e-05 loss: 0.0280 (0.0359) time: 3.6305 data: 0.0029 max mem: 19788 +Epoch: [15] [1910/2138] eta: 0:13:47 lr: 3.169797148258647e-05 loss: 0.0296 (0.0359) time: 3.6288 data: 0.0029 max mem: 19788 +Epoch: [15] [1920/2138] eta: 0:13:11 lr: 3.169243616930585e-05 loss: 0.0340 (0.0359) time: 3.6302 data: 0.0031 max mem: 19788 +Epoch: [15] [1930/2138] eta: 0:12:34 lr: 3.1686900748602863e-05 loss: 0.0400 (0.0359) time: 3.6378 data: 0.0032 max mem: 19788 +Epoch: [15] [1940/2138] eta: 0:11:58 lr: 3.168136522045457e-05 loss: 0.0344 (0.0359) time: 3.6359 data: 0.0030 max mem: 19788 +Epoch: [15] [1950/2138] eta: 0:11:22 lr: 3.167582958483804e-05 loss: 0.0308 (0.0359) time: 3.6312 data: 0.0029 max mem: 19788 +Epoch: [15] [1960/2138] eta: 0:10:46 lr: 3.1670293841730306e-05 loss: 0.0302 (0.0358) time: 3.6341 data: 0.0031 max mem: 19788 +Epoch: [15] [1970/2138] eta: 0:10:09 lr: 3.1664757991108404e-05 loss: 0.0313 (0.0358) time: 3.6347 data: 0.0032 max mem: 19788 +Epoch: [15] [1980/2138] eta: 0:09:33 lr: 3.1659222032949355e-05 loss: 0.0308 (0.0358) time: 3.6332 data: 0.0030 max mem: 19788 +Epoch: [15] [1990/2138] eta: 0:08:57 lr: 3.165368596723019e-05 loss: 0.0304 (0.0358) time: 3.6324 data: 0.0029 max mem: 19788 +Epoch: [15] [2000/2138] eta: 0:08:20 lr: 3.164814979392791e-05 loss: 0.0309 (0.0358) time: 3.6319 data: 0.0031 max mem: 19788 +Epoch: [15] [2010/2138] eta: 0:07:44 lr: 3.1642613513019514e-05 loss: 0.0352 (0.0358) time: 3.6290 data: 0.0031 max mem: 19788 +Epoch: [15] [2020/2138] eta: 0:07:08 lr: 3.163707712448199e-05 loss: 0.0364 (0.0358) time: 3.6315 data: 0.0029 max mem: 19788 +Epoch: [15] [2030/2138] eta: 0:06:31 lr: 3.1631540628292306e-05 loss: 0.0364 (0.0358) time: 3.6351 data: 0.0031 max mem: 19788 +Epoch: [15] [2040/2138] eta: 0:05:55 lr: 3.162600402442745e-05 loss: 0.0316 (0.0359) time: 3.6335 data: 0.0032 max mem: 19788 +Epoch: [15] [2050/2138] eta: 0:05:19 lr: 3.1620467312864375e-05 loss: 0.0350 (0.0359) time: 3.6310 data: 0.0030 max mem: 19788 +Epoch: [15] [2060/2138] eta: 0:04:43 lr: 3.1614930493580034e-05 loss: 0.0363 (0.0359) time: 3.6327 data: 0.0031 max mem: 19788 +Epoch: [15] [2070/2138] eta: 0:04:06 lr: 3.160939356655135e-05 loss: 0.0340 (0.0359) time: 3.6354 data: 0.0031 max mem: 19788 +Epoch: [15] [2080/2138] eta: 0:03:30 lr: 3.1603856531755294e-05 loss: 0.0332 (0.0359) time: 3.6349 data: 0.0030 max mem: 19788 +Epoch: [15] [2090/2138] eta: 0:02:54 lr: 3.159831938916876e-05 loss: 0.0332 (0.0359) time: 3.6368 data: 0.0031 max mem: 19788 +Epoch: [15] [2100/2138] eta: 0:02:17 lr: 3.159278213876866e-05 loss: 0.0304 (0.0359) time: 3.6368 data: 0.0031 max mem: 19788 +Epoch: [15] [2110/2138] eta: 0:01:41 lr: 3.158724478053191e-05 loss: 0.0359 (0.0359) time: 3.6379 data: 0.0029 max mem: 19788 +Epoch: [15] [2120/2138] eta: 0:01:05 lr: 3.15817073144354e-05 loss: 0.0441 (0.0360) time: 3.6383 data: 0.0029 max mem: 19788 +Epoch: [15] [2130/2138] eta: 0:00:29 lr: 3.157616974045602e-05 loss: 0.0397 (0.0360) time: 3.6233 data: 0.0029 max mem: 19788 +Epoch: [15] Total time: 2:09:21 +Test: [ 0/21770] eta: 18:24:36 time: 3.0444 data: 2.8671 max mem: 19788 +Test: [ 100/21770] eta: 0:34:30 time: 0.0785 data: 0.0024 max mem: 19788 +Test: [ 200/21770] eta: 0:29:02 time: 0.0702 data: 0.0024 max mem: 19788 +Test: [ 300/21770] eta: 0:26:48 time: 0.0638 data: 0.0020 max mem: 19788 +Test: [ 400/21770] eta: 0:25:47 time: 0.0755 data: 0.0019 max mem: 19788 +Test: [ 500/21770] eta: 0:25:35 time: 0.0637 data: 0.0020 max mem: 19788 +Test: [ 600/21770] eta: 0:25:11 time: 0.0611 data: 0.0017 max mem: 19788 +Test: [ 700/21770] eta: 0:24:49 time: 0.0616 data: 0.0017 max mem: 19788 +Test: [ 800/21770] eta: 0:24:32 time: 0.0752 data: 0.0022 max mem: 19788 +Test: [ 900/21770] eta: 0:24:29 time: 0.0673 data: 0.0020 max mem: 19788 +Test: [ 1000/21770] eta: 0:24:10 time: 0.0684 data: 0.0021 max mem: 19788 +Test: [ 1100/21770] eta: 0:23:51 time: 0.0606 data: 0.0019 max mem: 19788 +Test: [ 1200/21770] eta: 0:23:36 time: 0.0631 data: 0.0018 max mem: 19788 +Test: [ 1300/21770] eta: 0:23:23 time: 0.0607 data: 0.0018 max mem: 19788 +Test: [ 1400/21770] eta: 0:23:11 time: 0.0644 data: 0.0019 max mem: 19788 +Test: [ 1500/21770] eta: 0:23:02 time: 0.0687 data: 0.0021 max mem: 19788 +Test: [ 1600/21770] eta: 0:22:51 time: 0.0713 data: 0.0023 max mem: 19788 +Test: [ 1700/21770] eta: 0:22:40 time: 0.0617 data: 0.0019 max mem: 19788 +Test: [ 1800/21770] eta: 0:22:39 time: 0.0717 data: 0.0021 max mem: 19788 +Test: [ 1900/21770] eta: 0:22:26 time: 0.0607 data: 0.0018 max mem: 19788 +Test: [ 2000/21770] eta: 0:22:16 time: 0.0692 data: 0.0020 max mem: 19788 +Test: [ 2100/21770] eta: 0:22:09 time: 0.0607 data: 0.0018 max mem: 19788 +Test: [ 2200/21770] eta: 0:22:00 time: 0.0626 data: 0.0020 max mem: 19788 +Test: [ 2300/21770] eta: 0:21:49 time: 0.0669 data: 0.0020 max mem: 19788 +Test: [ 2400/21770] eta: 0:21:41 time: 0.0703 data: 0.0021 max mem: 19788 +Test: [ 2500/21770] eta: 0:21:31 time: 0.0609 data: 0.0018 max mem: 19788 +Test: [ 2600/21770] eta: 0:21:26 time: 0.0763 data: 0.0023 max mem: 19788 +Test: [ 2700/21770] eta: 0:21:19 time: 0.0697 data: 0.0020 max mem: 19788 +Test: [ 2800/21770] eta: 0:21:14 time: 0.0648 data: 0.0021 max mem: 19788 +Test: [ 2900/21770] eta: 0:21:05 time: 0.0604 data: 0.0017 max mem: 19788 +Test: [ 3000/21770] eta: 0:20:58 time: 0.0625 data: 0.0019 max mem: 19788 +Test: [ 3100/21770] eta: 0:20:54 time: 0.0745 data: 0.0021 max mem: 19788 +Test: [ 3200/21770] eta: 0:20:47 time: 0.0639 data: 0.0020 max mem: 19788 +Test: [ 3300/21770] eta: 0:20:38 time: 0.0657 data: 0.0020 max mem: 19788 +Test: [ 3400/21770] eta: 0:20:31 time: 0.0779 data: 0.0023 max mem: 19788 +Test: [ 3500/21770] eta: 0:20:26 time: 0.0720 data: 0.0018 max mem: 19788 +Test: [ 3600/21770] eta: 0:20:19 time: 0.0654 data: 0.0019 max mem: 19788 +Test: [ 3700/21770] eta: 0:20:16 time: 0.0827 data: 0.0024 max mem: 19788 +Test: [ 3800/21770] eta: 0:20:15 time: 0.0763 data: 0.0023 max mem: 19788 +Test: [ 3900/21770] eta: 0:20:09 time: 0.0690 data: 0.0019 max mem: 19788 +Test: [ 4000/21770] eta: 0:20:04 time: 0.0626 data: 0.0019 max mem: 19788 +Test: [ 4100/21770] eta: 0:20:00 time: 0.0728 data: 0.0021 max mem: 19788 +Test: [ 4200/21770] eta: 0:19:53 time: 0.0610 data: 0.0019 max mem: 19788 +Test: [ 4300/21770] eta: 0:19:46 time: 0.0609 data: 0.0017 max mem: 19788 +Test: [ 4400/21770] eta: 0:19:39 time: 0.0797 data: 0.0025 max mem: 19788 +Test: [ 4500/21770] eta: 0:19:34 time: 0.0800 data: 0.0024 max mem: 19788 +Test: [ 4600/21770] eta: 0:19:28 time: 0.0698 data: 0.0019 max mem: 19788 +Test: [ 4700/21770] eta: 0:19:21 time: 0.0595 data: 0.0018 max mem: 19788 +Test: [ 4800/21770] eta: 0:19:15 time: 0.0660 data: 0.0021 max mem: 19788 +Test: [ 4900/21770] eta: 0:19:09 time: 0.0635 data: 0.0020 max mem: 19788 +Test: [ 5000/21770] eta: 0:19:00 time: 0.0663 data: 0.0021 max mem: 19788 +Test: [ 5100/21770] eta: 0:18:53 time: 0.0630 data: 0.0019 max mem: 19788 +Test: [ 5200/21770] eta: 0:18:48 time: 0.0633 data: 0.0022 max mem: 19788 +Test: [ 5300/21770] eta: 0:18:40 time: 0.0784 data: 0.0023 max mem: 19788 +Test: [ 5400/21770] eta: 0:18:35 time: 0.0682 data: 0.0017 max mem: 19788 +Test: [ 5500/21770] eta: 0:18:29 time: 0.0756 data: 0.0020 max mem: 19788 +Test: [ 5600/21770] eta: 0:18:23 time: 0.0698 data: 0.0021 max mem: 19788 +Test: [ 5700/21770] eta: 0:18:15 time: 0.0637 data: 0.0020 max mem: 19788 +Test: [ 5800/21770] eta: 0:18:09 time: 0.0745 data: 0.0020 max mem: 19788 +Test: [ 5900/21770] eta: 0:18:01 time: 0.0618 data: 0.0018 max mem: 19788 +Test: [ 6000/21770] eta: 0:17:54 time: 0.0632 data: 0.0020 max mem: 19788 +Test: [ 6100/21770] eta: 0:17:47 time: 0.0678 data: 0.0020 max mem: 19788 +Test: [ 6200/21770] eta: 0:17:40 time: 0.0616 data: 0.0018 max mem: 19788 +Test: [ 6300/21770] eta: 0:17:33 time: 0.0631 data: 0.0019 max mem: 19788 +Test: [ 6400/21770] eta: 0:17:25 time: 0.0768 data: 0.0021 max mem: 19788 +Test: [ 6500/21770] eta: 0:17:18 time: 0.0657 data: 0.0019 max mem: 19788 +Test: [ 6600/21770] eta: 0:17:10 time: 0.0671 data: 0.0019 max mem: 19788 +Test: [ 6700/21770] eta: 0:17:04 time: 0.0648 data: 0.0021 max mem: 19788 +Test: [ 6800/21770] eta: 0:16:57 time: 0.0607 data: 0.0020 max mem: 19788 +Test: [ 6900/21770] eta: 0:16:49 time: 0.0642 data: 0.0018 max mem: 19788 +Test: [ 7000/21770] eta: 0:16:41 time: 0.0646 data: 0.0020 max mem: 19788 +Test: [ 7100/21770] eta: 0:16:33 time: 0.0636 data: 0.0019 max mem: 19788 +Test: [ 7200/21770] eta: 0:16:26 time: 0.0736 data: 0.0019 max mem: 19788 +Test: [ 7300/21770] eta: 0:16:19 time: 0.0702 data: 0.0023 max mem: 19788 +Test: [ 7400/21770] eta: 0:16:13 time: 0.0807 data: 0.0023 max mem: 19788 +Test: [ 7500/21770] eta: 0:16:07 time: 0.0685 data: 0.0020 max mem: 19788 +Test: [ 7600/21770] eta: 0:16:00 time: 0.0671 data: 0.0019 max mem: 19788 +Test: [ 7700/21770] eta: 0:15:53 time: 0.0623 data: 0.0017 max mem: 19788 +Test: [ 7800/21770] eta: 0:15:46 time: 0.0624 data: 0.0019 max mem: 19788 +Test: [ 7900/21770] eta: 0:15:40 time: 0.0760 data: 0.0024 max mem: 19788 +Test: [ 8000/21770] eta: 0:15:35 time: 0.0609 data: 0.0020 max mem: 19788 +Test: [ 8100/21770] eta: 0:15:28 time: 0.0621 data: 0.0019 max mem: 19788 +Test: [ 8200/21770] eta: 0:15:20 time: 0.0706 data: 0.0021 max mem: 19788 +Test: [ 8300/21770] eta: 0:15:13 time: 0.0618 data: 0.0019 max mem: 19788 +Test: [ 8400/21770] eta: 0:15:05 time: 0.0708 data: 0.0017 max mem: 19788 +Test: [ 8500/21770] eta: 0:14:58 time: 0.0664 data: 0.0019 max mem: 19788 +Test: [ 8600/21770] eta: 0:14:52 time: 0.0773 data: 0.0022 max mem: 19788 +Test: [ 8700/21770] eta: 0:14:45 time: 0.0645 data: 0.0020 max mem: 19788 +Test: [ 8800/21770] eta: 0:14:39 time: 0.0648 data: 0.0019 max mem: 19788 +Test: [ 8900/21770] eta: 0:14:32 time: 0.0678 data: 0.0017 max mem: 19788 +Test: [ 9000/21770] eta: 0:14:25 time: 0.0657 data: 0.0018 max mem: 19788 +Test: [ 9100/21770] eta: 0:14:18 time: 0.0654 data: 0.0020 max mem: 19788 +Test: [ 9200/21770] eta: 0:14:11 time: 0.0755 data: 0.0023 max mem: 19788 +Test: [ 9300/21770] eta: 0:14:05 time: 0.0702 data: 0.0022 max mem: 19788 +Test: [ 9400/21770] eta: 0:13:59 time: 0.0677 data: 0.0020 max mem: 19788 +Test: [ 9500/21770] eta: 0:13:53 time: 0.0820 data: 0.0024 max mem: 19788 +Test: [ 9600/21770] eta: 0:13:46 time: 0.0632 data: 0.0019 max mem: 19788 +Test: [ 9700/21770] eta: 0:13:39 time: 0.0654 data: 0.0020 max mem: 19788 +Test: [ 9800/21770] eta: 0:13:33 time: 0.0799 data: 0.0023 max mem: 19788 +Test: [ 9900/21770] eta: 0:13:26 time: 0.0654 data: 0.0020 max mem: 19788 +Test: [10000/21770] eta: 0:13:20 time: 0.0726 data: 0.0018 max mem: 19788 +Test: [10100/21770] eta: 0:13:12 time: 0.0611 data: 0.0017 max mem: 19788 +Test: [10200/21770] eta: 0:13:05 time: 0.0703 data: 0.0020 max mem: 19788 +Test: [10300/21770] eta: 0:12:59 time: 0.0821 data: 0.0024 max mem: 19788 +Test: [10400/21770] eta: 0:12:52 time: 0.0620 data: 0.0017 max mem: 19788 +Test: [10500/21770] eta: 0:12:45 time: 0.0624 data: 0.0018 max mem: 19788 +Test: [10600/21770] eta: 0:12:38 time: 0.0691 data: 0.0022 max mem: 19788 +Test: [10700/21770] eta: 0:12:32 time: 0.0777 data: 0.0022 max mem: 19788 +Test: [10800/21770] eta: 0:12:26 time: 0.0599 data: 0.0018 max mem: 19788 +Test: [10900/21770] eta: 0:12:19 time: 0.0812 data: 0.0020 max mem: 19788 +Test: [11000/21770] eta: 0:12:12 time: 0.0679 data: 0.0020 max mem: 19788 +Test: [11100/21770] eta: 0:12:05 time: 0.0719 data: 0.0024 max mem: 19788 +Test: [11200/21770] eta: 0:11:58 time: 0.0638 data: 0.0017 max mem: 19788 +Test: [11300/21770] eta: 0:11:52 time: 0.0759 data: 0.0019 max mem: 19788 +Test: [11400/21770] eta: 0:11:46 time: 0.0662 data: 0.0020 max mem: 19788 +Test: [11500/21770] eta: 0:11:39 time: 0.0722 data: 0.0021 max mem: 19788 +Test: [11600/21770] eta: 0:11:32 time: 0.0805 data: 0.0024 max mem: 19788 +Test: [11700/21770] eta: 0:11:26 time: 0.0650 data: 0.0019 max mem: 19788 +Test: [11800/21770] eta: 0:11:19 time: 0.0646 data: 0.0021 max mem: 19788 +Test: [11900/21770] eta: 0:11:12 time: 0.0708 data: 0.0022 max mem: 19788 +Test: [12000/21770] eta: 0:11:05 time: 0.0772 data: 0.0021 max mem: 19788 +Test: [12100/21770] eta: 0:10:59 time: 0.0699 data: 0.0020 max mem: 19788 +Test: [12200/21770] eta: 0:10:52 time: 0.0697 data: 0.0021 max mem: 19788 +Test: [12300/21770] eta: 0:10:45 time: 0.0684 data: 0.0020 max mem: 19788 +Test: [12400/21770] eta: 0:10:39 time: 0.0625 data: 0.0018 max mem: 19788 +Test: [12500/21770] eta: 0:10:32 time: 0.0821 data: 0.0026 max mem: 19788 +Test: [12600/21770] eta: 0:10:25 time: 0.0626 data: 0.0018 max mem: 19788 +Test: [12700/21770] eta: 0:10:19 time: 0.0783 data: 0.0024 max mem: 19788 +Test: [12800/21770] eta: 0:10:12 time: 0.0768 data: 0.0023 max mem: 19788 +Test: [12900/21770] eta: 0:10:06 time: 0.0677 data: 0.0020 max mem: 19788 +Test: [13000/21770] eta: 0:09:59 time: 0.0628 data: 0.0021 max mem: 19788 +Test: [13100/21770] eta: 0:09:53 time: 0.0829 data: 0.0020 max mem: 19788 +Test: [13200/21770] eta: 0:09:46 time: 0.0627 data: 0.0018 max mem: 19788 +Test: [13300/21770] eta: 0:09:39 time: 0.0733 data: 0.0022 max mem: 19788 +Test: [13400/21770] eta: 0:09:33 time: 0.0627 data: 0.0019 max mem: 19788 +Test: [13500/21770] eta: 0:09:26 time: 0.0787 data: 0.0023 max mem: 19788 +Test: [13600/21770] eta: 0:09:19 time: 0.0626 data: 0.0020 max mem: 19788 +Test: [13700/21770] eta: 0:09:12 time: 0.0595 data: 0.0018 max mem: 19788 +Test: [13800/21770] eta: 0:09:05 time: 0.0632 data: 0.0018 max mem: 19788 +Test: [13900/21770] eta: 0:08:58 time: 0.0756 data: 0.0019 max mem: 19788 +Test: [14000/21770] eta: 0:08:51 time: 0.0740 data: 0.0023 max mem: 19788 +Test: [14100/21770] eta: 0:08:45 time: 0.0822 data: 0.0019 max mem: 19788 +Test: [14200/21770] eta: 0:08:38 time: 0.0699 data: 0.0021 max mem: 19788 +Test: [14300/21770] eta: 0:08:31 time: 0.0688 data: 0.0021 max mem: 19788 +Test: [14400/21770] eta: 0:08:24 time: 0.0666 data: 0.0020 max mem: 19788 +Test: [14500/21770] eta: 0:08:18 time: 0.0650 data: 0.0019 max mem: 19788 +Test: [14600/21770] eta: 0:08:11 time: 0.0755 data: 0.0020 max mem: 19788 +Test: [14700/21770] eta: 0:08:04 time: 0.0662 data: 0.0019 max mem: 19788 +Test: [14800/21770] eta: 0:07:58 time: 0.0719 data: 0.0021 max mem: 19788 +Test: [14900/21770] eta: 0:07:51 time: 0.0671 data: 0.0019 max mem: 19788 +Test: [15000/21770] eta: 0:07:44 time: 0.0618 data: 0.0018 max mem: 19788 +Test: [15100/21770] eta: 0:07:37 time: 0.0599 data: 0.0017 max mem: 19788 +Test: [15200/21770] eta: 0:07:30 time: 0.0673 data: 0.0018 max mem: 19788 +Test: [15300/21770] eta: 0:07:23 time: 0.0758 data: 0.0019 max mem: 19788 +Test: [15400/21770] eta: 0:07:16 time: 0.0734 data: 0.0019 max mem: 19788 +Test: [15500/21770] eta: 0:07:09 time: 0.0635 data: 0.0017 max mem: 19788 +Test: [15600/21770] eta: 0:07:02 time: 0.0627 data: 0.0016 max mem: 19788 +Test: [15700/21770] eta: 0:06:55 time: 0.0651 data: 0.0019 max mem: 19788 +Test: [15800/21770] eta: 0:06:48 time: 0.0639 data: 0.0019 max mem: 19788 +Test: [15900/21770] eta: 0:06:41 time: 0.0746 data: 0.0020 max mem: 19788 +Test: [16000/21770] eta: 0:06:35 time: 0.0624 data: 0.0018 max mem: 19788 +Test: [16100/21770] eta: 0:06:27 time: 0.0638 data: 0.0018 max mem: 19788 +Test: [16200/21770] eta: 0:06:21 time: 0.0656 data: 0.0020 max mem: 19788 +Test: [16300/21770] eta: 0:06:14 time: 0.0788 data: 0.0023 max mem: 19788 +Test: [16400/21770] eta: 0:06:07 time: 0.0621 data: 0.0020 max mem: 19788 +Test: [16500/21770] eta: 0:06:00 time: 0.0641 data: 0.0019 max mem: 19788 +Test: [16600/21770] eta: 0:05:53 time: 0.0653 data: 0.0019 max mem: 19788 +Test: [16700/21770] eta: 0:05:46 time: 0.0726 data: 0.0023 max mem: 19788 +Test: [16800/21770] eta: 0:05:40 time: 0.0715 data: 0.0020 max mem: 19788 +Test: [16900/21770] eta: 0:05:33 time: 0.0618 data: 0.0020 max mem: 19788 +Test: [17000/21770] eta: 0:05:26 time: 0.0632 data: 0.0018 max mem: 19788 +Test: [17100/21770] eta: 0:05:19 time: 0.0612 data: 0.0018 max mem: 19788 +Test: [17200/21770] eta: 0:05:12 time: 0.0614 data: 0.0018 max mem: 19788 +Test: [17300/21770] eta: 0:05:05 time: 0.0632 data: 0.0019 max mem: 19788 +Test: [17400/21770] eta: 0:04:58 time: 0.0617 data: 0.0019 max mem: 19788 +Test: [17500/21770] eta: 0:04:51 time: 0.0629 data: 0.0020 max mem: 19788 +Test: [17600/21770] eta: 0:04:44 time: 0.0710 data: 0.0023 max mem: 19788 +Test: [17700/21770] eta: 0:04:38 time: 0.0808 data: 0.0025 max mem: 19788 +Test: [17800/21770] eta: 0:04:31 time: 0.0672 data: 0.0020 max mem: 19788 +Test: [17900/21770] eta: 0:04:24 time: 0.0750 data: 0.0020 max mem: 19788 +Test: [18000/21770] eta: 0:04:17 time: 0.0682 data: 0.0021 max mem: 19788 +Test: [18100/21770] eta: 0:04:10 time: 0.0617 data: 0.0017 max mem: 19788 +Test: [18200/21770] eta: 0:04:03 time: 0.0768 data: 0.0021 max mem: 19788 +Test: [18300/21770] eta: 0:03:57 time: 0.0705 data: 0.0021 max mem: 19788 +Test: [18400/21770] eta: 0:03:50 time: 0.0821 data: 0.0023 max mem: 19788 +Test: [18500/21770] eta: 0:03:43 time: 0.0810 data: 0.0024 max mem: 19788 +Test: [18600/21770] eta: 0:03:36 time: 0.0706 data: 0.0021 max mem: 19788 +Test: [18700/21770] eta: 0:03:30 time: 0.0822 data: 0.0019 max mem: 19788 +Test: [18800/21770] eta: 0:03:23 time: 0.0709 data: 0.0021 max mem: 19788 +Test: [18900/21770] eta: 0:03:16 time: 0.0626 data: 0.0018 max mem: 19788 +Test: [19000/21770] eta: 0:03:09 time: 0.0612 data: 0.0019 max mem: 19788 +Test: [19100/21770] eta: 0:03:02 time: 0.0650 data: 0.0019 max mem: 19788 +Test: [19200/21770] eta: 0:02:55 time: 0.0645 data: 0.0020 max mem: 19788 +Test: [19300/21770] eta: 0:02:48 time: 0.0624 data: 0.0018 max mem: 19788 +Test: [19400/21770] eta: 0:02:42 time: 0.0614 data: 0.0017 max mem: 19788 +Test: [19500/21770] eta: 0:02:35 time: 0.0794 data: 0.0024 max mem: 19788 +Test: [19600/21770] eta: 0:02:28 time: 0.0612 data: 0.0021 max mem: 19788 +Test: [19700/21770] eta: 0:02:21 time: 0.0617 data: 0.0019 max mem: 19788 +Test: [19800/21770] eta: 0:02:14 time: 0.0692 data: 0.0021 max mem: 19788 +Test: [19900/21770] eta: 0:02:07 time: 0.0658 data: 0.0019 max mem: 19788 +Test: [20000/21770] eta: 0:02:01 time: 0.0636 data: 0.0019 max mem: 19788 +Test: [20100/21770] eta: 0:01:54 time: 0.0642 data: 0.0020 max mem: 19788 +Test: [20200/21770] eta: 0:01:47 time: 0.0615 data: 0.0017 max mem: 19788 +Test: [20300/21770] eta: 0:01:40 time: 0.0656 data: 0.0018 max mem: 19788 +Test: [20400/21770] eta: 0:01:33 time: 0.0615 data: 0.0018 max mem: 19788 +Test: [20500/21770] eta: 0:01:26 time: 0.0722 data: 0.0018 max mem: 19788 +Test: [20600/21770] eta: 0:01:19 time: 0.0636 data: 0.0018 max mem: 19788 +Test: [20700/21770] eta: 0:01:13 time: 0.0696 data: 0.0021 max mem: 19788 +Test: [20800/21770] eta: 0:01:06 time: 0.0754 data: 0.0023 max mem: 19788 +Test: [20900/21770] eta: 0:00:59 time: 0.0656 data: 0.0019 max mem: 19788 +Test: [21000/21770] eta: 0:00:52 time: 0.0736 data: 0.0024 max mem: 19788 +Test: [21100/21770] eta: 0:00:45 time: 0.0618 data: 0.0019 max mem: 19788 +Test: [21200/21770] eta: 0:00:38 time: 0.0743 data: 0.0019 max mem: 19788 +Test: [21300/21770] eta: 0:00:32 time: 0.0788 data: 0.0024 max mem: 19788 +Test: [21400/21770] eta: 0:00:25 time: 0.0640 data: 0.0018 max mem: 19788 +Test: [21500/21770] eta: 0:00:18 time: 0.0805 data: 0.0023 max mem: 19788 +Test: [21600/21770] eta: 0:00:11 time: 0.0659 data: 0.0019 max mem: 19788 +Test: [21700/21770] eta: 0:00:04 time: 0.0629 data: 0.0020 max mem: 19788 +Test: Total time: 0:24:48 +Final results: +Mean IoU is 62.14 + + precision@0.5 = 68.91 + precision@0.6 = 63.53 + precision@0.7 = 56.67 + precision@0.8 = 46.05 + precision@0.9 = 22.84 + overall IoU = 63.29 + mean IoU = 62.14 + +Mean accuracy for one-to-zero sample is 83.63 + +Average object IoU 0.6214277764437398 +Overall IoU 63.28813171386719 +Epoch: [16] [ 0/2138] eta: 3:46:36 lr: 3.157173960358131e-05 loss: 0.0353 (0.0353) time: 6.3595 data: 2.2122 max mem: 19788 +Epoch: [16] [ 10/2138] eta: 2:18:50 lr: 3.1566201835354476e-05 loss: 0.0246 (0.0291) time: 3.9149 data: 0.2041 max mem: 19788 +Epoch: [16] [ 20/2138] eta: 2:13:55 lr: 3.1560663959179984e-05 loss: 0.0275 (0.0338) time: 3.6657 data: 0.0028 max mem: 19788 +Epoch: [16] [ 30/2138] eta: 2:11:38 lr: 3.15551259750347e-05 loss: 0.0275 (0.0318) time: 3.6548 data: 0.0027 max mem: 19788 +Epoch: [16] [ 40/2138] eta: 2:10:06 lr: 3.1549587882895466e-05 loss: 0.0311 (0.0331) time: 3.6442 data: 0.0031 max mem: 19788 +Epoch: [16] [ 50/2138] eta: 2:08:55 lr: 3.1544049682739105e-05 loss: 0.0321 (0.0338) time: 3.6392 data: 0.0031 max mem: 19788 +Epoch: [16] [ 60/2138] eta: 2:07:54 lr: 3.153851137454242e-05 loss: 0.0266 (0.0332) time: 3.6367 data: 0.0030 max mem: 19788 +Epoch: [16] [ 70/2138] eta: 2:07:00 lr: 3.153297295828224e-05 loss: 0.0226 (0.0322) time: 3.6342 data: 0.0030 max mem: 19788 +Epoch: [16] [ 80/2138] eta: 2:06:07 lr: 3.152743443393538e-05 loss: 0.0277 (0.0324) time: 3.6269 data: 0.0028 max mem: 19788 +Epoch: [16] [ 90/2138] eta: 2:05:16 lr: 3.1521895801478614e-05 loss: 0.0323 (0.0328) time: 3.6182 data: 0.0027 max mem: 19788 +Epoch: [16] [ 100/2138] eta: 2:04:28 lr: 3.151635706088872e-05 loss: 0.0364 (0.0333) time: 3.6160 data: 0.0027 max mem: 19788 +Epoch: [16] [ 110/2138] eta: 2:03:43 lr: 3.151081821214247e-05 loss: 0.0351 (0.0338) time: 3.6173 data: 0.0028 max mem: 19788 +Epoch: [16] [ 120/2138] eta: 2:02:59 lr: 3.150527925521665e-05 loss: 0.0304 (0.0341) time: 3.6178 data: 0.0027 max mem: 19788 +Epoch: [16] [ 130/2138] eta: 2:02:23 lr: 3.1499740190088005e-05 loss: 0.0345 (0.0343) time: 3.6388 data: 0.0029 max mem: 19788 +Epoch: [16] [ 140/2138] eta: 2:01:41 lr: 3.149420101673327e-05 loss: 0.0341 (0.0341) time: 3.6377 data: 0.0029 max mem: 19788 +Epoch: [16] [ 150/2138] eta: 2:00:59 lr: 3.148866173512917e-05 loss: 0.0266 (0.0340) time: 3.6158 data: 0.0028 max mem: 19788 +Epoch: [16] [ 160/2138] eta: 2:00:19 lr: 3.148312234525246e-05 loss: 0.0302 (0.0344) time: 3.6179 data: 0.0030 max mem: 19788 +Epoch: [16] [ 170/2138] eta: 1:59:40 lr: 3.147758284707984e-05 loss: 0.0356 (0.0345) time: 3.6226 data: 0.0029 max mem: 19788 +Epoch: [16] [ 180/2138] eta: 1:59:01 lr: 3.147204324058801e-05 loss: 0.0373 (0.0347) time: 3.6258 data: 0.0029 max mem: 19788 +Epoch: [16] [ 190/2138] eta: 1:58:21 lr: 3.146650352575368e-05 loss: 0.0324 (0.0346) time: 3.6217 data: 0.0031 max mem: 19788 +Epoch: [16] [ 200/2138] eta: 1:57:42 lr: 3.146096370255352e-05 loss: 0.0273 (0.0341) time: 3.6201 data: 0.0029 max mem: 19788 +Epoch: [16] [ 210/2138] eta: 1:57:03 lr: 3.145542377096424e-05 loss: 0.0330 (0.0345) time: 3.6183 data: 0.0029 max mem: 19788 +Epoch: [16] [ 220/2138] eta: 1:56:25 lr: 3.144988373096246e-05 loss: 0.0341 (0.0342) time: 3.6178 data: 0.0032 max mem: 19788 +Epoch: [16] [ 230/2138] eta: 1:55:47 lr: 3.144434358252488e-05 loss: 0.0339 (0.0347) time: 3.6224 data: 0.0031 max mem: 19788 +Epoch: [16] [ 240/2138] eta: 1:55:09 lr: 3.143880332562813e-05 loss: 0.0331 (0.0346) time: 3.6226 data: 0.0029 max mem: 19788 +Epoch: [16] [ 250/2138] eta: 1:54:31 lr: 3.1433262960248854e-05 loss: 0.0331 (0.0347) time: 3.6223 data: 0.0031 max mem: 19788 +Epoch: [16] [ 260/2138] eta: 1:53:53 lr: 3.142772248636367e-05 loss: 0.0325 (0.0345) time: 3.6202 data: 0.0033 max mem: 19788 +Epoch: [16] [ 270/2138] eta: 1:53:16 lr: 3.1422181903949225e-05 loss: 0.0325 (0.0347) time: 3.6209 data: 0.0034 max mem: 19788 +Epoch: [16] [ 280/2138] eta: 1:52:38 lr: 3.1416641212982103e-05 loss: 0.0330 (0.0346) time: 3.6232 data: 0.0032 max mem: 19788 +Epoch: [16] [ 290/2138] eta: 1:52:01 lr: 3.141110041343891e-05 loss: 0.0326 (0.0347) time: 3.6207 data: 0.0030 max mem: 19788 +Epoch: [16] [ 300/2138] eta: 1:51:24 lr: 3.140555950529624e-05 loss: 0.0320 (0.0346) time: 3.6212 data: 0.0028 max mem: 19788 +Epoch: [16] [ 310/2138] eta: 1:50:47 lr: 3.140001848853068e-05 loss: 0.0308 (0.0345) time: 3.6239 data: 0.0027 max mem: 19788 +Epoch: [16] [ 320/2138] eta: 1:50:09 lr: 3.13944773631188e-05 loss: 0.0331 (0.0345) time: 3.6224 data: 0.0029 max mem: 19788 +Epoch: [16] [ 330/2138] eta: 1:49:33 lr: 3.138893612903715e-05 loss: 0.0336 (0.0346) time: 3.6260 data: 0.0030 max mem: 19788 +Epoch: [16] [ 340/2138] eta: 1:48:55 lr: 3.1383394786262296e-05 loss: 0.0341 (0.0348) time: 3.6227 data: 0.0032 max mem: 19788 +Epoch: [16] [ 350/2138] eta: 1:48:18 lr: 3.137785333477077e-05 loss: 0.0341 (0.0347) time: 3.6145 data: 0.0032 max mem: 19788 +Epoch: [16] [ 360/2138] eta: 1:47:41 lr: 3.1372311774539125e-05 loss: 0.0328 (0.0347) time: 3.6146 data: 0.0028 max mem: 19788 +Epoch: [16] [ 370/2138] eta: 1:47:03 lr: 3.136677010554387e-05 loss: 0.0328 (0.0350) time: 3.6154 data: 0.0030 max mem: 19788 +Epoch: [16] [ 380/2138] eta: 1:46:27 lr: 3.1361228327761503e-05 loss: 0.0344 (0.0351) time: 3.6219 data: 0.0031 max mem: 19788 +Epoch: [16] [ 390/2138] eta: 1:45:50 lr: 3.1355686441168556e-05 loss: 0.0305 (0.0351) time: 3.6264 data: 0.0029 max mem: 19788 +Epoch: [16] [ 400/2138] eta: 1:45:13 lr: 3.135014444574151e-05 loss: 0.0338 (0.0352) time: 3.6236 data: 0.0030 max mem: 19788 +Epoch: [16] [ 410/2138] eta: 1:44:36 lr: 3.1344602341456854e-05 loss: 0.0350 (0.0353) time: 3.6200 data: 0.0031 max mem: 19788 +Epoch: [16] [ 420/2138] eta: 1:44:00 lr: 3.133906012829106e-05 loss: 0.0355 (0.0352) time: 3.6193 data: 0.0029 max mem: 19788 +Epoch: [16] [ 430/2138] eta: 1:43:23 lr: 3.133351780622059e-05 loss: 0.0336 (0.0353) time: 3.6219 data: 0.0030 max mem: 19788 +Epoch: [16] [ 440/2138] eta: 1:42:46 lr: 3.1327975375221915e-05 loss: 0.0367 (0.0353) time: 3.6218 data: 0.0030 max mem: 19788 +Epoch: [16] [ 450/2138] eta: 1:42:09 lr: 3.132243283527146e-05 loss: 0.0379 (0.0353) time: 3.6196 data: 0.0029 max mem: 19788 +Epoch: [16] [ 460/2138] eta: 1:41:32 lr: 3.131689018634567e-05 loss: 0.0359 (0.0355) time: 3.6182 data: 0.0028 max mem: 19788 +Epoch: [16] [ 470/2138] eta: 1:40:55 lr: 3.131134742842097e-05 loss: 0.0359 (0.0357) time: 3.6140 data: 0.0029 max mem: 19788 +Epoch: [16] [ 480/2138] eta: 1:40:19 lr: 3.130580456147379e-05 loss: 0.0348 (0.0358) time: 3.6161 data: 0.0030 max mem: 19788 +Epoch: [16] [ 490/2138] eta: 1:39:42 lr: 3.130026158548052e-05 loss: 0.0342 (0.0358) time: 3.6190 data: 0.0028 max mem: 19788 +Epoch: [16] [ 500/2138] eta: 1:39:06 lr: 3.129471850041756e-05 loss: 0.0322 (0.0358) time: 3.6216 data: 0.0028 max mem: 19788 +Epoch: [16] [ 510/2138] eta: 1:38:29 lr: 3.1289175306261306e-05 loss: 0.0354 (0.0358) time: 3.6228 data: 0.0029 max mem: 19788 +Epoch: [16] [ 520/2138] eta: 1:37:53 lr: 3.128363200298813e-05 loss: 0.0350 (0.0358) time: 3.6229 data: 0.0030 max mem: 19788 +Epoch: [16] [ 530/2138] eta: 1:37:16 lr: 3.127808859057439e-05 loss: 0.0300 (0.0358) time: 3.6268 data: 0.0032 max mem: 19788 +Epoch: [16] [ 540/2138] eta: 1:36:40 lr: 3.127254506899646e-05 loss: 0.0295 (0.0357) time: 3.6231 data: 0.0032 max mem: 19788 +Epoch: [16] [ 550/2138] eta: 1:36:03 lr: 3.126700143823069e-05 loss: 0.0295 (0.0357) time: 3.6195 data: 0.0031 max mem: 19788 +Epoch: [16] [ 560/2138] eta: 1:35:27 lr: 3.12614576982534e-05 loss: 0.0368 (0.0358) time: 3.6219 data: 0.0029 max mem: 19788 +Epoch: [16] [ 570/2138] eta: 1:34:50 lr: 3.125591384904093e-05 loss: 0.0375 (0.0358) time: 3.6204 data: 0.0029 max mem: 19788 +Epoch: [16] [ 580/2138] eta: 1:34:13 lr: 3.125036989056961e-05 loss: 0.0369 (0.0358) time: 3.6182 data: 0.0029 max mem: 19788 +Epoch: [16] [ 590/2138] eta: 1:33:37 lr: 3.124482582281573e-05 loss: 0.0361 (0.0357) time: 3.6221 data: 0.0028 max mem: 19788 +Epoch: [16] [ 600/2138] eta: 1:33:00 lr: 3.12392816457556e-05 loss: 0.0288 (0.0357) time: 3.6221 data: 0.0030 max mem: 19788 +Epoch: [16] [ 610/2138] eta: 1:32:24 lr: 3.123373735936549e-05 loss: 0.0292 (0.0357) time: 3.6180 data: 0.0030 max mem: 19788 +Epoch: [16] [ 620/2138] eta: 1:31:47 lr: 3.1228192963621725e-05 loss: 0.0301 (0.0356) time: 3.6155 data: 0.0029 max mem: 19788 +Epoch: [16] [ 630/2138] eta: 1:31:11 lr: 3.122264845850053e-05 loss: 0.0298 (0.0356) time: 3.6159 data: 0.0029 max mem: 19788 +Epoch: [16] [ 640/2138] eta: 1:30:34 lr: 3.1217103843978185e-05 loss: 0.0281 (0.0355) time: 3.6162 data: 0.0029 max mem: 19788 +Epoch: [16] [ 650/2138] eta: 1:29:58 lr: 3.121155912003093e-05 loss: 0.0286 (0.0354) time: 3.6179 data: 0.0030 max mem: 19788 +Epoch: [16] [ 660/2138] eta: 1:29:21 lr: 3.120601428663502e-05 loss: 0.0301 (0.0354) time: 3.6211 data: 0.0030 max mem: 19788 +Epoch: [16] [ 670/2138] eta: 1:28:45 lr: 3.120046934376668e-05 loss: 0.0317 (0.0354) time: 3.6175 data: 0.0030 max mem: 19788 +Epoch: [16] [ 680/2138] eta: 1:28:08 lr: 3.119492429140212e-05 loss: 0.0304 (0.0353) time: 3.6178 data: 0.0029 max mem: 19788 +Epoch: [16] [ 690/2138] eta: 1:27:32 lr: 3.118937912951756e-05 loss: 0.0304 (0.0353) time: 3.6174 data: 0.0031 max mem: 19788 +Epoch: [16] [ 700/2138] eta: 1:26:55 lr: 3.118383385808921e-05 loss: 0.0340 (0.0353) time: 3.6160 data: 0.0033 max mem: 19788 +Epoch: [16] [ 710/2138] eta: 1:26:19 lr: 3.1178288477093245e-05 loss: 0.0334 (0.0352) time: 3.6247 data: 0.0032 max mem: 19788 +Epoch: [16] [ 720/2138] eta: 1:25:43 lr: 3.117274298650585e-05 loss: 0.0334 (0.0353) time: 3.6286 data: 0.0032 max mem: 19788 +Epoch: [16] [ 730/2138] eta: 1:25:06 lr: 3.11671973863032e-05 loss: 0.0321 (0.0354) time: 3.6250 data: 0.0030 max mem: 19788 +Epoch: [16] [ 740/2138] eta: 1:24:30 lr: 3.116165167646145e-05 loss: 0.0316 (0.0353) time: 3.6209 data: 0.0029 max mem: 19788 +Epoch: [16] [ 750/2138] eta: 1:23:54 lr: 3.115610585695677e-05 loss: 0.0309 (0.0352) time: 3.6241 data: 0.0029 max mem: 19788 +Epoch: [16] [ 760/2138] eta: 1:23:17 lr: 3.115055992776528e-05 loss: 0.0339 (0.0353) time: 3.6286 data: 0.0030 max mem: 19788 +Epoch: [16] [ 770/2138] eta: 1:22:41 lr: 3.114501388886312e-05 loss: 0.0361 (0.0353) time: 3.6244 data: 0.0032 max mem: 19788 +Epoch: [16] [ 780/2138] eta: 1:22:05 lr: 3.1139467740226414e-05 loss: 0.0361 (0.0353) time: 3.6187 data: 0.0032 max mem: 19788 +Epoch: [16] [ 790/2138] eta: 1:21:28 lr: 3.113392148183127e-05 loss: 0.0361 (0.0353) time: 3.6194 data: 0.0031 max mem: 19788 +Epoch: [16] [ 800/2138] eta: 1:20:52 lr: 3.112837511365379e-05 loss: 0.0327 (0.0353) time: 3.6208 data: 0.0029 max mem: 19788 +Epoch: [16] [ 810/2138] eta: 1:20:16 lr: 3.112282863567007e-05 loss: 0.0306 (0.0352) time: 3.6190 data: 0.0030 max mem: 19788 +Epoch: [16] [ 820/2138] eta: 1:19:39 lr: 3.111728204785618e-05 loss: 0.0308 (0.0353) time: 3.6204 data: 0.0033 max mem: 19788 +Epoch: [16] [ 830/2138] eta: 1:19:03 lr: 3.111173535018821e-05 loss: 0.0304 (0.0353) time: 3.6183 data: 0.0033 max mem: 19788 +Epoch: [16] [ 840/2138] eta: 1:18:26 lr: 3.1106188542642216e-05 loss: 0.0255 (0.0353) time: 3.6169 data: 0.0029 max mem: 19788 +Epoch: [16] [ 850/2138] eta: 1:17:50 lr: 3.110064162519424e-05 loss: 0.0263 (0.0352) time: 3.6220 data: 0.0028 max mem: 19788 +Epoch: [16] [ 860/2138] eta: 1:17:14 lr: 3.1095094597820354e-05 loss: 0.0296 (0.0353) time: 3.6263 data: 0.0029 max mem: 19788 +Epoch: [16] [ 870/2138] eta: 1:16:38 lr: 3.1089547460496546e-05 loss: 0.0337 (0.0354) time: 3.6285 data: 0.0030 max mem: 19788 +Epoch: [16] [ 880/2138] eta: 1:16:01 lr: 3.108400021319886e-05 loss: 0.0337 (0.0354) time: 3.6237 data: 0.0031 max mem: 19788 +Epoch: [16] [ 890/2138] eta: 1:15:25 lr: 3.107845285590332e-05 loss: 0.0328 (0.0354) time: 3.6212 data: 0.0031 max mem: 19788 +Epoch: [16] [ 900/2138] eta: 1:14:49 lr: 3.107290538858592e-05 loss: 0.0342 (0.0355) time: 3.6195 data: 0.0031 max mem: 19788 +Epoch: [16] [ 910/2138] eta: 1:14:12 lr: 3.106735781122263e-05 loss: 0.0356 (0.0355) time: 3.6225 data: 0.0032 max mem: 19788 +Epoch: [16] [ 920/2138] eta: 1:13:36 lr: 3.106181012378946e-05 loss: 0.0346 (0.0355) time: 3.6248 data: 0.0032 max mem: 19788 +Epoch: [16] [ 930/2138] eta: 1:13:00 lr: 3.1056262326262386e-05 loss: 0.0349 (0.0355) time: 3.6186 data: 0.0031 max mem: 19788 +Epoch: [16] [ 940/2138] eta: 1:12:23 lr: 3.105071441861735e-05 loss: 0.0346 (0.0355) time: 3.6172 data: 0.0031 max mem: 19788 +Epoch: [16] [ 950/2138] eta: 1:11:47 lr: 3.104516640083031e-05 loss: 0.0313 (0.0355) time: 3.6191 data: 0.0030 max mem: 19788 +Epoch: [16] [ 960/2138] eta: 1:11:11 lr: 3.1039618272877216e-05 loss: 0.0313 (0.0355) time: 3.6227 data: 0.0028 max mem: 19788 +Epoch: [16] [ 970/2138] eta: 1:10:34 lr: 3.1034070034733995e-05 loss: 0.0309 (0.0355) time: 3.6238 data: 0.0029 max mem: 19788 +Epoch: [16] [ 980/2138] eta: 1:09:58 lr: 3.102852168637657e-05 loss: 0.0277 (0.0354) time: 3.6234 data: 0.0031 max mem: 19788 +Epoch: [16] [ 990/2138] eta: 1:09:22 lr: 3.102297322778084e-05 loss: 0.0299 (0.0354) time: 3.6256 data: 0.0029 max mem: 19788 +Epoch: [16] [1000/2138] eta: 1:08:46 lr: 3.101742465892273e-05 loss: 0.0329 (0.0354) time: 3.6299 data: 0.0028 max mem: 19788 +Epoch: [16] [1010/2138] eta: 1:08:09 lr: 3.101187597977811e-05 loss: 0.0362 (0.0354) time: 3.6310 data: 0.0029 max mem: 19788 +Epoch: [16] [1020/2138] eta: 1:07:33 lr: 3.100632719032289e-05 loss: 0.0269 (0.0353) time: 3.6289 data: 0.0031 max mem: 19788 +Epoch: [16] [1030/2138] eta: 1:06:57 lr: 3.1000778290532914e-05 loss: 0.0269 (0.0353) time: 3.6228 data: 0.0032 max mem: 19788 +Epoch: [16] [1040/2138] eta: 1:06:21 lr: 3.099522928038406e-05 loss: 0.0316 (0.0353) time: 3.6258 data: 0.0030 max mem: 19788 +Epoch: [16] [1050/2138] eta: 1:05:44 lr: 3.098968015985218e-05 loss: 0.0303 (0.0352) time: 3.6290 data: 0.0029 max mem: 19788 +Epoch: [16] [1060/2138] eta: 1:05:08 lr: 3.09841309289131e-05 loss: 0.0314 (0.0353) time: 3.6245 data: 0.0030 max mem: 19788 +Epoch: [16] [1070/2138] eta: 1:04:32 lr: 3.097858158754266e-05 loss: 0.0314 (0.0354) time: 3.6243 data: 0.0030 max mem: 19788 +Epoch: [16] [1080/2138] eta: 1:03:56 lr: 3.0973032135716685e-05 loss: 0.0326 (0.0354) time: 3.6237 data: 0.0030 max mem: 19788 +Epoch: [16] [1090/2138] eta: 1:03:19 lr: 3.096748257341099e-05 loss: 0.0330 (0.0354) time: 3.6235 data: 0.0029 max mem: 19788 +Epoch: [16] [1100/2138] eta: 1:02:43 lr: 3.0961932900601364e-05 loss: 0.0356 (0.0355) time: 3.6220 data: 0.0030 max mem: 19788 +Epoch: [16] [1110/2138] eta: 1:02:07 lr: 3.095638311726361e-05 loss: 0.0331 (0.0354) time: 3.6239 data: 0.0029 max mem: 19788 +Epoch: [16] [1120/2138] eta: 1:01:30 lr: 3.095083322337349e-05 loss: 0.0317 (0.0354) time: 3.6242 data: 0.0029 max mem: 19788 +Epoch: [16] [1130/2138] eta: 1:00:54 lr: 3.0945283218906805e-05 loss: 0.0328 (0.0355) time: 3.6192 data: 0.0029 max mem: 19788 +Epoch: [16] [1140/2138] eta: 1:00:18 lr: 3.0939733103839295e-05 loss: 0.0327 (0.0355) time: 3.6216 data: 0.0029 max mem: 19788 +Epoch: [16] [1150/2138] eta: 0:59:42 lr: 3.0934182878146714e-05 loss: 0.0286 (0.0355) time: 3.6235 data: 0.0029 max mem: 19788 +Epoch: [16] [1160/2138] eta: 0:59:05 lr: 3.09286325418048e-05 loss: 0.0281 (0.0355) time: 3.6230 data: 0.0030 max mem: 19788 +Epoch: [16] [1170/2138] eta: 0:58:29 lr: 3.092308209478929e-05 loss: 0.0335 (0.0355) time: 3.6245 data: 0.0032 max mem: 19788 +Epoch: [16] [1180/2138] eta: 0:57:53 lr: 3.091753153707589e-05 loss: 0.0349 (0.0355) time: 3.6237 data: 0.0033 max mem: 19788 +Epoch: [16] [1190/2138] eta: 0:57:17 lr: 3.091198086864033e-05 loss: 0.0309 (0.0355) time: 3.6230 data: 0.0030 max mem: 19788 +Epoch: [16] [1200/2138] eta: 0:56:40 lr: 3.09064300894583e-05 loss: 0.0357 (0.0356) time: 3.6260 data: 0.0029 max mem: 19788 +Epoch: [16] [1210/2138] eta: 0:56:04 lr: 3.090087919950548e-05 loss: 0.0329 (0.0355) time: 3.6316 data: 0.0032 max mem: 19788 +Epoch: [16] [1220/2138] eta: 0:55:28 lr: 3.089532819875757e-05 loss: 0.0339 (0.0355) time: 3.6297 data: 0.0033 max mem: 19788 +Epoch: [16] [1230/2138] eta: 0:54:52 lr: 3.088977708719021e-05 loss: 0.0340 (0.0355) time: 3.6264 data: 0.0032 max mem: 19788 +Epoch: [16] [1240/2138] eta: 0:54:15 lr: 3.0884225864779094e-05 loss: 0.0330 (0.0355) time: 3.6265 data: 0.0032 max mem: 19788 +Epoch: [16] [1250/2138] eta: 0:53:39 lr: 3.087867453149985e-05 loss: 0.0330 (0.0355) time: 3.6262 data: 0.0031 max mem: 19788 +Epoch: [16] [1260/2138] eta: 0:53:03 lr: 3.087312308732811e-05 loss: 0.0307 (0.0355) time: 3.6268 data: 0.0029 max mem: 19788 +Epoch: [16] [1270/2138] eta: 0:52:27 lr: 3.086757153223951e-05 loss: 0.0279 (0.0355) time: 3.6261 data: 0.0028 max mem: 19788 +Epoch: [16] [1280/2138] eta: 0:51:50 lr: 3.086201986620969e-05 loss: 0.0286 (0.0354) time: 3.6264 data: 0.0028 max mem: 19788 +Epoch: [16] [1290/2138] eta: 0:51:14 lr: 3.0856468089214224e-05 loss: 0.0325 (0.0355) time: 3.6230 data: 0.0028 max mem: 19788 +Epoch: [16] [1300/2138] eta: 0:50:38 lr: 3.0850916201228726e-05 loss: 0.0319 (0.0355) time: 3.6211 data: 0.0028 max mem: 19788 +Epoch: [16] [1310/2138] eta: 0:50:01 lr: 3.084536420222877e-05 loss: 0.0315 (0.0355) time: 3.6237 data: 0.0028 max mem: 19788 +Epoch: [16] [1320/2138] eta: 0:49:25 lr: 3.0839812092189957e-05 loss: 0.0356 (0.0355) time: 3.6277 data: 0.0030 max mem: 19788 +Epoch: [16] [1330/2138] eta: 0:48:49 lr: 3.083425987108784e-05 loss: 0.0361 (0.0355) time: 3.6298 data: 0.0031 max mem: 19788 +Epoch: [16] [1340/2138] eta: 0:48:13 lr: 3.0828707538897964e-05 loss: 0.0381 (0.0356) time: 3.6243 data: 0.0030 max mem: 19788 +Epoch: [16] [1350/2138] eta: 0:47:36 lr: 3.08231550955959e-05 loss: 0.0407 (0.0356) time: 3.6200 data: 0.0029 max mem: 19788 +Epoch: [16] [1360/2138] eta: 0:47:00 lr: 3.0817602541157166e-05 loss: 0.0364 (0.0356) time: 3.6261 data: 0.0031 max mem: 19788 +Epoch: [16] [1370/2138] eta: 0:46:24 lr: 3.08120498755573e-05 loss: 0.0342 (0.0356) time: 3.6313 data: 0.0032 max mem: 19788 +Epoch: [16] [1380/2138] eta: 0:45:48 lr: 3.0806497098771796e-05 loss: 0.0324 (0.0356) time: 3.6356 data: 0.0028 max mem: 19788 +Epoch: [16] [1390/2138] eta: 0:45:12 lr: 3.080094421077618e-05 loss: 0.0367 (0.0356) time: 3.6312 data: 0.0030 max mem: 19788 +Epoch: [16] [1400/2138] eta: 0:44:35 lr: 3.0795391211545945e-05 loss: 0.0325 (0.0356) time: 3.6235 data: 0.0032 max mem: 19788 +Epoch: [16] [1410/2138] eta: 0:43:59 lr: 3.0789838101056565e-05 loss: 0.0314 (0.0355) time: 3.6271 data: 0.0031 max mem: 19788 +Epoch: [16] [1420/2138] eta: 0:43:23 lr: 3.078428487928352e-05 loss: 0.0316 (0.0355) time: 3.6281 data: 0.0031 max mem: 19788 +Epoch: [16] [1430/2138] eta: 0:42:47 lr: 3.077873154620228e-05 loss: 0.0344 (0.0356) time: 3.6256 data: 0.0030 max mem: 19788 +Epoch: [16] [1440/2138] eta: 0:42:10 lr: 3.0773178101788287e-05 loss: 0.0307 (0.0355) time: 3.6255 data: 0.0030 max mem: 19788 +Epoch: [16] [1450/2138] eta: 0:41:34 lr: 3.076762454601699e-05 loss: 0.0330 (0.0355) time: 3.6237 data: 0.0028 max mem: 19788 +Epoch: [16] [1460/2138] eta: 0:40:58 lr: 3.076207087886382e-05 loss: 0.0333 (0.0355) time: 3.6238 data: 0.0028 max mem: 19788 +Epoch: [16] [1470/2138] eta: 0:40:22 lr: 3.075651710030421e-05 loss: 0.0313 (0.0355) time: 3.6286 data: 0.0029 max mem: 19788 +Epoch: [16] [1480/2138] eta: 0:39:45 lr: 3.0750963210313554e-05 loss: 0.0342 (0.0355) time: 3.6296 data: 0.0029 max mem: 19788 +Epoch: [16] [1490/2138] eta: 0:39:09 lr: 3.074540920886726e-05 loss: 0.0343 (0.0355) time: 3.6278 data: 0.0030 max mem: 19788 +Epoch: [16] [1500/2138] eta: 0:38:33 lr: 3.073985509594073e-05 loss: 0.0308 (0.0355) time: 3.6252 data: 0.0030 max mem: 19788 +Epoch: [16] [1510/2138] eta: 0:37:56 lr: 3.0734300871509335e-05 loss: 0.0323 (0.0355) time: 3.6254 data: 0.0029 max mem: 19788 +Epoch: [16] [1520/2138] eta: 0:37:20 lr: 3.072874653554845e-05 loss: 0.0323 (0.0355) time: 3.6307 data: 0.0029 max mem: 19788 +Epoch: [16] [1530/2138] eta: 0:36:44 lr: 3.0723192088033424e-05 loss: 0.0281 (0.0355) time: 3.6311 data: 0.0031 max mem: 19788 +Epoch: [16] [1540/2138] eta: 0:36:08 lr: 3.0717637528939624e-05 loss: 0.0308 (0.0355) time: 3.6275 data: 0.0029 max mem: 19788 +Epoch: [16] [1550/2138] eta: 0:35:31 lr: 3.071208285824238e-05 loss: 0.0331 (0.0354) time: 3.6233 data: 0.0029 max mem: 19788 +Epoch: [16] [1560/2138] eta: 0:34:55 lr: 3.070652807591703e-05 loss: 0.0331 (0.0354) time: 3.6221 data: 0.0029 max mem: 19788 +Epoch: [16] [1570/2138] eta: 0:34:19 lr: 3.070097318193887e-05 loss: 0.0329 (0.0354) time: 3.6269 data: 0.0028 max mem: 19788 +Epoch: [16] [1580/2138] eta: 0:33:43 lr: 3.069541817628323e-05 loss: 0.0286 (0.0354) time: 3.6285 data: 0.0029 max mem: 19788 +Epoch: [16] [1590/2138] eta: 0:33:06 lr: 3.06898630589254e-05 loss: 0.0291 (0.0354) time: 3.6255 data: 0.0030 max mem: 19788 +Epoch: [16] [1600/2138] eta: 0:32:30 lr: 3.068430782984068e-05 loss: 0.0367 (0.0354) time: 3.6228 data: 0.0029 max mem: 19788 +Epoch: [16] [1610/2138] eta: 0:31:54 lr: 3.067875248900433e-05 loss: 0.0300 (0.0354) time: 3.6248 data: 0.0030 max mem: 19788 +Epoch: [16] [1620/2138] eta: 0:31:18 lr: 3.0673197036391607e-05 loss: 0.0284 (0.0354) time: 3.6242 data: 0.0032 max mem: 19788 +Epoch: [16] [1630/2138] eta: 0:30:41 lr: 3.06676414719778e-05 loss: 0.0330 (0.0354) time: 3.6234 data: 0.0032 max mem: 19788 +Epoch: [16] [1640/2138] eta: 0:30:05 lr: 3.0662085795738134e-05 loss: 0.0317 (0.0353) time: 3.6246 data: 0.0030 max mem: 19788 +Epoch: [16] [1650/2138] eta: 0:29:29 lr: 3.065653000764784e-05 loss: 0.0269 (0.0353) time: 3.6260 data: 0.0028 max mem: 19788 +Epoch: [16] [1660/2138] eta: 0:28:53 lr: 3.065097410768215e-05 loss: 0.0297 (0.0353) time: 3.6267 data: 0.0029 max mem: 19788 +Epoch: [16] [1670/2138] eta: 0:28:16 lr: 3.0645418095816285e-05 loss: 0.0303 (0.0353) time: 3.6252 data: 0.0030 max mem: 19788 +Epoch: [16] [1680/2138] eta: 0:27:40 lr: 3.063986197202544e-05 loss: 0.0303 (0.0353) time: 3.6307 data: 0.0030 max mem: 19788 +Epoch: [16] [1690/2138] eta: 0:27:04 lr: 3.0634305736284805e-05 loss: 0.0311 (0.0353) time: 3.6294 data: 0.0031 max mem: 19788 +Epoch: [16] [1700/2138] eta: 0:26:28 lr: 3.062874938856957e-05 loss: 0.0304 (0.0352) time: 3.6274 data: 0.0030 max mem: 19788 +Epoch: [16] [1710/2138] eta: 0:25:51 lr: 3.06231929288549e-05 loss: 0.0299 (0.0352) time: 3.6302 data: 0.0030 max mem: 19788 +Epoch: [16] [1720/2138] eta: 0:25:15 lr: 3.061763635711597e-05 loss: 0.0294 (0.0352) time: 3.6308 data: 0.0030 max mem: 19788 +Epoch: [16] [1730/2138] eta: 0:24:39 lr: 3.061207967332791e-05 loss: 0.0313 (0.0352) time: 3.6298 data: 0.0031 max mem: 19788 +Epoch: [16] [1740/2138] eta: 0:24:03 lr: 3.060652287746588e-05 loss: 0.0316 (0.0352) time: 3.6857 data: 0.0030 max mem: 19788 +Epoch: [16] [1750/2138] eta: 0:23:27 lr: 3.0600965969505e-05 loss: 0.0327 (0.0352) time: 3.6995 data: 0.0028 max mem: 19788 +Epoch: [16] [1760/2138] eta: 0:22:50 lr: 3.05954089494204e-05 loss: 0.0341 (0.0352) time: 3.6480 data: 0.0028 max mem: 19788 +Epoch: [16] [1770/2138] eta: 0:22:14 lr: 3.058985181718717e-05 loss: 0.0295 (0.0352) time: 3.6400 data: 0.0029 max mem: 19788 +Epoch: [16] [1780/2138] eta: 0:21:38 lr: 3.058429457278043e-05 loss: 0.0332 (0.0352) time: 3.6374 data: 0.0029 max mem: 19788 +Epoch: [16] [1790/2138] eta: 0:21:02 lr: 3.0578737216175257e-05 loss: 0.0338 (0.0352) time: 3.6420 data: 0.0029 max mem: 19788 +Epoch: [16] [1800/2138] eta: 0:20:25 lr: 3.057317974734673e-05 loss: 0.0329 (0.0352) time: 3.6483 data: 0.0030 max mem: 19788 +Epoch: [16] [1810/2138] eta: 0:19:49 lr: 3.05676221662699e-05 loss: 0.0336 (0.0352) time: 3.6406 data: 0.0031 max mem: 19788 +Epoch: [16] [1820/2138] eta: 0:19:13 lr: 3.056206447291985e-05 loss: 0.0336 (0.0352) time: 3.6289 data: 0.0031 max mem: 19788 +Epoch: [16] [1830/2138] eta: 0:18:37 lr: 3.055650666727162e-05 loss: 0.0333 (0.0352) time: 3.6228 data: 0.0029 max mem: 19788 +Epoch: [16] [1840/2138] eta: 0:18:00 lr: 3.055094874930022e-05 loss: 0.0350 (0.0353) time: 3.6154 data: 0.0028 max mem: 19788 +Epoch: [16] [1850/2138] eta: 0:17:24 lr: 3.05453907189807e-05 loss: 0.0356 (0.0353) time: 3.6161 data: 0.0032 max mem: 19788 +Epoch: [16] [1860/2138] eta: 0:16:48 lr: 3.053983257628808e-05 loss: 0.0356 (0.0353) time: 3.6216 data: 0.0031 max mem: 19788 +Epoch: [16] [1870/2138] eta: 0:16:12 lr: 3.0534274321197345e-05 loss: 0.0379 (0.0353) time: 3.6250 data: 0.0030 max mem: 19788 +Epoch: [16] [1880/2138] eta: 0:15:35 lr: 3.052871595368348e-05 loss: 0.0307 (0.0353) time: 3.6231 data: 0.0033 max mem: 19788 +Epoch: [16] [1890/2138] eta: 0:14:59 lr: 3.0523157473721494e-05 loss: 0.0305 (0.0353) time: 3.6179 data: 0.0033 max mem: 19788 +Epoch: [16] [1900/2138] eta: 0:14:23 lr: 3.051759888128634e-05 loss: 0.0301 (0.0353) time: 3.6241 data: 0.0031 max mem: 19788 +Epoch: [16] [1910/2138] eta: 0:13:46 lr: 3.051204017635298e-05 loss: 0.0301 (0.0353) time: 3.6257 data: 0.0030 max mem: 19788 +Epoch: [16] [1920/2138] eta: 0:13:10 lr: 3.0506481358896365e-05 loss: 0.0285 (0.0353) time: 3.6210 data: 0.0029 max mem: 19788 +Epoch: [16] [1930/2138] eta: 0:12:34 lr: 3.0500922428891438e-05 loss: 0.0319 (0.0353) time: 3.6228 data: 0.0029 max mem: 19788 +Epoch: [16] [1940/2138] eta: 0:11:58 lr: 3.049536338631313e-05 loss: 0.0341 (0.0353) time: 3.6225 data: 0.0029 max mem: 19788 +Epoch: [16] [1950/2138] eta: 0:11:21 lr: 3.0489804231136353e-05 loss: 0.0317 (0.0353) time: 3.6218 data: 0.0028 max mem: 19788 +Epoch: [16] [1960/2138] eta: 0:10:45 lr: 3.0484244963336018e-05 loss: 0.0293 (0.0352) time: 3.6263 data: 0.0028 max mem: 19788 +Epoch: [16] [1970/2138] eta: 0:10:09 lr: 3.0478685582887013e-05 loss: 0.0313 (0.0352) time: 3.6264 data: 0.0028 max mem: 19788 +Epoch: [16] [1980/2138] eta: 0:09:33 lr: 3.0473126089764238e-05 loss: 0.0284 (0.0352) time: 3.6235 data: 0.0029 max mem: 19788 +Epoch: [16] [1990/2138] eta: 0:08:56 lr: 3.046756648394256e-05 loss: 0.0292 (0.0352) time: 3.6237 data: 0.0031 max mem: 19788 +Epoch: [16] [2000/2138] eta: 0:08:20 lr: 3.0462006765396837e-05 loss: 0.0305 (0.0352) time: 3.6268 data: 0.0030 max mem: 19788 +Epoch: [16] [2010/2138] eta: 0:07:44 lr: 3.045644693410194e-05 loss: 0.0320 (0.0352) time: 3.6258 data: 0.0032 max mem: 19788 +Epoch: [16] [2020/2138] eta: 0:07:07 lr: 3.04508869900327e-05 loss: 0.0321 (0.0352) time: 3.6230 data: 0.0033 max mem: 19788 +Epoch: [16] [2030/2138] eta: 0:06:31 lr: 3.044532693316396e-05 loss: 0.0344 (0.0352) time: 3.6236 data: 0.0034 max mem: 19788 +Epoch: [16] [2040/2138] eta: 0:05:55 lr: 3.0439766763470528e-05 loss: 0.0344 (0.0352) time: 3.6243 data: 0.0033 max mem: 19788 +Epoch: [16] [2050/2138] eta: 0:05:19 lr: 3.043420648092722e-05 loss: 0.0348 (0.0352) time: 3.6248 data: 0.0029 max mem: 19788 +Epoch: [16] [2060/2138] eta: 0:04:42 lr: 3.0428646085508838e-05 loss: 0.0324 (0.0352) time: 3.6258 data: 0.0029 max mem: 19788 +Epoch: [16] [2070/2138] eta: 0:04:06 lr: 3.042308557719018e-05 loss: 0.0321 (0.0352) time: 3.6263 data: 0.0031 max mem: 19788 +Epoch: [16] [2080/2138] eta: 0:03:30 lr: 3.041752495594601e-05 loss: 0.0297 (0.0352) time: 3.6174 data: 0.0031 max mem: 19788 +Epoch: [16] [2090/2138] eta: 0:02:54 lr: 3.0411964221751106e-05 loss: 0.0318 (0.0352) time: 3.6151 data: 0.0030 max mem: 19788 +Epoch: [16] [2100/2138] eta: 0:02:17 lr: 3.0406403374580218e-05 loss: 0.0302 (0.0351) time: 3.6172 data: 0.0029 max mem: 19788 +Epoch: [16] [2110/2138] eta: 0:01:41 lr: 3.040084241440809e-05 loss: 0.0330 (0.0352) time: 3.6196 data: 0.0030 max mem: 19788 +Epoch: [16] [2120/2138] eta: 0:01:05 lr: 3.0395281341209474e-05 loss: 0.0403 (0.0352) time: 3.6250 data: 0.0030 max mem: 19788 +Epoch: [16] [2130/2138] eta: 0:00:29 lr: 3.0389720154959083e-05 loss: 0.0364 (0.0352) time: 3.6119 data: 0.0030 max mem: 19788 +Epoch: [16] Total time: 2:09:14 +Test: [ 0/21770] eta: 18:45:14 time: 3.1013 data: 3.0104 max mem: 19788 +Test: [ 100/21770] eta: 0:36:32 time: 0.0647 data: 0.0019 max mem: 19788 +Test: [ 200/21770] eta: 0:30:43 time: 0.0798 data: 0.0024 max mem: 19788 +Test: [ 300/21770] eta: 0:28:31 time: 0.0622 data: 0.0020 max mem: 19788 +Test: [ 400/21770] eta: 0:27:12 time: 0.0700 data: 0.0023 max mem: 19788 +Test: [ 500/21770] eta: 0:26:13 time: 0.0610 data: 0.0019 max mem: 19788 +Test: [ 600/21770] eta: 0:25:25 time: 0.0618 data: 0.0019 max mem: 19788 +Test: [ 700/21770] eta: 0:24:54 time: 0.0668 data: 0.0019 max mem: 19788 +Test: [ 800/21770] eta: 0:24:47 time: 0.0703 data: 0.0021 max mem: 19788 +Test: [ 900/21770] eta: 0:24:36 time: 0.0754 data: 0.0022 max mem: 19788 +Test: [ 1000/21770] eta: 0:24:14 time: 0.0603 data: 0.0020 max mem: 19788 +Test: [ 1100/21770] eta: 0:23:57 time: 0.0712 data: 0.0021 max mem: 19788 +Test: [ 1200/21770] eta: 0:23:48 time: 0.0666 data: 0.0022 max mem: 19788 +Test: [ 1300/21770] eta: 0:23:36 time: 0.0784 data: 0.0024 max mem: 19788 +Test: [ 1400/21770] eta: 0:23:28 time: 0.0702 data: 0.0022 max mem: 19788 +Test: [ 1500/21770] eta: 0:23:19 time: 0.0732 data: 0.0021 max mem: 19788 +Test: [ 1600/21770] eta: 0:23:04 time: 0.0704 data: 0.0022 max mem: 19788 +Test: [ 1700/21770] eta: 0:22:53 time: 0.0618 data: 0.0019 max mem: 19788 +Test: [ 1800/21770] eta: 0:22:43 time: 0.0619 data: 0.0017 max mem: 19788 +Test: [ 1900/21770] eta: 0:22:35 time: 0.0635 data: 0.0025 max mem: 19788 +Test: [ 2000/21770] eta: 0:22:25 time: 0.0614 data: 0.0018 max mem: 19788 +Test: [ 2100/21770] eta: 0:22:20 time: 0.0686 data: 0.0023 max mem: 19788 +Test: [ 2200/21770] eta: 0:22:12 time: 0.0670 data: 0.0020 max mem: 19788 +Test: [ 2300/21770] eta: 0:22:08 time: 0.0636 data: 0.0020 max mem: 19788 +Test: [ 2400/21770] eta: 0:21:56 time: 0.0591 data: 0.0019 max mem: 19788 +Test: [ 2500/21770] eta: 0:21:45 time: 0.0619 data: 0.0020 max mem: 19788 +Test: [ 2600/21770] eta: 0:21:34 time: 0.0630 data: 0.0018 max mem: 19788 +Test: [ 2700/21770] eta: 0:21:27 time: 0.0601 data: 0.0018 max mem: 19788 +Test: [ 2800/21770] eta: 0:21:22 time: 0.0654 data: 0.0018 max mem: 19788 +Test: [ 2900/21770] eta: 0:21:14 time: 0.0615 data: 0.0017 max mem: 19788 +Test: [ 3000/21770] eta: 0:21:04 time: 0.0629 data: 0.0018 max mem: 19788 +Test: [ 3100/21770] eta: 0:20:56 time: 0.0691 data: 0.0020 max mem: 19788 +Test: [ 3200/21770] eta: 0:20:54 time: 0.0716 data: 0.0024 max mem: 19788 +Test: [ 3300/21770] eta: 0:20:45 time: 0.0626 data: 0.0019 max mem: 19788 +Test: [ 3400/21770] eta: 0:20:39 time: 0.0822 data: 0.0025 max mem: 19788 +Test: [ 3500/21770] eta: 0:20:33 time: 0.0690 data: 0.0018 max mem: 19788 +Test: [ 3600/21770] eta: 0:20:25 time: 0.0611 data: 0.0018 max mem: 19788 +Test: [ 3700/21770] eta: 0:20:16 time: 0.0665 data: 0.0021 max mem: 19788 +Test: [ 3800/21770] eta: 0:20:12 time: 0.0649 data: 0.0019 max mem: 19788 +Test: [ 3900/21770] eta: 0:20:05 time: 0.0649 data: 0.0018 max mem: 19788 +Test: [ 4000/21770] eta: 0:19:57 time: 0.0622 data: 0.0020 max mem: 19788 +Test: [ 4100/21770] eta: 0:19:49 time: 0.0670 data: 0.0018 max mem: 19788 +Test: [ 4200/21770] eta: 0:19:45 time: 0.0622 data: 0.0018 max mem: 19788 +Test: [ 4300/21770] eta: 0:19:38 time: 0.0642 data: 0.0019 max mem: 19788 +Test: [ 4400/21770] eta: 0:19:35 time: 0.0820 data: 0.0019 max mem: 19788 +Test: [ 4500/21770] eta: 0:19:28 time: 0.0658 data: 0.0019 max mem: 19788 +Test: [ 4600/21770] eta: 0:19:21 time: 0.0653 data: 0.0019 max mem: 19788 +Test: [ 4700/21770] eta: 0:19:13 time: 0.0640 data: 0.0019 max mem: 19788 +Test: [ 4800/21770] eta: 0:19:06 time: 0.0702 data: 0.0020 max mem: 19788 +Test: [ 4900/21770] eta: 0:19:00 time: 0.0686 data: 0.0019 max mem: 19788 +Test: [ 5000/21770] eta: 0:18:53 time: 0.0654 data: 0.0018 max mem: 19788 +Test: [ 5100/21770] eta: 0:18:47 time: 0.0637 data: 0.0019 max mem: 19788 +Test: [ 5200/21770] eta: 0:18:40 time: 0.0631 data: 0.0019 max mem: 19788 +Test: [ 5300/21770] eta: 0:18:33 time: 0.0650 data: 0.0020 max mem: 19788 +Test: [ 5400/21770] eta: 0:18:27 time: 0.0801 data: 0.0024 max mem: 19788 +Test: [ 5500/21770] eta: 0:18:21 time: 0.0631 data: 0.0019 max mem: 19788 +Test: [ 5600/21770] eta: 0:18:12 time: 0.0626 data: 0.0017 max mem: 19788 +Test: [ 5700/21770] eta: 0:18:05 time: 0.0681 data: 0.0021 max mem: 19788 +Test: [ 5800/21770] eta: 0:18:01 time: 0.0754 data: 0.0020 max mem: 19788 +Test: [ 5900/21770] eta: 0:17:53 time: 0.0668 data: 0.0021 max mem: 19788 +Test: [ 6000/21770] eta: 0:17:47 time: 0.0612 data: 0.0017 max mem: 19788 +Test: [ 6100/21770] eta: 0:17:40 time: 0.0815 data: 0.0024 max mem: 19788 +Test: [ 6200/21770] eta: 0:17:33 time: 0.0651 data: 0.0020 max mem: 19788 +Test: [ 6300/21770] eta: 0:17:25 time: 0.0631 data: 0.0018 max mem: 19788 +Test: [ 6400/21770] eta: 0:17:17 time: 0.0629 data: 0.0019 max mem: 19788 +Test: [ 6500/21770] eta: 0:17:10 time: 0.0623 data: 0.0018 max mem: 19788 +Test: [ 6600/21770] eta: 0:17:02 time: 0.0666 data: 0.0020 max mem: 19788 +Test: [ 6700/21770] eta: 0:16:55 time: 0.0696 data: 0.0021 max mem: 19788 +Test: [ 6800/21770] eta: 0:16:49 time: 0.0631 data: 0.0018 max mem: 19788 +Test: [ 6900/21770] eta: 0:16:42 time: 0.0637 data: 0.0018 max mem: 19788 +Test: [ 7000/21770] eta: 0:16:34 time: 0.0634 data: 0.0026 max mem: 19788 +Test: [ 7100/21770] eta: 0:16:27 time: 0.0627 data: 0.0019 max mem: 19788 +Test: [ 7200/21770] eta: 0:16:20 time: 0.0624 data: 0.0020 max mem: 19788 +Test: [ 7300/21770] eta: 0:16:12 time: 0.0627 data: 0.0019 max mem: 19788 +Test: [ 7400/21770] eta: 0:16:06 time: 0.0665 data: 0.0022 max mem: 19788 +Test: [ 7500/21770] eta: 0:15:58 time: 0.0608 data: 0.0018 max mem: 19788 +Test: [ 7600/21770] eta: 0:15:52 time: 0.0644 data: 0.0018 max mem: 19788 +Test: [ 7700/21770] eta: 0:15:45 time: 0.0764 data: 0.0022 max mem: 19788 +Test: [ 7800/21770] eta: 0:15:39 time: 0.0656 data: 0.0021 max mem: 19788 +Test: [ 7900/21770] eta: 0:15:32 time: 0.0760 data: 0.0023 max mem: 19788 +Test: [ 8000/21770] eta: 0:15:26 time: 0.0711 data: 0.0020 max mem: 19788 +Test: [ 8100/21770] eta: 0:15:19 time: 0.0602 data: 0.0017 max mem: 19788 +Test: [ 8200/21770] eta: 0:15:12 time: 0.0600 data: 0.0019 max mem: 19788 +Test: [ 8300/21770] eta: 0:15:05 time: 0.0668 data: 0.0019 max mem: 19788 +Test: [ 8400/21770] eta: 0:14:59 time: 0.0622 data: 0.0019 max mem: 19788 +Test: [ 8500/21770] eta: 0:14:52 time: 0.0686 data: 0.0020 max mem: 19788 +Test: [ 8600/21770] eta: 0:14:46 time: 0.0628 data: 0.0019 max mem: 19788 +Test: [ 8700/21770] eta: 0:14:39 time: 0.0730 data: 0.0021 max mem: 19788 +Test: [ 8800/21770] eta: 0:14:32 time: 0.0681 data: 0.0021 max mem: 19788 +Test: [ 8900/21770] eta: 0:14:26 time: 0.0636 data: 0.0019 max mem: 19788 +Test: [ 9000/21770] eta: 0:14:19 time: 0.0635 data: 0.0018 max mem: 19788 +Test: [ 9100/21770] eta: 0:14:12 time: 0.0799 data: 0.0023 max mem: 19788 +Test: [ 9200/21770] eta: 0:14:05 time: 0.0626 data: 0.0018 max mem: 19788 +Test: [ 9300/21770] eta: 0:13:58 time: 0.0735 data: 0.0020 max mem: 19788 +Test: [ 9400/21770] eta: 0:13:52 time: 0.0754 data: 0.0024 max mem: 19788 +Test: [ 9500/21770] eta: 0:13:46 time: 0.0675 data: 0.0021 max mem: 19788 +Test: [ 9600/21770] eta: 0:13:38 time: 0.0593 data: 0.0018 max mem: 19788 +Test: [ 9700/21770] eta: 0:13:31 time: 0.0638 data: 0.0018 max mem: 19788 +Test: [ 9800/21770] eta: 0:13:24 time: 0.0632 data: 0.0019 max mem: 19788 +Test: [ 9900/21770] eta: 0:13:18 time: 0.0717 data: 0.0021 max mem: 19788 +Test: [10000/21770] eta: 0:13:11 time: 0.0648 data: 0.0019 max mem: 19788 +Test: [10100/21770] eta: 0:13:05 time: 0.0722 data: 0.0021 max mem: 19788 +Test: [10200/21770] eta: 0:12:58 time: 0.0706 data: 0.0022 max mem: 19788 +Test: [10300/21770] eta: 0:12:51 time: 0.0603 data: 0.0018 max mem: 19788 +Test: [10400/21770] eta: 0:12:44 time: 0.0640 data: 0.0020 max mem: 19788 +Test: [10500/21770] eta: 0:12:38 time: 0.0799 data: 0.0022 max mem: 19788 +Test: [10600/21770] eta: 0:12:32 time: 0.0680 data: 0.0019 max mem: 19788 +Test: [10700/21770] eta: 0:12:25 time: 0.0617 data: 0.0018 max mem: 19788 +Test: [10800/21770] eta: 0:12:18 time: 0.0643 data: 0.0018 max mem: 19788 +Test: [10900/21770] eta: 0:12:13 time: 0.0815 data: 0.0024 max mem: 19788 +Test: [11000/21770] eta: 0:12:06 time: 0.0627 data: 0.0018 max mem: 19788 +Test: [11100/21770] eta: 0:11:59 time: 0.0672 data: 0.0017 max mem: 19788 +Test: [11200/21770] eta: 0:11:52 time: 0.0698 data: 0.0021 max mem: 19788 +Test: [11300/21770] eta: 0:11:45 time: 0.0630 data: 0.0018 max mem: 19788 +Test: [11400/21770] eta: 0:11:39 time: 0.0737 data: 0.0020 max mem: 19788 +Test: [11500/21770] eta: 0:11:32 time: 0.0711 data: 0.0021 max mem: 19788 +Test: [11600/21770] eta: 0:11:25 time: 0.0806 data: 0.0023 max mem: 19788 +Test: [11700/21770] eta: 0:11:19 time: 0.0652 data: 0.0020 max mem: 19788 +Test: [11800/21770] eta: 0:11:13 time: 0.0732 data: 0.0019 max mem: 19788 +Test: [11900/21770] eta: 0:11:07 time: 0.0770 data: 0.0023 max mem: 19788 +Test: [12000/21770] eta: 0:11:01 time: 0.0790 data: 0.0019 max mem: 19788 +Test: [12100/21770] eta: 0:10:54 time: 0.0653 data: 0.0018 max mem: 19788 +Test: [12200/21770] eta: 0:10:47 time: 0.0649 data: 0.0020 max mem: 19788 +Test: [12300/21770] eta: 0:10:41 time: 0.0625 data: 0.0019 max mem: 19788 +Test: [12400/21770] eta: 0:10:34 time: 0.0620 data: 0.0020 max mem: 19788 +Test: [12500/21770] eta: 0:10:27 time: 0.0739 data: 0.0022 max mem: 19788 +Test: [12600/21770] eta: 0:10:21 time: 0.0648 data: 0.0020 max mem: 19788 +Test: [12700/21770] eta: 0:10:14 time: 0.0671 data: 0.0020 max mem: 19788 +Test: [12800/21770] eta: 0:10:08 time: 0.0748 data: 0.0021 max mem: 19788 +Test: [12900/21770] eta: 0:10:01 time: 0.0711 data: 0.0019 max mem: 19788 +Test: [13000/21770] eta: 0:09:54 time: 0.0677 data: 0.0019 max mem: 19788 +Test: [13100/21770] eta: 0:09:48 time: 0.0615 data: 0.0021 max mem: 19788 +Test: [13200/21770] eta: 0:09:41 time: 0.0609 data: 0.0018 max mem: 19788 +Test: [13300/21770] eta: 0:09:33 time: 0.0623 data: 0.0020 max mem: 19788 +Test: [13400/21770] eta: 0:09:26 time: 0.0654 data: 0.0019 max mem: 19788 +Test: [13500/21770] eta: 0:09:20 time: 0.0632 data: 0.0019 max mem: 19788 +Test: [13600/21770] eta: 0:09:13 time: 0.0643 data: 0.0019 max mem: 19788 +Test: [13700/21770] eta: 0:09:06 time: 0.0704 data: 0.0018 max mem: 19788 +Test: [13800/21770] eta: 0:09:00 time: 0.0720 data: 0.0023 max mem: 19788 +Test: [13900/21770] eta: 0:08:53 time: 0.0715 data: 0.0022 max mem: 19788 +Test: [14000/21770] eta: 0:08:46 time: 0.0710 data: 0.0019 max mem: 19788 +Test: [14100/21770] eta: 0:08:39 time: 0.0645 data: 0.0018 max mem: 19788 +Test: [14200/21770] eta: 0:08:33 time: 0.0703 data: 0.0022 max mem: 19788 +Test: [14300/21770] eta: 0:08:26 time: 0.0761 data: 0.0023 max mem: 19788 +Test: [14400/21770] eta: 0:08:20 time: 0.0660 data: 0.0018 max mem: 19788 +Test: [14500/21770] eta: 0:08:13 time: 0.0675 data: 0.0019 max mem: 19788 +Test: [14600/21770] eta: 0:08:06 time: 0.0668 data: 0.0020 max mem: 19788 +Test: [14700/21770] eta: 0:07:59 time: 0.0645 data: 0.0018 max mem: 19788 +Test: [14800/21770] eta: 0:07:52 time: 0.0681 data: 0.0020 max mem: 19788 +Test: [14900/21770] eta: 0:07:46 time: 0.0776 data: 0.0024 max mem: 19788 +Test: [15000/21770] eta: 0:07:39 time: 0.0604 data: 0.0018 max mem: 19788 +Test: [15100/21770] eta: 0:07:32 time: 0.0702 data: 0.0022 max mem: 19788 +Test: [15200/21770] eta: 0:07:25 time: 0.0620 data: 0.0017 max mem: 19788 +Test: [15300/21770] eta: 0:07:18 time: 0.0783 data: 0.0020 max mem: 19788 +Test: [15400/21770] eta: 0:07:12 time: 0.0702 data: 0.0020 max mem: 19788 +Test: [15500/21770] eta: 0:07:05 time: 0.0724 data: 0.0021 max mem: 19788 +Test: [15600/21770] eta: 0:06:58 time: 0.0641 data: 0.0019 max mem: 19788 +Test: [15700/21770] eta: 0:06:52 time: 0.0625 data: 0.0019 max mem: 19788 +Test: [15800/21770] eta: 0:06:45 time: 0.0669 data: 0.0020 max mem: 19788 +Test: [15900/21770] eta: 0:06:38 time: 0.0698 data: 0.0018 max mem: 19788 +Test: [16000/21770] eta: 0:06:31 time: 0.0640 data: 0.0019 max mem: 19788 +Test: [16100/21770] eta: 0:06:24 time: 0.0708 data: 0.0019 max mem: 19788 +Test: [16200/21770] eta: 0:06:17 time: 0.0600 data: 0.0019 max mem: 19788 +Test: [16300/21770] eta: 0:06:11 time: 0.0629 data: 0.0018 max mem: 19788 +Test: [16400/21770] eta: 0:06:04 time: 0.0646 data: 0.0017 max mem: 19788 +Test: [16500/21770] eta: 0:05:57 time: 0.0696 data: 0.0019 max mem: 19788 +Test: [16600/21770] eta: 0:05:50 time: 0.0635 data: 0.0020 max mem: 19788 +Test: [16700/21770] eta: 0:05:44 time: 0.0690 data: 0.0021 max mem: 19788 +Test: [16800/21770] eta: 0:05:37 time: 0.0653 data: 0.0019 max mem: 19788 +Test: [16900/21770] eta: 0:05:30 time: 0.0661 data: 0.0019 max mem: 19788 +Test: [17000/21770] eta: 0:05:23 time: 0.0630 data: 0.0017 max mem: 19788 +Test: [17100/21770] eta: 0:05:16 time: 0.0763 data: 0.0021 max mem: 19788 +Test: [17200/21770] eta: 0:05:09 time: 0.0620 data: 0.0018 max mem: 19788 +Test: [17300/21770] eta: 0:05:03 time: 0.0617 data: 0.0018 max mem: 19788 +Test: [17400/21770] eta: 0:04:56 time: 0.0624 data: 0.0020 max mem: 19788 +Test: [17500/21770] eta: 0:04:49 time: 0.0697 data: 0.0020 max mem: 19788 +Test: [17600/21770] eta: 0:04:42 time: 0.0616 data: 0.0017 max mem: 19788 +Test: [17700/21770] eta: 0:04:35 time: 0.0790 data: 0.0021 max mem: 19788 +Test: [17800/21770] eta: 0:04:29 time: 0.0607 data: 0.0019 max mem: 19788 +Test: [17900/21770] eta: 0:04:22 time: 0.0709 data: 0.0021 max mem: 19788 +Test: [18000/21770] eta: 0:04:15 time: 0.0652 data: 0.0021 max mem: 19788 +Test: [18100/21770] eta: 0:04:08 time: 0.0614 data: 0.0021 max mem: 19788 +Test: [18200/21770] eta: 0:04:01 time: 0.0619 data: 0.0018 max mem: 19788 +Test: [18300/21770] eta: 0:03:55 time: 0.0632 data: 0.0020 max mem: 19788 +Test: [18400/21770] eta: 0:03:48 time: 0.0696 data: 0.0019 max mem: 19788 +Test: [18500/21770] eta: 0:03:41 time: 0.0631 data: 0.0020 max mem: 19788 +Test: [18600/21770] eta: 0:03:34 time: 0.0624 data: 0.0019 max mem: 19788 +Test: [18700/21770] eta: 0:03:27 time: 0.0658 data: 0.0020 max mem: 19788 +Test: [18800/21770] eta: 0:03:21 time: 0.0619 data: 0.0020 max mem: 19788 +Test: [18900/21770] eta: 0:03:14 time: 0.0605 data: 0.0017 max mem: 19788 +Test: [19000/21770] eta: 0:03:07 time: 0.0667 data: 0.0021 max mem: 19788 +Test: [19100/21770] eta: 0:03:00 time: 0.0754 data: 0.0023 max mem: 19788 +Test: [19200/21770] eta: 0:02:53 time: 0.0717 data: 0.0019 max mem: 19788 +Test: [19300/21770] eta: 0:02:47 time: 0.0745 data: 0.0018 max mem: 19788 +Test: [19400/21770] eta: 0:02:40 time: 0.0687 data: 0.0020 max mem: 19788 +Test: [19500/21770] eta: 0:02:33 time: 0.0689 data: 0.0020 max mem: 19788 +Test: [19600/21770] eta: 0:02:26 time: 0.0640 data: 0.0018 max mem: 19788 +Test: [19700/21770] eta: 0:02:20 time: 0.0611 data: 0.0017 max mem: 19788 +Test: [19800/21770] eta: 0:02:13 time: 0.0623 data: 0.0020 max mem: 19788 +Test: [19900/21770] eta: 0:02:06 time: 0.0647 data: 0.0021 max mem: 19788 +Test: [20000/21770] eta: 0:01:59 time: 0.0717 data: 0.0021 max mem: 19788 +Test: [20100/21770] eta: 0:01:53 time: 0.0639 data: 0.0020 max mem: 19788 +Test: [20200/21770] eta: 0:01:46 time: 0.0612 data: 0.0019 max mem: 19788 +Test: [20300/21770] eta: 0:01:39 time: 0.0697 data: 0.0018 max mem: 19788 +Test: [20400/21770] eta: 0:01:32 time: 0.0712 data: 0.0022 max mem: 19788 +Test: [20500/21770] eta: 0:01:25 time: 0.0620 data: 0.0019 max mem: 19788 +Test: [20600/21770] eta: 0:01:19 time: 0.0635 data: 0.0019 max mem: 19788 +Test: [20700/21770] eta: 0:01:12 time: 0.0781 data: 0.0024 max mem: 19788 +Test: [20800/21770] eta: 0:01:05 time: 0.0611 data: 0.0018 max mem: 19788 +Test: [20900/21770] eta: 0:00:58 time: 0.0692 data: 0.0022 max mem: 19788 +Test: [21000/21770] eta: 0:00:52 time: 0.0625 data: 0.0018 max mem: 19788 +Test: [21100/21770] eta: 0:00:45 time: 0.0720 data: 0.0021 max mem: 19788 +Test: [21200/21770] eta: 0:00:38 time: 0.0818 data: 0.0023 max mem: 19788 +Test: [21300/21770] eta: 0:00:31 time: 0.0647 data: 0.0018 max mem: 19788 +Test: [21400/21770] eta: 0:00:25 time: 0.0676 data: 0.0018 max mem: 19788 +Test: [21500/21770] eta: 0:00:18 time: 0.0622 data: 0.0018 max mem: 19788 +Test: [21600/21770] eta: 0:00:11 time: 0.0669 data: 0.0019 max mem: 19788 +Test: [21700/21770] eta: 0:00:04 time: 0.0629 data: 0.0020 max mem: 19788 +Test: Total time: 0:24:33 +Final results: +Mean IoU is 62.44 + + precision@0.5 = 69.10 + precision@0.6 = 63.81 + precision@0.7 = 56.92 + precision@0.8 = 46.30 + precision@0.9 = 23.43 + overall IoU = 63.40 + mean IoU = 62.44 + +Mean accuracy for one-to-zero sample is 82.38 + +Average object IoU 0.6243740603460619 +Overall IoU 63.39683532714844 +Epoch: [17] [ 0/2138] eta: 9:02:39 lr: 3.0385271124544502e-05 loss: 0.0294 (0.0294) time: 15.2290 data: 1.7013 max mem: 19788 +Epoch: [17] [ 10/2138] eta: 2:46:18 lr: 3.037970973473719e-05 loss: 0.0234 (0.0260) time: 4.6889 data: 0.1573 max mem: 19788 +Epoch: [17] [ 20/2138] eta: 2:27:47 lr: 3.0374148231807275e-05 loss: 0.0267 (0.0272) time: 3.6344 data: 0.0025 max mem: 19788 +Epoch: [17] [ 30/2138] eta: 2:20:51 lr: 3.0368586615729457e-05 loss: 0.0271 (0.0272) time: 3.6356 data: 0.0027 max mem: 19788 +Epoch: [17] [ 40/2138] eta: 2:16:58 lr: 3.036302488647838e-05 loss: 0.0283 (0.0291) time: 3.6345 data: 0.0032 max mem: 19788 +Epoch: [17] [ 50/2138] eta: 2:14:22 lr: 3.0357463044028723e-05 loss: 0.0325 (0.0302) time: 3.6314 data: 0.0032 max mem: 19788 +Epoch: [17] [ 60/2138] eta: 2:12:18 lr: 3.0351901088355144e-05 loss: 0.0261 (0.0297) time: 3.6216 data: 0.0032 max mem: 19788 +Epoch: [17] [ 70/2138] eta: 2:10:43 lr: 3.0346339019432275e-05 loss: 0.0235 (0.0297) time: 3.6179 data: 0.0031 max mem: 19788 +Epoch: [17] [ 80/2138] eta: 2:09:21 lr: 3.034077683723474e-05 loss: 0.0300 (0.0301) time: 3.6228 data: 0.0030 max mem: 19788 +Epoch: [17] [ 90/2138] eta: 2:08:11 lr: 3.0335214541737166e-05 loss: 0.0301 (0.0301) time: 3.6252 data: 0.0030 max mem: 19788 +Epoch: [17] [ 100/2138] eta: 2:07:07 lr: 3.0329652132914164e-05 loss: 0.0306 (0.0300) time: 3.6256 data: 0.0030 max mem: 19788 +Epoch: [17] [ 110/2138] eta: 2:06:06 lr: 3.032408961074033e-05 loss: 0.0304 (0.0301) time: 3.6193 data: 0.0031 max mem: 19788 +Epoch: [17] [ 120/2138] eta: 2:05:11 lr: 3.0318526975190237e-05 loss: 0.0280 (0.0305) time: 3.6196 data: 0.0029 max mem: 19788 +Epoch: [17] [ 130/2138] eta: 2:04:18 lr: 3.0312964226238476e-05 loss: 0.0343 (0.0313) time: 3.6202 data: 0.0028 max mem: 19788 +Epoch: [17] [ 140/2138] eta: 2:03:29 lr: 3.030740136385961e-05 loss: 0.0332 (0.0310) time: 3.6249 data: 0.0030 max mem: 19788 +Epoch: [17] [ 150/2138] eta: 2:02:40 lr: 3.030183838802818e-05 loss: 0.0274 (0.0309) time: 3.6261 data: 0.0029 max mem: 19788 +Epoch: [17] [ 160/2138] eta: 2:01:53 lr: 3.029627529871874e-05 loss: 0.0330 (0.0314) time: 3.6195 data: 0.0028 max mem: 19788 +Epoch: [17] [ 170/2138] eta: 2:01:07 lr: 3.0290712095905828e-05 loss: 0.0354 (0.0315) time: 3.6202 data: 0.0030 max mem: 19788 +Epoch: [17] [ 180/2138] eta: 2:00:23 lr: 3.0285148779563948e-05 loss: 0.0348 (0.0317) time: 3.6211 data: 0.0030 max mem: 19788 +Epoch: [17] [ 190/2138] eta: 1:59:39 lr: 3.0279585349667618e-05 loss: 0.0331 (0.0316) time: 3.6229 data: 0.0030 max mem: 19788 +Epoch: [17] [ 200/2138] eta: 1:58:56 lr: 3.0274021806191332e-05 loss: 0.0227 (0.0312) time: 3.6208 data: 0.0032 max mem: 19788 +Epoch: [17] [ 210/2138] eta: 1:58:13 lr: 3.0268458149109598e-05 loss: 0.0310 (0.0316) time: 3.6193 data: 0.0030 max mem: 19788 +Epoch: [17] [ 220/2138] eta: 1:57:32 lr: 3.0262894378396873e-05 loss: 0.0321 (0.0314) time: 3.6221 data: 0.0028 max mem: 19788 +Epoch: [17] [ 230/2138] eta: 1:56:50 lr: 3.025733049402762e-05 loss: 0.0317 (0.0317) time: 3.6230 data: 0.0029 max mem: 19788 +Epoch: [17] [ 240/2138] eta: 1:56:10 lr: 3.0251766495976308e-05 loss: 0.0317 (0.0316) time: 3.6255 data: 0.0029 max mem: 19788 +Epoch: [17] [ 250/2138] eta: 1:55:30 lr: 3.024620238421738e-05 loss: 0.0291 (0.0317) time: 3.6259 data: 0.0029 max mem: 19788 +Epoch: [17] [ 260/2138] eta: 1:54:50 lr: 3.0240638158725264e-05 loss: 0.0260 (0.0316) time: 3.6250 data: 0.0029 max mem: 19788 +Epoch: [17] [ 270/2138] eta: 1:54:10 lr: 3.0235073819474385e-05 loss: 0.0291 (0.0317) time: 3.6247 data: 0.0028 max mem: 19788 +Epoch: [17] [ 280/2138] eta: 1:53:30 lr: 3.0229509366439145e-05 loss: 0.0299 (0.0317) time: 3.6215 data: 0.0032 max mem: 19788 +Epoch: [17] [ 290/2138] eta: 1:52:51 lr: 3.0223944799593967e-05 loss: 0.0333 (0.0319) time: 3.6266 data: 0.0033 max mem: 19788 +Epoch: [17] [ 300/2138] eta: 1:52:12 lr: 3.021838011891322e-05 loss: 0.0305 (0.0318) time: 3.6261 data: 0.0032 max mem: 19788 +Epoch: [17] [ 310/2138] eta: 1:51:37 lr: 3.0212815324371292e-05 loss: 0.0304 (0.0320) time: 3.6582 data: 0.0033 max mem: 19788 +Epoch: [17] [ 320/2138] eta: 1:50:59 lr: 3.020725041594254e-05 loss: 0.0304 (0.0320) time: 3.6622 data: 0.0032 max mem: 19788 +Epoch: [17] [ 330/2138] eta: 1:50:19 lr: 3.020168539360133e-05 loss: 0.0298 (0.0320) time: 3.6211 data: 0.0033 max mem: 19788 +Epoch: [17] [ 340/2138] eta: 1:49:40 lr: 3.0196120257322015e-05 loss: 0.0295 (0.0320) time: 3.6173 data: 0.0032 max mem: 19788 +Epoch: [17] [ 350/2138] eta: 1:49:02 lr: 3.0190555007078907e-05 loss: 0.0317 (0.0320) time: 3.6230 data: 0.0030 max mem: 19788 +Epoch: [17] [ 360/2138] eta: 1:48:24 lr: 3.018498964284634e-05 loss: 0.0307 (0.0320) time: 3.6229 data: 0.0030 max mem: 19788 +Epoch: [17] [ 370/2138] eta: 1:47:45 lr: 3.017942416459864e-05 loss: 0.0307 (0.0322) time: 3.6185 data: 0.0030 max mem: 19788 +Epoch: [17] [ 380/2138] eta: 1:47:07 lr: 3.0173858572310094e-05 loss: 0.0310 (0.0322) time: 3.6154 data: 0.0030 max mem: 19788 +Epoch: [17] [ 390/2138] eta: 1:46:28 lr: 3.0168292865954984e-05 loss: 0.0318 (0.0323) time: 3.6158 data: 0.0033 max mem: 19788 +Epoch: [17] [ 400/2138] eta: 1:45:50 lr: 3.0162727045507606e-05 loss: 0.0334 (0.0323) time: 3.6167 data: 0.0035 max mem: 19788 +Epoch: [17] [ 410/2138] eta: 1:45:13 lr: 3.0157161110942217e-05 loss: 0.0335 (0.0325) time: 3.6236 data: 0.0031 max mem: 19788 +Epoch: [17] [ 420/2138] eta: 1:44:34 lr: 3.0151595062233084e-05 loss: 0.0307 (0.0324) time: 3.6238 data: 0.0032 max mem: 19788 +Epoch: [17] [ 430/2138] eta: 1:43:57 lr: 3.0146028899354446e-05 loss: 0.0285 (0.0325) time: 3.6173 data: 0.0033 max mem: 19788 +Epoch: [17] [ 440/2138] eta: 1:43:19 lr: 3.0140462622280534e-05 loss: 0.0347 (0.0327) time: 3.6215 data: 0.0031 max mem: 19788 +Epoch: [17] [ 450/2138] eta: 1:42:42 lr: 3.013489623098558e-05 loss: 0.0357 (0.0327) time: 3.6244 data: 0.0031 max mem: 19788 +Epoch: [17] [ 460/2138] eta: 1:42:04 lr: 3.0129329725443796e-05 loss: 0.0303 (0.0328) time: 3.6271 data: 0.0031 max mem: 19788 +Epoch: [17] [ 470/2138] eta: 1:41:27 lr: 3.0123763105629372e-05 loss: 0.0332 (0.0327) time: 3.6236 data: 0.0030 max mem: 19788 +Epoch: [17] [ 480/2138] eta: 1:40:49 lr: 3.011819637151651e-05 loss: 0.0324 (0.0328) time: 3.6226 data: 0.0028 max mem: 19788 +Epoch: [17] [ 490/2138] eta: 1:40:12 lr: 3.011262952307939e-05 loss: 0.0280 (0.0327) time: 3.6278 data: 0.0029 max mem: 19788 +Epoch: [17] [ 500/2138] eta: 1:39:35 lr: 3.0107062560292164e-05 loss: 0.0270 (0.0327) time: 3.6295 data: 0.0030 max mem: 19788 +Epoch: [17] [ 510/2138] eta: 1:38:58 lr: 3.0101495483129005e-05 loss: 0.0324 (0.0326) time: 3.6309 data: 0.0031 max mem: 19788 +Epoch: [17] [ 520/2138] eta: 1:38:21 lr: 3.0095928291564062e-05 loss: 0.0330 (0.0327) time: 3.6291 data: 0.0029 max mem: 19788 +Epoch: [17] [ 530/2138] eta: 1:37:44 lr: 3.0090360985571457e-05 loss: 0.0309 (0.0327) time: 3.6280 data: 0.0027 max mem: 19788 +Epoch: [17] [ 540/2138] eta: 1:37:07 lr: 3.0084793565125313e-05 loss: 0.0272 (0.0326) time: 3.6291 data: 0.0028 max mem: 19788 +Epoch: [17] [ 550/2138] eta: 1:36:30 lr: 3.0079226030199746e-05 loss: 0.0293 (0.0326) time: 3.6263 data: 0.0030 max mem: 19788 +Epoch: [17] [ 560/2138] eta: 1:35:53 lr: 3.007365838076887e-05 loss: 0.0277 (0.0327) time: 3.6238 data: 0.0031 max mem: 19788 +Epoch: [17] [ 570/2138] eta: 1:35:16 lr: 3.006809061680676e-05 loss: 0.0262 (0.0327) time: 3.6235 data: 0.0030 max mem: 19788 +Epoch: [17] [ 580/2138] eta: 1:34:38 lr: 3.0062522738287492e-05 loss: 0.0342 (0.0327) time: 3.6200 data: 0.0028 max mem: 19788 +Epoch: [17] [ 590/2138] eta: 1:34:01 lr: 3.0056954745185134e-05 loss: 0.0342 (0.0327) time: 3.6210 data: 0.0030 max mem: 19788 +Epoch: [17] [ 600/2138] eta: 1:33:25 lr: 3.0051386637473754e-05 loss: 0.0295 (0.0329) time: 3.6262 data: 0.0031 max mem: 19788 +Epoch: [17] [ 610/2138] eta: 1:32:48 lr: 3.004581841512739e-05 loss: 0.0321 (0.0329) time: 3.6279 data: 0.0029 max mem: 19788 +Epoch: [17] [ 620/2138] eta: 1:32:11 lr: 3.0040250078120074e-05 loss: 0.0352 (0.0330) time: 3.6271 data: 0.0030 max mem: 19788 +Epoch: [17] [ 630/2138] eta: 1:31:34 lr: 3.0034681626425832e-05 loss: 0.0303 (0.0329) time: 3.6238 data: 0.0030 max mem: 19788 +Epoch: [17] [ 640/2138] eta: 1:30:57 lr: 3.0029113060018677e-05 loss: 0.0300 (0.0329) time: 3.6206 data: 0.0028 max mem: 19788 +Epoch: [17] [ 650/2138] eta: 1:30:20 lr: 3.0023544378872604e-05 loss: 0.0299 (0.0328) time: 3.6215 data: 0.0030 max mem: 19788 +Epoch: [17] [ 660/2138] eta: 1:29:43 lr: 3.00179755829616e-05 loss: 0.0299 (0.0328) time: 3.6238 data: 0.0033 max mem: 19788 +Epoch: [17] [ 670/2138] eta: 1:29:06 lr: 3.0012406672259646e-05 loss: 0.0318 (0.0328) time: 3.6258 data: 0.0033 max mem: 19788 +Epoch: [17] [ 680/2138] eta: 1:28:30 lr: 3.000683764674071e-05 loss: 0.0320 (0.0328) time: 3.6247 data: 0.0032 max mem: 19788 +Epoch: [17] [ 690/2138] eta: 1:27:53 lr: 3.000126850637875e-05 loss: 0.0309 (0.0328) time: 3.6225 data: 0.0030 max mem: 19788 +Epoch: [17] [ 700/2138] eta: 1:27:16 lr: 2.9995699251147704e-05 loss: 0.0294 (0.0327) time: 3.6227 data: 0.0029 max mem: 19788 +Epoch: [17] [ 710/2138] eta: 1:26:39 lr: 2.9990129881021495e-05 loss: 0.0294 (0.0327) time: 3.6227 data: 0.0030 max mem: 19788 +Epoch: [17] [ 720/2138] eta: 1:26:02 lr: 2.9984560395974064e-05 loss: 0.0272 (0.0327) time: 3.6250 data: 0.0030 max mem: 19788 +Epoch: [17] [ 730/2138] eta: 1:25:26 lr: 2.997899079597932e-05 loss: 0.0292 (0.0328) time: 3.6255 data: 0.0028 max mem: 19788 +Epoch: [17] [ 740/2138] eta: 1:24:49 lr: 2.9973421081011137e-05 loss: 0.0292 (0.0327) time: 3.6265 data: 0.0029 max mem: 19788 +Epoch: [17] [ 750/2138] eta: 1:24:13 lr: 2.9967851251043426e-05 loss: 0.0275 (0.0327) time: 3.6316 data: 0.0029 max mem: 19788 +Epoch: [17] [ 760/2138] eta: 1:23:36 lr: 2.996228130605006e-05 loss: 0.0324 (0.0327) time: 3.6353 data: 0.0031 max mem: 19788 +Epoch: [17] [ 770/2138] eta: 1:22:59 lr: 2.9956711246004888e-05 loss: 0.0310 (0.0327) time: 3.6322 data: 0.0031 max mem: 19788 +Epoch: [17] [ 780/2138] eta: 1:22:23 lr: 2.9951141070881778e-05 loss: 0.0309 (0.0327) time: 3.6261 data: 0.0029 max mem: 19788 +Epoch: [17] [ 790/2138] eta: 1:21:46 lr: 2.9945570780654568e-05 loss: 0.0336 (0.0327) time: 3.6207 data: 0.0030 max mem: 19788 +Epoch: [17] [ 800/2138] eta: 1:21:09 lr: 2.9940000375297095e-05 loss: 0.0294 (0.0328) time: 3.6186 data: 0.0030 max mem: 19788 +Epoch: [17] [ 810/2138] eta: 1:20:33 lr: 2.9934429854783165e-05 loss: 0.0323 (0.0328) time: 3.6255 data: 0.0029 max mem: 19788 +Epoch: [17] [ 820/2138] eta: 1:19:56 lr: 2.992885921908659e-05 loss: 0.0343 (0.0328) time: 3.6305 data: 0.0030 max mem: 19788 +Epoch: [17] [ 830/2138] eta: 1:19:20 lr: 2.9923288468181177e-05 loss: 0.0257 (0.0327) time: 3.6314 data: 0.0029 max mem: 19788 +Epoch: [17] [ 840/2138] eta: 1:18:43 lr: 2.9917717602040695e-05 loss: 0.0242 (0.0327) time: 3.6268 data: 0.0028 max mem: 19788 +Epoch: [17] [ 850/2138] eta: 1:18:06 lr: 2.991214662063893e-05 loss: 0.0242 (0.0326) time: 3.6199 data: 0.0030 max mem: 19788 +Epoch: [17] [ 860/2138] eta: 1:17:30 lr: 2.990657552394964e-05 loss: 0.0315 (0.0327) time: 3.6222 data: 0.0030 max mem: 19788 +Epoch: [17] [ 870/2138] eta: 1:16:53 lr: 2.990100431194657e-05 loss: 0.0312 (0.0327) time: 3.6262 data: 0.0029 max mem: 19788 +Epoch: [17] [ 880/2138] eta: 1:16:17 lr: 2.989543298460347e-05 loss: 0.0304 (0.0327) time: 3.6275 data: 0.0030 max mem: 19788 +Epoch: [17] [ 890/2138] eta: 1:15:40 lr: 2.988986154189406e-05 loss: 0.0284 (0.0327) time: 3.6278 data: 0.0033 max mem: 19788 +Epoch: [17] [ 900/2138] eta: 1:15:04 lr: 2.988428998379206e-05 loss: 0.0300 (0.0327) time: 3.6274 data: 0.0032 max mem: 19788 +Epoch: [17] [ 910/2138] eta: 1:14:27 lr: 2.9878718310271176e-05 loss: 0.0300 (0.0327) time: 3.6253 data: 0.0031 max mem: 19788 +Epoch: [17] [ 920/2138] eta: 1:13:52 lr: 2.9873146521305102e-05 loss: 0.0285 (0.0327) time: 3.6911 data: 0.0031 max mem: 19788 +Epoch: [17] [ 930/2138] eta: 1:13:16 lr: 2.9867574616867516e-05 loss: 0.0311 (0.0327) time: 3.7020 data: 0.0029 max mem: 19788 +Epoch: [17] [ 940/2138] eta: 1:12:40 lr: 2.9862002596932085e-05 loss: 0.0319 (0.0327) time: 3.6448 data: 0.0028 max mem: 19788 +Epoch: [17] [ 950/2138] eta: 1:12:03 lr: 2.9856430461472484e-05 loss: 0.0319 (0.0327) time: 3.6403 data: 0.0029 max mem: 19788 +Epoch: [17] [ 960/2138] eta: 1:11:27 lr: 2.9850858210462355e-05 loss: 0.0326 (0.0327) time: 3.6335 data: 0.0030 max mem: 19788 +Epoch: [17] [ 970/2138] eta: 1:10:50 lr: 2.984528584387532e-05 loss: 0.0325 (0.0327) time: 3.6326 data: 0.0031 max mem: 19788 +Epoch: [17] [ 980/2138] eta: 1:10:14 lr: 2.9839713361685017e-05 loss: 0.0273 (0.0327) time: 3.6361 data: 0.0030 max mem: 19788 +Epoch: [17] [ 990/2138] eta: 1:09:37 lr: 2.9834140763865065e-05 loss: 0.0301 (0.0328) time: 3.6381 data: 0.0029 max mem: 19788 +Epoch: [17] [1000/2138] eta: 1:09:01 lr: 2.9828568050389055e-05 loss: 0.0345 (0.0328) time: 3.6366 data: 0.0029 max mem: 19788 +Epoch: [17] [1010/2138] eta: 1:08:24 lr: 2.9822995221230578e-05 loss: 0.0264 (0.0327) time: 3.6295 data: 0.0030 max mem: 19788 +Epoch: [17] [1020/2138] eta: 1:07:48 lr: 2.9817422276363212e-05 loss: 0.0244 (0.0327) time: 3.6242 data: 0.0029 max mem: 19788 +Epoch: [17] [1030/2138] eta: 1:07:11 lr: 2.9811849215760534e-05 loss: 0.0257 (0.0327) time: 3.6211 data: 0.0028 max mem: 19788 +Epoch: [17] [1040/2138] eta: 1:06:35 lr: 2.9806276039396096e-05 loss: 0.0294 (0.0327) time: 3.6206 data: 0.0029 max mem: 19788 +Epoch: [17] [1050/2138] eta: 1:05:58 lr: 2.980070274724343e-05 loss: 0.0328 (0.0328) time: 3.6191 data: 0.0030 max mem: 19788 +Epoch: [17] [1060/2138] eta: 1:05:21 lr: 2.979512933927609e-05 loss: 0.0328 (0.0328) time: 3.6186 data: 0.0028 max mem: 19788 +Epoch: [17] [1070/2138] eta: 1:04:45 lr: 2.9789555815467584e-05 loss: 0.0292 (0.0328) time: 3.6277 data: 0.0029 max mem: 19788 +Epoch: [17] [1080/2138] eta: 1:04:08 lr: 2.9783982175791414e-05 loss: 0.0295 (0.0328) time: 3.6292 data: 0.0031 max mem: 19788 +Epoch: [17] [1090/2138] eta: 1:03:32 lr: 2.9778408420221093e-05 loss: 0.0296 (0.0328) time: 3.6230 data: 0.0030 max mem: 19788 +Epoch: [17] [1100/2138] eta: 1:02:56 lr: 2.9772834548730105e-05 loss: 0.0324 (0.0328) time: 3.6449 data: 0.0030 max mem: 19788 +Epoch: [17] [1110/2138] eta: 1:02:19 lr: 2.976726056129192e-05 loss: 0.0309 (0.0328) time: 3.6462 data: 0.0029 max mem: 19788 +Epoch: [17] [1120/2138] eta: 1:01:43 lr: 2.976168645788e-05 loss: 0.0309 (0.0328) time: 3.6190 data: 0.0029 max mem: 19788 +Epoch: [17] [1130/2138] eta: 1:01:06 lr: 2.9756112238467802e-05 loss: 0.0324 (0.0328) time: 3.6176 data: 0.0029 max mem: 19788 +Epoch: [17] [1140/2138] eta: 1:00:30 lr: 2.9750537903028768e-05 loss: 0.0301 (0.0329) time: 3.6198 data: 0.0029 max mem: 19788 +Epoch: [17] [1150/2138] eta: 0:59:53 lr: 2.9744963451536323e-05 loss: 0.0287 (0.0328) time: 3.6179 data: 0.0030 max mem: 19788 +Epoch: [17] [1160/2138] eta: 0:59:17 lr: 2.9739388883963874e-05 loss: 0.0292 (0.0328) time: 3.6192 data: 0.0031 max mem: 19788 +Epoch: [17] [1170/2138] eta: 0:58:40 lr: 2.973381420028484e-05 loss: 0.0294 (0.0328) time: 3.6208 data: 0.0029 max mem: 19788 +Epoch: [17] [1180/2138] eta: 0:58:05 lr: 2.972823940047261e-05 loss: 0.0349 (0.0328) time: 3.6942 data: 0.0030 max mem: 19788 +Epoch: [17] [1190/2138] eta: 0:57:28 lr: 2.972266448450058e-05 loss: 0.0292 (0.0328) time: 3.6916 data: 0.0031 max mem: 19788 +Epoch: [17] [1200/2138] eta: 0:56:52 lr: 2.971708945234209e-05 loss: 0.0313 (0.0329) time: 3.6194 data: 0.0029 max mem: 19788 +Epoch: [17] [1210/2138] eta: 0:56:15 lr: 2.9711514303970516e-05 loss: 0.0323 (0.0329) time: 3.6241 data: 0.0029 max mem: 19788 +Epoch: [17] [1220/2138] eta: 0:55:39 lr: 2.9705939039359215e-05 loss: 0.0314 (0.0329) time: 3.6265 data: 0.0031 max mem: 19788 +Epoch: [17] [1230/2138] eta: 0:55:02 lr: 2.9700363658481506e-05 loss: 0.0298 (0.0329) time: 3.6282 data: 0.0030 max mem: 19788 +Epoch: [17] [1240/2138] eta: 0:54:26 lr: 2.9694788161310716e-05 loss: 0.0297 (0.0329) time: 3.6235 data: 0.0030 max mem: 19788 +Epoch: [17] [1250/2138] eta: 0:53:49 lr: 2.968921254782016e-05 loss: 0.0303 (0.0328) time: 3.6195 data: 0.0032 max mem: 19788 +Epoch: [17] [1260/2138] eta: 0:53:13 lr: 2.968363681798314e-05 loss: 0.0261 (0.0328) time: 3.6213 data: 0.0031 max mem: 19788 +Epoch: [17] [1270/2138] eta: 0:52:36 lr: 2.967806097177295e-05 loss: 0.0243 (0.0327) time: 3.6233 data: 0.0032 max mem: 19788 +Epoch: [17] [1280/2138] eta: 0:52:00 lr: 2.9672485009162843e-05 loss: 0.0243 (0.0327) time: 3.6224 data: 0.0033 max mem: 19788 +Epoch: [17] [1290/2138] eta: 0:51:24 lr: 2.9666908930126108e-05 loss: 0.0273 (0.0327) time: 3.6229 data: 0.0030 max mem: 19788 +Epoch: [17] [1300/2138] eta: 0:50:47 lr: 2.9661332734635993e-05 loss: 0.0344 (0.0327) time: 3.6252 data: 0.0027 max mem: 19788 +Epoch: [17] [1310/2138] eta: 0:50:11 lr: 2.9655756422665735e-05 loss: 0.0344 (0.0328) time: 3.6307 data: 0.0028 max mem: 19788 +Epoch: [17] [1320/2138] eta: 0:49:34 lr: 2.9650179994188566e-05 loss: 0.0332 (0.0328) time: 3.6272 data: 0.0028 max mem: 19788 +Epoch: [17] [1330/2138] eta: 0:48:58 lr: 2.9644603449177698e-05 loss: 0.0286 (0.0327) time: 3.6203 data: 0.0031 max mem: 19788 +Epoch: [17] [1340/2138] eta: 0:48:21 lr: 2.9639026787606355e-05 loss: 0.0286 (0.0328) time: 3.6211 data: 0.0032 max mem: 19788 +Epoch: [17] [1350/2138] eta: 0:47:45 lr: 2.963345000944772e-05 loss: 0.0372 (0.0328) time: 3.6209 data: 0.0031 max mem: 19788 +Epoch: [17] [1360/2138] eta: 0:47:08 lr: 2.962787311467497e-05 loss: 0.0389 (0.0329) time: 3.6210 data: 0.0030 max mem: 19788 +Epoch: [17] [1370/2138] eta: 0:46:32 lr: 2.9622296103261287e-05 loss: 0.0305 (0.0329) time: 3.6229 data: 0.0029 max mem: 19788 +Epoch: [17] [1380/2138] eta: 0:45:56 lr: 2.961671897517983e-05 loss: 0.0305 (0.0329) time: 3.6214 data: 0.0029 max mem: 19788 +Epoch: [17] [1390/2138] eta: 0:45:19 lr: 2.9611141730403735e-05 loss: 0.0327 (0.0329) time: 3.6203 data: 0.0029 max mem: 19788 +Epoch: [17] [1400/2138] eta: 0:44:43 lr: 2.960556436890614e-05 loss: 0.0294 (0.0329) time: 3.6233 data: 0.0031 max mem: 19788 +Epoch: [17] [1410/2138] eta: 0:44:06 lr: 2.9599986890660185e-05 loss: 0.0282 (0.0328) time: 3.6249 data: 0.0032 max mem: 19788 +Epoch: [17] [1420/2138] eta: 0:43:30 lr: 2.9594409295638975e-05 loss: 0.0275 (0.0328) time: 3.6213 data: 0.0030 max mem: 19788 +Epoch: [17] [1430/2138] eta: 0:42:53 lr: 2.9588831583815597e-05 loss: 0.0306 (0.0328) time: 3.6211 data: 0.0029 max mem: 19788 +Epoch: [17] [1440/2138] eta: 0:42:17 lr: 2.9583253755163147e-05 loss: 0.0277 (0.0328) time: 3.6296 data: 0.0030 max mem: 19788 +Epoch: [17] [1450/2138] eta: 0:41:41 lr: 2.9577675809654716e-05 loss: 0.0318 (0.0328) time: 3.6329 data: 0.0029 max mem: 19788 +Epoch: [17] [1460/2138] eta: 0:41:04 lr: 2.9572097747263348e-05 loss: 0.0341 (0.0328) time: 3.6260 data: 0.0029 max mem: 19788 +Epoch: [17] [1470/2138] eta: 0:40:28 lr: 2.9566519567962104e-05 loss: 0.0296 (0.0328) time: 3.6258 data: 0.0031 max mem: 19788 +Epoch: [17] [1480/2138] eta: 0:39:51 lr: 2.9560941271724028e-05 loss: 0.0313 (0.0328) time: 3.6303 data: 0.0031 max mem: 19788 +Epoch: [17] [1490/2138] eta: 0:39:15 lr: 2.9555362858522144e-05 loss: 0.0322 (0.0328) time: 3.6254 data: 0.0030 max mem: 19788 +Epoch: [17] [1500/2138] eta: 0:38:39 lr: 2.9549784328329482e-05 loss: 0.0305 (0.0328) time: 3.6224 data: 0.0029 max mem: 19788 +Epoch: [17] [1510/2138] eta: 0:38:02 lr: 2.9544205681119025e-05 loss: 0.0305 (0.0328) time: 3.6291 data: 0.0030 max mem: 19788 +Epoch: [17] [1520/2138] eta: 0:37:26 lr: 2.9538626916863783e-05 loss: 0.0283 (0.0328) time: 3.6359 data: 0.0031 max mem: 19788 +Epoch: [17] [1530/2138] eta: 0:36:50 lr: 2.9533048035536737e-05 loss: 0.0273 (0.0328) time: 3.6316 data: 0.0030 max mem: 19788 +Epoch: [17] [1540/2138] eta: 0:36:13 lr: 2.9527469037110855e-05 loss: 0.0312 (0.0328) time: 3.6294 data: 0.0029 max mem: 19788 +Epoch: [17] [1550/2138] eta: 0:35:37 lr: 2.9521889921559086e-05 loss: 0.0326 (0.0328) time: 3.6309 data: 0.0028 max mem: 19788 +Epoch: [17] [1560/2138] eta: 0:35:00 lr: 2.951631068885438e-05 loss: 0.0298 (0.0328) time: 3.6290 data: 0.0029 max mem: 19788 +Epoch: [17] [1570/2138] eta: 0:34:24 lr: 2.9510731338969687e-05 loss: 0.0298 (0.0328) time: 3.6228 data: 0.0032 max mem: 19788 +Epoch: [17] [1580/2138] eta: 0:33:48 lr: 2.950515187187791e-05 loss: 0.0272 (0.0328) time: 3.6304 data: 0.0032 max mem: 19788 +Epoch: [17] [1590/2138] eta: 0:33:11 lr: 2.9499572287551963e-05 loss: 0.0298 (0.0328) time: 3.6342 data: 0.0029 max mem: 19788 +Epoch: [17] [1600/2138] eta: 0:32:35 lr: 2.9493992585964746e-05 loss: 0.0358 (0.0328) time: 3.6226 data: 0.0031 max mem: 19788 +Epoch: [17] [1610/2138] eta: 0:31:59 lr: 2.948841276708915e-05 loss: 0.0299 (0.0328) time: 3.6243 data: 0.0031 max mem: 19788 +Epoch: [17] [1620/2138] eta: 0:31:22 lr: 2.9482832830898043e-05 loss: 0.0264 (0.0328) time: 3.6276 data: 0.0028 max mem: 19788 +Epoch: [17] [1630/2138] eta: 0:30:46 lr: 2.947725277736429e-05 loss: 0.0315 (0.0328) time: 3.6268 data: 0.0030 max mem: 19788 +Epoch: [17] [1640/2138] eta: 0:30:09 lr: 2.947167260646073e-05 loss: 0.0304 (0.0328) time: 3.6228 data: 0.0032 max mem: 19788 +Epoch: [17] [1650/2138] eta: 0:29:33 lr: 2.9466092318160232e-05 loss: 0.0282 (0.0328) time: 3.6267 data: 0.0030 max mem: 19788 +Epoch: [17] [1660/2138] eta: 0:28:57 lr: 2.9460511912435584e-05 loss: 0.0297 (0.0328) time: 3.6290 data: 0.0030 max mem: 19788 +Epoch: [17] [1670/2138] eta: 0:28:20 lr: 2.9454931389259615e-05 loss: 0.0291 (0.0328) time: 3.6257 data: 0.0032 max mem: 19788 +Epoch: [17] [1680/2138] eta: 0:27:44 lr: 2.9449350748605143e-05 loss: 0.0291 (0.0328) time: 3.6328 data: 0.0030 max mem: 19788 +Epoch: [17] [1690/2138] eta: 0:27:08 lr: 2.9443769990444942e-05 loss: 0.0299 (0.0328) time: 3.6321 data: 0.0029 max mem: 19788 +Epoch: [17] [1700/2138] eta: 0:26:31 lr: 2.9438189114751784e-05 loss: 0.0278 (0.0327) time: 3.6260 data: 0.0029 max mem: 19788 +Epoch: [17] [1710/2138] eta: 0:25:55 lr: 2.9432608121498445e-05 loss: 0.0301 (0.0327) time: 3.6245 data: 0.0031 max mem: 19788 +Epoch: [17] [1720/2138] eta: 0:25:19 lr: 2.942702701065769e-05 loss: 0.0302 (0.0328) time: 3.6274 data: 0.0031 max mem: 19788 +Epoch: [17] [1730/2138] eta: 0:24:42 lr: 2.942144578220224e-05 loss: 0.0328 (0.0328) time: 3.6293 data: 0.0029 max mem: 19788 +Epoch: [17] [1740/2138] eta: 0:24:06 lr: 2.9415864436104836e-05 loss: 0.0306 (0.0328) time: 3.6290 data: 0.0029 max mem: 19788 +Epoch: [17] [1750/2138] eta: 0:23:30 lr: 2.9410282972338186e-05 loss: 0.0306 (0.0328) time: 3.6339 data: 0.0029 max mem: 19788 +Epoch: [17] [1760/2138] eta: 0:22:53 lr: 2.9404701390875018e-05 loss: 0.0357 (0.0328) time: 3.6333 data: 0.0030 max mem: 19788 +Epoch: [17] [1770/2138] eta: 0:22:17 lr: 2.9399119691688006e-05 loss: 0.0325 (0.0328) time: 3.6277 data: 0.0029 max mem: 19788 +Epoch: [17] [1780/2138] eta: 0:21:41 lr: 2.9393537874749834e-05 loss: 0.0304 (0.0328) time: 3.6276 data: 0.0028 max mem: 19788 +Epoch: [17] [1790/2138] eta: 0:21:04 lr: 2.9387955940033168e-05 loss: 0.0306 (0.0329) time: 3.6319 data: 0.0028 max mem: 19788 +Epoch: [17] [1800/2138] eta: 0:20:28 lr: 2.9382373887510685e-05 loss: 0.0333 (0.0329) time: 3.6313 data: 0.0029 max mem: 19788 +Epoch: [17] [1810/2138] eta: 0:19:51 lr: 2.9376791717155012e-05 loss: 0.0328 (0.0329) time: 3.6252 data: 0.0031 max mem: 19788 +Epoch: [17] [1820/2138] eta: 0:19:15 lr: 2.9371209428938784e-05 loss: 0.0304 (0.0329) time: 3.6352 data: 0.0032 max mem: 19788 +Epoch: [17] [1830/2138] eta: 0:18:39 lr: 2.9365627022834625e-05 loss: 0.0307 (0.0329) time: 3.6358 data: 0.0029 max mem: 19788 +Epoch: [17] [1840/2138] eta: 0:18:02 lr: 2.936004449881514e-05 loss: 0.0311 (0.0330) time: 3.6233 data: 0.0030 max mem: 19788 +Epoch: [17] [1850/2138] eta: 0:17:26 lr: 2.9354461856852944e-05 loss: 0.0331 (0.0330) time: 3.6240 data: 0.0031 max mem: 19788 +Epoch: [17] [1860/2138] eta: 0:16:50 lr: 2.934887909692059e-05 loss: 0.0304 (0.0330) time: 3.6323 data: 0.0030 max mem: 19788 +Epoch: [17] [1870/2138] eta: 0:16:13 lr: 2.9343296218990675e-05 loss: 0.0288 (0.0330) time: 3.6307 data: 0.0029 max mem: 19788 +Epoch: [17] [1880/2138] eta: 0:15:37 lr: 2.933771322303575e-05 loss: 0.0298 (0.0330) time: 3.6260 data: 0.0031 max mem: 19788 +Epoch: [17] [1890/2138] eta: 0:15:01 lr: 2.9332130109028372e-05 loss: 0.0307 (0.0330) time: 3.6329 data: 0.0035 max mem: 19788 +Epoch: [17] [1900/2138] eta: 0:14:24 lr: 2.9326546876941058e-05 loss: 0.0294 (0.0329) time: 3.6317 data: 0.0036 max mem: 19788 +Epoch: [17] [1910/2138] eta: 0:13:48 lr: 2.9320963526746342e-05 loss: 0.0296 (0.0329) time: 3.6246 data: 0.0031 max mem: 19788 +Epoch: [17] [1920/2138] eta: 0:13:12 lr: 2.931538005841674e-05 loss: 0.0322 (0.0330) time: 3.6266 data: 0.0030 max mem: 19788 +Epoch: [17] [1930/2138] eta: 0:12:35 lr: 2.9309796471924756e-05 loss: 0.0312 (0.0330) time: 3.6317 data: 0.0031 max mem: 19788 +Epoch: [17] [1940/2138] eta: 0:11:59 lr: 2.9304212767242856e-05 loss: 0.0312 (0.0330) time: 3.6289 data: 0.0030 max mem: 19788 +Epoch: [17] [1950/2138] eta: 0:11:23 lr: 2.9298628944343525e-05 loss: 0.0305 (0.0330) time: 3.6262 data: 0.0029 max mem: 19788 +Epoch: [17] [1960/2138] eta: 0:10:46 lr: 2.9293045003199242e-05 loss: 0.0309 (0.0330) time: 3.6287 data: 0.0028 max mem: 19788 +Epoch: [17] [1970/2138] eta: 0:10:10 lr: 2.928746094378243e-05 loss: 0.0309 (0.0330) time: 3.6239 data: 0.0030 max mem: 19788 +Epoch: [17] [1980/2138] eta: 0:09:34 lr: 2.928187676606554e-05 loss: 0.0279 (0.0330) time: 3.6225 data: 0.0030 max mem: 19788 +Epoch: [17] [1990/2138] eta: 0:08:57 lr: 2.9276292470021006e-05 loss: 0.0266 (0.0330) time: 3.6343 data: 0.0029 max mem: 19788 +Epoch: [17] [2000/2138] eta: 0:08:21 lr: 2.9270708055621228e-05 loss: 0.0302 (0.0330) time: 3.6348 data: 0.0029 max mem: 19788 +Epoch: [17] [2010/2138] eta: 0:07:45 lr: 2.9265123522838607e-05 loss: 0.0336 (0.0330) time: 3.6292 data: 0.0029 max mem: 19788 +Epoch: [17] [2020/2138] eta: 0:07:08 lr: 2.9259538871645537e-05 loss: 0.0345 (0.0330) time: 3.6294 data: 0.0028 max mem: 19788 +Epoch: [17] [2030/2138] eta: 0:06:32 lr: 2.9253954102014397e-05 loss: 0.0330 (0.0330) time: 3.6337 data: 0.0029 max mem: 19788 +Epoch: [17] [2040/2138] eta: 0:05:56 lr: 2.924836921391755e-05 loss: 0.0325 (0.0330) time: 3.6332 data: 0.0030 max mem: 19788 +Epoch: [17] [2050/2138] eta: 0:05:19 lr: 2.924278420732734e-05 loss: 0.0327 (0.0331) time: 3.6260 data: 0.0029 max mem: 19788 +Epoch: [17] [2060/2138] eta: 0:04:43 lr: 2.9237199082216117e-05 loss: 0.0327 (0.0331) time: 3.6414 data: 0.0027 max mem: 19788 +Epoch: [17] [2070/2138] eta: 0:04:07 lr: 2.9231613838556203e-05 loss: 0.0312 (0.0331) time: 3.7414 data: 0.0028 max mem: 19788 +Epoch: [17] [2080/2138] eta: 0:03:30 lr: 2.9226028476319916e-05 loss: 0.0310 (0.0331) time: 3.7378 data: 0.0030 max mem: 19788 +Epoch: [17] [2090/2138] eta: 0:02:54 lr: 2.922044299547955e-05 loss: 0.0306 (0.0331) time: 3.6378 data: 0.0030 max mem: 19788 +Epoch: [17] [2100/2138] eta: 0:02:18 lr: 2.921485739600741e-05 loss: 0.0296 (0.0330) time: 3.6249 data: 0.0030 max mem: 19788 +Epoch: [17] [2110/2138] eta: 0:01:41 lr: 2.9209271677875767e-05 loss: 0.0311 (0.0331) time: 3.6294 data: 0.0029 max mem: 19788 +Epoch: [17] [2120/2138] eta: 0:01:05 lr: 2.920368584105688e-05 loss: 0.0370 (0.0331) time: 3.6271 data: 0.0028 max mem: 19788 +Epoch: [17] [2130/2138] eta: 0:00:29 lr: 2.9198099885523007e-05 loss: 0.0343 (0.0332) time: 3.6136 data: 0.0027 max mem: 19788 +Epoch: [17] Total time: 2:09:30 +Test: [ 0/21770] eta: 17:17:44 time: 2.8601 data: 2.7724 max mem: 19788 +Test: [ 100/21770] eta: 0:36:12 time: 0.0711 data: 0.0022 max mem: 19788 +Test: [ 200/21770] eta: 0:30:24 time: 0.0682 data: 0.0021 max mem: 19788 +Test: [ 300/21770] eta: 0:28:35 time: 0.0653 data: 0.0019 max mem: 19788 +Test: [ 400/21770] eta: 0:27:08 time: 0.0767 data: 0.0020 max mem: 19788 +Test: [ 500/21770] eta: 0:26:39 time: 0.0725 data: 0.0022 max mem: 19788 +Test: [ 600/21770] eta: 0:26:13 time: 0.0704 data: 0.0021 max mem: 19788 +Test: [ 700/21770] eta: 0:25:37 time: 0.0603 data: 0.0019 max mem: 19788 +Test: [ 800/21770] eta: 0:25:11 time: 0.0632 data: 0.0019 max mem: 19788 +Test: [ 900/21770] eta: 0:24:46 time: 0.0667 data: 0.0019 max mem: 19788 +Test: [ 1000/21770] eta: 0:24:27 time: 0.0736 data: 0.0023 max mem: 19788 +Test: [ 1100/21770] eta: 0:24:06 time: 0.0627 data: 0.0019 max mem: 19788 +Test: [ 1200/21770] eta: 0:24:00 time: 0.0682 data: 0.0021 max mem: 19788 +Test: [ 1300/21770] eta: 0:23:45 time: 0.0656 data: 0.0019 max mem: 19788 +Test: [ 1400/21770] eta: 0:23:31 time: 0.0774 data: 0.0023 max mem: 19788 +Test: [ 1500/21770] eta: 0:23:19 time: 0.0689 data: 0.0019 max mem: 19788 +Test: [ 1600/21770] eta: 0:23:07 time: 0.0608 data: 0.0018 max mem: 19788 +Test: [ 1700/21770] eta: 0:22:51 time: 0.0614 data: 0.0019 max mem: 19788 +Test: [ 1800/21770] eta: 0:22:44 time: 0.0666 data: 0.0020 max mem: 19788 +Test: [ 1900/21770] eta: 0:22:30 time: 0.0609 data: 0.0022 max mem: 19788 +Test: [ 2000/21770] eta: 0:22:21 time: 0.0685 data: 0.0019 max mem: 19788 +Test: [ 2100/21770] eta: 0:22:13 time: 0.0634 data: 0.0018 max mem: 19788 +Test: [ 2200/21770] eta: 0:22:03 time: 0.0661 data: 0.0021 max mem: 19788 +Test: [ 2300/21770] eta: 0:21:54 time: 0.0672 data: 0.0019 max mem: 19788 +Test: [ 2400/21770] eta: 0:21:54 time: 0.0668 data: 0.0019 max mem: 19788 +Test: [ 2500/21770] eta: 0:21:50 time: 0.0685 data: 0.0021 max mem: 19788 +Test: [ 2600/21770] eta: 0:21:44 time: 0.0647 data: 0.0019 max mem: 19788 +Test: [ 2700/21770] eta: 0:21:35 time: 0.0727 data: 0.0022 max mem: 19788 +Test: [ 2800/21770] eta: 0:21:28 time: 0.0643 data: 0.0017 max mem: 19788 +Test: [ 2900/21770] eta: 0:21:23 time: 0.0696 data: 0.0019 max mem: 19788 +Test: [ 3000/21770] eta: 0:21:17 time: 0.0681 data: 0.0019 max mem: 19788 +Test: [ 3100/21770] eta: 0:21:08 time: 0.0645 data: 0.0018 max mem: 19788 +Test: [ 3200/21770] eta: 0:21:05 time: 0.0727 data: 0.0020 max mem: 19788 +Test: [ 3300/21770] eta: 0:20:57 time: 0.0797 data: 0.0024 max mem: 19788 +Test: [ 3400/21770] eta: 0:20:53 time: 0.0638 data: 0.0018 max mem: 19788 +Test: [ 3500/21770] eta: 0:20:49 time: 0.0677 data: 0.0019 max mem: 19788 +Test: [ 3600/21770] eta: 0:20:40 time: 0.0635 data: 0.0019 max mem: 19788 +Test: [ 3700/21770] eta: 0:20:34 time: 0.0755 data: 0.0022 max mem: 19788 +Test: [ 3800/21770] eta: 0:20:31 time: 0.0824 data: 0.0024 max mem: 19788 +Test: [ 3900/21770] eta: 0:20:26 time: 0.0672 data: 0.0020 max mem: 19788 +Test: [ 4000/21770] eta: 0:20:20 time: 0.0674 data: 0.0019 max mem: 19788 +Test: [ 4100/21770] eta: 0:20:15 time: 0.0762 data: 0.0023 max mem: 19788 +Test: [ 4200/21770] eta: 0:20:07 time: 0.0620 data: 0.0016 max mem: 19788 +Test: [ 4300/21770] eta: 0:20:00 time: 0.0727 data: 0.0022 max mem: 19788 +Test: [ 4400/21770] eta: 0:19:52 time: 0.0657 data: 0.0019 max mem: 19788 +Test: [ 4500/21770] eta: 0:19:44 time: 0.0626 data: 0.0021 max mem: 19788 +Test: [ 4600/21770] eta: 0:19:36 time: 0.0644 data: 0.0020 max mem: 19788 +Test: [ 4700/21770] eta: 0:19:30 time: 0.0640 data: 0.0019 max mem: 19788 +Test: [ 4800/21770] eta: 0:19:24 time: 0.0656 data: 0.0018 max mem: 19788 +Test: [ 4900/21770] eta: 0:19:18 time: 0.0674 data: 0.0017 max mem: 19788 +Test: [ 5000/21770] eta: 0:19:11 time: 0.0686 data: 0.0021 max mem: 19788 +Test: [ 5100/21770] eta: 0:19:06 time: 0.0617 data: 0.0019 max mem: 19788 +Test: [ 5200/21770] eta: 0:18:58 time: 0.0707 data: 0.0019 max mem: 19788 +Test: [ 5300/21770] eta: 0:18:51 time: 0.0618 data: 0.0018 max mem: 19788 +Test: [ 5400/21770] eta: 0:18:44 time: 0.0666 data: 0.0018 max mem: 19788 +Test: [ 5500/21770] eta: 0:18:36 time: 0.0628 data: 0.0019 max mem: 19788 +Test: [ 5600/21770] eta: 0:18:29 time: 0.0793 data: 0.0022 max mem: 19788 +Test: [ 5700/21770] eta: 0:18:24 time: 0.0675 data: 0.0020 max mem: 19788 +Test: [ 5800/21770] eta: 0:18:17 time: 0.0686 data: 0.0019 max mem: 19788 +Test: [ 5900/21770] eta: 0:18:10 time: 0.0793 data: 0.0024 max mem: 19788 +Test: [ 6000/21770] eta: 0:18:02 time: 0.0615 data: 0.0019 max mem: 19788 +Test: [ 6100/21770] eta: 0:17:55 time: 0.0651 data: 0.0018 max mem: 19788 +Test: [ 6200/21770] eta: 0:17:48 time: 0.0764 data: 0.0023 max mem: 19788 +Test: [ 6300/21770] eta: 0:17:42 time: 0.0709 data: 0.0024 max mem: 19788 +Test: [ 6400/21770] eta: 0:17:35 time: 0.0639 data: 0.0020 max mem: 19788 +Test: [ 6500/21770] eta: 0:17:28 time: 0.0638 data: 0.0018 max mem: 19788 +Test: [ 6600/21770] eta: 0:17:22 time: 0.0754 data: 0.0021 max mem: 19788 +Test: [ 6700/21770] eta: 0:17:14 time: 0.0621 data: 0.0019 max mem: 19788 +Test: [ 6800/21770] eta: 0:17:07 time: 0.0776 data: 0.0022 max mem: 19788 +Test: [ 6900/21770] eta: 0:17:00 time: 0.0654 data: 0.0022 max mem: 19788 +Test: [ 7000/21770] eta: 0:16:53 time: 0.0796 data: 0.0021 max mem: 19788 +Test: [ 7100/21770] eta: 0:16:46 time: 0.0679 data: 0.0020 max mem: 19788 +Test: [ 7200/21770] eta: 0:16:40 time: 0.0639 data: 0.0018 max mem: 19788 +Test: [ 7300/21770] eta: 0:16:32 time: 0.0766 data: 0.0024 max mem: 19788 +Test: [ 7400/21770] eta: 0:16:27 time: 0.0809 data: 0.0023 max mem: 19788 +Test: [ 7500/21770] eta: 0:16:20 time: 0.0665 data: 0.0019 max mem: 19788 +Test: [ 7600/21770] eta: 0:16:12 time: 0.0649 data: 0.0019 max mem: 19788 +Test: [ 7700/21770] eta: 0:16:06 time: 0.0653 data: 0.0020 max mem: 19788 +Test: [ 7800/21770] eta: 0:15:59 time: 0.0653 data: 0.0021 max mem: 19788 +Test: [ 7900/21770] eta: 0:15:51 time: 0.0629 data: 0.0021 max mem: 19788 +Test: [ 8000/21770] eta: 0:15:45 time: 0.0605 data: 0.0019 max mem: 19788 +Test: [ 8100/21770] eta: 0:15:37 time: 0.0612 data: 0.0017 max mem: 19788 +Test: [ 8200/21770] eta: 0:15:31 time: 0.0755 data: 0.0024 max mem: 19788 +Test: [ 8300/21770] eta: 0:15:24 time: 0.0747 data: 0.0023 max mem: 19788 +Test: [ 8400/21770] eta: 0:15:17 time: 0.0690 data: 0.0019 max mem: 19788 +Test: [ 8500/21770] eta: 0:15:10 time: 0.0654 data: 0.0019 max mem: 19788 +Test: [ 8600/21770] eta: 0:15:03 time: 0.0681 data: 0.0018 max mem: 19788 +Test: [ 8700/21770] eta: 0:14:56 time: 0.0629 data: 0.0018 max mem: 19788 +Test: [ 8800/21770] eta: 0:14:48 time: 0.0617 data: 0.0020 max mem: 19788 +Test: [ 8900/21770] eta: 0:14:41 time: 0.0636 data: 0.0020 max mem: 19788 +Test: [ 9000/21770] eta: 0:14:34 time: 0.0706 data: 0.0020 max mem: 19788 +Test: [ 9100/21770] eta: 0:14:27 time: 0.0627 data: 0.0018 max mem: 19788 +Test: [ 9200/21770] eta: 0:14:20 time: 0.0622 data: 0.0019 max mem: 19788 +Test: [ 9300/21770] eta: 0:14:13 time: 0.0629 data: 0.0020 max mem: 19788 +Test: [ 9400/21770] eta: 0:14:06 time: 0.0610 data: 0.0018 max mem: 19788 +Test: [ 9500/21770] eta: 0:14:00 time: 0.0624 data: 0.0017 max mem: 19788 +Test: [ 9600/21770] eta: 0:13:53 time: 0.0686 data: 0.0022 max mem: 19788 +Test: [ 9700/21770] eta: 0:13:46 time: 0.0618 data: 0.0020 max mem: 19788 +Test: [ 9800/21770] eta: 0:13:40 time: 0.0653 data: 0.0020 max mem: 19788 +Test: [ 9900/21770] eta: 0:13:33 time: 0.0660 data: 0.0021 max mem: 19788 +Test: [10000/21770] eta: 0:13:27 time: 0.0692 data: 0.0018 max mem: 19788 +Test: [10100/21770] eta: 0:13:20 time: 0.0743 data: 0.0021 max mem: 19788 +Test: [10200/21770] eta: 0:13:13 time: 0.0663 data: 0.0019 max mem: 19788 +Test: [10300/21770] eta: 0:13:06 time: 0.0635 data: 0.0018 max mem: 19788 +Test: [10400/21770] eta: 0:12:59 time: 0.0761 data: 0.0022 max mem: 19788 +Test: [10500/21770] eta: 0:12:52 time: 0.0798 data: 0.0022 max mem: 19788 +Test: [10600/21770] eta: 0:12:46 time: 0.0659 data: 0.0019 max mem: 19788 +Test: [10700/21770] eta: 0:12:39 time: 0.0693 data: 0.0019 max mem: 19788 +Test: [10800/21770] eta: 0:12:32 time: 0.0676 data: 0.0018 max mem: 19788 +Test: [10900/21770] eta: 0:12:25 time: 0.0701 data: 0.0020 max mem: 19788 +Test: [11000/21770] eta: 0:12:18 time: 0.0612 data: 0.0017 max mem: 19788 +Test: [11100/21770] eta: 0:12:11 time: 0.0647 data: 0.0019 max mem: 19788 +Test: [11200/21770] eta: 0:12:05 time: 0.0648 data: 0.0017 max mem: 19788 +Test: [11300/21770] eta: 0:11:58 time: 0.0731 data: 0.0021 max mem: 19788 +Test: [11400/21770] eta: 0:11:51 time: 0.0629 data: 0.0018 max mem: 19788 +Test: [11500/21770] eta: 0:11:44 time: 0.0632 data: 0.0019 max mem: 19788 +Test: [11600/21770] eta: 0:11:37 time: 0.0622 data: 0.0017 max mem: 19788 +Test: [11700/21770] eta: 0:11:30 time: 0.0628 data: 0.0018 max mem: 19788 +Test: [11800/21770] eta: 0:11:23 time: 0.0727 data: 0.0022 max mem: 19788 +Test: [11900/21770] eta: 0:11:15 time: 0.0626 data: 0.0021 max mem: 19788 +Test: [12000/21770] eta: 0:11:09 time: 0.0812 data: 0.0024 max mem: 19788 +Test: [12100/21770] eta: 0:11:02 time: 0.0674 data: 0.0018 max mem: 19788 +Test: [12200/21770] eta: 0:10:56 time: 0.0673 data: 0.0020 max mem: 19788 +Test: [12300/21770] eta: 0:10:49 time: 0.0640 data: 0.0019 max mem: 19788 +Test: [12400/21770] eta: 0:10:42 time: 0.0620 data: 0.0017 max mem: 19788 +Test: [12500/21770] eta: 0:10:35 time: 0.0601 data: 0.0017 max mem: 19788 +Test: [12600/21770] eta: 0:10:28 time: 0.0677 data: 0.0020 max mem: 19788 +Test: [12700/21770] eta: 0:10:21 time: 0.0728 data: 0.0022 max mem: 19788 +Test: [12800/21770] eta: 0:10:15 time: 0.0621 data: 0.0017 max mem: 19788 +Test: [12900/21770] eta: 0:10:08 time: 0.0693 data: 0.0020 max mem: 19788 +Test: [13000/21770] eta: 0:10:01 time: 0.0664 data: 0.0022 max mem: 19788 +Test: [13100/21770] eta: 0:09:54 time: 0.0779 data: 0.0024 max mem: 19788 +Test: [13200/21770] eta: 0:09:47 time: 0.0657 data: 0.0021 max mem: 19788 +Test: [13300/21770] eta: 0:09:41 time: 0.0803 data: 0.0025 max mem: 19788 +Test: [13400/21770] eta: 0:09:34 time: 0.0619 data: 0.0020 max mem: 19788 +Test: [13500/21770] eta: 0:09:27 time: 0.0731 data: 0.0022 max mem: 19788 +Test: [13600/21770] eta: 0:09:21 time: 0.0819 data: 0.0019 max mem: 19788 +Test: [13700/21770] eta: 0:09:14 time: 0.0719 data: 0.0019 max mem: 19788 +Test: [13800/21770] eta: 0:09:07 time: 0.0642 data: 0.0019 max mem: 19788 +Test: [13900/21770] eta: 0:09:01 time: 0.0766 data: 0.0023 max mem: 19788 +Test: [14000/21770] eta: 0:08:54 time: 0.0643 data: 0.0018 max mem: 19788 +Test: [14100/21770] eta: 0:08:47 time: 0.0657 data: 0.0018 max mem: 19788 +Test: [14200/21770] eta: 0:08:40 time: 0.0717 data: 0.0021 max mem: 19788 +Test: [14300/21770] eta: 0:08:34 time: 0.0706 data: 0.0022 max mem: 19788 +Test: [14400/21770] eta: 0:08:26 time: 0.0654 data: 0.0018 max mem: 19788 +Test: [14500/21770] eta: 0:08:20 time: 0.0630 data: 0.0021 max mem: 19788 +Test: [14600/21770] eta: 0:08:13 time: 0.0596 data: 0.0017 max mem: 19788 +Test: [14700/21770] eta: 0:08:06 time: 0.0678 data: 0.0019 max mem: 19788 +Test: [14800/21770] eta: 0:07:59 time: 0.0756 data: 0.0022 max mem: 19788 +Test: [14900/21770] eta: 0:07:52 time: 0.0622 data: 0.0018 max mem: 19788 +Test: [15000/21770] eta: 0:07:45 time: 0.0632 data: 0.0019 max mem: 19788 +Test: [15100/21770] eta: 0:07:38 time: 0.0617 data: 0.0019 max mem: 19788 +Test: [15200/21770] eta: 0:07:31 time: 0.0726 data: 0.0022 max mem: 19788 +Test: [15300/21770] eta: 0:07:24 time: 0.0649 data: 0.0017 max mem: 19788 +Test: [15400/21770] eta: 0:07:17 time: 0.0651 data: 0.0019 max mem: 19788 +Test: [15500/21770] eta: 0:07:10 time: 0.0681 data: 0.0020 max mem: 19788 +Test: [15600/21770] eta: 0:07:03 time: 0.0786 data: 0.0023 max mem: 19788 +Test: [15700/21770] eta: 0:06:56 time: 0.0728 data: 0.0021 max mem: 19788 +Test: [15800/21770] eta: 0:06:50 time: 0.0792 data: 0.0021 max mem: 19788 +Test: [15900/21770] eta: 0:06:43 time: 0.0615 data: 0.0019 max mem: 19788 +Test: [16000/21770] eta: 0:06:36 time: 0.0656 data: 0.0022 max mem: 19788 +Test: [16100/21770] eta: 0:06:29 time: 0.0698 data: 0.0019 max mem: 19788 +Test: [16200/21770] eta: 0:06:22 time: 0.0614 data: 0.0018 max mem: 19788 +Test: [16300/21770] eta: 0:06:15 time: 0.0665 data: 0.0022 max mem: 19788 +Test: [16400/21770] eta: 0:06:08 time: 0.0669 data: 0.0021 max mem: 19788 +Test: [16500/21770] eta: 0:06:01 time: 0.0636 data: 0.0019 max mem: 19788 +Test: [16600/21770] eta: 0:05:54 time: 0.0636 data: 0.0020 max mem: 19788 +Test: [16700/21770] eta: 0:05:48 time: 0.0641 data: 0.0018 max mem: 19788 +Test: [16800/21770] eta: 0:05:41 time: 0.0586 data: 0.0018 max mem: 19788 +Test: [16900/21770] eta: 0:05:34 time: 0.0638 data: 0.0018 max mem: 19788 +Test: [17000/21770] eta: 0:05:27 time: 0.0737 data: 0.0022 max mem: 19788 +Test: [17100/21770] eta: 0:05:20 time: 0.0729 data: 0.0020 max mem: 19788 +Test: [17200/21770] eta: 0:05:13 time: 0.0710 data: 0.0019 max mem: 19788 +Test: [17300/21770] eta: 0:05:06 time: 0.0636 data: 0.0019 max mem: 19788 +Test: [17400/21770] eta: 0:04:59 time: 0.0618 data: 0.0019 max mem: 19788 +Test: [17500/21770] eta: 0:04:52 time: 0.0617 data: 0.0020 max mem: 19788 +Test: [17600/21770] eta: 0:04:46 time: 0.0672 data: 0.0021 max mem: 19788 +Test: [17700/21770] eta: 0:04:39 time: 0.0627 data: 0.0017 max mem: 19788 +Test: [17800/21770] eta: 0:04:32 time: 0.0638 data: 0.0017 max mem: 19788 +Test: [17900/21770] eta: 0:04:25 time: 0.0773 data: 0.0021 max mem: 19788 +Test: [18000/21770] eta: 0:04:18 time: 0.0634 data: 0.0019 max mem: 19788 +Test: [18100/21770] eta: 0:04:11 time: 0.0671 data: 0.0020 max mem: 19788 +Test: [18200/21770] eta: 0:04:04 time: 0.0741 data: 0.0023 max mem: 19788 +Test: [18300/21770] eta: 0:03:58 time: 0.0677 data: 0.0021 max mem: 19788 +Test: [18400/21770] eta: 0:03:51 time: 0.0749 data: 0.0022 max mem: 19788 +Test: [18500/21770] eta: 0:03:44 time: 0.0675 data: 0.0019 max mem: 19788 +Test: [18600/21770] eta: 0:03:37 time: 0.0646 data: 0.0019 max mem: 19788 +Test: [18700/21770] eta: 0:03:30 time: 0.0676 data: 0.0021 max mem: 19788 +Test: [18800/21770] eta: 0:03:23 time: 0.0709 data: 0.0020 max mem: 19788 +Test: [18900/21770] eta: 0:03:16 time: 0.0724 data: 0.0020 max mem: 19788 +Test: [19000/21770] eta: 0:03:09 time: 0.0685 data: 0.0020 max mem: 19788 +Test: [19100/21770] eta: 0:03:03 time: 0.0648 data: 0.0017 max mem: 19788 +Test: [19200/21770] eta: 0:02:56 time: 0.0689 data: 0.0020 max mem: 19788 +Test: [19300/21770] eta: 0:02:49 time: 0.0621 data: 0.0021 max mem: 19788 +Test: [19400/21770] eta: 0:02:42 time: 0.0623 data: 0.0018 max mem: 19788 +Test: [19500/21770] eta: 0:02:35 time: 0.0768 data: 0.0024 max mem: 19788 +Test: [19600/21770] eta: 0:02:28 time: 0.0817 data: 0.0024 max mem: 19788 +Test: [19700/21770] eta: 0:02:22 time: 0.0625 data: 0.0018 max mem: 19788 +Test: [19800/21770] eta: 0:02:15 time: 0.0716 data: 0.0021 max mem: 19788 +Test: [19900/21770] eta: 0:02:08 time: 0.0639 data: 0.0018 max mem: 19788 +Test: [20000/21770] eta: 0:02:01 time: 0.0740 data: 0.0022 max mem: 19788 +Test: [20100/21770] eta: 0:01:54 time: 0.0597 data: 0.0018 max mem: 19788 +Test: [20200/21770] eta: 0:01:47 time: 0.0705 data: 0.0020 max mem: 19788 +Test: [20300/21770] eta: 0:01:40 time: 0.0621 data: 0.0019 max mem: 19788 +Test: [20400/21770] eta: 0:01:33 time: 0.0624 data: 0.0020 max mem: 19788 +Test: [20500/21770] eta: 0:01:27 time: 0.0624 data: 0.0019 max mem: 19788 +Test: [20600/21770] eta: 0:01:20 time: 0.0602 data: 0.0018 max mem: 19788 +Test: [20700/21770] eta: 0:01:13 time: 0.0624 data: 0.0018 max mem: 19788 +Test: [20800/21770] eta: 0:01:06 time: 0.0615 data: 0.0020 max mem: 19788 +Test: [20900/21770] eta: 0:00:59 time: 0.0818 data: 0.0025 max mem: 19788 +Test: [21000/21770] eta: 0:00:52 time: 0.0634 data: 0.0020 max mem: 19788 +Test: [21100/21770] eta: 0:00:45 time: 0.0766 data: 0.0022 max mem: 19788 +Test: [21200/21770] eta: 0:00:39 time: 0.0786 data: 0.0022 max mem: 19788 +Test: [21300/21770] eta: 0:00:32 time: 0.0626 data: 0.0018 max mem: 19788 +Test: [21400/21770] eta: 0:00:25 time: 0.0648 data: 0.0019 max mem: 19788 +Test: [21500/21770] eta: 0:00:18 time: 0.0828 data: 0.0020 max mem: 19788 +Test: [21600/21770] eta: 0:00:11 time: 0.0611 data: 0.0016 max mem: 19788 +Test: [21700/21770] eta: 0:00:04 time: 0.0553 data: 0.0016 max mem: 19788 +Test: Total time: 0:24:55 +Final results: +Mean IoU is 62.78 + + precision@0.5 = 69.46 + precision@0.6 = 64.24 + precision@0.7 = 57.36 + precision@0.8 = 46.77 + precision@0.9 = 23.35 + overall IoU = 63.35 + mean IoU = 62.78 + +Mean accuracy for one-to-zero sample is 81.44 + +Average object IoU 0.6277948365071737 +Overall IoU 63.34967041015625 +Epoch: [18] [ 0/2138] eta: 3:14:01 lr: 2.919363103560247e-05 loss: 0.0313 (0.0313) time: 5.4450 data: 1.4280 max mem: 19788 +Epoch: [18] [ 10/2138] eta: 2:14:57 lr: 2.918804486631166e-05 loss: 0.0249 (0.0292) time: 3.8051 data: 0.1317 max mem: 19788 +Epoch: [18] [ 20/2138] eta: 2:11:23 lr: 2.9182458578228104e-05 loss: 0.0250 (0.0283) time: 3.6358 data: 0.0020 max mem: 19788 +Epoch: [18] [ 30/2138] eta: 2:09:44 lr: 2.917687217132402e-05 loss: 0.0263 (0.0279) time: 3.6314 data: 0.0024 max mem: 19788 +Epoch: [18] [ 40/2138] eta: 2:08:35 lr: 2.9171285645571594e-05 loss: 0.0291 (0.0292) time: 3.6313 data: 0.0032 max mem: 19788 +Epoch: [18] [ 50/2138] eta: 2:07:40 lr: 2.9165699000942997e-05 loss: 0.0322 (0.0312) time: 3.6312 data: 0.0033 max mem: 19788 +Epoch: [18] [ 60/2138] eta: 2:06:49 lr: 2.9160112237410408e-05 loss: 0.0290 (0.0305) time: 3.6291 data: 0.0031 max mem: 19788 +Epoch: [18] [ 70/2138] eta: 2:06:05 lr: 2.9154525354945987e-05 loss: 0.0260 (0.0299) time: 3.6316 data: 0.0029 max mem: 19788 +Epoch: [18] [ 80/2138] eta: 2:05:20 lr: 2.9148938353521878e-05 loss: 0.0272 (0.0300) time: 3.6323 data: 0.0028 max mem: 19788 +Epoch: [18] [ 90/2138] eta: 2:04:38 lr: 2.9143351233110195e-05 loss: 0.0293 (0.0305) time: 3.6282 data: 0.0029 max mem: 19788 +Epoch: [18] [ 100/2138] eta: 2:03:53 lr: 2.9137763993683075e-05 loss: 0.0304 (0.0308) time: 3.6188 data: 0.0029 max mem: 19788 +Epoch: [18] [ 110/2138] eta: 2:03:12 lr: 2.9132176635212623e-05 loss: 0.0311 (0.0308) time: 3.6153 data: 0.0029 max mem: 19788 +Epoch: [18] [ 120/2138] eta: 2:02:31 lr: 2.9126589157670924e-05 loss: 0.0313 (0.0311) time: 3.6209 data: 0.0031 max mem: 19788 +Epoch: [18] [ 130/2138] eta: 2:01:51 lr: 2.9121001561030057e-05 loss: 0.0298 (0.0315) time: 3.6194 data: 0.0030 max mem: 19788 +Epoch: [18] [ 140/2138] eta: 2:01:11 lr: 2.9115413845262108e-05 loss: 0.0268 (0.0316) time: 3.6187 data: 0.0029 max mem: 19788 +Epoch: [18] [ 150/2138] eta: 2:00:32 lr: 2.910982601033912e-05 loss: 0.0267 (0.0314) time: 3.6172 data: 0.0031 max mem: 19788 +Epoch: [18] [ 160/2138] eta: 1:59:54 lr: 2.910423805623314e-05 loss: 0.0298 (0.0319) time: 3.6211 data: 0.0031 max mem: 19788 +Epoch: [18] [ 170/2138] eta: 1:59:16 lr: 2.90986499829162e-05 loss: 0.0326 (0.0320) time: 3.6252 data: 0.0031 max mem: 19788 +Epoch: [18] [ 180/2138] eta: 1:58:38 lr: 2.9093061790360315e-05 loss: 0.0313 (0.0323) time: 3.6203 data: 0.0030 max mem: 19788 +Epoch: [18] [ 190/2138] eta: 1:57:59 lr: 2.9087473478537503e-05 loss: 0.0312 (0.0323) time: 3.6158 data: 0.0029 max mem: 19788 +Epoch: [18] [ 200/2138] eta: 1:57:22 lr: 2.908188504741975e-05 loss: 0.0256 (0.0320) time: 3.6214 data: 0.0030 max mem: 19788 +Epoch: [18] [ 210/2138] eta: 1:56:44 lr: 2.9076296496979032e-05 loss: 0.0345 (0.0323) time: 3.6222 data: 0.0029 max mem: 19788 +Epoch: [18] [ 220/2138] eta: 1:56:07 lr: 2.907070782718732e-05 loss: 0.0344 (0.0320) time: 3.6186 data: 0.0030 max mem: 19788 +Epoch: [18] [ 230/2138] eta: 1:55:30 lr: 2.906511903801658e-05 loss: 0.0340 (0.0334) time: 3.6217 data: 0.0031 max mem: 19788 +Epoch: [18] [ 240/2138] eta: 1:54:53 lr: 2.905953012943875e-05 loss: 0.0340 (0.0333) time: 3.6234 data: 0.0029 max mem: 19788 +Epoch: [18] [ 250/2138] eta: 1:54:16 lr: 2.9053941101425753e-05 loss: 0.0294 (0.0331) time: 3.6216 data: 0.0029 max mem: 19788 +Epoch: [18] [ 260/2138] eta: 1:53:39 lr: 2.9048351953949516e-05 loss: 0.0292 (0.0330) time: 3.6241 data: 0.0029 max mem: 19788 +Epoch: [18] [ 270/2138] eta: 1:53:02 lr: 2.9042762686981944e-05 loss: 0.0290 (0.0330) time: 3.6240 data: 0.0030 max mem: 19788 +Epoch: [18] [ 280/2138] eta: 1:52:25 lr: 2.903717330049493e-05 loss: 0.0292 (0.0329) time: 3.6203 data: 0.0031 max mem: 19788 +Epoch: [18] [ 290/2138] eta: 1:51:48 lr: 2.903158379446034e-05 loss: 0.0296 (0.0330) time: 3.6230 data: 0.0030 max mem: 19788 +Epoch: [18] [ 300/2138] eta: 1:51:12 lr: 2.902599416885007e-05 loss: 0.0287 (0.0328) time: 3.6248 data: 0.0030 max mem: 19788 +Epoch: [18] [ 310/2138] eta: 1:50:36 lr: 2.902040442363596e-05 loss: 0.0270 (0.0328) time: 3.6297 data: 0.0030 max mem: 19788 +Epoch: [18] [ 320/2138] eta: 1:49:59 lr: 2.9014814558789848e-05 loss: 0.0300 (0.0327) time: 3.6283 data: 0.0030 max mem: 19788 +Epoch: [18] [ 330/2138] eta: 1:49:22 lr: 2.9009224574283567e-05 loss: 0.0282 (0.0327) time: 3.6202 data: 0.0031 max mem: 19788 +Epoch: [18] [ 340/2138] eta: 1:48:45 lr: 2.9003634470088935e-05 loss: 0.0293 (0.0326) time: 3.6200 data: 0.0030 max mem: 19788 +Epoch: [18] [ 350/2138] eta: 1:48:09 lr: 2.8998044246177762e-05 loss: 0.0300 (0.0326) time: 3.6225 data: 0.0032 max mem: 19788 +Epoch: [18] [ 360/2138] eta: 1:47:32 lr: 2.8992453902521834e-05 loss: 0.0300 (0.0326) time: 3.6235 data: 0.0031 max mem: 19788 +Epoch: [18] [ 370/2138] eta: 1:46:55 lr: 2.8986863439092926e-05 loss: 0.0323 (0.0327) time: 3.6242 data: 0.0030 max mem: 19788 +Epoch: [18] [ 380/2138] eta: 1:46:19 lr: 2.898127285586282e-05 loss: 0.0323 (0.0326) time: 3.6209 data: 0.0030 max mem: 19788 +Epoch: [18] [ 390/2138] eta: 1:45:42 lr: 2.897568215280325e-05 loss: 0.0268 (0.0327) time: 3.6189 data: 0.0031 max mem: 19788 +Epoch: [18] [ 400/2138] eta: 1:45:05 lr: 2.8970091329885974e-05 loss: 0.0284 (0.0326) time: 3.6186 data: 0.0032 max mem: 19788 +Epoch: [18] [ 410/2138] eta: 1:44:29 lr: 2.8964500387082704e-05 loss: 0.0318 (0.0328) time: 3.6238 data: 0.0031 max mem: 19788 +Epoch: [18] [ 420/2138] eta: 1:43:53 lr: 2.8958909324365175e-05 loss: 0.0339 (0.0327) time: 3.6287 data: 0.0028 max mem: 19788 +Epoch: [18] [ 430/2138] eta: 1:43:16 lr: 2.8953318141705077e-05 loss: 0.0287 (0.0328) time: 3.6244 data: 0.0029 max mem: 19788 +Epoch: [18] [ 440/2138] eta: 1:42:40 lr: 2.8947726839074095e-05 loss: 0.0308 (0.0329) time: 3.6212 data: 0.0030 max mem: 19788 +Epoch: [18] [ 450/2138] eta: 1:42:03 lr: 2.8942135416443922e-05 loss: 0.0261 (0.0329) time: 3.6203 data: 0.0029 max mem: 19788 +Epoch: [18] [ 460/2138] eta: 1:41:27 lr: 2.8936543873786216e-05 loss: 0.0286 (0.0329) time: 3.6247 data: 0.0030 max mem: 19788 +Epoch: [18] [ 470/2138] eta: 1:40:50 lr: 2.8930952211072625e-05 loss: 0.0300 (0.0332) time: 3.6253 data: 0.0032 max mem: 19788 +Epoch: [18] [ 480/2138] eta: 1:40:14 lr: 2.892536042827479e-05 loss: 0.0300 (0.0332) time: 3.6257 data: 0.0032 max mem: 19788 +Epoch: [18] [ 490/2138] eta: 1:39:38 lr: 2.891976852536433e-05 loss: 0.0276 (0.0331) time: 3.6276 data: 0.0032 max mem: 19788 +Epoch: [18] [ 500/2138] eta: 1:39:01 lr: 2.891417650231288e-05 loss: 0.0262 (0.0331) time: 3.6249 data: 0.0030 max mem: 19788 +Epoch: [18] [ 510/2138] eta: 1:38:25 lr: 2.8908584359092018e-05 loss: 0.0309 (0.0330) time: 3.6240 data: 0.0029 max mem: 19788 +Epoch: [18] [ 520/2138] eta: 1:37:49 lr: 2.8902992095673343e-05 loss: 0.0311 (0.0330) time: 3.6311 data: 0.0029 max mem: 19788 +Epoch: [18] [ 530/2138] eta: 1:37:13 lr: 2.889739971202842e-05 loss: 0.0294 (0.0330) time: 3.6300 data: 0.0031 max mem: 19788 +Epoch: [18] [ 540/2138] eta: 1:36:36 lr: 2.889180720812883e-05 loss: 0.0294 (0.0329) time: 3.6256 data: 0.0030 max mem: 19788 +Epoch: [18] [ 550/2138] eta: 1:36:00 lr: 2.888621458394611e-05 loss: 0.0287 (0.0329) time: 3.6330 data: 0.0029 max mem: 19788 +Epoch: [18] [ 560/2138] eta: 1:35:24 lr: 2.8880621839451792e-05 loss: 0.0287 (0.0329) time: 3.6340 data: 0.0031 max mem: 19788 +Epoch: [18] [ 570/2138] eta: 1:34:48 lr: 2.88750289746174e-05 loss: 0.0274 (0.0329) time: 3.6323 data: 0.0032 max mem: 19788 +Epoch: [18] [ 580/2138] eta: 1:34:12 lr: 2.886943598941446e-05 loss: 0.0350 (0.0329) time: 3.6305 data: 0.0032 max mem: 19788 +Epoch: [18] [ 590/2138] eta: 1:33:35 lr: 2.8863842883814463e-05 loss: 0.0350 (0.0329) time: 3.6267 data: 0.0033 max mem: 19788 +Epoch: [18] [ 600/2138] eta: 1:32:59 lr: 2.885824965778888e-05 loss: 0.0301 (0.0329) time: 3.6215 data: 0.0032 max mem: 19788 +Epoch: [18] [ 610/2138] eta: 1:32:23 lr: 2.88526563113092e-05 loss: 0.0281 (0.0329) time: 3.6215 data: 0.0030 max mem: 19788 +Epoch: [18] [ 620/2138] eta: 1:31:46 lr: 2.8847062844346873e-05 loss: 0.0311 (0.0329) time: 3.6255 data: 0.0031 max mem: 19788 +Epoch: [18] [ 630/2138] eta: 1:31:10 lr: 2.8841469256873343e-05 loss: 0.0297 (0.0328) time: 3.6242 data: 0.0031 max mem: 19788 +Epoch: [18] [ 640/2138] eta: 1:30:34 lr: 2.8835875548860055e-05 loss: 0.0277 (0.0328) time: 3.6249 data: 0.0030 max mem: 19788 +Epoch: [18] [ 650/2138] eta: 1:29:57 lr: 2.883028172027842e-05 loss: 0.0300 (0.0328) time: 3.6272 data: 0.0030 max mem: 19788 +Epoch: [18] [ 660/2138] eta: 1:29:21 lr: 2.8824687771099852e-05 loss: 0.0316 (0.0328) time: 3.6272 data: 0.0032 max mem: 19788 +Epoch: [18] [ 670/2138] eta: 1:28:45 lr: 2.8819093701295735e-05 loss: 0.0343 (0.0328) time: 3.6260 data: 0.0031 max mem: 19788 +Epoch: [18] [ 680/2138] eta: 1:28:08 lr: 2.8813499510837454e-05 loss: 0.0330 (0.0329) time: 3.6243 data: 0.0028 max mem: 19788 +Epoch: [18] [ 690/2138] eta: 1:27:32 lr: 2.880790519969639e-05 loss: 0.0302 (0.0328) time: 3.6246 data: 0.0028 max mem: 19788 +Epoch: [18] [ 700/2138] eta: 1:26:56 lr: 2.880231076784389e-05 loss: 0.0298 (0.0328) time: 3.6268 data: 0.0029 max mem: 19788 +Epoch: [18] [ 710/2138] eta: 1:26:19 lr: 2.8796716215251284e-05 loss: 0.0324 (0.0329) time: 3.6274 data: 0.0029 max mem: 19788 +Epoch: [18] [ 720/2138] eta: 1:25:43 lr: 2.879112154188992e-05 loss: 0.0324 (0.0331) time: 3.6252 data: 0.0033 max mem: 19788 +Epoch: [18] [ 730/2138] eta: 1:25:07 lr: 2.8785526747731106e-05 loss: 0.0386 (0.0332) time: 3.6250 data: 0.0035 max mem: 19788 +Epoch: [18] [ 740/2138] eta: 1:24:30 lr: 2.8779931832746155e-05 loss: 0.0285 (0.0331) time: 3.6213 data: 0.0031 max mem: 19788 +Epoch: [18] [ 750/2138] eta: 1:23:54 lr: 2.8774336796906342e-05 loss: 0.0255 (0.0331) time: 3.6172 data: 0.0030 max mem: 19788 +Epoch: [18] [ 760/2138] eta: 1:23:18 lr: 2.8768741640182955e-05 loss: 0.0314 (0.0332) time: 3.6231 data: 0.0032 max mem: 19788 +Epoch: [18] [ 770/2138] eta: 1:22:41 lr: 2.8763146362547254e-05 loss: 0.0329 (0.0332) time: 3.6283 data: 0.0030 max mem: 19788 +Epoch: [18] [ 780/2138] eta: 1:22:05 lr: 2.8757550963970505e-05 loss: 0.0331 (0.0332) time: 3.6287 data: 0.0029 max mem: 19788 +Epoch: [18] [ 790/2138] eta: 1:21:29 lr: 2.8751955444423915e-05 loss: 0.0321 (0.0332) time: 3.6286 data: 0.0029 max mem: 19788 +Epoch: [18] [ 800/2138] eta: 1:20:53 lr: 2.874635980387874e-05 loss: 0.0315 (0.0332) time: 3.6251 data: 0.0032 max mem: 19788 +Epoch: [18] [ 810/2138] eta: 1:20:16 lr: 2.8740764042306185e-05 loss: 0.0325 (0.0332) time: 3.6234 data: 0.0032 max mem: 19788 +Epoch: [18] [ 820/2138] eta: 1:19:40 lr: 2.8735168159677438e-05 loss: 0.0303 (0.0332) time: 3.6277 data: 0.0029 max mem: 19788 +Epoch: [18] [ 830/2138] eta: 1:19:04 lr: 2.8729572155963692e-05 loss: 0.0294 (0.0331) time: 3.6305 data: 0.0030 max mem: 19788 +Epoch: [18] [ 840/2138] eta: 1:18:27 lr: 2.8723976031136117e-05 loss: 0.0253 (0.0331) time: 3.6267 data: 0.0030 max mem: 19788 +Epoch: [18] [ 850/2138] eta: 1:17:51 lr: 2.8718379785165883e-05 loss: 0.0253 (0.0330) time: 3.6223 data: 0.0029 max mem: 19788 +Epoch: [18] [ 860/2138] eta: 1:17:15 lr: 2.871278341802413e-05 loss: 0.0293 (0.0330) time: 3.6252 data: 0.0030 max mem: 19788 +Epoch: [18] [ 870/2138] eta: 1:16:39 lr: 2.870718692968199e-05 loss: 0.0342 (0.0331) time: 3.6267 data: 0.0031 max mem: 19788 +Epoch: [18] [ 880/2138] eta: 1:16:02 lr: 2.8701590320110582e-05 loss: 0.0305 (0.0331) time: 3.6262 data: 0.0030 max mem: 19788 +Epoch: [18] [ 890/2138] eta: 1:15:26 lr: 2.8695993589281023e-05 loss: 0.0304 (0.0331) time: 3.6297 data: 0.0029 max mem: 19788 +Epoch: [18] [ 900/2138] eta: 1:14:50 lr: 2.8690396737164403e-05 loss: 0.0342 (0.0331) time: 3.6271 data: 0.0031 max mem: 19788 +Epoch: [18] [ 910/2138] eta: 1:14:13 lr: 2.868479976373179e-05 loss: 0.0304 (0.0332) time: 3.6241 data: 0.0030 max mem: 19788 +Epoch: [18] [ 920/2138] eta: 1:13:37 lr: 2.8679202668954276e-05 loss: 0.0286 (0.0332) time: 3.6269 data: 0.0029 max mem: 19788 +Epoch: [18] [ 930/2138] eta: 1:13:01 lr: 2.86736054528029e-05 loss: 0.0325 (0.0332) time: 3.6265 data: 0.0030 max mem: 19788 +Epoch: [18] [ 940/2138] eta: 1:12:25 lr: 2.8668008115248694e-05 loss: 0.0343 (0.0333) time: 3.6247 data: 0.0031 max mem: 19788 +Epoch: [18] [ 950/2138] eta: 1:11:48 lr: 2.8662410656262712e-05 loss: 0.0317 (0.0333) time: 3.6246 data: 0.0030 max mem: 19788 +Epoch: [18] [ 960/2138] eta: 1:11:12 lr: 2.8656813075815953e-05 loss: 0.0304 (0.0333) time: 3.6244 data: 0.0030 max mem: 19788 +Epoch: [18] [ 970/2138] eta: 1:10:36 lr: 2.8651215373879427e-05 loss: 0.0298 (0.0332) time: 3.6245 data: 0.0030 max mem: 19788 +Epoch: [18] [ 980/2138] eta: 1:09:59 lr: 2.864561755042411e-05 loss: 0.0263 (0.0331) time: 3.6262 data: 0.0030 max mem: 19788 +Epoch: [18] [ 990/2138] eta: 1:09:23 lr: 2.8640019605420982e-05 loss: 0.0301 (0.0332) time: 3.6249 data: 0.0031 max mem: 19788 +Epoch: [18] [1000/2138] eta: 1:08:47 lr: 2.8634421538841018e-05 loss: 0.0321 (0.0332) time: 3.6262 data: 0.0030 max mem: 19788 +Epoch: [18] [1010/2138] eta: 1:08:11 lr: 2.8628823350655152e-05 loss: 0.0290 (0.0332) time: 3.6253 data: 0.0030 max mem: 19788 +Epoch: [18] [1020/2138] eta: 1:07:34 lr: 2.862322504083433e-05 loss: 0.0275 (0.0331) time: 3.6242 data: 0.0029 max mem: 19788 +Epoch: [18] [1030/2138] eta: 1:06:58 lr: 2.8617626609349464e-05 loss: 0.0275 (0.0331) time: 3.6283 data: 0.0029 max mem: 19788 +Epoch: [18] [1040/2138] eta: 1:06:22 lr: 2.8612028056171474e-05 loss: 0.0283 (0.0331) time: 3.6260 data: 0.0030 max mem: 19788 +Epoch: [18] [1050/2138] eta: 1:05:46 lr: 2.8606429381271255e-05 loss: 0.0299 (0.0331) time: 3.6277 data: 0.0031 max mem: 19788 +Epoch: [18] [1060/2138] eta: 1:05:09 lr: 2.860083058461968e-05 loss: 0.0308 (0.0331) time: 3.6280 data: 0.0030 max mem: 19788 +Epoch: [18] [1070/2138] eta: 1:04:33 lr: 2.8595231666187627e-05 loss: 0.0290 (0.0331) time: 3.6270 data: 0.0030 max mem: 19788 +Epoch: [18] [1080/2138] eta: 1:03:57 lr: 2.858963262594595e-05 loss: 0.0281 (0.0330) time: 3.6286 data: 0.0030 max mem: 19788 +Epoch: [18] [1090/2138] eta: 1:03:20 lr: 2.8584033463865494e-05 loss: 0.0281 (0.0331) time: 3.6273 data: 0.0029 max mem: 19788 +Epoch: [18] [1100/2138] eta: 1:02:44 lr: 2.857843417991708e-05 loss: 0.0334 (0.0331) time: 3.6298 data: 0.0029 max mem: 19788 +Epoch: [18] [1110/2138] eta: 1:02:08 lr: 2.8572834774071533e-05 loss: 0.0322 (0.0331) time: 3.6273 data: 0.0029 max mem: 19788 +Epoch: [18] [1120/2138] eta: 1:01:32 lr: 2.856723524629965e-05 loss: 0.0321 (0.0332) time: 3.6226 data: 0.0030 max mem: 19788 +Epoch: [18] [1130/2138] eta: 1:00:55 lr: 2.8561635596572234e-05 loss: 0.0321 (0.0332) time: 3.6270 data: 0.0031 max mem: 19788 +Epoch: [18] [1140/2138] eta: 1:00:19 lr: 2.855603582486004e-05 loss: 0.0293 (0.0332) time: 3.6307 data: 0.0032 max mem: 19788 +Epoch: [18] [1150/2138] eta: 0:59:43 lr: 2.8550435931133835e-05 loss: 0.0287 (0.0331) time: 3.6256 data: 0.0032 max mem: 19788 +Epoch: [18] [1160/2138] eta: 0:59:07 lr: 2.8544835915364387e-05 loss: 0.0280 (0.0331) time: 3.6252 data: 0.0029 max mem: 19788 +Epoch: [18] [1170/2138] eta: 0:58:30 lr: 2.8539235777522417e-05 loss: 0.0306 (0.0331) time: 3.6310 data: 0.0029 max mem: 19788 +Epoch: [18] [1180/2138] eta: 0:57:54 lr: 2.8533635517578645e-05 loss: 0.0322 (0.0331) time: 3.6313 data: 0.0031 max mem: 19788 +Epoch: [18] [1190/2138] eta: 0:57:18 lr: 2.852803513550378e-05 loss: 0.0309 (0.0331) time: 3.6302 data: 0.0033 max mem: 19788 +Epoch: [18] [1200/2138] eta: 0:56:42 lr: 2.8522434631268536e-05 loss: 0.0292 (0.0330) time: 3.6238 data: 0.0032 max mem: 19788 +Epoch: [18] [1210/2138] eta: 0:56:06 lr: 2.8516834004843572e-05 loss: 0.0293 (0.0330) time: 3.6695 data: 0.0031 max mem: 19788 +Epoch: [18] [1220/2138] eta: 0:55:31 lr: 2.8511233256199565e-05 loss: 0.0293 (0.0330) time: 3.7292 data: 0.0031 max mem: 19788 +Epoch: [18] [1230/2138] eta: 0:54:54 lr: 2.8505632385307178e-05 loss: 0.0275 (0.0330) time: 3.6879 data: 0.0030 max mem: 19788 +Epoch: [18] [1240/2138] eta: 0:54:18 lr: 2.850003139213705e-05 loss: 0.0290 (0.0330) time: 3.6461 data: 0.0028 max mem: 19788 +Epoch: [18] [1250/2138] eta: 0:53:42 lr: 2.8494430276659793e-05 loss: 0.0267 (0.0330) time: 3.6528 data: 0.0028 max mem: 19788 +Epoch: [18] [1260/2138] eta: 0:53:06 lr: 2.8488829038846042e-05 loss: 0.0259 (0.0329) time: 3.6608 data: 0.0028 max mem: 19788 +Epoch: [18] [1270/2138] eta: 0:52:30 lr: 2.8483227678666398e-05 loss: 0.0250 (0.0329) time: 3.6566 data: 0.0027 max mem: 19788 +Epoch: [18] [1280/2138] eta: 0:51:54 lr: 2.847762619609144e-05 loss: 0.0257 (0.0329) time: 3.6392 data: 0.0026 max mem: 19788 +Epoch: [18] [1290/2138] eta: 0:51:18 lr: 2.847202459109174e-05 loss: 0.0277 (0.0329) time: 3.6465 data: 0.0026 max mem: 19788 +Epoch: [18] [1300/2138] eta: 0:50:41 lr: 2.846642286363786e-05 loss: 0.0282 (0.0329) time: 3.6535 data: 0.0027 max mem: 19788 +Epoch: [18] [1310/2138] eta: 0:50:05 lr: 2.8460821013700363e-05 loss: 0.0282 (0.0328) time: 3.6634 data: 0.0027 max mem: 19788 +Epoch: [18] [1320/2138] eta: 0:49:29 lr: 2.8455219041249763e-05 loss: 0.0353 (0.0329) time: 3.6744 data: 0.0026 max mem: 19788 +Epoch: [18] [1330/2138] eta: 0:48:53 lr: 2.8449616946256592e-05 loss: 0.0316 (0.0329) time: 3.6557 data: 0.0026 max mem: 19788 +Epoch: [18] [1340/2138] eta: 0:48:17 lr: 2.8444014728691354e-05 loss: 0.0309 (0.0329) time: 3.6468 data: 0.0026 max mem: 19788 +Epoch: [18] [1350/2138] eta: 0:47:41 lr: 2.8438412388524545e-05 loss: 0.0388 (0.0330) time: 3.6423 data: 0.0026 max mem: 19788 +Epoch: [18] [1360/2138] eta: 0:47:05 lr: 2.843280992572664e-05 loss: 0.0348 (0.0330) time: 3.6520 data: 0.0026 max mem: 19788 +Epoch: [18] [1370/2138] eta: 0:46:28 lr: 2.8427207340268107e-05 loss: 0.0302 (0.0330) time: 3.6518 data: 0.0027 max mem: 19788 +Epoch: [18] [1380/2138] eta: 0:45:52 lr: 2.842160463211939e-05 loss: 0.0302 (0.0330) time: 3.6399 data: 0.0027 max mem: 19788 +Epoch: [18] [1390/2138] eta: 0:45:16 lr: 2.8416001801250952e-05 loss: 0.0336 (0.0330) time: 3.6540 data: 0.0027 max mem: 19788 +Epoch: [18] [1400/2138] eta: 0:44:40 lr: 2.84103988476332e-05 loss: 0.0290 (0.0330) time: 3.6506 data: 0.0027 max mem: 19788 +Epoch: [18] [1410/2138] eta: 0:44:03 lr: 2.8404795771236542e-05 loss: 0.0290 (0.0330) time: 3.6599 data: 0.0027 max mem: 19788 +Epoch: [18] [1420/2138] eta: 0:43:27 lr: 2.8399192572031384e-05 loss: 0.0298 (0.0330) time: 3.6608 data: 0.0027 max mem: 19788 +Epoch: [18] [1430/2138] eta: 0:42:51 lr: 2.839358924998812e-05 loss: 0.0310 (0.0330) time: 3.6569 data: 0.0027 max mem: 19788 +Epoch: [18] [1440/2138] eta: 0:42:15 lr: 2.83879858050771e-05 loss: 0.0284 (0.0329) time: 3.6665 data: 0.0027 max mem: 19788 +Epoch: [18] [1450/2138] eta: 0:41:39 lr: 2.8382382237268696e-05 loss: 0.0311 (0.0330) time: 3.6540 data: 0.0027 max mem: 19788 +Epoch: [18] [1460/2138] eta: 0:41:02 lr: 2.8376778546533246e-05 loss: 0.0319 (0.0329) time: 3.6530 data: 0.0027 max mem: 19788 +Epoch: [18] [1470/2138] eta: 0:40:26 lr: 2.8371174732841084e-05 loss: 0.0302 (0.0330) time: 3.6538 data: 0.0028 max mem: 19788 +Epoch: [18] [1480/2138] eta: 0:39:50 lr: 2.8365570796162523e-05 loss: 0.0316 (0.0330) time: 3.6591 data: 0.0028 max mem: 19788 +Epoch: [18] [1490/2138] eta: 0:39:14 lr: 2.8359966736467863e-05 loss: 0.0316 (0.0330) time: 3.6607 data: 0.0027 max mem: 19788 +Epoch: [18] [1500/2138] eta: 0:38:37 lr: 2.83543625537274e-05 loss: 0.0322 (0.0330) time: 3.6437 data: 0.0027 max mem: 19788 +Epoch: [18] [1510/2138] eta: 0:38:01 lr: 2.8348758247911406e-05 loss: 0.0322 (0.0330) time: 3.6410 data: 0.0027 max mem: 19788 +Epoch: [18] [1520/2138] eta: 0:37:25 lr: 2.834315381899014e-05 loss: 0.0279 (0.0330) time: 3.6382 data: 0.0026 max mem: 19788 +Epoch: [18] [1530/2138] eta: 0:36:49 lr: 2.833754926693385e-05 loss: 0.0258 (0.0329) time: 3.6427 data: 0.0026 max mem: 19788 +Epoch: [18] [1540/2138] eta: 0:36:12 lr: 2.8331944591712778e-05 loss: 0.0258 (0.0329) time: 3.6497 data: 0.0027 max mem: 19788 +Epoch: [18] [1550/2138] eta: 0:35:36 lr: 2.8326339793297137e-05 loss: 0.0294 (0.0329) time: 3.6542 data: 0.0027 max mem: 19788 +Epoch: [18] [1560/2138] eta: 0:35:00 lr: 2.8320734871657128e-05 loss: 0.0355 (0.0329) time: 3.6582 data: 0.0027 max mem: 19788 +Epoch: [18] [1570/2138] eta: 0:34:24 lr: 2.8315129826762953e-05 loss: 0.0316 (0.0329) time: 3.6457 data: 0.0027 max mem: 19788 +Epoch: [18] [1580/2138] eta: 0:33:47 lr: 2.830952465858479e-05 loss: 0.0315 (0.0329) time: 3.6444 data: 0.0028 max mem: 19788 +Epoch: [18] [1590/2138] eta: 0:33:11 lr: 2.8303919367092808e-05 loss: 0.0330 (0.0329) time: 3.6430 data: 0.0027 max mem: 19788 +Epoch: [18] [1600/2138] eta: 0:32:35 lr: 2.8298313952257145e-05 loss: 0.0343 (0.0329) time: 3.6522 data: 0.0027 max mem: 19788 +Epoch: [18] [1610/2138] eta: 0:31:58 lr: 2.8292708414047946e-05 loss: 0.0314 (0.0329) time: 3.6586 data: 0.0027 max mem: 19788 +Epoch: [18] [1620/2138] eta: 0:31:22 lr: 2.828710275243534e-05 loss: 0.0280 (0.0329) time: 3.6492 data: 0.0029 max mem: 19788 +Epoch: [18] [1630/2138] eta: 0:30:46 lr: 2.8281496967389437e-05 loss: 0.0296 (0.0329) time: 3.6549 data: 0.0031 max mem: 19788 +Epoch: [18] [1640/2138] eta: 0:30:10 lr: 2.8275891058880323e-05 loss: 0.0280 (0.0329) time: 3.7126 data: 0.0035 max mem: 19788 +Epoch: [18] [1650/2138] eta: 0:29:34 lr: 2.8270285026878085e-05 loss: 0.0270 (0.0328) time: 3.7314 data: 0.0033 max mem: 19788 +Epoch: [18] [1660/2138] eta: 0:28:57 lr: 2.8264678871352795e-05 loss: 0.0252 (0.0328) time: 3.6809 data: 0.0032 max mem: 19788 +Epoch: [18] [1670/2138] eta: 0:28:21 lr: 2.825907259227451e-05 loss: 0.0247 (0.0327) time: 3.7062 data: 0.0032 max mem: 19788 +Epoch: [18] [1680/2138] eta: 0:27:45 lr: 2.825346618961326e-05 loss: 0.0265 (0.0327) time: 3.7271 data: 0.0030 max mem: 19788 +Epoch: [18] [1690/2138] eta: 0:27:09 lr: 2.8247859663339076e-05 loss: 0.0295 (0.0327) time: 3.6892 data: 0.0030 max mem: 19788 +Epoch: [18] [1700/2138] eta: 0:26:33 lr: 2.8242253013421983e-05 loss: 0.0286 (0.0327) time: 3.6841 data: 0.0031 max mem: 19788 +Epoch: [18] [1710/2138] eta: 0:25:57 lr: 2.8236646239831964e-05 loss: 0.0276 (0.0327) time: 3.7154 data: 0.0031 max mem: 19788 +Epoch: [18] [1720/2138] eta: 0:25:20 lr: 2.823103934253901e-05 loss: 0.0289 (0.0327) time: 3.6977 data: 0.0031 max mem: 19788 +Epoch: [18] [1730/2138] eta: 0:24:44 lr: 2.8225432321513097e-05 loss: 0.0319 (0.0327) time: 3.6667 data: 0.0032 max mem: 19788 +Epoch: [18] [1740/2138] eta: 0:24:08 lr: 2.821982517672418e-05 loss: 0.0318 (0.0327) time: 3.6668 data: 0.0032 max mem: 19788 +Epoch: [18] [1750/2138] eta: 0:23:31 lr: 2.8214217908142205e-05 loss: 0.0301 (0.0327) time: 3.6764 data: 0.0033 max mem: 19788 +Epoch: [18] [1760/2138] eta: 0:22:55 lr: 2.8208610515737084e-05 loss: 0.0290 (0.0327) time: 3.6892 data: 0.0032 max mem: 19788 +Epoch: [18] [1770/2138] eta: 0:22:19 lr: 2.8203002999478752e-05 loss: 0.0256 (0.0327) time: 3.6767 data: 0.0031 max mem: 19788 +Epoch: [18] [1780/2138] eta: 0:21:42 lr: 2.8197395359337107e-05 loss: 0.0285 (0.0327) time: 3.6741 data: 0.0033 max mem: 19788 +Epoch: [18] [1790/2138] eta: 0:21:06 lr: 2.8191787595282044e-05 loss: 0.0281 (0.0327) time: 3.6774 data: 0.0031 max mem: 19788 +Epoch: [18] [1800/2138] eta: 0:20:30 lr: 2.818617970728341e-05 loss: 0.0281 (0.0327) time: 3.6853 data: 0.0029 max mem: 19788 +Epoch: [18] [1810/2138] eta: 0:19:53 lr: 2.818057169531109e-05 loss: 0.0299 (0.0327) time: 3.6838 data: 0.0029 max mem: 19788 +Epoch: [18] [1820/2138] eta: 0:19:17 lr: 2.8174963559334926e-05 loss: 0.0282 (0.0326) time: 3.6716 data: 0.0029 max mem: 19788 +Epoch: [18] [1830/2138] eta: 0:18:41 lr: 2.8169355299324745e-05 loss: 0.0284 (0.0326) time: 3.6711 data: 0.0029 max mem: 19788 +Epoch: [18] [1840/2138] eta: 0:18:04 lr: 2.816374691525036e-05 loss: 0.0299 (0.0326) time: 3.6688 data: 0.0028 max mem: 19788 +Epoch: [18] [1850/2138] eta: 0:17:28 lr: 2.8158138407081586e-05 loss: 0.0314 (0.0327) time: 3.6737 data: 0.0029 max mem: 19788 +Epoch: [18] [1860/2138] eta: 0:16:52 lr: 2.815252977478821e-05 loss: 0.0310 (0.0327) time: 3.6702 data: 0.0029 max mem: 19788 +Epoch: [18] [1870/2138] eta: 0:16:15 lr: 2.8146921018339995e-05 loss: 0.0299 (0.0327) time: 3.6583 data: 0.0029 max mem: 19788 +Epoch: [18] [1880/2138] eta: 0:15:39 lr: 2.8141312137706717e-05 loss: 0.0285 (0.0327) time: 3.6697 data: 0.0029 max mem: 19788 +Epoch: [18] [1890/2138] eta: 0:15:03 lr: 2.8135703132858114e-05 loss: 0.0273 (0.0326) time: 3.7181 data: 0.0029 max mem: 19788 +Epoch: [18] [1900/2138] eta: 0:14:26 lr: 2.8130094003763934e-05 loss: 0.0262 (0.0326) time: 3.7837 data: 0.0029 max mem: 19788 +Epoch: [18] [1910/2138] eta: 0:13:50 lr: 2.8124484750393882e-05 loss: 0.0269 (0.0326) time: 3.7929 data: 0.0029 max mem: 19788 +Epoch: [18] [1920/2138] eta: 0:13:14 lr: 2.8118875372717662e-05 loss: 0.0289 (0.0326) time: 3.7826 data: 0.0031 max mem: 19788 +Epoch: [18] [1930/2138] eta: 0:12:38 lr: 2.8113265870704975e-05 loss: 0.0300 (0.0326) time: 3.8295 data: 0.0031 max mem: 19788 +Epoch: [18] [1940/2138] eta: 0:12:01 lr: 2.8107656244325496e-05 loss: 0.0285 (0.0326) time: 3.8244 data: 0.0029 max mem: 19788 +Epoch: [18] [1950/2138] eta: 0:11:25 lr: 2.8102046493548882e-05 loss: 0.0283 (0.0326) time: 3.8268 data: 0.0029 max mem: 19788 +Epoch: [18] [1960/2138] eta: 0:10:49 lr: 2.809643661834479e-05 loss: 0.0281 (0.0325) time: 3.8341 data: 0.0029 max mem: 19788 +Epoch: [18] [1970/2138] eta: 0:10:12 lr: 2.8090826618682846e-05 loss: 0.0300 (0.0326) time: 3.7375 data: 0.0029 max mem: 19788 +Epoch: [18] [1980/2138] eta: 0:09:36 lr: 2.8085216494532685e-05 loss: 0.0300 (0.0326) time: 3.6675 data: 0.0031 max mem: 19788 +Epoch: [18] [1990/2138] eta: 0:09:00 lr: 2.8079606245863894e-05 loss: 0.0287 (0.0326) time: 3.7289 data: 0.0031 max mem: 19788 +Epoch: [18] [2000/2138] eta: 0:08:23 lr: 2.807399587264607e-05 loss: 0.0305 (0.0326) time: 3.7526 data: 0.0028 max mem: 19788 +Epoch: [18] [2010/2138] eta: 0:07:47 lr: 2.8068385374848806e-05 loss: 0.0324 (0.0326) time: 3.6728 data: 0.0030 max mem: 19788 +Epoch: [18] [2020/2138] eta: 0:07:10 lr: 2.806277475244165e-05 loss: 0.0324 (0.0326) time: 3.8132 data: 0.0030 max mem: 19788 +Epoch: [18] [2030/2138] eta: 0:06:34 lr: 2.8057164005394154e-05 loss: 0.0325 (0.0326) time: 3.8216 data: 0.0029 max mem: 19788 +Epoch: [18] [2040/2138] eta: 0:05:57 lr: 2.8051553133675855e-05 loss: 0.0300 (0.0326) time: 3.7687 data: 0.0029 max mem: 19788 +Epoch: [18] [2050/2138] eta: 0:05:21 lr: 2.804594213725629e-05 loss: 0.0317 (0.0326) time: 3.9249 data: 0.0029 max mem: 19788 +Epoch: [18] [2060/2138] eta: 0:04:45 lr: 2.8040331016104944e-05 loss: 0.0321 (0.0326) time: 3.8924 data: 0.0029 max mem: 19788 +Epoch: [18] [2070/2138] eta: 0:04:08 lr: 2.8034719770191307e-05 loss: 0.0266 (0.0326) time: 3.7620 data: 0.0029 max mem: 19788 +Epoch: [18] [2080/2138] eta: 0:03:32 lr: 2.8029108399484876e-05 loss: 0.0309 (0.0326) time: 3.7987 data: 0.0029 max mem: 19788 +Epoch: [18] [2090/2138] eta: 0:02:55 lr: 2.802349690395511e-05 loss: 0.0309 (0.0325) time: 3.8527 data: 0.0027 max mem: 19788 +Epoch: [18] [2100/2138] eta: 0:02:19 lr: 2.8017885283571456e-05 loss: 0.0262 (0.0326) time: 3.8989 data: 0.0028 max mem: 19788 +Epoch: [18] [2110/2138] eta: 0:01:42 lr: 2.8012273538303342e-05 loss: 0.0349 (0.0326) time: 3.9805 data: 0.0029 max mem: 19788 +Epoch: [18] [2120/2138] eta: 0:01:05 lr: 2.80066616681202e-05 loss: 0.0364 (0.0326) time: 3.8061 data: 0.0032 max mem: 19788 +Epoch: [18] [2130/2138] eta: 0:00:29 lr: 2.800104967299143e-05 loss: 0.0327 (0.0327) time: 3.8713 data: 0.0032 max mem: 19788 +Epoch: [18] Total time: 2:10:30 +Test: [ 0/21770] eta: 18:58:04 time: 3.1366 data: 2.9572 max mem: 19788 +Test: [ 100/21770] eta: 0:33:32 time: 0.0617 data: 0.0019 max mem: 19788 +Test: [ 200/21770] eta: 0:28:13 time: 0.0614 data: 0.0018 max mem: 19788 +Test: [ 300/21770] eta: 0:27:10 time: 0.0713 data: 0.0021 max mem: 19788 +Test: [ 400/21770] eta: 0:26:29 time: 0.0618 data: 0.0019 max mem: 19788 +Test: [ 500/21770] eta: 0:26:10 time: 0.0817 data: 0.0021 max mem: 19788 +Test: [ 600/21770] eta: 0:25:56 time: 0.0620 data: 0.0018 max mem: 19788 +Test: [ 700/21770] eta: 0:25:22 time: 0.0614 data: 0.0019 max mem: 19788 +Test: [ 800/21770] eta: 0:24:46 time: 0.0603 data: 0.0017 max mem: 19788 +Test: [ 900/21770] eta: 0:24:19 time: 0.0636 data: 0.0019 max mem: 19788 +Test: [ 1000/21770] eta: 0:24:00 time: 0.0719 data: 0.0021 max mem: 19788 +Test: [ 1100/21770] eta: 0:23:41 time: 0.0670 data: 0.0019 max mem: 19788 +Test: [ 1200/21770] eta: 0:23:24 time: 0.0638 data: 0.0019 max mem: 19788 +Test: [ 1300/21770] eta: 0:23:21 time: 0.0714 data: 0.0019 max mem: 19788 +Test: [ 1400/21770] eta: 0:23:13 time: 0.0771 data: 0.0024 max mem: 19788 +Test: [ 1500/21770] eta: 0:23:16 time: 0.0604 data: 0.0017 max mem: 19788 +Test: [ 1600/21770] eta: 0:23:08 time: 0.0677 data: 0.0021 max mem: 19788 +Test: [ 1700/21770] eta: 0:22:54 time: 0.0594 data: 0.0018 max mem: 19788 +Test: [ 1800/21770] eta: 0:22:47 time: 0.0703 data: 0.0023 max mem: 19788 +Test: [ 1900/21770] eta: 0:22:48 time: 0.0712 data: 0.0022 max mem: 19788 +Test: [ 2000/21770] eta: 0:22:45 time: 0.0793 data: 0.0023 max mem: 19788 +Test: [ 2100/21770] eta: 0:22:37 time: 0.0764 data: 0.0023 max mem: 19788 +Test: [ 2200/21770] eta: 0:22:40 time: 0.0817 data: 0.0024 max mem: 19788 +Test: [ 2300/21770] eta: 0:22:37 time: 0.0773 data: 0.0023 max mem: 19788 +Test: [ 2400/21770] eta: 0:22:24 time: 0.0629 data: 0.0021 max mem: 19788 +Test: [ 2500/21770] eta: 0:22:17 time: 0.0812 data: 0.0024 max mem: 19788 +Test: [ 2600/21770] eta: 0:22:16 time: 0.0814 data: 0.0026 max mem: 19788 +Test: [ 2700/21770] eta: 0:22:17 time: 0.0801 data: 0.0022 max mem: 19788 +Test: [ 2800/21770] eta: 0:22:15 time: 0.0794 data: 0.0024 max mem: 19788 +Test: [ 2900/21770] eta: 0:22:06 time: 0.0630 data: 0.0018 max mem: 19788 +Test: [ 3000/21770] eta: 0:22:03 time: 0.0737 data: 0.0020 max mem: 19788 +Test: [ 3100/21770] eta: 0:21:58 time: 0.0817 data: 0.0026 max mem: 19788 +Test: [ 3200/21770] eta: 0:21:58 time: 0.0815 data: 0.0025 max mem: 19788 +Test: [ 3300/21770] eta: 0:21:52 time: 0.0633 data: 0.0020 max mem: 19788 +Test: [ 3400/21770] eta: 0:21:40 time: 0.0632 data: 0.0019 max mem: 19788 +Test: [ 3500/21770] eta: 0:21:30 time: 0.0636 data: 0.0018 max mem: 19788 +Test: [ 3600/21770] eta: 0:21:20 time: 0.0718 data: 0.0022 max mem: 19788 +Test: [ 3700/21770] eta: 0:21:14 time: 0.0814 data: 0.0024 max mem: 19788 +Test: [ 3800/21770] eta: 0:21:10 time: 0.0652 data: 0.0018 max mem: 19788 +Test: [ 3900/21770] eta: 0:21:02 time: 0.0674 data: 0.0019 max mem: 19788 +Test: [ 4000/21770] eta: 0:20:55 time: 0.0786 data: 0.0020 max mem: 19788 +Test: [ 4100/21770] eta: 0:20:47 time: 0.0635 data: 0.0019 max mem: 19788 +Test: [ 4200/21770] eta: 0:20:37 time: 0.0635 data: 0.0020 max mem: 19788 +Test: [ 4300/21770] eta: 0:20:26 time: 0.0610 data: 0.0019 max mem: 19788 +Test: [ 4400/21770] eta: 0:20:18 time: 0.0780 data: 0.0022 max mem: 19788 +Test: [ 4500/21770] eta: 0:20:11 time: 0.0675 data: 0.0021 max mem: 19788 +Test: [ 4600/21770] eta: 0:20:02 time: 0.0622 data: 0.0020 max mem: 19788 +Test: [ 4700/21770] eta: 0:19:53 time: 0.0679 data: 0.0018 max mem: 19788 +Test: [ 4800/21770] eta: 0:19:47 time: 0.0821 data: 0.0024 max mem: 19788 +Test: [ 4900/21770] eta: 0:19:41 time: 0.0666 data: 0.0020 max mem: 19788 +Test: [ 5000/21770] eta: 0:19:32 time: 0.0618 data: 0.0018 max mem: 19788 +Test: [ 5100/21770] eta: 0:19:22 time: 0.0611 data: 0.0017 max mem: 19788 +Test: [ 5200/21770] eta: 0:19:12 time: 0.0621 data: 0.0018 max mem: 19788 +Test: [ 5300/21770] eta: 0:19:05 time: 0.0817 data: 0.0025 max mem: 19788 +Test: [ 5400/21770] eta: 0:19:02 time: 0.0808 data: 0.0025 max mem: 19788 +Test: [ 5500/21770] eta: 0:18:57 time: 0.0665 data: 0.0017 max mem: 19788 +Test: [ 5600/21770] eta: 0:18:52 time: 0.0810 data: 0.0023 max mem: 19788 +Test: [ 5700/21770] eta: 0:18:48 time: 0.0813 data: 0.0026 max mem: 19788 +Test: [ 5800/21770] eta: 0:18:42 time: 0.0767 data: 0.0022 max mem: 19788 +Test: [ 5900/21770] eta: 0:18:36 time: 0.0788 data: 0.0024 max mem: 19788 +Test: [ 6000/21770] eta: 0:18:30 time: 0.0649 data: 0.0018 max mem: 19788 +Test: [ 6100/21770] eta: 0:18:22 time: 0.0616 data: 0.0018 max mem: 19788 +Test: [ 6200/21770] eta: 0:18:15 time: 0.0814 data: 0.0024 max mem: 19788 +Test: [ 6300/21770] eta: 0:18:11 time: 0.0747 data: 0.0020 max mem: 19788 +Test: [ 6400/21770] eta: 0:18:04 time: 0.0697 data: 0.0020 max mem: 19788 +Test: [ 6500/21770] eta: 0:17:56 time: 0.0636 data: 0.0020 max mem: 19788 +Test: [ 6600/21770] eta: 0:17:48 time: 0.0722 data: 0.0020 max mem: 19788 +Test: [ 6700/21770] eta: 0:17:42 time: 0.0710 data: 0.0022 max mem: 19788 +Test: [ 6800/21770] eta: 0:17:34 time: 0.0630 data: 0.0020 max mem: 19788 +Test: [ 6900/21770] eta: 0:17:29 time: 0.0813 data: 0.0026 max mem: 19788 +Test: [ 7000/21770] eta: 0:17:21 time: 0.0638 data: 0.0019 max mem: 19788 +Test: [ 7100/21770] eta: 0:17:15 time: 0.0638 data: 0.0017 max mem: 19788 +Test: [ 7200/21770] eta: 0:17:07 time: 0.0631 data: 0.0018 max mem: 19788 +Test: [ 7300/21770] eta: 0:16:58 time: 0.0620 data: 0.0019 max mem: 19788 +Test: [ 7400/21770] eta: 0:16:50 time: 0.0578 data: 0.0018 max mem: 19788 +Test: [ 7500/21770] eta: 0:16:43 time: 0.0775 data: 0.0025 max mem: 19788 +Test: [ 7600/21770] eta: 0:16:36 time: 0.0763 data: 0.0023 max mem: 19788 +Test: [ 7700/21770] eta: 0:16:30 time: 0.0677 data: 0.0019 max mem: 19788 +Test: [ 7800/21770] eta: 0:16:21 time: 0.0633 data: 0.0017 max mem: 19788 +Test: [ 7900/21770] eta: 0:16:13 time: 0.0771 data: 0.0022 max mem: 19788 +Test: [ 8000/21770] eta: 0:16:06 time: 0.0734 data: 0.0022 max mem: 19788 +Test: [ 8100/21770] eta: 0:15:59 time: 0.0628 data: 0.0017 max mem: 19788 +Test: [ 8200/21770] eta: 0:15:52 time: 0.0774 data: 0.0022 max mem: 19788 +Test: [ 8300/21770] eta: 0:15:44 time: 0.0635 data: 0.0019 max mem: 19788 +Test: [ 8400/21770] eta: 0:15:38 time: 0.0724 data: 0.0023 max mem: 19788 +Test: [ 8500/21770] eta: 0:15:30 time: 0.0628 data: 0.0017 max mem: 19788 +Test: [ 8600/21770] eta: 0:15:23 time: 0.0768 data: 0.0023 max mem: 19788 +Test: [ 8700/21770] eta: 0:15:16 time: 0.0668 data: 0.0018 max mem: 19788 +Test: [ 8800/21770] eta: 0:15:11 time: 0.0825 data: 0.0025 max mem: 19788 +Test: [ 8900/21770] eta: 0:15:04 time: 0.0640 data: 0.0018 max mem: 19788 +Test: [ 9000/21770] eta: 0:14:57 time: 0.0708 data: 0.0019 max mem: 19788 +Test: [ 9100/21770] eta: 0:14:49 time: 0.0758 data: 0.0022 max mem: 19788 +Test: [ 9200/21770] eta: 0:14:42 time: 0.0683 data: 0.0020 max mem: 19788 +Test: [ 9300/21770] eta: 0:14:33 time: 0.0602 data: 0.0018 max mem: 19788 +Test: [ 9400/21770] eta: 0:14:26 time: 0.0703 data: 0.0021 max mem: 19788 +Test: [ 9500/21770] eta: 0:14:19 time: 0.0631 data: 0.0018 max mem: 19788 +Test: [ 9600/21770] eta: 0:14:11 time: 0.0800 data: 0.0023 max mem: 19788 +Test: [ 9700/21770] eta: 0:14:04 time: 0.0635 data: 0.0017 max mem: 19788 +Test: [ 9800/21770] eta: 0:13:57 time: 0.0636 data: 0.0020 max mem: 19788 +Test: [ 9900/21770] eta: 0:13:49 time: 0.0683 data: 0.0019 max mem: 19788 +Test: [10000/21770] eta: 0:13:43 time: 0.0821 data: 0.0025 max mem: 19788 +Test: [10100/21770] eta: 0:13:37 time: 0.0640 data: 0.0019 max mem: 19788 +Test: [10200/21770] eta: 0:13:30 time: 0.0814 data: 0.0026 max mem: 19788 +Test: [10300/21770] eta: 0:13:24 time: 0.0817 data: 0.0022 max mem: 19788 +Test: [10400/21770] eta: 0:13:17 time: 0.0629 data: 0.0019 max mem: 19788 +Test: [10500/21770] eta: 0:13:11 time: 0.0741 data: 0.0020 max mem: 19788 +Test: [10600/21770] eta: 0:13:04 time: 0.0689 data: 0.0020 max mem: 19788 +Test: [10700/21770] eta: 0:12:56 time: 0.0631 data: 0.0018 max mem: 19788 +Test: [10800/21770] eta: 0:12:48 time: 0.0651 data: 0.0020 max mem: 19788 +Test: [10900/21770] eta: 0:12:41 time: 0.0626 data: 0.0018 max mem: 19788 +Test: [11000/21770] eta: 0:12:34 time: 0.0698 data: 0.0020 max mem: 19788 +Test: [11100/21770] eta: 0:12:27 time: 0.0748 data: 0.0021 max mem: 19788 +Test: [11200/21770] eta: 0:12:21 time: 0.0811 data: 0.0025 max mem: 19788 +Test: [11300/21770] eta: 0:12:14 time: 0.0720 data: 0.0022 max mem: 19788 +Test: [11400/21770] eta: 0:12:08 time: 0.0767 data: 0.0022 max mem: 19788 +Test: [11500/21770] eta: 0:12:02 time: 0.0811 data: 0.0025 max mem: 19788 +Test: [11600/21770] eta: 0:11:55 time: 0.0655 data: 0.0020 max mem: 19788 +Test: [11700/21770] eta: 0:11:49 time: 0.0813 data: 0.0025 max mem: 19788 +Test: [11800/21770] eta: 0:11:42 time: 0.0715 data: 0.0021 max mem: 19788 +Test: [11900/21770] eta: 0:11:35 time: 0.0749 data: 0.0023 max mem: 19788 +Test: [12000/21770] eta: 0:11:27 time: 0.0640 data: 0.0018 max mem: 19788 +Test: [12100/21770] eta: 0:11:20 time: 0.0640 data: 0.0019 max mem: 19788 +Test: [12200/21770] eta: 0:11:12 time: 0.0679 data: 0.0018 max mem: 19788 +Test: [12300/21770] eta: 0:11:05 time: 0.0715 data: 0.0020 max mem: 19788 +Test: [12400/21770] eta: 0:10:59 time: 0.0749 data: 0.0024 max mem: 19788 +Test: [12500/21770] eta: 0:10:51 time: 0.0622 data: 0.0018 max mem: 19788 +Test: [12600/21770] eta: 0:10:44 time: 0.0751 data: 0.0023 max mem: 19788 +Test: [12700/21770] eta: 0:10:37 time: 0.0685 data: 0.0021 max mem: 19788 +Test: [12800/21770] eta: 0:10:31 time: 0.0586 data: 0.0018 max mem: 19788 +Test: [12900/21770] eta: 0:10:24 time: 0.0811 data: 0.0025 max mem: 19788 +Test: [13000/21770] eta: 0:10:17 time: 0.0631 data: 0.0019 max mem: 19788 +Test: [13100/21770] eta: 0:10:10 time: 0.0690 data: 0.0022 max mem: 19788 +Test: [13200/21770] eta: 0:10:03 time: 0.0633 data: 0.0021 max mem: 19788 +Test: [13300/21770] eta: 0:09:56 time: 0.0827 data: 0.0027 max mem: 19788 +Test: [13400/21770] eta: 0:09:49 time: 0.0815 data: 0.0024 max mem: 19788 +Test: [13500/21770] eta: 0:09:42 time: 0.0787 data: 0.0022 max mem: 19788 +Test: [13600/21770] eta: 0:09:35 time: 0.0703 data: 0.0020 max mem: 19788 +Test: [13700/21770] eta: 0:09:28 time: 0.0652 data: 0.0018 max mem: 19788 +Test: [13800/21770] eta: 0:09:21 time: 0.0782 data: 0.0023 max mem: 19788 +Test: [13900/21770] eta: 0:09:14 time: 0.0825 data: 0.0024 max mem: 19788 +Test: [14000/21770] eta: 0:09:07 time: 0.0627 data: 0.0017 max mem: 19788 +Test: [14100/21770] eta: 0:09:00 time: 0.0815 data: 0.0025 max mem: 19788 +Test: [14200/21770] eta: 0:08:53 time: 0.0822 data: 0.0025 max mem: 19788 +Test: [14300/21770] eta: 0:08:46 time: 0.0652 data: 0.0018 max mem: 19788 +Test: [14400/21770] eta: 0:08:39 time: 0.0607 data: 0.0018 max mem: 19788 +Test: [14500/21770] eta: 0:08:31 time: 0.0624 data: 0.0019 max mem: 19788 +Test: [14600/21770] eta: 0:08:24 time: 0.0657 data: 0.0020 max mem: 19788 +Test: [14700/21770] eta: 0:08:17 time: 0.0633 data: 0.0018 max mem: 19788 +Test: [14800/21770] eta: 0:08:10 time: 0.0708 data: 0.0022 max mem: 19788 +Test: [14900/21770] eta: 0:08:03 time: 0.0813 data: 0.0025 max mem: 19788 +Test: [15000/21770] eta: 0:07:56 time: 0.0809 data: 0.0025 max mem: 19788 +Test: [15100/21770] eta: 0:07:49 time: 0.0691 data: 0.0019 max mem: 19788 +Test: [15200/21770] eta: 0:07:43 time: 0.0819 data: 0.0019 max mem: 19788 +Test: [15300/21770] eta: 0:07:36 time: 0.0696 data: 0.0020 max mem: 19788 +Test: [15400/21770] eta: 0:07:28 time: 0.0707 data: 0.0022 max mem: 19788 +Test: [15500/21770] eta: 0:07:22 time: 0.0825 data: 0.0023 max mem: 19788 +Test: [15600/21770] eta: 0:07:15 time: 0.0789 data: 0.0024 max mem: 19788 +Test: [15700/21770] eta: 0:07:08 time: 0.0721 data: 0.0021 max mem: 19788 +Test: [15800/21770] eta: 0:07:00 time: 0.0641 data: 0.0017 max mem: 19788 +Test: [15900/21770] eta: 0:06:53 time: 0.0642 data: 0.0021 max mem: 19788 +Test: [16000/21770] eta: 0:06:46 time: 0.0807 data: 0.0026 max mem: 19788 +Test: [16100/21770] eta: 0:06:39 time: 0.0827 data: 0.0021 max mem: 19788 +Test: [16200/21770] eta: 0:06:32 time: 0.0607 data: 0.0017 max mem: 19788 +Test: [16300/21770] eta: 0:06:25 time: 0.0806 data: 0.0025 max mem: 19788 +Test: [16400/21770] eta: 0:06:18 time: 0.0672 data: 0.0022 max mem: 19788 +Test: [16500/21770] eta: 0:06:11 time: 0.0705 data: 0.0020 max mem: 19788 +Test: [16600/21770] eta: 0:06:04 time: 0.0602 data: 0.0019 max mem: 19788 +Test: [16700/21770] eta: 0:05:56 time: 0.0626 data: 0.0018 max mem: 19788 +Test: [16800/21770] eta: 0:05:49 time: 0.0621 data: 0.0018 max mem: 19788 +Test: [16900/21770] eta: 0:05:42 time: 0.0613 data: 0.0020 max mem: 19788 +Test: [17000/21770] eta: 0:05:35 time: 0.0798 data: 0.0022 max mem: 19788 +Test: [17100/21770] eta: 0:05:28 time: 0.0784 data: 0.0022 max mem: 19788 +Test: [17200/21770] eta: 0:05:21 time: 0.0650 data: 0.0019 max mem: 19788 +Test: [17300/21770] eta: 0:05:14 time: 0.0635 data: 0.0019 max mem: 19788 +Test: [17400/21770] eta: 0:05:07 time: 0.0624 data: 0.0018 max mem: 19788 +Test: [17500/21770] eta: 0:04:59 time: 0.0712 data: 0.0020 max mem: 19788 +Test: [17600/21770] eta: 0:04:52 time: 0.0703 data: 0.0018 max mem: 19788 +Test: [17700/21770] eta: 0:04:45 time: 0.0593 data: 0.0019 max mem: 19788 +Test: [17800/21770] eta: 0:04:38 time: 0.0641 data: 0.0017 max mem: 19788 +Test: [17900/21770] eta: 0:04:31 time: 0.0655 data: 0.0020 max mem: 19788 +Test: [18000/21770] eta: 0:04:24 time: 0.0817 data: 0.0024 max mem: 19788 +Test: [18100/21770] eta: 0:04:17 time: 0.0616 data: 0.0018 max mem: 19788 +Test: [18200/21770] eta: 0:04:10 time: 0.0625 data: 0.0019 max mem: 19788 +Test: [18300/21770] eta: 0:04:03 time: 0.0637 data: 0.0017 max mem: 19788 +Test: [18400/21770] eta: 0:03:56 time: 0.0608 data: 0.0016 max mem: 19788 +Test: [18500/21770] eta: 0:03:49 time: 0.0815 data: 0.0024 max mem: 19788 +Test: [18600/21770] eta: 0:03:42 time: 0.0622 data: 0.0019 max mem: 19788 +Test: [18700/21770] eta: 0:03:35 time: 0.0822 data: 0.0023 max mem: 19788 +Test: [18800/21770] eta: 0:03:28 time: 0.0618 data: 0.0019 max mem: 19788 +Test: [18900/21770] eta: 0:03:21 time: 0.0803 data: 0.0024 max mem: 19788 +Test: [19000/21770] eta: 0:03:14 time: 0.0812 data: 0.0022 max mem: 19788 +Test: [19100/21770] eta: 0:03:07 time: 0.0607 data: 0.0019 max mem: 19788 +Test: [19200/21770] eta: 0:03:00 time: 0.0626 data: 0.0018 max mem: 19788 +Test: [19300/21770] eta: 0:02:53 time: 0.0716 data: 0.0021 max mem: 19788 +Test: [19400/21770] eta: 0:02:46 time: 0.0614 data: 0.0018 max mem: 19788 +Test: [19500/21770] eta: 0:02:39 time: 0.0632 data: 0.0019 max mem: 19788 +Test: [19600/21770] eta: 0:02:32 time: 0.0817 data: 0.0024 max mem: 19788 +Test: [19700/21770] eta: 0:02:25 time: 0.0812 data: 0.0024 max mem: 19788 +Test: [19800/21770] eta: 0:02:18 time: 0.0603 data: 0.0019 max mem: 19788 +Test: [19900/21770] eta: 0:02:11 time: 0.0734 data: 0.0020 max mem: 19788 +Test: [20000/21770] eta: 0:02:04 time: 0.0769 data: 0.0021 max mem: 19788 +Test: [20100/21770] eta: 0:01:57 time: 0.0736 data: 0.0020 max mem: 19788 +Test: [20200/21770] eta: 0:01:50 time: 0.0812 data: 0.0024 max mem: 19788 +Test: [20300/21770] eta: 0:01:43 time: 0.0610 data: 0.0019 max mem: 19788 +Test: [20400/21770] eta: 0:01:36 time: 0.0632 data: 0.0019 max mem: 19788 +Test: [20500/21770] eta: 0:01:29 time: 0.0615 data: 0.0018 max mem: 19788 +Test: [20600/21770] eta: 0:01:22 time: 0.0633 data: 0.0018 max mem: 19788 +Test: [20700/21770] eta: 0:01:15 time: 0.0652 data: 0.0019 max mem: 19788 +Test: [20800/21770] eta: 0:01:08 time: 0.0823 data: 0.0024 max mem: 19788 +Test: [20900/21770] eta: 0:01:01 time: 0.0704 data: 0.0020 max mem: 19788 +Test: [21000/21770] eta: 0:00:53 time: 0.0646 data: 0.0019 max mem: 19788 +Test: [21100/21770] eta: 0:00:46 time: 0.0609 data: 0.0018 max mem: 19788 +Test: [21200/21770] eta: 0:00:39 time: 0.0638 data: 0.0018 max mem: 19788 +Test: [21300/21770] eta: 0:00:32 time: 0.0826 data: 0.0025 max mem: 19788 +Test: [21400/21770] eta: 0:00:25 time: 0.0628 data: 0.0019 max mem: 19788 +Test: [21500/21770] eta: 0:00:18 time: 0.0643 data: 0.0018 max mem: 19788 +Test: [21600/21770] eta: 0:00:11 time: 0.0649 data: 0.0020 max mem: 19788 +Test: [21700/21770] eta: 0:00:04 time: 0.0628 data: 0.0019 max mem: 19788 +Test: Total time: 0:25:27 +Final results: +Mean IoU is 62.81 + + precision@0.5 = 69.32 + precision@0.6 = 63.97 + precision@0.7 = 57.52 + precision@0.8 = 46.91 + precision@0.9 = 23.32 + overall IoU = 63.42 + mean IoU = 62.81 + +Mean accuracy for one-to-zero sample is 83.67 + +Average object IoU 0.6281319694101962 +Overall IoU 63.419151306152344 +Epoch: [19] [ 0/2138] eta: 7:14:15 lr: 2.7996559986907e-05 loss: 0.0349 (0.0349) time: 12.1868 data: 2.5747 max mem: 19788 +Epoch: [19] [ 10/2138] eta: 2:39:45 lr: 2.7990947766798976e-05 loss: 0.0265 (0.0273) time: 4.5046 data: 0.2362 max mem: 19788 +Epoch: [19] [ 20/2138] eta: 2:26:16 lr: 2.798533542165959e-05 loss: 0.0253 (0.0272) time: 3.7417 data: 0.0020 max mem: 19788 +Epoch: [19] [ 30/2138] eta: 2:20:54 lr: 2.7979722951458194e-05 loss: 0.0253 (0.0271) time: 3.7391 data: 0.0023 max mem: 19788 +Epoch: [19] [ 40/2138] eta: 2:18:59 lr: 2.7974110356164125e-05 loss: 0.0287 (0.0287) time: 3.7981 data: 0.0030 max mem: 19788 +Epoch: [19] [ 50/2138] eta: 2:16:04 lr: 2.7968497635746715e-05 loss: 0.0287 (0.0300) time: 3.7540 data: 0.0031 max mem: 19788 +Epoch: [19] [ 60/2138] eta: 2:13:58 lr: 2.796288479017527e-05 loss: 0.0271 (0.0299) time: 3.6497 data: 0.0032 max mem: 19788 +Epoch: [19] [ 70/2138] eta: 2:13:01 lr: 2.795727181941908e-05 loss: 0.0281 (0.0303) time: 3.7299 data: 0.0031 max mem: 19788 +Epoch: [19] [ 80/2138] eta: 2:11:24 lr: 2.7951658723447426e-05 loss: 0.0300 (0.0304) time: 3.7173 data: 0.0030 max mem: 19788 +Epoch: [19] [ 90/2138] eta: 2:10:02 lr: 2.7946045502229588e-05 loss: 0.0300 (0.0306) time: 3.6336 data: 0.0030 max mem: 19788 +Epoch: [19] [ 100/2138] eta: 2:08:55 lr: 2.794043215573481e-05 loss: 0.0301 (0.0305) time: 3.6529 data: 0.0030 max mem: 19788 +Epoch: [19] [ 110/2138] eta: 2:07:50 lr: 2.7934818683932323e-05 loss: 0.0313 (0.0313) time: 3.6572 data: 0.0031 max mem: 19788 +Epoch: [19] [ 120/2138] eta: 2:06:46 lr: 2.7929205086791353e-05 loss: 0.0329 (0.0317) time: 3.6362 data: 0.0031 max mem: 19788 +Epoch: [19] [ 130/2138] eta: 2:05:47 lr: 2.7923591364281122e-05 loss: 0.0330 (0.0329) time: 3.6284 data: 0.0029 max mem: 19788 +Epoch: [19] [ 140/2138] eta: 2:04:57 lr: 2.7917977516370807e-05 loss: 0.0310 (0.0327) time: 3.6489 data: 0.0029 max mem: 19788 +Epoch: [19] [ 150/2138] eta: 2:04:46 lr: 2.791236354302959e-05 loss: 0.0297 (0.0324) time: 3.8144 data: 0.0030 max mem: 19788 +Epoch: [19] [ 160/2138] eta: 2:04:12 lr: 2.790674944422664e-05 loss: 0.0311 (0.0329) time: 3.8739 data: 0.0032 max mem: 19788 +Epoch: [19] [ 170/2138] eta: 2:03:49 lr: 2.7901135219931124e-05 loss: 0.0347 (0.0329) time: 3.8416 data: 0.0033 max mem: 19788 +Epoch: [19] [ 180/2138] eta: 2:03:29 lr: 2.7895520870112158e-05 loss: 0.0369 (0.0331) time: 3.9171 data: 0.0031 max mem: 19788 +Epoch: [19] [ 190/2138] eta: 2:02:36 lr: 2.7889906394738863e-05 loss: 0.0357 (0.0330) time: 3.7872 data: 0.0030 max mem: 19788 +Epoch: [19] [ 200/2138] eta: 2:01:44 lr: 2.7884291793780354e-05 loss: 0.0250 (0.0325) time: 3.6345 data: 0.0029 max mem: 19788 +Epoch: [19] [ 210/2138] eta: 2:00:57 lr: 2.7878677067205727e-05 loss: 0.0338 (0.0337) time: 3.6522 data: 0.0028 max mem: 19788 +Epoch: [19] [ 220/2138] eta: 2:00:11 lr: 2.7873062214984052e-05 loss: 0.0356 (0.0336) time: 3.6649 data: 0.0029 max mem: 19788 +Epoch: [19] [ 230/2138] eta: 1:59:22 lr: 2.7867447237084392e-05 loss: 0.0351 (0.0338) time: 3.6449 data: 0.0030 max mem: 19788 +Epoch: [19] [ 240/2138] eta: 1:58:47 lr: 2.7861832133475813e-05 loss: 0.0335 (0.0337) time: 3.7091 data: 0.0030 max mem: 19788 +Epoch: [19] [ 250/2138] eta: 1:58:17 lr: 2.7856216904127335e-05 loss: 0.0263 (0.0336) time: 3.8199 data: 0.0030 max mem: 19788 +Epoch: [19] [ 260/2138] eta: 1:57:56 lr: 2.7850601549007976e-05 loss: 0.0252 (0.0333) time: 3.9179 data: 0.0030 max mem: 19788 +Epoch: [19] [ 270/2138] eta: 1:57:25 lr: 2.7844986068086748e-05 loss: 0.0283 (0.0335) time: 3.9242 data: 0.0031 max mem: 19788 +Epoch: [19] [ 280/2138] eta: 1:56:54 lr: 2.7839370461332647e-05 loss: 0.0315 (0.0335) time: 3.8691 data: 0.0030 max mem: 19788 +Epoch: [19] [ 290/2138] eta: 1:56:15 lr: 2.7833754728714644e-05 loss: 0.0302 (0.0334) time: 3.8156 data: 0.0030 max mem: 19788 +Epoch: [19] [ 300/2138] eta: 1:55:32 lr: 2.7828138870201693e-05 loss: 0.0291 (0.0333) time: 3.7231 data: 0.0031 max mem: 19788 +Epoch: [19] [ 310/2138] eta: 1:54:45 lr: 2.7822522885762753e-05 loss: 0.0291 (0.0331) time: 3.6515 data: 0.0029 max mem: 19788 +Epoch: [19] [ 320/2138] eta: 1:54:02 lr: 2.781690677536675e-05 loss: 0.0289 (0.0331) time: 3.6446 data: 0.0028 max mem: 19788 +Epoch: [19] [ 330/2138] eta: 1:53:19 lr: 2.781129053898261e-05 loss: 0.0289 (0.0332) time: 3.6658 data: 0.0029 max mem: 19788 +Epoch: [19] [ 340/2138] eta: 1:52:33 lr: 2.7805674176579223e-05 loss: 0.0281 (0.0330) time: 3.6347 data: 0.0029 max mem: 19788 +Epoch: [19] [ 350/2138] eta: 1:51:51 lr: 2.7800057688125484e-05 loss: 0.0290 (0.0330) time: 3.6382 data: 0.0028 max mem: 19788 +Epoch: [19] [ 360/2138] eta: 1:51:08 lr: 2.7794441073590278e-05 loss: 0.0290 (0.0329) time: 3.6553 data: 0.0027 max mem: 19788 +Epoch: [19] [ 370/2138] eta: 1:50:27 lr: 2.7788824332942454e-05 loss: 0.0313 (0.0331) time: 3.6616 data: 0.0027 max mem: 19788 +Epoch: [19] [ 380/2138] eta: 1:49:47 lr: 2.7783207466150845e-05 loss: 0.0313 (0.0331) time: 3.6830 data: 0.0027 max mem: 19788 +Epoch: [19] [ 390/2138] eta: 1:49:04 lr: 2.77775904731843e-05 loss: 0.0283 (0.0331) time: 3.6626 data: 0.0028 max mem: 19788 +Epoch: [19] [ 400/2138] eta: 1:48:24 lr: 2.7771973354011634e-05 loss: 0.0297 (0.0330) time: 3.6538 data: 0.0028 max mem: 19788 +Epoch: [19] [ 410/2138] eta: 1:47:42 lr: 2.7766356108601637e-05 loss: 0.0311 (0.0332) time: 3.6518 data: 0.0027 max mem: 19788 +Epoch: [19] [ 420/2138] eta: 1:47:02 lr: 2.7760738736923093e-05 loss: 0.0322 (0.0331) time: 3.6552 data: 0.0028 max mem: 19788 +Epoch: [19] [ 430/2138] eta: 1:46:21 lr: 2.775512123894478e-05 loss: 0.0297 (0.0331) time: 3.6591 data: 0.0028 max mem: 19788 +Epoch: [19] [ 440/2138] eta: 1:45:40 lr: 2.774950361463546e-05 loss: 0.0281 (0.0331) time: 3.6505 data: 0.0027 max mem: 19788 +Epoch: [19] [ 450/2138] eta: 1:45:01 lr: 2.7743885863963865e-05 loss: 0.0281 (0.0330) time: 3.6695 data: 0.0027 max mem: 19788 +Epoch: [19] [ 460/2138] eta: 1:44:20 lr: 2.773826798689872e-05 loss: 0.0316 (0.0330) time: 3.6593 data: 0.0026 max mem: 19788 +Epoch: [19] [ 470/2138] eta: 1:43:41 lr: 2.773264998340874e-05 loss: 0.0296 (0.0329) time: 3.6568 data: 0.0027 max mem: 19788 +Epoch: [19] [ 480/2138] eta: 1:43:00 lr: 2.772703185346263e-05 loss: 0.0293 (0.0329) time: 3.6569 data: 0.0028 max mem: 19788 +Epoch: [19] [ 490/2138] eta: 1:42:22 lr: 2.7721413597029073e-05 loss: 0.0289 (0.0328) time: 3.6668 data: 0.0030 max mem: 19788 +Epoch: [19] [ 500/2138] eta: 1:41:43 lr: 2.7715795214076718e-05 loss: 0.0289 (0.0327) time: 3.6819 data: 0.0030 max mem: 19788 +Epoch: [19] [ 510/2138] eta: 1:41:03 lr: 2.7710176704574232e-05 loss: 0.0313 (0.0327) time: 3.6625 data: 0.0030 max mem: 19788 +Epoch: [19] [ 520/2138] eta: 1:40:24 lr: 2.7704558068490255e-05 loss: 0.0314 (0.0327) time: 3.6628 data: 0.0029 max mem: 19788 +Epoch: [19] [ 530/2138] eta: 1:39:45 lr: 2.76989393057934e-05 loss: 0.0263 (0.0326) time: 3.6594 data: 0.0029 max mem: 19788 +Epoch: [19] [ 540/2138] eta: 1:39:07 lr: 2.769332041645228e-05 loss: 0.0250 (0.0325) time: 3.6706 data: 0.0029 max mem: 19788 +Epoch: [19] [ 550/2138] eta: 1:38:28 lr: 2.7687701400435495e-05 loss: 0.0302 (0.0325) time: 3.6835 data: 0.0029 max mem: 19788 +Epoch: [19] [ 560/2138] eta: 1:37:49 lr: 2.7682082257711615e-05 loss: 0.0312 (0.0324) time: 3.6606 data: 0.0028 max mem: 19788 +Epoch: [19] [ 570/2138] eta: 1:37:10 lr: 2.76764629882492e-05 loss: 0.0269 (0.0325) time: 3.6555 data: 0.0027 max mem: 19788 +Epoch: [19] [ 580/2138] eta: 1:36:30 lr: 2.767084359201681e-05 loss: 0.0305 (0.0324) time: 3.6428 data: 0.0027 max mem: 19788 +Epoch: [19] [ 590/2138] eta: 1:35:52 lr: 2.766522406898298e-05 loss: 0.0305 (0.0324) time: 3.6404 data: 0.0027 max mem: 19788 +Epoch: [19] [ 600/2138] eta: 1:35:12 lr: 2.765960441911622e-05 loss: 0.0262 (0.0325) time: 3.6462 data: 0.0027 max mem: 19788 +Epoch: [19] [ 610/2138] eta: 1:34:34 lr: 2.7653984642385033e-05 loss: 0.0249 (0.0325) time: 3.6499 data: 0.0026 max mem: 19788 +Epoch: [19] [ 620/2138] eta: 1:33:56 lr: 2.764836473875791e-05 loss: 0.0304 (0.0325) time: 3.6628 data: 0.0026 max mem: 19788 +Epoch: [19] [ 630/2138] eta: 1:33:17 lr: 2.764274470820333e-05 loss: 0.0270 (0.0324) time: 3.6515 data: 0.0027 max mem: 19788 +Epoch: [19] [ 640/2138] eta: 1:32:39 lr: 2.763712455068976e-05 loss: 0.0252 (0.0323) time: 3.6600 data: 0.0027 max mem: 19788 +Epoch: [19] [ 650/2138] eta: 1:32:00 lr: 2.7631504266185622e-05 loss: 0.0268 (0.0323) time: 3.6565 data: 0.0027 max mem: 19788 +Epoch: [19] [ 660/2138] eta: 1:31:22 lr: 2.762588385465935e-05 loss: 0.0289 (0.0323) time: 3.6504 data: 0.0027 max mem: 19788 +Epoch: [19] [ 670/2138] eta: 1:30:44 lr: 2.762026331607938e-05 loss: 0.0285 (0.0322) time: 3.6643 data: 0.0027 max mem: 19788 +Epoch: [19] [ 680/2138] eta: 1:30:05 lr: 2.7614642650414093e-05 loss: 0.0304 (0.0322) time: 3.6554 data: 0.0029 max mem: 19788 +Epoch: [19] [ 690/2138] eta: 1:29:27 lr: 2.7609021857631867e-05 loss: 0.0335 (0.0322) time: 3.6528 data: 0.0030 max mem: 19788 +Epoch: [19] [ 700/2138] eta: 1:28:49 lr: 2.7603400937701086e-05 loss: 0.0303 (0.0322) time: 3.6497 data: 0.0028 max mem: 19788 +Epoch: [19] [ 710/2138] eta: 1:28:11 lr: 2.7597779890590103e-05 loss: 0.0294 (0.0322) time: 3.6477 data: 0.0028 max mem: 19788 +Epoch: [19] [ 720/2138] eta: 1:27:33 lr: 2.7592158716267254e-05 loss: 0.0304 (0.0322) time: 3.6545 data: 0.0028 max mem: 19788 +Epoch: [19] [ 730/2138] eta: 1:26:56 lr: 2.758653741470085e-05 loss: 0.0304 (0.0323) time: 3.6867 data: 0.0027 max mem: 19788 +Epoch: [19] [ 740/2138] eta: 1:26:21 lr: 2.7580915985859218e-05 loss: 0.0272 (0.0322) time: 3.7549 data: 0.0029 max mem: 19788 +Epoch: [19] [ 750/2138] eta: 1:25:50 lr: 2.7575294429710653e-05 loss: 0.0278 (0.0322) time: 3.9371 data: 0.0031 max mem: 19788 +Epoch: [19] [ 760/2138] eta: 1:25:14 lr: 2.7569672746223424e-05 loss: 0.0297 (0.0322) time: 3.9139 data: 0.0031 max mem: 19788 +Epoch: [19] [ 770/2138] eta: 1:24:40 lr: 2.7564050935365794e-05 loss: 0.0323 (0.0322) time: 3.8102 data: 0.0030 max mem: 19788 +Epoch: [19] [ 780/2138] eta: 1:24:06 lr: 2.7558428997106013e-05 loss: 0.0343 (0.0323) time: 3.8952 data: 0.0030 max mem: 19788 +Epoch: [19] [ 790/2138] eta: 1:23:28 lr: 2.7552806931412324e-05 loss: 0.0306 (0.0323) time: 3.7918 data: 0.0029 max mem: 19788 +Epoch: [19] [ 800/2138] eta: 1:22:50 lr: 2.754718473825294e-05 loss: 0.0268 (0.0322) time: 3.6709 data: 0.0028 max mem: 19788 +Epoch: [19] [ 810/2138] eta: 1:22:13 lr: 2.7541562417596056e-05 loss: 0.0260 (0.0322) time: 3.6744 data: 0.0028 max mem: 19788 +Epoch: [19] [ 820/2138] eta: 1:21:34 lr: 2.7535939969409867e-05 loss: 0.0260 (0.0321) time: 3.6665 data: 0.0030 max mem: 19788 +Epoch: [19] [ 830/2138] eta: 1:20:56 lr: 2.7530317393662553e-05 loss: 0.0250 (0.0321) time: 3.6566 data: 0.0030 max mem: 19788 +Epoch: [19] [ 840/2138] eta: 1:20:20 lr: 2.752469469032226e-05 loss: 0.0243 (0.0320) time: 3.6932 data: 0.0030 max mem: 19788 +Epoch: [19] [ 850/2138] eta: 1:19:43 lr: 2.751907185935713e-05 loss: 0.0243 (0.0320) time: 3.7264 data: 0.0030 max mem: 19788 +Epoch: [19] [ 860/2138] eta: 1:19:05 lr: 2.7513448900735305e-05 loss: 0.0274 (0.0320) time: 3.6997 data: 0.0031 max mem: 19788 +Epoch: [19] [ 870/2138] eta: 1:18:31 lr: 2.7507825814424885e-05 loss: 0.0311 (0.0320) time: 3.8190 data: 0.0032 max mem: 19788 +Epoch: [19] [ 880/2138] eta: 1:17:56 lr: 2.7502202600393973e-05 loss: 0.0297 (0.0319) time: 3.8959 data: 0.0029 max mem: 19788 +Epoch: [19] [ 890/2138] eta: 1:17:21 lr: 2.7496579258610637e-05 loss: 0.0277 (0.0319) time: 3.8549 data: 0.0028 max mem: 19788 +Epoch: [19] [ 900/2138] eta: 1:16:45 lr: 2.7490955789042973e-05 loss: 0.0299 (0.0320) time: 3.8292 data: 0.0029 max mem: 19788 +Epoch: [19] [ 910/2138] eta: 1:16:08 lr: 2.7485332191659002e-05 loss: 0.0288 (0.0320) time: 3.7857 data: 0.0031 max mem: 19788 +Epoch: [19] [ 920/2138] eta: 1:15:32 lr: 2.7479708466426772e-05 loss: 0.0279 (0.0320) time: 3.7786 data: 0.0031 max mem: 19788 +Epoch: [19] [ 930/2138] eta: 1:14:55 lr: 2.7474084613314305e-05 loss: 0.0272 (0.0319) time: 3.7656 data: 0.0032 max mem: 19788 +Epoch: [19] [ 940/2138] eta: 1:14:22 lr: 2.746846063228961e-05 loss: 0.0275 (0.0320) time: 3.8994 data: 0.0032 max mem: 19788 +Epoch: [19] [ 950/2138] eta: 1:13:45 lr: 2.7462836523320674e-05 loss: 0.0279 (0.0320) time: 3.8832 data: 0.0031 max mem: 19788 +Epoch: [19] [ 960/2138] eta: 1:13:07 lr: 2.745721228637546e-05 loss: 0.0294 (0.0320) time: 3.6975 data: 0.0032 max mem: 19788 +Epoch: [19] [ 970/2138] eta: 1:12:30 lr: 2.7451587921421947e-05 loss: 0.0280 (0.0319) time: 3.6997 data: 0.0030 max mem: 19788 +Epoch: [19] [ 980/2138] eta: 1:11:53 lr: 2.744596342842807e-05 loss: 0.0265 (0.0319) time: 3.7480 data: 0.0030 max mem: 19788 +Epoch: [19] [ 990/2138] eta: 1:11:15 lr: 2.744033880736176e-05 loss: 0.0300 (0.0319) time: 3.7308 data: 0.0032 max mem: 19788 +Epoch: [19] [1000/2138] eta: 1:10:38 lr: 2.7434714058190925e-05 loss: 0.0302 (0.0319) time: 3.6986 data: 0.0030 max mem: 19788 +Epoch: [19] [1010/2138] eta: 1:10:00 lr: 2.742908918088347e-05 loss: 0.0281 (0.0319) time: 3.6786 data: 0.0029 max mem: 19788 +Epoch: [19] [1020/2138] eta: 1:09:22 lr: 2.7423464175407283e-05 loss: 0.0267 (0.0318) time: 3.6680 data: 0.0029 max mem: 19788 +Epoch: [19] [1030/2138] eta: 1:08:45 lr: 2.741783904173022e-05 loss: 0.0260 (0.0318) time: 3.7344 data: 0.0029 max mem: 19788 +Epoch: [19] [1040/2138] eta: 1:08:08 lr: 2.7412213779820135e-05 loss: 0.0294 (0.0318) time: 3.7334 data: 0.0029 max mem: 19788 +Epoch: [19] [1050/2138] eta: 1:07:31 lr: 2.7406588389644866e-05 loss: 0.0305 (0.0318) time: 3.6995 data: 0.0029 max mem: 19788 +Epoch: [19] [1060/2138] eta: 1:06:53 lr: 2.740096287117224e-05 loss: 0.0304 (0.0318) time: 3.7021 data: 0.0028 max mem: 19788 +Epoch: [19] [1070/2138] eta: 1:06:16 lr: 2.7395337224370066e-05 loss: 0.0290 (0.0318) time: 3.7082 data: 0.0030 max mem: 19788 +Epoch: [19] [1080/2138] eta: 1:05:38 lr: 2.738971144920612e-05 loss: 0.0279 (0.0317) time: 3.7127 data: 0.0032 max mem: 19788 +Epoch: [19] [1090/2138] eta: 1:05:01 lr: 2.7384085545648186e-05 loss: 0.0280 (0.0317) time: 3.6950 data: 0.0032 max mem: 19788 +Epoch: [19] [1100/2138] eta: 1:04:23 lr: 2.737845951366403e-05 loss: 0.0318 (0.0318) time: 3.7092 data: 0.0030 max mem: 19788 +Epoch: [19] [1110/2138] eta: 1:03:46 lr: 2.737283335322138e-05 loss: 0.0297 (0.0318) time: 3.6875 data: 0.0030 max mem: 19788 +Epoch: [19] [1120/2138] eta: 1:03:08 lr: 2.7367207064287975e-05 loss: 0.0303 (0.0318) time: 3.6835 data: 0.0031 max mem: 19788 +Epoch: [19] [1130/2138] eta: 1:02:31 lr: 2.736158064683153e-05 loss: 0.0303 (0.0318) time: 3.6865 data: 0.0031 max mem: 19788 +Epoch: [19] [1140/2138] eta: 1:01:54 lr: 2.735595410081974e-05 loss: 0.0286 (0.0318) time: 3.7121 data: 0.0032 max mem: 19788 +Epoch: [19] [1150/2138] eta: 1:01:16 lr: 2.7350327426220286e-05 loss: 0.0281 (0.0318) time: 3.7414 data: 0.0030 max mem: 19788 +Epoch: [19] [1160/2138] eta: 1:00:39 lr: 2.7344700623000836e-05 loss: 0.0270 (0.0318) time: 3.7254 data: 0.0030 max mem: 19788 +Epoch: [19] [1170/2138] eta: 1:00:02 lr: 2.7339073691129042e-05 loss: 0.0348 (0.0318) time: 3.7014 data: 0.0031 max mem: 19788 +Epoch: [19] [1180/2138] eta: 0:59:24 lr: 2.733344663057254e-05 loss: 0.0334 (0.0319) time: 3.6792 data: 0.0030 max mem: 19788 +Epoch: [19] [1190/2138] eta: 0:58:47 lr: 2.7327819441298946e-05 loss: 0.0334 (0.0319) time: 3.6780 data: 0.0030 max mem: 19788 +Epoch: [19] [1200/2138] eta: 0:58:09 lr: 2.732219212327587e-05 loss: 0.0307 (0.0319) time: 3.6763 data: 0.0029 max mem: 19788 +Epoch: [19] [1210/2138] eta: 0:57:32 lr: 2.73165646764709e-05 loss: 0.0298 (0.0318) time: 3.6895 data: 0.0029 max mem: 19788 +Epoch: [19] [1220/2138] eta: 0:56:55 lr: 2.731093710085161e-05 loss: 0.0263 (0.0319) time: 3.7177 data: 0.0029 max mem: 19788 +Epoch: [19] [1230/2138] eta: 0:56:19 lr: 2.7305309396385546e-05 loss: 0.0270 (0.0318) time: 3.8010 data: 0.0031 max mem: 19788 +Epoch: [19] [1240/2138] eta: 0:55:42 lr: 2.729968156304027e-05 loss: 0.0308 (0.0318) time: 3.8445 data: 0.0031 max mem: 19788 +Epoch: [19] [1250/2138] eta: 0:55:06 lr: 2.7294053600783303e-05 loss: 0.0298 (0.0318) time: 3.8438 data: 0.0029 max mem: 19788 +Epoch: [19] [1260/2138] eta: 0:54:29 lr: 2.728842550958215e-05 loss: 0.0250 (0.0318) time: 3.8435 data: 0.0029 max mem: 19788 +Epoch: [19] [1270/2138] eta: 0:53:52 lr: 2.7282797289404298e-05 loss: 0.0259 (0.0318) time: 3.7422 data: 0.0028 max mem: 19788 +Epoch: [19] [1280/2138] eta: 0:53:14 lr: 2.7277168940217247e-05 loss: 0.0259 (0.0317) time: 3.6857 data: 0.0028 max mem: 19788 +Epoch: [19] [1290/2138] eta: 0:52:38 lr: 2.7271540461988453e-05 loss: 0.0279 (0.0317) time: 3.7927 data: 0.0028 max mem: 19788 +Epoch: [19] [1300/2138] eta: 0:52:01 lr: 2.726591185468536e-05 loss: 0.0285 (0.0317) time: 3.8473 data: 0.0031 max mem: 19788 +Epoch: [19] [1310/2138] eta: 0:51:25 lr: 2.7260283118275402e-05 loss: 0.0287 (0.0317) time: 3.8330 data: 0.0031 max mem: 19788 +Epoch: [19] [1320/2138] eta: 0:50:48 lr: 2.7254654252726004e-05 loss: 0.0323 (0.0317) time: 3.7917 data: 0.0030 max mem: 19788 +Epoch: [19] [1330/2138] eta: 0:50:11 lr: 2.7249025258004556e-05 loss: 0.0282 (0.0317) time: 3.7810 data: 0.0031 max mem: 19788 +Epoch: [19] [1340/2138] eta: 0:49:34 lr: 2.7243396134078458e-05 loss: 0.0266 (0.0317) time: 3.8193 data: 0.0031 max mem: 19788 +Epoch: [19] [1350/2138] eta: 0:48:57 lr: 2.723776688091506e-05 loss: 0.0374 (0.0317) time: 3.7953 data: 0.0030 max mem: 19788 +Epoch: [19] [1360/2138] eta: 0:48:21 lr: 2.723213749848173e-05 loss: 0.0321 (0.0317) time: 3.8346 data: 0.0029 max mem: 19788 +Epoch: [19] [1370/2138] eta: 0:47:45 lr: 2.7226507986745808e-05 loss: 0.0295 (0.0317) time: 3.9522 data: 0.0031 max mem: 19788 +Epoch: [19] [1380/2138] eta: 0:47:12 lr: 2.7220878345674612e-05 loss: 0.0303 (0.0317) time: 4.2514 data: 0.0031 max mem: 19788 +Epoch: [19] [1390/2138] eta: 0:46:35 lr: 2.721524857523544e-05 loss: 0.0323 (0.0317) time: 4.1392 data: 0.0031 max mem: 19788 +Epoch: [19] [1400/2138] eta: 0:45:57 lr: 2.72096186753956e-05 loss: 0.0295 (0.0317) time: 3.7257 data: 0.0032 max mem: 19788 +Epoch: [19] [1410/2138] eta: 0:45:20 lr: 2.7203988646122363e-05 loss: 0.0283 (0.0317) time: 3.7050 data: 0.0030 max mem: 19788 +Epoch: [19] [1420/2138] eta: 0:44:43 lr: 2.719835848738298e-05 loss: 0.0275 (0.0317) time: 3.8111 data: 0.0029 max mem: 19788 +Epoch: [19] [1430/2138] eta: 0:44:06 lr: 2.71927281991447e-05 loss: 0.0280 (0.0317) time: 3.8100 data: 0.0029 max mem: 19788 +Epoch: [19] [1440/2138] eta: 0:43:29 lr: 2.7187097781374752e-05 loss: 0.0280 (0.0317) time: 3.7493 data: 0.0029 max mem: 19788 +Epoch: [19] [1450/2138] eta: 0:42:52 lr: 2.7181467234040354e-05 loss: 0.0314 (0.0320) time: 3.8454 data: 0.0028 max mem: 19788 +Epoch: [19] [1460/2138] eta: 0:42:15 lr: 2.7175836557108687e-05 loss: 0.0337 (0.0320) time: 3.8106 data: 0.0028 max mem: 19788 +Epoch: [19] [1470/2138] eta: 0:41:37 lr: 2.717020575054694e-05 loss: 0.0318 (0.0320) time: 3.6685 data: 0.0030 max mem: 19788 +Epoch: [19] [1480/2138] eta: 0:40:59 lr: 2.716457481432228e-05 loss: 0.0301 (0.0320) time: 3.6583 data: 0.0031 max mem: 19788 +Epoch: [19] [1490/2138] eta: 0:40:22 lr: 2.7158943748401855e-05 loss: 0.0308 (0.0320) time: 3.7596 data: 0.0029 max mem: 19788 +Epoch: [19] [1500/2138] eta: 0:39:45 lr: 2.7153312552752786e-05 loss: 0.0308 (0.0320) time: 3.8841 data: 0.0028 max mem: 19788 +Epoch: [19] [1510/2138] eta: 0:39:08 lr: 2.7147681227342202e-05 loss: 0.0308 (0.0320) time: 3.8180 data: 0.0028 max mem: 19788 +Epoch: [19] [1520/2138] eta: 0:38:31 lr: 2.7142049772137213e-05 loss: 0.0303 (0.0320) time: 3.7386 data: 0.0030 max mem: 19788 +Epoch: [19] [1530/2138] eta: 0:37:53 lr: 2.7136418187104885e-05 loss: 0.0255 (0.0319) time: 3.7296 data: 0.0030 max mem: 19788 +Epoch: [19] [1540/2138] eta: 0:37:16 lr: 2.713078647221229e-05 loss: 0.0255 (0.0320) time: 3.6929 data: 0.0028 max mem: 19788 +Epoch: [19] [1550/2138] eta: 0:36:38 lr: 2.7125154627426486e-05 loss: 0.0301 (0.0320) time: 3.6707 data: 0.0028 max mem: 19788 +Epoch: [19] [1560/2138] eta: 0:36:00 lr: 2.7119522652714513e-05 loss: 0.0323 (0.0320) time: 3.7016 data: 0.0028 max mem: 19788 +Epoch: [19] [1570/2138] eta: 0:35:23 lr: 2.7113890548043392e-05 loss: 0.0332 (0.0320) time: 3.7222 data: 0.0029 max mem: 19788 +Epoch: [19] [1580/2138] eta: 0:34:45 lr: 2.7108258313380115e-05 loss: 0.0299 (0.0320) time: 3.7024 data: 0.0031 max mem: 19788 +Epoch: [19] [1590/2138] eta: 0:34:08 lr: 2.7102625948691685e-05 loss: 0.0291 (0.0320) time: 3.7818 data: 0.0031 max mem: 19788 +Epoch: [19] [1600/2138] eta: 0:33:31 lr: 2.7096993453945074e-05 loss: 0.0300 (0.0320) time: 3.8333 data: 0.0030 max mem: 19788 +Epoch: [19] [1610/2138] eta: 0:32:54 lr: 2.7091360829107237e-05 loss: 0.0288 (0.0319) time: 3.8532 data: 0.0028 max mem: 19788 +Epoch: [19] [1620/2138] eta: 0:32:17 lr: 2.708572807414511e-05 loss: 0.0268 (0.0319) time: 3.7973 data: 0.0029 max mem: 19788 +Epoch: [19] [1630/2138] eta: 0:31:40 lr: 2.7080095189025622e-05 loss: 0.0320 (0.0319) time: 3.8068 data: 0.0029 max mem: 19788 +Epoch: [19] [1640/2138] eta: 0:31:02 lr: 2.7074462173715686e-05 loss: 0.0305 (0.0319) time: 3.7991 data: 0.0029 max mem: 19788 +Epoch: [19] [1650/2138] eta: 0:30:25 lr: 2.7068829028182196e-05 loss: 0.0243 (0.0319) time: 3.7537 data: 0.0029 max mem: 19788 +Epoch: [19] [1660/2138] eta: 0:29:48 lr: 2.7063195752392013e-05 loss: 0.0257 (0.0319) time: 3.8633 data: 0.0029 max mem: 19788 +Epoch: [19] [1670/2138] eta: 0:29:11 lr: 2.7057562346312015e-05 loss: 0.0259 (0.0318) time: 3.7784 data: 0.0030 max mem: 19788 +Epoch: [19] [1680/2138] eta: 0:28:34 lr: 2.705192880990904e-05 loss: 0.0274 (0.0318) time: 3.7796 data: 0.0032 max mem: 19788 +Epoch: [19] [1690/2138] eta: 0:27:56 lr: 2.704629514314992e-05 loss: 0.0274 (0.0318) time: 3.8170 data: 0.0030 max mem: 19788 +Epoch: [19] [1700/2138] eta: 0:27:19 lr: 2.704066134600146e-05 loss: 0.0267 (0.0318) time: 3.7266 data: 0.0033 max mem: 19788 +Epoch: [19] [1710/2138] eta: 0:26:42 lr: 2.703502741843047e-05 loss: 0.0281 (0.0318) time: 3.8364 data: 0.0035 max mem: 19788 +Epoch: [19] [1720/2138] eta: 0:26:04 lr: 2.7029393360403717e-05 loss: 0.0281 (0.0318) time: 3.8161 data: 0.0030 max mem: 19788 +Epoch: [19] [1730/2138] eta: 0:25:27 lr: 2.7023759171887964e-05 loss: 0.0273 (0.0317) time: 3.7512 data: 0.0029 max mem: 19788 +Epoch: [19] [1740/2138] eta: 0:24:50 lr: 2.7018124852849963e-05 loss: 0.0281 (0.0317) time: 3.9813 data: 0.0028 max mem: 19788 +Epoch: [19] [1750/2138] eta: 0:24:13 lr: 2.701249040325645e-05 loss: 0.0305 (0.0317) time: 3.9246 data: 0.0031 max mem: 19788 +Epoch: [19] [1760/2138] eta: 0:23:35 lr: 2.7006855823074147e-05 loss: 0.0305 (0.0317) time: 3.6983 data: 0.0031 max mem: 19788 +Epoch: [19] [1770/2138] eta: 0:22:58 lr: 2.700122111226973e-05 loss: 0.0289 (0.0317) time: 3.7973 data: 0.0029 max mem: 19788 +Epoch: [19] [1780/2138] eta: 0:22:21 lr: 2.69955862708099e-05 loss: 0.0280 (0.0317) time: 3.8407 data: 0.0030 max mem: 19788 +Epoch: [19] [1790/2138] eta: 0:21:43 lr: 2.698995129866132e-05 loss: 0.0280 (0.0318) time: 3.7305 data: 0.0032 max mem: 19788 +Epoch: [19] [1800/2138] eta: 0:21:06 lr: 2.6984316195790645e-05 loss: 0.0257 (0.0317) time: 3.6927 data: 0.0032 max mem: 19788 +Epoch: [19] [1810/2138] eta: 0:20:28 lr: 2.69786809621645e-05 loss: 0.0259 (0.0317) time: 3.7127 data: 0.0031 max mem: 19788 +Epoch: [19] [1820/2138] eta: 0:19:51 lr: 2.69730455977495e-05 loss: 0.0262 (0.0317) time: 3.8079 data: 0.0033 max mem: 19788 +Epoch: [19] [1830/2138] eta: 0:19:14 lr: 2.6967410102512263e-05 loss: 0.0274 (0.0317) time: 3.8719 data: 0.0031 max mem: 19788 +Epoch: [19] [1840/2138] eta: 0:18:36 lr: 2.6961774476419372e-05 loss: 0.0283 (0.0317) time: 3.8072 data: 0.0030 max mem: 19788 +Epoch: [19] [1850/2138] eta: 0:17:59 lr: 2.6956138719437373e-05 loss: 0.0314 (0.0317) time: 3.7962 data: 0.0031 max mem: 19788 +Epoch: [19] [1860/2138] eta: 0:17:21 lr: 2.695050283153285e-05 loss: 0.0301 (0.0317) time: 3.7607 data: 0.0032 max mem: 19788 +Epoch: [19] [1870/2138] eta: 0:16:44 lr: 2.694486681267232e-05 loss: 0.0277 (0.0317) time: 3.7123 data: 0.0033 max mem: 19788 +Epoch: [19] [1880/2138] eta: 0:16:06 lr: 2.6939230662822312e-05 loss: 0.0275 (0.0317) time: 3.7036 data: 0.0032 max mem: 19788 +Epoch: [19] [1890/2138] eta: 0:15:29 lr: 2.6933594381949324e-05 loss: 0.0272 (0.0317) time: 3.6969 data: 0.0031 max mem: 19788 +Epoch: [19] [1900/2138] eta: 0:14:51 lr: 2.692795797001984e-05 loss: 0.0269 (0.0317) time: 3.6974 data: 0.0031 max mem: 19788 +Epoch: [19] [1910/2138] eta: 0:14:14 lr: 2.6922321427000346e-05 loss: 0.0268 (0.0317) time: 3.6746 data: 0.0031 max mem: 19788 +Epoch: [19] [1920/2138] eta: 0:13:36 lr: 2.6916684752857292e-05 loss: 0.0276 (0.0317) time: 3.8391 data: 0.0030 max mem: 19788 +Epoch: [19] [1930/2138] eta: 0:12:59 lr: 2.69110479475571e-05 loss: 0.0293 (0.0317) time: 3.9000 data: 0.0029 max mem: 19788 +Epoch: [19] [1940/2138] eta: 0:12:22 lr: 2.6905411011066213e-05 loss: 0.0293 (0.0317) time: 3.8450 data: 0.0030 max mem: 19788 +Epoch: [19] [1950/2138] eta: 0:11:44 lr: 2.6899773943351024e-05 loss: 0.0287 (0.0317) time: 3.9267 data: 0.0031 max mem: 19788 +Epoch: [19] [1960/2138] eta: 0:11:07 lr: 2.6894136744377933e-05 loss: 0.0287 (0.0316) time: 3.9335 data: 0.0031 max mem: 19788 +Epoch: [19] [1970/2138] eta: 0:10:30 lr: 2.68884994141133e-05 loss: 0.0286 (0.0317) time: 3.8385 data: 0.0030 max mem: 19788 +Epoch: [19] [1980/2138] eta: 0:09:52 lr: 2.6882861952523487e-05 loss: 0.0266 (0.0317) time: 3.7931 data: 0.0031 max mem: 19788 +Epoch: [19] [1990/2138] eta: 0:09:15 lr: 2.6877224359574844e-05 loss: 0.0277 (0.0317) time: 3.8355 data: 0.0032 max mem: 19788 +Epoch: [19] [2000/2138] eta: 0:08:37 lr: 2.6871586635233674e-05 loss: 0.0318 (0.0317) time: 3.8041 data: 0.0032 max mem: 19788 +Epoch: [19] [2010/2138] eta: 0:08:00 lr: 2.68659487794663e-05 loss: 0.0333 (0.0317) time: 3.7151 data: 0.0030 max mem: 19788 +Epoch: [19] [2020/2138] eta: 0:07:22 lr: 2.6860310792239008e-05 loss: 0.0329 (0.0317) time: 3.7523 data: 0.0029 max mem: 19788 +Epoch: [19] [2030/2138] eta: 0:06:45 lr: 2.685467267351807e-05 loss: 0.0298 (0.0317) time: 4.1260 data: 0.0028 max mem: 19788 +Epoch: [19] [2040/2138] eta: 0:06:07 lr: 2.6849034423269743e-05 loss: 0.0267 (0.0316) time: 4.0793 data: 0.0030 max mem: 19788 +Epoch: [19] [2050/2138] eta: 0:05:30 lr: 2.684339604146026e-05 loss: 0.0280 (0.0317) time: 3.8622 data: 0.0032 max mem: 19788 +Epoch: [19] [2060/2138] eta: 0:04:52 lr: 2.683775752805587e-05 loss: 0.0292 (0.0317) time: 3.9098 data: 0.0033 max mem: 19788 +Epoch: [19] [2070/2138] eta: 0:04:15 lr: 2.6832118883022757e-05 loss: 0.0269 (0.0317) time: 3.7883 data: 0.0031 max mem: 19788 +Epoch: [19] [2080/2138] eta: 0:03:37 lr: 2.6826480106327118e-05 loss: 0.0277 (0.0317) time: 3.9230 data: 0.0031 max mem: 19788 +Epoch: [19] [2090/2138] eta: 0:03:00 lr: 2.6820841197935125e-05 loss: 0.0267 (0.0316) time: 3.9633 data: 0.0032 max mem: 19788 +Epoch: [19] [2100/2138] eta: 0:02:22 lr: 2.681520215781295e-05 loss: 0.0267 (0.0316) time: 3.8476 data: 0.0030 max mem: 19788 +Epoch: [19] [2110/2138] eta: 0:01:45 lr: 2.6809562985926728e-05 loss: 0.0318 (0.0317) time: 3.7660 data: 0.0030 max mem: 19788 +Epoch: [19] [2120/2138] eta: 0:01:07 lr: 2.680392368224257e-05 loss: 0.0338 (0.0317) time: 3.7243 data: 0.0030 max mem: 19788 +Epoch: [19] [2130/2138] eta: 0:00:30 lr: 2.6798284246726596e-05 loss: 0.0336 (0.0317) time: 3.7197 data: 0.0029 max mem: 19788 +Epoch: [19] Total time: 2:13:54 +Test: [ 0/21770] eta: 18:14:32 time: 3.0167 data: 2.7391 max mem: 19788 +Test: [ 100/21770] eta: 0:38:08 time: 0.0820 data: 0.0020 max mem: 19788 +Test: [ 200/21770] eta: 0:31:39 time: 0.0592 data: 0.0019 max mem: 19788 +Test: [ 300/21770] eta: 0:28:50 time: 0.0629 data: 0.0020 max mem: 19788 +Test: [ 400/21770] eta: 0:28:00 time: 0.0676 data: 0.0018 max mem: 19788 +Test: [ 500/21770] eta: 0:26:51 time: 0.0625 data: 0.0019 max mem: 19788 +Test: [ 600/21770] eta: 0:26:19 time: 0.0653 data: 0.0019 max mem: 19788 +Test: [ 700/21770] eta: 0:26:13 time: 0.0671 data: 0.0020 max mem: 19788 +Test: [ 800/21770] eta: 0:26:03 time: 0.0815 data: 0.0025 max mem: 19788 +Test: [ 900/21770] eta: 0:25:39 time: 0.0629 data: 0.0021 max mem: 19788 +Test: [ 1000/21770] eta: 0:25:22 time: 0.0614 data: 0.0021 max mem: 19788 +Test: [ 1100/21770] eta: 0:24:55 time: 0.0602 data: 0.0019 max mem: 19788 +Test: [ 1200/21770] eta: 0:24:52 time: 0.0826 data: 0.0025 max mem: 19788 +Test: [ 1300/21770] eta: 0:24:32 time: 0.0623 data: 0.0019 max mem: 19788 +Test: [ 1400/21770] eta: 0:24:08 time: 0.0602 data: 0.0020 max mem: 19788 +Test: [ 1500/21770] eta: 0:24:04 time: 0.0677 data: 0.0020 max mem: 19788 +Test: [ 1600/21770] eta: 0:23:51 time: 0.0821 data: 0.0024 max mem: 19788 +Test: [ 1700/21770] eta: 0:23:53 time: 0.0675 data: 0.0020 max mem: 19788 +Test: [ 1800/21770] eta: 0:23:41 time: 0.0814 data: 0.0025 max mem: 19788 +Test: [ 1900/21770] eta: 0:23:28 time: 0.0705 data: 0.0023 max mem: 19788 +Test: [ 2000/21770] eta: 0:23:23 time: 0.0611 data: 0.0019 max mem: 19788 +Test: [ 2100/21770] eta: 0:23:15 time: 0.0823 data: 0.0025 max mem: 19788 +Test: [ 2200/21770] eta: 0:23:12 time: 0.0816 data: 0.0025 max mem: 19788 +Test: [ 2300/21770] eta: 0:23:09 time: 0.0695 data: 0.0021 max mem: 19788 +Test: [ 2400/21770] eta: 0:23:00 time: 0.0700 data: 0.0021 max mem: 19788 +Test: [ 2500/21770] eta: 0:22:50 time: 0.0818 data: 0.0022 max mem: 19788 +Test: [ 2600/21770] eta: 0:22:47 time: 0.0827 data: 0.0025 max mem: 19788 +Test: [ 2700/21770] eta: 0:22:36 time: 0.0656 data: 0.0020 max mem: 19788 +Test: [ 2800/21770] eta: 0:22:31 time: 0.0776 data: 0.0019 max mem: 19788 +Test: [ 2900/21770] eta: 0:22:28 time: 0.0751 data: 0.0022 max mem: 19788 +Test: [ 3000/21770] eta: 0:22:20 time: 0.0636 data: 0.0018 max mem: 19788 +Test: [ 3100/21770] eta: 0:22:13 time: 0.0618 data: 0.0018 max mem: 19788 +Test: [ 3200/21770] eta: 0:22:01 time: 0.0616 data: 0.0020 max mem: 19788 +Test: [ 3300/21770] eta: 0:21:49 time: 0.0620 data: 0.0017 max mem: 19788 +Test: [ 3400/21770] eta: 0:21:39 time: 0.0634 data: 0.0019 max mem: 19788 +Test: [ 3500/21770] eta: 0:21:29 time: 0.0613 data: 0.0018 max mem: 19788 +Test: [ 3600/21770] eta: 0:21:20 time: 0.0608 data: 0.0019 max mem: 19788 +Test: [ 3700/21770] eta: 0:21:14 time: 0.0785 data: 0.0022 max mem: 19788 +Test: [ 3800/21770] eta: 0:21:04 time: 0.0612 data: 0.0018 max mem: 19788 +Test: [ 3900/21770] eta: 0:20:53 time: 0.0615 data: 0.0019 max mem: 19788 +Test: [ 4000/21770] eta: 0:20:47 time: 0.0622 data: 0.0019 max mem: 19788 +Test: [ 4100/21770] eta: 0:20:41 time: 0.0790 data: 0.0019 max mem: 19788 +Test: [ 4200/21770] eta: 0:20:34 time: 0.0817 data: 0.0021 max mem: 19788 +Test: [ 4300/21770] eta: 0:20:24 time: 0.0635 data: 0.0017 max mem: 19788 +Test: [ 4400/21770] eta: 0:20:18 time: 0.0618 data: 0.0017 max mem: 19788 +Test: [ 4500/21770] eta: 0:20:09 time: 0.0632 data: 0.0019 max mem: 19788 +Test: [ 4600/21770] eta: 0:20:05 time: 0.0678 data: 0.0019 max mem: 19788 +Test: [ 4700/21770] eta: 0:19:57 time: 0.0688 data: 0.0019 max mem: 19788 +Test: [ 4800/21770] eta: 0:19:52 time: 0.0813 data: 0.0024 max mem: 19788 +Test: [ 4900/21770] eta: 0:19:48 time: 0.0760 data: 0.0022 max mem: 19788 +Test: [ 5000/21770] eta: 0:19:41 time: 0.0707 data: 0.0022 max mem: 19788 +Test: [ 5100/21770] eta: 0:19:32 time: 0.0642 data: 0.0019 max mem: 19788 +Test: [ 5200/21770] eta: 0:19:27 time: 0.0785 data: 0.0023 max mem: 19788 +Test: [ 5300/21770] eta: 0:19:22 time: 0.0616 data: 0.0019 max mem: 19788 +Test: [ 5400/21770] eta: 0:19:12 time: 0.0629 data: 0.0017 max mem: 19788 +Test: [ 5500/21770] eta: 0:19:02 time: 0.0576 data: 0.0018 max mem: 19788 +Test: [ 5600/21770] eta: 0:18:52 time: 0.0580 data: 0.0018 max mem: 19788 +Test: [ 5700/21770] eta: 0:18:46 time: 0.0813 data: 0.0025 max mem: 19788 +Test: [ 5800/21770] eta: 0:18:38 time: 0.0638 data: 0.0017 max mem: 19788 +Test: [ 5900/21770] eta: 0:18:30 time: 0.0680 data: 0.0018 max mem: 19788 +Test: [ 6000/21770] eta: 0:18:23 time: 0.0648 data: 0.0019 max mem: 19788 +Test: [ 6100/21770] eta: 0:18:16 time: 0.0616 data: 0.0018 max mem: 19788 +Test: [ 6200/21770] eta: 0:18:09 time: 0.0622 data: 0.0020 max mem: 19788 +Test: [ 6300/21770] eta: 0:18:01 time: 0.0628 data: 0.0017 max mem: 19788 +Test: [ 6400/21770] eta: 0:17:52 time: 0.0632 data: 0.0020 max mem: 19788 +Test: [ 6500/21770] eta: 0:17:45 time: 0.0725 data: 0.0021 max mem: 19788 +Test: [ 6600/21770] eta: 0:17:38 time: 0.0614 data: 0.0018 max mem: 19788 +Test: [ 6700/21770] eta: 0:17:31 time: 0.0821 data: 0.0024 max mem: 19788 +Test: [ 6800/21770] eta: 0:17:24 time: 0.0634 data: 0.0017 max mem: 19788 +Test: [ 6900/21770] eta: 0:17:16 time: 0.0618 data: 0.0017 max mem: 19788 +Test: [ 7000/21770] eta: 0:17:09 time: 0.0730 data: 0.0020 max mem: 19788 +Test: [ 7100/21770] eta: 0:17:01 time: 0.0674 data: 0.0023 max mem: 19788 +Test: [ 7200/21770] eta: 0:16:56 time: 0.0823 data: 0.0023 max mem: 19788 +Test: [ 7300/21770] eta: 0:16:49 time: 0.0691 data: 0.0021 max mem: 19788 +Test: [ 7400/21770] eta: 0:16:43 time: 0.0818 data: 0.0023 max mem: 19788 +Test: [ 7500/21770] eta: 0:16:37 time: 0.0690 data: 0.0020 max mem: 19788 +Test: [ 7600/21770] eta: 0:16:28 time: 0.0609 data: 0.0016 max mem: 19788 +Test: [ 7700/21770] eta: 0:16:22 time: 0.0751 data: 0.0023 max mem: 19788 +Test: [ 7800/21770] eta: 0:16:16 time: 0.0816 data: 0.0024 max mem: 19788 +Test: [ 7900/21770] eta: 0:16:11 time: 0.0817 data: 0.0025 max mem: 19788 +Test: [ 8000/21770] eta: 0:16:05 time: 0.0628 data: 0.0019 max mem: 19788 +Test: [ 8100/21770] eta: 0:15:56 time: 0.0623 data: 0.0019 max mem: 19788 +Test: [ 8200/21770] eta: 0:15:51 time: 0.0818 data: 0.0025 max mem: 19788 +Test: [ 8300/21770] eta: 0:15:46 time: 0.0766 data: 0.0029 max mem: 19788 +Test: [ 8400/21770] eta: 0:15:39 time: 0.0652 data: 0.0019 max mem: 19788 +Test: [ 8500/21770] eta: 0:15:34 time: 0.0825 data: 0.0020 max mem: 19788 +Test: [ 8600/21770] eta: 0:15:27 time: 0.0783 data: 0.0024 max mem: 19788 +Test: [ 8700/21770] eta: 0:15:19 time: 0.0703 data: 0.0019 max mem: 19788 +Test: [ 8800/21770] eta: 0:15:13 time: 0.0690 data: 0.0019 max mem: 19788 +Test: [ 8900/21770] eta: 0:15:07 time: 0.0736 data: 0.0020 max mem: 19788 +Test: [ 9000/21770] eta: 0:15:00 time: 0.0718 data: 0.0022 max mem: 19788 +Test: [ 9100/21770] eta: 0:14:53 time: 0.0806 data: 0.0023 max mem: 19788 +Test: [ 9200/21770] eta: 0:14:47 time: 0.0638 data: 0.0018 max mem: 19788 +Test: [ 9300/21770] eta: 0:14:40 time: 0.0774 data: 0.0023 max mem: 19788 +Test: [ 9400/21770] eta: 0:14:34 time: 0.0826 data: 0.0023 max mem: 19788 +Test: [ 9500/21770] eta: 0:14:28 time: 0.0634 data: 0.0021 max mem: 19788 +Test: [ 9600/21770] eta: 0:14:20 time: 0.0653 data: 0.0019 max mem: 19788 +Test: [ 9700/21770] eta: 0:14:12 time: 0.0649 data: 0.0019 max mem: 19788 +Test: [ 9800/21770] eta: 0:14:05 time: 0.0780 data: 0.0023 max mem: 19788 +Test: [ 9900/21770] eta: 0:13:58 time: 0.0629 data: 0.0018 max mem: 19788 +Test: [10000/21770] eta: 0:13:52 time: 0.0817 data: 0.0022 max mem: 19788 +Test: [10100/21770] eta: 0:13:45 time: 0.0630 data: 0.0017 max mem: 19788 +Test: [10200/21770] eta: 0:13:37 time: 0.0623 data: 0.0018 max mem: 19788 +Test: [10300/21770] eta: 0:13:29 time: 0.0639 data: 0.0019 max mem: 19788 +Test: [10400/21770] eta: 0:13:21 time: 0.0624 data: 0.0021 max mem: 19788 +Test: [10500/21770] eta: 0:13:14 time: 0.0680 data: 0.0020 max mem: 19788 +Test: [10600/21770] eta: 0:13:08 time: 0.0721 data: 0.0020 max mem: 19788 +Test: [10700/21770] eta: 0:13:02 time: 0.0824 data: 0.0023 max mem: 19788 +Test: [10800/21770] eta: 0:12:55 time: 0.0661 data: 0.0019 max mem: 19788 +Test: [10900/21770] eta: 0:12:49 time: 0.0723 data: 0.0021 max mem: 19788 +Test: [11000/21770] eta: 0:12:41 time: 0.0765 data: 0.0020 max mem: 19788 +Test: [11100/21770] eta: 0:12:34 time: 0.0693 data: 0.0018 max mem: 19788 +Test: [11200/21770] eta: 0:12:27 time: 0.0822 data: 0.0025 max mem: 19788 +Test: [11300/21770] eta: 0:12:21 time: 0.0679 data: 0.0021 max mem: 19788 +Test: [11400/21770] eta: 0:12:13 time: 0.0624 data: 0.0018 max mem: 19788 +Test: [11500/21770] eta: 0:12:05 time: 0.0629 data: 0.0019 max mem: 19788 +Test: [11600/21770] eta: 0:11:58 time: 0.0634 data: 0.0019 max mem: 19788 +Test: [11700/21770] eta: 0:11:51 time: 0.0632 data: 0.0020 max mem: 19788 +Test: [11800/21770] eta: 0:11:43 time: 0.0673 data: 0.0019 max mem: 19788 +Test: [11900/21770] eta: 0:11:36 time: 0.0613 data: 0.0018 max mem: 19788 +Test: [12000/21770] eta: 0:11:29 time: 0.0690 data: 0.0020 max mem: 19788 +Test: [12100/21770] eta: 0:11:22 time: 0.0815 data: 0.0022 max mem: 19788 +Test: [12200/21770] eta: 0:11:16 time: 0.0812 data: 0.0022 max mem: 19788 +Test: [12300/21770] eta: 0:11:10 time: 0.0737 data: 0.0021 max mem: 19788 +Test: [12400/21770] eta: 0:11:03 time: 0.0677 data: 0.0020 max mem: 19788 +Test: [12500/21770] eta: 0:10:55 time: 0.0610 data: 0.0018 max mem: 19788 +Test: [12600/21770] eta: 0:10:48 time: 0.0813 data: 0.0024 max mem: 19788 +Test: [12700/21770] eta: 0:10:41 time: 0.0624 data: 0.0017 max mem: 19788 +Test: [12800/21770] eta: 0:10:34 time: 0.0786 data: 0.0023 max mem: 19788 +Test: [12900/21770] eta: 0:10:27 time: 0.0831 data: 0.0019 max mem: 19788 +Test: [13000/21770] eta: 0:10:20 time: 0.0618 data: 0.0017 max mem: 19788 +Test: [13100/21770] eta: 0:10:13 time: 0.0817 data: 0.0024 max mem: 19788 +Test: [13200/21770] eta: 0:10:07 time: 0.0641 data: 0.0020 max mem: 19788 +Test: [13300/21770] eta: 0:09:59 time: 0.0784 data: 0.0019 max mem: 19788 +Test: [13400/21770] eta: 0:09:52 time: 0.0768 data: 0.0021 max mem: 19788 +Test: [13500/21770] eta: 0:09:46 time: 0.0823 data: 0.0024 max mem: 19788 +Test: [13600/21770] eta: 0:09:39 time: 0.0819 data: 0.0026 max mem: 19788 +Test: [13700/21770] eta: 0:09:33 time: 0.0728 data: 0.0021 max mem: 19788 +Test: [13800/21770] eta: 0:09:26 time: 0.0798 data: 0.0022 max mem: 19788 +Test: [13900/21770] eta: 0:09:19 time: 0.0711 data: 0.0020 max mem: 19788 +Test: [14000/21770] eta: 0:09:12 time: 0.0815 data: 0.0024 max mem: 19788 +Test: [14100/21770] eta: 0:09:05 time: 0.0681 data: 0.0019 max mem: 19788 +Test: [14200/21770] eta: 0:08:58 time: 0.0802 data: 0.0019 max mem: 19788 +Test: [14300/21770] eta: 0:08:51 time: 0.0621 data: 0.0017 max mem: 19788 +Test: [14400/21770] eta: 0:08:44 time: 0.0653 data: 0.0019 max mem: 19788 +Test: [14500/21770] eta: 0:08:36 time: 0.0736 data: 0.0020 max mem: 19788 +Test: [14600/21770] eta: 0:08:29 time: 0.0696 data: 0.0020 max mem: 19788 +Test: [14700/21770] eta: 0:08:22 time: 0.0619 data: 0.0018 max mem: 19788 +Test: [14800/21770] eta: 0:08:15 time: 0.0630 data: 0.0019 max mem: 19788 +Test: [14900/21770] eta: 0:08:07 time: 0.0817 data: 0.0023 max mem: 19788 +Test: [15000/21770] eta: 0:08:00 time: 0.0630 data: 0.0018 max mem: 19788 +Test: [15100/21770] eta: 0:07:52 time: 0.0619 data: 0.0018 max mem: 19788 +Test: [15200/21770] eta: 0:07:46 time: 0.0817 data: 0.0025 max mem: 19788 +Test: [15300/21770] eta: 0:07:38 time: 0.0636 data: 0.0018 max mem: 19788 +Test: [15400/21770] eta: 0:07:31 time: 0.0610 data: 0.0017 max mem: 19788 +Test: [15500/21770] eta: 0:07:24 time: 0.0646 data: 0.0017 max mem: 19788 +Test: [15600/21770] eta: 0:07:16 time: 0.0698 data: 0.0019 max mem: 19788 +Test: [15700/21770] eta: 0:07:09 time: 0.0632 data: 0.0020 max mem: 19788 +Test: [15800/21770] eta: 0:07:02 time: 0.0689 data: 0.0019 max mem: 19788 +Test: [15900/21770] eta: 0:06:55 time: 0.0664 data: 0.0021 max mem: 19788 +Test: [16000/21770] eta: 0:06:48 time: 0.0618 data: 0.0017 max mem: 19788 +Test: [16100/21770] eta: 0:06:40 time: 0.0692 data: 0.0021 max mem: 19788 +Test: [16200/21770] eta: 0:06:33 time: 0.0637 data: 0.0019 max mem: 19788 +Test: [16300/21770] eta: 0:06:26 time: 0.0826 data: 0.0019 max mem: 19788 +Test: [16400/21770] eta: 0:06:19 time: 0.0633 data: 0.0018 max mem: 19788 +Test: [16500/21770] eta: 0:06:12 time: 0.0617 data: 0.0019 max mem: 19788 +Test: [16600/21770] eta: 0:06:05 time: 0.0823 data: 0.0023 max mem: 19788 +Test: [16700/21770] eta: 0:05:58 time: 0.0806 data: 0.0023 max mem: 19788 +Test: [16800/21770] eta: 0:05:51 time: 0.0748 data: 0.0020 max mem: 19788 +Test: [16900/21770] eta: 0:05:44 time: 0.0773 data: 0.0022 max mem: 19788 +Test: [17000/21770] eta: 0:05:36 time: 0.0636 data: 0.0018 max mem: 19788 +Test: [17100/21770] eta: 0:05:29 time: 0.0831 data: 0.0024 max mem: 19788 +Test: [17200/21770] eta: 0:05:22 time: 0.0785 data: 0.0024 max mem: 19788 +Test: [17300/21770] eta: 0:05:15 time: 0.0712 data: 0.0021 max mem: 19788 +Test: [17400/21770] eta: 0:05:08 time: 0.0620 data: 0.0021 max mem: 19788 +Test: [17500/21770] eta: 0:05:01 time: 0.0831 data: 0.0025 max mem: 19788 +Test: [17600/21770] eta: 0:04:54 time: 0.0663 data: 0.0020 max mem: 19788 +Test: [17700/21770] eta: 0:04:47 time: 0.0600 data: 0.0019 max mem: 19788 +Test: [17800/21770] eta: 0:04:40 time: 0.0762 data: 0.0022 max mem: 19788 +Test: [17900/21770] eta: 0:04:33 time: 0.0767 data: 0.0019 max mem: 19788 +Test: [18000/21770] eta: 0:04:26 time: 0.0750 data: 0.0022 max mem: 19788 +Test: [18100/21770] eta: 0:04:19 time: 0.0706 data: 0.0024 max mem: 19788 +Test: [18200/21770] eta: 0:04:12 time: 0.0619 data: 0.0019 max mem: 19788 +Test: [18300/21770] eta: 0:04:05 time: 0.0809 data: 0.0024 max mem: 19788 +Test: [18400/21770] eta: 0:03:58 time: 0.0624 data: 0.0019 max mem: 19788 +Test: [18500/21770] eta: 0:03:50 time: 0.0636 data: 0.0018 max mem: 19788 +Test: [18600/21770] eta: 0:03:44 time: 0.0823 data: 0.0019 max mem: 19788 +Test: [18700/21770] eta: 0:03:36 time: 0.0617 data: 0.0018 max mem: 19788 +Test: [18800/21770] eta: 0:03:29 time: 0.0607 data: 0.0018 max mem: 19788 +Test: [18900/21770] eta: 0:03:22 time: 0.0623 data: 0.0017 max mem: 19788 +Test: [19000/21770] eta: 0:03:15 time: 0.0668 data: 0.0020 max mem: 19788 +Test: [19100/21770] eta: 0:03:08 time: 0.0624 data: 0.0019 max mem: 19788 +Test: [19200/21770] eta: 0:03:01 time: 0.0627 data: 0.0018 max mem: 19788 +Test: [19300/21770] eta: 0:02:54 time: 0.0749 data: 0.0022 max mem: 19788 +Test: [19400/21770] eta: 0:02:46 time: 0.0689 data: 0.0017 max mem: 19788 +Test: [19500/21770] eta: 0:02:39 time: 0.0620 data: 0.0019 max mem: 19788 +Test: [19600/21770] eta: 0:02:32 time: 0.0668 data: 0.0020 max mem: 19788 +Test: [19700/21770] eta: 0:02:25 time: 0.0829 data: 0.0021 max mem: 19788 +Test: [19800/21770] eta: 0:02:18 time: 0.0666 data: 0.0020 max mem: 19788 +Test: [19900/21770] eta: 0:02:11 time: 0.0828 data: 0.0021 max mem: 19788 +Test: [20000/21770] eta: 0:02:04 time: 0.0632 data: 0.0016 max mem: 19788 +Test: [20100/21770] eta: 0:01:57 time: 0.0816 data: 0.0024 max mem: 19788 +Test: [20200/21770] eta: 0:01:50 time: 0.0787 data: 0.0024 max mem: 19788 +Test: [20300/21770] eta: 0:01:43 time: 0.0830 data: 0.0022 max mem: 19788 +Test: [20400/21770] eta: 0:01:36 time: 0.0817 data: 0.0025 max mem: 19788 +Test: [20500/21770] eta: 0:01:29 time: 0.0825 data: 0.0032 max mem: 19788 +Test: [20600/21770] eta: 0:01:22 time: 0.0626 data: 0.0020 max mem: 19788 +Test: [20700/21770] eta: 0:01:15 time: 0.0664 data: 0.0018 max mem: 19788 +Test: [20800/21770] eta: 0:01:08 time: 0.0606 data: 0.0020 max mem: 19788 +Test: [20900/21770] eta: 0:01:01 time: 0.0634 data: 0.0019 max mem: 19788 +Test: [21000/21770] eta: 0:00:54 time: 0.0608 data: 0.0017 max mem: 19788 +Test: [21100/21770] eta: 0:00:47 time: 0.0658 data: 0.0018 max mem: 19788 +Test: [21200/21770] eta: 0:00:40 time: 0.0606 data: 0.0018 max mem: 19788 +Test: [21300/21770] eta: 0:00:33 time: 0.0682 data: 0.0019 max mem: 19788 +Test: [21400/21770] eta: 0:00:26 time: 0.0762 data: 0.0021 max mem: 19788 +Test: [21500/21770] eta: 0:00:19 time: 0.0634 data: 0.0018 max mem: 19788 +Test: [21600/21770] eta: 0:00:11 time: 0.0614 data: 0.0019 max mem: 19788 +Test: [21700/21770] eta: 0:00:04 time: 0.0609 data: 0.0018 max mem: 19788 +Test: Total time: 0:25:35 +Final results: +Mean IoU is 62.79 + + precision@0.5 = 69.64 + precision@0.6 = 64.16 + precision@0.7 = 57.42 + precision@0.8 = 46.76 + precision@0.9 = 22.97 + overall IoU = 63.60 + mean IoU = 62.79 + +Mean accuracy for one-to-zero sample is 84.44 + +Average object IoU 0.6278851550281556 +Overall IoU 63.60118103027344 +Better epoch: 19 + +Epoch: [20] [ 0/2138] eta: 3:27:46 lr: 2.679377260337213e-05 loss: 0.0342 (0.0342) time: 5.8309 data: 1.9451 max mem: 19788 +Epoch: [20] [ 10/2138] eta: 2:18:05 lr: 2.6788132930473424e-05 loss: 0.0264 (0.0283) time: 3.8935 data: 0.1783 max mem: 19788 +Epoch: [20] [ 20/2138] eta: 2:14:01 lr: 2.6782493125647916e-05 loss: 0.0237 (0.0262) time: 3.6952 data: 0.0015 max mem: 19788 +Epoch: [20] [ 30/2138] eta: 2:11:50 lr: 2.677685318886165e-05 loss: 0.0241 (0.0261) time: 3.6752 data: 0.0021 max mem: 19788 +Epoch: [20] [ 40/2138] eta: 2:12:03 lr: 2.6771213120080657e-05 loss: 0.0277 (0.0272) time: 3.7556 data: 0.0029 max mem: 19788 +Epoch: [20] [ 50/2138] eta: 2:12:17 lr: 2.6765572919270943e-05 loss: 0.0290 (0.0282) time: 3.8769 data: 0.0031 max mem: 19788 +Epoch: [20] [ 60/2138] eta: 2:11:03 lr: 2.6759932586398506e-05 loss: 0.0240 (0.0277) time: 3.7995 data: 0.0029 max mem: 19788 +Epoch: [20] [ 70/2138] eta: 2:10:04 lr: 2.6754292121429316e-05 loss: 0.0208 (0.0273) time: 3.7047 data: 0.0029 max mem: 19788 +Epoch: [20] [ 80/2138] eta: 2:09:19 lr: 2.674865152432935e-05 loss: 0.0251 (0.0281) time: 3.7274 data: 0.0030 max mem: 19788 +Epoch: [20] [ 90/2138] eta: 2:08:46 lr: 2.6743010795064534e-05 loss: 0.0287 (0.0285) time: 3.7681 data: 0.0031 max mem: 19788 +Epoch: [20] [ 100/2138] eta: 2:07:56 lr: 2.673736993360081e-05 loss: 0.0290 (0.0285) time: 3.7521 data: 0.0032 max mem: 19788 +Epoch: [20] [ 110/2138] eta: 2:07:52 lr: 2.6731728939904083e-05 loss: 0.0291 (0.0287) time: 3.8319 data: 0.0031 max mem: 19788 +Epoch: [20] [ 120/2138] eta: 2:06:52 lr: 2.6726087813940247e-05 loss: 0.0292 (0.0289) time: 3.8005 data: 0.0034 max mem: 19788 +Epoch: [20] [ 130/2138] eta: 2:06:49 lr: 2.6720446555675184e-05 loss: 0.0301 (0.0294) time: 3.8234 data: 0.0034 max mem: 19788 +Epoch: [20] [ 140/2138] eta: 2:06:47 lr: 2.6714805165074752e-05 loss: 0.0285 (0.0293) time: 4.0206 data: 0.0029 max mem: 19788 +Epoch: [20] [ 150/2138] eta: 2:06:02 lr: 2.6709163642104788e-05 loss: 0.0245 (0.0291) time: 3.8973 data: 0.0029 max mem: 19788 +Epoch: [20] [ 160/2138] eta: 2:05:13 lr: 2.6703521986731127e-05 loss: 0.0289 (0.0299) time: 3.7355 data: 0.0030 max mem: 19788 +Epoch: [20] [ 170/2138] eta: 2:04:18 lr: 2.6697880198919578e-05 loss: 0.0317 (0.0300) time: 3.6865 data: 0.0031 max mem: 19788 +Epoch: [20] [ 180/2138] eta: 2:03:31 lr: 2.6692238278635932e-05 loss: 0.0293 (0.0300) time: 3.6808 data: 0.0031 max mem: 19788 +Epoch: [20] [ 190/2138] eta: 2:02:40 lr: 2.6686596225845965e-05 loss: 0.0268 (0.0297) time: 3.6805 data: 0.0030 max mem: 19788 +Epoch: [20] [ 200/2138] eta: 2:02:00 lr: 2.6680954040515444e-05 loss: 0.0213 (0.0293) time: 3.7028 data: 0.0032 max mem: 19788 +Epoch: [20] [ 210/2138] eta: 2:01:32 lr: 2.6675311722610098e-05 loss: 0.0316 (0.0297) time: 3.8200 data: 0.0033 max mem: 19788 +Epoch: [20] [ 220/2138] eta: 2:00:58 lr: 2.6669669272095658e-05 loss: 0.0316 (0.0295) time: 3.8569 data: 0.0032 max mem: 19788 +Epoch: [20] [ 230/2138] eta: 2:00:15 lr: 2.6664026688937844e-05 loss: 0.0291 (0.0298) time: 3.7752 data: 0.0032 max mem: 19788 +Epoch: [20] [ 240/2138] eta: 1:59:27 lr: 2.665838397310233e-05 loss: 0.0306 (0.0298) time: 3.6844 data: 0.0032 max mem: 19788 +Epoch: [20] [ 250/2138] eta: 1:58:45 lr: 2.6652741124554804e-05 loss: 0.0260 (0.0296) time: 3.6846 data: 0.0031 max mem: 19788 +Epoch: [20] [ 260/2138] eta: 1:58:05 lr: 2.6647098143260914e-05 loss: 0.0238 (0.0296) time: 3.7317 data: 0.0031 max mem: 19788 +Epoch: [20] [ 270/2138] eta: 1:57:35 lr: 2.6641455029186312e-05 loss: 0.0253 (0.0297) time: 3.8110 data: 0.0031 max mem: 19788 +Epoch: [20] [ 280/2138] eta: 1:56:48 lr: 2.663581178229661e-05 loss: 0.0298 (0.0297) time: 3.7654 data: 0.0033 max mem: 19788 +Epoch: [20] [ 290/2138] eta: 1:56:18 lr: 2.6630168402557426e-05 loss: 0.0287 (0.0297) time: 3.7648 data: 0.0033 max mem: 19788 +Epoch: [20] [ 300/2138] eta: 1:55:41 lr: 2.6624524889934337e-05 loss: 0.0263 (0.0295) time: 3.8406 data: 0.0030 max mem: 19788 +Epoch: [20] [ 310/2138] eta: 1:55:08 lr: 2.6618881244392934e-05 loss: 0.0249 (0.0294) time: 3.8231 data: 0.0029 max mem: 19788 +Epoch: [20] [ 320/2138] eta: 1:54:25 lr: 2.6613237465898756e-05 loss: 0.0282 (0.0295) time: 3.7725 data: 0.0028 max mem: 19788 +Epoch: [20] [ 330/2138] eta: 1:53:48 lr: 2.660759355441735e-05 loss: 0.0313 (0.0297) time: 3.7459 data: 0.0029 max mem: 19788 +Epoch: [20] [ 340/2138] eta: 1:53:08 lr: 2.660194950991423e-05 loss: 0.0292 (0.0296) time: 3.7652 data: 0.0029 max mem: 19788 +Epoch: [20] [ 350/2138] eta: 1:52:36 lr: 2.6596305332354914e-05 loss: 0.0273 (0.0295) time: 3.8089 data: 0.0030 max mem: 19788 +Epoch: [20] [ 360/2138] eta: 1:51:56 lr: 2.6590661021704883e-05 loss: 0.0270 (0.0295) time: 3.8047 data: 0.0033 max mem: 19788 +Epoch: [20] [ 370/2138] eta: 1:51:29 lr: 2.6585016577929605e-05 loss: 0.0272 (0.0296) time: 3.8655 data: 0.0033 max mem: 19788 +Epoch: [20] [ 380/2138] eta: 1:51:09 lr: 2.657937200099453e-05 loss: 0.0282 (0.0296) time: 4.0889 data: 0.0031 max mem: 19788 +Epoch: [20] [ 390/2138] eta: 1:50:29 lr: 2.6573727290865107e-05 loss: 0.0275 (0.0296) time: 3.9600 data: 0.0032 max mem: 19788 +Epoch: [20] [ 400/2138] eta: 1:49:49 lr: 2.6568082447506742e-05 loss: 0.0291 (0.0296) time: 3.7414 data: 0.0031 max mem: 19788 +Epoch: [20] [ 410/2138] eta: 1:49:08 lr: 2.656243747088485e-05 loss: 0.0305 (0.0298) time: 3.7356 data: 0.0031 max mem: 19788 +Epoch: [20] [ 420/2138] eta: 1:48:27 lr: 2.65567923609648e-05 loss: 0.0327 (0.0298) time: 3.7257 data: 0.0033 max mem: 19788 +Epoch: [20] [ 430/2138] eta: 1:47:50 lr: 2.6551147117711978e-05 loss: 0.0283 (0.0299) time: 3.7571 data: 0.0033 max mem: 19788 +Epoch: [20] [ 440/2138] eta: 1:47:10 lr: 2.6545501741091716e-05 loss: 0.0285 (0.0298) time: 3.7717 data: 0.0032 max mem: 19788 +Epoch: [20] [ 450/2138] eta: 1:46:30 lr: 2.653985623106936e-05 loss: 0.0271 (0.0298) time: 3.7359 data: 0.0030 max mem: 19788 +Epoch: [20] [ 460/2138] eta: 1:45:52 lr: 2.653421058761022e-05 loss: 0.0291 (0.0299) time: 3.7509 data: 0.0029 max mem: 19788 +Epoch: [20] [ 470/2138] eta: 1:45:20 lr: 2.6528564810679608e-05 loss: 0.0289 (0.0299) time: 3.8605 data: 0.0030 max mem: 19788 +Epoch: [20] [ 480/2138] eta: 1:44:38 lr: 2.6522918900242784e-05 loss: 0.0279 (0.0299) time: 3.8066 data: 0.0032 max mem: 19788 +Epoch: [20] [ 490/2138] eta: 1:43:56 lr: 2.6517272856265025e-05 loss: 0.0270 (0.0302) time: 3.6753 data: 0.0031 max mem: 19788 +Epoch: [20] [ 500/2138] eta: 1:43:17 lr: 2.6511626678711576e-05 loss: 0.0261 (0.0302) time: 3.7117 data: 0.0031 max mem: 19788 +Epoch: [20] [ 510/2138] eta: 1:42:43 lr: 2.6505980367547666e-05 loss: 0.0288 (0.0302) time: 3.8277 data: 0.0032 max mem: 19788 +Epoch: [20] [ 520/2138] eta: 1:42:02 lr: 2.6500333922738517e-05 loss: 0.0310 (0.0303) time: 3.8005 data: 0.0030 max mem: 19788 +Epoch: [20] [ 530/2138] eta: 1:41:21 lr: 2.6494687344249308e-05 loss: 0.0300 (0.0306) time: 3.6696 data: 0.0030 max mem: 19788 +Epoch: [20] [ 540/2138] eta: 1:40:42 lr: 2.648904063204523e-05 loss: 0.0270 (0.0305) time: 3.6997 data: 0.0031 max mem: 19788 +Epoch: [20] [ 550/2138] eta: 1:40:02 lr: 2.6483393786091436e-05 loss: 0.0278 (0.0305) time: 3.7381 data: 0.0033 max mem: 19788 +Epoch: [20] [ 560/2138] eta: 1:39:35 lr: 2.6477746806353077e-05 loss: 0.0287 (0.0305) time: 3.9457 data: 0.0032 max mem: 19788 +Epoch: [20] [ 570/2138] eta: 1:38:57 lr: 2.6472099692795265e-05 loss: 0.0277 (0.0306) time: 3.9710 data: 0.0031 max mem: 19788 +Epoch: [20] [ 580/2138] eta: 1:38:24 lr: 2.6466452445383127e-05 loss: 0.0277 (0.0306) time: 3.8711 data: 0.0032 max mem: 19788 +Epoch: [20] [ 590/2138] eta: 1:37:46 lr: 2.646080506408174e-05 loss: 0.0274 (0.0306) time: 3.8636 data: 0.0032 max mem: 19788 +Epoch: [20] [ 600/2138] eta: 1:37:10 lr: 2.6455157548856187e-05 loss: 0.0258 (0.0306) time: 3.8196 data: 0.0032 max mem: 19788 +Epoch: [20] [ 610/2138] eta: 1:36:36 lr: 2.6449509899671514e-05 loss: 0.0262 (0.0306) time: 3.9048 data: 0.0032 max mem: 19788 +Epoch: [20] [ 620/2138] eta: 1:35:58 lr: 2.644386211649278e-05 loss: 0.0321 (0.0307) time: 3.8729 data: 0.0032 max mem: 19788 +Epoch: [20] [ 630/2138] eta: 1:35:23 lr: 2.6438214199284977e-05 loss: 0.0294 (0.0307) time: 3.8636 data: 0.0034 max mem: 19788 +Epoch: [20] [ 640/2138] eta: 1:34:46 lr: 2.6432566148013138e-05 loss: 0.0253 (0.0307) time: 3.8652 data: 0.0034 max mem: 19788 +Epoch: [20] [ 650/2138] eta: 1:34:10 lr: 2.6426917962642227e-05 loss: 0.0274 (0.0307) time: 3.8506 data: 0.0033 max mem: 19788 +Epoch: [20] [ 660/2138] eta: 1:33:30 lr: 2.6421269643137235e-05 loss: 0.0281 (0.0306) time: 3.8129 data: 0.0031 max mem: 19788 +Epoch: [20] [ 670/2138] eta: 1:32:51 lr: 2.6415621189463095e-05 loss: 0.0291 (0.0306) time: 3.7243 data: 0.0030 max mem: 19788 +Epoch: [20] [ 680/2138] eta: 1:32:10 lr: 2.6409972601584754e-05 loss: 0.0303 (0.0306) time: 3.6853 data: 0.0030 max mem: 19788 +Epoch: [20] [ 690/2138] eta: 1:31:33 lr: 2.640432387946712e-05 loss: 0.0304 (0.0307) time: 3.7661 data: 0.0031 max mem: 19788 +Epoch: [20] [ 700/2138] eta: 1:30:54 lr: 2.63986750230751e-05 loss: 0.0289 (0.0306) time: 3.8042 data: 0.0031 max mem: 19788 +Epoch: [20] [ 710/2138] eta: 1:30:15 lr: 2.6393026032373563e-05 loss: 0.0289 (0.0306) time: 3.7353 data: 0.0032 max mem: 19788 +Epoch: [20] [ 720/2138] eta: 1:29:35 lr: 2.6387376907327387e-05 loss: 0.0258 (0.0306) time: 3.6974 data: 0.0032 max mem: 19788 +Epoch: [20] [ 730/2138] eta: 1:28:56 lr: 2.6381727647901416e-05 loss: 0.0246 (0.0306) time: 3.7110 data: 0.0031 max mem: 19788 +Epoch: [20] [ 740/2138] eta: 1:28:16 lr: 2.6376078254060478e-05 loss: 0.0239 (0.0309) time: 3.7140 data: 0.0030 max mem: 19788 +Epoch: [20] [ 750/2138] eta: 1:27:40 lr: 2.6370428725769373e-05 loss: 0.0261 (0.0309) time: 3.7762 data: 0.0030 max mem: 19788 +Epoch: [20] [ 760/2138] eta: 1:27:08 lr: 2.6364779062992917e-05 loss: 0.0311 (0.0309) time: 3.9950 data: 0.0033 max mem: 19788 +Epoch: [20] [ 770/2138] eta: 1:26:28 lr: 2.635912926569587e-05 loss: 0.0311 (0.0312) time: 3.9049 data: 0.0033 max mem: 19788 +Epoch: [20] [ 780/2138] eta: 1:25:50 lr: 2.6353479333843e-05 loss: 0.0309 (0.0312) time: 3.7309 data: 0.0032 max mem: 19788 +Epoch: [20] [ 790/2138] eta: 1:25:10 lr: 2.6347829267399036e-05 loss: 0.0304 (0.0312) time: 3.7306 data: 0.0030 max mem: 19788 +Epoch: [20] [ 800/2138] eta: 1:24:31 lr: 2.634217906632872e-05 loss: 0.0288 (0.0312) time: 3.7088 data: 0.0031 max mem: 19788 +Epoch: [20] [ 810/2138] eta: 1:23:53 lr: 2.6336528730596743e-05 loss: 0.0300 (0.0312) time: 3.7528 data: 0.0031 max mem: 19788 +Epoch: [20] [ 820/2138] eta: 1:23:14 lr: 2.6330878260167795e-05 loss: 0.0315 (0.0312) time: 3.7680 data: 0.0031 max mem: 19788 +Epoch: [20] [ 830/2138] eta: 1:22:37 lr: 2.6325227655006557e-05 loss: 0.0274 (0.0311) time: 3.7793 data: 0.0032 max mem: 19788 +Epoch: [20] [ 840/2138] eta: 1:21:58 lr: 2.631957691507766e-05 loss: 0.0229 (0.0310) time: 3.7585 data: 0.0033 max mem: 19788 +Epoch: [20] [ 850/2138] eta: 1:21:18 lr: 2.6313926040345765e-05 loss: 0.0243 (0.0310) time: 3.6902 data: 0.0034 max mem: 19788 +Epoch: [20] [ 860/2138] eta: 1:20:39 lr: 2.630827503077547e-05 loss: 0.0266 (0.0311) time: 3.6801 data: 0.0033 max mem: 19788 +Epoch: [20] [ 870/2138] eta: 1:20:00 lr: 2.6302623886331384e-05 loss: 0.0309 (0.0311) time: 3.7227 data: 0.0031 max mem: 19788 +Epoch: [20] [ 880/2138] eta: 1:19:21 lr: 2.6296972606978083e-05 loss: 0.0294 (0.0311) time: 3.7253 data: 0.0031 max mem: 19788 +Epoch: [20] [ 890/2138] eta: 1:18:42 lr: 2.6291321192680142e-05 loss: 0.0299 (0.0312) time: 3.6748 data: 0.0029 max mem: 19788 +Epoch: [20] [ 900/2138] eta: 1:18:02 lr: 2.6285669643402093e-05 loss: 0.0342 (0.0313) time: 3.6621 data: 0.0030 max mem: 19788 +Epoch: [20] [ 910/2138] eta: 1:17:26 lr: 2.6280017959108477e-05 loss: 0.0293 (0.0312) time: 3.7843 data: 0.0031 max mem: 19788 +Epoch: [20] [ 920/2138] eta: 1:16:46 lr: 2.6274366139763795e-05 loss: 0.0281 (0.0312) time: 3.7805 data: 0.0030 max mem: 19788 +Epoch: [20] [ 930/2138] eta: 1:16:09 lr: 2.626871418533255e-05 loss: 0.0278 (0.0312) time: 3.7371 data: 0.0030 max mem: 19788 +Epoch: [20] [ 940/2138] eta: 1:15:31 lr: 2.62630620957792e-05 loss: 0.0299 (0.0312) time: 3.7739 data: 0.0030 max mem: 19788 +Epoch: [20] [ 950/2138] eta: 1:14:51 lr: 2.6257409871068227e-05 loss: 0.0299 (0.0312) time: 3.6990 data: 0.0029 max mem: 19788 +Epoch: [20] [ 960/2138] eta: 1:14:12 lr: 2.625175751116405e-05 loss: 0.0282 (0.0312) time: 3.6731 data: 0.0029 max mem: 19788 +Epoch: [20] [ 970/2138] eta: 1:13:34 lr: 2.6246105016031104e-05 loss: 0.0268 (0.0312) time: 3.7060 data: 0.0030 max mem: 19788 +Epoch: [20] [ 980/2138] eta: 1:12:58 lr: 2.6240452385633778e-05 loss: 0.0262 (0.0311) time: 3.8171 data: 0.0030 max mem: 19788 +Epoch: [20] [ 990/2138] eta: 1:12:19 lr: 2.6234799619936474e-05 loss: 0.0274 (0.0311) time: 3.8184 data: 0.0029 max mem: 19788 +Epoch: [20] [1000/2138] eta: 1:11:41 lr: 2.6229146718903546e-05 loss: 0.0313 (0.0312) time: 3.7529 data: 0.0028 max mem: 19788 +Epoch: [20] [1010/2138] eta: 1:11:04 lr: 2.6223493682499357e-05 loss: 0.0270 (0.0312) time: 3.7855 data: 0.0028 max mem: 19788 +Epoch: [20] [1020/2138] eta: 1:10:25 lr: 2.6217840510688223e-05 loss: 0.0267 (0.0311) time: 3.7478 data: 0.0029 max mem: 19788 +Epoch: [20] [1030/2138] eta: 1:09:47 lr: 2.6212187203434475e-05 loss: 0.0267 (0.0311) time: 3.7110 data: 0.0030 max mem: 19788 +Epoch: [20] [1040/2138] eta: 1:09:09 lr: 2.6206533760702395e-05 loss: 0.0276 (0.0311) time: 3.7393 data: 0.0029 max mem: 19788 +Epoch: [20] [1050/2138] eta: 1:08:33 lr: 2.620088018245627e-05 loss: 0.0276 (0.0311) time: 3.8611 data: 0.0028 max mem: 19788 +Epoch: [20] [1060/2138] eta: 1:07:54 lr: 2.6195226468660362e-05 loss: 0.0275 (0.0310) time: 3.8459 data: 0.0028 max mem: 19788 +Epoch: [20] [1070/2138] eta: 1:07:15 lr: 2.6189572619278907e-05 loss: 0.0270 (0.0310) time: 3.6845 data: 0.0032 max mem: 19788 +Epoch: [20] [1080/2138] eta: 1:06:37 lr: 2.6183918634276127e-05 loss: 0.0262 (0.0310) time: 3.6817 data: 0.0034 max mem: 19788 +Epoch: [20] [1090/2138] eta: 1:05:58 lr: 2.617826451361624e-05 loss: 0.0262 (0.0310) time: 3.6826 data: 0.0030 max mem: 19788 +Epoch: [20] [1100/2138] eta: 1:05:19 lr: 2.617261025726342e-05 loss: 0.0344 (0.0311) time: 3.6485 data: 0.0030 max mem: 19788 +Epoch: [20] [1110/2138] eta: 1:04:42 lr: 2.616695586518184e-05 loss: 0.0322 (0.0310) time: 3.7534 data: 0.0031 max mem: 19788 +Epoch: [20] [1120/2138] eta: 1:04:05 lr: 2.6161301337335658e-05 loss: 0.0270 (0.0310) time: 3.8795 data: 0.0030 max mem: 19788 +Epoch: [20] [1130/2138] eta: 1:03:26 lr: 2.615564667368901e-05 loss: 0.0301 (0.0310) time: 3.7871 data: 0.0032 max mem: 19788 +Epoch: [20] [1140/2138] eta: 1:02:49 lr: 2.614999187420601e-05 loss: 0.0301 (0.0310) time: 3.7672 data: 0.0032 max mem: 19788 +Epoch: [20] [1150/2138] eta: 1:02:12 lr: 2.6144336938850744e-05 loss: 0.0255 (0.0309) time: 3.8433 data: 0.0028 max mem: 19788 +Epoch: [20] [1160/2138] eta: 1:01:34 lr: 2.6138681867587305e-05 loss: 0.0256 (0.0309) time: 3.7924 data: 0.0028 max mem: 19788 +Epoch: [20] [1170/2138] eta: 1:00:56 lr: 2.6133026660379744e-05 loss: 0.0272 (0.0309) time: 3.7649 data: 0.0029 max mem: 19788 +Epoch: [20] [1180/2138] eta: 1:00:18 lr: 2.6127371317192118e-05 loss: 0.0272 (0.0310) time: 3.7582 data: 0.0029 max mem: 19788 +Epoch: [20] [1190/2138] eta: 0:59:43 lr: 2.6121715837988437e-05 loss: 0.0263 (0.0309) time: 3.8868 data: 0.0028 max mem: 19788 +Epoch: [20] [1200/2138] eta: 0:59:04 lr: 2.6116060222732724e-05 loss: 0.0292 (0.0309) time: 3.8917 data: 0.0029 max mem: 19788 +Epoch: [20] [1210/2138] eta: 0:58:26 lr: 2.611040447138895e-05 loss: 0.0292 (0.0309) time: 3.6986 data: 0.0031 max mem: 19788 +Epoch: [20] [1220/2138] eta: 0:57:48 lr: 2.61047485839211e-05 loss: 0.0268 (0.0309) time: 3.6886 data: 0.0030 max mem: 19788 +Epoch: [20] [1230/2138] eta: 0:57:11 lr: 2.6099092560293115e-05 loss: 0.0268 (0.0309) time: 3.8630 data: 0.0029 max mem: 19788 +Epoch: [20] [1240/2138] eta: 0:56:34 lr: 2.609343640046894e-05 loss: 0.0282 (0.0309) time: 3.9065 data: 0.0030 max mem: 19788 +Epoch: [20] [1250/2138] eta: 0:55:56 lr: 2.6087780104412484e-05 loss: 0.0282 (0.0309) time: 3.8294 data: 0.0030 max mem: 19788 +Epoch: [20] [1260/2138] eta: 0:55:18 lr: 2.608212367208765e-05 loss: 0.0290 (0.0309) time: 3.7459 data: 0.0030 max mem: 19788 +Epoch: [20] [1270/2138] eta: 0:54:41 lr: 2.6076467103458308e-05 loss: 0.0264 (0.0309) time: 3.7715 data: 0.0031 max mem: 19788 +Epoch: [20] [1280/2138] eta: 0:54:05 lr: 2.6070810398488326e-05 loss: 0.0268 (0.0308) time: 3.9991 data: 0.0033 max mem: 19788 +Epoch: [20] [1290/2138] eta: 0:53:28 lr: 2.6065153557141546e-05 loss: 0.0278 (0.0308) time: 3.9608 data: 0.0034 max mem: 19788 +Epoch: [20] [1300/2138] eta: 0:52:50 lr: 2.6059496579381797e-05 loss: 0.0278 (0.0308) time: 3.8025 data: 0.0034 max mem: 19788 +Epoch: [20] [1310/2138] eta: 0:52:12 lr: 2.6053839465172874e-05 loss: 0.0278 (0.0308) time: 3.7646 data: 0.0032 max mem: 19788 +Epoch: [20] [1320/2138] eta: 0:51:35 lr: 2.6048182214478578e-05 loss: 0.0286 (0.0308) time: 3.8309 data: 0.0030 max mem: 19788 +Epoch: [20] [1330/2138] eta: 0:50:59 lr: 2.6042524827262665e-05 loss: 0.0271 (0.0308) time: 4.0488 data: 0.0029 max mem: 19788 +Epoch: [20] [1340/2138] eta: 0:50:21 lr: 2.6036867303488897e-05 loss: 0.0289 (0.0309) time: 3.9261 data: 0.0029 max mem: 19788 +Epoch: [20] [1350/2138] eta: 0:49:42 lr: 2.6031209643121e-05 loss: 0.0361 (0.0309) time: 3.6650 data: 0.0031 max mem: 19788 +Epoch: [20] [1360/2138] eta: 0:49:03 lr: 2.602555184612269e-05 loss: 0.0337 (0.0309) time: 3.6544 data: 0.0034 max mem: 19788 +Epoch: [20] [1370/2138] eta: 0:48:26 lr: 2.6019893912457666e-05 loss: 0.0302 (0.0309) time: 3.7601 data: 0.0033 max mem: 19788 +Epoch: [20] [1380/2138] eta: 0:47:48 lr: 2.6014235842089607e-05 loss: 0.0279 (0.0309) time: 3.7957 data: 0.0029 max mem: 19788 +Epoch: [20] [1390/2138] eta: 0:47:10 lr: 2.6008577634982163e-05 loss: 0.0288 (0.0309) time: 3.7301 data: 0.0030 max mem: 19788 +Epoch: [20] [1400/2138] eta: 0:46:32 lr: 2.6002919291098983e-05 loss: 0.0288 (0.0309) time: 3.7902 data: 0.0032 max mem: 19788 +Epoch: [20] [1410/2138] eta: 0:45:55 lr: 2.5997260810403678e-05 loss: 0.0276 (0.0308) time: 3.8512 data: 0.0032 max mem: 19788 +Epoch: [20] [1420/2138] eta: 0:45:17 lr: 2.5991602192859864e-05 loss: 0.0269 (0.0308) time: 3.7859 data: 0.0029 max mem: 19788 +Epoch: [20] [1430/2138] eta: 0:44:38 lr: 2.5985943438431127e-05 loss: 0.0273 (0.0308) time: 3.6816 data: 0.0029 max mem: 19788 +Epoch: [20] [1440/2138] eta: 0:44:00 lr: 2.5980284547081026e-05 loss: 0.0273 (0.0308) time: 3.6932 data: 0.0031 max mem: 19788 +Epoch: [20] [1450/2138] eta: 0:43:22 lr: 2.597462551877311e-05 loss: 0.0308 (0.0308) time: 3.7283 data: 0.0032 max mem: 19788 +Epoch: [20] [1460/2138] eta: 0:42:44 lr: 2.596896635347091e-05 loss: 0.0316 (0.0309) time: 3.7251 data: 0.0033 max mem: 19788 +Epoch: [20] [1470/2138] eta: 0:42:06 lr: 2.5963307051137942e-05 loss: 0.0297 (0.0309) time: 3.7474 data: 0.0034 max mem: 19788 +Epoch: [20] [1480/2138] eta: 0:41:28 lr: 2.5957647611737683e-05 loss: 0.0315 (0.0309) time: 3.7470 data: 0.0032 max mem: 19788 +Epoch: [20] [1490/2138] eta: 0:40:50 lr: 2.5951988035233632e-05 loss: 0.0311 (0.0309) time: 3.6967 data: 0.0029 max mem: 19788 +Epoch: [20] [1500/2138] eta: 0:40:12 lr: 2.594632832158922e-05 loss: 0.0292 (0.0309) time: 3.7063 data: 0.0029 max mem: 19788 +Epoch: [20] [1510/2138] eta: 0:39:33 lr: 2.5940668470767898e-05 loss: 0.0292 (0.0309) time: 3.7095 data: 0.0031 max mem: 19788 +Epoch: [20] [1520/2138] eta: 0:38:55 lr: 2.5935008482733082e-05 loss: 0.0265 (0.0309) time: 3.6916 data: 0.0031 max mem: 19788 +Epoch: [20] [1530/2138] eta: 0:38:17 lr: 2.592934835744817e-05 loss: 0.0252 (0.0309) time: 3.7459 data: 0.0032 max mem: 19788 +Epoch: [20] [1540/2138] eta: 0:37:40 lr: 2.5923688094876538e-05 loss: 0.0252 (0.0309) time: 3.7863 data: 0.0032 max mem: 19788 +Epoch: [20] [1550/2138] eta: 0:37:03 lr: 2.5918027694981557e-05 loss: 0.0315 (0.0309) time: 3.8870 data: 0.0030 max mem: 19788 +Epoch: [20] [1560/2138] eta: 0:36:25 lr: 2.5912367157726557e-05 loss: 0.0322 (0.0309) time: 3.8603 data: 0.0029 max mem: 19788 +Epoch: [20] [1570/2138] eta: 0:35:47 lr: 2.5906706483074884e-05 loss: 0.0312 (0.0309) time: 3.7823 data: 0.0029 max mem: 19788 +Epoch: [20] [1580/2138] eta: 0:35:09 lr: 2.5901045670989825e-05 loss: 0.0260 (0.0309) time: 3.7673 data: 0.0032 max mem: 19788 +Epoch: [20] [1590/2138] eta: 0:34:31 lr: 2.5895384721434684e-05 loss: 0.0263 (0.0309) time: 3.6837 data: 0.0031 max mem: 19788 +Epoch: [20] [1600/2138] eta: 0:33:53 lr: 2.588972363437271e-05 loss: 0.0331 (0.0309) time: 3.6919 data: 0.0028 max mem: 19788 +Epoch: [20] [1610/2138] eta: 0:33:15 lr: 2.5884062409767175e-05 loss: 0.0270 (0.0309) time: 3.6883 data: 0.0029 max mem: 19788 +Epoch: [20] [1620/2138] eta: 0:32:36 lr: 2.5878401047581285e-05 loss: 0.0269 (0.0309) time: 3.6533 data: 0.0032 max mem: 19788 +Epoch: [20] [1630/2138] eta: 0:31:58 lr: 2.587273954777828e-05 loss: 0.0291 (0.0309) time: 3.6517 data: 0.0034 max mem: 19788 +Epoch: [20] [1640/2138] eta: 0:31:20 lr: 2.586707791032133e-05 loss: 0.0287 (0.0308) time: 3.6956 data: 0.0032 max mem: 19788 +Epoch: [20] [1650/2138] eta: 0:30:43 lr: 2.5861416135173627e-05 loss: 0.0252 (0.0308) time: 3.8386 data: 0.0031 max mem: 19788 +Epoch: [20] [1660/2138] eta: 0:30:05 lr: 2.5855754222298317e-05 loss: 0.0240 (0.0308) time: 3.8309 data: 0.0031 max mem: 19788 +Epoch: [20] [1670/2138] eta: 0:29:28 lr: 2.585009217165854e-05 loss: 0.0240 (0.0308) time: 3.8486 data: 0.0031 max mem: 19788 +Epoch: [20] [1680/2138] eta: 0:28:51 lr: 2.5844429983217416e-05 loss: 0.0257 (0.0308) time: 4.0911 data: 0.0031 max mem: 19788 +Epoch: [20] [1690/2138] eta: 0:28:13 lr: 2.5838767656938046e-05 loss: 0.0283 (0.0308) time: 3.9707 data: 0.0030 max mem: 19788 +Epoch: [20] [1700/2138] eta: 0:27:35 lr: 2.58331051927835e-05 loss: 0.0274 (0.0308) time: 3.7330 data: 0.0030 max mem: 19788 +Epoch: [20] [1710/2138] eta: 0:26:58 lr: 2.5827442590716855e-05 loss: 0.0274 (0.0308) time: 3.8057 data: 0.0032 max mem: 19788 +Epoch: [20] [1720/2138] eta: 0:26:20 lr: 2.5821779850701145e-05 loss: 0.0269 (0.0308) time: 3.8669 data: 0.0032 max mem: 19788 +Epoch: [20] [1730/2138] eta: 0:25:43 lr: 2.5816116972699394e-05 loss: 0.0272 (0.0308) time: 3.8923 data: 0.0031 max mem: 19788 +Epoch: [20] [1740/2138] eta: 0:25:05 lr: 2.5810453956674614e-05 loss: 0.0275 (0.0308) time: 3.7928 data: 0.0031 max mem: 19788 +Epoch: [20] [1750/2138] eta: 0:24:27 lr: 2.580479080258978e-05 loss: 0.0301 (0.0308) time: 3.7267 data: 0.0032 max mem: 19788 +Epoch: [20] [1760/2138] eta: 0:23:49 lr: 2.5799127510407867e-05 loss: 0.0305 (0.0308) time: 3.8820 data: 0.0031 max mem: 19788 +Epoch: [20] [1770/2138] eta: 0:23:12 lr: 2.5793464080091818e-05 loss: 0.0279 (0.0308) time: 3.8614 data: 0.0030 max mem: 19788 +Epoch: [20] [1780/2138] eta: 0:22:33 lr: 2.578780051160457e-05 loss: 0.0264 (0.0308) time: 3.7028 data: 0.0032 max mem: 19788 +Epoch: [20] [1790/2138] eta: 0:21:56 lr: 2.5782136804909023e-05 loss: 0.0275 (0.0308) time: 3.7649 data: 0.0033 max mem: 19788 +Epoch: [20] [1800/2138] eta: 0:21:19 lr: 2.5776472959968084e-05 loss: 0.0260 (0.0308) time: 3.9947 data: 0.0030 max mem: 19788 +Epoch: [20] [1810/2138] eta: 0:20:41 lr: 2.577080897674461e-05 loss: 0.0260 (0.0308) time: 3.9928 data: 0.0029 max mem: 19788 +Epoch: [20] [1820/2138] eta: 0:20:03 lr: 2.5765144855201457e-05 loss: 0.0262 (0.0308) time: 3.8839 data: 0.0030 max mem: 19788 +Epoch: [20] [1830/2138] eta: 0:19:25 lr: 2.5759480595301462e-05 loss: 0.0276 (0.0308) time: 3.8212 data: 0.0030 max mem: 19788 +Epoch: [20] [1840/2138] eta: 0:18:47 lr: 2.575381619700744e-05 loss: 0.0290 (0.0308) time: 3.7397 data: 0.0031 max mem: 19788 +Epoch: [20] [1850/2138] eta: 0:18:10 lr: 2.5748151660282187e-05 loss: 0.0298 (0.0308) time: 3.7379 data: 0.0031 max mem: 19788 +Epoch: [20] [1860/2138] eta: 0:17:32 lr: 2.574248698508848e-05 loss: 0.0308 (0.0308) time: 3.7173 data: 0.0030 max mem: 19788 +Epoch: [20] [1870/2138] eta: 0:16:54 lr: 2.5736822171389074e-05 loss: 0.0308 (0.0308) time: 3.7933 data: 0.0030 max mem: 19788 +Epoch: [20] [1880/2138] eta: 0:16:16 lr: 2.5731157219146713e-05 loss: 0.0280 (0.0308) time: 3.8118 data: 0.0031 max mem: 19788 +Epoch: [20] [1890/2138] eta: 0:15:38 lr: 2.5725492128324107e-05 loss: 0.0264 (0.0308) time: 3.7231 data: 0.0033 max mem: 19788 +Epoch: [20] [1900/2138] eta: 0:15:00 lr: 2.5719826898883962e-05 loss: 0.0250 (0.0308) time: 3.7975 data: 0.0032 max mem: 19788 +Epoch: [20] [1910/2138] eta: 0:14:22 lr: 2.5714161530788967e-05 loss: 0.0250 (0.0308) time: 3.7663 data: 0.0034 max mem: 19788 +Epoch: [20] [1920/2138] eta: 0:13:44 lr: 2.570849602400177e-05 loss: 0.0281 (0.0308) time: 3.6890 data: 0.0035 max mem: 19788 +Epoch: [20] [1930/2138] eta: 0:13:07 lr: 2.570283037848502e-05 loss: 0.0289 (0.0308) time: 3.7731 data: 0.0032 max mem: 19788 +Epoch: [20] [1940/2138] eta: 0:12:29 lr: 2.5697164594201344e-05 loss: 0.0276 (0.0308) time: 3.8220 data: 0.0030 max mem: 19788 +Epoch: [20] [1950/2138] eta: 0:11:51 lr: 2.569149867111334e-05 loss: 0.0266 (0.0308) time: 3.7796 data: 0.0030 max mem: 19788 +Epoch: [20] [1960/2138] eta: 0:11:13 lr: 2.5685832609183604e-05 loss: 0.0255 (0.0307) time: 3.7835 data: 0.0031 max mem: 19788 +Epoch: [20] [1970/2138] eta: 0:10:35 lr: 2.5680166408374685e-05 loss: 0.0257 (0.0307) time: 3.7785 data: 0.0031 max mem: 19788 +Epoch: [20] [1980/2138] eta: 0:09:57 lr: 2.5674500068649143e-05 loss: 0.0253 (0.0307) time: 3.7433 data: 0.0032 max mem: 19788 +Epoch: [20] [1990/2138] eta: 0:09:20 lr: 2.5668833589969494e-05 loss: 0.0253 (0.0307) time: 3.8085 data: 0.0031 max mem: 19788 +Epoch: [20] [2000/2138] eta: 0:08:42 lr: 2.5663166972298257e-05 loss: 0.0310 (0.0307) time: 3.8140 data: 0.0030 max mem: 19788 +Epoch: [20] [2010/2138] eta: 0:08:04 lr: 2.5657500215597918e-05 loss: 0.0282 (0.0307) time: 3.7969 data: 0.0029 max mem: 19788 +Epoch: [20] [2020/2138] eta: 0:07:26 lr: 2.565183331983094e-05 loss: 0.0282 (0.0307) time: 3.8937 data: 0.0029 max mem: 19788 +Epoch: [20] [2030/2138] eta: 0:06:48 lr: 2.5646166284959782e-05 loss: 0.0287 (0.0307) time: 3.8523 data: 0.0030 max mem: 19788 +Epoch: [20] [2040/2138] eta: 0:06:10 lr: 2.564049911094687e-05 loss: 0.0268 (0.0307) time: 3.7760 data: 0.0032 max mem: 19788 +Epoch: [20] [2050/2138] eta: 0:05:33 lr: 2.5634831797754616e-05 loss: 0.0271 (0.0307) time: 3.8609 data: 0.0033 max mem: 19788 +Epoch: [20] [2060/2138] eta: 0:04:55 lr: 2.5629164345345402e-05 loss: 0.0286 (0.0307) time: 3.9248 data: 0.0031 max mem: 19788 +Epoch: [20] [2070/2138] eta: 0:04:17 lr: 2.562349675368162e-05 loss: 0.0294 (0.0307) time: 3.8374 data: 0.0029 max mem: 19788 +Epoch: [20] [2080/2138] eta: 0:03:39 lr: 2.5617829022725603e-05 loss: 0.0271 (0.0307) time: 3.7260 data: 0.0029 max mem: 19788 +Epoch: [20] [2090/2138] eta: 0:03:01 lr: 2.56121611524397e-05 loss: 0.0271 (0.0307) time: 3.7153 data: 0.0031 max mem: 19788 +Epoch: [20] [2100/2138] eta: 0:02:23 lr: 2.560649314278622e-05 loss: 0.0249 (0.0307) time: 3.8335 data: 0.0032 max mem: 19788 +Epoch: [20] [2110/2138] eta: 0:01:46 lr: 2.5600824993727456e-05 loss: 0.0301 (0.0307) time: 3.8475 data: 0.0030 max mem: 19788 +Epoch: [20] [2120/2138] eta: 0:01:08 lr: 2.5595156705225674e-05 loss: 0.0347 (0.0307) time: 3.8713 data: 0.0029 max mem: 19788 +Epoch: [20] [2130/2138] eta: 0:00:30 lr: 2.5589488277243157e-05 loss: 0.0284 (0.0307) time: 3.8149 data: 0.0029 max mem: 19788 +Epoch: [20] Total time: 2:14:54 +Test: [ 0/21770] eta: 18:13:01 time: 3.0125 data: 2.6564 max mem: 19788 +Test: [ 100/21770] eta: 0:36:18 time: 0.0772 data: 0.0023 max mem: 19788 +Test: [ 200/21770] eta: 0:30:10 time: 0.0661 data: 0.0019 max mem: 19788 +Test: [ 300/21770] eta: 0:28:07 time: 0.0699 data: 0.0020 max mem: 19788 +Test: [ 400/21770] eta: 0:26:52 time: 0.0778 data: 0.0021 max mem: 19788 +Test: [ 500/21770] eta: 0:26:25 time: 0.0595 data: 0.0019 max mem: 19788 +Test: [ 600/21770] eta: 0:26:14 time: 0.0723 data: 0.0021 max mem: 19788 +Test: [ 700/21770] eta: 0:25:32 time: 0.0650 data: 0.0020 max mem: 19788 +Test: [ 800/21770] eta: 0:25:10 time: 0.0732 data: 0.0022 max mem: 19788 +Test: [ 900/21770] eta: 0:24:59 time: 0.0787 data: 0.0024 max mem: 19788 +Test: [ 1000/21770] eta: 0:24:41 time: 0.0661 data: 0.0020 max mem: 19788 +Test: [ 1100/21770] eta: 0:24:40 time: 0.0614 data: 0.0017 max mem: 19788 +Test: [ 1200/21770] eta: 0:24:22 time: 0.0615 data: 0.0019 max mem: 19788 +Test: [ 1300/21770] eta: 0:24:18 time: 0.0617 data: 0.0019 max mem: 19788 +Test: [ 1400/21770] eta: 0:24:08 time: 0.0635 data: 0.0020 max mem: 19788 +Test: [ 1500/21770] eta: 0:23:47 time: 0.0601 data: 0.0018 max mem: 19788 +Test: [ 1600/21770] eta: 0:23:35 time: 0.0634 data: 0.0020 max mem: 19788 +Test: [ 1700/21770] eta: 0:23:20 time: 0.0629 data: 0.0018 max mem: 19788 +Test: [ 1800/21770] eta: 0:23:04 time: 0.0606 data: 0.0020 max mem: 19788 +Test: [ 1900/21770] eta: 0:23:00 time: 0.0709 data: 0.0020 max mem: 19788 +Test: [ 2000/21770] eta: 0:22:53 time: 0.0598 data: 0.0018 max mem: 19788 +Test: [ 2100/21770] eta: 0:22:46 time: 0.0820 data: 0.0026 max mem: 19788 +Test: [ 2200/21770] eta: 0:22:47 time: 0.0665 data: 0.0020 max mem: 19788 +Test: [ 2300/21770] eta: 0:22:41 time: 0.0637 data: 0.0019 max mem: 19788 +Test: [ 2400/21770] eta: 0:22:37 time: 0.0656 data: 0.0020 max mem: 19788 +Test: [ 2500/21770] eta: 0:22:33 time: 0.0761 data: 0.0019 max mem: 19788 +Test: [ 2600/21770] eta: 0:22:20 time: 0.0624 data: 0.0018 max mem: 19788 +Test: [ 2700/21770] eta: 0:22:17 time: 0.0815 data: 0.0024 max mem: 19788 +Test: [ 2800/21770] eta: 0:22:16 time: 0.0724 data: 0.0023 max mem: 19788 +Test: [ 2900/21770] eta: 0:22:13 time: 0.0815 data: 0.0020 max mem: 19788 +Test: [ 3000/21770] eta: 0:22:03 time: 0.0588 data: 0.0019 max mem: 19788 +Test: [ 3100/21770] eta: 0:21:56 time: 0.0633 data: 0.0018 max mem: 19788 +Test: [ 3200/21770] eta: 0:21:44 time: 0.0641 data: 0.0019 max mem: 19788 +Test: [ 3300/21770] eta: 0:21:43 time: 0.0815 data: 0.0026 max mem: 19788 +Test: [ 3400/21770] eta: 0:21:42 time: 0.0810 data: 0.0024 max mem: 19788 +Test: [ 3500/21770] eta: 0:21:39 time: 0.0742 data: 0.0024 max mem: 19788 +Test: [ 3600/21770] eta: 0:21:29 time: 0.0669 data: 0.0020 max mem: 19788 +Test: [ 3700/21770] eta: 0:21:22 time: 0.0636 data: 0.0018 max mem: 19788 +Test: [ 3800/21770] eta: 0:21:17 time: 0.0825 data: 0.0019 max mem: 19788 +Test: [ 3900/21770] eta: 0:21:11 time: 0.0816 data: 0.0023 max mem: 19788 +Test: [ 4000/21770] eta: 0:21:02 time: 0.0617 data: 0.0020 max mem: 19788 +Test: [ 4100/21770] eta: 0:20:54 time: 0.0810 data: 0.0020 max mem: 19788 +Test: [ 4200/21770] eta: 0:20:48 time: 0.0814 data: 0.0025 max mem: 19788 +Test: [ 4300/21770] eta: 0:20:41 time: 0.0636 data: 0.0019 max mem: 19788 +Test: [ 4400/21770] eta: 0:20:30 time: 0.0625 data: 0.0018 max mem: 19788 +Test: [ 4500/21770] eta: 0:20:19 time: 0.0639 data: 0.0018 max mem: 19788 +Test: [ 4600/21770] eta: 0:20:12 time: 0.0669 data: 0.0019 max mem: 19788 +Test: [ 4700/21770] eta: 0:20:07 time: 0.0632 data: 0.0018 max mem: 19788 +Test: [ 4800/21770] eta: 0:19:58 time: 0.0613 data: 0.0017 max mem: 19788 +Test: [ 4900/21770] eta: 0:19:48 time: 0.0643 data: 0.0018 max mem: 19788 +Test: [ 5000/21770] eta: 0:19:40 time: 0.0674 data: 0.0020 max mem: 19788 +Test: [ 5100/21770] eta: 0:19:32 time: 0.0834 data: 0.0025 max mem: 19788 +Test: [ 5200/21770] eta: 0:19:28 time: 0.0730 data: 0.0020 max mem: 19788 +Test: [ 5300/21770] eta: 0:19:22 time: 0.0619 data: 0.0018 max mem: 19788 +Test: [ 5400/21770] eta: 0:19:14 time: 0.0645 data: 0.0019 max mem: 19788 +Test: [ 5500/21770] eta: 0:19:06 time: 0.0629 data: 0.0018 max mem: 19788 +Test: [ 5600/21770] eta: 0:18:59 time: 0.0754 data: 0.0024 max mem: 19788 +Test: [ 5700/21770] eta: 0:18:51 time: 0.0698 data: 0.0021 max mem: 19788 +Test: [ 5800/21770] eta: 0:18:43 time: 0.0679 data: 0.0020 max mem: 19788 +Test: [ 5900/21770] eta: 0:18:35 time: 0.0720 data: 0.0022 max mem: 19788 +Test: [ 6000/21770] eta: 0:18:27 time: 0.0626 data: 0.0019 max mem: 19788 +Test: [ 6100/21770] eta: 0:18:21 time: 0.0764 data: 0.0022 max mem: 19788 +Test: [ 6200/21770] eta: 0:18:12 time: 0.0620 data: 0.0019 max mem: 19788 +Test: [ 6300/21770] eta: 0:18:04 time: 0.0600 data: 0.0019 max mem: 19788 +Test: [ 6400/21770] eta: 0:17:58 time: 0.0816 data: 0.0018 max mem: 19788 +Test: [ 6500/21770] eta: 0:17:52 time: 0.0700 data: 0.0020 max mem: 19788 +Test: [ 6600/21770] eta: 0:17:44 time: 0.0631 data: 0.0018 max mem: 19788 +Test: [ 6700/21770] eta: 0:17:35 time: 0.0649 data: 0.0018 max mem: 19788 +Test: [ 6800/21770] eta: 0:17:29 time: 0.0630 data: 0.0019 max mem: 19788 +Test: [ 6900/21770] eta: 0:17:23 time: 0.0674 data: 0.0018 max mem: 19788 +Test: [ 7000/21770] eta: 0:17:14 time: 0.0620 data: 0.0018 max mem: 19788 +Test: [ 7100/21770] eta: 0:17:07 time: 0.0603 data: 0.0021 max mem: 19788 +Test: [ 7200/21770] eta: 0:17:00 time: 0.0713 data: 0.0019 max mem: 19788 +Test: [ 7300/21770] eta: 0:16:53 time: 0.0702 data: 0.0019 max mem: 19788 +Test: [ 7400/21770] eta: 0:16:45 time: 0.0634 data: 0.0018 max mem: 19788 +Test: [ 7500/21770] eta: 0:16:38 time: 0.0658 data: 0.0019 max mem: 19788 +Test: [ 7600/21770] eta: 0:16:31 time: 0.0813 data: 0.0025 max mem: 19788 +Test: [ 7700/21770] eta: 0:16:25 time: 0.0649 data: 0.0019 max mem: 19788 +Test: [ 7800/21770] eta: 0:16:17 time: 0.0625 data: 0.0019 max mem: 19788 +Test: [ 7900/21770] eta: 0:16:09 time: 0.0692 data: 0.0020 max mem: 19788 +Test: [ 8000/21770] eta: 0:16:02 time: 0.0613 data: 0.0018 max mem: 19788 +Test: [ 8100/21770] eta: 0:15:55 time: 0.0777 data: 0.0023 max mem: 19788 +Test: [ 8200/21770] eta: 0:15:48 time: 0.0781 data: 0.0023 max mem: 19788 +Test: [ 8300/21770] eta: 0:15:43 time: 0.0799 data: 0.0024 max mem: 19788 +Test: [ 8400/21770] eta: 0:15:36 time: 0.0819 data: 0.0025 max mem: 19788 +Test: [ 8500/21770] eta: 0:15:29 time: 0.0680 data: 0.0019 max mem: 19788 +Test: [ 8600/21770] eta: 0:15:21 time: 0.0629 data: 0.0019 max mem: 19788 +Test: [ 8700/21770] eta: 0:15:13 time: 0.0600 data: 0.0018 max mem: 19788 +Test: [ 8800/21770] eta: 0:15:06 time: 0.0677 data: 0.0019 max mem: 19788 +Test: [ 8900/21770] eta: 0:14:59 time: 0.0796 data: 0.0021 max mem: 19788 +Test: [ 9000/21770] eta: 0:14:52 time: 0.0757 data: 0.0020 max mem: 19788 +Test: [ 9100/21770] eta: 0:14:46 time: 0.0665 data: 0.0020 max mem: 19788 +Test: [ 9200/21770] eta: 0:14:39 time: 0.0813 data: 0.0024 max mem: 19788 +Test: [ 9300/21770] eta: 0:14:32 time: 0.0609 data: 0.0020 max mem: 19788 +Test: [ 9400/21770] eta: 0:14:24 time: 0.0632 data: 0.0017 max mem: 19788 +Test: [ 9500/21770] eta: 0:14:17 time: 0.0826 data: 0.0021 max mem: 19788 +Test: [ 9600/21770] eta: 0:14:10 time: 0.0639 data: 0.0019 max mem: 19788 +Test: [ 9700/21770] eta: 0:14:03 time: 0.0776 data: 0.0021 max mem: 19788 +Test: [ 9800/21770] eta: 0:13:56 time: 0.0633 data: 0.0018 max mem: 19788 +Test: [ 9900/21770] eta: 0:13:48 time: 0.0630 data: 0.0018 max mem: 19788 +Test: [10000/21770] eta: 0:13:42 time: 0.0788 data: 0.0019 max mem: 19788 +Test: [10100/21770] eta: 0:13:35 time: 0.0652 data: 0.0020 max mem: 19788 +Test: [10200/21770] eta: 0:13:28 time: 0.0656 data: 0.0019 max mem: 19788 +Test: [10300/21770] eta: 0:13:21 time: 0.0642 data: 0.0018 max mem: 19788 +Test: [10400/21770] eta: 0:13:13 time: 0.0702 data: 0.0020 max mem: 19788 +Test: [10500/21770] eta: 0:13:07 time: 0.0794 data: 0.0025 max mem: 19788 +Test: [10600/21770] eta: 0:13:01 time: 0.0815 data: 0.0023 max mem: 19788 +Test: [10700/21770] eta: 0:12:53 time: 0.0680 data: 0.0020 max mem: 19788 +Test: [10800/21770] eta: 0:12:47 time: 0.0784 data: 0.0024 max mem: 19788 +Test: [10900/21770] eta: 0:12:40 time: 0.0685 data: 0.0020 max mem: 19788 +Test: [11000/21770] eta: 0:12:32 time: 0.0714 data: 0.0017 max mem: 19788 +Test: [11100/21770] eta: 0:12:25 time: 0.0671 data: 0.0018 max mem: 19788 +Test: [11200/21770] eta: 0:12:18 time: 0.0787 data: 0.0024 max mem: 19788 +Test: [11300/21770] eta: 0:12:12 time: 0.0751 data: 0.0025 max mem: 19788 +Test: [11400/21770] eta: 0:12:06 time: 0.0812 data: 0.0024 max mem: 19788 +Test: [11500/21770] eta: 0:11:59 time: 0.0713 data: 0.0021 max mem: 19788 +Test: [11600/21770] eta: 0:11:51 time: 0.0648 data: 0.0018 max mem: 19788 +Test: [11700/21770] eta: 0:11:44 time: 0.0807 data: 0.0024 max mem: 19788 +Test: [11800/21770] eta: 0:11:37 time: 0.0649 data: 0.0021 max mem: 19788 +Test: [11900/21770] eta: 0:11:30 time: 0.0642 data: 0.0018 max mem: 19788 +Test: [12000/21770] eta: 0:11:23 time: 0.0823 data: 0.0025 max mem: 19788 +Test: [12100/21770] eta: 0:11:17 time: 0.0820 data: 0.0026 max mem: 19788 +Test: [12200/21770] eta: 0:11:11 time: 0.0823 data: 0.0026 max mem: 19788 +Test: [12300/21770] eta: 0:11:05 time: 0.0810 data: 0.0023 max mem: 19788 +Test: [12400/21770] eta: 0:10:58 time: 0.0650 data: 0.0020 max mem: 19788 +Test: [12500/21770] eta: 0:10:51 time: 0.0635 data: 0.0017 max mem: 19788 +Test: [12600/21770] eta: 0:10:44 time: 0.0644 data: 0.0019 max mem: 19788 +Test: [12700/21770] eta: 0:10:37 time: 0.0800 data: 0.0020 max mem: 19788 +Test: [12800/21770] eta: 0:10:30 time: 0.0641 data: 0.0019 max mem: 19788 +Test: [12900/21770] eta: 0:10:23 time: 0.0806 data: 0.0024 max mem: 19788 +Test: [13000/21770] eta: 0:10:16 time: 0.0632 data: 0.0022 max mem: 19788 +Test: [13100/21770] eta: 0:10:08 time: 0.0646 data: 0.0022 max mem: 19788 +Test: [13200/21770] eta: 0:10:01 time: 0.0632 data: 0.0019 max mem: 19788 +Test: [13300/21770] eta: 0:09:54 time: 0.0752 data: 0.0021 max mem: 19788 +Test: [13400/21770] eta: 0:09:47 time: 0.0669 data: 0.0019 max mem: 19788 +Test: [13500/21770] eta: 0:09:40 time: 0.0763 data: 0.0021 max mem: 19788 +Test: [13600/21770] eta: 0:09:33 time: 0.0628 data: 0.0018 max mem: 19788 +Test: [13700/21770] eta: 0:09:25 time: 0.0655 data: 0.0020 max mem: 19788 +Test: [13800/21770] eta: 0:09:18 time: 0.0625 data: 0.0019 max mem: 19788 +Test: [13900/21770] eta: 0:09:11 time: 0.0669 data: 0.0020 max mem: 19788 +Test: [14000/21770] eta: 0:09:04 time: 0.0782 data: 0.0021 max mem: 19788 +Test: [14100/21770] eta: 0:08:57 time: 0.0662 data: 0.0018 max mem: 19788 +Test: [14200/21770] eta: 0:08:50 time: 0.0819 data: 0.0022 max mem: 19788 +Test: [14300/21770] eta: 0:08:43 time: 0.0633 data: 0.0021 max mem: 19788 +Test: [14400/21770] eta: 0:08:36 time: 0.0669 data: 0.0019 max mem: 19788 +Test: [14500/21770] eta: 0:08:29 time: 0.0667 data: 0.0019 max mem: 19788 +Test: [14600/21770] eta: 0:08:22 time: 0.0822 data: 0.0022 max mem: 19788 +Test: [14700/21770] eta: 0:08:15 time: 0.0607 data: 0.0019 max mem: 19788 +Test: [14800/21770] eta: 0:08:08 time: 0.0675 data: 0.0020 max mem: 19788 +Test: [14900/21770] eta: 0:08:01 time: 0.0652 data: 0.0018 max mem: 19788 +Test: [15000/21770] eta: 0:07:54 time: 0.0656 data: 0.0018 max mem: 19788 +Test: [15100/21770] eta: 0:07:47 time: 0.0642 data: 0.0018 max mem: 19788 +Test: [15200/21770] eta: 0:07:40 time: 0.0640 data: 0.0023 max mem: 19788 +Test: [15300/21770] eta: 0:07:33 time: 0.0589 data: 0.0018 max mem: 19788 +Test: [15400/21770] eta: 0:07:25 time: 0.0650 data: 0.0020 max mem: 19788 +Test: [15500/21770] eta: 0:07:18 time: 0.0817 data: 0.0024 max mem: 19788 +Test: [15600/21770] eta: 0:07:11 time: 0.0831 data: 0.0023 max mem: 19788 +Test: [15700/21770] eta: 0:07:04 time: 0.0648 data: 0.0019 max mem: 19788 +Test: [15800/21770] eta: 0:06:57 time: 0.0611 data: 0.0018 max mem: 19788 +Test: [15900/21770] eta: 0:06:50 time: 0.0812 data: 0.0024 max mem: 19788 +Test: [16000/21770] eta: 0:06:44 time: 0.0785 data: 0.0020 max mem: 19788 +Test: [16100/21770] eta: 0:06:37 time: 0.0714 data: 0.0022 max mem: 19788 +Test: [16200/21770] eta: 0:06:30 time: 0.0645 data: 0.0019 max mem: 19788 +Test: [16300/21770] eta: 0:06:23 time: 0.0675 data: 0.0019 max mem: 19788 +Test: [16400/21770] eta: 0:06:16 time: 0.0641 data: 0.0019 max mem: 19788 +Test: [16500/21770] eta: 0:06:09 time: 0.0829 data: 0.0027 max mem: 19788 +Test: [16600/21770] eta: 0:06:02 time: 0.0637 data: 0.0017 max mem: 19788 +Test: [16700/21770] eta: 0:05:54 time: 0.0610 data: 0.0019 max mem: 19788 +Test: [16800/21770] eta: 0:05:47 time: 0.0601 data: 0.0018 max mem: 19788 +Test: [16900/21770] eta: 0:05:40 time: 0.0724 data: 0.0019 max mem: 19788 +Test: [17000/21770] eta: 0:05:33 time: 0.0617 data: 0.0020 max mem: 19788 +Test: [17100/21770] eta: 0:05:26 time: 0.0644 data: 0.0017 max mem: 19788 +Test: [17200/21770] eta: 0:05:19 time: 0.0627 data: 0.0018 max mem: 19788 +Test: [17300/21770] eta: 0:05:12 time: 0.0606 data: 0.0018 max mem: 19788 +Test: [17400/21770] eta: 0:05:05 time: 0.0796 data: 0.0024 max mem: 19788 +Test: [17500/21770] eta: 0:04:58 time: 0.0633 data: 0.0018 max mem: 19788 +Test: [17600/21770] eta: 0:04:51 time: 0.0640 data: 0.0019 max mem: 19788 +Test: [17700/21770] eta: 0:04:44 time: 0.0818 data: 0.0024 max mem: 19788 +Test: [17800/21770] eta: 0:04:37 time: 0.0777 data: 0.0023 max mem: 19788 +Test: [17900/21770] eta: 0:04:30 time: 0.0759 data: 0.0023 max mem: 19788 +Test: [18000/21770] eta: 0:04:23 time: 0.0817 data: 0.0024 max mem: 19788 +Test: [18100/21770] eta: 0:04:16 time: 0.0815 data: 0.0023 max mem: 19788 +Test: [18200/21770] eta: 0:04:09 time: 0.0640 data: 0.0021 max mem: 19788 +Test: [18300/21770] eta: 0:04:02 time: 0.0622 data: 0.0022 max mem: 19788 +Test: [18400/21770] eta: 0:03:55 time: 0.0794 data: 0.0023 max mem: 19788 +Test: [18500/21770] eta: 0:03:48 time: 0.0610 data: 0.0016 max mem: 19788 +Test: [18600/21770] eta: 0:03:41 time: 0.0619 data: 0.0019 max mem: 19788 +Test: [18700/21770] eta: 0:03:34 time: 0.0616 data: 0.0017 max mem: 19788 +Test: [18800/21770] eta: 0:03:27 time: 0.0593 data: 0.0018 max mem: 19788 +Test: [18900/21770] eta: 0:03:20 time: 0.0719 data: 0.0021 max mem: 19788 +Test: [19000/21770] eta: 0:03:13 time: 0.0622 data: 0.0018 max mem: 19788 +Test: [19100/21770] eta: 0:03:06 time: 0.0597 data: 0.0019 max mem: 19788 +Test: [19200/21770] eta: 0:02:59 time: 0.0619 data: 0.0017 max mem: 19788 +Test: [19300/21770] eta: 0:02:52 time: 0.0609 data: 0.0018 max mem: 19788 +Test: [19400/21770] eta: 0:02:45 time: 0.0622 data: 0.0018 max mem: 19788 +Test: [19500/21770] eta: 0:02:38 time: 0.0637 data: 0.0019 max mem: 19788 +Test: [19600/21770] eta: 0:02:31 time: 0.0631 data: 0.0018 max mem: 19788 +Test: [19700/21770] eta: 0:02:24 time: 0.0639 data: 0.0018 max mem: 19788 +Test: [19800/21770] eta: 0:02:17 time: 0.0622 data: 0.0019 max mem: 19788 +Test: [19900/21770] eta: 0:02:10 time: 0.0643 data: 0.0019 max mem: 19788 +Test: [20000/21770] eta: 0:02:03 time: 0.0773 data: 0.0020 max mem: 19788 +Test: [20100/21770] eta: 0:01:56 time: 0.0624 data: 0.0019 max mem: 19788 +Test: [20200/21770] eta: 0:01:49 time: 0.0816 data: 0.0024 max mem: 19788 +Test: [20300/21770] eta: 0:01:42 time: 0.0822 data: 0.0023 max mem: 19788 +Test: [20400/21770] eta: 0:01:35 time: 0.0608 data: 0.0018 max mem: 19788 +Test: [20500/21770] eta: 0:01:28 time: 0.0670 data: 0.0019 max mem: 19788 +Test: [20600/21770] eta: 0:01:21 time: 0.0751 data: 0.0023 max mem: 19788 +Test: [20700/21770] eta: 0:01:14 time: 0.0635 data: 0.0018 max mem: 19788 +Test: [20800/21770] eta: 0:01:07 time: 0.0743 data: 0.0023 max mem: 19788 +Test: [20900/21770] eta: 0:01:00 time: 0.0829 data: 0.0019 max mem: 19788 +Test: [21000/21770] eta: 0:00:53 time: 0.0706 data: 0.0022 max mem: 19788 +Test: [21100/21770] eta: 0:00:46 time: 0.0608 data: 0.0018 max mem: 19788 +Test: [21200/21770] eta: 0:00:39 time: 0.0624 data: 0.0018 max mem: 19788 +Test: [21300/21770] eta: 0:00:32 time: 0.0818 data: 0.0025 max mem: 19788 +Test: [21400/21770] eta: 0:00:25 time: 0.0666 data: 0.0019 max mem: 19788 +Test: [21500/21770] eta: 0:00:18 time: 0.0761 data: 0.0023 max mem: 19788 +Test: [21600/21770] eta: 0:00:11 time: 0.0624 data: 0.0018 max mem: 19788 +Test: [21700/21770] eta: 0:00:04 time: 0.0828 data: 0.0023 max mem: 19788 +Test: Total time: 0:25:20 +Final results: +Mean IoU is 63.11 + + precision@0.5 = 69.65 + precision@0.6 = 64.04 + precision@0.7 = 57.36 + precision@0.8 = 47.05 + precision@0.9 = 23.64 + overall IoU = 63.35 + mean IoU = 63.11 + +Mean accuracy for one-to-zero sample is 84.66 + +Average object IoU 0.6310653711726197 +Overall IoU 63.3549690246582 +Epoch: [21] [ 0/2138] eta: 9:02:01 lr: 2.5584953434405612e-05 loss: 0.0305 (0.0305) time: 15.2110 data: 2.0436 max mem: 19788 +Epoch: [21] [ 10/2138] eta: 2:49:41 lr: 2.557928475526255e-05 loss: 0.0227 (0.0240) time: 4.7847 data: 0.1876 max mem: 19788 +Epoch: [21] [ 20/2138] eta: 2:34:03 lr: 2.5573615936532952e-05 loss: 0.0239 (0.0255) time: 3.8220 data: 0.0023 max mem: 19788 +Epoch: [21] [ 30/2138] eta: 2:26:09 lr: 2.5567946978178993e-05 loss: 0.0252 (0.0256) time: 3.8162 data: 0.0027 max mem: 19788 +Epoch: [21] [ 40/2138] eta: 2:22:14 lr: 2.556227788016284e-05 loss: 0.0276 (0.0266) time: 3.7568 data: 0.0032 max mem: 19788 +Epoch: [21] [ 50/2138] eta: 2:19:20 lr: 2.5556608642446627e-05 loss: 0.0272 (0.0281) time: 3.7631 data: 0.0033 max mem: 19788 +Epoch: [21] [ 60/2138] eta: 2:17:56 lr: 2.5550939264992485e-05 loss: 0.0228 (0.0274) time: 3.8087 data: 0.0030 max mem: 19788 +Epoch: [21] [ 70/2138] eta: 2:16:51 lr: 2.554526974776251e-05 loss: 0.0212 (0.0267) time: 3.8848 data: 0.0032 max mem: 19788 +Epoch: [21] [ 80/2138] eta: 2:15:16 lr: 2.5539600090718796e-05 loss: 0.0228 (0.0268) time: 3.8245 data: 0.0034 max mem: 19788 +Epoch: [21] [ 90/2138] eta: 2:14:05 lr: 2.5533930293823395e-05 loss: 0.0239 (0.0268) time: 3.7783 data: 0.0033 max mem: 19788 +Epoch: [21] [ 100/2138] eta: 2:13:03 lr: 2.5528260357038358e-05 loss: 0.0239 (0.0277) time: 3.8093 data: 0.0033 max mem: 19788 +Epoch: [21] [ 110/2138] eta: 2:11:51 lr: 2.5522590280325714e-05 loss: 0.0264 (0.0277) time: 3.7759 data: 0.0031 max mem: 19788 +Epoch: [21] [ 120/2138] eta: 2:11:43 lr: 2.5516920063647453e-05 loss: 0.0275 (0.0278) time: 3.9123 data: 0.0028 max mem: 19788 +Epoch: [21] [ 130/2138] eta: 2:10:59 lr: 2.5511249706965575e-05 loss: 0.0281 (0.0280) time: 3.9890 data: 0.0029 max mem: 19788 +Epoch: [21] [ 140/2138] eta: 2:10:17 lr: 2.5505579210242032e-05 loss: 0.0291 (0.0279) time: 3.8907 data: 0.0032 max mem: 19788 +Epoch: [21] [ 150/2138] eta: 2:09:58 lr: 2.5499908573438786e-05 loss: 0.0238 (0.0282) time: 3.9786 data: 0.0030 max mem: 19788 +Epoch: [21] [ 160/2138] eta: 2:09:18 lr: 2.5494237796517744e-05 loss: 0.0285 (0.0286) time: 3.9894 data: 0.0028 max mem: 19788 +Epoch: [21] [ 170/2138] eta: 2:08:55 lr: 2.548856687944083e-05 loss: 0.0320 (0.0287) time: 3.9915 data: 0.0028 max mem: 19788 +Epoch: [21] [ 180/2138] eta: 2:07:54 lr: 2.5482895822169917e-05 loss: 0.0320 (0.0287) time: 3.8988 data: 0.0029 max mem: 19788 +Epoch: [21] [ 190/2138] eta: 2:07:36 lr: 2.547722462466688e-05 loss: 0.0246 (0.0286) time: 3.9254 data: 0.0029 max mem: 19788 +Epoch: [21] [ 200/2138] eta: 2:06:36 lr: 2.5471553286893563e-05 loss: 0.0218 (0.0282) time: 3.9229 data: 0.0031 max mem: 19788 +Epoch: [21] [ 210/2138] eta: 2:05:42 lr: 2.5465881808811793e-05 loss: 0.0292 (0.0285) time: 3.7381 data: 0.0031 max mem: 19788 +Epoch: [21] [ 220/2138] eta: 2:04:47 lr: 2.5460210190383372e-05 loss: 0.0301 (0.0283) time: 3.7411 data: 0.0030 max mem: 19788 +Epoch: [21] [ 230/2138] eta: 2:04:02 lr: 2.5454538431570096e-05 loss: 0.0276 (0.0286) time: 3.7781 data: 0.0030 max mem: 19788 +Epoch: [21] [ 240/2138] eta: 2:03:06 lr: 2.5448866532333726e-05 loss: 0.0296 (0.0287) time: 3.7610 data: 0.0030 max mem: 19788 +Epoch: [21] [ 250/2138] eta: 2:02:28 lr: 2.544319449263602e-05 loss: 0.0259 (0.0286) time: 3.7950 data: 0.0030 max mem: 19788 +Epoch: [21] [ 260/2138] eta: 2:01:54 lr: 2.543752231243869e-05 loss: 0.0235 (0.0286) time: 3.9265 data: 0.0031 max mem: 19788 +Epoch: [21] [ 270/2138] eta: 2:01:03 lr: 2.5431849991703454e-05 loss: 0.0251 (0.0288) time: 3.8404 data: 0.0030 max mem: 19788 +Epoch: [21] [ 280/2138] eta: 2:00:12 lr: 2.5426177530392e-05 loss: 0.0275 (0.0287) time: 3.7119 data: 0.0029 max mem: 19788 +Epoch: [21] [ 290/2138] eta: 1:59:24 lr: 2.542050492846599e-05 loss: 0.0266 (0.0288) time: 3.7218 data: 0.0029 max mem: 19788 +Epoch: [21] [ 300/2138] eta: 1:58:52 lr: 2.5414832185887073e-05 loss: 0.0253 (0.0287) time: 3.8627 data: 0.0029 max mem: 19788 +Epoch: [21] [ 310/2138] eta: 1:58:00 lr: 2.540915930261688e-05 loss: 0.0253 (0.0287) time: 3.8205 data: 0.0029 max mem: 19788 +Epoch: [21] [ 320/2138] eta: 1:57:08 lr: 2.5403486278617017e-05 loss: 0.0268 (0.0288) time: 3.6495 data: 0.0031 max mem: 19788 +Epoch: [21] [ 330/2138] eta: 1:56:33 lr: 2.5397813113849077e-05 loss: 0.0272 (0.0288) time: 3.7888 data: 0.0030 max mem: 19788 +Epoch: [21] [ 340/2138] eta: 1:56:04 lr: 2.5392139808274617e-05 loss: 0.0275 (0.0288) time: 3.9973 data: 0.0029 max mem: 19788 +Epoch: [21] [ 350/2138] eta: 1:55:26 lr: 2.5386466361855198e-05 loss: 0.0261 (0.0287) time: 3.9699 data: 0.0032 max mem: 19788 +Epoch: [21] [ 360/2138] eta: 1:54:42 lr: 2.5380792774552335e-05 loss: 0.0261 (0.0287) time: 3.8280 data: 0.0031 max mem: 19788 +Epoch: [21] [ 370/2138] eta: 1:54:06 lr: 2.537511904632755e-05 loss: 0.0286 (0.0289) time: 3.8511 data: 0.0030 max mem: 19788 +Epoch: [21] [ 380/2138] eta: 1:53:25 lr: 2.5369445177142316e-05 loss: 0.0277 (0.0288) time: 3.8768 data: 0.0029 max mem: 19788 +Epoch: [21] [ 390/2138] eta: 1:52:37 lr: 2.5363771166958112e-05 loss: 0.0255 (0.0288) time: 3.7378 data: 0.0030 max mem: 19788 +Epoch: [21] [ 400/2138] eta: 1:51:50 lr: 2.535809701573638e-05 loss: 0.0279 (0.0289) time: 3.6655 data: 0.0034 max mem: 19788 +Epoch: [21] [ 410/2138] eta: 1:51:17 lr: 2.5352422723438546e-05 loss: 0.0323 (0.0290) time: 3.8321 data: 0.0033 max mem: 19788 +Epoch: [21] [ 420/2138] eta: 1:50:35 lr: 2.5346748290026023e-05 loss: 0.0286 (0.0290) time: 3.8912 data: 0.0030 max mem: 19788 +Epoch: [21] [ 430/2138] eta: 1:49:55 lr: 2.5341073715460185e-05 loss: 0.0269 (0.0290) time: 3.8048 data: 0.0029 max mem: 19788 +Epoch: [21] [ 440/2138] eta: 1:49:08 lr: 2.5335398999702416e-05 loss: 0.0273 (0.0291) time: 3.7323 data: 0.0031 max mem: 19788 +Epoch: [21] [ 450/2138] eta: 1:48:29 lr: 2.5329724142714052e-05 loss: 0.0303 (0.0291) time: 3.7476 data: 0.0031 max mem: 19788 +Epoch: [21] [ 460/2138] eta: 1:47:49 lr: 2.5324049144456425e-05 loss: 0.0317 (0.0292) time: 3.8256 data: 0.0031 max mem: 19788 +Epoch: [21] [ 470/2138] eta: 1:47:03 lr: 2.5318374004890826e-05 loss: 0.0317 (0.0292) time: 3.7321 data: 0.0034 max mem: 19788 +Epoch: [21] [ 480/2138] eta: 1:46:29 lr: 2.5312698723978566e-05 loss: 0.0321 (0.0293) time: 3.8129 data: 0.0035 max mem: 19788 +Epoch: [21] [ 490/2138] eta: 1:45:55 lr: 2.5307023301680894e-05 loss: 0.0293 (0.0292) time: 3.9782 data: 0.0035 max mem: 19788 +Epoch: [21] [ 500/2138] eta: 1:45:18 lr: 2.5301347737959064e-05 loss: 0.0256 (0.0292) time: 3.9500 data: 0.0031 max mem: 19788 +Epoch: [21] [ 510/2138] eta: 1:44:36 lr: 2.5295672032774286e-05 loss: 0.0271 (0.0292) time: 3.8322 data: 0.0030 max mem: 19788 +Epoch: [21] [ 520/2138] eta: 1:43:55 lr: 2.5289996186087784e-05 loss: 0.0268 (0.0291) time: 3.7624 data: 0.0030 max mem: 19788 +Epoch: [21] [ 530/2138] eta: 1:43:15 lr: 2.528432019786073e-05 loss: 0.0265 (0.0292) time: 3.7997 data: 0.0029 max mem: 19788 +Epoch: [21] [ 540/2138] eta: 1:42:45 lr: 2.5278644068054296e-05 loss: 0.0240 (0.0291) time: 3.9747 data: 0.0030 max mem: 19788 +Epoch: [21] [ 550/2138] eta: 1:42:05 lr: 2.5272967796629615e-05 loss: 0.0263 (0.0291) time: 3.9747 data: 0.0029 max mem: 19788 +Epoch: [21] [ 560/2138] eta: 1:41:26 lr: 2.5267291383547825e-05 loss: 0.0281 (0.0291) time: 3.8181 data: 0.0030 max mem: 19788 +Epoch: [21] [ 570/2138] eta: 1:40:46 lr: 2.5261614828770013e-05 loss: 0.0277 (0.0291) time: 3.8135 data: 0.0031 max mem: 19788 +Epoch: [21] [ 580/2138] eta: 1:40:15 lr: 2.5255938132257283e-05 loss: 0.0300 (0.0292) time: 3.9762 data: 0.0030 max mem: 19788 +Epoch: [21] [ 590/2138] eta: 1:39:39 lr: 2.5250261293970673e-05 loss: 0.0279 (0.0292) time: 4.0498 data: 0.0028 max mem: 19788 +Epoch: [21] [ 600/2138] eta: 1:38:55 lr: 2.5244584313871245e-05 loss: 0.0264 (0.0291) time: 3.8125 data: 0.0032 max mem: 19788 +Epoch: [21] [ 610/2138] eta: 1:38:11 lr: 2.5238907191920003e-05 loss: 0.0264 (0.0291) time: 3.6589 data: 0.0032 max mem: 19788 +Epoch: [21] [ 620/2138] eta: 1:37:32 lr: 2.5233229928077968e-05 loss: 0.0279 (0.0291) time: 3.7376 data: 0.0029 max mem: 19788 +Epoch: [21] [ 630/2138] eta: 1:36:51 lr: 2.5227552522306103e-05 loss: 0.0262 (0.0291) time: 3.7787 data: 0.0030 max mem: 19788 +Epoch: [21] [ 640/2138] eta: 1:36:10 lr: 2.5221874974565374e-05 loss: 0.0240 (0.0291) time: 3.7485 data: 0.0034 max mem: 19788 +Epoch: [21] [ 650/2138] eta: 1:35:28 lr: 2.5216197284816722e-05 loss: 0.0244 (0.0291) time: 3.7315 data: 0.0035 max mem: 19788 +Epoch: [21] [ 660/2138] eta: 1:34:50 lr: 2.5210519453021064e-05 loss: 0.0274 (0.0291) time: 3.7779 data: 0.0032 max mem: 19788 +Epoch: [21] [ 670/2138] eta: 1:34:07 lr: 2.5204841479139303e-05 loss: 0.0278 (0.0290) time: 3.7623 data: 0.0029 max mem: 19788 +Epoch: [21] [ 680/2138] eta: 1:33:26 lr: 2.519916336313231e-05 loss: 0.0278 (0.0291) time: 3.6874 data: 0.0029 max mem: 19788 +Epoch: [21] [ 690/2138] eta: 1:32:45 lr: 2.5193485104960946e-05 loss: 0.0285 (0.0291) time: 3.7160 data: 0.0028 max mem: 19788 +Epoch: [21] [ 700/2138] eta: 1:32:05 lr: 2.5187806704586054e-05 loss: 0.0285 (0.0291) time: 3.7488 data: 0.0028 max mem: 19788 +Epoch: [21] [ 710/2138] eta: 1:31:23 lr: 2.5182128161968438e-05 loss: 0.0287 (0.0291) time: 3.7115 data: 0.0029 max mem: 19788 +Epoch: [21] [ 720/2138] eta: 1:30:43 lr: 2.5176449477068898e-05 loss: 0.0260 (0.0291) time: 3.7303 data: 0.0030 max mem: 19788 +Epoch: [21] [ 730/2138] eta: 1:30:06 lr: 2.5170770649848215e-05 loss: 0.0263 (0.0292) time: 3.8535 data: 0.0031 max mem: 19788 +Epoch: [21] [ 740/2138] eta: 1:29:28 lr: 2.5165091680267135e-05 loss: 0.0249 (0.0291) time: 3.8801 data: 0.0030 max mem: 19788 +Epoch: [21] [ 750/2138] eta: 1:28:49 lr: 2.5159412568286396e-05 loss: 0.0247 (0.0291) time: 3.8376 data: 0.0028 max mem: 19788 +Epoch: [21] [ 760/2138] eta: 1:28:11 lr: 2.5153733313866706e-05 loss: 0.0284 (0.0291) time: 3.8229 data: 0.0029 max mem: 19788 +Epoch: [21] [ 770/2138] eta: 1:27:30 lr: 2.5148053916968767e-05 loss: 0.0285 (0.0291) time: 3.7770 data: 0.0031 max mem: 19788 +Epoch: [21] [ 780/2138] eta: 1:26:51 lr: 2.5142374377553234e-05 loss: 0.0288 (0.0291) time: 3.7535 data: 0.0030 max mem: 19788 +Epoch: [21] [ 790/2138] eta: 1:26:10 lr: 2.5136694695580783e-05 loss: 0.0255 (0.0291) time: 3.7194 data: 0.0030 max mem: 19788 +Epoch: [21] [ 800/2138] eta: 1:25:30 lr: 2.5131014871012015e-05 loss: 0.0255 (0.0291) time: 3.7109 data: 0.0031 max mem: 19788 +Epoch: [21] [ 810/2138] eta: 1:24:50 lr: 2.512533490380756e-05 loss: 0.0270 (0.0291) time: 3.7500 data: 0.0029 max mem: 19788 +Epoch: [21] [ 820/2138] eta: 1:24:10 lr: 2.5119654793928003e-05 loss: 0.0287 (0.0291) time: 3.7296 data: 0.0031 max mem: 19788 +Epoch: [21] [ 830/2138] eta: 1:23:30 lr: 2.5113974541333907e-05 loss: 0.0282 (0.0291) time: 3.7320 data: 0.0033 max mem: 19788 +Epoch: [21] [ 840/2138] eta: 1:22:52 lr: 2.5108294145985815e-05 loss: 0.0233 (0.0290) time: 3.7790 data: 0.0031 max mem: 19788 +Epoch: [21] [ 850/2138] eta: 1:22:16 lr: 2.5102613607844265e-05 loss: 0.0235 (0.0290) time: 3.9234 data: 0.0030 max mem: 19788 +Epoch: [21] [ 860/2138] eta: 1:21:40 lr: 2.5096932926869754e-05 loss: 0.0254 (0.0290) time: 3.9956 data: 0.0030 max mem: 19788 +Epoch: [21] [ 870/2138] eta: 1:21:00 lr: 2.509125210302277e-05 loss: 0.0306 (0.0290) time: 3.8502 data: 0.0031 max mem: 19788 +Epoch: [21] [ 880/2138] eta: 1:20:19 lr: 2.5085571136263776e-05 loss: 0.0270 (0.0290) time: 3.6969 data: 0.0032 max mem: 19788 +Epoch: [21] [ 890/2138] eta: 1:19:43 lr: 2.507989002655321e-05 loss: 0.0266 (0.0290) time: 3.8174 data: 0.0029 max mem: 19788 +Epoch: [21] [ 900/2138] eta: 1:19:02 lr: 2.5074208773851493e-05 loss: 0.0296 (0.0291) time: 3.8158 data: 0.0029 max mem: 19788 +Epoch: [21] [ 910/2138] eta: 1:18:25 lr: 2.5068527378119038e-05 loss: 0.0293 (0.0291) time: 3.7696 data: 0.0030 max mem: 19788 +Epoch: [21] [ 920/2138] eta: 1:17:45 lr: 2.5062845839316206e-05 loss: 0.0265 (0.0291) time: 3.8056 data: 0.0029 max mem: 19788 +Epoch: [21] [ 930/2138] eta: 1:17:08 lr: 2.5057164157403373e-05 loss: 0.0260 (0.0291) time: 3.8452 data: 0.0029 max mem: 19788 +Epoch: [21] [ 940/2138] eta: 1:16:31 lr: 2.505148233234087e-05 loss: 0.0282 (0.0292) time: 3.9301 data: 0.0030 max mem: 19788 +Epoch: [21] [ 950/2138] eta: 1:15:53 lr: 2.5045800364089018e-05 loss: 0.0282 (0.0292) time: 3.8921 data: 0.0031 max mem: 19788 +Epoch: [21] [ 960/2138] eta: 1:15:17 lr: 2.50401182526081e-05 loss: 0.0278 (0.0292) time: 3.9344 data: 0.0031 max mem: 19788 +Epoch: [21] [ 970/2138] eta: 1:14:38 lr: 2.5034435997858403e-05 loss: 0.0264 (0.0292) time: 3.8934 data: 0.0032 max mem: 19788 +Epoch: [21] [ 980/2138] eta: 1:13:58 lr: 2.5028753599800176e-05 loss: 0.0246 (0.0291) time: 3.7315 data: 0.0031 max mem: 19788 +Epoch: [21] [ 990/2138] eta: 1:13:19 lr: 2.5023071058393653e-05 loss: 0.0272 (0.0292) time: 3.7104 data: 0.0030 max mem: 19788 +Epoch: [21] [1000/2138] eta: 1:12:38 lr: 2.501738837359905e-05 loss: 0.0282 (0.0292) time: 3.7119 data: 0.0030 max mem: 19788 +Epoch: [21] [1010/2138] eta: 1:11:58 lr: 2.5011705545376553e-05 loss: 0.0257 (0.0292) time: 3.6721 data: 0.0029 max mem: 19788 +Epoch: [21] [1020/2138] eta: 1:11:18 lr: 2.5006022573686333e-05 loss: 0.0235 (0.0293) time: 3.6629 data: 0.0030 max mem: 19788 +Epoch: [21] [1030/2138] eta: 1:10:38 lr: 2.500033945848853e-05 loss: 0.0257 (0.0293) time: 3.6467 data: 0.0030 max mem: 19788 +Epoch: [21] [1040/2138] eta: 1:09:59 lr: 2.4994656199743284e-05 loss: 0.0278 (0.0293) time: 3.7281 data: 0.0029 max mem: 19788 +Epoch: [21] [1050/2138] eta: 1:09:20 lr: 2.4988972797410692e-05 loss: 0.0289 (0.0293) time: 3.7731 data: 0.0029 max mem: 19788 +Epoch: [21] [1060/2138] eta: 1:08:40 lr: 2.4983289251450846e-05 loss: 0.0289 (0.0293) time: 3.6937 data: 0.0029 max mem: 19788 +Epoch: [21] [1070/2138] eta: 1:08:00 lr: 2.4977605561823804e-05 loss: 0.0287 (0.0293) time: 3.6556 data: 0.0029 max mem: 19788 +Epoch: [21] [1080/2138] eta: 1:07:21 lr: 2.4971921728489614e-05 loss: 0.0269 (0.0293) time: 3.6633 data: 0.0029 max mem: 19788 +Epoch: [21] [1090/2138] eta: 1:06:42 lr: 2.496623775140829e-05 loss: 0.0283 (0.0293) time: 3.6944 data: 0.0029 max mem: 19788 +Epoch: [21] [1100/2138] eta: 1:06:02 lr: 2.496055363053984e-05 loss: 0.0308 (0.0294) time: 3.7234 data: 0.0030 max mem: 19788 +Epoch: [21] [1110/2138] eta: 1:05:23 lr: 2.4954869365844232e-05 loss: 0.0332 (0.0294) time: 3.6804 data: 0.0031 max mem: 19788 +Epoch: [21] [1120/2138] eta: 1:04:44 lr: 2.494918495728144e-05 loss: 0.0278 (0.0294) time: 3.7231 data: 0.0029 max mem: 19788 +Epoch: [21] [1130/2138] eta: 1:04:06 lr: 2.494350040481138e-05 loss: 0.0278 (0.0294) time: 3.7870 data: 0.0028 max mem: 19788 +Epoch: [21] [1140/2138] eta: 1:03:26 lr: 2.4937815708393984e-05 loss: 0.0291 (0.0294) time: 3.7199 data: 0.0031 max mem: 19788 +Epoch: [21] [1150/2138] eta: 1:02:47 lr: 2.4932130867989135e-05 loss: 0.0254 (0.0294) time: 3.7010 data: 0.0033 max mem: 19788 +Epoch: [21] [1160/2138] eta: 1:02:08 lr: 2.4926445883556712e-05 loss: 0.0254 (0.0294) time: 3.6969 data: 0.0032 max mem: 19788 +Epoch: [21] [1170/2138] eta: 1:01:29 lr: 2.492076075505656e-05 loss: 0.0275 (0.0294) time: 3.6685 data: 0.0029 max mem: 19788 +Epoch: [21] [1180/2138] eta: 1:00:50 lr: 2.491507548244852e-05 loss: 0.0285 (0.0294) time: 3.7021 data: 0.0029 max mem: 19788 +Epoch: [21] [1190/2138] eta: 1:00:11 lr: 2.490939006569238e-05 loss: 0.0275 (0.0295) time: 3.6908 data: 0.0029 max mem: 19788 +Epoch: [21] [1200/2138] eta: 0:59:31 lr: 2.4903704504747947e-05 loss: 0.0275 (0.0295) time: 3.6554 data: 0.0030 max mem: 19788 +Epoch: [21] [1210/2138] eta: 0:58:53 lr: 2.4898018799574972e-05 loss: 0.0274 (0.0295) time: 3.6955 data: 0.0031 max mem: 19788 +Epoch: [21] [1220/2138] eta: 0:58:14 lr: 2.489233295013321e-05 loss: 0.0274 (0.0295) time: 3.6971 data: 0.0031 max mem: 19788 +Epoch: [21] [1230/2138] eta: 0:57:34 lr: 2.4886646956382376e-05 loss: 0.0273 (0.0295) time: 3.6625 data: 0.0029 max mem: 19788 +Epoch: [21] [1240/2138] eta: 0:56:56 lr: 2.4880960818282174e-05 loss: 0.0264 (0.0295) time: 3.7313 data: 0.0031 max mem: 19788 +Epoch: [21] [1250/2138] eta: 0:56:18 lr: 2.487527453579228e-05 loss: 0.0274 (0.0295) time: 3.7766 data: 0.0030 max mem: 19788 +Epoch: [21] [1260/2138] eta: 0:55:39 lr: 2.486958810887236e-05 loss: 0.0260 (0.0295) time: 3.7499 data: 0.0031 max mem: 19788 +Epoch: [21] [1270/2138] eta: 0:55:01 lr: 2.486390153748204e-05 loss: 0.0260 (0.0295) time: 3.7127 data: 0.0033 max mem: 19788 +Epoch: [21] [1280/2138] eta: 0:54:24 lr: 2.4858214821580946e-05 loss: 0.0255 (0.0294) time: 3.8252 data: 0.0032 max mem: 19788 +Epoch: [21] [1290/2138] eta: 0:53:48 lr: 2.4852527961128655e-05 loss: 0.0270 (0.0294) time: 4.0505 data: 0.0030 max mem: 19788 +Epoch: [21] [1300/2138] eta: 0:53:12 lr: 2.4846840956084756e-05 loss: 0.0287 (0.0294) time: 4.1147 data: 0.0029 max mem: 19788 +Epoch: [21] [1310/2138] eta: 0:52:34 lr: 2.484115380640879e-05 loss: 0.0246 (0.0294) time: 3.9673 data: 0.0030 max mem: 19788 +Epoch: [21] [1320/2138] eta: 0:51:56 lr: 2.483546651206029e-05 loss: 0.0296 (0.0295) time: 3.8532 data: 0.0031 max mem: 19788 +Epoch: [21] [1330/2138] eta: 0:51:18 lr: 2.4829779072998763e-05 loss: 0.0285 (0.0294) time: 3.8880 data: 0.0030 max mem: 19788 +Epoch: [21] [1340/2138] eta: 0:50:40 lr: 2.4824091489183686e-05 loss: 0.0270 (0.0295) time: 3.8601 data: 0.0032 max mem: 19788 +Epoch: [21] [1350/2138] eta: 0:50:03 lr: 2.481840376057453e-05 loss: 0.0330 (0.0295) time: 3.8649 data: 0.0033 max mem: 19788 +Epoch: [21] [1360/2138] eta: 0:49:24 lr: 2.4812715887130733e-05 loss: 0.0318 (0.0295) time: 3.8260 data: 0.0032 max mem: 19788 +Epoch: [21] [1370/2138] eta: 0:48:46 lr: 2.4807027868811725e-05 loss: 0.0282 (0.0295) time: 3.7347 data: 0.0032 max mem: 19788 +Epoch: [21] [1380/2138] eta: 0:48:08 lr: 2.480133970557689e-05 loss: 0.0268 (0.0296) time: 3.8292 data: 0.0030 max mem: 19788 +Epoch: [21] [1390/2138] eta: 0:47:30 lr: 2.4795651397385615e-05 loss: 0.0278 (0.0296) time: 3.8305 data: 0.0030 max mem: 19788 +Epoch: [21] [1400/2138] eta: 0:46:51 lr: 2.478996294419725e-05 loss: 0.0271 (0.0295) time: 3.6967 data: 0.0031 max mem: 19788 +Epoch: [21] [1410/2138] eta: 0:46:12 lr: 2.4784274345971134e-05 loss: 0.0251 (0.0295) time: 3.6617 data: 0.0031 max mem: 19788 +Epoch: [21] [1420/2138] eta: 0:45:33 lr: 2.477858560266657e-05 loss: 0.0252 (0.0295) time: 3.6705 data: 0.0031 max mem: 19788 +Epoch: [21] [1430/2138] eta: 0:44:55 lr: 2.477289671424286e-05 loss: 0.0305 (0.0295) time: 3.7059 data: 0.0030 max mem: 19788 +Epoch: [21] [1440/2138] eta: 0:44:16 lr: 2.476720768065926e-05 loss: 0.0288 (0.0295) time: 3.6966 data: 0.0033 max mem: 19788 +Epoch: [21] [1450/2138] eta: 0:43:39 lr: 2.4761518501875023e-05 loss: 0.0295 (0.0295) time: 3.7844 data: 0.0034 max mem: 19788 +Epoch: [21] [1460/2138] eta: 0:43:00 lr: 2.4755829177849367e-05 loss: 0.0311 (0.0295) time: 3.8467 data: 0.0030 max mem: 19788 +Epoch: [21] [1470/2138] eta: 0:42:22 lr: 2.47501397085415e-05 loss: 0.0295 (0.0295) time: 3.7834 data: 0.0028 max mem: 19788 +Epoch: [21] [1480/2138] eta: 0:41:43 lr: 2.4744450093910597e-05 loss: 0.0294 (0.0296) time: 3.7187 data: 0.0029 max mem: 19788 +Epoch: [21] [1490/2138] eta: 0:41:06 lr: 2.473876033391583e-05 loss: 0.0294 (0.0296) time: 3.7479 data: 0.0030 max mem: 19788 +Epoch: [21] [1500/2138] eta: 0:40:28 lr: 2.4733070428516316e-05 loss: 0.0323 (0.0296) time: 3.8642 data: 0.0029 max mem: 19788 +Epoch: [21] [1510/2138] eta: 0:39:49 lr: 2.472738037767119e-05 loss: 0.0320 (0.0296) time: 3.7681 data: 0.0030 max mem: 19788 +Epoch: [21] [1520/2138] eta: 0:39:11 lr: 2.4721690181339525e-05 loss: 0.0274 (0.0296) time: 3.7011 data: 0.0032 max mem: 19788 +Epoch: [21] [1530/2138] eta: 0:38:33 lr: 2.4715999839480408e-05 loss: 0.0249 (0.0295) time: 3.8296 data: 0.0033 max mem: 19788 +Epoch: [21] [1540/2138] eta: 0:37:55 lr: 2.4710309352052877e-05 loss: 0.0242 (0.0295) time: 3.7789 data: 0.0033 max mem: 19788 +Epoch: [21] [1550/2138] eta: 0:37:16 lr: 2.4704618719015965e-05 loss: 0.0245 (0.0295) time: 3.6577 data: 0.0033 max mem: 19788 +Epoch: [21] [1560/2138] eta: 0:36:38 lr: 2.4698927940328672e-05 loss: 0.0277 (0.0295) time: 3.7099 data: 0.0032 max mem: 19788 +Epoch: [21] [1570/2138] eta: 0:36:00 lr: 2.4693237015949987e-05 loss: 0.0277 (0.0296) time: 3.7784 data: 0.0029 max mem: 19788 +Epoch: [21] [1580/2138] eta: 0:35:21 lr: 2.4687545945838866e-05 loss: 0.0260 (0.0296) time: 3.7711 data: 0.0028 max mem: 19788 +Epoch: [21] [1590/2138] eta: 0:34:43 lr: 2.468185472995425e-05 loss: 0.0254 (0.0296) time: 3.7770 data: 0.0030 max mem: 19788 +Epoch: [21] [1600/2138] eta: 0:34:05 lr: 2.467616336825505e-05 loss: 0.0301 (0.0296) time: 3.7452 data: 0.0033 max mem: 19788 +Epoch: [21] [1610/2138] eta: 0:33:28 lr: 2.4670471860700174e-05 loss: 0.0263 (0.0296) time: 3.8634 data: 0.0033 max mem: 19788 +Epoch: [21] [1620/2138] eta: 0:32:50 lr: 2.466478020724848e-05 loss: 0.0251 (0.0295) time: 3.9703 data: 0.0030 max mem: 19788 +Epoch: [21] [1630/2138] eta: 0:32:12 lr: 2.465908840785882e-05 loss: 0.0288 (0.0296) time: 3.8592 data: 0.0029 max mem: 19788 +Epoch: [21] [1640/2138] eta: 0:31:34 lr: 2.465339646249003e-05 loss: 0.0257 (0.0295) time: 3.8472 data: 0.0028 max mem: 19788 +Epoch: [21] [1650/2138] eta: 0:30:56 lr: 2.4647704371100905e-05 loss: 0.0242 (0.0295) time: 3.8043 data: 0.0030 max mem: 19788 +Epoch: [21] [1660/2138] eta: 0:30:19 lr: 2.464201213365024e-05 loss: 0.0223 (0.0295) time: 3.9413 data: 0.0030 max mem: 19788 +Epoch: [21] [1670/2138] eta: 0:29:42 lr: 2.463631975009679e-05 loss: 0.0223 (0.0294) time: 4.1247 data: 0.0032 max mem: 19788 +Epoch: [21] [1680/2138] eta: 0:29:03 lr: 2.4630627220399296e-05 loss: 0.0257 (0.0294) time: 3.9294 data: 0.0033 max mem: 19788 +Epoch: [21] [1690/2138] eta: 0:28:25 lr: 2.462493454451647e-05 loss: 0.0272 (0.0294) time: 3.7754 data: 0.0031 max mem: 19788 +Epoch: [21] [1700/2138] eta: 0:27:47 lr: 2.4619241722407016e-05 loss: 0.0269 (0.0294) time: 3.8200 data: 0.0031 max mem: 19788 +Epoch: [21] [1710/2138] eta: 0:27:10 lr: 2.4613548754029596e-05 loss: 0.0255 (0.0294) time: 3.8656 data: 0.0031 max mem: 19788 +Epoch: [21] [1720/2138] eta: 0:26:32 lr: 2.460785563934287e-05 loss: 0.0265 (0.0294) time: 3.9745 data: 0.0032 max mem: 19788 +Epoch: [21] [1730/2138] eta: 0:25:54 lr: 2.4602162378305456e-05 loss: 0.0278 (0.0294) time: 3.8929 data: 0.0033 max mem: 19788 +Epoch: [21] [1740/2138] eta: 0:25:15 lr: 2.4596468970875967e-05 loss: 0.0288 (0.0294) time: 3.7376 data: 0.0033 max mem: 19788 +Epoch: [21] [1750/2138] eta: 0:24:38 lr: 2.459077541701298e-05 loss: 0.0280 (0.0294) time: 3.8035 data: 0.0031 max mem: 19788 +Epoch: [21] [1760/2138] eta: 0:23:59 lr: 2.4585081716675062e-05 loss: 0.0275 (0.0294) time: 3.7996 data: 0.0031 max mem: 19788 +Epoch: [21] [1770/2138] eta: 0:23:21 lr: 2.4579387869820747e-05 loss: 0.0267 (0.0294) time: 3.7646 data: 0.0032 max mem: 19788 +Epoch: [21] [1780/2138] eta: 0:22:43 lr: 2.4573693876408554e-05 loss: 0.0249 (0.0294) time: 3.7254 data: 0.0031 max mem: 19788 +Epoch: [21] [1790/2138] eta: 0:22:04 lr: 2.456799973639697e-05 loss: 0.0249 (0.0294) time: 3.6613 data: 0.0031 max mem: 19788 +Epoch: [21] [1800/2138] eta: 0:21:26 lr: 2.4562305449744473e-05 loss: 0.0245 (0.0294) time: 3.7298 data: 0.0030 max mem: 19788 +Epoch: [21] [1810/2138] eta: 0:20:48 lr: 2.455661101640951e-05 loss: 0.0259 (0.0294) time: 3.8238 data: 0.0029 max mem: 19788 +Epoch: [21] [1820/2138] eta: 0:20:10 lr: 2.4550916436350503e-05 loss: 0.0273 (0.0294) time: 3.8249 data: 0.0031 max mem: 19788 +Epoch: [21] [1830/2138] eta: 0:19:32 lr: 2.454522170952586e-05 loss: 0.0265 (0.0294) time: 3.7288 data: 0.0031 max mem: 19788 +Epoch: [21] [1840/2138] eta: 0:18:54 lr: 2.453952683589396e-05 loss: 0.0294 (0.0294) time: 3.6556 data: 0.0031 max mem: 19788 +Epoch: [21] [1850/2138] eta: 0:18:15 lr: 2.453383181541316e-05 loss: 0.0298 (0.0294) time: 3.6986 data: 0.0031 max mem: 19788 +Epoch: [21] [1860/2138] eta: 0:17:37 lr: 2.4528136648041806e-05 loss: 0.0264 (0.0294) time: 3.7003 data: 0.0033 max mem: 19788 +Epoch: [21] [1870/2138] eta: 0:16:59 lr: 2.452244133373819e-05 loss: 0.0250 (0.0294) time: 3.7001 data: 0.0034 max mem: 19788 +Epoch: [21] [1880/2138] eta: 0:16:21 lr: 2.4516745872460624e-05 loss: 0.0254 (0.0294) time: 3.7674 data: 0.0033 max mem: 19788 +Epoch: [21] [1890/2138] eta: 0:15:43 lr: 2.4511050264167363e-05 loss: 0.0254 (0.0294) time: 3.7638 data: 0.0032 max mem: 19788 +Epoch: [21] [1900/2138] eta: 0:15:05 lr: 2.4505354508816667e-05 loss: 0.0253 (0.0294) time: 3.7172 data: 0.0031 max mem: 19788 +Epoch: [21] [1910/2138] eta: 0:14:27 lr: 2.449965860636674e-05 loss: 0.0264 (0.0293) time: 3.7992 data: 0.0030 max mem: 19788 +Epoch: [21] [1920/2138] eta: 0:13:49 lr: 2.4493962556775796e-05 loss: 0.0261 (0.0293) time: 3.8574 data: 0.0029 max mem: 19788 +Epoch: [21] [1930/2138] eta: 0:13:11 lr: 2.448826636000201e-05 loss: 0.0280 (0.0293) time: 3.7464 data: 0.0029 max mem: 19788 +Epoch: [21] [1940/2138] eta: 0:12:33 lr: 2.448257001600353e-05 loss: 0.0284 (0.0293) time: 3.7691 data: 0.0028 max mem: 19788 +Epoch: [21] [1950/2138] eta: 0:11:55 lr: 2.4476873524738495e-05 loss: 0.0268 (0.0293) time: 3.8547 data: 0.0029 max mem: 19788 +Epoch: [21] [1960/2138] eta: 0:11:16 lr: 2.4471176886165007e-05 loss: 0.0247 (0.0293) time: 3.7642 data: 0.0030 max mem: 19788 +Epoch: [21] [1970/2138] eta: 0:10:38 lr: 2.4465480100241166e-05 loss: 0.0258 (0.0293) time: 3.7409 data: 0.0029 max mem: 19788 +Epoch: [21] [1980/2138] eta: 0:10:00 lr: 2.445978316692502e-05 loss: 0.0257 (0.0293) time: 3.7719 data: 0.0033 max mem: 19788 +Epoch: [21] [1990/2138] eta: 0:09:22 lr: 2.445408608617462e-05 loss: 0.0266 (0.0293) time: 3.8743 data: 0.0033 max mem: 19788 +Epoch: [21] [2000/2138] eta: 0:08:45 lr: 2.444838885794798e-05 loss: 0.0271 (0.0293) time: 4.0715 data: 0.0031 max mem: 19788 +Epoch: [21] [2010/2138] eta: 0:08:07 lr: 2.4442691482203105e-05 loss: 0.0280 (0.0293) time: 4.0561 data: 0.0030 max mem: 19788 +Epoch: [21] [2020/2138] eta: 0:07:29 lr: 2.4436993958897953e-05 loss: 0.0280 (0.0293) time: 3.8923 data: 0.0029 max mem: 19788 +Epoch: [21] [2030/2138] eta: 0:06:51 lr: 2.4431296287990484e-05 loss: 0.0276 (0.0293) time: 3.8393 data: 0.0029 max mem: 19788 +Epoch: [21] [2040/2138] eta: 0:06:13 lr: 2.4425598469438616e-05 loss: 0.0271 (0.0293) time: 3.8517 data: 0.0030 max mem: 19788 +Epoch: [21] [2050/2138] eta: 0:05:34 lr: 2.4419900503200264e-05 loss: 0.0273 (0.0293) time: 3.7921 data: 0.0030 max mem: 19788 +Epoch: [21] [2060/2138] eta: 0:04:56 lr: 2.44142023892333e-05 loss: 0.0284 (0.0293) time: 3.8386 data: 0.0030 max mem: 19788 +Epoch: [21] [2070/2138] eta: 0:04:18 lr: 2.440850412749559e-05 loss: 0.0261 (0.0293) time: 3.7899 data: 0.0029 max mem: 19788 +Epoch: [21] [2080/2138] eta: 0:03:40 lr: 2.4402805717944957e-05 loss: 0.0261 (0.0293) time: 3.6667 data: 0.0033 max mem: 19788 +Epoch: [21] [2090/2138] eta: 0:03:02 lr: 2.4397107160539225e-05 loss: 0.0257 (0.0293) time: 3.6732 data: 0.0034 max mem: 19788 +Epoch: [21] [2100/2138] eta: 0:02:24 lr: 2.4391408455236177e-05 loss: 0.0262 (0.0293) time: 3.6666 data: 0.0030 max mem: 19788 +Epoch: [21] [2110/2138] eta: 0:01:46 lr: 2.4385709601993584e-05 loss: 0.0298 (0.0293) time: 3.7448 data: 0.0029 max mem: 19788 +Epoch: [21] [2120/2138] eta: 0:01:08 lr: 2.4380010600769178e-05 loss: 0.0354 (0.0293) time: 3.9361 data: 0.0029 max mem: 19788 +Epoch: [21] [2130/2138] eta: 0:00:30 lr: 2.43743114515207e-05 loss: 0.0333 (0.0293) time: 3.9832 data: 0.0029 max mem: 19788 +Epoch: [21] Total time: 2:15:37 +Test: [ 0/21770] eta: 16:20:26 time: 2.7022 data: 2.5788 max mem: 19788 +Test: [ 100/21770] eta: 0:32:05 time: 0.0605 data: 0.0019 max mem: 19788 +Test: [ 200/21770] eta: 0:28:38 time: 0.0766 data: 0.0022 max mem: 19788 +Test: [ 300/21770] eta: 0:27:54 time: 0.0591 data: 0.0018 max mem: 19788 +Test: [ 400/21770] eta: 0:26:28 time: 0.0719 data: 0.0021 max mem: 19788 +Test: [ 500/21770] eta: 0:26:14 time: 0.0698 data: 0.0021 max mem: 19788 +Test: [ 600/21770] eta: 0:26:02 time: 0.0745 data: 0.0019 max mem: 19788 +Test: [ 700/21770] eta: 0:25:51 time: 0.0618 data: 0.0017 max mem: 19788 +Test: [ 800/21770] eta: 0:25:32 time: 0.0743 data: 0.0022 max mem: 19788 +Test: [ 900/21770] eta: 0:25:44 time: 0.0826 data: 0.0020 max mem: 19788 +Test: [ 1000/21770] eta: 0:25:27 time: 0.0729 data: 0.0021 max mem: 19788 +Test: [ 1100/21770] eta: 0:25:10 time: 0.0780 data: 0.0025 max mem: 19788 +Test: [ 1200/21770] eta: 0:24:56 time: 0.0620 data: 0.0016 max mem: 19788 +Test: [ 1300/21770] eta: 0:24:34 time: 0.0610 data: 0.0018 max mem: 19788 +Test: [ 1400/21770] eta: 0:24:23 time: 0.0823 data: 0.0024 max mem: 19788 +Test: [ 1500/21770] eta: 0:24:14 time: 0.0682 data: 0.0020 max mem: 19788 +Test: [ 1600/21770] eta: 0:24:03 time: 0.0658 data: 0.0018 max mem: 19788 +Test: [ 1700/21770] eta: 0:23:50 time: 0.0770 data: 0.0023 max mem: 19788 +Test: [ 1800/21770] eta: 0:23:35 time: 0.0592 data: 0.0018 max mem: 19788 +Test: [ 1900/21770] eta: 0:23:29 time: 0.0811 data: 0.0024 max mem: 19788 +Test: [ 2000/21770] eta: 0:23:31 time: 0.0745 data: 0.0021 max mem: 19788 +Test: [ 2100/21770] eta: 0:23:27 time: 0.0828 data: 0.0025 max mem: 19788 +Test: [ 2200/21770] eta: 0:23:19 time: 0.0728 data: 0.0023 max mem: 19788 +Test: [ 2300/21770] eta: 0:23:16 time: 0.0638 data: 0.0019 max mem: 19788 +Test: [ 2400/21770] eta: 0:23:08 time: 0.0730 data: 0.0023 max mem: 19788 +Test: [ 2500/21770] eta: 0:23:00 time: 0.0676 data: 0.0020 max mem: 19788 +Test: [ 2600/21770] eta: 0:22:46 time: 0.0609 data: 0.0019 max mem: 19788 +Test: [ 2700/21770] eta: 0:22:39 time: 0.0679 data: 0.0022 max mem: 19788 +Test: [ 2800/21770] eta: 0:22:27 time: 0.0670 data: 0.0019 max mem: 19788 +Test: [ 2900/21770] eta: 0:22:16 time: 0.0618 data: 0.0019 max mem: 19788 +Test: [ 3000/21770] eta: 0:22:04 time: 0.0677 data: 0.0019 max mem: 19788 +Test: [ 3100/21770] eta: 0:21:56 time: 0.0717 data: 0.0021 max mem: 19788 +Test: [ 3200/21770] eta: 0:21:50 time: 0.0741 data: 0.0019 max mem: 19788 +Test: [ 3300/21770] eta: 0:21:47 time: 0.0829 data: 0.0026 max mem: 19788 +Test: [ 3400/21770] eta: 0:21:40 time: 0.0617 data: 0.0018 max mem: 19788 +Test: [ 3500/21770] eta: 0:21:30 time: 0.0589 data: 0.0018 max mem: 19788 +Test: [ 3600/21770] eta: 0:21:19 time: 0.0632 data: 0.0018 max mem: 19788 +Test: [ 3700/21770] eta: 0:21:14 time: 0.0826 data: 0.0021 max mem: 19788 +Test: [ 3800/21770] eta: 0:21:07 time: 0.0735 data: 0.0023 max mem: 19788 +Test: [ 3900/21770] eta: 0:21:00 time: 0.0739 data: 0.0022 max mem: 19788 +Test: [ 4000/21770] eta: 0:20:58 time: 0.0823 data: 0.0025 max mem: 19788 +Test: [ 4100/21770] eta: 0:20:51 time: 0.0826 data: 0.0025 max mem: 19788 +Test: [ 4200/21770] eta: 0:20:48 time: 0.0800 data: 0.0024 max mem: 19788 +Test: [ 4300/21770] eta: 0:20:40 time: 0.0817 data: 0.0024 max mem: 19788 +Test: [ 4400/21770] eta: 0:20:30 time: 0.0635 data: 0.0018 max mem: 19788 +Test: [ 4500/21770] eta: 0:20:22 time: 0.0617 data: 0.0018 max mem: 19788 +Test: [ 4600/21770] eta: 0:20:13 time: 0.0732 data: 0.0021 max mem: 19788 +Test: [ 4700/21770] eta: 0:20:06 time: 0.0670 data: 0.0019 max mem: 19788 +Test: [ 4800/21770] eta: 0:19:58 time: 0.0829 data: 0.0026 max mem: 19788 +Test: [ 4900/21770] eta: 0:19:52 time: 0.0767 data: 0.0024 max mem: 19788 +Test: [ 5000/21770] eta: 0:19:48 time: 0.0665 data: 0.0020 max mem: 19788 +Test: [ 5100/21770] eta: 0:19:39 time: 0.0629 data: 0.0016 max mem: 19788 +Test: [ 5200/21770] eta: 0:19:30 time: 0.0649 data: 0.0018 max mem: 19788 +Test: [ 5300/21770] eta: 0:19:22 time: 0.0765 data: 0.0024 max mem: 19788 +Test: [ 5400/21770] eta: 0:19:15 time: 0.0680 data: 0.0020 max mem: 19788 +Test: [ 5500/21770] eta: 0:19:07 time: 0.0654 data: 0.0019 max mem: 19788 +Test: [ 5600/21770] eta: 0:19:00 time: 0.0583 data: 0.0017 max mem: 19788 +Test: [ 5700/21770] eta: 0:18:51 time: 0.0534 data: 0.0015 max mem: 19788 +Test: [ 5800/21770] eta: 0:18:43 time: 0.0774 data: 0.0107 max mem: 19788 +Test: [ 5900/21770] eta: 0:18:47 time: 0.0765 data: 0.0014 max mem: 19788 +Test: [ 6000/21770] eta: 0:18:39 time: 0.0622 data: 0.0020 max mem: 19788 +Test: [ 6100/21770] eta: 0:18:31 time: 0.0616 data: 0.0017 max mem: 19788 +Test: [ 6200/21770] eta: 0:18:23 time: 0.0631 data: 0.0019 max mem: 19788 +Test: [ 6300/21770] eta: 0:18:17 time: 0.0796 data: 0.0022 max mem: 19788 +Test: [ 6400/21770] eta: 0:18:09 time: 0.0712 data: 0.0022 max mem: 19788 +Test: [ 6500/21770] eta: 0:18:01 time: 0.0642 data: 0.0017 max mem: 19788 +Test: [ 6600/21770] eta: 0:17:53 time: 0.0637 data: 0.0018 max mem: 19788 +Test: [ 6700/21770] eta: 0:17:46 time: 0.0744 data: 0.0023 max mem: 19788 +Test: [ 6800/21770] eta: 0:17:38 time: 0.0741 data: 0.0019 max mem: 19788 +Test: [ 6900/21770] eta: 0:17:31 time: 0.0654 data: 0.0020 max mem: 19788 +Test: [ 7000/21770] eta: 0:17:25 time: 0.0668 data: 0.0019 max mem: 19788 +Test: [ 7100/21770] eta: 0:17:19 time: 0.0766 data: 0.0024 max mem: 19788 +Test: [ 7200/21770] eta: 0:17:11 time: 0.0669 data: 0.0019 max mem: 19788 +Test: [ 7300/21770] eta: 0:17:06 time: 0.0745 data: 0.0021 max mem: 19788 +Test: [ 7400/21770] eta: 0:16:58 time: 0.0713 data: 0.0019 max mem: 19788 +Test: [ 7500/21770] eta: 0:16:50 time: 0.0744 data: 0.0022 max mem: 19788 +Test: [ 7600/21770] eta: 0:16:42 time: 0.0640 data: 0.0020 max mem: 19788 +Test: [ 7700/21770] eta: 0:16:34 time: 0.0625 data: 0.0018 max mem: 19788 +Test: [ 7800/21770] eta: 0:16:27 time: 0.0762 data: 0.0023 max mem: 19788 +Test: [ 7900/21770] eta: 0:16:21 time: 0.0789 data: 0.0021 max mem: 19788 +Test: [ 8000/21770] eta: 0:16:14 time: 0.0728 data: 0.0020 max mem: 19788 +Test: [ 8100/21770] eta: 0:16:07 time: 0.0817 data: 0.0026 max mem: 19788 +Test: [ 8200/21770] eta: 0:16:01 time: 0.0816 data: 0.0025 max mem: 19788 +Test: [ 8300/21770] eta: 0:15:55 time: 0.0655 data: 0.0019 max mem: 19788 +Test: [ 8400/21770] eta: 0:15:47 time: 0.0733 data: 0.0019 max mem: 19788 +Test: [ 8500/21770] eta: 0:15:42 time: 0.0818 data: 0.0024 max mem: 19788 +Test: [ 8600/21770] eta: 0:15:35 time: 0.0783 data: 0.0024 max mem: 19788 +Test: [ 8700/21770] eta: 0:15:27 time: 0.0612 data: 0.0017 max mem: 19788 +Test: [ 8800/21770] eta: 0:15:19 time: 0.0644 data: 0.0018 max mem: 19788 +Test: [ 8900/21770] eta: 0:15:12 time: 0.0620 data: 0.0019 max mem: 19788 +Test: [ 9000/21770] eta: 0:15:05 time: 0.0678 data: 0.0020 max mem: 19788 +Test: [ 9100/21770] eta: 0:14:57 time: 0.0700 data: 0.0019 max mem: 19788 +Test: [ 9200/21770] eta: 0:14:50 time: 0.0817 data: 0.0024 max mem: 19788 +Test: [ 9300/21770] eta: 0:14:43 time: 0.0673 data: 0.0018 max mem: 19788 +Test: [ 9400/21770] eta: 0:14:34 time: 0.0609 data: 0.0017 max mem: 19788 +Test: [ 9500/21770] eta: 0:14:26 time: 0.0646 data: 0.0018 max mem: 19788 +Test: [ 9600/21770] eta: 0:14:18 time: 0.0659 data: 0.0018 max mem: 19788 +Test: [ 9700/21770] eta: 0:14:11 time: 0.0739 data: 0.0020 max mem: 19788 +Test: [ 9800/21770] eta: 0:14:05 time: 0.0834 data: 0.0021 max mem: 19788 +Test: [ 9900/21770] eta: 0:13:58 time: 0.0717 data: 0.0019 max mem: 19788 +Test: [10000/21770] eta: 0:13:51 time: 0.0632 data: 0.0018 max mem: 19788 +Test: [10100/21770] eta: 0:13:44 time: 0.0642 data: 0.0019 max mem: 19788 +Test: [10200/21770] eta: 0:13:37 time: 0.0653 data: 0.0018 max mem: 19788 +Test: [10300/21770] eta: 0:13:29 time: 0.0640 data: 0.0018 max mem: 19788 +Test: [10400/21770] eta: 0:13:22 time: 0.0674 data: 0.0020 max mem: 19788 +Test: [10500/21770] eta: 0:13:15 time: 0.0695 data: 0.0021 max mem: 19788 +Test: [10600/21770] eta: 0:13:08 time: 0.0659 data: 0.0018 max mem: 19788 +Test: [10700/21770] eta: 0:13:01 time: 0.0680 data: 0.0020 max mem: 19788 +Test: [10800/21770] eta: 0:12:53 time: 0.0664 data: 0.0020 max mem: 19788 +Test: [10900/21770] eta: 0:12:47 time: 0.0706 data: 0.0020 max mem: 19788 +Test: [11000/21770] eta: 0:12:40 time: 0.0645 data: 0.0021 max mem: 19788 +Test: [11100/21770] eta: 0:12:32 time: 0.0641 data: 0.0019 max mem: 19788 +Test: [11200/21770] eta: 0:12:25 time: 0.0703 data: 0.0022 max mem: 19788 +Test: [11300/21770] eta: 0:12:18 time: 0.0754 data: 0.0021 max mem: 19788 +Test: [11400/21770] eta: 0:12:12 time: 0.0826 data: 0.0026 max mem: 19788 +Test: [11500/21770] eta: 0:12:05 time: 0.0628 data: 0.0019 max mem: 19788 +Test: [11600/21770] eta: 0:11:58 time: 0.0825 data: 0.0024 max mem: 19788 +Test: [11700/21770] eta: 0:11:52 time: 0.0810 data: 0.0024 max mem: 19788 +Test: [11800/21770] eta: 0:11:45 time: 0.0811 data: 0.0025 max mem: 19788 +Test: 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0:10:09 time: 0.0825 data: 0.0026 max mem: 19788 +Test: [13300/21770] eta: 0:10:02 time: 0.0757 data: 0.0025 max mem: 19788 +Test: [13400/21770] eta: 0:09:55 time: 0.0824 data: 0.0025 max mem: 19788 +Test: [13500/21770] eta: 0:09:48 time: 0.0666 data: 0.0019 max mem: 19788 +Test: [13600/21770] eta: 0:09:41 time: 0.0685 data: 0.0020 max mem: 19788 +Test: [13700/21770] eta: 0:09:34 time: 0.0830 data: 0.0026 max mem: 19788 +Test: [13800/21770] eta: 0:09:28 time: 0.0657 data: 0.0020 max mem: 19788 +Test: [13900/21770] eta: 0:09:20 time: 0.0832 data: 0.0026 max mem: 19788 +Test: [14000/21770] eta: 0:09:13 time: 0.0794 data: 0.0025 max mem: 19788 +Test: [14100/21770] eta: 0:09:07 time: 0.0827 data: 0.0025 max mem: 19788 +Test: [14200/21770] eta: 0:08:59 time: 0.0619 data: 0.0019 max mem: 19788 +Test: [14300/21770] eta: 0:08:53 time: 0.0823 data: 0.0024 max mem: 19788 +Test: [14400/21770] eta: 0:08:46 time: 0.0637 data: 0.0020 max mem: 19788 +Test: [14500/21770] eta: 0:08:38 time: 0.0623 data: 0.0018 max mem: 19788 +Test: [14600/21770] eta: 0:08:31 time: 0.0716 data: 0.0023 max mem: 19788 +Test: [14700/21770] eta: 0:08:24 time: 0.0786 data: 0.0024 max mem: 19788 +Test: [14800/21770] eta: 0:08:16 time: 0.0602 data: 0.0019 max mem: 19788 +Test: [14900/21770] eta: 0:08:09 time: 0.0625 data: 0.0019 max mem: 19788 +Test: [15000/21770] eta: 0:08:01 time: 0.0748 data: 0.0020 max mem: 19788 +Test: [15100/21770] eta: 0:07:55 time: 0.0828 data: 0.0024 max mem: 19788 +Test: [15200/21770] eta: 0:07:48 time: 0.0629 data: 0.0018 max mem: 19788 +Test: [15300/21770] eta: 0:07:40 time: 0.0653 data: 0.0019 max mem: 19788 +Test: [15400/21770] eta: 0:07:33 time: 0.0819 data: 0.0025 max mem: 19788 +Test: [15500/21770] eta: 0:07:27 time: 0.0821 data: 0.0025 max mem: 19788 +Test: [15600/21770] eta: 0:07:20 time: 0.0679 data: 0.0020 max mem: 19788 +Test: [15700/21770] eta: 0:07:12 time: 0.0613 data: 0.0018 max mem: 19788 +Test: [15800/21770] eta: 0:07:05 time: 0.0641 data: 0.0018 max mem: 19788 +Test: [15900/21770] eta: 0:06:57 time: 0.0630 data: 0.0018 max mem: 19788 +Test: [16000/21770] eta: 0:06:50 time: 0.0628 data: 0.0018 max mem: 19788 +Test: [16100/21770] eta: 0:06:43 time: 0.0655 data: 0.0020 max mem: 19788 +Test: [16200/21770] eta: 0:06:35 time: 0.0637 data: 0.0020 max mem: 19788 +Test: [16300/21770] eta: 0:06:28 time: 0.0650 data: 0.0021 max mem: 19788 +Test: [16400/21770] eta: 0:06:21 time: 0.0692 data: 0.0019 max mem: 19788 +Test: [16500/21770] eta: 0:06:14 time: 0.0830 data: 0.0026 max mem: 19788 +Test: [16600/21770] eta: 0:06:07 time: 0.0662 data: 0.0020 max mem: 19788 +Test: [16700/21770] eta: 0:05:59 time: 0.0632 data: 0.0020 max mem: 19788 +Test: [16800/21770] eta: 0:05:52 time: 0.0626 data: 0.0019 max mem: 19788 +Test: [16900/21770] eta: 0:05:45 time: 0.0630 data: 0.0019 max mem: 19788 +Test: [17000/21770] eta: 0:05:38 time: 0.0842 data: 0.0025 max mem: 19788 +Test: [17100/21770] eta: 0:05:31 time: 0.0826 data: 0.0024 max mem: 19788 +Test: [17200/21770] eta: 0:05:24 time: 0.0825 data: 0.0025 max mem: 19788 +Test: [17300/21770] eta: 0:05:17 time: 0.0840 data: 0.0021 max mem: 19788 +Test: [17400/21770] eta: 0:05:10 time: 0.0613 data: 0.0017 max mem: 19788 +Test: [17500/21770] eta: 0:05:03 time: 0.0837 data: 0.0022 max mem: 19788 +Test: [17600/21770] eta: 0:04:56 time: 0.0762 data: 0.0021 max mem: 19788 +Test: [17700/21770] eta: 0:04:49 time: 0.0819 data: 0.0023 max mem: 19788 +Test: [17800/21770] eta: 0:04:42 time: 0.0784 data: 0.0024 max mem: 19788 +Test: [17900/21770] eta: 0:04:35 time: 0.0754 data: 0.0021 max mem: 19788 +Test: [18000/21770] eta: 0:04:28 time: 0.0833 data: 0.0019 max mem: 19788 +Test: [18100/21770] eta: 0:04:21 time: 0.0829 data: 0.0024 max mem: 19788 +Test: [18200/21770] eta: 0:04:14 time: 0.0818 data: 0.0024 max mem: 19788 +Test: [18300/21770] eta: 0:04:07 time: 0.0839 data: 0.0024 max mem: 19788 +Test: [18400/21770] eta: 0:04:00 time: 0.0638 data: 0.0019 max mem: 19788 +Test: [18500/21770] eta: 0:03:53 time: 0.0628 data: 0.0019 max mem: 19788 +Test: [18600/21770] eta: 0:03:46 time: 0.0611 data: 0.0018 max mem: 19788 +Test: [18700/21770] eta: 0:03:38 time: 0.0630 data: 0.0018 max mem: 19788 +Test: [18800/21770] eta: 0:03:31 time: 0.0637 data: 0.0019 max mem: 19788 +Test: [18900/21770] eta: 0:03:24 time: 0.0836 data: 0.0024 max mem: 19788 +Test: [19000/21770] eta: 0:03:17 time: 0.0815 data: 0.0025 max mem: 19788 +Test: [19100/21770] eta: 0:03:10 time: 0.0766 data: 0.0025 max mem: 19788 +Test: [19200/21770] eta: 0:03:03 time: 0.0639 data: 0.0019 max mem: 19788 +Test: [19300/21770] eta: 0:02:56 time: 0.0828 data: 0.0026 max mem: 19788 +Test: [19400/21770] eta: 0:02:48 time: 0.0749 data: 0.0019 max mem: 19788 +Test: [19500/21770] eta: 0:02:41 time: 0.0821 data: 0.0023 max mem: 19788 +Test: [19600/21770] eta: 0:02:34 time: 0.0621 data: 0.0016 max mem: 19788 +Test: [19700/21770] eta: 0:02:27 time: 0.0742 data: 0.0021 max mem: 19788 +Test: [19800/21770] eta: 0:02:20 time: 0.0817 data: 0.0025 max mem: 19788 +Test: [19900/21770] eta: 0:02:13 time: 0.0816 data: 0.0024 max mem: 19788 +Test: [20000/21770] eta: 0:02:06 time: 0.0608 data: 0.0019 max mem: 19788 +Test: [20100/21770] eta: 0:01:59 time: 0.0700 data: 0.0020 max mem: 19788 +Test: [20200/21770] eta: 0:01:51 time: 0.0626 data: 0.0018 max mem: 19788 +Test: [20300/21770] eta: 0:01:44 time: 0.0738 data: 0.0020 max mem: 19788 +Test: [20400/21770] eta: 0:01:37 time: 0.0640 data: 0.0019 max mem: 19788 +Test: [20500/21770] eta: 0:01:30 time: 0.0615 data: 0.0019 max mem: 19788 +Test: [20600/21770] eta: 0:01:23 time: 0.0664 data: 0.0023 max mem: 19788 +Test: [20700/21770] eta: 0:01:16 time: 0.0769 data: 0.0023 max mem: 19788 +Test: [20800/21770] eta: 0:01:09 time: 0.0640 data: 0.0019 max mem: 19788 +Test: [20900/21770] eta: 0:01:01 time: 0.0792 data: 0.0021 max mem: 19788 +Test: [21000/21770] eta: 0:00:54 time: 0.0819 data: 0.0026 max mem: 19788 +Test: [21100/21770] eta: 0:00:47 time: 0.0814 data: 0.0020 max mem: 19788 +Test: [21200/21770] eta: 0:00:40 time: 0.0840 data: 0.0020 max mem: 19788 +Test: [21300/21770] eta: 0:00:33 time: 0.0676 data: 0.0021 max mem: 19788 +Test: [21400/21770] eta: 0:00:26 time: 0.0635 data: 0.0020 max mem: 19788 +Test: [21500/21770] eta: 0:00:19 time: 0.0644 data: 0.0019 max mem: 19788 +Test: [21600/21770] eta: 0:00:12 time: 0.0732 data: 0.0021 max mem: 19788 +Test: [21700/21770] eta: 0:00:04 time: 0.0622 data: 0.0020 max mem: 19788 +Test: Total time: 0:25:50 +Final results: +Mean IoU is 63.38 + + precision@0.5 = 70.14 + precision@0.6 = 64.67 + precision@0.7 = 58.18 + precision@0.8 = 47.91 + precision@0.9 = 24.17 + overall IoU = 63.79 + mean IoU = 63.38 + +Mean accuracy for one-to-zero sample is 81.61 + +Average object IoU 0.6337798051411863 +Overall IoU 63.78872299194336 +Better epoch: 21 + +Epoch: [22] [ 0/2138] eta: 6:47:51 lr: 2.4369752025516136e-05 loss: 0.0297 (0.0297) time: 11.4458 data: 2.1088 max mem: 19788 +Epoch: [22] [ 10/2138] eta: 2:37:17 lr: 2.436405260971768e-05 loss: 0.0247 (0.0262) time: 4.4348 data: 0.1943 max mem: 19788 +Epoch: [22] [ 20/2138] eta: 2:30:26 lr: 2.435835304577663e-05 loss: 0.0236 (0.0249) time: 3.9025 data: 0.0026 max mem: 19788 +Epoch: [22] [ 30/2138] eta: 2:23:00 lr: 2.4352653333650624e-05 loss: 0.0236 (0.0248) time: 3.8703 data: 0.0027 max mem: 19788 +Epoch: [22] [ 40/2138] eta: 2:19:53 lr: 2.434695347329726e-05 loss: 0.0257 (0.0258) time: 3.7268 data: 0.0028 max mem: 19788 +Epoch: [22] [ 50/2138] eta: 2:17:18 lr: 2.4341253464674138e-05 loss: 0.0270 (0.0263) time: 3.7516 data: 0.0030 max mem: 19788 +Epoch: [22] [ 60/2138] eta: 2:15:24 lr: 2.433555330773881e-05 loss: 0.0230 (0.0258) time: 3.7236 data: 0.0031 max mem: 19788 +Epoch: [22] [ 70/2138] eta: 2:13:33 lr: 2.4329853002448823e-05 loss: 0.0217 (0.0257) time: 3.6954 data: 0.0032 max mem: 19788 +Epoch: [22] [ 80/2138] eta: 2:13:20 lr: 2.4324152548761688e-05 loss: 0.0258 (0.0263) time: 3.8185 data: 0.0031 max mem: 19788 +Epoch: [22] [ 90/2138] eta: 2:11:48 lr: 2.43184519466349e-05 loss: 0.0261 (0.0263) time: 3.8149 data: 0.0031 max mem: 19788 +Epoch: [22] [ 100/2138] eta: 2:10:34 lr: 2.4312751196025933e-05 loss: 0.0260 (0.0264) time: 3.6702 data: 0.0032 max mem: 19788 +Epoch: [22] [ 110/2138] eta: 2:09:36 lr: 2.4307050296892227e-05 loss: 0.0250 (0.0265) time: 3.7111 data: 0.0031 max mem: 19788 +Epoch: [22] [ 120/2138] eta: 2:08:27 lr: 2.430134924919121e-05 loss: 0.0254 (0.0268) time: 3.6941 data: 0.0031 max mem: 19788 +Epoch: [22] [ 130/2138] eta: 2:07:26 lr: 2.429564805288028e-05 loss: 0.0281 (0.0269) time: 3.6615 data: 0.0030 max mem: 19788 +Epoch: [22] [ 140/2138] eta: 2:06:43 lr: 2.428994670791681e-05 loss: 0.0268 (0.0268) time: 3.7209 data: 0.0030 max mem: 19788 +Epoch: [22] [ 150/2138] eta: 2:06:06 lr: 2.4284245214258167e-05 loss: 0.0245 (0.0266) time: 3.7927 data: 0.0030 max mem: 19788 +Epoch: [22] [ 160/2138] eta: 2:05:42 lr: 2.4278543571861666e-05 loss: 0.0285 (0.0270) time: 3.8662 data: 0.0030 max mem: 19788 +Epoch: [22] [ 170/2138] eta: 2:05:28 lr: 2.4272841780684617e-05 loss: 0.0290 (0.0271) time: 3.9702 data: 0.0033 max mem: 19788 +Epoch: [22] [ 180/2138] eta: 2:04:57 lr: 2.4267139840684307e-05 loss: 0.0279 (0.0274) time: 3.9596 data: 0.0032 max mem: 19788 +Epoch: [22] [ 190/2138] eta: 2:04:17 lr: 2.4261437751817996e-05 loss: 0.0239 (0.0274) time: 3.8528 data: 0.0029 max mem: 19788 +Epoch: [22] [ 200/2138] eta: 2:04:16 lr: 2.4255735514042918e-05 loss: 0.0208 (0.0271) time: 4.0107 data: 0.0029 max mem: 19788 +Epoch: [22] [ 210/2138] eta: 2:04:18 lr: 2.425003312731629e-05 loss: 0.0312 (0.0276) time: 4.2548 data: 0.0030 max mem: 19788 +Epoch: [22] [ 220/2138] eta: 2:03:55 lr: 2.424433059159529e-05 loss: 0.0310 (0.0275) time: 4.1728 data: 0.0031 max mem: 19788 +Epoch: [22] [ 230/2138] eta: 2:03:31 lr: 2.42386279068371e-05 loss: 0.0267 (0.0280) time: 4.0493 data: 0.0031 max mem: 19788 +Epoch: [22] [ 240/2138] eta: 2:03:05 lr: 2.423292507299885e-05 loss: 0.0304 (0.0280) time: 4.0521 data: 0.0031 max mem: 19788 +Epoch: [22] [ 250/2138] eta: 2:02:32 lr: 2.4227222090037665e-05 loss: 0.0254 (0.0280) time: 4.0092 data: 0.0030 max mem: 19788 +Epoch: [22] [ 260/2138] eta: 2:01:42 lr: 2.422151895791064e-05 loss: 0.0239 (0.0279) time: 3.8538 data: 0.0029 max mem: 19788 +Epoch: [22] [ 270/2138] eta: 2:00:47 lr: 2.4215815676574845e-05 loss: 0.0252 (0.0280) time: 3.6978 data: 0.0030 max mem: 19788 +Epoch: [22] [ 280/2138] eta: 2:00:00 lr: 2.421011224598733e-05 loss: 0.0271 (0.0279) time: 3.7058 data: 0.0030 max mem: 19788 +Epoch: [22] [ 290/2138] eta: 1:59:21 lr: 2.420440866610511e-05 loss: 0.0276 (0.0279) time: 3.8174 data: 0.0030 max mem: 19788 +Epoch: [22] [ 300/2138] eta: 1:58:39 lr: 2.4198704936885203e-05 loss: 0.0249 (0.0278) time: 3.8474 data: 0.0029 max mem: 19788 +Epoch: [22] [ 310/2138] eta: 1:57:47 lr: 2.419300105828457e-05 loss: 0.0241 (0.0277) time: 3.7334 data: 0.0032 max mem: 19788 +Epoch: [22] [ 320/2138] eta: 1:57:02 lr: 2.4187297030260177e-05 loss: 0.0270 (0.0278) time: 3.7018 data: 0.0033 max mem: 19788 +Epoch: [22] [ 330/2138] eta: 1:56:12 lr: 2.4181592852768946e-05 loss: 0.0292 (0.0281) time: 3.7022 data: 0.0031 max mem: 19788 +Epoch: [22] [ 340/2138] eta: 1:55:29 lr: 2.417588852576779e-05 loss: 0.0253 (0.0281) time: 3.7082 data: 0.0031 max mem: 19788 +Epoch: [22] [ 350/2138] eta: 1:54:49 lr: 2.4170184049213584e-05 loss: 0.0253 (0.0280) time: 3.8044 data: 0.0031 max mem: 19788 +Epoch: [22] [ 360/2138] eta: 1:54:05 lr: 2.4164479423063197e-05 loss: 0.0271 (0.0280) time: 3.7829 data: 0.0033 max mem: 19788 +Epoch: [22] [ 370/2138] eta: 1:53:19 lr: 2.415877464727345e-05 loss: 0.0287 (0.0281) time: 3.7111 data: 0.0034 max mem: 19788 +Epoch: [22] [ 380/2138] eta: 1:52:34 lr: 2.4153069721801165e-05 loss: 0.0272 (0.0280) time: 3.7001 data: 0.0031 max mem: 19788 +Epoch: [22] [ 390/2138] eta: 1:51:52 lr: 2.4147364646603122e-05 loss: 0.0245 (0.0280) time: 3.7313 data: 0.0030 max mem: 19788 +Epoch: [22] [ 400/2138] eta: 1:51:09 lr: 2.4141659421636095e-05 loss: 0.0264 (0.0280) time: 3.7512 data: 0.0031 max mem: 19788 +Epoch: [22] [ 410/2138] eta: 1:50:26 lr: 2.4135954046856814e-05 loss: 0.0295 (0.0282) time: 3.7294 data: 0.0030 max mem: 19788 +Epoch: [22] [ 420/2138] eta: 1:49:39 lr: 2.4130248522221998e-05 loss: 0.0295 (0.0281) time: 3.6795 data: 0.0030 max mem: 19788 +Epoch: [22] [ 430/2138] eta: 1:49:00 lr: 2.4124542847688338e-05 loss: 0.0255 (0.0281) time: 3.7277 data: 0.0030 max mem: 19788 +Epoch: [22] [ 440/2138] eta: 1:48:21 lr: 2.4118837023212506e-05 loss: 0.0257 (0.0282) time: 3.8107 data: 0.0030 max mem: 19788 +Epoch: [22] [ 450/2138] eta: 1:47:39 lr: 2.4113131048751143e-05 loss: 0.0282 (0.0282) time: 3.7604 data: 0.0029 max mem: 19788 +Epoch: [22] [ 460/2138] eta: 1:47:03 lr: 2.410742492426087e-05 loss: 0.0291 (0.0283) time: 3.8020 data: 0.0030 max mem: 19788 +Epoch: [22] [ 470/2138] eta: 1:46:30 lr: 2.4101718649698278e-05 loss: 0.0291 (0.0282) time: 3.9321 data: 0.0033 max mem: 19788 +Epoch: [22] [ 480/2138] eta: 1:45:46 lr: 2.409601222501995e-05 loss: 0.0265 (0.0282) time: 3.8203 data: 0.0031 max mem: 19788 +Epoch: [22] [ 490/2138] eta: 1:45:03 lr: 2.4090305650182425e-05 loss: 0.0274 (0.0282) time: 3.6874 data: 0.0033 max mem: 19788 +Epoch: [22] [ 500/2138] eta: 1:44:20 lr: 2.4084598925142237e-05 loss: 0.0263 (0.0282) time: 3.6826 data: 0.0034 max mem: 19788 +Epoch: [22] [ 510/2138] eta: 1:43:40 lr: 2.4078892049855874e-05 loss: 0.0284 (0.0283) time: 3.7235 data: 0.0032 max mem: 19788 +Epoch: [22] [ 520/2138] eta: 1:43:00 lr: 2.407318502427982e-05 loss: 0.0290 (0.0282) time: 3.7639 data: 0.0032 max mem: 19788 +Epoch: [22] [ 530/2138] eta: 1:42:19 lr: 2.4067477848370527e-05 loss: 0.0253 (0.0282) time: 3.7393 data: 0.0033 max mem: 19788 +Epoch: [22] [ 540/2138] eta: 1:41:51 lr: 2.406177052208442e-05 loss: 0.0253 (0.0282) time: 3.9574 data: 0.0032 max mem: 19788 +Epoch: [22] [ 550/2138] eta: 1:41:08 lr: 2.4056063045377903e-05 loss: 0.0266 (0.0282) time: 3.9145 data: 0.0030 max mem: 19788 +Epoch: [22] [ 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19788 +Epoch: [22] [ 640/2138] eta: 1:35:59 lr: 2.4004688978895558e-05 loss: 0.0237 (0.0283) time: 3.9822 data: 0.0031 max mem: 19788 +Epoch: [22] [ 650/2138] eta: 1:35:22 lr: 2.3998979995581856e-05 loss: 0.0247 (0.0282) time: 4.0304 data: 0.0029 max mem: 19788 +Epoch: [22] [ 660/2138] eta: 1:34:40 lr: 2.3993270861366582e-05 loss: 0.0258 (0.0282) time: 3.7919 data: 0.0031 max mem: 19788 +Epoch: [22] [ 670/2138] eta: 1:33:59 lr: 2.3987561576205862e-05 loss: 0.0258 (0.0282) time: 3.7129 data: 0.0031 max mem: 19788 +Epoch: [22] [ 680/2138] eta: 1:33:24 lr: 2.398185214005578e-05 loss: 0.0279 (0.0282) time: 3.8718 data: 0.0030 max mem: 19788 +Epoch: [22] [ 690/2138] eta: 1:32:45 lr: 2.39761425528724e-05 loss: 0.0287 (0.0282) time: 3.9066 data: 0.0032 max mem: 19788 +Epoch: [22] [ 700/2138] eta: 1:32:07 lr: 2.3970432814611766e-05 loss: 0.0276 (0.0282) time: 3.8300 data: 0.0033 max mem: 19788 +Epoch: [22] [ 710/2138] eta: 1:31:25 lr: 2.396472292522989e-05 loss: 0.0270 (0.0282) time: 3.7733 data: 0.0031 max mem: 19788 +Epoch: [22] [ 720/2138] eta: 1:30:48 lr: 2.3959012884682757e-05 loss: 0.0270 (0.0282) time: 3.7925 data: 0.0031 max mem: 19788 +Epoch: [22] [ 730/2138] eta: 1:30:06 lr: 2.3953302692926343e-05 loss: 0.0282 (0.0283) time: 3.7673 data: 0.0031 max mem: 19788 +Epoch: [22] [ 740/2138] eta: 1:29:26 lr: 2.3947592349916584e-05 loss: 0.0258 (0.0282) time: 3.7084 data: 0.0032 max mem: 19788 +Epoch: [22] [ 750/2138] eta: 1:28:44 lr: 2.3941881855609407e-05 loss: 0.0244 (0.0282) time: 3.7103 data: 0.0035 max mem: 19788 +Epoch: [22] [ 760/2138] eta: 1:28:06 lr: 2.3936171209960688e-05 loss: 0.0293 (0.0283) time: 3.7446 data: 0.0034 max mem: 19788 +Epoch: [22] [ 770/2138] eta: 1:27:27 lr: 2.393046041292631e-05 loss: 0.0293 (0.0283) time: 3.8317 data: 0.0029 max mem: 19788 +Epoch: [22] [ 780/2138] eta: 1:26:49 lr: 2.3924749464462106e-05 loss: 0.0291 (0.0284) time: 3.8459 data: 0.0029 max mem: 19788 +Epoch: [22] [ 790/2138] eta: 1:26:10 lr: 2.3919038364523912e-05 loss: 0.0271 (0.0283) time: 3.8107 data: 0.0030 max mem: 19788 +Epoch: [22] [ 800/2138] eta: 1:25:30 lr: 2.3913327113067498e-05 loss: 0.0239 (0.0283) time: 3.7604 data: 0.0028 max mem: 19788 +Epoch: [22] [ 810/2138] eta: 1:24:49 lr: 2.3907615710048657e-05 loss: 0.0239 (0.0283) time: 3.7130 data: 0.0029 max mem: 19788 +Epoch: [22] [ 820/2138] eta: 1:24:09 lr: 2.3901904155423116e-05 loss: 0.0267 (0.0283) time: 3.7134 data: 0.0030 max mem: 19788 +Epoch: [22] [ 830/2138] eta: 1:23:31 lr: 2.389619244914661e-05 loss: 0.0238 (0.0282) time: 3.7919 data: 0.0030 max mem: 19788 +Epoch: [22] [ 840/2138] eta: 1:22:50 lr: 2.3890480591174827e-05 loss: 0.0231 (0.0282) time: 3.7344 data: 0.0033 max mem: 19788 +Epoch: [22] [ 850/2138] eta: 1:22:13 lr: 2.3884768581463444e-05 loss: 0.0238 (0.0282) time: 3.7968 data: 0.0033 max mem: 19788 +Epoch: [22] [ 860/2138] eta: 1:21:35 lr: 2.3879056419968096e-05 loss: 0.0263 (0.0282) time: 3.8981 data: 0.0032 max mem: 19788 +Epoch: [22] [ 870/2138] eta: 1:20:55 lr: 2.3873344106644417e-05 loss: 0.0273 (0.0282) time: 3.7649 data: 0.0032 max mem: 19788 +Epoch: [22] [ 880/2138] eta: 1:20:15 lr: 2.3867631641447998e-05 loss: 0.0264 (0.0282) time: 3.6942 data: 0.0031 max mem: 19788 +Epoch: [22] [ 890/2138] eta: 1:19:37 lr: 2.3861919024334414e-05 loss: 0.0284 (0.0284) time: 3.7903 data: 0.0033 max mem: 19788 +Epoch: [22] [ 900/2138] eta: 1:18:58 lr: 2.385620625525921e-05 loss: 0.0288 (0.0285) time: 3.8102 data: 0.0034 max mem: 19788 +Epoch: [22] [ 910/2138] eta: 1:18:18 lr: 2.3850493334177905e-05 loss: 0.0259 (0.0285) time: 3.7442 data: 0.0031 max mem: 19788 +Epoch: [22] [ 920/2138] eta: 1:17:41 lr: 2.3844780261046008e-05 loss: 0.0250 (0.0285) time: 3.8037 data: 0.0030 max mem: 19788 +Epoch: [22] [ 930/2138] eta: 1:17:02 lr: 2.3839067035818977e-05 loss: 0.0286 (0.0285) time: 3.8413 data: 0.0032 max mem: 19788 +Epoch: [22] [ 940/2138] eta: 1:16:27 lr: 2.383335365845227e-05 loss: 0.0299 (0.0285) time: 3.9628 data: 0.0033 max mem: 19788 +Epoch: [22] [ 950/2138] eta: 1:15:51 lr: 2.3827640128901306e-05 loss: 0.0290 (0.0285) time: 4.0447 data: 0.0032 max mem: 19788 +Epoch: [22] [ 960/2138] eta: 1:15:16 lr: 2.3821926447121484e-05 loss: 0.0291 (0.0285) time: 4.0533 data: 0.0031 max mem: 19788 +Epoch: [22] [ 970/2138] eta: 1:14:40 lr: 2.3816212613068177e-05 loss: 0.0291 (0.0285) time: 4.0483 data: 0.0031 max mem: 19788 +Epoch: [22] [ 980/2138] eta: 1:14:00 lr: 2.3810498626696733e-05 loss: 0.0275 (0.0285) time: 3.8490 data: 0.0030 max mem: 19788 +Epoch: [22] [ 990/2138] eta: 1:13:21 lr: 2.380478448796247e-05 loss: 0.0275 (0.0285) time: 3.7746 data: 0.0030 max mem: 19788 +Epoch: [22] [1000/2138] eta: 1:12:45 lr: 2.37990701968207e-05 loss: 0.0272 (0.0285) time: 3.8969 data: 0.0030 max mem: 19788 +Epoch: [22] [1010/2138] eta: 1:12:06 lr: 2.3793355753226676e-05 loss: 0.0259 (0.0285) time: 3.8697 data: 0.0030 max mem: 19788 +Epoch: [22] [1020/2138] eta: 1:11:27 lr: 2.3787641157135665e-05 loss: 0.0236 (0.0285) time: 3.7786 data: 0.0030 max mem: 19788 +Epoch: [22] [1030/2138] eta: 1:10:46 lr: 2.3781926408502873e-05 loss: 0.0236 (0.0284) time: 3.7092 data: 0.0029 max mem: 19788 +Epoch: [22] [1040/2138] eta: 1:10:06 lr: 2.3776211507283517e-05 loss: 0.0281 (0.0284) time: 3.6329 data: 0.0031 max mem: 19788 +Epoch: [22] [1050/2138] eta: 1:09:26 lr: 2.377049645343275e-05 loss: 0.0285 (0.0284) time: 3.6405 data: 0.0030 max mem: 19788 +Epoch: [22] [1060/2138] eta: 1:08:45 lr: 2.376478124690573e-05 loss: 0.0279 (0.0284) time: 3.6327 data: 0.0029 max mem: 19788 +Epoch: [22] [1070/2138] eta: 1:08:05 lr: 2.3759065887657574e-05 loss: 0.0267 (0.0284) time: 3.6241 data: 0.0030 max mem: 19788 +Epoch: [22] [1080/2138] eta: 1:07:25 lr: 2.375335037564339e-05 loss: 0.0263 (0.0284) time: 3.6273 data: 0.0031 max mem: 19788 +Epoch: [22] [1090/2138] eta: 1:06:45 lr: 2.3747634710818234e-05 loss: 0.0263 (0.0284) time: 3.6350 data: 0.0032 max mem: 19788 +Epoch: [22] [1100/2138] eta: 1:06:05 lr: 2.3741918893137167e-05 loss: 0.0300 (0.0285) time: 3.6332 data: 0.0030 max mem: 19788 +Epoch: [22] [1110/2138] eta: 1:05:25 lr: 2.3736202922555198e-05 loss: 0.0293 (0.0284) time: 3.6325 data: 0.0028 max mem: 19788 +Epoch: [22] [1120/2138] eta: 1:04:45 lr: 2.3730486799027332e-05 loss: 0.0254 (0.0284) time: 3.6375 data: 0.0028 max mem: 19788 +Epoch: [22] [1130/2138] eta: 1:04:05 lr: 2.3724770522508535e-05 loss: 0.0260 (0.0285) time: 3.6303 data: 0.0029 max mem: 19788 +Epoch: [22] [1140/2138] eta: 1:03:25 lr: 2.3719054092953757e-05 loss: 0.0258 (0.0285) time: 3.6246 data: 0.0029 max mem: 19788 +Epoch: [22] [1150/2138] eta: 1:02:46 lr: 2.371333751031791e-05 loss: 0.0235 (0.0284) time: 3.6302 data: 0.0028 max mem: 19788 +Epoch: [22] [1160/2138] eta: 1:02:06 lr: 2.37076207745559e-05 loss: 0.0235 (0.0285) time: 3.6276 data: 0.0028 max mem: 19788 +Epoch: [22] [1170/2138] eta: 1:01:26 lr: 2.3701903885622585e-05 loss: 0.0257 (0.0284) time: 3.6213 data: 0.0027 max mem: 19788 +Epoch: [22] [1180/2138] eta: 1:00:47 lr: 2.369618684347282e-05 loss: 0.0260 (0.0286) time: 3.6207 data: 0.0029 max mem: 19788 +Epoch: [22] [1190/2138] eta: 1:00:07 lr: 2.3690469648061413e-05 loss: 0.0260 (0.0286) time: 3.6263 data: 0.0029 max mem: 19788 +Epoch: [22] [1200/2138] eta: 0:59:28 lr: 2.3684752299343164e-05 loss: 0.0253 (0.0286) time: 3.6291 data: 0.0027 max mem: 19788 +Epoch: [22] [1210/2138] eta: 0:58:48 lr: 2.367903479727284e-05 loss: 0.0253 (0.0285) time: 3.6232 data: 0.0027 max mem: 19788 +Epoch: [22] [1220/2138] eta: 0:58:09 lr: 2.3673317141805176e-05 loss: 0.0258 (0.0285) time: 3.6206 data: 0.0029 max mem: 19788 +Epoch: [22] [1230/2138] eta: 0:57:30 lr: 2.3667599332894903e-05 loss: 0.0258 (0.0285) time: 3.6334 data: 0.0030 max mem: 19788 +Epoch: [22] [1240/2138] eta: 0:56:50 lr: 2.3661881370496693e-05 loss: 0.0257 (0.0285) time: 3.6359 data: 0.0029 max mem: 19788 +Epoch: [22] [1250/2138] eta: 0:56:11 lr: 2.365616325456523e-05 loss: 0.0259 (0.0286) time: 3.6204 data: 0.0029 max mem: 19788 +Epoch: [22] [1260/2138] eta: 0:55:32 lr: 2.3650444985055143e-05 loss: 0.0259 (0.0285) time: 3.6258 data: 0.0028 max mem: 19788 +Epoch: [22] [1270/2138] eta: 0:54:53 lr: 2.3644726561921053e-05 loss: 0.0216 (0.0285) time: 3.6279 data: 0.0029 max mem: 19788 +Epoch: [22] [1280/2138] eta: 0:54:14 lr: 2.363900798511754e-05 loss: 0.0232 (0.0285) time: 3.6196 data: 0.0031 max mem: 19788 +Epoch: [22] [1290/2138] eta: 0:53:35 lr: 2.3633289254599177e-05 loss: 0.0285 (0.0285) time: 3.6444 data: 0.0029 max mem: 19788 +Epoch: [22] [1300/2138] eta: 0:52:56 lr: 2.3627570370320492e-05 loss: 0.0263 (0.0285) time: 3.6469 data: 0.0026 max mem: 19788 +Epoch: [22] [1310/2138] eta: 0:52:17 lr: 2.362185133223601e-05 loss: 0.0244 (0.0285) time: 3.6204 data: 0.0026 max mem: 19788 +Epoch: [22] [1320/2138] eta: 0:51:38 lr: 2.36161321403002e-05 loss: 0.0265 (0.0285) time: 3.6276 data: 0.0027 max mem: 19788 +Epoch: [22] [1330/2138] eta: 0:50:59 lr: 2.361041279446754e-05 loss: 0.0283 (0.0285) time: 3.6296 data: 0.0028 max mem: 19788 +Epoch: [22] [1340/2138] eta: 0:50:20 lr: 2.3604693294692444e-05 loss: 0.0287 (0.0286) time: 3.6224 data: 0.0027 max mem: 19788 +Epoch: [22] [1350/2138] eta: 0:49:42 lr: 2.359897364092934e-05 loss: 0.0333 (0.0286) time: 3.6180 data: 0.0028 max mem: 19788 +Epoch: [22] [1360/2138] eta: 0:49:03 lr: 2.3593253833132606e-05 loss: 0.0303 (0.0286) time: 3.6180 data: 0.0029 max mem: 19788 +Epoch: [22] [1370/2138] eta: 0:48:24 lr: 2.3587533871256596e-05 loss: 0.0280 (0.0286) time: 3.6248 data: 0.0029 max mem: 19788 +Epoch: [22] [1380/2138] eta: 0:47:45 lr: 2.358181375525564e-05 loss: 0.0257 (0.0287) time: 3.6244 data: 0.0028 max mem: 19788 +Epoch: [22] [1390/2138] eta: 0:47:07 lr: 2.3576093485084053e-05 loss: 0.0295 (0.0287) time: 3.6204 data: 0.0026 max mem: 19788 +Epoch: [22] [1400/2138] eta: 0:46:28 lr: 2.35703730606961e-05 loss: 0.0277 (0.0287) time: 3.6184 data: 0.0027 max mem: 19788 +Epoch: [22] [1410/2138] eta: 0:45:50 lr: 2.3564652482046054e-05 loss: 0.0258 (0.0286) time: 3.6247 data: 0.0028 max mem: 19788 +Epoch: [22] [1420/2138] eta: 0:45:11 lr: 2.3558931749088123e-05 loss: 0.0243 (0.0286) time: 3.6282 data: 0.0029 max mem: 19788 +Epoch: [22] [1430/2138] eta: 0:44:32 lr: 2.3553210861776522e-05 loss: 0.0290 (0.0286) time: 3.6211 data: 0.0030 max mem: 19788 +Epoch: [22] [1440/2138] eta: 0:43:54 lr: 2.354748982006542e-05 loss: 0.0265 (0.0287) time: 3.6196 data: 0.0032 max mem: 19788 +Epoch: [22] [1450/2138] eta: 0:43:15 lr: 2.3541768623908976e-05 loss: 0.0295 (0.0287) time: 3.6184 data: 0.0030 max mem: 19788 +Epoch: [22] [1460/2138] eta: 0:42:37 lr: 2.3536047273261304e-05 loss: 0.0301 (0.0287) time: 3.6168 data: 0.0027 max mem: 19788 +Epoch: [22] [1470/2138] eta: 0:41:59 lr: 2.3530325768076513e-05 loss: 0.0329 (0.0287) time: 3.6228 data: 0.0027 max mem: 19788 +Epoch: [22] [1480/2138] eta: 0:41:20 lr: 2.3524604108308662e-05 loss: 0.0288 (0.0287) time: 3.6238 data: 0.0031 max mem: 19788 +Epoch: [22] [1490/2138] eta: 0:40:42 lr: 2.351888229391181e-05 loss: 0.0280 (0.0287) time: 3.6181 data: 0.0032 max mem: 19788 +Epoch: [22] [1500/2138] eta: 0:40:04 lr: 2.351316032483997e-05 loss: 0.0276 (0.0287) time: 3.6162 data: 0.0028 max mem: 19788 +Epoch: [22] [1510/2138] eta: 0:39:25 lr: 2.350743820104713e-05 loss: 0.0272 (0.0288) time: 3.6303 data: 0.0027 max mem: 19788 +Epoch: [22] [1520/2138] eta: 0:38:47 lr: 2.3501715922487272e-05 loss: 0.0236 (0.0287) time: 3.6345 data: 0.0030 max mem: 19788 +Epoch: [22] [1530/2138] eta: 0:38:09 lr: 2.349599348911432e-05 loss: 0.0227 (0.0287) time: 3.6246 data: 0.0030 max mem: 19788 +Epoch: [22] [1540/2138] eta: 0:37:31 lr: 2.349027090088221e-05 loss: 0.0229 (0.0287) time: 3.6305 data: 0.0028 max mem: 19788 +Epoch: [22] [1550/2138] eta: 0:36:52 lr: 2.348454815774481e-05 loss: 0.0246 (0.0287) time: 3.6261 data: 0.0031 max mem: 19788 +Epoch: [22] [1560/2138] eta: 0:36:14 lr: 2.3478825259656e-05 loss: 0.0260 (0.0287) time: 3.6219 data: 0.0030 max mem: 19788 +Epoch: [22] [1570/2138] eta: 0:35:36 lr: 2.3473102206569604e-05 loss: 0.0259 (0.0288) time: 3.6308 data: 0.0028 max mem: 19788 +Epoch: [22] [1580/2138] eta: 0:34:58 lr: 2.3467378998439444e-05 loss: 0.0251 (0.0287) time: 3.6273 data: 0.0027 max mem: 19788 +Epoch: [22] [1590/2138] eta: 0:34:20 lr: 2.346165563521929e-05 loss: 0.0246 (0.0287) time: 3.6257 data: 0.0028 max mem: 19788 +Epoch: [22] [1600/2138] eta: 0:33:42 lr: 2.3455932116862918e-05 loss: 0.0305 (0.0288) time: 3.6273 data: 0.0029 max mem: 19788 +Epoch: [22] [1610/2138] eta: 0:33:04 lr: 2.345020844332404e-05 loss: 0.0266 (0.0287) time: 3.6269 data: 0.0027 max mem: 19788 +Epoch: [22] [1620/2138] eta: 0:32:26 lr: 2.3444484614556378e-05 loss: 0.0244 (0.0287) time: 3.6278 data: 0.0030 max mem: 19788 +Epoch: [22] [1630/2138] eta: 0:31:48 lr: 2.34387606305136e-05 loss: 0.0270 (0.0287) time: 3.6403 data: 0.0031 max mem: 19788 +Epoch: [22] [1640/2138] eta: 0:31:10 lr: 2.3433036491149364e-05 loss: 0.0270 (0.0288) time: 3.6386 data: 0.0029 max mem: 19788 +Epoch: [22] [1650/2138] eta: 0:30:32 lr: 2.3427312196417286e-05 loss: 0.0244 (0.0287) time: 3.6246 data: 0.0028 max mem: 19788 +Epoch: [22] [1660/2138] eta: 0:29:54 lr: 2.3421587746270983e-05 loss: 0.0234 (0.0287) time: 3.6238 data: 0.0028 max mem: 19788 +Epoch: [22] [1670/2138] eta: 0:29:16 lr: 2.341586314066401e-05 loss: 0.0234 (0.0287) time: 3.6199 data: 0.0028 max mem: 19788 +Epoch: [22] [1680/2138] eta: 0:28:38 lr: 2.341013837954993e-05 loss: 0.0266 (0.0287) time: 3.6164 data: 0.0028 max mem: 19788 +Epoch: [22] [1690/2138] eta: 0:28:01 lr: 2.3404413462882246e-05 loss: 0.0278 (0.0287) time: 3.6199 data: 0.0028 max mem: 19788 +Epoch: [22] [1700/2138] eta: 0:27:23 lr: 2.339868839061447e-05 loss: 0.0271 (0.0287) time: 3.6237 data: 0.0027 max mem: 19788 +Epoch: [22] [1710/2138] eta: 0:26:45 lr: 2.339296316270005e-05 loss: 0.0258 (0.0287) time: 3.6191 data: 0.0027 max mem: 19788 +Epoch: [22] [1720/2138] eta: 0:26:07 lr: 2.338723777909244e-05 loss: 0.0259 (0.0287) time: 3.6151 data: 0.0026 max mem: 19788 +Epoch: [22] [1730/2138] eta: 0:25:29 lr: 2.3381512239745045e-05 loss: 0.0263 (0.0287) time: 3.6208 data: 0.0026 max mem: 19788 +Epoch: [22] [1740/2138] eta: 0:24:51 lr: 2.3375786544611264e-05 loss: 0.0248 (0.0287) time: 3.6201 data: 0.0026 max mem: 19788 +Epoch: [22] [1750/2138] eta: 0:24:14 lr: 2.3370060693644444e-05 loss: 0.0254 (0.0287) time: 3.6176 data: 0.0029 max mem: 19788 +Epoch: [22] [1760/2138] eta: 0:23:36 lr: 2.336433468679793e-05 loss: 0.0263 (0.0287) time: 3.6222 data: 0.0030 max mem: 19788 +Epoch: [22] [1770/2138] eta: 0:22:58 lr: 2.3358608524025022e-05 loss: 0.0263 (0.0287) time: 3.6269 data: 0.0029 max mem: 19788 +Epoch: [22] [1780/2138] eta: 0:22:20 lr: 2.3352882205279006e-05 loss: 0.0248 (0.0287) time: 3.6259 data: 0.0029 max mem: 19788 +Epoch: [22] [1790/2138] eta: 0:21:43 lr: 2.3347155730513126e-05 loss: 0.0244 (0.0287) time: 3.6178 data: 0.0029 max mem: 19788 +Epoch: [22] [1800/2138] eta: 0:21:05 lr: 2.334142909968062e-05 loss: 0.0245 (0.0287) time: 3.6167 data: 0.0028 max mem: 19788 +Epoch: [22] [1810/2138] eta: 0:20:27 lr: 2.3335702312734688e-05 loss: 0.0261 (0.0287) time: 3.6235 data: 0.0029 max mem: 19788 +Epoch: [22] [1820/2138] eta: 0:19:50 lr: 2.332997536962849e-05 loss: 0.0275 (0.0287) time: 3.6245 data: 0.0029 max mem: 19788 +Epoch: [22] [1830/2138] eta: 0:19:12 lr: 2.3324248270315187e-05 loss: 0.0282 (0.0287) time: 3.6273 data: 0.0027 max mem: 19788 +Epoch: [22] [1840/2138] eta: 0:18:35 lr: 2.3318521014747892e-05 loss: 0.0267 (0.0287) time: 3.6257 data: 0.0028 max mem: 19788 +Epoch: [22] [1850/2138] eta: 0:17:57 lr: 2.33127936028797e-05 loss: 0.0285 (0.0287) time: 3.6162 data: 0.0029 max mem: 19788 +Epoch: [22] [1860/2138] eta: 0:17:19 lr: 2.3307066034663674e-05 loss: 0.0313 (0.0288) time: 3.6154 data: 0.0028 max mem: 19788 +Epoch: [22] [1870/2138] eta: 0:16:42 lr: 2.330133831005286e-05 loss: 0.0295 (0.0288) time: 3.6182 data: 0.0026 max mem: 19788 +Epoch: [22] [1880/2138] eta: 0:16:04 lr: 2.3295610429000258e-05 loss: 0.0268 (0.0288) time: 3.6317 data: 0.0028 max mem: 19788 +Epoch: [22] [1890/2138] eta: 0:15:27 lr: 2.328988239145887e-05 loss: 0.0255 (0.0287) time: 3.6253 data: 0.0029 max mem: 19788 +Epoch: [22] [1900/2138] eta: 0:14:49 lr: 2.328415419738164e-05 loss: 0.0265 (0.0288) time: 3.6245 data: 0.0029 max mem: 19788 +Epoch: [22] [1910/2138] eta: 0:14:12 lr: 2.3278425846721506e-05 loss: 0.0264 (0.0287) time: 3.6271 data: 0.0028 max mem: 19788 +Epoch: [22] [1920/2138] eta: 0:13:34 lr: 2.3272697339431364e-05 loss: 0.0236 (0.0287) time: 3.6171 data: 0.0029 max mem: 19788 +Epoch: [22] [1930/2138] eta: 0:12:57 lr: 2.3266968675464108e-05 loss: 0.0252 (0.0287) time: 3.6299 data: 0.0030 max mem: 19788 +Epoch: [22] [1940/2138] eta: 0:12:19 lr: 2.326123985477257e-05 loss: 0.0260 (0.0287) time: 3.6315 data: 0.0028 max mem: 19788 +Epoch: [22] [1950/2138] eta: 0:11:42 lr: 2.3255510877309583e-05 loss: 0.0269 (0.0287) time: 3.6255 data: 0.0028 max mem: 19788 +Epoch: [22] [1960/2138] eta: 0:11:04 lr: 2.3249781743027937e-05 loss: 0.0270 (0.0287) time: 3.6307 data: 0.0030 max mem: 19788 +Epoch: [22] [1970/2138] eta: 0:10:27 lr: 2.324405245188041e-05 loss: 0.0246 (0.0287) time: 3.6376 data: 0.0030 max mem: 19788 +Epoch: [22] [1980/2138] eta: 0:09:49 lr: 2.3238323003819733e-05 loss: 0.0217 (0.0287) time: 3.6295 data: 0.0030 max mem: 19788 +Epoch: [22] [1990/2138] eta: 0:09:12 lr: 2.323259339879863e-05 loss: 0.0228 (0.0287) time: 3.6268 data: 0.0031 max mem: 19788 +Epoch: [22] [2000/2138] eta: 0:08:35 lr: 2.3226863636769776e-05 loss: 0.0259 (0.0287) time: 3.6268 data: 0.0030 max mem: 19788 +Epoch: [22] [2010/2138] eta: 0:07:57 lr: 2.3221133717685843e-05 loss: 0.0271 (0.0287) time: 3.6223 data: 0.0029 max mem: 19788 +Epoch: [22] [2020/2138] eta: 0:07:20 lr: 2.3215403641499457e-05 loss: 0.0274 (0.0287) time: 3.6238 data: 0.0030 max mem: 19788 +Epoch: [22] [2030/2138] eta: 0:06:42 lr: 2.3209673408163227e-05 loss: 0.0274 (0.0287) time: 3.6346 data: 0.0030 max mem: 19788 +Epoch: [22] [2040/2138] eta: 0:06:05 lr: 2.3203943017629724e-05 loss: 0.0266 (0.0287) time: 3.6495 data: 0.0032 max mem: 19788 +Epoch: [22] [2050/2138] eta: 0:05:28 lr: 2.319821246985151e-05 loss: 0.0271 (0.0287) time: 3.6418 data: 0.0031 max mem: 19788 +Epoch: [22] [2060/2138] eta: 0:04:50 lr: 2.3192481764781095e-05 loss: 0.0269 (0.0287) time: 3.6308 data: 0.0029 max mem: 19788 +Epoch: [22] [2070/2138] eta: 0:04:13 lr: 2.3186750902370988e-05 loss: 0.0261 (0.0287) time: 3.6366 data: 0.0031 max mem: 19788 +Epoch: [22] [2080/2138] eta: 0:03:36 lr: 2.318101988257365e-05 loss: 0.0290 (0.0287) time: 3.6299 data: 0.0029 max mem: 19788 +Epoch: [22] [2090/2138] eta: 0:02:58 lr: 2.3175288705341525e-05 loss: 0.0301 (0.0287) time: 3.6158 data: 0.0027 max mem: 19788 +Epoch: [22] [2100/2138] eta: 0:02:21 lr: 2.316955737062702e-05 loss: 0.0239 (0.0287) time: 3.6310 data: 0.0028 max mem: 19788 +Epoch: [22] [2110/2138] eta: 0:01:44 lr: 2.3163825878382536e-05 loss: 0.0305 (0.0287) time: 3.6357 data: 0.0028 max mem: 19788 +Epoch: [22] [2120/2138] eta: 0:01:07 lr: 2.315809422856042e-05 loss: 0.0321 (0.0287) time: 3.6269 data: 0.0029 max mem: 19788 +Epoch: [22] [2130/2138] eta: 0:00:29 lr: 2.3152362421113002e-05 loss: 0.0278 (0.0287) time: 3.6160 data: 0.0028 max mem: 19788 +Epoch: [22] Total time: 2:12:46 +Test: [ 0/21770] eta: 19:14:25 time: 3.1817 data: 2.8241 max mem: 19788 +Test: [ 100/21770] eta: 0:35:09 time: 0.0618 data: 0.0017 max mem: 19788 +Test: [ 200/21770] eta: 0:30:21 time: 0.0718 data: 0.0021 max mem: 19788 +Test: [ 300/21770] eta: 0:28:09 time: 0.0626 data: 0.0017 max mem: 19788 +Test: [ 400/21770] eta: 0:26:54 time: 0.0594 data: 0.0017 max mem: 19788 +Test: [ 500/21770] eta: 0:26:09 time: 0.0606 data: 0.0021 max mem: 19788 +Test: [ 600/21770] eta: 0:25:23 time: 0.0634 data: 0.0019 max mem: 19788 +Test: [ 700/21770] eta: 0:24:54 time: 0.0713 data: 0.0021 max mem: 19788 +Test: [ 800/21770] eta: 0:24:54 time: 0.0795 data: 0.0024 max mem: 19788 +Test: [ 900/21770] eta: 0:24:39 time: 0.0674 data: 0.0018 max mem: 19788 +Test: [ 1000/21770] eta: 0:24:28 time: 0.0651 data: 0.0019 max mem: 19788 +Test: [ 1100/21770] eta: 0:24:08 time: 0.0610 data: 0.0018 max mem: 19788 +Test: [ 1200/21770] eta: 0:23:53 time: 0.0611 data: 0.0020 max mem: 19788 +Test: [ 1300/21770] eta: 0:23:35 time: 0.0607 data: 0.0019 max mem: 19788 +Test: [ 1400/21770] eta: 0:23:37 time: 0.0740 data: 0.0021 max mem: 19788 +Test: [ 1500/21770] eta: 0:23:28 time: 0.0637 data: 0.0019 max mem: 19788 +Test: [ 1600/21770] eta: 0:23:12 time: 0.0672 data: 0.0020 max mem: 19788 +Test: [ 1700/21770] eta: 0:23:04 time: 0.0705 data: 0.0018 max mem: 19788 +Test: [ 1800/21770] eta: 0:22:54 time: 0.0614 data: 0.0018 max mem: 19788 +Test: [ 1900/21770] eta: 0:22:42 time: 0.0673 data: 0.0021 max mem: 19788 +Test: [ 2000/21770] eta: 0:22:38 time: 0.0622 data: 0.0019 max mem: 19788 +Test: [ 2100/21770] eta: 0:22:34 time: 0.0701 data: 0.0021 max mem: 19788 +Test: [ 2200/21770] eta: 0:22:23 time: 0.0643 data: 0.0019 max mem: 19788 +Test: [ 2300/21770] eta: 0:22:12 time: 0.0664 data: 0.0018 max mem: 19788 +Test: [ 2400/21770] eta: 0:22:09 time: 0.0619 data: 0.0016 max mem: 19788 +Test: [ 2500/21770] eta: 0:22:06 time: 0.0617 data: 0.0017 max mem: 19788 +Test: [ 2600/21770] eta: 0:22:01 time: 0.0713 data: 0.0020 max mem: 19788 +Test: [ 2700/21770] eta: 0:21:54 time: 0.0626 data: 0.0018 max mem: 19788 +Test: [ 2800/21770] eta: 0:21:43 time: 0.0680 data: 0.0020 max mem: 19788 +Test: [ 2900/21770] eta: 0:21:35 time: 0.0691 data: 0.0021 max mem: 19788 +Test: [ 3000/21770] eta: 0:21:27 time: 0.0621 data: 0.0018 max mem: 19788 +Test: [ 3100/21770] eta: 0:21:23 time: 0.0678 data: 0.0018 max mem: 19788 +Test: [ 3200/21770] eta: 0:21:16 time: 0.0630 data: 0.0019 max mem: 19788 +Test: [ 3300/21770] eta: 0:21:09 time: 0.0617 data: 0.0019 max mem: 19788 +Test: [ 3400/21770] eta: 0:20:59 time: 0.0671 data: 0.0018 max mem: 19788 +Test: [ 3500/21770] eta: 0:20:54 time: 0.0769 data: 0.0025 max mem: 19788 +Test: [ 3600/21770] eta: 0:20:46 time: 0.0672 data: 0.0020 max mem: 19788 +Test: [ 3700/21770] eta: 0:20:37 time: 0.0671 data: 0.0020 max mem: 19788 +Test: [ 3800/21770] eta: 0:20:32 time: 0.0773 data: 0.0024 max mem: 19788 +Test: [ 3900/21770] eta: 0:20:25 time: 0.0609 data: 0.0017 max mem: 19788 +Test: [ 4000/21770] eta: 0:20:18 time: 0.0681 data: 0.0019 max mem: 19788 +Test: [ 4100/21770] eta: 0:20:12 time: 0.0655 data: 0.0019 max mem: 19788 +Test: [ 4200/21770] eta: 0:20:03 time: 0.0636 data: 0.0019 max mem: 19788 +Test: [ 4300/21770] eta: 0:19:56 time: 0.0613 data: 0.0018 max mem: 19788 +Test: [ 4400/21770] eta: 0:19:50 time: 0.0717 data: 0.0021 max mem: 19788 +Test: [ 4500/21770] eta: 0:19:42 time: 0.0622 data: 0.0018 max mem: 19788 +Test: [ 4600/21770] eta: 0:19:34 time: 0.0631 data: 0.0018 max mem: 19788 +Test: [ 4700/21770] eta: 0:19:27 time: 0.0693 data: 0.0021 max mem: 19788 +Test: [ 4800/21770] eta: 0:19:20 time: 0.0603 data: 0.0017 max mem: 19788 +Test: [ 4900/21770] eta: 0:19:13 time: 0.0739 data: 0.0022 max mem: 19788 +Test: [ 5000/21770] eta: 0:19:05 time: 0.0638 data: 0.0019 max mem: 19788 +Test: [ 5100/21770] eta: 0:18:59 time: 0.0705 data: 0.0020 max mem: 19788 +Test: [ 5200/21770] eta: 0:18:52 time: 0.0789 data: 0.0022 max mem: 19788 +Test: [ 5300/21770] eta: 0:18:45 time: 0.0639 data: 0.0018 max mem: 19788 +Test: [ 5400/21770] eta: 0:18:40 time: 0.0693 data: 0.0019 max mem: 19788 +Test: [ 5500/21770] eta: 0:18:31 time: 0.0640 data: 0.0020 max mem: 19788 +Test: [ 5600/21770] eta: 0:18:25 time: 0.0665 data: 0.0020 max mem: 19788 +Test: [ 5700/21770] eta: 0:18:18 time: 0.0701 data: 0.0019 max mem: 19788 +Test: [ 5800/21770] eta: 0:18:12 time: 0.0676 data: 0.0020 max mem: 19788 +Test: [ 5900/21770] eta: 0:18:04 time: 0.0620 data: 0.0019 max mem: 19788 +Test: [ 6000/21770] eta: 0:17:58 time: 0.0642 data: 0.0019 max mem: 19788 +Test: [ 6100/21770] eta: 0:17:52 time: 0.0710 data: 0.0019 max mem: 19788 +Test: [ 6200/21770] eta: 0:17:44 time: 0.0608 data: 0.0018 max mem: 19788 +Test: [ 6300/21770] eta: 0:17:37 time: 0.0605 data: 0.0017 max mem: 19788 +Test: [ 6400/21770] eta: 0:17:30 time: 0.0670 data: 0.0020 max mem: 19788 +Test: [ 6500/21770] eta: 0:17:23 time: 0.0620 data: 0.0019 max mem: 19788 +Test: [ 6600/21770] eta: 0:17:15 time: 0.0622 data: 0.0017 max mem: 19788 +Test: [ 6700/21770] eta: 0:17:08 time: 0.0655 data: 0.0020 max mem: 19788 +Test: [ 6800/21770] eta: 0:17:01 time: 0.0650 data: 0.0019 max mem: 19788 +Test: [ 6900/21770] eta: 0:16:54 time: 0.0631 data: 0.0017 max mem: 19788 +Test: [ 7000/21770] eta: 0:16:48 time: 0.0650 data: 0.0018 max mem: 19788 +Test: [ 7100/21770] eta: 0:16:40 time: 0.0607 data: 0.0019 max mem: 19788 +Test: [ 7200/21770] eta: 0:16:34 time: 0.0673 data: 0.0019 max mem: 19788 +Test: [ 7300/21770] eta: 0:16:26 time: 0.0637 data: 0.0020 max mem: 19788 +Test: [ 7400/21770] eta: 0:16:19 time: 0.0704 data: 0.0022 max mem: 19788 +Test: [ 7500/21770] eta: 0:16:12 time: 0.0649 data: 0.0018 max mem: 19788 +Test: [ 7600/21770] eta: 0:16:05 time: 0.0735 data: 0.0021 max mem: 19788 +Test: [ 7700/21770] eta: 0:15:58 time: 0.0601 data: 0.0018 max mem: 19788 +Test: [ 7800/21770] eta: 0:15:50 time: 0.0693 data: 0.0018 max mem: 19788 +Test: [ 7900/21770] eta: 0:15:43 time: 0.0637 data: 0.0018 max mem: 19788 +Test: [ 8000/21770] eta: 0:15:36 time: 0.0677 data: 0.0020 max mem: 19788 +Test: [ 8100/21770] eta: 0:15:28 time: 0.0626 data: 0.0019 max mem: 19788 +Test: [ 8200/21770] eta: 0:15:21 time: 0.0616 data: 0.0019 max mem: 19788 +Test: [ 8300/21770] eta: 0:15:14 time: 0.0665 data: 0.0020 max mem: 19788 +Test: [ 8400/21770] eta: 0:15:07 time: 0.0758 data: 0.0021 max mem: 19788 +Test: [ 8500/21770] eta: 0:15:00 time: 0.0620 data: 0.0019 max mem: 19788 +Test: [ 8600/21770] eta: 0:14:53 time: 0.0623 data: 0.0017 max mem: 19788 +Test: [ 8700/21770] eta: 0:14:45 time: 0.0715 data: 0.0020 max mem: 19788 +Test: [ 8800/21770] eta: 0:14:40 time: 0.0807 data: 0.0025 max mem: 19788 +Test: [ 8900/21770] eta: 0:14:34 time: 0.0633 data: 0.0019 max mem: 19788 +Test: [ 9000/21770] eta: 0:14:27 time: 0.0710 data: 0.0020 max mem: 19788 +Test: [ 9100/21770] eta: 0:14:20 time: 0.0636 data: 0.0019 max mem: 19788 +Test: [ 9200/21770] eta: 0:14:13 time: 0.0707 data: 0.0021 max mem: 19788 +Test: [ 9300/21770] eta: 0:14:05 time: 0.0684 data: 0.0021 max mem: 19788 +Test: [ 9400/21770] eta: 0:13:59 time: 0.0781 data: 0.0023 max mem: 19788 +Test: [ 9500/21770] eta: 0:13:53 time: 0.0692 data: 0.0021 max mem: 19788 +Test: [ 9600/21770] eta: 0:13:47 time: 0.0620 data: 0.0019 max mem: 19788 +Test: [ 9700/21770] eta: 0:13:41 time: 0.0719 data: 0.0022 max mem: 19788 +Test: [ 9800/21770] eta: 0:13:34 time: 0.0628 data: 0.0019 max mem: 19788 +Test: [ 9900/21770] eta: 0:13:27 time: 0.0682 data: 0.0021 max mem: 19788 +Test: [10000/21770] eta: 0:13:20 time: 0.0639 data: 0.0020 max mem: 19788 +Test: [10100/21770] eta: 0:13:13 time: 0.0720 data: 0.0019 max mem: 19788 +Test: [10200/21770] eta: 0:13:06 time: 0.0752 data: 0.0022 max mem: 19788 +Test: [10300/21770] eta: 0:13:00 time: 0.0761 data: 0.0025 max mem: 19788 +Test: [10400/21770] eta: 0:12:54 time: 0.0669 data: 0.0019 max mem: 19788 +Test: [10500/21770] eta: 0:12:47 time: 0.0650 data: 0.0019 max mem: 19788 +Test: [10600/21770] eta: 0:12:40 time: 0.0822 data: 0.0024 max mem: 19788 +Test: [10700/21770] eta: 0:12:34 time: 0.0693 data: 0.0019 max mem: 19788 +Test: [10800/21770] eta: 0:12:27 time: 0.0653 data: 0.0019 max mem: 19788 +Test: [10900/21770] eta: 0:12:20 time: 0.0708 data: 0.0018 max mem: 19788 +Test: [11000/21770] eta: 0:12:13 time: 0.0609 data: 0.0018 max mem: 19788 +Test: [11100/21770] eta: 0:12:06 time: 0.0634 data: 0.0018 max mem: 19788 +Test: [11200/21770] eta: 0:11:59 time: 0.0804 data: 0.0023 max mem: 19788 +Test: [11300/21770] eta: 0:11:53 time: 0.0789 data: 0.0022 max mem: 19788 +Test: [11400/21770] eta: 0:11:47 time: 0.0791 data: 0.0020 max mem: 19788 +Test: [11500/21770] eta: 0:11:40 time: 0.0602 data: 0.0017 max mem: 19788 +Test: [11600/21770] eta: 0:11:33 time: 0.0730 data: 0.0021 max mem: 19788 +Test: [11700/21770] eta: 0:11:26 time: 0.0724 data: 0.0020 max mem: 19788 +Test: [11800/21770] eta: 0:11:19 time: 0.0650 data: 0.0018 max mem: 19788 +Test: [11900/21770] eta: 0:11:13 time: 0.0818 data: 0.0019 max mem: 19788 +Test: [12000/21770] eta: 0:11:06 time: 0.0634 data: 0.0018 max mem: 19788 +Test: [12100/21770] eta: 0:11:00 time: 0.0792 data: 0.0018 max mem: 19788 +Test: [12200/21770] eta: 0:10:54 time: 0.0805 data: 0.0023 max mem: 19788 +Test: [12300/21770] eta: 0:10:46 time: 0.0630 data: 0.0017 max mem: 19788 +Test: [12400/21770] eta: 0:10:39 time: 0.0667 data: 0.0019 max mem: 19788 +Test: [12500/21770] eta: 0:10:33 time: 0.0807 data: 0.0025 max mem: 19788 +Test: [12600/21770] eta: 0:10:26 time: 0.0687 data: 0.0021 max mem: 19788 +Test: [12700/21770] eta: 0:10:20 time: 0.0669 data: 0.0018 max mem: 19788 +Test: [12800/21770] eta: 0:10:13 time: 0.0605 data: 0.0018 max mem: 19788 +Test: [12900/21770] eta: 0:10:06 time: 0.0714 data: 0.0018 max mem: 19788 +Test: [13000/21770] eta: 0:09:59 time: 0.0624 data: 0.0017 max mem: 19788 +Test: [13100/21770] eta: 0:09:52 time: 0.0627 data: 0.0020 max mem: 19788 +Test: [13200/21770] eta: 0:09:46 time: 0.0761 data: 0.0021 max mem: 19788 +Test: [13300/21770] eta: 0:09:39 time: 0.0664 data: 0.0019 max mem: 19788 +Test: [13400/21770] eta: 0:09:31 time: 0.0653 data: 0.0019 max mem: 19788 +Test: [13500/21770] eta: 0:09:25 time: 0.0685 data: 0.0022 max mem: 19788 +Test: [13600/21770] eta: 0:09:18 time: 0.0612 data: 0.0017 max mem: 19788 +Test: [13700/21770] eta: 0:09:11 time: 0.0638 data: 0.0019 max mem: 19788 +Test: [13800/21770] eta: 0:09:04 time: 0.0641 data: 0.0017 max mem: 19788 +Test: [13900/21770] eta: 0:08:57 time: 0.0618 data: 0.0017 max mem: 19788 +Test: [14000/21770] eta: 0:08:50 time: 0.0642 data: 0.0019 max mem: 19788 +Test: [14100/21770] eta: 0:08:43 time: 0.0802 data: 0.0022 max mem: 19788 +Test: [14200/21770] eta: 0:08:36 time: 0.0677 data: 0.0022 max mem: 19788 +Test: [14300/21770] eta: 0:08:29 time: 0.0635 data: 0.0019 max mem: 19788 +Test: [14400/21770] eta: 0:08:23 time: 0.0768 data: 0.0022 max mem: 19788 +Test: [14500/21770] eta: 0:08:16 time: 0.0638 data: 0.0019 max mem: 19788 +Test: [14600/21770] eta: 0:08:09 time: 0.0727 data: 0.0021 max mem: 19788 +Test: [14700/21770] eta: 0:08:02 time: 0.0653 data: 0.0018 max mem: 19788 +Test: [14800/21770] eta: 0:07:55 time: 0.0646 data: 0.0018 max mem: 19788 +Test: [14900/21770] eta: 0:07:48 time: 0.0661 data: 0.0020 max mem: 19788 +Test: [15000/21770] eta: 0:07:41 time: 0.0819 data: 0.0023 max mem: 19788 +Test: [15100/21770] eta: 0:07:34 time: 0.0667 data: 0.0020 max mem: 19788 +Test: [15200/21770] eta: 0:07:27 time: 0.0650 data: 0.0019 max mem: 19788 +Test: [15300/21770] eta: 0:07:20 time: 0.0612 data: 0.0017 max mem: 19788 +Test: [15400/21770] eta: 0:07:14 time: 0.0731 data: 0.0021 max mem: 19788 +Test: [15500/21770] eta: 0:07:07 time: 0.0673 data: 0.0020 max mem: 19788 +Test: [15600/21770] eta: 0:07:00 time: 0.0663 data: 0.0018 max mem: 19788 +Test: [15700/21770] eta: 0:06:53 time: 0.0639 data: 0.0018 max mem: 19788 +Test: [15800/21770] eta: 0:06:46 time: 0.0815 data: 0.0025 max mem: 19788 +Test: [15900/21770] eta: 0:06:40 time: 0.0806 data: 0.0024 max mem: 19788 +Test: [16000/21770] eta: 0:06:33 time: 0.0701 data: 0.0019 max mem: 19788 +Test: [16100/21770] eta: 0:06:26 time: 0.0696 data: 0.0019 max mem: 19788 +Test: [16200/21770] eta: 0:06:20 time: 0.0817 data: 0.0025 max mem: 19788 +Test: [16300/21770] eta: 0:06:13 time: 0.0698 data: 0.0020 max mem: 19788 +Test: [16400/21770] eta: 0:06:06 time: 0.0627 data: 0.0018 max mem: 19788 +Test: [16500/21770] eta: 0:05:59 time: 0.0697 data: 0.0021 max mem: 19788 +Test: [16600/21770] eta: 0:05:52 time: 0.0692 data: 0.0022 max mem: 19788 +Test: [16700/21770] eta: 0:05:46 time: 0.0614 data: 0.0016 max mem: 19788 +Test: [16800/21770] eta: 0:05:39 time: 0.0660 data: 0.0019 max mem: 19788 +Test: [16900/21770] eta: 0:05:32 time: 0.0688 data: 0.0017 max mem: 19788 +Test: [17000/21770] eta: 0:05:25 time: 0.0738 data: 0.0021 max mem: 19788 +Test: [17100/21770] eta: 0:05:18 time: 0.0642 data: 0.0018 max mem: 19788 +Test: [17200/21770] eta: 0:05:11 time: 0.0699 data: 0.0021 max mem: 19788 +Test: [17300/21770] eta: 0:05:05 time: 0.0639 data: 0.0018 max mem: 19788 +Test: [17400/21770] eta: 0:04:58 time: 0.0627 data: 0.0020 max mem: 19788 +Test: [17500/21770] eta: 0:04:51 time: 0.0668 data: 0.0022 max mem: 19788 +Test: [17600/21770] eta: 0:04:44 time: 0.0624 data: 0.0018 max mem: 19788 +Test: [17700/21770] eta: 0:04:37 time: 0.0719 data: 0.0019 max mem: 19788 +Test: [17800/21770] eta: 0:04:30 time: 0.0757 data: 0.0020 max mem: 19788 +Test: [17900/21770] eta: 0:04:23 time: 0.0704 data: 0.0022 max mem: 19788 +Test: [18000/21770] eta: 0:04:16 time: 0.0647 data: 0.0020 max mem: 19788 +Test: [18100/21770] eta: 0:04:10 time: 0.0647 data: 0.0020 max mem: 19788 +Test: [18200/21770] eta: 0:04:03 time: 0.0811 data: 0.0023 max mem: 19788 +Test: [18300/21770] eta: 0:03:56 time: 0.0803 data: 0.0025 max mem: 19788 +Test: [18400/21770] eta: 0:03:49 time: 0.0628 data: 0.0018 max mem: 19788 +Test: [18500/21770] eta: 0:03:42 time: 0.0755 data: 0.0020 max mem: 19788 +Test: [18600/21770] eta: 0:03:35 time: 0.0635 data: 0.0020 max mem: 19788 +Test: [18700/21770] eta: 0:03:29 time: 0.0648 data: 0.0019 max mem: 19788 +Test: [18800/21770] eta: 0:03:22 time: 0.0677 data: 0.0018 max mem: 19788 +Test: [18900/21770] eta: 0:03:15 time: 0.0690 data: 0.0019 max mem: 19788 +Test: [19000/21770] eta: 0:03:08 time: 0.0657 data: 0.0019 max mem: 19788 +Test: [19100/21770] eta: 0:03:01 time: 0.0638 data: 0.0020 max mem: 19788 +Test: [19200/21770] eta: 0:02:54 time: 0.0729 data: 0.0019 max mem: 19788 +Test: [19300/21770] eta: 0:02:48 time: 0.0690 data: 0.0021 max mem: 19788 +Test: [19400/21770] eta: 0:02:41 time: 0.0607 data: 0.0017 max mem: 19788 +Test: [19500/21770] eta: 0:02:34 time: 0.0679 data: 0.0020 max mem: 19788 +Test: [19600/21770] eta: 0:02:27 time: 0.0625 data: 0.0018 max mem: 19788 +Test: [19700/21770] eta: 0:02:20 time: 0.0622 data: 0.0020 max mem: 19788 +Test: [19800/21770] eta: 0:02:13 time: 0.0789 data: 0.0025 max mem: 19788 +Test: [19900/21770] eta: 0:02:07 time: 0.0665 data: 0.0021 max mem: 19788 +Test: [20000/21770] eta: 0:02:00 time: 0.0628 data: 0.0018 max mem: 19788 +Test: [20100/21770] eta: 0:01:53 time: 0.0636 data: 0.0018 max mem: 19788 +Test: [20200/21770] eta: 0:01:46 time: 0.0767 data: 0.0018 max mem: 19788 +Test: [20300/21770] eta: 0:01:39 time: 0.0619 data: 0.0018 max mem: 19788 +Test: [20400/21770] eta: 0:01:33 time: 0.0749 data: 0.0021 max mem: 19788 +Test: [20500/21770] eta: 0:01:26 time: 0.0723 data: 0.0018 max mem: 19788 +Test: [20600/21770] eta: 0:01:19 time: 0.0643 data: 0.0019 max mem: 19788 +Test: [20700/21770] eta: 0:01:12 time: 0.0732 data: 0.0022 max mem: 19788 +Test: [20800/21770] eta: 0:01:05 time: 0.0600 data: 0.0018 max mem: 19788 +Test: [20900/21770] eta: 0:00:59 time: 0.0608 data: 0.0018 max mem: 19788 +Test: [21000/21770] eta: 0:00:52 time: 0.0696 data: 0.0021 max mem: 19788 +Test: [21100/21770] eta: 0:00:45 time: 0.0644 data: 0.0017 max mem: 19788 +Test: [21200/21770] eta: 0:00:38 time: 0.0618 data: 0.0016 max mem: 19788 +Test: [21300/21770] eta: 0:00:31 time: 0.0648 data: 0.0022 max mem: 19788 +Test: [21400/21770] eta: 0:00:25 time: 0.0707 data: 0.0022 max mem: 19788 +Test: [21500/21770] eta: 0:00:18 time: 0.0741 data: 0.0020 max mem: 19788 +Test: [21600/21770] eta: 0:00:11 time: 0.0648 data: 0.0020 max mem: 19788 +Test: [21700/21770] eta: 0:00:04 time: 0.0577 data: 0.0017 max mem: 19788 +Test: Total time: 0:24:40 +Final results: +Mean IoU is 63.08 + + precision@0.5 = 69.81 + precision@0.6 = 64.52 + precision@0.7 = 57.56 + precision@0.8 = 47.25 + precision@0.9 = 23.65 + overall IoU = 63.58 + mean IoU = 63.08 + +Mean accuracy for one-to-zero sample is 83.93 + +Average object IoU 0.630774870092101 +Overall IoU 63.57782745361328 +Epoch: [23] [ 0/2138] eta: 10:34:09 lr: 2.3147776861632803e-05 loss: 0.0254 (0.0254) time: 17.7968 data: 1.8542 max mem: 19788 +Epoch: [23] [ 10/2138] eta: 2:54:25 lr: 2.314204477033964e-05 loss: 0.0228 (0.0233) time: 4.9182 data: 0.1703 max mem: 19788 +Epoch: [23] [ 20/2138] eta: 2:31:56 lr: 2.3136312521287552e-05 loss: 0.0228 (0.0231) time: 3.6297 data: 0.0020 max mem: 19788 +Epoch: [23] [ 30/2138] eta: 2:23:36 lr: 2.3130580114428785e-05 loss: 0.0235 (0.0234) time: 3.6310 data: 0.0027 max mem: 19788 +Epoch: [23] [ 40/2138] eta: 2:18:59 lr: 2.3124847549715517e-05 loss: 0.0252 (0.0245) time: 3.6295 data: 0.0031 max mem: 19788 +Epoch: [23] [ 50/2138] eta: 2:15:53 lr: 2.3119114827099936e-05 loss: 0.0252 (0.0251) time: 3.6212 data: 0.0034 max mem: 19788 +Epoch: [23] [ 60/2138] eta: 2:13:37 lr: 2.311338194653417e-05 loss: 0.0229 (0.0252) time: 3.6191 data: 0.0034 max mem: 19788 +Epoch: [23] [ 70/2138] eta: 2:11:48 lr: 2.3107648907970354e-05 loss: 0.0221 (0.0248) time: 3.6189 data: 0.0030 max mem: 19788 +Epoch: [23] [ 80/2138] eta: 2:10:17 lr: 2.3101915711360557e-05 loss: 0.0251 (0.0251) time: 3.6160 data: 0.0029 max mem: 19788 +Epoch: [23] [ 90/2138] eta: 2:08:57 lr: 2.309618235665685e-05 loss: 0.0252 (0.0250) time: 3.6143 data: 0.0029 max mem: 19788 +Epoch: [23] [ 100/2138] eta: 2:07:47 lr: 2.309044884381126e-05 loss: 0.0244 (0.0253) time: 3.6151 data: 0.0028 max mem: 19788 +Epoch: [23] [ 110/2138] eta: 2:06:43 lr: 2.30847151727758e-05 loss: 0.0252 (0.0258) time: 3.6167 data: 0.0030 max mem: 19788 +Epoch: [23] [ 120/2138] eta: 2:05:43 lr: 2.3078981343502436e-05 loss: 0.0272 (0.0260) time: 3.6162 data: 0.0031 max mem: 19788 +Epoch: [23] [ 130/2138] eta: 2:04:50 lr: 2.3073247355943133e-05 loss: 0.0272 (0.0261) time: 3.6262 data: 0.0029 max mem: 19788 +Epoch: [23] [ 140/2138] eta: 2:03:59 lr: 2.3067513210049793e-05 loss: 0.0298 (0.0261) time: 3.6356 data: 0.0029 max mem: 19788 +Epoch: [23] [ 150/2138] eta: 2:03:12 lr: 2.3061778905774326e-05 loss: 0.0257 (0.0264) time: 3.6417 data: 0.0030 max mem: 19788 +Epoch: [23] [ 160/2138] eta: 2:02:37 lr: 2.305604444306859e-05 loss: 0.0263 (0.0265) time: 3.6924 data: 0.0031 max mem: 19788 +Epoch: [23] [ 170/2138] eta: 2:01:48 lr: 2.3050309821884417e-05 loss: 0.0264 (0.0267) time: 3.6784 data: 0.0033 max mem: 19788 +Epoch: [23] [ 180/2138] eta: 2:01:02 lr: 2.3044575042173626e-05 loss: 0.0277 (0.0270) time: 3.6226 data: 0.0031 max mem: 19788 +Epoch: [23] [ 190/2138] eta: 2:00:18 lr: 2.3038840103887994e-05 loss: 0.0278 (0.0269) time: 3.6331 data: 0.0028 max mem: 19788 +Epoch: [23] [ 200/2138] eta: 1:59:32 lr: 2.303310500697928e-05 loss: 0.0203 (0.0265) time: 3.6278 data: 0.0032 max mem: 19788 +Epoch: [23] [ 210/2138] eta: 1:58:48 lr: 2.30273697513992e-05 loss: 0.0274 (0.0269) time: 3.6178 data: 0.0033 max mem: 19788 +Epoch: [23] [ 220/2138] eta: 1:58:09 lr: 2.3021634337099465e-05 loss: 0.0288 (0.0267) time: 3.6475 data: 0.0029 max mem: 19788 +Epoch: [23] [ 230/2138] eta: 1:57:27 lr: 2.301589876403173e-05 loss: 0.0252 (0.0270) time: 3.6551 data: 0.0029 max mem: 19788 +Epoch: [23] [ 240/2138] eta: 1:56:43 lr: 2.3010163032147646e-05 loss: 0.0260 (0.0270) time: 3.6250 data: 0.0028 max mem: 19788 +Epoch: [23] [ 250/2138] eta: 1:56:01 lr: 2.300442714139882e-05 loss: 0.0251 (0.0269) time: 3.6131 data: 0.0027 max mem: 19788 +Epoch: [23] [ 260/2138] eta: 1:55:19 lr: 2.2998691091736846e-05 loss: 0.0237 (0.0269) time: 3.6144 data: 0.0028 max mem: 19788 +Epoch: [23] [ 270/2138] eta: 1:54:38 lr: 2.299295488311327e-05 loss: 0.0237 (0.0269) time: 3.6185 data: 0.0030 max mem: 19788 +Epoch: [23] [ 280/2138] eta: 1:53:57 lr: 2.2987218515479632e-05 loss: 0.0263 (0.0268) time: 3.6232 data: 0.0031 max mem: 19788 +Epoch: [23] [ 290/2138] eta: 1:53:16 lr: 2.298148198878742e-05 loss: 0.0263 (0.0269) time: 3.6225 data: 0.0030 max mem: 19788 +Epoch: [23] [ 300/2138] eta: 1:52:36 lr: 2.2975745302988114e-05 loss: 0.0237 (0.0268) time: 3.6181 data: 0.0033 max mem: 19788 +Epoch: [23] [ 310/2138] eta: 1:51:56 lr: 2.2970008458033155e-05 loss: 0.0236 (0.0268) time: 3.6219 data: 0.0033 max mem: 19788 +Epoch: [23] [ 320/2138] eta: 1:51:17 lr: 2.296427145387397e-05 loss: 0.0245 (0.0268) time: 3.6290 data: 0.0029 max mem: 19788 +Epoch: [23] [ 330/2138] eta: 1:50:37 lr: 2.2958534290461923e-05 loss: 0.0248 (0.0269) time: 3.6244 data: 0.0028 max mem: 19788 +Epoch: [23] [ 340/2138] eta: 1:49:58 lr: 2.2952796967748394e-05 loss: 0.0238 (0.0270) time: 3.6253 data: 0.0029 max mem: 19788 +Epoch: [23] [ 350/2138] eta: 1:49:19 lr: 2.2947059485684705e-05 loss: 0.0248 (0.0270) time: 3.6289 data: 0.0029 max mem: 19788 +Epoch: [23] [ 360/2138] eta: 1:48:41 lr: 2.294132184422216e-05 loss: 0.0247 (0.0270) time: 3.6246 data: 0.0030 max mem: 19788 +Epoch: [23] [ 370/2138] eta: 1:48:02 lr: 2.293558404331203e-05 loss: 0.0247 (0.0272) time: 3.6241 data: 0.0030 max mem: 19788 +Epoch: [23] [ 380/2138] eta: 1:47:23 lr: 2.2929846082905567e-05 loss: 0.0304 (0.0272) time: 3.6270 data: 0.0029 max mem: 19788 +Epoch: [23] [ 390/2138] eta: 1:46:45 lr: 2.2924107962953982e-05 loss: 0.0270 (0.0272) time: 3.6325 data: 0.0028 max mem: 19788 +Epoch: [23] [ 400/2138] eta: 1:46:07 lr: 2.2918369683408465e-05 loss: 0.0270 (0.0273) time: 3.6302 data: 0.0028 max mem: 19788 +Epoch: [23] [ 410/2138] eta: 1:45:29 lr: 2.2912631244220174e-05 loss: 0.0296 (0.0274) time: 3.6257 data: 0.0028 max mem: 19788 +Epoch: [23] [ 420/2138] eta: 1:44:51 lr: 2.2906892645340244e-05 loss: 0.0318 (0.0274) time: 3.6246 data: 0.0027 max mem: 19788 +Epoch: [23] [ 430/2138] eta: 1:44:12 lr: 2.2901153886719773e-05 loss: 0.0249 (0.0274) time: 3.6179 data: 0.0029 max mem: 19788 +Epoch: [23] [ 440/2138] eta: 1:43:34 lr: 2.2895414968309843e-05 loss: 0.0274 (0.0276) time: 3.6167 data: 0.0031 max mem: 19788 +Epoch: [23] [ 450/2138] eta: 1:42:56 lr: 2.288967589006149e-05 loss: 0.0245 (0.0276) time: 3.6210 data: 0.0031 max mem: 19788 +Epoch: [23] [ 460/2138] eta: 1:42:18 lr: 2.2883936651925743e-05 loss: 0.0263 (0.0276) time: 3.6248 data: 0.0029 max mem: 19788 +Epoch: [23] [ 470/2138] eta: 1:41:40 lr: 2.2878197253853578e-05 loss: 0.0276 (0.0276) time: 3.6246 data: 0.0029 max mem: 19788 +Epoch: [23] [ 480/2138] eta: 1:41:03 lr: 2.2872457695795957e-05 loss: 0.0297 (0.0276) time: 3.6228 data: 0.0029 max mem: 19788 +Epoch: [23] [ 490/2138] eta: 1:40:25 lr: 2.2866717977703818e-05 loss: 0.0262 (0.0276) time: 3.6221 data: 0.0028 max mem: 19788 +Epoch: [23] [ 500/2138] eta: 1:39:47 lr: 2.2860978099528055e-05 loss: 0.0262 (0.0275) time: 3.6204 data: 0.0032 max mem: 19788 +Epoch: [23] [ 510/2138] eta: 1:39:10 lr: 2.285523806121955e-05 loss: 0.0267 (0.0275) time: 3.6274 data: 0.0033 max mem: 19788 +Epoch: [23] [ 520/2138] eta: 1:38:32 lr: 2.2849497862729132e-05 loss: 0.0275 (0.0275) time: 3.6278 data: 0.0032 max mem: 19788 +Epoch: [23] [ 530/2138] eta: 1:37:55 lr: 2.284375750400764e-05 loss: 0.0256 (0.0277) time: 3.6215 data: 0.0030 max mem: 19788 +Epoch: [23] [ 540/2138] eta: 1:37:17 lr: 2.283801698500584e-05 loss: 0.0243 (0.0277) time: 3.6188 data: 0.0030 max mem: 19788 +Epoch: [23] [ 550/2138] eta: 1:36:39 lr: 2.28322763056745e-05 loss: 0.0275 (0.0277) time: 3.6176 data: 0.0030 max mem: 19788 +Epoch: [23] [ 560/2138] eta: 1:36:03 lr: 2.2826535465964345e-05 loss: 0.0267 (0.0277) time: 3.6374 data: 0.0029 max mem: 19788 +Epoch: [23] [ 570/2138] eta: 1:35:28 lr: 2.2820794465826085e-05 loss: 0.0234 (0.0277) time: 3.6765 data: 0.0031 max mem: 19788 +Epoch: [23] [ 580/2138] eta: 1:34:51 lr: 2.2815053305210378e-05 loss: 0.0243 (0.0276) time: 3.6771 data: 0.0034 max mem: 19788 +Epoch: [23] [ 590/2138] eta: 1:34:17 lr: 2.2809311984067874e-05 loss: 0.0253 (0.0276) time: 3.6957 data: 0.0033 max mem: 19788 +Epoch: [23] [ 600/2138] eta: 1:33:43 lr: 2.280357050234918e-05 loss: 0.0246 (0.0276) time: 3.7370 data: 0.0031 max mem: 19788 +Epoch: [23] [ 610/2138] eta: 1:33:09 lr: 2.2797828860004895e-05 loss: 0.0246 (0.0276) time: 3.7510 data: 0.0030 max mem: 19788 +Epoch: [23] [ 620/2138] eta: 1:32:33 lr: 2.2792087056985554e-05 loss: 0.0265 (0.0276) time: 3.7268 data: 0.0030 max mem: 19788 +Epoch: [23] [ 630/2138] eta: 1:31:55 lr: 2.27863450932417e-05 loss: 0.0234 (0.0276) time: 3.6569 data: 0.0030 max mem: 19788 +Epoch: [23] [ 640/2138] eta: 1:31:18 lr: 2.2780602968723818e-05 loss: 0.0230 (0.0275) time: 3.6211 data: 0.0028 max mem: 19788 +Epoch: [23] [ 650/2138] eta: 1:30:41 lr: 2.277486068338239e-05 loss: 0.0231 (0.0275) time: 3.6200 data: 0.0031 max mem: 19788 +Epoch: [23] [ 660/2138] eta: 1:30:03 lr: 2.2769118237167837e-05 loss: 0.0245 (0.0275) time: 3.6269 data: 0.0031 max mem: 19788 +Epoch: [23] [ 670/2138] eta: 1:29:26 lr: 2.2763375630030585e-05 loss: 0.0269 (0.0276) time: 3.6269 data: 0.0029 max mem: 19788 +Epoch: [23] [ 680/2138] eta: 1:28:49 lr: 2.2757632861921006e-05 loss: 0.0265 (0.0276) time: 3.6209 data: 0.0029 max mem: 19788 +Epoch: [23] [ 690/2138] eta: 1:28:12 lr: 2.275188993278945e-05 loss: 0.0278 (0.0276) time: 3.6217 data: 0.0028 max mem: 19788 +Epoch: [23] [ 700/2138] eta: 1:27:34 lr: 2.2746146842586246e-05 loss: 0.0274 (0.0276) time: 3.6206 data: 0.0028 max mem: 19788 +Epoch: [23] [ 710/2138] eta: 1:26:57 lr: 2.2740403591261684e-05 loss: 0.0274 (0.0276) time: 3.6258 data: 0.0028 max mem: 19788 +Epoch: [23] [ 720/2138] eta: 1:26:20 lr: 2.273466017876602e-05 loss: 0.0222 (0.0276) time: 3.6289 data: 0.0030 max mem: 19788 +Epoch: [23] [ 730/2138] eta: 1:25:43 lr: 2.27289166050495e-05 loss: 0.0230 (0.0276) time: 3.6251 data: 0.0030 max mem: 19788 +Epoch: [23] [ 740/2138] eta: 1:25:06 lr: 2.2723172870062323e-05 loss: 0.0241 (0.0276) time: 3.6218 data: 0.0029 max mem: 19788 +Epoch: [23] [ 750/2138] eta: 1:24:29 lr: 2.2717428973754667e-05 loss: 0.0238 (0.0276) time: 3.6185 data: 0.0029 max mem: 19788 +Epoch: [23] [ 760/2138] eta: 1:23:52 lr: 2.271168491607667e-05 loss: 0.0282 (0.0276) time: 3.6174 data: 0.0028 max mem: 19788 +Epoch: [23] [ 770/2138] eta: 1:23:15 lr: 2.270594069697846e-05 loss: 0.0282 (0.0276) time: 3.6173 data: 0.0030 max mem: 19788 +Epoch: [23] [ 780/2138] eta: 1:22:38 lr: 2.2700196316410122e-05 loss: 0.0272 (0.0276) time: 3.6207 data: 0.0032 max mem: 19788 +Epoch: [23] [ 790/2138] eta: 1:22:01 lr: 2.2694451774321705e-05 loss: 0.0267 (0.0276) time: 3.6304 data: 0.0030 max mem: 19788 +Epoch: [23] [ 800/2138] eta: 1:21:24 lr: 2.2688707070663247e-05 loss: 0.0263 (0.0276) time: 3.6279 data: 0.0028 max mem: 19788 +Epoch: [23] [ 810/2138] eta: 1:20:47 lr: 2.2682962205384733e-05 loss: 0.0254 (0.0276) time: 3.6183 data: 0.0029 max mem: 19788 +Epoch: [23] [ 820/2138] eta: 1:20:10 lr: 2.2677217178436154e-05 loss: 0.0252 (0.0275) time: 3.6183 data: 0.0029 max mem: 19788 +Epoch: [23] [ 830/2138] eta: 1:19:33 lr: 2.267147198976743e-05 loss: 0.0229 (0.0275) time: 3.6177 data: 0.0029 max mem: 19788 +Epoch: [23] [ 840/2138] eta: 1:18:56 lr: 2.266572663932848e-05 loss: 0.0219 (0.0274) time: 3.6200 data: 0.0030 max mem: 19788 +Epoch: [23] [ 850/2138] eta: 1:18:19 lr: 2.265998112706918e-05 loss: 0.0220 (0.0274) time: 3.6196 data: 0.0028 max mem: 19788 +Epoch: [23] [ 860/2138] eta: 1:17:42 lr: 2.265423545293939e-05 loss: 0.0258 (0.0274) time: 3.6197 data: 0.0026 max mem: 19788 +Epoch: [23] [ 870/2138] eta: 1:17:05 lr: 2.2648489616888917e-05 loss: 0.0268 (0.0274) time: 3.6212 data: 0.0028 max mem: 19788 +Epoch: [23] [ 880/2138] eta: 1:16:28 lr: 2.2642743618867567e-05 loss: 0.0262 (0.0274) time: 3.6183 data: 0.0028 max mem: 19788 +Epoch: [23] [ 890/2138] eta: 1:15:51 lr: 2.2636997458825088e-05 loss: 0.0262 (0.0274) time: 3.6181 data: 0.0027 max mem: 19788 +Epoch: [23] [ 900/2138] eta: 1:15:14 lr: 2.2631251136711227e-05 loss: 0.0279 (0.0274) time: 3.6179 data: 0.0028 max mem: 19788 +Epoch: [23] [ 910/2138] eta: 1:14:37 lr: 2.262550465247567e-05 loss: 0.0261 (0.0274) time: 3.6160 data: 0.0029 max mem: 19788 +Epoch: [23] [ 920/2138] eta: 1:14:01 lr: 2.2619758006068098e-05 loss: 0.0230 (0.0274) time: 3.6158 data: 0.0029 max mem: 19788 +Epoch: [23] [ 930/2138] eta: 1:13:24 lr: 2.261401119743815e-05 loss: 0.0241 (0.0274) time: 3.6189 data: 0.0029 max mem: 19788 +Epoch: [23] [ 940/2138] eta: 1:12:47 lr: 2.2608264226535445e-05 loss: 0.0261 (0.0275) time: 3.6182 data: 0.0031 max mem: 19788 +Epoch: [23] [ 950/2138] eta: 1:12:10 lr: 2.260251709330956e-05 loss: 0.0247 (0.0274) time: 3.6301 data: 0.0033 max mem: 19788 +Epoch: [23] [ 960/2138] eta: 1:11:34 lr: 2.2596769797710048e-05 loss: 0.0247 (0.0274) time: 3.6320 data: 0.0030 max mem: 19788 +Epoch: [23] [ 970/2138] eta: 1:10:57 lr: 2.259102233968643e-05 loss: 0.0242 (0.0274) time: 3.6164 data: 0.0030 max mem: 19788 +Epoch: [23] [ 980/2138] eta: 1:10:20 lr: 2.2585274719188206e-05 loss: 0.0221 (0.0274) time: 3.6154 data: 0.0029 max mem: 19788 +Epoch: [23] [ 990/2138] eta: 1:09:43 lr: 2.2579526936164832e-05 loss: 0.0258 (0.0274) time: 3.6173 data: 0.0030 max mem: 19788 +Epoch: [23] [1000/2138] eta: 1:09:07 lr: 2.2573778990565747e-05 loss: 0.0275 (0.0274) time: 3.6179 data: 0.0031 max mem: 19788 +Epoch: [23] [1010/2138] eta: 1:08:30 lr: 2.2568030882340347e-05 loss: 0.0253 (0.0273) time: 3.6164 data: 0.0029 max mem: 19788 +Epoch: [23] [1020/2138] eta: 1:07:53 lr: 2.256228261143801e-05 loss: 0.0238 (0.0273) time: 3.6137 data: 0.0029 max mem: 19788 +Epoch: [23] [1030/2138] eta: 1:07:16 lr: 2.2556534177808072e-05 loss: 0.0258 (0.0273) time: 3.6155 data: 0.0029 max mem: 19788 +Epoch: [23] [1040/2138] eta: 1:06:40 lr: 2.2550785581399854e-05 loss: 0.0245 (0.0273) time: 3.6363 data: 0.0031 max mem: 19788 +Epoch: [23] [1050/2138] eta: 1:06:04 lr: 2.2545036822162634e-05 loss: 0.0266 (0.0273) time: 3.6633 data: 0.0035 max mem: 19788 +Epoch: [23] [1060/2138] eta: 1:05:28 lr: 2.2539287900045664e-05 loss: 0.0268 (0.0273) time: 3.7030 data: 0.0034 max mem: 19788 +Epoch: [23] [1070/2138] eta: 1:04:52 lr: 2.253353881499817e-05 loss: 0.0252 (0.0273) time: 3.6783 data: 0.0029 max mem: 19788 +Epoch: [23] [1080/2138] eta: 1:04:15 lr: 2.2527789566969335e-05 loss: 0.0252 (0.0273) time: 3.6282 data: 0.0028 max mem: 19788 +Epoch: [23] [1090/2138] eta: 1:03:39 lr: 2.2522040155908328e-05 loss: 0.0265 (0.0273) time: 3.6543 data: 0.0029 max mem: 19788 +Epoch: [23] [1100/2138] eta: 1:03:03 lr: 2.2516290581764277e-05 loss: 0.0275 (0.0273) time: 3.6680 data: 0.0029 max mem: 19788 +Epoch: [23] [1110/2138] eta: 1:02:26 lr: 2.2510540844486285e-05 loss: 0.0264 (0.0273) time: 3.6364 data: 0.0032 max mem: 19788 +Epoch: [23] [1120/2138] eta: 1:01:50 lr: 2.2504790944023418e-05 loss: 0.0259 (0.0274) time: 3.6407 data: 0.0032 max mem: 19788 +Epoch: [23] [1130/2138] eta: 1:01:13 lr: 2.2499040880324725e-05 loss: 0.0262 (0.0273) time: 3.6559 data: 0.0030 max mem: 19788 +Epoch: [23] [1140/2138] eta: 1:00:37 lr: 2.2493290653339206e-05 loss: 0.0258 (0.0274) time: 3.6447 data: 0.0028 max mem: 19788 +Epoch: [23] [1150/2138] eta: 1:00:01 lr: 2.248754026301585e-05 loss: 0.0233 (0.0273) time: 3.6535 data: 0.0028 max mem: 19788 +Epoch: [23] [1160/2138] eta: 0:59:24 lr: 2.2481789709303593e-05 loss: 0.0229 (0.0273) time: 3.6368 data: 0.0028 max mem: 19788 +Epoch: [23] [1170/2138] eta: 0:58:47 lr: 2.247603899215137e-05 loss: 0.0252 (0.0273) time: 3.6161 data: 0.0029 max mem: 19788 +Epoch: [23] [1180/2138] eta: 0:58:11 lr: 2.247028811150805e-05 loss: 0.0252 (0.0273) time: 3.6482 data: 0.0032 max mem: 19788 +Epoch: [23] [1190/2138] eta: 0:57:34 lr: 2.2464537067322507e-05 loss: 0.0250 (0.0273) time: 3.6570 data: 0.0030 max mem: 19788 +Epoch: [23] [1200/2138] eta: 0:56:58 lr: 2.245878585954356e-05 loss: 0.0225 (0.0273) time: 3.6284 data: 0.0028 max mem: 19788 +Epoch: [23] [1210/2138] eta: 0:56:21 lr: 2.245303448812001e-05 loss: 0.0262 (0.0273) time: 3.6189 data: 0.0028 max mem: 19788 +Epoch: [23] [1220/2138] eta: 0:55:45 lr: 2.2447282953000613e-05 loss: 0.0262 (0.0273) time: 3.6223 data: 0.0029 max mem: 19788 +Epoch: [23] [1230/2138] eta: 0:55:08 lr: 2.244153125413412e-05 loss: 0.0262 (0.0274) time: 3.6236 data: 0.0031 max mem: 19788 +Epoch: [23] [1240/2138] eta: 0:54:31 lr: 2.2435779391469218e-05 loss: 0.0279 (0.0274) time: 3.6175 data: 0.0030 max mem: 19788 +Epoch: [23] [1250/2138] eta: 0:53:55 lr: 2.2430027364954595e-05 loss: 0.0261 (0.0274) time: 3.6159 data: 0.0026 max mem: 19788 +Epoch: [23] [1260/2138] eta: 0:53:18 lr: 2.242427517453888e-05 loss: 0.0239 (0.0274) time: 3.6168 data: 0.0028 max mem: 19788 +Epoch: [23] [1270/2138] eta: 0:52:42 lr: 2.2418522820170702e-05 loss: 0.0223 (0.0273) time: 3.6192 data: 0.0028 max mem: 19788 +Epoch: [23] [1280/2138] eta: 0:52:05 lr: 2.2412770301798626e-05 loss: 0.0234 (0.0273) time: 3.6154 data: 0.0027 max mem: 19788 +Epoch: [23] [1290/2138] eta: 0:51:28 lr: 2.2407017619371217e-05 loss: 0.0231 (0.0273) time: 3.6156 data: 0.0028 max mem: 19788 +Epoch: [23] [1300/2138] eta: 0:50:52 lr: 2.2401264772836984e-05 loss: 0.0243 (0.0273) time: 3.6212 data: 0.0031 max mem: 19788 +Epoch: [23] [1310/2138] eta: 0:50:15 lr: 2.2395511762144426e-05 loss: 0.0259 (0.0273) time: 3.6192 data: 0.0031 max mem: 19788 +Epoch: [23] [1320/2138] eta: 0:49:39 lr: 2.2389758587241985e-05 loss: 0.0261 (0.0273) time: 3.6150 data: 0.0029 max mem: 19788 +Epoch: [23] [1330/2138] eta: 0:49:02 lr: 2.238400524807811e-05 loss: 0.0238 (0.0273) time: 3.6158 data: 0.0028 max mem: 19788 +Epoch: [23] [1340/2138] eta: 0:48:25 lr: 2.2378251744601177e-05 loss: 0.0241 (0.0273) time: 3.6146 data: 0.0029 max mem: 19788 +Epoch: [23] [1350/2138] eta: 0:47:49 lr: 2.2372498076759567e-05 loss: 0.0280 (0.0273) time: 3.6099 data: 0.0028 max mem: 19788 +Epoch: [23] [1360/2138] eta: 0:47:12 lr: 2.2366744244501604e-05 loss: 0.0297 (0.0273) time: 3.6139 data: 0.0027 max mem: 19788 +Epoch: [23] [1370/2138] eta: 0:46:36 lr: 2.23609902477756e-05 loss: 0.0272 (0.0273) time: 3.6168 data: 0.0029 max mem: 19788 +Epoch: [23] [1380/2138] eta: 0:45:59 lr: 2.2355236086529827e-05 loss: 0.0286 (0.0274) time: 3.6176 data: 0.0029 max mem: 19788 +Epoch: [23] [1390/2138] eta: 0:45:23 lr: 2.2349481760712512e-05 loss: 0.0275 (0.0274) time: 3.6286 data: 0.0029 max mem: 19788 +Epoch: [23] [1400/2138] eta: 0:44:46 lr: 2.234372727027188e-05 loss: 0.0266 (0.0274) time: 3.6323 data: 0.0028 max mem: 19788 +Epoch: [23] [1410/2138] eta: 0:44:10 lr: 2.23379726151561e-05 loss: 0.0248 (0.0273) time: 3.6239 data: 0.0028 max mem: 19788 +Epoch: [23] [1420/2138] eta: 0:43:33 lr: 2.2332217795313335e-05 loss: 0.0246 (0.0273) time: 3.6248 data: 0.0027 max mem: 19788 +Epoch: [23] [1430/2138] eta: 0:42:57 lr: 2.2326462810691683e-05 loss: 0.0252 (0.0273) time: 3.6293 data: 0.0027 max mem: 19788 +Epoch: [23] [1440/2138] eta: 0:42:20 lr: 2.2320707661239245e-05 loss: 0.0239 (0.0273) time: 3.6303 data: 0.0028 max mem: 19788 +Epoch: [23] [1450/2138] eta: 0:41:44 lr: 2.2314952346904062e-05 loss: 0.0273 (0.0273) time: 3.6317 data: 0.0030 max mem: 19788 +Epoch: [23] [1460/2138] eta: 0:41:08 lr: 2.2309196867634173e-05 loss: 0.0286 (0.0274) time: 3.6295 data: 0.0028 max mem: 19788 +Epoch: [23] [1470/2138] eta: 0:40:31 lr: 2.2303441223377553e-05 loss: 0.0263 (0.0274) time: 3.6228 data: 0.0027 max mem: 19788 +Epoch: [23] [1480/2138] eta: 0:39:54 lr: 2.2297685414082174e-05 loss: 0.0275 (0.0274) time: 3.6171 data: 0.0027 max mem: 19788 +Epoch: [23] [1490/2138] eta: 0:39:18 lr: 2.2291929439695953e-05 loss: 0.0283 (0.0274) time: 3.6182 data: 0.0031 max mem: 19788 +Epoch: [23] [1500/2138] eta: 0:38:42 lr: 2.2286173300166806e-05 loss: 0.0292 (0.0274) time: 3.6230 data: 0.0031 max mem: 19788 +Epoch: [23] [1510/2138] eta: 0:38:05 lr: 2.2280416995442584e-05 loss: 0.0292 (0.0274) time: 3.6272 data: 0.0028 max mem: 19788 +Epoch: [23] [1520/2138] eta: 0:37:29 lr: 2.2274660525471132e-05 loss: 0.0239 (0.0274) time: 3.6314 data: 0.0029 max mem: 19788 +Epoch: [23] [1530/2138] eta: 0:36:52 lr: 2.2268903890200244e-05 loss: 0.0231 (0.0274) time: 3.6283 data: 0.0028 max mem: 19788 +Epoch: [23] [1540/2138] eta: 0:36:16 lr: 2.22631470895777e-05 loss: 0.0237 (0.0274) time: 3.6223 data: 0.0030 max mem: 19788 +Epoch: [23] [1550/2138] eta: 0:35:39 lr: 2.225739012355123e-05 loss: 0.0270 (0.0274) time: 3.6211 data: 0.0030 max mem: 19788 +Epoch: [23] [1560/2138] eta: 0:35:03 lr: 2.2251632992068555e-05 loss: 0.0257 (0.0274) time: 3.6219 data: 0.0027 max mem: 19788 +Epoch: [23] [1570/2138] eta: 0:34:26 lr: 2.2245875695077345e-05 loss: 0.0259 (0.0274) time: 3.6237 data: 0.0027 max mem: 19788 +Epoch: [23] [1580/2138] eta: 0:33:50 lr: 2.2240118232525252e-05 loss: 0.0253 (0.0274) time: 3.6217 data: 0.0027 max mem: 19788 +Epoch: [23] [1590/2138] eta: 0:33:14 lr: 2.2234360604359877e-05 loss: 0.0251 (0.0274) time: 3.6205 data: 0.0027 max mem: 19788 +Epoch: [23] [1600/2138] eta: 0:32:37 lr: 2.222860281052882e-05 loss: 0.0264 (0.0275) time: 3.6281 data: 0.0028 max mem: 19788 +Epoch: [23] [1610/2138] eta: 0:32:01 lr: 2.222284485097962e-05 loss: 0.0254 (0.0274) time: 3.6293 data: 0.0030 max mem: 19788 +Epoch: [23] [1620/2138] eta: 0:31:24 lr: 2.22170867256598e-05 loss: 0.0244 (0.0275) time: 3.6244 data: 0.0030 max mem: 19788 +Epoch: [23] [1630/2138] eta: 0:30:48 lr: 2.2211328434516838e-05 loss: 0.0294 (0.0275) time: 3.6238 data: 0.0029 max mem: 19788 +Epoch: [23] [1640/2138] eta: 0:30:11 lr: 2.220556997749821e-05 loss: 0.0245 (0.0275) time: 3.6242 data: 0.0030 max mem: 19788 +Epoch: [23] [1650/2138] eta: 0:29:35 lr: 2.219981135455132e-05 loss: 0.0237 (0.0275) time: 3.6225 data: 0.0028 max mem: 19788 +Epoch: [23] [1660/2138] eta: 0:28:59 lr: 2.2194052565623574e-05 loss: 0.0234 (0.0275) time: 3.6223 data: 0.0027 max mem: 19788 +Epoch: [23] [1670/2138] eta: 0:28:22 lr: 2.2188293610662318e-05 loss: 0.0232 (0.0274) time: 3.6212 data: 0.0029 max mem: 19788 +Epoch: [23] [1680/2138] eta: 0:27:46 lr: 2.2182534489614896e-05 loss: 0.0261 (0.0274) time: 3.6244 data: 0.0029 max mem: 19788 +Epoch: [23] [1690/2138] eta: 0:27:09 lr: 2.2176775202428595e-05 loss: 0.0278 (0.0275) time: 3.6249 data: 0.0028 max mem: 19788 +Epoch: [23] [1700/2138] eta: 0:26:33 lr: 2.2171015749050676e-05 loss: 0.0258 (0.0274) time: 3.6175 data: 0.0028 max mem: 19788 +Epoch: [23] [1710/2138] eta: 0:25:56 lr: 2.216525612942838e-05 loss: 0.0255 (0.0274) time: 3.6212 data: 0.0028 max mem: 19788 +Epoch: [23] [1720/2138] eta: 0:25:20 lr: 2.21594963435089e-05 loss: 0.0263 (0.0274) time: 3.6294 data: 0.0028 max mem: 19788 +Epoch: [23] [1730/2138] eta: 0:24:44 lr: 2.215373639123941e-05 loss: 0.0263 (0.0274) time: 3.6519 data: 0.0028 max mem: 19788 +Epoch: [23] [1740/2138] eta: 0:24:07 lr: 2.2147976272567037e-05 loss: 0.0236 (0.0274) time: 3.6692 data: 0.0028 max mem: 19788 +Epoch: [23] [1750/2138] eta: 0:23:31 lr: 2.21422159874389e-05 loss: 0.0252 (0.0274) time: 3.6835 data: 0.0028 max mem: 19788 +Epoch: [23] [1760/2138] eta: 0:22:55 lr: 2.213645553580206e-05 loss: 0.0266 (0.0274) time: 3.6902 data: 0.0028 max mem: 19788 +Epoch: [23] [1770/2138] eta: 0:22:18 lr: 2.2130694917603563e-05 loss: 0.0258 (0.0275) time: 3.6524 data: 0.0028 max mem: 19788 +Epoch: [23] [1780/2138] eta: 0:21:42 lr: 2.212493413279041e-05 loss: 0.0248 (0.0275) time: 3.6234 data: 0.0029 max mem: 19788 +Epoch: [23] [1790/2138] eta: 0:21:06 lr: 2.2119173181309584e-05 loss: 0.0277 (0.0275) time: 3.6340 data: 0.0030 max mem: 19788 +Epoch: [23] [1800/2138] eta: 0:20:29 lr: 2.211341206310802e-05 loss: 0.0260 (0.0275) time: 3.6602 data: 0.0028 max mem: 19788 +Epoch: [23] [1810/2138] eta: 0:19:53 lr: 2.2107650778132643e-05 loss: 0.0257 (0.0275) time: 3.6473 data: 0.0029 max mem: 19788 +Epoch: [23] [1820/2138] eta: 0:19:17 lr: 2.2101889326330315e-05 loss: 0.0245 (0.0275) time: 3.6196 data: 0.0032 max mem: 19788 +Epoch: [23] [1830/2138] eta: 0:18:40 lr: 2.20961277076479e-05 loss: 0.0231 (0.0275) time: 3.6201 data: 0.0030 max mem: 19788 +Epoch: [23] [1840/2138] eta: 0:18:04 lr: 2.209036592203219e-05 loss: 0.0266 (0.0275) time: 3.6221 data: 0.0027 max mem: 19788 +Epoch: [23] [1850/2138] eta: 0:17:27 lr: 2.208460396942999e-05 loss: 0.0286 (0.0275) time: 3.6225 data: 0.0027 max mem: 19788 +Epoch: [23] [1860/2138] eta: 0:16:51 lr: 2.2078841849788035e-05 loss: 0.0301 (0.0276) time: 3.6337 data: 0.0030 max mem: 19788 +Epoch: [23] [1870/2138] eta: 0:16:15 lr: 2.207307956305305e-05 loss: 0.0256 (0.0276) time: 3.6379 data: 0.0032 max mem: 19788 +Epoch: [23] [1880/2138] eta: 0:15:38 lr: 2.2067317109171706e-05 loss: 0.0249 (0.0276) time: 3.6409 data: 0.0032 max mem: 19788 +Epoch: [23] [1890/2138] eta: 0:15:02 lr: 2.2061554488090674e-05 loss: 0.0249 (0.0276) time: 3.6374 data: 0.0029 max mem: 19788 +Epoch: [23] [1900/2138] eta: 0:14:25 lr: 2.205579169975656e-05 loss: 0.0230 (0.0275) time: 3.6199 data: 0.0031 max mem: 19788 +Epoch: [23] [1910/2138] eta: 0:13:49 lr: 2.205002874411596e-05 loss: 0.0230 (0.0275) time: 3.6175 data: 0.0033 max mem: 19788 +Epoch: [23] [1920/2138] eta: 0:13:13 lr: 2.204426562111542e-05 loss: 0.0243 (0.0275) time: 3.6158 data: 0.0030 max mem: 19788 +Epoch: [23] [1930/2138] eta: 0:12:36 lr: 2.2038502330701468e-05 loss: 0.0270 (0.0275) time: 3.6138 data: 0.0029 max mem: 19788 +Epoch: [23] [1940/2138] eta: 0:12:00 lr: 2.2032738872820585e-05 loss: 0.0284 (0.0275) time: 3.6177 data: 0.0031 max mem: 19788 +Epoch: [23] [1950/2138] eta: 0:11:23 lr: 2.202697524741924e-05 loss: 0.0253 (0.0275) time: 3.6246 data: 0.0032 max mem: 19788 +Epoch: [23] [1960/2138] eta: 0:10:47 lr: 2.2021211454443844e-05 loss: 0.0253 (0.0275) time: 3.6252 data: 0.0029 max mem: 19788 +Epoch: [23] [1970/2138] eta: 0:10:11 lr: 2.2015447493840803e-05 loss: 0.0258 (0.0275) time: 3.6233 data: 0.0030 max mem: 19788 +Epoch: [23] [1980/2138] eta: 0:09:34 lr: 2.2009683365556456e-05 loss: 0.0260 (0.0275) time: 3.6269 data: 0.0030 max mem: 19788 +Epoch: [23] [1990/2138] eta: 0:08:58 lr: 2.2003919069537146e-05 loss: 0.0248 (0.0275) time: 3.6328 data: 0.0028 max mem: 19788 +Epoch: [23] [2000/2138] eta: 0:08:21 lr: 2.199815460572916e-05 loss: 0.0253 (0.0275) time: 3.6264 data: 0.0031 max mem: 19788 +Epoch: [23] [2010/2138] eta: 0:07:45 lr: 2.1992389974078755e-05 loss: 0.0263 (0.0275) time: 3.6225 data: 0.0031 max mem: 19788 +Epoch: [23] [2020/2138] eta: 0:07:09 lr: 2.198662517453216e-05 loss: 0.0275 (0.0275) time: 3.6310 data: 0.0028 max mem: 19788 +Epoch: [23] [2030/2138] eta: 0:06:32 lr: 2.1980860207035563e-05 loss: 0.0262 (0.0275) time: 3.6309 data: 0.0029 max mem: 19788 +Epoch: [23] [2040/2138] eta: 0:05:56 lr: 2.1975095071535143e-05 loss: 0.0252 (0.0275) time: 3.6360 data: 0.0029 max mem: 19788 +Epoch: [23] [2050/2138] eta: 0:05:20 lr: 2.1969329767977007e-05 loss: 0.0252 (0.0275) time: 3.6529 data: 0.0028 max mem: 19788 +Epoch: [23] [2060/2138] eta: 0:04:43 lr: 2.1963564296307266e-05 loss: 0.0257 (0.0275) time: 3.6638 data: 0.0028 max mem: 19788 +Epoch: [23] [2070/2138] eta: 0:04:07 lr: 2.195779865647197e-05 loss: 0.0272 (0.0275) time: 3.6565 data: 0.0028 max mem: 19788 +Epoch: [23] [2080/2138] eta: 0:03:30 lr: 2.1952032848417162e-05 loss: 0.0270 (0.0275) time: 3.6486 data: 0.0030 max mem: 19788 +Epoch: [23] [2090/2138] eta: 0:02:54 lr: 2.1946266872088826e-05 loss: 0.0267 (0.0275) time: 3.6470 data: 0.0029 max mem: 19788 +Epoch: [23] [2100/2138] eta: 0:02:18 lr: 2.1940500727432933e-05 loss: 0.0249 (0.0275) time: 3.6647 data: 0.0029 max mem: 19788 +Epoch: [23] [2110/2138] eta: 0:01:41 lr: 2.1934734414395404e-05 loss: 0.0304 (0.0276) time: 3.6691 data: 0.0029 max mem: 19788 +Epoch: [23] [2120/2138] eta: 0:01:05 lr: 2.192896793292215e-05 loss: 0.0304 (0.0276) time: 3.6470 data: 0.0029 max mem: 19788 +Epoch: [23] [2130/2138] eta: 0:00:29 lr: 2.1923201282959016e-05 loss: 0.0292 (0.0276) time: 3.6230 data: 0.0028 max mem: 19788 +Epoch: [23] Total time: 2:09:38 +Test: [ 0/21770] eta: 17:50:38 time: 2.9508 data: 2.7217 max mem: 19788 +Test: [ 100/21770] eta: 0:35:36 time: 0.0742 data: 0.0020 max mem: 19788 +Test: [ 200/21770] eta: 0:29:20 time: 0.0645 data: 0.0020 max mem: 19788 +Test: [ 300/21770] eta: 0:27:40 time: 0.0692 data: 0.0019 max mem: 19788 +Test: [ 400/21770] eta: 0:26:38 time: 0.0674 data: 0.0021 max mem: 19788 +Test: [ 500/21770] eta: 0:25:43 time: 0.0674 data: 0.0021 max mem: 19788 +Test: [ 600/21770] eta: 0:25:17 time: 0.0691 data: 0.0021 max mem: 19788 +Test: [ 700/21770] eta: 0:24:55 time: 0.0663 data: 0.0021 max mem: 19788 +Test: [ 800/21770] eta: 0:24:43 time: 0.0735 data: 0.0021 max mem: 19788 +Test: [ 900/21770] eta: 0:24:31 time: 0.0620 data: 0.0018 max mem: 19788 +Test: [ 1000/21770] eta: 0:24:10 time: 0.0646 data: 0.0020 max mem: 19788 +Test: [ 1100/21770] eta: 0:23:55 time: 0.0643 data: 0.0020 max mem: 19788 +Test: [ 1200/21770] eta: 0:23:34 time: 0.0581 data: 0.0017 max mem: 19788 +Test: [ 1300/21770] eta: 0:23:24 time: 0.0616 data: 0.0018 max mem: 19788 +Test: [ 1400/21770] eta: 0:23:20 time: 0.0658 data: 0.0020 max mem: 19788 +Test: [ 1500/21770] eta: 0:23:09 time: 0.0620 data: 0.0018 max mem: 19788 +Test: [ 1600/21770] eta: 0:22:54 time: 0.0656 data: 0.0017 max mem: 19788 +Test: [ 1700/21770] eta: 0:22:40 time: 0.0609 data: 0.0018 max mem: 19788 +Test: [ 1800/21770] eta: 0:22:36 time: 0.0707 data: 0.0020 max mem: 19788 +Test: [ 1900/21770] eta: 0:22:34 time: 0.0815 data: 0.0025 max mem: 19788 +Test: [ 2000/21770] eta: 0:22:23 time: 0.0601 data: 0.0019 max mem: 19788 +Test: [ 2100/21770] eta: 0:22:19 time: 0.0705 data: 0.0019 max mem: 19788 +Test: [ 2200/21770] eta: 0:22:06 time: 0.0603 data: 0.0018 max mem: 19788 +Test: [ 2300/21770] eta: 0:21:59 time: 0.0596 data: 0.0019 max mem: 19788 +Test: [ 2400/21770] eta: 0:21:48 time: 0.0649 data: 0.0019 max mem: 19788 +Test: [ 2500/21770] eta: 0:21:41 time: 0.0665 data: 0.0020 max mem: 19788 +Test: [ 2600/21770] eta: 0:21:36 time: 0.0745 data: 0.0022 max mem: 19788 +Test: [ 2700/21770] eta: 0:21:29 time: 0.0640 data: 0.0020 max mem: 19788 +Test: [ 2800/21770] eta: 0:21:26 time: 0.0837 data: 0.0020 max mem: 19788 +Test: [ 2900/21770] eta: 0:21:24 time: 0.0691 data: 0.0020 max mem: 19788 +Test: [ 3000/21770] eta: 0:21:16 time: 0.0693 data: 0.0020 max mem: 19788 +Test: [ 3100/21770] eta: 0:21:11 time: 0.0709 data: 0.0020 max mem: 19788 +Test: [ 3200/21770] eta: 0:21:09 time: 0.0693 data: 0.0024 max mem: 19788 +Test: [ 3300/21770] eta: 0:21:01 time: 0.0638 data: 0.0017 max mem: 19788 +Test: [ 3400/21770] eta: 0:20:55 time: 0.0765 data: 0.0023 max mem: 19788 +Test: [ 3500/21770] eta: 0:20:50 time: 0.0636 data: 0.0019 max mem: 19788 +Test: [ 3600/21770] eta: 0:20:46 time: 0.0785 data: 0.0019 max mem: 19788 +Test: [ 3700/21770] eta: 0:20:39 time: 0.0641 data: 0.0018 max mem: 19788 +Test: [ 3800/21770] eta: 0:20:30 time: 0.0662 data: 0.0020 max mem: 19788 +Test: [ 3900/21770] eta: 0:20:27 time: 0.0832 data: 0.0029 max mem: 19788 +Test: [ 4000/21770] eta: 0:20:21 time: 0.0639 data: 0.0019 max mem: 19788 +Test: [ 4100/21770] eta: 0:20:15 time: 0.0703 data: 0.0021 max mem: 19788 +Test: [ 4200/21770] eta: 0:20:08 time: 0.0738 data: 0.0022 max mem: 19788 +Test: [ 4300/21770] eta: 0:20:01 time: 0.0767 data: 0.0022 max mem: 19788 +Test: [ 4400/21770] eta: 0:19:57 time: 0.0739 data: 0.0022 max mem: 19788 +Test: [ 4500/21770] eta: 0:19:51 time: 0.0657 data: 0.0018 max mem: 19788 +Test: [ 4600/21770] eta: 0:19:46 time: 0.0665 data: 0.0020 max mem: 19788 +Test: [ 4700/21770] eta: 0:19:39 time: 0.0787 data: 0.0022 max mem: 19788 +Test: [ 4800/21770] eta: 0:19:32 time: 0.0725 data: 0.0022 max mem: 19788 +Test: [ 4900/21770] eta: 0:19:29 time: 0.0828 data: 0.0024 max mem: 19788 +Test: [ 5000/21770] eta: 0:19:22 time: 0.0644 data: 0.0017 max mem: 19788 +Test: [ 5100/21770] eta: 0:19:14 time: 0.0709 data: 0.0021 max mem: 19788 +Test: [ 5200/21770] eta: 0:19:07 time: 0.0803 data: 0.0027 max mem: 19788 +Test: [ 5300/21770] eta: 0:19:00 time: 0.0650 data: 0.0019 max mem: 19788 +Test: [ 5400/21770] eta: 0:18:52 time: 0.0687 data: 0.0024 max mem: 19788 +Test: [ 5500/21770] eta: 0:18:46 time: 0.0649 data: 0.0019 max mem: 19788 +Test: [ 5600/21770] eta: 0:18:40 time: 0.0690 data: 0.0020 max mem: 19788 +Test: [ 5700/21770] eta: 0:18:35 time: 0.0759 data: 0.0023 max mem: 19788 +Test: [ 5800/21770] eta: 0:18:27 time: 0.0626 data: 0.0019 max mem: 19788 +Test: [ 5900/21770] eta: 0:18:22 time: 0.0822 data: 0.0025 max mem: 19788 +Test: [ 6000/21770] eta: 0:18:16 time: 0.0740 data: 0.0022 max mem: 19788 +Test: [ 6100/21770] eta: 0:18:08 time: 0.0823 data: 0.0025 max mem: 19788 +Test: [ 6200/21770] eta: 0:18:01 time: 0.0657 data: 0.0020 max mem: 19788 +Test: [ 6300/21770] eta: 0:17:54 time: 0.0750 data: 0.0023 max mem: 19788 +Test: [ 6400/21770] eta: 0:17:49 time: 0.0681 data: 0.0023 max mem: 19788 +Test: [ 6500/21770] eta: 0:17:43 time: 0.0745 data: 0.0019 max mem: 19788 +Test: [ 6600/21770] eta: 0:17:36 time: 0.0661 data: 0.0019 max mem: 19788 +Test: [ 6700/21770] eta: 0:17:29 time: 0.0746 data: 0.0022 max mem: 19788 +Test: [ 6800/21770] eta: 0:17:23 time: 0.0622 data: 0.0018 max mem: 19788 +Test: [ 6900/21770] eta: 0:17:16 time: 0.0656 data: 0.0019 max mem: 19788 +Test: [ 7000/21770] eta: 0:17:08 time: 0.0635 data: 0.0022 max mem: 19788 +Test: [ 7100/21770] eta: 0:17:01 time: 0.0700 data: 0.0022 max mem: 19788 +Test: [ 7200/21770] eta: 0:16:54 time: 0.0620 data: 0.0020 max mem: 19788 +Test: [ 7300/21770] eta: 0:16:48 time: 0.0762 data: 0.0024 max mem: 19788 +Test: [ 7400/21770] eta: 0:16:41 time: 0.0621 data: 0.0019 max mem: 19788 +Test: [ 7500/21770] eta: 0:16:32 time: 0.0643 data: 0.0019 max mem: 19788 +Test: [ 7600/21770] eta: 0:16:25 time: 0.0694 data: 0.0022 max mem: 19788 +Test: [ 7700/21770] eta: 0:16:18 time: 0.0632 data: 0.0019 max mem: 19788 +Test: [ 7800/21770] eta: 0:16:11 time: 0.0666 data: 0.0020 max mem: 19788 +Test: [ 7900/21770] eta: 0:16:04 time: 0.0643 data: 0.0020 max mem: 19788 +Test: [ 8000/21770] eta: 0:15:58 time: 0.0784 data: 0.0023 max mem: 19788 +Test: [ 8100/21770] eta: 0:15:52 time: 0.0645 data: 0.0018 max mem: 19788 +Test: [ 8200/21770] eta: 0:15:45 time: 0.0792 data: 0.0025 max mem: 19788 +Test: [ 8300/21770] eta: 0:15:37 time: 0.0601 data: 0.0018 max mem: 19788 +Test: [ 8400/21770] eta: 0:15:30 time: 0.0719 data: 0.0023 max mem: 19788 +Test: [ 8500/21770] eta: 0:15:23 time: 0.0682 data: 0.0019 max mem: 19788 +Test: [ 8600/21770] eta: 0:15:17 time: 0.0832 data: 0.0025 max mem: 19788 +Test: [ 8700/21770] eta: 0:15:10 time: 0.0638 data: 0.0019 max mem: 19788 +Test: [ 8800/21770] eta: 0:15:02 time: 0.0628 data: 0.0020 max mem: 19788 +Test: [ 8900/21770] eta: 0:14:55 time: 0.0643 data: 0.0021 max mem: 19788 +Test: [ 9000/21770] eta: 0:14:48 time: 0.0608 data: 0.0019 max mem: 19788 +Test: [ 9100/21770] eta: 0:14:41 time: 0.0786 data: 0.0021 max mem: 19788 +Test: [ 9200/21770] eta: 0:14:36 time: 0.0829 data: 0.0026 max mem: 19788 +Test: [ 9300/21770] eta: 0:14:29 time: 0.0655 data: 0.0020 max mem: 19788 +Test: [ 9400/21770] eta: 0:14:23 time: 0.0642 data: 0.0020 max mem: 19788 +Test: [ 9500/21770] eta: 0:14:17 time: 0.0640 data: 0.0018 max mem: 19788 +Test: [ 9600/21770] eta: 0:14:09 time: 0.0658 data: 0.0020 max mem: 19788 +Test: [ 9700/21770] eta: 0:14:02 time: 0.0666 data: 0.0019 max mem: 19788 +Test: [ 9800/21770] eta: 0:13:55 time: 0.0756 data: 0.0023 max mem: 19788 +Test: [ 9900/21770] eta: 0:13:49 time: 0.0736 data: 0.0022 max mem: 19788 +Test: [10000/21770] eta: 0:13:42 time: 0.0676 data: 0.0021 max mem: 19788 +Test: [10100/21770] eta: 0:13:35 time: 0.0633 data: 0.0021 max mem: 19788 +Test: [10200/21770] eta: 0:13:29 time: 0.0824 data: 0.0027 max mem: 19788 +Test: [10300/21770] eta: 0:13:21 time: 0.0635 data: 0.0018 max mem: 19788 +Test: [10400/21770] eta: 0:13:14 time: 0.0633 data: 0.0020 max mem: 19788 +Test: [10500/21770] eta: 0:13:08 time: 0.0646 data: 0.0020 max mem: 19788 +Test: [10600/21770] eta: 0:13:01 time: 0.0651 data: 0.0019 max mem: 19788 +Test: [10700/21770] eta: 0:12:54 time: 0.0638 data: 0.0022 max mem: 19788 +Test: [10800/21770] eta: 0:12:47 time: 0.0790 data: 0.0024 max mem: 19788 +Test: [10900/21770] eta: 0:12:40 time: 0.0721 data: 0.0020 max mem: 19788 +Test: [11000/21770] eta: 0:12:34 time: 0.0670 data: 0.0019 max mem: 19788 +Test: [11100/21770] eta: 0:12:27 time: 0.0620 data: 0.0020 max mem: 19788 +Test: [11200/21770] eta: 0:12:19 time: 0.0684 data: 0.0020 max mem: 19788 +Test: [11300/21770] eta: 0:12:12 time: 0.0630 data: 0.0019 max mem: 19788 +Test: [11400/21770] eta: 0:12:05 time: 0.0760 data: 0.0022 max mem: 19788 +Test: [11500/21770] eta: 0:11:58 time: 0.0649 data: 0.0020 max mem: 19788 +Test: [11600/21770] eta: 0:11:51 time: 0.0645 data: 0.0019 max mem: 19788 +Test: [11700/21770] eta: 0:11:43 time: 0.0640 data: 0.0019 max mem: 19788 +Test: [11800/21770] eta: 0:11:36 time: 0.0728 data: 0.0022 max mem: 19788 +Test: [11900/21770] eta: 0:11:29 time: 0.0638 data: 0.0018 max mem: 19788 +Test: [12000/21770] eta: 0:11:22 time: 0.0747 data: 0.0019 max mem: 19788 +Test: [12100/21770] eta: 0:11:16 time: 0.0823 data: 0.0026 max mem: 19788 +Test: [12200/21770] eta: 0:11:10 time: 0.0829 data: 0.0025 max mem: 19788 +Test: [12300/21770] eta: 0:11:03 time: 0.0617 data: 0.0018 max mem: 19788 +Test: [12400/21770] eta: 0:10:56 time: 0.0647 data: 0.0019 max mem: 19788 +Test: [12500/21770] eta: 0:10:50 time: 0.0637 data: 0.0019 max mem: 19788 +Test: [12600/21770] eta: 0:10:43 time: 0.0788 data: 0.0019 max mem: 19788 +Test: [12700/21770] eta: 0:10:36 time: 0.0633 data: 0.0019 max mem: 19788 +Test: [12800/21770] eta: 0:10:29 time: 0.0761 data: 0.0019 max mem: 19788 +Test: [12900/21770] eta: 0:10:22 time: 0.0634 data: 0.0019 max mem: 19788 +Test: [13000/21770] eta: 0:10:15 time: 0.0631 data: 0.0020 max mem: 19788 +Test: [13100/21770] eta: 0:10:08 time: 0.0633 data: 0.0019 max mem: 19788 +Test: [13200/21770] eta: 0:10:01 time: 0.0825 data: 0.0024 max mem: 19788 +Test: [13300/21770] eta: 0:09:54 time: 0.0654 data: 0.0020 max mem: 19788 +Test: [13400/21770] eta: 0:09:46 time: 0.0642 data: 0.0019 max mem: 19788 +Test: [13500/21770] eta: 0:09:39 time: 0.0713 data: 0.0021 max mem: 19788 +Test: [13600/21770] eta: 0:09:32 time: 0.0767 data: 0.0021 max mem: 19788 +Test: [13700/21770] eta: 0:09:25 time: 0.0741 data: 0.0024 max mem: 19788 +Test: [13800/21770] eta: 0:09:18 time: 0.0756 data: 0.0019 max mem: 19788 +Test: [13900/21770] eta: 0:09:12 time: 0.0801 data: 0.0023 max mem: 19788 +Test: [14000/21770] eta: 0:09:05 time: 0.0758 data: 0.0023 max mem: 19788 +Test: [14100/21770] eta: 0:08:58 time: 0.0621 data: 0.0018 max mem: 19788 +Test: [14200/21770] eta: 0:08:50 time: 0.0663 data: 0.0020 max mem: 19788 +Test: [14300/21770] eta: 0:08:43 time: 0.0743 data: 0.0022 max mem: 19788 +Test: [14400/21770] eta: 0:08:37 time: 0.0748 data: 0.0020 max mem: 19788 +Test: [14500/21770] eta: 0:08:30 time: 0.0639 data: 0.0018 max mem: 19788 +Test: [14600/21770] eta: 0:08:23 time: 0.0826 data: 0.0025 max mem: 19788 +Test: [14700/21770] eta: 0:08:16 time: 0.0704 data: 0.0021 max mem: 19788 +Test: [14800/21770] eta: 0:08:09 time: 0.0830 data: 0.0025 max mem: 19788 +Test: [14900/21770] eta: 0:08:02 time: 0.0636 data: 0.0019 max mem: 19788 +Test: [15000/21770] eta: 0:07:55 time: 0.0626 data: 0.0019 max mem: 19788 +Test: [15100/21770] eta: 0:07:47 time: 0.0686 data: 0.0021 max mem: 19788 +Test: [15200/21770] eta: 0:07:40 time: 0.0692 data: 0.0020 max mem: 19788 +Test: [15300/21770] eta: 0:07:33 time: 0.0640 data: 0.0018 max mem: 19788 +Test: [15400/21770] eta: 0:07:26 time: 0.0648 data: 0.0018 max mem: 19788 +Test: [15500/21770] eta: 0:07:19 time: 0.0687 data: 0.0021 max mem: 19788 +Test: [15600/21770] eta: 0:07:12 time: 0.0731 data: 0.0023 max mem: 19788 +Test: [15700/21770] eta: 0:07:05 time: 0.0686 data: 0.0020 max mem: 19788 +Test: [15800/21770] eta: 0:06:58 time: 0.0741 data: 0.0021 max mem: 19788 +Test: [15900/21770] eta: 0:06:51 time: 0.0678 data: 0.0020 max mem: 19788 +Test: [16000/21770] eta: 0:06:44 time: 0.0783 data: 0.0024 max mem: 19788 +Test: [16100/21770] eta: 0:06:37 time: 0.0824 data: 0.0026 max mem: 19788 +Test: [16200/21770] eta: 0:06:30 time: 0.0835 data: 0.0025 max mem: 19788 +Test: [16300/21770] eta: 0:06:23 time: 0.0685 data: 0.0020 max mem: 19788 +Test: [16400/21770] eta: 0:06:16 time: 0.0607 data: 0.0019 max mem: 19788 +Test: [16500/21770] eta: 0:06:09 time: 0.0634 data: 0.0020 max mem: 19788 +Test: [16600/21770] eta: 0:06:02 time: 0.0614 data: 0.0020 max mem: 19788 +Test: [16700/21770] eta: 0:05:55 time: 0.0597 data: 0.0018 max mem: 19788 +Test: [16800/21770] eta: 0:05:48 time: 0.0812 data: 0.0025 max mem: 19788 +Test: [16900/21770] eta: 0:05:41 time: 0.0832 data: 0.0024 max mem: 19788 +Test: [17000/21770] eta: 0:05:34 time: 0.0674 data: 0.0020 max mem: 19788 +Test: [17100/21770] eta: 0:05:27 time: 0.0631 data: 0.0019 max mem: 19788 +Test: [17200/21770] eta: 0:05:20 time: 0.0633 data: 0.0019 max mem: 19788 +Test: [17300/21770] eta: 0:05:13 time: 0.0793 data: 0.0026 max mem: 19788 +Test: [17400/21770] eta: 0:05:06 time: 0.0631 data: 0.0019 max mem: 19788 +Test: [17500/21770] eta: 0:04:59 time: 0.0814 data: 0.0025 max mem: 19788 +Test: [17600/21770] eta: 0:04:52 time: 0.0743 data: 0.0022 max mem: 19788 +Test: [17700/21770] eta: 0:04:45 time: 0.0757 data: 0.0024 max mem: 19788 +Test: [17800/21770] eta: 0:04:38 time: 0.0667 data: 0.0022 max mem: 19788 +Test: [17900/21770] eta: 0:04:31 time: 0.0629 data: 0.0018 max mem: 19788 +Test: [18000/21770] eta: 0:04:24 time: 0.0649 data: 0.0019 max mem: 19788 +Test: [18100/21770] eta: 0:04:17 time: 0.0764 data: 0.0022 max mem: 19788 +Test: [18200/21770] eta: 0:04:10 time: 0.0635 data: 0.0018 max mem: 19788 +Test: [18300/21770] eta: 0:04:03 time: 0.0727 data: 0.0024 max mem: 19788 +Test: [18400/21770] eta: 0:03:56 time: 0.0617 data: 0.0019 max mem: 19788 +Test: [18500/21770] eta: 0:03:49 time: 0.0797 data: 0.0021 max mem: 19788 +Test: [18600/21770] eta: 0:03:42 time: 0.0750 data: 0.0024 max mem: 19788 +Test: [18700/21770] eta: 0:03:35 time: 0.0816 data: 0.0025 max mem: 19788 +Test: [18800/21770] eta: 0:03:28 time: 0.0697 data: 0.0021 max mem: 19788 +Test: [18900/21770] eta: 0:03:21 time: 0.0736 data: 0.0021 max mem: 19788 +Test: [19000/21770] eta: 0:03:14 time: 0.0827 data: 0.0024 max mem: 19788 +Test: [19100/21770] eta: 0:03:07 time: 0.0802 data: 0.0024 max mem: 19788 +Test: [19200/21770] eta: 0:03:00 time: 0.0629 data: 0.0019 max mem: 19788 +Test: [19300/21770] eta: 0:02:53 time: 0.0618 data: 0.0020 max mem: 19788 +Test: [19400/21770] eta: 0:02:46 time: 0.0641 data: 0.0019 max mem: 19788 +Test: [19500/21770] eta: 0:02:39 time: 0.0618 data: 0.0020 max mem: 19788 +Test: [19600/21770] eta: 0:02:31 time: 0.0676 data: 0.0020 max mem: 19788 +Test: [19700/21770] eta: 0:02:24 time: 0.0666 data: 0.0018 max mem: 19788 +Test: [19800/21770] eta: 0:02:17 time: 0.0638 data: 0.0019 max mem: 19788 +Test: [19900/21770] eta: 0:02:10 time: 0.0652 data: 0.0021 max mem: 19788 +Test: [20000/21770] eta: 0:02:03 time: 0.0740 data: 0.0021 max mem: 19788 +Test: [20100/21770] eta: 0:01:56 time: 0.0617 data: 0.0020 max mem: 19788 +Test: [20200/21770] eta: 0:01:49 time: 0.0625 data: 0.0021 max mem: 19788 +Test: [20300/21770] eta: 0:01:42 time: 0.0690 data: 0.0022 max mem: 19788 +Test: [20400/21770] eta: 0:01:35 time: 0.0711 data: 0.0021 max mem: 19788 +Test: [20500/21770] eta: 0:01:28 time: 0.0682 data: 0.0021 max mem: 19788 +Test: [20600/21770] eta: 0:01:21 time: 0.0836 data: 0.0027 max mem: 19788 +Test: [20700/21770] eta: 0:01:14 time: 0.0738 data: 0.0023 max mem: 19788 +Test: [20800/21770] eta: 0:01:07 time: 0.0648 data: 0.0019 max mem: 19788 +Test: [20900/21770] eta: 0:01:00 time: 0.0663 data: 0.0021 max mem: 19788 +Test: [21000/21770] eta: 0:00:53 time: 0.0824 data: 0.0026 max mem: 19788 +Test: [21100/21770] eta: 0:00:46 time: 0.0772 data: 0.0024 max mem: 19788 +Test: [21200/21770] eta: 0:00:39 time: 0.0595 data: 0.0018 max mem: 19788 +Test: [21300/21770] eta: 0:00:32 time: 0.0724 data: 0.0020 max mem: 19788 +Test: [21400/21770] eta: 0:00:25 time: 0.0635 data: 0.0018 max mem: 19788 +Test: [21500/21770] eta: 0:00:18 time: 0.0616 data: 0.0017 max mem: 19788 +Test: [21600/21770] eta: 0:00:11 time: 0.0638 data: 0.0018 max mem: 19788 +Test: [21700/21770] eta: 0:00:04 time: 0.0756 data: 0.0022 max mem: 19788 +Test: Total time: 0:25:24 +Final results: +Mean IoU is 62.35 + + precision@0.5 = 69.03 + precision@0.6 = 63.82 + precision@0.7 = 57.37 + precision@0.8 = 47.04 + precision@0.9 = 23.62 + overall IoU = 63.67 + mean IoU = 62.35 + +Mean accuracy for one-to-zero sample is 85.99 + +Average object IoU 0.6234632180617343 +Overall IoU 63.67146301269531 +Epoch: [24] [ 0/2138] eta: 12:54:39 lr: 2.1918587841639406e-05 loss: 0.0256 (0.0256) time: 21.7395 data: 1.7709 max mem: 19788 +Epoch: [24] [ 10/2138] eta: 3:13:47 lr: 2.1912820888257983e-05 loss: 0.0239 (0.0266) time: 5.4640 data: 0.1639 max mem: 19788 +Epoch: [24] [ 20/2138] eta: 2:44:59 lr: 2.1907053766234922e-05 loss: 0.0229 (0.0245) time: 3.8209 data: 0.0030 max mem: 19788 +Epoch: [24] [ 30/2138] eta: 2:33:22 lr: 2.190128647551598e-05 loss: 0.0228 (0.0241) time: 3.7615 data: 0.0029 max mem: 19788 +Epoch: [24] [ 40/2138] eta: 2:26:54 lr: 2.189551901604685e-05 loss: 0.0255 (0.0251) time: 3.7045 data: 0.0030 max mem: 19788 +Epoch: [24] [ 50/2138] eta: 2:22:47 lr: 2.1889751387773192e-05 loss: 0.0271 (0.0258) time: 3.6970 data: 0.0030 max mem: 19788 +Epoch: [24] [ 60/2138] eta: 2:19:47 lr: 2.1883983590640664e-05 loss: 0.0256 (0.0252) time: 3.6985 data: 0.0034 max mem: 19788 +Epoch: [24] [ 70/2138] eta: 2:17:43 lr: 2.187821562459485e-05 loss: 0.0193 (0.0245) time: 3.7209 data: 0.0034 max mem: 19788 +Epoch: [24] [ 80/2138] eta: 2:15:31 lr: 2.1872447489581336e-05 loss: 0.0241 (0.0252) time: 3.6912 data: 0.0031 max mem: 19788 +Epoch: [24] [ 90/2138] eta: 2:13:49 lr: 2.1866679185545645e-05 loss: 0.0254 (0.0249) time: 3.6544 data: 0.0031 max mem: 19788 +Epoch: [24] [ 100/2138] eta: 2:12:13 lr: 2.186091071243329e-05 loss: 0.0223 (0.0248) time: 3.6568 data: 0.0031 max mem: 19788 +Epoch: [24] [ 110/2138] eta: 2:11:25 lr: 2.1855142070189736e-05 loss: 0.0250 (0.0251) time: 3.7410 data: 0.0029 max mem: 19788 +Epoch: [24] [ 120/2138] eta: 2:10:29 lr: 2.1849373258760424e-05 loss: 0.0259 (0.0254) time: 3.8149 data: 0.0032 max mem: 19788 +Epoch: [24] [ 130/2138] eta: 2:09:41 lr: 2.184360427809075e-05 loss: 0.0263 (0.0258) time: 3.8040 data: 0.0036 max mem: 19788 +Epoch: [24] [ 140/2138] eta: 2:08:46 lr: 2.1837835128126085e-05 loss: 0.0263 (0.0258) time: 3.7881 data: 0.0034 max mem: 19788 +Epoch: [24] [ 150/2138] eta: 2:07:57 lr: 2.183206580881176e-05 loss: 0.0240 (0.0257) time: 3.7722 data: 0.0032 max mem: 19788 +Epoch: [24] [ 160/2138] eta: 2:06:50 lr: 2.1826296320093087e-05 loss: 0.0252 (0.0261) time: 3.7097 data: 0.0030 max mem: 19788 +Epoch: [24] [ 170/2138] eta: 2:05:47 lr: 2.1820526661915323e-05 loss: 0.0281 (0.0262) time: 3.6320 data: 0.0028 max mem: 19788 +Epoch: [24] [ 180/2138] eta: 2:04:46 lr: 2.1814756834223708e-05 loss: 0.0256 (0.0265) time: 3.6327 data: 0.0029 max mem: 19788 +Epoch: [24] [ 190/2138] eta: 2:03:50 lr: 2.180898683696344e-05 loss: 0.0258 (0.0265) time: 3.6402 data: 0.0028 max mem: 19788 +Epoch: [24] [ 200/2138] eta: 2:03:08 lr: 2.1803216670079686e-05 loss: 0.0184 (0.0261) time: 3.7124 data: 0.0028 max mem: 19788 +Epoch: [24] [ 210/2138] eta: 2:02:22 lr: 2.179744633351757e-05 loss: 0.0276 (0.0265) time: 3.7487 data: 0.0031 max mem: 19788 +Epoch: [24] [ 220/2138] eta: 2:01:29 lr: 2.1791675827222207e-05 loss: 0.0276 (0.0262) time: 3.6812 data: 0.0031 max mem: 19788 +Epoch: [24] [ 230/2138] eta: 2:00:38 lr: 2.1785905151138645e-05 loss: 0.0240 (0.0264) time: 3.6398 data: 0.0029 max mem: 19788 +Epoch: [24] [ 240/2138] eta: 1:59:51 lr: 2.178013430521193e-05 loss: 0.0258 (0.0264) time: 3.6603 data: 0.0028 max mem: 19788 +Epoch: [24] [ 250/2138] eta: 1:59:02 lr: 2.177436328938704e-05 loss: 0.0249 (0.0264) time: 3.6598 data: 0.0026 max mem: 19788 +Epoch: [24] [ 260/2138] eta: 1:58:15 lr: 2.1768592103608957e-05 loss: 0.0226 (0.0263) time: 3.6480 data: 0.0026 max mem: 19788 +Epoch: [24] [ 270/2138] eta: 1:57:32 lr: 2.176282074782259e-05 loss: 0.0264 (0.0264) time: 3.6797 data: 0.0028 max mem: 19788 +Epoch: [24] [ 280/2138] eta: 1:56:54 lr: 2.1757049221972854e-05 loss: 0.0264 (0.0264) time: 3.7334 data: 0.0028 max mem: 19788 +Epoch: [24] [ 290/2138] eta: 1:56:10 lr: 2.175127752600459e-05 loss: 0.0260 (0.0264) time: 3.7222 data: 0.0028 max mem: 19788 +Epoch: [24] [ 300/2138] eta: 1:55:23 lr: 2.174550565986264e-05 loss: 0.0260 (0.0263) time: 3.6552 data: 0.0028 max mem: 19788 +Epoch: [24] [ 310/2138] eta: 1:54:38 lr: 2.1739733623491786e-05 loss: 0.0222 (0.0262) time: 3.6302 data: 0.0028 max mem: 19788 +Epoch: [24] [ 320/2138] eta: 1:53:53 lr: 2.1733961416836794e-05 loss: 0.0239 (0.0262) time: 3.6298 data: 0.0029 max mem: 19788 +Epoch: [24] [ 330/2138] eta: 1:53:08 lr: 2.1728189039842373e-05 loss: 0.0251 (0.0263) time: 3.6276 data: 0.0030 max mem: 19788 +Epoch: [24] [ 340/2138] eta: 1:52:23 lr: 2.172241649245323e-05 loss: 0.0238 (0.0262) time: 3.6242 data: 0.0030 max mem: 19788 +Epoch: [24] [ 350/2138] eta: 1:51:39 lr: 2.171664377461401e-05 loss: 0.0236 (0.0262) time: 3.6238 data: 0.0027 max mem: 19788 +Epoch: [24] [ 360/2138] eta: 1:50:56 lr: 2.171087088626933e-05 loss: 0.0244 (0.0261) time: 3.6266 data: 0.0027 max mem: 19788 +Epoch: [24] [ 370/2138] eta: 1:50:14 lr: 2.1705097827363787e-05 loss: 0.0247 (0.0262) time: 3.6377 data: 0.0028 max mem: 19788 +Epoch: [24] [ 380/2138] eta: 1:49:35 lr: 2.1699324597841925e-05 loss: 0.0242 (0.0262) time: 3.6733 data: 0.0030 max mem: 19788 +Epoch: [24] [ 390/2138] eta: 1:48:52 lr: 2.1693551197648268e-05 loss: 0.0240 (0.0262) time: 3.6608 data: 0.0029 max mem: 19788 +Epoch: [24] [ 400/2138] eta: 1:48:09 lr: 2.1687777626727287e-05 loss: 0.0266 (0.0263) time: 3.6208 data: 0.0027 max mem: 19788 +Epoch: [24] [ 410/2138] eta: 1:47:28 lr: 2.1682003885023447e-05 loss: 0.0285 (0.0264) time: 3.6234 data: 0.0027 max mem: 19788 +Epoch: [24] [ 420/2138] eta: 1:46:46 lr: 2.1676229972481146e-05 loss: 0.0279 (0.0264) time: 3.6236 data: 0.0027 max mem: 19788 +Epoch: [24] [ 430/2138] eta: 1:46:11 lr: 2.1670455889044777e-05 loss: 0.0235 (0.0264) time: 3.7070 data: 0.0028 max mem: 19788 +Epoch: [24] [ 440/2138] eta: 1:45:34 lr: 2.1664681634658674e-05 loss: 0.0261 (0.0265) time: 3.7654 data: 0.0029 max mem: 19788 +Epoch: [24] [ 450/2138] eta: 1:44:58 lr: 2.1658907209267156e-05 loss: 0.0269 (0.0265) time: 3.7579 data: 0.0029 max mem: 19788 +Epoch: [24] [ 460/2138] eta: 1:44:22 lr: 2.1653132612814492e-05 loss: 0.0243 (0.0265) time: 3.7735 data: 0.0026 max mem: 19788 +Epoch: [24] [ 470/2138] eta: 1:43:47 lr: 2.164735784524493e-05 loss: 0.0241 (0.0265) time: 3.7807 data: 0.0028 max mem: 19788 +Epoch: [24] [ 480/2138] eta: 1:43:11 lr: 2.1641582906502667e-05 loss: 0.0278 (0.0266) time: 3.7846 data: 0.0028 max mem: 19788 +Epoch: [24] [ 490/2138] eta: 1:42:36 lr: 2.1635807796531884e-05 loss: 0.0282 (0.0266) time: 3.7789 data: 0.0028 max mem: 19788 +Epoch: [24] [ 500/2138] eta: 1:41:59 lr: 2.163003251527671e-05 loss: 0.0254 (0.0265) time: 3.7707 data: 0.0029 max mem: 19788 +Epoch: [24] [ 510/2138] eta: 1:41:24 lr: 2.1624257062681256e-05 loss: 0.0265 (0.0265) time: 3.7778 data: 0.0029 max mem: 19788 +Epoch: [24] [ 520/2138] eta: 1:40:48 lr: 2.1618481438689576e-05 loss: 0.0265 (0.0265) time: 3.7888 data: 0.0027 max mem: 19788 +Epoch: [24] [ 530/2138] eta: 1:40:11 lr: 2.161270564324571e-05 loss: 0.0226 (0.0265) time: 3.7779 data: 0.0028 max mem: 19788 +Epoch: [24] [ 540/2138] eta: 1:39:35 lr: 2.1606929676293657e-05 loss: 0.0220 (0.0264) time: 3.7694 data: 0.0029 max mem: 19788 +Epoch: [24] [ 550/2138] eta: 1:38:55 lr: 2.160115353777738e-05 loss: 0.0234 (0.0264) time: 3.7049 data: 0.0029 max mem: 19788 +Epoch: [24] [ 560/2138] eta: 1:38:15 lr: 2.15953772276408e-05 loss: 0.0234 (0.0264) time: 3.6555 data: 0.0030 max mem: 19788 +Epoch: [24] [ 570/2138] eta: 1:37:37 lr: 2.1589600745827815e-05 loss: 0.0211 (0.0264) time: 3.6893 data: 0.0031 max mem: 19788 +Epoch: [24] [ 580/2138] eta: 1:36:57 lr: 2.1583824092282275e-05 loss: 0.0236 (0.0264) time: 3.6741 data: 0.0031 max mem: 19788 +Epoch: [24] [ 590/2138] eta: 1:36:18 lr: 2.1578047266948018e-05 loss: 0.0249 (0.0264) time: 3.6529 data: 0.0031 max mem: 19788 +Epoch: [24] [ 600/2138] eta: 1:35:39 lr: 2.157227026976881e-05 loss: 0.0229 (0.0264) time: 3.6646 data: 0.0033 max mem: 19788 +Epoch: [24] [ 610/2138] eta: 1:34:59 lr: 2.1566493100688424e-05 loss: 0.0224 (0.0264) time: 3.6430 data: 0.0032 max mem: 19788 +Epoch: [24] [ 620/2138] eta: 1:34:22 lr: 2.156071575965056e-05 loss: 0.0277 (0.0264) time: 3.6803 data: 0.0029 max mem: 19788 +Epoch: [24] [ 630/2138] eta: 1:33:42 lr: 2.155493824659891e-05 loss: 0.0242 (0.0264) time: 3.6860 data: 0.0027 max mem: 19788 +Epoch: [24] [ 640/2138] eta: 1:33:04 lr: 2.1549160561477115e-05 loss: 0.0237 (0.0264) time: 3.6605 data: 0.0028 max mem: 19788 +Epoch: [24] [ 650/2138] eta: 1:32:24 lr: 2.1543382704228795e-05 loss: 0.0255 (0.0264) time: 3.6552 data: 0.0029 max mem: 19788 +Epoch: [24] [ 660/2138] eta: 1:31:46 lr: 2.1537604674797518e-05 loss: 0.0248 (0.0264) time: 3.6428 data: 0.0031 max mem: 19788 +Epoch: [24] [ 670/2138] eta: 1:31:06 lr: 2.153182647312682e-05 loss: 0.0244 (0.0264) time: 3.6489 data: 0.0031 max mem: 19788 +Epoch: [24] [ 680/2138] eta: 1:30:28 lr: 2.152604809916022e-05 loss: 0.0264 (0.0264) time: 3.6535 data: 0.0029 max mem: 19788 +Epoch: [24] [ 690/2138] eta: 1:29:51 lr: 2.1520269552841172e-05 loss: 0.0256 (0.0264) time: 3.6913 data: 0.0028 max mem: 19788 +Epoch: [24] [ 700/2138] eta: 1:29:11 lr: 2.1514490834113128e-05 loss: 0.0258 (0.0264) time: 3.6733 data: 0.0031 max mem: 19788 +Epoch: [24] [ 710/2138] eta: 1:28:33 lr: 2.1508711942919475e-05 loss: 0.0265 (0.0264) time: 3.6485 data: 0.0031 max mem: 19788 +Epoch: [24] [ 720/2138] eta: 1:27:55 lr: 2.1502932879203582e-05 loss: 0.0220 (0.0264) time: 3.6686 data: 0.0028 max mem: 19788 +Epoch: [24] [ 730/2138] eta: 1:27:16 lr: 2.149715364290877e-05 loss: 0.0228 (0.0264) time: 3.6526 data: 0.0028 max mem: 19788 +Epoch: [24] [ 740/2138] eta: 1:26:38 lr: 2.149137423397834e-05 loss: 0.0233 (0.0264) time: 3.6487 data: 0.0028 max mem: 19788 +Epoch: [24] [ 750/2138] eta: 1:26:00 lr: 2.1485594652355543e-05 loss: 0.0232 (0.0264) time: 3.6639 data: 0.0029 max mem: 19788 +Epoch: [24] [ 760/2138] eta: 1:25:21 lr: 2.1479814897983608e-05 loss: 0.0271 (0.0264) time: 3.6501 data: 0.0028 max mem: 19788 +Epoch: [24] [ 770/2138] eta: 1:24:43 lr: 2.147403497080571e-05 loss: 0.0263 (0.0264) time: 3.6477 data: 0.0031 max mem: 19788 +Epoch: [24] [ 780/2138] eta: 1:24:05 lr: 2.1468254870765004e-05 loss: 0.0257 (0.0264) time: 3.6595 data: 0.0031 max mem: 19788 +Epoch: [24] [ 790/2138] eta: 1:23:27 lr: 2.1462474597804608e-05 loss: 0.0257 (0.0264) time: 3.6630 data: 0.0028 max mem: 19788 +Epoch: [24] [ 800/2138] eta: 1:22:49 lr: 2.1456694151867598e-05 loss: 0.0239 (0.0263) time: 3.6850 data: 0.0028 max mem: 19788 +Epoch: [24] [ 810/2138] eta: 1:22:11 lr: 2.145091353289701e-05 loss: 0.0226 (0.0263) time: 3.6790 data: 0.0028 max mem: 19788 +Epoch: [24] [ 820/2138] eta: 1:21:33 lr: 2.1445132740835863e-05 loss: 0.0249 (0.0264) time: 3.6470 data: 0.0029 max mem: 19788 +Epoch: [24] [ 830/2138] eta: 1:20:56 lr: 2.1439351775627117e-05 loss: 0.0201 (0.0263) time: 3.6720 data: 0.0032 max mem: 19788 +Epoch: [24] [ 840/2138] eta: 1:20:17 lr: 2.1433570637213717e-05 loss: 0.0208 (0.0263) time: 3.6726 data: 0.0032 max mem: 19788 +Epoch: [24] [ 850/2138] eta: 1:19:39 lr: 2.142778932553855e-05 loss: 0.0213 (0.0262) time: 3.6461 data: 0.0031 max mem: 19788 +Epoch: [24] [ 860/2138] eta: 1:19:02 lr: 2.1422007840544497e-05 loss: 0.0219 (0.0262) time: 3.6712 data: 0.0031 max mem: 19788 +Epoch: [24] [ 870/2138] eta: 1:18:26 lr: 2.141622618217437e-05 loss: 0.0268 (0.0263) time: 3.7319 data: 0.0029 max mem: 19788 +Epoch: [24] [ 880/2138] eta: 1:17:56 lr: 2.1410444350370965e-05 loss: 0.0251 (0.0263) time: 3.9975 data: 0.0028 max mem: 19788 +Epoch: [24] [ 890/2138] eta: 1:17:19 lr: 2.1404662345077033e-05 loss: 0.0249 (0.0263) time: 3.9620 data: 0.0029 max mem: 19788 +Epoch: [24] [ 900/2138] eta: 1:16:40 lr: 2.1398880166235306e-05 loss: 0.0261 (0.0264) time: 3.6685 data: 0.0028 max mem: 19788 +Epoch: [24] [ 910/2138] eta: 1:16:03 lr: 2.139309781378845e-05 loss: 0.0240 (0.0263) time: 3.6558 data: 0.0032 max mem: 19788 +Epoch: [24] [ 920/2138] eta: 1:15:24 lr: 2.138731528767913e-05 loss: 0.0223 (0.0263) time: 3.6551 data: 0.0032 max mem: 19788 +Epoch: [24] [ 930/2138] eta: 1:14:48 lr: 2.138153258784994e-05 loss: 0.0223 (0.0263) time: 3.6982 data: 0.0030 max mem: 19788 +Epoch: [24] [ 940/2138] eta: 1:14:10 lr: 2.137574971424347e-05 loss: 0.0259 (0.0263) time: 3.7147 data: 0.0028 max mem: 19788 +Epoch: [24] [ 950/2138] eta: 1:13:32 lr: 2.136996666680225e-05 loss: 0.0244 (0.0263) time: 3.6460 data: 0.0027 max mem: 19788 +Epoch: [24] [ 960/2138] eta: 1:12:54 lr: 2.1364183445468774e-05 loss: 0.0243 (0.0264) time: 3.6522 data: 0.0027 max mem: 19788 +Epoch: [24] [ 970/2138] eta: 1:12:17 lr: 2.1358400050185522e-05 loss: 0.0243 (0.0264) time: 3.6774 data: 0.0031 max mem: 19788 +Epoch: [24] [ 980/2138] eta: 1:11:38 lr: 2.1352616480894912e-05 loss: 0.0220 (0.0263) time: 3.6511 data: 0.0031 max mem: 19788 +Epoch: [24] [ 990/2138] eta: 1:11:00 lr: 2.134683273753935e-05 loss: 0.0240 (0.0264) time: 3.6272 data: 0.0027 max mem: 19788 +Epoch: [24] [1000/2138] eta: 1:10:22 lr: 2.134104882006118e-05 loss: 0.0286 (0.0264) time: 3.6225 data: 0.0029 max mem: 19788 +Epoch: [24] [1010/2138] eta: 1:09:44 lr: 2.1335264728402727e-05 loss: 0.0247 (0.0265) time: 3.6330 data: 0.0031 max mem: 19788 +Epoch: [24] [1020/2138] eta: 1:09:07 lr: 2.1329480462506276e-05 loss: 0.0232 (0.0264) time: 3.6877 data: 0.0031 max mem: 19788 +Epoch: [24] [1030/2138] eta: 1:08:31 lr: 2.1323696022314073e-05 loss: 0.0232 (0.0264) time: 3.7435 data: 0.0032 max mem: 19788 +Epoch: [24] [1040/2138] eta: 1:07:54 lr: 2.1317911407768327e-05 loss: 0.0274 (0.0264) time: 3.7425 data: 0.0034 max mem: 19788 +Epoch: [24] [1050/2138] eta: 1:07:16 lr: 2.1312126618811216e-05 loss: 0.0258 (0.0264) time: 3.6937 data: 0.0033 max mem: 19788 +Epoch: [24] [1060/2138] eta: 1:06:39 lr: 2.1306341655384867e-05 loss: 0.0257 (0.0264) time: 3.6559 data: 0.0032 max mem: 19788 +Epoch: [24] [1070/2138] eta: 1:06:02 lr: 2.1300556517431398e-05 loss: 0.0252 (0.0264) time: 3.6904 data: 0.0032 max mem: 19788 +Epoch: [24] [1080/2138] eta: 1:05:25 lr: 2.129477120489285e-05 loss: 0.0252 (0.0264) time: 3.7540 data: 0.0034 max mem: 19788 +Epoch: [24] [1090/2138] eta: 1:04:47 lr: 2.1288985717711275e-05 loss: 0.0264 (0.0264) time: 3.7059 data: 0.0033 max mem: 19788 +Epoch: [24] [1100/2138] eta: 1:04:10 lr: 2.1283200055828646e-05 loss: 0.0270 (0.0265) time: 3.6736 data: 0.0031 max mem: 19788 +Epoch: [24] [1110/2138] eta: 1:03:33 lr: 2.1277414219186925e-05 loss: 0.0246 (0.0264) time: 3.6942 data: 0.0029 max mem: 19788 +Epoch: [24] [1120/2138] eta: 1:02:56 lr: 2.127162820772802e-05 loss: 0.0215 (0.0264) time: 3.6759 data: 0.0030 max mem: 19788 +Epoch: [24] [1130/2138] eta: 1:02:18 lr: 2.1265842021393823e-05 loss: 0.0265 (0.0264) time: 3.6522 data: 0.0032 max mem: 19788 +Epoch: [24] [1140/2138] eta: 1:01:41 lr: 2.1260055660126166e-05 loss: 0.0272 (0.0264) time: 3.6651 data: 0.0029 max mem: 19788 +Epoch: [24] [1150/2138] eta: 1:01:03 lr: 2.1254269123866865e-05 loss: 0.0260 (0.0264) time: 3.6918 data: 0.0027 max mem: 19788 +Epoch: [24] [1160/2138] eta: 1:00:25 lr: 2.124848241255768e-05 loss: 0.0243 (0.0265) time: 3.6535 data: 0.0029 max mem: 19788 +Epoch: [24] [1170/2138] eta: 0:59:49 lr: 2.124269552614035e-05 loss: 0.0256 (0.0265) time: 3.6750 data: 0.0032 max mem: 19788 +Epoch: [24] [1180/2138] eta: 0:59:11 lr: 2.1236908464556567e-05 loss: 0.0268 (0.0265) time: 3.6934 data: 0.0032 max mem: 19788 +Epoch: [24] [1190/2138] eta: 0:58:34 lr: 2.123112122774799e-05 loss: 0.0246 (0.0265) time: 3.6581 data: 0.0029 max mem: 19788 +Epoch: [24] [1200/2138] eta: 0:57:57 lr: 2.1225333815656236e-05 loss: 0.0245 (0.0265) time: 3.6922 data: 0.0029 max mem: 19788 +Epoch: [24] [1210/2138] eta: 0:57:19 lr: 2.12195462282229e-05 loss: 0.0250 (0.0265) time: 3.6935 data: 0.0030 max mem: 19788 +Epoch: [24] [1220/2138] eta: 0:56:42 lr: 2.1213758465389512e-05 loss: 0.0251 (0.0265) time: 3.6848 data: 0.0030 max mem: 19788 +Epoch: [24] [1230/2138] eta: 0:56:05 lr: 2.1207970527097594e-05 loss: 0.0251 (0.0265) time: 3.7254 data: 0.0031 max mem: 19788 +Epoch: [24] [1240/2138] eta: 0:55:29 lr: 2.1202182413288614e-05 loss: 0.0270 (0.0265) time: 3.7373 data: 0.0030 max mem: 19788 +Epoch: [24] [1250/2138] eta: 0:54:52 lr: 2.119639412390401e-05 loss: 0.0229 (0.0265) time: 3.7299 data: 0.0029 max mem: 19788 +Epoch: [24] [1260/2138] eta: 0:54:14 lr: 2.1190605658885175e-05 loss: 0.0209 (0.0265) time: 3.6767 data: 0.0028 max mem: 19788 +Epoch: [24] [1270/2138] eta: 0:53:36 lr: 2.1184817018173465e-05 loss: 0.0230 (0.0266) time: 3.6320 data: 0.0026 max mem: 19788 +Epoch: [24] [1280/2138] eta: 0:52:59 lr: 2.117902820171022e-05 loss: 0.0254 (0.0266) time: 3.6642 data: 0.0028 max mem: 19788 +Epoch: [24] [1290/2138] eta: 0:52:22 lr: 2.11732392094367e-05 loss: 0.0234 (0.0266) time: 3.6998 data: 0.0028 max mem: 19788 +Epoch: [24] [1300/2138] eta: 0:51:45 lr: 2.1167450041294178e-05 loss: 0.0243 (0.0266) time: 3.6762 data: 0.0030 max mem: 19788 +Epoch: [24] [1310/2138] eta: 0:51:07 lr: 2.116166069722385e-05 loss: 0.0247 (0.0266) time: 3.6484 data: 0.0029 max mem: 19788 +Epoch: [24] [1320/2138] eta: 0:50:30 lr: 2.1155871177166894e-05 loss: 0.0272 (0.0266) time: 3.6906 data: 0.0028 max mem: 19788 +Epoch: [24] [1330/2138] eta: 0:49:53 lr: 2.115008148106444e-05 loss: 0.0255 (0.0266) time: 3.7205 data: 0.0029 max mem: 19788 +Epoch: [24] [1340/2138] eta: 0:49:16 lr: 2.1144291608857595e-05 loss: 0.0242 (0.0267) time: 3.6672 data: 0.0028 max mem: 19788 +Epoch: [24] [1350/2138] eta: 0:48:39 lr: 2.1138501560487407e-05 loss: 0.0313 (0.0267) time: 3.6444 data: 0.0027 max mem: 19788 +Epoch: [24] [1360/2138] eta: 0:48:02 lr: 2.113271133589491e-05 loss: 0.0293 (0.0267) time: 3.7091 data: 0.0028 max mem: 19788 +Epoch: [24] [1370/2138] eta: 0:47:24 lr: 2.1126920935021077e-05 loss: 0.0255 (0.0267) time: 3.7012 data: 0.0028 max mem: 19788 +Epoch: [24] [1380/2138] eta: 0:46:47 lr: 2.112113035780687e-05 loss: 0.0254 (0.0267) time: 3.6395 data: 0.0028 max mem: 19788 +Epoch: [24] [1390/2138] eta: 0:46:10 lr: 2.1115339604193183e-05 loss: 0.0288 (0.0267) time: 3.6283 data: 0.0028 max mem: 19788 +Epoch: [24] [1400/2138] eta: 0:45:32 lr: 2.1109548674120898e-05 loss: 0.0261 (0.0268) time: 3.6282 data: 0.0026 max mem: 19788 +Epoch: [24] [1410/2138] eta: 0:44:55 lr: 2.110375756753084e-05 loss: 0.0256 (0.0267) time: 3.6350 data: 0.0026 max mem: 19788 +Epoch: [24] [1420/2138] eta: 0:44:18 lr: 2.1097966284363815e-05 loss: 0.0260 (0.0268) time: 3.6922 data: 0.0027 max mem: 19788 +Epoch: [24] [1430/2138] eta: 0:43:41 lr: 2.109217482456057e-05 loss: 0.0260 (0.0267) time: 3.7028 data: 0.0027 max mem: 19788 +Epoch: [24] [1440/2138] eta: 0:43:03 lr: 2.108638318806184e-05 loss: 0.0243 (0.0267) time: 3.6475 data: 0.0029 max mem: 19788 +Epoch: [24] [1450/2138] eta: 0:42:27 lr: 2.1080591374808283e-05 loss: 0.0277 (0.0268) time: 3.7316 data: 0.0031 max mem: 19788 +Epoch: [24] [1460/2138] eta: 0:41:50 lr: 2.1074799384740567e-05 loss: 0.0292 (0.0268) time: 3.7415 data: 0.0029 max mem: 19788 +Epoch: [24] [1470/2138] eta: 0:41:12 lr: 2.106900721779928e-05 loss: 0.0278 (0.0268) time: 3.6455 data: 0.0027 max mem: 19788 +Epoch: [24] [1480/2138] eta: 0:40:35 lr: 2.1063214873925003e-05 loss: 0.0277 (0.0268) time: 3.6371 data: 0.0028 max mem: 19788 +Epoch: [24] [1490/2138] eta: 0:39:58 lr: 2.105742235305825e-05 loss: 0.0277 (0.0268) time: 3.6343 data: 0.0029 max mem: 19788 +Epoch: [24] [1500/2138] eta: 0:39:21 lr: 2.105162965513953e-05 loss: 0.0287 (0.0268) time: 3.6376 data: 0.0029 max mem: 19788 +Epoch: [24] [1510/2138] eta: 0:38:44 lr: 2.1045836780109284e-05 loss: 0.0293 (0.0268) time: 3.6772 data: 0.0030 max mem: 19788 +Epoch: [24] [1520/2138] eta: 0:38:07 lr: 2.104004372790793e-05 loss: 0.0236 (0.0268) time: 3.7360 data: 0.0031 max mem: 19788 +Epoch: [24] [1530/2138] eta: 0:37:30 lr: 2.1034250498475843e-05 loss: 0.0213 (0.0268) time: 3.7008 data: 0.0030 max mem: 19788 +Epoch: [24] [1540/2138] eta: 0:36:52 lr: 2.1028457091753366e-05 loss: 0.0227 (0.0268) time: 3.6364 data: 0.0030 max mem: 19788 +Epoch: [24] [1550/2138] eta: 0:36:15 lr: 2.1022663507680794e-05 loss: 0.0238 (0.0268) time: 3.6362 data: 0.0030 max mem: 19788 +Epoch: [24] [1560/2138] eta: 0:35:38 lr: 2.1016869746198395e-05 loss: 0.0249 (0.0268) time: 3.6539 data: 0.0028 max mem: 19788 +Epoch: [24] [1570/2138] eta: 0:35:01 lr: 2.1011075807246384e-05 loss: 0.0249 (0.0268) time: 3.6660 data: 0.0027 max mem: 19788 +Epoch: [24] [1580/2138] eta: 0:34:24 lr: 2.100528169076495e-05 loss: 0.0229 (0.0268) time: 3.6513 data: 0.0029 max mem: 19788 +Epoch: [24] [1590/2138] eta: 0:33:46 lr: 2.099948739669424e-05 loss: 0.0230 (0.0268) time: 3.6378 data: 0.0032 max mem: 19788 +Epoch: [24] [1600/2138] eta: 0:33:10 lr: 2.0993692924974354e-05 loss: 0.0288 (0.0268) time: 3.6862 data: 0.0030 max mem: 19788 +Epoch: [24] [1610/2138] eta: 0:32:32 lr: 2.098789827554537e-05 loss: 0.0258 (0.0268) time: 3.6924 data: 0.0029 max mem: 19788 +Epoch: [24] [1620/2138] eta: 0:31:55 lr: 2.098210344834731e-05 loss: 0.0231 (0.0268) time: 3.6426 data: 0.0029 max mem: 19788 +Epoch: [24] [1630/2138] eta: 0:31:18 lr: 2.097630844332018e-05 loss: 0.0253 (0.0268) time: 3.6336 data: 0.0029 max mem: 19788 +Epoch: [24] [1640/2138] eta: 0:30:41 lr: 2.0970513260403916e-05 loss: 0.0234 (0.0268) time: 3.6392 data: 0.0029 max mem: 19788 +Epoch: [24] [1650/2138] eta: 0:30:04 lr: 2.0964717899538445e-05 loss: 0.0217 (0.0268) time: 3.6859 data: 0.0029 max mem: 19788 +Epoch: [24] [1660/2138] eta: 0:29:27 lr: 2.0958922360663634e-05 loss: 0.0229 (0.0267) time: 3.6758 data: 0.0031 max mem: 19788 +Epoch: [24] [1670/2138] eta: 0:28:50 lr: 2.0953126643719326e-05 loss: 0.0235 (0.0267) time: 3.6341 data: 0.0030 max mem: 19788 +Epoch: [24] [1680/2138] eta: 0:28:13 lr: 2.094733074864531e-05 loss: 0.0259 (0.0267) time: 3.6735 data: 0.0029 max mem: 19788 +Epoch: [24] [1690/2138] eta: 0:27:36 lr: 2.094153467538136e-05 loss: 0.0264 (0.0267) time: 3.6987 data: 0.0030 max mem: 19788 +Epoch: [24] [1700/2138] eta: 0:26:59 lr: 2.0935738423867183e-05 loss: 0.0239 (0.0267) time: 3.6637 data: 0.0029 max mem: 19788 +Epoch: [24] [1710/2138] eta: 0:26:22 lr: 2.0929941994042467e-05 loss: 0.0239 (0.0267) time: 3.6629 data: 0.0030 max mem: 19788 +Epoch: [24] [1720/2138] eta: 0:25:45 lr: 2.0924145385846847e-05 loss: 0.0239 (0.0267) time: 3.6892 data: 0.0032 max mem: 19788 +Epoch: [24] [1730/2138] eta: 0:25:08 lr: 2.091834859921994e-05 loss: 0.0263 (0.0268) time: 3.6565 data: 0.0031 max mem: 19788 +Epoch: [24] [1740/2138] eta: 0:24:30 lr: 2.091255163410129e-05 loss: 0.0267 (0.0268) time: 3.6254 data: 0.0028 max mem: 19788 +Epoch: [24] [1750/2138] eta: 0:23:53 lr: 2.0906754490430445e-05 loss: 0.0301 (0.0268) time: 3.6298 data: 0.0031 max mem: 19788 +Epoch: [24] [1760/2138] eta: 0:23:16 lr: 2.090095716814687e-05 loss: 0.0303 (0.0268) time: 3.6335 data: 0.0034 max mem: 19788 +Epoch: [24] [1770/2138] eta: 0:22:39 lr: 2.0895159667190028e-05 loss: 0.0255 (0.0268) time: 3.6325 data: 0.0029 max mem: 19788 +Epoch: [24] [1780/2138] eta: 0:22:02 lr: 2.0889361987499315e-05 loss: 0.0241 (0.0268) time: 3.6297 data: 0.0026 max mem: 19788 +Epoch: [24] [1790/2138] eta: 0:21:25 lr: 2.0883564129014108e-05 loss: 0.0249 (0.0268) time: 3.6298 data: 0.0027 max mem: 19788 +Epoch: [24] [1800/2138] eta: 0:20:48 lr: 2.0877766091673724e-05 loss: 0.0253 (0.0268) time: 3.6276 data: 0.0028 max mem: 19788 +Epoch: [24] [1810/2138] eta: 0:20:11 lr: 2.087196787541747e-05 loss: 0.0255 (0.0268) time: 3.6268 data: 0.0028 max mem: 19788 +Epoch: [24] [1820/2138] eta: 0:19:34 lr: 2.0866169480184583e-05 loss: 0.0250 (0.0268) time: 3.6316 data: 0.0027 max mem: 19788 +Epoch: [24] [1830/2138] eta: 0:18:57 lr: 2.0860370905914282e-05 loss: 0.0248 (0.0268) time: 3.6342 data: 0.0026 max mem: 19788 +Epoch: [24] [1840/2138] eta: 0:18:20 lr: 2.085457215254573e-05 loss: 0.0266 (0.0269) time: 3.6352 data: 0.0026 max mem: 19788 +Epoch: [24] [1850/2138] eta: 0:17:43 lr: 2.084877322001807e-05 loss: 0.0285 (0.0269) time: 3.6333 data: 0.0028 max mem: 19788 +Epoch: [24] [1860/2138] eta: 0:17:06 lr: 2.084297410827038e-05 loss: 0.0285 (0.0270) time: 3.6329 data: 0.0029 max mem: 19788 +Epoch: [24] [1870/2138] eta: 0:16:29 lr: 2.083717481724173e-05 loss: 0.0273 (0.0270) time: 3.6338 data: 0.0027 max mem: 19788 +Epoch: [24] [1880/2138] eta: 0:15:52 lr: 2.0831375346871122e-05 loss: 0.0268 (0.0270) time: 3.6286 data: 0.0028 max mem: 19788 +Epoch: [24] [1890/2138] eta: 0:15:15 lr: 2.0825575697097532e-05 loss: 0.0258 (0.0270) time: 3.6302 data: 0.0031 max mem: 19788 +Epoch: [24] [1900/2138] eta: 0:14:38 lr: 2.0819775867859897e-05 loss: 0.0246 (0.0270) time: 3.6359 data: 0.0030 max mem: 19788 +Epoch: [24] [1910/2138] eta: 0:14:01 lr: 2.0813975859097108e-05 loss: 0.0246 (0.0270) time: 3.6350 data: 0.0027 max mem: 19788 +Epoch: [24] [1920/2138] eta: 0:13:24 lr: 2.0808175670748023e-05 loss: 0.0231 (0.0269) time: 3.6326 data: 0.0026 max mem: 19788 +Epoch: [24] [1930/2138] eta: 0:12:47 lr: 2.080237530275145e-05 loss: 0.0237 (0.0269) time: 3.6305 data: 0.0028 max mem: 19788 +Epoch: [24] [1940/2138] eta: 0:12:10 lr: 2.0796574755046178e-05 loss: 0.0252 (0.0270) time: 3.6282 data: 0.0028 max mem: 19788 +Epoch: [24] [1950/2138] eta: 0:11:33 lr: 2.0790774027570926e-05 loss: 0.0251 (0.0269) time: 3.6273 data: 0.0029 max mem: 19788 +Epoch: [24] [1960/2138] eta: 0:10:56 lr: 2.0784973120264402e-05 loss: 0.0227 (0.0269) time: 3.6263 data: 0.0029 max mem: 19788 +Epoch: [24] [1970/2138] eta: 0:10:19 lr: 2.0779172033065255e-05 loss: 0.0236 (0.0269) time: 3.6268 data: 0.0028 max mem: 19788 +Epoch: [24] [1980/2138] eta: 0:09:42 lr: 2.0773370765912105e-05 loss: 0.0228 (0.0269) time: 3.6290 data: 0.0028 max mem: 19788 +Epoch: [24] [1990/2138] eta: 0:09:05 lr: 2.0767569318743522e-05 loss: 0.0230 (0.0269) time: 3.6295 data: 0.0029 max mem: 19788 +Epoch: [24] [2000/2138] eta: 0:08:28 lr: 2.076176769149805e-05 loss: 0.0246 (0.0269) time: 3.6349 data: 0.0027 max mem: 19788 +Epoch: [24] [2010/2138] eta: 0:07:51 lr: 2.0755965884114173e-05 loss: 0.0264 (0.0269) time: 3.6393 data: 0.0026 max mem: 19788 +Epoch: [24] [2020/2138] eta: 0:07:15 lr: 2.0750163896530356e-05 loss: 0.0269 (0.0269) time: 3.6395 data: 0.0025 max mem: 19788 +Epoch: [24] [2030/2138] eta: 0:06:38 lr: 2.0744361728685007e-05 loss: 0.0264 (0.0269) time: 3.6378 data: 0.0027 max mem: 19788 +Epoch: [24] [2040/2138] eta: 0:06:01 lr: 2.0738559380516513e-05 loss: 0.0248 (0.0269) time: 3.6340 data: 0.0028 max mem: 19788 +Epoch: [24] [2050/2138] eta: 0:05:24 lr: 2.073275685196319e-05 loss: 0.0248 (0.0269) time: 3.6312 data: 0.0027 max mem: 19788 +Epoch: [24] [2060/2138] eta: 0:04:47 lr: 2.072695414296335e-05 loss: 0.0246 (0.0269) time: 3.6314 data: 0.0029 max mem: 19788 +Epoch: [24] [2070/2138] eta: 0:04:10 lr: 2.0721151253455233e-05 loss: 0.0240 (0.0269) time: 3.6341 data: 0.0029 max mem: 19788 +Epoch: [24] [2080/2138] eta: 0:03:33 lr: 2.071534818337707e-05 loss: 0.0269 (0.0269) time: 3.6351 data: 0.0028 max mem: 19788 +Epoch: [24] [2090/2138] eta: 0:02:56 lr: 2.0709544932667015e-05 loss: 0.0243 (0.0269) time: 3.6360 data: 0.0029 max mem: 19788 +Epoch: [24] [2100/2138] eta: 0:02:20 lr: 2.0703741501263217e-05 loss: 0.0243 (0.0269) time: 3.6347 data: 0.0030 max mem: 19788 +Epoch: [24] [2110/2138] eta: 0:01:43 lr: 2.0697937889103757e-05 loss: 0.0278 (0.0269) time: 3.6335 data: 0.0030 max mem: 19788 +Epoch: [24] [2120/2138] eta: 0:01:06 lr: 2.06921340961267e-05 loss: 0.0308 (0.0269) time: 3.6316 data: 0.0028 max mem: 19788 +Epoch: [24] [2130/2138] eta: 0:00:29 lr: 2.0686330122270044e-05 loss: 0.0261 (0.0269) time: 3.6210 data: 0.0028 max mem: 19788 +Epoch: [24] Total time: 2:11:16 +Test: [ 0/21770] eta: 20:05:04 time: 3.3213 data: 3.2123 max mem: 19788 +Test: [ 100/21770] eta: 0:34:38 time: 0.0719 data: 0.0021 max mem: 19788 +Test: [ 200/21770] eta: 0:28:35 time: 0.0616 data: 0.0018 max mem: 19788 +Test: [ 300/21770] eta: 0:26:35 time: 0.0643 data: 0.0019 max mem: 19788 +Test: [ 400/21770] eta: 0:25:46 time: 0.0643 data: 0.0020 max mem: 19788 +Test: [ 500/21770] eta: 0:25:18 time: 0.0676 data: 0.0018 max mem: 19788 +Test: [ 600/21770] eta: 0:25:05 time: 0.0673 data: 0.0018 max mem: 19788 +Test: [ 700/21770] eta: 0:24:37 time: 0.0608 data: 0.0020 max mem: 19788 +Test: [ 800/21770] eta: 0:24:11 time: 0.0649 data: 0.0020 max mem: 19788 +Test: [ 900/21770] eta: 0:23:54 time: 0.0808 data: 0.0023 max mem: 19788 +Test: [ 1000/21770] eta: 0:23:46 time: 0.0609 data: 0.0016 max mem: 19788 +Test: [ 1100/21770] eta: 0:23:27 time: 0.0627 data: 0.0018 max mem: 19788 +Test: [ 1200/21770] eta: 0:23:23 time: 0.0817 data: 0.0025 max mem: 19788 +Test: [ 1300/21770] eta: 0:23:18 time: 0.0712 data: 0.0022 max mem: 19788 +Test: [ 1400/21770] eta: 0:23:09 time: 0.0606 data: 0.0020 max mem: 19788 +Test: [ 1500/21770] eta: 0:22:55 time: 0.0626 data: 0.0019 max mem: 19788 +Test: [ 1600/21770] eta: 0:22:50 time: 0.0602 data: 0.0018 max mem: 19788 +Test: [ 1700/21770] eta: 0:22:37 time: 0.0704 data: 0.0021 max mem: 19788 +Test: [ 1800/21770] eta: 0:22:31 time: 0.0669 data: 0.0021 max mem: 19788 +Test: [ 1900/21770] eta: 0:22:20 time: 0.0666 data: 0.0021 max mem: 19788 +Test: [ 2000/21770] eta: 0:22:15 time: 0.0783 data: 0.0023 max mem: 19788 +Test: [ 2100/21770] eta: 0:22:03 time: 0.0585 data: 0.0016 max mem: 19788 +Test: [ 2200/21770] eta: 0:22:01 time: 0.0612 data: 0.0018 max mem: 19788 +Test: [ 2300/21770] eta: 0:21:51 time: 0.0589 data: 0.0017 max mem: 19788 +Test: [ 2400/21770] eta: 0:21:43 time: 0.0744 data: 0.0022 max mem: 19788 +Test: [ 2500/21770] eta: 0:21:35 time: 0.0696 data: 0.0021 max mem: 19788 +Test: [ 2600/21770] eta: 0:21:26 time: 0.0622 data: 0.0018 max mem: 19788 +Test: [ 2700/21770] eta: 0:21:18 time: 0.0615 data: 0.0020 max mem: 19788 +Test: [ 2800/21770] eta: 0:21:09 time: 0.0635 data: 0.0018 max mem: 19788 +Test: [ 2900/21770] eta: 0:21:07 time: 0.0657 data: 0.0021 max mem: 19788 +Test: [ 3000/21770] eta: 0:21:01 time: 0.0627 data: 0.0020 max mem: 19788 +Test: [ 3100/21770] eta: 0:20:52 time: 0.0615 data: 0.0018 max mem: 19788 +Test: [ 3200/21770] eta: 0:20:45 time: 0.0614 data: 0.0018 max mem: 19788 +Test: [ 3300/21770] eta: 0:20:37 time: 0.0661 data: 0.0021 max mem: 19788 +Test: [ 3400/21770] eta: 0:20:29 time: 0.0618 data: 0.0019 max mem: 19788 +Test: [ 3500/21770] eta: 0:20:22 time: 0.0644 data: 0.0021 max mem: 19788 +Test: [ 3600/21770] eta: 0:20:16 time: 0.0662 data: 0.0020 max mem: 19788 +Test: [ 3700/21770] eta: 0:20:10 time: 0.0613 data: 0.0018 max mem: 19788 +Test: [ 3800/21770] eta: 0:20:02 time: 0.0602 data: 0.0018 max mem: 19788 +Test: [ 3900/21770] eta: 0:19:59 time: 0.0645 data: 0.0018 max mem: 19788 +Test: [ 4000/21770] eta: 0:19:52 time: 0.0661 data: 0.0019 max mem: 19788 +Test: [ 4100/21770] eta: 0:19:43 time: 0.0698 data: 0.0018 max mem: 19788 +Test: [ 4200/21770] eta: 0:19:35 time: 0.0638 data: 0.0017 max mem: 19788 +Test: [ 4300/21770] eta: 0:19:29 time: 0.0695 data: 0.0020 max mem: 19788 +Test: [ 4400/21770] eta: 0:19:21 time: 0.0645 data: 0.0017 max mem: 19788 +Test: [ 4500/21770] eta: 0:19:15 time: 0.0728 data: 0.0019 max mem: 19788 +Test: [ 4600/21770] eta: 0:19:09 time: 0.0628 data: 0.0017 max mem: 19788 +Test: [ 4700/21770] eta: 0:19:02 time: 0.0645 data: 0.0018 max mem: 19788 +Test: [ 4800/21770] eta: 0:18:54 time: 0.0593 data: 0.0017 max mem: 19788 +Test: [ 4900/21770] eta: 0:18:47 time: 0.0690 data: 0.0019 max mem: 19788 +Test: [ 5000/21770] eta: 0:18:40 time: 0.0627 data: 0.0018 max mem: 19788 +Test: [ 5100/21770] eta: 0:18:33 time: 0.0653 data: 0.0021 max mem: 19788 +Test: [ 5200/21770] eta: 0:18:25 time: 0.0657 data: 0.0019 max mem: 19788 +Test: [ 5300/21770] eta: 0:18:18 time: 0.0630 data: 0.0019 max mem: 19788 +Test: [ 5400/21770] eta: 0:18:11 time: 0.0742 data: 0.0020 max mem: 19788 +Test: [ 5500/21770] eta: 0:18:04 time: 0.0692 data: 0.0020 max mem: 19788 +Test: [ 5600/21770] eta: 0:17:58 time: 0.0771 data: 0.0020 max mem: 19788 +Test: [ 5700/21770] eta: 0:17:51 time: 0.0660 data: 0.0021 max mem: 19788 +Test: [ 5800/21770] eta: 0:17:45 time: 0.0761 data: 0.0024 max mem: 19788 +Test: [ 5900/21770] eta: 0:17:41 time: 0.0667 data: 0.0021 max mem: 19788 +Test: [ 6000/21770] eta: 0:17:33 time: 0.0572 data: 0.0017 max mem: 19788 +Test: [ 6100/21770] eta: 0:17:27 time: 0.0632 data: 0.0020 max mem: 19788 +Test: [ 6200/21770] eta: 0:17:22 time: 0.0826 data: 0.0022 max mem: 19788 +Test: [ 6300/21770] eta: 0:17:15 time: 0.0768 data: 0.0023 max mem: 19788 +Test: [ 6400/21770] eta: 0:17:09 time: 0.0652 data: 0.0020 max mem: 19788 +Test: [ 6500/21770] eta: 0:17:03 time: 0.0607 data: 0.0016 max mem: 19788 +Test: [ 6600/21770] eta: 0:16:55 time: 0.0626 data: 0.0016 max mem: 19788 +Test: [ 6700/21770] eta: 0:16:48 time: 0.0653 data: 0.0020 max mem: 19788 +Test: [ 6800/21770] eta: 0:16:40 time: 0.0608 data: 0.0018 max mem: 19788 +Test: [ 6900/21770] eta: 0:16:34 time: 0.0728 data: 0.0020 max mem: 19788 +Test: [ 7000/21770] eta: 0:16:26 time: 0.0638 data: 0.0019 max mem: 19788 +Test: [ 7100/21770] eta: 0:16:19 time: 0.0616 data: 0.0018 max mem: 19788 +Test: [ 7200/21770] eta: 0:16:12 time: 0.0622 data: 0.0018 max mem: 19788 +Test: [ 7300/21770] eta: 0:16:07 time: 0.0612 data: 0.0018 max mem: 19788 +Test: [ 7400/21770] eta: 0:16:01 time: 0.0817 data: 0.0024 max mem: 19788 +Test: [ 7500/21770] eta: 0:15:55 time: 0.0669 data: 0.0021 max mem: 19788 +Test: [ 7600/21770] eta: 0:15:48 time: 0.0697 data: 0.0020 max mem: 19788 +Test: [ 7700/21770] eta: 0:15:42 time: 0.0702 data: 0.0020 max mem: 19788 +Test: [ 7800/21770] eta: 0:15:34 time: 0.0660 data: 0.0018 max mem: 19788 +Test: [ 7900/21770] eta: 0:15:27 time: 0.0625 data: 0.0019 max mem: 19788 +Test: [ 8000/21770] eta: 0:15:21 time: 0.0665 data: 0.0020 max mem: 19788 +Test: [ 8100/21770] eta: 0:15:14 time: 0.0683 data: 0.0020 max mem: 19788 +Test: [ 8200/21770] eta: 0:15:08 time: 0.0732 data: 0.0022 max mem: 19788 +Test: [ 8300/21770] eta: 0:15:02 time: 0.0662 data: 0.0019 max mem: 19788 +Test: [ 8400/21770] eta: 0:14:55 time: 0.0655 data: 0.0020 max mem: 19788 +Test: [ 8500/21770] eta: 0:14:48 time: 0.0743 data: 0.0022 max mem: 19788 +Test: [ 8600/21770] eta: 0:14:41 time: 0.0618 data: 0.0018 max mem: 19788 +Test: [ 8700/21770] eta: 0:14:34 time: 0.0609 data: 0.0018 max mem: 19788 +Test: [ 8800/21770] eta: 0:14:27 time: 0.0615 data: 0.0017 max mem: 19788 +Test: [ 8900/21770] eta: 0:14:20 time: 0.0608 data: 0.0018 max mem: 19788 +Test: [ 9000/21770] eta: 0:14:13 time: 0.0687 data: 0.0020 max mem: 19788 +Test: [ 9100/21770] eta: 0:14:06 time: 0.0622 data: 0.0019 max mem: 19788 +Test: [ 9200/21770] eta: 0:13:59 time: 0.0619 data: 0.0019 max mem: 19788 +Test: [ 9300/21770] eta: 0:13:52 time: 0.0620 data: 0.0019 max mem: 19788 +Test: [ 9400/21770] eta: 0:13:45 time: 0.0803 data: 0.0023 max mem: 19788 +Test: [ 9500/21770] eta: 0:13:39 time: 0.0678 data: 0.0018 max mem: 19788 +Test: [ 9600/21770] eta: 0:13:33 time: 0.0711 data: 0.0021 max mem: 19788 +Test: [ 9700/21770] eta: 0:13:26 time: 0.0608 data: 0.0018 max mem: 19788 +Test: [ 9800/21770] eta: 0:13:19 time: 0.0628 data: 0.0021 max mem: 19788 +Test: [ 9900/21770] eta: 0:13:12 time: 0.0802 data: 0.0020 max mem: 19788 +Test: [10000/21770] eta: 0:13:05 time: 0.0645 data: 0.0017 max mem: 19788 +Test: [10100/21770] eta: 0:12:59 time: 0.0596 data: 0.0018 max mem: 19788 +Test: [10200/21770] eta: 0:12:53 time: 0.0799 data: 0.0019 max mem: 19788 +Test: [10300/21770] eta: 0:12:46 time: 0.0628 data: 0.0017 max mem: 19788 +Test: [10400/21770] eta: 0:12:39 time: 0.0669 data: 0.0019 max mem: 19788 +Test: [10500/21770] eta: 0:12:33 time: 0.0800 data: 0.0019 max mem: 19788 +Test: [10600/21770] eta: 0:12:27 time: 0.0639 data: 0.0018 max mem: 19788 +Test: [10700/21770] eta: 0:12:20 time: 0.0714 data: 0.0021 max mem: 19788 +Test: [10800/21770] eta: 0:12:14 time: 0.0632 data: 0.0017 max mem: 19788 +Test: [10900/21770] eta: 0:12:07 time: 0.0724 data: 0.0021 max mem: 19788 +Test: [11000/21770] eta: 0:12:00 time: 0.0648 data: 0.0020 max mem: 19788 +Test: [11100/21770] eta: 0:11:54 time: 0.0814 data: 0.0024 max mem: 19788 +Test: [11200/21770] eta: 0:11:48 time: 0.0864 data: 0.0024 max mem: 19788 +Test: [11300/21770] eta: 0:11:42 time: 0.0762 data: 0.0019 max mem: 19788 +Test: [11400/21770] eta: 0:11:36 time: 0.0627 data: 0.0018 max mem: 19788 +Test: [11500/21770] eta: 0:11:29 time: 0.0653 data: 0.0020 max mem: 19788 +Test: [11600/21770] eta: 0:11:22 time: 0.0633 data: 0.0020 max mem: 19788 +Test: [11700/21770] eta: 0:11:15 time: 0.0718 data: 0.0021 max mem: 19788 +Test: [11800/21770] eta: 0:11:08 time: 0.0773 data: 0.0018 max mem: 19788 +Test: [11900/21770] eta: 0:11:02 time: 0.0653 data: 0.0019 max mem: 19788 +Test: [12000/21770] eta: 0:10:55 time: 0.0633 data: 0.0018 max mem: 19788 +Test: [12100/21770] eta: 0:10:49 time: 0.0751 data: 0.0023 max mem: 19788 +Test: [12200/21770] eta: 0:10:42 time: 0.0631 data: 0.0018 max mem: 19788 +Test: [12300/21770] eta: 0:10:35 time: 0.0637 data: 0.0019 max mem: 19788 +Test: [12400/21770] eta: 0:10:29 time: 0.0758 data: 0.0023 max mem: 19788 +Test: [12500/21770] eta: 0:10:23 time: 0.0638 data: 0.0020 max mem: 19788 +Test: [12600/21770] eta: 0:10:16 time: 0.0675 data: 0.0020 max mem: 19788 +Test: [12700/21770] eta: 0:10:09 time: 0.0797 data: 0.0018 max mem: 19788 +Test: [12800/21770] eta: 0:10:03 time: 0.0696 data: 0.0020 max mem: 19788 +Test: [12900/21770] eta: 0:09:56 time: 0.0582 data: 0.0018 max mem: 19788 +Test: [13000/21770] eta: 0:09:50 time: 0.0807 data: 0.0022 max mem: 19788 +Test: [13100/21770] eta: 0:09:43 time: 0.0684 data: 0.0019 max mem: 19788 +Test: [13200/21770] eta: 0:09:37 time: 0.0613 data: 0.0018 max mem: 19788 +Test: [13300/21770] eta: 0:09:30 time: 0.0624 data: 0.0018 max mem: 19788 +Test: [13400/21770] eta: 0:09:23 time: 0.0740 data: 0.0021 max mem: 19788 +Test: [13500/21770] eta: 0:09:17 time: 0.0634 data: 0.0016 max mem: 19788 +Test: [13600/21770] eta: 0:09:10 time: 0.0654 data: 0.0018 max mem: 19788 +Test: [13700/21770] eta: 0:09:03 time: 0.0637 data: 0.0017 max mem: 19788 +Test: [13800/21770] eta: 0:08:56 time: 0.0789 data: 0.0023 max mem: 19788 +Test: [13900/21770] eta: 0:08:50 time: 0.0655 data: 0.0018 max mem: 19788 +Test: [14000/21770] eta: 0:08:43 time: 0.0644 data: 0.0017 max mem: 19788 +Test: [14100/21770] eta: 0:08:36 time: 0.0657 data: 0.0018 max mem: 19788 +Test: [14200/21770] eta: 0:08:30 time: 0.0686 data: 0.0019 max mem: 19788 +Test: [14300/21770] eta: 0:08:23 time: 0.0725 data: 0.0018 max mem: 19788 +Test: [14400/21770] eta: 0:08:16 time: 0.0671 data: 0.0019 max mem: 19788 +Test: [14500/21770] eta: 0:08:10 time: 0.0793 data: 0.0025 max mem: 19788 +Test: [14600/21770] eta: 0:08:03 time: 0.0633 data: 0.0022 max mem: 19788 +Test: [14700/21770] eta: 0:07:56 time: 0.0775 data: 0.0023 max mem: 19788 +Test: [14800/21770] eta: 0:07:50 time: 0.0770 data: 0.0024 max mem: 19788 +Test: [14900/21770] eta: 0:07:43 time: 0.0621 data: 0.0019 max mem: 19788 +Test: [15000/21770] eta: 0:07:36 time: 0.0630 data: 0.0018 max mem: 19788 +Test: [15100/21770] eta: 0:07:30 time: 0.0814 data: 0.0024 max mem: 19788 +Test: [15200/21770] eta: 0:07:23 time: 0.0636 data: 0.0019 max mem: 19788 +Test: [15300/21770] eta: 0:07:16 time: 0.0713 data: 0.0019 max mem: 19788 +Test: [15400/21770] eta: 0:07:10 time: 0.0628 data: 0.0021 max mem: 19788 +Test: [15500/21770] eta: 0:07:03 time: 0.0776 data: 0.0021 max mem: 19788 +Test: [15600/21770] eta: 0:06:56 time: 0.0823 data: 0.0025 max mem: 19788 +Test: [15700/21770] eta: 0:06:50 time: 0.0678 data: 0.0020 max mem: 19788 +Test: [15800/21770] eta: 0:06:43 time: 0.0748 data: 0.0022 max mem: 19788 +Test: [15900/21770] eta: 0:06:36 time: 0.0658 data: 0.0019 max mem: 19788 +Test: [16000/21770] eta: 0:06:30 time: 0.0658 data: 0.0017 max mem: 19788 +Test: [16100/21770] eta: 0:06:23 time: 0.0626 data: 0.0017 max mem: 19788 +Test: [16200/21770] eta: 0:06:16 time: 0.0664 data: 0.0018 max mem: 19788 +Test: [16300/21770] eta: 0:06:10 time: 0.0633 data: 0.0019 max mem: 19788 +Test: [16400/21770] eta: 0:06:03 time: 0.0616 data: 0.0017 max mem: 19788 +Test: [16500/21770] eta: 0:05:56 time: 0.0665 data: 0.0019 max mem: 19788 +Test: [16600/21770] eta: 0:05:49 time: 0.0689 data: 0.0019 max mem: 19788 +Test: [16700/21770] eta: 0:05:43 time: 0.0781 data: 0.0023 max mem: 19788 +Test: [16800/21770] eta: 0:05:36 time: 0.0732 data: 0.0022 max mem: 19788 +Test: [16900/21770] eta: 0:05:29 time: 0.0655 data: 0.0017 max mem: 19788 +Test: [17000/21770] eta: 0:05:22 time: 0.0651 data: 0.0019 max mem: 19788 +Test: [17100/21770] eta: 0:05:16 time: 0.0617 data: 0.0021 max mem: 19788 +Test: [17200/21770] eta: 0:05:09 time: 0.0665 data: 0.0021 max mem: 19788 +Test: [17300/21770] eta: 0:05:02 time: 0.0592 data: 0.0018 max mem: 19788 +Test: [17400/21770] eta: 0:04:55 time: 0.0717 data: 0.0021 max mem: 19788 +Test: [17500/21770] eta: 0:04:48 time: 0.0654 data: 0.0018 max mem: 19788 +Test: [17600/21770] eta: 0:04:42 time: 0.0809 data: 0.0025 max mem: 19788 +Test: [17700/21770] eta: 0:04:35 time: 0.0709 data: 0.0019 max mem: 19788 +Test: [17800/21770] eta: 0:04:28 time: 0.0700 data: 0.0020 max mem: 19788 +Test: [17900/21770] eta: 0:04:21 time: 0.0661 data: 0.0018 max mem: 19788 +Test: [18000/21770] eta: 0:04:15 time: 0.0648 data: 0.0018 max mem: 19788 +Test: [18100/21770] eta: 0:04:08 time: 0.0627 data: 0.0020 max mem: 19788 +Test: [18200/21770] eta: 0:04:01 time: 0.0620 data: 0.0023 max mem: 19788 +Test: [18300/21770] eta: 0:03:54 time: 0.0622 data: 0.0017 max mem: 19788 +Test: [18400/21770] eta: 0:03:48 time: 0.0817 data: 0.0023 max mem: 19788 +Test: [18500/21770] eta: 0:03:41 time: 0.0613 data: 0.0019 max mem: 19788 +Test: [18600/21770] eta: 0:03:34 time: 0.0620 data: 0.0019 max mem: 19788 +Test: [18700/21770] eta: 0:03:27 time: 0.0637 data: 0.0019 max mem: 19788 +Test: [18800/21770] eta: 0:03:20 time: 0.0668 data: 0.0021 max mem: 19788 +Test: [18900/21770] eta: 0:03:14 time: 0.0670 data: 0.0019 max mem: 19788 +Test: [19000/21770] eta: 0:03:07 time: 0.0719 data: 0.0019 max mem: 19788 +Test: [19100/21770] eta: 0:03:00 time: 0.0631 data: 0.0018 max mem: 19788 +Test: [19200/21770] eta: 0:02:53 time: 0.0629 data: 0.0017 max mem: 19788 +Test: [19300/21770] eta: 0:02:47 time: 0.0608 data: 0.0018 max mem: 19788 +Test: [19400/21770] eta: 0:02:40 time: 0.0628 data: 0.0019 max mem: 19788 +Test: [19500/21770] eta: 0:02:33 time: 0.0654 data: 0.0019 max mem: 19788 +Test: [19600/21770] eta: 0:02:26 time: 0.0643 data: 0.0020 max mem: 19788 +Test: [19700/21770] eta: 0:02:19 time: 0.0683 data: 0.0021 max mem: 19788 +Test: [19800/21770] eta: 0:02:13 time: 0.0612 data: 0.0017 max mem: 19788 +Test: [19900/21770] eta: 0:02:06 time: 0.0624 data: 0.0019 max mem: 19788 +Test: [20000/21770] eta: 0:01:59 time: 0.0634 data: 0.0018 max mem: 19788 +Test: [20100/21770] eta: 0:01:52 time: 0.0803 data: 0.0020 max mem: 19788 +Test: [20200/21770] eta: 0:01:46 time: 0.0629 data: 0.0019 max mem: 19788 +Test: [20300/21770] eta: 0:01:39 time: 0.0757 data: 0.0023 max mem: 19788 +Test: [20400/21770] eta: 0:01:32 time: 0.0702 data: 0.0020 max mem: 19788 +Test: [20500/21770] eta: 0:01:25 time: 0.0728 data: 0.0018 max mem: 19788 +Test: [20600/21770] eta: 0:01:19 time: 0.0613 data: 0.0018 max mem: 19788 +Test: [20700/21770] eta: 0:01:12 time: 0.0622 data: 0.0017 max mem: 19788 +Test: [20800/21770] eta: 0:01:05 time: 0.0807 data: 0.0024 max mem: 19788 +Test: [20900/21770] eta: 0:00:58 time: 0.0710 data: 0.0020 max mem: 19788 +Test: [21000/21770] eta: 0:00:52 time: 0.0802 data: 0.0023 max mem: 19788 +Test: [21100/21770] eta: 0:00:45 time: 0.0765 data: 0.0022 max mem: 19788 +Test: [21200/21770] eta: 0:00:38 time: 0.0783 data: 0.0023 max mem: 19788 +Test: [21300/21770] eta: 0:00:31 time: 0.0674 data: 0.0019 max mem: 19788 +Test: [21400/21770] eta: 0:00:25 time: 0.0703 data: 0.0020 max mem: 19788 +Test: [21500/21770] eta: 0:00:18 time: 0.0802 data: 0.0024 max mem: 19788 +Test: [21600/21770] eta: 0:00:11 time: 0.0807 data: 0.0024 max mem: 19788 +Test: [21700/21770] eta: 0:00:04 time: 0.0677 data: 0.0018 max mem: 19788 +Test: Total time: 0:24:37 +Final results: +Mean IoU is 63.17 + + precision@0.5 = 70.04 + precision@0.6 = 64.61 + precision@0.7 = 58.02 + precision@0.8 = 47.75 + precision@0.9 = 23.55 + overall IoU = 63.96 + mean IoU = 63.17 + +Mean accuracy for one-to-zero sample is 84.01 + +Average object IoU 0.6317226231435514 +Overall IoU 63.95835876464844 +Better epoch: 24 + +Epoch: [25] [ 0/2138] eta: 5:10:11 lr: 2.068168681290973e-05 loss: 0.0259 (0.0259) time: 8.7049 data: 1.6139 max mem: 19788 +Epoch: [25] [ 10/2138] eta: 2:25:44 lr: 2.0675882513313462e-05 loss: 0.0244 (0.0254) time: 4.1095 data: 0.1490 max mem: 19788 +Epoch: [25] [ 20/2138] eta: 2:17:09 lr: 2.0670078032663827e-05 loss: 0.0213 (0.0234) time: 3.6447 data: 0.0023 max mem: 19788 +Epoch: [25] [ 30/2138] eta: 2:13:43 lr: 2.066427337089866e-05 loss: 0.0214 (0.0231) time: 3.6395 data: 0.0024 max mem: 19788 +Epoch: [25] [ 40/2138] eta: 2:11:38 lr: 2.0658468527955797e-05 loss: 0.0248 (0.0243) time: 3.6382 data: 0.0030 max mem: 19788 +Epoch: [25] [ 50/2138] eta: 2:10:08 lr: 2.0652663503773e-05 loss: 0.0255 (0.0256) time: 3.6369 data: 0.0031 max mem: 19788 +Epoch: [25] [ 60/2138] eta: 2:08:54 lr: 2.0646858298288015e-05 loss: 0.0218 (0.0249) time: 3.6335 data: 0.0027 max mem: 19788 +Epoch: [25] [ 70/2138] eta: 2:07:50 lr: 2.0641052911438527e-05 loss: 0.0187 (0.0245) time: 3.6316 data: 0.0027 max mem: 19788 +Epoch: [25] [ 80/2138] eta: 2:06:52 lr: 2.0635247343162195e-05 loss: 0.0219 (0.0256) time: 3.6286 data: 0.0028 max mem: 19788 +Epoch: [25] [ 90/2138] eta: 2:05:59 lr: 2.0629441593396627e-05 loss: 0.0245 (0.0265) time: 3.6255 data: 0.0030 max mem: 19788 +Epoch: [25] [ 100/2138] eta: 2:05:09 lr: 2.0623635662079396e-05 loss: 0.0248 (0.0263) time: 3.6278 data: 0.0030 max mem: 19788 +Epoch: [25] [ 110/2138] eta: 2:04:22 lr: 2.0617829549148028e-05 loss: 0.0241 (0.0262) time: 3.6301 data: 0.0029 max mem: 19788 +Epoch: [25] [ 120/2138] eta: 2:03:37 lr: 2.0612023254540023e-05 loss: 0.0241 (0.0262) time: 3.6295 data: 0.0029 max mem: 19788 +Epoch: [25] [ 130/2138] eta: 2:02:54 lr: 2.0606216778192818e-05 loss: 0.0251 (0.0262) time: 3.6313 data: 0.0029 max mem: 19788 +Epoch: [25] [ 140/2138] eta: 2:02:10 lr: 2.0600410120043824e-05 loss: 0.0260 (0.0260) time: 3.6291 data: 0.0028 max mem: 19788 +Epoch: [25] [ 150/2138] eta: 2:01:28 lr: 2.0594603280030406e-05 loss: 0.0225 (0.0258) time: 3.6262 data: 0.0029 max mem: 19788 +Epoch: [25] [ 160/2138] eta: 2:00:47 lr: 2.058879625808989e-05 loss: 0.0246 (0.0260) time: 3.6297 data: 0.0029 max mem: 19788 +Epoch: [25] [ 170/2138] eta: 2:00:06 lr: 2.0582989054159553e-05 loss: 0.0274 (0.0262) time: 3.6296 data: 0.0029 max mem: 19788 +Epoch: [25] [ 180/2138] eta: 1:59:27 lr: 2.057718166817665e-05 loss: 0.0274 (0.0261) time: 3.6308 data: 0.0027 max mem: 19788 +Epoch: [25] [ 190/2138] eta: 1:58:47 lr: 2.057137410007837e-05 loss: 0.0223 (0.0260) time: 3.6292 data: 0.0028 max mem: 19788 +Epoch: [25] [ 200/2138] eta: 1:58:07 lr: 2.056556634980188e-05 loss: 0.0209 (0.0258) time: 3.6253 data: 0.0029 max mem: 19788 +Epoch: [25] [ 210/2138] eta: 1:57:27 lr: 2.0559758417284287e-05 loss: 0.0263 (0.0261) time: 3.6245 data: 0.0031 max mem: 19788 +Epoch: [25] [ 220/2138] eta: 1:56:48 lr: 2.055395030246268e-05 loss: 0.0267 (0.0260) time: 3.6237 data: 0.0031 max mem: 19788 +Epoch: [25] [ 230/2138] eta: 1:56:09 lr: 2.0548142005274087e-05 loss: 0.0239 (0.0261) time: 3.6242 data: 0.0029 max mem: 19788 +Epoch: [25] [ 240/2138] eta: 1:55:30 lr: 2.0542333525655496e-05 loss: 0.0251 (0.0261) time: 3.6217 data: 0.0029 max mem: 19788 +Epoch: [25] [ 250/2138] eta: 1:54:51 lr: 2.0536524863543874e-05 loss: 0.0236 (0.0260) time: 3.6210 data: 0.0028 max mem: 19788 +Epoch: [25] [ 260/2138] eta: 1:54:12 lr: 2.0530716018876116e-05 loss: 0.0215 (0.0260) time: 3.6220 data: 0.0028 max mem: 19788 +Epoch: [25] [ 270/2138] eta: 1:53:34 lr: 2.0524906991589098e-05 loss: 0.0258 (0.0261) time: 3.6211 data: 0.0029 max mem: 19788 +Epoch: [25] [ 280/2138] eta: 1:52:56 lr: 2.0519097781619645e-05 loss: 0.0255 (0.0260) time: 3.6228 data: 0.0028 max mem: 19788 +Epoch: [25] [ 290/2138] eta: 1:52:18 lr: 2.051328838890455e-05 loss: 0.0255 (0.0260) time: 3.6235 data: 0.0029 max mem: 19788 +Epoch: [25] [ 300/2138] eta: 1:51:40 lr: 2.050747881338054e-05 loss: 0.0253 (0.0260) time: 3.6234 data: 0.0031 max mem: 19788 +Epoch: [25] [ 310/2138] eta: 1:51:02 lr: 2.0501669054984333e-05 loss: 0.0234 (0.0259) time: 3.6233 data: 0.0031 max mem: 19788 +Epoch: [25] [ 320/2138] eta: 1:50:25 lr: 2.0495859113652573e-05 loss: 0.0249 (0.0260) time: 3.6240 data: 0.0028 max mem: 19788 +Epoch: [25] [ 330/2138] eta: 1:49:47 lr: 2.0490048989321892e-05 loss: 0.0269 (0.0261) time: 3.6269 data: 0.0026 max mem: 19788 +Epoch: [25] [ 340/2138] eta: 1:49:10 lr: 2.0484238681928855e-05 loss: 0.0251 (0.0261) time: 3.6270 data: 0.0027 max mem: 19788 +Epoch: [25] [ 350/2138] eta: 1:48:33 lr: 2.0478428191410005e-05 loss: 0.0251 (0.0261) time: 3.6253 data: 0.0030 max mem: 19788 +Epoch: [25] [ 360/2138] eta: 1:47:56 lr: 2.047261751770183e-05 loss: 0.0240 (0.0261) time: 3.6269 data: 0.0029 max mem: 19788 +Epoch: [25] [ 370/2138] eta: 1:47:19 lr: 2.0466806660740778e-05 loss: 0.0239 (0.0262) time: 3.6304 data: 0.0028 max mem: 19788 +Epoch: [25] [ 380/2138] eta: 1:46:42 lr: 2.0460995620463258e-05 loss: 0.0283 (0.0263) time: 3.6308 data: 0.0030 max mem: 19788 +Epoch: [25] [ 390/2138] eta: 1:46:05 lr: 2.045518439680564e-05 loss: 0.0253 (0.0263) time: 3.6296 data: 0.0032 max mem: 19788 +Epoch: [25] [ 400/2138] eta: 1:45:28 lr: 2.0449372989704234e-05 loss: 0.0247 (0.0262) time: 3.6325 data: 0.0031 max mem: 19788 +Epoch: [25] [ 410/2138] eta: 1:44:51 lr: 2.0443561399095333e-05 loss: 0.0265 (0.0263) time: 3.6326 data: 0.0030 max mem: 19788 +Epoch: [25] [ 420/2138] eta: 1:44:14 lr: 2.0437749624915172e-05 loss: 0.0266 (0.0263) time: 3.6318 data: 0.0029 max mem: 19788 +Epoch: [25] [ 430/2138] eta: 1:43:37 lr: 2.0431937667099955e-05 loss: 0.0207 (0.0263) time: 3.6296 data: 0.0027 max mem: 19788 +Epoch: [25] [ 440/2138] eta: 1:43:01 lr: 2.042612552558582e-05 loss: 0.0230 (0.0263) time: 3.6298 data: 0.0029 max mem: 19788 +Epoch: [25] [ 450/2138] eta: 1:42:24 lr: 2.0420313200308896e-05 loss: 0.0230 (0.0263) time: 3.6326 data: 0.0028 max mem: 19788 +Epoch: [25] [ 460/2138] eta: 1:41:48 lr: 2.041450069120524e-05 loss: 0.0251 (0.0263) time: 3.6389 data: 0.0027 max mem: 19788 +Epoch: [25] [ 470/2138] eta: 1:41:12 lr: 2.0408687998210887e-05 loss: 0.0266 (0.0263) time: 3.6450 data: 0.0029 max mem: 19788 +Epoch: [25] [ 480/2138] eta: 1:40:35 lr: 2.0402875121261815e-05 loss: 0.0275 (0.0264) time: 3.6400 data: 0.0032 max mem: 19788 +Epoch: [25] [ 490/2138] eta: 1:39:59 lr: 2.039706206029397e-05 loss: 0.0237 (0.0264) time: 3.6400 data: 0.0032 max mem: 19788 +Epoch: [25] [ 500/2138] eta: 1:39:22 lr: 2.039124881524325e-05 loss: 0.0234 (0.0264) time: 3.6381 data: 0.0032 max mem: 19788 +Epoch: [25] [ 510/2138] eta: 1:38:45 lr: 2.0385435386045514e-05 loss: 0.0242 (0.0264) time: 3.6328 data: 0.0031 max mem: 19788 +Epoch: [25] [ 520/2138] eta: 1:38:09 lr: 2.0379621772636574e-05 loss: 0.0249 (0.0263) time: 3.6337 data: 0.0028 max mem: 19788 +Epoch: [25] [ 530/2138] eta: 1:37:32 lr: 2.0373807974952195e-05 loss: 0.0249 (0.0264) time: 3.6335 data: 0.0026 max mem: 19788 +Epoch: [25] [ 540/2138] eta: 1:36:56 lr: 2.0367993992928118e-05 loss: 0.0232 (0.0263) time: 3.6359 data: 0.0027 max mem: 19788 +Epoch: [25] [ 550/2138] eta: 1:36:19 lr: 2.036217982650001e-05 loss: 0.0246 (0.0263) time: 3.6313 data: 0.0029 max mem: 19788 +Epoch: [25] [ 560/2138] eta: 1:35:42 lr: 2.0356365475603536e-05 loss: 0.0246 (0.0263) time: 3.6267 data: 0.0027 max mem: 19788 +Epoch: [25] [ 570/2138] eta: 1:35:06 lr: 2.035055094017428e-05 loss: 0.0237 (0.0263) time: 3.6313 data: 0.0028 max mem: 19788 +Epoch: [25] [ 580/2138] eta: 1:34:29 lr: 2.0344736220147807e-05 loss: 0.0261 (0.0264) time: 3.6302 data: 0.0030 max mem: 19788 +Epoch: [25] [ 590/2138] eta: 1:33:53 lr: 2.0338921315459623e-05 loss: 0.0261 (0.0264) time: 3.6318 data: 0.0030 max mem: 19788 +Epoch: [25] [ 600/2138] eta: 1:33:16 lr: 2.0333106226045213e-05 loss: 0.0233 (0.0264) time: 3.6303 data: 0.0031 max mem: 19788 +Epoch: [25] [ 610/2138] eta: 1:32:39 lr: 2.0327290951839987e-05 loss: 0.0239 (0.0264) time: 3.6298 data: 0.0029 max mem: 19788 +Epoch: [25] [ 620/2138] eta: 1:32:03 lr: 2.0321475492779347e-05 loss: 0.0272 (0.0264) time: 3.6318 data: 0.0028 max mem: 19788 +Epoch: [25] [ 630/2138] eta: 1:31:26 lr: 2.0315659848798615e-05 loss: 0.0225 (0.0263) time: 3.6312 data: 0.0029 max mem: 19788 +Epoch: [25] [ 640/2138] eta: 1:30:50 lr: 2.030984401983311e-05 loss: 0.0225 (0.0263) time: 3.6319 data: 0.0027 max mem: 19788 +Epoch: [25] [ 650/2138] eta: 1:30:13 lr: 2.030402800581807e-05 loss: 0.0231 (0.0262) time: 3.6302 data: 0.0027 max mem: 19788 +Epoch: [25] [ 660/2138] eta: 1:29:37 lr: 2.0298211806688726e-05 loss: 0.0231 (0.0263) time: 3.6332 data: 0.0026 max mem: 19788 +Epoch: [25] [ 670/2138] eta: 1:29:00 lr: 2.029239542238022e-05 loss: 0.0246 (0.0262) time: 3.6331 data: 0.0027 max mem: 19788 +Epoch: [25] [ 680/2138] eta: 1:28:24 lr: 2.0286578852827706e-05 loss: 0.0255 (0.0263) time: 3.6310 data: 0.0030 max mem: 19788 +Epoch: [25] [ 690/2138] eta: 1:27:47 lr: 2.0280762097966245e-05 loss: 0.0248 (0.0263) time: 3.6346 data: 0.0032 max mem: 19788 +Epoch: [25] [ 700/2138] eta: 1:27:11 lr: 2.027494515773089e-05 loss: 0.0236 (0.0263) time: 3.6342 data: 0.0031 max mem: 19788 +Epoch: [25] [ 710/2138] eta: 1:26:34 lr: 2.0269128032056618e-05 loss: 0.0250 (0.0262) time: 3.6343 data: 0.0028 max mem: 19788 +Epoch: [25] [ 720/2138] eta: 1:25:58 lr: 2.0263310720878398e-05 loss: 0.0221 (0.0263) time: 3.6410 data: 0.0027 max mem: 19788 +Epoch: [25] [ 730/2138] eta: 1:25:22 lr: 2.0257493224131126e-05 loss: 0.0226 (0.0263) time: 3.6427 data: 0.0028 max mem: 19788 +Epoch: [25] [ 740/2138] eta: 1:24:45 lr: 2.0251675541749676e-05 loss: 0.0218 (0.0262) time: 3.6415 data: 0.0028 max mem: 19788 +Epoch: [25] [ 750/2138] eta: 1:24:09 lr: 2.024585767366886e-05 loss: 0.0214 (0.0262) time: 3.6384 data: 0.0030 max mem: 19788 +Epoch: [25] [ 760/2138] eta: 1:23:33 lr: 2.024003961982346e-05 loss: 0.0267 (0.0262) time: 3.6371 data: 0.0032 max mem: 19788 +Epoch: [25] [ 770/2138] eta: 1:22:56 lr: 2.02342213801482e-05 loss: 0.0259 (0.0263) time: 3.6351 data: 0.0030 max mem: 19788 +Epoch: [25] [ 780/2138] eta: 1:22:21 lr: 2.022840295457779e-05 loss: 0.0255 (0.0263) time: 3.6574 data: 0.0030 max mem: 19788 +Epoch: [25] [ 790/2138] eta: 1:21:44 lr: 2.022258434304685e-05 loss: 0.0282 (0.0263) time: 3.6592 data: 0.0031 max mem: 19788 +Epoch: [25] [ 800/2138] eta: 1:21:08 lr: 2.0216765545489998e-05 loss: 0.0246 (0.0263) time: 3.6374 data: 0.0029 max mem: 19788 +Epoch: [25] [ 810/2138] eta: 1:20:31 lr: 2.0210946561841784e-05 loss: 0.0246 (0.0263) time: 3.6378 data: 0.0026 max mem: 19788 +Epoch: [25] [ 820/2138] eta: 1:19:55 lr: 2.020512739203673e-05 loss: 0.0257 (0.0263) time: 3.6353 data: 0.0026 max mem: 19788 +Epoch: [25] [ 830/2138] eta: 1:19:19 lr: 2.01993080360093e-05 loss: 0.0209 (0.0262) time: 3.6406 data: 0.0027 max mem: 19788 +Epoch: [25] [ 840/2138] eta: 1:18:42 lr: 2.0193488493693912e-05 loss: 0.0198 (0.0262) time: 3.6451 data: 0.0027 max mem: 19788 +Epoch: [25] [ 850/2138] eta: 1:18:06 lr: 2.0187668765024965e-05 loss: 0.0198 (0.0262) time: 3.6373 data: 0.0027 max mem: 19788 +Epoch: [25] [ 860/2138] eta: 1:17:29 lr: 2.018184884993678e-05 loss: 0.0227 (0.0262) time: 3.6339 data: 0.0028 max mem: 19788 +Epoch: [25] [ 870/2138] eta: 1:16:53 lr: 2.017602874836366e-05 loss: 0.0257 (0.0262) time: 3.6361 data: 0.0030 max mem: 19788 +Epoch: [25] [ 880/2138] eta: 1:16:17 lr: 2.017020846023985e-05 loss: 0.0235 (0.0261) time: 3.6347 data: 0.0030 max mem: 19788 +Epoch: [25] [ 890/2138] eta: 1:15:40 lr: 2.0164387985499555e-05 loss: 0.0235 (0.0261) time: 3.6345 data: 0.0029 max mem: 19788 +Epoch: [25] [ 900/2138] eta: 1:15:04 lr: 2.0158567324076934e-05 loss: 0.0259 (0.0262) time: 3.6346 data: 0.0029 max mem: 19788 +Epoch: [25] [ 910/2138] eta: 1:14:27 lr: 2.015274647590611e-05 loss: 0.0255 (0.0262) time: 3.6350 data: 0.0028 max mem: 19788 +Epoch: [25] [ 920/2138] eta: 1:13:51 lr: 2.014692544092114e-05 loss: 0.0234 (0.0262) time: 3.6335 data: 0.0028 max mem: 19788 +Epoch: [25] [ 930/2138] eta: 1:13:14 lr: 2.014110421905607e-05 loss: 0.0223 (0.0262) time: 3.6383 data: 0.0030 max mem: 19788 +Epoch: [25] [ 940/2138] eta: 1:12:38 lr: 2.0135282810244867e-05 loss: 0.0260 (0.0262) time: 3.6426 data: 0.0035 max mem: 19788 +Epoch: [25] [ 950/2138] eta: 1:12:02 lr: 2.0129461214421482e-05 loss: 0.0246 (0.0262) time: 3.6367 data: 0.0032 max mem: 19788 +Epoch: [25] [ 960/2138] eta: 1:11:25 lr: 2.0123639431519795e-05 loss: 0.0246 (0.0262) time: 3.6318 data: 0.0027 max mem: 19788 +Epoch: [25] [ 970/2138] eta: 1:10:49 lr: 2.011781746147367e-05 loss: 0.0246 (0.0262) time: 3.6322 data: 0.0028 max mem: 19788 +Epoch: [25] [ 980/2138] eta: 1:10:12 lr: 2.0111995304216894e-05 loss: 0.0225 (0.0262) time: 3.6338 data: 0.0029 max mem: 19788 +Epoch: [25] [ 990/2138] eta: 1:09:36 lr: 2.0106172959683238e-05 loss: 0.0236 (0.0262) time: 3.6347 data: 0.0028 max mem: 19788 +Epoch: [25] [1000/2138] eta: 1:09:00 lr: 2.0100350427806412e-05 loss: 0.0269 (0.0262) time: 3.6379 data: 0.0029 max mem: 19788 +Epoch: [25] [1010/2138] eta: 1:08:23 lr: 2.00945277085201e-05 loss: 0.0226 (0.0262) time: 3.6363 data: 0.0031 max mem: 19788 +Epoch: [25] [1020/2138] eta: 1:07:47 lr: 2.0088704801757902e-05 loss: 0.0214 (0.0261) time: 3.6351 data: 0.0029 max mem: 19788 +Epoch: [25] [1030/2138] eta: 1:07:10 lr: 2.008288170745342e-05 loss: 0.0224 (0.0261) time: 3.6376 data: 0.0028 max mem: 19788 +Epoch: [25] [1040/2138] eta: 1:06:34 lr: 2.0077058425540174e-05 loss: 0.0238 (0.0261) time: 3.6332 data: 0.0029 max mem: 19788 +Epoch: [25] [1050/2138] eta: 1:05:57 lr: 2.007123495595167e-05 loss: 0.0248 (0.0261) time: 3.6333 data: 0.0032 max mem: 19788 +Epoch: [25] [1060/2138] eta: 1:05:21 lr: 2.0065411298621333e-05 loss: 0.0258 (0.0261) time: 3.6352 data: 0.0031 max mem: 19788 +Epoch: [25] [1070/2138] eta: 1:04:45 lr: 2.0059587453482583e-05 loss: 0.0254 (0.0261) time: 3.6323 data: 0.0029 max mem: 19788 +Epoch: [25] [1080/2138] eta: 1:04:08 lr: 2.005376342046876e-05 loss: 0.0229 (0.0261) time: 3.6328 data: 0.0031 max mem: 19788 +Epoch: [25] [1090/2138] eta: 1:03:32 lr: 2.0047939199513188e-05 loss: 0.0240 (0.0261) time: 3.6339 data: 0.0029 max mem: 19788 +Epoch: [25] [1100/2138] eta: 1:02:55 lr: 2.004211479054912e-05 loss: 0.0272 (0.0261) time: 3.6365 data: 0.0028 max mem: 19788 +Epoch: [25] [1110/2138] eta: 1:02:19 lr: 2.0036290193509782e-05 loss: 0.0262 (0.0261) time: 3.6363 data: 0.0030 max mem: 19788 +Epoch: [25] [1120/2138] eta: 1:01:43 lr: 2.003046540832834e-05 loss: 0.0247 (0.0261) time: 3.6346 data: 0.0030 max mem: 19788 +Epoch: [25] [1130/2138] eta: 1:01:06 lr: 2.0024640434937938e-05 loss: 0.0259 (0.0261) time: 3.6368 data: 0.0028 max mem: 19788 +Epoch: [25] [1140/2138] eta: 1:00:30 lr: 2.0018815273271646e-05 loss: 0.0236 (0.0261) time: 3.6386 data: 0.0028 max mem: 19788 +Epoch: [25] [1150/2138] eta: 0:59:54 lr: 2.0012989923262504e-05 loss: 0.0224 (0.0261) time: 3.6394 data: 0.0029 max mem: 19788 +Epoch: [25] [1160/2138] eta: 0:59:17 lr: 2.000716438484351e-05 loss: 0.0218 (0.0261) time: 3.6390 data: 0.0031 max mem: 19788 +Epoch: [25] [1170/2138] eta: 0:58:41 lr: 2.0001338657947602e-05 loss: 0.0239 (0.0261) time: 3.6369 data: 0.0030 max mem: 19788 +Epoch: [25] [1180/2138] eta: 0:58:04 lr: 1.9995512742507694e-05 loss: 0.0243 (0.0261) time: 3.6362 data: 0.0027 max mem: 19788 +Epoch: [25] [1190/2138] eta: 0:57:28 lr: 1.9989686638456628e-05 loss: 0.0248 (0.0261) time: 3.6379 data: 0.0026 max mem: 19788 +Epoch: [25] [1200/2138] eta: 0:56:52 lr: 1.9983860345727225e-05 loss: 0.0252 (0.0261) time: 3.6404 data: 0.0027 max mem: 19788 +Epoch: [25] [1210/2138] eta: 0:56:15 lr: 1.9978033864252244e-05 loss: 0.0245 (0.0261) time: 3.6440 data: 0.0027 max mem: 19788 +Epoch: [25] [1220/2138] eta: 0:55:39 lr: 1.9972207193964406e-05 loss: 0.0236 (0.0260) time: 3.6450 data: 0.0028 max mem: 19788 +Epoch: [25] [1230/2138] eta: 0:55:03 lr: 1.996638033479638e-05 loss: 0.0236 (0.0260) time: 3.6420 data: 0.0028 max mem: 19788 +Epoch: [25] [1240/2138] eta: 0:54:26 lr: 1.99605532866808e-05 loss: 0.0229 (0.0260) time: 3.6389 data: 0.0026 max mem: 19788 +Epoch: [25] [1250/2138] eta: 0:53:50 lr: 1.9954726049550236e-05 loss: 0.0216 (0.0260) time: 3.6374 data: 0.0029 max mem: 19788 +Epoch: [25] [1260/2138] eta: 0:53:14 lr: 1.994889862333724e-05 loss: 0.0211 (0.0260) time: 3.6384 data: 0.0032 max mem: 19788 +Epoch: [25] [1270/2138] eta: 0:52:37 lr: 1.9943071007974283e-05 loss: 0.0236 (0.0260) time: 3.6419 data: 0.0029 max mem: 19788 +Epoch: [25] [1280/2138] eta: 0:52:01 lr: 1.993724320339382e-05 loss: 0.0240 (0.0260) time: 3.6414 data: 0.0030 max mem: 19788 +Epoch: [25] [1290/2138] eta: 0:51:24 lr: 1.993141520952824e-05 loss: 0.0237 (0.0260) time: 3.6415 data: 0.0032 max mem: 19788 +Epoch: [25] [1300/2138] eta: 0:50:48 lr: 1.9925587026309906e-05 loss: 0.0225 (0.0260) time: 3.6424 data: 0.0029 max mem: 19788 +Epoch: [25] [1310/2138] eta: 0:50:12 lr: 1.9919758653671108e-05 loss: 0.0237 (0.0260) time: 3.6378 data: 0.0027 max mem: 19788 +Epoch: [25] [1320/2138] eta: 0:49:35 lr: 1.9913930091544117e-05 loss: 0.0240 (0.0260) time: 3.6355 data: 0.0028 max mem: 19788 +Epoch: [25] [1330/2138] eta: 0:48:59 lr: 1.9908101339861134e-05 loss: 0.0240 (0.0260) time: 3.6370 data: 0.0028 max mem: 19788 +Epoch: [25] [1340/2138] eta: 0:48:23 lr: 1.990227239855434e-05 loss: 0.0225 (0.0260) time: 3.6367 data: 0.0029 max mem: 19788 +Epoch: [25] [1350/2138] eta: 0:47:46 lr: 1.9896443267555837e-05 loss: 0.0275 (0.0261) time: 3.6366 data: 0.0030 max mem: 19788 +Epoch: [25] [1360/2138] eta: 0:47:10 lr: 1.9890613946797715e-05 loss: 0.0274 (0.0261) time: 3.6421 data: 0.0029 max mem: 19788 +Epoch: [25] [1370/2138] eta: 0:46:34 lr: 1.9884784436211982e-05 loss: 0.0242 (0.0261) time: 3.6470 data: 0.0029 max mem: 19788 +Epoch: [25] [1380/2138] eta: 0:45:57 lr: 1.987895473573064e-05 loss: 0.0242 (0.0261) time: 3.6439 data: 0.0031 max mem: 19788 +Epoch: [25] [1390/2138] eta: 0:45:21 lr: 1.9873124845285603e-05 loss: 0.0253 (0.0261) time: 3.6433 data: 0.0033 max mem: 19788 +Epoch: [25] [1400/2138] eta: 0:44:44 lr: 1.986729476480877e-05 loss: 0.0250 (0.0261) time: 3.6455 data: 0.0032 max mem: 19788 +Epoch: [25] [1410/2138] eta: 0:44:08 lr: 1.986146449423198e-05 loss: 0.0247 (0.0261) time: 3.6418 data: 0.0029 max mem: 19788 +Epoch: [25] [1420/2138] eta: 0:43:32 lr: 1.9855634033487024e-05 loss: 0.0247 (0.0261) time: 3.6430 data: 0.0029 max mem: 19788 +Epoch: [25] [1430/2138] eta: 0:42:55 lr: 1.9849803382505648e-05 loss: 0.0252 (0.0261) time: 3.6460 data: 0.0028 max mem: 19788 +Epoch: [25] [1440/2138] eta: 0:42:19 lr: 1.984397254121956e-05 loss: 0.0235 (0.0261) time: 3.6441 data: 0.0027 max mem: 19788 +Epoch: [25] [1450/2138] eta: 0:41:43 lr: 1.9838141509560406e-05 loss: 0.0267 (0.0261) time: 3.6454 data: 0.0028 max mem: 19788 +Epoch: [25] [1460/2138] eta: 0:41:06 lr: 1.983231028745979e-05 loss: 0.0281 (0.0261) time: 3.6437 data: 0.0030 max mem: 19788 +Epoch: [25] [1470/2138] eta: 0:40:30 lr: 1.9826478874849283e-05 loss: 0.0250 (0.0261) time: 3.6419 data: 0.0030 max mem: 19788 +Epoch: [25] [1480/2138] eta: 0:39:54 lr: 1.9820647271660383e-05 loss: 0.0264 (0.0261) time: 3.6440 data: 0.0030 max mem: 19788 +Epoch: [25] [1490/2138] eta: 0:39:17 lr: 1.981481547782457e-05 loss: 0.0268 (0.0261) time: 3.6442 data: 0.0030 max mem: 19788 +Epoch: [25] [1500/2138] eta: 0:38:41 lr: 1.9808983493273252e-05 loss: 0.0253 (0.0261) time: 3.6434 data: 0.0031 max mem: 19788 +Epoch: [25] [1510/2138] eta: 0:38:04 lr: 1.9803151317937808e-05 loss: 0.0253 (0.0261) time: 3.6391 data: 0.0031 max mem: 19788 +Epoch: [25] [1520/2138] eta: 0:37:28 lr: 1.9797318951749554e-05 loss: 0.0237 (0.0261) time: 3.6375 data: 0.0032 max mem: 19788 +Epoch: [25] [1530/2138] eta: 0:36:52 lr: 1.9791486394639776e-05 loss: 0.0233 (0.0261) time: 3.6433 data: 0.0030 max mem: 19788 +Epoch: [25] [1540/2138] eta: 0:36:15 lr: 1.9785653646539694e-05 loss: 0.0215 (0.0261) time: 3.6436 data: 0.0027 max mem: 19788 +Epoch: [25] [1550/2138] eta: 0:35:39 lr: 1.9779820707380506e-05 loss: 0.0211 (0.0261) time: 3.6419 data: 0.0029 max mem: 19788 +Epoch: [25] [1560/2138] eta: 0:35:03 lr: 1.9773987577093327e-05 loss: 0.0238 (0.0261) time: 3.6415 data: 0.0028 max mem: 19788 +Epoch: [25] [1570/2138] eta: 0:34:26 lr: 1.9768154255609264e-05 loss: 0.0247 (0.0262) time: 3.6412 data: 0.0028 max mem: 19788 +Epoch: [25] [1580/2138] eta: 0:33:50 lr: 1.9762320742859343e-05 loss: 0.0227 (0.0261) time: 3.6437 data: 0.0032 max mem: 19788 +Epoch: [25] [1590/2138] eta: 0:33:14 lr: 1.975648703877457e-05 loss: 0.0244 (0.0261) time: 3.6430 data: 0.0032 max mem: 19788 +Epoch: [25] [1600/2138] eta: 0:32:37 lr: 1.9750653143285874e-05 loss: 0.0267 (0.0262) time: 3.6643 data: 0.0029 max mem: 19788 +Epoch: [25] [1610/2138] eta: 0:32:01 lr: 1.974481905632417e-05 loss: 0.0247 (0.0261) time: 3.6682 data: 0.0030 max mem: 19788 +Epoch: [25] [1620/2138] eta: 0:31:25 lr: 1.9738984777820294e-05 loss: 0.0219 (0.0261) time: 3.6480 data: 0.0028 max mem: 19788 +Epoch: [25] [1630/2138] eta: 0:30:48 lr: 1.973315030770506e-05 loss: 0.0271 (0.0262) time: 3.6462 data: 0.0027 max mem: 19788 +Epoch: [25] [1640/2138] eta: 0:30:12 lr: 1.9727315645909207e-05 loss: 0.0255 (0.0261) time: 3.6424 data: 0.0027 max mem: 19788 +Epoch: [25] [1650/2138] eta: 0:29:35 lr: 1.972148079236346e-05 loss: 0.0217 (0.0261) time: 3.6379 data: 0.0028 max mem: 19788 +Epoch: [25] [1660/2138] eta: 0:28:59 lr: 1.9715645746998466e-05 loss: 0.0217 (0.0261) time: 3.6372 data: 0.0031 max mem: 19788 +Epoch: [25] [1670/2138] eta: 0:28:23 lr: 1.970981050974484e-05 loss: 0.0211 (0.0261) time: 3.6380 data: 0.0032 max mem: 19788 +Epoch: [25] [1680/2138] eta: 0:27:46 lr: 1.9703975080533146e-05 loss: 0.0245 (0.0261) time: 3.6396 data: 0.0029 max mem: 19788 +Epoch: [25] [1690/2138] eta: 0:27:10 lr: 1.96981394592939e-05 loss: 0.0240 (0.0261) time: 3.6399 data: 0.0030 max mem: 19788 +Epoch: [25] [1700/2138] eta: 0:26:33 lr: 1.969230364595756e-05 loss: 0.0224 (0.0261) time: 3.6397 data: 0.0029 max mem: 19788 +Epoch: [25] [1710/2138] eta: 0:25:57 lr: 1.9686467640454563e-05 loss: 0.0229 (0.0260) time: 3.6362 data: 0.0030 max mem: 19788 +Epoch: [25] [1720/2138] eta: 0:25:21 lr: 1.968063144271526e-05 loss: 0.0234 (0.0260) time: 3.6347 data: 0.0030 max mem: 19788 +Epoch: [25] [1730/2138] eta: 0:24:44 lr: 1.967479505266999e-05 loss: 0.0234 (0.0260) time: 3.6352 data: 0.0030 max mem: 19788 +Epoch: [25] [1740/2138] eta: 0:24:08 lr: 1.966895847024902e-05 loss: 0.0253 (0.0260) time: 3.6332 data: 0.0030 max mem: 19788 +Epoch: [25] [1750/2138] eta: 0:23:31 lr: 1.966312169538257e-05 loss: 0.0243 (0.0260) time: 3.6322 data: 0.0027 max mem: 19788 +Epoch: [25] [1760/2138] eta: 0:22:55 lr: 1.9657284728000832e-05 loss: 0.0242 (0.0260) time: 3.6298 data: 0.0028 max mem: 19788 +Epoch: [25] [1770/2138] eta: 0:22:19 lr: 1.9651447568033923e-05 loss: 0.0235 (0.0260) time: 3.6311 data: 0.0031 max mem: 19788 +Epoch: [25] [1780/2138] eta: 0:21:42 lr: 1.964561021541193e-05 loss: 0.0234 (0.0260) time: 3.6317 data: 0.0030 max mem: 19788 +Epoch: [25] [1790/2138] eta: 0:21:06 lr: 1.963977267006489e-05 loss: 0.0221 (0.0260) time: 3.6301 data: 0.0029 max mem: 19788 +Epoch: [25] [1800/2138] eta: 0:20:29 lr: 1.963393493192278e-05 loss: 0.0228 (0.0260) time: 3.6282 data: 0.0028 max mem: 19788 +Epoch: [25] [1810/2138] eta: 0:19:53 lr: 1.9628097000915535e-05 loss: 0.0242 (0.0260) time: 3.6288 data: 0.0027 max mem: 19788 +Epoch: [25] [1820/2138] eta: 0:19:17 lr: 1.962225887697305e-05 loss: 0.0239 (0.0260) time: 3.6350 data: 0.0027 max mem: 19788 +Epoch: [25] [1830/2138] eta: 0:18:40 lr: 1.961642056002515e-05 loss: 0.0229 (0.0260) time: 3.6369 data: 0.0029 max mem: 19788 +Epoch: [25] [1840/2138] eta: 0:18:04 lr: 1.961058205000164e-05 loss: 0.0264 (0.0260) time: 3.6377 data: 0.0029 max mem: 19788 +Epoch: [25] [1850/2138] eta: 0:17:27 lr: 1.960474334683225e-05 loss: 0.0266 (0.0260) time: 3.6392 data: 0.0028 max mem: 19788 +Epoch: [25] [1860/2138] eta: 0:16:51 lr: 1.9598904450446677e-05 loss: 0.0262 (0.0260) time: 3.6364 data: 0.0028 max mem: 19788 +Epoch: [25] [1870/2138] eta: 0:16:15 lr: 1.959306536077456e-05 loss: 0.0235 (0.0260) time: 3.6370 data: 0.0031 max mem: 19788 +Epoch: [25] [1880/2138] eta: 0:15:38 lr: 1.95872260777455e-05 loss: 0.0235 (0.0260) time: 3.6379 data: 0.0032 max mem: 19788 +Epoch: [25] [1890/2138] eta: 0:15:02 lr: 1.9581386601289028e-05 loss: 0.0216 (0.0260) time: 3.6363 data: 0.0032 max mem: 19788 +Epoch: [25] [1900/2138] eta: 0:14:26 lr: 1.957554693133466e-05 loss: 0.0228 (0.0260) time: 3.6447 data: 0.0031 max mem: 19788 +Epoch: [25] [1910/2138] eta: 0:13:49 lr: 1.9569707067811824e-05 loss: 0.0248 (0.0260) time: 3.6488 data: 0.0032 max mem: 19788 +Epoch: [25] [1920/2138] eta: 0:13:13 lr: 1.9563867010649932e-05 loss: 0.0226 (0.0260) time: 3.6385 data: 0.0032 max mem: 19788 +Epoch: [25] [1930/2138] eta: 0:12:36 lr: 1.9558026759778324e-05 loss: 0.0253 (0.0260) time: 3.6384 data: 0.0031 max mem: 19788 +Epoch: [25] [1940/2138] eta: 0:12:00 lr: 1.955218631512631e-05 loss: 0.0258 (0.0260) time: 3.6425 data: 0.0031 max mem: 19788 +Epoch: [25] [1950/2138] eta: 0:11:24 lr: 1.9546345676623124e-05 loss: 0.0246 (0.0260) time: 3.6411 data: 0.0028 max mem: 19788 +Epoch: [25] [1960/2138] eta: 0:10:47 lr: 1.9540504844197984e-05 loss: 0.0231 (0.0260) time: 3.6441 data: 0.0027 max mem: 19788 +Epoch: [25] [1970/2138] eta: 0:10:11 lr: 1.9534663817780024e-05 loss: 0.0241 (0.0260) time: 3.6452 data: 0.0028 max mem: 19788 +Epoch: [25] [1980/2138] eta: 0:09:34 lr: 1.9528822597298363e-05 loss: 0.0229 (0.0260) time: 3.6410 data: 0.0030 max mem: 19788 +Epoch: [25] [1990/2138] eta: 0:08:58 lr: 1.9522981182682043e-05 loss: 0.0216 (0.0260) time: 3.6427 data: 0.0031 max mem: 19788 +Epoch: [25] [2000/2138] eta: 0:08:22 lr: 1.951713957386007e-05 loss: 0.0241 (0.0260) time: 3.6465 data: 0.0033 max mem: 19788 +Epoch: [25] [2010/2138] eta: 0:07:45 lr: 1.9511297770761397e-05 loss: 0.0249 (0.0260) time: 3.6404 data: 0.0032 max mem: 19788 +Epoch: [25] [2020/2138] eta: 0:07:09 lr: 1.9505455773314933e-05 loss: 0.0249 (0.0260) time: 3.6347 data: 0.0028 max mem: 19788 +Epoch: [25] [2030/2138] eta: 0:06:32 lr: 1.9499613581449522e-05 loss: 0.0251 (0.0260) time: 3.6354 data: 0.0028 max mem: 19788 +Epoch: [25] [2040/2138] eta: 0:05:56 lr: 1.949377119509398e-05 loss: 0.0266 (0.0260) time: 3.6366 data: 0.0029 max mem: 19788 +Epoch: [25] [2050/2138] eta: 0:05:20 lr: 1.9487928614177054e-05 loss: 0.0268 (0.0260) time: 3.6325 data: 0.0028 max mem: 19788 +Epoch: [25] [2060/2138] eta: 0:04:43 lr: 1.9482085838627446e-05 loss: 0.0244 (0.0260) time: 3.6315 data: 0.0027 max mem: 19788 +Epoch: [25] [2070/2138] eta: 0:04:07 lr: 1.9476242868373824e-05 loss: 0.0240 (0.0260) time: 3.6332 data: 0.0029 max mem: 19788 +Epoch: [25] [2080/2138] eta: 0:03:31 lr: 1.9470399703344775e-05 loss: 0.0240 (0.0260) time: 3.6329 data: 0.0030 max mem: 19788 +Epoch: [25] [2090/2138] eta: 0:02:54 lr: 1.9464556343468868e-05 loss: 0.0225 (0.0260) time: 3.6268 data: 0.0030 max mem: 19788 +Epoch: [25] [2100/2138] eta: 0:02:18 lr: 1.94587127886746e-05 loss: 0.0235 (0.0260) time: 3.6303 data: 0.0030 max mem: 19788 +Epoch: [25] [2110/2138] eta: 0:01:41 lr: 1.9452869038890433e-05 loss: 0.0286 (0.0260) time: 3.6406 data: 0.0029 max mem: 19788 +Epoch: [25] [2120/2138] eta: 0:01:05 lr: 1.9447025094044764e-05 loss: 0.0282 (0.0260) time: 3.6353 data: 0.0029 max mem: 19788 +Epoch: [25] [2130/2138] eta: 0:00:29 lr: 1.9441180954065956e-05 loss: 0.0254 (0.0260) time: 3.6161 data: 0.0028 max mem: 19788 +Epoch: [25] Total time: 2:09:39 +Test: [ 0/21770] eta: 18:40:19 time: 3.0877 data: 2.7721 max mem: 19788 +Test: [ 100/21770] eta: 0:35:16 time: 0.0665 data: 0.0020 max mem: 19788 +Test: [ 200/21770] eta: 0:29:54 time: 0.0619 data: 0.0018 max mem: 19788 +Test: [ 300/21770] eta: 0:27:59 time: 0.0612 data: 0.0018 max mem: 19788 +Test: [ 400/21770] eta: 0:26:46 time: 0.0663 data: 0.0019 max mem: 19788 +Test: [ 500/21770] eta: 0:25:45 time: 0.0610 data: 0.0019 max mem: 19788 +Test: [ 600/21770] eta: 0:25:16 time: 0.0730 data: 0.0023 max mem: 19788 +Test: [ 700/21770] eta: 0:24:51 time: 0.0663 data: 0.0020 max mem: 19788 +Test: [ 800/21770] eta: 0:24:30 time: 0.0626 data: 0.0017 max mem: 19788 +Test: [ 900/21770] eta: 0:24:22 time: 0.0673 data: 0.0018 max mem: 19788 +Test: [ 1000/21770] eta: 0:24:17 time: 0.0728 data: 0.0019 max mem: 19788 +Test: [ 1100/21770] eta: 0:23:57 time: 0.0676 data: 0.0019 max mem: 19788 +Test: [ 1200/21770] eta: 0:23:36 time: 0.0601 data: 0.0017 max mem: 19788 +Test: [ 1300/21770] eta: 0:23:20 time: 0.0613 data: 0.0017 max mem: 19788 +Test: [ 1400/21770] eta: 0:23:11 time: 0.0762 data: 0.0018 max mem: 19788 +Test: [ 1500/21770] eta: 0:23:04 time: 0.0707 data: 0.0020 max mem: 19788 +Test: [ 1600/21770] eta: 0:22:54 time: 0.0645 data: 0.0017 max mem: 19788 +Test: [ 1700/21770] eta: 0:22:39 time: 0.0649 data: 0.0019 max mem: 19788 +Test: [ 1800/21770] eta: 0:22:29 time: 0.0597 data: 0.0020 max mem: 19788 +Test: [ 1900/21770] eta: 0:22:21 time: 0.0607 data: 0.0017 max mem: 19788 +Test: [ 2000/21770] eta: 0:22:11 time: 0.0611 data: 0.0019 max mem: 19788 +Test: [ 2100/21770] eta: 0:22:07 time: 0.0624 data: 0.0019 max mem: 19788 +Test: [ 2200/21770] eta: 0:21:58 time: 0.0612 data: 0.0017 max mem: 19788 +Test: [ 2300/21770] eta: 0:21:51 time: 0.0752 data: 0.0024 max mem: 19788 +Test: [ 2400/21770] eta: 0:21:48 time: 0.0657 data: 0.0018 max mem: 19788 +Test: [ 2500/21770] eta: 0:21:42 time: 0.0662 data: 0.0019 max mem: 19788 +Test: [ 2600/21770] eta: 0:21:40 time: 0.0692 data: 0.0019 max mem: 19788 +Test: [ 2700/21770] eta: 0:21:31 time: 0.0720 data: 0.0017 max mem: 19788 +Test: [ 2800/21770] eta: 0:21:28 time: 0.0733 data: 0.0021 max mem: 19788 +Test: [ 2900/21770] eta: 0:21:26 time: 0.0744 data: 0.0021 max mem: 19788 +Test: [ 3000/21770] eta: 0:21:15 time: 0.0621 data: 0.0018 max mem: 19788 +Test: [ 3100/21770] eta: 0:21:09 time: 0.0622 data: 0.0019 max mem: 19788 +Test: [ 3200/21770] eta: 0:21:01 time: 0.0624 data: 0.0017 max mem: 19788 +Test: [ 3300/21770] eta: 0:20:54 time: 0.0634 data: 0.0017 max mem: 19788 +Test: [ 3400/21770] eta: 0:20:47 time: 0.0766 data: 0.0022 max mem: 19788 +Test: [ 3500/21770] eta: 0:20:43 time: 0.0749 data: 0.0023 max mem: 19788 +Test: [ 3600/21770] eta: 0:20:37 time: 0.0689 data: 0.0020 max mem: 19788 +Test: [ 3700/21770] eta: 0:20:30 time: 0.0645 data: 0.0019 max mem: 19788 +Test: [ 3800/21770] eta: 0:20:23 time: 0.0650 data: 0.0018 max mem: 19788 +Test: [ 3900/21770] eta: 0:20:18 time: 0.0676 data: 0.0020 max mem: 19788 +Test: [ 4000/21770] eta: 0:20:10 time: 0.0640 data: 0.0018 max mem: 19788 +Test: [ 4100/21770] eta: 0:20:02 time: 0.0733 data: 0.0019 max mem: 19788 +Test: [ 4200/21770] eta: 0:19:54 time: 0.0664 data: 0.0019 max mem: 19788 +Test: [ 4300/21770] eta: 0:19:47 time: 0.0644 data: 0.0019 max mem: 19788 +Test: [ 4400/21770] eta: 0:19:42 time: 0.0747 data: 0.0018 max mem: 19788 +Test: [ 4500/21770] eta: 0:19:36 time: 0.0757 data: 0.0022 max mem: 19788 +Test: [ 4600/21770] eta: 0:19:31 time: 0.0621 data: 0.0019 max mem: 19788 +Test: [ 4700/21770] eta: 0:19:27 time: 0.0666 data: 0.0020 max mem: 19788 +Test: [ 4800/21770] eta: 0:19:21 time: 0.0709 data: 0.0021 max mem: 19788 +Test: [ 4900/21770] eta: 0:19:14 time: 0.0587 data: 0.0017 max mem: 19788 +Test: [ 5000/21770] eta: 0:19:05 time: 0.0625 data: 0.0022 max mem: 19788 +Test: [ 5100/21770] eta: 0:18:58 time: 0.0658 data: 0.0017 max mem: 19788 +Test: [ 5200/21770] eta: 0:18:50 time: 0.0653 data: 0.0019 max mem: 19788 +Test: [ 5300/21770] eta: 0:18:44 time: 0.0718 data: 0.0021 max mem: 19788 +Test: [ 5400/21770] eta: 0:18:37 time: 0.0635 data: 0.0018 max mem: 19788 +Test: [ 5500/21770] eta: 0:18:32 time: 0.0734 data: 0.0022 max mem: 19788 +Test: [ 5600/21770] eta: 0:18:24 time: 0.0577 data: 0.0017 max mem: 19788 +Test: [ 5700/21770] eta: 0:18:17 time: 0.0788 data: 0.0023 max mem: 19788 +Test: [ 5800/21770] eta: 0:18:11 time: 0.0639 data: 0.0018 max mem: 19788 +Test: [ 5900/21770] eta: 0:18:03 time: 0.0624 data: 0.0018 max mem: 19788 +Test: [ 6000/21770] eta: 0:17:56 time: 0.0635 data: 0.0020 max mem: 19788 +Test: [ 6100/21770] eta: 0:17:49 time: 0.0653 data: 0.0021 max mem: 19788 +Test: [ 6200/21770] eta: 0:17:42 time: 0.0770 data: 0.0019 max mem: 19788 +Test: [ 6300/21770] eta: 0:17:37 time: 0.0820 data: 0.0020 max mem: 19788 +Test: [ 6400/21770] eta: 0:17:31 time: 0.0655 data: 0.0018 max mem: 19788 +Test: [ 6500/21770] eta: 0:17:24 time: 0.0728 data: 0.0019 max mem: 19788 +Test: [ 6600/21770] eta: 0:17:15 time: 0.0639 data: 0.0019 max mem: 19788 +Test: [ 6700/21770] eta: 0:17:07 time: 0.0612 data: 0.0017 max mem: 19788 +Test: [ 6800/21770] eta: 0:17:01 time: 0.0617 data: 0.0020 max mem: 19788 +Test: [ 6900/21770] eta: 0:16:53 time: 0.0629 data: 0.0018 max mem: 19788 +Test: [ 7000/21770] eta: 0:16:46 time: 0.0730 data: 0.0021 max mem: 19788 +Test: [ 7100/21770] eta: 0:16:38 time: 0.0675 data: 0.0021 max mem: 19788 +Test: [ 7200/21770] eta: 0:16:32 time: 0.0624 data: 0.0019 max mem: 19788 +Test: [ 7300/21770] eta: 0:16:25 time: 0.0785 data: 0.0017 max mem: 19788 +Test: [ 7400/21770] eta: 0:16:19 time: 0.0710 data: 0.0022 max mem: 19788 +Test: [ 7500/21770] eta: 0:16:12 time: 0.0593 data: 0.0017 max mem: 19788 +Test: [ 7600/21770] eta: 0:16:05 time: 0.0608 data: 0.0016 max mem: 19788 +Test: [ 7700/21770] eta: 0:15:57 time: 0.0728 data: 0.0022 max mem: 19788 +Test: [ 7800/21770] eta: 0:15:51 time: 0.0619 data: 0.0018 max mem: 19788 +Test: [ 7900/21770] eta: 0:15:44 time: 0.0775 data: 0.0018 max mem: 19788 +Test: [ 8000/21770] eta: 0:15:37 time: 0.0718 data: 0.0018 max mem: 19788 +Test: [ 8100/21770] eta: 0:15:31 time: 0.0672 data: 0.0019 max mem: 19788 +Test: [ 8200/21770] eta: 0:15:24 time: 0.0667 data: 0.0019 max mem: 19788 +Test: [ 8300/21770] eta: 0:15:17 time: 0.0711 data: 0.0021 max mem: 19788 +Test: [ 8400/21770] eta: 0:15:10 time: 0.0707 data: 0.0021 max mem: 19788 +Test: [ 8500/21770] eta: 0:15:04 time: 0.0721 data: 0.0022 max mem: 19788 +Test: [ 8600/21770] eta: 0:14:57 time: 0.0813 data: 0.0025 max mem: 19788 +Test: [ 8700/21770] eta: 0:14:51 time: 0.0810 data: 0.0021 max mem: 19788 +Test: [ 8800/21770] eta: 0:14:44 time: 0.0625 data: 0.0017 max mem: 19788 +Test: [ 8900/21770] eta: 0:14:37 time: 0.0670 data: 0.0020 max mem: 19788 +Test: [ 9000/21770] eta: 0:14:30 time: 0.0622 data: 0.0017 max mem: 19788 +Test: [ 9100/21770] eta: 0:14:23 time: 0.0646 data: 0.0020 max mem: 19788 +Test: [ 9200/21770] eta: 0:14:17 time: 0.0678 data: 0.0018 max mem: 19788 +Test: [ 9300/21770] eta: 0:14:10 time: 0.0618 data: 0.0019 max mem: 19788 +Test: [ 9400/21770] eta: 0:14:03 time: 0.0681 data: 0.0021 max mem: 19788 +Test: [ 9500/21770] eta: 0:13:55 time: 0.0665 data: 0.0020 max mem: 19788 +Test: [ 9600/21770] eta: 0:13:49 time: 0.0810 data: 0.0021 max mem: 19788 +Test: [ 9700/21770] eta: 0:13:42 time: 0.0610 data: 0.0016 max mem: 19788 +Test: [ 9800/21770] eta: 0:13:35 time: 0.0642 data: 0.0021 max mem: 19788 +Test: [ 9900/21770] eta: 0:13:29 time: 0.0728 data: 0.0020 max mem: 19788 +Test: [10000/21770] eta: 0:13:22 time: 0.0675 data: 0.0019 max mem: 19788 +Test: [10100/21770] eta: 0:13:15 time: 0.0720 data: 0.0022 max mem: 19788 +Test: [10200/21770] eta: 0:13:09 time: 0.0816 data: 0.0024 max mem: 19788 +Test: [10300/21770] eta: 0:13:02 time: 0.0828 data: 0.0021 max mem: 19788 +Test: [10400/21770] eta: 0:12:55 time: 0.0693 data: 0.0021 max mem: 19788 +Test: [10500/21770] eta: 0:12:49 time: 0.0650 data: 0.0020 max mem: 19788 +Test: [10600/21770] eta: 0:12:42 time: 0.0730 data: 0.0022 max mem: 19788 +Test: [10700/21770] eta: 0:12:35 time: 0.0770 data: 0.0023 max mem: 19788 +Test: [10800/21770] eta: 0:12:29 time: 0.0729 data: 0.0021 max mem: 19788 +Test: [10900/21770] eta: 0:12:23 time: 0.0634 data: 0.0018 max mem: 19788 +Test: [11000/21770] eta: 0:12:15 time: 0.0700 data: 0.0020 max mem: 19788 +Test: [11100/21770] eta: 0:12:08 time: 0.0614 data: 0.0017 max mem: 19788 +Test: [11200/21770] eta: 0:12:01 time: 0.0680 data: 0.0022 max mem: 19788 +Test: [11300/21770] eta: 0:11:54 time: 0.0627 data: 0.0019 max mem: 19788 +Test: [11400/21770] eta: 0:11:48 time: 0.0770 data: 0.0021 max mem: 19788 +Test: [11500/21770] eta: 0:11:41 time: 0.0732 data: 0.0021 max mem: 19788 +Test: [11600/21770] eta: 0:11:34 time: 0.0750 data: 0.0022 max mem: 19788 +Test: [11700/21770] eta: 0:11:27 time: 0.0667 data: 0.0018 max mem: 19788 +Test: [11800/21770] eta: 0:11:20 time: 0.0741 data: 0.0021 max mem: 19788 +Test: [11900/21770] eta: 0:11:14 time: 0.0681 data: 0.0018 max mem: 19788 +Test: [12000/21770] eta: 0:11:07 time: 0.0647 data: 0.0020 max mem: 19788 +Test: [12100/21770] eta: 0:11:01 time: 0.0790 data: 0.0021 max mem: 19788 +Test: [12200/21770] eta: 0:10:54 time: 0.0740 data: 0.0023 max mem: 19788 +Test: [12300/21770] eta: 0:10:48 time: 0.0804 data: 0.0024 max mem: 19788 +Test: [12400/21770] eta: 0:10:41 time: 0.0821 data: 0.0019 max mem: 19788 +Test: [12500/21770] eta: 0:10:35 time: 0.0803 data: 0.0024 max mem: 19788 +Test: [12600/21770] eta: 0:10:28 time: 0.0620 data: 0.0019 max mem: 19788 +Test: [12700/21770] eta: 0:10:22 time: 0.0689 data: 0.0020 max mem: 19788 +Test: [12800/21770] eta: 0:10:15 time: 0.0634 data: 0.0019 max mem: 19788 +Test: [12900/21770] eta: 0:10:08 time: 0.0809 data: 0.0024 max mem: 19788 +Test: [13000/21770] eta: 0:10:01 time: 0.0603 data: 0.0019 max mem: 19788 +Test: [13100/21770] eta: 0:09:55 time: 0.0610 data: 0.0020 max mem: 19788 +Test: [13200/21770] eta: 0:09:47 time: 0.0620 data: 0.0019 max mem: 19788 +Test: [13300/21770] eta: 0:09:40 time: 0.0798 data: 0.0024 max mem: 19788 +Test: [13400/21770] eta: 0:09:33 time: 0.0699 data: 0.0020 max mem: 19788 +Test: [13500/21770] eta: 0:09:27 time: 0.0644 data: 0.0020 max mem: 19788 +Test: [13600/21770] eta: 0:09:20 time: 0.0702 data: 0.0020 max mem: 19788 +Test: [13700/21770] eta: 0:09:13 time: 0.0738 data: 0.0021 max mem: 19788 +Test: [13800/21770] eta: 0:09:07 time: 0.0820 data: 0.0024 max mem: 19788 +Test: [13900/21770] eta: 0:09:00 time: 0.0729 data: 0.0023 max mem: 19788 +Test: [14000/21770] eta: 0:08:53 time: 0.0628 data: 0.0017 max mem: 19788 +Test: [14100/21770] eta: 0:08:46 time: 0.0691 data: 0.0021 max mem: 19788 +Test: [14200/21770] eta: 0:08:39 time: 0.0677 data: 0.0019 max mem: 19788 +Test: [14300/21770] eta: 0:08:32 time: 0.0613 data: 0.0019 max mem: 19788 +Test: [14400/21770] eta: 0:08:25 time: 0.0699 data: 0.0021 max mem: 19788 +Test: [14500/21770] eta: 0:08:18 time: 0.0632 data: 0.0019 max mem: 19788 +Test: [14600/21770] eta: 0:08:12 time: 0.0652 data: 0.0019 max mem: 19788 +Test: [14700/21770] eta: 0:08:05 time: 0.0706 data: 0.0021 max mem: 19788 +Test: [14800/21770] eta: 0:07:58 time: 0.0647 data: 0.0019 max mem: 19788 +Test: [14900/21770] eta: 0:07:51 time: 0.0621 data: 0.0018 max mem: 19788 +Test: [15000/21770] eta: 0:07:44 time: 0.0693 data: 0.0018 max mem: 19788 +Test: [15100/21770] eta: 0:07:37 time: 0.0655 data: 0.0020 max mem: 19788 +Test: [15200/21770] eta: 0:07:30 time: 0.0623 data: 0.0019 max mem: 19788 +Test: [15300/21770] eta: 0:07:23 time: 0.0612 data: 0.0018 max mem: 19788 +Test: [15400/21770] eta: 0:07:16 time: 0.0639 data: 0.0017 max mem: 19788 +Test: [15500/21770] eta: 0:07:09 time: 0.0620 data: 0.0020 max mem: 19788 +Test: [15600/21770] eta: 0:07:02 time: 0.0681 data: 0.0020 max mem: 19788 +Test: [15700/21770] eta: 0:06:55 time: 0.0645 data: 0.0017 max mem: 19788 +Test: [15800/21770] eta: 0:06:48 time: 0.0747 data: 0.0019 max mem: 19788 +Test: [15900/21770] eta: 0:06:42 time: 0.0774 data: 0.0023 max mem: 19788 +Test: [16000/21770] eta: 0:06:35 time: 0.0771 data: 0.0019 max mem: 19788 +Test: [16100/21770] eta: 0:06:28 time: 0.0695 data: 0.0018 max mem: 19788 +Test: [16200/21770] eta: 0:06:21 time: 0.0663 data: 0.0018 max mem: 19788 +Test: [16300/21770] eta: 0:06:14 time: 0.0765 data: 0.0023 max mem: 19788 +Test: [16400/21770] eta: 0:06:07 time: 0.0680 data: 0.0020 max mem: 19788 +Test: [16500/21770] eta: 0:06:00 time: 0.0804 data: 0.0023 max mem: 19788 +Test: [16600/21770] eta: 0:05:54 time: 0.0710 data: 0.0020 max mem: 19788 +Test: [16700/21770] eta: 0:05:47 time: 0.0674 data: 0.0021 max mem: 19788 +Test: [16800/21770] eta: 0:05:40 time: 0.0795 data: 0.0023 max mem: 19788 +Test: [16900/21770] eta: 0:05:33 time: 0.0678 data: 0.0020 max mem: 19788 +Test: [17000/21770] eta: 0:05:26 time: 0.0724 data: 0.0022 max mem: 19788 +Test: [17100/21770] eta: 0:05:19 time: 0.0668 data: 0.0020 max mem: 19788 +Test: [17200/21770] eta: 0:05:12 time: 0.0718 data: 0.0018 max mem: 19788 +Test: [17300/21770] eta: 0:05:06 time: 0.0734 data: 0.0021 max mem: 19788 +Test: [17400/21770] eta: 0:04:59 time: 0.0624 data: 0.0019 max mem: 19788 +Test: [17500/21770] eta: 0:04:52 time: 0.0795 data: 0.0020 max mem: 19788 +Test: [17600/21770] eta: 0:04:45 time: 0.0744 data: 0.0022 max mem: 19788 +Test: [17700/21770] eta: 0:04:38 time: 0.0624 data: 0.0019 max mem: 19788 +Test: [17800/21770] eta: 0:04:31 time: 0.0727 data: 0.0022 max mem: 19788 +Test: [17900/21770] eta: 0:04:25 time: 0.0671 data: 0.0020 max mem: 19788 +Test: [18000/21770] eta: 0:04:18 time: 0.0632 data: 0.0019 max mem: 19788 +Test: [18100/21770] eta: 0:04:11 time: 0.0637 data: 0.0018 max mem: 19788 +Test: [18200/21770] eta: 0:04:04 time: 0.0807 data: 0.0024 max mem: 19788 +Test: [18300/21770] eta: 0:03:57 time: 0.0606 data: 0.0018 max mem: 19788 +Test: [18400/21770] eta: 0:03:50 time: 0.0731 data: 0.0022 max mem: 19788 +Test: [18500/21770] eta: 0:03:43 time: 0.0631 data: 0.0018 max mem: 19788 +Test: [18600/21770] eta: 0:03:36 time: 0.0596 data: 0.0019 max mem: 19788 +Test: [18700/21770] eta: 0:03:30 time: 0.0684 data: 0.0019 max mem: 19788 +Test: [18800/21770] eta: 0:03:23 time: 0.0620 data: 0.0018 max mem: 19788 +Test: [18900/21770] eta: 0:03:16 time: 0.0680 data: 0.0022 max mem: 19788 +Test: [19000/21770] eta: 0:03:09 time: 0.0611 data: 0.0018 max mem: 19788 +Test: [19100/21770] eta: 0:03:02 time: 0.0753 data: 0.0019 max mem: 19788 +Test: [19200/21770] eta: 0:02:55 time: 0.0638 data: 0.0021 max mem: 19788 +Test: [19300/21770] eta: 0:02:48 time: 0.0732 data: 0.0022 max mem: 19788 +Test: [19400/21770] eta: 0:02:42 time: 0.0622 data: 0.0016 max mem: 19788 +Test: [19500/21770] eta: 0:02:35 time: 0.0741 data: 0.0023 max mem: 19788 +Test: [19600/21770] eta: 0:02:28 time: 0.0788 data: 0.0023 max mem: 19788 +Test: [19700/21770] eta: 0:02:21 time: 0.0748 data: 0.0020 max mem: 19788 +Test: [19800/21770] eta: 0:02:14 time: 0.0788 data: 0.0024 max mem: 19788 +Test: [19900/21770] eta: 0:02:07 time: 0.0631 data: 0.0017 max mem: 19788 +Test: [20000/21770] eta: 0:02:01 time: 0.0617 data: 0.0019 max mem: 19788 +Test: [20100/21770] eta: 0:01:54 time: 0.0707 data: 0.0021 max mem: 19788 +Test: [20200/21770] eta: 0:01:47 time: 0.0687 data: 0.0020 max mem: 19788 +Test: [20300/21770] eta: 0:01:40 time: 0.0627 data: 0.0019 max mem: 19788 +Test: [20400/21770] eta: 0:01:33 time: 0.0630 data: 0.0018 max mem: 19788 +Test: [20500/21770] eta: 0:01:26 time: 0.0665 data: 0.0020 max mem: 19788 +Test: [20600/21770] eta: 0:01:19 time: 0.0660 data: 0.0017 max mem: 19788 +Test: [20700/21770] eta: 0:01:13 time: 0.0806 data: 0.0024 max mem: 19788 +Test: [20800/21770] eta: 0:01:06 time: 0.0638 data: 0.0019 max mem: 19788 +Test: [20900/21770] eta: 0:00:59 time: 0.0630 data: 0.0018 max mem: 19788 +Test: [21000/21770] eta: 0:00:52 time: 0.0752 data: 0.0021 max mem: 19788 +Test: [21100/21770] eta: 0:00:45 time: 0.0699 data: 0.0023 max mem: 19788 +Test: [21200/21770] eta: 0:00:38 time: 0.0617 data: 0.0017 max mem: 19788 +Test: [21300/21770] eta: 0:00:32 time: 0.0617 data: 0.0019 max mem: 19788 +Test: [21400/21770] eta: 0:00:25 time: 0.0809 data: 0.0025 max mem: 19788 +Test: [21500/21770] eta: 0:00:18 time: 0.0620 data: 0.0019 max mem: 19788 +Test: [21600/21770] eta: 0:00:11 time: 0.1117 data: 0.0078 max mem: 19788 +Test: [21700/21770] eta: 0:00:04 time: 0.0752 data: 0.0039 max mem: 19788 +Test: Total time: 0:24:48 +Final results: +Mean IoU is 62.95 + + precision@0.5 = 69.75 + precision@0.6 = 64.51 + precision@0.7 = 58.11 + precision@0.8 = 47.99 + precision@0.9 = 23.65 + overall IoU = 63.93 + mean IoU = 62.95 + +Mean accuracy for one-to-zero sample is 84.49 + +Average object IoU 0.6295303398333968 +Overall IoU 63.9256591796875 +Epoch: [26] [ 0/2138] eta: 3:16:55 lr: 1.9436505501538867e-05 loss: 0.0255 (0.0255) time: 5.5262 data: 1.6504 max mem: 19788 +Epoch: [26] [ 10/2138] eta: 2:15:34 lr: 1.9430661010139682e-05 loss: 0.0205 (0.0222) time: 3.8226 data: 0.1521 max mem: 19788 +Epoch: [26] [ 20/2138] eta: 2:11:57 lr: 1.942481632340649e-05 loss: 0.0205 (0.0217) time: 3.6490 data: 0.0023 max mem: 19788 +Epoch: [26] [ 30/2138] eta: 2:10:17 lr: 1.9418971441267437e-05 loss: 0.0209 (0.0218) time: 3.6456 data: 0.0027 max mem: 19788 +Epoch: [26] [ 40/2138] eta: 2:09:04 lr: 1.9413126363650645e-05 loss: 0.0232 (0.0227) time: 3.6416 data: 0.0030 max mem: 19788 +Epoch: [26] [ 50/2138] eta: 2:08:08 lr: 1.9407281090484167e-05 loss: 0.0239 (0.0234) time: 3.6417 data: 0.0029 max mem: 19788 +Epoch: [26] [ 60/2138] eta: 2:07:16 lr: 1.9401435621696023e-05 loss: 0.0211 (0.0229) time: 3.6417 data: 0.0029 max mem: 19788 +Epoch: [26] [ 70/2138] eta: 2:06:31 lr: 1.939558995721417e-05 loss: 0.0189 (0.0224) time: 3.6414 data: 0.0034 max mem: 19788 +Epoch: [26] [ 80/2138] eta: 2:05:45 lr: 1.938974409696652e-05 loss: 0.0206 (0.0231) time: 3.6407 data: 0.0034 max mem: 19788 +Epoch: [26] [ 90/2138] eta: 2:05:01 lr: 1.938389804088093e-05 loss: 0.0225 (0.0230) time: 3.6356 data: 0.0028 max mem: 19788 +Epoch: [26] [ 100/2138] eta: 2:04:20 lr: 1.937805178888522e-05 loss: 0.0228 (0.0233) time: 3.6367 data: 0.0027 max mem: 19788 +Epoch: [26] [ 110/2138] eta: 2:03:40 lr: 1.9372205340907133e-05 loss: 0.0246 (0.0236) time: 3.6413 data: 0.0027 max mem: 19788 +Epoch: [26] [ 120/2138] eta: 2:03:01 lr: 1.936635869687438e-05 loss: 0.0254 (0.0237) time: 3.6443 data: 0.0027 max mem: 19788 +Epoch: [26] [ 130/2138] eta: 2:02:21 lr: 1.9360511856714624e-05 loss: 0.0254 (0.0238) time: 3.6407 data: 0.0027 max mem: 19788 +Epoch: [26] [ 140/2138] eta: 2:01:43 lr: 1.9354664820355463e-05 loss: 0.0252 (0.0238) time: 3.6388 data: 0.0028 max mem: 19788 +Epoch: [26] [ 150/2138] eta: 2:01:05 lr: 1.9348817587724456e-05 loss: 0.0231 (0.0237) time: 3.6426 data: 0.0030 max mem: 19788 +Epoch: [26] [ 160/2138] eta: 2:00:25 lr: 1.93429701587491e-05 loss: 0.0240 (0.0240) time: 3.6388 data: 0.0031 max mem: 19788 +Epoch: [26] [ 170/2138] eta: 1:59:47 lr: 1.9337122533356862e-05 loss: 0.0260 (0.0241) time: 3.6365 data: 0.0031 max mem: 19788 +Epoch: [26] [ 180/2138] eta: 1:59:09 lr: 1.9331274711475124e-05 loss: 0.0228 (0.0242) time: 3.6362 data: 0.0030 max mem: 19788 +Epoch: [26] [ 190/2138] eta: 1:58:31 lr: 1.9325426693031252e-05 loss: 0.0224 (0.0241) time: 3.6379 data: 0.0029 max mem: 19788 +Epoch: [26] [ 200/2138] eta: 1:57:54 lr: 1.9319578477952527e-05 loss: 0.0202 (0.0239) time: 3.6428 data: 0.0027 max mem: 19788 +Epoch: [26] [ 210/2138] eta: 1:57:17 lr: 1.9313730066166212e-05 loss: 0.0268 (0.0242) time: 3.6421 data: 0.0028 max mem: 19788 +Epoch: [26] [ 220/2138] eta: 1:56:40 lr: 1.9307881457599494e-05 loss: 0.0268 (0.0241) time: 3.6435 data: 0.0029 max mem: 19788 +Epoch: [26] [ 230/2138] eta: 1:56:02 lr: 1.9302032652179523e-05 loss: 0.0235 (0.0243) time: 3.6424 data: 0.0032 max mem: 19788 +Epoch: [26] [ 240/2138] eta: 1:55:25 lr: 1.929618364983338e-05 loss: 0.0238 (0.0243) time: 3.6384 data: 0.0030 max mem: 19788 +Epoch: [26] [ 250/2138] eta: 1:54:48 lr: 1.9290334450488124e-05 loss: 0.0226 (0.0243) time: 3.6385 data: 0.0030 max mem: 19788 +Epoch: [26] [ 260/2138] eta: 1:54:11 lr: 1.9284485054070725e-05 loss: 0.0202 (0.0243) time: 3.6410 data: 0.0029 max mem: 19788 +Epoch: [26] [ 270/2138] eta: 1:53:34 lr: 1.9278635460508138e-05 loss: 0.0233 (0.0244) time: 3.6392 data: 0.0028 max mem: 19788 +Epoch: [26] [ 280/2138] eta: 1:52:56 lr: 1.9272785669727232e-05 loss: 0.0246 (0.0244) time: 3.6339 data: 0.0030 max mem: 19788 +Epoch: [26] [ 290/2138] eta: 1:52:19 lr: 1.926693568165486e-05 loss: 0.0246 (0.0244) time: 3.6357 data: 0.0029 max mem: 19788 +Epoch: [26] [ 300/2138] eta: 1:51:42 lr: 1.926108549621779e-05 loss: 0.0229 (0.0243) time: 3.6389 data: 0.0028 max mem: 19788 +Epoch: [26] [ 310/2138] eta: 1:51:05 lr: 1.925523511334276e-05 loss: 0.0207 (0.0245) time: 3.6365 data: 0.0028 max mem: 19788 +Epoch: [26] [ 320/2138] eta: 1:50:28 lr: 1.9249384532956443e-05 loss: 0.0225 (0.0245) time: 3.6338 data: 0.0029 max mem: 19788 +Epoch: [26] [ 330/2138] eta: 1:49:50 lr: 1.924353375498547e-05 loss: 0.0243 (0.0247) time: 3.6310 data: 0.0031 max mem: 19788 +Epoch: [26] [ 340/2138] eta: 1:49:14 lr: 1.9237682779356412e-05 loss: 0.0243 (0.0246) time: 3.6407 data: 0.0033 max mem: 19788 +Epoch: [26] [ 350/2138] eta: 1:48:37 lr: 1.9231831605995796e-05 loss: 0.0229 (0.0246) time: 3.6438 data: 0.0031 max mem: 19788 +Epoch: [26] [ 360/2138] eta: 1:48:01 lr: 1.9225980234830083e-05 loss: 0.0230 (0.0246) time: 3.6390 data: 0.0030 max mem: 19788 +Epoch: [26] [ 370/2138] eta: 1:47:24 lr: 1.9220128665785707e-05 loss: 0.0252 (0.0247) time: 3.6426 data: 0.0029 max mem: 19788 +Epoch: [26] [ 380/2138] eta: 1:46:47 lr: 1.921427689878902e-05 loss: 0.0246 (0.0247) time: 3.6416 data: 0.0030 max mem: 19788 +Epoch: [26] [ 390/2138] eta: 1:46:11 lr: 1.9208424933766342e-05 loss: 0.0226 (0.0247) time: 3.6406 data: 0.0030 max mem: 19788 +Epoch: [26] [ 400/2138] eta: 1:45:34 lr: 1.9202572770643933e-05 loss: 0.0247 (0.0247) time: 3.6403 data: 0.0029 max mem: 19788 +Epoch: [26] [ 410/2138] eta: 1:44:57 lr: 1.9196720409347994e-05 loss: 0.0263 (0.0248) time: 3.6389 data: 0.0027 max mem: 19788 +Epoch: [26] [ 420/2138] eta: 1:44:21 lr: 1.9190867849804696e-05 loss: 0.0247 (0.0248) time: 3.6397 data: 0.0029 max mem: 19788 +Epoch: [26] [ 430/2138] eta: 1:43:44 lr: 1.9185015091940122e-05 loss: 0.0242 (0.0248) time: 3.6442 data: 0.0030 max mem: 19788 +Epoch: [26] [ 440/2138] eta: 1:43:08 lr: 1.9179162135680347e-05 loss: 0.0248 (0.0249) time: 3.6394 data: 0.0030 max mem: 19788 +Epoch: [26] [ 450/2138] eta: 1:42:31 lr: 1.917330898095135e-05 loss: 0.0237 (0.0249) time: 3.6333 data: 0.0031 max mem: 19788 +Epoch: [26] [ 460/2138] eta: 1:41:54 lr: 1.9167455627679087e-05 loss: 0.0250 (0.0250) time: 3.6344 data: 0.0032 max mem: 19788 +Epoch: [26] [ 470/2138] eta: 1:41:17 lr: 1.9161602075789444e-05 loss: 0.0248 (0.0250) time: 3.6382 data: 0.0035 max mem: 19788 +Epoch: [26] [ 480/2138] eta: 1:40:41 lr: 1.915574832520827e-05 loss: 0.0240 (0.0250) time: 3.6421 data: 0.0037 max mem: 19788 +Epoch: [26] [ 490/2138] eta: 1:40:04 lr: 1.914989437586134e-05 loss: 0.0240 (0.0250) time: 3.6397 data: 0.0036 max mem: 19788 +Epoch: [26] [ 500/2138] eta: 1:39:27 lr: 1.9144040227674404e-05 loss: 0.0224 (0.0250) time: 3.6329 data: 0.0034 max mem: 19788 +Epoch: [26] [ 510/2138] eta: 1:38:51 lr: 1.9138185880573126e-05 loss: 0.0257 (0.0250) time: 3.6333 data: 0.0032 max mem: 19788 +Epoch: [26] [ 520/2138] eta: 1:38:14 lr: 1.9132331334483148e-05 loss: 0.0247 (0.0250) time: 3.6374 data: 0.0029 max mem: 19788 +Epoch: [26] [ 530/2138] eta: 1:37:38 lr: 1.9126476589330032e-05 loss: 0.0223 (0.0250) time: 3.6375 data: 0.0031 max mem: 19788 +Epoch: [26] [ 540/2138] eta: 1:37:01 lr: 1.912062164503931e-05 loss: 0.0217 (0.0249) time: 3.6353 data: 0.0030 max mem: 19788 +Epoch: [26] [ 550/2138] eta: 1:36:24 lr: 1.911476650153645e-05 loss: 0.0220 (0.0249) time: 3.6340 data: 0.0028 max mem: 19788 +Epoch: [26] [ 560/2138] eta: 1:35:47 lr: 1.9108911158746866e-05 loss: 0.0233 (0.0249) time: 3.6343 data: 0.0029 max mem: 19788 +Epoch: [26] [ 570/2138] eta: 1:35:11 lr: 1.9103055616595917e-05 loss: 0.0233 (0.0250) time: 3.6379 data: 0.0030 max mem: 19788 +Epoch: [26] [ 580/2138] eta: 1:34:35 lr: 1.9097199875008915e-05 loss: 0.0253 (0.0251) time: 3.6435 data: 0.0029 max mem: 19788 +Epoch: [26] [ 590/2138] eta: 1:33:58 lr: 1.909134393391111e-05 loss: 0.0243 (0.0250) time: 3.6422 data: 0.0027 max mem: 19788 +Epoch: [26] [ 600/2138] eta: 1:33:22 lr: 1.9085487793227714e-05 loss: 0.0222 (0.0250) time: 3.6386 data: 0.0029 max mem: 19788 +Epoch: [26] [ 610/2138] eta: 1:32:45 lr: 1.9079631452883866e-05 loss: 0.0232 (0.0251) time: 3.6375 data: 0.0029 max mem: 19788 +Epoch: [26] [ 620/2138] eta: 1:32:09 lr: 1.907377491280466e-05 loss: 0.0269 (0.0251) time: 3.6388 data: 0.0029 max mem: 19788 +Epoch: [26] [ 630/2138] eta: 1:31:32 lr: 1.9067918172915146e-05 loss: 0.0215 (0.0251) time: 3.6445 data: 0.0029 max mem: 19788 +Epoch: [26] [ 640/2138] eta: 1:30:56 lr: 1.9062061233140305e-05 loss: 0.0230 (0.0251) time: 3.6391 data: 0.0028 max mem: 19788 +Epoch: [26] [ 650/2138] eta: 1:30:19 lr: 1.9056204093405064e-05 loss: 0.0230 (0.0251) time: 3.6388 data: 0.0028 max mem: 19788 +Epoch: [26] [ 660/2138] eta: 1:29:43 lr: 1.905034675363432e-05 loss: 0.0228 (0.0251) time: 3.6455 data: 0.0027 max mem: 19788 +Epoch: [26] [ 670/2138] eta: 1:29:06 lr: 1.9044489213752878e-05 loss: 0.0258 (0.0251) time: 3.6420 data: 0.0027 max mem: 19788 +Epoch: [26] [ 680/2138] eta: 1:28:30 lr: 1.903863147368553e-05 loss: 0.0258 (0.0251) time: 3.6372 data: 0.0030 max mem: 19788 +Epoch: [26] [ 690/2138] eta: 1:27:53 lr: 1.9032773533356973e-05 loss: 0.0254 (0.0251) time: 3.6342 data: 0.0031 max mem: 19788 +Epoch: [26] [ 700/2138] eta: 1:27:17 lr: 1.9026915392691888e-05 loss: 0.0238 (0.0251) time: 3.6402 data: 0.0029 max mem: 19788 +Epoch: [26] [ 710/2138] eta: 1:26:40 lr: 1.902105705161488e-05 loss: 0.0248 (0.0251) time: 3.6387 data: 0.0029 max mem: 19788 +Epoch: [26] [ 720/2138] eta: 1:26:04 lr: 1.9015198510050493e-05 loss: 0.0229 (0.0251) time: 3.6343 data: 0.0028 max mem: 19788 +Epoch: [26] [ 730/2138] eta: 1:25:27 lr: 1.9009339767923246e-05 loss: 0.0229 (0.0252) time: 3.6370 data: 0.0027 max mem: 19788 +Epoch: [26] [ 740/2138] eta: 1:24:51 lr: 1.900348082515757e-05 loss: 0.0223 (0.0251) time: 3.6378 data: 0.0027 max mem: 19788 +Epoch: [26] [ 750/2138] eta: 1:24:14 lr: 1.899762168167787e-05 loss: 0.0224 (0.0251) time: 3.6371 data: 0.0029 max mem: 19788 +Epoch: [26] [ 760/2138] eta: 1:23:38 lr: 1.899176233740847e-05 loss: 0.0255 (0.0251) time: 3.6368 data: 0.0031 max mem: 19788 +Epoch: [26] [ 770/2138] eta: 1:23:01 lr: 1.8985902792273673e-05 loss: 0.0255 (0.0252) time: 3.6337 data: 0.0029 max mem: 19788 +Epoch: [26] [ 780/2138] eta: 1:22:24 lr: 1.8980043046197684e-05 loss: 0.0274 (0.0252) time: 3.6306 data: 0.0028 max mem: 19788 +Epoch: [26] [ 790/2138] eta: 1:21:48 lr: 1.89741830991047e-05 loss: 0.0260 (0.0252) time: 3.6328 data: 0.0033 max mem: 19788 +Epoch: [26] [ 800/2138] eta: 1:21:12 lr: 1.8968322950918827e-05 loss: 0.0231 (0.0252) time: 3.6366 data: 0.0033 max mem: 19788 +Epoch: [26] [ 810/2138] eta: 1:20:35 lr: 1.8962462601564137e-05 loss: 0.0231 (0.0252) time: 3.6355 data: 0.0029 max mem: 19788 +Epoch: [26] [ 820/2138] eta: 1:19:59 lr: 1.8956602050964634e-05 loss: 0.0255 (0.0252) time: 3.6416 data: 0.0027 max mem: 19788 +Epoch: [26] [ 830/2138] eta: 1:19:22 lr: 1.895074129904428e-05 loss: 0.0206 (0.0251) time: 3.6471 data: 0.0027 max mem: 19788 +Epoch: [26] [ 840/2138] eta: 1:18:46 lr: 1.894488034572697e-05 loss: 0.0196 (0.0251) time: 3.6396 data: 0.0027 max mem: 19788 +Epoch: [26] [ 850/2138] eta: 1:18:09 lr: 1.8939019190936556e-05 loss: 0.0205 (0.0251) time: 3.6356 data: 0.0027 max mem: 19788 +Epoch: [26] [ 860/2138] eta: 1:17:33 lr: 1.8933157834596822e-05 loss: 0.0253 (0.0251) time: 3.6336 data: 0.0030 max mem: 19788 +Epoch: [26] [ 870/2138] eta: 1:16:56 lr: 1.8927296276631508e-05 loss: 0.0253 (0.0251) time: 3.6315 data: 0.0032 max mem: 19788 +Epoch: [26] [ 880/2138] eta: 1:16:20 lr: 1.892143451696429e-05 loss: 0.0241 (0.0251) time: 3.6334 data: 0.0033 max mem: 19788 +Epoch: [26] [ 890/2138] eta: 1:15:43 lr: 1.8915572555518802e-05 loss: 0.0265 (0.0251) time: 3.6424 data: 0.0032 max mem: 19788 +Epoch: [26] [ 900/2138] eta: 1:15:07 lr: 1.8909710392218603e-05 loss: 0.0279 (0.0252) time: 3.6424 data: 0.0030 max mem: 19788 +Epoch: [26] [ 910/2138] eta: 1:14:30 lr: 1.890384802698722e-05 loss: 0.0244 (0.0252) time: 3.6365 data: 0.0031 max mem: 19788 +Epoch: [26] [ 920/2138] eta: 1:13:54 lr: 1.8897985459748098e-05 loss: 0.0237 (0.0252) time: 3.6388 data: 0.0029 max mem: 19788 +Epoch: [26] [ 930/2138] eta: 1:13:18 lr: 1.889212269042466e-05 loss: 0.0222 (0.0252) time: 3.6422 data: 0.0029 max mem: 19788 +Epoch: [26] [ 940/2138] eta: 1:12:41 lr: 1.8886259718940234e-05 loss: 0.0236 (0.0252) time: 3.6393 data: 0.0031 max mem: 19788 +Epoch: [26] [ 950/2138] eta: 1:12:05 lr: 1.8880396545218132e-05 loss: 0.0234 (0.0252) time: 3.6346 data: 0.0030 max mem: 19788 +Epoch: [26] [ 960/2138] eta: 1:11:28 lr: 1.8874533169181574e-05 loss: 0.0234 (0.0252) time: 3.6343 data: 0.0029 max mem: 19788 +Epoch: [26] [ 970/2138] eta: 1:10:52 lr: 1.8868669590753757e-05 loss: 0.0230 (0.0251) time: 3.6317 data: 0.0033 max mem: 19788 +Epoch: [26] [ 980/2138] eta: 1:10:15 lr: 1.8862805809857795e-05 loss: 0.0213 (0.0251) time: 3.6308 data: 0.0036 max mem: 19788 +Epoch: [26] [ 990/2138] eta: 1:09:39 lr: 1.8856941826416773e-05 loss: 0.0249 (0.0251) time: 3.6380 data: 0.0032 max mem: 19788 +Epoch: [26] [1000/2138] eta: 1:09:02 lr: 1.8851077640353683e-05 loss: 0.0265 (0.0251) time: 3.6449 data: 0.0029 max mem: 19788 +Epoch: [26] [1010/2138] eta: 1:08:26 lr: 1.884521325159151e-05 loss: 0.0227 (0.0251) time: 3.6437 data: 0.0031 max mem: 19788 +Epoch: [26] [1020/2138] eta: 1:07:50 lr: 1.883934866005314e-05 loss: 0.0230 (0.0251) time: 3.6354 data: 0.0031 max mem: 19788 +Epoch: [26] [1030/2138] eta: 1:07:13 lr: 1.8833483865661423e-05 loss: 0.0236 (0.0251) time: 3.6336 data: 0.0030 max mem: 19788 +Epoch: [26] [1040/2138] eta: 1:06:37 lr: 1.882761886833915e-05 loss: 0.0212 (0.0252) time: 3.6372 data: 0.0029 max mem: 19788 +Epoch: [26] [1050/2138] eta: 1:06:00 lr: 1.8821753668009056e-05 loss: 0.0247 (0.0252) time: 3.6353 data: 0.0028 max mem: 19788 +Epoch: [26] [1060/2138] eta: 1:05:24 lr: 1.8815888264593825e-05 loss: 0.0247 (0.0252) time: 3.6317 data: 0.0030 max mem: 19788 +Epoch: [26] [1070/2138] eta: 1:04:47 lr: 1.881002265801607e-05 loss: 0.0223 (0.0251) time: 3.6328 data: 0.0033 max mem: 19788 +Epoch: [26] [1080/2138] eta: 1:04:11 lr: 1.880415684819836e-05 loss: 0.0210 (0.0251) time: 3.6378 data: 0.0032 max mem: 19788 +Epoch: [26] [1090/2138] eta: 1:03:34 lr: 1.8798290835063205e-05 loss: 0.0241 (0.0251) time: 3.6383 data: 0.0028 max mem: 19788 +Epoch: [26] [1100/2138] eta: 1:02:58 lr: 1.8792424618533062e-05 loss: 0.0268 (0.0251) time: 3.6406 data: 0.0028 max mem: 19788 +Epoch: [26] [1110/2138] eta: 1:02:22 lr: 1.8786558198530316e-05 loss: 0.0262 (0.0251) time: 3.6437 data: 0.0029 max mem: 19788 +Epoch: [26] [1120/2138] eta: 1:01:45 lr: 1.8780691574977325e-05 loss: 0.0229 (0.0252) time: 3.6414 data: 0.0031 max mem: 19788 +Epoch: [26] [1130/2138] eta: 1:01:09 lr: 1.877482474779635e-05 loss: 0.0235 (0.0252) time: 3.6567 data: 0.0032 max mem: 19788 +Epoch: [26] [1140/2138] eta: 1:00:33 lr: 1.8768957716909644e-05 loss: 0.0228 (0.0252) time: 3.6528 data: 0.0032 max mem: 19788 +Epoch: [26] [1150/2138] eta: 0:59:56 lr: 1.8763090482239353e-05 loss: 0.0221 (0.0251) time: 3.6303 data: 0.0030 max mem: 19788 +Epoch: [26] [1160/2138] eta: 0:59:20 lr: 1.8757223043707605e-05 loss: 0.0230 (0.0251) time: 3.6303 data: 0.0030 max mem: 19788 +Epoch: [26] [1170/2138] eta: 0:58:43 lr: 1.875135540123645e-05 loss: 0.0230 (0.0251) time: 3.6293 data: 0.0032 max mem: 19788 +Epoch: [26] [1180/2138] eta: 0:58:07 lr: 1.874548755474789e-05 loss: 0.0250 (0.0251) time: 3.6337 data: 0.0033 max mem: 19788 +Epoch: [26] [1190/2138] eta: 0:57:30 lr: 1.8739619504163868e-05 loss: 0.0239 (0.0251) time: 3.6370 data: 0.0033 max mem: 19788 +Epoch: [26] [1200/2138] eta: 0:56:54 lr: 1.873375124940627e-05 loss: 0.0230 (0.0251) time: 3.6329 data: 0.0030 max mem: 19788 +Epoch: [26] [1210/2138] eta: 0:56:17 lr: 1.8727882790396917e-05 loss: 0.0244 (0.0251) time: 3.6338 data: 0.0029 max mem: 19788 +Epoch: [26] [1220/2138] eta: 0:55:41 lr: 1.8722014127057595e-05 loss: 0.0247 (0.0252) time: 3.6400 data: 0.0030 max mem: 19788 +Epoch: [26] [1230/2138] eta: 0:55:05 lr: 1.8716145259309997e-05 loss: 0.0214 (0.0251) time: 3.6432 data: 0.0028 max mem: 19788 +Epoch: [26] [1240/2138] eta: 0:54:28 lr: 1.8710276187075802e-05 loss: 0.0230 (0.0251) time: 3.6393 data: 0.0028 max mem: 19788 +Epoch: [26] [1250/2138] eta: 0:53:52 lr: 1.870440691027659e-05 loss: 0.0230 (0.0251) time: 3.6378 data: 0.0028 max mem: 19788 +Epoch: [26] [1260/2138] eta: 0:53:15 lr: 1.8698537428833925e-05 loss: 0.0211 (0.0251) time: 3.6394 data: 0.0029 max mem: 19788 +Epoch: [26] [1270/2138] eta: 0:52:39 lr: 1.8692667742669263e-05 loss: 0.0208 (0.0251) time: 3.6392 data: 0.0028 max mem: 19788 +Epoch: [26] [1280/2138] eta: 0:52:03 lr: 1.868679785170406e-05 loss: 0.0226 (0.0251) time: 3.6389 data: 0.0029 max mem: 19788 +Epoch: [26] [1290/2138] eta: 0:51:26 lr: 1.8680927755859666e-05 loss: 0.0224 (0.0251) time: 3.6353 data: 0.0029 max mem: 19788 +Epoch: [26] [1300/2138] eta: 0:50:50 lr: 1.86750574550574e-05 loss: 0.0230 (0.0251) time: 3.6344 data: 0.0027 max mem: 19788 +Epoch: [26] [1310/2138] eta: 0:50:13 lr: 1.8669186949218513e-05 loss: 0.0239 (0.0251) time: 3.6384 data: 0.0026 max mem: 19788 +Epoch: [26] [1320/2138] eta: 0:49:37 lr: 1.8663316238264207e-05 loss: 0.0239 (0.0251) time: 3.6372 data: 0.0028 max mem: 19788 +Epoch: [26] [1330/2138] eta: 0:49:00 lr: 1.8657445322115617e-05 loss: 0.0237 (0.0251) time: 3.6354 data: 0.0029 max mem: 19788 +Epoch: [26] [1340/2138] eta: 0:48:24 lr: 1.8651574200693813e-05 loss: 0.0231 (0.0251) time: 3.6421 data: 0.0028 max mem: 19788 +Epoch: [26] [1350/2138] eta: 0:47:48 lr: 1.864570287391984e-05 loss: 0.0284 (0.0252) time: 3.6416 data: 0.0027 max mem: 19788 +Epoch: [26] [1360/2138] eta: 0:47:11 lr: 1.8639831341714638e-05 loss: 0.0290 (0.0252) time: 3.6471 data: 0.0027 max mem: 19788 +Epoch: [26] [1370/2138] eta: 0:46:35 lr: 1.8633959603999136e-05 loss: 0.0256 (0.0252) time: 3.6477 data: 0.0027 max mem: 19788 +Epoch: [26] [1380/2138] eta: 0:45:59 lr: 1.8628087660694162e-05 loss: 0.0245 (0.0253) time: 3.6385 data: 0.0029 max mem: 19788 +Epoch: [26] [1390/2138] eta: 0:45:22 lr: 1.8622215511720525e-05 loss: 0.0263 (0.0255) time: 3.6489 data: 0.0029 max mem: 19788 +Epoch: [26] [1400/2138] eta: 0:44:46 lr: 1.861634315699894e-05 loss: 0.0242 (0.0255) time: 3.6478 data: 0.0029 max mem: 19788 +Epoch: [26] [1410/2138] eta: 0:44:10 lr: 1.861047059645009e-05 loss: 0.0229 (0.0255) time: 3.6396 data: 0.0029 max mem: 19788 +Epoch: [26] [1420/2138] eta: 0:43:33 lr: 1.8604597829994588e-05 loss: 0.0234 (0.0255) time: 3.6397 data: 0.0028 max mem: 19788 +Epoch: [26] [1430/2138] eta: 0:42:57 lr: 1.8598724857552992e-05 loss: 0.0247 (0.0255) time: 3.6501 data: 0.0028 max mem: 19788 +Epoch: [26] [1440/2138] eta: 0:42:20 lr: 1.8592851679045794e-05 loss: 0.0241 (0.0254) time: 3.6535 data: 0.0031 max mem: 19788 +Epoch: [26] [1450/2138] eta: 0:41:44 lr: 1.8586978294393446e-05 loss: 0.0264 (0.0255) time: 3.6467 data: 0.0032 max mem: 19788 +Epoch: [26] [1460/2138] eta: 0:41:08 lr: 1.858110470351631e-05 loss: 0.0278 (0.0255) time: 3.6420 data: 0.0030 max mem: 19788 +Epoch: [26] [1470/2138] eta: 0:40:31 lr: 1.857523090633473e-05 loss: 0.0274 (0.0256) time: 3.6351 data: 0.0030 max mem: 19788 +Epoch: [26] [1480/2138] eta: 0:39:55 lr: 1.8569356902768943e-05 loss: 0.0266 (0.0256) time: 3.6344 data: 0.0027 max mem: 19788 +Epoch: [26] [1490/2138] eta: 0:39:18 lr: 1.856348269273918e-05 loss: 0.0266 (0.0256) time: 3.6367 data: 0.0027 max mem: 19788 +Epoch: [26] [1500/2138] eta: 0:38:42 lr: 1.855760827616557e-05 loss: 0.0256 (0.0256) time: 3.6340 data: 0.0030 max mem: 19788 +Epoch: [26] [1510/2138] eta: 0:38:06 lr: 1.8551733652968206e-05 loss: 0.0256 (0.0256) time: 3.6355 data: 0.0029 max mem: 19788 +Epoch: [26] [1520/2138] eta: 0:37:29 lr: 1.854585882306711e-05 loss: 0.0230 (0.0255) time: 3.6368 data: 0.0031 max mem: 19788 +Epoch: [26] [1530/2138] eta: 0:36:53 lr: 1.8539983786382256e-05 loss: 0.0203 (0.0255) time: 3.6378 data: 0.0031 max mem: 19788 +Epoch: [26] [1540/2138] eta: 0:36:16 lr: 1.8534108542833547e-05 loss: 0.0203 (0.0255) time: 3.6367 data: 0.0030 max mem: 19788 +Epoch: [26] [1550/2138] eta: 0:35:40 lr: 1.8528233092340842e-05 loss: 0.0235 (0.0255) time: 3.6329 data: 0.0031 max mem: 19788 +Epoch: [26] [1560/2138] eta: 0:35:03 lr: 1.852235743482392e-05 loss: 0.0235 (0.0255) time: 3.6366 data: 0.0030 max mem: 19788 +Epoch: [26] [1570/2138] eta: 0:34:27 lr: 1.8516481570202525e-05 loss: 0.0227 (0.0255) time: 3.6338 data: 0.0032 max mem: 19788 +Epoch: [26] [1580/2138] eta: 0:33:51 lr: 1.8510605498396313e-05 loss: 0.0218 (0.0255) time: 3.6373 data: 0.0031 max mem: 19788 +Epoch: [26] [1590/2138] eta: 0:33:14 lr: 1.8504729219324916e-05 loss: 0.0224 (0.0255) time: 3.6369 data: 0.0031 max mem: 19788 +Epoch: [26] [1600/2138] eta: 0:32:38 lr: 1.8498852732907864e-05 loss: 0.0259 (0.0255) time: 3.6298 data: 0.0032 max mem: 19788 +Epoch: [26] [1610/2138] eta: 0:32:01 lr: 1.8492976039064673e-05 loss: 0.0231 (0.0255) time: 3.6330 data: 0.0031 max mem: 19788 +Epoch: [26] [1620/2138] eta: 0:31:25 lr: 1.8487099137714762e-05 loss: 0.0214 (0.0254) time: 3.6382 data: 0.0031 max mem: 19788 +Epoch: [26] [1630/2138] eta: 0:30:49 lr: 1.8481222028777503e-05 loss: 0.0247 (0.0254) time: 3.6423 data: 0.0031 max mem: 19788 +Epoch: [26] [1640/2138] eta: 0:30:12 lr: 1.847534471217222e-05 loss: 0.0240 (0.0254) time: 3.6412 data: 0.0028 max mem: 19788 +Epoch: [26] [1650/2138] eta: 0:29:36 lr: 1.8469467187818158e-05 loss: 0.0210 (0.0254) time: 3.6431 data: 0.0027 max mem: 19788 +Epoch: [26] [1660/2138] eta: 0:28:59 lr: 1.846358945563452e-05 loss: 0.0203 (0.0254) time: 3.6446 data: 0.0031 max mem: 19788 +Epoch: [26] [1670/2138] eta: 0:28:23 lr: 1.8457711515540428e-05 loss: 0.0225 (0.0254) time: 3.6346 data: 0.0033 max mem: 19788 +Epoch: [26] [1680/2138] eta: 0:27:47 lr: 1.8451833367454966e-05 loss: 0.0234 (0.0254) time: 3.6262 data: 0.0029 max mem: 19788 +Epoch: [26] [1690/2138] eta: 0:27:10 lr: 1.844595501129714e-05 loss: 0.0234 (0.0254) time: 3.6353 data: 0.0026 max mem: 19788 +Epoch: [26] [1700/2138] eta: 0:26:34 lr: 1.844007644698591e-05 loss: 0.0216 (0.0254) time: 3.6444 data: 0.0027 max mem: 19788 +Epoch: [26] [1710/2138] eta: 0:25:57 lr: 1.843419767444016e-05 loss: 0.0231 (0.0254) time: 3.6414 data: 0.0028 max mem: 19788 +Epoch: [26] [1720/2138] eta: 0:25:21 lr: 1.842831869357874e-05 loss: 0.0237 (0.0254) time: 3.6425 data: 0.0028 max mem: 19788 +Epoch: [26] [1730/2138] eta: 0:24:45 lr: 1.8422439504320403e-05 loss: 0.0246 (0.0254) time: 3.6457 data: 0.0028 max mem: 19788 +Epoch: [26] [1740/2138] eta: 0:24:08 lr: 1.8416560106583873e-05 loss: 0.0253 (0.0254) time: 3.6370 data: 0.0027 max mem: 19788 +Epoch: [26] [1750/2138] eta: 0:23:32 lr: 1.8410680500287794e-05 loss: 0.0235 (0.0254) time: 3.6324 data: 0.0028 max mem: 19788 +Epoch: [26] [1760/2138] eta: 0:22:55 lr: 1.8404800685350767e-05 loss: 0.0235 (0.0254) time: 3.6421 data: 0.0029 max mem: 19788 +Epoch: [26] [1770/2138] eta: 0:22:19 lr: 1.839892066169131e-05 loss: 0.0235 (0.0254) time: 3.6400 data: 0.0029 max mem: 19788 +Epoch: [26] [1780/2138] eta: 0:21:43 lr: 1.83930404292279e-05 loss: 0.0228 (0.0254) time: 3.6401 data: 0.0031 max mem: 19788 +Epoch: [26] [1790/2138] eta: 0:21:06 lr: 1.8387159987878938e-05 loss: 0.0228 (0.0254) time: 3.6434 data: 0.0029 max mem: 19788 +Epoch: [26] [1800/2138] eta: 0:20:30 lr: 1.8381279337562784e-05 loss: 0.0215 (0.0254) time: 3.6383 data: 0.0027 max mem: 19788 +Epoch: [26] [1810/2138] eta: 0:19:53 lr: 1.8375398478197707e-05 loss: 0.0216 (0.0254) time: 3.6374 data: 0.0029 max mem: 19788 +Epoch: [26] [1820/2138] eta: 0:19:17 lr: 1.8369517409701953e-05 loss: 0.0229 (0.0254) time: 3.6401 data: 0.0028 max mem: 19788 +Epoch: [26] [1830/2138] eta: 0:18:41 lr: 1.836363613199367e-05 loss: 0.0226 (0.0254) time: 3.6398 data: 0.0030 max mem: 19788 +Epoch: [26] [1840/2138] eta: 0:18:04 lr: 1.835775464499097e-05 loss: 0.0236 (0.0255) time: 3.6390 data: 0.0031 max mem: 19788 +Epoch: [26] [1850/2138] eta: 0:17:28 lr: 1.8351872948611892e-05 loss: 0.0272 (0.0255) time: 3.6351 data: 0.0029 max mem: 19788 +Epoch: [26] [1860/2138] eta: 0:16:51 lr: 1.8345991042774417e-05 loss: 0.0256 (0.0255) time: 3.6323 data: 0.0029 max mem: 19788 +Epoch: [26] [1870/2138] eta: 0:16:15 lr: 1.834010892739646e-05 loss: 0.0231 (0.0255) time: 3.6358 data: 0.0029 max mem: 19788 +Epoch: [26] [1880/2138] eta: 0:15:39 lr: 1.8334226602395896e-05 loss: 0.0225 (0.0255) time: 3.6384 data: 0.0029 max mem: 19788 +Epoch: [26] [1890/2138] eta: 0:15:02 lr: 1.8328344067690498e-05 loss: 0.0225 (0.0255) time: 3.6419 data: 0.0028 max mem: 19788 +Epoch: [26] [1900/2138] eta: 0:14:26 lr: 1.8322461323198018e-05 loss: 0.0200 (0.0255) time: 3.6411 data: 0.0029 max mem: 19788 +Epoch: [26] [1910/2138] eta: 0:13:49 lr: 1.831657836883612e-05 loss: 0.0225 (0.0254) time: 3.6361 data: 0.0029 max mem: 19788 +Epoch: [26] [1920/2138] eta: 0:13:13 lr: 1.831069520452242e-05 loss: 0.0226 (0.0254) time: 3.6350 data: 0.0030 max mem: 19788 +Epoch: [26] [1930/2138] eta: 0:12:37 lr: 1.8304811830174472e-05 loss: 0.0229 (0.0254) time: 3.6370 data: 0.0030 max mem: 19788 +Epoch: [26] [1940/2138] eta: 0:12:00 lr: 1.8298928245709752e-05 loss: 0.0241 (0.0254) time: 3.6395 data: 0.0031 max mem: 19788 +Epoch: [26] [1950/2138] eta: 0:11:24 lr: 1.8293044451045698e-05 loss: 0.0230 (0.0254) time: 3.6423 data: 0.0031 max mem: 19788 +Epoch: [26] [1960/2138] eta: 0:10:47 lr: 1.8287160446099667e-05 loss: 0.0234 (0.0254) time: 3.6374 data: 0.0030 max mem: 19788 +Epoch: [26] [1970/2138] eta: 0:10:11 lr: 1.828127623078896e-05 loss: 0.0234 (0.0254) time: 3.6385 data: 0.0028 max mem: 19788 +Epoch: [26] [1980/2138] eta: 0:09:35 lr: 1.8275391805030826e-05 loss: 0.0216 (0.0254) time: 3.6556 data: 0.0029 max mem: 19788 +Epoch: [26] [1990/2138] eta: 0:08:58 lr: 1.8269507168742435e-05 loss: 0.0225 (0.0254) time: 3.6507 data: 0.0029 max mem: 19788 +Epoch: [26] [2000/2138] eta: 0:08:22 lr: 1.82636223218409e-05 loss: 0.0242 (0.0254) time: 3.6342 data: 0.0028 max mem: 19788 +Epoch: [26] [2010/2138] eta: 0:07:45 lr: 1.825773726424329e-05 loss: 0.0242 (0.0254) time: 3.6316 data: 0.0029 max mem: 19788 +Epoch: [26] [2020/2138] eta: 0:07:09 lr: 1.8251851995866573e-05 loss: 0.0242 (0.0254) time: 3.6314 data: 0.0029 max mem: 19788 +Epoch: [26] [2030/2138] eta: 0:06:33 lr: 1.8245966516627697e-05 loss: 0.0260 (0.0254) time: 3.6420 data: 0.0030 max mem: 19788 +Epoch: [26] [2040/2138] eta: 0:05:56 lr: 1.8240080826443515e-05 loss: 0.0243 (0.0254) time: 3.6403 data: 0.0030 max mem: 19788 +Epoch: [26] [2050/2138] eta: 0:05:20 lr: 1.823419492523084e-05 loss: 0.0239 (0.0254) time: 3.6350 data: 0.0029 max mem: 19788 +Epoch: [26] [2060/2138] eta: 0:04:43 lr: 1.82283088129064e-05 loss: 0.0238 (0.0254) time: 3.6363 data: 0.0030 max mem: 19788 +Epoch: [26] [2070/2138] eta: 0:04:07 lr: 1.822242248938689e-05 loss: 0.0221 (0.0254) time: 3.6347 data: 0.0033 max mem: 19788 +Epoch: [26] [2080/2138] eta: 0:03:31 lr: 1.821653595458891e-05 loss: 0.0231 (0.0254) time: 3.6394 data: 0.0032 max mem: 19788 +Epoch: [26] [2090/2138] eta: 0:02:54 lr: 1.821064920842902e-05 loss: 0.0227 (0.0254) time: 3.6411 data: 0.0028 max mem: 19788 +Epoch: [26] [2100/2138] eta: 0:02:18 lr: 1.8204762250823706e-05 loss: 0.0204 (0.0254) time: 3.6404 data: 0.0028 max mem: 19788 +Epoch: [26] [2110/2138] eta: 0:01:41 lr: 1.8198875081689397e-05 loss: 0.0272 (0.0254) time: 3.6426 data: 0.0030 max mem: 19788 +Epoch: [26] [2120/2138] eta: 0:01:05 lr: 1.8192987700942455e-05 loss: 0.0294 (0.0254) time: 3.6393 data: 0.0030 max mem: 19788 +Epoch: [26] [2130/2138] eta: 0:00:29 lr: 1.8187100108499182e-05 loss: 0.0260 (0.0254) time: 3.6215 data: 0.0028 max mem: 19788 +Epoch: [26] Total time: 2:09:41 +Test: [ 0/21770] eta: 19:55:24 time: 3.2946 data: 3.1690 max mem: 19788 +Test: [ 100/21770] eta: 0:35:51 time: 0.0595 data: 0.0017 max mem: 19788 +Test: [ 200/21770] eta: 0:29:29 time: 0.0705 data: 0.0020 max mem: 19788 +Test: [ 300/21770] eta: 0:27:26 time: 0.0628 data: 0.0018 max mem: 19788 +Test: [ 400/21770] eta: 0:25:59 time: 0.0614 data: 0.0020 max mem: 19788 +Test: [ 500/21770] eta: 0:25:13 time: 0.0633 data: 0.0019 max mem: 19788 +Test: [ 600/21770] eta: 0:24:47 time: 0.0691 data: 0.0018 max mem: 19788 +Test: [ 700/21770] eta: 0:24:24 time: 0.0616 data: 0.0018 max mem: 19788 +Test: [ 800/21770] eta: 0:24:16 time: 0.0681 data: 0.0019 max mem: 19788 +Test: [ 900/21770] eta: 0:24:12 time: 0.0730 data: 0.0024 max mem: 19788 +Test: [ 1000/21770] eta: 0:23:56 time: 0.0661 data: 0.0018 max mem: 19788 +Test: [ 1100/21770] eta: 0:24:01 time: 0.0815 data: 0.0019 max mem: 19788 +Test: [ 1200/21770] eta: 0:24:00 time: 0.0791 data: 0.0023 max mem: 19788 +Test: [ 1300/21770] eta: 0:24:00 time: 0.0754 data: 0.0022 max mem: 19788 +Test: [ 1400/21770] eta: 0:23:43 time: 0.0621 data: 0.0019 max mem: 19788 +Test: [ 1500/21770] eta: 0:23:36 time: 0.0667 data: 0.0019 max mem: 19788 +Test: [ 1600/21770] eta: 0:23:24 time: 0.0695 data: 0.0020 max mem: 19788 +Test: [ 1700/21770] eta: 0:23:17 time: 0.0686 data: 0.0019 max mem: 19788 +Test: [ 1800/21770] eta: 0:23:08 time: 0.0721 data: 0.0022 max mem: 19788 +Test: [ 1900/21770] eta: 0:22:59 time: 0.0674 data: 0.0020 max mem: 19788 +Test: [ 2000/21770] eta: 0:22:48 time: 0.0762 data: 0.0018 max mem: 19788 +Test: [ 2100/21770] eta: 0:22:39 time: 0.0590 data: 0.0018 max mem: 19788 +Test: [ 2200/21770] eta: 0:22:25 time: 0.0634 data: 0.0021 max mem: 19788 +Test: [ 2300/21770] eta: 0:22:17 time: 0.0673 data: 0.0019 max mem: 19788 +Test: [ 2400/21770] eta: 0:22:12 time: 0.0787 data: 0.0019 max mem: 19788 +Test: [ 2500/21770] eta: 0:22:00 time: 0.0615 data: 0.0021 max mem: 19788 +Test: [ 2600/21770] eta: 0:21:55 time: 0.0758 data: 0.0019 max mem: 19788 +Test: [ 2700/21770] eta: 0:21:51 time: 0.0649 data: 0.0017 max mem: 19788 +Test: [ 2800/21770] eta: 0:21:47 time: 0.0764 data: 0.0023 max mem: 19788 +Test: [ 2900/21770] eta: 0:21:41 time: 0.0657 data: 0.0020 max mem: 19788 +Test: [ 3000/21770] eta: 0:21:32 time: 0.0754 data: 0.0022 max mem: 19788 +Test: [ 3100/21770] eta: 0:21:23 time: 0.0628 data: 0.0021 max mem: 19788 +Test: [ 3200/21770] eta: 0:21:18 time: 0.0713 data: 0.0022 max mem: 19788 +Test: [ 3300/21770] eta: 0:21:10 time: 0.0645 data: 0.0020 max mem: 19788 +Test: [ 3400/21770] eta: 0:21:03 time: 0.0736 data: 0.0022 max mem: 19788 +Test: [ 3500/21770] eta: 0:20:58 time: 0.0800 data: 0.0023 max mem: 19788 +Test: [ 3600/21770] eta: 0:20:54 time: 0.0700 data: 0.0022 max mem: 19788 +Test: [ 3700/21770] eta: 0:20:50 time: 0.0675 data: 0.0019 max mem: 19788 +Test: [ 3800/21770] eta: 0:20:41 time: 0.0761 data: 0.0022 max mem: 19788 +Test: [ 3900/21770] eta: 0:20:32 time: 0.0634 data: 0.0018 max mem: 19788 +Test: [ 4000/21770] eta: 0:20:25 time: 0.0685 data: 0.0021 max mem: 19788 +Test: [ 4100/21770] eta: 0:20:19 time: 0.0628 data: 0.0020 max mem: 19788 +Test: [ 4200/21770] eta: 0:20:14 time: 0.0753 data: 0.0019 max mem: 19788 +Test: [ 4300/21770] eta: 0:20:08 time: 0.0684 data: 0.0019 max mem: 19788 +Test: [ 4400/21770] eta: 0:20:00 time: 0.0618 data: 0.0018 max mem: 19788 +Test: [ 4500/21770] eta: 0:19:53 time: 0.0622 data: 0.0018 max mem: 19788 +Test: [ 4600/21770] eta: 0:19:46 time: 0.0629 data: 0.0017 max mem: 19788 +Test: [ 4700/21770] eta: 0:19:40 time: 0.0715 data: 0.0022 max mem: 19788 +Test: [ 4800/21770] eta: 0:19:33 time: 0.0682 data: 0.0021 max mem: 19788 +Test: [ 4900/21770] eta: 0:19:25 time: 0.0606 data: 0.0016 max mem: 19788 +Test: [ 5000/21770] eta: 0:19:18 time: 0.0690 data: 0.0019 max mem: 19788 +Test: [ 5100/21770] eta: 0:19:09 time: 0.0684 data: 0.0018 max mem: 19788 +Test: [ 5200/21770] eta: 0:19:01 time: 0.0778 data: 0.0023 max mem: 19788 +Test: [ 5300/21770] eta: 0:18:55 time: 0.0625 data: 0.0018 max mem: 19788 +Test: [ 5400/21770] eta: 0:18:48 time: 0.0672 data: 0.0018 max mem: 19788 +Test: [ 5500/21770] eta: 0:18:42 time: 0.0717 data: 0.0019 max mem: 19788 +Test: [ 5600/21770] eta: 0:18:35 time: 0.0690 data: 0.0019 max mem: 19788 +Test: [ 5700/21770] eta: 0:18:27 time: 0.0733 data: 0.0023 max mem: 19788 +Test: [ 5800/21770] eta: 0:18:20 time: 0.0796 data: 0.0023 max mem: 19788 +Test: [ 5900/21770] eta: 0:18:14 time: 0.0668 data: 0.0018 max mem: 19788 +Test: [ 6000/21770] eta: 0:18:07 time: 0.0680 data: 0.0018 max mem: 19788 +Test: [ 6100/21770] eta: 0:18:00 time: 0.0694 data: 0.0018 max mem: 19788 +Test: [ 6200/21770] eta: 0:17:52 time: 0.0631 data: 0.0018 max mem: 19788 +Test: [ 6300/21770] eta: 0:17:44 time: 0.0617 data: 0.0019 max mem: 19788 +Test: [ 6400/21770] eta: 0:17:36 time: 0.0626 data: 0.0019 max mem: 19788 +Test: [ 6500/21770] eta: 0:17:28 time: 0.0621 data: 0.0021 max mem: 19788 +Test: [ 6600/21770] eta: 0:17:21 time: 0.0622 data: 0.0018 max mem: 19788 +Test: [ 6700/21770] eta: 0:17:13 time: 0.0644 data: 0.0018 max mem: 19788 +Test: [ 6800/21770] eta: 0:17:06 time: 0.0616 data: 0.0016 max mem: 19788 +Test: [ 6900/21770] eta: 0:16:59 time: 0.0610 data: 0.0018 max mem: 19788 +Test: [ 7000/21770] eta: 0:16:52 time: 0.0623 data: 0.0018 max mem: 19788 +Test: [ 7100/21770] eta: 0:16:46 time: 0.0606 data: 0.0018 max mem: 19788 +Test: [ 7200/21770] eta: 0:16:40 time: 0.0618 data: 0.0019 max mem: 19788 +Test: [ 7300/21770] eta: 0:16:32 time: 0.0618 data: 0.0016 max mem: 19788 +Test: [ 7400/21770] eta: 0:16:24 time: 0.0629 data: 0.0019 max mem: 19788 +Test: [ 7500/21770] eta: 0:16:17 time: 0.0725 data: 0.0022 max mem: 19788 +Test: [ 7600/21770] eta: 0:16:09 time: 0.0682 data: 0.0020 max mem: 19788 +Test: [ 7700/21770] eta: 0:16:02 time: 0.0620 data: 0.0017 max mem: 19788 +Test: [ 7800/21770] eta: 0:15:55 time: 0.0640 data: 0.0018 max mem: 19788 +Test: [ 7900/21770] eta: 0:15:48 time: 0.0629 data: 0.0018 max mem: 19788 +Test: [ 8000/21770] eta: 0:15:41 time: 0.0679 data: 0.0019 max mem: 19788 +Test: [ 8100/21770] eta: 0:15:33 time: 0.0610 data: 0.0017 max mem: 19788 +Test: [ 8200/21770] eta: 0:15:26 time: 0.0618 data: 0.0019 max mem: 19788 +Test: [ 8300/21770] eta: 0:15:18 time: 0.0709 data: 0.0020 max mem: 19788 +Test: [ 8400/21770] eta: 0:15:12 time: 0.0644 data: 0.0018 max mem: 19788 +Test: [ 8500/21770] eta: 0:15:05 time: 0.0620 data: 0.0018 max mem: 19788 +Test: [ 8600/21770] eta: 0:14:58 time: 0.0619 data: 0.0020 max mem: 19788 +Test: [ 8700/21770] eta: 0:14:51 time: 0.0614 data: 0.0020 max mem: 19788 +Test: [ 8800/21770] eta: 0:14:44 time: 0.0809 data: 0.0024 max mem: 19788 +Test: [ 8900/21770] eta: 0:14:38 time: 0.0811 data: 0.0026 max mem: 19788 +Test: [ 9000/21770] eta: 0:14:32 time: 0.0740 data: 0.0021 max mem: 19788 +Test: [ 9100/21770] eta: 0:14:24 time: 0.0630 data: 0.0018 max mem: 19788 +Test: [ 9200/21770] eta: 0:14:17 time: 0.0746 data: 0.0021 max mem: 19788 +Test: [ 9300/21770] eta: 0:14:10 time: 0.0682 data: 0.0019 max mem: 19788 +Test: [ 9400/21770] eta: 0:14:03 time: 0.0702 data: 0.0018 max mem: 19788 +Test: [ 9500/21770] eta: 0:13:57 time: 0.0746 data: 0.0023 max mem: 19788 +Test: [ 9600/21770] eta: 0:13:50 time: 0.0786 data: 0.0024 max mem: 19788 +Test: [ 9700/21770] eta: 0:13:44 time: 0.0672 data: 0.0019 max mem: 19788 +Test: [ 9800/21770] eta: 0:13:36 time: 0.0613 data: 0.0020 max mem: 19788 +Test: [ 9900/21770] eta: 0:13:29 time: 0.0686 data: 0.0021 max mem: 19788 +Test: [10000/21770] eta: 0:13:23 time: 0.0813 data: 0.0025 max mem: 19788 +Test: [10100/21770] eta: 0:13:16 time: 0.0778 data: 0.0024 max mem: 19788 +Test: [10200/21770] eta: 0:13:09 time: 0.0636 data: 0.0018 max mem: 19788 +Test: [10300/21770] eta: 0:13:04 time: 0.0719 data: 0.0018 max mem: 19788 +Test: [10400/21770] eta: 0:12:57 time: 0.0642 data: 0.0019 max mem: 19788 +Test: [10500/21770] eta: 0:12:50 time: 0.0623 data: 0.0020 max mem: 19788 +Test: [10600/21770] eta: 0:12:43 time: 0.0776 data: 0.0024 max mem: 19788 +Test: [10700/21770] eta: 0:12:35 time: 0.0635 data: 0.0018 max mem: 19788 +Test: [10800/21770] eta: 0:12:29 time: 0.0725 data: 0.0019 max mem: 19788 +Test: [10900/21770] eta: 0:12:23 time: 0.0734 data: 0.0022 max mem: 19788 +Test: [11000/21770] eta: 0:12:16 time: 0.0761 data: 0.0023 max mem: 19788 +Test: [11100/21770] eta: 0:12:10 time: 0.0713 data: 0.0020 max mem: 19788 +Test: [11200/21770] eta: 0:12:03 time: 0.0685 data: 0.0019 max mem: 19788 +Test: [11300/21770] eta: 0:11:56 time: 0.0642 data: 0.0019 max mem: 19788 +Test: [11400/21770] eta: 0:11:49 time: 0.0653 data: 0.0019 max mem: 19788 +Test: [11500/21770] eta: 0:11:42 time: 0.0613 data: 0.0018 max mem: 19788 +Test: [11600/21770] eta: 0:11:35 time: 0.0620 data: 0.0018 max mem: 19788 +Test: [11700/21770] eta: 0:11:28 time: 0.0796 data: 0.0023 max mem: 19788 +Test: [11800/21770] eta: 0:11:22 time: 0.0673 data: 0.0021 max mem: 19788 +Test: [11900/21770] eta: 0:11:15 time: 0.0815 data: 0.0024 max mem: 19788 +Test: [12000/21770] eta: 0:11:09 time: 0.0742 data: 0.0022 max mem: 19788 +Test: [12100/21770] eta: 0:11:02 time: 0.0751 data: 0.0020 max mem: 19788 +Test: [12200/21770] eta: 0:10:55 time: 0.0691 data: 0.0017 max mem: 19788 +Test: [12300/21770] eta: 0:10:48 time: 0.0620 data: 0.0018 max mem: 19788 +Test: [12400/21770] eta: 0:10:41 time: 0.0620 data: 0.0018 max mem: 19788 +Test: [12500/21770] eta: 0:10:34 time: 0.0772 data: 0.0022 max mem: 19788 +Test: [12600/21770] eta: 0:10:27 time: 0.0634 data: 0.0019 max mem: 19788 +Test: [12700/21770] eta: 0:10:20 time: 0.0624 data: 0.0018 max mem: 19788 +Test: [12800/21770] eta: 0:10:13 time: 0.0636 data: 0.0017 max mem: 19788 +Test: [12900/21770] eta: 0:10:06 time: 0.0636 data: 0.0019 max mem: 19788 +Test: [13000/21770] eta: 0:09:59 time: 0.0715 data: 0.0022 max mem: 19788 +Test: [13100/21770] eta: 0:09:53 time: 0.0740 data: 0.0021 max mem: 19788 +Test: [13200/21770] eta: 0:09:46 time: 0.0624 data: 0.0016 max mem: 19788 +Test: [13300/21770] eta: 0:09:39 time: 0.0704 data: 0.0018 max mem: 19788 +Test: [13400/21770] eta: 0:09:33 time: 0.0651 data: 0.0019 max mem: 19788 +Test: [13500/21770] eta: 0:09:26 time: 0.0649 data: 0.0020 max mem: 19788 +Test: [13600/21770] eta: 0:09:19 time: 0.0685 data: 0.0021 max mem: 19788 +Test: [13700/21770] eta: 0:09:12 time: 0.0619 data: 0.0018 max mem: 19788 +Test: [13800/21770] eta: 0:09:05 time: 0.0676 data: 0.0022 max mem: 19788 +Test: [13900/21770] eta: 0:08:58 time: 0.0715 data: 0.0019 max mem: 19788 +Test: [14000/21770] eta: 0:08:51 time: 0.0606 data: 0.0019 max mem: 19788 +Test: [14100/21770] eta: 0:08:44 time: 0.0669 data: 0.0019 max mem: 19788 +Test: [14200/21770] eta: 0:08:37 time: 0.0736 data: 0.0021 max mem: 19788 +Test: [14300/21770] eta: 0:08:30 time: 0.0715 data: 0.0017 max mem: 19788 +Test: [14400/21770] eta: 0:08:24 time: 0.0622 data: 0.0017 max mem: 19788 +Test: [14500/21770] eta: 0:08:17 time: 0.0716 data: 0.0021 max mem: 19788 +Test: [14600/21770] eta: 0:08:10 time: 0.0621 data: 0.0018 max mem: 19788 +Test: [14700/21770] eta: 0:08:03 time: 0.0620 data: 0.0018 max mem: 19788 +Test: [14800/21770] eta: 0:07:56 time: 0.0703 data: 0.0020 max mem: 19788 +Test: [14900/21770] eta: 0:07:49 time: 0.0723 data: 0.0021 max mem: 19788 +Test: [15000/21770] eta: 0:07:42 time: 0.0774 data: 0.0022 max mem: 19788 +Test: [15100/21770] eta: 0:07:35 time: 0.0630 data: 0.0020 max mem: 19788 +Test: [15200/21770] eta: 0:07:29 time: 0.0738 data: 0.0021 max mem: 19788 +Test: [15300/21770] eta: 0:07:22 time: 0.0629 data: 0.0019 max mem: 19788 +Test: [15400/21770] eta: 0:07:15 time: 0.0651 data: 0.0018 max mem: 19788 +Test: [15500/21770] eta: 0:07:08 time: 0.0676 data: 0.0021 max mem: 19788 +Test: [15600/21770] eta: 0:07:01 time: 0.0634 data: 0.0020 max mem: 19788 +Test: [15700/21770] eta: 0:06:54 time: 0.0634 data: 0.0018 max mem: 19788 +Test: [15800/21770] eta: 0:06:47 time: 0.0632 data: 0.0018 max mem: 19788 +Test: [15900/21770] eta: 0:06:40 time: 0.0813 data: 0.0023 max mem: 19788 +Test: [16000/21770] eta: 0:06:33 time: 0.0679 data: 0.0021 max mem: 19788 +Test: [16100/21770] eta: 0:06:26 time: 0.0606 data: 0.0018 max mem: 19788 +Test: [16200/21770] eta: 0:06:20 time: 0.0689 data: 0.0019 max mem: 19788 +Test: [16300/21770] eta: 0:06:13 time: 0.0658 data: 0.0020 max mem: 19788 +Test: [16400/21770] eta: 0:06:06 time: 0.0615 data: 0.0016 max mem: 19788 +Test: [16500/21770] eta: 0:05:59 time: 0.0600 data: 0.0019 max mem: 19788 +Test: [16600/21770] eta: 0:05:52 time: 0.0613 data: 0.0020 max mem: 19788 +Test: [16700/21770] eta: 0:05:45 time: 0.0632 data: 0.0018 max mem: 19788 +Test: [16800/21770] eta: 0:05:38 time: 0.0682 data: 0.0017 max mem: 19788 +Test: [16900/21770] eta: 0:05:31 time: 0.0727 data: 0.0019 max mem: 19788 +Test: [17000/21770] eta: 0:05:24 time: 0.0620 data: 0.0021 max mem: 19788 +Test: [17100/21770] eta: 0:05:17 time: 0.0663 data: 0.0017 max mem: 19788 +Test: [17200/21770] eta: 0:05:11 time: 0.0760 data: 0.0020 max mem: 19788 +Test: [17300/21770] eta: 0:05:04 time: 0.0602 data: 0.0016 max mem: 19788 +Test: [17400/21770] eta: 0:04:57 time: 0.0627 data: 0.0020 max mem: 19788 +Test: [17500/21770] eta: 0:04:50 time: 0.0729 data: 0.0022 max mem: 19788 +Test: [17600/21770] eta: 0:04:43 time: 0.0584 data: 0.0017 max mem: 19788 +Test: [17700/21770] eta: 0:04:36 time: 0.0619 data: 0.0016 max mem: 19788 +Test: [17800/21770] eta: 0:04:30 time: 0.0762 data: 0.0023 max mem: 19788 +Test: [17900/21770] eta: 0:04:23 time: 0.0816 data: 0.0021 max mem: 19788 +Test: [18000/21770] eta: 0:04:16 time: 0.0584 data: 0.0017 max mem: 19788 +Test: [18100/21770] eta: 0:04:09 time: 0.0664 data: 0.0020 max mem: 19788 +Test: [18200/21770] eta: 0:04:02 time: 0.0757 data: 0.0023 max mem: 19788 +Test: [18300/21770] eta: 0:03:56 time: 0.0678 data: 0.0019 max mem: 19788 +Test: [18400/21770] eta: 0:03:49 time: 0.0719 data: 0.0021 max mem: 19788 +Test: [18500/21770] eta: 0:03:42 time: 0.0642 data: 0.0018 max mem: 19788 +Test: [18600/21770] eta: 0:03:35 time: 0.0612 data: 0.0020 max mem: 19788 +Test: [18700/21770] eta: 0:03:28 time: 0.0628 data: 0.0018 max mem: 19788 +Test: [18800/21770] eta: 0:03:21 time: 0.0630 data: 0.0018 max mem: 19788 +Test: [18900/21770] eta: 0:03:15 time: 0.0601 data: 0.0019 max mem: 19788 +Test: [19000/21770] eta: 0:03:08 time: 0.0726 data: 0.0021 max mem: 19788 +Test: [19100/21770] eta: 0:03:01 time: 0.0798 data: 0.0024 max mem: 19788 +Test: [19200/21770] eta: 0:02:54 time: 0.0661 data: 0.0018 max mem: 19788 +Test: [19300/21770] eta: 0:02:47 time: 0.0709 data: 0.0018 max mem: 19788 +Test: [19400/21770] eta: 0:02:41 time: 0.0755 data: 0.0020 max mem: 19788 +Test: [19500/21770] eta: 0:02:34 time: 0.0817 data: 0.0019 max mem: 19788 +Test: [19600/21770] eta: 0:02:27 time: 0.0751 data: 0.0022 max mem: 19788 +Test: [19700/21770] eta: 0:02:20 time: 0.0794 data: 0.0023 max mem: 19788 +Test: [19800/21770] eta: 0:02:14 time: 0.0727 data: 0.0020 max mem: 19788 +Test: [19900/21770] eta: 0:02:07 time: 0.0643 data: 0.0017 max mem: 19788 +Test: [20000/21770] eta: 0:02:00 time: 0.0790 data: 0.0023 max mem: 19788 +Test: [20100/21770] eta: 0:01:53 time: 0.0712 data: 0.0021 max mem: 19788 +Test: [20200/21770] eta: 0:01:46 time: 0.0623 data: 0.0020 max mem: 19788 +Test: [20300/21770] eta: 0:01:40 time: 0.0627 data: 0.0019 max mem: 19788 +Test: [20400/21770] eta: 0:01:33 time: 0.0741 data: 0.0020 max mem: 19788 +Test: [20500/21770] eta: 0:01:26 time: 0.0726 data: 0.0020 max mem: 19788 +Test: [20600/21770] eta: 0:01:19 time: 0.0628 data: 0.0019 max mem: 19788 +Test: [20700/21770] eta: 0:01:12 time: 0.0687 data: 0.0020 max mem: 19788 +Test: [20800/21770] eta: 0:01:06 time: 0.0705 data: 0.0021 max mem: 19788 +Test: [20900/21770] eta: 0:00:59 time: 0.0787 data: 0.0023 max mem: 19788 +Test: [21000/21770] eta: 0:00:52 time: 0.0617 data: 0.0019 max mem: 19788 +Test: [21100/21770] eta: 0:00:45 time: 0.0663 data: 0.0019 max mem: 19788 +Test: [21200/21770] eta: 0:00:38 time: 0.0619 data: 0.0018 max mem: 19788 +Test: [21300/21770] eta: 0:00:32 time: 0.0638 data: 0.0018 max mem: 19788 +Test: [21400/21770] eta: 0:00:25 time: 0.0688 data: 0.0020 max mem: 19788 +Test: [21500/21770] eta: 0:00:18 time: 0.0812 data: 0.0023 max mem: 19788 +Test: [21600/21770] eta: 0:00:11 time: 0.0610 data: 0.0018 max mem: 19788 +Test: [21700/21770] eta: 0:00:04 time: 0.0957 data: 0.0047 max mem: 19788 +Test: Total time: 0:24:45 +Final results: +Mean IoU is 62.84 + + precision@0.5 = 69.60 + precision@0.6 = 64.39 + precision@0.7 = 57.87 + precision@0.8 = 47.54 + precision@0.9 = 23.93 + overall IoU = 63.57 + mean IoU = 62.84 + +Mean accuracy for one-to-zero sample is 86.16 + +Average object IoU 0.6283728668572898 +Overall IoU 63.573055267333984 +Epoch: [27] [ 0/2138] eta: 3:15:09 lr: 1.818238988206691e-05 loss: 0.0220 (0.0220) time: 5.4769 data: 1.5771 max mem: 19788 +Epoch: [27] [ 10/2138] eta: 2:15:32 lr: 1.8176501908359112e-05 loss: 0.0220 (0.0209) time: 3.8214 data: 0.1464 max mem: 19788 +Epoch: [27] [ 20/2138] eta: 2:12:04 lr: 1.8170613722720275e-05 loss: 0.0195 (0.0203) time: 3.6547 data: 0.0027 max mem: 19788 +Epoch: [27] [ 30/2138] eta: 2:10:21 lr: 1.8164725325066475e-05 loss: 0.0210 (0.0209) time: 3.6492 data: 0.0025 max mem: 19788 +Epoch: [27] [ 40/2138] eta: 2:09:09 lr: 1.8158836715313694e-05 loss: 0.0234 (0.0220) time: 3.6436 data: 0.0032 max mem: 19788 +Epoch: [27] [ 50/2138] eta: 2:08:09 lr: 1.815294789337788e-05 loss: 0.0230 (0.0224) time: 3.6402 data: 0.0031 max mem: 19788 +Epoch: [27] [ 60/2138] eta: 2:07:18 lr: 1.8147058859174883e-05 loss: 0.0213 (0.0221) time: 3.6397 data: 0.0029 max mem: 19788 +Epoch: [27] [ 70/2138] eta: 2:06:29 lr: 1.814116961262052e-05 loss: 0.0194 (0.0219) time: 3.6378 data: 0.0030 max mem: 19788 +Epoch: [27] [ 80/2138] eta: 2:05:43 lr: 1.8135280153630527e-05 loss: 0.0205 (0.0222) time: 3.6341 data: 0.0028 max mem: 19788 +Epoch: [27] [ 90/2138] eta: 2:05:01 lr: 1.8129390482120588e-05 loss: 0.0226 (0.0223) time: 3.6367 data: 0.0028 max mem: 19788 +Epoch: [27] [ 100/2138] eta: 2:04:18 lr: 1.812350059800631e-05 loss: 0.0237 (0.0224) time: 3.6358 data: 0.0030 max mem: 19788 +Epoch: [27] [ 110/2138] eta: 2:03:37 lr: 1.8117610501203247e-05 loss: 0.0230 (0.0227) time: 3.6336 data: 0.0031 max mem: 19788 +Epoch: [27] [ 120/2138] eta: 2:02:57 lr: 1.8111720191626875e-05 loss: 0.0235 (0.0230) time: 3.6371 data: 0.0032 max mem: 19788 +Epoch: [27] [ 130/2138] eta: 2:02:18 lr: 1.810582966919263e-05 loss: 0.0250 (0.0233) time: 3.6386 data: 0.0031 max mem: 19788 +Epoch: [27] [ 140/2138] eta: 2:01:39 lr: 1.8099938933815857e-05 loss: 0.0251 (0.0236) time: 3.6364 data: 0.0030 max mem: 19788 +Epoch: [27] [ 150/2138] eta: 2:01:00 lr: 1.8094047985411854e-05 loss: 0.0251 (0.0236) time: 3.6360 data: 0.0029 max mem: 19788 +Epoch: [27] [ 160/2138] eta: 2:00:22 lr: 1.8088156823895846e-05 loss: 0.0257 (0.0242) time: 3.6368 data: 0.0028 max mem: 19788 +Epoch: [27] [ 170/2138] eta: 1:59:44 lr: 1.8082265449183004e-05 loss: 0.0257 (0.0243) time: 3.6402 data: 0.0029 max mem: 19788 +Epoch: [27] [ 180/2138] eta: 1:59:07 lr: 1.8076373861188418e-05 loss: 0.0231 (0.0243) time: 3.6444 data: 0.0031 max mem: 19788 +Epoch: [27] [ 190/2138] eta: 1:58:30 lr: 1.8070482059827133e-05 loss: 0.0217 (0.0242) time: 3.6441 data: 0.0030 max mem: 19788 +Epoch: [27] [ 200/2138] eta: 1:57:52 lr: 1.8064590045014105e-05 loss: 0.0196 (0.0240) time: 3.6416 data: 0.0030 max mem: 19788 +Epoch: [27] [ 210/2138] eta: 1:57:15 lr: 1.8058697816664254e-05 loss: 0.0244 (0.0242) time: 3.6396 data: 0.0029 max mem: 19788 +Epoch: [27] [ 220/2138] eta: 1:56:38 lr: 1.8052805374692412e-05 loss: 0.0260 (0.0241) time: 3.6390 data: 0.0030 max mem: 19788 +Epoch: [27] [ 230/2138] eta: 1:56:00 lr: 1.804691271901336e-05 loss: 0.0238 (0.0244) time: 3.6363 data: 0.0032 max mem: 19788 +Epoch: [27] [ 240/2138] eta: 1:55:22 lr: 1.8041019849541806e-05 loss: 0.0239 (0.0244) time: 3.6346 data: 0.0031 max mem: 19788 +Epoch: [27] [ 250/2138] eta: 1:54:45 lr: 1.80351267661924e-05 loss: 0.0212 (0.0243) time: 3.6337 data: 0.0029 max mem: 19788 +Epoch: [27] [ 260/2138] eta: 1:54:09 lr: 1.8029233468879713e-05 loss: 0.0212 (0.0243) time: 3.6413 data: 0.0029 max mem: 19788 +Epoch: [27] [ 270/2138] eta: 1:53:31 lr: 1.8023339957518276e-05 loss: 0.0226 (0.0244) time: 3.6425 data: 0.0029 max mem: 19788 +Epoch: [27] [ 280/2138] eta: 1:52:54 lr: 1.8017446232022528e-05 loss: 0.0241 (0.0244) time: 3.6343 data: 0.0027 max mem: 19788 +Epoch: [27] [ 290/2138] eta: 1:52:16 lr: 1.8011552292306853e-05 loss: 0.0249 (0.0244) time: 3.6296 data: 0.0028 max mem: 19788 +Epoch: [27] [ 300/2138] eta: 1:51:39 lr: 1.8005658138285577e-05 loss: 0.0222 (0.0244) time: 3.6286 data: 0.0030 max mem: 19788 +Epoch: [27] [ 310/2138] eta: 1:51:01 lr: 1.799976376987295e-05 loss: 0.0220 (0.0243) time: 3.6306 data: 0.0030 max mem: 19788 +Epoch: [27] [ 320/2138] eta: 1:50:24 lr: 1.7993869186983166e-05 loss: 0.0220 (0.0243) time: 3.6321 data: 0.0029 max mem: 19788 +Epoch: [27] [ 330/2138] eta: 1:49:48 lr: 1.7987974389530344e-05 loss: 0.0234 (0.0245) time: 3.6374 data: 0.0030 max mem: 19788 +Epoch: [27] [ 340/2138] eta: 1:49:11 lr: 1.7982079377428545e-05 loss: 0.0233 (0.0244) time: 3.6352 data: 0.0031 max mem: 19788 +Epoch: [27] [ 350/2138] eta: 1:48:33 lr: 1.7976184150591754e-05 loss: 0.0218 (0.0244) time: 3.6263 data: 0.0032 max mem: 19788 +Epoch: [27] [ 360/2138] eta: 1:47:56 lr: 1.797028870893391e-05 loss: 0.0222 (0.0243) time: 3.6275 data: 0.0035 max mem: 19788 +Epoch: [27] [ 370/2138] eta: 1:47:19 lr: 1.7964393052368857e-05 loss: 0.0245 (0.0244) time: 3.6331 data: 0.0031 max mem: 19788 +Epoch: [27] [ 380/2138] eta: 1:46:42 lr: 1.7958497180810403e-05 loss: 0.0232 (0.0244) time: 3.6329 data: 0.0027 max mem: 19788 +Epoch: [27] [ 390/2138] eta: 1:46:06 lr: 1.795260109417226e-05 loss: 0.0229 (0.0245) time: 3.6324 data: 0.0029 max mem: 19788 +Epoch: [27] [ 400/2138] eta: 1:45:29 lr: 1.794670479236811e-05 loss: 0.0240 (0.0246) time: 3.6366 data: 0.0029 max mem: 19788 +Epoch: [27] [ 410/2138] eta: 1:44:52 lr: 1.7940808275311537e-05 loss: 0.0251 (0.0247) time: 3.6377 data: 0.0031 max mem: 19788 +Epoch: [27] [ 420/2138] eta: 1:44:16 lr: 1.793491154291607e-05 loss: 0.0244 (0.0247) time: 3.6371 data: 0.0030 max mem: 19788 +Epoch: [27] [ 430/2138] eta: 1:43:40 lr: 1.7929014595095176e-05 loss: 0.0219 (0.0248) time: 3.6425 data: 0.0029 max mem: 19788 +Epoch: [27] [ 440/2138] eta: 1:43:03 lr: 1.7923117431762256e-05 loss: 0.0239 (0.0249) time: 3.6378 data: 0.0029 max mem: 19788 +Epoch: [27] [ 450/2138] eta: 1:42:27 lr: 1.7917220052830624e-05 loss: 0.0245 (0.0249) time: 3.6401 data: 0.0028 max mem: 19788 +Epoch: [27] [ 460/2138] eta: 1:41:50 lr: 1.7911322458213565e-05 loss: 0.0262 (0.0250) time: 3.6452 data: 0.0028 max mem: 19788 +Epoch: [27] [ 470/2138] eta: 1:41:15 lr: 1.7905424647824258e-05 loss: 0.0257 (0.0250) time: 3.6629 data: 0.0030 max mem: 19788 +Epoch: [27] [ 480/2138] eta: 1:40:39 lr: 1.7899526621575848e-05 loss: 0.0243 (0.0250) time: 3.6624 data: 0.0031 max mem: 19788 +Epoch: [27] [ 490/2138] eta: 1:40:04 lr: 1.7893628379381386e-05 loss: 0.0229 (0.0250) time: 3.6591 data: 0.0030 max mem: 19788 +Epoch: [27] [ 500/2138] eta: 1:39:28 lr: 1.788772992115388e-05 loss: 0.0229 (0.0249) time: 3.6703 data: 0.0030 max mem: 19788 +Epoch: [27] [ 510/2138] eta: 1:38:52 lr: 1.7881831246806248e-05 loss: 0.0260 (0.0250) time: 3.6667 data: 0.0029 max mem: 19788 +Epoch: [27] [ 520/2138] eta: 1:38:16 lr: 1.787593235625137e-05 loss: 0.0269 (0.0250) time: 3.6631 data: 0.0033 max mem: 19788 +Epoch: [27] [ 530/2138] eta: 1:37:43 lr: 1.7870033249402018e-05 loss: 0.0213 (0.0250) time: 3.6983 data: 0.0034 max mem: 19788 +Epoch: [27] [ 540/2138] eta: 1:37:07 lr: 1.786413392617094e-05 loss: 0.0210 (0.0249) time: 3.7049 data: 0.0031 max mem: 19788 +Epoch: [27] [ 550/2138] eta: 1:36:31 lr: 1.7858234386470787e-05 loss: 0.0222 (0.0249) time: 3.6636 data: 0.0033 max mem: 19788 +Epoch: [27] [ 560/2138] eta: 1:35:58 lr: 1.785233463021416e-05 loss: 0.0222 (0.0248) time: 3.7192 data: 0.0036 max mem: 19788 +Epoch: [27] [ 570/2138] eta: 1:35:22 lr: 1.784643465731358e-05 loss: 0.0231 (0.0249) time: 3.7234 data: 0.0035 max mem: 19788 +Epoch: [27] [ 580/2138] eta: 1:34:48 lr: 1.7840534467681513e-05 loss: 0.0247 (0.0249) time: 3.7129 data: 0.0032 max mem: 19788 +Epoch: [27] [ 590/2138] eta: 1:34:19 lr: 1.7834634061230345e-05 loss: 0.0232 (0.0248) time: 3.8413 data: 0.0030 max mem: 19788 +Epoch: [27] [ 600/2138] eta: 1:33:52 lr: 1.7828733437872396e-05 loss: 0.0225 (0.0249) time: 3.9859 data: 0.0030 max mem: 19788 +Epoch: [27] [ 610/2138] eta: 1:33:25 lr: 1.7822832597519927e-05 loss: 0.0225 (0.0249) time: 4.0406 data: 0.0033 max mem: 19788 +Epoch: [27] [ 620/2138] eta: 1:32:58 lr: 1.7816931540085124e-05 loss: 0.0232 (0.0249) time: 4.0446 data: 0.0033 max mem: 19788 +Epoch: [27] [ 630/2138] eta: 1:32:30 lr: 1.7811030265480117e-05 loss: 0.0219 (0.0248) time: 4.0578 data: 0.0031 max mem: 19788 +Epoch: [27] [ 640/2138] eta: 1:32:02 lr: 1.7805128773616942e-05 loss: 0.0209 (0.0248) time: 4.0584 data: 0.0031 max mem: 19788 +Epoch: [27] [ 650/2138] eta: 1:31:34 lr: 1.7799227064407597e-05 loss: 0.0220 (0.0248) time: 4.0528 data: 0.0030 max mem: 19788 +Epoch: [27] [ 660/2138] eta: 1:31:05 lr: 1.7793325137763993e-05 loss: 0.0221 (0.0248) time: 4.0516 data: 0.0031 max mem: 19788 +Epoch: [27] [ 670/2138] eta: 1:30:36 lr: 1.7787422993597984e-05 loss: 0.0245 (0.0248) time: 4.0492 data: 0.0031 max mem: 19788 +Epoch: [27] [ 680/2138] eta: 1:30:06 lr: 1.7781520631821337e-05 loss: 0.0251 (0.0248) time: 4.0488 data: 0.0031 max mem: 19788 +Epoch: [27] [ 690/2138] eta: 1:29:36 lr: 1.7775618052345778e-05 loss: 0.0255 (0.0248) time: 4.0531 data: 0.0035 max mem: 19788 +Epoch: [27] [ 700/2138] eta: 1:29:06 lr: 1.776971525508294e-05 loss: 0.0232 (0.0248) time: 4.0615 data: 0.0035 max mem: 19788 +Epoch: [27] [ 710/2138] eta: 1:28:36 lr: 1.7763812239944404e-05 loss: 0.0243 (0.0248) time: 4.0660 data: 0.0031 max mem: 19788 +Epoch: [27] [ 720/2138] eta: 1:28:05 lr: 1.775790900684167e-05 loss: 0.0216 (0.0248) time: 4.0626 data: 0.0029 max mem: 19788 +Epoch: [27] [ 730/2138] eta: 1:27:35 lr: 1.775200555568619e-05 loss: 0.0216 (0.0248) time: 4.0667 data: 0.0029 max mem: 19788 +Epoch: [27] [ 740/2138] eta: 1:27:04 lr: 1.7746101886389312e-05 loss: 0.0213 (0.0248) time: 4.0606 data: 0.0030 max mem: 19788 +Epoch: [27] [ 750/2138] eta: 1:26:32 lr: 1.7740197998862355e-05 loss: 0.0215 (0.0248) time: 4.0552 data: 0.0031 max mem: 19788 +Epoch: [27] [ 760/2138] eta: 1:26:00 lr: 1.7734293893016534e-05 loss: 0.0250 (0.0248) time: 4.0567 data: 0.0033 max mem: 19788 +Epoch: [27] [ 770/2138] eta: 1:25:28 lr: 1.7728389568763025e-05 loss: 0.0250 (0.0248) time: 4.0560 data: 0.0032 max mem: 19788 +Epoch: [27] [ 780/2138] eta: 1:24:56 lr: 1.772248502601291e-05 loss: 0.0252 (0.0249) time: 4.0563 data: 0.0032 max mem: 19788 +Epoch: [27] [ 790/2138] eta: 1:24:24 lr: 1.7716580264677228e-05 loss: 0.0247 (0.0250) time: 4.0555 data: 0.0031 max mem: 19788 +Epoch: [27] [ 800/2138] eta: 1:23:52 lr: 1.7710675284666914e-05 loss: 0.0220 (0.0249) time: 4.0619 data: 0.0030 max mem: 19788 +Epoch: [27] [ 810/2138] eta: 1:23:19 lr: 1.770477008589287e-05 loss: 0.0220 (0.0249) time: 4.0563 data: 0.0030 max mem: 19788 +Epoch: [27] [ 820/2138] eta: 1:22:45 lr: 1.76988646682659e-05 loss: 0.0232 (0.0250) time: 4.0350 data: 0.0031 max mem: 19788 +Epoch: [27] [ 830/2138] eta: 1:22:12 lr: 1.769295903169676e-05 loss: 0.0227 (0.0249) time: 4.0298 data: 0.0033 max mem: 19788 +Epoch: [27] [ 840/2138] eta: 1:21:38 lr: 1.7687053176096124e-05 loss: 0.0200 (0.0249) time: 4.0463 data: 0.0034 max mem: 19788 +Epoch: [27] [ 850/2138] eta: 1:21:05 lr: 1.7681147101374605e-05 loss: 0.0200 (0.0249) time: 4.0501 data: 0.0033 max mem: 19788 +Epoch: [27] [ 860/2138] eta: 1:20:31 lr: 1.7675240807442725e-05 loss: 0.0221 (0.0249) time: 4.0473 data: 0.0033 max mem: 19788 +Epoch: [27] [ 870/2138] eta: 1:19:57 lr: 1.7669334294210975e-05 loss: 0.0248 (0.0249) time: 4.0570 data: 0.0031 max mem: 19788 +Epoch: [27] [ 880/2138] eta: 1:19:23 lr: 1.766342756158973e-05 loss: 0.0236 (0.0248) time: 4.0563 data: 0.0032 max mem: 19788 +Epoch: [27] [ 890/2138] eta: 1:18:49 lr: 1.7657520609489336e-05 loss: 0.0229 (0.0248) time: 4.0540 data: 0.0033 max mem: 19788 +Epoch: [27] [ 900/2138] eta: 1:18:15 lr: 1.7651613437820046e-05 loss: 0.0246 (0.0249) time: 4.0533 data: 0.0034 max mem: 19788 +Epoch: [27] [ 910/2138] eta: 1:17:40 lr: 1.7645706046492045e-05 loss: 0.0234 (0.0249) time: 4.0543 data: 0.0037 max mem: 19788 +Epoch: [27] [ 920/2138] eta: 1:17:06 lr: 1.7639798435415458e-05 loss: 0.0220 (0.0249) time: 4.0527 data: 0.0034 max mem: 19788 +Epoch: [27] [ 930/2138] eta: 1:16:31 lr: 1.7633890604500323e-05 loss: 0.0212 (0.0249) time: 4.0520 data: 0.0033 max mem: 19788 +Epoch: [27] [ 940/2138] eta: 1:15:56 lr: 1.7627982553656627e-05 loss: 0.0258 (0.0249) time: 4.0569 data: 0.0033 max mem: 19788 +Epoch: [27] [ 950/2138] eta: 1:15:21 lr: 1.7622074282794273e-05 loss: 0.0241 (0.0249) time: 4.0521 data: 0.0033 max mem: 19788 +Epoch: [27] [ 960/2138] eta: 1:14:46 lr: 1.7616165791823103e-05 loss: 0.0249 (0.0249) time: 4.0516 data: 0.0037 max mem: 19788 +Epoch: [27] [ 970/2138] eta: 1:14:11 lr: 1.761025708065287e-05 loss: 0.0248 (0.0249) time: 4.0544 data: 0.0040 max mem: 19788 +Epoch: [27] [ 980/2138] eta: 1:13:36 lr: 1.7604348149193288e-05 loss: 0.0209 (0.0248) time: 4.0569 data: 0.0036 max mem: 19788 +Epoch: [27] [ 990/2138] eta: 1:13:01 lr: 1.7598438997353968e-05 loss: 0.0218 (0.0249) time: 4.0555 data: 0.0035 max mem: 19788 +Epoch: [27] [1000/2138] eta: 1:12:25 lr: 1.759252962504447e-05 loss: 0.0247 (0.0249) time: 4.0531 data: 0.0034 max mem: 19788 +Epoch: [27] [1010/2138] eta: 1:11:50 lr: 1.7586620032174272e-05 loss: 0.0218 (0.0248) time: 4.0580 data: 0.0033 max mem: 19788 +Epoch: [27] [1020/2138] eta: 1:11:14 lr: 1.7580710218652797e-05 loss: 0.0191 (0.0248) time: 4.0466 data: 0.0033 max mem: 19788 +Epoch: [27] [1030/2138] eta: 1:10:38 lr: 1.7574800184389372e-05 loss: 0.0212 (0.0248) time: 4.0416 data: 0.0032 max mem: 19788 +Epoch: [27] [1040/2138] eta: 1:10:02 lr: 1.756888992929328e-05 loss: 0.0216 (0.0248) time: 4.0481 data: 0.0032 max mem: 19788 +Epoch: [27] [1050/2138] eta: 1:09:26 lr: 1.756297945327371e-05 loss: 0.0239 (0.0248) time: 4.0504 data: 0.0032 max mem: 19788 +Epoch: [27] [1060/2138] eta: 1:08:50 lr: 1.7557068756239798e-05 loss: 0.0247 (0.0248) time: 4.0534 data: 0.0034 max mem: 19788 +Epoch: [27] [1070/2138] eta: 1:08:14 lr: 1.7551157838100586e-05 loss: 0.0222 (0.0247) time: 4.0541 data: 0.0034 max mem: 19788 +Epoch: [27] [1080/2138] eta: 1:07:38 lr: 1.754524669876508e-05 loss: 0.0210 (0.0247) time: 4.0563 data: 0.0032 max mem: 19788 +Epoch: [27] [1090/2138] eta: 1:07:02 lr: 1.7539335338142172e-05 loss: 0.0263 (0.0248) time: 4.0588 data: 0.0032 max mem: 19788 +Epoch: [27] [1100/2138] eta: 1:06:25 lr: 1.753342375614072e-05 loss: 0.0268 (0.0248) time: 4.0591 data: 0.0031 max mem: 19788 +Epoch: [27] [1110/2138] eta: 1:05:49 lr: 1.752751195266948e-05 loss: 0.0238 (0.0248) time: 4.0560 data: 0.0031 max mem: 19788 +Epoch: [27] [1120/2138] eta: 1:05:13 lr: 1.752159992763716e-05 loss: 0.0227 (0.0248) time: 4.0564 data: 0.0031 max mem: 19788 +Epoch: [27] [1130/2138] eta: 1:04:36 lr: 1.7515687680952382e-05 loss: 0.0258 (0.0248) time: 4.0543 data: 0.0032 max mem: 19788 +Epoch: [27] [1140/2138] eta: 1:03:59 lr: 1.75097752125237e-05 loss: 0.0258 (0.0248) time: 4.0571 data: 0.0032 max mem: 19788 +Epoch: [27] [1150/2138] eta: 1:03:23 lr: 1.7503862522259593e-05 loss: 0.0200 (0.0247) time: 4.0614 data: 0.0032 max mem: 19788 +Epoch: [27] [1160/2138] eta: 1:02:46 lr: 1.7497949610068482e-05 loss: 0.0208 (0.0247) time: 4.0552 data: 0.0033 max mem: 19788 +Epoch: [27] [1170/2138] eta: 1:02:09 lr: 1.7492036475858688e-05 loss: 0.0211 (0.0247) time: 4.0526 data: 0.0032 max mem: 19788 +Epoch: [27] [1180/2138] eta: 1:01:32 lr: 1.7486123119538492e-05 loss: 0.0234 (0.0247) time: 4.0524 data: 0.0032 max mem: 19788 +Epoch: [27] [1190/2138] eta: 1:00:55 lr: 1.7480209541016078e-05 loss: 0.0239 (0.0247) time: 4.0503 data: 0.0033 max mem: 19788 +Epoch: [27] [1200/2138] eta: 1:00:18 lr: 1.747429574019957e-05 loss: 0.0239 (0.0247) time: 4.0490 data: 0.0032 max mem: 19788 +Epoch: [27] [1210/2138] eta: 0:59:41 lr: 1.7468381716997013e-05 loss: 0.0221 (0.0247) time: 4.0505 data: 0.0031 max mem: 19788 +Epoch: [27] [1220/2138] eta: 0:59:04 lr: 1.7462467471316383e-05 loss: 0.0231 (0.0247) time: 4.0572 data: 0.0032 max mem: 19788 +Epoch: [27] [1230/2138] eta: 0:58:27 lr: 1.745655300306559e-05 loss: 0.0225 (0.0247) time: 4.0569 data: 0.0036 max mem: 19788 +Epoch: [27] [1240/2138] eta: 0:57:50 lr: 1.7450638312152447e-05 loss: 0.0217 (0.0248) time: 4.0535 data: 0.0036 max mem: 19788 +Epoch: [27] [1250/2138] eta: 0:57:12 lr: 1.7444723398484735e-05 loss: 0.0222 (0.0248) time: 4.0518 data: 0.0032 max mem: 19788 +Epoch: [27] [1260/2138] eta: 0:56:35 lr: 1.743880826197011e-05 loss: 0.0217 (0.0247) time: 4.0508 data: 0.0033 max mem: 19788 +Epoch: [27] [1270/2138] eta: 0:55:57 lr: 1.7432892902516202e-05 loss: 0.0195 (0.0247) time: 4.0517 data: 0.0033 max mem: 19788 +Epoch: [27] [1280/2138] eta: 0:55:20 lr: 1.7426977320030547e-05 loss: 0.0223 (0.0247) time: 4.0506 data: 0.0033 max mem: 19788 +Epoch: [27] [1290/2138] eta: 0:54:43 lr: 1.7421061514420603e-05 loss: 0.0223 (0.0247) time: 4.0548 data: 0.0034 max mem: 19788 +Epoch: [27] [1300/2138] eta: 0:54:05 lr: 1.741514548559376e-05 loss: 0.0204 (0.0247) time: 4.0537 data: 0.0033 max mem: 19788 +Epoch: [27] [1310/2138] eta: 0:53:27 lr: 1.740922923345735e-05 loss: 0.0217 (0.0247) time: 4.0504 data: 0.0032 max mem: 19788 +Epoch: [27] [1320/2138] eta: 0:52:50 lr: 1.74033127579186e-05 loss: 0.0245 (0.0247) time: 4.0510 data: 0.0031 max mem: 19788 +Epoch: [27] [1330/2138] eta: 0:52:12 lr: 1.739739605888469e-05 loss: 0.0230 (0.0247) time: 4.0508 data: 0.0032 max mem: 19788 +Epoch: [27] [1340/2138] eta: 0:51:34 lr: 1.7391479136262712e-05 loss: 0.0231 (0.0247) time: 4.0533 data: 0.0033 max mem: 19788 +Epoch: [27] [1350/2138] eta: 0:50:57 lr: 1.7385561989959696e-05 loss: 0.0266 (0.0247) time: 4.0547 data: 0.0033 max mem: 19788 +Epoch: [27] [1360/2138] eta: 0:50:19 lr: 1.7379644619882583e-05 loss: 0.0268 (0.0247) time: 4.0564 data: 0.0032 max mem: 19788 +Epoch: [27] [1370/2138] eta: 0:49:41 lr: 1.7373727025938256e-05 loss: 0.0240 (0.0247) time: 4.0547 data: 0.0033 max mem: 19788 +Epoch: [27] [1380/2138] eta: 0:49:03 lr: 1.7367809208033506e-05 loss: 0.0254 (0.0248) time: 4.0551 data: 0.0035 max mem: 19788 +Epoch: [27] [1390/2138] eta: 0:48:25 lr: 1.7361891166075076e-05 loss: 0.0265 (0.0248) time: 4.0558 data: 0.0036 max mem: 19788 +Epoch: [27] [1400/2138] eta: 0:47:47 lr: 1.7355972899969604e-05 loss: 0.0257 (0.0248) time: 4.0575 data: 0.0034 max mem: 19788 +Epoch: [27] [1410/2138] eta: 0:47:09 lr: 1.7350054409623682e-05 loss: 0.0221 (0.0247) time: 4.0509 data: 0.0033 max mem: 19788 +Epoch: [27] [1420/2138] eta: 0:46:31 lr: 1.73441356949438e-05 loss: 0.0212 (0.0247) time: 4.0437 data: 0.0034 max mem: 19788 +Epoch: [27] [1430/2138] eta: 0:45:53 lr: 1.7338216755836403e-05 loss: 0.0241 (0.0247) time: 4.0527 data: 0.0034 max mem: 19788 +Epoch: [27] [1440/2138] eta: 0:45:15 lr: 1.7332297592207834e-05 loss: 0.0226 (0.0247) time: 4.0550 data: 0.0031 max mem: 19788 +Epoch: [27] [1450/2138] eta: 0:44:37 lr: 1.7326378203964382e-05 loss: 0.0242 (0.0247) time: 4.0558 data: 0.0032 max mem: 19788 +Epoch: [27] [1460/2138] eta: 0:43:59 lr: 1.7320458591012248e-05 loss: 0.0265 (0.0247) time: 4.0589 data: 0.0032 max mem: 19788 +Epoch: [27] [1470/2138] eta: 0:43:21 lr: 1.731453875325757e-05 loss: 0.0228 (0.0247) time: 4.0590 data: 0.0035 max mem: 19788 +Epoch: [27] [1480/2138] eta: 0:42:42 lr: 1.7308618690606397e-05 loss: 0.0235 (0.0248) time: 4.0553 data: 0.0034 max mem: 19788 +Epoch: [27] [1490/2138] eta: 0:42:04 lr: 1.7302698402964714e-05 loss: 0.0235 (0.0248) time: 4.0542 data: 0.0031 max mem: 19788 +Epoch: [27] [1500/2138] eta: 0:41:26 lr: 1.729677789023843e-05 loss: 0.0218 (0.0248) time: 4.0543 data: 0.0032 max mem: 19788 +Epoch: [27] [1510/2138] eta: 0:40:47 lr: 1.729085715233337e-05 loss: 0.0235 (0.0248) time: 4.0506 data: 0.0032 max mem: 19788 +Epoch: [27] [1520/2138] eta: 0:40:09 lr: 1.7284936189155298e-05 loss: 0.0205 (0.0247) time: 4.0516 data: 0.0033 max mem: 19788 +Epoch: [27] [1530/2138] eta: 0:39:31 lr: 1.7279015000609883e-05 loss: 0.0202 (0.0247) time: 4.0527 data: 0.0035 max mem: 19788 +Epoch: [27] [1540/2138] eta: 0:38:52 lr: 1.7273093586602747e-05 loss: 0.0211 (0.0247) time: 4.0541 data: 0.0035 max mem: 19788 +Epoch: [27] [1550/2138] eta: 0:38:14 lr: 1.72671719470394e-05 loss: 0.0219 (0.0247) time: 4.0547 data: 0.0034 max mem: 19788 +Epoch: [27] [1560/2138] eta: 0:37:36 lr: 1.7261250081825314e-05 loss: 0.0238 (0.0247) time: 4.0624 data: 0.0032 max mem: 19788 +Epoch: [27] [1570/2138] eta: 0:36:57 lr: 1.7255327990865858e-05 loss: 0.0241 (0.0247) time: 4.0615 data: 0.0031 max mem: 19788 +Epoch: [27] [1580/2138] eta: 0:36:18 lr: 1.7249405674066338e-05 loss: 0.0227 (0.0247) time: 4.0419 data: 0.0031 max mem: 19788 +Epoch: [27] [1590/2138] eta: 0:35:40 lr: 1.7243483131331976e-05 loss: 0.0216 (0.0247) time: 4.0410 data: 0.0030 max mem: 19788 +Epoch: [27] [1600/2138] eta: 0:35:01 lr: 1.723756036256793e-05 loss: 0.0256 (0.0247) time: 4.0520 data: 0.0031 max mem: 19788 +Epoch: [27] [1610/2138] eta: 0:34:23 lr: 1.723163736767927e-05 loss: 0.0246 (0.0247) time: 4.0569 data: 0.0031 max mem: 19788 +Epoch: [27] [1620/2138] eta: 0:33:44 lr: 1.7225714146571e-05 loss: 0.0212 (0.0247) time: 4.0595 data: 0.0030 max mem: 19788 +Epoch: [27] [1630/2138] eta: 0:33:06 lr: 1.7219790699148032e-05 loss: 0.0238 (0.0247) time: 4.0611 data: 0.0030 max mem: 19788 +Epoch: [27] [1640/2138] eta: 0:32:27 lr: 1.7213867025315224e-05 loss: 0.0217 (0.0247) time: 4.0638 data: 0.0034 max mem: 19788 +Epoch: [27] [1650/2138] eta: 0:31:48 lr: 1.7207943124977336e-05 loss: 0.0203 (0.0247) time: 4.0583 data: 0.0035 max mem: 19788 +Epoch: [27] [1660/2138] eta: 0:31:10 lr: 1.7202018998039072e-05 loss: 0.0211 (0.0246) time: 4.0527 data: 0.0035 max mem: 19788 +Epoch: [27] [1670/2138] eta: 0:30:31 lr: 1.7196094644405034e-05 loss: 0.0216 (0.0246) time: 4.0520 data: 0.0034 max mem: 19788 +Epoch: [27] [1680/2138] eta: 0:29:52 lr: 1.719017006397978e-05 loss: 0.0225 (0.0246) time: 4.0570 data: 0.0036 max mem: 19788 +Epoch: [27] [1690/2138] eta: 0:29:13 lr: 1.7184245256667755e-05 loss: 0.0231 (0.0246) time: 4.0570 data: 0.0035 max mem: 19788 +Epoch: [27] [1700/2138] eta: 0:28:35 lr: 1.717832022237336e-05 loss: 0.0227 (0.0246) time: 4.0533 data: 0.0033 max mem: 19788 +Epoch: [27] [1710/2138] eta: 0:27:56 lr: 1.7172394961000897e-05 loss: 0.0222 (0.0246) time: 4.0565 data: 0.0033 max mem: 19788 +Epoch: [27] [1720/2138] eta: 0:27:17 lr: 1.7166469472454603e-05 loss: 0.0231 (0.0246) time: 4.0544 data: 0.0033 max mem: 19788 +Epoch: [27] [1730/2138] eta: 0:26:38 lr: 1.7160543756638625e-05 loss: 0.0242 (0.0246) time: 4.0546 data: 0.0034 max mem: 19788 +Epoch: [27] [1740/2138] eta: 0:25:59 lr: 1.7154617813457052e-05 loss: 0.0226 (0.0246) time: 4.0526 data: 0.0035 max mem: 19788 +Epoch: [27] [1750/2138] eta: 0:25:20 lr: 1.7148691642813876e-05 loss: 0.0227 (0.0246) time: 4.0513 data: 0.0035 max mem: 19788 +Epoch: [27] [1760/2138] eta: 0:24:41 lr: 1.7142765244613024e-05 loss: 0.0237 (0.0246) time: 4.0535 data: 0.0035 max mem: 19788 +Epoch: [27] [1770/2138] eta: 0:24:02 lr: 1.713683861875834e-05 loss: 0.0214 (0.0246) time: 4.0553 data: 0.0033 max mem: 19788 +Epoch: [27] [1780/2138] eta: 0:23:24 lr: 1.713091176515359e-05 loss: 0.0213 (0.0246) time: 4.0597 data: 0.0032 max mem: 19788 +Epoch: [27] [1790/2138] eta: 0:22:45 lr: 1.7124984683702473e-05 loss: 0.0211 (0.0246) time: 4.0571 data: 0.0031 max mem: 19788 +Epoch: [27] [1800/2138] eta: 0:22:06 lr: 1.71190573743086e-05 loss: 0.0199 (0.0246) time: 4.0507 data: 0.0032 max mem: 19788 +Epoch: [27] [1810/2138] eta: 0:21:27 lr: 1.7113129836875497e-05 loss: 0.0210 (0.0246) time: 4.0475 data: 0.0034 max mem: 19788 +Epoch: [27] [1820/2138] eta: 0:20:48 lr: 1.7107202071306625e-05 loss: 0.0223 (0.0246) time: 4.0525 data: 0.0033 max mem: 19788 +Epoch: [27] [1830/2138] eta: 0:20:09 lr: 1.710127407750537e-05 loss: 0.0222 (0.0246) time: 4.0522 data: 0.0035 max mem: 19788 +Epoch: [27] [1840/2138] eta: 0:19:29 lr: 1.7095345855375018e-05 loss: 0.0225 (0.0246) time: 4.0483 data: 0.0036 max mem: 19788 +Epoch: [27] [1850/2138] eta: 0:18:50 lr: 1.7089417404818807e-05 loss: 0.0266 (0.0246) time: 4.0516 data: 0.0034 max mem: 19788 +Epoch: [27] [1860/2138] eta: 0:18:11 lr: 1.708348872573987e-05 loss: 0.0247 (0.0246) time: 4.0522 data: 0.0032 max mem: 19788 +Epoch: [27] [1870/2138] eta: 0:17:32 lr: 1.707755981804128e-05 loss: 0.0221 (0.0246) time: 4.0505 data: 0.0030 max mem: 19788 +Epoch: [27] [1880/2138] eta: 0:16:53 lr: 1.7071630681626017e-05 loss: 0.0217 (0.0246) time: 4.0478 data: 0.0030 max mem: 19788 +Epoch: [27] [1890/2138] eta: 0:16:14 lr: 1.7065701316397002e-05 loss: 0.0214 (0.0246) time: 4.0493 data: 0.0032 max mem: 19788 +Epoch: [27] [1900/2138] eta: 0:15:35 lr: 1.7059771722257045e-05 loss: 0.0200 (0.0246) time: 4.0522 data: 0.0032 max mem: 19788 +Epoch: [27] [1910/2138] eta: 0:14:56 lr: 1.7053841899108917e-05 loss: 0.0200 (0.0246) time: 4.0526 data: 0.0033 max mem: 19788 +Epoch: [27] [1920/2138] eta: 0:14:17 lr: 1.7047911846855274e-05 loss: 0.0217 (0.0246) time: 4.0572 data: 0.0032 max mem: 19788 +Epoch: [27] [1930/2138] eta: 0:13:37 lr: 1.7041981565398723e-05 loss: 0.0236 (0.0246) time: 4.0553 data: 0.0031 max mem: 19788 +Epoch: [27] [1940/2138] eta: 0:12:58 lr: 1.7036051054641767e-05 loss: 0.0236 (0.0246) time: 4.0517 data: 0.0033 max mem: 19788 +Epoch: [27] [1950/2138] eta: 0:12:19 lr: 1.703012031448685e-05 loss: 0.0215 (0.0245) time: 4.0512 data: 0.0032 max mem: 19788 +Epoch: [27] [1960/2138] eta: 0:11:40 lr: 1.7024189344836317e-05 loss: 0.0223 (0.0245) time: 4.0551 data: 0.0031 max mem: 19788 +Epoch: [27] [1970/2138] eta: 0:11:00 lr: 1.7018258145592456e-05 loss: 0.0226 (0.0245) time: 4.0515 data: 0.0032 max mem: 19788 +Epoch: [27] [1980/2138] eta: 0:10:21 lr: 1.701232671665745e-05 loss: 0.0211 (0.0245) time: 4.0474 data: 0.0033 max mem: 19788 +Epoch: [27] [1990/2138] eta: 0:09:42 lr: 1.700639505793343e-05 loss: 0.0211 (0.0245) time: 4.0544 data: 0.0033 max mem: 19788 +Epoch: [27] [2000/2138] eta: 0:09:03 lr: 1.700046316932242e-05 loss: 0.0224 (0.0245) time: 4.0525 data: 0.0033 max mem: 19788 +Epoch: [27] [2010/2138] eta: 0:08:23 lr: 1.6994531050726394e-05 loss: 0.0245 (0.0245) time: 4.0507 data: 0.0030 max mem: 19788 +Epoch: [27] [2020/2138] eta: 0:07:44 lr: 1.6988598702047215e-05 loss: 0.0257 (0.0245) time: 4.0502 data: 0.0030 max mem: 19788 +Epoch: [27] [2030/2138] eta: 0:07:05 lr: 1.6982666123186688e-05 loss: 0.0243 (0.0245) time: 4.0525 data: 0.0033 max mem: 19788 +Epoch: [27] [2040/2138] eta: 0:06:25 lr: 1.6976733314046525e-05 loss: 0.0227 (0.0245) time: 4.0599 data: 0.0034 max mem: 19788 +Epoch: [27] [2050/2138] eta: 0:05:46 lr: 1.6970800274528373e-05 loss: 0.0227 (0.0245) time: 4.0600 data: 0.0035 max mem: 19788 +Epoch: [27] [2060/2138] eta: 0:05:07 lr: 1.6964867004533778e-05 loss: 0.0227 (0.0245) time: 4.0648 data: 0.0034 max mem: 19788 +Epoch: [27] [2070/2138] eta: 0:04:27 lr: 1.6958933503964232e-05 loss: 0.0228 (0.0245) time: 4.0620 data: 0.0031 max mem: 19788 +Epoch: [27] [2080/2138] eta: 0:03:48 lr: 1.6952999772721116e-05 loss: 0.0228 (0.0245) time: 4.0554 data: 0.0032 max mem: 19788 +Epoch: [27] [2090/2138] eta: 0:03:09 lr: 1.6947065810705757e-05 loss: 0.0253 (0.0245) time: 4.0611 data: 0.0033 max mem: 19788 +Epoch: [27] [2100/2138] eta: 0:02:29 lr: 1.6941131617819385e-05 loss: 0.0224 (0.0245) time: 4.0606 data: 0.0033 max mem: 19788 +Epoch: [27] [2110/2138] eta: 0:01:50 lr: 1.6935197193963157e-05 loss: 0.0267 (0.0245) time: 4.0552 data: 0.0035 max mem: 19788 +Epoch: [27] [2120/2138] eta: 0:01:10 lr: 1.6929262539038147e-05 loss: 0.0292 (0.0245) time: 4.0548 data: 0.0035 max mem: 19788 +Epoch: [27] [2130/2138] eta: 0:00:31 lr: 1.6923327652945344e-05 loss: 0.0274 (0.0245) time: 4.0346 data: 0.0033 max mem: 19788 +Epoch: [27] Total time: 2:20:32 +Test: [ 0/21770] eta: 18:07:56 time: 2.9984 data: 2.6612 max mem: 19788 +Test: [ 100/21770] eta: 0:35:40 time: 0.0771 data: 0.0023 max mem: 19788 +Test: [ 200/21770] eta: 0:29:49 time: 0.0657 data: 0.0019 max mem: 19788 +Test: [ 300/21770] eta: 0:27:26 time: 0.0709 data: 0.0021 max mem: 19788 +Test: [ 400/21770] eta: 0:26:40 time: 0.0648 data: 0.0021 max mem: 19788 +Test: [ 500/21770] eta: 0:25:51 time: 0.0621 data: 0.0019 max mem: 19788 +Test: [ 600/21770] eta: 0:25:41 time: 0.0647 data: 0.0020 max mem: 19788 +Test: [ 700/21770] eta: 0:25:27 time: 0.0701 data: 0.0024 max mem: 19788 +Test: [ 800/21770] eta: 0:25:09 time: 0.0622 data: 0.0019 max mem: 19788 +Test: [ 900/21770] eta: 0:24:55 time: 0.0642 data: 0.0020 max mem: 19788 +Test: [ 1000/21770] eta: 0:24:38 time: 0.0704 data: 0.0022 max mem: 19788 +Test: [ 1100/21770] eta: 0:24:27 time: 0.0715 data: 0.0022 max mem: 19788 +Test: [ 1200/21770] eta: 0:24:15 time: 0.0725 data: 0.0019 max mem: 19788 +Test: [ 1300/21770] eta: 0:24:02 time: 0.0632 data: 0.0018 max mem: 19788 +Test: [ 1400/21770] eta: 0:23:53 time: 0.0672 data: 0.0020 max mem: 19788 +Test: [ 1500/21770] eta: 0:23:38 time: 0.0622 data: 0.0018 max mem: 19788 +Test: [ 1600/21770] eta: 0:23:25 time: 0.0654 data: 0.0021 max mem: 19788 +Test: [ 1700/21770] eta: 0:23:17 time: 0.0645 data: 0.0019 max mem: 19788 +Test: [ 1800/21770] eta: 0:23:10 time: 0.0678 data: 0.0018 max mem: 19788 +Test: [ 1900/21770] eta: 0:23:06 time: 0.0658 data: 0.0020 max mem: 19788 +Test: [ 2000/21770] eta: 0:22:55 time: 0.0652 data: 0.0019 max mem: 19788 +Test: [ 2100/21770] eta: 0:22:44 time: 0.0640 data: 0.0020 max mem: 19788 +Test: [ 2200/21770] eta: 0:22:43 time: 0.0813 data: 0.0022 max mem: 19788 +Test: [ 2300/21770] eta: 0:22:35 time: 0.0662 data: 0.0023 max mem: 19788 +Test: [ 2400/21770] eta: 0:22:32 time: 0.0652 data: 0.0018 max mem: 19788 +Test: [ 2500/21770] eta: 0:22:25 time: 0.0652 data: 0.0020 max mem: 19788 +Test: [ 2600/21770] eta: 0:22:18 time: 0.0633 data: 0.0022 max mem: 19788 +Test: [ 2700/21770] eta: 0:22:12 time: 0.0653 data: 0.0019 max mem: 19788 +Test: [ 2800/21770] eta: 0:22:04 time: 0.0786 data: 0.0023 max mem: 19788 +Test: [ 2900/21770] eta: 0:21:58 time: 0.0659 data: 0.0020 max mem: 19788 +Test: [ 3000/21770] eta: 0:21:57 time: 0.0851 data: 0.0025 max mem: 19788 +Test: [ 3100/21770] eta: 0:21:56 time: 0.0853 data: 0.0021 max mem: 19788 +Test: [ 3200/21770] eta: 0:21:48 time: 0.0707 data: 0.0023 max mem: 19788 +Test: [ 3300/21770] eta: 0:21:41 time: 0.0678 data: 0.0019 max mem: 19788 +Test: [ 3400/21770] eta: 0:21:37 time: 0.0760 data: 0.0023 max mem: 19788 +Test: [ 3500/21770] eta: 0:21:31 time: 0.0669 data: 0.0021 max mem: 19788 +Test: [ 3600/21770] eta: 0:21:22 time: 0.0636 data: 0.0019 max mem: 19788 +Test: [ 3700/21770] eta: 0:21:13 time: 0.0638 data: 0.0019 max mem: 19788 +Test: [ 3800/21770] eta: 0:21:07 time: 0.0705 data: 0.0020 max mem: 19788 +Test: [ 3900/21770] eta: 0:21:02 time: 0.0837 data: 0.0026 max mem: 19788 +Test: [ 4000/21770] eta: 0:20:56 time: 0.0630 data: 0.0020 max mem: 19788 +Test: [ 4100/21770] eta: 0:20:51 time: 0.0735 data: 0.0023 max mem: 19788 +Test: [ 4200/21770] eta: 0:20:47 time: 0.0812 data: 0.0025 max mem: 19788 +Test: [ 4300/21770] eta: 0:20:40 time: 0.0631 data: 0.0021 max mem: 19788 +Test: [ 4400/21770] eta: 0:20:31 time: 0.0659 data: 0.0019 max mem: 19788 +Test: [ 4500/21770] eta: 0:20:26 time: 0.0669 data: 0.0022 max mem: 19788 +Test: [ 4600/21770] eta: 0:20:22 time: 0.0838 data: 0.0021 max mem: 19788 +Test: [ 4700/21770] eta: 0:20:16 time: 0.0832 data: 0.0026 max mem: 19788 +Test: [ 4800/21770] eta: 0:20:11 time: 0.0704 data: 0.0020 max mem: 19788 +Test: [ 4900/21770] eta: 0:20:04 time: 0.0670 data: 0.0021 max mem: 19788 +Test: [ 5000/21770] eta: 0:19:59 time: 0.0661 data: 0.0021 max mem: 19788 +Test: [ 5100/21770] eta: 0:19:54 time: 0.0722 data: 0.0018 max mem: 19788 +Test: [ 5200/21770] eta: 0:19:47 time: 0.0811 data: 0.0025 max mem: 19788 +Test: [ 5300/21770] eta: 0:19:42 time: 0.0772 data: 0.0020 max mem: 19788 +Test: [ 5400/21770] eta: 0:19:34 time: 0.0762 data: 0.0025 max mem: 19788 +Test: [ 5500/21770] eta: 0:19:27 time: 0.0848 data: 0.0025 max mem: 19788 +Test: [ 5600/21770] eta: 0:19:21 time: 0.0720 data: 0.0021 max mem: 19788 +Test: [ 5700/21770] eta: 0:19:13 time: 0.0853 data: 0.0026 max mem: 19788 +Test: [ 5800/21770] eta: 0:19:07 time: 0.0746 data: 0.0023 max mem: 19788 +Test: [ 5900/21770] eta: 0:19:01 time: 0.0771 data: 0.0025 max mem: 19788 +Test: [ 6000/21770] eta: 0:18:55 time: 0.0761 data: 0.0023 max mem: 19788 +Test: [ 6100/21770] eta: 0:18:49 time: 0.0644 data: 0.0020 max mem: 19788 +Test: [ 6200/21770] eta: 0:18:39 time: 0.0653 data: 0.0018 max mem: 19788 +Test: [ 6300/21770] eta: 0:18:33 time: 0.0633 data: 0.0021 max mem: 19788 +Test: [ 6400/21770] eta: 0:18:26 time: 0.0666 data: 0.0018 max mem: 19788 +Test: [ 6500/21770] eta: 0:18:20 time: 0.0718 data: 0.0020 max mem: 19788 +Test: [ 6600/21770] eta: 0:18:12 time: 0.0700 data: 0.0021 max mem: 19788 +Test: [ 6700/21770] eta: 0:18:05 time: 0.0696 data: 0.0021 max mem: 19788 +Test: [ 6800/21770] eta: 0:17:58 time: 0.0627 data: 0.0019 max mem: 19788 +Test: [ 6900/21770] eta: 0:17:50 time: 0.0632 data: 0.0019 max mem: 19788 +Test: [ 7000/21770] eta: 0:17:44 time: 0.0794 data: 0.0021 max mem: 19788 +Test: [ 7100/21770] eta: 0:17:36 time: 0.0636 data: 0.0017 max mem: 19788 +Test: [ 7200/21770] eta: 0:17:29 time: 0.0661 data: 0.0020 max mem: 19788 +Test: [ 7300/21770] eta: 0:17:21 time: 0.0766 data: 0.0023 max mem: 19788 +Test: [ 7400/21770] eta: 0:17:15 time: 0.0739 data: 0.0020 max mem: 19788 +Test: [ 7500/21770] eta: 0:17:09 time: 0.0790 data: 0.0026 max mem: 19788 +Test: [ 7600/21770] eta: 0:17:02 time: 0.0668 data: 0.0019 max mem: 19788 +Test: [ 7700/21770] eta: 0:16:55 time: 0.0673 data: 0.0020 max mem: 19788 +Test: [ 7800/21770] eta: 0:16:47 time: 0.0761 data: 0.0022 max mem: 19788 +Test: [ 7900/21770] eta: 0:16:40 time: 0.0845 data: 0.0026 max mem: 19788 +Test: [ 8000/21770] eta: 0:16:33 time: 0.0767 data: 0.0021 max mem: 19788 +Test: [ 8100/21770] eta: 0:16:26 time: 0.0772 data: 0.0023 max mem: 19788 +Test: [ 8200/21770] eta: 0:16:17 time: 0.0634 data: 0.0019 max mem: 19788 +Test: [ 8300/21770] eta: 0:16:10 time: 0.0769 data: 0.0021 max mem: 19788 +Test: [ 8400/21770] eta: 0:16:02 time: 0.0655 data: 0.0020 max mem: 19788 +Test: [ 8500/21770] eta: 0:15:54 time: 0.0653 data: 0.0020 max mem: 19788 +Test: [ 8600/21770] eta: 0:15:47 time: 0.0721 data: 0.0022 max mem: 19788 +Test: [ 8700/21770] eta: 0:15:41 time: 0.0829 data: 0.0026 max mem: 19788 +Test: [ 8800/21770] eta: 0:15:34 time: 0.0650 data: 0.0021 max mem: 19788 +Test: [ 8900/21770] eta: 0:15:26 time: 0.0657 data: 0.0020 max mem: 19788 +Test: [ 9000/21770] eta: 0:15:19 time: 0.0685 data: 0.0019 max mem: 19788 +Test: [ 9100/21770] eta: 0:15:11 time: 0.0645 data: 0.0018 max mem: 19788 +Test: [ 9200/21770] eta: 0:15:03 time: 0.0729 data: 0.0020 max mem: 19788 +Test: [ 9300/21770] eta: 0:14:57 time: 0.0663 data: 0.0023 max mem: 19788 +Test: [ 9400/21770] eta: 0:14:49 time: 0.0753 data: 0.0024 max mem: 19788 +Test: [ 9500/21770] eta: 0:14:42 time: 0.0668 data: 0.0020 max mem: 19788 +Test: [ 9600/21770] eta: 0:14:35 time: 0.0671 data: 0.0021 max mem: 19788 +Test: [ 9700/21770] eta: 0:14:27 time: 0.0739 data: 0.0021 max mem: 19788 +Test: [ 9800/21770] eta: 0:14:20 time: 0.0793 data: 0.0025 max mem: 19788 +Test: [ 9900/21770] eta: 0:14:12 time: 0.0686 data: 0.0019 max mem: 19788 +Test: [10000/21770] eta: 0:14:05 time: 0.0700 data: 0.0021 max mem: 19788 +Test: [10100/21770] eta: 0:13:58 time: 0.0697 data: 0.0023 max mem: 19788 +Test: [10200/21770] eta: 0:13:51 time: 0.0725 data: 0.0020 max mem: 19788 +Test: [10300/21770] eta: 0:13:44 time: 0.0657 data: 0.0020 max mem: 19788 +Test: [10400/21770] eta: 0:13:37 time: 0.0700 data: 0.0020 max mem: 19788 +Test: [10500/21770] eta: 0:13:29 time: 0.0767 data: 0.0023 max mem: 19788 +Test: [10600/21770] eta: 0:13:22 time: 0.0668 data: 0.0020 max mem: 19788 +Test: [10700/21770] eta: 0:13:15 time: 0.0704 data: 0.0024 max mem: 19788 +Test: [10800/21770] eta: 0:13:08 time: 0.0690 data: 0.0021 max mem: 19788 +Test: [10900/21770] eta: 0:13:01 time: 0.0793 data: 0.0025 max mem: 19788 +Test: [11000/21770] eta: 0:12:54 time: 0.0717 data: 0.0023 max mem: 19788 +Test: [11100/21770] eta: 0:12:47 time: 0.0654 data: 0.0022 max mem: 19788 +Test: [11200/21770] eta: 0:12:40 time: 0.0677 data: 0.0020 max mem: 19788 +Test: [11300/21770] eta: 0:12:33 time: 0.0834 data: 0.0026 max mem: 19788 +Test: [11400/21770] eta: 0:12:26 time: 0.0831 data: 0.0026 max mem: 19788 +Test: [11500/21770] eta: 0:12:19 time: 0.0674 data: 0.0019 max mem: 19788 +Test: [11600/21770] eta: 0:12:12 time: 0.0710 data: 0.0022 max mem: 19788 +Test: [11700/21770] eta: 0:12:04 time: 0.0644 data: 0.0020 max mem: 19788 +Test: [11800/21770] eta: 0:11:57 time: 0.0839 data: 0.0025 max mem: 19788 +Test: [11900/21770] eta: 0:11:51 time: 0.0848 data: 0.0027 max mem: 19788 +Test: [12000/21770] eta: 0:11:44 time: 0.0750 data: 0.0020 max mem: 19788 +Test: [12100/21770] eta: 0:11:36 time: 0.0680 data: 0.0020 max mem: 19788 +Test: [12200/21770] eta: 0:11:29 time: 0.0677 data: 0.0019 max mem: 19788 +Test: [12300/21770] eta: 0:11:22 time: 0.0685 data: 0.0019 max mem: 19788 +Test: [12400/21770] eta: 0:11:15 time: 0.0655 data: 0.0019 max mem: 19788 +Test: [12500/21770] eta: 0:11:08 time: 0.0806 data: 0.0024 max mem: 19788 +Test: [12600/21770] eta: 0:11:00 time: 0.0734 data: 0.0022 max mem: 19788 +Test: [12700/21770] eta: 0:10:53 time: 0.0707 data: 0.0022 max mem: 19788 +Test: [12800/21770] eta: 0:10:45 time: 0.0636 data: 0.0018 max mem: 19788 +Test: [12900/21770] eta: 0:10:38 time: 0.0667 data: 0.0020 max mem: 19788 +Test: [13000/21770] eta: 0:10:31 time: 0.0854 data: 0.0025 max mem: 19788 +Test: [13100/21770] eta: 0:10:24 time: 0.0735 data: 0.0021 max mem: 19788 +Test: [13200/21770] eta: 0:10:17 time: 0.0861 data: 0.0026 max mem: 19788 +Test: [13300/21770] eta: 0:10:10 time: 0.0787 data: 0.0022 max mem: 19788 +Test: [13400/21770] eta: 0:10:03 time: 0.0691 data: 0.0021 max mem: 19788 +Test: [13500/21770] eta: 0:09:56 time: 0.0660 data: 0.0020 max mem: 19788 +Test: [13600/21770] eta: 0:09:48 time: 0.0728 data: 0.0021 max mem: 19788 +Test: [13700/21770] eta: 0:09:41 time: 0.0676 data: 0.0021 max mem: 19788 +Test: [13800/21770] eta: 0:09:34 time: 0.0778 data: 0.0026 max mem: 19788 +Test: [13900/21770] eta: 0:09:27 time: 0.0850 data: 0.0026 max mem: 19788 +Test: [14000/21770] eta: 0:09:20 time: 0.0722 data: 0.0020 max mem: 19788 +Test: [14100/21770] eta: 0:09:13 time: 0.0715 data: 0.0021 max mem: 19788 +Test: [14200/21770] eta: 0:09:06 time: 0.0673 data: 0.0021 max mem: 19788 +Test: [14300/21770] eta: 0:08:58 time: 0.0665 data: 0.0019 max mem: 19788 +Test: [14400/21770] eta: 0:08:51 time: 0.0719 data: 0.0022 max mem: 19788 +Test: [14500/21770] eta: 0:08:43 time: 0.0800 data: 0.0023 max mem: 19788 +Test: [14600/21770] eta: 0:08:36 time: 0.0711 data: 0.0021 max mem: 19788 +Test: [14700/21770] eta: 0:08:29 time: 0.0710 data: 0.0023 max mem: 19788 +Test: [14800/21770] eta: 0:08:22 time: 0.0737 data: 0.0023 max mem: 19788 +Test: [14900/21770] eta: 0:08:15 time: 0.0674 data: 0.0019 max mem: 19788 +Test: [15000/21770] eta: 0:08:07 time: 0.0674 data: 0.0019 max mem: 19788 +Test: [15100/21770] eta: 0:08:00 time: 0.0746 data: 0.0023 max mem: 19788 +Test: [15200/21770] eta: 0:07:53 time: 0.0711 data: 0.0019 max mem: 19788 +Test: [15300/21770] eta: 0:07:46 time: 0.0646 data: 0.0018 max mem: 19788 +Test: [15400/21770] eta: 0:07:38 time: 0.0635 data: 0.0020 max mem: 19788 +Test: [15500/21770] eta: 0:07:31 time: 0.0658 data: 0.0019 max mem: 19788 +Test: [15600/21770] eta: 0:07:24 time: 0.0657 data: 0.0021 max mem: 19788 +Test: [15700/21770] eta: 0:07:17 time: 0.0761 data: 0.0024 max mem: 19788 +Test: [15800/21770] eta: 0:07:10 time: 0.0643 data: 0.0020 max mem: 19788 +Test: [15900/21770] eta: 0:07:02 time: 0.0684 data: 0.0020 max mem: 19788 +Test: [16000/21770] eta: 0:06:55 time: 0.0765 data: 0.0023 max mem: 19788 +Test: [16100/21770] eta: 0:06:48 time: 0.0847 data: 0.0027 max mem: 19788 +Test: [16200/21770] eta: 0:06:41 time: 0.0786 data: 0.0024 max mem: 19788 +Test: [16300/21770] eta: 0:06:34 time: 0.0646 data: 0.0019 max mem: 19788 +Test: [16400/21770] eta: 0:06:26 time: 0.0683 data: 0.0019 max mem: 19788 +Test: [16500/21770] eta: 0:06:19 time: 0.0853 data: 0.0026 max mem: 19788 +Test: [16600/21770] eta: 0:06:12 time: 0.0643 data: 0.0021 max mem: 19788 +Test: [16700/21770] eta: 0:06:05 time: 0.0631 data: 0.0019 max mem: 19788 +Test: [16800/21770] eta: 0:05:57 time: 0.0638 data: 0.0018 max mem: 19788 +Test: [16900/21770] eta: 0:05:50 time: 0.0862 data: 0.0020 max mem: 19788 +Test: [17000/21770] eta: 0:05:43 time: 0.0631 data: 0.0021 max mem: 19788 +Test: [17100/21770] eta: 0:05:36 time: 0.0713 data: 0.0024 max mem: 19788 +Test: [17200/21770] eta: 0:05:29 time: 0.0827 data: 0.0023 max mem: 19788 +Test: [17300/21770] eta: 0:05:22 time: 0.0646 data: 0.0019 max mem: 19788 +Test: [17400/21770] eta: 0:05:14 time: 0.0688 data: 0.0023 max mem: 19788 +Test: [17500/21770] eta: 0:05:07 time: 0.0734 data: 0.0022 max mem: 19788 +Test: [17600/21770] eta: 0:05:00 time: 0.0659 data: 0.0020 max mem: 19788 +Test: [17700/21770] eta: 0:04:52 time: 0.0632 data: 0.0018 max mem: 19788 +Test: [17800/21770] eta: 0:04:45 time: 0.0799 data: 0.0023 max mem: 19788 +Test: [17900/21770] eta: 0:04:38 time: 0.0666 data: 0.0020 max mem: 19788 +Test: [18000/21770] eta: 0:04:31 time: 0.0691 data: 0.0022 max mem: 19788 +Test: [18100/21770] eta: 0:04:24 time: 0.0839 data: 0.0025 max mem: 19788 +Test: [18200/21770] eta: 0:04:16 time: 0.0646 data: 0.0021 max mem: 19788 +Test: [18300/21770] eta: 0:04:09 time: 0.0848 data: 0.0027 max mem: 19788 +Test: [18400/21770] eta: 0:04:02 time: 0.0688 data: 0.0021 max mem: 19788 +Test: [18500/21770] eta: 0:03:55 time: 0.0693 data: 0.0021 max mem: 19788 +Test: [18600/21770] eta: 0:03:48 time: 0.0690 data: 0.0020 max mem: 19788 +Test: [18700/21770] eta: 0:03:41 time: 0.0725 data: 0.0022 max mem: 19788 +Test: [18800/21770] eta: 0:03:33 time: 0.0716 data: 0.0021 max mem: 19788 +Test: [18900/21770] eta: 0:03:26 time: 0.0699 data: 0.0022 max mem: 19788 +Test: [19000/21770] eta: 0:03:19 time: 0.0826 data: 0.0022 max mem: 19788 +Test: [19100/21770] eta: 0:03:12 time: 0.0773 data: 0.0022 max mem: 19788 +Test: [19200/21770] eta: 0:03:05 time: 0.0632 data: 0.0019 max mem: 19788 +Test: [19300/21770] eta: 0:02:57 time: 0.0652 data: 0.0018 max mem: 19788 +Test: [19400/21770] eta: 0:02:50 time: 0.0735 data: 0.0022 max mem: 19788 +Test: [19500/21770] eta: 0:02:43 time: 0.0741 data: 0.0020 max mem: 19788 +Test: [19600/21770] eta: 0:02:36 time: 0.0736 data: 0.0023 max mem: 19788 +Test: [19700/21770] eta: 0:02:29 time: 0.0711 data: 0.0019 max mem: 19788 +Test: [19800/21770] eta: 0:02:21 time: 0.0647 data: 0.0021 max mem: 19788 +Test: [19900/21770] eta: 0:02:14 time: 0.0676 data: 0.0023 max mem: 19788 +Test: [20000/21770] eta: 0:02:07 time: 0.0727 data: 0.0022 max mem: 19788 +Test: [20100/21770] eta: 0:02:00 time: 0.0770 data: 0.0025 max mem: 19788 +Test: [20200/21770] eta: 0:01:52 time: 0.0642 data: 0.0020 max mem: 19788 +Test: [20300/21770] eta: 0:01:45 time: 0.0643 data: 0.0020 max mem: 19788 +Test: [20400/21770] eta: 0:01:38 time: 0.0737 data: 0.0022 max mem: 19788 +Test: [20500/21770] eta: 0:01:31 time: 0.0706 data: 0.0022 max mem: 19788 +Test: [20600/21770] eta: 0:01:24 time: 0.0813 data: 0.0021 max mem: 19788 +Test: [20700/21770] eta: 0:01:16 time: 0.0658 data: 0.0020 max mem: 19788 +Test: [20800/21770] eta: 0:01:09 time: 0.0662 data: 0.0020 max mem: 19788 +Test: [20900/21770] eta: 0:01:02 time: 0.0643 data: 0.0019 max mem: 19788 +Test: [21000/21770] eta: 0:00:55 time: 0.0657 data: 0.0018 max mem: 19788 +Test: [21100/21770] eta: 0:00:48 time: 0.0715 data: 0.0023 max mem: 19788 +Test: [21200/21770] eta: 0:00:41 time: 0.0805 data: 0.0025 max mem: 19788 +Test: [21300/21770] eta: 0:00:33 time: 0.0642 data: 0.0018 max mem: 19788 +Test: [21400/21770] eta: 0:00:26 time: 0.0888 data: 0.0039 max mem: 19788 +Test: [21500/21770] eta: 0:00:19 time: 0.0632 data: 0.0020 max mem: 19788 +Test: [21600/21770] eta: 0:00:12 time: 0.0656 data: 0.0019 max mem: 19788 +Test: [21700/21770] eta: 0:00:05 time: 0.1029 data: 0.0030 max mem: 19788 +Test: Total time: 0:26:06 +Final results: +Mean IoU is 63.06 + + precision@0.5 = 69.86 + precision@0.6 = 64.72 + precision@0.7 = 58.10 + precision@0.8 = 47.74 + precision@0.9 = 23.97 + overall IoU = 64.00 + mean IoU = 63.06 + +Mean accuracy for one-to-zero sample is 85.78 + +Average object IoU 0.6305583099855226 +Overall IoU 64.00065612792969 +Better epoch: 27 + +Epoch: [28] [ 0/2138] eta: 3:31:59 lr: 1.691857957756371e-05 loss: 0.0234 (0.0234) time: 5.9494 data: 1.6311 max mem: 19788 +Epoch: [28] [ 10/2138] eta: 2:30:02 lr: 1.6912644275119132e-05 loss: 0.0198 (0.0201) time: 4.2305 data: 0.1517 max mem: 19788 +Epoch: [28] [ 20/2138] eta: 2:26:17 lr: 1.690670874122911e-05 loss: 0.0193 (0.0196) time: 4.0539 data: 0.0030 max mem: 19788 +Epoch: [28] [ 30/2138] eta: 2:24:28 lr: 1.6900772975794338e-05 loss: 0.0194 (0.0202) time: 4.0474 data: 0.0029 max mem: 19788 +Epoch: [28] [ 40/2138] eta: 2:23:10 lr: 1.6894836978715405e-05 loss: 0.0217 (0.0214) time: 4.0424 data: 0.0036 max mem: 19788 +Epoch: [28] [ 50/2138] eta: 2:22:05 lr: 1.688890074989285e-05 loss: 0.0228 (0.0219) time: 4.0372 data: 0.0034 max mem: 19788 +Epoch: [28] [ 60/2138] eta: 2:21:13 lr: 1.6882964289227097e-05 loss: 0.0201 (0.0215) time: 4.0430 data: 0.0032 max mem: 19788 +Epoch: [28] [ 70/2138] eta: 2:20:21 lr: 1.6877027596618517e-05 loss: 0.0175 (0.0211) time: 4.0449 data: 0.0034 max mem: 19788 +Epoch: [28] [ 80/2138] eta: 2:19:35 lr: 1.6871090671967376e-05 loss: 0.0189 (0.0214) time: 4.0451 data: 0.0034 max mem: 19788 +Epoch: [28] [ 90/2138] eta: 2:18:48 lr: 1.686515351517388e-05 loss: 0.0212 (0.0215) time: 4.0473 data: 0.0032 max mem: 19788 +Epoch: [28] [ 100/2138] eta: 2:18:01 lr: 1.685921612613813e-05 loss: 0.0237 (0.0217) time: 4.0381 data: 0.0032 max mem: 19788 +Epoch: [28] [ 110/2138] eta: 2:17:15 lr: 1.6853278504760167e-05 loss: 0.0236 (0.0220) time: 4.0345 data: 0.0032 max mem: 19788 +Epoch: [28] [ 120/2138] eta: 2:16:30 lr: 1.6847340650939934e-05 loss: 0.0223 (0.0221) time: 4.0341 data: 0.0033 max mem: 19788 +Epoch: [28] [ 130/2138] eta: 2:15:47 lr: 1.68414025645773e-05 loss: 0.0234 (0.0225) time: 4.0370 data: 0.0033 max mem: 19788 +Epoch: [28] [ 140/2138] eta: 2:15:02 lr: 1.6835464245572043e-05 loss: 0.0235 (0.0224) time: 4.0370 data: 0.0031 max mem: 19788 +Epoch: [28] [ 150/2138] eta: 2:14:20 lr: 1.682952569382387e-05 loss: 0.0235 (0.0226) time: 4.0365 data: 0.0031 max mem: 19788 +Epoch: [28] [ 160/2138] eta: 2:13:38 lr: 1.6823586909232404e-05 loss: 0.0258 (0.0229) time: 4.0436 data: 0.0033 max mem: 19788 +Epoch: [28] [ 170/2138] eta: 2:12:57 lr: 1.6817647891697166e-05 loss: 0.0249 (0.0230) time: 4.0475 data: 0.0031 max mem: 19788 +Epoch: [28] [ 180/2138] eta: 2:12:16 lr: 1.6811708641117627e-05 loss: 0.0232 (0.0232) time: 4.0480 data: 0.0032 max mem: 19788 +Epoch: [28] [ 190/2138] eta: 2:11:34 lr: 1.6805769157393144e-05 loss: 0.0223 (0.0232) time: 4.0429 data: 0.0033 max mem: 19788 +Epoch: [28] [ 200/2138] eta: 2:10:50 lr: 1.6799829440423015e-05 loss: 0.0164 (0.0231) time: 4.0292 data: 0.0035 max mem: 19788 +Epoch: [28] [ 210/2138] eta: 2:10:07 lr: 1.6793889490106435e-05 loss: 0.0259 (0.0234) time: 4.0188 data: 0.0035 max mem: 19788 +Epoch: [28] [ 220/2138] eta: 2:09:25 lr: 1.6787949306342533e-05 loss: 0.0255 (0.0233) time: 4.0276 data: 0.0032 max mem: 19788 +Epoch: [28] [ 230/2138] eta: 2:08:42 lr: 1.6782008889030336e-05 loss: 0.0224 (0.0235) time: 4.0274 data: 0.0033 max mem: 19788 +Epoch: [28] [ 240/2138] eta: 2:08:00 lr: 1.6776068238068814e-05 loss: 0.0224 (0.0234) time: 4.0202 data: 0.0036 max mem: 19788 +Epoch: [28] [ 250/2138] eta: 2:07:19 lr: 1.6770127353356824e-05 loss: 0.0205 (0.0237) time: 4.0321 data: 0.0037 max mem: 19788 +Epoch: [28] [ 260/2138] eta: 2:06:38 lr: 1.6764186234793165e-05 loss: 0.0209 (0.0237) time: 4.0437 data: 0.0035 max mem: 19788 +Epoch: [28] [ 270/2138] eta: 2:05:58 lr: 1.6758244882276526e-05 loss: 0.0227 (0.0237) time: 4.0463 data: 0.0035 max mem: 19788 +Epoch: [28] [ 280/2138] eta: 2:05:18 lr: 1.6752303295705545e-05 loss: 0.0234 (0.0237) time: 4.0473 data: 0.0033 max mem: 19788 +Epoch: [28] [ 290/2138] eta: 2:04:37 lr: 1.6746361474978746e-05 loss: 0.0234 (0.0237) time: 4.0437 data: 0.0033 max mem: 19788 +Epoch: [28] [ 300/2138] eta: 2:03:54 lr: 1.6740419419994584e-05 loss: 0.0218 (0.0237) time: 4.0280 data: 0.0032 max mem: 19788 +Epoch: [28] [ 310/2138] eta: 2:03:13 lr: 1.6734477130651425e-05 loss: 0.0206 (0.0236) time: 4.0232 data: 0.0032 max mem: 19788 +Epoch: [28] [ 320/2138] eta: 2:02:32 lr: 1.6728534606847557e-05 loss: 0.0217 (0.0236) time: 4.0319 data: 0.0033 max mem: 19788 +Epoch: [28] [ 330/2138] eta: 2:01:50 lr: 1.6722591848481174e-05 loss: 0.0236 (0.0237) time: 4.0241 data: 0.0036 max mem: 19788 +Epoch: [28] [ 340/2138] eta: 2:01:09 lr: 1.6716648855450395e-05 loss: 0.0250 (0.0237) time: 4.0207 data: 0.0037 max mem: 19788 +Epoch: [28] [ 350/2138] eta: 2:00:28 lr: 1.6710705627653246e-05 loss: 0.0235 (0.0237) time: 4.0314 data: 0.0035 max mem: 19788 +Epoch: [28] [ 360/2138] eta: 1:59:47 lr: 1.6704762164987682e-05 loss: 0.0232 (0.0237) time: 4.0338 data: 0.0035 max mem: 19788 +Epoch: [28] [ 370/2138] eta: 1:59:06 lr: 1.6698818467351553e-05 loss: 0.0230 (0.0238) time: 4.0321 data: 0.0035 max mem: 19788 +Epoch: [28] [ 380/2138] eta: 1:58:26 lr: 1.6692874534642646e-05 loss: 0.0225 (0.0238) time: 4.0394 data: 0.0034 max mem: 19788 +Epoch: [28] [ 390/2138] eta: 1:57:45 lr: 1.6686930366758642e-05 loss: 0.0208 (0.0239) time: 4.0442 data: 0.0032 max mem: 19788 +Epoch: [28] [ 400/2138] eta: 1:57:05 lr: 1.6680985963597153e-05 loss: 0.0240 (0.0240) time: 4.0443 data: 0.0035 max mem: 19788 +Epoch: [28] [ 410/2138] eta: 1:56:25 lr: 1.6675041325055694e-05 loss: 0.0253 (0.0241) time: 4.0478 data: 0.0036 max mem: 19788 +Epoch: [28] [ 420/2138] eta: 1:55:44 lr: 1.6669096451031717e-05 loss: 0.0249 (0.0240) time: 4.0400 data: 0.0033 max mem: 19788 +Epoch: [28] [ 430/2138] eta: 1:55:03 lr: 1.6663151341422555e-05 loss: 0.0203 (0.0241) time: 4.0307 data: 0.0032 max mem: 19788 +Epoch: [28] [ 440/2138] eta: 1:54:22 lr: 1.665720599612548e-05 loss: 0.0235 (0.0241) time: 4.0267 data: 0.0031 max mem: 19788 +Epoch: [28] [ 450/2138] eta: 1:53:42 lr: 1.665126041503767e-05 loss: 0.0221 (0.0242) time: 4.0339 data: 0.0031 max mem: 19788 +Epoch: [28] [ 460/2138] eta: 1:53:01 lr: 1.6645314598056225e-05 loss: 0.0238 (0.0242) time: 4.0384 data: 0.0032 max mem: 19788 +Epoch: [28] [ 470/2138] eta: 1:52:20 lr: 1.6639368545078147e-05 loss: 0.0238 (0.0242) time: 4.0305 data: 0.0034 max mem: 19788 +Epoch: [28] [ 480/2138] eta: 1:51:39 lr: 1.6633422256000352e-05 loss: 0.0224 (0.0242) time: 4.0304 data: 0.0033 max mem: 19788 +Epoch: [28] [ 490/2138] eta: 1:50:59 lr: 1.6627475730719692e-05 loss: 0.0224 (0.0242) time: 4.0367 data: 0.0034 max mem: 19788 +Epoch: [28] [ 500/2138] eta: 1:50:19 lr: 1.6621528969132902e-05 loss: 0.0208 (0.0241) time: 4.0455 data: 0.0033 max mem: 19788 +Epoch: [28] [ 510/2138] eta: 1:49:38 lr: 1.6615581971136656e-05 loss: 0.0222 (0.0241) time: 4.0443 data: 0.0031 max mem: 19788 +Epoch: [28] [ 520/2138] eta: 1:48:58 lr: 1.6609634736627526e-05 loss: 0.0222 (0.0241) time: 4.0352 data: 0.0033 max mem: 19788 +Epoch: [28] [ 530/2138] eta: 1:48:17 lr: 1.660368726550201e-05 loss: 0.0209 (0.0241) time: 4.0384 data: 0.0033 max mem: 19788 +Epoch: [28] [ 540/2138] eta: 1:47:37 lr: 1.65977395576565e-05 loss: 0.0201 (0.0241) time: 4.0450 data: 0.0032 max mem: 19788 +Epoch: [28] [ 550/2138] eta: 1:46:56 lr: 1.659179161298733e-05 loss: 0.0210 (0.0241) time: 4.0393 data: 0.0031 max mem: 19788 +Epoch: [28] [ 560/2138] eta: 1:46:16 lr: 1.6585843431390716e-05 loss: 0.0221 (0.0240) time: 4.0367 data: 0.0031 max mem: 19788 +Epoch: [28] [ 570/2138] eta: 1:45:36 lr: 1.6579895012762818e-05 loss: 0.0203 (0.0240) time: 4.0434 data: 0.0032 max mem: 19788 +Epoch: [28] [ 580/2138] eta: 1:44:56 lr: 1.6573946356999674e-05 loss: 0.0215 (0.0240) time: 4.0470 data: 0.0031 max mem: 19788 +Epoch: [28] [ 590/2138] eta: 1:44:15 lr: 1.656799746399728e-05 loss: 0.0239 (0.0240) time: 4.0460 data: 0.0031 max mem: 19788 +Epoch: [28] [ 600/2138] eta: 1:43:35 lr: 1.6562048333651492e-05 loss: 0.0210 (0.0240) time: 4.0474 data: 0.0033 max mem: 19788 +Epoch: [28] [ 610/2138] eta: 1:42:55 lr: 1.655609896585813e-05 loss: 0.0217 (0.0241) time: 4.0500 data: 0.0033 max mem: 19788 +Epoch: [28] [ 620/2138] eta: 1:42:15 lr: 1.6550149360512886e-05 loss: 0.0234 (0.0241) time: 4.0497 data: 0.0033 max mem: 19788 +Epoch: [28] [ 630/2138] eta: 1:41:34 lr: 1.6544199517511388e-05 loss: 0.0212 (0.0240) time: 4.0501 data: 0.0034 max mem: 19788 +Epoch: [28] [ 640/2138] eta: 1:40:54 lr: 1.653824943674917e-05 loss: 0.0211 (0.0240) time: 4.0528 data: 0.0036 max mem: 19788 +Epoch: [28] [ 650/2138] eta: 1:40:14 lr: 1.6532299118121677e-05 loss: 0.0212 (0.0240) time: 4.0566 data: 0.0036 max mem: 19788 +Epoch: [28] [ 660/2138] eta: 1:39:34 lr: 1.6526348561524263e-05 loss: 0.0211 (0.0240) time: 4.0522 data: 0.0036 max mem: 19788 +Epoch: [28] [ 670/2138] eta: 1:38:54 lr: 1.652039776685221e-05 loss: 0.0221 (0.0240) time: 4.0438 data: 0.0036 max mem: 19788 +Epoch: [28] [ 680/2138] eta: 1:38:13 lr: 1.651444673400068e-05 loss: 0.0223 (0.0240) time: 4.0465 data: 0.0036 max mem: 19788 +Epoch: [28] [ 690/2138] eta: 1:37:33 lr: 1.650849546286479e-05 loss: 0.0220 (0.0240) time: 4.0471 data: 0.0034 max mem: 19788 +Epoch: [28] [ 700/2138] eta: 1:36:52 lr: 1.650254395333953e-05 loss: 0.0228 (0.0240) time: 4.0422 data: 0.0035 max mem: 19788 +Epoch: [28] [ 710/2138] eta: 1:36:12 lr: 1.6496592205319826e-05 loss: 0.0243 (0.0240) time: 4.0412 data: 0.0035 max mem: 19788 +Epoch: [28] [ 720/2138] eta: 1:35:31 lr: 1.64906402187005e-05 loss: 0.0213 (0.0240) time: 4.0401 data: 0.0031 max mem: 19788 +Epoch: [28] [ 730/2138] eta: 1:34:51 lr: 1.64846879933763e-05 loss: 0.0213 (0.0240) time: 4.0387 data: 0.0033 max mem: 19788 +Epoch: [28] [ 740/2138] eta: 1:34:10 lr: 1.6478735529241863e-05 loss: 0.0206 (0.0240) time: 4.0353 data: 0.0035 max mem: 19788 +Epoch: [28] [ 750/2138] eta: 1:33:30 lr: 1.6472782826191776e-05 loss: 0.0206 (0.0240) time: 4.0423 data: 0.0034 max mem: 19788 +Epoch: [28] [ 760/2138] eta: 1:32:50 lr: 1.646682988412049e-05 loss: 0.0231 (0.0240) time: 4.0456 data: 0.0032 max mem: 19788 +Epoch: [28] [ 770/2138] eta: 1:32:10 lr: 1.6460876702922405e-05 loss: 0.0235 (0.0240) time: 4.0485 data: 0.0033 max mem: 19788 +Epoch: [28] [ 780/2138] eta: 1:31:29 lr: 1.6454923282491814e-05 loss: 0.0237 (0.0240) time: 4.0551 data: 0.0036 max mem: 19788 +Epoch: [28] [ 790/2138] eta: 1:30:49 lr: 1.644896962272291e-05 loss: 0.0226 (0.0240) time: 4.0541 data: 0.0035 max mem: 19788 +Epoch: [28] [ 800/2138] eta: 1:30:09 lr: 1.644301572350983e-05 loss: 0.0209 (0.0240) time: 4.0505 data: 0.0033 max mem: 19788 +Epoch: [28] [ 810/2138] eta: 1:29:28 lr: 1.643706158474659e-05 loss: 0.0209 (0.0239) time: 4.0485 data: 0.0034 max mem: 19788 +Epoch: [28] [ 820/2138] eta: 1:28:48 lr: 1.6431107206327128e-05 loss: 0.0229 (0.0239) time: 4.0545 data: 0.0032 max mem: 19788 +Epoch: [28] [ 830/2138] eta: 1:28:08 lr: 1.6425152588145298e-05 loss: 0.0200 (0.0239) time: 4.0558 data: 0.0034 max mem: 19788 +Epoch: [28] [ 840/2138] eta: 1:27:28 lr: 1.641919773009486e-05 loss: 0.0199 (0.0239) time: 4.0501 data: 0.0036 max mem: 19788 +Epoch: [28] [ 850/2138] eta: 1:26:47 lr: 1.6413242632069472e-05 loss: 0.0199 (0.0238) time: 4.0445 data: 0.0035 max mem: 19788 +Epoch: [28] [ 860/2138] eta: 1:26:07 lr: 1.6407287293962726e-05 loss: 0.0222 (0.0238) time: 4.0430 data: 0.0035 max mem: 19788 +Epoch: [28] [ 870/2138] eta: 1:25:26 lr: 1.64013317156681e-05 loss: 0.0250 (0.0238) time: 4.0409 data: 0.0033 max mem: 19788 +Epoch: [28] [ 880/2138] eta: 1:24:46 lr: 1.6395375897079002e-05 loss: 0.0223 (0.0238) time: 4.0375 data: 0.0031 max mem: 19788 +Epoch: [28] [ 890/2138] eta: 1:24:05 lr: 1.6389419838088728e-05 loss: 0.0225 (0.0238) time: 4.0345 data: 0.0032 max mem: 19788 +Epoch: [28] [ 900/2138] eta: 1:23:25 lr: 1.638346353859051e-05 loss: 0.0237 (0.0238) time: 4.0348 data: 0.0034 max mem: 19788 +Epoch: [28] [ 910/2138] eta: 1:22:44 lr: 1.637750699847746e-05 loss: 0.0219 (0.0238) time: 4.0396 data: 0.0033 max mem: 19788 +Epoch: [28] [ 920/2138] eta: 1:22:04 lr: 1.6371550217642633e-05 loss: 0.0213 (0.0238) time: 4.0357 data: 0.0033 max mem: 19788 +Epoch: [28] [ 930/2138] eta: 1:21:23 lr: 1.6365593195978954e-05 loss: 0.0202 (0.0238) time: 4.0351 data: 0.0033 max mem: 19788 +Epoch: [28] [ 940/2138] eta: 1:20:43 lr: 1.6359635933379294e-05 loss: 0.0212 (0.0238) time: 4.0389 data: 0.0034 max mem: 19788 +Epoch: [28] [ 950/2138] eta: 1:20:02 lr: 1.63536784297364e-05 loss: 0.0259 (0.0239) time: 4.0386 data: 0.0035 max mem: 19788 +Epoch: [28] [ 960/2138] eta: 1:19:22 lr: 1.6347720684942965e-05 loss: 0.0259 (0.0239) time: 4.0381 data: 0.0034 max mem: 19788 +Epoch: [28] [ 970/2138] eta: 1:18:41 lr: 1.6341762698891553e-05 loss: 0.0233 (0.0238) time: 4.0386 data: 0.0032 max mem: 19788 +Epoch: [28] [ 980/2138] eta: 1:18:01 lr: 1.6335804471474664e-05 loss: 0.0207 (0.0238) time: 4.0440 data: 0.0032 max mem: 19788 +Epoch: [28] [ 990/2138] eta: 1:17:20 lr: 1.6329846002584684e-05 loss: 0.0226 (0.0239) time: 4.0445 data: 0.0033 max mem: 19788 +Epoch: [28] [1000/2138] eta: 1:16:40 lr: 1.6323887292113938e-05 loss: 0.0237 (0.0239) time: 4.0449 data: 0.0032 max mem: 19788 +Epoch: [28] [1010/2138] eta: 1:16:00 lr: 1.631792833995462e-05 loss: 0.0216 (0.0239) time: 4.0482 data: 0.0033 max mem: 19788 +Epoch: [28] [1020/2138] eta: 1:15:19 lr: 1.6311969145998872e-05 loss: 0.0208 (0.0238) time: 4.0503 data: 0.0033 max mem: 19788 +Epoch: [28] [1030/2138] eta: 1:14:39 lr: 1.630600971013871e-05 loss: 0.0190 (0.0238) time: 4.0503 data: 0.0034 max mem: 19788 +Epoch: [28] [1040/2138] eta: 1:13:59 lr: 1.6300050032266084e-05 loss: 0.0231 (0.0239) time: 4.0508 data: 0.0034 max mem: 19788 +Epoch: [28] [1050/2138] eta: 1:13:18 lr: 1.629409011227283e-05 loss: 0.0231 (0.0239) time: 4.0553 data: 0.0033 max mem: 19788 +Epoch: [28] [1060/2138] eta: 1:12:38 lr: 1.6288129950050717e-05 loss: 0.0229 (0.0238) time: 4.0586 data: 0.0033 max mem: 19788 +Epoch: [28] [1070/2138] eta: 1:11:58 lr: 1.62821695454914e-05 loss: 0.0223 (0.0238) time: 4.0452 data: 0.0035 max mem: 19788 +Epoch: [28] [1080/2138] eta: 1:11:17 lr: 1.627620889848644e-05 loss: 0.0219 (0.0238) time: 4.0347 data: 0.0035 max mem: 19788 +Epoch: [28] [1090/2138] eta: 1:10:37 lr: 1.6270248008927324e-05 loss: 0.0229 (0.0238) time: 4.0387 data: 0.0035 max mem: 19788 +Epoch: [28] [1100/2138] eta: 1:09:56 lr: 1.626428687670543e-05 loss: 0.0246 (0.0238) time: 4.0414 data: 0.0034 max mem: 19788 +Epoch: [28] [1110/2138] eta: 1:09:16 lr: 1.6258325501712056e-05 loss: 0.0228 (0.0238) time: 4.0417 data: 0.0033 max mem: 19788 +Epoch: [28] [1120/2138] eta: 1:08:35 lr: 1.6252363883838395e-05 loss: 0.0203 (0.0238) time: 4.0417 data: 0.0033 max mem: 19788 +Epoch: [28] [1130/2138] eta: 1:07:55 lr: 1.6246402022975558e-05 loss: 0.0228 (0.0238) time: 4.0392 data: 0.0032 max mem: 19788 +Epoch: [28] [1140/2138] eta: 1:07:14 lr: 1.6240439919014544e-05 loss: 0.0226 (0.0238) time: 4.0410 data: 0.0031 max mem: 19788 +Epoch: [28] [1150/2138] eta: 1:06:34 lr: 1.6234477571846287e-05 loss: 0.0204 (0.0238) time: 4.0458 data: 0.0031 max mem: 19788 +Epoch: [28] [1160/2138] eta: 1:05:54 lr: 1.62285149813616e-05 loss: 0.0200 (0.0238) time: 4.0483 data: 0.0033 max mem: 19788 +Epoch: [28] [1170/2138] eta: 1:05:13 lr: 1.6222552147451226e-05 loss: 0.0226 (0.0238) time: 4.0489 data: 0.0036 max mem: 19788 +Epoch: [28] [1180/2138] eta: 1:04:33 lr: 1.621658907000579e-05 loss: 0.0225 (0.0238) time: 4.0502 data: 0.0037 max mem: 19788 +Epoch: [28] [1190/2138] eta: 1:03:52 lr: 1.621062574891584e-05 loss: 0.0224 (0.0238) time: 4.0516 data: 0.0035 max mem: 19788 +Epoch: [28] [1200/2138] eta: 1:03:12 lr: 1.620466218407183e-05 loss: 0.0224 (0.0238) time: 4.0400 data: 0.0033 max mem: 19788 +Epoch: [28] [1210/2138] eta: 1:02:32 lr: 1.6198698375364117e-05 loss: 0.0219 (0.0238) time: 4.0362 data: 0.0033 max mem: 19788 +Epoch: [28] [1220/2138] eta: 1:01:51 lr: 1.6192734322682952e-05 loss: 0.0219 (0.0238) time: 4.0437 data: 0.0033 max mem: 19788 +Epoch: [28] [1230/2138] eta: 1:01:11 lr: 1.6186770025918517e-05 loss: 0.0221 (0.0238) time: 4.0468 data: 0.0033 max mem: 19788 +Epoch: [28] [1240/2138] eta: 1:00:30 lr: 1.6180805484960867e-05 loss: 0.0232 (0.0238) time: 4.0445 data: 0.0034 max mem: 19788 +Epoch: [28] [1250/2138] eta: 0:59:50 lr: 1.61748406997e-05 loss: 0.0229 (0.0238) time: 4.0417 data: 0.0033 max mem: 19788 +Epoch: [28] [1260/2138] eta: 0:59:09 lr: 1.616887567002578e-05 loss: 0.0198 (0.0238) time: 4.0434 data: 0.0034 max mem: 19788 +Epoch: [28] [1270/2138] eta: 0:58:29 lr: 1.6162910395828015e-05 loss: 0.0194 (0.0237) time: 4.0434 data: 0.0034 max mem: 19788 +Epoch: [28] [1280/2138] eta: 0:57:48 lr: 1.6156944876996383e-05 loss: 0.0205 (0.0237) time: 4.0357 data: 0.0031 max mem: 19788 +Epoch: [28] [1290/2138] eta: 0:57:08 lr: 1.6150979113420494e-05 loss: 0.0229 (0.0237) time: 4.0326 data: 0.0033 max mem: 19788 +Epoch: [28] [1300/2138] eta: 0:56:27 lr: 1.6145013104989843e-05 loss: 0.0228 (0.0237) time: 4.0372 data: 0.0033 max mem: 19788 +Epoch: [28] [1310/2138] eta: 0:55:47 lr: 1.6139046851593845e-05 loss: 0.0227 (0.0237) time: 4.0462 data: 0.0032 max mem: 19788 +Epoch: [28] [1320/2138] eta: 0:55:07 lr: 1.6133080353121807e-05 loss: 0.0227 (0.0237) time: 4.0571 data: 0.0033 max mem: 19788 +Epoch: [28] [1330/2138] eta: 0:54:26 lr: 1.6127113609462956e-05 loss: 0.0222 (0.0237) time: 4.0495 data: 0.0034 max mem: 19788 +Epoch: [28] [1340/2138] eta: 0:53:46 lr: 1.61211466205064e-05 loss: 0.0218 (0.0237) time: 4.0424 data: 0.0033 max mem: 19788 +Epoch: [28] [1350/2138] eta: 0:53:05 lr: 1.611517938614118e-05 loss: 0.0254 (0.0238) time: 4.0433 data: 0.0033 max mem: 19788 +Epoch: [28] [1360/2138] eta: 0:52:25 lr: 1.6109211906256215e-05 loss: 0.0255 (0.0238) time: 4.0429 data: 0.0033 max mem: 19788 +Epoch: [28] [1370/2138] eta: 0:51:45 lr: 1.6103244180740347e-05 loss: 0.0230 (0.0238) time: 4.0455 data: 0.0032 max mem: 19788 +Epoch: [28] [1380/2138] eta: 0:51:04 lr: 1.609727620948231e-05 loss: 0.0230 (0.0238) time: 4.0423 data: 0.0035 max mem: 19788 +Epoch: [28] [1390/2138] eta: 0:50:24 lr: 1.6091307992370742e-05 loss: 0.0241 (0.0238) time: 4.0397 data: 0.0034 max mem: 19788 +Epoch: [28] [1400/2138] eta: 0:49:43 lr: 1.6085339529294195e-05 loss: 0.0232 (0.0238) time: 4.0392 data: 0.0031 max mem: 19788 +Epoch: [28] [1410/2138] eta: 0:49:03 lr: 1.6079370820141117e-05 loss: 0.0209 (0.0238) time: 4.0434 data: 0.0032 max mem: 19788 +Epoch: [28] [1420/2138] eta: 0:48:22 lr: 1.607340186479986e-05 loss: 0.0209 (0.0238) time: 4.0493 data: 0.0033 max mem: 19788 +Epoch: [28] [1430/2138] eta: 0:47:42 lr: 1.606743266315867e-05 loss: 0.0237 (0.0238) time: 4.0507 data: 0.0033 max mem: 19788 +Epoch: [28] [1440/2138] eta: 0:47:02 lr: 1.6061463215105725e-05 loss: 0.0231 (0.0238) time: 4.0496 data: 0.0033 max mem: 19788 +Epoch: [28] [1450/2138] eta: 0:46:21 lr: 1.6055493520529068e-05 loss: 0.0233 (0.0238) time: 4.0511 data: 0.0032 max mem: 19788 +Epoch: [28] [1460/2138] eta: 0:45:41 lr: 1.604952357931668e-05 loss: 0.0261 (0.0238) time: 4.0523 data: 0.0032 max mem: 19788 +Epoch: [28] [1470/2138] eta: 0:45:01 lr: 1.6043553391356413e-05 loss: 0.0261 (0.0238) time: 4.0488 data: 0.0032 max mem: 19788 +Epoch: [28] [1480/2138] eta: 0:44:20 lr: 1.603758295653605e-05 loss: 0.0252 (0.0238) time: 4.0527 data: 0.0032 max mem: 19788 +Epoch: [28] [1490/2138] eta: 0:43:40 lr: 1.6031612274743248e-05 loss: 0.0241 (0.0238) time: 4.0514 data: 0.0034 max mem: 19788 +Epoch: [28] [1500/2138] eta: 0:42:59 lr: 1.60256413458656e-05 loss: 0.0213 (0.0238) time: 4.0407 data: 0.0034 max mem: 19788 +Epoch: [28] [1510/2138] eta: 0:42:19 lr: 1.601967016979057e-05 loss: 0.0235 (0.0238) time: 4.0398 data: 0.0032 max mem: 19788 +Epoch: [28] [1520/2138] eta: 0:41:38 lr: 1.6013698746405545e-05 loss: 0.0195 (0.0238) time: 4.0460 data: 0.0031 max mem: 19788 +Epoch: [28] [1530/2138] eta: 0:40:58 lr: 1.60077270755978e-05 loss: 0.0192 (0.0238) time: 4.0460 data: 0.0033 max mem: 19788 +Epoch: [28] [1540/2138] eta: 0:40:18 lr: 1.6001755157254526e-05 loss: 0.0213 (0.0238) time: 4.0488 data: 0.0034 max mem: 19788 +Epoch: [28] [1550/2138] eta: 0:39:37 lr: 1.5995782991262795e-05 loss: 0.0229 (0.0238) time: 4.0910 data: 0.0036 max mem: 19788 +Epoch: [28] [1560/2138] eta: 0:38:57 lr: 1.598981057750961e-05 loss: 0.0229 (0.0238) time: 4.0889 data: 0.0036 max mem: 19788 +Epoch: [28] [1570/2138] eta: 0:38:16 lr: 1.598383791588184e-05 loss: 0.0220 (0.0238) time: 4.0353 data: 0.0036 max mem: 19788 +Epoch: [28] [1580/2138] eta: 0:37:36 lr: 1.5977865006266295e-05 loss: 0.0215 (0.0238) time: 4.0309 data: 0.0035 max mem: 19788 +Epoch: [28] [1590/2138] eta: 0:36:56 lr: 1.597189184854965e-05 loss: 0.0251 (0.0238) time: 4.0473 data: 0.0032 max mem: 19788 +Epoch: [28] [1600/2138] eta: 0:36:15 lr: 1.5965918442618508e-05 loss: 0.0263 (0.0238) time: 4.0519 data: 0.0032 max mem: 19788 +Epoch: [28] [1610/2138] eta: 0:35:35 lr: 1.595994478835935e-05 loss: 0.0235 (0.0238) time: 4.0506 data: 0.0034 max mem: 19788 +Epoch: [28] [1620/2138] eta: 0:34:54 lr: 1.5953970885658583e-05 loss: 0.0198 (0.0238) time: 4.0533 data: 0.0033 max mem: 19788 +Epoch: [28] [1630/2138] eta: 0:34:14 lr: 1.5947996734402488e-05 loss: 0.0238 (0.0238) time: 4.0546 data: 0.0031 max mem: 19788 +Epoch: [28] [1640/2138] eta: 0:33:34 lr: 1.594202233447727e-05 loss: 0.0234 (0.0238) time: 4.0444 data: 0.0033 max mem: 19788 +Epoch: [28] [1650/2138] eta: 0:32:53 lr: 1.5936047685769014e-05 loss: 0.0199 (0.0238) time: 4.0344 data: 0.0036 max mem: 19788 +Epoch: [28] [1660/2138] eta: 0:32:13 lr: 1.5930072788163732e-05 loss: 0.0195 (0.0238) time: 4.0394 data: 0.0035 max mem: 19788 +Epoch: [28] [1670/2138] eta: 0:31:32 lr: 1.5924097641547302e-05 loss: 0.0199 (0.0238) time: 4.0433 data: 0.0031 max mem: 19788 +Epoch: [28] [1680/2138] eta: 0:30:52 lr: 1.5918122245805535e-05 loss: 0.0228 (0.0238) time: 4.0456 data: 0.0032 max mem: 19788 +Epoch: [28] [1690/2138] eta: 0:30:11 lr: 1.5912146600824124e-05 loss: 0.0235 (0.0238) time: 4.0511 data: 0.0032 max mem: 19788 +Epoch: [28] [1700/2138] eta: 0:29:31 lr: 1.590617070648865e-05 loss: 0.0221 (0.0238) time: 4.0525 data: 0.0030 max mem: 19788 +Epoch: [28] [1710/2138] eta: 0:28:50 lr: 1.590019456268463e-05 loss: 0.0216 (0.0237) time: 4.0414 data: 0.0031 max mem: 19788 +Epoch: [28] [1720/2138] eta: 0:28:10 lr: 1.5894218169297444e-05 loss: 0.0226 (0.0238) time: 4.0327 data: 0.0034 max mem: 19788 +Epoch: [28] [1730/2138] eta: 0:27:30 lr: 1.58882415262124e-05 loss: 0.0226 (0.0237) time: 4.0631 data: 0.0035 max mem: 19788 +Epoch: [28] [1740/2138] eta: 0:26:49 lr: 1.5882264633314673e-05 loss: 0.0223 (0.0237) time: 4.0682 data: 0.0033 max mem: 19788 +Epoch: [28] [1750/2138] eta: 0:26:09 lr: 1.5876287490489373e-05 loss: 0.0233 (0.0237) time: 4.0470 data: 0.0033 max mem: 19788 +Epoch: [28] [1760/2138] eta: 0:25:28 lr: 1.5870310097621486e-05 loss: 0.0233 (0.0237) time: 4.0502 data: 0.0033 max mem: 19788 +Epoch: [28] [1770/2138] eta: 0:24:48 lr: 1.5864332454595906e-05 loss: 0.0209 (0.0237) time: 4.0489 data: 0.0032 max mem: 19788 +Epoch: [28] [1780/2138] eta: 0:24:07 lr: 1.5858354561297416e-05 loss: 0.0210 (0.0237) time: 4.0456 data: 0.0034 max mem: 19788 +Epoch: [28] [1790/2138] eta: 0:23:27 lr: 1.5852376417610715e-05 loss: 0.0210 (0.0237) time: 4.0432 data: 0.0036 max mem: 19788 +Epoch: [28] [1800/2138] eta: 0:22:47 lr: 1.584639802342038e-05 loss: 0.0213 (0.0237) time: 4.0425 data: 0.0036 max mem: 19788 +Epoch: [28] [1810/2138] eta: 0:22:06 lr: 1.5840419378610904e-05 loss: 0.0214 (0.0237) time: 4.0447 data: 0.0034 max mem: 19788 +Epoch: [28] [1820/2138] eta: 0:21:26 lr: 1.5834440483066662e-05 loss: 0.0220 (0.0237) time: 4.0509 data: 0.0034 max mem: 19788 +Epoch: [28] [1830/2138] eta: 0:20:45 lr: 1.582846133667195e-05 loss: 0.0214 (0.0237) time: 4.0433 data: 0.0034 max mem: 19788 +Epoch: [28] [1840/2138] eta: 0:20:05 lr: 1.5822481939310933e-05 loss: 0.0240 (0.0238) time: 4.0283 data: 0.0034 max mem: 19788 +Epoch: [28] [1850/2138] eta: 0:19:24 lr: 1.5816502290867698e-05 loss: 0.0256 (0.0238) time: 4.0294 data: 0.0033 max mem: 19788 +Epoch: [28] [1860/2138] eta: 0:18:44 lr: 1.5810522391226216e-05 loss: 0.0231 (0.0238) time: 4.0398 data: 0.0034 max mem: 19788 +Epoch: [28] [1870/2138] eta: 0:18:03 lr: 1.5804542240270364e-05 loss: 0.0225 (0.0238) time: 4.0437 data: 0.0034 max mem: 19788 +Epoch: [28] [1880/2138] eta: 0:17:23 lr: 1.579856183788391e-05 loss: 0.0217 (0.0238) time: 4.0424 data: 0.0031 max mem: 19788 +Epoch: [28] [1890/2138] eta: 0:16:42 lr: 1.579258118395052e-05 loss: 0.0199 (0.0238) time: 4.0451 data: 0.0032 max mem: 19788 +Epoch: [28] [1900/2138] eta: 0:16:02 lr: 1.5786600278353762e-05 loss: 0.0192 (0.0237) time: 4.0478 data: 0.0034 max mem: 19788 +Epoch: [28] [1910/2138] eta: 0:15:22 lr: 1.5780619120977103e-05 loss: 0.0200 (0.0237) time: 4.0407 data: 0.0032 max mem: 19788 +Epoch: [28] [1920/2138] eta: 0:14:41 lr: 1.577463771170389e-05 loss: 0.0222 (0.0237) time: 4.0389 data: 0.0030 max mem: 19788 +Epoch: [28] [1930/2138] eta: 0:14:01 lr: 1.576865605041739e-05 loss: 0.0222 (0.0237) time: 4.0364 data: 0.0030 max mem: 19788 +Epoch: [28] [1940/2138] eta: 0:13:20 lr: 1.576267413700075e-05 loss: 0.0226 (0.0237) time: 4.0265 data: 0.0033 max mem: 19788 +Epoch: [28] [1950/2138] eta: 0:12:40 lr: 1.5756691971337024e-05 loss: 0.0230 (0.0237) time: 4.0345 data: 0.0034 max mem: 19788 +Epoch: [28] [1960/2138] eta: 0:11:59 lr: 1.5750709553309148e-05 loss: 0.0218 (0.0237) time: 4.0311 data: 0.0032 max mem: 19788 +Epoch: [28] [1970/2138] eta: 0:11:19 lr: 1.5744726882799977e-05 loss: 0.0234 (0.0237) time: 4.0243 data: 0.0034 max mem: 19788 +Epoch: [28] [1980/2138] eta: 0:10:38 lr: 1.5738743959692236e-05 loss: 0.0207 (0.0237) time: 4.0342 data: 0.0037 max mem: 19788 +Epoch: [28] [1990/2138] eta: 0:09:58 lr: 1.573276078386857e-05 loss: 0.0217 (0.0237) time: 4.0305 data: 0.0035 max mem: 19788 +Epoch: [28] [2000/2138] eta: 0:09:18 lr: 1.5726777355211503e-05 loss: 0.0234 (0.0237) time: 4.0221 data: 0.0033 max mem: 19788 +Epoch: [28] [2010/2138] eta: 0:08:37 lr: 1.5720793673603454e-05 loss: 0.0237 (0.0237) time: 4.0264 data: 0.0033 max mem: 19788 +Epoch: [28] [2020/2138] eta: 0:07:57 lr: 1.5714809738926758e-05 loss: 0.0237 (0.0237) time: 4.0279 data: 0.0035 max mem: 19788 +Epoch: [28] [2030/2138] eta: 0:07:16 lr: 1.5708825551063616e-05 loss: 0.0229 (0.0237) time: 4.0210 data: 0.0035 max mem: 19788 +Epoch: [28] [2040/2138] eta: 0:06:36 lr: 1.570284110989616e-05 loss: 0.0229 (0.0237) time: 4.0310 data: 0.0034 max mem: 19788 +Epoch: [28] [2050/2138] eta: 0:05:55 lr: 1.569685641530637e-05 loss: 0.0219 (0.0237) time: 4.0476 data: 0.0034 max mem: 19788 +Epoch: [28] [2060/2138] eta: 0:05:15 lr: 1.5690871467176173e-05 loss: 0.0205 (0.0237) time: 4.0492 data: 0.0035 max mem: 19788 +Epoch: [28] [2070/2138] eta: 0:04:34 lr: 1.5684886265387353e-05 loss: 0.0219 (0.0237) time: 4.0479 data: 0.0039 max mem: 19788 +Epoch: [28] [2080/2138] eta: 0:03:54 lr: 1.5678900809821607e-05 loss: 0.0230 (0.0237) time: 4.0471 data: 0.0038 max mem: 19788 +Epoch: [28] [2090/2138] eta: 0:03:14 lr: 1.5672915100360514e-05 loss: 0.0231 (0.0237) time: 4.0421 data: 0.0034 max mem: 19788 +Epoch: [28] [2100/2138] eta: 0:02:33 lr: 1.5666929136885562e-05 loss: 0.0217 (0.0237) time: 4.0426 data: 0.0034 max mem: 19788 +Epoch: [28] [2110/2138] eta: 0:01:53 lr: 1.566094291927812e-05 loss: 0.0255 (0.0237) time: 4.0477 data: 0.0034 max mem: 19788 +Epoch: [28] [2120/2138] eta: 0:01:12 lr: 1.5654956447419467e-05 loss: 0.0279 (0.0237) time: 4.0419 data: 0.0032 max mem: 19788 +Epoch: [28] [2130/2138] eta: 0:00:32 lr: 1.564896972119075e-05 loss: 0.0244 (0.0238) time: 4.0213 data: 0.0030 max mem: 19788 +Epoch: [28] Total time: 2:24:05 +Test: [ 0/21770] eta: 20:52:53 time: 3.4531 data: 3.2336 max mem: 19788 +Test: [ 100/21770] eta: 0:38:46 time: 0.0732 data: 0.0024 max mem: 19788 +Test: [ 200/21770] eta: 0:31:22 time: 0.0659 data: 0.0020 max mem: 19788 +Test: [ 300/21770] eta: 0:28:49 time: 0.0728 data: 0.0022 max mem: 19788 +Test: [ 400/21770] eta: 0:27:50 time: 0.0654 data: 0.0020 max mem: 19788 +Test: [ 500/21770] eta: 0:27:06 time: 0.0646 data: 0.0020 max mem: 19788 +Test: [ 600/21770] eta: 0:26:21 time: 0.0637 data: 0.0021 max mem: 19788 +Test: [ 700/21770] eta: 0:25:40 time: 0.0668 data: 0.0021 max mem: 19788 +Test: [ 800/21770] eta: 0:25:22 time: 0.0737 data: 0.0021 max mem: 19788 +Test: [ 900/21770] eta: 0:25:13 time: 0.0629 data: 0.0020 max mem: 19788 +Test: [ 1000/21770] eta: 0:25:07 time: 0.0725 data: 0.0023 max mem: 19788 +Test: [ 1100/21770] eta: 0:25:06 time: 0.0772 data: 0.0021 max mem: 19788 +Test: [ 1200/21770] eta: 0:24:49 time: 0.0727 data: 0.0023 max mem: 19788 +Test: [ 1300/21770] eta: 0:24:54 time: 0.0817 data: 0.0027 max mem: 19788 +Test: [ 1400/21770] eta: 0:24:49 time: 0.0784 data: 0.0026 max mem: 19788 +Test: [ 1500/21770] eta: 0:24:39 time: 0.0655 data: 0.0024 max mem: 19788 +Test: [ 1600/21770] eta: 0:24:25 time: 0.0640 data: 0.0021 max mem: 19788 +Test: [ 1700/21770] eta: 0:24:09 time: 0.0697 data: 0.0023 max mem: 19788 +Test: [ 1800/21770] eta: 0:23:56 time: 0.0647 data: 0.0022 max mem: 19788 +Test: [ 1900/21770] eta: 0:23:41 time: 0.0645 data: 0.0021 max mem: 19788 +Test: [ 2000/21770] eta: 0:23:32 time: 0.0693 data: 0.0021 max mem: 19788 +Test: [ 2100/21770] eta: 0:23:26 time: 0.0630 data: 0.0020 max mem: 19788 +Test: [ 2200/21770] eta: 0:23:15 time: 0.0709 data: 0.0020 max mem: 19788 +Test: [ 2300/21770] eta: 0:23:14 time: 0.0835 data: 0.0026 max mem: 19788 +Test: [ 2400/21770] eta: 0:23:08 time: 0.0654 data: 0.0019 max mem: 19788 +Test: [ 2500/21770] eta: 0:22:59 time: 0.0774 data: 0.0022 max mem: 19788 +Test: [ 2600/21770] eta: 0:22:51 time: 0.0672 data: 0.0020 max mem: 19788 +Test: [ 2700/21770] eta: 0:22:46 time: 0.0855 data: 0.0027 max mem: 19788 +Test: [ 2800/21770] eta: 0:22:41 time: 0.0667 data: 0.0022 max mem: 19788 +Test: [ 2900/21770] eta: 0:22:34 time: 0.0710 data: 0.0021 max mem: 19788 +Test: [ 3000/21770] eta: 0:22:25 time: 0.0647 data: 0.0019 max mem: 19788 +Test: [ 3100/21770] eta: 0:22:18 time: 0.0752 data: 0.0023 max mem: 19788 +Test: [ 3200/21770] eta: 0:22:10 time: 0.0843 data: 0.0027 max mem: 19788 +Test: [ 3300/21770] eta: 0:22:05 time: 0.0660 data: 0.0020 max mem: 19788 +Test: [ 3400/21770] eta: 0:21:59 time: 0.0680 data: 0.0019 max mem: 19788 +Test: [ 3500/21770] eta: 0:21:51 time: 0.0683 data: 0.0022 max mem: 19788 +Test: [ 3600/21770] eta: 0:21:43 time: 0.0736 data: 0.0022 max mem: 19788 +Test: [ 3700/21770] eta: 0:21:38 time: 0.0686 data: 0.0021 max mem: 19788 +Test: [ 3800/21770] eta: 0:21:27 time: 0.0646 data: 0.0022 max mem: 19788 +Test: [ 3900/21770] eta: 0:21:19 time: 0.0734 data: 0.0022 max mem: 19788 +Test: [ 4000/21770] eta: 0:21:10 time: 0.0785 data: 0.0025 max mem: 19788 +Test: [ 4100/21770] eta: 0:21:04 time: 0.0689 data: 0.0020 max mem: 19788 +Test: [ 4200/21770] eta: 0:20:59 time: 0.0747 data: 0.0025 max mem: 19788 +Test: [ 4300/21770] eta: 0:20:53 time: 0.0641 data: 0.0018 max mem: 19788 +Test: [ 4400/21770] eta: 0:20:42 time: 0.0639 data: 0.0020 max mem: 19788 +Test: [ 4500/21770] eta: 0:20:33 time: 0.0641 data: 0.0022 max mem: 19788 +Test: [ 4600/21770] eta: 0:20:26 time: 0.0753 data: 0.0021 max mem: 19788 +Test: [ 4700/21770] eta: 0:20:18 time: 0.0707 data: 0.0024 max mem: 19788 +Test: [ 4800/21770] eta: 0:20:11 time: 0.0664 data: 0.0022 max mem: 19788 +Test: [ 4900/21770] eta: 0:20:06 time: 0.0693 data: 0.0022 max mem: 19788 +Test: [ 5000/21770] eta: 0:19:59 time: 0.0691 data: 0.0019 max mem: 19788 +Test: [ 5100/21770] eta: 0:19:53 time: 0.0852 data: 0.0028 max mem: 19788 +Test: [ 5200/21770] eta: 0:19:46 time: 0.0689 data: 0.0020 max mem: 19788 +Test: [ 5300/21770] eta: 0:19:37 time: 0.0651 data: 0.0020 max mem: 19788 +Test: [ 5400/21770] eta: 0:19:29 time: 0.0698 data: 0.0020 max mem: 19788 +Test: [ 5500/21770] eta: 0:19:22 time: 0.0812 data: 0.0026 max mem: 19788 +Test: [ 5600/21770] eta: 0:19:16 time: 0.0779 data: 0.0024 max mem: 19788 +Test: [ 5700/21770] eta: 0:19:10 time: 0.0815 data: 0.0022 max mem: 19788 +Test: [ 5800/21770] eta: 0:19:05 time: 0.0784 data: 0.0025 max mem: 19788 +Test: [ 5900/21770] eta: 0:18:56 time: 0.0629 data: 0.0020 max mem: 19788 +Test: [ 6000/21770] eta: 0:18:49 time: 0.0765 data: 0.0022 max mem: 19788 +Test: [ 6100/21770] eta: 0:18:44 time: 0.0754 data: 0.0024 max mem: 19788 +Test: [ 6200/21770] eta: 0:18:37 time: 0.0682 data: 0.0020 max mem: 19788 +Test: [ 6300/21770] eta: 0:18:31 time: 0.0651 data: 0.0020 max mem: 19788 +Test: [ 6400/21770] eta: 0:18:23 time: 0.0659 data: 0.0019 max mem: 19788 +Test: [ 6500/21770] eta: 0:18:15 time: 0.0710 data: 0.0021 max mem: 19788 +Test: [ 6600/21770] eta: 0:18:09 time: 0.0707 data: 0.0019 max mem: 19788 +Test: [ 6700/21770] eta: 0:18:03 time: 0.0697 data: 0.0020 max mem: 19788 +Test: [ 6800/21770] eta: 0:17:56 time: 0.0719 data: 0.0022 max mem: 19788 +Test: [ 6900/21770] eta: 0:17:49 time: 0.0852 data: 0.0021 max mem: 19788 +Test: [ 7000/21770] eta: 0:17:42 time: 0.0635 data: 0.0017 max mem: 19788 +Test: [ 7100/21770] eta: 0:17:34 time: 0.0661 data: 0.0020 max mem: 19788 +Test: [ 7200/21770] eta: 0:17:27 time: 0.0699 data: 0.0022 max mem: 19788 +Test: [ 7300/21770] eta: 0:17:19 time: 0.0631 data: 0.0020 max mem: 19788 +Test: [ 7400/21770] eta: 0:17:11 time: 0.0681 data: 0.0021 max mem: 19788 +Test: [ 7500/21770] eta: 0:17:04 time: 0.0668 data: 0.0019 max mem: 19788 +Test: [ 7600/21770] eta: 0:16:57 time: 0.0682 data: 0.0020 max mem: 19788 +Test: [ 7700/21770] eta: 0:16:49 time: 0.0708 data: 0.0022 max mem: 19788 +Test: [ 7800/21770] eta: 0:16:42 time: 0.0755 data: 0.0022 max mem: 19788 +Test: [ 7900/21770] eta: 0:16:35 time: 0.0715 data: 0.0022 max mem: 19788 +Test: [ 8000/21770] eta: 0:16:29 time: 0.0692 data: 0.0019 max mem: 19788 +Test: [ 8100/21770] eta: 0:16:22 time: 0.0745 data: 0.0024 max mem: 19788 +Test: [ 8200/21770] eta: 0:16:14 time: 0.0640 data: 0.0019 max mem: 19788 +Test: [ 8300/21770] eta: 0:16:07 time: 0.0788 data: 0.0021 max mem: 19788 +Test: [ 8400/21770] eta: 0:15:59 time: 0.0641 data: 0.0020 max mem: 19788 +Test: [ 8500/21770] eta: 0:15:51 time: 0.0736 data: 0.0023 max mem: 19788 +Test: [ 8600/21770] eta: 0:15:45 time: 0.0718 data: 0.0022 max mem: 19788 +Test: [ 8700/21770] eta: 0:15:36 time: 0.0643 data: 0.0019 max mem: 19788 +Test: [ 8800/21770] eta: 0:15:29 time: 0.0654 data: 0.0021 max mem: 19788 +Test: [ 8900/21770] eta: 0:15:22 time: 0.0862 data: 0.0020 max mem: 19788 +Test: [ 9000/21770] eta: 0:15:15 time: 0.0687 data: 0.0021 max mem: 19788 +Test: [ 9100/21770] eta: 0:15:07 time: 0.0629 data: 0.0019 max mem: 19788 +Test: [ 9200/21770] eta: 0:15:00 time: 0.0649 data: 0.0020 max mem: 19788 +Test: [ 9300/21770] eta: 0:14:53 time: 0.0701 data: 0.0020 max mem: 19788 +Test: [ 9400/21770] eta: 0:14:46 time: 0.0736 data: 0.0023 max mem: 19788 +Test: [ 9500/21770] eta: 0:14:39 time: 0.0765 data: 0.0023 max mem: 19788 +Test: [ 9600/21770] eta: 0:14:32 time: 0.0693 data: 0.0020 max mem: 19788 +Test: [ 9700/21770] eta: 0:14:24 time: 0.0719 data: 0.0022 max mem: 19788 +Test: [ 9800/21770] eta: 0:14:17 time: 0.0664 data: 0.0019 max mem: 19788 +Test: [ 9900/21770] eta: 0:14:10 time: 0.0753 data: 0.0023 max mem: 19788 +Test: [10000/21770] eta: 0:14:02 time: 0.0767 data: 0.0025 max mem: 19788 +Test: [10100/21770] eta: 0:13:55 time: 0.0766 data: 0.0021 max mem: 19788 +Test: [10200/21770] eta: 0:13:48 time: 0.0849 data: 0.0021 max mem: 19788 +Test: [10300/21770] eta: 0:13:42 time: 0.0724 data: 0.0022 max mem: 19788 +Test: [10400/21770] eta: 0:13:35 time: 0.0758 data: 0.0024 max mem: 19788 +Test: [10500/21770] eta: 0:13:28 time: 0.0861 data: 0.0019 max mem: 19788 +Test: [10600/21770] eta: 0:13:21 time: 0.0743 data: 0.0025 max mem: 19788 +Test: [10700/21770] eta: 0:13:15 time: 0.0678 data: 0.0020 max mem: 19788 +Test: [10800/21770] eta: 0:13:07 time: 0.0674 data: 0.0020 max mem: 19788 +Test: [10900/21770] eta: 0:12:59 time: 0.0657 data: 0.0021 max mem: 19788 +Test: [11000/21770] eta: 0:12:52 time: 0.0727 data: 0.0023 max mem: 19788 +Test: [11100/21770] eta: 0:12:45 time: 0.0729 data: 0.0023 max mem: 19788 +Test: [11200/21770] eta: 0:12:38 time: 0.0651 data: 0.0019 max mem: 19788 +Test: [11300/21770] eta: 0:12:31 time: 0.0677 data: 0.0021 max mem: 19788 +Test: [11400/21770] eta: 0:12:24 time: 0.0646 data: 0.0020 max mem: 19788 +Test: [11500/21770] eta: 0:12:17 time: 0.0715 data: 0.0021 max mem: 19788 +Test: [11600/21770] eta: 0:12:10 time: 0.0793 data: 0.0024 max mem: 19788 +Test: [11700/21770] eta: 0:12:03 time: 0.0719 data: 0.0020 max mem: 19788 +Test: [11800/21770] eta: 0:11:56 time: 0.0658 data: 0.0022 max mem: 19788 +Test: [11900/21770] eta: 0:11:49 time: 0.0820 data: 0.0023 max mem: 19788 +Test: [12000/21770] eta: 0:11:42 time: 0.0654 data: 0.0020 max mem: 19788 +Test: [12100/21770] eta: 0:11:34 time: 0.0722 data: 0.0024 max mem: 19788 +Test: [12200/21770] eta: 0:11:27 time: 0.0650 data: 0.0020 max mem: 19788 +Test: [12300/21770] eta: 0:11:20 time: 0.0826 data: 0.0025 max mem: 19788 +Test: [12400/21770] eta: 0:11:13 time: 0.0869 data: 0.0025 max mem: 19788 +Test: [12500/21770] eta: 0:11:06 time: 0.0709 data: 0.0021 max mem: 19788 +Test: [12600/21770] eta: 0:10:59 time: 0.0671 data: 0.0020 max mem: 19788 +Test: [12700/21770] eta: 0:10:52 time: 0.0732 data: 0.0023 max mem: 19788 +Test: [12800/21770] eta: 0:10:45 time: 0.0770 data: 0.0023 max mem: 19788 +Test: [12900/21770] eta: 0:10:38 time: 0.0787 data: 0.0026 max mem: 19788 +Test: [13000/21770] eta: 0:10:31 time: 0.0701 data: 0.0020 max mem: 19788 +Test: [13100/21770] eta: 0:10:24 time: 0.0753 data: 0.0022 max mem: 19788 +Test: [13200/21770] eta: 0:10:16 time: 0.0769 data: 0.0022 max mem: 19788 +Test: [13300/21770] eta: 0:10:09 time: 0.0680 data: 0.0020 max mem: 19788 +Test: [13400/21770] eta: 0:10:02 time: 0.0764 data: 0.0026 max mem: 19788 +Test: [13500/21770] eta: 0:09:55 time: 0.0664 data: 0.0019 max mem: 19788 +Test: [13600/21770] eta: 0:09:48 time: 0.0773 data: 0.0021 max mem: 19788 +Test: [13700/21770] eta: 0:09:41 time: 0.0851 data: 0.0025 max mem: 19788 +Test: [13800/21770] eta: 0:09:34 time: 0.0699 data: 0.0021 max mem: 19788 +Test: [13900/21770] eta: 0:09:27 time: 0.0699 data: 0.0021 max mem: 19788 +Test: [14000/21770] eta: 0:09:20 time: 0.0849 data: 0.0028 max mem: 19788 +Test: [14100/21770] eta: 0:09:13 time: 0.0637 data: 0.0018 max mem: 19788 +Test: [14200/21770] eta: 0:09:06 time: 0.0667 data: 0.0021 max mem: 19788 +Test: [14300/21770] eta: 0:08:59 time: 0.0705 data: 0.0021 max mem: 19788 +Test: [14400/21770] eta: 0:08:52 time: 0.0664 data: 0.0021 max mem: 19788 +Test: [14500/21770] eta: 0:08:44 time: 0.0698 data: 0.0018 max mem: 19788 +Test: [14600/21770] eta: 0:08:37 time: 0.0669 data: 0.0020 max mem: 19788 +Test: [14700/21770] eta: 0:08:30 time: 0.0738 data: 0.0024 max mem: 19788 +Test: [14800/21770] eta: 0:08:22 time: 0.0787 data: 0.0025 max mem: 19788 +Test: [14900/21770] eta: 0:08:16 time: 0.0787 data: 0.0025 max mem: 19788 +Test: [15000/21770] eta: 0:08:08 time: 0.0773 data: 0.0025 max mem: 19788 +Test: [15100/21770] eta: 0:08:01 time: 0.0641 data: 0.0022 max mem: 19788 +Test: [15200/21770] eta: 0:07:54 time: 0.0806 data: 0.0026 max mem: 19788 +Test: [15300/21770] eta: 0:07:47 time: 0.0680 data: 0.0020 max mem: 19788 +Test: [15400/21770] eta: 0:07:40 time: 0.0633 data: 0.0019 max mem: 19788 +Test: [15500/21770] eta: 0:07:33 time: 0.0781 data: 0.0025 max mem: 19788 +Test: [15600/21770] eta: 0:07:25 time: 0.0682 data: 0.0023 max mem: 19788 +Test: [15700/21770] eta: 0:07:18 time: 0.0699 data: 0.0021 max mem: 19788 +Test: [15800/21770] eta: 0:07:11 time: 0.0646 data: 0.0019 max mem: 19788 +Test: [15900/21770] eta: 0:07:04 time: 0.0848 data: 0.0026 max mem: 19788 +Test: [16000/21770] eta: 0:06:57 time: 0.0763 data: 0.0021 max mem: 19788 +Test: [16100/21770] eta: 0:06:50 time: 0.0706 data: 0.0021 max mem: 19788 +Test: [16200/21770] eta: 0:06:42 time: 0.0646 data: 0.0020 max mem: 19788 +Test: [16300/21770] eta: 0:06:35 time: 0.0831 data: 0.0026 max mem: 19788 +Test: [16400/21770] eta: 0:06:28 time: 0.0763 data: 0.0023 max mem: 19788 +Test: [16500/21770] eta: 0:06:20 time: 0.0671 data: 0.0023 max mem: 19788 +Test: [16600/21770] eta: 0:06:13 time: 0.0754 data: 0.0026 max mem: 19788 +Test: [16700/21770] eta: 0:06:06 time: 0.0651 data: 0.0020 max mem: 19788 +Test: [16800/21770] eta: 0:05:58 time: 0.0684 data: 0.0020 max mem: 19788 +Test: [16900/21770] eta: 0:05:51 time: 0.0659 data: 0.0021 max mem: 19788 +Test: [17000/21770] eta: 0:05:44 time: 0.0773 data: 0.0021 max mem: 19788 +Test: [17100/21770] eta: 0:05:37 time: 0.0690 data: 0.0022 max mem: 19788 +Test: [17200/21770] eta: 0:05:29 time: 0.0672 data: 0.0019 max mem: 19788 +Test: [17300/21770] eta: 0:05:22 time: 0.0684 data: 0.0020 max mem: 19788 +Test: [17400/21770] eta: 0:05:15 time: 0.0724 data: 0.0022 max mem: 19788 +Test: [17500/21770] eta: 0:05:08 time: 0.0807 data: 0.0025 max mem: 19788 +Test: [17600/21770] eta: 0:05:00 time: 0.0721 data: 0.0021 max mem: 19788 +Test: [17700/21770] eta: 0:04:53 time: 0.0746 data: 0.0021 max mem: 19788 +Test: [17800/21770] eta: 0:04:46 time: 0.0729 data: 0.0021 max mem: 19788 +Test: [17900/21770] eta: 0:04:39 time: 0.0644 data: 0.0021 max mem: 19788 +Test: [18000/21770] eta: 0:04:32 time: 0.0782 data: 0.0024 max mem: 19788 +Test: [18100/21770] eta: 0:04:24 time: 0.0715 data: 0.0022 max mem: 19788 +Test: [18200/21770] eta: 0:04:17 time: 0.0855 data: 0.0027 max mem: 19788 +Test: [18300/21770] eta: 0:04:10 time: 0.0860 data: 0.0026 max mem: 19788 +Test: [18400/21770] eta: 0:04:03 time: 0.0692 data: 0.0021 max mem: 19788 +Test: [18500/21770] eta: 0:03:56 time: 0.0736 data: 0.0021 max mem: 19788 +Test: [18600/21770] eta: 0:03:48 time: 0.0686 data: 0.0021 max mem: 19788 +Test: [18700/21770] eta: 0:03:41 time: 0.0635 data: 0.0020 max mem: 19788 +Test: [18800/21770] eta: 0:03:34 time: 0.0662 data: 0.0019 max mem: 19788 +Test: [18900/21770] eta: 0:03:27 time: 0.0834 data: 0.0025 max mem: 19788 +Test: [19000/21770] eta: 0:03:19 time: 0.0673 data: 0.0022 max mem: 19788 +Test: [19100/21770] eta: 0:03:12 time: 0.0690 data: 0.0021 max mem: 19788 +Test: [19200/21770] eta: 0:03:05 time: 0.0708 data: 0.0021 max mem: 19788 +Test: [19300/21770] eta: 0:02:58 time: 0.0780 data: 0.0023 max mem: 19788 +Test: [19400/21770] eta: 0:02:51 time: 0.0832 data: 0.0025 max mem: 19788 +Test: [19500/21770] eta: 0:02:43 time: 0.0752 data: 0.0023 max mem: 19788 +Test: [19600/21770] eta: 0:02:36 time: 0.0749 data: 0.0024 max mem: 19788 +Test: [19700/21770] eta: 0:02:29 time: 0.0674 data: 0.0021 max mem: 19788 +Test: [19800/21770] eta: 0:02:22 time: 0.0788 data: 0.0022 max mem: 19788 +Test: [19900/21770] eta: 0:02:15 time: 0.0632 data: 0.0019 max mem: 19788 +Test: [20000/21770] eta: 0:02:07 time: 0.0710 data: 0.0025 max mem: 19788 +Test: [20100/21770] eta: 0:02:00 time: 0.0863 data: 0.0027 max mem: 19788 +Test: [20200/21770] eta: 0:01:53 time: 0.0643 data: 0.0020 max mem: 19788 +Test: [20300/21770] eta: 0:01:46 time: 0.0713 data: 0.0024 max mem: 19788 +Test: [20400/21770] eta: 0:01:38 time: 0.0740 data: 0.0023 max mem: 19788 +Test: [20500/21770] eta: 0:01:31 time: 0.0695 data: 0.0021 max mem: 19788 +Test: [20600/21770] eta: 0:01:24 time: 0.0704 data: 0.0023 max mem: 19788 +Test: [20700/21770] eta: 0:01:17 time: 0.0686 data: 0.0022 max mem: 19788 +Test: [20800/21770] eta: 0:01:10 time: 0.0699 data: 0.0021 max mem: 19788 +Test: [20900/21770] eta: 0:01:02 time: 0.0647 data: 0.0019 max mem: 19788 +Test: [21000/21770] eta: 0:00:55 time: 0.0701 data: 0.0023 max mem: 19788 +Test: [21100/21770] eta: 0:00:48 time: 0.0723 data: 0.0021 max mem: 19788 +Test: [21200/21770] eta: 0:00:41 time: 0.0693 data: 0.0021 max mem: 19788 +Test: [21300/21770] eta: 0:00:33 time: 0.0859 data: 0.0028 max mem: 19788 +Test: [21400/21770] eta: 0:00:26 time: 0.0688 data: 0.0023 max mem: 19788 +Test: [21500/21770] eta: 0:00:19 time: 0.0646 data: 0.0021 max mem: 19788 +Test: [21600/21770] eta: 0:00:12 time: 0.0792 data: 0.0039 max mem: 19788 +Test: [21700/21770] eta: 0:00:05 time: 0.0561 data: 0.0017 max mem: 19788 +Test: Total time: 0:26:11 +Final results: +Mean IoU is 62.66 + + precision@0.5 = 69.40 + precision@0.6 = 64.14 + precision@0.7 = 57.89 + precision@0.8 = 47.29 + precision@0.9 = 23.21 + overall IoU = 63.77 + mean IoU = 62.66 + +Mean accuracy for one-to-zero sample is 84.36 + +Average object IoU 0.6265619743491359 +Overall IoU 63.77328872680664 +Epoch: [29] [ 0/2138] eta: 3:42:08 lr: 1.5644180156981413e-05 loss: 0.0239 (0.0239) time: 6.2343 data: 1.8114 max mem: 19788 +Epoch: [29] [ 10/2138] eta: 2:32:18 lr: 1.5638192972586798e-05 loss: 0.0192 (0.0206) time: 4.2944 data: 0.1665 max mem: 19788 +Epoch: [29] [ 20/2138] eta: 2:28:03 lr: 1.5632205533488817e-05 loss: 0.0183 (0.0199) time: 4.0920 data: 0.0026 max mem: 19788 +Epoch: [29] [ 30/2138] eta: 2:26:17 lr: 1.562621783956824e-05 loss: 0.0183 (0.0202) time: 4.0920 data: 0.0033 max mem: 19788 +Epoch: [29] [ 40/2138] eta: 2:24:56 lr: 1.5620229890705708e-05 loss: 0.0225 (0.0214) time: 4.0937 data: 0.0032 max mem: 19788 +Epoch: [29] [ 50/2138] eta: 2:23:46 lr: 1.561424168678177e-05 loss: 0.0242 (0.0219) time: 4.0813 data: 0.0031 max mem: 19788 +Epoch: [29] [ 60/2138] eta: 2:22:38 lr: 1.5608253227676868e-05 loss: 0.0193 (0.0214) time: 4.0645 data: 0.0032 max mem: 19788 +Epoch: [29] [ 70/2138] eta: 2:21:37 lr: 1.5602264513271333e-05 loss: 0.0179 (0.0211) time: 4.0520 data: 0.0033 max mem: 19788 +Epoch: [29] [ 80/2138] eta: 2:20:40 lr: 1.5596275543445392e-05 loss: 0.0184 (0.0215) time: 4.0481 data: 0.0035 max mem: 19788 +Epoch: [29] [ 90/2138] eta: 2:19:46 lr: 1.5590286318079158e-05 loss: 0.0225 (0.0216) time: 4.0448 data: 0.0036 max mem: 19788 +Epoch: [29] [ 100/2138] eta: 2:18:53 lr: 1.5584296837052648e-05 loss: 0.0234 (0.0218) time: 4.0404 data: 0.0036 max mem: 19788 +Epoch: [29] [ 110/2138] eta: 2:18:04 lr: 1.5578307100245755e-05 loss: 0.0234 (0.0220) time: 4.0403 data: 0.0032 max mem: 19788 +Epoch: [29] [ 120/2138] eta: 2:17:15 lr: 1.5572317107538283e-05 loss: 0.0225 (0.0221) time: 4.0386 data: 0.0031 max mem: 19788 +Epoch: [29] [ 130/2138] eta: 2:16:28 lr: 1.556632685880991e-05 loss: 0.0231 (0.0223) time: 4.0375 data: 0.0032 max mem: 19788 +Epoch: [29] [ 140/2138] eta: 2:15:43 lr: 1.5560336353940228e-05 loss: 0.0236 (0.0222) time: 4.0444 data: 0.0034 max mem: 19788 +Epoch: [29] [ 150/2138] eta: 2:14:56 lr: 1.5554345592808687e-05 loss: 0.0202 (0.0221) time: 4.0402 data: 0.0036 max mem: 19788 +Epoch: [29] [ 160/2138] eta: 2:14:12 lr: 1.5548354575294674e-05 loss: 0.0239 (0.0224) time: 4.0398 data: 0.0034 max mem: 19788 +Epoch: [29] [ 170/2138] eta: 2:13:29 lr: 1.554236330127742e-05 loss: 0.0245 (0.0225) time: 4.0465 data: 0.0032 max mem: 19788 +Epoch: [29] [ 180/2138] eta: 2:12:45 lr: 1.553637177063609e-05 loss: 0.0232 (0.0226) time: 4.0452 data: 0.0032 max mem: 19788 +Epoch: [29] [ 190/2138] eta: 2:12:03 lr: 1.5530379983249705e-05 loss: 0.0200 (0.0226) time: 4.0457 data: 0.0034 max mem: 19788 +Epoch: [29] [ 200/2138] eta: 2:11:19 lr: 1.55243879389972e-05 loss: 0.0169 (0.0223) time: 4.0410 data: 0.0035 max mem: 19788 +Epoch: [29] [ 210/2138] eta: 2:10:37 lr: 1.551839563775739e-05 loss: 0.0234 (0.0225) time: 4.0429 data: 0.0033 max mem: 19788 +Epoch: [29] [ 220/2138] eta: 2:09:54 lr: 1.5512403079408992e-05 loss: 0.0243 (0.0224) time: 4.0479 data: 0.0032 max mem: 19788 +Epoch: [29] [ 230/2138] eta: 2:09:12 lr: 1.55064102638306e-05 loss: 0.0219 (0.0226) time: 4.0445 data: 0.0032 max mem: 19788 +Epoch: [29] [ 240/2138] eta: 2:08:30 lr: 1.5500417190900702e-05 loss: 0.0225 (0.0225) time: 4.0428 data: 0.0033 max mem: 19788 +Epoch: [29] [ 250/2138] eta: 2:07:47 lr: 1.5494423860497683e-05 loss: 0.0202 (0.0224) time: 4.0365 data: 0.0033 max mem: 19788 +Epoch: [29] [ 260/2138] eta: 2:07:03 lr: 1.5488430272499814e-05 loss: 0.0202 (0.0224) time: 4.0279 data: 0.0033 max mem: 19788 +Epoch: [29] [ 270/2138] eta: 2:06:21 lr: 1.5482436426785253e-05 loss: 0.0215 (0.0225) time: 4.0289 data: 0.0034 max mem: 19788 +Epoch: [29] [ 280/2138] eta: 2:05:39 lr: 1.5476442323232057e-05 loss: 0.0232 (0.0225) time: 4.0333 data: 0.0032 max mem: 19788 +Epoch: [29] [ 290/2138] eta: 2:04:57 lr: 1.547044796171816e-05 loss: 0.0232 (0.0226) time: 4.0389 data: 0.0032 max mem: 19788 +Epoch: [29] [ 300/2138] eta: 2:04:15 lr: 1.54644533421214e-05 loss: 0.0226 (0.0226) time: 4.0376 data: 0.0033 max mem: 19788 +Epoch: [29] [ 310/2138] eta: 2:03:34 lr: 1.545845846431949e-05 loss: 0.0209 (0.0226) time: 4.0339 data: 0.0034 max mem: 19788 +Epoch: [29] [ 320/2138] eta: 2:02:52 lr: 1.5452463328190044e-05 loss: 0.0219 (0.0226) time: 4.0354 data: 0.0033 max mem: 19788 +Epoch: [29] [ 330/2138] eta: 2:02:10 lr: 1.5446467933610555e-05 loss: 0.0225 (0.0227) time: 4.0352 data: 0.0033 max mem: 19788 +Epoch: [29] [ 340/2138] eta: 2:01:29 lr: 1.5440472280458422e-05 loss: 0.0225 (0.0227) time: 4.0365 data: 0.0033 max mem: 19788 +Epoch: [29] [ 350/2138] eta: 2:00:48 lr: 1.5434476368610917e-05 loss: 0.0218 (0.0227) time: 4.0456 data: 0.0032 max mem: 19788 +Epoch: [29] [ 360/2138] eta: 2:00:07 lr: 1.5428480197945195e-05 loss: 0.0226 (0.0228) time: 4.0470 data: 0.0031 max mem: 19788 +Epoch: [29] [ 370/2138] eta: 1:59:26 lr: 1.542248376833832e-05 loss: 0.0228 (0.0229) time: 4.0422 data: 0.0033 max mem: 19788 +Epoch: [29] [ 380/2138] eta: 1:58:45 lr: 1.541648707966723e-05 loss: 0.0227 (0.0229) time: 4.0412 data: 0.0036 max mem: 19788 +Epoch: [29] [ 390/2138] eta: 1:58:03 lr: 1.5410490131808762e-05 loss: 0.0212 (0.0229) time: 4.0354 data: 0.0035 max mem: 19788 +Epoch: [29] [ 400/2138] eta: 1:57:22 lr: 1.540449292463963e-05 loss: 0.0235 (0.0231) time: 4.0356 data: 0.0033 max mem: 19788 +Epoch: [29] [ 410/2138] eta: 1:56:41 lr: 1.5398495458036442e-05 loss: 0.0255 (0.0232) time: 4.0420 data: 0.0032 max mem: 19788 +Epoch: [29] [ 420/2138] eta: 1:56:01 lr: 1.5392497731875688e-05 loss: 0.0238 (0.0231) time: 4.0467 data: 0.0036 max mem: 19788 +Epoch: [29] [ 430/2138] eta: 1:55:20 lr: 1.538649974603376e-05 loss: 0.0226 (0.0232) time: 4.0442 data: 0.0037 max mem: 19788 +Epoch: [29] [ 440/2138] eta: 1:54:39 lr: 1.5380501500386918e-05 loss: 0.0252 (0.0233) time: 4.0400 data: 0.0034 max mem: 19788 +Epoch: [29] [ 450/2138] eta: 1:53:57 lr: 1.537450299481133e-05 loss: 0.0254 (0.0233) time: 4.0360 data: 0.0034 max mem: 19788 +Epoch: [29] [ 460/2138] eta: 1:53:17 lr: 1.5368504229183027e-05 loss: 0.0230 (0.0233) time: 4.0423 data: 0.0034 max mem: 19788 +Epoch: [29] [ 470/2138] eta: 1:52:36 lr: 1.5362505203377955e-05 loss: 0.0241 (0.0233) time: 4.0436 data: 0.0031 max mem: 19788 +Epoch: [29] [ 480/2138] eta: 1:51:55 lr: 1.5356505917271923e-05 loss: 0.0237 (0.0234) time: 4.0415 data: 0.0032 max mem: 19788 +Epoch: [29] [ 490/2138] eta: 1:51:14 lr: 1.5350506370740644e-05 loss: 0.0210 (0.0234) time: 4.0407 data: 0.0036 max mem: 19788 +Epoch: [29] [ 500/2138] eta: 1:50:34 lr: 1.53445065636597e-05 loss: 0.0210 (0.0235) time: 4.0400 data: 0.0036 max mem: 19788 +Epoch: [29] [ 510/2138] eta: 1:49:53 lr: 1.533850649590458e-05 loss: 0.0231 (0.0235) time: 4.0471 data: 0.0032 max mem: 19788 +Epoch: [29] [ 520/2138] eta: 1:49:13 lr: 1.533250616735064e-05 loss: 0.0214 (0.0236) time: 4.0509 data: 0.0033 max mem: 19788 +Epoch: [29] [ 530/2138] eta: 1:48:32 lr: 1.5326505577873138e-05 loss: 0.0207 (0.0236) time: 4.0479 data: 0.0034 max mem: 19788 +Epoch: [29] [ 540/2138] eta: 1:47:51 lr: 1.5320504727347206e-05 loss: 0.0207 (0.0235) time: 4.0456 data: 0.0034 max mem: 19788 +Epoch: [29] [ 550/2138] eta: 1:47:11 lr: 1.5314503615647875e-05 loss: 0.0224 (0.0236) time: 4.0450 data: 0.0033 max mem: 19788 +Epoch: [29] [ 560/2138] eta: 1:46:30 lr: 1.530850224265004e-05 loss: 0.0227 (0.0235) time: 4.0425 data: 0.0033 max mem: 19788 +Epoch: [29] [ 570/2138] eta: 1:45:49 lr: 1.5302500608228516e-05 loss: 0.0196 (0.0235) time: 4.0403 data: 0.0033 max mem: 19788 +Epoch: [29] [ 580/2138] eta: 1:45:08 lr: 1.529649871225796e-05 loss: 0.0218 (0.0236) time: 4.0394 data: 0.0031 max mem: 19788 +Epoch: [29] [ 590/2138] eta: 1:44:27 lr: 1.5290496554612953e-05 loss: 0.0215 (0.0235) time: 4.0376 data: 0.0030 max mem: 19788 +Epoch: [29] [ 600/2138] eta: 1:43:46 lr: 1.5284494135167935e-05 loss: 0.0203 (0.0235) time: 4.0313 data: 0.0031 max mem: 19788 +Epoch: [29] [ 610/2138] eta: 1:43:06 lr: 1.5278491453797253e-05 loss: 0.0208 (0.0235) time: 4.0356 data: 0.0031 max mem: 19788 +Epoch: [29] [ 620/2138] eta: 1:42:25 lr: 1.5272488510375112e-05 loss: 0.0242 (0.0235) time: 4.0479 data: 0.0031 max mem: 19788 +Epoch: [29] [ 630/2138] eta: 1:41:45 lr: 1.526648530477563e-05 loss: 0.0197 (0.0235) time: 4.0553 data: 0.0031 max mem: 19788 +Epoch: [29] [ 640/2138] eta: 1:41:05 lr: 1.5260481836872786e-05 loss: 0.0217 (0.0235) time: 4.0522 data: 0.0032 max mem: 19788 +Epoch: [29] [ 650/2138] eta: 1:40:24 lr: 1.5254478106540462e-05 loss: 0.0222 (0.0235) time: 4.0400 data: 0.0032 max mem: 19788 +Epoch: [29] [ 660/2138] eta: 1:39:43 lr: 1.5248474113652411e-05 loss: 0.0206 (0.0234) time: 4.0377 data: 0.0033 max mem: 19788 +Epoch: [29] [ 670/2138] eta: 1:39:04 lr: 1.524246985808227e-05 loss: 0.0229 (0.0234) time: 4.0788 data: 0.0033 max mem: 19788 +Epoch: [29] [ 680/2138] eta: 1:38:23 lr: 1.5236465339703573e-05 loss: 0.0241 (0.0235) time: 4.0777 data: 0.0033 max mem: 19788 +Epoch: [29] [ 690/2138] eta: 1:37:43 lr: 1.523046055838972e-05 loss: 0.0217 (0.0234) time: 4.0447 data: 0.0033 max mem: 19788 +Epoch: [29] [ 700/2138] eta: 1:37:02 lr: 1.5224455514014014e-05 loss: 0.0216 (0.0234) time: 4.0438 data: 0.0034 max mem: 19788 +Epoch: [29] [ 710/2138] eta: 1:36:22 lr: 1.5218450206449619e-05 loss: 0.0220 (0.0234) time: 4.0443 data: 0.0035 max mem: 19788 +Epoch: [29] [ 720/2138] eta: 1:35:41 lr: 1.5212444635569606e-05 loss: 0.0217 (0.0234) time: 4.0413 data: 0.0036 max mem: 19788 +Epoch: [29] [ 730/2138] eta: 1:35:00 lr: 1.5206438801246906e-05 loss: 0.0213 (0.0235) time: 4.0337 data: 0.0037 max mem: 19788 +Epoch: [29] [ 740/2138] eta: 1:34:19 lr: 1.5200432703354355e-05 loss: 0.0196 (0.0235) time: 4.0358 data: 0.0036 max mem: 19788 +Epoch: [29] [ 750/2138] eta: 1:33:39 lr: 1.5194426341764653e-05 loss: 0.0205 (0.0234) time: 4.0385 data: 0.0033 max mem: 19788 +Epoch: [29] [ 760/2138] eta: 1:32:58 lr: 1.5188419716350399e-05 loss: 0.0237 (0.0235) time: 4.0409 data: 0.0032 max mem: 19788 +Epoch: [29] [ 770/2138] eta: 1:32:18 lr: 1.5182412826984052e-05 loss: 0.0248 (0.0235) time: 4.0423 data: 0.0033 max mem: 19788 +Epoch: [29] [ 780/2138] eta: 1:31:37 lr: 1.5176405673537983e-05 loss: 0.0254 (0.0235) time: 4.0462 data: 0.0034 max mem: 19788 +Epoch: [29] [ 790/2138] eta: 1:30:57 lr: 1.5170398255884416e-05 loss: 0.0219 (0.0235) time: 4.0518 data: 0.0034 max mem: 19788 +Epoch: [29] [ 800/2138] eta: 1:30:16 lr: 1.5164390573895482e-05 loss: 0.0190 (0.0235) time: 4.0521 data: 0.0034 max mem: 19788 +Epoch: [29] [ 810/2138] eta: 1:29:36 lr: 1.5158382627443169e-05 loss: 0.0204 (0.0234) time: 4.0484 data: 0.0033 max mem: 19788 +Epoch: [29] [ 820/2138] eta: 1:28:55 lr: 1.515237441639937e-05 loss: 0.0240 (0.0235) time: 4.0403 data: 0.0031 max mem: 19788 +Epoch: [29] [ 830/2138] eta: 1:28:14 lr: 1.5146365940635843e-05 loss: 0.0188 (0.0234) time: 4.0344 data: 0.0031 max mem: 19788 +Epoch: [29] [ 840/2138] eta: 1:27:34 lr: 1.5140357200024241e-05 loss: 0.0176 (0.0234) time: 4.0391 data: 0.0032 max mem: 19788 +Epoch: [29] [ 850/2138] eta: 1:26:53 lr: 1.5134348194436082e-05 loss: 0.0178 (0.0234) time: 4.0444 data: 0.0032 max mem: 19788 +Epoch: [29] [ 860/2138] eta: 1:26:13 lr: 1.512833892374278e-05 loss: 0.0237 (0.0234) time: 4.0452 data: 0.0034 max mem: 19788 +Epoch: [29] [ 870/2138] eta: 1:25:32 lr: 1.5122329387815614e-05 loss: 0.0249 (0.0234) time: 4.0456 data: 0.0032 max mem: 19788 +Epoch: [29] [ 880/2138] eta: 1:24:52 lr: 1.5116319586525767e-05 loss: 0.0209 (0.0234) time: 4.0446 data: 0.0033 max mem: 19788 +Epoch: [29] [ 890/2138] eta: 1:24:11 lr: 1.5110309519744276e-05 loss: 0.0209 (0.0234) time: 4.0499 data: 0.0034 max mem: 19788 +Epoch: [29] [ 900/2138] eta: 1:23:31 lr: 1.5104299187342078e-05 loss: 0.0265 (0.0234) time: 4.0527 data: 0.0033 max mem: 19788 +Epoch: [29] [ 910/2138] eta: 1:22:50 lr: 1.5098288589189977e-05 loss: 0.0245 (0.0234) time: 4.0445 data: 0.0036 max mem: 19788 +Epoch: [29] [ 920/2138] eta: 1:22:10 lr: 1.5092277725158669e-05 loss: 0.0209 (0.0234) time: 4.0383 data: 0.0040 max mem: 19788 +Epoch: [29] [ 930/2138] eta: 1:21:29 lr: 1.5086266595118717e-05 loss: 0.0200 (0.0234) time: 4.0383 data: 0.0039 max mem: 19788 +Epoch: [29] [ 940/2138] eta: 1:20:49 lr: 1.5080255198940579e-05 loss: 0.0235 (0.0234) time: 4.0382 data: 0.0036 max mem: 19788 +Epoch: [29] [ 950/2138] eta: 1:20:08 lr: 1.5074243536494582e-05 loss: 0.0248 (0.0234) time: 4.0461 data: 0.0033 max mem: 19788 +Epoch: [29] [ 960/2138] eta: 1:19:28 lr: 1.5068231607650924e-05 loss: 0.0224 (0.0234) time: 4.0484 data: 0.0032 max mem: 19788 +Epoch: [29] [ 970/2138] eta: 1:18:47 lr: 1.5062219412279704e-05 loss: 0.0223 (0.0234) time: 4.0409 data: 0.0032 max mem: 19788 +Epoch: [29] [ 980/2138] eta: 1:18:06 lr: 1.505620695025088e-05 loss: 0.0201 (0.0234) time: 4.0405 data: 0.0033 max mem: 19788 +Epoch: [29] [ 990/2138] eta: 1:17:26 lr: 1.5050194221434305e-05 loss: 0.0218 (0.0234) time: 4.0383 data: 0.0034 max mem: 19788 +Epoch: [29] [1000/2138] eta: 1:16:45 lr: 1.5044181225699693e-05 loss: 0.0243 (0.0234) time: 4.0368 data: 0.0033 max mem: 19788 +Epoch: [29] [1010/2138] eta: 1:16:05 lr: 1.5038167962916664e-05 loss: 0.0217 (0.0234) time: 4.0345 data: 0.0032 max mem: 19788 +Epoch: [29] [1020/2138] eta: 1:15:24 lr: 1.5032154432954676e-05 loss: 0.0201 (0.0234) time: 4.0397 data: 0.0030 max mem: 19788 +Epoch: [29] [1030/2138] eta: 1:14:44 lr: 1.5026140635683105e-05 loss: 0.0201 (0.0234) time: 4.0422 data: 0.0031 max mem: 19788 +Epoch: [29] [1040/2138] eta: 1:14:03 lr: 1.5020126570971178e-05 loss: 0.0222 (0.0234) time: 4.0438 data: 0.0033 max mem: 19788 +Epoch: [29] [1050/2138] eta: 1:13:23 lr: 1.5014112238688018e-05 loss: 0.0222 (0.0234) time: 4.0521 data: 0.0033 max mem: 19788 +Epoch: [29] [1060/2138] eta: 1:12:42 lr: 1.5008097638702608e-05 loss: 0.0205 (0.0234) time: 4.0532 data: 0.0032 max mem: 19788 +Epoch: [29] [1070/2138] eta: 1:12:02 lr: 1.5002082770883827e-05 loss: 0.0200 (0.0234) time: 4.0527 data: 0.0034 max mem: 19788 +Epoch: [29] [1080/2138] eta: 1:11:21 lr: 1.4996067635100413e-05 loss: 0.0199 (0.0234) time: 4.0507 data: 0.0037 max mem: 19788 +Epoch: [29] [1090/2138] eta: 1:10:41 lr: 1.4990052231221002e-05 loss: 0.0211 (0.0234) time: 4.0446 data: 0.0036 max mem: 19788 +Epoch: [29] [1100/2138] eta: 1:10:00 lr: 1.4984036559114081e-05 loss: 0.0254 (0.0234) time: 4.0428 data: 0.0036 max mem: 19788 +Epoch: [29] [1110/2138] eta: 1:09:20 lr: 1.4978020618648043e-05 loss: 0.0247 (0.0234) time: 4.0492 data: 0.0036 max mem: 19788 +Epoch: [29] [1120/2138] eta: 1:08:40 lr: 1.4972004409691127e-05 loss: 0.0241 (0.0234) time: 4.0539 data: 0.0033 max mem: 19788 +Epoch: [29] [1130/2138] eta: 1:07:59 lr: 1.4965987932111477e-05 loss: 0.0241 (0.0234) time: 4.0502 data: 0.0033 max mem: 19788 +Epoch: [29] [1140/2138] eta: 1:07:19 lr: 1.4959971185777093e-05 loss: 0.0229 (0.0234) time: 4.0422 data: 0.0031 max mem: 19788 +Epoch: [29] [1150/2138] eta: 1:06:38 lr: 1.4953954170555868e-05 loss: 0.0198 (0.0234) time: 4.0363 data: 0.0033 max mem: 19788 +Epoch: [29] [1160/2138] eta: 1:05:57 lr: 1.4947936886315547e-05 loss: 0.0198 (0.0234) time: 4.0321 data: 0.0035 max mem: 19788 +Epoch: [29] [1170/2138] eta: 1:05:17 lr: 1.4941919332923781e-05 loss: 0.0218 (0.0234) time: 4.0364 data: 0.0034 max mem: 19788 +Epoch: [29] [1180/2138] eta: 1:04:36 lr: 1.4935901510248065e-05 loss: 0.0243 (0.0234) time: 4.0441 data: 0.0035 max mem: 19788 +Epoch: [29] [1190/2138] eta: 1:03:56 lr: 1.4929883418155801e-05 loss: 0.0240 (0.0234) time: 4.0421 data: 0.0033 max mem: 19788 +Epoch: [29] [1200/2138] eta: 1:03:15 lr: 1.4923865056514239e-05 loss: 0.0234 (0.0234) time: 4.0417 data: 0.0032 max mem: 19788 +Epoch: [29] [1210/2138] eta: 1:02:35 lr: 1.4917846425190523e-05 loss: 0.0228 (0.0234) time: 4.0411 data: 0.0033 max mem: 19788 +Epoch: [29] [1220/2138] eta: 1:01:54 lr: 1.491182752405166e-05 loss: 0.0221 (0.0234) time: 4.0383 data: 0.0034 max mem: 19788 +Epoch: [29] [1230/2138] eta: 1:01:14 lr: 1.4905808352964542e-05 loss: 0.0206 (0.0234) time: 4.0275 data: 0.0033 max mem: 19788 +Epoch: [29] [1240/2138] eta: 1:00:33 lr: 1.489978891179592e-05 loss: 0.0197 (0.0234) time: 4.0264 data: 0.0030 max mem: 19788 +Epoch: [29] [1250/2138] eta: 0:59:53 lr: 1.4893769200412442e-05 loss: 0.0227 (0.0234) time: 4.0416 data: 0.0030 max mem: 19788 +Epoch: [29] [1260/2138] eta: 0:59:12 lr: 1.488774921868061e-05 loss: 0.0199 (0.0233) time: 4.0484 data: 0.0032 max mem: 19788 +Epoch: [29] [1270/2138] eta: 0:58:32 lr: 1.4881728966466807e-05 loss: 0.0189 (0.0233) time: 4.0494 data: 0.0032 max mem: 19788 +Epoch: [29] [1280/2138] eta: 0:57:51 lr: 1.4875708443637295e-05 loss: 0.0192 (0.0233) time: 4.0527 data: 0.0031 max mem: 19788 +Epoch: [29] [1290/2138] eta: 0:57:11 lr: 1.4869687650058197e-05 loss: 0.0199 (0.0233) time: 4.0555 data: 0.0032 max mem: 19788 +Epoch: [29] [1300/2138] eta: 0:56:31 lr: 1.4863666585595532e-05 loss: 0.0199 (0.0233) time: 4.0530 data: 0.0033 max mem: 19788 +Epoch: [29] [1310/2138] eta: 0:55:50 lr: 1.485764525011516e-05 loss: 0.0210 (0.0233) time: 4.0487 data: 0.0032 max mem: 19788 +Epoch: [29] [1320/2138] eta: 0:55:10 lr: 1.4851623643482851e-05 loss: 0.0222 (0.0233) time: 4.0479 data: 0.0033 max mem: 19788 +Epoch: [29] [1330/2138] eta: 0:54:30 lr: 1.4845601765564212e-05 loss: 0.0218 (0.0233) time: 4.0861 data: 0.0034 max mem: 19788 +Epoch: [29] [1340/2138] eta: 0:53:49 lr: 1.4839579616224755e-05 loss: 0.0216 (0.0233) time: 4.0845 data: 0.0033 max mem: 19788 +Epoch: [29] [1350/2138] eta: 0:53:09 lr: 1.4833557195329837e-05 loss: 0.0244 (0.0233) time: 4.0415 data: 0.0032 max mem: 19788 +Epoch: [29] [1360/2138] eta: 0:52:28 lr: 1.4827534502744711e-05 loss: 0.0266 (0.0233) time: 4.0399 data: 0.0033 max mem: 19788 +Epoch: [29] [1370/2138] eta: 0:51:48 lr: 1.4821511538334482e-05 loss: 0.0241 (0.0233) time: 4.0382 data: 0.0033 max mem: 19788 +Epoch: [29] [1380/2138] eta: 0:51:07 lr: 1.4815488301964145e-05 loss: 0.0241 (0.0233) time: 4.0390 data: 0.0034 max mem: 19788 +Epoch: [29] [1390/2138] eta: 0:50:27 lr: 1.4809464793498548e-05 loss: 0.0234 (0.0233) time: 4.0437 data: 0.0035 max mem: 19788 +Epoch: [29] [1400/2138] eta: 0:49:46 lr: 1.4803441012802432e-05 loss: 0.0224 (0.0233) time: 4.0341 data: 0.0034 max mem: 19788 +Epoch: [29] [1410/2138] eta: 0:49:14 lr: 1.4797416959740393e-05 loss: 0.0224 (0.0233) time: 4.8287 data: 0.0033 max mem: 19788 +Epoch: [29] [1420/2138] eta: 0:48:33 lr: 1.4791392634176907e-05 loss: 0.0210 (0.0233) time: 4.8309 data: 0.0032 max mem: 19788 +Epoch: [29] [1430/2138] eta: 0:47:52 lr: 1.4785368035976313e-05 loss: 0.0230 (0.0233) time: 4.0369 data: 0.0032 max mem: 19788 +Epoch: [29] [1440/2138] eta: 0:47:12 lr: 1.4779343165002835e-05 loss: 0.0215 (0.0233) time: 4.0513 data: 0.0030 max mem: 19788 +Epoch: [29] [1450/2138] eta: 0:46:31 lr: 1.4773318021120547e-05 loss: 0.0256 (0.0233) time: 4.0567 data: 0.0030 max mem: 19788 +Epoch: [29] [1460/2138] eta: 0:45:51 lr: 1.4767292604193422e-05 loss: 0.0256 (0.0233) time: 4.0595 data: 0.0030 max mem: 19788 +Epoch: [29] [1470/2138] eta: 0:45:10 lr: 1.476126691408527e-05 loss: 0.0218 (0.0233) time: 4.0546 data: 0.0033 max mem: 19788 +Epoch: [29] [1480/2138] eta: 0:44:29 lr: 1.4755240950659802e-05 loss: 0.0232 (0.0233) time: 4.0391 data: 0.0034 max mem: 19788 +Epoch: [29] [1490/2138] eta: 0:43:49 lr: 1.4749214713780576e-05 loss: 0.0240 (0.0233) time: 4.0336 data: 0.0033 max mem: 19788 +Epoch: [29] [1500/2138] eta: 0:43:08 lr: 1.4743188203311037e-05 loss: 0.0223 (0.0233) time: 4.0365 data: 0.0036 max mem: 19788 +Epoch: [29] [1510/2138] eta: 0:42:27 lr: 1.4737161419114488e-05 loss: 0.0226 (0.0234) time: 4.0318 data: 0.0035 max mem: 19788 +Epoch: [29] [1520/2138] eta: 0:41:47 lr: 1.4731134361054108e-05 loss: 0.0239 (0.0234) time: 4.0375 data: 0.0032 max mem: 19788 +Epoch: [29] [1530/2138] eta: 0:41:06 lr: 1.472510702899294e-05 loss: 0.0198 (0.0233) time: 4.0451 data: 0.0032 max mem: 19788 +Epoch: [29] [1540/2138] eta: 0:40:25 lr: 1.4719079422793907e-05 loss: 0.0194 (0.0233) time: 4.0361 data: 0.0033 max mem: 19788 +Epoch: [29] [1550/2138] eta: 0:39:45 lr: 1.4713051542319784e-05 loss: 0.0197 (0.0233) time: 4.0359 data: 0.0034 max mem: 19788 +Epoch: [29] [1560/2138] eta: 0:39:04 lr: 1.4707023387433234e-05 loss: 0.0219 (0.0233) time: 4.0393 data: 0.0033 max mem: 19788 +Epoch: [29] [1570/2138] eta: 0:38:23 lr: 1.4700994957996773e-05 loss: 0.0215 (0.0233) time: 4.0414 data: 0.0032 max mem: 19788 +Epoch: [29] [1580/2138] eta: 0:37:43 lr: 1.4694966253872785e-05 loss: 0.0205 (0.0233) time: 4.0414 data: 0.0032 max mem: 19788 +Epoch: [29] [1590/2138] eta: 0:37:02 lr: 1.4688937274923544e-05 loss: 0.0230 (0.0233) time: 4.0393 data: 0.0032 max mem: 19788 +Epoch: [29] [1600/2138] eta: 0:36:22 lr: 1.4682908021011164e-05 loss: 0.0240 (0.0233) time: 4.0423 data: 0.0032 max mem: 19788 +Epoch: [29] [1610/2138] eta: 0:35:41 lr: 1.4676878491997646e-05 loss: 0.0227 (0.0233) time: 4.0366 data: 0.0033 max mem: 19788 +Epoch: [29] [1620/2138] eta: 0:35:00 lr: 1.4670848687744846e-05 loss: 0.0207 (0.0233) time: 4.0347 data: 0.0033 max mem: 19788 +Epoch: [29] [1630/2138] eta: 0:34:20 lr: 1.4664818608114506e-05 loss: 0.0228 (0.0233) time: 4.0396 data: 0.0031 max mem: 19788 +Epoch: [29] [1640/2138] eta: 0:33:39 lr: 1.4658788252968209e-05 loss: 0.0209 (0.0233) time: 4.0435 data: 0.0032 max mem: 19788 +Epoch: [29] [1650/2138] eta: 0:32:59 lr: 1.4652757622167428e-05 loss: 0.0199 (0.0233) time: 4.0392 data: 0.0035 max mem: 19788 +Epoch: [29] [1660/2138] eta: 0:32:18 lr: 1.4646726715573492e-05 loss: 0.0187 (0.0233) time: 4.0332 data: 0.0034 max mem: 19788 +Epoch: [29] [1670/2138] eta: 0:31:37 lr: 1.4640695533047602e-05 loss: 0.0186 (0.0233) time: 4.0348 data: 0.0032 max mem: 19788 +Epoch: [29] [1680/2138] eta: 0:30:57 lr: 1.4634664074450815e-05 loss: 0.0210 (0.0233) time: 4.0649 data: 0.0032 max mem: 19788 +Epoch: [29] [1690/2138] eta: 0:30:16 lr: 1.462863233964407e-05 loss: 0.0222 (0.0233) time: 4.0676 data: 0.0035 max mem: 19788 +Epoch: [29] [1700/2138] eta: 0:29:36 lr: 1.4622600328488159e-05 loss: 0.0212 (0.0232) time: 4.0422 data: 0.0035 max mem: 19788 +Epoch: [29] [1710/2138] eta: 0:28:55 lr: 1.4616568040843753e-05 loss: 0.0212 (0.0232) time: 4.0365 data: 0.0033 max mem: 19788 +Epoch: [29] [1720/2138] eta: 0:28:15 lr: 1.4610535476571366e-05 loss: 0.0219 (0.0232) time: 4.0301 data: 0.0032 max mem: 19788 +Epoch: [29] [1730/2138] eta: 0:27:34 lr: 1.4604502635531412e-05 loss: 0.0231 (0.0232) time: 4.0284 data: 0.0031 max mem: 19788 +Epoch: [29] [1740/2138] eta: 0:26:53 lr: 1.4598469517584132e-05 loss: 0.0221 (0.0232) time: 4.0238 data: 0.0032 max mem: 19788 +Epoch: [29] [1750/2138] eta: 0:26:13 lr: 1.4592436122589667e-05 loss: 0.0219 (0.0233) time: 4.0236 data: 0.0033 max mem: 19788 +Epoch: [29] [1760/2138] eta: 0:25:32 lr: 1.4586402450407996e-05 loss: 0.0220 (0.0233) time: 4.0255 data: 0.0033 max mem: 19788 +Epoch: [29] [1770/2138] eta: 0:24:51 lr: 1.4580368500898984e-05 loss: 0.0218 (0.0232) time: 4.0297 data: 0.0034 max mem: 19788 +Epoch: [29] [1780/2138] eta: 0:24:11 lr: 1.4574334273922339e-05 loss: 0.0218 (0.0232) time: 4.0328 data: 0.0033 max mem: 19788 +Epoch: [29] [1790/2138] eta: 0:23:30 lr: 1.4568299769337659e-05 loss: 0.0222 (0.0233) time: 4.0486 data: 0.0032 max mem: 19788 +Epoch: [29] [1800/2138] eta: 0:22:50 lr: 1.4562264987004379e-05 loss: 0.0206 (0.0232) time: 4.0590 data: 0.0032 max mem: 19788 +Epoch: [29] [1810/2138] eta: 0:22:09 lr: 1.4556229926781825e-05 loss: 0.0206 (0.0232) time: 4.0504 data: 0.0033 max mem: 19788 +Epoch: [29] [1820/2138] eta: 0:21:29 lr: 1.4550194588529165e-05 loss: 0.0219 (0.0232) time: 4.0480 data: 0.0034 max mem: 19788 +Epoch: [29] [1830/2138] eta: 0:20:48 lr: 1.4544158972105443e-05 loss: 0.0226 (0.0232) time: 4.0473 data: 0.0034 max mem: 19788 +Epoch: [29] [1840/2138] eta: 0:20:08 lr: 1.4538123077369557e-05 loss: 0.0243 (0.0233) time: 4.0440 data: 0.0032 max mem: 19788 +Epoch: [29] [1850/2138] eta: 0:19:27 lr: 1.4532086904180284e-05 loss: 0.0251 (0.0233) time: 4.0452 data: 0.0033 max mem: 19788 +Epoch: [29] [1860/2138] eta: 0:18:46 lr: 1.4526050452396245e-05 loss: 0.0237 (0.0233) time: 4.0427 data: 0.0034 max mem: 19788 +Epoch: [29] [1870/2138] eta: 0:18:06 lr: 1.452001372187594e-05 loss: 0.0228 (0.0233) time: 4.0404 data: 0.0033 max mem: 19788 +Epoch: [29] [1880/2138] eta: 0:17:25 lr: 1.4513976712477725e-05 loss: 0.0222 (0.0233) time: 4.0365 data: 0.0034 max mem: 19788 +Epoch: [29] [1890/2138] eta: 0:16:45 lr: 1.4507939424059808e-05 loss: 0.0202 (0.0233) time: 4.0328 data: 0.0032 max mem: 19788 +Epoch: [29] [1900/2138] eta: 0:16:04 lr: 1.4501901856480282e-05 loss: 0.0190 (0.0233) time: 4.0291 data: 0.0032 max mem: 19788 +Epoch: [29] [1910/2138] eta: 0:15:24 lr: 1.4495864009597083e-05 loss: 0.0208 (0.0233) time: 4.0252 data: 0.0033 max mem: 19788 +Epoch: [29] [1920/2138] eta: 0:14:43 lr: 1.4489825883268019e-05 loss: 0.0208 (0.0233) time: 4.0261 data: 0.0032 max mem: 19788 +Epoch: [29] [1930/2138] eta: 0:14:03 lr: 1.4483787477350752e-05 loss: 0.0224 (0.0233) time: 4.0219 data: 0.0033 max mem: 19788 +Epoch: [29] [1940/2138] eta: 0:13:22 lr: 1.4477748791702819e-05 loss: 0.0231 (0.0233) time: 4.0268 data: 0.0034 max mem: 19788 +Epoch: [29] [1950/2138] eta: 0:12:41 lr: 1.4471709826181595e-05 loss: 0.0222 (0.0232) time: 4.0366 data: 0.0032 max mem: 19788 +Epoch: [29] [1960/2138] eta: 0:12:01 lr: 1.446567058064435e-05 loss: 0.0219 (0.0232) time: 4.0402 data: 0.0033 max mem: 19788 +Epoch: [29] [1970/2138] eta: 0:11:20 lr: 1.4459631054948175e-05 loss: 0.0216 (0.0232) time: 4.0401 data: 0.0035 max mem: 19788 +Epoch: [29] [1980/2138] eta: 0:10:40 lr: 1.445359124895006e-05 loss: 0.0203 (0.0232) time: 4.0302 data: 0.0034 max mem: 19788 +Epoch: [29] [1990/2138] eta: 0:09:59 lr: 1.4447551162506823e-05 loss: 0.0196 (0.0232) time: 4.0236 data: 0.0034 max mem: 19788 +Epoch: [29] [2000/2138] eta: 0:09:19 lr: 1.4441510795475171e-05 loss: 0.0221 (0.0232) time: 4.0342 data: 0.0033 max mem: 19788 +Epoch: [29] [2010/2138] eta: 0:08:38 lr: 1.4435470147711644e-05 loss: 0.0231 (0.0232) time: 4.0340 data: 0.0033 max mem: 19788 +Epoch: [29] [2020/2138] eta: 0:07:58 lr: 1.4429429219072665e-05 loss: 0.0217 (0.0232) time: 4.0194 data: 0.0034 max mem: 19788 +Epoch: [29] [2030/2138] eta: 0:07:17 lr: 1.4423388009414499e-05 loss: 0.0215 (0.0232) time: 4.0194 data: 0.0033 max mem: 19788 +Epoch: [29] [2040/2138] eta: 0:06:37 lr: 1.4417346518593285e-05 loss: 0.0229 (0.0232) time: 4.0262 data: 0.0032 max mem: 19788 +Epoch: [29] [2050/2138] eta: 0:05:56 lr: 1.441130474646501e-05 loss: 0.0229 (0.0232) time: 4.0227 data: 0.0032 max mem: 19788 +Epoch: [29] [2060/2138] eta: 0:05:16 lr: 1.4405262692885533e-05 loss: 0.0228 (0.0233) time: 4.0257 data: 0.0032 max mem: 19788 +Epoch: [29] [2070/2138] eta: 0:04:35 lr: 1.4399220357710549e-05 loss: 0.0203 (0.0233) time: 4.0334 data: 0.0031 max mem: 19788 +Epoch: [29] [2080/2138] eta: 0:03:54 lr: 1.4393177740795644e-05 loss: 0.0226 (0.0233) time: 4.0383 data: 0.0032 max mem: 19788 +Epoch: [29] [2090/2138] eta: 0:03:14 lr: 1.4387134841996228e-05 loss: 0.0223 (0.0233) time: 4.0651 data: 0.0032 max mem: 19788 +Epoch: [29] [2100/2138] eta: 0:02:33 lr: 1.4381091661167604e-05 loss: 0.0208 (0.0232) time: 4.0572 data: 0.0032 max mem: 19788 +Epoch: [29] [2110/2138] eta: 0:01:53 lr: 1.4375048198164895e-05 loss: 0.0238 (0.0233) time: 4.0312 data: 0.0031 max mem: 19788 +Epoch: [29] [2120/2138] eta: 0:01:12 lr: 1.4369004452843121e-05 loss: 0.0269 (0.0233) time: 4.0390 data: 0.0032 max mem: 19788 +Epoch: [29] [2130/2138] eta: 0:00:32 lr: 1.4362960425057128e-05 loss: 0.0246 (0.0233) time: 4.0175 data: 0.0032 max mem: 19788 +Epoch: [29] Total time: 2:24:21 +Test: [ 0/21770] eta: 19:36:00 time: 3.2412 data: 2.9732 max mem: 19788 +Test: [ 100/21770] eta: 0:36:34 time: 0.0676 data: 0.0020 max mem: 19788 +Test: [ 200/21770] eta: 0:30:02 time: 0.0646 data: 0.0018 max mem: 19788 +Test: [ 300/21770] eta: 0:27:57 time: 0.0705 data: 0.0022 max mem: 19788 +Test: [ 400/21770] eta: 0:27:22 time: 0.0762 data: 0.0024 max mem: 19788 +Test: [ 500/21770] eta: 0:26:50 time: 0.0628 data: 0.0017 max mem: 19788 +Test: [ 600/21770] eta: 0:26:08 time: 0.0637 data: 0.0021 max mem: 19788 +Test: [ 700/21770] eta: 0:25:47 time: 0.0610 data: 0.0020 max mem: 19788 +Test: [ 800/21770] eta: 0:25:26 time: 0.0741 data: 0.0023 max mem: 19788 +Test: [ 900/21770] eta: 0:25:23 time: 0.0765 data: 0.0023 max mem: 19788 +Test: [ 1000/21770] eta: 0:25:09 time: 0.0661 data: 0.0019 max mem: 19788 +Test: [ 1100/21770] eta: 0:24:49 time: 0.0691 data: 0.0022 max mem: 19788 +Test: [ 1200/21770] eta: 0:24:31 time: 0.0632 data: 0.0018 max mem: 19788 +Test: [ 1300/21770] eta: 0:24:26 time: 0.0731 data: 0.0021 max mem: 19788 +Test: [ 1400/21770] eta: 0:24:14 time: 0.0823 data: 0.0021 max mem: 19788 +Test: [ 1500/21770] eta: 0:23:59 time: 0.0637 data: 0.0019 max mem: 19788 +Test: [ 1600/21770] eta: 0:23:51 time: 0.0730 data: 0.0021 max mem: 19788 +Test: [ 1700/21770] eta: 0:23:44 time: 0.0636 data: 0.0021 max mem: 19788 +Test: [ 1800/21770] eta: 0:23:39 time: 0.0703 data: 0.0024 max mem: 19788 +Test: [ 1900/21770] eta: 0:23:32 time: 0.0747 data: 0.0022 max mem: 19788 +Test: [ 2000/21770] eta: 0:23:26 time: 0.0773 data: 0.0024 max mem: 19788 +Test: [ 2100/21770] eta: 0:23:18 time: 0.0792 data: 0.0023 max mem: 19788 +Test: [ 2200/21770] eta: 0:23:07 time: 0.0648 data: 0.0020 max mem: 19788 +Test: [ 2300/21770] eta: 0:22:59 time: 0.0697 data: 0.0021 max mem: 19788 +Test: [ 2400/21770] eta: 0:22:57 time: 0.0707 data: 0.0020 max mem: 19788 +Test: [ 2500/21770] eta: 0:22:48 time: 0.0696 data: 0.0023 max mem: 19788 +Test: [ 2600/21770] eta: 0:22:44 time: 0.0827 data: 0.0025 max mem: 19788 +Test: [ 2700/21770] eta: 0:22:34 time: 0.0749 data: 0.0024 max mem: 19788 +Test: [ 2800/21770] eta: 0:22:29 time: 0.0817 data: 0.0024 max mem: 19788 +Test: [ 2900/21770] eta: 0:22:19 time: 0.0654 data: 0.0019 max mem: 19788 +Test: [ 3000/21770] eta: 0:22:10 time: 0.0662 data: 0.0021 max mem: 19788 +Test: [ 3100/21770] eta: 0:22:01 time: 0.0823 data: 0.0027 max mem: 19788 +Test: [ 3200/21770] eta: 0:21:53 time: 0.0673 data: 0.0020 max mem: 19788 +Test: [ 3300/21770] eta: 0:21:44 time: 0.0676 data: 0.0019 max mem: 19788 +Test: [ 3400/21770] eta: 0:21:40 time: 0.0746 data: 0.0026 max mem: 19788 +Test: [ 3500/21770] eta: 0:21:30 time: 0.0703 data: 0.0022 max mem: 19788 +Test: [ 3600/21770] eta: 0:21:22 time: 0.0639 data: 0.0019 max mem: 19788 +Test: [ 3700/21770] eta: 0:21:15 time: 0.0844 data: 0.0024 max mem: 19788 +Test: [ 3800/21770] eta: 0:21:12 time: 0.0827 data: 0.0020 max mem: 19788 +Test: [ 3900/21770] eta: 0:21:06 time: 0.0637 data: 0.0019 max mem: 19788 +Test: [ 4000/21770] eta: 0:20:59 time: 0.0811 data: 0.0026 max mem: 19788 +Test: [ 4100/21770] eta: 0:20:53 time: 0.0786 data: 0.0025 max mem: 19788 +Test: [ 4200/21770] eta: 0:20:45 time: 0.0675 data: 0.0020 max mem: 19788 +Test: [ 4300/21770] eta: 0:20:37 time: 0.0636 data: 0.0020 max mem: 19788 +Test: [ 4400/21770] eta: 0:20:30 time: 0.0752 data: 0.0025 max mem: 19788 +Test: [ 4500/21770] eta: 0:20:23 time: 0.0681 data: 0.0021 max mem: 19788 +Test: [ 4600/21770] eta: 0:20:15 time: 0.0721 data: 0.0021 max mem: 19788 +Test: [ 4700/21770] eta: 0:20:09 time: 0.0687 data: 0.0021 max mem: 19788 +Test: [ 4800/21770] eta: 0:20:01 time: 0.0616 data: 0.0018 max mem: 19788 +Test: [ 4900/21770] eta: 0:19:52 time: 0.0699 data: 0.0018 max mem: 19788 +Test: [ 5000/21770] eta: 0:19:46 time: 0.0742 data: 0.0021 max mem: 19788 +Test: [ 5100/21770] eta: 0:19:39 time: 0.0723 data: 0.0024 max mem: 19788 +Test: [ 5200/21770] eta: 0:19:31 time: 0.0665 data: 0.0020 max mem: 19788 +Test: [ 5300/21770] eta: 0:19:25 time: 0.0784 data: 0.0024 max mem: 19788 +Test: [ 5400/21770] eta: 0:19:20 time: 0.0681 data: 0.0020 max mem: 19788 +Test: [ 5500/21770] eta: 0:19:11 time: 0.0652 data: 0.0019 max mem: 19788 +Test: [ 5600/21770] eta: 0:19:05 time: 0.0718 data: 0.0022 max mem: 19788 +Test: [ 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time: 0.0767 data: 0.0021 max mem: 19788 +Test: [ 7100/21770] eta: 0:17:20 time: 0.0643 data: 0.0021 max mem: 19788 +Test: [ 7200/21770] eta: 0:17:12 time: 0.0648 data: 0.0019 max mem: 19788 +Test: [ 7300/21770] eta: 0:17:04 time: 0.0680 data: 0.0019 max mem: 19788 +Test: [ 7400/21770] eta: 0:16:56 time: 0.0684 data: 0.0022 max mem: 19788 +Test: [ 7500/21770] eta: 0:16:49 time: 0.0721 data: 0.0020 max mem: 19788 +Test: [ 7600/21770] eta: 0:16:42 time: 0.0790 data: 0.0023 max mem: 19788 +Test: [ 7700/21770] eta: 0:16:35 time: 0.0798 data: 0.0025 max mem: 19788 +Test: [ 7800/21770] eta: 0:16:29 time: 0.0692 data: 0.0020 max mem: 19788 +Test: [ 7900/21770] eta: 0:16:22 time: 0.0779 data: 0.0024 max mem: 19788 +Test: [ 8000/21770] eta: 0:16:15 time: 0.0727 data: 0.0023 max mem: 19788 +Test: [ 8100/21770] eta: 0:16:08 time: 0.0648 data: 0.0019 max mem: 19788 +Test: [ 8200/21770] eta: 0:16:01 time: 0.0660 data: 0.0024 max mem: 19788 +Test: [ 8300/21770] eta: 0:15:54 time: 0.0654 data: 0.0020 max mem: 19788 +Test: [ 8400/21770] eta: 0:15:47 time: 0.0761 data: 0.0025 max mem: 19788 +Test: [ 8500/21770] eta: 0:15:41 time: 0.0689 data: 0.0021 max mem: 19788 +Test: [ 8600/21770] eta: 0:15:35 time: 0.0747 data: 0.0022 max mem: 19788 +Test: [ 8700/21770] eta: 0:15:27 time: 0.0643 data: 0.0019 max mem: 19788 +Test: [ 8800/21770] eta: 0:15:20 time: 0.0792 data: 0.0022 max mem: 19788 +Test: [ 8900/21770] eta: 0:15:12 time: 0.0636 data: 0.0020 max mem: 19788 +Test: [ 9000/21770] eta: 0:15:04 time: 0.0660 data: 0.0021 max mem: 19788 +Test: [ 9100/21770] eta: 0:14:57 time: 0.0820 data: 0.0025 max mem: 19788 +Test: [ 9200/21770] eta: 0:14:50 time: 0.0662 data: 0.0020 max mem: 19788 +Test: [ 9300/21770] eta: 0:14:42 time: 0.0648 data: 0.0020 max mem: 19788 +Test: [ 9400/21770] eta: 0:14:35 time: 0.0625 data: 0.0021 max mem: 19788 +Test: [ 9500/21770] eta: 0:14:28 time: 0.0656 data: 0.0020 max mem: 19788 +Test: [ 9600/21770] eta: 0:14:21 time: 0.0804 data: 0.0025 max mem: 19788 +Test: [ 9700/21770] eta: 0:14:14 time: 0.0851 data: 0.0020 max mem: 19788 +Test: [ 9800/21770] eta: 0:14:08 time: 0.0711 data: 0.0021 max mem: 19788 +Test: [ 9900/21770] eta: 0:14:01 time: 0.0695 data: 0.0021 max mem: 19788 +Test: [10000/21770] eta: 0:13:53 time: 0.0651 data: 0.0021 max mem: 19788 +Test: [10100/21770] eta: 0:13:47 time: 0.0825 data: 0.0028 max mem: 19788 +Test: [10200/21770] eta: 0:13:39 time: 0.0772 data: 0.0021 max mem: 19788 +Test: [10300/21770] eta: 0:13:33 time: 0.0832 data: 0.0023 max mem: 19788 +Test: [10400/21770] eta: 0:13:26 time: 0.0717 data: 0.0023 max mem: 19788 +Test: [10500/21770] eta: 0:13:18 time: 0.0668 data: 0.0022 max mem: 19788 +Test: [10600/21770] eta: 0:13:12 time: 0.0811 data: 0.0021 max mem: 19788 +Test: [10700/21770] eta: 0:13:06 time: 0.0850 data: 0.0028 max mem: 19788 +Test: [10800/21770] eta: 0:12:59 time: 0.0803 data: 0.0025 max mem: 19788 +Test: [10900/21770] eta: 0:12:51 time: 0.0684 data: 0.0019 max mem: 19788 +Test: [11000/21770] eta: 0:12:44 time: 0.0647 data: 0.0021 max mem: 19788 +Test: [11100/21770] eta: 0:12:37 time: 0.0654 data: 0.0019 max mem: 19788 +Test: [11200/21770] eta: 0:12:30 time: 0.0716 data: 0.0022 max mem: 19788 +Test: [11300/21770] eta: 0:12:23 time: 0.0677 data: 0.0019 max mem: 19788 +Test: [11400/21770] eta: 0:12:15 time: 0.0682 data: 0.0020 max mem: 19788 +Test: [11500/21770] eta: 0:12:08 time: 0.0650 data: 0.0018 max mem: 19788 +Test: [11600/21770] eta: 0:12:01 time: 0.0856 data: 0.0028 max mem: 19788 +Test: [11700/21770] eta: 0:11:54 time: 0.0666 data: 0.0020 max mem: 19788 +Test: [11800/21770] eta: 0:11:47 time: 0.0657 data: 0.0019 max mem: 19788 +Test: [11900/21770] eta: 0:11:40 time: 0.0728 data: 0.0021 max mem: 19788 +Test: [12000/21770] eta: 0:11:34 time: 0.0823 data: 0.0025 max mem: 19788 +Test: [12100/21770] eta: 0:11:27 time: 0.0688 data: 0.0019 max mem: 19788 +Test: [12200/21770] eta: 0:11:20 time: 0.0692 data: 0.0019 max mem: 19788 +Test: [12300/21770] eta: 0:11:13 time: 0.0651 data: 0.0020 max mem: 19788 +Test: [12400/21770] eta: 0:11:05 time: 0.0695 data: 0.0022 max mem: 19788 +Test: [12500/21770] eta: 0:10:58 time: 0.0738 data: 0.0023 max mem: 19788 +Test: [12600/21770] eta: 0:10:51 time: 0.0746 data: 0.0022 max mem: 19788 +Test: [12700/21770] eta: 0:10:44 time: 0.0667 data: 0.0019 max mem: 19788 +Test: [12800/21770] eta: 0:10:37 time: 0.0792 data: 0.0024 max mem: 19788 +Test: [12900/21770] eta: 0:10:30 time: 0.0698 data: 0.0019 max mem: 19788 +Test: [13000/21770] eta: 0:10:23 time: 0.0710 data: 0.0020 max mem: 19788 +Test: [13100/21770] eta: 0:10:15 time: 0.0643 data: 0.0019 max mem: 19788 +Test: [13200/21770] eta: 0:10:08 time: 0.0639 data: 0.0020 max mem: 19788 +Test: [13300/21770] eta: 0:10:01 time: 0.0653 data: 0.0020 max mem: 19788 +Test: [13400/21770] eta: 0:09:54 time: 0.0688 data: 0.0021 max mem: 19788 +Test: [13500/21770] eta: 0:09:46 time: 0.0697 data: 0.0021 max mem: 19788 +Test: [13600/21770] eta: 0:09:40 time: 0.0711 data: 0.0021 max mem: 19788 +Test: [13700/21770] eta: 0:09:33 time: 0.0802 data: 0.0021 max mem: 19788 +Test: [13800/21770] eta: 0:09:26 time: 0.0636 data: 0.0023 max mem: 19788 +Test: [13900/21770] eta: 0:09:19 time: 0.0716 data: 0.0020 max mem: 19788 +Test: [14000/21770] eta: 0:09:12 time: 0.0748 data: 0.0021 max mem: 19788 +Test: [14100/21770] eta: 0:09:06 time: 0.0827 data: 0.0024 max mem: 19788 +Test: [14200/21770] eta: 0:08:59 time: 0.0728 data: 0.0021 max mem: 19788 +Test: [14300/21770] eta: 0:08:52 time: 0.0650 data: 0.0019 max mem: 19788 +Test: [14400/21770] eta: 0:08:44 time: 0.0732 data: 0.0022 max mem: 19788 +Test: [14500/21770] eta: 0:08:37 time: 0.0673 data: 0.0020 max mem: 19788 +Test: [14600/21770] eta: 0:08:30 time: 0.0635 data: 0.0018 max mem: 19788 +Test: [14700/21770] eta: 0:08:23 time: 0.0797 data: 0.0024 max mem: 19788 +Test: [14800/21770] eta: 0:08:16 time: 0.0667 data: 0.0021 max mem: 19788 +Test: [14900/21770] eta: 0:08:09 time: 0.0655 data: 0.0022 max mem: 19788 +Test: [15000/21770] eta: 0:08:02 time: 0.0856 data: 0.0028 max mem: 19788 +Test: [15100/21770] eta: 0:07:55 time: 0.0664 data: 0.0019 max mem: 19788 +Test: [15200/21770] eta: 0:07:48 time: 0.0665 data: 0.0022 max mem: 19788 +Test: [15300/21770] eta: 0:07:41 time: 0.0660 data: 0.0019 max mem: 19788 +Test: [15400/21770] eta: 0:07:33 time: 0.0716 data: 0.0021 max mem: 19788 +Test: [15500/21770] eta: 0:07:26 time: 0.0850 data: 0.0020 max mem: 19788 +Test: [15600/21770] eta: 0:07:19 time: 0.0667 data: 0.0020 max mem: 19788 +Test: [15700/21770] eta: 0:07:12 time: 0.0736 data: 0.0021 max mem: 19788 +Test: [15800/21770] eta: 0:07:05 time: 0.0654 data: 0.0020 max mem: 19788 +Test: [15900/21770] eta: 0:06:58 time: 0.0662 data: 0.0019 max mem: 19788 +Test: [16000/21770] eta: 0:06:50 time: 0.0649 data: 0.0020 max mem: 19788 +Test: [16100/21770] eta: 0:06:44 time: 0.0858 data: 0.0027 max mem: 19788 +Test: [16200/21770] eta: 0:06:36 time: 0.0632 data: 0.0019 max mem: 19788 +Test: [16300/21770] eta: 0:06:29 time: 0.0661 data: 0.0020 max mem: 19788 +Test: [16400/21770] eta: 0:06:22 time: 0.0645 data: 0.0020 max mem: 19788 +Test: [16500/21770] eta: 0:06:15 time: 0.0648 data: 0.0020 max mem: 19788 +Test: [16600/21770] eta: 0:06:08 time: 0.0788 data: 0.0023 max mem: 19788 +Test: [16700/21770] eta: 0:06:01 time: 0.0719 data: 0.0022 max mem: 19788 +Test: [16800/21770] eta: 0:05:54 time: 0.0675 data: 0.0019 max mem: 19788 +Test: [16900/21770] eta: 0:05:47 time: 0.0736 data: 0.0022 max mem: 19788 +Test: [17000/21770] eta: 0:05:40 time: 0.0809 data: 0.0025 max mem: 19788 +Test: [17100/21770] eta: 0:05:32 time: 0.0726 data: 0.0022 max mem: 19788 +Test: [17200/21770] eta: 0:05:25 time: 0.0668 data: 0.0018 max mem: 19788 +Test: [17300/21770] eta: 0:05:18 time: 0.0654 data: 0.0022 max mem: 19788 +Test: [17400/21770] eta: 0:05:11 time: 0.0828 data: 0.0020 max mem: 19788 +Test: [17500/21770] eta: 0:05:04 time: 0.0636 data: 0.0020 max mem: 19788 +Test: [17600/21770] eta: 0:04:57 time: 0.0692 data: 0.0019 max mem: 19788 +Test: [17700/21770] eta: 0:04:49 time: 0.0657 data: 0.0019 max mem: 19788 +Test: [17800/21770] eta: 0:04:42 time: 0.0768 data: 0.0024 max mem: 19788 +Test: [17900/21770] eta: 0:04:35 time: 0.0796 data: 0.0023 max mem: 19788 +Test: [18000/21770] eta: 0:04:28 time: 0.0690 data: 0.0022 max mem: 19788 +Test: [18100/21770] eta: 0:04:21 time: 0.0723 data: 0.0021 max mem: 19788 +Test: [18200/21770] eta: 0:04:14 time: 0.0682 data: 0.0020 max mem: 19788 +Test: [18300/21770] eta: 0:04:07 time: 0.0740 data: 0.0022 max mem: 19788 +Test: [18400/21770] eta: 0:04:00 time: 0.0843 data: 0.0026 max mem: 19788 +Test: [18500/21770] eta: 0:03:53 time: 0.0690 data: 0.0020 max mem: 19788 +Test: [18600/21770] eta: 0:03:46 time: 0.0843 data: 0.0026 max mem: 19788 +Test: [18700/21770] eta: 0:03:39 time: 0.0789 data: 0.0025 max mem: 19788 +Test: [18800/21770] eta: 0:03:31 time: 0.0648 data: 0.0021 max mem: 19788 +Test: [18900/21770] eta: 0:03:24 time: 0.0786 data: 0.0024 max mem: 19788 +Test: [19000/21770] eta: 0:03:17 time: 0.0822 data: 0.0026 max mem: 19788 +Test: [19100/21770] eta: 0:03:10 time: 0.0702 data: 0.0020 max mem: 19788 +Test: [19200/21770] eta: 0:03:03 time: 0.0639 data: 0.0021 max mem: 19788 +Test: [19300/21770] eta: 0:02:56 time: 0.0679 data: 0.0019 max mem: 19788 +Test: [19400/21770] eta: 0:02:48 time: 0.0614 data: 0.0018 max mem: 19788 +Test: [19500/21770] eta: 0:02:41 time: 0.0645 data: 0.0018 max mem: 19788 +Test: [19600/21770] eta: 0:02:34 time: 0.0773 data: 0.0025 max mem: 19788 +Test: [19700/21770] eta: 0:02:27 time: 0.0634 data: 0.0020 max mem: 19788 +Test: [19800/21770] eta: 0:02:20 time: 0.0694 data: 0.0022 max mem: 19788 +Test: [19900/21770] eta: 0:02:13 time: 0.0656 data: 0.0022 max mem: 19788 +Test: [20000/21770] eta: 0:02:06 time: 0.0665 data: 0.0022 max mem: 19788 +Test: [20100/21770] eta: 0:01:58 time: 0.0632 data: 0.0019 max mem: 19788 +Test: [20200/21770] eta: 0:01:51 time: 0.0723 data: 0.0021 max mem: 19788 +Test: [20300/21770] eta: 0:01:44 time: 0.0638 data: 0.0020 max mem: 19788 +Test: [20400/21770] eta: 0:01:37 time: 0.0685 data: 0.0024 max mem: 19788 +Test: [20500/21770] eta: 0:01:30 time: 0.0679 data: 0.0019 max mem: 19788 +Test: [20600/21770] eta: 0:01:23 time: 0.0701 data: 0.0020 max mem: 19788 +Test: [20700/21770] eta: 0:01:16 time: 0.0696 data: 0.0021 max mem: 19788 +Test: [20800/21770] eta: 0:01:09 time: 0.0760 data: 0.0024 max mem: 19788 +Test: [20900/21770] eta: 0:01:01 time: 0.0858 data: 0.0027 max mem: 19788 +Test: [21000/21770] eta: 0:00:54 time: 0.0650 data: 0.0022 max mem: 19788 +Test: [21100/21770] eta: 0:00:47 time: 0.0640 data: 0.0020 max mem: 19788 +Test: [21200/21770] eta: 0:00:40 time: 0.0686 data: 0.0022 max mem: 19788 +Test: [21300/21770] eta: 0:00:33 time: 0.0694 data: 0.0020 max mem: 19788 +Test: [21400/21770] eta: 0:00:26 time: 0.0675 data: 0.0021 max mem: 19788 +Test: [21500/21770] eta: 0:00:19 time: 0.0718 data: 0.0020 max mem: 19788 +Test: [21600/21770] eta: 0:00:12 time: 0.0676 data: 0.0018 max mem: 19788 +Test: [21700/21770] eta: 0:00:04 time: 0.0684 data: 0.0019 max mem: 19788 +Test: Total time: 0:25:50 +Final results: +Mean IoU is 63.35 + + precision@0.5 = 70.07 + precision@0.6 = 64.85 + precision@0.7 = 58.28 + precision@0.8 = 48.00 + precision@0.9 = 23.75 + overall IoU = 64.00 + mean IoU = 63.35 + +Mean accuracy for one-to-zero sample is 85.39 + +Average object IoU 0.6335457557830751 +Overall IoU 63.99967575073242 +Epoch: [30] [ 0/2138] eta: 14:08:02 lr: 1.4358124999356481e-05 loss: 0.0206 (0.0206) time: 23.7990 data: 1.9265 max mem: 19788 +Epoch: [30] [ 10/2138] eta: 3:27:47 lr: 1.4352080462768693e-05 loss: 0.0180 (0.0186) time: 5.8588 data: 0.1783 max mem: 19788 +Epoch: [30] [ 20/2138] eta: 3:05:36 lr: 1.4346035643309543e-05 loss: 0.0180 (0.0187) time: 4.3311 data: 0.0027 max mem: 19788 +Epoch: [30] [ 30/2138] eta: 21:43:56 lr: 1.4339990540833336e-05 loss: 0.0187 (0.0194) time: 54.3043 data: 49.8837 max mem: 19788 +Epoch: [30] [ 40/2138] eta: 16:55:40 lr: 1.4333945155194256e-05 loss: 0.0234 (0.0204) time: 54.0249 data: 49.8841 max mem: 19788 +Epoch: [30] [ 50/2138] eta: 14:00:03 lr: 1.4327899486246322e-05 loss: 0.0224 (0.0209) time: 4.0291 data: 0.0026 max mem: 19788 +Epoch: [30] [ 60/2138] eta: 12:01:52 lr: 1.4321853533843429e-05 loss: 0.0198 (0.0207) time: 4.0269 data: 0.0029 max mem: 19788 +Epoch: [30] [ 70/2138] eta: 10:36:47 lr: 1.4315807297839312e-05 loss: 0.0171 (0.0202) time: 4.0318 data: 0.0032 max mem: 19788 +Epoch: [30] [ 80/2138] eta: 9:32:31 lr: 1.4309760778087574e-05 loss: 0.0182 (0.0205) time: 4.0277 data: 0.0033 max mem: 19788 +Epoch: [30] [ 90/2138] eta: 8:42:15 lr: 1.4303713974441663e-05 loss: 0.0202 (0.0205) time: 4.0307 data: 0.0035 max mem: 19788 +Epoch: [30] [ 100/2138] eta: 8:01:49 lr: 1.4297666886754893e-05 loss: 0.0201 (0.0208) time: 4.0337 data: 0.0035 max mem: 19788 +Epoch: [30] [ 110/2138] eta: 7:28:32 lr: 1.4291619514880423e-05 loss: 0.0209 (0.0209) time: 4.0341 data: 0.0036 max mem: 19788 +Epoch: [30] [ 120/2138] eta: 7:00:40 lr: 1.4285571858671278e-05 loss: 0.0229 (0.0212) time: 4.0385 data: 0.0033 max mem: 19788 +Epoch: [30] [ 130/2138] eta: 6:36:56 lr: 1.4279523917980326e-05 loss: 0.0244 (0.0214) time: 4.0348 data: 0.0031 max mem: 19788 +Epoch: [30] [ 140/2138] eta: 6:16:26 lr: 1.4273475692660298e-05 loss: 0.0240 (0.0217) time: 4.0250 data: 0.0033 max mem: 19788 +Epoch: [30] [ 150/2138] eta: 5:58:37 lr: 1.4267427182563775e-05 loss: 0.0210 (0.0217) time: 4.0325 data: 0.0034 max mem: 19788 +Epoch: [30] [ 160/2138] eta: 5:42:55 lr: 1.4261378387543201e-05 loss: 0.0230 (0.0219) time: 4.0380 data: 0.0033 max mem: 19788 +Epoch: [30] [ 170/2138] eta: 5:28:58 lr: 1.4255329307450857e-05 loss: 0.0240 (0.0220) time: 4.0363 data: 0.0032 max mem: 19788 +Epoch: [30] [ 180/2138] eta: 5:16:29 lr: 1.4249279942138896e-05 loss: 0.0246 (0.0222) time: 4.0364 data: 0.0033 max mem: 19788 +Epoch: [30] [ 190/2138] eta: 5:05:13 lr: 1.4243230291459305e-05 loss: 0.0206 (0.0221) time: 4.0261 data: 0.0031 max mem: 19788 +Epoch: [30] [ 200/2138] eta: 4:55:01 lr: 1.4237180355263955e-05 loss: 0.0165 (0.0218) time: 4.0241 data: 0.0031 max mem: 19788 +Epoch: [30] [ 210/2138] eta: 4:45:44 lr: 1.4231130133404527e-05 loss: 0.0238 (0.0221) time: 4.0305 data: 0.0034 max mem: 19788 +Epoch: [30] [ 220/2138] eta: 4:37:12 lr: 1.42250796257326e-05 loss: 0.0238 (0.0219) time: 4.0262 data: 0.0033 max mem: 19788 +Epoch: [30] [ 230/2138] eta: 4:29:22 lr: 1.421902883209957e-05 loss: 0.0214 (0.0221) time: 4.0246 data: 0.0032 max mem: 19788 +Epoch: [30] [ 240/2138] eta: 4:22:07 lr: 1.4212977752356698e-05 loss: 0.0215 (0.0220) time: 4.0265 data: 0.0034 max mem: 19788 +Epoch: [30] [ 250/2138] eta: 4:15:23 lr: 1.4206926386355113e-05 loss: 0.0193 (0.0219) time: 4.0226 data: 0.0032 max mem: 19788 +Epoch: [30] [ 260/2138] eta: 4:09:09 lr: 1.4200874733945769e-05 loss: 0.0193 (0.0219) time: 4.0329 data: 0.0032 max mem: 19788 +Epoch: [30] [ 270/2138] eta: 4:03:19 lr: 1.4194822794979493e-05 loss: 0.0204 (0.0220) time: 4.0450 data: 0.0034 max mem: 19788 +Epoch: [30] [ 280/2138] eta: 3:57:50 lr: 1.4188770569306948e-05 loss: 0.0221 (0.0220) time: 4.0302 data: 0.0034 max mem: 19788 +Epoch: [30] [ 290/2138] eta: 3:52:41 lr: 1.4182718056778663e-05 loss: 0.0240 (0.0222) time: 4.0214 data: 0.0034 max mem: 19788 +Epoch: [30] [ 300/2138] eta: 3:47:50 lr: 1.4176665257245e-05 loss: 0.0214 (0.0221) time: 4.0283 data: 0.0037 max mem: 19788 +Epoch: [30] [ 310/2138] eta: 3:43:15 lr: 1.41706121705562e-05 loss: 0.0195 (0.0220) time: 4.0215 data: 0.0036 max mem: 19788 +Epoch: [30] [ 320/2138] eta: 3:38:54 lr: 1.4164558796562316e-05 loss: 0.0210 (0.0221) time: 4.0205 data: 0.0034 max mem: 19788 +Epoch: [30] [ 330/2138] eta: 3:34:47 lr: 1.4158505135113292e-05 loss: 0.0213 (0.0222) time: 4.0243 data: 0.0033 max mem: 19788 +Epoch: [30] [ 340/2138] eta: 3:30:52 lr: 1.4152451186058893e-05 loss: 0.0210 (0.0221) time: 4.0178 data: 0.0033 max mem: 19788 +Epoch: [30] [ 350/2138] eta: 3:27:08 lr: 1.414639694924875e-05 loss: 0.0222 (0.0222) time: 4.0226 data: 0.0034 max mem: 19788 +Epoch: [30] [ 360/2138] eta: 3:23:35 lr: 1.4140342424532326e-05 loss: 0.0225 (0.0222) time: 4.0284 data: 0.0033 max mem: 19788 +Epoch: [30] [ 370/2138] eta: 3:20:10 lr: 1.4134287611758964e-05 loss: 0.0218 (0.0223) time: 4.0177 data: 0.0031 max mem: 19788 +Epoch: [30] [ 380/2138] eta: 3:16:54 lr: 1.412823251077782e-05 loss: 0.0219 (0.0223) time: 4.0184 data: 0.0032 max mem: 19788 +Epoch: [30] [ 390/2138] eta: 3:13:47 lr: 1.4122177121437932e-05 loss: 0.0221 (0.0223) time: 4.0277 data: 0.0034 max mem: 19788 +Epoch: [30] [ 400/2138] eta: 3:10:46 lr: 1.4116121443588162e-05 loss: 0.0228 (0.0223) time: 4.0199 data: 0.0033 max mem: 19788 +Epoch: [30] [ 410/2138] eta: 3:07:52 lr: 1.4110065477077238e-05 loss: 0.0239 (0.0224) time: 4.0172 data: 0.0033 max mem: 19788 +Epoch: [30] [ 420/2138] eta: 3:05:05 lr: 1.4104009221753722e-05 loss: 0.0240 (0.0224) time: 4.0235 data: 0.0034 max mem: 19788 +Epoch: [30] [ 430/2138] eta: 3:02:23 lr: 1.409795267746604e-05 loss: 0.0202 (0.0224) time: 4.0202 data: 0.0033 max mem: 19788 +Epoch: [30] [ 440/2138] eta: 2:59:48 lr: 1.4091895844062448e-05 loss: 0.0224 (0.0225) time: 4.0239 data: 0.0033 max mem: 19788 +Epoch: [30] [ 450/2138] eta: 2:57:17 lr: 1.408583872139107e-05 loss: 0.0218 (0.0226) time: 4.0319 data: 0.0037 max mem: 19788 +Epoch: [30] [ 460/2138] eta: 2:54:51 lr: 1.4079781309299857e-05 loss: 0.0218 (0.0226) time: 4.0238 data: 0.0037 max mem: 19788 +Epoch: [30] [ 470/2138] eta: 2:52:30 lr: 1.407372360763663e-05 loss: 0.0222 (0.0226) time: 4.0198 data: 0.0036 max mem: 19788 +Epoch: [30] [ 480/2138] eta: 2:50:12 lr: 1.406766561624903e-05 loss: 0.0222 (0.0226) time: 4.0256 data: 0.0036 max mem: 19788 +Epoch: [30] [ 490/2138] eta: 2:47:59 lr: 1.406160733498457e-05 loss: 0.0216 (0.0226) time: 4.0238 data: 0.0035 max mem: 19788 +Epoch: [30] [ 500/2138] eta: 2:45:49 lr: 1.4055548763690593e-05 loss: 0.0213 (0.0226) time: 4.0219 data: 0.0032 max mem: 19788 +Epoch: [30] [ 510/2138] eta: 2:43:44 lr: 1.4049489902214303e-05 loss: 0.0218 (0.0226) time: 4.0268 data: 0.0033 max mem: 19788 +Epoch: [30] [ 520/2138] eta: 2:41:41 lr: 1.4043430750402733e-05 loss: 0.0222 (0.0226) time: 4.0251 data: 0.0035 max mem: 19788 +Epoch: [30] [ 530/2138] eta: 2:39:41 lr: 1.4037371308102772e-05 loss: 0.0205 (0.0225) time: 4.0201 data: 0.0033 max mem: 19788 +Epoch: [30] [ 540/2138] eta: 2:37:44 lr: 1.4031311575161162e-05 loss: 0.0191 (0.0225) time: 4.0232 data: 0.0032 max mem: 19788 +Epoch: [30] [ 550/2138] eta: 2:35:50 lr: 1.402525155142447e-05 loss: 0.0212 (0.0225) time: 4.0251 data: 0.0034 max mem: 19788 +Epoch: [30] [ 560/2138] eta: 2:33:59 lr: 1.4019191236739132e-05 loss: 0.0212 (0.0225) time: 4.0257 data: 0.0034 max mem: 19788 +Epoch: [30] [ 570/2138] eta: 2:32:10 lr: 1.4013130630951407e-05 loss: 0.0202 (0.0225) time: 4.0247 data: 0.0034 max mem: 19788 +Epoch: [30] [ 580/2138] eta: 2:30:24 lr: 1.4007069733907422e-05 loss: 0.0204 (0.0226) time: 4.0240 data: 0.0032 max mem: 19788 +Epoch: [30] [ 590/2138] eta: 2:28:39 lr: 1.4001008545453123e-05 loss: 0.0230 (0.0226) time: 4.0226 data: 0.0032 max mem: 19788 +Epoch: [30] [ 600/2138] eta: 2:26:57 lr: 1.3994947065434324e-05 loss: 0.0212 (0.0226) time: 4.0216 data: 0.0033 max mem: 19788 +Epoch: [30] [ 610/2138] eta: 2:25:17 lr: 1.3988885293696663e-05 loss: 0.0208 (0.0227) time: 4.0266 data: 0.0032 max mem: 19788 +Epoch: [30] [ 620/2138] eta: 2:23:39 lr: 1.3982823230085643e-05 loss: 0.0228 (0.0227) time: 4.0263 data: 0.0031 max mem: 19788 +Epoch: [30] [ 630/2138] eta: 2:22:03 lr: 1.3976760874446588e-05 loss: 0.0218 (0.0226) time: 4.0215 data: 0.0031 max mem: 19788 +Epoch: [30] [ 640/2138] eta: 2:20:28 lr: 1.3970698226624688e-05 loss: 0.0213 (0.0226) time: 4.0224 data: 0.0033 max mem: 19788 +Epoch: [30] [ 650/2138] eta: 2:18:55 lr: 1.3964635286464953e-05 loss: 0.0215 (0.0226) time: 4.0230 data: 0.0032 max mem: 19788 +Epoch: [30] [ 660/2138] eta: 2:17:24 lr: 1.3958572053812258e-05 loss: 0.0238 (0.0226) time: 4.0229 data: 0.0029 max mem: 19788 +Epoch: [30] [ 670/2138] eta: 2:15:54 lr: 1.3952508528511302e-05 loss: 0.0210 (0.0226) time: 4.0302 data: 0.0030 max mem: 19788 +Epoch: [30] [ 680/2138] eta: 2:14:26 lr: 1.3946444710406648e-05 loss: 0.0219 (0.0226) time: 4.0297 data: 0.0033 max mem: 19788 +Epoch: [30] [ 690/2138] eta: 2:12:59 lr: 1.394038059934267e-05 loss: 0.0219 (0.0226) time: 4.0196 data: 0.0035 max mem: 19788 +Epoch: [30] [ 700/2138] eta: 2:11:33 lr: 1.3934316195163621e-05 loss: 0.0230 (0.0226) time: 4.0205 data: 0.0034 max mem: 19788 +Epoch: [30] [ 710/2138] eta: 2:10:09 lr: 1.3928251497713566e-05 loss: 0.0230 (0.0226) time: 4.0244 data: 0.0033 max mem: 19788 +Epoch: [30] [ 720/2138] eta: 2:08:46 lr: 1.392218650683643e-05 loss: 0.0206 (0.0226) time: 4.0256 data: 0.0031 max mem: 19788 +Epoch: [30] [ 730/2138] eta: 2:07:24 lr: 1.3916121222375964e-05 loss: 0.0210 (0.0227) time: 4.0245 data: 0.0031 max mem: 19788 +Epoch: [30] [ 740/2138] eta: 2:06:03 lr: 1.3910055644175776e-05 loss: 0.0211 (0.0226) time: 4.0268 data: 0.0033 max mem: 19788 +Epoch: [30] [ 750/2138] eta: 2:04:44 lr: 1.3903989772079301e-05 loss: 0.0211 (0.0227) time: 4.0349 data: 0.0035 max mem: 19788 +Epoch: [30] [ 760/2138] eta: 2:03:25 lr: 1.389792360592983e-05 loss: 0.0236 (0.0227) time: 4.0284 data: 0.0032 max mem: 19788 +Epoch: [30] [ 770/2138] eta: 2:02:07 lr: 1.3891857145570475e-05 loss: 0.0245 (0.0227) time: 4.0226 data: 0.0033 max mem: 19788 +Epoch: [30] [ 780/2138] eta: 2:00:51 lr: 1.3885790390844205e-05 loss: 0.0243 (0.0227) time: 4.0242 data: 0.0034 max mem: 19788 +Epoch: [30] [ 790/2138] eta: 1:59:35 lr: 1.387972334159382e-05 loss: 0.0224 (0.0227) time: 4.0222 data: 0.0031 max mem: 19788 +Epoch: [30] [ 800/2138] eta: 1:58:20 lr: 1.3873655997661964e-05 loss: 0.0197 (0.0227) time: 4.0337 data: 0.0032 max mem: 19788 +Epoch: [30] [ 810/2138] eta: 1:57:06 lr: 1.3867588358891112e-05 loss: 0.0194 (0.0227) time: 4.0364 data: 0.0032 max mem: 19788 +Epoch: [30] [ 820/2138] eta: 1:55:53 lr: 1.3861520425123594e-05 loss: 0.0194 (0.0227) time: 4.0284 data: 0.0031 max mem: 19788 +Epoch: [30] [ 830/2138] eta: 1:54:41 lr: 1.3855452196201569e-05 loss: 0.0178 (0.0227) time: 4.0305 data: 0.0033 max mem: 19788 +Epoch: [30] [ 840/2138] eta: 1:53:29 lr: 1.3849383671967022e-05 loss: 0.0179 (0.0227) time: 4.0367 data: 0.0034 max mem: 19788 +Epoch: [30] [ 850/2138] eta: 1:52:18 lr: 1.3843314852261804e-05 loss: 0.0205 (0.0226) time: 4.0382 data: 0.0034 max mem: 19788 +Epoch: [30] [ 860/2138] eta: 1:51:08 lr: 1.3837245736927582e-05 loss: 0.0232 (0.0227) time: 4.0283 data: 0.0035 max mem: 19788 +Epoch: [30] [ 870/2138] eta: 1:49:59 lr: 1.3831176325805872e-05 loss: 0.0243 (0.0227) time: 4.0284 data: 0.0035 max mem: 19788 +Epoch: [30] [ 880/2138] eta: 1:48:50 lr: 1.3825106618738024e-05 loss: 0.0222 (0.0227) time: 4.0353 data: 0.0038 max mem: 19788 +Epoch: [30] [ 890/2138] eta: 1:47:42 lr: 1.3819036615565226e-05 loss: 0.0208 (0.0227) time: 4.0259 data: 0.0038 max mem: 19788 +Epoch: [30] [ 900/2138] eta: 1:46:34 lr: 1.38129663161285e-05 loss: 0.0235 (0.0227) time: 4.0245 data: 0.0034 max mem: 19788 +Epoch: [30] [ 910/2138] eta: 1:45:27 lr: 1.3806895720268717e-05 loss: 0.0218 (0.0227) time: 4.0397 data: 0.0034 max mem: 19788 +Epoch: [30] [ 920/2138] eta: 1:44:21 lr: 1.3800824827826567e-05 loss: 0.0218 (0.0227) time: 4.0480 data: 0.0035 max mem: 19788 +Epoch: [30] [ 930/2138] eta: 1:43:16 lr: 1.379475363864259e-05 loss: 0.0213 (0.0227) time: 4.0471 data: 0.0037 max mem: 19788 +Epoch: [30] [ 940/2138] eta: 1:42:11 lr: 1.3788682152557152e-05 loss: 0.0213 (0.0228) time: 4.0554 data: 0.0037 max mem: 19788 +Epoch: [30] [ 950/2138] eta: 1:41:06 lr: 1.3782610369410474e-05 loss: 0.0222 (0.0228) time: 4.0593 data: 0.0034 max mem: 19788 +Epoch: [30] [ 960/2138] eta: 1:40:02 lr: 1.3776538289042582e-05 loss: 0.0221 (0.0228) time: 4.0420 data: 0.0032 max mem: 19788 +Epoch: [30] [ 970/2138] eta: 1:38:58 lr: 1.3770465911293368e-05 loss: 0.0201 (0.0227) time: 4.0215 data: 0.0032 max mem: 19788 +Epoch: [30] [ 980/2138] eta: 1:37:55 lr: 1.3764393236002538e-05 loss: 0.0189 (0.0227) time: 4.0184 data: 0.0034 max mem: 19788 +Epoch: [30] [ 990/2138] eta: 1:36:52 lr: 1.3758320263009647e-05 loss: 0.0211 (0.0227) time: 4.0310 data: 0.0034 max mem: 19788 +Epoch: [30] [1000/2138] eta: 1:35:50 lr: 1.3752246992154071e-05 loss: 0.0229 (0.0227) time: 4.0346 data: 0.0032 max mem: 19788 +Epoch: [30] [1010/2138] eta: 1:34:48 lr: 1.374617342327504e-05 loss: 0.0202 (0.0227) time: 4.0324 data: 0.0031 max mem: 19788 +Epoch: [30] [1020/2138] eta: 1:33:46 lr: 1.3740099556211598e-05 loss: 0.0204 (0.0227) time: 4.0271 data: 0.0033 max mem: 19788 +Epoch: [30] [1030/2138] eta: 1:32:45 lr: 1.3734025390802636e-05 loss: 0.0231 (0.0227) time: 4.0244 data: 0.0032 max mem: 19788 +Epoch: [30] [1040/2138] eta: 1:31:44 lr: 1.3727950926886864e-05 loss: 0.0200 (0.0227) time: 4.0298 data: 0.0030 max mem: 19788 +Epoch: [30] [1050/2138] eta: 1:30:44 lr: 1.3721876164302853e-05 loss: 0.0206 (0.0227) time: 4.0389 data: 0.0031 max mem: 19788 +Epoch: [30] [1060/2138] eta: 1:29:44 lr: 1.371580110288897e-05 loss: 0.0224 (0.0227) time: 4.0351 data: 0.0034 max mem: 19788 +Epoch: [30] [1070/2138] eta: 1:28:45 lr: 1.3709725742483456e-05 loss: 0.0211 (0.0227) time: 4.0285 data: 0.0034 max mem: 19788 +Epoch: [30] [1080/2138] eta: 1:27:45 lr: 1.3703650082924343e-05 loss: 0.0211 (0.0227) time: 4.0249 data: 0.0033 max mem: 19788 +Epoch: [30] [1090/2138] eta: 1:26:46 lr: 1.3697574124049537e-05 loss: 0.0217 (0.0227) time: 4.0206 data: 0.0034 max mem: 19788 +Epoch: [30] [1100/2138] eta: 1:25:48 lr: 1.3691497865696735e-05 loss: 0.0240 (0.0227) time: 4.0260 data: 0.0035 max mem: 19788 +Epoch: [30] [1110/2138] eta: 1:24:50 lr: 1.3685421307703502e-05 loss: 0.0231 (0.0227) time: 4.0385 data: 0.0034 max mem: 19788 +Epoch: [30] [1120/2138] eta: 1:23:52 lr: 1.3679344449907205e-05 loss: 0.0188 (0.0227) time: 4.0377 data: 0.0034 max mem: 19788 +Epoch: [30] [1130/2138] eta: 1:22:54 lr: 1.3673267292145073e-05 loss: 0.0225 (0.0227) time: 4.0245 data: 0.0033 max mem: 19788 +Epoch: [30] [1140/2138] eta: 1:21:57 lr: 1.3667189834254137e-05 loss: 0.0213 (0.0227) time: 4.0289 data: 0.0032 max mem: 19788 +Epoch: [30] [1150/2138] eta: 1:21:00 lr: 1.3661112076071272e-05 loss: 0.0205 (0.0227) time: 4.0270 data: 0.0033 max mem: 19788 +Epoch: [30] [1160/2138] eta: 1:20:03 lr: 1.365503401743319e-05 loss: 0.0202 (0.0227) time: 4.0202 data: 0.0033 max mem: 19788 +Epoch: [30] [1170/2138] eta: 1:19:07 lr: 1.3648955658176417e-05 loss: 0.0203 (0.0227) time: 4.0389 data: 0.0034 max mem: 19788 +Epoch: [30] [1180/2138] eta: 1:18:11 lr: 1.364287699813733e-05 loss: 0.0216 (0.0227) time: 4.0405 data: 0.0035 max mem: 19788 +Epoch: [30] [1190/2138] eta: 1:17:15 lr: 1.3636798037152113e-05 loss: 0.0217 (0.0226) time: 4.0232 data: 0.0036 max mem: 19788 +Epoch: [30] [1200/2138] eta: 1:16:19 lr: 1.36307187750568e-05 loss: 0.0205 (0.0227) time: 4.0299 data: 0.0034 max mem: 19788 +Epoch: [30] [1210/2138] eta: 1:15:24 lr: 1.3624639211687237e-05 loss: 0.0216 (0.0226) time: 4.0350 data: 0.0033 max mem: 19788 +Epoch: [30] [1220/2138] eta: 1:14:29 lr: 1.361855934687912e-05 loss: 0.0216 (0.0226) time: 4.0281 data: 0.0036 max mem: 19788 +Epoch: [30] [1230/2138] eta: 1:13:34 lr: 1.3612479180467947e-05 loss: 0.0209 (0.0226) time: 4.0311 data: 0.0034 max mem: 19788 +Epoch: [30] [1240/2138] eta: 1:12:39 lr: 1.360639871228907e-05 loss: 0.0193 (0.0226) time: 4.0310 data: 0.0031 max mem: 19788 +Epoch: [30] [1250/2138] eta: 1:11:45 lr: 1.3600317942177648e-05 loss: 0.0199 (0.0226) time: 4.0285 data: 0.0031 max mem: 19788 +Epoch: [30] [1260/2138] eta: 1:10:51 lr: 1.359423686996869e-05 loss: 0.0185 (0.0226) time: 4.0318 data: 0.0031 max mem: 19788 +Epoch: [30] [1270/2138] eta: 1:09:57 lr: 1.3588155495497013e-05 loss: 0.0184 (0.0226) time: 4.0305 data: 0.0031 max mem: 19788 +Epoch: [30] [1280/2138] eta: 1:09:03 lr: 1.3582073818597275e-05 loss: 0.0210 (0.0226) time: 4.0288 data: 0.0031 max mem: 19788 +Epoch: [30] [1290/2138] eta: 1:08:09 lr: 1.3575991839103943e-05 loss: 0.0204 (0.0226) time: 4.0299 data: 0.0035 max mem: 19788 +Epoch: [30] [1300/2138] eta: 1:07:16 lr: 1.3569909556851343e-05 loss: 0.0196 (0.0226) time: 4.0236 data: 0.0038 max mem: 19788 +Epoch: [30] [1310/2138] eta: 1:06:23 lr: 1.3563826971673591e-05 loss: 0.0208 (0.0226) time: 4.0224 data: 0.0034 max mem: 19788 +Epoch: [30] [1320/2138] eta: 1:05:30 lr: 1.355774408340466e-05 loss: 0.0212 (0.0226) time: 4.0280 data: 0.0034 max mem: 19788 +Epoch: [30] [1330/2138] eta: 1:04:37 lr: 1.3551660891878326e-05 loss: 0.0234 (0.0226) time: 4.0218 data: 0.0036 max mem: 19788 +Epoch: [30] [1340/2138] eta: 1:03:45 lr: 1.3545577396928211e-05 loss: 0.0208 (0.0226) time: 4.0193 data: 0.0034 max mem: 19788 +Epoch: [30] [1350/2138] eta: 1:02:52 lr: 1.3539493598387739e-05 loss: 0.0230 (0.0226) time: 4.0259 data: 0.0033 max mem: 19788 +Epoch: [30] [1360/2138] eta: 1:02:00 lr: 1.3533409496090188e-05 loss: 0.0258 (0.0227) time: 4.0225 data: 0.0033 max mem: 19788 +Epoch: [30] [1370/2138] eta: 1:01:08 lr: 1.352732508986863e-05 loss: 0.0227 (0.0227) time: 4.0201 data: 0.0033 max mem: 19788 +Epoch: [30] [1380/2138] eta: 1:00:16 lr: 1.3521240379555994e-05 loss: 0.0235 (0.0227) time: 4.0253 data: 0.0033 max mem: 19788 +Epoch: [30] [1390/2138] eta: 0:59:24 lr: 1.3515155364985005e-05 loss: 0.0235 (0.0227) time: 4.0249 data: 0.0032 max mem: 19788 +Epoch: [30] [1400/2138] eta: 0:58:33 lr: 1.3509070045988235e-05 loss: 0.0216 (0.0227) time: 4.0203 data: 0.0033 max mem: 19788 +Epoch: [30] [1410/2138] eta: 0:57:41 lr: 1.3502984422398057e-05 loss: 0.0198 (0.0227) time: 4.0238 data: 0.0035 max mem: 19788 +Epoch: [30] [1420/2138] eta: 0:56:50 lr: 1.3496898494046695e-05 loss: 0.0198 (0.0227) time: 4.0270 data: 0.0033 max mem: 19788 +Epoch: [30] [1430/2138] eta: 0:55:59 lr: 1.3490812260766166e-05 loss: 0.0227 (0.0227) time: 4.0202 data: 0.0033 max mem: 19788 +Epoch: [30] [1440/2138] eta: 0:55:08 lr: 1.3484725722388342e-05 loss: 0.0195 (0.0227) time: 4.0192 data: 0.0032 max mem: 19788 +Epoch: [30] [1450/2138] eta: 0:54:17 lr: 1.3478638878744892e-05 loss: 0.0246 (0.0227) time: 4.0230 data: 0.0033 max mem: 19788 +Epoch: [30] [1460/2138] eta: 0:53:26 lr: 1.3472551729667315e-05 loss: 0.0247 (0.0227) time: 4.0265 data: 0.0037 max mem: 19788 +Epoch: [30] [1470/2138] eta: 0:52:36 lr: 1.3466464274986945e-05 loss: 0.0229 (0.0227) time: 4.0252 data: 0.0035 max mem: 19788 +Epoch: [30] [1480/2138] eta: 0:51:46 lr: 1.3460376514534914e-05 loss: 0.0235 (0.0227) time: 4.0199 data: 0.0032 max mem: 19788 +Epoch: [30] [1490/2138] eta: 0:50:55 lr: 1.3454288448142208e-05 loss: 0.0235 (0.0227) time: 4.0251 data: 0.0033 max mem: 19788 +Epoch: [30] [1500/2138] eta: 0:50:05 lr: 1.3448200075639598e-05 loss: 0.0228 (0.0227) time: 4.0312 data: 0.0032 max mem: 19788 +Epoch: [30] [1510/2138] eta: 0:49:15 lr: 1.3442111396857709e-05 loss: 0.0228 (0.0227) time: 4.0184 data: 0.0031 max mem: 19788 +Epoch: [30] [1520/2138] eta: 0:48:25 lr: 1.3436022411626962e-05 loss: 0.0207 (0.0227) time: 4.0214 data: 0.0030 max mem: 19788 +Epoch: [30] [1530/2138] eta: 0:47:36 lr: 1.3429933119777616e-05 loss: 0.0195 (0.0227) time: 4.0324 data: 0.0030 max mem: 19788 +Epoch: [30] [1540/2138] eta: 0:46:46 lr: 1.3423843521139737e-05 loss: 0.0195 (0.0227) time: 4.0227 data: 0.0033 max mem: 19788 +Epoch: [30] [1550/2138] eta: 0:45:57 lr: 1.3417753615543227e-05 loss: 0.0202 (0.0227) time: 4.0249 data: 0.0036 max mem: 19788 +Epoch: [30] [1560/2138] eta: 0:45:07 lr: 1.341166340281779e-05 loss: 0.0225 (0.0227) time: 4.0312 data: 0.0035 max mem: 19788 +Epoch: [30] [1570/2138] eta: 0:44:18 lr: 1.3405572882792963e-05 loss: 0.0205 (0.0227) time: 4.0206 data: 0.0032 max mem: 19788 +Epoch: [30] [1580/2138] eta: 0:43:29 lr: 1.3399482055298094e-05 loss: 0.0205 (0.0227) time: 4.0196 data: 0.0032 max mem: 19788 +Epoch: [30] [1590/2138] eta: 0:42:40 lr: 1.3393390920162357e-05 loss: 0.0215 (0.0227) time: 4.0272 data: 0.0035 max mem: 19788 +Epoch: [30] [1600/2138] eta: 0:41:51 lr: 1.3387299477214734e-05 loss: 0.0229 (0.0227) time: 4.0239 data: 0.0034 max mem: 19788 +Epoch: [30] [1610/2138] eta: 0:41:02 lr: 1.3381207726284046e-05 loss: 0.0220 (0.0227) time: 4.0203 data: 0.0033 max mem: 19788 +Epoch: [30] [1620/2138] eta: 0:40:14 lr: 1.33751156671989e-05 loss: 0.0187 (0.0227) time: 4.0248 data: 0.0035 max mem: 19788 +Epoch: [30] [1630/2138] eta: 0:39:25 lr: 1.3369023299787759e-05 loss: 0.0230 (0.0227) time: 4.0221 data: 0.0037 max mem: 19788 +Epoch: [30] [1640/2138] eta: 0:38:36 lr: 1.3362930623878867e-05 loss: 0.0214 (0.0227) time: 4.0229 data: 0.0033 max mem: 19788 +Epoch: [30] [1650/2138] eta: 0:37:48 lr: 1.3356837639300318e-05 loss: 0.0199 (0.0226) time: 4.0278 data: 0.0030 max mem: 19788 +Epoch: [30] [1660/2138] eta: 0:37:00 lr: 1.3350744345879993e-05 loss: 0.0199 (0.0226) time: 4.0187 data: 0.0031 max mem: 19788 +Epoch: [30] [1670/2138] eta: 0:36:12 lr: 1.3344650743445613e-05 loss: 0.0195 (0.0226) time: 4.0175 data: 0.0032 max mem: 19788 +Epoch: [30] [1680/2138] eta: 0:35:24 lr: 1.33385568318247e-05 loss: 0.0210 (0.0226) time: 4.0265 data: 0.0033 max mem: 19788 +Epoch: [30] [1690/2138] eta: 0:34:36 lr: 1.3332462610844609e-05 loss: 0.0216 (0.0226) time: 4.0300 data: 0.0035 max mem: 19788 +Epoch: [30] [1700/2138] eta: 0:33:48 lr: 1.332636808033249e-05 loss: 0.0203 (0.0226) time: 4.0252 data: 0.0036 max mem: 19788 +Epoch: [30] [1710/2138] eta: 0:33:00 lr: 1.3320273240115327e-05 loss: 0.0201 (0.0226) time: 4.0220 data: 0.0035 max mem: 19788 +Epoch: [30] [1720/2138] eta: 0:32:12 lr: 1.3314178090019902e-05 loss: 0.0207 (0.0226) time: 4.0251 data: 0.0035 max mem: 19788 +Epoch: [30] [1730/2138] eta: 0:31:24 lr: 1.3308082629872832e-05 loss: 0.0228 (0.0226) time: 4.0309 data: 0.0036 max mem: 19788 +Epoch: [30] [1740/2138] eta: 0:30:37 lr: 1.3301986859500531e-05 loss: 0.0214 (0.0226) time: 4.0273 data: 0.0035 max mem: 19788 +Epoch: [30] [1750/2138] eta: 0:29:49 lr: 1.329589077872923e-05 loss: 0.0214 (0.0226) time: 4.0238 data: 0.0034 max mem: 19788 +Epoch: [30] [1760/2138] eta: 0:29:02 lr: 1.3289794387384994e-05 loss: 0.0236 (0.0226) time: 4.0259 data: 0.0032 max mem: 19788 +Epoch: [30] [1770/2138] eta: 0:28:15 lr: 1.3283697685293668e-05 loss: 0.0232 (0.0226) time: 4.0188 data: 0.0031 max mem: 19788 +Epoch: [30] [1780/2138] eta: 0:27:27 lr: 1.3277600672280943e-05 loss: 0.0206 (0.0226) time: 4.0205 data: 0.0032 max mem: 19788 +Epoch: [30] [1790/2138] eta: 0:26:40 lr: 1.3271503348172295e-05 loss: 0.0206 (0.0226) time: 4.0283 data: 0.0035 max mem: 19788 +Epoch: [30] [1800/2138] eta: 0:25:53 lr: 1.3265405712793044e-05 loss: 0.0201 (0.0226) time: 4.0226 data: 0.0032 max mem: 19788 +Epoch: [30] [1810/2138] eta: 0:25:06 lr: 1.325930776596829e-05 loss: 0.0210 (0.0227) time: 4.0260 data: 0.0031 max mem: 19788 +Epoch: [30] [1820/2138] eta: 0:24:19 lr: 1.3253209507522974e-05 loss: 0.0218 (0.0227) time: 4.0312 data: 0.0033 max mem: 19788 +Epoch: [30] [1830/2138] eta: 0:23:32 lr: 1.324711093728182e-05 loss: 0.0204 (0.0227) time: 4.0232 data: 0.0035 max mem: 19788 +Epoch: [30] [1840/2138] eta: 0:22:46 lr: 1.3241012055069397e-05 loss: 0.0221 (0.0227) time: 4.0233 data: 0.0036 max mem: 19788 +Epoch: [30] [1850/2138] eta: 0:21:59 lr: 1.3234912860710053e-05 loss: 0.0234 (0.0227) time: 4.0278 data: 0.0033 max mem: 19788 +Epoch: [30] [1860/2138] eta: 0:21:12 lr: 1.3228813354027973e-05 loss: 0.0228 (0.0227) time: 4.0164 data: 0.0032 max mem: 19788 +Epoch: [30] [1870/2138] eta: 0:20:26 lr: 1.322271353484713e-05 loss: 0.0212 (0.0227) time: 4.0324 data: 0.0031 max mem: 19788 +Epoch: [30] [1880/2138] eta: 0:19:39 lr: 1.3216613402991338e-05 loss: 0.0207 (0.0227) time: 4.0610 data: 0.0032 max mem: 19788 +Epoch: [30] [1890/2138] eta: 0:18:53 lr: 1.321051295828418e-05 loss: 0.0196 (0.0227) time: 4.0639 data: 0.0034 max mem: 19788 +Epoch: [30] [1900/2138] eta: 0:18:07 lr: 1.3204412200549094e-05 loss: 0.0179 (0.0227) time: 4.0603 data: 0.0034 max mem: 19788 +Epoch: [30] [1910/2138] eta: 0:17:20 lr: 1.3198311129609284e-05 loss: 0.0208 (0.0227) time: 4.0585 data: 0.0032 max mem: 19788 +Epoch: [30] [1920/2138] eta: 0:16:34 lr: 1.3192209745287804e-05 loss: 0.0209 (0.0227) time: 4.0585 data: 0.0031 max mem: 19788 +Epoch: [30] [1930/2138] eta: 0:15:48 lr: 1.3186108047407481e-05 loss: 0.0211 (0.0227) time: 4.0605 data: 0.0032 max mem: 19788 +Epoch: [30] [1940/2138] eta: 0:15:02 lr: 1.3180006035790981e-05 loss: 0.0214 (0.0227) time: 4.0658 data: 0.0033 max mem: 19788 +Epoch: [30] [1950/2138] eta: 0:14:16 lr: 1.3173903710260751e-05 loss: 0.0213 (0.0226) time: 4.0598 data: 0.0033 max mem: 19788 +Epoch: [30] [1960/2138] eta: 0:13:30 lr: 1.3167801070639074e-05 loss: 0.0207 (0.0226) time: 4.0642 data: 0.0033 max mem: 19788 +Epoch: [30] [1970/2138] eta: 0:12:44 lr: 1.3161698116748017e-05 loss: 0.0211 (0.0226) time: 4.0679 data: 0.0033 max mem: 19788 +Epoch: [30] [1980/2138] eta: 0:11:58 lr: 1.3155594848409469e-05 loss: 0.0178 (0.0226) time: 4.0682 data: 0.0033 max mem: 19788 +Epoch: [30] [1990/2138] eta: 0:11:12 lr: 1.3149491265445113e-05 loss: 0.0193 (0.0226) time: 4.0718 data: 0.0033 max mem: 19788 +Epoch: [30] [2000/2138] eta: 0:10:26 lr: 1.314338736767646e-05 loss: 0.0215 (0.0226) time: 4.0664 data: 0.0032 max mem: 19788 +Epoch: [30] [2010/2138] eta: 0:09:41 lr: 1.3137283154924802e-05 loss: 0.0242 (0.0226) time: 4.0630 data: 0.0031 max mem: 19788 +Epoch: [30] [2020/2138] eta: 0:08:55 lr: 1.3131178627011262e-05 loss: 0.0228 (0.0226) time: 4.0710 data: 0.0032 max mem: 19788 +Epoch: [30] [2030/2138] eta: 0:08:09 lr: 1.3125073783756742e-05 loss: 0.0214 (0.0226) time: 4.0698 data: 0.0031 max mem: 19788 +Epoch: [30] [2040/2138] eta: 0:07:24 lr: 1.3118968624981981e-05 loss: 0.0210 (0.0226) time: 4.0578 data: 0.0034 max mem: 19788 +Epoch: [30] [2050/2138] eta: 0:06:38 lr: 1.3112863150507499e-05 loss: 0.0208 (0.0226) time: 4.0609 data: 0.0034 max mem: 19788 +Epoch: [30] [2060/2138] eta: 0:05:53 lr: 1.310675736015362e-05 loss: 0.0214 (0.0226) time: 4.0626 data: 0.0032 max mem: 19788 +Epoch: [30] [2070/2138] eta: 0:05:07 lr: 1.31006512537405e-05 loss: 0.0218 (0.0226) time: 4.0454 data: 0.0033 max mem: 19788 +Epoch: [30] [2080/2138] eta: 0:04:22 lr: 1.3094544831088062e-05 loss: 0.0218 (0.0226) time: 4.0271 data: 0.0034 max mem: 19788 +Epoch: [30] [2090/2138] eta: 0:03:37 lr: 1.308843809201607e-05 loss: 0.0211 (0.0226) time: 4.0256 data: 0.0034 max mem: 19788 +Epoch: [30] [2100/2138] eta: 0:02:51 lr: 1.3082331036344056e-05 loss: 0.0194 (0.0226) time: 4.0346 data: 0.0033 max mem: 19788 +Epoch: [30] [2110/2138] eta: 0:02:06 lr: 1.3076223663891388e-05 loss: 0.0232 (0.0226) time: 4.0371 data: 0.0034 max mem: 19788 +Epoch: [30] [2120/2138] eta: 0:01:21 lr: 1.307011597447721e-05 loss: 0.0258 (0.0227) time: 4.0306 data: 0.0035 max mem: 19788 +Epoch: [30] [2130/2138] eta: 0:00:36 lr: 1.3064007967920495e-05 loss: 0.0235 (0.0227) time: 4.0146 data: 0.0032 max mem: 19788 +Epoch: [30] Total time: 2:40:43 +Test: [ 0/21770] eta: 18:16:06 time: 3.0210 data: 2.7417 max mem: 19788 +Test: [ 100/21770] eta: 0:37:10 time: 0.0678 data: 0.0021 max mem: 19788 +Test: [ 200/21770] eta: 0:31:05 time: 0.0670 data: 0.0019 max mem: 19788 +Test: [ 300/21770] eta: 0:29:15 time: 0.0816 data: 0.0026 max mem: 19788 +Test: [ 400/21770] eta: 0:28:06 time: 0.0698 data: 0.0020 max mem: 19788 +Test: [ 500/21770] eta: 0:27:08 time: 0.0624 data: 0.0019 max mem: 19788 +Test: [ 600/21770] eta: 0:26:14 time: 0.0638 data: 0.0020 max mem: 19788 +Test: [ 700/21770] eta: 0:26:03 time: 0.0846 data: 0.0026 max mem: 19788 +Test: [ 800/21770] eta: 0:26:02 time: 0.0854 data: 0.0021 max mem: 19788 +Test: [ 900/21770] eta: 0:25:55 time: 0.0695 data: 0.0022 max mem: 19788 +Test: [ 1000/21770] eta: 0:25:39 time: 0.0643 data: 0.0019 max mem: 19788 +Test: [ 1100/21770] eta: 0:25:21 time: 0.0681 data: 0.0019 max mem: 19788 +Test: [ 1200/21770] eta: 0:25:01 time: 0.0652 data: 0.0021 max mem: 19788 +Test: [ 1300/21770] eta: 0:24:56 time: 0.0847 data: 0.0021 max mem: 19788 +Test: [ 1400/21770] eta: 0:24:41 time: 0.0670 data: 0.0023 max mem: 19788 +Test: [ 1500/21770] eta: 0:24:27 time: 0.0648 data: 0.0018 max mem: 19788 +Test: [ 1600/21770] eta: 0:24:22 time: 0.0849 data: 0.0026 max mem: 19788 +Test: [ 1700/21770] eta: 0:24:11 time: 0.0738 data: 0.0021 max mem: 19788 +Test: [ 1800/21770] eta: 0:23:58 time: 0.0646 data: 0.0019 max mem: 19788 +Test: [ 1900/21770] eta: 0:23:46 time: 0.0687 data: 0.0019 max mem: 19788 +Test: [ 2000/21770] eta: 0:23:40 time: 0.0712 data: 0.0022 max mem: 19788 +Test: [ 2100/21770] eta: 0:23:36 time: 0.0740 data: 0.0021 max mem: 19788 +Test: [ 2200/21770] eta: 0:23:28 time: 0.0646 data: 0.0020 max mem: 19788 +Test: [ 2300/21770] eta: 0:23:20 time: 0.0735 data: 0.0022 max mem: 19788 +Test: [ 2400/21770] eta: 0:23:11 time: 0.0671 data: 0.0020 max mem: 19788 +Test: [ 2500/21770] eta: 0:22:59 time: 0.0631 data: 0.0021 max mem: 19788 +Test: [ 2600/21770] eta: 0:22:53 time: 0.0644 data: 0.0022 max mem: 19788 +Test: [ 2700/21770] eta: 0:22:42 time: 0.0654 data: 0.0020 max mem: 19788 +Test: [ 2800/21770] eta: 0:22:31 time: 0.0648 data: 0.0021 max mem: 19788 +Test: [ 2900/21770] eta: 0:22:22 time: 0.0666 data: 0.0020 max mem: 19788 +Test: [ 3000/21770] eta: 0:22:12 time: 0.0647 data: 0.0020 max mem: 19788 +Test: [ 3100/21770] eta: 0:22:02 time: 0.0725 data: 0.0020 max mem: 19788 +Test: [ 3200/21770] eta: 0:21:58 time: 0.0745 data: 0.0022 max mem: 19788 +Test: [ 3300/21770] eta: 0:21:53 time: 0.0789 data: 0.0021 max mem: 19788 +Test: [ 3400/21770] eta: 0:21:49 time: 0.0690 data: 0.0020 max mem: 19788 +Test: [ 3500/21770] eta: 0:21:47 time: 0.0804 data: 0.0024 max mem: 19788 +Test: [ 3600/21770] eta: 0:21:42 time: 0.0713 data: 0.0022 max mem: 19788 +Test: [ 3700/21770] eta: 0:21:36 time: 0.0659 data: 0.0020 max mem: 19788 +Test: [ 3800/21770] eta: 0:21:29 time: 0.0653 data: 0.0019 max mem: 19788 +Test: [ 3900/21770] eta: 0:21:21 time: 0.0660 data: 0.0022 max mem: 19788 +Test: [ 4000/21770] eta: 0:21:14 time: 0.0677 data: 0.0026 max mem: 19788 +Test: [ 4100/21770] eta: 0:21:06 time: 0.0647 data: 0.0019 max mem: 19788 +Test: [ 4200/21770] eta: 0:20:57 time: 0.0640 data: 0.0020 max mem: 19788 +Test: [ 4300/21770] eta: 0:20:49 time: 0.0651 data: 0.0022 max mem: 19788 +Test: [ 4400/21770] eta: 0:20:42 time: 0.0685 data: 0.0020 max mem: 19788 +Test: [ 4500/21770] eta: 0:20:33 time: 0.0774 data: 0.0023 max mem: 19788 +Test: [ 4600/21770] eta: 0:20:28 time: 0.0866 data: 0.0028 max mem: 19788 +Test: [ 4700/21770] eta: 0:20:21 time: 0.0701 data: 0.0022 max mem: 19788 +Test: [ 4800/21770] eta: 0:20:14 time: 0.0671 data: 0.0021 max mem: 19788 +Test: [ 4900/21770] eta: 0:20:06 time: 0.0667 data: 0.0019 max mem: 19788 +Test: [ 5000/21770] eta: 0:19:59 time: 0.0776 data: 0.0025 max mem: 19788 +Test: [ 5100/21770] eta: 0:19:52 time: 0.0815 data: 0.0024 max mem: 19788 +Test: [ 5200/21770] eta: 0:19:44 time: 0.0641 data: 0.0019 max mem: 19788 +Test: [ 5300/21770] eta: 0:19:37 time: 0.0719 data: 0.0020 max mem: 19788 +Test: [ 5400/21770] eta: 0:19:29 time: 0.0630 data: 0.0018 max mem: 19788 +Test: [ 5500/21770] eta: 0:19:22 time: 0.0846 data: 0.0026 max mem: 19788 +Test: [ 5600/21770] eta: 0:19:16 time: 0.0776 data: 0.0021 max mem: 19788 +Test: [ 5700/21770] eta: 0:19:11 time: 0.0772 data: 0.0023 max mem: 19788 +Test: [ 5800/21770] eta: 0:19:02 time: 0.0656 data: 0.0019 max mem: 19788 +Test: [ 5900/21770] eta: 0:18:55 time: 0.0651 data: 0.0020 max mem: 19788 +Test: [ 6000/21770] eta: 0:18:46 time: 0.0672 data: 0.0019 max mem: 19788 +Test: [ 6100/21770] eta: 0:18:37 time: 0.0656 data: 0.0021 max mem: 19788 +Test: [ 6200/21770] eta: 0:18:29 time: 0.0672 data: 0.0019 max mem: 19788 +Test: [ 6300/21770] eta: 0:18:23 time: 0.0780 data: 0.0020 max mem: 19788 +Test: [ 6400/21770] eta: 0:18:15 time: 0.0662 data: 0.0021 max mem: 19788 +Test: [ 6500/21770] eta: 0:18:08 time: 0.0848 data: 0.0026 max mem: 19788 +Test: [ 6600/21770] eta: 0:18:01 time: 0.0653 data: 0.0023 max mem: 19788 +Test: [ 6700/21770] eta: 0:17:54 time: 0.0660 data: 0.0020 max mem: 19788 +Test: [ 6800/21770] eta: 0:17:47 time: 0.0663 data: 0.0020 max mem: 19788 +Test: [ 6900/21770] eta: 0:17:42 time: 0.0728 data: 0.0023 max mem: 19788 +Test: [ 7000/21770] eta: 0:17:35 time: 0.0724 data: 0.0022 max mem: 19788 +Test: [ 7100/21770] eta: 0:17:27 time: 0.0614 data: 0.0018 max mem: 19788 +Test: [ 7200/21770] eta: 0:17:19 time: 0.0726 data: 0.0023 max mem: 19788 +Test: [ 7300/21770] eta: 0:17:12 time: 0.0660 data: 0.0020 max mem: 19788 +Test: [ 7400/21770] eta: 0:17:04 time: 0.0672 data: 0.0021 max mem: 19788 +Test: [ 7500/21770] eta: 0:16:58 time: 0.0830 data: 0.0024 max mem: 19788 +Test: [ 7600/21770] eta: 0:16:50 time: 0.0649 data: 0.0019 max mem: 19788 +Test: [ 7700/21770] eta: 0:16:43 time: 0.0658 data: 0.0022 max mem: 19788 +Test: [ 7800/21770] eta: 0:16:37 time: 0.0779 data: 0.0024 max mem: 19788 +Test: [ 7900/21770] eta: 0:16:29 time: 0.0658 data: 0.0019 max mem: 19788 +Test: [ 8000/21770] eta: 0:16:22 time: 0.0680 data: 0.0020 max mem: 19788 +Test: [ 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time: 0.0773 data: 0.0023 max mem: 19788 +Test: [ 9500/21770] eta: 0:14:35 time: 0.0697 data: 0.0020 max mem: 19788 +Test: [ 9600/21770] eta: 0:14:29 time: 0.0861 data: 0.0021 max mem: 19788 +Test: [ 9700/21770] eta: 0:14:22 time: 0.0683 data: 0.0023 max mem: 19788 +Test: [ 9800/21770] eta: 0:14:15 time: 0.0839 data: 0.0026 max mem: 19788 +Test: [ 9900/21770] eta: 0:14:08 time: 0.0721 data: 0.0020 max mem: 19788 +Test: [10000/21770] eta: 0:14:02 time: 0.0699 data: 0.0022 max mem: 19788 +Test: [10100/21770] eta: 0:13:55 time: 0.0789 data: 0.0022 max mem: 19788 +Test: [10200/21770] eta: 0:13:48 time: 0.0845 data: 0.0027 max mem: 19788 +Test: [10300/21770] eta: 0:13:40 time: 0.0662 data: 0.0020 max mem: 19788 +Test: [10400/21770] eta: 0:13:33 time: 0.0649 data: 0.0020 max mem: 19788 +Test: [10500/21770] eta: 0:13:25 time: 0.0713 data: 0.0021 max mem: 19788 +Test: [10600/21770] eta: 0:13:18 time: 0.0690 data: 0.0018 max mem: 19788 +Test: [10700/21770] eta: 0:13:11 time: 0.0843 data: 0.0022 max mem: 19788 +Test: [10800/21770] eta: 0:13:04 time: 0.0734 data: 0.0022 max mem: 19788 +Test: [10900/21770] eta: 0:12:57 time: 0.0744 data: 0.0023 max mem: 19788 +Test: [11000/21770] eta: 0:12:50 time: 0.0775 data: 0.0022 max mem: 19788 +Test: [11100/21770] eta: 0:12:43 time: 0.0742 data: 0.0022 max mem: 19788 +Test: [11200/21770] eta: 0:12:36 time: 0.0689 data: 0.0020 max mem: 19788 +Test: [11300/21770] eta: 0:12:29 time: 0.0668 data: 0.0022 max mem: 19788 +Test: [11400/21770] eta: 0:12:21 time: 0.0834 data: 0.0027 max mem: 19788 +Test: [11500/21770] eta: 0:12:14 time: 0.0745 data: 0.0021 max mem: 19788 +Test: [11600/21770] eta: 0:12:07 time: 0.0741 data: 0.0024 max mem: 19788 +Test: [11700/21770] eta: 0:12:00 time: 0.0714 data: 0.0020 max mem: 19788 +Test: [11800/21770] eta: 0:11:53 time: 0.0658 data: 0.0019 max mem: 19788 +Test: [11900/21770] eta: 0:11:46 time: 0.0673 data: 0.0020 max mem: 19788 +Test: [12000/21770] eta: 0:11:39 time: 0.0863 data: 0.0026 max mem: 19788 +Test: [12100/21770] eta: 0:11:32 time: 0.0665 data: 0.0020 max mem: 19788 +Test: [12200/21770] eta: 0:11:25 time: 0.0770 data: 0.0021 max mem: 19788 +Test: [12300/21770] eta: 0:11:18 time: 0.0717 data: 0.0020 max mem: 19788 +Test: [12400/21770] eta: 0:11:10 time: 0.0666 data: 0.0019 max mem: 19788 +Test: [12500/21770] eta: 0:11:03 time: 0.0657 data: 0.0020 max mem: 19788 +Test: [12600/21770] eta: 0:10:56 time: 0.0716 data: 0.0023 max mem: 19788 +Test: [12700/21770] eta: 0:10:49 time: 0.0659 data: 0.0017 max mem: 19788 +Test: [12800/21770] eta: 0:10:42 time: 0.0822 data: 0.0026 max mem: 19788 +Test: [12900/21770] eta: 0:10:35 time: 0.0818 data: 0.0027 max mem: 19788 +Test: [13000/21770] eta: 0:10:28 time: 0.0848 data: 0.0026 max mem: 19788 +Test: [13100/21770] eta: 0:10:21 time: 0.0663 data: 0.0020 max mem: 19788 +Test: [13200/21770] eta: 0:10:13 time: 0.0633 data: 0.0019 max mem: 19788 +Test: [13300/21770] eta: 0:10:06 time: 0.0652 data: 0.0019 max mem: 19788 +Test: [13400/21770] eta: 0:09:59 time: 0.0837 data: 0.0021 max mem: 19788 +Test: [13500/21770] eta: 0:09:52 time: 0.0712 data: 0.0022 max mem: 19788 +Test: [13600/21770] eta: 0:09:45 time: 0.0665 data: 0.0019 max mem: 19788 +Test: [13700/21770] eta: 0:09:37 time: 0.0657 data: 0.0020 max mem: 19788 +Test: [13800/21770] eta: 0:09:30 time: 0.0711 data: 0.0021 max mem: 19788 +Test: [13900/21770] eta: 0:09:23 time: 0.0720 data: 0.0021 max mem: 19788 +Test: [14000/21770] eta: 0:09:15 time: 0.0635 data: 0.0018 max mem: 19788 +Test: [14100/21770] eta: 0:09:08 time: 0.0671 data: 0.0019 max mem: 19788 +Test: [14200/21770] eta: 0:09:01 time: 0.0748 data: 0.0025 max mem: 19788 +Test: [14300/21770] eta: 0:08:54 time: 0.0654 data: 0.0019 max mem: 19788 +Test: [14400/21770] eta: 0:08:47 time: 0.0669 data: 0.0020 max mem: 19788 +Test: [14500/21770] eta: 0:08:40 time: 0.0858 data: 0.0022 max mem: 19788 +Test: [14600/21770] eta: 0:08:33 time: 0.0673 data: 0.0019 max mem: 19788 +Test: [14700/21770] eta: 0:08:26 time: 0.0764 data: 0.0024 max mem: 19788 +Test: [14800/21770] eta: 0:08:19 time: 0.0801 data: 0.0023 max mem: 19788 +Test: [14900/21770] eta: 0:08:11 time: 0.0666 data: 0.0020 max mem: 19788 +Test: [15000/21770] eta: 0:08:05 time: 0.0833 data: 0.0026 max mem: 19788 +Test: [15100/21770] eta: 0:07:58 time: 0.0844 data: 0.0022 max mem: 19788 +Test: [15200/21770] eta: 0:07:51 time: 0.0818 data: 0.0024 max mem: 19788 +Test: [15300/21770] eta: 0:07:44 time: 0.0673 data: 0.0019 max mem: 19788 +Test: [15400/21770] eta: 0:07:37 time: 0.0770 data: 0.0023 max mem: 19788 +Test: [15500/21770] eta: 0:07:30 time: 0.0753 data: 0.0022 max mem: 19788 +Test: [15600/21770] eta: 0:07:23 time: 0.0667 data: 0.0020 max mem: 19788 +Test: [15700/21770] eta: 0:07:15 time: 0.0673 data: 0.0021 max mem: 19788 +Test: [15800/21770] eta: 0:07:08 time: 0.0660 data: 0.0022 max mem: 19788 +Test: [15900/21770] eta: 0:07:01 time: 0.0756 data: 0.0022 max mem: 19788 +Test: [16000/21770] eta: 0:06:54 time: 0.0849 data: 0.0021 max mem: 19788 +Test: [16100/21770] eta: 0:06:47 time: 0.0715 data: 0.0023 max mem: 19788 +Test: [16200/21770] eta: 0:06:39 time: 0.0690 data: 0.0021 max mem: 19788 +Test: [16300/21770] eta: 0:06:32 time: 0.0749 data: 0.0025 max mem: 19788 +Test: [16400/21770] eta: 0:06:25 time: 0.0785 data: 0.0024 max mem: 19788 +Test: [16500/21770] eta: 0:06:18 time: 0.0671 data: 0.0020 max mem: 19788 +Test: [16600/21770] eta: 0:06:11 time: 0.0836 data: 0.0026 max mem: 19788 +Test: [16700/21770] eta: 0:06:03 time: 0.0701 data: 0.0019 max mem: 19788 +Test: [16800/21770] eta: 0:05:56 time: 0.0823 data: 0.0026 max mem: 19788 +Test: [16900/21770] eta: 0:05:49 time: 0.0708 data: 0.0026 max mem: 19788 +Test: [17000/21770] eta: 0:05:42 time: 0.0671 data: 0.0019 max mem: 19788 +Test: [17100/21770] eta: 0:05:35 time: 0.0755 data: 0.0020 max mem: 19788 +Test: [17200/21770] eta: 0:05:28 time: 0.0666 data: 0.0022 max mem: 19788 +Test: [17300/21770] eta: 0:05:21 time: 0.0747 data: 0.0021 max mem: 19788 +Test: [17400/21770] eta: 0:05:13 time: 0.0805 data: 0.0021 max mem: 19788 +Test: [17500/21770] eta: 0:05:06 time: 0.0830 data: 0.0025 max mem: 19788 +Test: [17600/21770] eta: 0:04:59 time: 0.0635 data: 0.0018 max mem: 19788 +Test: [17700/21770] eta: 0:04:52 time: 0.0770 data: 0.0022 max mem: 19788 +Test: [17800/21770] eta: 0:04:45 time: 0.0633 data: 0.0020 max mem: 19788 +Test: [17900/21770] eta: 0:04:38 time: 0.0641 data: 0.0019 max mem: 19788 +Test: [18000/21770] eta: 0:04:30 time: 0.0862 data: 0.0028 max mem: 19788 +Test: [18100/21770] eta: 0:04:23 time: 0.0680 data: 0.0019 max mem: 19788 +Test: [18200/21770] eta: 0:04:16 time: 0.0675 data: 0.0019 max mem: 19788 +Test: [18300/21770] eta: 0:04:09 time: 0.0849 data: 0.0027 max mem: 19788 +Test: [18400/21770] eta: 0:04:02 time: 0.0742 data: 0.0024 max mem: 19788 +Test: [18500/21770] eta: 0:03:55 time: 0.0672 data: 0.0021 max mem: 19788 +Test: [18600/21770] eta: 0:03:47 time: 0.0690 data: 0.0021 max mem: 19788 +Test: [18700/21770] eta: 0:03:40 time: 0.0744 data: 0.0024 max mem: 19788 +Test: [18800/21770] eta: 0:03:33 time: 0.0737 data: 0.0022 max mem: 19788 +Test: [18900/21770] eta: 0:03:26 time: 0.0843 data: 0.0025 max mem: 19788 +Test: [19000/21770] eta: 0:03:19 time: 0.0709 data: 0.0021 max mem: 19788 +Test: [19100/21770] eta: 0:03:12 time: 0.0803 data: 0.0022 max mem: 19788 +Test: [19200/21770] eta: 0:03:04 time: 0.0713 data: 0.0021 max mem: 19788 +Test: [19300/21770] eta: 0:02:57 time: 0.0689 data: 0.0021 max mem: 19788 +Test: [19400/21770] eta: 0:02:50 time: 0.0650 data: 0.0021 max mem: 19788 +Test: [19500/21770] eta: 0:02:43 time: 0.0663 data: 0.0023 max mem: 19788 +Test: [19600/21770] eta: 0:02:36 time: 0.0640 data: 0.0023 max mem: 19788 +Test: [19700/21770] eta: 0:02:28 time: 0.0646 data: 0.0020 max mem: 19788 +Test: [19800/21770] eta: 0:02:21 time: 0.0716 data: 0.0020 max mem: 19788 +Test: [19900/21770] eta: 0:02:14 time: 0.0744 data: 0.0021 max mem: 19788 +Test: [20000/21770] eta: 0:02:07 time: 0.0768 data: 0.0023 max mem: 19788 +Test: [20100/21770] eta: 0:02:00 time: 0.0684 data: 0.0022 max mem: 19788 +Test: [20200/21770] eta: 0:01:52 time: 0.0660 data: 0.0022 max mem: 19788 +Test: [20300/21770] eta: 0:01:45 time: 0.0750 data: 0.0024 max mem: 19788 +Test: [20400/21770] eta: 0:01:38 time: 0.0719 data: 0.0020 max mem: 19788 +Test: [20500/21770] eta: 0:01:31 time: 0.0764 data: 0.0022 max mem: 19788 +Test: [20600/21770] eta: 0:01:24 time: 0.0661 data: 0.0021 max mem: 19788 +Test: [20700/21770] eta: 0:01:16 time: 0.0675 data: 0.0021 max mem: 19788 +Test: [20800/21770] eta: 0:01:09 time: 0.0662 data: 0.0020 max mem: 19788 +Test: [20900/21770] eta: 0:01:02 time: 0.0776 data: 0.0024 max mem: 19788 +Test: [21000/21770] eta: 0:00:55 time: 0.0631 data: 0.0019 max mem: 19788 +Test: [21100/21770] eta: 0:00:48 time: 0.0633 data: 0.0018 max mem: 19788 +Test: [21200/21770] eta: 0:00:40 time: 0.0724 data: 0.0024 max mem: 19788 +Test: [21300/21770] eta: 0:00:33 time: 0.0678 data: 0.0020 max mem: 19788 +Test: [21400/21770] eta: 0:00:26 time: 0.0649 data: 0.0018 max mem: 19788 +Test: [21500/21770] eta: 0:00:19 time: 0.0814 data: 0.0020 max mem: 19788 +Test: [21600/21770] eta: 0:00:12 time: 0.0736 data: 0.0021 max mem: 19788 +Test: [21700/21770] eta: 0:00:05 time: 0.0586 data: 0.0018 max mem: 19788 +Test: Total time: 0:26:04 +Final results: +Mean IoU is 63.07 + + precision@0.5 = 69.80 + precision@0.6 = 64.59 + precision@0.7 = 58.24 + precision@0.8 = 47.82 + precision@0.9 = 24.02 + overall IoU = 63.92 + mean IoU = 63.07 + +Mean accuracy for one-to-zero sample is 86.03 + +Average object IoU 0.6307314806009048 +Overall IoU 63.916656494140625 +Epoch: [31] [ 0/2138] eta: 4:16:52 lr: 1.30591213342107e-05 loss: 0.0220 (0.0220) time: 7.2086 data: 2.3766 max mem: 19788 +Epoch: [31] [ 10/2138] eta: 2:34:43 lr: 1.3053012756340541e-05 loss: 0.0183 (0.0190) time: 4.3627 data: 0.2184 max mem: 19788 +Epoch: [31] [ 20/2138] eta: 2:29:01 lr: 1.304690386081988e-05 loss: 0.0183 (0.0190) time: 4.0722 data: 0.0023 max mem: 19788 +Epoch: [31] [ 30/2138] eta: 2:26:32 lr: 1.3040794647466905e-05 loss: 0.0183 (0.0193) time: 4.0654 data: 0.0029 max mem: 19788 +Epoch: [31] [ 40/2138] eta: 2:24:53 lr: 1.3034685116099643e-05 loss: 0.0228 (0.0202) time: 4.0622 data: 0.0038 max mem: 19788 +Epoch: [31] [ 50/2138] eta: 2:23:36 lr: 1.3028575266535885e-05 loss: 0.0229 (0.0205) time: 4.0583 data: 0.0037 max mem: 19788 +Epoch: [31] [ 60/2138] eta: 2:22:31 lr: 1.3022465098593258e-05 loss: 0.0194 (0.0202) time: 4.0563 data: 0.0034 max mem: 19788 +Epoch: [31] [ 70/2138] eta: 2:21:30 lr: 1.3016354612089154e-05 loss: 0.0170 (0.0199) time: 4.0526 data: 0.0034 max mem: 19788 +Epoch: [31] [ 80/2138] eta: 2:20:37 lr: 1.3010243806840802e-05 loss: 0.0186 (0.0204) time: 4.0541 data: 0.0036 max mem: 19788 +Epoch: [31] [ 90/2138] eta: 2:19:45 lr: 1.3004132682665193e-05 loss: 0.0219 (0.0204) time: 4.0536 data: 0.0036 max mem: 19788 +Epoch: [31] [ 100/2138] eta: 2:18:55 lr: 1.2998021239379152e-05 loss: 0.0199 (0.0205) time: 4.0490 data: 0.0035 max mem: 19788 +Epoch: [31] [ 110/2138] eta: 2:18:06 lr: 1.299190947679928e-05 loss: 0.0199 (0.0206) time: 4.0477 data: 0.0035 max mem: 19788 +Epoch: [31] [ 120/2138] eta: 2:17:19 lr: 1.2985797394741977e-05 loss: 0.0213 (0.0207) time: 4.0482 data: 0.0035 max mem: 19788 +Epoch: [31] [ 130/2138] eta: 2:16:32 lr: 1.2979684993023458e-05 loss: 0.0224 (0.0209) time: 4.0462 data: 0.0034 max mem: 19788 +Epoch: [31] [ 140/2138] eta: 2:15:47 lr: 1.2973572271459718e-05 loss: 0.0226 (0.0208) time: 4.0460 data: 0.0032 max mem: 19788 +Epoch: [31] [ 150/2138] eta: 2:15:03 lr: 1.2967459229866572e-05 loss: 0.0198 (0.0207) time: 4.0520 data: 0.0033 max mem: 19788 +Epoch: [31] [ 160/2138] eta: 2:14:18 lr: 1.2961345868059599e-05 loss: 0.0215 (0.0210) time: 4.0497 data: 0.0037 max mem: 19788 +Epoch: [31] [ 170/2138] eta: 2:13:35 lr: 1.2955232185854211e-05 loss: 0.0236 (0.0211) time: 4.0498 data: 0.0035 max mem: 19788 +Epoch: [31] [ 180/2138] eta: 2:12:52 lr: 1.2949118183065584e-05 loss: 0.0204 (0.0212) time: 4.0532 data: 0.0030 max mem: 19788 +Epoch: [31] [ 190/2138] eta: 2:12:10 lr: 1.2943003859508724e-05 loss: 0.0191 (0.0211) time: 4.0539 data: 0.0032 max mem: 19788 +Epoch: [31] [ 200/2138] eta: 2:11:25 lr: 1.2936889214998397e-05 loss: 0.0164 (0.0209) time: 4.0432 data: 0.0035 max mem: 19788 +Epoch: [31] [ 210/2138] eta: 2:10:41 lr: 1.2930774249349199e-05 loss: 0.0228 (0.0212) time: 4.0288 data: 0.0035 max mem: 19788 +Epoch: [31] [ 220/2138] eta: 2:09:57 lr: 1.2924658962375494e-05 loss: 0.0237 (0.0211) time: 4.0307 data: 0.0034 max mem: 19788 +Epoch: [31] [ 230/2138] eta: 2:09:14 lr: 1.291854335389146e-05 loss: 0.0212 (0.0212) time: 4.0333 data: 0.0033 max mem: 19788 +Epoch: [31] [ 240/2138] eta: 2:08:30 lr: 1.2912427423711057e-05 loss: 0.0214 (0.0212) time: 4.0291 data: 0.0031 max mem: 19788 +Epoch: [31] [ 250/2138] eta: 2:07:47 lr: 1.290631117164805e-05 loss: 0.0197 (0.0213) time: 4.0277 data: 0.0030 max mem: 19788 +Epoch: [31] [ 260/2138] eta: 2:07:04 lr: 1.2900194597515985e-05 loss: 0.0186 (0.0213) time: 4.0271 data: 0.0033 max mem: 19788 +Epoch: [31] [ 270/2138] eta: 2:06:22 lr: 1.2894077701128222e-05 loss: 0.0201 (0.0214) time: 4.0301 data: 0.0034 max mem: 19788 +Epoch: [31] [ 280/2138] eta: 2:05:39 lr: 1.2887960482297883e-05 loss: 0.0225 (0.0213) time: 4.0343 data: 0.0033 max mem: 19788 +Epoch: [31] [ 290/2138] eta: 2:04:58 lr: 1.2881842940837924e-05 loss: 0.0225 (0.0214) time: 4.0379 data: 0.0032 max mem: 19788 +Epoch: [31] [ 300/2138] eta: 2:04:16 lr: 1.2875725076561051e-05 loss: 0.0214 (0.0215) time: 4.0433 data: 0.0033 max mem: 19788 +Epoch: [31] [ 310/2138] eta: 2:03:35 lr: 1.2869606889279797e-05 loss: 0.0198 (0.0214) time: 4.0413 data: 0.0034 max mem: 19788 +Epoch: [31] [ 320/2138] eta: 2:02:53 lr: 1.2863488378806463e-05 loss: 0.0195 (0.0214) time: 4.0356 data: 0.0034 max mem: 19788 +Epoch: [31] [ 330/2138] eta: 2:02:11 lr: 1.2857369544953163e-05 loss: 0.0228 (0.0215) time: 4.0328 data: 0.0034 max mem: 19788 +Epoch: [31] [ 340/2138] eta: 2:01:30 lr: 1.2851250387531776e-05 loss: 0.0198 (0.0214) time: 4.0348 data: 0.0034 max mem: 19788 +Epoch: [31] [ 350/2138] eta: 2:00:48 lr: 1.2845130906354006e-05 loss: 0.0200 (0.0214) time: 4.0378 data: 0.0037 max mem: 19788 +Epoch: [31] [ 360/2138] eta: 2:00:06 lr: 1.2839011101231307e-05 loss: 0.0210 (0.0215) time: 4.0290 data: 0.0038 max mem: 19788 +Epoch: [31] [ 370/2138] eta: 1:59:24 lr: 1.2832890971974965e-05 loss: 0.0222 (0.0216) time: 4.0236 data: 0.0034 max mem: 19788 +Epoch: [31] [ 380/2138] eta: 1:58:43 lr: 1.2826770518396019e-05 loss: 0.0209 (0.0216) time: 4.0308 data: 0.0031 max mem: 19788 +Epoch: [31] [ 390/2138] eta: 1:58:01 lr: 1.282064974030533e-05 loss: 0.0215 (0.0216) time: 4.0296 data: 0.0032 max mem: 19788 +Epoch: [31] [ 400/2138] eta: 1:57:20 lr: 1.2814528637513523e-05 loss: 0.0221 (0.0216) time: 4.0277 data: 0.0034 max mem: 19788 +Epoch: [31] [ 410/2138] eta: 1:56:39 lr: 1.2808407209831017e-05 loss: 0.0232 (0.0218) time: 4.0363 data: 0.0034 max mem: 19788 +Epoch: [31] [ 420/2138] eta: 1:55:58 lr: 1.2802285457068037e-05 loss: 0.0244 (0.0218) time: 4.0387 data: 0.0033 max mem: 19788 +Epoch: [31] [ 430/2138] eta: 1:55:16 lr: 1.2796163379034572e-05 loss: 0.0211 (0.0218) time: 4.0340 data: 0.0031 max mem: 19788 +Epoch: [31] [ 440/2138] eta: 1:54:35 lr: 1.2790040975540421e-05 loss: 0.0211 (0.0218) time: 4.0306 data: 0.0033 max mem: 19788 +Epoch: [31] [ 450/2138] eta: 1:53:54 lr: 1.278391824639515e-05 loss: 0.0202 (0.0219) time: 4.0304 data: 0.0036 max mem: 19788 +Epoch: [31] [ 460/2138] eta: 1:53:13 lr: 1.2777795191408133e-05 loss: 0.0222 (0.0219) time: 4.0354 data: 0.0038 max mem: 19788 +Epoch: [31] [ 470/2138] eta: 1:52:32 lr: 1.2771671810388505e-05 loss: 0.0223 (0.0219) time: 4.0399 data: 0.0037 max mem: 19788 +Epoch: [31] [ 480/2138] eta: 1:51:52 lr: 1.2765548103145218e-05 loss: 0.0216 (0.0220) time: 4.0403 data: 0.0035 max mem: 19788 +Epoch: [31] [ 490/2138] eta: 1:51:11 lr: 1.275942406948698e-05 loss: 0.0221 (0.0220) time: 4.0373 data: 0.0034 max mem: 19788 +Epoch: [31] [ 500/2138] eta: 1:50:30 lr: 1.2753299709222316e-05 loss: 0.0213 (0.0220) time: 4.0311 data: 0.0032 max mem: 19788 +Epoch: [31] [ 510/2138] eta: 1:49:49 lr: 1.2747175022159502e-05 loss: 0.0213 (0.0220) time: 4.0290 data: 0.0031 max mem: 19788 +Epoch: [31] [ 520/2138] eta: 1:49:08 lr: 1.2741050008106634e-05 loss: 0.0218 (0.0220) time: 4.0345 data: 0.0034 max mem: 19788 +Epoch: [31] [ 530/2138] eta: 1:48:27 lr: 1.2734924666871558e-05 loss: 0.0206 (0.0221) time: 4.0308 data: 0.0034 max mem: 19788 +Epoch: [31] [ 540/2138] eta: 1:47:46 lr: 1.272879899826194e-05 loss: 0.0194 (0.0220) time: 4.0321 data: 0.0031 max mem: 19788 +Epoch: [31] [ 550/2138] eta: 1:47:05 lr: 1.2722673002085194e-05 loss: 0.0209 (0.0220) time: 4.0294 data: 0.0031 max mem: 19788 +Epoch: [31] [ 560/2138] eta: 1:46:24 lr: 1.2716546678148552e-05 loss: 0.0209 (0.0220) time: 4.0283 data: 0.0031 max mem: 19788 +Epoch: [31] [ 570/2138] eta: 1:45:43 lr: 1.2710420026258998e-05 loss: 0.0196 (0.0220) time: 4.0397 data: 0.0032 max mem: 19788 +Epoch: [31] [ 580/2138] eta: 1:45:03 lr: 1.2704293046223329e-05 loss: 0.0212 (0.0220) time: 4.0422 data: 0.0033 max mem: 19788 +Epoch: [31] [ 590/2138] eta: 1:44:22 lr: 1.2698165737848092e-05 loss: 0.0235 (0.0221) time: 4.0375 data: 0.0032 max mem: 19788 +Epoch: [31] [ 600/2138] eta: 1:43:41 lr: 1.269203810093965e-05 loss: 0.0207 (0.0221) time: 4.0351 data: 0.0034 max mem: 19788 +Epoch: [31] [ 610/2138] eta: 1:43:00 lr: 1.2685910135304115e-05 loss: 0.0207 (0.0222) time: 4.0278 data: 0.0036 max mem: 19788 +Epoch: [31] [ 620/2138] eta: 1:42:20 lr: 1.2679781840747415e-05 loss: 0.0220 (0.0222) time: 4.0263 data: 0.0035 max mem: 19788 +Epoch: [31] [ 630/2138] eta: 1:41:39 lr: 1.2673653217075224e-05 loss: 0.0209 (0.0222) time: 4.0345 data: 0.0033 max mem: 19788 +Epoch: [31] [ 640/2138] eta: 1:40:58 lr: 1.2667524264093026e-05 loss: 0.0209 (0.0222) time: 4.0296 data: 0.0031 max mem: 19788 +Epoch: [31] [ 650/2138] eta: 1:40:17 lr: 1.2661394981606061e-05 loss: 0.0208 (0.0221) time: 4.0242 data: 0.0032 max mem: 19788 +Epoch: [31] [ 660/2138] eta: 1:39:36 lr: 1.2655265369419378e-05 loss: 0.0194 (0.0221) time: 4.0300 data: 0.0033 max mem: 19788 +Epoch: [31] [ 670/2138] eta: 1:38:56 lr: 1.264913542733777e-05 loss: 0.0224 (0.0222) time: 4.0390 data: 0.0034 max mem: 19788 +Epoch: [31] [ 680/2138] eta: 1:38:15 lr: 1.264300515516584e-05 loss: 0.0250 (0.0222) time: 4.0369 data: 0.0033 max mem: 19788 +Epoch: [31] [ 690/2138] eta: 1:37:34 lr: 1.2636874552707953e-05 loss: 0.0236 (0.0222) time: 4.0304 data: 0.0031 max mem: 19788 +Epoch: [31] [ 700/2138] eta: 1:36:54 lr: 1.2630743619768261e-05 loss: 0.0210 (0.0222) time: 4.0296 data: 0.0031 max mem: 19788 +Epoch: [31] [ 710/2138] eta: 1:36:13 lr: 1.2624612356150689e-05 loss: 0.0226 (0.0222) time: 4.0336 data: 0.0033 max mem: 19788 +Epoch: [31] [ 720/2138] eta: 1:35:33 lr: 1.2618480761658934e-05 loss: 0.0201 (0.0222) time: 4.0373 data: 0.0034 max mem: 19788 +Epoch: [31] [ 730/2138] eta: 1:34:52 lr: 1.261234883609649e-05 loss: 0.0212 (0.0223) time: 4.0478 data: 0.0033 max mem: 19788 +Epoch: [31] [ 740/2138] eta: 1:34:12 lr: 1.2606216579266605e-05 loss: 0.0198 (0.0222) time: 4.0506 data: 0.0034 max mem: 19788 +Epoch: [31] [ 750/2138] eta: 1:33:32 lr: 1.2600083990972327e-05 loss: 0.0198 (0.0222) time: 4.0522 data: 0.0034 max mem: 19788 +Epoch: [31] [ 760/2138] eta: 1:32:52 lr: 1.2593951071016453e-05 loss: 0.0214 (0.0222) time: 4.0612 data: 0.0036 max mem: 19788 +Epoch: [31] [ 770/2138] eta: 1:32:11 lr: 1.2587817819201584e-05 loss: 0.0239 (0.0222) time: 4.0446 data: 0.0035 max mem: 19788 +Epoch: [31] [ 780/2138] eta: 1:31:30 lr: 1.258168423533007e-05 loss: 0.0243 (0.0222) time: 4.0276 data: 0.0032 max mem: 19788 +Epoch: [31] [ 790/2138] eta: 1:30:50 lr: 1.2575550319204063e-05 loss: 0.0212 (0.0222) time: 4.0288 data: 0.0032 max mem: 19788 +Epoch: [31] [ 800/2138] eta: 1:30:09 lr: 1.2569416070625464e-05 loss: 0.0191 (0.0222) time: 4.0305 data: 0.0035 max mem: 19788 +Epoch: [31] [ 810/2138] eta: 1:29:29 lr: 1.2563281489395972e-05 loss: 0.0183 (0.0222) time: 4.0371 data: 0.0035 max mem: 19788 +Epoch: [31] [ 820/2138] eta: 1:28:48 lr: 1.255714657531704e-05 loss: 0.0212 (0.0222) time: 4.0421 data: 0.0031 max mem: 19788 +Epoch: [31] [ 830/2138] eta: 1:28:08 lr: 1.255101132818991e-05 loss: 0.0199 (0.0221) time: 4.0493 data: 0.0031 max mem: 19788 +Epoch: [31] [ 840/2138] eta: 1:27:27 lr: 1.2544875747815583e-05 loss: 0.0180 (0.0221) time: 4.0462 data: 0.0033 max mem: 19788 +Epoch: [31] [ 850/2138] eta: 1:26:47 lr: 1.2538739833994851e-05 loss: 0.0189 (0.0222) time: 4.0390 data: 0.0033 max mem: 19788 +Epoch: [31] [ 860/2138] eta: 1:26:07 lr: 1.2532603586528251e-05 loss: 0.0242 (0.0222) time: 4.0456 data: 0.0031 max mem: 19788 +Epoch: [31] [ 870/2138] eta: 1:25:26 lr: 1.2526467005216133e-05 loss: 0.0228 (0.0222) time: 4.0372 data: 0.0031 max mem: 19788 +Epoch: [31] [ 880/2138] eta: 1:24:46 lr: 1.252033008985857e-05 loss: 0.0209 (0.0222) time: 4.0337 data: 0.0033 max mem: 19788 +Epoch: [31] [ 890/2138] eta: 1:24:05 lr: 1.2514192840255453e-05 loss: 0.0214 (0.0222) time: 4.0397 data: 0.0035 max mem: 19788 +Epoch: [31] [ 900/2138] eta: 1:23:25 lr: 1.2508055256206406e-05 loss: 0.0225 (0.0222) time: 4.0399 data: 0.0036 max mem: 19788 +Epoch: [31] [ 910/2138] eta: 1:22:44 lr: 1.2501917337510848e-05 loss: 0.0219 (0.0222) time: 4.0478 data: 0.0038 max mem: 19788 +Epoch: [31] [ 920/2138] eta: 1:22:04 lr: 1.2495779083967957e-05 loss: 0.0200 (0.0222) time: 4.0518 data: 0.0038 max mem: 19788 +Epoch: [31] [ 930/2138] eta: 1:21:24 lr: 1.2489640495376692e-05 loss: 0.0188 (0.0222) time: 4.0479 data: 0.0037 max mem: 19788 +Epoch: [31] [ 940/2138] eta: 1:20:43 lr: 1.2483501571535757e-05 loss: 0.0213 (0.0222) time: 4.0388 data: 0.0037 max mem: 19788 +Epoch: [31] [ 950/2138] eta: 1:20:02 lr: 1.2477362312243657e-05 loss: 0.0213 (0.0222) time: 4.0276 data: 0.0035 max mem: 19788 +Epoch: [31] [ 960/2138] eta: 1:19:22 lr: 1.2471222717298639e-05 loss: 0.0209 (0.0222) time: 4.0238 data: 0.0034 max mem: 19788 +Epoch: [31] [ 970/2138] eta: 1:18:41 lr: 1.246508278649874e-05 loss: 0.0209 (0.0222) time: 4.0272 data: 0.0035 max mem: 19788 +Epoch: [31] [ 980/2138] eta: 1:18:01 lr: 1.245894251964174e-05 loss: 0.0182 (0.0221) time: 4.0330 data: 0.0036 max mem: 19788 +Epoch: [31] [ 990/2138] eta: 1:17:20 lr: 1.2452801916525217e-05 loss: 0.0214 (0.0222) time: 4.0483 data: 0.0037 max mem: 19788 +Epoch: [31] [1000/2138] eta: 1:16:40 lr: 1.2446660976946484e-05 loss: 0.0231 (0.0222) time: 4.0532 data: 0.0039 max mem: 19788 +Epoch: [31] [1010/2138] eta: 1:16:00 lr: 1.2440519700702648e-05 loss: 0.0215 (0.0222) time: 4.0478 data: 0.0037 max mem: 19788 +Epoch: [31] [1020/2138] eta: 1:15:19 lr: 1.2434378087590566e-05 loss: 0.0182 (0.0221) time: 4.0383 data: 0.0034 max mem: 19788 +Epoch: [31] [1030/2138] eta: 1:14:39 lr: 1.242823613740686e-05 loss: 0.0184 (0.0221) time: 4.0414 data: 0.0032 max mem: 19788 +Epoch: [31] [1040/2138] eta: 1:13:58 lr: 1.2422093849947933e-05 loss: 0.0205 (0.0221) time: 4.0417 data: 0.0033 max mem: 19788 +Epoch: [31] [1050/2138] eta: 1:13:18 lr: 1.241595122500993e-05 loss: 0.0207 (0.0221) time: 4.0330 data: 0.0034 max mem: 19788 +Epoch: [31] [1060/2138] eta: 1:12:37 lr: 1.240980826238879e-05 loss: 0.0225 (0.0221) time: 4.0428 data: 0.0035 max mem: 19788 +Epoch: [31] [1070/2138] eta: 1:11:57 lr: 1.2403664961880186e-05 loss: 0.0199 (0.0221) time: 4.0507 data: 0.0035 max mem: 19788 +Epoch: [31] [1080/2138] eta: 1:11:17 lr: 1.2397521323279576e-05 loss: 0.0186 (0.0221) time: 4.0561 data: 0.0034 max mem: 19788 +Epoch: [31] [1090/2138] eta: 1:10:36 lr: 1.2391377346382169e-05 loss: 0.0210 (0.0221) time: 4.0533 data: 0.0033 max mem: 19788 +Epoch: [31] [1100/2138] eta: 1:09:56 lr: 1.238523303098295e-05 loss: 0.0240 (0.0221) time: 4.0405 data: 0.0031 max mem: 19788 +Epoch: [31] [1110/2138] eta: 1:09:15 lr: 1.2379088376876651e-05 loss: 0.0206 (0.0221) time: 4.0268 data: 0.0033 max mem: 19788 +Epoch: [31] [1120/2138] eta: 1:08:35 lr: 1.237294338385778e-05 loss: 0.0204 (0.0221) time: 4.0296 data: 0.0034 max mem: 19788 +Epoch: [31] [1130/2138] eta: 1:07:54 lr: 1.2366798051720595e-05 loss: 0.0226 (0.0221) time: 4.0349 data: 0.0036 max mem: 19788 +Epoch: [31] [1140/2138] eta: 1:07:14 lr: 1.236065238025913e-05 loss: 0.0208 (0.0221) time: 4.0324 data: 0.0039 max mem: 19788 +Epoch: [31] [1150/2138] eta: 1:06:33 lr: 1.235450636926716e-05 loss: 0.0191 (0.0221) time: 4.0400 data: 0.0035 max mem: 19788 +Epoch: [31] [1160/2138] eta: 1:05:53 lr: 1.2348360018538245e-05 loss: 0.0191 (0.0221) time: 4.0438 data: 0.0033 max mem: 19788 +Epoch: [31] [1170/2138] eta: 1:05:12 lr: 1.2342213327865682e-05 loss: 0.0205 (0.0221) time: 4.0360 data: 0.0035 max mem: 19788 +Epoch: [31] [1180/2138] eta: 1:04:32 lr: 1.2336066297042544e-05 loss: 0.0213 (0.0221) time: 4.0399 data: 0.0033 max mem: 19788 +Epoch: [31] [1190/2138] eta: 1:03:52 lr: 1.2329918925861653e-05 loss: 0.0216 (0.0221) time: 4.0419 data: 0.0032 max mem: 19788 +Epoch: [31] [1200/2138] eta: 1:03:11 lr: 1.2323771214115602e-05 loss: 0.0216 (0.0221) time: 4.0401 data: 0.0033 max mem: 19788 +Epoch: [31] [1210/2138] eta: 1:02:31 lr: 1.2317623161596724e-05 loss: 0.0201 (0.0221) time: 4.0477 data: 0.0032 max mem: 19788 +Epoch: [31] [1220/2138] eta: 1:01:50 lr: 1.2311474768097133e-05 loss: 0.0220 (0.0221) time: 4.0432 data: 0.0031 max mem: 19788 +Epoch: [31] [1230/2138] eta: 1:01:10 lr: 1.2305326033408677e-05 loss: 0.0220 (0.0221) time: 4.0297 data: 0.0033 max mem: 19788 +Epoch: [31] [1240/2138] eta: 1:00:29 lr: 1.2299176957322988e-05 loss: 0.0213 (0.0221) time: 4.0313 data: 0.0033 max mem: 19788 +Epoch: [31] [1250/2138] eta: 0:59:49 lr: 1.2293027539631422e-05 loss: 0.0196 (0.0221) time: 4.0381 data: 0.0032 max mem: 19788 +Epoch: [31] [1260/2138] eta: 0:59:08 lr: 1.2286877780125128e-05 loss: 0.0191 (0.0221) time: 4.0357 data: 0.0032 max mem: 19788 +Epoch: [31] [1270/2138] eta: 0:58:28 lr: 1.2280727678594977e-05 loss: 0.0182 (0.0221) time: 4.0287 data: 0.0032 max mem: 19788 +Epoch: [31] [1280/2138] eta: 0:57:47 lr: 1.2274577234831622e-05 loss: 0.0194 (0.0221) time: 4.0274 data: 0.0031 max mem: 19788 +Epoch: [31] [1290/2138] eta: 0:57:07 lr: 1.2268426448625453e-05 loss: 0.0194 (0.0221) time: 4.0435 data: 0.0033 max mem: 19788 +Epoch: [31] [1300/2138] eta: 0:56:27 lr: 1.2262275319766633e-05 loss: 0.0190 (0.0221) time: 4.0496 data: 0.0036 max mem: 19788 +Epoch: [31] [1310/2138] eta: 0:55:46 lr: 1.2256123848045054e-05 loss: 0.0194 (0.0221) time: 4.0429 data: 0.0036 max mem: 19788 +Epoch: [31] [1320/2138] eta: 0:55:06 lr: 1.224997203325039e-05 loss: 0.0218 (0.0221) time: 4.0422 data: 0.0034 max mem: 19788 +Epoch: [31] [1330/2138] eta: 0:54:25 lr: 1.2243819875172047e-05 loss: 0.0214 (0.0221) time: 4.0462 data: 0.0034 max mem: 19788 +Epoch: [31] [1340/2138] eta: 0:53:45 lr: 1.2237667373599194e-05 loss: 0.0196 (0.0221) time: 4.0448 data: 0.0033 max mem: 19788 +Epoch: [31] [1350/2138] eta: 0:53:04 lr: 1.2231514528320753e-05 loss: 0.0212 (0.0222) time: 4.0333 data: 0.0032 max mem: 19788 +Epoch: [31] [1360/2138] eta: 0:52:24 lr: 1.222536133912539e-05 loss: 0.0239 (0.0222) time: 4.0359 data: 0.0033 max mem: 19788 +Epoch: [31] [1370/2138] eta: 0:51:44 lr: 1.2219207805801539e-05 loss: 0.0215 (0.0221) time: 4.0412 data: 0.0033 max mem: 19788 +Epoch: [31] [1380/2138] eta: 0:51:03 lr: 1.2213053928137363e-05 loss: 0.0215 (0.0222) time: 4.0464 data: 0.0032 max mem: 19788 +Epoch: [31] [1390/2138] eta: 0:50:23 lr: 1.2206899705920803e-05 loss: 0.0237 (0.0222) time: 4.0472 data: 0.0031 max mem: 19788 +Epoch: [31] [1400/2138] eta: 0:49:42 lr: 1.2200745138939519e-05 loss: 0.0218 (0.0222) time: 4.0396 data: 0.0032 max mem: 19788 +Epoch: [31] [1410/2138] eta: 0:49:02 lr: 1.2194590226980953e-05 loss: 0.0196 (0.0222) time: 4.0407 data: 0.0033 max mem: 19788 +Epoch: [31] [1420/2138] eta: 0:48:22 lr: 1.2188434969832272e-05 loss: 0.0184 (0.0222) time: 4.0412 data: 0.0032 max mem: 19788 +Epoch: [31] [1430/2138] eta: 0:47:41 lr: 1.2182279367280407e-05 loss: 0.0231 (0.0222) time: 4.0333 data: 0.0032 max mem: 19788 +Epoch: [31] [1440/2138] eta: 0:47:01 lr: 1.2176123419112024e-05 loss: 0.0212 (0.0222) time: 4.0352 data: 0.0034 max mem: 19788 +Epoch: [31] [1450/2138] eta: 0:46:20 lr: 1.2169967125113558e-05 loss: 0.0235 (0.0222) time: 4.0385 data: 0.0036 max mem: 19788 +Epoch: [31] [1460/2138] eta: 0:45:40 lr: 1.2163810485071169e-05 loss: 0.0235 (0.0222) time: 4.0319 data: 0.0034 max mem: 19788 +Epoch: [31] [1470/2138] eta: 0:44:59 lr: 1.2157653498770782e-05 loss: 0.0211 (0.0222) time: 4.0337 data: 0.0033 max mem: 19788 +Epoch: [31] [1480/2138] eta: 0:44:19 lr: 1.2151496165998056e-05 loss: 0.0222 (0.0222) time: 4.0306 data: 0.0035 max mem: 19788 +Epoch: [31] [1490/2138] eta: 0:43:38 lr: 1.2145338486538411e-05 loss: 0.0228 (0.0222) time: 4.0272 data: 0.0036 max mem: 19788 +Epoch: [31] [1500/2138] eta: 0:42:58 lr: 1.2139180460176994e-05 loss: 0.0213 (0.0222) time: 4.0336 data: 0.0035 max mem: 19788 +Epoch: [31] [1510/2138] eta: 0:42:18 lr: 1.213302208669872e-05 loss: 0.0220 (0.0222) time: 4.0465 data: 0.0035 max mem: 19788 +Epoch: [31] [1520/2138] eta: 0:41:37 lr: 1.2126863365888226e-05 loss: 0.0218 (0.0222) time: 4.0468 data: 0.0035 max mem: 19788 +Epoch: [31] [1530/2138] eta: 0:40:57 lr: 1.2120704297529918e-05 loss: 0.0182 (0.0222) time: 4.0433 data: 0.0034 max mem: 19788 +Epoch: [31] [1540/2138] eta: 0:40:16 lr: 1.2114544881407922e-05 loss: 0.0184 (0.0222) time: 4.0485 data: 0.0031 max mem: 19788 +Epoch: [31] [1550/2138] eta: 0:39:36 lr: 1.210838511730613e-05 loss: 0.0187 (0.0222) time: 4.0513 data: 0.0033 max mem: 19788 +Epoch: [31] [1560/2138] eta: 0:38:56 lr: 1.2102225005008158e-05 loss: 0.0211 (0.0222) time: 4.0500 data: 0.0034 max mem: 19788 +Epoch: [31] [1570/2138] eta: 0:38:15 lr: 1.2096064544297384e-05 loss: 0.0227 (0.0222) time: 4.0355 data: 0.0035 max mem: 19788 +Epoch: [31] [1580/2138] eta: 0:37:35 lr: 1.2089903734956906e-05 loss: 0.0202 (0.0222) time: 4.0356 data: 0.0037 max mem: 19788 +Epoch: [31] [1590/2138] eta: 0:36:54 lr: 1.2083742576769592e-05 loss: 0.0207 (0.0222) time: 4.0509 data: 0.0035 max mem: 19788 +Epoch: [31] [1600/2138] eta: 0:36:14 lr: 1.207758106951802e-05 loss: 0.0228 (0.0222) time: 4.0507 data: 0.0031 max mem: 19788 +Epoch: [31] [1610/2138] eta: 0:35:34 lr: 1.2071419212984544e-05 loss: 0.0218 (0.0222) time: 4.0475 data: 0.0031 max mem: 19788 +Epoch: [31] [1620/2138] eta: 0:34:53 lr: 1.2065257006951229e-05 loss: 0.0183 (0.0222) time: 4.0503 data: 0.0033 max mem: 19788 +Epoch: [31] [1630/2138] eta: 0:34:13 lr: 1.2059094451199887e-05 loss: 0.0234 (0.0222) time: 4.0552 data: 0.0035 max mem: 19788 +Epoch: [31] [1640/2138] eta: 0:33:32 lr: 1.2052931545512087e-05 loss: 0.0204 (0.0222) time: 4.0563 data: 0.0034 max mem: 19788 +Epoch: [31] [1650/2138] eta: 0:32:52 lr: 1.2046768289669115e-05 loss: 0.0183 (0.0222) time: 4.0532 data: 0.0034 max mem: 19788 +Epoch: [31] [1660/2138] eta: 0:32:12 lr: 1.2040604683452014e-05 loss: 0.0182 (0.0222) time: 4.0561 data: 0.0033 max mem: 19788 +Epoch: [31] [1670/2138] eta: 0:31:31 lr: 1.2034440726641548e-05 loss: 0.0182 (0.0222) time: 4.0513 data: 0.0031 max mem: 19788 +Epoch: [31] [1680/2138] eta: 0:30:51 lr: 1.202827641901824e-05 loss: 0.0204 (0.0222) time: 4.0414 data: 0.0031 max mem: 19788 +Epoch: [31] [1690/2138] eta: 0:30:10 lr: 1.2022111760362325e-05 loss: 0.0210 (0.0222) time: 4.0318 data: 0.0033 max mem: 19788 +Epoch: [31] [1700/2138] eta: 0:29:30 lr: 1.20159467504538e-05 loss: 0.0207 (0.0222) time: 4.0309 data: 0.0035 max mem: 19788 +Epoch: [31] [1710/2138] eta: 0:28:49 lr: 1.200978138907238e-05 loss: 0.0208 (0.0222) time: 4.0387 data: 0.0034 max mem: 19788 +Epoch: [31] [1720/2138] eta: 0:28:09 lr: 1.2003615675997533e-05 loss: 0.0216 (0.0222) time: 4.0422 data: 0.0035 max mem: 19788 +Epoch: [31] [1730/2138] eta: 0:27:29 lr: 1.1997449611008438e-05 loss: 0.0209 (0.0222) time: 4.0475 data: 0.0035 max mem: 19788 +Epoch: [31] [1740/2138] eta: 0:26:48 lr: 1.1991283193884043e-05 loss: 0.0206 (0.0222) time: 4.0564 data: 0.0033 max mem: 19788 +Epoch: [31] [1750/2138] eta: 0:26:08 lr: 1.1985116424402996e-05 loss: 0.0206 (0.0222) time: 4.0548 data: 0.0033 max mem: 19788 +Epoch: [31] [1760/2138] eta: 0:25:27 lr: 1.1978949302343705e-05 loss: 0.0232 (0.0222) time: 4.0472 data: 0.0035 max mem: 19788 +Epoch: [31] [1770/2138] eta: 0:24:47 lr: 1.1972781827484294e-05 loss: 0.0203 (0.0222) time: 4.0407 data: 0.0033 max mem: 19788 +Epoch: [31] [1780/2138] eta: 0:24:07 lr: 1.1966613999602641e-05 loss: 0.0208 (0.0222) time: 4.0387 data: 0.0033 max mem: 19788 +Epoch: [31] [1790/2138] eta: 0:23:26 lr: 1.1960445818476329e-05 loss: 0.0198 (0.0222) time: 4.0467 data: 0.0033 max mem: 19788 +Epoch: [31] [1800/2138] eta: 0:22:46 lr: 1.1954277283882703e-05 loss: 0.0198 (0.0222) time: 4.0457 data: 0.0031 max mem: 19788 +Epoch: [31] [1810/2138] eta: 0:22:05 lr: 1.1948108395598813e-05 loss: 0.0208 (0.0222) time: 4.0338 data: 0.0031 max mem: 19788 +Epoch: [31] [1820/2138] eta: 0:21:25 lr: 1.1941939153401467e-05 loss: 0.0212 (0.0222) time: 4.0361 data: 0.0031 max mem: 19788 +Epoch: [31] [1830/2138] eta: 0:20:45 lr: 1.1935769557067173e-05 loss: 0.0198 (0.0222) time: 4.0501 data: 0.0033 max mem: 19788 +Epoch: [31] [1840/2138] eta: 0:20:04 lr: 1.19295996063722e-05 loss: 0.0205 (0.0222) time: 4.0550 data: 0.0036 max mem: 19788 +Epoch: [31] [1850/2138] eta: 0:19:24 lr: 1.1923429301092524e-05 loss: 0.0229 (0.0222) time: 4.0484 data: 0.0037 max mem: 19788 +Epoch: [31] [1860/2138] eta: 0:18:43 lr: 1.191725864100387e-05 loss: 0.0228 (0.0222) time: 4.0382 data: 0.0035 max mem: 19788 +Epoch: [31] [1870/2138] eta: 0:18:03 lr: 1.191108762588167e-05 loss: 0.0228 (0.0222) time: 4.0285 data: 0.0033 max mem: 19788 +Epoch: [31] [1880/2138] eta: 0:17:22 lr: 1.1904916255501108e-05 loss: 0.0206 (0.0222) time: 4.0230 data: 0.0034 max mem: 19788 +Epoch: [31] [1890/2138] eta: 0:16:42 lr: 1.1898744529637071e-05 loss: 0.0186 (0.0222) time: 4.0449 data: 0.0033 max mem: 19788 +Epoch: [31] [1900/2138] eta: 0:16:02 lr: 1.1892572448064202e-05 loss: 0.0175 (0.0222) time: 4.0467 data: 0.0032 max mem: 19788 +Epoch: [31] [1910/2138] eta: 0:15:21 lr: 1.1886400010556843e-05 loss: 0.0196 (0.0222) time: 4.0282 data: 0.0033 max mem: 19788 +Epoch: [31] [1920/2138] eta: 0:14:41 lr: 1.1880227216889085e-05 loss: 0.0202 (0.0222) time: 4.0345 data: 0.0033 max mem: 19788 +Epoch: [31] [1930/2138] eta: 0:14:00 lr: 1.1874054066834733e-05 loss: 0.0208 (0.0222) time: 4.0333 data: 0.0034 max mem: 19788 +Epoch: [31] [1940/2138] eta: 0:13:20 lr: 1.1867880560167314e-05 loss: 0.0218 (0.0222) time: 4.0436 data: 0.0033 max mem: 19788 +Epoch: [31] [1950/2138] eta: 0:12:39 lr: 1.1861706696660094e-05 loss: 0.0208 (0.0222) time: 4.0538 data: 0.0033 max mem: 19788 +Epoch: [31] [1960/2138] eta: 0:11:59 lr: 1.185553247608605e-05 loss: 0.0210 (0.0222) time: 4.0480 data: 0.0033 max mem: 19788 +Epoch: [31] [1970/2138] eta: 0:11:19 lr: 1.1849357898217896e-05 loss: 0.0208 (0.0222) time: 4.0376 data: 0.0031 max mem: 19788 +Epoch: [31] [1980/2138] eta: 0:10:38 lr: 1.1843182962828053e-05 loss: 0.0169 (0.0222) time: 4.0300 data: 0.0031 max mem: 19788 +Epoch: [31] [1990/2138] eta: 0:09:58 lr: 1.1837007669688688e-05 loss: 0.0187 (0.0221) time: 4.0366 data: 0.0031 max mem: 19788 +Epoch: [31] [2000/2138] eta: 0:09:17 lr: 1.1830832018571664e-05 loss: 0.0205 (0.0222) time: 4.0412 data: 0.0033 max mem: 19788 +Epoch: [31] [2010/2138] eta: 0:08:37 lr: 1.1824656009248592e-05 loss: 0.0232 (0.0222) time: 4.0445 data: 0.0032 max mem: 19788 +Epoch: [31] [2020/2138] eta: 0:07:56 lr: 1.1818479641490778e-05 loss: 0.0232 (0.0222) time: 4.0424 data: 0.0032 max mem: 19788 +Epoch: [31] [2030/2138] eta: 0:07:16 lr: 1.1812302915069279e-05 loss: 0.0216 (0.0222) time: 4.0344 data: 0.0031 max mem: 19788 +Epoch: [31] [2040/2138] eta: 0:06:36 lr: 1.1806125829754843e-05 loss: 0.0206 (0.0222) time: 4.0279 data: 0.0031 max mem: 19788 +Epoch: [31] [2050/2138] eta: 0:05:55 lr: 1.1799948385317963e-05 loss: 0.0206 (0.0222) time: 4.0319 data: 0.0033 max mem: 19788 +Epoch: [31] [2060/2138] eta: 0:05:15 lr: 1.1793770581528832e-05 loss: 0.0205 (0.0222) time: 4.0389 data: 0.0034 max mem: 19788 +Epoch: [31] [2070/2138] eta: 0:04:34 lr: 1.178759241815738e-05 loss: 0.0195 (0.0222) time: 4.0368 data: 0.0034 max mem: 19788 +Epoch: [31] [2080/2138] eta: 0:03:54 lr: 1.1781413894973236e-05 loss: 0.0203 (0.0222) time: 4.0407 data: 0.0034 max mem: 19788 +Epoch: [31] [2090/2138] eta: 0:03:14 lr: 1.1775235011745766e-05 loss: 0.0203 (0.0221) time: 4.0462 data: 0.0033 max mem: 19788 +Epoch: [31] [2100/2138] eta: 0:02:33 lr: 1.1769055768244039e-05 loss: 0.0199 (0.0221) time: 4.0330 data: 0.0032 max mem: 19788 +Epoch: [31] [2110/2138] eta: 0:01:53 lr: 1.1762876164236856e-05 loss: 0.0228 (0.0222) time: 4.0349 data: 0.0031 max mem: 19788 +Epoch: [31] [2120/2138] eta: 0:01:12 lr: 1.1756696199492713e-05 loss: 0.0252 (0.0222) time: 4.0453 data: 0.0031 max mem: 19788 +Epoch: [31] [2130/2138] eta: 0:00:32 lr: 1.1750515873779849e-05 loss: 0.0230 (0.0222) time: 4.0205 data: 0.0032 max mem: 19788 +Epoch: [31] Total time: 2:24:01 +Test: [ 0/21770] eta: 20:47:28 time: 3.4382 data: 3.2553 max mem: 19788 +Test: [ 100/21770] eta: 0:37:59 time: 0.0641 data: 0.0021 max mem: 19788 +Test: [ 200/21770] eta: 0:31:21 time: 0.0724 data: 0.0024 max mem: 19788 +Test: [ 300/21770] eta: 0:29:49 time: 0.0680 data: 0.0021 max mem: 19788 +Test: [ 400/21770] eta: 0:28:19 time: 0.0737 data: 0.0020 max mem: 19788 +Test: [ 500/21770] eta: 0:27:39 time: 0.0841 data: 0.0024 max mem: 19788 +Test: [ 600/21770] eta: 0:27:35 time: 0.0732 data: 0.0021 max mem: 19788 +Test: [ 700/21770] eta: 0:27:06 time: 0.0656 data: 0.0020 max mem: 19788 +Test: [ 800/21770] eta: 0:26:27 time: 0.0693 data: 0.0020 max mem: 19788 +Test: [ 900/21770] eta: 0:25:59 time: 0.0626 data: 0.0020 max mem: 19788 +Test: [ 1000/21770] eta: 0:25:32 time: 0.0634 data: 0.0020 max mem: 19788 +Test: [ 1100/21770] eta: 0:25:11 time: 0.0665 data: 0.0022 max mem: 19788 +Test: [ 1200/21770] eta: 0:24:57 time: 0.0646 data: 0.0023 max mem: 19788 +Test: [ 1300/21770] eta: 0:24:49 time: 0.0848 data: 0.0022 max mem: 19788 +Test: [ 1400/21770] eta: 0:24:41 time: 0.0616 data: 0.0021 max mem: 19788 +Test: [ 1500/21770] eta: 0:24:28 time: 0.0623 data: 0.0021 max mem: 19788 +Test: [ 1600/21770] eta: 0:24:23 time: 0.0658 data: 0.0022 max mem: 19788 +Test: [ 1700/21770] eta: 0:24:20 time: 0.0662 data: 0.0019 max mem: 19788 +Test: [ 1800/21770] eta: 0:24:07 time: 0.0646 data: 0.0019 max mem: 19788 +Test: [ 1900/21770] eta: 0:23:54 time: 0.0645 data: 0.0020 max mem: 19788 +Test: [ 2000/21770] eta: 0:23:40 time: 0.0699 data: 0.0022 max mem: 19788 +Test: [ 2100/21770] eta: 0:23:26 time: 0.0638 data: 0.0017 max mem: 19788 +Test: [ 2200/21770] eta: 0:23:15 time: 0.0645 data: 0.0022 max mem: 19788 +Test: [ 2300/21770] eta: 0:23:09 time: 0.0847 data: 0.0027 max mem: 19788 +Test: [ 2400/21770] eta: 0:23:02 time: 0.0721 data: 0.0021 max mem: 19788 +Test: [ 2500/21770] eta: 0:22:51 time: 0.0660 data: 0.0019 max mem: 19788 +Test: [ 2600/21770] eta: 0:22:44 time: 0.0766 data: 0.0025 max mem: 19788 +Test: [ 2700/21770] eta: 0:22:36 time: 0.0649 data: 0.0019 max mem: 19788 +Test: [ 2800/21770] eta: 0:22:25 time: 0.0668 data: 0.0017 max mem: 19788 +Test: [ 2900/21770] eta: 0:22:14 time: 0.0638 data: 0.0020 max mem: 19788 +Test: [ 3000/21770] eta: 0:22:04 time: 0.0634 data: 0.0020 max mem: 19788 +Test: [ 3100/21770] eta: 0:21:57 time: 0.0678 data: 0.0021 max mem: 19788 +Test: [ 3200/21770] eta: 0:21:50 time: 0.0704 data: 0.0020 max mem: 19788 +Test: [ 3300/21770] eta: 0:21:43 time: 0.0696 data: 0.0018 max mem: 19788 +Test: [ 3400/21770] eta: 0:21:39 time: 0.0663 data: 0.0020 max mem: 19788 +Test: [ 3500/21770] eta: 0:21:30 time: 0.0651 data: 0.0018 max mem: 19788 +Test: [ 3600/21770] eta: 0:21:22 time: 0.0661 data: 0.0021 max mem: 19788 +Test: [ 3700/21770] eta: 0:21:16 time: 0.0791 data: 0.0025 max mem: 19788 +Test: [ 3800/21770] eta: 0:21:07 time: 0.0635 data: 0.0020 max mem: 19788 +Test: [ 3900/21770] eta: 0:21:03 time: 0.0849 data: 0.0023 max mem: 19788 +Test: [ 4000/21770] eta: 0:20:59 time: 0.0718 data: 0.0022 max mem: 19788 +Test: [ 4100/21770] eta: 0:20:51 time: 0.0747 data: 0.0022 max mem: 19788 +Test: [ 4200/21770] eta: 0:20:43 time: 0.0653 data: 0.0022 max mem: 19788 +Test: [ 4300/21770] eta: 0:20:34 time: 0.0660 data: 0.0019 max mem: 19788 +Test: [ 4400/21770] eta: 0:20:28 time: 0.0712 data: 0.0020 max mem: 19788 +Test: [ 4500/21770] eta: 0:20:21 time: 0.0699 data: 0.0021 max mem: 19788 +Test: [ 4600/21770] eta: 0:20:14 time: 0.0649 data: 0.0021 max mem: 19788 +Test: [ 4700/21770] eta: 0:20:08 time: 0.0669 data: 0.0021 max mem: 19788 +Test: [ 4800/21770] eta: 0:20:01 time: 0.0712 data: 0.0021 max mem: 19788 +Test: [ 4900/21770] eta: 0:19:52 time: 0.0643 data: 0.0020 max mem: 19788 +Test: [ 5000/21770] eta: 0:19:45 time: 0.0827 data: 0.0024 max mem: 19788 +Test: [ 5100/21770] eta: 0:19:39 time: 0.0679 data: 0.0022 max mem: 19788 +Test: [ 5200/21770] eta: 0:19:32 time: 0.0743 data: 0.0023 max mem: 19788 +Test: [ 5300/21770] eta: 0:19:26 time: 0.0845 data: 0.0026 max mem: 19788 +Test: [ 5400/21770] eta: 0:19:21 time: 0.0712 data: 0.0020 max mem: 19788 +Test: [ 5500/21770] eta: 0:19:14 time: 0.0634 data: 0.0019 max mem: 19788 +Test: [ 5600/21770] eta: 0:19:07 time: 0.0787 data: 0.0023 max mem: 19788 +Test: [ 5700/21770] eta: 0:19:00 time: 0.0638 data: 0.0018 max mem: 19788 +Test: [ 5800/21770] eta: 0:18:54 time: 0.0794 data: 0.0025 max mem: 19788 +Test: [ 5900/21770] eta: 0:18:45 time: 0.0608 data: 0.0020 max mem: 19788 +Test: [ 6000/21770] eta: 0:18:37 time: 0.0630 data: 0.0018 max mem: 19788 +Test: [ 6100/21770] eta: 0:18:32 time: 0.0854 data: 0.0020 max mem: 19788 +Test: [ 6200/21770] eta: 0:18:27 time: 0.0740 data: 0.0022 max mem: 19788 +Test: [ 6300/21770] eta: 0:18:20 time: 0.0839 data: 0.0021 max mem: 19788 +Test: [ 6400/21770] eta: 0:18:12 time: 0.0664 data: 0.0018 max mem: 19788 +Test: [ 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time: 0.0647 data: 0.0018 max mem: 19788 +Test: [ 7900/21770] eta: 0:16:21 time: 0.0732 data: 0.0022 max mem: 19788 +Test: [ 8000/21770] eta: 0:16:13 time: 0.0686 data: 0.0020 max mem: 19788 +Test: [ 8100/21770] eta: 0:16:07 time: 0.0727 data: 0.0022 max mem: 19788 +Test: [ 8200/21770] eta: 0:15:59 time: 0.0724 data: 0.0022 max mem: 19788 +Test: [ 8300/21770] eta: 0:15:53 time: 0.0681 data: 0.0020 max mem: 19788 +Test: [ 8400/21770] eta: 0:15:45 time: 0.0641 data: 0.0019 max mem: 19788 +Test: [ 8500/21770] eta: 0:15:39 time: 0.0688 data: 0.0022 max mem: 19788 +Test: [ 8600/21770] eta: 0:15:32 time: 0.0656 data: 0.0020 max mem: 19788 +Test: [ 8700/21770] eta: 0:15:25 time: 0.0648 data: 0.0020 max mem: 19788 +Test: [ 8800/21770] eta: 0:15:18 time: 0.0661 data: 0.0020 max mem: 19788 +Test: [ 8900/21770] eta: 0:15:11 time: 0.0707 data: 0.0024 max mem: 19788 +Test: [ 9000/21770] eta: 0:15:04 time: 0.0648 data: 0.0019 max mem: 19788 +Test: [ 9100/21770] eta: 0:14:58 time: 0.0686 data: 0.0022 max mem: 19788 +Test: [ 9200/21770] eta: 0:14:52 time: 0.0731 data: 0.0025 max mem: 19788 +Test: [ 9300/21770] eta: 0:14:45 time: 0.0737 data: 0.0021 max mem: 19788 +Test: [ 9400/21770] eta: 0:14:37 time: 0.0660 data: 0.0021 max mem: 19788 +Test: [ 9500/21770] eta: 0:14:30 time: 0.0713 data: 0.0022 max mem: 19788 +Test: [ 9600/21770] eta: 0:14:23 time: 0.0660 data: 0.0018 max mem: 19788 +Test: [ 9700/21770] eta: 0:14:17 time: 0.0781 data: 0.0023 max mem: 19788 +Test: [ 9800/21770] eta: 0:14:10 time: 0.0656 data: 0.0020 max mem: 19788 +Test: [ 9900/21770] eta: 0:14:03 time: 0.0658 data: 0.0019 max mem: 19788 +Test: [10000/21770] eta: 0:13:56 time: 0.0814 data: 0.0025 max mem: 19788 +Test: [10100/21770] eta: 0:13:50 time: 0.0755 data: 0.0025 max mem: 19788 +Test: [10200/21770] eta: 0:13:43 time: 0.0644 data: 0.0020 max mem: 19788 +Test: [10300/21770] eta: 0:13:36 time: 0.0660 data: 0.0019 max mem: 19788 +Test: [10400/21770] eta: 0:13:28 time: 0.0652 data: 0.0022 max mem: 19788 +Test: [10500/21770] eta: 0:13:22 time: 0.0856 data: 0.0025 max mem: 19788 +Test: [10600/21770] eta: 0:13:14 time: 0.0657 data: 0.0021 max mem: 19788 +Test: [10700/21770] eta: 0:13:07 time: 0.0686 data: 0.0020 max mem: 19788 +Test: [10800/21770] eta: 0:13:01 time: 0.0841 data: 0.0027 max mem: 19788 +Test: [10900/21770] eta: 0:12:54 time: 0.0641 data: 0.0019 max mem: 19788 +Test: [11000/21770] eta: 0:12:48 time: 0.0823 data: 0.0025 max mem: 19788 +Test: [11100/21770] eta: 0:12:41 time: 0.0667 data: 0.0019 max mem: 19788 +Test: [11200/21770] eta: 0:12:34 time: 0.0765 data: 0.0022 max mem: 19788 +Test: [11300/21770] eta: 0:12:26 time: 0.0667 data: 0.0019 max mem: 19788 +Test: [11400/21770] eta: 0:12:19 time: 0.0650 data: 0.0018 max mem: 19788 +Test: [11500/21770] eta: 0:12:12 time: 0.0688 data: 0.0020 max mem: 19788 +Test: [11600/21770] eta: 0:12:04 time: 0.0658 data: 0.0020 max mem: 19788 +Test: [11700/21770] eta: 0:11:57 time: 0.0675 data: 0.0019 max mem: 19788 +Test: [11800/21770] eta: 0:11:50 time: 0.0657 data: 0.0019 max mem: 19788 +Test: [11900/21770] eta: 0:11:42 time: 0.0649 data: 0.0020 max mem: 19788 +Test: [12000/21770] eta: 0:11:35 time: 0.0706 data: 0.0021 max mem: 19788 +Test: [12100/21770] eta: 0:11:28 time: 0.0741 data: 0.0022 max mem: 19788 +Test: [12200/21770] eta: 0:11:21 time: 0.0817 data: 0.0026 max mem: 19788 +Test: [12300/21770] eta: 0:11:13 time: 0.0658 data: 0.0018 max mem: 19788 +Test: [12400/21770] eta: 0:11:06 time: 0.0701 data: 0.0022 max mem: 19788 +Test: [12500/21770] eta: 0:11:00 time: 0.0775 data: 0.0020 max mem: 19788 +Test: [12600/21770] eta: 0:10:52 time: 0.0684 data: 0.0021 max mem: 19788 +Test: [12700/21770] eta: 0:10:46 time: 0.0657 data: 0.0020 max mem: 19788 +Test: [12800/21770] eta: 0:10:39 time: 0.0860 data: 0.0029 max mem: 19788 +Test: [12900/21770] eta: 0:10:32 time: 0.0773 data: 0.0024 max mem: 19788 +Test: [13000/21770] eta: 0:10:25 time: 0.0717 data: 0.0022 max mem: 19788 +Test: [13100/21770] eta: 0:10:17 time: 0.0658 data: 0.0021 max mem: 19788 +Test: [13200/21770] eta: 0:10:10 time: 0.0725 data: 0.0020 max mem: 19788 +Test: [13300/21770] eta: 0:10:03 time: 0.0688 data: 0.0022 max mem: 19788 +Test: [13400/21770] eta: 0:09:56 time: 0.0658 data: 0.0022 max mem: 19788 +Test: [13500/21770] eta: 0:09:49 time: 0.0647 data: 0.0019 max mem: 19788 +Test: [13600/21770] eta: 0:09:42 time: 0.0701 data: 0.0021 max mem: 19788 +Test: [13700/21770] eta: 0:09:35 time: 0.0667 data: 0.0020 max mem: 19788 +Test: [13800/21770] eta: 0:09:27 time: 0.0663 data: 0.0021 max mem: 19788 +Test: [13900/21770] eta: 0:09:21 time: 0.0673 data: 0.0022 max mem: 19788 +Test: [14000/21770] eta: 0:09:13 time: 0.0732 data: 0.0023 max mem: 19788 +Test: [14100/21770] eta: 0:09:06 time: 0.0716 data: 0.0020 max mem: 19788 +Test: [14200/21770] eta: 0:08:59 time: 0.0665 data: 0.0022 max mem: 19788 +Test: [14300/21770] eta: 0:08:52 time: 0.0663 data: 0.0021 max mem: 19788 +Test: [14400/21770] eta: 0:08:45 time: 0.0689 data: 0.0024 max mem: 19788 +Test: [14500/21770] eta: 0:08:38 time: 0.0660 data: 0.0020 max mem: 19788 +Test: [14600/21770] eta: 0:08:31 time: 0.0836 data: 0.0025 max mem: 19788 +Test: [14700/21770] eta: 0:08:24 time: 0.0736 data: 0.0022 max mem: 19788 +Test: [14800/21770] eta: 0:08:17 time: 0.0643 data: 0.0018 max mem: 19788 +Test: [14900/21770] eta: 0:08:10 time: 0.0659 data: 0.0019 max mem: 19788 +Test: [15000/21770] eta: 0:08:03 time: 0.0666 data: 0.0021 max mem: 19788 +Test: [15100/21770] eta: 0:07:55 time: 0.0674 data: 0.0022 max mem: 19788 +Test: [15200/21770] eta: 0:07:49 time: 0.0798 data: 0.0021 max mem: 19788 +Test: [15300/21770] eta: 0:07:41 time: 0.0660 data: 0.0019 max mem: 19788 +Test: [15400/21770] eta: 0:07:34 time: 0.0668 data: 0.0018 max mem: 19788 +Test: [15500/21770] eta: 0:07:27 time: 0.0668 data: 0.0026 max mem: 19788 +Test: [15600/21770] eta: 0:07:20 time: 0.0670 data: 0.0021 max mem: 19788 +Test: [15700/21770] eta: 0:07:13 time: 0.0701 data: 0.0021 max mem: 19788 +Test: [15800/21770] eta: 0:07:06 time: 0.0827 data: 0.0019 max mem: 19788 +Test: [15900/21770] eta: 0:06:58 time: 0.0644 data: 0.0018 max mem: 19788 +Test: [16000/21770] eta: 0:06:51 time: 0.0745 data: 0.0020 max mem: 19788 +Test: [16100/21770] eta: 0:06:44 time: 0.0666 data: 0.0021 max mem: 19788 +Test: [16200/21770] eta: 0:06:37 time: 0.0670 data: 0.0020 max mem: 19788 +Test: [16300/21770] eta: 0:06:30 time: 0.0745 data: 0.0025 max mem: 19788 +Test: [16400/21770] eta: 0:06:23 time: 0.0796 data: 0.0025 max mem: 19788 +Test: [16500/21770] eta: 0:06:16 time: 0.0699 data: 0.0023 max mem: 19788 +Test: [16600/21770] eta: 0:06:09 time: 0.0792 data: 0.0022 max mem: 19788 +Test: [16700/21770] eta: 0:06:01 time: 0.0800 data: 0.0025 max mem: 19788 +Test: [16800/21770] eta: 0:05:54 time: 0.0678 data: 0.0021 max mem: 19788 +Test: [16900/21770] eta: 0:05:47 time: 0.0717 data: 0.0021 max mem: 19788 +Test: [17000/21770] eta: 0:05:40 time: 0.0640 data: 0.0019 max mem: 19788 +Test: [17100/21770] eta: 0:05:33 time: 0.0641 data: 0.0020 max mem: 19788 +Test: [17200/21770] eta: 0:05:26 time: 0.0752 data: 0.0018 max mem: 19788 +Test: [17300/21770] eta: 0:05:19 time: 0.0760 data: 0.0023 max mem: 19788 +Test: [17400/21770] eta: 0:05:11 time: 0.0632 data: 0.0020 max mem: 19788 +Test: [17500/21770] eta: 0:05:04 time: 0.0739 data: 0.0023 max mem: 19788 +Test: [17600/21770] eta: 0:04:57 time: 0.0842 data: 0.0021 max mem: 19788 +Test: [17700/21770] eta: 0:04:50 time: 0.0788 data: 0.0022 max mem: 19788 +Test: [17800/21770] eta: 0:04:43 time: 0.0753 data: 0.0020 max mem: 19788 +Test: [17900/21770] eta: 0:04:36 time: 0.0694 data: 0.0023 max mem: 19788 +Test: [18000/21770] eta: 0:04:29 time: 0.0662 data: 0.0020 max mem: 19788 +Test: [18100/21770] eta: 0:04:22 time: 0.0714 data: 0.0021 max mem: 19788 +Test: [18200/21770] eta: 0:04:15 time: 0.0713 data: 0.0023 max mem: 19788 +Test: [18300/21770] eta: 0:04:07 time: 0.0859 data: 0.0025 max mem: 19788 +Test: [18400/21770] eta: 0:04:00 time: 0.0681 data: 0.0021 max mem: 19788 +Test: [18500/21770] eta: 0:03:53 time: 0.0778 data: 0.0021 max mem: 19788 +Test: [18600/21770] eta: 0:03:46 time: 0.0835 data: 0.0025 max mem: 19788 +Test: [18700/21770] eta: 0:03:39 time: 0.0645 data: 0.0021 max mem: 19788 +Test: [18800/21770] eta: 0:03:32 time: 0.0670 data: 0.0020 max mem: 19788 +Test: [18900/21770] eta: 0:03:25 time: 0.0693 data: 0.0021 max mem: 19788 +Test: [19000/21770] eta: 0:03:17 time: 0.0697 data: 0.0021 max mem: 19788 +Test: [19100/21770] eta: 0:03:10 time: 0.0699 data: 0.0019 max mem: 19788 +Test: [19200/21770] eta: 0:03:03 time: 0.0642 data: 0.0018 max mem: 19788 +Test: [19300/21770] eta: 0:02:56 time: 0.0640 data: 0.0020 max mem: 19788 +Test: [19400/21770] eta: 0:02:49 time: 0.0684 data: 0.0022 max mem: 19788 +Test: [19500/21770] eta: 0:02:42 time: 0.0641 data: 0.0021 max mem: 19788 +Test: [19600/21770] eta: 0:02:34 time: 0.0682 data: 0.0019 max mem: 19788 +Test: [19700/21770] eta: 0:02:27 time: 0.0629 data: 0.0019 max mem: 19788 +Test: [19800/21770] eta: 0:02:20 time: 0.0726 data: 0.0021 max mem: 19788 +Test: [19900/21770] eta: 0:02:13 time: 0.0644 data: 0.0019 max mem: 19788 +Test: [20000/21770] eta: 0:02:06 time: 0.0667 data: 0.0020 max mem: 19788 +Test: [20100/21770] eta: 0:01:59 time: 0.0662 data: 0.0021 max mem: 19788 +Test: [20200/21770] eta: 0:01:51 time: 0.0644 data: 0.0018 max mem: 19788 +Test: [20300/21770] eta: 0:01:44 time: 0.0657 data: 0.0020 max mem: 19788 +Test: [20400/21770] eta: 0:01:37 time: 0.0656 data: 0.0019 max mem: 19788 +Test: [20500/21770] eta: 0:01:30 time: 0.0696 data: 0.0021 max mem: 19788 +Test: [20600/21770] eta: 0:01:23 time: 0.0859 data: 0.0025 max mem: 19788 +Test: [20700/21770] eta: 0:01:16 time: 0.0723 data: 0.0021 max mem: 19788 +Test: [20800/21770] eta: 0:01:09 time: 0.0748 data: 0.0023 max mem: 19788 +Test: [20900/21770] eta: 0:01:02 time: 0.0757 data: 0.0024 max mem: 19788 +Test: [21000/21770] eta: 0:00:54 time: 0.0644 data: 0.0019 max mem: 19788 +Test: [21100/21770] eta: 0:00:47 time: 0.0833 data: 0.0021 max mem: 19788 +Test: [21200/21770] eta: 0:00:40 time: 0.0760 data: 0.0022 max mem: 19788 +Test: [21300/21770] eta: 0:00:33 time: 0.0759 data: 0.0023 max mem: 19788 +Test: [21400/21770] eta: 0:00:26 time: 0.0718 data: 0.0019 max mem: 19788 +Test: [21500/21770] eta: 0:00:19 time: 0.0656 data: 0.0022 max mem: 19788 +Test: [21600/21770] eta: 0:00:12 time: 0.0707 data: 0.0021 max mem: 19788 +Test: [21700/21770] eta: 0:00:04 time: 0.0673 data: 0.0019 max mem: 19788 +Test: Total time: 0:25:55 +Final results: +Mean IoU is 62.81 + + precision@0.5 = 69.55 + precision@0.6 = 64.46 + precision@0.7 = 57.92 + precision@0.8 = 47.52 + precision@0.9 = 23.57 + overall IoU = 63.84 + mean IoU = 62.81 + +Mean accuracy for one-to-zero sample is 86.55 + +Average object IoU 0.6280621151028823 +Overall IoU 63.843326568603516 +Epoch: [32] [ 0/2138] eta: 8:18:40 lr: 1.1745571353156134e-05 loss: 0.0220 (0.0220) time: 13.9947 data: 2.3617 max mem: 19788 +Epoch: [32] [ 10/2138] eta: 2:56:13 lr: 1.1739390377114576e-05 loss: 0.0181 (0.0184) time: 4.9689 data: 0.2171 max mem: 19788 +Epoch: [32] [ 20/2138] eta: 2:40:05 lr: 1.17332090394538e-05 loss: 0.0171 (0.0178) time: 4.0622 data: 0.0023 max mem: 19788 +Epoch: [32] [ 30/2138] eta: 2:33:48 lr: 1.1727027339940956e-05 loss: 0.0176 (0.0187) time: 4.0524 data: 0.0027 max mem: 19788 +Epoch: [32] [ 40/2138] eta: 2:30:16 lr: 1.1720845278342888e-05 loss: 0.0200 (0.0201) time: 4.0484 data: 0.0034 max mem: 19788 +Epoch: [32] [ 50/2138] eta: 2:27:50 lr: 1.1714662854426177e-05 loss: 0.0215 (0.0203) time: 4.0474 data: 0.0035 max mem: 19788 +Epoch: [32] [ 60/2138] eta: 2:25:55 lr: 1.170848006795709e-05 loss: 0.0181 (0.0199) time: 4.0401 data: 0.0037 max mem: 19788 +Epoch: [32] [ 70/2138] eta: 2:24:23 lr: 1.170229691870163e-05 loss: 0.0174 (0.0196) time: 4.0401 data: 0.0035 max mem: 19788 +Epoch: [32] [ 80/2138] eta: 2:23:00 lr: 1.169611340642549e-05 loss: 0.0184 (0.0199) time: 4.0349 data: 0.0033 max mem: 19788 +Epoch: [32] [ 90/2138] eta: 2:21:48 lr: 1.1689929530894099e-05 loss: 0.0189 (0.0198) time: 4.0311 data: 0.0034 max mem: 19788 +Epoch: [32] [ 100/2138] eta: 2:20:42 lr: 1.1683745291872567e-05 loss: 0.0211 (0.0203) time: 4.0353 data: 0.0034 max mem: 19788 +Epoch: [32] [ 110/2138] eta: 2:19:42 lr: 1.1677560689125742e-05 loss: 0.0219 (0.0204) time: 4.0374 data: 0.0033 max mem: 19788 +Epoch: [32] [ 120/2138] eta: 2:18:44 lr: 1.1671375722418158e-05 loss: 0.0217 (0.0206) time: 4.0362 data: 0.0031 max mem: 19788 +Epoch: [32] [ 130/2138] eta: 2:17:50 lr: 1.1665190391514077e-05 loss: 0.0224 (0.0207) time: 4.0358 data: 0.0031 max mem: 19788 +Epoch: [32] [ 140/2138] eta: 2:16:57 lr: 1.1659004696177452e-05 loss: 0.0224 (0.0207) time: 4.0372 data: 0.0030 max mem: 19788 +Epoch: [32] [ 150/2138] eta: 2:16:05 lr: 1.1652818636171961e-05 loss: 0.0199 (0.0208) time: 4.0356 data: 0.0032 max mem: 19788 +Epoch: [32] [ 160/2138] eta: 2:15:15 lr: 1.1646632211260971e-05 loss: 0.0210 (0.0210) time: 4.0331 data: 0.0034 max mem: 19788 +Epoch: [32] [ 170/2138] eta: 2:14:25 lr: 1.1640445421207576e-05 loss: 0.0233 (0.0212) time: 4.0268 data: 0.0034 max mem: 19788 +Epoch: [32] [ 180/2138] eta: 2:13:34 lr: 1.1634258265774556e-05 loss: 0.0212 (0.0212) time: 4.0183 data: 0.0033 max mem: 19788 +Epoch: [32] [ 190/2138] eta: 2:12:47 lr: 1.1628070744724416e-05 loss: 0.0183 (0.0212) time: 4.0225 data: 0.0033 max mem: 19788 +Epoch: [32] [ 200/2138] eta: 2:12:01 lr: 1.1621882857819345e-05 loss: 0.0160 (0.0210) time: 4.0326 data: 0.0036 max mem: 19788 +Epoch: [32] [ 210/2138] eta: 2:11:14 lr: 1.1615694604821257e-05 loss: 0.0230 (0.0212) time: 4.0253 data: 0.0036 max mem: 19788 +Epoch: [32] [ 220/2138] eta: 2:10:27 lr: 1.1609505985491751e-05 loss: 0.0230 (0.0211) time: 4.0188 data: 0.0032 max mem: 19788 +Epoch: [32] [ 230/2138] eta: 2:09:42 lr: 1.1603316999592153e-05 loss: 0.0211 (0.0213) time: 4.0263 data: 0.0033 max mem: 19788 +Epoch: [32] [ 240/2138] eta: 2:08:57 lr: 1.1597127646883465e-05 loss: 0.0211 (0.0213) time: 4.0272 data: 0.0032 max mem: 19788 +Epoch: [32] [ 250/2138] eta: 2:08:14 lr: 1.1590937927126415e-05 loss: 0.0180 (0.0212) time: 4.0320 data: 0.0031 max mem: 19788 +Epoch: [32] [ 260/2138] eta: 2:07:30 lr: 1.1584747840081412e-05 loss: 0.0182 (0.0212) time: 4.0363 data: 0.0030 max mem: 19788 +Epoch: [32] [ 270/2138] eta: 2:06:45 lr: 1.1578557385508588e-05 loss: 0.0204 (0.0212) time: 4.0232 data: 0.0032 max mem: 19788 +Epoch: [32] [ 280/2138] eta: 2:06:01 lr: 1.1572366563167758e-05 loss: 0.0209 (0.0212) time: 4.0186 data: 0.0033 max mem: 19788 +Epoch: [32] [ 290/2138] eta: 2:05:17 lr: 1.1566175372818437e-05 loss: 0.0223 (0.0213) time: 4.0218 data: 0.0033 max mem: 19788 +Epoch: [32] [ 300/2138] eta: 2:04:34 lr: 1.1559983814219861e-05 loss: 0.0225 (0.0212) time: 4.0278 data: 0.0033 max mem: 19788 +Epoch: [32] [ 310/2138] eta: 2:03:51 lr: 1.1553791887130936e-05 loss: 0.0186 (0.0212) time: 4.0253 data: 0.0033 max mem: 19788 +Epoch: [32] [ 320/2138] eta: 2:03:08 lr: 1.1547599591310294e-05 loss: 0.0196 (0.0212) time: 4.0213 data: 0.0034 max mem: 19788 +Epoch: [32] [ 330/2138] eta: 2:02:25 lr: 1.1541406926516238e-05 loss: 0.0215 (0.0212) time: 4.0241 data: 0.0032 max mem: 19788 +Epoch: [32] [ 340/2138] eta: 2:01:42 lr: 1.1535213892506793e-05 loss: 0.0212 (0.0212) time: 4.0240 data: 0.0032 max mem: 19788 +Epoch: [32] [ 350/2138] eta: 2:01:00 lr: 1.1529020489039663e-05 loss: 0.0208 (0.0212) time: 4.0236 data: 0.0034 max mem: 19788 +Epoch: [32] [ 360/2138] eta: 2:00:17 lr: 1.1522826715872264e-05 loss: 0.0198 (0.0212) time: 4.0223 data: 0.0033 max mem: 19788 +Epoch: [32] [ 370/2138] eta: 1:59:35 lr: 1.1516632572761687e-05 loss: 0.0208 (0.0213) time: 4.0215 data: 0.0034 max mem: 19788 +Epoch: [32] [ 380/2138] eta: 1:58:53 lr: 1.1510438059464743e-05 loss: 0.0208 (0.0213) time: 4.0249 data: 0.0038 max mem: 19788 +Epoch: [32] [ 390/2138] eta: 1:58:11 lr: 1.1504243175737912e-05 loss: 0.0208 (0.0214) time: 4.0251 data: 0.0036 max mem: 19788 +Epoch: [32] [ 400/2138] eta: 1:57:29 lr: 1.149804792133739e-05 loss: 0.0219 (0.0214) time: 4.0282 data: 0.0034 max mem: 19788 +Epoch: [32] [ 410/2138] eta: 1:56:47 lr: 1.1491852296019051e-05 loss: 0.0225 (0.0215) time: 4.0235 data: 0.0033 max mem: 19788 +Epoch: [32] [ 420/2138] eta: 1:56:05 lr: 1.1485656299538476e-05 loss: 0.0225 (0.0215) time: 4.0228 data: 0.0032 max mem: 19788 +Epoch: [32] [ 430/2138] eta: 1:55:24 lr: 1.147945993165092e-05 loss: 0.0206 (0.0215) time: 4.0322 data: 0.0033 max mem: 19788 +Epoch: [32] [ 440/2138] eta: 1:54:42 lr: 1.1473263192111353e-05 loss: 0.0219 (0.0215) time: 4.0223 data: 0.0031 max mem: 19788 +Epoch: [32] [ 450/2138] eta: 1:54:01 lr: 1.1467066080674407e-05 loss: 0.0194 (0.0216) time: 4.0323 data: 0.0030 max mem: 19788 +Epoch: [32] [ 460/2138] eta: 1:53:20 lr: 1.146086859709444e-05 loss: 0.0220 (0.0216) time: 4.0432 data: 0.0030 max mem: 19788 +Epoch: [32] [ 470/2138] eta: 1:52:38 lr: 1.145467074112546e-05 loss: 0.0225 (0.0216) time: 4.0284 data: 0.0032 max mem: 19788 +Epoch: [32] [ 480/2138] eta: 1:51:57 lr: 1.1448472512521206e-05 loss: 0.0220 (0.0217) time: 4.0260 data: 0.0035 max mem: 19788 +Epoch: [32] [ 490/2138] eta: 1:51:16 lr: 1.1442273911035067e-05 loss: 0.0207 (0.0216) time: 4.0290 data: 0.0037 max mem: 19788 +Epoch: [32] [ 500/2138] eta: 1:50:34 lr: 1.1436074936420154e-05 loss: 0.0205 (0.0216) time: 4.0245 data: 0.0036 max mem: 19788 +Epoch: [32] [ 510/2138] eta: 1:49:53 lr: 1.1429875588429235e-05 loss: 0.0209 (0.0216) time: 4.0231 data: 0.0034 max mem: 19788 +Epoch: [32] [ 520/2138] eta: 1:49:12 lr: 1.1423675866814797e-05 loss: 0.0218 (0.0216) time: 4.0222 data: 0.0032 max mem: 19788 +Epoch: [32] [ 530/2138] eta: 1:48:30 lr: 1.1417475771328982e-05 loss: 0.0203 (0.0216) time: 4.0219 data: 0.0033 max mem: 19788 +Epoch: [32] [ 540/2138] eta: 1:47:49 lr: 1.1411275301723643e-05 loss: 0.0193 (0.0216) time: 4.0225 data: 0.0032 max mem: 19788 +Epoch: [32] [ 550/2138] eta: 1:47:08 lr: 1.1405074457750299e-05 loss: 0.0201 (0.0216) time: 4.0262 data: 0.0031 max mem: 19788 +Epoch: [32] [ 560/2138] eta: 1:46:27 lr: 1.1398873239160174e-05 loss: 0.0201 (0.0215) time: 4.0312 data: 0.0031 max mem: 19788 +Epoch: [32] [ 570/2138] eta: 1:45:46 lr: 1.1392671645704152e-05 loss: 0.0187 (0.0215) time: 4.0355 data: 0.0030 max mem: 19788 +Epoch: [32] [ 580/2138] eta: 1:45:05 lr: 1.138646967713283e-05 loss: 0.0202 (0.0216) time: 4.0309 data: 0.0031 max mem: 19788 +Epoch: [32] [ 590/2138] eta: 1:44:24 lr: 1.1380267333196458e-05 loss: 0.0204 (0.0215) time: 4.0223 data: 0.0031 max mem: 19788 +Epoch: [32] [ 600/2138] eta: 1:43:43 lr: 1.1374064613644984e-05 loss: 0.0200 (0.0216) time: 4.0310 data: 0.0030 max mem: 19788 +Epoch: [32] [ 610/2138] eta: 1:43:02 lr: 1.1367861518228042e-05 loss: 0.0209 (0.0216) time: 4.0286 data: 0.0030 max mem: 19788 +Epoch: [32] [ 620/2138] eta: 1:42:21 lr: 1.1361658046694931e-05 loss: 0.0215 (0.0216) time: 4.0216 data: 0.0033 max mem: 19788 +Epoch: [32] [ 630/2138] eta: 1:41:40 lr: 1.1355454198794652e-05 loss: 0.0200 (0.0216) time: 4.0268 data: 0.0036 max mem: 19788 +Epoch: [32] [ 640/2138] eta: 1:40:59 lr: 1.1349249974275868e-05 loss: 0.0197 (0.0216) time: 4.0214 data: 0.0035 max mem: 19788 +Epoch: [32] [ 650/2138] eta: 1:40:18 lr: 1.1343045372886932e-05 loss: 0.0191 (0.0216) time: 4.0175 data: 0.0034 max mem: 19788 +Epoch: [32] [ 660/2138] eta: 1:39:37 lr: 1.1336840394375864e-05 loss: 0.0190 (0.0216) time: 4.0246 data: 0.0035 max mem: 19788 +Epoch: [32] [ 670/2138] eta: 1:38:56 lr: 1.133063503849038e-05 loss: 0.0220 (0.0216) time: 4.0221 data: 0.0035 max mem: 19788 +Epoch: [32] [ 680/2138] eta: 1:38:15 lr: 1.1324429304977855e-05 loss: 0.0226 (0.0216) time: 4.0204 data: 0.0034 max mem: 19788 +Epoch: [32] [ 690/2138] eta: 1:37:35 lr: 1.131822319358536e-05 loss: 0.0208 (0.0216) time: 4.0278 data: 0.0034 max mem: 19788 +Epoch: [32] [ 700/2138] eta: 1:36:54 lr: 1.131201670405962e-05 loss: 0.0208 (0.0216) time: 4.0262 data: 0.0034 max mem: 19788 +Epoch: [32] [ 710/2138] eta: 1:36:13 lr: 1.1305809836147057e-05 loss: 0.0226 (0.0216) time: 4.0246 data: 0.0035 max mem: 19788 +Epoch: [32] [ 720/2138] eta: 1:35:32 lr: 1.1299602589593749e-05 loss: 0.0211 (0.0216) time: 4.0262 data: 0.0034 max mem: 19788 +Epoch: [32] [ 730/2138] eta: 1:34:52 lr: 1.129339496414547e-05 loss: 0.0205 (0.0217) time: 4.0257 data: 0.0033 max mem: 19788 +Epoch: [32] [ 740/2138] eta: 1:34:11 lr: 1.1287186959547647e-05 loss: 0.0201 (0.0217) time: 4.0193 data: 0.0034 max mem: 19788 +Epoch: [32] [ 750/2138] eta: 1:33:30 lr: 1.1280978575545399e-05 loss: 0.0201 (0.0217) time: 4.0199 data: 0.0034 max mem: 19788 +Epoch: [32] [ 760/2138] eta: 1:32:49 lr: 1.1274769811883493e-05 loss: 0.0226 (0.0217) time: 4.0208 data: 0.0034 max mem: 19788 +Epoch: [32] [ 770/2138] eta: 1:32:08 lr: 1.1268560668306401e-05 loss: 0.0223 (0.0217) time: 4.0177 data: 0.0034 max mem: 19788 +Epoch: [32] [ 780/2138] eta: 1:31:27 lr: 1.1262351144558233e-05 loss: 0.0223 (0.0218) time: 4.0228 data: 0.0033 max mem: 19788 +Epoch: [32] [ 790/2138] eta: 1:30:47 lr: 1.12561412403828e-05 loss: 0.0193 (0.0218) time: 4.0218 data: 0.0033 max mem: 19788 +Epoch: [32] [ 800/2138] eta: 1:30:06 lr: 1.1249930955523552e-05 loss: 0.0193 (0.0218) time: 4.0209 data: 0.0036 max mem: 19788 +Epoch: [32] [ 810/2138] eta: 1:29:25 lr: 1.1243720289723644e-05 loss: 0.0200 (0.0217) time: 4.0246 data: 0.0036 max mem: 19788 +Epoch: [32] [ 820/2138] eta: 1:28:44 lr: 1.1237509242725863e-05 loss: 0.0200 (0.0218) time: 4.0221 data: 0.0040 max mem: 19788 +Epoch: [32] [ 830/2138] eta: 1:28:04 lr: 1.1231297814272698e-05 loss: 0.0169 (0.0217) time: 4.0206 data: 0.0038 max mem: 19788 +Epoch: [32] [ 840/2138] eta: 1:27:23 lr: 1.1225086004106277e-05 loss: 0.0174 (0.0217) time: 4.0307 data: 0.0034 max mem: 19788 +Epoch: [32] [ 850/2138] eta: 1:26:43 lr: 1.1218873811968419e-05 loss: 0.0187 (0.0217) time: 4.0257 data: 0.0036 max mem: 19788 +Epoch: [32] [ 860/2138] eta: 1:26:02 lr: 1.1212661237600589e-05 loss: 0.0195 (0.0217) time: 4.0221 data: 0.0033 max mem: 19788 +Epoch: [32] [ 870/2138] eta: 1:25:22 lr: 1.1206448280743937e-05 loss: 0.0224 (0.0217) time: 4.0306 data: 0.0033 max mem: 19788 +Epoch: [32] [ 880/2138] eta: 1:24:41 lr: 1.1200234941139256e-05 loss: 0.0207 (0.0217) time: 4.0235 data: 0.0033 max mem: 19788 +Epoch: [32] [ 890/2138] eta: 1:24:00 lr: 1.119402121852703e-05 loss: 0.0205 (0.0217) time: 4.0183 data: 0.0033 max mem: 19788 +Epoch: [32] [ 900/2138] eta: 1:23:20 lr: 1.1187807112647387e-05 loss: 0.0231 (0.0217) time: 4.0250 data: 0.0034 max mem: 19788 +Epoch: [32] [ 910/2138] eta: 1:22:39 lr: 1.1181592623240113e-05 loss: 0.0210 (0.0217) time: 4.0227 data: 0.0033 max mem: 19788 +Epoch: [32] [ 920/2138] eta: 1:21:58 lr: 1.1175377750044683e-05 loss: 0.0210 (0.0218) time: 4.0204 data: 0.0033 max mem: 19788 +Epoch: [32] [ 930/2138] eta: 1:21:18 lr: 1.1169162492800207e-05 loss: 0.0225 (0.0218) time: 4.0359 data: 0.0034 max mem: 19788 +Epoch: [32] [ 940/2138] eta: 1:20:38 lr: 1.116294685124548e-05 loss: 0.0225 (0.0218) time: 4.0404 data: 0.0035 max mem: 19788 +Epoch: [32] [ 950/2138] eta: 1:19:58 lr: 1.1156730825118929e-05 loss: 0.0241 (0.0219) time: 4.0563 data: 0.0033 max mem: 19788 +Epoch: [32] [ 960/2138] eta: 1:19:17 lr: 1.1150514414158671e-05 loss: 0.0208 (0.0219) time: 4.0549 data: 0.0032 max mem: 19788 +Epoch: [32] [ 970/2138] eta: 1:18:37 lr: 1.1144297618102459e-05 loss: 0.0200 (0.0218) time: 4.0222 data: 0.0033 max mem: 19788 +Epoch: [32] [ 980/2138] eta: 1:17:56 lr: 1.1138080436687722e-05 loss: 0.0192 (0.0218) time: 4.0223 data: 0.0033 max mem: 19788 +Epoch: [32] [ 990/2138] eta: 1:17:16 lr: 1.113186286965153e-05 loss: 0.0211 (0.0218) time: 4.0300 data: 0.0033 max mem: 19788 +Epoch: [32] [1000/2138] eta: 1:16:35 lr: 1.112564491673063e-05 loss: 0.0238 (0.0218) time: 4.0228 data: 0.0031 max mem: 19788 +Epoch: [32] [1010/2138] eta: 1:15:55 lr: 1.1119426577661401e-05 loss: 0.0197 (0.0218) time: 4.0310 data: 0.0029 max mem: 19788 +Epoch: [32] [1020/2138] eta: 1:15:14 lr: 1.1113207852179907e-05 loss: 0.0180 (0.0218) time: 4.0374 data: 0.0031 max mem: 19788 +Epoch: [32] [1030/2138] eta: 1:14:34 lr: 1.1106988740021842e-05 loss: 0.0192 (0.0218) time: 4.0309 data: 0.0033 max mem: 19788 +Epoch: [32] [1040/2138] eta: 1:13:53 lr: 1.1100769240922571e-05 loss: 0.0192 (0.0218) time: 4.0280 data: 0.0032 max mem: 19788 +Epoch: [32] [1050/2138] eta: 1:13:13 lr: 1.10945493546171e-05 loss: 0.0201 (0.0218) time: 4.0251 data: 0.0031 max mem: 19788 +Epoch: [32] [1060/2138] eta: 1:12:32 lr: 1.1088329080840104e-05 loss: 0.0193 (0.0218) time: 4.0266 data: 0.0032 max mem: 19788 +Epoch: [32] [1070/2138] eta: 1:11:52 lr: 1.1082108419325892e-05 loss: 0.0193 (0.0218) time: 4.0294 data: 0.0033 max mem: 19788 +Epoch: [32] [1080/2138] eta: 1:11:11 lr: 1.1075887369808448e-05 loss: 0.0197 (0.0218) time: 4.0272 data: 0.0031 max mem: 19788 +Epoch: [32] [1090/2138] eta: 1:10:31 lr: 1.106966593202138e-05 loss: 0.0197 (0.0218) time: 4.0271 data: 0.0031 max mem: 19788 +Epoch: [32] [1100/2138] eta: 1:09:51 lr: 1.1063444105697974e-05 loss: 0.0226 (0.0218) time: 4.0380 data: 0.0031 max mem: 19788 +Epoch: [32] [1110/2138] eta: 1:09:10 lr: 1.105722189057114e-05 loss: 0.0226 (0.0218) time: 4.0354 data: 0.0032 max mem: 19788 +Epoch: [32] [1120/2138] eta: 1:08:30 lr: 1.1050999286373464e-05 loss: 0.0194 (0.0218) time: 4.0264 data: 0.0034 max mem: 19788 +Epoch: [32] [1130/2138] eta: 1:07:49 lr: 1.1044776292837155e-05 loss: 0.0214 (0.0218) time: 4.0371 data: 0.0036 max mem: 19788 +Epoch: [32] [1140/2138] eta: 1:07:09 lr: 1.103855290969409e-05 loss: 0.0212 (0.0218) time: 4.0523 data: 0.0033 max mem: 19788 +Epoch: [32] [1150/2138] eta: 1:06:29 lr: 1.1032329136675778e-05 loss: 0.0202 (0.0217) time: 4.0548 data: 0.0032 max mem: 19788 +Epoch: [32] [1160/2138] eta: 1:05:49 lr: 1.1026104973513391e-05 loss: 0.0193 (0.0217) time: 4.0489 data: 0.0035 max mem: 19788 +Epoch: [32] [1170/2138] eta: 1:05:08 lr: 1.1019880419937727e-05 loss: 0.0200 (0.0217) time: 4.0426 data: 0.0035 max mem: 19788 +Epoch: [32] [1180/2138] eta: 1:04:28 lr: 1.1013655475679249e-05 loss: 0.0211 (0.0217) time: 4.0358 data: 0.0036 max mem: 19788 +Epoch: [32] [1190/2138] eta: 1:03:47 lr: 1.1007430140468045e-05 loss: 0.0230 (0.0217) time: 4.0296 data: 0.0037 max mem: 19788 +Epoch: [32] [1200/2138] eta: 1:03:07 lr: 1.100120441403387e-05 loss: 0.0208 (0.0217) time: 4.0274 data: 0.0032 max mem: 19788 +Epoch: [32] [1210/2138] eta: 1:02:26 lr: 1.0994978296106102e-05 loss: 0.0205 (0.0217) time: 4.0366 data: 0.0034 max mem: 19788 +Epoch: [32] [1220/2138] eta: 1:01:46 lr: 1.0988751786413762e-05 loss: 0.0206 (0.0217) time: 4.0476 data: 0.0036 max mem: 19788 +Epoch: [32] [1230/2138] eta: 1:01:06 lr: 1.0982524884685531e-05 loss: 0.0180 (0.0217) time: 4.0487 data: 0.0034 max mem: 19788 +Epoch: [32] [1240/2138] eta: 1:00:26 lr: 1.097629759064971e-05 loss: 0.0180 (0.0217) time: 4.0499 data: 0.0034 max mem: 19788 +Epoch: [32] [1250/2138] eta: 0:59:45 lr: 1.0970069904034259e-05 loss: 0.0197 (0.0217) time: 4.0514 data: 0.0035 max mem: 19788 +Epoch: [32] [1260/2138] eta: 0:59:05 lr: 1.0963841824566754e-05 loss: 0.0202 (0.0218) time: 4.0497 data: 0.0036 max mem: 19788 +Epoch: [32] [1270/2138] eta: 0:58:25 lr: 1.0957613351974443e-05 loss: 0.0190 (0.0217) time: 4.0422 data: 0.0033 max mem: 19788 +Epoch: [32] [1280/2138] eta: 0:57:44 lr: 1.0951384485984174e-05 loss: 0.0198 (0.0218) time: 4.0433 data: 0.0033 max mem: 19788 +Epoch: [32] [1290/2138] eta: 0:57:04 lr: 1.0945155226322469e-05 loss: 0.0202 (0.0217) time: 4.0500 data: 0.0033 max mem: 19788 +Epoch: [32] [1300/2138] eta: 0:56:24 lr: 1.0938925572715454e-05 loss: 0.0191 (0.0218) time: 4.0456 data: 0.0032 max mem: 19788 +Epoch: [32] [1310/2138] eta: 0:55:43 lr: 1.093269552488892e-05 loss: 0.0217 (0.0217) time: 4.0377 data: 0.0033 max mem: 19788 +Epoch: [32] [1320/2138] eta: 0:55:03 lr: 1.092646508256827e-05 loss: 0.0217 (0.0218) time: 4.0347 data: 0.0035 max mem: 19788 +Epoch: [32] [1330/2138] eta: 0:54:22 lr: 1.0920234245478561e-05 loss: 0.0204 (0.0218) time: 4.0279 data: 0.0036 max mem: 19788 +Epoch: [32] [1340/2138] eta: 0:53:42 lr: 1.0914003013344463e-05 loss: 0.0207 (0.0218) time: 4.0317 data: 0.0035 max mem: 19788 +Epoch: [32] [1350/2138] eta: 0:53:02 lr: 1.0907771385890303e-05 loss: 0.0248 (0.0218) time: 4.0528 data: 0.0032 max mem: 19788 +Epoch: [32] [1360/2138] eta: 0:52:22 lr: 1.0901539362840016e-05 loss: 0.0242 (0.0218) time: 4.0649 data: 0.0030 max mem: 19788 +Epoch: [32] [1370/2138] eta: 0:51:41 lr: 1.0895306943917194e-05 loss: 0.0197 (0.0218) time: 4.0801 data: 0.0033 max mem: 19788 +Epoch: [32] [1380/2138] eta: 0:51:01 lr: 1.0889074128845034e-05 loss: 0.0207 (0.0219) time: 4.0898 data: 0.0032 max mem: 19788 +Epoch: [32] [1390/2138] eta: 0:50:21 lr: 1.0882840917346387e-05 loss: 0.0226 (0.0219) time: 4.0857 data: 0.0032 max mem: 19788 +Epoch: [32] [1400/2138] eta: 0:49:41 lr: 1.0876607309143715e-05 loss: 0.0214 (0.0219) time: 4.0847 data: 0.0035 max mem: 19788 +Epoch: [32] [1410/2138] eta: 0:49:01 lr: 1.0870373303959125e-05 loss: 0.0190 (0.0218) time: 4.0860 data: 0.0035 max mem: 19788 +Epoch: [32] [1420/2138] eta: 0:48:21 lr: 1.0864138901514332e-05 loss: 0.0175 (0.0218) time: 4.0789 data: 0.0034 max mem: 19788 +Epoch: [32] [1430/2138] eta: 0:47:40 lr: 1.0857904101530706e-05 loss: 0.0220 (0.0218) time: 4.0791 data: 0.0032 max mem: 19788 +Epoch: [32] [1440/2138] eta: 0:47:00 lr: 1.085166890372921e-05 loss: 0.0211 (0.0218) time: 4.0811 data: 0.0033 max mem: 19788 +Epoch: [32] [1450/2138] eta: 0:46:20 lr: 1.0845433307830467e-05 loss: 0.0237 (0.0219) time: 4.0725 data: 0.0035 max mem: 19788 +Epoch: [32] [1460/2138] eta: 0:45:40 lr: 1.0839197313554697e-05 loss: 0.0239 (0.0219) time: 4.0811 data: 0.0035 max mem: 19788 +Epoch: [32] [1470/2138] eta: 0:44:59 lr: 1.0832960920621765e-05 loss: 0.0211 (0.0219) time: 4.0834 data: 0.0033 max mem: 19788 +Epoch: [32] [1480/2138] eta: 0:44:19 lr: 1.0826724128751142e-05 loss: 0.0219 (0.0219) time: 4.0838 data: 0.0032 max mem: 19788 +Epoch: [32] [1490/2138] eta: 0:43:39 lr: 1.0820486937661941e-05 loss: 0.0226 (0.0219) time: 4.0894 data: 0.0032 max mem: 19788 +Epoch: [32] [1500/2138] eta: 0:42:59 lr: 1.0814249347072883e-05 loss: 0.0199 (0.0219) time: 4.0844 data: 0.0035 max mem: 19788 +Epoch: [32] [1510/2138] eta: 0:42:19 lr: 1.0808011356702307e-05 loss: 0.0215 (0.0219) time: 4.0844 data: 0.0034 max mem: 19788 +Epoch: [32] [1520/2138] eta: 0:41:38 lr: 1.0801772966268192e-05 loss: 0.0187 (0.0219) time: 4.0762 data: 0.0032 max mem: 19788 +Epoch: [32] [1530/2138] eta: 0:40:58 lr: 1.0795534175488115e-05 loss: 0.0180 (0.0218) time: 4.0636 data: 0.0035 max mem: 19788 +Epoch: [32] [1540/2138] eta: 0:40:17 lr: 1.0789294984079292e-05 loss: 0.0180 (0.0218) time: 4.0611 data: 0.0036 max mem: 19788 +Epoch: [32] [1550/2138] eta: 0:39:37 lr: 1.0783055391758536e-05 loss: 0.0193 (0.0218) time: 4.0463 data: 0.0035 max mem: 19788 +Epoch: [32] [1560/2138] eta: 0:38:57 lr: 1.0776815398242302e-05 loss: 0.0202 (0.0218) time: 4.0346 data: 0.0033 max mem: 19788 +Epoch: [32] [1570/2138] eta: 0:38:16 lr: 1.0770575003246636e-05 loss: 0.0199 (0.0218) time: 4.0430 data: 0.0033 max mem: 19788 +Epoch: [32] [1580/2138] eta: 0:37:36 lr: 1.0764334206487226e-05 loss: 0.0196 (0.0218) time: 4.0465 data: 0.0033 max mem: 19788 +Epoch: [32] [1590/2138] eta: 0:36:55 lr: 1.0758093007679352e-05 loss: 0.0212 (0.0218) time: 4.0527 data: 0.0033 max mem: 19788 +Epoch: [32] [1600/2138] eta: 0:36:15 lr: 1.0751851406537929e-05 loss: 0.0237 (0.0218) time: 4.0536 data: 0.0034 max mem: 19788 +Epoch: [32] [1610/2138] eta: 0:35:34 lr: 1.0745609402777465e-05 loss: 0.0222 (0.0219) time: 4.0474 data: 0.0036 max mem: 19788 +Epoch: [32] [1620/2138] eta: 0:34:54 lr: 1.0739366996112102e-05 loss: 0.0181 (0.0219) time: 4.0408 data: 0.0034 max mem: 19788 +Epoch: [32] [1630/2138] eta: 0:34:14 lr: 1.0733124186255577e-05 loss: 0.0207 (0.0219) time: 4.0348 data: 0.0031 max mem: 19788 +Epoch: [32] [1640/2138] eta: 0:33:33 lr: 1.0726880972921253e-05 loss: 0.0207 (0.0218) time: 4.0389 data: 0.0030 max mem: 19788 +Epoch: [32] [1650/2138] eta: 0:32:53 lr: 1.0720637355822087e-05 loss: 0.0190 (0.0218) time: 4.0371 data: 0.0030 max mem: 19788 +Epoch: [32] [1660/2138] eta: 0:32:12 lr: 1.0714393334670665e-05 loss: 0.0170 (0.0218) time: 4.0388 data: 0.0033 max mem: 19788 +Epoch: [32] [1670/2138] eta: 0:31:32 lr: 1.0708148909179163e-05 loss: 0.0168 (0.0218) time: 4.0398 data: 0.0033 max mem: 19788 +Epoch: [32] [1680/2138] eta: 0:30:51 lr: 1.0701904079059386e-05 loss: 0.0221 (0.0218) time: 4.0380 data: 0.0032 max mem: 19788 +Epoch: [32] [1690/2138] eta: 0:30:11 lr: 1.0695658844022724e-05 loss: 0.0215 (0.0218) time: 4.0430 data: 0.0033 max mem: 19788 +Epoch: [32] [1700/2138] eta: 0:29:30 lr: 1.0689413203780196e-05 loss: 0.0196 (0.0218) time: 4.0436 data: 0.0033 max mem: 19788 +Epoch: [32] [1710/2138] eta: 0:28:50 lr: 1.0683167158042405e-05 loss: 0.0200 (0.0218) time: 4.0430 data: 0.0031 max mem: 19788 +Epoch: [32] [1720/2138] eta: 0:28:10 lr: 1.0676920706519582e-05 loss: 0.0210 (0.0218) time: 4.0508 data: 0.0032 max mem: 19788 +Epoch: [32] [1730/2138] eta: 0:27:29 lr: 1.0670673848921538e-05 loss: 0.0210 (0.0218) time: 4.0520 data: 0.0037 max mem: 19788 +Epoch: [32] [1740/2138] eta: 0:26:49 lr: 1.0664426584957715e-05 loss: 0.0203 (0.0218) time: 4.0480 data: 0.0037 max mem: 19788 +Epoch: [32] [1750/2138] eta: 0:26:08 lr: 1.0658178914337125e-05 loss: 0.0222 (0.0218) time: 4.0463 data: 0.0033 max mem: 19788 +Epoch: [32] [1760/2138] eta: 0:25:28 lr: 1.065193083676842e-05 loss: 0.0222 (0.0218) time: 4.0473 data: 0.0032 max mem: 19788 +Epoch: [32] [1770/2138] eta: 0:24:48 lr: 1.0645682351959818e-05 loss: 0.0212 (0.0218) time: 4.0478 data: 0.0034 max mem: 19788 +Epoch: [32] [1780/2138] eta: 0:24:07 lr: 1.0639433459619163e-05 loss: 0.0195 (0.0218) time: 4.0447 data: 0.0033 max mem: 19788 +Epoch: [32] [1790/2138] eta: 0:23:27 lr: 1.0633184159453877e-05 loss: 0.0195 (0.0218) time: 4.0521 data: 0.0032 max mem: 19788 +Epoch: [32] [1800/2138] eta: 0:22:46 lr: 1.0626934451171006e-05 loss: 0.0181 (0.0218) time: 4.0514 data: 0.0032 max mem: 19788 +Epoch: [32] [1810/2138] eta: 0:22:06 lr: 1.0620684334477174e-05 loss: 0.0190 (0.0218) time: 4.0495 data: 0.0033 max mem: 19788 +Epoch: [32] [1820/2138] eta: 0:21:25 lr: 1.06144338090786e-05 loss: 0.0206 (0.0218) time: 4.0422 data: 0.0036 max mem: 19788 +Epoch: [32] [1830/2138] eta: 0:20:45 lr: 1.0608182874681121e-05 loss: 0.0206 (0.0218) time: 4.0296 data: 0.0036 max mem: 19788 +Epoch: [32] [1840/2138] eta: 0:20:04 lr: 1.0601931530990142e-05 loss: 0.0224 (0.0218) time: 4.0262 data: 0.0035 max mem: 19788 +Epoch: [32] [1850/2138] eta: 0:19:24 lr: 1.0595679777710694e-05 loss: 0.0218 (0.0218) time: 4.0257 data: 0.0035 max mem: 19788 +Epoch: [32] [1860/2138] eta: 0:18:44 lr: 1.0589427614547365e-05 loss: 0.0211 (0.0218) time: 4.0337 data: 0.0035 max mem: 19788 +Epoch: [32] [1870/2138] eta: 0:18:03 lr: 1.0583175041204372e-05 loss: 0.0211 (0.0218) time: 4.0356 data: 0.0035 max mem: 19788 +Epoch: [32] [1880/2138] eta: 0:17:23 lr: 1.0576922057385495e-05 loss: 0.0196 (0.0218) time: 4.0372 data: 0.0034 max mem: 19788 +Epoch: [32] [1890/2138] eta: 0:16:42 lr: 1.0570668662794131e-05 loss: 0.0188 (0.0218) time: 4.0449 data: 0.0034 max mem: 19788 +Epoch: [32] [1900/2138] eta: 0:16:02 lr: 1.056441485713324e-05 loss: 0.0204 (0.0218) time: 4.0397 data: 0.0031 max mem: 19788 +Epoch: [32] [1910/2138] eta: 0:15:21 lr: 1.0558160640105401e-05 loss: 0.0205 (0.0218) time: 4.0371 data: 0.0030 max mem: 19788 +Epoch: [32] [1920/2138] eta: 0:14:41 lr: 1.0551906011412754e-05 loss: 0.0188 (0.0218) time: 4.0466 data: 0.0032 max mem: 19788 +Epoch: [32] [1930/2138] eta: 0:14:00 lr: 1.0545650970757054e-05 loss: 0.0191 (0.0218) time: 4.0369 data: 0.0033 max mem: 19788 +Epoch: [32] [1940/2138] eta: 0:13:20 lr: 1.0539395517839615e-05 loss: 0.0206 (0.0218) time: 4.0244 data: 0.0033 max mem: 19788 +Epoch: [32] [1950/2138] eta: 0:12:40 lr: 1.0533139652361363e-05 loss: 0.0209 (0.0218) time: 4.0293 data: 0.0032 max mem: 19788 +Epoch: [32] [1960/2138] eta: 0:11:59 lr: 1.0526883374022791e-05 loss: 0.0207 (0.0218) time: 4.0307 data: 0.0032 max mem: 19788 +Epoch: [32] [1970/2138] eta: 0:11:19 lr: 1.0520626682523992e-05 loss: 0.0206 (0.0218) time: 4.0253 data: 0.0031 max mem: 19788 +Epoch: [32] [1980/2138] eta: 0:10:38 lr: 1.0514369577564623e-05 loss: 0.0199 (0.0218) time: 4.0233 data: 0.0030 max mem: 19788 +Epoch: [32] [1990/2138] eta: 0:09:58 lr: 1.0508112058843948e-05 loss: 0.0194 (0.0217) time: 4.0355 data: 0.0033 max mem: 19788 +Epoch: [32] [2000/2138] eta: 0:09:17 lr: 1.050185412606079e-05 loss: 0.0203 (0.0217) time: 4.0402 data: 0.0033 max mem: 19788 +Epoch: [32] [2010/2138] eta: 0:08:37 lr: 1.0495595778913575e-05 loss: 0.0204 (0.0217) time: 4.0377 data: 0.0035 max mem: 19788 +Epoch: [32] [2020/2138] eta: 0:07:57 lr: 1.0489337017100285e-05 loss: 0.0222 (0.0218) time: 4.0411 data: 0.0036 max mem: 19788 +Epoch: [32] [2030/2138] eta: 0:07:16 lr: 1.048307784031851e-05 loss: 0.0224 (0.0218) time: 4.0423 data: 0.0035 max mem: 19788 +Epoch: [32] [2040/2138] eta: 0:06:36 lr: 1.047681824826539e-05 loss: 0.0204 (0.0218) time: 4.0334 data: 0.0034 max mem: 19788 +Epoch: [32] [2050/2138] eta: 0:05:55 lr: 1.0470558240637667e-05 loss: 0.0196 (0.0218) time: 4.0282 data: 0.0031 max mem: 19788 +Epoch: [32] [2060/2138] eta: 0:05:15 lr: 1.0464297817131638e-05 loss: 0.0188 (0.0218) time: 4.0251 data: 0.0030 max mem: 19788 +Epoch: [32] [2070/2138] eta: 0:04:34 lr: 1.04580369774432e-05 loss: 0.0186 (0.0218) time: 4.0208 data: 0.0031 max mem: 19788 +Epoch: [32] [2080/2138] eta: 0:03:54 lr: 1.0451775721267798e-05 loss: 0.0195 (0.0217) time: 4.0378 data: 0.0034 max mem: 19788 +Epoch: [32] [2090/2138] eta: 0:03:14 lr: 1.044551404830048e-05 loss: 0.0200 (0.0217) time: 4.0455 data: 0.0035 max mem: 19788 +Epoch: [32] [2100/2138] eta: 0:02:33 lr: 1.043925195823584e-05 loss: 0.0196 (0.0217) time: 4.0349 data: 0.0033 max mem: 19788 +Epoch: [32] [2110/2138] eta: 0:01:53 lr: 1.0432989450768071e-05 loss: 0.0212 (0.0218) time: 4.0243 data: 0.0033 max mem: 19788 +Epoch: [32] [2120/2138] eta: 0:01:12 lr: 1.0426726525590917e-05 loss: 0.0261 (0.0218) time: 4.0257 data: 0.0034 max mem: 19788 +Epoch: [32] [2130/2138] eta: 0:00:32 lr: 1.0420463182397695e-05 loss: 0.0238 (0.0218) time: 4.0197 data: 0.0032 max mem: 19788 +Epoch: [32] Total time: 2:24:02 +Test: [ 0/21770] eta: 20:26:59 time: 3.3817 data: 3.1515 max mem: 19788 +Test: [ 100/21770] eta: 0:34:33 time: 0.0657 data: 0.0021 max mem: 19788 +Test: [ 200/21770] eta: 0:30:00 time: 0.0755 data: 0.0024 max mem: 19788 +Test: [ 300/21770] eta: 0:27:46 time: 0.0636 data: 0.0017 max mem: 19788 +Test: [ 400/21770] eta: 0:26:44 time: 0.0682 data: 0.0021 max mem: 19788 +Test: [ 500/21770] eta: 0:25:50 time: 0.0616 data: 0.0019 max mem: 19788 +Test: [ 600/21770] eta: 0:25:20 time: 0.0794 data: 0.0026 max mem: 19788 +Test: [ 700/21770] eta: 0:24:57 time: 0.0629 data: 0.0020 max mem: 19788 +Test: [ 800/21770] eta: 0:24:42 time: 0.0729 data: 0.0022 max mem: 19788 +Test: [ 900/21770] eta: 0:24:37 time: 0.0644 data: 0.0019 max mem: 19788 +Test: [ 1000/21770] eta: 0:24:21 time: 0.0651 data: 0.0019 max mem: 19788 +Test: [ 1100/21770] eta: 0:24:11 time: 0.0653 data: 0.0020 max mem: 19788 +Test: [ 1200/21770] eta: 0:24:00 time: 0.0697 data: 0.0022 max mem: 19788 +Test: [ 1300/21770] eta: 0:23:52 time: 0.0754 data: 0.0023 max mem: 19788 +Test: [ 1400/21770] eta: 0:23:36 time: 0.0655 data: 0.0019 max mem: 19788 +Test: [ 1500/21770] eta: 0:23:30 time: 0.0698 data: 0.0022 max mem: 19788 +Test: [ 1600/21770] eta: 0:23:18 time: 0.0644 data: 0.0019 max mem: 19788 +Test: [ 1700/21770] eta: 0:23:06 time: 0.0644 data: 0.0018 max mem: 19788 +Test: [ 1800/21770] eta: 0:23:00 time: 0.0742 data: 0.0024 max mem: 19788 +Test: [ 1900/21770] eta: 0:22:48 time: 0.0648 data: 0.0019 max mem: 19788 +Test: [ 2000/21770] eta: 0:22:41 time: 0.0730 data: 0.0024 max mem: 19788 +Test: [ 2100/21770] eta: 0:22:32 time: 0.0733 data: 0.0024 max mem: 19788 +Test: [ 2200/21770] eta: 0:22:25 time: 0.0665 data: 0.0019 max mem: 19788 +Test: [ 2300/21770] eta: 0:22:20 time: 0.0640 data: 0.0018 max mem: 19788 +Test: [ 2400/21770] eta: 0:22:13 time: 0.0671 data: 0.0021 max mem: 19788 +Test: [ 2500/21770] eta: 0:22:07 time: 0.0652 data: 0.0019 max mem: 19788 +Test: [ 2600/21770] eta: 0:22:02 time: 0.0712 data: 0.0024 max mem: 19788 +Test: [ 2700/21770] eta: 0:22:01 time: 0.0736 data: 0.0023 max mem: 19788 +Test: [ 2800/21770] eta: 0:21:56 time: 0.0652 data: 0.0022 max mem: 19788 +Test: [ 2900/21770] eta: 0:21:52 time: 0.0644 data: 0.0020 max mem: 19788 +Test: [ 3000/21770] eta: 0:21:46 time: 0.0638 data: 0.0021 max mem: 19788 +Test: [ 3100/21770] eta: 0:21:42 time: 0.0818 data: 0.0026 max mem: 19788 +Test: [ 3200/21770] eta: 0:21:34 time: 0.0706 data: 0.0019 max mem: 19788 +Test: [ 3300/21770] eta: 0:21:28 time: 0.0658 data: 0.0019 max mem: 19788 +Test: [ 3400/21770] eta: 0:21:23 time: 0.0648 data: 0.0021 max mem: 19788 +Test: [ 3500/21770] eta: 0:21:17 time: 0.0688 data: 0.0019 max mem: 19788 +Test: [ 3600/21770] eta: 0:21:11 time: 0.0683 data: 0.0022 max mem: 19788 +Test: [ 3700/21770] eta: 0:21:04 time: 0.0798 data: 0.0025 max mem: 19788 +Test: [ 3800/21770] eta: 0:20:58 time: 0.0719 data: 0.0022 max mem: 19788 +Test: [ 3900/21770] eta: 0:20:51 time: 0.0667 data: 0.0019 max mem: 19788 +Test: [ 4000/21770] eta: 0:20:45 time: 0.0695 data: 0.0020 max mem: 19788 +Test: [ 4100/21770] eta: 0:20:36 time: 0.0686 data: 0.0022 max mem: 19788 +Test: [ 4200/21770] eta: 0:20:29 time: 0.0691 data: 0.0021 max mem: 19788 +Test: [ 4300/21770] eta: 0:20:25 time: 0.0683 data: 0.0021 max mem: 19788 +Test: [ 4400/21770] eta: 0:20:18 time: 0.0690 data: 0.0024 max mem: 19788 +Test: [ 4500/21770] eta: 0:20:13 time: 0.0739 data: 0.0023 max mem: 19788 +Test: [ 4600/21770] eta: 0:20:07 time: 0.0635 data: 0.0020 max mem: 19788 +Test: [ 4700/21770] eta: 0:19:59 time: 0.0698 data: 0.0026 max mem: 19788 +Test: [ 4800/21770] eta: 0:19:51 time: 0.0633 data: 0.0020 max mem: 19788 +Test: [ 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time: 0.0674 data: 0.0021 max mem: 19788 +Test: [ 6300/21770] eta: 0:18:07 time: 0.0655 data: 0.0019 max mem: 19788 +Test: [ 6400/21770] eta: 0:18:00 time: 0.0751 data: 0.0021 max mem: 19788 +Test: [ 6500/21770] eta: 0:17:54 time: 0.0863 data: 0.0025 max mem: 19788 +Test: [ 6600/21770] eta: 0:17:46 time: 0.0655 data: 0.0018 max mem: 19788 +Test: [ 6700/21770] eta: 0:17:38 time: 0.0649 data: 0.0020 max mem: 19788 +Test: [ 6800/21770] eta: 0:17:32 time: 0.0669 data: 0.0021 max mem: 19788 +Test: [ 6900/21770] eta: 0:17:25 time: 0.0674 data: 0.0020 max mem: 19788 +Test: [ 7000/21770] eta: 0:17:19 time: 0.0715 data: 0.0022 max mem: 19788 +Test: [ 7100/21770] eta: 0:17:13 time: 0.0833 data: 0.0026 max mem: 19788 +Test: [ 7200/21770] eta: 0:17:06 time: 0.0710 data: 0.0021 max mem: 19788 +Test: [ 7300/21770] eta: 0:17:01 time: 0.0655 data: 0.0020 max mem: 19788 +Test: [ 7400/21770] eta: 0:16:54 time: 0.0643 data: 0.0019 max mem: 19788 +Test: [ 7500/21770] eta: 0:16:47 time: 0.0672 data: 0.0018 max mem: 19788 +Test: [ 7600/21770] eta: 0:16:39 time: 0.0642 data: 0.0021 max mem: 19788 +Test: [ 7700/21770] eta: 0:16:32 time: 0.0660 data: 0.0019 max mem: 19788 +Test: [ 7800/21770] eta: 0:16:25 time: 0.0799 data: 0.0020 max mem: 19788 +Test: [ 7900/21770] eta: 0:16:18 time: 0.0660 data: 0.0022 max mem: 19788 +Test: [ 8000/21770] eta: 0:16:12 time: 0.0762 data: 0.0025 max mem: 19788 +Test: [ 8100/21770] eta: 0:16:04 time: 0.0688 data: 0.0020 max mem: 19788 +Test: [ 8200/21770] eta: 0:15:58 time: 0.0718 data: 0.0024 max mem: 19788 +Test: [ 8300/21770] eta: 0:15:52 time: 0.0735 data: 0.0022 max mem: 19788 +Test: [ 8400/21770] eta: 0:15:44 time: 0.0636 data: 0.0020 max mem: 19788 +Test: [ 8500/21770] eta: 0:15:36 time: 0.0710 data: 0.0020 max mem: 19788 +Test: [ 8600/21770] eta: 0:15:28 time: 0.0661 data: 0.0020 max mem: 19788 +Test: [ 8700/21770] eta: 0:15:22 time: 0.0740 data: 0.0021 max mem: 19788 +Test: [ 8800/21770] eta: 0:15:15 time: 0.0686 data: 0.0020 max mem: 19788 +Test: [ 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time: 0.0644 data: 0.0021 max mem: 19788 +Test: [10300/21770] eta: 0:13:32 time: 0.0728 data: 0.0023 max mem: 19788 +Test: [10400/21770] eta: 0:13:24 time: 0.0664 data: 0.0019 max mem: 19788 +Test: [10500/21770] eta: 0:13:17 time: 0.0795 data: 0.0023 max mem: 19788 +Test: [10600/21770] eta: 0:13:10 time: 0.0682 data: 0.0022 max mem: 19788 +Test: [10700/21770] eta: 0:13:03 time: 0.0698 data: 0.0020 max mem: 19788 +Test: [10800/21770] eta: 0:12:56 time: 0.0677 data: 0.0021 max mem: 19788 +Test: [10900/21770] eta: 0:12:49 time: 0.0766 data: 0.0024 max mem: 19788 +Test: [11000/21770] eta: 0:12:42 time: 0.0721 data: 0.0020 max mem: 19788 +Test: [11100/21770] eta: 0:12:35 time: 0.0712 data: 0.0020 max mem: 19788 +Test: [11200/21770] eta: 0:12:28 time: 0.0841 data: 0.0026 max mem: 19788 +Test: [11300/21770] eta: 0:12:22 time: 0.0648 data: 0.0021 max mem: 19788 +Test: [11400/21770] eta: 0:12:15 time: 0.0801 data: 0.0024 max mem: 19788 +Test: [11500/21770] eta: 0:12:07 time: 0.0779 data: 0.0024 max mem: 19788 +Test: [11600/21770] eta: 0:12:00 time: 0.0787 data: 0.0024 max mem: 19788 +Test: [11700/21770] eta: 0:11:53 time: 0.0722 data: 0.0022 max mem: 19788 +Test: [11800/21770] eta: 0:11:46 time: 0.0654 data: 0.0021 max mem: 19788 +Test: [11900/21770] eta: 0:11:38 time: 0.0835 data: 0.0026 max mem: 19788 +Test: [12000/21770] eta: 0:11:31 time: 0.0661 data: 0.0023 max mem: 19788 +Test: [12100/21770] eta: 0:11:24 time: 0.0816 data: 0.0026 max mem: 19788 +Test: [12200/21770] eta: 0:11:17 time: 0.0783 data: 0.0023 max mem: 19788 +Test: [12300/21770] eta: 0:11:10 time: 0.0774 data: 0.0021 max mem: 19788 +Test: [12400/21770] eta: 0:11:03 time: 0.0814 data: 0.0025 max mem: 19788 +Test: [12500/21770] eta: 0:10:57 time: 0.0862 data: 0.0027 max mem: 19788 +Test: [12600/21770] eta: 0:10:50 time: 0.0682 data: 0.0022 max mem: 19788 +Test: [12700/21770] eta: 0:10:43 time: 0.0846 data: 0.0025 max mem: 19788 +Test: [12800/21770] eta: 0:10:36 time: 0.0685 data: 0.0022 max mem: 19788 +Test: [12900/21770] eta: 0:10:29 time: 0.0805 data: 0.0026 max mem: 19788 +Test: [13000/21770] eta: 0:10:23 time: 0.0850 data: 0.0025 max mem: 19788 +Test: [13100/21770] eta: 0:10:16 time: 0.0659 data: 0.0020 max mem: 19788 +Test: [13200/21770] eta: 0:10:09 time: 0.0751 data: 0.0022 max mem: 19788 +Test: [13300/21770] eta: 0:10:01 time: 0.0660 data: 0.0020 max mem: 19788 +Test: [13400/21770] eta: 0:09:55 time: 0.0756 data: 0.0025 max mem: 19788 +Test: [13500/21770] eta: 0:09:48 time: 0.0826 data: 0.0022 max mem: 19788 +Test: [13600/21770] eta: 0:09:41 time: 0.0842 data: 0.0026 max mem: 19788 +Test: [13700/21770] eta: 0:09:34 time: 0.0640 data: 0.0020 max mem: 19788 +Test: [13800/21770] eta: 0:09:26 time: 0.0641 data: 0.0020 max mem: 19788 +Test: [13900/21770] eta: 0:09:19 time: 0.0840 data: 0.0025 max mem: 19788 +Test: [14000/21770] eta: 0:09:12 time: 0.0646 data: 0.0020 max mem: 19788 +Test: [14100/21770] eta: 0:09:05 time: 0.0652 data: 0.0020 max mem: 19788 +Test: [14200/21770] eta: 0:08:58 time: 0.0644 data: 0.0020 max mem: 19788 +Test: [14300/21770] eta: 0:08:51 time: 0.0648 data: 0.0021 max mem: 19788 +Test: [14400/21770] eta: 0:08:44 time: 0.0784 data: 0.0023 max mem: 19788 +Test: [14500/21770] eta: 0:08:37 time: 0.0769 data: 0.0023 max mem: 19788 +Test: [14600/21770] eta: 0:08:31 time: 0.0672 data: 0.0018 max mem: 19788 +Test: [14700/21770] eta: 0:08:24 time: 0.0734 data: 0.0020 max mem: 19788 +Test: [14800/21770] eta: 0:08:16 time: 0.0628 data: 0.0020 max mem: 19788 +Test: [14900/21770] eta: 0:08:09 time: 0.0668 data: 0.0019 max mem: 19788 +Test: [15000/21770] eta: 0:08:02 time: 0.0648 data: 0.0020 max mem: 19788 +Test: [15100/21770] eta: 0:07:55 time: 0.0851 data: 0.0026 max mem: 19788 +Test: [15200/21770] eta: 0:07:48 time: 0.0683 data: 0.0021 max mem: 19788 +Test: [15300/21770] eta: 0:07:41 time: 0.0663 data: 0.0019 max mem: 19788 +Test: [15400/21770] eta: 0:07:34 time: 0.0848 data: 0.0027 max mem: 19788 +Test: [15500/21770] eta: 0:07:27 time: 0.0830 data: 0.0025 max mem: 19788 +Test: [15600/21770] eta: 0:07:20 time: 0.0799 data: 0.0023 max mem: 19788 +Test: [15700/21770] eta: 0:07:13 time: 0.0726 data: 0.0021 max mem: 19788 +Test: [15800/21770] eta: 0:07:05 time: 0.0692 data: 0.0020 max mem: 19788 +Test: [15900/21770] eta: 0:06:59 time: 0.0838 data: 0.0025 max mem: 19788 +Test: [16000/21770] eta: 0:06:52 time: 0.0668 data: 0.0019 max mem: 19788 +Test: [16100/21770] eta: 0:06:44 time: 0.0719 data: 0.0021 max mem: 19788 +Test: [16200/21770] eta: 0:06:37 time: 0.0675 data: 0.0019 max mem: 19788 +Test: [16300/21770] eta: 0:06:30 time: 0.0648 data: 0.0019 max mem: 19788 +Test: [16400/21770] eta: 0:06:23 time: 0.0670 data: 0.0018 max mem: 19788 +Test: [16500/21770] eta: 0:06:15 time: 0.0726 data: 0.0023 max mem: 19788 +Test: [16600/21770] eta: 0:06:08 time: 0.0783 data: 0.0020 max mem: 19788 +Test: [16700/21770] eta: 0:06:02 time: 0.0860 data: 0.0021 max mem: 19788 +Test: [16800/21770] eta: 0:05:54 time: 0.0750 data: 0.0022 max mem: 19788 +Test: [16900/21770] eta: 0:05:47 time: 0.0674 data: 0.0022 max mem: 19788 +Test: [17000/21770] eta: 0:05:40 time: 0.0867 data: 0.0027 max mem: 19788 +Test: [17100/21770] eta: 0:05:33 time: 0.0647 data: 0.0026 max mem: 19788 +Test: [17200/21770] eta: 0:05:26 time: 0.0632 data: 0.0019 max mem: 19788 +Test: [17300/21770] eta: 0:05:19 time: 0.0733 data: 0.0022 max mem: 19788 +Test: [17400/21770] eta: 0:05:12 time: 0.0644 data: 0.0019 max mem: 19788 +Test: [17500/21770] eta: 0:05:04 time: 0.0669 data: 0.0023 max mem: 19788 +Test: [17600/21770] eta: 0:04:57 time: 0.0651 data: 0.0018 max mem: 19788 +Test: [17700/21770] eta: 0:04:50 time: 0.0759 data: 0.0023 max mem: 19788 +Test: [17800/21770] eta: 0:04:43 time: 0.0647 data: 0.0019 max mem: 19788 +Test: [17900/21770] eta: 0:04:36 time: 0.0701 data: 0.0020 max mem: 19788 +Test: [18000/21770] eta: 0:04:28 time: 0.0653 data: 0.0019 max mem: 19788 +Test: [18100/21770] eta: 0:04:21 time: 0.0679 data: 0.0020 max mem: 19788 +Test: [18200/21770] eta: 0:04:14 time: 0.0756 data: 0.0019 max mem: 19788 +Test: [18300/21770] eta: 0:04:07 time: 0.0666 data: 0.0021 max mem: 19788 +Test: [18400/21770] eta: 0:04:00 time: 0.0863 data: 0.0027 max mem: 19788 +Test: [18500/21770] eta: 0:03:53 time: 0.0862 data: 0.0028 max mem: 19788 +Test: [18600/21770] eta: 0:03:46 time: 0.0768 data: 0.0021 max mem: 19788 +Test: [18700/21770] eta: 0:03:39 time: 0.0618 data: 0.0018 max mem: 19788 +Test: [18800/21770] eta: 0:03:32 time: 0.0734 data: 0.0021 max mem: 19788 +Test: [18900/21770] eta: 0:03:25 time: 0.0687 data: 0.0020 max mem: 19788 +Test: [19000/21770] eta: 0:03:17 time: 0.0693 data: 0.0023 max mem: 19788 +Test: [19100/21770] eta: 0:03:10 time: 0.0759 data: 0.0023 max mem: 19788 +Test: [19200/21770] eta: 0:03:03 time: 0.0727 data: 0.0021 max mem: 19788 +Test: [19300/21770] eta: 0:02:56 time: 0.0713 data: 0.0018 max mem: 19788 +Test: [19400/21770] eta: 0:02:49 time: 0.0849 data: 0.0025 max mem: 19788 +Test: [19500/21770] eta: 0:02:42 time: 0.0667 data: 0.0023 max mem: 19788 +Test: [19600/21770] eta: 0:02:35 time: 0.0665 data: 0.0020 max mem: 19788 +Test: [19700/21770] eta: 0:02:27 time: 0.0800 data: 0.0025 max mem: 19788 +Test: [19800/21770] eta: 0:02:20 time: 0.0733 data: 0.0024 max mem: 19788 +Test: [19900/21770] eta: 0:02:13 time: 0.0739 data: 0.0023 max mem: 19788 +Test: [20000/21770] eta: 0:02:06 time: 0.0676 data: 0.0019 max mem: 19788 +Test: [20100/21770] eta: 0:01:59 time: 0.0834 data: 0.0027 max mem: 19788 +Test: [20200/21770] eta: 0:01:52 time: 0.0659 data: 0.0021 max mem: 19788 +Test: [20300/21770] eta: 0:01:45 time: 0.0630 data: 0.0019 max mem: 19788 +Test: [20400/21770] eta: 0:01:37 time: 0.0752 data: 0.0022 max mem: 19788 +Test: [20500/21770] eta: 0:01:30 time: 0.0643 data: 0.0024 max mem: 19788 +Test: [20600/21770] eta: 0:01:23 time: 0.0770 data: 0.0023 max mem: 19788 +Test: [20700/21770] eta: 0:01:16 time: 0.0687 data: 0.0020 max mem: 19788 +Test: [20800/21770] eta: 0:01:09 time: 0.0692 data: 0.0019 max mem: 19788 +Test: [20900/21770] eta: 0:01:02 time: 0.0853 data: 0.0025 max mem: 19788 +Test: [21000/21770] eta: 0:00:55 time: 0.0630 data: 0.0019 max mem: 19788 +Test: [21100/21770] eta: 0:00:47 time: 0.0648 data: 0.0018 max mem: 19788 +Test: [21200/21770] eta: 0:00:40 time: 0.0656 data: 0.0021 max mem: 19788 +Test: [21300/21770] eta: 0:00:33 time: 0.0665 data: 0.0020 max mem: 19788 +Test: [21400/21770] eta: 0:00:26 time: 0.0652 data: 0.0018 max mem: 19788 +Test: [21500/21770] eta: 0:00:19 time: 0.0698 data: 0.0023 max mem: 19788 +Test: [21600/21770] eta: 0:00:12 time: 0.0692 data: 0.0020 max mem: 19788 +Test: [21700/21770] eta: 0:00:04 time: 0.0793 data: 0.0027 max mem: 19788 +Test: Total time: 0:25:54 +Final results: +Mean IoU is 63.22 + + precision@0.5 = 70.01 + precision@0.6 = 64.66 + precision@0.7 = 58.41 + precision@0.8 = 47.88 + precision@0.9 = 23.84 + overall IoU = 64.04 + mean IoU = 63.22 + +Mean accuracy for one-to-zero sample is 85.95 + +Average object IoU 0.6321891796920854 +Overall IoU 64.04153442382812 +Better epoch: 32 + +Epoch: [33] [ 0/2138] eta: 10:27:57 lr: 1.041545220666519e-05 loss: 0.0198 (0.0198) time: 17.6227 data: 1.8604 max mem: 19788 +Epoch: [33] [ 10/2138] eta: 3:07:56 lr: 1.0409188110268857e-05 loss: 0.0171 (0.0174) time: 5.2989 data: 0.1723 max mem: 19788 +Epoch: [33] [ 20/2138] eta: 2:46:08 lr: 1.0402923594995464e-05 loss: 0.0171 (0.0182) time: 4.0609 data: 0.0028 max mem: 19788 +Epoch: [33] [ 30/2138] eta: 2:38:07 lr: 1.039665866053671e-05 loss: 0.0184 (0.0185) time: 4.0618 data: 0.0027 max mem: 19788 +Epoch: [33] [ 40/2138] eta: 2:33:28 lr: 1.0390393306583828e-05 loss: 0.0193 (0.0197) time: 4.0559 data: 0.0036 max mem: 19788 +Epoch: [33] [ 50/2138] eta: 2:30:21 lr: 1.0384127532827644e-05 loss: 0.0215 (0.0201) time: 4.0419 data: 0.0038 max mem: 19788 +Epoch: [33] [ 60/2138] eta: 2:28:06 lr: 1.0377861338958529e-05 loss: 0.0189 (0.0197) time: 4.0447 data: 0.0037 max mem: 19788 +Epoch: [33] [ 70/2138] eta: 2:26:13 lr: 1.0371594724666437e-05 loss: 0.0164 (0.0193) time: 4.0425 data: 0.0035 max mem: 19788 +Epoch: [33] [ 80/2138] eta: 2:24:39 lr: 1.036532768964086e-05 loss: 0.0169 (0.0198) time: 4.0375 data: 0.0032 max mem: 19788 +Epoch: [33] [ 90/2138] eta: 2:23:18 lr: 1.035906023357088e-05 loss: 0.0220 (0.0199) time: 4.0433 data: 0.0031 max mem: 19788 +Epoch: [33] [ 100/2138] eta: 2:22:03 lr: 1.0352792356145113e-05 loss: 0.0210 (0.0199) time: 4.0397 data: 0.0033 max mem: 19788 +Epoch: [33] [ 110/2138] eta: 2:20:54 lr: 1.0346524057051759e-05 loss: 0.0216 (0.0201) time: 4.0329 data: 0.0032 max mem: 19788 +Epoch: [33] [ 120/2138] eta: 2:19:49 lr: 1.0340255335978556e-05 loss: 0.0209 (0.0202) time: 4.0331 data: 0.0032 max mem: 19788 +Epoch: [33] [ 130/2138] eta: 2:18:51 lr: 1.0333986192612822e-05 loss: 0.0209 (0.0204) time: 4.0387 data: 0.0031 max mem: 19788 +Epoch: [33] [ 140/2138] eta: 2:17:52 lr: 1.0327716626641408e-05 loss: 0.0226 (0.0204) time: 4.0371 data: 0.0031 max mem: 19788 +Epoch: [33] [ 150/2138] eta: 2:16:59 lr: 1.0321446637750749e-05 loss: 0.0195 (0.0204) time: 4.0388 data: 0.0033 max mem: 19788 +Epoch: [33] [ 160/2138] eta: 2:16:06 lr: 1.0315176225626809e-05 loss: 0.0212 (0.0206) time: 4.0465 data: 0.0034 max mem: 19788 +Epoch: [33] [ 170/2138] eta: 2:15:13 lr: 1.0308905389955118e-05 loss: 0.0221 (0.0206) time: 4.0369 data: 0.0033 max mem: 19788 +Epoch: [33] [ 180/2138] eta: 2:14:23 lr: 1.030263413042077e-05 loss: 0.0221 (0.0207) time: 4.0348 data: 0.0031 max mem: 19788 +Epoch: [33] [ 190/2138] eta: 2:13:34 lr: 1.0296362446708388e-05 loss: 0.0216 (0.0208) time: 4.0414 data: 0.0032 max mem: 19788 +Epoch: [33] [ 200/2138] eta: 2:12:45 lr: 1.0290090338502176e-05 loss: 0.0154 (0.0205) time: 4.0381 data: 0.0035 max mem: 19788 +Epoch: [33] [ 210/2138] eta: 2:11:56 lr: 1.0283817805485857e-05 loss: 0.0237 (0.0208) time: 4.0277 data: 0.0034 max mem: 19788 +Epoch: [33] [ 220/2138] eta: 2:11:08 lr: 1.0277544847342734e-05 loss: 0.0231 (0.0207) time: 4.0237 data: 0.0033 max mem: 19788 +Epoch: [33] [ 230/2138] eta: 2:10:22 lr: 1.0271271463755634e-05 loss: 0.0209 (0.0208) time: 4.0321 data: 0.0032 max mem: 19788 +Epoch: [33] [ 240/2138] eta: 2:09:36 lr: 1.0264997654406953e-05 loss: 0.0215 (0.0210) time: 4.0391 data: 0.0033 max mem: 19788 +Epoch: [33] [ 250/2138] eta: 2:08:51 lr: 1.0258723418978613e-05 loss: 0.0190 (0.0209) time: 4.0391 data: 0.0032 max mem: 19788 +Epoch: [33] [ 260/2138] eta: 2:08:05 lr: 1.0252448757152108e-05 loss: 0.0188 (0.0209) time: 4.0338 data: 0.0030 max mem: 19788 +Epoch: [33] [ 270/2138] eta: 2:07:19 lr: 1.0246173668608443e-05 loss: 0.0186 (0.0210) time: 4.0239 data: 0.0031 max mem: 19788 +Epoch: [33] [ 280/2138] eta: 2:06:34 lr: 1.0239898153028202e-05 loss: 0.0193 (0.0209) time: 4.0215 data: 0.0033 max mem: 19788 +Epoch: [33] [ 290/2138] eta: 2:05:49 lr: 1.0233622210091488e-05 loss: 0.0214 (0.0209) time: 4.0220 data: 0.0033 max mem: 19788 +Epoch: [33] [ 300/2138] eta: 2:05:04 lr: 1.0227345839477961e-05 loss: 0.0197 (0.0209) time: 4.0239 data: 0.0031 max mem: 19788 +Epoch: [33] [ 310/2138] eta: 2:04:21 lr: 1.0221069040866808e-05 loss: 0.0181 (0.0208) time: 4.0377 data: 0.0034 max mem: 19788 +Epoch: [33] [ 320/2138] eta: 2:03:39 lr: 1.0214791813936774e-05 loss: 0.0193 (0.0208) time: 4.0500 data: 0.0033 max mem: 19788 +Epoch: [33] [ 330/2138] eta: 2:02:55 lr: 1.0208514158366122e-05 loss: 0.0200 (0.0210) time: 4.0422 data: 0.0032 max mem: 19788 +Epoch: [33] [ 340/2138] eta: 2:02:12 lr: 1.0202236073832678e-05 loss: 0.0200 (0.0209) time: 4.0339 data: 0.0034 max mem: 19788 +Epoch: [33] [ 350/2138] eta: 2:01:30 lr: 1.0195957560013777e-05 loss: 0.0204 (0.0209) time: 4.0375 data: 0.0033 max mem: 19788 +Epoch: [33] [ 360/2138] eta: 2:00:47 lr: 1.0189678616586323e-05 loss: 0.0221 (0.0209) time: 4.0385 data: 0.0032 max mem: 19788 +Epoch: [33] [ 370/2138] eta: 2:00:04 lr: 1.0183399243226719e-05 loss: 0.0206 (0.0210) time: 4.0355 data: 0.0034 max mem: 19788 +Epoch: [33] [ 380/2138] eta: 1:59:21 lr: 1.0177119439610941e-05 loss: 0.0199 (0.0210) time: 4.0306 data: 0.0037 max mem: 19788 +Epoch: [33] [ 390/2138] eta: 1:58:39 lr: 1.017083920541446e-05 loss: 0.0197 (0.0210) time: 4.0301 data: 0.0036 max mem: 19788 +Epoch: [33] [ 400/2138] eta: 1:57:56 lr: 1.0164558540312316e-05 loss: 0.0215 (0.0210) time: 4.0279 data: 0.0035 max mem: 19788 +Epoch: [33] [ 410/2138] eta: 1:57:13 lr: 1.0158277443979048e-05 loss: 0.0222 (0.0211) time: 4.0231 data: 0.0033 max mem: 19788 +Epoch: [33] [ 420/2138] eta: 1:56:30 lr: 1.015199591608875e-05 loss: 0.0223 (0.0211) time: 4.0248 data: 0.0032 max mem: 19788 +Epoch: [33] [ 430/2138] eta: 1:55:48 lr: 1.0145713956315026e-05 loss: 0.0187 (0.0211) time: 4.0240 data: 0.0034 max mem: 19788 +Epoch: [33] [ 440/2138] eta: 1:55:06 lr: 1.0139431564331032e-05 loss: 0.0199 (0.0211) time: 4.0240 data: 0.0033 max mem: 19788 +Epoch: [33] [ 450/2138] eta: 1:54:23 lr: 1.013314873980942e-05 loss: 0.0195 (0.0212) time: 4.0258 data: 0.0032 max mem: 19788 +Epoch: [33] [ 460/2138] eta: 1:53:41 lr: 1.0126865482422403e-05 loss: 0.0223 (0.0213) time: 4.0214 data: 0.0034 max mem: 19788 +Epoch: [33] [ 470/2138] eta: 1:52:59 lr: 1.0120581791841692e-05 loss: 0.0223 (0.0213) time: 4.0241 data: 0.0039 max mem: 19788 +Epoch: [33] [ 480/2138] eta: 1:52:17 lr: 1.011429766773853e-05 loss: 0.0214 (0.0213) time: 4.0312 data: 0.0041 max mem: 19788 +Epoch: [33] [ 490/2138] eta: 1:51:35 lr: 1.0108013109783696e-05 loss: 0.0194 (0.0213) time: 4.0305 data: 0.0038 max mem: 19788 +Epoch: [33] [ 500/2138] eta: 1:50:54 lr: 1.0101728117647469e-05 loss: 0.0195 (0.0213) time: 4.0359 data: 0.0035 max mem: 19788 +Epoch: [33] [ 510/2138] eta: 1:50:13 lr: 1.0095442690999673e-05 loss: 0.0206 (0.0213) time: 4.0424 data: 0.0039 max mem: 19788 +Epoch: [33] [ 520/2138] eta: 1:49:32 lr: 1.0089156829509633e-05 loss: 0.0206 (0.0213) time: 4.0418 data: 0.0038 max mem: 19788 +Epoch: [33] [ 530/2138] eta: 1:48:50 lr: 1.0082870532846209e-05 loss: 0.0200 (0.0213) time: 4.0413 data: 0.0033 max mem: 19788 +Epoch: [33] [ 540/2138] eta: 1:48:09 lr: 1.007658380067776e-05 loss: 0.0182 (0.0212) time: 4.0361 data: 0.0032 max mem: 19788 +Epoch: [33] [ 550/2138] eta: 1:47:28 lr: 1.0070296632672185e-05 loss: 0.0195 (0.0212) time: 4.0368 data: 0.0033 max mem: 19788 +Epoch: [33] [ 560/2138] eta: 1:46:47 lr: 1.0064009028496879e-05 loss: 0.0201 (0.0212) time: 4.0441 data: 0.0033 max mem: 19788 +Epoch: [33] [ 570/2138] eta: 1:46:05 lr: 1.005772098781877e-05 loss: 0.0191 (0.0212) time: 4.0431 data: 0.0032 max mem: 19788 +Epoch: [33] [ 580/2138] eta: 1:45:25 lr: 1.0051432510304278e-05 loss: 0.0205 (0.0213) time: 4.0459 data: 0.0032 max mem: 19788 +Epoch: [33] [ 590/2138] eta: 1:44:44 lr: 1.0045143595619365e-05 loss: 0.0212 (0.0213) time: 4.0486 data: 0.0034 max mem: 19788 +Epoch: [33] [ 600/2138] eta: 1:44:03 lr: 1.0038854243429474e-05 loss: 0.0197 (0.0213) time: 4.0451 data: 0.0035 max mem: 19788 +Epoch: [33] [ 610/2138] eta: 1:43:22 lr: 1.0032564453399584e-05 loss: 0.0197 (0.0213) time: 4.0467 data: 0.0034 max mem: 19788 +Epoch: [33] [ 620/2138] eta: 1:42:41 lr: 1.0026274225194166e-05 loss: 0.0218 (0.0213) time: 4.0474 data: 0.0033 max mem: 19788 +Epoch: [33] [ 630/2138] eta: 1:42:00 lr: 1.0019983558477217e-05 loss: 0.0199 (0.0213) time: 4.0455 data: 0.0032 max mem: 19788 +Epoch: [33] [ 640/2138] eta: 1:41:19 lr: 1.001369245291222e-05 loss: 0.0187 (0.0213) time: 4.0390 data: 0.0032 max mem: 19788 +Epoch: [33] [ 650/2138] eta: 1:40:38 lr: 1.0007400908162189e-05 loss: 0.0188 (0.0212) time: 4.0366 data: 0.0031 max mem: 19788 +Epoch: [33] [ 660/2138] eta: 1:39:57 lr: 1.0001108923889622e-05 loss: 0.0192 (0.0212) time: 4.0400 data: 0.0032 max mem: 19788 +Epoch: [33] [ 670/2138] eta: 1:39:16 lr: 9.994816499756537e-06 loss: 0.0206 (0.0212) time: 4.0398 data: 0.0033 max mem: 19788 +Epoch: [33] [ 680/2138] eta: 1:38:35 lr: 9.988523635424444e-06 loss: 0.0229 (0.0213) time: 4.0426 data: 0.0034 max mem: 19788 +Epoch: [33] [ 690/2138] eta: 1:37:54 lr: 9.982230330554372e-06 loss: 0.0199 (0.0213) time: 4.0403 data: 0.0032 max mem: 19788 +Epoch: [33] [ 700/2138] eta: 1:37:13 lr: 9.975936584806825e-06 loss: 0.0202 (0.0213) time: 4.0385 data: 0.0030 max mem: 19788 +Epoch: [33] [ 710/2138] eta: 1:36:32 lr: 9.969642397841836e-06 loss: 0.0221 (0.0213) time: 4.0406 data: 0.0031 max mem: 19788 +Epoch: [33] [ 720/2138] eta: 1:35:51 lr: 9.963347769318911e-06 loss: 0.0188 (0.0213) time: 4.0413 data: 0.0031 max mem: 19788 +Epoch: [33] [ 730/2138] eta: 1:35:11 lr: 9.95705269889708e-06 loss: 0.0191 (0.0214) time: 4.0414 data: 0.0031 max mem: 19788 +Epoch: [33] [ 740/2138] eta: 1:34:30 lr: 9.950757186234844e-06 loss: 0.0174 (0.0213) time: 4.0374 data: 0.0033 max mem: 19788 +Epoch: [33] [ 750/2138] eta: 1:33:49 lr: 9.944461230990224e-06 loss: 0.0182 (0.0213) time: 4.0411 data: 0.0031 max mem: 19788 +Epoch: [33] [ 760/2138] eta: 1:33:08 lr: 9.938164832820713e-06 loss: 0.0212 (0.0213) time: 4.0388 data: 0.0033 max mem: 19788 +Epoch: [33] [ 770/2138] eta: 1:32:27 lr: 9.931867991383318e-06 loss: 0.0212 (0.0213) time: 4.0333 data: 0.0034 max mem: 19788 +Epoch: [33] [ 780/2138] eta: 1:31:46 lr: 9.925570706334527e-06 loss: 0.0226 (0.0214) time: 4.0394 data: 0.0033 max mem: 19788 +Epoch: [33] [ 790/2138] eta: 1:31:05 lr: 9.919272977330315e-06 loss: 0.0195 (0.0214) time: 4.0439 data: 0.0031 max mem: 19788 +Epoch: [33] [ 800/2138] eta: 1:30:25 lr: 9.912974804026164e-06 loss: 0.0191 (0.0213) time: 4.0388 data: 0.0030 max mem: 19788 +Epoch: [33] [ 810/2138] eta: 1:29:44 lr: 9.906676186077025e-06 loss: 0.0182 (0.0213) time: 4.0299 data: 0.0031 max mem: 19788 +Epoch: [33] [ 820/2138] eta: 1:29:03 lr: 9.90037712313736e-06 loss: 0.0187 (0.0213) time: 4.0333 data: 0.0033 max mem: 19788 +Epoch: [33] [ 830/2138] eta: 1:28:22 lr: 9.894077614861092e-06 loss: 0.0176 (0.0213) time: 4.0389 data: 0.0032 max mem: 19788 +Epoch: [33] [ 840/2138] eta: 1:27:41 lr: 9.887777660901656e-06 loss: 0.0174 (0.0213) time: 4.0312 data: 0.0032 max mem: 19788 +Epoch: [33] [ 850/2138] eta: 1:27:00 lr: 9.881477260911947e-06 loss: 0.0174 (0.0212) time: 4.0347 data: 0.0034 max mem: 19788 +Epoch: [33] [ 860/2138] eta: 1:26:19 lr: 9.875176414544366e-06 loss: 0.0216 (0.0212) time: 4.0398 data: 0.0036 max mem: 19788 +Epoch: [33] [ 870/2138] eta: 1:25:39 lr: 9.868875121450777e-06 loss: 0.0225 (0.0213) time: 4.0376 data: 0.0034 max mem: 19788 +Epoch: [33] [ 880/2138] eta: 1:24:58 lr: 9.862573381282544e-06 loss: 0.0199 (0.0212) time: 4.0389 data: 0.0032 max mem: 19788 +Epoch: [33] [ 890/2138] eta: 1:24:17 lr: 9.85627119369049e-06 loss: 0.0201 (0.0212) time: 4.0389 data: 0.0033 max mem: 19788 +Epoch: [33] [ 900/2138] eta: 1:23:36 lr: 9.849968558324942e-06 loss: 0.0220 (0.0213) time: 4.0344 data: 0.0032 max mem: 19788 +Epoch: [33] [ 910/2138] eta: 1:22:56 lr: 9.843665474835675e-06 loss: 0.0220 (0.0213) time: 4.0261 data: 0.0032 max mem: 19788 +Epoch: [33] [ 920/2138] eta: 1:22:15 lr: 9.837361942871974e-06 loss: 0.0202 (0.0213) time: 4.0270 data: 0.0033 max mem: 19788 +Epoch: [33] [ 930/2138] eta: 1:21:34 lr: 9.831057962082568e-06 loss: 0.0193 (0.0213) time: 4.0397 data: 0.0032 max mem: 19788 +Epoch: [33] [ 940/2138] eta: 1:20:54 lr: 9.824753532115689e-06 loss: 0.0210 (0.0213) time: 4.0456 data: 0.0033 max mem: 19788 +Epoch: [33] [ 950/2138] eta: 1:20:13 lr: 9.818448652619013e-06 loss: 0.0210 (0.0213) time: 4.0454 data: 0.0036 max mem: 19788 +Epoch: [33] [ 960/2138] eta: 1:19:32 lr: 9.812143323239719e-06 loss: 0.0210 (0.0213) time: 4.0410 data: 0.0037 max mem: 19788 +Epoch: [33] [ 970/2138] eta: 1:18:51 lr: 9.805837543624427e-06 loss: 0.0187 (0.0213) time: 4.0311 data: 0.0033 max mem: 19788 +Epoch: [33] [ 980/2138] eta: 1:18:11 lr: 9.799531313419255e-06 loss: 0.0186 (0.0213) time: 4.0271 data: 0.0032 max mem: 19788 +Epoch: [33] [ 990/2138] eta: 1:17:30 lr: 9.79322463226976e-06 loss: 0.0202 (0.0213) time: 4.0352 data: 0.0033 max mem: 19788 +Epoch: [33] [1000/2138] eta: 1:16:50 lr: 9.786917499820999e-06 loss: 0.0216 (0.0213) time: 4.0497 data: 0.0033 max mem: 19788 +Epoch: [33] [1010/2138] eta: 1:16:09 lr: 9.780609915717462e-06 loss: 0.0195 (0.0213) time: 4.0499 data: 0.0033 max mem: 19788 +Epoch: [33] [1020/2138] eta: 1:15:28 lr: 9.774301879603134e-06 loss: 0.0188 (0.0213) time: 4.0459 data: 0.0033 max mem: 19788 +Epoch: [33] [1030/2138] eta: 1:14:48 lr: 9.767993391121439e-06 loss: 0.0188 (0.0213) time: 4.0481 data: 0.0033 max mem: 19788 +Epoch: [33] [1040/2138] eta: 1:14:07 lr: 9.761684449915285e-06 loss: 0.0192 (0.0213) time: 4.0490 data: 0.0033 max mem: 19788 +Epoch: [33] [1050/2138] eta: 1:13:27 lr: 9.75537505562702e-06 loss: 0.0192 (0.0213) time: 4.0493 data: 0.0034 max mem: 19788 +Epoch: [33] [1060/2138] eta: 1:12:46 lr: 9.749065207898476e-06 loss: 0.0188 (0.0212) time: 4.0483 data: 0.0034 max mem: 19788 +Epoch: [33] [1070/2138] eta: 1:12:06 lr: 9.742754906370924e-06 loss: 0.0188 (0.0212) time: 4.0437 data: 0.0033 max mem: 19788 +Epoch: [33] [1080/2138] eta: 1:11:25 lr: 9.736444150685095e-06 loss: 0.0182 (0.0212) time: 4.0388 data: 0.0033 max mem: 19788 +Epoch: [33] [1090/2138] eta: 1:10:44 lr: 9.730132940481193e-06 loss: 0.0189 (0.0212) time: 4.0400 data: 0.0031 max mem: 19788 +Epoch: [33] [1100/2138] eta: 1:10:04 lr: 9.723821275398855e-06 loss: 0.0235 (0.0212) time: 4.0395 data: 0.0031 max mem: 19788 +Epoch: [33] [1110/2138] eta: 1:09:23 lr: 9.717509155077199e-06 loss: 0.0235 (0.0213) time: 4.0370 data: 0.0031 max mem: 19788 +Epoch: [33] [1120/2138] eta: 1:08:43 lr: 9.711196579154761e-06 loss: 0.0212 (0.0213) time: 4.0395 data: 0.0031 max mem: 19788 +Epoch: [33] [1130/2138] eta: 1:08:02 lr: 9.704883547269567e-06 loss: 0.0219 (0.0213) time: 4.0357 data: 0.0033 max mem: 19788 +Epoch: [33] [1140/2138] eta: 1:07:21 lr: 9.698570059059059e-06 loss: 0.0209 (0.0213) time: 4.0351 data: 0.0034 max mem: 19788 +Epoch: [33] [1150/2138] eta: 1:06:41 lr: 9.692256114160158e-06 loss: 0.0188 (0.0213) time: 4.0410 data: 0.0032 max mem: 19788 +Epoch: [33] [1160/2138] eta: 1:06:00 lr: 9.685941712209206e-06 loss: 0.0184 (0.0212) time: 4.0436 data: 0.0032 max mem: 19788 +Epoch: [33] [1170/2138] eta: 1:05:20 lr: 9.679626852842015e-06 loss: 0.0200 (0.0212) time: 4.0446 data: 0.0034 max mem: 19788 +Epoch: [33] [1180/2138] eta: 1:04:39 lr: 9.673311535693824e-06 loss: 0.0200 (0.0212) time: 4.0469 data: 0.0034 max mem: 19788 +Epoch: [33] [1190/2138] eta: 1:03:59 lr: 9.666995760399333e-06 loss: 0.0198 (0.0212) time: 4.0493 data: 0.0033 max mem: 19788 +Epoch: [33] [1200/2138] eta: 1:03:18 lr: 9.660679526592668e-06 loss: 0.0198 (0.0212) time: 4.0469 data: 0.0034 max mem: 19788 +Epoch: [33] [1210/2138] eta: 1:02:38 lr: 9.654362833907418e-06 loss: 0.0205 (0.0212) time: 4.0447 data: 0.0036 max mem: 19788 +Epoch: [33] [1220/2138] eta: 1:01:57 lr: 9.648045681976585e-06 loss: 0.0200 (0.0212) time: 4.0476 data: 0.0036 max mem: 19788 +Epoch: [33] [1230/2138] eta: 1:01:16 lr: 9.641728070432639e-06 loss: 0.0189 (0.0212) time: 4.0397 data: 0.0033 max mem: 19788 +Epoch: [33] [1240/2138] eta: 1:00:36 lr: 9.635409998907463e-06 loss: 0.0187 (0.0212) time: 4.0354 data: 0.0034 max mem: 19788 +Epoch: [33] [1250/2138] eta: 0:59:55 lr: 9.6290914670324e-06 loss: 0.0196 (0.0212) time: 4.0411 data: 0.0034 max mem: 19788 +Epoch: [33] [1260/2138] eta: 0:59:15 lr: 9.622772474438203e-06 loss: 0.0195 (0.0212) time: 4.0464 data: 0.0033 max mem: 19788 +Epoch: [33] [1270/2138] eta: 0:58:34 lr: 9.616453020755089e-06 loss: 0.0172 (0.0212) time: 4.0435 data: 0.0033 max mem: 19788 +Epoch: [33] [1280/2138] eta: 0:57:54 lr: 9.610133105612674e-06 loss: 0.0191 (0.0212) time: 4.0391 data: 0.0032 max mem: 19788 +Epoch: [33] [1290/2138] eta: 0:57:13 lr: 9.603812728640043e-06 loss: 0.0191 (0.0212) time: 4.0421 data: 0.0033 max mem: 19788 +Epoch: [33] [1300/2138] eta: 0:56:33 lr: 9.597491889465672e-06 loss: 0.0194 (0.0212) time: 4.0450 data: 0.0035 max mem: 19788 +Epoch: [33] [1310/2138] eta: 0:55:52 lr: 9.591170587717504e-06 loss: 0.0208 (0.0212) time: 4.0484 data: 0.0034 max mem: 19788 +Epoch: [33] [1320/2138] eta: 0:55:12 lr: 9.584848823022875e-06 loss: 0.0212 (0.0212) time: 4.0488 data: 0.0033 max mem: 19788 +Epoch: [33] [1330/2138] eta: 0:54:31 lr: 9.57852659500858e-06 loss: 0.0204 (0.0212) time: 4.0492 data: 0.0033 max mem: 19788 +Epoch: [33] [1340/2138] eta: 0:53:51 lr: 9.57220390330081e-06 loss: 0.0198 (0.0212) time: 4.0480 data: 0.0032 max mem: 19788 +Epoch: [33] [1350/2138] eta: 0:53:10 lr: 9.565880747525205e-06 loss: 0.0220 (0.0212) time: 4.0470 data: 0.0033 max mem: 19788 +Epoch: [33] [1360/2138] eta: 0:52:30 lr: 9.559557127306802e-06 loss: 0.0233 (0.0212) time: 4.0506 data: 0.0034 max mem: 19788 +Epoch: [33] [1370/2138] eta: 0:51:49 lr: 9.553233042270087e-06 loss: 0.0208 (0.0212) time: 4.0507 data: 0.0033 max mem: 19788 +Epoch: [33] [1380/2138] eta: 0:51:09 lr: 9.546908492038947e-06 loss: 0.0198 (0.0213) time: 4.0446 data: 0.0037 max mem: 19788 +Epoch: [33] [1390/2138] eta: 0:50:28 lr: 9.540583476236683e-06 loss: 0.0220 (0.0213) time: 4.0407 data: 0.0038 max mem: 19788 +Epoch: [33] [1400/2138] eta: 0:49:48 lr: 9.534257994486037e-06 loss: 0.0212 (0.0213) time: 4.0354 data: 0.0036 max mem: 19788 +Epoch: [33] [1410/2138] eta: 0:49:07 lr: 9.527932046409142e-06 loss: 0.0189 (0.0212) time: 4.0388 data: 0.0033 max mem: 19788 +Epoch: [33] [1420/2138] eta: 0:48:27 lr: 9.521605631627564e-06 loss: 0.0180 (0.0212) time: 4.0408 data: 0.0031 max mem: 19788 +Epoch: [33] [1430/2138] eta: 0:47:46 lr: 9.515278749762264e-06 loss: 0.0199 (0.0212) time: 4.0430 data: 0.0032 max mem: 19788 +Epoch: [33] [1440/2138] eta: 0:47:06 lr: 9.50895140043364e-06 loss: 0.0192 (0.0212) time: 4.0469 data: 0.0033 max mem: 19788 +Epoch: [33] [1450/2138] eta: 0:46:25 lr: 9.50262358326147e-06 loss: 0.0217 (0.0212) time: 4.0398 data: 0.0033 max mem: 19788 +Epoch: [33] [1460/2138] eta: 0:45:44 lr: 9.496295297864974e-06 loss: 0.0230 (0.0212) time: 4.0369 data: 0.0032 max mem: 19788 +Epoch: [33] [1470/2138] eta: 0:45:04 lr: 9.489966543862745e-06 loss: 0.0203 (0.0213) time: 4.0392 data: 0.0033 max mem: 19788 +Epoch: [33] [1480/2138] eta: 0:44:23 lr: 9.483637320872816e-06 loss: 0.0220 (0.0213) time: 4.0448 data: 0.0033 max mem: 19788 +Epoch: [33] [1490/2138] eta: 0:43:43 lr: 9.477307628512598e-06 loss: 0.0217 (0.0213) time: 4.0481 data: 0.0032 max mem: 19788 +Epoch: [33] [1500/2138] eta: 0:43:03 lr: 9.470977466398926e-06 loss: 0.0196 (0.0213) time: 4.0503 data: 0.0032 max mem: 19788 +Epoch: [33] [1510/2138] eta: 0:42:22 lr: 9.464646834148023e-06 loss: 0.0205 (0.0213) time: 4.0477 data: 0.0034 max mem: 19788 +Epoch: [33] [1520/2138] eta: 0:41:41 lr: 9.458315731375523e-06 loss: 0.0200 (0.0212) time: 4.0429 data: 0.0035 max mem: 19788 +Epoch: [33] [1530/2138] eta: 0:41:01 lr: 9.451984157696447e-06 loss: 0.0189 (0.0212) time: 4.0398 data: 0.0035 max mem: 19788 +Epoch: [33] [1540/2138] eta: 0:40:20 lr: 9.445652112725236e-06 loss: 0.0189 (0.0212) time: 4.0382 data: 0.0034 max mem: 19788 +Epoch: [33] [1550/2138] eta: 0:39:40 lr: 9.4393195960757e-06 loss: 0.0196 (0.0212) time: 4.0382 data: 0.0033 max mem: 19788 +Epoch: [33] [1560/2138] eta: 0:38:59 lr: 9.432986607361071e-06 loss: 0.0206 (0.0212) time: 4.0398 data: 0.0032 max mem: 19788 +Epoch: [33] [1570/2138] eta: 0:38:19 lr: 9.42665314619395e-06 loss: 0.0198 (0.0212) time: 4.0411 data: 0.0031 max mem: 19788 +Epoch: [33] [1580/2138] eta: 0:37:38 lr: 9.42031921218636e-06 loss: 0.0196 (0.0212) time: 4.0399 data: 0.0031 max mem: 19788 +Epoch: [33] [1590/2138] eta: 0:36:58 lr: 9.413984804949682e-06 loss: 0.0197 (0.0212) time: 4.0380 data: 0.0033 max mem: 19788 +Epoch: [33] [1600/2138] eta: 0:36:17 lr: 9.40764992409472e-06 loss: 0.0214 (0.0212) time: 4.0426 data: 0.0034 max mem: 19788 +Epoch: [33] [1610/2138] eta: 0:35:37 lr: 9.401314569231632e-06 loss: 0.0204 (0.0212) time: 4.0480 data: 0.0034 max mem: 19788 +Epoch: [33] [1620/2138] eta: 0:34:56 lr: 9.39497873997e-06 loss: 0.0178 (0.0212) time: 4.0485 data: 0.0036 max mem: 19788 +Epoch: [33] [1630/2138] eta: 0:34:16 lr: 9.388642435918756e-06 loss: 0.0212 (0.0212) time: 4.0513 data: 0.0033 max mem: 19788 +Epoch: [33] [1640/2138] eta: 0:33:36 lr: 9.382305656686243e-06 loss: 0.0205 (0.0212) time: 4.0578 data: 0.0031 max mem: 19788 +Epoch: [33] [1650/2138] eta: 0:32:55 lr: 9.375968401880171e-06 loss: 0.0186 (0.0212) time: 4.0607 data: 0.0031 max mem: 19788 +Epoch: [33] [1660/2138] eta: 0:32:15 lr: 9.369630671107644e-06 loss: 0.0179 (0.0212) time: 4.0499 data: 0.0031 max mem: 19788 +Epoch: [33] [1670/2138] eta: 0:31:34 lr: 9.36329246397513e-06 loss: 0.0170 (0.0212) time: 4.0475 data: 0.0032 max mem: 19788 +Epoch: [33] [1680/2138] eta: 0:30:54 lr: 9.35695378008849e-06 loss: 0.0199 (0.0212) time: 4.0463 data: 0.0031 max mem: 19788 +Epoch: [33] [1690/2138] eta: 0:30:13 lr: 9.350614619052957e-06 loss: 0.0199 (0.0212) time: 4.0422 data: 0.0033 max mem: 19788 +Epoch: [33] [1700/2138] eta: 0:29:33 lr: 9.344274980473127e-06 loss: 0.0190 (0.0212) time: 4.0381 data: 0.0034 max mem: 19788 +Epoch: [33] [1710/2138] eta: 0:28:52 lr: 9.337934863952997e-06 loss: 0.0192 (0.0212) time: 4.0323 data: 0.0033 max mem: 19788 +Epoch: [33] [1720/2138] eta: 0:28:12 lr: 9.331594269095905e-06 loss: 0.0204 (0.0212) time: 4.0351 data: 0.0032 max mem: 19788 +Epoch: [33] [1730/2138] eta: 0:27:31 lr: 9.325253195504593e-06 loss: 0.0204 (0.0212) time: 4.0382 data: 0.0033 max mem: 19788 +Epoch: [33] [1740/2138] eta: 0:26:51 lr: 9.318911642781142e-06 loss: 0.0201 (0.0212) time: 4.0382 data: 0.0034 max mem: 19788 +Epoch: [33] [1750/2138] eta: 0:26:10 lr: 9.312569610527027e-06 loss: 0.0201 (0.0212) time: 4.0387 data: 0.0032 max mem: 19788 +Epoch: [33] [1760/2138] eta: 0:25:30 lr: 9.306227098343063e-06 loss: 0.0213 (0.0212) time: 4.0390 data: 0.0031 max mem: 19788 +Epoch: [33] [1770/2138] eta: 0:24:49 lr: 9.299884105829459e-06 loss: 0.0210 (0.0212) time: 4.0416 data: 0.0030 max mem: 19788 +Epoch: [33] [1780/2138] eta: 0:24:09 lr: 9.29354063258576e-06 loss: 0.0210 (0.0212) time: 4.0401 data: 0.0035 max mem: 19788 +Epoch: [33] [1790/2138] eta: 0:23:28 lr: 9.287196678210899e-06 loss: 0.0194 (0.0212) time: 4.0357 data: 0.0037 max mem: 19788 +Epoch: [33] [1800/2138] eta: 0:22:48 lr: 9.280852242303146e-06 loss: 0.0178 (0.0212) time: 4.0403 data: 0.0035 max mem: 19788 +Epoch: [33] [1810/2138] eta: 0:22:07 lr: 9.274507324460155e-06 loss: 0.0178 (0.0212) time: 4.0373 data: 0.0035 max mem: 19788 +Epoch: [33] [1820/2138] eta: 0:21:27 lr: 9.268161924278908e-06 loss: 0.0197 (0.0212) time: 4.0376 data: 0.0034 max mem: 19788 +Epoch: [33] [1830/2138] eta: 0:20:46 lr: 9.261816041355774e-06 loss: 0.0194 (0.0212) time: 4.0418 data: 0.0032 max mem: 19788 +Epoch: [33] [1840/2138] eta: 0:20:06 lr: 9.25546967528645e-06 loss: 0.0197 (0.0212) time: 4.0412 data: 0.0034 max mem: 19788 +Epoch: [33] [1850/2138] eta: 0:19:25 lr: 9.249122825666009e-06 loss: 0.0205 (0.0212) time: 4.0468 data: 0.0037 max mem: 19788 +Epoch: [33] [1860/2138] eta: 0:18:45 lr: 9.242775492088852e-06 loss: 0.0225 (0.0212) time: 4.0504 data: 0.0040 max mem: 19788 +Epoch: [33] [1870/2138] eta: 0:18:04 lr: 9.236427674148755e-06 loss: 0.0206 (0.0212) time: 4.0417 data: 0.0037 max mem: 19788 +Epoch: [33] [1880/2138] eta: 0:17:24 lr: 9.23007937143882e-06 loss: 0.0197 (0.0212) time: 4.0323 data: 0.0031 max mem: 19788 +Epoch: [33] [1890/2138] eta: 0:16:43 lr: 9.223730583551516e-06 loss: 0.0186 (0.0212) time: 4.0332 data: 0.0031 max mem: 19788 +Epoch: [33] [1900/2138] eta: 0:16:03 lr: 9.217381310078635e-06 loss: 0.0171 (0.0212) time: 4.0344 data: 0.0032 max mem: 19788 +Epoch: [33] [1910/2138] eta: 0:15:22 lr: 9.211031550611338e-06 loss: 0.0187 (0.0212) time: 4.0293 data: 0.0031 max mem: 19788 +Epoch: [33] [1920/2138] eta: 0:14:42 lr: 9.204681304740106e-06 loss: 0.0211 (0.0212) time: 4.0263 data: 0.0032 max mem: 19788 +Epoch: [33] [1930/2138] eta: 0:14:01 lr: 9.19833057205478e-06 loss: 0.0211 (0.0212) time: 4.0320 data: 0.0032 max mem: 19788 +Epoch: [33] [1940/2138] eta: 0:13:21 lr: 9.191979352144519e-06 loss: 0.0212 (0.0212) time: 4.0332 data: 0.0031 max mem: 19788 +Epoch: [33] [1950/2138] eta: 0:12:40 lr: 9.185627644597844e-06 loss: 0.0212 (0.0212) time: 4.0282 data: 0.0031 max mem: 19788 +Epoch: [33] [1960/2138] eta: 0:12:00 lr: 9.179275449002584e-06 loss: 0.0210 (0.0212) time: 4.0375 data: 0.0033 max mem: 19788 +Epoch: [33] [1970/2138] eta: 0:11:19 lr: 9.172922764945934e-06 loss: 0.0193 (0.0212) time: 4.0504 data: 0.0032 max mem: 19788 +Epoch: [33] [1980/2138] eta: 0:10:39 lr: 9.166569592014391e-06 loss: 0.0160 (0.0212) time: 4.0508 data: 0.0032 max mem: 19788 +Epoch: [33] [1990/2138] eta: 0:09:58 lr: 9.160215929793811e-06 loss: 0.0170 (0.0212) time: 4.0504 data: 0.0032 max mem: 19788 +Epoch: [33] [2000/2138] eta: 0:09:18 lr: 9.153861777869358e-06 loss: 0.0200 (0.0212) time: 4.0508 data: 0.0033 max mem: 19788 +Epoch: [33] [2010/2138] eta: 0:08:37 lr: 9.14750713582553e-06 loss: 0.0204 (0.0212) time: 4.0486 data: 0.0033 max mem: 19788 +Epoch: [33] [2020/2138] eta: 0:07:57 lr: 9.141152003246164e-06 loss: 0.0223 (0.0212) time: 4.0473 data: 0.0032 max mem: 19788 +Epoch: [33] [2030/2138] eta: 0:07:17 lr: 9.1347963797144e-06 loss: 0.0218 (0.0212) time: 4.0499 data: 0.0034 max mem: 19788 +Epoch: [33] [2040/2138] eta: 0:06:36 lr: 9.128440264812723e-06 loss: 0.0208 (0.0212) time: 4.0528 data: 0.0035 max mem: 19788 +Epoch: [33] [2050/2138] eta: 0:05:56 lr: 9.122083658122922e-06 loss: 0.0206 (0.0212) time: 4.0513 data: 0.0034 max mem: 19788 +Epoch: [33] [2060/2138] eta: 0:05:15 lr: 9.115726559226121e-06 loss: 0.0185 (0.0212) time: 4.0483 data: 0.0032 max mem: 19788 +Epoch: [33] [2070/2138] eta: 0:04:35 lr: 9.109368967702745e-06 loss: 0.0185 (0.0212) time: 4.0466 data: 0.0033 max mem: 19788 +Epoch: [33] [2080/2138] eta: 0:03:54 lr: 9.103010883132558e-06 loss: 0.0202 (0.0212) time: 4.0436 data: 0.0034 max mem: 19788 +Epoch: [33] [2090/2138] eta: 0:03:14 lr: 9.096652305094614e-06 loss: 0.0205 (0.0212) time: 4.0442 data: 0.0033 max mem: 19788 +Epoch: [33] [2100/2138] eta: 0:02:33 lr: 9.090293233167305e-06 loss: 0.0186 (0.0212) time: 4.0507 data: 0.0034 max mem: 19788 +Epoch: [33] [2110/2138] eta: 0:01:53 lr: 9.083933666928311e-06 loss: 0.0206 (0.0212) time: 4.0459 data: 0.0036 max mem: 19788 +Epoch: [33] [2120/2138] eta: 0:01:12 lr: 9.077573605954647e-06 loss: 0.0244 (0.0213) time: 4.0381 data: 0.0035 max mem: 19788 +Epoch: [33] [2130/2138] eta: 0:00:32 lr: 9.071213049822608e-06 loss: 0.0209 (0.0213) time: 4.0260 data: 0.0032 max mem: 19788 +Epoch: [33] Total time: 2:24:12 +Test: [ 0/21770] eta: 21:34:30 time: 3.5678 data: 3.4758 max mem: 19788 +Test: [ 100/21770] eta: 0:36:39 time: 0.0639 data: 0.0020 max mem: 19788 +Test: [ 200/21770] eta: 0:30:12 time: 0.0637 data: 0.0023 max mem: 19788 +Test: [ 300/21770] eta: 0:28:43 time: 0.0711 data: 0.0022 max mem: 19788 +Test: [ 400/21770] eta: 0:27:38 time: 0.0718 data: 0.0023 max mem: 19788 +Test: [ 500/21770] eta: 0:26:40 time: 0.0642 data: 0.0020 max mem: 19788 +Test: [ 600/21770] eta: 0:26:42 time: 0.0828 data: 0.0025 max mem: 19788 +Test: [ 700/21770] eta: 0:26:14 time: 0.0707 data: 0.0021 max mem: 19788 +Test: [ 800/21770] eta: 0:25:54 time: 0.0811 data: 0.0021 max mem: 19788 +Test: [ 900/21770] eta: 0:25:28 time: 0.0665 data: 0.0022 max mem: 19788 +Test: [ 1000/21770] eta: 0:25:01 time: 0.0622 data: 0.0019 max mem: 19788 +Test: [ 1100/21770] eta: 0:24:41 time: 0.0656 data: 0.0019 max mem: 19788 +Test: [ 1200/21770] eta: 0:24:25 time: 0.0638 data: 0.0021 max mem: 19788 +Test: [ 1300/21770] eta: 0:24:22 time: 0.0652 data: 0.0021 max mem: 19788 +Test: [ 1400/21770] eta: 0:24:17 time: 0.0779 data: 0.0022 max mem: 19788 +Test: [ 1500/21770] eta: 0:24:04 time: 0.0659 data: 0.0022 max mem: 19788 +Test: [ 1600/21770] eta: 0:23:51 time: 0.0635 data: 0.0022 max mem: 19788 +Test: [ 1700/21770] eta: 0:23:47 time: 0.0622 data: 0.0020 max mem: 19788 +Test: [ 1800/21770] eta: 0:23:46 time: 0.0642 data: 0.0021 max mem: 19788 +Test: [ 1900/21770] eta: 0:23:34 time: 0.0735 data: 0.0023 max mem: 19788 +Test: [ 2000/21770] eta: 0:23:27 time: 0.0644 data: 0.0020 max mem: 19788 +Test: [ 2100/21770] eta: 0:23:24 time: 0.0845 data: 0.0025 max mem: 19788 +Test: [ 2200/21770] eta: 0:23:17 time: 0.0642 data: 0.0019 max mem: 19788 +Test: [ 2300/21770] eta: 0:23:07 time: 0.0635 data: 0.0021 max mem: 19788 +Test: [ 2400/21770] eta: 0:23:00 time: 0.0858 data: 0.0027 max mem: 19788 +Test: [ 2500/21770] eta: 0:22:57 time: 0.0638 data: 0.0020 max mem: 19788 +Test: [ 2600/21770] eta: 0:22:50 time: 0.0639 data: 0.0021 max mem: 19788 +Test: [ 2700/21770] eta: 0:22:41 time: 0.0655 data: 0.0022 max mem: 19788 +Test: [ 2800/21770] eta: 0:22:35 time: 0.0853 data: 0.0026 max mem: 19788 +Test: [ 2900/21770] eta: 0:22:27 time: 0.0686 data: 0.0021 max mem: 19788 +Test: [ 3000/21770] eta: 0:22:18 time: 0.0705 data: 0.0022 max mem: 19788 +Test: [ 3100/21770] eta: 0:22:09 time: 0.0697 data: 0.0020 max mem: 19788 +Test: [ 3200/21770] eta: 0:22:02 time: 0.0695 data: 0.0021 max mem: 19788 +Test: [ 3300/21770] eta: 0:21:58 time: 0.0762 data: 0.0022 max mem: 19788 +Test: [ 3400/21770] eta: 0:21:51 time: 0.0660 data: 0.0020 max mem: 19788 +Test: [ 3500/21770] eta: 0:21:41 time: 0.0679 data: 0.0021 max mem: 19788 +Test: [ 3600/21770] eta: 0:21:32 time: 0.0647 data: 0.0020 max mem: 19788 +Test: [ 3700/21770] eta: 0:21:25 time: 0.0732 data: 0.0019 max mem: 19788 +Test: [ 3800/21770] eta: 0:21:16 time: 0.0689 data: 0.0021 max mem: 19788 +Test: [ 3900/21770] eta: 0:21:12 time: 0.0794 data: 0.0020 max mem: 19788 +Test: [ 4000/21770] eta: 0:21:05 time: 0.0767 data: 0.0024 max mem: 19788 +Test: [ 4100/21770] eta: 0:20:57 time: 0.0755 data: 0.0022 max mem: 19788 +Test: [ 4200/21770] eta: 0:20:48 time: 0.0710 data: 0.0020 max mem: 19788 +Test: [ 4300/21770] eta: 0:20:39 time: 0.0748 data: 0.0019 max mem: 19788 +Test: [ 4400/21770] eta: 0:20:32 time: 0.0687 data: 0.0021 max mem: 19788 +Test: [ 4500/21770] eta: 0:20:25 time: 0.0650 data: 0.0018 max mem: 19788 +Test: [ 4600/21770] eta: 0:20:16 time: 0.0674 data: 0.0026 max mem: 19788 +Test: [ 4700/21770] eta: 0:20:08 time: 0.0684 data: 0.0020 max mem: 19788 +Test: [ 4800/21770] eta: 0:20:00 time: 0.0689 data: 0.0021 max mem: 19788 +Test: [ 4900/21770] eta: 0:19:51 time: 0.0644 data: 0.0019 max mem: 19788 +Test: [ 5000/21770] eta: 0:19:47 time: 0.0741 data: 0.0022 max mem: 19788 +Test: [ 5100/21770] eta: 0:19:40 time: 0.0681 data: 0.0023 max mem: 19788 +Test: [ 5200/21770] eta: 0:19:33 time: 0.0671 data: 0.0020 max mem: 19788 +Test: [ 5300/21770] eta: 0:19:27 time: 0.0698 data: 0.0022 max mem: 19788 +Test: [ 5400/21770] eta: 0:19:19 time: 0.0657 data: 0.0019 max mem: 19788 +Test: [ 5500/21770] eta: 0:19:13 time: 0.0855 data: 0.0026 max mem: 19788 +Test: [ 5600/21770] eta: 0:19:06 time: 0.0663 data: 0.0023 max mem: 19788 +Test: [ 5700/21770] eta: 0:18:59 time: 0.0668 data: 0.0021 max mem: 19788 +Test: [ 5800/21770] eta: 0:18:53 time: 0.0725 data: 0.0025 max mem: 19788 +Test: [ 5900/21770] eta: 0:18:47 time: 0.0681 data: 0.0021 max mem: 19788 +Test: [ 6000/21770] eta: 0:18:39 time: 0.0668 data: 0.0020 max mem: 19788 +Test: [ 6100/21770] eta: 0:18:31 time: 0.0802 data: 0.0024 max mem: 19788 +Test: [ 6200/21770] eta: 0:18:26 time: 0.0693 data: 0.0020 max mem: 19788 +Test: [ 6300/21770] eta: 0:18:18 time: 0.0649 data: 0.0019 max mem: 19788 +Test: [ 6400/21770] eta: 0:18:11 time: 0.0654 data: 0.0018 max mem: 19788 +Test: [ 6500/21770] eta: 0:18:04 time: 0.0640 data: 0.0022 max mem: 19788 +Test: [ 6600/21770] eta: 0:17:58 time: 0.0806 data: 0.0026 max mem: 19788 +Test: [ 6700/21770] eta: 0:17:51 time: 0.0732 data: 0.0021 max mem: 19788 +Test: [ 6800/21770] eta: 0:17:43 time: 0.0698 data: 0.0020 max mem: 19788 +Test: [ 6900/21770] eta: 0:17:36 time: 0.0645 data: 0.0021 max mem: 19788 +Test: [ 7000/21770] eta: 0:17:27 time: 0.0674 data: 0.0020 max mem: 19788 +Test: [ 7100/21770] eta: 0:17:21 time: 0.0660 data: 0.0019 max mem: 19788 +Test: [ 7200/21770] eta: 0:17:14 time: 0.0637 data: 0.0018 max mem: 19788 +Test: [ 7300/21770] eta: 0:17:07 time: 0.0766 data: 0.0024 max mem: 19788 +Test: [ 7400/21770] eta: 0:17:00 time: 0.0678 data: 0.0020 max mem: 19788 +Test: [ 7500/21770] eta: 0:16:54 time: 0.0719 data: 0.0023 max mem: 19788 +Test: [ 7600/21770] eta: 0:16:48 time: 0.0796 data: 0.0024 max mem: 19788 +Test: [ 7700/21770] eta: 0:16:42 time: 0.0857 data: 0.0026 max mem: 19788 +Test: [ 7800/21770] eta: 0:16:36 time: 0.0796 data: 0.0023 max mem: 19788 +Test: [ 7900/21770] eta: 0:16:29 time: 0.0698 data: 0.0021 max mem: 19788 +Test: [ 8000/21770] eta: 0:16:22 time: 0.0665 data: 0.0019 max mem: 19788 +Test: [ 8100/21770] eta: 0:16:14 time: 0.0695 data: 0.0020 max mem: 19788 +Test: [ 8200/21770] eta: 0:16:07 time: 0.0662 data: 0.0020 max mem: 19788 +Test: [ 8300/21770] eta: 0:16:00 time: 0.0844 data: 0.0026 max mem: 19788 +Test: [ 8400/21770] eta: 0:15:53 time: 0.0666 data: 0.0020 max mem: 19788 +Test: [ 8500/21770] eta: 0:15:45 time: 0.0656 data: 0.0019 max mem: 19788 +Test: [ 8600/21770] eta: 0:15:38 time: 0.0658 data: 0.0020 max mem: 19788 +Test: [ 8700/21770] eta: 0:15:31 time: 0.0865 data: 0.0021 max mem: 19788 +Test: [ 8800/21770] eta: 0:15:23 time: 0.0649 data: 0.0020 max mem: 19788 +Test: [ 8900/21770] eta: 0:15:16 time: 0.0627 data: 0.0019 max mem: 19788 +Test: [ 9000/21770] eta: 0:15:08 time: 0.0715 data: 0.0022 max mem: 19788 +Test: [ 9100/21770] eta: 0:15:01 time: 0.0653 data: 0.0020 max mem: 19788 +Test: [ 9200/21770] eta: 0:14:53 time: 0.0815 data: 0.0027 max mem: 19788 +Test: [ 9300/21770] eta: 0:14:46 time: 0.0666 data: 0.0020 max mem: 19788 +Test: [ 9400/21770] eta: 0:14:39 time: 0.0658 data: 0.0022 max mem: 19788 +Test: [ 9500/21770] eta: 0:14:32 time: 0.0696 data: 0.0018 max mem: 19788 +Test: [ 9600/21770] eta: 0:14:25 time: 0.0674 data: 0.0020 max mem: 19788 +Test: [ 9700/21770] eta: 0:14:18 time: 0.0680 data: 0.0020 max mem: 19788 +Test: [ 9800/21770] eta: 0:14:11 time: 0.0750 data: 0.0024 max mem: 19788 +Test: [ 9900/21770] eta: 0:14:04 time: 0.0771 data: 0.0020 max mem: 19788 +Test: [10000/21770] eta: 0:13:57 time: 0.0670 data: 0.0021 max mem: 19788 +Test: [10100/21770] eta: 0:13:50 time: 0.0863 data: 0.0026 max mem: 19788 +Test: [10200/21770] eta: 0:13:43 time: 0.0675 data: 0.0021 max mem: 19788 +Test: [10300/21770] eta: 0:13:36 time: 0.0732 data: 0.0021 max mem: 19788 +Test: [10400/21770] eta: 0:13:29 time: 0.0716 data: 0.0022 max mem: 19788 +Test: [10500/21770] eta: 0:13:22 time: 0.0722 data: 0.0020 max mem: 19788 +Test: [10600/21770] eta: 0:13:16 time: 0.0779 data: 0.0023 max mem: 19788 +Test: [10700/21770] eta: 0:13:09 time: 0.0832 data: 0.0026 max mem: 19788 +Test: [10800/21770] eta: 0:13:03 time: 0.0756 data: 0.0021 max mem: 19788 +Test: [10900/21770] eta: 0:12:57 time: 0.0863 data: 0.0027 max mem: 19788 +Test: [11000/21770] eta: 0:12:50 time: 0.0691 data: 0.0022 max mem: 19788 +Test: [11100/21770] eta: 0:12:43 time: 0.0776 data: 0.0023 max mem: 19788 +Test: [11200/21770] eta: 0:12:37 time: 0.0723 data: 0.0023 max mem: 19788 +Test: [11300/21770] eta: 0:12:29 time: 0.0696 data: 0.0021 max mem: 19788 +Test: [11400/21770] eta: 0:12:22 time: 0.0684 data: 0.0019 max mem: 19788 +Test: [11500/21770] eta: 0:12:15 time: 0.0663 data: 0.0019 max mem: 19788 +Test: [11600/21770] eta: 0:12:08 time: 0.0787 data: 0.0023 max mem: 19788 +Test: [11700/21770] eta: 0:12:02 time: 0.0866 data: 0.0025 max mem: 19788 +Test: [11800/21770] eta: 0:11:55 time: 0.0748 data: 0.0023 max mem: 19788 +Test: [11900/21770] eta: 0:11:48 time: 0.0764 data: 0.0024 max mem: 19788 +Test: [12000/21770] eta: 0:11:41 time: 0.0678 data: 0.0021 max mem: 19788 +Test: [12100/21770] eta: 0:11:34 time: 0.0788 data: 0.0024 max mem: 19788 +Test: [12200/21770] eta: 0:11:26 time: 0.0651 data: 0.0024 max mem: 19788 +Test: [12300/21770] eta: 0:11:19 time: 0.0646 data: 0.0019 max mem: 19788 +Test: [12400/21770] eta: 0:11:12 time: 0.0794 data: 0.0024 max mem: 19788 +Test: [12500/21770] eta: 0:11:05 time: 0.0738 data: 0.0021 max mem: 19788 +Test: [12600/21770] eta: 0:10:57 time: 0.0692 data: 0.0020 max mem: 19788 +Test: [12700/21770] eta: 0:10:50 time: 0.0794 data: 0.0023 max mem: 19788 +Test: [12800/21770] eta: 0:10:44 time: 0.0862 data: 0.0027 max mem: 19788 +Test: [12900/21770] eta: 0:10:37 time: 0.0848 data: 0.0023 max mem: 19788 +Test: [13000/21770] eta: 0:10:30 time: 0.0657 data: 0.0018 max mem: 19788 +Test: [13100/21770] eta: 0:10:22 time: 0.0677 data: 0.0021 max mem: 19788 +Test: [13200/21770] eta: 0:10:15 time: 0.0703 data: 0.0021 max mem: 19788 +Test: [13300/21770] eta: 0:10:07 time: 0.0672 data: 0.0018 max mem: 19788 +Test: [13400/21770] eta: 0:10:00 time: 0.0785 data: 0.0022 max mem: 19788 +Test: [13500/21770] eta: 0:09:53 time: 0.0672 data: 0.0020 max mem: 19788 +Test: [13600/21770] eta: 0:09:46 time: 0.0644 data: 0.0019 max mem: 19788 +Test: [13700/21770] eta: 0:09:38 time: 0.0726 data: 0.0021 max mem: 19788 +Test: [13800/21770] eta: 0:09:31 time: 0.0680 data: 0.0020 max mem: 19788 +Test: [13900/21770] eta: 0:09:24 time: 0.0718 data: 0.0021 max mem: 19788 +Test: [14000/21770] eta: 0:09:17 time: 0.0852 data: 0.0027 max mem: 19788 +Test: [14100/21770] eta: 0:09:10 time: 0.0792 data: 0.0024 max mem: 19788 +Test: [14200/21770] eta: 0:09:03 time: 0.0649 data: 0.0020 max mem: 19788 +Test: [14300/21770] eta: 0:08:56 time: 0.0775 data: 0.0022 max mem: 19788 +Test: [14400/21770] eta: 0:08:49 time: 0.0659 data: 0.0020 max mem: 19788 +Test: [14500/21770] eta: 0:08:41 time: 0.0633 data: 0.0020 max mem: 19788 +Test: [14600/21770] eta: 0:08:34 time: 0.0831 data: 0.0025 max mem: 19788 +Test: [14700/21770] eta: 0:08:27 time: 0.0649 data: 0.0021 max mem: 19788 +Test: [14800/21770] eta: 0:08:20 time: 0.0842 data: 0.0027 max mem: 19788 +Test: [14900/21770] eta: 0:08:13 time: 0.0771 data: 0.0022 max mem: 19788 +Test: [15000/21770] eta: 0:08:05 time: 0.0737 data: 0.0021 max mem: 19788 +Test: [15100/21770] eta: 0:07:58 time: 0.0706 data: 0.0022 max mem: 19788 +Test: [15200/21770] eta: 0:07:51 time: 0.0773 data: 0.0021 max mem: 19788 +Test: [15300/21770] eta: 0:07:44 time: 0.0635 data: 0.0020 max mem: 19788 +Test: [15400/21770] eta: 0:07:37 time: 0.0738 data: 0.0020 max mem: 19788 +Test: [15500/21770] eta: 0:07:30 time: 0.0787 data: 0.0025 max mem: 19788 +Test: [15600/21770] eta: 0:07:23 time: 0.0671 data: 0.0019 max mem: 19788 +Test: [15700/21770] eta: 0:07:16 time: 0.0710 data: 0.0020 max mem: 19788 +Test: [15800/21770] eta: 0:07:09 time: 0.0699 data: 0.0021 max mem: 19788 +Test: [15900/21770] eta: 0:07:02 time: 0.0865 data: 0.0027 max mem: 19788 +Test: [16000/21770] eta: 0:06:55 time: 0.0660 data: 0.0020 max mem: 19788 +Test: [16100/21770] eta: 0:06:47 time: 0.0724 data: 0.0021 max mem: 19788 +Test: [16200/21770] eta: 0:06:40 time: 0.0724 data: 0.0023 max mem: 19788 +Test: [16300/21770] eta: 0:06:33 time: 0.0634 data: 0.0019 max mem: 19788 +Test: [16400/21770] eta: 0:06:26 time: 0.0846 data: 0.0021 max mem: 19788 +Test: [16500/21770] eta: 0:06:19 time: 0.0691 data: 0.0020 max mem: 19788 +Test: [16600/21770] eta: 0:06:12 time: 0.0785 data: 0.0024 max mem: 19788 +Test: [16700/21770] eta: 0:06:04 time: 0.0655 data: 0.0021 max mem: 19788 +Test: [16800/21770] eta: 0:05:57 time: 0.0664 data: 0.0023 max mem: 19788 +Test: [16900/21770] eta: 0:05:50 time: 0.0643 data: 0.0021 max mem: 19788 +Test: [17000/21770] eta: 0:05:43 time: 0.0676 data: 0.0022 max mem: 19788 +Test: [17100/21770] eta: 0:05:36 time: 0.0728 data: 0.0024 max mem: 19788 +Test: [17200/21770] eta: 0:05:28 time: 0.0648 data: 0.0019 max mem: 19788 +Test: [17300/21770] eta: 0:05:21 time: 0.0621 data: 0.0020 max mem: 19788 +Test: [17400/21770] eta: 0:05:14 time: 0.0633 data: 0.0019 max mem: 19788 +Test: [17500/21770] eta: 0:05:06 time: 0.0754 data: 0.0020 max mem: 19788 +Test: [17600/21770] eta: 0:04:59 time: 0.0656 data: 0.0020 max mem: 19788 +Test: [17700/21770] eta: 0:04:52 time: 0.0835 data: 0.0026 max mem: 19788 +Test: [17800/21770] eta: 0:04:45 time: 0.0652 data: 0.0018 max mem: 19788 +Test: [17900/21770] eta: 0:04:37 time: 0.0790 data: 0.0021 max mem: 19788 +Test: [18000/21770] eta: 0:04:30 time: 0.0843 data: 0.0021 max mem: 19788 +Test: [18100/21770] eta: 0:04:23 time: 0.0662 data: 0.0022 max mem: 19788 +Test: [18200/21770] eta: 0:04:16 time: 0.0680 data: 0.0020 max mem: 19788 +Test: [18300/21770] eta: 0:04:09 time: 0.0743 data: 0.0024 max mem: 19788 +Test: [18400/21770] eta: 0:04:01 time: 0.0712 data: 0.0022 max mem: 19788 +Test: [18500/21770] eta: 0:03:54 time: 0.0656 data: 0.0022 max mem: 19788 +Test: [18600/21770] eta: 0:03:47 time: 0.0853 data: 0.0026 max mem: 19788 +Test: [18700/21770] eta: 0:03:40 time: 0.0698 data: 0.0022 max mem: 19788 +Test: [18800/21770] eta: 0:03:33 time: 0.0783 data: 0.0025 max mem: 19788 +Test: [18900/21770] eta: 0:03:26 time: 0.0730 data: 0.0023 max mem: 19788 +Test: [19000/21770] eta: 0:03:18 time: 0.0760 data: 0.0021 max mem: 19788 +Test: [19100/21770] eta: 0:03:11 time: 0.0829 data: 0.0027 max mem: 19788 +Test: [19200/21770] eta: 0:03:04 time: 0.0734 data: 0.0023 max mem: 19788 +Test: [19300/21770] eta: 0:02:57 time: 0.0700 data: 0.0021 max mem: 19788 +Test: [19400/21770] eta: 0:02:50 time: 0.0717 data: 0.0022 max mem: 19788 +Test: [19500/21770] eta: 0:02:43 time: 0.0674 data: 0.0023 max mem: 19788 +Test: [19600/21770] eta: 0:02:35 time: 0.0651 data: 0.0020 max mem: 19788 +Test: [19700/21770] eta: 0:02:28 time: 0.0828 data: 0.0023 max mem: 19788 +Test: [19800/21770] eta: 0:02:21 time: 0.0663 data: 0.0023 max mem: 19788 +Test: [19900/21770] eta: 0:02:14 time: 0.0673 data: 0.0022 max mem: 19788 +Test: [20000/21770] eta: 0:02:07 time: 0.0646 data: 0.0021 max mem: 19788 +Test: [20100/21770] eta: 0:02:00 time: 0.0678 data: 0.0021 max mem: 19788 +Test: [20200/21770] eta: 0:01:52 time: 0.0674 data: 0.0020 max mem: 19788 +Test: [20300/21770] eta: 0:01:45 time: 0.0644 data: 0.0019 max mem: 19788 +Test: [20400/21770] eta: 0:01:38 time: 0.0754 data: 0.0022 max mem: 19788 +Test: [20500/21770] eta: 0:01:31 time: 0.0681 data: 0.0021 max mem: 19788 +Test: [20600/21770] eta: 0:01:24 time: 0.0711 data: 0.0021 max mem: 19788 +Test: [20700/21770] eta: 0:01:16 time: 0.0646 data: 0.0020 max mem: 19788 +Test: [20800/21770] eta: 0:01:09 time: 0.0783 data: 0.0024 max mem: 19788 +Test: [20900/21770] eta: 0:01:02 time: 0.0679 data: 0.0020 max mem: 19788 +Test: [21000/21770] eta: 0:00:55 time: 0.0828 data: 0.0025 max mem: 19788 +Test: [21100/21770] eta: 0:00:48 time: 0.0720 data: 0.0019 max mem: 19788 +Test: [21200/21770] eta: 0:00:40 time: 0.0819 data: 0.0021 max mem: 19788 +Test: [21300/21770] eta: 0:00:33 time: 0.0756 data: 0.0024 max mem: 19788 +Test: [21400/21770] eta: 0:00:26 time: 0.0845 data: 0.0025 max mem: 19788 +Test: [21500/21770] eta: 0:00:19 time: 0.0678 data: 0.0020 max mem: 19788 +Test: [21600/21770] eta: 0:00:12 time: 0.1272 data: 0.0070 max mem: 19788 +Test: [21700/21770] eta: 0:00:05 time: 0.0619 data: 0.0020 max mem: 19788 +Test: Total time: 0:26:06 +Final results: +Mean IoU is 63.07 + + precision@0.5 = 69.96 + precision@0.6 = 64.71 + precision@0.7 = 58.04 + precision@0.8 = 47.66 + precision@0.9 = 23.78 + overall IoU = 64.01 + mean IoU = 63.07 + +Mean accuracy for one-to-zero sample is 87.19 + +Average object IoU 0.6307322531103872 +Overall IoU 64.01131439208984 +Epoch: [34] [ 0/2138] eta: 7:10:57 lr: 9.06612424811779e-06 loss: 0.0199 (0.0199) time: 12.0944 data: 1.5964 max mem: 19788 +Epoch: [34] [ 10/2138] eta: 2:50:14 lr: 9.059762799630787e-06 loss: 0.0173 (0.0180) time: 4.7999 data: 0.1484 max mem: 19788 +Epoch: [34] [ 20/2138] eta: 2:37:01 lr: 9.053400854795385e-06 loss: 0.0165 (0.0176) time: 4.0661 data: 0.0037 max mem: 19788 +Epoch: [34] [ 30/2138] eta: 2:31:47 lr: 9.047038413185262e-06 loss: 0.0174 (0.0179) time: 4.0570 data: 0.0037 max mem: 19788 +Epoch: [34] [ 40/2138] eta: 2:28:40 lr: 9.040675474373383e-06 loss: 0.0201 (0.0193) time: 4.0454 data: 0.0036 max mem: 19788 +Epoch: [34] [ 50/2138] eta: 2:26:34 lr: 9.034312037932008e-06 loss: 0.0220 (0.0197) time: 4.0440 data: 0.0033 max mem: 19788 +Epoch: [34] [ 60/2138] eta: 2:24:56 lr: 9.02794810343271e-06 loss: 0.0191 (0.0195) time: 4.0477 data: 0.0033 max mem: 19788 +Epoch: [34] [ 70/2138] eta: 2:23:34 lr: 9.021583670446336e-06 loss: 0.0174 (0.0193) time: 4.0462 data: 0.0034 max mem: 19788 +Epoch: [34] [ 80/2138] eta: 2:22:21 lr: 9.015218738543049e-06 loss: 0.0170 (0.0194) time: 4.0457 data: 0.0034 max mem: 19788 +Epoch: [34] [ 90/2138] eta: 2:21:17 lr: 9.008853307292282e-06 loss: 0.0189 (0.0194) time: 4.0470 data: 0.0032 max mem: 19788 +Epoch: [34] [ 100/2138] eta: 2:20:15 lr: 9.00248737626278e-06 loss: 0.0189 (0.0195) time: 4.0428 data: 0.0033 max mem: 19788 +Epoch: [34] [ 110/2138] eta: 2:19:13 lr: 8.996120945022555e-06 loss: 0.0205 (0.0196) time: 4.0268 data: 0.0034 max mem: 19788 +Epoch: [34] [ 120/2138] eta: 2:18:17 lr: 8.989754013138922e-06 loss: 0.0205 (0.0197) time: 4.0222 data: 0.0033 max mem: 19788 +Epoch: [34] [ 130/2138] eta: 2:17:23 lr: 8.983386580178468e-06 loss: 0.0209 (0.0199) time: 4.0302 data: 0.0034 max mem: 19788 +Epoch: [34] [ 140/2138] eta: 2:16:32 lr: 8.977018645707081e-06 loss: 0.0226 (0.0201) time: 4.0321 data: 0.0033 max mem: 19788 +Epoch: [34] [ 150/2138] eta: 2:15:42 lr: 8.970650209289907e-06 loss: 0.0185 (0.0199) time: 4.0324 data: 0.0033 max mem: 19788 +Epoch: [34] [ 160/2138] eta: 2:14:55 lr: 8.964281270491393e-06 loss: 0.0200 (0.0202) time: 4.0386 data: 0.0033 max mem: 19788 +Epoch: [34] [ 170/2138] eta: 2:14:07 lr: 8.957911828875244e-06 loss: 0.0215 (0.0203) time: 4.0395 data: 0.0035 max mem: 19788 +Epoch: [34] [ 180/2138] eta: 2:13:21 lr: 8.951541884004466e-06 loss: 0.0211 (0.0204) time: 4.0378 data: 0.0035 max mem: 19788 +Epoch: [34] [ 190/2138] eta: 2:12:35 lr: 8.945171435441311e-06 loss: 0.0174 (0.0203) time: 4.0403 data: 0.0033 max mem: 19788 +Epoch: [34] [ 200/2138] eta: 2:11:50 lr: 8.938800482747331e-06 loss: 0.0148 (0.0200) time: 4.0399 data: 0.0033 max mem: 19788 +Epoch: [34] [ 210/2138] eta: 2:11:06 lr: 8.932429025483322e-06 loss: 0.0214 (0.0203) time: 4.0402 data: 0.0032 max mem: 19788 +Epoch: [34] [ 220/2138] eta: 2:10:21 lr: 8.926057063209373e-06 loss: 0.0225 (0.0202) time: 4.0387 data: 0.0033 max mem: 19788 +Epoch: [34] [ 230/2138] eta: 2:09:37 lr: 8.919684595484821e-06 loss: 0.0210 (0.0204) time: 4.0385 data: 0.0033 max mem: 19788 +Epoch: [34] [ 240/2138] eta: 2:08:57 lr: 8.913311621868286e-06 loss: 0.0208 (0.0203) time: 4.0595 data: 0.0031 max mem: 19788 +Epoch: [34] [ 250/2138] eta: 2:08:13 lr: 8.906938141917634e-06 loss: 0.0183 (0.0203) time: 4.0590 data: 0.0031 max mem: 19788 +Epoch: [34] [ 260/2138] eta: 2:07:31 lr: 8.900564155190008e-06 loss: 0.0181 (0.0202) time: 4.0453 data: 0.0034 max mem: 19788 +Epoch: [34] [ 270/2138] eta: 2:06:47 lr: 8.894189661241798e-06 loss: 0.0192 (0.0203) time: 4.0434 data: 0.0035 max mem: 19788 +Epoch: [34] [ 280/2138] eta: 2:06:04 lr: 8.887814659628666e-06 loss: 0.0192 (0.0202) time: 4.0357 data: 0.0033 max mem: 19788 +Epoch: [34] [ 290/2138] eta: 2:05:21 lr: 8.88143914990551e-06 loss: 0.0198 (0.0202) time: 4.0361 data: 0.0035 max mem: 19788 +Epoch: [34] [ 300/2138] eta: 2:04:39 lr: 8.87506313162651e-06 loss: 0.0188 (0.0202) time: 4.0388 data: 0.0034 max mem: 19788 +Epoch: [34] [ 310/2138] eta: 2:03:56 lr: 8.86868660434507e-06 loss: 0.0179 (0.0201) time: 4.0377 data: 0.0035 max mem: 19788 +Epoch: [34] [ 320/2138] eta: 2:03:13 lr: 8.862309567613872e-06 loss: 0.0193 (0.0202) time: 4.0358 data: 0.0034 max mem: 19788 +Epoch: [34] [ 330/2138] eta: 2:02:31 lr: 8.85593202098482e-06 loss: 0.0197 (0.0203) time: 4.0380 data: 0.0035 max mem: 19788 +Epoch: [34] [ 340/2138] eta: 2:01:49 lr: 8.849553964009087e-06 loss: 0.0194 (0.0202) time: 4.0338 data: 0.0036 max mem: 19788 +Epoch: [34] [ 350/2138] eta: 2:01:07 lr: 8.84317539623708e-06 loss: 0.0193 (0.0202) time: 4.0333 data: 0.0034 max mem: 19788 +Epoch: [34] [ 360/2138] eta: 2:00:25 lr: 8.836796317218444e-06 loss: 0.0198 (0.0202) time: 4.0406 data: 0.0035 max mem: 19788 +Epoch: [34] [ 370/2138] eta: 1:59:43 lr: 8.830416726502088e-06 loss: 0.0214 (0.0203) time: 4.0423 data: 0.0033 max mem: 19788 +Epoch: [34] [ 380/2138] eta: 1:59:02 lr: 8.824036623636128e-06 loss: 0.0188 (0.0203) time: 4.0427 data: 0.0033 max mem: 19788 +Epoch: [34] [ 390/2138] eta: 1:58:20 lr: 8.817656008167952e-06 loss: 0.0186 (0.0203) time: 4.0423 data: 0.0035 max mem: 19788 +Epoch: [34] [ 400/2138] eta: 1:57:39 lr: 8.81127487964415e-06 loss: 0.0206 (0.0203) time: 4.0430 data: 0.0035 max mem: 19788 +Epoch: [34] [ 410/2138] eta: 1:56:57 lr: 8.804893237610579e-06 loss: 0.0224 (0.0204) time: 4.0369 data: 0.0034 max mem: 19788 +Epoch: [34] [ 420/2138] eta: 1:56:16 lr: 8.798511081612298e-06 loss: 0.0219 (0.0204) time: 4.0411 data: 0.0033 max mem: 19788 +Epoch: [34] [ 430/2138] eta: 1:55:35 lr: 8.792128411193618e-06 loss: 0.0184 (0.0204) time: 4.0485 data: 0.0032 max mem: 19788 +Epoch: [34] [ 440/2138] eta: 1:54:53 lr: 8.785745225898062e-06 loss: 0.0195 (0.0206) time: 4.0377 data: 0.0031 max mem: 19788 +Epoch: [34] [ 450/2138] eta: 1:54:11 lr: 8.779361525268395e-06 loss: 0.0193 (0.0206) time: 4.0298 data: 0.0032 max mem: 19788 +Epoch: [34] [ 460/2138] eta: 1:53:30 lr: 8.772977308846589e-06 loss: 0.0209 (0.0206) time: 4.0364 data: 0.0035 max mem: 19788 +Epoch: [34] [ 470/2138] eta: 1:52:49 lr: 8.766592576173857e-06 loss: 0.0213 (0.0207) time: 4.0432 data: 0.0037 max mem: 19788 +Epoch: [34] [ 480/2138] eta: 1:52:08 lr: 8.760207326790609e-06 loss: 0.0212 (0.0208) time: 4.0456 data: 0.0037 max mem: 19788 +Epoch: [34] [ 490/2138] eta: 1:51:27 lr: 8.753821560236502e-06 loss: 0.0205 (0.0208) time: 4.0484 data: 0.0035 max mem: 19788 +Epoch: [34] [ 500/2138] eta: 1:50:46 lr: 8.747435276050378e-06 loss: 0.0189 (0.0207) time: 4.0494 data: 0.0034 max mem: 19788 +Epoch: [34] [ 510/2138] eta: 1:50:05 lr: 8.741048473770323e-06 loss: 0.0213 (0.0208) time: 4.0504 data: 0.0034 max mem: 19788 +Epoch: [34] [ 520/2138] eta: 1:49:24 lr: 8.734661152933609e-06 loss: 0.0205 (0.0207) time: 4.0471 data: 0.0034 max mem: 19788 +Epoch: [34] [ 530/2138] eta: 1:48:43 lr: 8.728273313076744e-06 loss: 0.0184 (0.0207) time: 4.0454 data: 0.0036 max mem: 19788 +Epoch: [34] [ 540/2138] eta: 1:48:03 lr: 8.721884953735419e-06 loss: 0.0184 (0.0207) time: 4.0473 data: 0.0035 max mem: 19788 +Epoch: [34] [ 550/2138] eta: 1:47:22 lr: 8.715496074444552e-06 loss: 0.0201 (0.0207) time: 4.0466 data: 0.0033 max mem: 19788 +Epoch: [34] [ 560/2138] eta: 1:46:40 lr: 8.709106674738252e-06 loss: 0.0201 (0.0207) time: 4.0401 data: 0.0036 max mem: 19788 +Epoch: [34] [ 570/2138] eta: 1:46:00 lr: 8.702716754149844e-06 loss: 0.0182 (0.0207) time: 4.0388 data: 0.0037 max mem: 19788 +Epoch: [34] [ 580/2138] eta: 1:45:18 lr: 8.696326312211833e-06 loss: 0.0198 (0.0208) time: 4.0344 data: 0.0035 max mem: 19788 +Epoch: [34] [ 590/2138] eta: 1:44:37 lr: 8.689935348455948e-06 loss: 0.0198 (0.0208) time: 4.0323 data: 0.0033 max mem: 19788 +Epoch: [34] [ 600/2138] eta: 1:43:56 lr: 8.683543862413087e-06 loss: 0.0197 (0.0208) time: 4.0368 data: 0.0033 max mem: 19788 +Epoch: [34] [ 610/2138] eta: 1:43:15 lr: 8.677151853613368e-06 loss: 0.0197 (0.0208) time: 4.0419 data: 0.0035 max mem: 19788 +Epoch: [34] [ 620/2138] eta: 1:42:34 lr: 8.67075932158608e-06 loss: 0.0208 (0.0208) time: 4.0403 data: 0.0033 max mem: 19788 +Epoch: [34] [ 630/2138] eta: 1:41:53 lr: 8.66436626585972e-06 loss: 0.0184 (0.0208) time: 4.0350 data: 0.0034 max mem: 19788 +Epoch: [34] [ 640/2138] eta: 1:41:12 lr: 8.657972685961956e-06 loss: 0.0185 (0.0207) time: 4.0361 data: 0.0035 max mem: 19788 +Epoch: [34] [ 650/2138] eta: 1:40:32 lr: 8.65157858141966e-06 loss: 0.0193 (0.0207) time: 4.0385 data: 0.0032 max mem: 19788 +Epoch: [34] [ 660/2138] eta: 1:39:51 lr: 8.645183951758876e-06 loss: 0.0198 (0.0207) time: 4.0509 data: 0.0031 max mem: 19788 +Epoch: [34] [ 670/2138] eta: 1:39:11 lr: 8.638788796504823e-06 loss: 0.0203 (0.0207) time: 4.0583 data: 0.0032 max mem: 19788 +Epoch: [34] [ 680/2138] eta: 1:38:30 lr: 8.632393115181923e-06 loss: 0.0199 (0.0207) time: 4.0472 data: 0.0033 max mem: 19788 +Epoch: [34] [ 690/2138] eta: 1:37:49 lr: 8.62599690731375e-06 loss: 0.0199 (0.0207) time: 4.0427 data: 0.0032 max mem: 19788 +Epoch: [34] [ 700/2138] eta: 1:37:09 lr: 8.619600172423082e-06 loss: 0.0202 (0.0207) time: 4.0500 data: 0.0031 max mem: 19788 +Epoch: [34] [ 710/2138] eta: 1:36:28 lr: 8.613202910031835e-06 loss: 0.0217 (0.0207) time: 4.0469 data: 0.0033 max mem: 19788 +Epoch: [34] [ 720/2138] eta: 1:35:47 lr: 8.606805119661135e-06 loss: 0.0177 (0.0207) time: 4.0426 data: 0.0034 max mem: 19788 +Epoch: [34] [ 730/2138] eta: 1:35:06 lr: 8.600406800831243e-06 loss: 0.0177 (0.0208) time: 4.0457 data: 0.0032 max mem: 19788 +Epoch: [34] [ 740/2138] eta: 1:34:26 lr: 8.594007953061615e-06 loss: 0.0172 (0.0207) time: 4.0497 data: 0.0032 max mem: 19788 +Epoch: [34] [ 750/2138] eta: 1:33:45 lr: 8.587608575870846e-06 loss: 0.0179 (0.0207) time: 4.0448 data: 0.0031 max mem: 19788 +Epoch: [34] [ 760/2138] eta: 1:33:04 lr: 8.58120866877672e-06 loss: 0.0210 (0.0207) time: 4.0399 data: 0.0030 max mem: 19788 +Epoch: [34] [ 770/2138] eta: 1:32:23 lr: 8.57480823129616e-06 loss: 0.0221 (0.0208) time: 4.0398 data: 0.0031 max mem: 19788 +Epoch: [34] [ 780/2138] eta: 1:31:43 lr: 8.568407262945264e-06 loss: 0.0226 (0.0208) time: 4.0368 data: 0.0034 max mem: 19788 +Epoch: [34] [ 790/2138] eta: 1:31:02 lr: 8.562005763239272e-06 loss: 0.0198 (0.0209) time: 4.0342 data: 0.0034 max mem: 19788 +Epoch: [34] [ 800/2138] eta: 1:30:21 lr: 8.555603731692594e-06 loss: 0.0186 (0.0209) time: 4.0453 data: 0.0031 max mem: 19788 +Epoch: [34] [ 810/2138] eta: 1:29:41 lr: 8.549201167818774e-06 loss: 0.0175 (0.0209) time: 4.0722 data: 0.0033 max mem: 19788 +Epoch: [34] [ 820/2138] eta: 1:29:02 lr: 8.542798071130524e-06 loss: 0.0196 (0.0209) time: 4.0891 data: 0.0034 max mem: 19788 +Epoch: [34] [ 830/2138] eta: 1:28:22 lr: 8.536394441139686e-06 loss: 0.0180 (0.0209) time: 4.0922 data: 0.0034 max mem: 19788 +Epoch: [34] [ 840/2138] eta: 1:27:42 lr: 8.529990277357268e-06 loss: 0.0168 (0.0209) time: 4.0896 data: 0.0035 max mem: 19788 +Epoch: [34] [ 850/2138] eta: 1:27:01 lr: 8.523585579293396e-06 loss: 0.0187 (0.0208) time: 4.0781 data: 0.0034 max mem: 19788 +Epoch: [34] [ 860/2138] eta: 1:26:21 lr: 8.517180346457367e-06 loss: 0.0200 (0.0208) time: 4.0654 data: 0.0037 max mem: 19788 +Epoch: [34] [ 870/2138] eta: 1:25:40 lr: 8.510774578357585e-06 loss: 0.0223 (0.0208) time: 4.0622 data: 0.0040 max mem: 19788 +Epoch: [34] [ 880/2138] eta: 1:25:00 lr: 8.50436827450162e-06 loss: 0.0212 (0.0208) time: 4.0707 data: 0.0036 max mem: 19788 +Epoch: [34] [ 890/2138] eta: 1:24:20 lr: 8.497961434396148e-06 loss: 0.0197 (0.0208) time: 4.0818 data: 0.0033 max mem: 19788 +Epoch: [34] [ 900/2138] eta: 1:23:40 lr: 8.491554057547008e-06 loss: 0.0216 (0.0209) time: 4.0826 data: 0.0032 max mem: 19788 +Epoch: [34] [ 910/2138] eta: 1:22:59 lr: 8.485146143459138e-06 loss: 0.0211 (0.0209) time: 4.0702 data: 0.0031 max mem: 19788 +Epoch: [34] [ 920/2138] eta: 1:22:19 lr: 8.478737691636632e-06 loss: 0.0205 (0.0209) time: 4.0655 data: 0.0033 max mem: 19788 +Epoch: [34] [ 930/2138] eta: 1:21:39 lr: 8.47232870158268e-06 loss: 0.0177 (0.0209) time: 4.0676 data: 0.0036 max mem: 19788 +Epoch: [34] [ 940/2138] eta: 1:20:58 lr: 8.465919172799627e-06 loss: 0.0204 (0.0209) time: 4.0617 data: 0.0035 max mem: 19788 +Epoch: [34] [ 950/2138] eta: 1:20:18 lr: 8.459509104788915e-06 loss: 0.0220 (0.0209) time: 4.0638 data: 0.0033 max mem: 19788 +Epoch: [34] [ 960/2138] eta: 1:19:38 lr: 8.453098497051105e-06 loss: 0.0210 (0.0209) time: 4.0776 data: 0.0035 max mem: 19788 +Epoch: [34] [ 970/2138] eta: 1:18:57 lr: 8.446687349085894e-06 loss: 0.0203 (0.0209) time: 4.0890 data: 0.0034 max mem: 19788 +Epoch: [34] [ 980/2138] eta: 1:18:17 lr: 8.440275660392066e-06 loss: 0.0185 (0.0209) time: 4.0884 data: 0.0035 max mem: 19788 +Epoch: [34] [ 990/2138] eta: 1:17:37 lr: 8.433863430467546e-06 loss: 0.0208 (0.0209) time: 4.0884 data: 0.0034 max mem: 19788 +Epoch: [34] [1000/2138] eta: 1:16:57 lr: 8.427450658809336e-06 loss: 0.0209 (0.0209) time: 4.0847 data: 0.0032 max mem: 19788 +Epoch: [34] [1010/2138] eta: 1:16:16 lr: 8.421037344913579e-06 loss: 0.0191 (0.0209) time: 4.0666 data: 0.0033 max mem: 19788 +Epoch: [34] [1020/2138] eta: 1:15:35 lr: 8.414623488275487e-06 loss: 0.0174 (0.0209) time: 4.0499 data: 0.0035 max mem: 19788 +Epoch: [34] [1030/2138] eta: 1:14:55 lr: 8.40820908838941e-06 loss: 0.0179 (0.0209) time: 4.0513 data: 0.0034 max mem: 19788 +Epoch: [34] [1040/2138] eta: 1:14:14 lr: 8.401794144748762e-06 loss: 0.0190 (0.0209) time: 4.0551 data: 0.0032 max mem: 19788 +Epoch: [34] [1050/2138] eta: 1:13:34 lr: 8.395378656846087e-06 loss: 0.0193 (0.0209) time: 4.0522 data: 0.0034 max mem: 19788 +Epoch: [34] [1060/2138] eta: 1:12:53 lr: 8.388962624173002e-06 loss: 0.0188 (0.0209) time: 4.0493 data: 0.0034 max mem: 19788 +Epoch: [34] [1070/2138] eta: 1:12:12 lr: 8.38254604622023e-06 loss: 0.0186 (0.0209) time: 4.0485 data: 0.0032 max mem: 19788 +Epoch: [34] [1080/2138] eta: 1:11:32 lr: 8.37612892247757e-06 loss: 0.0203 (0.0208) time: 4.0494 data: 0.0033 max mem: 19788 +Epoch: [34] [1090/2138] eta: 1:10:51 lr: 8.369711252433927e-06 loss: 0.0209 (0.0209) time: 4.0415 data: 0.0034 max mem: 19788 +Epoch: [34] [1100/2138] eta: 1:10:10 lr: 8.363293035577272e-06 loss: 0.0226 (0.0209) time: 4.0348 data: 0.0034 max mem: 19788 +Epoch: [34] [1110/2138] eta: 1:09:29 lr: 8.35687427139468e-06 loss: 0.0215 (0.0209) time: 4.0321 data: 0.0032 max mem: 19788 +Epoch: [34] [1120/2138] eta: 1:08:48 lr: 8.350454959372284e-06 loss: 0.0201 (0.0209) time: 3.9890 data: 0.0030 max mem: 19788 +Epoch: [34] [1130/2138] eta: 1:08:04 lr: 8.344035098995318e-06 loss: 0.0215 (0.0209) time: 3.7984 data: 0.0030 max mem: 19788 +Epoch: [34] [1140/2138] eta: 1:07:20 lr: 8.33761468974807e-06 loss: 0.0186 (0.0209) time: 3.6691 data: 0.0031 max mem: 19788 +Epoch: [34] [1150/2138] eta: 1:06:36 lr: 8.33119373111392e-06 loss: 0.0183 (0.0208) time: 3.6711 data: 0.0031 max mem: 19788 +Epoch: [34] [1160/2138] eta: 1:05:52 lr: 8.324772222575304e-06 loss: 0.0187 (0.0208) time: 3.6577 data: 0.0028 max mem: 19788 +Epoch: [34] [1170/2138] eta: 1:05:09 lr: 8.318350163613743e-06 loss: 0.0190 (0.0208) time: 3.6663 data: 0.0027 max mem: 19788 +Epoch: [34] [1180/2138] eta: 1:04:27 lr: 8.3119275537098e-06 loss: 0.0199 (0.0208) time: 3.7938 data: 0.0029 max mem: 19788 +Epoch: [34] [1190/2138] eta: 1:03:47 lr: 8.305504392343132e-06 loss: 0.0192 (0.0208) time: 3.9855 data: 0.0032 max mem: 19788 +Epoch: [34] [1200/2138] eta: 1:03:07 lr: 8.299080678992422e-06 loss: 0.0182 (0.0208) time: 4.0505 data: 0.0034 max mem: 19788 +Epoch: [34] [1210/2138] eta: 1:02:27 lr: 8.29265641313545e-06 loss: 0.0190 (0.0208) time: 4.0488 data: 0.0034 max mem: 19788 +Epoch: [34] [1220/2138] eta: 1:01:46 lr: 8.28623159424901e-06 loss: 0.0193 (0.0208) time: 4.0512 data: 0.0034 max mem: 19788 +Epoch: [34] [1230/2138] eta: 1:01:06 lr: 8.279806221808992e-06 loss: 0.0180 (0.0208) time: 4.0536 data: 0.0031 max mem: 19788 +Epoch: [34] [1240/2138] eta: 1:00:26 lr: 8.2733802952903e-06 loss: 0.0180 (0.0209) time: 4.0554 data: 0.0030 max mem: 19788 +Epoch: [34] [1250/2138] eta: 0:59:46 lr: 8.266953814166912e-06 loss: 0.0184 (0.0208) time: 4.0572 data: 0.0030 max mem: 19788 +Epoch: [34] [1260/2138] eta: 0:59:05 lr: 8.260526777911841e-06 loss: 0.0172 (0.0208) time: 4.0524 data: 0.0032 max mem: 19788 +Epoch: [34] [1270/2138] eta: 0:58:25 lr: 8.254099185997132e-06 loss: 0.0169 (0.0208) time: 4.0473 data: 0.0032 max mem: 19788 +Epoch: [34] [1280/2138] eta: 0:57:45 lr: 8.247671037893902e-06 loss: 0.0187 (0.0208) time: 4.0485 data: 0.0033 max mem: 19788 +Epoch: [34] [1290/2138] eta: 0:57:04 lr: 8.24124233307227e-06 loss: 0.0201 (0.0208) time: 4.0483 data: 0.0033 max mem: 19788 +Epoch: [34] [1300/2138] eta: 0:56:24 lr: 8.23481307100142e-06 loss: 0.0212 (0.0208) time: 4.0495 data: 0.0034 max mem: 19788 +Epoch: [34] [1310/2138] eta: 0:55:44 lr: 8.228383251149547e-06 loss: 0.0198 (0.0208) time: 4.0519 data: 0.0034 max mem: 19788 +Epoch: [34] [1320/2138] eta: 0:55:03 lr: 8.221952872983896e-06 loss: 0.0198 (0.0208) time: 4.0516 data: 0.0033 max mem: 19788 +Epoch: [34] [1330/2138] eta: 0:54:23 lr: 8.215521935970716e-06 loss: 0.0197 (0.0208) time: 4.0529 data: 0.0031 max mem: 19788 +Epoch: [34] [1340/2138] eta: 0:53:43 lr: 8.209090439575307e-06 loss: 0.0197 (0.0208) time: 4.0549 data: 0.0032 max mem: 19788 +Epoch: [34] [1350/2138] eta: 0:53:02 lr: 8.202658383261967e-06 loss: 0.0221 (0.0209) time: 4.0524 data: 0.0036 max mem: 19788 +Epoch: [34] [1360/2138] eta: 0:52:22 lr: 8.196225766494039e-06 loss: 0.0228 (0.0209) time: 4.0342 data: 0.0037 max mem: 19788 +Epoch: [34] [1370/2138] eta: 0:51:42 lr: 8.189792588733856e-06 loss: 0.0186 (0.0209) time: 4.0325 data: 0.0034 max mem: 19788 +Epoch: [34] [1380/2138] eta: 0:51:01 lr: 8.18335884944279e-06 loss: 0.0196 (0.0209) time: 4.0508 data: 0.0031 max mem: 19788 +Epoch: [34] [1390/2138] eta: 0:50:21 lr: 8.176924548081203e-06 loss: 0.0207 (0.0209) time: 4.0560 data: 0.0030 max mem: 19788 +Epoch: [34] [1400/2138] eta: 0:49:41 lr: 8.170489684108492e-06 loss: 0.0205 (0.0209) time: 4.0484 data: 0.0031 max mem: 19788 +Epoch: [34] [1410/2138] eta: 0:49:00 lr: 8.164054256983028e-06 loss: 0.0193 (0.0209) time: 4.0480 data: 0.0031 max mem: 19788 +Epoch: [34] [1420/2138] eta: 0:48:20 lr: 8.15761826616222e-06 loss: 0.0195 (0.0209) time: 4.0456 data: 0.0029 max mem: 19788 +Epoch: [34] [1430/2138] eta: 0:47:40 lr: 8.151181711102447e-06 loss: 0.0199 (0.0209) time: 4.0411 data: 0.0030 max mem: 19788 +Epoch: [34] [1440/2138] eta: 0:46:59 lr: 8.144744591259113e-06 loss: 0.0187 (0.0208) time: 4.0414 data: 0.0033 max mem: 19788 +Epoch: [34] [1450/2138] eta: 0:46:19 lr: 8.138306906086591e-06 loss: 0.0208 (0.0209) time: 4.0399 data: 0.0034 max mem: 19788 +Epoch: [34] [1460/2138] eta: 0:45:38 lr: 8.131868655038278e-06 loss: 0.0235 (0.0209) time: 4.0473 data: 0.0032 max mem: 19788 +Epoch: [34] [1470/2138] eta: 0:44:58 lr: 8.125429837566527e-06 loss: 0.0217 (0.0209) time: 4.0472 data: 0.0030 max mem: 19788 +Epoch: [34] [1480/2138] eta: 0:44:18 lr: 8.11899045312271e-06 loss: 0.0226 (0.0209) time: 4.0432 data: 0.0031 max mem: 19788 +Epoch: [34] [1490/2138] eta: 0:43:37 lr: 8.112550501157156e-06 loss: 0.0218 (0.0209) time: 4.0435 data: 0.0030 max mem: 19788 +Epoch: [34] [1500/2138] eta: 0:42:57 lr: 8.106109981119203e-06 loss: 0.0190 (0.0209) time: 4.0409 data: 0.0031 max mem: 19788 +Epoch: [34] [1510/2138] eta: 0:42:16 lr: 8.099668892457138e-06 loss: 0.0199 (0.0209) time: 4.0390 data: 0.0034 max mem: 19788 +Epoch: [34] [1520/2138] eta: 0:41:36 lr: 8.093227234618256e-06 loss: 0.0199 (0.0209) time: 4.0419 data: 0.0033 max mem: 19788 +Epoch: [34] [1530/2138] eta: 0:40:56 lr: 8.086785007048794e-06 loss: 0.0172 (0.0209) time: 4.0387 data: 0.0031 max mem: 19788 +Epoch: [34] [1540/2138] eta: 0:40:15 lr: 8.08034220919399e-06 loss: 0.0168 (0.0209) time: 4.0541 data: 0.0030 max mem: 19788 +Epoch: [34] [1550/2138] eta: 0:39:35 lr: 8.073898840498022e-06 loss: 0.0185 (0.0209) time: 4.0521 data: 0.0030 max mem: 19788 +Epoch: [34] [1560/2138] eta: 0:38:54 lr: 8.067454900404056e-06 loss: 0.0207 (0.0209) time: 4.0272 data: 0.0032 max mem: 19788 +Epoch: [34] [1570/2138] eta: 0:38:14 lr: 8.061010388354205e-06 loss: 0.0190 (0.0209) time: 4.0261 data: 0.0034 max mem: 19788 +Epoch: [34] [1580/2138] eta: 0:37:34 lr: 8.05456530378954e-06 loss: 0.0183 (0.0209) time: 4.0366 data: 0.0033 max mem: 19788 +Epoch: [34] [1590/2138] eta: 0:36:53 lr: 8.048119646150107e-06 loss: 0.0187 (0.0209) time: 4.0406 data: 0.0032 max mem: 19788 +Epoch: [34] [1600/2138] eta: 0:36:13 lr: 8.04167341487488e-06 loss: 0.0221 (0.0209) time: 4.0413 data: 0.0030 max mem: 19788 +Epoch: [34] [1610/2138] eta: 0:35:32 lr: 8.03522660940181e-06 loss: 0.0211 (0.0209) time: 4.0432 data: 0.0030 max mem: 19788 +Epoch: [34] [1620/2138] eta: 0:34:52 lr: 8.028779229167767e-06 loss: 0.0178 (0.0209) time: 4.0456 data: 0.0031 max mem: 19788 +Epoch: [34] [1630/2138] eta: 0:34:12 lr: 8.022331273608595e-06 loss: 0.0194 (0.0209) time: 4.0463 data: 0.0034 max mem: 19788 +Epoch: [34] [1640/2138] eta: 0:33:31 lr: 8.015882742159055e-06 loss: 0.0190 (0.0209) time: 4.0419 data: 0.0035 max mem: 19788 +Epoch: [34] [1650/2138] eta: 0:32:51 lr: 8.009433634252867e-06 loss: 0.0175 (0.0208) time: 4.0391 data: 0.0033 max mem: 19788 +Epoch: [34] [1660/2138] eta: 0:32:11 lr: 8.002983949322667e-06 loss: 0.0175 (0.0208) time: 4.0365 data: 0.0031 max mem: 19788 +Epoch: [34] [1670/2138] eta: 0:31:30 lr: 7.996533686800046e-06 loss: 0.0171 (0.0208) time: 4.0400 data: 0.0030 max mem: 19788 +Epoch: [34] [1680/2138] eta: 0:30:50 lr: 7.990082846115503e-06 loss: 0.0199 (0.0208) time: 4.0409 data: 0.0032 max mem: 19788 +Epoch: [34] [1690/2138] eta: 0:30:09 lr: 7.983631426698484e-06 loss: 0.0200 (0.0208) time: 4.0430 data: 0.0033 max mem: 19788 +Epoch: [34] [1700/2138] eta: 0:29:29 lr: 7.977179427977342e-06 loss: 0.0182 (0.0208) time: 4.0429 data: 0.0033 max mem: 19788 +Epoch: [34] [1710/2138] eta: 0:28:49 lr: 7.970726849379368e-06 loss: 0.0186 (0.0208) time: 4.0358 data: 0.0033 max mem: 19788 +Epoch: [34] [1720/2138] eta: 0:28:08 lr: 7.964273690330751e-06 loss: 0.0208 (0.0208) time: 4.0383 data: 0.0032 max mem: 19788 +Epoch: [34] [1730/2138] eta: 0:27:28 lr: 7.95781995025662e-06 loss: 0.0208 (0.0208) time: 4.0378 data: 0.0033 max mem: 19788 +Epoch: [34] [1740/2138] eta: 0:26:47 lr: 7.951365628580984e-06 loss: 0.0198 (0.0208) time: 4.0380 data: 0.0032 max mem: 19788 +Epoch: [34] [1750/2138] eta: 0:26:07 lr: 7.944910724726799e-06 loss: 0.0197 (0.0208) time: 4.0365 data: 0.0032 max mem: 19788 +Epoch: [34] [1760/2138] eta: 0:25:27 lr: 7.93845523811589e-06 loss: 0.0209 (0.0208) time: 4.0304 data: 0.0033 max mem: 19788 +Epoch: [34] [1770/2138] eta: 0:24:46 lr: 7.931999168169015e-06 loss: 0.0191 (0.0208) time: 4.0274 data: 0.0032 max mem: 19788 +Epoch: [34] [1780/2138] eta: 0:24:06 lr: 7.925542514305807e-06 loss: 0.0190 (0.0208) time: 4.0236 data: 0.0031 max mem: 19788 +Epoch: [34] [1790/2138] eta: 0:23:25 lr: 7.91908527594482e-06 loss: 0.0190 (0.0208) time: 4.0332 data: 0.0033 max mem: 19788 +Epoch: [34] [1800/2138] eta: 0:22:45 lr: 7.91262745250348e-06 loss: 0.0181 (0.0208) time: 4.0402 data: 0.0033 max mem: 19788 +Epoch: [34] [1810/2138] eta: 0:22:04 lr: 7.906169043398118e-06 loss: 0.0179 (0.0208) time: 4.0434 data: 0.0032 max mem: 19788 +Epoch: [34] [1820/2138] eta: 0:21:24 lr: 7.899710048043938e-06 loss: 0.0200 (0.0208) time: 4.0473 data: 0.0032 max mem: 19788 +Epoch: [34] [1830/2138] eta: 0:20:44 lr: 7.893250465855052e-06 loss: 0.0200 (0.0208) time: 4.0418 data: 0.0030 max mem: 19788 +Epoch: [34] [1840/2138] eta: 0:20:03 lr: 7.886790296244425e-06 loss: 0.0202 (0.0208) time: 4.0391 data: 0.0031 max mem: 19788 +Epoch: [34] [1850/2138] eta: 0:19:23 lr: 7.880329538623922e-06 loss: 0.0218 (0.0208) time: 4.0376 data: 0.0032 max mem: 19788 +Epoch: [34] [1860/2138] eta: 0:18:43 lr: 7.873868192404264e-06 loss: 0.0205 (0.0208) time: 4.0396 data: 0.0032 max mem: 19788 +Epoch: [34] [1870/2138] eta: 0:18:02 lr: 7.867406256995068e-06 loss: 0.0191 (0.0208) time: 4.0380 data: 0.0034 max mem: 19788 +Epoch: [34] [1880/2138] eta: 0:17:22 lr: 7.860943731804796e-06 loss: 0.0193 (0.0208) time: 4.0359 data: 0.0033 max mem: 19788 +Epoch: [34] [1890/2138] eta: 0:16:41 lr: 7.85448061624078e-06 loss: 0.0193 (0.0208) time: 4.0436 data: 0.0031 max mem: 19788 +Epoch: [34] [1900/2138] eta: 0:16:01 lr: 7.848016909709229e-06 loss: 0.0167 (0.0208) time: 4.0420 data: 0.0031 max mem: 19788 +Epoch: [34] [1910/2138] eta: 0:15:21 lr: 7.841552611615188e-06 loss: 0.0196 (0.0208) time: 4.0383 data: 0.0032 max mem: 19788 +Epoch: [34] [1920/2138] eta: 0:14:40 lr: 7.835087721362584e-06 loss: 0.0200 (0.0208) time: 4.0324 data: 0.0032 max mem: 19788 +Epoch: [34] [1930/2138] eta: 0:14:00 lr: 7.828622238354167e-06 loss: 0.0197 (0.0208) time: 4.0336 data: 0.0033 max mem: 19788 +Epoch: [34] [1940/2138] eta: 0:13:19 lr: 7.822156161991564e-06 loss: 0.0208 (0.0208) time: 4.0379 data: 0.0033 max mem: 19788 +Epoch: [34] [1950/2138] eta: 0:12:39 lr: 7.815689491675221e-06 loss: 0.0202 (0.0208) time: 4.0401 data: 0.0032 max mem: 19788 +Epoch: [34] [1960/2138] eta: 0:11:59 lr: 7.809222226804454e-06 loss: 0.0192 (0.0208) time: 4.0486 data: 0.0033 max mem: 19788 +Epoch: [34] [1970/2138] eta: 0:11:18 lr: 7.80275436677739e-06 loss: 0.0192 (0.0208) time: 4.0465 data: 0.0031 max mem: 19788 +Epoch: [34] [1980/2138] eta: 0:10:38 lr: 7.79628591099102e-06 loss: 0.0167 (0.0208) time: 4.0445 data: 0.0029 max mem: 19788 +Epoch: [34] [1990/2138] eta: 0:09:57 lr: 7.78981685884114e-06 loss: 0.0169 (0.0208) time: 4.0330 data: 0.0030 max mem: 19788 +Epoch: [34] [2000/2138] eta: 0:09:17 lr: 7.7833472097224e-06 loss: 0.0189 (0.0208) time: 4.0244 data: 0.0031 max mem: 19788 +Epoch: [34] [2010/2138] eta: 0:08:37 lr: 7.776876963028254e-06 loss: 0.0219 (0.0208) time: 4.0282 data: 0.0032 max mem: 19788 +Epoch: [34] [2020/2138] eta: 0:07:56 lr: 7.770406118151e-06 loss: 0.0206 (0.0208) time: 4.0264 data: 0.0032 max mem: 19788 +Epoch: [34] [2030/2138] eta: 0:07:16 lr: 7.76393467448173e-06 loss: 0.0206 (0.0208) time: 4.0217 data: 0.0032 max mem: 19788 +Epoch: [34] [2040/2138] eta: 0:06:35 lr: 7.757462631410378e-06 loss: 0.0206 (0.0208) time: 4.0221 data: 0.0031 max mem: 19788 +Epoch: [34] [2050/2138] eta: 0:05:55 lr: 7.750989988325667e-06 loss: 0.0199 (0.0208) time: 4.0373 data: 0.0034 max mem: 19788 +Epoch: [34] [2060/2138] eta: 0:05:15 lr: 7.744516744615152e-06 loss: 0.0196 (0.0208) time: 4.0452 data: 0.0037 max mem: 19788 +Epoch: [34] [2070/2138] eta: 0:04:34 lr: 7.738042899665167e-06 loss: 0.0205 (0.0208) time: 4.0344 data: 0.0038 max mem: 19788 +Epoch: [34] [2080/2138] eta: 0:03:54 lr: 7.731568452860874e-06 loss: 0.0213 (0.0208) time: 4.0350 data: 0.0037 max mem: 19788 +Epoch: [34] [2090/2138] eta: 0:03:13 lr: 7.72509340358621e-06 loss: 0.0200 (0.0208) time: 4.0409 data: 0.0034 max mem: 19788 +Epoch: [34] [2100/2138] eta: 0:02:33 lr: 7.71861775122393e-06 loss: 0.0194 (0.0207) time: 4.0371 data: 0.0031 max mem: 19788 +Epoch: [34] [2110/2138] eta: 0:01:53 lr: 7.712141495155556e-06 loss: 0.0216 (0.0208) time: 4.0421 data: 0.0030 max mem: 19788 +Epoch: [34] [2120/2138] eta: 0:01:12 lr: 7.705664634761423e-06 loss: 0.0246 (0.0208) time: 4.0498 data: 0.0032 max mem: 19788 +Epoch: [34] [2130/2138] eta: 0:00:32 lr: 7.69918716942063e-06 loss: 0.0220 (0.0208) time: 4.0340 data: 0.0031 max mem: 19788 +Epoch: [34] Total time: 2:23:56 +Test: [ 0/21770] eta: 18:33:42 time: 3.0695 data: 2.8173 max mem: 19788 +Test: [ 100/21770] eta: 0:35:32 time: 0.0641 data: 0.0019 max mem: 19788 +Test: [ 200/21770] eta: 0:30:07 time: 0.0659 data: 0.0021 max mem: 19788 +Test: [ 300/21770] eta: 0:28:45 time: 0.0797 data: 0.0029 max mem: 19788 +Test: [ 400/21770] eta: 0:27:26 time: 0.0646 data: 0.0019 max mem: 19788 +Test: [ 500/21770] eta: 0:26:37 time: 0.0626 data: 0.0019 max mem: 19788 +Test: [ 600/21770] eta: 0:26:17 time: 0.0700 data: 0.0021 max mem: 19788 +Test: [ 700/21770] eta: 0:26:02 time: 0.0681 data: 0.0021 max mem: 19788 +Test: [ 800/21770] eta: 0:25:40 time: 0.0790 data: 0.0021 max mem: 19788 +Test: [ 900/21770] eta: 0:25:36 time: 0.0719 data: 0.0022 max mem: 19788 +Test: [ 1000/21770] eta: 0:25:19 time: 0.0652 data: 0.0022 max mem: 19788 +Test: [ 1100/21770] eta: 0:24:56 time: 0.0637 data: 0.0020 max mem: 19788 +Test: [ 1200/21770] eta: 0:24:40 time: 0.0731 data: 0.0025 max mem: 19788 +Test: [ 1300/21770] eta: 0:24:35 time: 0.0720 data: 0.0025 max mem: 19788 +Test: [ 1400/21770] eta: 0:24:28 time: 0.0715 data: 0.0025 max mem: 19788 +Test: [ 1500/21770] eta: 0:24:16 time: 0.0650 data: 0.0019 max mem: 19788 +Test: [ 1600/21770] eta: 0:23:59 time: 0.0645 data: 0.0020 max mem: 19788 +Test: [ 1700/21770] eta: 0:24:01 time: 0.0701 data: 0.0023 max mem: 19788 +Test: [ 1800/21770] eta: 0:23:51 time: 0.0774 data: 0.0025 max mem: 19788 +Test: [ 1900/21770] eta: 0:23:38 time: 0.0694 data: 0.0022 max mem: 19788 +Test: [ 2000/21770] eta: 0:23:28 time: 0.0621 data: 0.0018 max mem: 19788 +Test: [ 2100/21770] eta: 0:23:16 time: 0.0661 data: 0.0021 max mem: 19788 +Test: [ 2200/21770] eta: 0:23:06 time: 0.0631 data: 0.0019 max mem: 19788 +Test: [ 2300/21770] eta: 0:22:58 time: 0.0625 data: 0.0020 max mem: 19788 +Test: [ 2400/21770] eta: 0:22:56 time: 0.0849 data: 0.0020 max mem: 19788 +Test: [ 2500/21770] eta: 0:22:53 time: 0.0737 data: 0.0022 max mem: 19788 +Test: [ 2600/21770] eta: 0:22:47 time: 0.0703 data: 0.0023 max mem: 19788 +Test: [ 2700/21770] eta: 0:22:37 time: 0.0657 data: 0.0020 max mem: 19788 +Test: [ 2800/21770] eta: 0:22:31 time: 0.0737 data: 0.0024 max mem: 19788 +Test: [ 2900/21770] eta: 0:22:24 time: 0.0660 data: 0.0019 max mem: 19788 +Test: [ 3000/21770] eta: 0:22:22 time: 0.0852 data: 0.0028 max mem: 19788 +Test: [ 3100/21770] eta: 0:22:17 time: 0.0722 data: 0.0023 max mem: 19788 +Test: [ 3200/21770] eta: 0:22:09 time: 0.0774 data: 0.0023 max mem: 19788 +Test: [ 3300/21770] eta: 0:22:03 time: 0.0656 data: 0.0021 max mem: 19788 +Test: [ 3400/21770] eta: 0:21:52 time: 0.0703 data: 0.0022 max mem: 19788 +Test: [ 3500/21770] eta: 0:21:44 time: 0.0669 data: 0.0021 max mem: 19788 +Test: [ 3600/21770] eta: 0:21:34 time: 0.0643 data: 0.0018 max mem: 19788 +Test: [ 3700/21770] eta: 0:21:26 time: 0.0691 data: 0.0021 max mem: 19788 +Test: [ 3800/21770] eta: 0:21:25 time: 0.0852 data: 0.0027 max mem: 19788 +Test: [ 3900/21770] eta: 0:21:20 time: 0.0665 data: 0.0020 max mem: 19788 +Test: [ 4000/21770] eta: 0:21:16 time: 0.0801 data: 0.0026 max mem: 19788 +Test: [ 4100/21770] eta: 0:21:10 time: 0.0866 data: 0.0023 max mem: 19788 +Test: [ 4200/21770] eta: 0:21:04 time: 0.0775 data: 0.0023 max mem: 19788 +Test: [ 4300/21770] eta: 0:20:57 time: 0.0645 data: 0.0021 max mem: 19788 +Test: [ 4400/21770] eta: 0:20:51 time: 0.0666 data: 0.0022 max mem: 19788 +Test: [ 4500/21770] eta: 0:20:44 time: 0.0726 data: 0.0023 max mem: 19788 +Test: [ 4600/21770] eta: 0:20:37 time: 0.0621 data: 0.0019 max mem: 19788 +Test: [ 4700/21770] eta: 0:20:28 time: 0.0654 data: 0.0018 max mem: 19788 +Test: [ 4800/21770] eta: 0:20:20 time: 0.0623 data: 0.0021 max mem: 19788 +Test: [ 4900/21770] eta: 0:20:12 time: 0.0629 data: 0.0021 max mem: 19788 +Test: [ 5000/21770] eta: 0:20:05 time: 0.0717 data: 0.0022 max mem: 19788 +Test: [ 5100/21770] eta: 0:19:56 time: 0.0652 data: 0.0022 max mem: 19788 +Test: [ 5200/21770] eta: 0:19:51 time: 0.0670 data: 0.0019 max mem: 19788 +Test: [ 5300/21770] eta: 0:19:42 time: 0.0626 data: 0.0019 max mem: 19788 +Test: [ 5400/21770] eta: 0:19:33 time: 0.0633 data: 0.0019 max mem: 19788 +Test: [ 5500/21770] eta: 0:19:23 time: 0.0658 data: 0.0018 max mem: 19788 +Test: [ 5600/21770] eta: 0:19:17 time: 0.0850 data: 0.0025 max mem: 19788 +Test: [ 5700/21770] eta: 0:19:08 time: 0.0659 data: 0.0019 max mem: 19788 +Test: [ 5800/21770] eta: 0:19:02 time: 0.0786 data: 0.0024 max mem: 19788 +Test: [ 5900/21770] eta: 0:18:53 time: 0.0659 data: 0.0019 max mem: 19788 +Test: [ 6000/21770] eta: 0:18:45 time: 0.0721 data: 0.0023 max mem: 19788 +Test: [ 6100/21770] eta: 0:18:37 time: 0.0643 data: 0.0024 max mem: 19788 +Test: [ 6200/21770] eta: 0:18:31 time: 0.0777 data: 0.0026 max mem: 19788 +Test: [ 6300/21770] eta: 0:18:23 time: 0.0720 data: 0.0022 max mem: 19788 +Test: [ 6400/21770] eta: 0:18:17 time: 0.0658 data: 0.0019 max mem: 19788 +Test: [ 6500/21770] eta: 0:18:08 time: 0.0648 data: 0.0019 max mem: 19788 +Test: [ 6600/21770] eta: 0:18:00 time: 0.0694 data: 0.0017 max mem: 19788 +Test: [ 6700/21770] eta: 0:17:53 time: 0.0857 data: 0.0027 max mem: 19788 +Test: [ 6800/21770] eta: 0:17:45 time: 0.0708 data: 0.0020 max mem: 19788 +Test: [ 6900/21770] eta: 0:17:37 time: 0.0652 data: 0.0019 max mem: 19788 +Test: [ 7000/21770] eta: 0:17:30 time: 0.0631 data: 0.0017 max mem: 19788 +Test: [ 7100/21770] eta: 0:17:24 time: 0.0702 data: 0.0020 max mem: 19788 +Test: [ 7200/21770] eta: 0:17:18 time: 0.0671 data: 0.0020 max mem: 19788 +Test: [ 7300/21770] eta: 0:17:11 time: 0.0660 data: 0.0018 max mem: 19788 +Test: [ 7400/21770] eta: 0:17:02 time: 0.0648 data: 0.0020 max mem: 19788 +Test: [ 7500/21770] eta: 0:16:55 time: 0.0715 data: 0.0021 max mem: 19788 +Test: [ 7600/21770] eta: 0:16:49 time: 0.0659 data: 0.0018 max mem: 19788 +Test: [ 7700/21770] eta: 0:16:41 time: 0.0650 data: 0.0019 max mem: 19788 +Test: [ 7800/21770] eta: 0:16:33 time: 0.0689 data: 0.0019 max mem: 19788 +Test: [ 7900/21770] eta: 0:16:28 time: 0.0767 data: 0.0022 max mem: 19788 +Test: [ 8000/21770] eta: 0:16:22 time: 0.0766 data: 0.0023 max mem: 19788 +Test: [ 8100/21770] eta: 0:16:14 time: 0.0729 data: 0.0022 max mem: 19788 +Test: [ 8200/21770] eta: 0:16:07 time: 0.0633 data: 0.0021 max mem: 19788 +Test: [ 8300/21770] eta: 0:15:59 time: 0.0701 data: 0.0019 max mem: 19788 +Test: [ 8400/21770] eta: 0:15:53 time: 0.0838 data: 0.0024 max mem: 19788 +Test: [ 8500/21770] eta: 0:15:45 time: 0.0733 data: 0.0020 max mem: 19788 +Test: [ 8600/21770] eta: 0:15:38 time: 0.0659 data: 0.0019 max mem: 19788 +Test: [ 8700/21770] eta: 0:15:30 time: 0.0658 data: 0.0020 max mem: 19788 +Test: [ 8800/21770] eta: 0:15:22 time: 0.0660 data: 0.0019 max mem: 19788 +Test: [ 8900/21770] eta: 0:15:15 time: 0.0810 data: 0.0025 max mem: 19788 +Test: [ 9000/21770] eta: 0:15:08 time: 0.0766 data: 0.0023 max mem: 19788 +Test: [ 9100/21770] eta: 0:15:00 time: 0.0628 data: 0.0020 max mem: 19788 +Test: [ 9200/21770] eta: 0:14:53 time: 0.0773 data: 0.0022 max mem: 19788 +Test: [ 9300/21770] eta: 0:14:47 time: 0.0747 data: 0.0020 max mem: 19788 +Test: [ 9400/21770] eta: 0:14:40 time: 0.0812 data: 0.0026 max mem: 19788 +Test: [ 9500/21770] eta: 0:14:34 time: 0.0850 data: 0.0027 max mem: 19788 +Test: [ 9600/21770] eta: 0:14:26 time: 0.0668 data: 0.0019 max mem: 19788 +Test: [ 9700/21770] eta: 0:14:19 time: 0.0712 data: 0.0021 max mem: 19788 +Test: [ 9800/21770] eta: 0:14:12 time: 0.0665 data: 0.0021 max mem: 19788 +Test: [ 9900/21770] eta: 0:14:05 time: 0.0827 data: 0.0025 max mem: 19788 +Test: [10000/21770] eta: 0:13:57 time: 0.0649 data: 0.0018 max mem: 19788 +Test: [10100/21770] eta: 0:13:51 time: 0.0842 data: 0.0026 max mem: 19788 +Test: [10200/21770] eta: 0:13:44 time: 0.0670 data: 0.0020 max mem: 19788 +Test: [10300/21770] eta: 0:13:37 time: 0.0652 data: 0.0020 max mem: 19788 +Test: [10400/21770] eta: 0:13:29 time: 0.0704 data: 0.0023 max mem: 19788 +Test: [10500/21770] eta: 0:13:22 time: 0.0698 data: 0.0020 max mem: 19788 +Test: [10600/21770] eta: 0:13:15 time: 0.0668 data: 0.0020 max mem: 19788 +Test: [10700/21770] eta: 0:13:08 time: 0.0678 data: 0.0020 max mem: 19788 +Test: [10800/21770] eta: 0:13:02 time: 0.0674 data: 0.0020 max mem: 19788 +Test: [10900/21770] eta: 0:12:54 time: 0.0666 data: 0.0018 max mem: 19788 +Test: [11000/21770] eta: 0:12:47 time: 0.0723 data: 0.0021 max mem: 19788 +Test: [11100/21770] eta: 0:12:40 time: 0.0682 data: 0.0020 max mem: 19788 +Test: [11200/21770] eta: 0:12:34 time: 0.0813 data: 0.0026 max mem: 19788 +Test: [11300/21770] eta: 0:12:26 time: 0.0623 data: 0.0018 max mem: 19788 +Test: [11400/21770] eta: 0:12:19 time: 0.0740 data: 0.0020 max mem: 19788 +Test: [11500/21770] eta: 0:12:12 time: 0.0640 data: 0.0018 max mem: 19788 +Test: [11600/21770] eta: 0:12:05 time: 0.0648 data: 0.0020 max mem: 19788 +Test: [11700/21770] eta: 0:11:58 time: 0.0844 data: 0.0025 max mem: 19788 +Test: [11800/21770] eta: 0:11:51 time: 0.0685 data: 0.0022 max mem: 19788 +Test: [11900/21770] eta: 0:11:44 time: 0.0690 data: 0.0019 max mem: 19788 +Test: [12000/21770] eta: 0:11:37 time: 0.0721 data: 0.0023 max mem: 19788 +Test: [12100/21770] eta: 0:11:30 time: 0.0753 data: 0.0024 max mem: 19788 +Test: [12200/21770] eta: 0:11:23 time: 0.0737 data: 0.0023 max mem: 19788 +Test: [12300/21770] eta: 0:11:16 time: 0.0756 data: 0.0023 max mem: 19788 +Test: [12400/21770] eta: 0:11:09 time: 0.0774 data: 0.0022 max mem: 19788 +Test: [12500/21770] eta: 0:11:02 time: 0.0725 data: 0.0024 max mem: 19788 +Test: [12600/21770] eta: 0:10:54 time: 0.0676 data: 0.0020 max mem: 19788 +Test: [12700/21770] eta: 0:10:47 time: 0.0687 data: 0.0022 max mem: 19788 +Test: [12800/21770] eta: 0:10:40 time: 0.0752 data: 0.0023 max mem: 19788 +Test: [12900/21770] eta: 0:10:33 time: 0.0650 data: 0.0020 max mem: 19788 +Test: [13000/21770] eta: 0:10:26 time: 0.0665 data: 0.0020 max mem: 19788 +Test: [13100/21770] eta: 0:10:18 time: 0.0674 data: 0.0021 max mem: 19788 +Test: [13200/21770] eta: 0:10:11 time: 0.0685 data: 0.0020 max mem: 19788 +Test: [13300/21770] eta: 0:10:04 time: 0.0639 data: 0.0019 max mem: 19788 +Test: [13400/21770] eta: 0:09:56 time: 0.0664 data: 0.0019 max mem: 19788 +Test: [13500/21770] eta: 0:09:49 time: 0.0675 data: 0.0018 max mem: 19788 +Test: [13600/21770] eta: 0:09:42 time: 0.0663 data: 0.0022 max mem: 19788 +Test: [13700/21770] eta: 0:09:35 time: 0.0782 data: 0.0025 max mem: 19788 +Test: [13800/21770] eta: 0:09:28 time: 0.0839 data: 0.0027 max mem: 19788 +Test: [13900/21770] eta: 0:09:21 time: 0.0788 data: 0.0025 max mem: 19788 +Test: [14000/21770] eta: 0:09:14 time: 0.0820 data: 0.0026 max mem: 19788 +Test: [14100/21770] eta: 0:09:06 time: 0.0665 data: 0.0020 max mem: 19788 +Test: [14200/21770] eta: 0:08:59 time: 0.0686 data: 0.0022 max mem: 19788 +Test: [14300/21770] eta: 0:08:53 time: 0.0847 data: 0.0027 max mem: 19788 +Test: [14400/21770] eta: 0:08:46 time: 0.0653 data: 0.0019 max mem: 19788 +Test: [14500/21770] eta: 0:08:39 time: 0.0683 data: 0.0021 max mem: 19788 +Test: [14600/21770] eta: 0:08:31 time: 0.0699 data: 0.0021 max mem: 19788 +Test: [14700/21770] eta: 0:08:24 time: 0.0852 data: 0.0027 max mem: 19788 +Test: [14800/21770] eta: 0:08:17 time: 0.0654 data: 0.0019 max mem: 19788 +Test: [14900/21770] eta: 0:08:10 time: 0.0689 data: 0.0022 max mem: 19788 +Test: [15000/21770] eta: 0:08:03 time: 0.0815 data: 0.0027 max mem: 19788 +Test: [15100/21770] eta: 0:07:55 time: 0.0675 data: 0.0021 max mem: 19788 +Test: [15200/21770] eta: 0:07:49 time: 0.0652 data: 0.0019 max mem: 19788 +Test: [15300/21770] eta: 0:07:41 time: 0.0661 data: 0.0020 max mem: 19788 +Test: [15400/21770] eta: 0:07:34 time: 0.0652 data: 0.0019 max mem: 19788 +Test: [15500/21770] eta: 0:07:27 time: 0.0681 data: 0.0022 max mem: 19788 +Test: [15600/21770] eta: 0:07:20 time: 0.0665 data: 0.0021 max mem: 19788 +Test: [15700/21770] eta: 0:07:13 time: 0.0686 data: 0.0018 max mem: 19788 +Test: [15800/21770] eta: 0:07:05 time: 0.0649 data: 0.0021 max mem: 19788 +Test: [15900/21770] eta: 0:06:58 time: 0.0756 data: 0.0024 max mem: 19788 +Test: [16000/21770] eta: 0:06:52 time: 0.0701 data: 0.0019 max mem: 19788 +Test: [16100/21770] eta: 0:06:44 time: 0.0640 data: 0.0019 max mem: 19788 +Test: [16200/21770] eta: 0:06:37 time: 0.0670 data: 0.0020 max mem: 19788 +Test: [16300/21770] eta: 0:06:30 time: 0.0740 data: 0.0022 max mem: 19788 +Test: [16400/21770] eta: 0:06:23 time: 0.0652 data: 0.0019 max mem: 19788 +Test: [16500/21770] eta: 0:06:16 time: 0.0674 data: 0.0019 max mem: 19788 +Test: [16600/21770] eta: 0:06:08 time: 0.0801 data: 0.0022 max mem: 19788 +Test: [16700/21770] eta: 0:06:01 time: 0.0699 data: 0.0022 max mem: 19788 +Test: [16800/21770] eta: 0:05:54 time: 0.0862 data: 0.0025 max mem: 19788 +Test: [16900/21770] eta: 0:05:47 time: 0.0749 data: 0.0021 max mem: 19788 +Test: [17000/21770] eta: 0:05:40 time: 0.0757 data: 0.0022 max mem: 19788 +Test: [17100/21770] eta: 0:05:33 time: 0.0802 data: 0.0023 max mem: 19788 +Test: [17200/21770] eta: 0:05:26 time: 0.0671 data: 0.0018 max mem: 19788 +Test: [17300/21770] eta: 0:05:19 time: 0.0783 data: 0.0023 max mem: 19788 +Test: [17400/21770] eta: 0:05:11 time: 0.0650 data: 0.0019 max mem: 19788 +Test: [17500/21770] eta: 0:05:04 time: 0.0643 data: 0.0020 max mem: 19788 +Test: [17600/21770] eta: 0:04:57 time: 0.0690 data: 0.0021 max mem: 19788 +Test: [17700/21770] eta: 0:04:50 time: 0.0684 data: 0.0022 max mem: 19788 +Test: [17800/21770] eta: 0:04:42 time: 0.0650 data: 0.0022 max mem: 19788 +Test: [17900/21770] eta: 0:04:35 time: 0.0862 data: 0.0025 max mem: 19788 +Test: [18000/21770] eta: 0:04:28 time: 0.0793 data: 0.0025 max mem: 19788 +Test: [18100/21770] eta: 0:04:21 time: 0.0658 data: 0.0021 max mem: 19788 +Test: [18200/21770] eta: 0:04:14 time: 0.0729 data: 0.0021 max mem: 19788 +Test: [18300/21770] eta: 0:04:07 time: 0.0849 data: 0.0027 max mem: 19788 +Test: [18400/21770] eta: 0:04:00 time: 0.0642 data: 0.0018 max mem: 19788 +Test: [18500/21770] eta: 0:03:53 time: 0.0698 data: 0.0022 max mem: 19788 +Test: [18600/21770] eta: 0:03:46 time: 0.0714 data: 0.0022 max mem: 19788 +Test: [18700/21770] eta: 0:03:38 time: 0.0650 data: 0.0020 max mem: 19788 +Test: [18800/21770] eta: 0:03:31 time: 0.0753 data: 0.0021 max mem: 19788 +Test: [18900/21770] eta: 0:03:24 time: 0.0854 data: 0.0026 max mem: 19788 +Test: [19000/21770] eta: 0:03:17 time: 0.0769 data: 0.0025 max mem: 19788 +Test: [19100/21770] eta: 0:03:10 time: 0.0848 data: 0.0027 max mem: 19788 +Test: [19200/21770] eta: 0:03:03 time: 0.0675 data: 0.0021 max mem: 19788 +Test: [19300/21770] eta: 0:02:56 time: 0.0757 data: 0.0023 max mem: 19788 +Test: [19400/21770] eta: 0:02:48 time: 0.0655 data: 0.0019 max mem: 19788 +Test: [19500/21770] eta: 0:02:41 time: 0.0794 data: 0.0025 max mem: 19788 +Test: [19600/21770] eta: 0:02:34 time: 0.0642 data: 0.0020 max mem: 19788 +Test: [19700/21770] eta: 0:02:27 time: 0.0683 data: 0.0022 max mem: 19788 +Test: [19800/21770] eta: 0:02:20 time: 0.0710 data: 0.0020 max mem: 19788 +Test: [19900/21770] eta: 0:02:13 time: 0.0754 data: 0.0025 max mem: 19788 +Test: [20000/21770] eta: 0:02:06 time: 0.0677 data: 0.0019 max mem: 19788 +Test: [20100/21770] eta: 0:01:59 time: 0.0710 data: 0.0022 max mem: 19788 +Test: [20200/21770] eta: 0:01:51 time: 0.0798 data: 0.0025 max mem: 19788 +Test: [20300/21770] eta: 0:01:44 time: 0.0664 data: 0.0021 max mem: 19788 +Test: [20400/21770] eta: 0:01:37 time: 0.0769 data: 0.0021 max mem: 19788 +Test: [20500/21770] eta: 0:01:30 time: 0.0638 data: 0.0018 max mem: 19788 +Test: [20600/21770] eta: 0:01:23 time: 0.0795 data: 0.0025 max mem: 19788 +Test: [20700/21770] eta: 0:01:16 time: 0.0855 data: 0.0027 max mem: 19788 +Test: [20800/21770] eta: 0:01:09 time: 0.0641 data: 0.0020 max mem: 19788 +Test: [20900/21770] eta: 0:01:02 time: 0.0854 data: 0.0026 max mem: 19788 +Test: [21000/21770] eta: 0:00:54 time: 0.0691 data: 0.0020 max mem: 19788 +Test: [21100/21770] eta: 0:00:47 time: 0.0867 data: 0.0026 max mem: 19788 +Test: [21200/21770] eta: 0:00:40 time: 0.0785 data: 0.0022 max mem: 19788 +Test: [21300/21770] eta: 0:00:33 time: 0.0639 data: 0.0021 max mem: 19788 +Test: [21400/21770] eta: 0:00:26 time: 0.0684 data: 0.0022 max mem: 19788 +Test: [21500/21770] eta: 0:00:19 time: 0.0654 data: 0.0021 max mem: 19788 +Test: [21600/21770] eta: 0:00:12 time: 0.0771 data: 0.0020 max mem: 19788 +Test: [21700/21770] eta: 0:00:04 time: 0.0719 data: 0.0021 max mem: 19788 +Test: Total time: 0:25:55 +Final results: +Mean IoU is 62.83 + + precision@0.5 = 69.65 + precision@0.6 = 64.52 + precision@0.7 = 58.02 + precision@0.8 = 47.68 + precision@0.9 = 23.84 + overall IoU = 63.99 + mean IoU = 62.83 + +Mean accuracy for one-to-zero sample is 86.59 + +Average object IoU 0.6282844911138323 +Overall IoU 63.98686218261719 +Epoch: [35] [ 0/2138] eta: 10:52:26 lr: 7.694004761168391e-06 loss: 0.0197 (0.0197) time: 18.3101 data: 2.3192 max mem: 19788 +Epoch: [35] [ 10/2138] eta: 3:10:12 lr: 7.687526205355074e-06 loss: 0.0171 (0.0179) time: 5.3630 data: 0.2159 max mem: 19788 +Epoch: [35] [ 20/2138] eta: 2:47:26 lr: 7.681047042850111e-06 loss: 0.0168 (0.0173) time: 4.0652 data: 0.0043 max mem: 19788 +Epoch: [35] [ 30/2138] eta: 2:38:59 lr: 7.674567273027946e-06 loss: 0.0170 (0.0176) time: 4.0643 data: 0.0033 max mem: 19788 +Epoch: [35] [ 40/2138] eta: 2:34:15 lr: 7.668086895261816e-06 loss: 0.0202 (0.0190) time: 4.0632 data: 0.0037 max mem: 19788 +Epoch: [35] [ 50/2138] eta: 2:31:06 lr: 7.661605908923695e-06 loss: 0.0209 (0.0193) time: 4.0584 data: 0.0034 max mem: 19788 +Epoch: [35] [ 60/2138] eta: 2:28:49 lr: 7.655124313384348e-06 loss: 0.0180 (0.0190) time: 4.0617 data: 0.0032 max mem: 19788 +Epoch: [35] [ 70/2138] eta: 2:27:00 lr: 7.648642108013265e-06 loss: 0.0163 (0.0187) time: 4.0696 data: 0.0032 max mem: 19788 +Epoch: [35] [ 80/2138] eta: 2:25:25 lr: 7.642159292178717e-06 loss: 0.0168 (0.0189) time: 4.0658 data: 0.0031 max mem: 19788 +Epoch: [35] [ 90/2138] eta: 2:24:00 lr: 7.635675865247698e-06 loss: 0.0177 (0.0187) time: 4.0549 data: 0.0033 max mem: 19788 +Epoch: [35] [ 100/2138] eta: 2:22:45 lr: 7.629191826585974e-06 loss: 0.0179 (0.0189) time: 4.0541 data: 0.0036 max mem: 19788 +Epoch: [35] [ 110/2138] eta: 2:21:36 lr: 7.6227071755580306e-06 loss: 0.0189 (0.0190) time: 4.0554 data: 0.0036 max mem: 19788 +Epoch: [35] [ 120/2138] eta: 2:20:32 lr: 7.616221911527111e-06 loss: 0.0205 (0.0191) time: 4.0565 data: 0.0034 max mem: 19788 +Epoch: [35] [ 130/2138] eta: 2:19:30 lr: 7.609736033855172e-06 loss: 0.0212 (0.0192) time: 4.0531 data: 0.0035 max mem: 19788 +Epoch: [35] [ 140/2138] eta: 2:18:33 lr: 7.6032495419029265e-06 loss: 0.0212 (0.0192) time: 4.0508 data: 0.0035 max mem: 19788 +Epoch: [35] [ 150/2138] eta: 2:17:35 lr: 7.5967624350297885e-06 loss: 0.0196 (0.0192) time: 4.0487 data: 0.0033 max mem: 19788 +Epoch: [35] [ 160/2138] eta: 2:16:41 lr: 7.5902747125939214e-06 loss: 0.0206 (0.0195) time: 4.0472 data: 0.0034 max mem: 19788 +Epoch: [35] [ 170/2138] eta: 2:15:49 lr: 7.5837863739521825e-06 loss: 0.0219 (0.0196) time: 4.0501 data: 0.0033 max mem: 19788 +Epoch: [35] [ 180/2138] eta: 2:14:56 lr: 7.57729741846017e-06 loss: 0.0190 (0.0196) time: 4.0426 data: 0.0031 max mem: 19788 +Epoch: [35] [ 190/2138] eta: 2:14:05 lr: 7.570807845472172e-06 loss: 0.0176 (0.0196) time: 4.0408 data: 0.0031 max mem: 19788 +Epoch: [35] [ 200/2138] eta: 2:13:15 lr: 7.564317654341205e-06 loss: 0.0142 (0.0194) time: 4.0413 data: 0.0032 max mem: 19788 +Epoch: [35] [ 210/2138] eta: 2:12:27 lr: 7.557826844418969e-06 loss: 0.0212 (0.0196) time: 4.0458 data: 0.0033 max mem: 19788 +Epoch: [35] [ 220/2138] eta: 2:11:40 lr: 7.551335415055888e-06 loss: 0.0212 (0.0195) time: 4.0511 data: 0.0034 max mem: 19788 +Epoch: [35] [ 230/2138] eta: 2:10:54 lr: 7.544843365601066e-06 loss: 0.0200 (0.0197) time: 4.0537 data: 0.0035 max mem: 19788 +Epoch: [35] [ 240/2138] eta: 2:10:08 lr: 7.538350695402299e-06 loss: 0.0200 (0.0197) time: 4.0581 data: 0.0033 max mem: 19788 +Epoch: [35] [ 250/2138] eta: 2:09:22 lr: 7.53185740380609e-06 loss: 0.0177 (0.0196) time: 4.0521 data: 0.0033 max mem: 19788 +Epoch: [35] [ 260/2138] eta: 2:08:36 lr: 7.525363490157605e-06 loss: 0.0177 (0.0196) time: 4.0505 data: 0.0034 max mem: 19788 +Epoch: [35] [ 270/2138] eta: 2:07:51 lr: 7.518868953800712e-06 loss: 0.0186 (0.0197) time: 4.0497 data: 0.0034 max mem: 19788 +Epoch: [35] [ 280/2138] eta: 2:07:06 lr: 7.5123737940779345e-06 loss: 0.0196 (0.0196) time: 4.0508 data: 0.0033 max mem: 19788 +Epoch: [35] [ 290/2138] eta: 2:06:21 lr: 7.5058780103304945e-06 loss: 0.0207 (0.0197) time: 4.0496 data: 0.0033 max mem: 19788 +Epoch: [35] [ 300/2138] eta: 2:05:37 lr: 7.4993816018982575e-06 loss: 0.0204 (0.0197) time: 4.0466 data: 0.0033 max mem: 19788 +Epoch: [35] [ 310/2138] eta: 2:04:53 lr: 7.49288456811978e-06 loss: 0.0185 (0.0196) time: 4.0504 data: 0.0035 max mem: 19788 +Epoch: [35] [ 320/2138] eta: 2:04:09 lr: 7.486386908332256e-06 loss: 0.0194 (0.0197) time: 4.0457 data: 0.0036 max mem: 19788 +Epoch: [35] [ 330/2138] eta: 2:03:25 lr: 7.479888621871562e-06 loss: 0.0209 (0.0198) time: 4.0461 data: 0.0036 max mem: 19788 +Epoch: [35] [ 340/2138] eta: 2:02:42 lr: 7.473389708072198e-06 loss: 0.0190 (0.0198) time: 4.0521 data: 0.0035 max mem: 19788 +Epoch: [35] [ 350/2138] eta: 2:01:59 lr: 7.466890166267349e-06 loss: 0.0190 (0.0198) time: 4.0533 data: 0.0036 max mem: 19788 +Epoch: [35] [ 360/2138] eta: 2:01:16 lr: 7.4603899957888104e-06 loss: 0.0202 (0.0198) time: 4.0498 data: 0.0035 max mem: 19788 +Epoch: [35] [ 370/2138] eta: 2:00:33 lr: 7.45388919596705e-06 loss: 0.0196 (0.0198) time: 4.0480 data: 0.0033 max mem: 19788 +Epoch: [35] [ 380/2138] eta: 1:59:50 lr: 7.4473877661311435e-06 loss: 0.0189 (0.0198) time: 4.0495 data: 0.0038 max mem: 19788 +Epoch: [35] [ 390/2138] eta: 1:59:07 lr: 7.44088570560883e-06 loss: 0.0188 (0.0199) time: 4.0438 data: 0.0037 max mem: 19788 +Epoch: [35] [ 400/2138] eta: 1:58:24 lr: 7.43438301372645e-06 loss: 0.0201 (0.0199) time: 4.0410 data: 0.0034 max mem: 19788 +Epoch: [35] [ 410/2138] eta: 1:57:41 lr: 7.427879689808992e-06 loss: 0.0210 (0.0200) time: 4.0419 data: 0.0035 max mem: 19788 +Epoch: [35] [ 420/2138] eta: 1:56:58 lr: 7.421375733180044e-06 loss: 0.0215 (0.0199) time: 4.0389 data: 0.0036 max mem: 19788 +Epoch: [35] [ 430/2138] eta: 1:56:16 lr: 7.414871143161833e-06 loss: 0.0175 (0.0200) time: 4.0409 data: 0.0039 max mem: 19788 +Epoch: [35] [ 440/2138] eta: 1:55:33 lr: 7.4083659190751765e-06 loss: 0.0205 (0.0200) time: 4.0392 data: 0.0040 max mem: 19788 +Epoch: [35] [ 450/2138] eta: 1:54:51 lr: 7.401860060239522e-06 loss: 0.0204 (0.0201) time: 4.0436 data: 0.0037 max mem: 19788 +Epoch: [35] [ 460/2138] eta: 1:54:08 lr: 7.395353565972898e-06 loss: 0.0227 (0.0201) time: 4.0404 data: 0.0037 max mem: 19788 +Epoch: [35] [ 470/2138] eta: 1:53:26 lr: 7.388846435591958e-06 loss: 0.0216 (0.0201) time: 4.0304 data: 0.0036 max mem: 19788 +Epoch: [35] [ 480/2138] eta: 1:52:43 lr: 7.3823386684119245e-06 loss: 0.0206 (0.0202) time: 4.0346 data: 0.0033 max mem: 19788 +Epoch: [35] [ 490/2138] eta: 1:52:01 lr: 7.375830263746638e-06 loss: 0.0205 (0.0202) time: 4.0342 data: 0.0033 max mem: 19788 +Epoch: [35] [ 500/2138] eta: 1:51:19 lr: 7.369321220908502e-06 loss: 0.0187 (0.0202) time: 4.0402 data: 0.0034 max mem: 19788 +Epoch: [35] [ 510/2138] eta: 1:50:37 lr: 7.362811539208524e-06 loss: 0.0195 (0.0202) time: 4.0399 data: 0.0035 max mem: 19788 +Epoch: [35] [ 520/2138] eta: 1:49:55 lr: 7.3563012179562755e-06 loss: 0.0204 (0.0202) time: 4.0327 data: 0.0034 max mem: 19788 +Epoch: [35] [ 530/2138] eta: 1:49:13 lr: 7.349790256459899e-06 loss: 0.0187 (0.0202) time: 4.0305 data: 0.0033 max mem: 19788 +Epoch: [35] [ 540/2138] eta: 1:48:31 lr: 7.343278654026125e-06 loss: 0.0183 (0.0202) time: 4.0404 data: 0.0034 max mem: 19788 +Epoch: [35] [ 550/2138] eta: 1:47:50 lr: 7.3367664099602315e-06 loss: 0.0191 (0.0202) time: 4.0506 data: 0.0034 max mem: 19788 +Epoch: [35] [ 560/2138] eta: 1:47:08 lr: 7.330253523566072e-06 loss: 0.0191 (0.0202) time: 4.0370 data: 0.0035 max mem: 19788 +Epoch: [35] [ 570/2138] eta: 1:46:26 lr: 7.323739994146038e-06 loss: 0.0184 (0.0202) time: 4.0320 data: 0.0034 max mem: 19788 +Epoch: [35] [ 580/2138] eta: 1:45:44 lr: 7.317225821001099e-06 loss: 0.0205 (0.0202) time: 4.0362 data: 0.0033 max mem: 19788 +Epoch: [35] [ 590/2138] eta: 1:45:02 lr: 7.310711003430744e-06 loss: 0.0200 (0.0202) time: 4.0305 data: 0.0032 max mem: 19788 +Epoch: [35] [ 600/2138] eta: 1:44:21 lr: 7.304195540733031e-06 loss: 0.0188 (0.0202) time: 4.0386 data: 0.0032 max mem: 19788 +Epoch: [35] [ 610/2138] eta: 1:43:39 lr: 7.297679432204533e-06 loss: 0.0188 (0.0203) time: 4.0468 data: 0.0034 max mem: 19788 +Epoch: [35] [ 620/2138] eta: 1:42:58 lr: 7.291162677140381e-06 loss: 0.0194 (0.0203) time: 4.0395 data: 0.0034 max mem: 19788 +Epoch: [35] [ 630/2138] eta: 1:42:17 lr: 7.284645274834213e-06 loss: 0.0184 (0.0202) time: 4.0396 data: 0.0031 max mem: 19788 +Epoch: [35] [ 640/2138] eta: 1:41:35 lr: 7.278127224578214e-06 loss: 0.0185 (0.0202) time: 4.0473 data: 0.0031 max mem: 19788 +Epoch: [35] [ 650/2138] eta: 1:40:54 lr: 7.2716085256630695e-06 loss: 0.0184 (0.0202) time: 4.0542 data: 0.0034 max mem: 19788 +Epoch: [35] [ 660/2138] eta: 1:40:13 lr: 7.265089177378e-06 loss: 0.0183 (0.0202) time: 4.0492 data: 0.0033 max mem: 19788 +Epoch: [35] [ 670/2138] eta: 1:39:32 lr: 7.258569179010717e-06 loss: 0.0206 (0.0202) time: 4.0435 data: 0.0032 max mem: 19788 +Epoch: [35] [ 680/2138] eta: 1:38:50 lr: 7.252048529847464e-06 loss: 0.0214 (0.0202) time: 4.0367 data: 0.0032 max mem: 19788 +Epoch: [35] [ 690/2138] eta: 1:38:09 lr: 7.245527229172957e-06 loss: 0.0197 (0.0202) time: 4.0323 data: 0.0032 max mem: 19788 +Epoch: [35] [ 700/2138] eta: 1:37:28 lr: 7.239005276270443e-06 loss: 0.0196 (0.0202) time: 4.0366 data: 0.0032 max mem: 19788 +Epoch: [35] [ 710/2138] eta: 1:36:46 lr: 7.232482670421631e-06 loss: 0.0200 (0.0202) time: 4.0359 data: 0.0035 max mem: 19788 +Epoch: [35] [ 720/2138] eta: 1:36:05 lr: 7.225959410906742e-06 loss: 0.0189 (0.0202) time: 4.0333 data: 0.0036 max mem: 19788 +Epoch: [35] [ 730/2138] eta: 1:35:24 lr: 7.219435497004463e-06 loss: 0.0188 (0.0203) time: 4.0349 data: 0.0034 max mem: 19788 +Epoch: [35] [ 740/2138] eta: 1:34:43 lr: 7.212910927991977e-06 loss: 0.0182 (0.0202) time: 4.0372 data: 0.0034 max mem: 19788 +Epoch: [35] [ 750/2138] eta: 1:34:02 lr: 7.20638570314492e-06 loss: 0.0182 (0.0202) time: 4.0438 data: 0.0031 max mem: 19788 +Epoch: [35] [ 760/2138] eta: 1:33:21 lr: 7.1998598217374245e-06 loss: 0.0197 (0.0202) time: 4.0513 data: 0.0035 max mem: 19788 +Epoch: [35] [ 770/2138] eta: 1:32:40 lr: 7.193333283042057e-06 loss: 0.0209 (0.0202) time: 4.0461 data: 0.0035 max mem: 19788 +Epoch: [35] [ 780/2138] eta: 1:31:59 lr: 7.186806086329874e-06 loss: 0.0226 (0.0203) time: 4.0358 data: 0.0035 max mem: 19788 +Epoch: [35] [ 790/2138] eta: 1:31:18 lr: 7.18027823087036e-06 loss: 0.0187 (0.0203) time: 4.0350 data: 0.0035 max mem: 19788 +Epoch: [35] [ 800/2138] eta: 1:30:36 lr: 7.173749715931474e-06 loss: 0.0172 (0.0203) time: 4.0337 data: 0.0034 max mem: 19788 +Epoch: [35] [ 810/2138] eta: 1:29:55 lr: 7.1672205407795966e-06 loss: 0.0174 (0.0202) time: 4.0320 data: 0.0034 max mem: 19788 +Epoch: [35] [ 820/2138] eta: 1:29:14 lr: 7.160690704679575e-06 loss: 0.0201 (0.0203) time: 4.0406 data: 0.0033 max mem: 19788 +Epoch: [35] [ 830/2138] eta: 1:28:33 lr: 7.154160206894669e-06 loss: 0.0179 (0.0202) time: 4.0328 data: 0.0033 max mem: 19788 +Epoch: [35] [ 840/2138] eta: 1:27:52 lr: 7.147629046686574e-06 loss: 0.0168 (0.0202) time: 4.0270 data: 0.0034 max mem: 19788 +Epoch: [35] [ 850/2138] eta: 1:27:11 lr: 7.141097223315428e-06 loss: 0.0182 (0.0202) time: 4.0381 data: 0.0036 max mem: 19788 +Epoch: [35] [ 860/2138] eta: 1:26:30 lr: 7.134564736039762e-06 loss: 0.0209 (0.0202) time: 4.0395 data: 0.0039 max mem: 19788 +Epoch: [35] [ 870/2138] eta: 1:25:49 lr: 7.128031584116551e-06 loss: 0.0218 (0.0202) time: 4.0372 data: 0.0040 max mem: 19788 +Epoch: [35] [ 880/2138] eta: 1:25:08 lr: 7.121497766801155e-06 loss: 0.0187 (0.0202) time: 4.0448 data: 0.0036 max mem: 19788 +Epoch: [35] [ 890/2138] eta: 1:24:27 lr: 7.114963283347366e-06 loss: 0.0187 (0.0202) time: 4.0382 data: 0.0032 max mem: 19788 +Epoch: [35] [ 900/2138] eta: 1:23:46 lr: 7.1084281330073496e-06 loss: 0.0212 (0.0203) time: 4.0280 data: 0.0034 max mem: 19788 +Epoch: [35] [ 910/2138] eta: 1:23:05 lr: 7.1018923150316925e-06 loss: 0.0205 (0.0203) time: 4.0337 data: 0.0035 max mem: 19788 +Epoch: [35] [ 920/2138] eta: 1:22:24 lr: 7.095355828669348e-06 loss: 0.0198 (0.0203) time: 4.0337 data: 0.0032 max mem: 19788 +Epoch: [35] [ 930/2138] eta: 1:21:43 lr: 7.088818673167677e-06 loss: 0.0191 (0.0203) time: 4.0373 data: 0.0034 max mem: 19788 +Epoch: [35] [ 940/2138] eta: 1:21:03 lr: 7.082280847772402e-06 loss: 0.0200 (0.0203) time: 4.0376 data: 0.0034 max mem: 19788 +Epoch: [35] [ 950/2138] eta: 1:20:22 lr: 7.075742351727637e-06 loss: 0.0200 (0.0203) time: 4.0295 data: 0.0034 max mem: 19788 +Epoch: [35] [ 960/2138] eta: 1:19:41 lr: 7.069203184275848e-06 loss: 0.0199 (0.0203) time: 4.0295 data: 0.0035 max mem: 19788 +Epoch: [35] [ 970/2138] eta: 1:19:00 lr: 7.06266334465789e-06 loss: 0.0195 (0.0203) time: 4.0388 data: 0.0033 max mem: 19788 +Epoch: [35] [ 980/2138] eta: 1:18:19 lr: 7.056122832112947e-06 loss: 0.0180 (0.0203) time: 4.0529 data: 0.0034 max mem: 19788 +Epoch: [35] [ 990/2138] eta: 1:17:39 lr: 7.049581645878589e-06 loss: 0.0193 (0.0203) time: 4.0550 data: 0.0035 max mem: 19788 +Epoch: [35] [1000/2138] eta: 1:16:58 lr: 7.043039785190705e-06 loss: 0.0199 (0.0203) time: 4.0458 data: 0.0035 max mem: 19788 +Epoch: [35] [1010/2138] eta: 1:16:17 lr: 7.0364972492835595e-06 loss: 0.0195 (0.0203) time: 4.0403 data: 0.0034 max mem: 19788 +Epoch: [35] [1020/2138] eta: 1:15:36 lr: 7.029954037389721e-06 loss: 0.0175 (0.0203) time: 4.0403 data: 0.0031 max mem: 19788 +Epoch: [35] [1030/2138] eta: 1:14:55 lr: 7.023410148740126e-06 loss: 0.0180 (0.0203) time: 4.0397 data: 0.0030 max mem: 19788 +Epoch: [35] [1040/2138] eta: 1:14:15 lr: 7.016865582564006e-06 loss: 0.0185 (0.0203) time: 4.0415 data: 0.0030 max mem: 19788 +Epoch: [35] [1050/2138] eta: 1:13:34 lr: 7.010320338088945e-06 loss: 0.0190 (0.0203) time: 4.0395 data: 0.0031 max mem: 19788 +Epoch: [35] [1060/2138] eta: 1:12:53 lr: 7.003774414540815e-06 loss: 0.0190 (0.0203) time: 4.0305 data: 0.0033 max mem: 19788 +Epoch: [35] [1070/2138] eta: 1:12:12 lr: 6.9972278111438295e-06 loss: 0.0182 (0.0203) time: 4.0287 data: 0.0035 max mem: 19788 +Epoch: [35] [1080/2138] eta: 1:11:32 lr: 6.990680527120479e-06 loss: 0.0180 (0.0203) time: 4.0397 data: 0.0034 max mem: 19788 +Epoch: [35] [1090/2138] eta: 1:10:51 lr: 6.984132561691581e-06 loss: 0.0190 (0.0203) time: 4.0440 data: 0.0032 max mem: 19788 +Epoch: [35] [1100/2138] eta: 1:10:10 lr: 6.9775839140762234e-06 loss: 0.0227 (0.0203) time: 4.0422 data: 0.0031 max mem: 19788 +Epoch: [35] [1110/2138] eta: 1:09:29 lr: 6.971034583491811e-06 loss: 0.0194 (0.0203) time: 4.0385 data: 0.0035 max mem: 19788 +Epoch: [35] [1120/2138] eta: 1:08:49 lr: 6.9644845691540035e-06 loss: 0.0185 (0.0203) time: 4.0357 data: 0.0037 max mem: 19788 +Epoch: [35] [1130/2138] eta: 1:08:08 lr: 6.957933870276767e-06 loss: 0.0205 (0.0203) time: 4.0459 data: 0.0034 max mem: 19788 +Epoch: [35] [1140/2138] eta: 1:07:27 lr: 6.951382486072322e-06 loss: 0.0197 (0.0203) time: 4.0468 data: 0.0033 max mem: 19788 +Epoch: [35] [1150/2138] eta: 1:06:47 lr: 6.9448304157511555e-06 loss: 0.0183 (0.0203) time: 4.0375 data: 0.0034 max mem: 19788 +Epoch: [35] [1160/2138] eta: 1:06:06 lr: 6.938277658522035e-06 loss: 0.0183 (0.0203) time: 4.0309 data: 0.0033 max mem: 19788 +Epoch: [35] [1170/2138] eta: 1:05:25 lr: 6.93172421359196e-06 loss: 0.0188 (0.0203) time: 4.0356 data: 0.0032 max mem: 19788 +Epoch: [35] [1180/2138] eta: 1:04:45 lr: 6.925170080166206e-06 loss: 0.0195 (0.0203) time: 4.0446 data: 0.0032 max mem: 19788 +Epoch: [35] [1190/2138] eta: 1:04:04 lr: 6.918615257448265e-06 loss: 0.0191 (0.0203) time: 4.0528 data: 0.0034 max mem: 19788 +Epoch: [35] [1200/2138] eta: 1:03:23 lr: 6.912059744639897e-06 loss: 0.0182 (0.0203) time: 4.0589 data: 0.0035 max mem: 19788 +Epoch: [35] [1210/2138] eta: 1:02:43 lr: 6.905503540941069e-06 loss: 0.0197 (0.0203) time: 4.0544 data: 0.0034 max mem: 19788 +Epoch: [35] [1220/2138] eta: 1:02:02 lr: 6.898946645549999e-06 loss: 0.0195 (0.0203) time: 4.0452 data: 0.0034 max mem: 19788 +Epoch: [35] [1230/2138] eta: 1:01:22 lr: 6.892389057663104e-06 loss: 0.0182 (0.0203) time: 4.0411 data: 0.0035 max mem: 19788 +Epoch: [35] [1240/2138] eta: 1:00:41 lr: 6.885830776475038e-06 loss: 0.0182 (0.0203) time: 4.0388 data: 0.0034 max mem: 19788 +Epoch: [35] [1250/2138] eta: 1:00:00 lr: 6.879271801178648e-06 loss: 0.0187 (0.0203) time: 4.0371 data: 0.0030 max mem: 19788 +Epoch: [35] [1260/2138] eta: 0:59:20 lr: 6.872712130965002e-06 loss: 0.0170 (0.0203) time: 4.0357 data: 0.0031 max mem: 19788 +Epoch: [35] [1270/2138] eta: 0:58:39 lr: 6.866151765023343e-06 loss: 0.0172 (0.0202) time: 4.0311 data: 0.0032 max mem: 19788 +Epoch: [35] [1280/2138] eta: 0:57:58 lr: 6.859590702541134e-06 loss: 0.0182 (0.0202) time: 4.0340 data: 0.0033 max mem: 19788 +Epoch: [35] [1290/2138] eta: 0:57:17 lr: 6.853028942703998e-06 loss: 0.0182 (0.0202) time: 4.0339 data: 0.0033 max mem: 19788 +Epoch: [35] [1300/2138] eta: 0:56:37 lr: 6.846466484695764e-06 loss: 0.0173 (0.0202) time: 4.0321 data: 0.0032 max mem: 19788 +Epoch: [35] [1310/2138] eta: 0:55:56 lr: 6.839903327698408e-06 loss: 0.0194 (0.0202) time: 4.0361 data: 0.0033 max mem: 19788 +Epoch: [35] [1320/2138] eta: 0:55:15 lr: 6.833339470892102e-06 loss: 0.0204 (0.0202) time: 4.0369 data: 0.0036 max mem: 19788 +Epoch: [35] [1330/2138] eta: 0:54:35 lr: 6.826774913455155e-06 loss: 0.0194 (0.0202) time: 4.0326 data: 0.0035 max mem: 19788 +Epoch: [35] [1340/2138] eta: 0:53:54 lr: 6.820209654564055e-06 loss: 0.0194 (0.0202) time: 4.0312 data: 0.0033 max mem: 19788 +Epoch: [35] [1350/2138] eta: 0:53:13 lr: 6.8136436933934174e-06 loss: 0.0223 (0.0203) time: 4.0346 data: 0.0032 max mem: 19788 +Epoch: [35] [1360/2138] eta: 0:52:33 lr: 6.807077029116027e-06 loss: 0.0219 (0.0203) time: 4.0372 data: 0.0032 max mem: 19788 +Epoch: [35] [1370/2138] eta: 0:51:52 lr: 6.800509660902777e-06 loss: 0.0205 (0.0203) time: 4.0376 data: 0.0034 max mem: 19788 +Epoch: [35] [1380/2138] eta: 0:51:12 lr: 6.793941587922723e-06 loss: 0.0189 (0.0203) time: 4.0380 data: 0.0033 max mem: 19788 +Epoch: [35] [1390/2138] eta: 0:50:31 lr: 6.7873728093430165e-06 loss: 0.0197 (0.0203) time: 4.0405 data: 0.0032 max mem: 19788 +Epoch: [35] [1400/2138] eta: 0:49:50 lr: 6.780803324328956e-06 loss: 0.0198 (0.0203) time: 4.0406 data: 0.0032 max mem: 19788 +Epoch: [35] [1410/2138] eta: 0:49:10 lr: 6.774233132043926e-06 loss: 0.0188 (0.0203) time: 4.0455 data: 0.0031 max mem: 19788 +Epoch: [35] [1420/2138] eta: 0:48:29 lr: 6.767662231649443e-06 loss: 0.0183 (0.0203) time: 4.0475 data: 0.0032 max mem: 19788 +Epoch: [35] [1430/2138] eta: 0:47:49 lr: 6.761090622305101e-06 loss: 0.0188 (0.0203) time: 4.0343 data: 0.0032 max mem: 19788 +Epoch: [35] [1440/2138] eta: 0:47:08 lr: 6.7545183031686064e-06 loss: 0.0187 (0.0203) time: 4.0309 data: 0.0031 max mem: 19788 +Epoch: [35] [1450/2138] eta: 0:46:28 lr: 6.7479452733957436e-06 loss: 0.0216 (0.0203) time: 4.0425 data: 0.0033 max mem: 19788 +Epoch: [35] [1460/2138] eta: 0:45:47 lr: 6.741371532140369e-06 loss: 0.0216 (0.0203) time: 4.0511 data: 0.0034 max mem: 19788 +Epoch: [35] [1470/2138] eta: 0:45:06 lr: 6.734797078554437e-06 loss: 0.0189 (0.0203) time: 4.0465 data: 0.0033 max mem: 19788 +Epoch: [35] [1480/2138] eta: 0:44:26 lr: 6.728221911787946e-06 loss: 0.0199 (0.0203) time: 4.0433 data: 0.0034 max mem: 19788 +Epoch: [35] [1490/2138] eta: 0:43:45 lr: 6.721646030988979e-06 loss: 0.0204 (0.0203) time: 4.0477 data: 0.0031 max mem: 19788 +Epoch: [35] [1500/2138] eta: 0:43:05 lr: 6.715069435303649e-06 loss: 0.0188 (0.0203) time: 4.0416 data: 0.0031 max mem: 19788 +Epoch: [35] [1510/2138] eta: 0:42:24 lr: 6.7084921238761435e-06 loss: 0.0191 (0.0203) time: 4.0435 data: 0.0034 max mem: 19788 +Epoch: [35] [1520/2138] eta: 0:41:44 lr: 6.7019140958486645e-06 loss: 0.0195 (0.0203) time: 4.0381 data: 0.0034 max mem: 19788 +Epoch: [35] [1530/2138] eta: 0:41:03 lr: 6.695335350361479e-06 loss: 0.0187 (0.0203) time: 4.0270 data: 0.0032 max mem: 19788 +Epoch: [35] [1540/2138] eta: 0:40:22 lr: 6.688755886552851e-06 loss: 0.0175 (0.0203) time: 4.0415 data: 0.0031 max mem: 19788 +Epoch: [35] [1550/2138] eta: 0:39:42 lr: 6.682175703559099e-06 loss: 0.0177 (0.0203) time: 4.0496 data: 0.0032 max mem: 19788 +Epoch: [35] [1560/2138] eta: 0:39:01 lr: 6.675594800514526e-06 loss: 0.0185 (0.0203) time: 4.0426 data: 0.0033 max mem: 19788 +Epoch: [35] [1570/2138] eta: 0:38:21 lr: 6.669013176551471e-06 loss: 0.0185 (0.0203) time: 4.0443 data: 0.0031 max mem: 19788 +Epoch: [35] [1580/2138] eta: 0:37:40 lr: 6.66243083080025e-06 loss: 0.0179 (0.0203) time: 4.0455 data: 0.0031 max mem: 19788 +Epoch: [35] [1590/2138] eta: 0:37:00 lr: 6.655847762389197e-06 loss: 0.0190 (0.0203) time: 4.0360 data: 0.0031 max mem: 19788 +Epoch: [35] [1600/2138] eta: 0:36:19 lr: 6.6492639704446105e-06 loss: 0.0212 (0.0203) time: 4.0376 data: 0.0031 max mem: 19788 +Epoch: [35] [1610/2138] eta: 0:35:39 lr: 6.6426794540907945e-06 loss: 0.0206 (0.0203) time: 4.0390 data: 0.0032 max mem: 19788 +Epoch: [35] [1620/2138] eta: 0:34:58 lr: 6.6360942124500045e-06 loss: 0.0180 (0.0203) time: 4.0329 data: 0.0032 max mem: 19788 +Epoch: [35] [1630/2138] eta: 0:34:18 lr: 6.629508244642486e-06 loss: 0.0207 (0.0203) time: 4.0411 data: 0.0034 max mem: 19788 +Epoch: [35] [1640/2138] eta: 0:33:37 lr: 6.622921549786421e-06 loss: 0.0197 (0.0203) time: 4.0498 data: 0.0035 max mem: 19788 +Epoch: [35] [1650/2138] eta: 0:32:56 lr: 6.616334126997968e-06 loss: 0.0173 (0.0203) time: 4.0417 data: 0.0033 max mem: 19788 +Epoch: [35] [1660/2138] eta: 0:32:16 lr: 6.6097459753912115e-06 loss: 0.0173 (0.0203) time: 4.0408 data: 0.0033 max mem: 19788 +Epoch: [35] [1670/2138] eta: 0:31:35 lr: 6.603157094078196e-06 loss: 0.0168 (0.0203) time: 4.0479 data: 0.0032 max mem: 19788 +Epoch: [35] [1680/2138] eta: 0:30:55 lr: 6.596567482168874e-06 loss: 0.0199 (0.0203) time: 4.0466 data: 0.0032 max mem: 19788 +Epoch: [35] [1690/2138] eta: 0:30:14 lr: 6.58997713877115e-06 loss: 0.0193 (0.0203) time: 4.0359 data: 0.0034 max mem: 19788 +Epoch: [35] [1700/2138] eta: 0:29:34 lr: 6.583386062990822e-06 loss: 0.0177 (0.0203) time: 4.0351 data: 0.0034 max mem: 19788 +Epoch: [35] [1710/2138] eta: 0:28:53 lr: 6.5767942539316216e-06 loss: 0.0185 (0.0203) time: 4.0378 data: 0.0032 max mem: 19788 +Epoch: [35] [1720/2138] eta: 0:28:13 lr: 6.570201710695159e-06 loss: 0.0207 (0.0203) time: 4.0303 data: 0.0030 max mem: 19788 +Epoch: [35] [1730/2138] eta: 0:27:32 lr: 6.5636084323809686e-06 loss: 0.0207 (0.0203) time: 4.0324 data: 0.0032 max mem: 19788 +Epoch: [35] [1740/2138] eta: 0:26:52 lr: 6.557014418086453e-06 loss: 0.0194 (0.0203) time: 4.0343 data: 0.0032 max mem: 19788 +Epoch: [35] [1750/2138] eta: 0:26:11 lr: 6.550419666906897e-06 loss: 0.0197 (0.0203) time: 4.0348 data: 0.0033 max mem: 19788 +Epoch: [35] [1760/2138] eta: 0:25:30 lr: 6.543824177935478e-06 loss: 0.0200 (0.0203) time: 4.0321 data: 0.0035 max mem: 19788 +Epoch: [35] [1770/2138] eta: 0:24:50 lr: 6.537227950263218e-06 loss: 0.0195 (0.0203) time: 4.0327 data: 0.0037 max mem: 19788 +Epoch: [35] [1780/2138] eta: 0:24:09 lr: 6.530630982979021e-06 loss: 0.0193 (0.0203) time: 4.0408 data: 0.0036 max mem: 19788 +Epoch: [35] [1790/2138] eta: 0:23:29 lr: 6.524033275169618e-06 loss: 0.0191 (0.0203) time: 4.0406 data: 0.0033 max mem: 19788 +Epoch: [35] [1800/2138] eta: 0:22:48 lr: 6.517434825919612e-06 loss: 0.0189 (0.0203) time: 4.0446 data: 0.0033 max mem: 19788 +Epoch: [35] [1810/2138] eta: 0:22:08 lr: 6.510835634311418e-06 loss: 0.0194 (0.0203) time: 4.0499 data: 0.0033 max mem: 19788 +Epoch: [35] [1820/2138] eta: 0:21:27 lr: 6.504235699425304e-06 loss: 0.0202 (0.0203) time: 4.0485 data: 0.0033 max mem: 19788 +Epoch: [35] [1830/2138] eta: 0:20:47 lr: 6.4976350203393365e-06 loss: 0.0200 (0.0203) time: 4.0403 data: 0.0033 max mem: 19788 +Epoch: [35] [1840/2138] eta: 0:20:06 lr: 6.491033596129421e-06 loss: 0.0196 (0.0203) time: 4.0362 data: 0.0033 max mem: 19788 +Epoch: [35] [1850/2138] eta: 0:19:26 lr: 6.484431425869245e-06 loss: 0.0208 (0.0203) time: 4.0325 data: 0.0034 max mem: 19788 +Epoch: [35] [1860/2138] eta: 0:18:45 lr: 6.477828508630318e-06 loss: 0.0208 (0.0203) time: 4.0326 data: 0.0037 max mem: 19788 +Epoch: [35] [1870/2138] eta: 0:18:05 lr: 6.47122484348192e-06 loss: 0.0190 (0.0203) time: 4.0375 data: 0.0038 max mem: 19788 +Epoch: [35] [1880/2138] eta: 0:17:24 lr: 6.464620429491138e-06 loss: 0.0193 (0.0203) time: 4.0307 data: 0.0033 max mem: 19788 +Epoch: [35] [1890/2138] eta: 0:16:44 lr: 6.458015265722807e-06 loss: 0.0180 (0.0203) time: 4.0304 data: 0.0032 max mem: 19788 +Epoch: [35] [1900/2138] eta: 0:16:03 lr: 6.45140935123956e-06 loss: 0.0169 (0.0203) time: 4.0307 data: 0.0033 max mem: 19788 +Epoch: [35] [1910/2138] eta: 0:15:23 lr: 6.44480268510176e-06 loss: 0.0197 (0.0203) time: 4.0305 data: 0.0033 max mem: 19788 +Epoch: [35] [1920/2138] eta: 0:14:42 lr: 6.438195266367551e-06 loss: 0.0190 (0.0203) time: 4.0305 data: 0.0034 max mem: 19788 +Epoch: [35] [1930/2138] eta: 0:14:02 lr: 6.431587094092796e-06 loss: 0.0190 (0.0203) time: 4.0298 data: 0.0033 max mem: 19788 +Epoch: [35] [1940/2138] eta: 0:13:21 lr: 6.424978167331118e-06 loss: 0.0203 (0.0203) time: 4.0326 data: 0.0031 max mem: 19788 +Epoch: [35] [1950/2138] eta: 0:12:41 lr: 6.418368485133842e-06 loss: 0.0202 (0.0203) time: 4.0304 data: 0.0030 max mem: 19788 +Epoch: [35] [1960/2138] eta: 0:12:00 lr: 6.411758046550041e-06 loss: 0.0181 (0.0203) time: 4.0299 data: 0.0032 max mem: 19788 +Epoch: [35] [1970/2138] eta: 0:11:20 lr: 6.405146850626474e-06 loss: 0.0186 (0.0203) time: 4.0339 data: 0.0034 max mem: 19788 +Epoch: [35] [1980/2138] eta: 0:10:39 lr: 6.398534896407629e-06 loss: 0.0158 (0.0203) time: 4.0297 data: 0.0033 max mem: 19788 +Epoch: [35] [1990/2138] eta: 0:09:59 lr: 6.391922182935664e-06 loss: 0.0175 (0.0203) time: 4.0300 data: 0.0033 max mem: 19788 +Epoch: [35] [2000/2138] eta: 0:09:18 lr: 6.385308709250451e-06 loss: 0.0191 (0.0203) time: 4.0339 data: 0.0033 max mem: 19788 +Epoch: [35] [2010/2138] eta: 0:08:38 lr: 6.378694474389515e-06 loss: 0.0197 (0.0203) time: 4.0368 data: 0.0035 max mem: 19788 +Epoch: [35] [2020/2138] eta: 0:07:57 lr: 6.372079477388078e-06 loss: 0.0197 (0.0203) time: 4.0450 data: 0.0035 max mem: 19788 +Epoch: [35] [2030/2138] eta: 0:07:17 lr: 6.365463717279001e-06 loss: 0.0197 (0.0203) time: 4.0511 data: 0.0036 max mem: 19788 +Epoch: [35] [2040/2138] eta: 0:06:36 lr: 6.358847193092821e-06 loss: 0.0197 (0.0203) time: 4.0537 data: 0.0034 max mem: 19788 +Epoch: [35] [2050/2138] eta: 0:05:56 lr: 6.3522299038577035e-06 loss: 0.0194 (0.0203) time: 4.0516 data: 0.0032 max mem: 19788 +Epoch: [35] [2060/2138] eta: 0:05:15 lr: 6.345611848599453e-06 loss: 0.0177 (0.0203) time: 4.0445 data: 0.0030 max mem: 19788 +Epoch: [35] [2070/2138] eta: 0:04:35 lr: 6.338993026341522e-06 loss: 0.0173 (0.0203) time: 4.0449 data: 0.0030 max mem: 19788 +Epoch: [35] [2080/2138] eta: 0:03:54 lr: 6.332373436104956e-06 loss: 0.0191 (0.0203) time: 4.0432 data: 0.0032 max mem: 19788 +Epoch: [35] [2090/2138] eta: 0:03:14 lr: 6.32575307690844e-06 loss: 0.0191 (0.0203) time: 4.0348 data: 0.0032 max mem: 19788 +Epoch: [35] [2100/2138] eta: 0:02:33 lr: 6.319131947768234e-06 loss: 0.0185 (0.0202) time: 4.0487 data: 0.0030 max mem: 19788 +Epoch: [35] [2110/2138] eta: 0:01:53 lr: 6.312510047698221e-06 loss: 0.0209 (0.0203) time: 4.0602 data: 0.0030 max mem: 19788 +Epoch: [35] [2120/2138] eta: 0:01:12 lr: 6.305887375709843e-06 loss: 0.0233 (0.0203) time: 4.0575 data: 0.0032 max mem: 19788 +Epoch: [35] [2130/2138] eta: 0:00:32 lr: 6.299263930812145e-06 loss: 0.0208 (0.0203) time: 4.0383 data: 0.0031 max mem: 19788 +Epoch: [35] Total time: 2:24:16 +Test: [ 0/21770] eta: 20:09:17 time: 3.3329 data: 3.1381 max mem: 19788 +Test: [ 100/21770] eta: 0:37:24 time: 0.0737 data: 0.0024 max mem: 19788 +Test: [ 200/21770] eta: 0:33:10 time: 0.0819 data: 0.0022 max mem: 19788 +Test: [ 300/21770] eta: 0:30:34 time: 0.0716 data: 0.0020 max mem: 19788 +Test: [ 400/21770] eta: 0:28:42 time: 0.0634 data: 0.0019 max mem: 19788 +Test: [ 500/21770] eta: 0:27:37 time: 0.0684 data: 0.0023 max mem: 19788 +Test: [ 600/21770] eta: 0:26:41 time: 0.0666 data: 0.0022 max mem: 19788 +Test: [ 700/21770] eta: 0:26:18 time: 0.0625 data: 0.0019 max mem: 19788 +Test: [ 800/21770] eta: 0:25:41 time: 0.0661 data: 0.0020 max mem: 19788 +Test: [ 900/21770] eta: 0:25:18 time: 0.0725 data: 0.0025 max mem: 19788 +Test: [ 1000/21770] eta: 0:25:13 time: 0.0730 data: 0.0022 max mem: 19788 +Test: [ 1100/21770] eta: 0:24:50 time: 0.0621 data: 0.0020 max mem: 19788 +Test: [ 1200/21770] eta: 0:24:35 time: 0.0634 data: 0.0023 max mem: 19788 +Test: [ 1300/21770] eta: 0:24:21 time: 0.0682 data: 0.0020 max mem: 19788 +Test: [ 1400/21770] eta: 0:24:10 time: 0.0672 data: 0.0020 max mem: 19788 +Test: [ 1500/21770] eta: 0:23:58 time: 0.0673 data: 0.0022 max mem: 19788 +Test: [ 1600/21770] eta: 0:23:46 time: 0.0618 data: 0.0019 max mem: 19788 +Test: [ 1700/21770] eta: 0:23:43 time: 0.0797 data: 0.0025 max mem: 19788 +Test: [ 1800/21770] eta: 0:23:37 time: 0.0660 data: 0.0019 max mem: 19788 +Test: [ 1900/21770] eta: 0:23:28 time: 0.0741 data: 0.0020 max mem: 19788 +Test: [ 2000/21770] eta: 0:23:24 time: 0.0761 data: 0.0023 max mem: 19788 +Test: [ 2100/21770] eta: 0:23:13 time: 0.0726 data: 0.0021 max mem: 19788 +Test: [ 2200/21770] eta: 0:23:04 time: 0.0631 data: 0.0021 max mem: 19788 +Test: [ 2300/21770] eta: 0:22:53 time: 0.0635 data: 0.0019 max mem: 19788 +Test: [ 2400/21770] eta: 0:22:46 time: 0.0680 data: 0.0020 max mem: 19788 +Test: [ 2500/21770] eta: 0:22:41 time: 0.0636 data: 0.0016 max mem: 19788 +Test: [ 2600/21770] eta: 0:22:35 time: 0.0863 data: 0.0025 max mem: 19788 +Test: [ 2700/21770] eta: 0:22:30 time: 0.0848 data: 0.0026 max mem: 19788 +Test: [ 2800/21770] eta: 0:22:23 time: 0.0681 data: 0.0021 max mem: 19788 +Test: [ 2900/21770] eta: 0:22:15 time: 0.0670 data: 0.0021 max mem: 19788 +Test: [ 3000/21770] eta: 0:22:07 time: 0.0652 data: 0.0019 max mem: 19788 +Test: [ 3100/21770] eta: 0:22:02 time: 0.0763 data: 0.0021 max mem: 19788 +Test: [ 3200/21770] eta: 0:21:57 time: 0.0674 data: 0.0019 max mem: 19788 +Test: [ 3300/21770] eta: 0:21:51 time: 0.0730 data: 0.0020 max mem: 19788 +Test: [ 3400/21770] eta: 0:21:42 time: 0.0693 data: 0.0021 max mem: 19788 +Test: [ 3500/21770] eta: 0:21:36 time: 0.0805 data: 0.0023 max mem: 19788 +Test: [ 3600/21770] eta: 0:21:30 time: 0.0640 data: 0.0021 max mem: 19788 +Test: [ 3700/21770] eta: 0:21:21 time: 0.0705 data: 0.0022 max mem: 19788 +Test: [ 3800/21770] eta: 0:21:13 time: 0.0647 data: 0.0018 max mem: 19788 +Test: [ 3900/21770] eta: 0:21:08 time: 0.0799 data: 0.0023 max mem: 19788 +Test: [ 4000/21770] eta: 0:21:00 time: 0.0635 data: 0.0019 max mem: 19788 +Test: [ 4100/21770] eta: 0:20:52 time: 0.0640 data: 0.0019 max mem: 19788 +Test: [ 4200/21770] eta: 0:20:43 time: 0.0715 data: 0.0021 max mem: 19788 +Test: [ 4300/21770] eta: 0:20:35 time: 0.0653 data: 0.0023 max mem: 19788 +Test: [ 4400/21770] eta: 0:20:28 time: 0.0699 data: 0.0019 max mem: 19788 +Test: [ 4500/21770] eta: 0:20:21 time: 0.0713 data: 0.0022 max mem: 19788 +Test: [ 4600/21770] eta: 0:20:15 time: 0.0734 data: 0.0023 max mem: 19788 +Test: [ 4700/21770] eta: 0:20:09 time: 0.0666 data: 0.0019 max mem: 19788 +Test: [ 4800/21770] eta: 0:20:00 time: 0.0646 data: 0.0017 max mem: 19788 +Test: [ 4900/21770] eta: 0:19:55 time: 0.0705 data: 0.0024 max mem: 19788 +Test: [ 5000/21770] eta: 0:19:47 time: 0.0637 data: 0.0020 max mem: 19788 +Test: [ 5100/21770] eta: 0:19:41 time: 0.0719 data: 0.0022 max mem: 19788 +Test: [ 5200/21770] eta: 0:19:34 time: 0.0683 data: 0.0019 max mem: 19788 +Test: [ 5300/21770] eta: 0:19:28 time: 0.0680 data: 0.0021 max mem: 19788 +Test: [ 5400/21770] eta: 0:19:20 time: 0.0632 data: 0.0020 max mem: 19788 +Test: [ 5500/21770] eta: 0:19:12 time: 0.0795 data: 0.0024 max mem: 19788 +Test: [ 5600/21770] eta: 0:19:04 time: 0.0731 data: 0.0019 max mem: 19788 +Test: [ 5700/21770] eta: 0:18:57 time: 0.0848 data: 0.0027 max mem: 19788 +Test: [ 5800/21770] eta: 0:18:50 time: 0.0649 data: 0.0023 max mem: 19788 +Test: [ 5900/21770] eta: 0:18:42 time: 0.0655 data: 0.0019 max mem: 19788 +Test: [ 6000/21770] eta: 0:18:36 time: 0.0744 data: 0.0023 max mem: 19788 +Test: [ 6100/21770] eta: 0:18:28 time: 0.0659 data: 0.0019 max mem: 19788 +Test: [ 6200/21770] eta: 0:18:20 time: 0.0638 data: 0.0020 max mem: 19788 +Test: [ 6300/21770] eta: 0:18:13 time: 0.0752 data: 0.0020 max mem: 19788 +Test: [ 6400/21770] eta: 0:18:07 time: 0.0816 data: 0.0021 max mem: 19788 +Test: [ 6500/21770] eta: 0:18:01 time: 0.0722 data: 0.0020 max mem: 19788 +Test: [ 6600/21770] eta: 0:17:54 time: 0.0830 data: 0.0024 max mem: 19788 +Test: [ 6700/21770] eta: 0:17:46 time: 0.0657 data: 0.0019 max mem: 19788 +Test: [ 6800/21770] eta: 0:17:38 time: 0.0651 data: 0.0020 max mem: 19788 +Test: [ 6900/21770] eta: 0:17:30 time: 0.0709 data: 0.0021 max mem: 19788 +Test: [ 7000/21770] eta: 0:17:22 time: 0.0661 data: 0.0019 max mem: 19788 +Test: [ 7100/21770] eta: 0:17:14 time: 0.0637 data: 0.0018 max mem: 19788 +Test: [ 7200/21770] eta: 0:17:08 time: 0.0715 data: 0.0022 max mem: 19788 +Test: [ 7300/21770] eta: 0:17:00 time: 0.0646 data: 0.0021 max mem: 19788 +Test: [ 7400/21770] eta: 0:16:53 time: 0.0733 data: 0.0022 max mem: 19788 +Test: [ 7500/21770] eta: 0:16:47 time: 0.0832 data: 0.0027 max mem: 19788 +Test: [ 7600/21770] eta: 0:16:40 time: 0.0659 data: 0.0020 max mem: 19788 +Test: [ 7700/21770] eta: 0:16:33 time: 0.0816 data: 0.0023 max mem: 19788 +Test: [ 7800/21770] eta: 0:16:27 time: 0.0845 data: 0.0024 max mem: 19788 +Test: [ 7900/21770] eta: 0:16:19 time: 0.0733 data: 0.0020 max mem: 19788 +Test: [ 8000/21770] eta: 0:16:12 time: 0.0770 data: 0.0024 max mem: 19788 +Test: [ 8100/21770] eta: 0:16:04 time: 0.0652 data: 0.0019 max mem: 19788 +Test: [ 8200/21770] eta: 0:15:58 time: 0.0672 data: 0.0022 max mem: 19788 +Test: [ 8300/21770] eta: 0:15:52 time: 0.0819 data: 0.0024 max mem: 19788 +Test: [ 8400/21770] eta: 0:15:45 time: 0.0656 data: 0.0020 max mem: 19788 +Test: [ 8500/21770] eta: 0:15:37 time: 0.0632 data: 0.0018 max mem: 19788 +Test: [ 8600/21770] eta: 0:15:29 time: 0.0652 data: 0.0019 max mem: 19788 +Test: [ 8700/21770] eta: 0:15:22 time: 0.0649 data: 0.0021 max mem: 19788 +Test: [ 8800/21770] eta: 0:15:15 time: 0.0716 data: 0.0023 max mem: 19788 +Test: [ 8900/21770] eta: 0:15:07 time: 0.0668 data: 0.0021 max mem: 19788 +Test: [ 9000/21770] eta: 0:15:00 time: 0.0677 data: 0.0021 max mem: 19788 +Test: [ 9100/21770] eta: 0:14:52 time: 0.0707 data: 0.0022 max mem: 19788 +Test: [ 9200/21770] eta: 0:14:45 time: 0.0624 data: 0.0018 max mem: 19788 +Test: [ 9300/21770] eta: 0:14:38 time: 0.0790 data: 0.0023 max mem: 19788 +Test: [ 9400/21770] eta: 0:14:31 time: 0.0655 data: 0.0019 max mem: 19788 +Test: [ 9500/21770] eta: 0:14:24 time: 0.0830 data: 0.0021 max mem: 19788 +Test: [ 9600/21770] eta: 0:14:17 time: 0.0657 data: 0.0019 max mem: 19788 +Test: [ 9700/21770] eta: 0:14:11 time: 0.0752 data: 0.0023 max mem: 19788 +Test: [ 9800/21770] eta: 0:14:04 time: 0.0819 data: 0.0020 max mem: 19788 +Test: [ 9900/21770] eta: 0:13:57 time: 0.0760 data: 0.0023 max mem: 19788 +Test: [10000/21770] eta: 0:13:51 time: 0.0832 data: 0.0026 max mem: 19788 +Test: [10100/21770] eta: 0:13:43 time: 0.0740 data: 0.0021 max mem: 19788 +Test: [10200/21770] eta: 0:13:36 time: 0.0668 data: 0.0020 max mem: 19788 +Test: [10300/21770] eta: 0:13:29 time: 0.0696 data: 0.0023 max mem: 19788 +Test: [10400/21770] eta: 0:13:23 time: 0.0769 data: 0.0024 max mem: 19788 +Test: [10500/21770] eta: 0:13:16 time: 0.0827 data: 0.0026 max mem: 19788 +Test: [10600/21770] eta: 0:13:09 time: 0.0725 data: 0.0022 max mem: 19788 +Test: [10700/21770] eta: 0:13:02 time: 0.0677 data: 0.0021 max mem: 19788 +Test: [10800/21770] eta: 0:12:55 time: 0.0797 data: 0.0023 max mem: 19788 +Test: [10900/21770] eta: 0:12:48 time: 0.0668 data: 0.0021 max mem: 19788 +Test: [11000/21770] eta: 0:12:42 time: 0.0775 data: 0.0025 max mem: 19788 +Test: [11100/21770] eta: 0:12:34 time: 0.0646 data: 0.0019 max mem: 19788 +Test: [11200/21770] eta: 0:12:27 time: 0.0673 data: 0.0020 max mem: 19788 +Test: [11300/21770] eta: 0:12:20 time: 0.0812 data: 0.0025 max mem: 19788 +Test: [11400/21770] eta: 0:12:13 time: 0.0692 data: 0.0021 max mem: 19788 +Test: [11500/21770] eta: 0:12:06 time: 0.0659 data: 0.0018 max mem: 19788 +Test: [11600/21770] eta: 0:12:00 time: 0.0805 data: 0.0022 max mem: 19788 +Test: [11700/21770] eta: 0:11:53 time: 0.0835 data: 0.0025 max mem: 19788 +Test: [11800/21770] eta: 0:11:46 time: 0.0844 data: 0.0021 max mem: 19788 +Test: [11900/21770] eta: 0:11:39 time: 0.0627 data: 0.0019 max mem: 19788 +Test: [12000/21770] eta: 0:11:32 time: 0.0701 data: 0.0020 max mem: 19788 +Test: [12100/21770] eta: 0:11:25 time: 0.0691 data: 0.0022 max mem: 19788 +Test: [12200/21770] eta: 0:11:18 time: 0.0665 data: 0.0021 max mem: 19788 +Test: [12300/21770] eta: 0:11:11 time: 0.0656 data: 0.0020 max mem: 19788 +Test: [12400/21770] eta: 0:11:04 time: 0.0649 data: 0.0020 max mem: 19788 +Test: [12500/21770] eta: 0:10:57 time: 0.0701 data: 0.0022 max mem: 19788 +Test: [12600/21770] eta: 0:10:50 time: 0.0769 data: 0.0020 max mem: 19788 +Test: [12700/21770] eta: 0:10:43 time: 0.0691 data: 0.0022 max mem: 19788 +Test: [12800/21770] eta: 0:10:36 time: 0.0853 data: 0.0027 max mem: 19788 +Test: [12900/21770] eta: 0:10:29 time: 0.0691 data: 0.0021 max mem: 19788 +Test: [13000/21770] eta: 0:10:22 time: 0.0726 data: 0.0022 max mem: 19788 +Test: [13100/21770] eta: 0:10:15 time: 0.0801 data: 0.0021 max mem: 19788 +Test: [13200/21770] eta: 0:10:08 time: 0.0646 data: 0.0019 max mem: 19788 +Test: [13300/21770] eta: 0:10:00 time: 0.0660 data: 0.0020 max mem: 19788 +Test: [13400/21770] eta: 0:09:53 time: 0.0638 data: 0.0020 max mem: 19788 +Test: [13500/21770] eta: 0:09:46 time: 0.0676 data: 0.0021 max mem: 19788 +Test: [13600/21770] eta: 0:09:39 time: 0.0747 data: 0.0021 max mem: 19788 +Test: [13700/21770] eta: 0:09:32 time: 0.0861 data: 0.0024 max mem: 19788 +Test: [13800/21770] eta: 0:09:25 time: 0.0729 data: 0.0020 max mem: 19788 +Test: [13900/21770] eta: 0:09:18 time: 0.0692 data: 0.0020 max mem: 19788 +Test: [14000/21770] eta: 0:09:11 time: 0.0853 data: 0.0026 max mem: 19788 +Test: [14100/21770] eta: 0:09:04 time: 0.0648 data: 0.0019 max mem: 19788 +Test: [14200/21770] eta: 0:08:57 time: 0.0718 data: 0.0023 max mem: 19788 +Test: [14300/21770] eta: 0:08:50 time: 0.0862 data: 0.0021 max mem: 19788 +Test: [14400/21770] eta: 0:08:43 time: 0.0801 data: 0.0024 max mem: 19788 +Test: [14500/21770] eta: 0:08:36 time: 0.0663 data: 0.0020 max mem: 19788 +Test: [14600/21770] eta: 0:08:28 time: 0.0664 data: 0.0019 max mem: 19788 +Test: [14700/21770] eta: 0:08:21 time: 0.0664 data: 0.0020 max mem: 19788 +Test: [14800/21770] eta: 0:08:14 time: 0.0736 data: 0.0022 max mem: 19788 +Test: [14900/21770] eta: 0:08:07 time: 0.0652 data: 0.0019 max mem: 19788 +Test: [15000/21770] eta: 0:08:00 time: 0.0622 data: 0.0020 max mem: 19788 +Test: [15100/21770] eta: 0:07:52 time: 0.0631 data: 0.0018 max mem: 19788 +Test: [15200/21770] eta: 0:07:45 time: 0.0676 data: 0.0021 max mem: 19788 +Test: [15300/21770] eta: 0:07:38 time: 0.0707 data: 0.0021 max mem: 19788 +Test: [15400/21770] eta: 0:07:31 time: 0.0668 data: 0.0021 max mem: 19788 +Test: [15500/21770] eta: 0:07:24 time: 0.0640 data: 0.0020 max mem: 19788 +Test: [15600/21770] eta: 0:07:17 time: 0.0658 data: 0.0021 max mem: 19788 +Test: [15700/21770] eta: 0:07:10 time: 0.0739 data: 0.0019 max mem: 19788 +Test: [15800/21770] eta: 0:07:03 time: 0.0691 data: 0.0020 max mem: 19788 +Test: [15900/21770] eta: 0:06:56 time: 0.0739 data: 0.0024 max mem: 19788 +Test: [16000/21770] eta: 0:06:49 time: 0.0779 data: 0.0025 max mem: 19788 +Test: [16100/21770] eta: 0:06:42 time: 0.0666 data: 0.0021 max mem: 19788 +Test: [16200/21770] eta: 0:06:34 time: 0.0650 data: 0.0019 max mem: 19788 +Test: [16300/21770] eta: 0:06:27 time: 0.0654 data: 0.0020 max mem: 19788 +Test: [16400/21770] eta: 0:06:20 time: 0.0826 data: 0.0027 max mem: 19788 +Test: [16500/21770] eta: 0:06:13 time: 0.0648 data: 0.0019 max mem: 19788 +Test: [16600/21770] eta: 0:06:06 time: 0.0708 data: 0.0024 max mem: 19788 +Test: [16700/21770] eta: 0:05:59 time: 0.0840 data: 0.0026 max mem: 19788 +Test: [16800/21770] eta: 0:05:52 time: 0.0781 data: 0.0025 max mem: 19788 +Test: [16900/21770] eta: 0:05:45 time: 0.0654 data: 0.0022 max mem: 19788 +Test: [17000/21770] eta: 0:05:38 time: 0.0674 data: 0.0020 max mem: 19788 +Test: [17100/21770] eta: 0:05:31 time: 0.0777 data: 0.0020 max mem: 19788 +Test: [17200/21770] eta: 0:05:24 time: 0.0657 data: 0.0019 max mem: 19788 +Test: [17300/21770] eta: 0:05:17 time: 0.0693 data: 0.0022 max mem: 19788 +Test: [17400/21770] eta: 0:05:10 time: 0.0638 data: 0.0019 max mem: 19788 +Test: [17500/21770] eta: 0:05:03 time: 0.0736 data: 0.0023 max mem: 19788 +Test: [17600/21770] eta: 0:04:56 time: 0.0657 data: 0.0020 max mem: 19788 +Test: [17700/21770] eta: 0:04:49 time: 0.0660 data: 0.0019 max mem: 19788 +Test: [17800/21770] eta: 0:04:41 time: 0.0656 data: 0.0019 max mem: 19788 +Test: [17900/21770] eta: 0:04:34 time: 0.0714 data: 0.0021 max mem: 19788 +Test: [18000/21770] eta: 0:04:27 time: 0.0624 data: 0.0019 max mem: 19788 +Test: [18100/21770] eta: 0:04:20 time: 0.0704 data: 0.0022 max mem: 19788 +Test: [18200/21770] eta: 0:04:13 time: 0.0633 data: 0.0020 max mem: 19788 +Test: [18300/21770] eta: 0:04:06 time: 0.0645 data: 0.0020 max mem: 19788 +Test: [18400/21770] eta: 0:03:58 time: 0.0622 data: 0.0021 max mem: 19788 +Test: [18500/21770] eta: 0:03:51 time: 0.0766 data: 0.0020 max mem: 19788 +Test: [18600/21770] eta: 0:03:44 time: 0.0699 data: 0.0023 max mem: 19788 +Test: [18700/21770] eta: 0:03:37 time: 0.0705 data: 0.0021 max mem: 19788 +Test: [18800/21770] eta: 0:03:30 time: 0.0657 data: 0.0020 max mem: 19788 +Test: [18900/21770] eta: 0:03:23 time: 0.0803 data: 0.0025 max mem: 19788 +Test: [19000/21770] eta: 0:03:16 time: 0.0760 data: 0.0020 max mem: 19788 +Test: [19100/21770] eta: 0:03:09 time: 0.0744 data: 0.0020 max mem: 19788 +Test: [19200/21770] eta: 0:03:02 time: 0.0667 data: 0.0020 max mem: 19788 +Test: [19300/21770] eta: 0:02:55 time: 0.0794 data: 0.0023 max mem: 19788 +Test: [19400/21770] eta: 0:02:48 time: 0.0837 data: 0.0026 max mem: 19788 +Test: [19500/21770] eta: 0:02:40 time: 0.0647 data: 0.0019 max mem: 19788 +Test: [19600/21770] eta: 0:02:33 time: 0.0829 data: 0.0022 max mem: 19788 +Test: [19700/21770] eta: 0:02:26 time: 0.0705 data: 0.0022 max mem: 19788 +Test: [19800/21770] eta: 0:02:19 time: 0.0795 data: 0.0026 max mem: 19788 +Test: [19900/21770] eta: 0:02:12 time: 0.0735 data: 0.0022 max mem: 19788 +Test: [20000/21770] eta: 0:02:05 time: 0.0839 data: 0.0025 max mem: 19788 +Test: [20100/21770] eta: 0:01:58 time: 0.0642 data: 0.0020 max mem: 19788 +Test: [20200/21770] eta: 0:01:51 time: 0.0672 data: 0.0020 max mem: 19788 +Test: [20300/21770] eta: 0:01:44 time: 0.0640 data: 0.0022 max mem: 19788 +Test: [20400/21770] eta: 0:01:37 time: 0.0856 data: 0.0026 max mem: 19788 +Test: [20500/21770] eta: 0:01:30 time: 0.0703 data: 0.0020 max mem: 19788 +Test: [20600/21770] eta: 0:01:23 time: 0.0643 data: 0.0018 max mem: 19788 +Test: [20700/21770] eta: 0:01:15 time: 0.0735 data: 0.0023 max mem: 19788 +Test: [20800/21770] eta: 0:01:08 time: 0.0649 data: 0.0019 max mem: 19788 +Test: [20900/21770] eta: 0:01:01 time: 0.0685 data: 0.0023 max mem: 19788 +Test: [21000/21770] eta: 0:00:54 time: 0.0647 data: 0.0019 max mem: 19788 +Test: [21100/21770] eta: 0:00:47 time: 0.0671 data: 0.0020 max mem: 19788 +Test: [21200/21770] eta: 0:00:40 time: 0.0738 data: 0.0021 max mem: 19788 +Test: [21300/21770] eta: 0:00:33 time: 0.0857 data: 0.0024 max mem: 19788 +Test: [21400/21770] eta: 0:00:26 time: 0.0650 data: 0.0019 max mem: 19788 +Test: [21500/21770] eta: 0:00:19 time: 0.0657 data: 0.0018 max mem: 19788 +Test: [21600/21770] eta: 0:00:12 time: 0.0700 data: 0.0020 max mem: 19788 +Test: [21700/21770] eta: 0:00:04 time: 0.0689 data: 0.0019 max mem: 19788 +Test: Total time: 0:25:44 +Final results: +Mean IoU is 62.93 + + precision@0.5 = 69.86 + precision@0.6 = 64.72 + precision@0.7 = 58.32 + precision@0.8 = 47.95 + precision@0.9 = 23.94 + overall IoU = 64.14 + mean IoU = 62.93 + +Mean accuracy for one-to-zero sample is 86.55 + +Average object IoU 0.6293319120424263 +Overall IoU 64.14086151123047 +Better epoch: 35 + +Epoch: [36] [ 0/2138] eta: 14:31:01 lr: 6.293964617731786e-06 loss: 0.0596 (0.0596) time: 24.4441 data: 1.8761 max mem: 19788 +Epoch: [36] [ 10/2138] eta: 3:30:08 lr: 6.28733977909229e-06 loss: 0.0166 (0.0209) time: 5.9250 data: 0.1725 max mem: 19788 +Epoch: [36] [ 20/2138] eta: 2:57:39 lr: 6.280714164755802e-06 loss: 0.0165 (0.0189) time: 4.0625 data: 0.0021 max mem: 19788 +Epoch: [36] [ 30/2138] eta: 2:45:44 lr: 6.274087773722053e-06 loss: 0.0167 (0.0187) time: 4.0533 data: 0.0029 max mem: 19788 +Epoch: [36] [ 40/2138] eta: 2:39:14 lr: 6.267460604988337e-06 loss: 0.0189 (0.0193) time: 4.0512 data: 0.0037 max mem: 19788 +Epoch: [36] [ 50/2138] eta: 2:35:01 lr: 6.260832657549447e-06 loss: 0.0205 (0.0197) time: 4.0480 data: 0.0038 max mem: 19788 +Epoch: [36] [ 60/2138] eta: 2:31:57 lr: 6.254203930397719e-06 loss: 0.0196 (0.0197) time: 4.0468 data: 0.0035 max mem: 19788 +Epoch: [36] [ 70/2138] eta: 2:29:35 lr: 6.247574422522971e-06 loss: 0.0162 (0.0192) time: 4.0467 data: 0.0033 max mem: 19788 +Epoch: [36] [ 80/2138] eta: 2:27:38 lr: 6.240944132912543e-06 loss: 0.0166 (0.0192) time: 4.0500 data: 0.0032 max mem: 19788 +Epoch: [36] [ 90/2138] eta: 2:25:57 lr: 6.2343130605512415e-06 loss: 0.0181 (0.0191) time: 4.0496 data: 0.0030 max mem: 19788 +Epoch: [36] [ 100/2138] eta: 2:24:28 lr: 6.227681204421378e-06 loss: 0.0184 (0.0192) time: 4.0465 data: 0.0032 max mem: 19788 +Epoch: [36] [ 110/2138] eta: 2:23:07 lr: 6.221048563502716e-06 loss: 0.0184 (0.0192) time: 4.0451 data: 0.0032 max mem: 19788 +Epoch: [36] [ 120/2138] eta: 2:21:52 lr: 6.21441513677248e-06 loss: 0.0199 (0.0193) time: 4.0420 data: 0.0030 max mem: 19788 +Epoch: [36] [ 130/2138] eta: 2:20:44 lr: 6.2077809232053644e-06 loss: 0.0208 (0.0195) time: 4.0434 data: 0.0031 max mem: 19788 +Epoch: [36] [ 140/2138] eta: 2:19:36 lr: 6.201145921773485e-06 loss: 0.0197 (0.0195) time: 4.0353 data: 0.0032 max mem: 19788 +Epoch: [36] [ 150/2138] eta: 2:18:34 lr: 6.194510131446413e-06 loss: 0.0182 (0.0193) time: 4.0322 data: 0.0031 max mem: 19788 +Epoch: [36] [ 160/2138] eta: 2:17:35 lr: 6.18787355119112e-06 loss: 0.0196 (0.0196) time: 4.0408 data: 0.0032 max mem: 19788 +Epoch: [36] [ 170/2138] eta: 2:16:37 lr: 6.181236179972018e-06 loss: 0.0211 (0.0196) time: 4.0370 data: 0.0030 max mem: 19788 +Epoch: [36] [ 180/2138] eta: 2:15:42 lr: 6.174598016750897e-06 loss: 0.0188 (0.0197) time: 4.0398 data: 0.0032 max mem: 19788 +Epoch: [36] [ 190/2138] eta: 2:14:50 lr: 6.167959060486969e-06 loss: 0.0184 (0.0197) time: 4.0486 data: 0.0034 max mem: 19788 +Epoch: [36] [ 200/2138] eta: 2:13:58 lr: 6.161319310136806e-06 loss: 0.0160 (0.0195) time: 4.0509 data: 0.0034 max mem: 19788 +Epoch: [36] [ 210/2138] eta: 2:13:08 lr: 6.1546787646543806e-06 loss: 0.0204 (0.0197) time: 4.0515 data: 0.0035 max mem: 19788 +Epoch: [36] [ 220/2138] eta: 2:12:18 lr: 6.148037422991007e-06 loss: 0.0214 (0.0196) time: 4.0483 data: 0.0034 max mem: 19788 +Epoch: [36] [ 230/2138] eta: 2:11:29 lr: 6.1413952840953814e-06 loss: 0.0193 (0.0198) time: 4.0460 data: 0.0031 max mem: 19788 +Epoch: [36] [ 240/2138] eta: 2:10:39 lr: 6.13475234691352e-06 loss: 0.0201 (0.0197) time: 4.0376 data: 0.0032 max mem: 19788 +Epoch: [36] [ 250/2138] eta: 2:09:50 lr: 6.128108610388803e-06 loss: 0.0178 (0.0197) time: 4.0255 data: 0.0032 max mem: 19788 +Epoch: [36] [ 260/2138] eta: 2:09:02 lr: 6.12146407346191e-06 loss: 0.0177 (0.0196) time: 4.0300 data: 0.0036 max mem: 19788 +Epoch: [36] [ 270/2138] eta: 2:08:16 lr: 6.1148187350708655e-06 loss: 0.0207 (0.0197) time: 4.0421 data: 0.0037 max mem: 19788 +Epoch: [36] [ 280/2138] eta: 2:07:30 lr: 6.1081725941509715e-06 loss: 0.0207 (0.0197) time: 4.0516 data: 0.0033 max mem: 19788 +Epoch: [36] [ 290/2138] eta: 2:06:45 lr: 6.1015256496348556e-06 loss: 0.0197 (0.0197) time: 4.0525 data: 0.0032 max mem: 19788 +Epoch: [36] [ 300/2138] eta: 2:06:00 lr: 6.0948779004524034e-06 loss: 0.0187 (0.0197) time: 4.0507 data: 0.0033 max mem: 19788 +Epoch: [36] [ 310/2138] eta: 2:05:14 lr: 6.088229345530805e-06 loss: 0.0171 (0.0195) time: 4.0465 data: 0.0033 max mem: 19788 +Epoch: [36] [ 320/2138] eta: 2:04:29 lr: 6.081579983794488e-06 loss: 0.0183 (0.0196) time: 4.0375 data: 0.0033 max mem: 19788 +Epoch: [36] [ 330/2138] eta: 2:03:46 lr: 6.0749298141651655e-06 loss: 0.0208 (0.0197) time: 4.0578 data: 0.0036 max mem: 19788 +Epoch: [36] [ 340/2138] eta: 2:03:04 lr: 6.068278835561765e-06 loss: 0.0202 (0.0197) time: 4.0840 data: 0.0036 max mem: 19788 +Epoch: [36] [ 350/2138] eta: 2:02:21 lr: 6.061627046900481e-06 loss: 0.0192 (0.0197) time: 4.0758 data: 0.0033 max mem: 19788 +Epoch: [36] [ 360/2138] eta: 2:01:39 lr: 6.054974447094701e-06 loss: 0.0193 (0.0197) time: 4.0739 data: 0.0033 max mem: 19788 +Epoch: [36] [ 370/2138] eta: 2:00:57 lr: 6.048321035055053e-06 loss: 0.0206 (0.0198) time: 4.0872 data: 0.0034 max mem: 19788 +Epoch: [36] [ 380/2138] eta: 2:00:17 lr: 6.041666809689348e-06 loss: 0.0187 (0.0198) time: 4.1084 data: 0.0032 max mem: 19788 +Epoch: [36] [ 390/2138] eta: 1:59:36 lr: 6.035011769902609e-06 loss: 0.0177 (0.0198) time: 4.1126 data: 0.0034 max mem: 19788 +Epoch: [36] [ 400/2138] eta: 1:58:54 lr: 6.028355914597027e-06 loss: 0.0199 (0.0198) time: 4.0961 data: 0.0037 max mem: 19788 +Epoch: [36] [ 410/2138] eta: 1:58:12 lr: 6.02169924267196e-06 loss: 0.0209 (0.0199) time: 4.0886 data: 0.0035 max mem: 19788 +Epoch: [36] [ 420/2138] eta: 1:57:30 lr: 6.01504175302395e-06 loss: 0.0212 (0.0198) time: 4.0804 data: 0.0035 max mem: 19788 +Epoch: [36] [ 430/2138] eta: 1:56:47 lr: 6.00838344454666e-06 loss: 0.0182 (0.0198) time: 4.0711 data: 0.0032 max mem: 19788 +Epoch: [36] [ 440/2138] eta: 1:56:05 lr: 6.001724316130922e-06 loss: 0.0195 (0.0200) time: 4.0659 data: 0.0033 max mem: 19788 +Epoch: [36] [ 450/2138] eta: 1:55:23 lr: 5.995064366664664e-06 loss: 0.0191 (0.0200) time: 4.0658 data: 0.0033 max mem: 19788 +Epoch: [36] [ 460/2138] eta: 1:54:40 lr: 5.988403595032962e-06 loss: 0.0206 (0.0200) time: 4.0621 data: 0.0033 max mem: 19788 +Epoch: [36] [ 470/2138] eta: 1:53:58 lr: 5.98174200011797e-06 loss: 0.0206 (0.0200) time: 4.0637 data: 0.0035 max mem: 19788 +Epoch: [36] [ 480/2138] eta: 1:53:16 lr: 5.975079580798963e-06 loss: 0.0196 (0.0201) time: 4.0659 data: 0.0036 max mem: 19788 +Epoch: [36] [ 490/2138] eta: 1:52:34 lr: 5.968416335952275e-06 loss: 0.0190 (0.0201) time: 4.0727 data: 0.0035 max mem: 19788 +Epoch: [36] [ 500/2138] eta: 1:51:52 lr: 5.961752264451338e-06 loss: 0.0190 (0.0201) time: 4.0729 data: 0.0033 max mem: 19788 +Epoch: [36] [ 510/2138] eta: 1:51:10 lr: 5.955087365166617e-06 loss: 0.0191 (0.0200) time: 4.0620 data: 0.0033 max mem: 19788 +Epoch: [36] [ 520/2138] eta: 1:50:28 lr: 5.948421636965657e-06 loss: 0.0200 (0.0200) time: 4.0616 data: 0.0036 max mem: 19788 +Epoch: [36] [ 530/2138] eta: 1:49:45 lr: 5.941755078713012e-06 loss: 0.0183 (0.0200) time: 4.0455 data: 0.0035 max mem: 19788 +Epoch: [36] [ 540/2138] eta: 1:49:02 lr: 5.935087689270291e-06 loss: 0.0173 (0.0200) time: 4.0304 data: 0.0032 max mem: 19788 +Epoch: [36] [ 550/2138] eta: 1:48:19 lr: 5.928419467496091e-06 loss: 0.0184 (0.0200) time: 4.0295 data: 0.0033 max mem: 19788 +Epoch: [36] [ 560/2138] eta: 1:47:36 lr: 5.921750412246043e-06 loss: 0.0190 (0.0200) time: 4.0281 data: 0.0032 max mem: 19788 +Epoch: [36] [ 570/2138] eta: 1:46:54 lr: 5.915080522372738e-06 loss: 0.0171 (0.0200) time: 4.0309 data: 0.0031 max mem: 19788 +Epoch: [36] [ 580/2138] eta: 1:46:11 lr: 5.90840979672578e-06 loss: 0.0188 (0.0200) time: 4.0351 data: 0.0032 max mem: 19788 +Epoch: [36] [ 590/2138] eta: 1:45:29 lr: 5.901738234151712e-06 loss: 0.0196 (0.0200) time: 4.0340 data: 0.0030 max mem: 19788 +Epoch: [36] [ 600/2138] eta: 1:44:46 lr: 5.895065833494062e-06 loss: 0.0186 (0.0200) time: 4.0276 data: 0.0031 max mem: 19788 +Epoch: [36] [ 610/2138] eta: 1:44:04 lr: 5.888392593593277e-06 loss: 0.0189 (0.0200) time: 4.0242 data: 0.0032 max mem: 19788 +Epoch: [36] [ 620/2138] eta: 1:43:22 lr: 5.881718513286762e-06 loss: 0.0196 (0.0200) time: 4.0373 data: 0.0032 max mem: 19788 +Epoch: [36] [ 630/2138] eta: 1:42:40 lr: 5.87504359140882e-06 loss: 0.0188 (0.0200) time: 4.0489 data: 0.0032 max mem: 19788 +Epoch: [36] [ 640/2138] eta: 1:41:59 lr: 5.868367826790687e-06 loss: 0.0191 (0.0200) time: 4.0456 data: 0.0032 max mem: 19788 +Epoch: [36] [ 650/2138] eta: 1:41:17 lr: 5.861691218260472e-06 loss: 0.0186 (0.0199) time: 4.0402 data: 0.0033 max mem: 19788 +Epoch: [36] [ 660/2138] eta: 1:40:35 lr: 5.855013764643194e-06 loss: 0.0179 (0.0200) time: 4.0372 data: 0.0034 max mem: 19788 +Epoch: [36] [ 670/2138] eta: 1:39:53 lr: 5.848335464760719e-06 loss: 0.0183 (0.0199) time: 4.0428 data: 0.0037 max mem: 19788 +Epoch: [36] [ 680/2138] eta: 1:39:12 lr: 5.8416563174318e-06 loss: 0.0200 (0.0200) time: 4.0467 data: 0.0035 max mem: 19788 +Epoch: [36] [ 690/2138] eta: 1:38:30 lr: 5.834976321472011e-06 loss: 0.0196 (0.0199) time: 4.0452 data: 0.0032 max mem: 19788 +Epoch: [36] [ 700/2138] eta: 1:37:48 lr: 5.82829547569379e-06 loss: 0.0189 (0.0200) time: 4.0482 data: 0.0031 max mem: 19788 +Epoch: [36] [ 710/2138] eta: 1:37:06 lr: 5.8216137789063745e-06 loss: 0.0209 (0.0200) time: 4.0365 data: 0.0032 max mem: 19788 +Epoch: [36] [ 720/2138] eta: 1:36:25 lr: 5.814931229915819e-06 loss: 0.0185 (0.0200) time: 4.0252 data: 0.0034 max mem: 19788 +Epoch: [36] [ 730/2138] eta: 1:35:43 lr: 5.808247827524991e-06 loss: 0.0185 (0.0200) time: 4.0324 data: 0.0033 max mem: 19788 +Epoch: [36] [ 740/2138] eta: 1:35:01 lr: 5.801563570533517e-06 loss: 0.0169 (0.0200) time: 4.0323 data: 0.0032 max mem: 19788 +Epoch: [36] [ 750/2138] eta: 1:34:20 lr: 5.7948784577378244e-06 loss: 0.0172 (0.0200) time: 4.0307 data: 0.0032 max mem: 19788 +Epoch: [36] [ 760/2138] eta: 1:33:38 lr: 5.788192487931074e-06 loss: 0.0199 (0.0200) time: 4.0408 data: 0.0031 max mem: 19788 +Epoch: [36] [ 770/2138] eta: 1:32:57 lr: 5.781505659903198e-06 loss: 0.0199 (0.0200) time: 4.0480 data: 0.0032 max mem: 19788 +Epoch: [36] [ 780/2138] eta: 1:32:16 lr: 5.774817972440839e-06 loss: 0.0222 (0.0201) time: 4.0481 data: 0.0033 max mem: 19788 +Epoch: [36] [ 790/2138] eta: 1:31:34 lr: 5.768129424327383e-06 loss: 0.0193 (0.0201) time: 4.0412 data: 0.0035 max mem: 19788 +Epoch: [36] [ 800/2138] eta: 1:30:53 lr: 5.761440014342902e-06 loss: 0.0176 (0.0200) time: 4.0359 data: 0.0034 max mem: 19788 +Epoch: [36] [ 810/2138] eta: 1:30:11 lr: 5.7547497412641846e-06 loss: 0.0166 (0.0200) time: 4.0374 data: 0.0032 max mem: 19788 +Epoch: [36] [ 820/2138] eta: 1:29:30 lr: 5.7480586038646774e-06 loss: 0.0185 (0.0200) time: 4.0413 data: 0.0031 max mem: 19788 +Epoch: [36] [ 830/2138] eta: 1:28:49 lr: 5.74136660091452e-06 loss: 0.0158 (0.0200) time: 4.0444 data: 0.0031 max mem: 19788 +Epoch: [36] [ 840/2138] eta: 1:28:08 lr: 5.734673731180482e-06 loss: 0.0157 (0.0200) time: 4.0449 data: 0.0032 max mem: 19788 +Epoch: [36] [ 850/2138] eta: 1:27:27 lr: 5.727979993425998e-06 loss: 0.0161 (0.0199) time: 4.0501 data: 0.0032 max mem: 19788 +Epoch: [36] [ 860/2138] eta: 1:26:46 lr: 5.721285386411107e-06 loss: 0.0169 (0.0199) time: 4.0502 data: 0.0034 max mem: 19788 +Epoch: [36] [ 870/2138] eta: 1:26:04 lr: 5.714589908892485e-06 loss: 0.0218 (0.0199) time: 4.0447 data: 0.0036 max mem: 19788 +Epoch: [36] [ 880/2138] eta: 1:25:23 lr: 5.707893559623386e-06 loss: 0.0185 (0.0199) time: 4.0355 data: 0.0035 max mem: 19788 +Epoch: [36] [ 890/2138] eta: 1:24:42 lr: 5.701196337353674e-06 loss: 0.0187 (0.0199) time: 4.0262 data: 0.0035 max mem: 19788 +Epoch: [36] [ 900/2138] eta: 1:24:00 lr: 5.69449824082976e-06 loss: 0.0204 (0.0200) time: 4.0262 data: 0.0034 max mem: 19788 +Epoch: [36] [ 910/2138] eta: 1:23:19 lr: 5.6877992687946426e-06 loss: 0.0191 (0.0199) time: 4.0383 data: 0.0032 max mem: 19788 +Epoch: [36] [ 920/2138] eta: 1:22:38 lr: 5.681099419987837e-06 loss: 0.0176 (0.0199) time: 4.0477 data: 0.0033 max mem: 19788 +Epoch: [36] [ 930/2138] eta: 1:21:57 lr: 5.6743986931454166e-06 loss: 0.0174 (0.0200) time: 4.0489 data: 0.0035 max mem: 19788 +Epoch: [36] [ 940/2138] eta: 1:21:16 lr: 5.667697086999944e-06 loss: 0.0193 (0.0200) time: 4.0373 data: 0.0034 max mem: 19788 +Epoch: [36] [ 950/2138] eta: 1:20:35 lr: 5.660994600280514e-06 loss: 0.0186 (0.0200) time: 4.0376 data: 0.0033 max mem: 19788 +Epoch: [36] [ 960/2138] eta: 1:19:54 lr: 5.65429123171268e-06 loss: 0.0177 (0.0200) time: 4.0442 data: 0.0033 max mem: 19788 +Epoch: [36] [ 970/2138] eta: 1:19:13 lr: 5.647586980018498e-06 loss: 0.0175 (0.0200) time: 4.0361 data: 0.0034 max mem: 19788 +Epoch: [36] [ 980/2138] eta: 1:18:32 lr: 5.640881843916457e-06 loss: 0.0171 (0.0199) time: 4.0362 data: 0.0034 max mem: 19788 +Epoch: [36] [ 990/2138] eta: 1:17:50 lr: 5.634175822121518e-06 loss: 0.0192 (0.0200) time: 4.0299 data: 0.0031 max mem: 19788 +Epoch: [36] [1000/2138] eta: 1:17:09 lr: 5.627468913345044e-06 loss: 0.0202 (0.0200) time: 4.0268 data: 0.0031 max mem: 19788 +Epoch: [36] [1010/2138] eta: 1:16:28 lr: 5.620761116294843e-06 loss: 0.0183 (0.0200) time: 4.0325 data: 0.0032 max mem: 19788 +Epoch: [36] [1020/2138] eta: 1:15:47 lr: 5.614052429675105e-06 loss: 0.0175 (0.0200) time: 4.0339 data: 0.0031 max mem: 19788 +Epoch: [36] [1030/2138] eta: 1:15:06 lr: 5.607342852186402e-06 loss: 0.0188 (0.0200) time: 4.0335 data: 0.0032 max mem: 19788 +Epoch: [36] [1040/2138] eta: 1:14:25 lr: 5.600632382525702e-06 loss: 0.0186 (0.0199) time: 4.0292 data: 0.0036 max mem: 19788 +Epoch: [36] [1050/2138] eta: 1:13:44 lr: 5.593921019386301e-06 loss: 0.0191 (0.0200) time: 4.0313 data: 0.0038 max mem: 19788 +Epoch: [36] [1060/2138] eta: 1:13:03 lr: 5.587208761457865e-06 loss: 0.0194 (0.0200) time: 4.0412 data: 0.0034 max mem: 19788 +Epoch: [36] [1070/2138] eta: 1:12:22 lr: 5.580495607426356e-06 loss: 0.0187 (0.0200) time: 4.0417 data: 0.0033 max mem: 19788 +Epoch: [36] [1080/2138] eta: 1:11:41 lr: 5.573781555974077e-06 loss: 0.0180 (0.0200) time: 4.0291 data: 0.0031 max mem: 19788 +Epoch: [36] [1090/2138] eta: 1:11:00 lr: 5.5670666057795984e-06 loss: 0.0165 (0.0200) time: 4.0252 data: 0.0029 max mem: 19788 +Epoch: [36] [1100/2138] eta: 1:10:19 lr: 5.560350755517799e-06 loss: 0.0216 (0.0200) time: 4.0317 data: 0.0030 max mem: 19788 +Epoch: [36] [1110/2138] eta: 1:09:38 lr: 5.553634003859796e-06 loss: 0.0210 (0.0200) time: 4.0321 data: 0.0032 max mem: 19788 +Epoch: [36] [1120/2138] eta: 1:08:57 lr: 5.5469163494729825e-06 loss: 0.0177 (0.0200) time: 4.0248 data: 0.0031 max mem: 19788 +Epoch: [36] [1130/2138] eta: 1:08:16 lr: 5.5401977910209565e-06 loss: 0.0198 (0.0200) time: 4.0286 data: 0.0031 max mem: 19788 +Epoch: [36] [1140/2138] eta: 1:07:35 lr: 5.533478327163563e-06 loss: 0.0194 (0.0200) time: 4.0443 data: 0.0032 max mem: 19788 +Epoch: [36] [1150/2138] eta: 1:06:55 lr: 5.526757956556823e-06 loss: 0.0183 (0.0199) time: 4.0469 data: 0.0034 max mem: 19788 +Epoch: [36] [1160/2138] eta: 1:06:14 lr: 5.5200366778529686e-06 loss: 0.0178 (0.0199) time: 4.0465 data: 0.0033 max mem: 19788 +Epoch: [36] [1170/2138] eta: 1:05:33 lr: 5.513314489700376e-06 loss: 0.0184 (0.0199) time: 4.0538 data: 0.0033 max mem: 19788 +Epoch: [36] [1180/2138] eta: 1:04:52 lr: 5.506591390743603e-06 loss: 0.0203 (0.0199) time: 4.0545 data: 0.0034 max mem: 19788 +Epoch: [36] [1190/2138] eta: 1:04:12 lr: 5.499867379623319e-06 loss: 0.0196 (0.0199) time: 4.0479 data: 0.0032 max mem: 19788 +Epoch: [36] [1200/2138] eta: 1:03:31 lr: 5.49314245497634e-06 loss: 0.0176 (0.0199) time: 4.0431 data: 0.0030 max mem: 19788 +Epoch: [36] [1210/2138] eta: 1:02:50 lr: 5.486416615435564e-06 loss: 0.0179 (0.0199) time: 4.0392 data: 0.0032 max mem: 19788 +Epoch: [36] [1220/2138] eta: 1:02:09 lr: 5.47968985963e-06 loss: 0.0186 (0.0199) time: 4.0360 data: 0.0033 max mem: 19788 +Epoch: [36] [1230/2138] eta: 1:01:28 lr: 5.472962186184708e-06 loss: 0.0176 (0.0199) time: 4.0427 data: 0.0032 max mem: 19788 +Epoch: [36] [1240/2138] eta: 1:00:48 lr: 5.466233593720826e-06 loss: 0.0176 (0.0199) time: 4.0486 data: 0.0033 max mem: 19788 +Epoch: [36] [1250/2138] eta: 1:00:07 lr: 5.459504080855509e-06 loss: 0.0178 (0.0199) time: 4.0410 data: 0.0033 max mem: 19788 +Epoch: [36] [1260/2138] eta: 0:59:26 lr: 5.452773646201954e-06 loss: 0.0166 (0.0199) time: 4.0395 data: 0.0034 max mem: 19788 +Epoch: [36] [1270/2138] eta: 0:58:45 lr: 5.446042288369344e-06 loss: 0.0166 (0.0199) time: 4.0396 data: 0.0034 max mem: 19788 +Epoch: [36] [1280/2138] eta: 0:58:05 lr: 5.439310005962872e-06 loss: 0.0174 (0.0199) time: 4.0409 data: 0.0033 max mem: 19788 +Epoch: [36] [1290/2138] eta: 0:57:24 lr: 5.4325767975836784e-06 loss: 0.0185 (0.0199) time: 4.0393 data: 0.0033 max mem: 19788 +Epoch: [36] [1300/2138] eta: 0:56:43 lr: 5.425842661828884e-06 loss: 0.0176 (0.0199) time: 4.0292 data: 0.0032 max mem: 19788 +Epoch: [36] [1310/2138] eta: 0:56:02 lr: 5.419107597291518e-06 loss: 0.0185 (0.0199) time: 4.0265 data: 0.0032 max mem: 19788 +Epoch: [36] [1320/2138] eta: 0:55:21 lr: 5.412371602560556e-06 loss: 0.0199 (0.0199) time: 4.0237 data: 0.0034 max mem: 19788 +Epoch: [36] [1330/2138] eta: 0:54:40 lr: 5.4056346762208575e-06 loss: 0.0195 (0.0199) time: 4.0259 data: 0.0034 max mem: 19788 +Epoch: [36] [1340/2138] eta: 0:54:00 lr: 5.398896816853164e-06 loss: 0.0191 (0.0199) time: 4.0322 data: 0.0035 max mem: 19788 +Epoch: [36] [1350/2138] eta: 0:53:19 lr: 5.392158023034104e-06 loss: 0.0207 (0.0199) time: 4.0277 data: 0.0035 max mem: 19788 +Epoch: [36] [1360/2138] eta: 0:52:38 lr: 5.385418293336128e-06 loss: 0.0211 (0.0199) time: 4.0272 data: 0.0034 max mem: 19788 +Epoch: [36] [1370/2138] eta: 0:51:57 lr: 5.378677626327546e-06 loss: 0.0207 (0.0199) time: 4.0385 data: 0.0035 max mem: 19788 +Epoch: [36] [1380/2138] eta: 0:51:17 lr: 5.371936020572451e-06 loss: 0.0200 (0.0200) time: 4.0494 data: 0.0035 max mem: 19788 +Epoch: [36] [1390/2138] eta: 0:50:36 lr: 5.365193474630759e-06 loss: 0.0200 (0.0200) time: 4.0493 data: 0.0036 max mem: 19788 +Epoch: [36] [1400/2138] eta: 0:49:55 lr: 5.3584499870581365e-06 loss: 0.0196 (0.0200) time: 4.0476 data: 0.0035 max mem: 19788 +Epoch: [36] [1410/2138] eta: 0:49:15 lr: 5.351705556406035e-06 loss: 0.0183 (0.0199) time: 4.0451 data: 0.0035 max mem: 19788 +Epoch: [36] [1420/2138] eta: 0:48:34 lr: 5.344960181221616e-06 loss: 0.0166 (0.0199) time: 4.0425 data: 0.0036 max mem: 19788 +Epoch: [36] [1430/2138] eta: 0:47:53 lr: 5.338213860047793e-06 loss: 0.0204 (0.0199) time: 4.0398 data: 0.0036 max mem: 19788 +Epoch: [36] [1440/2138] eta: 0:47:13 lr: 5.331466591423154e-06 loss: 0.0181 (0.0199) time: 4.0340 data: 0.0034 max mem: 19788 +Epoch: [36] [1450/2138] eta: 0:46:32 lr: 5.3247183738819964e-06 loss: 0.0203 (0.0200) time: 4.0313 data: 0.0032 max mem: 19788 +Epoch: [36] [1460/2138] eta: 0:45:51 lr: 5.317969205954259e-06 loss: 0.0216 (0.0199) time: 4.0314 data: 0.0032 max mem: 19788 +Epoch: [36] [1470/2138] eta: 0:45:11 lr: 5.311219086165548e-06 loss: 0.0200 (0.0200) time: 4.0325 data: 0.0033 max mem: 19788 +Epoch: [36] [1480/2138] eta: 0:44:30 lr: 5.304468013037077e-06 loss: 0.0205 (0.0200) time: 4.0263 data: 0.0032 max mem: 19788 +Epoch: [36] [1490/2138] eta: 0:43:49 lr: 5.297715985085688e-06 loss: 0.0203 (0.0200) time: 4.0312 data: 0.0031 max mem: 19788 +Epoch: [36] [1500/2138] eta: 0:43:09 lr: 5.29096300082379e-06 loss: 0.0192 (0.0200) time: 4.0455 data: 0.0033 max mem: 19788 +Epoch: [36] [1510/2138] eta: 0:42:28 lr: 5.2842090587593834e-06 loss: 0.0192 (0.0200) time: 4.0486 data: 0.0033 max mem: 19788 +Epoch: [36] [1520/2138] eta: 0:41:47 lr: 5.277454157395995e-06 loss: 0.0203 (0.0200) time: 4.0480 data: 0.0032 max mem: 19788 +Epoch: [36] [1530/2138] eta: 0:41:07 lr: 5.2706982952327075e-06 loss: 0.0172 (0.0200) time: 4.0530 data: 0.0032 max mem: 19788 +Epoch: [36] [1540/2138] eta: 0:40:26 lr: 5.263941470764085e-06 loss: 0.0169 (0.0200) time: 4.0498 data: 0.0032 max mem: 19788 +Epoch: [36] [1550/2138] eta: 0:39:45 lr: 5.257183682480211e-06 loss: 0.0188 (0.0200) time: 4.0456 data: 0.0033 max mem: 19788 +Epoch: [36] [1560/2138] eta: 0:39:05 lr: 5.250424928866615e-06 loss: 0.0188 (0.0200) time: 4.0420 data: 0.0034 max mem: 19788 +Epoch: [36] [1570/2138] eta: 0:38:24 lr: 5.243665208404298e-06 loss: 0.0181 (0.0200) time: 4.0412 data: 0.0035 max mem: 19788 +Epoch: [36] [1580/2138] eta: 0:37:44 lr: 5.236904519569669e-06 loss: 0.0181 (0.0200) time: 4.0418 data: 0.0034 max mem: 19788 +Epoch: [36] [1590/2138] eta: 0:37:03 lr: 5.230142860834572e-06 loss: 0.0182 (0.0200) time: 4.0402 data: 0.0035 max mem: 19788 +Epoch: [36] [1600/2138] eta: 0:36:22 lr: 5.223380230666215e-06 loss: 0.0217 (0.0200) time: 4.0382 data: 0.0035 max mem: 19788 +Epoch: [36] [1610/2138] eta: 0:35:42 lr: 5.216616627527199e-06 loss: 0.0201 (0.0200) time: 4.0358 data: 0.0032 max mem: 19788 +Epoch: [36] [1620/2138] eta: 0:35:01 lr: 5.209852049875456e-06 loss: 0.0180 (0.0200) time: 4.0444 data: 0.0033 max mem: 19788 +Epoch: [36] [1630/2138] eta: 0:34:21 lr: 5.2030864961642434e-06 loss: 0.0192 (0.0200) time: 4.0727 data: 0.0034 max mem: 19788 +Epoch: [36] [1640/2138] eta: 0:33:40 lr: 5.196319964842146e-06 loss: 0.0187 (0.0200) time: 4.0638 data: 0.0033 max mem: 19788 +Epoch: [36] [1650/2138] eta: 0:32:59 lr: 5.189552454353009e-06 loss: 0.0170 (0.0199) time: 4.0304 data: 0.0033 max mem: 19788 +Epoch: [36] [1660/2138] eta: 0:32:19 lr: 5.182783963135965e-06 loss: 0.0177 (0.0199) time: 4.0264 data: 0.0035 max mem: 19788 +Epoch: [36] [1670/2138] eta: 0:31:38 lr: 5.176014489625365e-06 loss: 0.0168 (0.0199) time: 4.0283 data: 0.0035 max mem: 19788 +Epoch: [36] [1680/2138] eta: 0:30:57 lr: 5.169244032250808e-06 loss: 0.0188 (0.0199) time: 4.0319 data: 0.0036 max mem: 19788 +Epoch: [36] [1690/2138] eta: 0:30:17 lr: 5.162472589437067e-06 loss: 0.0191 (0.0199) time: 4.0269 data: 0.0036 max mem: 19788 +Epoch: [36] [1700/2138] eta: 0:29:36 lr: 5.155700159604118e-06 loss: 0.0179 (0.0199) time: 4.0335 data: 0.0032 max mem: 19788 +Epoch: [36] [1710/2138] eta: 0:28:55 lr: 5.148926741167069e-06 loss: 0.0184 (0.0199) time: 4.0332 data: 0.0032 max mem: 19788 +Epoch: [36] [1720/2138] eta: 0:28:15 lr: 5.142152332536187e-06 loss: 0.0196 (0.0199) time: 4.0231 data: 0.0032 max mem: 19788 +Epoch: [36] [1730/2138] eta: 0:27:34 lr: 5.135376932116825e-06 loss: 0.0195 (0.0199) time: 4.0298 data: 0.0032 max mem: 19788 +Epoch: [36] [1740/2138] eta: 0:26:54 lr: 5.128600538309456e-06 loss: 0.0186 (0.0199) time: 4.0296 data: 0.0033 max mem: 19788 +Epoch: [36] [1750/2138] eta: 0:26:13 lr: 5.121823149509591e-06 loss: 0.0185 (0.0199) time: 4.0273 data: 0.0033 max mem: 19788 +Epoch: [36] [1760/2138] eta: 0:25:32 lr: 5.1150447641078115e-06 loss: 0.0210 (0.0199) time: 4.0368 data: 0.0032 max mem: 19788 +Epoch: [36] [1770/2138] eta: 0:24:52 lr: 5.108265380489701e-06 loss: 0.0199 (0.0199) time: 4.0307 data: 0.0031 max mem: 19788 +Epoch: [36] [1780/2138] eta: 0:24:11 lr: 5.101484997035864e-06 loss: 0.0199 (0.0199) time: 4.0222 data: 0.0032 max mem: 19788 +Epoch: [36] [1790/2138] eta: 0:23:31 lr: 5.094703612121857e-06 loss: 0.0190 (0.0199) time: 4.0313 data: 0.0032 max mem: 19788 +Epoch: [36] [1800/2138] eta: 0:22:50 lr: 5.0879212241182195e-06 loss: 0.0177 (0.0199) time: 4.0294 data: 0.0032 max mem: 19788 +Epoch: [36] [1810/2138] eta: 0:22:09 lr: 5.081137831390393e-06 loss: 0.0190 (0.0199) time: 4.0255 data: 0.0033 max mem: 19788 +Epoch: [36] [1820/2138] eta: 0:21:29 lr: 5.0743534322987525e-06 loss: 0.0203 (0.0199) time: 4.0397 data: 0.0032 max mem: 19788 +Epoch: [36] [1830/2138] eta: 0:20:48 lr: 5.067568025198533e-06 loss: 0.0189 (0.0199) time: 4.0401 data: 0.0033 max mem: 19788 +Epoch: [36] [1840/2138] eta: 0:20:08 lr: 5.060781608439854e-06 loss: 0.0189 (0.0199) time: 4.0317 data: 0.0035 max mem: 19788 +Epoch: [36] [1850/2138] eta: 0:19:27 lr: 5.053994180367647e-06 loss: 0.0211 (0.0199) time: 4.0386 data: 0.0035 max mem: 19788 +Epoch: [36] [1860/2138] eta: 0:18:47 lr: 5.047205739321684e-06 loss: 0.0200 (0.0200) time: 4.0393 data: 0.0035 max mem: 19788 +Epoch: [36] [1870/2138] eta: 0:18:06 lr: 5.040416283636495e-06 loss: 0.0184 (0.0200) time: 4.0284 data: 0.0035 max mem: 19788 +Epoch: [36] [1880/2138] eta: 0:17:25 lr: 5.033625811641407e-06 loss: 0.0182 (0.0200) time: 4.0254 data: 0.0034 max mem: 19788 +Epoch: [36] [1890/2138] eta: 0:16:45 lr: 5.0268343216604555e-06 loss: 0.0177 (0.0199) time: 4.0308 data: 0.0034 max mem: 19788 +Epoch: [36] [1900/2138] eta: 0:16:04 lr: 5.020041812012422e-06 loss: 0.0176 (0.0199) time: 4.0278 data: 0.0034 max mem: 19788 +Epoch: [36] [1910/2138] eta: 0:15:24 lr: 5.01324828101075e-06 loss: 0.0187 (0.0199) time: 4.0259 data: 0.0033 max mem: 19788 +Epoch: [36] [1920/2138] eta: 0:14:43 lr: 5.006453726963579e-06 loss: 0.0191 (0.0199) time: 4.0316 data: 0.0032 max mem: 19788 +Epoch: [36] [1930/2138] eta: 0:14:03 lr: 4.999658148173668e-06 loss: 0.0192 (0.0199) time: 4.0320 data: 0.0031 max mem: 19788 +Epoch: [36] [1940/2138] eta: 0:13:22 lr: 4.992861542938393e-06 loss: 0.0195 (0.0199) time: 4.0327 data: 0.0032 max mem: 19788 +Epoch: [36] [1950/2138] eta: 0:12:41 lr: 4.9860639095497395e-06 loss: 0.0195 (0.0199) time: 4.0332 data: 0.0033 max mem: 19788 +Epoch: [36] [1960/2138] eta: 0:12:01 lr: 4.979265246294236e-06 loss: 0.0188 (0.0199) time: 4.0366 data: 0.0032 max mem: 19788 +Epoch: [36] [1970/2138] eta: 0:11:20 lr: 4.972465551452975e-06 loss: 0.0188 (0.0199) time: 4.0431 data: 0.0032 max mem: 19788 +Epoch: [36] [1980/2138] eta: 0:10:40 lr: 4.965664823301536e-06 loss: 0.0166 (0.0199) time: 4.0421 data: 0.0031 max mem: 19788 +Epoch: [36] [1990/2138] eta: 0:09:59 lr: 4.958863060110016e-06 loss: 0.0170 (0.0199) time: 4.0364 data: 0.0032 max mem: 19788 +Epoch: [36] [2000/2138] eta: 0:09:19 lr: 4.9520602601429485e-06 loss: 0.0179 (0.0199) time: 4.0337 data: 0.0035 max mem: 19788 +Epoch: [36] [2010/2138] eta: 0:08:38 lr: 4.945256421659326e-06 loss: 0.0194 (0.0199) time: 4.0481 data: 0.0034 max mem: 19788 +Epoch: [36] [2020/2138] eta: 0:07:58 lr: 4.93845154291253e-06 loss: 0.0191 (0.0199) time: 4.0403 data: 0.0031 max mem: 19788 +Epoch: [36] [2030/2138] eta: 0:07:17 lr: 4.931645622150346e-06 loss: 0.0200 (0.0199) time: 4.0261 data: 0.0032 max mem: 19788 +Epoch: [36] [2040/2138] eta: 0:06:37 lr: 4.924838657614895e-06 loss: 0.0200 (0.0199) time: 4.0386 data: 0.0033 max mem: 19788 +Epoch: [36] [2050/2138] eta: 0:05:56 lr: 4.918030647542651e-06 loss: 0.0199 (0.0199) time: 4.0363 data: 0.0032 max mem: 19788 +Epoch: [36] [2060/2138] eta: 0:05:16 lr: 4.911221590164365e-06 loss: 0.0187 (0.0199) time: 4.0356 data: 0.0033 max mem: 19788 +Epoch: [36] [2070/2138] eta: 0:04:35 lr: 4.9044114837050925e-06 loss: 0.0170 (0.0199) time: 4.0385 data: 0.0035 max mem: 19788 +Epoch: [36] [2080/2138] eta: 0:03:55 lr: 4.8976003263841075e-06 loss: 0.0184 (0.0199) time: 4.0352 data: 0.0036 max mem: 19788 +Epoch: [36] [2090/2138] eta: 0:03:14 lr: 4.890788116414932e-06 loss: 0.0187 (0.0199) time: 4.0328 data: 0.0035 max mem: 19788 +Epoch: [36] [2100/2138] eta: 0:02:33 lr: 4.883974852005257e-06 loss: 0.0187 (0.0199) time: 4.0308 data: 0.0033 max mem: 19788 +Epoch: [36] [2110/2138] eta: 0:01:53 lr: 4.877160531356961e-06 loss: 0.0211 (0.0199) time: 4.0248 data: 0.0031 max mem: 19788 +Epoch: [36] [2120/2138] eta: 0:01:12 lr: 4.8703451526660365e-06 loss: 0.0235 (0.0199) time: 4.0288 data: 0.0032 max mem: 19788 +Epoch: [36] [2130/2138] eta: 0:00:32 lr: 4.863528714122609e-06 loss: 0.0207 (0.0199) time: 4.0358 data: 0.0031 max mem: 19788 +Epoch: [36] Total time: 2:24:23 +Test: [ 0/21770] eta: 18:53:35 time: 3.1243 data: 2.9791 max mem: 19788 +Test: [ 100/21770] eta: 0:36:58 time: 0.0858 data: 0.0021 max mem: 19788 +Test: [ 200/21770] eta: 0:30:10 time: 0.0628 data: 0.0021 max mem: 19788 +Test: [ 300/21770] eta: 0:28:52 time: 0.0710 data: 0.0023 max mem: 19788 +Test: [ 400/21770] eta: 0:27:51 time: 0.0616 data: 0.0019 max mem: 19788 +Test: [ 500/21770] eta: 0:26:48 time: 0.0736 data: 0.0021 max mem: 19788 +Test: [ 600/21770] eta: 0:26:10 time: 0.0694 data: 0.0021 max mem: 19788 +Test: [ 700/21770] eta: 0:25:56 time: 0.0683 data: 0.0022 max mem: 19788 +Test: [ 800/21770] eta: 0:25:32 time: 0.0620 data: 0.0019 max mem: 19788 +Test: [ 900/21770] eta: 0:25:21 time: 0.0770 data: 0.0025 max mem: 19788 +Test: [ 1000/21770] eta: 0:25:19 time: 0.0685 data: 0.0020 max mem: 19788 +Test: [ 1100/21770] eta: 0:25:11 time: 0.0834 data: 0.0024 max mem: 19788 +Test: [ 1200/21770] eta: 0:24:57 time: 0.0653 data: 0.0019 max mem: 19788 +Test: [ 1300/21770] eta: 0:24:42 time: 0.0645 data: 0.0021 max mem: 19788 +Test: [ 1400/21770] eta: 0:24:30 time: 0.0660 data: 0.0020 max mem: 19788 +Test: [ 1500/21770] eta: 0:24:31 time: 0.0801 data: 0.0026 max mem: 19788 +Test: [ 1600/21770] eta: 0:24:23 time: 0.0637 data: 0.0020 max mem: 19788 +Test: [ 1700/21770] eta: 0:24:08 time: 0.0642 data: 0.0020 max mem: 19788 +Test: [ 1800/21770] eta: 0:23:59 time: 0.0848 data: 0.0022 max mem: 19788 +Test: [ 1900/21770] eta: 0:23:48 time: 0.0683 data: 0.0019 max mem: 19788 +Test: [ 2000/21770] eta: 0:23:43 time: 0.0715 data: 0.0022 max mem: 19788 +Test: [ 2100/21770] eta: 0:23:32 time: 0.0675 data: 0.0021 max mem: 19788 +Test: [ 2200/21770] eta: 0:23:24 time: 0.0782 data: 0.0023 max mem: 19788 +Test: [ 2300/21770] eta: 0:23:13 time: 0.0643 data: 0.0022 max mem: 19788 +Test: [ 2400/21770] eta: 0:23:06 time: 0.0854 data: 0.0026 max mem: 19788 +Test: [ 2500/21770] eta: 0:23:06 time: 0.0839 data: 0.0025 max mem: 19788 +Test: [ 2600/21770] eta: 0:22:58 time: 0.0783 data: 0.0025 max mem: 19788 +Test: [ 2700/21770] eta: 0:22:52 time: 0.0837 data: 0.0026 max mem: 19788 +Test: [ 2800/21770] eta: 0:22:45 time: 0.0842 data: 0.0027 max mem: 19788 +Test: [ 2900/21770] eta: 0:22:38 time: 0.0759 data: 0.0022 max mem: 19788 +Test: [ 3000/21770] eta: 0:22:28 time: 0.0709 data: 0.0019 max mem: 19788 +Test: [ 3100/21770] eta: 0:22:19 time: 0.0641 data: 0.0020 max mem: 19788 +Test: [ 3200/21770] eta: 0:22:08 time: 0.0636 data: 0.0019 max mem: 19788 +Test: [ 3300/21770] eta: 0:21:59 time: 0.0654 data: 0.0020 max mem: 19788 +Test: [ 3400/21770] eta: 0:21:51 time: 0.0654 data: 0.0021 max mem: 19788 +Test: [ 3500/21770] eta: 0:21:45 time: 0.0843 data: 0.0025 max mem: 19788 +Test: [ 3600/21770] eta: 0:21:39 time: 0.0639 data: 0.0019 max mem: 19788 +Test: [ 3700/21770] eta: 0:21:29 time: 0.0666 data: 0.0020 max mem: 19788 +Test: [ 3800/21770] eta: 0:21:21 time: 0.0651 data: 0.0019 max mem: 19788 +Test: [ 3900/21770] eta: 0:21:15 time: 0.0840 data: 0.0026 max mem: 19788 +Test: [ 4000/21770] eta: 0:21:07 time: 0.0685 data: 0.0019 max mem: 19788 +Test: [ 4100/21770] eta: 0:20:58 time: 0.0643 data: 0.0022 max mem: 19788 +Test: [ 4200/21770] eta: 0:20:52 time: 0.0729 data: 0.0025 max mem: 19788 +Test: [ 4300/21770] eta: 0:20:46 time: 0.0814 data: 0.0025 max mem: 19788 +Test: [ 4400/21770] eta: 0:20:38 time: 0.0688 data: 0.0020 max mem: 19788 +Test: [ 4500/21770] eta: 0:20:32 time: 0.0736 data: 0.0019 max mem: 19788 +Test: [ 4600/21770] eta: 0:20:23 time: 0.0661 data: 0.0020 max mem: 19788 +Test: [ 4700/21770] eta: 0:20:19 time: 0.0651 data: 0.0018 max mem: 19788 +Test: [ 4800/21770] eta: 0:20:10 time: 0.0738 data: 0.0021 max mem: 19788 +Test: [ 4900/21770] eta: 0:20:03 time: 0.0647 data: 0.0018 max mem: 19788 +Test: [ 5000/21770] eta: 0:19:57 time: 0.0712 data: 0.0023 max mem: 19788 +Test: [ 5100/21770] eta: 0:19:49 time: 0.0716 data: 0.0021 max mem: 19788 +Test: [ 5200/21770] eta: 0:19:43 time: 0.0764 data: 0.0022 max mem: 19788 +Test: [ 5300/21770] eta: 0:19:36 time: 0.0724 data: 0.0021 max mem: 19788 +Test: [ 5400/21770] eta: 0:19:28 time: 0.0664 data: 0.0019 max mem: 19788 +Test: [ 5500/21770] eta: 0:19:20 time: 0.0734 data: 0.0022 max mem: 19788 +Test: [ 5600/21770] eta: 0:19:14 time: 0.0820 data: 0.0025 max mem: 19788 +Test: [ 5700/21770] eta: 0:19:06 time: 0.0759 data: 0.0021 max mem: 19788 +Test: [ 5800/21770] eta: 0:19:00 time: 0.0739 data: 0.0022 max mem: 19788 +Test: [ 5900/21770] eta: 0:18:52 time: 0.0655 data: 0.0020 max mem: 19788 +Test: [ 6000/21770] eta: 0:18:44 time: 0.0754 data: 0.0023 max mem: 19788 +Test: [ 6100/21770] eta: 0:18:38 time: 0.0656 data: 0.0021 max mem: 19788 +Test: [ 6200/21770] eta: 0:18:30 time: 0.0789 data: 0.0024 max mem: 19788 +Test: [ 6300/21770] eta: 0:18:25 time: 0.0833 data: 0.0024 max mem: 19788 +Test: [ 6400/21770] eta: 0:18:18 time: 0.0832 data: 0.0024 max mem: 19788 +Test: [ 6500/21770] eta: 0:18:11 time: 0.0760 data: 0.0023 max mem: 19788 +Test: [ 6600/21770] eta: 0:18:03 time: 0.0630 data: 0.0020 max mem: 19788 +Test: [ 6700/21770] eta: 0:17:56 time: 0.0791 data: 0.0024 max mem: 19788 +Test: [ 6800/21770] eta: 0:17:48 time: 0.0849 data: 0.0026 max mem: 19788 +Test: [ 6900/21770] eta: 0:17:42 time: 0.0637 data: 0.0020 max mem: 19788 +Test: [ 7000/21770] eta: 0:17:36 time: 0.0791 data: 0.0025 max mem: 19788 +Test: [ 7100/21770] eta: 0:17:28 time: 0.0773 data: 0.0023 max mem: 19788 +Test: [ 7200/21770] eta: 0:17:20 time: 0.0727 data: 0.0022 max mem: 19788 +Test: [ 7300/21770] eta: 0:17:14 time: 0.0646 data: 0.0021 max mem: 19788 +Test: [ 7400/21770] eta: 0:17:06 time: 0.0700 data: 0.0021 max mem: 19788 +Test: [ 7500/21770] eta: 0:16:58 time: 0.0717 data: 0.0022 max mem: 19788 +Test: [ 7600/21770] eta: 0:16:51 time: 0.0671 data: 0.0019 max mem: 19788 +Test: [ 7700/21770] eta: 0:16:45 time: 0.0730 data: 0.0019 max mem: 19788 +Test: [ 7800/21770] eta: 0:16:38 time: 0.0767 data: 0.0022 max mem: 19788 +Test: [ 7900/21770] eta: 0:16:31 time: 0.0830 data: 0.0025 max mem: 19788 +Test: [ 8000/21770] eta: 0:16:24 time: 0.0703 data: 0.0022 max mem: 19788 +Test: [ 8100/21770] eta: 0:16:16 time: 0.0643 data: 0.0021 max mem: 19788 +Test: [ 8200/21770] eta: 0:16:08 time: 0.0662 data: 0.0021 max mem: 19788 +Test: [ 8300/21770] eta: 0:16:01 time: 0.0744 data: 0.0023 max mem: 19788 +Test: [ 8400/21770] eta: 0:15:54 time: 0.0716 data: 0.0021 max mem: 19788 +Test: [ 8500/21770] eta: 0:15:48 time: 0.0658 data: 0.0022 max mem: 19788 +Test: [ 8600/21770] eta: 0:15:40 time: 0.0628 data: 0.0020 max mem: 19788 +Test: [ 8700/21770] eta: 0:15:32 time: 0.0712 data: 0.0021 max mem: 19788 +Test: [ 8800/21770] eta: 0:15:24 time: 0.0643 data: 0.0019 max mem: 19788 +Test: [ 8900/21770] eta: 0:15:16 time: 0.0708 data: 0.0022 max mem: 19788 +Test: [ 9000/21770] eta: 0:15:10 time: 0.0852 data: 0.0027 max mem: 19788 +Test: [ 9100/21770] eta: 0:15:03 time: 0.0641 data: 0.0019 max mem: 19788 +Test: [ 9200/21770] eta: 0:14:56 time: 0.0701 data: 0.0020 max mem: 19788 +Test: [ 9300/21770] eta: 0:14:48 time: 0.0675 data: 0.0018 max mem: 19788 +Test: [ 9400/21770] eta: 0:14:40 time: 0.0760 data: 0.0019 max mem: 19788 +Test: [ 9500/21770] eta: 0:14:33 time: 0.0650 data: 0.0022 max mem: 19788 +Test: [ 9600/21770] eta: 0:14:26 time: 0.0625 data: 0.0017 max mem: 19788 +Test: [ 9700/21770] eta: 0:14:20 time: 0.0731 data: 0.0022 max mem: 19788 +Test: [ 9800/21770] eta: 0:14:12 time: 0.0797 data: 0.0021 max mem: 19788 +Test: [ 9900/21770] eta: 0:14:05 time: 0.0644 data: 0.0019 max mem: 19788 +Test: [10000/21770] eta: 0:13:58 time: 0.0676 data: 0.0021 max mem: 19788 +Test: [10100/21770] eta: 0:13:52 time: 0.0819 data: 0.0025 max mem: 19788 +Test: [10200/21770] eta: 0:13:46 time: 0.0860 data: 0.0026 max mem: 19788 +Test: [10300/21770] eta: 0:13:39 time: 0.0647 data: 0.0020 max mem: 19788 +Test: [10400/21770] eta: 0:13:32 time: 0.0685 data: 0.0022 max mem: 19788 +Test: [10500/21770] eta: 0:13:24 time: 0.0671 data: 0.0020 max mem: 19788 +Test: [10600/21770] eta: 0:13:17 time: 0.0663 data: 0.0021 max mem: 19788 +Test: [10700/21770] eta: 0:13:09 time: 0.0650 data: 0.0020 max mem: 19788 +Test: [10800/21770] eta: 0:13:03 time: 0.0707 data: 0.0021 max mem: 19788 +Test: [10900/21770] eta: 0:12:56 time: 0.0821 data: 0.0024 max mem: 19788 +Test: [11000/21770] eta: 0:12:49 time: 0.0665 data: 0.0019 max mem: 19788 +Test: [11100/21770] eta: 0:12:41 time: 0.0664 data: 0.0018 max mem: 19788 +Test: [11200/21770] eta: 0:12:34 time: 0.0682 data: 0.0020 max mem: 19788 +Test: [11300/21770] eta: 0:12:27 time: 0.0661 data: 0.0021 max mem: 19788 +Test: [11400/21770] eta: 0:12:19 time: 0.0710 data: 0.0021 max mem: 19788 +Test: [11500/21770] eta: 0:12:12 time: 0.0625 data: 0.0019 max mem: 19788 +Test: [11600/21770] eta: 0:12:04 time: 0.0730 data: 0.0021 max mem: 19788 +Test: [11700/21770] eta: 0:11:58 time: 0.0853 data: 0.0022 max mem: 19788 +Test: [11800/21770] eta: 0:11:51 time: 0.0717 data: 0.0022 max mem: 19788 +Test: [11900/21770] eta: 0:11:45 time: 0.0724 data: 0.0019 max mem: 19788 +Test: [12000/21770] eta: 0:11:38 time: 0.0691 data: 0.0021 max mem: 19788 +Test: [12100/21770] eta: 0:11:30 time: 0.0703 data: 0.0020 max mem: 19788 +Test: [12200/21770] eta: 0:11:23 time: 0.0661 data: 0.0019 max mem: 19788 +Test: [12300/21770] eta: 0:11:16 time: 0.0830 data: 0.0044 max mem: 19788 +Test: [12400/21770] eta: 0:11:09 time: 0.0859 data: 0.0023 max mem: 19788 +Test: [12500/21770] eta: 0:11:02 time: 0.0633 data: 0.0018 max mem: 19788 +Test: [12600/21770] eta: 0:10:54 time: 0.0673 data: 0.0019 max mem: 19788 +Test: [12700/21770] eta: 0:10:47 time: 0.0656 data: 0.0019 max mem: 19788 +Test: [12800/21770] eta: 0:10:41 time: 0.0664 data: 0.0020 max mem: 19788 +Test: [12900/21770] eta: 0:10:33 time: 0.0673 data: 0.0020 max mem: 19788 +Test: [13000/21770] eta: 0:10:26 time: 0.0857 data: 0.0026 max mem: 19788 +Test: [13100/21770] eta: 0:10:19 time: 0.0650 data: 0.0018 max mem: 19788 +Test: [13200/21770] eta: 0:10:12 time: 0.0660 data: 0.0020 max mem: 19788 +Test: [13300/21770] eta: 0:10:05 time: 0.0675 data: 0.0021 max mem: 19788 +Test: [13400/21770] eta: 0:09:58 time: 0.0633 data: 0.0019 max mem: 19788 +Test: [13500/21770] eta: 0:09:51 time: 0.0772 data: 0.0020 max mem: 19788 +Test: [13600/21770] eta: 0:09:43 time: 0.0792 data: 0.0024 max mem: 19788 +Test: [13700/21770] eta: 0:09:36 time: 0.0669 data: 0.0019 max mem: 19788 +Test: [13800/21770] eta: 0:09:29 time: 0.0646 data: 0.0020 max mem: 19788 +Test: [13900/21770] eta: 0:09:22 time: 0.0794 data: 0.0024 max mem: 19788 +Test: [14000/21770] eta: 0:09:15 time: 0.0811 data: 0.0020 max mem: 19788 +Test: [14100/21770] eta: 0:09:08 time: 0.0730 data: 0.0021 max mem: 19788 +Test: [14200/21770] eta: 0:09:01 time: 0.0664 data: 0.0019 max mem: 19788 +Test: [14300/21770] eta: 0:08:54 time: 0.0776 data: 0.0022 max mem: 19788 +Test: [14400/21770] eta: 0:08:47 time: 0.0805 data: 0.0024 max mem: 19788 +Test: [14500/21770] eta: 0:08:40 time: 0.0802 data: 0.0022 max mem: 19788 +Test: [14600/21770] eta: 0:08:33 time: 0.0695 data: 0.0022 max mem: 19788 +Test: [14700/21770] eta: 0:08:26 time: 0.0667 data: 0.0019 max mem: 19788 +Test: [14800/21770] eta: 0:08:19 time: 0.0826 data: 0.0026 max mem: 19788 +Test: [14900/21770] eta: 0:08:11 time: 0.0683 data: 0.0019 max mem: 19788 +Test: [15000/21770] eta: 0:08:04 time: 0.0798 data: 0.0024 max mem: 19788 +Test: [15100/21770] eta: 0:07:57 time: 0.0704 data: 0.0021 max mem: 19788 +Test: [15200/21770] eta: 0:07:50 time: 0.0651 data: 0.0018 max mem: 19788 +Test: [15300/21770] eta: 0:07:42 time: 0.0668 data: 0.0021 max mem: 19788 +Test: [15400/21770] eta: 0:07:35 time: 0.0635 data: 0.0020 max mem: 19788 +Test: [15500/21770] eta: 0:07:28 time: 0.0666 data: 0.0020 max mem: 19788 +Test: [15600/21770] eta: 0:07:21 time: 0.0810 data: 0.0025 max mem: 19788 +Test: [15700/21770] eta: 0:07:14 time: 0.0663 data: 0.0023 max mem: 19788 +Test: [15800/21770] eta: 0:07:07 time: 0.0792 data: 0.0019 max mem: 19788 +Test: [15900/21770] eta: 0:07:00 time: 0.0843 data: 0.0022 max mem: 19788 +Test: [16000/21770] eta: 0:06:53 time: 0.0771 data: 0.0021 max mem: 19788 +Test: [16100/21770] eta: 0:06:46 time: 0.0647 data: 0.0021 max mem: 19788 +Test: [16200/21770] eta: 0:06:39 time: 0.0701 data: 0.0022 max mem: 19788 +Test: [16300/21770] eta: 0:06:32 time: 0.0723 data: 0.0021 max mem: 19788 +Test: [16400/21770] eta: 0:06:24 time: 0.0642 data: 0.0018 max mem: 19788 +Test: [16500/21770] eta: 0:06:17 time: 0.0646 data: 0.0020 max mem: 19788 +Test: [16600/21770] eta: 0:06:10 time: 0.0663 data: 0.0021 max mem: 19788 +Test: [16700/21770] eta: 0:06:03 time: 0.0627 data: 0.0019 max mem: 19788 +Test: [16800/21770] eta: 0:05:56 time: 0.0792 data: 0.0020 max mem: 19788 +Test: [16900/21770] eta: 0:05:48 time: 0.0666 data: 0.0021 max mem: 19788 +Test: [17000/21770] eta: 0:05:41 time: 0.0683 data: 0.0020 max mem: 19788 +Test: [17100/21770] eta: 0:05:34 time: 0.0703 data: 0.0020 max mem: 19788 +Test: [17200/21770] eta: 0:05:27 time: 0.0783 data: 0.0020 max mem: 19788 +Test: [17300/21770] eta: 0:05:20 time: 0.0636 data: 0.0022 max mem: 19788 +Test: [17400/21770] eta: 0:05:13 time: 0.0648 data: 0.0020 max mem: 19788 +Test: [17500/21770] eta: 0:05:05 time: 0.0689 data: 0.0024 max mem: 19788 +Test: [17600/21770] eta: 0:04:58 time: 0.0732 data: 0.0021 max mem: 19788 +Test: [17700/21770] eta: 0:04:51 time: 0.0662 data: 0.0020 max mem: 19788 +Test: [17800/21770] eta: 0:04:44 time: 0.0629 data: 0.0019 max mem: 19788 +Test: [17900/21770] eta: 0:04:37 time: 0.0761 data: 0.0023 max mem: 19788 +Test: [18000/21770] eta: 0:04:29 time: 0.0829 data: 0.0024 max mem: 19788 +Test: [18100/21770] eta: 0:04:22 time: 0.0650 data: 0.0020 max mem: 19788 +Test: [18200/21770] eta: 0:04:15 time: 0.0653 data: 0.0021 max mem: 19788 +Test: [18300/21770] eta: 0:04:08 time: 0.0782 data: 0.0024 max mem: 19788 +Test: [18400/21770] eta: 0:04:01 time: 0.0823 data: 0.0020 max mem: 19788 +Test: [18500/21770] eta: 0:03:54 time: 0.0714 data: 0.0021 max mem: 19788 +Test: [18600/21770] eta: 0:03:46 time: 0.0638 data: 0.0020 max mem: 19788 +Test: [18700/21770] eta: 0:03:39 time: 0.0666 data: 0.0020 max mem: 19788 +Test: [18800/21770] eta: 0:03:32 time: 0.0662 data: 0.0019 max mem: 19788 +Test: [18900/21770] eta: 0:03:25 time: 0.0701 data: 0.0022 max mem: 19788 +Test: [19000/21770] eta: 0:03:18 time: 0.0739 data: 0.0023 max mem: 19788 +Test: [19100/21770] eta: 0:03:11 time: 0.0762 data: 0.0023 max mem: 19788 +Test: [19200/21770] eta: 0:03:03 time: 0.0664 data: 0.0021 max mem: 19788 +Test: [19300/21770] eta: 0:02:56 time: 0.0631 data: 0.0020 max mem: 19788 +Test: [19400/21770] eta: 0:02:49 time: 0.0675 data: 0.0022 max mem: 19788 +Test: [19500/21770] eta: 0:02:42 time: 0.0656 data: 0.0019 max mem: 19788 +Test: [19600/21770] eta: 0:02:35 time: 0.0669 data: 0.0020 max mem: 19788 +Test: [19700/21770] eta: 0:02:27 time: 0.0628 data: 0.0020 max mem: 19788 +Test: [19800/21770] eta: 0:02:20 time: 0.0671 data: 0.0020 max mem: 19788 +Test: [19900/21770] eta: 0:02:13 time: 0.0690 data: 0.0019 max mem: 19788 +Test: [20000/21770] eta: 0:02:06 time: 0.0645 data: 0.0017 max mem: 19788 +Test: [20100/21770] eta: 0:01:59 time: 0.0650 data: 0.0020 max mem: 19788 +Test: [20200/21770] eta: 0:01:51 time: 0.0651 data: 0.0021 max mem: 19788 +Test: [20300/21770] eta: 0:01:44 time: 0.0724 data: 0.0022 max mem: 19788 +Test: [20400/21770] eta: 0:01:37 time: 0.0680 data: 0.0021 max mem: 19788 +Test: [20500/21770] eta: 0:01:30 time: 0.0678 data: 0.0021 max mem: 19788 +Test: [20600/21770] eta: 0:01:23 time: 0.0741 data: 0.0022 max mem: 19788 +Test: [20700/21770] eta: 0:01:16 time: 0.0744 data: 0.0023 max mem: 19788 +Test: [20800/21770] eta: 0:01:09 time: 0.0776 data: 0.0019 max mem: 19788 +Test: [20900/21770] eta: 0:01:02 time: 0.0822 data: 0.0021 max mem: 19788 +Test: [21000/21770] eta: 0:00:54 time: 0.0634 data: 0.0019 max mem: 19788 +Test: [21100/21770] eta: 0:00:47 time: 0.0629 data: 0.0020 max mem: 19788 +Test: [21200/21770] eta: 0:00:40 time: 0.0756 data: 0.0021 max mem: 19788 +Test: [21300/21770] eta: 0:00:33 time: 0.0677 data: 0.0023 max mem: 19788 +Test: [21400/21770] eta: 0:00:26 time: 0.0780 data: 0.0024 max mem: 19788 +Test: [21500/21770] eta: 0:00:19 time: 0.0717 data: 0.0024 max mem: 19788 +Test: [21600/21770] eta: 0:00:12 time: 0.0795 data: 0.0026 max mem: 19788 +Test: [21700/21770] eta: 0:00:04 time: 0.0722 data: 0.0020 max mem: 19788 +Test: Total time: 0:25:55 +Final results: +Mean IoU is 62.64 + + precision@0.5 = 69.38 + precision@0.6 = 64.43 + precision@0.7 = 57.89 + precision@0.8 = 47.60 + precision@0.9 = 23.76 + overall IoU = 63.81 + mean IoU = 62.64 + +Mean accuracy for one-to-zero sample is 87.67 + +Average object IoU 0.6264240176736526 +Overall IoU 63.81306838989258 +Epoch: [37] [ 0/2138] eta: 10:35:19 lr: 4.858074798974034e-06 loss: 0.0189 (0.0189) time: 17.8294 data: 1.8790 max mem: 19788 +Epoch: [37] [ 10/2138] eta: 3:08:44 lr: 4.85125644811626e-06 loss: 0.0164 (0.0166) time: 5.3215 data: 0.1729 max mem: 19788 +Epoch: [37] [ 20/2138] eta: 2:46:34 lr: 4.844437032306703e-06 loss: 0.0154 (0.0163) time: 4.0634 data: 0.0022 max mem: 19788 +Epoch: [37] [ 30/2138] eta: 2:38:20 lr: 4.83761654971284e-06 loss: 0.0165 (0.0172) time: 4.0591 data: 0.0027 max mem: 19788 +Epoch: [37] [ 40/2138] eta: 2:33:45 lr: 4.830794998496095e-06 loss: 0.0194 (0.0182) time: 4.0600 data: 0.0034 max mem: 19788 +Epoch: [37] [ 50/2138] eta: 2:30:44 lr: 4.8239723768118545e-06 loss: 0.0205 (0.0186) time: 4.0601 data: 0.0035 max mem: 19788 +Epoch: [37] [ 60/2138] eta: 2:28:26 lr: 4.817148682809398e-06 loss: 0.0170 (0.0183) time: 4.0580 data: 0.0036 max mem: 19788 +Epoch: [37] [ 70/2138] eta: 2:26:34 lr: 4.8103239146319065e-06 loss: 0.0152 (0.0179) time: 4.0511 data: 0.0033 max mem: 19788 +Epoch: [37] [ 80/2138] eta: 2:25:02 lr: 4.803498070416389e-06 loss: 0.0166 (0.0182) time: 4.0532 data: 0.0032 max mem: 19788 +Epoch: [37] [ 90/2138] eta: 2:23:40 lr: 4.796671148293705e-06 loss: 0.0170 (0.0180) time: 4.0559 data: 0.0034 max mem: 19788 +Epoch: [37] [ 100/2138] eta: 2:22:26 lr: 4.789843146388477e-06 loss: 0.0165 (0.0182) time: 4.0519 data: 0.0036 max mem: 19788 +Epoch: [37] [ 110/2138] eta: 2:21:18 lr: 4.783014062819114e-06 loss: 0.0195 (0.0183) time: 4.0501 data: 0.0033 max mem: 19788 +Epoch: [37] [ 120/2138] eta: 2:20:15 lr: 4.776183895697731e-06 loss: 0.0193 (0.0185) time: 4.0526 data: 0.0031 max mem: 19788 +Epoch: [37] [ 130/2138] eta: 2:19:16 lr: 4.769352643130169e-06 loss: 0.0210 (0.0186) time: 4.0550 data: 0.0032 max mem: 19788 +Epoch: [37] [ 140/2138] eta: 2:18:18 lr: 4.762520303215911e-06 loss: 0.0214 (0.0187) time: 4.0523 data: 0.0033 max mem: 19788 +Epoch: [37] [ 150/2138] eta: 2:17:24 lr: 4.7556868740481e-06 loss: 0.0176 (0.0186) time: 4.0513 data: 0.0032 max mem: 19788 +Epoch: [37] [ 160/2138] eta: 2:16:29 lr: 4.748852353713465e-06 loss: 0.0190 (0.0189) time: 4.0453 data: 0.0030 max mem: 19788 +Epoch: [37] [ 170/2138] eta: 2:15:36 lr: 4.74201674029233e-06 loss: 0.0218 (0.0191) time: 4.0381 data: 0.0031 max mem: 19788 +Epoch: [37] [ 180/2138] eta: 2:14:44 lr: 4.7351800318585374e-06 loss: 0.0209 (0.0191) time: 4.0406 data: 0.0032 max mem: 19788 +Epoch: [37] [ 190/2138] eta: 2:13:55 lr: 4.7283422264794645e-06 loss: 0.0165 (0.0191) time: 4.0474 data: 0.0032 max mem: 19788 +Epoch: [37] [ 200/2138] eta: 2:13:10 lr: 4.721503322215941e-06 loss: 0.0140 (0.0189) time: 4.0653 data: 0.0033 max mem: 19788 +Epoch: [37] [ 210/2138] eta: 2:12:22 lr: 4.714663317122268e-06 loss: 0.0217 (0.0191) time: 4.0656 data: 0.0033 max mem: 19788 +Epoch: [37] [ 220/2138] eta: 2:11:35 lr: 4.7078222092461305e-06 loss: 0.0217 (0.0191) time: 4.0505 data: 0.0035 max mem: 19788 +Epoch: [37] [ 230/2138] eta: 2:10:54 lr: 4.7009799966286215e-06 loss: 0.0198 (0.0192) time: 4.0888 data: 0.0036 max mem: 19788 +Epoch: [37] [ 240/2138] eta: 2:10:08 lr: 4.694136677304153e-06 loss: 0.0196 (0.0192) time: 4.0882 data: 0.0033 max mem: 19788 +Epoch: [37] [ 250/2138] eta: 2:09:20 lr: 4.687292249300477e-06 loss: 0.0170 (0.0191) time: 4.0368 data: 0.0032 max mem: 19788 +Epoch: [37] [ 260/2138] eta: 2:08:33 lr: 4.680446710638597e-06 loss: 0.0171 (0.0191) time: 4.0284 data: 0.0031 max mem: 19788 +Epoch: [37] [ 270/2138] eta: 2:07:48 lr: 4.673600059332787e-06 loss: 0.0184 (0.0192) time: 4.0391 data: 0.0033 max mem: 19788 +Epoch: [37] [ 280/2138] eta: 2:07:03 lr: 4.6667522933905165e-06 loss: 0.0193 (0.0192) time: 4.0493 data: 0.0034 max mem: 19788 +Epoch: [37] [ 290/2138] eta: 2:06:18 lr: 4.659903410812429e-06 loss: 0.0193 (0.0192) time: 4.0442 data: 0.0034 max mem: 19788 +Epoch: [37] [ 300/2138] eta: 2:05:33 lr: 4.653053409592328e-06 loss: 0.0191 (0.0192) time: 4.0354 data: 0.0035 max mem: 19788 +Epoch: [37] [ 310/2138] eta: 2:04:48 lr: 4.6462022877171015e-06 loss: 0.0180 (0.0191) time: 4.0314 data: 0.0035 max mem: 19788 +Epoch: [37] [ 320/2138] eta: 2:04:03 lr: 4.639350043166736e-06 loss: 0.0180 (0.0191) time: 4.0249 data: 0.0035 max mem: 19788 +Epoch: [37] [ 330/2138] eta: 2:03:18 lr: 4.6324966739142274e-06 loss: 0.0199 (0.0192) time: 4.0256 data: 0.0035 max mem: 19788 +Epoch: [37] [ 340/2138] eta: 2:02:35 lr: 4.6256421779256006e-06 loss: 0.0194 (0.0192) time: 4.0436 data: 0.0034 max mem: 19788 +Epoch: [37] [ 350/2138] eta: 2:01:52 lr: 4.61878655315982e-06 loss: 0.0183 (0.0192) time: 4.0528 data: 0.0034 max mem: 19788 +Epoch: [37] [ 360/2138] eta: 2:01:09 lr: 4.6119297975688074e-06 loss: 0.0198 (0.0192) time: 4.0488 data: 0.0032 max mem: 19788 +Epoch: [37] [ 370/2138] eta: 2:00:26 lr: 4.60507190909735e-06 loss: 0.0188 (0.0193) time: 4.0391 data: 0.0033 max mem: 19788 +Epoch: [37] [ 380/2138] eta: 1:59:42 lr: 4.59821288568312e-06 loss: 0.0180 (0.0193) time: 4.0307 data: 0.0035 max mem: 19788 +Epoch: [37] [ 390/2138] eta: 1:58:59 lr: 4.591352725256583e-06 loss: 0.0174 (0.0193) time: 4.0290 data: 0.0035 max mem: 19788 +Epoch: [37] [ 400/2138] eta: 1:58:15 lr: 4.584491425741017e-06 loss: 0.0194 (0.0193) time: 4.0207 data: 0.0033 max mem: 19788 +Epoch: [37] [ 410/2138] eta: 1:57:32 lr: 4.577628985052418e-06 loss: 0.0197 (0.0194) time: 4.0256 data: 0.0032 max mem: 19788 +Epoch: [37] [ 420/2138] eta: 1:56:49 lr: 4.570765401099518e-06 loss: 0.0204 (0.0194) time: 4.0353 data: 0.0030 max mem: 19788 +Epoch: [37] [ 430/2138] eta: 1:56:07 lr: 4.563900671783695e-06 loss: 0.0181 (0.0194) time: 4.0326 data: 0.0030 max mem: 19788 +Epoch: [37] [ 440/2138] eta: 1:55:24 lr: 4.557034794998985e-06 loss: 0.0199 (0.0195) time: 4.0355 data: 0.0031 max mem: 19788 +Epoch: [37] [ 450/2138] eta: 1:54:42 lr: 4.5501677686319925e-06 loss: 0.0199 (0.0195) time: 4.0413 data: 0.0034 max mem: 19788 +Epoch: [37] [ 460/2138] eta: 1:54:01 lr: 4.543299590561908e-06 loss: 0.0203 (0.0195) time: 4.0477 data: 0.0037 max mem: 19788 +Epoch: [37] [ 470/2138] eta: 1:53:19 lr: 4.536430258660409e-06 loss: 0.0203 (0.0195) time: 4.0536 data: 0.0036 max mem: 19788 +Epoch: [37] [ 480/2138] eta: 1:52:37 lr: 4.529559770791685e-06 loss: 0.0200 (0.0196) time: 4.0529 data: 0.0031 max mem: 19788 +Epoch: [37] [ 490/2138] eta: 1:51:56 lr: 4.52268812481233e-06 loss: 0.0200 (0.0196) time: 4.0577 data: 0.0030 max mem: 19788 +Epoch: [37] [ 500/2138] eta: 1:51:14 lr: 4.515815318571371e-06 loss: 0.0176 (0.0196) time: 4.0507 data: 0.0031 max mem: 19788 +Epoch: [37] [ 510/2138] eta: 1:50:33 lr: 4.508941349910166e-06 loss: 0.0193 (0.0196) time: 4.0452 data: 0.0031 max mem: 19788 +Epoch: [37] [ 520/2138] eta: 1:49:51 lr: 4.5020662166624195e-06 loss: 0.0194 (0.0196) time: 4.0457 data: 0.0032 max mem: 19788 +Epoch: [37] [ 530/2138] eta: 1:49:10 lr: 4.4951899166540916e-06 loss: 0.0171 (0.0196) time: 4.0472 data: 0.0032 max mem: 19788 +Epoch: [37] [ 540/2138] eta: 1:48:28 lr: 4.488312447703403e-06 loss: 0.0164 (0.0195) time: 4.0470 data: 0.0033 max mem: 19788 +Epoch: [37] [ 550/2138] eta: 1:47:46 lr: 4.481433807620749e-06 loss: 0.0179 (0.0195) time: 4.0437 data: 0.0033 max mem: 19788 +Epoch: [37] [ 560/2138] eta: 1:47:05 lr: 4.47455399420871e-06 loss: 0.0192 (0.0195) time: 4.0501 data: 0.0032 max mem: 19788 +Epoch: [37] [ 570/2138] eta: 1:46:24 lr: 4.46767300526195e-06 loss: 0.0190 (0.0196) time: 4.0463 data: 0.0032 max mem: 19788 +Epoch: [37] [ 580/2138] eta: 1:45:42 lr: 4.4607908385672365e-06 loss: 0.0190 (0.0196) time: 4.0434 data: 0.0033 max mem: 19788 +Epoch: [37] [ 590/2138] eta: 1:45:01 lr: 4.453907491903347e-06 loss: 0.0186 (0.0195) time: 4.0424 data: 0.0034 max mem: 19788 +Epoch: [37] [ 600/2138] eta: 1:44:19 lr: 4.447022963041049e-06 loss: 0.0181 (0.0195) time: 4.0430 data: 0.0033 max mem: 19788 +Epoch: [37] [ 610/2138] eta: 1:43:38 lr: 4.440137249743074e-06 loss: 0.0187 (0.0196) time: 4.0441 data: 0.0032 max mem: 19788 +Epoch: [37] [ 620/2138] eta: 1:42:57 lr: 4.43325034976403e-06 loss: 0.0198 (0.0196) time: 4.0449 data: 0.0034 max mem: 19788 +Epoch: [37] [ 630/2138] eta: 1:42:15 lr: 4.426362260850413e-06 loss: 0.0185 (0.0196) time: 4.0404 data: 0.0034 max mem: 19788 +Epoch: [37] [ 640/2138] eta: 1:41:34 lr: 4.419472980740508e-06 loss: 0.0185 (0.0196) time: 4.0357 data: 0.0033 max mem: 19788 +Epoch: [37] [ 650/2138] eta: 1:40:53 lr: 4.4125825071643965e-06 loss: 0.0185 (0.0195) time: 4.0425 data: 0.0033 max mem: 19788 +Epoch: [37] [ 660/2138] eta: 1:40:11 lr: 4.405690837843864e-06 loss: 0.0185 (0.0195) time: 4.0491 data: 0.0032 max mem: 19788 +Epoch: [37] [ 670/2138] eta: 1:39:30 lr: 4.398797970492404e-06 loss: 0.0199 (0.0195) time: 4.0502 data: 0.0031 max mem: 19788 +Epoch: [37] [ 680/2138] eta: 1:38:49 lr: 4.391903902815123e-06 loss: 0.0199 (0.0196) time: 4.0429 data: 0.0032 max mem: 19788 +Epoch: [37] [ 690/2138] eta: 1:38:08 lr: 4.385008632508745e-06 loss: 0.0189 (0.0195) time: 4.0428 data: 0.0034 max mem: 19788 +Epoch: [37] [ 700/2138] eta: 1:37:27 lr: 4.3781121572615185e-06 loss: 0.0189 (0.0195) time: 4.0499 data: 0.0035 max mem: 19788 +Epoch: [37] [ 710/2138] eta: 1:36:46 lr: 4.371214474753217e-06 loss: 0.0207 (0.0195) time: 4.0431 data: 0.0033 max mem: 19788 +Epoch: [37] [ 720/2138] eta: 1:36:05 lr: 4.3643155826550435e-06 loss: 0.0174 (0.0195) time: 4.0410 data: 0.0033 max mem: 19788 +Epoch: [37] [ 730/2138] eta: 1:35:24 lr: 4.357415478629639e-06 loss: 0.0177 (0.0196) time: 4.0462 data: 0.0035 max mem: 19788 +Epoch: [37] [ 740/2138] eta: 1:34:43 lr: 4.350514160330977e-06 loss: 0.0181 (0.0195) time: 4.0450 data: 0.0032 max mem: 19788 +Epoch: [37] [ 750/2138] eta: 1:34:01 lr: 4.343611625404374e-06 loss: 0.0171 (0.0195) time: 4.0405 data: 0.0031 max mem: 19788 +Epoch: [37] [ 760/2138] eta: 1:33:20 lr: 4.336707871486386e-06 loss: 0.0194 (0.0196) time: 4.0394 data: 0.0032 max mem: 19788 +Epoch: [37] [ 770/2138] eta: 1:32:39 lr: 4.329802896204818e-06 loss: 0.0206 (0.0196) time: 4.0442 data: 0.0034 max mem: 19788 +Epoch: [37] [ 780/2138] eta: 1:31:58 lr: 4.3228966971786155e-06 loss: 0.0207 (0.0197) time: 4.0396 data: 0.0035 max mem: 19788 +Epoch: [37] [ 790/2138] eta: 1:31:17 lr: 4.315989272017876e-06 loss: 0.0187 (0.0197) time: 4.0402 data: 0.0033 max mem: 19788 +Epoch: [37] [ 800/2138] eta: 1:30:36 lr: 4.309080618323743e-06 loss: 0.0171 (0.0196) time: 4.0439 data: 0.0033 max mem: 19788 +Epoch: [37] [ 810/2138] eta: 1:29:56 lr: 4.302170733688411e-06 loss: 0.0174 (0.0196) time: 4.0481 data: 0.0032 max mem: 19788 +Epoch: [37] [ 820/2138] eta: 1:29:15 lr: 4.295259615695025e-06 loss: 0.0174 (0.0197) time: 4.0479 data: 0.0031 max mem: 19788 +Epoch: [37] [ 830/2138] eta: 1:28:34 lr: 4.288347261917677e-06 loss: 0.0162 (0.0196) time: 4.0430 data: 0.0032 max mem: 19788 +Epoch: [37] [ 840/2138] eta: 1:27:53 lr: 4.281433669921309e-06 loss: 0.0162 (0.0196) time: 4.0449 data: 0.0033 max mem: 19788 +Epoch: [37] [ 850/2138] eta: 1:27:12 lr: 4.274518837261713e-06 loss: 0.0168 (0.0196) time: 4.0423 data: 0.0032 max mem: 19788 +Epoch: [37] [ 860/2138] eta: 1:26:31 lr: 4.2676027614854276e-06 loss: 0.0173 (0.0196) time: 4.0431 data: 0.0033 max mem: 19788 +Epoch: [37] [ 870/2138] eta: 1:25:50 lr: 4.260685440129737e-06 loss: 0.0211 (0.0196) time: 4.0453 data: 0.0037 max mem: 19788 +Epoch: [37] [ 880/2138] eta: 1:25:09 lr: 4.253766870722568e-06 loss: 0.0190 (0.0196) time: 4.0492 data: 0.0036 max mem: 19788 +Epoch: [37] [ 890/2138] eta: 1:24:28 lr: 4.246847050782493e-06 loss: 0.0188 (0.0196) time: 4.0505 data: 0.0035 max mem: 19788 +Epoch: [37] [ 900/2138] eta: 1:23:47 lr: 4.239925977818626e-06 loss: 0.0196 (0.0196) time: 4.0403 data: 0.0036 max mem: 19788 +Epoch: [37] [ 910/2138] eta: 1:23:07 lr: 4.233003649330593e-06 loss: 0.0193 (0.0196) time: 4.0426 data: 0.0033 max mem: 19788 +Epoch: [37] [ 920/2138] eta: 1:22:26 lr: 4.226080062808496e-06 loss: 0.0181 (0.0196) time: 4.0495 data: 0.0036 max mem: 19788 +Epoch: [37] [ 930/2138] eta: 1:21:45 lr: 4.219155215732816e-06 loss: 0.0178 (0.0196) time: 4.0504 data: 0.0038 max mem: 19788 +Epoch: [37] [ 940/2138] eta: 1:21:04 lr: 4.212229105574409e-06 loss: 0.0196 (0.0196) time: 4.0404 data: 0.0037 max mem: 19788 +Epoch: [37] [ 950/2138] eta: 1:20:23 lr: 4.205301729794399e-06 loss: 0.0198 (0.0196) time: 4.0369 data: 0.0035 max mem: 19788 +Epoch: [37] [ 960/2138] eta: 1:19:43 lr: 4.198373085844177e-06 loss: 0.0197 (0.0196) time: 4.0514 data: 0.0032 max mem: 19788 +Epoch: [37] [ 970/2138] eta: 1:19:02 lr: 4.191443171165289e-06 loss: 0.0191 (0.0196) time: 4.0527 data: 0.0032 max mem: 19788 +Epoch: [37] [ 980/2138] eta: 1:18:21 lr: 4.184511983189439e-06 loss: 0.0170 (0.0196) time: 4.0539 data: 0.0032 max mem: 19788 +Epoch: [37] [ 990/2138] eta: 1:17:40 lr: 4.177579519338376e-06 loss: 0.0195 (0.0196) time: 4.0485 data: 0.0033 max mem: 19788 +Epoch: [37] [1000/2138] eta: 1:17:00 lr: 4.170645777023887e-06 loss: 0.0195 (0.0196) time: 4.0417 data: 0.0034 max mem: 19788 +Epoch: [37] [1010/2138] eta: 1:16:19 lr: 4.163710753647694e-06 loss: 0.0181 (0.0196) time: 4.0425 data: 0.0034 max mem: 19788 +Epoch: [37] [1020/2138] eta: 1:15:38 lr: 4.1567744466014455e-06 loss: 0.0181 (0.0196) time: 4.0459 data: 0.0033 max mem: 19788 +Epoch: [37] [1030/2138] eta: 1:14:57 lr: 4.149836853266604e-06 loss: 0.0173 (0.0196) time: 4.0492 data: 0.0033 max mem: 19788 +Epoch: [37] [1040/2138] eta: 1:14:17 lr: 4.142897971014443e-06 loss: 0.0174 (0.0196) time: 4.0455 data: 0.0032 max mem: 19788 +Epoch: [37] [1050/2138] eta: 1:13:36 lr: 4.135957797205936e-06 loss: 0.0209 (0.0197) time: 4.0467 data: 0.0030 max mem: 19788 +Epoch: [37] [1060/2138] eta: 1:12:55 lr: 4.1290163291917446e-06 loss: 0.0208 (0.0196) time: 4.0401 data: 0.0032 max mem: 19788 +Epoch: [37] [1070/2138] eta: 1:12:14 lr: 4.122073564312114e-06 loss: 0.0169 (0.0196) time: 4.0372 data: 0.0033 max mem: 19788 +Epoch: [37] [1080/2138] eta: 1:11:34 lr: 4.1151294998968564e-06 loss: 0.0172 (0.0196) time: 4.0399 data: 0.0031 max mem: 19788 +Epoch: [37] [1090/2138] eta: 1:10:53 lr: 4.108184133265247e-06 loss: 0.0181 (0.0196) time: 4.0426 data: 0.0033 max mem: 19788 +Epoch: [37] [1100/2138] eta: 1:10:12 lr: 4.101237461726006e-06 loss: 0.0215 (0.0197) time: 4.0467 data: 0.0033 max mem: 19788 +Epoch: [37] [1110/2138] eta: 1:09:31 lr: 4.094289482577191e-06 loss: 0.0215 (0.0197) time: 4.0357 data: 0.0032 max mem: 19788 +Epoch: [37] [1120/2138] eta: 1:08:51 lr: 4.087340193106186e-06 loss: 0.0177 (0.0197) time: 4.0409 data: 0.0031 max mem: 19788 +Epoch: [37] [1130/2138] eta: 1:08:10 lr: 4.080389590589583e-06 loss: 0.0199 (0.0197) time: 4.0457 data: 0.0033 max mem: 19788 +Epoch: [37] [1140/2138] eta: 1:07:29 lr: 4.073437672293174e-06 loss: 0.0190 (0.0197) time: 4.0388 data: 0.0034 max mem: 19788 +Epoch: [37] [1150/2138] eta: 1:06:48 lr: 4.066484435471837e-06 loss: 0.0180 (0.0197) time: 4.0413 data: 0.0031 max mem: 19788 +Epoch: [37] [1160/2138] eta: 1:06:08 lr: 4.0595298773695195e-06 loss: 0.0173 (0.0196) time: 4.0436 data: 0.0030 max mem: 19788 +Epoch: [37] [1170/2138] eta: 1:05:27 lr: 4.052573995219125e-06 loss: 0.0185 (0.0196) time: 4.0352 data: 0.0030 max mem: 19788 +Epoch: [37] [1180/2138] eta: 1:04:46 lr: 4.0456167862424975e-06 loss: 0.0187 (0.0196) time: 4.0343 data: 0.0031 max mem: 19788 +Epoch: [37] [1190/2138] eta: 1:04:06 lr: 4.038658247650307e-06 loss: 0.0179 (0.0196) time: 4.0483 data: 0.0032 max mem: 19788 +Epoch: [37] [1200/2138] eta: 1:03:25 lr: 4.031698376642031e-06 loss: 0.0179 (0.0196) time: 4.0507 data: 0.0033 max mem: 19788 +Epoch: [37] [1210/2138] eta: 1:02:44 lr: 4.024737170405848e-06 loss: 0.0192 (0.0196) time: 4.0477 data: 0.0033 max mem: 19788 +Epoch: [37] [1220/2138] eta: 1:02:04 lr: 4.017774626118584e-06 loss: 0.0190 (0.0196) time: 4.0431 data: 0.0033 max mem: 19788 +Epoch: [37] [1230/2138] eta: 1:01:23 lr: 4.010810740945667e-06 loss: 0.0173 (0.0196) time: 4.0407 data: 0.0033 max mem: 19788 +Epoch: [37] [1240/2138] eta: 1:00:42 lr: 4.003845512041015e-06 loss: 0.0182 (0.0197) time: 4.0385 data: 0.0032 max mem: 19788 +Epoch: [37] [1250/2138] eta: 1:00:02 lr: 3.9968789365470135e-06 loss: 0.0187 (0.0197) time: 4.0413 data: 0.0033 max mem: 19788 +Epoch: [37] [1260/2138] eta: 0:59:21 lr: 3.989911011594401e-06 loss: 0.0184 (0.0196) time: 4.0431 data: 0.0033 max mem: 19788 +Epoch: [37] [1270/2138] eta: 0:58:40 lr: 3.982941734302247e-06 loss: 0.0163 (0.0196) time: 4.0391 data: 0.0034 max mem: 19788 +Epoch: [37] [1280/2138] eta: 0:58:00 lr: 3.975971101777829e-06 loss: 0.0184 (0.0196) time: 4.0413 data: 0.0035 max mem: 19788 +Epoch: [37] [1290/2138] eta: 0:57:19 lr: 3.968999111116617e-06 loss: 0.0166 (0.0196) time: 4.0383 data: 0.0034 max mem: 19788 +Epoch: [37] [1300/2138] eta: 0:56:38 lr: 3.962025759402145e-06 loss: 0.0199 (0.0196) time: 4.0413 data: 0.0032 max mem: 19788 +Epoch: [37] [1310/2138] eta: 0:55:58 lr: 3.955051043705995e-06 loss: 0.0199 (0.0196) time: 4.0424 data: 0.0033 max mem: 19788 +Epoch: [37] [1320/2138] eta: 0:55:17 lr: 3.948074961087671e-06 loss: 0.0201 (0.0196) time: 4.0395 data: 0.0034 max mem: 19788 +Epoch: [37] [1330/2138] eta: 0:54:36 lr: 3.941097508594577e-06 loss: 0.0181 (0.0196) time: 4.0433 data: 0.0035 max mem: 19788 +Epoch: [37] [1340/2138] eta: 0:53:56 lr: 3.9341186832618885e-06 loss: 0.0179 (0.0196) time: 4.0430 data: 0.0035 max mem: 19788 +Epoch: [37] [1350/2138] eta: 0:53:15 lr: 3.927138482112538e-06 loss: 0.0205 (0.0197) time: 4.0444 data: 0.0034 max mem: 19788 +Epoch: [37] [1360/2138] eta: 0:52:34 lr: 3.920156902157079e-06 loss: 0.0223 (0.0197) time: 4.0430 data: 0.0037 max mem: 19788 +Epoch: [37] [1370/2138] eta: 0:51:54 lr: 3.913173940393666e-06 loss: 0.0199 (0.0197) time: 4.0445 data: 0.0035 max mem: 19788 +Epoch: [37] [1380/2138] eta: 0:51:13 lr: 3.906189593807928e-06 loss: 0.0190 (0.0197) time: 4.0373 data: 0.0034 max mem: 19788 +Epoch: [37] [1390/2138] eta: 0:50:33 lr: 3.899203859372938e-06 loss: 0.0192 (0.0197) time: 4.0343 data: 0.0036 max mem: 19788 +Epoch: [37] [1400/2138] eta: 0:49:52 lr: 3.8922167340490895e-06 loss: 0.0192 (0.0197) time: 4.0345 data: 0.0033 max mem: 19788 +Epoch: [37] [1410/2138] eta: 0:49:11 lr: 3.8852282147840685e-06 loss: 0.0175 (0.0197) time: 4.0285 data: 0.0035 max mem: 19788 +Epoch: [37] [1420/2138] eta: 0:48:31 lr: 3.878238298512717e-06 loss: 0.0176 (0.0197) time: 4.0390 data: 0.0035 max mem: 19788 +Epoch: [37] [1430/2138] eta: 0:47:50 lr: 3.871246982157014e-06 loss: 0.0191 (0.0197) time: 4.0489 data: 0.0034 max mem: 19788 +Epoch: [37] [1440/2138] eta: 0:47:09 lr: 3.86425426262594e-06 loss: 0.0181 (0.0197) time: 4.0446 data: 0.0034 max mem: 19788 +Epoch: [37] [1450/2138] eta: 0:46:29 lr: 3.857260136815444e-06 loss: 0.0216 (0.0197) time: 4.0329 data: 0.0032 max mem: 19788 +Epoch: [37] [1460/2138] eta: 0:45:48 lr: 3.850264601608316e-06 loss: 0.0220 (0.0197) time: 4.0431 data: 0.0032 max mem: 19788 +Epoch: [37] [1470/2138] eta: 0:45:08 lr: 3.843267653874153e-06 loss: 0.0205 (0.0197) time: 4.0566 data: 0.0031 max mem: 19788 +Epoch: [37] [1480/2138] eta: 0:44:27 lr: 3.836269290469224e-06 loss: 0.0203 (0.0198) time: 4.0377 data: 0.0031 max mem: 19788 +Epoch: [37] [1490/2138] eta: 0:43:46 lr: 3.829269508236444e-06 loss: 0.0196 (0.0198) time: 4.0237 data: 0.0032 max mem: 19788 +Epoch: [37] [1500/2138] eta: 0:43:06 lr: 3.822268304005235e-06 loss: 0.0183 (0.0198) time: 4.0363 data: 0.0032 max mem: 19788 +Epoch: [37] [1510/2138] eta: 0:42:25 lr: 3.815265674591467e-06 loss: 0.0183 (0.0198) time: 4.0461 data: 0.0033 max mem: 19788 +Epoch: [37] [1520/2138] eta: 0:41:45 lr: 3.8082616167973936e-06 loss: 0.0180 (0.0198) time: 4.0433 data: 0.0035 max mem: 19788 +Epoch: [37] [1530/2138] eta: 0:41:04 lr: 3.8012561274115108e-06 loss: 0.0173 (0.0197) time: 4.0505 data: 0.0034 max mem: 19788 +Epoch: [37] [1540/2138] eta: 0:40:24 lr: 3.794249203208532e-06 loss: 0.0173 (0.0197) time: 4.0542 data: 0.0031 max mem: 19788 +Epoch: [37] [1550/2138] eta: 0:39:43 lr: 3.787240840949243e-06 loss: 0.0174 (0.0197) time: 4.0439 data: 0.0031 max mem: 19788 +Epoch: [37] [1560/2138] eta: 0:39:02 lr: 3.7802310373804652e-06 loss: 0.0183 (0.0197) time: 4.0406 data: 0.0032 max mem: 19788 +Epoch: [37] [1570/2138] eta: 0:38:22 lr: 3.773219789234915e-06 loss: 0.0184 (0.0197) time: 4.0462 data: 0.0033 max mem: 19788 +Epoch: [37] [1580/2138] eta: 0:37:41 lr: 3.766207093231168e-06 loss: 0.0183 (0.0197) time: 4.0551 data: 0.0033 max mem: 19788 +Epoch: [37] [1590/2138] eta: 0:37:01 lr: 3.7591929460735114e-06 loss: 0.0183 (0.0197) time: 4.0534 data: 0.0032 max mem: 19788 +Epoch: [37] [1600/2138] eta: 0:36:20 lr: 3.7521773444519097e-06 loss: 0.0212 (0.0197) time: 4.0462 data: 0.0033 max mem: 19788 +Epoch: [37] [1610/2138] eta: 0:35:40 lr: 3.745160285041855e-06 loss: 0.0181 (0.0197) time: 4.0396 data: 0.0033 max mem: 19788 +Epoch: [37] [1620/2138] eta: 0:34:59 lr: 3.7381417645043303e-06 loss: 0.0169 (0.0197) time: 4.0360 data: 0.0034 max mem: 19788 +Epoch: [37] [1630/2138] eta: 0:34:18 lr: 3.731121779485659e-06 loss: 0.0193 (0.0197) time: 4.0423 data: 0.0035 max mem: 19788 +Epoch: [37] [1640/2138] eta: 0:33:38 lr: 3.724100326617468e-06 loss: 0.0186 (0.0197) time: 4.0545 data: 0.0033 max mem: 19788 +Epoch: [37] [1650/2138] eta: 0:32:57 lr: 3.7170774025165333e-06 loss: 0.0175 (0.0197) time: 4.0518 data: 0.0034 max mem: 19788 +Epoch: [37] [1660/2138] eta: 0:32:17 lr: 3.7100530037847406e-06 loss: 0.0169 (0.0197) time: 4.0454 data: 0.0034 max mem: 19788 +Epoch: [37] [1670/2138] eta: 0:31:36 lr: 3.703027127008933e-06 loss: 0.0161 (0.0197) time: 4.0499 data: 0.0032 max mem: 19788 +Epoch: [37] [1680/2138] eta: 0:30:56 lr: 3.6959997687608675e-06 loss: 0.0192 (0.0197) time: 4.0470 data: 0.0034 max mem: 19788 +Epoch: [37] [1690/2138] eta: 0:30:15 lr: 3.688970925597061e-06 loss: 0.0192 (0.0197) time: 4.0454 data: 0.0034 max mem: 19788 +Epoch: [37] [1700/2138] eta: 0:29:35 lr: 3.681940594058745e-06 loss: 0.0181 (0.0197) time: 4.0462 data: 0.0033 max mem: 19788 +Epoch: [37] [1710/2138] eta: 0:28:54 lr: 3.674908770671711e-06 loss: 0.0192 (0.0197) time: 4.0472 data: 0.0034 max mem: 19788 +Epoch: [37] [1720/2138] eta: 0:28:14 lr: 3.667875451946263e-06 loss: 0.0199 (0.0197) time: 4.0463 data: 0.0034 max mem: 19788 +Epoch: [37] [1730/2138] eta: 0:27:33 lr: 3.66084063437706e-06 loss: 0.0202 (0.0197) time: 4.0448 data: 0.0033 max mem: 19788 +Epoch: [37] [1740/2138] eta: 0:26:53 lr: 3.6538043144430675e-06 loss: 0.0193 (0.0197) time: 4.0523 data: 0.0032 max mem: 19788 +Epoch: [37] [1750/2138] eta: 0:26:12 lr: 3.6467664886074005e-06 loss: 0.0192 (0.0197) time: 4.0536 data: 0.0031 max mem: 19788 +Epoch: [37] [1760/2138] eta: 0:25:31 lr: 3.6397271533172683e-06 loss: 0.0191 (0.0197) time: 4.0485 data: 0.0031 max mem: 19788 +Epoch: [37] [1770/2138] eta: 0:24:51 lr: 3.6326863050038186e-06 loss: 0.0191 (0.0197) time: 4.0358 data: 0.0032 max mem: 19788 +Epoch: [37] [1780/2138] eta: 0:24:10 lr: 3.6256439400820815e-06 loss: 0.0182 (0.0197) time: 4.0324 data: 0.0033 max mem: 19788 +Epoch: [37] [1790/2138] eta: 0:23:30 lr: 3.618600054950811e-06 loss: 0.0181 (0.0197) time: 4.0360 data: 0.0031 max mem: 19788 +Epoch: [37] [1800/2138] eta: 0:22:49 lr: 3.6115546459924244e-06 loss: 0.0175 (0.0197) time: 4.0315 data: 0.0033 max mem: 19788 +Epoch: [37] [1810/2138] eta: 0:22:09 lr: 3.6045077095728512e-06 loss: 0.0180 (0.0197) time: 4.0411 data: 0.0035 max mem: 19788 +Epoch: [37] [1820/2138] eta: 0:21:28 lr: 3.5974592420414377e-06 loss: 0.0193 (0.0197) time: 4.0448 data: 0.0034 max mem: 19788 +Epoch: [37] [1830/2138] eta: 0:20:48 lr: 3.5904092397308583e-06 loss: 0.0193 (0.0197) time: 4.0339 data: 0.0032 max mem: 19788 +Epoch: [37] [1840/2138] eta: 0:20:07 lr: 3.583357698956953e-06 loss: 0.0206 (0.0197) time: 4.0287 data: 0.0033 max mem: 19788 +Epoch: [37] [1850/2138] eta: 0:19:26 lr: 3.5763046160186713e-06 loss: 0.0206 (0.0197) time: 4.0306 data: 0.0033 max mem: 19788 +Epoch: [37] [1860/2138] eta: 0:18:46 lr: 3.5692499871978964e-06 loss: 0.0204 (0.0197) time: 4.0440 data: 0.0031 max mem: 19788 +Epoch: [37] [1870/2138] eta: 0:18:05 lr: 3.5621938087593917e-06 loss: 0.0189 (0.0197) time: 4.0541 data: 0.0035 max mem: 19788 +Epoch: [37] [1880/2138] eta: 0:17:25 lr: 3.555136076950623e-06 loss: 0.0188 (0.0197) time: 4.0528 data: 0.0036 max mem: 19788 +Epoch: [37] [1890/2138] eta: 0:16:44 lr: 3.5480767880016966e-06 loss: 0.0176 (0.0197) time: 4.0511 data: 0.0032 max mem: 19788 +Epoch: [37] [1900/2138] eta: 0:16:04 lr: 3.541015938125189e-06 loss: 0.0174 (0.0197) time: 4.0499 data: 0.0032 max mem: 19788 +Epoch: [37] [1910/2138] eta: 0:15:23 lr: 3.533953523516075e-06 loss: 0.0186 (0.0197) time: 4.0492 data: 0.0034 max mem: 19788 +Epoch: [37] [1920/2138] eta: 0:14:43 lr: 3.526889540351557e-06 loss: 0.0186 (0.0197) time: 4.0466 data: 0.0034 max mem: 19788 +Epoch: [37] [1930/2138] eta: 0:14:02 lr: 3.5198239847909953e-06 loss: 0.0188 (0.0197) time: 4.0448 data: 0.0034 max mem: 19788 +Epoch: [37] [1940/2138] eta: 0:13:22 lr: 3.512756852975728e-06 loss: 0.0194 (0.0197) time: 4.0472 data: 0.0036 max mem: 19788 +Epoch: [37] [1950/2138] eta: 0:12:41 lr: 3.5056881410290043e-06 loss: 0.0188 (0.0197) time: 4.0517 data: 0.0033 max mem: 19788 +Epoch: [37] [1960/2138] eta: 0:12:01 lr: 3.498617845055803e-06 loss: 0.0188 (0.0197) time: 4.0545 data: 0.0033 max mem: 19788 +Epoch: [37] [1970/2138] eta: 0:11:20 lr: 3.4915459611427578e-06 loss: 0.0186 (0.0197) time: 4.0527 data: 0.0036 max mem: 19788 +Epoch: [37] [1980/2138] eta: 0:10:40 lr: 3.484472485357978e-06 loss: 0.0165 (0.0197) time: 4.0532 data: 0.0033 max mem: 19788 +Epoch: [37] [1990/2138] eta: 0:09:59 lr: 3.47739741375097e-06 loss: 0.0173 (0.0197) time: 4.0533 data: 0.0032 max mem: 19788 +Epoch: [37] [2000/2138] eta: 0:09:19 lr: 3.4703207423524556e-06 loss: 0.0186 (0.0197) time: 4.0549 data: 0.0034 max mem: 19788 +Epoch: [37] [2010/2138] eta: 0:08:38 lr: 3.4632424671742937e-06 loss: 0.0196 (0.0197) time: 4.0586 data: 0.0034 max mem: 19788 +Epoch: [37] [2020/2138] eta: 0:07:58 lr: 3.4561625842092894e-06 loss: 0.0196 (0.0197) time: 4.0578 data: 0.0034 max mem: 19788 +Epoch: [37] [2030/2138] eta: 0:07:17 lr: 3.449081089431121e-06 loss: 0.0198 (0.0197) time: 4.0483 data: 0.0035 max mem: 19788 +Epoch: [37] [2040/2138] eta: 0:06:37 lr: 3.4419979787941445e-06 loss: 0.0191 (0.0197) time: 4.0502 data: 0.0036 max mem: 19788 +Epoch: [37] [2050/2138] eta: 0:05:56 lr: 3.4349132482333124e-06 loss: 0.0191 (0.0197) time: 4.0637 data: 0.0034 max mem: 19788 +Epoch: [37] [2060/2138] eta: 0:05:16 lr: 3.4278268936639816e-06 loss: 0.0185 (0.0197) time: 4.0594 data: 0.0032 max mem: 19788 +Epoch: [37] [2070/2138] eta: 0:04:35 lr: 3.4207389109818294e-06 loss: 0.0173 (0.0197) time: 4.0446 data: 0.0032 max mem: 19788 +Epoch: [37] [2080/2138] eta: 0:03:55 lr: 3.413649296062658e-06 loss: 0.0179 (0.0197) time: 4.0388 data: 0.0034 max mem: 19788 +Epoch: [37] [2090/2138] eta: 0:03:14 lr: 3.4065580447623055e-06 loss: 0.0188 (0.0197) time: 4.0405 data: 0.0034 max mem: 19788 +Epoch: [37] [2100/2138] eta: 0:02:33 lr: 3.3994651529164494e-06 loss: 0.0186 (0.0197) time: 4.0479 data: 0.0033 max mem: 19788 +Epoch: [37] [2110/2138] eta: 0:01:53 lr: 3.3923706163405158e-06 loss: 0.0202 (0.0197) time: 4.0536 data: 0.0033 max mem: 19788 +Epoch: [37] [2120/2138] eta: 0:01:12 lr: 3.385274430829487e-06 loss: 0.0229 (0.0197) time: 4.0517 data: 0.0032 max mem: 19788 +Epoch: [37] [2130/2138] eta: 0:00:32 lr: 3.378176592157771e-06 loss: 0.0204 (0.0197) time: 4.0275 data: 0.0031 max mem: 19788 +Epoch: [37] Total time: 2:24:23 +Test: [ 0/21770] eta: 20:32:03 time: 3.3957 data: 3.2915 max mem: 19788 +Test: [ 100/21770] eta: 0:38:58 time: 0.0640 data: 0.0019 max mem: 19788 +Test: [ 200/21770] eta: 0:32:02 time: 0.0688 data: 0.0022 max mem: 19788 +Test: [ 300/21770] eta: 0:29:40 time: 0.0833 data: 0.0022 max mem: 19788 +Test: [ 400/21770] eta: 0:28:09 time: 0.0653 data: 0.0020 max mem: 19788 +Test: [ 500/21770] eta: 0:27:47 time: 0.0749 data: 0.0024 max mem: 19788 +Test: [ 600/21770] eta: 0:26:55 time: 0.0798 data: 0.0025 max mem: 19788 +Test: [ 700/21770] eta: 0:26:24 time: 0.0662 data: 0.0020 max mem: 19788 +Test: [ 800/21770] eta: 0:25:51 time: 0.0663 data: 0.0021 max mem: 19788 +Test: [ 900/21770] eta: 0:25:18 time: 0.0636 data: 0.0019 max mem: 19788 +Test: [ 1000/21770] eta: 0:25:07 time: 0.0749 data: 0.0019 max mem: 19788 +Test: [ 1100/21770] eta: 0:24:59 time: 0.0711 data: 0.0022 max mem: 19788 +Test: [ 1200/21770] eta: 0:24:48 time: 0.0648 data: 0.0019 max mem: 19788 +Test: [ 1300/21770] eta: 0:24:34 time: 0.0642 data: 0.0019 max mem: 19788 +Test: [ 1400/21770] eta: 0:24:20 time: 0.0742 data: 0.0022 max mem: 19788 +Test: [ 1500/21770] eta: 0:24:08 time: 0.0823 data: 0.0023 max mem: 19788 +Test: [ 1600/21770] eta: 0:23:59 time: 0.0672 data: 0.0023 max mem: 19788 +Test: [ 1700/21770] eta: 0:23:47 time: 0.0676 data: 0.0020 max mem: 19788 +Test: [ 1800/21770] eta: 0:23:36 time: 0.0689 data: 0.0021 max mem: 19788 +Test: [ 1900/21770] eta: 0:23:26 time: 0.0744 data: 0.0021 max mem: 19788 +Test: [ 2000/21770] eta: 0:23:17 time: 0.0637 data: 0.0018 max mem: 19788 +Test: [ 2100/21770] eta: 0:23:06 time: 0.0642 data: 0.0020 max mem: 19788 +Test: [ 2200/21770] eta: 0:23:01 time: 0.0727 data: 0.0022 max mem: 19788 +Test: [ 2300/21770] eta: 0:22:55 time: 0.0639 data: 0.0019 max mem: 19788 +Test: [ 2400/21770] eta: 0:22:51 time: 0.0657 data: 0.0020 max mem: 19788 +Test: [ 2500/21770] eta: 0:22:46 time: 0.0774 data: 0.0025 max mem: 19788 +Test: [ 2600/21770] eta: 0:22:44 time: 0.0763 data: 0.0022 max mem: 19788 +Test: [ 2700/21770] eta: 0:22:39 time: 0.0684 data: 0.0021 max mem: 19788 +Test: [ 2800/21770] eta: 0:22:34 time: 0.0706 data: 0.0021 max mem: 19788 +Test: [ 2900/21770] eta: 0:22:28 time: 0.0644 data: 0.0019 max mem: 19788 +Test: [ 3000/21770] eta: 0:22:22 time: 0.0859 data: 0.0022 max mem: 19788 +Test: [ 3100/21770] eta: 0:22:12 time: 0.0731 data: 0.0023 max mem: 19788 +Test: [ 3200/21770] eta: 0:22:05 time: 0.0668 data: 0.0022 max mem: 19788 +Test: [ 3300/21770] eta: 0:21:59 time: 0.0648 data: 0.0023 max mem: 19788 +Test: [ 3400/21770] eta: 0:21:53 time: 0.0793 data: 0.0025 max mem: 19788 +Test: [ 3500/21770] eta: 0:21:44 time: 0.0667 data: 0.0019 max mem: 19788 +Test: [ 3600/21770] eta: 0:21:38 time: 0.0658 data: 0.0020 max mem: 19788 +Test: [ 3700/21770] eta: 0:21:29 time: 0.0656 data: 0.0019 max mem: 19788 +Test: [ 3800/21770] eta: 0:21:26 time: 0.0724 data: 0.0022 max mem: 19788 +Test: [ 3900/21770] eta: 0:21:17 time: 0.0651 data: 0.0021 max mem: 19788 +Test: [ 4000/21770] eta: 0:21:12 time: 0.0856 data: 0.0021 max mem: 19788 +Test: [ 4100/21770] eta: 0:21:05 time: 0.0650 data: 0.0020 max mem: 19788 +Test: [ 4200/21770] eta: 0:20:58 time: 0.0657 data: 0.0020 max mem: 19788 +Test: [ 4300/21770] eta: 0:20:50 time: 0.0844 data: 0.0026 max mem: 19788 +Test: [ 4400/21770] eta: 0:20:44 time: 0.0652 data: 0.0019 max mem: 19788 +Test: [ 4500/21770] eta: 0:20:36 time: 0.0762 data: 0.0022 max mem: 19788 +Test: [ 4600/21770] eta: 0:20:30 time: 0.0768 data: 0.0024 max mem: 19788 +Test: [ 4700/21770] eta: 0:20:23 time: 0.0840 data: 0.0025 max mem: 19788 +Test: [ 4800/21770] eta: 0:20:15 time: 0.0676 data: 0.0019 max mem: 19788 +Test: [ 4900/21770] eta: 0:20:07 time: 0.0767 data: 0.0022 max mem: 19788 +Test: [ 5000/21770] eta: 0:20:00 time: 0.0647 data: 0.0021 max mem: 19788 +Test: [ 5100/21770] eta: 0:19:55 time: 0.0850 data: 0.0021 max mem: 19788 +Test: [ 5200/21770] eta: 0:19:50 time: 0.0856 data: 0.0024 max mem: 19788 +Test: [ 5300/21770] eta: 0:19:41 time: 0.0666 data: 0.0021 max mem: 19788 +Test: [ 5400/21770] eta: 0:19:34 time: 0.0702 data: 0.0019 max mem: 19788 +Test: [ 5500/21770] eta: 0:19:27 time: 0.0725 data: 0.0022 max mem: 19788 +Test: [ 5600/21770] eta: 0:19:18 time: 0.0654 data: 0.0022 max mem: 19788 +Test: [ 5700/21770] eta: 0:19:11 time: 0.0653 data: 0.0021 max mem: 19788 +Test: [ 5800/21770] eta: 0:19:02 time: 0.0765 data: 0.0022 max mem: 19788 +Test: [ 5900/21770] eta: 0:18:53 time: 0.0653 data: 0.0020 max mem: 19788 +Test: [ 6000/21770] eta: 0:18:45 time: 0.0808 data: 0.0026 max mem: 19788 +Test: [ 6100/21770] eta: 0:18:38 time: 0.0698 data: 0.0021 max mem: 19788 +Test: [ 6200/21770] eta: 0:18:30 time: 0.0685 data: 0.0021 max mem: 19788 +Test: [ 6300/21770] eta: 0:18:24 time: 0.0752 data: 0.0021 max mem: 19788 +Test: [ 6400/21770] eta: 0:18:15 time: 0.0701 data: 0.0022 max mem: 19788 +Test: [ 6500/21770] eta: 0:18:09 time: 0.0795 data: 0.0021 max mem: 19788 +Test: [ 6600/21770] eta: 0:18:01 time: 0.0638 data: 0.0020 max mem: 19788 +Test: [ 6700/21770] eta: 0:17:55 time: 0.0775 data: 0.0024 max mem: 19788 +Test: [ 6800/21770] eta: 0:17:47 time: 0.0642 data: 0.0020 max mem: 19788 +Test: [ 6900/21770] eta: 0:17:39 time: 0.0700 data: 0.0024 max mem: 19788 +Test: [ 7000/21770] eta: 0:17:32 time: 0.0702 data: 0.0020 max mem: 19788 +Test: [ 7100/21770] eta: 0:17:24 time: 0.0666 data: 0.0019 max mem: 19788 +Test: [ 7200/21770] eta: 0:17:17 time: 0.0688 data: 0.0022 max mem: 19788 +Test: [ 7300/21770] eta: 0:17:10 time: 0.0763 data: 0.0022 max mem: 19788 +Test: [ 7400/21770] eta: 0:17:02 time: 0.0612 data: 0.0017 max mem: 19788 +Test: [ 7500/21770] eta: 0:16:54 time: 0.0740 data: 0.0024 max mem: 19788 +Test: [ 7600/21770] eta: 0:16:46 time: 0.0634 data: 0.0020 max mem: 19788 +Test: [ 7700/21770] eta: 0:16:39 time: 0.0758 data: 0.0020 max mem: 19788 +Test: [ 7800/21770] eta: 0:16:33 time: 0.0852 data: 0.0025 max mem: 19788 +Test: [ 7900/21770] eta: 0:16:26 time: 0.0629 data: 0.0018 max mem: 19788 +Test: [ 8000/21770] eta: 0:16:20 time: 0.0729 data: 0.0019 max mem: 19788 +Test: [ 8100/21770] eta: 0:16:13 time: 0.0840 data: 0.0027 max mem: 19788 +Test: [ 8200/21770] eta: 0:16:05 time: 0.0635 data: 0.0021 max mem: 19788 +Test: [ 8300/21770] eta: 0:15:58 time: 0.0649 data: 0.0018 max mem: 19788 +Test: [ 8400/21770] eta: 0:15:51 time: 0.0718 data: 0.0021 max mem: 19788 +Test: [ 8500/21770] eta: 0:15:43 time: 0.0712 data: 0.0022 max mem: 19788 +Test: [ 8600/21770] eta: 0:15:37 time: 0.0806 data: 0.0025 max mem: 19788 +Test: [ 8700/21770] eta: 0:15:31 time: 0.0784 data: 0.0023 max mem: 19788 +Test: [ 8800/21770] eta: 0:15:24 time: 0.0759 data: 0.0022 max mem: 19788 +Test: [ 8900/21770] eta: 0:15:18 time: 0.0785 data: 0.0024 max mem: 19788 +Test: [ 9000/21770] eta: 0:15:10 time: 0.0634 data: 0.0021 max mem: 19788 +Test: [ 9100/21770] eta: 0:15:03 time: 0.0720 data: 0.0021 max mem: 19788 +Test: [ 9200/21770] eta: 0:14:56 time: 0.0652 data: 0.0020 max mem: 19788 +Test: [ 9300/21770] eta: 0:14:49 time: 0.0640 data: 0.0018 max mem: 19788 +Test: [ 9400/21770] eta: 0:14:41 time: 0.0635 data: 0.0021 max mem: 19788 +Test: [ 9500/21770] eta: 0:14:34 time: 0.0785 data: 0.0024 max mem: 19788 +Test: [ 9600/21770] eta: 0:14:28 time: 0.0848 data: 0.0026 max mem: 19788 +Test: [ 9700/21770] eta: 0:14:22 time: 0.0750 data: 0.0019 max mem: 19788 +Test: [ 9800/21770] eta: 0:14:15 time: 0.0710 data: 0.0022 max mem: 19788 +Test: [ 9900/21770] eta: 0:14:09 time: 0.0671 data: 0.0020 max mem: 19788 +Test: [10000/21770] eta: 0:14:02 time: 0.0644 data: 0.0018 max mem: 19788 +Test: [10100/21770] eta: 0:13:54 time: 0.0671 data: 0.0019 max mem: 19788 +Test: [10200/21770] eta: 0:13:47 time: 0.0763 data: 0.0021 max mem: 19788 +Test: [10300/21770] eta: 0:13:40 time: 0.0644 data: 0.0020 max mem: 19788 +Test: [10400/21770] eta: 0:13:33 time: 0.0821 data: 0.0027 max mem: 19788 +Test: [10500/21770] eta: 0:13:27 time: 0.0857 data: 0.0028 max mem: 19788 +Test: [10600/21770] eta: 0:13:20 time: 0.0836 data: 0.0026 max mem: 19788 +Test: [10700/21770] eta: 0:13:13 time: 0.0659 data: 0.0021 max mem: 19788 +Test: [10800/21770] eta: 0:13:06 time: 0.0754 data: 0.0020 max mem: 19788 +Test: [10900/21770] eta: 0:12:58 time: 0.0686 data: 0.0020 max mem: 19788 +Test: [11000/21770] eta: 0:12:51 time: 0.0677 data: 0.0021 max mem: 19788 +Test: [11100/21770] eta: 0:12:44 time: 0.0716 data: 0.0021 max mem: 19788 +Test: [11200/21770] eta: 0:12:36 time: 0.0689 data: 0.0023 max mem: 19788 +Test: [11300/21770] eta: 0:12:28 time: 0.0695 data: 0.0020 max mem: 19788 +Test: [11400/21770] eta: 0:12:22 time: 0.0844 data: 0.0024 max mem: 19788 +Test: [11500/21770] eta: 0:12:16 time: 0.0702 data: 0.0024 max mem: 19788 +Test: [11600/21770] eta: 0:12:08 time: 0.0720 data: 0.0023 max mem: 19788 +Test: [11700/21770] eta: 0:12:01 time: 0.0820 data: 0.0020 max mem: 19788 +Test: [11800/21770] eta: 0:11:54 time: 0.0643 data: 0.0022 max mem: 19788 +Test: [11900/21770] eta: 0:11:47 time: 0.0629 data: 0.0021 max mem: 19788 +Test: [12000/21770] eta: 0:11:41 time: 0.0693 data: 0.0024 max mem: 19788 +Test: [12100/21770] eta: 0:11:34 time: 0.0854 data: 0.0024 max mem: 19788 +Test: [12200/21770] eta: 0:11:27 time: 0.0807 data: 0.0025 max mem: 19788 +Test: [12300/21770] eta: 0:11:20 time: 0.0754 data: 0.0024 max mem: 19788 +Test: [12400/21770] eta: 0:11:13 time: 0.0715 data: 0.0024 max mem: 19788 +Test: [12500/21770] eta: 0:11:06 time: 0.0719 data: 0.0024 max mem: 19788 +Test: [12600/21770] eta: 0:10:58 time: 0.0652 data: 0.0020 max mem: 19788 +Test: [12700/21770] eta: 0:10:52 time: 0.0665 data: 0.0021 max mem: 19788 +Test: [12800/21770] eta: 0:10:44 time: 0.0691 data: 0.0021 max mem: 19788 +Test: [12900/21770] eta: 0:10:37 time: 0.0850 data: 0.0028 max mem: 19788 +Test: [13000/21770] eta: 0:10:30 time: 0.0666 data: 0.0019 max mem: 19788 +Test: [13100/21770] eta: 0:10:23 time: 0.0676 data: 0.0019 max mem: 19788 +Test: [13200/21770] eta: 0:10:15 time: 0.0685 data: 0.0022 max mem: 19788 +Test: [13300/21770] eta: 0:10:08 time: 0.0635 data: 0.0018 max mem: 19788 +Test: [13400/21770] eta: 0:10:01 time: 0.0648 data: 0.0019 max mem: 19788 +Test: [13500/21770] eta: 0:09:53 time: 0.0662 data: 0.0020 max mem: 19788 +Test: [13600/21770] eta: 0:09:46 time: 0.0685 data: 0.0021 max mem: 19788 +Test: [13700/21770] eta: 0:09:39 time: 0.0678 data: 0.0021 max mem: 19788 +Test: [13800/21770] eta: 0:09:31 time: 0.0617 data: 0.0019 max mem: 19788 +Test: [13900/21770] eta: 0:09:24 time: 0.0740 data: 0.0020 max mem: 19788 +Test: [14000/21770] eta: 0:09:18 time: 0.0860 data: 0.0026 max mem: 19788 +Test: [14100/21770] eta: 0:09:10 time: 0.0740 data: 0.0022 max mem: 19788 +Test: [14200/21770] eta: 0:09:03 time: 0.0686 data: 0.0020 max mem: 19788 +Test: [14300/21770] eta: 0:08:56 time: 0.0665 data: 0.0022 max mem: 19788 +Test: [14400/21770] eta: 0:08:48 time: 0.0717 data: 0.0022 max mem: 19788 +Test: [14500/21770] eta: 0:08:41 time: 0.0793 data: 0.0026 max mem: 19788 +Test: [14600/21770] eta: 0:08:35 time: 0.0684 data: 0.0020 max mem: 19788 +Test: [14700/21770] eta: 0:08:27 time: 0.0661 data: 0.0021 max mem: 19788 +Test: [14800/21770] eta: 0:08:20 time: 0.0731 data: 0.0021 max mem: 19788 +Test: [14900/21770] eta: 0:08:13 time: 0.0774 data: 0.0026 max mem: 19788 +Test: [15000/21770] eta: 0:08:06 time: 0.0669 data: 0.0021 max mem: 19788 +Test: [15100/21770] eta: 0:07:59 time: 0.0725 data: 0.0024 max mem: 19788 +Test: [15200/21770] eta: 0:07:51 time: 0.0631 data: 0.0019 max mem: 19788 +Test: [15300/21770] eta: 0:07:44 time: 0.0727 data: 0.0022 max mem: 19788 +Test: [15400/21770] eta: 0:07:37 time: 0.0871 data: 0.0026 max mem: 19788 +Test: [15500/21770] eta: 0:07:30 time: 0.0801 data: 0.0025 max mem: 19788 +Test: [15600/21770] eta: 0:07:23 time: 0.0704 data: 0.0023 max mem: 19788 +Test: [15700/21770] eta: 0:07:15 time: 0.0648 data: 0.0019 max mem: 19788 +Test: [15800/21770] eta: 0:07:08 time: 0.0678 data: 0.0021 max mem: 19788 +Test: [15900/21770] eta: 0:07:01 time: 0.0658 data: 0.0022 max mem: 19788 +Test: [16000/21770] eta: 0:06:54 time: 0.0637 data: 0.0019 max mem: 19788 +Test: [16100/21770] eta: 0:06:46 time: 0.0673 data: 0.0019 max mem: 19788 +Test: [16200/21770] eta: 0:06:39 time: 0.0700 data: 0.0021 max mem: 19788 +Test: [16300/21770] eta: 0:06:32 time: 0.0641 data: 0.0020 max mem: 19788 +Test: [16400/21770] eta: 0:06:25 time: 0.0827 data: 0.0028 max mem: 19788 +Test: [16500/21770] eta: 0:06:18 time: 0.0679 data: 0.0021 max mem: 19788 +Test: [16600/21770] eta: 0:06:11 time: 0.0865 data: 0.0027 max mem: 19788 +Test: [16700/21770] eta: 0:06:04 time: 0.0674 data: 0.0018 max mem: 19788 +Test: [16800/21770] eta: 0:05:57 time: 0.0659 data: 0.0020 max mem: 19788 +Test: [16900/21770] eta: 0:05:50 time: 0.0697 data: 0.0020 max mem: 19788 +Test: [17000/21770] eta: 0:05:42 time: 0.0721 data: 0.0021 max mem: 19788 +Test: [17100/21770] eta: 0:05:35 time: 0.0722 data: 0.0024 max mem: 19788 +Test: [17200/21770] eta: 0:05:28 time: 0.0772 data: 0.0020 max mem: 19788 +Test: [17300/21770] eta: 0:05:21 time: 0.0678 data: 0.0022 max mem: 19788 +Test: [17400/21770] eta: 0:05:13 time: 0.0696 data: 0.0023 max mem: 19788 +Test: [17500/21770] eta: 0:05:06 time: 0.0642 data: 0.0018 max mem: 19788 +Test: [17600/21770] eta: 0:04:59 time: 0.0619 data: 0.0017 max mem: 19788 +Test: [17700/21770] eta: 0:04:52 time: 0.0650 data: 0.0022 max mem: 19788 +Test: [17800/21770] eta: 0:04:44 time: 0.0759 data: 0.0023 max mem: 19788 +Test: [17900/21770] eta: 0:04:37 time: 0.0632 data: 0.0019 max mem: 19788 +Test: [18000/21770] eta: 0:04:30 time: 0.0690 data: 0.0021 max mem: 19788 +Test: [18100/21770] eta: 0:04:23 time: 0.0668 data: 0.0021 max mem: 19788 +Test: [18200/21770] eta: 0:04:15 time: 0.0674 data: 0.0019 max mem: 19788 +Test: [18300/21770] eta: 0:04:08 time: 0.0659 data: 0.0021 max mem: 19788 +Test: [18400/21770] eta: 0:04:01 time: 0.0691 data: 0.0021 max mem: 19788 +Test: [18500/21770] eta: 0:03:54 time: 0.0708 data: 0.0024 max mem: 19788 +Test: [18600/21770] eta: 0:03:47 time: 0.0730 data: 0.0024 max mem: 19788 +Test: [18700/21770] eta: 0:03:39 time: 0.0804 data: 0.0026 max mem: 19788 +Test: [18800/21770] eta: 0:03:32 time: 0.0735 data: 0.0022 max mem: 19788 +Test: [18900/21770] eta: 0:03:25 time: 0.0642 data: 0.0020 max mem: 19788 +Test: [19000/21770] eta: 0:03:18 time: 0.0654 data: 0.0019 max mem: 19788 +Test: [19100/21770] eta: 0:03:11 time: 0.0857 data: 0.0024 max mem: 19788 +Test: [19200/21770] eta: 0:03:04 time: 0.0866 data: 0.0025 max mem: 19788 +Test: [19300/21770] eta: 0:02:57 time: 0.0692 data: 0.0021 max mem: 19788 +Test: [19400/21770] eta: 0:02:49 time: 0.0639 data: 0.0019 max mem: 19788 +Test: [19500/21770] eta: 0:02:42 time: 0.0641 data: 0.0018 max mem: 19788 +Test: [19600/21770] eta: 0:02:35 time: 0.0666 data: 0.0021 max mem: 19788 +Test: [19700/21770] eta: 0:02:28 time: 0.0688 data: 0.0024 max mem: 19788 +Test: [19800/21770] eta: 0:02:21 time: 0.0676 data: 0.0018 max mem: 19788 +Test: [19900/21770] eta: 0:02:14 time: 0.0684 data: 0.0022 max mem: 19788 +Test: [20000/21770] eta: 0:02:06 time: 0.0658 data: 0.0021 max mem: 19788 +Test: [20100/21770] eta: 0:01:59 time: 0.0806 data: 0.0023 max mem: 19788 +Test: [20200/21770] eta: 0:01:52 time: 0.0676 data: 0.0020 max mem: 19788 +Test: [20300/21770] eta: 0:01:45 time: 0.0642 data: 0.0017 max mem: 19788 +Test: [20400/21770] eta: 0:01:38 time: 0.0866 data: 0.0026 max mem: 19788 +Test: [20500/21770] eta: 0:01:31 time: 0.0827 data: 0.0026 max mem: 19788 +Test: [20600/21770] eta: 0:01:23 time: 0.0704 data: 0.0021 max mem: 19788 +Test: [20700/21770] eta: 0:01:16 time: 0.0665 data: 0.0021 max mem: 19788 +Test: [20800/21770] eta: 0:01:09 time: 0.0633 data: 0.0018 max mem: 19788 +Test: [20900/21770] eta: 0:01:02 time: 0.0727 data: 0.0022 max mem: 19788 +Test: [21000/21770] eta: 0:00:55 time: 0.0811 data: 0.0026 max mem: 19788 +Test: [21100/21770] eta: 0:00:48 time: 0.0660 data: 0.0020 max mem: 19788 +Test: [21200/21770] eta: 0:00:40 time: 0.0648 data: 0.0020 max mem: 19788 +Test: [21300/21770] eta: 0:00:33 time: 0.0808 data: 0.0023 max mem: 19788 +Test: [21400/21770] eta: 0:00:26 time: 0.0694 data: 0.0022 max mem: 19788 +Test: [21500/21770] eta: 0:00:19 time: 0.0861 data: 0.0026 max mem: 19788 +Test: [21600/21770] eta: 0:00:12 time: 0.0642 data: 0.0020 max mem: 19788 +Test: [21700/21770] eta: 0:00:05 time: 0.0605 data: 0.0019 max mem: 19788 +Test: Total time: 0:26:05 +Final results: +Mean IoU is 62.88 + + precision@0.5 = 69.67 + precision@0.6 = 64.75 + precision@0.7 = 58.29 + precision@0.8 = 47.84 + precision@0.9 = 23.79 + overall IoU = 64.04 + mean IoU = 62.88 + +Mean accuracy for one-to-zero sample is 87.24 + +Average object IoU 0.6288461682615784 +Overall IoU 64.04109954833984 +Epoch: [38] [ 0/2138] eta: 5:13:27 lr: 3.372497128091893e-06 loss: 0.0189 (0.0189) time: 8.7967 data: 1.8373 max mem: 19788 +Epoch: [38] [ 10/2138] eta: 2:39:32 lr: 3.3653963030162514e-06 loss: 0.0160 (0.0165) time: 4.4985 data: 0.1706 max mem: 19788 +Epoch: [38] [ 20/2138] eta: 2:31:25 lr: 3.358293812837573e-06 loss: 0.0155 (0.0166) time: 4.0644 data: 0.0030 max mem: 19788 +Epoch: [38] [ 30/2138] eta: 2:28:07 lr: 3.351189653250742e-06 loss: 0.0165 (0.0170) time: 4.0607 data: 0.0026 max mem: 19788 +Epoch: [38] [ 40/2138] eta: 2:25:56 lr: 3.3440838199293173e-06 loss: 0.0184 (0.0179) time: 4.0519 data: 0.0033 max mem: 19788 +Epoch: [38] [ 50/2138] eta: 2:24:24 lr: 3.336976308525428e-06 loss: 0.0203 (0.0181) time: 4.0462 data: 0.0033 max mem: 19788 +Epoch: [38] [ 60/2138] eta: 2:23:02 lr: 3.3298671146695647e-06 loss: 0.0172 (0.0180) time: 4.0408 data: 0.0035 max mem: 19788 +Epoch: [38] [ 70/2138] eta: 2:21:53 lr: 3.32275623397047e-06 loss: 0.0153 (0.0176) time: 4.0337 data: 0.0035 max mem: 19788 +Epoch: [38] [ 80/2138] eta: 2:20:55 lr: 3.315643662014928e-06 loss: 0.0162 (0.0178) time: 4.0429 data: 0.0036 max mem: 19788 +Epoch: [38] [ 90/2138] eta: 2:20:03 lr: 3.3085293943676545e-06 loss: 0.0173 (0.0178) time: 4.0549 data: 0.0038 max mem: 19788 +Epoch: [38] [ 100/2138] eta: 2:19:11 lr: 3.3014134265710803e-06 loss: 0.0174 (0.0179) time: 4.0535 data: 0.0034 max mem: 19788 +Epoch: [38] [ 110/2138] eta: 2:18:17 lr: 3.2942957541452374e-06 loss: 0.0189 (0.0180) time: 4.0394 data: 0.0034 max mem: 19788 +Epoch: [38] [ 120/2138] eta: 2:17:29 lr: 3.2871763725875413e-06 loss: 0.0189 (0.0182) time: 4.0384 data: 0.0034 max mem: 19788 +Epoch: [38] [ 130/2138] eta: 2:16:39 lr: 3.2800552773726763e-06 loss: 0.0203 (0.0183) time: 4.0366 data: 0.0034 max mem: 19788 +Epoch: [38] [ 140/2138] eta: 2:15:52 lr: 3.2729324639523667e-06 loss: 0.0210 (0.0184) time: 4.0360 data: 0.0035 max mem: 19788 +Epoch: [38] [ 150/2138] eta: 2:15:04 lr: 3.2658079277552648e-06 loss: 0.0179 (0.0183) time: 4.0340 data: 0.0033 max mem: 19788 +Epoch: [38] [ 160/2138] eta: 2:14:17 lr: 3.258681664186726e-06 loss: 0.0192 (0.0186) time: 4.0238 data: 0.0033 max mem: 19788 +Epoch: [38] [ 170/2138] eta: 2:13:31 lr: 3.251553668628656e-06 loss: 0.0219 (0.0188) time: 4.0272 data: 0.0033 max mem: 19788 +Epoch: [38] [ 180/2138] eta: 2:12:46 lr: 3.2444239364393524e-06 loss: 0.0211 (0.0188) time: 4.0310 data: 0.0033 max mem: 19788 +Epoch: [38] [ 190/2138] eta: 2:12:03 lr: 3.2372924629532787e-06 loss: 0.0173 (0.0188) time: 4.0398 data: 0.0034 max mem: 19788 +Epoch: [38] [ 200/2138] eta: 2:11:19 lr: 3.2301592434809395e-06 loss: 0.0141 (0.0186) time: 4.0379 data: 0.0033 max mem: 19788 +Epoch: [38] [ 210/2138] eta: 2:10:35 lr: 3.223024273308642e-06 loss: 0.0212 (0.0189) time: 4.0282 data: 0.0031 max mem: 19788 +Epoch: [38] [ 220/2138] eta: 2:09:51 lr: 3.2158875476983645e-06 loss: 0.0212 (0.0188) time: 4.0306 data: 0.0034 max mem: 19788 +Epoch: [38] [ 230/2138] eta: 2:09:10 lr: 3.2087490618875206e-06 loss: 0.0189 (0.0189) time: 4.0397 data: 0.0033 max mem: 19788 +Epoch: [38] [ 240/2138] eta: 2:08:29 lr: 3.201608811088821e-06 loss: 0.0196 (0.0190) time: 4.0556 data: 0.0032 max mem: 19788 +Epoch: [38] [ 250/2138] eta: 2:07:47 lr: 3.1944667904900307e-06 loss: 0.0181 (0.0189) time: 4.0529 data: 0.0033 max mem: 19788 +Epoch: [38] [ 260/2138] eta: 2:07:04 lr: 3.1873229952538325e-06 loss: 0.0169 (0.0189) time: 4.0380 data: 0.0032 max mem: 19788 +Epoch: [38] [ 270/2138] eta: 2:06:23 lr: 3.180177420517575e-06 loss: 0.0180 (0.0189) time: 4.0388 data: 0.0032 max mem: 19788 +Epoch: [38] [ 280/2138] eta: 2:05:42 lr: 3.173030061393138e-06 loss: 0.0187 (0.0189) time: 4.0473 data: 0.0031 max mem: 19788 +Epoch: [38] [ 290/2138] eta: 2:04:59 lr: 3.165880912966673e-06 loss: 0.0187 (0.0189) time: 4.0399 data: 0.0031 max mem: 19788 +Epoch: [38] [ 300/2138] eta: 2:04:18 lr: 3.1587299702984597e-06 loss: 0.0178 (0.0189) time: 4.0377 data: 0.0032 max mem: 19788 +Epoch: [38] [ 310/2138] eta: 2:03:35 lr: 3.151577228422654e-06 loss: 0.0169 (0.0188) time: 4.0366 data: 0.0035 max mem: 19788 +Epoch: [38] [ 320/2138] eta: 2:02:53 lr: 3.1444226823471326e-06 loss: 0.0181 (0.0190) time: 4.0254 data: 0.0036 max mem: 19788 +Epoch: [38] [ 330/2138] eta: 2:02:11 lr: 3.1372663270532343e-06 loss: 0.0201 (0.0190) time: 4.0301 data: 0.0036 max mem: 19788 +Epoch: [38] [ 340/2138] eta: 2:01:29 lr: 3.130108157495608e-06 loss: 0.0185 (0.0190) time: 4.0332 data: 0.0033 max mem: 19788 +Epoch: [38] [ 350/2138] eta: 2:00:48 lr: 3.122948168601944e-06 loss: 0.0181 (0.0190) time: 4.0341 data: 0.0031 max mem: 19788 +Epoch: [38] [ 360/2138] eta: 2:00:06 lr: 3.1157863552728205e-06 loss: 0.0185 (0.0190) time: 4.0331 data: 0.0032 max mem: 19788 +Epoch: [38] [ 370/2138] eta: 1:59:25 lr: 3.1086227123814304e-06 loss: 0.0190 (0.0191) time: 4.0336 data: 0.0033 max mem: 19788 +Epoch: [38] [ 380/2138] eta: 1:58:44 lr: 3.1014572347734185e-06 loss: 0.0180 (0.0190) time: 4.0389 data: 0.0035 max mem: 19788 +Epoch: [38] [ 390/2138] eta: 1:58:03 lr: 3.0942899172666103e-06 loss: 0.0189 (0.0191) time: 4.0384 data: 0.0035 max mem: 19788 +Epoch: [38] [ 400/2138] eta: 1:57:21 lr: 3.087120754650843e-06 loss: 0.0195 (0.0191) time: 4.0346 data: 0.0034 max mem: 19788 +Epoch: [38] [ 410/2138] eta: 1:56:40 lr: 3.079949741687687e-06 loss: 0.0200 (0.0192) time: 4.0304 data: 0.0033 max mem: 19788 +Epoch: [38] [ 420/2138] eta: 1:55:59 lr: 3.0727768731102726e-06 loss: 0.0200 (0.0192) time: 4.0323 data: 0.0034 max mem: 19788 +Epoch: [38] [ 430/2138] eta: 1:55:17 lr: 3.0656021436230103e-06 loss: 0.0172 (0.0192) time: 4.0314 data: 0.0032 max mem: 19788 +Epoch: [38] [ 440/2138] eta: 1:54:36 lr: 3.058425547901409e-06 loss: 0.0190 (0.0192) time: 4.0348 data: 0.0032 max mem: 19788 +Epoch: [38] [ 450/2138] eta: 1:53:56 lr: 3.0512470805917916e-06 loss: 0.0190 (0.0192) time: 4.0468 data: 0.0035 max mem: 19788 +Epoch: [38] [ 460/2138] eta: 1:53:15 lr: 3.0440667363111116e-06 loss: 0.0206 (0.0193) time: 4.0442 data: 0.0034 max mem: 19788 +Epoch: [38] [ 470/2138] eta: 1:52:34 lr: 3.036884509646666e-06 loss: 0.0206 (0.0193) time: 4.0417 data: 0.0032 max mem: 19788 +Epoch: [38] [ 480/2138] eta: 1:51:54 lr: 3.0297003951558746e-06 loss: 0.0203 (0.0194) time: 4.0451 data: 0.0033 max mem: 19788 +Epoch: [38] [ 490/2138] eta: 1:51:13 lr: 3.0225143873660576e-06 loss: 0.0187 (0.0193) time: 4.0463 data: 0.0034 max mem: 19788 +Epoch: [38] [ 500/2138] eta: 1:50:32 lr: 3.0153264807741386e-06 loss: 0.0176 (0.0193) time: 4.0437 data: 0.0036 max mem: 19788 +Epoch: [38] [ 510/2138] eta: 1:49:51 lr: 3.008136669846453e-06 loss: 0.0189 (0.0193) time: 4.0370 data: 0.0037 max mem: 19788 +Epoch: [38] [ 520/2138] eta: 1:49:10 lr: 3.0009449490184385e-06 loss: 0.0194 (0.0193) time: 4.0339 data: 0.0033 max mem: 19788 +Epoch: [38] [ 530/2138] eta: 1:48:29 lr: 2.9937513126944358e-06 loss: 0.0182 (0.0193) time: 4.0325 data: 0.0033 max mem: 19788 +Epoch: [38] [ 540/2138] eta: 1:47:49 lr: 2.986555755247377e-06 loss: 0.0167 (0.0193) time: 4.0415 data: 0.0035 max mem: 19788 +Epoch: [38] [ 550/2138] eta: 1:47:08 lr: 2.9793582710185785e-06 loss: 0.0187 (0.0193) time: 4.0365 data: 0.0035 max mem: 19788 +Epoch: [38] [ 560/2138] eta: 1:46:27 lr: 2.9721588543174245e-06 loss: 0.0182 (0.0193) time: 4.0319 data: 0.0034 max mem: 19788 +Epoch: [38] [ 570/2138] eta: 1:45:46 lr: 2.964957499421153e-06 loss: 0.0168 (0.0193) time: 4.0375 data: 0.0035 max mem: 19788 +Epoch: [38] [ 580/2138] eta: 1:45:05 lr: 2.9577542005745346e-06 loss: 0.0184 (0.0193) time: 4.0313 data: 0.0036 max mem: 19788 +Epoch: [38] [ 590/2138] eta: 1:44:24 lr: 2.9505489519896536e-06 loss: 0.0186 (0.0193) time: 4.0328 data: 0.0035 max mem: 19788 +Epoch: [38] [ 600/2138] eta: 1:43:44 lr: 2.943341747845578e-06 loss: 0.0175 (0.0193) time: 4.0389 data: 0.0036 max mem: 19788 +Epoch: [38] [ 610/2138] eta: 1:43:03 lr: 2.936132582288136e-06 loss: 0.0187 (0.0193) time: 4.0380 data: 0.0033 max mem: 19788 +Epoch: [38] [ 620/2138] eta: 1:42:22 lr: 2.92892144942958e-06 loss: 0.0200 (0.0193) time: 4.0332 data: 0.0034 max mem: 19788 +Epoch: [38] [ 630/2138] eta: 1:41:42 lr: 2.9217083433483573e-06 loss: 0.0175 (0.0193) time: 4.0413 data: 0.0033 max mem: 19788 +Epoch: [38] [ 640/2138] eta: 1:41:02 lr: 2.9144932580887666e-06 loss: 0.0175 (0.0193) time: 4.0521 data: 0.0033 max mem: 19788 +Epoch: [38] [ 650/2138] eta: 1:40:21 lr: 2.9072761876607215e-06 loss: 0.0182 (0.0193) time: 4.0475 data: 0.0037 max mem: 19788 +Epoch: [38] [ 660/2138] eta: 1:39:42 lr: 2.900057126039403e-06 loss: 0.0182 (0.0193) time: 4.0717 data: 0.0036 max mem: 19788 +Epoch: [38] [ 670/2138] eta: 1:39:01 lr: 2.892836067165015e-06 loss: 0.0182 (0.0193) time: 4.0769 data: 0.0034 max mem: 19788 +Epoch: [38] [ 680/2138] eta: 1:38:22 lr: 2.8856130049424297e-06 loss: 0.0198 (0.0193) time: 4.0729 data: 0.0032 max mem: 19788 +Epoch: [38] [ 690/2138] eta: 1:37:41 lr: 2.878387933240937e-06 loss: 0.0189 (0.0193) time: 4.0669 data: 0.0032 max mem: 19788 +Epoch: [38] [ 700/2138] eta: 1:37:01 lr: 2.871160845893881e-06 loss: 0.0192 (0.0193) time: 4.0454 data: 0.0035 max mem: 19788 +Epoch: [38] [ 710/2138] eta: 1:36:20 lr: 2.863931736698407e-06 loss: 0.0202 (0.0193) time: 4.0491 data: 0.0034 max mem: 19788 +Epoch: [38] [ 720/2138] eta: 1:35:40 lr: 2.856700599415087e-06 loss: 0.0170 (0.0193) time: 4.0499 data: 0.0032 max mem: 19788 +Epoch: [38] [ 730/2138] eta: 1:34:59 lr: 2.8494674277676576e-06 loss: 0.0188 (0.0193) time: 4.0507 data: 0.0032 max mem: 19788 +Epoch: [38] [ 740/2138] eta: 1:34:19 lr: 2.842232215442644e-06 loss: 0.0170 (0.0193) time: 4.0414 data: 0.0031 max mem: 19788 +Epoch: [38] [ 750/2138] eta: 1:33:38 lr: 2.8349949560890866e-06 loss: 0.0170 (0.0193) time: 4.0450 data: 0.0033 max mem: 19788 +Epoch: [38] [ 760/2138] eta: 1:32:57 lr: 2.8277556433181587e-06 loss: 0.0194 (0.0193) time: 4.0397 data: 0.0034 max mem: 19788 +Epoch: [38] [ 770/2138] eta: 1:32:17 lr: 2.820514270702885e-06 loss: 0.0201 (0.0193) time: 4.0298 data: 0.0032 max mem: 19788 +Epoch: [38] [ 780/2138] eta: 1:31:36 lr: 2.8132708317777575e-06 loss: 0.0204 (0.0193) time: 4.0375 data: 0.0032 max mem: 19788 +Epoch: [38] [ 790/2138] eta: 1:30:56 lr: 2.8060253200384136e-06 loss: 0.0179 (0.0193) time: 4.0492 data: 0.0032 max mem: 19788 +Epoch: [38] [ 800/2138] eta: 1:30:15 lr: 2.7987777289413123e-06 loss: 0.0172 (0.0193) time: 4.0538 data: 0.0033 max mem: 19788 +Epoch: [38] [ 810/2138] eta: 1:29:35 lr: 2.791528051903334e-06 loss: 0.0168 (0.0193) time: 4.0505 data: 0.0036 max mem: 19788 +Epoch: [38] [ 820/2138] eta: 1:28:54 lr: 2.7842762823014843e-06 loss: 0.0168 (0.0193) time: 4.0479 data: 0.0035 max mem: 19788 +Epoch: [38] [ 830/2138] eta: 1:28:14 lr: 2.7770224134724794e-06 loss: 0.0161 (0.0193) time: 4.0439 data: 0.0034 max mem: 19788 +Epoch: [38] [ 840/2138] eta: 1:27:33 lr: 2.769766438712439e-06 loss: 0.0157 (0.0193) time: 4.0433 data: 0.0033 max mem: 19788 +Epoch: [38] [ 850/2138] eta: 1:26:53 lr: 2.762508351276464e-06 loss: 0.0163 (0.0192) time: 4.0516 data: 0.0032 max mem: 19788 +Epoch: [38] [ 860/2138] eta: 1:26:12 lr: 2.755248144378323e-06 loss: 0.0181 (0.0192) time: 4.0531 data: 0.0034 max mem: 19788 +Epoch: [38] [ 870/2138] eta: 1:25:32 lr: 2.7479858111900175e-06 loss: 0.0200 (0.0192) time: 4.0473 data: 0.0032 max mem: 19788 +Epoch: [38] [ 880/2138] eta: 1:24:52 lr: 2.74072134484146e-06 loss: 0.0194 (0.0192) time: 4.0472 data: 0.0031 max mem: 19788 +Epoch: [38] [ 890/2138] eta: 1:24:11 lr: 2.7334547384200353e-06 loss: 0.0186 (0.0192) time: 4.0466 data: 0.0033 max mem: 19788 +Epoch: [38] [ 900/2138] eta: 1:23:30 lr: 2.7261859849702617e-06 loss: 0.0192 (0.0193) time: 4.0401 data: 0.0033 max mem: 19788 +Epoch: [38] [ 910/2138] eta: 1:22:50 lr: 2.7189150774933466e-06 loss: 0.0188 (0.0193) time: 4.0399 data: 0.0031 max mem: 19788 +Epoch: [38] [ 920/2138] eta: 1:22:09 lr: 2.71164200894684e-06 loss: 0.0178 (0.0193) time: 4.0470 data: 0.0034 max mem: 19788 +Epoch: [38] [ 930/2138] eta: 1:21:29 lr: 2.704366772244178e-06 loss: 0.0171 (0.0193) time: 4.0394 data: 0.0034 max mem: 19788 +Epoch: [38] [ 940/2138] eta: 1:20:48 lr: 2.6970893602543266e-06 loss: 0.0196 (0.0193) time: 4.0384 data: 0.0032 max mem: 19788 +Epoch: [38] [ 950/2138] eta: 1:20:08 lr: 2.6898097658013137e-06 loss: 0.0208 (0.0193) time: 4.0468 data: 0.0032 max mem: 19788 +Epoch: [38] [ 960/2138] eta: 1:19:27 lr: 2.682527981663867e-06 loss: 0.0199 (0.0193) time: 4.0509 data: 0.0031 max mem: 19788 +Epoch: [38] [ 970/2138] eta: 1:18:47 lr: 2.675244000574934e-06 loss: 0.0183 (0.0193) time: 4.0499 data: 0.0033 max mem: 19788 +Epoch: [38] [ 980/2138] eta: 1:18:06 lr: 2.6679578152213065e-06 loss: 0.0165 (0.0193) time: 4.0393 data: 0.0033 max mem: 19788 +Epoch: [38] [ 990/2138] eta: 1:17:26 lr: 2.660669418243133e-06 loss: 0.0178 (0.0193) time: 4.0383 data: 0.0034 max mem: 19788 +Epoch: [38] [1000/2138] eta: 1:16:45 lr: 2.653378802233533e-06 loss: 0.0197 (0.0193) time: 4.0414 data: 0.0035 max mem: 19788 +Epoch: [38] [1010/2138] eta: 1:16:05 lr: 2.646085959738096e-06 loss: 0.0186 (0.0193) time: 4.0379 data: 0.0034 max mem: 19788 +Epoch: [38] [1020/2138] eta: 1:15:24 lr: 2.6387908832544865e-06 loss: 0.0166 (0.0193) time: 4.0438 data: 0.0035 max mem: 19788 +Epoch: [38] [1030/2138] eta: 1:14:44 lr: 2.6314935652319307e-06 loss: 0.0166 (0.0193) time: 4.0486 data: 0.0034 max mem: 19788 +Epoch: [38] [1040/2138] eta: 1:14:03 lr: 2.624193998070811e-06 loss: 0.0172 (0.0193) time: 4.0473 data: 0.0032 max mem: 19788 +Epoch: [38] [1050/2138] eta: 1:13:23 lr: 2.61689217412214e-06 loss: 0.0176 (0.0193) time: 4.0491 data: 0.0036 max mem: 19788 +Epoch: [38] [1060/2138] eta: 1:12:42 lr: 2.609588085687144e-06 loss: 0.0176 (0.0193) time: 4.0536 data: 0.0038 max mem: 19788 +Epoch: [38] [1070/2138] eta: 1:12:02 lr: 2.602281725016732e-06 loss: 0.0174 (0.0192) time: 4.0480 data: 0.0036 max mem: 19788 +Epoch: [38] [1080/2138] eta: 1:11:21 lr: 2.594973084311031e-06 loss: 0.0158 (0.0192) time: 4.0447 data: 0.0034 max mem: 19788 +Epoch: [38] [1090/2138] eta: 1:10:41 lr: 2.5876621557189144e-06 loss: 0.0164 (0.0192) time: 4.0466 data: 0.0033 max mem: 19788 +Epoch: [38] [1100/2138] eta: 1:10:00 lr: 2.5803489313374527e-06 loss: 0.0212 (0.0193) time: 4.0476 data: 0.0032 max mem: 19788 +Epoch: [38] [1110/2138] eta: 1:09:20 lr: 2.5730334032114655e-06 loss: 0.0191 (0.0193) time: 4.0483 data: 0.0033 max mem: 19788 +Epoch: [38] [1120/2138] eta: 1:08:39 lr: 2.5657155633329522e-06 loss: 0.0182 (0.0193) time: 4.0439 data: 0.0034 max mem: 19788 +Epoch: [38] [1130/2138] eta: 1:07:59 lr: 2.558395403640629e-06 loss: 0.0207 (0.0193) time: 4.0441 data: 0.0035 max mem: 19788 +Epoch: [38] [1140/2138] eta: 1:07:18 lr: 2.551072916019349e-06 loss: 0.0189 (0.0193) time: 4.0451 data: 0.0034 max mem: 19788 +Epoch: [38] [1150/2138] eta: 1:06:38 lr: 2.543748092299623e-06 loss: 0.0174 (0.0193) time: 4.0355 data: 0.0031 max mem: 19788 +Epoch: [38] [1160/2138] eta: 1:05:57 lr: 2.5364209242570267e-06 loss: 0.0168 (0.0192) time: 4.0301 data: 0.0031 max mem: 19788 +Epoch: [38] [1170/2138] eta: 1:05:17 lr: 2.5290914036117097e-06 loss: 0.0182 (0.0192) time: 4.0298 data: 0.0032 max mem: 19788 +Epoch: [38] [1180/2138] eta: 1:04:36 lr: 2.521759522027784e-06 loss: 0.0185 (0.0192) time: 4.0340 data: 0.0032 max mem: 19788 +Epoch: [38] [1190/2138] eta: 1:03:56 lr: 2.5144252711128213e-06 loss: 0.0194 (0.0192) time: 4.0492 data: 0.0033 max mem: 19788 +Epoch: [38] [1200/2138] eta: 1:03:15 lr: 2.5070886424172258e-06 loss: 0.0204 (0.0193) time: 4.0481 data: 0.0034 max mem: 19788 +Epoch: [38] [1210/2138] eta: 1:02:35 lr: 2.499749627433717e-06 loss: 0.0192 (0.0193) time: 4.0321 data: 0.0031 max mem: 19788 +Epoch: [38] [1220/2138] eta: 1:01:54 lr: 2.4924082175966874e-06 loss: 0.0192 (0.0193) time: 4.0270 data: 0.0031 max mem: 19788 +Epoch: [38] [1230/2138] eta: 1:01:13 lr: 2.485064404281669e-06 loss: 0.0192 (0.0193) time: 4.0338 data: 0.0033 max mem: 19788 +Epoch: [38] [1240/2138] eta: 1:00:33 lr: 2.4777181788046755e-06 loss: 0.0167 (0.0193) time: 4.0478 data: 0.0034 max mem: 19788 +Epoch: [38] [1250/2138] eta: 0:59:53 lr: 2.4703695324216514e-06 loss: 0.0181 (0.0193) time: 4.0510 data: 0.0032 max mem: 19788 +Epoch: [38] [1260/2138] eta: 0:59:12 lr: 2.4630184563278013e-06 loss: 0.0175 (0.0193) time: 4.0370 data: 0.0032 max mem: 19788 +Epoch: [38] [1270/2138] eta: 0:58:31 lr: 2.4556649416570204e-06 loss: 0.0160 (0.0193) time: 4.0315 data: 0.0033 max mem: 19788 +Epoch: [38] [1280/2138] eta: 0:57:51 lr: 2.448308979481204e-06 loss: 0.0167 (0.0193) time: 4.0298 data: 0.0032 max mem: 19788 +Epoch: [38] [1290/2138] eta: 0:57:10 lr: 2.440950560809666e-06 loss: 0.0176 (0.0193) time: 4.0286 data: 0.0033 max mem: 19788 +Epoch: [38] [1300/2138] eta: 0:56:30 lr: 2.433589676588428e-06 loss: 0.0165 (0.0193) time: 4.0303 data: 0.0032 max mem: 19788 +Epoch: [38] [1310/2138] eta: 0:55:49 lr: 2.4262263176996194e-06 loss: 0.0182 (0.0193) time: 4.0306 data: 0.0033 max mem: 19788 +Epoch: [38] [1320/2138] eta: 0:55:09 lr: 2.4188604749607524e-06 loss: 0.0189 (0.0193) time: 4.0358 data: 0.0033 max mem: 19788 +Epoch: [38] [1330/2138] eta: 0:54:28 lr: 2.411492139124098e-06 loss: 0.0188 (0.0193) time: 4.0478 data: 0.0031 max mem: 19788 +Epoch: [38] [1340/2138] eta: 0:53:48 lr: 2.4041213008759453e-06 loss: 0.0183 (0.0193) time: 4.0477 data: 0.0032 max mem: 19788 +Epoch: [38] [1350/2138] eta: 0:53:07 lr: 2.39674795083596e-06 loss: 0.0197 (0.0193) time: 4.0354 data: 0.0034 max mem: 19788 +Epoch: [38] [1360/2138] eta: 0:52:27 lr: 2.3893720795564214e-06 loss: 0.0201 (0.0193) time: 4.0353 data: 0.0034 max mem: 19788 +Epoch: [38] [1370/2138] eta: 0:51:46 lr: 2.3819936775215627e-06 loss: 0.0194 (0.0193) time: 4.0435 data: 0.0035 max mem: 19788 +Epoch: [38] [1380/2138] eta: 0:51:06 lr: 2.3746127351467957e-06 loss: 0.0186 (0.0193) time: 4.0487 data: 0.0034 max mem: 19788 +Epoch: [38] [1390/2138] eta: 0:50:25 lr: 2.3672292427779925e-06 loss: 0.0184 (0.0193) time: 4.0435 data: 0.0031 max mem: 19788 +Epoch: [38] [1400/2138] eta: 0:49:45 lr: 2.359843190690763e-06 loss: 0.0189 (0.0193) time: 4.0411 data: 0.0032 max mem: 19788 +Epoch: [38] [1410/2138] eta: 0:49:04 lr: 2.3524545690896446e-06 loss: 0.0175 (0.0193) time: 4.0414 data: 0.0034 max mem: 19788 +Epoch: [38] [1420/2138] eta: 0:48:24 lr: 2.3450633681073914e-06 loss: 0.0175 (0.0193) time: 4.0440 data: 0.0034 max mem: 19788 +Epoch: [38] [1430/2138] eta: 0:47:44 lr: 2.3376695778041364e-06 loss: 0.0203 (0.0193) time: 4.0378 data: 0.0034 max mem: 19788 +Epoch: [38] [1440/2138] eta: 0:47:03 lr: 2.3302731881666593e-06 loss: 0.0177 (0.0193) time: 4.0278 data: 0.0034 max mem: 19788 +Epoch: [38] [1450/2138] eta: 0:46:22 lr: 2.322874189107524e-06 loss: 0.0201 (0.0193) time: 4.0335 data: 0.0032 max mem: 19788 +Epoch: [38] [1460/2138] eta: 0:45:42 lr: 2.3154725704643247e-06 loss: 0.0202 (0.0193) time: 4.0371 data: 0.0033 max mem: 19788 +Epoch: [38] [1470/2138] eta: 0:45:01 lr: 2.3080683219988006e-06 loss: 0.0188 (0.0193) time: 4.0318 data: 0.0039 max mem: 19788 +Epoch: [38] [1480/2138] eta: 0:44:21 lr: 2.3006614333960544e-06 loss: 0.0196 (0.0194) time: 4.0287 data: 0.0037 max mem: 19788 +Epoch: [38] [1490/2138] eta: 0:43:40 lr: 2.293251894263647e-06 loss: 0.0206 (0.0194) time: 4.0324 data: 0.0033 max mem: 19788 +Epoch: [38] [1500/2138] eta: 0:43:00 lr: 2.285839694130789e-06 loss: 0.0188 (0.0194) time: 4.0370 data: 0.0032 max mem: 19788 +Epoch: [38] [1510/2138] eta: 0:42:20 lr: 2.2784248224474105e-06 loss: 0.0193 (0.0194) time: 4.0383 data: 0.0032 max mem: 19788 +Epoch: [38] [1520/2138] eta: 0:41:39 lr: 2.2710072685833262e-06 loss: 0.0198 (0.0194) time: 4.0390 data: 0.0034 max mem: 19788 +Epoch: [38] [1530/2138] eta: 0:40:59 lr: 2.2635870218272815e-06 loss: 0.0175 (0.0194) time: 4.0356 data: 0.0034 max mem: 19788 +Epoch: [38] [1540/2138] eta: 0:40:18 lr: 2.2561640713860873e-06 loss: 0.0167 (0.0194) time: 4.0292 data: 0.0033 max mem: 19788 +Epoch: [38] [1550/2138] eta: 0:39:38 lr: 2.2487384063836402e-06 loss: 0.0163 (0.0193) time: 4.0301 data: 0.0030 max mem: 19788 +Epoch: [38] [1560/2138] eta: 0:38:57 lr: 2.2413100158600316e-06 loss: 0.0170 (0.0193) time: 4.0402 data: 0.0030 max mem: 19788 +Epoch: [38] [1570/2138] eta: 0:38:17 lr: 2.233878888770537e-06 loss: 0.0177 (0.0194) time: 4.0353 data: 0.0032 max mem: 19788 +Epoch: [38] [1580/2138] eta: 0:37:36 lr: 2.2264450139846988e-06 loss: 0.0187 (0.0194) time: 4.0304 data: 0.0032 max mem: 19788 +Epoch: [38] [1590/2138] eta: 0:36:56 lr: 2.219008380285283e-06 loss: 0.0188 (0.0194) time: 4.0437 data: 0.0030 max mem: 19788 +Epoch: [38] [1600/2138] eta: 0:36:15 lr: 2.2115689763673347e-06 loss: 0.0203 (0.0194) time: 4.0390 data: 0.0032 max mem: 19788 +Epoch: [38] [1610/2138] eta: 0:35:35 lr: 2.204126790837105e-06 loss: 0.0175 (0.0194) time: 4.0304 data: 0.0033 max mem: 19788 +Epoch: [38] [1620/2138] eta: 0:34:54 lr: 2.1966818122110723e-06 loss: 0.0171 (0.0194) time: 4.0310 data: 0.0032 max mem: 19788 +Epoch: [38] [1630/2138] eta: 0:34:14 lr: 2.1892340289148412e-06 loss: 0.0191 (0.0194) time: 4.0441 data: 0.0031 max mem: 19788 +Epoch: [38] [1640/2138] eta: 0:33:33 lr: 2.1817834292821292e-06 loss: 0.0185 (0.0194) time: 4.0539 data: 0.0033 max mem: 19788 +Epoch: [38] [1650/2138] eta: 0:32:53 lr: 2.174330001553633e-06 loss: 0.0175 (0.0194) time: 4.0527 data: 0.0032 max mem: 19788 +Epoch: [38] [1660/2138] eta: 0:32:13 lr: 2.1668737338759835e-06 loss: 0.0161 (0.0193) time: 4.0523 data: 0.0031 max mem: 19788 +Epoch: [38] [1670/2138] eta: 0:31:32 lr: 2.159414614300575e-06 loss: 0.0160 (0.0193) time: 4.0497 data: 0.0032 max mem: 19788 +Epoch: [38] [1680/2138] eta: 0:30:52 lr: 2.151952630782488e-06 loss: 0.0188 (0.0193) time: 4.0518 data: 0.0033 max mem: 19788 +Epoch: [38] [1690/2138] eta: 0:30:11 lr: 2.1444877711792904e-06 loss: 0.0191 (0.0193) time: 4.0539 data: 0.0033 max mem: 19788 +Epoch: [38] [1700/2138] eta: 0:29:31 lr: 2.1370200232498852e-06 loss: 0.0170 (0.0193) time: 4.0428 data: 0.0032 max mem: 19788 +Epoch: [38] [1710/2138] eta: 0:28:50 lr: 2.1295493746533486e-06 loss: 0.0170 (0.0193) time: 4.0335 data: 0.0032 max mem: 19788 +Epoch: [38] [1720/2138] eta: 0:28:10 lr: 2.12207581294767e-06 loss: 0.0187 (0.0193) time: 4.0285 data: 0.0031 max mem: 19788 +Epoch: [38] [1730/2138] eta: 0:27:29 lr: 2.1145993255885833e-06 loss: 0.0191 (0.0193) time: 4.0340 data: 0.0030 max mem: 19788 +Epoch: [38] [1740/2138] eta: 0:26:49 lr: 2.107119899928264e-06 loss: 0.0184 (0.0193) time: 4.0453 data: 0.0031 max mem: 19788 +Epoch: [38] [1750/2138] eta: 0:26:09 lr: 2.0996375232141207e-06 loss: 0.0184 (0.0193) time: 4.0416 data: 0.0032 max mem: 19788 +Epoch: [38] [1760/2138] eta: 0:25:28 lr: 2.0921521825874496e-06 loss: 0.0201 (0.0193) time: 4.0371 data: 0.0032 max mem: 19788 +Epoch: [38] [1770/2138] eta: 0:24:48 lr: 2.0846638650821845e-06 loss: 0.0184 (0.0193) time: 4.0426 data: 0.0033 max mem: 19788 +Epoch: [38] [1780/2138] eta: 0:24:07 lr: 2.077172557623511e-06 loss: 0.0184 (0.0193) time: 4.0515 data: 0.0032 max mem: 19788 +Epoch: [38] [1790/2138] eta: 0:23:27 lr: 2.0696782470265717e-06 loss: 0.0181 (0.0193) time: 4.0507 data: 0.0032 max mem: 19788 +Epoch: [38] [1800/2138] eta: 0:22:46 lr: 2.0621809199950353e-06 loss: 0.0163 (0.0193) time: 4.0487 data: 0.0033 max mem: 19788 +Epoch: [38] [1810/2138] eta: 0:22:06 lr: 2.0546805631197585e-06 loss: 0.0172 (0.0193) time: 4.0508 data: 0.0033 max mem: 19788 +Epoch: [38] [1820/2138] eta: 0:21:26 lr: 2.0471771628773097e-06 loss: 0.0193 (0.0193) time: 4.0501 data: 0.0033 max mem: 19788 +Epoch: [38] [1830/2138] eta: 0:20:45 lr: 2.0396707056285815e-06 loss: 0.0186 (0.0193) time: 4.0491 data: 0.0031 max mem: 19788 +Epoch: [38] [1840/2138] eta: 0:20:05 lr: 2.0321611776172675e-06 loss: 0.0199 (0.0194) time: 4.0442 data: 0.0031 max mem: 19788 +Epoch: [38] [1850/2138] eta: 0:19:24 lr: 2.0246485649684276e-06 loss: 0.0209 (0.0194) time: 4.0374 data: 0.0032 max mem: 19788 +Epoch: [38] [1860/2138] eta: 0:18:44 lr: 2.0171328536869126e-06 loss: 0.0209 (0.0194) time: 4.0388 data: 0.0033 max mem: 19788 +Epoch: [38] [1870/2138] eta: 0:18:03 lr: 2.0096140296558785e-06 loss: 0.0196 (0.0194) time: 4.0417 data: 0.0033 max mem: 19788 +Epoch: [38] [1880/2138] eta: 0:17:23 lr: 2.0020920786351613e-06 loss: 0.0181 (0.0194) time: 4.0419 data: 0.0032 max mem: 19788 +Epoch: [38] [1890/2138] eta: 0:16:42 lr: 1.994566986259736e-06 loss: 0.0170 (0.0194) time: 4.0418 data: 0.0033 max mem: 19788 +Epoch: [38] [1900/2138] eta: 0:16:02 lr: 1.987038738038038e-06 loss: 0.0159 (0.0194) time: 4.0333 data: 0.0034 max mem: 19788 +Epoch: [38] [1910/2138] eta: 0:15:22 lr: 1.9795073193503657e-06 loss: 0.0166 (0.0194) time: 4.0235 data: 0.0034 max mem: 19788 +Epoch: [38] [1920/2138] eta: 0:14:41 lr: 1.9719727154471463e-06 loss: 0.0180 (0.0194) time: 4.0280 data: 0.0031 max mem: 19788 +Epoch: [38] [1930/2138] eta: 0:14:01 lr: 1.9644349114472807e-06 loss: 0.0191 (0.0194) time: 4.0337 data: 0.0030 max mem: 19788 +Epoch: [38] [1940/2138] eta: 0:13:20 lr: 1.956893892336349e-06 loss: 0.0195 (0.0194) time: 4.0314 data: 0.0031 max mem: 19788 +Epoch: [38] [1950/2138] eta: 0:12:40 lr: 1.9493496429648946e-06 loss: 0.0188 (0.0194) time: 4.0401 data: 0.0031 max mem: 19788 +Epoch: [38] [1960/2138] eta: 0:11:59 lr: 1.94180214804657e-06 loss: 0.0188 (0.0194) time: 4.0527 data: 0.0030 max mem: 19788 +Epoch: [38] [1970/2138] eta: 0:11:19 lr: 1.9342513921563565e-06 loss: 0.0179 (0.0194) time: 4.0495 data: 0.0033 max mem: 19788 +Epoch: [38] [1980/2138] eta: 0:10:38 lr: 1.926697359728645e-06 loss: 0.0156 (0.0194) time: 4.0398 data: 0.0035 max mem: 19788 +Epoch: [38] [1990/2138] eta: 0:09:58 lr: 1.9191400350553918e-06 loss: 0.0166 (0.0193) time: 4.0290 data: 0.0033 max mem: 19788 +Epoch: [38] [2000/2138] eta: 0:09:18 lr: 1.911579402284135e-06 loss: 0.0183 (0.0194) time: 4.0299 data: 0.0032 max mem: 19788 +Epoch: [38] [2010/2138] eta: 0:08:37 lr: 1.9040154454160506e-06 loss: 0.0205 (0.0194) time: 4.0311 data: 0.0031 max mem: 19788 +Epoch: [38] [2020/2138] eta: 0:07:57 lr: 1.8964481483039666e-06 loss: 0.0188 (0.0194) time: 4.0272 data: 0.0032 max mem: 19788 +Epoch: [38] [2030/2138] eta: 0:07:16 lr: 1.8888774946502752e-06 loss: 0.0188 (0.0194) time: 4.0337 data: 0.0034 max mem: 19788 +Epoch: [38] [2040/2138] eta: 0:06:36 lr: 1.8813034680049136e-06 loss: 0.0192 (0.0194) time: 4.0443 data: 0.0032 max mem: 19788 +Epoch: [38] [2050/2138] eta: 0:05:55 lr: 1.8737260517631872e-06 loss: 0.0192 (0.0194) time: 4.0504 data: 0.0030 max mem: 19788 +Epoch: [38] [2060/2138] eta: 0:05:15 lr: 1.8661452291636773e-06 loss: 0.0188 (0.0194) time: 4.0552 data: 0.0031 max mem: 19788 +Epoch: [38] [2070/2138] eta: 0:04:34 lr: 1.8585609832859862e-06 loss: 0.0163 (0.0194) time: 4.0547 data: 0.0031 max mem: 19788 +Epoch: [38] [2080/2138] eta: 0:03:54 lr: 1.8509732970485593e-06 loss: 0.0175 (0.0194) time: 4.0361 data: 0.0032 max mem: 19788 +Epoch: [38] [2090/2138] eta: 0:03:14 lr: 1.8433821532063533e-06 loss: 0.0186 (0.0194) time: 4.0248 data: 0.0034 max mem: 19788 +Epoch: [38] [2100/2138] eta: 0:02:33 lr: 1.8357875343485712e-06 loss: 0.0180 (0.0193) time: 4.0275 data: 0.0034 max mem: 19788 +Epoch: [38] [2110/2138] eta: 0:01:53 lr: 1.8281894228962427e-06 loss: 0.0201 (0.0194) time: 4.0331 data: 0.0035 max mem: 19788 +Epoch: [38] [2120/2138] eta: 0:01:12 lr: 1.8205878010998733e-06 loss: 0.0224 (0.0194) time: 4.0332 data: 0.0034 max mem: 19788 +Epoch: [38] [2130/2138] eta: 0:00:32 lr: 1.8129826510369329e-06 loss: 0.0204 (0.0194) time: 4.0175 data: 0.0031 max mem: 19788 +Epoch: [38] Total time: 2:24:05 +Test: [ 0/21770] eta: 19:00:42 time: 3.1439 data: 3.0500 max mem: 19788 +Test: [ 100/21770] eta: 0:36:26 time: 0.0715 data: 0.0021 max mem: 19788 +Test: [ 200/21770] eta: 0:31:30 time: 0.0831 data: 0.0024 max mem: 19788 +Test: [ 300/21770] eta: 0:29:16 time: 0.0642 data: 0.0021 max mem: 19788 +Test: [ 400/21770] eta: 0:28:24 time: 0.0838 data: 0.0026 max mem: 19788 +Test: [ 500/21770] eta: 0:28:02 time: 0.0706 data: 0.0022 max mem: 19788 +Test: [ 600/21770] eta: 0:27:14 time: 0.0715 data: 0.0021 max mem: 19788 +Test: [ 700/21770] eta: 0:26:58 time: 0.0785 data: 0.0022 max mem: 19788 +Test: [ 800/21770] eta: 0:26:20 time: 0.0655 data: 0.0020 max mem: 19788 +Test: [ 900/21770] eta: 0:26:00 time: 0.0752 data: 0.0022 max mem: 19788 +Test: [ 1000/21770] eta: 0:25:36 time: 0.0729 data: 0.0019 max mem: 19788 +Test: [ 1100/21770] eta: 0:25:22 time: 0.0736 data: 0.0023 max mem: 19788 +Test: [ 1200/21770] eta: 0:25:18 time: 0.0764 data: 0.0023 max mem: 19788 +Test: [ 1300/21770] eta: 0:25:05 time: 0.0806 data: 0.0024 max mem: 19788 +Test: [ 1400/21770] eta: 0:24:51 time: 0.0683 data: 0.0019 max mem: 19788 +Test: [ 1500/21770] eta: 0:24:30 time: 0.0617 data: 0.0020 max mem: 19788 +Test: [ 1600/21770] eta: 0:24:19 time: 0.0762 data: 0.0023 max mem: 19788 +Test: [ 1700/21770] eta: 0:24:09 time: 0.0671 data: 0.0019 max mem: 19788 +Test: [ 1800/21770] eta: 0:23:59 time: 0.0721 data: 0.0020 max mem: 19788 +Test: [ 1900/21770] eta: 0:23:53 time: 0.0768 data: 0.0023 max mem: 19788 +Test: [ 2000/21770] eta: 0:23:45 time: 0.0664 data: 0.0019 max mem: 19788 +Test: [ 2100/21770] eta: 0:23:35 time: 0.0629 data: 0.0019 max mem: 19788 +Test: [ 2200/21770] eta: 0:23:21 time: 0.0625 data: 0.0021 max mem: 19788 +Test: [ 2300/21770] eta: 0:23:10 time: 0.0670 data: 0.0020 max mem: 19788 +Test: [ 2400/21770] eta: 0:23:03 time: 0.0661 data: 0.0019 max mem: 19788 +Test: [ 2500/21770] eta: 0:22:53 time: 0.0668 data: 0.0020 max mem: 19788 +Test: [ 2600/21770] eta: 0:22:47 time: 0.0720 data: 0.0023 max mem: 19788 +Test: [ 2700/21770] eta: 0:22:40 time: 0.0843 data: 0.0027 max mem: 19788 +Test: [ 2800/21770] eta: 0:22:40 time: 0.0868 data: 0.0027 max mem: 19788 +Test: [ 2900/21770] eta: 0:22:30 time: 0.0667 data: 0.0022 max mem: 19788 +Test: [ 3000/21770] eta: 0:22:18 time: 0.0643 data: 0.0019 max mem: 19788 +Test: [ 3100/21770] eta: 0:22:11 time: 0.0651 data: 0.0024 max mem: 19788 +Test: [ 3200/21770] eta: 0:22:02 time: 0.0682 data: 0.0022 max mem: 19788 +Test: [ 3300/21770] eta: 0:21:55 time: 0.0772 data: 0.0022 max mem: 19788 +Test: [ 3400/21770] eta: 0:21:48 time: 0.0636 data: 0.0021 max mem: 19788 +Test: [ 3500/21770] eta: 0:21:39 time: 0.0623 data: 0.0018 max mem: 19788 +Test: [ 3600/21770] eta: 0:21:31 time: 0.0682 data: 0.0021 max mem: 19788 +Test: [ 3700/21770] eta: 0:21:27 time: 0.0832 data: 0.0025 max mem: 19788 +Test: [ 3800/21770] eta: 0:21:22 time: 0.0721 data: 0.0021 max mem: 19788 +Test: [ 3900/21770] eta: 0:21:15 time: 0.0670 data: 0.0020 max mem: 19788 +Test: [ 4000/21770] eta: 0:21:09 time: 0.0772 data: 0.0023 max mem: 19788 +Test: [ 4100/21770] eta: 0:21:04 time: 0.0741 data: 0.0020 max mem: 19788 +Test: [ 4200/21770] eta: 0:20:57 time: 0.0654 data: 0.0019 max mem: 19788 +Test: [ 4300/21770] eta: 0:20:50 time: 0.0785 data: 0.0024 max mem: 19788 +Test: [ 4400/21770] eta: 0:20:43 time: 0.0720 data: 0.0020 max mem: 19788 +Test: [ 4500/21770] eta: 0:20:35 time: 0.0680 data: 0.0020 max mem: 19788 +Test: [ 4600/21770] eta: 0:20:25 time: 0.0642 data: 0.0019 max mem: 19788 +Test: [ 4700/21770] eta: 0:20:17 time: 0.0825 data: 0.0020 max mem: 19788 +Test: [ 4800/21770] eta: 0:20:13 time: 0.0814 data: 0.0024 max mem: 19788 +Test: [ 4900/21770] eta: 0:20:04 time: 0.0781 data: 0.0020 max mem: 19788 +Test: [ 5000/21770] eta: 0:19:58 time: 0.0823 data: 0.0023 max mem: 19788 +Test: [ 5100/21770] eta: 0:19:53 time: 0.0830 data: 0.0024 max mem: 19788 +Test: [ 5200/21770] eta: 0:19:46 time: 0.0719 data: 0.0021 max mem: 19788 +Test: [ 5300/21770] eta: 0:19:39 time: 0.0822 data: 0.0024 max mem: 19788 +Test: [ 5400/21770] eta: 0:19:32 time: 0.0777 data: 0.0020 max mem: 19788 +Test: [ 5500/21770] eta: 0:19:24 time: 0.0690 data: 0.0019 max mem: 19788 +Test: [ 5600/21770] eta: 0:19:17 time: 0.0728 data: 0.0025 max mem: 19788 +Test: [ 5700/21770] eta: 0:19:10 time: 0.0664 data: 0.0018 max mem: 19788 +Test: [ 5800/21770] eta: 0:19:02 time: 0.0673 data: 0.0020 max mem: 19788 +Test: [ 5900/21770] eta: 0:18:54 time: 0.0693 data: 0.0021 max mem: 19788 +Test: [ 6000/21770] eta: 0:18:47 time: 0.0662 data: 0.0021 max mem: 19788 +Test: [ 6100/21770] eta: 0:18:39 time: 0.0634 data: 0.0022 max mem: 19788 +Test: [ 6200/21770] eta: 0:18:32 time: 0.0673 data: 0.0021 max mem: 19788 +Test: [ 6300/21770] eta: 0:18:26 time: 0.0835 data: 0.0025 max mem: 19788 +Test: [ 6400/21770] eta: 0:18:18 time: 0.0653 data: 0.0020 max mem: 19788 +Test: [ 6500/21770] eta: 0:18:10 time: 0.0642 data: 0.0019 max mem: 19788 +Test: [ 6600/21770] eta: 0:18:02 time: 0.0711 data: 0.0020 max mem: 19788 +Test: [ 6700/21770] eta: 0:17:54 time: 0.0724 data: 0.0018 max mem: 19788 +Test: [ 6800/21770] eta: 0:17:47 time: 0.0684 data: 0.0023 max mem: 19788 +Test: [ 6900/21770] eta: 0:17:41 time: 0.0854 data: 0.0026 max mem: 19788 +Test: [ 7000/21770] eta: 0:17:36 time: 0.0706 data: 0.0020 max mem: 19788 +Test: [ 7100/21770] eta: 0:17:29 time: 0.0662 data: 0.0020 max mem: 19788 +Test: [ 7200/21770] eta: 0:17:22 time: 0.0774 data: 0.0026 max mem: 19788 +Test: [ 7300/21770] eta: 0:17:15 time: 0.0733 data: 0.0023 max mem: 19788 +Test: [ 7400/21770] eta: 0:17:09 time: 0.0759 data: 0.0022 max mem: 19788 +Test: [ 7500/21770] eta: 0:17:02 time: 0.0761 data: 0.0022 max mem: 19788 +Test: [ 7600/21770] eta: 0:16:54 time: 0.0654 data: 0.0020 max mem: 19788 +Test: [ 7700/21770] eta: 0:16:48 time: 0.0842 data: 0.0024 max mem: 19788 +Test: [ 7800/21770] eta: 0:16:40 time: 0.0650 data: 0.0019 max mem: 19788 +Test: [ 7900/21770] eta: 0:16:33 time: 0.0655 data: 0.0022 max mem: 19788 +Test: [ 8000/21770] eta: 0:16:26 time: 0.0644 data: 0.0020 max mem: 19788 +Test: [ 8100/21770] eta: 0:16:19 time: 0.0649 data: 0.0019 max mem: 19788 +Test: [ 8200/21770] eta: 0:16:11 time: 0.0714 data: 0.0023 max mem: 19788 +Test: [ 8300/21770] eta: 0:16:03 time: 0.0643 data: 0.0019 max mem: 19788 +Test: [ 8400/21770] eta: 0:15:57 time: 0.0760 data: 0.0021 max mem: 19788 +Test: [ 8500/21770] eta: 0:15:49 time: 0.0662 data: 0.0020 max mem: 19788 +Test: [ 8600/21770] eta: 0:15:41 time: 0.0662 data: 0.0021 max mem: 19788 +Test: [ 8700/21770] eta: 0:15:35 time: 0.0731 data: 0.0019 max mem: 19788 +Test: [ 8800/21770] eta: 0:15:28 time: 0.0807 data: 0.0026 max mem: 19788 +Test: [ 8900/21770] eta: 0:15:20 time: 0.0621 data: 0.0020 max mem: 19788 +Test: [ 9000/21770] eta: 0:15:12 time: 0.0641 data: 0.0019 max mem: 19788 +Test: [ 9100/21770] eta: 0:15:05 time: 0.0713 data: 0.0021 max mem: 19788 +Test: [ 9200/21770] eta: 0:14:57 time: 0.0751 data: 0.0023 max mem: 19788 +Test: [ 9300/21770] eta: 0:14:50 time: 0.0729 data: 0.0021 max mem: 19788 +Test: [ 9400/21770] eta: 0:14:42 time: 0.0658 data: 0.0021 max mem: 19788 +Test: [ 9500/21770] eta: 0:14:35 time: 0.0671 data: 0.0021 max mem: 19788 +Test: [ 9600/21770] eta: 0:14:27 time: 0.0645 data: 0.0020 max mem: 19788 +Test: [ 9700/21770] eta: 0:14:20 time: 0.0734 data: 0.0023 max mem: 19788 +Test: [ 9800/21770] eta: 0:14:13 time: 0.0651 data: 0.0019 max mem: 19788 +Test: [ 9900/21770] eta: 0:14:05 time: 0.0614 data: 0.0019 max mem: 19788 +Test: [10000/21770] eta: 0:13:58 time: 0.0668 data: 0.0020 max mem: 19788 +Test: [10100/21770] eta: 0:13:51 time: 0.0668 data: 0.0018 max mem: 19788 +Test: [10200/21770] eta: 0:13:44 time: 0.0673 data: 0.0022 max mem: 19788 +Test: [10300/21770] eta: 0:13:36 time: 0.0678 data: 0.0020 max mem: 19788 +Test: [10400/21770] eta: 0:13:30 time: 0.0842 data: 0.0026 max mem: 19788 +Test: [10500/21770] eta: 0:13:23 time: 0.0732 data: 0.0021 max mem: 19788 +Test: [10600/21770] eta: 0:13:16 time: 0.0672 data: 0.0020 max mem: 19788 +Test: [10700/21770] eta: 0:13:09 time: 0.0727 data: 0.0019 max mem: 19788 +Test: [10800/21770] eta: 0:13:01 time: 0.0733 data: 0.0020 max mem: 19788 +Test: [10900/21770] eta: 0:12:55 time: 0.0717 data: 0.0022 max mem: 19788 +Test: [11000/21770] eta: 0:12:48 time: 0.0846 data: 0.0027 max mem: 19788 +Test: [11100/21770] eta: 0:12:42 time: 0.0836 data: 0.0024 max mem: 19788 +Test: [11200/21770] eta: 0:12:34 time: 0.0647 data: 0.0020 max mem: 19788 +Test: [11300/21770] eta: 0:12:27 time: 0.0697 data: 0.0021 max mem: 19788 +Test: [11400/21770] eta: 0:12:20 time: 0.0662 data: 0.0020 max mem: 19788 +Test: [11500/21770] eta: 0:12:12 time: 0.0709 data: 0.0021 max mem: 19788 +Test: [11600/21770] eta: 0:12:05 time: 0.0764 data: 0.0024 max mem: 19788 +Test: [11700/21770] eta: 0:11:58 time: 0.0687 data: 0.0023 max mem: 19788 +Test: [11800/21770] eta: 0:11:51 time: 0.0740 data: 0.0023 max mem: 19788 +Test: [11900/21770] eta: 0:11:44 time: 0.0696 data: 0.0020 max mem: 19788 +Test: [12000/21770] eta: 0:11:37 time: 0.0804 data: 0.0026 max mem: 19788 +Test: [12100/21770] eta: 0:11:30 time: 0.0818 data: 0.0021 max mem: 19788 +Test: [12200/21770] eta: 0:11:23 time: 0.0716 data: 0.0021 max mem: 19788 +Test: [12300/21770] eta: 0:11:16 time: 0.0739 data: 0.0024 max mem: 19788 +Test: [12400/21770] eta: 0:11:09 time: 0.0801 data: 0.0024 max mem: 19788 +Test: [12500/21770] eta: 0:11:02 time: 0.0860 data: 0.0025 max mem: 19788 +Test: [12600/21770] eta: 0:10:56 time: 0.0860 data: 0.0025 max mem: 19788 +Test: [12700/21770] eta: 0:10:48 time: 0.0656 data: 0.0021 max mem: 19788 +Test: [12800/21770] eta: 0:10:41 time: 0.0764 data: 0.0024 max mem: 19788 +Test: [12900/21770] eta: 0:10:35 time: 0.0793 data: 0.0025 max mem: 19788 +Test: [13000/21770] eta: 0:10:27 time: 0.0653 data: 0.0019 max mem: 19788 +Test: [13100/21770] eta: 0:10:20 time: 0.0843 data: 0.0027 max mem: 19788 +Test: [13200/21770] eta: 0:10:13 time: 0.0660 data: 0.0020 max mem: 19788 +Test: [13300/21770] eta: 0:10:06 time: 0.0680 data: 0.0022 max mem: 19788 +Test: [13400/21770] eta: 0:09:58 time: 0.0751 data: 0.0023 max mem: 19788 +Test: [13500/21770] eta: 0:09:52 time: 0.0833 data: 0.0025 max mem: 19788 +Test: [13600/21770] eta: 0:09:44 time: 0.0706 data: 0.0020 max mem: 19788 +Test: [13700/21770] eta: 0:09:37 time: 0.0650 data: 0.0019 max mem: 19788 +Test: [13800/21770] eta: 0:09:29 time: 0.0738 data: 0.0023 max mem: 19788 +Test: [13900/21770] eta: 0:09:22 time: 0.0727 data: 0.0020 max mem: 19788 +Test: [14000/21770] eta: 0:09:15 time: 0.0673 data: 0.0018 max mem: 19788 +Test: [14100/21770] eta: 0:09:08 time: 0.0751 data: 0.0026 max mem: 19788 +Test: [14200/21770] eta: 0:09:01 time: 0.0701 data: 0.0020 max mem: 19788 +Test: [14300/21770] eta: 0:08:54 time: 0.0822 data: 0.0024 max mem: 19788 +Test: [14400/21770] eta: 0:08:47 time: 0.0647 data: 0.0022 max mem: 19788 +Test: [14500/21770] eta: 0:08:39 time: 0.0714 data: 0.0021 max mem: 19788 +Test: [14600/21770] eta: 0:08:33 time: 0.0762 data: 0.0022 max mem: 19788 +Test: [14700/21770] eta: 0:08:26 time: 0.0855 data: 0.0019 max mem: 19788 +Test: [14800/21770] eta: 0:08:19 time: 0.0771 data: 0.0022 max mem: 19788 +Test: [14900/21770] eta: 0:08:11 time: 0.0667 data: 0.0019 max mem: 19788 +Test: [15000/21770] eta: 0:08:04 time: 0.0753 data: 0.0024 max mem: 19788 +Test: [15100/21770] eta: 0:07:57 time: 0.0815 data: 0.0025 max mem: 19788 +Test: [15200/21770] eta: 0:07:50 time: 0.0663 data: 0.0019 max mem: 19788 +Test: [15300/21770] eta: 0:07:43 time: 0.0659 data: 0.0022 max mem: 19788 +Test: [15400/21770] eta: 0:07:35 time: 0.0713 data: 0.0023 max mem: 19788 +Test: [15500/21770] eta: 0:07:28 time: 0.0661 data: 0.0019 max mem: 19788 +Test: [15600/21770] eta: 0:07:21 time: 0.0751 data: 0.0023 max mem: 19788 +Test: [15700/21770] eta: 0:07:14 time: 0.0760 data: 0.0026 max mem: 19788 +Test: [15800/21770] eta: 0:07:07 time: 0.0674 data: 0.0021 max mem: 19788 +Test: [15900/21770] eta: 0:07:00 time: 0.0782 data: 0.0023 max mem: 19788 +Test: [16000/21770] eta: 0:06:53 time: 0.0783 data: 0.0021 max mem: 19788 +Test: [16100/21770] eta: 0:06:46 time: 0.0681 data: 0.0020 max mem: 19788 +Test: [16200/21770] eta: 0:06:39 time: 0.0658 data: 0.0020 max mem: 19788 +Test: [16300/21770] eta: 0:06:31 time: 0.0644 data: 0.0021 max mem: 19788 +Test: [16400/21770] eta: 0:06:24 time: 0.0714 data: 0.0022 max mem: 19788 +Test: [16500/21770] eta: 0:06:17 time: 0.0662 data: 0.0019 max mem: 19788 +Test: [16600/21770] eta: 0:06:10 time: 0.0651 data: 0.0018 max mem: 19788 +Test: [16700/21770] eta: 0:06:02 time: 0.0721 data: 0.0022 max mem: 19788 +Test: [16800/21770] eta: 0:05:55 time: 0.0687 data: 0.0022 max mem: 19788 +Test: [16900/21770] eta: 0:05:48 time: 0.0654 data: 0.0019 max mem: 19788 +Test: [17000/21770] eta: 0:05:41 time: 0.0642 data: 0.0019 max mem: 19788 +Test: [17100/21770] eta: 0:05:33 time: 0.0835 data: 0.0026 max mem: 19788 +Test: [17200/21770] eta: 0:05:26 time: 0.0665 data: 0.0020 max mem: 19788 +Test: [17300/21770] eta: 0:05:19 time: 0.0738 data: 0.0024 max mem: 19788 +Test: [17400/21770] eta: 0:05:12 time: 0.0697 data: 0.0022 max mem: 19788 +Test: [17500/21770] eta: 0:05:05 time: 0.0842 data: 0.0022 max mem: 19788 +Test: [17600/21770] eta: 0:04:57 time: 0.0640 data: 0.0020 max mem: 19788 +Test: [17700/21770] eta: 0:04:50 time: 0.0666 data: 0.0021 max mem: 19788 +Test: [17800/21770] eta: 0:04:43 time: 0.0630 data: 0.0019 max mem: 19788 +Test: [17900/21770] eta: 0:04:36 time: 0.0647 data: 0.0021 max mem: 19788 +Test: [18000/21770] eta: 0:04:29 time: 0.0808 data: 0.0025 max mem: 19788 +Test: [18100/21770] eta: 0:04:22 time: 0.0762 data: 0.0024 max mem: 19788 +Test: [18200/21770] eta: 0:04:14 time: 0.0717 data: 0.0024 max mem: 19788 +Test: [18300/21770] eta: 0:04:07 time: 0.0715 data: 0.0020 max mem: 19788 +Test: [18400/21770] eta: 0:04:00 time: 0.0723 data: 0.0023 max mem: 19788 +Test: [18500/21770] eta: 0:03:53 time: 0.0852 data: 0.0026 max mem: 19788 +Test: [18600/21770] eta: 0:03:46 time: 0.0706 data: 0.0022 max mem: 19788 +Test: [18700/21770] eta: 0:03:39 time: 0.0651 data: 0.0020 max mem: 19788 +Test: [18800/21770] eta: 0:03:31 time: 0.0642 data: 0.0019 max mem: 19788 +Test: [18900/21770] eta: 0:03:24 time: 0.0740 data: 0.0021 max mem: 19788 +Test: [19000/21770] eta: 0:03:17 time: 0.0812 data: 0.0021 max mem: 19788 +Test: [19100/21770] eta: 0:03:10 time: 0.0729 data: 0.0022 max mem: 19788 +Test: [19200/21770] eta: 0:03:03 time: 0.0710 data: 0.0025 max mem: 19788 +Test: [19300/21770] eta: 0:02:56 time: 0.0733 data: 0.0022 max mem: 19788 +Test: [19400/21770] eta: 0:02:49 time: 0.0799 data: 0.0025 max mem: 19788 +Test: [19500/21770] eta: 0:02:41 time: 0.0639 data: 0.0018 max mem: 19788 +Test: [19600/21770] eta: 0:02:34 time: 0.0657 data: 0.0019 max mem: 19788 +Test: [19700/21770] eta: 0:02:27 time: 0.0673 data: 0.0023 max mem: 19788 +Test: [19800/21770] eta: 0:02:20 time: 0.0698 data: 0.0020 max mem: 19788 +Test: [19900/21770] eta: 0:02:13 time: 0.0773 data: 0.0024 max mem: 19788 +Test: [20000/21770] eta: 0:02:06 time: 0.0658 data: 0.0021 max mem: 19788 +Test: [20100/21770] eta: 0:01:59 time: 0.0636 data: 0.0021 max mem: 19788 +Test: [20200/21770] eta: 0:01:51 time: 0.0800 data: 0.0023 max mem: 19788 +Test: [20300/21770] eta: 0:01:44 time: 0.0686 data: 0.0021 max mem: 19788 +Test: [20400/21770] eta: 0:01:37 time: 0.0690 data: 0.0020 max mem: 19788 +Test: [20500/21770] eta: 0:01:30 time: 0.0781 data: 0.0023 max mem: 19788 +Test: [20600/21770] eta: 0:01:23 time: 0.0860 data: 0.0026 max mem: 19788 +Test: [20700/21770] eta: 0:01:16 time: 0.0662 data: 0.0019 max mem: 19788 +Test: [20800/21770] eta: 0:01:09 time: 0.0653 data: 0.0020 max mem: 19788 +Test: [20900/21770] eta: 0:01:01 time: 0.0707 data: 0.0022 max mem: 19788 +Test: [21000/21770] eta: 0:00:54 time: 0.0642 data: 0.0020 max mem: 19788 +Test: [21100/21770] eta: 0:00:47 time: 0.0691 data: 0.0022 max mem: 19788 +Test: [21200/21770] eta: 0:00:40 time: 0.0837 data: 0.0026 max mem: 19788 +Test: [21300/21770] eta: 0:00:33 time: 0.0742 data: 0.0022 max mem: 19788 +Test: [21400/21770] eta: 0:00:26 time: 0.0789 data: 0.0025 max mem: 19788 +Test: [21500/21770] eta: 0:00:19 time: 0.0739 data: 0.0023 max mem: 19788 +Test: [21600/21770] eta: 0:00:12 time: 0.0708 data: 0.0023 max mem: 19788 +Test: [21700/21770] eta: 0:00:04 time: 0.0706 data: 0.0020 max mem: 19788 +Test: Total time: 0:25:53 +Final results: +Mean IoU is 62.39 + + precision@0.5 = 69.19 + precision@0.6 = 64.17 + precision@0.7 = 57.74 + precision@0.8 = 47.70 + precision@0.9 = 23.60 + overall IoU = 63.94 + mean IoU = 62.39 + +Mean accuracy for one-to-zero sample is 87.97 + +Average object IoU 0.623918508870197 +Overall IoU 63.93999481201172 +Epoch: [39] [ 0/2138] eta: 10:56:58 lr: 1.8068959784787458e-06 loss: 0.0183 (0.0183) time: 18.4371 data: 1.9008 max mem: 19788 +Epoch: [39] [ 10/2138] eta: 3:11:05 lr: 1.7992844318094101e-06 loss: 0.0160 (0.0175) time: 5.3880 data: 0.1756 max mem: 19788 +Epoch: [39] [ 20/2138] eta: 2:47:56 lr: 1.791669305748589e-06 loss: 0.0150 (0.0166) time: 4.0733 data: 0.0029 max mem: 19788 +Epoch: [39] [ 30/2138] eta: 2:39:12 lr: 1.784050581693132e-06 loss: 0.0165 (0.0172) time: 4.0603 data: 0.0029 max mem: 19788 +Epoch: [39] [ 40/2138] eta: 2:34:21 lr: 1.7764282408544076e-06 loss: 0.0197 (0.0183) time: 4.0547 data: 0.0031 max mem: 19788 +Epoch: [39] [ 50/2138] eta: 2:31:06 lr: 1.7688022642555827e-06 loss: 0.0203 (0.0185) time: 4.0488 data: 0.0034 max mem: 19788 +Epoch: [39] [ 60/2138] eta: 2:28:47 lr: 1.7611726327288473e-06 loss: 0.0174 (0.0183) time: 4.0537 data: 0.0033 max mem: 19788 +Epoch: [39] [ 70/2138] eta: 2:26:52 lr: 1.7535393269125126e-06 loss: 0.0156 (0.0178) time: 4.0558 data: 0.0031 max mem: 19788 +Epoch: [39] [ 80/2138] eta: 2:25:15 lr: 1.7459023272481615e-06 loss: 0.0160 (0.0180) time: 4.0480 data: 0.0032 max mem: 19788 +Epoch: [39] [ 90/2138] eta: 2:23:53 lr: 1.738261613977624e-06 loss: 0.0181 (0.0179) time: 4.0515 data: 0.0032 max mem: 19788 +Epoch: [39] [ 100/2138] eta: 2:22:38 lr: 1.7306171671400094e-06 loss: 0.0178 (0.0180) time: 4.0550 data: 0.0032 max mem: 19788 +Epoch: [39] [ 110/2138] eta: 2:21:28 lr: 1.7229689665685638e-06 loss: 0.0183 (0.0181) time: 4.0491 data: 0.0032 max mem: 19788 +Epoch: [39] [ 120/2138] eta: 2:20:21 lr: 1.7153169918875766e-06 loss: 0.0189 (0.0183) time: 4.0425 data: 0.0032 max mem: 19788 +Epoch: [39] [ 130/2138] eta: 2:19:22 lr: 1.7076612225091129e-06 loss: 0.0189 (0.0184) time: 4.0478 data: 0.0033 max mem: 19788 +Epoch: [39] [ 140/2138] eta: 2:18:23 lr: 1.7000016376297888e-06 loss: 0.0203 (0.0184) time: 4.0503 data: 0.0032 max mem: 19788 +Epoch: [39] [ 150/2138] eta: 2:17:29 lr: 1.6923382162273727e-06 loss: 0.0184 (0.0183) time: 4.0537 data: 0.0035 max mem: 19788 +Epoch: [39] [ 160/2138] eta: 2:16:39 lr: 1.6846709370574245e-06 loss: 0.0196 (0.0186) time: 4.0694 data: 0.0038 max mem: 19788 +Epoch: [39] [ 170/2138] eta: 2:15:46 lr: 1.6769997786497529e-06 loss: 0.0212 (0.0187) time: 4.0632 data: 0.0036 max mem: 19788 +Epoch: [39] [ 180/2138] eta: 2:14:53 lr: 1.6693247193049173e-06 loss: 0.0177 (0.0188) time: 4.0384 data: 0.0034 max mem: 19788 +Epoch: [39] [ 190/2138] eta: 2:14:01 lr: 1.6616457370905329e-06 loss: 0.0163 (0.0188) time: 4.0311 data: 0.0034 max mem: 19788 +Epoch: [39] [ 200/2138] eta: 2:13:12 lr: 1.6539628098376229e-06 loss: 0.0150 (0.0186) time: 4.0392 data: 0.0034 max mem: 19788 +Epoch: [39] [ 210/2138] eta: 2:12:23 lr: 1.64627591513677e-06 loss: 0.0208 (0.0188) time: 4.0415 data: 0.0033 max mem: 19788 +Epoch: [39] [ 220/2138] eta: 2:11:35 lr: 1.638585030334308e-06 loss: 0.0208 (0.0188) time: 4.0422 data: 0.0031 max mem: 19788 +Epoch: [39] [ 230/2138] eta: 2:10:48 lr: 1.6308901325283105e-06 loss: 0.0190 (0.0189) time: 4.0438 data: 0.0032 max mem: 19788 +Epoch: [39] [ 240/2138] eta: 2:10:01 lr: 1.6231911985646127e-06 loss: 0.0194 (0.0189) time: 4.0415 data: 0.0036 max mem: 19788 +Epoch: [39] [ 250/2138] eta: 2:09:15 lr: 1.6154882050326319e-06 loss: 0.0169 (0.0189) time: 4.0443 data: 0.0035 max mem: 19788 +Epoch: [39] [ 260/2138] eta: 2:08:29 lr: 1.6077811282612095e-06 loss: 0.0172 (0.0189) time: 4.0437 data: 0.0034 max mem: 19788 +Epoch: [39] [ 270/2138] eta: 2:07:45 lr: 1.60006994431425e-06 loss: 0.0172 (0.0191) time: 4.0463 data: 0.0032 max mem: 19788 +Epoch: [39] [ 280/2138] eta: 2:07:03 lr: 1.5923546289863772e-06 loss: 0.0184 (0.0190) time: 4.0743 data: 0.0032 max mem: 19788 +Epoch: [39] [ 290/2138] eta: 2:06:19 lr: 1.5846351577983817e-06 loss: 0.0192 (0.0191) time: 4.0776 data: 0.0035 max mem: 19788 +Epoch: [39] [ 300/2138] eta: 2:05:35 lr: 1.576911505992678e-06 loss: 0.0181 (0.0191) time: 4.0513 data: 0.0034 max mem: 19788 +Epoch: [39] [ 310/2138] eta: 2:04:53 lr: 1.5691836485285519e-06 loss: 0.0165 (0.0190) time: 4.0629 data: 0.0033 max mem: 19788 +Epoch: [39] [ 320/2138] eta: 2:04:09 lr: 1.5614515600774097e-06 loss: 0.0173 (0.0190) time: 4.0647 data: 0.0033 max mem: 19788 +Epoch: [39] [ 330/2138] eta: 2:03:25 lr: 1.5537152150178083e-06 loss: 0.0209 (0.0191) time: 4.0490 data: 0.0033 max mem: 19788 +Epoch: [39] [ 340/2138] eta: 2:02:42 lr: 1.5459745874304885e-06 loss: 0.0192 (0.0191) time: 4.0505 data: 0.0032 max mem: 19788 +Epoch: [39] [ 350/2138] eta: 2:01:58 lr: 1.5382296510931834e-06 loss: 0.0180 (0.0190) time: 4.0471 data: 0.0034 max mem: 19788 +Epoch: [39] [ 360/2138] eta: 2:01:19 lr: 1.5304803794753838e-06 loss: 0.0179 (0.0190) time: 4.0812 data: 0.0037 max mem: 19788 +Epoch: [39] [ 370/2138] eta: 2:00:37 lr: 1.52272674573298e-06 loss: 0.0180 (0.0191) time: 4.0939 data: 0.0036 max mem: 19788 +Epoch: [39] [ 380/2138] eta: 1:59:57 lr: 1.5149687227027078e-06 loss: 0.0180 (0.0191) time: 4.0926 data: 0.0032 max mem: 19788 +Epoch: [39] [ 390/2138] eta: 1:59:15 lr: 1.5072062828965747e-06 loss: 0.0192 (0.0191) time: 4.0953 data: 0.0032 max mem: 19788 +Epoch: [39] [ 400/2138] eta: 1:58:33 lr: 1.4994393984960358e-06 loss: 0.0199 (0.0191) time: 4.0774 data: 0.0033 max mem: 19788 +Epoch: [39] [ 410/2138] eta: 1:57:51 lr: 1.4916680413461532e-06 loss: 0.0201 (0.0192) time: 4.0759 data: 0.0033 max mem: 19788 +Epoch: [39] [ 420/2138] eta: 1:57:10 lr: 1.483892182949495e-06 loss: 0.0201 (0.0191) time: 4.0713 data: 0.0034 max mem: 19788 +Epoch: [39] [ 430/2138] eta: 1:56:28 lr: 1.4761117944600106e-06 loss: 0.0174 (0.0191) time: 4.0699 data: 0.0033 max mem: 19788 +Epoch: [39] [ 440/2138] eta: 1:55:47 lr: 1.4683268466766376e-06 loss: 0.0192 (0.0192) time: 4.0780 data: 0.0032 max mem: 19788 +Epoch: [39] [ 450/2138] eta: 1:55:05 lr: 1.460537310036873e-06 loss: 0.0189 (0.0192) time: 4.0810 data: 0.0032 max mem: 19788 +Epoch: [39] [ 460/2138] eta: 1:54:24 lr: 1.4527431546100722e-06 loss: 0.0191 (0.0192) time: 4.0733 data: 0.0032 max mem: 19788 +Epoch: [39] [ 470/2138] eta: 1:53:42 lr: 1.4449443500906982e-06 loss: 0.0192 (0.0193) time: 4.0682 data: 0.0032 max mem: 19788 +Epoch: [39] [ 480/2138] eta: 1:53:00 lr: 1.4371408657912909e-06 loss: 0.0193 (0.0193) time: 4.0685 data: 0.0031 max mem: 19788 +Epoch: [39] [ 490/2138] eta: 1:52:19 lr: 1.4293326706353767e-06 loss: 0.0180 (0.0193) time: 4.0767 data: 0.0030 max mem: 19788 +Epoch: [39] [ 500/2138] eta: 1:51:38 lr: 1.4215197331500866e-06 loss: 0.0178 (0.0193) time: 4.0818 data: 0.0032 max mem: 19788 +Epoch: [39] [ 510/2138] eta: 1:50:56 lr: 1.4137020214587051e-06 loss: 0.0184 (0.0193) time: 4.0766 data: 0.0031 max mem: 19788 +Epoch: [39] [ 520/2138] eta: 1:50:15 lr: 1.405879503272915e-06 loss: 0.0189 (0.0193) time: 4.0720 data: 0.0032 max mem: 19788 +Epoch: [39] [ 530/2138] eta: 1:49:33 lr: 1.398052145884961e-06 loss: 0.0176 (0.0193) time: 4.0662 data: 0.0033 max mem: 19788 +Epoch: [39] [ 540/2138] eta: 1:48:52 lr: 1.390219916159499e-06 loss: 0.0176 (0.0193) time: 4.0630 data: 0.0032 max mem: 19788 +Epoch: [39] [ 550/2138] eta: 1:48:11 lr: 1.3823827805253511e-06 loss: 0.0189 (0.0193) time: 4.0793 data: 0.0032 max mem: 19788 +Epoch: [39] [ 560/2138] eta: 1:47:29 lr: 1.3745407049669294e-06 loss: 0.0177 (0.0193) time: 4.0787 data: 0.0031 max mem: 19788 +Epoch: [39] [ 570/2138] eta: 1:47:00 lr: 1.366693655015558e-06 loss: 0.0168 (0.0193) time: 4.2856 data: 0.0031 max mem: 19788 +Epoch: [39] [ 580/2138] eta: 2:15:06 lr: 1.3588415957404455e-06 loss: 0.0178 (0.0193) time: 36.5015 data: 32.1820 max mem: 19788 +Epoch: [39] [ 590/2138] eta: 2:13:44 lr: 1.3509844917395413e-06 loss: 0.0182 (0.0193) time: 36.2701 data: 32.1814 max mem: 19788 +Epoch: [39] [ 600/2138] eta: 2:12:23 lr: 1.3431223071300293e-06 loss: 0.0176 (0.0192) time: 4.0465 data: 0.0026 max mem: 19788 +Epoch: [39] [ 610/2138] eta: 2:11:03 lr: 1.3352550055386868e-06 loss: 0.0182 (0.0193) time: 4.0504 data: 0.0033 max mem: 19788 +Epoch: [39] [ 620/2138] eta: 2:09:45 lr: 1.3273825500918667e-06 loss: 0.0198 (0.0193) time: 4.0510 data: 0.0032 max mem: 19788 +Epoch: [39] [ 630/2138] eta: 2:08:28 lr: 1.3195049034053253e-06 loss: 0.0175 (0.0193) time: 4.0501 data: 0.0032 max mem: 19788 +Epoch: [39] [ 640/2138] eta: 2:07:12 lr: 1.3116220275736578e-06 loss: 0.0173 (0.0192) time: 4.0489 data: 0.0031 max mem: 19788 +Epoch: [39] [ 650/2138] eta: 2:05:57 lr: 1.3037338841595605e-06 loss: 0.0181 (0.0192) time: 4.0481 data: 0.0031 max mem: 19788 +Epoch: [39] [ 660/2138] eta: 2:04:43 lr: 1.2958404341826858e-06 loss: 0.0181 (0.0192) time: 4.0486 data: 0.0032 max mem: 19788 +Epoch: [39] [ 670/2138] eta: 2:03:31 lr: 1.2879416381082633e-06 loss: 0.0189 (0.0192) time: 4.0502 data: 0.0034 max mem: 19788 +Epoch: [39] [ 680/2138] eta: 2:02:21 lr: 1.280037455835402e-06 loss: 0.0197 (0.0192) time: 4.0924 data: 0.0033 max mem: 19788 +Epoch: [39] [ 690/2138] eta: 2:01:10 lr: 1.2721278466849874e-06 loss: 0.0187 (0.0192) time: 4.0963 data: 0.0033 max mem: 19788 +Epoch: [39] [ 700/2138] eta: 2:00:00 lr: 1.2642127693873504e-06 loss: 0.0187 (0.0192) time: 4.0618 data: 0.0033 max mem: 19788 +Epoch: [39] [ 710/2138] eta: 1:58:51 lr: 1.2562921820694617e-06 loss: 0.0197 (0.0192) time: 4.0564 data: 0.0035 max mem: 19788 +Epoch: [39] [ 720/2138] eta: 1:57:42 lr: 1.2483660422418803e-06 loss: 0.0183 (0.0192) time: 4.0512 data: 0.0036 max mem: 19788 +Epoch: [39] [ 730/2138] eta: 1:56:34 lr: 1.2404343067852014e-06 loss: 0.0183 (0.0192) time: 4.0531 data: 0.0032 max mem: 19788 +Epoch: [39] [ 740/2138] eta: 1:55:27 lr: 1.2324969319362338e-06 loss: 0.0163 (0.0192) time: 4.0474 data: 0.0032 max mem: 19788 +Epoch: [39] [ 750/2138] eta: 1:54:21 lr: 1.224553873273645e-06 loss: 0.0167 (0.0192) time: 4.0451 data: 0.0034 max mem: 19788 +Epoch: [39] [ 760/2138] eta: 1:53:15 lr: 1.2166050857033093e-06 loss: 0.0204 (0.0192) time: 4.0427 data: 0.0034 max mem: 19788 +Epoch: [39] [ 770/2138] eta: 1:52:10 lr: 1.2086505234430922e-06 loss: 0.0199 (0.0192) time: 4.0348 data: 0.0032 max mem: 19788 +Epoch: [39] [ 780/2138] eta: 1:51:05 lr: 1.2006901400073044e-06 loss: 0.0207 (0.0193) time: 4.0313 data: 0.0033 max mem: 19788 +Epoch: [39] [ 790/2138] eta: 1:50:01 lr: 1.1927238881905617e-06 loss: 0.0178 (0.0193) time: 4.0283 data: 0.0034 max mem: 19788 +Epoch: [39] [ 800/2138] eta: 1:48:58 lr: 1.1847517200512748e-06 loss: 0.0170 (0.0192) time: 4.0307 data: 0.0034 max mem: 19788 +Epoch: [39] [ 810/2138] eta: 1:47:55 lr: 1.1767735868945132e-06 loss: 0.0157 (0.0192) time: 4.0381 data: 0.0033 max mem: 19788 +Epoch: [39] [ 820/2138] eta: 1:46:53 lr: 1.1687894392544598e-06 loss: 0.0161 (0.0192) time: 4.0467 data: 0.0033 max mem: 19788 +Epoch: [39] [ 830/2138] eta: 1:45:52 lr: 1.1607992268761954e-06 loss: 0.0161 (0.0192) time: 4.0527 data: 0.0031 max mem: 19788 +Epoch: [39] [ 840/2138] eta: 1:44:50 lr: 1.1528028986970382e-06 loss: 0.0156 (0.0192) time: 4.0385 data: 0.0032 max mem: 19788 +Epoch: [39] [ 850/2138] eta: 1:43:50 lr: 1.1448004028271656e-06 loss: 0.0156 (0.0192) time: 4.0373 data: 0.0034 max mem: 19788 +Epoch: [39] [ 860/2138] eta: 1:42:50 lr: 1.1367916865297445e-06 loss: 0.0162 (0.0192) time: 4.0587 data: 0.0034 max mem: 19788 +Epoch: [39] [ 870/2138] eta: 1:41:50 lr: 1.1287766962003e-06 loss: 0.0208 (0.0192) time: 4.0605 data: 0.0032 max mem: 19788 +Epoch: [39] [ 880/2138] eta: 1:40:51 lr: 1.120755377345537e-06 loss: 0.0183 (0.0192) time: 4.0524 data: 0.0032 max mem: 19788 +Epoch: [39] [ 890/2138] eta: 1:39:53 lr: 1.1127276745613514e-06 loss: 0.0183 (0.0192) time: 4.0556 data: 0.0032 max mem: 19788 +Epoch: [39] [ 900/2138] eta: 1:38:54 lr: 1.1046935315102375e-06 loss: 0.0210 (0.0192) time: 4.0586 data: 0.0032 max mem: 19788 +Epoch: [39] [ 910/2138] eta: 1:37:56 lr: 1.0966528908978244e-06 loss: 0.0196 (0.0192) time: 4.0580 data: 0.0032 max mem: 19788 +Epoch: [39] [ 920/2138] eta: 1:36:59 lr: 1.088605694448753e-06 loss: 0.0176 (0.0192) time: 4.0555 data: 0.0031 max mem: 19788 +Epoch: [39] [ 930/2138] eta: 1:36:02 lr: 1.0805518828816135e-06 loss: 0.0164 (0.0192) time: 4.0526 data: 0.0032 max mem: 19788 +Epoch: [39] [ 940/2138] eta: 1:35:04 lr: 1.072491395883157e-06 loss: 0.0181 (0.0192) time: 4.0386 data: 0.0035 max mem: 19788 +Epoch: [39] [ 950/2138] eta: 1:34:08 lr: 1.064424172081506e-06 loss: 0.0181 (0.0192) time: 4.0252 data: 0.0035 max mem: 19788 +Epoch: [39] [ 960/2138] eta: 1:33:11 lr: 1.056350149018517e-06 loss: 0.0174 (0.0192) time: 4.0321 data: 0.0032 max mem: 19788 +Epoch: [39] [ 970/2138] eta: 1:32:15 lr: 1.048269263121182e-06 loss: 0.0188 (0.0192) time: 4.0347 data: 0.0032 max mem: 19788 +Epoch: [39] [ 980/2138] eta: 1:31:19 lr: 1.040181449671942e-06 loss: 0.0170 (0.0192) time: 4.0318 data: 0.0032 max mem: 19788 +Epoch: [39] [ 990/2138] eta: 1:30:24 lr: 1.0320866427780701e-06 loss: 0.0194 (0.0192) time: 4.0263 data: 0.0032 max mem: 19788 +Epoch: [39] [1000/2138] eta: 1:29:29 lr: 1.0239847753398322e-06 loss: 0.0199 (0.0192) time: 4.0245 data: 0.0033 max mem: 19788 +Epoch: [39] [1010/2138] eta: 1:28:34 lr: 1.0158757790176238e-06 loss: 0.0187 (0.0192) time: 4.0251 data: 0.0033 max mem: 19788 +Epoch: [39] [1020/2138] eta: 1:27:39 lr: 1.007759584197787e-06 loss: 0.0173 (0.0192) time: 4.0356 data: 0.0033 max mem: 19788 +Epoch: [39] [1030/2138] eta: 1:26:45 lr: 9.996361199572952e-07 loss: 0.0173 (0.0192) time: 4.0425 data: 0.0035 max mem: 19788 +Epoch: [39] [1040/2138] eta: 1:25:51 lr: 9.915053140270074e-07 loss: 0.0170 (0.0192) time: 4.0452 data: 0.0036 max mem: 19788 +Epoch: [39] [1050/2138] eta: 1:24:58 lr: 9.83367092753669e-07 loss: 0.0178 (0.0192) time: 4.0461 data: 0.0034 max mem: 19788 +Epoch: [39] [1060/2138] eta: 1:24:04 lr: 9.752213810603572e-07 loss: 0.0182 (0.0192) time: 4.0411 data: 0.0032 max mem: 19788 +Epoch: [39] [1070/2138] eta: 1:23:11 lr: 9.67068102405544e-07 loss: 0.0175 (0.0192) time: 4.0395 data: 0.0034 max mem: 19788 +Epoch: [39] [1080/2138] eta: 1:22:18 lr: 9.589071787404587e-07 loss: 0.0171 (0.0192) time: 4.0420 data: 0.0034 max mem: 19788 +Epoch: [39] [1090/2138] eta: 1:21:25 lr: 9.507385304649222e-07 loss: 0.0169 (0.0192) time: 4.0403 data: 0.0032 max mem: 19788 +Epoch: [39] [1100/2138] eta: 1:20:33 lr: 9.425620763813255e-07 loss: 0.0211 (0.0192) time: 4.0424 data: 0.0034 max mem: 19788 +Epoch: [39] [1110/2138] eta: 1:19:41 lr: 9.343777336469135e-07 loss: 0.0195 (0.0192) time: 4.0516 data: 0.0035 max mem: 19788 +Epoch: [39] [1120/2138] eta: 1:18:49 lr: 9.261854177240348e-07 loss: 0.0170 (0.0192) time: 4.0533 data: 0.0033 max mem: 19788 +Epoch: [39] [1130/2138] eta: 1:17:57 lr: 9.179850423285137e-07 loss: 0.0186 (0.0192) time: 4.0518 data: 0.0033 max mem: 19788 +Epoch: [39] [1140/2138] eta: 1:17:06 lr: 9.097765193757906e-07 loss: 0.0186 (0.0192) time: 4.0457 data: 0.0032 max mem: 19788 +Epoch: [39] [1150/2138] eta: 1:16:14 lr: 9.015597589249747e-07 loss: 0.0178 (0.0192) time: 4.0439 data: 0.0034 max mem: 19788 +Epoch: [39] [1160/2138] eta: 1:15:23 lr: 8.933346691204408e-07 loss: 0.0165 (0.0192) time: 4.0441 data: 0.0036 max mem: 19788 +Epoch: [39] [1170/2138] eta: 1:14:32 lr: 8.851011561311062e-07 loss: 0.0175 (0.0192) time: 4.0406 data: 0.0035 max mem: 19788 +Epoch: [39] [1180/2138] eta: 1:13:41 lr: 8.768591240869986e-07 loss: 0.0182 (0.0192) time: 4.0409 data: 0.0031 max mem: 19788 +Epoch: [39] [1190/2138] eta: 1:12:50 lr: 8.686084750132372e-07 loss: 0.0178 (0.0192) time: 4.0458 data: 0.0033 max mem: 19788 +Epoch: [39] [1200/2138] eta: 1:12:00 lr: 8.603491087610217e-07 loss: 0.0173 (0.0192) time: 4.0433 data: 0.0034 max mem: 19788 +Epoch: [39] [1210/2138] eta: 1:11:09 lr: 8.520809229357311e-07 loss: 0.0173 (0.0192) time: 4.0398 data: 0.0033 max mem: 19788 +Epoch: [39] [1220/2138] eta: 1:10:19 lr: 8.438038128217101e-07 loss: 0.0175 (0.0192) time: 4.0387 data: 0.0033 max mem: 19788 +Epoch: [39] [1230/2138] eta: 1:09:29 lr: 8.3551767130382e-07 loss: 0.0175 (0.0192) time: 4.0376 data: 0.0034 max mem: 19788 +Epoch: [39] [1240/2138] eta: 1:08:39 lr: 8.27222388785312e-07 loss: 0.0166 (0.0192) time: 4.0399 data: 0.0038 max mem: 19788 +Epoch: [39] [1250/2138] eta: 1:07:49 lr: 8.189178531020726e-07 loss: 0.0167 (0.0192) time: 4.0397 data: 0.0036 max mem: 19788 +Epoch: [39] [1260/2138] eta: 1:07:00 lr: 8.106039494327827e-07 loss: 0.0166 (0.0192) time: 4.0384 data: 0.0032 max mem: 19788 +Epoch: [39] [1270/2138] eta: 1:06:10 lr: 8.02280560204954e-07 loss: 0.0157 (0.0192) time: 4.0449 data: 0.0034 max mem: 19788 +Epoch: [39] [1280/2138] eta: 1:05:21 lr: 7.939475649965178e-07 loss: 0.0167 (0.0192) time: 4.0531 data: 0.0035 max mem: 19788 +Epoch: [39] [1290/2138] eta: 1:04:32 lr: 7.856048404326239e-07 loss: 0.0170 (0.0191) time: 4.0495 data: 0.0036 max mem: 19788 +Epoch: [39] [1300/2138] eta: 1:03:43 lr: 7.772522600775587e-07 loss: 0.0170 (0.0192) time: 4.0439 data: 0.0037 max mem: 19788 +Epoch: [39] [1310/2138] eta: 1:02:54 lr: 7.688896943212389e-07 loss: 0.0190 (0.0191) time: 4.0458 data: 0.0036 max mem: 19788 +Epoch: [39] [1320/2138] eta: 1:02:05 lr: 7.605170102602012e-07 loss: 0.0198 (0.0192) time: 4.0497 data: 0.0034 max mem: 19788 +Epoch: [39] [1330/2138] eta: 1:01:17 lr: 7.521340715724864e-07 loss: 0.0182 (0.0192) time: 4.0511 data: 0.0034 max mem: 19788 +Epoch: [39] [1340/2138] eta: 1:00:28 lr: 7.437407383862923e-07 loss: 0.0178 (0.0192) time: 4.0475 data: 0.0034 max mem: 19788 +Epoch: [39] [1350/2138] eta: 0:59:40 lr: 7.353368671417338e-07 loss: 0.0209 (0.0192) time: 4.0470 data: 0.0033 max mem: 19788 +Epoch: [39] [1360/2138] eta: 0:58:52 lr: 7.269223104455271e-07 loss: 0.0212 (0.0192) time: 4.0492 data: 0.0032 max mem: 19788 +Epoch: [39] [1370/2138] eta: 0:58:03 lr: 7.18496916917868e-07 loss: 0.0180 (0.0192) time: 4.0470 data: 0.0031 max mem: 19788 +Epoch: [39] [1380/2138] eta: 0:57:15 lr: 7.100605310312515e-07 loss: 0.0180 (0.0192) time: 4.0471 data: 0.0031 max mem: 19788 +Epoch: [39] [1390/2138] eta: 0:56:27 lr: 7.016129929404212e-07 loss: 0.0185 (0.0192) time: 4.0487 data: 0.0033 max mem: 19788 +Epoch: [39] [1400/2138] eta: 0:55:39 lr: 6.931541383031113e-07 loss: 0.0187 (0.0192) time: 4.0430 data: 0.0033 max mem: 19788 +Epoch: [39] [1410/2138] eta: 0:54:52 lr: 6.846837980906752e-07 loss: 0.0175 (0.0192) time: 4.0359 data: 0.0032 max mem: 19788 +Epoch: [39] [1420/2138] eta: 0:54:04 lr: 6.762017983881569e-07 loss: 0.0173 (0.0192) time: 4.0363 data: 0.0031 max mem: 19788 +Epoch: [39] [1430/2138] eta: 0:53:17 lr: 6.677079601827898e-07 loss: 0.0193 (0.0192) time: 4.0440 data: 0.0030 max mem: 19788 +Epoch: [39] [1440/2138] eta: 0:52:29 lr: 6.5920209914035e-07 loss: 0.0174 (0.0192) time: 4.0464 data: 0.0031 max mem: 19788 +Epoch: [39] [1450/2138] eta: 0:51:42 lr: 6.50684025368211e-07 loss: 0.0205 (0.0192) time: 4.0482 data: 0.0032 max mem: 19788 +Epoch: [39] [1460/2138] eta: 0:50:55 lr: 6.421535431643774e-07 loss: 0.0216 (0.0192) time: 4.0496 data: 0.0032 max mem: 19788 +Epoch: [39] [1470/2138] eta: 0:50:07 lr: 6.336104507511724e-07 loss: 0.0189 (0.0192) time: 4.0491 data: 0.0031 max mem: 19788 +Epoch: [39] [1480/2138] eta: 0:49:20 lr: 6.250545399926742e-07 loss: 0.0195 (0.0192) time: 4.0539 data: 0.0031 max mem: 19788 +Epoch: [39] [1490/2138] eta: 0:48:33 lr: 6.164855960943685e-07 loss: 0.0192 (0.0192) time: 4.0570 data: 0.0031 max mem: 19788 +Epoch: [39] [1500/2138] eta: 0:47:47 lr: 6.079033972838832e-07 loss: 0.0182 (0.0192) time: 4.0529 data: 0.0030 max mem: 19788 +Epoch: [39] [1510/2138] eta: 0:47:00 lr: 5.993077144710203e-07 loss: 0.0182 (0.0192) time: 4.0443 data: 0.0031 max mem: 19788 +Epoch: [39] [1520/2138] eta: 0:46:13 lr: 5.906983108856695e-07 loss: 0.0184 (0.0192) time: 4.0415 data: 0.0031 max mem: 19788 +Epoch: [39] [1530/2138] eta: 0:45:26 lr: 5.820749416915006e-07 loss: 0.0166 (0.0192) time: 4.0414 data: 0.0032 max mem: 19788 +Epoch: [39] [1540/2138] eta: 0:44:40 lr: 5.734373535736714e-07 loss: 0.0173 (0.0192) time: 4.0509 data: 0.0032 max mem: 19788 +Epoch: [39] [1550/2138] eta: 0:43:53 lr: 5.647852842980559e-07 loss: 0.0177 (0.0192) time: 4.0468 data: 0.0032 max mem: 19788 +Epoch: [39] [1560/2138] eta: 0:43:07 lr: 5.561184622397874e-07 loss: 0.0181 (0.0192) time: 4.0277 data: 0.0032 max mem: 19788 +Epoch: [39] [1570/2138] eta: 0:42:21 lr: 5.474366058781372e-07 loss: 0.0186 (0.0192) time: 4.0343 data: 0.0034 max mem: 19788 +Epoch: [39] [1580/2138] eta: 0:41:34 lr: 5.387394232549124e-07 loss: 0.0181 (0.0192) time: 4.0464 data: 0.0034 max mem: 19788 +Epoch: [39] [1590/2138] eta: 0:40:48 lr: 5.300266113929408e-07 loss: 0.0184 (0.0192) time: 4.0377 data: 0.0034 max mem: 19788 +Epoch: [39] [1600/2138] eta: 0:40:02 lr: 5.212978556708312e-07 loss: 0.0203 (0.0192) time: 4.0433 data: 0.0035 max mem: 19788 +Epoch: [39] [1610/2138] eta: 0:39:16 lr: 5.12552829150069e-07 loss: 0.0187 (0.0192) time: 4.0493 data: 0.0033 max mem: 19788 +Epoch: [39] [1620/2138] eta: 0:38:30 lr: 5.037911918495582e-07 loss: 0.0170 (0.0192) time: 4.0408 data: 0.0033 max mem: 19788 +Epoch: [39] [1630/2138] eta: 0:37:44 lr: 4.950125899626973e-07 loss: 0.0187 (0.0192) time: 4.0381 data: 0.0032 max mem: 19788 +Epoch: [39] [1640/2138] eta: 0:36:58 lr: 4.862166550109214e-07 loss: 0.0186 (0.0192) time: 4.0379 data: 0.0031 max mem: 19788 +Epoch: [39] [1650/2138] eta: 0:36:12 lr: 4.774030029274631e-07 loss: 0.0169 (0.0192) time: 4.0376 data: 0.0032 max mem: 19788 +Epoch: [39] [1660/2138] eta: 0:35:27 lr: 4.685712330637316e-07 loss: 0.0163 (0.0192) time: 4.0417 data: 0.0032 max mem: 19788 +Epoch: [39] [1670/2138] eta: 0:34:41 lr: 4.5972092711030764e-07 loss: 0.0156 (0.0192) time: 4.0640 data: 0.0034 max mem: 19788 +Epoch: [39] [1680/2138] eta: 0:33:56 lr: 4.5085164792293195e-07 loss: 0.0196 (0.0192) time: 4.0612 data: 0.0035 max mem: 19788 +Epoch: [39] [1690/2138] eta: 0:33:10 lr: 4.419629382431529e-07 loss: 0.0196 (0.0192) time: 4.0525 data: 0.0033 max mem: 19788 +Epoch: [39] [1700/2138] eta: 0:32:25 lr: 4.3305431930131103e-07 loss: 0.0176 (0.0192) time: 4.0531 data: 0.0033 max mem: 19788 +Epoch: [39] [1710/2138] eta: 0:31:39 lr: 4.241252892883906e-07 loss: 0.0177 (0.0192) time: 4.0501 data: 0.0032 max mem: 19788 +Epoch: [39] [1720/2138] eta: 0:30:54 lr: 4.151753216807653e-07 loss: 0.0189 (0.0192) time: 4.0459 data: 0.0034 max mem: 19788 +Epoch: [39] [1730/2138] eta: 0:30:09 lr: 4.062038634001008e-07 loss: 0.0191 (0.0192) time: 4.0375 data: 0.0035 max mem: 19788 +Epoch: [39] [1740/2138] eta: 0:29:23 lr: 3.972103327874347e-07 loss: 0.0185 (0.0192) time: 4.0469 data: 0.0035 max mem: 19788 +Epoch: [39] [1750/2138] eta: 0:28:38 lr: 3.8819411736780753e-07 loss: 0.0187 (0.0192) time: 4.0506 data: 0.0036 max mem: 19788 +Epoch: [39] [1760/2138] eta: 0:27:53 lr: 3.791545713774987e-07 loss: 0.0199 (0.0192) time: 4.0470 data: 0.0036 max mem: 19788 +Epoch: [39] [1770/2138] eta: 0:27:08 lr: 3.700910130219835e-07 loss: 0.0189 (0.0192) time: 4.0397 data: 0.0034 max mem: 19788 +Epoch: [39] [1780/2138] eta: 0:26:23 lr: 3.610027214268202e-07 loss: 0.0188 (0.0192) time: 4.0330 data: 0.0032 max mem: 19788 +Epoch: [39] [1790/2138] eta: 0:25:38 lr: 3.5188893323780186e-07 loss: 0.0181 (0.0192) time: 4.0294 data: 0.0032 max mem: 19788 +Epoch: [39] [1800/2138] eta: 0:24:53 lr: 3.4274883881841556e-07 loss: 0.0171 (0.0192) time: 4.0510 data: 0.0036 max mem: 19788 +Epoch: [39] [1810/2138] eta: 0:24:08 lr: 3.335815779838248e-07 loss: 0.0188 (0.0192) time: 4.0888 data: 0.0039 max mem: 19788 +Epoch: [39] [1820/2138] eta: 0:23:24 lr: 3.243862351986195e-07 loss: 0.0188 (0.0192) time: 4.0874 data: 0.0035 max mem: 19788 +Epoch: [39] [1830/2138] eta: 0:22:39 lr: 3.1516183415215e-07 loss: 0.0181 (0.0192) time: 4.0898 data: 0.0030 max mem: 19788 +Epoch: [39] [1840/2138] eta: 0:21:54 lr: 3.0590733160747654e-07 loss: 0.0186 (0.0192) time: 4.0933 data: 0.0031 max mem: 19788 +Epoch: [39] [1850/2138] eta: 0:21:10 lr: 2.9662161039916844e-07 loss: 0.0193 (0.0192) time: 4.0847 data: 0.0036 max mem: 19788 +Epoch: [39] [1860/2138] eta: 0:20:25 lr: 2.873034714279703e-07 loss: 0.0193 (0.0192) time: 4.0856 data: 0.0039 max mem: 19788 +Epoch: [39] [1870/2138] eta: 0:19:40 lr: 2.7795162446739944e-07 loss: 0.0181 (0.0192) time: 4.0831 data: 0.0037 max mem: 19788 +Epoch: [39] [1880/2138] eta: 0:18:56 lr: 2.685646775543319e-07 loss: 0.0178 (0.0193) time: 4.0853 data: 0.0034 max mem: 19788 +Epoch: [39] [1890/2138] eta: 0:18:11 lr: 2.5914112468189935e-07 loss: 0.0173 (0.0192) time: 4.0797 data: 0.0031 max mem: 19788 +Epoch: [39] [1900/2138] eta: 0:17:27 lr: 2.4967933144283587e-07 loss: 0.0171 (0.0192) time: 4.0852 data: 0.0030 max mem: 19788 +Epoch: [39] [1910/2138] eta: 0:16:43 lr: 2.4017751818051645e-07 loss: 0.0178 (0.0192) time: 4.0975 data: 0.0031 max mem: 19788 +Epoch: [39] [1920/2138] eta: 0:15:58 lr: 2.3063374008579354e-07 loss: 0.0186 (0.0192) time: 4.0953 data: 0.0035 max mem: 19788 +Epoch: [39] [1930/2138] eta: 0:15:14 lr: 2.2104586351851978e-07 loss: 0.0183 (0.0192) time: 4.0972 data: 0.0037 max mem: 19788 +Epoch: [39] [1940/2138] eta: 0:14:30 lr: 2.1141153761978375e-07 loss: 0.0190 (0.0192) time: 4.0940 data: 0.0034 max mem: 19788 +Epoch: [39] [1950/2138] eta: 0:13:46 lr: 2.0172815998954485e-07 loss: 0.0179 (0.0192) time: 4.0901 data: 0.0034 max mem: 19788 +Epoch: [39] [1960/2138] eta: 0:13:01 lr: 1.9199283480312792e-07 loss: 0.0172 (0.0192) time: 4.0905 data: 0.0036 max mem: 19788 +Epoch: [39] [1970/2138] eta: 0:12:17 lr: 1.822023211754555e-07 loss: 0.0186 (0.0192) time: 4.0831 data: 0.0033 max mem: 19788 +Epoch: [39] [1980/2138] eta: 0:11:33 lr: 1.7235296877704624e-07 loss: 0.0160 (0.0192) time: 4.0800 data: 0.0034 max mem: 19788 +Epoch: [39] [1990/2138] eta: 0:10:49 lr: 1.6244063653278367e-07 loss: 0.0175 (0.0192) time: 4.0862 data: 0.0034 max mem: 19788 +Epoch: [39] [2000/2138] eta: 0:10:05 lr: 1.5246058849162085e-07 loss: 0.0181 (0.0192) time: 4.0767 data: 0.0033 max mem: 19788 +Epoch: [39] [2010/2138] eta: 0:09:21 lr: 1.4240735829943892e-07 loss: 0.0185 (0.0192) time: 4.0579 data: 0.0034 max mem: 19788 +Epoch: [39] [2020/2138] eta: 0:08:37 lr: 1.3227456955259268e-07 loss: 0.0186 (0.0192) time: 4.0492 data: 0.0034 max mem: 19788 +Epoch: [39] [2030/2138] eta: 0:07:53 lr: 1.220546926024544e-07 loss: 0.0186 (0.0192) time: 4.0488 data: 0.0035 max mem: 19788 +Epoch: [39] [2040/2138] eta: 0:07:09 lr: 1.1173870716487489e-07 loss: 0.0183 (0.0192) time: 4.0443 data: 0.0032 max mem: 19788 +Epoch: [39] [2050/2138] eta: 0:06:25 lr: 1.013156205312557e-07 loss: 0.0182 (0.0192) time: 4.0329 data: 0.0033 max mem: 19788 +Epoch: [39] [2060/2138] eta: 0:05:41 lr: 9.077175536454375e-08 loss: 0.0171 (0.0192) time: 4.0280 data: 0.0036 max mem: 19788 +Epoch: [39] [2070/2138] eta: 0:04:57 lr: 8.00896514809128e-08 loss: 0.0168 (0.0192) time: 4.0275 data: 0.0035 max mem: 19788 +Epoch: [39] [2080/2138] eta: 0:04:13 lr: 6.924628063148144e-08 loss: 0.0177 (0.0192) time: 4.0300 data: 0.0033 max mem: 19788 +Epoch: [39] [2090/2138] eta: 0:03:29 lr: 5.820994024959554e-08 loss: 0.0179 (0.0192) time: 4.0250 data: 0.0034 max mem: 19788 +Epoch: [39] [2100/2138] eta: 0:02:46 lr: 4.693433112807911e-08 loss: 0.0179 (0.0192) time: 4.0258 data: 0.0033 max mem: 19788 +Epoch: [39] [2110/2138] eta: 0:02:02 lr: 3.5345690402822716e-08 loss: 0.0205 (0.0192) time: 4.0462 data: 0.0031 max mem: 19788 +Epoch: [39] [2120/2138] eta: 0:01:18 lr: 2.330843478335392e-08 loss: 0.0229 (0.0192) time: 4.0566 data: 0.0031 max mem: 19788 +Epoch: [39] [2130/2138] eta: 0:00:34 lr: 1.048811202260214e-08 loss: 0.0229 (0.0192) time: 4.0402 data: 0.0031 max mem: 19788 +Epoch: [39] Total time: 2:35:30 +Test: [ 0/21770] eta: 19:26:18 time: 3.2144 data: 2.9794 max mem: 19788 +Test: [ 100/21770] eta: 0:34:24 time: 0.0623 data: 0.0019 max mem: 19788 +Test: [ 200/21770] eta: 0:29:32 time: 0.0627 data: 0.0019 max mem: 19788 +Test: [ 300/21770] eta: 0:27:46 time: 0.0623 data: 0.0021 max mem: 19788 +Test: [ 400/21770] eta: 0:26:52 time: 0.0640 data: 0.0019 max mem: 19788 +Test: [ 500/21770] eta: 0:26:30 time: 0.0703 data: 0.0024 max mem: 19788 +Test: [ 600/21770] eta: 0:26:02 time: 0.0745 data: 0.0021 max mem: 19788 +Test: [ 700/21770] eta: 0:25:41 time: 0.0764 data: 0.0024 max mem: 19788 +Test: [ 800/21770] eta: 0:25:34 time: 0.0669 data: 0.0019 max mem: 19788 +Test: [ 900/21770] eta: 0:25:14 time: 0.0756 data: 0.0023 max mem: 19788 +Test: [ 1000/21770] eta: 0:24:57 time: 0.0636 data: 0.0019 max mem: 19788 +Test: [ 1100/21770] eta: 0:24:51 time: 0.0822 data: 0.0025 max mem: 19788 +Test: [ 1200/21770] eta: 0:24:39 time: 0.0665 data: 0.0020 max mem: 19788 +Test: [ 1300/21770] eta: 0:24:36 time: 0.0780 data: 0.0025 max mem: 19788 +Test: [ 1400/21770] eta: 0:24:21 time: 0.0737 data: 0.0022 max mem: 19788 +Test: [ 1500/21770] eta: 0:24:05 time: 0.0612 data: 0.0019 max mem: 19788 +Test: [ 1600/21770] eta: 0:23:52 time: 0.0655 data: 0.0023 max mem: 19788 +Test: [ 1700/21770] eta: 0:23:39 time: 0.0693 data: 0.0020 max mem: 19788 +Test: [ 1800/21770] eta: 0:23:38 time: 0.0642 data: 0.0020 max mem: 19788 +Test: [ 1900/21770] eta: 0:23:30 time: 0.0605 data: 0.0020 max mem: 19788 +Test: [ 2000/21770] eta: 0:23:22 time: 0.0803 data: 0.0024 max mem: 19788 +Test: [ 2100/21770] eta: 0:23:13 time: 0.0762 data: 0.0021 max mem: 19788 +Test: [ 2200/21770] eta: 0:23:02 time: 0.0636 data: 0.0018 max mem: 19788 +Test: [ 2300/21770] eta: 0:22:50 time: 0.0655 data: 0.0020 max mem: 19788 +Test: [ 2400/21770] eta: 0:22:48 time: 0.0826 data: 0.0025 max mem: 19788 +Test: [ 2500/21770] eta: 0:22:40 time: 0.0697 data: 0.0022 max mem: 19788 +Test: [ 2600/21770] eta: 0:22:36 time: 0.0676 data: 0.0022 max mem: 19788 +Test: [ 2700/21770] eta: 0:22:32 time: 0.0770 data: 0.0023 max mem: 19788 +Test: [ 2800/21770] eta: 0:22:26 time: 0.0859 data: 0.0028 max mem: 19788 +Test: [ 2900/21770] eta: 0:22:19 time: 0.0779 data: 0.0023 max mem: 19788 +Test: [ 3000/21770] eta: 0:22:11 time: 0.0810 data: 0.0021 max mem: 19788 +Test: [ 3100/21770] eta: 0:22:08 time: 0.0688 data: 0.0021 max mem: 19788 +Test: [ 3200/21770] eta: 0:22:04 time: 0.0729 data: 0.0023 max mem: 19788 +Test: [ 3300/21770] eta: 0:21:58 time: 0.0662 data: 0.0020 max mem: 19788 +Test: [ 3400/21770] eta: 0:21:49 time: 0.0731 data: 0.0019 max mem: 19788 +Test: [ 3500/21770] eta: 0:21:42 time: 0.0855 data: 0.0026 max mem: 19788 +Test: [ 3600/21770] eta: 0:21:35 time: 0.0674 data: 0.0022 max mem: 19788 +Test: [ 3700/21770] eta: 0:21:26 time: 0.0643 data: 0.0021 max mem: 19788 +Test: [ 3800/21770] eta: 0:21:21 time: 0.0651 data: 0.0020 max mem: 19788 +Test: [ 3900/21770] eta: 0:21:15 time: 0.0658 data: 0.0020 max mem: 19788 +Test: [ 4000/21770] eta: 0:21:06 time: 0.0706 data: 0.0021 max mem: 19788 +Test: [ 4100/21770] eta: 0:20:58 time: 0.0715 data: 0.0020 max mem: 19788 +Test: [ 4200/21770] eta: 0:20:52 time: 0.0671 data: 0.0021 max mem: 19788 +Test: [ 4300/21770] eta: 0:20:47 time: 0.0806 data: 0.0027 max mem: 19788 +Test: [ 4400/21770] eta: 0:20:41 time: 0.0656 data: 0.0021 max mem: 19788 +Test: [ 4500/21770] eta: 0:20:35 time: 0.0848 data: 0.0026 max mem: 19788 +Test: [ 4600/21770] eta: 0:20:26 time: 0.0662 data: 0.0019 max mem: 19788 +Test: [ 4700/21770] eta: 0:20:21 time: 0.0836 data: 0.0027 max mem: 19788 +Test: [ 4800/21770] eta: 0:20:13 time: 0.0712 data: 0.0023 max mem: 19788 +Test: [ 4900/21770] eta: 0:20:06 time: 0.0726 data: 0.0024 max mem: 19788 +Test: [ 5000/21770] eta: 0:20:01 time: 0.0720 data: 0.0021 max mem: 19788 +Test: [ 5100/21770] eta: 0:19:53 time: 0.0650 data: 0.0022 max mem: 19788 +Test: [ 5200/21770] eta: 0:19:46 time: 0.0742 data: 0.0023 max mem: 19788 +Test: [ 5300/21770] eta: 0:19:38 time: 0.0754 data: 0.0024 max mem: 19788 +Test: [ 5400/21770] eta: 0:19:32 time: 0.0847 data: 0.0025 max mem: 19788 +Test: [ 5500/21770] eta: 0:19:27 time: 0.0781 data: 0.0026 max mem: 19788 +Test: [ 5600/21770] eta: 0:19:22 time: 0.0769 data: 0.0020 max mem: 19788 +Test: [ 5700/21770] eta: 0:19:15 time: 0.0632 data: 0.0019 max mem: 19788 +Test: [ 5800/21770] eta: 0:19:08 time: 0.0778 data: 0.0022 max mem: 19788 +Test: [ 5900/21770] eta: 0:19:01 time: 0.0768 data: 0.0021 max mem: 19788 +Test: [ 6000/21770] eta: 0:18:54 time: 0.0697 data: 0.0021 max mem: 19788 +Test: [ 6100/21770] eta: 0:18:46 time: 0.0632 data: 0.0019 max mem: 19788 +Test: [ 6200/21770] eta: 0:18:39 time: 0.0659 data: 0.0020 max mem: 19788 +Test: [ 6300/21770] eta: 0:18:31 time: 0.0748 data: 0.0023 max mem: 19788 +Test: [ 6400/21770] eta: 0:18:22 time: 0.0640 data: 0.0020 max mem: 19788 +Test: [ 6500/21770] eta: 0:18:14 time: 0.0626 data: 0.0020 max mem: 19788 +Test: [ 6600/21770] eta: 0:18:07 time: 0.0757 data: 0.0023 max mem: 19788 +Test: [ 6700/21770] eta: 0:18:00 time: 0.0715 data: 0.0020 max mem: 19788 +Test: [ 6800/21770] eta: 0:17:53 time: 0.0679 data: 0.0020 max mem: 19788 +Test: [ 6900/21770] eta: 0:17:46 time: 0.0833 data: 0.0027 max mem: 19788 +Test: [ 7000/21770] eta: 0:17:41 time: 0.0825 data: 0.0026 max mem: 19788 +Test: [ 7100/21770] eta: 0:17:34 time: 0.0650 data: 0.0019 max mem: 19788 +Test: [ 7200/21770] eta: 0:17:27 time: 0.0778 data: 0.0025 max mem: 19788 +Test: [ 7300/21770] eta: 0:17:19 time: 0.0739 data: 0.0020 max mem: 19788 +Test: [ 7400/21770] eta: 0:17:12 time: 0.0637 data: 0.0017 max mem: 19788 +Test: [ 7500/21770] eta: 0:17:05 time: 0.0679 data: 0.0019 max mem: 19788 +Test: [ 7600/21770] eta: 0:16:58 time: 0.0724 data: 0.0023 max mem: 19788 +Test: [ 7700/21770] eta: 0:16:51 time: 0.0648 data: 0.0022 max mem: 19788 +Test: [ 7800/21770] eta: 0:16:45 time: 0.0839 data: 0.0026 max mem: 19788 +Test: [ 7900/21770] eta: 0:16:37 time: 0.0681 data: 0.0019 max mem: 19788 +Test: [ 8000/21770] eta: 0:16:30 time: 0.0694 data: 0.0021 max mem: 19788 +Test: [ 8100/21770] eta: 0:16:23 time: 0.0641 data: 0.0021 max mem: 19788 +Test: [ 8200/21770] eta: 0:16:15 time: 0.0656 data: 0.0019 max mem: 19788 +Test: [ 8300/21770] eta: 0:16:06 time: 0.0622 data: 0.0019 max mem: 19788 +Test: [ 8400/21770] eta: 0:15:59 time: 0.0742 data: 0.0022 max mem: 19788 +Test: [ 8500/21770] eta: 0:15:52 time: 0.0662 data: 0.0020 max mem: 19788 +Test: [ 8600/21770] eta: 0:15:45 time: 0.0699 data: 0.0023 max mem: 19788 +Test: [ 8700/21770] eta: 0:15:37 time: 0.0729 data: 0.0021 max mem: 19788 +Test: [ 8800/21770] eta: 0:15:29 time: 0.0717 data: 0.0021 max mem: 19788 +Test: [ 8900/21770] eta: 0:15:22 time: 0.0798 data: 0.0023 max mem: 19788 +Test: [ 9000/21770] eta: 0:15:16 time: 0.0782 data: 0.0021 max mem: 19788 +Test: [ 9100/21770] eta: 0:15:10 time: 0.0725 data: 0.0023 max mem: 19788 +Test: [ 9200/21770] eta: 0:15:03 time: 0.0633 data: 0.0019 max mem: 19788 +Test: [ 9300/21770] eta: 0:14:55 time: 0.0637 data: 0.0019 max mem: 19788 +Test: [ 9400/21770] eta: 0:14:48 time: 0.0685 data: 0.0022 max mem: 19788 +Test: [ 9500/21770] eta: 0:14:41 time: 0.0680 data: 0.0020 max mem: 19788 +Test: [ 9600/21770] eta: 0:14:34 time: 0.0826 data: 0.0026 max mem: 19788 +Test: [ 9700/21770] eta: 0:14:26 time: 0.0676 data: 0.0021 max mem: 19788 +Test: [ 9800/21770] eta: 0:14:20 time: 0.0853 data: 0.0026 max mem: 19788 +Test: [ 9900/21770] eta: 0:14:13 time: 0.0662 data: 0.0019 max mem: 19788 +Test: [10000/21770] eta: 0:14:06 time: 0.0648 data: 0.0019 max mem: 19788 +Test: [10100/21770] eta: 0:13:59 time: 0.0814 data: 0.0020 max mem: 19788 +Test: [10200/21770] eta: 0:13:52 time: 0.0854 data: 0.0027 max mem: 19788 +Test: [10300/21770] eta: 0:13:45 time: 0.0699 data: 0.0022 max mem: 19788 +Test: [10400/21770] eta: 0:13:38 time: 0.0782 data: 0.0026 max mem: 19788 +Test: [10500/21770] eta: 0:13:31 time: 0.0649 data: 0.0020 max mem: 19788 +Test: [10600/21770] eta: 0:13:24 time: 0.0767 data: 0.0023 max mem: 19788 +Test: [10700/21770] eta: 0:13:17 time: 0.0766 data: 0.0024 max mem: 19788 +Test: [10800/21770] eta: 0:13:11 time: 0.0853 data: 0.0027 max mem: 19788 +Test: [10900/21770] eta: 0:13:04 time: 0.0726 data: 0.0022 max mem: 19788 +Test: [11000/21770] eta: 0:12:57 time: 0.0706 data: 0.0021 max mem: 19788 +Test: [11100/21770] eta: 0:12:50 time: 0.0755 data: 0.0025 max mem: 19788 +Test: [11200/21770] eta: 0:12:43 time: 0.0755 data: 0.0023 max mem: 19788 +Test: [11300/21770] eta: 0:12:36 time: 0.0813 data: 0.0026 max mem: 19788 +Test: [11400/21770] eta: 0:12:28 time: 0.0683 data: 0.0022 max mem: 19788 +Test: [11500/21770] eta: 0:12:21 time: 0.0649 data: 0.0020 max mem: 19788 +Test: [11600/21770] eta: 0:12:13 time: 0.0634 data: 0.0019 max mem: 19788 +Test: [11700/21770] eta: 0:12:06 time: 0.0784 data: 0.0023 max mem: 19788 +Test: [11800/21770] eta: 0:12:00 time: 0.0712 data: 0.0024 max mem: 19788 +Test: [11900/21770] eta: 0:11:53 time: 0.0732 data: 0.0024 max mem: 19788 +Test: [12000/21770] eta: 0:11:45 time: 0.0674 data: 0.0019 max mem: 19788 +Test: [12100/21770] eta: 0:11:38 time: 0.0656 data: 0.0019 max mem: 19788 +Test: [12200/21770] eta: 0:11:31 time: 0.0832 data: 0.0026 max mem: 19788 +Test: [12300/21770] eta: 0:11:24 time: 0.0661 data: 0.0021 max mem: 19788 +Test: [12400/21770] eta: 0:11:16 time: 0.0666 data: 0.0021 max mem: 19788 +Test: [12500/21770] eta: 0:11:09 time: 0.0653 data: 0.0019 max mem: 19788 +Test: [12600/21770] eta: 0:11:02 time: 0.0783 data: 0.0025 max mem: 19788 +Test: [12700/21770] eta: 0:10:54 time: 0.0787 data: 0.0023 max mem: 19788 +Test: [12800/21770] eta: 0:10:47 time: 0.0675 data: 0.0021 max mem: 19788 +Test: [12900/21770] eta: 0:10:40 time: 0.0718 data: 0.0022 max mem: 19788 +Test: [13000/21770] eta: 0:10:33 time: 0.0651 data: 0.0020 max mem: 19788 +Test: [13100/21770] eta: 0:10:25 time: 0.0700 data: 0.0020 max mem: 19788 +Test: [13200/21770] eta: 0:10:18 time: 0.0675 data: 0.0022 max mem: 19788 +Test: [13300/21770] eta: 0:10:11 time: 0.0677 data: 0.0020 max mem: 19788 +Test: [13400/21770] eta: 0:10:04 time: 0.0746 data: 0.0022 max mem: 19788 +Test: [13500/21770] eta: 0:09:56 time: 0.0689 data: 0.0021 max mem: 19788 +Test: [13600/21770] eta: 0:09:49 time: 0.0651 data: 0.0018 max mem: 19788 +Test: [13700/21770] eta: 0:09:42 time: 0.0684 data: 0.0020 max mem: 19788 +Test: [13800/21770] eta: 0:09:35 time: 0.0690 data: 0.0022 max mem: 19788 +Test: [13900/21770] eta: 0:09:28 time: 0.0661 data: 0.0019 max mem: 19788 +Test: [14000/21770] eta: 0:09:21 time: 0.0799 data: 0.0024 max mem: 19788 +Test: [14100/21770] eta: 0:09:13 time: 0.0740 data: 0.0019 max mem: 19788 +Test: [14200/21770] eta: 0:09:06 time: 0.0707 data: 0.0022 max mem: 19788 +Test: [14300/21770] eta: 0:08:59 time: 0.0786 data: 0.0021 max mem: 19788 +Test: [14400/21770] eta: 0:08:52 time: 0.0674 data: 0.0022 max mem: 19788 +Test: [14500/21770] eta: 0:08:44 time: 0.0672 data: 0.0020 max mem: 19788 +Test: [14600/21770] eta: 0:08:37 time: 0.0699 data: 0.0023 max mem: 19788 +Test: [14700/21770] eta: 0:08:30 time: 0.0656 data: 0.0022 max mem: 19788 +Test: [14800/21770] eta: 0:08:22 time: 0.0670 data: 0.0020 max mem: 19788 +Test: [14900/21770] eta: 0:08:15 time: 0.0795 data: 0.0022 max mem: 19788 +Test: [15000/21770] eta: 0:08:08 time: 0.0675 data: 0.0022 max mem: 19788 +Test: [15100/21770] eta: 0:08:00 time: 0.0693 data: 0.0021 max mem: 19788 +Test: [15200/21770] eta: 0:07:53 time: 0.0651 data: 0.0020 max mem: 19788 +Test: [15300/21770] eta: 0:07:46 time: 0.0805 data: 0.0025 max mem: 19788 +Test: [15400/21770] eta: 0:07:39 time: 0.0766 data: 0.0023 max mem: 19788 +Test: [15500/21770] eta: 0:07:32 time: 0.0669 data: 0.0020 max mem: 19788 +Test: [15600/21770] eta: 0:07:24 time: 0.0807 data: 0.0025 max mem: 19788 +Test: [15700/21770] eta: 0:07:17 time: 0.0644 data: 0.0018 max mem: 19788 +Test: [15800/21770] eta: 0:07:10 time: 0.0654 data: 0.0020 max mem: 19788 +Test: [15900/21770] eta: 0:07:03 time: 0.0702 data: 0.0020 max mem: 19788 +Test: [16000/21770] eta: 0:06:56 time: 0.0763 data: 0.0020 max mem: 19788 +Test: 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0:05:14 time: 0.0664 data: 0.0019 max mem: 19788 +Test: [17500/21770] eta: 0:05:07 time: 0.0689 data: 0.0020 max mem: 19788 +Test: [17600/21770] eta: 0:05:00 time: 0.0787 data: 0.0023 max mem: 19788 +Test: [17700/21770] eta: 0:04:52 time: 0.0626 data: 0.0018 max mem: 19788 +Test: [17800/21770] eta: 0:04:45 time: 0.0676 data: 0.0020 max mem: 19788 +Test: [17900/21770] eta: 0:04:38 time: 0.0782 data: 0.0025 max mem: 19788 +Test: [18000/21770] eta: 0:04:31 time: 0.0705 data: 0.0025 max mem: 19788 +Test: [18100/21770] eta: 0:04:24 time: 0.0645 data: 0.0019 max mem: 19788 +Test: [18200/21770] eta: 0:04:16 time: 0.0694 data: 0.0020 max mem: 19788 +Test: [18300/21770] eta: 0:04:09 time: 0.0654 data: 0.0019 max mem: 19788 +Test: [18400/21770] eta: 0:04:02 time: 0.0658 data: 0.0019 max mem: 19788 +Test: [18500/21770] eta: 0:03:55 time: 0.0639 data: 0.0018 max mem: 19788 +Test: [18600/21770] eta: 0:03:48 time: 0.0733 data: 0.0023 max mem: 19788 +Test: [18700/21770] eta: 0:03:40 time: 0.0843 data: 0.0026 max mem: 19788 +Test: [18800/21770] eta: 0:03:33 time: 0.0744 data: 0.0024 max mem: 19788 +Test: [18900/21770] eta: 0:03:26 time: 0.0761 data: 0.0023 max mem: 19788 +Test: [19000/21770] eta: 0:03:19 time: 0.0738 data: 0.0022 max mem: 19788 +Test: [19100/21770] eta: 0:03:12 time: 0.0714 data: 0.0020 max mem: 19788 +Test: [19200/21770] eta: 0:03:05 time: 0.0654 data: 0.0019 max mem: 19788 +Test: [19300/21770] eta: 0:02:57 time: 0.0652 data: 0.0021 max mem: 19788 +Test: [19400/21770] eta: 0:02:50 time: 0.0656 data: 0.0019 max mem: 19788 +Test: [19500/21770] eta: 0:02:43 time: 0.0851 data: 0.0026 max mem: 19788 +Test: [19600/21770] eta: 0:02:36 time: 0.0778 data: 0.0026 max mem: 19788 +Test: [19700/21770] eta: 0:02:29 time: 0.0807 data: 0.0025 max mem: 19788 +Test: [19800/21770] eta: 0:02:21 time: 0.0681 data: 0.0021 max mem: 19788 +Test: [19900/21770] eta: 0:02:14 time: 0.0725 data: 0.0025 max mem: 19788 +Test: [20000/21770] eta: 0:02:07 time: 0.0687 data: 0.0020 max mem: 19788 +Test: [20100/21770] eta: 0:02:00 time: 0.0650 data: 0.0019 max mem: 19788 +Test: [20200/21770] eta: 0:01:53 time: 0.0856 data: 0.0027 max mem: 19788 +Test: [20300/21770] eta: 0:01:45 time: 0.0711 data: 0.0020 max mem: 19788 +Test: [20400/21770] eta: 0:01:38 time: 0.0697 data: 0.0020 max mem: 19788 +Test: [20500/21770] eta: 0:01:31 time: 0.0831 data: 0.0025 max mem: 19788 +Test: [20600/21770] eta: 0:01:24 time: 0.0642 data: 0.0019 max mem: 19788 +Test: [20700/21770] eta: 0:01:16 time: 0.0640 data: 0.0022 max mem: 19788 +Test: [20800/21770] eta: 0:01:09 time: 0.0714 data: 0.0024 max mem: 19788 +Test: [20900/21770] eta: 0:01:02 time: 0.0749 data: 0.0022 max mem: 19788 +Test: [21000/21770] eta: 0:00:55 time: 0.0825 data: 0.0028 max mem: 19788 +Test: [21100/21770] eta: 0:00:48 time: 0.0651 data: 0.0020 max mem: 19788 +Test: [21200/21770] eta: 0:00:40 time: 0.0783 data: 0.0023 max mem: 19788 +Test: [21300/21770] eta: 0:00:33 time: 0.0682 data: 0.0020 max mem: 19788 +Test: [21400/21770] eta: 0:00:26 time: 0.0680 data: 0.0020 max mem: 19788 +Test: [21500/21770] eta: 0:00:19 time: 0.0768 data: 0.0026 max mem: 19788 +Test: [21600/21770] eta: 0:00:12 time: 0.0647 data: 0.0021 max mem: 19788 +Test: [21700/21770] eta: 0:00:05 time: 0.0609 data: 0.0019 max mem: 19788 +Test: Total time: 0:26:02 +Final results: +Mean IoU is 62.31 + + precision@0.5 = 69.09 + precision@0.6 = 64.14 + precision@0.7 = 57.88 + precision@0.8 = 47.68 + precision@0.9 = 23.69 + overall IoU = 63.94 + mean IoU = 62.31 + +Mean accuracy for one-to-zero sample is 88.40 + +Average object IoU 0.6231048043352804 +Overall IoU 63.94245910644531 +Training time 4 days, 11:52:39 diff --git a/LAVT-RIS/logs/test_gref_m10_mg10_tmp010_4gpu_bs16_ang.txt b/LAVT-RIS/logs/test_gref_m10_mg10_tmp010_4gpu_bs16_ang.txt new file mode 100644 index 0000000000000000000000000000000000000000..7b4b17c5204a39a8e890a5ebf1d959269d4e4746 --- /dev/null +++ b/LAVT-RIS/logs/test_gref_m10_mg10_tmp010_4gpu_bs16_ang.txt @@ -0,0 +1,116 @@ +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/timm/models/layers/__init__.py:48: FutureWarning: Importing from timm.models.layers is deprecated, please import via timm.layers + warnings.warn(f"Importing from {__name__} is deprecated, please import via timm.layers", FutureWarning) +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torch/functional.py:478: UserWarning: torch.meshgrid: in an upcoming release, it will be required to pass the indexing argument. (Triggered internally at ../aten/src/ATen/native/TensorShape.cpp:2894.) + return _VF.meshgrid(tensors, **kwargs) # type: ignore[attr-defined] +Image size: 480 +loading dataset refcocog into memory... +creating index... +index created. +DONE (t=7.29s) +lavt_one +Window size 12! +Randomly initialize Multi-modal Swin Transformer weights. +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/5023] eta: 5:37:06 time: 4.0268 data: 1.1096 max mem: 1021 +Test: [ 100/5023] eta: 0:17:02 time: 0.1748 data: 0.0020 max mem: 1021 +Test: [ 200/5023] eta: 0:15:01 time: 0.1646 data: 0.0020 max mem: 1021 +Test: [ 300/5023] eta: 0:14:19 time: 0.1690 data: 0.0020 max mem: 1021 +Test: [ 400/5023] eta: 0:13:41 time: 0.1636 data: 0.0019 max mem: 1021 +Test: [ 500/5023] eta: 0:13:15 time: 0.1718 data: 0.0020 max mem: 1021 +Test: [ 600/5023] eta: 0:12:53 time: 0.1758 data: 0.0019 max mem: 1021 +Test: [ 700/5023] eta: 0:12:33 time: 0.1642 data: 0.0019 max mem: 1021 +Test: [ 800/5023] eta: 0:12:15 time: 0.1724 data: 0.0018 max mem: 1021 +Test: [ 900/5023] eta: 0:11:56 time: 0.1718 data: 0.0019 max mem: 1021 +Test: [1000/5023] eta: 0:11:36 time: 0.1723 data: 0.0019 max mem: 1021 +Test: [1100/5023] eta: 0:11:18 time: 0.1670 data: 0.0019 max mem: 1021 +Test: [1200/5023] eta: 0:10:59 time: 0.1698 data: 0.0017 max mem: 1021 +Test: [1300/5023] eta: 0:10:41 time: 0.1686 data: 0.0018 max mem: 1021 +Test: [1400/5023] eta: 0:10:23 time: 0.1597 data: 0.0019 max mem: 1021 +Test: [1500/5023] eta: 0:10:05 time: 0.1722 data: 0.0019 max mem: 1021 +Test: [1600/5023] eta: 0:09:47 time: 0.1677 data: 0.0019 max mem: 1021 +Test: [1700/5023] eta: 0:09:30 time: 0.1679 data: 0.0019 max mem: 1021 +Test: [1800/5023] eta: 0:09:13 time: 0.1728 data: 0.0019 max mem: 1021 +Test: [1900/5023] eta: 0:08:55 time: 0.1698 data: 0.0018 max mem: 1021 +Test: [2000/5023] eta: 0:08:37 time: 0.1773 data: 0.0019 max mem: 1021 +Test: [2100/5023] eta: 0:08:19 time: 0.1604 data: 0.0018 max mem: 1021 +Test: [2200/5023] eta: 0:08:02 time: 0.1553 data: 0.0018 max mem: 1021 +Test: [2300/5023] eta: 0:07:44 time: 0.1773 data: 0.0019 max mem: 1021 +Test: [2400/5023] eta: 0:07:27 time: 0.1665 data: 0.0018 max mem: 1021 +Test: [2500/5023] eta: 0:07:10 time: 0.1724 data: 0.0019 max mem: 1021 +Test: [2600/5023] eta: 0:06:53 time: 0.1680 data: 0.0018 max mem: 1021 +Test: [2700/5023] eta: 0:06:36 time: 0.1715 data: 0.0018 max mem: 1021 +Test: [2800/5023] eta: 0:06:19 time: 0.1737 data: 0.0019 max mem: 1021 +Test: [2900/5023] eta: 0:06:02 time: 0.1764 data: 0.0019 max mem: 1021 +Test: [3000/5023] eta: 0:05:45 time: 0.1712 data: 0.0018 max mem: 1021 +Test: [3100/5023] eta: 0:05:28 time: 0.1764 data: 0.0018 max mem: 1021 +Test: [3200/5023] eta: 0:05:10 time: 0.1683 data: 0.0020 max mem: 1021 +Test: [3300/5023] eta: 0:04:53 time: 0.1679 data: 0.0019 max mem: 1021 +Test: [3400/5023] eta: 0:04:36 time: 0.1516 data: 0.0018 max mem: 1021 +Test: [3500/5023] eta: 0:04:19 time: 0.1636 data: 0.0018 max mem: 1021 +Test: [3600/5023] eta: 0:04:02 time: 0.1746 data: 0.0020 max mem: 1021 +Test: [3700/5023] eta: 0:03:45 time: 0.1731 data: 0.0019 max mem: 1021 +Test: [3800/5023] eta: 0:03:28 time: 0.1802 data: 0.0020 max mem: 1021 +Test: [3900/5023] eta: 0:03:11 time: 0.1660 data: 0.0018 max mem: 1021 +Test: [4000/5023] eta: 0:02:54 time: 0.1589 data: 0.0019 max mem: 1021 +Test: [4100/5023] eta: 0:02:36 time: 0.1654 data: 0.0019 max mem: 1021 +Test: [4200/5023] eta: 0:02:19 time: 0.1684 data: 0.0019 max mem: 1021 +Test: [4300/5023] eta: 0:02:02 time: 0.1710 data: 0.0017 max mem: 1021 +Test: [4400/5023] eta: 0:01:45 time: 0.1634 data: 0.0018 max mem: 1021 +Test: [4500/5023] eta: 0:01:28 time: 0.1584 data: 0.0019 max mem: 1021 +Test: [4600/5023] eta: 0:01:11 time: 0.1562 data: 0.0020 max mem: 1021 +Test: [4700/5023] eta: 0:00:54 time: 0.1737 data: 0.0020 max mem: 1021 +Test: [4800/5023] eta: 0:00:37 time: 0.1673 data: 0.0018 max mem: 1021 +Test: [4900/5023] eta: 0:00:20 time: 0.1678 data: 0.0019 max mem: 1021 +Test: [5000/5023] eta: 0:00:03 time: 0.1716 data: 0.0018 max mem: 1021 +Test: Total time: 0:14:11 +Final results: +Mean IoU is 65.62 + + precision@0.5 = 73.84 + precision@0.6 = 68.64 + precision@0.7 = 62.16 + precision@0.8 = 51.44 + precision@0.9 = 26.92 + overall IoU = 63.82 + +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/timm/models/layers/__init__.py:48: FutureWarning: Importing from timm.models.layers is deprecated, please import via timm.layers + warnings.warn(f"Importing from {__name__} is deprecated, please import via timm.layers", FutureWarning) +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torch/functional.py:478: UserWarning: torch.meshgrid: in an upcoming release, it will be required to pass the indexing argument. (Triggered internally at ../aten/src/ATen/native/TensorShape.cpp:2894.) + return _VF.meshgrid(tensors, **kwargs) # type: ignore[attr-defined] +Image size: 480 +Easy & Hard Example Experiments - dataset : refcocog, split : motion +loading dataset refcocog into memory... +creating index... +index created. +DONE (t=6.72s) +lavt_one +Window size 12! +Randomly initialize Multi-modal Swin Transformer weights. +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/151] eta: 0:08:57 time: 3.5600 data: 1.0243 max mem: 1021 +Test: [100/151] eta: 0:00:06 time: 0.0902 data: 0.0019 max mem: 1021 +Test: Total time: 0:00:17 +Final results: +Mean IoU is 57.49 + + precision@0.5 = 63.58 + precision@0.6 = 62.25 + precision@0.7 = 58.94 + precision@0.8 = 50.99 + precision@0.9 = 27.81 + overall IoU = 49.78 + diff --git a/LAVT-RIS/logs/test_gref_m10_mg12_tmp007_4gpu_bs32_ang.txt b/LAVT-RIS/logs/test_gref_m10_mg12_tmp007_4gpu_bs32_ang.txt new file mode 100644 index 0000000000000000000000000000000000000000..340f02e2bcd37dfa27f25449db7c199bba203871 --- /dev/null +++ b/LAVT-RIS/logs/test_gref_m10_mg12_tmp007_4gpu_bs32_ang.txt @@ -0,0 +1,116 @@ +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/timm/models/layers/__init__.py:48: FutureWarning: Importing from timm.models.layers is deprecated, please import via timm.layers + warnings.warn(f"Importing from {__name__} is deprecated, please import via timm.layers", FutureWarning) +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torch/functional.py:478: UserWarning: torch.meshgrid: in an upcoming release, it will be required to pass the indexing argument. (Triggered internally at ../aten/src/ATen/native/TensorShape.cpp:2894.) + return _VF.meshgrid(tensors, **kwargs) # type: ignore[attr-defined] +Image size: 480 +loading dataset refcocog into memory... +creating index... +index created. +DONE (t=7.17s) +lavt_one +Window size 12! +Randomly initialize Multi-modal Swin Transformer weights. +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/5023] eta: 1 day, 6:53:34 time: 22.1410 data: 1.3678 max mem: 1021 +Test: [ 100/5023] eta: 0:31:16 time: 0.1666 data: 0.0018 max mem: 1021 +Test: [ 200/5023] eta: 0:21:49 time: 0.1606 data: 0.0017 max mem: 1021 +Test: [ 300/5023] eta: 0:18:36 time: 0.1651 data: 0.0019 max mem: 1021 +Test: [ 400/5023] eta: 0:16:47 time: 0.1623 data: 0.0018 max mem: 1021 +Test: [ 500/5023] eta: 0:15:36 time: 0.1651 data: 0.0018 max mem: 1021 +Test: [ 600/5023] eta: 0:14:43 time: 0.1689 data: 0.0017 max mem: 1021 +Test: [ 700/5023] eta: 0:14:01 time: 0.1570 data: 0.0017 max mem: 1021 +Test: [ 800/5023] eta: 0:13:27 time: 0.1659 data: 0.0016 max mem: 1021 +Test: [ 900/5023] eta: 0:12:56 time: 0.1672 data: 0.0018 max mem: 1021 +Test: [1000/5023] eta: 0:12:27 time: 0.1671 data: 0.0017 max mem: 1021 +Test: [1100/5023] eta: 0:12:00 time: 0.1619 data: 0.0018 max mem: 1021 +Test: [1200/5023] eta: 0:11:36 time: 0.1659 data: 0.0016 max mem: 1021 +Test: [1300/5023] eta: 0:11:12 time: 0.1608 data: 0.0017 max mem: 1021 +Test: [1400/5023] eta: 0:10:49 time: 0.1527 data: 0.0017 max mem: 1021 +Test: [1500/5023] eta: 0:10:27 time: 0.1660 data: 0.0017 max mem: 1021 +Test: [1600/5023] eta: 0:10:06 time: 0.1619 data: 0.0017 max mem: 1021 +Test: [1700/5023] eta: 0:09:45 time: 0.1618 data: 0.0016 max mem: 1021 +Test: [1800/5023] eta: 0:09:26 time: 0.1653 data: 0.0017 max mem: 1021 +Test: [1900/5023] eta: 0:09:06 time: 0.1657 data: 0.0017 max mem: 1021 +Test: [2000/5023] eta: 0:08:47 time: 0.1715 data: 0.0017 max mem: 1021 +Test: [2100/5023] eta: 0:08:28 time: 0.1535 data: 0.0016 max mem: 1021 +Test: [2200/5023] eta: 0:08:09 time: 0.1491 data: 0.0016 max mem: 1021 +Test: [2300/5023] eta: 0:07:50 time: 0.1710 data: 0.0017 max mem: 1021 +Test: [2400/5023] eta: 0:07:32 time: 0.1611 data: 0.0018 max mem: 1021 +Test: [2500/5023] eta: 0:07:14 time: 0.1651 data: 0.0017 max mem: 1021 +Test: [2600/5023] eta: 0:06:56 time: 0.1612 data: 0.0016 max mem: 1021 +Test: [2700/5023] eta: 0:06:38 time: 0.1658 data: 0.0018 max mem: 1021 +Test: [2800/5023] eta: 0:06:20 time: 0.1654 data: 0.0017 max mem: 1021 +Test: [2900/5023] eta: 0:06:03 time: 0.1699 data: 0.0017 max mem: 1021 +Test: [3000/5023] eta: 0:05:45 time: 0.1653 data: 0.0016 max mem: 1021 +Test: [3100/5023] eta: 0:05:27 time: 0.1699 data: 0.0016 max mem: 1021 +Test: [3200/5023] eta: 0:05:10 time: 0.1621 data: 0.0017 max mem: 1021 +Test: [3300/5023] eta: 0:04:52 time: 0.1620 data: 0.0017 max mem: 1021 +Test: [3400/5023] eta: 0:04:35 time: 0.1450 data: 0.0016 max mem: 1021 +Test: [3500/5023] eta: 0:04:17 time: 0.1569 data: 0.0016 max mem: 1021 +Test: [3600/5023] eta: 0:04:00 time: 0.1652 data: 0.0018 max mem: 1021 +Test: [3700/5023] eta: 0:03:43 time: 0.1655 data: 0.0017 max mem: 1021 +Test: [3800/5023] eta: 0:03:26 time: 0.1694 data: 0.0017 max mem: 1021 +Test: [3900/5023] eta: 0:03:09 time: 0.1580 data: 0.0018 max mem: 1021 +Test: [4000/5023] eta: 0:02:52 time: 0.1537 data: 0.0018 max mem: 1021 +Test: [4100/5023] eta: 0:02:35 time: 0.1574 data: 0.0017 max mem: 1021 +Test: [4200/5023] eta: 0:02:18 time: 0.1613 data: 0.0017 max mem: 1021 +Test: [4300/5023] eta: 0:02:01 time: 0.1649 data: 0.0016 max mem: 1021 +Test: [4400/5023] eta: 0:01:44 time: 0.1568 data: 0.0017 max mem: 1021 +Test: [4500/5023] eta: 0:01:27 time: 0.1533 data: 0.0017 max mem: 1021 +Test: [4600/5023] eta: 0:01:10 time: 0.1488 data: 0.0017 max mem: 1021 +Test: [4700/5023] eta: 0:00:53 time: 0.1644 data: 0.0017 max mem: 1021 +Test: [4800/5023] eta: 0:00:37 time: 0.1608 data: 0.0016 max mem: 1021 +Test: [4900/5023] eta: 0:00:20 time: 0.1613 data: 0.0017 max mem: 1021 +Test: [5000/5023] eta: 0:00:03 time: 0.1658 data: 0.0018 max mem: 1021 +Test: Total time: 0:13:57 +Final results: +Mean IoU is 65.42 + + precision@0.5 = 73.56 + precision@0.6 = 68.73 + precision@0.7 = 61.66 + precision@0.8 = 50.79 + precision@0.9 = 26.92 + overall IoU = 63.83 + +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/timm/models/layers/__init__.py:48: FutureWarning: Importing from timm.models.layers is deprecated, please import via timm.layers + warnings.warn(f"Importing from {__name__} is deprecated, please import via timm.layers", FutureWarning) +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torch/functional.py:478: UserWarning: torch.meshgrid: in an upcoming release, it will be required to pass the indexing argument. (Triggered internally at ../aten/src/ATen/native/TensorShape.cpp:2894.) + return _VF.meshgrid(tensors, **kwargs) # type: ignore[attr-defined] +Image size: 480 +Easy & Hard Example Experiments - dataset : refcocog, split : motion +loading dataset refcocog into memory... +creating index... +index created. +DONE (t=6.38s) +lavt_one +Window size 12! +Randomly initialize Multi-modal Swin Transformer weights. +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/151] eta: 0:08:37 time: 3.4244 data: 1.1409 max mem: 1021 +Test: [100/151] eta: 0:00:06 time: 0.0868 data: 0.0018 max mem: 1021 +Test: Total time: 0:00:16 +Final results: +Mean IoU is 57.05 + + precision@0.5 = 64.24 + precision@0.6 = 61.59 + precision@0.7 = 56.95 + precision@0.8 = 51.66 + precision@0.9 = 31.79 + overall IoU = 50.44 + diff --git a/LAVT-RIS/logs/test_gref_m10_mg15_tmp010_4gpu_bs32_ang.txt b/LAVT-RIS/logs/test_gref_m10_mg15_tmp010_4gpu_bs32_ang.txt new file mode 100644 index 0000000000000000000000000000000000000000..ea88592517fea043704483c870dfd631f7892a7d --- /dev/null +++ b/LAVT-RIS/logs/test_gref_m10_mg15_tmp010_4gpu_bs32_ang.txt @@ -0,0 +1,116 @@ +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/timm/models/layers/__init__.py:48: FutureWarning: Importing from timm.models.layers is deprecated, please import via timm.layers + warnings.warn(f"Importing from {__name__} is deprecated, please import via timm.layers", FutureWarning) +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torch/functional.py:478: UserWarning: torch.meshgrid: in an upcoming release, it will be required to pass the indexing argument. (Triggered internally at ../aten/src/ATen/native/TensorShape.cpp:2894.) + return _VF.meshgrid(tensors, **kwargs) # type: ignore[attr-defined] +Image size: 480 +loading dataset refcocog into memory... +creating index... +index created. +DONE (t=6.51s) +lavt_one +Window size 12! +Randomly initialize Multi-modal Swin Transformer weights. +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/5023] eta: 8:09:27 time: 5.8466 data: 1.0544 max mem: 1021 +Test: [ 100/5023] eta: 0:18:04 time: 0.1681 data: 0.0017 max mem: 1021 +Test: [ 200/5023] eta: 0:15:20 time: 0.1616 data: 0.0017 max mem: 1021 +Test: [ 300/5023] eta: 0:14:23 time: 0.1650 data: 0.0016 max mem: 1021 +Test: [ 400/5023] eta: 0:13:41 time: 0.1617 data: 0.0016 max mem: 1021 +Test: [ 500/5023] eta: 0:13:10 time: 0.1654 data: 0.0017 max mem: 1021 +Test: [ 600/5023] eta: 0:12:45 time: 0.1702 data: 0.0017 max mem: 1021 +Test: [ 700/5023] eta: 0:12:23 time: 0.1584 data: 0.0018 max mem: 1021 +Test: [ 800/5023] eta: 0:12:03 time: 0.1659 data: 0.0016 max mem: 1021 +Test: [ 900/5023] eta: 0:11:43 time: 0.1661 data: 0.0016 max mem: 1021 +Test: [1000/5023] eta: 0:11:22 time: 0.1666 data: 0.0018 max mem: 1021 +Test: [1100/5023] eta: 0:11:03 time: 0.1631 data: 0.0016 max mem: 1021 +Test: [1200/5023] eta: 0:10:45 time: 0.1666 data: 0.0016 max mem: 1021 +Test: [1300/5023] eta: 0:10:27 time: 0.1628 data: 0.0016 max mem: 1021 +Test: [1400/5023] eta: 0:10:08 time: 0.1541 data: 0.0016 max mem: 1021 +Test: [1500/5023] eta: 0:09:51 time: 0.1665 data: 0.0016 max mem: 1021 +Test: [1600/5023] eta: 0:09:32 time: 0.1621 data: 0.0016 max mem: 1021 +Test: [1700/5023] eta: 0:09:15 time: 0.1620 data: 0.0016 max mem: 1021 +Test: [1800/5023] eta: 0:08:59 time: 0.1673 data: 0.0017 max mem: 1021 +Test: [1900/5023] eta: 0:08:41 time: 0.1670 data: 0.0017 max mem: 1021 +Test: [2000/5023] eta: 0:08:24 time: 0.1712 data: 0.0017 max mem: 1021 +Test: [2100/5023] eta: 0:08:07 time: 0.1543 data: 0.0016 max mem: 1021 +Test: [2200/5023] eta: 0:07:49 time: 0.1510 data: 0.0016 max mem: 1021 +Test: [2300/5023] eta: 0:07:32 time: 0.1719 data: 0.0018 max mem: 1021 +Test: [2400/5023] eta: 0:07:16 time: 0.1631 data: 0.0019 max mem: 1021 +Test: [2500/5023] eta: 0:06:59 time: 0.1669 data: 0.0017 max mem: 1021 +Test: [2600/5023] eta: 0:06:42 time: 0.1627 data: 0.0018 max mem: 1021 +Test: [2700/5023] eta: 0:06:26 time: 0.1666 data: 0.0017 max mem: 1021 +Test: [2800/5023] eta: 0:06:09 time: 0.1672 data: 0.0017 max mem: 1021 +Test: [2900/5023] eta: 0:05:52 time: 0.1709 data: 0.0017 max mem: 1021 +Test: [3000/5023] eta: 0:05:35 time: 0.1657 data: 0.0016 max mem: 1021 +Test: [3100/5023] eta: 0:05:19 time: 0.1697 data: 0.0016 max mem: 1021 +Test: [3200/5023] eta: 0:05:02 time: 0.1631 data: 0.0018 max mem: 1021 +Test: [3300/5023] eta: 0:04:45 time: 0.1636 data: 0.0018 max mem: 1021 +Test: [3400/5023] eta: 0:04:28 time: 0.1451 data: 0.0016 max mem: 1021 +Test: [3500/5023] eta: 0:04:12 time: 0.1586 data: 0.0017 max mem: 1021 +Test: [3600/5023] eta: 0:03:55 time: 0.1665 data: 0.0017 max mem: 1021 +Test: [3700/5023] eta: 0:03:38 time: 0.1676 data: 0.0018 max mem: 1021 +Test: [3800/5023] eta: 0:03:22 time: 0.1712 data: 0.0017 max mem: 1021 +Test: [3900/5023] eta: 0:03:05 time: 0.1584 data: 0.0017 max mem: 1021 +Test: [4000/5023] eta: 0:02:49 time: 0.1535 data: 0.0017 max mem: 1021 +Test: [4100/5023] eta: 0:02:32 time: 0.1583 data: 0.0017 max mem: 1021 +Test: [4200/5023] eta: 0:02:15 time: 0.1629 data: 0.0017 max mem: 1021 +Test: [4300/5023] eta: 0:01:59 time: 0.1663 data: 0.0016 max mem: 1021 +Test: [4400/5023] eta: 0:01:42 time: 0.1581 data: 0.0017 max mem: 1021 +Test: [4500/5023] eta: 0:01:26 time: 0.1552 data: 0.0016 max mem: 1021 +Test: [4600/5023] eta: 0:01:09 time: 0.1492 data: 0.0017 max mem: 1021 +Test: [4700/5023] eta: 0:00:53 time: 0.1652 data: 0.0017 max mem: 1021 +Test: [4800/5023] eta: 0:00:36 time: 0.1618 data: 0.0016 max mem: 1021 +Test: [4900/5023] eta: 0:00:20 time: 0.1620 data: 0.0017 max mem: 1021 +Test: [5000/5023] eta: 0:00:03 time: 0.1661 data: 0.0017 max mem: 1021 +Test: Total time: 0:13:45 +Final results: +Mean IoU is 64.99 + + precision@0.5 = 72.83 + precision@0.6 = 68.12 + precision@0.7 = 60.85 + precision@0.8 = 50.27 + precision@0.9 = 25.92 + overall IoU = 63.40 + +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/timm/models/layers/__init__.py:48: FutureWarning: Importing from timm.models.layers is deprecated, please import via timm.layers + warnings.warn(f"Importing from {__name__} is deprecated, please import via timm.layers", FutureWarning) +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torch/functional.py:478: UserWarning: torch.meshgrid: in an upcoming release, it will be required to pass the indexing argument. (Triggered internally at ../aten/src/ATen/native/TensorShape.cpp:2894.) + return _VF.meshgrid(tensors, **kwargs) # type: ignore[attr-defined] +Image size: 480 +Easy & Hard Example Experiments - dataset : refcocog, split : motion +loading dataset refcocog into memory... +creating index... +index created. +DONE (t=6.42s) +lavt_one +Window size 12! +Randomly initialize Multi-modal Swin Transformer weights. +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum. + warnings.warn( +Test: [ 0/151] eta: 0:08:30 time: 3.3821 data: 1.0747 max mem: 1021 +Test: [100/151] eta: 0:00:06 time: 0.0859 data: 0.0017 max mem: 1021 +Test: Total time: 0:00:16 +Final results: +Mean IoU is 53.89 + + precision@0.5 = 57.62 + precision@0.6 = 56.95 + precision@0.7 = 53.64 + precision@0.8 = 50.99 + precision@0.9 = 25.83 + overall IoU = 49.18 + diff --git a/LAVT-RIS/models/gref_m05_tmp010_4gpu_bs32_orig/model_best_gref_m05_tmp010_4gpu_bs32_orig.pth b/LAVT-RIS/models/gref_m05_tmp010_4gpu_bs32_orig/model_best_gref_m05_tmp010_4gpu_bs32_orig.pth new file mode 100644 index 0000000000000000000000000000000000000000..457e41b3308965d4564b020a745088109491bcb6 --- /dev/null +++ b/LAVT-RIS/models/gref_m05_tmp010_4gpu_bs32_orig/model_best_gref_m05_tmp010_4gpu_bs32_orig.pth @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:7fb86578b4a1660d42243e7ceaa1a323e24d1fe1b329ac772058325aee0e66c5 +size 2416741868 diff --git 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We provide all kinds of splits here. + + + + +
Mountain View
+ +## Citation +If you used the following three datasets RefClef, RefCOCO and RefCOCO+ that were collected by UNC, please consider cite our EMNLP2014 paper; if you want to compare with our recent results, please check our ECCV2016 paper. +```bash +Kazemzadeh, Sahar, et al. "ReferItGame: Referring to Objects in Photographs of Natural Scenes." EMNLP 2014. +Yu, Licheng, et al. "Modeling Context in Referring Expressions." ECCV 2016. +``` + +## Setup +Run "make" before using the code. +It will generate ``_mask.c`` and ``_mask.so`` in ``external/`` folder. +These mask-related codes are copied from mscoco [API](https://github.com/pdollar/coco). + +## Download +Download the cleaned data and extract them into "data" folder +- 1) http://bvisionweb1.cs.unc.edu/licheng/referit/data/refclef.zip +- 2) http://bvisionweb1.cs.unc.edu/licheng/referit/data/refcoco.zip +- 3) http://bvisionweb1.cs.unc.edu/licheng/referit/data/refcoco+.zip +- 4) http://bvisionweb1.cs.unc.edu/licheng/referit/data/refcocog.zip + +## Prepare Images: +Besides, add "mscoco" into the ``data/images`` folder, which can be from [mscoco](http://mscoco.org/dataset/#overview) +COCO's images are used for RefCOCO, RefCOCO+ and refCOCOg. +For RefCLEF, please add ``saiapr_tc-12`` into ``data/images`` folder. We extracted the related 19997 images to the cleaned RefCLEF dataset, which is a subset of the original [imageCLEF](http://imageclef.org/SIAPRdata). Download the [subset](http://bvisionweb1.cs.unc.edu/licheng/referit/data/images/saiapr_tc-12.zip) and unzip it to ``data/images/saiapr_tc-12``. + +## How to use +The "refer.py" is able to load all 4 datasets with different kinds of data split by UNC, Google, UMD and UC Berkeley. +**Note for RefCOCOg, we suggest use UMD's split which has train/val/test splits and there is no overlap of images between different split.** +```bash +# locate your own data_root, and choose the dataset_splitBy you want to use +refer = REFER(data_root, dataset='refclef', splitBy='unc') +refer = REFER(data_root, dataset='refclef', splitBy='berkeley') # 2 train and 1 test images missed +refer = REFER(data_root, dataset='refcoco', splitBy='unc') +refer = REFER(data_root, dataset='refcoco', splitBy='google') +refer = REFER(data_root, dataset='refcoco+', splitBy='unc') +refer = REFER(data_root, dataset='refcocog', splitBy='google') # test split not released yet +refer = REFER(data_root, dataset='refcocog', splitBy='umd') # Recommended, including train/val/test +``` + + + diff --git a/LAVT-RIS/refer/__pycache__/refer.cpython-39.pyc b/LAVT-RIS/refer/__pycache__/refer.cpython-39.pyc new file mode 100644 index 0000000000000000000000000000000000000000..25d47736f1e86dcc9695c49066920ca62be146a7 Binary files /dev/null and b/LAVT-RIS/refer/__pycache__/refer.cpython-39.pyc differ diff --git a/LAVT-RIS/refer/__pycache__/refer_zom.cpython-39.pyc b/LAVT-RIS/refer/__pycache__/refer_zom.cpython-39.pyc new file mode 100644 index 0000000000000000000000000000000000000000..56324a723cea67569f508e157ff9fd76bfae151a Binary files /dev/null and b/LAVT-RIS/refer/__pycache__/refer_zom.cpython-39.pyc differ diff --git a/LAVT-RIS/refer/data/ref-zom/instances.json b/LAVT-RIS/refer/data/ref-zom/instances.json new file mode 100644 index 0000000000000000000000000000000000000000..0c49d7ca5abd2717a1d06ef725f807c9bfd7f357 --- /dev/null +++ b/LAVT-RIS/refer/data/ref-zom/instances.json @@ -0,0 +1,3 @@ +version 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0000000000000000000000000000000000000000..0c92b0eb65a5dbcfe2321e3afcdde6904f7dfa48 --- /dev/null +++ b/LAVT-RIS/refer/data/refcoco/refs(google).p @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:2bb306561f788f0eaa191bf7bbddb52e3a8148722f5bd99f1e3a67332259e90b +size 31776065 diff --git a/LAVT-RIS/refer/data/refcoco/refs(unc).p b/LAVT-RIS/refer/data/refcoco/refs(unc).p new file mode 100644 index 0000000000000000000000000000000000000000..84fa9ca35265d62b0697e9b706abaa65c896a00f --- /dev/null +++ b/LAVT-RIS/refer/data/refcoco/refs(unc).p @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:d4a8dd3152f130127924f9d0f0ea30f4dc43ec19e1b47bc55af972f90614f8ba +size 31742595 diff --git a/LAVT-RIS/refer/data/refcocog/instances.json b/LAVT-RIS/refer/data/refcocog/instances.json new file mode 100644 index 0000000000000000000000000000000000000000..8846484d8556771de5a226972f7e7e83e5d8b02b --- /dev/null +++ b/LAVT-RIS/refer/data/refcocog/instances.json @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:96c89b426c657f2f32247c16848ba67c3cb61fca74945da16c19e1027575c924 +size 124416571 diff --git a/LAVT-RIS/refer/data/refcocog/refs(google).p b/LAVT-RIS/refer/data/refcocog/refs(google).p new file mode 100644 index 0000000000000000000000000000000000000000..47aad2c94a92b5c1fb49c52274ea871d4871b68c --- /dev/null +++ b/LAVT-RIS/refer/data/refcocog/refs(google).p @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:e4d8320dfd15fc213b2f23f877608e22db6ab8c8b417185b1d1d95f0a951b546 +size 33853786 diff --git a/LAVT-RIS/refer/data/refcocog/refs(umd).p b/LAVT-RIS/refer/data/refcocog/refs(umd).p new file mode 100644 index 0000000000000000000000000000000000000000..f82563329d0afa65d3f84e9e8d29d06674f44998 --- /dev/null +++ b/LAVT-RIS/refer/data/refcocog/refs(umd).p @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:0331c7533537b67c2f7ac8c8bab0da2d379d1754c6f5c110fd79f70e17e7bddb +size 33853676 diff --git a/LAVT-RIS/refer/evaluation/__init__.py b/LAVT-RIS/refer/evaluation/__init__.py new file mode 100644 index 0000000000000000000000000000000000000000..66e55e9332e33fa7bceb187bb7aa2aed53428c65 --- /dev/null +++ b/LAVT-RIS/refer/evaluation/__init__.py @@ -0,0 +1,3 @@ +__author__ = 'licheng' + + diff --git a/LAVT-RIS/refer/evaluation/bleu/LICENSE b/LAVT-RIS/refer/evaluation/bleu/LICENSE new file mode 100644 index 0000000000000000000000000000000000000000..9ccf677900b5238062979c7bc1e7102e501e0be4 --- /dev/null +++ b/LAVT-RIS/refer/evaluation/bleu/LICENSE @@ -0,0 +1,19 @@ +Copyright (c) 2015 Xinlei Chen, Hao Fang, Tsung-Yi Lin, and Ramakrishna Vedantam + +Permission is hereby granted, free of charge, to any person obtaining a copy +of this software and associated documentation files (the "Software"), to deal +in the Software without restriction, including without limitation the rights +to use, copy, modify, merge, publish, distribute, sublicense, and/or sell +copies of the Software, and to permit persons to whom the Software is +furnished to do so, subject to the following conditions: + +The above copyright notice and this permission notice shall be included in +all copies or substantial portions of the Software. + +THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR +IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, +FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE +AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER +LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, +OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN +THE SOFTWARE. diff --git a/LAVT-RIS/refer/evaluation/bleu/__init__.py b/LAVT-RIS/refer/evaluation/bleu/__init__.py new file mode 100644 index 0000000000000000000000000000000000000000..3f7d85bba884ea8f83fc6ab2a1e6ade80d98d4d9 --- /dev/null +++ b/LAVT-RIS/refer/evaluation/bleu/__init__.py @@ -0,0 +1 @@ +__author__ = 'tylin' diff --git a/LAVT-RIS/refer/evaluation/bleu/bleu.py b/LAVT-RIS/refer/evaluation/bleu/bleu.py new file mode 100644 index 0000000000000000000000000000000000000000..b0da5dd4e741f1b42ee737e622ec9bb8fb537a50 --- /dev/null +++ b/LAVT-RIS/refer/evaluation/bleu/bleu.py @@ -0,0 +1,47 @@ +#!/usr/bin/env python +# +# File Name : bleu.py +# +# Description : Wrapper for BLEU scorer. +# +# Creation Date : 06-01-2015 +# Last Modified : Thu 19 Mar 2015 09:13:28 PM PDT +# Authors : Hao Fang and Tsung-Yi Lin + +from bleu_scorer import BleuScorer + + +class Bleu: + def __init__(self, n=4): + # default compute Blue score up to 4 + self._n = n + self._hypo_for_image = {} + self.ref_for_image = {} + + def compute_score(self, gts, res): + + assert(gts.keys() == res.keys()) + imgIds = gts.keys() + + bleu_scorer = BleuScorer(n=self._n) + for id in imgIds: + hypo = res[id] + ref = gts[id] + + # Sanity check. + assert(type(hypo) is list) + assert(len(hypo) == 1) + assert(type(ref) is list) + assert(len(ref) >= 1) + + bleu_scorer += (hypo[0], ref) + + #score, scores = bleu_scorer.compute_score(option='shortest') + score, scores = bleu_scorer.compute_score(option='closest', verbose=1) + #score, scores = bleu_scorer.compute_score(option='average', verbose=1) + + # return (bleu, bleu_info) + return score, scores + + def method(self): + return "Bleu" diff --git a/LAVT-RIS/refer/evaluation/bleu/bleu_scorer.py b/LAVT-RIS/refer/evaluation/bleu/bleu_scorer.py new file mode 100644 index 0000000000000000000000000000000000000000..3685e058398ac2216961bdc27287cf34cf01c134 --- /dev/null +++ b/LAVT-RIS/refer/evaluation/bleu/bleu_scorer.py @@ -0,0 +1,263 @@ +#!/usr/bin/env python + +# bleu_scorer.py +# David Chiang + +# Copyright (c) 2004-2006 University of Maryland. All rights +# reserved. Do not redistribute without permission from the +# author. Not for commercial use. + +# Modified by: +# Hao Fang +# Tsung-Yi Lin + +'''Provides: +cook_refs(refs, n=4): Transform a list of reference sentences as strings into a form usable by cook_test(). +cook_test(test, refs, n=4): Transform a test sentence as a string (together with the cooked reference sentences) into a form usable by score_cooked(). +''' + +import copy +import sys, math, re +from collections import defaultdict + +def precook(s, n=4, out=False): + """Takes a string as input and returns an object that can be given to + either cook_refs or cook_test. This is optional: cook_refs and cook_test + can take string arguments as well.""" + words = s.split() + counts = defaultdict(int) + for k in xrange(1,n+1): + for i in xrange(len(words)-k+1): + ngram = tuple(words[i:i+k]) + counts[ngram] += 1 + return (len(words), counts) + +def cook_refs(refs, eff=None, n=4): ## lhuang: oracle will call with "average" + '''Takes a list of reference sentences for a single segment + and returns an object that encapsulates everything that BLEU + needs to know about them.''' + + reflen = [] + maxcounts = {} + for ref in refs: + rl, counts = precook(ref, n) + reflen.append(rl) + for (ngram,count) in counts.iteritems(): + maxcounts[ngram] = max(maxcounts.get(ngram,0), count) + + # Calculate effective reference sentence length. + if eff == "shortest": + reflen = min(reflen) + elif eff == "average": + reflen = float(sum(reflen))/len(reflen) + + ## lhuang: N.B.: leave reflen computaiton to the very end!! + + ## lhuang: N.B.: in case of "closest", keep a list of reflens!! (bad design) + + return (reflen, maxcounts) + +def cook_test(test, (reflen, refmaxcounts), eff=None, n=4): + '''Takes a test sentence and returns an object that + encapsulates everything that BLEU needs to know about it.''' + + testlen, counts = precook(test, n, True) + + result = {} + + # Calculate effective reference sentence length. + + if eff == "closest": + result["reflen"] = min((abs(l-testlen), l) for l in reflen)[1] + else: ## i.e., "average" or "shortest" or None + result["reflen"] = reflen + + result["testlen"] = testlen + + result["guess"] = [max(0,testlen-k+1) for k in xrange(1,n+1)] + + result['correct'] = [0]*n + for (ngram, count) in counts.iteritems(): + result["correct"][len(ngram)-1] += min(refmaxcounts.get(ngram,0), count) + + return result + +class BleuScorer(object): + """Bleu scorer. + """ + + __slots__ = "n", "crefs", "ctest", "_score", "_ratio", "_testlen", "_reflen", "special_reflen" + # special_reflen is used in oracle (proportional effective ref len for a node). + + def copy(self): + ''' copy the refs.''' + new = BleuScorer(n=self.n) + new.ctest = copy.copy(self.ctest) + new.crefs = copy.copy(self.crefs) + new._score = None + return new + + def __init__(self, test=None, refs=None, n=4, special_reflen=None): + ''' singular instance ''' + + self.n = n + self.crefs = [] + self.ctest = [] + self.cook_append(test, refs) + self.special_reflen = special_reflen + + def cook_append(self, test, refs): + '''called by constructor and __iadd__ to avoid creating new instances.''' + + if refs is not None: + self.crefs.append(cook_refs(refs)) + if test is not None: + cooked_test = cook_test(test, self.crefs[-1]) + self.ctest.append(cooked_test) ## N.B.: -1 + else: + self.ctest.append(None) # lens of crefs and ctest have to match + + self._score = None ## need to recompute + + def ratio(self, option=None): + self.compute_score(option=option) + return self._ratio + + def score_ratio(self, option=None): + '''return (bleu, len_ratio) pair''' + return (self.fscore(option=option), self.ratio(option=option)) + + def score_ratio_str(self, option=None): + return "%.4f (%.2f)" % self.score_ratio(option) + + def reflen(self, option=None): + self.compute_score(option=option) + return self._reflen + + def testlen(self, option=None): + self.compute_score(option=option) + return self._testlen + + def retest(self, new_test): + if type(new_test) is str: + new_test = [new_test] + assert len(new_test) == len(self.crefs), new_test + self.ctest = [] + for t, rs in zip(new_test, self.crefs): + self.ctest.append(cook_test(t, rs)) + self._score = None + + return self + + def rescore(self, new_test): + ''' replace test(s) with new test(s), and returns the new score.''' + + return self.retest(new_test).compute_score() + + def size(self): + assert len(self.crefs) == len(self.ctest), "refs/test mismatch! %d<>%d" % (len(self.crefs), len(self.ctest)) + return len(self.crefs) + + def __iadd__(self, other): + '''add an instance (e.g., from another sentence).''' + + if type(other) is tuple: + ## avoid creating new BleuScorer instances + self.cook_append(other[0], other[1]) + else: + assert self.compatible(other), "incompatible BLEUs." + self.ctest.extend(other.ctest) + self.crefs.extend(other.crefs) + self._score = None ## need to recompute + + return self + + def compatible(self, other): + return isinstance(other, BleuScorer) and self.n == other.n + + def single_reflen(self, option="average"): + return self._single_reflen(self.crefs[0][0], option) + + def _single_reflen(self, reflens, option=None, testlen=None): + + if option == "shortest": + reflen = min(reflens) + elif option == "average": + reflen = float(sum(reflens))/len(reflens) + elif option == "closest": + reflen = min((abs(l-testlen), l) for l in reflens)[1] + else: + assert False, "unsupported reflen option %s" % option + + return reflen + + def recompute_score(self, option=None, verbose=0): + self._score = None + return self.compute_score(option, verbose) + + def compute_score(self, option=None, verbose=0): + n = self.n + small = 1e-9 + tiny = 1e-15 ## so that if guess is 0 still return 0 + bleu_list = [[] for _ in range(n)] + + if self._score is not None: + return self._score + + if option is None: + option = "average" if len(self.crefs) == 1 else "closest" + + self._testlen = 0 + self._reflen = 0 + totalcomps = {'testlen':0, 'reflen':0, 'guess':[0]*n, 'correct':[0]*n} + + # for each sentence + for comps in self.ctest: + testlen = comps['testlen'] + self._testlen += testlen + + if self.special_reflen is None: ## need computation + reflen = self._single_reflen(comps['reflen'], option, testlen) + else: + reflen = self.special_reflen + + self._reflen += reflen + + for key in ['guess','correct']: + for k in xrange(n): + totalcomps[key][k] += comps[key][k] + + # append per image bleu score + bleu = 1. + for k in xrange(n): + bleu *= (float(comps['correct'][k]) + tiny) \ + /(float(comps['guess'][k]) + small) + bleu_list[k].append(bleu ** (1./(k+1))) + ratio = (testlen + tiny) / (reflen + small) ## N.B.: avoid zero division + if ratio < 1: + for k in xrange(n): + bleu_list[k][-1] *= math.exp(1 - 1/ratio) + + if verbose > 1: + print comps, reflen + + totalcomps['reflen'] = self._reflen + totalcomps['testlen'] = self._testlen + + bleus = [] + bleu = 1. + for k in xrange(n): + bleu *= float(totalcomps['correct'][k] + tiny) \ + / (totalcomps['guess'][k] + small) + bleus.append(bleu ** (1./(k+1))) + ratio = (self._testlen + tiny) / (self._reflen + small) ## N.B.: avoid zero division + if ratio < 1: + for k in xrange(n): + bleus[k] *= math.exp(1 - 1/ratio) + + if verbose > 0: + print totalcomps + print "ratio:", ratio + + self._score = bleus + return self._score, bleu_list diff --git a/LAVT-RIS/refer/evaluation/cider/__init__.py b/LAVT-RIS/refer/evaluation/cider/__init__.py new file mode 100644 index 0000000000000000000000000000000000000000..3f7d85bba884ea8f83fc6ab2a1e6ade80d98d4d9 --- /dev/null +++ b/LAVT-RIS/refer/evaluation/cider/__init__.py @@ -0,0 +1 @@ +__author__ = 'tylin' diff --git a/LAVT-RIS/refer/evaluation/cider/cider.py b/LAVT-RIS/refer/evaluation/cider/cider.py new file mode 100644 index 0000000000000000000000000000000000000000..d0b99ee768e156f2791ddcc941c3d091e1b2dbb0 --- /dev/null +++ b/LAVT-RIS/refer/evaluation/cider/cider.py @@ -0,0 +1,54 @@ +# Filename: cider.py +# +# Description: Describes the class to compute the CIDEr (Consensus-Based Image Description Evaluation) Metric +# by Vedantam, Zitnick, and Parikh (http://arxiv.org/abs/1411.5726) +# +# Creation Date: Sun Feb 8 14:16:54 2015 +# +# Authors: Ramakrishna Vedantam and Tsung-Yi Lin + +from cider_scorer import CiderScorer +import pdb + +class Cider: + """ + Main Class to compute the CIDEr metric + + """ + def __init__(self, test=None, refs=None, n=4, sigma=6.0): + # set cider to sum over 1 to 4-grams + self._n = n + # set the standard deviation parameter for gaussian penalty + self._sigma = sigma + + def compute_score(self, gts, res): + """ + Main function to compute CIDEr score + :param hypo_for_image (dict) : dictionary with key and value + ref_for_image (dict) : dictionary with key and value + :return: cider (float) : computed CIDEr score for the corpus + """ + + assert(gts.keys() == res.keys()) + imgIds = gts.keys() + + cider_scorer = CiderScorer(n=self._n, sigma=self._sigma) + + for id in imgIds: + hypo = res[id] + ref = gts[id] + + # Sanity check. + assert(type(hypo) is list) + assert(len(hypo) == 1) + assert(type(ref) is list) + assert(len(ref) > 0) + + cider_scorer += (hypo[0], ref) + + (score, scores) = cider_scorer.compute_score() + + return score, scores + + def method(self): + return "CIDEr" \ No newline at end of file diff --git a/LAVT-RIS/refer/evaluation/cider/cider_scorer.py b/LAVT-RIS/refer/evaluation/cider/cider_scorer.py new file mode 100644 index 0000000000000000000000000000000000000000..a73405e594b29adf4a3df69ecddd81763818f6df --- /dev/null +++ b/LAVT-RIS/refer/evaluation/cider/cider_scorer.py @@ -0,0 +1,192 @@ +#!/usr/bin/env python +# Tsung-Yi Lin +# Ramakrishna Vedantam + +import copy +from collections import defaultdict +import numpy as np +import pdb +import math + +def precook(s, n=4, out=False): + """ + Takes a string as input and returns an object that can be given to + either cook_refs or cook_test. This is optional: cook_refs and cook_test + can take string arguments as well. + :param s: string : sentence to be converted into ngrams + :param n: int : number of ngrams for which representation is calculated + :return: term frequency vector for occuring ngrams + """ + words = s.split() + counts = defaultdict(int) + for k in xrange(1,n+1): + for i in xrange(len(words)-k+1): + ngram = tuple(words[i:i+k]) + counts[ngram] += 1 + return counts + +def cook_refs(refs, n=4): ## lhuang: oracle will call with "average" + '''Takes a list of reference sentences for a single segment + and returns an object that encapsulates everything that BLEU + needs to know about them. + :param refs: list of string : reference sentences for some image + :param n: int : number of ngrams for which (ngram) representation is calculated + :return: result (list of dict) + ''' + return [precook(ref, n) for ref in refs] + +def cook_test(test, n=4): + '''Takes a test sentence and returns an object that + encapsulates everything that BLEU needs to know about it. + :param test: list of string : hypothesis sentence for some image + :param n: int : number of ngrams for which (ngram) representation is calculated + :return: result (dict) + ''' + return precook(test, n, True) + +class CiderScorer(object): + """CIDEr scorer. + """ + + def copy(self): + ''' copy the refs.''' + new = CiderScorer(n=self.n) + new.ctest = copy.copy(self.ctest) + new.crefs = copy.copy(self.crefs) + return new + + def __init__(self, test=None, refs=None, n=4, sigma=6.0): + ''' singular instance ''' + self.n = n + self.sigma = sigma + self.crefs = [] + self.ctest = [] + self.document_frequency = defaultdict(float) + self.cook_append(test, refs) + self.ref_len = None + + def cook_append(self, test, refs): + '''called by constructor and __iadd__ to avoid creating new instances.''' + + if refs is not None: + self.crefs.append(cook_refs(refs)) + if test is not None: + self.ctest.append(cook_test(test)) ## N.B.: -1 + else: + self.ctest.append(None) # lens of crefs and ctest have to match + + def size(self): + assert len(self.crefs) == len(self.ctest), "refs/test mismatch! %d<>%d" % (len(self.crefs), len(self.ctest)) + return len(self.crefs) + + def __iadd__(self, other): + '''add an instance (e.g., from another sentence).''' + + if type(other) is tuple: + ## avoid creating new CiderScorer instances + self.cook_append(other[0], other[1]) + else: + self.ctest.extend(other.ctest) + self.crefs.extend(other.crefs) + + return self + def compute_doc_freq(self): + ''' + Compute term frequency for reference data. + This will be used to compute idf (inverse document frequency later) + The term frequency is stored in the object + :return: None + ''' + for refs in self.crefs: + # refs, k ref captions of one image + for ngram in set([ngram for ref in refs for (ngram,count) in ref.iteritems()]): + self.document_frequency[ngram] += 1 + # maxcounts[ngram] = max(maxcounts.get(ngram,0), count) + + def compute_cider(self): + def counts2vec(cnts): + """ + Function maps counts of ngram to vector of tfidf weights. + The function returns vec, an array of dictionary that store mapping of n-gram and tf-idf weights. + The n-th entry of array denotes length of n-grams. + :param cnts: + :return: vec (array of dict), norm (array of float), length (int) + """ + vec = [defaultdict(float) for _ in range(self.n)] + length = 0 + norm = [0.0 for _ in range(self.n)] + for (ngram,term_freq) in cnts.iteritems(): + # give word count 1 if it doesn't appear in reference corpus + df = np.log(max(1.0, self.document_frequency[ngram])) + # ngram index + n = len(ngram)-1 + # tf (term_freq) * idf (precomputed idf) for n-grams + vec[n][ngram] = float(term_freq)*(self.ref_len - df) + # compute norm for the vector. the norm will be used for computing similarity + norm[n] += pow(vec[n][ngram], 2) + + if n == 1: + length += term_freq + norm = [np.sqrt(n) for n in norm] + return vec, norm, length + + def sim(vec_hyp, vec_ref, norm_hyp, norm_ref, length_hyp, length_ref): + ''' + Compute the cosine similarity of two vectors. + :param vec_hyp: array of dictionary for vector corresponding to hypothesis + :param vec_ref: array of dictionary for vector corresponding to reference + :param norm_hyp: array of float for vector corresponding to hypothesis + :param norm_ref: array of float for vector corresponding to reference + :param length_hyp: int containing length of hypothesis + :param length_ref: int containing length of reference + :return: array of score for each n-grams cosine similarity + ''' + delta = float(length_hyp - length_ref) + # measure consine similarity + val = np.array([0.0 for _ in range(self.n)]) + for n in range(self.n): + # ngram + for (ngram,count) in vec_hyp[n].iteritems(): + # vrama91 : added clipping + val[n] += min(vec_hyp[n][ngram], vec_ref[n][ngram]) * vec_ref[n][ngram] + + if (norm_hyp[n] != 0) and (norm_ref[n] != 0): + val[n] /= (norm_hyp[n]*norm_ref[n]) + + assert(not math.isnan(val[n])) + # vrama91: added a length based gaussian penalty + val[n] *= np.e**(-(delta**2)/(2*self.sigma**2)) + return val + + # compute log reference length + self.ref_len = np.log(float(len(self.crefs))) + + scores = [] + for test, refs in zip(self.ctest, self.crefs): + # compute vector for test captions + vec, norm, length = counts2vec(test) + # compute vector for ref captions + score = np.array([0.0 for _ in range(self.n)]) + for ref in refs: + vec_ref, norm_ref, length_ref = counts2vec(ref) + score += sim(vec, vec_ref, norm, norm_ref, length, length_ref) + # change by vrama91 - mean of ngram scores, instead of sum + score_avg = np.mean(score) + # divide by number of references + score_avg /= len(refs) + # multiply score by 10 + score_avg *= 10.0 + # append score of an image to the score list + scores.append(score_avg) + return scores + + def compute_score(self, option=None, verbose=0): + # compute idf + self.compute_doc_freq() + # assert to check document frequency + assert(len(self.ctest) >= max(self.document_frequency.values())) + # compute cider score + score = self.compute_cider() + # debug + # print score + return np.mean(np.array(score)), np.array(score) \ No newline at end of file diff --git a/LAVT-RIS/refer/evaluation/meteor/__init__.py b/LAVT-RIS/refer/evaluation/meteor/__init__.py new file mode 100644 index 0000000000000000000000000000000000000000..3f7d85bba884ea8f83fc6ab2a1e6ade80d98d4d9 --- /dev/null +++ b/LAVT-RIS/refer/evaluation/meteor/__init__.py @@ -0,0 +1 @@ +__author__ = 'tylin' diff --git a/LAVT-RIS/refer/evaluation/meteor/meteor.py b/LAVT-RIS/refer/evaluation/meteor/meteor.py new file mode 100644 index 0000000000000000000000000000000000000000..64729489f4458e9c0dec3fe345f90a1fddd13f33 --- /dev/null +++ b/LAVT-RIS/refer/evaluation/meteor/meteor.py @@ -0,0 +1,76 @@ +#!/usr/bin/env python + +# Python wrapper for METEOR implementation, by Xinlei Chen +# Acknowledge Michael Denkowski for the generous discussion and help + +import os +import sys +import subprocess +import threading + +# Assumes meteor-1.5.jar is in the same directory as meteor.py. Change as needed. +METEOR_JAR = 'meteor-1.5.jar' +# print METEOR_JAR + +class Meteor: + + def __init__(self): + self.meteor_cmd = ['java', '-jar', '-Xmx2G', METEOR_JAR, \ + '-', '-', '-stdio', '-l', 'en', '-norm'] + self.meteor_p = subprocess.Popen(self.meteor_cmd, \ + cwd=os.path.dirname(os.path.abspath(__file__)), \ + stdin=subprocess.PIPE, \ + stdout=subprocess.PIPE, \ + stderr=subprocess.PIPE) + # Used to guarantee thread safety + self.lock = threading.Lock() + + def compute_score(self, gts, res): + assert(gts.keys() == res.keys()) + imgIds = gts.keys() + scores = [] + + eval_line = 'EVAL' + self.lock.acquire() + for i in imgIds: + assert(len(res[i]) == 1) + stat = self._stat(res[i][0], gts[i]) + eval_line += ' ||| {}'.format(stat) + + self.meteor_p.stdin.write('{}\n'.format(eval_line)) + for i in range(0,len(imgIds)): + scores.append(float(self.meteor_p.stdout.readline().strip())) + score = float(self.meteor_p.stdout.readline().strip()) + self.lock.release() + + return score, scores + + def method(self): + return "METEOR" + + def _stat(self, hypothesis_str, reference_list): + # SCORE ||| reference 1 words ||| reference n words ||| hypothesis words + hypothesis_str = hypothesis_str.replace('|||','').replace(' ',' ') + score_line = ' ||| '.join(('SCORE', ' ||| '.join(reference_list), hypothesis_str)) + self.meteor_p.stdin.write('{}\n'.format(score_line)) + return self.meteor_p.stdout.readline().strip() + + def _score(self, hypothesis_str, reference_list): + self.lock.acquire() + # SCORE ||| reference 1 words ||| reference n words ||| hypothesis words + hypothesis_str = hypothesis_str.replace('|||','').replace(' ',' ') + score_line = ' ||| '.join(('SCORE', ' ||| '.join(reference_list), hypothesis_str)) + self.meteor_p.stdin.write('{}\n'.format(score_line)) + stats = self.meteor_p.stdout.readline().strip() + eval_line = 'EVAL ||| {}'.format(stats) + # EVAL ||| stats + self.meteor_p.stdin.write('{}\n'.format(eval_line)) + score = float(self.meteor_p.stdout.readline().strip()) + self.lock.release() + return score + + def __exit__(self): + self.lock.acquire() + self.meteor_p.stdin.close() + self.meteor_p.wait() + self.lock.release() diff --git a/LAVT-RIS/refer/evaluation/readme.txt b/LAVT-RIS/refer/evaluation/readme.txt new file mode 100644 index 0000000000000000000000000000000000000000..4491b5a806468b6ca9b974fa04d3cd9fb3b4150c --- /dev/null +++ b/LAVT-RIS/refer/evaluation/readme.txt @@ -0,0 +1,11 @@ +This folder contains modified coco-caption evaluation, which is downloaded from https://github.com/tylin/coco-caption.git +and refEvaluation which is to be called by the refer algorithm. + +More specifically, this folder contains: +1. bleu/ +2. cider/ +3. meteor/ +4. rouge/ +5. tokenizer/ +6. __init__.py +7. refEvaluation.py diff --git a/LAVT-RIS/refer/evaluation/refEvaluation.py b/LAVT-RIS/refer/evaluation/refEvaluation.py new file mode 100644 index 0000000000000000000000000000000000000000..bfa11ede76d03efb9cd272304e812f204b652dba --- /dev/null +++ b/LAVT-RIS/refer/evaluation/refEvaluation.py @@ -0,0 +1,136 @@ +from tokenizer.ptbtokenizer import PTBTokenizer +from bleu.bleu import Bleu +from meteor.meteor import Meteor +from rouge.rouge import Rouge +from cider.cider import Cider + +""" +Input: refer and Res = [{ref_id, sent}] + +Things of interest +evalRefs - list of ['ref_id', 'CIDEr', 'Bleu_1', 'Bleu_2', 'Bleu_3', 'Bleu_4', 'ROUGE_L', 'METEOR'] +eval - dict of {metric: score} +refToEval - dict of {ref_id: ['ref_id', 'CIDEr', 'Bleu_1', 'Bleu_2', 'Bleu_3', 'Bleu_4', 'ROUGE_L', 'METEOR']} +""" + +class RefEvaluation: + def __init__ (self, refer, Res): + """ + :param refer: refer class of current dataset + :param Res: [{'ref_id', 'sent'}] + """ + self.evalRefs = [] + self.eval = {} + self.refToEval = {} + self.refer = refer + self.Res = Res + + def evaluate(self): + + evalRefIds = [ann['ref_id'] for ann in self.Res] + + refToGts = {} + for ref_id in evalRefIds: + ref = self.refer.Refs[ref_id] + gt_sents = [sent['sent'].encode('ascii', 'ignore').decode('ascii') for sent in ref['sentences']] # up to 3 expressions + refToGts[ref_id] = gt_sents + refToRes = {ann['ref_id']: [ann['sent']] for ann in self.Res} + + print 'tokenization...' + tokenizer = PTBTokenizer() + self.refToRes = tokenizer.tokenize(refToRes) + self.refToGts = tokenizer.tokenize(refToGts) + + # ================================================= + # Set up scorers + # ================================================= + print 'setting up scorers...' + scorers = [ + (Bleu(4), ["Bleu_1", "Bleu_2", "Bleu_3", "Bleu_4"]), + (Meteor(),"METEOR"), + (Rouge(), "ROUGE_L"), + (Cider(), "CIDEr") + ] + + # ================================================= + # Compute scores + # ================================================= + for scorer, method in scorers: + print 'computing %s score...'%(scorer.method()) + score, scores = scorer.compute_score(self.refToGts, self.refToRes) + if type(method) == list: + for sc, scs, m in zip(score, scores, method): + self.setEval(sc, m) + self.setRefToEvalRefs(scs, self.refToGts.keys(), m) + print "%s: %0.3f"%(m, sc) + else: + self.setEval(score, method) + self.setRefToEvalRefs(scores, self.refToGts.keys(), method) + print "%s: %0.3f"%(method, score) + self.setEvalRefs() + + def setEval(self, score, method): + self.eval[method] = score + + def setRefToEvalRefs(self, scores, refIds, method): + for refId, score in zip(refIds, scores): + if not refId in self.refToEval: + self.refToEval[refId] = {} + self.refToEval[refId]["ref_id"] = refId + self.refToEval[refId][method] = score + + def setEvalRefs(self): + self.evalRefs = [eval for refId, eval in self.refToEval.items()] + + +if __name__ == '__main__': + + import os.path as osp + import sys + ROOT_DIR = osp.abspath(osp.join(osp.dirname(__file__), '..', '..')) + sys.path.insert(0, osp.join(ROOT_DIR, 'lib', 'datasets')) + from refer import REFER + + # load refer of dataset + dataset = 'refcoco' + refer = REFER(dataset, splitBy = 'google') + + # mimic some Res + val_refIds = refer.getRefIds(split='test') + ref_id = 49767 + print "GD: %s" % refer.Refs[ref_id]['sentences'] + Res = [{'ref_id': ref_id, 'sent': 'left bottle'}] + + # evaluate some refer expressions + refEval = RefEvaluation(refer, Res) + refEval.evaluate() + + # print output evaluation scores + for metric, score in refEval.eval.items(): + print '%s: %.3f'%(metric, score) + + # demo how to use evalImgs to retrieve low score result + # evals = [eva for eva in refEval.evalRefs if eva['CIDEr']<30] + # print 'ground truth sents' + # refId = evals[0]['ref_id'] + # print 'refId: %s' % refId + # print [sent['sent'] for sent in refer.Refs[refId]['sentences']] + # + # print 'generated sent (CIDEr score %0.1f)' % (evals[0]['CIDEr']) + + # print refEval.refToEval[8] + + + + + + + + + + + + + + + diff --git a/LAVT-RIS/refer/evaluation/rouge/__init__.py b/LAVT-RIS/refer/evaluation/rouge/__init__.py new file mode 100644 index 0000000000000000000000000000000000000000..43a773e12ea2e960f9a62fa1c2179a73d8c0dd35 --- /dev/null +++ b/LAVT-RIS/refer/evaluation/rouge/__init__.py @@ -0,0 +1 @@ +__author__ = 'vrama91' diff --git a/LAVT-RIS/refer/evaluation/rouge/rouge.py b/LAVT-RIS/refer/evaluation/rouge/rouge.py new file mode 100644 index 0000000000000000000000000000000000000000..3a10f5a50371328d397dcb53c7c9d81eac9472fa --- /dev/null +++ b/LAVT-RIS/refer/evaluation/rouge/rouge.py @@ -0,0 +1,105 @@ +#!/usr/bin/env python +# +# File Name : rouge.py +# +# Description : Computes ROUGE-L metric as described by Lin and Hovey (2004) +# +# Creation Date : 2015-01-07 06:03 +# Author : Ramakrishna Vedantam + +import numpy as np +import pdb + +def my_lcs(string, sub): + """ + Calculates longest common subsequence for a pair of tokenized strings + :param string : list of str : tokens from a string split using whitespace + :param sub : list of str : shorter string, also split using whitespace + :returns: length (list of int): length of the longest common subsequence between the two strings + + Note: my_lcs only gives length of the longest common subsequence, not the actual LCS + """ + if(len(string)< len(sub)): + sub, string = string, sub + + lengths = [[0 for i in range(0,len(sub)+1)] for j in range(0,len(string)+1)] + + for j in range(1,len(sub)+1): + for i in range(1,len(string)+1): + if(string[i-1] == sub[j-1]): + lengths[i][j] = lengths[i-1][j-1] + 1 + else: + lengths[i][j] = max(lengths[i-1][j] , lengths[i][j-1]) + + return lengths[len(string)][len(sub)] + +class Rouge(): + ''' + Class for computing ROUGE-L score for a set of candidate sentences for the MS COCO test set + + ''' + def __init__(self): + # vrama91: updated the value below based on discussion with Hovey + self.beta = 1.2 + + def calc_score(self, candidate, refs): + """ + Compute ROUGE-L score given one candidate and references for an image + :param candidate: str : candidate sentence to be evaluated + :param refs: list of str : COCO reference sentences for the particular image to be evaluated + :returns score: int (ROUGE-L score for the candidate evaluated against references) + """ + assert(len(candidate)==1) + assert(len(refs)>0) + prec = [] + rec = [] + + # split into tokens + token_c = candidate[0].split(" ") + + for reference in refs: + # split into tokens + token_r = reference.split(" ") + # compute the longest common subsequence + lcs = my_lcs(token_r, token_c) + prec.append(lcs/float(len(token_c))) + rec.append(lcs/float(len(token_r))) + + prec_max = max(prec) + rec_max = max(rec) + + if(prec_max!=0 and rec_max !=0): + score = ((1 + self.beta**2)*prec_max*rec_max)/float(rec_max + self.beta**2*prec_max) + else: + score = 0.0 + return score + + def compute_score(self, gts, res): + """ + Computes Rouge-L score given a set of reference and candidate sentences for the dataset + Invoked by evaluate_captions.py + :param hypo_for_image: dict : candidate / test sentences with "image name" key and "tokenized sentences" as values + :param ref_for_image: dict : reference MS-COCO sentences with "image name" key and "tokenized sentences" as values + :returns: average_score: float (mean ROUGE-L score computed by averaging scores for all the images) + """ + assert(gts.keys() == res.keys()) + imgIds = gts.keys() + + score = [] + for id in imgIds: + hypo = res[id] + ref = gts[id] + + score.append(self.calc_score(hypo, ref)) + + # Sanity check. + assert(type(hypo) is list) + assert(len(hypo) == 1) + assert(type(ref) is list) + assert(len(ref) > 0) + + average_score = np.mean(np.array(score)) + return average_score, np.array(score) + + def method(self): + return "Rouge" diff --git a/LAVT-RIS/refer/evaluation/tokenizer/__init__.py b/LAVT-RIS/refer/evaluation/tokenizer/__init__.py new file mode 100644 index 0000000000000000000000000000000000000000..71357a4bff7219ddcf7f7321cfeb4484bd8bee08 --- /dev/null +++ b/LAVT-RIS/refer/evaluation/tokenizer/__init__.py @@ -0,0 +1 @@ +__author__ = 'hfang' diff --git a/LAVT-RIS/refer/evaluation/tokenizer/ptbtokenizer.py b/LAVT-RIS/refer/evaluation/tokenizer/ptbtokenizer.py new file mode 100644 index 0000000000000000000000000000000000000000..346ebe784fa63b24121a0c587e9b163c887c3199 --- /dev/null +++ b/LAVT-RIS/refer/evaluation/tokenizer/ptbtokenizer.py @@ -0,0 +1,68 @@ +#!/usr/bin/env python +# +# File Name : ptbtokenizer.py +# +# Description : Do the PTB Tokenization and remove punctuations. +# +# Creation Date : 29-12-2014 +# Last Modified : Thu Mar 19 09:53:35 2015 +# Authors : Hao Fang and Tsung-Yi Lin + +import os +import sys +import subprocess +import tempfile +import itertools + +# path to the stanford corenlp jar +STANFORD_CORENLP_3_4_1_JAR = 'stanford-corenlp-3.4.1.jar' + +# punctuations to be removed from the sentences +PUNCTUATIONS = ["''", "'", "``", "`", "-LRB-", "-RRB-", "-LCB-", "-RCB-", \ + ".", "?", "!", ",", ":", "-", "--", "...", ";"] + +class PTBTokenizer: + """Python wrapper of Stanford PTBTokenizer""" + + def tokenize(self, captions_for_image): + cmd = ['java', '-cp', STANFORD_CORENLP_3_4_1_JAR, \ + 'edu.stanford.nlp.process.PTBTokenizer', \ + '-preserveLines', '-lowerCase'] + + # ====================================================== + # prepare data for PTB Tokenizer + # ====================================================== + final_tokenized_captions_for_image = {} + image_id = [k for k, v in captions_for_image.items() for _ in range(len(v))] + sentences = '\n'.join([c.replace('\n', ' ') for k, v in captions_for_image.items() for c in v]) + + # ====================================================== + # save sentences to temporary file + # ====================================================== + path_to_jar_dirname=os.path.dirname(os.path.abspath(__file__)) + tmp_file = tempfile.NamedTemporaryFile(delete=False, dir=path_to_jar_dirname) + tmp_file.write(sentences) + tmp_file.close() + + # ====================================================== + # tokenize sentence + # ====================================================== + cmd.append(os.path.basename(tmp_file.name)) + p_tokenizer = subprocess.Popen(cmd, cwd=path_to_jar_dirname, \ + stdout=subprocess.PIPE) + token_lines = p_tokenizer.communicate(input=sentences.rstrip())[0] + lines = token_lines.split('\n') + # remove temp file + os.remove(tmp_file.name) + + # ====================================================== + # create dictionary for tokenized captions + # ====================================================== + for k, line in zip(image_id, lines): + if not k in final_tokenized_captions_for_image: + final_tokenized_captions_for_image[k] = [] + tokenized_caption = ' '.join([w for w in line.rstrip().split(' ') \ + if w not in PUNCTUATIONS]) + final_tokenized_captions_for_image[k].append(tokenized_caption) + + return final_tokenized_captions_for_image diff --git a/LAVT-RIS/refer/evaluation/tokenizer/stanford-corenlp-3.4.1.jar b/LAVT-RIS/refer/evaluation/tokenizer/stanford-corenlp-3.4.1.jar new file mode 100644 index 0000000000000000000000000000000000000000..07e4e5e4f90d7060180c968bf31ca35084627c2d --- /dev/null +++ b/LAVT-RIS/refer/evaluation/tokenizer/stanford-corenlp-3.4.1.jar @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:2fcb91bb7a111f93d71e264f4ee0e3afd19ba0dde6d21b38605088df9e940399 +size 5921410 diff --git a/LAVT-RIS/refer/external/README.md b/LAVT-RIS/refer/external/README.md new file mode 100644 index 0000000000000000000000000000000000000000..0a0a681c7c1aaf41cfc2ae73cbdbffe55437d210 --- /dev/null +++ b/LAVT-RIS/refer/external/README.md @@ -0,0 +1 @@ +The codes inside this folder are copied from pycocotools: https://github.com/pdollar/coco \ No newline at end of file diff --git a/LAVT-RIS/refer/external/__init__.py b/LAVT-RIS/refer/external/__init__.py new file mode 100644 index 0000000000000000000000000000000000000000..3f7d85bba884ea8f83fc6ab2a1e6ade80d98d4d9 --- /dev/null +++ b/LAVT-RIS/refer/external/__init__.py @@ -0,0 +1 @@ +__author__ = 'tylin' diff --git a/LAVT-RIS/refer/external/_mask.pyx b/LAVT-RIS/refer/external/_mask.pyx new file mode 100644 index 0000000000000000000000000000000000000000..9f0562c26bc45bc927e8ef65c1f60f1670c50be1 --- /dev/null +++ b/LAVT-RIS/refer/external/_mask.pyx @@ -0,0 +1,291 @@ +# distutils: language = c +# distutils: sources = external/maskApi.c + +#************************************************************************** +# Microsoft COCO Toolbox. version 2.0 +# Data, paper, and tutorials available at: http://mscoco.org/ +# Code written by Piotr Dollar and Tsung-Yi Lin, 2015. +# Licensed under the Simplified BSD License [see coco/license.txt] +#************************************************************************** + +__author__ = 'tsungyi' + +# import both Python-level and C-level symbols of Numpy +# the API uses Numpy to interface C and Python +import numpy as np +cimport numpy as np +from libc.stdlib cimport malloc, free + +# intialized Numpy. must do. +np.import_array() + +# import numpy C function +# we use PyArray_ENABLEFLAGS to make Numpy ndarray responsible to memoery management +cdef extern from "numpy/arrayobject.h": + void PyArray_ENABLEFLAGS(np.ndarray arr, int flags) + +# Declare the prototype of the C functions in MaskApi.h +cdef extern from "maskApi.h": + ctypedef unsigned int uint + ctypedef unsigned long siz + ctypedef unsigned char byte + ctypedef double* BB + ctypedef struct RLE: + siz h, + siz w, + siz m, + uint* cnts, + void rlesInit( RLE **R, siz n ) + void rleEncode( RLE *R, const byte *M, siz h, siz w, siz n ) + void rleDecode( const RLE *R, byte *mask, siz n ) + void rleMerge( const RLE *R, RLE *M, siz n, bint intersect ) + void rleArea( const RLE *R, siz n, uint *a ) + void rleIou( RLE *dt, RLE *gt, siz m, siz n, byte *iscrowd, double *o ) + void bbIou( BB dt, BB gt, siz m, siz n, byte *iscrowd, double *o ) + void rleToBbox( const RLE *R, BB bb, siz n ) + void rleFrBbox( RLE *R, const BB bb, siz h, siz w, siz n ) + void rleFrPoly( RLE *R, const double *xy, siz k, siz h, siz w ) + char* rleToString( const RLE *R ) + void rleFrString( RLE *R, char *s, siz h, siz w ) + +# python class to wrap RLE array in C +# the class handles the memory allocation and deallocation +cdef class RLEs: + cdef RLE *_R + cdef siz _n + + def __cinit__(self, siz n =0): + rlesInit(&self._R, n) + self._n = n + + # free the RLE array here + def __dealloc__(self): + if self._R is not NULL: + for i in range(self._n): + free(self._R[i].cnts) + free(self._R) + def __getattr__(self, key): + if key == 'n': + return self._n + raise AttributeError(key) + +# python class to wrap Mask array in C +# the class handles the memory allocation and deallocation +cdef class Masks: + cdef byte *_mask + cdef siz _h + cdef siz _w + cdef siz _n + + def __cinit__(self, h, w, n): + self._mask = malloc(h*w*n* sizeof(byte)) + self._h = h + self._w = w + self._n = n + # def __dealloc__(self): + # the memory management of _mask has been passed to np.ndarray + # it doesn't need to be freed here + + # called when passing into np.array() and return an np.ndarray in column-major order + def __array__(self): + cdef np.npy_intp shape[1] + shape[0] = self._h*self._w*self._n + # Create a 1D array, and reshape it to fortran/Matlab column-major array + ndarray = np.PyArray_SimpleNewFromData(1, shape, np.NPY_UINT8, self._mask).reshape((self._h, self._w, self._n), order='F') + # The _mask allocated by Masks is now handled by ndarray + PyArray_ENABLEFLAGS(ndarray, np.NPY_OWNDATA) + return ndarray + +# internal conversion from Python RLEs object to compressed RLE format +def _toString(RLEs Rs): + cdef siz n = Rs.n + cdef bytes py_string + cdef char* c_string + objs = [] + for i in range(n): + c_string = rleToString( &Rs._R[i] ) + py_string = c_string + objs.append({ + 'size': [Rs._R[i].h, Rs._R[i].w], + 'counts': py_string + }) + free(c_string) + return objs + +# internal conversion from compressed RLE format to Python RLEs object +def _frString(rleObjs): + cdef siz n = len(rleObjs) + Rs = RLEs(n) + cdef bytes py_string + cdef char* c_string + for i, obj in enumerate(rleObjs): + py_string = str(obj['counts']) + c_string = py_string + rleFrString( &Rs._R[i], c_string, obj['size'][0], obj['size'][1] ) + return Rs + +# encode mask to RLEs objects +# list of RLE string can be generated by RLEs member function +def encode(np.ndarray[np.uint8_t, ndim=3, mode='fortran'] mask): + h, w, n = mask.shape[0], mask.shape[1], mask.shape[2] + cdef RLEs Rs = RLEs(n) + rleEncode(Rs._R,mask.data,h,w,n) + objs = _toString(Rs) + return objs + +# decode mask from compressed list of RLE string or RLEs object +def decode(rleObjs): + cdef RLEs Rs = _frString(rleObjs) + h, w, n = Rs._R[0].h, Rs._R[0].w, Rs._n + masks = Masks(h, w, n) + rleDecode( Rs._R, masks._mask, n ); + return np.array(masks) + +def merge(rleObjs, bint intersect=0): + cdef RLEs Rs = _frString(rleObjs) + cdef RLEs R = RLEs(1) + rleMerge(Rs._R, R._R, Rs._n, intersect) + obj = _toString(R)[0] + return obj + +def area(rleObjs): + cdef RLEs Rs = _frString(rleObjs) + cdef uint* _a = malloc(Rs._n* sizeof(uint)) + rleArea(Rs._R, Rs._n, _a) + cdef np.npy_intp shape[1] + shape[0] = Rs._n + a = np.array((Rs._n, ), dtype=np.uint8) + a = np.PyArray_SimpleNewFromData(1, shape, np.NPY_UINT32, _a) + PyArray_ENABLEFLAGS(a, np.NPY_OWNDATA) + return a + +# iou computation. support function overload (RLEs-RLEs and bbox-bbox). +def iou( dt, gt, pyiscrowd ): + def _preproc(objs): + if len(objs) == 0: + return objs + if type(objs) == np.ndarray: + if len(objs.shape) == 1: + objs = objs.reshape((objs[0], 1)) + # check if it's Nx4 bbox + if not len(objs.shape) == 2 or not objs.shape[1] == 4: + raise Exception('numpy ndarray input is only for *bounding boxes* and should have Nx4 dimension') + objs = objs.astype(np.double) + elif type(objs) == list: + # check if list is in box format and convert it to np.ndarray + isbox = np.all(np.array([(len(obj)==4) and ((type(obj)==list) or (type(obj)==np.ndarray)) for obj in objs])) + isrle = np.all(np.array([type(obj) == dict for obj in objs])) + if isbox: + objs = np.array(objs, dtype=np.double) + if len(objs.shape) == 1: + objs = objs.reshape((1,objs.shape[0])) + elif isrle: + objs = _frString(objs) + else: + raise Exception('list input can be bounding box (Nx4) or RLEs ([RLE])') + else: + raise Exception('unrecognized type. The following type: RLEs (rle), np.ndarray (box), and list (box) are supported.') + return objs + def _rleIou(RLEs dt, RLEs gt, np.ndarray[np.uint8_t, ndim=1] iscrowd, siz m, siz n, np.ndarray[np.double_t, ndim=1] _iou): + rleIou( dt._R, gt._R, m, n, iscrowd.data, _iou.data ) + def _bbIou(np.ndarray[np.double_t, ndim=2] dt, np.ndarray[np.double_t, ndim=2] gt, np.ndarray[np.uint8_t, ndim=1] iscrowd, siz m, siz n, np.ndarray[np.double_t, ndim=1] _iou): + bbIou( dt.data, gt.data, m, n, iscrowd.data, _iou.data ) + def _len(obj): + cdef siz N = 0 + if type(obj) == RLEs: + N = obj.n + elif len(obj)==0: + pass + elif type(obj) == np.ndarray: + N = obj.shape[0] + return N + # convert iscrowd to numpy array + cdef np.ndarray[np.uint8_t, ndim=1] iscrowd = np.array(pyiscrowd, dtype=np.uint8) + # simple type checking + cdef siz m, n + dt = _preproc(dt) + gt = _preproc(gt) + m = _len(dt) + n = _len(gt) + if m == 0 or n == 0: + return [] + if not type(dt) == type(gt): + raise Exception('The dt and gt should have the same data type, either RLEs, list or np.ndarray') + + # define local variables + cdef double* _iou = 0 + cdef np.npy_intp shape[1] + # check type and assign iou function + if type(dt) == RLEs: + _iouFun = _rleIou + elif type(dt) == np.ndarray: + _iouFun = _bbIou + else: + raise Exception('input data type not allowed.') + _iou = malloc(m*n* sizeof(double)) + iou = np.zeros((m*n, ), dtype=np.double) + shape[0] = m*n + iou = np.PyArray_SimpleNewFromData(1, shape, np.NPY_DOUBLE, _iou) + PyArray_ENABLEFLAGS(iou, np.NPY_OWNDATA) + _iouFun(dt, gt, iscrowd, m, n, iou) + return iou.reshape((m,n), order='F') + +def toBbox( rleObjs ): + cdef RLEs Rs = _frString(rleObjs) + cdef siz n = Rs.n + cdef BB _bb = malloc(4*n* sizeof(double)) + rleToBbox( Rs._R, _bb, n ) + cdef np.npy_intp shape[1] + shape[0] = 4*n + bb = np.array((1,4*n), dtype=np.double) + bb = np.PyArray_SimpleNewFromData(1, shape, np.NPY_DOUBLE, _bb).reshape((n, 4)) + PyArray_ENABLEFLAGS(bb, np.NPY_OWNDATA) + return bb + +def frBbox(np.ndarray[np.double_t, ndim=2] bb, siz h, siz w ): + cdef siz n = bb.shape[0] + Rs = RLEs(n) + rleFrBbox( Rs._R, bb.data, h, w, n ) + objs = _toString(Rs) + return objs + +def frPoly( poly, siz h, siz w ): + cdef np.ndarray[np.double_t, ndim=1] np_poly + n = len(poly) + Rs = RLEs(n) + for i, p in enumerate(poly): + np_poly = np.array(p, dtype=np.double, order='F') + rleFrPoly( &Rs._R[i], np_poly.data, len(np_poly)/2, h, w ) + objs = _toString(Rs) + return objs + +def frUncompressedRLE(ucRles, siz h, siz w): + cdef np.ndarray[np.uint32_t, ndim=1] cnts + cdef RLE R + cdef uint *data + n = len(ucRles) + objs = [] + for i in range(n): + Rs = RLEs(1) + cnts = np.array(ucRles[i]['counts'], dtype=np.uint32) + # time for malloc can be saved here but it's fine + data = malloc(len(cnts)* sizeof(uint)) + for j in range(len(cnts)): + data[j] = cnts[j] + R = RLE(ucRles[i]['size'][0], ucRles[i]['size'][1], len(cnts), data) + Rs._R[0] = R + objs.append(_toString(Rs)[0]) + return objs + +def frPyObjects(pyobj, siz h, w): + if type(pyobj) == np.ndarray: + objs = frBbox(pyobj, h, w ) + elif type(pyobj) == list and len(pyobj[0]) == 4: + objs = frBbox(pyobj, h, w ) + elif type(pyobj) == list and len(pyobj[0]) > 4: + objs = frPoly(pyobj, h, w ) + elif type(pyobj) == list and type(pyobj[0]) == dict: + objs = frUncompressedRLE(pyobj, h, w) + else: + raise Exception('input type is not supported.') + return objs diff --git a/LAVT-RIS/refer/external/mask.py b/LAVT-RIS/refer/external/mask.py new file mode 100644 index 0000000000000000000000000000000000000000..5462c341d99d02500b0e0abe6418bde5b5838b0c --- /dev/null +++ b/LAVT-RIS/refer/external/mask.py @@ -0,0 +1,82 @@ +__author__ = 'tsungyi' + +import external._mask as _mask + +# Interface for manipulating masks stored in RLE format. +# +# RLE is a simple yet efficient format for storing binary masks. RLE +# first divides a vector (or vectorized image) into a series of piecewise +# constant regions and then for each piece simply stores the length of +# that piece. For example, given M=[0 0 1 1 1 0 1] the RLE counts would +# be [2 3 1 1], or for M=[1 1 1 1 1 1 0] the counts would be [0 6 1] +# (note that the odd counts are always the numbers of zeros). Instead of +# storing the counts directly, additional compression is achieved with a +# variable bitrate representation based on a common scheme called LEB128. +# +# Compression is greatest given large piecewise constant regions. +# Specifically, the size of the RLE is proportional to the number of +# *boundaries* in M (or for an image the number of boundaries in the y +# direction). Assuming fairly simple shapes, the RLE representation is +# O(sqrt(n)) where n is number of pixels in the object. Hence space usage +# is substantially lower, especially for large simple objects (large n). +# +# Many common operations on masks can be computed directly using the RLE +# (without need for decoding). This includes computations such as area, +# union, intersection, etc. All of these operations are linear in the +# size of the RLE, in other words they are O(sqrt(n)) where n is the area +# of the object. Computing these operations on the original mask is O(n). +# Thus, using the RLE can result in substantial computational savings. +# +# The following API functions are defined: +# encode - Encode binary masks using RLE. +# decode - Decode binary masks encoded via RLE. +# merge - Compute union or intersection of encoded masks. +# iou - Compute intersection over union between masks. +# area - Compute area of encoded masks. +# toBbox - Get bounding boxes surrounding encoded masks. +# frPyObjects - Convert polygon, bbox, and uncompressed RLE to encoded RLE mask. +# +# Usage: +# Rs = encode( masks ) +# masks = decode( Rs ) +# R = merge( Rs, intersect=false ) +# o = iou( dt, gt, iscrowd ) +# a = area( Rs ) +# bbs = toBbox( Rs ) +# Rs = frPyObjects( [pyObjects], h, w ) +# +# In the API the following formats are used: +# Rs - [dict] Run-length encoding of binary masks +# R - dict Run-length encoding of binary mask +# masks - [hxwxn] Binary mask(s) (must have type np.ndarray(dtype=uint8) in column-major order) +# iscrowd - [nx1] list of np.ndarray. 1 indicates corresponding gt image has crowd region to ignore +# bbs - [nx4] Bounding box(es) stored as [x y w h] +# poly - Polygon stored as [[x1 y1 x2 y2...],[x1 y1 ...],...] (2D list) +# dt,gt - May be either bounding boxes or encoded masks +# Both poly and bbs are 0-indexed (bbox=[0 0 1 1] encloses first pixel). +# +# Finally, a note about the intersection over union (iou) computation. +# The standard iou of a ground truth (gt) and detected (dt) object is +# iou(gt,dt) = area(intersect(gt,dt)) / area(union(gt,dt)) +# For "crowd" regions, we use a modified criteria. If a gt object is +# marked as "iscrowd", we allow a dt to match any subregion of the gt. +# Choosing gt' in the crowd gt that best matches the dt can be done using +# gt'=intersect(dt,gt). Since by definition union(gt',dt)=dt, computing +# iou(gt,dt,iscrowd) = iou(gt',dt) = area(intersect(gt,dt)) / area(dt) +# For crowd gt regions we use this modified criteria above for the iou. +# +# To compile run "python setup.py build_ext --inplace" +# Please do not contact us for help with compiling. +# +# Microsoft COCO Toolbox. version 2.0 +# Data, paper, and tutorials available at: http://mscoco.org/ +# Code written by Piotr Dollar and Tsung-Yi Lin, 2015. +# Licensed under the Simplified BSD License [see coco/license.txt] + +encode = _mask.encode +decode = _mask.decode +iou = _mask.iou +merge = _mask.merge +area = _mask.area +toBbox = _mask.toBbox +frPyObjects = _mask.frPyObjects \ No newline at end of file diff --git a/LAVT-RIS/refer/external/maskApi.c b/LAVT-RIS/refer/external/maskApi.c new file mode 100644 index 0000000000000000000000000000000000000000..85e397918278126ce11f225dc109efbeb8a9394f --- /dev/null +++ b/LAVT-RIS/refer/external/maskApi.c @@ -0,0 +1,230 @@ +/************************************************************************** +* Microsoft COCO Toolbox. version 2.0 +* Data, paper, and tutorials available at: http://mscoco.org/ +* Code written by Piotr Dollar and Tsung-Yi Lin, 2015. +* Licensed under the Simplified BSD License [see coco/license.txt] +**************************************************************************/ +#include "maskApi.h" +#include +#include + +uint umin( uint a, uint b ) { return (ab) ? a : b; } + +void rleInit( RLE *R, siz h, siz w, siz m, uint *cnts ) { + R->h=h; R->w=w; R->m=m; R->cnts=(m==0)?0:malloc(sizeof(uint)*m); + siz j; if(cnts) for(j=0; jcnts[j]=cnts[j]; +} + +void rleFree( RLE *R ) { + free(R->cnts); R->cnts=0; +} + +void rlesInit( RLE **R, siz n ) { + siz i; *R = (RLE*) malloc(sizeof(RLE)*n); + for(i=0; i0 ) { + c=umin(ca,cb); cc+=c; ct=0; + ca-=c; if(!ca && a0) { + crowd=iscrowd!=NULL && iscrowd[g]; + if(dt[d].h!=gt[g].h || dt[d].w!=gt[g].w) { o[g*m+d]=-1; continue; } + siz ka, kb, a, b; uint c, ca, cb, ct, i, u; int va, vb; + ca=dt[d].cnts[0]; ka=dt[d].m; va=vb=0; + cb=gt[g].cnts[0]; kb=gt[g].m; a=b=1; i=u=0; ct=1; + while( ct>0 ) { + c=umin(ca,cb); if(va||vb) { u+=c; if(va&&vb) i+=c; } ct=0; + ca-=c; if(!ca && athr) keep[j]=0; + } + } +} + +void bbIou( BB dt, BB gt, siz m, siz n, byte *iscrowd, double *o ) { + double h, w, i, u, ga, da; siz g, d; int crowd; + for( g=0; gthr) keep[j]=0; + } + } +} + +void rleToBbox( const RLE *R, BB bb, siz n ) { + siz i; for( i=0; id?1:c=dy && xs>xe) || (dxye); + if(flip) { t=xs; xs=xe; xe=t; t=ys; ys=ye; ye=t; } + s = dx>=dy ? (double)(ye-ys)/dx : (double)(xe-xs)/dy; + if(dx>=dy) for( d=0; d<=dx; d++ ) { + t=flip?dx-d:d; u[m]=t+xs; v[m]=(int)(ys+s*t+.5); m++; + } else for( d=0; d<=dy; d++ ) { + t=flip?dy-d:d; v[m]=t+ys; u[m]=(int)(xs+s*t+.5); m++; + } + } + /* get points along y-boundary and downsample */ + free(x); free(y); k=m; m=0; double xd, yd; + x=malloc(sizeof(int)*k); y=malloc(sizeof(int)*k); + for( j=1; jw-1 ) continue; + yd=(double)(v[j]h) yd=h; yd=ceil(yd); + x[m]=(int) xd; y[m]=(int) yd; m++; + } + /* compute rle encoding given y-boundary points */ + k=m; a=malloc(sizeof(uint)*(k+1)); + for( j=0; j0) b[m++]=a[j++]; else { + j++; if(jm, p=0; long x; int more; + char *s=malloc(sizeof(char)*m*6); + for( i=0; icnts[i]; if(i>2) x-=(long) R->cnts[i-2]; more=1; + while( more ) { + char c=x & 0x1f; x >>= 5; more=(c & 0x10) ? x!=-1 : x!=0; + if(more) c |= 0x20; c+=48; s[p++]=c; + } + } + s[p]=0; return s; +} + +void rleFrString( RLE *R, char *s, siz h, siz w ) { + siz m=0, p=0, k; long x; int more; uint *cnts; + while( s[m] ) m++; cnts=malloc(sizeof(uint)*m); m=0; + while( s[p] ) { + x=0; k=0; more=1; + while( more ) { + char c=s[p]-48; x |= (c & 0x1f) << 5*k; + more = c & 0x20; p++; k++; + if(!more && (c & 0x10)) x |= -1 << 5*k; + } + if(m>2) x+=(long) cnts[m-2]; cnts[m++]=(uint) x; + } + rleInit(R,h,w,m,cnts); free(cnts); +} diff --git a/LAVT-RIS/refer/external/maskApi.h b/LAVT-RIS/refer/external/maskApi.h new file mode 100644 index 0000000000000000000000000000000000000000..ebc7892da38289b459d6be824e1f849878bd4069 --- /dev/null +++ b/LAVT-RIS/refer/external/maskApi.h @@ -0,0 +1,60 @@ +/************************************************************************** +* Microsoft COCO Toolbox. version 2.0 +* Data, paper, and tutorials available at: http://mscoco.org/ +* Code written by Piotr Dollar and Tsung-Yi Lin, 2015. +* Licensed under the Simplified BSD License [see coco/license.txt] +**************************************************************************/ +#pragma once + +typedef unsigned int uint; +typedef unsigned long siz; +typedef unsigned char byte; +typedef double* BB; +typedef struct { siz h, w, m; uint *cnts; } RLE; + +/* Initialize/destroy RLE. */ +void rleInit( RLE *R, siz h, siz w, siz m, uint *cnts ); +void rleFree( RLE *R ); + +/* Initialize/destroy RLE array. */ +void rlesInit( RLE **R, siz n ); +void rlesFree( RLE **R, siz n ); + +/* Encode binary masks using RLE. */ +void rleEncode( RLE *R, const byte *mask, siz h, siz w, siz n ); + +/* Decode binary masks encoded via RLE. */ +void rleDecode( const RLE *R, byte *mask, siz n ); + +/* Compute union or intersection of encoded masks. */ +void rleMerge( const RLE *R, RLE *M, siz n, int intersect ); + +/* Compute area of encoded masks. */ +void rleArea( const RLE *R, siz n, uint *a ); + +/* Compute intersection over union between masks. */ +void rleIou( RLE *dt, RLE *gt, siz m, siz n, byte *iscrowd, double *o ); + +/* Compute non-maximum suppression between bounding masks */ +void rleNms( RLE *dt, siz n, uint *keep, double thr ); + +/* Compute intersection over union between bounding boxes. */ +void bbIou( BB dt, BB gt, siz m, siz n, byte *iscrowd, double *o ); + +/* Compute non-maximum suppression between bounding boxes */ +void bbNms( BB dt, siz n, uint *keep, double thr ); + +/* Get bounding boxes surrounding encoded masks. */ +void rleToBbox( const RLE *R, BB bb, siz n ); + +/* Convert bounding boxes to encoded masks. */ +void rleFrBbox( RLE *R, const BB bb, siz h, siz w, siz n ); + +/* Convert polygon to encoded mask. */ +void rleFrPoly( RLE *R, const double *xy, siz k, siz h, siz w ); + +/* Get compressed string representation of encoded mask. */ +char* rleToString( const RLE *R ); + +/* Convert from compressed string representation of encoded mask. */ +void rleFrString( RLE *R, char *s, siz h, siz w ); diff --git a/LAVT-RIS/refer/pyEvalDemo.ipynb b/LAVT-RIS/refer/pyEvalDemo.ipynb new file mode 100644 index 0000000000000000000000000000000000000000..54936371ebd0f3c96a172d3c684bcc0d2fdbfa55 --- /dev/null +++ b/LAVT-RIS/refer/pyEvalDemo.ipynb @@ -0,0 +1,308 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": 1, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [ + "%matplotlib inline\n", + "from refer import REFER\n", + "import numpy as np\n", + "import sys\n", + "import os.path as osp\n", + "import json\n", + "import matplotlib.pyplot as plt\n", + "from matplotlib.patches import Rectangle" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "loading dataset refcoco into memory...\n", + "creating index...\n", + "index created.\n", + "DONE (t=9.47s)\n" + ] + } + ], + "source": [ + "data_root = './data' # contains refclef, refcoco, refcoco+, refcocog and images\n", + "dataset = 'refcoco'\n", + "splitBy = 'unc'\n", + "refer = REFER(data_root, dataset, splitBy)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# 1. Evaluate Refering Expressions by Language Metrics" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [ + "sys.path.insert(0, './evaluation')\n", + "from refEvaluation import RefEvaluation" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "{u'sent': u'man in black', u'ref_id': 47}\n" + ] + } + ], + "source": [ + "# Here's our example expression file\n", + "sample_expr_file = json.load(open('test/sample_expressions_testA.json', 'r'))\n", + "sample_exprs = sample_expr_file['predictions']\n", + "print sample_exprs[0]" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "tokenization...\n", + "setting up scorers...\n", + "computing Bleu score...\n", + "{'reflen': 5356, 'guess': [5009, 3034, 1477, 275], 'testlen': 5009, 'correct': [2576, 580, 112, 2]}\n", + "ratio: 0.935212845407\n", + "Bleu_1: 0.480\n", + "Bleu_2: 0.293\n", + "Bleu_3: 0.182\n", + "Bleu_4: 0.080\n", + "computing METEOR score...\n", + "METEOR: 0.172\n", + "computing Rouge score...\n", + "ROUGE_L: 0.414\n", + "computing CIDEr score...\n", + "CIDEr: 0.669\n" + ] + } + ], + "source": [ + "refEval = RefEvaluation(refer, sample_exprs)\n", + "refEval.evaluate()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# 2. Evaluate Referring Expressions by Duplicate Rate" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "108/750 (14.40%) images have duplicate predicted sentences.\n" + ] + } + ], + "source": [ + "# evalue how many images contain duplicate expressions\n", + "pred_refToSent = {int(it['ref_id']): it['sent'] for it in sample_exprs}\n", + "pred_imgToSents = {}\n", + "for ref_id, pred_sent in pred_refToSent.items():\n", + " image_id = refer.Refs[ref_id]['image_id']\n", + " pred_imgToSents[image_id] = pred_imgToSents.get(image_id, []) + [pred_sent]\n", + "# count duplicate\n", + "duplicate = 0\n", + "for image_id, sents in pred_imgToSents.items():\n", + " if len(set(sents)) < len(sents):\n", + " duplicate += 1\n", + "ratio = duplicate*100.0 / len(pred_imgToSents)\n", + "print '%s/%s (%.2f%%) images have duplicate predicted sentences.' % (duplicate, len(pred_imgToSents), ratio)" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "collapsed": true + }, + "source": [ + "# 3.Evaluate Referring Comprehension" + ] + }, + { + "cell_type": "code", + "execution_count": 49, + "metadata": { + "collapsed": true + }, + "outputs": [], + "source": [ + "# IoU function\n", + "def computeIoU(box1, box2):\n", + " # each box is of [x1, y1, w, h]\n", + " inter_x1 = max(box1[0], box2[0])\n", + " inter_y1 = max(box1[1], box2[1])\n", + " inter_x2 = min(box1[0]+box1[2]-1, box2[0]+box2[2]-1)\n", + " inter_y2 = min(box1[1]+box1[3]-1, box2[1]+box2[3]-1)\n", + "\n", + " if inter_x1 < inter_x2 and inter_y1 < inter_y2:\n", + " inter = (inter_x2-inter_x1+1)*(inter_y2-inter_y1+1)\n", + " else:\n", + " inter = 0\n", + " union = box1[2]*box1[3] + box2[2]*box2[3] - inter\n", + " return float(inter)/union" + ] + }, + { + "cell_type": "code", + "execution_count": 41, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [ + "# randomly sample one ref\n", + "ref_ids = refer.getRefIds()\n", + "ref_id = ref_ids[np.random.randint(0, len(ref_ids))]\n", + "ref = refer.Refs[ref_id]\n", + "\n", + "# let's fake one bounding box by randomly picking one instance inside this image\n", + "image_id = ref['image_id']\n", + "anns = refer.imgToAnns[image_id]\n", + "ann = anns[np.random.randint(0, len(anns))]" + ] + }, + { + "cell_type": "code", + "execution_count": 42, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "1. person bending\n", + "2. man\n", + "3. the person bending over\n" + ] + }, + { + "data": { + "image/png": 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dlH6UYKdwbgdWXsoCnznvOC6YGdYvT3EwPoALYzT8JrwLZDHn4cN/RFRDrUZf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\nEeknS58+j0g/Wfr0eUT+H9bjcOnSi+aPAAAAAElFTkSuQmCC\n", + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "# draw box of the ref using 'green'\n", + "plt.figure()\n", + "refer.showRef(ref, seg_box='box')\n", + "# draw box of the ann using 'red'\n", + "ax = plt.gca()\n", + "bbox = ann['bbox']\n", + "box_plot = Rectangle((bbox[0], bbox[1]), bbox[2], bbox[3], fill=False, edgecolor='red', linewidth=2)\n", + "ax.add_patch(box_plot)\n", + "plt.show()" + ] + }, + { + "cell_type": "code", + "execution_count": 51, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "IoU=[0.09], wrong comprehension!\n" + ] + } + ], + "source": [ + "# Is the ann actually our ref?\n", + "# i.e., IoU >= 0.5?\n", + "ref_box = refer.refToAnn[ref_id]['bbox']\n", + "ann_box = ann['bbox']\n", + "IoU = computeIoU(ref_box, ann_box)\n", + "if IoU >= 0.5:\n", + " print 'IoU=[%.2f], correct comprehension!' % IoU\n", + "else:\n", + " print 'IoU=[%.2f], wrong comprehension!' % IoU" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "collapsed": true + }, + "outputs": [], + "source": [] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 2", + "language": "python", + "name": "python2" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 2 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython2", + "version": "2.7.6" + } + }, + "nbformat": 4, + "nbformat_minor": 0 +} diff --git a/LAVT-RIS/refer/pyReferDemo.ipynb b/LAVT-RIS/refer/pyReferDemo.ipynb new file mode 100644 index 0000000000000000000000000000000000000000..5e0acca58e58539979beeb256048f09d0a092145 --- /dev/null +++ b/LAVT-RIS/refer/pyReferDemo.ipynb @@ -0,0 +1,229 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": 1, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [ + "%matplotlib inline\n", + "from refer import REFER\n", + "import numpy as np\n", + "import skimage.io as io\n", + "import matplotlib.pyplot as plt" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Load Refer Dataset" + ] + }, + { + "cell_type": "code", + "execution_count": 18, + "metadata": { + "collapsed": false, + "scrolled": true + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "loading dataset refcoco into memory...\n", + "creating index...\n", + "index created.\n", + "DONE (t=9.88s)\n" + ] + } + ], + "source": [ + "data_root = './data' # contains refclef, refcoco, refcoco+, refcocog and images\n", + "dataset = 'refcoco'\n", + "splitBy = 'unc'\n", + "refer = REFER(data_root, dataset, splitBy)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Stats about the Dataset" + ] + }, + { + "cell_type": "code", + "execution_count": 19, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "dataset [refcoco_unc] contains: \n", + "142210 expressions for 50000 refs in 19994 images.\n", + "\n", + "Among them:\n", + "42404 refs are in split [train].\n", + "3811 refs are in split [val].\n", + "3785 refs are in split [test].\n" + ] + } + ], + "source": [ + "# print stats about the given dataset\n", + "print 'dataset [%s_%s] contains: ' % (dataset, splitBy)\n", + "ref_ids = refer.getRefIds()\n", + "image_ids = refer.getImgIds()\n", + "print '%s expressions for %s refs in %s images.' % (len(refer.Sents), len(ref_ids), len(image_ids))\n", + "\n", + "print '\\nAmong them:'\n", + "if dataset == 'refclef':\n", + " if splitBy == 'unc':\n", + " splits = ['train', 'val', 'testA', 'testB', 'testC']\n", + " else:\n", + " splits = ['train', 'val', 'test']\n", + "elif dataset == 'refcoco':\n", + " splits = ['train', 'val', 'test']\n", + "elif dataset == 'refcoco+':\n", + " splits = ['train', 'val', 'test']\n", + "elif dataset == 'refcocog':\n", + " splits = ['train', 'val'] # we don't have test split for refcocog right now.\n", + " \n", + "for split in splits:\n", + " ref_ids = refer.getRefIds(split=split)\n", + " print '%s refs are in split [%s].' % (len(ref_ids), split)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Show Refered Object and its Expressions" + ] + }, + { + "cell_type": "code", + "execution_count": 24, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "ref_id [22758] (ann_id [540661])\n", + "1. woman in front\n", + "2. lady smiling\n", + "3. woman\n" + ] + }, + { + "data": { + "image/png": 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h3+fadMrb3/koV6/fJLuxTUvVvO+RcwgZsn5si6qqqKuKXm/AbLoL1mCKCiUg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esn6enpxQlbCNEhFDtArGpsuv71FC6+GRSbLkXH1CwKo6PM+T69bVjnC/pDAyVQqLRjQqkSxwlR\nnNClqAyagoHRYWaPHeKmdZuorK2yOrdAJARqIYsTRIz0DPDxP+7n8EQW3g3iTXDh1fcijemXdGRR\nHFMtlYFOBpYkHZ69/E8W+VJ2OJDi/PH4vE+wKjqCy0CRpPM5No5OUMjaxLqOIj2ErJEfNFDTAt8K\n8Yhp1JuUKhVWSyVOnjzNn7zvz7jlttu59rrraDQbPPrYY2xav4Err7qUb37761SK83z3W1+kv8fG\nsgye2Pc8S3WXQOh4cUwUhSSE+FGIoen89Z//FRddsINatYaiKHzuXz/EYC8Yaoxpg5oU8etneMsb\nL3rZe/YVCxbVEDS9Jrahk0sU7BiCtQqGIqm3q7T8BnML50BV2LprJ8uLy0gEczMLjI1O0p3rZenc\nCvVqm3LdZbZY48CJUyRC4IQ+1XqV559/ntmFeSr1BiuVKsVmg5LThJTOwPoxpJWh5oU0Y4Ebi04H\nYNIxqEtn06zf0UbZD+yAarOXLZs20hO67I01+ppttDgk39tPkksj0wpJ5GK6HlbYZMzW2aVo7PEU\nml7IwsoyCytr5Hp6qCQ+aSdm+9ZtVJwW6uhujOvew5LjkQMaK0VUoVAHllMq08Uih44dR9i9uInA\n8UNiVMIkgThkSDPRLYv1TouD//RRBkWCranU6w2efOEgmp0iCiL8us/n/uJSVn9FhQ2g3hlSGHkf\nitIAEoSi0Xaa52eQn7hY58nQL6ZbnUMvFgHil6piL739fLXu0aefIG2a6EpETz7NrvFB3nPz1bxt\n907ecf0NXL91F06lTdvzMHWLHTt2MNQ7yrNPH+LA8yd49JGnOHzwEN25Am996y/w+S98ktnZ4wRu\nA1s1WGqGrHkxrqoRCIWW53VmFTrEZCFUFEWhN1fgV9/+diZGR3nyqWfRUlk+8YVPIc0MMrKwZYwa\n1rnppr0ve8++YsHy/NP7OHz4GE899xxP7X+B/ceO8sLx4zx38DjTZ1c5fWyWdO8o5PtotkLarQjX\nCRlYvxlfgjnQjT3Ui6pp9PQPsnnzTiY3byZ22ihuk5wpaJdLhI02MozpzufoTqfIahopFdxaGaRL\nFLh47TZe26HdqKMlESk1IQxcBkeWOh2FV0J9eZRWbY3CUC+psQ0E6RzVcpOVdgUqdeIoIdYUlC4b\nK5Mim89jJgqJDuPSY53QiJttHMVAzw4wtGMTU4vn0IRgcf+DyBOPkbFtotijJOssN6uUc2kOiQij\np4eB7gwZUURTYxwnRJUKhRgsoeC0A3r0LkpCIZ94bBIpUpHKOlWCVNm5cTetpouIE1bnPf7pv12I\n91EBU6D+3RL57DtBhigiRtP+F3PvHWXZWZ15/973xHturpw6R6kldYtWzmoFMKAGkYwMzmBg7DEG\n883YHnscZuzBJjiQwUnYBgmwMEpGEkLIVkChgzp3V3dXdVV1hVtVN9+Tz3m/P251Sx6PNesz3yzN\nWavWqnvuunfdqvXuu/d+9rOfR19BueiSKKW2whlLEQpUkiKUQKguUCy1eEXUr5ttEpWS0oXE/+7R\nb9Mz1o9pw3DO45bL1pKzfQrFhHVFxa51A7x352Z2rRvk1vWjDM2d5eYNq9h9w/UkQUSr5bJ+64WM\nrBnmt379w5w++hK6UigBHgmNSBEiCVyP2O9gGRpSKDRpYZo5nIKNZVskKiWfyfHB930AyzT43Be+\nxJ6jx/j4H/4eod+lUxXKBartV2/wXzN1l/r0fgxDx281MVVC2PIIiFheWoZEccG2bdRrNQI/otFo\nMDo62i0V/ADDMhGmQbPeIGsZBK6HiFOk6or2LdbaHDo0Thy6xAoaQUBpcAAVgopjEIo0SbuoW1c3\nlcD1aTRqmJaB1AW2ZnLLT97H2Mcm4D3wbOYNFMav4/h3nmJ7VEQszLG0bgC7ETE7NUF++zZe3LeX\n9UG3NGkUTXwvwpOSZ/WQzYMbmW/UmWxXKBXK+HGAEgk9vqJgaMi2C1FEU0s4Y2hoZoGBLVtJpyeQ\n7TYyjUFP6RkcZT4Oqfg+se9jeS2uLQwj9AzNRpueNCESiuNJwMCG9eydX2DQyFIoGKT1Nr4b0mPn\nueJ2l/f+9iHk1cBnIL7jE6jkA1z5ustYrHqk6St4YSu9ystlmESpmCSNu573wkIRIdC6KwFSEkuF\nJTWsGC5d18tvvuUGCsqknYCmQRiBIS3SpMW9B8eZXgxZkzrE0uHOX/gQzsgAX/zrL3NyZorTp8ZJ\n0rA7PBUaqRJI3SRB6y6cKYUQiiiKMU0Dx3GQUpAkASRpl4irGyBg9ab1XHXtNSzXUz760Z/mr/7y\n77nnr/+c9/z4rXR8lz/45Bf+/eou/6cufXoeI5dFy+g0GnXKpsPcmSlqbpvLd1xOdaFCZaFCz8Ag\nY2NjBEFAEscrBzvG0vMsLC8yNjRErlzGa7dpNVucPHqEZjui4ackKYRJCEowO7eEplIM08Z1g64V\ntUgg7fKeVJoiNJ0gTknjGFe59I/NdDPL56C8Zyf1ZkqY7+HQyXkylmIWH3CpWwlm3OaoneKlMesS\njbZSGMrA7kTEdkipWGR6epI1WYeF2UUGizmsYpZ8T5H6zByZWEcJG4yYvsEicaqTkHRp42HAKimx\nQ4U3O48sZ1FpgkhBGxvlmfkGPXqEHccMWTmsyCeHwG97DBqCTHMJApOsk0PXE3wV8dTTQxh/P81d\nv9OAb4DYvQepaQwPj1BvnsEPwvPI8bkgOUdtEXTLNEM3yTgGKtVRRMRRiu/7pEhIUmIFIYoXzsxw\nshNz+XCZchIjBEQdH9NOCWuKvMgxH9U42pzg4rUX8I5f/hne/M638MzzTxIFCUolKOhuMmomCI0I\nSRwG6LogCWPSNMayLDKZruNwFIfINEYq0IREJQkIyenx06Rpwsj6HXzuK1/mY7/0K7zw1HfZvfst\nfOKPP/nqZ/b/eFT8G5dWskmkwA07ZDSdEwePoDIGWSvD7Owcru9jZrM03Q5n5xcQmkTTJUvLS7Ta\nbUbXrMXMOEw0WoxpDi035qUDJ3l+/z4u3Xkpjp6lKTRklMHBwUhZkQcyMTNxd58mdKkuzBGFMXam\nK5sjTQMhBP1jbazpCByIenIcf2aJTRdfy9MPPsZOzaR3aJQr33ob3mSFxalJ/L4epjXB8qET+J06\nkZGnXa9TckpkE52Z1hLlYo4kjuloMYFKaLSaSK8FkYchbAQdcipDve0SxDFLrWW0NGFEghP7WKli\nUUuIlIORagRCMbTpQp6ZfZaBzRvxDp8kSlK0KKKYM5iZX0A3FNbKvklISqLD2bDFyPBmxo9m4bYG\neAA+y0vLHDt6tLtHI1bWIekGi9Qkw8PDCAFnz851SWMi7cLFSYTUFGoFYBZKoqUKiSRVKYGe5z99\n6V4+/5GfYV0mRQJSS/E6Lkr3eeeOLVy3wWCyPs/vP/wIdjHDc49/H8sU+LGHNEzCVENJA01aKAQq\n6fqIpqqrG21ZDsVinlq9jiZFN+PRHbSKtFu6KaUYXjWG1BxmJo7Sahd5/PGn+aNP/h6Tx4/y0Q//\nCl/9+v3/5pl9zYLlhyeOsW39ZuxYY2l5mQt27sQjJhYC3XJIgoT6UpVGa46Lb7iaqFKntjxLwRnG\ncfIQpfhtj3y5zKmjx5mZPovKGbzjP76bU7NTLJ2ushwuMWAMIoMElYCuKZI4IEWR6hq+nxAlPmmS\n4HsJmqbheQmWqbNmQ+V8vzJ3qpdqM+X7f/cQ5cWAvoEyZilDy29QPXKSilclCOusWb8Wv+3T2x4i\n1BX+2Bqe3HeARcsiKxJEHNNUAdtHVrNQr1JPwekk5JRAJREaGo6hs+w2MfIl9EhDpG0SobEUxtha\nhobUiE2bRIQkSvHCdx/j9mtu5rFnn+baiy5BOzlHIi2M0iaaHMNIFXUV4UcJ2zds5qXnnqZ3aJR6\nfZGeKA8O4IIXdHj08RdII0GMD5hwLqugMEyd5doSuq6jGTpxrBBaCnqKUAopdUAghUCQoIQiJUGT\nAtIYz3T4yKfuZt2gxU+9882U05RhpUgzDs3GIrpdpt5uMTo8yHSnARHUgpBEpCSpBMNB0v0iU0kC\nKkEIiaWbWLqGLgVLy/PkslmiwMM8v82pMAwbP4lYs2EduVwOJ+tw+OA4laUF/qb2FT78/g/Q8nwy\nnVc/s69ZsFx2xQ7OPHeAkUKZgqE4tf8FPN+jMDSAYVi49RamoZPXE6Tv4S8vklMRTr6HpcoybhAh\nUsHx4wepRx5WPs9CZ47D33+Esws1dFlApj4in8HMZNAMhUKjo8Ucq0zik5DpgJEG6KmGiGOUiEji\nCDO2yQ9MwkPANXD65AjaQottpsWAErw4cZANi3mKZkJ09CShDKlGIWptm+kzp9DNPHpGRwiLqzds\n4/Fmg1nDBi+inDWZn6lQtxQzOUna9hiTBpbUMOIYqULypTKtBGwRkWoJU4FL3jBZVehl1UiJuaBD\nkArCJCEnNLz5BTbkexifmWRV6MLazWz97U/ztZ+9kTXFMmOlHoglZ6tVMk6RHrtEppzHap+BDOBC\nELpMzzWJ0rSrMilWuF5JsgIjy/Obkud6mXN0/jQ9l2G68PG5HucccoZKSZSkYRXYV005+pWHkF6d\ngWKG3lKRN197I6uMhMG+HhrP76HabiHtEh2lo2s26DZCGgip0xWeAKlinIxBLmvjtpqEvo9jGlh0\nuZ8qDhFKR9N0UgkXbN2GlbEJgoADLx3A8wJUPWDf1Cmcj/wSgxsu5+6//e6rntnXLFiWJk8yONpP\n2HJpVltki0VWb9xIrdNCpQnFgT6iOETTU+J6jUwxS2epw+mzC8wtLOAGMfOzi7RDj0AI3CShlTYo\n9BZRkWBka4npIzO4RsyZ1gJSxgil8LSIZbdKYmnMNT02j43Rp/cQtTyMjI4fBhhSY92WRjezfAD6\n67tYXjhEdk2GUn+ZM9UOc+2QUhBTzGYR+TzxUpVcrsjJ0ENTFkHQQERZZmstVtsmSXEj4VrJ8swp\ndMegd3iA2XqFgTVrmZ+ZJO/kSSOPQpSQsWzSyEBzl4nMAp6pM9pXJm4soYwSeWnRjjxSLUVKRbtV\nIwl8jLLAlRLR8LkkG7FzZAN+2CaOPZSf4C17ZHSYmTrJhtLFtBuqm1k8kJpLtbGAkCkGGRKSLny8\nklm6Oy3y/HwFJFJ20bFusKgVe/V0RU6sO9HXNK1rjZd6CF0hE4hj0Ap9TMYpzY5G2xnimJdyevoM\n61avZvHMJGGsIS0HodtdpftIgRIomaJpXd8XXU9pNqpIIrKOQeInhJ0WhiHJWBkCP0KzLNZs3oKR\nsanMz3P27Bxh4JEAeZGy66ab2L/3ea697kru++qXXvXMvmbQcauZ8MILL3BgYoLxZp2jy8u8ODvN\nVOhzarFFVVi4fSW0tZvwCmVEoUxkd+G9jF1mvuPS6rFYNl1OhcskeZN8uY9TM2fpHevhxMxJFIKg\nUUdTAUGnTZp0mFuYYvHsNNs3bmCpUWeuVWX/wjgzUZWWiHHjgHwhoCiqMAnpNo2kM4bpdUGD03rA\nruF1LJiKHxwYZ7bTJPRcCoYJekh2oJeKCoikIHA9NMuglCS0jxxkuT7PyMAqyoP9JColqjXRUoEx\nUkYZGa74zF9RyfRhz7kkwqMw2IdMJTdccytnGw2SKEZHI5fJk9VzZHxIhMLPm2R0iUxjGrqkp13n\n/h9/J72VOVqtJVSQYKQpsd8m9FysUoE4V0A5fefLMClc2s1uHaIQKCkRmkTJrkCFpmlIKVAqAWKE\neHk4qes6UnZdy4QQXSES0ZWOPUfGlMIgjWISkRDLhCiI0WJFHEb4aUJs2bQ0g/XbLiZnFQiiBENo\nmOgoZWAKSUYXZHQNR9PQkxi/3UYkKWkQE3o+SRpi2Dq5bAY39LH7Brhgx6WkwMnDxzgzNU07cPHC\nABuJLiV3vvUtPP/iS5w4dQZT/F+6KUkUsvOyK3DKZTw3xEjBVyEDm7ZSH58gSSSWAq/SIUybHDkx\nTuqH1LwOSwsV6iKinQFRsOkEdSqdCloEzWab+T37Wbd5PZqSWJZFGkUEvk8ninVmP2gAACAASURB\nVNh88YW0jvucmjzOdddfwpnTk0hp4qUerdYSWc2gd/hUV970Cliqj/DSvjMMjg1Ttw3KF1/CWs3i\nhrEiD56a4FDVZTgyyHspxmyFVfk+3OWzOAnIJMUulljyO+TCGF+IrkaairD7imRsEy9UxEYZrzjK\nfGE9V/3UXTz6F18gXKyxfugCnvPP0pidQTgFGm1Jbz4HQsc0ffKaiTIFk4vLFI0SQ6aO8udQpo6h\nm+Q0gS40MDTSWGHnshSFIJ/ro3Z8nGKvfz5YNOkipUGagJIvy8DJlUZfrcCzL18KIbp9yrmSq1ui\npYj/CXiVgEol59deVhgDADfdcAN9AwOMDo4hDItHv/c4qwZGyGQ6LNeapJqDFBLDshBJB1K3K7RI\njKZJAs/H0rq9Usax0TSNlu/ROzLG6g1bmZqaYurMma4IvEqRKqXftlASzs5Nsmb9CG9565v49J98\ngSB+dUXK1yyzrF8zigTcxRpxrUZzbo6wXieqVHDdJrHuEzTbLM9XOHXsJLXlJpWlGpXmIktJi6rX\nYGG5wsTZBQIvpO41cGOPZr1Jp+Ezf3IBGaZ0Gh3qtSb1dodKrcFz+/eiZQze9LbdNFoVDEsnTWM0\nXXH7rmsxtZTtO314GrgWqktrye2fY/OFm4mFQpRLPPrM06hDRxmRivzqYRbTFDVSwjctypvWMW3r\nzMURS3HAYuoShhFODGkYkxnsQaUJKQJTN5Cxy1C7RaNylNHThzh87z8wnKTYmqSlJfRlDDpnTpI0\nXUbWbaOTCDoqwU8j2ipEapLUV9RFyrrRzahEQyiIkogMEpQgSCIaUYu03SGptcgqgRX4pLE437Po\n0mO5XkOTAl3vcsLOy7WqlzcIX6nqoq1knHPZw7KsrmPbK3ZdpHz5sZTdH1S3sDNMk8suv4KMafPc\nC3tYWFziJ3/iPXzw/e9HVxFB6IEE01ToeoSKG5C00WVAGPmEoY8SCVKHQiGHIqHd9igPjaJncuzZ\nu4fxEye6mgKkyDih13ZYNzpKvVXj3e/9Ce657z7Wb1rP1MTU/26r+LXLLM3GMpq0qdbbECf09ZZZ\nWlpi7uxZ5GCBtGwzfWqOg0cOUllcRAFBEDDbqDHfqiJti56+fmq1Fl670f02jCOiOIVEUsr1YCQm\nIoqIUoGQOkmgWKxVKOtZHn3oASoVl/6eXrykw5YL17E4N8mmoV6Kvd/tBsuvwcETFr0L85x1fWbn\np9ASn6hS5YZsiaEwxtw6zMGpBeKZChMlk4t6VqEGxsm3AzKBT7NooXSDwTTDvB5hDZTJLNeo1ZYx\nTBNXS+gPwZYh87//G+gyJPQ7ZG0TreUhUp0eBFYhz/yp49iD/eilDLFQUMzSXKpywcAIZ2pLnFia\nor+3h9T30VLQIoVuKtIVSaNcrNDDEL/VwtFs5oLay5lF82g1GkjdIE67Si5qZXj7ykwhVrhfauXA\nn8sqSdIVretKvP7LfRgpX7lR+TKXzPM8+gYGmTgyzro165ivLrPvxb3UWg02blxP70AvL+0/ht3f\nS+RVsWSK1B08zyOKU1JiTNOkXCrQ7rRRcYLpZKg3XOrNCkngEa2QQkGR1QS5osPeicM0g5R3vP3d\nPPXUP/Pg/d/H0jMkvPry12uWWcL+tcwsNxjbso7NN11L2pNh/euvZPTai7FX5UmMAHuNzZYbL6a8\ndZBf+fh/Zviqtex6600MO2W0jmJ+fo6lSoXGfI2wE5PEgiBIsHMlEqGYixqMN2ZpRQ2Eimh3OoyM\njiJSi+efOUbchsWFGko3OHTqOEZ/L4enxxnorcAe4GoY35+jd6lB9ugUNzYk6zsR/bqJ3vawZULj\nif2svmUnfUWTDUJw9qEHGK4sstSpM9Xx8ZYj9EKBlpmS13VaUUrQU0aaOraRo9QA31CkUUrQcSm2\nOsxLRTnNopsSgpCCYaDqVQZNh1KuiNsO8L2QNNUIMhbj9Vmu0Er0Tc8T5mzMKCUQMSEhUzLtGp6K\nlFgltA2D05HH3qhJZTLoZhYPNFxKWafrE0myIkAh0YREItC1rt4xSp1fQxZ0AyCO45XASLDsrtyr\nUglCvAIRY4U+o+kIoaGURhDFzM0voUSC57U4evQopd4yd9zxRq67/Aqk5zNSyqC5dWzDIEKj2qgT\nJjFxmpCRgpxlUKs3afkRgZah1gxZWlzC7bQJ4nOfM6Ug4MLNG5lZXiJKNOrNZZycze7db+Tur/49\nkXDx+b/UU1KGDaZnTtGX0/jB/Q8Q9OdIJkzqHZflyjJ9g12r59mjC2iWxncf/w7DY0VOn55h7ZYh\nvMOn6FSbZJ0Sy60OmiYgihkuDaCkoFWpEHsBbTcm0EMypka908Br+vzlX/8Fb3/nO/H8BqVckdGx\nQSYnjnH1bTch7YNoBxSshxk3g1qQrB9ZxfzJCbzeIka5n9bqtaQLiwyXcljNGpN7j1MUJt78IiVl\nUkVjQShqvXlealUpzjTIK+gIyZm5BbZvvIiFVpswk2OREBkpxoDUkCSpRlMKWmlEmIYsixA76OBn\nTYr9ZTqNGmm7hu5k6MTdnRMj0Znwa1w2tgE1MkRcrZEJLE6qEF2zmGt0KMcJPf1DOJbNxi0Xcnz2\nFKv7HRIm0KRCJorFyjRSSgxdEEcKeb5Hkf+Chv8yXX9lYCk19FcIWkgJ6fnK7V9uW57brjRNiedF\n+H6KZWaJfY877riDam2ORx99mIWFBW66+Qbu+/vvML+4gJNz6PgB0F0atCwD3dTxfB83iImUxA+6\nWtFx3JWLUqKbDaRSjI6NcvTUKRJdcmZihge+9tfc/tY7+ME/7UHZo0hrEBV7wOy/fWb/fzv9/x8v\nt9Egly/z/N6XWOhUGZ+d4tvffpgXnt6HEhnuvec7zE4tcfTEGQ4dHedv7/kWLTdi1dqN9GwY5Pa3\nv55Y02g16pg5i0QFZB2DKGyhpSE7b7yEN77jRmICGq0Wy/UGw2MDDI/1c/z0US68eAuf/OPfxg/q\nJKnP4Ogov/2pP8BLnjnfr0zMDzMUaCT1DkY5T1LM0p5bZK5ZpV5t0Jmv0u+lBDNLyA2rOKWHHOpN\nedHyOaQ6hKUsGy68iHJ/P5uHRrl89Tp2rBrFDH1K/aM0/YCeTRspjKxCIYiJuz2GrrNspvRsWkfP\n6jUUevsYXr2WzNAgKuxQbLUx4hRPSlI0AlJm0xC5XCc8coqqbRHuuhlj+3bsUGLkMvT0j+AjqNVr\nTI0fw12oMD4/ReCKlxExPWSgp4+c5aBrEhCvYBmrFURMvtyz6GLlua5NxjkErNu7vFx6nVO2lOdR\ntS6sbJoWqK7Nn+8HVKvLfP/xf8IyHW64fhcTp6a56srryOdLdNohUujouoZhGCgl8KOEjhcSq64I\n4LmVgvOfL+2Oixw7w0KtRjOMOHj4MEePjrNqcJAXnn+OW267DS9uoJsGwvde9cy+ZsEyfmicE8cn\nmVuoM1VrMF93ydt9zIwv8MT3nmFsbAMvPH+AltvBMB1I8zzy8PMcOHiMu+/7FntPnqKWKJqNBhnH\nYmikj49+9MPYJVi7ZZAd127lzXft4qY3XgkiwpQBZytnkZbgyWeeICVk/OQhNmxcw9LSAs1WjaXF\nGhevX4QngBvg+cMmuVgi0pSznYD8mlGCpQp9vUUm9JRD0TInHZ+jGcUPY5ewUGSkZ4TbdlzD69Zu\n5uL1FzDQ24fX7iBbHvHcIiO2xeLyLGvWbaSvp5czk9MEcZfQqSmwhIGumURS44mnn2JucRGv4zM7\nc5aJmWnK+Sxre3pI/YBOHGObWWJNQ5Vy7JEVUhljB5JLrn8T+06dwPRc0qBDc6lC1GyQCyPyYcCQ\nYxDGbWJfdkuxDihRJwoCMrpNPp+jUMyfb8zPXWmadqWSVm69cif/3GPDMP4Vbf/cde6eYRjouoZl\n2mQyOeyMg27o3PnWn2BhvsX4iWluvvkNTE9PsfuOt2Ca5srr5XnQoNXxiFKIku6cB/FyXyQBQ9PJ\nmBaGZiB1k+/94El0M8O+gwcxyFAu9pOmHh987y188g8+wP33/Mm/+ryvvF41WIQQthDiOSHEfiHE\nESHE/1i53yOEeEwIcUII8agQovSK1/y6EGJcCHFMCHH7v/XeodugN2+RzzkMlnrxF5apN+rEpqRa\nr9FqNujtKRErl2xOp9Dr4IUtnv2n5xjIjiACQeK2yZgWuq74mfftxhppsvs9b6B3XR+5fMIPnnuM\nn37fexnbOExuKM9dv/AGshmL3/zQr3H11TvQMpIdl1zOzh0XoWKoLcxz0bomPAncAsXC63GGshys\n11hOXOaXl5j225woaey1Qcv1wc6t3LT5Yi5atYHtN1yHJmKaLZfleo2lEyeoVpaYbTWYczt4fhux\nMMsqIYimp7DaTdaYJp2wjWnYSGVTtwR5H5ZSn5xRQMSK5U6HfBAST4+jt5axHBs7Y+DFMZlSH6a0\nSF2fyU5CZyRPLCLu/6OPkY087JLFgDQxpIahdfuGIIkRskBDA38+A9uAf4bX76ogpQ1agohC9CRg\nsOxQzOkkaXenRWoaUqQYEjS6fU26slUqdW1FMznCMLtN/Cub+lcuj8VxiqbpDPbnGT89TjtMeOCB\nh3H9Brvf+mN0vAaPPfFdbrplF1EUct211yJJCWKPUIV4SbBiIqGhCYkuu0KB5zKfoWuYmqLc14uP\n4Mqrb+GB+x5AVzEbegtU/UVOHjzEJz78MXJzFY7+/bd45Atf/PcHi1LKB25WSu0ALqErDn4dP6JF\nHkBzqU5zqYG/3ES4EWM9Q2SERdYuIJTNqZNTFItl+nsGOXJonOnTc0ydnkOXDp1Wyr69R8gVewhN\nqLfaHDlxhly+QMNd5KorrmL9qo2YRg9/9bW/Zf2OtfSuK/Hc80dZWK6z58BeNmxYz+J8nWPjR9m+\n/WLu3H0H116mY+4DNsBUaHHoyCKZVKPvkq2Mmwmtusugnud1F17EzhuvYdXatYwUe2m0axza+zwy\njqjNLTI/MUncaBAv1zA7PlmnQKhpCMNApmA1m5hnZxg2dGzdJB8ktNIEteMqZsb6cHSNDamOSANk\nHDFNlchr8jqVoTq/zOxiBdKIjAZL8zPoAlIhsDIWs7UGQQB2JyDwGjS8NpECpWsopQikotps0AlC\nik4P+77ZB78I/Bm88+2zJGlKsafA0KoxpGmRCoFh2UgBGdvGsTPknCzFfB4NgSFkl9mLJPS7lHgh\nBJZlr2QP/V/QZLp7ZF1TJNd1CYOAQqFAs9lk165bkFJy5MgRrr/+eqIw5aX9x9ix/UriUONDH/hl\nMrpD5CVI9PMl3cpZ7QaJYZDJOKxet4bPf/mzxCrhs5//PJdddSmWOcDnP/VV2o1JVpf6WXpuP/2t\nGKfqkql2EM32vz9YVj7EuUmNSdfZpkbXIu/ulft3A29d+f28RZ5SahI4Z5H3r64wSfHCgNjUmQld\nJpcWOVOpsFhtYBg6pqFz843X8a633YGT0ZBS0VPo+rckSdT9R3shhqXTky2QkzmK1jCnZ2Y4PnmA\nKA7Bh//ygY/QN1DkpcMHaTY8ZGziRjEkNqODQ5imxK0GXH7xZfzKL2yDx4DboLK0mUsvvphksoqm\n2/S9bgcvNSrMNGtUpqYp5Iu0m01ap+eonj5DcnqaTCvETiRZx8QyDRxNIoOIfCYHpkGCxItSlJXB\n0BReHFMNQ3KJpJ7V6fv5D7Drzp9CpQqHhKJh4mkQ6CYNoaiSEBs2UurIlkvarCGjAA2FkpI0CBmf\nn6GR0cAGzZIoqXAltMMI0zTRHItMzmH9RRfQP7KKqf2XE+4yYBbGFjxueb2iubREMVcGdKJY4fsh\nRSeHTLuSVBnLQpOyCyunCkPTsQwdkSp0qZ1Hyrp0/pdh5nPZpcspM3CcLNValbm5WdasWcOLL7zI\nt775TY4cPszePXu46uorCUKXY8cP0dtXYM+Lz/NL/+E/krWzqFStIGtdfloul6Pc08OqVavYvGUT\nd/34XVx7/c387n//BA8++CRTU3XWrhsl9Ov0FPr5wd88gNloEy0vcnZxCalSMhn7RwsWIYQUQuyn\na4X3hFLqMK9ukTfzipf/Ly3yAOqtDs0oZMatM9FcwstoWLaF8APQUu58725kMeTW22/hwW99izfd\ndjuZjE6pN0cua7J563rcuEnetNBNna/d8zdYWYtdt7yeN+zaxcPfvw8vqNOiyYv7fsj99z7C63dv\nZ9X6IvuPPcmZs8eoVZe5eONFfPqzn+Uv7/kqvvtQN1huhYe/t8zBffsxay5zk6fI5QpsvOIq3JzF\n/IFxMkoQzldpN+usMfKsLfZRyHWNYPNCUM6Vuor3YUhfqZcl36XlB3iui8haSLvAqq0XMotPM2zR\nGyVc0Ih4/LNfIdE1Qk1gSR0jShhMbHryvTRNg7xSpJ0WuucyiMJMU9qRj65p2NkisabTbjVpyhQ/\nCImiGKlJpGWjazqaadJstDl+7AR7D+3lBz98nqe+Uepml8/Am982iabbTExOEMYxiRJknAKObaJU\njK4LNCkw9W6A2LZFwbLZuGoNYwNDGJpGlITEIiVfLICmd20QSLoSfJEPiYelh5TzGqQB9aV5Tp04\nyKWXbmHVcJmevM383DQv/vAptm5dg50RHJ88wZt234Fj2uzcsYOeQh5EimEY5PN5CoUCG9avp1Qq\nIzE5fmKCk6dnMNFYv+4CLtx5OS/+8/fYtWsHowMbeP7pp3nx+CGeOHaIQ6dPUYk9NOdHVKRU3fHt\nDiFEEXhECHHz//S8Ev+SB/Gv3uJ/dfPRZw+CJvHTGLOg4wwUMYWOsjXe/f73cGr5ONXA5I8+8/vc\ncusu3vXuOwh1nxPjZzl55Bij61az/YpL6C0WaLrLXLN1I5/9yz9k68WX89k//yJXXbOVmUmfb/7D\nPzK2aj0/PPXPPPa9Z2nVTPa+tJcPfvBXefQ7/8jOay/ld3/nN4hYYn2+AwcguRp2b/oE/oIg2Xs/\n2cpZJmZmiD1B2HIpSRCOQZKAMiUly6aqSeYXKmR0ExHGuFKSdprUhM7A8GrCfIaiodGXNTBH+jnS\nCEgT6JAwpVxWx4LHfveXWZW2mDUVwovI6Sm9UuIkCqfWJpEChUAkJpoQZIUASwfLQsYQS4FeHMDq\n+BxyXQbsApaQ5GKNOPIRrZg0kAxIjSHNYtmyWW9oVP6mQHrfInITXP+JNuu2WIyfjMlZ+ZWBY0Sk\nEuJErcC+Okkao5kGQRgy3DdAo17HyeZI0gQtFIgoIKcC1o/102NZZE0b27QIQw9NJZDEQMzk499k\nVCnSiUlOnXqWYnGY2WqL7RdvZ/0FFzC6fi25fJEzU3M8+MAD6JZGYbDA23beyZHDJzh+/CQZO4vj\n5LoKLvU6b3rTndxy+y1knR6efvIfCDJFwiN1solPGLl87APvY+PYGPuPHELYJqEUPDVxGk6P/2jB\n8oqgaAghHgJ28iNa5AHcfOkWMrZNtdPCk4Jjc7O4qUa+r8htt9+A+VJ3u3DXh67kySef49jkUerM\ncOzkIW655QaOnj5BYaCIKCjq1WVanmTjuo08+K2Huevdb+eev7uXU4cr5JwCb7rjDoazZf7rf/k4\nv/tbHwe9j/vveZS2t8zP7f55Pv+N/4EjfsCNWeAqODKd470/+RF+9rpb2d3TQys6i6y1yJo2VrlA\n2mmweGySIKcz5ClqkUczhdn5eWTOIRMm5Ab6MCxBnC9SXDeGmj5JtqdA7HbVGRfrddx2h3I7Reo6\nbuKD5pGkBqkfsVrL4CQxWRLMWBGnAkNKyqnAJ6JhKfw4hUhHej62MpDEFLIO+9t1ooxFoNoYiY4X\nuvT19EC1jiUsDDTcyjRJGFBTJqUJi1N782x6Zwu+DG952ySf/qNVQIJKFAhFnIJlOyRpSrzi2UIK\ntpOnFngYOiRBh4IhWV0cpGTrmEnXwUymMWnSIPElBTPTLVHtLHEcYJo2cZhSa7UoFnp5z6/+Otsu\nv5xEM4hQ6EnKsQOHufzSbbznZ36STMlBaBopgjhUfOQjH2XPnn1omiTVTXpGBhjd0MPQSJZHH3wQ\nldFZu6qM/9zz7L7rx/CExxsu2cGDzzzDHTt2UjQEvhXTiXwMS+P7x/6d/ixCiD4gVkrVhRAZ4Da6\n9p0/kkUeQEBKO+jgmoqFWhN0C98L6Mtn+frD36DSmqY23SF3x5t5+83vZbxyGg5n2HJRTLaQ4V13\n3cFzB/cwM71AbbbNoSWPky8tYOcz3Pu1++grbuakv4iXtMk5EcWi4NFHHuG//9ff4MDk83zmE/cS\nBW1+9b/9J971jnfQWfg6fKf7Fz73fA6tpVh1skOQxEw6El/T8aVJPVgmDn1yi4v4wxnqZ5pEvRkc\ny8Eu5RlYtQoxeZaak8FUIdO+YnFmkUqzypHFKgVT0h9J1ndCZlIXTNlFmYRNIBXIGBlqCGK0RIHo\nNrK6adJJIgbf/R4O/eNDZDothBF1B4MxdCyJb5jIIKZj6yRAKCUi6VoRYlgk0kRTJkmS0kg6yMFh\nJqKIpudRuHuATb/WgjfAO47VuPsra+i4JrFKkehErEzkhUClEZCSJooUgUwgb2foz1jkiBEoojBE\nL5TQDAu1skqcoFj2A4SXorkdDF0j9j2CMAGrwM//4se44KprSbqNDqYQKCnYtuMStmzaxNLCNH5k\nkS/1oltZpKb4s898mr17XuLDv/wRrt+5k2LR4fiBl7jrnXfyM+9/F9VaG7PZ5pg/T2wF/OCLf8uw\nnuUd11xB4rkokVIyLEQcI+JX1w3732WWYeDuFURL0jVgfVwIsQ/4hhDi54FJ4F3QtcgTQpyzyIv5\nNyzyADKOjUpjmvUWaRITBC5pHLG8WME0d7Bt+zamC0t85ut/w5urCzTbEROVRXoHTfpHCoRhwI2X\nX8ex4ktIXyCDlDBoM1Du4+ihM5x+8cWu2aaj8dS+F7jk0ksYGR7m8OwLfO2+v+Nzn/g0n/7yH3Hm\nzAT7Dx7gva/34JeAe+DJzytKPb1c3rOG6X37WHPppRiDJeLpRbzEZzyuUQgjBre/jiF1lqDHolBP\nmDFjnHKJ2Wde4jhtMu2AKjF2FDIgLGwzZWsgEaSISJDP5jhrpEwFErM8gLY4ThgJYsMmR0is64Sx\nwFIproq54t3vYv6Sm7ioXOTEl7+EFuiYwuOsZnLFh38VM3B57HNfIDR1HDRSNExSIpkyl4ToCtww\nJDE0NMumnM1hFfNYizWWT+ep5ubp2dzBfCjmTW9Z5p6v9qGQ3UySxF3HrzRF0w2EUF0ULlFkMwll\nS6IrRS0SmKZNb18PzWYdEQY0Gx2QKYi0OydRCkNKzFTHTTtkzSx33Pl2Nm/aRGVmlqGR4a5h0gpL\nWZGSmhqprhP7MbWFRRJVwSn3gYC+vh6+8udf4MD+fTiGxtatP0ZraYlSXy+F3hzZoknPxWvIWQ69\nVh5baFSbVY7PnsHrhOzcvh0VRSjtRwgWpdRB4F8pjymlqvwIFnkAepxQsCycVANdJ84YxArcdp3G\ncpUjp8+y64bbmD1Z57uP/ID3/cJPUunU2Dy6jsu3X8Zv/bff5pfe/4tct/V27v/277Fq1RiLs7OE\nYUzg+xi64s53vZF/euE5Jien+IuvfY2xoTJ2j4UIDf7wc3/KwkKNW2+/Ca9zmAE3hCp4WzSOHtbY\nmMkye/AgvbrO/mef5XUf+nke//7TCE1x0+23MzW7xLFnX2TY6OXM9Cx+pc7BpE0qJW5jgXLWYBSD\nNX5KLVYMlPppLs4hkSyJmELWxnRsCoUyW3fewtCmy9n/6Y+QMt6116aAGemkwkXFCbbUePLebzOs\nl6kYZTa/78O0dB0z1RhwBYtVi75mFWv1KGPrS7z4xDNd8mgagW5QKJZwMnmySifJGBCEK1CrjkoT\nIiU5+dh2rvjlZ+CT8LPf9Xji4T7aboCfxoQRhGFILpddoYgJ9DjANgzGijlyxERRQDNJCNOYTqVC\n5LvEcYTUjC6tXuuylnXdYN3adczOTBOEHT72X/8zA2Nj5B2HgtSpLyyQSLBtB8vJIlBYhsXA4DCG\nSImSBKnpSDPT9cHM5wHYcuE6Yi8AvUvsFKaJihRK0zD6BhjadBF3/cFmFmfmeOwfvo2+1KSUtRl7\n448x8eILuOP7XvXMvnYie0qQeiFlJ0eP7WBJwUBfEcsy2bf3AFpgceLFU1Qmljg7vcxTzzxHY2GW\nxx77Pnd/7W8Z6B/mG/d9g9Kg5PrLdvCm22/EKphMnV4gb9t86e4vcsFFWzCMmGwujy5Nbr3hJkaH\nBnnPu3+an33bz7F69Ua+8537ufmqFL4H3AKHTvRw5c4rWS8z5DoeZrNJf5zwg69/HcPt0KpX6cxW\nWD49yRVaLzNLC4xUWqz1U64UDjsSk8tyvWxrCxJ8HEsnDlr0rxqi7Uiigk1fYtCrW4i2R7tWIaou\nkPPrWGkHPeknCTOse9/vMfaR36IjFKGuI0RKD4JCtUkxN8LRMy0sLYfrCzqFEk5e8Mgzj+DnNTpZ\nRWSB0iSlUg8500EFAaHXot2qU63M05ibJapVSV0Xr93Am53nqb+2aV0PzED++Dxv2A1SKBzLxDRN\nSqUSzWaT0PNI4xgpNXqyIUUjIVEhiVQIkeJHAW7YIVIhURqCVNgZC0OCY2uUB/q5aOeVIBVrx0aw\ncwZ9Q/2kgUeqKyxTJ2caqMCnubjI/MwMM6cnCIKIdqzQ7CyaaXOORiCkXLHt0+i4blfAwsmilCKj\na0RRwNCadWBb6MODDF1+Ce/5nd/k4ltfz6SrOF6P+bmPfwK3Z+hVz+xrFix+EuHHIYHnoXyPkpMj\nn3UYGOzhtl2vZ356mQN7XmJ2cgInZzExMc3EsSk0Suzfd4JmPeXMVJNPffkbfPPeR/i93/wEOXMQ\nQ2bJmxZPPfNdHnviYb7yp3/BwEAvN9x8NZ/848/QarrceuU13HTdZdx08zauv+FyxoZOnp+vPPpE\nzMG9e7hkbDNxNSArcxRFgUFNQOQy1NNLc2Eed3EWe2aOmr/ISJSySVgMGhQ2KQAAIABJREFUBinL\nS3PMagnCzpA6WXrtAsLziBsN0kab1AuJVUwnSajrKQu2xvQLT3DmM78PnkfD1FC4ZAsDREtzJImJ\nrws8GVOTMdrW11GvThJXjnF07z/T8Kp0vAQqi4RnJykeOMnonnFu6h/C1HUCz0MkEXGzg5MKdNcn\nh05eN9DjrnKlCkOGM+D4Bi/+4xj8B+BL8P4POZRLeRzTwrZt4jhmcHAQx85gmRZKKvot+P0v/xmf\nffg73PiOtyB1jcT10KKYkXIfRcvCzJi4gYtjmdimzuLyMlahiC4EUwuzjG7bypG5M3gqQnMMnP4i\nViGLZupIBXk7y3D/APlCATub7VYiKzpN5+gzQghiT2EmNrXZBrWFOpWZs8wcPc7pA0eonjlLZ6GC\nUilGDFLovP3XPkz/RVvIRxoyDXh0OnrVM/uaBYsXKaJkhYCnNEi6Huydus+D33yIWqVGu9Uil7MI\nl5cQbZ2rbroK3ckyd7rOsecmWZ7osOeHe8mZOTLCYfLQCfKahZPv5Zlj+1i1ZYQ7f/od5JwybnWR\nu7/4dYYHx/jiN7/E//OpD7P7tt1sHZtiOHu0y0O4DQ4dyBEFAb07LkEbHqDRajGX1VB2gXapH3to\nlPZMhUvtIqkecfuuN9C/eSvFjesYHRulGcTkiyb1zhJZL0DVWph+QhAleJrN3tTlsIg5mIMzXoDR\nM8zqkVHCsElLU2iRS1baHPnUzzLztU9jaQGhSvC0gFU37abpRgjhkNl2HbkNOzHMIqG7xJMPfh1D\nBDi9WUwlWbNxDEOzSNKUXKyIIh+hCUxNYaUx0pK4XoMojDCETcNzsS0b/+A1cCfwXRDiCd7zoZ+j\nxzQp2Xkcy0ZLIpyMSRh5lLKCDat7cPIdQhnyzvd/mKGhke43vqahpCBBEocJ0nQwBAwbCiFthoaG\nsGRKyczxZx//U7ZdcCnCNJFCB6WjdB27mKcwUiY/XEYWDBKRop9nDHTXnaE79IyiiCjwiWVCHAf4\n7TZhs0PqNRgcHcTp66XQ1wtSEho6qdJQsYtZkAgke/ee4JqrL33VM/uaUfSjKOmiHkIjVQozm8MK\nXaQmqEYe5XIvbrWJ2/QZGRnk4ItHSKTP/OwijmlCpJAqREU6sZ5w0TUX0gzrJM2Ivfv3YTgaO7Zd\ngKmDbQs2btvMPz7zMDu2bOWS9Zfy8T/8Ew7t/wU+eM3zsAu4CSZTk5OndCwh2X/vQ1yU0ZnUfaw4\nJlMuM7plI3ue/SF5dLKxxA1aPPoPD7JrzUYKzRbC87Adkx5rgFR3WJIabRkxqSWgYoLBPqIo4ILe\nYZy8w1LBZ7LtkhkcoGZKZCS6U3IBIjVIhY4rXZzIJGM6aPr/y9x7B1l2VYf6394n3nz7dg7Tk2c0\nmpE0kpBQlkAiCBDYYJGTcQJjA8bhZ8CGR7IBG2QQwc+Bn22wjQy2iEKAJBSRUBxJM6PJPaFzuH3j\nyXvv98dtCWyD6tVzueRT1VXdXbdvh7tW77PXXuv7NI9++VPk0hgtNVp4yKhNU1iYbIVS3qHVDXAC\nzajOk+9ECJWC45OkGSmSIArxbBvfLeJTxCoNYMahG4ToKOHBr81x+Xt98iJCHKpz1VVD3PrVPhrN\nLkq5mAw8Zajm8rhCMbPQ4cuf+CtU3wSv/s13cuUvXcPBj30CWwpq1QIrSzNkVrWnnnAMnjRUSmUW\nZ+dwbRtjLJJOwIff/34++KcfXmtbWevvlwLRE68jRC+onzy1+49Nmq7j4FZ6trK+/hroHjvs/rtu\nZf3pp2GcPEb0sLOGbG2kI+YjH3kfP370CFMzs1x77cv52Ef++OfG7DOWLFGSYSwJvk9S9TgVNvGr\nRRxtcAJFq9mltdjC8nzmTq1gxS7dhQ5nbdnCKWeR5aU6+ZJPa6WBcgTz8yeoTQ7ilQqYVNBXq7Ln\n3gOI1GJxeZGbvnMrh4+c4sBpO3jp5a9i4eQcV5zxAGwA/hDmXi35kz8apur4jISKrY0OpfFRFpc0\n24Th5N7Hqe7eRcH36Pd9gnaHNE0pCodTcZsRS9K2bKbDgAVfc6K7QuIVcQfy1OwC7vpxJopFDu3b\nR7fdQocdvHyOUmOV0LWoC0FiFFIrhOOCyRDGIpOaunTIZwGzt36LzbHBRbPi+VS27uDEY7dRdmxC\nu0dd7KiMFIu5hx/g8gvP4cGH7iVLMuycT3VslI7KKFQHQAjsCHKFEq2gjc759BVKDG7bRGdOkH/e\nj+EWkG+9jWte9Wq+/q3bGLXhkQcfYGhkgPmFaXTXcOexaR44uEitf4Db736EN7/z7RjLI0Ew32gR\nGYlWhlLOQxJhVMa69ROUiyUsIUlTRalQJHN9/vWGr/DKN7zpJxRMoNdhtTY7w3+uVpmfuhWDNWZA\npjBaMTMzxRnnno10PdI1jpjBIJXg2IO3sf873+Liq6/kknMuYHnjGJaTe9qYfcaSJU4zUCCNRbcR\n4foWjfkljNak0lBfamKlAs+zCGOFLTwWjy9QdmwWp+eZ3LAOJRM8u4wnHZpRSNKMCE2ClXdY6tZZ\nPrbC6Ogwh/ZOsboU8LZffwefvf46br7xFnKuhbTpdbr9Drz5FevJWhYX797OWYs2g/dOoWZnuOS0\n01k8cIxRIUgbTdpTR+m3Xdo6o+La9GmH6VaThpMjEZrVvMvWnVtZpwyVYh+NNMXu1FmYn6NvfIJs\nZYUgESRJh8LYEIPGsBxFdHIuSgsqwsKono3LkpLTXvA29NgWVr7+t5QX5mlaisxyKF38HJx1W2gf\nfRShmuQLVWTaIdUaZdu0U8PNd9/C5MZ1+C1BF0GQpgRK0Zib70EzjKAetylWKhxbXKajUvLlMg/d\n4nD1VcANYN7wLYLpjdQqw2BnnLXrbO6773b6B8os15t0ZI7lTLK00MCZX+HeX3k71hoL+eRyE8e2\nGRsqYlu9FUNKRRJ1yOVKiCzFc12MVqhUUyzV0GtJ8aQ8SRowQv6MNOld/26FMRotLIQUaG1YmDvJ\n2MZJjLSRWqCF6fEJtGHq+zczkobs+ee/Z9vSHCPPvgzKE08bs8/cpKRlYVuSTCd4nsdi0KLTCigU\nynRWO/gih+UZklYdbQEiZKgyQBIabKvI0myTOOlQLRZxKxlpGEK7hLZS+ko1Vo81oAvzJ+aoVovU\n5xa5/lOf5qKLLuJNb3wtb33HrxJkgrxvoA2/+drX8tUvf4tqrcSBHzxE3tj0KZvZY1O4hQIjGyf5\n4UN72GoVsVWANIay0uSVYrRSYWDHRor5HG5jlczyScpFomPTLBZ98vNLtCxBog2ZMthCMpqroo3N\nahqyHIeMbNvKyftnEZYLmaFjW/RpTTtapdpYJVg6icCghEFJydSP70Td/QMKMkJ6OewkQFk2jiNI\ntcb2HCy7yOqpORynQBTDilTIKKakbcqWhWdprM4q/W6BmUSx3nXplz4Hb8q4+u+Bt4GwfswnP/cJ\nFrsOOo1IVYxtSVbrLaRXQGaGTCdEUpFiiI0NGGzL7uFVHYdjC4uctWEUS9ggUsLmCvc98lhvolIF\nqCxjKWwyPD6BEZIelUyscf5+1nryMy6jESRk+IhMszRznHWTo6Q42FriCE2MJCWDTpc0bLGqEpSX\n47E7bsNyNCNXvPBpv8Uzt7IkGYklek6/ekZR+OR8izhOKVsaXwgGijWs/hpBGJJzXfr7aywkbdIw\nxsnlKdkediugYXwmd20gtQKChiJoNOi0AzIR4SY2aZQwMVbjd9/1W3zmf3+Wr33H4rQzzySOj5Ov\ndaAOS+k+Xvnmq7nxU1/h4uJOWo15cp6HEjZxqFln59Ck5KwcWWLjFMo4QYhWCWFzlajeh5UmyHbE\n1I8ewLdAtTtYZOSlQyHTlKVPw8nT6HYYLPjE2tBIEhYXOmw8+wIOuUN0pMFJu1hZRmZs2nd8i9Ww\ng2/nCJwiIgvI0g6uiQikTd/wBnJZiBEKy3dwhU0sBBpBtxkRpE3cTGHZhkazxdjQCHGjjePmiJOM\nwMpoCk3HV2R9/RT8MusaNkc7Dps3pHiPw6YdTVbvy5OomLwDoRLIQhWF1VNTJBGOlVKrVqkOjWPb\nNsv1ZeIwIo4jxvsHUEYyuG4Twckp8rZP2XM4kqRYWUI3Cpmfm6O9OIc2vYlI1igxGDBCIHs48qdd\nYTQSKcBIxcLMCXZfeCndRGF5AoNC4uBpxZc//D7spEPec/E8H8tIHrrjDtbH/0OrYXpttFRhcIxh\nzM8x6vusy+fYXupnfaWKo1NUGlFxbbwsY3FmmvnlVdAWWRCRE3myvMu5z9tNTEyu1EdHR/RP9nH1\ny67kkpedxfrTx4gCTb2b8cDex/jg+z/Kq1/2ClABfmEE+oE6pMeWOHTfE1xV3cFQCOUzt8K2TTRG\nBzk1VuGEpRizLESnw3JfhZf/1WdYyeWQ0lCWNtHCEuHcIu5SA9NsMTk2SqmvhCUEqTJYmeqVTitF\nUiFZCTssBQFB1GHdWB+n9jzK5i07OO/Fv4i2HIRIyIxBhW1Cr8AZb/5dVM0nswSRFmRCUj19B/sr\nhv2FhE6niT41x7C0ed3zr+ZtV76ID1/1AtZJG1dq8jpDhhkJhlYY0MEQeRahgKbJOKkkt59a4IfH\np9h/4jCP35XvHTvfAhdc2KSbJiRGESQZKstQWYolIE0z0ixGoyiW8jhub2Vprjao1+skSUK9u8rU\n4jK37zlEXB1iMc0oDVSwPRfbcpmZ7akG9/7gJvb/8HasNTpNxhqvWKW9JNC9w1CQaxt4+RPSjAGJ\nhdSG9vIitUqRTBYo+AUsIdEGNBo01CqS2+56kMUgJkXg5QsUK0NM3/fQ08bsM6eckBZC2kg0mdG9\ndgNbY3kClSginZF5kkYckQsSSm6eILMpeA4qb4jjDs04ZHjzMMudRaTjM3OixdJsl+0b+zFOxhlb\nzmbP3f8Mnk03EFxx6TXsP34YlTXZfc5OllYfYrIGrEDu4UWOfW+awkCRsy+9mvrMcep2zA8ff5Rd\nu87gjkfvY3eqsKVkfbXMzG23MxwmVI2DygTacoiSlIqSOGlCrVJmJuhSzZfQRXDaAftnTxHmCkjP\nR1gghMb3ffJByqpq4uZ97v7mPzIg81jao+vaaJXH3riFfccPE7QXyTKFbbt0BcyvzhEMlUiNxTWT\n2zm3OkSzmsM9Nk+hHWHCFq5tsHVvHxRZFqueRcOzkN0OsSvw8jkqrsfFV76Avffdj9dXZHOhzNLj\nwFWPw5/C+Z8OCD9eQRiDwCBEhqVV7zXTMdIGx3YQQtJYbVKvL9NptQFQAprtCG0kLVvQPdhFOjnW\nnzhMHCvySuEVPMZGN6PDjOl7HmFl73G8aoXa+Dhj27dSGhumow22ULhCoozACAnGwqLn505JwQJX\npMzNHGd8ch2YhFQLLPFkmcAiCRqUfIfS5BbCMGA+jamuG0TbFuVK+elj9r89K37OpdKeCTfKehST\nxLbIPEmGYjVokPeKpGlGkGr6q/1k7ZhcLo+QMathG993QWXEi6s0hI8q52ksrOCmNscOTFGuVdg8\nuYsoMPiuAT/lSzd+ie07NnHJxefzsU98mFdfNQG1U1CHS97xOu67/yYeb5/kiscOMhcv0LV9dlWH\nWKjPsl3bKKNwkRSmFzjxDzfQj0ViKTCGbquF6StRKeSoxRlHpmdopSlWt4VVreJKSXVilPXrtnLq\noXtxohjdavT2Oc2YNO9igoCJqEnLleREjK0iVKLQhw6xcnIW45aRsoFQhk5R0Cmk9PeXkdUyjxxZ\nYJ1yEd2AfGKYFyH3lDo8kcswKWSuwLgOHZ2y+awzaJ9cQDgWgRTUV+tkjx9htFxhauoUwmtTUiOo\n9z+O9TCcuSlmoJxQb/YGuzKToeOQfM7tlbANRFGIY7tMTc+RJRHwpJPSgNFYdk8TsdII8HzF7T/8\nIeO+jYOgubhIqgRWsUot1bSbTbLlFeaOHmfq7jsYGKty1mXn44yMIws5MmkjsFFC4aaGRr0Fto3r\neDQ7K6zMzbF+/WaCuQXKE6NPUTK1ELQWj7LaiGnl+hkuhRhjmFrqsH7CJrGdp43ZZyxZEq1Radaz\nRMUZIT1/iCVcEmxazTYq620UF5oN/AyKdg4jE1yrZ/kySuF0MurNZaqTo4x4NTpZl9ZcnbO3n8FX\nv/IVan0FtmxaRz1cZXpmiv1P7OG2W79PrVKj07iPAkAbDh38Nhd5fZxIHCrLK+wql/l+VCcUKecs\nCfwgwbYkfcKiGmsyYZOaDGF6YDadCrQRhI6krG2eWFlm/Zk7iZqrpIUcVmiI3DzLs4vMzs5SNoZB\nY6GSkKKfZ0VpBqpDzCwuUTnjXKLZJ8jNL9MtxeRDBeU8+Z1bWLn7doRvY9b1oTxDFAe0ybh/yGd2\n/gT5pZDnbttO7blns27HGMt//Fn8xQ5OOUfJclhstWmVA1pBBztRBFKSWZJG6wSDW7awYcfzOfr4\nEwwkLvuPepzxrBh5N1xwccx3vtMrrUocjE7oBqtYlgEJntsTCbXbbWzRm4y0LKtXypU8JUOybUGc\narSVoynBLeXxhSENQ2T/CMtBl5yXBw3tWOEoSdReIZv5JiU/o1Yu4fQV0Y5FYjxmFldZbiVEiUVo\nFBvOmmR86w4+/+m/ZvvIZl74xmuxiw6ZsHFUysrULHsOHCUSNaRK8Up9fPWmB3jjC3aTHx162ph9\nxpLFIBBrI6iW7dK1NHg2cZwitIUrLIIkAqGZTxtMrBtlKYkZrhYwShN2NbZwaFkZnqnQmmoh7JSS\n7+Bphz233Idfi0AqFqamML7N+jPXMT4+yr59+3nFCwXDJ+fgTtDXQ/onozQX9rJlaBg/9Viu+AzO\nCyrawk0CbFsyahzyGLQNek2vZ5DITGO0xJYufRsmGWh3aJBwzoUX86Pvf4OFpQZmaYllnTIysZWi\nsJBZhCdtSrk8rSAidW2WrYTh85/N0PBWnnjsAfAkfpondmLSoM7cw4/gbOqjU/WIshgLi26nSVcr\nDrY0J4qS933u41xy3qWkpDz0yc/h9Q1gFiNkGCCkh2tplmbmKJYLpJ2IgVKFUBhUo8H0448Rjq4g\nleTI9Ay7HxiBq07ALXDJpRE33ZTvvXbaoLXqJYq2npp9f/jhR7BtB6Oyp2j7BvHUIaNlWSidgYAt\nO3ZRrOTZOFDlru9+E5FmNIfGcZKQzDiA04PkoWhGsBDlqAqNu9DFpo0jBUmq6Tg2890Y2y7Q7qzy\nojf/ItLro7MsiEZyaCxYkyoZJPNTxwhSGMlHnGp0aNUF4xOjpEHMYqP9tDH7jG3wVc9QhzKgPXsN\n0pYQqhRsTXUoj3QFCEllpMpqEDB/qsX+Q9PsvvwC6nFIq5vjil94HkGWEkcxUjn4iaHP1+w8dx3D\nI4MMFirkY4uyLDNamOD0LZNUcy7XXHw/vBX4GNx99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D5jyfLYocOorKevE1auVypMNUaD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\n2WXanrPs2Z5dpu05y57t2WXa/wVjO2xV5Ti03wAAAABJRU5ErkJggg==\n", + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "# randomly sample one ref\n", + "ref_ids = refer.getRefIds()\n", + "ref_id = ref_ids[np.random.randint(0, len(ref_ids))]\n", + "ref = refer.Refs[ref_id]\n", + "print 'ref_id [%s] (ann_id [%s])' % (ref_id, refer.refToAnn[ref_id]['id'])\n", + "# show the segmentation of the referred object\n", + "plt.figure()\n", + "refer.showRef(ref, seg_box='seg')\n", + "plt.show()" + ] + }, + { + "cell_type": "code", + "execution_count": 25, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "1. woman in front\n", + "2. lady smiling\n", + "3. woman\n" + ] + }, + { + "data": { + "image/png": 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J0okoJxNiDJRH3JrNeO/7nuXm7bsUd/boKMOH3nEZIWO2zuzSNA2maRgMRsxn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\nKSVlWVLXNU3bIoyhe0ZbaPARowzW2sUxLux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+ "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "# or show the bounding box of the referred object\n", + "refer.showRef(ref, seg_box='box')\n", + "plt.show()" + ] + }, + { + "cell_type": "code", + "execution_count": 26, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "sent_id[64727]: woman in front\n", + "sent_id[64728]: lady smiling\n", + "sent_id[64729]: woman\n" + ] + } + ], + "source": [ + "# let's look at the details of each ref\n", + "for sent in ref['sentences']:\n", + " print 'sent_id[%s]: %s' % (sent['sent_id'], sent['sent'])" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 2", + "language": "python", + "name": "python2" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 2 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython2", + "version": "2.7.6" + } + }, + "nbformat": 4, + "nbformat_minor": 0 +} diff --git a/LAVT-RIS/refer/refer.py b/LAVT-RIS/refer/refer.py new file mode 100644 index 0000000000000000000000000000000000000000..f83cf92dcb89a83601313a607a1404435cf12bde --- /dev/null +++ b/LAVT-RIS/refer/refer.py @@ -0,0 +1,386 @@ +""" +This interface provides access to four datasets: +1) refclef +2) refcoco +3) refcoco+ +4) refcocog +split by unc and google +The following API functions are defined: +REFER - REFER api class +getRefIds - get ref ids that satisfy given filter conditions. +getAnnIds - get ann ids that satisfy given filter conditions. +getImgIds - get image ids that satisfy given filter conditions. +getCatIds - get category ids that satisfy given filter conditions. +loadRefs - load refs with the specified ref ids. +loadAnns - load anns with the specified ann ids. +loadImgs - load images with the specified image ids. +loadCats - load category names with the specified category ids. +getRefBox - get ref's bounding box [x, y, w, h] given the ref_id +showRef - show image, segmentation or box of the referred object with the ref +getMask - get mask and area of the referred object given ref +showMask - show mask of the referred object given ref +""" + +import itertools +import json +import os.path as osp +import pickle +import sys +import time +from pprint import pprint + +import matplotlib.pyplot as plt +import numpy as np +import skimage.io as io +from matplotlib.collections import PatchCollection +from matplotlib.patches import Polygon, Rectangle +from pycocotools import mask + + + +class REFER: + def __init__(self, data_root='/data2/dataset/COCO2014/', dataset='refcoco', splitBy='unc'): + # provide data_root folder which contains refclef, refcoco, refcoco+ and refcocog + # also provide dataset name and splitBy information + # e.g., dataset = 'refcoco', splitBy = 'unc' + print('loading dataset %s into memory...' % dataset) + self.ROOT_DIR = osp.abspath(osp.dirname(__file__)) + self.DATA_DIR = osp.join('/data2/dataset/RefCOCO/', dataset) + if dataset in ['refcoco', 'refcoco+', 'refcocog']: + self.IMAGE_DIR = osp.join(data_root, 'trainval2014') + elif dataset == 'ref-zom' : + self.IMAGE_DIR = osp.join(data_root, 'trainval2014') + elif dataset == 'refclef': + self.IMAGE_DIR = osp.join(data_root, 'images/saiapr_tc-12') + else: + print('No refer dataset is called [%s]' % dataset) + sys.exit() + + # load refs from data/dataset/refs(dataset).json + tic = time.time() + ref_file = osp.join(self.DATA_DIR, 'refs(' + splitBy + ').p') + self.data = {} + self.data['dataset'] = dataset + + self.data['refs'] = pickle.load(open(ref_file, 'rb'), fix_imports=True) + + # load annotations from data/dataset/instances.json + instances_file = osp.join(self.DATA_DIR, 'instances.json') + instances = json.load(open(instances_file, 'r')) + self.data['images'] = instances['images'] + self.data['annotations'] = instances['annotations'] + self.data['categories'] = instances['categories'] + + # create index + self.createIndex() + print('DONE (t=%.2fs)' % (time.time() - tic)) + + def createIndex(self): + # create sets of mapping + # 1) Refs: {ref_id: ref} + # 2) Anns: {ann_id: ann} + # 3) Imgs: {image_id: image} + # 4) Cats: {category_id: category_name} + # 5) Sents: {sent_id: sent} + # 6) imgToRefs: {image_id: refs} + # 7) imgToAnns: {image_id: anns} + # 8) refToAnn: {ref_id: ann} + # 9) annToRef: {ann_id: ref} + # 10) catToRefs: {category_id: refs} + # 11) sentToRef: {sent_id: ref} + # 12) sentToTokens: {sent_id: tokens} + print('creating index...') + # fetch info from instances + Anns, Imgs, Cats, imgToAnns = {}, {}, {}, {} + for ann in self.data['annotations']: + Anns[ann['id']] = ann + imgToAnns[ann['image_id']] = imgToAnns.get(ann['image_id'], + []) + [ann] + for img in self.data['images']: + Imgs[img['id']] = img + for cat in self.data['categories']: + Cats[cat['id']] = cat['name'] + + # fetch info from refs + Refs, imgToRefs, refToAnn, annToRef, catToRefs = {}, {}, {}, {}, {} + Sents, sentToRef, sentToTokens = {}, {}, {} + for ref in self.data['refs']: + # ids + ref_id = ref['ref_id'] + ann_id = ref['ann_id'] + category_id = ref['category_id'] + image_id = ref['image_id'] + + # add mapping related to ref + Refs[ref_id] = ref + imgToRefs[image_id] = imgToRefs.get(image_id, []) + [ref] + catToRefs[category_id] = catToRefs.get(category_id, []) + [ref] + refToAnn[ref_id] = Anns[ann_id] + annToRef[ann_id] = ref + + # add mapping of sent + for sent in ref['sentences']: + Sents[sent['sent_id']] = sent + sentToRef[sent['sent_id']] = ref + sentToTokens[sent['sent_id']] = sent['tokens'] + + # create class members + self.Refs = Refs + self.Anns = Anns + self.Imgs = Imgs + self.Cats = Cats + self.Sents = Sents + self.imgToRefs = imgToRefs + self.imgToAnns = imgToAnns + self.refToAnn = refToAnn + self.annToRef = annToRef + self.catToRefs = catToRefs + self.sentToRef = sentToRef + self.sentToTokens = sentToTokens + print('index created.') + + def getRefIds(self, image_ids=[], cat_ids=[], ref_ids=[], split=''): + image_ids = image_ids if type(image_ids) == list else [image_ids] + cat_ids = cat_ids if type(cat_ids) == list else [cat_ids] + ref_ids = ref_ids if type(ref_ids) == list else [ref_ids] + + if len(image_ids) == len(cat_ids) == len(ref_ids) == len(split) == 0: + refs = self.data['refs'] + else: + if not len(image_ids) == 0: + refs = [self.imgToRefs[image_id] for image_id in image_ids] + else: + refs = self.data['refs'] + if not len(cat_ids) == 0: + refs = [ref for ref in refs if ref['category_id'] in cat_ids] + if not len(ref_ids) == 0: + refs = [ref for ref in refs if ref['ref_id'] in ref_ids] + if not len(split) == 0: + if split in ['testA', 'testB', 'testC']: + refs = [ref for ref in refs if split[-1] in ref['split'] + ] # we also consider testAB, testBC, ... + elif split in ['testAB', 'testBC', 'testAC']: + refs = [ref for ref in refs + if ref['split'] == split] # rarely used I guess... + elif split == 'test': + refs = [ref for ref in refs if 'test' in ref['split']] + elif split == 'train' or split == 'val': + refs = [ref for ref in refs if ref['split'] == split] + else: + print('No such split [%s]' % split) + sys.exit() + ref_ids = [ref['ref_id'] for ref in refs] + return ref_ids + + def getAnnIds(self, image_ids=[], cat_ids=[], ref_ids=[]): + image_ids = image_ids if type(image_ids) == list else [image_ids] + cat_ids = cat_ids if type(cat_ids) == list else [cat_ids] + ref_ids = ref_ids if type(ref_ids) == list else [ref_ids] + + if len(image_ids) == len(cat_ids) == len(ref_ids) == 0: + ann_ids = [ann['id'] for ann in self.data['annotations']] + else: + if not len(image_ids) == 0: + lists = [ + self.imgToAnns[image_id] for image_id in image_ids + if image_id in self.imgToAnns + ] # list of [anns] + anns = list(itertools.chain.from_iterable(lists)) + else: + anns = self.data['annotations'] + if not len(cat_ids) == 0: + anns = [ann for ann in anns if ann['category_id'] in cat_ids] + ann_ids = [ann['id'] for ann in anns] + if not len(ref_ids) == 0: + ids = set(ann_ids).intersection( + set([self.Refs[ref_id]['ann_id'] for ref_id in ref_ids])) + return ann_ids + + def getImgIds(self, ref_ids=[]): + ref_ids = ref_ids if type(ref_ids) == list else [ref_ids] + + if not len(ref_ids) == 0: + image_ids = list( + set([self.Refs[ref_id]['image_id'] for ref_id in ref_ids])) + else: + image_ids = self.Imgs.keys() + return image_ids + + def getCatIds(self): + return self.Cats.keys() + + def loadRefs(self, ref_ids=[]): + if type(ref_ids) == list: + return [self.Refs[ref_id] for ref_id in ref_ids] + elif type(ref_ids) == int: + return [self.Refs[ref_ids]] + + def loadAnns(self, ann_ids=[]): + if type(ann_ids) == list: + return [self.Anns[ann_id] for ann_id in ann_ids] + elif type(ann_ids) == int or type(ann_ids) == unicode: + return [self.Anns[ann_ids]] + + def loadImgs(self, image_ids=[]): + if type(image_ids) == list: + return [self.Imgs[image_id] for image_id in image_ids] + elif type(image_ids) == int: + return [self.Imgs[image_ids]] + + def loadCats(self, cat_ids=[]): + if type(cat_ids) == list: + return [self.Cats[cat_id] for cat_id in cat_ids] + elif type(cat_ids) == int: + return [self.Cats[cat_ids]] + + def getRefBox(self, ref_id): + ref = self.Refs[ref_id] + ann = self.refToAnn[ref_id] + return ann['bbox'] # [x, y, w, h] + + def showRef(self, ref, seg_box='seg'): + ax = plt.gca() + + image = self.Imgs[ref['image_id']] + I = io.imread(osp.join(self.IMAGE_DIR, image['file_name'])) + ax.imshow(I) + + for sid, sent in enumerate(ref['sentences']): + print('%s. %s' % (sid + 1, sent['sent'])) + + if seg_box == 'seg': + ann_id = ref['ann_id'] + ann = self.Anns[ann_id] + polygons = [] + color = [] + c = (np.random.random((1, 3)) * 0.6 + 0.4).tolist()[0] + + if type(ann['segmentation'][0]) == list: + # polygon used for refcoco* + for seg in ann['segmentation']: + poly = np.array(seg).reshape((int(len(seg) / 2), 2)) + polygons.append(Polygon(poly)) + color.append(c) + + p = PatchCollection(polygons, + facecolors=(221/255, 160/255, 221/255), # ¿¬º¸¶ó»ö + linewidths=0, + alpha=0.4) + ax.add_collection(p) + + p = PatchCollection(polygons, + facecolors='none', + edgecolors=color, + linewidths=2) + ax.add_collection(p) + else: + # mask used for refclef + rle = ann['segmentation'] + m = mask.decode(rle) + img = np.ones((m.shape[0], m.shape[1], 3)) + color_mask = np.array([2.0, 166.0, 101.0]) / 255 + for i in range(3): + img[:, :, i] = color_mask[i] + ax.imshow(np.dstack((img, m * 0.5))) + + # bounding box + elif seg_box == 'box': + ann_id = ref['ann_id'] + ann = self.Anns[ann_id] + bbox = self.getRefBox(ref['ref_id']) + box_plot = Rectangle((bbox[0], bbox[1]), + bbox[2], + bbox[3], + fill=False, + edgecolor='green', + linewidth=3) + ax.add_patch(box_plot) + + def getMask(self, ref): + # return mask, area and mask-center + ann = self.refToAnn[ref['ref_id']] + image = self.Imgs[ref['image_id']] + if type(ann['segmentation'][0]) == list: # polygon + rle = mask.frPyObjects(ann['segmentation'], image['height'], + image['width']) + else: + rle = ann['segmentation'] + + # for i in range(len(rle['counts'])): + # print(rle) + m = mask.decode(rle) + m = np.sum( + m, axis=2 + ) # sometimes there are multiple binary map (corresponding to multiple segs) + m = m.astype(np.uint8) # convert to np.uint8 + # compute area + area = sum(mask.area(rle)) # should be close to ann['area'] + return {'mask': m, 'area': area} + # # position + # position_x = np.mean(np.where(m==1)[1]) # [1] means columns (matlab style) -> x (c style) + # position_y = np.mean(np.where(m==1)[0]) # [0] means rows (matlab style) -> y (c style) + # # mass position (if there were multiple regions, we use the largest one.) + # label_m = label(m, connectivity=m.ndim) + # regions = regionprops(label_m) + # if len(regions) > 0: + # largest_id = np.argmax(np.array([props.filled_area for props in regions])) + # largest_props = regions[largest_id] + # mass_y, mass_x = largest_props.centroid + # else: + # mass_x, mass_y = position_x, position_y + # # if centroid is not in mask, we find the closest point to it from mask + # if m[mass_y, mass_x] != 1: + # print 'Finding closes mask point ...' + # kernel = np.ones((10, 10),np.uint8) + # me = cv2.erode(m, kernel, iterations = 1) + # points = zip(np.where(me == 1)[0].tolist(), np.where(me == 1)[1].tolist()) # row, col style + # points = np.array(points) + # dist = np.sum((points - (mass_y, mass_x))**2, axis=1) + # id = np.argsort(dist)[0] + # mass_y, mass_x = points[id] + # # return + # return {'mask': m, 'area': area, 'position_x': position_x, 'position_y': position_y, 'mass_x': mass_x, 'mass_y': mass_y} + # # show image and mask + # I = io.imread(osp.join(self.IMAGE_DIR, image['file_name'])) + # plt.figure() + # plt.imshow(I) + # ax = plt.gca() + # img = np.ones( (m.shape[0], m.shape[1], 3) ) + # color_mask = np.array([2.0,166.0,101.0])/255 + # for i in range(3): + # img[:,:,i] = color_mask[i] + # ax.imshow(np.dstack( (img, m*0.5) )) + # plt.show() + + def showMask(self, ref): + M = self.getMask(ref) + msk = M['mask'] + ax = plt.gca() + ax.imshow(msk) + + +if __name__ == '__main__': + refer = REFER(dataset='refcocog', splitBy='google') + ref_ids = refer.getRefIds() + print(len(ref_ids)) + + print(len(refer.Imgs)) + print(len(refer.imgToRefs)) + + ref_ids = refer.getRefIds(split='train') + print('There are %s training referred objects.' % len(ref_ids)) + + for ref_id in ref_ids: + ref = refer.loadRefs(ref_id)[0] + if len(ref['sentences']) < 2: + continue + + pprint(ref) + print('The label is %s.' % refer.Cats[ref['category_id']]) + plt.figure() + refer.showRef(ref, seg_box='box') + plt.show() + + # plt.figure() + # refer.showMask(ref) + # plt.show() diff --git a/LAVT-RIS/refer/refer_test.py b/LAVT-RIS/refer/refer_test.py new file mode 100644 index 0000000000000000000000000000000000000000..6b62bb6cc6074da9c9536c7fccda65c9b6df0583 --- /dev/null +++ b/LAVT-RIS/refer/refer_test.py @@ -0,0 +1,381 @@ +""" +This interface provides access to four datasets: +1) refclef +2) refcoco +3) refcoco+ +4) refcocog +split by unc and google + +The following API functions are defined: +REFER - REFER api class +getRefIds - get ref ids that satisfy given filter conditions. +getAnnIds - get ann ids that satisfy given filter conditions. +getImgIds - get image ids that satisfy given filter conditions. +getCatIds - get category ids that satisfy given filter conditions. +loadRefs - load refs with the specified ref ids. +loadAnns - load anns with the specified ann ids. +loadImgs - load images with the specified image ids. +loadCats - load category names with the specified category ids. +getRefBox - get ref's bounding box [x, y, w, h] given the ref_id +showRef - show image, segmentation or box of the referred object with the ref +getMask - get mask and area of the referred object given ref +showMask - show mask of the referred object given ref +""" +import os +import sys +import os.path as osp +import json +import pickle as pickle +import time +import itertools +import skimage.io as io +import matplotlib.pyplot as plt +from matplotlib.collections import PatchCollection +from matplotlib.patches import Polygon, Rectangle +from pprint import pprint +import numpy as np +from pycocotools import mask + +def read_idx(fname): + integer_list = [] + + with open(fname, 'r') as file: + for line in file: + try: + integer = int(line.strip()) + integer_list.append(integer) + except ValueError: + print(f"Skipping non-integer line: {line.strip()}") + + return list(set(integer_list)) + + + +class REFER: + + def __init__(self, data_root, dataset='refcoco', splitBy='unc'): + # provide data_root folder which contains refclef, refcoco, refcoco+ and refcocog + # also provide dataset name and splitBy information + # e.g., dataset = 'refcoco', splitBy = 'unc' + print('loading dataset %s into memory...' % dataset) + if dataset == 'refcocog': + print('Split by {}!'.format(splitBy)) + self.ROOT_DIR = osp.abspath(osp.dirname(__file__)) + self.DATA_DIR = osp.join(data_root, dataset) + if dataset in ['refcoco', 'refcoco+', 'refcocog', 'grefcoco']: + self.IMAGE_DIR = osp.join(data_root, 'images/train2014') + elif dataset == 'refclef': + self.IMAGE_DIR = osp.join(data_root, 'images/saiapr_tc-12') + else: + print('No refer dataset is called [%s]' % dataset) + sys.exit() + + # load refs from data/dataset/refs(dataset).json + tic = time.time() + ref_file = osp.join(self.DATA_DIR, 'refs(' + splitBy + ').p') + if dataset == "grefcoco": + ref_file = osp.join(self.DATA_DIR, 'grefs(unc).json') + self.data = {} + self.data['dataset'] = dataset + f = open(ref_file, 'r') + self.data['refs'] = pickle.load(open(ref_file, 'rb')) + + # load annotations from data/dataset/instances.json + instances_file = osp.join(self.DATA_DIR, 'instances.json') + instances = json.load(open(instances_file, 'r')) + self.data['images'] = instances['images'] + self.data['annotations'] = instances['annotations'] + self.data['categories'] = instances['categories'] + + + # make testA for easy, testB for hard example + easy_ids = read_idx('/data2/projects/donghwa/RIS/LAVT-RIS/refer/refcocog_easy_idx.txt') + hard_ids = read_idx('/data2/projects/donghwa/RIS/LAVT-RIS/refer/refcocog_hard_idx.txt') + + for easy_id in easy_ids: + self.data['refs'][easy_id]['split'] = 'testA' + for hard_id in hard_ids: + self.data['refs'][hard_id]['split'] = 'testB' + + + # create index + self.createIndex() + print('DONE (t=%.2fs)' % (time.time() - tic)) + + def createIndex(self): + # create sets of mapping + # 1) Refs: {ref_id: ref} + # 2) Anns: {ann_id: ann} + # 3) Imgs: {image_id: image} + # 4) Cats: {category_id: category_name} + # 5) Sents: {sent_id: sent} + # 6) imgToRefs: {image_id: refs} + # 7) imgToAnns: {image_id: anns} + # 8) refToAnn: {ref_id: ann} + # 9) annToRef: {ann_id: ref} + # 10) catToRefs: {category_id: refs} + # 11) sentToRef: {sent_id: ref} + # 12) sentToTokens: {sent_id: tokens} + + # 13) sentToObject : {sent_id: object} + # 14) sentToContext : {sent_id: Context} + print('creating index...') + # fetch info from instances + Anns, Imgs, Cats, imgToAnns = {}, {}, {}, {} + for ann in self.data['annotations']: + Anns[ann['id']] = ann + imgToAnns[ann['image_id']] = imgToAnns.get(ann['image_id'], []) + [ann] + for img in self.data['images']: + Imgs[img['id']] = img + for cat in self.data['categories']: + Cats[cat['id']] = cat['name'] + + # fetch info from refs + Refs, imgToRefs, refToAnn, annToRef, catToRefs = {}, {}, {}, {}, {} + Sents, sentToRef, sentToTokens = {}, {}, {} + + + sentToObject, sentToContext = {}, {} + pre_prompt = "what is main object of the given sentence? just briefly answer only 1~2 words" + for idx, ref in enumerate(self.data['refs']): + # ids + ref_id = ref['ref_id'] + ann_id = ref['ann_id'] + category_id = ref['category_id'] + image_id = ref['image_id'] + assert idx == ref_id + # add mapping related to ref + Refs[ref_id] = ref + imgToRefs[image_id] = imgToRefs.get(image_id, []) + [ref] + catToRefs[category_id] = catToRefs.get(category_id, []) + [ref] + refToAnn[ref_id] = Anns[ann_id] + annToRef[ann_id] = ref + + # add mapping of sent + for sent in ref['sentences']: + Sents[sent['sent_id']] = sent + sentToRef[sent['sent_id']] = ref + sentToTokens[sent['sent_id']] = sent['tokens'] + + # create class members + self.Refs = Refs + self.Anns = Anns + self.Imgs = Imgs + self.Cats = Cats + self.Sents = Sents + self.imgToRefs = imgToRefs + self.imgToAnns = imgToAnns + self.refToAnn = refToAnn + self.annToRef = annToRef + self.catToRefs = catToRefs + self.sentToRef = sentToRef + self.sentToTokens = sentToTokens + print('index created.') + + def getRefIds(self, image_ids=[], cat_ids=[], ref_ids=[], split=''): + image_ids = image_ids if type(image_ids) == list else [image_ids] + cat_ids = cat_ids if type(cat_ids) == list else [cat_ids] + ref_ids = ref_ids if type(ref_ids) == list else [ref_ids] + + if len(image_ids) == len(cat_ids) == len(ref_ids) == len(split) == 0: + refs = self.data['refs'] + else: + if not len(image_ids) == 0: + refs = [self.imgToRefs[image_id] for image_id in image_ids] + else: + refs = self.data['refs'] + if not len(cat_ids) == 0: + refs = [ref for ref in refs if ref['category_id'] in cat_ids] + if not len(ref_ids) == 0: + refs = [ref for ref in refs if ref['ref_id'] in ref_ids] + if not len(split) == 0: + if split in ['testA', 'testB', 'testC']: + refs = [ref for ref in refs if split[-1] in ref['split']] # we also consider testAB, testBC, ... + elif split in ['testAB', 'testBC', 'testAC']: + refs = [ref for ref in refs if ref['split'] == split] # rarely used I guess... + elif split == 'test': + refs = [ref for ref in refs if 'test' in ref['split']] + elif split == 'train' or split == 'val': + refs = [ref for ref in refs if ref['split'] == split] + else: + print('No such split [%s]' % split) + sys.exit() + ref_ids = [ref['ref_id'] for ref in refs] + return ref_ids + + def getAnnIds(self, image_ids=[], cat_ids=[], ref_ids=[]): + image_ids = image_ids if type(image_ids) == list else [image_ids] + cat_ids = cat_ids if type(cat_ids) == list else [cat_ids] + ref_ids = ref_ids if type(ref_ids) == list else [ref_ids] + + if len(image_ids) == len(cat_ids) == len(ref_ids) == 0: + ann_ids = [ann['id'] for ann in self.data['annotations']] + else: + if not len(image_ids) == 0: + lists = [self.imgToAnns[image_id] for image_id in image_ids if + image_id in self.imgToAnns] # list of [anns] + anns = list(itertools.chain.from_iterable(lists)) + else: + anns = self.data['annotations'] + if not len(cat_ids) == 0: + anns = [ann for ann in anns if ann['category_id'] in cat_ids] + ann_ids = [ann['id'] for ann in anns] + if not len(ref_ids) == 0: + ids = set(ann_ids).intersection(set([self.Refs[ref_id]['ann_id'] for ref_id in ref_ids])) + return ann_ids + + def getImgIds(self, ref_ids=[]): + ref_ids = ref_ids if type(ref_ids) == list else [ref_ids] + + if not len(ref_ids) == 0: + image_ids = list(set([self.Refs[ref_id]['image_id'] for ref_id in ref_ids])) + else: + image_ids = self.Imgs.keys() + return image_ids + + def getCatIds(self): + return self.Cats.keys() + + def loadRefs(self, ref_ids=[]): + if type(ref_ids) == list: + return [self.Refs[ref_id] for ref_id in ref_ids] + elif type(ref_ids) == int: + return [self.Refs[ref_ids]] + + def loadAnns(self, ann_ids=[]): + if type(ann_ids) == list: + return [self.Anns[ann_id] for ann_id in ann_ids] + elif type(ann_ids) == int or type(ann_ids) == unicode: + return [self.Anns[ann_ids]] + + def loadImgs(self, image_ids=[]): + if type(image_ids) == list: + return [self.Imgs[image_id] for image_id in image_ids] + elif type(image_ids) == int: + return [self.Imgs[image_ids]] + + def loadCats(self, cat_ids=[]): + if type(cat_ids) == list: + return [self.Cats[cat_id] for cat_id in cat_ids] + elif type(cat_ids) == int: + return [self.Cats[cat_ids]] + + def getRefBox(self, ref_id): + ref = self.Refs[ref_id] + ann = self.refToAnn[ref_id] + return ann['bbox'] # [x, y, w, h] + + def showRef(self, ref, seg_box='seg'): + ax = plt.gca() + # show image + image = self.Imgs[ref['image_id']] + I = io.imread(osp.join(self.IMAGE_DIR, image['file_name'])) + ax.imshow(I) + # show refer expression + for sid, sent in enumerate(ref['sentences']): + print('%s. %s' % (sid + 1, sent['sent'])) + # show segmentations + if seg_box == 'seg': + ann_id = ref['ann_id'] + ann = self.Anns[ann_id] + polygons = [] + color = [] + c = 'none' + if type(ann['segmentation'][0]) == list: + # polygon used for refcoco* + for seg in ann['segmentation']: + poly = np.array(seg).reshape((len(seg) / 2, 2)) + polygons.append(Polygon(poly, True, alpha=0.4)) + color.append(c) + p = PatchCollection(polygons, facecolors=color, edgecolors=(1, 1, 0, 0), linewidths=3, alpha=1) + ax.add_collection(p) # thick yellow polygon + p = PatchCollection(polygons, facecolors=color, edgecolors=(1, 0, 0, 0), linewidths=1, alpha=1) + ax.add_collection(p) # thin red polygon + else: + # mask used for refclef + rle = ann['segmentation'] + m = mask.decode(rle) + img = np.ones((m.shape[0], m.shape[1], 3)) + color_mask = np.array([2.0, 166.0, 101.0]) / 255 + for i in range(3): + img[:, :, i] = color_mask[i] + ax.imshow(np.dstack((img, m * 0.5))) + # show bounding-box + elif seg_box == 'box': + ann_id = ref['ann_id'] + ann = self.Anns[ann_id] + bbox = self.getRefBox(ref['ref_id']) + box_plot = Rectangle((bbox[0], bbox[1]), bbox[2], bbox[3], fill=False, edgecolor='green', linewidth=3) + ax.add_patch(box_plot) + + def getMask(self, ref): + # return mask, area and mask-center + ann = self.refToAnn[ref['ref_id']] + image = self.Imgs[ref['image_id']] + + if type(ann['segmentation'][0]) == list: # polygon + rle = mask.frPyObjects(ann['segmentation'], image['height'], image['width']) + else: + rle = ann['segmentation'] + + m = mask.decode(rle) + m = np.sum(m, axis=2) # sometimes there are multiple binary map (corresponding to multiple segs) + m = m.astype(np.uint8) # convert to np.uint8 + # compute area + area = sum(mask.area(rle)) # should be close to ann['area'] + return {'mask': m, 'area': area} + + + def showMask(self, ref): + M = self.getMask(ref) + msk = M['mask'] + ax = plt.gca() + ax.imshow(msk) + + +if __name__ == '__main__': + refer = REFER(data_root='/data2/projects/donghwa/RIS/LAVT-RIS/refer/data', dataset='refcocog', splitBy='umd') + # ref_ids = refer.getRefIds() + + ref_ids = refer.getRefIds(split='testA') + import pudb; pudb.set_trace() + # print('There are %s training referred objects.' % len(ref_ids)) + + # for ref_id in ref_ids: + # ref = refer.loadRefs(ref_id)[0] + # if len(ref['sentences']) < 2: + # continue + # print('The label is %s.' % refer.Cats[ref['category_id']]) + # plt.figure() + # refer.showRef(ref, seg_box='box') + # plt.show() + # import pudb; pudb.set_trace() + + """make test samples""" + # ref_ids = refer.getRefIds(split='testA') + # ids = np.random.choice(1000, 50) + # f = open("refcoco+_testA.txt", "w") + # lines = [] + # Refs = refer.Refs + # for id in ids : + # ref_id = ref_ids[id] + # ref = Refs[ref_id] + # file_name = ref['file_name'] + # if len(ref['sentences']) > 1 : + # for item in ref['sentences']: + # sent = item['raw'] + # aline = [file_name, sent, ref_id] + # f.write(f"{aline}\n") + # else : + # sent = ref['sentences'][0]['raw'] + # aline = [file_name, sent, ref_id] + # # lines.append(aline) + # f.write(f"{aline}\n") + + # f.close() + + + + + + diff --git a/LAVT-RIS/refer/refer_zom.py b/LAVT-RIS/refer/refer_zom.py new file mode 100644 index 0000000000000000000000000000000000000000..1676e682adbe9885c93dca1ae0db628b96163f98 --- /dev/null +++ b/LAVT-RIS/refer/refer_zom.py @@ -0,0 +1,351 @@ +""" +This interface provides access to four datasets: +1) refclef +2) refcoco +3) refcoco+ +4) refcocog +split by unc and google + +The following API functions are defined: +REFER - REFER api class +getRefIds - get ref ids that satisfy given filter conditions. +getAnnIds - get ann ids that satisfy given filter conditions. +getImgIds - get image ids that satisfy given filter conditions. +getCatIds - get category ids that satisfy given filter conditions. +loadRefs - load refs with the specified ref ids. +loadAnns - load anns with the specified ann ids. +loadImgs - load images with the specified image ids. +loadCats - load category names with the specified category ids. +getRefBox - get ref's bounding box [x, y, w, h] given the ref_id +showRef - show image, segmentation or box of the referred object with the ref +getMask - get mask and area of the referred object given ref +showMask - show mask of the referred object given ref +""" + +import sys +import os.path as osp +import json +import pickle as pickle +import time +import itertools +import skimage.io as io +import matplotlib.pyplot as plt +from matplotlib.collections import PatchCollection +from matplotlib.patches import Polygon, Rectangle +from pprint import pprint +import numpy as np +from pycocotools import mask + + +class ZREFER: + def __init__(self, data_root='/data2/dataset/COCO2014/', dataset='refcoco', splitBy='unc'): + # provide data_root folder which contains refclef, refcoco, refcoco+ and refcocog + # also provide dataset name and splitBy information + # e.g., dataset = 'refcoco', splitBy = 'unc' + print('loading dataset %s into memory...' % dataset) + print(f'loading dataset split {splitBy}') + self.ROOT_DIR = osp.abspath(osp.dirname(__file__)) + self.DATA_DIR = osp.join('/data2/dataset/RefCOCO/', dataset) + if dataset in ['refcoco', 'refcoco+', 'refcocog']: + self.IMAGE_DIR = osp.join(data_root, 'trainval2014') + elif dataset == 'ref-zom' : + self.IMAGE_DIR = osp.join(data_root, 'trainval2014') + elif dataset == 'refclef': + self.IMAGE_DIR = osp.join(data_root, 'images/saiapr_tc-12') + else: + print('No refer dataset is called [%s]' % dataset) + sys.exit() + # load refs from data/dataset/refs(dataset).json + tic = time.time() + ref_file = osp.join(self.DATA_DIR, 'refs(' + splitBy + ').p') + self.data = {} + self.data['dataset'] = dataset + f = open(ref_file, 'r') + self.data['refs'] = pickle.load(open(ref_file, 'rb')) + + # load annotations from data/dataset/instances.json + instances_file = osp.join(self.DATA_DIR, 'instances.json') + instances = json.load(open(instances_file, 'r')) + + self.data['images'] = instances['images'] + self.data['annotations'] = instances['annotations'] + self.data['categories'] = instances['categories'] + + # create index + self.createIndex() + print('DONE (t=%.2fs)' % (time.time() - tic)) + + def createIndex(self): + # create sets of mapping + # 1) Refs: {ref_id: ref} + # 2) Anns: {ann_id: ann} + # 3) Imgs: {image_id: image} + # 4) Cats: {category_id: category_name} + # 5) Sents: {sent_id: sent} + # 6) imgToRefs: {image_id: refs} + # 7) imgToAnns: {image_id: anns} + # 8) refToAnn: {ref_id: ann} + # 9) annToRef: {ann_id: ref} + # 10) catToRefs: {category_id: refs} + # 11) sentToRef: {sent_id: ref} + # 12) sentToTokens: {sent_id: tokens} + print('creating index...') + # fetch info from instances + Anns, Imgs, Cats, imgToAnns = {}, {}, {}, {} + for ann in self.data['annotations']: + Anns[ann['id']] = ann + imgToAnns[ann['image_id']] = imgToAnns.get(ann['image_id'], []) + [ann] + + for img in self.data['images']: + Imgs[img['id']] = img + for cat in self.data['categories']: + Cats[cat['id']] = cat['name'] + + # fetch info from refs + Refs, imgToRefs, refToAnn, annToRef, catToRefs = {}, {}, {}, {}, {} + Sents, sentToRef, sentToTokens = {}, {}, {} + for ref in self.data['refs']: + # ids + ref_id = ref['ref_id'] + ann_ids = ref['ann_id'] + image_id = ref['image_id'] + + # add mapping related to ref + Refs[ref_id] = ref + imgToRefs[image_id] = imgToRefs.get(image_id, []) + [ref_id] + + try: + if isinstance(ann_ids,list): + refToAnn[ref_id] = [Anns[ann_id] for ann_id in ann_ids] + else: + refToAnn[ref_id] = [Anns[ann_ids]] + except: + import pdb + pdb.set_trace() + # add mapping of sent + for sent in ref['sentences']: + Sents[sent['sent_id']] = sent + sentToRef[sent['sent_id']] = ref + sentToTokens[sent['sent_id']] = sent['tokens'] + + # create class members + self.Refs = Refs + self.Anns = Anns + self.Imgs = Imgs + self.Cats = Cats + self.Sents = Sents + self.imgToRefs = imgToRefs + self.imgToAnns = imgToAnns + self.refToAnn = refToAnn + # self.annToRef = annToRef + self.catToRefs = catToRefs + self.sentToRef = sentToRef + self.sentToTokens = sentToTokens + print('index created.') + + def getRefIds(self, image_ids=[], cat_ids=[], ref_ids=[], split=''): + image_ids = image_ids if type(image_ids) == list else [image_ids] + cat_ids = cat_ids if type(cat_ids) == list else [cat_ids] + ref_ids = ref_ids if type(ref_ids) == list else [ref_ids] + + if len(image_ids) == len(cat_ids) == len(ref_ids) == len(split) == 0: + refs = self.data['refs'] + else: + if not len(image_ids) == 0: + refs = [self.imgToRefs[image_id] for image_id in image_ids] + else: + refs = self.data['refs'] + if not len(cat_ids) == 0: + refs = [ref for ref in refs if ref['category_id'] in cat_ids] + if not len(ref_ids) == 0: + refs = [ref for ref in refs if ref['ref_id'] in ref_ids] + if not len(split) == 0: + if split in ['testA', 'testB', 'testC']: + refs = [ref for ref in refs if split[-1] in ref['split']] # we also consider testAB, testBC, ... + elif split in ['testAB', 'testBC', 'testAC']: + refs = [ref for ref in refs if ref['split'] == split] # rarely used I guess... + elif split == 'test': + refs = [ref for ref in refs if 'test' in ref['split']] + elif split == 'train' or split == 'val': + refs = [ref for ref in refs if ref['split'] == split] + else: + print('No such split [%s]' % split) + sys.exit() + ref_ids = [ref['ref_id'] for ref in refs] + return ref_ids + + def getAnnIds(self, image_ids=[], cat_ids=[], ref_ids=[]): + image_ids = image_ids if type(image_ids) == list else [image_ids] + cat_ids = cat_ids if type(cat_ids) == list else [cat_ids] + ref_ids = ref_ids if type(ref_ids) == list else [ref_ids] + + if len(image_ids) == len(cat_ids) == len(ref_ids) == 0: + ann_ids = [ann['id'] for ann in self.data['annotations']] + else: + if not len(image_ids) == 0: + lists = [self.imgToAnns[image_id] for image_id in image_ids if + image_id in self.imgToAnns] # list of [anns] + anns = list(itertools.chain.from_iterable(lists)) + else: + anns = self.data['annotations'] + if not len(cat_ids) == 0: + anns = [ann for ann in anns if ann['category_id'] in cat_ids] + ann_ids = [ann['id'] for ann in anns] + if not len(ref_ids) == 0: + ids = set(ann_ids).intersection(set([self.Refs[ref_id]['ann_id'] for ref_id in ref_ids])) + return ann_ids + + def getImgIds(self, ref_ids=[]): + ref_ids = ref_ids if type(ref_ids) == list else [ref_ids] + + if not len(ref_ids) == 0: + image_ids = list(set([self.Refs[ref_id]['image_id'] for ref_id in ref_ids])) + else: + image_ids = self.Imgs.keys() + return image_ids + + def getCatIds(self): + return self.Cats.keys() + + def loadRefs(self, ref_ids=[]): + if type(ref_ids) == list: + return [self.Refs[ref_id] for ref_id in ref_ids] + elif type(ref_ids) == int: + return [self.Refs[ref_ids]] + + def loadAnns(self, ann_ids=[]): + if type(ann_ids) == list: + return [self.Anns[ann_id] for ann_id in ann_ids] + elif type(ann_ids) == int or type(ann_ids) == unicode: + return [self.Anns[ann_ids]] + + def loadImgs(self, image_ids=[]): + if type(image_ids) == list: + return [self.Imgs[image_id] for image_id in image_ids] + elif type(image_ids) == int: + return [self.Imgs[image_ids]] + + def loadCats(self, cat_ids=[]): + if type(cat_ids) == list: + return [self.Cats[cat_id] for cat_id in cat_ids] + elif type(cat_ids) == int: + return [self.Cats[cat_ids]] + + def getRefBox(self, ref_id): + ref = self.Refs[ref_id] + ann = self.refToAnn[ref_id] + return ann['bbox'] # [x, y, w, h] + + def showRef(self, ref, seg_box='seg'): + ax = plt.gca() + + image = self.Imgs[ref['image_id']] + I = io.imread(osp.join(self.IMAGE_DIR, image['file_name'])) + ax.imshow(I) + + for sid, sent in enumerate(ref['sentences']): + print('%s. %s' % (sid + 1, sent['sent'])) + + if seg_box == 'seg': + ann_id = ref['ann_id'] + ann = self.Anns[ann_id] + polygons = [] + color = [] + c = (np.random.random((1, 3)) * 0.6 + 0.4).tolist()[0] + + if type(ann['segmentation'][0]) == list: + # polygon used for refcoco* + for seg in ann['segmentation']: + poly = np.array(seg).reshape((int(len(seg) / 2), 2)) + polygons.append(Polygon(poly)) + color.append(c) + + p = PatchCollection(polygons, + facecolors=(221/255, 160/255, 221/255), # ¿¬º¸¶ó»ö + linewidths=0, + alpha=0.4) + ax.add_collection(p) + + p = PatchCollection(polygons, + facecolors='none', + edgecolors=color, + linewidths=2) + ax.add_collection(p) + else: + # mask used for refclef + rle = ann['segmentation'] + m = mask.decode(rle) + img = np.ones((m.shape[0], m.shape[1], 3)) + color_mask = np.array([2.0, 166.0, 101.0]) / 255 + for i in range(3): + img[:, :, i] = color_mask[i] + ax.imshow(np.dstack((img, m * 0.5))) + + # bounding box + elif seg_box == 'box': + ann_id = ref['ann_id'] + ann = self.Anns[ann_id] + bbox = self.getRefBox(ref['ref_id']) + box_plot = Rectangle((bbox[0], bbox[1]), + bbox[2], + bbox[3], + fill=False, + edgecolor='green', + linewidth=3) + ax.add_patch(box_plot) + + def getMask(self, ref): + # return mask, area and mask-center + + anns = self.refToAnn[ref['ref_id']] + image = self.Imgs[ref['image_id']] + try: + source_type = ref['source'] + except: + source_type='one' + + if source_type!='zero': + all_mask = [] + for ann in anns: + if type(ann['segmentation'][0]) == list: # polygon + rle = mask.frPyObjects(ann['segmentation'], image['height'], image['width']) + else: + rle = ann['segmentation'] + m = mask.decode(rle) + m = np.sum(m, axis=2) # sometimes there are multiple binary map (corresponding to multiple segs) + m = m.astype(np.uint8) # convert to np.uint8 + all_mask.append(m) + # compute area + area = sum(mask.area(rle)) # should be close to ann['area'] + + all_mask = np.stack(all_mask,axis=0) + all_mask = np.sum(all_mask,axis=0) + all_mask = np.where(all_mask!=0,1,all_mask) + else: + all_mask = np.zeros((image['height'], image['width'])) + area = 0 + return {'mask': all_mask, 'area': area} + + + def showMask(self, ref): + M = self.getMask(ref) + msk = M['mask'] + ax = plt.gca() + ax.imshow(msk) + + +if __name__ == '__main__': + refer = REFER(dataset='refcocog', splitBy='google') + ref_ids = refer.getRefIds() + + ref_ids = refer.getRefIds(split='train') + print('There are %s training referred objects.' % len(ref_ids)) + + for ref_id in ref_ids: + ref = refer.loadRefs(ref_id)[0] + if len(ref['sentences']) < 2: + continue + print('The label is %s.' % refer.Cats[ref['category_id']]) + plt.figure() + refer.showRef(ref, seg_box='box') + plt.show() diff --git a/LAVT-RIS/refer/setup.py b/LAVT-RIS/refer/setup.py new file mode 100644 index 0000000000000000000000000000000000000000..63b2d4d2da0bc7c05e67d0c5ed884aba97104445 --- /dev/null +++ b/LAVT-RIS/refer/setup.py @@ -0,0 +1,21 @@ +from distutils.core import setup +from Cython.Build import cythonize +from distutils.extension import Extension +import numpy as np + +ext_modules = [ + Extension( + 'external._mask', + sources=['external/maskApi.c', 'external/_mask.pyx'], + include_dirs = [np.get_include(), 'external'], + extra_compile_args=['-Wno-cpp', '-Wno-unused-function', '-std=c99'], + ) + ] + +setup( + name='external', + packages=['external'], + package_dir = {'external': 'external'}, + version='2.0', + ext_modules=cythonize(ext_modules) + ) diff --git a/LAVT-RIS/refer/test/sample_expressions_testA.json b/LAVT-RIS/refer/test/sample_expressions_testA.json new file mode 100644 index 0000000000000000000000000000000000000000..275e3a37ff1a247bf302bcc583190f49bc6cd2ef --- /dev/null +++ b/LAVT-RIS/refer/test/sample_expressions_testA.json @@ -0,0 +1 @@ +{"predictions":[{"sent":"man in black","ref_id":47},{"sent":"person on right","ref_id":109},{"sent":"woman in red","ref_id":110},{"sent":"car behind bike","ref_id":111},{"sent":"car on left","ref_id":112},{"sent":"man in blue","ref_id":382},{"sent":"man in white","ref_id":383},{"sent":"left person","ref_id":519},{"sent":"man on right","ref_id":520},{"sent":"person in background","ref_id":525},{"sent":"person on left","ref_id":526},{"sent":"man in white","ref_id":527},{"sent":"guy in white","ref_id":528},{"sent":"guy in red","ref_id":537},{"sent":"white shirt","ref_id":538},{"sent":"player in white","ref_id":539},{"sent":"red shirt","ref_id":557},{"sent":"girl","ref_id":558},{"sent":"baby","ref_id":588},{"sent":"baby","ref_id":589},{"sent":"woman in front","ref_id":640},{"sent":"girl","ref_id":641},{"sent":"right guy","ref_id":732},{"sent":"man in white","ref_id":733},{"sent":"middle guy","ref_id":734},{"sent":"woman","ref_id":756},{"sent":"man on right","ref_id":757},{"sent":"woman","ref_id":814},{"sent":"man in white","ref_id":815},{"sent":"man in white shirt","ref_id":828},{"sent":"woman on right","ref_id":829},{"sent":"man in red","ref_id":931},{"sent":"woman in pink","ref_id":932},{"sent":"girl in pink","ref_id":933},{"sent":"middle guy","ref_id":945},{"sent":"second from right","ref_id":946},{"sent":"left guy","ref_id":947},{"sent":"white jacket","ref_id":954},{"sent":"right guy","ref_id":955},{"sent":"blue jacket","ref_id":956},{"sent":"man in white shirt","ref_id":1023},{"sent":"man","ref_id":1024},{"sent":"man in back","ref_id":1052},{"sent":"left guy","ref_id":1053},{"sent":"woman on right","ref_id":1152},{"sent":"woman on right","ref_id":1153},{"sent":"left guy","ref_id":1154},{"sent":"woman on right","ref_id":1333},{"sent":"man in black shirt","ref_id":1334},{"sent":"man","ref_id":1362},{"sent":"man","ref_id":1363},{"sent":"right guy","ref_id":1371},{"sent":"left guy","ref_id":1372},{"sent":"man in front","ref_id":1406},{"sent":"man on left","ref_id":1407},{"sent":"person on right","ref_id":1568},{"sent":"person in front","ref_id":1569},{"sent":"man in black","ref_id":1582},{"sent":"man in front","ref_id":1583},{"sent":"right skier","ref_id":1623},{"sent":"person in front","ref_id":1624},{"sent":"second from left","ref_id":1679},{"sent":"man on left","ref_id":1680},{"sent":"second from right","ref_id":1681},{"sent":"left guy","ref_id":1682},{"sent":"woman on right","ref_id":1683},{"sent":"girl on right","ref_id":1684},{"sent":"man on right","ref_id":1811},{"sent":"man in front of man in white shirt","ref_id":1812},{"sent":"woman in white shirt","ref_id":1861},{"sent":"man in black","ref_id":1862},{"sent":"groom","ref_id":1882},{"sent":"bride","ref_id":1883},{"sent":"middle guy","ref_id":1977},{"sent":"left guy","ref_id":1978},{"sent":"right guy","ref_id":1979},{"sent":"second from left","ref_id":1980},{"sent":"person on left","ref_id":1990},{"sent":"left person","ref_id":1991},{"sent":"player","ref_id":2001},{"sent":"top left corner","ref_id":2002},{"sent":"girl in white on left","ref_id":2129},{"sent":"white shirt","ref_id":2130},{"sent":"woman in white","ref_id":2131},{"sent":"red jacket","ref_id":2173},{"sent":"red","ref_id":2174},{"sent":"catcher","ref_id":2256},{"sent":"umpire","ref_id":2257},{"sent":"baby","ref_id":2264},{"sent":"man","ref_id":2265},{"sent":"boy in blue","ref_id":2291},{"sent":"boy in red","ref_id":2292},{"sent":"man in black","ref_id":2375},{"sent":"man in black","ref_id":2376},{"sent":"blue jacket","ref_id":2721},{"sent":"bottom left","ref_id":2722},{"sent":"man","ref_id":2767},{"sent":"man","ref_id":2768},{"sent":"batter","ref_id":2805},{"sent":"right guy","ref_id":2806},{"sent":"batter","ref_id":2807},{"sent":"woman in black","ref_id":2981},{"sent":"woman in white","ref_id":2982},{"sent":"left girl","ref_id":3247},{"sent":"man in white","ref_id":3248},{"sent":"man on left","ref_id":3257},{"sent":"woman in middle","ref_id":3258},{"sent":"woman on right","ref_id":3259},{"sent":"man in middle","ref_id":3260},{"sent":"guy on right","ref_id":3366},{"sent":"left person","ref_id":3367},{"sent":"girl in pink","ref_id":3768},{"sent":"girl in pink","ref_id":3769},{"sent":"right guy","ref_id":3772},{"sent":"man","ref_id":3773},{"sent":"man in blue shirt","ref_id":3805},{"sent":"person in blue shirt","ref_id":3806},{"sent":"man in black","ref_id":3807},{"sent":"guy in red","ref_id":4002},{"sent":"second horse from left","ref_id":4003},{"sent":"guy in blue shirt","ref_id":4014},{"sent":"man in blue shirt","ref_id":4015},{"sent":"left person","ref_id":4016},{"sent":"man in blue","ref_id":4017},{"sent":"girl on right","ref_id":4089},{"sent":"girl","ref_id":4090},{"sent":"woman","ref_id":4101},{"sent":"girl","ref_id":4102},{"sent":"woman in black","ref_id":4143},{"sent":"person sitting on left","ref_id":4144},{"sent":"man in black","ref_id":4145},{"sent":"white shirt","ref_id":4159},{"sent":"man on right","ref_id":4160},{"sent":"right girl","ref_id":4174},{"sent":"left girl","ref_id":4175},{"sent":"person on right","ref_id":4176},{"sent":"girl on 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right corner","ref_id":232},{"sent":"pizza in front","ref_id":233},{"sent":"glass in back","ref_id":234},{"sent":"left glass","ref_id":235},{"sent":"yellow fruit on left","ref_id":259}]} \ No newline at end of file diff --git a/LAVT-RIS/requirements.txt b/LAVT-RIS/requirements.txt new file mode 100644 index 0000000000000000000000000000000000000000..9cb7e037ed9179ca75ea3a86497e68307401a645 --- /dev/null +++ b/LAVT-RIS/requirements.txt @@ -0,0 +1,14 @@ +requests +filelock +tqdm +timm +mmcv-full==1.3.12 +mmsegmentation==0.17.0 +ftfy +regex +scipy +scikit-image +pycocotools==2.0.2 +opencv-python==4.5.3.56 +tokenizers==0.8.1rc1 +h5py \ No newline at end of file diff --git a/LAVT-RIS/run.sh b/LAVT-RIS/run.sh new file mode 100644 index 0000000000000000000000000000000000000000..aa25453fe6091c92c8852b01f950f5fa8811ca1c --- /dev/null +++ b/LAVT-RIS/run.sh @@ -0,0 +1,15 @@ +#!/bin/bash +#SBATCH --job-name=jupyter # Submit a job named "example" +#SBATCH --partition=a6000 # ????? ???? ????: a6000 or a100 +#SBATCH --gres=gpu:1 # Use 1 GPU +#SBATCH --time=10-04:30:00 # d-hh:mm:ss ????, ???? job?? max time limit ???? +#SBATCH --mem=80G # cpu memory size +#SBATCH --cpus-per-task=6 # cpu ???? +#SBATCH --output=datagen.txt # ?????? ???? ??? std output?? ?????? ???? ??? + +ml purge +ml load cuda/11.3 +eval "$(conda shell.bash hook)" +conda activate cris + +srun jupyter notebook --no-browser --port=9821 \ No newline at end of file diff --git a/LAVT-RIS/scripts/baseline_refzom_angle.sh b/LAVT-RIS/scripts/baseline_refzom_angle.sh new file mode 100644 index 0000000000000000000000000000000000000000..087c708c338f8d9abbd2b0dd12450a286a7da44f --- /dev/null +++ b/LAVT-RIS/scripts/baseline_refzom_angle.sh @@ -0,0 +1,57 @@ +#!/bin/bash +#SBATCH --job-name=lvrz1 +#SBATCH --partition=a6000 +#SBATCH --gres=gpu:4 +#SBATCH --time=13-11:30:00 # d-hh:mm:ss ??¢®¡×??, ¢®¡×???? job?? max time limit ?????? +#SBATCH --mem=60000 # cpu memory size +#SBATCH --cpus-per-task=8 # cpu ?¢ç¡§¢®??¨£¢®¡×?? +#SBATCH --output=./logs/rzom_m10_mg12_tmp007_4gpu_bs32_ang.log + +ml purge +ml load cuda/11.8 +eval "$(conda shell.bash hook)" +conda activate risall + +cd /data2/projects/chaeyun/LAVT-RIS/ + + +export NCCL_P2P_DISABLE=1 +export NVIDIA_TF32_OVERRIDE=0 + +GPUS=4 +OUTPUT_DIR=$1 +EXP_NAME=$2 +MARGIN=$3 +TEMP=$4 +MODE=$5 +MLW=$6 +PORT=7852 + + +# TRAIN +# addzero is set to none for default. we don't include zero target cases in MRaCL +CUDA_VISIBLE_DEVICES=0,1,2,3 torchrun \ + --nproc_per_node=$GPUS --master_port=$PORT train_refzom_angle.py \ + --model lavt_one \ + --dataset ref-zom \ + --splitBy final \ + --split test \ + --output-dir ${OUTPUT_DIR} \ + --model_id ${EXP_NAME} \ + --batch-size 8 \ + --lr 0.00005 \ + --wd 1e-2 \ + --swin_type base \ + --pretrained_swin_weights ./pretrained_weights/swin_base_patch4_window12_384_22k.pth \ + --epochs 40 \ + --img_size 480 \ + --metric_learning \ + --margin_value ${MARGIN} \ + --temperature ${TEMP} \ + --metric_mode ${MODE} \ + --metric_loss_weight ${MLW} \ + --exclude_multiobj + + +# rzom_m10_mg12_tmp007_4gpu_bs32_ang original +# # sbatch ./scripts/baseline_refzom_angle.sh ./models/rzom_m10_mg12_tmp007_4gpu_bs32_ang rzom_m10_mg12_tmp007_4gpu_bs32_ang 12 0.07 hardpos_only 0.10 diff --git a/LAVT-RIS/scripts/baseline_refzom_angle_lr.sh b/LAVT-RIS/scripts/baseline_refzom_angle_lr.sh new file mode 100644 index 0000000000000000000000000000000000000000..8fa32471374a6dee33adb83df373ea6f7bcb28a1 --- /dev/null +++ b/LAVT-RIS/scripts/baseline_refzom_angle_lr.sh @@ -0,0 +1,57 @@ +#!/bin/bash +#SBATCH --job-name=lvrz1/2 +#SBATCH --partition=a6000 +#SBATCH --gres=gpu:4 +#SBATCH --time=13-11:30:00 # d-hh:mm:ss ??¢®¡×??, ¢®¡×???? job?? max time limit ?????? +#SBATCH --mem=60000 # cpu memory size +#SBATCH --cpus-per-task=8 # cpu ?¢ç¡§¢®??¨£¢®¡×?? +#SBATCH --output=./logs/rzom_m10_mg12_tmp007_4gpu_bs32_anghf.log + +ml purge +ml load cuda/11.8 +eval "$(conda shell.bash hook)" +conda activate risall + +cd /data2/projects/chaeyun/LAVT-RIS/ + + +export NCCL_P2P_DISABLE=1 +export NVIDIA_TF32_OVERRIDE=0 + +GPUS=4 +OUTPUT_DIR=$1 +EXP_NAME=$2 +MARGIN=$3 +TEMP=$4 +MODE=$5 +MLW=$6 +PORT=5982 + + +# TRAIN +# addzero is set to none for default. we don't include zero target cases in MRaCL +CUDA_VISIBLE_DEVICES=0,1,2,3 torchrun \ + --nproc_per_node=$GPUS --master_port=$PORT train_refzom_anglehalf.py \ + --model lavt_one \ + --dataset ref-zom \ + --splitBy final \ + --split test \ + --output-dir ${OUTPUT_DIR} \ + --model_id ${EXP_NAME} \ + --batch-size 8 \ + --lr 0.00005 \ + --wd 1e-2 \ + --swin_type base \ + --pretrained_swin_weights ./pretrained_weights/swin_base_patch4_window12_384_22k.pth \ + --epochs 40 \ + --img_size 480 \ + --metric_learning \ + --margin_value ${MARGIN} \ + --temperature ${TEMP} \ + --metric_mode ${MODE} \ + --metric_loss_weight ${MLW} \ + --exclude_multiobj + + +# rzom_m10_mg12_tmp007_4gpu_bs32_ang original +# # sbatch ./scripts/baseline_refzom_angle_lr.sh ./models/rzom_m10_mg12_tmp007_4gpu_bs32_anghf rzom_m10_mg12_tmp007_4gpu_bs32_anghf 12 0.07 hardpos_only 0.10 diff --git a/LAVT-RIS/scripts/baseline_repro_refzom.sh b/LAVT-RIS/scripts/baseline_repro_refzom.sh new file mode 100644 index 0000000000000000000000000000000000000000..9878b94808959df290ad46598334fd653414c74f --- /dev/null +++ b/LAVT-RIS/scripts/baseline_repro_refzom.sh @@ -0,0 +1,55 @@ +#!/bin/bash +#SBATCH --job-name=lavt-rz-trial +#SBATCH --partition=a6000 +#SBATCH --gres=gpu:2 +#SBATCH --time=13-11:30:00 # d-hh:mm:ss ??¨ö?, ¨¬??? job?? max time limit ???¢´ +#SBATCH --mem=28000 # cpu memory size +#SBATCH --cpus-per-task=4 # cpu ¡Æ©ø¨ù? +#SBATCH --output=./logs/lavt_refzom_repro_bs32.log + +ml purge +ml load cuda/11.8 +eval "$(conda shell.bash hook)" +conda activate risall + +cd /data2/projects/chaeyun/LAVT-RIS/ + +export NCCL_P2P_DISABLE=1 +export NVIDIA_TF32_OVERRIDE=0 + +GPUS=2 +OUTPUT_DIR=$1 +EXP_NAME=$2 +PORT=7852 + +# TRAIN +# hardpos_only, hardpos_only_rev +CUDA_VISIBLE_DEVICES=0,1 torchrun \ + --nproc_per_node=$GPUS --master_port=$PORT train_refzom.py \ + --model lavt_one \ + --dataset ref-zom \ + --splitBy final \ + --split test \ + --output-dir ${OUTPUT_DIR} \ + --model_id ${EXP_NAME} \ + --batch-size 16 \ + --lr 0.00005 \ + --wd 1e-2 \ + --swin_type base \ + --pretrained_swin_weights ./pretrained_weights/swin_base_patch4_window12_384_22k.pth \ + --resume /data2/projects/chaeyun/LAVT-RIS/models/refzom_lavt_bs32_repro/model_best_refzom_lavt_bs32_repro.pth \ + --epochs 40 \ + --img_size 480 + +# lavt-rzom +# sbatch ./scripts/baseline_test_lr2.sh ./models/gref_m05_tmp010_4gpu_bs32_orig gref_m05_tmp010_4gpu_bs32_orig 10 0.10 hardpos_only 0.05 + + +# gref_m10_tmp005_4gpu_bs32 +# margin 10 tmp 0.05 refined +# sbatch ./scripts/baseline_test_lr2.sh ./models/gref_m10_tmp005_4gpu_bs32 gref_m10_tmp005_4gpu_bs32 10 0.05 hardpos_only_refined + +# sbatch ./scripts/baseline_repro_refzom.sh ./models/refzom_lavt_bs32_repro refzom_lavt_bs32_repro + +# sbatch ./scripts/baseline_repro_refzom.sh ./models/refzom_lavt_bs16_repro refzom_lavt_bs16_repro + diff --git a/LAVT-RIS/scripts/baseline_test.sh b/LAVT-RIS/scripts/baseline_test.sh new file mode 100644 index 0000000000000000000000000000000000000000..846fdb78d82392f1ec4864cd026c7798c51892cb --- /dev/null +++ b/LAVT-RIS/scripts/baseline_test.sh @@ -0,0 +1,25 @@ +#!/bin/bash +#SBATCH --job-name=lavt_test +#SBATCH --partition=a4000 # a6000 or a100 +#SBATCH --gres=gpu:1 +#SBATCH --time=7-00:00:00 # d-hh:mm:ss, max time limit +#SBATCH --mem=48000 # cpu memory size +#SBATCH --cpus-per-task=4 # cpu num +#SBATCH --output=./logs/test_gref_m10_mg10_tmp010_4gpu_bs16_ang.txt + +ml purge +ml load cuda/11.3 +eval "$(conda shell.bash hook)" +conda activate cris + +cd /data2/projects/chaeyun/LAVT-RIS/ + + +MODEL_ID="gref_m10_mg10_tmp010_4gpu_bs16_ang" +# MODEL_ID="posonly_mlw005_b32_2" + +# python test.py --model lavt_one --swin_type base --dataset refcocog --splitBy umd --split val --resume ./models/$MODEL_ID/model_best_$MODEL_ID.pth --workers 4 --ddp_trained_weights --window12 --img_size 480 +# python test_mostat.py --model lavt_one --swin_type base --dataset refcocog --splitBy umd --split static --resume ./models/$MODEL_ID/model_best_$MODEL_ID.pth --workers 4 --ddp_trained_weights --window12 --img_size 480 + +python test.py --model lavt_one --swin_type base --dataset refcocog --splitBy umd --split test --resume ./models/$MODEL_ID/model_best_$MODEL_ID.pth --workers 4 --ddp_trained_weights --window12 --img_size 480 +python test_mostat.py --model lavt_one --swin_type base --dataset refcocog --splitBy umd --split motion --resume ./models/$MODEL_ID/model_best_$MODEL_ID.pth --workers 4 --ddp_trained_weights --window12 --img_size 480 diff --git a/LAVT-RIS/scripts/baseline_test_lr2.sh b/LAVT-RIS/scripts/baseline_test_lr2.sh new file mode 100644 index 0000000000000000000000000000000000000000..60023f24d4d70b82fb3673cc657cdeecbf2b99ab --- /dev/null +++ b/LAVT-RIS/scripts/baseline_test_lr2.sh @@ -0,0 +1,66 @@ +#!/bin/bash +#SBATCH --job-name=mlw010-or2 +#SBATCH --partition=a6000 +#SBATCH --gres=gpu:4 +#SBATCH --time=13-11:30:00 # d-hh:mm:ss ??¨ö?, ¨¬??? job?? max time limit ???¢´ +#SBATCH --mem=64000 # cpu memory size +#SBATCH --cpus-per-task=12 # cpu ¡Æ©ø¨ù? +#SBATCH --output=./logs/gref_m05_tmp010_4gpu_bs32_orig.log + +ml purge +ml load cuda/11.3 +eval "$(conda shell.bash hook)" +conda activate cris + +cd /data2/projects/chaeyun/LAVT-RIS/ + +# todo +# gref_m05_tmp010_4gpu_bs32_orig +# mlw 0.05 margin 10 tmp 0.10 original +# sbatch ./scripts/baseline_test_lr2.sh ./models/gref_m05_tmp010_4gpu_bs32_orig gref_m05_tmp010_4gpu_bs32_orig 10 0.10 hardpos_only 0.05 + + +# gref_m10_tmp005_4gpu_bs32 +# margin 10 tmp 0.05 refined +# sbatch ./scripts/baseline_test_lr2.sh ./models/gref_m10_tmp005_4gpu_bs32 gref_m10_tmp005_4gpu_bs32 10 0.05 hardpos_only_refined 0.10 + + + + +# margin temp mlw + +export NCCL_P2P_DISABLE=1 +export NVIDIA_TF32_OVERRIDE=0 + +GPUS=4 +OUTPUT_DIR=$1 +EXP_NAME=$2 +MARGIN=$3 +TEMP=$4 +MODE=$5 +MLW=$6 + + +# TRAIN +# hardpos_only, hardpos_only_rev +python_args="--model lavt_one \ +--dataset refcocog \ +--splitBy umd \ +--output-dir ${OUTPUT_DIR} \ +--model_id ${EXP_NAME} \ +--batch-size 8 \ +--lr 0.00005 \ +--wd 1e-2 \ +--swin_type base \ +--pretrained_swin_weights ./pretrained_weights/swin_base_patch4_window12_384_22k.pth \ +--epochs 40 \ +--img_size 480 \ +--metric_learning \ +--margin_value ${MARGIN} \ +--temperature ${TEMP} \ +--metric_mode ${MODE} \ +--hp_selection naive \ +--metric_loss_weight ${MLW} \ +--exclude_multiobj " + +python -m torch.distributed.launch --nproc_per_node=$GPUS --master_port=3928 train.py $python_args \ No newline at end of file diff --git a/LAVT-RIS/scripts/baseline_test_lr_angle.sh b/LAVT-RIS/scripts/baseline_test_lr_angle.sh new file mode 100644 index 0000000000000000000000000000000000000000..676828d7bac2bf3711f0523076f2a1610666c55f --- /dev/null +++ b/LAVT-RIS/scripts/baseline_test_lr_angle.sh @@ -0,0 +1,74 @@ +#!/bin/bash + +ml purge +ml load cuda/11.3 +eval "$(conda shell.bash hook)" +conda activate cris + +cd /data2/projects/chaeyun/LAVT-RIS/ + + +# todo after 241208 +# gref_m10_mg10_tmp010_4gpu_bs32_ang +# mlw 0.10 margin 8 tmp 0.10 original +# # bash ./scripts/baseline_test_lr_angle.sh ./models/gref_m10_mg10_tmp010_4gpu_bs32_ang gref_m10_mg10_tmp010_4gpu_bs32_ang 10 0.10 hardpos_only 0.10 > ./logs/gref_m10_mg10_tmp010_4gpu_bs32_ang.log 2>&1 + + +# # bash ./scripts/baseline_test_lr.sh ./models/gref_m10_mg08_tmp010_4gpu_bs32_ang gref_m10_mg08_tmp010_4gpu_bs32_ang 8 0.10 hardpos_only 0.10 > ./logs/gref_m10_mg08_tmp010_4gpu_bs32_ang.log 2>&1 + + +# gref_m10_tmp010_4gpu_bs32_orig +# done : margin 10 tmp 0.10 original + + +export NCCL_P2P_DISABLE=1 +export NVIDIA_TF32_OVERRIDE=0 + +GPUS=4 +OUTPUT_DIR=$1 +EXP_NAME=$2 +MARGIN=$3 +TEMP=$4 +MODE=$5 +MLW=$6 + + +# # Create the directory if it does not exist +# if [[ ! -d "${OPT_DIR}/${EXP_NAME}" ]]; then +# echo "Directory ${OPT_DIR}/${EXP_NAME} does not exist. Creating it..." +# mkdir -p "${OPT_DIR}/${EXP_NAME}" +# fi + + +# TRAIN +# hardpos_only, hardpos_only_rev +python_args="--model lavt_one \ +--dataset refcocog \ +--splitBy umd \ +--output-dir ${OUTPUT_DIR} \ +--model_id ${EXP_NAME} \ +--batch-size 8 \ +--lr 0.00005 \ +--wd 1e-2 \ +--swin_type base \ +--pretrained_swin_weights ./pretrained_weights/swin_base_patch4_window12_384_22k.pth \ +--epochs 40 \ +--img_size 480 \ +--metric_learning \ +--margin_value ${MARGIN} \ +--temperature ${TEMP} \ +--metric_mode ${MODE} \ +--metric_loss_weight ${MLW} \ +--exclude_multiobj " + +python -m torch.distributed.launch --nproc_per_node=$GPUS --master_port=3928 train_angle.py $python_args + +# sbatch ./scripts/baseline_test_lr.sh ./models/gref_hp10_m10_tmp003 gref_hp10_m10_tmp003 10 0.03 hardpos_only_refined +# sbatch ./scripts/baseline_test_lr.sh ./models/gref_hp10_m10_tmp010 gref_hp10_m10_tmp010 10 0.10 hardpos_only_refined +# sbatch ./scripts/baseline_test_lr.sh ./models/gref_hp10_m15_tmp005 gref_hp10_m15_tmp005 15 0.05 hardpos_only_refined +# sbatch ./scripts/baseline_test_lr.sh ./models/gref_hp10_m20_tmp005 gref_hp10_m20_tmp005 20 0.05 hardpos_only_refined + + +# python test.py --model lavt_one --swin_type base --dataset refcocog --splitBy umd --split test --resume ./models/gref_umd/lavt_test_lr/gref_testlr_4gpu.pth --workers 4 --ddp_trained_weights --window12 --img_size 480 + +# /data2/projects/chaeyun/LAVT-RIS/models/refzom_lavt_bs32_repro/model_best_refzom_lavt_bs32_repro.pth diff --git a/LAVT-RIS/scripts/baseline_test_lr_angle2.sh b/LAVT-RIS/scripts/baseline_test_lr_angle2.sh new file mode 100644 index 0000000000000000000000000000000000000000..e69eecf3ad78448b448f3060b81148b32a9ebe86 --- /dev/null +++ b/LAVT-RIS/scripts/baseline_test_lr_angle2.sh @@ -0,0 +1,85 @@ +#!/bin/bash +#SBATCH --job-name=angle2 +#SBATCH --partition=a6000 +#SBATCH --gres=gpu:4 +#SBATCH --time=13-11:30:00 # d-hh:mm:ss ??¡§??, ¡§???? job?? max time limit ????¢¥ +#SBATCH --mem=60000 # cpu memory size +#SBATCH --cpus-per-task=8 # cpu ¢®¨¡?©ª¡§?? +#SBATCH --output=./logs/gref_m10_mg10_tmp007_4gpu_bs32_ang.log + +ml purge +ml load cuda/11.3 +eval "$(conda shell.bash hook)" +conda activate cris + +cd /data2/projects/chaeyun/LAVT-RIS/ + +# gref_m10_mg10_tmp007_4gpu_bs32_ang +# # sbatch ./scripts/baseline_test_lr_angle2.sh ./models/gref_m10_mg10_tmp007_4gpu_bs32_ang gref_m10_mg10_tmp007_4gpu_bs32_ang 10 0.07 hardpos_only 0.10 + +# todo after 241208 +# gref_m10_mg10_tmp010_4gpu_bs32_ang +# mlw 0.10 margin 8 tmp 0.10 original +# # bash ./scripts/baseline_test_lr_angle.sh ./models/gref_m10_mg10_tmp010_4gpu_bs32_ang gref_m10_mg10_tmp010_4gpu_bs32_ang 10 0.10 hardpos_only 0.10 > ./logs/gref_m10_mg10_tmp010_4gpu_bs32_ang.log 2>&1 + + +# # bash ./scripts/baseline_test_lr.sh ./models/gref_m10_mg08_tmp010_4gpu_bs32_ang gref_m10_mg08_tmp010_4gpu_bs32_ang 8 0.10 hardpos_only 0.10 > ./logs/gref_m10_mg08_tmp010_4gpu_bs32_ang.log 2>&1 + + +# gref_m10_mg12_tmp007_4gpu_bs32_ang +# gref_m10_mg12_tmp010_4gpu_bs32_ang +# gref_m10_mg10_tmp007_4gpu_bs32_ang +# gref_m10_mg10_tmp010_4gpu_bs32_ang +# gref_m10_mg15_tmp010_4gpu_bs32_ang + + + +export NCCL_P2P_DISABLE=1 +export NVIDIA_TF32_OVERRIDE=0 + +GPUS=4 +OUTPUT_DIR=$1 +EXP_NAME=$2 +MARGIN=$3 +TEMP=$4 +MODE=$5 +MLW=$6 + + +# # Create the directory if it does not exist +# if [[ ! -d "${OPT_DIR}/${EXP_NAME}" ]]; then +# echo "Directory ${OPT_DIR}/${EXP_NAME} does not exist. Creating it..." +# mkdir -p "${OPT_DIR}/${EXP_NAME}" +# fi + + +# TRAIN +# hardpos_only, hardpos_only_rev +python_args="--model lavt_one \ +--dataset refcocog \ +--splitBy umd \ +--output-dir ${OUTPUT_DIR} \ +--model_id ${EXP_NAME} \ +--batch-size 8 \ +--lr 0.00005 \ +--wd 1e-2 \ +--swin_type base \ +--pretrained_swin_weights ./pretrained_weights/swin_base_patch4_window12_384_22k.pth \ +--epochs 40 \ +--img_size 480 \ +--metric_learning \ +--margin_value ${MARGIN} \ +--temperature ${TEMP} \ +--metric_mode ${MODE} \ +--metric_loss_weight ${MLW} \ +--exclude_multiobj " + +python -m torch.distributed.launch --nproc_per_node=$GPUS --master_port=6872 train_angle.py $python_args + +# sbatch ./scripts/baseline_test_lr.sh ./models/gref_hp10_m10_tmp003 gref_hp10_m10_tmp003 10 0.03 hardpos_only_refined +# sbatch ./scripts/baseline_test_lr.sh ./models/gref_hp10_m10_tmp010 gref_hp10_m10_tmp010 10 0.10 hardpos_only_refined +# sbatch ./scripts/baseline_test_lr.sh ./models/gref_hp10_m15_tmp005 gref_hp10_m15_tmp005 15 0.05 hardpos_only_refined +# sbatch ./scripts/baseline_test_lr.sh ./models/gref_hp10_m20_tmp005 gref_hp10_m20_tmp005 20 0.05 hardpos_only_refined + + +# python test.py --model lavt_one --swin_type base --dataset refcocog --splitBy umd --split test --resume ./models/gref_umd/lavt_test_lr/gref_testlr_4gpu.pth --workers 4 --ddp_trained_weights --window12 --img_size 480 diff --git a/LAVT-RIS/scripts/baseline_test_lr_resume_mlw005.sh b/LAVT-RIS/scripts/baseline_test_lr_resume_mlw005.sh new file mode 100644 index 0000000000000000000000000000000000000000..d06db3a5696a9563937d6837365ddafb5192b84d --- /dev/null +++ b/LAVT-RIS/scripts/baseline_test_lr_resume_mlw005.sh @@ -0,0 +1,73 @@ +#!/bin/bash +#SBATCH --job-name=lavt_mlw005-res +#SBATCH --nodes=1 +#SBATCH --gres=gpu:4 +#SBATCH --time=0-12:00:00 # d-hh:mm:ss, job time limit +#SBATCH --mem=75000 # cpu memory size +#SBATCH --cpus-per-task=6 +#SBATCH --output=./logs/gref_hp05_m10_tmp005_resume.log + +source ${HOME}/.bashrc +source ${HOME}/miniconda3/bin/activate base +conda activate cris + +cd /home/s1/chaeyunkim/LAVT-RIS + + +# gref_hp05_m10_tmp005_resume +# --metric_loss_weight 0.05 \ +# sbatch ./scripts/baseline_test_lr_resume_mlw005.sh ./models/gref_hp05_m10_tmp005 gref_hp05_m10_tmp005 10 0.05 hardpos_only_refined /home/s1/chaeyunkim/LAVT-RIS/models/gref_hp05_m10_tmp005/model_best_gref_hp05_m10_tmp005.pth + + +#--metric_loss_weight 0.05 \ +# gref_hp05_m10_tmp005_orig_resume +# sbatch ./scripts/baseline_test_lr_resume_mlw005.sh ./models/gref_hp05_m10_tmp005_orig gref_hp05_m10_tmp005_orig 10 0.05 hardpos_only /home/s1/chaeyunkim/LAVT-RIS/models/gref_hp05_m10_tmp005_orig/model_best_gref_hp05_m10_tmp005_orig.pth + + + +export NCCL_P2P_DISABLE=1 +export NVIDIA_TF32_OVERRIDE=0 + +# # core args +# BATCH_SIZE=64 +GPUS=4 +OUTPUT_DIR=$1 +EXP_NAME=$2 +MARGIN=$3 +TEMP=$4 +MODE=$5 +RESUME=$6 + +# # Create the directory if it does not exist +# if [[ ! -d "${OPT_DIR}/${EXP_NAME}" ]]; then +# echo "Directory ${OPT_DIR}/${EXP_NAME} does not exist. Creating it..." +# mkdir -p "${OPT_DIR}/${EXP_NAME}" +# fi + + +# TRAIN +# hardpos_only, hardpos_only_rev +python_args="--model lavt_one \ +--dataset refcocog \ +--splitBy umd \ +--output-dir ${OUTPUT_DIR} \ +--model_id ${EXP_NAME} \ +--batch-size 4 \ +--lr 0.00005 \ +--wd 1e-2 \ +--swin_type base \ +--pretrained_swin_weights ./pretrained_weights/swin_base_patch4_window12_384_22k.pth \ +--epochs 40 \ +--img_size 480 \ +--metric_learning \ +--margin_value ${MARGIN} \ +--temperature ${TEMP} \ +--resume ${RESUME} \ +--metric_mode ${MODE} \ +--metric_loss_weight 0.05 \ +--exclude_multiobj " + +python -m torch.distributed.launch --nproc_per_node=$GPUS train.py $python_args + + +# python test.py --model lavt_one --swin_type base --dataset refcocog --splitBy umd --split test --resume ./models/gref_umd/lavt_test_lr/gref_testlr_4gpu.pth --workers 4 --ddp_trained_weights --window12 --img_size 480 diff --git a/LAVT-RIS/test.py b/LAVT-RIS/test.py new file mode 100644 index 0000000000000000000000000000000000000000..5f214ff7194acfaa4f6a38eac8f9d03fb717b375 --- /dev/null +++ b/LAVT-RIS/test.py @@ -0,0 +1,139 @@ +import datetime +import os +import time + +import torch +import torch.utils.data +from torch import nn + +from bert.modeling_bert import BertModel +import torchvision + +from lib import segmentation +import transforms as T +import utils + +import numpy as np +from PIL import Image +import torch.nn.functional as F + + +def get_dataset(image_set, transform, args): + from data.dataset_refer_bert import ReferDataset + ds = ReferDataset(args, + split=image_set, + image_transforms=transform, + target_transforms=None, + eval_mode=True + ) + num_classes = 2 + return ds, num_classes + + +def evaluate(model, data_loader, bert_model, device): + model.eval() + metric_logger = utils.MetricLogger(delimiter=" ") + + # evaluation variables + cum_I, cum_U = 0, 0 + eval_seg_iou_list = [.5, .6, .7, .8, .9] + seg_correct = np.zeros(len(eval_seg_iou_list), dtype=np.int32) + seg_total = 0 + mean_IoU = [] + header = 'Test:' + + with torch.no_grad(): + for data in metric_logger.log_every(data_loader, 100, header): + image, target, sentences, attentions = data + image, target, sentences, attentions = image.to(device), target.to(device), \ + sentences.to(device), attentions.to(device) + sentences = sentences.squeeze(1) + attentions = attentions.squeeze(1) + target = target.cpu().data.numpy() + for j in range(sentences.size(-1)): + if bert_model is not None: + last_hidden_states = bert_model(sentences[:, :, j], attention_mask=attentions[:, :, j])[0] + embedding = last_hidden_states.permute(0, 2, 1) + output = model(image, embedding, l_mask=attentions[:, :, j].unsqueeze(-1), is_train=False) + else: + output = model(image, sentences[:, :, j], l_mask=attentions[:, :, j], is_train=False) + + output = output.cpu() + output_mask = output.argmax(1).data.numpy() + I, U = computeIoU(output_mask, target) + if U == 0: + this_iou = 0.0 + else: + this_iou = I*1.0/U + mean_IoU.append(this_iou) + cum_I += I + cum_U += U + for n_eval_iou in range(len(eval_seg_iou_list)): + eval_seg_iou = eval_seg_iou_list[n_eval_iou] + seg_correct[n_eval_iou] += (this_iou >= eval_seg_iou) + seg_total += 1 + + del image, target, sentences, attentions, output, output_mask + if bert_model is not None: + del last_hidden_states, embedding + + mean_IoU = np.array(mean_IoU) + mIoU = np.mean(mean_IoU) + print('Final results:') + print('Mean IoU is %.2f\n' % (mIoU*100.)) + results_str = '' + for n_eval_iou in range(len(eval_seg_iou_list)): + results_str += ' precision@%s = %.2f\n' % \ + (str(eval_seg_iou_list[n_eval_iou]), seg_correct[n_eval_iou] * 100. / seg_total) + results_str += ' overall IoU = %.2f\n' % (cum_I * 100. / cum_U) + print(results_str) + + +def get_transform(args): + transforms = [T.Resize(args.img_size, args.img_size), + T.ToTensor(), + T.Normalize(mean=[0.485, 0.456, 0.406], std=[0.229, 0.224, 0.225]) + ] + + return T.Compose(transforms) + + +def computeIoU(pred_seg, gd_seg): + I = np.sum(np.logical_and(pred_seg, gd_seg)) + U = np.sum(np.logical_or(pred_seg, gd_seg)) + + return I, U + + +def main(args): + device = torch.device(args.device) + dataset_test, _ = get_dataset(args.split, get_transform(args=args), args) + test_sampler = torch.utils.data.SequentialSampler(dataset_test) + data_loader_test = torch.utils.data.DataLoader(dataset_test, batch_size=1, + sampler=test_sampler, num_workers=args.workers) + print(args.model) + single_model = segmentation.__dict__[args.model](pretrained='',args=args) + checkpoint = torch.load(args.resume, map_location='cpu') + single_model.load_state_dict(checkpoint['model']) + model = single_model.to(device) + + if args.model != 'lavt_one': + model_class = BertModel + single_bert_model = model_class.from_pretrained(args.ck_bert) + # work-around for a transformers bug; need to update to a newer version of transformers to remove these two lines + if args.ddp_trained_weights: + single_bert_model.pooler = None + single_bert_model.load_state_dict(checkpoint['bert_model']) + bert_model = single_bert_model.to(device) + else: + bert_model = None + + evaluate(model, data_loader_test, bert_model, device=device) + + +if __name__ == "__main__": + from args import get_parser + parser = get_parser() + args = parser.parse_args() + print('Image size: {}'.format(str(args.img_size))) + main(args) diff --git a/LAVT-RIS/test_ablation_motion.json b/LAVT-RIS/test_ablation_motion.json new file mode 100644 index 0000000000000000000000000000000000000000..0d2c155ef5ca2dc055b259a64a51f5db0bde1067 --- /dev/null +++ b/LAVT-RIS/test_ablation_motion.json @@ -0,0 +1 @@ +[{"bbox": [384, 167, 510, 460], "cat": 0, "segment_id": 1939, "img_name": "COCO_train2014_000000247660.jpg", "sentences": [{"idx": 0, "sent_id": 44227, "sent": "a person in white shorts with an event smock and dark jacket"}], "sentences_num": 1, "version": "original"}, {"bbox": [265, 161, 367, 329], "cat": 0, "segment_id": 4952, "img_name": "COCO_train2014_000000425148.jpg", "sentences": [{"idx": 0, "sent_id": 90168, "sent": "a person driving a bike"}], "sentences_num": 1, "version": "original"}, {"bbox": [232, 111, 411, 459], "cat": 0, "segment_id": 1977, "img_name": "COCO_train2014_000000078578.jpg", "sentences": [{"idx": 0, "sent_id": 45097, "sent": "person cutting a cake"}], "sentences_num": 1, "version": "original"}, {"bbox": [155, 182, 382, 479], "cat": 0, "segment_id": 3980, "img_name": "COCO_train2014_000000297251.jpg", "sentences": [{"idx": 0, "sent_id": 91174, "sent": "person carrying another person on one's back at zoo"}], "sentences_num": 1, "version": "original"}, {"bbox": [259, 112, 426, 282], "cat": 0, "segment_id": 4868, "img_name": "COCO_train2014_000000035964.jpg", "sentences": [{"idx": 0, "sent_id": 70727, "sent": "woman reaching for an item on a table"}], "sentences_num": 1, "version": "original"}, {"bbox": [5, 79, 210, 263], "cat": 0, "segment_id": 5019, "img_name": "COCO_train2014_000000035964.jpg", "sentences": [{"idx": 0, "sent_id": 103845, "sent": "the woman is putting chili on the meat ball sandwich"}], "sentences_num": 1, "version": "original"}, {"bbox": [2, 43, 340, 360], "cat": 0, "segment_id": 1992, "img_name": "COCO_train2014_000000243824.jpg", "sentences": [{"idx": 0, "sent_id": 45388, "sent": "person is looking down at his pizza"}], "sentences_num": 1, "version": "original"}, {"bbox": [317, 49, 638, 374], "cat": 0, "segment_id": 4303, "img_name": "COCO_train2014_000000243824.jpg", "sentences": [{"idx": 0, "sent_id": 99563, "sent": "a person holding a knife and a fork in her hands at the table"}], "sentences_num": 1, "version": "original"}, {"bbox": [306, 192, 579, 353], "cat": 19, "segment_id": 2007, "img_name": "COCO_train2014_000000314051.jpg", "sentences": [{"idx": 0, "sent_id": 45876, "sent": "cow laying on the ground"}], "sentences_num": 1, "version": "original"}, {"bbox": [80, 98, 226, 313], "cat": 19, "segment_id": 3276, "img_name": "COCO_train2014_000000314051.jpg", "sentences": [{"idx": 0, "sent_id": 74695, "sent": "a cow standing in a field next to a cow laying down"}], "sentences_num": 1, "version": "original"}, {"bbox": [151, 0, 390, 640], "cat": 0, "segment_id": 2010, "img_name": "COCO_train2014_000000240378.jpg", "sentences": [{"idx": 0, "sent_id": 45897, "sent": "person smiling and getting one's tie tied"}], "sentences_num": 1, "version": "original"}, {"bbox": [4, 35, 293, 627], "cat": 0, "segment_id": 2401, "img_name": "COCO_train2014_000000240378.jpg", "sentences": [{"idx": 0, "sent_id": 54847, "sent": "the person fixing another person's tie"}], "sentences_num": 1, "version": "original"}, {"bbox": [285, 5, 434, 420], "cat": 0, "segment_id": 2011, "img_name": "COCO_train2014_000000514243.jpg", "sentences": [{"idx": 0, "sent_id": 45909, "sent": "a girl talking on her cell phone"}], "sentences_num": 1, "version": "original"}, {"bbox": [436, 41, 608, 395], "cat": 0, "segment_id": 2884, "img_name": "COCO_train2014_000000514243.jpg", "sentences": [{"idx": 0, "sent_id": 65819, "sent": "a woman sitting behind another woman"}], "sentences_num": 1, "version": "original"}, {"bbox": [2, 129, 270, 638], "cat": 0, "segment_id": 2051, "img_name": "COCO_train2014_000000492219.jpg", "sentences": [{"idx": 0, "sent_id": 46849, "sent": "man reaching out his right arm"}], "sentences_num": 1, "version": "original"}, {"bbox": [250, 133, 460, 472], "cat": 0, "segment_id": 2070, "img_name": "COCO_train2014_000000147941.jpg", "sentences": [{"idx": 0, "sent_id": 47233, "sent": "a woman playing tennis"}], "sentences_num": 1, "version": "original"}, {"bbox": [0, 16, 391, 474], "cat": 0, "segment_id": 3832, "img_name": "COCO_train2014_000000102281.jpg", "sentences": [{"idx": 0, "sent_id": 87598, "sent": "a person adjusting another person's tie"}], "sentences_num": 1, "version": "original"}, {"bbox": [136, 47, 433, 498], "cat": 0, "segment_id": 2919, "img_name": 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[{"idx": 0, "sent_id": 50066, "sent": "a woman walking"}], "sentences_num": 1, "version": "original"}, {"bbox": [0, 70, 91, 374], "cat": 0, "segment_id": 2214, "img_name": "COCO_train2014_000000522074.jpg", "sentences": [{"idx": 0, "sent_id": 50208, "sent": "a woman holding a donut"}], "sentences_num": 1, "version": "original"}, {"bbox": [78, 75, 205, 368], "cat": 0, "segment_id": 2266, "img_name": "COCO_train2014_000000522074.jpg", "sentences": [{"idx": 0, "sent_id": 51661, "sent": "the woman holding a purse"}], "sentences_num": 1, "version": "original"}, {"bbox": [507, 239, 639, 418], "cat": 0, "segment_id": 2272, "img_name": "COCO_train2014_000000070161.jpg", "sentences": [{"idx": 0, "sent_id": 51815, "sent": "person catching a ball"}], "sentences_num": 1, "version": "original"}, {"bbox": [227, 53, 465, 352], "cat": 0, "segment_id": 2495, "img_name": "COCO_train2014_000000070161.jpg", "sentences": [{"idx": 0, "sent_id": 56804, "sent": "a baseball player swinging at a ball"}], "sentences_num": 1, "version": "original"}, {"bbox": [283, 238, 443, 458], "cat": 0, "segment_id": 2286, "img_name": "COCO_train2014_000000471966.jpg", "sentences": [{"idx": 0, "sent_id": 52227, "sent": "a man swings at a ball during a baseball game"}], "sentences_num": 1, "version": "original"}, {"bbox": [286, 105, 637, 408], "cat": 18, "segment_id": 2290, "img_name": "COCO_train2014_000000504259.jpg", "sentences": [{"idx": 0, "sent_id": 52302, "sent": "a white sheep standing in the pasture next to a sitting sheep"}], "sentences_num": 1, "version": "original"}, {"bbox": [262, 41, 438, 124], "cat": 18, "segment_id": 2347, "img_name": "COCO_train2014_000000504259.jpg", "sentences": [{"idx": 0, "sent_id": 53861, "sent": "a sheep sitting down in the grass"}], "sentences_num": 1, "version": "original"}, {"bbox": [332, 204, 628, 453], "cat": 0, "segment_id": 4434, "img_name": "COCO_train2014_000000291366.jpg", "sentences": [{"idx": 0, "sent_id": 102335, "sent": "a man spectating a tennis 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"cat": 0, "segment_id": 169, "img_name": "COCO_train2014_000000520767.jpg", "sentences": [{"idx": 0, "sent_id": 4003, "sent": "a small person in a light blue shirt"}], "sentences_num": 1, "version": "original"}, {"bbox": [69, 34, 417, 414], "cat": 0, "segment_id": 1850, "img_name": "COCO_train2014_000000522947.jpg", "sentences": [{"idx": 0, "sent_id": 42079, "sent": "a man wearing a red color tie"}], "sentences_num": 1, "version": "original"}, {"bbox": [0, 8, 494, 399], "cat": 0, "segment_id": 3757, "img_name": "COCO_train2014_000000523455.jpg", "sentences": [{"idx": 0, "sent_id": 85762, "sent": "person in a blue hoodie"}], "sentences_num": 1, "version": "original"}, {"bbox": [0, 67, 190, 339], "cat": 0, "segment_id": 41, "img_name": "COCO_train2014_000000538537.jpg", "sentences": [{"idx": 0, "sent_id": 962, "sent": "woman on the far left"}], "sentences_num": 1, "version": "original"}, {"bbox": [56, 63, 426, 632], "cat": 0, "segment_id": 885, "img_name": "COCO_train2014_000000539475.jpg", "sentences": [{"idx": 0, "sent_id": 19927, "sent": "bigger person in black blouse"}], "sentences_num": 1, "version": "original"}, {"bbox": [87, 341, 371, 539], "cat": 0, "segment_id": 4862, "img_name": "COCO_train2014_000000539475.jpg", "sentences": [{"idx": 0, "sent_id": 69277, "sent": "smaller person wearing white pajamas"}], "sentences_num": 1, "version": "original"}, {"bbox": [112, 247, 276, 372], "cat": 20, "segment_id": 5786, "img_name": "COCO_train2014_000000010495.jpg", "sentences": [{"idx": 0, "sent_id": 45910, "sent": "woman in blue shirt and white shorts"}], "sentences_num": 1, "version": "original"}, {"bbox": [247, 120, 362, 257], "cat": 3, "segment_id": 6123, "img_name": "COCO_train2014_000000578705.jpg", "sentences": [{"idx": 0, "sent_id": 65820, "sent": "woman with black hair wearing jeans, a striped gray shirt and flip flops"}], "sentences_num": 1, "version": "original"}] \ No newline at end of file diff --git a/LAVT-RIS/test_mostat.py b/LAVT-RIS/test_mostat.py new file mode 100644 index 0000000000000000000000000000000000000000..6eaade34173573a0206bc92f96ef955005a1c37c --- /dev/null +++ b/LAVT-RIS/test_mostat.py @@ -0,0 +1,139 @@ +import datetime +import os +import time + +import torch +import torch.utils.data +from torch import nn + +from bert.modeling_bert import BertModel +import torchvision + +from lib import segmentation +import transforms as T +import utils + +import numpy as np +from PIL import Image +import torch.nn.functional as F + + +def get_dataset(image_set, transform, args): + from data.dataset_refer_bert_mostat import ReferDataset + ds = ReferDataset(args, + split=image_set, + image_transforms=transform, + target_transforms=None, + eval_mode=True + ) + num_classes = 2 + return ds, num_classes + + +def evaluate(model, data_loader, bert_model, device): + model.eval() + metric_logger = utils.MetricLogger(delimiter=" ") + + # evaluation variables + cum_I, cum_U = 0, 0 + eval_seg_iou_list = [.5, .6, .7, .8, .9] + seg_correct = np.zeros(len(eval_seg_iou_list), dtype=np.int32) + seg_total = 0 + mean_IoU = [] + header = 'Test:' + + with torch.no_grad(): + for data in metric_logger.log_every(data_loader, 100, header): + image, target, sentences, attentions = data + image, target, sentences, attentions = image.to(device), target.to(device), \ + sentences.to(device), attentions.to(device) + sentences = sentences.squeeze(1) + attentions = attentions.squeeze(1) + target = target.cpu().data.numpy() + for j in range(sentences.size(-1)): + if bert_model is not None: + last_hidden_states = bert_model(sentences[:, :, j], attention_mask=attentions[:, :, j])[0] + embedding = last_hidden_states.permute(0, 2, 1) + output = model(image, embedding, l_mask=attentions[:, :, j].unsqueeze(-1)) + else: + output = model(image, sentences[:, :, j], l_mask=attentions[:, :, j], is_train=False) + + output = output.cpu() + output_mask = output.argmax(1).data.numpy() + I, U = computeIoU(output_mask, target) + if U == 0: + this_iou = 0.0 + else: + this_iou = I*1.0/U + mean_IoU.append(this_iou) + cum_I += I + cum_U += U + for n_eval_iou in range(len(eval_seg_iou_list)): + eval_seg_iou = eval_seg_iou_list[n_eval_iou] + seg_correct[n_eval_iou] += (this_iou >= eval_seg_iou) + seg_total += 1 + + del image, target, sentences, attentions, output, output_mask + if bert_model is not None: + del last_hidden_states, embedding + + mean_IoU = np.array(mean_IoU) + mIoU = np.mean(mean_IoU) + print('Final results:') + print('Mean IoU is %.2f\n' % (mIoU*100.)) + results_str = '' + for n_eval_iou in range(len(eval_seg_iou_list)): + results_str += ' precision@%s = %.2f\n' % \ + (str(eval_seg_iou_list[n_eval_iou]), seg_correct[n_eval_iou] * 100. / seg_total) + results_str += ' overall IoU = %.2f\n' % (cum_I * 100. / cum_U) + print(results_str) + + +def get_transform(args): + transforms = [T.Resize(args.img_size, args.img_size), + T.ToTensor(), + T.Normalize(mean=[0.485, 0.456, 0.406], std=[0.229, 0.224, 0.225]) + ] + + return T.Compose(transforms) + + +def computeIoU(pred_seg, gd_seg): + I = np.sum(np.logical_and(pred_seg, gd_seg)) + U = np.sum(np.logical_or(pred_seg, gd_seg)) + + return I, U + + +def main(args): + device = torch.device(args.device) + dataset_test, _ = get_dataset(args.split, get_transform(args=args), args) + test_sampler = torch.utils.data.SequentialSampler(dataset_test) + data_loader_test = torch.utils.data.DataLoader(dataset_test, batch_size=1, + sampler=test_sampler, num_workers=args.workers) + print(args.model) + single_model = segmentation.__dict__[args.model](pretrained='',args=args) + checkpoint = torch.load(args.resume, map_location='cpu') + single_model.load_state_dict(checkpoint['model']) + model = single_model.to(device) + + if args.model != 'lavt_one': + model_class = BertModel + single_bert_model = model_class.from_pretrained(args.ck_bert) + # work-around for a transformers bug; need to update to a newer version of transformers to remove these two lines + if args.ddp_trained_weights: + single_bert_model.pooler = None + single_bert_model.load_state_dict(checkpoint['bert_model']) + bert_model = single_bert_model.to(device) + else: + bert_model = None + + evaluate(model, data_loader_test, bert_model, device=device) + + +if __name__ == "__main__": + from args import get_parser + parser = get_parser() + args = parser.parse_args() + print('Image size: {}'.format(str(args.img_size))) + main(args) diff --git a/LAVT-RIS/train_angle.py b/LAVT-RIS/train_angle.py new file mode 100644 index 0000000000000000000000000000000000000000..340fd1c888f289595cdab0d3a50c140b4c5ab0c9 --- /dev/null +++ b/LAVT-RIS/train_angle.py @@ -0,0 +1,597 @@ +import datetime +import os +import time + +import torch +import torch.utils.data +from torch import nn + +from functools import reduce +import operator +from bert.modeling_bert import BertModel + +import torchvision +from lib import segmentation + +import transforms as T +import utils +import numpy as np + +import torch.nn.functional as F + +import gc +from collections import OrderedDict +from torch.utils.tensorboard import SummaryWriter + + +def get_dataset(image_set, transform, args): + from data.dataset_refer_bert_rev import ReferDataset + ds = ReferDataset(args, + split=image_set, + image_transforms=transform, + target_transforms=None, + eval_mode=image_set == 'val' + ) + num_classes = 2 + + return ds, num_classes + + +# IoU calculation for validation +def IoU(pred, gt): + pred = pred.argmax(1) + + intersection = torch.sum(torch.mul(pred, gt)) + union = torch.sum(torch.add(pred, gt)) - intersection + + if intersection == 0 or union == 0: + iou = 0 + else: + iou = float(intersection) / float(union) + + return iou, intersection, union + + +def get_transform(args): + transforms = [T.Resize(args.img_size, args.img_size), + T.ToTensor(), + T.Normalize(mean=[0.485, 0.456, 0.406], std=[0.229, 0.224, 0.225]) + ] + + return T.Compose(transforms) + + +def criterion(input, target): + weight = torch.FloatTensor([0.9, 1.1]).cuda() + return nn.functional.cross_entropy(input, target, weight=weight) + +# def return_mask(metric_mask, B_): +# negative_mask = None + +# sim_mask = torch.zeros(B_, B_, device=metric_mask.device) +# n_pos = B_//2 + +# sim_mask.fill_diagonal_(1) # Set diagonal elements to 1 for all cases +# sim_mask.diagonal(offset=n_pos).fill_(1) +# sim_mask.diagonal(offset=-n_pos).fill_(1) + + +# return sim_mask, negative_mask + + +def return_mask(emb_distance, verb_mask=None): + B_, B_ = emb_distance.shape + positive_mask = torch.zeros_like(emb_distance) + positive_mask.fill_diagonal_(1) # Set diagonal elements to 1 for all cases + + if B_ < len(verb_mask): + # If B_ equals to 2*K (double the number of verb phrase) + for i in range(B_ // 2): + positive_mask[2 * i, 2 * i + 1] = 1 + positive_mask[2 * i + 1, 2 * i] = 1 + else: + # Process the case where we have a mix of sentences with and without verbs + i = 0 + while i < B_: + if verb_mask[i] == 1: + positive_mask[i, i + 1] = 1 + positive_mask[i + 1, i] = 1 + i += 2 + else: + i += 1 + negative_mask = torch.ones_like(emb_distance) - positive_mask + return positive_mask, negative_mask + + +def UniAngularContrastLoss(total_fq, verb_mask, alpha=0.5, verbonly=True, m=0.5, tau=0.05, args=None): + _, C, H, W = total_fq.shape + + if verbonly : + B = total_fq[verb_mask].shape[0] + emb = torch.mean(total_fq[verb_mask], dim=(-1, -2)).reshape(B, C) + assert emb.shape[0] % 2 == 0, f"Embedding count {emb.shape[0]} is not divisible by 2." + else : + emb = torch.mean(total_fq, dim=-1) + + B_ = emb.shape[0] + emb_i = emb.unsqueeze(1).repeat(1, B_, 1) # (B_, B_, C) + emb_j = emb.unsqueeze(0).repeat(B_, 1, 1) # (B_, B_, C) + sim = nn.CosineSimilarity(dim=-1, eps=1e-6) + sim_matrix = sim(emb_i, emb_j).reshape(B_, B_) # (B_, B_) + sim_matrix = torch.clamp(sim_matrix, min=-0.9999, max=0.9999) + + positive_mask, negative_mask = return_mask(sim_matrix, verb_mask) + if len(positive_mask) > 0 : + sim_matrix_with_margin = sim_matrix.clone() + sim_matrix_with_margin[positive_mask.bool()] = torch.cos(torch.acos(sim_matrix[positive_mask.bool()]) + m / 57.2958) + + logits = sim_matrix_with_margin / tau + exp_logits = torch.exp(logits) + pos_exp_logits = exp_logits * positive_mask.long() + pos_exp_logits = pos_exp_logits.sum(dim=-1) + + # print("pos_exp_logits: ", pos_exp_logits.shape) + total_exp_logits = exp_logits.sum(dim=-1) + positive_loss = -torch.log(pos_exp_logits / total_exp_logits) + angular_loss = positive_loss.mean() + + return angular_loss + else : + return torch.tensor(0.0, device=total_fq.device) + + + +def UniAngularLogitContrastLoss(total_fq, verb_mask, alpha=0.5, verbonly=True, m=0.5, tau=0.05, args=None): + epsilon = 1e-10 # Stability term for numerical issues + _, C, H, W = total_fq.shape + + # Calculate embeddings + if verbonly : + B = total_fq[verb_mask].shape[0] + emb = torch.mean(total_fq[verb_mask], dim=(-1, -2)).reshape(B, C) + assert emb.shape[0] % 2 == 0, f"Embedding count {emb.shape[0]} is not divisible by 2." + else : + emb = torch.mean(total_fq, dim=-1) + + B_ = emb.shape[0] + emb_i = emb.unsqueeze(1).repeat(1, B_, 1) # (B_, B_, C) + emb_j = emb.unsqueeze(0).repeat(B_, 1, 1) # (B_, B_, C) + + sim = nn.CosineSimilarity(dim=-1, eps=1e-6) + sim_matrix = sim(emb_i, emb_j).reshape(B_, B_) # (B_, B_) + sim_matrix = torch.clamp(sim_matrix, min=-0.9999, max=0.9999) + + margin_in_radians = m / 57.2958 # Convert degrees to radians + theta_matrix = (torch.pi / 2) - torch.acos(sim_matrix) + positive_mask, negative_mask = return_mask(sim_matrix, verb_mask) + + theta_with_margin = theta_matrix.clone() + theta_with_margin[positive_mask.bool()] -= margin_in_radians # Subtract margin directly for positives + + logits = theta_with_margin / tau # Scale with temperature + + # Compute exponential logits for softmax + exp_logits = torch.exp(logits) + # pos_exp_logits = (exp_logits * positive_mask).sum(dim=-1) # Positive term + pos_exp_logits = exp_logits * positive_mask + pos_exp_logits = pos_exp_logits.sum(dim=-1) + + # neg_exp_logits = (exp_logits * negative_mask).sum(dim=-1) # Negative term + # total_exp_logits = pos_exp_logits + neg_exp_logits + total_exp_logits = exp_logits.sum(dim=-1) + + # pos_exp_logits = pos_exp_logits + epsilon + # total_exp_logits = total_exp_logits + epsilon + + # Compute angular loss + loss = -torch.log(pos_exp_logits / total_exp_logits) + angular_loss = loss.mean() + + return angular_loss + +# def UniAngularContrastLoss(samples_with_pos, metric_mask, m=0.5, tau=0.05, verb_mask=None, verbonly=True, args=None): +# B_, C, H, W = samples_with_pos.shape + +# emb = torch.mean(samples_with_pos, dim=(-1, -2)).reshape(B_, C) +# if len(emb) > 0: +# sim = nn.CosineSimilarity(dim=-1, eps=1e-6) +# sim_matrix = sim(emb.unsqueeze(1), emb.unsqueeze(0)) # (B_, B_) +# sim_matrix = torch.clamp(sim_matrix, min=-0.9999, max=0.9999) + +# sim_mask, negative_mask = return_mask(emb, B_) +# assert sim_mask.shape == sim_matrix.shape, f"sim_mask shape {sim_mask.shape} is not equal to sim_matrix shape {sim_matrix.shape}." + +# # Apply margin to positive pairs +# sim_matrix_with_margin = sim_matrix.clone() +# sim_matrix_with_margin[sim_mask.bool()] = torch.cos(torch.acos(sim_matrix[sim_mask.bool()]) + m / 57.2958) + +# # Scale logits with temperature +# logits = sim_matrix_with_margin / tau + +# # Compute the softmax loss for all pairs +# exp_logits = torch.exp(logits) +# # print("exp_logits: ", exp_logits.shape) +# pos_exp_logits = exp_logits * sim_mask.long() +# pos_exp_logits = pos_exp_logits.sum(dim=-1) +# #print("pos_exp_logits: ", pos_exp_logits.shape) +# # print("pos_exp_logits: ", pos_exp_logits.shape) +# total_exp_logits = exp_logits.sum(dim=-1) +# positive_loss = -torch.log(pos_exp_logits / total_exp_logits) +# angular_loss = positive_loss.mean() + +# return angular_loss +# else : +# return torch.tensor(0.0, device=samples_with_pos.device) + + +def evaluate(model, data_loader, bert_model): + #print("current model : ", model) + model.eval() + metric_logger = utils.MetricLogger(delimiter=" ") + header = 'Test:' + total_its = 0 + acc_ious = 0 + + # evaluation variables + cum_I, cum_U = 0, 0 + eval_seg_iou_list = [.5, .6, .7, .8, .9] + seg_correct = np.zeros(len(eval_seg_iou_list), dtype=np.int32) + seg_total = 0 + mean_IoU = [] + + with torch.no_grad(): + for data in metric_logger.log_every(data_loader, 100, header): + total_its += 1 + image, target, sentences, attentions = data + image, target, sentences, attentions = \ + image.cuda(non_blocking=True),\ + target.cuda(non_blocking=True),\ + sentences.cuda(non_blocking=True),\ + attentions.cuda(non_blocking=True) + + sentences = sentences.squeeze(1) + attentions = attentions.squeeze(1) + + if bert_model is not None: + last_hidden_states = bert_model(sentences, attention_mask=attentions)[0] + embedding = last_hidden_states.permute(0, 2, 1) # (B, 768, N_l) to make Conv1d happy + attentions = attentions.unsqueeze(dim=-1) # (B, N_l, 1) + output = model(image, embedding, l_mask=attentions, is_train=False) + else: + sentences = sentences.squeeze(0).transpose(0, 1) + attentions = attentions.squeeze(0).transpose(0, 1) + image = torch.repeat_interleave(image, sentences.shape[0], dim=0) + target = torch.repeat_interleave(target, sentences.shape[0], dim=0) + output = model(image, sentences, l_mask=attentions, is_train=False) + + for i in range(output.shape[0]): + iou, I, U = IoU(output[i].unsqueeze(0), target[i]) + acc_ious += iou + mean_IoU.append(iou) + cum_I += I + cum_U += U + for n_eval_iou in range(len(eval_seg_iou_list)): + eval_seg_iou = eval_seg_iou_list[n_eval_iou] + seg_correct[n_eval_iou] += (iou >= eval_seg_iou) + seg_total += 1 + iou = acc_ious / seg_total + + mean_IoU = np.array(mean_IoU) + mIoU = np.mean(mean_IoU) + print('Final results:') + print('Mean IoU is %.2f\n' % (mIoU * 100.)) + results_str = '' + + precs = [] + for n_eval_iou in range(len(eval_seg_iou_list)): + results_str += ' precision@%s = %.2f\n' % \ + (str(eval_seg_iou_list[n_eval_iou]), seg_correct[n_eval_iou] * 100. / seg_total) + precs.append(seg_correct[n_eval_iou] * 100. / seg_total) + results_str += ' overall IoU = %.2f\n' % (cum_I * 100. / cum_U) + print(results_str) + + return 100 * iou, 100 * cum_I / cum_U, precs + + +def train_one_epoch(model, criterion, optimizer, data_loader, lr_scheduler, epoch, print_freq, + iterations, bert_model, metric_learning=False, args=None): + model.train() + metric_logger = utils.MetricLogger(delimiter=" ") + metric_logger.add_meter('lr', utils.SmoothedValue(window_size=1, fmt='{value}')) + header = 'Epoch: [{}]'.format(epoch) + train_loss = 0 + total_its = 0 + mlw = args.metric_loss_weight + metric_mode = args.metric_mode + if not metric_learning: + mlw = 0 + + for data in metric_logger.log_every(data_loader, print_freq, header): + #print("data : ", data) + total_its += 1 + if 'hardpos_only' in metric_mode : + image, target, sentences, attentions, pos_sent, pos_attn_mask = data + image, target, sentences, attentions, pos_sent, pos_attn_mask = \ + image.cuda(non_blocking=True),\ + target.cuda(non_blocking=True),\ + sentences.cuda(non_blocking=True),\ + attentions.cuda(non_blocking=True),\ + pos_sent.cuda(non_blocking=True),\ + pos_attn_mask.cuda(non_blocking=True) + + sentences = sentences.squeeze(1) + attentions = attentions.squeeze(1) + pos_sent = pos_sent.squeeze(1) + pos_attn_mask = pos_attn_mask.squeeze(1) + # print(image.shape, target.shape, sentences.shape, attentions.shape, pos_sent.shape, pos_attn_mask.shape) + + else : + image, target, sentences, attentions, pos_sent, pos_attn_mask, neg_sent, neg_attn_mask= data + image, target, sentences, attentions, pos_sent, pos_attn_mask, neg_sent, neg_attn_mask = \ + image.cuda(non_blocking=True),\ + target.cuda(non_blocking=True),\ + sentences.cuda(non_blocking=True),\ + attentions.cuda(non_blocking=True),\ + pos_sent.cuda(non_blocking=True),\ + pos_attn_mask.cuda(non_blocking=True),\ + neg_sent.cuda(non_blocking=True),\ + neg_attn_mask.cuda(non_blocking=True) + + sentences = sentences.squeeze(1) + attentions = attentions.squeeze(1) + pos_sent = pos_sent.squeeze(1) + pos_attn_mask = pos_attn_mask.squeeze(1) + neg_sent = neg_sent.squeeze(1) + neg_attn_mask = neg_attn_mask.squeeze(1) + + loss = 0 + metric_loss = 0 + + if bert_model is not None: + last_hidden_states = bert_model(sentences, attention_mask=attentions)[0] # (6, 10, 768) + embedding = last_hidden_states.permute(0, 2, 1) # (B, 768, N_l) to make Conv1d happy + attentions = attentions.unsqueeze(dim=-1) # (batch, N_l, 1) + output = model(image, embedding, l_mask=attentions) + + else: + assert pos_sent is not None, "pos_sent must be provided" + + pos_mask = pos_attn_mask.sum(dim=-1) > 0 # Boolean mask for positive samples + + verb_masks = [] + cl_masks = [] + images = [] + targets = [] + sentences_ = [] + attentions_ = [] + + for idx in range(len(image)) : + # Append original data + sentences_.append(sentences[idx]) + images.append(image[idx]) + targets.append(target[idx]) + attentions_.append(attentions[idx]) + + if pos_mask[idx]: + verb_masks.extend([1, 1]) + cl_masks.extend([1, 0]) + sentences_.append(pos_sent[idx]) + images.append(image[idx]) + targets.append(target[idx]) + attentions_.append(pos_attn_mask[idx]) + + else: + verb_masks.append(0) + cl_masks.append(1) + + sentences = torch.stack(sentences_) + image = torch.stack(images) + target = torch.stack(targets) + attentions = torch.stack(attentions_) + verb_masks = torch.tensor(verb_masks, dtype=torch.bool) + cl_masks = torch.tensor(cl_masks, dtype=torch.bool) + + # image = torch.cat([image, image[pos_mask]], dim=0) + # target = torch.cat([target, target[pos_mask]], dim=0) + # sentences = torch.cat([sentences, pos_sent[pos_mask]], dim=0) + # attentions = torch.cat([attentions, pos_attn_mask[pos_mask]], dim=0) + + # print(pos_mask, image.shape, target.shape, sentences.shape, attentions.shape) + + output, metric_tensors = model(image, sentences, l_mask=attentions) + + # print(output.shape, metric_tensors.shape, output[cl_masks].shape, target[cl_masks].shape) + + ce_loss = criterion(output[cl_masks], target[cl_masks]) # can't we just detach output and target? + + if metric_learning and sum(pos_mask) > 0: + # verbonly option + # metric_loss = UniAngularContrastLoss(metric_tensors, verb_masks, m=args.margin_value, tau=args.temperature, verbonly=True, args=args) + metric_loss = UniAngularLogitContrastLoss(metric_tensors, verb_masks, m=args.margin_value, tau=args.temperature, verbonly=True, args=args) + + loss = (ce_loss + metric_loss * mlw) / (1+mlw) + optimizer.zero_grad() # set_to_none=True is only available in pytorch 1.6+ + loss.backward() + optimizer.step() + lr_scheduler.step() + + torch.cuda.synchronize() + train_loss += loss.item() + iterations += 1 + metric_logger.update(loss=loss.item(), lr=optimizer.param_groups[0]["lr"]) + + del image, target, sentences, attentions, loss, output, data + if bert_model is not None: + del last_hidden_states, embedding + + gc.collect() + torch.cuda.empty_cache() + torch.cuda.synchronize() + + loss_log = { + 'loss': metric_logger.meters['loss'].global_avg + } + return iterations, loss_log + + + +def main(args): + writer = SummaryWriter('./experiments/{}/{}'.format("_".join([args.dataset, args.splitBy]), args.model_id)) + + dataset, num_classes = get_dataset("train", + get_transform(args=args), + args=args) + dataset_test, _ = get_dataset("val", + get_transform(args=args), + args=args) + + # batch sampler + print(f"local rank {args.local_rank} / global rank {utils.get_rank()} successfully built train dataset.") + num_tasks = utils.get_world_size() + global_rank = utils.get_rank() + train_sampler = torch.utils.data.distributed.DistributedSampler(dataset, num_replicas=num_tasks, rank=global_rank, + shuffle=True) + test_sampler = torch.utils.data.SequentialSampler(dataset_test) + + # data loader + data_loader = torch.utils.data.DataLoader( + dataset, batch_size=args.batch_size, + sampler=train_sampler, num_workers=args.workers, pin_memory=args.pin_mem, drop_last=True) + + data_loader_test = torch.utils.data.DataLoader( + dataset_test, batch_size=1, sampler=test_sampler, num_workers=args.workers) + + # model initialization + print(args.model) + model = segmentation.__dict__[args.model](pretrained=args.pretrained_swin_weights, + args=args) + model = torch.nn.SyncBatchNorm.convert_sync_batchnorm(model) + model.cuda() + model = torch.nn.parallel.DistributedDataParallel(model, device_ids=[args.local_rank], find_unused_parameters=True) + single_model = model.module + + if args.model != 'lavt_one': + model_class = BertModel + bert_model = model_class.from_pretrained(args.ck_bert) + bert_model.pooler = None # a work-around for a bug in Transformers = 3.0.2 that appears for DistributedDataParallel + bert_model.cuda() + bert_model = torch.nn.SyncBatchNorm.convert_sync_batchnorm(bert_model) + bert_model = torch.nn.parallel.DistributedDataParallel(bert_model, device_ids=[args.local_rank]) + single_bert_model = bert_model.module + else: + bert_model = None + single_bert_model = None + + # resume training + if args.resume: + checkpoint = torch.load(args.resume, map_location='cpu') + single_model.load_state_dict(checkpoint['model']) + if args.model != 'lavt_one': + single_bert_model.load_state_dict(checkpoint['bert_model']) + + # parameters to optimize + backbone_no_decay = list() + backbone_decay = list() + for name, m in single_model.backbone.named_parameters(): + if 'norm' in name or 'absolute_pos_embed' in name or 'relative_position_bias_table' in name: + backbone_no_decay.append(m) + else: + backbone_decay.append(m) + + if args.model != 'lavt_one': + params_to_optimize = [ + {'params': backbone_no_decay, 'weight_decay': 0.0}, + {'params': backbone_decay}, + {"params": [p for p in single_model.classifier.parameters() if p.requires_grad]}, + # the following are the parameters of bert + {"params": reduce(operator.concat, + [[p for p in single_bert_model.encoder.layer[i].parameters() + if p.requires_grad] for i in range(10)])}, + ] + else: + params_to_optimize = [ + {'params': backbone_no_decay, 'weight_decay': 0.0}, + {'params': backbone_decay}, + {"params": [p for p in single_model.classifier.parameters() if p.requires_grad]}, + # the following are the parameters of bert + {"params": reduce(operator.concat, + [[p for p in single_model.text_encoder.encoder.layer[i].parameters() + if p.requires_grad] for i in range(10)]), 'lr': args.lr/10}, + ] + + # optimizer + optimizer = torch.optim.AdamW(params_to_optimize, + lr=args.lr, + weight_decay=args.weight_decay, + amsgrad=args.amsgrad + ) + + # learning rate scheduler + lr_scheduler = torch.optim.lr_scheduler.LambdaLR(optimizer, + lambda x: (1 - x / (len(data_loader) * args.epochs)) ** 0.9) + + # housekeeping + start_time = time.time() + iterations = 0 + best_oIoU = -0.1 + + # resume training (optimizer, lr scheduler, and the epoch) + if args.resume: + optimizer.load_state_dict(checkpoint['optimizer']) + lr_scheduler.load_state_dict(checkpoint['lr_scheduler']) + resume_epoch = checkpoint['epoch'] + else: + resume_epoch = -999 + + # training loops + for epoch in range(max(0, resume_epoch+1), args.epochs): + data_loader.sampler.set_epoch(epoch) + itrs_temp, loss_log = train_one_epoch(model, criterion, optimizer, data_loader, lr_scheduler, epoch, args.print_freq, + iterations, bert_model, metric_learning=args.metric_learning, args=args) + iou, overallIoU, precs = evaluate(model, data_loader_test, bert_model) + + print('Average object IoU {}'.format(iou)) + print('Overall IoU {}'.format(overallIoU)) + save_checkpoint = (best_oIoU < overallIoU) + if save_checkpoint: + print('Better epoch: {}\n'.format(epoch)) + if single_bert_model is not None: + dict_to_save = {'model': single_model.state_dict(), 'bert_model': single_bert_model.state_dict(), + 'optimizer': optimizer.state_dict(), 'epoch': epoch, 'args': args, + 'lr_scheduler': lr_scheduler.state_dict()} + else: + dict_to_save = {'model': single_model.state_dict(), + 'optimizer': optimizer.state_dict(), 'epoch': epoch, 'args': args, + 'lr_scheduler': lr_scheduler.state_dict()} + + utils.save_on_master(dict_to_save, os.path.join(args.output_dir, + 'model_best_{}.pth'.format(args.model_id))) + best_oIoU = overallIoU + + + if utils.is_main_process(): + writer.add_scalar('val/mIoU', iou, epoch) + writer.add_scalar('val/oIoU', overallIoU, epoch) + writer.add_scalar('val/Prec/50', precs[0], epoch) + writer.add_scalar('val/Prec/60', precs[1], epoch) + writer.add_scalar('val/Prec/70', precs[2], epoch) + writer.add_scalar('val/Prec/80', precs[3], epoch) + writer.add_scalar('val/Prec/90', precs[4], epoch) + writer.add_scalar('train/loss', loss_log['loss'], epoch) + + writer.flush() + + # summarize + total_time = time.time() - start_time + total_time_str = str(datetime.timedelta(seconds=int(total_time))) + print('Training time {}'.format(total_time_str)) + + +if __name__ == "__main__": + from args import get_parser + parser = get_parser() + args = parser.parse_args() + # set up distributed learning + utils.init_distributed_mode(args) + print('Image size: {}'.format(str(args.img_size))) + main(args) diff --git a/LAVT-RIS/train_refzom.py b/LAVT-RIS/train_refzom.py new file mode 100644 index 0000000000000000000000000000000000000000..ffb644e6f5a6ad7ef19d7c29b082cea210d138f3 --- /dev/null +++ b/LAVT-RIS/train_refzom.py @@ -0,0 +1,421 @@ +import datetime +import os +import time + +import torch +import torch.utils.data +from torch import nn + +from functools import reduce +import operator +from bert.modeling_bert import BertModel + +import torchvision +from lib import segmentation + +import transforms as T +import utils +import numpy as np + +import torch.nn.functional as F +from data.dataset_refer_zom import Referzom_Dataset, Refzom_DistributedSampler +from data.dataset_refer_bert_rev import ReferDataset +import gc +from collections import OrderedDict +from torch.utils.tensorboard import SummaryWriter + + +def get_dataset(image_set, transform, args, eval_mode=False): + if args.dataset == 'ref-zom': + ds = Referzom_Dataset(args, + split=image_set, + image_transforms=transform, + target_transforms=None, + eval_mode=eval_mode) + else : + ds = ReferDataset(args, + split=image_set, + image_transforms=transform, + target_transforms=None, + eval_mode=image_set == 'val' + ) + num_classes = 2 + + return ds, num_classes + + +# IoU calculation for validation +# def IoU(pred, gt): +# pred = pred.argmax(1) + +# intersection = torch.sum(torch.mul(pred, gt)) +# union = torch.sum(torch.add(pred, gt)) - intersection + +# if intersection == 0 or union == 0: +# iou = 0 +# else: +# iou = float(intersection) / float(union) + +# return iou, intersection, union + +# def computeIoU(pred_seg, gd_seg): +# I = np.sum(np.logical_and(pred_seg, gd_seg)) +# U = np.sum(np.logical_or(pred_seg, gd_seg)) + +# return I, U + +def IoU(pred, gt): + pred = pred.argmax(1) + + intersection = torch.sum(torch.mul(pred, gt)) + union = torch.sum(torch.add(pred, gt)) - intersection + + if intersection == 0 or union == 0: + iou = 0 + else: + iou = float(intersection) / float(union) + + return iou, intersection, union + + +def get_transform(args): + transforms = [T.Resize(args.img_size, args.img_size), + T.ToTensor(), + T.Normalize(mean=[0.485, 0.456, 0.406], std=[0.229, 0.224, 0.225]) + ] + + return T.Compose(transforms) + + +def criterion(input, target): + weight = torch.FloatTensor([0.9, 1.1]).cuda() + return nn.functional.cross_entropy(input, target, weight=weight) + + +def evaluate(model, data_loader, bert_model): + #print("current model : ", model) + model.eval() + metric_logger = utils.MetricLogger(delimiter=" ") + header = 'Test:' + total_its = 0 + acc_ious = 0 + + # evaluation variables + cum_I, cum_U = 0, 0 + eval_seg_iou_list = [.5, .6, .7, .8, .9] + seg_correct = np.zeros(len(eval_seg_iou_list), dtype=np.int32) + seg_total = 0 + mean_IoU = [] + mean_acc = [] + + with torch.no_grad(): + for data in metric_logger.log_every(data_loader, 100, header): + total_its += 1 + # Unpack data + image, target, source_type, sentences, attentions = data + image, target, sentences, attentions = ( + image.cuda(non_blocking=True), + target.cuda(non_blocking=True), + sentences.cuda(non_blocking=True), + attentions.cuda(non_blocking=True) + ) + + # Squeeze unnecessary dimensions + sentences = sentences.squeeze(-1) + attentions = attentions.squeeze(-1) + + # Model inference + if bert_model is not None: + last_hidden_states = bert_model(sentences, attention_mask=attentions)[0] + embedding = last_hidden_states.permute(0, 2, 1) # [B, N, 768] -> [B, 768, N] + attentions = attentions.unsqueeze(-1) # [B, N] -> [B, N, 1] + output = model(image, embedding, l_mask=attentions) + else: + output = model(image, sentences, l_mask=attentions, is_train=False) + + + # Zero target case + if source_type[0] == 'zero': + pred = output.argmax(1) + incorrect_num = torch.sum(pred).item() # Count non-zero predictions + acc = 1 if incorrect_num == 0 else 0 + mean_acc.append(acc) + else: + # Non-zero target case + this_iou, I, U = IoU(output, target) # Use the provided IoU function + mean_IoU.append(this_iou) + cum_I += I + cum_U += U + + for n_eval_iou in range(len(eval_seg_iou_list)): + eval_seg_iou = eval_seg_iou_list[n_eval_iou] + seg_correct[n_eval_iou] += (this_iou >= eval_seg_iou) + + seg_total += 1 + + mIoU = np.mean(mean_IoU) + mean_acc = np.mean(mean_acc) + print('Final results:') + print('Mean IoU is %.2f\n' % (mIoU * 100.)) + + results_str = '' + precs = [] + for n_eval_iou in range(len(eval_seg_iou_list)): + results_str += ' precision@%s = %.2f\n' % \ + (str(eval_seg_iou_list[n_eval_iou]), seg_correct[n_eval_iou] * 100. / seg_total) + precs.append(seg_correct[n_eval_iou] * 100. / seg_total) + results_str += ' overall IoU = %.2f\n' % (cum_I * 100. / cum_U) + results_str += ' mean IoU = %.2f\n' % (mIoU * 100.) + print(results_str) + if args.dataset == 'ref-zom': + print('Mean accuracy for one-to-zero sample is %.2f\n' % (mean_acc*100)) + + return mIoU, 100 * cum_I / cum_U, precs + + +def train_one_epoch(model, criterion, optimizer, data_loader, lr_scheduler, epoch, print_freq, + iterations, bert_model, metric_learning=False, args=None): + model.train() + metric_logger = utils.MetricLogger(delimiter=" ") + metric_logger.add_meter('lr', utils.SmoothedValue(window_size=1, fmt='{value}')) + header = 'Epoch: [{}]'.format(epoch) + train_loss = 0 + total_its = 0 + mlw = args.metric_loss_weight + metric_mode = args.metric_mode + if not metric_learning: + mlw = 0 + + for data in metric_logger.log_every(data_loader, print_freq, header): + #print("data : ", data) + total_its += 1 + + # Ref-Zom Repro + image, target, source_type, sentences, attentions = data + source_type = np.array(source_type) + target_flag = np.where(source_type=='zero', 0, 1) + target_flag = torch.tensor(target_flag) + + image, target, sentences, target_flag, attentions = image.cuda(non_blocking=True),\ + target.cuda(non_blocking=True),\ + sentences.cuda(non_blocking=True),\ + target_flag.cuda(non_blocking=True),\ + attentions.cuda(non_blocking=True) + + sentences = sentences.squeeze(1) + attentions = attentions.squeeze(1) + + if bert_model is not None: + last_hidden_states = bert_model(sentences, attention_mask=attentions)[0] # (6, 10, 768) + embedding = last_hidden_states.permute(0, 2, 1) # (B, 768, N_l) to make Conv1d happy + attentions = attentions.unsqueeze(dim=-1) # (batch, N_l, 1) + output = model(image, embedding, l_mask=attentions) + + else: + output, _ = model(image, sentences, l_mask=attentions) + + + loss = criterion(output, target) + optimizer.zero_grad() # set_to_none=True is only available in pytorch 1.6+ + loss.backward() + optimizer.step() + lr_scheduler.step() + + torch.cuda.synchronize() + train_loss += loss.item() + iterations += 1 + metric_logger.update(loss=loss.item(), lr=optimizer.param_groups[0]["lr"]) + + del image, target, sentences, attentions, loss, output, data + if bert_model is not None: + del last_hidden_states, embedding + + gc.collect() + torch.cuda.empty_cache() + torch.cuda.synchronize() + + loss_log = { + 'loss': metric_logger.meters['loss'].global_avg + } + return iterations, loss_log + + + +def main(args): + writer = SummaryWriter('./experiments/{}/{}'.format("_".join([args.dataset, args.splitBy]), args.model_id)) + + dataset, num_classes = get_dataset("train", + get_transform(args=args), + args=args, + eval_mode=False) + dataset_test, _ = get_dataset(args.split, + get_transform(args=args), + args=args, + eval_mode=True) + + # batch sampler + print(f"local rank {args.local_rank} / global rank {utils.get_rank()} successfully built train dataset.") + num_tasks = utils.get_world_size() + global_rank = utils.get_rank() + + if args.dataset == 'ref-zom': + train_sampler = Refzom_DistributedSampler(dataset, num_replicas=num_tasks, rank=global_rank, + shuffle=True) + else: + train_sampler = torch.utils.data.distributed.DistributedSampler(dataset, num_replicas=num_tasks, rank=global_rank, + shuffle=True) + test_sampler = torch.utils.data.SequentialSampler(dataset_test) + + # data loader + data_loader = torch.utils.data.DataLoader( + dataset, batch_size=args.batch_size, + sampler=train_sampler, num_workers=args.workers, pin_memory=args.pin_mem, drop_last=True) + + data_loader_test = torch.utils.data.DataLoader( + dataset_test, batch_size=1, sampler=test_sampler, num_workers=args.workers) + + # model initialization + print(args.model) + model = segmentation.__dict__[args.model](pretrained=args.pretrained_swin_weights, + args=args) + model = torch.nn.SyncBatchNorm.convert_sync_batchnorm(model) + model.cuda() + model = torch.nn.parallel.DistributedDataParallel(model, device_ids=[args.local_rank], find_unused_parameters=True) + single_model = model.module + + if args.model != 'lavt_one': + model_class = BertModel + bert_model = model_class.from_pretrained(args.ck_bert) + bert_model.pooler = None # a work-around for a bug in Transformers = 3.0.2 that appears for DistributedDataParallel + bert_model.cuda() + bert_model = torch.nn.SyncBatchNorm.convert_sync_batchnorm(bert_model) + bert_model = torch.nn.parallel.DistributedDataParallel(bert_model, device_ids=[args.local_rank]) + single_bert_model = bert_model.module + else: + bert_model = None + single_bert_model = None + + # resume training + if args.resume: + checkpoint = torch.load(args.resume, map_location='cpu') + single_model.load_state_dict(checkpoint['model']) + if args.model != 'lavt_one': + single_bert_model.load_state_dict(checkpoint['bert_model']) + + # parameters to optimize + backbone_no_decay = list() + backbone_decay = list() + for name, m in single_model.backbone.named_parameters(): + if 'norm' in name or 'absolute_pos_embed' in name or 'relative_position_bias_table' in name: + backbone_no_decay.append(m) + else: + backbone_decay.append(m) + + if args.model != 'lavt_one': + params_to_optimize = [ + {'params': backbone_no_decay, 'weight_decay': 0.0}, + {'params': backbone_decay}, + {"params": [p for p in single_model.classifier.parameters() if p.requires_grad]}, + # the following are the parameters of bert + {"params": reduce(operator.concat, + [[p for p in single_bert_model.encoder.layer[i].parameters() + if p.requires_grad] for i in range(10)])}, + ] + else: + params_to_optimize = [ + {'params': backbone_no_decay, 'weight_decay': 0.0}, + {'params': backbone_decay}, + {"params": [p for p in single_model.classifier.parameters() if p.requires_grad]}, + # the following are the parameters of bert + {"params": reduce(operator.concat, + [[p for p in single_model.text_encoder.encoder.layer[i].parameters() + if p.requires_grad] for i in range(10)])}, + ] + + # optimizer + optimizer = torch.optim.AdamW(params_to_optimize, + lr=args.lr, + weight_decay=args.weight_decay, + amsgrad=args.amsgrad + ) + + # learning rate scheduler + lr_scheduler = torch.optim.lr_scheduler.LambdaLR(optimizer, + lambda x: (1 - x / (len(data_loader) * args.epochs)) ** 0.9) + + # housekeeping + start_time = time.time() + iterations = 0 + best_oIoU = -0.1 + + # resume training (optimizer, lr scheduler, and the epoch) + if args.resume: + optimizer.load_state_dict(checkpoint['optimizer']) + lr_scheduler.load_state_dict(checkpoint['lr_scheduler']) + resume_epoch = checkpoint['epoch'] + else: + resume_epoch = -999 + + # training loops + for epoch in range(max(0, resume_epoch+1), args.epochs): + data_loader.sampler.set_epoch(epoch) + itrs_temp, loss_log = train_one_epoch(model, criterion, optimizer, data_loader, lr_scheduler, epoch, args.print_freq, + iterations, bert_model, metric_learning=args.metric_learning, args=args) + iou, overallIoU, precs = evaluate(model, data_loader_test, bert_model) + + print('Average object IoU {}'.format(iou)) + print('Overall IoU {}'.format(overallIoU)) + save_checkpoint = (best_oIoU < overallIoU) + if save_checkpoint: + print('Better epoch: {}\n'.format(epoch)) + if single_bert_model is not None: + dict_to_save = {'model': single_model.state_dict(), 'bert_model': single_bert_model.state_dict(), + 'optimizer': optimizer.state_dict(), 'epoch': epoch, 'args': args, + 'lr_scheduler': lr_scheduler.state_dict()} + else: + dict_to_save = {'model': single_model.state_dict(), + 'optimizer': optimizer.state_dict(), 'epoch': epoch, 'args': args, + 'lr_scheduler': lr_scheduler.state_dict()} + + utils.save_on_master(dict_to_save, os.path.join(args.output_dir, + 'model_best_{}.pth'.format(args.model_id))) + best_oIoU = overallIoU + + + if utils.is_main_process(): + writer.add_scalar('val/mIoU', iou, epoch) + writer.add_scalar('val/oIoU', overallIoU, epoch) + writer.add_scalar('val/Prec/50', precs[0], epoch) + writer.add_scalar('val/Prec/60', precs[1], epoch) + writer.add_scalar('val/Prec/70', precs[2], epoch) + writer.add_scalar('val/Prec/80', precs[3], epoch) + writer.add_scalar('val/Prec/90', precs[4], epoch) + writer.add_scalar('train/loss', loss_log['loss'], epoch) + + writer.flush() + + # summarize + total_time = time.time() - start_time + total_time_str = str(datetime.timedelta(seconds=int(total_time))) + print('Training time {}'.format(total_time_str)) + + +if __name__ == "__main__": + from args import get_parser + parser = get_parser() + args = parser.parse_args() + # set up distributed learning + + if "LOCAL_RANK" in os.environ: + local_rank = int(os.environ["LOCAL_RANK"]) + else: + local_rank = 0 # Default value for non-distributed mode + + print(f"Local Rank: {local_rank}, World Size: {os.environ.get('WORLD_SIZE', '1')}") + + utils.init_distributed_mode(args) + print('Image size: {}'.format(str(args.img_size))) + print('metric learning flag : ', args.metric_learning) + + print(args) + main(args) diff --git a/LAVT-RIS/train_refzom_angle.py b/LAVT-RIS/train_refzom_angle.py new file mode 100644 index 0000000000000000000000000000000000000000..537e0e3f7c265b7bb66952f1519fcc79d8677a7f --- /dev/null +++ b/LAVT-RIS/train_refzom_angle.py @@ -0,0 +1,603 @@ +import datetime +import os +import time + +import torch +import torch.utils.data +from torch import nn + +from functools import reduce +import operator +from bert.modeling_bert import BertModel + +import torchvision +from lib import segmentation + +import transforms as T +import utils +import numpy as np + +import torch.nn.functional as F +from data.dataset_refer_zom import Referzom_Dataset, Refzom_DistributedSampler +from data.dataset_refer_bert_rev import ReferDataset +import gc +from collections import OrderedDict +from torch.utils.tensorboard import SummaryWriter + + +def get_dataset(image_set, transform, args, eval_mode=False): + if args.dataset == 'ref-zom': + ds = Referzom_Dataset(args, + split=image_set, + image_transforms=transform, + target_transforms=None, + eval_mode=eval_mode) + else : + ds = ReferDataset(args, + split=image_set, + image_transforms=transform, + target_transforms=None, + eval_mode=image_set == 'val' + ) + num_classes = 2 + + return ds, num_classes + + +# IoU calculation for validation +# def IoU(pred, gt): +# pred = pred.argmax(1) + +# intersection = torch.sum(torch.mul(pred, gt)) +# union = torch.sum(torch.add(pred, gt)) - intersection + +# if intersection == 0 or union == 0: +# iou = 0 +# else: +# iou = float(intersection) / float(union) + +# return iou, intersection, union + +def IoU(pred, gt): + pred = pred.argmax(1) + + intersection = torch.sum(torch.mul(pred, gt)) + union = torch.sum(torch.add(pred, gt)) - intersection + + if intersection == 0 or union == 0: + iou = 0 + else: + iou = float(intersection) / float(union) + + return iou, intersection, union + + +def get_transform(args): + transforms = [T.Resize(args.img_size, args.img_size), + T.ToTensor(), + T.Normalize(mean=[0.485, 0.456, 0.406], std=[0.229, 0.224, 0.225]) + ] + + return T.Compose(transforms) + + +def criterion(input, target): + weight = torch.FloatTensor([0.9, 1.1]).cuda() + return nn.functional.cross_entropy(input, target, weight=weight) + + + + +def return_mask(emb_distance, verb_mask=None): + B_, B_ = emb_distance.shape + positive_mask = torch.zeros_like(emb_distance) + positive_mask.fill_diagonal_(1) # Set diagonal elements to 1 for all cases + + if B_ < len(verb_mask): + # If B_ equals to 2*K (double the number of verb phrase) + for i in range(B_ // 2): + positive_mask[2 * i, 2 * i + 1] = 1 + positive_mask[2 * i + 1, 2 * i] = 1 + else: + # Process the case where we have a mix of sentences with and without verbs + i = 0 + while i < B_: + if verb_mask[i] == 1: + positive_mask[i, i + 1] = 1 + positive_mask[i + 1, i] = 1 + i += 2 + else: + i += 1 + negative_mask = torch.ones_like(emb_distance) - positive_mask + return positive_mask, negative_mask + + +def UniAngularContrastLoss(total_fq, verb_mask, alpha=0.5, verbonly=True, m=0.5, tau=0.05, args=None): + _, C, H, W = total_fq.shape + + if verbonly : + B = total_fq[verb_mask].shape[0] + emb = torch.mean(total_fq[verb_mask], dim=(-1, -2)).reshape(B, C) + assert emb.shape[0] % 2 == 0, f"Embedding count {emb.shape[0]} is not divisible by 2." + else : + emb = torch.mean(total_fq, dim=-1) + + B_ = emb.shape[0] + emb_i = emb.unsqueeze(1).repeat(1, B_, 1) # (B_, B_, C) + emb_j = emb.unsqueeze(0).repeat(B_, 1, 1) # (B_, B_, C) + sim = nn.CosineSimilarity(dim=-1, eps=1e-6) + sim_matrix = sim(emb_i, emb_j).reshape(B_, B_) # (B_, B_) + sim_matrix = torch.clamp(sim_matrix, min=-0.9999, max=0.9999) + + positive_mask, negative_mask = return_mask(sim_matrix, verb_mask) + if len(positive_mask) > 0 : + sim_matrix_with_margin = sim_matrix.clone() + sim_matrix_with_margin[positive_mask.bool()] = torch.cos(torch.acos(sim_matrix[positive_mask.bool()]) + m / 57.2958) + + logits = sim_matrix_with_margin / tau + exp_logits = torch.exp(logits) + pos_exp_logits = exp_logits * positive_mask.long() + pos_exp_logits = pos_exp_logits.sum(dim=-1) + + # print("pos_exp_logits: ", pos_exp_logits.shape) + total_exp_logits = exp_logits.sum(dim=-1) + positive_loss = -torch.log(pos_exp_logits / total_exp_logits) + angular_loss = positive_loss.mean() + + return angular_loss + else : + return torch.tensor(0.0, device=total_fq.device) + + + +def UniAngularLogitContrastLoss(total_fq, verb_mask, alpha=0.5, verbonly=True, m=0.5, tau=0.05, args=None): + epsilon = 1e-10 # Stability term for numerical issues + _, C, H, W = total_fq.shape + + # Calculate embeddings + if verbonly : + B = total_fq[verb_mask].shape[0] + emb = torch.mean(total_fq[verb_mask], dim=(-1, -2)).reshape(B, C) + assert emb.shape[0] % 2 == 0, f"Embedding count {emb.shape[0]} is not divisible by 2." + else : + emb = torch.mean(total_fq, dim=-1) + + B_ = emb.shape[0] + emb_i = emb.unsqueeze(1).repeat(1, B_, 1) # (B_, B_, C) + emb_j = emb.unsqueeze(0).repeat(B_, 1, 1) # (B_, B_, C) + + sim = nn.CosineSimilarity(dim=-1, eps=1e-6) + sim_matrix = sim(emb_i, emb_j).reshape(B_, B_) # (B_, B_) + sim_matrix = torch.clamp(sim_matrix, min=-0.9999, max=0.9999) + + margin_in_radians = m / 57.2958 # Convert degrees to radians + theta_matrix = (torch.pi / 2) - torch.acos(sim_matrix) + positive_mask, negative_mask = return_mask(sim_matrix, verb_mask) + + theta_with_margin = theta_matrix.clone() + theta_with_margin[positive_mask.bool()] -= margin_in_radians # Subtract margin directly for positives + + logits = theta_with_margin / tau # Scale with temperature + + # Compute exponential logits for softmax + exp_logits = torch.exp(logits) + # pos_exp_logits = (exp_logits * positive_mask).sum(dim=-1) # Positive term + pos_exp_logits = exp_logits * positive_mask + pos_exp_logits = pos_exp_logits.sum(dim=-1) + + # neg_exp_logits = (exp_logits * negative_mask).sum(dim=-1) # Negative term + # total_exp_logits = pos_exp_logits + neg_exp_logits + total_exp_logits = exp_logits.sum(dim=-1) + + # pos_exp_logits = pos_exp_logits + epsilon + # total_exp_logits = total_exp_logits + epsilon + + # Compute angular loss + loss = -torch.log(pos_exp_logits / total_exp_logits) + angular_loss = loss.mean() + + return angular_loss + + + +def evaluate(model, data_loader, bert_model): + #print("current model : ", model) + model.eval() + metric_logger = utils.MetricLogger(delimiter=" ") + header = 'Test:' + total_its = 0 + acc_ious = 0 + + # evaluation variables + cum_I, cum_U = 0, 0 + eval_seg_iou_list = [.5, .6, .7, .8, .9] + seg_correct = np.zeros(len(eval_seg_iou_list), dtype=np.int32) + seg_total = 0 + mean_IoU = [] + mean_acc = [] + + with torch.no_grad(): + for data in metric_logger.log_every(data_loader, 100, header): + total_its += 1 + # Unpack data + image, target, source_type, sentences, attentions = data + image, target, sentences, attentions = ( + image.cuda(non_blocking=True), + target.cuda(non_blocking=True), + sentences.cuda(non_blocking=True), + attentions.cuda(non_blocking=True) + ) + + # Squeeze unnecessary dimensions + sentences = sentences.squeeze(-1) + attentions = attentions.squeeze(-1) + + # Model inference + if bert_model is not None: + last_hidden_states = bert_model(sentences, attention_mask=attentions)[0] + embedding = last_hidden_states.permute(0, 2, 1) # [B, N, 768] -> [B, 768, N] + attentions = attentions.unsqueeze(-1) # [B, N] -> [B, N, 1] + output = model(image, embedding, l_mask=attentions) + else: + output = model(image, sentences, l_mask=attentions, is_train=False) + + + # Zero target case + if source_type[0] == 'zero': + pred = output.argmax(1) + incorrect_num = torch.sum(pred).item() # Count non-zero predictions + acc = 1 if incorrect_num == 0 else 0 + mean_acc.append(acc) + else: + # Non-zero target case + this_iou, I, U = IoU(output, target) # Use the provided IoU function + mean_IoU.append(this_iou) + cum_I += I + cum_U += U + + for n_eval_iou in range(len(eval_seg_iou_list)): + eval_seg_iou = eval_seg_iou_list[n_eval_iou] + seg_correct[n_eval_iou] += (this_iou >= eval_seg_iou) + + seg_total += 1 + + mIoU = np.mean(mean_IoU) + mean_acc = np.mean(mean_acc) + print('Final results:') + print('Mean IoU is %.2f\n' % (mIoU * 100.)) + + results_str = '' + precs = [] + for n_eval_iou in range(len(eval_seg_iou_list)): + results_str += ' precision@%s = %.2f\n' % \ + (str(eval_seg_iou_list[n_eval_iou]), seg_correct[n_eval_iou] * 100. / seg_total) + precs.append(seg_correct[n_eval_iou] * 100. / seg_total) + results_str += ' overall IoU = %.2f\n' % (cum_I * 100. / cum_U) + results_str += ' mean IoU = %.2f\n' % (mIoU * 100.) + print(results_str) + if args.dataset == 'ref-zom': + print('Mean accuracy for one-to-zero sample is %.2f\n' % (mean_acc*100)) + + return mIoU, 100 * cum_I / cum_U, precs + + +def train_one_epoch(model, criterion, optimizer, data_loader, lr_scheduler, epoch, print_freq, + iterations, bert_model, metric_learning=False, args=None): + model.train() + metric_logger = utils.MetricLogger(delimiter=" ") + metric_logger.add_meter('lr', utils.SmoothedValue(window_size=1, fmt='{value}')) + header = 'Epoch: [{}]'.format(epoch) + train_loss = 0 + total_its = 0 + mlw = args.metric_loss_weight + metric_mode = args.metric_mode + if not metric_learning: + mlw = 0 + + for data in metric_logger.log_every(data_loader, print_freq, header): + #print("data : ", data) + total_its += 1 + + # Ref-Zom Repro + image, target, source_type, sentences, attentions, pos_sent, pos_attn_mask, pos_type = data + + source_type = np.array(source_type) + target_flag = torch.tensor(np.where(source_type == 'zero', 0, 1)) + if args.addzero : + hardpos_flag = torch.tensor(np.where(pos_type == 'hardpos', 1, 0)) + else : + # default option for training : only include one, many targets! + hardpos_flag = torch.tensor(np.where((source_type != 'zero') & (pos_type == 'hardpos'), 1, 0)) + + + sentences = sentences.squeeze(1) + attentions = attentions.squeeze(1) + pos_sent = pos_sent.squeeze(1) + pos_attn_mask = pos_attn_mask.squeeze(1) + + + ## ver 1 : hardpos flag outside the model + verb_masks = [] + cl_masks = [] + images = [] + targets = [] + sentences_ = [] + attentions_ = [] + + for idx in range(len(image)) : + # Append original data + sentences_.append(sentences[idx]) + images.append(image[idx]) + targets.append(target[idx]) + attentions_.append(attentions[idx]) + + if hardpos_flag[idx] : + verb_masks.extend([1, 1]) + cl_masks.extend([1, 0]) + sentences_.append(pos_sent[idx]) + images.append(image[idx]) + targets.append(target[idx]) + attentions_.append(pos_attn_mask[idx]) + else: + verb_masks.append(0) + cl_masks.append(1) + + image, target, sentences, attentions, verb_masks, cl_masks = \ + torch.stack(images).cuda(non_blocking=True),\ + torch.stack(targets).cuda(non_blocking=True),\ + torch.stack(sentences_).cuda(non_blocking=True),\ + torch.stack(attentions_).cuda(non_blocking=True),\ + torch.tensor(verb_masks, dtype=torch.bool, device='cuda'),\ + torch.tensor(cl_masks, dtype=torch.bool, device='cuda') + + + loss = 0 + metric_loss = 0 + + if bert_model is not None: + last_hidden_states = bert_model(sentences, attention_mask=attentions)[0] # (6, 10, 768) + embedding = last_hidden_states.permute(0, 2, 1) # (B, 768, N_l) to make Conv1d happy + attentions = attentions.unsqueeze(dim=-1) # (batch, N_l, 1) + output = model(image, embedding, l_mask=attentions) + + else: + output, metric_tensors = model(image, sentences, l_mask=attentions) + + ce_loss = criterion(output[cl_masks], target[cl_masks]) + + + if metric_learning: + hardpos_count = sum(hardpos_flag) + divn = 1 + if hardpos_count >= 3: + metric_loss = UniAngularLogitContrastLoss(metric_tensors, verb_masks, m=args.margin_value, tau=args.temperature, verbonly=True, args=args) + divn+=mlw # (1+mlw) + else: + metric_loss = 0 + else: + metric_loss = 0 + divn = 1 + + # if metric_learning and sum(hardpos_flag) > 0 : + # metric_loss = UniAngularLogitContrastLoss(metric_tensors, verb_masks, m=args.margin_value, tau=args.temperature, verbonly=True, args=args) + + loss = (ce_loss + metric_loss * mlw) / divn + optimizer.zero_grad() # set_to_none=True is only available in pytorch 1.6+ + loss.backward() + optimizer.step() + lr_scheduler.step() + + torch.cuda.synchronize() + train_loss += loss.item() + iterations += 1 + metric_logger.update(loss=loss.item(), lr=optimizer.param_groups[0]["lr"]) + + del image, target, sentences, attentions, loss, output, data + if bert_model is not None: + del last_hidden_states, embedding + + gc.collect() + torch.cuda.empty_cache() + torch.cuda.synchronize() + + loss_log = { + 'loss': metric_logger.meters['loss'].global_avg + } + return iterations, loss_log + + + +def main(args): + writer = SummaryWriter('./experiments/{}/{}'.format("_".join([args.dataset, args.splitBy]), args.model_id)) + + dataset, num_classes = get_dataset("train", + get_transform(args=args), + args=args, + eval_mode=False) + dataset_test, _ = get_dataset(args.split, + get_transform(args=args), + args=args, + eval_mode=True) + + # batch sampler + print(f"local rank {args.local_rank} / global rank {utils.get_rank()} successfully built train dataset.") + num_tasks = utils.get_world_size() + global_rank = utils.get_rank() + + if args.dataset == 'ref-zom': + train_sampler = Refzom_DistributedSampler(dataset, num_replicas=num_tasks, rank=global_rank, + shuffle=True) + else: + train_sampler = torch.utils.data.distributed.DistributedSampler(dataset, num_replicas=num_tasks, rank=global_rank, + shuffle=True) + test_sampler = torch.utils.data.SequentialSampler(dataset_test) + + # data loader + data_loader = torch.utils.data.DataLoader( + dataset, batch_size=args.batch_size, + sampler=train_sampler, num_workers=args.workers, pin_memory=args.pin_mem, drop_last=True) + + data_loader_test = torch.utils.data.DataLoader( + dataset_test, batch_size=1, sampler=test_sampler, num_workers=args.workers) + + # model initialization + print(args.model) + model = segmentation.__dict__[args.model](pretrained=args.pretrained_swin_weights, + args=args) + model = torch.nn.SyncBatchNorm.convert_sync_batchnorm(model) + model.cuda() + model = torch.nn.parallel.DistributedDataParallel(model, device_ids=[args.local_rank], find_unused_parameters=True) + single_model = model.module + + if args.model != 'lavt_one': + model_class = BertModel + bert_model = model_class.from_pretrained(args.ck_bert) + bert_model.pooler = None # a work-around for a bug in Transformers = 3.0.2 that appears for DistributedDataParallel + bert_model.cuda() + bert_model = torch.nn.SyncBatchNorm.convert_sync_batchnorm(bert_model) + bert_model = torch.nn.parallel.DistributedDataParallel(bert_model, device_ids=[args.local_rank]) + single_bert_model = bert_model.module + else: + bert_model = None + single_bert_model = None + + # resume training + if args.resume: + checkpoint = torch.load(args.resume, map_location='cpu') + single_model.load_state_dict(checkpoint['model']) + if args.model != 'lavt_one': + single_bert_model.load_state_dict(checkpoint['bert_model']) + + # parameters to optimize + backbone_no_decay = list() + backbone_decay = list() + for name, m in single_model.backbone.named_parameters(): + if 'norm' in name or 'absolute_pos_embed' in name or 'relative_position_bias_table' in name: + backbone_no_decay.append(m) + else: + backbone_decay.append(m) + + if args.model != 'lavt_one': + params_to_optimize = [ + {'params': backbone_no_decay, 'weight_decay': 0.0}, + {'params': backbone_decay}, + {"params": [p for p in single_model.classifier.parameters() if p.requires_grad]}, + # the following are the parameters of bert + {"params": reduce(operator.concat, + [[p for p in single_bert_model.encoder.layer[i].parameters() + if p.requires_grad] for i in range(10)])}, + ] + else: + params_to_optimize = [ + {'params': backbone_no_decay, 'weight_decay': 0.0}, + {'params': backbone_decay}, + {"params": [p for p in single_model.classifier.parameters() if p.requires_grad]}, + # the following are the parameters of bert + {"params": reduce(operator.concat, + [[p for p in single_model.text_encoder.encoder.layer[i].parameters() + if p.requires_grad] for i in range(10)])}, + ] + # params_to_optimize = [ + # {'params': backbone_no_decay, 'weight_decay': 0.0}, + # {'params': backbone_decay}, + # {"params": [p for p in single_model.classifier.parameters() if p.requires_grad]}, + # # the following are the parameters of bert + # {"params": reduce(operator.concat, + # [[p for p in single_model.text_encoder.encoder.layer[i].parameters() + # if p.requires_grad] for i in range(10)]), 'lr': args.lr/10}, + # ] + + + # optimizer + optimizer = torch.optim.AdamW(params_to_optimize, + lr=args.lr, + weight_decay=args.weight_decay, + amsgrad=args.amsgrad + ) + + # learning rate scheduler + lr_scheduler = torch.optim.lr_scheduler.LambdaLR(optimizer, + lambda x: (1 - x / (len(data_loader) * args.epochs)) ** 0.9) + + # housekeeping + start_time = time.time() + iterations = 0 + best_oIoU = -0.1 + + # resume training (optimizer, lr scheduler, and the epoch) + if args.resume: + optimizer.load_state_dict(checkpoint['optimizer']) + lr_scheduler.load_state_dict(checkpoint['lr_scheduler']) + resume_epoch = checkpoint['epoch'] + else: + resume_epoch = -999 + + # training loops + for epoch in range(max(0, resume_epoch+1), args.epochs): + data_loader.sampler.set_epoch(epoch) + itrs_temp, loss_log = train_one_epoch(model, criterion, optimizer, data_loader, lr_scheduler, epoch, args.print_freq, + iterations, bert_model, metric_learning=args.metric_learning, args=args) + iou, overallIoU, precs = evaluate(model, data_loader_test, bert_model) + + print('Average object IoU {}'.format(iou)) + print('Overall IoU {}'.format(overallIoU)) + save_checkpoint = (best_oIoU < overallIoU) + if save_checkpoint: + print('Better epoch: {}\n'.format(epoch)) + if single_bert_model is not None: + dict_to_save = {'model': single_model.state_dict(), 'bert_model': single_bert_model.state_dict(), + 'optimizer': optimizer.state_dict(), 'epoch': epoch, 'args': args, + 'lr_scheduler': lr_scheduler.state_dict()} + else: + dict_to_save = {'model': single_model.state_dict(), + 'optimizer': optimizer.state_dict(), 'epoch': epoch, 'args': args, + 'lr_scheduler': lr_scheduler.state_dict()} + + utils.save_on_master(dict_to_save, os.path.join(args.output_dir, + 'model_best_{}.pth'.format(args.model_id))) + best_oIoU = overallIoU + + + if utils.is_main_process(): + writer.add_scalar('val/mIoU', iou, epoch) + writer.add_scalar('val/oIoU', overallIoU, epoch) + writer.add_scalar('val/Prec/50', precs[0], epoch) + writer.add_scalar('val/Prec/60', precs[1], epoch) + writer.add_scalar('val/Prec/70', precs[2], epoch) + writer.add_scalar('val/Prec/80', precs[3], epoch) + writer.add_scalar('val/Prec/90', precs[4], epoch) + writer.add_scalar('train/loss', loss_log['loss'], epoch) + + writer.flush() + + # summarize + total_time = time.time() - start_time + total_time_str = str(datetime.timedelta(seconds=int(total_time))) + print('Training time {}'.format(total_time_str)) + + +if __name__ == "__main__": + from args import get_parser + parser = get_parser() + args = parser.parse_args() + # set up distributed learning + + if "LOCAL_RANK" in os.environ: + local_rank = int(os.environ["LOCAL_RANK"]) + else: + local_rank = 0 # Default value for non-distributed mode + + print(f"Local Rank: {local_rank}, World Size: {os.environ.get('WORLD_SIZE', '1')}") + + utils.init_distributed_mode(args) + print('Image size: {}'.format(str(args.img_size))) + print('Metric Learning Ops') + print('metric learning flag : ', args.metric_learning) + print('metric loss weight : ', args.metric_loss_weight) + print('metric mode and hardpos selection : ', args.metric_mode, args.hp_selection) + print('margin value : ', args.margin_value) + print('temperature : ', args.temperature) + print('add zero in ACE loss : ', args.addzero) + + print(args) + main(args) diff --git a/LAVT-RIS/train_refzom_anglehalf.py b/LAVT-RIS/train_refzom_anglehalf.py new file mode 100644 index 0000000000000000000000000000000000000000..8d20d9cd5783be7fbab0ad2d01488d3bd7c0e36b --- /dev/null +++ b/LAVT-RIS/train_refzom_anglehalf.py @@ -0,0 +1,593 @@ +import datetime +import os +import time + +import torch +import torch.utils.data +from torch import nn + +from functools import reduce +import operator +from bert.modeling_bert import BertModel + +import torchvision +from lib import segmentation + +import transforms as T +import utils +import numpy as np + +import torch.nn.functional as F +from data.dataset_refer_zom import Referzom_Dataset, Refzom_DistributedSampler +from data.dataset_refer_bert_rev import ReferDataset +import gc +from collections import OrderedDict +from torch.utils.tensorboard import SummaryWriter + + +def get_dataset(image_set, transform, args, eval_mode=False): + if args.dataset == 'ref-zom': + ds = Referzom_Dataset(args, + split=image_set, + image_transforms=transform, + target_transforms=None, + eval_mode=eval_mode) + else : + ds = ReferDataset(args, + split=image_set, + image_transforms=transform, + target_transforms=None, + eval_mode=image_set == 'val' + ) + num_classes = 2 + + return ds, num_classes + + +# IoU calculation for validation +# def IoU(pred, gt): +# pred = pred.argmax(1) + +# intersection = torch.sum(torch.mul(pred, gt)) +# union = torch.sum(torch.add(pred, gt)) - intersection + +# if intersection == 0 or union == 0: +# iou = 0 +# else: +# iou = float(intersection) / float(union) + +# return iou, intersection, union + +def IoU(pred, gt): + pred = pred.argmax(1) + + intersection = torch.sum(torch.mul(pred, gt)) + union = torch.sum(torch.add(pred, gt)) - intersection + + if intersection == 0 or union == 0: + iou = 0 + else: + iou = float(intersection) / float(union) + + return iou, intersection, union + + +def get_transform(args): + transforms = [T.Resize(args.img_size, args.img_size), + T.ToTensor(), + T.Normalize(mean=[0.485, 0.456, 0.406], std=[0.229, 0.224, 0.225]) + ] + + return T.Compose(transforms) + + +def criterion(input, target): + weight = torch.FloatTensor([0.9, 1.1]).cuda() + return nn.functional.cross_entropy(input, target, weight=weight) + + + + +def return_mask(emb_distance, verb_mask=None): + B_, B_ = emb_distance.shape + positive_mask = torch.zeros_like(emb_distance) + positive_mask.fill_diagonal_(1) # Set diagonal elements to 1 for all cases + + if B_ < len(verb_mask): + # If B_ equals to 2*K (double the number of verb phrase) + for i in range(B_ // 2): + positive_mask[2 * i, 2 * i + 1] = 1 + positive_mask[2 * i + 1, 2 * i] = 1 + else: + # Process the case where we have a mix of sentences with and without verbs + i = 0 + while i < B_: + if verb_mask[i] == 1: + positive_mask[i, i + 1] = 1 + positive_mask[i + 1, i] = 1 + i += 2 + else: + i += 1 + negative_mask = torch.ones_like(emb_distance) - positive_mask + return positive_mask, negative_mask + + +def UniAngularContrastLoss(total_fq, verb_mask, alpha=0.5, verbonly=True, m=0.5, tau=0.05, args=None): + _, C, H, W = total_fq.shape + + if verbonly : + B = total_fq[verb_mask].shape[0] + emb = torch.mean(total_fq[verb_mask], dim=(-1, -2)).reshape(B, C) + assert emb.shape[0] % 2 == 0, f"Embedding count {emb.shape[0]} is not divisible by 2." + else : + emb = torch.mean(total_fq, dim=-1) + + B_ = emb.shape[0] + emb_i = emb.unsqueeze(1).repeat(1, B_, 1) # (B_, B_, C) + emb_j = emb.unsqueeze(0).repeat(B_, 1, 1) # (B_, B_, C) + sim = nn.CosineSimilarity(dim=-1, eps=1e-6) + sim_matrix = sim(emb_i, emb_j).reshape(B_, B_) # (B_, B_) + sim_matrix = torch.clamp(sim_matrix, min=-0.9999, max=0.9999) + + positive_mask, negative_mask = return_mask(sim_matrix, verb_mask) + if len(positive_mask) > 0 : + sim_matrix_with_margin = sim_matrix.clone() + sim_matrix_with_margin[positive_mask.bool()] = torch.cos(torch.acos(sim_matrix[positive_mask.bool()]) + m / 57.2958) + + logits = sim_matrix_with_margin / tau + exp_logits = torch.exp(logits) + pos_exp_logits = exp_logits * positive_mask.long() + pos_exp_logits = pos_exp_logits.sum(dim=-1) + + # print("pos_exp_logits: ", pos_exp_logits.shape) + total_exp_logits = exp_logits.sum(dim=-1) + positive_loss = -torch.log(pos_exp_logits / total_exp_logits) + angular_loss = positive_loss.mean() + + return angular_loss + else : + return torch.tensor(0.0, device=total_fq.device) + + + +def UniAngularLogitContrastLoss(total_fq, verb_mask, alpha=0.5, verbonly=True, m=0.5, tau=0.05, args=None): + epsilon = 1e-10 # Stability term for numerical issues + _, C, H, W = total_fq.shape + + # Calculate embeddings + if verbonly : + B = total_fq[verb_mask].shape[0] + emb = torch.mean(total_fq[verb_mask], dim=(-1, -2)).reshape(B, C) + assert emb.shape[0] % 2 == 0, f"Embedding count {emb.shape[0]} is not divisible by 2." + else : + emb = torch.mean(total_fq, dim=-1) + + B_ = emb.shape[0] + emb_i = emb.unsqueeze(1).repeat(1, B_, 1) # (B_, B_, C) + emb_j = emb.unsqueeze(0).repeat(B_, 1, 1) # (B_, B_, C) + + sim = nn.CosineSimilarity(dim=-1, eps=1e-6) + sim_matrix = sim(emb_i, emb_j).reshape(B_, B_) # (B_, B_) + sim_matrix = torch.clamp(sim_matrix, min=-0.9999, max=0.9999) + + margin_in_radians = m / 57.2958 # Convert degrees to radians + theta_matrix = (torch.pi / 2) - torch.acos(sim_matrix) + positive_mask, negative_mask = return_mask(sim_matrix, verb_mask) + + theta_with_margin = theta_matrix.clone() + theta_with_margin[positive_mask.bool()] -= margin_in_radians # Subtract margin directly for positives + + logits = theta_with_margin / tau # Scale with temperature + + # Compute exponential logits for softmax + exp_logits = torch.exp(logits) + # pos_exp_logits = (exp_logits * positive_mask).sum(dim=-1) # Positive term + pos_exp_logits = exp_logits * positive_mask + pos_exp_logits = pos_exp_logits.sum(dim=-1) + + # neg_exp_logits = (exp_logits * negative_mask).sum(dim=-1) # Negative term + # total_exp_logits = pos_exp_logits + neg_exp_logits + total_exp_logits = exp_logits.sum(dim=-1) + + # pos_exp_logits = pos_exp_logits + epsilon + # total_exp_logits = total_exp_logits + epsilon + + # Compute angular loss + loss = -torch.log(pos_exp_logits / total_exp_logits) + angular_loss = loss.mean() + + return angular_loss + + + +def evaluate(model, data_loader, bert_model): + #print("current model : ", model) + model.eval() + metric_logger = utils.MetricLogger(delimiter=" ") + header = 'Test:' + total_its = 0 + acc_ious = 0 + + # evaluation variables + cum_I, cum_U = 0, 0 + eval_seg_iou_list = [.5, .6, .7, .8, .9] + seg_correct = np.zeros(len(eval_seg_iou_list), dtype=np.int32) + seg_total = 0 + mean_IoU = [] + mean_acc = [] + + with torch.no_grad(): + for data in metric_logger.log_every(data_loader, 100, header): + total_its += 1 + # Unpack data + image, target, source_type, sentences, attentions = data + image, target, sentences, attentions = ( + image.cuda(non_blocking=True), + target.cuda(non_blocking=True), + sentences.cuda(non_blocking=True), + attentions.cuda(non_blocking=True) + ) + + # Squeeze unnecessary dimensions + sentences = sentences.squeeze(-1) + attentions = attentions.squeeze(-1) + + # Model inference + if bert_model is not None: + last_hidden_states = bert_model(sentences, attention_mask=attentions)[0] + embedding = last_hidden_states.permute(0, 2, 1) # [B, N, 768] -> [B, 768, N] + attentions = attentions.unsqueeze(-1) # [B, N] -> [B, N, 1] + output = model(image, embedding, l_mask=attentions) + else: + output = model(image, sentences, l_mask=attentions, is_train=False) + + + # Zero target case + if source_type[0] == 'zero': + pred = output.argmax(1) + incorrect_num = torch.sum(pred).item() # Count non-zero predictions + acc = 1 if incorrect_num == 0 else 0 + mean_acc.append(acc) + else: + # Non-zero target case + this_iou, I, U = IoU(output, target) # Use the provided IoU function + mean_IoU.append(this_iou) + cum_I += I + cum_U += U + + for n_eval_iou in range(len(eval_seg_iou_list)): + eval_seg_iou = eval_seg_iou_list[n_eval_iou] + seg_correct[n_eval_iou] += (this_iou >= eval_seg_iou) + + seg_total += 1 + + mIoU = np.mean(mean_IoU) + mean_acc = np.mean(mean_acc) + print('Final results:') + print('Mean IoU is %.2f\n' % (mIoU * 100.)) + + results_str = '' + precs = [] + for n_eval_iou in range(len(eval_seg_iou_list)): + results_str += ' precision@%s = %.2f\n' % \ + (str(eval_seg_iou_list[n_eval_iou]), seg_correct[n_eval_iou] * 100. / seg_total) + precs.append(seg_correct[n_eval_iou] * 100. / seg_total) + results_str += ' overall IoU = %.2f\n' % (cum_I * 100. / cum_U) + results_str += ' mean IoU = %.2f\n' % (mIoU * 100.) + print(results_str) + if args.dataset == 'ref-zom': + print('Mean accuracy for one-to-zero sample is %.2f\n' % (mean_acc*100)) + + return mIoU, 100 * cum_I / cum_U, precs + + +def train_one_epoch(model, criterion, optimizer, data_loader, lr_scheduler, epoch, print_freq, + iterations, bert_model, metric_learning=False, args=None): + model.train() + metric_logger = utils.MetricLogger(delimiter=" ") + metric_logger.add_meter('lr', utils.SmoothedValue(window_size=1, fmt='{value}')) + header = 'Epoch: [{}]'.format(epoch) + train_loss = 0 + total_its = 0 + mlw = args.metric_loss_weight + metric_mode = args.metric_mode + if not metric_learning: + mlw = 0 + + for data in metric_logger.log_every(data_loader, print_freq, header): + #print("data : ", data) + total_its += 1 + + # Ref-Zom Repro + image, target, source_type, sentences, attentions, pos_sent, pos_attn_mask, pos_type = data + source_type = np.array(source_type) + target_flag = torch.tensor(np.where(source_type == 'zero', 0, 1)) + if args.addzero : + hardpos_flag = torch.tensor(np.where(pos_type == 'hardpos', 1, 0)) + else : + # default option for training : only include one, many targets! + hardpos_flag = torch.tensor(np.where((source_type != 'zero') & (pos_type == 'hardpos'), 1, 0)) + + + sentences = sentences.squeeze(1) + attentions = attentions.squeeze(1) + pos_sent = pos_sent.squeeze(1) + pos_attn_mask = pos_attn_mask.squeeze(1) + + + ## ver 1 : hardpos flag outside the model + verb_masks = [] + cl_masks = [] + images = [] + targets = [] + sentences_ = [] + attentions_ = [] + + for idx in range(len(image)) : + # Append original data + sentences_.append(sentences[idx]) + images.append(image[idx]) + targets.append(target[idx]) + attentions_.append(attentions[idx]) + + if hardpos_flag[idx] : + verb_masks.extend([1, 1]) + cl_masks.extend([1, 0]) + sentences_.append(pos_sent[idx]) + images.append(image[idx]) + targets.append(target[idx]) + attentions_.append(pos_attn_mask[idx]) + else: + verb_masks.append(0) + cl_masks.append(1) + + image, target, sentences, attentions, verb_masks, cl_masks = \ + torch.stack(images).cuda(non_blocking=True),\ + torch.stack(targets).cuda(non_blocking=True),\ + torch.stack(sentences_).cuda(non_blocking=True),\ + torch.stack(attentions_).cuda(non_blocking=True),\ + torch.tensor(verb_masks, dtype=torch.bool, device='cuda'),\ + torch.tensor(cl_masks, dtype=torch.bool, device='cuda') + + + loss = 0 + metric_loss = 0 + + if bert_model is not None: + last_hidden_states = bert_model(sentences, attention_mask=attentions)[0] # (6, 10, 768) + embedding = last_hidden_states.permute(0, 2, 1) # (B, 768, N_l) to make Conv1d happy + attentions = attentions.unsqueeze(dim=-1) # (batch, N_l, 1) + output = model(image, embedding, l_mask=attentions) + + else: + output, metric_tensors = model(image, sentences, l_mask=attentions) + + ce_loss = criterion(output[cl_masks], target[cl_masks]) + + + if metric_learning: + hardpos_count = sum(hardpos_flag) + divn = 1 + if hardpos_count >= 3: + metric_loss = UniAngularLogitContrastLoss(metric_tensors, verb_masks, m=args.margin_value, tau=args.temperature, verbonly=True, args=args) + divn+=mlw # (1+mlw) + else: + metric_loss = 0 + else: + metric_loss = 0 + divn = 1 + + # if metric_learning and sum(hardpos_flag) > 0 : + # metric_loss = UniAngularLogitContrastLoss(metric_tensors, verb_masks, m=args.margin_value, tau=args.temperature, verbonly=True, args=args) + + loss = (ce_loss + metric_loss * mlw) / divn + optimizer.zero_grad() # set_to_none=True is only available in pytorch 1.6+ + loss.backward() + optimizer.step() + lr_scheduler.step() + + torch.cuda.synchronize() + train_loss += loss.item() + iterations += 1 + metric_logger.update(loss=loss.item(), lr=optimizer.param_groups[0]["lr"]) + + del image, target, sentences, attentions, loss, output, data + if bert_model is not None: + del last_hidden_states, embedding + + gc.collect() + torch.cuda.empty_cache() + torch.cuda.synchronize() + + loss_log = { + 'loss': metric_logger.meters['loss'].global_avg + } + return iterations, loss_log + + + +def main(args): + writer = SummaryWriter('./experiments/{}/{}'.format("_".join([args.dataset, args.splitBy]), args.model_id)) + + dataset, num_classes = get_dataset("train", + get_transform(args=args), + args=args, + eval_mode=False) + dataset_test, _ = get_dataset(args.split, + get_transform(args=args), + args=args, + eval_mode=True) + + # batch sampler + print(f"local rank {args.local_rank} / global rank {utils.get_rank()} successfully built train dataset.") + num_tasks = utils.get_world_size() + global_rank = utils.get_rank() + + if args.dataset == 'ref-zom': + train_sampler = Refzom_DistributedSampler(dataset, num_replicas=num_tasks, rank=global_rank, + shuffle=True) + else: + train_sampler = torch.utils.data.distributed.DistributedSampler(dataset, num_replicas=num_tasks, rank=global_rank, + shuffle=True) + test_sampler = torch.utils.data.SequentialSampler(dataset_test) + + # data loader + data_loader = torch.utils.data.DataLoader( + dataset, batch_size=args.batch_size, + sampler=train_sampler, num_workers=args.workers, pin_memory=args.pin_mem, drop_last=True) + + data_loader_test = torch.utils.data.DataLoader( + dataset_test, batch_size=1, sampler=test_sampler, num_workers=args.workers) + + # model initialization + print(args.model) + model = segmentation.__dict__[args.model](pretrained=args.pretrained_swin_weights, + args=args) + model = torch.nn.SyncBatchNorm.convert_sync_batchnorm(model) + model.cuda() + model = torch.nn.parallel.DistributedDataParallel(model, device_ids=[args.local_rank], find_unused_parameters=True) + single_model = model.module + + if args.model != 'lavt_one': + model_class = BertModel + bert_model = model_class.from_pretrained(args.ck_bert) + bert_model.pooler = None # a work-around for a bug in Transformers = 3.0.2 that appears for DistributedDataParallel + bert_model.cuda() + bert_model = torch.nn.SyncBatchNorm.convert_sync_batchnorm(bert_model) + bert_model = torch.nn.parallel.DistributedDataParallel(bert_model, device_ids=[args.local_rank]) + single_bert_model = bert_model.module + else: + bert_model = None + single_bert_model = None + + # resume training + if args.resume: + checkpoint = torch.load(args.resume, map_location='cpu') + single_model.load_state_dict(checkpoint['model']) + if args.model != 'lavt_one': + single_bert_model.load_state_dict(checkpoint['bert_model']) + + # parameters to optimize + backbone_no_decay = list() + backbone_decay = list() + for name, m in single_model.backbone.named_parameters(): + if 'norm' in name or 'absolute_pos_embed' in name or 'relative_position_bias_table' in name: + backbone_no_decay.append(m) + else: + backbone_decay.append(m) + + if args.model != 'lavt_one': + params_to_optimize = [ + {'params': backbone_no_decay, 'weight_decay': 0.0}, + {'params': backbone_decay}, + {"params": [p for p in single_model.classifier.parameters() if p.requires_grad]}, + # the following are the parameters of bert + {"params": reduce(operator.concat, + [[p for p in single_bert_model.encoder.layer[i].parameters() + if p.requires_grad] for i in range(10)])}, + ] + else: + params_to_optimize = [ + {'params': backbone_no_decay, 'weight_decay': 0.0}, + {'params': backbone_decay}, + {"params": [p for p in single_model.classifier.parameters() if p.requires_grad]}, + # the following are the parameters of bert + {"params": reduce(operator.concat, + [[p for p in single_model.text_encoder.encoder.layer[i].parameters() + if p.requires_grad] for i in range(10)]), 'lr': args.lr/10}, + ] + + + # optimizer + optimizer = torch.optim.AdamW(params_to_optimize, + lr=args.lr, + weight_decay=args.weight_decay, + amsgrad=args.amsgrad + ) + + # learning rate scheduler + lr_scheduler = torch.optim.lr_scheduler.LambdaLR(optimizer, + lambda x: (1 - x / (len(data_loader) * args.epochs)) ** 0.9) + + # housekeeping + start_time = time.time() + iterations = 0 + best_oIoU = -0.1 + + # resume training (optimizer, lr scheduler, and the epoch) + if args.resume: + optimizer.load_state_dict(checkpoint['optimizer']) + lr_scheduler.load_state_dict(checkpoint['lr_scheduler']) + resume_epoch = checkpoint['epoch'] + else: + resume_epoch = -999 + + # training loops + for epoch in range(max(0, resume_epoch+1), args.epochs): + data_loader.sampler.set_epoch(epoch) + itrs_temp, loss_log = train_one_epoch(model, criterion, optimizer, data_loader, lr_scheduler, epoch, args.print_freq, + iterations, bert_model, metric_learning=args.metric_learning, args=args) + iou, overallIoU, precs = evaluate(model, data_loader_test, bert_model) + + print('Average object IoU {}'.format(iou)) + print('Overall IoU {}'.format(overallIoU)) + save_checkpoint = (best_oIoU < overallIoU) + if save_checkpoint: + print('Better epoch: {}\n'.format(epoch)) + if single_bert_model is not None: + dict_to_save = {'model': single_model.state_dict(), 'bert_model': single_bert_model.state_dict(), + 'optimizer': optimizer.state_dict(), 'epoch': epoch, 'args': args, + 'lr_scheduler': lr_scheduler.state_dict()} + else: + dict_to_save = {'model': single_model.state_dict(), + 'optimizer': optimizer.state_dict(), 'epoch': epoch, 'args': args, + 'lr_scheduler': lr_scheduler.state_dict()} + + utils.save_on_master(dict_to_save, os.path.join(args.output_dir, + 'model_best_{}.pth'.format(args.model_id))) + best_oIoU = overallIoU + + + if utils.is_main_process(): + writer.add_scalar('val/mIoU', iou, epoch) + writer.add_scalar('val/oIoU', overallIoU, epoch) + writer.add_scalar('val/Prec/50', precs[0], epoch) + writer.add_scalar('val/Prec/60', precs[1], epoch) + writer.add_scalar('val/Prec/70', precs[2], epoch) + writer.add_scalar('val/Prec/80', precs[3], epoch) + writer.add_scalar('val/Prec/90', precs[4], epoch) + writer.add_scalar('train/loss', loss_log['loss'], epoch) + + writer.flush() + + # summarize + total_time = time.time() - start_time + total_time_str = str(datetime.timedelta(seconds=int(total_time))) + print('Training time {}'.format(total_time_str)) + + +if __name__ == "__main__": + from args import get_parser + parser = get_parser() + args = parser.parse_args() + # set up distributed learning + + if "LOCAL_RANK" in os.environ: + local_rank = int(os.environ["LOCAL_RANK"]) + else: + local_rank = 0 # Default value for non-distributed mode + + print(f"Local Rank: {local_rank}, World Size: {os.environ.get('WORLD_SIZE', '1')}") + + utils.init_distributed_mode(args) + print('Image size: {}'.format(str(args.img_size))) + print('Metric Learning Ops') + print('metric learning flag : ', args.metric_learning) + print('metric loss weight : ', args.metric_loss_weight) + print('metric mode and hardpos selection : ', args.metric_mode, args.hp_selection) + print('margin value : ', args.margin_value) + print('temperature : ', args.temperature) + print('add zero in ACE loss : ', args.addzero) + + print(args) + main(args) diff --git a/LAVT-RIS/train_refzom_sanity.py b/LAVT-RIS/train_refzom_sanity.py new file mode 100644 index 0000000000000000000000000000000000000000..f358d14f21ccabe041ab29c1e883d767bb1eb528 --- /dev/null +++ b/LAVT-RIS/train_refzom_sanity.py @@ -0,0 +1,428 @@ +import datetime +import os +import time + +import torch +import torch.utils.data +from torch import nn + +from functools import reduce +import operator +from bert.modeling_bert import BertModel + +import torchvision +from lib import segmentation + +import transforms as T +import utils +import numpy as np + +import torch.nn.functional as F +from data.dataset_refer_zom import Referzom_Dataset, Refzom_DistributedSampler +from data.dataset_refer_bert_rev import ReferDataset +import gc +from collections import OrderedDict +from torch.utils.tensorboard import SummaryWriter + + +def get_dataset(image_set, transform, args, eval_mode=False): + if args.dataset == 'ref-zom': + ds = Referzom_Dataset(args, + split=image_set, + image_transforms=transform, + target_transforms=None, + eval_mode=eval_mode) + else : + ds = ReferDataset(args, + split=image_set, + image_transforms=transform, + target_transforms=None, + eval_mode=image_set == 'val' + ) + num_classes = 2 + + return ds, num_classes + + +# IoU calculation for validation +# def IoU(pred, gt): +# pred = pred.argmax(1) + +# intersection = torch.sum(torch.mul(pred, gt)) +# union = torch.sum(torch.add(pred, gt)) - intersection + +# if intersection == 0 or union == 0: +# iou = 0 +# else: +# iou = float(intersection) / float(union) + +# return iou, intersection, union + +# def computeIoU(pred_seg, gd_seg): +# I = np.sum(np.logical_and(pred_seg, gd_seg)) +# U = np.sum(np.logical_or(pred_seg, gd_seg)) + +# return I, U + +def IoU(pred, gt): + pred = pred.argmax(1) + + intersection = torch.sum(torch.mul(pred, gt)) + union = torch.sum(torch.add(pred, gt)) - intersection + + if intersection == 0 or union == 0: + iou = 0 + else: + iou = float(intersection) / float(union) + + return iou, intersection, union + + +def get_transform(args): + transforms = [T.Resize(args.img_size, args.img_size), + T.ToTensor(), + T.Normalize(mean=[0.485, 0.456, 0.406], std=[0.229, 0.224, 0.225]) + ] + + return T.Compose(transforms) + + +def criterion(input, target): + weight = torch.FloatTensor([0.9, 1.1]).cuda() + return nn.functional.cross_entropy(input, target, weight=weight) + + +def evaluate(model, data_loader, bert_model): + #print("current model : ", model) + model.eval() + metric_logger = utils.MetricLogger(delimiter=" ") + header = 'Test:' + total_its = 0 + acc_ious = 0 + + # evaluation variables + cum_I, cum_U = 0, 0 + eval_seg_iou_list = [.5, .6, .7, .8, .9] + seg_correct = np.zeros(len(eval_seg_iou_list), dtype=np.int32) + seg_total = 0 + mean_IoU = [] + mean_acc = [] + + with torch.no_grad(): + for data in metric_logger.log_every(data_loader, 100, header): + total_its += 1 + # Unpack data + image, target, source_type, sentences, attentions = data + image, target, sentences, attentions = ( + image.cuda(non_blocking=True), + target.cuda(non_blocking=True), + sentences.cuda(non_blocking=True), + attentions.cuda(non_blocking=True) + ) + + if total_its == 0 : + print(sentences.shape, attentions.shape, target.shape, image.shape) + + # Squeeze unnecessary dimensions + sentences = sentences.squeeze(1) + attentions = attentions.squeeze(1) + + if total_its == 0 : + print('after squeezing dim 1') + print(sentences.shape, attentions.shape) + + for j in range(sentences.size(-1)): + # Model inference + if bert_model is not None: + last_hidden_states = bert_model(sentences, attention_mask=attentions)[0] + embedding = last_hidden_states.permute(0, 2, 1) # [B, N, 768] -> [B, 768, N] + attentions = attentions.unsqueeze(-1) # [B, N] -> [B, N, 1] + output = model(image, embedding, l_mask=attentions) + else: + output = model(image, sentences, l_mask=attentions, is_train=False) + + # Zero target case + if source_type[0] == 'zero': + pred = output.argmax(1) + incorrect_num = torch.sum(pred).item() # Count non-zero predictions + acc = 1 if incorrect_num == 0 else 0 + mean_acc.append(acc) + else: + # Non-zero target case + iou, I, U = IoU(output, target) # Use the provided IoU function + mean_IoU.append(iou) + cum_I += I + cum_U += U + + for n_eval_iou in range(len(eval_seg_iou_list)): + eval_seg_iou = eval_seg_iou_list[n_eval_iou] + seg_correct[n_eval_iou] += (iou >= eval_seg_iou) + + seg_total += 1 + + mIoU = np.mean(mean_IoU) + mean_acc = np.mean(mean_acc) + print('Final results:') + print('Mean IoU is %.2f\n' % (mIoU * 100.)) + + results_str = '' + precs = [] + for n_eval_iou in range(len(eval_seg_iou_list)): + results_str += ' precision@%s = %.2f\n' % \ + (str(eval_seg_iou_list[n_eval_iou]), seg_correct[n_eval_iou] * 100. / seg_total) + precs.append(seg_correct[n_eval_iou] * 100. / seg_total) + results_str += ' overall IoU = %.2f\n' % (cum_I * 100. / cum_U) + results_str += ' mean IoU = %.2f\n' % (mIoU * 100.) + print(results_str) + if args.dataset == 'ref-zom': + print('Mean accuracy for one-to-zero sample is %.2f\n' % (mean_acc*100)) + + return mIoU, 100 * cum_I / cum_U, precs + + +def train_one_epoch(model, criterion, optimizer, data_loader, lr_scheduler, epoch, print_freq, + iterations, bert_model, metric_learning=False, args=None): + model.train() + metric_logger = utils.MetricLogger(delimiter=" ") + metric_logger.add_meter('lr', utils.SmoothedValue(window_size=1, fmt='{value}')) + header = 'Epoch: [{}]'.format(epoch) + train_loss = 0 + total_its = 0 + mlw = args.metric_loss_weight + metric_mode = args.metric_mode + if not metric_learning: + mlw = 0 + + for data in metric_logger.log_every(data_loader, print_freq, header): + #print("data : ", data) + total_its += 1 + + # Ref-Zom Repro + image, target, source_type, sentences, attentions = data + source_type = np.array(source_type) + target_flag = np.where(source_type=='zero', 0, 1) + target_flag = torch.tensor(target_flag) + + image, target, sentences, target_flag, attentions = image.cuda(non_blocking=True),\ + target.cuda(non_blocking=True),\ + sentences.cuda(non_blocking=True),\ + target_flag.cuda(non_blocking=True),\ + attentions.cuda(non_blocking=True) + + sentences = sentences.squeeze(1) + attentions = attentions.squeeze(1) + + if bert_model is not None: + last_hidden_states = bert_model(sentences, attention_mask=attentions)[0] # (6, 10, 768) + embedding = last_hidden_states.permute(0, 2, 1) # (B, 768, N_l) to make Conv1d happy + attentions = attentions.unsqueeze(dim=-1) # (batch, N_l, 1) + output = model(image, embedding, l_mask=attentions) + + else: + output, _ = model(image, sentences, l_mask=attentions) + + + loss = criterion(output, target) + optimizer.zero_grad() # set_to_none=True is only available in pytorch 1.6+ + loss.backward() + optimizer.step() + lr_scheduler.step() + + torch.cuda.synchronize() + train_loss += loss.item() + iterations += 1 + metric_logger.update(loss=loss.item(), lr=optimizer.param_groups[0]["lr"]) + + del image, target, sentences, attentions, loss, output, data + if bert_model is not None: + del last_hidden_states, embedding + + gc.collect() + torch.cuda.empty_cache() + torch.cuda.synchronize() + + loss_log = { + 'loss': metric_logger.meters['loss'].global_avg + } + return iterations, loss_log + + + +def main(args): + writer = SummaryWriter('./experiments/{}/{}'.format("_".join([args.dataset, args.splitBy]), args.model_id)) + + dataset, num_classes = get_dataset("train", + get_transform(args=args), + args=args, + eval_mode=False) + dataset_test, _ = get_dataset(args.split, + get_transform(args=args), + args=args, + eval_mode=True) + + # batch sampler + print(f"local rank {args.local_rank} / global rank {utils.get_rank()} successfully built train dataset.") + num_tasks = utils.get_world_size() + global_rank = utils.get_rank() + + if args.dataset == 'ref-zom': + train_sampler = Refzom_DistributedSampler(dataset, num_replicas=num_tasks, rank=global_rank, + shuffle=True) + else: + train_sampler = torch.utils.data.distributed.DistributedSampler(dataset, num_replicas=num_tasks, rank=global_rank, + shuffle=True) + test_sampler = torch.utils.data.SequentialSampler(dataset_test) + + # data loader + data_loader = torch.utils.data.DataLoader( + dataset, batch_size=args.batch_size, + sampler=train_sampler, num_workers=args.workers, pin_memory=args.pin_mem, drop_last=True) + + data_loader_test = torch.utils.data.DataLoader( + dataset_test, batch_size=1, sampler=test_sampler, num_workers=args.workers) + + # model initialization + print(args.model) + model = segmentation.__dict__[args.model](pretrained=args.pretrained_swin_weights, + args=args) + model = torch.nn.SyncBatchNorm.convert_sync_batchnorm(model) + model.cuda() + model = torch.nn.parallel.DistributedDataParallel(model, device_ids=[args.local_rank], find_unused_parameters=True) + single_model = model.module + + if args.model != 'lavt_one': + model_class = BertModel + bert_model = model_class.from_pretrained(args.ck_bert) + bert_model.pooler = None # a work-around for a bug in Transformers = 3.0.2 that appears for DistributedDataParallel + bert_model.cuda() + bert_model = torch.nn.SyncBatchNorm.convert_sync_batchnorm(bert_model) + bert_model = torch.nn.parallel.DistributedDataParallel(bert_model, device_ids=[args.local_rank]) + single_bert_model = bert_model.module + else: + bert_model = None + single_bert_model = None + + # resume training + if args.resume: + checkpoint = torch.load(args.resume, map_location='cpu') + single_model.load_state_dict(checkpoint['model']) + if args.model != 'lavt_one': + single_bert_model.load_state_dict(checkpoint['bert_model']) + + # parameters to optimize + backbone_no_decay = list() + backbone_decay = list() + for name, m in single_model.backbone.named_parameters(): + if 'norm' in name or 'absolute_pos_embed' in name or 'relative_position_bias_table' in name: + backbone_no_decay.append(m) + else: + backbone_decay.append(m) + + if args.model != 'lavt_one': + params_to_optimize = [ + {'params': backbone_no_decay, 'weight_decay': 0.0}, + {'params': backbone_decay}, + {"params": [p for p in single_model.classifier.parameters() if p.requires_grad]}, + # the following are the parameters of bert + {"params": reduce(operator.concat, + [[p for p in single_bert_model.encoder.layer[i].parameters() + if p.requires_grad] for i in range(10)])}, + ] + else: + params_to_optimize = [ + {'params': backbone_no_decay, 'weight_decay': 0.0}, + {'params': backbone_decay}, + {"params": [p for p in single_model.classifier.parameters() if p.requires_grad]}, + # the following are the parameters of bert + {"params": reduce(operator.concat, + [[p for p in single_model.text_encoder.encoder.layer[i].parameters() + if p.requires_grad] for i in range(10)])}, + ] + + # optimizer + optimizer = torch.optim.AdamW(params_to_optimize, + lr=args.lr, + weight_decay=args.weight_decay, + amsgrad=args.amsgrad + ) + + # learning rate scheduler + lr_scheduler = torch.optim.lr_scheduler.LambdaLR(optimizer, + lambda x: (1 - x / (len(data_loader) * args.epochs)) ** 0.9) + + # housekeeping + start_time = time.time() + iterations = 0 + best_oIoU = -0.1 + + # resume training (optimizer, lr scheduler, and the epoch) + if args.resume: + optimizer.load_state_dict(checkpoint['optimizer']) + lr_scheduler.load_state_dict(checkpoint['lr_scheduler']) + resume_epoch = checkpoint['epoch'] + else: + resume_epoch = -999 + + # training loops + for epoch in range(max(0, resume_epoch+1), args.epochs): + data_loader.sampler.set_epoch(epoch) + itrs_temp, loss_log = train_one_epoch(model, criterion, optimizer, data_loader, lr_scheduler, epoch, args.print_freq, + iterations, bert_model, metric_learning=args.metric_learning, args=args) + iou, overallIoU, precs = evaluate(model, data_loader_test, bert_model) + + print('Average object IoU {}'.format(iou)) + print('Overall IoU {}'.format(overallIoU)) + save_checkpoint = (best_oIoU < overallIoU) + if save_checkpoint: + print('Better epoch: {}\n'.format(epoch)) + if single_bert_model is not None: + dict_to_save = {'model': single_model.state_dict(), 'bert_model': single_bert_model.state_dict(), + 'optimizer': optimizer.state_dict(), 'epoch': epoch, 'args': args, + 'lr_scheduler': lr_scheduler.state_dict()} + else: + dict_to_save = {'model': single_model.state_dict(), + 'optimizer': optimizer.state_dict(), 'epoch': epoch, 'args': args, + 'lr_scheduler': lr_scheduler.state_dict()} + + utils.save_on_master(dict_to_save, os.path.join(args.output_dir, + 'model_best_{}.pth'.format(args.model_id))) + best_oIoU = overallIoU + + + if utils.is_main_process(): + writer.add_scalar('val/mIoU', iou, epoch) + writer.add_scalar('val/oIoU', overallIoU, epoch) + writer.add_scalar('val/Prec/50', precs[0], epoch) + writer.add_scalar('val/Prec/60', precs[1], epoch) + writer.add_scalar('val/Prec/70', precs[2], epoch) + writer.add_scalar('val/Prec/80', precs[3], epoch) + writer.add_scalar('val/Prec/90', precs[4], epoch) + writer.add_scalar('train/loss', loss_log['loss'], epoch) + + writer.flush() + + # summarize + total_time = time.time() - start_time + total_time_str = str(datetime.timedelta(seconds=int(total_time))) + print('Training time {}'.format(total_time_str)) + + +if __name__ == "__main__": + from args import get_parser + parser = get_parser() + args = parser.parse_args() + # set up distributed learning + + if "LOCAL_RANK" in os.environ: + local_rank = int(os.environ["LOCAL_RANK"]) + else: + local_rank = 0 # Default value for non-distributed mode + + print(f"Local Rank: {local_rank}, World Size: {os.environ.get('WORLD_SIZE', '1')}") + + utils.init_distributed_mode(args) + print('Image size: {}'.format(str(args.img_size))) + print('metric learning flag : ', args.metric_learning) + + print(args) + main(args) diff --git a/LAVT-RIS/transforms.py b/LAVT-RIS/transforms.py new file mode 100644 index 0000000000000000000000000000000000000000..0d22889dbab930ebe2a41dd01b8067465343079f --- /dev/null +++ b/LAVT-RIS/transforms.py @@ -0,0 +1,124 @@ +import numpy as np +from PIL import Image +import random + +import torch +from torchvision import transforms as T +from torchvision.transforms import functional as F + + +def pad_if_smaller(img, size, fill=0): + min_size = min(img.size) + if min_size < size: + ow, oh = img.size + padh = size - oh if oh < size else 0 + padw = size - ow if ow < size else 0 + img = F.pad(img, (0, 0, padw, padh), fill=fill) + return img + + +class Compose(object): + def __init__(self, transforms): + self.transforms = transforms + + def __call__(self, image, target): + for t in self.transforms: + image, target = t(image, target) + return image, target + + +class Resize(object): + def __init__(self, h, w): + self.h = h + self.w = w + + def __call__(self, image, target): + image = F.resize(image, (self.h, self.w)) + # If size is a sequence like (h, w), the output size will be matched to this. + # If size is an int, the smaller edge of the image will be matched to this number maintaining the aspect ratio + target = F.resize(target, (self.h, self.w), interpolation=Image.NEAREST) + return image, target + + +class RandomResize(object): + def __init__(self, min_size, max_size=None): + self.min_size = min_size + if max_size is None: + max_size = min_size + self.max_size = max_size + + def __call__(self, image, target): + size = random.randint(self.min_size, self.max_size) # Return a random integer N such that a <= N <= b. Alias for randrange(a, b+1) + image = F.resize(image, size) + # If size is a sequence like (h, w), the output size will be matched to this. + # If size is an int, the smaller edge of the image will be matched to this number maintaining the aspect ratio + target = F.resize(target, size, interpolation=Image.NEAREST) + return image, target + + +class RandomHorizontalFlip(object): + def __init__(self, flip_prob): + self.flip_prob = flip_prob + + def __call__(self, image, target): + if random.random() < self.flip_prob: + image = F.hflip(image) + target = F.hflip(target) + return image, target + + +class RandomCrop(object): + def __init__(self, size): + self.size = size + + def __call__(self, image, target): + image = pad_if_smaller(image, self.size) + target = pad_if_smaller(target, self.size, fill=255) + crop_params = T.RandomCrop.get_params(image, (self.size, self.size)) + image = F.crop(image, *crop_params) + target = F.crop(target, *crop_params) + return image, target + + +class CenterCrop(object): + def __init__(self, size): + self.size = size + + def __call__(self, image, target): + image = F.center_crop(image, self.size) + target = F.center_crop(target, self.size) + return image, target + + +class ToTensor(object): + def __call__(self, image, target): + image = F.to_tensor(image) + target = torch.as_tensor(np.asarray(target).copy(), dtype=torch.int64) + return image, target + + +class RandomAffine(object): + def __init__(self, angle, translate, scale, shear, resample=0, fillcolor=None): + self.angle = angle + self.translate = translate + self.scale = scale + self.shear = shear + self.resample = resample + self.fillcolor = fillcolor + + def __call__(self, image, target): + affine_params = T.RandomAffine.get_params(self.angle, self.translate, self.scale, self.shear, image.size) + image = F.affine(image, *affine_params) + target = F.affine(target, *affine_params) + return image, target + + +class Normalize(object): + def __init__(self, mean, std): + self.mean = mean + self.std = std + + def __call__(self, image, target): + image = F.normalize(image, mean=self.mean, std=self.std) + return image, target + diff --git a/LAVT-RIS/utils.py b/LAVT-RIS/utils.py new file mode 100644 index 0000000000000000000000000000000000000000..c9b6803da72d477dfb3e5f4b15d366497c2c592c --- /dev/null +++ b/LAVT-RIS/utils.py @@ -0,0 +1,224 @@ +from __future__ import print_function +from collections import defaultdict, deque +import datetime +import math +import time +import torch +import torch.distributed as dist +import torch.backends.cudnn as cudnn + +import errno +import os + +import sys + + +class SmoothedValue(object): + """Track a series of values and provide access to smoothed values over a + window or the global series average. + """ + + def __init__(self, window_size=20, fmt=None): + if fmt is None: + fmt = "{median:.4f} ({global_avg:.4f})" + self.deque = deque(maxlen=window_size) + self.total = 0.0 + self.count = 0 + self.fmt = fmt + + def update(self, value, n=1): + self.deque.append(value) + self.count += n + self.total += value * n + + def synchronize_between_processes(self): + """ + Warning: does not synchronize the deque! + """ + if not is_dist_avail_and_initialized(): + return + t = torch.tensor([self.count, self.total], dtype=torch.float64, device='cuda') + dist.barrier() + dist.all_reduce(t) + t = t.tolist() + self.count = int(t[0]) + self.total = t[1] + + @property + def median(self): + d = torch.tensor(list(self.deque)) + return d.median().item() + + @property + def avg(self): + d = torch.tensor(list(self.deque), dtype=torch.float32) + return d.mean().item() + + @property + def global_avg(self): + return self.total / self.count + + @property + def max(self): + return max(self.deque) + + @property + def value(self): + return self.deque[-1] + + def __str__(self): + return self.fmt.format( + median=self.median, + avg=self.avg, + global_avg=self.global_avg, + max=self.max, + value=self.value) + + +class MetricLogger(object): + def __init__(self, delimiter="\t"): + self.meters = defaultdict(SmoothedValue) + self.delimiter = delimiter + + def update(self, **kwargs): + for k, v in kwargs.items(): + if isinstance(v, torch.Tensor): + v = v.item() + assert isinstance(v, (float, int)) + self.meters[k].update(v) + + def __getattr__(self, attr): + if attr in self.meters: + return self.meters[attr] + if attr in self.__dict__: + return self.__dict__[attr] + raise AttributeError("'{}' object has no attribute '{}'".format( + type(self).__name__, attr)) + + def __str__(self): + loss_str = [] + for name, meter in self.meters.items(): + loss_str.append( + "{}: {}".format(name, str(meter)) + ) + return self.delimiter.join(loss_str) + + def synchronize_between_processes(self): + for meter in self.meters.values(): + meter.synchronize_between_processes() + + def add_meter(self, name, meter): + self.meters[name] = meter + + def log_every(self, iterable, print_freq, header=None): + i = 0 + if not header: + header = '' + start_time = time.time() + end = time.time() + iter_time = SmoothedValue(fmt='{avg:.4f}') + data_time = SmoothedValue(fmt='{avg:.4f}') + space_fmt = ':' + str(len(str(len(iterable)))) + 'd' + log_msg = self.delimiter.join([ + header, + '[{0' + space_fmt + '}/{1}]', + 'eta: {eta}', + '{meters}', + 'time: {time}', + 'data: {data}', + 'max mem: {memory:.0f}' + ]) + MB = 1024.0 * 1024.0 + for obj in iterable: + data_time.update(time.time() - end) + yield obj + iter_time.update(time.time() - end) + if i % print_freq == 0: + eta_seconds = iter_time.global_avg * (len(iterable) - i) + eta_string = str(datetime.timedelta(seconds=int(eta_seconds))) + print(log_msg.format( + i, len(iterable), eta=eta_string, + meters=str(self), + time=str(iter_time), data=str(data_time), + memory=torch.cuda.max_memory_allocated() / MB)) + sys.stdout.flush() + + i += 1 + end = time.time() + total_time = time.time() - start_time + total_time_str = str(datetime.timedelta(seconds=int(total_time))) + print('{} Total time: {}'.format(header, total_time_str)) + + +def mkdir(path): + try: + os.makedirs(path) + except OSError as e: + if e.errno != errno.EEXIST: + raise + + +def setup_for_distributed(is_master): + """ + This function disables printing when not in master process + """ + import builtins as __builtin__ + builtin_print = __builtin__.print + + def print(*args, **kwargs): + force = kwargs.pop('force', False) + if is_master or force: + builtin_print(*args, **kwargs) + + __builtin__.print = print + + +def is_dist_avail_and_initialized(): + if not dist.is_available(): + return False + if not dist.is_initialized(): + return False + return True + + +def get_world_size(): + if not is_dist_avail_and_initialized(): + return 1 + return dist.get_world_size() + + +def get_rank(): + if not is_dist_avail_and_initialized(): + return 0 + return dist.get_rank() + + +def is_main_process(): + return get_rank() == 0 + + +def save_on_master(*args, **kwargs): + if is_main_process(): + torch.save(*args, **kwargs) + + +def init_distributed_mode(args): + if 'RANK' in os.environ and 'WORLD_SIZE' in os.environ: + rank = int(os.environ["RANK"]) + world_size = int(os.environ['WORLD_SIZE']) + args.local_rank = int(os.environ["LOCAL_RANK"]) + print(f"RANK and WORLD_SIZE in environment: {rank}/{world_size}") + else: + rank = -1 + world_size = -1 + args.local_rank = 0 # Default to single GPU mode + + torch.cuda.set_device(args.local_rank) + torch.distributed.init_process_group(backend='nccl', init_method='env://', world_size=world_size, rank=rank) + torch.distributed.barrier() + setup_for_distributed(is_main_process()) + + if args.output_dir: + mkdir(args.output_dir) + if args.model_id: + mkdir(os.path.join('./models/', args.model_id)) diff --git a/LAVT-RIS/ytvos_rev.py b/LAVT-RIS/ytvos_rev.py new file mode 100644 index 0000000000000000000000000000000000000000..28c2e72833409f08812d3374d5e13852bf80e326 --- /dev/null +++ b/LAVT-RIS/ytvos_rev.py @@ -0,0 +1,226 @@ +""" +Ref-YoutubeVOS data loader +""" +from pathlib import Path + +import torch +from torch.autograd.grad_mode import F +from torch.utils.data import Dataset +import datasets.transforms_video as T + +import os +from PIL import Image +import json +import numpy as np +import random + +from datasets.categories import ytvos_category_dict as category_dict + + +class YTVOSDataset(Dataset): + """ + A dataset class for the Refer-Youtube-VOS dataset which was first introduced in the paper: + "URVOS: Unified Referring Video Object Segmentation Network with a Large-Scale Benchmark" + (see https://link.springer.com/content/pdf/10.1007/978-3-030-58555-6_13.pdf). + The original release of the dataset contained both 'first-frame' and 'full-video' expressions. However, the first + dataset is not publicly available anymore as now only the harder 'full-video' subset is available to download + through the Youtube-VOS referring video object segmentation competition page at: + https://competitions.codalab.org/competitions/29139 + Furthermore, for the competition the subset's original validation set, which consists of 507 videos, was split into + two competition 'validation' & 'test' subsets, consisting of 202 and 305 videos respectively. Evaluation can + currently only be done on the competition 'validation' subset using the competition's server, as + annotations were publicly released only for the 'train' subset of the competition. + + """ + def __init__(self, img_folder: Path, ann_file: Path, transforms, return_masks: bool, + num_frames: int, max_skip: int): + self.img_folder = img_folder + self.ann_file = ann_file + self._transforms = transforms + self.return_masks = return_masks # not used + self.num_frames = num_frames + self.max_skip = max_skip + # create video meta data + self.prepare_metas() + + print('\n video num: ', len(self.videos), ' clip num: ', len(self.metas)) + print('\n') + + + def prepare_metas(self): + # read object information + with open(os.path.join(str(self.img_folder), 'meta.json'), 'r') as f: + subset_metas_by_video = json.load(f)['videos'] + + # read expression data + with open(str(self.ann_file), 'r') as f: + subset_expressions_by_video = json.load(f)['videos'] + self.videos = list(subset_expressions_by_video.keys()) + + self.metas = [] + for vid in self.videos: + vid_meta = subset_metas_by_video[vid] + vid_data = subset_expressions_by_video[vid] + vid_frames = sorted(vid_data['frames']) + vid_len = len(vid_frames) + + obj_id_to_category = {} + obj_ids = set() + for exp_id, exp_dict in vid_data['expressions'].items() : + obj_id = exp_dict['obj_id'] + category = exp_dict['category'] + obj_ids.add(obj_id) + obj_id_to_category[obj_id] = category + + obj_ids = list(obj_ids) + obj_ids.sort() + + start_idx, end_idx = 2, vid_len - 2 + bin_size = (end_idx - start_idx) // 4 + bins = [] + for i in range(4): + bin_start = start_idx + i * bin_size + bin_end = bin_start + bin_size if i < 3 else end_idx + bins.append((bin_start, bin_end)) + + + # Create meta data for each selected frame + vid_metas = [] + for bin_start, bin_end in bins: + frame_idx = random.randint(bin_start, bin_end - 1) # Randomly sample a frame in the bin + meta = { + 'video': vid, + 'frame_idx': frame_idx, + 'frames': vid_frames, + 'bins' : bins, + 'obj_ids' : obj_ids, + 'obj_id_to_category': obj_id_to_category # Map of obj_id to category + } + vid_metas.append(meta) + + self.metas.append(vid_metas) + + + @staticmethod + def bounding_box(img): + rows = np.any(img, axis=1) + cols = np.any(img, axis=0) + rmin, rmax = np.where(rows)[0][[0, -1]] + cmin, cmax = np.where(cols)[0][[0, -1]] + return rmin, rmax, cmin, cmax # y1, y2, x1, x2 + + def __len__(self): + return len(self.metas) + + + def __getitem__(self, idx): + instance_check = False + while not instance_check: + vid_metas = self.metas[idx] # List of metadata dictionaries, one per bin + video = vid_metas[0]['video'] + frames = vid_metas[0]['frames'] + bins = vid_metas[0]['bins'] + obj_ids = vid_metas[0]['obj_ids'] + obj_id_to_category = vid_metas[0]['obj_id_to_category'] + + sample_indx = [meta['frame_idx'] for meta in vid_metas] + annotations = {} + + for frame_indx in sample_indx: + frame_name = frames[frame_indx] + img_path = os.path.join(str(self.img_folder), 'JPEGImages', video, frame_name + '.jpg') + mask_path = os.path.join(str(self.img_folder), 'Annotations', video, frame_name + '.png') + + img = Image.open(img_path).convert('RGB') + mask = Image.open(mask_path).convert('P') + mask_np = np.array(mask) + + frame_annotations = {} + for obj_id in obj_ids: + obj_mask = (mask_np == obj_id).astype(np.float32) # Object-specific binary mask + if obj_mask.any(): + y1, y2, x1, x2 = self.bounding_box(obj_mask) + bbox = [x1, y1, x2, y2] # Bounding box in xyxy format + else: + bbox = [0, 0, 0, 0] # No valid object, default bbox + + frame_annotations[obj_id] = { + 'category_name': obj_id_to_category[obj_id], + 'bbox': bbox, + 'mask': obj_mask + } + + annotations[frame_indx] = frame_annotations + + # Prepare the output dictionary + video_metadata = { + 'bins': bins, + 'annotations': annotations, # Object annotations per frame + 'frames': sample_indx, # Sampled frame indices + 'video_path': os.path.join(str(self.img_folder), 'JPEGImages', video) + } + + # Check if there's at least one valid instance + valid_check = any( + any(frame_annotations[obj_id]['bbox'] != [0, 0, 0, 0] for obj_id in frame_annotations) + for frame_annotations in annotations.values() + ) + if valid_check: + instance_check = True + else: + idx = random.randint(0, self.__len__() - 1) + + return video_metadata + + +def make_coco_transforms(image_set, max_size=640): + normalize = T.Compose([ + T.ToTensor(), + T.Normalize([0.485, 0.456, 0.406], [0.229, 0.224, 0.225]) + ]) + + scales = [288, 320, 352, 392, 416, 448, 480, 512] + + if image_set == 'train': + return T.Compose([ + T.RandomHorizontalFlip(), + T.PhotometricDistort(), + T.RandomSelect( + T.Compose([ + T.RandomResize(scales, max_size=max_size), + T.Check(), + ]), + T.Compose([ + T.RandomResize([400, 500, 600]), + T.RandomSizeCrop(384, 600), + T.RandomResize(scales, max_size=max_size), + T.Check(), + ]) + ), + normalize, + ]) + + # we do not use the 'val' set since the annotations are inaccessible + if image_set == 'val': + return T.Compose([ + T.RandomResize([360], max_size=640), + normalize, + ]) + + raise ValueError(f'unknown {image_set}') + + +def build(image_set, args): + root = Path(args.ytvos_path) + assert root.exists(), f'provided YTVOS path {root} does not exist' + PATHS = { + "train": (root / "train", root / "meta_expressions" / "train" / "meta_expressions.json"), + "val": (root / "valid", root / "meta_expressions" / "valid" / "meta_expressions.json"), # not used actually + } + img_folder, ann_file = PATHS[image_set] + # dataset = YTVOSDataset(img_folder, ann_file, transforms=make_coco_transforms(image_set, max_size=args.max_size), return_masks=args.masks, + # num_frames=args.num_frames, max_skip=args.max_skip) + dataset = YTVOSDataset(img_folder, ann_file, transforms=None, return_masks=args.masks, + num_frames=args.num_frames, max_skip=args.max_skip) + return dataset +